(not at the head of any monitored branch or PR)
2022-07-26 15:58.06: New job: test owl-opt.0.0.1 with ounit2.2.2.0, using opam dev
                              from https://github.com/ocaml/opam-repository.git#refs/pull/21354/head (10b49fadb0efcff442ed8cae85f7cc119fe28629)
                              on debian-11-ocaml-4.14/amd64

To reproduce locally:

git clone --recursive "https://github.com/ocaml/opam-repository.git" && cd "opam-repository" && git fetch origin "refs/pull/21354/head" && git reset --hard 10b49fad
git fetch origin master
git merge 42e749bdca1e36a9f7bbef60b3507d34c6c57fa3
cat > ../Dockerfile <<'END-OF-DOCKERFILE'
FROM ocaml/opam:debian-11-ocaml-4.14@sha256:1461d919411f5999f6d7ffd573b9b5385cda91accf83d3866b26097e791220be
USER 1000:1000
WORKDIR /home/opam
RUN for pkg in $(opam pin list --short); do opam pin remove "$pkg"; done
RUN opam repository remove -a multicore || true
RUN sudo ln -f /usr/bin/opam-dev /usr/bin/opam
RUN opam init --reinit -ni
ENV OPAMDOWNLOADJOBS="1"
ENV OPAMERRLOGLEN="0"
ENV OPAMSOLVERTIMEOUT="500"
ENV OPAMPRECISETRACKING="1"
RUN rm -rf opam-repository/
COPY --chown=1000:1000 . opam-repository/
RUN opam repository set-url --strict default opam-repository/
RUN opam pin add -k version -yn ounit2.2.2.0 2.2.0
RUN opam update --depexts
RUN opam remove ounit2.2.2.0 && opam install --deps-only ounit2.2.2.0 && opam install -v ounit2.2.2.0; \
    res=$?; \
    test "$res" != 31 && exit "$res"; \
    export OPAMCLI=2.0; \
    build_dir=$(opam var prefix)/.opam-switch/build; \
    failed=$(ls "$build_dir"); \
    for pkg in $failed; do \
    if opam show -f x-ci-accept-failures: "$pkg" | grep -qF "\"debian-11\""; then \
    echo "A package failed and has been disabled for CI using the 'x-ci-accept-failures' field."; \
    fi; \
    done; \
    exit 1
RUN opam update --depexts
RUN opam remove owl-opt.0.0.1 && opam install --deps-only owl-opt.0.0.1 && opam install -v owl-opt.0.0.1; \
    res=$?; \
    test "$res" != 31 && exit "$res"; \
    export OPAMCLI=2.0; \
    build_dir=$(opam var prefix)/.opam-switch/build; \
    failed=$(ls "$build_dir"); \
    for pkg in $failed; do \
    if opam show -f x-ci-accept-failures: "$pkg" | grep -qF "\"debian-11\""; then \
    echo "A package failed and has been disabled for CI using the 'x-ci-accept-failures' field."; \
    fi; \
    done; \
    exit 1
RUN opam update --depexts
RUN opam remove owl-opt.0.0.1 && opam install --deps-only --with-test owl-opt.0.0.1 && opam install -v --with-test owl-opt.0.0.1; \
    res=$?; \
    test "$res" != 31 && exit "$res"; \
    export OPAMCLI=2.0; \
    build_dir=$(opam var prefix)/.opam-switch/build; \
    failed=$(ls "$build_dir"); \
    for pkg in $failed; do \
    if opam show -f x-ci-accept-failures: "$pkg" | grep -qF "\"debian-11\""; then \
    echo "A package failed and has been disabled for CI using the 'x-ci-accept-failures' field."; \
    fi; \
    done; \
    exit 1

END-OF-DOCKERFILE
docker build -f ../Dockerfile .

2022-07-26 15:58.06: Using cache hint "ocaml/opam:debian-11-ocaml-4.14@sha256:1461d919411f5999f6d7ffd573b9b5385cda91accf83d3866b26097e791220be-ounit2.2.2.0-owl-opt.0.0.1-10b49fadb0efcff442ed8cae85f7cc119fe28629"
2022-07-26 15:58.06: Using OBuilder spec:
((from ocaml/opam:debian-11-ocaml-4.14@sha256:1461d919411f5999f6d7ffd573b9b5385cda91accf83d3866b26097e791220be)
 (user (uid 1000) (gid 1000))
 (workdir /home/opam)
 (run (shell "for pkg in $(opam pin list --short); do opam pin remove \"$pkg\"; done"))
 (run (shell "opam repository remove -a multicore || true"))
 (run (shell "sudo ln -f /usr/bin/opam-dev /usr/bin/opam"))
 (run (shell "opam init --reinit --config .opamrc-sandbox -ni"))
 (env OPAMDOWNLOADJOBS 1)
 (env OPAMERRLOGLEN 0)
 (env OPAMSOLVERTIMEOUT 500)
 (env OPAMPRECISETRACKING 1)
 (run (shell "rm -rf opam-repository/"))
 (copy (src .) (dst opam-repository/))
 (run (shell "opam repository set-url --strict default opam-repository/"))
 (run (shell "opam pin add -k version -yn ounit2.2.2.0 2.2.0"))
 (run (network host)
      (shell "opam update --depexts"))
 (run (cache (opam-archives (target /home/opam/.opam/download-cache)))
      (network host)
      (shell  "opam remove ounit2.2.2.0 && opam install --deps-only ounit2.2.2.0 && opam install -v ounit2.2.2.0;\
             \n        res=$?;\
             \n        test \"$res\" != 31 && exit \"$res\";\
             \n        export OPAMCLI=2.0;\
             \n        build_dir=$(opam var prefix)/.opam-switch/build;\
             \n        failed=$(ls \"$build_dir\");\
             \n        for pkg in $failed; do\
             \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-11\\\"\"; then\
             \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
             \n          fi;\
             \n        done;\
             \n        exit 1"))
 (run (network host)
      (shell "opam update --depexts"))
 (run (cache (opam-archives (target /home/opam/.opam/download-cache)))
      (network host)
      (shell  "opam remove owl-opt.0.0.1 && opam install --deps-only owl-opt.0.0.1 && opam install -v owl-opt.0.0.1;\
             \n        res=$?;\
             \n        test \"$res\" != 31 && exit \"$res\";\
             \n        export OPAMCLI=2.0;\
             \n        build_dir=$(opam var prefix)/.opam-switch/build;\
             \n        failed=$(ls \"$build_dir\");\
             \n        for pkg in $failed; do\
             \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-11\\\"\"; then\
             \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
             \n          fi;\
             \n        done;\
             \n        exit 1"))
 (run (network host)
      (shell "opam update --depexts"))
 (run (cache (opam-archives (target /home/opam/.opam/download-cache)))
      (network host)
      (shell  "opam remove owl-opt.0.0.1 && opam install --deps-only --with-test owl-opt.0.0.1 && opam install -v --with-test owl-opt.0.0.1;\
             \n        res=$?;\
             \n        test \"$res\" != 31 && exit \"$res\";\
             \n        export OPAMCLI=2.0;\
             \n        build_dir=$(opam var prefix)/.opam-switch/build;\
             \n        failed=$(ls \"$build_dir\");\
             \n        for pkg in $failed; do\
             \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-11\\\"\"; then\
             \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
             \n          fi;\
             \n        done;\
             \n        exit 1"))
)

2022-07-26 15:58.06: Waiting for resource in pool OCluster
2022-07-27 04:51.23: Waiting for worker...
2022-07-27 04:53.06: Got resource from pool OCluster
Building on x86-bm-3.ocamllabs.io
All commits already cached
Updating files:  25% (6830/26809)
Updating files:  26% (6971/26809)
Updating files:  27% (7239/26809)
Updating files:  28% (7507/26809)
Updating files:  29% (7775/26809)
Updating files:  30% (8043/26809)
Updating files:  31% (8311/26809)
Updating files:  32% (8579/26809)
Updating files:  33% (8847/26809)
Updating files:  34% (9116/26809)
Updating files:  35% (9384/26809)
Updating files:  36% (9652/26809)
Updating files:  36% (9884/26809)
Updating files:  37% (9920/26809)
Updating files:  38% (10188/26809)
Updating files:  39% (10456/26809)
Updating files:  40% (10724/26809)
Updating files:  41% (10992/26809)
Updating files:  42% (11260/26809)
Updating files:  43% (11528/26809)
Updating files:  44% (11796/26809)
Updating files:  45% (12065/26809)
Updating files:  46% (12333/26809)
Updating files:  47% (12601/26809)
Updating files:  48% (12869/26809)
Updating files:  48% (12989/26809)
Updating files:  49% (13137/26809)
Updating files:  50% (13405/26809)
Updating files:  51% (13673/26809)
Updating files:  52% (13941/26809)
Updating files:  53% (14209/26809)
Updating files:  54% (14477/26809)
Updating files:  55% (14745/26809)
Updating files:  56% (15014/26809)
Updating files:  56% (15163/26809)
Updating files:  57% (15282/26809)
Updating files:  58% (15550/26809)
Updating files:  59% (15818/26809)
Updating files:  60% (16086/26809)
Updating files:  61% (16354/26809)
Updating files:  61% (16424/26809)
Updating files:  62% (16622/26809)
Updating files:  63% (16890/26809)
Updating files:  64% (17158/26809)
Updating files:  65% (17426/26809)
Updating files:  66% (17694/26809)
Updating files:  67% (17963/26809)
Updating files:  67% (17979/26809)
Updating files:  68% (18231/26809)
Updating files:  69% (18499/26809)
Updating files:  70% (18767/26809)
Updating files:  71% (19035/26809)
Updating files:  72% (19303/26809)
Updating files:  73% (19571/26809)
Updating files:  74% (19839/26809)
Updating files:  75% (20107/26809)
Updating files:  76% (20375/26809)
Updating files:  77% (20643/26809)
Updating files:  78% (20912/26809)
Updating files:  79% (21180/26809)
Updating files:  79% (21445/26809)
Updating files:  80% (21448/26809)
Updating files:  81% (21716/26809)
Updating files:  82% (21984/26809)
Updating files:  82% (22034/26809)
Updating files:  83% (22252/26809)
Updating files:  84% (22520/26809)
Updating files:  85% (22788/26809)
Updating files:  86% (23056/26809)
Updating files:  87% (23324/26809)
Updating files:  88% (23592/26809)
Updating files:  89% (23861/26809)
Updating files:  90% (24129/26809)
Updating files:  91% (24397/26809)
Updating files:  91% (24519/26809)
Updating files:  92% (24665/26809)
Updating files:  93% (24933/26809)
Updating files:  94% (25201/26809)
Updating files:  95% (25469/26809)
Updating files:  96% (25737/26809)
Updating files:  97% (26005/26809)
Updating files:  98% (26273/26809)
Updating files:  99% (26541/26809)
Updating files: 100% (26809/26809)
Updating files: 100% (26809/26809), done.
HEAD is now at 42e749bdca Merge pull request #21885 from kit-ty-kate/fix-123
Merge made by the 'ort' strategy.
 packages/ounit2/ounit2.2.2.0/opam | 3 +++
 packages/ounit2/ounit2.2.2.1/opam | 3 +++
 packages/ounit2/ounit2.2.2.2/opam | 3 +++
 packages/ounit2/ounit2.2.2.3/opam | 3 +++
 packages/ounit2/ounit2.2.2.4/opam | 3 +++
 packages/ounit2/ounit2.2.2.5/opam | 3 +++
 packages/ounit2/ounit2.2.2.6/opam | 3 +++
 7 files changed, 21 insertions(+)

(from ocaml/opam:debian-11-ocaml-4.14@sha256:1461d919411f5999f6d7ffd573b9b5385cda91accf83d3866b26097e791220be)
2022-07-27 04:54.24 ---> using "d837bbe1b6e58c32e942b55a1eb695ef30d2cac63c8a5d708beb3548d17192b4" from cache

/: (user (uid 1000) (gid 1000))

/: (workdir /home/opam)

/home/opam: (run (shell "for pkg in $(opam pin list --short); do opam pin remove \"$pkg\"; done"))
Ok, ocaml-base-compiler is no longer pinned to https://github.com/ocaml/ocaml/archive/4.14.0.tar.gz (version 4.14.0)
No package build needed.
Nothing to do.
# Run eval $(opam env) to update the current shell environment
2022-07-27 04:54.24 ---> using "543d29c04ee698e03faf7cfdc4bb3cf9e04a80ab924d981f1055393f1479d117" from cache

/home/opam: (run (shell "opam repository remove -a multicore || true"))
[WARNING] No configured repositories by these names found: multicore
2022-07-27 04:54.24 ---> using "e8a5c58b05459f7be98d7b03e29623d3a05b15b34833b50ebffb60eff7871cde" from cache

/home/opam: (run (shell "sudo ln -f /usr/bin/opam-dev /usr/bin/opam"))
2022-07-27 04:54.24 ---> using "4687a20afa7557b4b2498b537430ed75c7b51cd6cad60d9c4757ff852befb1a7" from cache

/home/opam: (run (shell "opam init --reinit --config .opamrc-sandbox -ni"))
Configuring from /home/opam/.opamrc-sandbox, then /home/opam/.opamrc, and finally from built-in defaults.
Checking for available remotes: rsync and local, git.
  - you won't be able to use mercurial repositories unless you install the hg command on your system.
  - you won't be able to use darcs repositories unless you install the darcs command on your system.

This development version of opam requires an update to the layout of /home/opam/.opam from version 2.0 to version 2.1, which can't be reverted.
You may want to back it up before going further.

Continue? [y/n] y
Format upgrade done.

<><> Updating repositories ><><><><><><><><><><><><><><><><><><><><><><><><><><>
[default] synchronised from file:///home/opam/opam-repository
2022-07-27 04:54.24 ---> using "87c4051d859f505ce794fbdc2ed87105744babed536dd4b09731a9b1e22fd3d4" from cache

/home/opam: (env OPAMDOWNLOADJOBS 1)

/home/opam: (env OPAMERRLOGLEN 0)

/home/opam: (env OPAMSOLVERTIMEOUT 500)

/home/opam: (env OPAMPRECISETRACKING 1)

/home/opam: (run (shell "rm -rf opam-repository/"))
2022-07-27 04:54.24 ---> using "96a067e6b08152c0f77ff1628817c13e12ac3db1ba1ac882a90278edcbb3d011" from cache

/home/opam: (copy (src .) (dst opam-repository/))
2022-07-27 04:54.27 ---> using "5ce106567f73501cd746c3358ba50b49e5b3ad28d47e7894c1f65b44fcda87e7" from cache

/home/opam: (run (shell "opam repository set-url --strict default opam-repository/"))
[default] Initialised
2022-07-27 04:54.27 ---> using "0981e55d831537155c9e161d0ab37d0aeee18cf4c3d1dbad8143304b4c508a5d" from cache

/home/opam: (run (shell "opam pin add -k version -yn ounit2.2.2.0 2.2.0"))
ounit2 is now pinned to version 2.2.0
2022-07-27 04:54.27 ---> using "a5b811fe2c6ab2fd90efb98285ea9db0346a5de8dadc9481e3cd36fb68f11371" from cache

/home/opam: (run (network host)
                 (shell "opam update --depexts"))
+ /usr/bin/sudo "apt-get" "update"
- Hit:1 http://deb.debian.org/debian bullseye InRelease
- Get:2 http://deb.debian.org/debian-security bullseye-security InRelease [48.4 kB]
- Get:3 http://deb.debian.org/debian bullseye-updates InRelease [44.1 kB]
- Get:4 http://deb.debian.org/debian-security bullseye-security/main amd64 Packages [168 kB]
- Fetched 261 kB in 1s (197 kB/s)
- Reading package lists...
- 
2022-07-27 04:54.27 ---> using "db2d7bb6f3a492dbe20e0d4ddb4733d768da5e64ce8f97c3cbc89325acd13b48" from cache

/home/opam: (run (cache (opam-archives (target /home/opam/.opam/download-cache)))
                 (network host)
                 (shell  "opam remove ounit2.2.2.0 && opam install --deps-only ounit2.2.2.0 && opam install -v ounit2.2.2.0;\
                        \n        res=$?;\
                        \n        test \"$res\" != 31 && exit \"$res\";\
                        \n        export OPAMCLI=2.0;\
                        \n        build_dir=$(opam var prefix)/.opam-switch/build;\
                        \n        failed=$(ls \"$build_dir\");\
                        \n        for pkg in $failed; do\
                        \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-11\\\"\"; then\
                        \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
                        \n          fi;\
                        \n        done;\
                        \n        exit 1"))
[NOTE] ounit2.2.2.0 is not installed.

Nothing to do.
The following actions will be performed:
=== install 4 packages
  - install base-bytes   base  [required by ounit2]
  - install dune         3.4.1 [required by ounit2]
  - install ocamlfind    1.9.5 [required by base-bytes]
  - install stdlib-shims 0.3.0 [required by ounit2]

<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>
-> retrieved dune.3.4.1  (cached)
-> retrieved ocamlfind.1.9.5  (cached)
-> retrieved stdlib-shims.0.3.0  (cached)
-> installed ocamlfind.1.9.5
-> installed base-bytes.base
-> installed dune.3.4.1
-> installed stdlib-shims.0.3.0
Done.
# Run eval $(opam env) to update the current shell environment
The following actions will be performed:
=== install 1 package
  - install ounit2 2.2.0 (pinned)

<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>
Processing  1/3:
-> retrieved ounit2.2.2.0  (cached)
Processing  2/3: [ounit2: dune build]
+ /home/opam/.opam/opam-init/hooks/sandbox.sh "build" "dune" "build" "-p" "ounit2" "-j" "31" (CWD=/home/opam/.opam/4.14/.opam-switch/build/ounit2.2.2.0)
- (cd _build/default && /home/opam/.opam/4.14/bin/ocamlc.opt -w -40 -g -bin-annot -I src/lib/ounit2/advanced/.oUnitAdvanced.objs/byte -I /home/opam/.opam/4.14/lib/stdlib-shims -no-alias-deps -o src/lib/ounit2/advanced/.oUnitAdvanced.objs/byte/oUnitAssert.cmo -c -impl src/lib/ounit2/advanced/oUnitAssert.ml)
- File "src/lib/ounit2/advanced/oUnitAssert.ml", line 130, characters 13-27:
- 130 |     ?(sinput=Stream.of_list [])
-                    ^^^^^^^^^^^^^^
- Alert deprecated: module Stdlib.Stream
- Use the camlp-streams library instead.
- File "src/lib/ounit2/advanced/oUnitAssert.ml", line 270, characters 13-24:
- 270 |              Stream.iter
-                    ^^^^^^^^^^^
- Alert deprecated: module Stdlib.Stream
- Use the camlp-streams library instead.
- File "src/lib/ounit2/advanced/oUnitAssert.ml", line 315, characters 26-43:
- 315 |                  foutput (Stream.of_channel chn)
-                                 ^^^^^^^^^^^^^^^^^
- Alert deprecated: module Stdlib.Stream
- Use the camlp-streams library instead.
- (cd _build/default && /home/opam/.opam/4.14/bin/ocamlopt.opt -w -40 -g -I src/lib/ounit2/advanced/.oUnitAdvanced.objs/byte -I src/lib/ounit2/advanced/.oUnitAdvanced.objs/native -I /home/opam/.opam/4.14/lib/stdlib-shims -intf-suffix .ml -no-alias-deps -o src/lib/ounit2/advanced/.oUnitAdvanced.objs/native/oUnitAssert.cmx -c -impl src/lib/ounit2/advanced/oUnitAssert.ml)
- File "src/lib/ounit2/advanced/oUnitAssert.ml", line 130, characters 13-27:
- 130 |     ?(sinput=Stream.of_list [])
-                    ^^^^^^^^^^^^^^
- Alert deprecated: module Stdlib.Stream
- Use the camlp-streams library instead.
- File "src/lib/ounit2/advanced/oUnitAssert.ml", line 270, characters 13-24:
- 270 |              Stream.iter
-                    ^^^^^^^^^^^
- Alert deprecated: module Stdlib.Stream
- Use the camlp-streams library instead.
- File "src/lib/ounit2/advanced/oUnitAssert.ml", line 315, characters 26-43:
- 315 |                  foutput (Stream.of_channel chn)
-                                 ^^^^^^^^^^^^^^^^^
- Alert deprecated: module Stdlib.Stream
- Use the camlp-streams library instead.
- (cd _build/default && /home/opam/.opam/4.14/bin/ocamlc.opt -w -40 -g -bin-annot -I src/lib/ounit2/.oUnit.objs/byte -I /home/opam/.opam/4.14/lib/stdlib-shims -I src/lib/ounit2/advanced/.oUnitAdvanced.objs/byte -no-alias-deps -o src/lib/ounit2/.oUnit.objs/byte/oUnit2.cmi -c -intf src/lib/ounit2/oUnit2.mli)
- File "src/lib/ounit2/oUnit2.mli", line 88, characters 17-25:
- 88 |     ?sinput:char Stream.t ->
-                       ^^^^^^^^
- Alert deprecated: module Stdlib.Stream
- Use the camlp-streams library instead.
- File "src/lib/ounit2/oUnit2.mli", line 89, characters 19-27:
- 89 |     ?foutput:(char Stream.t -> unit) ->
-                         ^^^^^^^^
- Alert deprecated: module Stdlib.Stream
- Use the camlp-streams library instead.
- (cd _build/default && /home/opam/.opam/4.14/bin/ocamlc.opt -w -40 -g -bin-annot -I src/lib/ounit2/.oUnit.objs/byte -I /home/opam/.opam/4.14/lib/stdlib-shims -I src/lib/ounit2/advanced/.oUnitAdvanced.objs/byte -no-alias-deps -o src/lib/ounit2/.oUnit.objs/byte/oUnit.cmi -c -intf src/lib/ounit2/oUnit.mli)
- File "src/lib/ounit2/oUnit.mli", line 80, characters 17-25:
- 80 |     ?sinput:char Stream.t ->
-                       ^^^^^^^^
- Alert deprecated: module Stdlib.Stream
- Use the camlp-streams library instead.
- File "src/lib/ounit2/oUnit.mli", line 81, characters 19-27:
- 81 |     ?foutput:(char Stream.t -> unit) ->
-                         ^^^^^^^^
- Alert deprecated: module Stdlib.Stream
- Use the camlp-streams library instead.
- (cd _build/default && /home/opam/.opam/4.14/bin/ocamlc.opt -w -40 -g -bin-annot -I src/lib/ounit2/threads/.oUnitThreads.objs/byte -I src/lib/ounit2/threads/.oUnitThreads.objs/public_cmi -I /home/opam/.opam/4.14/lib/ocaml/threads -I /home/opam/.opam/4.14/lib/stdlib-shims -I src/lib/ounit2/.oUnit.objs/byte -I src/lib/ounit2/advanced/.oUnitAdvanced.objs/byte -no-alias-deps -open OUnitThreads__ -o src/lib/ounit2/threads/.oUnitThreads.objs/byte/oUnitThreads__OUnitRunnerThreads.cmo -c -impl src/lib/ounit2/threads/oUnitRunnerThreads.ml)
- File "src/lib/ounit2/threads/oUnitRunnerThreads.ml", line 147, characters 8-19:
- 147 |         Thread.kill thread;
-               ^^^^^^^^^^^
- Alert deprecated: Thread.kill
- Not implemented, do not use
- (cd _build/default && /home/opam/.opam/4.14/bin/ocamlopt.opt -w -40 -g -I src/lib/ounit2/threads/.oUnitThreads.objs/byte -I src/lib/ounit2/threads/.oUnitThreads.objs/native -I src/lib/ounit2/threads/.oUnitThreads.objs/public_cmi -I /home/opam/.opam/4.14/lib/ocaml/threads -I /home/opam/.opam/4.14/lib/stdlib-shims -I src/lib/ounit2/.oUnit.objs/byte -I src/lib/ounit2/.oUnit.objs/native -I src/lib/ounit2/advanced/.oUnitAdvanced.objs/byte -I src/lib/ounit2/advanced/.oUnitAdvanced.objs/native -intf-suffix .ml -no-alias-deps -open OUnitThreads__ -o src/lib/ounit2/threads/.oUnitThreads.objs/native/oUnitThreads__OUnitRunnerThreads.cmx -c -impl src/lib/ounit2/threads/oUnitRunnerThreads.ml)
- File "src/lib/ounit2/threads/oUnitRunnerThreads.ml", line 147, characters 8-19:
- 147 |         Thread.kill thread;
-               ^^^^^^^^^^^
- Alert deprecated: Thread.kill
- Not implemented, do not use
-> compiled  ounit2.2.2.0
-> installed ounit2.2.2.0
Done.
# Run eval $(opam env) to update the current shell environment
2022-07-27 04:54.27 ---> using "549816a256be73d9a20d8aac9e10b779e4fdffd8e09de149b8d5e327ac84c14f" from cache

/home/opam: (run (network host)
                 (shell "opam update --depexts"))
+ /usr/bin/sudo "apt-get" "update"
- Hit:1 http://deb.debian.org/debian bullseye InRelease
- Hit:2 http://deb.debian.org/debian-security bullseye-security InRelease
- Hit:3 http://deb.debian.org/debian bullseye-updates InRelease
- Reading package lists...
- 
2022-07-27 04:54.27 ---> using "ed77e423a302c60a5809ee2b791a97889b346ae238a3ae55d40f898cb095304c" from cache

/home/opam: (run (cache (opam-archives (target /home/opam/.opam/download-cache)))
                 (network host)
                 (shell  "opam remove owl-opt.0.0.1 && opam install --deps-only owl-opt.0.0.1 && opam install -v owl-opt.0.0.1;\
                        \n        res=$?;\
                        \n        test \"$res\" != 31 && exit \"$res\";\
                        \n        export OPAMCLI=2.0;\
                        \n        build_dir=$(opam var prefix)/.opam-switch/build;\
                        \n        failed=$(ls \"$build_dir\");\
                        \n        for pkg in $failed; do\
                        \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-11\\\"\"; then\
                        \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
                        \n          fi;\
                        \n        done;\
                        \n        exit 1"))
Nothing to do.
[NOTE] owl-opt.0.0.1 is not installed.

The following actions will be performed:
=== install 20 packages
  - install base                v0.15.0 [required by owl, ppx-owl-opt]
  - install bigarray-compat     1.1.0   [required by ctypes]
  - install camlzip             1.11    [required by npy]
  - install conf-openblas       0.2.1   [required by owl]
  - install conf-pkg-config     2       [required by conf-zlib]
  - install conf-zlib           1       [required by camlzip]
  - install csexp               1.5.1   [required by dune-configurator]
  - install ctypes              0.20.1  [required by owl]
  - install dune-configurator   3.4.1   [required by owl]
  - install eigen               0.3.3   [required by owl]
  - install integers            0.7.0   [required by ctypes]
  - install npy                 0.0.9   [required by owl]
  - install ocaml-compiler-libs v0.12.4 [required by ppxlib]
  - install owl                 1.0.2-1 [required by owl-opt]
  - install owl-base            1.0.2   [required by owl]
  - install ppx-owl-opt         0.0.1   [required by owl-opt]
  - install ppx_derivers        1.2.1   [required by ppxlib]
  - install ppxlib              0.27.0  [required by ppx-owl-opt]
  - install sexplib0            v0.15.1 [required by base, ppxlib]
  - install stdio               v0.15.0 [required by owl]

The following system packages will first need to be installed:
    liblapacke-dev libopenblas-dev pkg-config zlib1g-dev

<><> Handling external dependencies <><><><><><><><><><><><><><><><><><><><><><>

opam believes some required external dependencies are missing. opam can:
> 1. Run apt-get to install them (may need root/sudo access)
  2. Display the recommended apt-get command and wait while you run it manually (e.g. in another terminal)
  3. Attempt installation anyway, and permanently register that this external dependency is present, but not detectable
  4. Abort the installation

[1/2/3/4] 1
+ /usr/bin/sudo "apt-get" "install" "-qq" "-yy" "liblapacke-dev" "libopenblas-dev" "pkg-config" "zlib1g-dev"
- debconf: delaying package configuration, since apt-utils is not installed
- Selecting previously unselected package libgfortran5:amd64.
- (Reading database ... 
(Reading database ... 5%
(Reading database ... 10%
(Reading database ... 15%
(Reading database ... 20%
(Reading database ... 25%
(Reading database ... 30%
(Reading database ... 35%
(Reading database ... 40%
(Reading database ... 45%
(Reading database ... 50%
(Reading database ... 55%
(Reading database ... 60%
(Reading database ... 65%
(Reading database ... 70%
(Reading database ... 75%
(Reading database ... 80%
(Reading database ... 85%
(Reading database ... 90%
(Reading database ... 95%
(Reading database ... 100%
(Reading database ... 18331 files and directories currently installed.)
- Preparing to unpack .../00-libgfortran5_10.2.1-6_amd64.deb ...
- Unpacking libgfortran5:amd64 (10.2.1-6) ...
- Selecting previously unselected package libglib2.0-0:amd64.
- Preparing to unpack .../01-libglib2.0-0_2.66.8-1_amd64.deb ...
- Unpacking libglib2.0-0:amd64 (2.66.8-1) ...
- Selecting previously unselected package libglib2.0-data.
- Preparing to unpack .../02-libglib2.0-data_2.66.8-1_all.deb ...
- Unpacking libglib2.0-data (2.66.8-1) ...
- Selecting previously unselected package libicu67:amd64.
- Preparing to unpack .../03-libicu67_67.1-7_amd64.deb ...
- Unpacking libicu67:amd64 (67.1-7) ...
- Selecting previously unselected package libopenblas0-pthread:amd64.
- Preparing to unpack .../04-libopenblas0-pthread_0.3.13+ds-3_amd64.deb ...
- Unpacking libopenblas0-pthread:amd64 (0.3.13+ds-3) ...
- Selecting previously unselected package libtmglib3:amd64.
- Preparing to unpack .../05-libtmglib3_3.9.0-3_amd64.deb ...
- Unpacking libtmglib3:amd64 (3.9.0-3) ...
- Selecting previously unselected package liblapacke:amd64.
- Preparing to unpack .../06-liblapacke_3.9.0-3_amd64.deb ...
- Unpacking liblapacke:amd64 (3.9.0-3) ...
- Selecting previously unselected package libopenblas-pthread-dev:amd64.
- Preparing to unpack .../07-libopenblas-pthread-dev_0.3.13+ds-3_amd64.deb ...
- Unpacking libopenblas-pthread-dev:amd64 (0.3.13+ds-3) ...
- Selecting previously unselected package libtmglib-dev:amd64.
- Preparing to unpack .../08-libtmglib-dev_3.9.0-3_amd64.deb ...
- Unpacking libtmglib-dev:amd64 (3.9.0-3) ...
- Selecting previously unselected package liblapacke-dev:amd64.
- Preparing to unpack .../09-liblapacke-dev_3.9.0-3_amd64.deb ...
- Unpacking liblapacke-dev:amd64 (3.9.0-3) ...
- Selecting previously unselected package libopenblas0:amd64.
- Preparing to unpack .../10-libopenblas0_0.3.13+ds-3_amd64.deb ...
- Unpacking libopenblas0:amd64 (0.3.13+ds-3) ...
- Selecting previously unselected package libopenblas-dev:amd64.
- Preparing to unpack .../11-libopenblas-dev_0.3.13+ds-3_amd64.deb ...
- Unpacking libopenblas-dev:amd64 (0.3.13+ds-3) ...
- Selecting previously unselected package libxml2:amd64.
- Preparing to unpack .../12-libxml2_2.9.10+dfsg-6.7+deb11u2_amd64.deb ...
- Unpacking libxml2:amd64 (2.9.10+dfsg-6.7+deb11u2) ...
- Selecting previously unselected package pkg-config.
- Preparing to unpack .../13-pkg-config_0.29.2-1_amd64.deb ...
- Unpacking pkg-config (0.29.2-1) ...
- Selecting previously unselected package shared-mime-info.
- Preparing to unpack .../14-shared-mime-info_2.0-1_amd64.deb ...
- Unpacking shared-mime-info (2.0-1) ...
- Selecting previously unselected package xdg-user-dirs.
- Preparing to unpack .../15-xdg-user-dirs_0.17-2_amd64.deb ...
- Unpacking xdg-user-dirs (0.17-2) ...
- Selecting previously unselected package zlib1g-dev:amd64.
- Preparing to unpack .../16-zlib1g-dev_1%3a1.2.11.dfsg-2+deb11u1_amd64.deb ...
- Unpacking zlib1g-dev:amd64 (1:1.2.11.dfsg-2+deb11u1) ...
- Setting up libicu67:amd64 (67.1-7) ...
- Setting up xdg-user-dirs (0.17-2) ...
- Setting up libglib2.0-0:amd64 (2.66.8-1) ...
- No schema files found: doing nothing.
- Setting up libglib2.0-data (2.66.8-1) ...
- Setting up pkg-config (0.29.2-1) ...
- Setting up libgfortran5:amd64 (10.2.1-6) ...
- Setting up zlib1g-dev:amd64 (1:1.2.11.dfsg-2+deb11u1) ...
- Setting up libxml2:amd64 (2.9.10+dfsg-6.7+deb11u2) ...
- Setting up libopenblas0-pthread:amd64 (0.3.13+ds-3) ...
- update-alternatives: using /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so.3 to provide /usr/lib/x86_64-linux-gnu/libblas.so.3 (libblas.so.3-x86_64-linux-gnu) in auto mode
- update-alternatives: using /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so.3 to provide /usr/lib/x86_64-linux-gnu/liblapack.so.3 (liblapack.so.3-x86_64-linux-gnu) in auto mode
- update-alternatives: using /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblas.so.0 to provide /usr/lib/x86_64-linux-gnu/libopenblas.so.0 (libopenblas.so.0-x86_64-linux-gnu) in auto mode
- Setting up libtmglib3:amd64 (3.9.0-3) ...
- Setting up shared-mime-info (2.0-1) ...
- Setting up libopenblas0:amd64 (0.3.13+ds-3) ...
- Setting up liblapacke:amd64 (3.9.0-3) ...
- Setting up libopenblas-pthread-dev:amd64 (0.3.13+ds-3) ...
- update-alternatives: using /usr/lib/x86_64-linux-gnu/openblas-pthread/libblas.so to provide /usr/lib/x86_64-linux-gnu/libblas.so (libblas.so-x86_64-linux-gnu) in auto mode
- update-alternatives: using /usr/lib/x86_64-linux-gnu/openblas-pthread/liblapack.so to provide /usr/lib/x86_64-linux-gnu/liblapack.so (liblapack.so-x86_64-linux-gnu) in auto mode
- update-alternatives: using /usr/lib/x86_64-linux-gnu/openblas-pthread/libopenblas.so to provide /usr/lib/x86_64-linux-gnu/libopenblas.so (libopenblas.so-x86_64-linux-gnu) in auto mode
- Setting up libopenblas-dev:amd64 (0.3.13+ds-3) ...
- Setting up libtmglib-dev:amd64 (3.9.0-3) ...
- Setting up liblapacke-dev:amd64 (3.9.0-3) ...
- Processing triggers for libc-bin (2.31-13+deb11u3) ...

<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>
-> retrieved base.v0.15.0  (cached)
-> retrieved bigarray-compat.1.1.0  (cached)
-> retrieved camlzip.1.11  (cached)
-> retrieved csexp.1.5.1  (cached)
-> retrieved ctypes.0.20.1  (cached)
-> installed conf-pkg-config.2
-> installed bigarray-compat.1.1.0
-> installed conf-openblas.0.2.1
-> installed csexp.1.5.1
-> installed conf-zlib.1
-> retrieved dune-configurator.3.4.1  (cached)
-> retrieved eigen.0.3.3  (cached)
-> installed camlzip.1.11
-> retrieved integers.0.7.0  (cached)
-> retrieved npy.0.0.9  (cached)
-> retrieved ocaml-compiler-libs.v0.12.4  (cached)
-> installed npy.0.0.9
-> installed integers.0.7.0
-> installed ocaml-compiler-libs.v0.12.4
-> installed dune-configurator.3.4.1
-> retrieved owl.1.0.2-1, owl-base.1.0.2  (cached)
-> retrieved ppx-owl-opt.0.0.1  (cached)
-> retrieved ppx_derivers.1.2.1  (cached)
-> retrieved ppxlib.0.27.0  (cached)
-> installed ppx_derivers.1.2.1
-> retrieved sexplib0.v0.15.1  (cached)
-> retrieved stdio.v0.15.0  (cached)
-> installed sexplib0.v0.15.1
-> installed owl-base.1.0.2
-> installed ctypes.0.20.1
-> installed base.v0.15.0
-> installed stdio.v0.15.0
-> installed ppxlib.0.27.0
-> installed ppx-owl-opt.0.0.1
-> installed eigen.0.3.3
-> installed owl.1.0.2-1
Done.
# Run eval $(opam env) to update the current shell environment
The following actions will be performed:
=== install 1 package
  - install owl-opt 0.0.1

<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>
Processing  1/3:
-> retrieved owl-opt.0.0.1  (cached)
Processing  2/3: [owl-opt: dune build]
+ /home/opam/.opam/opam-init/hooks/sandbox.sh "build" "dune" "build" "-p" "owl-opt" "-j" "31" (CWD=/home/opam/.opam/4.14/.opam-switch/build/owl-opt.0.0.1)
- File "dune-project", line 2, characters 11-14:
- 2 | (using fmt 1.1)
-                ^^^
- Warning: Version 1.1 of integration with automatic formatters is not
- supported until version 1.7 of the dune language.
- Supported versions of this extension in version 1.5 of the dune language:
- - 1.0
-> compiled  owl-opt.0.0.1
-> installed owl-opt.0.0.1
Done.
# Run eval $(opam env) to update the current shell environment
2022-07-27 05:00.42 ---> saved as "6c52e74ebc997d87ec095ff7a5450982727f6bdcc4f406a38a9333084b9a0aec"

/home/opam: (run (network host)
                 (shell "opam update --depexts"))
+ /usr/bin/sudo "apt-get" "update"
- Hit:1 http://deb.debian.org/debian bullseye InRelease
- Hit:2 http://deb.debian.org/debian-security bullseye-security InRelease
- Hit:3 http://deb.debian.org/debian bullseye-updates InRelease
- Reading package lists...
- 
2022-07-27 05:00.49 ---> saved as "69ca8d4d83842b8bfe6f3eec7c4c2320901d7b16cdc60252c89aad8ae0adaf0a"

/home/opam: (run (cache (opam-archives (target /home/opam/.opam/download-cache)))
                 (network host)
                 (shell  "opam remove owl-opt.0.0.1 && opam install --deps-only --with-test owl-opt.0.0.1 && opam install -v --with-test owl-opt.0.0.1;\
                        \n        res=$?;\
                        \n        test \"$res\" != 31 && exit \"$res\";\
                        \n        export OPAMCLI=2.0;\
                        \n        build_dir=$(opam var prefix)/.opam-switch/build;\
                        \n        failed=$(ls \"$build_dir\");\
                        \n        for pkg in $failed; do\
                        \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-11\\\"\"; then\
                        \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
                        \n          fi;\
                        \n        done;\
                        \n        exit 1"))
The following actions will be performed:
=== remove 1 package
  - remove owl-opt 0.0.1

<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>
-> removed   owl-opt.0.0.1
Done.
# Run eval $(opam env) to update the current shell environment
Nothing to do.
# Run eval $(opam env) to update the current shell environment
The following actions will be performed:
=== install 1 package
  - install owl-opt 0.0.1

<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>
Processing  1/3:
-> retrieved owl-opt.0.0.1  (cached)
Processing  2/3: [owl-opt: dune build]
+ /home/opam/.opam/opam-init/hooks/sandbox.sh "build" "dune" "build" "-p" "owl-opt" "-j" "31" (CWD=/home/opam/.opam/4.14/.opam-switch/build/owl-opt.0.0.1)
- File "dune-project", line 2, characters 11-14:
- 2 | (using fmt 1.1)
-                ^^^
- Warning: Version 1.1 of integration with automatic formatters is not
- supported until version 1.7 of the dune language.
- Supported versions of this extension in version 1.5 of the dune language:
- - 1.0
Processing  2/3: [owl-opt: dune runtest]
+ /home/opam/.opam/opam-init/hooks/sandbox.sh "build" "dune" "runtest" "examples/opt" "-p" "owl-opt" "-j" "31" (CWD=/home/opam/.opam/4.14/.opam-switch/build/owl-opt.0.0.1)
- File "dune-project", line 2, characters 11-14:
- 2 | (using fmt 1.1)
-                ^^^
- Warning: Version 1.1 of integration with automatic formatters is not
- supported until version 1.7 of the dune language.
- Supported versions of this extension in version 1.5 of the dune language:
- - 1.0
- (cd _build/default/examples/opt && ./single.exe)
- 
step: 0 | loss: 1.338356080
step: 10 | loss: 1.337060535
step: 20 | loss: 1.335621711
step: 30 | loss: 1.334183676
step: 40 | loss: 1.332746486
step: 50 | loss: 1.331310173
step: 60 | loss: 1.329874755
step: 70 | loss: 1.328440239
step: 80 | loss: 1.327006626
step: 90 | loss: 1.325573918
step: 100 | loss: 1.324142114
step: 110 | loss: 1.322711212
step: 120 | loss: 1.321281212
step: 130 | loss: 1.319852112
step: 140 | loss: 1.318423912
step: 150 | loss: 1.316996609
step: 160 | loss: 1.315570203
step: 170 | loss: 1.314144692
step: 180 | loss: 1.312720075
step: 190 | loss: 1.311296350
step: 200 | loss: 1.309873517
step: 210 | loss: 1.308451574
step: 220 | loss: 1.307030520
step: 230 | loss: 1.305610354
step: 240 | loss: 1.304191073
step: 250 | loss: 1.302772678
step: 260 | loss: 1.301355166
step: 270 | loss: 1.299938536
step: 280 | loss: 1.298522787
step: 290 | loss: 1.297107917
step: 300 | loss: 1.295693926
step: 310 | loss: 1.294280812
step: 320 | loss: 1.292868573
step: 330 | loss: 1.291457208
step: 340 | loss: 1.290046716
step: 350 | loss: 1.288637095
step: 360 | loss: 1.287228345
step: 370 | loss: 1.285820463
step: 380 | loss: 1.284413448
step: 390 | loss: 1.283007299
step: 400 | loss: 1.281602015
step: 410 | loss: 1.280197594
step: 420 | loss: 1.278794034
step: 430 | loss: 1.277391335
step: 440 | loss: 1.275989495
step: 450 | loss: 1.274588512
step: 460 | loss: 1.273188385
step: 470 | loss: 1.271789112
step: 480 | loss: 1.270390693
step: 490 | loss: 1.268993125
step: 500 | loss: 1.267596408
step: 510 | loss: 1.266200539
step: 520 | loss: 1.264805518
step: 530 | loss: 1.263411343
step: 540 | loss: 1.262018011
step: 550 | loss: 1.260625523
step: 560 | loss: 1.259233876
step: 570 | loss: 1.257843069
step: 580 | loss: 1.256453100
step: 590 | loss: 1.255063968
step: 600 | loss: 1.253675672
step: 610 | loss: 1.252288209
step: 620 | loss: 1.250901578
step: 630 | loss: 1.249515778
step: 640 | loss: 1.248130808
step: 650 | loss: 1.246746664
step: 660 | loss: 1.245363347
step: 670 | loss: 1.243980855
step: 680 | loss: 1.242599185
step: 690 | loss: 1.241218336
step: 700 | loss: 1.239838308
step: 710 | loss: 1.238459097
step: 720 | loss: 1.237080703
step: 730 | loss: 1.235703124
step: 740 | loss: 1.234326358
step: 750 | loss: 1.232950403
step: 760 | loss: 1.231575259
step: 770 | loss: 1.230200923
step: 780 | loss: 1.228827394
step: 790 | loss: 1.227454670
step: 800 | loss: 1.226082749
step: 810 | loss: 1.224711630
step: 820 | loss: 1.223341311
step: 830 | loss: 1.221971790
step: 840 | loss: 1.220603066
step: 850 | loss: 1.219235137
step: 860 | loss: 1.217868001
step: 870 | loss: 1.216501657
step: 880 | loss: 1.215136102
step: 890 | loss: 1.213771336
step: 900 | loss: 1.212407356
step: 910 | loss: 1.211044161
step: 920 | loss: 1.209681748
step: 930 | loss: 1.208320117
step: 940 | loss: 1.206959265
step: 950 | loss: 1.205599190
step: 960 | loss: 1.204239892
step: 970 | loss: 1.202881367
step: 980 | loss: 1.201523615
step: 990 | loss: 1.200166633
step: 1000 | loss: 1.198810419
step: 1010 | loss: 1.197454973
step: 1020 | loss: 1.196100291
step: 1030 | loss: 1.194746373
step: 1040 | loss: 1.193393216
step: 1050 | loss: 1.192040818
step: 1060 | loss: 1.190689178
step: 1070 | loss: 1.189338294
step: 1080 | loss: 1.187988164
step: 1090 | loss: 1.186638786
step: 1100 | loss: 1.185290159
step: 1110 | loss: 1.183942279
step: 1120 | loss: 1.182595147
step: 1130 | loss: 1.181248759
step: 1140 | loss: 1.179903113
step: 1150 | loss: 1.178558209
step: 1160 | loss: 1.177214043
step: 1170 | loss: 1.175870615
step: 1180 | loss: 1.174527922
step: 1190 | loss: 1.173185962
step: 1200 | loss: 1.171844734
step: 1210 | loss: 1.170504235
step: 1220 | loss: 1.169164464
step: 1230 | loss: 1.167825418
step: 1240 | loss: 1.166487096
step: 1250 | loss: 1.165149496
step: 1260 | loss: 1.163812616
step: 1270 | loss: 1.162476454
step: 1280 | loss: 1.161141008
step: 1290 | loss: 1.159806276
step: 1300 | loss: 1.158472256
step: 1310 | loss: 1.157138947
step: 1320 | loss: 1.155806345
step: 1330 | loss: 1.154474450
step: 1340 | loss: 1.153143260
step: 1350 | loss: 1.151812772
step: 1360 | loss: 1.150482985
step: 1370 | loss: 1.149153896
step: 1380 | loss: 1.147825504
step: 1390 | loss: 1.146497807
step: 1400 | loss: 1.145170803
step: 1410 | loss: 1.143844490
step: 1420 | loss: 1.142518865
step: 1430 | loss: 1.141193928
step: 1440 | loss: 1.139869676
step: 1450 | loss: 1.138546107
step: 1460 | loss: 1.137223219
step: 1470 | loss: 1.135901011
step: 1480 | loss: 1.134579480
step: 1490 | loss: 1.133258624
step: 1500 | loss: 1.131938443
step: 1510 | loss: 1.130618933
step: 1520 | loss: 1.129300093
step: 1530 | loss: 1.127981921
step: 1540 | loss: 1.126664415
step: 1550 | loss: 1.125347573
step: 1560 | loss: 1.124031393
step: 1570 | loss: 1.122715874
step: 1580 | loss: 1.121401013
step: 1590 | loss: 1.120086810
step: 1600 | loss: 1.118773261
step: 1610 | loss: 1.117460365
step: 1620 | loss: 1.116148120
step: 1630 | loss: 1.114836525
step: 1640 | loss: 1.113525577
step: 1650 | loss: 1.112215275
step: 1660 | loss: 1.110905617
step: 1670 | loss: 1.109596601
step: 1680 | loss: 1.108288226
step: 1690 | loss: 1.106980489
step: 1700 | loss: 1.105673390
step: 1710 | loss: 1.104366925
step: 1720 | loss: 1.103061094
step: 1730 | loss: 1.101755894
step: 1740 | loss: 1.100451325
step: 1750 | loss: 1.099147384
step: 1760 | loss: 1.097844069
step: 1770 | loss: 1.096541380
step: 1780 | loss: 1.095239313
step: 1790 | loss: 1.093937869
step: 1800 | loss: 1.092637044
step: 1810 | loss: 1.091336838
step: 1820 | loss: 1.090037249
step: 1830 | loss: 1.088738275
step: 1840 | loss: 1.087439914
step: 1850 | loss: 1.086142166
step: 1860 | loss: 1.084845029
step: 1870 | loss: 1.083548500
step: 1880 | loss: 1.082252579
step: 1890 | loss: 1.080957264
step: 1900 | loss: 1.079662554
step: 1910 | loss: 1.078368447
step: 1920 | loss: 1.077074942
step: 1930 | loss: 1.075782037
step: 1940 | loss: 1.074489731
step: 1950 | loss: 1.073198023
step: 1960 | loss: 1.071906911
step: 1970 | loss: 1.070616393
step: 1980 | loss: 1.069326469
step: 1990 | loss: 1.068037138
step: 2000 | loss: 1.066748397
step: 2010 | loss: 1.065460246
step: 2020 | loss: 1.064172683
step: 2030 | loss: 1.062885708
step: 2040 | loss: 1.061599318
step: 2050 | loss: 1.060313514
step: 2060 | loss: 1.059028293
step: 2070 | loss: 1.057743654
step: 2080 | loss: 1.056459597
step: 2090 | loss: 1.055176120
step: 2100 | loss: 1.053893222
step: 2110 | loss: 1.052610902
step: 2120 | loss: 1.051329159
step: 2130 | loss: 1.050047993
step: 2140 | loss: 1.048767401
step: 2150 | loss: 1.047487383
step: 2160 | loss: 1.046207938
step: 2170 | loss: 1.044929065
step: 2180 | loss: 1.043650764
step: 2190 | loss: 1.042373033
step: 2200 | loss: 1.041095870
step: 2210 | loss: 1.039819277
step: 2220 | loss: 1.038543251
step: 2230 | loss: 1.037267792
step: 2240 | loss: 1.035992899
step: 2250 | loss: 1.034718571
step: 2260 | loss: 1.033444807
step: 2270 | loss: 1.032171607
step: 2280 | loss: 1.030898970
step: 2290 | loss: 1.029626896
step: 2300 | loss: 1.028355382
step: 2310 | loss: 1.027084430
step: 2320 | loss: 1.025814038
step: 2330 | loss: 1.024544205
step: 2340 | loss: 1.023274931
step: 2350 | loss: 1.022006215
step: 2360 | loss: 1.020738058
step: 2370 | loss: 1.019470457
step: 2380 | loss: 1.018203413
step: 2390 | loss: 1.016936925
step: 2400 | loss: 1.015670992
step: 2410 | loss: 1.014405614
step: 2420 | loss: 1.013140791
step: 2430 | loss: 1.011876522
step: 2440 | loss: 1.010612807
step: 2450 | loss: 1.009349644
step: 2460 | loss: 1.008087035
step: 2470 | loss: 1.006824977
step: 2480 | loss: 1.005563472
step: 2490 | loss: 1.004302517
step: 2500 | loss: 1.003042114
step: 2510 | loss: 1.001782262
step: 2520 | loss: 1.000522960
step: 2530 | loss: 0.999264208
step: 2540 | loss: 0.998006006
step: 2550 | loss: 0.996748353
step: 2560 | loss: 0.995491250
step: 2570 | loss: 0.994234695
step: 2580 | loss: 0.992978688
step: 2590 | loss: 0.991723230
step: 2600 | loss: 0.990468319
step: 2610 | loss: 0.989213957
step: 2620 | loss: 0.987960142
step: 2630 | loss: 0.986706874
step: 2640 | loss: 0.985454153
step: 2650 | loss: 0.984201978
step: 2660 | loss: 0.982950351
step: 2670 | loss: 0.981699269
step: 2680 | loss: 0.980448734
step: 2690 | loss: 0.979198744
step: 2700 | loss: 0.977949301
step: 2710 | loss: 0.976700403
step: 2720 | loss: 0.975452050
step: 2730 | loss: 0.974204242
step: 2740 | loss: 0.972956980
step: 2750 | loss: 0.971710262
step: 2760 | loss: 0.970464089
step: 2770 | loss: 0.969218461
step: 2780 | loss: 0.967973377
step: 2790 | loss: 0.966728837
step: 2800 | loss: 0.965484841
step: 2810 | loss: 0.964241390
step: 2820 | loss: 0.962998482
step: 2830 | loss: 0.961756117
step: 2840 | loss: 0.960514296
step: 2850 | loss: 0.959273019
step: 2860 | loss: 0.958032285
step: 2870 | loss: 0.956792094
step: 2880 | loss: 0.955552446
step: 2890 | loss: 0.954313340
step: 2900 | loss: 0.953074778
step: 2910 | loss: 0.951836758
step: 2920 | loss: 0.950599280
step: 2930 | loss: 0.949362345
step: 2940 | loss: 0.948125952
step: 2950 | loss: 0.946890100
step: 2960 | loss: 0.945654791
step: 2970 | loss: 0.944420023
step: 2980 | loss: 0.943185797
step: 2990 | loss: 0.941952113
step: 3000 | loss: 0.940718969
step: 3010 | loss: 0.939486367
step: 3020 | loss: 0.938254306
step: 3030 | loss: 0.937022785
step: 3040 | loss: 0.935791806
step: 3050 | loss: 0.934561366
step: 3060 | loss: 0.933331467
step: 3070 | loss: 0.932102108
step: 3080 | loss: 0.930873290
step: 3090 | loss: 0.929645010
step: 3100 | loss: 0.928417271
step: 3110 | loss: 0.927190071
step: 3120 | loss: 0.925963410
step: 3130 | loss: 0.924737288
step: 3140 | loss: 0.923511705
step: 3150 | loss: 0.922286661
step: 3160 | loss: 0.921062155
step: 3170 | loss: 0.919838188
step: 3180 | loss: 0.918614758
step: 3190 | loss: 0.917391866
step: 3200 | loss: 0.916169512
step: 3210 | loss: 0.914947695
step: 3220 | loss: 0.913726415
step: 3230 | loss: 0.912505672
step: 3240 | loss: 0.911285466
step: 3250 | loss: 0.910065796
step: 3260 | loss: 0.908846662
step: 3270 | loss: 0.907628064
step: 3280 | loss: 0.906410001
step: 3290 | loss: 0.905192474
step: 3300 | loss: 0.903975482
step: 3310 | loss: 0.902759025
step: 3320 | loss: 0.901543102
step: 3330 | loss: 0.900327714
step: 3340 | loss: 0.899112859
step: 3350 | loss: 0.897898538
step: 3360 | loss: 0.896684750
step: 3370 | loss: 0.895471495
step: 3380 | loss: 0.894258773
step: 3390 | loss: 0.893046584
step: 3400 | loss: 0.891834926
step: 3410 | loss: 0.890623800
step: 3420 | loss: 0.889413205
step: 3430 | loss: 0.888203142
step: 3440 | loss: 0.886993609
step: 3450 | loss: 0.885784606
step: 3460 | loss: 0.884576134
step: 3470 | loss: 0.883368191
step: 3480 | loss: 0.882160777
step: 3490 | loss: 0.880953892
step: 3500 | loss: 0.879747536
step: 3510 | loss: 0.878541708
step: 3520 | loss: 0.877336408
step: 3530 | loss: 0.876131636
step: 3540 | loss: 0.874927390
step: 3550 | loss: 0.873723671
step: 3560 | loss: 0.872520478
step: 3570 | loss: 0.871317811
step: 3580 | loss: 0.870115670
step: 3590 | loss: 0.868914054
step: 3600 | loss: 0.867712962
step: 3610 | loss: 0.866512395
step: 3620 | loss: 0.865312352
step: 3630 | loss: 0.864112832
step: 3640 | loss: 0.862913835
step: 3650 | loss: 0.861715360
step: 3660 | loss: 0.860517408
step: 3670 | loss: 0.859319978
step: 3680 | loss: 0.858123069
step: 3690 | loss: 0.856926681
step: 3700 | loss: 0.855730814
step: 3710 | loss: 0.854535466
step: 3720 | loss: 0.853340639
step: 3730 | loss: 0.852146330
step: 3740 | loss: 0.850952541
step: 3750 | loss: 0.849759269
step: 3760 | loss: 0.848566516
step: 3770 | loss: 0.847374280
step: 3780 | loss: 0.846182562
step: 3790 | loss: 0.844991360
step: 3800 | loss: 0.843800674
step: 3810 | loss: 0.842610505
step: 3820 | loss: 0.841420850
step: 3830 | loss: 0.840231711
step: 3840 | loss: 0.839043086
step: 3850 | loss: 0.837854975
step: 3860 | loss: 0.836667378
step: 3870 | loss: 0.835480295
step: 3880 | loss: 0.834293724
step: 3890 | loss: 0.833107665
step: 3900 | loss: 0.831922119
step: 3910 | loss: 0.830737085
step: 3920 | loss: 0.829552561
step: 3930 | loss: 0.828368549
step: 3940 | loss: 0.827185047
step: 3950 | loss: 0.826002055
step: 3960 | loss: 0.824819572
step: 3970 | loss: 0.823637599
step: 3980 | loss: 0.822456135
step: 3990 | loss: 0.821275180
step: 4000 | loss: 0.820094733
step: 4010 | loss: 0.818914793
step: 4020 | loss: 0.817735361
step: 4030 | loss: 0.816556436
step: 4040 | loss: 0.815378018
step: 4050 | loss: 0.814200106
step: 4060 | loss: 0.813022700
step: 4070 | loss: 0.811845800
step: 4080 | loss: 0.810669406
step: 4090 | loss: 0.809493516
step: 4100 | loss: 0.808318132
step: 4110 | loss: 0.807143252
step: 4120 | loss: 0.805968876
step: 4130 | loss: 0.804795004
step: 4140 | loss: 0.803621636
step: 4150 | loss: 0.802448772
step: 4160 | loss: 0.801276411
step: 4170 | loss: 0.800104552
step: 4180 | loss: 0.798933197
step: 4190 | loss: 0.797762343
step: 4200 | loss: 0.796591993
step: 4210 | loss: 0.795422144
step: 4220 | loss: 0.794252797
step: 4230 | loss: 0.793083952
step: 4240 | loss: 0.791915609
step: 4250 | loss: 0.790747767
step: 4260 | loss: 0.789580427
step: 4270 | loss: 0.788413587
step: 4280 | loss: 0.787247249
step: 4290 | loss: 0.786081412
step: 4300 | loss: 0.784916075
step: 4310 | loss: 0.783751240
step: 4320 | loss: 0.782586905
step: 4330 | loss: 0.781423071
step: 4340 | loss: 0.780259737
step: 4350 | loss: 0.779096904
step: 4360 | loss: 0.777934572
step: 4370 | loss: 0.776772741
step: 4380 | loss: 0.775611410
step: 4390 | loss: 0.774450580
step: 4400 | loss: 0.773290250
step: 4410 | loss: 0.772130422
step: 4420 | loss: 0.770971094
step: 4430 | loss: 0.769812268
step: 4440 | loss: 0.768653942
step: 4450 | loss: 0.767496118
step: 4460 | loss: 0.766338796
step: 4470 | loss: 0.765181975
step: 4480 | loss: 0.764025655
step: 4490 | loss: 0.762869838
step: 4500 | loss: 0.761714523
step: 4510 | loss: 0.760559710
step: 4520 | loss: 0.759405400
step: 4530 | loss: 0.758251593
step: 4540 | loss: 0.757098290
step: 4550 | loss: 0.755945489
step: 4560 | loss: 0.754793193
step: 4570 | loss: 0.753641401
step: 4580 | loss: 0.752490113
step: 4590 | loss: 0.751339331
step: 4600 | loss: 0.750189053
step: 4610 | loss: 0.749039282
step: 4620 | loss: 0.747890017
step: 4630 | loss: 0.746741258
step: 4640 | loss: 0.745593006
step: 4650 | loss: 0.744445262
step: 4660 | loss: 0.743298026
step: 4670 | loss: 0.742151298
step: 4680 | loss: 0.741005080
step: 4690 | loss: 0.739859371
step: 4700 | loss: 0.738714173
step: 4710 | loss: 0.737569485
step: 4720 | loss: 0.736425309
step: 4730 | loss: 0.735281645
step: 4740 | loss: 0.734138494
step: 4750 | loss: 0.732995856
step: 4760 | loss: 0.731853732
step: 4770 | loss: 0.730712123
step: 4780 | loss: 0.729571030
step: 4790 | loss: 0.728430452
step: 4800 | loss: 0.727290392
step: 4810 | loss: 0.726150849
step: 4820 | loss: 0.725011825
step: 4830 | loss: 0.723873321
step: 4840 | loss: 0.722735336
step: 4850 | loss: 0.721597873
step: 4860 | loss: 0.720460931
step: 4870 | loss: 0.719324512
step: 4880 | loss: 0.718188617
step: 4890 | loss: 0.717053247
step: 4900 | loss: 0.715918402
step: 4910 | loss: 0.714784083
step: 4920 | loss: 0.713650292
step: 4930 | loss: 0.712517029
step: 4940 | loss: 0.711384295
step: 4950 | loss: 0.710252092
step: 4960 | loss: 0.709120421
step: 4970 | loss: 0.707989281
step: 4980 | loss: 0.706858676
step: 4990 | loss: 0.705728605
step: 5000 | loss: 0.704599069
step: 5010 | loss: 0.703470070
step: 5020 | loss: 0.702341610
step: 5030 | loss: 0.701213688
step: 5040 | loss: 0.700086306
step: 5050 | loss: 0.698959466
step: 5060 | loss: 0.697833168
step: 5070 | loss: 0.696707414
step: 5080 | loss: 0.695582205
step: 5090 | loss: 0.694457542
step: 5100 | loss: 0.693333426
step: 5110 | loss: 0.692209858
step: 5120 | loss: 0.691086841
step: 5130 | loss: 0.689964375
step: 5140 | loss: 0.688842461
step: 5150 | loss: 0.687721100
step: 5160 | loss: 0.686600295
step: 5170 | loss: 0.685480046
step: 5180 | loss: 0.684360354
step: 5190 | loss: 0.683241221
step: 5200 | loss: 0.682122649
step: 5210 | loss: 0.681004638
step: 5220 | loss: 0.679887190
step: 5230 | loss: 0.678770307
step: 5240 | loss: 0.677653989
step: 5250 | loss: 0.676538239
step: 5260 | loss: 0.675423057
step: 5270 | loss: 0.674308445
step: 5280 | loss: 0.673194404
step: 5290 | loss: 0.672080936
step: 5300 | loss: 0.670968042
step: 5310 | loss: 0.669855725
step: 5320 | loss: 0.668743984
step: 5330 | loss: 0.667632822
step: 5340 | loss: 0.666522240
step: 5350 | loss: 0.665412239
step: 5360 | loss: 0.664302822
step: 5370 | loss: 0.663193989
step: 5380 | loss: 0.662085742
step: 5390 | loss: 0.660978083
step: 5400 | loss: 0.659871013
step: 5410 | loss: 0.658764533
step: 5420 | loss: 0.657658646
step: 5430 | loss: 0.656553352
step: 5440 | loss: 0.655448654
step: 5450 | loss: 0.654344552
step: 5460 | loss: 0.653241048
step: 5470 | loss: 0.652138145
step: 5480 | loss: 0.651035842
step: 5490 | loss: 0.649934143
step: 5500 | loss: 0.648833048
step: 5510 | loss: 0.647732559
step: 5520 | loss: 0.646632678
step: 5530 | loss: 0.645533406
step: 5540 | loss: 0.644434745
step: 5550 | loss: 0.643336696
step: 5560 | loss: 0.642239261
step: 5570 | loss: 0.641142442
step: 5580 | loss: 0.640046240
step: 5590 | loss: 0.638950656
step: 5600 | loss: 0.637855693
step: 5610 | loss: 0.636761352
step: 5620 | loss: 0.635667635
step: 5630 | loss: 0.634574542
step: 5640 | loss: 0.633482077
step: 5650 | loss: 0.632390239
step: 5660 | loss: 0.631299032
step: 5670 | loss: 0.630208456
step: 5680 | loss: 0.629118513
step: 5690 | loss: 0.628029206
step: 5700 | loss: 0.626940534
step: 5710 | loss: 0.625852501
step: 5720 | loss: 0.624765107
step: 5730 | loss: 0.623678354
step: 5740 | loss: 0.622592244
step: 5750 | loss: 0.621506779
step: 5760 | loss: 0.620421959
step: 5770 | loss: 0.619337787
step: 5780 | loss: 0.618254265
step: 5790 | loss: 0.617171393
step: 5800 | loss: 0.616089174
step: 5810 | loss: 0.615007609
step: 5820 | loss: 0.613926700
step: 5830 | loss: 0.612846448
step: 5840 | loss: 0.611766854
step: 5850 | loss: 0.610687922
step: 5860 | loss: 0.609609651
step: 5870 | loss: 0.608532044
step: 5880 | loss: 0.607455102
step: 5890 | loss: 0.606378827
step: 5900 | loss: 0.605303221
step: 5910 | loss: 0.604228285
step: 5920 | loss: 0.603154020
step: 5930 | loss: 0.602080428
step: 5940 | loss: 0.601007512
step: 5950 | loss: 0.599935271
step: 5960 | loss: 0.598863709
step: 5970 | loss: 0.597792826
step: 5980 | loss: 0.596722624
step: 5990 | loss: 0.595653104
step: 6000 | loss: 0.594584269
step: 6010 | loss: 0.593516119
step: 6020 | loss: 0.592448657
step: 6030 | loss: 0.591381884
step: 6040 | loss: 0.590315801
step: 6050 | loss: 0.589250409
step: 6060 | loss: 0.588185711
step: 6070 | loss: 0.587121708
step: 6080 | loss: 0.586058402
step: 6090 | loss: 0.584995793
step: 6100 | loss: 0.583933884
step: 6110 | loss: 0.582872676
step: 6120 | loss: 0.581812170
step: 6130 | loss: 0.580752368
step: 6140 | loss: 0.579693272
step: 6150 | loss: 0.578634882
step: 6160 | loss: 0.577577201
step: 6170 | loss: 0.576520229
step: 6180 | loss: 0.575463969
step: 6190 | loss: 0.574408422
step: 6200 | loss: 0.573353588
step: 6210 | loss: 0.572299470
step: 6220 | loss: 0.571246070
step: 6230 | loss: 0.570193387
step: 6240 | loss: 0.569141425
step: 6250 | loss: 0.568090183
step: 6260 | loss: 0.567039665
step: 6270 | loss: 0.565989870
step: 6280 | loss: 0.564940801
step: 6290 | loss: 0.563892458
step: 6300 | loss: 0.562844844
step: 6310 | loss: 0.561797958
step: 6320 | loss: 0.560751804
step: 6330 | loss: 0.559706382
step: 6340 | loss: 0.558661693
step: 6350 | loss: 0.557617739
step: 6360 | loss: 0.556574521
step: 6370 | loss: 0.555532041
step: 6380 | loss: 0.554490299
step: 6390 | loss: 0.553449296
step: 6400 | loss: 0.552409035
step: 6410 | loss: 0.551369517
step: 6420 | loss: 0.550330742
step: 6430 | loss: 0.549292711
step: 6440 | loss: 0.548255427
step: 6450 | loss: 0.547218890
step: 6460 | loss: 0.546183102
step: 6470 | loss: 0.545148063
step: 6480 | loss: 0.544113774
step: 6490 | loss: 0.543080238
step: 6500 | loss: 0.542047455
step: 6510 | loss: 0.541015426
step: 6520 | loss: 0.539984152
step: 6530 | loss: 0.538953634
step: 6540 | loss: 0.537923874
step: 6550 | loss: 0.536894873
step: 6560 | loss: 0.535866631
step: 6570 | loss: 0.534839150
step: 6580 | loss: 0.533812430
step: 6590 | loss: 0.532786474
step: 6600 | loss: 0.531761280
step: 6610 | loss: 0.530736852
step: 6620 | loss: 0.529713189
step: 6630 | loss: 0.528690293
step: 6640 | loss: 0.527668164
step: 6650 | loss: 0.526646804
step: 6660 | loss: 0.525626213
step: 6670 | loss: 0.524606392
step: 6680 | loss: 0.523587342
step: 6690 | loss: 0.522569065
step: 6700 | loss: 0.521551560
step: 6710 | loss: 0.520534829
step: 6720 | loss: 0.519518873
step: 6730 | loss: 0.518503691
step: 6740 | loss: 0.517489286
step: 6750 | loss: 0.516475658
step: 6760 | loss: 0.515462807
step: 6770 | loss: 0.514450734
step: 6780 | loss: 0.513439440
step: 6790 | loss: 0.512428927
step: 6800 | loss: 0.511419193
step: 6810 | loss: 0.510410240
step: 6820 | loss: 0.509402069
step: 6830 | loss: 0.508394681
step: 6840 | loss: 0.507388075
step: 6850 | loss: 0.506382252
step: 6860 | loss: 0.505377214
step: 6870 | loss: 0.504372960
step: 6880 | loss: 0.503369491
step: 6890 | loss: 0.502366808
step: 6900 | loss: 0.501364911
step: 6910 | loss: 0.500363800
step: 6920 | loss: 0.499363477
step: 6930 | loss: 0.498363940
step: 6940 | loss: 0.497365192
step: 6950 | loss: 0.496367232
step: 6960 | loss: 0.495370060
step: 6970 | loss: 0.494373677
step: 6980 | loss: 0.493378084
step: 6990 | loss: 0.492383279
step: 7000 | loss: 0.491389265
step: 7010 | loss: 0.490396041
step: 7020 | loss: 0.489403607
step: 7030 | loss: 0.488411964
step: 7040 | loss: 0.487421112
step: 7050 | loss: 0.486431050
step: 7060 | loss: 0.485441780
step: 7070 | loss: 0.484453300
step: 7080 | loss: 0.483465613
step: 7090 | loss: 0.482478716
step: 7100 | loss: 0.481492612
step: 7110 | loss: 0.480507298
step: 7120 | loss: 0.479522777
step: 7130 | loss: 0.478539047
step: 7140 | loss: 0.477556109
step: 7150 | loss: 0.476573963
step: 7160 | loss: 0.475592608
step: 7170 | loss: 0.474612044
step: 7180 | loss: 0.473632273
step: 7190 | loss: 0.472653292
step: 7200 | loss: 0.471675103
step: 7210 | loss: 0.470697705
step: 7220 | loss: 0.469721097
step: 7230 | loss: 0.468745281
step: 7240 | loss: 0.467770255
step: 7250 | loss: 0.466796019
step: 7260 | loss: 0.465822574
step: 7270 | loss: 0.464849918
step: 7280 | loss: 0.463878051
step: 7290 | loss: 0.462906974
step: 7300 | loss: 0.461936686
step: 7310 | loss: 0.460967186
step: 7320 | loss: 0.459998474
step: 7330 | loss: 0.459030551
step: 7340 | loss: 0.458063414
step: 7350 | loss: 0.457097064
step: 7360 | loss: 0.456131501
step: 7370 | loss: 0.455166724
step: 7380 | loss: 0.454202733
step: 7390 | loss: 0.453239526
step: 7400 | loss: 0.452277105
step: 7410 | loss: 0.451315467
step: 7420 | loss: 0.450354612
step: 7430 | loss: 0.449394541
step: 7440 | loss: 0.448435252
step: 7450 | loss: 0.447476745
step: 7460 | loss: 0.446519018
step: 7470 | loss: 0.445562073
step: 7480 | loss: 0.444605907
step: 7490 | loss: 0.443650520
step: 7500 | loss: 0.442695912
step: 7510 | loss: 0.441742081
step: 7520 | loss: 0.440789028
step: 7530 | loss: 0.439836751
step: 7540 | loss: 0.438885250
step: 7550 | loss: 0.437934524
step: 7560 | loss: 0.436984572
step: 7570 | loss: 0.436035393
step: 7580 | loss: 0.435086987
step: 7590 | loss: 0.434139353
step: 7600 | loss: 0.433192490
step: 7610 | loss: 0.432246397
step: 7620 | loss: 0.431301074
step: 7630 | loss: 0.430356519
step: 7640 | loss: 0.429412732
step: 7650 | loss: 0.428469711
step: 7660 | loss: 0.427527457
step: 7670 | loss: 0.426585968
step: 7680 | loss: 0.425645243
step: 7690 | loss: 0.424705281
step: 7700 | loss: 0.423766082
step: 7710 | loss: 0.422827644
step: 7720 | loss: 0.421889968
step: 7730 | loss: 0.420953051
step: 7740 | loss: 0.420016893
step: 7750 | loss: 0.419081492
step: 7760 | loss: 0.418146849
step: 7770 | loss: 0.417212962
step: 7780 | loss: 0.416279831
step: 7790 | loss: 0.415347453
step: 7800 | loss: 0.414415829
step: 7810 | loss: 0.413484957
step: 7820 | loss: 0.412554837
step: 7830 | loss: 0.411625467
step: 7840 | loss: 0.410696848
step: 7850 | loss: 0.409768976
step: 7860 | loss: 0.408841853
step: 7870 | loss: 0.407915476
step: 7880 | loss: 0.406989846
step: 7890 | loss: 0.406064960
step: 7900 | loss: 0.405140819
step: 7910 | loss: 0.404217421
step: 7920 | loss: 0.403294765
step: 7930 | loss: 0.402372851
step: 7940 | loss: 0.401451677
step: 7950 | loss: 0.400531243
step: 7960 | loss: 0.399611548
step: 7970 | loss: 0.398692590
step: 7980 | loss: 0.397774370
step: 7990 | loss: 0.396856886
step: 8000 | loss: 0.395940138
step: 8010 | loss: 0.395024124
step: 8020 | loss: 0.394108844
step: 8030 | loss: 0.393194296
step: 8040 | loss: 0.392280481
step: 8050 | loss: 0.391367398
step: 8060 | loss: 0.390455044
step: 8070 | loss: 0.389543421
step: 8080 | loss: 0.388632527
step: 8090 | loss: 0.387722361
step: 8100 | loss: 0.386812923
step: 8110 | loss: 0.385904212
step: 8120 | loss: 0.384996226
step: 8130 | loss: 0.384088967
step: 8140 | loss: 0.383182432
step: 8150 | loss: 0.382276622
step: 8160 | loss: 0.381371535
step: 8170 | loss: 0.380467171
step: 8180 | loss: 0.379563530
step: 8190 | loss: 0.378660611
step: 8200 | loss: 0.377758412
step: 8210 | loss: 0.376856935
step: 8220 | loss: 0.375956177
step: 8230 | loss: 0.375056139
step: 8240 | loss: 0.374156820
step: 8250 | loss: 0.373258220
step: 8260 | loss: 0.372360338
step: 8270 | loss: 0.371463174
step: 8280 | loss: 0.370566727
step: 8290 | loss: 0.369670997
step: 8300 | loss: 0.368775984
step: 8310 | loss: 0.367881687
step: 8320 | loss: 0.366988105
step: 8330 | loss: 0.366095239
step: 8340 | loss: 0.365203087
step: 8350 | loss: 0.364311651
step: 8360 | loss: 0.363420929
step: 8370 | loss: 0.362530921
step: 8380 | loss: 0.361641627
step: 8390 | loss: 0.360753047
step: 8400 | loss: 0.359865181
step: 8410 | loss: 0.358978027
step: 8420 | loss: 0.358091587
step: 8430 | loss: 0.357205859
step: 8440 | loss: 0.356320844
step: 8450 | loss: 0.355436542
step: 8460 | loss: 0.354552952
step: 8470 | loss: 0.353670074
step: 8480 | loss: 0.352787909
step: 8490 | loss: 0.351906455
step: 8500 | loss: 0.351025713
step: 8510 | loss: 0.350145684
step: 8520 | loss: 0.349266366
step: 8530 | loss: 0.348387760
step: 8540 | loss: 0.347509865
step: 8550 | loss: 0.346632683
step: 8560 | loss: 0.345756212
step: 8570 | loss: 0.344880452
step: 8580 | loss: 0.344005404
step: 8590 | loss: 0.343131068
step: 8600 | loss: 0.342257444
step: 8610 | loss: 0.341384531
step: 8620 | loss: 0.340512329
step: 8630 | loss: 0.339640840
step: 8640 | loss: 0.338770062
step: 8650 | loss: 0.337899995
step: 8660 | loss: 0.337030641
step: 8670 | loss: 0.336161998
step: 8680 | loss: 0.335294067
step: 8690 | loss: 0.334426848
step: 8700 | loss: 0.333560340
step: 8710 | loss: 0.332694544
step: 8720 | loss: 0.331829461
step: 8730 | loss: 0.330965089
step: 8740 | loss: 0.330101428
step: 8750 | loss: 0.329238480
step: 8760 | loss: 0.328376244
step: 8770 | loss: 0.327514719
step: 8780 | loss: 0.326653906
step: 8790 | loss: 0.325793805
step: 8800 | loss: 0.324934416
step: 8810 | loss: 0.324075738
step: 8820 | loss: 0.323217772
step: 8830 | loss: 0.322360518
step: 8840 | loss: 0.321503975
step: 8850 | loss: 0.320648143
step: 8860 | loss: 0.319793022
step: 8870 | loss: 0.318938613
step: 8880 | loss: 0.318084914
step: 8890 | loss: 0.317231926
step: 8900 | loss: 0.316379648
step: 8910 | loss: 0.315528081
step: 8920 | loss: 0.314677224
step: 8930 | loss: 0.313827076
step: 8940 | loss: 0.312977638
step: 8950 | loss: 0.312128909
step: 8960 | loss: 0.311280889
step: 8970 | loss: 0.310433577
step: 8980 | loss: 0.309586974
step: 8990 | loss: 0.308741078
step: 9000 | loss: 0.307895889
step: 9010 | loss: 0.307051406
step: 9020 | loss: 0.306207630
step: 9030 | loss: 0.305364559
step: 9040 | loss: 0.304522193
step: 9050 | loss: 0.303680532
step: 9060 | loss: 0.302839574
step: 9070 | loss: 0.301999319
step: 9080 | loss: 0.301159767
step: 9090 | loss: 0.300320916
step: 9100 | loss: 0.299482766
step: 9110 | loss: 0.298645315
step: 9120 | loss: 0.297808564
step: 9130 | loss: 0.296972511
step: 9140 | loss: 0.296137155
step: 9150 | loss: 0.295302494
step: 9160 | loss: 0.294468529
step: 9170 | loss: 0.293635258
step: 9180 | loss: 0.292802680
step: 9190 | loss: 0.291970793
step: 9200 | loss: 0.291139597
step: 9210 | loss: 0.290309089
step: 9220 | loss: 0.289479270
step: 9230 | loss: 0.288650137
step: 9240 | loss: 0.287821689
step: 9250 | loss: 0.286993925
step: 9260 | loss: 0.286166842
step: 9270 | loss: 0.285340440
step: 9280 | loss: 0.284514717
step: 9290 | loss: 0.283689671
step: 9300 | loss: 0.282865300
step: 9310 | loss: 0.282041603
step: 9320 | loss: 0.281218578
step: 9330 | loss: 0.280396223
step: 9340 | loss: 0.279574536
step: 9350 | loss: 0.278753515
step: 9360 | loss: 0.277933158
step: 9370 | loss: 0.277113463
step: 9380 | loss: 0.276294427
step: 9390 | loss: 0.275476049
step: 9400 | loss: 0.274658327
step: 9410 | loss: 0.273841257
step: 9420 | loss: 0.273024838
step: 9430 | loss: 0.272209067
step: 9440 | loss: 0.271393942
step: 9450 | loss: 0.270579460
step: 9460 | loss: 0.269765618
step: 9470 | loss: 0.268952414
step: 9480 | loss: 0.268139845
step: 9490 | loss: 0.267327909
step: 9500 | loss: 0.266516602
step: 9510 | loss: 0.265705922
step: 9520 | loss: 0.264895866
step: 9530 | loss: 0.264086430
step: 9540 | loss: 0.263277612
step: 9550 | loss: 0.262469408
step: 9560 | loss: 0.261661816
step: 9570 | loss: 0.260854832
step: 9580 | loss: 0.260048452
step: 9590 | loss: 0.259242675
step: 9600 | loss: 0.258437495
step: 9610 | loss: 0.257632909
step: 9620 | loss: 0.256828915
step: 9630 | loss: 0.256025508
step: 9640 | loss: 0.255222686
step: 9650 | loss: 0.254420443
step: 9660 | loss: 0.253618777
step: 9670 | loss: 0.252817683
step: 9680 | loss: 0.252017158
step: 9690 | loss: 0.251217198
step: 9700 | loss: 0.250417800
step: 9710 | loss: 0.249618958
step: 9720 | loss: 0.248820669
step: 9730 | loss: 0.248022928
step: 9740 | loss: 0.247225733
step: 9750 | loss: 0.246429078
step: 9760 | loss: 0.245632959
step: 9770 | loss: 0.244837372
step: 9780 | loss: 0.244042312
step: 9790 | loss: 0.243247776
step: 9800 | loss: 0.242453758
step: 9810 | loss: 0.241660255
step: 9820 | loss: 0.240867261
step: 9830 | loss: 0.240074773
step: 9840 | loss: 0.239282785
step: 9850 | loss: 0.238491293
step: 9860 | loss: 0.237700292
step: 9870 | loss: 0.236909777
step: 9880 | loss: 0.236119744
step: 9890 | loss: 0.235330189
step: 9900 | loss: 0.234541105
step: 9910 | loss: 0.233752488
step: 9920 | loss: 0.232964334
step: 9930 | loss: 0.232176637
step: 9940 | loss: 0.231389392
step: 9950 | loss: 0.230602595
step: 9960 | loss: 0.229816241
step: 9970 | loss: 0.229030323
step: 9980 | loss: 0.228244838
step: 9990 | loss: 0.227459781
step: 10000 | loss: 0.226675145
step: 10010 | loss: 0.225890927
step: 10020 | loss: 0.225107120
step: 10030 | loss: 0.224323720
step: 10040 | loss: 0.223540722
step: 10050 | loss: 0.222758120
step: 10060 | loss: 0.221975909
step: 10070 | loss: 0.221194084
step: 10080 | loss: 0.220412641
step: 10090 | loss: 0.219631572
step: 10100 | loss: 0.218850875
step: 10110 | loss: 0.218070542
step: 10120 | loss: 0.217290569
step: 10130 | loss: 0.216510951
step: 10140 | loss: 0.215731683
step: 10150 | loss: 0.214952759
step: 10160 | loss: 0.214174174
step: 10170 | loss: 0.213395923
step: 10180 | loss: 0.212618001
step: 10190 | loss: 0.211840403
step: 10200 | loss: 0.211063123
step: 10210 | loss: 0.210286156
step: 10220 | loss: 0.209509498
step: 10230 | loss: 0.208733143
step: 10240 | loss: 0.207957086
step: 10250 | loss: 0.207181322
step: 10260 | loss: 0.206405845
step: 10270 | loss: 0.205630652
step: 10280 | loss: 0.204855737
step: 10290 | loss: 0.204081096
step: 10300 | loss: 0.203306722
step: 10310 | loss: 0.202532612
step: 10320 | loss: 0.201758760
step: 10330 | loss: 0.200985162
step: 10340 | loss: 0.200211813
step: 10350 | loss: 0.199438708
step: 10360 | loss: 0.198665842
step: 10370 | loss: 0.197893212
step: 10380 | loss: 0.197120812
step: 10390 | loss: 0.196348638
step: 10400 | loss: 0.195576685
step: 10410 | loss: 0.194804948
step: 10420 | loss: 0.194033425
step: 10430 | loss: 0.193262109
step: 10440 | loss: 0.192490997
step: 10450 | loss: 0.191720085
step: 10460 | loss: 0.190949368
step: 10470 | loss: 0.190178843
step: 10480 | loss: 0.189408504
step: 10490 | loss: 0.188638349
step: 10500 | loss: 0.187868373
step: 10510 | loss: 0.187098573
step: 10520 | loss: 0.186328943
step: 10530 | loss: 0.185559482
step: 10540 | loss: 0.184790184
step: 10550 | loss: 0.184021047
step: 10560 | loss: 0.183252067
step: 10570 | loss: 0.182483240
step: 10580 | loss: 0.181714562
step: 10590 | loss: 0.180946031
step: 10600 | loss: 0.180177643
step: 10610 | loss: 0.179409395
step: 10620 | loss: 0.178641283
step: 10630 | loss: 0.177873305
step: 10640 | loss: 0.177105457
step: 10650 | loss: 0.176337736
step: 10660 | loss: 0.175570139
step: 10670 | loss: 0.174802665
step: 10680 | loss: 0.174035308
step: 10690 | loss: 0.173268068
step: 10700 | loss: 0.172500941
step: 10710 | loss: 0.171733924
step: 10720 | loss: 0.170967016
step: 10730 | loss: 0.170200213
step: 10740 | loss: 0.169433513
step: 10750 | loss: 0.168666914
step: 10760 | loss: 0.167900413
step: 10770 | loss: 0.167134008
step: 10780 | loss: 0.166367697
step: 10790 | loss: 0.165601478
step: 10800 | loss: 0.164835349
step: 10810 | loss: 0.164069308
step: 10820 | loss: 0.163303352
step: 10830 | loss: 0.162537480
step: 10840 | loss: 0.161771690
step: 10850 | loss: 0.161005980
step: 10860 | loss: 0.160240348
step: 10870 | loss: 0.159474793
step: 10880 | loss: 0.158709313
step: 10890 | loss: 0.157943907
step: 10900 | loss: 0.157178573
step: 10910 | loss: 0.156413309
step: 10920 | loss: 0.155648113
step: 10930 | loss: 0.154882986
step: 10940 | loss: 0.154117925
step: 10950 | loss: 0.153352928
step: 10960 | loss: 0.152587995
step: 10970 | loss: 0.151823125
step: 10980 | loss: 0.151058315
step: 10990 | loss: 0.150293566
step: 11000 | loss: 0.149528875
step: 11010 | loss: 0.148764242
step: 11020 | loss: 0.147999666
step: 11030 | loss: 0.147235146
step: 11040 | loss: 0.146470680
step: 11050 | loss: 0.145706268
step: 11060 | loss: 0.144941909
step: 11070 | loss: 0.144177602
step: 11080 | loss: 0.143413346
step: 11090 | loss: 0.142649140
step: 11100 | loss: 0.141884984
step: 11110 | loss: 0.141120876
step: 11120 | loss: 0.140356816
step: 11130 | loss: 0.139592804
step: 11140 | loss: 0.138828838
step: 11150 | loss: 0.138064918
step: 11160 | loss: 0.137301042
step: 11170 | loss: 0.136537212
step: 11180 | loss: 0.135773425
step: 11190 | loss: 0.135009681
step: 11200 | loss: 0.134245980
step: 11210 | loss: 0.133482321
step: 11220 | loss: 0.132718704
step: 11230 | loss: 0.131955127
step: 11240 | loss: 0.131191591
step: 11250 | loss: 0.130428095
step: 11260 | loss: 0.129664639
step: 11270 | loss: 0.128901221
step: 11280 | loss: 0.128137841
step: 11290 | loss: 0.127374500
step: 11300 | loss: 0.126611196
step: 11310 | loss: 0.125847929
step: 11320 | loss: 0.125084699
step: 11330 | loss: 0.124321505
step: 11340 | loss: 0.123558347
step: 11350 | loss: 0.122795224
step: 11360 | loss: 0.122032136
step: 11370 | loss: 0.121269083
step: 11380 | loss: 0.120506064
step: 11390 | loss: 0.119743079
step: 11400 | loss: 0.118980127
step: 11410 | loss: 0.118217209
step: 11420 | loss: 0.117454323
step: 11430 | loss: 0.116691469
step: 11440 | loss: 0.115928648
step: 11450 | loss: 0.115165858
step: 11460 | loss: 0.114403100
step: 11470 | loss: 0.113640373
step: 11480 | loss: 0.112877676
step: 11490 | loss: 0.112115010
step: 11500 | loss: 0.111352374
step: 11510 | loss: 0.110589768
step: 11520 | loss: 0.109827191
step: 11530 | loss: 0.109064644
step: 11540 | loss: 0.108302125
step: 11550 | loss: 0.107539635
step: 11560 | loss: 0.106777173
step: 11570 | loss: 0.106014739
step: 11580 | loss: 0.105252333
step: 11590 | loss: 0.104489954
step: 11600 | loss: 0.103727602
step: 11610 | loss: 0.102965278
step: 11620 | loss: 0.102202979
step: 11630 | loss: 0.101440708
step: 11640 | loss: 0.100678462
step: 11650 | loss: 0.099916242
step: 11660 | loss: 0.099154047
step: 11670 | loss: 0.098391878
step: 11680 | loss: 0.097629734
step: 11690 | loss: 0.096867615
step: 11700 | loss: 0.096105520
step: 11710 | loss: 0.095343449
step: 11720 | loss: 0.094581403
step: 11730 | loss: 0.093819380
step: 11740 | loss: 0.093057381
step: 11750 | loss: 0.092295405
step: 11760 | loss: 0.091533452
step: 11770 | loss: 0.090771522
step: 11780 | loss: 0.090009614
step: 11790 | loss: 0.089247729
step: 11800 | loss: 0.088485867
step: 11810 | loss: 0.087724026
step: 11820 | loss: 0.086962207
step: 11830 | loss: 0.086200409
step: 11840 | loss: 0.085438633
step: 11850 | loss: 0.084676877
step: 11860 | loss: 0.083915143
step: 11870 | loss: 0.083153429
step: 11880 | loss: 0.082391736
step: 11890 | loss: 0.081630063
step: 11900 | loss: 0.080868410
step: 11910 | loss: 0.080106776
step: 11920 | loss: 0.079345163
step: 11930 | loss: 0.078583569
step: 11940 | loss: 0.077821994
step: 11950 | loss: 0.077060438
step: 11960 | loss: 0.076298901
step: 11970 | loss: 0.075537382
step: 11980 | loss: 0.074775883
step: 11990 | loss: 0.074014401
step: 12000 | loss: 0.073252938
step: 12010 | loss: 0.072491492
step: 12020 | loss: 0.071730064
step: 12030 | loss: 0.070968654
step: 12040 | loss: 0.070207262
step: 12050 | loss: 0.069445886
step: 12060 | loss: 0.068684527
step: 12070 | loss: 0.067923186
step: 12080 | loss: 0.067161861
step: 12090 | loss: 0.066400553
step: 12100 | loss: 0.065639261
step: 12110 | loss: 0.064877985
step: 12120 | loss: 0.064116725
step: 12130 | loss: 0.063355481
step: 12140 | loss: 0.062594253
step: 12150 | loss: 0.061833041
step: 12160 | loss: 0.061071844
step: 12170 | loss: 0.060310662
step: 12180 | loss: 0.059549495
step: 12190 | loss: 0.058788344
step: 12200 | loss: 0.058027207
step: 12210 | loss: 0.057266084
step: 12220 | loss: 0.056504977
step: 12230 | loss: 0.055743883
step: 12240 | loss: 0.054982804
step: 12250 | loss: 0.054221739
step: 12260 | loss: 0.053460688
step: 12270 | loss: 0.052699651
step: 12280 | loss: 0.051938627
step: 12290 | loss: 0.051177617
step: 12300 | loss: 0.050416620
step: 12310 | loss: 0.049655637
step: 12320 | loss: 0.048894666
step: 12330 | loss: 0.048133709
step: 12340 | loss: 0.047372764
step: 12350 | loss: 0.046611833
step: 12360 | loss: 0.045850913
step: 12370 | loss: 0.045090007
step: 12380 | loss: 0.044329112
step: 12390 | loss: 0.043568230
step: 12400 | loss: 0.042807360
step: 12410 | loss: 0.042046502
step: 12420 | loss: 0.041285656
step: 12430 | loss: 0.040524822
step: 12440 | loss: 0.039763999
step: 12450 | loss: 0.039003188
step: 12460 | loss: 0.038242388
step: 12470 | loss: 0.037481600
step: 12480 | loss: 0.036720823
step: 12490 | loss: 0.035960056
step: 12500 | loss: 0.035199301
step: 12510 | loss: 0.034438557
step: 12520 | loss: 0.033677823
step: 12530 | loss: 0.032917100
step: 12540 | loss: 0.032156387
step: 12550 | loss: 0.031395685
step: 12560 | loss: 0.030634993
step: 12570 | loss: 0.029874312
step: 12580 | loss: 0.029113640
step: 12590 | loss: 0.028352978
step: 12600 | loss: 0.027592327
step: 12610 | loss: 0.026831685
step: 12620 | loss: 0.026071053
step: 12630 | loss: 0.025310431
step: 12640 | loss: 0.024549818
step: 12650 | loss: 0.023789214
step: 12660 | loss: 0.023028620
step: 12670 | loss: 0.022268035
step: 12680 | loss: 0.021507459
step: 12690 | loss: 0.020746892
step: 12700 | loss: 0.019986334
step: 12710 | loss: 0.019225785
step: 12720 | loss: 0.018465245
step: 12730 | loss: 0.017704714
step: 12740 | loss: 0.016944191
step: 12750 | loss: 0.016183677
step: 12760 | loss: 0.015423171
step: 12770 | loss: 0.014662673
step: 12780 | loss: 0.013902184
step: 12790 | loss: 0.013141703
step: 12800 | loss: 0.012381230
step: 12810 | loss: 0.011620765
step: 12820 | loss: 0.010860308
step: 12830 | loss: 0.010099859
step: 12840 | loss: 0.009339417
step: 12850 | loss: 0.008578983
step: 12860 | loss: 0.007818557
step: 12870 | loss: 0.007058139
step: 12880 | loss: 0.006297728
step: 12890 | loss: 0.005537324
step: 12900 | loss: 0.004776928
step: 12910 | loss: 0.004016539
step: 12920 | loss: 0.003256157
step: 12930 | loss: 0.002495782
step: 12940 | loss: 0.001735415
step: 12950 | loss: 0.000975054
- final loss: 0.000975
- (cd _build/default/examples/opt && ./rmsprop.exe)
- 
step: 0 | loss: 3.696120939
step: 10 | loss: 3.688972760
step: 20 | loss: 3.683905673
step: 30 | loss: 3.679276444
step: 40 | loss: 3.674772899
step: 50 | loss: 3.670310761
step: 60 | loss: 3.665862913
step: 70 | loss: 3.661420156
step: 80 | loss: 3.656979311
step: 90 | loss: 3.652539274
step: 100 | loss: 3.648099662
step: 110 | loss: 3.643660341
step: 120 | loss: 3.639221265
step: 130 | loss: 3.634782419
step: 140 | loss: 3.630343798
step: 150 | loss: 3.625905401
step: 160 | loss: 3.621467228
step: 170 | loss: 3.617029279
step: 180 | loss: 3.612591555
step: 190 | loss: 3.608154058
step: 200 | loss: 3.603716787
step: 210 | loss: 3.599279743
step: 220 | loss: 3.594842929
step: 230 | loss: 3.590406343
step: 240 | loss: 3.585969988
step: 250 | loss: 3.581533864
step: 260 | loss: 3.577097972
step: 270 | loss: 3.572662313
step: 280 | loss: 3.568226887
step: 290 | loss: 3.563791696
step: 300 | loss: 3.559356740
step: 310 | loss: 3.554922020
step: 320 | loss: 3.550487538
step: 330 | loss: 3.546053293
step: 340 | loss: 3.541619288
step: 350 | loss: 3.537185522
step: 360 | loss: 3.532751998
step: 370 | loss: 3.528318714
step: 380 | loss: 3.523885674
step: 390 | loss: 3.519452877
step: 400 | loss: 3.515020324
step: 410 | loss: 3.510588016
step: 420 | loss: 3.506155955
step: 430 | loss: 3.501724141
step: 440 | loss: 3.497292575
step: 450 | loss: 3.492861259
step: 460 | loss: 3.488430192
step: 470 | loss: 3.483999376
step: 480 | loss: 3.479568812
step: 490 | loss: 3.475138501
step: 500 | loss: 3.470708444
step: 510 | loss: 3.466278642
step: 520 | loss: 3.461849096
step: 530 | loss: 3.457419806
step: 540 | loss: 3.452990774
step: 550 | loss: 3.448562001
step: 560 | loss: 3.444133488
step: 570 | loss: 3.439705235
step: 580 | loss: 3.435277245
step: 590 | loss: 3.430849517
step: 600 | loss: 3.426422053
step: 610 | loss: 3.421994853
step: 620 | loss: 3.417567920
step: 630 | loss: 3.413141254
step: 640 | loss: 3.408714855
step: 650 | loss: 3.404288726
step: 660 | loss: 3.399862866
step: 670 | loss: 3.395437278
step: 680 | loss: 3.391011962
step: 690 | loss: 3.386586919
step: 700 | loss: 3.382162150
step: 710 | loss: 3.377737657
step: 720 | loss: 3.373313440
step: 730 | loss: 3.368889501
step: 740 | loss: 3.364465840
step: 750 | loss: 3.360042459
step: 760 | loss: 3.355619359
step: 770 | loss: 3.351196541
step: 780 | loss: 3.346774006
step: 790 | loss: 3.342351755
step: 800 | loss: 3.337929790
step: 810 | loss: 3.333508111
step: 820 | loss: 3.329086719
step: 830 | loss: 3.324665617
step: 840 | loss: 3.320244804
step: 850 | loss: 3.315824282
step: 860 | loss: 3.311404053
step: 870 | loss: 3.306984117
step: 880 | loss: 3.302564475
step: 890 | loss: 3.298145130
step: 900 | loss: 3.293726081
step: 910 | loss: 3.289307330
step: 920 | loss: 3.284888879
step: 930 | loss: 3.280470728
step: 940 | loss: 3.276052880
step: 950 | loss: 3.271635334
step: 960 | loss: 3.267218092
step: 970 | loss: 3.262801156
step: 980 | loss: 3.258384526
step: 990 | loss: 3.253968205
step: 1000 | loss: 3.249552192
step: 1010 | loss: 3.245136491
step: 1020 | loss: 3.240721101
step: 1030 | loss: 3.236306023
step: 1040 | loss: 3.231891261
step: 1050 | loss: 3.227476813
step: 1060 | loss: 3.223062683
step: 1070 | loss: 3.218648871
step: 1080 | loss: 3.214235378
step: 1090 | loss: 3.209822207
step: 1100 | loss: 3.205409357
step: 1110 | loss: 3.200996831
step: 1120 | loss: 3.196584629
step: 1130 | loss: 3.192172754
step: 1140 | loss: 3.187761206
step: 1150 | loss: 3.183349987
step: 1160 | loss: 3.178939099
step: 1170 | loss: 3.174528542
step: 1180 | loss: 3.170118318
step: 1190 | loss: 3.165708428
step: 1200 | loss: 3.161298874
step: 1210 | loss: 3.156889658
step: 1220 | loss: 3.152480780
step: 1230 | loss: 3.148072242
step: 1240 | loss: 3.143664045
step: 1250 | loss: 3.139256191
step: 1260 | loss: 3.134848682
step: 1270 | loss: 3.130441519
step: 1280 | loss: 3.126034702
step: 1290 | loss: 3.121628235
step: 1300 | loss: 3.117222118
step: 1310 | loss: 3.112816352
step: 1320 | loss: 3.108410940
step: 1330 | loss: 3.104005882
step: 1340 | loss: 3.099601180
step: 1350 | loss: 3.095196837
step: 1360 | loss: 3.090792852
step: 1370 | loss: 3.086389228
step: 1380 | loss: 3.081985967
step: 1390 | loss: 3.077583070
step: 1400 | loss: 3.073180538
step: 1410 | loss: 3.068778373
step: 1420 | loss: 3.064376576
step: 1430 | loss: 3.059975150
step: 1440 | loss: 3.055574096
step: 1450 | loss: 3.051173415
step: 1460 | loss: 3.046773109
step: 1470 | loss: 3.042373179
step: 1480 | loss: 3.037973628
step: 1490 | loss: 3.033574457
step: 1500 | loss: 3.029175668
step: 1510 | loss: 3.024777261
step: 1520 | loss: 3.020379240
step: 1530 | loss: 3.015981605
step: 1540 | loss: 3.011584359
step: 1550 | loss: 3.007187502
step: 1560 | loss: 3.002791038
step: 1570 | loss: 2.998394966
step: 1580 | loss: 2.993999290
step: 1590 | loss: 2.989604011
step: 1600 | loss: 2.985209130
step: 1610 | loss: 2.980814650
step: 1620 | loss: 2.976420572
step: 1630 | loss: 2.972026898
step: 1640 | loss: 2.967633630
step: 1650 | loss: 2.963240769
step: 1660 | loss: 2.958848318
step: 1670 | loss: 2.954456278
step: 1680 | loss: 2.950064651
step: 1690 | loss: 2.945673439
step: 1700 | loss: 2.941282644
step: 1710 | loss: 2.936892267
step: 1720 | loss: 2.932502311
step: 1730 | loss: 2.928112777
step: 1740 | loss: 2.923723668
step: 1750 | loss: 2.919334985
step: 1760 | loss: 2.914946729
step: 1770 | loss: 2.910558904
step: 1780 | loss: 2.906171511
step: 1790 | loss: 2.901784552
step: 1800 | loss: 2.897398029
step: 1810 | loss: 2.893011944
step: 1820 | loss: 2.888626299
step: 1830 | loss: 2.884241095
step: 1840 | loss: 2.879856336
step: 1850 | loss: 2.875472022
step: 1860 | loss: 2.871088157
step: 1870 | loss: 2.866704742
step: 1880 | loss: 2.862321778
step: 1890 | loss: 2.857939269
step: 1900 | loss: 2.853557217
step: 1910 | loss: 2.849175622
step: 1920 | loss: 2.844794489
step: 1930 | loss: 2.840413817
step: 1940 | loss: 2.836033611
step: 1950 | loss: 2.831653872
step: 1960 | loss: 2.827274602
step: 1970 | loss: 2.822895803
step: 1980 | loss: 2.818517477
step: 1990 | loss: 2.814139627
step: 2000 | loss: 2.809762256
step: 2010 | loss: 2.805385364
step: 2020 | loss: 2.801008955
step: 2030 | loss: 2.796633030
step: 2040 | loss: 2.792257593
step: 2050 | loss: 2.787882644
step: 2060 | loss: 2.783508188
step: 2070 | loss: 2.779134225
step: 2080 | loss: 2.774760758
step: 2090 | loss: 2.770387790
step: 2100 | loss: 2.766015323
step: 2110 | loss: 2.761643359
step: 2120 | loss: 2.757271901
step: 2130 | loss: 2.752900950
step: 2140 | loss: 2.748530511
step: 2150 | loss: 2.744160584
step: 2160 | loss: 2.739791173
step: 2170 | loss: 2.735422280
step: 2180 | loss: 2.731053907
step: 2190 | loss: 2.726686056
step: 2200 | loss: 2.722318732
step: 2210 | loss: 2.717951935
step: 2220 | loss: 2.713585668
step: 2230 | loss: 2.709219935
step: 2240 | loss: 2.704854737
step: 2250 | loss: 2.700490078
step: 2260 | loss: 2.696125959
step: 2270 | loss: 2.691762383
step: 2280 | loss: 2.687399354
step: 2290 | loss: 2.683036874
step: 2300 | loss: 2.678674945
step: 2310 | loss: 2.674313570
step: 2320 | loss: 2.669952751
step: 2330 | loss: 2.665592493
step: 2340 | loss: 2.661232796
step: 2350 | loss: 2.656873665
step: 2360 | loss: 2.652515102
step: 2370 | loss: 2.648157109
step: 2380 | loss: 2.643799690
step: 2390 | loss: 2.639442847
step: 2400 | loss: 2.635086583
step: 2410 | loss: 2.630730901
step: 2420 | loss: 2.626375805
step: 2430 | loss: 2.622021296
step: 2440 | loss: 2.617667378
step: 2450 | loss: 2.613314053
step: 2460 | loss: 2.608961326
step: 2470 | loss: 2.604609198
step: 2480 | loss: 2.600257672
step: 2490 | loss: 2.595906753
step: 2500 | loss: 2.591556442
step: 2510 | loss: 2.587206743
step: 2520 | loss: 2.582857659
step: 2530 | loss: 2.578509193
step: 2540 | loss: 2.574161348
step: 2550 | loss: 2.569814128
step: 2560 | loss: 2.565467535
step: 2570 | loss: 2.561121573
step: 2580 | loss: 2.556776245
step: 2590 | loss: 2.552431553
step: 2600 | loss: 2.548087503
step: 2610 | loss: 2.543744095
step: 2620 | loss: 2.539401335
step: 2630 | loss: 2.535059225
step: 2640 | loss: 2.530717769
step: 2650 | loss: 2.526376970
step: 2660 | loss: 2.522036831
step: 2670 | loss: 2.517697356
step: 2680 | loss: 2.513358548
step: 2690 | loss: 2.509020411
step: 2700 | loss: 2.504682948
step: 2710 | loss: 2.500346163
step: 2720 | loss: 2.496010059
step: 2730 | loss: 2.491674640
step: 2740 | loss: 2.487339909
step: 2750 | loss: 2.483005870
step: 2760 | loss: 2.478672527
step: 2770 | loss: 2.474339883
step: 2780 | loss: 2.470007942
step: 2790 | loss: 2.465676707
step: 2800 | loss: 2.461346183
step: 2810 | loss: 2.457016372
step: 2820 | loss: 2.452687280
step: 2830 | loss: 2.448358909
step: 2840 | loss: 2.444031264
step: 2850 | loss: 2.439704348
step: 2860 | loss: 2.435378166
step: 2870 | loss: 2.431052720
step: 2880 | loss: 2.426728016
step: 2890 | loss: 2.422404057
step: 2900 | loss: 2.418080847
step: 2910 | loss: 2.413758389
step: 2920 | loss: 2.409436689
step: 2930 | loss: 2.405115750
step: 2940 | loss: 2.400795577
step: 2950 | loss: 2.396476173
step: 2960 | loss: 2.392157542
step: 2970 | loss: 2.387839689
step: 2980 | loss: 2.383522618
step: 2990 | loss: 2.379206334
step: 3000 | loss: 2.374890840
step: 3010 | loss: 2.370576141
step: 3020 | loss: 2.366262241
step: 3030 | loss: 2.361949144
step: 3040 | loss: 2.357636856
step: 3050 | loss: 2.353325380
step: 3060 | loss: 2.349014721
step: 3070 | loss: 2.344704883
step: 3080 | loss: 2.340395871
step: 3090 | loss: 2.336087690
step: 3100 | loss: 2.331780344
step: 3110 | loss: 2.327473837
step: 3120 | loss: 2.323168175
step: 3130 | loss: 2.318863362
step: 3140 | loss: 2.314559402
step: 3150 | loss: 2.310256302
step: 3160 | loss: 2.305954064
step: 3170 | loss: 2.301652695
step: 3180 | loss: 2.297352199
step: 3190 | loss: 2.293052581
step: 3200 | loss: 2.288753846
step: 3210 | loss: 2.284455998
step: 3220 | loss: 2.280159044
step: 3230 | loss: 2.275862988
step: 3240 | loss: 2.271567834
step: 3250 | loss: 2.267273589
step: 3260 | loss: 2.262980257
step: 3270 | loss: 2.258687844
step: 3280 | loss: 2.254396354
step: 3290 | loss: 2.250105794
step: 3300 | loss: 2.245816168
step: 3310 | loss: 2.241527481
step: 3320 | loss: 2.237239740
step: 3330 | loss: 2.232952949
step: 3340 | loss: 2.228667115
step: 3350 | loss: 2.224382242
step: 3360 | loss: 2.220098336
step: 3370 | loss: 2.215815403
step: 3380 | loss: 2.211533448
step: 3390 | loss: 2.207252477
step: 3400 | loss: 2.202972496
step: 3410 | loss: 2.198693510
step: 3420 | loss: 2.194415526
step: 3430 | loss: 2.190138550
step: 3440 | loss: 2.185862586
step: 3450 | loss: 2.181587641
step: 3460 | loss: 2.177313722
step: 3470 | loss: 2.173040833
step: 3480 | loss: 2.168768982
step: 3490 | loss: 2.164498174
step: 3500 | loss: 2.160228416
step: 3510 | loss: 2.155959713
step: 3520 | loss: 2.151692072
step: 3530 | loss: 2.147425500
step: 3540 | loss: 2.143160002
step: 3550 | loss: 2.138895586
step: 3560 | loss: 2.134632257
step: 3570 | loss: 2.130370022
step: 3580 | loss: 2.126108888
step: 3590 | loss: 2.121848861
step: 3600 | loss: 2.117589948
step: 3610 | loss: 2.113332156
step: 3620 | loss: 2.109075491
step: 3630 | loss: 2.104819961
step: 3640 | loss: 2.100565572
step: 3650 | loss: 2.096312331
step: 3660 | loss: 2.092060245
step: 3670 | loss: 2.087809321
step: 3680 | loss: 2.083559566
step: 3690 | loss: 2.079310988
step: 3700 | loss: 2.075063593
step: 3710 | loss: 2.070817389
step: 3720 | loss: 2.066572384
step: 3730 | loss: 2.062328584
step: 3740 | loss: 2.058085997
step: 3750 | loss: 2.053844631
step: 3760 | loss: 2.049604492
step: 3770 | loss: 2.045365590
step: 3780 | loss: 2.041127931
step: 3790 | loss: 2.036891523
step: 3800 | loss: 2.032656374
step: 3810 | loss: 2.028422492
step: 3820 | loss: 2.024189885
step: 3830 | loss: 2.019958560
step: 3840 | loss: 2.015728526
step: 3850 | loss: 2.011499791
step: 3860 | loss: 2.007272364
step: 3870 | loss: 2.003046252
step: 3880 | loss: 1.998821463
step: 3890 | loss: 1.994598007
step: 3900 | loss: 1.990375891
step: 3910 | loss: 1.986155124
step: 3920 | loss: 1.981935715
step: 3930 | loss: 1.977717673
step: 3940 | loss: 1.973501005
step: 3950 | loss: 1.969285722
step: 3960 | loss: 1.965071831
step: 3970 | loss: 1.960859343
step: 3980 | loss: 1.956648265
step: 3990 | loss: 1.952438606
step: 4000 | loss: 1.948230378
step: 4010 | loss: 1.944023587
step: 4020 | loss: 1.939818244
step: 4030 | loss: 1.935614358
step: 4040 | loss: 1.931411939
step: 4050 | loss: 1.927210996
step: 4060 | loss: 1.923011539
step: 4070 | loss: 1.918813578
step: 4080 | loss: 1.914617122
step: 4090 | loss: 1.910422181
step: 4100 | loss: 1.906228765
step: 4110 | loss: 1.902036885
step: 4120 | loss: 1.897846550
step: 4130 | loss: 1.893657771
step: 4140 | loss: 1.889470558
step: 4150 | loss: 1.885284921
step: 4160 | loss: 1.881100872
step: 4170 | loss: 1.876918419
step: 4180 | loss: 1.872737575
step: 4190 | loss: 1.868558350
step: 4200 | loss: 1.864380755
step: 4210 | loss: 1.860204800
step: 4220 | loss: 1.856030498
step: 4230 | loss: 1.851857858
step: 4240 | loss: 1.847686892
step: 4250 | loss: 1.843517612
step: 4260 | loss: 1.839350029
step: 4270 | loss: 1.835184154
step: 4280 | loss: 1.831019999
step: 4290 | loss: 1.826857576
step: 4300 | loss: 1.822696897
step: 4310 | loss: 1.818537974
step: 4320 | loss: 1.814380817
step: 4330 | loss: 1.810225441
step: 4340 | loss: 1.806071857
step: 4350 | loss: 1.801920077
step: 4360 | loss: 1.797770114
step: 4370 | loss: 1.793621980
step: 4380 | loss: 1.789475688
step: 4390 | loss: 1.785331251
step: 4400 | loss: 1.781188682
step: 4410 | loss: 1.777047993
step: 4420 | loss: 1.772909199
step: 4430 | loss: 1.768772311
step: 4440 | loss: 1.764637344
step: 4450 | loss: 1.760504312
step: 4460 | loss: 1.756373226
step: 4470 | loss: 1.752244102
step: 4480 | loss: 1.748116953
step: 4490 | loss: 1.743991794
step: 4500 | loss: 1.739868637
step: 4510 | loss: 1.735747498
step: 4520 | loss: 1.731628391
step: 4530 | loss: 1.727511330
step: 4540 | loss: 1.723396331
step: 4550 | loss: 1.719283406
step: 4560 | loss: 1.715172572
step: 4570 | loss: 1.711063844
step: 4580 | loss: 1.706957237
step: 4590 | loss: 1.702852765
step: 4600 | loss: 1.698750445
step: 4610 | loss: 1.694650291
step: 4620 | loss: 1.690552321
step: 4630 | loss: 1.686456548
step: 4640 | loss: 1.682362990
step: 4650 | loss: 1.678271663
step: 4660 | loss: 1.674182583
step: 4670 | loss: 1.670095766
step: 4680 | loss: 1.666011229
step: 4690 | loss: 1.661928988
step: 4700 | loss: 1.657849061
step: 4710 | loss: 1.653771465
step: 4720 | loss: 1.649696216
step: 4730 | loss: 1.645623332
step: 4740 | loss: 1.641552831
step: 4750 | loss: 1.637484731
step: 4760 | loss: 1.633419048
step: 4770 | loss: 1.629355802
step: 4780 | loss: 1.625295010
step: 4790 | loss: 1.621236691
step: 4800 | loss: 1.617180863
step: 4810 | loss: 1.613127544
step: 4820 | loss: 1.609076755
step: 4830 | loss: 1.605028514
step: 4840 | loss: 1.600982839
step: 4850 | loss: 1.596939751
step: 4860 | loss: 1.592899269
step: 4870 | loss: 1.588861413
step: 4880 | loss: 1.584826203
step: 4890 | loss: 1.580793658
step: 4900 | loss: 1.576763800
step: 4910 | loss: 1.572736648
step: 4920 | loss: 1.568712224
step: 4930 | loss: 1.564690549
step: 4940 | loss: 1.560671643
step: 4950 | loss: 1.556655528
step: 4960 | loss: 1.552642225
step: 4970 | loss: 1.548631757
step: 4980 | loss: 1.544624144
step: 4990 | loss: 1.540619410
step: 5000 | loss: 1.536617576
step: 5010 | loss: 1.532618665
step: 5020 | loss: 1.528622701
step: 5030 | loss: 1.524629705
step: 5040 | loss: 1.520639701
step: 5050 | loss: 1.516652713
step: 5060 | loss: 1.512668764
step: 5070 | loss: 1.508687878
step: 5080 | loss: 1.504710080
step: 5090 | loss: 1.500735393
step: 5100 | loss: 1.496763843
step: 5110 | loss: 1.492795453
step: 5120 | loss: 1.488830250
step: 5130 | loss: 1.484868258
step: 5140 | loss: 1.480909504
step: 5150 | loss: 1.476954012
step: 5160 | loss: 1.473001810
step: 5170 | loss: 1.469052922
step: 5180 | loss: 1.465107377
step: 5190 | loss: 1.461165200
step: 5200 | loss: 1.457226419
step: 5210 | loss: 1.453291062
step: 5220 | loss: 1.449359155
step: 5230 | loss: 1.445430727
step: 5240 | loss: 1.441505806
step: 5250 | loss: 1.437584420
step: 5260 | loss: 1.433666598
step: 5270 | loss: 1.429752370
step: 5280 | loss: 1.425841764
step: 5290 | loss: 1.421934810
step: 5300 | loss: 1.418031538
step: 5310 | loss: 1.414131978
step: 5320 | loss: 1.410236161
step: 5330 | loss: 1.406344117
step: 5340 | loss: 1.402455877
step: 5350 | loss: 1.398571473
step: 5360 | loss: 1.394690937
step: 5370 | loss: 1.390814300
step: 5380 | loss: 1.386941595
step: 5390 | loss: 1.383072854
step: 5400 | loss: 1.379208111
step: 5410 | loss: 1.375347399
step: 5420 | loss: 1.371490751
step: 5430 | loss: 1.367638201
step: 5440 | loss: 1.363789783
step: 5450 | loss: 1.359945533
step: 5460 | loss: 1.356105485
step: 5470 | loss: 1.352269675
step: 5480 | loss: 1.348438138
step: 5490 | loss: 1.344610909
step: 5500 | loss: 1.340788027
step: 5510 | loss: 1.336969526
step: 5520 | loss: 1.333155445
step: 5530 | loss: 1.329345821
step: 5540 | loss: 1.325540691
step: 5550 | loss: 1.321740095
step: 5560 | loss: 1.317944069
step: 5570 | loss: 1.314152654
step: 5580 | loss: 1.310365889
step: 5590 | loss: 1.306583813
step: 5600 | loss: 1.302806467
step: 5610 | loss: 1.299033890
step: 5620 | loss: 1.295266125
step: 5630 | loss: 1.291503212
step: 5640 | loss: 1.287745194
step: 5650 | loss: 1.283992111
step: 5660 | loss: 1.280244007
step: 5670 | loss: 1.276500924
step: 5680 | loss: 1.272762907
step: 5690 | loss: 1.269029998
step: 5700 | loss: 1.265302243
step: 5710 | loss: 1.261579685
step: 5720 | loss: 1.257862369
step: 5730 | loss: 1.254150342
step: 5740 | loss: 1.250443649
step: 5750 | loss: 1.246742336
step: 5760 | loss: 1.243046451
step: 5770 | loss: 1.239356041
step: 5780 | loss: 1.235671152
step: 5790 | loss: 1.231991834
step: 5800 | loss: 1.228318135
step: 5810 | loss: 1.224650104
step: 5820 | loss: 1.220987791
step: 5830 | loss: 1.217331245
step: 5840 | loss: 1.213680517
step: 5850 | loss: 1.210035658
step: 5860 | loss: 1.206396719
step: 5870 | loss: 1.202763752
step: 5880 | loss: 1.199136809
step: 5890 | loss: 1.195515943
step: 5900 | loss: 1.191901207
step: 5910 | loss: 1.188292655
step: 5920 | loss: 1.184690340
step: 5930 | loss: 1.181094317
step: 5940 | loss: 1.177504642
step: 5950 | loss: 1.173921369
step: 5960 | loss: 1.170344554
step: 5970 | loss: 1.166774254
step: 5980 | loss: 1.163210525
step: 5990 | loss: 1.159653425
step: 6000 | loss: 1.156103010
step: 6010 | loss: 1.152559340
step: 6020 | loss: 1.149022471
step: 6030 | loss: 1.145492463
step: 6040 | loss: 1.141969374
step: 6050 | loss: 1.138453265
step: 6060 | loss: 1.134944194
step: 6070 | loss: 1.131442221
step: 6080 | loss: 1.127947407
step: 6090 | loss: 1.124459811
step: 6100 | loss: 1.120979494
step: 6110 | loss: 1.117506517
step: 6120 | loss: 1.114040939
step: 6130 | loss: 1.110582823
step: 6140 | loss: 1.107132227
step: 6150 | loss: 1.103689212
step: 6160 | loss: 1.100253837
step: 6170 | loss: 1.096826163
step: 6180 | loss: 1.093406247
step: 6190 | loss: 1.089994146
step: 6200 | loss: 1.086589918
step: 6210 | loss: 1.083193617
step: 6220 | loss: 1.079805296
step: 6230 | loss: 1.076425005
step: 6240 | loss: 1.073052791
step: 6250 | loss: 1.069688697
step: 6260 | loss: 1.066332759
step: 6270 | loss: 1.062985008
step: 6280 | loss: 1.059645463
step: 6290 | loss: 1.056314130
step: 6300 | loss: 1.052990997
step: 6310 | loss: 1.049676023
step: 6320 | loss: 1.046369126
step: 6330 | loss: 1.043070161
step: 6340 | loss: 1.039778884
step: 6350 | loss: 1.036494894
step: 6360 | loss: 1.033217587
step: 6370 | loss: 1.029946240
step: 6380 | loss: 1.026680374
step: 6390 | loss: 1.023419896
step: 6400 | loss: 1.020164833
step: 6410 | loss: 1.016915215
step: 6420 | loss: 1.013671072
step: 6430 | loss: 1.010432429
step: 6440 | loss: 1.007199308
step: 6450 | loss: 1.003971723
step: 6460 | loss: 1.000749681
step: 6470 | loss: 0.997533179
step: 6480 | loss: 0.994322198
step: 6490 | loss: 0.991116699
step: 6500 | loss: 0.987916613
step: 6510 | loss: 0.984721825
step: 6520 | loss: 0.981532150
step: 6530 | loss: 0.978347293
step: 6540 | loss: 0.975166785
step: 6550 | loss: 0.971989941
step: 6560 | loss: 0.968815983
step: 6570 | loss: 0.965644433
step: 6580 | loss: 0.962475205
step: 6590 | loss: 0.959308316
step: 6600 | loss: 0.956143789
step: 6610 | loss: 0.952981647
step: 6620 | loss: 0.949821914
step: 6630 | loss: 0.946664613
step: 6640 | loss: 0.943509768
step: 6650 | loss: 0.940357403
step: 6660 | loss: 0.937207543
step: 6670 | loss: 0.934060213
step: 6680 | loss: 0.930915438
step: 6690 | loss: 0.927773242
step: 6700 | loss: 0.924633653
step: 6710 | loss: 0.921496695
step: 6720 | loss: 0.918362396
step: 6730 | loss: 0.915230782
step: 6740 | loss: 0.912101879
step: 6750 | loss: 0.908975716
step: 6760 | loss: 0.905852319
step: 6770 | loss: 0.902731717
step: 6780 | loss: 0.899613939
step: 6790 | loss: 0.896499012
step: 6800 | loss: 0.893386965
step: 6810 | loss: 0.890277829
step: 6820 | loss: 0.887171632
step: 6830 | loss: 0.884068405
step: 6840 | loss: 0.880968177
step: 6850 | loss: 0.877870981
step: 6860 | loss: 0.874776846
step: 6870 | loss: 0.871685805
step: 6880 | loss: 0.868597889
step: 6890 | loss: 0.865513130
step: 6900 | loss: 0.862431560
step: 6910 | loss: 0.859353214
step: 6920 | loss: 0.856278124
step: 6930 | loss: 0.853206323
step: 6940 | loss: 0.850137847
step: 6950 | loss: 0.847072729
step: 6960 | loss: 0.844011004
step: 6970 | loss: 0.840952707
step: 6980 | loss: 0.837897875
step: 6990 | loss: 0.834846542
step: 7000 | loss: 0.831798746
step: 7010 | loss: 0.828754523
step: 7020 | loss: 0.825713910
step: 7030 | loss: 0.822676945
step: 7040 | loss: 0.819643665
step: 7050 | loss: 0.816614110
step: 7060 | loss: 0.813588316
step: 7070 | loss: 0.810566325
step: 7080 | loss: 0.807548173
step: 7090 | loss: 0.804533902
step: 7100 | loss: 0.801523552
step: 7110 | loss: 0.798517161
step: 7120 | loss: 0.795514771
step: 7130 | loss: 0.792516423
step: 7140 | loss: 0.789522158
step: 7150 | loss: 0.786532016
step: 7160 | loss: 0.783546039
step: 7170 | loss: 0.780564269
step: 7180 | loss: 0.777586746
step: 7190 | loss: 0.774613512
step: 7200 | loss: 0.771644610
step: 7210 | loss: 0.768680079
step: 7220 | loss: 0.765719961
step: 7230 | loss: 0.762764296
step: 7240 | loss: 0.759813125
step: 7250 | loss: 0.756866487
step: 7260 | loss: 0.753924420
step: 7270 | loss: 0.750986961
step: 7280 | loss: 0.748054146
step: 7290 | loss: 0.745126010
step: 7300 | loss: 0.742202582
step: 7310 | loss: 0.739283892
step: 7320 | loss: 0.736369963
step: 7330 | loss: 0.733460816
step: 7340 | loss: 0.730556462
step: 7350 | loss: 0.727656905
step: 7360 | loss: 0.724762139
step: 7370 | loss: 0.721872141
step: 7380 | loss: 0.718986867
step: 7390 | loss: 0.716106243
step: 7400 | loss: 0.713230151
step: 7410 | loss: 0.710358409
step: 7420 | loss: 0.707490731
step: 7430 | loss: 0.704626669
step: 7440 | loss: 0.701765527
step: 7450 | loss: 0.698906304
step: 7460 | loss: 0.696047898
step: 7470 | loss: 0.693189670
step: 7480 | loss: 0.690331496
step: 7490 | loss: 0.687473374
step: 7500 | loss: 0.684615302
step: 7510 | loss: 0.681757281
step: 7520 | loss: 0.678899313
step: 7530 | loss: 0.676041397
step: 7540 | loss: 0.673183534
step: 7550 | loss: 0.670325726
step: 7560 | loss: 0.667467971
step: 7570 | loss: 0.664610273
step: 7580 | loss: 0.661752630
step: 7590 | loss: 0.658895044
step: 7600 | loss: 0.656037516
step: 7610 | loss: 0.653180046
step: 7620 | loss: 0.650322635
step: 7630 | loss: 0.647465284
step: 7640 | loss: 0.644607994
step: 7650 | loss: 0.641750765
step: 7660 | loss: 0.638893599
step: 7670 | loss: 0.636036495
step: 7680 | loss: 0.633179456
step: 7690 | loss: 0.630322481
step: 7700 | loss: 0.627465572
step: 7710 | loss: 0.624608730
step: 7720 | loss: 0.621751955
step: 7730 | loss: 0.618895249
step: 7740 | loss: 0.616038612
step: 7750 | loss: 0.613182045
step: 7760 | loss: 0.610325550
step: 7770 | loss: 0.607469128
step: 7780 | loss: 0.604612779
step: 7790 | loss: 0.601756504
step: 7800 | loss: 0.598900305
step: 7810 | loss: 0.596044182
step: 7820 | loss: 0.593188138
step: 7830 | loss: 0.590332172
step: 7840 | loss: 0.587476286
step: 7850 | loss: 0.584620481
step: 7860 | loss: 0.581764759
step: 7870 | loss: 0.578909120
step: 7880 | loss: 0.576053566
step: 7890 | loss: 0.573198098
step: 7900 | loss: 0.570342718
step: 7910 | loss: 0.567487426
step: 7920 | loss: 0.564632224
step: 7930 | loss: 0.561777114
step: 7940 | loss: 0.558922097
step: 7950 | loss: 0.556067174
step: 7960 | loss: 0.553212346
step: 7970 | loss: 0.550357616
step: 7980 | loss: 0.547502985
step: 7990 | loss: 0.544648454
step: 8000 | loss: 0.541794024
step: 8010 | loss: 0.538939699
step: 8020 | loss: 0.536085478
step: 8030 | loss: 0.533231364
step: 8040 | loss: 0.530377359
step: 8050 | loss: 0.527523464
step: 8060 | loss: 0.524669681
step: 8070 | loss: 0.521816012
step: 8080 | loss: 0.518962459
step: 8090 | loss: 0.516109024
step: 8100 | loss: 0.513255709
step: 8110 | loss: 0.510402515
step: 8120 | loss: 0.507549445
step: 8130 | loss: 0.504696500
step: 8140 | loss: 0.501843684
step: 8150 | loss: 0.498990998
step: 8160 | loss: 0.496138445
step: 8170 | loss: 0.493286026
step: 8180 | loss: 0.490433744
step: 8190 | loss: 0.487581602
step: 8200 | loss: 0.484729602
step: 8210 | loss: 0.481877746
step: 8220 | loss: 0.479026038
step: 8230 | loss: 0.476174479
step: 8240 | loss: 0.473323072
step: 8250 | loss: 0.470471821
step: 8260 | loss: 0.467620727
step: 8270 | loss: 0.464769795
step: 8280 | loss: 0.461919026
step: 8290 | loss: 0.459068425
step: 8300 | loss: 0.456217993
step: 8310 | loss: 0.453367735
step: 8320 | loss: 0.450517653
step: 8330 | loss: 0.447667752
step: 8340 | loss: 0.444818033
step: 8350 | loss: 0.441968502
step: 8360 | loss: 0.439119161
step: 8370 | loss: 0.436270015
step: 8380 | loss: 0.433421067
step: 8390 | loss: 0.430572320
step: 8400 | loss: 0.427723780
step: 8410 | loss: 0.424875450
step: 8420 | loss: 0.422027335
step: 8430 | loss: 0.419179438
step: 8440 | loss: 0.416331765
step: 8450 | loss: 0.413484320
step: 8460 | loss: 0.410637107
step: 8470 | loss: 0.407790132
step: 8480 | loss: 0.404943400
step: 8490 | loss: 0.402096915
step: 8500 | loss: 0.399250684
step: 8510 | loss: 0.396404710
step: 8520 | loss: 0.393559001
step: 8530 | loss: 0.390713562
step: 8540 | loss: 0.387868398
step: 8550 | loss: 0.385023517
step: 8560 | loss: 0.382178923
step: 8570 | loss: 0.379334624
step: 8580 | loss: 0.376490627
step: 8590 | loss: 0.373646938
step: 8600 | loss: 0.370803563
step: 8610 | loss: 0.367960512
step: 8620 | loss: 0.365117790
step: 8630 | loss: 0.362275407
step: 8640 | loss: 0.359433369
step: 8650 | loss: 0.356591685
step: 8660 | loss: 0.353750364
step: 8670 | loss: 0.350909415
step: 8680 | loss: 0.348068845
step: 8690 | loss: 0.345228666
step: 8700 | loss: 0.342388887
step: 8710 | loss: 0.339549516
step: 8720 | loss: 0.336710566
step: 8730 | loss: 0.333872047
step: 8740 | loss: 0.331033969
step: 8750 | loss: 0.328196344
step: 8760 | loss: 0.325359185
step: 8770 | loss: 0.322522502
step: 8780 | loss: 0.319686310
step: 8790 | loss: 0.316850620
step: 8800 | loss: 0.314015447
step: 8810 | loss: 0.311180805
step: 8820 | loss: 0.308346708
step: 8830 | loss: 0.305513172
step: 8840 | loss: 0.302680212
step: 8850 | loss: 0.299847844
step: 8860 | loss: 0.297016086
step: 8870 | loss: 0.294184955
step: 8880 | loss: 0.291354469
step: 8890 | loss: 0.288524647
step: 8900 | loss: 0.285695509
step: 8910 | loss: 0.282867075
step: 8920 | loss: 0.280039367
step: 8930 | loss: 0.277212407
step: 8940 | loss: 0.274386218
step: 8950 | loss: 0.271560823
step: 8960 | loss: 0.268736249
step: 8970 | loss: 0.265912520
step: 8980 | loss: 0.263089664
step: 8990 | loss: 0.260267710
step: 9000 | loss: 0.257446686
step: 9010 | loss: 0.254626624
step: 9020 | loss: 0.251807557
step: 9030 | loss: 0.248989517
step: 9040 | loss: 0.246172540
step: 9050 | loss: 0.243356662
step: 9060 | loss: 0.240541922
step: 9070 | loss: 0.237728361
step: 9080 | loss: 0.234916021
step: 9090 | loss: 0.232104945
step: 9100 | loss: 0.229295180
step: 9110 | loss: 0.226486775
step: 9120 | loss: 0.223679780
step: 9130 | loss: 0.220874250
step: 9140 | loss: 0.218070240
step: 9150 | loss: 0.215267809
step: 9160 | loss: 0.212467021
step: 9170 | loss: 0.209667939
step: 9180 | loss: 0.206870634
step: 9190 | loss: 0.204075178
step: 9200 | loss: 0.201281647
step: 9210 | loss: 0.198490122
step: 9220 | loss: 0.195700688
step: 9230 | loss: 0.192913436
step: 9240 | loss: 0.190128461
step: 9250 | loss: 0.187345864
step: 9260 | loss: 0.184565752
step: 9270 | loss: 0.181788236
step: 9280 | loss: 0.179013439
step: 9290 | loss: 0.176241486
step: 9300 | loss: 0.173472514
step: 9310 | loss: 0.170706665
step: 9320 | loss: 0.167944092
step: 9330 | loss: 0.165184959
step: 9340 | loss: 0.162429439
step: 9350 | loss: 0.159677716
step: 9360 | loss: 0.156929988
step: 9370 | loss: 0.154186467
step: 9380 | loss: 0.151447377
step: 9390 | loss: 0.148712960
step: 9400 | loss: 0.145983475
step: 9410 | loss: 0.143259199
step: 9420 | loss: 0.140540431
step: 9430 | loss: 0.137827491
step: 9440 | loss: 0.135120723
step: 9450 | loss: 0.132420498
step: 9460 | loss: 0.129727216
step: 9470 | loss: 0.127041310
step: 9480 | loss: 0.124363245
step: 9490 | loss: 0.121693525
step: 9500 | loss: 0.119032698
step: 9510 | loss: 0.116381353
step: 9520 | loss: 0.113740134
step: 9530 | loss: 0.111109736
step: 9540 | loss: 0.108490917
step: 9550 | loss: 0.105884500
step: 9560 | loss: 0.103291381
step: 9570 | loss: 0.100712535
step: 9580 | loss: 0.098149026
step: 9590 | loss: 0.095602011
step: 9600 | loss: 0.093072751
step: 9610 | loss: 0.090562620
step: 9620 | loss: 0.088073111
step: 9630 | loss: 0.085605845
step: 9640 | loss: 0.083162577
step: 9650 | loss: 0.080745199
step: 9660 | loss: 0.078355737
step: 9670 | loss: 0.075996338
step: 9680 | loss: 0.073669249
step: 9690 | loss: 0.071376761
step: 9700 | loss: 0.069121115
step: 9710 | loss: 0.066904339
step: 9720 | loss: 0.064727951
step: 9730 | loss: 0.062592427
step: 9740 | loss: 0.060496261
step: 9750 | loss: 0.058434404
step: 9760 | loss: 0.056396594
step: 9770 | loss: 0.054369230
step: 9780 | loss: 0.052343725
step: 9790 | loss: 0.050318378
step: 9800 | loss: 0.048293071
step: 9810 | loss: 0.046267778
step: 9820 | loss: 0.044242491
step: 9830 | loss: 0.042217205
step: 9840 | loss: 0.040191920
step: 9850 | loss: 0.038166635
step: 9860 | loss: 0.036141350
step: 9870 | loss: 0.034116065
step: 9880 | loss: 0.032090780
step: 9890 | loss: 0.030065495
step: 9900 | loss: 0.028040210
step: 9910 | loss: 0.026014925
step: 9920 | loss: 0.023989640
step: 9930 | loss: 0.021964355
step: 9940 | loss: 0.019939070
step: 9950 | loss: 0.017913785
step: 9960 | loss: 0.015888500
step: 9970 | loss: 0.013863215
step: 9980 | loss: 0.011837931
step: 9990 | loss: 0.009812646
step: 10000 | loss: 0.007787361
step: 10010 | loss: 0.005762076
step: 10020 | loss: 0.003736791
step: 10030 | loss: 0.001711506
- final loss: 0.000901
- (cd _build/default/examples/opt && ./adam.exe)
- 
step: 0 | loss: 1.488656239
step: 10 | loss: 1.486751119
step: 20 | loss: 1.484637609
step: 30 | loss: 1.482527930
step: 40 | loss: 1.480422308
step: 50 | loss: 1.478320842
step: 60 | loss: 1.476223537
step: 70 | loss: 1.474130351
step: 80 | loss: 1.472041216
step: 90 | loss: 1.469956054
step: 100 | loss: 1.467874780
step: 110 | loss: 1.465797310
step: 120 | loss: 1.463723556
step: 130 | loss: 1.461653436
step: 140 | loss: 1.459586866
step: 150 | loss: 1.457523766
step: 160 | loss: 1.455464056
step: 170 | loss: 1.453407662
step: 180 | loss: 1.451354510
step: 190 | loss: 1.449304532
step: 200 | loss: 1.447257662
step: 210 | loss: 1.445213838
step: 220 | loss: 1.443173003
step: 230 | loss: 1.441135104
step: 240 | loss: 1.439100089
step: 250 | loss: 1.437067914
step: 260 | loss: 1.435038537
step: 270 | loss: 1.433011918
step: 280 | loss: 1.430988022
step: 290 | loss: 1.428966819
step: 300 | loss: 1.426948278
step: 310 | loss: 1.424932374
step: 320 | loss: 1.422919082
step: 330 | loss: 1.420908381
step: 340 | loss: 1.418900251
step: 350 | loss: 1.416894673
step: 360 | loss: 1.414891631
step: 370 | loss: 1.412891109
step: 380 | loss: 1.410893092
step: 390 | loss: 1.408897567
step: 400 | loss: 1.406904521
step: 410 | loss: 1.404913940
step: 420 | loss: 1.402925812
step: 430 | loss: 1.400940127
step: 440 | loss: 1.398956871
step: 450 | loss: 1.396976035
step: 460 | loss: 1.394997606
step: 470 | loss: 1.393021573
step: 480 | loss: 1.391047925
step: 490 | loss: 1.389076651
step: 500 | loss: 1.387107741
step: 510 | loss: 1.385141182
step: 520 | loss: 1.383176964
step: 530 | loss: 1.381215076
step: 540 | loss: 1.379255505
step: 550 | loss: 1.377298242
step: 560 | loss: 1.375343274
step: 570 | loss: 1.373390589
step: 580 | loss: 1.371440178
step: 590 | loss: 1.369492027
step: 600 | loss: 1.367546125
step: 610 | loss: 1.365602460
step: 620 | loss: 1.363661021
step: 630 | loss: 1.361721795
step: 640 | loss: 1.359784771
step: 650 | loss: 1.357849936
step: 660 | loss: 1.355917278
step: 670 | loss: 1.353986785
step: 680 | loss: 1.352058445
step: 690 | loss: 1.350132245
step: 700 | loss: 1.348208173
step: 710 | loss: 1.346286216
step: 720 | loss: 1.344366362
step: 730 | loss: 1.342448598
step: 740 | loss: 1.340532911
step: 750 | loss: 1.338619288
step: 760 | loss: 1.336707717
step: 770 | loss: 1.334798184
step: 780 | loss: 1.332890677
step: 790 | loss: 1.330985183
step: 800 | loss: 1.329081688
step: 810 | loss: 1.327180179
step: 820 | loss: 1.325280644
step: 830 | loss: 1.323383068
step: 840 | loss: 1.321487438
step: 850 | loss: 1.319593741
step: 860 | loss: 1.317701964
step: 870 | loss: 1.315812093
step: 880 | loss: 1.313924114
step: 890 | loss: 1.312038015
step: 900 | loss: 1.310153780
step: 910 | loss: 1.308271398
step: 920 | loss: 1.306390853
step: 930 | loss: 1.304512132
step: 940 | loss: 1.302635222
step: 950 | loss: 1.300760108
step: 960 | loss: 1.298886777
step: 970 | loss: 1.297015215
step: 980 | loss: 1.295145409
step: 990 | loss: 1.293277343
step: 1000 | loss: 1.291411005
step: 1010 | loss: 1.289546380
step: 1020 | loss: 1.287683454
step: 1030 | loss: 1.285822213
step: 1040 | loss: 1.283962645
step: 1050 | loss: 1.282104733
step: 1060 | loss: 1.280248465
step: 1070 | loss: 1.278393827
step: 1080 | loss: 1.276540804
step: 1090 | loss: 1.274689383
step: 1100 | loss: 1.272839549
step: 1110 | loss: 1.270991289
step: 1120 | loss: 1.269144589
step: 1130 | loss: 1.267299434
step: 1140 | loss: 1.265455812
step: 1150 | loss: 1.263613707
step: 1160 | loss: 1.261773107
step: 1170 | loss: 1.259933997
step: 1180 | loss: 1.258096363
step: 1190 | loss: 1.256260193
step: 1200 | loss: 1.254425471
step: 1210 | loss: 1.252592185
step: 1220 | loss: 1.250760320
step: 1230 | loss: 1.248929864
step: 1240 | loss: 1.247100802
step: 1250 | loss: 1.245273122
step: 1260 | loss: 1.243446809
step: 1270 | loss: 1.241621850
step: 1280 | loss: 1.239798233
step: 1290 | loss: 1.237975943
step: 1300 | loss: 1.236154968
step: 1310 | loss: 1.234335294
step: 1320 | loss: 1.232516908
step: 1330 | loss: 1.230699798
step: 1340 | loss: 1.228883950
step: 1350 | loss: 1.227069352
step: 1360 | loss: 1.225255991
step: 1370 | loss: 1.223443855
step: 1380 | loss: 1.221632930
step: 1390 | loss: 1.219823204
step: 1400 | loss: 1.218014665
step: 1410 | loss: 1.216207301
step: 1420 | loss: 1.214401099
step: 1430 | loss: 1.212596048
step: 1440 | loss: 1.210792135
step: 1450 | loss: 1.208989348
step: 1460 | loss: 1.207187677
step: 1470 | loss: 1.205387108
step: 1480 | loss: 1.203587631
step: 1490 | loss: 1.201789234
step: 1500 | loss: 1.199991905
step: 1510 | loss: 1.198195635
step: 1520 | loss: 1.196400411
step: 1530 | loss: 1.194606222
step: 1540 | loss: 1.192813058
step: 1550 | loss: 1.191020908
step: 1560 | loss: 1.189229762
step: 1570 | loss: 1.187439608
step: 1580 | loss: 1.185650437
step: 1590 | loss: 1.183862239
step: 1600 | loss: 1.182075003
step: 1610 | loss: 1.180288719
step: 1620 | loss: 1.178503378
step: 1630 | loss: 1.176718970
step: 1640 | loss: 1.174935486
step: 1650 | loss: 1.173152915
step: 1660 | loss: 1.171371249
step: 1670 | loss: 1.169590479
step: 1680 | loss: 1.167810595
step: 1690 | loss: 1.166031590
step: 1700 | loss: 1.164253453
step: 1710 | loss: 1.162476177
step: 1720 | loss: 1.160699753
step: 1730 | loss: 1.158924173
step: 1740 | loss: 1.157149429
step: 1750 | loss: 1.155375513
step: 1760 | loss: 1.153602416
step: 1770 | loss: 1.151830132
step: 1780 | loss: 1.150058652
step: 1790 | loss: 1.148287969
step: 1800 | loss: 1.146518076
step: 1810 | loss: 1.144748966
step: 1820 | loss: 1.142980631
step: 1830 | loss: 1.141213066
step: 1840 | loss: 1.139446262
step: 1850 | loss: 1.137680215
step: 1860 | loss: 1.135914916
step: 1870 | loss: 1.134150360
step: 1880 | loss: 1.132386540
step: 1890 | loss: 1.130623452
step: 1900 | loss: 1.128861087
step: 1910 | loss: 1.127099442
step: 1920 | loss: 1.125338510
step: 1930 | loss: 1.123578286
step: 1940 | loss: 1.121818765
step: 1950 | loss: 1.120059941
step: 1960 | loss: 1.118301809
step: 1970 | loss: 1.116544364
step: 1980 | loss: 1.114787601
step: 1990 | loss: 1.113031517
step: 2000 | loss: 1.111276105
step: 2010 | loss: 1.109521362
step: 2020 | loss: 1.107767284
step: 2030 | loss: 1.106013866
step: 2040 | loss: 1.104261104
step: 2050 | loss: 1.102508994
step: 2060 | loss: 1.100757533
step: 2070 | loss: 1.099006716
step: 2080 | loss: 1.097256541
step: 2090 | loss: 1.095507003
step: 2100 | loss: 1.093758099
step: 2110 | loss: 1.092009827
step: 2120 | loss: 1.090262183
step: 2130 | loss: 1.088515163
step: 2140 | loss: 1.086768766
step: 2150 | loss: 1.085022989
step: 2160 | loss: 1.083277828
step: 2170 | loss: 1.081533281
step: 2180 | loss: 1.079789345
step: 2190 | loss: 1.078046020
step: 2200 | loss: 1.076303301
step: 2210 | loss: 1.074561187
step: 2220 | loss: 1.072819676
step: 2230 | loss: 1.071078767
step: 2240 | loss: 1.069338456
step: 2250 | loss: 1.067598743
step: 2260 | loss: 1.065859625
step: 2270 | loss: 1.064121102
step: 2280 | loss: 1.062383172
step: 2290 | loss: 1.060645833
step: 2300 | loss: 1.058909084
step: 2310 | loss: 1.057172924
step: 2320 | loss: 1.055437352
step: 2330 | loss: 1.053702367
step: 2340 | loss: 1.051967968
step: 2350 | loss: 1.050234153
step: 2360 | loss: 1.048500923
step: 2370 | loss: 1.046768277
step: 2380 | loss: 1.045036213
step: 2390 | loss: 1.043304732
step: 2400 | loss: 1.041573833
step: 2410 | loss: 1.039843516
step: 2420 | loss: 1.038113780
step: 2430 | loss: 1.036384625
step: 2440 | loss: 1.034656050
step: 2450 | loss: 1.032928057
step: 2460 | loss: 1.031200644
step: 2470 | loss: 1.029473812
step: 2480 | loss: 1.027747561
step: 2490 | loss: 1.026021891
step: 2500 | loss: 1.024296802
step: 2510 | loss: 1.022572295
step: 2520 | loss: 1.020848369
step: 2530 | loss: 1.019125026
step: 2540 | loss: 1.017402266
step: 2550 | loss: 1.015680089
step: 2560 | loss: 1.013958495
step: 2570 | loss: 1.012237487
step: 2580 | loss: 1.010517063
step: 2590 | loss: 1.008797225
step: 2600 | loss: 1.007077974
step: 2610 | loss: 1.005359310
step: 2620 | loss: 1.003641234
step: 2630 | loss: 1.001923748
step: 2640 | loss: 1.000206852
step: 2650 | loss: 0.998490547
step: 2660 | loss: 0.996774834
step: 2670 | loss: 0.995059714
step: 2680 | loss: 0.993345189
step: 2690 | loss: 0.991631260
step: 2700 | loss: 0.989917927
step: 2710 | loss: 0.988205193
step: 2720 | loss: 0.986493057
step: 2730 | loss: 0.984781523
step: 2740 | loss: 0.983070590
step: 2750 | loss: 0.981360261
step: 2760 | loss: 0.979650537
step: 2770 | loss: 0.977941418
step: 2780 | loss: 0.976232908
step: 2790 | loss: 0.974525007
step: 2800 | loss: 0.972817717
step: 2810 | loss: 0.971111039
step: 2820 | loss: 0.969404975
step: 2830 | loss: 0.967699526
step: 2840 | loss: 0.965994695
step: 2850 | loss: 0.964290483
step: 2860 | loss: 0.962586891
step: 2870 | loss: 0.960883922
step: 2880 | loss: 0.959181577
step: 2890 | loss: 0.957479857
step: 2900 | loss: 0.955778766
step: 2910 | loss: 0.954078304
step: 2920 | loss: 0.952378473
step: 2930 | loss: 0.950679275
step: 2940 | loss: 0.948980713
step: 2950 | loss: 0.947282787
step: 2960 | loss: 0.945585501
step: 2970 | loss: 0.943888855
step: 2980 | loss: 0.942192852
step: 2990 | loss: 0.940497494
step: 3000 | loss: 0.938802782
step: 3010 | loss: 0.937108720
step: 3020 | loss: 0.935415308
step: 3030 | loss: 0.933722550
step: 3040 | loss: 0.932030446
step: 3050 | loss: 0.930338999
step: 3060 | loss: 0.928648211
step: 3070 | loss: 0.926958085
step: 3080 | loss: 0.925268622
step: 3090 | loss: 0.923579824
step: 3100 | loss: 0.921891695
step: 3110 | loss: 0.920204235
step: 3120 | loss: 0.918517447
step: 3130 | loss: 0.916831333
step: 3140 | loss: 0.915145895
step: 3150 | loss: 0.913461137
step: 3160 | loss: 0.911777059
step: 3170 | loss: 0.910093664
step: 3180 | loss: 0.908410955
step: 3190 | loss: 0.906728933
step: 3200 | loss: 0.905047602
step: 3210 | loss: 0.903366962
step: 3220 | loss: 0.901687017
step: 3230 | loss: 0.900007770
step: 3240 | loss: 0.898329221
step: 3250 | loss: 0.896651374
step: 3260 | loss: 0.894974230
step: 3270 | loss: 0.893297793
step: 3280 | loss: 0.891622065
step: 3290 | loss: 0.889947048
step: 3300 | loss: 0.888272744
step: 3310 | loss: 0.886599156
step: 3320 | loss: 0.884926286
step: 3330 | loss: 0.883254137
step: 3340 | loss: 0.881582712
step: 3350 | loss: 0.879912011
step: 3360 | loss: 0.878242039
step: 3370 | loss: 0.876572798
step: 3380 | loss: 0.874904289
step: 3390 | loss: 0.873236516
step: 3400 | loss: 0.871569481
step: 3410 | loss: 0.869903186
step: 3420 | loss: 0.868237635
step: 3430 | loss: 0.866572829
step: 3440 | loss: 0.864908771
step: 3450 | loss: 0.863245463
step: 3460 | loss: 0.861582909
step: 3470 | loss: 0.859921111
step: 3480 | loss: 0.858260071
step: 3490 | loss: 0.856599792
step: 3500 | loss: 0.854940276
step: 3510 | loss: 0.853281526
step: 3520 | loss: 0.851623546
step: 3530 | loss: 0.849966336
step: 3540 | loss: 0.848309901
step: 3550 | loss: 0.846654242
step: 3560 | loss: 0.844999362
step: 3570 | loss: 0.843345264
step: 3580 | loss: 0.841691951
step: 3590 | loss: 0.840039424
step: 3600 | loss: 0.838387688
step: 3610 | loss: 0.836736744
step: 3620 | loss: 0.835086596
step: 3630 | loss: 0.833437245
step: 3640 | loss: 0.831788696
step: 3650 | loss: 0.830140949
step: 3660 | loss: 0.828494008
step: 3670 | loss: 0.826847877
step: 3680 | loss: 0.825202557
step: 3690 | loss: 0.823558051
step: 3700 | loss: 0.821914362
step: 3710 | loss: 0.820271493
step: 3720 | loss: 0.818629446
step: 3730 | loss: 0.816988225
step: 3740 | loss: 0.815347831
step: 3750 | loss: 0.813708269
step: 3760 | loss: 0.812069540
step: 3770 | loss: 0.810431648
step: 3780 | loss: 0.808794594
step: 3790 | loss: 0.807158383
step: 3800 | loss: 0.805523017
step: 3810 | loss: 0.803888498
step: 3820 | loss: 0.802254830
step: 3830 | loss: 0.800622015
step: 3840 | loss: 0.798990056
step: 3850 | loss: 0.797358956
step: 3860 | loss: 0.795728718
step: 3870 | loss: 0.794099344
step: 3880 | loss: 0.792470838
step: 3890 | loss: 0.790843202
step: 3900 | loss: 0.789216440
step: 3910 | loss: 0.787590553
step: 3920 | loss: 0.785965545
step: 3930 | loss: 0.784341419
step: 3940 | loss: 0.782718178
step: 3950 | loss: 0.781095824
step: 3960 | loss: 0.779474361
step: 3970 | loss: 0.777853791
step: 3980 | loss: 0.776234117
step: 3990 | loss: 0.774615342
step: 4000 | loss: 0.772997469
step: 4010 | loss: 0.771380501
step: 4020 | loss: 0.769764440
step: 4030 | loss: 0.768149290
step: 4040 | loss: 0.766535054
step: 4050 | loss: 0.764921734
step: 4060 | loss: 0.763309333
step: 4070 | loss: 0.761697854
step: 4080 | loss: 0.760087301
step: 4090 | loss: 0.758477675
step: 4100 | loss: 0.756868981
step: 4110 | loss: 0.755261220
step: 4120 | loss: 0.753654396
step: 4130 | loss: 0.752048511
step: 4140 | loss: 0.750443569
step: 4150 | loss: 0.748839572
step: 4160 | loss: 0.747236524
step: 4170 | loss: 0.745634427
step: 4180 | loss: 0.744033283
step: 4190 | loss: 0.742433097
step: 4200 | loss: 0.740833871
step: 4210 | loss: 0.739235607
step: 4220 | loss: 0.737638309
step: 4230 | loss: 0.736041979
step: 4240 | loss: 0.734446621
step: 4250 | loss: 0.732852237
step: 4260 | loss: 0.731258830
step: 4270 | loss: 0.729666403
step: 4280 | loss: 0.728074959
step: 4290 | loss: 0.726484500
step: 4300 | loss: 0.724895030
step: 4310 | loss: 0.723306552
step: 4320 | loss: 0.721719067
step: 4330 | loss: 0.720132580
step: 4340 | loss: 0.718547093
step: 4350 | loss: 0.716962608
step: 4360 | loss: 0.715379129
step: 4370 | loss: 0.713796658
step: 4380 | loss: 0.712215198
step: 4390 | loss: 0.710634752
step: 4400 | loss: 0.709055322
step: 4410 | loss: 0.707476912
step: 4420 | loss: 0.705899525
step: 4430 | loss: 0.704323162
step: 4440 | loss: 0.702747827
step: 4450 | loss: 0.701173522
step: 4460 | loss: 0.699600250
step: 4470 | loss: 0.698028014
step: 4480 | loss: 0.696456817
step: 4490 | loss: 0.694886661
step: 4500 | loss: 0.693317548
step: 4510 | loss: 0.691749482
step: 4520 | loss: 0.690182466
step: 4530 | loss: 0.688616501
step: 4540 | loss: 0.687051590
step: 4550 | loss: 0.685487737
step: 4560 | loss: 0.683924943
step: 4570 | loss: 0.682363211
step: 4580 | loss: 0.680802543
step: 4590 | loss: 0.679242943
step: 4600 | loss: 0.677684413
step: 4610 | loss: 0.676126955
step: 4620 | loss: 0.674570571
step: 4630 | loss: 0.673015265
step: 4640 | loss: 0.671461038
step: 4650 | loss: 0.669907893
step: 4660 | loss: 0.668355832
step: 4670 | loss: 0.666804859
step: 4680 | loss: 0.665254974
step: 4690 | loss: 0.663706181
step: 4700 | loss: 0.662158481
step: 4710 | loss: 0.660611878
step: 4720 | loss: 0.659066373
step: 4730 | loss: 0.657521968
step: 4740 | loss: 0.655978666
step: 4750 | loss: 0.654436469
step: 4760 | loss: 0.652895379
step: 4770 | loss: 0.651355398
step: 4780 | loss: 0.649816529
step: 4790 | loss: 0.648278773
step: 4800 | loss: 0.646742132
step: 4810 | loss: 0.645206609
step: 4820 | loss: 0.643672206
step: 4830 | loss: 0.642138923
step: 4840 | loss: 0.640606764
step: 4850 | loss: 0.639075730
step: 4860 | loss: 0.637545824
step: 4870 | loss: 0.636017046
step: 4880 | loss: 0.634489399
step: 4890 | loss: 0.632962884
step: 4900 | loss: 0.631437503
step: 4910 | loss: 0.629913259
step: 4920 | loss: 0.628390151
step: 4930 | loss: 0.626868183
step: 4940 | loss: 0.625347356
step: 4950 | loss: 0.623827671
step: 4960 | loss: 0.622309129
step: 4970 | loss: 0.620791733
step: 4980 | loss: 0.619275483
step: 4990 | loss: 0.617760381
step: 5000 | loss: 0.616246429
step: 5010 | loss: 0.614733627
step: 5020 | loss: 0.613221976
step: 5030 | loss: 0.611711479
step: 5040 | loss: 0.610202136
step: 5050 | loss: 0.608693948
step: 5060 | loss: 0.607186917
step: 5070 | loss: 0.605681042
step: 5080 | loss: 0.604176326
step: 5090 | loss: 0.602672770
step: 5100 | loss: 0.601170373
step: 5110 | loss: 0.599669137
step: 5120 | loss: 0.598169062
step: 5130 | loss: 0.596670150
step: 5140 | loss: 0.595172401
step: 5150 | loss: 0.593675815
step: 5160 | loss: 0.592180394
step: 5170 | loss: 0.590686137
step: 5180 | loss: 0.589193045
step: 5190 | loss: 0.587701118
step: 5200 | loss: 0.586210357
step: 5210 | loss: 0.584720762
step: 5220 | loss: 0.583232333
step: 5230 | loss: 0.581745070
step: 5240 | loss: 0.580258973
step: 5250 | loss: 0.578774043
step: 5260 | loss: 0.577290279
step: 5270 | loss: 0.575807681
step: 5280 | loss: 0.574326249
step: 5290 | loss: 0.572845982
step: 5300 | loss: 0.571366881
step: 5310 | loss: 0.569888945
step: 5320 | loss: 0.568412173
step: 5330 | loss: 0.566936566
step: 5340 | loss: 0.565462121
step: 5350 | loss: 0.563988840
step: 5360 | loss: 0.562516720
step: 5370 | loss: 0.561045761
step: 5380 | loss: 0.559575963
step: 5390 | loss: 0.558107324
step: 5400 | loss: 0.556639844
step: 5410 | loss: 0.555173520
step: 5420 | loss: 0.553708352
step: 5430 | loss: 0.552244340
step: 5440 | loss: 0.550781480
step: 5450 | loss: 0.549319773
step: 5460 | loss: 0.547859215
step: 5470 | loss: 0.546399807
step: 5480 | loss: 0.544941546
step: 5490 | loss: 0.543484431
step: 5500 | loss: 0.542028459
step: 5510 | loss: 0.540573629
step: 5520 | loss: 0.539119938
step: 5530 | loss: 0.537667385
step: 5540 | loss: 0.536215968
step: 5550 | loss: 0.534765684
step: 5560 | loss: 0.533316531
step: 5570 | loss: 0.531868507
step: 5580 | loss: 0.530421609
step: 5590 | loss: 0.528975834
step: 5600 | loss: 0.527531179
step: 5610 | loss: 0.526087643
step: 5620 | loss: 0.524645222
step: 5630 | loss: 0.523203913
step: 5640 | loss: 0.521763714
step: 5650 | loss: 0.520324620
step: 5660 | loss: 0.518886629
step: 5670 | loss: 0.517449738
step: 5680 | loss: 0.516013943
step: 5690 | loss: 0.514579240
step: 5700 | loss: 0.513145627
step: 5710 | loss: 0.511713098
step: 5720 | loss: 0.510281652
step: 5730 | loss: 0.508851283
step: 5740 | loss: 0.507421988
step: 5750 | loss: 0.505993762
step: 5760 | loss: 0.504566602
step: 5770 | loss: 0.503140504
step: 5780 | loss: 0.501715462
step: 5790 | loss: 0.500291473
step: 5800 | loss: 0.498868532
step: 5810 | loss: 0.497446635
step: 5820 | loss: 0.496025776
step: 5830 | loss: 0.494605951
step: 5840 | loss: 0.493187156
step: 5850 | loss: 0.491769384
step: 5860 | loss: 0.490352631
step: 5870 | loss: 0.488936892
step: 5880 | loss: 0.487522162
step: 5890 | loss: 0.486108435
step: 5900 | loss: 0.484695705
step: 5910 | loss: 0.483283968
step: 5920 | loss: 0.481873217
step: 5930 | loss: 0.480463447
step: 5940 | loss: 0.479054652
step: 5950 | loss: 0.477646827
step: 5960 | loss: 0.476239964
step: 5970 | loss: 0.474834058
step: 5980 | loss: 0.473429104
step: 5990 | loss: 0.472025094
step: 6000 | loss: 0.470622022
step: 6010 | loss: 0.469219882
step: 6020 | loss: 0.467818668
step: 6030 | loss: 0.466418372
step: 6040 | loss: 0.465018988
step: 6050 | loss: 0.463620510
step: 6060 | loss: 0.462222930
step: 6070 | loss: 0.460826242
step: 6080 | loss: 0.459430439
step: 6090 | loss: 0.458035513
step: 6100 | loss: 0.456641458
step: 6110 | loss: 0.455248265
step: 6120 | loss: 0.453855929
step: 6130 | loss: 0.452464442
step: 6140 | loss: 0.451073795
step: 6150 | loss: 0.449683983
step: 6160 | loss: 0.448294996
step: 6170 | loss: 0.446906828
step: 6180 | loss: 0.445519471
step: 6190 | loss: 0.444132918
step: 6200 | loss: 0.442747159
step: 6210 | loss: 0.441362188
step: 6220 | loss: 0.439977997
step: 6230 | loss: 0.438594577
step: 6240 | loss: 0.437211921
step: 6250 | loss: 0.435830021
step: 6260 | loss: 0.434448868
step: 6270 | loss: 0.433068454
step: 6280 | loss: 0.431688772
step: 6290 | loss: 0.430309813
step: 6300 | loss: 0.428931568
step: 6310 | loss: 0.427554030
step: 6320 | loss: 0.426177190
step: 6330 | loss: 0.424801039
step: 6340 | loss: 0.423425570
step: 6350 | loss: 0.422050774
step: 6360 | loss: 0.420676643
step: 6370 | loss: 0.419303168
step: 6380 | loss: 0.417930340
step: 6390 | loss: 0.416558151
step: 6400 | loss: 0.415186594
step: 6410 | loss: 0.413815658
step: 6420 | loss: 0.412445336
step: 6430 | loss: 0.411075619
step: 6440 | loss: 0.409706499
step: 6450 | loss: 0.408337967
step: 6460 | loss: 0.406970015
step: 6470 | loss: 0.405602634
step: 6480 | loss: 0.404235816
step: 6490 | loss: 0.402869552
step: 6500 | loss: 0.401503834
step: 6510 | loss: 0.400138653
step: 6520 | loss: 0.398774002
step: 6530 | loss: 0.397409871
step: 6540 | loss: 0.396046252
step: 6550 | loss: 0.394683137
step: 6560 | loss: 0.393320518
step: 6570 | loss: 0.391958386
step: 6580 | loss: 0.390596733
step: 6590 | loss: 0.389235551
step: 6600 | loss: 0.387874833
step: 6610 | loss: 0.386514569
step: 6620 | loss: 0.385154752
step: 6630 | loss: 0.383795374
step: 6640 | loss: 0.382436426
step: 6650 | loss: 0.381077902
step: 6660 | loss: 0.379719793
step: 6670 | loss: 0.378362091
step: 6680 | loss: 0.377004789
step: 6690 | loss: 0.375647879
step: 6700 | loss: 0.374291354
step: 6710 | loss: 0.372935206
step: 6720 | loss: 0.371579428
step: 6730 | loss: 0.370224013
step: 6740 | loss: 0.368868952
step: 6750 | loss: 0.367514240
step: 6760 | loss: 0.366159869
step: 6770 | loss: 0.364805831
step: 6780 | loss: 0.363452121
step: 6790 | loss: 0.362098731
step: 6800 | loss: 0.360745654
step: 6810 | loss: 0.359392884
step: 6820 | loss: 0.358040415
step: 6830 | loss: 0.356688239
step: 6840 | loss: 0.355336351
step: 6850 | loss: 0.353984744
step: 6860 | loss: 0.352633412
step: 6870 | loss: 0.351282349
step: 6880 | loss: 0.349931549
step: 6890 | loss: 0.348581006
step: 6900 | loss: 0.347230714
step: 6910 | loss: 0.345880668
step: 6920 | loss: 0.344530862
step: 6930 | loss: 0.343181290
step: 6940 | loss: 0.341831948
step: 6950 | loss: 0.340482830
step: 6960 | loss: 0.339133930
step: 6970 | loss: 0.337785245
step: 6980 | loss: 0.336436768
step: 6990 | loss: 0.335088494
step: 7000 | loss: 0.333740420
step: 7010 | loss: 0.332392541
step: 7020 | loss: 0.331044851
step: 7030 | loss: 0.329697347
step: 7040 | loss: 0.328350024
step: 7050 | loss: 0.327002878
step: 7060 | loss: 0.325655905
step: 7070 | loss: 0.324309100
step: 7080 | loss: 0.322962461
step: 7090 | loss: 0.321615982
step: 7100 | loss: 0.320269660
step: 7110 | loss: 0.318923492
step: 7120 | loss: 0.317577474
step: 7130 | loss: 0.316231602
step: 7140 | loss: 0.314885874
step: 7150 | loss: 0.313540285
step: 7160 | loss: 0.312194833
step: 7170 | loss: 0.310849515
step: 7180 | loss: 0.309504327
step: 7190 | loss: 0.308159267
step: 7200 | loss: 0.306814332
step: 7210 | loss: 0.305469518
step: 7220 | loss: 0.304124824
step: 7230 | loss: 0.302780247
step: 7240 | loss: 0.301435784
step: 7250 | loss: 0.300091433
step: 7260 | loss: 0.298747191
step: 7270 | loss: 0.297403056
step: 7280 | loss: 0.296059026
step: 7290 | loss: 0.294715099
step: 7300 | loss: 0.293371273
step: 7310 | loss: 0.292027545
step: 7320 | loss: 0.290683914
step: 7330 | loss: 0.289340378
step: 7340 | loss: 0.287996934
step: 7350 | loss: 0.286653582
step: 7360 | loss: 0.285310319
step: 7370 | loss: 0.283967144
step: 7380 | loss: 0.282624055
step: 7390 | loss: 0.281281051
step: 7400 | loss: 0.279938130
step: 7410 | loss: 0.278595291
step: 7420 | loss: 0.277252532
step: 7430 | loss: 0.275909851
step: 7440 | loss: 0.274567249
step: 7450 | loss: 0.273224722
step: 7460 | loss: 0.271882271
step: 7470 | loss: 0.270539894
step: 7480 | loss: 0.269197589
step: 7490 | loss: 0.267855356
step: 7500 | loss: 0.266513193
step: 7510 | loss: 0.265171100
step: 7520 | loss: 0.263829075
step: 7530 | loss: 0.262487118
step: 7540 | loss: 0.261145227
step: 7550 | loss: 0.259803401
step: 7560 | loss: 0.258461641
step: 7570 | loss: 0.257119944
step: 7580 | loss: 0.255778309
step: 7590 | loss: 0.254436737
step: 7600 | loss: 0.253095227
step: 7610 | loss: 0.251753776
step: 7620 | loss: 0.250412385
step: 7630 | loss: 0.249071054
step: 7640 | loss: 0.247729780
step: 7650 | loss: 0.246388564
step: 7660 | loss: 0.245047405
step: 7670 | loss: 0.243706301
step: 7680 | loss: 0.242365254
step: 7690 | loss: 0.241024261
step: 7700 | loss: 0.239683322
step: 7710 | loss: 0.238342436
step: 7720 | loss: 0.237001604
step: 7730 | loss: 0.235660824
step: 7740 | loss: 0.234320096
step: 7750 | loss: 0.232979419
step: 7760 | loss: 0.231638792
step: 7770 | loss: 0.230298216
step: 7780 | loss: 0.228957689
step: 7790 | loss: 0.227617211
step: 7800 | loss: 0.226276782
step: 7810 | loss: 0.224936400
step: 7820 | loss: 0.223596066
step: 7830 | loss: 0.222255779
step: 7840 | loss: 0.220915538
step: 7850 | loss: 0.219575343
step: 7860 | loss: 0.218235194
step: 7870 | loss: 0.216895090
step: 7880 | loss: 0.215555030
step: 7890 | loss: 0.214215014
step: 7900 | loss: 0.212875042
step: 7910 | loss: 0.211535113
step: 7920 | loss: 0.210195227
step: 7930 | loss: 0.208855383
step: 7940 | loss: 0.207515581
step: 7950 | loss: 0.206175820
step: 7960 | loss: 0.204836101
step: 7970 | loss: 0.203496422
step: 7980 | loss: 0.202156783
step: 7990 | loss: 0.200817184
step: 8000 | loss: 0.199477624
step: 8010 | loss: 0.198138103
step: 8020 | loss: 0.196798621
step: 8030 | loss: 0.195459177
step: 8040 | loss: 0.194119771
step: 8050 | loss: 0.192780402
step: 8060 | loss: 0.191441071
step: 8070 | loss: 0.190101776
step: 8080 | loss: 0.188762517
step: 8090 | loss: 0.187423294
step: 8100 | loss: 0.186084107
step: 8110 | loss: 0.184744955
step: 8120 | loss: 0.183405838
step: 8130 | loss: 0.182066755
step: 8140 | loss: 0.180727707
step: 8150 | loss: 0.179388692
step: 8160 | loss: 0.178049711
step: 8170 | loss: 0.176710763
step: 8180 | loss: 0.175371848
step: 8190 | loss: 0.174032965
step: 8200 | loss: 0.172694115
step: 8210 | loss: 0.171355296
step: 8220 | loss: 0.170016509
step: 8230 | loss: 0.168677753
step: 8240 | loss: 0.167339028
step: 8250 | loss: 0.166000333
step: 8260 | loss: 0.164661669
step: 8270 | loss: 0.163323035
step: 8280 | loss: 0.161984430
step: 8290 | loss: 0.160645855
step: 8300 | loss: 0.159307309
step: 8310 | loss: 0.157968792
step: 8320 | loss: 0.156630303
step: 8330 | loss: 0.155291842
step: 8340 | loss: 0.153953409
step: 8350 | loss: 0.152615004
step: 8360 | loss: 0.151276627
step: 8370 | loss: 0.149938276
step: 8380 | loss: 0.148599952
step: 8390 | loss: 0.147261655
step: 8400 | loss: 0.145923384
step: 8410 | loss: 0.144585139
step: 8420 | loss: 0.143246920
step: 8430 | loss: 0.141908726
step: 8440 | loss: 0.140570558
step: 8450 | loss: 0.139232415
step: 8460 | loss: 0.137894296
step: 8470 | loss: 0.136556202
step: 8480 | loss: 0.135218132
step: 8490 | loss: 0.133880086
step: 8500 | loss: 0.132542064
step: 8510 | loss: 0.131204066
step: 8520 | loss: 0.129866090
step: 8530 | loss: 0.128528138
step: 8540 | loss: 0.127190209
step: 8550 | loss: 0.125852302
step: 8560 | loss: 0.124514418
step: 8570 | loss: 0.123176556
step: 8580 | loss: 0.121838715
step: 8590 | loss: 0.120500897
step: 8600 | loss: 0.119163100
step: 8610 | loss: 0.117825324
step: 8620 | loss: 0.116487569
step: 8630 | loss: 0.115149835
step: 8640 | loss: 0.113812122
step: 8650 | loss: 0.112474429
step: 8660 | loss: 0.111136757
step: 8670 | loss: 0.109799105
step: 8680 | loss: 0.108461472
step: 8690 | loss: 0.107123859
step: 8700 | loss: 0.105786265
step: 8710 | loss: 0.104448691
step: 8720 | loss: 0.103111136
step: 8730 | loss: 0.101773599
step: 8740 | loss: 0.100436082
step: 8750 | loss: 0.099098582
step: 8760 | loss: 0.097761102
step: 8770 | loss: 0.096423639
step: 8780 | loss: 0.095086194
step: 8790 | loss: 0.093748767
step: 8800 | loss: 0.092411357
step: 8810 | loss: 0.091073965
step: 8820 | loss: 0.089736590
step: 8830 | loss: 0.088399232
step: 8840 | loss: 0.087061892
step: 8850 | loss: 0.085724567
step: 8860 | loss: 0.084387260
step: 8870 | loss: 0.083049968
step: 8880 | loss: 0.081712693
step: 8890 | loss: 0.080375434
step: 8900 | loss: 0.079038191
step: 8910 | loss: 0.077700964
step: 8920 | loss: 0.076363752
step: 8930 | loss: 0.075026556
step: 8940 | loss: 0.073689375
step: 8950 | loss: 0.072352209
step: 8960 | loss: 0.071015058
step: 8970 | loss: 0.069677922
step: 8980 | loss: 0.068340801
step: 8990 | loss: 0.067003694
step: 9000 | loss: 0.065666601
step: 9010 | loss: 0.064329523
step: 9020 | loss: 0.062992459
step: 9030 | loss: 0.061655408
step: 9040 | loss: 0.060318372
step: 9050 | loss: 0.058981349
step: 9060 | loss: 0.057644340
step: 9070 | loss: 0.056307344
step: 9080 | loss: 0.054970387
step: 9090 | loss: 0.053633395
step: 9100 | loss: 0.052296444
step: 9110 | loss: 0.050959494
step: 9120 | loss: 0.049622563
step: 9130 | loss: 0.048285645
step: 9140 | loss: 0.046948739
step: 9150 | loss: 0.045611846
step: 9160 | loss: 0.044274965
step: 9170 | loss: 0.042938096
step: 9180 | loss: 0.041601239
step: 9190 | loss: 0.040264394
step: 9200 | loss: 0.038927561
step: 9210 | loss: 0.037590739
step: 9220 | loss: 0.036253929
step: 9230 | loss: 0.034917130
step: 9240 | loss: 0.033580343
step: 9250 | loss: 0.032243567
step: 9260 | loss: 0.030906802
step: 9270 | loss: 0.029570048
step: 9280 | loss: 0.028233305
step: 9290 | loss: 0.026896650
step: 9300 | loss: 0.025559863
step: 9310 | loss: 0.024223149
step: 9320 | loss: 0.022886443
step: 9330 | loss: 0.021549750
step: 9340 | loss: 0.020213070
step: 9350 | loss: 0.018876400
step: 9360 | loss: 0.017539739
step: 9370 | loss: 0.016203089
step: 9380 | loss: 0.014866485
step: 9390 | loss: 0.013529844
step: 9400 | loss: 0.012193206
step: 9410 | loss: 0.010856599
step: 9420 | loss: 0.009519995
step: 9430 | loss: 0.008183482
step: 9440 | loss: 0.006846847
step: 9450 | loss: 0.005510277
step: 9460 | loss: 0.004173705
step: 9470 | loss: 0.002837478
step: 9480 | loss: 0.001501304
- final loss: 0.000966
- (cd _build/default/examples/opt && ./gd.exe)
- 
iter: 0 | loss: 4.835298
iter: 1 | loss: 4.835298
iter: 2 | loss: 4.835104
iter: 3 | loss: 4.834911
iter: 4 | loss: 4.834717
iter: 5 | loss: 4.834524
iter: 6 | loss: 4.834331
iter: 7 | loss: 4.834137
iter: 8 | loss: 4.833944
iter: 9 | loss: 4.833750
iter: 10 | loss: 4.833557
iter: 11 | loss: 4.833364
iter: 12 | loss: 4.833170
iter: 13 | loss: 4.832977
iter: 14 | loss: 4.832784
iter: 15 | loss: 4.832590
iter: 16 | loss: 4.832397
iter: 17 | loss: 4.832203
iter: 18 | loss: 4.832010
iter: 19 | loss: 4.831817
iter: 20 | loss: 4.831623
iter: 21 | loss: 4.831430
iter: 22 | loss: 4.831236
iter: 23 | loss: 4.831043
iter: 24 | loss: 4.830850
iter: 25 | loss: 4.830656
iter: 26 | loss: 4.830463
iter: 27 | loss: 4.830270
iter: 28 | loss: 4.830076
iter: 29 | loss: 4.829883
iter: 30 | loss: 4.829689
iter: 31 | loss: 4.829496
iter: 32 | loss: 4.829303
iter: 33 | loss: 4.829109
iter: 34 | loss: 4.828916
iter: 35 | loss: 4.828722
iter: 36 | loss: 4.828529
iter: 37 | loss: 4.828336
iter: 38 | loss: 4.828142
iter: 39 | loss: 4.827949
iter: 40 | loss: 4.827755
iter: 41 | loss: 4.827562
iter: 42 | loss: 4.827369
iter: 43 | loss: 4.827175
iter: 44 | loss: 4.826982
iter: 45 | loss: 4.826789
iter: 46 | loss: 4.826595
iter: 47 | loss: 4.826402
iter: 48 | loss: 4.826208
iter: 49 | loss: 4.826015
iter: 50 | loss: 4.825822
iter: 51 | loss: 4.825628
iter: 52 | loss: 4.825435
iter: 53 | loss: 4.825241
iter: 54 | loss: 4.825048
iter: 55 | loss: 4.824855
iter: 56 | loss: 4.824661
iter: 57 | loss: 4.824468
iter: 58 | loss: 4.824275
iter: 59 | loss: 4.824081
iter: 60 | loss: 4.823888
iter: 61 | loss: 4.823694
iter: 62 | loss: 4.823501
iter: 63 | loss: 4.823308
iter: 64 | loss: 4.823114
iter: 65 | loss: 4.822921
iter: 66 | loss: 4.822727
iter: 67 | loss: 4.822534
iter: 68 | loss: 4.822341
iter: 69 | loss: 4.822147
iter: 70 | loss: 4.821954
iter: 71 | loss: 4.821761
iter: 72 | loss: 4.821567
iter: 73 | loss: 4.821374
iter: 74 | loss: 4.821180
iter: 75 | loss: 4.820987
iter: 76 | loss: 4.820794
iter: 77 | loss: 4.820600
iter: 78 | loss: 4.820407
iter: 79 | loss: 4.820213
iter: 80 | loss: 4.820020
iter: 81 | loss: 4.819827
iter: 82 | loss: 4.819633
iter: 83 | loss: 4.819440
iter: 84 | loss: 4.819246
iter: 85 | loss: 4.819053
iter: 86 | loss: 4.818860
iter: 87 | loss: 4.818666
iter: 88 | loss: 4.818473
iter: 89 | loss: 4.818280
iter: 90 | loss: 4.818086
iter: 91 | loss: 4.817893
iter: 92 | loss: 4.817699
iter: 93 | loss: 4.817506
iter: 94 | loss: 4.817313
iter: 95 | loss: 4.817119
iter: 96 | loss: 4.816926
iter: 97 | loss: 4.816732
iter: 98 | loss: 4.816539
iter: 99 | loss: 4.816346
iter: 100 | loss: 4.816152
iter: 101 | loss: 4.815959
iter: 102 | loss: 4.815766
iter: 103 | loss: 4.815572
iter: 104 | loss: 4.815379
iter: 105 | loss: 4.815185
iter: 106 | loss: 4.814992
iter: 107 | loss: 4.814799
iter: 108 | loss: 4.814605
iter: 109 | loss: 4.814412
iter: 110 | loss: 4.814218
iter: 111 | loss: 4.814025
iter: 112 | loss: 4.813832
iter: 113 | loss: 4.813638
iter: 114 | loss: 4.813445
iter: 115 | loss: 4.813251
iter: 116 | loss: 4.813058
iter: 117 | loss: 4.812865
iter: 118 | loss: 4.812671
iter: 119 | loss: 4.812478
iter: 120 | loss: 4.812285
iter: 121 | loss: 4.812091
iter: 122 | loss: 4.811898
iter: 123 | loss: 4.811704
iter: 124 | loss: 4.811511
iter: 125 | loss: 4.811318
iter: 126 | loss: 4.811124
iter: 127 | loss: 4.810931
iter: 128 | loss: 4.810737
iter: 129 | loss: 4.810544
iter: 130 | loss: 4.810351
iter: 131 | loss: 4.810157
iter: 132 | loss: 4.809964
iter: 133 | loss: 4.809771
iter: 134 | loss: 4.809577
iter: 135 | loss: 4.809384
iter: 136 | loss: 4.809190
iter: 137 | loss: 4.808997
iter: 138 | loss: 4.808804
iter: 139 | loss: 4.808610
iter: 140 | loss: 4.808417
iter: 141 | loss: 4.808223
iter: 142 | loss: 4.808030
iter: 143 | loss: 4.807837
iter: 144 | loss: 4.807643
iter: 145 | loss: 4.807450
iter: 146 | loss: 4.807256
iter: 147 | loss: 4.807063
iter: 148 | loss: 4.806870
iter: 149 | loss: 4.806676
iter: 150 | loss: 4.806483
iter: 151 | loss: 4.806290
iter: 152 | loss: 4.806096
iter: 153 | loss: 4.805903
iter: 154 | loss: 4.805709
iter: 155 | loss: 4.805516
iter: 156 | loss: 4.805323
iter: 157 | loss: 4.805129
iter: 158 | loss: 4.804936
iter: 159 | loss: 4.804742
iter: 160 | loss: 4.804549
iter: 161 | loss: 4.804356
iter: 162 | loss: 4.804162
iter: 163 | loss: 4.803969
iter: 164 | loss: 4.803776
iter: 165 | loss: 4.803582
iter: 166 | loss: 4.803389
iter: 167 | loss: 4.803195
iter: 168 | loss: 4.803002
iter: 169 | loss: 4.802809
iter: 170 | loss: 4.802615
iter: 171 | loss: 4.802422
iter: 172 | loss: 4.802228
iter: 173 | loss: 4.802035
iter: 174 | loss: 4.801842
iter: 175 | loss: 4.801648
iter: 176 | loss: 4.801455
iter: 177 | loss: 4.801261
iter: 178 | loss: 4.801068
iter: 179 | loss: 4.800875
iter: 180 | loss: 4.800681
iter: 181 | loss: 4.800488
iter: 182 | loss: 4.800295
iter: 183 | loss: 4.800101
iter: 184 | loss: 4.799908
iter: 185 | loss: 4.799714
iter: 186 | loss: 4.799521
iter: 187 | loss: 4.799328
iter: 188 | loss: 4.799134
iter: 189 | loss: 4.798941
iter: 190 | loss: 4.798747
iter: 191 | loss: 4.798554
iter: 192 | loss: 4.798361
iter: 193 | loss: 4.798167
iter: 194 | loss: 4.797974
iter: 195 | loss: 4.797781
iter: 196 | loss: 4.797587
iter: 197 | loss: 4.797394
iter: 198 | loss: 4.797200
iter: 199 | loss: 4.797007
iter: 200 | loss: 4.796814
iter: 201 | loss: 4.796620
iter: 202 | loss: 4.796427
iter: 203 | loss: 4.796233
iter: 204 | loss: 4.796040
iter: 205 | loss: 4.795847
iter: 206 | loss: 4.795653
iter: 207 | loss: 4.795460
iter: 208 | loss: 4.795266
iter: 209 | loss: 4.795073
iter: 210 | loss: 4.794880
iter: 211 | loss: 4.794686
iter: 212 | loss: 4.794493
iter: 213 | loss: 4.794300
iter: 214 | loss: 4.794106
iter: 215 | loss: 4.793913
iter: 216 | loss: 4.793719
iter: 217 | loss: 4.793526
iter: 218 | loss: 4.793333
iter: 219 | loss: 4.793139
iter: 220 | loss: 4.792946
iter: 221 | loss: 4.792752
iter: 222 | loss: 4.792559
iter: 223 | loss: 4.792366
iter: 224 | loss: 4.792172
iter: 225 | loss: 4.791979
iter: 226 | loss: 4.791786
iter: 227 | loss: 4.791592
iter: 228 | loss: 4.791399
iter: 229 | loss: 4.791205
iter: 230 | loss: 4.791012
iter: 231 | loss: 4.790819
iter: 232 | loss: 4.790625
iter: 233 | loss: 4.790432
iter: 234 | loss: 4.790238
iter: 235 | loss: 4.790045
iter: 236 | loss: 4.789852
iter: 237 | loss: 4.789658
iter: 238 | loss: 4.789465
iter: 239 | loss: 4.789271
iter: 240 | loss: 4.789078
iter: 241 | loss: 4.788885
iter: 242 | loss: 4.788691
iter: 243 | loss: 4.788498
iter: 244 | loss: 4.788305
iter: 245 | loss: 4.788111
iter: 246 | loss: 4.787918
iter: 247 | loss: 4.787724
iter: 248 | loss: 4.787531
iter: 249 | loss: 4.787338
iter: 250 | loss: 4.787144
iter: 251 | loss: 4.786951
iter: 252 | loss: 4.786757
iter: 253 | loss: 4.786564
iter: 254 | loss: 4.786371
iter: 255 | loss: 4.786177
iter: 256 | loss: 4.785984
iter: 257 | loss: 4.785791
iter: 258 | loss: 4.785597
iter: 259 | loss: 4.785404
iter: 260 | loss: 4.785210
iter: 261 | loss: 4.785017
iter: 262 | loss: 4.784824
iter: 263 | loss: 4.784630
iter: 264 | loss: 4.784437
iter: 265 | loss: 4.784243
iter: 266 | loss: 4.784050
iter: 267 | loss: 4.783857
iter: 268 | loss: 4.783663
iter: 269 | loss: 4.783470
iter: 270 | loss: 4.783276
iter: 271 | loss: 4.783083
iter: 272 | loss: 4.782890
iter: 273 | loss: 4.782696
iter: 274 | loss: 4.782503
iter: 275 | loss: 4.782310
iter: 276 | loss: 4.782116
iter: 277 | loss: 4.781923
iter: 278 | loss: 4.781729
iter: 279 | loss: 4.781536
iter: 280 | loss: 4.781343
iter: 281 | loss: 4.781149
iter: 282 | loss: 4.780956
iter: 283 | loss: 4.780762
iter: 284 | loss: 4.780569
iter: 285 | loss: 4.780376
iter: 286 | loss: 4.780182
iter: 287 | loss: 4.779989
iter: 288 | loss: 4.779796
iter: 289 | loss: 4.779602
iter: 290 | loss: 4.779409
iter: 291 | loss: 4.779215
iter: 292 | loss: 4.779022
iter: 293 | loss: 4.778829
iter: 294 | loss: 4.778635
iter: 295 | loss: 4.778442
iter: 296 | loss: 4.778248
iter: 297 | loss: 4.778055
iter: 298 | loss: 4.777862
iter: 299 | loss: 4.777668
iter: 300 | loss: 4.777475
iter: 301 | loss: 4.777281
iter: 302 | loss: 4.777088
iter: 303 | loss: 4.776895
iter: 304 | loss: 4.776701
iter: 305 | loss: 4.776508
iter: 306 | loss: 4.776315
iter: 307 | loss: 4.776121
iter: 308 | loss: 4.775928
iter: 309 | loss: 4.775734
iter: 310 | loss: 4.775541
iter: 311 | loss: 4.775348
iter: 312 | loss: 4.775154
iter: 313 | loss: 4.774961
iter: 314 | loss: 4.774767
iter: 315 | loss: 4.774574
iter: 316 | loss: 4.774381
iter: 317 | loss: 4.774187
iter: 318 | loss: 4.773994
iter: 319 | loss: 4.773801
iter: 320 | loss: 4.773607
iter: 321 | loss: 4.773414
iter: 322 | loss: 4.773220
iter: 323 | loss: 4.773027
iter: 324 | loss: 4.772834
iter: 325 | loss: 4.772640
iter: 326 | loss: 4.772447
iter: 327 | loss: 4.772253
iter: 328 | loss: 4.772060
iter: 329 | loss: 4.771867
iter: 330 | loss: 4.771673
iter: 331 | loss: 4.771480
iter: 332 | loss: 4.771286
iter: 333 | loss: 4.771093
iter: 334 | loss: 4.770900
iter: 335 | loss: 4.770706
iter: 336 | loss: 4.770513
iter: 337 | loss: 4.770320
iter: 338 | loss: 4.770126
iter: 339 | loss: 4.769933
iter: 340 | loss: 4.769739
iter: 341 | loss: 4.769546
iter: 342 | loss: 4.769353
iter: 343 | loss: 4.769159
iter: 344 | loss: 4.768966
iter: 345 | loss: 4.768772
iter: 346 | loss: 4.768579
iter: 347 | loss: 4.768386
iter: 348 | loss: 4.768192
iter: 349 | loss: 4.767999
iter: 350 | loss: 4.767806
iter: 351 | loss: 4.767612
iter: 352 | loss: 4.767419
iter: 353 | loss: 4.767225
iter: 354 | loss: 4.767032
iter: 355 | loss: 4.766839
iter: 356 | loss: 4.766645
iter: 357 | loss: 4.766452
iter: 358 | loss: 4.766258
iter: 359 | loss: 4.766065
iter: 360 | loss: 4.765872
iter: 361 | loss: 4.765678
iter: 362 | loss: 4.765485
iter: 363 | loss: 4.765291
iter: 364 | loss: 4.765098
iter: 365 | loss: 4.764905
iter: 366 | loss: 4.764711
iter: 367 | loss: 4.764518
iter: 368 | loss: 4.764325
iter: 369 | loss: 4.764131
iter: 370 | loss: 4.763938
iter: 371 | loss: 4.763744
iter: 372 | loss: 4.763551
iter: 373 | loss: 4.763358
iter: 374 | loss: 4.763164
iter: 375 | loss: 4.762971
iter: 376 | loss: 4.762777
iter: 377 | loss: 4.762584
iter: 378 | loss: 4.762391
iter: 379 | loss: 4.762197
iter: 380 | loss: 4.762004
iter: 381 | loss: 4.761811
iter: 382 | loss: 4.761617
iter: 383 | loss: 4.761424
iter: 384 | loss: 4.761230
iter: 385 | loss: 4.761037
iter: 386 | loss: 4.760844
iter: 387 | loss: 4.760650
iter: 388 | loss: 4.760457
iter: 389 | loss: 4.760263
iter: 390 | loss: 4.760070
iter: 391 | loss: 4.759877
iter: 392 | loss: 4.759683
iter: 393 | loss: 4.759490
iter: 394 | loss: 4.759297
iter: 395 | loss: 4.759103
iter: 396 | loss: 4.758910
iter: 397 | loss: 4.758716
iter: 398 | loss: 4.758523
iter: 399 | loss: 4.758330
iter: 400 | loss: 4.758136
iter: 401 | loss: 4.757943
iter: 402 | loss: 4.757749
iter: 403 | loss: 4.757556
iter: 404 | loss: 4.757363
iter: 405 | loss: 4.757169
iter: 406 | loss: 4.756976
iter: 407 | loss: 4.756782
iter: 408 | loss: 4.756589
iter: 409 | loss: 4.756396
iter: 410 | loss: 4.756202
iter: 411 | loss: 4.756009
iter: 412 | loss: 4.755816
iter: 413 | loss: 4.755622
iter: 414 | loss: 4.755429
iter: 415 | loss: 4.755235
iter: 416 | loss: 4.755042
iter: 417 | loss: 4.754849
iter: 418 | loss: 4.754655
iter: 419 | loss: 4.754462
iter: 420 | loss: 4.754268
iter: 421 | loss: 4.754075
iter: 422 | loss: 4.753882
iter: 423 | loss: 4.753688
iter: 424 | loss: 4.753495
iter: 425 | loss: 4.753302
iter: 426 | loss: 4.753108
iter: 427 | loss: 4.752915
iter: 428 | loss: 4.752721
iter: 429 | loss: 4.752528
iter: 430 | loss: 4.752335
iter: 431 | loss: 4.752141
iter: 432 | loss: 4.751948
iter: 433 | loss: 4.751754
iter: 434 | loss: 4.751561
iter: 435 | loss: 4.751368
iter: 436 | loss: 4.751174
iter: 437 | loss: 4.750981
iter: 438 | loss: 4.750787
iter: 439 | loss: 4.750594
iter: 440 | loss: 4.750401
iter: 441 | loss: 4.750207
iter: 442 | loss: 4.750014
iter: 443 | loss: 4.749821
iter: 444 | loss: 4.749627
iter: 445 | loss: 4.749434
iter: 446 | loss: 4.749240
iter: 447 | loss: 4.749047
iter: 448 | loss: 4.748854
iter: 449 | loss: 4.748660
iter: 450 | loss: 4.748467
iter: 451 | loss: 4.748273
iter: 452 | loss: 4.748080
iter: 453 | loss: 4.747887
iter: 454 | loss: 4.747693
iter: 455 | loss: 4.747500
iter: 456 | loss: 4.747307
iter: 457 | loss: 4.747113
iter: 458 | loss: 4.746920
iter: 459 | loss: 4.746726
iter: 460 | loss: 4.746533
iter: 461 | loss: 4.746340
iter: 462 | loss: 4.746146
iter: 463 | loss: 4.745953
iter: 464 | loss: 4.745759
iter: 465 | loss: 4.745566
iter: 466 | loss: 4.745373
iter: 467 | loss: 4.745179
iter: 468 | loss: 4.744986
iter: 469 | loss: 4.744792
iter: 470 | loss: 4.744599
iter: 471 | loss: 4.744406
iter: 472 | loss: 4.744212
iter: 473 | loss: 4.744019
iter: 474 | loss: 4.743826
iter: 475 | loss: 4.743632
iter: 476 | loss: 4.743439
iter: 477 | loss: 4.743245
iter: 478 | loss: 4.743052
iter: 479 | loss: 4.742859
iter: 480 | loss: 4.742665
iter: 481 | loss: 4.742472
iter: 482 | loss: 4.742278
iter: 483 | loss: 4.742085
iter: 484 | loss: 4.741892
iter: 485 | loss: 4.741698
iter: 486 | loss: 4.741505
iter: 487 | loss: 4.741312
iter: 488 | loss: 4.741118
iter: 489 | loss: 4.740925
iter: 490 | loss: 4.740731
iter: 491 | loss: 4.740538
iter: 492 | loss: 4.740345
iter: 493 | loss: 4.740151
iter: 494 | loss: 4.739958
iter: 495 | loss: 4.739764
iter: 496 | loss: 4.739571
iter: 497 | loss: 4.739378
iter: 498 | loss: 4.739184
iter: 499 | loss: 4.738991
iter: 500 | loss: 4.738797
iter: 501 | loss: 4.738604
iter: 502 | loss: 4.738411
iter: 503 | loss: 4.738217
iter: 504 | loss: 4.738024
iter: 505 | loss: 4.737831
iter: 506 | loss: 4.737637
iter: 507 | loss: 4.737444
iter: 508 | loss: 4.737250
iter: 509 | loss: 4.737057
iter: 510 | loss: 4.736864
iter: 511 | loss: 4.736670
iter: 512 | loss: 4.736477
iter: 513 | loss: 4.736283
iter: 514 | loss: 4.736090
iter: 515 | loss: 4.735897
iter: 516 | loss: 4.735703
iter: 517 | loss: 4.735510
iter: 518 | loss: 4.735317
iter: 519 | loss: 4.735123
iter: 520 | loss: 4.734930
iter: 521 | loss: 4.734736
iter: 522 | loss: 4.734543
iter: 523 | loss: 4.734350
iter: 524 | loss: 4.734156
iter: 525 | loss: 4.733963
iter: 526 | loss: 4.733769
iter: 527 | loss: 4.733576
iter: 528 | loss: 4.733383
iter: 529 | loss: 4.733189
iter: 530 | loss: 4.732996
iter: 531 | loss: 4.732802
iter: 532 | loss: 4.732609
iter: 533 | loss: 4.732416
iter: 534 | loss: 4.732222
iter: 535 | loss: 4.732029
iter: 536 | loss: 4.731836
iter: 537 | loss: 4.731642
iter: 538 | loss: 4.731449
iter: 539 | loss: 4.731255
iter: 540 | loss: 4.731062
iter: 541 | loss: 4.730869
iter: 542 | loss: 4.730675
iter: 543 | loss: 4.730482
iter: 544 | loss: 4.730288
iter: 545 | loss: 4.730095
iter: 546 | loss: 4.729902
iter: 547 | loss: 4.729708
iter: 548 | loss: 4.729515
iter: 549 | loss: 4.729322
iter: 550 | loss: 4.729128
iter: 551 | loss: 4.728935
iter: 552 | loss: 4.728741
iter: 553 | loss: 4.728548
iter: 554 | loss: 4.728355
iter: 555 | loss: 4.728161
iter: 556 | loss: 4.727968
iter: 557 | loss: 4.727774
iter: 558 | loss: 4.727581
iter: 559 | loss: 4.727388
iter: 560 | loss: 4.727194
iter: 561 | loss: 4.727001
iter: 562 | loss: 4.726807
iter: 563 | loss: 4.726614
iter: 564 | loss: 4.726421
iter: 565 | loss: 4.726227
iter: 566 | loss: 4.726034
iter: 567 | loss: 4.725841
iter: 568 | loss: 4.725647
iter: 569 | loss: 4.725454
iter: 570 | loss: 4.725260
iter: 571 | loss: 4.725067
iter: 572 | loss: 4.724874
iter: 573 | loss: 4.724680
iter: 574 | loss: 4.724487
iter: 575 | loss: 4.724293
iter: 576 | loss: 4.724100
iter: 577 | loss: 4.723907
iter: 578 | loss: 4.723713
iter: 579 | loss: 4.723520
iter: 580 | loss: 4.723327
iter: 581 | loss: 4.723133
iter: 582 | loss: 4.722940
iter: 583 | loss: 4.722746
iter: 584 | loss: 4.722553
iter: 585 | loss: 4.722360
iter: 586 | loss: 4.722166
iter: 587 | loss: 4.721973
iter: 588 | loss: 4.721779
iter: 589 | loss: 4.721586
iter: 590 | loss: 4.721393
iter: 591 | loss: 4.721199
iter: 592 | loss: 4.721006
iter: 593 | loss: 4.720812
iter: 594 | loss: 4.720619
iter: 595 | loss: 4.720426
iter: 596 | loss: 4.720232
iter: 597 | loss: 4.720039
iter: 598 | loss: 4.719846
iter: 599 | loss: 4.719652
iter: 600 | loss: 4.719459
iter: 601 | loss: 4.719265
iter: 602 | loss: 4.719072
iter: 603 | loss: 4.718879
iter: 604 | loss: 4.718685
iter: 605 | loss: 4.718492
iter: 606 | loss: 4.718298
iter: 607 | loss: 4.718105
iter: 608 | loss: 4.717912
iter: 609 | loss: 4.717718
iter: 610 | loss: 4.717525
iter: 611 | loss: 4.717332
iter: 612 | loss: 4.717138
iter: 613 | loss: 4.716945
iter: 614 | loss: 4.716751
iter: 615 | loss: 4.716558
iter: 616 | loss: 4.716365
iter: 617 | loss: 4.716171
iter: 618 | loss: 4.715978
iter: 619 | loss: 4.715784
iter: 620 | loss: 4.715591
iter: 621 | loss: 4.715398
iter: 622 | loss: 4.715204
iter: 623 | loss: 4.715011
iter: 624 | loss: 4.714817
iter: 625 | loss: 4.714624
iter: 626 | loss: 4.714431
iter: 627 | loss: 4.714237
iter: 628 | loss: 4.714044
iter: 629 | loss: 4.713851
iter: 630 | loss: 4.713657
iter: 631 | loss: 4.713464
iter: 632 | loss: 4.713270
iter: 633 | loss: 4.713077
iter: 634 | loss: 4.712884
iter: 635 | loss: 4.712690
iter: 636 | loss: 4.712497
iter: 637 | loss: 4.712303
iter: 638 | loss: 4.712110
iter: 639 | loss: 4.711917
iter: 640 | loss: 4.711723
iter: 641 | loss: 4.711530
iter: 642 | loss: 4.711337
iter: 643 | loss: 4.711143
iter: 644 | loss: 4.710950
iter: 645 | loss: 4.710756
iter: 646 | loss: 4.710563
iter: 647 | loss: 4.710370
iter: 648 | loss: 4.710176
iter: 649 | loss: 4.709983
iter: 650 | loss: 4.709789
iter: 651 | loss: 4.709596
iter: 652 | loss: 4.709403
iter: 653 | loss: 4.709209
iter: 654 | loss: 4.709016
iter: 655 | loss: 4.708822
iter: 656 | loss: 4.708629
iter: 657 | loss: 4.708436
iter: 658 | loss: 4.708242
iter: 659 | loss: 4.708049
iter: 660 | loss: 4.707856
iter: 661 | loss: 4.707662
iter: 662 | loss: 4.707469
iter: 663 | loss: 4.707275
iter: 664 | loss: 4.707082
iter: 665 | loss: 4.706889
iter: 666 | loss: 4.706695
iter: 667 | loss: 4.706502
iter: 668 | loss: 4.706308
iter: 669 | loss: 4.706115
iter: 670 | loss: 4.705922
iter: 671 | loss: 4.705728
iter: 672 | loss: 4.705535
iter: 673 | loss: 4.705342
iter: 674 | loss: 4.705148
iter: 675 | loss: 4.704955
iter: 676 | loss: 4.704761
iter: 677 | loss: 4.704568
iter: 678 | loss: 4.704375
iter: 679 | loss: 4.704181
iter: 680 | loss: 4.703988
iter: 681 | loss: 4.703794
iter: 682 | loss: 4.703601
iter: 683 | loss: 4.703408
iter: 684 | loss: 4.703214
iter: 685 | loss: 4.703021
iter: 686 | loss: 4.702827
iter: 687 | loss: 4.702634
iter: 688 | loss: 4.702441
iter: 689 | loss: 4.702247
iter: 690 | loss: 4.702054
iter: 691 | loss: 4.701861
iter: 692 | loss: 4.701667
iter: 693 | loss: 4.701474
iter: 694 | loss: 4.701280
iter: 695 | loss: 4.701087
iter: 696 | loss: 4.700894
iter: 697 | loss: 4.700700
iter: 698 | loss: 4.700507
iter: 699 | loss: 4.700313
iter: 700 | loss: 4.700120
iter: 701 | loss: 4.699927
iter: 702 | loss: 4.699733
iter: 703 | loss: 4.699540
iter: 704 | loss: 4.699347
iter: 705 | loss: 4.699153
iter: 706 | loss: 4.698960
iter: 707 | loss: 4.698766
iter: 708 | loss: 4.698573
iter: 709 | loss: 4.698380
iter: 710 | loss: 4.698186
iter: 711 | loss: 4.697993
iter: 712 | loss: 4.697799
iter: 713 | loss: 4.697606
iter: 714 | loss: 4.697413
iter: 715 | loss: 4.697219
iter: 716 | loss: 4.697026
iter: 717 | loss: 4.696833
iter: 718 | loss: 4.696639
iter: 719 | loss: 4.696446
iter: 720 | loss: 4.696252
iter: 721 | loss: 4.696059
iter: 722 | loss: 4.695866
iter: 723 | loss: 4.695672
iter: 724 | loss: 4.695479
iter: 725 | loss: 4.695285
iter: 726 | loss: 4.695092
iter: 727 | loss: 4.694899
iter: 728 | loss: 4.694705
iter: 729 | loss: 4.694512
iter: 730 | loss: 4.694318
iter: 731 | loss: 4.694125
iter: 732 | loss: 4.693932
iter: 733 | loss: 4.693738
iter: 734 | loss: 4.693545
iter: 735 | loss: 4.693352
iter: 736 | loss: 4.693158
iter: 737 | loss: 4.692965
iter: 738 | loss: 4.692771
iter: 739 | loss: 4.692578
iter: 740 | loss: 4.692385
iter: 741 | loss: 4.692191
iter: 742 | loss: 4.691998
iter: 743 | loss: 4.691804
iter: 744 | loss: 4.691611
iter: 745 | loss: 4.691418
iter: 746 | loss: 4.691224
iter: 747 | loss: 4.691031
iter: 748 | loss: 4.690838
iter: 749 | loss: 4.690644
iter: 750 | loss: 4.690451
iter: 751 | loss: 4.690257
iter: 752 | loss: 4.690064
iter: 753 | loss: 4.689871
iter: 754 | loss: 4.689677
iter: 755 | loss: 4.689484
iter: 756 | loss: 4.689290
iter: 757 | loss: 4.689097
iter: 758 | loss: 4.688904
iter: 759 | loss: 4.688710
iter: 760 | loss: 4.688517
iter: 761 | loss: 4.688323
iter: 762 | loss: 4.688130
iter: 763 | loss: 4.687937
iter: 764 | loss: 4.687743
iter: 765 | loss: 4.687550
iter: 766 | loss: 4.687357
iter: 767 | loss: 4.687163
iter: 768 | loss: 4.686970
iter: 769 | loss: 4.686776
iter: 770 | loss: 4.686583
iter: 771 | loss: 4.686390
iter: 772 | loss: 4.686196
iter: 773 | loss: 4.686003
iter: 774 | loss: 4.685809
iter: 775 | loss: 4.685616
iter: 776 | loss: 4.685423
iter: 777 | loss: 4.685229
iter: 778 | loss: 4.685036
iter: 779 | loss: 4.684843
iter: 780 | loss: 4.684649
iter: 781 | loss: 4.684456
iter: 782 | loss: 4.684262
iter: 783 | loss: 4.684069
iter: 784 | loss: 4.683876
iter: 785 | loss: 4.683682
iter: 786 | loss: 4.683489
iter: 787 | loss: 4.683295
iter: 788 | loss: 4.683102
iter: 789 | loss: 4.682909
iter: 790 | loss: 4.682715
iter: 791 | loss: 4.682522
iter: 792 | loss: 4.682328
iter: 793 | loss: 4.682135
iter: 794 | loss: 4.681942
iter: 795 | loss: 4.681748
iter: 796 | loss: 4.681555
iter: 797 | loss: 4.681362
iter: 798 | loss: 4.681168
iter: 799 | loss: 4.680975
iter: 800 | loss: 4.680781
iter: 801 | loss: 4.680588
iter: 802 | loss: 4.680395
iter: 803 | loss: 4.680201
iter: 804 | loss: 4.680008
iter: 805 | loss: 4.679814
iter: 806 | loss: 4.679621
iter: 807 | loss: 4.679428
iter: 808 | loss: 4.679234
iter: 809 | loss: 4.679041
iter: 810 | loss: 4.678848
iter: 811 | loss: 4.678654
iter: 812 | loss: 4.678461
iter: 813 | loss: 4.678267
iter: 814 | loss: 4.678074
iter: 815 | loss: 4.677881
iter: 816 | loss: 4.677687
iter: 817 | loss: 4.677494
iter: 818 | loss: 4.677300
iter: 819 | loss: 4.677107
iter: 820 | loss: 4.676914
iter: 821 | loss: 4.676720
iter: 822 | loss: 4.676527
iter: 823 | loss: 4.676333
iter: 824 | loss: 4.676140
iter: 825 | loss: 4.675947
iter: 826 | loss: 4.675753
iter: 827 | loss: 4.675560
iter: 828 | loss: 4.675367
iter: 829 | loss: 4.675173
iter: 830 | loss: 4.674980
iter: 831 | loss: 4.674786
iter: 832 | loss: 4.674593
iter: 833 | loss: 4.674400
iter: 834 | loss: 4.674206
iter: 835 | loss: 4.674013
iter: 836 | loss: 4.673819
iter: 837 | loss: 4.673626
iter: 838 | loss: 4.673433
iter: 839 | loss: 4.673239
iter: 840 | loss: 4.673046
iter: 841 | loss: 4.672853
iter: 842 | loss: 4.672659
iter: 843 | loss: 4.672466
iter: 844 | loss: 4.672272
iter: 845 | loss: 4.672079
iter: 846 | loss: 4.671886
iter: 847 | loss: 4.671692
iter: 848 | loss: 4.671499
iter: 849 | loss: 4.671305
iter: 850 | loss: 4.671112
iter: 851 | loss: 4.670919
iter: 852 | loss: 4.670725
iter: 853 | loss: 4.670532
iter: 854 | loss: 4.670338
iter: 855 | loss: 4.670145
iter: 856 | loss: 4.669952
iter: 857 | loss: 4.669758
iter: 858 | loss: 4.669565
iter: 859 | loss: 4.669372
iter: 860 | loss: 4.669178
iter: 861 | loss: 4.668985
iter: 862 | loss: 4.668791
iter: 863 | loss: 4.668598
iter: 864 | loss: 4.668405
iter: 865 | loss: 4.668211
iter: 866 | loss: 4.668018
iter: 867 | loss: 4.667824
iter: 868 | loss: 4.667631
iter: 869 | loss: 4.667438
iter: 870 | loss: 4.667244
iter: 871 | loss: 4.667051
iter: 872 | loss: 4.666858
iter: 873 | loss: 4.666664
iter: 874 | loss: 4.666471
iter: 875 | loss: 4.666277
iter: 876 | loss: 4.666084
iter: 877 | loss: 4.665891
iter: 878 | loss: 4.665697
iter: 879 | loss: 4.665504
iter: 880 | loss: 4.665310
iter: 881 | loss: 4.665117
iter: 882 | loss: 4.664924
iter: 883 | loss: 4.664730
iter: 884 | loss: 4.664537
iter: 885 | loss: 4.664343
iter: 886 | loss: 4.664150
iter: 887 | loss: 4.663957
iter: 888 | loss: 4.663763
iter: 889 | loss: 4.663570
iter: 890 | loss: 4.663377
iter: 891 | loss: 4.663183
iter: 892 | loss: 4.662990
iter: 893 | loss: 4.662796
iter: 894 | loss: 4.662603
iter: 895 | loss: 4.662410
iter: 896 | loss: 4.662216
iter: 897 | loss: 4.662023
iter: 898 | loss: 4.661829
iter: 899 | loss: 4.661636
iter: 900 | loss: 4.661443
iter: 901 | loss: 4.661249
iter: 902 | loss: 4.661056
iter: 903 | loss: 4.660863
iter: 904 | loss: 4.660669
iter: 905 | loss: 4.660476
iter: 906 | loss: 4.660282
iter: 907 | loss: 4.660089
iter: 908 | loss: 4.659896
iter: 909 | loss: 4.659702
iter: 910 | loss: 4.659509
iter: 911 | loss: 4.659315
iter: 912 | loss: 4.659122
iter: 913 | loss: 4.658929
iter: 914 | loss: 4.658735
iter: 915 | loss: 4.658542
iter: 916 | loss: 4.658348
iter: 917 | loss: 4.658155
iter: 918 | loss: 4.657962
iter: 919 | loss: 4.657768
iter: 920 | loss: 4.657575
iter: 921 | loss: 4.657382
iter: 922 | loss: 4.657188
iter: 923 | loss: 4.656995
iter: 924 | loss: 4.656801
iter: 925 | loss: 4.656608
iter: 926 | loss: 4.656415
iter: 927 | loss: 4.656221
iter: 928 | loss: 4.656028
iter: 929 | loss: 4.655834
iter: 930 | loss: 4.655641
iter: 931 | loss: 4.655448
iter: 932 | loss: 4.655254
iter: 933 | loss: 4.655061
iter: 934 | loss: 4.654868
iter: 935 | loss: 4.654674
iter: 936 | loss: 4.654481
iter: 937 | loss: 4.654287
iter: 938 | loss: 4.654094
iter: 939 | loss: 4.653901
iter: 940 | loss: 4.653707
iter: 941 | loss: 4.653514
iter: 942 | loss: 4.653320
iter: 943 | loss: 4.653127
iter: 944 | loss: 4.652934
iter: 945 | loss: 4.652740
iter: 946 | loss: 4.652547
iter: 947 | loss: 4.652353
iter: 948 | loss: 4.652160
iter: 949 | loss: 4.651967
iter: 950 | loss: 4.651773
iter: 951 | loss: 4.651580
iter: 952 | loss: 4.651387
iter: 953 | loss: 4.651193
iter: 954 | loss: 4.651000
iter: 955 | loss: 4.650806
iter: 956 | loss: 4.650613
iter: 957 | loss: 4.650420
iter: 958 | loss: 4.650226
iter: 959 | loss: 4.650033
iter: 960 | loss: 4.649839
iter: 961 | loss: 4.649646
iter: 962 | loss: 4.649453
iter: 963 | loss: 4.649259
iter: 964 | loss: 4.649066
iter: 965 | loss: 4.648873
iter: 966 | loss: 4.648679
iter: 967 | loss: 4.648486
iter: 968 | loss: 4.648292
iter: 969 | loss: 4.648099
iter: 970 | loss: 4.647906
iter: 971 | loss: 4.647712
iter: 972 | loss: 4.647519
iter: 973 | loss: 4.647325
iter: 974 | loss: 4.647132
iter: 975 | loss: 4.646939
iter: 976 | loss: 4.646745
iter: 977 | loss: 4.646552
iter: 978 | loss: 4.646358
iter: 979 | loss: 4.646165
iter: 980 | loss: 4.645972
iter: 981 | loss: 4.645778
iter: 982 | loss: 4.645585
iter: 983 | loss: 4.645392
iter: 984 | loss: 4.645198
iter: 985 | loss: 4.645005
iter: 986 | loss: 4.644811
iter: 987 | loss: 4.644618
iter: 988 | loss: 4.644425
iter: 989 | loss: 4.644231
iter: 990 | loss: 4.644038
iter: 991 | loss: 4.643844
iter: 992 | loss: 4.643651
iter: 993 | loss: 4.643458
iter: 994 | loss: 4.643264
iter: 995 | loss: 4.643071
iter: 996 | loss: 4.642878
iter: 997 | loss: 4.642684
iter: 998 | loss: 4.642491
iter: 999 | loss: 4.642297
iter: 1000 | loss: 4.642104
iter: 1001 | loss: 4.641911
iter: 1002 | loss: 4.641717
iter: 1003 | loss: 4.641524
iter: 1004 | loss: 4.641330
iter: 1005 | loss: 4.641137
iter: 1006 | loss: 4.640944
iter: 1007 | loss: 4.640750
iter: 1008 | loss: 4.640557
iter: 1009 | loss: 4.640363
iter: 1010 | loss: 4.640170
iter: 1011 | loss: 4.639977
iter: 1012 | loss: 4.639783
iter: 1013 | loss: 4.639590
iter: 1014 | loss: 4.639397
iter: 1015 | loss: 4.639203
iter: 1016 | loss: 4.639010
iter: 1017 | loss: 4.638816
iter: 1018 | loss: 4.638623
iter: 1019 | loss: 4.638430
iter: 1020 | loss: 4.638236
iter: 1021 | loss: 4.638043
iter: 1022 | loss: 4.637849
iter: 1023 | loss: 4.637656
iter: 1024 | loss: 4.637463
iter: 1025 | loss: 4.637269
iter: 1026 | loss: 4.637076
iter: 1027 | loss: 4.636883
iter: 1028 | loss: 4.636689
iter: 1029 | loss: 4.636496
iter: 1030 | loss: 4.636302
iter: 1031 | loss: 4.636109
iter: 1032 | loss: 4.635916
iter: 1033 | loss: 4.635722
iter: 1034 | loss: 4.635529
iter: 1035 | loss: 4.635335
iter: 1036 | loss: 4.635142
iter: 1037 | loss: 4.634949
iter: 1038 | loss: 4.634755
iter: 1039 | loss: 4.634562
iter: 1040 | loss: 4.634369
iter: 1041 | loss: 4.634175
iter: 1042 | loss: 4.633982
iter: 1043 | loss: 4.633788
iter: 1044 | loss: 4.633595
iter: 1045 | loss: 4.633402
iter: 1046 | loss: 4.633208
iter: 1047 | loss: 4.633015
iter: 1048 | loss: 4.632821
iter: 1049 | loss: 4.632628
iter: 1050 | loss: 4.632435
iter: 1051 | loss: 4.632241
iter: 1052 | loss: 4.632048
iter: 1053 | loss: 4.631854
iter: 1054 | loss: 4.631661
iter: 1055 | loss: 4.631468
iter: 1056 | loss: 4.631274
iter: 1057 | loss: 4.631081
iter: 1058 | loss: 4.630888
iter: 1059 | loss: 4.630694
iter: 1060 | loss: 4.630501
iter: 1061 | loss: 4.630307
iter: 1062 | loss: 4.630114
iter: 1063 | loss: 4.629921
iter: 1064 | loss: 4.629727
iter: 1065 | loss: 4.629534
iter: 1066 | loss: 4.629340
iter: 1067 | loss: 4.629147
iter: 1068 | loss: 4.628954
iter: 1069 | loss: 4.628760
iter: 1070 | loss: 4.628567
iter: 1071 | loss: 4.628374
iter: 1072 | loss: 4.628180
iter: 1073 | loss: 4.627987
iter: 1074 | loss: 4.627793
iter: 1075 | loss: 4.627600
iter: 1076 | loss: 4.627407
iter: 1077 | loss: 4.627213
iter: 1078 | loss: 4.627020
iter: 1079 | loss: 4.626826
iter: 1080 | loss: 4.626633
iter: 1081 | loss: 4.626440
iter: 1082 | loss: 4.626246
iter: 1083 | loss: 4.626053
iter: 1084 | loss: 4.625859
iter: 1085 | loss: 4.625666
iter: 1086 | loss: 4.625473
iter: 1087 | loss: 4.625279
iter: 1088 | loss: 4.625086
iter: 1089 | loss: 4.624893
iter: 1090 | loss: 4.624699
iter: 1091 | loss: 4.624506
iter: 1092 | loss: 4.624312
iter: 1093 | loss: 4.624119
iter: 1094 | loss: 4.623926
iter: 1095 | loss: 4.623732
iter: 1096 | loss: 4.623539
iter: 1097 | loss: 4.623345
iter: 1098 | loss: 4.623152
iter: 1099 | loss: 4.622959
iter: 1100 | loss: 4.622765
iter: 1101 | loss: 4.622572
iter: 1102 | loss: 4.622379
iter: 1103 | loss: 4.622185
iter: 1104 | loss: 4.621992
iter: 1105 | loss: 4.621798
iter: 1106 | loss: 4.621605
iter: 1107 | loss: 4.621412
iter: 1108 | loss: 4.621218
iter: 1109 | loss: 4.621025
iter: 1110 | loss: 4.620831
iter: 1111 | loss: 4.620638
iter: 1112 | loss: 4.620445
iter: 1113 | loss: 4.620251
iter: 1114 | loss: 4.620058
iter: 1115 | loss: 4.619864
iter: 1116 | loss: 4.619671
iter: 1117 | loss: 4.619478
iter: 1118 | loss: 4.619284
iter: 1119 | loss: 4.619091
iter: 1120 | loss: 4.618898
iter: 1121 | loss: 4.618704
iter: 1122 | loss: 4.618511
iter: 1123 | loss: 4.618317
iter: 1124 | loss: 4.618124
iter: 1125 | loss: 4.617931
iter: 1126 | loss: 4.617737
iter: 1127 | loss: 4.617544
iter: 1128 | loss: 4.617350
iter: 1129 | loss: 4.617157
iter: 1130 | loss: 4.616964
iter: 1131 | loss: 4.616770
iter: 1132 | loss: 4.616577
iter: 1133 | loss: 4.616384
iter: 1134 | loss: 4.616190
iter: 1135 | loss: 4.615997
iter: 1136 | loss: 4.615803
iter: 1137 | loss: 4.615610
iter: 1138 | loss: 4.615417
iter: 1139 | loss: 4.615223
iter: 1140 | loss: 4.615030
iter: 1141 | loss: 4.614836
iter: 1142 | loss: 4.614643
iter: 1143 | loss: 4.614450
iter: 1144 | loss: 4.614256
iter: 1145 | loss: 4.614063
iter: 1146 | loss: 4.613869
iter: 1147 | loss: 4.613676
iter: 1148 | loss: 4.613483
iter: 1149 | loss: 4.613289
iter: 1150 | loss: 4.613096
iter: 1151 | loss: 4.612903
iter: 1152 | loss: 4.612709
iter: 1153 | loss: 4.612516
iter: 1154 | loss: 4.612322
iter: 1155 | loss: 4.612129
iter: 1156 | loss: 4.611936
iter: 1157 | loss: 4.611742
iter: 1158 | loss: 4.611549
iter: 1159 | loss: 4.611355
iter: 1160 | loss: 4.611162
iter: 1161 | loss: 4.610969
iter: 1162 | loss: 4.610775
iter: 1163 | loss: 4.610582
iter: 1164 | loss: 4.610389
iter: 1165 | loss: 4.610195
iter: 1166 | loss: 4.610002
iter: 1167 | loss: 4.609808
iter: 1168 | loss: 4.609615
iter: 1169 | loss: 4.609422
iter: 1170 | loss: 4.609228
iter: 1171 | loss: 4.609035
iter: 1172 | loss: 4.608841
iter: 1173 | loss: 4.608648
iter: 1174 | loss: 4.608455
iter: 1175 | loss: 4.608261
iter: 1176 | loss: 4.608068
iter: 1177 | loss: 4.607874
iter: 1178 | loss: 4.607681
iter: 1179 | loss: 4.607488
iter: 1180 | loss: 4.607294
iter: 1181 | loss: 4.607101
iter: 1182 | loss: 4.606908
iter: 1183 | loss: 4.606714
iter: 1184 | loss: 4.606521
iter: 1185 | loss: 4.606327
iter: 1186 | loss: 4.606134
iter: 1187 | loss: 4.605941
iter: 1188 | loss: 4.605747
iter: 1189 | loss: 4.605554
iter: 1190 | loss: 4.605360
iter: 1191 | loss: 4.605167
iter: 1192 | loss: 4.604974
iter: 1193 | loss: 4.604780
iter: 1194 | loss: 4.604587
iter: 1195 | loss: 4.604394
iter: 1196 | loss: 4.604200
iter: 1197 | loss: 4.604007
iter: 1198 | loss: 4.603813
iter: 1199 | loss: 4.603620
iter: 1200 | loss: 4.603427
iter: 1201 | loss: 4.603233
iter: 1202 | loss: 4.603040
iter: 1203 | loss: 4.602846
iter: 1204 | loss: 4.602653
iter: 1205 | loss: 4.602460
iter: 1206 | loss: 4.602266
iter: 1207 | loss: 4.602073
iter: 1208 | loss: 4.601879
iter: 1209 | loss: 4.601686
iter: 1210 | loss: 4.601493
iter: 1211 | loss: 4.601299
iter: 1212 | loss: 4.601106
iter: 1213 | loss: 4.600913
iter: 1214 | loss: 4.600719
iter: 1215 | loss: 4.600526
iter: 1216 | loss: 4.600332
iter: 1217 | loss: 4.600139
iter: 1218 | loss: 4.599946
iter: 1219 | loss: 4.599752
iter: 1220 | loss: 4.599559
iter: 1221 | loss: 4.599365
iter: 1222 | loss: 4.599172
iter: 1223 | loss: 4.598979
iter: 1224 | loss: 4.598785
iter: 1225 | loss: 4.598592
iter: 1226 | loss: 4.598399
iter: 1227 | loss: 4.598205
iter: 1228 | loss: 4.598012
iter: 1229 | loss: 4.597818
iter: 1230 | loss: 4.597625
iter: 1231 | loss: 4.597432
iter: 1232 | loss: 4.597238
iter: 1233 | loss: 4.597045
iter: 1234 | loss: 4.596851
iter: 1235 | loss: 4.596658
iter: 1236 | loss: 4.596465
iter: 1237 | loss: 4.596271
iter: 1238 | loss: 4.596078
iter: 1239 | loss: 4.595884
iter: 1240 | loss: 4.595691
iter: 1241 | loss: 4.595498
iter: 1242 | loss: 4.595304
iter: 1243 | loss: 4.595111
iter: 1244 | loss: 4.594918
iter: 1245 | loss: 4.594724
iter: 1246 | loss: 4.594531
iter: 1247 | loss: 4.594337
iter: 1248 | loss: 4.594144
iter: 1249 | loss: 4.593951
iter: 1250 | loss: 4.593757
iter: 1251 | loss: 4.593564
iter: 1252 | loss: 4.593370
iter: 1253 | loss: 4.593177
iter: 1254 | loss: 4.592984
iter: 1255 | loss: 4.592790
iter: 1256 | loss: 4.592597
iter: 1257 | loss: 4.592404
iter: 1258 | loss: 4.592210
iter: 1259 | loss: 4.592017
iter: 1260 | loss: 4.591823
iter: 1261 | loss: 4.591630
iter: 1262 | loss: 4.591437
iter: 1263 | loss: 4.591243
iter: 1264 | loss: 4.591050
iter: 1265 | loss: 4.590856
iter: 1266 | loss: 4.590663
iter: 1267 | loss: 4.590470
iter: 1268 | loss: 4.590276
iter: 1269 | loss: 4.590083
iter: 1270 | loss: 4.589889
iter: 1271 | loss: 4.589696
iter: 1272 | loss: 4.589503
iter: 1273 | loss: 4.589309
iter: 1274 | loss: 4.589116
iter: 1275 | loss: 4.588923
iter: 1276 | loss: 4.588729
iter: 1277 | loss: 4.588536
iter: 1278 | loss: 4.588342
iter: 1279 | loss: 4.588149
iter: 1280 | loss: 4.587956
iter: 1281 | loss: 4.587762
iter: 1282 | loss: 4.587569
iter: 1283 | loss: 4.587375
iter: 1284 | loss: 4.587182
iter: 1285 | loss: 4.586989
iter: 1286 | loss: 4.586795
iter: 1287 | loss: 4.586602
iter: 1288 | loss: 4.586409
iter: 1289 | loss: 4.586215
iter: 1290 | loss: 4.586022
iter: 1291 | loss: 4.585828
iter: 1292 | loss: 4.585635
iter: 1293 | loss: 4.585442
iter: 1294 | loss: 4.585248
iter: 1295 | loss: 4.585055
iter: 1296 | loss: 4.584861
iter: 1297 | loss: 4.584668
iter: 1298 | loss: 4.584475
iter: 1299 | loss: 4.584281
iter: 1300 | loss: 4.584088
iter: 1301 | loss: 4.583894
iter: 1302 | loss: 4.583701
iter: 1303 | loss: 4.583508
iter: 1304 | loss: 4.583314
iter: 1305 | loss: 4.583121
iter: 1306 | loss: 4.582928
iter: 1307 | loss: 4.582734
iter: 1308 | loss: 4.582541
iter: 1309 | loss: 4.582347
iter: 1310 | loss: 4.582154
iter: 1311 | loss: 4.581961
iter: 1312 | loss: 4.581767
iter: 1313 | loss: 4.581574
iter: 1314 | loss: 4.581380
iter: 1315 | loss: 4.581187
iter: 1316 | loss: 4.580994
iter: 1317 | loss: 4.580800
iter: 1318 | loss: 4.580607
iter: 1319 | loss: 4.580414
iter: 1320 | loss: 4.580220
iter: 1321 | loss: 4.580027
iter: 1322 | loss: 4.579833
iter: 1323 | loss: 4.579640
iter: 1324 | loss: 4.579447
iter: 1325 | loss: 4.579253
iter: 1326 | loss: 4.579060
iter: 1327 | loss: 4.578866
iter: 1328 | loss: 4.578673
iter: 1329 | loss: 4.578480
iter: 1330 | loss: 4.578286
iter: 1331 | loss: 4.578093
iter: 1332 | loss: 4.577899
iter: 1333 | loss: 4.577706
iter: 1334 | loss: 4.577513
iter: 1335 | loss: 4.577319
iter: 1336 | loss: 4.577126
iter: 1337 | loss: 4.576933
iter: 1338 | loss: 4.576739
iter: 1339 | loss: 4.576546
iter: 1340 | loss: 4.576352
iter: 1341 | loss: 4.576159
iter: 1342 | loss: 4.575966
iter: 1343 | loss: 4.575772
iter: 1344 | loss: 4.575579
iter: 1345 | loss: 4.575385
iter: 1346 | loss: 4.575192
iter: 1347 | loss: 4.574999
iter: 1348 | loss: 4.574805
iter: 1349 | loss: 4.574612
iter: 1350 | loss: 4.574419
iter: 1351 | loss: 4.574225
iter: 1352 | loss: 4.574032
iter: 1353 | loss: 4.573838
iter: 1354 | loss: 4.573645
iter: 1355 | loss: 4.573452
iter: 1356 | loss: 4.573258
iter: 1357 | loss: 4.573065
iter: 1358 | loss: 4.572871
iter: 1359 | loss: 4.572678
iter: 1360 | loss: 4.572485
iter: 1361 | loss: 4.572291
iter: 1362 | loss: 4.572098
iter: 1363 | loss: 4.571905
iter: 1364 | loss: 4.571711
iter: 1365 | loss: 4.571518
iter: 1366 | loss: 4.571324
iter: 1367 | loss: 4.571131
iter: 1368 | loss: 4.570938
iter: 1369 | loss: 4.570744
iter: 1370 | loss: 4.570551
iter: 1371 | loss: 4.570357
iter: 1372 | loss: 4.570164
iter: 1373 | loss: 4.569971
iter: 1374 | loss: 4.569777
iter: 1375 | loss: 4.569584
iter: 1376 | loss: 4.569390
iter: 1377 | loss: 4.569197
iter: 1378 | loss: 4.569004
iter: 1379 | loss: 4.568810
iter: 1380 | loss: 4.568617
iter: 1381 | loss: 4.568424
iter: 1382 | loss: 4.568230
iter: 1383 | loss: 4.568037
iter: 1384 | loss: 4.567843
iter: 1385 | loss: 4.567650
iter: 1386 | loss: 4.567457
iter: 1387 | loss: 4.567263
iter: 1388 | loss: 4.567070
iter: 1389 | loss: 4.566876
iter: 1390 | loss: 4.566683
iter: 1391 | loss: 4.566490
iter: 1392 | loss: 4.566296
iter: 1393 | loss: 4.566103
iter: 1394 | loss: 4.565910
iter: 1395 | loss: 4.565716
iter: 1396 | loss: 4.565523
iter: 1397 | loss: 4.565329
iter: 1398 | loss: 4.565136
iter: 1399 | loss: 4.564943
iter: 1400 | loss: 4.564749
iter: 1401 | loss: 4.564556
iter: 1402 | loss: 4.564362
iter: 1403 | loss: 4.564169
iter: 1404 | loss: 4.563976
iter: 1405 | loss: 4.563782
iter: 1406 | loss: 4.563589
iter: 1407 | loss: 4.563395
iter: 1408 | loss: 4.563202
iter: 1409 | loss: 4.563009
iter: 1410 | loss: 4.562815
iter: 1411 | loss: 4.562622
iter: 1412 | loss: 4.562429
iter: 1413 | loss: 4.562235
iter: 1414 | loss: 4.562042
iter: 1415 | loss: 4.561848
iter: 1416 | loss: 4.561655
iter: 1417 | loss: 4.561462
iter: 1418 | loss: 4.561268
iter: 1419 | loss: 4.561075
iter: 1420 | loss: 4.560881
iter: 1421 | loss: 4.560688
iter: 1422 | loss: 4.560495
iter: 1423 | loss: 4.560301
iter: 1424 | loss: 4.560108
iter: 1425 | loss: 4.559915
iter: 1426 | loss: 4.559721
iter: 1427 | loss: 4.559528
iter: 1428 | loss: 4.559334
iter: 1429 | loss: 4.559141
iter: 1430 | loss: 4.558948
iter: 1431 | loss: 4.558754
iter: 1432 | loss: 4.558561
iter: 1433 | loss: 4.558367
iter: 1434 | loss: 4.558174
iter: 1435 | loss: 4.557981
iter: 1436 | loss: 4.557787
iter: 1437 | loss: 4.557594
iter: 1438 | loss: 4.557400
iter: 1439 | loss: 4.557207
iter: 1440 | loss: 4.557014
iter: 1441 | loss: 4.556820
iter: 1442 | loss: 4.556627
iter: 1443 | loss: 4.556434
iter: 1444 | loss: 4.556240
iter: 1445 | loss: 4.556047
iter: 1446 | loss: 4.555853
iter: 1447 | loss: 4.555660
iter: 1448 | loss: 4.555467
iter: 1449 | loss: 4.555273
iter: 1450 | loss: 4.555080
iter: 1451 | loss: 4.554886
iter: 1452 | loss: 4.554693
iter: 1453 | loss: 4.554500
iter: 1454 | loss: 4.554306
iter: 1455 | loss: 4.554113
iter: 1456 | loss: 4.553920
iter: 1457 | loss: 4.553726
iter: 1458 | loss: 4.553533
iter: 1459 | loss: 4.553339
iter: 1460 | loss: 4.553146
iter: 1461 | loss: 4.552953
iter: 1462 | loss: 4.552759
iter: 1463 | loss: 4.552566
iter: 1464 | loss: 4.552372
iter: 1465 | loss: 4.552179
iter: 1466 | loss: 4.551986
iter: 1467 | loss: 4.551792
iter: 1468 | loss: 4.551599
iter: 1469 | loss: 4.551405
iter: 1470 | loss: 4.551212
iter: 1471 | loss: 4.551019
iter: 1472 | loss: 4.550825
iter: 1473 | loss: 4.550632
iter: 1474 | loss: 4.550439
iter: 1475 | loss: 4.550245
iter: 1476 | loss: 4.550052
iter: 1477 | loss: 4.549858
iter: 1478 | loss: 4.549665
iter: 1479 | loss: 4.549472
iter: 1480 | loss: 4.549278
iter: 1481 | loss: 4.549085
iter: 1482 | loss: 4.548891
iter: 1483 | loss: 4.548698
iter: 1484 | loss: 4.548505
iter: 1485 | loss: 4.548311
iter: 1486 | loss: 4.548118
iter: 1487 | loss: 4.547925
iter: 1488 | loss: 4.547731
iter: 1489 | loss: 4.547538
iter: 1490 | loss: 4.547344
iter: 1491 | loss: 4.547151
iter: 1492 | loss: 4.546958
iter: 1493 | loss: 4.546764
iter: 1494 | loss: 4.546571
iter: 1495 | loss: 4.546377
iter: 1496 | loss: 4.546184
iter: 1497 | loss: 4.545991
iter: 1498 | loss: 4.545797
iter: 1499 | loss: 4.545604
iter: 1500 | loss: 4.545410
iter: 1501 | loss: 4.545217
iter: 1502 | loss: 4.545024
iter: 1503 | loss: 4.544830
iter: 1504 | loss: 4.544637
iter: 1505 | loss: 4.544444
iter: 1506 | loss: 4.544250
iter: 1507 | loss: 4.544057
iter: 1508 | loss: 4.543863
iter: 1509 | loss: 4.543670
iter: 1510 | loss: 4.543477
iter: 1511 | loss: 4.543283
iter: 1512 | loss: 4.543090
iter: 1513 | loss: 4.542896
iter: 1514 | loss: 4.542703
iter: 1515 | loss: 4.542510
iter: 1516 | loss: 4.542316
iter: 1517 | loss: 4.542123
iter: 1518 | loss: 4.541930
iter: 1519 | loss: 4.541736
iter: 1520 | loss: 4.541543
iter: 1521 | loss: 4.541349
iter: 1522 | loss: 4.541156
iter: 1523 | loss: 4.540963
iter: 1524 | loss: 4.540769
iter: 1525 | loss: 4.540576
iter: 1526 | loss: 4.540382
iter: 1527 | loss: 4.540189
iter: 1528 | loss: 4.539996
iter: 1529 | loss: 4.539802
iter: 1530 | loss: 4.539609
iter: 1531 | loss: 4.539415
iter: 1532 | loss: 4.539222
iter: 1533 | loss: 4.539029
iter: 1534 | loss: 4.538835
iter: 1535 | loss: 4.538642
iter: 1536 | loss: 4.538449
iter: 1537 | loss: 4.538255
iter: 1538 | loss: 4.538062
iter: 1539 | loss: 4.537868
iter: 1540 | loss: 4.537675
iter: 1541 | loss: 4.537482
iter: 1542 | loss: 4.537288
iter: 1543 | loss: 4.537095
iter: 1544 | loss: 4.536901
iter: 1545 | loss: 4.536708
iter: 1546 | loss: 4.536515
iter: 1547 | loss: 4.536321
iter: 1548 | loss: 4.536128
iter: 1549 | loss: 4.535935
iter: 1550 | loss: 4.535741
iter: 1551 | loss: 4.535548
iter: 1552 | loss: 4.535354
iter: 1553 | loss: 4.535161
iter: 1554 | loss: 4.534968
iter: 1555 | loss: 4.534774
iter: 1556 | loss: 4.534581
iter: 1557 | loss: 4.534387
iter: 1558 | loss: 4.534194
iter: 1559 | loss: 4.534001
iter: 1560 | loss: 4.533807
iter: 1561 | loss: 4.533614
iter: 1562 | loss: 4.533420
iter: 1563 | loss: 4.533227
iter: 1564 | loss: 4.533034
iter: 1565 | loss: 4.532840
iter: 1566 | loss: 4.532647
iter: 1567 | loss: 4.532454
iter: 1568 | loss: 4.532260
iter: 1569 | loss: 4.532067
iter: 1570 | loss: 4.531873
iter: 1571 | loss: 4.531680
iter: 1572 | loss: 4.531487
iter: 1573 | loss: 4.531293
iter: 1574 | loss: 4.531100
iter: 1575 | loss: 4.530906
iter: 1576 | loss: 4.530713
iter: 1577 | loss: 4.530520
iter: 1578 | loss: 4.530326
iter: 1579 | loss: 4.530133
iter: 1580 | loss: 4.529940
iter: 1581 | loss: 4.529746
iter: 1582 | loss: 4.529553
iter: 1583 | loss: 4.529359
iter: 1584 | loss: 4.529166
iter: 1585 | loss: 4.528973
iter: 1586 | loss: 4.528779
iter: 1587 | loss: 4.528586
iter: 1588 | loss: 4.528392
iter: 1589 | loss: 4.528199
iter: 1590 | loss: 4.528006
iter: 1591 | loss: 4.527812
iter: 1592 | loss: 4.527619
iter: 1593 | loss: 4.527425
iter: 1594 | loss: 4.527232
iter: 1595 | loss: 4.527039
iter: 1596 | loss: 4.526845
iter: 1597 | loss: 4.526652
iter: 1598 | loss: 4.526459
iter: 1599 | loss: 4.526265
iter: 1600 | loss: 4.526072
iter: 1601 | loss: 4.525878
iter: 1602 | loss: 4.525685
iter: 1603 | loss: 4.525492
iter: 1604 | loss: 4.525298
iter: 1605 | loss: 4.525105
iter: 1606 | loss: 4.524911
iter: 1607 | loss: 4.524718
iter: 1608 | loss: 4.524525
iter: 1609 | loss: 4.524331
iter: 1610 | loss: 4.524138
iter: 1611 | loss: 4.523945
iter: 1612 | loss: 4.523751
iter: 1613 | loss: 4.523558
iter: 1614 | loss: 4.523364
iter: 1615 | loss: 4.523171
iter: 1616 | loss: 4.522978
iter: 1617 | loss: 4.522784
iter: 1618 | loss: 4.522591
iter: 1619 | loss: 4.522397
iter: 1620 | loss: 4.522204
iter: 1621 | loss: 4.522011
iter: 1622 | loss: 4.521817
iter: 1623 | loss: 4.521624
iter: 1624 | loss: 4.521430
iter: 1625 | loss: 4.521237
iter: 1626 | loss: 4.521044
iter: 1627 | loss: 4.520850
iter: 1628 | loss: 4.520657
iter: 1629 | loss: 4.520464
iter: 1630 | loss: 4.520270
iter: 1631 | loss: 4.520077
iter: 1632 | loss: 4.519883
iter: 1633 | loss: 4.519690
iter: 1634 | loss: 4.519497
iter: 1635 | loss: 4.519303
iter: 1636 | loss: 4.519110
iter: 1637 | loss: 4.518916
iter: 1638 | loss: 4.518723
iter: 1639 | loss: 4.518530
iter: 1640 | loss: 4.518336
iter: 1641 | loss: 4.518143
iter: 1642 | loss: 4.517950
iter: 1643 | loss: 4.517756
iter: 1644 | loss: 4.517563
iter: 1645 | loss: 4.517369
iter: 1646 | loss: 4.517176
iter: 1647 | loss: 4.516983
iter: 1648 | loss: 4.516789
iter: 1649 | loss: 4.516596
iter: 1650 | loss: 4.516402
iter: 1651 | loss: 4.516209
iter: 1652 | loss: 4.516016
iter: 1653 | loss: 4.515822
iter: 1654 | loss: 4.515629
iter: 1655 | loss: 4.515435
iter: 1656 | loss: 4.515242
iter: 1657 | loss: 4.515049
iter: 1658 | loss: 4.514855
iter: 1659 | loss: 4.514662
iter: 1660 | loss: 4.514469
iter: 1661 | loss: 4.514275
iter: 1662 | loss: 4.514082
iter: 1663 | loss: 4.513888
iter: 1664 | loss: 4.513695
iter: 1665 | loss: 4.513502
iter: 1666 | loss: 4.513308
iter: 1667 | loss: 4.513115
iter: 1668 | loss: 4.512921
iter: 1669 | loss: 4.512728
iter: 1670 | loss: 4.512535
iter: 1671 | loss: 4.512341
iter: 1672 | loss: 4.512148
iter: 1673 | loss: 4.511955
iter: 1674 | loss: 4.511761
iter: 1675 | loss: 4.511568
iter: 1676 | loss: 4.511374
iter: 1677 | loss: 4.511181
iter: 1678 | loss: 4.510988
iter: 1679 | loss: 4.510794
iter: 1680 | loss: 4.510601
iter: 1681 | loss: 4.510407
iter: 1682 | loss: 4.510214
iter: 1683 | loss: 4.510021
iter: 1684 | loss: 4.509827
iter: 1685 | loss: 4.509634
iter: 1686 | loss: 4.509441
iter: 1687 | loss: 4.509247
iter: 1688 | loss: 4.509054
iter: 1689 | loss: 4.508860
iter: 1690 | loss: 4.508667
iter: 1691 | loss: 4.508474
iter: 1692 | loss: 4.508280
iter: 1693 | loss: 4.508087
iter: 1694 | loss: 4.507893
iter: 1695 | loss: 4.507700
iter: 1696 | loss: 4.507507
iter: 1697 | loss: 4.507313
iter: 1698 | loss: 4.507120
iter: 1699 | loss: 4.506926
iter: 1700 | loss: 4.506733
iter: 1701 | loss: 4.506540
iter: 1702 | loss: 4.506346
iter: 1703 | loss: 4.506153
iter: 1704 | loss: 4.505960
iter: 1705 | loss: 4.505766
iter: 1706 | loss: 4.505573
iter: 1707 | loss: 4.505379
iter: 1708 | loss: 4.505186
iter: 1709 | loss: 4.504993
iter: 1710 | loss: 4.504799
iter: 1711 | loss: 4.504606
iter: 1712 | loss: 4.504412
iter: 1713 | loss: 4.504219
iter: 1714 | loss: 4.504026
iter: 1715 | loss: 4.503832
iter: 1716 | loss: 4.503639
iter: 1717 | loss: 4.503446
iter: 1718 | loss: 4.503252
iter: 1719 | loss: 4.503059
iter: 1720 | loss: 4.502865
iter: 1721 | loss: 4.502672
iter: 1722 | loss: 4.502479
iter: 1723 | loss: 4.502285
iter: 1724 | loss: 4.502092
iter: 1725 | loss: 4.501898
iter: 1726 | loss: 4.501705
iter: 1727 | loss: 4.501512
iter: 1728 | loss: 4.501318
iter: 1729 | loss: 4.501125
iter: 1730 | loss: 4.500931
iter: 1731 | loss: 4.500738
iter: 1732 | loss: 4.500545
iter: 1733 | loss: 4.500351
iter: 1734 | loss: 4.500158
iter: 1735 | loss: 4.499965
iter: 1736 | loss: 4.499771
iter: 1737 | loss: 4.499578
iter: 1738 | loss: 4.499384
iter: 1739 | loss: 4.499191
iter: 1740 | loss: 4.498998
iter: 1741 | loss: 4.498804
iter: 1742 | loss: 4.498611
iter: 1743 | loss: 4.498417
iter: 1744 | loss: 4.498224
iter: 1745 | loss: 4.498031
iter: 1746 | loss: 4.497837
iter: 1747 | loss: 4.497644
iter: 1748 | loss: 4.497451
iter: 1749 | loss: 4.497257
iter: 1750 | loss: 4.497064
iter: 1751 | loss: 4.496870
iter: 1752 | loss: 4.496677
iter: 1753 | loss: 4.496484
iter: 1754 | loss: 4.496290
iter: 1755 | loss: 4.496097
iter: 1756 | loss: 4.495903
iter: 1757 | loss: 4.495710
iter: 1758 | loss: 4.495517
iter: 1759 | loss: 4.495323
iter: 1760 | loss: 4.495130
iter: 1761 | loss: 4.494936
iter: 1762 | loss: 4.494743
iter: 1763 | loss: 4.494550
iter: 1764 | loss: 4.494356
iter: 1765 | loss: 4.494163
iter: 1766 | loss: 4.493970
iter: 1767 | loss: 4.493776
iter: 1768 | loss: 4.493583
iter: 1769 | loss: 4.493389
iter: 1770 | loss: 4.493196
iter: 1771 | loss: 4.493003
iter: 1772 | loss: 4.492809
iter: 1773 | loss: 4.492616
iter: 1774 | loss: 4.492422
iter: 1775 | loss: 4.492229
iter: 1776 | loss: 4.492036
iter: 1777 | loss: 4.491842
iter: 1778 | loss: 4.491649
iter: 1779 | loss: 4.491456
iter: 1780 | loss: 4.491262
iter: 1781 | loss: 4.491069
iter: 1782 | loss: 4.490875
iter: 1783 | loss: 4.490682
iter: 1784 | loss: 4.490489
iter: 1785 | loss: 4.490295
iter: 1786 | loss: 4.490102
iter: 1787 | loss: 4.489908
iter: 1788 | loss: 4.489715
iter: 1789 | loss: 4.489522
iter: 1790 | loss: 4.489328
iter: 1791 | loss: 4.489135
iter: 1792 | loss: 4.488941
iter: 1793 | loss: 4.488748
iter: 1794 | loss: 4.488555
iter: 1795 | loss: 4.488361
iter: 1796 | loss: 4.488168
iter: 1797 | loss: 4.487975
iter: 1798 | loss: 4.487781
iter: 1799 | loss: 4.487588
iter: 1800 | loss: 4.487394
iter: 1801 | loss: 4.487201
iter: 1802 | loss: 4.487008
iter: 1803 | loss: 4.486814
iter: 1804 | loss: 4.486621
iter: 1805 | loss: 4.486427
iter: 1806 | loss: 4.486234
iter: 1807 | loss: 4.486041
iter: 1808 | loss: 4.485847
iter: 1809 | loss: 4.485654
iter: 1810 | loss: 4.485461
iter: 1811 | loss: 4.485267
iter: 1812 | loss: 4.485074
iter: 1813 | loss: 4.484880
iter: 1814 | loss: 4.484687
iter: 1815 | loss: 4.484494
iter: 1816 | loss: 4.484300
iter: 1817 | loss: 4.484107
iter: 1818 | loss: 4.483913
iter: 1819 | loss: 4.483720
iter: 1820 | loss: 4.483527
iter: 1821 | loss: 4.483333
iter: 1822 | loss: 4.483140
iter: 1823 | loss: 4.482946
iter: 1824 | loss: 4.482753
iter: 1825 | loss: 4.482560
iter: 1826 | loss: 4.482366
iter: 1827 | loss: 4.482173
iter: 1828 | loss: 4.481980
iter: 1829 | loss: 4.481786
iter: 1830 | loss: 4.481593
iter: 1831 | loss: 4.481399
iter: 1832 | loss: 4.481206
iter: 1833 | loss: 4.481013
iter: 1834 | loss: 4.480819
iter: 1835 | loss: 4.480626
iter: 1836 | loss: 4.480432
iter: 1837 | loss: 4.480239
iter: 1838 | loss: 4.480046
iter: 1839 | loss: 4.479852
iter: 1840 | loss: 4.479659
iter: 1841 | loss: 4.479466
iter: 1842 | loss: 4.479272
iter: 1843 | loss: 4.479079
iter: 1844 | loss: 4.478885
iter: 1845 | loss: 4.478692
iter: 1846 | loss: 4.478499
iter: 1847 | loss: 4.478305
iter: 1848 | loss: 4.478112
iter: 1849 | loss: 4.477918
iter: 1850 | loss: 4.477725
iter: 1851 | loss: 4.477532
iter: 1852 | loss: 4.477338
iter: 1853 | loss: 4.477145
iter: 1854 | loss: 4.476951
iter: 1855 | loss: 4.476758
iter: 1856 | loss: 4.476565
iter: 1857 | loss: 4.476371
iter: 1858 | loss: 4.476178
iter: 1859 | loss: 4.475985
iter: 1860 | loss: 4.475791
iter: 1861 | loss: 4.475598
iter: 1862 | loss: 4.475404
iter: 1863 | loss: 4.475211
iter: 1864 | loss: 4.475018
iter: 1865 | loss: 4.474824
iter: 1866 | loss: 4.474631
iter: 1867 | loss: 4.474437
iter: 1868 | loss: 4.474244
iter: 1869 | loss: 4.474051
iter: 1870 | loss: 4.473857
iter: 1871 | loss: 4.473664
iter: 1872 | loss: 4.473471
iter: 1873 | loss: 4.473277
iter: 1874 | loss: 4.473084
iter: 1875 | loss: 4.472890
iter: 1876 | loss: 4.472697
iter: 1877 | loss: 4.472504
iter: 1878 | loss: 4.472310
iter: 1879 | loss: 4.472117
iter: 1880 | loss: 4.471923
iter: 1881 | loss: 4.471730
iter: 1882 | loss: 4.471537
iter: 1883 | loss: 4.471343
iter: 1884 | loss: 4.471150
iter: 1885 | loss: 4.470956
iter: 1886 | loss: 4.470763
iter: 1887 | loss: 4.470570
iter: 1888 | loss: 4.470376
iter: 1889 | loss: 4.470183
iter: 1890 | loss: 4.469990
iter: 1891 | loss: 4.469796
iter: 1892 | loss: 4.469603
iter: 1893 | loss: 4.469409
iter: 1894 | loss: 4.469216
iter: 1895 | loss: 4.469023
iter: 1896 | loss: 4.468829
iter: 1897 | loss: 4.468636
iter: 1898 | loss: 4.468442
iter: 1899 | loss: 4.468249
iter: 1900 | loss: 4.468056
iter: 1901 | loss: 4.467862
iter: 1902 | loss: 4.467669
iter: 1903 | loss: 4.467476
iter: 1904 | loss: 4.467282
iter: 1905 | loss: 4.467089
iter: 1906 | loss: 4.466895
iter: 1907 | loss: 4.466702
iter: 1908 | loss: 4.466509
iter: 1909 | loss: 4.466315
iter: 1910 | loss: 4.466122
iter: 1911 | loss: 4.465928
iter: 1912 | loss: 4.465735
iter: 1913 | loss: 4.465542
iter: 1914 | loss: 4.465348
iter: 1915 | loss: 4.465155
iter: 1916 | loss: 4.464961
iter: 1917 | loss: 4.464768
iter: 1918 | loss: 4.464575
iter: 1919 | loss: 4.464381
iter: 1920 | loss: 4.464188
iter: 1921 | loss: 4.463995
iter: 1922 | loss: 4.463801
iter: 1923 | loss: 4.463608
iter: 1924 | loss: 4.463414
iter: 1925 | loss: 4.463221
iter: 1926 | loss: 4.463028
iter: 1927 | loss: 4.462834
iter: 1928 | loss: 4.462641
iter: 1929 | loss: 4.462447
iter: 1930 | loss: 4.462254
iter: 1931 | loss: 4.462061
iter: 1932 | loss: 4.461867
iter: 1933 | loss: 4.461674
iter: 1934 | loss: 4.461481
iter: 1935 | loss: 4.461287
iter: 1936 | loss: 4.461094
iter: 1937 | loss: 4.460900
iter: 1938 | loss: 4.460707
iter: 1939 | loss: 4.460514
iter: 1940 | loss: 4.460320
iter: 1941 | loss: 4.460127
iter: 1942 | loss: 4.459933
iter: 1943 | loss: 4.459740
iter: 1944 | loss: 4.459547
iter: 1945 | loss: 4.459353
iter: 1946 | loss: 4.459160
iter: 1947 | loss: 4.458966
iter: 1948 | loss: 4.458773
iter: 1949 | loss: 4.458580
iter: 1950 | loss: 4.458386
iter: 1951 | loss: 4.458193
iter: 1952 | loss: 4.458000
iter: 1953 | loss: 4.457806
iter: 1954 | loss: 4.457613
iter: 1955 | loss: 4.457419
iter: 1956 | loss: 4.457226
iter: 1957 | loss: 4.457033
iter: 1958 | loss: 4.456839
iter: 1959 | loss: 4.456646
iter: 1960 | loss: 4.456452
iter: 1961 | loss: 4.456259
iter: 1962 | loss: 4.456066
iter: 1963 | loss: 4.455872
iter: 1964 | loss: 4.455679
iter: 1965 | loss: 4.455486
iter: 1966 | loss: 4.455292
iter: 1967 | loss: 4.455099
iter: 1968 | loss: 4.454905
iter: 1969 | loss: 4.454712
iter: 1970 | loss: 4.454519
iter: 1971 | loss: 4.454325
iter: 1972 | loss: 4.454132
iter: 1973 | loss: 4.453938
iter: 1974 | loss: 4.453745
iter: 1975 | loss: 4.453552
iter: 1976 | loss: 4.453358
iter: 1977 | loss: 4.453165
iter: 1978 | loss: 4.452971
iter: 1979 | loss: 4.452778
iter: 1980 | loss: 4.452585
iter: 1981 | loss: 4.452391
iter: 1982 | loss: 4.452198
iter: 1983 | loss: 4.452005
iter: 1984 | loss: 4.451811
iter: 1985 | loss: 4.451618
iter: 1986 | loss: 4.451424
iter: 1987 | loss: 4.451231
iter: 1988 | loss: 4.451038
iter: 1989 | loss: 4.450844
iter: 1990 | loss: 4.450651
iter: 1991 | loss: 4.450457
iter: 1992 | loss: 4.450264
iter: 1993 | loss: 4.450071
iter: 1994 | loss: 4.449877
iter: 1995 | loss: 4.449684
iter: 1996 | loss: 4.449491
iter: 1997 | loss: 4.449297
iter: 1998 | loss: 4.449104
iter: 1999 | loss: 4.448910
iter: 2000 | loss: 4.448717
iter: 2001 | loss: 4.448524
iter: 2002 | loss: 4.448330
iter: 2003 | loss: 4.448137
iter: 2004 | loss: 4.447943
iter: 2005 | loss: 4.447750
iter: 2006 | loss: 4.447557
iter: 2007 | loss: 4.447363
iter: 2008 | loss: 4.447170
iter: 2009 | loss: 4.446977
iter: 2010 | loss: 4.446783
iter: 2011 | loss: 4.446590
iter: 2012 | loss: 4.446396
iter: 2013 | loss: 4.446203
iter: 2014 | loss: 4.446010
iter: 2015 | loss: 4.445816
iter: 2016 | loss: 4.445623
iter: 2017 | loss: 4.445429
iter: 2018 | loss: 4.445236
iter: 2019 | loss: 4.445043
iter: 2020 | loss: 4.444849
iter: 2021 | loss: 4.444656
iter: 2022 | loss: 4.444462
iter: 2023 | loss: 4.444269
iter: 2024 | loss: 4.444076
iter: 2025 | loss: 4.443882
iter: 2026 | loss: 4.443689
iter: 2027 | loss: 4.443496
iter: 2028 | loss: 4.443302
iter: 2029 | loss: 4.443109
iter: 2030 | loss: 4.442915
iter: 2031 | loss: 4.442722
iter: 2032 | loss: 4.442529
iter: 2033 | loss: 4.442335
iter: 2034 | loss: 4.442142
iter: 2035 | loss: 4.441948
iter: 2036 | loss: 4.441755
iter: 2037 | loss: 4.441562
iter: 2038 | loss: 4.441368
iter: 2039 | loss: 4.441175
iter: 2040 | loss: 4.440982
iter: 2041 | loss: 4.440788
iter: 2042 | loss: 4.440595
iter: 2043 | loss: 4.440401
iter: 2044 | loss: 4.440208
iter: 2045 | loss: 4.440015
iter: 2046 | loss: 4.439821
iter: 2047 | loss: 4.439628
iter: 2048 | loss: 4.439434
iter: 2049 | loss: 4.439241
iter: 2050 | loss: 4.439048
iter: 2051 | loss: 4.438854
iter: 2052 | loss: 4.438661
iter: 2053 | loss: 4.438467
iter: 2054 | loss: 4.438274
iter: 2055 | loss: 4.438081
iter: 2056 | loss: 4.437887
iter: 2057 | loss: 4.437694
iter: 2058 | loss: 4.437501
iter: 2059 | loss: 4.437307
iter: 2060 | loss: 4.437114
iter: 2061 | loss: 4.436920
iter: 2062 | loss: 4.436727
iter: 2063 | loss: 4.436534
iter: 2064 | loss: 4.436340
iter: 2065 | loss: 4.436147
iter: 2066 | loss: 4.435953
iter: 2067 | loss: 4.435760
iter: 2068 | loss: 4.435567
iter: 2069 | loss: 4.435373
iter: 2070 | loss: 4.435180
iter: 2071 | loss: 4.434987
iter: 2072 | loss: 4.434793
iter: 2073 | loss: 4.434600
iter: 2074 | loss: 4.434406
iter: 2075 | loss: 4.434213
iter: 2076 | loss: 4.434020
iter: 2077 | loss: 4.433826
iter: 2078 | loss: 4.433633
iter: 2079 | loss: 4.433439
iter: 2080 | loss: 4.433246
iter: 2081 | loss: 4.433053
iter: 2082 | loss: 4.432859
iter: 2083 | loss: 4.432666
iter: 2084 | loss: 4.432472
iter: 2085 | loss: 4.432279
iter: 2086 | loss: 4.432086
iter: 2087 | loss: 4.431892
iter: 2088 | loss: 4.431699
iter: 2089 | loss: 4.431506
iter: 2090 | loss: 4.431312
iter: 2091 | loss: 4.431119
iter: 2092 | loss: 4.430925
iter: 2093 | loss: 4.430732
iter: 2094 | loss: 4.430539
iter: 2095 | loss: 4.430345
iter: 2096 | loss: 4.430152
iter: 2097 | loss: 4.429958
iter: 2098 | loss: 4.429765
iter: 2099 | loss: 4.429572
iter: 2100 | loss: 4.429378
iter: 2101 | loss: 4.429185
iter: 2102 | loss: 4.428992
iter: 2103 | loss: 4.428798
iter: 2104 | loss: 4.428605
iter: 2105 | loss: 4.428411
iter: 2106 | loss: 4.428218
iter: 2107 | loss: 4.428025
iter: 2108 | loss: 4.427831
iter: 2109 | loss: 4.427638
iter: 2110 | loss: 4.427444
iter: 2111 | loss: 4.427251
iter: 2112 | loss: 4.427058
iter: 2113 | loss: 4.426864
iter: 2114 | loss: 4.426671
iter: 2115 | loss: 4.426477
iter: 2116 | loss: 4.426284
iter: 2117 | loss: 4.426091
iter: 2118 | loss: 4.425897
iter: 2119 | loss: 4.425704
iter: 2120 | loss: 4.425511
iter: 2121 | loss: 4.425317
iter: 2122 | loss: 4.425124
iter: 2123 | loss: 4.424930
iter: 2124 | loss: 4.424737
iter: 2125 | loss: 4.424544
iter: 2126 | loss: 4.424350
iter: 2127 | loss: 4.424157
iter: 2128 | loss: 4.423963
iter: 2129 | loss: 4.423770
iter: 2130 | loss: 4.423577
iter: 2131 | loss: 4.423383
iter: 2132 | loss: 4.423190
iter: 2133 | loss: 4.422997
iter: 2134 | loss: 4.422803
iter: 2135 | loss: 4.422610
iter: 2136 | loss: 4.422416
iter: 2137 | loss: 4.422223
iter: 2138 | loss: 4.422030
iter: 2139 | loss: 4.421836
iter: 2140 | loss: 4.421643
iter: 2141 | loss: 4.421449
iter: 2142 | loss: 4.421256
iter: 2143 | loss: 4.421063
iter: 2144 | loss: 4.420869
iter: 2145 | loss: 4.420676
iter: 2146 | loss: 4.420482
iter: 2147 | loss: 4.420289
iter: 2148 | loss: 4.420096
iter: 2149 | loss: 4.419902
iter: 2150 | loss: 4.419709
iter: 2151 | loss: 4.419516
iter: 2152 | loss: 4.419322
iter: 2153 | loss: 4.419129
iter: 2154 | loss: 4.418935
iter: 2155 | loss: 4.418742
iter: 2156 | loss: 4.418549
iter: 2157 | loss: 4.418355
iter: 2158 | loss: 4.418162
iter: 2159 | loss: 4.417968
iter: 2160 | loss: 4.417775
iter: 2161 | loss: 4.417582
iter: 2162 | loss: 4.417388
iter: 2163 | loss: 4.417195
iter: 2164 | loss: 4.417002
iter: 2165 | loss: 4.416808
iter: 2166 | loss: 4.416615
iter: 2167 | loss: 4.416421
iter: 2168 | loss: 4.416228
iter: 2169 | loss: 4.416035
iter: 2170 | loss: 4.415841
iter: 2171 | loss: 4.415648
iter: 2172 | loss: 4.415454
iter: 2173 | loss: 4.415261
iter: 2174 | loss: 4.415068
iter: 2175 | loss: 4.414874
iter: 2176 | loss: 4.414681
iter: 2177 | loss: 4.414487
iter: 2178 | loss: 4.414294
iter: 2179 | loss: 4.414101
iter: 2180 | loss: 4.413907
iter: 2181 | loss: 4.413714
iter: 2182 | loss: 4.413521
iter: 2183 | loss: 4.413327
iter: 2184 | loss: 4.413134
iter: 2185 | loss: 4.412940
iter: 2186 | loss: 4.412747
iter: 2187 | loss: 4.412554
iter: 2188 | loss: 4.412360
iter: 2189 | loss: 4.412167
iter: 2190 | loss: 4.411973
iter: 2191 | loss: 4.411780
iter: 2192 | loss: 4.411587
iter: 2193 | loss: 4.411393
iter: 2194 | loss: 4.411200
iter: 2195 | loss: 4.411007
iter: 2196 | loss: 4.410813
iter: 2197 | loss: 4.410620
iter: 2198 | loss: 4.410426
iter: 2199 | loss: 4.410233
iter: 2200 | loss: 4.410040
iter: 2201 | loss: 4.409846
iter: 2202 | loss: 4.409653
iter: 2203 | loss: 4.409459
iter: 2204 | loss: 4.409266
iter: 2205 | loss: 4.409073
iter: 2206 | loss: 4.408879
iter: 2207 | loss: 4.408686
iter: 2208 | loss: 4.408492
iter: 2209 | loss: 4.408299
iter: 2210 | loss: 4.408106
iter: 2211 | loss: 4.407912
iter: 2212 | loss: 4.407719
iter: 2213 | loss: 4.407526
iter: 2214 | loss: 4.407332
iter: 2215 | loss: 4.407139
iter: 2216 | loss: 4.406945
iter: 2217 | loss: 4.406752
iter: 2218 | loss: 4.406559
iter: 2219 | loss: 4.406365
iter: 2220 | loss: 4.406172
iter: 2221 | loss: 4.405978
iter: 2222 | loss: 4.405785
iter: 2223 | loss: 4.405592
iter: 2224 | loss: 4.405398
iter: 2225 | loss: 4.405205
iter: 2226 | loss: 4.405012
iter: 2227 | loss: 4.404818
iter: 2228 | loss: 4.404625
iter: 2229 | loss: 4.404431
iter: 2230 | loss: 4.404238
iter: 2231 | loss: 4.404045
iter: 2232 | loss: 4.403851
iter: 2233 | loss: 4.403658
iter: 2234 | loss: 4.403464
iter: 2235 | loss: 4.403271
iter: 2236 | loss: 4.403078
iter: 2237 | loss: 4.402884
iter: 2238 | loss: 4.402691
iter: 2239 | loss: 4.402497
iter: 2240 | loss: 4.402304
iter: 2241 | loss: 4.402111
iter: 2242 | loss: 4.401917
iter: 2243 | loss: 4.401724
iter: 2244 | loss: 4.401531
iter: 2245 | loss: 4.401337
iter: 2246 | loss: 4.401144
iter: 2247 | loss: 4.400950
iter: 2248 | loss: 4.400757
iter: 2249 | loss: 4.400564
iter: 2250 | loss: 4.400370
iter: 2251 | loss: 4.400177
iter: 2252 | loss: 4.399983
iter: 2253 | loss: 4.399790
iter: 2254 | loss: 4.399597
iter: 2255 | loss: 4.399403
iter: 2256 | loss: 4.399210
iter: 2257 | loss: 4.399017
iter: 2258 | loss: 4.398823
iter: 2259 | loss: 4.398630
iter: 2260 | loss: 4.398436
iter: 2261 | loss: 4.398243
iter: 2262 | loss: 4.398050
iter: 2263 | loss: 4.397856
iter: 2264 | loss: 4.397663
iter: 2265 | loss: 4.397469
iter: 2266 | loss: 4.397276
iter: 2267 | loss: 4.397083
iter: 2268 | loss: 4.396889
iter: 2269 | loss: 4.396696
iter: 2270 | loss: 4.396502
iter: 2271 | loss: 4.396309
iter: 2272 | loss: 4.396116
iter: 2273 | loss: 4.395922
iter: 2274 | loss: 4.395729
iter: 2275 | loss: 4.395536
iter: 2276 | loss: 4.395342
iter: 2277 | loss: 4.395149
iter: 2278 | loss: 4.394955
iter: 2279 | loss: 4.394762
iter: 2280 | loss: 4.394569
iter: 2281 | loss: 4.394375
iter: 2282 | loss: 4.394182
iter: 2283 | loss: 4.393988
iter: 2284 | loss: 4.393795
iter: 2285 | loss: 4.393602
iter: 2286 | loss: 4.393408
iter: 2287 | loss: 4.393215
iter: 2288 | loss: 4.393022
iter: 2289 | loss: 4.392828
iter: 2290 | loss: 4.392635
iter: 2291 | loss: 4.392441
iter: 2292 | loss: 4.392248
iter: 2293 | loss: 4.392055
iter: 2294 | loss: 4.391861
iter: 2295 | loss: 4.391668
iter: 2296 | loss: 4.391474
iter: 2297 | loss: 4.391281
iter: 2298 | loss: 4.391088
iter: 2299 | loss: 4.390894
iter: 2300 | loss: 4.390701
iter: 2301 | loss: 4.390507
iter: 2302 | loss: 4.390314
iter: 2303 | loss: 4.390121
iter: 2304 | loss: 4.389927
iter: 2305 | loss: 4.389734
iter: 2306 | loss: 4.389541
iter: 2307 | loss: 4.389347
iter: 2308 | loss: 4.389154
iter: 2309 | loss: 4.388960
iter: 2310 | loss: 4.388767
iter: 2311 | loss: 4.388574
iter: 2312 | loss: 4.388380
iter: 2313 | loss: 4.388187
iter: 2314 | loss: 4.387993
iter: 2315 | loss: 4.387800
iter: 2316 | loss: 4.387607
iter: 2317 | loss: 4.387413
iter: 2318 | loss: 4.387220
iter: 2319 | loss: 4.387027
iter: 2320 | loss: 4.386833
iter: 2321 | loss: 4.386640
iter: 2322 | loss: 4.386446
iter: 2323 | loss: 4.386253
iter: 2324 | loss: 4.386060
iter: 2325 | loss: 4.385866
iter: 2326 | loss: 4.385673
iter: 2327 | loss: 4.385479
iter: 2328 | loss: 4.385286
iter: 2329 | loss: 4.385093
iter: 2330 | loss: 4.384899
iter: 2331 | loss: 4.384706
iter: 2332 | loss: 4.384513
iter: 2333 | loss: 4.384319
iter: 2334 | loss: 4.384126
iter: 2335 | loss: 4.383932
iter: 2336 | loss: 4.383739
iter: 2337 | loss: 4.383546
iter: 2338 | loss: 4.383352
iter: 2339 | loss: 4.383159
iter: 2340 | loss: 4.382965
iter: 2341 | loss: 4.382772
iter: 2342 | loss: 4.382579
iter: 2343 | loss: 4.382385
iter: 2344 | loss: 4.382192
iter: 2345 | loss: 4.381998
iter: 2346 | loss: 4.381805
iter: 2347 | loss: 4.381612
iter: 2348 | loss: 4.381418
iter: 2349 | loss: 4.381225
iter: 2350 | loss: 4.381032
iter: 2351 | loss: 4.380838
iter: 2352 | loss: 4.380645
iter: 2353 | loss: 4.380451
iter: 2354 | loss: 4.380258
iter: 2355 | loss: 4.380065
iter: 2356 | loss: 4.379871
iter: 2357 | loss: 4.379678
iter: 2358 | loss: 4.379484
iter: 2359 | loss: 4.379291
iter: 2360 | loss: 4.379098
iter: 2361 | loss: 4.378904
iter: 2362 | loss: 4.378711
iter: 2363 | loss: 4.378518
iter: 2364 | loss: 4.378324
iter: 2365 | loss: 4.378131
iter: 2366 | loss: 4.377937
iter: 2367 | loss: 4.377744
iter: 2368 | loss: 4.377551
iter: 2369 | loss: 4.377357
iter: 2370 | loss: 4.377164
iter: 2371 | loss: 4.376970
iter: 2372 | loss: 4.376777
iter: 2373 | loss: 4.376584
iter: 2374 | loss: 4.376390
iter: 2375 | loss: 4.376197
iter: 2376 | loss: 4.376003
iter: 2377 | loss: 4.375810
iter: 2378 | loss: 4.375617
iter: 2379 | loss: 4.375423
iter: 2380 | loss: 4.375230
iter: 2381 | loss: 4.375037
iter: 2382 | loss: 4.374843
iter: 2383 | loss: 4.374650
iter: 2384 | loss: 4.374456
iter: 2385 | loss: 4.374263
iter: 2386 | loss: 4.374070
iter: 2387 | loss: 4.373876
iter: 2388 | loss: 4.373683
iter: 2389 | loss: 4.373489
iter: 2390 | loss: 4.373296
iter: 2391 | loss: 4.373103
iter: 2392 | loss: 4.372909
iter: 2393 | loss: 4.372716
iter: 2394 | loss: 4.372523
iter: 2395 | loss: 4.372329
iter: 2396 | loss: 4.372136
iter: 2397 | loss: 4.371942
iter: 2398 | loss: 4.371749
iter: 2399 | loss: 4.371556
iter: 2400 | loss: 4.371362
iter: 2401 | loss: 4.371169
iter: 2402 | loss: 4.370975
iter: 2403 | loss: 4.370782
iter: 2404 | loss: 4.370589
iter: 2405 | loss: 4.370395
iter: 2406 | loss: 4.370202
iter: 2407 | loss: 4.370008
iter: 2408 | loss: 4.369815
iter: 2409 | loss: 4.369622
iter: 2410 | loss: 4.369428
iter: 2411 | loss: 4.369235
iter: 2412 | loss: 4.369042
iter: 2413 | loss: 4.368848
iter: 2414 | loss: 4.368655
iter: 2415 | loss: 4.368461
iter: 2416 | loss: 4.368268
iter: 2417 | loss: 4.368075
iter: 2418 | loss: 4.367881
iter: 2419 | loss: 4.367688
iter: 2420 | loss: 4.367494
iter: 2421 | loss: 4.367301
iter: 2422 | loss: 4.367108
iter: 2423 | loss: 4.366914
iter: 2424 | loss: 4.366721
iter: 2425 | loss: 4.366528
iter: 2426 | loss: 4.366334
iter: 2427 | loss: 4.366141
iter: 2428 | loss: 4.365947
iter: 2429 | loss: 4.365754
iter: 2430 | loss: 4.365561
iter: 2431 | loss: 4.365367
iter: 2432 | loss: 4.365174
iter: 2433 | loss: 4.364980
iter: 2434 | loss: 4.364787
iter: 2435 | loss: 4.364594
iter: 2436 | loss: 4.364400
iter: 2437 | loss: 4.364207
iter: 2438 | loss: 4.364013
iter: 2439 | loss: 4.363820
iter: 2440 | loss: 4.363627
iter: 2441 | loss: 4.363433
iter: 2442 | loss: 4.363240
iter: 2443 | loss: 4.363047
iter: 2444 | loss: 4.362853
iter: 2445 | loss: 4.362660
iter: 2446 | loss: 4.362466
iter: 2447 | loss: 4.362273
iter: 2448 | loss: 4.362080
iter: 2449 | loss: 4.361886
iter: 2450 | loss: 4.361693
iter: 2451 | loss: 4.361499
iter: 2452 | loss: 4.361306
iter: 2453 | loss: 4.361113
iter: 2454 | loss: 4.360919
iter: 2455 | loss: 4.360726
iter: 2456 | loss: 4.360533
iter: 2457 | loss: 4.360339
iter: 2458 | loss: 4.360146
iter: 2459 | loss: 4.359952
iter: 2460 | loss: 4.359759
iter: 2461 | loss: 4.359566
iter: 2462 | loss: 4.359372
iter: 2463 | loss: 4.359179
iter: 2464 | loss: 4.358985
iter: 2465 | loss: 4.358792
iter: 2466 | loss: 4.358599
iter: 2467 | loss: 4.358405
iter: 2468 | loss: 4.358212
iter: 2469 | loss: 4.358018
iter: 2470 | loss: 4.357825
iter: 2471 | loss: 4.357632
iter: 2472 | loss: 4.357438
iter: 2473 | loss: 4.357245
iter: 2474 | loss: 4.357052
iter: 2475 | loss: 4.356858
iter: 2476 | loss: 4.356665
iter: 2477 | loss: 4.356471
iter: 2478 | loss: 4.356278
iter: 2479 | loss: 4.356085
iter: 2480 | loss: 4.355891
iter: 2481 | loss: 4.355698
iter: 2482 | loss: 4.355504
iter: 2483 | loss: 4.355311
iter: 2484 | loss: 4.355118
iter: 2485 | loss: 4.354924
iter: 2486 | loss: 4.354731
iter: 2487 | loss: 4.354538
iter: 2488 | loss: 4.354344
iter: 2489 | loss: 4.354151
iter: 2490 | loss: 4.353957
iter: 2491 | loss: 4.353764
iter: 2492 | loss: 4.353571
iter: 2493 | loss: 4.353377
iter: 2494 | loss: 4.353184
iter: 2495 | loss: 4.352990
iter: 2496 | loss: 4.352797
iter: 2497 | loss: 4.352604
iter: 2498 | loss: 4.352410
iter: 2499 | loss: 4.352217
iter: 2500 | loss: 4.352023
iter: 2501 | loss: 4.351830
iter: 2502 | loss: 4.351637
iter: 2503 | loss: 4.351443
iter: 2504 | loss: 4.351250
iter: 2505 | loss: 4.351057
iter: 2506 | loss: 4.350863
iter: 2507 | loss: 4.350670
iter: 2508 | loss: 4.350476
iter: 2509 | loss: 4.350283
iter: 2510 | loss: 4.350090
iter: 2511 | loss: 4.349896
iter: 2512 | loss: 4.349703
iter: 2513 | loss: 4.349509
iter: 2514 | loss: 4.349316
iter: 2515 | loss: 4.349123
iter: 2516 | loss: 4.348929
iter: 2517 | loss: 4.348736
iter: 2518 | loss: 4.348543
iter: 2519 | loss: 4.348349
iter: 2520 | loss: 4.348156
iter: 2521 | loss: 4.347962
iter: 2522 | loss: 4.347769
iter: 2523 | loss: 4.347576
iter: 2524 | loss: 4.347382
iter: 2525 | loss: 4.347189
iter: 2526 | loss: 4.346995
iter: 2527 | loss: 4.346802
iter: 2528 | loss: 4.346609
iter: 2529 | loss: 4.346415
iter: 2530 | loss: 4.346222
iter: 2531 | loss: 4.346028
iter: 2532 | loss: 4.345835
iter: 2533 | loss: 4.345642
iter: 2534 | loss: 4.345448
iter: 2535 | loss: 4.345255
iter: 2536 | loss: 4.345062
iter: 2537 | loss: 4.344868
iter: 2538 | loss: 4.344675
iter: 2539 | loss: 4.344481
iter: 2540 | loss: 4.344288
iter: 2541 | loss: 4.344095
iter: 2542 | loss: 4.343901
iter: 2543 | loss: 4.343708
iter: 2544 | loss: 4.343514
iter: 2545 | loss: 4.343321
iter: 2546 | loss: 4.343128
iter: 2547 | loss: 4.342934
iter: 2548 | loss: 4.342741
iter: 2549 | loss: 4.342548
iter: 2550 | loss: 4.342354
iter: 2551 | loss: 4.342161
iter: 2552 | loss: 4.341967
iter: 2553 | loss: 4.341774
iter: 2554 | loss: 4.341581
iter: 2555 | loss: 4.341387
iter: 2556 | loss: 4.341194
iter: 2557 | loss: 4.341000
iter: 2558 | loss: 4.340807
iter: 2559 | loss: 4.340614
iter: 2560 | loss: 4.340420
iter: 2561 | loss: 4.340227
iter: 2562 | loss: 4.340033
iter: 2563 | loss: 4.339840
iter: 2564 | loss: 4.339647
iter: 2565 | loss: 4.339453
iter: 2566 | loss: 4.339260
iter: 2567 | loss: 4.339067
iter: 2568 | loss: 4.338873
iter: 2569 | loss: 4.338680
iter: 2570 | loss: 4.338486
iter: 2571 | loss: 4.338293
iter: 2572 | loss: 4.338100
iter: 2573 | loss: 4.337906
iter: 2574 | loss: 4.337713
iter: 2575 | loss: 4.337519
iter: 2576 | loss: 4.337326
iter: 2577 | loss: 4.337133
iter: 2578 | loss: 4.336939
iter: 2579 | loss: 4.336746
iter: 2580 | loss: 4.336553
iter: 2581 | loss: 4.336359
iter: 2582 | loss: 4.336166
iter: 2583 | loss: 4.335972
iter: 2584 | loss: 4.335779
iter: 2585 | loss: 4.335586
iter: 2586 | loss: 4.335392
iter: 2587 | loss: 4.335199
iter: 2588 | loss: 4.335005
iter: 2589 | loss: 4.334812
iter: 2590 | loss: 4.334619
iter: 2591 | loss: 4.334425
iter: 2592 | loss: 4.334232
iter: 2593 | loss: 4.334038
iter: 2594 | loss: 4.333845
iter: 2595 | loss: 4.333652
iter: 2596 | loss: 4.333458
iter: 2597 | loss: 4.333265
iter: 2598 | loss: 4.333072
iter: 2599 | loss: 4.332878
iter: 2600 | loss: 4.332685
iter: 2601 | loss: 4.332491
iter: 2602 | loss: 4.332298
iter: 2603 | loss: 4.332105
iter: 2604 | loss: 4.331911
iter: 2605 | loss: 4.331718
iter: 2606 | loss: 4.331524
iter: 2607 | loss: 4.331331
iter: 2608 | loss: 4.331138
iter: 2609 | loss: 4.330944
iter: 2610 | loss: 4.330751
iter: 2611 | loss: 4.330558
iter: 2612 | loss: 4.330364
iter: 2613 | loss: 4.330171
iter: 2614 | loss: 4.329977
iter: 2615 | loss: 4.329784
iter: 2616 | loss: 4.329591
iter: 2617 | loss: 4.329397
iter: 2618 | loss: 4.329204
iter: 2619 | loss: 4.329010
iter: 2620 | loss: 4.328817
iter: 2621 | loss: 4.328624
iter: 2622 | loss: 4.328430
iter: 2623 | loss: 4.328237
iter: 2624 | loss: 4.328043
iter: 2625 | loss: 4.327850
iter: 2626 | loss: 4.327657
iter: 2627 | loss: 4.327463
iter: 2628 | loss: 4.327270
iter: 2629 | loss: 4.327077
iter: 2630 | loss: 4.326883
iter: 2631 | loss: 4.326690
iter: 2632 | loss: 4.326496
iter: 2633 | loss: 4.326303
iter: 2634 | loss: 4.326110
iter: 2635 | loss: 4.325916
iter: 2636 | loss: 4.325723
iter: 2637 | loss: 4.325529
iter: 2638 | loss: 4.325336
iter: 2639 | loss: 4.325143
iter: 2640 | loss: 4.324949
iter: 2641 | loss: 4.324756
iter: 2642 | loss: 4.324563
iter: 2643 | loss: 4.324369
iter: 2644 | loss: 4.324176
iter: 2645 | loss: 4.323982
iter: 2646 | loss: 4.323789
iter: 2647 | loss: 4.323596
iter: 2648 | loss: 4.323402
iter: 2649 | loss: 4.323209
iter: 2650 | loss: 4.323015
iter: 2651 | loss: 4.322822
iter: 2652 | loss: 4.322629
iter: 2653 | loss: 4.322435
iter: 2654 | loss: 4.322242
iter: 2655 | loss: 4.322049
iter: 2656 | loss: 4.321855
iter: 2657 | loss: 4.321662
iter: 2658 | loss: 4.321468
iter: 2659 | loss: 4.321275
iter: 2660 | loss: 4.321082
iter: 2661 | loss: 4.320888
iter: 2662 | loss: 4.320695
iter: 2663 | loss: 4.320501
iter: 2664 | loss: 4.320308
iter: 2665 | loss: 4.320115
iter: 2666 | loss: 4.319921
iter: 2667 | loss: 4.319728
iter: 2668 | loss: 4.319534
iter: 2669 | loss: 4.319341
iter: 2670 | loss: 4.319148
iter: 2671 | loss: 4.318954
iter: 2672 | loss: 4.318761
iter: 2673 | loss: 4.318568
iter: 2674 | loss: 4.318374
iter: 2675 | loss: 4.318181
iter: 2676 | loss: 4.317987
iter: 2677 | loss: 4.317794
iter: 2678 | loss: 4.317601
iter: 2679 | loss: 4.317407
iter: 2680 | loss: 4.317214
iter: 2681 | loss: 4.317020
iter: 2682 | loss: 4.316827
iter: 2683 | loss: 4.316634
iter: 2684 | loss: 4.316440
iter: 2685 | loss: 4.316247
iter: 2686 | loss: 4.316054
iter: 2687 | loss: 4.315860
iter: 2688 | loss: 4.315667
iter: 2689 | loss: 4.315473
iter: 2690 | loss: 4.315280
iter: 2691 | loss: 4.315087
iter: 2692 | loss: 4.314893
iter: 2693 | loss: 4.314700
iter: 2694 | loss: 4.314506
iter: 2695 | loss: 4.314313
iter: 2696 | loss: 4.314120
iter: 2697 | loss: 4.313926
iter: 2698 | loss: 4.313733
iter: 2699 | loss: 4.313539
iter: 2700 | loss: 4.313346
iter: 2701 | loss: 4.313153
iter: 2702 | loss: 4.312959
iter: 2703 | loss: 4.312766
iter: 2704 | loss: 4.312573
iter: 2705 | loss: 4.312379
iter: 2706 | loss: 4.312186
iter: 2707 | loss: 4.311992
iter: 2708 | loss: 4.311799
iter: 2709 | loss: 4.311606
iter: 2710 | loss: 4.311412
iter: 2711 | loss: 4.311219
iter: 2712 | loss: 4.311025
iter: 2713 | loss: 4.310832
iter: 2714 | loss: 4.310639
iter: 2715 | loss: 4.310445
iter: 2716 | loss: 4.310252
iter: 2717 | loss: 4.310059
iter: 2718 | loss: 4.309865
iter: 2719 | loss: 4.309672
iter: 2720 | loss: 4.309478
iter: 2721 | loss: 4.309285
iter: 2722 | loss: 4.309092
iter: 2723 | loss: 4.308898
iter: 2724 | loss: 4.308705
iter: 2725 | loss: 4.308511
iter: 2726 | loss: 4.308318
iter: 2727 | loss: 4.308125
iter: 2728 | loss: 4.307931
iter: 2729 | loss: 4.307738
iter: 2730 | loss: 4.307544
iter: 2731 | loss: 4.307351
iter: 2732 | loss: 4.307158
iter: 2733 | loss: 4.306964
iter: 2734 | loss: 4.306771
iter: 2735 | loss: 4.306578
iter: 2736 | loss: 4.306384
iter: 2737 | loss: 4.306191
iter: 2738 | loss: 4.305997
iter: 2739 | loss: 4.305804
iter: 2740 | loss: 4.305611
iter: 2741 | loss: 4.305417
iter: 2742 | loss: 4.305224
iter: 2743 | loss: 4.305030
iter: 2744 | loss: 4.304837
iter: 2745 | loss: 4.304644
iter: 2746 | loss: 4.304450
iter: 2747 | loss: 4.304257
iter: 2748 | loss: 4.304064
iter: 2749 | loss: 4.303870
iter: 2750 | loss: 4.303677
iter: 2751 | loss: 4.303483
iter: 2752 | loss: 4.303290
iter: 2753 | loss: 4.303097
iter: 2754 | loss: 4.302903
iter: 2755 | loss: 4.302710
iter: 2756 | loss: 4.302516
iter: 2757 | loss: 4.302323
iter: 2758 | loss: 4.302130
iter: 2759 | loss: 4.301936
iter: 2760 | loss: 4.301743
iter: 2761 | loss: 4.301549
iter: 2762 | loss: 4.301356
iter: 2763 | loss: 4.301163
iter: 2764 | loss: 4.300969
iter: 2765 | loss: 4.300776
iter: 2766 | loss: 4.300583
iter: 2767 | loss: 4.300389
iter: 2768 | loss: 4.300196
iter: 2769 | loss: 4.300002
iter: 2770 | loss: 4.299809
iter: 2771 | loss: 4.299616
iter: 2772 | loss: 4.299422
iter: 2773 | loss: 4.299229
iter: 2774 | loss: 4.299035
iter: 2775 | loss: 4.298842
iter: 2776 | loss: 4.298649
iter: 2777 | loss: 4.298455
iter: 2778 | loss: 4.298262
iter: 2779 | loss: 4.298069
iter: 2780 | loss: 4.297875
iter: 2781 | loss: 4.297682
iter: 2782 | loss: 4.297488
iter: 2783 | loss: 4.297295
iter: 2784 | loss: 4.297102
iter: 2785 | loss: 4.296908
iter: 2786 | loss: 4.296715
iter: 2787 | loss: 4.296521
iter: 2788 | loss: 4.296328
iter: 2789 | loss: 4.296135
iter: 2790 | loss: 4.295941
iter: 2791 | loss: 4.295748
iter: 2792 | loss: 4.295554
iter: 2793 | loss: 4.295361
iter: 2794 | loss: 4.295168
iter: 2795 | loss: 4.294974
iter: 2796 | loss: 4.294781
iter: 2797 | loss: 4.294588
iter: 2798 | loss: 4.294394
iter: 2799 | loss: 4.294201
iter: 2800 | loss: 4.294007
iter: 2801 | loss: 4.293814
iter: 2802 | loss: 4.293621
iter: 2803 | loss: 4.293427
iter: 2804 | loss: 4.293234
iter: 2805 | loss: 4.293040
iter: 2806 | loss: 4.292847
iter: 2807 | loss: 4.292654
iter: 2808 | loss: 4.292460
iter: 2809 | loss: 4.292267
iter: 2810 | loss: 4.292074
iter: 2811 | loss: 4.291880
iter: 2812 | loss: 4.291687
iter: 2813 | loss: 4.291493
iter: 2814 | loss: 4.291300
iter: 2815 | loss: 4.291107
iter: 2816 | loss: 4.290913
iter: 2817 | loss: 4.290720
iter: 2818 | loss: 4.290526
iter: 2819 | loss: 4.290333
iter: 2820 | loss: 4.290140
iter: 2821 | loss: 4.289946
iter: 2822 | loss: 4.289753
iter: 2823 | loss: 4.289559
iter: 2824 | loss: 4.289366
iter: 2825 | loss: 4.289173
iter: 2826 | loss: 4.288979
iter: 2827 | loss: 4.288786
iter: 2828 | loss: 4.288593
iter: 2829 | loss: 4.288399
iter: 2830 | loss: 4.288206
iter: 2831 | loss: 4.288012
iter: 2832 | loss: 4.287819
iter: 2833 | loss: 4.287626
iter: 2834 | loss: 4.287432
iter: 2835 | loss: 4.287239
iter: 2836 | loss: 4.287045
iter: 2837 | loss: 4.286852
iter: 2838 | loss: 4.286659
iter: 2839 | loss: 4.286465
iter: 2840 | loss: 4.286272
iter: 2841 | loss: 4.286079
iter: 2842 | loss: 4.285885
iter: 2843 | loss: 4.285692
iter: 2844 | loss: 4.285498
iter: 2845 | loss: 4.285305
iter: 2846 | loss: 4.285112
iter: 2847 | loss: 4.284918
iter: 2848 | loss: 4.284725
iter: 2849 | loss: 4.284531
iter: 2850 | loss: 4.284338
iter: 2851 | loss: 4.284145
iter: 2852 | loss: 4.283951
iter: 2853 | loss: 4.283758
iter: 2854 | loss: 4.283564
iter: 2855 | loss: 4.283371
iter: 2856 | loss: 4.283178
iter: 2857 | loss: 4.282984
iter: 2858 | loss: 4.282791
iter: 2859 | loss: 4.282598
iter: 2860 | loss: 4.282404
iter: 2861 | loss: 4.282211
iter: 2862 | loss: 4.282017
iter: 2863 | loss: 4.281824
iter: 2864 | loss: 4.281631
iter: 2865 | loss: 4.281437
iter: 2866 | loss: 4.281244
iter: 2867 | loss: 4.281050
iter: 2868 | loss: 4.280857
iter: 2869 | loss: 4.280664
iter: 2870 | loss: 4.280470
iter: 2871 | loss: 4.280277
iter: 2872 | loss: 4.280084
iter: 2873 | loss: 4.279890
iter: 2874 | loss: 4.279697
iter: 2875 | loss: 4.279503
iter: 2876 | loss: 4.279310
iter: 2877 | loss: 4.279117
iter: 2878 | loss: 4.278923
iter: 2879 | loss: 4.278730
iter: 2880 | loss: 4.278536
iter: 2881 | loss: 4.278343
iter: 2882 | loss: 4.278150
iter: 2883 | loss: 4.277956
iter: 2884 | loss: 4.277763
iter: 2885 | loss: 4.277569
iter: 2886 | loss: 4.277376
iter: 2887 | loss: 4.277183
iter: 2888 | loss: 4.276989
iter: 2889 | loss: 4.276796
iter: 2890 | loss: 4.276603
iter: 2891 | loss: 4.276409
iter: 2892 | loss: 4.276216
iter: 2893 | loss: 4.276022
iter: 2894 | loss: 4.275829
iter: 2895 | loss: 4.275636
iter: 2896 | loss: 4.275442
iter: 2897 | loss: 4.275249
iter: 2898 | loss: 4.275055
iter: 2899 | loss: 4.274862
iter: 2900 | loss: 4.274669
iter: 2901 | loss: 4.274475
iter: 2902 | loss: 4.274282
iter: 2903 | loss: 4.274089
iter: 2904 | loss: 4.273895
iter: 2905 | loss: 4.273702
iter: 2906 | loss: 4.273508
iter: 2907 | loss: 4.273315
iter: 2908 | loss: 4.273122
iter: 2909 | loss: 4.272928
iter: 2910 | loss: 4.272735
iter: 2911 | loss: 4.272541
iter: 2912 | loss: 4.272348
iter: 2913 | loss: 4.272155
iter: 2914 | loss: 4.271961
iter: 2915 | loss: 4.271768
iter: 2916 | loss: 4.271574
iter: 2917 | loss: 4.271381
iter: 2918 | loss: 4.271188
iter: 2919 | loss: 4.270994
iter: 2920 | loss: 4.270801
iter: 2921 | loss: 4.270608
iter: 2922 | loss: 4.270414
iter: 2923 | loss: 4.270221
iter: 2924 | loss: 4.270027
iter: 2925 | loss: 4.269834
iter: 2926 | loss: 4.269641
iter: 2927 | loss: 4.269447
iter: 2928 | loss: 4.269254
iter: 2929 | loss: 4.269060
iter: 2930 | loss: 4.268867
iter: 2931 | loss: 4.268674
iter: 2932 | loss: 4.268480
iter: 2933 | loss: 4.268287
iter: 2934 | loss: 4.268094
iter: 2935 | loss: 4.267900
iter: 2936 | loss: 4.267707
iter: 2937 | loss: 4.267513
iter: 2938 | loss: 4.267320
iter: 2939 | loss: 4.267127
iter: 2940 | loss: 4.266933
iter: 2941 | loss: 4.266740
iter: 2942 | loss: 4.266546
iter: 2943 | loss: 4.266353
iter: 2944 | loss: 4.266160
iter: 2945 | loss: 4.265966
iter: 2946 | loss: 4.265773
iter: 2947 | loss: 4.265579
iter: 2948 | loss: 4.265386
iter: 2949 | loss: 4.265193
iter: 2950 | loss: 4.264999
iter: 2951 | loss: 4.264806
iter: 2952 | loss: 4.264613
iter: 2953 | loss: 4.264419
iter: 2954 | loss: 4.264226
iter: 2955 | loss: 4.264032
iter: 2956 | loss: 4.263839
iter: 2957 | loss: 4.263646
iter: 2958 | loss: 4.263452
iter: 2959 | loss: 4.263259
iter: 2960 | loss: 4.263065
iter: 2961 | loss: 4.262872
iter: 2962 | loss: 4.262679
iter: 2963 | loss: 4.262485
iter: 2964 | loss: 4.262292
iter: 2965 | loss: 4.262099
iter: 2966 | loss: 4.261905
iter: 2967 | loss: 4.261712
iter: 2968 | loss: 4.261518
iter: 2969 | loss: 4.261325
iter: 2970 | loss: 4.261132
iter: 2971 | loss: 4.260938
iter: 2972 | loss: 4.260745
iter: 2973 | loss: 4.260551
iter: 2974 | loss: 4.260358
iter: 2975 | loss: 4.260165
iter: 2976 | loss: 4.259971
iter: 2977 | loss: 4.259778
iter: 2978 | loss: 4.259585
iter: 2979 | loss: 4.259391
iter: 2980 | loss: 4.259198
iter: 2981 | loss: 4.259004
iter: 2982 | loss: 4.258811
iter: 2983 | loss: 4.258618
iter: 2984 | loss: 4.258424
iter: 2985 | loss: 4.258231
iter: 2986 | loss: 4.258037
iter: 2987 | loss: 4.257844
iter: 2988 | loss: 4.257651
iter: 2989 | loss: 4.257457
iter: 2990 | loss: 4.257264
iter: 2991 | loss: 4.257070
iter: 2992 | loss: 4.256877
iter: 2993 | loss: 4.256684
iter: 2994 | loss: 4.256490
iter: 2995 | loss: 4.256297
iter: 2996 | loss: 4.256104
iter: 2997 | loss: 4.255910
iter: 2998 | loss: 4.255717
iter: 2999 | loss: 4.255523
iter: 3000 | loss: 4.255330
iter: 3001 | loss: 4.255137
iter: 3002 | loss: 4.254943
iter: 3003 | loss: 4.254750
iter: 3004 | loss: 4.254556
iter: 3005 | loss: 4.254363
iter: 3006 | loss: 4.254170
iter: 3007 | loss: 4.253976
iter: 3008 | loss: 4.253783
iter: 3009 | loss: 4.253590
iter: 3010 | loss: 4.253396
iter: 3011 | loss: 4.253203
iter: 3012 | loss: 4.253009
iter: 3013 | loss: 4.252816
iter: 3014 | loss: 4.252623
iter: 3015 | loss: 4.252429
iter: 3016 | loss: 4.252236
iter: 3017 | loss: 4.252042
iter: 3018 | loss: 4.251849
iter: 3019 | loss: 4.251656
iter: 3020 | loss: 4.251462
iter: 3021 | loss: 4.251269
iter: 3022 | loss: 4.251075
iter: 3023 | loss: 4.250882
iter: 3024 | loss: 4.250689
iter: 3025 | loss: 4.250495
iter: 3026 | loss: 4.250302
iter: 3027 | loss: 4.250109
iter: 3028 | loss: 4.249915
iter: 3029 | loss: 4.249722
iter: 3030 | loss: 4.249528
iter: 3031 | loss: 4.249335
iter: 3032 | loss: 4.249142
iter: 3033 | loss: 4.248948
iter: 3034 | loss: 4.248755
iter: 3035 | loss: 4.248561
iter: 3036 | loss: 4.248368
iter: 3037 | loss: 4.248175
iter: 3038 | loss: 4.247981
iter: 3039 | loss: 4.247788
iter: 3040 | loss: 4.247595
iter: 3041 | loss: 4.247401
iter: 3042 | loss: 4.247208
iter: 3043 | loss: 4.247014
iter: 3044 | loss: 4.246821
iter: 3045 | loss: 4.246628
iter: 3046 | loss: 4.246434
iter: 3047 | loss: 4.246241
iter: 3048 | loss: 4.246047
iter: 3049 | loss: 4.245854
iter: 3050 | loss: 4.245661
iter: 3051 | loss: 4.245467
iter: 3052 | loss: 4.245274
iter: 3053 | loss: 4.245080
iter: 3054 | loss: 4.244887
iter: 3055 | loss: 4.244694
iter: 3056 | loss: 4.244500
iter: 3057 | loss: 4.244307
iter: 3058 | loss: 4.244114
iter: 3059 | loss: 4.243920
iter: 3060 | loss: 4.243727
iter: 3061 | loss: 4.243533
iter: 3062 | loss: 4.243340
iter: 3063 | loss: 4.243147
iter: 3064 | loss: 4.242953
iter: 3065 | loss: 4.242760
iter: 3066 | loss: 4.242566
iter: 3067 | loss: 4.242373
iter: 3068 | loss: 4.242180
iter: 3069 | loss: 4.241986
iter: 3070 | loss: 4.241793
iter: 3071 | loss: 4.241600
iter: 3072 | loss: 4.241406
iter: 3073 | loss: 4.241213
iter: 3074 | loss: 4.241019
iter: 3075 | loss: 4.240826
iter: 3076 | loss: 4.240633
iter: 3077 | loss: 4.240439
iter: 3078 | loss: 4.240246
iter: 3079 | loss: 4.240052
iter: 3080 | loss: 4.239859
iter: 3081 | loss: 4.239666
iter: 3082 | loss: 4.239472
iter: 3083 | loss: 4.239279
iter: 3084 | loss: 4.239085
iter: 3085 | loss: 4.238892
iter: 3086 | loss: 4.238699
iter: 3087 | loss: 4.238505
iter: 3088 | loss: 4.238312
iter: 3089 | loss: 4.238119
iter: 3090 | loss: 4.237925
iter: 3091 | loss: 4.237732
iter: 3092 | loss: 4.237538
iter: 3093 | loss: 4.237345
iter: 3094 | loss: 4.237152
iter: 3095 | loss: 4.236958
iter: 3096 | loss: 4.236765
iter: 3097 | loss: 4.236571
iter: 3098 | loss: 4.236378
iter: 3099 | loss: 4.236185
iter: 3100 | loss: 4.235991
iter: 3101 | loss: 4.235798
iter: 3102 | loss: 4.235605
iter: 3103 | loss: 4.235411
iter: 3104 | loss: 4.235218
iter: 3105 | loss: 4.235024
iter: 3106 | loss: 4.234831
iter: 3107 | loss: 4.234638
iter: 3108 | loss: 4.234444
iter: 3109 | loss: 4.234251
iter: 3110 | loss: 4.234057
iter: 3111 | loss: 4.233864
iter: 3112 | loss: 4.233671
iter: 3113 | loss: 4.233477
iter: 3114 | loss: 4.233284
iter: 3115 | loss: 4.233090
iter: 3116 | loss: 4.232897
iter: 3117 | loss: 4.232704
iter: 3118 | loss: 4.232510
iter: 3119 | loss: 4.232317
iter: 3120 | loss: 4.232124
iter: 3121 | loss: 4.231930
iter: 3122 | loss: 4.231737
iter: 3123 | loss: 4.231543
iter: 3124 | loss: 4.231350
iter: 3125 | loss: 4.231157
iter: 3126 | loss: 4.230963
iter: 3127 | loss: 4.230770
iter: 3128 | loss: 4.230576
iter: 3129 | loss: 4.230383
iter: 3130 | loss: 4.230190
iter: 3131 | loss: 4.229996
iter: 3132 | loss: 4.229803
iter: 3133 | loss: 4.229610
iter: 3134 | loss: 4.229416
iter: 3135 | loss: 4.229223
iter: 3136 | loss: 4.229029
iter: 3137 | loss: 4.228836
iter: 3138 | loss: 4.228643
iter: 3139 | loss: 4.228449
iter: 3140 | loss: 4.228256
iter: 3141 | loss: 4.228062
iter: 3142 | loss: 4.227869
iter: 3143 | loss: 4.227676
iter: 3144 | loss: 4.227482
iter: 3145 | loss: 4.227289
iter: 3146 | loss: 4.227095
iter: 3147 | loss: 4.226902
iter: 3148 | loss: 4.226709
iter: 3149 | loss: 4.226515
iter: 3150 | loss: 4.226322
iter: 3151 | loss: 4.226129
iter: 3152 | loss: 4.225935
iter: 3153 | loss: 4.225742
iter: 3154 | loss: 4.225548
iter: 3155 | loss: 4.225355
iter: 3156 | loss: 4.225162
iter: 3157 | loss: 4.224968
iter: 3158 | loss: 4.224775
iter: 3159 | loss: 4.224581
iter: 3160 | loss: 4.224388
iter: 3161 | loss: 4.224195
iter: 3162 | loss: 4.224001
iter: 3163 | loss: 4.223808
iter: 3164 | loss: 4.223615
iter: 3165 | loss: 4.223421
iter: 3166 | loss: 4.223228
iter: 3167 | loss: 4.223034
iter: 3168 | loss: 4.222841
iter: 3169 | loss: 4.222648
iter: 3170 | loss: 4.222454
iter: 3171 | loss: 4.222261
iter: 3172 | loss: 4.222067
iter: 3173 | loss: 4.221874
iter: 3174 | loss: 4.221681
iter: 3175 | loss: 4.221487
iter: 3176 | loss: 4.221294
iter: 3177 | loss: 4.221100
iter: 3178 | loss: 4.220907
iter: 3179 | loss: 4.220714
iter: 3180 | loss: 4.220520
iter: 3181 | loss: 4.220327
iter: 3182 | loss: 4.220134
iter: 3183 | loss: 4.219940
iter: 3184 | loss: 4.219747
iter: 3185 | loss: 4.219553
iter: 3186 | loss: 4.219360
iter: 3187 | loss: 4.219167
iter: 3188 | loss: 4.218973
iter: 3189 | loss: 4.218780
iter: 3190 | loss: 4.218586
iter: 3191 | loss: 4.218393
iter: 3192 | loss: 4.218200
iter: 3193 | loss: 4.218006
iter: 3194 | loss: 4.217813
iter: 3195 | loss: 4.217620
iter: 3196 | loss: 4.217426
iter: 3197 | loss: 4.217233
iter: 3198 | loss: 4.217039
iter: 3199 | loss: 4.216846
iter: 3200 | loss: 4.216653
iter: 3201 | loss: 4.216459
iter: 3202 | loss: 4.216266
iter: 3203 | loss: 4.216072
iter: 3204 | loss: 4.215879
iter: 3205 | loss: 4.215686
iter: 3206 | loss: 4.215492
iter: 3207 | loss: 4.215299
iter: 3208 | loss: 4.215105
iter: 3209 | loss: 4.214912
iter: 3210 | loss: 4.214719
iter: 3211 | loss: 4.214525
iter: 3212 | loss: 4.214332
iter: 3213 | loss: 4.214139
iter: 3214 | loss: 4.213945
iter: 3215 | loss: 4.213752
iter: 3216 | loss: 4.213558
iter: 3217 | loss: 4.213365
iter: 3218 | loss: 4.213172
iter: 3219 | loss: 4.212978
iter: 3220 | loss: 4.212785
iter: 3221 | loss: 4.212591
iter: 3222 | loss: 4.212398
iter: 3223 | loss: 4.212205
iter: 3224 | loss: 4.212011
iter: 3225 | loss: 4.211818
iter: 3226 | loss: 4.211625
iter: 3227 | loss: 4.211431
iter: 3228 | loss: 4.211238
iter: 3229 | loss: 4.211044
iter: 3230 | loss: 4.210851
iter: 3231 | loss: 4.210658
iter: 3232 | loss: 4.210464
iter: 3233 | loss: 4.210271
iter: 3234 | loss: 4.210077
iter: 3235 | loss: 4.209884
iter: 3236 | loss: 4.209691
iter: 3237 | loss: 4.209497
iter: 3238 | loss: 4.209304
iter: 3239 | loss: 4.209110
iter: 3240 | loss: 4.208917
iter: 3241 | loss: 4.208724
iter: 3242 | loss: 4.208530
iter: 3243 | loss: 4.208337
iter: 3244 | loss: 4.208144
iter: 3245 | loss: 4.207950
iter: 3246 | loss: 4.207757
iter: 3247 | loss: 4.207563
iter: 3248 | loss: 4.207370
iter: 3249 | loss: 4.207177
iter: 3250 | loss: 4.206983
iter: 3251 | loss: 4.206790
iter: 3252 | loss: 4.206596
iter: 3253 | loss: 4.206403
iter: 3254 | loss: 4.206210
iter: 3255 | loss: 4.206016
iter: 3256 | loss: 4.205823
iter: 3257 | loss: 4.205630
iter: 3258 | loss: 4.205436
iter: 3259 | loss: 4.205243
iter: 3260 | loss: 4.205049
iter: 3261 | loss: 4.204856
iter: 3262 | loss: 4.204663
iter: 3263 | loss: 4.204469
iter: 3264 | loss: 4.204276
iter: 3265 | loss: 4.204082
iter: 3266 | loss: 4.203889
iter: 3267 | loss: 4.203696
iter: 3268 | loss: 4.203502
iter: 3269 | loss: 4.203309
iter: 3270 | loss: 4.203115
iter: 3271 | loss: 4.202922
iter: 3272 | loss: 4.202729
iter: 3273 | loss: 4.202535
iter: 3274 | loss: 4.202342
iter: 3275 | loss: 4.202149
iter: 3276 | loss: 4.201955
iter: 3277 | loss: 4.201762
iter: 3278 | loss: 4.201568
iter: 3279 | loss: 4.201375
iter: 3280 | loss: 4.201182
iter: 3281 | loss: 4.200988
iter: 3282 | loss: 4.200795
iter: 3283 | loss: 4.200601
iter: 3284 | loss: 4.200408
iter: 3285 | loss: 4.200215
iter: 3286 | loss: 4.200021
iter: 3287 | loss: 4.199828
iter: 3288 | loss: 4.199635
iter: 3289 | loss: 4.199441
iter: 3290 | loss: 4.199248
iter: 3291 | loss: 4.199054
iter: 3292 | loss: 4.198861
iter: 3293 | loss: 4.198668
iter: 3294 | loss: 4.198474
iter: 3295 | loss: 4.198281
iter: 3296 | loss: 4.198087
iter: 3297 | loss: 4.197894
iter: 3298 | loss: 4.197701
iter: 3299 | loss: 4.197507
iter: 3300 | loss: 4.197314
iter: 3301 | loss: 4.197121
iter: 3302 | loss: 4.196927
iter: 3303 | loss: 4.196734
iter: 3304 | loss: 4.196540
iter: 3305 | loss: 4.196347
iter: 3306 | loss: 4.196154
iter: 3307 | loss: 4.195960
iter: 3308 | loss: 4.195767
iter: 3309 | loss: 4.195573
iter: 3310 | loss: 4.195380
iter: 3311 | loss: 4.195187
iter: 3312 | loss: 4.194993
iter: 3313 | loss: 4.194800
iter: 3314 | loss: 4.194606
iter: 3315 | loss: 4.194413
iter: 3316 | loss: 4.194220
iter: 3317 | loss: 4.194026
iter: 3318 | loss: 4.193833
iter: 3319 | loss: 4.193640
iter: 3320 | loss: 4.193446
iter: 3321 | loss: 4.193253
iter: 3322 | loss: 4.193059
iter: 3323 | loss: 4.192866
iter: 3324 | loss: 4.192673
iter: 3325 | loss: 4.192479
iter: 3326 | loss: 4.192286
iter: 3327 | loss: 4.192092
iter: 3328 | loss: 4.191899
iter: 3329 | loss: 4.191706
iter: 3330 | loss: 4.191512
iter: 3331 | loss: 4.191319
iter: 3332 | loss: 4.191126
iter: 3333 | loss: 4.190932
iter: 3334 | loss: 4.190739
iter: 3335 | loss: 4.190545
iter: 3336 | loss: 4.190352
iter: 3337 | loss: 4.190159
iter: 3338 | loss: 4.189965
iter: 3339 | loss: 4.189772
iter: 3340 | loss: 4.189578
iter: 3341 | loss: 4.189385
iter: 3342 | loss: 4.189192
iter: 3343 | loss: 4.188998
iter: 3344 | loss: 4.188805
iter: 3345 | loss: 4.188611
iter: 3346 | loss: 4.188418
iter: 3347 | loss: 4.188225
iter: 3348 | loss: 4.188031
iter: 3349 | loss: 4.187838
iter: 3350 | loss: 4.187645
iter: 3351 | loss: 4.187451
iter: 3352 | loss: 4.187258
iter: 3353 | loss: 4.187064
iter: 3354 | loss: 4.186871
iter: 3355 | loss: 4.186678
iter: 3356 | loss: 4.186484
iter: 3357 | loss: 4.186291
iter: 3358 | loss: 4.186097
iter: 3359 | loss: 4.185904
iter: 3360 | loss: 4.185711
iter: 3361 | loss: 4.185517
iter: 3362 | loss: 4.185324
iter: 3363 | loss: 4.185131
iter: 3364 | loss: 4.184937
iter: 3365 | loss: 4.184744
iter: 3366 | loss: 4.184550
iter: 3367 | loss: 4.184357
iter: 3368 | loss: 4.184164
iter: 3369 | loss: 4.183970
iter: 3370 | loss: 4.183777
iter: 3371 | loss: 4.183583
iter: 3372 | loss: 4.183390
iter: 3373 | loss: 4.183197
iter: 3374 | loss: 4.183003
iter: 3375 | loss: 4.182810
iter: 3376 | loss: 4.182616
iter: 3377 | loss: 4.182423
iter: 3378 | loss: 4.182230
iter: 3379 | loss: 4.182036
iter: 3380 | loss: 4.181843
iter: 3381 | loss: 4.181650
iter: 3382 | loss: 4.181456
iter: 3383 | loss: 4.181263
iter: 3384 | loss: 4.181069
iter: 3385 | loss: 4.180876
iter: 3386 | loss: 4.180683
iter: 3387 | loss: 4.180489
iter: 3388 | loss: 4.180296
iter: 3389 | loss: 4.180102
iter: 3390 | loss: 4.179909
iter: 3391 | loss: 4.179716
iter: 3392 | loss: 4.179522
iter: 3393 | loss: 4.179329
iter: 3394 | loss: 4.179136
iter: 3395 | loss: 4.178942
iter: 3396 | loss: 4.178749
iter: 3397 | loss: 4.178555
iter: 3398 | loss: 4.178362
iter: 3399 | loss: 4.178169
iter: 3400 | loss: 4.177975
iter: 3401 | loss: 4.177782
iter: 3402 | loss: 4.177588
iter: 3403 | loss: 4.177395
iter: 3404 | loss: 4.177202
iter: 3405 | loss: 4.177008
iter: 3406 | loss: 4.176815
iter: 3407 | loss: 4.176621
iter: 3408 | loss: 4.176428
iter: 3409 | loss: 4.176235
iter: 3410 | loss: 4.176041
iter: 3411 | loss: 4.175848
iter: 3412 | loss: 4.175655
iter: 3413 | loss: 4.175461
iter: 3414 | loss: 4.175268
iter: 3415 | loss: 4.175074
iter: 3416 | loss: 4.174881
iter: 3417 | loss: 4.174688
iter: 3418 | loss: 4.174494
iter: 3419 | loss: 4.174301
iter: 3420 | loss: 4.174107
iter: 3421 | loss: 4.173914
iter: 3422 | loss: 4.173721
iter: 3423 | loss: 4.173527
iter: 3424 | loss: 4.173334
iter: 3425 | loss: 4.173141
iter: 3426 | loss: 4.172947
iter: 3427 | loss: 4.172754
iter: 3428 | loss: 4.172560
iter: 3429 | loss: 4.172367
iter: 3430 | loss: 4.172174
iter: 3431 | loss: 4.171980
iter: 3432 | loss: 4.171787
iter: 3433 | loss: 4.171593
iter: 3434 | loss: 4.171400
iter: 3435 | loss: 4.171207
iter: 3436 | loss: 4.171013
iter: 3437 | loss: 4.170820
iter: 3438 | loss: 4.170626
iter: 3439 | loss: 4.170433
iter: 3440 | loss: 4.170240
iter: 3441 | loss: 4.170046
iter: 3442 | loss: 4.169853
iter: 3443 | loss: 4.169660
iter: 3444 | loss: 4.169466
iter: 3445 | loss: 4.169273
iter: 3446 | loss: 4.169079
iter: 3447 | loss: 4.168886
iter: 3448 | loss: 4.168693
iter: 3449 | loss: 4.168499
iter: 3450 | loss: 4.168306
iter: 3451 | loss: 4.168112
iter: 3452 | loss: 4.167919
iter: 3453 | loss: 4.167726
iter: 3454 | loss: 4.167532
iter: 3455 | loss: 4.167339
iter: 3456 | loss: 4.167146
iter: 3457 | loss: 4.166952
iter: 3458 | loss: 4.166759
iter: 3459 | loss: 4.166565
iter: 3460 | loss: 4.166372
iter: 3461 | loss: 4.166179
iter: 3462 | loss: 4.165985
iter: 3463 | loss: 4.165792
iter: 3464 | loss: 4.165598
iter: 3465 | loss: 4.165405
iter: 3466 | loss: 4.165212
iter: 3467 | loss: 4.165018
iter: 3468 | loss: 4.164825
iter: 3469 | loss: 4.164631
iter: 3470 | loss: 4.164438
iter: 3471 | loss: 4.164245
iter: 3472 | loss: 4.164051
iter: 3473 | loss: 4.163858
iter: 3474 | loss: 4.163665
iter: 3475 | loss: 4.163471
iter: 3476 | loss: 4.163278
iter: 3477 | loss: 4.163084
iter: 3478 | loss: 4.162891
iter: 3479 | loss: 4.162698
iter: 3480 | loss: 4.162504
iter: 3481 | loss: 4.162311
iter: 3482 | loss: 4.162117
iter: 3483 | loss: 4.161924
iter: 3484 | loss: 4.161731
iter: 3485 | loss: 4.161537
iter: 3486 | loss: 4.161344
iter: 3487 | loss: 4.161151
iter: 3488 | loss: 4.160957
iter: 3489 | loss: 4.160764
iter: 3490 | loss: 4.160570
iter: 3491 | loss: 4.160377
iter: 3492 | loss: 4.160184
iter: 3493 | loss: 4.159990
iter: 3494 | loss: 4.159797
iter: 3495 | loss: 4.159603
iter: 3496 | loss: 4.159410
iter: 3497 | loss: 4.159217
iter: 3498 | loss: 4.159023
iter: 3499 | loss: 4.158830
iter: 3500 | loss: 4.158636
iter: 3501 | loss: 4.158443
iter: 3502 | loss: 4.158250
iter: 3503 | loss: 4.158056
iter: 3504 | loss: 4.157863
iter: 3505 | loss: 4.157670
iter: 3506 | loss: 4.157476
iter: 3507 | loss: 4.157283
iter: 3508 | loss: 4.157089
iter: 3509 | loss: 4.156896
iter: 3510 | loss: 4.156703
iter: 3511 | loss: 4.156509
iter: 3512 | loss: 4.156316
iter: 3513 | loss: 4.156122
iter: 3514 | loss: 4.155929
iter: 3515 | loss: 4.155736
iter: 3516 | loss: 4.155542
iter: 3517 | loss: 4.155349
iter: 3518 | loss: 4.155156
iter: 3519 | loss: 4.154962
iter: 3520 | loss: 4.154769
iter: 3521 | loss: 4.154575
iter: 3522 | loss: 4.154382
iter: 3523 | loss: 4.154189
iter: 3524 | loss: 4.153995
iter: 3525 | loss: 4.153802
iter: 3526 | loss: 4.153608
iter: 3527 | loss: 4.153415
iter: 3528 | loss: 4.153222
iter: 3529 | loss: 4.153028
iter: 3530 | loss: 4.152835
iter: 3531 | loss: 4.152641
iter: 3532 | loss: 4.152448
iter: 3533 | loss: 4.152255
iter: 3534 | loss: 4.152061
iter: 3535 | loss: 4.151868
iter: 3536 | loss: 4.151675
iter: 3537 | loss: 4.151481
iter: 3538 | loss: 4.151288
iter: 3539 | loss: 4.151094
iter: 3540 | loss: 4.150901
iter: 3541 | loss: 4.150708
iter: 3542 | loss: 4.150514
iter: 3543 | loss: 4.150321
iter: 3544 | loss: 4.150127
iter: 3545 | loss: 4.149934
iter: 3546 | loss: 4.149741
iter: 3547 | loss: 4.149547
iter: 3548 | loss: 4.149354
iter: 3549 | loss: 4.149161
iter: 3550 | loss: 4.148967
iter: 3551 | loss: 4.148774
iter: 3552 | loss: 4.148580
iter: 3553 | loss: 4.148387
iter: 3554 | loss: 4.148194
iter: 3555 | loss: 4.148000
iter: 3556 | loss: 4.147807
iter: 3557 | loss: 4.147613
iter: 3558 | loss: 4.147420
iter: 3559 | loss: 4.147227
iter: 3560 | loss: 4.147033
iter: 3561 | loss: 4.146840
iter: 3562 | loss: 4.146646
iter: 3563 | loss: 4.146453
iter: 3564 | loss: 4.146260
iter: 3565 | loss: 4.146066
iter: 3566 | loss: 4.145873
iter: 3567 | loss: 4.145680
iter: 3568 | loss: 4.145486
iter: 3569 | loss: 4.145293
iter: 3570 | loss: 4.145099
iter: 3571 | loss: 4.144906
iter: 3572 | loss: 4.144713
iter: 3573 | loss: 4.144519
iter: 3574 | loss: 4.144326
iter: 3575 | loss: 4.144132
iter: 3576 | loss: 4.143939
iter: 3577 | loss: 4.143746
iter: 3578 | loss: 4.143552
iter: 3579 | loss: 4.143359
iter: 3580 | loss: 4.143166
iter: 3581 | loss: 4.142972
iter: 3582 | loss: 4.142779
iter: 3583 | loss: 4.142585
iter: 3584 | loss: 4.142392
iter: 3585 | loss: 4.142199
iter: 3586 | loss: 4.142005
iter: 3587 | loss: 4.141812
iter: 3588 | loss: 4.141618
iter: 3589 | loss: 4.141425
iter: 3590 | loss: 4.141232
iter: 3591 | loss: 4.141038
iter: 3592 | loss: 4.140845
iter: 3593 | loss: 4.140651
iter: 3594 | loss: 4.140458
iter: 3595 | loss: 4.140265
iter: 3596 | loss: 4.140071
iter: 3597 | loss: 4.139878
iter: 3598 | loss: 4.139685
iter: 3599 | loss: 4.139491
iter: 3600 | loss: 4.139298
iter: 3601 | loss: 4.139104
iter: 3602 | loss: 4.138911
iter: 3603 | loss: 4.138718
iter: 3604 | loss: 4.138524
iter: 3605 | loss: 4.138331
iter: 3606 | loss: 4.138137
iter: 3607 | loss: 4.137944
iter: 3608 | loss: 4.137751
iter: 3609 | loss: 4.137557
iter: 3610 | loss: 4.137364
iter: 3611 | loss: 4.137171
iter: 3612 | loss: 4.136977
iter: 3613 | loss: 4.136784
iter: 3614 | loss: 4.136590
iter: 3615 | loss: 4.136397
iter: 3616 | loss: 4.136204
iter: 3617 | loss: 4.136010
iter: 3618 | loss: 4.135817
iter: 3619 | loss: 4.135623
iter: 3620 | loss: 4.135430
iter: 3621 | loss: 4.135237
iter: 3622 | loss: 4.135043
iter: 3623 | loss: 4.134850
iter: 3624 | loss: 4.134657
iter: 3625 | loss: 4.134463
iter: 3626 | loss: 4.134270
iter: 3627 | loss: 4.134076
iter: 3628 | loss: 4.133883
iter: 3629 | loss: 4.133690
iter: 3630 | loss: 4.133496
iter: 3631 | loss: 4.133303
iter: 3632 | loss: 4.133109
iter: 3633 | loss: 4.132916
iter: 3634 | loss: 4.132723
iter: 3635 | loss: 4.132529
iter: 3636 | loss: 4.132336
iter: 3637 | loss: 4.132142
iter: 3638 | loss: 4.131949
iter: 3639 | loss: 4.131756
iter: 3640 | loss: 4.131562
iter: 3641 | loss: 4.131369
iter: 3642 | loss: 4.131176
iter: 3643 | loss: 4.130982
iter: 3644 | loss: 4.130789
iter: 3645 | loss: 4.130595
iter: 3646 | loss: 4.130402
iter: 3647 | loss: 4.130209
iter: 3648 | loss: 4.130015
iter: 3649 | loss: 4.129822
iter: 3650 | loss: 4.129628
iter: 3651 | loss: 4.129435
iter: 3652 | loss: 4.129242
iter: 3653 | loss: 4.129048
iter: 3654 | loss: 4.128855
iter: 3655 | loss: 4.128662
iter: 3656 | loss: 4.128468
iter: 3657 | loss: 4.128275
iter: 3658 | loss: 4.128081
iter: 3659 | loss: 4.127888
iter: 3660 | loss: 4.127695
iter: 3661 | loss: 4.127501
iter: 3662 | loss: 4.127308
iter: 3663 | loss: 4.127114
iter: 3664 | loss: 4.126921
iter: 3665 | loss: 4.126728
iter: 3666 | loss: 4.126534
iter: 3667 | loss: 4.126341
iter: 3668 | loss: 4.126147
iter: 3669 | loss: 4.125954
iter: 3670 | loss: 4.125761
iter: 3671 | loss: 4.125567
iter: 3672 | loss: 4.125374
iter: 3673 | loss: 4.125181
iter: 3674 | loss: 4.124987
iter: 3675 | loss: 4.124794
iter: 3676 | loss: 4.124600
iter: 3677 | loss: 4.124407
iter: 3678 | loss: 4.124214
iter: 3679 | loss: 4.124020
iter: 3680 | loss: 4.123827
iter: 3681 | loss: 4.123633
iter: 3682 | loss: 4.123440
iter: 3683 | loss: 4.123247
iter: 3684 | loss: 4.123053
iter: 3685 | loss: 4.122860
iter: 3686 | loss: 4.122667
iter: 3687 | loss: 4.122473
iter: 3688 | loss: 4.122280
iter: 3689 | loss: 4.122086
iter: 3690 | loss: 4.121893
iter: 3691 | loss: 4.121700
iter: 3692 | loss: 4.121506
iter: 3693 | loss: 4.121313
iter: 3694 | loss: 4.121119
iter: 3695 | loss: 4.120926
iter: 3696 | loss: 4.120733
iter: 3697 | loss: 4.120539
iter: 3698 | loss: 4.120346
iter: 3699 | loss: 4.120152
iter: 3700 | loss: 4.119959
iter: 3701 | loss: 4.119766
iter: 3702 | loss: 4.119572
iter: 3703 | loss: 4.119379
iter: 3704 | loss: 4.119186
iter: 3705 | loss: 4.118992
iter: 3706 | loss: 4.118799
iter: 3707 | loss: 4.118605
iter: 3708 | loss: 4.118412
iter: 3709 | loss: 4.118219
iter: 3710 | loss: 4.118025
iter: 3711 | loss: 4.117832
iter: 3712 | loss: 4.117638
iter: 3713 | loss: 4.117445
iter: 3714 | loss: 4.117252
iter: 3715 | loss: 4.117058
iter: 3716 | loss: 4.116865
iter: 3717 | loss: 4.116672
iter: 3718 | loss: 4.116478
iter: 3719 | loss: 4.116285
iter: 3720 | loss: 4.116091
iter: 3721 | loss: 4.115898
iter: 3722 | loss: 4.115705
iter: 3723 | loss: 4.115511
iter: 3724 | loss: 4.115318
iter: 3725 | loss: 4.115124
iter: 3726 | loss: 4.114931
iter: 3727 | loss: 4.114738
iter: 3728 | loss: 4.114544
iter: 3729 | loss: 4.114351
iter: 3730 | loss: 4.114157
iter: 3731 | loss: 4.113964
iter: 3732 | loss: 4.113771
iter: 3733 | loss: 4.113577
iter: 3734 | loss: 4.113384
iter: 3735 | loss: 4.113191
iter: 3736 | loss: 4.112997
iter: 3737 | loss: 4.112804
iter: 3738 | loss: 4.112610
iter: 3739 | loss: 4.112417
iter: 3740 | loss: 4.112224
iter: 3741 | loss: 4.112030
iter: 3742 | loss: 4.111837
iter: 3743 | loss: 4.111643
iter: 3744 | loss: 4.111450
iter: 3745 | loss: 4.111257
iter: 3746 | loss: 4.111063
iter: 3747 | loss: 4.110870
iter: 3748 | loss: 4.110677
iter: 3749 | loss: 4.110483
iter: 3750 | loss: 4.110290
iter: 3751 | loss: 4.110096
iter: 3752 | loss: 4.109903
iter: 3753 | loss: 4.109710
iter: 3754 | loss: 4.109516
iter: 3755 | loss: 4.109323
iter: 3756 | loss: 4.109129
iter: 3757 | loss: 4.108936
iter: 3758 | loss: 4.108743
iter: 3759 | loss: 4.108549
iter: 3760 | loss: 4.108356
iter: 3761 | loss: 4.108162
iter: 3762 | loss: 4.107969
iter: 3763 | loss: 4.107776
iter: 3764 | loss: 4.107582
iter: 3765 | loss: 4.107389
iter: 3766 | loss: 4.107196
iter: 3767 | loss: 4.107002
iter: 3768 | loss: 4.106809
iter: 3769 | loss: 4.106615
iter: 3770 | loss: 4.106422
iter: 3771 | loss: 4.106229
iter: 3772 | loss: 4.106035
iter: 3773 | loss: 4.105842
iter: 3774 | loss: 4.105648
iter: 3775 | loss: 4.105455
iter: 3776 | loss: 4.105262
iter: 3777 | loss: 4.105068
iter: 3778 | loss: 4.104875
iter: 3779 | loss: 4.104682
iter: 3780 | loss: 4.104488
iter: 3781 | loss: 4.104295
iter: 3782 | loss: 4.104101
iter: 3783 | loss: 4.103908
iter: 3784 | loss: 4.103715
iter: 3785 | loss: 4.103521
iter: 3786 | loss: 4.103328
iter: 3787 | loss: 4.103134
iter: 3788 | loss: 4.102941
iter: 3789 | loss: 4.102748
iter: 3790 | loss: 4.102554
iter: 3791 | loss: 4.102361
iter: 3792 | loss: 4.102167
iter: 3793 | loss: 4.101974
iter: 3794 | loss: 4.101781
iter: 3795 | loss: 4.101587
iter: 3796 | loss: 4.101394
iter: 3797 | loss: 4.101201
iter: 3798 | loss: 4.101007
iter: 3799 | loss: 4.100814
iter: 3800 | loss: 4.100620
iter: 3801 | loss: 4.100427
iter: 3802 | loss: 4.100234
iter: 3803 | loss: 4.100040
iter: 3804 | loss: 4.099847
iter: 3805 | loss: 4.099653
iter: 3806 | loss: 4.099460
iter: 3807 | loss: 4.099267
iter: 3808 | loss: 4.099073
iter: 3809 | loss: 4.098880
iter: 3810 | loss: 4.098687
iter: 3811 | loss: 4.098493
iter: 3812 | loss: 4.098300
iter: 3813 | loss: 4.098106
iter: 3814 | loss: 4.097913
iter: 3815 | loss: 4.097720
iter: 3816 | loss: 4.097526
iter: 3817 | loss: 4.097333
iter: 3818 | loss: 4.097139
iter: 3819 | loss: 4.096946
iter: 3820 | loss: 4.096753
iter: 3821 | loss: 4.096559
iter: 3822 | loss: 4.096366
iter: 3823 | loss: 4.096172
iter: 3824 | loss: 4.095979
iter: 3825 | loss: 4.095786
iter: 3826 | loss: 4.095592
iter: 3827 | loss: 4.095399
iter: 3828 | loss: 4.095206
iter: 3829 | loss: 4.095012
iter: 3830 | loss: 4.094819
iter: 3831 | loss: 4.094625
iter: 3832 | loss: 4.094432
iter: 3833 | loss: 4.094239
iter: 3834 | loss: 4.094045
iter: 3835 | loss: 4.093852
iter: 3836 | loss: 4.093658
iter: 3837 | loss: 4.093465
iter: 3838 | loss: 4.093272
iter: 3839 | loss: 4.093078
iter: 3840 | loss: 4.092885
iter: 3841 | loss: 4.092692
iter: 3842 | loss: 4.092498
iter: 3843 | loss: 4.092305
iter: 3844 | loss: 4.092111
iter: 3845 | loss: 4.091918
iter: 3846 | loss: 4.091725
iter: 3847 | loss: 4.091531
iter: 3848 | loss: 4.091338
iter: 3849 | loss: 4.091144
iter: 3850 | loss: 4.090951
iter: 3851 | loss: 4.090758
iter: 3852 | loss: 4.090564
iter: 3853 | loss: 4.090371
iter: 3854 | loss: 4.090177
iter: 3855 | loss: 4.089984
iter: 3856 | loss: 4.089791
iter: 3857 | loss: 4.089597
iter: 3858 | loss: 4.089404
iter: 3859 | loss: 4.089211
iter: 3860 | loss: 4.089017
iter: 3861 | loss: 4.088824
iter: 3862 | loss: 4.088630
iter: 3863 | loss: 4.088437
iter: 3864 | loss: 4.088244
iter: 3865 | loss: 4.088050
iter: 3866 | loss: 4.087857
iter: 3867 | loss: 4.087663
iter: 3868 | loss: 4.087470
iter: 3869 | loss: 4.087277
iter: 3870 | loss: 4.087083
iter: 3871 | loss: 4.086890
iter: 3872 | loss: 4.086697
iter: 3873 | loss: 4.086503
iter: 3874 | loss: 4.086310
iter: 3875 | loss: 4.086116
iter: 3876 | loss: 4.085923
iter: 3877 | loss: 4.085730
iter: 3878 | loss: 4.085536
iter: 3879 | loss: 4.085343
iter: 3880 | loss: 4.085149
iter: 3881 | loss: 4.084956
iter: 3882 | loss: 4.084763
iter: 3883 | loss: 4.084569
iter: 3884 | loss: 4.084376
iter: 3885 | loss: 4.084182
iter: 3886 | loss: 4.083989
iter: 3887 | loss: 4.083796
iter: 3888 | loss: 4.083602
iter: 3889 | loss: 4.083409
iter: 3890 | loss: 4.083216
iter: 3891 | loss: 4.083022
iter: 3892 | loss: 4.082829
iter: 3893 | loss: 4.082635
iter: 3894 | loss: 4.082442
iter: 3895 | loss: 4.082249
iter: 3896 | loss: 4.082055
iter: 3897 | loss: 4.081862
iter: 3898 | loss: 4.081668
iter: 3899 | loss: 4.081475
iter: 3900 | loss: 4.081282
iter: 3901 | loss: 4.081088
iter: 3902 | loss: 4.080895
iter: 3903 | loss: 4.080702
iter: 3904 | loss: 4.080508
iter: 3905 | loss: 4.080315
iter: 3906 | loss: 4.080121
iter: 3907 | loss: 4.079928
iter: 3908 | loss: 4.079735
iter: 3909 | loss: 4.079541
iter: 3910 | loss: 4.079348
iter: 3911 | loss: 4.079154
iter: 3912 | loss: 4.078961
iter: 3913 | loss: 4.078768
iter: 3914 | loss: 4.078574
iter: 3915 | loss: 4.078381
iter: 3916 | loss: 4.078187
iter: 3917 | loss: 4.077994
iter: 3918 | loss: 4.077801
iter: 3919 | loss: 4.077607
iter: 3920 | loss: 4.077414
iter: 3921 | loss: 4.077221
iter: 3922 | loss: 4.077027
iter: 3923 | loss: 4.076834
iter: 3924 | loss: 4.076640
iter: 3925 | loss: 4.076447
iter: 3926 | loss: 4.076254
iter: 3927 | loss: 4.076060
iter: 3928 | loss: 4.075867
iter: 3929 | loss: 4.075673
iter: 3930 | loss: 4.075480
iter: 3931 | loss: 4.075287
iter: 3932 | loss: 4.075093
iter: 3933 | loss: 4.074900
iter: 3934 | loss: 4.074707
iter: 3935 | loss: 4.074513
iter: 3936 | loss: 4.074320
iter: 3937 | loss: 4.074126
iter: 3938 | loss: 4.073933
iter: 3939 | loss: 4.073740
iter: 3940 | loss: 4.073546
iter: 3941 | loss: 4.073353
iter: 3942 | loss: 4.073159
iter: 3943 | loss: 4.072966
iter: 3944 | loss: 4.072773
iter: 3945 | loss: 4.072579
iter: 3946 | loss: 4.072386
iter: 3947 | loss: 4.072193
iter: 3948 | loss: 4.071999
iter: 3949 | loss: 4.071806
iter: 3950 | loss: 4.071612
iter: 3951 | loss: 4.071419
iter: 3952 | loss: 4.071226
iter: 3953 | loss: 4.071032
iter: 3954 | loss: 4.070839
iter: 3955 | loss: 4.070645
iter: 3956 | loss: 4.070452
iter: 3957 | loss: 4.070259
iter: 3958 | loss: 4.070065
iter: 3959 | loss: 4.069872
iter: 3960 | loss: 4.069678
iter: 3961 | loss: 4.069485
iter: 3962 | loss: 4.069292
iter: 3963 | loss: 4.069098
iter: 3964 | loss: 4.068905
iter: 3965 | loss: 4.068712
iter: 3966 | loss: 4.068518
iter: 3967 | loss: 4.068325
iter: 3968 | loss: 4.068131
iter: 3969 | loss: 4.067938
iter: 3970 | loss: 4.067745
iter: 3971 | loss: 4.067551
iter: 3972 | loss: 4.067358
iter: 3973 | loss: 4.067164
iter: 3974 | loss: 4.066971
iter: 3975 | loss: 4.066778
iter: 3976 | loss: 4.066584
iter: 3977 | loss: 4.066391
iter: 3978 | loss: 4.066198
iter: 3979 | loss: 4.066004
iter: 3980 | loss: 4.065811
iter: 3981 | loss: 4.065617
iter: 3982 | loss: 4.065424
iter: 3983 | loss: 4.065231
iter: 3984 | loss: 4.065037
iter: 3985 | loss: 4.064844
iter: 3986 | loss: 4.064650
iter: 3987 | loss: 4.064457
iter: 3988 | loss: 4.064264
iter: 3989 | loss: 4.064070
iter: 3990 | loss: 4.063877
iter: 3991 | loss: 4.063683
iter: 3992 | loss: 4.063490
iter: 3993 | loss: 4.063297
iter: 3994 | loss: 4.063103
iter: 3995 | loss: 4.062910
iter: 3996 | loss: 4.062717
iter: 3997 | loss: 4.062523
iter: 3998 | loss: 4.062330
iter: 3999 | loss: 4.062136
iter: 4000 | loss: 4.061943
iter: 4001 | loss: 4.061750
iter: 4002 | loss: 4.061556
iter: 4003 | loss: 4.061363
iter: 4004 | loss: 4.061169
iter: 4005 | loss: 4.060976
iter: 4006 | loss: 4.060783
iter: 4007 | loss: 4.060589
iter: 4008 | loss: 4.060396
iter: 4009 | loss: 4.060203
iter: 4010 | loss: 4.060009
iter: 4011 | loss: 4.059816
iter: 4012 | loss: 4.059622
iter: 4013 | loss: 4.059429
iter: 4014 | loss: 4.059236
iter: 4015 | loss: 4.059042
iter: 4016 | loss: 4.058849
iter: 4017 | loss: 4.058655
iter: 4018 | loss: 4.058462
iter: 4019 | loss: 4.058269
iter: 4020 | loss: 4.058075
iter: 4021 | loss: 4.057882
iter: 4022 | loss: 4.057688
iter: 4023 | loss: 4.057495
iter: 4024 | loss: 4.057302
iter: 4025 | loss: 4.057108
iter: 4026 | loss: 4.056915
iter: 4027 | loss: 4.056722
iter: 4028 | loss: 4.056528
iter: 4029 | loss: 4.056335
iter: 4030 | loss: 4.056141
iter: 4031 | loss: 4.055948
iter: 4032 | loss: 4.055755
iter: 4033 | loss: 4.055561
iter: 4034 | loss: 4.055368
iter: 4035 | loss: 4.055174
iter: 4036 | loss: 4.054981
iter: 4037 | loss: 4.054788
iter: 4038 | loss: 4.054594
iter: 4039 | loss: 4.054401
iter: 4040 | loss: 4.054208
iter: 4041 | loss: 4.054014
iter: 4042 | loss: 4.053821
iter: 4043 | loss: 4.053627
iter: 4044 | loss: 4.053434
iter: 4045 | loss: 4.053241
iter: 4046 | loss: 4.053047
iter: 4047 | loss: 4.052854
iter: 4048 | loss: 4.052660
iter: 4049 | loss: 4.052467
iter: 4050 | loss: 4.052274
iter: 4051 | loss: 4.052080
iter: 4052 | loss: 4.051887
iter: 4053 | loss: 4.051693
iter: 4054 | loss: 4.051500
iter: 4055 | loss: 4.051307
iter: 4056 | loss: 4.051113
iter: 4057 | loss: 4.050920
iter: 4058 | loss: 4.050727
iter: 4059 | loss: 4.050533
iter: 4060 | loss: 4.050340
iter: 4061 | loss: 4.050146
iter: 4062 | loss: 4.049953
iter: 4063 | loss: 4.049760
iter: 4064 | loss: 4.049566
iter: 4065 | loss: 4.049373
iter: 4066 | loss: 4.049179
iter: 4067 | loss: 4.048986
iter: 4068 | loss: 4.048793
iter: 4069 | loss: 4.048599
iter: 4070 | loss: 4.048406
iter: 4071 | loss: 4.048213
iter: 4072 | loss: 4.048019
iter: 4073 | loss: 4.047826
iter: 4074 | loss: 4.047632
iter: 4075 | loss: 4.047439
iter: 4076 | loss: 4.047246
iter: 4077 | loss: 4.047052
iter: 4078 | loss: 4.046859
iter: 4079 | loss: 4.046665
iter: 4080 | loss: 4.046472
iter: 4081 | loss: 4.046279
iter: 4082 | loss: 4.046085
iter: 4083 | loss: 4.045892
iter: 4084 | loss: 4.045698
iter: 4085 | loss: 4.045505
iter: 4086 | loss: 4.045312
iter: 4087 | loss: 4.045118
iter: 4088 | loss: 4.044925
iter: 4089 | loss: 4.044732
iter: 4090 | loss: 4.044538
iter: 4091 | loss: 4.044345
iter: 4092 | loss: 4.044151
iter: 4093 | loss: 4.043958
iter: 4094 | loss: 4.043765
iter: 4095 | loss: 4.043571
iter: 4096 | loss: 4.043378
iter: 4097 | loss: 4.043184
iter: 4098 | loss: 4.042991
iter: 4099 | loss: 4.042798
iter: 4100 | loss: 4.042604
iter: 4101 | loss: 4.042411
iter: 4102 | loss: 4.042218
iter: 4103 | loss: 4.042024
iter: 4104 | loss: 4.041831
iter: 4105 | loss: 4.041637
iter: 4106 | loss: 4.041444
iter: 4107 | loss: 4.041251
iter: 4108 | loss: 4.041057
iter: 4109 | loss: 4.040864
iter: 4110 | loss: 4.040670
iter: 4111 | loss: 4.040477
iter: 4112 | loss: 4.040284
iter: 4113 | loss: 4.040090
iter: 4114 | loss: 4.039897
iter: 4115 | loss: 4.039703
iter: 4116 | loss: 4.039510
iter: 4117 | loss: 4.039317
iter: 4118 | loss: 4.039123
iter: 4119 | loss: 4.038930
iter: 4120 | loss: 4.038737
iter: 4121 | loss: 4.038543
iter: 4122 | loss: 4.038350
iter: 4123 | loss: 4.038156
iter: 4124 | loss: 4.037963
iter: 4125 | loss: 4.037770
iter: 4126 | loss: 4.037576
iter: 4127 | loss: 4.037383
iter: 4128 | loss: 4.037189
iter: 4129 | loss: 4.036996
iter: 4130 | loss: 4.036803
iter: 4131 | loss: 4.036609
iter: 4132 | loss: 4.036416
iter: 4133 | loss: 4.036223
iter: 4134 | loss: 4.036029
iter: 4135 | loss: 4.035836
iter: 4136 | loss: 4.035642
iter: 4137 | loss: 4.035449
iter: 4138 | loss: 4.035256
iter: 4139 | loss: 4.035062
iter: 4140 | loss: 4.034869
iter: 4141 | loss: 4.034675
iter: 4142 | loss: 4.034482
iter: 4143 | loss: 4.034289
iter: 4144 | loss: 4.034095
iter: 4145 | loss: 4.033902
iter: 4146 | loss: 4.033708
iter: 4147 | loss: 4.033515
iter: 4148 | loss: 4.033322
iter: 4149 | loss: 4.033128
iter: 4150 | loss: 4.032935
iter: 4151 | loss: 4.032742
iter: 4152 | loss: 4.032548
iter: 4153 | loss: 4.032355
iter: 4154 | loss: 4.032161
iter: 4155 | loss: 4.031968
iter: 4156 | loss: 4.031775
iter: 4157 | loss: 4.031581
iter: 4158 | loss: 4.031388
iter: 4159 | loss: 4.031194
iter: 4160 | loss: 4.031001
iter: 4161 | loss: 4.030808
iter: 4162 | loss: 4.030614
iter: 4163 | loss: 4.030421
iter: 4164 | loss: 4.030228
iter: 4165 | loss: 4.030034
iter: 4166 | loss: 4.029841
iter: 4167 | loss: 4.029647
iter: 4168 | loss: 4.029454
iter: 4169 | loss: 4.029261
iter: 4170 | loss: 4.029067
iter: 4171 | loss: 4.028874
iter: 4172 | loss: 4.028680
iter: 4173 | loss: 4.028487
iter: 4174 | loss: 4.028294
iter: 4175 | loss: 4.028100
iter: 4176 | loss: 4.027907
iter: 4177 | loss: 4.027713
iter: 4178 | loss: 4.027520
iter: 4179 | loss: 4.027327
iter: 4180 | loss: 4.027133
iter: 4181 | loss: 4.026940
iter: 4182 | loss: 4.026747
iter: 4183 | loss: 4.026553
iter: 4184 | loss: 4.026360
iter: 4185 | loss: 4.026166
iter: 4186 | loss: 4.025973
iter: 4187 | loss: 4.025780
iter: 4188 | loss: 4.025586
iter: 4189 | loss: 4.025393
iter: 4190 | loss: 4.025199
iter: 4191 | loss: 4.025006
iter: 4192 | loss: 4.024813
iter: 4193 | loss: 4.024619
iter: 4194 | loss: 4.024426
iter: 4195 | loss: 4.024233
iter: 4196 | loss: 4.024039
iter: 4197 | loss: 4.023846
iter: 4198 | loss: 4.023652
iter: 4199 | loss: 4.023459
iter: 4200 | loss: 4.023266
iter: 4201 | loss: 4.023072
iter: 4202 | loss: 4.022879
iter: 4203 | loss: 4.022685
iter: 4204 | loss: 4.022492
iter: 4205 | loss: 4.022299
iter: 4206 | loss: 4.022105
iter: 4207 | loss: 4.021912
iter: 4208 | loss: 4.021718
iter: 4209 | loss: 4.021525
iter: 4210 | loss: 4.021332
iter: 4211 | loss: 4.021138
iter: 4212 | loss: 4.020945
iter: 4213 | loss: 4.020752
iter: 4214 | loss: 4.020558
iter: 4215 | loss: 4.020365
iter: 4216 | loss: 4.020171
iter: 4217 | loss: 4.019978
iter: 4218 | loss: 4.019785
iter: 4219 | loss: 4.019591
iter: 4220 | loss: 4.019398
iter: 4221 | loss: 4.019204
iter: 4222 | loss: 4.019011
iter: 4223 | loss: 4.018818
iter: 4224 | loss: 4.018624
iter: 4225 | loss: 4.018431
iter: 4226 | loss: 4.018238
iter: 4227 | loss: 4.018044
iter: 4228 | loss: 4.017851
iter: 4229 | loss: 4.017657
iter: 4230 | loss: 4.017464
iter: 4231 | loss: 4.017271
iter: 4232 | loss: 4.017077
iter: 4233 | loss: 4.016884
iter: 4234 | loss: 4.016690
iter: 4235 | loss: 4.016497
iter: 4236 | loss: 4.016304
iter: 4237 | loss: 4.016110
iter: 4238 | loss: 4.015917
iter: 4239 | loss: 4.015723
iter: 4240 | loss: 4.015530
iter: 4241 | loss: 4.015337
iter: 4242 | loss: 4.015143
iter: 4243 | loss: 4.014950
iter: 4244 | loss: 4.014757
iter: 4245 | loss: 4.014563
iter: 4246 | loss: 4.014370
iter: 4247 | loss: 4.014176
iter: 4248 | loss: 4.013983
iter: 4249 | loss: 4.013790
iter: 4250 | loss: 4.013596
iter: 4251 | loss: 4.013403
iter: 4252 | loss: 4.013209
iter: 4253 | loss: 4.013016
iter: 4254 | loss: 4.012823
iter: 4255 | loss: 4.012629
iter: 4256 | loss: 4.012436
iter: 4257 | loss: 4.012243
iter: 4258 | loss: 4.012049
iter: 4259 | loss: 4.011856
iter: 4260 | loss: 4.011662
iter: 4261 | loss: 4.011469
iter: 4262 | loss: 4.011276
iter: 4263 | loss: 4.011082
iter: 4264 | loss: 4.010889
iter: 4265 | loss: 4.010695
iter: 4266 | loss: 4.010502
iter: 4267 | loss: 4.010309
iter: 4268 | loss: 4.010115
iter: 4269 | loss: 4.009922
iter: 4270 | loss: 4.009729
iter: 4271 | loss: 4.009535
iter: 4272 | loss: 4.009342
iter: 4273 | loss: 4.009148
iter: 4274 | loss: 4.008955
iter: 4275 | loss: 4.008762
iter: 4276 | loss: 4.008568
iter: 4277 | loss: 4.008375
iter: 4278 | loss: 4.008181
iter: 4279 | loss: 4.007988
iter: 4280 | loss: 4.007795
iter: 4281 | loss: 4.007601
iter: 4282 | loss: 4.007408
iter: 4283 | loss: 4.007214
iter: 4284 | loss: 4.007021
iter: 4285 | loss: 4.006828
iter: 4286 | loss: 4.006634
iter: 4287 | loss: 4.006441
iter: 4288 | loss: 4.006248
iter: 4289 | loss: 4.006054
iter: 4290 | loss: 4.005861
iter: 4291 | loss: 4.005667
iter: 4292 | loss: 4.005474
iter: 4293 | loss: 4.005281
iter: 4294 | loss: 4.005087
iter: 4295 | loss: 4.004894
iter: 4296 | loss: 4.004700
iter: 4297 | loss: 4.004507
iter: 4298 | loss: 4.004314
iter: 4299 | loss: 4.004120
iter: 4300 | loss: 4.003927
iter: 4301 | loss: 4.003734
iter: 4302 | loss: 4.003540
iter: 4303 | loss: 4.003347
iter: 4304 | loss: 4.003153
iter: 4305 | loss: 4.002960
iter: 4306 | loss: 4.002767
iter: 4307 | loss: 4.002573
iter: 4308 | loss: 4.002380
iter: 4309 | loss: 4.002186
iter: 4310 | loss: 4.001993
iter: 4311 | loss: 4.001800
iter: 4312 | loss: 4.001606
iter: 4313 | loss: 4.001413
iter: 4314 | loss: 4.001219
iter: 4315 | loss: 4.001026
iter: 4316 | loss: 4.000833
iter: 4317 | loss: 4.000639
iter: 4318 | loss: 4.000446
iter: 4319 | loss: 4.000253
iter: 4320 | loss: 4.000059
iter: 4321 | loss: 3.999866
iter: 4322 | loss: 3.999672
iter: 4323 | loss: 3.999479
iter: 4324 | loss: 3.999286
iter: 4325 | loss: 3.999092
iter: 4326 | loss: 3.998899
iter: 4327 | loss: 3.998705
iter: 4328 | loss: 3.998512
iter: 4329 | loss: 3.998319
iter: 4330 | loss: 3.998125
iter: 4331 | loss: 3.997932
iter: 4332 | loss: 3.997739
iter: 4333 | loss: 3.997545
iter: 4334 | loss: 3.997352
iter: 4335 | loss: 3.997158
iter: 4336 | loss: 3.996965
iter: 4337 | loss: 3.996772
iter: 4338 | loss: 3.996578
iter: 4339 | loss: 3.996385
iter: 4340 | loss: 3.996191
iter: 4341 | loss: 3.995998
iter: 4342 | loss: 3.995805
iter: 4343 | loss: 3.995611
iter: 4344 | loss: 3.995418
iter: 4345 | loss: 3.995224
iter: 4346 | loss: 3.995031
iter: 4347 | loss: 3.994838
iter: 4348 | loss: 3.994644
iter: 4349 | loss: 3.994451
iter: 4350 | loss: 3.994258
iter: 4351 | loss: 3.994064
iter: 4352 | loss: 3.993871
iter: 4353 | loss: 3.993677
iter: 4354 | loss: 3.993484
iter: 4355 | loss: 3.993291
iter: 4356 | loss: 3.993097
iter: 4357 | loss: 3.992904
iter: 4358 | loss: 3.992710
iter: 4359 | loss: 3.992517
iter: 4360 | loss: 3.992324
iter: 4361 | loss: 3.992130
iter: 4362 | loss: 3.991937
iter: 4363 | loss: 3.991744
iter: 4364 | loss: 3.991550
iter: 4365 | loss: 3.991357
iter: 4366 | loss: 3.991163
iter: 4367 | loss: 3.990970
iter: 4368 | loss: 3.990777
iter: 4369 | loss: 3.990583
iter: 4370 | loss: 3.990390
iter: 4371 | loss: 3.990196
iter: 4372 | loss: 3.990003
iter: 4373 | loss: 3.989810
iter: 4374 | loss: 3.989616
iter: 4375 | loss: 3.989423
iter: 4376 | loss: 3.989229
iter: 4377 | loss: 3.989036
iter: 4378 | loss: 3.988843
iter: 4379 | loss: 3.988649
iter: 4380 | loss: 3.988456
iter: 4381 | loss: 3.988263
iter: 4382 | loss: 3.988069
iter: 4383 | loss: 3.987876
iter: 4384 | loss: 3.987682
iter: 4385 | loss: 3.987489
iter: 4386 | loss: 3.987296
iter: 4387 | loss: 3.987102
iter: 4388 | loss: 3.986909
iter: 4389 | loss: 3.986715
iter: 4390 | loss: 3.986522
iter: 4391 | loss: 3.986329
iter: 4392 | loss: 3.986135
iter: 4393 | loss: 3.985942
iter: 4394 | loss: 3.985749
iter: 4395 | loss: 3.985555
iter: 4396 | loss: 3.985362
iter: 4397 | loss: 3.985168
iter: 4398 | loss: 3.984975
iter: 4399 | loss: 3.984782
iter: 4400 | loss: 3.984588
iter: 4401 | loss: 3.984395
iter: 4402 | loss: 3.984201
iter: 4403 | loss: 3.984008
iter: 4404 | loss: 3.983815
iter: 4405 | loss: 3.983621
iter: 4406 | loss: 3.983428
iter: 4407 | loss: 3.983234
iter: 4408 | loss: 3.983041
iter: 4409 | loss: 3.982848
iter: 4410 | loss: 3.982654
iter: 4411 | loss: 3.982461
iter: 4412 | loss: 3.982268
iter: 4413 | loss: 3.982074
iter: 4414 | loss: 3.981881
iter: 4415 | loss: 3.981687
iter: 4416 | loss: 3.981494
iter: 4417 | loss: 3.981301
iter: 4418 | loss: 3.981107
iter: 4419 | loss: 3.980914
iter: 4420 | loss: 3.980720
iter: 4421 | loss: 3.980527
iter: 4422 | loss: 3.980334
iter: 4423 | loss: 3.980140
iter: 4424 | loss: 3.979947
iter: 4425 | loss: 3.979754
iter: 4426 | loss: 3.979560
iter: 4427 | loss: 3.979367
iter: 4428 | loss: 3.979173
iter: 4429 | loss: 3.978980
iter: 4430 | loss: 3.978787
iter: 4431 | loss: 3.978593
iter: 4432 | loss: 3.978400
iter: 4433 | loss: 3.978206
iter: 4434 | loss: 3.978013
iter: 4435 | loss: 3.977820
iter: 4436 | loss: 3.977626
iter: 4437 | loss: 3.977433
iter: 4438 | loss: 3.977239
iter: 4439 | loss: 3.977046
iter: 4440 | loss: 3.976853
iter: 4441 | loss: 3.976659
iter: 4442 | loss: 3.976466
iter: 4443 | loss: 3.976273
iter: 4444 | loss: 3.976079
iter: 4445 | loss: 3.975886
iter: 4446 | loss: 3.975692
iter: 4447 | loss: 3.975499
iter: 4448 | loss: 3.975306
iter: 4449 | loss: 3.975112
iter: 4450 | loss: 3.974919
iter: 4451 | loss: 3.974725
iter: 4452 | loss: 3.974532
iter: 4453 | loss: 3.974339
iter: 4454 | loss: 3.974145
iter: 4455 | loss: 3.973952
iter: 4456 | loss: 3.973759
iter: 4457 | loss: 3.973565
iter: 4458 | loss: 3.973372
iter: 4459 | loss: 3.973178
iter: 4460 | loss: 3.972985
iter: 4461 | loss: 3.972792
iter: 4462 | loss: 3.972598
iter: 4463 | loss: 3.972405
iter: 4464 | loss: 3.972211
iter: 4465 | loss: 3.972018
iter: 4466 | loss: 3.971825
iter: 4467 | loss: 3.971631
iter: 4468 | loss: 3.971438
iter: 4469 | loss: 3.971244
iter: 4470 | loss: 3.971051
iter: 4471 | loss: 3.970858
iter: 4472 | loss: 3.970664
iter: 4473 | loss: 3.970471
iter: 4474 | loss: 3.970278
iter: 4475 | loss: 3.970084
iter: 4476 | loss: 3.969891
iter: 4477 | loss: 3.969697
iter: 4478 | loss: 3.969504
iter: 4479 | loss: 3.969311
iter: 4480 | loss: 3.969117
iter: 4481 | loss: 3.968924
iter: 4482 | loss: 3.968730
iter: 4483 | loss: 3.968537
iter: 4484 | loss: 3.968344
iter: 4485 | loss: 3.968150
iter: 4486 | loss: 3.967957
iter: 4487 | loss: 3.967764
iter: 4488 | loss: 3.967570
iter: 4489 | loss: 3.967377
iter: 4490 | loss: 3.967183
iter: 4491 | loss: 3.966990
iter: 4492 | loss: 3.966797
iter: 4493 | loss: 3.966603
iter: 4494 | loss: 3.966410
iter: 4495 | loss: 3.966216
iter: 4496 | loss: 3.966023
iter: 4497 | loss: 3.965830
iter: 4498 | loss: 3.965636
iter: 4499 | loss: 3.965443
iter: 4500 | loss: 3.965249
iter: 4501 | loss: 3.965056
iter: 4502 | loss: 3.964863
iter: 4503 | loss: 3.964669
iter: 4504 | loss: 3.964476
iter: 4505 | loss: 3.964283
iter: 4506 | loss: 3.964089
iter: 4507 | loss: 3.963896
iter: 4508 | loss: 3.963702
iter: 4509 | loss: 3.963509
iter: 4510 | loss: 3.963316
iter: 4511 | loss: 3.963122
iter: 4512 | loss: 3.962929
iter: 4513 | loss: 3.962735
iter: 4514 | loss: 3.962542
iter: 4515 | loss: 3.962349
iter: 4516 | loss: 3.962155
iter: 4517 | loss: 3.961962
iter: 4518 | loss: 3.961769
iter: 4519 | loss: 3.961575
iter: 4520 | loss: 3.961382
iter: 4521 | loss: 3.961188
iter: 4522 | loss: 3.960995
iter: 4523 | loss: 3.960802
iter: 4524 | loss: 3.960608
iter: 4525 | loss: 3.960415
iter: 4526 | loss: 3.960221
iter: 4527 | loss: 3.960028
iter: 4528 | loss: 3.959835
iter: 4529 | loss: 3.959641
iter: 4530 | loss: 3.959448
iter: 4531 | loss: 3.959254
iter: 4532 | loss: 3.959061
iter: 4533 | loss: 3.958868
iter: 4534 | loss: 3.958674
iter: 4535 | loss: 3.958481
iter: 4536 | loss: 3.958288
iter: 4537 | loss: 3.958094
iter: 4538 | loss: 3.957901
iter: 4539 | loss: 3.957707
iter: 4540 | loss: 3.957514
iter: 4541 | loss: 3.957321
iter: 4542 | loss: 3.957127
iter: 4543 | loss: 3.956934
iter: 4544 | loss: 3.956740
iter: 4545 | loss: 3.956547
iter: 4546 | loss: 3.956354
iter: 4547 | loss: 3.956160
iter: 4548 | loss: 3.955967
iter: 4549 | loss: 3.955774
iter: 4550 | loss: 3.955580
iter: 4551 | loss: 3.955387
iter: 4552 | loss: 3.955193
iter: 4553 | loss: 3.955000
iter: 4554 | loss: 3.954807
iter: 4555 | loss: 3.954613
iter: 4556 | loss: 3.954420
iter: 4557 | loss: 3.954226
iter: 4558 | loss: 3.954033
iter: 4559 | loss: 3.953840
iter: 4560 | loss: 3.953646
iter: 4561 | loss: 3.953453
iter: 4562 | loss: 3.953259
iter: 4563 | loss: 3.953066
iter: 4564 | loss: 3.952873
iter: 4565 | loss: 3.952679
iter: 4566 | loss: 3.952486
iter: 4567 | loss: 3.952293
iter: 4568 | loss: 3.952099
iter: 4569 | loss: 3.951906
iter: 4570 | loss: 3.951712
iter: 4571 | loss: 3.951519
iter: 4572 | loss: 3.951326
iter: 4573 | loss: 3.951132
iter: 4574 | loss: 3.950939
iter: 4575 | loss: 3.950745
iter: 4576 | loss: 3.950552
iter: 4577 | loss: 3.950359
iter: 4578 | loss: 3.950165
iter: 4579 | loss: 3.949972
iter: 4580 | loss: 3.949779
iter: 4581 | loss: 3.949585
iter: 4582 | loss: 3.949392
iter: 4583 | loss: 3.949198
iter: 4584 | loss: 3.949005
iter: 4585 | loss: 3.948812
iter: 4586 | loss: 3.948618
iter: 4587 | loss: 3.948425
iter: 4588 | loss: 3.948231
iter: 4589 | loss: 3.948038
iter: 4590 | loss: 3.947845
iter: 4591 | loss: 3.947651
iter: 4592 | loss: 3.947458
iter: 4593 | loss: 3.947265
iter: 4594 | loss: 3.947071
iter: 4595 | loss: 3.946878
iter: 4596 | loss: 3.946684
iter: 4597 | loss: 3.946491
iter: 4598 | loss: 3.946298
iter: 4599 | loss: 3.946104
iter: 4600 | loss: 3.945911
iter: 4601 | loss: 3.945717
iter: 4602 | loss: 3.945524
iter: 4603 | loss: 3.945331
iter: 4604 | loss: 3.945137
iter: 4605 | loss: 3.944944
iter: 4606 | loss: 3.944750
iter: 4607 | loss: 3.944557
iter: 4608 | loss: 3.944364
iter: 4609 | loss: 3.944170
iter: 4610 | loss: 3.943977
iter: 4611 | loss: 3.943784
iter: 4612 | loss: 3.943590
iter: 4613 | loss: 3.943397
iter: 4614 | loss: 3.943203
iter: 4615 | loss: 3.943010
iter: 4616 | loss: 3.942817
iter: 4617 | loss: 3.942623
iter: 4618 | loss: 3.942430
iter: 4619 | loss: 3.942236
iter: 4620 | loss: 3.942043
iter: 4621 | loss: 3.941850
iter: 4622 | loss: 3.941656
iter: 4623 | loss: 3.941463
iter: 4624 | loss: 3.941270
iter: 4625 | loss: 3.941076
iter: 4626 | loss: 3.940883
iter: 4627 | loss: 3.940689
iter: 4628 | loss: 3.940496
iter: 4629 | loss: 3.940303
iter: 4630 | loss: 3.940109
iter: 4631 | loss: 3.939916
iter: 4632 | loss: 3.939722
iter: 4633 | loss: 3.939529
iter: 4634 | loss: 3.939336
iter: 4635 | loss: 3.939142
iter: 4636 | loss: 3.938949
iter: 4637 | loss: 3.938755
iter: 4638 | loss: 3.938562
iter: 4639 | loss: 3.938369
iter: 4640 | loss: 3.938175
iter: 4641 | loss: 3.937982
iter: 4642 | loss: 3.937789
iter: 4643 | loss: 3.937595
iter: 4644 | loss: 3.937402
iter: 4645 | loss: 3.937208
iter: 4646 | loss: 3.937015
iter: 4647 | loss: 3.936822
iter: 4648 | loss: 3.936628
iter: 4649 | loss: 3.936435
iter: 4650 | loss: 3.936241
iter: 4651 | loss: 3.936048
iter: 4652 | loss: 3.935855
iter: 4653 | loss: 3.935661
iter: 4654 | loss: 3.935468
iter: 4655 | loss: 3.935275
iter: 4656 | loss: 3.935081
iter: 4657 | loss: 3.934888
iter: 4658 | loss: 3.934694
iter: 4659 | loss: 3.934501
iter: 4660 | loss: 3.934308
iter: 4661 | loss: 3.934114
iter: 4662 | loss: 3.933921
iter: 4663 | loss: 3.933727
iter: 4664 | loss: 3.933534
iter: 4665 | loss: 3.933341
iter: 4666 | loss: 3.933147
iter: 4667 | loss: 3.932954
iter: 4668 | loss: 3.932760
iter: 4669 | loss: 3.932567
iter: 4670 | loss: 3.932374
iter: 4671 | loss: 3.932180
iter: 4672 | loss: 3.931987
iter: 4673 | loss: 3.931794
iter: 4674 | loss: 3.931600
iter: 4675 | loss: 3.931407
iter: 4676 | loss: 3.931213
iter: 4677 | loss: 3.931020
iter: 4678 | loss: 3.930827
iter: 4679 | loss: 3.930633
iter: 4680 | loss: 3.930440
iter: 4681 | loss: 3.930246
iter: 4682 | loss: 3.930053
iter: 4683 | loss: 3.929860
iter: 4684 | loss: 3.929666
iter: 4685 | loss: 3.929473
iter: 4686 | loss: 3.929280
iter: 4687 | loss: 3.929086
iter: 4688 | loss: 3.928893
iter: 4689 | loss: 3.928699
iter: 4690 | loss: 3.928506
iter: 4691 | loss: 3.928313
iter: 4692 | loss: 3.928119
iter: 4693 | loss: 3.927926
iter: 4694 | loss: 3.927732
iter: 4695 | loss: 3.927539
iter: 4696 | loss: 3.927346
iter: 4697 | loss: 3.927152
iter: 4698 | loss: 3.926959
iter: 4699 | loss: 3.926765
iter: 4700 | loss: 3.926572
iter: 4701 | loss: 3.926379
iter: 4702 | loss: 3.926185
iter: 4703 | loss: 3.925992
iter: 4704 | loss: 3.925799
iter: 4705 | loss: 3.925605
iter: 4706 | loss: 3.925412
iter: 4707 | loss: 3.925218
iter: 4708 | loss: 3.925025
iter: 4709 | loss: 3.924832
iter: 4710 | loss: 3.924638
iter: 4711 | loss: 3.924445
iter: 4712 | loss: 3.924251
iter: 4713 | loss: 3.924058
iter: 4714 | loss: 3.923865
iter: 4715 | loss: 3.923671
iter: 4716 | loss: 3.923478
iter: 4717 | loss: 3.923285
iter: 4718 | loss: 3.923091
iter: 4719 | loss: 3.922898
iter: 4720 | loss: 3.922704
iter: 4721 | loss: 3.922511
iter: 4722 | loss: 3.922318
iter: 4723 | loss: 3.922124
iter: 4724 | loss: 3.921931
iter: 4725 | loss: 3.921737
iter: 4726 | loss: 3.921544
iter: 4727 | loss: 3.921351
iter: 4728 | loss: 3.921157
iter: 4729 | loss: 3.920964
iter: 4730 | loss: 3.920770
iter: 4731 | loss: 3.920577
iter: 4732 | loss: 3.920384
iter: 4733 | loss: 3.920190
iter: 4734 | loss: 3.919997
iter: 4735 | loss: 3.919804
iter: 4736 | loss: 3.919610
iter: 4737 | loss: 3.919417
iter: 4738 | loss: 3.919223
iter: 4739 | loss: 3.919030
iter: 4740 | loss: 3.918837
iter: 4741 | loss: 3.918643
iter: 4742 | loss: 3.918450
iter: 4743 | loss: 3.918256
iter: 4744 | loss: 3.918063
iter: 4745 | loss: 3.917870
iter: 4746 | loss: 3.917676
iter: 4747 | loss: 3.917483
iter: 4748 | loss: 3.917290
iter: 4749 | loss: 3.917096
iter: 4750 | loss: 3.916903
iter: 4751 | loss: 3.916709
iter: 4752 | loss: 3.916516
iter: 4753 | loss: 3.916323
iter: 4754 | loss: 3.916129
iter: 4755 | loss: 3.915936
iter: 4756 | loss: 3.915742
iter: 4757 | loss: 3.915549
iter: 4758 | loss: 3.915356
iter: 4759 | loss: 3.915162
iter: 4760 | loss: 3.914969
iter: 4761 | loss: 3.914775
iter: 4762 | loss: 3.914582
iter: 4763 | loss: 3.914389
iter: 4764 | loss: 3.914195
iter: 4765 | loss: 3.914002
iter: 4766 | loss: 3.913809
iter: 4767 | loss: 3.913615
iter: 4768 | loss: 3.913422
iter: 4769 | loss: 3.913228
iter: 4770 | loss: 3.913035
iter: 4771 | loss: 3.912842
iter: 4772 | loss: 3.912648
iter: 4773 | loss: 3.912455
iter: 4774 | loss: 3.912261
iter: 4775 | loss: 3.912068
iter: 4776 | loss: 3.911875
iter: 4777 | loss: 3.911681
iter: 4778 | loss: 3.911488
iter: 4779 | loss: 3.911295
iter: 4780 | loss: 3.911101
iter: 4781 | loss: 3.910908
iter: 4782 | loss: 3.910714
iter: 4783 | loss: 3.910521
iter: 4784 | loss: 3.910328
iter: 4785 | loss: 3.910134
iter: 4786 | loss: 3.909941
iter: 4787 | loss: 3.909747
iter: 4788 | loss: 3.909554
iter: 4789 | loss: 3.909361
iter: 4790 | loss: 3.909167
iter: 4791 | loss: 3.908974
iter: 4792 | loss: 3.908780
iter: 4793 | loss: 3.908587
iter: 4794 | loss: 3.908394
iter: 4795 | loss: 3.908200
iter: 4796 | loss: 3.908007
iter: 4797 | loss: 3.907814
iter: 4798 | loss: 3.907620
iter: 4799 | loss: 3.907427
iter: 4800 | loss: 3.907233
iter: 4801 | loss: 3.907040
iter: 4802 | loss: 3.906847
iter: 4803 | loss: 3.906653
iter: 4804 | loss: 3.906460
iter: 4805 | loss: 3.906266
iter: 4806 | loss: 3.906073
iter: 4807 | loss: 3.905880
iter: 4808 | loss: 3.905686
iter: 4809 | loss: 3.905493
iter: 4810 | loss: 3.905300
iter: 4811 | loss: 3.905106
iter: 4812 | loss: 3.904913
iter: 4813 | loss: 3.904719
iter: 4814 | loss: 3.904526
iter: 4815 | loss: 3.904333
iter: 4816 | loss: 3.904139
iter: 4817 | loss: 3.903946
iter: 4818 | loss: 3.903752
iter: 4819 | loss: 3.903559
iter: 4820 | loss: 3.903366
iter: 4821 | loss: 3.903172
iter: 4822 | loss: 3.902979
iter: 4823 | loss: 3.902785
iter: 4824 | loss: 3.902592
iter: 4825 | loss: 3.902399
iter: 4826 | loss: 3.902205
iter: 4827 | loss: 3.902012
iter: 4828 | loss: 3.901819
iter: 4829 | loss: 3.901625
iter: 4830 | loss: 3.901432
iter: 4831 | loss: 3.901238
iter: 4832 | loss: 3.901045
iter: 4833 | loss: 3.900852
iter: 4834 | loss: 3.900658
iter: 4835 | loss: 3.900465
iter: 4836 | loss: 3.900271
iter: 4837 | loss: 3.900078
iter: 4838 | loss: 3.899885
iter: 4839 | loss: 3.899691
iter: 4840 | loss: 3.899498
iter: 4841 | loss: 3.899305
iter: 4842 | loss: 3.899111
iter: 4843 | loss: 3.898918
iter: 4844 | loss: 3.898724
iter: 4845 | loss: 3.898531
iter: 4846 | loss: 3.898338
iter: 4847 | loss: 3.898144
iter: 4848 | loss: 3.897951
iter: 4849 | loss: 3.897757
iter: 4850 | loss: 3.897564
iter: 4851 | loss: 3.897371
iter: 4852 | loss: 3.897177
iter: 4853 | loss: 3.896984
iter: 4854 | loss: 3.896790
iter: 4855 | loss: 3.896597
iter: 4856 | loss: 3.896404
iter: 4857 | loss: 3.896210
iter: 4858 | loss: 3.896017
iter: 4859 | loss: 3.895824
iter: 4860 | loss: 3.895630
iter: 4861 | loss: 3.895437
iter: 4862 | loss: 3.895243
iter: 4863 | loss: 3.895050
iter: 4864 | loss: 3.894857
iter: 4865 | loss: 3.894663
iter: 4866 | loss: 3.894470
iter: 4867 | loss: 3.894276
iter: 4868 | loss: 3.894083
iter: 4869 | loss: 3.893890
iter: 4870 | loss: 3.893696
iter: 4871 | loss: 3.893503
iter: 4872 | loss: 3.893310
iter: 4873 | loss: 3.893116
iter: 4874 | loss: 3.892923
iter: 4875 | loss: 3.892729
iter: 4876 | loss: 3.892536
iter: 4877 | loss: 3.892343
iter: 4878 | loss: 3.892149
iter: 4879 | loss: 3.891956
iter: 4880 | loss: 3.891762
iter: 4881 | loss: 3.891569
iter: 4882 | loss: 3.891376
iter: 4883 | loss: 3.891182
iter: 4884 | loss: 3.890989
iter: 4885 | loss: 3.890796
iter: 4886 | loss: 3.890602
iter: 4887 | loss: 3.890409
iter: 4888 | loss: 3.890215
iter: 4889 | loss: 3.890022
iter: 4890 | loss: 3.889829
iter: 4891 | loss: 3.889635
iter: 4892 | loss: 3.889442
iter: 4893 | loss: 3.889248
iter: 4894 | loss: 3.889055
iter: 4895 | loss: 3.888862
iter: 4896 | loss: 3.888668
iter: 4897 | loss: 3.888475
iter: 4898 | loss: 3.888281
iter: 4899 | loss: 3.888088
iter: 4900 | loss: 3.887895
iter: 4901 | loss: 3.887701
iter: 4902 | loss: 3.887508
iter: 4903 | loss: 3.887315
iter: 4904 | loss: 3.887121
iter: 4905 | loss: 3.886928
iter: 4906 | loss: 3.886734
iter: 4907 | loss: 3.886541
iter: 4908 | loss: 3.886348
iter: 4909 | loss: 3.886154
iter: 4910 | loss: 3.885961
iter: 4911 | loss: 3.885767
iter: 4912 | loss: 3.885574
iter: 4913 | loss: 3.885381
iter: 4914 | loss: 3.885187
iter: 4915 | loss: 3.884994
iter: 4916 | loss: 3.884801
iter: 4917 | loss: 3.884607
iter: 4918 | loss: 3.884414
iter: 4919 | loss: 3.884220
iter: 4920 | loss: 3.884027
iter: 4921 | loss: 3.883834
iter: 4922 | loss: 3.883640
iter: 4923 | loss: 3.883447
iter: 4924 | loss: 3.883253
iter: 4925 | loss: 3.883060
iter: 4926 | loss: 3.882867
iter: 4927 | loss: 3.882673
iter: 4928 | loss: 3.882480
iter: 4929 | loss: 3.882286
iter: 4930 | loss: 3.882093
iter: 4931 | loss: 3.881900
iter: 4932 | loss: 3.881706
iter: 4933 | loss: 3.881513
iter: 4934 | loss: 3.881320
iter: 4935 | loss: 3.881126
iter: 4936 | loss: 3.880933
iter: 4937 | loss: 3.880739
iter: 4938 | loss: 3.880546
iter: 4939 | loss: 3.880353
iter: 4940 | loss: 3.880159
iter: 4941 | loss: 3.879966
iter: 4942 | loss: 3.879772
iter: 4943 | loss: 3.879579
iter: 4944 | loss: 3.879386
iter: 4945 | loss: 3.879192
iter: 4946 | loss: 3.878999
iter: 4947 | loss: 3.878806
iter: 4948 | loss: 3.878612
iter: 4949 | loss: 3.878419
iter: 4950 | loss: 3.878225
iter: 4951 | loss: 3.878032
iter: 4952 | loss: 3.877839
iter: 4953 | loss: 3.877645
iter: 4954 | loss: 3.877452
iter: 4955 | loss: 3.877258
iter: 4956 | loss: 3.877065
iter: 4957 | loss: 3.876872
iter: 4958 | loss: 3.876678
iter: 4959 | loss: 3.876485
iter: 4960 | loss: 3.876291
iter: 4961 | loss: 3.876098
iter: 4962 | loss: 3.875905
iter: 4963 | loss: 3.875711
iter: 4964 | loss: 3.875518
iter: 4965 | loss: 3.875325
iter: 4966 | loss: 3.875131
iter: 4967 | loss: 3.874938
iter: 4968 | loss: 3.874744
iter: 4969 | loss: 3.874551
iter: 4970 | loss: 3.874358
iter: 4971 | loss: 3.874164
iter: 4972 | loss: 3.873971
iter: 4973 | loss: 3.873777
iter: 4974 | loss: 3.873584
iter: 4975 | loss: 3.873391
iter: 4976 | loss: 3.873197
iter: 4977 | loss: 3.873004
iter: 4978 | loss: 3.872811
iter: 4979 | loss: 3.872617
iter: 4980 | loss: 3.872424
iter: 4981 | loss: 3.872230
iter: 4982 | loss: 3.872037
iter: 4983 | loss: 3.871844
iter: 4984 | loss: 3.871650
iter: 4985 | loss: 3.871457
iter: 4986 | loss: 3.871263
iter: 4987 | loss: 3.871070
iter: 4988 | loss: 3.870877
iter: 4989 | loss: 3.870683
iter: 4990 | loss: 3.870490
iter: 4991 | loss: 3.870296
iter: 4992 | loss: 3.870103
iter: 4993 | loss: 3.869910
iter: 4994 | loss: 3.869716
iter: 4995 | loss: 3.869523
iter: 4996 | loss: 3.869330
iter: 4997 | loss: 3.869136
iter: 4998 | loss: 3.868943
iter: 4999 | loss: 3.868749
iter: 5000 | loss: 3.868556
iter: 5001 | loss: 3.868363
iter: 5002 | loss: 3.868169
iter: 5003 | loss: 3.867976
iter: 5004 | loss: 3.867782
iter: 5005 | loss: 3.867589
iter: 5006 | loss: 3.867396
iter: 5007 | loss: 3.867202
iter: 5008 | loss: 3.867009
iter: 5009 | loss: 3.866816
iter: 5010 | loss: 3.866622
iter: 5011 | loss: 3.866429
iter: 5012 | loss: 3.866235
iter: 5013 | loss: 3.866042
iter: 5014 | loss: 3.865849
iter: 5015 | loss: 3.865655
iter: 5016 | loss: 3.865462
iter: 5017 | loss: 3.865268
iter: 5018 | loss: 3.865075
iter: 5019 | loss: 3.864882
iter: 5020 | loss: 3.864688
iter: 5021 | loss: 3.864495
iter: 5022 | loss: 3.864301
iter: 5023 | loss: 3.864108
iter: 5024 | loss: 3.863915
iter: 5025 | loss: 3.863721
iter: 5026 | loss: 3.863528
iter: 5027 | loss: 3.863335
iter: 5028 | loss: 3.863141
iter: 5029 | loss: 3.862948
iter: 5030 | loss: 3.862754
iter: 5031 | loss: 3.862561
iter: 5032 | loss: 3.862368
iter: 5033 | loss: 3.862174
iter: 5034 | loss: 3.861981
iter: 5035 | loss: 3.861787
iter: 5036 | loss: 3.861594
iter: 5037 | loss: 3.861401
iter: 5038 | loss: 3.861207
iter: 5039 | loss: 3.861014
iter: 5040 | loss: 3.860821
iter: 5041 | loss: 3.860627
iter: 5042 | loss: 3.860434
iter: 5043 | loss: 3.860240
iter: 5044 | loss: 3.860047
iter: 5045 | loss: 3.859854
iter: 5046 | loss: 3.859660
iter: 5047 | loss: 3.859467
iter: 5048 | loss: 3.859273
iter: 5049 | loss: 3.859080
iter: 5050 | loss: 3.858887
iter: 5051 | loss: 3.858693
iter: 5052 | loss: 3.858500
iter: 5053 | loss: 3.858306
iter: 5054 | loss: 3.858113
iter: 5055 | loss: 3.857920
iter: 5056 | loss: 3.857726
iter: 5057 | loss: 3.857533
iter: 5058 | loss: 3.857340
iter: 5059 | loss: 3.857146
iter: 5060 | loss: 3.856953
iter: 5061 | loss: 3.856759
iter: 5062 | loss: 3.856566
iter: 5063 | loss: 3.856373
iter: 5064 | loss: 3.856179
iter: 5065 | loss: 3.855986
iter: 5066 | loss: 3.855792
iter: 5067 | loss: 3.855599
iter: 5068 | loss: 3.855406
iter: 5069 | loss: 3.855212
iter: 5070 | loss: 3.855019
iter: 5071 | loss: 3.854826
iter: 5072 | loss: 3.854632
iter: 5073 | loss: 3.854439
iter: 5074 | loss: 3.854245
iter: 5075 | loss: 3.854052
iter: 5076 | loss: 3.853859
iter: 5077 | loss: 3.853665
iter: 5078 | loss: 3.853472
iter: 5079 | loss: 3.853278
iter: 5080 | loss: 3.853085
iter: 5081 | loss: 3.852892
iter: 5082 | loss: 3.852698
iter: 5083 | loss: 3.852505
iter: 5084 | loss: 3.852311
iter: 5085 | loss: 3.852118
iter: 5086 | loss: 3.851925
iter: 5087 | loss: 3.851731
iter: 5088 | loss: 3.851538
iter: 5089 | loss: 3.851345
iter: 5090 | loss: 3.851151
iter: 5091 | loss: 3.850958
iter: 5092 | loss: 3.850764
iter: 5093 | loss: 3.850571
iter: 5094 | loss: 3.850378
iter: 5095 | loss: 3.850184
iter: 5096 | loss: 3.849991
iter: 5097 | loss: 3.849797
iter: 5098 | loss: 3.849604
iter: 5099 | loss: 3.849411
iter: 5100 | loss: 3.849217
iter: 5101 | loss: 3.849024
iter: 5102 | loss: 3.848831
iter: 5103 | loss: 3.848637
iter: 5104 | loss: 3.848444
iter: 5105 | loss: 3.848250
iter: 5106 | loss: 3.848057
iter: 5107 | loss: 3.847864
iter: 5108 | loss: 3.847670
iter: 5109 | loss: 3.847477
iter: 5110 | loss: 3.847283
iter: 5111 | loss: 3.847090
iter: 5112 | loss: 3.846897
iter: 5113 | loss: 3.846703
iter: 5114 | loss: 3.846510
iter: 5115 | loss: 3.846316
iter: 5116 | loss: 3.846123
iter: 5117 | loss: 3.845930
iter: 5118 | loss: 3.845736
iter: 5119 | loss: 3.845543
iter: 5120 | loss: 3.845350
iter: 5121 | loss: 3.845156
iter: 5122 | loss: 3.844963
iter: 5123 | loss: 3.844769
iter: 5124 | loss: 3.844576
iter: 5125 | loss: 3.844383
iter: 5126 | loss: 3.844189
iter: 5127 | loss: 3.843996
iter: 5128 | loss: 3.843802
iter: 5129 | loss: 3.843609
iter: 5130 | loss: 3.843416
iter: 5131 | loss: 3.843222
iter: 5132 | loss: 3.843029
iter: 5133 | loss: 3.842836
iter: 5134 | loss: 3.842642
iter: 5135 | loss: 3.842449
iter: 5136 | loss: 3.842255
iter: 5137 | loss: 3.842062
iter: 5138 | loss: 3.841869
iter: 5139 | loss: 3.841675
iter: 5140 | loss: 3.841482
iter: 5141 | loss: 3.841288
iter: 5142 | loss: 3.841095
iter: 5143 | loss: 3.840902
iter: 5144 | loss: 3.840708
iter: 5145 | loss: 3.840515
iter: 5146 | loss: 3.840321
iter: 5147 | loss: 3.840128
iter: 5148 | loss: 3.839935
iter: 5149 | loss: 3.839741
iter: 5150 | loss: 3.839548
iter: 5151 | loss: 3.839355
iter: 5152 | loss: 3.839161
iter: 5153 | loss: 3.838968
iter: 5154 | loss: 3.838774
iter: 5155 | loss: 3.838581
iter: 5156 | loss: 3.838388
iter: 5157 | loss: 3.838194
iter: 5158 | loss: 3.838001
iter: 5159 | loss: 3.837807
iter: 5160 | loss: 3.837614
iter: 5161 | loss: 3.837421
iter: 5162 | loss: 3.837227
iter: 5163 | loss: 3.837034
iter: 5164 | loss: 3.836841
iter: 5165 | loss: 3.836647
iter: 5166 | loss: 3.836454
iter: 5167 | loss: 3.836260
iter: 5168 | loss: 3.836067
iter: 5169 | loss: 3.835874
iter: 5170 | loss: 3.835680
iter: 5171 | loss: 3.835487
iter: 5172 | loss: 3.835293
iter: 5173 | loss: 3.835100
iter: 5174 | loss: 3.834907
iter: 5175 | loss: 3.834713
iter: 5176 | loss: 3.834520
iter: 5177 | loss: 3.834326
iter: 5178 | loss: 3.834133
iter: 5179 | loss: 3.833940
iter: 5180 | loss: 3.833746
iter: 5181 | loss: 3.833553
iter: 5182 | loss: 3.833360
iter: 5183 | loss: 3.833166
iter: 5184 | loss: 3.832973
iter: 5185 | loss: 3.832779
iter: 5186 | loss: 3.832586
iter: 5187 | loss: 3.832393
iter: 5188 | loss: 3.832199
iter: 5189 | loss: 3.832006
iter: 5190 | loss: 3.831812
iter: 5191 | loss: 3.831619
iter: 5192 | loss: 3.831426
iter: 5193 | loss: 3.831232
iter: 5194 | loss: 3.831039
iter: 5195 | loss: 3.830846
iter: 5196 | loss: 3.830652
iter: 5197 | loss: 3.830459
iter: 5198 | loss: 3.830265
iter: 5199 | loss: 3.830072
iter: 5200 | loss: 3.829879
iter: 5201 | loss: 3.829685
iter: 5202 | loss: 3.829492
iter: 5203 | loss: 3.829298
iter: 5204 | loss: 3.829105
iter: 5205 | loss: 3.828912
iter: 5206 | loss: 3.828718
iter: 5207 | loss: 3.828525
iter: 5208 | loss: 3.828332
iter: 5209 | loss: 3.828138
iter: 5210 | loss: 3.827945
iter: 5211 | loss: 3.827751
iter: 5212 | loss: 3.827558
iter: 5213 | loss: 3.827365
iter: 5214 | loss: 3.827171
iter: 5215 | loss: 3.826978
iter: 5216 | loss: 3.826784
iter: 5217 | loss: 3.826591
iter: 5218 | loss: 3.826398
iter: 5219 | loss: 3.826204
iter: 5220 | loss: 3.826011
iter: 5221 | loss: 3.825817
iter: 5222 | loss: 3.825624
iter: 5223 | loss: 3.825431
iter: 5224 | loss: 3.825237
iter: 5225 | loss: 3.825044
iter: 5226 | loss: 3.824851
iter: 5227 | loss: 3.824657
iter: 5228 | loss: 3.824464
iter: 5229 | loss: 3.824270
iter: 5230 | loss: 3.824077
iter: 5231 | loss: 3.823884
iter: 5232 | loss: 3.823690
iter: 5233 | loss: 3.823497
iter: 5234 | loss: 3.823303
iter: 5235 | loss: 3.823110
iter: 5236 | loss: 3.822917
iter: 5237 | loss: 3.822723
iter: 5238 | loss: 3.822530
iter: 5239 | loss: 3.822337
iter: 5240 | loss: 3.822143
iter: 5241 | loss: 3.821950
iter: 5242 | loss: 3.821756
iter: 5243 | loss: 3.821563
iter: 5244 | loss: 3.821370
iter: 5245 | loss: 3.821176
iter: 5246 | loss: 3.820983
iter: 5247 | loss: 3.820789
iter: 5248 | loss: 3.820596
iter: 5249 | loss: 3.820403
iter: 5250 | loss: 3.820209
iter: 5251 | loss: 3.820016
iter: 5252 | loss: 3.819822
iter: 5253 | loss: 3.819629
iter: 5254 | loss: 3.819436
iter: 5255 | loss: 3.819242
iter: 5256 | loss: 3.819049
iter: 5257 | loss: 3.818856
iter: 5258 | loss: 3.818662
iter: 5259 | loss: 3.818469
iter: 5260 | loss: 3.818275
iter: 5261 | loss: 3.818082
iter: 5262 | loss: 3.817889
iter: 5263 | loss: 3.817695
iter: 5264 | loss: 3.817502
iter: 5265 | loss: 3.817308
iter: 5266 | loss: 3.817115
iter: 5267 | loss: 3.816922
iter: 5268 | loss: 3.816728
iter: 5269 | loss: 3.816535
iter: 5270 | loss: 3.816342
iter: 5271 | loss: 3.816148
iter: 5272 | loss: 3.815955
iter: 5273 | loss: 3.815761
iter: 5274 | loss: 3.815568
iter: 5275 | loss: 3.815375
iter: 5276 | loss: 3.815181
iter: 5277 | loss: 3.814988
iter: 5278 | loss: 3.814794
iter: 5279 | loss: 3.814601
iter: 5280 | loss: 3.814408
iter: 5281 | loss: 3.814214
iter: 5282 | loss: 3.814021
iter: 5283 | loss: 3.813827
iter: 5284 | loss: 3.813634
iter: 5285 | loss: 3.813441
iter: 5286 | loss: 3.813247
iter: 5287 | loss: 3.813054
iter: 5288 | loss: 3.812861
iter: 5289 | loss: 3.812667
iter: 5290 | loss: 3.812474
iter: 5291 | loss: 3.812280
iter: 5292 | loss: 3.812087
iter: 5293 | loss: 3.811894
iter: 5294 | loss: 3.811700
iter: 5295 | loss: 3.811507
iter: 5296 | loss: 3.811313
iter: 5297 | loss: 3.811120
iter: 5298 | loss: 3.810927
iter: 5299 | loss: 3.810733
iter: 5300 | loss: 3.810540
iter: 5301 | loss: 3.810347
iter: 5302 | loss: 3.810153
iter: 5303 | loss: 3.809960
iter: 5304 | loss: 3.809766
iter: 5305 | loss: 3.809573
iter: 5306 | loss: 3.809380
iter: 5307 | loss: 3.809186
iter: 5308 | loss: 3.808993
iter: 5309 | loss: 3.808799
iter: 5310 | loss: 3.808606
iter: 5311 | loss: 3.808413
iter: 5312 | loss: 3.808219
iter: 5313 | loss: 3.808026
iter: 5314 | loss: 3.807832
iter: 5315 | loss: 3.807639
iter: 5316 | loss: 3.807446
iter: 5317 | loss: 3.807252
iter: 5318 | loss: 3.807059
iter: 5319 | loss: 3.806866
iter: 5320 | loss: 3.806672
iter: 5321 | loss: 3.806479
iter: 5322 | loss: 3.806285
iter: 5323 | loss: 3.806092
iter: 5324 | loss: 3.805899
iter: 5325 | loss: 3.805705
iter: 5326 | loss: 3.805512
iter: 5327 | loss: 3.805318
iter: 5328 | loss: 3.805125
iter: 5329 | loss: 3.804932
iter: 5330 | loss: 3.804738
iter: 5331 | loss: 3.804545
iter: 5332 | loss: 3.804352
iter: 5333 | loss: 3.804158
iter: 5334 | loss: 3.803965
iter: 5335 | loss: 3.803771
iter: 5336 | loss: 3.803578
iter: 5337 | loss: 3.803385
iter: 5338 | loss: 3.803191
iter: 5339 | loss: 3.802998
iter: 5340 | loss: 3.802804
iter: 5341 | loss: 3.802611
iter: 5342 | loss: 3.802418
iter: 5343 | loss: 3.802224
iter: 5344 | loss: 3.802031
iter: 5345 | loss: 3.801837
iter: 5346 | loss: 3.801644
iter: 5347 | loss: 3.801451
iter: 5348 | loss: 3.801257
iter: 5349 | loss: 3.801064
iter: 5350 | loss: 3.800871
iter: 5351 | loss: 3.800677
iter: 5352 | loss: 3.800484
iter: 5353 | loss: 3.800290
iter: 5354 | loss: 3.800097
iter: 5355 | loss: 3.799904
iter: 5356 | loss: 3.799710
iter: 5357 | loss: 3.799517
iter: 5358 | loss: 3.799323
iter: 5359 | loss: 3.799130
iter: 5360 | loss: 3.798937
iter: 5361 | loss: 3.798743
iter: 5362 | loss: 3.798550
iter: 5363 | loss: 3.798357
iter: 5364 | loss: 3.798163
iter: 5365 | loss: 3.797970
iter: 5366 | loss: 3.797776
iter: 5367 | loss: 3.797583
iter: 5368 | loss: 3.797390
iter: 5369 | loss: 3.797196
iter: 5370 | loss: 3.797003
iter: 5371 | loss: 3.796809
iter: 5372 | loss: 3.796616
iter: 5373 | loss: 3.796423
iter: 5374 | loss: 3.796229
iter: 5375 | loss: 3.796036
iter: 5376 | loss: 3.795842
iter: 5377 | loss: 3.795649
iter: 5378 | loss: 3.795456
iter: 5379 | loss: 3.795262
iter: 5380 | loss: 3.795069
iter: 5381 | loss: 3.794876
iter: 5382 | loss: 3.794682
iter: 5383 | loss: 3.794489
iter: 5384 | loss: 3.794295
iter: 5385 | loss: 3.794102
iter: 5386 | loss: 3.793909
iter: 5387 | loss: 3.793715
iter: 5388 | loss: 3.793522
iter: 5389 | loss: 3.793328
iter: 5390 | loss: 3.793135
iter: 5391 | loss: 3.792942
iter: 5392 | loss: 3.792748
iter: 5393 | loss: 3.792555
iter: 5394 | loss: 3.792362
iter: 5395 | loss: 3.792168
iter: 5396 | loss: 3.791975
iter: 5397 | loss: 3.791781
iter: 5398 | loss: 3.791588
iter: 5399 | loss: 3.791395
iter: 5400 | loss: 3.791201
iter: 5401 | loss: 3.791008
iter: 5402 | loss: 3.790814
iter: 5403 | loss: 3.790621
iter: 5404 | loss: 3.790428
iter: 5405 | loss: 3.790234
iter: 5406 | loss: 3.790041
iter: 5407 | loss: 3.789847
iter: 5408 | loss: 3.789654
iter: 5409 | loss: 3.789461
iter: 5410 | loss: 3.789267
iter: 5411 | loss: 3.789074
iter: 5412 | loss: 3.788881
iter: 5413 | loss: 3.788687
iter: 5414 | loss: 3.788494
iter: 5415 | loss: 3.788300
iter: 5416 | loss: 3.788107
iter: 5417 | loss: 3.787914
iter: 5418 | loss: 3.787720
iter: 5419 | loss: 3.787527
iter: 5420 | loss: 3.787333
iter: 5421 | loss: 3.787140
iter: 5422 | loss: 3.786947
iter: 5423 | loss: 3.786753
iter: 5424 | loss: 3.786560
iter: 5425 | loss: 3.786367
iter: 5426 | loss: 3.786173
iter: 5427 | loss: 3.785980
iter: 5428 | loss: 3.785786
iter: 5429 | loss: 3.785593
iter: 5430 | loss: 3.785400
iter: 5431 | loss: 3.785206
iter: 5432 | loss: 3.785013
iter: 5433 | loss: 3.784819
iter: 5434 | loss: 3.784626
iter: 5435 | loss: 3.784433
iter: 5436 | loss: 3.784239
iter: 5437 | loss: 3.784046
iter: 5438 | loss: 3.783852
iter: 5439 | loss: 3.783659
iter: 5440 | loss: 3.783466
iter: 5441 | loss: 3.783272
iter: 5442 | loss: 3.783079
iter: 5443 | loss: 3.782886
iter: 5444 | loss: 3.782692
iter: 5445 | loss: 3.782499
iter: 5446 | loss: 3.782305
iter: 5447 | loss: 3.782112
iter: 5448 | loss: 3.781919
iter: 5449 | loss: 3.781725
iter: 5450 | loss: 3.781532
iter: 5451 | loss: 3.781338
iter: 5452 | loss: 3.781145
iter: 5453 | loss: 3.780952
iter: 5454 | loss: 3.780758
iter: 5455 | loss: 3.780565
iter: 5456 | loss: 3.780372
iter: 5457 | loss: 3.780178
iter: 5458 | loss: 3.779985
iter: 5459 | loss: 3.779791
iter: 5460 | loss: 3.779598
iter: 5461 | loss: 3.779405
iter: 5462 | loss: 3.779211
iter: 5463 | loss: 3.779018
iter: 5464 | loss: 3.778824
iter: 5465 | loss: 3.778631
iter: 5466 | loss: 3.778438
iter: 5467 | loss: 3.778244
iter: 5468 | loss: 3.778051
iter: 5469 | loss: 3.777857
iter: 5470 | loss: 3.777664
iter: 5471 | loss: 3.777471
iter: 5472 | loss: 3.777277
iter: 5473 | loss: 3.777084
iter: 5474 | loss: 3.776891
iter: 5475 | loss: 3.776697
iter: 5476 | loss: 3.776504
iter: 5477 | loss: 3.776310
iter: 5478 | loss: 3.776117
iter: 5479 | loss: 3.775924
iter: 5480 | loss: 3.775730
iter: 5481 | loss: 3.775537
iter: 5482 | loss: 3.775343
iter: 5483 | loss: 3.775150
iter: 5484 | loss: 3.774957
iter: 5485 | loss: 3.774763
iter: 5486 | loss: 3.774570
iter: 5487 | loss: 3.774377
iter: 5488 | loss: 3.774183
iter: 5489 | loss: 3.773990
iter: 5490 | loss: 3.773796
iter: 5491 | loss: 3.773603
iter: 5492 | loss: 3.773410
iter: 5493 | loss: 3.773216
iter: 5494 | loss: 3.773023
iter: 5495 | loss: 3.772829
iter: 5496 | loss: 3.772636
iter: 5497 | loss: 3.772443
iter: 5498 | loss: 3.772249
iter: 5499 | loss: 3.772056
iter: 5500 | loss: 3.771862
iter: 5501 | loss: 3.771669
iter: 5502 | loss: 3.771476
iter: 5503 | loss: 3.771282
iter: 5504 | loss: 3.771089
iter: 5505 | loss: 3.770896
iter: 5506 | loss: 3.770702
iter: 5507 | loss: 3.770509
iter: 5508 | loss: 3.770315
iter: 5509 | loss: 3.770122
iter: 5510 | loss: 3.769929
iter: 5511 | loss: 3.769735
iter: 5512 | loss: 3.769542
iter: 5513 | loss: 3.769348
iter: 5514 | loss: 3.769155
iter: 5515 | loss: 3.768962
iter: 5516 | loss: 3.768768
iter: 5517 | loss: 3.768575
iter: 5518 | loss: 3.768382
iter: 5519 | loss: 3.768188
iter: 5520 | loss: 3.767995
iter: 5521 | loss: 3.767801
iter: 5522 | loss: 3.767608
iter: 5523 | loss: 3.767415
iter: 5524 | loss: 3.767221
iter: 5525 | loss: 3.767028
iter: 5526 | loss: 3.766834
iter: 5527 | loss: 3.766641
iter: 5528 | loss: 3.766448
iter: 5529 | loss: 3.766254
iter: 5530 | loss: 3.766061
iter: 5531 | loss: 3.765868
iter: 5532 | loss: 3.765674
iter: 5533 | loss: 3.765481
iter: 5534 | loss: 3.765287
iter: 5535 | loss: 3.765094
iter: 5536 | loss: 3.764901
iter: 5537 | loss: 3.764707
iter: 5538 | loss: 3.764514
iter: 5539 | loss: 3.764320
iter: 5540 | loss: 3.764127
iter: 5541 | loss: 3.763934
iter: 5542 | loss: 3.763740
iter: 5543 | loss: 3.763547
iter: 5544 | loss: 3.763353
iter: 5545 | loss: 3.763160
iter: 5546 | loss: 3.762967
iter: 5547 | loss: 3.762773
iter: 5548 | loss: 3.762580
iter: 5549 | loss: 3.762387
iter: 5550 | loss: 3.762193
iter: 5551 | loss: 3.762000
iter: 5552 | loss: 3.761806
iter: 5553 | loss: 3.761613
iter: 5554 | loss: 3.761420
iter: 5555 | loss: 3.761226
iter: 5556 | loss: 3.761033
iter: 5557 | loss: 3.760839
iter: 5558 | loss: 3.760646
iter: 5559 | loss: 3.760453
iter: 5560 | loss: 3.760259
iter: 5561 | loss: 3.760066
iter: 5562 | loss: 3.759873
iter: 5563 | loss: 3.759679
iter: 5564 | loss: 3.759486
iter: 5565 | loss: 3.759292
iter: 5566 | loss: 3.759099
iter: 5567 | loss: 3.758906
iter: 5568 | loss: 3.758712
iter: 5569 | loss: 3.758519
iter: 5570 | loss: 3.758325
iter: 5571 | loss: 3.758132
iter: 5572 | loss: 3.757939
iter: 5573 | loss: 3.757745
iter: 5574 | loss: 3.757552
iter: 5575 | loss: 3.757358
iter: 5576 | loss: 3.757165
iter: 5577 | loss: 3.756972
iter: 5578 | loss: 3.756778
iter: 5579 | loss: 3.756585
iter: 5580 | loss: 3.756392
iter: 5581 | loss: 3.756198
iter: 5582 | loss: 3.756005
iter: 5583 | loss: 3.755811
iter: 5584 | loss: 3.755618
iter: 5585 | loss: 3.755425
iter: 5586 | loss: 3.755231
iter: 5587 | loss: 3.755038
iter: 5588 | loss: 3.754844
iter: 5589 | loss: 3.754651
iter: 5590 | loss: 3.754458
iter: 5591 | loss: 3.754264
iter: 5592 | loss: 3.754071
iter: 5593 | loss: 3.753878
iter: 5594 | loss: 3.753684
iter: 5595 | loss: 3.753491
iter: 5596 | loss: 3.753297
iter: 5597 | loss: 3.753104
iter: 5598 | loss: 3.752911
iter: 5599 | loss: 3.752717
iter: 5600 | loss: 3.752524
iter: 5601 | loss: 3.752330
iter: 5602 | loss: 3.752137
iter: 5603 | loss: 3.751944
iter: 5604 | loss: 3.751750
iter: 5605 | loss: 3.751557
iter: 5606 | loss: 3.751363
iter: 5607 | loss: 3.751170
iter: 5608 | loss: 3.750977
iter: 5609 | loss: 3.750783
iter: 5610 | loss: 3.750590
iter: 5611 | loss: 3.750397
iter: 5612 | loss: 3.750203
iter: 5613 | loss: 3.750010
iter: 5614 | loss: 3.749816
iter: 5615 | loss: 3.749623
iter: 5616 | loss: 3.749430
iter: 5617 | loss: 3.749236
iter: 5618 | loss: 3.749043
iter: 5619 | loss: 3.748849
iter: 5620 | loss: 3.748656
iter: 5621 | loss: 3.748463
iter: 5622 | loss: 3.748269
iter: 5623 | loss: 3.748076
iter: 5624 | loss: 3.747883
iter: 5625 | loss: 3.747689
iter: 5626 | loss: 3.747496
iter: 5627 | loss: 3.747302
iter: 5628 | loss: 3.747109
iter: 5629 | loss: 3.746916
iter: 5630 | loss: 3.746722
iter: 5631 | loss: 3.746529
iter: 5632 | loss: 3.746335
iter: 5633 | loss: 3.746142
iter: 5634 | loss: 3.745949
iter: 5635 | loss: 3.745755
iter: 5636 | loss: 3.745562
iter: 5637 | loss: 3.745368
iter: 5638 | loss: 3.745175
iter: 5639 | loss: 3.744982
iter: 5640 | loss: 3.744788
iter: 5641 | loss: 3.744595
iter: 5642 | loss: 3.744402
iter: 5643 | loss: 3.744208
iter: 5644 | loss: 3.744015
iter: 5645 | loss: 3.743821
iter: 5646 | loss: 3.743628
iter: 5647 | loss: 3.743435
iter: 5648 | loss: 3.743241
iter: 5649 | loss: 3.743048
iter: 5650 | loss: 3.742854
iter: 5651 | loss: 3.742661
iter: 5652 | loss: 3.742468
iter: 5653 | loss: 3.742274
iter: 5654 | loss: 3.742081
iter: 5655 | loss: 3.741888
iter: 5656 | loss: 3.741694
iter: 5657 | loss: 3.741501
iter: 5658 | loss: 3.741307
iter: 5659 | loss: 3.741114
iter: 5660 | loss: 3.740921
iter: 5661 | loss: 3.740727
iter: 5662 | loss: 3.740534
iter: 5663 | loss: 3.740340
iter: 5664 | loss: 3.740147
iter: 5665 | loss: 3.739954
iter: 5666 | loss: 3.739760
iter: 5667 | loss: 3.739567
iter: 5668 | loss: 3.739373
iter: 5669 | loss: 3.739180
iter: 5670 | loss: 3.738987
iter: 5671 | loss: 3.738793
iter: 5672 | loss: 3.738600
iter: 5673 | loss: 3.738407
iter: 5674 | loss: 3.738213
iter: 5675 | loss: 3.738020
iter: 5676 | loss: 3.737826
iter: 5677 | loss: 3.737633
iter: 5678 | loss: 3.737440
iter: 5679 | loss: 3.737246
iter: 5680 | loss: 3.737053
iter: 5681 | loss: 3.736859
iter: 5682 | loss: 3.736666
iter: 5683 | loss: 3.736473
iter: 5684 | loss: 3.736279
iter: 5685 | loss: 3.736086
iter: 5686 | loss: 3.735893
iter: 5687 | loss: 3.735699
iter: 5688 | loss: 3.735506
iter: 5689 | loss: 3.735312
iter: 5690 | loss: 3.735119
iter: 5691 | loss: 3.734926
iter: 5692 | loss: 3.734732
iter: 5693 | loss: 3.734539
iter: 5694 | loss: 3.734345
iter: 5695 | loss: 3.734152
iter: 5696 | loss: 3.733959
iter: 5697 | loss: 3.733765
iter: 5698 | loss: 3.733572
iter: 5699 | loss: 3.733378
iter: 5700 | loss: 3.733185
iter: 5701 | loss: 3.732992
iter: 5702 | loss: 3.732798
iter: 5703 | loss: 3.732605
iter: 5704 | loss: 3.732412
iter: 5705 | loss: 3.732218
iter: 5706 | loss: 3.732025
iter: 5707 | loss: 3.731831
iter: 5708 | loss: 3.731638
iter: 5709 | loss: 3.731445
iter: 5710 | loss: 3.731251
iter: 5711 | loss: 3.731058
iter: 5712 | loss: 3.730864
iter: 5713 | loss: 3.730671
iter: 5714 | loss: 3.730478
iter: 5715 | loss: 3.730284
iter: 5716 | loss: 3.730091
iter: 5717 | loss: 3.729898
iter: 5718 | loss: 3.729704
iter: 5719 | loss: 3.729511
iter: 5720 | loss: 3.729317
iter: 5721 | loss: 3.729124
iter: 5722 | loss: 3.728931
iter: 5723 | loss: 3.728737
iter: 5724 | loss: 3.728544
iter: 5725 | loss: 3.728350
iter: 5726 | loss: 3.728157
iter: 5727 | loss: 3.727964
iter: 5728 | loss: 3.727770
iter: 5729 | loss: 3.727577
iter: 5730 | loss: 3.727383
iter: 5731 | loss: 3.727190
iter: 5732 | loss: 3.726997
iter: 5733 | loss: 3.726803
iter: 5734 | loss: 3.726610
iter: 5735 | loss: 3.726417
iter: 5736 | loss: 3.726223
iter: 5737 | loss: 3.726030
iter: 5738 | loss: 3.725836
iter: 5739 | loss: 3.725643
iter: 5740 | loss: 3.725450
iter: 5741 | loss: 3.725256
iter: 5742 | loss: 3.725063
iter: 5743 | loss: 3.724869
iter: 5744 | loss: 3.724676
iter: 5745 | loss: 3.724483
iter: 5746 | loss: 3.724289
iter: 5747 | loss: 3.724096
iter: 5748 | loss: 3.723903
iter: 5749 | loss: 3.723709
iter: 5750 | loss: 3.723516
iter: 5751 | loss: 3.723322
iter: 5752 | loss: 3.723129
iter: 5753 | loss: 3.722936
iter: 5754 | loss: 3.722742
iter: 5755 | loss: 3.722549
iter: 5756 | loss: 3.722355
iter: 5757 | loss: 3.722162
iter: 5758 | loss: 3.721969
iter: 5759 | loss: 3.721775
iter: 5760 | loss: 3.721582
iter: 5761 | loss: 3.721388
iter: 5762 | loss: 3.721195
iter: 5763 | loss: 3.721002
iter: 5764 | loss: 3.720808
iter: 5765 | loss: 3.720615
iter: 5766 | loss: 3.720422
iter: 5767 | loss: 3.720228
iter: 5768 | loss: 3.720035
iter: 5769 | loss: 3.719841
iter: 5770 | loss: 3.719648
iter: 5771 | loss: 3.719455
iter: 5772 | loss: 3.719261
iter: 5773 | loss: 3.719068
iter: 5774 | loss: 3.718874
iter: 5775 | loss: 3.718681
iter: 5776 | loss: 3.718488
iter: 5777 | loss: 3.718294
iter: 5778 | loss: 3.718101
iter: 5779 | loss: 3.717908
iter: 5780 | loss: 3.717714
iter: 5781 | loss: 3.717521
iter: 5782 | loss: 3.717327
iter: 5783 | loss: 3.717134
iter: 5784 | loss: 3.716941
iter: 5785 | loss: 3.716747
iter: 5786 | loss: 3.716554
iter: 5787 | loss: 3.716360
iter: 5788 | loss: 3.716167
iter: 5789 | loss: 3.715974
iter: 5790 | loss: 3.715780
iter: 5791 | loss: 3.715587
iter: 5792 | loss: 3.715393
iter: 5793 | loss: 3.715200
iter: 5794 | loss: 3.715007
iter: 5795 | loss: 3.714813
iter: 5796 | loss: 3.714620
iter: 5797 | loss: 3.714427
iter: 5798 | loss: 3.714233
iter: 5799 | loss: 3.714040
iter: 5800 | loss: 3.713846
iter: 5801 | loss: 3.713653
iter: 5802 | loss: 3.713460
iter: 5803 | loss: 3.713266
iter: 5804 | loss: 3.713073
iter: 5805 | loss: 3.712879
iter: 5806 | loss: 3.712686
iter: 5807 | loss: 3.712493
iter: 5808 | loss: 3.712299
iter: 5809 | loss: 3.712106
iter: 5810 | loss: 3.711913
iter: 5811 | loss: 3.711719
iter: 5812 | loss: 3.711526
iter: 5813 | loss: 3.711332
iter: 5814 | loss: 3.711139
iter: 5815 | loss: 3.710946
iter: 5816 | loss: 3.710752
iter: 5817 | loss: 3.710559
iter: 5818 | loss: 3.710365
iter: 5819 | loss: 3.710172
iter: 5820 | loss: 3.709979
iter: 5821 | loss: 3.709785
iter: 5822 | loss: 3.709592
iter: 5823 | loss: 3.709398
iter: 5824 | loss: 3.709205
iter: 5825 | loss: 3.709012
iter: 5826 | loss: 3.708818
iter: 5827 | loss: 3.708625
iter: 5828 | loss: 3.708432
iter: 5829 | loss: 3.708238
iter: 5830 | loss: 3.708045
iter: 5831 | loss: 3.707851
iter: 5832 | loss: 3.707658
iter: 5833 | loss: 3.707465
iter: 5834 | loss: 3.707271
iter: 5835 | loss: 3.707078
iter: 5836 | loss: 3.706884
iter: 5837 | loss: 3.706691
iter: 5838 | loss: 3.706498
iter: 5839 | loss: 3.706304
iter: 5840 | loss: 3.706111
iter: 5841 | loss: 3.705918
iter: 5842 | loss: 3.705724
iter: 5843 | loss: 3.705531
iter: 5844 | loss: 3.705337
iter: 5845 | loss: 3.705144
iter: 5846 | loss: 3.704951
iter: 5847 | loss: 3.704757
iter: 5848 | loss: 3.704564
iter: 5849 | loss: 3.704370
iter: 5850 | loss: 3.704177
iter: 5851 | loss: 3.703984
iter: 5852 | loss: 3.703790
iter: 5853 | loss: 3.703597
iter: 5854 | loss: 3.703404
iter: 5855 | loss: 3.703210
iter: 5856 | loss: 3.703017
iter: 5857 | loss: 3.702823
iter: 5858 | loss: 3.702630
iter: 5859 | loss: 3.702437
iter: 5860 | loss: 3.702243
iter: 5861 | loss: 3.702050
iter: 5862 | loss: 3.701856
iter: 5863 | loss: 3.701663
iter: 5864 | loss: 3.701470
iter: 5865 | loss: 3.701276
iter: 5866 | loss: 3.701083
iter: 5867 | loss: 3.700889
iter: 5868 | loss: 3.700696
iter: 5869 | loss: 3.700503
iter: 5870 | loss: 3.700309
iter: 5871 | loss: 3.700116
iter: 5872 | loss: 3.699923
iter: 5873 | loss: 3.699729
iter: 5874 | loss: 3.699536
iter: 5875 | loss: 3.699342
iter: 5876 | loss: 3.699149
iter: 5877 | loss: 3.698956
iter: 5878 | loss: 3.698762
iter: 5879 | loss: 3.698569
iter: 5880 | loss: 3.698375
iter: 5881 | loss: 3.698182
iter: 5882 | loss: 3.697989
iter: 5883 | loss: 3.697795
iter: 5884 | loss: 3.697602
iter: 5885 | loss: 3.697409
iter: 5886 | loss: 3.697215
iter: 5887 | loss: 3.697022
iter: 5888 | loss: 3.696828
iter: 5889 | loss: 3.696635
iter: 5890 | loss: 3.696442
iter: 5891 | loss: 3.696248
iter: 5892 | loss: 3.696055
iter: 5893 | loss: 3.695861
iter: 5894 | loss: 3.695668
iter: 5895 | loss: 3.695475
iter: 5896 | loss: 3.695281
iter: 5897 | loss: 3.695088
iter: 5898 | loss: 3.694894
iter: 5899 | loss: 3.694701
iter: 5900 | loss: 3.694508
iter: 5901 | loss: 3.694314
iter: 5902 | loss: 3.694121
iter: 5903 | loss: 3.693928
iter: 5904 | loss: 3.693734
iter: 5905 | loss: 3.693541
iter: 5906 | loss: 3.693347
iter: 5907 | loss: 3.693154
iter: 5908 | loss: 3.692961
iter: 5909 | loss: 3.692767
iter: 5910 | loss: 3.692574
iter: 5911 | loss: 3.692380
iter: 5912 | loss: 3.692187
iter: 5913 | loss: 3.691994
iter: 5914 | loss: 3.691800
iter: 5915 | loss: 3.691607
iter: 5916 | loss: 3.691414
iter: 5917 | loss: 3.691220
iter: 5918 | loss: 3.691027
iter: 5919 | loss: 3.690833
iter: 5920 | loss: 3.690640
iter: 5921 | loss: 3.690447
iter: 5922 | loss: 3.690253
iter: 5923 | loss: 3.690060
iter: 5924 | loss: 3.689866
iter: 5925 | loss: 3.689673
iter: 5926 | loss: 3.689480
iter: 5927 | loss: 3.689286
iter: 5928 | loss: 3.689093
iter: 5929 | loss: 3.688899
iter: 5930 | loss: 3.688706
iter: 5931 | loss: 3.688513
iter: 5932 | loss: 3.688319
iter: 5933 | loss: 3.688126
iter: 5934 | loss: 3.687933
iter: 5935 | loss: 3.687739
iter: 5936 | loss: 3.687546
iter: 5937 | loss: 3.687352
iter: 5938 | loss: 3.687159
iter: 5939 | loss: 3.686966
iter: 5940 | loss: 3.686772
iter: 5941 | loss: 3.686579
iter: 5942 | loss: 3.686385
iter: 5943 | loss: 3.686192
iter: 5944 | loss: 3.685999
iter: 5945 | loss: 3.685805
iter: 5946 | loss: 3.685612
iter: 5947 | loss: 3.685419
iter: 5948 | loss: 3.685225
iter: 5949 | loss: 3.685032
iter: 5950 | loss: 3.684838
iter: 5951 | loss: 3.684645
iter: 5952 | loss: 3.684452
iter: 5953 | loss: 3.684258
iter: 5954 | loss: 3.684065
iter: 5955 | loss: 3.683871
iter: 5956 | loss: 3.683678
iter: 5957 | loss: 3.683485
iter: 5958 | loss: 3.683291
iter: 5959 | loss: 3.683098
iter: 5960 | loss: 3.682904
iter: 5961 | loss: 3.682711
iter: 5962 | loss: 3.682518
iter: 5963 | loss: 3.682324
iter: 5964 | loss: 3.682131
iter: 5965 | loss: 3.681938
iter: 5966 | loss: 3.681744
iter: 5967 | loss: 3.681551
iter: 5968 | loss: 3.681357
iter: 5969 | loss: 3.681164
iter: 5970 | loss: 3.680971
iter: 5971 | loss: 3.680777
iter: 5972 | loss: 3.680584
iter: 5973 | loss: 3.680390
iter: 5974 | loss: 3.680197
iter: 5975 | loss: 3.680004
iter: 5976 | loss: 3.679810
iter: 5977 | loss: 3.679617
iter: 5978 | loss: 3.679424
iter: 5979 | loss: 3.679230
iter: 5980 | loss: 3.679037
iter: 5981 | loss: 3.678843
iter: 5982 | loss: 3.678650
iter: 5983 | loss: 3.678457
iter: 5984 | loss: 3.678263
iter: 5985 | loss: 3.678070
iter: 5986 | loss: 3.677876
iter: 5987 | loss: 3.677683
iter: 5988 | loss: 3.677490
iter: 5989 | loss: 3.677296
iter: 5990 | loss: 3.677103
iter: 5991 | loss: 3.676909
iter: 5992 | loss: 3.676716
iter: 5993 | loss: 3.676523
iter: 5994 | loss: 3.676329
iter: 5995 | loss: 3.676136
iter: 5996 | loss: 3.675943
iter: 5997 | loss: 3.675749
iter: 5998 | loss: 3.675556
iter: 5999 | loss: 3.675362
iter: 6000 | loss: 3.675169
iter: 6001 | loss: 3.674976
iter: 6002 | loss: 3.674782
iter: 6003 | loss: 3.674589
iter: 6004 | loss: 3.674395
iter: 6005 | loss: 3.674202
iter: 6006 | loss: 3.674009
iter: 6007 | loss: 3.673815
iter: 6008 | loss: 3.673622
iter: 6009 | loss: 3.673429
iter: 6010 | loss: 3.673235
iter: 6011 | loss: 3.673042
iter: 6012 | loss: 3.672848
iter: 6013 | loss: 3.672655
iter: 6014 | loss: 3.672462
iter: 6015 | loss: 3.672268
iter: 6016 | loss: 3.672075
iter: 6017 | loss: 3.671881
iter: 6018 | loss: 3.671688
iter: 6019 | loss: 3.671495
iter: 6020 | loss: 3.671301
iter: 6021 | loss: 3.671108
iter: 6022 | loss: 3.670914
iter: 6023 | loss: 3.670721
iter: 6024 | loss: 3.670528
iter: 6025 | loss: 3.670334
iter: 6026 | loss: 3.670141
iter: 6027 | loss: 3.669948
iter: 6028 | loss: 3.669754
iter: 6029 | loss: 3.669561
iter: 6030 | loss: 3.669367
iter: 6031 | loss: 3.669174
iter: 6032 | loss: 3.668981
iter: 6033 | loss: 3.668787
iter: 6034 | loss: 3.668594
iter: 6035 | loss: 3.668400
iter: 6036 | loss: 3.668207
iter: 6037 | loss: 3.668014
iter: 6038 | loss: 3.667820
iter: 6039 | loss: 3.667627
iter: 6040 | loss: 3.667434
iter: 6041 | loss: 3.667240
iter: 6042 | loss: 3.667047
iter: 6043 | loss: 3.666853
iter: 6044 | loss: 3.666660
iter: 6045 | loss: 3.666467
iter: 6046 | loss: 3.666273
iter: 6047 | loss: 3.666080
iter: 6048 | loss: 3.665886
iter: 6049 | loss: 3.665693
iter: 6050 | loss: 3.665500
iter: 6051 | loss: 3.665306
iter: 6052 | loss: 3.665113
iter: 6053 | loss: 3.664919
iter: 6054 | loss: 3.664726
iter: 6055 | loss: 3.664533
iter: 6056 | loss: 3.664339
iter: 6057 | loss: 3.664146
iter: 6058 | loss: 3.663953
iter: 6059 | loss: 3.663759
iter: 6060 | loss: 3.663566
iter: 6061 | loss: 3.663372
iter: 6062 | loss: 3.663179
iter: 6063 | loss: 3.662986
iter: 6064 | loss: 3.662792
iter: 6065 | loss: 3.662599
iter: 6066 | loss: 3.662405
iter: 6067 | loss: 3.662212
iter: 6068 | loss: 3.662019
iter: 6069 | loss: 3.661825
iter: 6070 | loss: 3.661632
iter: 6071 | loss: 3.661439
iter: 6072 | loss: 3.661245
iter: 6073 | loss: 3.661052
iter: 6074 | loss: 3.660858
iter: 6075 | loss: 3.660665
iter: 6076 | loss: 3.660472
iter: 6077 | loss: 3.660278
iter: 6078 | loss: 3.660085
iter: 6079 | loss: 3.659891
iter: 6080 | loss: 3.659698
iter: 6081 | loss: 3.659505
iter: 6082 | loss: 3.659311
iter: 6083 | loss: 3.659118
iter: 6084 | loss: 3.658924
iter: 6085 | loss: 3.658731
iter: 6086 | loss: 3.658538
iter: 6087 | loss: 3.658344
iter: 6088 | loss: 3.658151
iter: 6089 | loss: 3.657958
iter: 6090 | loss: 3.657764
iter: 6091 | loss: 3.657571
iter: 6092 | loss: 3.657377
iter: 6093 | loss: 3.657184
iter: 6094 | loss: 3.656991
iter: 6095 | loss: 3.656797
iter: 6096 | loss: 3.656604
iter: 6097 | loss: 3.656410
iter: 6098 | loss: 3.656217
iter: 6099 | loss: 3.656024
iter: 6100 | loss: 3.655830
iter: 6101 | loss: 3.655637
iter: 6102 | loss: 3.655444
iter: 6103 | loss: 3.655250
iter: 6104 | loss: 3.655057
iter: 6105 | loss: 3.654863
iter: 6106 | loss: 3.654670
iter: 6107 | loss: 3.654477
iter: 6108 | loss: 3.654283
iter: 6109 | loss: 3.654090
iter: 6110 | loss: 3.653896
iter: 6111 | loss: 3.653703
iter: 6112 | loss: 3.653510
iter: 6113 | loss: 3.653316
iter: 6114 | loss: 3.653123
iter: 6115 | loss: 3.652929
iter: 6116 | loss: 3.652736
iter: 6117 | loss: 3.652543
iter: 6118 | loss: 3.652349
iter: 6119 | loss: 3.652156
iter: 6120 | loss: 3.651963
iter: 6121 | loss: 3.651769
iter: 6122 | loss: 3.651576
iter: 6123 | loss: 3.651382
iter: 6124 | loss: 3.651189
iter: 6125 | loss: 3.650996
iter: 6126 | loss: 3.650802
iter: 6127 | loss: 3.650609
iter: 6128 | loss: 3.650415
iter: 6129 | loss: 3.650222
iter: 6130 | loss: 3.650029
iter: 6131 | loss: 3.649835
iter: 6132 | loss: 3.649642
iter: 6133 | loss: 3.649449
iter: 6134 | loss: 3.649255
iter: 6135 | loss: 3.649062
iter: 6136 | loss: 3.648868
iter: 6137 | loss: 3.648675
iter: 6138 | loss: 3.648482
iter: 6139 | loss: 3.648288
iter: 6140 | loss: 3.648095
iter: 6141 | loss: 3.647901
iter: 6142 | loss: 3.647708
iter: 6143 | loss: 3.647515
iter: 6144 | loss: 3.647321
iter: 6145 | loss: 3.647128
iter: 6146 | loss: 3.646934
iter: 6147 | loss: 3.646741
iter: 6148 | loss: 3.646548
iter: 6149 | loss: 3.646354
iter: 6150 | loss: 3.646161
iter: 6151 | loss: 3.645968
iter: 6152 | loss: 3.645774
iter: 6153 | loss: 3.645581
iter: 6154 | loss: 3.645387
iter: 6155 | loss: 3.645194
iter: 6156 | loss: 3.645001
iter: 6157 | loss: 3.644807
iter: 6158 | loss: 3.644614
iter: 6159 | loss: 3.644420
iter: 6160 | loss: 3.644227
iter: 6161 | loss: 3.644034
iter: 6162 | loss: 3.643840
iter: 6163 | loss: 3.643647
iter: 6164 | loss: 3.643454
iter: 6165 | loss: 3.643260
iter: 6166 | loss: 3.643067
iter: 6167 | loss: 3.642873
iter: 6168 | loss: 3.642680
iter: 6169 | loss: 3.642487
iter: 6170 | loss: 3.642293
iter: 6171 | loss: 3.642100
iter: 6172 | loss: 3.641906
iter: 6173 | loss: 3.641713
iter: 6174 | loss: 3.641520
iter: 6175 | loss: 3.641326
iter: 6176 | loss: 3.641133
iter: 6177 | loss: 3.640940
iter: 6178 | loss: 3.640746
iter: 6179 | loss: 3.640553
iter: 6180 | loss: 3.640359
iter: 6181 | loss: 3.640166
iter: 6182 | loss: 3.639973
iter: 6183 | loss: 3.639779
iter: 6184 | loss: 3.639586
iter: 6185 | loss: 3.639392
iter: 6186 | loss: 3.639199
iter: 6187 | loss: 3.639006
iter: 6188 | loss: 3.638812
iter: 6189 | loss: 3.638619
iter: 6190 | loss: 3.638425
iter: 6191 | loss: 3.638232
iter: 6192 | loss: 3.638039
iter: 6193 | loss: 3.637845
iter: 6194 | loss: 3.637652
iter: 6195 | loss: 3.637459
iter: 6196 | loss: 3.637265
iter: 6197 | loss: 3.637072
iter: 6198 | loss: 3.636878
iter: 6199 | loss: 3.636685
iter: 6200 | loss: 3.636492
iter: 6201 | loss: 3.636298
iter: 6202 | loss: 3.636105
iter: 6203 | loss: 3.635911
iter: 6204 | loss: 3.635718
iter: 6205 | loss: 3.635525
iter: 6206 | loss: 3.635331
iter: 6207 | loss: 3.635138
iter: 6208 | loss: 3.634945
iter: 6209 | loss: 3.634751
iter: 6210 | loss: 3.634558
iter: 6211 | loss: 3.634364
iter: 6212 | loss: 3.634171
iter: 6213 | loss: 3.633978
iter: 6214 | loss: 3.633784
iter: 6215 | loss: 3.633591
iter: 6216 | loss: 3.633397
iter: 6217 | loss: 3.633204
iter: 6218 | loss: 3.633011
iter: 6219 | loss: 3.632817
iter: 6220 | loss: 3.632624
iter: 6221 | loss: 3.632430
iter: 6222 | loss: 3.632237
iter: 6223 | loss: 3.632044
iter: 6224 | loss: 3.631850
iter: 6225 | loss: 3.631657
iter: 6226 | loss: 3.631464
iter: 6227 | loss: 3.631270
iter: 6228 | loss: 3.631077
iter: 6229 | loss: 3.630883
iter: 6230 | loss: 3.630690
iter: 6231 | loss: 3.630497
iter: 6232 | loss: 3.630303
iter: 6233 | loss: 3.630110
iter: 6234 | loss: 3.629916
iter: 6235 | loss: 3.629723
iter: 6236 | loss: 3.629530
iter: 6237 | loss: 3.629336
iter: 6238 | loss: 3.629143
iter: 6239 | loss: 3.628950
iter: 6240 | loss: 3.628756
iter: 6241 | loss: 3.628563
iter: 6242 | loss: 3.628369
iter: 6243 | loss: 3.628176
iter: 6244 | loss: 3.627983
iter: 6245 | loss: 3.627789
iter: 6246 | loss: 3.627596
iter: 6247 | loss: 3.627402
iter: 6248 | loss: 3.627209
iter: 6249 | loss: 3.627016
iter: 6250 | loss: 3.626822
iter: 6251 | loss: 3.626629
iter: 6252 | loss: 3.626435
iter: 6253 | loss: 3.626242
iter: 6254 | loss: 3.626049
iter: 6255 | loss: 3.625855
iter: 6256 | loss: 3.625662
iter: 6257 | loss: 3.625469
iter: 6258 | loss: 3.625275
iter: 6259 | loss: 3.625082
iter: 6260 | loss: 3.624888
iter: 6261 | loss: 3.624695
iter: 6262 | loss: 3.624502
iter: 6263 | loss: 3.624308
iter: 6264 | loss: 3.624115
iter: 6265 | loss: 3.623921
iter: 6266 | loss: 3.623728
iter: 6267 | loss: 3.623535
iter: 6268 | loss: 3.623341
iter: 6269 | loss: 3.623148
iter: 6270 | loss: 3.622955
iter: 6271 | loss: 3.622761
iter: 6272 | loss: 3.622568
iter: 6273 | loss: 3.622374
iter: 6274 | loss: 3.622181
iter: 6275 | loss: 3.621988
iter: 6276 | loss: 3.621794
iter: 6277 | loss: 3.621601
iter: 6278 | loss: 3.621407
iter: 6279 | loss: 3.621214
iter: 6280 | loss: 3.621021
iter: 6281 | loss: 3.620827
iter: 6282 | loss: 3.620634
iter: 6283 | loss: 3.620440
iter: 6284 | loss: 3.620247
iter: 6285 | loss: 3.620054
iter: 6286 | loss: 3.619860
iter: 6287 | loss: 3.619667
iter: 6288 | loss: 3.619474
iter: 6289 | loss: 3.619280
iter: 6290 | loss: 3.619087
iter: 6291 | loss: 3.618893
iter: 6292 | loss: 3.618700
iter: 6293 | loss: 3.618507
iter: 6294 | loss: 3.618313
iter: 6295 | loss: 3.618120
iter: 6296 | loss: 3.617926
iter: 6297 | loss: 3.617733
iter: 6298 | loss: 3.617540
iter: 6299 | loss: 3.617346
iter: 6300 | loss: 3.617153
iter: 6301 | loss: 3.616960
iter: 6302 | loss: 3.616766
iter: 6303 | loss: 3.616573
iter: 6304 | loss: 3.616379
iter: 6305 | loss: 3.616186
iter: 6306 | loss: 3.615993
iter: 6307 | loss: 3.615799
iter: 6308 | loss: 3.615606
iter: 6309 | loss: 3.615412
iter: 6310 | loss: 3.615219
iter: 6311 | loss: 3.615026
iter: 6312 | loss: 3.614832
iter: 6313 | loss: 3.614639
iter: 6314 | loss: 3.614445
iter: 6315 | loss: 3.614252
iter: 6316 | loss: 3.614059
iter: 6317 | loss: 3.613865
iter: 6318 | loss: 3.613672
iter: 6319 | loss: 3.613479
iter: 6320 | loss: 3.613285
iter: 6321 | loss: 3.613092
iter: 6322 | loss: 3.612898
iter: 6323 | loss: 3.612705
iter: 6324 | loss: 3.612512
iter: 6325 | loss: 3.612318
iter: 6326 | loss: 3.612125
iter: 6327 | loss: 3.611931
iter: 6328 | loss: 3.611738
iter: 6329 | loss: 3.611545
iter: 6330 | loss: 3.611351
iter: 6331 | loss: 3.611158
iter: 6332 | loss: 3.610965
iter: 6333 | loss: 3.610771
iter: 6334 | loss: 3.610578
iter: 6335 | loss: 3.610384
iter: 6336 | loss: 3.610191
iter: 6337 | loss: 3.609998
iter: 6338 | loss: 3.609804
iter: 6339 | loss: 3.609611
iter: 6340 | loss: 3.609417
iter: 6341 | loss: 3.609224
iter: 6342 | loss: 3.609031
iter: 6343 | loss: 3.608837
iter: 6344 | loss: 3.608644
iter: 6345 | loss: 3.608450
iter: 6346 | loss: 3.608257
iter: 6347 | loss: 3.608064
iter: 6348 | loss: 3.607870
iter: 6349 | loss: 3.607677
iter: 6350 | loss: 3.607484
iter: 6351 | loss: 3.607290
iter: 6352 | loss: 3.607097
iter: 6353 | loss: 3.606903
iter: 6354 | loss: 3.606710
iter: 6355 | loss: 3.606517
iter: 6356 | loss: 3.606323
iter: 6357 | loss: 3.606130
iter: 6358 | loss: 3.605936
iter: 6359 | loss: 3.605743
iter: 6360 | loss: 3.605550
iter: 6361 | loss: 3.605356
iter: 6362 | loss: 3.605163
iter: 6363 | loss: 3.604970
iter: 6364 | loss: 3.604776
iter: 6365 | loss: 3.604583
iter: 6366 | loss: 3.604389
iter: 6367 | loss: 3.604196
iter: 6368 | loss: 3.604003
iter: 6369 | loss: 3.603809
iter: 6370 | loss: 3.603616
iter: 6371 | loss: 3.603422
iter: 6372 | loss: 3.603229
iter: 6373 | loss: 3.603036
iter: 6374 | loss: 3.602842
iter: 6375 | loss: 3.602649
iter: 6376 | loss: 3.602455
iter: 6377 | loss: 3.602262
iter: 6378 | loss: 3.602069
iter: 6379 | loss: 3.601875
iter: 6380 | loss: 3.601682
iter: 6381 | loss: 3.601489
iter: 6382 | loss: 3.601295
iter: 6383 | loss: 3.601102
iter: 6384 | loss: 3.600908
iter: 6385 | loss: 3.600715
iter: 6386 | loss: 3.600522
iter: 6387 | loss: 3.600328
iter: 6388 | loss: 3.600135
iter: 6389 | loss: 3.599941
iter: 6390 | loss: 3.599748
iter: 6391 | loss: 3.599555
iter: 6392 | loss: 3.599361
iter: 6393 | loss: 3.599168
iter: 6394 | loss: 3.598975
iter: 6395 | loss: 3.598781
iter: 6396 | loss: 3.598588
iter: 6397 | loss: 3.598394
iter: 6398 | loss: 3.598201
iter: 6399 | loss: 3.598008
iter: 6400 | loss: 3.597814
iter: 6401 | loss: 3.597621
iter: 6402 | loss: 3.597427
iter: 6403 | loss: 3.597234
iter: 6404 | loss: 3.597041
iter: 6405 | loss: 3.596847
iter: 6406 | loss: 3.596654
iter: 6407 | loss: 3.596460
iter: 6408 | loss: 3.596267
iter: 6409 | loss: 3.596074
iter: 6410 | loss: 3.595880
iter: 6411 | loss: 3.595687
iter: 6412 | loss: 3.595494
iter: 6413 | loss: 3.595300
iter: 6414 | loss: 3.595107
iter: 6415 | loss: 3.594913
iter: 6416 | loss: 3.594720
iter: 6417 | loss: 3.594527
iter: 6418 | loss: 3.594333
iter: 6419 | loss: 3.594140
iter: 6420 | loss: 3.593946
iter: 6421 | loss: 3.593753
iter: 6422 | loss: 3.593560
iter: 6423 | loss: 3.593366
iter: 6424 | loss: 3.593173
iter: 6425 | loss: 3.592980
iter: 6426 | loss: 3.592786
iter: 6427 | loss: 3.592593
iter: 6428 | loss: 3.592399
iter: 6429 | loss: 3.592206
iter: 6430 | loss: 3.592013
iter: 6431 | loss: 3.591819
iter: 6432 | loss: 3.591626
iter: 6433 | loss: 3.591432
iter: 6434 | loss: 3.591239
iter: 6435 | loss: 3.591046
iter: 6436 | loss: 3.590852
iter: 6437 | loss: 3.590659
iter: 6438 | loss: 3.590465
iter: 6439 | loss: 3.590272
iter: 6440 | loss: 3.590079
iter: 6441 | loss: 3.589885
iter: 6442 | loss: 3.589692
iter: 6443 | loss: 3.589499
iter: 6444 | loss: 3.589305
iter: 6445 | loss: 3.589112
iter: 6446 | loss: 3.588918
iter: 6447 | loss: 3.588725
iter: 6448 | loss: 3.588532
iter: 6449 | loss: 3.588338
iter: 6450 | loss: 3.588145
iter: 6451 | loss: 3.587951
iter: 6452 | loss: 3.587758
iter: 6453 | loss: 3.587565
iter: 6454 | loss: 3.587371
iter: 6455 | loss: 3.587178
iter: 6456 | loss: 3.586985
iter: 6457 | loss: 3.586791
iter: 6458 | loss: 3.586598
iter: 6459 | loss: 3.586404
iter: 6460 | loss: 3.586211
iter: 6461 | loss: 3.586018
iter: 6462 | loss: 3.585824
iter: 6463 | loss: 3.585631
iter: 6464 | loss: 3.585437
iter: 6465 | loss: 3.585244
iter: 6466 | loss: 3.585051
iter: 6467 | loss: 3.584857
iter: 6468 | loss: 3.584664
iter: 6469 | loss: 3.584470
iter: 6470 | loss: 3.584277
iter: 6471 | loss: 3.584084
iter: 6472 | loss: 3.583890
iter: 6473 | loss: 3.583697
iter: 6474 | loss: 3.583504
iter: 6475 | loss: 3.583310
iter: 6476 | loss: 3.583117
iter: 6477 | loss: 3.582923
iter: 6478 | loss: 3.582730
iter: 6479 | loss: 3.582537
iter: 6480 | loss: 3.582343
iter: 6481 | loss: 3.582150
iter: 6482 | loss: 3.581956
iter: 6483 | loss: 3.581763
iter: 6484 | loss: 3.581570
iter: 6485 | loss: 3.581376
iter: 6486 | loss: 3.581183
iter: 6487 | loss: 3.580990
iter: 6488 | loss: 3.580796
iter: 6489 | loss: 3.580603
iter: 6490 | loss: 3.580409
iter: 6491 | loss: 3.580216
iter: 6492 | loss: 3.580023
iter: 6493 | loss: 3.579829
iter: 6494 | loss: 3.579636
iter: 6495 | loss: 3.579442
iter: 6496 | loss: 3.579249
iter: 6497 | loss: 3.579056
iter: 6498 | loss: 3.578862
iter: 6499 | loss: 3.578669
iter: 6500 | loss: 3.578476
iter: 6501 | loss: 3.578282
iter: 6502 | loss: 3.578089
iter: 6503 | loss: 3.577895
iter: 6504 | loss: 3.577702
iter: 6505 | loss: 3.577509
iter: 6506 | loss: 3.577315
iter: 6507 | loss: 3.577122
iter: 6508 | loss: 3.576928
iter: 6509 | loss: 3.576735
iter: 6510 | loss: 3.576542
iter: 6511 | loss: 3.576348
iter: 6512 | loss: 3.576155
iter: 6513 | loss: 3.575961
iter: 6514 | loss: 3.575768
iter: 6515 | loss: 3.575575
iter: 6516 | loss: 3.575381
iter: 6517 | loss: 3.575188
iter: 6518 | loss: 3.574995
iter: 6519 | loss: 3.574801
iter: 6520 | loss: 3.574608
iter: 6521 | loss: 3.574414
iter: 6522 | loss: 3.574221
iter: 6523 | loss: 3.574028
iter: 6524 | loss: 3.573834
iter: 6525 | loss: 3.573641
iter: 6526 | loss: 3.573447
iter: 6527 | loss: 3.573254
iter: 6528 | loss: 3.573061
iter: 6529 | loss: 3.572867
iter: 6530 | loss: 3.572674
iter: 6531 | loss: 3.572481
iter: 6532 | loss: 3.572287
iter: 6533 | loss: 3.572094
iter: 6534 | loss: 3.571900
iter: 6535 | loss: 3.571707
iter: 6536 | loss: 3.571514
iter: 6537 | loss: 3.571320
iter: 6538 | loss: 3.571127
iter: 6539 | loss: 3.570933
iter: 6540 | loss: 3.570740
iter: 6541 | loss: 3.570547
iter: 6542 | loss: 3.570353
iter: 6543 | loss: 3.570160
iter: 6544 | loss: 3.569966
iter: 6545 | loss: 3.569773
iter: 6546 | loss: 3.569580
iter: 6547 | loss: 3.569386
iter: 6548 | loss: 3.569193
iter: 6549 | loss: 3.569000
iter: 6550 | loss: 3.568806
iter: 6551 | loss: 3.568613
iter: 6552 | loss: 3.568419
iter: 6553 | loss: 3.568226
iter: 6554 | loss: 3.568033
iter: 6555 | loss: 3.567839
iter: 6556 | loss: 3.567646
iter: 6557 | loss: 3.567452
iter: 6558 | loss: 3.567259
iter: 6559 | loss: 3.567066
iter: 6560 | loss: 3.566872
iter: 6561 | loss: 3.566679
iter: 6562 | loss: 3.566486
iter: 6563 | loss: 3.566292
iter: 6564 | loss: 3.566099
iter: 6565 | loss: 3.565905
iter: 6566 | loss: 3.565712
iter: 6567 | loss: 3.565519
iter: 6568 | loss: 3.565325
iter: 6569 | loss: 3.565132
iter: 6570 | loss: 3.564938
iter: 6571 | loss: 3.564745
iter: 6572 | loss: 3.564552
iter: 6573 | loss: 3.564358
iter: 6574 | loss: 3.564165
iter: 6575 | loss: 3.563971
iter: 6576 | loss: 3.563778
iter: 6577 | loss: 3.563585
iter: 6578 | loss: 3.563391
iter: 6579 | loss: 3.563198
iter: 6580 | loss: 3.563005
iter: 6581 | loss: 3.562811
iter: 6582 | loss: 3.562618
iter: 6583 | loss: 3.562424
iter: 6584 | loss: 3.562231
iter: 6585 | loss: 3.562038
iter: 6586 | loss: 3.561844
iter: 6587 | loss: 3.561651
iter: 6588 | loss: 3.561457
iter: 6589 | loss: 3.561264
iter: 6590 | loss: 3.561071
iter: 6591 | loss: 3.560877
iter: 6592 | loss: 3.560684
iter: 6593 | loss: 3.560491
iter: 6594 | loss: 3.560297
iter: 6595 | loss: 3.560104
iter: 6596 | loss: 3.559910
iter: 6597 | loss: 3.559717
iter: 6598 | loss: 3.559524
iter: 6599 | loss: 3.559330
iter: 6600 | loss: 3.559137
iter: 6601 | loss: 3.558943
iter: 6602 | loss: 3.558750
iter: 6603 | loss: 3.558557
iter: 6604 | loss: 3.558363
iter: 6605 | loss: 3.558170
iter: 6606 | loss: 3.557976
iter: 6607 | loss: 3.557783
iter: 6608 | loss: 3.557590
iter: 6609 | loss: 3.557396
iter: 6610 | loss: 3.557203
iter: 6611 | loss: 3.557010
iter: 6612 | loss: 3.556816
iter: 6613 | loss: 3.556623
iter: 6614 | loss: 3.556429
iter: 6615 | loss: 3.556236
iter: 6616 | loss: 3.556043
iter: 6617 | loss: 3.555849
iter: 6618 | loss: 3.555656
iter: 6619 | loss: 3.555462
iter: 6620 | loss: 3.555269
iter: 6621 | loss: 3.555076
iter: 6622 | loss: 3.554882
iter: 6623 | loss: 3.554689
iter: 6624 | loss: 3.554496
iter: 6625 | loss: 3.554302
iter: 6626 | loss: 3.554109
iter: 6627 | loss: 3.553915
iter: 6628 | loss: 3.553722
iter: 6629 | loss: 3.553529
iter: 6630 | loss: 3.553335
iter: 6631 | loss: 3.553142
iter: 6632 | loss: 3.552948
iter: 6633 | loss: 3.552755
iter: 6634 | loss: 3.552562
iter: 6635 | loss: 3.552368
iter: 6636 | loss: 3.552175
iter: 6637 | loss: 3.551981
iter: 6638 | loss: 3.551788
iter: 6639 | loss: 3.551595
iter: 6640 | loss: 3.551401
iter: 6641 | loss: 3.551208
iter: 6642 | loss: 3.551015
iter: 6643 | loss: 3.550821
iter: 6644 | loss: 3.550628
iter: 6645 | loss: 3.550434
iter: 6646 | loss: 3.550241
iter: 6647 | loss: 3.550048
iter: 6648 | loss: 3.549854
iter: 6649 | loss: 3.549661
iter: 6650 | loss: 3.549467
iter: 6651 | loss: 3.549274
iter: 6652 | loss: 3.549081
iter: 6653 | loss: 3.548887
iter: 6654 | loss: 3.548694
iter: 6655 | loss: 3.548501
iter: 6656 | loss: 3.548307
iter: 6657 | loss: 3.548114
iter: 6658 | loss: 3.547920
iter: 6659 | loss: 3.547727
iter: 6660 | loss: 3.547534
iter: 6661 | loss: 3.547340
iter: 6662 | loss: 3.547147
iter: 6663 | loss: 3.546953
iter: 6664 | loss: 3.546760
iter: 6665 | loss: 3.546567
iter: 6666 | loss: 3.546373
iter: 6667 | loss: 3.546180
iter: 6668 | loss: 3.545986
iter: 6669 | loss: 3.545793
iter: 6670 | loss: 3.545600
iter: 6671 | loss: 3.545406
iter: 6672 | loss: 3.545213
iter: 6673 | loss: 3.545020
iter: 6674 | loss: 3.544826
iter: 6675 | loss: 3.544633
iter: 6676 | loss: 3.544439
iter: 6677 | loss: 3.544246
iter: 6678 | loss: 3.544053
iter: 6679 | loss: 3.543859
iter: 6680 | loss: 3.543666
iter: 6681 | loss: 3.543472
iter: 6682 | loss: 3.543279
iter: 6683 | loss: 3.543086
iter: 6684 | loss: 3.542892
iter: 6685 | loss: 3.542699
iter: 6686 | loss: 3.542506
iter: 6687 | loss: 3.542312
iter: 6688 | loss: 3.542119
iter: 6689 | loss: 3.541925
iter: 6690 | loss: 3.541732
iter: 6691 | loss: 3.541539
iter: 6692 | loss: 3.541345
iter: 6693 | loss: 3.541152
iter: 6694 | loss: 3.540958
iter: 6695 | loss: 3.540765
iter: 6696 | loss: 3.540572
iter: 6697 | loss: 3.540378
iter: 6698 | loss: 3.540185
iter: 6699 | loss: 3.539991
iter: 6700 | loss: 3.539798
iter: 6701 | loss: 3.539605
iter: 6702 | loss: 3.539411
iter: 6703 | loss: 3.539218
iter: 6704 | loss: 3.539025
iter: 6705 | loss: 3.538831
iter: 6706 | loss: 3.538638
iter: 6707 | loss: 3.538444
iter: 6708 | loss: 3.538251
iter: 6709 | loss: 3.538058
iter: 6710 | loss: 3.537864
iter: 6711 | loss: 3.537671
iter: 6712 | loss: 3.537477
iter: 6713 | loss: 3.537284
iter: 6714 | loss: 3.537091
iter: 6715 | loss: 3.536897
iter: 6716 | loss: 3.536704
iter: 6717 | loss: 3.536511
iter: 6718 | loss: 3.536317
iter: 6719 | loss: 3.536124
iter: 6720 | loss: 3.535930
iter: 6721 | loss: 3.535737
iter: 6722 | loss: 3.535544
iter: 6723 | loss: 3.535350
iter: 6724 | loss: 3.535157
iter: 6725 | loss: 3.534963
iter: 6726 | loss: 3.534770
iter: 6727 | loss: 3.534577
iter: 6728 | loss: 3.534383
iter: 6729 | loss: 3.534190
iter: 6730 | loss: 3.533996
iter: 6731 | loss: 3.533803
iter: 6732 | loss: 3.533610
iter: 6733 | loss: 3.533416
iter: 6734 | loss: 3.533223
iter: 6735 | loss: 3.533030
iter: 6736 | loss: 3.532836
iter: 6737 | loss: 3.532643
iter: 6738 | loss: 3.532449
iter: 6739 | loss: 3.532256
iter: 6740 | loss: 3.532063
iter: 6741 | loss: 3.531869
iter: 6742 | loss: 3.531676
iter: 6743 | loss: 3.531482
iter: 6744 | loss: 3.531289
iter: 6745 | loss: 3.531096
iter: 6746 | loss: 3.530902
iter: 6747 | loss: 3.530709
iter: 6748 | loss: 3.530516
iter: 6749 | loss: 3.530322
iter: 6750 | loss: 3.530129
iter: 6751 | loss: 3.529935
iter: 6752 | loss: 3.529742
iter: 6753 | loss: 3.529549
iter: 6754 | loss: 3.529355
iter: 6755 | loss: 3.529162
iter: 6756 | loss: 3.528968
iter: 6757 | loss: 3.528775
iter: 6758 | loss: 3.528582
iter: 6759 | loss: 3.528388
iter: 6760 | loss: 3.528195
iter: 6761 | loss: 3.528001
iter: 6762 | loss: 3.527808
iter: 6763 | loss: 3.527615
iter: 6764 | loss: 3.527421
iter: 6765 | loss: 3.527228
iter: 6766 | loss: 3.527035
iter: 6767 | loss: 3.526841
iter: 6768 | loss: 3.526648
iter: 6769 | loss: 3.526454
iter: 6770 | loss: 3.526261
iter: 6771 | loss: 3.526068
iter: 6772 | loss: 3.525874
iter: 6773 | loss: 3.525681
iter: 6774 | loss: 3.525487
iter: 6775 | loss: 3.525294
iter: 6776 | loss: 3.525101
iter: 6777 | loss: 3.524907
iter: 6778 | loss: 3.524714
iter: 6779 | loss: 3.524521
iter: 6780 | loss: 3.524327
iter: 6781 | loss: 3.524134
iter: 6782 | loss: 3.523940
iter: 6783 | loss: 3.523747
iter: 6784 | loss: 3.523554
iter: 6785 | loss: 3.523360
iter: 6786 | loss: 3.523167
iter: 6787 | loss: 3.522973
iter: 6788 | loss: 3.522780
iter: 6789 | loss: 3.522587
iter: 6790 | loss: 3.522393
iter: 6791 | loss: 3.522200
iter: 6792 | loss: 3.522006
iter: 6793 | loss: 3.521813
iter: 6794 | loss: 3.521620
iter: 6795 | loss: 3.521426
iter: 6796 | loss: 3.521233
iter: 6797 | loss: 3.521040
iter: 6798 | loss: 3.520846
iter: 6799 | loss: 3.520653
iter: 6800 | loss: 3.520459
iter: 6801 | loss: 3.520266
iter: 6802 | loss: 3.520073
iter: 6803 | loss: 3.519879
iter: 6804 | loss: 3.519686
iter: 6805 | loss: 3.519492
iter: 6806 | loss: 3.519299
iter: 6807 | loss: 3.519106
iter: 6808 | loss: 3.518912
iter: 6809 | loss: 3.518719
iter: 6810 | loss: 3.518526
iter: 6811 | loss: 3.518332
iter: 6812 | loss: 3.518139
iter: 6813 | loss: 3.517945
iter: 6814 | loss: 3.517752
iter: 6815 | loss: 3.517559
iter: 6816 | loss: 3.517365
iter: 6817 | loss: 3.517172
iter: 6818 | loss: 3.516978
iter: 6819 | loss: 3.516785
iter: 6820 | loss: 3.516592
iter: 6821 | loss: 3.516398
iter: 6822 | loss: 3.516205
iter: 6823 | loss: 3.516012
iter: 6824 | loss: 3.515818
iter: 6825 | loss: 3.515625
iter: 6826 | loss: 3.515431
iter: 6827 | loss: 3.515238
iter: 6828 | loss: 3.515045
iter: 6829 | loss: 3.514851
iter: 6830 | loss: 3.514658
iter: 6831 | loss: 3.514464
iter: 6832 | loss: 3.514271
iter: 6833 | loss: 3.514078
iter: 6834 | loss: 3.513884
iter: 6835 | loss: 3.513691
iter: 6836 | loss: 3.513497
iter: 6837 | loss: 3.513304
iter: 6838 | loss: 3.513111
iter: 6839 | loss: 3.512917
iter: 6840 | loss: 3.512724
iter: 6841 | loss: 3.512531
iter: 6842 | loss: 3.512337
iter: 6843 | loss: 3.512144
iter: 6844 | loss: 3.511950
iter: 6845 | loss: 3.511757
iter: 6846 | loss: 3.511564
iter: 6847 | loss: 3.511370
iter: 6848 | loss: 3.511177
iter: 6849 | loss: 3.510983
iter: 6850 | loss: 3.510790
iter: 6851 | loss: 3.510597
iter: 6852 | loss: 3.510403
iter: 6853 | loss: 3.510210
iter: 6854 | loss: 3.510017
iter: 6855 | loss: 3.509823
iter: 6856 | loss: 3.509630
iter: 6857 | loss: 3.509436
iter: 6858 | loss: 3.509243
iter: 6859 | loss: 3.509050
iter: 6860 | loss: 3.508856
iter: 6861 | loss: 3.508663
iter: 6862 | loss: 3.508469
iter: 6863 | loss: 3.508276
iter: 6864 | loss: 3.508083
iter: 6865 | loss: 3.507889
iter: 6866 | loss: 3.507696
iter: 6867 | loss: 3.507502
iter: 6868 | loss: 3.507309
iter: 6869 | loss: 3.507116
iter: 6870 | loss: 3.506922
iter: 6871 | loss: 3.506729
iter: 6872 | loss: 3.506536
iter: 6873 | loss: 3.506342
iter: 6874 | loss: 3.506149
iter: 6875 | loss: 3.505955
iter: 6876 | loss: 3.505762
iter: 6877 | loss: 3.505569
iter: 6878 | loss: 3.505375
iter: 6879 | loss: 3.505182
iter: 6880 | loss: 3.504988
iter: 6881 | loss: 3.504795
iter: 6882 | loss: 3.504602
iter: 6883 | loss: 3.504408
iter: 6884 | loss: 3.504215
iter: 6885 | loss: 3.504022
iter: 6886 | loss: 3.503828
iter: 6887 | loss: 3.503635
iter: 6888 | loss: 3.503441
iter: 6889 | loss: 3.503248
iter: 6890 | loss: 3.503055
iter: 6891 | loss: 3.502861
iter: 6892 | loss: 3.502668
iter: 6893 | loss: 3.502474
iter: 6894 | loss: 3.502281
iter: 6895 | loss: 3.502088
iter: 6896 | loss: 3.501894
iter: 6897 | loss: 3.501701
iter: 6898 | loss: 3.501507
iter: 6899 | loss: 3.501314
iter: 6900 | loss: 3.501121
iter: 6901 | loss: 3.500927
iter: 6902 | loss: 3.500734
iter: 6903 | loss: 3.500541
iter: 6904 | loss: 3.500347
iter: 6905 | loss: 3.500154
iter: 6906 | loss: 3.499960
iter: 6907 | loss: 3.499767
iter: 6908 | loss: 3.499574
iter: 6909 | loss: 3.499380
iter: 6910 | loss: 3.499187
iter: 6911 | loss: 3.498993
iter: 6912 | loss: 3.498800
iter: 6913 | loss: 3.498607
iter: 6914 | loss: 3.498413
iter: 6915 | loss: 3.498220
iter: 6916 | loss: 3.498027
iter: 6917 | loss: 3.497833
iter: 6918 | loss: 3.497640
iter: 6919 | loss: 3.497446
iter: 6920 | loss: 3.497253
iter: 6921 | loss: 3.497060
iter: 6922 | loss: 3.496866
iter: 6923 | loss: 3.496673
iter: 6924 | loss: 3.496479
iter: 6925 | loss: 3.496286
iter: 6926 | loss: 3.496093
iter: 6927 | loss: 3.495899
iter: 6928 | loss: 3.495706
iter: 6929 | loss: 3.495512
iter: 6930 | loss: 3.495319
iter: 6931 | loss: 3.495126
iter: 6932 | loss: 3.494932
iter: 6933 | loss: 3.494739
iter: 6934 | loss: 3.494546
iter: 6935 | loss: 3.494352
iter: 6936 | loss: 3.494159
iter: 6937 | loss: 3.493965
iter: 6938 | loss: 3.493772
iter: 6939 | loss: 3.493579
iter: 6940 | loss: 3.493385
iter: 6941 | loss: 3.493192
iter: 6942 | loss: 3.492998
iter: 6943 | loss: 3.492805
iter: 6944 | loss: 3.492612
iter: 6945 | loss: 3.492418
iter: 6946 | loss: 3.492225
iter: 6947 | loss: 3.492032
iter: 6948 | loss: 3.491838
iter: 6949 | loss: 3.491645
iter: 6950 | loss: 3.491451
iter: 6951 | loss: 3.491258
iter: 6952 | loss: 3.491065
iter: 6953 | loss: 3.490871
iter: 6954 | loss: 3.490678
iter: 6955 | loss: 3.490484
iter: 6956 | loss: 3.490291
iter: 6957 | loss: 3.490098
iter: 6958 | loss: 3.489904
iter: 6959 | loss: 3.489711
iter: 6960 | loss: 3.489517
iter: 6961 | loss: 3.489324
iter: 6962 | loss: 3.489131
iter: 6963 | loss: 3.488937
iter: 6964 | loss: 3.488744
iter: 6965 | loss: 3.488551
iter: 6966 | loss: 3.488357
iter: 6967 | loss: 3.488164
iter: 6968 | loss: 3.487970
iter: 6969 | loss: 3.487777
iter: 6970 | loss: 3.487584
iter: 6971 | loss: 3.487390
iter: 6972 | loss: 3.487197
iter: 6973 | loss: 3.487003
iter: 6974 | loss: 3.486810
iter: 6975 | loss: 3.486617
iter: 6976 | loss: 3.486423
iter: 6977 | loss: 3.486230
iter: 6978 | loss: 3.486037
iter: 6979 | loss: 3.485843
iter: 6980 | loss: 3.485650
iter: 6981 | loss: 3.485456
iter: 6982 | loss: 3.485263
iter: 6983 | loss: 3.485070
iter: 6984 | loss: 3.484876
iter: 6985 | loss: 3.484683
iter: 6986 | loss: 3.484489
iter: 6987 | loss: 3.484296
iter: 6988 | loss: 3.484103
iter: 6989 | loss: 3.483909
iter: 6990 | loss: 3.483716
iter: 6991 | loss: 3.483522
iter: 6992 | loss: 3.483329
iter: 6993 | loss: 3.483136
iter: 6994 | loss: 3.482942
iter: 6995 | loss: 3.482749
iter: 6996 | loss: 3.482556
iter: 6997 | loss: 3.482362
iter: 6998 | loss: 3.482169
iter: 6999 | loss: 3.481975
iter: 7000 | loss: 3.481782
iter: 7001 | loss: 3.481589
iter: 7002 | loss: 3.481395
iter: 7003 | loss: 3.481202
iter: 7004 | loss: 3.481008
iter: 7005 | loss: 3.480815
iter: 7006 | loss: 3.480622
iter: 7007 | loss: 3.480428
iter: 7008 | loss: 3.480235
iter: 7009 | loss: 3.480042
iter: 7010 | loss: 3.479848
iter: 7011 | loss: 3.479655
iter: 7012 | loss: 3.479461
iter: 7013 | loss: 3.479268
iter: 7014 | loss: 3.479075
iter: 7015 | loss: 3.478881
iter: 7016 | loss: 3.478688
iter: 7017 | loss: 3.478494
iter: 7018 | loss: 3.478301
iter: 7019 | loss: 3.478108
iter: 7020 | loss: 3.477914
iter: 7021 | loss: 3.477721
iter: 7022 | loss: 3.477527
iter: 7023 | loss: 3.477334
iter: 7024 | loss: 3.477141
iter: 7025 | loss: 3.476947
iter: 7026 | loss: 3.476754
iter: 7027 | loss: 3.476561
iter: 7028 | loss: 3.476367
iter: 7029 | loss: 3.476174
iter: 7030 | loss: 3.475980
iter: 7031 | loss: 3.475787
iter: 7032 | loss: 3.475594
iter: 7033 | loss: 3.475400
iter: 7034 | loss: 3.475207
iter: 7035 | loss: 3.475013
iter: 7036 | loss: 3.474820
iter: 7037 | loss: 3.474627
iter: 7038 | loss: 3.474433
iter: 7039 | loss: 3.474240
iter: 7040 | loss: 3.474047
iter: 7041 | loss: 3.473853
iter: 7042 | loss: 3.473660
iter: 7043 | loss: 3.473466
iter: 7044 | loss: 3.473273
iter: 7045 | loss: 3.473080
iter: 7046 | loss: 3.472886
iter: 7047 | loss: 3.472693
iter: 7048 | loss: 3.472499
iter: 7049 | loss: 3.472306
iter: 7050 | loss: 3.472113
iter: 7051 | loss: 3.471919
iter: 7052 | loss: 3.471726
iter: 7053 | loss: 3.471532
iter: 7054 | loss: 3.471339
iter: 7055 | loss: 3.471146
iter: 7056 | loss: 3.470952
iter: 7057 | loss: 3.470759
iter: 7058 | loss: 3.470566
iter: 7059 | loss: 3.470372
iter: 7060 | loss: 3.470179
iter: 7061 | loss: 3.469985
iter: 7062 | loss: 3.469792
iter: 7063 | loss: 3.469599
iter: 7064 | loss: 3.469405
iter: 7065 | loss: 3.469212
iter: 7066 | loss: 3.469018
iter: 7067 | loss: 3.468825
iter: 7068 | loss: 3.468632
iter: 7069 | loss: 3.468438
iter: 7070 | loss: 3.468245
iter: 7071 | loss: 3.468052
iter: 7072 | loss: 3.467858
iter: 7073 | loss: 3.467665
iter: 7074 | loss: 3.467471
iter: 7075 | loss: 3.467278
iter: 7076 | loss: 3.467085
iter: 7077 | loss: 3.466891
iter: 7078 | loss: 3.466698
iter: 7079 | loss: 3.466504
iter: 7080 | loss: 3.466311
iter: 7081 | loss: 3.466118
iter: 7082 | loss: 3.465924
iter: 7083 | loss: 3.465731
iter: 7084 | loss: 3.465537
iter: 7085 | loss: 3.465344
iter: 7086 | loss: 3.465151
iter: 7087 | loss: 3.464957
iter: 7088 | loss: 3.464764
iter: 7089 | loss: 3.464571
iter: 7090 | loss: 3.464377
iter: 7091 | loss: 3.464184
iter: 7092 | loss: 3.463990
iter: 7093 | loss: 3.463797
iter: 7094 | loss: 3.463604
iter: 7095 | loss: 3.463410
iter: 7096 | loss: 3.463217
iter: 7097 | loss: 3.463023
iter: 7098 | loss: 3.462830
iter: 7099 | loss: 3.462637
iter: 7100 | loss: 3.462443
iter: 7101 | loss: 3.462250
iter: 7102 | loss: 3.462057
iter: 7103 | loss: 3.461863
iter: 7104 | loss: 3.461670
iter: 7105 | loss: 3.461476
iter: 7106 | loss: 3.461283
iter: 7107 | loss: 3.461090
iter: 7108 | loss: 3.460896
iter: 7109 | loss: 3.460703
iter: 7110 | loss: 3.460509
iter: 7111 | loss: 3.460316
iter: 7112 | loss: 3.460123
iter: 7113 | loss: 3.459929
iter: 7114 | loss: 3.459736
iter: 7115 | loss: 3.459542
iter: 7116 | loss: 3.459349
iter: 7117 | loss: 3.459156
iter: 7118 | loss: 3.458962
iter: 7119 | loss: 3.458769
iter: 7120 | loss: 3.458576
iter: 7121 | loss: 3.458382
iter: 7122 | loss: 3.458189
iter: 7123 | loss: 3.457995
iter: 7124 | loss: 3.457802
iter: 7125 | loss: 3.457609
iter: 7126 | loss: 3.457415
iter: 7127 | loss: 3.457222
iter: 7128 | loss: 3.457028
iter: 7129 | loss: 3.456835
iter: 7130 | loss: 3.456642
iter: 7131 | loss: 3.456448
iter: 7132 | loss: 3.456255
iter: 7133 | loss: 3.456062
iter: 7134 | loss: 3.455868
iter: 7135 | loss: 3.455675
iter: 7136 | loss: 3.455481
iter: 7137 | loss: 3.455288
iter: 7138 | loss: 3.455095
iter: 7139 | loss: 3.454901
iter: 7140 | loss: 3.454708
iter: 7141 | loss: 3.454514
iter: 7142 | loss: 3.454321
iter: 7143 | loss: 3.454128
iter: 7144 | loss: 3.453934
iter: 7145 | loss: 3.453741
iter: 7146 | loss: 3.453548
iter: 7147 | loss: 3.453354
iter: 7148 | loss: 3.453161
iter: 7149 | loss: 3.452967
iter: 7150 | loss: 3.452774
iter: 7151 | loss: 3.452581
iter: 7152 | loss: 3.452387
iter: 7153 | loss: 3.452194
iter: 7154 | loss: 3.452000
iter: 7155 | loss: 3.451807
iter: 7156 | loss: 3.451614
iter: 7157 | loss: 3.451420
iter: 7158 | loss: 3.451227
iter: 7159 | loss: 3.451033
iter: 7160 | loss: 3.450840
iter: 7161 | loss: 3.450647
iter: 7162 | loss: 3.450453
iter: 7163 | loss: 3.450260
iter: 7164 | loss: 3.450067
iter: 7165 | loss: 3.449873
iter: 7166 | loss: 3.449680
iter: 7167 | loss: 3.449486
iter: 7168 | loss: 3.449293
iter: 7169 | loss: 3.449100
iter: 7170 | loss: 3.448906
iter: 7171 | loss: 3.448713
iter: 7172 | loss: 3.448519
iter: 7173 | loss: 3.448326
iter: 7174 | loss: 3.448133
iter: 7175 | loss: 3.447939
iter: 7176 | loss: 3.447746
iter: 7177 | loss: 3.447553
iter: 7178 | loss: 3.447359
iter: 7179 | loss: 3.447166
iter: 7180 | loss: 3.446972
iter: 7181 | loss: 3.446779
iter: 7182 | loss: 3.446586
iter: 7183 | loss: 3.446392
iter: 7184 | loss: 3.446199
iter: 7185 | loss: 3.446005
iter: 7186 | loss: 3.445812
iter: 7187 | loss: 3.445619
iter: 7188 | loss: 3.445425
iter: 7189 | loss: 3.445232
iter: 7190 | loss: 3.445038
iter: 7191 | loss: 3.444845
iter: 7192 | loss: 3.444652
iter: 7193 | loss: 3.444458
iter: 7194 | loss: 3.444265
iter: 7195 | loss: 3.444072
iter: 7196 | loss: 3.443878
iter: 7197 | loss: 3.443685
iter: 7198 | loss: 3.443491
iter: 7199 | loss: 3.443298
iter: 7200 | loss: 3.443105
iter: 7201 | loss: 3.442911
iter: 7202 | loss: 3.442718
iter: 7203 | loss: 3.442524
iter: 7204 | loss: 3.442331
iter: 7205 | loss: 3.442138
iter: 7206 | loss: 3.441944
iter: 7207 | loss: 3.441751
iter: 7208 | loss: 3.441558
iter: 7209 | loss: 3.441364
iter: 7210 | loss: 3.441171
iter: 7211 | loss: 3.440977
iter: 7212 | loss: 3.440784
iter: 7213 | loss: 3.440591
iter: 7214 | loss: 3.440397
iter: 7215 | loss: 3.440204
iter: 7216 | loss: 3.440010
iter: 7217 | loss: 3.439817
iter: 7218 | loss: 3.439624
iter: 7219 | loss: 3.439430
iter: 7220 | loss: 3.439237
iter: 7221 | loss: 3.439043
iter: 7222 | loss: 3.438850
iter: 7223 | loss: 3.438657
iter: 7224 | loss: 3.438463
iter: 7225 | loss: 3.438270
iter: 7226 | loss: 3.438077
iter: 7227 | loss: 3.437883
iter: 7228 | loss: 3.437690
iter: 7229 | loss: 3.437496
iter: 7230 | loss: 3.437303
iter: 7231 | loss: 3.437110
iter: 7232 | loss: 3.436916
iter: 7233 | loss: 3.436723
iter: 7234 | loss: 3.436529
iter: 7235 | loss: 3.436336
iter: 7236 | loss: 3.436143
iter: 7237 | loss: 3.435949
iter: 7238 | loss: 3.435756
iter: 7239 | loss: 3.435563
iter: 7240 | loss: 3.435369
iter: 7241 | loss: 3.435176
iter: 7242 | loss: 3.434982
iter: 7243 | loss: 3.434789
iter: 7244 | loss: 3.434596
iter: 7245 | loss: 3.434402
iter: 7246 | loss: 3.434209
iter: 7247 | loss: 3.434015
iter: 7248 | loss: 3.433822
iter: 7249 | loss: 3.433629
iter: 7250 | loss: 3.433435
iter: 7251 | loss: 3.433242
iter: 7252 | loss: 3.433048
iter: 7253 | loss: 3.432855
iter: 7254 | loss: 3.432662
iter: 7255 | loss: 3.432468
iter: 7256 | loss: 3.432275
iter: 7257 | loss: 3.432082
iter: 7258 | loss: 3.431888
iter: 7259 | loss: 3.431695
iter: 7260 | loss: 3.431501
iter: 7261 | loss: 3.431308
iter: 7262 | loss: 3.431115
iter: 7263 | loss: 3.430921
iter: 7264 | loss: 3.430728
iter: 7265 | loss: 3.430534
iter: 7266 | loss: 3.430341
iter: 7267 | loss: 3.430148
iter: 7268 | loss: 3.429954
iter: 7269 | loss: 3.429761
iter: 7270 | loss: 3.429568
iter: 7271 | loss: 3.429374
iter: 7272 | loss: 3.429181
iter: 7273 | loss: 3.428987
iter: 7274 | loss: 3.428794
iter: 7275 | loss: 3.428601
iter: 7276 | loss: 3.428407
iter: 7277 | loss: 3.428214
iter: 7278 | loss: 3.428020
iter: 7279 | loss: 3.427827
iter: 7280 | loss: 3.427634
iter: 7281 | loss: 3.427440
iter: 7282 | loss: 3.427247
iter: 7283 | loss: 3.427053
iter: 7284 | loss: 3.426860
iter: 7285 | loss: 3.426667
iter: 7286 | loss: 3.426473
iter: 7287 | loss: 3.426280
iter: 7288 | loss: 3.426087
iter: 7289 | loss: 3.425893
iter: 7290 | loss: 3.425700
iter: 7291 | loss: 3.425506
iter: 7292 | loss: 3.425313
iter: 7293 | loss: 3.425120
iter: 7294 | loss: 3.424926
iter: 7295 | loss: 3.424733
iter: 7296 | loss: 3.424539
iter: 7297 | loss: 3.424346
iter: 7298 | loss: 3.424153
iter: 7299 | loss: 3.423959
iter: 7300 | loss: 3.423766
iter: 7301 | loss: 3.423573
iter: 7302 | loss: 3.423379
iter: 7303 | loss: 3.423186
iter: 7304 | loss: 3.422992
iter: 7305 | loss: 3.422799
iter: 7306 | loss: 3.422606
iter: 7307 | loss: 3.422412
iter: 7308 | loss: 3.422219
iter: 7309 | loss: 3.422025
iter: 7310 | loss: 3.421832
iter: 7311 | loss: 3.421639
iter: 7312 | loss: 3.421445
iter: 7313 | loss: 3.421252
iter: 7314 | loss: 3.421058
iter: 7315 | loss: 3.420865
iter: 7316 | loss: 3.420672
iter: 7317 | loss: 3.420478
iter: 7318 | loss: 3.420285
iter: 7319 | loss: 3.420092
iter: 7320 | loss: 3.419898
iter: 7321 | loss: 3.419705
iter: 7322 | loss: 3.419511
iter: 7323 | loss: 3.419318
iter: 7324 | loss: 3.419125
iter: 7325 | loss: 3.418931
iter: 7326 | loss: 3.418738
iter: 7327 | loss: 3.418544
iter: 7328 | loss: 3.418351
iter: 7329 | loss: 3.418158
iter: 7330 | loss: 3.417964
iter: 7331 | loss: 3.417771
iter: 7332 | loss: 3.417578
iter: 7333 | loss: 3.417384
iter: 7334 | loss: 3.417191
iter: 7335 | loss: 3.416997
iter: 7336 | loss: 3.416804
iter: 7337 | loss: 3.416611
iter: 7338 | loss: 3.416417
iter: 7339 | loss: 3.416224
iter: 7340 | loss: 3.416030
iter: 7341 | loss: 3.415837
iter: 7342 | loss: 3.415644
iter: 7343 | loss: 3.415450
iter: 7344 | loss: 3.415257
iter: 7345 | loss: 3.415063
iter: 7346 | loss: 3.414870
iter: 7347 | loss: 3.414677
iter: 7348 | loss: 3.414483
iter: 7349 | loss: 3.414290
iter: 7350 | loss: 3.414097
iter: 7351 | loss: 3.413903
iter: 7352 | loss: 3.413710
iter: 7353 | loss: 3.413516
iter: 7354 | loss: 3.413323
iter: 7355 | loss: 3.413130
iter: 7356 | loss: 3.412936
iter: 7357 | loss: 3.412743
iter: 7358 | loss: 3.412549
iter: 7359 | loss: 3.412356
iter: 7360 | loss: 3.412163
iter: 7361 | loss: 3.411969
iter: 7362 | loss: 3.411776
iter: 7363 | loss: 3.411583
iter: 7364 | loss: 3.411389
iter: 7365 | loss: 3.411196
iter: 7366 | loss: 3.411002
iter: 7367 | loss: 3.410809
iter: 7368 | loss: 3.410616
iter: 7369 | loss: 3.410422
iter: 7370 | loss: 3.410229
iter: 7371 | loss: 3.410035
iter: 7372 | loss: 3.409842
iter: 7373 | loss: 3.409649
iter: 7374 | loss: 3.409455
iter: 7375 | loss: 3.409262
iter: 7376 | loss: 3.409068
iter: 7377 | loss: 3.408875
iter: 7378 | loss: 3.408682
iter: 7379 | loss: 3.408488
iter: 7380 | loss: 3.408295
iter: 7381 | loss: 3.408102
iter: 7382 | loss: 3.407908
iter: 7383 | loss: 3.407715
iter: 7384 | loss: 3.407521
iter: 7385 | loss: 3.407328
iter: 7386 | loss: 3.407135
iter: 7387 | loss: 3.406941
iter: 7388 | loss: 3.406748
iter: 7389 | loss: 3.406554
iter: 7390 | loss: 3.406361
iter: 7391 | loss: 3.406168
iter: 7392 | loss: 3.405974
iter: 7393 | loss: 3.405781
iter: 7394 | loss: 3.405588
iter: 7395 | loss: 3.405394
iter: 7396 | loss: 3.405201
iter: 7397 | loss: 3.405007
iter: 7398 | loss: 3.404814
iter: 7399 | loss: 3.404621
iter: 7400 | loss: 3.404427
iter: 7401 | loss: 3.404234
iter: 7402 | loss: 3.404040
iter: 7403 | loss: 3.403847
iter: 7404 | loss: 3.403654
iter: 7405 | loss: 3.403460
iter: 7406 | loss: 3.403267
iter: 7407 | loss: 3.403073
iter: 7408 | loss: 3.402880
iter: 7409 | loss: 3.402687
iter: 7410 | loss: 3.402493
iter: 7411 | loss: 3.402300
iter: 7412 | loss: 3.402107
iter: 7413 | loss: 3.401913
iter: 7414 | loss: 3.401720
iter: 7415 | loss: 3.401526
iter: 7416 | loss: 3.401333
iter: 7417 | loss: 3.401140
iter: 7418 | loss: 3.400946
iter: 7419 | loss: 3.400753
iter: 7420 | loss: 3.400559
iter: 7421 | loss: 3.400366
iter: 7422 | loss: 3.400173
iter: 7423 | loss: 3.399979
iter: 7424 | loss: 3.399786
iter: 7425 | loss: 3.399593
iter: 7426 | loss: 3.399399
iter: 7427 | loss: 3.399206
iter: 7428 | loss: 3.399012
iter: 7429 | loss: 3.398819
iter: 7430 | loss: 3.398626
iter: 7431 | loss: 3.398432
iter: 7432 | loss: 3.398239
iter: 7433 | loss: 3.398045
iter: 7434 | loss: 3.397852
iter: 7435 | loss: 3.397659
iter: 7436 | loss: 3.397465
iter: 7437 | loss: 3.397272
iter: 7438 | loss: 3.397078
iter: 7439 | loss: 3.396885
iter: 7440 | loss: 3.396692
iter: 7441 | loss: 3.396498
iter: 7442 | loss: 3.396305
iter: 7443 | loss: 3.396112
iter: 7444 | loss: 3.395918
iter: 7445 | loss: 3.395725
iter: 7446 | loss: 3.395531
iter: 7447 | loss: 3.395338
iter: 7448 | loss: 3.395145
iter: 7449 | loss: 3.394951
iter: 7450 | loss: 3.394758
iter: 7451 | loss: 3.394564
iter: 7452 | loss: 3.394371
iter: 7453 | loss: 3.394178
iter: 7454 | loss: 3.393984
iter: 7455 | loss: 3.393791
iter: 7456 | loss: 3.393598
iter: 7457 | loss: 3.393404
iter: 7458 | loss: 3.393211
iter: 7459 | loss: 3.393017
iter: 7460 | loss: 3.392824
iter: 7461 | loss: 3.392631
iter: 7462 | loss: 3.392437
iter: 7463 | loss: 3.392244
iter: 7464 | loss: 3.392050
iter: 7465 | loss: 3.391857
iter: 7466 | loss: 3.391664
iter: 7467 | loss: 3.391470
iter: 7468 | loss: 3.391277
iter: 7469 | loss: 3.391084
iter: 7470 | loss: 3.390890
iter: 7471 | loss: 3.390697
iter: 7472 | loss: 3.390503
iter: 7473 | loss: 3.390310
iter: 7474 | loss: 3.390117
iter: 7475 | loss: 3.389923
iter: 7476 | loss: 3.389730
iter: 7477 | loss: 3.389536
iter: 7478 | loss: 3.389343
iter: 7479 | loss: 3.389150
iter: 7480 | loss: 3.388956
iter: 7481 | loss: 3.388763
iter: 7482 | loss: 3.388569
iter: 7483 | loss: 3.388376
iter: 7484 | loss: 3.388183
iter: 7485 | loss: 3.387989
iter: 7486 | loss: 3.387796
iter: 7487 | loss: 3.387603
iter: 7488 | loss: 3.387409
iter: 7489 | loss: 3.387216
iter: 7490 | loss: 3.387022
iter: 7491 | loss: 3.386829
iter: 7492 | loss: 3.386636
iter: 7493 | loss: 3.386442
iter: 7494 | loss: 3.386249
iter: 7495 | loss: 3.386055
iter: 7496 | loss: 3.385862
iter: 7497 | loss: 3.385669
iter: 7498 | loss: 3.385475
iter: 7499 | loss: 3.385282
iter: 7500 | loss: 3.385089
iter: 7501 | loss: 3.384895
iter: 7502 | loss: 3.384702
iter: 7503 | loss: 3.384508
iter: 7504 | loss: 3.384315
iter: 7505 | loss: 3.384122
iter: 7506 | loss: 3.383928
iter: 7507 | loss: 3.383735
iter: 7508 | loss: 3.383541
iter: 7509 | loss: 3.383348
iter: 7510 | loss: 3.383155
iter: 7511 | loss: 3.382961
iter: 7512 | loss: 3.382768
iter: 7513 | loss: 3.382574
iter: 7514 | loss: 3.382381
iter: 7515 | loss: 3.382188
iter: 7516 | loss: 3.381994
iter: 7517 | loss: 3.381801
iter: 7518 | loss: 3.381608
iter: 7519 | loss: 3.381414
iter: 7520 | loss: 3.381221
iter: 7521 | loss: 3.381027
iter: 7522 | loss: 3.380834
iter: 7523 | loss: 3.380641
iter: 7524 | loss: 3.380447
iter: 7525 | loss: 3.380254
iter: 7526 | loss: 3.380060
iter: 7527 | loss: 3.379867
iter: 7528 | loss: 3.379674
iter: 7529 | loss: 3.379480
iter: 7530 | loss: 3.379287
iter: 7531 | loss: 3.379094
iter: 7532 | loss: 3.378900
iter: 7533 | loss: 3.378707
iter: 7534 | loss: 3.378513
iter: 7535 | loss: 3.378320
iter: 7536 | loss: 3.378127
iter: 7537 | loss: 3.377933
iter: 7538 | loss: 3.377740
iter: 7539 | loss: 3.377546
iter: 7540 | loss: 3.377353
iter: 7541 | loss: 3.377160
iter: 7542 | loss: 3.376966
iter: 7543 | loss: 3.376773
iter: 7544 | loss: 3.376579
iter: 7545 | loss: 3.376386
iter: 7546 | loss: 3.376193
iter: 7547 | loss: 3.375999
iter: 7548 | loss: 3.375806
iter: 7549 | loss: 3.375613
iter: 7550 | loss: 3.375419
iter: 7551 | loss: 3.375226
iter: 7552 | loss: 3.375032
iter: 7553 | loss: 3.374839
iter: 7554 | loss: 3.374646
iter: 7555 | loss: 3.374452
iter: 7556 | loss: 3.374259
iter: 7557 | loss: 3.374065
iter: 7558 | loss: 3.373872
iter: 7559 | loss: 3.373679
iter: 7560 | loss: 3.373485
iter: 7561 | loss: 3.373292
iter: 7562 | loss: 3.373099
iter: 7563 | loss: 3.372905
iter: 7564 | loss: 3.372712
iter: 7565 | loss: 3.372518
iter: 7566 | loss: 3.372325
iter: 7567 | loss: 3.372132
iter: 7568 | loss: 3.371938
iter: 7569 | loss: 3.371745
iter: 7570 | loss: 3.371551
iter: 7571 | loss: 3.371358
iter: 7572 | loss: 3.371165
iter: 7573 | loss: 3.370971
iter: 7574 | loss: 3.370778
iter: 7575 | loss: 3.370584
iter: 7576 | loss: 3.370391
iter: 7577 | loss: 3.370198
iter: 7578 | loss: 3.370004
iter: 7579 | loss: 3.369811
iter: 7580 | loss: 3.369618
iter: 7581 | loss: 3.369424
iter: 7582 | loss: 3.369231
iter: 7583 | loss: 3.369037
iter: 7584 | loss: 3.368844
iter: 7585 | loss: 3.368651
iter: 7586 | loss: 3.368457
iter: 7587 | loss: 3.368264
iter: 7588 | loss: 3.368070
iter: 7589 | loss: 3.367877
iter: 7590 | loss: 3.367684
iter: 7591 | loss: 3.367490
iter: 7592 | loss: 3.367297
iter: 7593 | loss: 3.367104
iter: 7594 | loss: 3.366910
iter: 7595 | loss: 3.366717
iter: 7596 | loss: 3.366523
iter: 7597 | loss: 3.366330
iter: 7598 | loss: 3.366137
iter: 7599 | loss: 3.365943
iter: 7600 | loss: 3.365750
iter: 7601 | loss: 3.365556
iter: 7602 | loss: 3.365363
iter: 7603 | loss: 3.365170
iter: 7604 | loss: 3.364976
iter: 7605 | loss: 3.364783
iter: 7606 | loss: 3.364589
iter: 7607 | loss: 3.364396
iter: 7608 | loss: 3.364203
iter: 7609 | loss: 3.364009
iter: 7610 | loss: 3.363816
iter: 7611 | loss: 3.363623
iter: 7612 | loss: 3.363429
iter: 7613 | loss: 3.363236
iter: 7614 | loss: 3.363042
iter: 7615 | loss: 3.362849
iter: 7616 | loss: 3.362656
iter: 7617 | loss: 3.362462
iter: 7618 | loss: 3.362269
iter: 7619 | loss: 3.362075
iter: 7620 | loss: 3.361882
iter: 7621 | loss: 3.361689
iter: 7622 | loss: 3.361495
iter: 7623 | loss: 3.361302
iter: 7624 | loss: 3.361109
iter: 7625 | loss: 3.360915
iter: 7626 | loss: 3.360722
iter: 7627 | loss: 3.360528
iter: 7628 | loss: 3.360335
iter: 7629 | loss: 3.360142
iter: 7630 | loss: 3.359948
iter: 7631 | loss: 3.359755
iter: 7632 | loss: 3.359561
iter: 7633 | loss: 3.359368
iter: 7634 | loss: 3.359175
iter: 7635 | loss: 3.358981
iter: 7636 | loss: 3.358788
iter: 7637 | loss: 3.358594
iter: 7638 | loss: 3.358401
iter: 7639 | loss: 3.358208
iter: 7640 | loss: 3.358014
iter: 7641 | loss: 3.357821
iter: 7642 | loss: 3.357628
iter: 7643 | loss: 3.357434
iter: 7644 | loss: 3.357241
iter: 7645 | loss: 3.357047
iter: 7646 | loss: 3.356854
iter: 7647 | loss: 3.356661
iter: 7648 | loss: 3.356467
iter: 7649 | loss: 3.356274
iter: 7650 | loss: 3.356080
iter: 7651 | loss: 3.355887
iter: 7652 | loss: 3.355694
iter: 7653 | loss: 3.355500
iter: 7654 | loss: 3.355307
iter: 7655 | loss: 3.355114
iter: 7656 | loss: 3.354920
iter: 7657 | loss: 3.354727
iter: 7658 | loss: 3.354533
iter: 7659 | loss: 3.354340
iter: 7660 | loss: 3.354147
iter: 7661 | loss: 3.353953
iter: 7662 | loss: 3.353760
iter: 7663 | loss: 3.353566
iter: 7664 | loss: 3.353373
iter: 7665 | loss: 3.353180
iter: 7666 | loss: 3.352986
iter: 7667 | loss: 3.352793
iter: 7668 | loss: 3.352599
iter: 7669 | loss: 3.352406
iter: 7670 | loss: 3.352213
iter: 7671 | loss: 3.352019
iter: 7672 | loss: 3.351826
iter: 7673 | loss: 3.351633
iter: 7674 | loss: 3.351439
iter: 7675 | loss: 3.351246
iter: 7676 | loss: 3.351052
iter: 7677 | loss: 3.350859
iter: 7678 | loss: 3.350666
iter: 7679 | loss: 3.350472
iter: 7680 | loss: 3.350279
iter: 7681 | loss: 3.350085
iter: 7682 | loss: 3.349892
iter: 7683 | loss: 3.349699
iter: 7684 | loss: 3.349505
iter: 7685 | loss: 3.349312
iter: 7686 | loss: 3.349119
iter: 7687 | loss: 3.348925
iter: 7688 | loss: 3.348732
iter: 7689 | loss: 3.348538
iter: 7690 | loss: 3.348345
iter: 7691 | loss: 3.348152
iter: 7692 | loss: 3.347958
iter: 7693 | loss: 3.347765
iter: 7694 | loss: 3.347571
iter: 7695 | loss: 3.347378
iter: 7696 | loss: 3.347185
iter: 7697 | loss: 3.346991
iter: 7698 | loss: 3.346798
iter: 7699 | loss: 3.346604
iter: 7700 | loss: 3.346411
iter: 7701 | loss: 3.346218
iter: 7702 | loss: 3.346024
iter: 7703 | loss: 3.345831
iter: 7704 | loss: 3.345638
iter: 7705 | loss: 3.345444
iter: 7706 | loss: 3.345251
iter: 7707 | loss: 3.345057
iter: 7708 | loss: 3.344864
iter: 7709 | loss: 3.344671
iter: 7710 | loss: 3.344477
iter: 7711 | loss: 3.344284
iter: 7712 | loss: 3.344090
iter: 7713 | loss: 3.343897
iter: 7714 | loss: 3.343704
iter: 7715 | loss: 3.343510
iter: 7716 | loss: 3.343317
iter: 7717 | loss: 3.343124
iter: 7718 | loss: 3.342930
iter: 7719 | loss: 3.342737
iter: 7720 | loss: 3.342543
iter: 7721 | loss: 3.342350
iter: 7722 | loss: 3.342157
iter: 7723 | loss: 3.341963
iter: 7724 | loss: 3.341770
iter: 7725 | loss: 3.341576
iter: 7726 | loss: 3.341383
iter: 7727 | loss: 3.341190
iter: 7728 | loss: 3.340996
iter: 7729 | loss: 3.340803
iter: 7730 | loss: 3.340609
iter: 7731 | loss: 3.340416
iter: 7732 | loss: 3.340223
iter: 7733 | loss: 3.340029
iter: 7734 | loss: 3.339836
iter: 7735 | loss: 3.339643
iter: 7736 | loss: 3.339449
iter: 7737 | loss: 3.339256
iter: 7738 | loss: 3.339062
iter: 7739 | loss: 3.338869
iter: 7740 | loss: 3.338676
iter: 7741 | loss: 3.338482
iter: 7742 | loss: 3.338289
iter: 7743 | loss: 3.338095
iter: 7744 | loss: 3.337902
iter: 7745 | loss: 3.337709
iter: 7746 | loss: 3.337515
iter: 7747 | loss: 3.337322
iter: 7748 | loss: 3.337129
iter: 7749 | loss: 3.336935
iter: 7750 | loss: 3.336742
iter: 7751 | loss: 3.336548
iter: 7752 | loss: 3.336355
iter: 7753 | loss: 3.336162
iter: 7754 | loss: 3.335968
iter: 7755 | loss: 3.335775
iter: 7756 | loss: 3.335581
iter: 7757 | loss: 3.335388
iter: 7758 | loss: 3.335195
iter: 7759 | loss: 3.335001
iter: 7760 | loss: 3.334808
iter: 7761 | loss: 3.334614
iter: 7762 | loss: 3.334421
iter: 7763 | loss: 3.334228
iter: 7764 | loss: 3.334034
iter: 7765 | loss: 3.333841
iter: 7766 | loss: 3.333648
iter: 7767 | loss: 3.333454
iter: 7768 | loss: 3.333261
iter: 7769 | loss: 3.333067
iter: 7770 | loss: 3.332874
iter: 7771 | loss: 3.332681
iter: 7772 | loss: 3.332487
iter: 7773 | loss: 3.332294
iter: 7774 | loss: 3.332100
iter: 7775 | loss: 3.331907
iter: 7776 | loss: 3.331714
iter: 7777 | loss: 3.331520
iter: 7778 | loss: 3.331327
iter: 7779 | loss: 3.331134
iter: 7780 | loss: 3.330940
iter: 7781 | loss: 3.330747
iter: 7782 | loss: 3.330553
iter: 7783 | loss: 3.330360
iter: 7784 | loss: 3.330167
iter: 7785 | loss: 3.329973
iter: 7786 | loss: 3.329780
iter: 7787 | loss: 3.329586
iter: 7788 | loss: 3.329393
iter: 7789 | loss: 3.329200
iter: 7790 | loss: 3.329006
iter: 7791 | loss: 3.328813
iter: 7792 | loss: 3.328620
iter: 7793 | loss: 3.328426
iter: 7794 | loss: 3.328233
iter: 7795 | loss: 3.328039
iter: 7796 | loss: 3.327846
iter: 7797 | loss: 3.327653
iter: 7798 | loss: 3.327459
iter: 7799 | loss: 3.327266
iter: 7800 | loss: 3.327072
iter: 7801 | loss: 3.326879
iter: 7802 | loss: 3.326686
iter: 7803 | loss: 3.326492
iter: 7804 | loss: 3.326299
iter: 7805 | loss: 3.326105
iter: 7806 | loss: 3.325912
iter: 7807 | loss: 3.325719
iter: 7808 | loss: 3.325525
iter: 7809 | loss: 3.325332
iter: 7810 | loss: 3.325139
iter: 7811 | loss: 3.324945
iter: 7812 | loss: 3.324752
iter: 7813 | loss: 3.324558
iter: 7814 | loss: 3.324365
iter: 7815 | loss: 3.324172
iter: 7816 | loss: 3.323978
iter: 7817 | loss: 3.323785
iter: 7818 | loss: 3.323591
iter: 7819 | loss: 3.323398
iter: 7820 | loss: 3.323205
iter: 7821 | loss: 3.323011
iter: 7822 | loss: 3.322818
iter: 7823 | loss: 3.322625
iter: 7824 | loss: 3.322431
iter: 7825 | loss: 3.322238
iter: 7826 | loss: 3.322044
iter: 7827 | loss: 3.321851
iter: 7828 | loss: 3.321658
iter: 7829 | loss: 3.321464
iter: 7830 | loss: 3.321271
iter: 7831 | loss: 3.321077
iter: 7832 | loss: 3.320884
iter: 7833 | loss: 3.320691
iter: 7834 | loss: 3.320497
iter: 7835 | loss: 3.320304
iter: 7836 | loss: 3.320110
iter: 7837 | loss: 3.319917
iter: 7838 | loss: 3.319724
iter: 7839 | loss: 3.319530
iter: 7840 | loss: 3.319337
iter: 7841 | loss: 3.319144
iter: 7842 | loss: 3.318950
iter: 7843 | loss: 3.318757
iter: 7844 | loss: 3.318563
iter: 7845 | loss: 3.318370
iter: 7846 | loss: 3.318177
iter: 7847 | loss: 3.317983
iter: 7848 | loss: 3.317790
iter: 7849 | loss: 3.317596
iter: 7850 | loss: 3.317403
iter: 7851 | loss: 3.317210
iter: 7852 | loss: 3.317016
iter: 7853 | loss: 3.316823
iter: 7854 | loss: 3.316630
iter: 7855 | loss: 3.316436
iter: 7856 | loss: 3.316243
iter: 7857 | loss: 3.316049
iter: 7858 | loss: 3.315856
iter: 7859 | loss: 3.315663
iter: 7860 | loss: 3.315469
iter: 7861 | loss: 3.315276
iter: 7862 | loss: 3.315082
iter: 7863 | loss: 3.314889
iter: 7864 | loss: 3.314696
iter: 7865 | loss: 3.314502
iter: 7866 | loss: 3.314309
iter: 7867 | loss: 3.314115
iter: 7868 | loss: 3.313922
iter: 7869 | loss: 3.313729
iter: 7870 | loss: 3.313535
iter: 7871 | loss: 3.313342
iter: 7872 | loss: 3.313149
iter: 7873 | loss: 3.312955
iter: 7874 | loss: 3.312762
iter: 7875 | loss: 3.312568
iter: 7876 | loss: 3.312375
iter: 7877 | loss: 3.312182
iter: 7878 | loss: 3.311988
iter: 7879 | loss: 3.311795
iter: 7880 | loss: 3.311601
iter: 7881 | loss: 3.311408
iter: 7882 | loss: 3.311215
iter: 7883 | loss: 3.311021
iter: 7884 | loss: 3.310828
iter: 7885 | loss: 3.310635
iter: 7886 | loss: 3.310441
iter: 7887 | loss: 3.310248
iter: 7888 | loss: 3.310054
iter: 7889 | loss: 3.309861
iter: 7890 | loss: 3.309668
iter: 7891 | loss: 3.309474
iter: 7892 | loss: 3.309281
iter: 7893 | loss: 3.309087
iter: 7894 | loss: 3.308894
iter: 7895 | loss: 3.308701
iter: 7896 | loss: 3.308507
iter: 7897 | loss: 3.308314
iter: 7898 | loss: 3.308120
iter: 7899 | loss: 3.307927
iter: 7900 | loss: 3.307734
iter: 7901 | loss: 3.307540
iter: 7902 | loss: 3.307347
iter: 7903 | loss: 3.307154
iter: 7904 | loss: 3.306960
iter: 7905 | loss: 3.306767
iter: 7906 | loss: 3.306573
iter: 7907 | loss: 3.306380
iter: 7908 | loss: 3.306187
iter: 7909 | loss: 3.305993
iter: 7910 | loss: 3.305800
iter: 7911 | loss: 3.305606
iter: 7912 | loss: 3.305413
iter: 7913 | loss: 3.305220
iter: 7914 | loss: 3.305026
iter: 7915 | loss: 3.304833
iter: 7916 | loss: 3.304640
iter: 7917 | loss: 3.304446
iter: 7918 | loss: 3.304253
iter: 7919 | loss: 3.304059
iter: 7920 | loss: 3.303866
iter: 7921 | loss: 3.303673
iter: 7922 | loss: 3.303479
iter: 7923 | loss: 3.303286
iter: 7924 | loss: 3.303092
iter: 7925 | loss: 3.302899
iter: 7926 | loss: 3.302706
iter: 7927 | loss: 3.302512
iter: 7928 | loss: 3.302319
iter: 7929 | loss: 3.302125
iter: 7930 | loss: 3.301932
iter: 7931 | loss: 3.301739
iter: 7932 | loss: 3.301545
iter: 7933 | loss: 3.301352
iter: 7934 | loss: 3.301159
iter: 7935 | loss: 3.300965
iter: 7936 | loss: 3.300772
iter: 7937 | loss: 3.300578
iter: 7938 | loss: 3.300385
iter: 7939 | loss: 3.300192
iter: 7940 | loss: 3.299998
iter: 7941 | loss: 3.299805
iter: 7942 | loss: 3.299611
iter: 7943 | loss: 3.299418
iter: 7944 | loss: 3.299225
iter: 7945 | loss: 3.299031
iter: 7946 | loss: 3.298838
iter: 7947 | loss: 3.298645
iter: 7948 | loss: 3.298451
iter: 7949 | loss: 3.298258
iter: 7950 | loss: 3.298064
iter: 7951 | loss: 3.297871
iter: 7952 | loss: 3.297678
iter: 7953 | loss: 3.297484
iter: 7954 | loss: 3.297291
iter: 7955 | loss: 3.297097
iter: 7956 | loss: 3.296904
iter: 7957 | loss: 3.296711
iter: 7958 | loss: 3.296517
iter: 7959 | loss: 3.296324
iter: 7960 | loss: 3.296130
iter: 7961 | loss: 3.295937
iter: 7962 | loss: 3.295744
iter: 7963 | loss: 3.295550
iter: 7964 | loss: 3.295357
iter: 7965 | loss: 3.295164
iter: 7966 | loss: 3.294970
iter: 7967 | loss: 3.294777
iter: 7968 | loss: 3.294583
iter: 7969 | loss: 3.294390
iter: 7970 | loss: 3.294197
iter: 7971 | loss: 3.294003
iter: 7972 | loss: 3.293810
iter: 7973 | loss: 3.293616
iter: 7974 | loss: 3.293423
iter: 7975 | loss: 3.293230
iter: 7976 | loss: 3.293036
iter: 7977 | loss: 3.292843
iter: 7978 | loss: 3.292650
iter: 7979 | loss: 3.292456
iter: 7980 | loss: 3.292263
iter: 7981 | loss: 3.292069
iter: 7982 | loss: 3.291876
iter: 7983 | loss: 3.291683
iter: 7984 | loss: 3.291489
iter: 7985 | loss: 3.291296
iter: 7986 | loss: 3.291102
iter: 7987 | loss: 3.290909
iter: 7988 | loss: 3.290716
iter: 7989 | loss: 3.290522
iter: 7990 | loss: 3.290329
iter: 7991 | loss: 3.290135
iter: 7992 | loss: 3.289942
iter: 7993 | loss: 3.289749
iter: 7994 | loss: 3.289555
iter: 7995 | loss: 3.289362
iter: 7996 | loss: 3.289169
iter: 7997 | loss: 3.288975
iter: 7998 | loss: 3.288782
iter: 7999 | loss: 3.288588
iter: 8000 | loss: 3.288395
iter: 8001 | loss: 3.288202
iter: 8002 | loss: 3.288008
iter: 8003 | loss: 3.287815
iter: 8004 | loss: 3.287621
iter: 8005 | loss: 3.287428
iter: 8006 | loss: 3.287235
iter: 8007 | loss: 3.287041
iter: 8008 | loss: 3.286848
iter: 8009 | loss: 3.286655
iter: 8010 | loss: 3.286461
iter: 8011 | loss: 3.286268
iter: 8012 | loss: 3.286074
iter: 8013 | loss: 3.285881
iter: 8014 | loss: 3.285688
iter: 8015 | loss: 3.285494
iter: 8016 | loss: 3.285301
iter: 8017 | loss: 3.285107
iter: 8018 | loss: 3.284914
iter: 8019 | loss: 3.284721
iter: 8020 | loss: 3.284527
iter: 8021 | loss: 3.284334
iter: 8022 | loss: 3.284140
iter: 8023 | loss: 3.283947
iter: 8024 | loss: 3.283754
iter: 8025 | loss: 3.283560
iter: 8026 | loss: 3.283367
iter: 8027 | loss: 3.283174
iter: 8028 | loss: 3.282980
iter: 8029 | loss: 3.282787
iter: 8030 | loss: 3.282593
iter: 8031 | loss: 3.282400
iter: 8032 | loss: 3.282207
iter: 8033 | loss: 3.282013
iter: 8034 | loss: 3.281820
iter: 8035 | loss: 3.281626
iter: 8036 | loss: 3.281433
iter: 8037 | loss: 3.281240
iter: 8038 | loss: 3.281046
iter: 8039 | loss: 3.280853
iter: 8040 | loss: 3.280660
iter: 8041 | loss: 3.280466
iter: 8042 | loss: 3.280273
iter: 8043 | loss: 3.280079
iter: 8044 | loss: 3.279886
iter: 8045 | loss: 3.279693
iter: 8046 | loss: 3.279499
iter: 8047 | loss: 3.279306
iter: 8048 | loss: 3.279112
iter: 8049 | loss: 3.278919
iter: 8050 | loss: 3.278726
iter: 8051 | loss: 3.278532
iter: 8052 | loss: 3.278339
iter: 8053 | loss: 3.278145
iter: 8054 | loss: 3.277952
iter: 8055 | loss: 3.277759
iter: 8056 | loss: 3.277565
iter: 8057 | loss: 3.277372
iter: 8058 | loss: 3.277179
iter: 8059 | loss: 3.276985
iter: 8060 | loss: 3.276792
iter: 8061 | loss: 3.276598
iter: 8062 | loss: 3.276405
iter: 8063 | loss: 3.276212
iter: 8064 | loss: 3.276018
iter: 8065 | loss: 3.275825
iter: 8066 | loss: 3.275631
iter: 8067 | loss: 3.275438
iter: 8068 | loss: 3.275245
iter: 8069 | loss: 3.275051
iter: 8070 | loss: 3.274858
iter: 8071 | loss: 3.274665
iter: 8072 | loss: 3.274471
iter: 8073 | loss: 3.274278
iter: 8074 | loss: 3.274084
iter: 8075 | loss: 3.273891
iter: 8076 | loss: 3.273698
iter: 8077 | loss: 3.273504
iter: 8078 | loss: 3.273311
iter: 8079 | loss: 3.273117
iter: 8080 | loss: 3.272924
iter: 8081 | loss: 3.272731
iter: 8082 | loss: 3.272537
iter: 8083 | loss: 3.272344
iter: 8084 | loss: 3.272150
iter: 8085 | loss: 3.271957
iter: 8086 | loss: 3.271764
iter: 8087 | loss: 3.271570
iter: 8088 | loss: 3.271377
iter: 8089 | loss: 3.271184
iter: 8090 | loss: 3.270990
iter: 8091 | loss: 3.270797
iter: 8092 | loss: 3.270603
iter: 8093 | loss: 3.270410
iter: 8094 | loss: 3.270217
iter: 8095 | loss: 3.270023
iter: 8096 | loss: 3.269830
iter: 8097 | loss: 3.269636
iter: 8098 | loss: 3.269443
iter: 8099 | loss: 3.269250
iter: 8100 | loss: 3.269056
iter: 8101 | loss: 3.268863
iter: 8102 | loss: 3.268670
iter: 8103 | loss: 3.268476
iter: 8104 | loss: 3.268283
iter: 8105 | loss: 3.268089
iter: 8106 | loss: 3.267896
iter: 8107 | loss: 3.267703
iter: 8108 | loss: 3.267509
iter: 8109 | loss: 3.267316
iter: 8110 | loss: 3.267122
iter: 8111 | loss: 3.266929
iter: 8112 | loss: 3.266736
iter: 8113 | loss: 3.266542
iter: 8114 | loss: 3.266349
iter: 8115 | loss: 3.266156
iter: 8116 | loss: 3.265962
iter: 8117 | loss: 3.265769
iter: 8118 | loss: 3.265575
iter: 8119 | loss: 3.265382
iter: 8120 | loss: 3.265189
iter: 8121 | loss: 3.264995
iter: 8122 | loss: 3.264802
iter: 8123 | loss: 3.264608
iter: 8124 | loss: 3.264415
iter: 8125 | loss: 3.264222
iter: 8126 | loss: 3.264028
iter: 8127 | loss: 3.263835
iter: 8128 | loss: 3.263641
iter: 8129 | loss: 3.263448
iter: 8130 | loss: 3.263255
iter: 8131 | loss: 3.263061
iter: 8132 | loss: 3.262868
iter: 8133 | loss: 3.262675
iter: 8134 | loss: 3.262481
iter: 8135 | loss: 3.262288
iter: 8136 | loss: 3.262094
iter: 8137 | loss: 3.261901
iter: 8138 | loss: 3.261708
iter: 8139 | loss: 3.261514
iter: 8140 | loss: 3.261321
iter: 8141 | loss: 3.261127
iter: 8142 | loss: 3.260934
iter: 8143 | loss: 3.260741
iter: 8144 | loss: 3.260547
iter: 8145 | loss: 3.260354
iter: 8146 | loss: 3.260161
iter: 8147 | loss: 3.259967
iter: 8148 | loss: 3.259774
iter: 8149 | loss: 3.259580
iter: 8150 | loss: 3.259387
iter: 8151 | loss: 3.259194
iter: 8152 | loss: 3.259000
iter: 8153 | loss: 3.258807
iter: 8154 | loss: 3.258613
iter: 8155 | loss: 3.258420
iter: 8156 | loss: 3.258227
iter: 8157 | loss: 3.258033
iter: 8158 | loss: 3.257840
iter: 8159 | loss: 3.257646
iter: 8160 | loss: 3.257453
iter: 8161 | loss: 3.257260
iter: 8162 | loss: 3.257066
iter: 8163 | loss: 3.256873
iter: 8164 | loss: 3.256680
iter: 8165 | loss: 3.256486
iter: 8166 | loss: 3.256293
iter: 8167 | loss: 3.256099
iter: 8168 | loss: 3.255906
iter: 8169 | loss: 3.255713
iter: 8170 | loss: 3.255519
iter: 8171 | loss: 3.255326
iter: 8172 | loss: 3.255132
iter: 8173 | loss: 3.254939
iter: 8174 | loss: 3.254746
iter: 8175 | loss: 3.254552
iter: 8176 | loss: 3.254359
iter: 8177 | loss: 3.254166
iter: 8178 | loss: 3.253972
iter: 8179 | loss: 3.253779
iter: 8180 | loss: 3.253585
iter: 8181 | loss: 3.253392
iter: 8182 | loss: 3.253199
iter: 8183 | loss: 3.253005
iter: 8184 | loss: 3.252812
iter: 8185 | loss: 3.252618
iter: 8186 | loss: 3.252425
iter: 8187 | loss: 3.252232
iter: 8188 | loss: 3.252038
iter: 8189 | loss: 3.251845
iter: 8190 | loss: 3.251651
iter: 8191 | loss: 3.251458
iter: 8192 | loss: 3.251265
iter: 8193 | loss: 3.251071
iter: 8194 | loss: 3.250878
iter: 8195 | loss: 3.250685
iter: 8196 | loss: 3.250491
iter: 8197 | loss: 3.250298
iter: 8198 | loss: 3.250104
iter: 8199 | loss: 3.249911
iter: 8200 | loss: 3.249718
iter: 8201 | loss: 3.249524
iter: 8202 | loss: 3.249331
iter: 8203 | loss: 3.249137
iter: 8204 | loss: 3.248944
iter: 8205 | loss: 3.248751
iter: 8206 | loss: 3.248557
iter: 8207 | loss: 3.248364
iter: 8208 | loss: 3.248171
iter: 8209 | loss: 3.247977
iter: 8210 | loss: 3.247784
iter: 8211 | loss: 3.247590
iter: 8212 | loss: 3.247397
iter: 8213 | loss: 3.247204
iter: 8214 | loss: 3.247010
iter: 8215 | loss: 3.246817
iter: 8216 | loss: 3.246623
iter: 8217 | loss: 3.246430
iter: 8218 | loss: 3.246237
iter: 8219 | loss: 3.246043
iter: 8220 | loss: 3.245850
iter: 8221 | loss: 3.245656
iter: 8222 | loss: 3.245463
iter: 8223 | loss: 3.245270
iter: 8224 | loss: 3.245076
iter: 8225 | loss: 3.244883
iter: 8226 | loss: 3.244690
iter: 8227 | loss: 3.244496
iter: 8228 | loss: 3.244303
iter: 8229 | loss: 3.244109
iter: 8230 | loss: 3.243916
iter: 8231 | loss: 3.243723
iter: 8232 | loss: 3.243529
iter: 8233 | loss: 3.243336
iter: 8234 | loss: 3.243142
iter: 8235 | loss: 3.242949
iter: 8236 | loss: 3.242756
iter: 8237 | loss: 3.242562
iter: 8238 | loss: 3.242369
iter: 8239 | loss: 3.242176
iter: 8240 | loss: 3.241982
iter: 8241 | loss: 3.241789
iter: 8242 | loss: 3.241595
iter: 8243 | loss: 3.241402
iter: 8244 | loss: 3.241209
iter: 8245 | loss: 3.241015
iter: 8246 | loss: 3.240822
iter: 8247 | loss: 3.240628
iter: 8248 | loss: 3.240435
iter: 8249 | loss: 3.240242
iter: 8250 | loss: 3.240048
iter: 8251 | loss: 3.239855
iter: 8252 | loss: 3.239661
iter: 8253 | loss: 3.239468
iter: 8254 | loss: 3.239275
iter: 8255 | loss: 3.239081
iter: 8256 | loss: 3.238888
iter: 8257 | loss: 3.238695
iter: 8258 | loss: 3.238501
iter: 8259 | loss: 3.238308
iter: 8260 | loss: 3.238114
iter: 8261 | loss: 3.237921
iter: 8262 | loss: 3.237728
iter: 8263 | loss: 3.237534
iter: 8264 | loss: 3.237341
iter: 8265 | loss: 3.237147
iter: 8266 | loss: 3.236954
iter: 8267 | loss: 3.236761
iter: 8268 | loss: 3.236567
iter: 8269 | loss: 3.236374
iter: 8270 | loss: 3.236181
iter: 8271 | loss: 3.235987
iter: 8272 | loss: 3.235794
iter: 8273 | loss: 3.235600
iter: 8274 | loss: 3.235407
iter: 8275 | loss: 3.235214
iter: 8276 | loss: 3.235020
iter: 8277 | loss: 3.234827
iter: 8278 | loss: 3.234633
iter: 8279 | loss: 3.234440
iter: 8280 | loss: 3.234247
iter: 8281 | loss: 3.234053
iter: 8282 | loss: 3.233860
iter: 8283 | loss: 3.233666
iter: 8284 | loss: 3.233473
iter: 8285 | loss: 3.233280
iter: 8286 | loss: 3.233086
iter: 8287 | loss: 3.232893
iter: 8288 | loss: 3.232700
iter: 8289 | loss: 3.232506
iter: 8290 | loss: 3.232313
iter: 8291 | loss: 3.232119
iter: 8292 | loss: 3.231926
iter: 8293 | loss: 3.231733
iter: 8294 | loss: 3.231539
iter: 8295 | loss: 3.231346
iter: 8296 | loss: 3.231152
iter: 8297 | loss: 3.230959
iter: 8298 | loss: 3.230766
iter: 8299 | loss: 3.230572
iter: 8300 | loss: 3.230379
iter: 8301 | loss: 3.230186
iter: 8302 | loss: 3.229992
iter: 8303 | loss: 3.229799
iter: 8304 | loss: 3.229605
iter: 8305 | loss: 3.229412
iter: 8306 | loss: 3.229219
iter: 8307 | loss: 3.229025
iter: 8308 | loss: 3.228832
iter: 8309 | loss: 3.228638
iter: 8310 | loss: 3.228445
iter: 8311 | loss: 3.228252
iter: 8312 | loss: 3.228058
iter: 8313 | loss: 3.227865
iter: 8314 | loss: 3.227671
iter: 8315 | loss: 3.227478
iter: 8316 | loss: 3.227285
iter: 8317 | loss: 3.227091
iter: 8318 | loss: 3.226898
iter: 8319 | loss: 3.226705
iter: 8320 | loss: 3.226511
iter: 8321 | loss: 3.226318
iter: 8322 | loss: 3.226124
iter: 8323 | loss: 3.225931
iter: 8324 | loss: 3.225738
iter: 8325 | loss: 3.225544
iter: 8326 | loss: 3.225351
iter: 8327 | loss: 3.225157
iter: 8328 | loss: 3.224964
iter: 8329 | loss: 3.224771
iter: 8330 | loss: 3.224577
iter: 8331 | loss: 3.224384
iter: 8332 | loss: 3.224191
iter: 8333 | loss: 3.223997
iter: 8334 | loss: 3.223804
iter: 8335 | loss: 3.223610
iter: 8336 | loss: 3.223417
iter: 8337 | loss: 3.223224
iter: 8338 | loss: 3.223030
iter: 8339 | loss: 3.222837
iter: 8340 | loss: 3.222643
iter: 8341 | loss: 3.222450
iter: 8342 | loss: 3.222257
iter: 8343 | loss: 3.222063
iter: 8344 | loss: 3.221870
iter: 8345 | loss: 3.221676
iter: 8346 | loss: 3.221483
iter: 8347 | loss: 3.221290
iter: 8348 | loss: 3.221096
iter: 8349 | loss: 3.220903
iter: 8350 | loss: 3.220710
iter: 8351 | loss: 3.220516
iter: 8352 | loss: 3.220323
iter: 8353 | loss: 3.220129
iter: 8354 | loss: 3.219936
iter: 8355 | loss: 3.219743
iter: 8356 | loss: 3.219549
iter: 8357 | loss: 3.219356
iter: 8358 | loss: 3.219162
iter: 8359 | loss: 3.218969
iter: 8360 | loss: 3.218776
iter: 8361 | loss: 3.218582
iter: 8362 | loss: 3.218389
iter: 8363 | loss: 3.218196
iter: 8364 | loss: 3.218002
iter: 8365 | loss: 3.217809
iter: 8366 | loss: 3.217615
iter: 8367 | loss: 3.217422
iter: 8368 | loss: 3.217229
iter: 8369 | loss: 3.217035
iter: 8370 | loss: 3.216842
iter: 8371 | loss: 3.216648
iter: 8372 | loss: 3.216455
iter: 8373 | loss: 3.216262
iter: 8374 | loss: 3.216068
iter: 8375 | loss: 3.215875
iter: 8376 | loss: 3.215681
iter: 8377 | loss: 3.215488
iter: 8378 | loss: 3.215295
iter: 8379 | loss: 3.215101
iter: 8380 | loss: 3.214908
iter: 8381 | loss: 3.214715
iter: 8382 | loss: 3.214521
iter: 8383 | loss: 3.214328
iter: 8384 | loss: 3.214134
iter: 8385 | loss: 3.213941
iter: 8386 | loss: 3.213748
iter: 8387 | loss: 3.213554
iter: 8388 | loss: 3.213361
iter: 8389 | loss: 3.213167
iter: 8390 | loss: 3.212974
iter: 8391 | loss: 3.212781
iter: 8392 | loss: 3.212587
iter: 8393 | loss: 3.212394
iter: 8394 | loss: 3.212201
iter: 8395 | loss: 3.212007
iter: 8396 | loss: 3.211814
iter: 8397 | loss: 3.211620
iter: 8398 | loss: 3.211427
iter: 8399 | loss: 3.211234
iter: 8400 | loss: 3.211040
iter: 8401 | loss: 3.210847
iter: 8402 | loss: 3.210653
iter: 8403 | loss: 3.210460
iter: 8404 | loss: 3.210267
iter: 8405 | loss: 3.210073
iter: 8406 | loss: 3.209880
iter: 8407 | loss: 3.209686
iter: 8408 | loss: 3.209493
iter: 8409 | loss: 3.209300
iter: 8410 | loss: 3.209106
iter: 8411 | loss: 3.208913
iter: 8412 | loss: 3.208720
iter: 8413 | loss: 3.208526
iter: 8414 | loss: 3.208333
iter: 8415 | loss: 3.208139
iter: 8416 | loss: 3.207946
iter: 8417 | loss: 3.207753
iter: 8418 | loss: 3.207559
iter: 8419 | loss: 3.207366
iter: 8420 | loss: 3.207172
iter: 8421 | loss: 3.206979
iter: 8422 | loss: 3.206786
iter: 8423 | loss: 3.206592
iter: 8424 | loss: 3.206399
iter: 8425 | loss: 3.206206
iter: 8426 | loss: 3.206012
iter: 8427 | loss: 3.205819
iter: 8428 | loss: 3.205625
iter: 8429 | loss: 3.205432
iter: 8430 | loss: 3.205239
iter: 8431 | loss: 3.205045
iter: 8432 | loss: 3.204852
iter: 8433 | loss: 3.204658
iter: 8434 | loss: 3.204465
iter: 8435 | loss: 3.204272
iter: 8436 | loss: 3.204078
iter: 8437 | loss: 3.203885
iter: 8438 | loss: 3.203692
iter: 8439 | loss: 3.203498
iter: 8440 | loss: 3.203305
iter: 8441 | loss: 3.203111
iter: 8442 | loss: 3.202918
iter: 8443 | loss: 3.202725
iter: 8444 | loss: 3.202531
iter: 8445 | loss: 3.202338
iter: 8446 | loss: 3.202144
iter: 8447 | loss: 3.201951
iter: 8448 | loss: 3.201758
iter: 8449 | loss: 3.201564
iter: 8450 | loss: 3.201371
iter: 8451 | loss: 3.201177
iter: 8452 | loss: 3.200984
iter: 8453 | loss: 3.200791
iter: 8454 | loss: 3.200597
iter: 8455 | loss: 3.200404
iter: 8456 | loss: 3.200211
iter: 8457 | loss: 3.200017
iter: 8458 | loss: 3.199824
iter: 8459 | loss: 3.199630
iter: 8460 | loss: 3.199437
iter: 8461 | loss: 3.199244
iter: 8462 | loss: 3.199050
iter: 8463 | loss: 3.198857
iter: 8464 | loss: 3.198663
iter: 8465 | loss: 3.198470
iter: 8466 | loss: 3.198277
iter: 8467 | loss: 3.198083
iter: 8468 | loss: 3.197890
iter: 8469 | loss: 3.197697
iter: 8470 | loss: 3.197503
iter: 8471 | loss: 3.197310
iter: 8472 | loss: 3.197116
iter: 8473 | loss: 3.196923
iter: 8474 | loss: 3.196730
iter: 8475 | loss: 3.196536
iter: 8476 | loss: 3.196343
iter: 8477 | loss: 3.196149
iter: 8478 | loss: 3.195956
iter: 8479 | loss: 3.195763
iter: 8480 | loss: 3.195569
iter: 8481 | loss: 3.195376
iter: 8482 | loss: 3.195182
iter: 8483 | loss: 3.194989
iter: 8484 | loss: 3.194796
iter: 8485 | loss: 3.194602
iter: 8486 | loss: 3.194409
iter: 8487 | loss: 3.194216
iter: 8488 | loss: 3.194022
iter: 8489 | loss: 3.193829
iter: 8490 | loss: 3.193635
iter: 8491 | loss: 3.193442
iter: 8492 | loss: 3.193249
iter: 8493 | loss: 3.193055
iter: 8494 | loss: 3.192862
iter: 8495 | loss: 3.192668
iter: 8496 | loss: 3.192475
iter: 8497 | loss: 3.192282
iter: 8498 | loss: 3.192088
iter: 8499 | loss: 3.191895
iter: 8500 | loss: 3.191702
iter: 8501 | loss: 3.191508
iter: 8502 | loss: 3.191315
iter: 8503 | loss: 3.191121
iter: 8504 | loss: 3.190928
iter: 8505 | loss: 3.190735
iter: 8506 | loss: 3.190541
iter: 8507 | loss: 3.190348
iter: 8508 | loss: 3.190154
iter: 8509 | loss: 3.189961
iter: 8510 | loss: 3.189768
iter: 8511 | loss: 3.189574
iter: 8512 | loss: 3.189381
iter: 8513 | loss: 3.189187
iter: 8514 | loss: 3.188994
iter: 8515 | loss: 3.188801
iter: 8516 | loss: 3.188607
iter: 8517 | loss: 3.188414
iter: 8518 | loss: 3.188221
iter: 8519 | loss: 3.188027
iter: 8520 | loss: 3.187834
iter: 8521 | loss: 3.187640
iter: 8522 | loss: 3.187447
iter: 8523 | loss: 3.187254
iter: 8524 | loss: 3.187060
iter: 8525 | loss: 3.186867
iter: 8526 | loss: 3.186673
iter: 8527 | loss: 3.186480
iter: 8528 | loss: 3.186287
iter: 8529 | loss: 3.186093
iter: 8530 | loss: 3.185900
iter: 8531 | loss: 3.185707
iter: 8532 | loss: 3.185513
iter: 8533 | loss: 3.185320
iter: 8534 | loss: 3.185126
iter: 8535 | loss: 3.184933
iter: 8536 | loss: 3.184740
iter: 8537 | loss: 3.184546
iter: 8538 | loss: 3.184353
iter: 8539 | loss: 3.184159
iter: 8540 | loss: 3.183966
iter: 8541 | loss: 3.183773
iter: 8542 | loss: 3.183579
iter: 8543 | loss: 3.183386
iter: 8544 | loss: 3.183192
iter: 8545 | loss: 3.182999
iter: 8546 | loss: 3.182806
iter: 8547 | loss: 3.182612
iter: 8548 | loss: 3.182419
iter: 8549 | loss: 3.182226
iter: 8550 | loss: 3.182032
iter: 8551 | loss: 3.181839
iter: 8552 | loss: 3.181645
iter: 8553 | loss: 3.181452
iter: 8554 | loss: 3.181259
iter: 8555 | loss: 3.181065
iter: 8556 | loss: 3.180872
iter: 8557 | loss: 3.180678
iter: 8558 | loss: 3.180485
iter: 8559 | loss: 3.180292
iter: 8560 | loss: 3.180098
iter: 8561 | loss: 3.179905
iter: 8562 | loss: 3.179712
iter: 8563 | loss: 3.179518
iter: 8564 | loss: 3.179325
iter: 8565 | loss: 3.179131
iter: 8566 | loss: 3.178938
iter: 8567 | loss: 3.178745
iter: 8568 | loss: 3.178551
iter: 8569 | loss: 3.178358
iter: 8570 | loss: 3.178164
iter: 8571 | loss: 3.177971
iter: 8572 | loss: 3.177778
iter: 8573 | loss: 3.177584
iter: 8574 | loss: 3.177391
iter: 8575 | loss: 3.177197
iter: 8576 | loss: 3.177004
iter: 8577 | loss: 3.176811
iter: 8578 | loss: 3.176617
iter: 8579 | loss: 3.176424
iter: 8580 | loss: 3.176231
iter: 8581 | loss: 3.176037
iter: 8582 | loss: 3.175844
iter: 8583 | loss: 3.175650
iter: 8584 | loss: 3.175457
iter: 8585 | loss: 3.175264
iter: 8586 | loss: 3.175070
iter: 8587 | loss: 3.174877
iter: 8588 | loss: 3.174683
iter: 8589 | loss: 3.174490
iter: 8590 | loss: 3.174297
iter: 8591 | loss: 3.174103
iter: 8592 | loss: 3.173910
iter: 8593 | loss: 3.173717
iter: 8594 | loss: 3.173523
iter: 8595 | loss: 3.173330
iter: 8596 | loss: 3.173136
iter: 8597 | loss: 3.172943
iter: 8598 | loss: 3.172750
iter: 8599 | loss: 3.172556
iter: 8600 | loss: 3.172363
iter: 8601 | loss: 3.172169
iter: 8602 | loss: 3.171976
iter: 8603 | loss: 3.171783
iter: 8604 | loss: 3.171589
iter: 8605 | loss: 3.171396
iter: 8606 | loss: 3.171202
iter: 8607 | loss: 3.171009
iter: 8608 | loss: 3.170816
iter: 8609 | loss: 3.170622
iter: 8610 | loss: 3.170429
iter: 8611 | loss: 3.170236
iter: 8612 | loss: 3.170042
iter: 8613 | loss: 3.169849
iter: 8614 | loss: 3.169655
iter: 8615 | loss: 3.169462
iter: 8616 | loss: 3.169269
iter: 8617 | loss: 3.169075
iter: 8618 | loss: 3.168882
iter: 8619 | loss: 3.168688
iter: 8620 | loss: 3.168495
iter: 8621 | loss: 3.168302
iter: 8622 | loss: 3.168108
iter: 8623 | loss: 3.167915
iter: 8624 | loss: 3.167722
iter: 8625 | loss: 3.167528
iter: 8626 | loss: 3.167335
iter: 8627 | loss: 3.167141
iter: 8628 | loss: 3.166948
iter: 8629 | loss: 3.166755
iter: 8630 | loss: 3.166561
iter: 8631 | loss: 3.166368
iter: 8632 | loss: 3.166174
iter: 8633 | loss: 3.165981
iter: 8634 | loss: 3.165788
iter: 8635 | loss: 3.165594
iter: 8636 | loss: 3.165401
iter: 8637 | loss: 3.165207
iter: 8638 | loss: 3.165014
iter: 8639 | loss: 3.164821
iter: 8640 | loss: 3.164627
iter: 8641 | loss: 3.164434
iter: 8642 | loss: 3.164241
iter: 8643 | loss: 3.164047
iter: 8644 | loss: 3.163854
iter: 8645 | loss: 3.163660
iter: 8646 | loss: 3.163467
iter: 8647 | loss: 3.163274
iter: 8648 | loss: 3.163080
iter: 8649 | loss: 3.162887
iter: 8650 | loss: 3.162693
iter: 8651 | loss: 3.162500
iter: 8652 | loss: 3.162307
iter: 8653 | loss: 3.162113
iter: 8654 | loss: 3.161920
iter: 8655 | loss: 3.161727
iter: 8656 | loss: 3.161533
iter: 8657 | loss: 3.161340
iter: 8658 | loss: 3.161146
iter: 8659 | loss: 3.160953
iter: 8660 | loss: 3.160760
iter: 8661 | loss: 3.160566
iter: 8662 | loss: 3.160373
iter: 8663 | loss: 3.160179
iter: 8664 | loss: 3.159986
iter: 8665 | loss: 3.159793
iter: 8666 | loss: 3.159599
iter: 8667 | loss: 3.159406
iter: 8668 | loss: 3.159212
iter: 8669 | loss: 3.159019
iter: 8670 | loss: 3.158826
iter: 8671 | loss: 3.158632
iter: 8672 | loss: 3.158439
iter: 8673 | loss: 3.158246
iter: 8674 | loss: 3.158052
iter: 8675 | loss: 3.157859
iter: 8676 | loss: 3.157665
iter: 8677 | loss: 3.157472
iter: 8678 | loss: 3.157279
iter: 8679 | loss: 3.157085
iter: 8680 | loss: 3.156892
iter: 8681 | loss: 3.156698
iter: 8682 | loss: 3.156505
iter: 8683 | loss: 3.156312
iter: 8684 | loss: 3.156118
iter: 8685 | loss: 3.155925
iter: 8686 | loss: 3.155732
iter: 8687 | loss: 3.155538
iter: 8688 | loss: 3.155345
iter: 8689 | loss: 3.155151
iter: 8690 | loss: 3.154958
iter: 8691 | loss: 3.154765
iter: 8692 | loss: 3.154571
iter: 8693 | loss: 3.154378
iter: 8694 | loss: 3.154184
iter: 8695 | loss: 3.153991
iter: 8696 | loss: 3.153798
iter: 8697 | loss: 3.153604
iter: 8698 | loss: 3.153411
iter: 8699 | loss: 3.153217
iter: 8700 | loss: 3.153024
iter: 8701 | loss: 3.152831
iter: 8702 | loss: 3.152637
iter: 8703 | loss: 3.152444
iter: 8704 | loss: 3.152251
iter: 8705 | loss: 3.152057
iter: 8706 | loss: 3.151864
iter: 8707 | loss: 3.151670
iter: 8708 | loss: 3.151477
iter: 8709 | loss: 3.151284
iter: 8710 | loss: 3.151090
iter: 8711 | loss: 3.150897
iter: 8712 | loss: 3.150703
iter: 8713 | loss: 3.150510
iter: 8714 | loss: 3.150317
iter: 8715 | loss: 3.150123
iter: 8716 | loss: 3.149930
iter: 8717 | loss: 3.149737
iter: 8718 | loss: 3.149543
iter: 8719 | loss: 3.149350
iter: 8720 | loss: 3.149156
iter: 8721 | loss: 3.148963
iter: 8722 | loss: 3.148770
iter: 8723 | loss: 3.148576
iter: 8724 | loss: 3.148383
iter: 8725 | loss: 3.148189
iter: 8726 | loss: 3.147996
iter: 8727 | loss: 3.147803
iter: 8728 | loss: 3.147609
iter: 8729 | loss: 3.147416
iter: 8730 | loss: 3.147222
iter: 8731 | loss: 3.147029
iter: 8732 | loss: 3.146836
iter: 8733 | loss: 3.146642
iter: 8734 | loss: 3.146449
iter: 8735 | loss: 3.146256
iter: 8736 | loss: 3.146062
iter: 8737 | loss: 3.145869
iter: 8738 | loss: 3.145675
iter: 8739 | loss: 3.145482
iter: 8740 | loss: 3.145289
iter: 8741 | loss: 3.145095
iter: 8742 | loss: 3.144902
iter: 8743 | loss: 3.144708
iter: 8744 | loss: 3.144515
iter: 8745 | loss: 3.144322
iter: 8746 | loss: 3.144128
iter: 8747 | loss: 3.143935
iter: 8748 | loss: 3.143742
iter: 8749 | loss: 3.143548
iter: 8750 | loss: 3.143355
iter: 8751 | loss: 3.143161
iter: 8752 | loss: 3.142968
iter: 8753 | loss: 3.142775
iter: 8754 | loss: 3.142581
iter: 8755 | loss: 3.142388
iter: 8756 | loss: 3.142194
iter: 8757 | loss: 3.142001
iter: 8758 | loss: 3.141808
iter: 8759 | loss: 3.141614
iter: 8760 | loss: 3.141421
iter: 8761 | loss: 3.141228
iter: 8762 | loss: 3.141034
iter: 8763 | loss: 3.140841
iter: 8764 | loss: 3.140647
iter: 8765 | loss: 3.140454
iter: 8766 | loss: 3.140261
iter: 8767 | loss: 3.140067
iter: 8768 | loss: 3.139874
iter: 8769 | loss: 3.139680
iter: 8770 | loss: 3.139487
iter: 8771 | loss: 3.139294
iter: 8772 | loss: 3.139100
iter: 8773 | loss: 3.138907
iter: 8774 | loss: 3.138713
iter: 8775 | loss: 3.138520
iter: 8776 | loss: 3.138327
iter: 8777 | loss: 3.138133
iter: 8778 | loss: 3.137940
iter: 8779 | loss: 3.137747
iter: 8780 | loss: 3.137553
iter: 8781 | loss: 3.137360
iter: 8782 | loss: 3.137166
iter: 8783 | loss: 3.136973
iter: 8784 | loss: 3.136780
iter: 8785 | loss: 3.136586
iter: 8786 | loss: 3.136393
iter: 8787 | loss: 3.136199
iter: 8788 | loss: 3.136006
iter: 8789 | loss: 3.135813
iter: 8790 | loss: 3.135619
iter: 8791 | loss: 3.135426
iter: 8792 | loss: 3.135233
iter: 8793 | loss: 3.135039
iter: 8794 | loss: 3.134846
iter: 8795 | loss: 3.134652
iter: 8796 | loss: 3.134459
iter: 8797 | loss: 3.134266
iter: 8798 | loss: 3.134072
iter: 8799 | loss: 3.133879
iter: 8800 | loss: 3.133685
iter: 8801 | loss: 3.133492
iter: 8802 | loss: 3.133299
iter: 8803 | loss: 3.133105
iter: 8804 | loss: 3.132912
iter: 8805 | loss: 3.132718
iter: 8806 | loss: 3.132525
iter: 8807 | loss: 3.132332
iter: 8808 | loss: 3.132138
iter: 8809 | loss: 3.131945
iter: 8810 | loss: 3.131752
iter: 8811 | loss: 3.131558
iter: 8812 | loss: 3.131365
iter: 8813 | loss: 3.131171
iter: 8814 | loss: 3.130978
iter: 8815 | loss: 3.130785
iter: 8816 | loss: 3.130591
iter: 8817 | loss: 3.130398
iter: 8818 | loss: 3.130204
iter: 8819 | loss: 3.130011
iter: 8820 | loss: 3.129818
iter: 8821 | loss: 3.129624
iter: 8822 | loss: 3.129431
iter: 8823 | loss: 3.129238
iter: 8824 | loss: 3.129044
iter: 8825 | loss: 3.128851
iter: 8826 | loss: 3.128657
iter: 8827 | loss: 3.128464
iter: 8828 | loss: 3.128271
iter: 8829 | loss: 3.128077
iter: 8830 | loss: 3.127884
iter: 8831 | loss: 3.127690
iter: 8832 | loss: 3.127497
iter: 8833 | loss: 3.127304
iter: 8834 | loss: 3.127110
iter: 8835 | loss: 3.126917
iter: 8836 | loss: 3.126723
iter: 8837 | loss: 3.126530
iter: 8838 | loss: 3.126337
iter: 8839 | loss: 3.126143
iter: 8840 | loss: 3.125950
iter: 8841 | loss: 3.125757
iter: 8842 | loss: 3.125563
iter: 8843 | loss: 3.125370
iter: 8844 | loss: 3.125176
iter: 8845 | loss: 3.124983
iter: 8846 | loss: 3.124790
iter: 8847 | loss: 3.124596
iter: 8848 | loss: 3.124403
iter: 8849 | loss: 3.124209
iter: 8850 | loss: 3.124016
iter: 8851 | loss: 3.123823
iter: 8852 | loss: 3.123629
iter: 8853 | loss: 3.123436
iter: 8854 | loss: 3.123243
iter: 8855 | loss: 3.123049
iter: 8856 | loss: 3.122856
iter: 8857 | loss: 3.122662
iter: 8858 | loss: 3.122469
iter: 8859 | loss: 3.122276
iter: 8860 | loss: 3.122082
iter: 8861 | loss: 3.121889
iter: 8862 | loss: 3.121695
iter: 8863 | loss: 3.121502
iter: 8864 | loss: 3.121309
iter: 8865 | loss: 3.121115
iter: 8866 | loss: 3.120922
iter: 8867 | loss: 3.120728
iter: 8868 | loss: 3.120535
iter: 8869 | loss: 3.120342
iter: 8870 | loss: 3.120148
iter: 8871 | loss: 3.119955
iter: 8872 | loss: 3.119762
iter: 8873 | loss: 3.119568
iter: 8874 | loss: 3.119375
iter: 8875 | loss: 3.119181
iter: 8876 | loss: 3.118988
iter: 8877 | loss: 3.118795
iter: 8878 | loss: 3.118601
iter: 8879 | loss: 3.118408
iter: 8880 | loss: 3.118214
iter: 8881 | loss: 3.118021
iter: 8882 | loss: 3.117828
iter: 8883 | loss: 3.117634
iter: 8884 | loss: 3.117441
iter: 8885 | loss: 3.117248
iter: 8886 | loss: 3.117054
iter: 8887 | loss: 3.116861
iter: 8888 | loss: 3.116667
iter: 8889 | loss: 3.116474
iter: 8890 | loss: 3.116281
iter: 8891 | loss: 3.116087
iter: 8892 | loss: 3.115894
iter: 8893 | loss: 3.115700
iter: 8894 | loss: 3.115507
iter: 8895 | loss: 3.115314
iter: 8896 | loss: 3.115120
iter: 8897 | loss: 3.114927
iter: 8898 | loss: 3.114733
iter: 8899 | loss: 3.114540
iter: 8900 | loss: 3.114347
iter: 8901 | loss: 3.114153
iter: 8902 | loss: 3.113960
iter: 8903 | loss: 3.113767
iter: 8904 | loss: 3.113573
iter: 8905 | loss: 3.113380
iter: 8906 | loss: 3.113186
iter: 8907 | loss: 3.112993
iter: 8908 | loss: 3.112800
iter: 8909 | loss: 3.112606
iter: 8910 | loss: 3.112413
iter: 8911 | loss: 3.112219
iter: 8912 | loss: 3.112026
iter: 8913 | loss: 3.111833
iter: 8914 | loss: 3.111639
iter: 8915 | loss: 3.111446
iter: 8916 | loss: 3.111253
iter: 8917 | loss: 3.111059
iter: 8918 | loss: 3.110866
iter: 8919 | loss: 3.110672
iter: 8920 | loss: 3.110479
iter: 8921 | loss: 3.110286
iter: 8922 | loss: 3.110092
iter: 8923 | loss: 3.109899
iter: 8924 | loss: 3.109705
iter: 8925 | loss: 3.109512
iter: 8926 | loss: 3.109319
iter: 8927 | loss: 3.109125
iter: 8928 | loss: 3.108932
iter: 8929 | loss: 3.108738
iter: 8930 | loss: 3.108545
iter: 8931 | loss: 3.108352
iter: 8932 | loss: 3.108158
iter: 8933 | loss: 3.107965
iter: 8934 | loss: 3.107772
iter: 8935 | loss: 3.107578
iter: 8936 | loss: 3.107385
iter: 8937 | loss: 3.107191
iter: 8938 | loss: 3.106998
iter: 8939 | loss: 3.106805
iter: 8940 | loss: 3.106611
iter: 8941 | loss: 3.106418
iter: 8942 | loss: 3.106224
iter: 8943 | loss: 3.106031
iter: 8944 | loss: 3.105838
iter: 8945 | loss: 3.105644
iter: 8946 | loss: 3.105451
iter: 8947 | loss: 3.105258
iter: 8948 | loss: 3.105064
iter: 8949 | loss: 3.104871
iter: 8950 | loss: 3.104677
iter: 8951 | loss: 3.104484
iter: 8952 | loss: 3.104291
iter: 8953 | loss: 3.104097
iter: 8954 | loss: 3.103904
iter: 8955 | loss: 3.103710
iter: 8956 | loss: 3.103517
iter: 8957 | loss: 3.103324
iter: 8958 | loss: 3.103130
iter: 8959 | loss: 3.102937
iter: 8960 | loss: 3.102743
iter: 8961 | loss: 3.102550
iter: 8962 | loss: 3.102357
iter: 8963 | loss: 3.102163
iter: 8964 | loss: 3.101970
iter: 8965 | loss: 3.101777
iter: 8966 | loss: 3.101583
iter: 8967 | loss: 3.101390
iter: 8968 | loss: 3.101196
iter: 8969 | loss: 3.101003
iter: 8970 | loss: 3.100810
iter: 8971 | loss: 3.100616
iter: 8972 | loss: 3.100423
iter: 8973 | loss: 3.100229
iter: 8974 | loss: 3.100036
iter: 8975 | loss: 3.099843
iter: 8976 | loss: 3.099649
iter: 8977 | loss: 3.099456
iter: 8978 | loss: 3.099263
iter: 8979 | loss: 3.099069
iter: 8980 | loss: 3.098876
iter: 8981 | loss: 3.098682
iter: 8982 | loss: 3.098489
iter: 8983 | loss: 3.098296
iter: 8984 | loss: 3.098102
iter: 8985 | loss: 3.097909
iter: 8986 | loss: 3.097715
iter: 8987 | loss: 3.097522
iter: 8988 | loss: 3.097329
iter: 8989 | loss: 3.097135
iter: 8990 | loss: 3.096942
iter: 8991 | loss: 3.096748
iter: 8992 | loss: 3.096555
iter: 8993 | loss: 3.096362
iter: 8994 | loss: 3.096168
iter: 8995 | loss: 3.095975
iter: 8996 | loss: 3.095782
iter: 8997 | loss: 3.095588
iter: 8998 | loss: 3.095395
iter: 8999 | loss: 3.095201
iter: 9000 | loss: 3.095008
iter: 9001 | loss: 3.094815
iter: 9002 | loss: 3.094621
iter: 9003 | loss: 3.094428
iter: 9004 | loss: 3.094234
iter: 9005 | loss: 3.094041
iter: 9006 | loss: 3.093848
iter: 9007 | loss: 3.093654
iter: 9008 | loss: 3.093461
iter: 9009 | loss: 3.093268
iter: 9010 | loss: 3.093074
iter: 9011 | loss: 3.092881
iter: 9012 | loss: 3.092687
iter: 9013 | loss: 3.092494
iter: 9014 | loss: 3.092301
iter: 9015 | loss: 3.092107
iter: 9016 | loss: 3.091914
iter: 9017 | loss: 3.091720
iter: 9018 | loss: 3.091527
iter: 9019 | loss: 3.091334
iter: 9020 | loss: 3.091140
iter: 9021 | loss: 3.090947
iter: 9022 | loss: 3.090753
iter: 9023 | loss: 3.090560
iter: 9024 | loss: 3.090367
iter: 9025 | loss: 3.090173
iter: 9026 | loss: 3.089980
iter: 9027 | loss: 3.089787
iter: 9028 | loss: 3.089593
iter: 9029 | loss: 3.089400
iter: 9030 | loss: 3.089206
iter: 9031 | loss: 3.089013
iter: 9032 | loss: 3.088820
iter: 9033 | loss: 3.088626
iter: 9034 | loss: 3.088433
iter: 9035 | loss: 3.088239
iter: 9036 | loss: 3.088046
iter: 9037 | loss: 3.087853
iter: 9038 | loss: 3.087659
iter: 9039 | loss: 3.087466
iter: 9040 | loss: 3.087273
iter: 9041 | loss: 3.087079
iter: 9042 | loss: 3.086886
iter: 9043 | loss: 3.086692
iter: 9044 | loss: 3.086499
iter: 9045 | loss: 3.086306
iter: 9046 | loss: 3.086112
iter: 9047 | loss: 3.085919
iter: 9048 | loss: 3.085725
iter: 9049 | loss: 3.085532
iter: 9050 | loss: 3.085339
iter: 9051 | loss: 3.085145
iter: 9052 | loss: 3.084952
iter: 9053 | loss: 3.084758
iter: 9054 | loss: 3.084565
iter: 9055 | loss: 3.084372
iter: 9056 | loss: 3.084178
iter: 9057 | loss: 3.083985
iter: 9058 | loss: 3.083792
iter: 9059 | loss: 3.083598
iter: 9060 | loss: 3.083405
iter: 9061 | loss: 3.083211
iter: 9062 | loss: 3.083018
iter: 9063 | loss: 3.082825
iter: 9064 | loss: 3.082631
iter: 9065 | loss: 3.082438
iter: 9066 | loss: 3.082244
iter: 9067 | loss: 3.082051
iter: 9068 | loss: 3.081858
iter: 9069 | loss: 3.081664
iter: 9070 | loss: 3.081471
iter: 9071 | loss: 3.081278
iter: 9072 | loss: 3.081084
iter: 9073 | loss: 3.080891
iter: 9074 | loss: 3.080697
iter: 9075 | loss: 3.080504
iter: 9076 | loss: 3.080311
iter: 9077 | loss: 3.080117
iter: 9078 | loss: 3.079924
iter: 9079 | loss: 3.079730
iter: 9080 | loss: 3.079537
iter: 9081 | loss: 3.079344
iter: 9082 | loss: 3.079150
iter: 9083 | loss: 3.078957
iter: 9084 | loss: 3.078764
iter: 9085 | loss: 3.078570
iter: 9086 | loss: 3.078377
iter: 9087 | loss: 3.078183
iter: 9088 | loss: 3.077990
iter: 9089 | loss: 3.077797
iter: 9090 | loss: 3.077603
iter: 9091 | loss: 3.077410
iter: 9092 | loss: 3.077216
iter: 9093 | loss: 3.077023
iter: 9094 | loss: 3.076830
iter: 9095 | loss: 3.076636
iter: 9096 | loss: 3.076443
iter: 9097 | loss: 3.076249
iter: 9098 | loss: 3.076056
iter: 9099 | loss: 3.075863
iter: 9100 | loss: 3.075669
iter: 9101 | loss: 3.075476
iter: 9102 | loss: 3.075283
iter: 9103 | loss: 3.075089
iter: 9104 | loss: 3.074896
iter: 9105 | loss: 3.074702
iter: 9106 | loss: 3.074509
iter: 9107 | loss: 3.074316
iter: 9108 | loss: 3.074122
iter: 9109 | loss: 3.073929
iter: 9110 | loss: 3.073735
iter: 9111 | loss: 3.073542
iter: 9112 | loss: 3.073349
iter: 9113 | loss: 3.073155
iter: 9114 | loss: 3.072962
iter: 9115 | loss: 3.072769
iter: 9116 | loss: 3.072575
iter: 9117 | loss: 3.072382
iter: 9118 | loss: 3.072188
iter: 9119 | loss: 3.071995
iter: 9120 | loss: 3.071802
iter: 9121 | loss: 3.071608
iter: 9122 | loss: 3.071415
iter: 9123 | loss: 3.071221
iter: 9124 | loss: 3.071028
iter: 9125 | loss: 3.070835
iter: 9126 | loss: 3.070641
iter: 9127 | loss: 3.070448
iter: 9128 | loss: 3.070254
iter: 9129 | loss: 3.070061
iter: 9130 | loss: 3.069868
iter: 9131 | loss: 3.069674
iter: 9132 | loss: 3.069481
iter: 9133 | loss: 3.069288
iter: 9134 | loss: 3.069094
iter: 9135 | loss: 3.068901
iter: 9136 | loss: 3.068707
iter: 9137 | loss: 3.068514
iter: 9138 | loss: 3.068321
iter: 9139 | loss: 3.068127
iter: 9140 | loss: 3.067934
iter: 9141 | loss: 3.067740
iter: 9142 | loss: 3.067547
iter: 9143 | loss: 3.067354
iter: 9144 | loss: 3.067160
iter: 9145 | loss: 3.066967
iter: 9146 | loss: 3.066774
iter: 9147 | loss: 3.066580
iter: 9148 | loss: 3.066387
iter: 9149 | loss: 3.066193
iter: 9150 | loss: 3.066000
iter: 9151 | loss: 3.065807
iter: 9152 | loss: 3.065613
iter: 9153 | loss: 3.065420
iter: 9154 | loss: 3.065226
iter: 9155 | loss: 3.065033
iter: 9156 | loss: 3.064840
iter: 9157 | loss: 3.064646
iter: 9158 | loss: 3.064453
iter: 9159 | loss: 3.064259
iter: 9160 | loss: 3.064066
iter: 9161 | loss: 3.063873
iter: 9162 | loss: 3.063679
iter: 9163 | loss: 3.063486
iter: 9164 | loss: 3.063293
iter: 9165 | loss: 3.063099
iter: 9166 | loss: 3.062906
iter: 9167 | loss: 3.062712
iter: 9168 | loss: 3.062519
iter: 9169 | loss: 3.062326
iter: 9170 | loss: 3.062132
iter: 9171 | loss: 3.061939
iter: 9172 | loss: 3.061745
iter: 9173 | loss: 3.061552
iter: 9174 | loss: 3.061359
iter: 9175 | loss: 3.061165
iter: 9176 | loss: 3.060972
iter: 9177 | loss: 3.060779
iter: 9178 | loss: 3.060585
iter: 9179 | loss: 3.060392
iter: 9180 | loss: 3.060198
iter: 9181 | loss: 3.060005
iter: 9182 | loss: 3.059812
iter: 9183 | loss: 3.059618
iter: 9184 | loss: 3.059425
iter: 9185 | loss: 3.059231
iter: 9186 | loss: 3.059038
iter: 9187 | loss: 3.058845
iter: 9188 | loss: 3.058651
iter: 9189 | loss: 3.058458
iter: 9190 | loss: 3.058264
iter: 9191 | loss: 3.058071
iter: 9192 | loss: 3.057878
iter: 9193 | loss: 3.057684
iter: 9194 | loss: 3.057491
iter: 9195 | loss: 3.057298
iter: 9196 | loss: 3.057104
iter: 9197 | loss: 3.056911
iter: 9198 | loss: 3.056717
iter: 9199 | loss: 3.056524
iter: 9200 | loss: 3.056331
iter: 9201 | loss: 3.056137
iter: 9202 | loss: 3.055944
iter: 9203 | loss: 3.055750
iter: 9204 | loss: 3.055557
iter: 9205 | loss: 3.055364
iter: 9206 | loss: 3.055170
iter: 9207 | loss: 3.054977
iter: 9208 | loss: 3.054784
iter: 9209 | loss: 3.054590
iter: 9210 | loss: 3.054397
iter: 9211 | loss: 3.054203
iter: 9212 | loss: 3.054010
iter: 9213 | loss: 3.053817
iter: 9214 | loss: 3.053623
iter: 9215 | loss: 3.053430
iter: 9216 | loss: 3.053236
iter: 9217 | loss: 3.053043
iter: 9218 | loss: 3.052850
iter: 9219 | loss: 3.052656
iter: 9220 | loss: 3.052463
iter: 9221 | loss: 3.052269
iter: 9222 | loss: 3.052076
iter: 9223 | loss: 3.051883
iter: 9224 | loss: 3.051689
iter: 9225 | loss: 3.051496
iter: 9226 | loss: 3.051303
iter: 9227 | loss: 3.051109
iter: 9228 | loss: 3.050916
iter: 9229 | loss: 3.050722
iter: 9230 | loss: 3.050529
iter: 9231 | loss: 3.050336
iter: 9232 | loss: 3.050142
iter: 9233 | loss: 3.049949
iter: 9234 | loss: 3.049755
iter: 9235 | loss: 3.049562
iter: 9236 | loss: 3.049369
iter: 9237 | loss: 3.049175
iter: 9238 | loss: 3.048982
iter: 9239 | loss: 3.048789
iter: 9240 | loss: 3.048595
iter: 9241 | loss: 3.048402
iter: 9242 | loss: 3.048208
iter: 9243 | loss: 3.048015
iter: 9244 | loss: 3.047822
iter: 9245 | loss: 3.047628
iter: 9246 | loss: 3.047435
iter: 9247 | loss: 3.047241
iter: 9248 | loss: 3.047048
iter: 9249 | loss: 3.046855
iter: 9250 | loss: 3.046661
iter: 9251 | loss: 3.046468
iter: 9252 | loss: 3.046274
iter: 9253 | loss: 3.046081
iter: 9254 | loss: 3.045888
iter: 9255 | loss: 3.045694
iter: 9256 | loss: 3.045501
iter: 9257 | loss: 3.045308
iter: 9258 | loss: 3.045114
iter: 9259 | loss: 3.044921
iter: 9260 | loss: 3.044727
iter: 9261 | loss: 3.044534
iter: 9262 | loss: 3.044341
iter: 9263 | loss: 3.044147
iter: 9264 | loss: 3.043954
iter: 9265 | loss: 3.043760
iter: 9266 | loss: 3.043567
iter: 9267 | loss: 3.043374
iter: 9268 | loss: 3.043180
iter: 9269 | loss: 3.042987
iter: 9270 | loss: 3.042794
iter: 9271 | loss: 3.042600
iter: 9272 | loss: 3.042407
iter: 9273 | loss: 3.042213
iter: 9274 | loss: 3.042020
iter: 9275 | loss: 3.041827
iter: 9276 | loss: 3.041633
iter: 9277 | loss: 3.041440
iter: 9278 | loss: 3.041246
iter: 9279 | loss: 3.041053
iter: 9280 | loss: 3.040860
iter: 9281 | loss: 3.040666
iter: 9282 | loss: 3.040473
iter: 9283 | loss: 3.040279
iter: 9284 | loss: 3.040086
iter: 9285 | loss: 3.039893
iter: 9286 | loss: 3.039699
iter: 9287 | loss: 3.039506
iter: 9288 | loss: 3.039313
iter: 9289 | loss: 3.039119
iter: 9290 | loss: 3.038926
iter: 9291 | loss: 3.038732
iter: 9292 | loss: 3.038539
iter: 9293 | loss: 3.038346
iter: 9294 | loss: 3.038152
iter: 9295 | loss: 3.037959
iter: 9296 | loss: 3.037765
iter: 9297 | loss: 3.037572
iter: 9298 | loss: 3.037379
iter: 9299 | loss: 3.037185
iter: 9300 | loss: 3.036992
iter: 9301 | loss: 3.036799
iter: 9302 | loss: 3.036605
iter: 9303 | loss: 3.036412
iter: 9304 | loss: 3.036218
iter: 9305 | loss: 3.036025
iter: 9306 | loss: 3.035832
iter: 9307 | loss: 3.035638
iter: 9308 | loss: 3.035445
iter: 9309 | loss: 3.035251
iter: 9310 | loss: 3.035058
iter: 9311 | loss: 3.034865
iter: 9312 | loss: 3.034671
iter: 9313 | loss: 3.034478
iter: 9314 | loss: 3.034284
iter: 9315 | loss: 3.034091
iter: 9316 | loss: 3.033898
iter: 9317 | loss: 3.033704
iter: 9318 | loss: 3.033511
iter: 9319 | loss: 3.033318
iter: 9320 | loss: 3.033124
iter: 9321 | loss: 3.032931
iter: 9322 | loss: 3.032737
iter: 9323 | loss: 3.032544
iter: 9324 | loss: 3.032351
iter: 9325 | loss: 3.032157
iter: 9326 | loss: 3.031964
iter: 9327 | loss: 3.031770
iter: 9328 | loss: 3.031577
iter: 9329 | loss: 3.031384
iter: 9330 | loss: 3.031190
iter: 9331 | loss: 3.030997
iter: 9332 | loss: 3.030804
iter: 9333 | loss: 3.030610
iter: 9334 | loss: 3.030417
iter: 9335 | loss: 3.030223
iter: 9336 | loss: 3.030030
iter: 9337 | loss: 3.029837
iter: 9338 | loss: 3.029643
iter: 9339 | loss: 3.029450
iter: 9340 | loss: 3.029256
iter: 9341 | loss: 3.029063
iter: 9342 | loss: 3.028870
iter: 9343 | loss: 3.028676
iter: 9344 | loss: 3.028483
iter: 9345 | loss: 3.028289
iter: 9346 | loss: 3.028096
iter: 9347 | loss: 3.027903
iter: 9348 | loss: 3.027709
iter: 9349 | loss: 3.027516
iter: 9350 | loss: 3.027323
iter: 9351 | loss: 3.027129
iter: 9352 | loss: 3.026936
iter: 9353 | loss: 3.026742
iter: 9354 | loss: 3.026549
iter: 9355 | loss: 3.026356
iter: 9356 | loss: 3.026162
iter: 9357 | loss: 3.025969
iter: 9358 | loss: 3.025775
iter: 9359 | loss: 3.025582
iter: 9360 | loss: 3.025389
iter: 9361 | loss: 3.025195
iter: 9362 | loss: 3.025002
iter: 9363 | loss: 3.024809
iter: 9364 | loss: 3.024615
iter: 9365 | loss: 3.024422
iter: 9366 | loss: 3.024228
iter: 9367 | loss: 3.024035
iter: 9368 | loss: 3.023842
iter: 9369 | loss: 3.023648
iter: 9370 | loss: 3.023455
iter: 9371 | loss: 3.023261
iter: 9372 | loss: 3.023068
iter: 9373 | loss: 3.022875
iter: 9374 | loss: 3.022681
iter: 9375 | loss: 3.022488
iter: 9376 | loss: 3.022294
iter: 9377 | loss: 3.022101
iter: 9378 | loss: 3.021908
iter: 9379 | loss: 3.021714
iter: 9380 | loss: 3.021521
iter: 9381 | loss: 3.021328
iter: 9382 | loss: 3.021134
iter: 9383 | loss: 3.020941
iter: 9384 | loss: 3.020747
iter: 9385 | loss: 3.020554
iter: 9386 | loss: 3.020361
iter: 9387 | loss: 3.020167
iter: 9388 | loss: 3.019974
iter: 9389 | loss: 3.019780
iter: 9390 | loss: 3.019587
iter: 9391 | loss: 3.019394
iter: 9392 | loss: 3.019200
iter: 9393 | loss: 3.019007
iter: 9394 | loss: 3.018814
iter: 9395 | loss: 3.018620
iter: 9396 | loss: 3.018427
iter: 9397 | loss: 3.018233
iter: 9398 | loss: 3.018040
iter: 9399 | loss: 3.017847
iter: 9400 | loss: 3.017653
iter: 9401 | loss: 3.017460
iter: 9402 | loss: 3.017266
iter: 9403 | loss: 3.017073
iter: 9404 | loss: 3.016880
iter: 9405 | loss: 3.016686
iter: 9406 | loss: 3.016493
iter: 9407 | loss: 3.016300
iter: 9408 | loss: 3.016106
iter: 9409 | loss: 3.015913
iter: 9410 | loss: 3.015719
iter: 9411 | loss: 3.015526
iter: 9412 | loss: 3.015333
iter: 9413 | loss: 3.015139
iter: 9414 | loss: 3.014946
iter: 9415 | loss: 3.014752
iter: 9416 | loss: 3.014559
iter: 9417 | loss: 3.014366
iter: 9418 | loss: 3.014172
iter: 9419 | loss: 3.013979
iter: 9420 | loss: 3.013785
iter: 9421 | loss: 3.013592
iter: 9422 | loss: 3.013399
iter: 9423 | loss: 3.013205
iter: 9424 | loss: 3.013012
iter: 9425 | loss: 3.012819
iter: 9426 | loss: 3.012625
iter: 9427 | loss: 3.012432
iter: 9428 | loss: 3.012238
iter: 9429 | loss: 3.012045
iter: 9430 | loss: 3.011852
iter: 9431 | loss: 3.011658
iter: 9432 | loss: 3.011465
iter: 9433 | loss: 3.011271
iter: 9434 | loss: 3.011078
iter: 9435 | loss: 3.010885
iter: 9436 | loss: 3.010691
iter: 9437 | loss: 3.010498
iter: 9438 | loss: 3.010305
iter: 9439 | loss: 3.010111
iter: 9440 | loss: 3.009918
iter: 9441 | loss: 3.009724
iter: 9442 | loss: 3.009531
iter: 9443 | loss: 3.009338
iter: 9444 | loss: 3.009144
iter: 9445 | loss: 3.008951
iter: 9446 | loss: 3.008757
iter: 9447 | loss: 3.008564
iter: 9448 | loss: 3.008371
iter: 9449 | loss: 3.008177
iter: 9450 | loss: 3.007984
iter: 9451 | loss: 3.007790
iter: 9452 | loss: 3.007597
iter: 9453 | loss: 3.007404
iter: 9454 | loss: 3.007210
iter: 9455 | loss: 3.007017
iter: 9456 | loss: 3.006824
iter: 9457 | loss: 3.006630
iter: 9458 | loss: 3.006437
iter: 9459 | loss: 3.006243
iter: 9460 | loss: 3.006050
iter: 9461 | loss: 3.005857
iter: 9462 | loss: 3.005663
iter: 9463 | loss: 3.005470
iter: 9464 | loss: 3.005276
iter: 9465 | loss: 3.005083
iter: 9466 | loss: 3.004890
iter: 9467 | loss: 3.004696
iter: 9468 | loss: 3.004503
iter: 9469 | loss: 3.004310
iter: 9470 | loss: 3.004116
iter: 9471 | loss: 3.003923
iter: 9472 | loss: 3.003729
iter: 9473 | loss: 3.003536
iter: 9474 | loss: 3.003343
iter: 9475 | loss: 3.003149
iter: 9476 | loss: 3.002956
iter: 9477 | loss: 3.002762
iter: 9478 | loss: 3.002569
iter: 9479 | loss: 3.002376
iter: 9480 | loss: 3.002182
iter: 9481 | loss: 3.001989
iter: 9482 | loss: 3.001795
iter: 9483 | loss: 3.001602
iter: 9484 | loss: 3.001409
iter: 9485 | loss: 3.001215
iter: 9486 | loss: 3.001022
iter: 9487 | loss: 3.000829
iter: 9488 | loss: 3.000635
iter: 9489 | loss: 3.000442
iter: 9490 | loss: 3.000248
iter: 9491 | loss: 3.000055
iter: 9492 | loss: 2.999862
iter: 9493 | loss: 2.999668
iter: 9494 | loss: 2.999475
iter: 9495 | loss: 2.999281
iter: 9496 | loss: 2.999088
iter: 9497 | loss: 2.998895
iter: 9498 | loss: 2.998701
iter: 9499 | loss: 2.998508
iter: 9500 | loss: 2.998315
iter: 9501 | loss: 2.998121
iter: 9502 | loss: 2.997928
iter: 9503 | loss: 2.997734
iter: 9504 | loss: 2.997541
iter: 9505 | loss: 2.997348
iter: 9506 | loss: 2.997154
iter: 9507 | loss: 2.996961
iter: 9508 | loss: 2.996767
iter: 9509 | loss: 2.996574
iter: 9510 | loss: 2.996381
iter: 9511 | loss: 2.996187
iter: 9512 | loss: 2.995994
iter: 9513 | loss: 2.995800
iter: 9514 | loss: 2.995607
iter: 9515 | loss: 2.995414
iter: 9516 | loss: 2.995220
iter: 9517 | loss: 2.995027
iter: 9518 | loss: 2.994834
iter: 9519 | loss: 2.994640
iter: 9520 | loss: 2.994447
iter: 9521 | loss: 2.994253
iter: 9522 | loss: 2.994060
iter: 9523 | loss: 2.993867
iter: 9524 | loss: 2.993673
iter: 9525 | loss: 2.993480
iter: 9526 | loss: 2.993286
iter: 9527 | loss: 2.993093
iter: 9528 | loss: 2.992900
iter: 9529 | loss: 2.992706
iter: 9530 | loss: 2.992513
iter: 9531 | loss: 2.992320
iter: 9532 | loss: 2.992126
iter: 9533 | loss: 2.991933
iter: 9534 | loss: 2.991739
iter: 9535 | loss: 2.991546
iter: 9536 | loss: 2.991353
iter: 9537 | loss: 2.991159
iter: 9538 | loss: 2.990966
iter: 9539 | loss: 2.990772
iter: 9540 | loss: 2.990579
iter: 9541 | loss: 2.990386
iter: 9542 | loss: 2.990192
iter: 9543 | loss: 2.989999
iter: 9544 | loss: 2.989805
iter: 9545 | loss: 2.989612
iter: 9546 | loss: 2.989419
iter: 9547 | loss: 2.989225
iter: 9548 | loss: 2.989032
iter: 9549 | loss: 2.988839
iter: 9550 | loss: 2.988645
iter: 9551 | loss: 2.988452
iter: 9552 | loss: 2.988258
iter: 9553 | loss: 2.988065
iter: 9554 | loss: 2.987872
iter: 9555 | loss: 2.987678
iter: 9556 | loss: 2.987485
iter: 9557 | loss: 2.987291
iter: 9558 | loss: 2.987098
iter: 9559 | loss: 2.986905
iter: 9560 | loss: 2.986711
iter: 9561 | loss: 2.986518
iter: 9562 | loss: 2.986325
iter: 9563 | loss: 2.986131
iter: 9564 | loss: 2.985938
iter: 9565 | loss: 2.985744
iter: 9566 | loss: 2.985551
iter: 9567 | loss: 2.985358
iter: 9568 | loss: 2.985164
iter: 9569 | loss: 2.984971
iter: 9570 | loss: 2.984777
iter: 9571 | loss: 2.984584
iter: 9572 | loss: 2.984391
iter: 9573 | loss: 2.984197
iter: 9574 | loss: 2.984004
iter: 9575 | loss: 2.983810
iter: 9576 | loss: 2.983617
iter: 9577 | loss: 2.983424
iter: 9578 | loss: 2.983230
iter: 9579 | loss: 2.983037
iter: 9580 | loss: 2.982844
iter: 9581 | loss: 2.982650
iter: 9582 | loss: 2.982457
iter: 9583 | loss: 2.982263
iter: 9584 | loss: 2.982070
iter: 9585 | loss: 2.981877
iter: 9586 | loss: 2.981683
iter: 9587 | loss: 2.981490
iter: 9588 | loss: 2.981296
iter: 9589 | loss: 2.981103
iter: 9590 | loss: 2.980910
iter: 9591 | loss: 2.980716
iter: 9592 | loss: 2.980523
iter: 9593 | loss: 2.980330
iter: 9594 | loss: 2.980136
iter: 9595 | loss: 2.979943
iter: 9596 | loss: 2.979749
iter: 9597 | loss: 2.979556
iter: 9598 | loss: 2.979363
iter: 9599 | loss: 2.979169
iter: 9600 | loss: 2.978976
iter: 9601 | loss: 2.978782
iter: 9602 | loss: 2.978589
iter: 9603 | loss: 2.978396
iter: 9604 | loss: 2.978202
iter: 9605 | loss: 2.978009
iter: 9606 | loss: 2.977815
iter: 9607 | loss: 2.977622
iter: 9608 | loss: 2.977429
iter: 9609 | loss: 2.977235
iter: 9610 | loss: 2.977042
iter: 9611 | loss: 2.976849
iter: 9612 | loss: 2.976655
iter: 9613 | loss: 2.976462
iter: 9614 | loss: 2.976268
iter: 9615 | loss: 2.976075
iter: 9616 | loss: 2.975882
iter: 9617 | loss: 2.975688
iter: 9618 | loss: 2.975495
iter: 9619 | loss: 2.975301
iter: 9620 | loss: 2.975108
iter: 9621 | loss: 2.974915
iter: 9622 | loss: 2.974721
iter: 9623 | loss: 2.974528
iter: 9624 | loss: 2.974335
iter: 9625 | loss: 2.974141
iter: 9626 | loss: 2.973948
iter: 9627 | loss: 2.973754
iter: 9628 | loss: 2.973561
iter: 9629 | loss: 2.973368
iter: 9630 | loss: 2.973174
iter: 9631 | loss: 2.972981
iter: 9632 | loss: 2.972787
iter: 9633 | loss: 2.972594
iter: 9634 | loss: 2.972401
iter: 9635 | loss: 2.972207
iter: 9636 | loss: 2.972014
iter: 9637 | loss: 2.971820
iter: 9638 | loss: 2.971627
iter: 9639 | loss: 2.971434
iter: 9640 | loss: 2.971240
iter: 9641 | loss: 2.971047
iter: 9642 | loss: 2.970854
iter: 9643 | loss: 2.970660
iter: 9644 | loss: 2.970467
iter: 9645 | loss: 2.970273
iter: 9646 | loss: 2.970080
iter: 9647 | loss: 2.969887
iter: 9648 | loss: 2.969693
iter: 9649 | loss: 2.969500
iter: 9650 | loss: 2.969306
iter: 9651 | loss: 2.969113
iter: 9652 | loss: 2.968920
iter: 9653 | loss: 2.968726
iter: 9654 | loss: 2.968533
iter: 9655 | loss: 2.968340
iter: 9656 | loss: 2.968146
iter: 9657 | loss: 2.967953
iter: 9658 | loss: 2.967759
iter: 9659 | loss: 2.967566
iter: 9660 | loss: 2.967373
iter: 9661 | loss: 2.967179
iter: 9662 | loss: 2.966986
iter: 9663 | loss: 2.966792
iter: 9664 | loss: 2.966599
iter: 9665 | loss: 2.966406
iter: 9666 | loss: 2.966212
iter: 9667 | loss: 2.966019
iter: 9668 | loss: 2.965825
iter: 9669 | loss: 2.965632
iter: 9670 | loss: 2.965439
iter: 9671 | loss: 2.965245
iter: 9672 | loss: 2.965052
iter: 9673 | loss: 2.964859
iter: 9674 | loss: 2.964665
iter: 9675 | loss: 2.964472
iter: 9676 | loss: 2.964278
iter: 9677 | loss: 2.964085
iter: 9678 | loss: 2.963892
iter: 9679 | loss: 2.963698
iter: 9680 | loss: 2.963505
iter: 9681 | loss: 2.963311
iter: 9682 | loss: 2.963118
iter: 9683 | loss: 2.962925
iter: 9684 | loss: 2.962731
iter: 9685 | loss: 2.962538
iter: 9686 | loss: 2.962345
iter: 9687 | loss: 2.962151
iter: 9688 | loss: 2.961958
iter: 9689 | loss: 2.961764
iter: 9690 | loss: 2.961571
iter: 9691 | loss: 2.961378
iter: 9692 | loss: 2.961184
iter: 9693 | loss: 2.960991
iter: 9694 | loss: 2.960797
iter: 9695 | loss: 2.960604
iter: 9696 | loss: 2.960411
iter: 9697 | loss: 2.960217
iter: 9698 | loss: 2.960024
iter: 9699 | loss: 2.959830
iter: 9700 | loss: 2.959637
iter: 9701 | loss: 2.959444
iter: 9702 | loss: 2.959250
iter: 9703 | loss: 2.959057
iter: 9704 | loss: 2.958864
iter: 9705 | loss: 2.958670
iter: 9706 | loss: 2.958477
iter: 9707 | loss: 2.958283
iter: 9708 | loss: 2.958090
iter: 9709 | loss: 2.957897
iter: 9710 | loss: 2.957703
iter: 9711 | loss: 2.957510
iter: 9712 | loss: 2.957316
iter: 9713 | loss: 2.957123
iter: 9714 | loss: 2.956930
iter: 9715 | loss: 2.956736
iter: 9716 | loss: 2.956543
iter: 9717 | loss: 2.956350
iter: 9718 | loss: 2.956156
iter: 9719 | loss: 2.955963
iter: 9720 | loss: 2.955769
iter: 9721 | loss: 2.955576
iter: 9722 | loss: 2.955383
iter: 9723 | loss: 2.955189
iter: 9724 | loss: 2.954996
iter: 9725 | loss: 2.954802
iter: 9726 | loss: 2.954609
iter: 9727 | loss: 2.954416
iter: 9728 | loss: 2.954222
iter: 9729 | loss: 2.954029
iter: 9730 | loss: 2.953836
iter: 9731 | loss: 2.953642
iter: 9732 | loss: 2.953449
iter: 9733 | loss: 2.953255
iter: 9734 | loss: 2.953062
iter: 9735 | loss: 2.952869
iter: 9736 | loss: 2.952675
iter: 9737 | loss: 2.952482
iter: 9738 | loss: 2.952288
iter: 9739 | loss: 2.952095
iter: 9740 | loss: 2.951902
iter: 9741 | loss: 2.951708
iter: 9742 | loss: 2.951515
iter: 9743 | loss: 2.951321
iter: 9744 | loss: 2.951128
iter: 9745 | loss: 2.950935
iter: 9746 | loss: 2.950741
iter: 9747 | loss: 2.950548
iter: 9748 | loss: 2.950355
iter: 9749 | loss: 2.950161
iter: 9750 | loss: 2.949968
iter: 9751 | loss: 2.949774
iter: 9752 | loss: 2.949581
iter: 9753 | loss: 2.949388
iter: 9754 | loss: 2.949194
iter: 9755 | loss: 2.949001
iter: 9756 | loss: 2.948807
iter: 9757 | loss: 2.948614
iter: 9758 | loss: 2.948421
iter: 9759 | loss: 2.948227
iter: 9760 | loss: 2.948034
iter: 9761 | loss: 2.947841
iter: 9762 | loss: 2.947647
iter: 9763 | loss: 2.947454
iter: 9764 | loss: 2.947260
iter: 9765 | loss: 2.947067
iter: 9766 | loss: 2.946874
iter: 9767 | loss: 2.946680
iter: 9768 | loss: 2.946487
iter: 9769 | loss: 2.946293
iter: 9770 | loss: 2.946100
iter: 9771 | loss: 2.945907
iter: 9772 | loss: 2.945713
iter: 9773 | loss: 2.945520
iter: 9774 | loss: 2.945326
iter: 9775 | loss: 2.945133
iter: 9776 | loss: 2.944940
iter: 9777 | loss: 2.944746
iter: 9778 | loss: 2.944553
iter: 9779 | loss: 2.944360
iter: 9780 | loss: 2.944166
iter: 9781 | loss: 2.943973
iter: 9782 | loss: 2.943779
iter: 9783 | loss: 2.943586
iter: 9784 | loss: 2.943393
iter: 9785 | loss: 2.943199
iter: 9786 | loss: 2.943006
iter: 9787 | loss: 2.942812
iter: 9788 | loss: 2.942619
iter: 9789 | loss: 2.942426
iter: 9790 | loss: 2.942232
iter: 9791 | loss: 2.942039
iter: 9792 | loss: 2.941846
iter: 9793 | loss: 2.941652
iter: 9794 | loss: 2.941459
iter: 9795 | loss: 2.941265
iter: 9796 | loss: 2.941072
iter: 9797 | loss: 2.940879
iter: 9798 | loss: 2.940685
iter: 9799 | loss: 2.940492
iter: 9800 | loss: 2.940298
iter: 9801 | loss: 2.940105
iter: 9802 | loss: 2.939912
iter: 9803 | loss: 2.939718
iter: 9804 | loss: 2.939525
iter: 9805 | loss: 2.939331
iter: 9806 | loss: 2.939138
iter: 9807 | loss: 2.938945
iter: 9808 | loss: 2.938751
iter: 9809 | loss: 2.938558
iter: 9810 | loss: 2.938365
iter: 9811 | loss: 2.938171
iter: 9812 | loss: 2.937978
iter: 9813 | loss: 2.937784
iter: 9814 | loss: 2.937591
iter: 9815 | loss: 2.937398
iter: 9816 | loss: 2.937204
iter: 9817 | loss: 2.937011
iter: 9818 | loss: 2.936817
iter: 9819 | loss: 2.936624
iter: 9820 | loss: 2.936431
iter: 9821 | loss: 2.936237
iter: 9822 | loss: 2.936044
iter: 9823 | loss: 2.935851
iter: 9824 | loss: 2.935657
iter: 9825 | loss: 2.935464
iter: 9826 | loss: 2.935270
iter: 9827 | loss: 2.935077
iter: 9828 | loss: 2.934884
iter: 9829 | loss: 2.934690
iter: 9830 | loss: 2.934497
iter: 9831 | loss: 2.934303
iter: 9832 | loss: 2.934110
iter: 9833 | loss: 2.933917
iter: 9834 | loss: 2.933723
iter: 9835 | loss: 2.933530
iter: 9836 | loss: 2.933336
iter: 9837 | loss: 2.933143
iter: 9838 | loss: 2.932950
iter: 9839 | loss: 2.932756
iter: 9840 | loss: 2.932563
iter: 9841 | loss: 2.932370
iter: 9842 | loss: 2.932176
iter: 9843 | loss: 2.931983
iter: 9844 | loss: 2.931789
iter: 9845 | loss: 2.931596
iter: 9846 | loss: 2.931403
iter: 9847 | loss: 2.931209
iter: 9848 | loss: 2.931016
iter: 9849 | loss: 2.930822
iter: 9850 | loss: 2.930629
iter: 9851 | loss: 2.930436
iter: 9852 | loss: 2.930242
iter: 9853 | loss: 2.930049
iter: 9854 | loss: 2.929856
iter: 9855 | loss: 2.929662
iter: 9856 | loss: 2.929469
iter: 9857 | loss: 2.929275
iter: 9858 | loss: 2.929082
iter: 9859 | loss: 2.928889
iter: 9860 | loss: 2.928695
iter: 9861 | loss: 2.928502
iter: 9862 | loss: 2.928308
iter: 9863 | loss: 2.928115
iter: 9864 | loss: 2.927922
iter: 9865 | loss: 2.927728
iter: 9866 | loss: 2.927535
iter: 9867 | loss: 2.927341
iter: 9868 | loss: 2.927148
iter: 9869 | loss: 2.926955
iter: 9870 | loss: 2.926761
iter: 9871 | loss: 2.926568
iter: 9872 | loss: 2.926375
iter: 9873 | loss: 2.926181
iter: 9874 | loss: 2.925988
iter: 9875 | loss: 2.925794
iter: 9876 | loss: 2.925601
iter: 9877 | loss: 2.925408
iter: 9878 | loss: 2.925214
iter: 9879 | loss: 2.925021
iter: 9880 | loss: 2.924827
iter: 9881 | loss: 2.924634
iter: 9882 | loss: 2.924441
iter: 9883 | loss: 2.924247
iter: 9884 | loss: 2.924054
iter: 9885 | loss: 2.923861
iter: 9886 | loss: 2.923667
iter: 9887 | loss: 2.923474
iter: 9888 | loss: 2.923280
iter: 9889 | loss: 2.923087
iter: 9890 | loss: 2.922894
iter: 9891 | loss: 2.922700
iter: 9892 | loss: 2.922507
iter: 9893 | loss: 2.922313
iter: 9894 | loss: 2.922120
iter: 9895 | loss: 2.921927
iter: 9896 | loss: 2.921733
iter: 9897 | loss: 2.921540
iter: 9898 | loss: 2.921346
iter: 9899 | loss: 2.921153
iter: 9900 | loss: 2.920960
iter: 9901 | loss: 2.920766
iter: 9902 | loss: 2.920573
iter: 9903 | loss: 2.920380
iter: 9904 | loss: 2.920186
iter: 9905 | loss: 2.919993
iter: 9906 | loss: 2.919799
iter: 9907 | loss: 2.919606
iter: 9908 | loss: 2.919413
iter: 9909 | loss: 2.919219
iter: 9910 | loss: 2.919026
iter: 9911 | loss: 2.918832
iter: 9912 | loss: 2.918639
iter: 9913 | loss: 2.918446
iter: 9914 | loss: 2.918252
iter: 9915 | loss: 2.918059
iter: 9916 | loss: 2.917866
iter: 9917 | loss: 2.917672
iter: 9918 | loss: 2.917479
iter: 9919 | loss: 2.917285
iter: 9920 | loss: 2.917092
iter: 9921 | loss: 2.916899
iter: 9922 | loss: 2.916705
iter: 9923 | loss: 2.916512
iter: 9924 | loss: 2.916318
iter: 9925 | loss: 2.916125
iter: 9926 | loss: 2.915932
iter: 9927 | loss: 2.915738
iter: 9928 | loss: 2.915545
iter: 9929 | loss: 2.915351
iter: 9930 | loss: 2.915158
iter: 9931 | loss: 2.914965
iter: 9932 | loss: 2.914771
iter: 9933 | loss: 2.914578
iter: 9934 | loss: 2.914385
iter: 9935 | loss: 2.914191
iter: 9936 | loss: 2.913998
iter: 9937 | loss: 2.913804
iter: 9938 | loss: 2.913611
iter: 9939 | loss: 2.913418
iter: 9940 | loss: 2.913224
iter: 9941 | loss: 2.913031
iter: 9942 | loss: 2.912837
iter: 9943 | loss: 2.912644
iter: 9944 | loss: 2.912451
iter: 9945 | loss: 2.912257
iter: 9946 | loss: 2.912064
iter: 9947 | loss: 2.911871
iter: 9948 | loss: 2.911677
iter: 9949 | loss: 2.911484
iter: 9950 | loss: 2.911290
iter: 9951 | loss: 2.911097
iter: 9952 | loss: 2.910904
iter: 9953 | loss: 2.910710
iter: 9954 | loss: 2.910517
iter: 9955 | loss: 2.910323
iter: 9956 | loss: 2.910130
iter: 9957 | loss: 2.909937
iter: 9958 | loss: 2.909743
iter: 9959 | loss: 2.909550
iter: 9960 | loss: 2.909356
iter: 9961 | loss: 2.909163
iter: 9962 | loss: 2.908970
iter: 9963 | loss: 2.908776
iter: 9964 | loss: 2.908583
iter: 9965 | loss: 2.908390
iter: 9966 | loss: 2.908196
iter: 9967 | loss: 2.908003
iter: 9968 | loss: 2.907809
iter: 9969 | loss: 2.907616
iter: 9970 | loss: 2.907423
iter: 9971 | loss: 2.907229
iter: 9972 | loss: 2.907036
iter: 9973 | loss: 2.906842
iter: 9974 | loss: 2.906649
iter: 9975 | loss: 2.906456
iter: 9976 | loss: 2.906262
iter: 9977 | loss: 2.906069
iter: 9978 | loss: 2.905876
iter: 9979 | loss: 2.905682
iter: 9980 | loss: 2.905489
iter: 9981 | loss: 2.905295
iter: 9982 | loss: 2.905102
iter: 9983 | loss: 2.904909
iter: 9984 | loss: 2.904715
iter: 9985 | loss: 2.904522
iter: 9986 | loss: 2.904328
iter: 9987 | loss: 2.904135
iter: 9988 | loss: 2.903942
iter: 9989 | loss: 2.903748
iter: 9990 | loss: 2.903555
iter: 9991 | loss: 2.903361
iter: 9992 | loss: 2.903168
iter: 9993 | loss: 2.902975
iter: 9994 | loss: 2.902781
iter: 9995 | loss: 2.902588
iter: 9996 | loss: 2.902395
iter: 9997 | loss: 2.902201
iter: 9998 | loss: 2.902008
iter: 9999 | loss: 2.901814
iter: 10000 | loss: 2.901621
iter: 10001 | loss: 2.901428
iter: 10002 | loss: 2.901234
iter: 10003 | loss: 2.901041
iter: 10004 | loss: 2.900847
iter: 10005 | loss: 2.900654
iter: 10006 | loss: 2.900461
iter: 10007 | loss: 2.900267
iter: 10008 | loss: 2.900074
iter: 10009 | loss: 2.899881
iter: 10010 | loss: 2.899687
iter: 10011 | loss: 2.899494
iter: 10012 | loss: 2.899300
iter: 10013 | loss: 2.899107
iter: 10014 | loss: 2.898914
iter: 10015 | loss: 2.898720
iter: 10016 | loss: 2.898527
iter: 10017 | loss: 2.898333
iter: 10018 | loss: 2.898140
iter: 10019 | loss: 2.897947
iter: 10020 | loss: 2.897753
iter: 10021 | loss: 2.897560
iter: 10022 | loss: 2.897366
iter: 10023 | loss: 2.897173
iter: 10024 | loss: 2.896980
iter: 10025 | loss: 2.896786
iter: 10026 | loss: 2.896593
iter: 10027 | loss: 2.896400
iter: 10028 | loss: 2.896206
iter: 10029 | loss: 2.896013
iter: 10030 | loss: 2.895819
iter: 10031 | loss: 2.895626
iter: 10032 | loss: 2.895433
iter: 10033 | loss: 2.895239
iter: 10034 | loss: 2.895046
iter: 10035 | loss: 2.894852
iter: 10036 | loss: 2.894659
iter: 10037 | loss: 2.894466
iter: 10038 | loss: 2.894272
iter: 10039 | loss: 2.894079
iter: 10040 | loss: 2.893886
iter: 10041 | loss: 2.893692
iter: 10042 | loss: 2.893499
iter: 10043 | loss: 2.893305
iter: 10044 | loss: 2.893112
iter: 10045 | loss: 2.892919
iter: 10046 | loss: 2.892725
iter: 10047 | loss: 2.892532
iter: 10048 | loss: 2.892338
iter: 10049 | loss: 2.892145
iter: 10050 | loss: 2.891952
iter: 10051 | loss: 2.891758
iter: 10052 | loss: 2.891565
iter: 10053 | loss: 2.891372
iter: 10054 | loss: 2.891178
iter: 10055 | loss: 2.890985
iter: 10056 | loss: 2.890791
iter: 10057 | loss: 2.890598
iter: 10058 | loss: 2.890405
iter: 10059 | loss: 2.890211
iter: 10060 | loss: 2.890018
iter: 10061 | loss: 2.889824
iter: 10062 | loss: 2.889631
iter: 10063 | loss: 2.889438
iter: 10064 | loss: 2.889244
iter: 10065 | loss: 2.889051
iter: 10066 | loss: 2.888857
iter: 10067 | loss: 2.888664
iter: 10068 | loss: 2.888471
iter: 10069 | loss: 2.888277
iter: 10070 | loss: 2.888084
iter: 10071 | loss: 2.887891
iter: 10072 | loss: 2.887697
iter: 10073 | loss: 2.887504
iter: 10074 | loss: 2.887310
iter: 10075 | loss: 2.887117
iter: 10076 | loss: 2.886924
iter: 10077 | loss: 2.886730
iter: 10078 | loss: 2.886537
iter: 10079 | loss: 2.886343
iter: 10080 | loss: 2.886150
iter: 10081 | loss: 2.885957
iter: 10082 | loss: 2.885763
iter: 10083 | loss: 2.885570
iter: 10084 | loss: 2.885377
iter: 10085 | loss: 2.885183
iter: 10086 | loss: 2.884990
iter: 10087 | loss: 2.884796
iter: 10088 | loss: 2.884603
iter: 10089 | loss: 2.884410
iter: 10090 | loss: 2.884216
iter: 10091 | loss: 2.884023
iter: 10092 | loss: 2.883829
iter: 10093 | loss: 2.883636
iter: 10094 | loss: 2.883443
iter: 10095 | loss: 2.883249
iter: 10096 | loss: 2.883056
iter: 10097 | loss: 2.882862
iter: 10098 | loss: 2.882669
iter: 10099 | loss: 2.882476
iter: 10100 | loss: 2.882282
iter: 10101 | loss: 2.882089
iter: 10102 | loss: 2.881896
iter: 10103 | loss: 2.881702
iter: 10104 | loss: 2.881509
iter: 10105 | loss: 2.881315
iter: 10106 | loss: 2.881122
iter: 10107 | loss: 2.880929
iter: 10108 | loss: 2.880735
iter: 10109 | loss: 2.880542
iter: 10110 | loss: 2.880348
iter: 10111 | loss: 2.880155
iter: 10112 | loss: 2.879962
iter: 10113 | loss: 2.879768
iter: 10114 | loss: 2.879575
iter: 10115 | loss: 2.879382
iter: 10116 | loss: 2.879188
iter: 10117 | loss: 2.878995
iter: 10118 | loss: 2.878801
iter: 10119 | loss: 2.878608
iter: 10120 | loss: 2.878415
iter: 10121 | loss: 2.878221
iter: 10122 | loss: 2.878028
iter: 10123 | loss: 2.877834
iter: 10124 | loss: 2.877641
iter: 10125 | loss: 2.877448
iter: 10126 | loss: 2.877254
iter: 10127 | loss: 2.877061
iter: 10128 | loss: 2.876867
iter: 10129 | loss: 2.876674
iter: 10130 | loss: 2.876481
iter: 10131 | loss: 2.876287
iter: 10132 | loss: 2.876094
iter: 10133 | loss: 2.875901
iter: 10134 | loss: 2.875707
iter: 10135 | loss: 2.875514
iter: 10136 | loss: 2.875320
iter: 10137 | loss: 2.875127
iter: 10138 | loss: 2.874934
iter: 10139 | loss: 2.874740
iter: 10140 | loss: 2.874547
iter: 10141 | loss: 2.874353
iter: 10142 | loss: 2.874160
iter: 10143 | loss: 2.873967
iter: 10144 | loss: 2.873773
iter: 10145 | loss: 2.873580
iter: 10146 | loss: 2.873387
iter: 10147 | loss: 2.873193
iter: 10148 | loss: 2.873000
iter: 10149 | loss: 2.872806
iter: 10150 | loss: 2.872613
iter: 10151 | loss: 2.872420
iter: 10152 | loss: 2.872226
iter: 10153 | loss: 2.872033
iter: 10154 | loss: 2.871839
iter: 10155 | loss: 2.871646
iter: 10156 | loss: 2.871453
iter: 10157 | loss: 2.871259
iter: 10158 | loss: 2.871066
iter: 10159 | loss: 2.870872
iter: 10160 | loss: 2.870679
iter: 10161 | loss: 2.870486
iter: 10162 | loss: 2.870292
iter: 10163 | loss: 2.870099
iter: 10164 | loss: 2.869906
iter: 10165 | loss: 2.869712
iter: 10166 | loss: 2.869519
iter: 10167 | loss: 2.869325
iter: 10168 | loss: 2.869132
iter: 10169 | loss: 2.868939
iter: 10170 | loss: 2.868745
iter: 10171 | loss: 2.868552
iter: 10172 | loss: 2.868358
iter: 10173 | loss: 2.868165
iter: 10174 | loss: 2.867972
iter: 10175 | loss: 2.867778
iter: 10176 | loss: 2.867585
iter: 10177 | loss: 2.867392
iter: 10178 | loss: 2.867198
iter: 10179 | loss: 2.867005
iter: 10180 | loss: 2.866811
iter: 10181 | loss: 2.866618
iter: 10182 | loss: 2.866425
iter: 10183 | loss: 2.866231
iter: 10184 | loss: 2.866038
iter: 10185 | loss: 2.865844
iter: 10186 | loss: 2.865651
iter: 10187 | loss: 2.865458
iter: 10188 | loss: 2.865264
iter: 10189 | loss: 2.865071
iter: 10190 | loss: 2.864877
iter: 10191 | loss: 2.864684
iter: 10192 | loss: 2.864491
iter: 10193 | loss: 2.864297
iter: 10194 | loss: 2.864104
iter: 10195 | loss: 2.863911
iter: 10196 | loss: 2.863717
iter: 10197 | loss: 2.863524
iter: 10198 | loss: 2.863330
iter: 10199 | loss: 2.863137
iter: 10200 | loss: 2.862944
iter: 10201 | loss: 2.862750
iter: 10202 | loss: 2.862557
iter: 10203 | loss: 2.862363
iter: 10204 | loss: 2.862170
iter: 10205 | loss: 2.861977
iter: 10206 | loss: 2.861783
iter: 10207 | loss: 2.861590
iter: 10208 | loss: 2.861397
iter: 10209 | loss: 2.861203
iter: 10210 | loss: 2.861010
iter: 10211 | loss: 2.860816
iter: 10212 | loss: 2.860623
iter: 10213 | loss: 2.860430
iter: 10214 | loss: 2.860236
iter: 10215 | loss: 2.860043
iter: 10216 | loss: 2.859849
iter: 10217 | loss: 2.859656
iter: 10218 | loss: 2.859463
iter: 10219 | loss: 2.859269
iter: 10220 | loss: 2.859076
iter: 10221 | loss: 2.858882
iter: 10222 | loss: 2.858689
iter: 10223 | loss: 2.858496
iter: 10224 | loss: 2.858302
iter: 10225 | loss: 2.858109
iter: 10226 | loss: 2.857916
iter: 10227 | loss: 2.857722
iter: 10228 | loss: 2.857529
iter: 10229 | loss: 2.857335
iter: 10230 | loss: 2.857142
iter: 10231 | loss: 2.856949
iter: 10232 | loss: 2.856755
iter: 10233 | loss: 2.856562
iter: 10234 | loss: 2.856368
iter: 10235 | loss: 2.856175
iter: 10236 | loss: 2.855982
iter: 10237 | loss: 2.855788
iter: 10238 | loss: 2.855595
iter: 10239 | loss: 2.855402
iter: 10240 | loss: 2.855208
iter: 10241 | loss: 2.855015
iter: 10242 | loss: 2.854821
iter: 10243 | loss: 2.854628
iter: 10244 | loss: 2.854435
iter: 10245 | loss: 2.854241
iter: 10246 | loss: 2.854048
iter: 10247 | loss: 2.853854
iter: 10248 | loss: 2.853661
iter: 10249 | loss: 2.853468
iter: 10250 | loss: 2.853274
iter: 10251 | loss: 2.853081
iter: 10252 | loss: 2.852887
iter: 10253 | loss: 2.852694
iter: 10254 | loss: 2.852501
iter: 10255 | loss: 2.852307
iter: 10256 | loss: 2.852114
iter: 10257 | loss: 2.851921
iter: 10258 | loss: 2.851727
iter: 10259 | loss: 2.851534
iter: 10260 | loss: 2.851340
iter: 10261 | loss: 2.851147
iter: 10262 | loss: 2.850954
iter: 10263 | loss: 2.850760
iter: 10264 | loss: 2.850567
iter: 10265 | loss: 2.850373
iter: 10266 | loss: 2.850180
iter: 10267 | loss: 2.849987
iter: 10268 | loss: 2.849793
iter: 10269 | loss: 2.849600
iter: 10270 | loss: 2.849407
iter: 10271 | loss: 2.849213
iter: 10272 | loss: 2.849020
iter: 10273 | loss: 2.848826
iter: 10274 | loss: 2.848633
iter: 10275 | loss: 2.848440
iter: 10276 | loss: 2.848246
iter: 10277 | loss: 2.848053
iter: 10278 | loss: 2.847859
iter: 10279 | loss: 2.847666
iter: 10280 | loss: 2.847473
iter: 10281 | loss: 2.847279
iter: 10282 | loss: 2.847086
iter: 10283 | loss: 2.846892
iter: 10284 | loss: 2.846699
iter: 10285 | loss: 2.846506
iter: 10286 | loss: 2.846312
iter: 10287 | loss: 2.846119
iter: 10288 | loss: 2.845926
iter: 10289 | loss: 2.845732
iter: 10290 | loss: 2.845539
iter: 10291 | loss: 2.845345
iter: 10292 | loss: 2.845152
iter: 10293 | loss: 2.844959
iter: 10294 | loss: 2.844765
iter: 10295 | loss: 2.844572
iter: 10296 | loss: 2.844378
iter: 10297 | loss: 2.844185
iter: 10298 | loss: 2.843992
iter: 10299 | loss: 2.843798
iter: 10300 | loss: 2.843605
iter: 10301 | loss: 2.843412
iter: 10302 | loss: 2.843218
iter: 10303 | loss: 2.843025
iter: 10304 | loss: 2.842831
iter: 10305 | loss: 2.842638
iter: 10306 | loss: 2.842445
iter: 10307 | loss: 2.842251
iter: 10308 | loss: 2.842058
iter: 10309 | loss: 2.841864
iter: 10310 | loss: 2.841671
iter: 10311 | loss: 2.841478
iter: 10312 | loss: 2.841284
iter: 10313 | loss: 2.841091
iter: 10314 | loss: 2.840897
iter: 10315 | loss: 2.840704
iter: 10316 | loss: 2.840511
iter: 10317 | loss: 2.840317
iter: 10318 | loss: 2.840124
iter: 10319 | loss: 2.839931
iter: 10320 | loss: 2.839737
iter: 10321 | loss: 2.839544
iter: 10322 | loss: 2.839350
iter: 10323 | loss: 2.839157
iter: 10324 | loss: 2.838964
iter: 10325 | loss: 2.838770
iter: 10326 | loss: 2.838577
iter: 10327 | loss: 2.838383
iter: 10328 | loss: 2.838190
iter: 10329 | loss: 2.837997
iter: 10330 | loss: 2.837803
iter: 10331 | loss: 2.837610
iter: 10332 | loss: 2.837417
iter: 10333 | loss: 2.837223
iter: 10334 | loss: 2.837030
iter: 10335 | loss: 2.836836
iter: 10336 | loss: 2.836643
iter: 10337 | loss: 2.836450
iter: 10338 | loss: 2.836256
iter: 10339 | loss: 2.836063
iter: 10340 | loss: 2.835869
iter: 10341 | loss: 2.835676
iter: 10342 | loss: 2.835483
iter: 10343 | loss: 2.835289
iter: 10344 | loss: 2.835096
iter: 10345 | loss: 2.834902
iter: 10346 | loss: 2.834709
iter: 10347 | loss: 2.834516
iter: 10348 | loss: 2.834322
iter: 10349 | loss: 2.834129
iter: 10350 | loss: 2.833936
iter: 10351 | loss: 2.833742
iter: 10352 | loss: 2.833549
iter: 10353 | loss: 2.833355
iter: 10354 | loss: 2.833162
iter: 10355 | loss: 2.832969
iter: 10356 | loss: 2.832775
iter: 10357 | loss: 2.832582
iter: 10358 | loss: 2.832388
iter: 10359 | loss: 2.832195
iter: 10360 | loss: 2.832002
iter: 10361 | loss: 2.831808
iter: 10362 | loss: 2.831615
iter: 10363 | loss: 2.831422
iter: 10364 | loss: 2.831228
iter: 10365 | loss: 2.831035
iter: 10366 | loss: 2.830841
iter: 10367 | loss: 2.830648
iter: 10368 | loss: 2.830455
iter: 10369 | loss: 2.830261
iter: 10370 | loss: 2.830068
iter: 10371 | loss: 2.829874
iter: 10372 | loss: 2.829681
iter: 10373 | loss: 2.829488
iter: 10374 | loss: 2.829294
iter: 10375 | loss: 2.829101
iter: 10376 | loss: 2.828908
iter: 10377 | loss: 2.828714
iter: 10378 | loss: 2.828521
iter: 10379 | loss: 2.828327
iter: 10380 | loss: 2.828134
iter: 10381 | loss: 2.827941
iter: 10382 | loss: 2.827747
iter: 10383 | loss: 2.827554
iter: 10384 | loss: 2.827360
iter: 10385 | loss: 2.827167
iter: 10386 | loss: 2.826974
iter: 10387 | loss: 2.826780
iter: 10388 | loss: 2.826587
iter: 10389 | loss: 2.826393
iter: 10390 | loss: 2.826200
iter: 10391 | loss: 2.826007
iter: 10392 | loss: 2.825813
iter: 10393 | loss: 2.825620
iter: 10394 | loss: 2.825427
iter: 10395 | loss: 2.825233
iter: 10396 | loss: 2.825040
iter: 10397 | loss: 2.824846
iter: 10398 | loss: 2.824653
iter: 10399 | loss: 2.824460
iter: 10400 | loss: 2.824266
iter: 10401 | loss: 2.824073
iter: 10402 | loss: 2.823879
iter: 10403 | loss: 2.823686
iter: 10404 | loss: 2.823493
iter: 10405 | loss: 2.823299
iter: 10406 | loss: 2.823106
iter: 10407 | loss: 2.822913
iter: 10408 | loss: 2.822719
iter: 10409 | loss: 2.822526
iter: 10410 | loss: 2.822332
iter: 10411 | loss: 2.822139
iter: 10412 | loss: 2.821946
iter: 10413 | loss: 2.821752
iter: 10414 | loss: 2.821559
iter: 10415 | loss: 2.821365
iter: 10416 | loss: 2.821172
iter: 10417 | loss: 2.820979
iter: 10418 | loss: 2.820785
iter: 10419 | loss: 2.820592
iter: 10420 | loss: 2.820398
iter: 10421 | loss: 2.820205
iter: 10422 | loss: 2.820012
iter: 10423 | loss: 2.819818
iter: 10424 | loss: 2.819625
iter: 10425 | loss: 2.819432
iter: 10426 | loss: 2.819238
iter: 10427 | loss: 2.819045
iter: 10428 | loss: 2.818851
iter: 10429 | loss: 2.818658
iter: 10430 | loss: 2.818465
iter: 10431 | loss: 2.818271
iter: 10432 | loss: 2.818078
iter: 10433 | loss: 2.817884
iter: 10434 | loss: 2.817691
iter: 10435 | loss: 2.817498
iter: 10436 | loss: 2.817304
iter: 10437 | loss: 2.817111
iter: 10438 | loss: 2.816918
iter: 10439 | loss: 2.816724
iter: 10440 | loss: 2.816531
iter: 10441 | loss: 2.816337
iter: 10442 | loss: 2.816144
iter: 10443 | loss: 2.815951
iter: 10444 | loss: 2.815757
iter: 10445 | loss: 2.815564
iter: 10446 | loss: 2.815370
iter: 10447 | loss: 2.815177
iter: 10448 | loss: 2.814984
iter: 10449 | loss: 2.814790
iter: 10450 | loss: 2.814597
iter: 10451 | loss: 2.814403
iter: 10452 | loss: 2.814210
iter: 10453 | loss: 2.814017
iter: 10454 | loss: 2.813823
iter: 10455 | loss: 2.813630
iter: 10456 | loss: 2.813437
iter: 10457 | loss: 2.813243
iter: 10458 | loss: 2.813050
iter: 10459 | loss: 2.812856
iter: 10460 | loss: 2.812663
iter: 10461 | loss: 2.812470
iter: 10462 | loss: 2.812276
iter: 10463 | loss: 2.812083
iter: 10464 | loss: 2.811889
iter: 10465 | loss: 2.811696
iter: 10466 | loss: 2.811503
iter: 10467 | loss: 2.811309
iter: 10468 | loss: 2.811116
iter: 10469 | loss: 2.810923
iter: 10470 | loss: 2.810729
iter: 10471 | loss: 2.810536
iter: 10472 | loss: 2.810342
iter: 10473 | loss: 2.810149
iter: 10474 | loss: 2.809956
iter: 10475 | loss: 2.809762
iter: 10476 | loss: 2.809569
iter: 10477 | loss: 2.809375
iter: 10478 | loss: 2.809182
iter: 10479 | loss: 2.808989
iter: 10480 | loss: 2.808795
iter: 10481 | loss: 2.808602
iter: 10482 | loss: 2.808408
iter: 10483 | loss: 2.808215
iter: 10484 | loss: 2.808022
iter: 10485 | loss: 2.807828
iter: 10486 | loss: 2.807635
iter: 10487 | loss: 2.807442
iter: 10488 | loss: 2.807248
iter: 10489 | loss: 2.807055
iter: 10490 | loss: 2.806861
iter: 10491 | loss: 2.806668
iter: 10492 | loss: 2.806475
iter: 10493 | loss: 2.806281
iter: 10494 | loss: 2.806088
iter: 10495 | loss: 2.805894
iter: 10496 | loss: 2.805701
iter: 10497 | loss: 2.805508
iter: 10498 | loss: 2.805314
iter: 10499 | loss: 2.805121
iter: 10500 | loss: 2.804928
iter: 10501 | loss: 2.804734
iter: 10502 | loss: 2.804541
iter: 10503 | loss: 2.804347
iter: 10504 | loss: 2.804154
iter: 10505 | loss: 2.803961
iter: 10506 | loss: 2.803767
iter: 10507 | loss: 2.803574
iter: 10508 | loss: 2.803380
iter: 10509 | loss: 2.803187
iter: 10510 | loss: 2.802994
iter: 10511 | loss: 2.802800
iter: 10512 | loss: 2.802607
iter: 10513 | loss: 2.802413
iter: 10514 | loss: 2.802220
iter: 10515 | loss: 2.802027
iter: 10516 | loss: 2.801833
iter: 10517 | loss: 2.801640
iter: 10518 | loss: 2.801447
iter: 10519 | loss: 2.801253
iter: 10520 | loss: 2.801060
iter: 10521 | loss: 2.800866
iter: 10522 | loss: 2.800673
iter: 10523 | loss: 2.800480
iter: 10524 | loss: 2.800286
iter: 10525 | loss: 2.800093
iter: 10526 | loss: 2.799899
iter: 10527 | loss: 2.799706
iter: 10528 | loss: 2.799513
iter: 10529 | loss: 2.799319
iter: 10530 | loss: 2.799126
iter: 10531 | loss: 2.798933
iter: 10532 | loss: 2.798739
iter: 10533 | loss: 2.798546
iter: 10534 | loss: 2.798352
iter: 10535 | loss: 2.798159
iter: 10536 | loss: 2.797966
iter: 10537 | loss: 2.797772
iter: 10538 | loss: 2.797579
iter: 10539 | loss: 2.797385
iter: 10540 | loss: 2.797192
iter: 10541 | loss: 2.796999
iter: 10542 | loss: 2.796805
iter: 10543 | loss: 2.796612
iter: 10544 | loss: 2.796418
iter: 10545 | loss: 2.796225
iter: 10546 | loss: 2.796032
iter: 10547 | loss: 2.795838
iter: 10548 | loss: 2.795645
iter: 10549 | loss: 2.795452
iter: 10550 | loss: 2.795258
iter: 10551 | loss: 2.795065
iter: 10552 | loss: 2.794871
iter: 10553 | loss: 2.794678
iter: 10554 | loss: 2.794485
iter: 10555 | loss: 2.794291
iter: 10556 | loss: 2.794098
iter: 10557 | loss: 2.793904
iter: 10558 | loss: 2.793711
iter: 10559 | loss: 2.793518
iter: 10560 | loss: 2.793324
iter: 10561 | loss: 2.793131
iter: 10562 | loss: 2.792938
iter: 10563 | loss: 2.792744
iter: 10564 | loss: 2.792551
iter: 10565 | loss: 2.792357
iter: 10566 | loss: 2.792164
iter: 10567 | loss: 2.791971
iter: 10568 | loss: 2.791777
iter: 10569 | loss: 2.791584
iter: 10570 | loss: 2.791390
iter: 10571 | loss: 2.791197
iter: 10572 | loss: 2.791004
iter: 10573 | loss: 2.790810
iter: 10574 | loss: 2.790617
iter: 10575 | loss: 2.790423
iter: 10576 | loss: 2.790230
iter: 10577 | loss: 2.790037
iter: 10578 | loss: 2.789843
iter: 10579 | loss: 2.789650
iter: 10580 | loss: 2.789457
iter: 10581 | loss: 2.789263
iter: 10582 | loss: 2.789070
iter: 10583 | loss: 2.788876
iter: 10584 | loss: 2.788683
iter: 10585 | loss: 2.788490
iter: 10586 | loss: 2.788296
iter: 10587 | loss: 2.788103
iter: 10588 | loss: 2.787909
iter: 10589 | loss: 2.787716
iter: 10590 | loss: 2.787523
iter: 10591 | loss: 2.787329
iter: 10592 | loss: 2.787136
iter: 10593 | loss: 2.786943
iter: 10594 | loss: 2.786749
iter: 10595 | loss: 2.786556
iter: 10596 | loss: 2.786362
iter: 10597 | loss: 2.786169
iter: 10598 | loss: 2.785976
iter: 10599 | loss: 2.785782
iter: 10600 | loss: 2.785589
iter: 10601 | loss: 2.785395
iter: 10602 | loss: 2.785202
iter: 10603 | loss: 2.785009
iter: 10604 | loss: 2.784815
iter: 10605 | loss: 2.784622
iter: 10606 | loss: 2.784428
iter: 10607 | loss: 2.784235
iter: 10608 | loss: 2.784042
iter: 10609 | loss: 2.783848
iter: 10610 | loss: 2.783655
iter: 10611 | loss: 2.783462
iter: 10612 | loss: 2.783268
iter: 10613 | loss: 2.783075
iter: 10614 | loss: 2.782881
iter: 10615 | loss: 2.782688
iter: 10616 | loss: 2.782495
iter: 10617 | loss: 2.782301
iter: 10618 | loss: 2.782108
iter: 10619 | loss: 2.781914
iter: 10620 | loss: 2.781721
iter: 10621 | loss: 2.781528
iter: 10622 | loss: 2.781334
iter: 10623 | loss: 2.781141
iter: 10624 | loss: 2.780948
iter: 10625 | loss: 2.780754
iter: 10626 | loss: 2.780561
iter: 10627 | loss: 2.780367
iter: 10628 | loss: 2.780174
iter: 10629 | loss: 2.779981
iter: 10630 | loss: 2.779787
iter: 10631 | loss: 2.779594
iter: 10632 | loss: 2.779400
iter: 10633 | loss: 2.779207
iter: 10634 | loss: 2.779014
iter: 10635 | loss: 2.778820
iter: 10636 | loss: 2.778627
iter: 10637 | loss: 2.778433
iter: 10638 | loss: 2.778240
iter: 10639 | loss: 2.778047
iter: 10640 | loss: 2.777853
iter: 10641 | loss: 2.777660
iter: 10642 | loss: 2.777467
iter: 10643 | loss: 2.777273
iter: 10644 | loss: 2.777080
iter: 10645 | loss: 2.776886
iter: 10646 | loss: 2.776693
iter: 10647 | loss: 2.776500
iter: 10648 | loss: 2.776306
iter: 10649 | loss: 2.776113
iter: 10650 | loss: 2.775919
iter: 10651 | loss: 2.775726
iter: 10652 | loss: 2.775533
iter: 10653 | loss: 2.775339
iter: 10654 | loss: 2.775146
iter: 10655 | loss: 2.774953
iter: 10656 | loss: 2.774759
iter: 10657 | loss: 2.774566
iter: 10658 | loss: 2.774372
iter: 10659 | loss: 2.774179
iter: 10660 | loss: 2.773986
iter: 10661 | loss: 2.773792
iter: 10662 | loss: 2.773599
iter: 10663 | loss: 2.773405
iter: 10664 | loss: 2.773212
iter: 10665 | loss: 2.773019
iter: 10666 | loss: 2.772825
iter: 10667 | loss: 2.772632
iter: 10668 | loss: 2.772439
iter: 10669 | loss: 2.772245
iter: 10670 | loss: 2.772052
iter: 10671 | loss: 2.771858
iter: 10672 | loss: 2.771665
iter: 10673 | loss: 2.771472
iter: 10674 | loss: 2.771278
iter: 10675 | loss: 2.771085
iter: 10676 | loss: 2.770891
iter: 10677 | loss: 2.770698
iter: 10678 | loss: 2.770505
iter: 10679 | loss: 2.770311
iter: 10680 | loss: 2.770118
iter: 10681 | loss: 2.769924
iter: 10682 | loss: 2.769731
iter: 10683 | loss: 2.769538
iter: 10684 | loss: 2.769344
iter: 10685 | loss: 2.769151
iter: 10686 | loss: 2.768958
iter: 10687 | loss: 2.768764
iter: 10688 | loss: 2.768571
iter: 10689 | loss: 2.768377
iter: 10690 | loss: 2.768184
iter: 10691 | loss: 2.767991
iter: 10692 | loss: 2.767797
iter: 10693 | loss: 2.767604
iter: 10694 | loss: 2.767410
iter: 10695 | loss: 2.767217
iter: 10696 | loss: 2.767024
iter: 10697 | loss: 2.766830
iter: 10698 | loss: 2.766637
iter: 10699 | loss: 2.766444
iter: 10700 | loss: 2.766250
iter: 10701 | loss: 2.766057
iter: 10702 | loss: 2.765863
iter: 10703 | loss: 2.765670
iter: 10704 | loss: 2.765477
iter: 10705 | loss: 2.765283
iter: 10706 | loss: 2.765090
iter: 10707 | loss: 2.764896
iter: 10708 | loss: 2.764703
iter: 10709 | loss: 2.764510
iter: 10710 | loss: 2.764316
iter: 10711 | loss: 2.764123
iter: 10712 | loss: 2.763929
iter: 10713 | loss: 2.763736
iter: 10714 | loss: 2.763543
iter: 10715 | loss: 2.763349
iter: 10716 | loss: 2.763156
iter: 10717 | loss: 2.762963
iter: 10718 | loss: 2.762769
iter: 10719 | loss: 2.762576
iter: 10720 | loss: 2.762382
iter: 10721 | loss: 2.762189
iter: 10722 | loss: 2.761996
iter: 10723 | loss: 2.761802
iter: 10724 | loss: 2.761609
iter: 10725 | loss: 2.761415
iter: 10726 | loss: 2.761222
iter: 10727 | loss: 2.761029
iter: 10728 | loss: 2.760835
iter: 10729 | loss: 2.760642
iter: 10730 | loss: 2.760449
iter: 10731 | loss: 2.760255
iter: 10732 | loss: 2.760062
iter: 10733 | loss: 2.759868
iter: 10734 | loss: 2.759675
iter: 10735 | loss: 2.759482
iter: 10736 | loss: 2.759288
iter: 10737 | loss: 2.759095
iter: 10738 | loss: 2.758901
iter: 10739 | loss: 2.758708
iter: 10740 | loss: 2.758515
iter: 10741 | loss: 2.758321
iter: 10742 | loss: 2.758128
iter: 10743 | loss: 2.757934
iter: 10744 | loss: 2.757741
iter: 10745 | loss: 2.757548
iter: 10746 | loss: 2.757354
iter: 10747 | loss: 2.757161
iter: 10748 | loss: 2.756968
iter: 10749 | loss: 2.756774
iter: 10750 | loss: 2.756581
iter: 10751 | loss: 2.756387
iter: 10752 | loss: 2.756194
iter: 10753 | loss: 2.756001
iter: 10754 | loss: 2.755807
iter: 10755 | loss: 2.755614
iter: 10756 | loss: 2.755420
iter: 10757 | loss: 2.755227
iter: 10758 | loss: 2.755034
iter: 10759 | loss: 2.754840
iter: 10760 | loss: 2.754647
iter: 10761 | loss: 2.754454
iter: 10762 | loss: 2.754260
iter: 10763 | loss: 2.754067
iter: 10764 | loss: 2.753873
iter: 10765 | loss: 2.753680
iter: 10766 | loss: 2.753487
iter: 10767 | loss: 2.753293
iter: 10768 | loss: 2.753100
iter: 10769 | loss: 2.752906
iter: 10770 | loss: 2.752713
iter: 10771 | loss: 2.752520
iter: 10772 | loss: 2.752326
iter: 10773 | loss: 2.752133
iter: 10774 | loss: 2.751939
iter: 10775 | loss: 2.751746
iter: 10776 | loss: 2.751553
iter: 10777 | loss: 2.751359
iter: 10778 | loss: 2.751166
iter: 10779 | loss: 2.750973
iter: 10780 | loss: 2.750779
iter: 10781 | loss: 2.750586
iter: 10782 | loss: 2.750392
iter: 10783 | loss: 2.750199
iter: 10784 | loss: 2.750006
iter: 10785 | loss: 2.749812
iter: 10786 | loss: 2.749619
iter: 10787 | loss: 2.749425
iter: 10788 | loss: 2.749232
iter: 10789 | loss: 2.749039
iter: 10790 | loss: 2.748845
iter: 10791 | loss: 2.748652
iter: 10792 | loss: 2.748459
iter: 10793 | loss: 2.748265
iter: 10794 | loss: 2.748072
iter: 10795 | loss: 2.747878
iter: 10796 | loss: 2.747685
iter: 10797 | loss: 2.747492
iter: 10798 | loss: 2.747298
iter: 10799 | loss: 2.747105
iter: 10800 | loss: 2.746911
iter: 10801 | loss: 2.746718
iter: 10802 | loss: 2.746525
iter: 10803 | loss: 2.746331
iter: 10804 | loss: 2.746138
iter: 10805 | loss: 2.745944
iter: 10806 | loss: 2.745751
iter: 10807 | loss: 2.745558
iter: 10808 | loss: 2.745364
iter: 10809 | loss: 2.745171
iter: 10810 | loss: 2.744978
iter: 10811 | loss: 2.744784
iter: 10812 | loss: 2.744591
iter: 10813 | loss: 2.744397
iter: 10814 | loss: 2.744204
iter: 10815 | loss: 2.744011
iter: 10816 | loss: 2.743817
iter: 10817 | loss: 2.743624
iter: 10818 | loss: 2.743430
iter: 10819 | loss: 2.743237
iter: 10820 | loss: 2.743044
iter: 10821 | loss: 2.742850
iter: 10822 | loss: 2.742657
iter: 10823 | loss: 2.742464
iter: 10824 | loss: 2.742270
iter: 10825 | loss: 2.742077
iter: 10826 | loss: 2.741883
iter: 10827 | loss: 2.741690
iter: 10828 | loss: 2.741497
iter: 10829 | loss: 2.741303
iter: 10830 | loss: 2.741110
iter: 10831 | loss: 2.740916
iter: 10832 | loss: 2.740723
iter: 10833 | loss: 2.740530
iter: 10834 | loss: 2.740336
iter: 10835 | loss: 2.740143
iter: 10836 | loss: 2.739949
iter: 10837 | loss: 2.739756
iter: 10838 | loss: 2.739563
iter: 10839 | loss: 2.739369
iter: 10840 | loss: 2.739176
iter: 10841 | loss: 2.738983
iter: 10842 | loss: 2.738789
iter: 10843 | loss: 2.738596
iter: 10844 | loss: 2.738402
iter: 10845 | loss: 2.738209
iter: 10846 | loss: 2.738016
iter: 10847 | loss: 2.737822
iter: 10848 | loss: 2.737629
iter: 10849 | loss: 2.737435
iter: 10850 | loss: 2.737242
iter: 10851 | loss: 2.737049
iter: 10852 | loss: 2.736855
iter: 10853 | loss: 2.736662
iter: 10854 | loss: 2.736469
iter: 10855 | loss: 2.736275
iter: 10856 | loss: 2.736082
iter: 10857 | loss: 2.735888
iter: 10858 | loss: 2.735695
iter: 10859 | loss: 2.735502
iter: 10860 | loss: 2.735308
iter: 10861 | loss: 2.735115
iter: 10862 | loss: 2.734921
iter: 10863 | loss: 2.734728
iter: 10864 | loss: 2.734535
iter: 10865 | loss: 2.734341
iter: 10866 | loss: 2.734148
iter: 10867 | loss: 2.733954
iter: 10868 | loss: 2.733761
iter: 10869 | loss: 2.733568
iter: 10870 | loss: 2.733374
iter: 10871 | loss: 2.733181
iter: 10872 | loss: 2.732988
iter: 10873 | loss: 2.732794
iter: 10874 | loss: 2.732601
iter: 10875 | loss: 2.732407
iter: 10876 | loss: 2.732214
iter: 10877 | loss: 2.732021
iter: 10878 | loss: 2.731827
iter: 10879 | loss: 2.731634
iter: 10880 | loss: 2.731440
iter: 10881 | loss: 2.731247
iter: 10882 | loss: 2.731054
iter: 10883 | loss: 2.730860
iter: 10884 | loss: 2.730667
iter: 10885 | loss: 2.730474
iter: 10886 | loss: 2.730280
iter: 10887 | loss: 2.730087
iter: 10888 | loss: 2.729893
iter: 10889 | loss: 2.729700
iter: 10890 | loss: 2.729507
iter: 10891 | loss: 2.729313
iter: 10892 | loss: 2.729120
iter: 10893 | loss: 2.728926
iter: 10894 | loss: 2.728733
iter: 10895 | loss: 2.728540
iter: 10896 | loss: 2.728346
iter: 10897 | loss: 2.728153
iter: 10898 | loss: 2.727959
iter: 10899 | loss: 2.727766
iter: 10900 | loss: 2.727573
iter: 10901 | loss: 2.727379
iter: 10902 | loss: 2.727186
iter: 10903 | loss: 2.726993
iter: 10904 | loss: 2.726799
iter: 10905 | loss: 2.726606
iter: 10906 | loss: 2.726412
iter: 10907 | loss: 2.726219
iter: 10908 | loss: 2.726026
iter: 10909 | loss: 2.725832
iter: 10910 | loss: 2.725639
iter: 10911 | loss: 2.725445
iter: 10912 | loss: 2.725252
iter: 10913 | loss: 2.725059
iter: 10914 | loss: 2.724865
iter: 10915 | loss: 2.724672
iter: 10916 | loss: 2.724479
iter: 10917 | loss: 2.724285
iter: 10918 | loss: 2.724092
iter: 10919 | loss: 2.723898
iter: 10920 | loss: 2.723705
iter: 10921 | loss: 2.723512
iter: 10922 | loss: 2.723318
iter: 10923 | loss: 2.723125
iter: 10924 | loss: 2.722931
iter: 10925 | loss: 2.722738
iter: 10926 | loss: 2.722545
iter: 10927 | loss: 2.722351
iter: 10928 | loss: 2.722158
iter: 10929 | loss: 2.721964
iter: 10930 | loss: 2.721771
iter: 10931 | loss: 2.721578
iter: 10932 | loss: 2.721384
iter: 10933 | loss: 2.721191
iter: 10934 | loss: 2.720998
iter: 10935 | loss: 2.720804
iter: 10936 | loss: 2.720611
iter: 10937 | loss: 2.720417
iter: 10938 | loss: 2.720224
iter: 10939 | loss: 2.720031
iter: 10940 | loss: 2.719837
iter: 10941 | loss: 2.719644
iter: 10942 | loss: 2.719450
iter: 10943 | loss: 2.719257
iter: 10944 | loss: 2.719064
iter: 10945 | loss: 2.718870
iter: 10946 | loss: 2.718677
iter: 10947 | loss: 2.718484
iter: 10948 | loss: 2.718290
iter: 10949 | loss: 2.718097
iter: 10950 | loss: 2.717903
iter: 10951 | loss: 2.717710
iter: 10952 | loss: 2.717517
iter: 10953 | loss: 2.717323
iter: 10954 | loss: 2.717130
iter: 10955 | loss: 2.716936
iter: 10956 | loss: 2.716743
iter: 10957 | loss: 2.716550
iter: 10958 | loss: 2.716356
iter: 10959 | loss: 2.716163
iter: 10960 | loss: 2.715969
iter: 10961 | loss: 2.715776
iter: 10962 | loss: 2.715583
iter: 10963 | loss: 2.715389
iter: 10964 | loss: 2.715196
iter: 10965 | loss: 2.715003
iter: 10966 | loss: 2.714809
iter: 10967 | loss: 2.714616
iter: 10968 | loss: 2.714422
iter: 10969 | loss: 2.714229
iter: 10970 | loss: 2.714036
iter: 10971 | loss: 2.713842
iter: 10972 | loss: 2.713649
iter: 10973 | loss: 2.713455
iter: 10974 | loss: 2.713262
iter: 10975 | loss: 2.713069
iter: 10976 | loss: 2.712875
iter: 10977 | loss: 2.712682
iter: 10978 | loss: 2.712489
iter: 10979 | loss: 2.712295
iter: 10980 | loss: 2.712102
iter: 10981 | loss: 2.711908
iter: 10982 | loss: 2.711715
iter: 10983 | loss: 2.711522
iter: 10984 | loss: 2.711328
iter: 10985 | loss: 2.711135
iter: 10986 | loss: 2.710941
iter: 10987 | loss: 2.710748
iter: 10988 | loss: 2.710555
iter: 10989 | loss: 2.710361
iter: 10990 | loss: 2.710168
iter: 10991 | loss: 2.709975
iter: 10992 | loss: 2.709781
iter: 10993 | loss: 2.709588
iter: 10994 | loss: 2.709394
iter: 10995 | loss: 2.709201
iter: 10996 | loss: 2.709008
iter: 10997 | loss: 2.708814
iter: 10998 | loss: 2.708621
iter: 10999 | loss: 2.708427
iter: 11000 | loss: 2.708234
iter: 11001 | loss: 2.708041
iter: 11002 | loss: 2.707847
iter: 11003 | loss: 2.707654
iter: 11004 | loss: 2.707460
iter: 11005 | loss: 2.707267
iter: 11006 | loss: 2.707074
iter: 11007 | loss: 2.706880
iter: 11008 | loss: 2.706687
iter: 11009 | loss: 2.706494
iter: 11010 | loss: 2.706300
iter: 11011 | loss: 2.706107
iter: 11012 | loss: 2.705913
iter: 11013 | loss: 2.705720
iter: 11014 | loss: 2.705527
iter: 11015 | loss: 2.705333
iter: 11016 | loss: 2.705140
iter: 11017 | loss: 2.704946
iter: 11018 | loss: 2.704753
iter: 11019 | loss: 2.704560
iter: 11020 | loss: 2.704366
iter: 11021 | loss: 2.704173
iter: 11022 | loss: 2.703980
iter: 11023 | loss: 2.703786
iter: 11024 | loss: 2.703593
iter: 11025 | loss: 2.703399
iter: 11026 | loss: 2.703206
iter: 11027 | loss: 2.703013
iter: 11028 | loss: 2.702819
iter: 11029 | loss: 2.702626
iter: 11030 | loss: 2.702432
iter: 11031 | loss: 2.702239
iter: 11032 | loss: 2.702046
iter: 11033 | loss: 2.701852
iter: 11034 | loss: 2.701659
iter: 11035 | loss: 2.701465
iter: 11036 | loss: 2.701272
iter: 11037 | loss: 2.701079
iter: 11038 | loss: 2.700885
iter: 11039 | loss: 2.700692
iter: 11040 | loss: 2.700499
iter: 11041 | loss: 2.700305
iter: 11042 | loss: 2.700112
iter: 11043 | loss: 2.699918
iter: 11044 | loss: 2.699725
iter: 11045 | loss: 2.699532
iter: 11046 | loss: 2.699338
iter: 11047 | loss: 2.699145
iter: 11048 | loss: 2.698951
iter: 11049 | loss: 2.698758
iter: 11050 | loss: 2.698565
iter: 11051 | loss: 2.698371
iter: 11052 | loss: 2.698178
iter: 11053 | loss: 2.697985
iter: 11054 | loss: 2.697791
iter: 11055 | loss: 2.697598
iter: 11056 | loss: 2.697404
iter: 11057 | loss: 2.697211
iter: 11058 | loss: 2.697018
iter: 11059 | loss: 2.696824
iter: 11060 | loss: 2.696631
iter: 11061 | loss: 2.696437
iter: 11062 | loss: 2.696244
iter: 11063 | loss: 2.696051
iter: 11064 | loss: 2.695857
iter: 11065 | loss: 2.695664
iter: 11066 | loss: 2.695470
iter: 11067 | loss: 2.695277
iter: 11068 | loss: 2.695084
iter: 11069 | loss: 2.694890
iter: 11070 | loss: 2.694697
iter: 11071 | loss: 2.694504
iter: 11072 | loss: 2.694310
iter: 11073 | loss: 2.694117
iter: 11074 | loss: 2.693923
iter: 11075 | loss: 2.693730
iter: 11076 | loss: 2.693537
iter: 11077 | loss: 2.693343
iter: 11078 | loss: 2.693150
iter: 11079 | loss: 2.692956
iter: 11080 | loss: 2.692763
iter: 11081 | loss: 2.692570
iter: 11082 | loss: 2.692376
iter: 11083 | loss: 2.692183
iter: 11084 | loss: 2.691990
iter: 11085 | loss: 2.691796
iter: 11086 | loss: 2.691603
iter: 11087 | loss: 2.691409
iter: 11088 | loss: 2.691216
iter: 11089 | loss: 2.691023
iter: 11090 | loss: 2.690829
iter: 11091 | loss: 2.690636
iter: 11092 | loss: 2.690442
iter: 11093 | loss: 2.690249
iter: 11094 | loss: 2.690056
iter: 11095 | loss: 2.689862
iter: 11096 | loss: 2.689669
iter: 11097 | loss: 2.689475
iter: 11098 | loss: 2.689282
iter: 11099 | loss: 2.689089
iter: 11100 | loss: 2.688895
iter: 11101 | loss: 2.688702
iter: 11102 | loss: 2.688509
iter: 11103 | loss: 2.688315
iter: 11104 | loss: 2.688122
iter: 11105 | loss: 2.687928
iter: 11106 | loss: 2.687735
iter: 11107 | loss: 2.687542
iter: 11108 | loss: 2.687348
iter: 11109 | loss: 2.687155
iter: 11110 | loss: 2.686961
iter: 11111 | loss: 2.686768
iter: 11112 | loss: 2.686575
iter: 11113 | loss: 2.686381
iter: 11114 | loss: 2.686188
iter: 11115 | loss: 2.685995
iter: 11116 | loss: 2.685801
iter: 11117 | loss: 2.685608
iter: 11118 | loss: 2.685414
iter: 11119 | loss: 2.685221
iter: 11120 | loss: 2.685028
iter: 11121 | loss: 2.684834
iter: 11122 | loss: 2.684641
iter: 11123 | loss: 2.684447
iter: 11124 | loss: 2.684254
iter: 11125 | loss: 2.684061
iter: 11126 | loss: 2.683867
iter: 11127 | loss: 2.683674
iter: 11128 | loss: 2.683480
iter: 11129 | loss: 2.683287
iter: 11130 | loss: 2.683094
iter: 11131 | loss: 2.682900
iter: 11132 | loss: 2.682707
iter: 11133 | loss: 2.682514
iter: 11134 | loss: 2.682320
iter: 11135 | loss: 2.682127
iter: 11136 | loss: 2.681933
iter: 11137 | loss: 2.681740
iter: 11138 | loss: 2.681547
iter: 11139 | loss: 2.681353
iter: 11140 | loss: 2.681160
iter: 11141 | loss: 2.680966
iter: 11142 | loss: 2.680773
iter: 11143 | loss: 2.680580
iter: 11144 | loss: 2.680386
iter: 11145 | loss: 2.680193
iter: 11146 | loss: 2.680000
iter: 11147 | loss: 2.679806
iter: 11148 | loss: 2.679613
iter: 11149 | loss: 2.679419
iter: 11150 | loss: 2.679226
iter: 11151 | loss: 2.679033
iter: 11152 | loss: 2.678839
iter: 11153 | loss: 2.678646
iter: 11154 | loss: 2.678452
iter: 11155 | loss: 2.678259
iter: 11156 | loss: 2.678066
iter: 11157 | loss: 2.677872
iter: 11158 | loss: 2.677679
iter: 11159 | loss: 2.677485
iter: 11160 | loss: 2.677292
iter: 11161 | loss: 2.677099
iter: 11162 | loss: 2.676905
iter: 11163 | loss: 2.676712
iter: 11164 | loss: 2.676519
iter: 11165 | loss: 2.676325
iter: 11166 | loss: 2.676132
iter: 11167 | loss: 2.675938
iter: 11168 | loss: 2.675745
iter: 11169 | loss: 2.675552
iter: 11170 | loss: 2.675358
iter: 11171 | loss: 2.675165
iter: 11172 | loss: 2.674971
iter: 11173 | loss: 2.674778
iter: 11174 | loss: 2.674585
iter: 11175 | loss: 2.674391
iter: 11176 | loss: 2.674198
iter: 11177 | loss: 2.674005
iter: 11178 | loss: 2.673811
iter: 11179 | loss: 2.673618
iter: 11180 | loss: 2.673424
iter: 11181 | loss: 2.673231
iter: 11182 | loss: 2.673038
iter: 11183 | loss: 2.672844
iter: 11184 | loss: 2.672651
iter: 11185 | loss: 2.672457
iter: 11186 | loss: 2.672264
iter: 11187 | loss: 2.672071
iter: 11188 | loss: 2.671877
iter: 11189 | loss: 2.671684
iter: 11190 | loss: 2.671490
iter: 11191 | loss: 2.671297
iter: 11192 | loss: 2.671104
iter: 11193 | loss: 2.670910
iter: 11194 | loss: 2.670717
iter: 11195 | loss: 2.670524
iter: 11196 | loss: 2.670330
iter: 11197 | loss: 2.670137
iter: 11198 | loss: 2.669943
iter: 11199 | loss: 2.669750
iter: 11200 | loss: 2.669557
iter: 11201 | loss: 2.669363
iter: 11202 | loss: 2.669170
iter: 11203 | loss: 2.668976
iter: 11204 | loss: 2.668783
iter: 11205 | loss: 2.668590
iter: 11206 | loss: 2.668396
iter: 11207 | loss: 2.668203
iter: 11208 | loss: 2.668010
iter: 11209 | loss: 2.667816
iter: 11210 | loss: 2.667623
iter: 11211 | loss: 2.667429
iter: 11212 | loss: 2.667236
iter: 11213 | loss: 2.667043
iter: 11214 | loss: 2.666849
iter: 11215 | loss: 2.666656
iter: 11216 | loss: 2.666462
iter: 11217 | loss: 2.666269
iter: 11218 | loss: 2.666076
iter: 11219 | loss: 2.665882
iter: 11220 | loss: 2.665689
iter: 11221 | loss: 2.665495
iter: 11222 | loss: 2.665302
iter: 11223 | loss: 2.665109
iter: 11224 | loss: 2.664915
iter: 11225 | loss: 2.664722
iter: 11226 | loss: 2.664529
iter: 11227 | loss: 2.664335
iter: 11228 | loss: 2.664142
iter: 11229 | loss: 2.663948
iter: 11230 | loss: 2.663755
iter: 11231 | loss: 2.663562
iter: 11232 | loss: 2.663368
iter: 11233 | loss: 2.663175
iter: 11234 | loss: 2.662981
iter: 11235 | loss: 2.662788
iter: 11236 | loss: 2.662595
iter: 11237 | loss: 2.662401
iter: 11238 | loss: 2.662208
iter: 11239 | loss: 2.662015
iter: 11240 | loss: 2.661821
iter: 11241 | loss: 2.661628
iter: 11242 | loss: 2.661434
iter: 11243 | loss: 2.661241
iter: 11244 | loss: 2.661048
iter: 11245 | loss: 2.660854
iter: 11246 | loss: 2.660661
iter: 11247 | loss: 2.660467
iter: 11248 | loss: 2.660274
iter: 11249 | loss: 2.660081
iter: 11250 | loss: 2.659887
iter: 11251 | loss: 2.659694
iter: 11252 | loss: 2.659500
iter: 11253 | loss: 2.659307
iter: 11254 | loss: 2.659114
iter: 11255 | loss: 2.658920
iter: 11256 | loss: 2.658727
iter: 11257 | loss: 2.658534
iter: 11258 | loss: 2.658340
iter: 11259 | loss: 2.658147
iter: 11260 | loss: 2.657953
iter: 11261 | loss: 2.657760
iter: 11262 | loss: 2.657567
iter: 11263 | loss: 2.657373
iter: 11264 | loss: 2.657180
iter: 11265 | loss: 2.656986
iter: 11266 | loss: 2.656793
iter: 11267 | loss: 2.656600
iter: 11268 | loss: 2.656406
iter: 11269 | loss: 2.656213
iter: 11270 | loss: 2.656020
iter: 11271 | loss: 2.655826
iter: 11272 | loss: 2.655633
iter: 11273 | loss: 2.655439
iter: 11274 | loss: 2.655246
iter: 11275 | loss: 2.655053
iter: 11276 | loss: 2.654859
iter: 11277 | loss: 2.654666
iter: 11278 | loss: 2.654472
iter: 11279 | loss: 2.654279
iter: 11280 | loss: 2.654086
iter: 11281 | loss: 2.653892
iter: 11282 | loss: 2.653699
iter: 11283 | loss: 2.653505
iter: 11284 | loss: 2.653312
iter: 11285 | loss: 2.653119
iter: 11286 | loss: 2.652925
iter: 11287 | loss: 2.652732
iter: 11288 | loss: 2.652539
iter: 11289 | loss: 2.652345
iter: 11290 | loss: 2.652152
iter: 11291 | loss: 2.651958
iter: 11292 | loss: 2.651765
iter: 11293 | loss: 2.651572
iter: 11294 | loss: 2.651378
iter: 11295 | loss: 2.651185
iter: 11296 | loss: 2.650991
iter: 11297 | loss: 2.650798
iter: 11298 | loss: 2.650605
iter: 11299 | loss: 2.650411
iter: 11300 | loss: 2.650218
iter: 11301 | loss: 2.650025
iter: 11302 | loss: 2.649831
iter: 11303 | loss: 2.649638
iter: 11304 | loss: 2.649444
iter: 11305 | loss: 2.649251
iter: 11306 | loss: 2.649058
iter: 11307 | loss: 2.648864
iter: 11308 | loss: 2.648671
iter: 11309 | loss: 2.648477
iter: 11310 | loss: 2.648284
iter: 11311 | loss: 2.648091
iter: 11312 | loss: 2.647897
iter: 11313 | loss: 2.647704
iter: 11314 | loss: 2.647511
iter: 11315 | loss: 2.647317
iter: 11316 | loss: 2.647124
iter: 11317 | loss: 2.646930
iter: 11318 | loss: 2.646737
iter: 11319 | loss: 2.646544
iter: 11320 | loss: 2.646350
iter: 11321 | loss: 2.646157
iter: 11322 | loss: 2.645963
iter: 11323 | loss: 2.645770
iter: 11324 | loss: 2.645577
iter: 11325 | loss: 2.645383
iter: 11326 | loss: 2.645190
iter: 11327 | loss: 2.644996
iter: 11328 | loss: 2.644803
iter: 11329 | loss: 2.644610
iter: 11330 | loss: 2.644416
iter: 11331 | loss: 2.644223
iter: 11332 | loss: 2.644030
iter: 11333 | loss: 2.643836
iter: 11334 | loss: 2.643643
iter: 11335 | loss: 2.643449
iter: 11336 | loss: 2.643256
iter: 11337 | loss: 2.643063
iter: 11338 | loss: 2.642869
iter: 11339 | loss: 2.642676
iter: 11340 | loss: 2.642482
iter: 11341 | loss: 2.642289
iter: 11342 | loss: 2.642096
iter: 11343 | loss: 2.641902
iter: 11344 | loss: 2.641709
iter: 11345 | loss: 2.641516
iter: 11346 | loss: 2.641322
iter: 11347 | loss: 2.641129
iter: 11348 | loss: 2.640935
iter: 11349 | loss: 2.640742
iter: 11350 | loss: 2.640549
iter: 11351 | loss: 2.640355
iter: 11352 | loss: 2.640162
iter: 11353 | loss: 2.639968
iter: 11354 | loss: 2.639775
iter: 11355 | loss: 2.639582
iter: 11356 | loss: 2.639388
iter: 11357 | loss: 2.639195
iter: 11358 | loss: 2.639001
iter: 11359 | loss: 2.638808
iter: 11360 | loss: 2.638615
iter: 11361 | loss: 2.638421
iter: 11362 | loss: 2.638228
iter: 11363 | loss: 2.638035
iter: 11364 | loss: 2.637841
iter: 11365 | loss: 2.637648
iter: 11366 | loss: 2.637454
iter: 11367 | loss: 2.637261
iter: 11368 | loss: 2.637068
iter: 11369 | loss: 2.636874
iter: 11370 | loss: 2.636681
iter: 11371 | loss: 2.636487
iter: 11372 | loss: 2.636294
iter: 11373 | loss: 2.636101
iter: 11374 | loss: 2.635907
iter: 11375 | loss: 2.635714
iter: 11376 | loss: 2.635521
iter: 11377 | loss: 2.635327
iter: 11378 | loss: 2.635134
iter: 11379 | loss: 2.634940
iter: 11380 | loss: 2.634747
iter: 11381 | loss: 2.634554
iter: 11382 | loss: 2.634360
iter: 11383 | loss: 2.634167
iter: 11384 | loss: 2.633973
iter: 11385 | loss: 2.633780
iter: 11386 | loss: 2.633587
iter: 11387 | loss: 2.633393
iter: 11388 | loss: 2.633200
iter: 11389 | loss: 2.633006
iter: 11390 | loss: 2.632813
iter: 11391 | loss: 2.632620
iter: 11392 | loss: 2.632426
iter: 11393 | loss: 2.632233
iter: 11394 | loss: 2.632040
iter: 11395 | loss: 2.631846
iter: 11396 | loss: 2.631653
iter: 11397 | loss: 2.631459
iter: 11398 | loss: 2.631266
iter: 11399 | loss: 2.631073
iter: 11400 | loss: 2.630879
iter: 11401 | loss: 2.630686
iter: 11402 | loss: 2.630492
iter: 11403 | loss: 2.630299
iter: 11404 | loss: 2.630106
iter: 11405 | loss: 2.629912
iter: 11406 | loss: 2.629719
iter: 11407 | loss: 2.629526
iter: 11408 | loss: 2.629332
iter: 11409 | loss: 2.629139
iter: 11410 | loss: 2.628945
iter: 11411 | loss: 2.628752
iter: 11412 | loss: 2.628559
iter: 11413 | loss: 2.628365
iter: 11414 | loss: 2.628172
iter: 11415 | loss: 2.627978
iter: 11416 | loss: 2.627785
iter: 11417 | loss: 2.627592
iter: 11418 | loss: 2.627398
iter: 11419 | loss: 2.627205
iter: 11420 | loss: 2.627011
iter: 11421 | loss: 2.626818
iter: 11422 | loss: 2.626625
iter: 11423 | loss: 2.626431
iter: 11424 | loss: 2.626238
iter: 11425 | loss: 2.626045
iter: 11426 | loss: 2.625851
iter: 11427 | loss: 2.625658
iter: 11428 | loss: 2.625464
iter: 11429 | loss: 2.625271
iter: 11430 | loss: 2.625078
iter: 11431 | loss: 2.624884
iter: 11432 | loss: 2.624691
iter: 11433 | loss: 2.624497
iter: 11434 | loss: 2.624304
iter: 11435 | loss: 2.624111
iter: 11436 | loss: 2.623917
iter: 11437 | loss: 2.623724
iter: 11438 | loss: 2.623531
iter: 11439 | loss: 2.623337
iter: 11440 | loss: 2.623144
iter: 11441 | loss: 2.622950
iter: 11442 | loss: 2.622757
iter: 11443 | loss: 2.622564
iter: 11444 | loss: 2.622370
iter: 11445 | loss: 2.622177
iter: 11446 | loss: 2.621983
iter: 11447 | loss: 2.621790
iter: 11448 | loss: 2.621597
iter: 11449 | loss: 2.621403
iter: 11450 | loss: 2.621210
iter: 11451 | loss: 2.621016
iter: 11452 | loss: 2.620823
iter: 11453 | loss: 2.620630
iter: 11454 | loss: 2.620436
iter: 11455 | loss: 2.620243
iter: 11456 | loss: 2.620050
iter: 11457 | loss: 2.619856
iter: 11458 | loss: 2.619663
iter: 11459 | loss: 2.619469
iter: 11460 | loss: 2.619276
iter: 11461 | loss: 2.619083
iter: 11462 | loss: 2.618889
iter: 11463 | loss: 2.618696
iter: 11464 | loss: 2.618502
iter: 11465 | loss: 2.618309
iter: 11466 | loss: 2.618116
iter: 11467 | loss: 2.617922
iter: 11468 | loss: 2.617729
iter: 11469 | loss: 2.617536
iter: 11470 | loss: 2.617342
iter: 11471 | loss: 2.617149
iter: 11472 | loss: 2.616955
iter: 11473 | loss: 2.616762
iter: 11474 | loss: 2.616569
iter: 11475 | loss: 2.616375
iter: 11476 | loss: 2.616182
iter: 11477 | loss: 2.615988
iter: 11478 | loss: 2.615795
iter: 11479 | loss: 2.615602
iter: 11480 | loss: 2.615408
iter: 11481 | loss: 2.615215
iter: 11482 | loss: 2.615021
iter: 11483 | loss: 2.614828
iter: 11484 | loss: 2.614635
iter: 11485 | loss: 2.614441
iter: 11486 | loss: 2.614248
iter: 11487 | loss: 2.614055
iter: 11488 | loss: 2.613861
iter: 11489 | loss: 2.613668
iter: 11490 | loss: 2.613474
iter: 11491 | loss: 2.613281
iter: 11492 | loss: 2.613088
iter: 11493 | loss: 2.612894
iter: 11494 | loss: 2.612701
iter: 11495 | loss: 2.612507
iter: 11496 | loss: 2.612314
iter: 11497 | loss: 2.612121
iter: 11498 | loss: 2.611927
iter: 11499 | loss: 2.611734
iter: 11500 | loss: 2.611541
iter: 11501 | loss: 2.611347
iter: 11502 | loss: 2.611154
iter: 11503 | loss: 2.610960
iter: 11504 | loss: 2.610767
iter: 11505 | loss: 2.610574
iter: 11506 | loss: 2.610380
iter: 11507 | loss: 2.610187
iter: 11508 | loss: 2.609993
iter: 11509 | loss: 2.609800
iter: 11510 | loss: 2.609607
iter: 11511 | loss: 2.609413
iter: 11512 | loss: 2.609220
iter: 11513 | loss: 2.609026
iter: 11514 | loss: 2.608833
iter: 11515 | loss: 2.608640
iter: 11516 | loss: 2.608446
iter: 11517 | loss: 2.608253
iter: 11518 | loss: 2.608060
iter: 11519 | loss: 2.607866
iter: 11520 | loss: 2.607673
iter: 11521 | loss: 2.607479
iter: 11522 | loss: 2.607286
iter: 11523 | loss: 2.607093
iter: 11524 | loss: 2.606899
iter: 11525 | loss: 2.606706
iter: 11526 | loss: 2.606512
iter: 11527 | loss: 2.606319
iter: 11528 | loss: 2.606126
iter: 11529 | loss: 2.605932
iter: 11530 | loss: 2.605739
iter: 11531 | loss: 2.605546
iter: 11532 | loss: 2.605352
iter: 11533 | loss: 2.605159
iter: 11534 | loss: 2.604965
iter: 11535 | loss: 2.604772
iter: 11536 | loss: 2.604579
iter: 11537 | loss: 2.604385
iter: 11538 | loss: 2.604192
iter: 11539 | loss: 2.603998
iter: 11540 | loss: 2.603805
iter: 11541 | loss: 2.603612
iter: 11542 | loss: 2.603418
iter: 11543 | loss: 2.603225
iter: 11544 | loss: 2.603031
iter: 11545 | loss: 2.602838
iter: 11546 | loss: 2.602645
iter: 11547 | loss: 2.602451
iter: 11548 | loss: 2.602258
iter: 11549 | loss: 2.602065
iter: 11550 | loss: 2.601871
iter: 11551 | loss: 2.601678
iter: 11552 | loss: 2.601484
iter: 11553 | loss: 2.601291
iter: 11554 | loss: 2.601098
iter: 11555 | loss: 2.600904
iter: 11556 | loss: 2.600711
iter: 11557 | loss: 2.600517
iter: 11558 | loss: 2.600324
iter: 11559 | loss: 2.600131
iter: 11560 | loss: 2.599937
iter: 11561 | loss: 2.599744
iter: 11562 | loss: 2.599551
iter: 11563 | loss: 2.599357
iter: 11564 | loss: 2.599164
iter: 11565 | loss: 2.598970
iter: 11566 | loss: 2.598777
iter: 11567 | loss: 2.598584
iter: 11568 | loss: 2.598390
iter: 11569 | loss: 2.598197
iter: 11570 | loss: 2.598003
iter: 11571 | loss: 2.597810
iter: 11572 | loss: 2.597617
iter: 11573 | loss: 2.597423
iter: 11574 | loss: 2.597230
iter: 11575 | loss: 2.597036
iter: 11576 | loss: 2.596843
iter: 11577 | loss: 2.596650
iter: 11578 | loss: 2.596456
iter: 11579 | loss: 2.596263
iter: 11580 | loss: 2.596070
iter: 11581 | loss: 2.595876
iter: 11582 | loss: 2.595683
iter: 11583 | loss: 2.595489
iter: 11584 | loss: 2.595296
iter: 11585 | loss: 2.595103
iter: 11586 | loss: 2.594909
iter: 11587 | loss: 2.594716
iter: 11588 | loss: 2.594522
iter: 11589 | loss: 2.594329
iter: 11590 | loss: 2.594136
iter: 11591 | loss: 2.593942
iter: 11592 | loss: 2.593749
iter: 11593 | loss: 2.593556
iter: 11594 | loss: 2.593362
iter: 11595 | loss: 2.593169
iter: 11596 | loss: 2.592975
iter: 11597 | loss: 2.592782
iter: 11598 | loss: 2.592589
iter: 11599 | loss: 2.592395
iter: 11600 | loss: 2.592202
iter: 11601 | loss: 2.592008
iter: 11602 | loss: 2.591815
iter: 11603 | loss: 2.591622
iter: 11604 | loss: 2.591428
iter: 11605 | loss: 2.591235
iter: 11606 | loss: 2.591041
iter: 11607 | loss: 2.590848
iter: 11608 | loss: 2.590655
iter: 11609 | loss: 2.590461
iter: 11610 | loss: 2.590268
iter: 11611 | loss: 2.590075
iter: 11612 | loss: 2.589881
iter: 11613 | loss: 2.589688
iter: 11614 | loss: 2.589494
iter: 11615 | loss: 2.589301
iter: 11616 | loss: 2.589108
iter: 11617 | loss: 2.588914
iter: 11618 | loss: 2.588721
iter: 11619 | loss: 2.588527
iter: 11620 | loss: 2.588334
iter: 11621 | loss: 2.588141
iter: 11622 | loss: 2.587947
iter: 11623 | loss: 2.587754
iter: 11624 | loss: 2.587561
iter: 11625 | loss: 2.587367
iter: 11626 | loss: 2.587174
iter: 11627 | loss: 2.586980
iter: 11628 | loss: 2.586787
iter: 11629 | loss: 2.586594
iter: 11630 | loss: 2.586400
iter: 11631 | loss: 2.586207
iter: 11632 | loss: 2.586013
iter: 11633 | loss: 2.585820
iter: 11634 | loss: 2.585627
iter: 11635 | loss: 2.585433
iter: 11636 | loss: 2.585240
iter: 11637 | loss: 2.585047
iter: 11638 | loss: 2.584853
iter: 11639 | loss: 2.584660
iter: 11640 | loss: 2.584466
iter: 11641 | loss: 2.584273
iter: 11642 | loss: 2.584080
iter: 11643 | loss: 2.583886
iter: 11644 | loss: 2.583693
iter: 11645 | loss: 2.583499
iter: 11646 | loss: 2.583306
iter: 11647 | loss: 2.583113
iter: 11648 | loss: 2.582919
iter: 11649 | loss: 2.582726
iter: 11650 | loss: 2.582532
iter: 11651 | loss: 2.582339
iter: 11652 | loss: 2.582146
iter: 11653 | loss: 2.581952
iter: 11654 | loss: 2.581759
iter: 11655 | loss: 2.581566
iter: 11656 | loss: 2.581372
iter: 11657 | loss: 2.581179
iter: 11658 | loss: 2.580985
iter: 11659 | loss: 2.580792
iter: 11660 | loss: 2.580599
iter: 11661 | loss: 2.580405
iter: 11662 | loss: 2.580212
iter: 11663 | loss: 2.580018
iter: 11664 | loss: 2.579825
iter: 11665 | loss: 2.579632
iter: 11666 | loss: 2.579438
iter: 11667 | loss: 2.579245
iter: 11668 | loss: 2.579052
iter: 11669 | loss: 2.578858
iter: 11670 | loss: 2.578665
iter: 11671 | loss: 2.578471
iter: 11672 | loss: 2.578278
iter: 11673 | loss: 2.578085
iter: 11674 | loss: 2.577891
iter: 11675 | loss: 2.577698
iter: 11676 | loss: 2.577504
iter: 11677 | loss: 2.577311
iter: 11678 | loss: 2.577118
iter: 11679 | loss: 2.576924
iter: 11680 | loss: 2.576731
iter: 11681 | loss: 2.576537
iter: 11682 | loss: 2.576344
iter: 11683 | loss: 2.576151
iter: 11684 | loss: 2.575957
iter: 11685 | loss: 2.575764
iter: 11686 | loss: 2.575571
iter: 11687 | loss: 2.575377
iter: 11688 | loss: 2.575184
iter: 11689 | loss: 2.574990
iter: 11690 | loss: 2.574797
iter: 11691 | loss: 2.574604
iter: 11692 | loss: 2.574410
iter: 11693 | loss: 2.574217
iter: 11694 | loss: 2.574023
iter: 11695 | loss: 2.573830
iter: 11696 | loss: 2.573637
iter: 11697 | loss: 2.573443
iter: 11698 | loss: 2.573250
iter: 11699 | loss: 2.573057
iter: 11700 | loss: 2.572863
iter: 11701 | loss: 2.572670
iter: 11702 | loss: 2.572476
iter: 11703 | loss: 2.572283
iter: 11704 | loss: 2.572090
iter: 11705 | loss: 2.571896
iter: 11706 | loss: 2.571703
iter: 11707 | loss: 2.571509
iter: 11708 | loss: 2.571316
iter: 11709 | loss: 2.571123
iter: 11710 | loss: 2.570929
iter: 11711 | loss: 2.570736
iter: 11712 | loss: 2.570542
iter: 11713 | loss: 2.570349
iter: 11714 | loss: 2.570156
iter: 11715 | loss: 2.569962
iter: 11716 | loss: 2.569769
iter: 11717 | loss: 2.569576
iter: 11718 | loss: 2.569382
iter: 11719 | loss: 2.569189
iter: 11720 | loss: 2.568995
iter: 11721 | loss: 2.568802
iter: 11722 | loss: 2.568609
iter: 11723 | loss: 2.568415
iter: 11724 | loss: 2.568222
iter: 11725 | loss: 2.568028
iter: 11726 | loss: 2.567835
iter: 11727 | loss: 2.567642
iter: 11728 | loss: 2.567448
iter: 11729 | loss: 2.567255
iter: 11730 | loss: 2.567062
iter: 11731 | loss: 2.566868
iter: 11732 | loss: 2.566675
iter: 11733 | loss: 2.566481
iter: 11734 | loss: 2.566288
iter: 11735 | loss: 2.566095
iter: 11736 | loss: 2.565901
iter: 11737 | loss: 2.565708
iter: 11738 | loss: 2.565514
iter: 11739 | loss: 2.565321
iter: 11740 | loss: 2.565128
iter: 11741 | loss: 2.564934
iter: 11742 | loss: 2.564741
iter: 11743 | loss: 2.564547
iter: 11744 | loss: 2.564354
iter: 11745 | loss: 2.564161
iter: 11746 | loss: 2.563967
iter: 11747 | loss: 2.563774
iter: 11748 | loss: 2.563581
iter: 11749 | loss: 2.563387
iter: 11750 | loss: 2.563194
iter: 11751 | loss: 2.563000
iter: 11752 | loss: 2.562807
iter: 11753 | loss: 2.562614
iter: 11754 | loss: 2.562420
iter: 11755 | loss: 2.562227
iter: 11756 | loss: 2.562033
iter: 11757 | loss: 2.561840
iter: 11758 | loss: 2.561647
iter: 11759 | loss: 2.561453
iter: 11760 | loss: 2.561260
iter: 11761 | loss: 2.561067
iter: 11762 | loss: 2.560873
iter: 11763 | loss: 2.560680
iter: 11764 | loss: 2.560486
iter: 11765 | loss: 2.560293
iter: 11766 | loss: 2.560100
iter: 11767 | loss: 2.559906
iter: 11768 | loss: 2.559713
iter: 11769 | loss: 2.559519
iter: 11770 | loss: 2.559326
iter: 11771 | loss: 2.559133
iter: 11772 | loss: 2.558939
iter: 11773 | loss: 2.558746
iter: 11774 | loss: 2.558552
iter: 11775 | loss: 2.558359
iter: 11776 | loss: 2.558166
iter: 11777 | loss: 2.557972
iter: 11778 | loss: 2.557779
iter: 11779 | loss: 2.557586
iter: 11780 | loss: 2.557392
iter: 11781 | loss: 2.557199
iter: 11782 | loss: 2.557005
iter: 11783 | loss: 2.556812
iter: 11784 | loss: 2.556619
iter: 11785 | loss: 2.556425
iter: 11786 | loss: 2.556232
iter: 11787 | loss: 2.556038
iter: 11788 | loss: 2.555845
iter: 11789 | loss: 2.555652
iter: 11790 | loss: 2.555458
iter: 11791 | loss: 2.555265
iter: 11792 | loss: 2.555072
iter: 11793 | loss: 2.554878
iter: 11794 | loss: 2.554685
iter: 11795 | loss: 2.554491
iter: 11796 | loss: 2.554298
iter: 11797 | loss: 2.554105
iter: 11798 | loss: 2.553911
iter: 11799 | loss: 2.553718
iter: 11800 | loss: 2.553524
iter: 11801 | loss: 2.553331
iter: 11802 | loss: 2.553138
iter: 11803 | loss: 2.552944
iter: 11804 | loss: 2.552751
iter: 11805 | loss: 2.552557
iter: 11806 | loss: 2.552364
iter: 11807 | loss: 2.552171
iter: 11808 | loss: 2.551977
iter: 11809 | loss: 2.551784
iter: 11810 | loss: 2.551591
iter: 11811 | loss: 2.551397
iter: 11812 | loss: 2.551204
iter: 11813 | loss: 2.551010
iter: 11814 | loss: 2.550817
iter: 11815 | loss: 2.550624
iter: 11816 | loss: 2.550430
iter: 11817 | loss: 2.550237
iter: 11818 | loss: 2.550043
iter: 11819 | loss: 2.549850
iter: 11820 | loss: 2.549657
iter: 11821 | loss: 2.549463
iter: 11822 | loss: 2.549270
iter: 11823 | loss: 2.549077
iter: 11824 | loss: 2.548883
iter: 11825 | loss: 2.548690
iter: 11826 | loss: 2.548496
iter: 11827 | loss: 2.548303
iter: 11828 | loss: 2.548110
iter: 11829 | loss: 2.547916
iter: 11830 | loss: 2.547723
iter: 11831 | loss: 2.547529
iter: 11832 | loss: 2.547336
iter: 11833 | loss: 2.547143
iter: 11834 | loss: 2.546949
iter: 11835 | loss: 2.546756
iter: 11836 | loss: 2.546562
iter: 11837 | loss: 2.546369
iter: 11838 | loss: 2.546176
iter: 11839 | loss: 2.545982
iter: 11840 | loss: 2.545789
iter: 11841 | loss: 2.545596
iter: 11842 | loss: 2.545402
iter: 11843 | loss: 2.545209
iter: 11844 | loss: 2.545015
iter: 11845 | loss: 2.544822
iter: 11846 | loss: 2.544629
iter: 11847 | loss: 2.544435
iter: 11848 | loss: 2.544242
iter: 11849 | loss: 2.544048
iter: 11850 | loss: 2.543855
iter: 11851 | loss: 2.543662
iter: 11852 | loss: 2.543468
iter: 11853 | loss: 2.543275
iter: 11854 | loss: 2.543082
iter: 11855 | loss: 2.542888
iter: 11856 | loss: 2.542695
iter: 11857 | loss: 2.542501
iter: 11858 | loss: 2.542308
iter: 11859 | loss: 2.542115
iter: 11860 | loss: 2.541921
iter: 11861 | loss: 2.541728
iter: 11862 | loss: 2.541534
iter: 11863 | loss: 2.541341
iter: 11864 | loss: 2.541148
iter: 11865 | loss: 2.540954
iter: 11866 | loss: 2.540761
iter: 11867 | loss: 2.540567
iter: 11868 | loss: 2.540374
iter: 11869 | loss: 2.540181
iter: 11870 | loss: 2.539987
iter: 11871 | loss: 2.539794
iter: 11872 | loss: 2.539601
iter: 11873 | loss: 2.539407
iter: 11874 | loss: 2.539214
iter: 11875 | loss: 2.539020
iter: 11876 | loss: 2.538827
iter: 11877 | loss: 2.538634
iter: 11878 | loss: 2.538440
iter: 11879 | loss: 2.538247
iter: 11880 | loss: 2.538053
iter: 11881 | loss: 2.537860
iter: 11882 | loss: 2.537667
iter: 11883 | loss: 2.537473
iter: 11884 | loss: 2.537280
iter: 11885 | loss: 2.537087
iter: 11886 | loss: 2.536893
iter: 11887 | loss: 2.536700
iter: 11888 | loss: 2.536506
iter: 11889 | loss: 2.536313
iter: 11890 | loss: 2.536120
iter: 11891 | loss: 2.535926
iter: 11892 | loss: 2.535733
iter: 11893 | loss: 2.535539
iter: 11894 | loss: 2.535346
iter: 11895 | loss: 2.535153
iter: 11896 | loss: 2.534959
iter: 11897 | loss: 2.534766
iter: 11898 | loss: 2.534572
iter: 11899 | loss: 2.534379
iter: 11900 | loss: 2.534186
iter: 11901 | loss: 2.533992
iter: 11902 | loss: 2.533799
iter: 11903 | loss: 2.533606
iter: 11904 | loss: 2.533412
iter: 11905 | loss: 2.533219
iter: 11906 | loss: 2.533025
iter: 11907 | loss: 2.532832
iter: 11908 | loss: 2.532639
iter: 11909 | loss: 2.532445
iter: 11910 | loss: 2.532252
iter: 11911 | loss: 2.532058
iter: 11912 | loss: 2.531865
iter: 11913 | loss: 2.531672
iter: 11914 | loss: 2.531478
iter: 11915 | loss: 2.531285
iter: 11916 | loss: 2.531092
iter: 11917 | loss: 2.530898
iter: 11918 | loss: 2.530705
iter: 11919 | loss: 2.530511
iter: 11920 | loss: 2.530318
iter: 11921 | loss: 2.530125
iter: 11922 | loss: 2.529931
iter: 11923 | loss: 2.529738
iter: 11924 | loss: 2.529544
iter: 11925 | loss: 2.529351
iter: 11926 | loss: 2.529158
iter: 11927 | loss: 2.528964
iter: 11928 | loss: 2.528771
iter: 11929 | loss: 2.528577
iter: 11930 | loss: 2.528384
iter: 11931 | loss: 2.528191
iter: 11932 | loss: 2.527997
iter: 11933 | loss: 2.527804
iter: 11934 | loss: 2.527611
iter: 11935 | loss: 2.527417
iter: 11936 | loss: 2.527224
iter: 11937 | loss: 2.527030
iter: 11938 | loss: 2.526837
iter: 11939 | loss: 2.526644
iter: 11940 | loss: 2.526450
iter: 11941 | loss: 2.526257
iter: 11942 | loss: 2.526063
iter: 11943 | loss: 2.525870
iter: 11944 | loss: 2.525677
iter: 11945 | loss: 2.525483
iter: 11946 | loss: 2.525290
iter: 11947 | loss: 2.525097
iter: 11948 | loss: 2.524903
iter: 11949 | loss: 2.524710
iter: 11950 | loss: 2.524516
iter: 11951 | loss: 2.524323
iter: 11952 | loss: 2.524130
iter: 11953 | loss: 2.523936
iter: 11954 | loss: 2.523743
iter: 11955 | loss: 2.523549
iter: 11956 | loss: 2.523356
iter: 11957 | loss: 2.523163
iter: 11958 | loss: 2.522969
iter: 11959 | loss: 2.522776
iter: 11960 | loss: 2.522583
iter: 11961 | loss: 2.522389
iter: 11962 | loss: 2.522196
iter: 11963 | loss: 2.522002
iter: 11964 | loss: 2.521809
iter: 11965 | loss: 2.521616
iter: 11966 | loss: 2.521422
iter: 11967 | loss: 2.521229
iter: 11968 | loss: 2.521035
iter: 11969 | loss: 2.520842
iter: 11970 | loss: 2.520649
iter: 11971 | loss: 2.520455
iter: 11972 | loss: 2.520262
iter: 11973 | loss: 2.520068
iter: 11974 | loss: 2.519875
iter: 11975 | loss: 2.519682
iter: 11976 | loss: 2.519488
iter: 11977 | loss: 2.519295
iter: 11978 | loss: 2.519102
iter: 11979 | loss: 2.518908
iter: 11980 | loss: 2.518715
iter: 11981 | loss: 2.518521
iter: 11982 | loss: 2.518328
iter: 11983 | loss: 2.518135
iter: 11984 | loss: 2.517941
iter: 11985 | loss: 2.517748
iter: 11986 | loss: 2.517554
iter: 11987 | loss: 2.517361
iter: 11988 | loss: 2.517168
iter: 11989 | loss: 2.516974
iter: 11990 | loss: 2.516781
iter: 11991 | loss: 2.516588
iter: 11992 | loss: 2.516394
iter: 11993 | loss: 2.516201
iter: 11994 | loss: 2.516007
iter: 11995 | loss: 2.515814
iter: 11996 | loss: 2.515621
iter: 11997 | loss: 2.515427
iter: 11998 | loss: 2.515234
iter: 11999 | loss: 2.515040
iter: 12000 | loss: 2.514847
iter: 12001 | loss: 2.514654
iter: 12002 | loss: 2.514460
iter: 12003 | loss: 2.514267
iter: 12004 | loss: 2.514073
iter: 12005 | loss: 2.513880
iter: 12006 | loss: 2.513687
iter: 12007 | loss: 2.513493
iter: 12008 | loss: 2.513300
iter: 12009 | loss: 2.513107
iter: 12010 | loss: 2.512913
iter: 12011 | loss: 2.512720
iter: 12012 | loss: 2.512526
iter: 12013 | loss: 2.512333
iter: 12014 | loss: 2.512140
iter: 12015 | loss: 2.511946
iter: 12016 | loss: 2.511753
iter: 12017 | loss: 2.511559
iter: 12018 | loss: 2.511366
iter: 12019 | loss: 2.511173
iter: 12020 | loss: 2.510979
iter: 12021 | loss: 2.510786
iter: 12022 | loss: 2.510593
iter: 12023 | loss: 2.510399
iter: 12024 | loss: 2.510206
iter: 12025 | loss: 2.510012
iter: 12026 | loss: 2.509819
iter: 12027 | loss: 2.509626
iter: 12028 | loss: 2.509432
iter: 12029 | loss: 2.509239
iter: 12030 | loss: 2.509045
iter: 12031 | loss: 2.508852
iter: 12032 | loss: 2.508659
iter: 12033 | loss: 2.508465
iter: 12034 | loss: 2.508272
iter: 12035 | loss: 2.508078
iter: 12036 | loss: 2.507885
iter: 12037 | loss: 2.507692
iter: 12038 | loss: 2.507498
iter: 12039 | loss: 2.507305
iter: 12040 | loss: 2.507112
iter: 12041 | loss: 2.506918
iter: 12042 | loss: 2.506725
iter: 12043 | loss: 2.506531
iter: 12044 | loss: 2.506338
iter: 12045 | loss: 2.506145
iter: 12046 | loss: 2.505951
iter: 12047 | loss: 2.505758
iter: 12048 | loss: 2.505564
iter: 12049 | loss: 2.505371
iter: 12050 | loss: 2.505178
iter: 12051 | loss: 2.504984
iter: 12052 | loss: 2.504791
iter: 12053 | loss: 2.504598
iter: 12054 | loss: 2.504404
iter: 12055 | loss: 2.504211
iter: 12056 | loss: 2.504017
iter: 12057 | loss: 2.503824
iter: 12058 | loss: 2.503631
iter: 12059 | loss: 2.503437
iter: 12060 | loss: 2.503244
iter: 12061 | loss: 2.503050
iter: 12062 | loss: 2.502857
iter: 12063 | loss: 2.502664
iter: 12064 | loss: 2.502470
iter: 12065 | loss: 2.502277
iter: 12066 | loss: 2.502083
iter: 12067 | loss: 2.501890
iter: 12068 | loss: 2.501697
iter: 12069 | loss: 2.501503
iter: 12070 | loss: 2.501310
iter: 12071 | loss: 2.501117
iter: 12072 | loss: 2.500923
iter: 12073 | loss: 2.500730
iter: 12074 | loss: 2.500536
iter: 12075 | loss: 2.500343
iter: 12076 | loss: 2.500150
iter: 12077 | loss: 2.499956
iter: 12078 | loss: 2.499763
iter: 12079 | loss: 2.499569
iter: 12080 | loss: 2.499376
iter: 12081 | loss: 2.499183
iter: 12082 | loss: 2.498989
iter: 12083 | loss: 2.498796
iter: 12084 | loss: 2.498603
iter: 12085 | loss: 2.498409
iter: 12086 | loss: 2.498216
iter: 12087 | loss: 2.498022
iter: 12088 | loss: 2.497829
iter: 12089 | loss: 2.497636
iter: 12090 | loss: 2.497442
iter: 12091 | loss: 2.497249
iter: 12092 | loss: 2.497055
iter: 12093 | loss: 2.496862
iter: 12094 | loss: 2.496669
iter: 12095 | loss: 2.496475
iter: 12096 | loss: 2.496282
iter: 12097 | loss: 2.496088
iter: 12098 | loss: 2.495895
iter: 12099 | loss: 2.495702
iter: 12100 | loss: 2.495508
iter: 12101 | loss: 2.495315
iter: 12102 | loss: 2.495122
iter: 12103 | loss: 2.494928
iter: 12104 | loss: 2.494735
iter: 12105 | loss: 2.494541
iter: 12106 | loss: 2.494348
iter: 12107 | loss: 2.494155
iter: 12108 | loss: 2.493961
iter: 12109 | loss: 2.493768
iter: 12110 | loss: 2.493574
iter: 12111 | loss: 2.493381
iter: 12112 | loss: 2.493188
iter: 12113 | loss: 2.492994
iter: 12114 | loss: 2.492801
iter: 12115 | loss: 2.492608
iter: 12116 | loss: 2.492414
iter: 12117 | loss: 2.492221
iter: 12118 | loss: 2.492027
iter: 12119 | loss: 2.491834
iter: 12120 | loss: 2.491641
iter: 12121 | loss: 2.491447
iter: 12122 | loss: 2.491254
iter: 12123 | loss: 2.491060
iter: 12124 | loss: 2.490867
iter: 12125 | loss: 2.490674
iter: 12126 | loss: 2.490480
iter: 12127 | loss: 2.490287
iter: 12128 | loss: 2.490093
iter: 12129 | loss: 2.489900
iter: 12130 | loss: 2.489707
iter: 12131 | loss: 2.489513
iter: 12132 | loss: 2.489320
iter: 12133 | loss: 2.489127
iter: 12134 | loss: 2.488933
iter: 12135 | loss: 2.488740
iter: 12136 | loss: 2.488546
iter: 12137 | loss: 2.488353
iter: 12138 | loss: 2.488160
iter: 12139 | loss: 2.487966
iter: 12140 | loss: 2.487773
iter: 12141 | loss: 2.487579
iter: 12142 | loss: 2.487386
iter: 12143 | loss: 2.487193
iter: 12144 | loss: 2.486999
iter: 12145 | loss: 2.486806
iter: 12146 | loss: 2.486613
iter: 12147 | loss: 2.486419
iter: 12148 | loss: 2.486226
iter: 12149 | loss: 2.486032
iter: 12150 | loss: 2.485839
iter: 12151 | loss: 2.485646
iter: 12152 | loss: 2.485452
iter: 12153 | loss: 2.485259
iter: 12154 | loss: 2.485065
iter: 12155 | loss: 2.484872
iter: 12156 | loss: 2.484679
iter: 12157 | loss: 2.484485
iter: 12158 | loss: 2.484292
iter: 12159 | loss: 2.484098
iter: 12160 | loss: 2.483905
iter: 12161 | loss: 2.483712
iter: 12162 | loss: 2.483518
iter: 12163 | loss: 2.483325
iter: 12164 | loss: 2.483132
iter: 12165 | loss: 2.482938
iter: 12166 | loss: 2.482745
iter: 12167 | loss: 2.482551
iter: 12168 | loss: 2.482358
iter: 12169 | loss: 2.482165
iter: 12170 | loss: 2.481971
iter: 12171 | loss: 2.481778
iter: 12172 | loss: 2.481584
iter: 12173 | loss: 2.481391
iter: 12174 | loss: 2.481198
iter: 12175 | loss: 2.481004
iter: 12176 | loss: 2.480811
iter: 12177 | loss: 2.480618
iter: 12178 | loss: 2.480424
iter: 12179 | loss: 2.480231
iter: 12180 | loss: 2.480037
iter: 12181 | loss: 2.479844
iter: 12182 | loss: 2.479651
iter: 12183 | loss: 2.479457
iter: 12184 | loss: 2.479264
iter: 12185 | loss: 2.479070
iter: 12186 | loss: 2.478877
iter: 12187 | loss: 2.478684
iter: 12188 | loss: 2.478490
iter: 12189 | loss: 2.478297
iter: 12190 | loss: 2.478103
iter: 12191 | loss: 2.477910
iter: 12192 | loss: 2.477717
iter: 12193 | loss: 2.477523
iter: 12194 | loss: 2.477330
iter: 12195 | loss: 2.477137
iter: 12196 | loss: 2.476943
iter: 12197 | loss: 2.476750
iter: 12198 | loss: 2.476556
iter: 12199 | loss: 2.476363
iter: 12200 | loss: 2.476170
iter: 12201 | loss: 2.475976
iter: 12202 | loss: 2.475783
iter: 12203 | loss: 2.475589
iter: 12204 | loss: 2.475396
iter: 12205 | loss: 2.475203
iter: 12206 | loss: 2.475009
iter: 12207 | loss: 2.474816
iter: 12208 | loss: 2.474623
iter: 12209 | loss: 2.474429
iter: 12210 | loss: 2.474236
iter: 12211 | loss: 2.474042
iter: 12212 | loss: 2.473849
iter: 12213 | loss: 2.473656
iter: 12214 | loss: 2.473462
iter: 12215 | loss: 2.473269
iter: 12216 | loss: 2.473075
iter: 12217 | loss: 2.472882
iter: 12218 | loss: 2.472689
iter: 12219 | loss: 2.472495
iter: 12220 | loss: 2.472302
iter: 12221 | loss: 2.472108
iter: 12222 | loss: 2.471915
iter: 12223 | loss: 2.471722
iter: 12224 | loss: 2.471528
iter: 12225 | loss: 2.471335
iter: 12226 | loss: 2.471142
iter: 12227 | loss: 2.470948
iter: 12228 | loss: 2.470755
iter: 12229 | loss: 2.470561
iter: 12230 | loss: 2.470368
iter: 12231 | loss: 2.470175
iter: 12232 | loss: 2.469981
iter: 12233 | loss: 2.469788
iter: 12234 | loss: 2.469594
iter: 12235 | loss: 2.469401
iter: 12236 | loss: 2.469208
iter: 12237 | loss: 2.469014
iter: 12238 | loss: 2.468821
iter: 12239 | loss: 2.468628
iter: 12240 | loss: 2.468434
iter: 12241 | loss: 2.468241
iter: 12242 | loss: 2.468047
iter: 12243 | loss: 2.467854
iter: 12244 | loss: 2.467661
iter: 12245 | loss: 2.467467
iter: 12246 | loss: 2.467274
iter: 12247 | loss: 2.467080
iter: 12248 | loss: 2.466887
iter: 12249 | loss: 2.466694
iter: 12250 | loss: 2.466500
iter: 12251 | loss: 2.466307
iter: 12252 | loss: 2.466113
iter: 12253 | loss: 2.465920
iter: 12254 | loss: 2.465727
iter: 12255 | loss: 2.465533
iter: 12256 | loss: 2.465340
iter: 12257 | loss: 2.465147
iter: 12258 | loss: 2.464953
iter: 12259 | loss: 2.464760
iter: 12260 | loss: 2.464566
iter: 12261 | loss: 2.464373
iter: 12262 | loss: 2.464180
iter: 12263 | loss: 2.463986
iter: 12264 | loss: 2.463793
iter: 12265 | loss: 2.463599
iter: 12266 | loss: 2.463406
iter: 12267 | loss: 2.463213
iter: 12268 | loss: 2.463019
iter: 12269 | loss: 2.462826
iter: 12270 | loss: 2.462633
iter: 12271 | loss: 2.462439
iter: 12272 | loss: 2.462246
iter: 12273 | loss: 2.462052
iter: 12274 | loss: 2.461859
iter: 12275 | loss: 2.461666
iter: 12276 | loss: 2.461472
iter: 12277 | loss: 2.461279
iter: 12278 | loss: 2.461085
iter: 12279 | loss: 2.460892
iter: 12280 | loss: 2.460699
iter: 12281 | loss: 2.460505
iter: 12282 | loss: 2.460312
iter: 12283 | loss: 2.460119
iter: 12284 | loss: 2.459925
iter: 12285 | loss: 2.459732
iter: 12286 | loss: 2.459538
iter: 12287 | loss: 2.459345
iter: 12288 | loss: 2.459152
iter: 12289 | loss: 2.458958
iter: 12290 | loss: 2.458765
iter: 12291 | loss: 2.458571
iter: 12292 | loss: 2.458378
iter: 12293 | loss: 2.458185
iter: 12294 | loss: 2.457991
iter: 12295 | loss: 2.457798
iter: 12296 | loss: 2.457604
iter: 12297 | loss: 2.457411
iter: 12298 | loss: 2.457218
iter: 12299 | loss: 2.457024
iter: 12300 | loss: 2.456831
iter: 12301 | loss: 2.456638
iter: 12302 | loss: 2.456444
iter: 12303 | loss: 2.456251
iter: 12304 | loss: 2.456057
iter: 12305 | loss: 2.455864
iter: 12306 | loss: 2.455671
iter: 12307 | loss: 2.455477
iter: 12308 | loss: 2.455284
iter: 12309 | loss: 2.455090
iter: 12310 | loss: 2.454897
iter: 12311 | loss: 2.454704
iter: 12312 | loss: 2.454510
iter: 12313 | loss: 2.454317
iter: 12314 | loss: 2.454124
iter: 12315 | loss: 2.453930
iter: 12316 | loss: 2.453737
iter: 12317 | loss: 2.453543
iter: 12318 | loss: 2.453350
iter: 12319 | loss: 2.453157
iter: 12320 | loss: 2.452963
iter: 12321 | loss: 2.452770
iter: 12322 | loss: 2.452576
iter: 12323 | loss: 2.452383
iter: 12324 | loss: 2.452190
iter: 12325 | loss: 2.451996
iter: 12326 | loss: 2.451803
iter: 12327 | loss: 2.451609
iter: 12328 | loss: 2.451416
iter: 12329 | loss: 2.451223
iter: 12330 | loss: 2.451029
iter: 12331 | loss: 2.450836
iter: 12332 | loss: 2.450643
iter: 12333 | loss: 2.450449
iter: 12334 | loss: 2.450256
iter: 12335 | loss: 2.450062
iter: 12336 | loss: 2.449869
iter: 12337 | loss: 2.449676
iter: 12338 | loss: 2.449482
iter: 12339 | loss: 2.449289
iter: 12340 | loss: 2.449095
iter: 12341 | loss: 2.448902
iter: 12342 | loss: 2.448709
iter: 12343 | loss: 2.448515
iter: 12344 | loss: 2.448322
iter: 12345 | loss: 2.448129
iter: 12346 | loss: 2.447935
iter: 12347 | loss: 2.447742
iter: 12348 | loss: 2.447548
iter: 12349 | loss: 2.447355
iter: 12350 | loss: 2.447162
iter: 12351 | loss: 2.446968
iter: 12352 | loss: 2.446775
iter: 12353 | loss: 2.446581
iter: 12354 | loss: 2.446388
iter: 12355 | loss: 2.446195
iter: 12356 | loss: 2.446001
iter: 12357 | loss: 2.445808
iter: 12358 | loss: 2.445614
iter: 12359 | loss: 2.445421
iter: 12360 | loss: 2.445228
iter: 12361 | loss: 2.445034
iter: 12362 | loss: 2.444841
iter: 12363 | loss: 2.444648
iter: 12364 | loss: 2.444454
iter: 12365 | loss: 2.444261
iter: 12366 | loss: 2.444067
iter: 12367 | loss: 2.443874
iter: 12368 | loss: 2.443681
iter: 12369 | loss: 2.443487
iter: 12370 | loss: 2.443294
iter: 12371 | loss: 2.443100
iter: 12372 | loss: 2.442907
iter: 12373 | loss: 2.442714
iter: 12374 | loss: 2.442520
iter: 12375 | loss: 2.442327
iter: 12376 | loss: 2.442134
iter: 12377 | loss: 2.441940
iter: 12378 | loss: 2.441747
iter: 12379 | loss: 2.441553
iter: 12380 | loss: 2.441360
iter: 12381 | loss: 2.441167
iter: 12382 | loss: 2.440973
iter: 12383 | loss: 2.440780
iter: 12384 | loss: 2.440586
iter: 12385 | loss: 2.440393
iter: 12386 | loss: 2.440200
iter: 12387 | loss: 2.440006
iter: 12388 | loss: 2.439813
iter: 12389 | loss: 2.439619
iter: 12390 | loss: 2.439426
iter: 12391 | loss: 2.439233
iter: 12392 | loss: 2.439039
iter: 12393 | loss: 2.438846
iter: 12394 | loss: 2.438653
iter: 12395 | loss: 2.438459
iter: 12396 | loss: 2.438266
iter: 12397 | loss: 2.438072
iter: 12398 | loss: 2.437879
iter: 12399 | loss: 2.437686
iter: 12400 | loss: 2.437492
iter: 12401 | loss: 2.437299
iter: 12402 | loss: 2.437105
iter: 12403 | loss: 2.436912
iter: 12404 | loss: 2.436719
iter: 12405 | loss: 2.436525
iter: 12406 | loss: 2.436332
iter: 12407 | loss: 2.436139
iter: 12408 | loss: 2.435945
iter: 12409 | loss: 2.435752
iter: 12410 | loss: 2.435558
iter: 12411 | loss: 2.435365
iter: 12412 | loss: 2.435172
iter: 12413 | loss: 2.434978
iter: 12414 | loss: 2.434785
iter: 12415 | loss: 2.434591
iter: 12416 | loss: 2.434398
iter: 12417 | loss: 2.434205
iter: 12418 | loss: 2.434011
iter: 12419 | loss: 2.433818
iter: 12420 | loss: 2.433624
iter: 12421 | loss: 2.433431
iter: 12422 | loss: 2.433238
iter: 12423 | loss: 2.433044
iter: 12424 | loss: 2.432851
iter: 12425 | loss: 2.432658
iter: 12426 | loss: 2.432464
iter: 12427 | loss: 2.432271
iter: 12428 | loss: 2.432077
iter: 12429 | loss: 2.431884
iter: 12430 | loss: 2.431691
iter: 12431 | loss: 2.431497
iter: 12432 | loss: 2.431304
iter: 12433 | loss: 2.431110
iter: 12434 | loss: 2.430917
iter: 12435 | loss: 2.430724
iter: 12436 | loss: 2.430530
iter: 12437 | loss: 2.430337
iter: 12438 | loss: 2.430144
iter: 12439 | loss: 2.429950
iter: 12440 | loss: 2.429757
iter: 12441 | loss: 2.429563
iter: 12442 | loss: 2.429370
iter: 12443 | loss: 2.429177
iter: 12444 | loss: 2.428983
iter: 12445 | loss: 2.428790
iter: 12446 | loss: 2.428596
iter: 12447 | loss: 2.428403
iter: 12448 | loss: 2.428210
iter: 12449 | loss: 2.428016
iter: 12450 | loss: 2.427823
iter: 12451 | loss: 2.427629
iter: 12452 | loss: 2.427436
iter: 12453 | loss: 2.427243
iter: 12454 | loss: 2.427049
iter: 12455 | loss: 2.426856
iter: 12456 | loss: 2.426663
iter: 12457 | loss: 2.426469
iter: 12458 | loss: 2.426276
iter: 12459 | loss: 2.426082
iter: 12460 | loss: 2.425889
iter: 12461 | loss: 2.425696
iter: 12462 | loss: 2.425502
iter: 12463 | loss: 2.425309
iter: 12464 | loss: 2.425115
iter: 12465 | loss: 2.424922
iter: 12466 | loss: 2.424729
iter: 12467 | loss: 2.424535
iter: 12468 | loss: 2.424342
iter: 12469 | loss: 2.424149
iter: 12470 | loss: 2.423955
iter: 12471 | loss: 2.423762
iter: 12472 | loss: 2.423568
iter: 12473 | loss: 2.423375
iter: 12474 | loss: 2.423182
iter: 12475 | loss: 2.422988
iter: 12476 | loss: 2.422795
iter: 12477 | loss: 2.422601
iter: 12478 | loss: 2.422408
iter: 12479 | loss: 2.422215
iter: 12480 | loss: 2.422021
iter: 12481 | loss: 2.421828
iter: 12482 | loss: 2.421634
iter: 12483 | loss: 2.421441
iter: 12484 | loss: 2.421248
iter: 12485 | loss: 2.421054
iter: 12486 | loss: 2.420861
iter: 12487 | loss: 2.420668
iter: 12488 | loss: 2.420474
iter: 12489 | loss: 2.420281
iter: 12490 | loss: 2.420087
iter: 12491 | loss: 2.419894
iter: 12492 | loss: 2.419701
iter: 12493 | loss: 2.419507
iter: 12494 | loss: 2.419314
iter: 12495 | loss: 2.419120
iter: 12496 | loss: 2.418927
iter: 12497 | loss: 2.418734
iter: 12498 | loss: 2.418540
iter: 12499 | loss: 2.418347
iter: 12500 | loss: 2.418154
iter: 12501 | loss: 2.417960
iter: 12502 | loss: 2.417767
iter: 12503 | loss: 2.417573
iter: 12504 | loss: 2.417380
iter: 12505 | loss: 2.417187
iter: 12506 | loss: 2.416993
iter: 12507 | loss: 2.416800
iter: 12508 | loss: 2.416606
iter: 12509 | loss: 2.416413
iter: 12510 | loss: 2.416220
iter: 12511 | loss: 2.416026
iter: 12512 | loss: 2.415833
iter: 12513 | loss: 2.415639
iter: 12514 | loss: 2.415446
iter: 12515 | loss: 2.415253
iter: 12516 | loss: 2.415059
iter: 12517 | loss: 2.414866
iter: 12518 | loss: 2.414673
iter: 12519 | loss: 2.414479
iter: 12520 | loss: 2.414286
iter: 12521 | loss: 2.414092
iter: 12522 | loss: 2.413899
iter: 12523 | loss: 2.413706
iter: 12524 | loss: 2.413512
iter: 12525 | loss: 2.413319
iter: 12526 | loss: 2.413125
iter: 12527 | loss: 2.412932
iter: 12528 | loss: 2.412739
iter: 12529 | loss: 2.412545
iter: 12530 | loss: 2.412352
iter: 12531 | loss: 2.412159
iter: 12532 | loss: 2.411965
iter: 12533 | loss: 2.411772
iter: 12534 | loss: 2.411578
iter: 12535 | loss: 2.411385
iter: 12536 | loss: 2.411192
iter: 12537 | loss: 2.410998
iter: 12538 | loss: 2.410805
iter: 12539 | loss: 2.410611
iter: 12540 | loss: 2.410418
iter: 12541 | loss: 2.410225
iter: 12542 | loss: 2.410031
iter: 12543 | loss: 2.409838
iter: 12544 | loss: 2.409644
iter: 12545 | loss: 2.409451
iter: 12546 | loss: 2.409258
iter: 12547 | loss: 2.409064
iter: 12548 | loss: 2.408871
iter: 12549 | loss: 2.408678
iter: 12550 | loss: 2.408484
iter: 12551 | loss: 2.408291
iter: 12552 | loss: 2.408097
iter: 12553 | loss: 2.407904
iter: 12554 | loss: 2.407711
iter: 12555 | loss: 2.407517
iter: 12556 | loss: 2.407324
iter: 12557 | loss: 2.407130
iter: 12558 | loss: 2.406937
iter: 12559 | loss: 2.406744
iter: 12560 | loss: 2.406550
iter: 12561 | loss: 2.406357
iter: 12562 | loss: 2.406164
iter: 12563 | loss: 2.405970
iter: 12564 | loss: 2.405777
iter: 12565 | loss: 2.405583
iter: 12566 | loss: 2.405390
iter: 12567 | loss: 2.405197
iter: 12568 | loss: 2.405003
iter: 12569 | loss: 2.404810
iter: 12570 | loss: 2.404616
iter: 12571 | loss: 2.404423
iter: 12572 | loss: 2.404230
iter: 12573 | loss: 2.404036
iter: 12574 | loss: 2.403843
iter: 12575 | loss: 2.403649
iter: 12576 | loss: 2.403456
iter: 12577 | loss: 2.403263
iter: 12578 | loss: 2.403069
iter: 12579 | loss: 2.402876
iter: 12580 | loss: 2.402683
iter: 12581 | loss: 2.402489
iter: 12582 | loss: 2.402296
iter: 12583 | loss: 2.402102
iter: 12584 | loss: 2.401909
iter: 12585 | loss: 2.401716
iter: 12586 | loss: 2.401522
iter: 12587 | loss: 2.401329
iter: 12588 | loss: 2.401135
iter: 12589 | loss: 2.400942
iter: 12590 | loss: 2.400749
iter: 12591 | loss: 2.400555
iter: 12592 | loss: 2.400362
iter: 12593 | loss: 2.400169
iter: 12594 | loss: 2.399975
iter: 12595 | loss: 2.399782
iter: 12596 | loss: 2.399588
iter: 12597 | loss: 2.399395
iter: 12598 | loss: 2.399202
iter: 12599 | loss: 2.399008
iter: 12600 | loss: 2.398815
iter: 12601 | loss: 2.398621
iter: 12602 | loss: 2.398428
iter: 12603 | loss: 2.398235
iter: 12604 | loss: 2.398041
iter: 12605 | loss: 2.397848
iter: 12606 | loss: 2.397655
iter: 12607 | loss: 2.397461
iter: 12608 | loss: 2.397268
iter: 12609 | loss: 2.397074
iter: 12610 | loss: 2.396881
iter: 12611 | loss: 2.396688
iter: 12612 | loss: 2.396494
iter: 12613 | loss: 2.396301
iter: 12614 | loss: 2.396107
iter: 12615 | loss: 2.395914
iter: 12616 | loss: 2.395721
iter: 12617 | loss: 2.395527
iter: 12618 | loss: 2.395334
iter: 12619 | loss: 2.395140
iter: 12620 | loss: 2.394947
iter: 12621 | loss: 2.394754
iter: 12622 | loss: 2.394560
iter: 12623 | loss: 2.394367
iter: 12624 | loss: 2.394174
iter: 12625 | loss: 2.393980
iter: 12626 | loss: 2.393787
iter: 12627 | loss: 2.393593
iter: 12628 | loss: 2.393400
iter: 12629 | loss: 2.393207
iter: 12630 | loss: 2.393013
iter: 12631 | loss: 2.392820
iter: 12632 | loss: 2.392626
iter: 12633 | loss: 2.392433
iter: 12634 | loss: 2.392240
iter: 12635 | loss: 2.392046
iter: 12636 | loss: 2.391853
iter: 12637 | loss: 2.391660
iter: 12638 | loss: 2.391466
iter: 12639 | loss: 2.391273
iter: 12640 | loss: 2.391079
iter: 12641 | loss: 2.390886
iter: 12642 | loss: 2.390693
iter: 12643 | loss: 2.390499
iter: 12644 | loss: 2.390306
iter: 12645 | loss: 2.390112
iter: 12646 | loss: 2.389919
iter: 12647 | loss: 2.389726
iter: 12648 | loss: 2.389532
iter: 12649 | loss: 2.389339
iter: 12650 | loss: 2.389145
iter: 12651 | loss: 2.388952
iter: 12652 | loss: 2.388759
iter: 12653 | loss: 2.388565
iter: 12654 | loss: 2.388372
iter: 12655 | loss: 2.388179
iter: 12656 | loss: 2.387985
iter: 12657 | loss: 2.387792
iter: 12658 | loss: 2.387598
iter: 12659 | loss: 2.387405
iter: 12660 | loss: 2.387212
iter: 12661 | loss: 2.387018
iter: 12662 | loss: 2.386825
iter: 12663 | loss: 2.386631
iter: 12664 | loss: 2.386438
iter: 12665 | loss: 2.386245
iter: 12666 | loss: 2.386051
iter: 12667 | loss: 2.385858
iter: 12668 | loss: 2.385665
iter: 12669 | loss: 2.385471
iter: 12670 | loss: 2.385278
iter: 12671 | loss: 2.385084
iter: 12672 | loss: 2.384891
iter: 12673 | loss: 2.384698
iter: 12674 | loss: 2.384504
iter: 12675 | loss: 2.384311
iter: 12676 | loss: 2.384117
iter: 12677 | loss: 2.383924
iter: 12678 | loss: 2.383731
iter: 12679 | loss: 2.383537
iter: 12680 | loss: 2.383344
iter: 12681 | loss: 2.383150
iter: 12682 | loss: 2.382957
iter: 12683 | loss: 2.382764
iter: 12684 | loss: 2.382570
iter: 12685 | loss: 2.382377
iter: 12686 | loss: 2.382184
iter: 12687 | loss: 2.381990
iter: 12688 | loss: 2.381797
iter: 12689 | loss: 2.381603
iter: 12690 | loss: 2.381410
iter: 12691 | loss: 2.381217
iter: 12692 | loss: 2.381023
iter: 12693 | loss: 2.380830
iter: 12694 | loss: 2.380636
iter: 12695 | loss: 2.380443
iter: 12696 | loss: 2.380250
iter: 12697 | loss: 2.380056
iter: 12698 | loss: 2.379863
iter: 12699 | loss: 2.379670
iter: 12700 | loss: 2.379476
iter: 12701 | loss: 2.379283
iter: 12702 | loss: 2.379089
iter: 12703 | loss: 2.378896
iter: 12704 | loss: 2.378703
iter: 12705 | loss: 2.378509
iter: 12706 | loss: 2.378316
iter: 12707 | loss: 2.378122
iter: 12708 | loss: 2.377929
iter: 12709 | loss: 2.377736
iter: 12710 | loss: 2.377542
iter: 12711 | loss: 2.377349
iter: 12712 | loss: 2.377155
iter: 12713 | loss: 2.376962
iter: 12714 | loss: 2.376769
iter: 12715 | loss: 2.376575
iter: 12716 | loss: 2.376382
iter: 12717 | loss: 2.376189
iter: 12718 | loss: 2.375995
iter: 12719 | loss: 2.375802
iter: 12720 | loss: 2.375608
iter: 12721 | loss: 2.375415
iter: 12722 | loss: 2.375222
iter: 12723 | loss: 2.375028
iter: 12724 | loss: 2.374835
iter: 12725 | loss: 2.374641
iter: 12726 | loss: 2.374448
iter: 12727 | loss: 2.374255
iter: 12728 | loss: 2.374061
iter: 12729 | loss: 2.373868
iter: 12730 | loss: 2.373675
iter: 12731 | loss: 2.373481
iter: 12732 | loss: 2.373288
iter: 12733 | loss: 2.373094
iter: 12734 | loss: 2.372901
iter: 12735 | loss: 2.372708
iter: 12736 | loss: 2.372514
iter: 12737 | loss: 2.372321
iter: 12738 | loss: 2.372127
iter: 12739 | loss: 2.371934
iter: 12740 | loss: 2.371741
iter: 12741 | loss: 2.371547
iter: 12742 | loss: 2.371354
iter: 12743 | loss: 2.371160
iter: 12744 | loss: 2.370967
iter: 12745 | loss: 2.370774
iter: 12746 | loss: 2.370580
iter: 12747 | loss: 2.370387
iter: 12748 | loss: 2.370194
iter: 12749 | loss: 2.370000
iter: 12750 | loss: 2.369807
iter: 12751 | loss: 2.369613
iter: 12752 | loss: 2.369420
iter: 12753 | loss: 2.369227
iter: 12754 | loss: 2.369033
iter: 12755 | loss: 2.368840
iter: 12756 | loss: 2.368646
iter: 12757 | loss: 2.368453
iter: 12758 | loss: 2.368260
iter: 12759 | loss: 2.368066
iter: 12760 | loss: 2.367873
iter: 12761 | loss: 2.367680
iter: 12762 | loss: 2.367486
iter: 12763 | loss: 2.367293
iter: 12764 | loss: 2.367099
iter: 12765 | loss: 2.366906
iter: 12766 | loss: 2.366713
iter: 12767 | loss: 2.366519
iter: 12768 | loss: 2.366326
iter: 12769 | loss: 2.366132
iter: 12770 | loss: 2.365939
iter: 12771 | loss: 2.365746
iter: 12772 | loss: 2.365552
iter: 12773 | loss: 2.365359
iter: 12774 | loss: 2.365165
iter: 12775 | loss: 2.364972
iter: 12776 | loss: 2.364779
iter: 12777 | loss: 2.364585
iter: 12778 | loss: 2.364392
iter: 12779 | loss: 2.364199
iter: 12780 | loss: 2.364005
iter: 12781 | loss: 2.363812
iter: 12782 | loss: 2.363618
iter: 12783 | loss: 2.363425
iter: 12784 | loss: 2.363232
iter: 12785 | loss: 2.363038
iter: 12786 | loss: 2.362845
iter: 12787 | loss: 2.362651
iter: 12788 | loss: 2.362458
iter: 12789 | loss: 2.362265
iter: 12790 | loss: 2.362071
iter: 12791 | loss: 2.361878
iter: 12792 | loss: 2.361685
iter: 12793 | loss: 2.361491
iter: 12794 | loss: 2.361298
iter: 12795 | loss: 2.361104
iter: 12796 | loss: 2.360911
iter: 12797 | loss: 2.360718
iter: 12798 | loss: 2.360524
iter: 12799 | loss: 2.360331
iter: 12800 | loss: 2.360137
iter: 12801 | loss: 2.359944
iter: 12802 | loss: 2.359751
iter: 12803 | loss: 2.359557
iter: 12804 | loss: 2.359364
iter: 12805 | loss: 2.359170
iter: 12806 | loss: 2.358977
iter: 12807 | loss: 2.358784
iter: 12808 | loss: 2.358590
iter: 12809 | loss: 2.358397
iter: 12810 | loss: 2.358204
iter: 12811 | loss: 2.358010
iter: 12812 | loss: 2.357817
iter: 12813 | loss: 2.357623
iter: 12814 | loss: 2.357430
iter: 12815 | loss: 2.357237
iter: 12816 | loss: 2.357043
iter: 12817 | loss: 2.356850
iter: 12818 | loss: 2.356656
iter: 12819 | loss: 2.356463
iter: 12820 | loss: 2.356270
iter: 12821 | loss: 2.356076
iter: 12822 | loss: 2.355883
iter: 12823 | loss: 2.355690
iter: 12824 | loss: 2.355496
iter: 12825 | loss: 2.355303
iter: 12826 | loss: 2.355109
iter: 12827 | loss: 2.354916
iter: 12828 | loss: 2.354723
iter: 12829 | loss: 2.354529
iter: 12830 | loss: 2.354336
iter: 12831 | loss: 2.354142
iter: 12832 | loss: 2.353949
iter: 12833 | loss: 2.353756
iter: 12834 | loss: 2.353562
iter: 12835 | loss: 2.353369
iter: 12836 | loss: 2.353175
iter: 12837 | loss: 2.352982
iter: 12838 | loss: 2.352789
iter: 12839 | loss: 2.352595
iter: 12840 | loss: 2.352402
iter: 12841 | loss: 2.352209
iter: 12842 | loss: 2.352015
iter: 12843 | loss: 2.351822
iter: 12844 | loss: 2.351628
iter: 12845 | loss: 2.351435
iter: 12846 | loss: 2.351242
iter: 12847 | loss: 2.351048
iter: 12848 | loss: 2.350855
iter: 12849 | loss: 2.350661
iter: 12850 | loss: 2.350468
iter: 12851 | loss: 2.350275
iter: 12852 | loss: 2.350081
iter: 12853 | loss: 2.349888
iter: 12854 | loss: 2.349695
iter: 12855 | loss: 2.349501
iter: 12856 | loss: 2.349308
iter: 12857 | loss: 2.349114
iter: 12858 | loss: 2.348921
iter: 12859 | loss: 2.348728
iter: 12860 | loss: 2.348534
iter: 12861 | loss: 2.348341
iter: 12862 | loss: 2.348147
iter: 12863 | loss: 2.347954
iter: 12864 | loss: 2.347761
iter: 12865 | loss: 2.347567
iter: 12866 | loss: 2.347374
iter: 12867 | loss: 2.347180
iter: 12868 | loss: 2.346987
iter: 12869 | loss: 2.346794
iter: 12870 | loss: 2.346600
iter: 12871 | loss: 2.346407
iter: 12872 | loss: 2.346214
iter: 12873 | loss: 2.346020
iter: 12874 | loss: 2.345827
iter: 12875 | loss: 2.345633
iter: 12876 | loss: 2.345440
iter: 12877 | loss: 2.345247
iter: 12878 | loss: 2.345053
iter: 12879 | loss: 2.344860
iter: 12880 | loss: 2.344666
iter: 12881 | loss: 2.344473
iter: 12882 | loss: 2.344280
iter: 12883 | loss: 2.344086
iter: 12884 | loss: 2.343893
iter: 12885 | loss: 2.343700
iter: 12886 | loss: 2.343506
iter: 12887 | loss: 2.343313
iter: 12888 | loss: 2.343119
iter: 12889 | loss: 2.342926
iter: 12890 | loss: 2.342733
iter: 12891 | loss: 2.342539
iter: 12892 | loss: 2.342346
iter: 12893 | loss: 2.342152
iter: 12894 | loss: 2.341959
iter: 12895 | loss: 2.341766
iter: 12896 | loss: 2.341572
iter: 12897 | loss: 2.341379
iter: 12898 | loss: 2.341185
iter: 12899 | loss: 2.340992
iter: 12900 | loss: 2.340799
iter: 12901 | loss: 2.340605
iter: 12902 | loss: 2.340412
iter: 12903 | loss: 2.340219
iter: 12904 | loss: 2.340025
iter: 12905 | loss: 2.339832
iter: 12906 | loss: 2.339638
iter: 12907 | loss: 2.339445
iter: 12908 | loss: 2.339252
iter: 12909 | loss: 2.339058
iter: 12910 | loss: 2.338865
iter: 12911 | loss: 2.338671
iter: 12912 | loss: 2.338478
iter: 12913 | loss: 2.338285
iter: 12914 | loss: 2.338091
iter: 12915 | loss: 2.337898
iter: 12916 | loss: 2.337705
iter: 12917 | loss: 2.337511
iter: 12918 | loss: 2.337318
iter: 12919 | loss: 2.337124
iter: 12920 | loss: 2.336931
iter: 12921 | loss: 2.336738
iter: 12922 | loss: 2.336544
iter: 12923 | loss: 2.336351
iter: 12924 | loss: 2.336157
iter: 12925 | loss: 2.335964
iter: 12926 | loss: 2.335771
iter: 12927 | loss: 2.335577
iter: 12928 | loss: 2.335384
iter: 12929 | loss: 2.335191
iter: 12930 | loss: 2.334997
iter: 12931 | loss: 2.334804
iter: 12932 | loss: 2.334610
iter: 12933 | loss: 2.334417
iter: 12934 | loss: 2.334224
iter: 12935 | loss: 2.334030
iter: 12936 | loss: 2.333837
iter: 12937 | loss: 2.333643
iter: 12938 | loss: 2.333450
iter: 12939 | loss: 2.333257
iter: 12940 | loss: 2.333063
iter: 12941 | loss: 2.332870
iter: 12942 | loss: 2.332676
iter: 12943 | loss: 2.332483
iter: 12944 | loss: 2.332290
iter: 12945 | loss: 2.332096
iter: 12946 | loss: 2.331903
iter: 12947 | loss: 2.331710
iter: 12948 | loss: 2.331516
iter: 12949 | loss: 2.331323
iter: 12950 | loss: 2.331129
iter: 12951 | loss: 2.330936
iter: 12952 | loss: 2.330743
iter: 12953 | loss: 2.330549
iter: 12954 | loss: 2.330356
iter: 12955 | loss: 2.330162
iter: 12956 | loss: 2.329969
iter: 12957 | loss: 2.329776
iter: 12958 | loss: 2.329582
iter: 12959 | loss: 2.329389
iter: 12960 | loss: 2.329196
iter: 12961 | loss: 2.329002
iter: 12962 | loss: 2.328809
iter: 12963 | loss: 2.328615
iter: 12964 | loss: 2.328422
iter: 12965 | loss: 2.328229
iter: 12966 | loss: 2.328035
iter: 12967 | loss: 2.327842
iter: 12968 | loss: 2.327648
iter: 12969 | loss: 2.327455
iter: 12970 | loss: 2.327262
iter: 12971 | loss: 2.327068
iter: 12972 | loss: 2.326875
iter: 12973 | loss: 2.326681
iter: 12974 | loss: 2.326488
iter: 12975 | loss: 2.326295
iter: 12976 | loss: 2.326101
iter: 12977 | loss: 2.325908
iter: 12978 | loss: 2.325715
iter: 12979 | loss: 2.325521
iter: 12980 | loss: 2.325328
iter: 12981 | loss: 2.325134
iter: 12982 | loss: 2.324941
iter: 12983 | loss: 2.324748
iter: 12984 | loss: 2.324554
iter: 12985 | loss: 2.324361
iter: 12986 | loss: 2.324167
iter: 12987 | loss: 2.323974
iter: 12988 | loss: 2.323781
iter: 12989 | loss: 2.323587
iter: 12990 | loss: 2.323394
iter: 12991 | loss: 2.323201
iter: 12992 | loss: 2.323007
iter: 12993 | loss: 2.322814
iter: 12994 | loss: 2.322620
iter: 12995 | loss: 2.322427
iter: 12996 | loss: 2.322234
iter: 12997 | loss: 2.322040
iter: 12998 | loss: 2.321847
iter: 12999 | loss: 2.321653
iter: 13000 | loss: 2.321460
iter: 13001 | loss: 2.321267
iter: 13002 | loss: 2.321073
iter: 13003 | loss: 2.320880
iter: 13004 | loss: 2.320686
iter: 13005 | loss: 2.320493
iter: 13006 | loss: 2.320300
iter: 13007 | loss: 2.320106
iter: 13008 | loss: 2.319913
iter: 13009 | loss: 2.319720
iter: 13010 | loss: 2.319526
iter: 13011 | loss: 2.319333
iter: 13012 | loss: 2.319139
iter: 13013 | loss: 2.318946
iter: 13014 | loss: 2.318753
iter: 13015 | loss: 2.318559
iter: 13016 | loss: 2.318366
iter: 13017 | loss: 2.318172
iter: 13018 | loss: 2.317979
iter: 13019 | loss: 2.317786
iter: 13020 | loss: 2.317592
iter: 13021 | loss: 2.317399
iter: 13022 | loss: 2.317206
iter: 13023 | loss: 2.317012
iter: 13024 | loss: 2.316819
iter: 13025 | loss: 2.316625
iter: 13026 | loss: 2.316432
iter: 13027 | loss: 2.316239
iter: 13028 | loss: 2.316045
iter: 13029 | loss: 2.315852
iter: 13030 | loss: 2.315658
iter: 13031 | loss: 2.315465
iter: 13032 | loss: 2.315272
iter: 13033 | loss: 2.315078
iter: 13034 | loss: 2.314885
iter: 13035 | loss: 2.314691
iter: 13036 | loss: 2.314498
iter: 13037 | loss: 2.314305
iter: 13038 | loss: 2.314111
iter: 13039 | loss: 2.313918
iter: 13040 | loss: 2.313725
iter: 13041 | loss: 2.313531
iter: 13042 | loss: 2.313338
iter: 13043 | loss: 2.313144
iter: 13044 | loss: 2.312951
iter: 13045 | loss: 2.312758
iter: 13046 | loss: 2.312564
iter: 13047 | loss: 2.312371
iter: 13048 | loss: 2.312177
iter: 13049 | loss: 2.311984
iter: 13050 | loss: 2.311791
iter: 13051 | loss: 2.311597
iter: 13052 | loss: 2.311404
iter: 13053 | loss: 2.311211
iter: 13054 | loss: 2.311017
iter: 13055 | loss: 2.310824
iter: 13056 | loss: 2.310630
iter: 13057 | loss: 2.310437
iter: 13058 | loss: 2.310244
iter: 13059 | loss: 2.310050
iter: 13060 | loss: 2.309857
iter: 13061 | loss: 2.309663
iter: 13062 | loss: 2.309470
iter: 13063 | loss: 2.309277
iter: 13064 | loss: 2.309083
iter: 13065 | loss: 2.308890
iter: 13066 | loss: 2.308696
iter: 13067 | loss: 2.308503
iter: 13068 | loss: 2.308310
iter: 13069 | loss: 2.308116
iter: 13070 | loss: 2.307923
iter: 13071 | loss: 2.307730
iter: 13072 | loss: 2.307536
iter: 13073 | loss: 2.307343
iter: 13074 | loss: 2.307149
iter: 13075 | loss: 2.306956
iter: 13076 | loss: 2.306763
iter: 13077 | loss: 2.306569
iter: 13078 | loss: 2.306376
iter: 13079 | loss: 2.306182
iter: 13080 | loss: 2.305989
iter: 13081 | loss: 2.305796
iter: 13082 | loss: 2.305602
iter: 13083 | loss: 2.305409
iter: 13084 | loss: 2.305216
iter: 13085 | loss: 2.305022
iter: 13086 | loss: 2.304829
iter: 13087 | loss: 2.304635
iter: 13088 | loss: 2.304442
iter: 13089 | loss: 2.304249
iter: 13090 | loss: 2.304055
iter: 13091 | loss: 2.303862
iter: 13092 | loss: 2.303668
iter: 13093 | loss: 2.303475
iter: 13094 | loss: 2.303282
iter: 13095 | loss: 2.303088
iter: 13096 | loss: 2.302895
iter: 13097 | loss: 2.302701
iter: 13098 | loss: 2.302508
iter: 13099 | loss: 2.302315
iter: 13100 | loss: 2.302121
iter: 13101 | loss: 2.301928
iter: 13102 | loss: 2.301735
iter: 13103 | loss: 2.301541
iter: 13104 | loss: 2.301348
iter: 13105 | loss: 2.301154
iter: 13106 | loss: 2.300961
iter: 13107 | loss: 2.300768
iter: 13108 | loss: 2.300574
iter: 13109 | loss: 2.300381
iter: 13110 | loss: 2.300187
iter: 13111 | loss: 2.299994
iter: 13112 | loss: 2.299801
iter: 13113 | loss: 2.299607
iter: 13114 | loss: 2.299414
iter: 13115 | loss: 2.299221
iter: 13116 | loss: 2.299027
iter: 13117 | loss: 2.298834
iter: 13118 | loss: 2.298640
iter: 13119 | loss: 2.298447
iter: 13120 | loss: 2.298254
iter: 13121 | loss: 2.298060
iter: 13122 | loss: 2.297867
iter: 13123 | loss: 2.297673
iter: 13124 | loss: 2.297480
iter: 13125 | loss: 2.297287
iter: 13126 | loss: 2.297093
iter: 13127 | loss: 2.296900
iter: 13128 | loss: 2.296706
iter: 13129 | loss: 2.296513
iter: 13130 | loss: 2.296320
iter: 13131 | loss: 2.296126
iter: 13132 | loss: 2.295933
iter: 13133 | loss: 2.295740
iter: 13134 | loss: 2.295546
iter: 13135 | loss: 2.295353
iter: 13136 | loss: 2.295159
iter: 13137 | loss: 2.294966
iter: 13138 | loss: 2.294773
iter: 13139 | loss: 2.294579
iter: 13140 | loss: 2.294386
iter: 13141 | loss: 2.294192
iter: 13142 | loss: 2.293999
iter: 13143 | loss: 2.293806
iter: 13144 | loss: 2.293612
iter: 13145 | loss: 2.293419
iter: 13146 | loss: 2.293226
iter: 13147 | loss: 2.293032
iter: 13148 | loss: 2.292839
iter: 13149 | loss: 2.292645
iter: 13150 | loss: 2.292452
iter: 13151 | loss: 2.292259
iter: 13152 | loss: 2.292065
iter: 13153 | loss: 2.291872
iter: 13154 | loss: 2.291678
iter: 13155 | loss: 2.291485
iter: 13156 | loss: 2.291292
iter: 13157 | loss: 2.291098
iter: 13158 | loss: 2.290905
iter: 13159 | loss: 2.290711
iter: 13160 | loss: 2.290518
iter: 13161 | loss: 2.290325
iter: 13162 | loss: 2.290131
iter: 13163 | loss: 2.289938
iter: 13164 | loss: 2.289745
iter: 13165 | loss: 2.289551
iter: 13166 | loss: 2.289358
iter: 13167 | loss: 2.289164
iter: 13168 | loss: 2.288971
iter: 13169 | loss: 2.288778
iter: 13170 | loss: 2.288584
iter: 13171 | loss: 2.288391
iter: 13172 | loss: 2.288197
iter: 13173 | loss: 2.288004
iter: 13174 | loss: 2.287811
iter: 13175 | loss: 2.287617
iter: 13176 | loss: 2.287424
iter: 13177 | loss: 2.287231
iter: 13178 | loss: 2.287037
iter: 13179 | loss: 2.286844
iter: 13180 | loss: 2.286650
iter: 13181 | loss: 2.286457
iter: 13182 | loss: 2.286264
iter: 13183 | loss: 2.286070
iter: 13184 | loss: 2.285877
iter: 13185 | loss: 2.285683
iter: 13186 | loss: 2.285490
iter: 13187 | loss: 2.285297
iter: 13188 | loss: 2.285103
iter: 13189 | loss: 2.284910
iter: 13190 | loss: 2.284716
iter: 13191 | loss: 2.284523
iter: 13192 | loss: 2.284330
iter: 13193 | loss: 2.284136
iter: 13194 | loss: 2.283943
iter: 13195 | loss: 2.283750
iter: 13196 | loss: 2.283556
iter: 13197 | loss: 2.283363
iter: 13198 | loss: 2.283169
iter: 13199 | loss: 2.282976
iter: 13200 | loss: 2.282783
iter: 13201 | loss: 2.282589
iter: 13202 | loss: 2.282396
iter: 13203 | loss: 2.282202
iter: 13204 | loss: 2.282009
iter: 13205 | loss: 2.281816
iter: 13206 | loss: 2.281622
iter: 13207 | loss: 2.281429
iter: 13208 | loss: 2.281236
iter: 13209 | loss: 2.281042
iter: 13210 | loss: 2.280849
iter: 13211 | loss: 2.280655
iter: 13212 | loss: 2.280462
iter: 13213 | loss: 2.280269
iter: 13214 | loss: 2.280075
iter: 13215 | loss: 2.279882
iter: 13216 | loss: 2.279688
iter: 13217 | loss: 2.279495
iter: 13218 | loss: 2.279302
iter: 13219 | loss: 2.279108
iter: 13220 | loss: 2.278915
iter: 13221 | loss: 2.278721
iter: 13222 | loss: 2.278528
iter: 13223 | loss: 2.278335
iter: 13224 | loss: 2.278141
iter: 13225 | loss: 2.277948
iter: 13226 | loss: 2.277755
iter: 13227 | loss: 2.277561
iter: 13228 | loss: 2.277368
iter: 13229 | loss: 2.277174
iter: 13230 | loss: 2.276981
iter: 13231 | loss: 2.276788
iter: 13232 | loss: 2.276594
iter: 13233 | loss: 2.276401
iter: 13234 | loss: 2.276207
iter: 13235 | loss: 2.276014
iter: 13236 | loss: 2.275821
iter: 13237 | loss: 2.275627
iter: 13238 | loss: 2.275434
iter: 13239 | loss: 2.275241
iter: 13240 | loss: 2.275047
iter: 13241 | loss: 2.274854
iter: 13242 | loss: 2.274660
iter: 13243 | loss: 2.274467
iter: 13244 | loss: 2.274274
iter: 13245 | loss: 2.274080
iter: 13246 | loss: 2.273887
iter: 13247 | loss: 2.273693
iter: 13248 | loss: 2.273500
iter: 13249 | loss: 2.273307
iter: 13250 | loss: 2.273113
iter: 13251 | loss: 2.272920
iter: 13252 | loss: 2.272727
iter: 13253 | loss: 2.272533
iter: 13254 | loss: 2.272340
iter: 13255 | loss: 2.272146
iter: 13256 | loss: 2.271953
iter: 13257 | loss: 2.271760
iter: 13258 | loss: 2.271566
iter: 13259 | loss: 2.271373
iter: 13260 | loss: 2.271179
iter: 13261 | loss: 2.270986
iter: 13262 | loss: 2.270793
iter: 13263 | loss: 2.270599
iter: 13264 | loss: 2.270406
iter: 13265 | loss: 2.270212
iter: 13266 | loss: 2.270019
iter: 13267 | loss: 2.269826
iter: 13268 | loss: 2.269632
iter: 13269 | loss: 2.269439
iter: 13270 | loss: 2.269246
iter: 13271 | loss: 2.269052
iter: 13272 | loss: 2.268859
iter: 13273 | loss: 2.268665
iter: 13274 | loss: 2.268472
iter: 13275 | loss: 2.268279
iter: 13276 | loss: 2.268085
iter: 13277 | loss: 2.267892
iter: 13278 | loss: 2.267698
iter: 13279 | loss: 2.267505
iter: 13280 | loss: 2.267312
iter: 13281 | loss: 2.267118
iter: 13282 | loss: 2.266925
iter: 13283 | loss: 2.266732
iter: 13284 | loss: 2.266538
iter: 13285 | loss: 2.266345
iter: 13286 | loss: 2.266151
iter: 13287 | loss: 2.265958
iter: 13288 | loss: 2.265765
iter: 13289 | loss: 2.265571
iter: 13290 | loss: 2.265378
iter: 13291 | loss: 2.265184
iter: 13292 | loss: 2.264991
iter: 13293 | loss: 2.264798
iter: 13294 | loss: 2.264604
iter: 13295 | loss: 2.264411
iter: 13296 | loss: 2.264217
iter: 13297 | loss: 2.264024
iter: 13298 | loss: 2.263831
iter: 13299 | loss: 2.263637
iter: 13300 | loss: 2.263444
iter: 13301 | loss: 2.263251
iter: 13302 | loss: 2.263057
iter: 13303 | loss: 2.262864
iter: 13304 | loss: 2.262670
iter: 13305 | loss: 2.262477
iter: 13306 | loss: 2.262284
iter: 13307 | loss: 2.262090
iter: 13308 | loss: 2.261897
iter: 13309 | loss: 2.261703
iter: 13310 | loss: 2.261510
iter: 13311 | loss: 2.261317
iter: 13312 | loss: 2.261123
iter: 13313 | loss: 2.260930
iter: 13314 | loss: 2.260737
iter: 13315 | loss: 2.260543
iter: 13316 | loss: 2.260350
iter: 13317 | loss: 2.260156
iter: 13318 | loss: 2.259963
iter: 13319 | loss: 2.259770
iter: 13320 | loss: 2.259576
iter: 13321 | loss: 2.259383
iter: 13322 | loss: 2.259189
iter: 13323 | loss: 2.258996
iter: 13324 | loss: 2.258803
iter: 13325 | loss: 2.258609
iter: 13326 | loss: 2.258416
iter: 13327 | loss: 2.258222
iter: 13328 | loss: 2.258029
iter: 13329 | loss: 2.257836
iter: 13330 | loss: 2.257642
iter: 13331 | loss: 2.257449
iter: 13332 | loss: 2.257256
iter: 13333 | loss: 2.257062
iter: 13334 | loss: 2.256869
iter: 13335 | loss: 2.256675
iter: 13336 | loss: 2.256482
iter: 13337 | loss: 2.256289
iter: 13338 | loss: 2.256095
iter: 13339 | loss: 2.255902
iter: 13340 | loss: 2.255708
iter: 13341 | loss: 2.255515
iter: 13342 | loss: 2.255322
iter: 13343 | loss: 2.255128
iter: 13344 | loss: 2.254935
iter: 13345 | loss: 2.254742
iter: 13346 | loss: 2.254548
iter: 13347 | loss: 2.254355
iter: 13348 | loss: 2.254161
iter: 13349 | loss: 2.253968
iter: 13350 | loss: 2.253775
iter: 13351 | loss: 2.253581
iter: 13352 | loss: 2.253388
iter: 13353 | loss: 2.253194
iter: 13354 | loss: 2.253001
iter: 13355 | loss: 2.252808
iter: 13356 | loss: 2.252614
iter: 13357 | loss: 2.252421
iter: 13358 | loss: 2.252227
iter: 13359 | loss: 2.252034
iter: 13360 | loss: 2.251841
iter: 13361 | loss: 2.251647
iter: 13362 | loss: 2.251454
iter: 13363 | loss: 2.251261
iter: 13364 | loss: 2.251067
iter: 13365 | loss: 2.250874
iter: 13366 | loss: 2.250680
iter: 13367 | loss: 2.250487
iter: 13368 | loss: 2.250294
iter: 13369 | loss: 2.250100
iter: 13370 | loss: 2.249907
iter: 13371 | loss: 2.249713
iter: 13372 | loss: 2.249520
iter: 13373 | loss: 2.249327
iter: 13374 | loss: 2.249133
iter: 13375 | loss: 2.248940
iter: 13376 | loss: 2.248747
iter: 13377 | loss: 2.248553
iter: 13378 | loss: 2.248360
iter: 13379 | loss: 2.248166
iter: 13380 | loss: 2.247973
iter: 13381 | loss: 2.247780
iter: 13382 | loss: 2.247586
iter: 13383 | loss: 2.247393
iter: 13384 | loss: 2.247199
iter: 13385 | loss: 2.247006
iter: 13386 | loss: 2.246813
iter: 13387 | loss: 2.246619
iter: 13388 | loss: 2.246426
iter: 13389 | loss: 2.246232
iter: 13390 | loss: 2.246039
iter: 13391 | loss: 2.245846
iter: 13392 | loss: 2.245652
iter: 13393 | loss: 2.245459
iter: 13394 | loss: 2.245266
iter: 13395 | loss: 2.245072
iter: 13396 | loss: 2.244879
iter: 13397 | loss: 2.244685
iter: 13398 | loss: 2.244492
iter: 13399 | loss: 2.244299
iter: 13400 | loss: 2.244105
iter: 13401 | loss: 2.243912
iter: 13402 | loss: 2.243718
iter: 13403 | loss: 2.243525
iter: 13404 | loss: 2.243332
iter: 13405 | loss: 2.243138
iter: 13406 | loss: 2.242945
iter: 13407 | loss: 2.242752
iter: 13408 | loss: 2.242558
iter: 13409 | loss: 2.242365
iter: 13410 | loss: 2.242171
iter: 13411 | loss: 2.241978
iter: 13412 | loss: 2.241785
iter: 13413 | loss: 2.241591
iter: 13414 | loss: 2.241398
iter: 13415 | loss: 2.241204
iter: 13416 | loss: 2.241011
iter: 13417 | loss: 2.240818
iter: 13418 | loss: 2.240624
iter: 13419 | loss: 2.240431
iter: 13420 | loss: 2.240237
iter: 13421 | loss: 2.240044
iter: 13422 | loss: 2.239851
iter: 13423 | loss: 2.239657
iter: 13424 | loss: 2.239464
iter: 13425 | loss: 2.239271
iter: 13426 | loss: 2.239077
iter: 13427 | loss: 2.238884
iter: 13428 | loss: 2.238690
iter: 13429 | loss: 2.238497
iter: 13430 | loss: 2.238304
iter: 13431 | loss: 2.238110
iter: 13432 | loss: 2.237917
iter: 13433 | loss: 2.237723
iter: 13434 | loss: 2.237530
iter: 13435 | loss: 2.237337
iter: 13436 | loss: 2.237143
iter: 13437 | loss: 2.236950
iter: 13438 | loss: 2.236757
iter: 13439 | loss: 2.236563
iter: 13440 | loss: 2.236370
iter: 13441 | loss: 2.236176
iter: 13442 | loss: 2.235983
iter: 13443 | loss: 2.235790
iter: 13444 | loss: 2.235596
iter: 13445 | loss: 2.235403
iter: 13446 | loss: 2.235209
iter: 13447 | loss: 2.235016
iter: 13448 | loss: 2.234823
iter: 13449 | loss: 2.234629
iter: 13450 | loss: 2.234436
iter: 13451 | loss: 2.234242
iter: 13452 | loss: 2.234049
iter: 13453 | loss: 2.233856
iter: 13454 | loss: 2.233662
iter: 13455 | loss: 2.233469
iter: 13456 | loss: 2.233276
iter: 13457 | loss: 2.233082
iter: 13458 | loss: 2.232889
iter: 13459 | loss: 2.232695
iter: 13460 | loss: 2.232502
iter: 13461 | loss: 2.232309
iter: 13462 | loss: 2.232115
iter: 13463 | loss: 2.231922
iter: 13464 | loss: 2.231728
iter: 13465 | loss: 2.231535
iter: 13466 | loss: 2.231342
iter: 13467 | loss: 2.231148
iter: 13468 | loss: 2.230955
iter: 13469 | loss: 2.230762
iter: 13470 | loss: 2.230568
iter: 13471 | loss: 2.230375
iter: 13472 | loss: 2.230181
iter: 13473 | loss: 2.229988
iter: 13474 | loss: 2.229795
iter: 13475 | loss: 2.229601
iter: 13476 | loss: 2.229408
iter: 13477 | loss: 2.229214
iter: 13478 | loss: 2.229021
iter: 13479 | loss: 2.228828
iter: 13480 | loss: 2.228634
iter: 13481 | loss: 2.228441
iter: 13482 | loss: 2.228247
iter: 13483 | loss: 2.228054
iter: 13484 | loss: 2.227861
iter: 13485 | loss: 2.227667
iter: 13486 | loss: 2.227474
iter: 13487 | loss: 2.227281
iter: 13488 | loss: 2.227087
iter: 13489 | loss: 2.226894
iter: 13490 | loss: 2.226700
iter: 13491 | loss: 2.226507
iter: 13492 | loss: 2.226314
iter: 13493 | loss: 2.226120
iter: 13494 | loss: 2.225927
iter: 13495 | loss: 2.225733
iter: 13496 | loss: 2.225540
iter: 13497 | loss: 2.225347
iter: 13498 | loss: 2.225153
iter: 13499 | loss: 2.224960
iter: 13500 | loss: 2.224767
iter: 13501 | loss: 2.224573
iter: 13502 | loss: 2.224380
iter: 13503 | loss: 2.224186
iter: 13504 | loss: 2.223993
iter: 13505 | loss: 2.223800
iter: 13506 | loss: 2.223606
iter: 13507 | loss: 2.223413
iter: 13508 | loss: 2.223219
iter: 13509 | loss: 2.223026
iter: 13510 | loss: 2.222833
iter: 13511 | loss: 2.222639
iter: 13512 | loss: 2.222446
iter: 13513 | loss: 2.222252
iter: 13514 | loss: 2.222059
iter: 13515 | loss: 2.221866
iter: 13516 | loss: 2.221672
iter: 13517 | loss: 2.221479
iter: 13518 | loss: 2.221286
iter: 13519 | loss: 2.221092
iter: 13520 | loss: 2.220899
iter: 13521 | loss: 2.220705
iter: 13522 | loss: 2.220512
iter: 13523 | loss: 2.220319
iter: 13524 | loss: 2.220125
iter: 13525 | loss: 2.219932
iter: 13526 | loss: 2.219738
iter: 13527 | loss: 2.219545
iter: 13528 | loss: 2.219352
iter: 13529 | loss: 2.219158
iter: 13530 | loss: 2.218965
iter: 13531 | loss: 2.218772
iter: 13532 | loss: 2.218578
iter: 13533 | loss: 2.218385
iter: 13534 | loss: 2.218191
iter: 13535 | loss: 2.217998
iter: 13536 | loss: 2.217805
iter: 13537 | loss: 2.217611
iter: 13538 | loss: 2.217418
iter: 13539 | loss: 2.217224
iter: 13540 | loss: 2.217031
iter: 13541 | loss: 2.216838
iter: 13542 | loss: 2.216644
iter: 13543 | loss: 2.216451
iter: 13544 | loss: 2.216257
iter: 13545 | loss: 2.216064
iter: 13546 | loss: 2.215871
iter: 13547 | loss: 2.215677
iter: 13548 | loss: 2.215484
iter: 13549 | loss: 2.215291
iter: 13550 | loss: 2.215097
iter: 13551 | loss: 2.214904
iter: 13552 | loss: 2.214710
iter: 13553 | loss: 2.214517
iter: 13554 | loss: 2.214324
iter: 13555 | loss: 2.214130
iter: 13556 | loss: 2.213937
iter: 13557 | loss: 2.213743
iter: 13558 | loss: 2.213550
iter: 13559 | loss: 2.213357
iter: 13560 | loss: 2.213163
iter: 13561 | loss: 2.212970
iter: 13562 | loss: 2.212777
iter: 13563 | loss: 2.212583
iter: 13564 | loss: 2.212390
iter: 13565 | loss: 2.212196
iter: 13566 | loss: 2.212003
iter: 13567 | loss: 2.211810
iter: 13568 | loss: 2.211616
iter: 13569 | loss: 2.211423
iter: 13570 | loss: 2.211229
iter: 13571 | loss: 2.211036
iter: 13572 | loss: 2.210843
iter: 13573 | loss: 2.210649
iter: 13574 | loss: 2.210456
iter: 13575 | loss: 2.210263
iter: 13576 | loss: 2.210069
iter: 13577 | loss: 2.209876
iter: 13578 | loss: 2.209682
iter: 13579 | loss: 2.209489
iter: 13580 | loss: 2.209296
iter: 13581 | loss: 2.209102
iter: 13582 | loss: 2.208909
iter: 13583 | loss: 2.208715
iter: 13584 | loss: 2.208522
iter: 13585 | loss: 2.208329
iter: 13586 | loss: 2.208135
iter: 13587 | loss: 2.207942
iter: 13588 | loss: 2.207748
iter: 13589 | loss: 2.207555
iter: 13590 | loss: 2.207362
iter: 13591 | loss: 2.207168
iter: 13592 | loss: 2.206975
iter: 13593 | loss: 2.206782
iter: 13594 | loss: 2.206588
iter: 13595 | loss: 2.206395
iter: 13596 | loss: 2.206201
iter: 13597 | loss: 2.206008
iter: 13598 | loss: 2.205815
iter: 13599 | loss: 2.205621
iter: 13600 | loss: 2.205428
iter: 13601 | loss: 2.205234
iter: 13602 | loss: 2.205041
iter: 13603 | loss: 2.204848
iter: 13604 | loss: 2.204654
iter: 13605 | loss: 2.204461
iter: 13606 | loss: 2.204268
iter: 13607 | loss: 2.204074
iter: 13608 | loss: 2.203881
iter: 13609 | loss: 2.203687
iter: 13610 | loss: 2.203494
iter: 13611 | loss: 2.203301
iter: 13612 | loss: 2.203107
iter: 13613 | loss: 2.202914
iter: 13614 | loss: 2.202720
iter: 13615 | loss: 2.202527
iter: 13616 | loss: 2.202334
iter: 13617 | loss: 2.202140
iter: 13618 | loss: 2.201947
iter: 13619 | loss: 2.201753
iter: 13620 | loss: 2.201560
iter: 13621 | loss: 2.201367
iter: 13622 | loss: 2.201173
iter: 13623 | loss: 2.200980
iter: 13624 | loss: 2.200787
iter: 13625 | loss: 2.200593
iter: 13626 | loss: 2.200400
iter: 13627 | loss: 2.200206
iter: 13628 | loss: 2.200013
iter: 13629 | loss: 2.199820
iter: 13630 | loss: 2.199626
iter: 13631 | loss: 2.199433
iter: 13632 | loss: 2.199239
iter: 13633 | loss: 2.199046
iter: 13634 | loss: 2.198853
iter: 13635 | loss: 2.198659
iter: 13636 | loss: 2.198466
iter: 13637 | loss: 2.198273
iter: 13638 | loss: 2.198079
iter: 13639 | loss: 2.197886
iter: 13640 | loss: 2.197692
iter: 13641 | loss: 2.197499
iter: 13642 | loss: 2.197306
iter: 13643 | loss: 2.197112
iter: 13644 | loss: 2.196919
iter: 13645 | loss: 2.196725
iter: 13646 | loss: 2.196532
iter: 13647 | loss: 2.196339
iter: 13648 | loss: 2.196145
iter: 13649 | loss: 2.195952
iter: 13650 | loss: 2.195758
iter: 13651 | loss: 2.195565
iter: 13652 | loss: 2.195372
iter: 13653 | loss: 2.195178
iter: 13654 | loss: 2.194985
iter: 13655 | loss: 2.194792
iter: 13656 | loss: 2.194598
iter: 13657 | loss: 2.194405
iter: 13658 | loss: 2.194211
iter: 13659 | loss: 2.194018
iter: 13660 | loss: 2.193825
iter: 13661 | loss: 2.193631
iter: 13662 | loss: 2.193438
iter: 13663 | loss: 2.193244
iter: 13664 | loss: 2.193051
iter: 13665 | loss: 2.192858
iter: 13666 | loss: 2.192664
iter: 13667 | loss: 2.192471
iter: 13668 | loss: 2.192278
iter: 13669 | loss: 2.192084
iter: 13670 | loss: 2.191891
iter: 13671 | loss: 2.191697
iter: 13672 | loss: 2.191504
iter: 13673 | loss: 2.191311
iter: 13674 | loss: 2.191117
iter: 13675 | loss: 2.190924
iter: 13676 | loss: 2.190730
iter: 13677 | loss: 2.190537
iter: 13678 | loss: 2.190344
iter: 13679 | loss: 2.190150
iter: 13680 | loss: 2.189957
iter: 13681 | loss: 2.189763
iter: 13682 | loss: 2.189570
iter: 13683 | loss: 2.189377
iter: 13684 | loss: 2.189183
iter: 13685 | loss: 2.188990
iter: 13686 | loss: 2.188797
iter: 13687 | loss: 2.188603
iter: 13688 | loss: 2.188410
iter: 13689 | loss: 2.188216
iter: 13690 | loss: 2.188023
iter: 13691 | loss: 2.187830
iter: 13692 | loss: 2.187636
iter: 13693 | loss: 2.187443
iter: 13694 | loss: 2.187249
iter: 13695 | loss: 2.187056
iter: 13696 | loss: 2.186863
iter: 13697 | loss: 2.186669
iter: 13698 | loss: 2.186476
iter: 13699 | loss: 2.186283
iter: 13700 | loss: 2.186089
iter: 13701 | loss: 2.185896
iter: 13702 | loss: 2.185702
iter: 13703 | loss: 2.185509
iter: 13704 | loss: 2.185316
iter: 13705 | loss: 2.185122
iter: 13706 | loss: 2.184929
iter: 13707 | loss: 2.184735
iter: 13708 | loss: 2.184542
iter: 13709 | loss: 2.184349
iter: 13710 | loss: 2.184155
iter: 13711 | loss: 2.183962
iter: 13712 | loss: 2.183768
iter: 13713 | loss: 2.183575
iter: 13714 | loss: 2.183382
iter: 13715 | loss: 2.183188
iter: 13716 | loss: 2.182995
iter: 13717 | loss: 2.182802
iter: 13718 | loss: 2.182608
iter: 13719 | loss: 2.182415
iter: 13720 | loss: 2.182221
iter: 13721 | loss: 2.182028
iter: 13722 | loss: 2.181835
iter: 13723 | loss: 2.181641
iter: 13724 | loss: 2.181448
iter: 13725 | loss: 2.181254
iter: 13726 | loss: 2.181061
iter: 13727 | loss: 2.180868
iter: 13728 | loss: 2.180674
iter: 13729 | loss: 2.180481
iter: 13730 | loss: 2.180288
iter: 13731 | loss: 2.180094
iter: 13732 | loss: 2.179901
iter: 13733 | loss: 2.179707
iter: 13734 | loss: 2.179514
iter: 13735 | loss: 2.179321
iter: 13736 | loss: 2.179127
iter: 13737 | loss: 2.178934
iter: 13738 | loss: 2.178740
iter: 13739 | loss: 2.178547
iter: 13740 | loss: 2.178354
iter: 13741 | loss: 2.178160
iter: 13742 | loss: 2.177967
iter: 13743 | loss: 2.177773
iter: 13744 | loss: 2.177580
iter: 13745 | loss: 2.177387
iter: 13746 | loss: 2.177193
iter: 13747 | loss: 2.177000
iter: 13748 | loss: 2.176807
iter: 13749 | loss: 2.176613
iter: 13750 | loss: 2.176420
iter: 13751 | loss: 2.176226
iter: 13752 | loss: 2.176033
iter: 13753 | loss: 2.175840
iter: 13754 | loss: 2.175646
iter: 13755 | loss: 2.175453
iter: 13756 | loss: 2.175259
iter: 13757 | loss: 2.175066
iter: 13758 | loss: 2.174873
iter: 13759 | loss: 2.174679
iter: 13760 | loss: 2.174486
iter: 13761 | loss: 2.174293
iter: 13762 | loss: 2.174099
iter: 13763 | loss: 2.173906
iter: 13764 | loss: 2.173712
iter: 13765 | loss: 2.173519
iter: 13766 | loss: 2.173326
iter: 13767 | loss: 2.173132
iter: 13768 | loss: 2.172939
iter: 13769 | loss: 2.172745
iter: 13770 | loss: 2.172552
iter: 13771 | loss: 2.172359
iter: 13772 | loss: 2.172165
iter: 13773 | loss: 2.171972
iter: 13774 | loss: 2.171778
iter: 13775 | loss: 2.171585
iter: 13776 | loss: 2.171392
iter: 13777 | loss: 2.171198
iter: 13778 | loss: 2.171005
iter: 13779 | loss: 2.170812
iter: 13780 | loss: 2.170618
iter: 13781 | loss: 2.170425
iter: 13782 | loss: 2.170231
iter: 13783 | loss: 2.170038
iter: 13784 | loss: 2.169845
iter: 13785 | loss: 2.169651
iter: 13786 | loss: 2.169458
iter: 13787 | loss: 2.169264
iter: 13788 | loss: 2.169071
iter: 13789 | loss: 2.168878
iter: 13790 | loss: 2.168684
iter: 13791 | loss: 2.168491
iter: 13792 | loss: 2.168298
iter: 13793 | loss: 2.168104
iter: 13794 | loss: 2.167911
iter: 13795 | loss: 2.167717
iter: 13796 | loss: 2.167524
iter: 13797 | loss: 2.167331
iter: 13798 | loss: 2.167137
iter: 13799 | loss: 2.166944
iter: 13800 | loss: 2.166750
iter: 13801 | loss: 2.166557
iter: 13802 | loss: 2.166364
iter: 13803 | loss: 2.166170
iter: 13804 | loss: 2.165977
iter: 13805 | loss: 2.165783
iter: 13806 | loss: 2.165590
iter: 13807 | loss: 2.165397
iter: 13808 | loss: 2.165203
iter: 13809 | loss: 2.165010
iter: 13810 | loss: 2.164817
iter: 13811 | loss: 2.164623
iter: 13812 | loss: 2.164430
iter: 13813 | loss: 2.164236
iter: 13814 | loss: 2.164043
iter: 13815 | loss: 2.163850
iter: 13816 | loss: 2.163656
iter: 13817 | loss: 2.163463
iter: 13818 | loss: 2.163269
iter: 13819 | loss: 2.163076
iter: 13820 | loss: 2.162883
iter: 13821 | loss: 2.162689
iter: 13822 | loss: 2.162496
iter: 13823 | loss: 2.162303
iter: 13824 | loss: 2.162109
iter: 13825 | loss: 2.161916
iter: 13826 | loss: 2.161722
iter: 13827 | loss: 2.161529
iter: 13828 | loss: 2.161336
iter: 13829 | loss: 2.161142
iter: 13830 | loss: 2.160949
iter: 13831 | loss: 2.160755
iter: 13832 | loss: 2.160562
iter: 13833 | loss: 2.160369
iter: 13834 | loss: 2.160175
iter: 13835 | loss: 2.159982
iter: 13836 | loss: 2.159788
iter: 13837 | loss: 2.159595
iter: 13838 | loss: 2.159402
iter: 13839 | loss: 2.159208
iter: 13840 | loss: 2.159015
iter: 13841 | loss: 2.158822
iter: 13842 | loss: 2.158628
iter: 13843 | loss: 2.158435
iter: 13844 | loss: 2.158241
iter: 13845 | loss: 2.158048
iter: 13846 | loss: 2.157855
iter: 13847 | loss: 2.157661
iter: 13848 | loss: 2.157468
iter: 13849 | loss: 2.157274
iter: 13850 | loss: 2.157081
iter: 13851 | loss: 2.156888
iter: 13852 | loss: 2.156694
iter: 13853 | loss: 2.156501
iter: 13854 | loss: 2.156308
iter: 13855 | loss: 2.156114
iter: 13856 | loss: 2.155921
iter: 13857 | loss: 2.155727
iter: 13858 | loss: 2.155534
iter: 13859 | loss: 2.155341
iter: 13860 | loss: 2.155147
iter: 13861 | loss: 2.154954
iter: 13862 | loss: 2.154760
iter: 13863 | loss: 2.154567
iter: 13864 | loss: 2.154374
iter: 13865 | loss: 2.154180
iter: 13866 | loss: 2.153987
iter: 13867 | loss: 2.153793
iter: 13868 | loss: 2.153600
iter: 13869 | loss: 2.153407
iter: 13870 | loss: 2.153213
iter: 13871 | loss: 2.153020
iter: 13872 | loss: 2.152827
iter: 13873 | loss: 2.152633
iter: 13874 | loss: 2.152440
iter: 13875 | loss: 2.152246
iter: 13876 | loss: 2.152053
iter: 13877 | loss: 2.151860
iter: 13878 | loss: 2.151666
iter: 13879 | loss: 2.151473
iter: 13880 | loss: 2.151279
iter: 13881 | loss: 2.151086
iter: 13882 | loss: 2.150893
iter: 13883 | loss: 2.150699
iter: 13884 | loss: 2.150506
iter: 13885 | loss: 2.150313
iter: 13886 | loss: 2.150119
iter: 13887 | loss: 2.149926
iter: 13888 | loss: 2.149732
iter: 13889 | loss: 2.149539
iter: 13890 | loss: 2.149346
iter: 13891 | loss: 2.149152
iter: 13892 | loss: 2.148959
iter: 13893 | loss: 2.148765
iter: 13894 | loss: 2.148572
iter: 13895 | loss: 2.148379
iter: 13896 | loss: 2.148185
iter: 13897 | loss: 2.147992
iter: 13898 | loss: 2.147799
iter: 13899 | loss: 2.147605
iter: 13900 | loss: 2.147412
iter: 13901 | loss: 2.147218
iter: 13902 | loss: 2.147025
iter: 13903 | loss: 2.146832
iter: 13904 | loss: 2.146638
iter: 13905 | loss: 2.146445
iter: 13906 | loss: 2.146251
iter: 13907 | loss: 2.146058
iter: 13908 | loss: 2.145865
iter: 13909 | loss: 2.145671
iter: 13910 | loss: 2.145478
iter: 13911 | loss: 2.145284
iter: 13912 | loss: 2.145091
iter: 13913 | loss: 2.144898
iter: 13914 | loss: 2.144704
iter: 13915 | loss: 2.144511
iter: 13916 | loss: 2.144318
iter: 13917 | loss: 2.144124
iter: 13918 | loss: 2.143931
iter: 13919 | loss: 2.143737
iter: 13920 | loss: 2.143544
iter: 13921 | loss: 2.143351
iter: 13922 | loss: 2.143157
iter: 13923 | loss: 2.142964
iter: 13924 | loss: 2.142770
iter: 13925 | loss: 2.142577
iter: 13926 | loss: 2.142384
iter: 13927 | loss: 2.142190
iter: 13928 | loss: 2.141997
iter: 13929 | loss: 2.141804
iter: 13930 | loss: 2.141610
iter: 13931 | loss: 2.141417
iter: 13932 | loss: 2.141223
iter: 13933 | loss: 2.141030
iter: 13934 | loss: 2.140837
iter: 13935 | loss: 2.140643
iter: 13936 | loss: 2.140450
iter: 13937 | loss: 2.140256
iter: 13938 | loss: 2.140063
iter: 13939 | loss: 2.139870
iter: 13940 | loss: 2.139676
iter: 13941 | loss: 2.139483
iter: 13942 | loss: 2.139289
iter: 13943 | loss: 2.139096
iter: 13944 | loss: 2.138903
iter: 13945 | loss: 2.138709
iter: 13946 | loss: 2.138516
iter: 13947 | loss: 2.138323
iter: 13948 | loss: 2.138129
iter: 13949 | loss: 2.137936
iter: 13950 | loss: 2.137742
iter: 13951 | loss: 2.137549
iter: 13952 | loss: 2.137356
iter: 13953 | loss: 2.137162
iter: 13954 | loss: 2.136969
iter: 13955 | loss: 2.136775
iter: 13956 | loss: 2.136582
iter: 13957 | loss: 2.136389
iter: 13958 | loss: 2.136195
iter: 13959 | loss: 2.136002
iter: 13960 | loss: 2.135809
iter: 13961 | loss: 2.135615
iter: 13962 | loss: 2.135422
iter: 13963 | loss: 2.135228
iter: 13964 | loss: 2.135035
iter: 13965 | loss: 2.134842
iter: 13966 | loss: 2.134648
iter: 13967 | loss: 2.134455
iter: 13968 | loss: 2.134261
iter: 13969 | loss: 2.134068
iter: 13970 | loss: 2.133875
iter: 13971 | loss: 2.133681
iter: 13972 | loss: 2.133488
iter: 13973 | loss: 2.133294
iter: 13974 | loss: 2.133101
iter: 13975 | loss: 2.132908
iter: 13976 | loss: 2.132714
iter: 13977 | loss: 2.132521
iter: 13978 | loss: 2.132328
iter: 13979 | loss: 2.132134
iter: 13980 | loss: 2.131941
iter: 13981 | loss: 2.131747
iter: 13982 | loss: 2.131554
iter: 13983 | loss: 2.131361
iter: 13984 | loss: 2.131167
iter: 13985 | loss: 2.130974
iter: 13986 | loss: 2.130780
iter: 13987 | loss: 2.130587
iter: 13988 | loss: 2.130394
iter: 13989 | loss: 2.130200
iter: 13990 | loss: 2.130007
iter: 13991 | loss: 2.129814
iter: 13992 | loss: 2.129620
iter: 13993 | loss: 2.129427
iter: 13994 | loss: 2.129233
iter: 13995 | loss: 2.129040
iter: 13996 | loss: 2.128847
iter: 13997 | loss: 2.128653
iter: 13998 | loss: 2.128460
iter: 13999 | loss: 2.128266
iter: 14000 | loss: 2.128073
iter: 14001 | loss: 2.127880
iter: 14002 | loss: 2.127686
iter: 14003 | loss: 2.127493
iter: 14004 | loss: 2.127299
iter: 14005 | loss: 2.127106
iter: 14006 | loss: 2.126913
iter: 14007 | loss: 2.126719
iter: 14008 | loss: 2.126526
iter: 14009 | loss: 2.126333
iter: 14010 | loss: 2.126139
iter: 14011 | loss: 2.125946
iter: 14012 | loss: 2.125752
iter: 14013 | loss: 2.125559
iter: 14014 | loss: 2.125366
iter: 14015 | loss: 2.125172
iter: 14016 | loss: 2.124979
iter: 14017 | loss: 2.124785
iter: 14018 | loss: 2.124592
iter: 14019 | loss: 2.124399
iter: 14020 | loss: 2.124205
iter: 14021 | loss: 2.124012
iter: 14022 | loss: 2.123819
iter: 14023 | loss: 2.123625
iter: 14024 | loss: 2.123432
iter: 14025 | loss: 2.123238
iter: 14026 | loss: 2.123045
iter: 14027 | loss: 2.122852
iter: 14028 | loss: 2.122658
iter: 14029 | loss: 2.122465
iter: 14030 | loss: 2.122271
iter: 14031 | loss: 2.122078
iter: 14032 | loss: 2.121885
iter: 14033 | loss: 2.121691
iter: 14034 | loss: 2.121498
iter: 14035 | loss: 2.121304
iter: 14036 | loss: 2.121111
iter: 14037 | loss: 2.120918
iter: 14038 | loss: 2.120724
iter: 14039 | loss: 2.120531
iter: 14040 | loss: 2.120338
iter: 14041 | loss: 2.120144
iter: 14042 | loss: 2.119951
iter: 14043 | loss: 2.119757
iter: 14044 | loss: 2.119564
iter: 14045 | loss: 2.119371
iter: 14046 | loss: 2.119177
iter: 14047 | loss: 2.118984
iter: 14048 | loss: 2.118790
iter: 14049 | loss: 2.118597
iter: 14050 | loss: 2.118404
iter: 14051 | loss: 2.118210
iter: 14052 | loss: 2.118017
iter: 14053 | loss: 2.117824
iter: 14054 | loss: 2.117630
iter: 14055 | loss: 2.117437
iter: 14056 | loss: 2.117243
iter: 14057 | loss: 2.117050
iter: 14058 | loss: 2.116857
iter: 14059 | loss: 2.116663
iter: 14060 | loss: 2.116470
iter: 14061 | loss: 2.116276
iter: 14062 | loss: 2.116083
iter: 14063 | loss: 2.115890
iter: 14064 | loss: 2.115696
iter: 14065 | loss: 2.115503
iter: 14066 | loss: 2.115309
iter: 14067 | loss: 2.115116
iter: 14068 | loss: 2.114923
iter: 14069 | loss: 2.114729
iter: 14070 | loss: 2.114536
iter: 14071 | loss: 2.114343
iter: 14072 | loss: 2.114149
iter: 14073 | loss: 2.113956
iter: 14074 | loss: 2.113762
iter: 14075 | loss: 2.113569
iter: 14076 | loss: 2.113376
iter: 14077 | loss: 2.113182
iter: 14078 | loss: 2.112989
iter: 14079 | loss: 2.112795
iter: 14080 | loss: 2.112602
iter: 14081 | loss: 2.112409
iter: 14082 | loss: 2.112215
iter: 14083 | loss: 2.112022
iter: 14084 | loss: 2.111829
iter: 14085 | loss: 2.111635
iter: 14086 | loss: 2.111442
iter: 14087 | loss: 2.111248
iter: 14088 | loss: 2.111055
iter: 14089 | loss: 2.110862
iter: 14090 | loss: 2.110668
iter: 14091 | loss: 2.110475
iter: 14092 | loss: 2.110281
iter: 14093 | loss: 2.110088
iter: 14094 | loss: 2.109895
iter: 14095 | loss: 2.109701
iter: 14096 | loss: 2.109508
iter: 14097 | loss: 2.109314
iter: 14098 | loss: 2.109121
iter: 14099 | loss: 2.108928
iter: 14100 | loss: 2.108734
iter: 14101 | loss: 2.108541
iter: 14102 | loss: 2.108348
iter: 14103 | loss: 2.108154
iter: 14104 | loss: 2.107961
iter: 14105 | loss: 2.107767
iter: 14106 | loss: 2.107574
iter: 14107 | loss: 2.107381
iter: 14108 | loss: 2.107187
iter: 14109 | loss: 2.106994
iter: 14110 | loss: 2.106800
iter: 14111 | loss: 2.106607
iter: 14112 | loss: 2.106414
iter: 14113 | loss: 2.106220
iter: 14114 | loss: 2.106027
iter: 14115 | loss: 2.105834
iter: 14116 | loss: 2.105640
iter: 14117 | loss: 2.105447
iter: 14118 | loss: 2.105253
iter: 14119 | loss: 2.105060
iter: 14120 | loss: 2.104867
iter: 14121 | loss: 2.104673
iter: 14122 | loss: 2.104480
iter: 14123 | loss: 2.104286
iter: 14124 | loss: 2.104093
iter: 14125 | loss: 2.103900
iter: 14126 | loss: 2.103706
iter: 14127 | loss: 2.103513
iter: 14128 | loss: 2.103319
iter: 14129 | loss: 2.103126
iter: 14130 | loss: 2.102933
iter: 14131 | loss: 2.102739
iter: 14132 | loss: 2.102546
iter: 14133 | loss: 2.102353
iter: 14134 | loss: 2.102159
iter: 14135 | loss: 2.101966
iter: 14136 | loss: 2.101772
iter: 14137 | loss: 2.101579
iter: 14138 | loss: 2.101386
iter: 14139 | loss: 2.101192
iter: 14140 | loss: 2.100999
iter: 14141 | loss: 2.100805
iter: 14142 | loss: 2.100612
iter: 14143 | loss: 2.100419
iter: 14144 | loss: 2.100225
iter: 14145 | loss: 2.100032
iter: 14146 | loss: 2.099839
iter: 14147 | loss: 2.099645
iter: 14148 | loss: 2.099452
iter: 14149 | loss: 2.099258
iter: 14150 | loss: 2.099065
iter: 14151 | loss: 2.098872
iter: 14152 | loss: 2.098678
iter: 14153 | loss: 2.098485
iter: 14154 | loss: 2.098291
iter: 14155 | loss: 2.098098
iter: 14156 | loss: 2.097905
iter: 14157 | loss: 2.097711
iter: 14158 | loss: 2.097518
iter: 14159 | loss: 2.097324
iter: 14160 | loss: 2.097131
iter: 14161 | loss: 2.096938
iter: 14162 | loss: 2.096744
iter: 14163 | loss: 2.096551
iter: 14164 | loss: 2.096358
iter: 14165 | loss: 2.096164
iter: 14166 | loss: 2.095971
iter: 14167 | loss: 2.095777
iter: 14168 | loss: 2.095584
iter: 14169 | loss: 2.095391
iter: 14170 | loss: 2.095197
iter: 14171 | loss: 2.095004
iter: 14172 | loss: 2.094810
iter: 14173 | loss: 2.094617
iter: 14174 | loss: 2.094424
iter: 14175 | loss: 2.094230
iter: 14176 | loss: 2.094037
iter: 14177 | loss: 2.093844
iter: 14178 | loss: 2.093650
iter: 14179 | loss: 2.093457
iter: 14180 | loss: 2.093263
iter: 14181 | loss: 2.093070
iter: 14182 | loss: 2.092877
iter: 14183 | loss: 2.092683
iter: 14184 | loss: 2.092490
iter: 14185 | loss: 2.092296
iter: 14186 | loss: 2.092103
iter: 14187 | loss: 2.091910
iter: 14188 | loss: 2.091716
iter: 14189 | loss: 2.091523
iter: 14190 | loss: 2.091329
iter: 14191 | loss: 2.091136
iter: 14192 | loss: 2.090943
iter: 14193 | loss: 2.090749
iter: 14194 | loss: 2.090556
iter: 14195 | loss: 2.090363
iter: 14196 | loss: 2.090169
iter: 14197 | loss: 2.089976
iter: 14198 | loss: 2.089782
iter: 14199 | loss: 2.089589
iter: 14200 | loss: 2.089396
iter: 14201 | loss: 2.089202
iter: 14202 | loss: 2.089009
iter: 14203 | loss: 2.088815
iter: 14204 | loss: 2.088622
iter: 14205 | loss: 2.088429
iter: 14206 | loss: 2.088235
iter: 14207 | loss: 2.088042
iter: 14208 | loss: 2.087849
iter: 14209 | loss: 2.087655
iter: 14210 | loss: 2.087462
iter: 14211 | loss: 2.087268
iter: 14212 | loss: 2.087075
iter: 14213 | loss: 2.086882
iter: 14214 | loss: 2.086688
iter: 14215 | loss: 2.086495
iter: 14216 | loss: 2.086301
iter: 14217 | loss: 2.086108
iter: 14218 | loss: 2.085915
iter: 14219 | loss: 2.085721
iter: 14220 | loss: 2.085528
iter: 14221 | loss: 2.085335
iter: 14222 | loss: 2.085141
iter: 14223 | loss: 2.084948
iter: 14224 | loss: 2.084754
iter: 14225 | loss: 2.084561
iter: 14226 | loss: 2.084368
iter: 14227 | loss: 2.084174
iter: 14228 | loss: 2.083981
iter: 14229 | loss: 2.083787
iter: 14230 | loss: 2.083594
iter: 14231 | loss: 2.083401
iter: 14232 | loss: 2.083207
iter: 14233 | loss: 2.083014
iter: 14234 | loss: 2.082820
iter: 14235 | loss: 2.082627
iter: 14236 | loss: 2.082434
iter: 14237 | loss: 2.082240
iter: 14238 | loss: 2.082047
iter: 14239 | loss: 2.081854
iter: 14240 | loss: 2.081660
iter: 14241 | loss: 2.081467
iter: 14242 | loss: 2.081273
iter: 14243 | loss: 2.081080
iter: 14244 | loss: 2.080887
iter: 14245 | loss: 2.080693
iter: 14246 | loss: 2.080500
iter: 14247 | loss: 2.080306
iter: 14248 | loss: 2.080113
iter: 14249 | loss: 2.079920
iter: 14250 | loss: 2.079726
iter: 14251 | loss: 2.079533
iter: 14252 | loss: 2.079340
iter: 14253 | loss: 2.079146
iter: 14254 | loss: 2.078953
iter: 14255 | loss: 2.078759
iter: 14256 | loss: 2.078566
iter: 14257 | loss: 2.078373
iter: 14258 | loss: 2.078179
iter: 14259 | loss: 2.077986
iter: 14260 | loss: 2.077792
iter: 14261 | loss: 2.077599
iter: 14262 | loss: 2.077406
iter: 14263 | loss: 2.077212
iter: 14264 | loss: 2.077019
iter: 14265 | loss: 2.076825
iter: 14266 | loss: 2.076632
iter: 14267 | loss: 2.076439
iter: 14268 | loss: 2.076245
iter: 14269 | loss: 2.076052
iter: 14270 | loss: 2.075859
iter: 14271 | loss: 2.075665
iter: 14272 | loss: 2.075472
iter: 14273 | loss: 2.075278
iter: 14274 | loss: 2.075085
iter: 14275 | loss: 2.074892
iter: 14276 | loss: 2.074698
iter: 14277 | loss: 2.074505
iter: 14278 | loss: 2.074311
iter: 14279 | loss: 2.074118
iter: 14280 | loss: 2.073925
iter: 14281 | loss: 2.073731
iter: 14282 | loss: 2.073538
iter: 14283 | loss: 2.073345
iter: 14284 | loss: 2.073151
iter: 14285 | loss: 2.072958
iter: 14286 | loss: 2.072764
iter: 14287 | loss: 2.072571
iter: 14288 | loss: 2.072378
iter: 14289 | loss: 2.072184
iter: 14290 | loss: 2.071991
iter: 14291 | loss: 2.071797
iter: 14292 | loss: 2.071604
iter: 14293 | loss: 2.071411
iter: 14294 | loss: 2.071217
iter: 14295 | loss: 2.071024
iter: 14296 | loss: 2.070830
iter: 14297 | loss: 2.070637
iter: 14298 | loss: 2.070444
iter: 14299 | loss: 2.070250
iter: 14300 | loss: 2.070057
iter: 14301 | loss: 2.069864
iter: 14302 | loss: 2.069670
iter: 14303 | loss: 2.069477
iter: 14304 | loss: 2.069283
iter: 14305 | loss: 2.069090
iter: 14306 | loss: 2.068897
iter: 14307 | loss: 2.068703
iter: 14308 | loss: 2.068510
iter: 14309 | loss: 2.068316
iter: 14310 | loss: 2.068123
iter: 14311 | loss: 2.067930
iter: 14312 | loss: 2.067736
iter: 14313 | loss: 2.067543
iter: 14314 | loss: 2.067350
iter: 14315 | loss: 2.067156
iter: 14316 | loss: 2.066963
iter: 14317 | loss: 2.066769
iter: 14318 | loss: 2.066576
iter: 14319 | loss: 2.066383
iter: 14320 | loss: 2.066189
iter: 14321 | loss: 2.065996
iter: 14322 | loss: 2.065802
iter: 14323 | loss: 2.065609
iter: 14324 | loss: 2.065416
iter: 14325 | loss: 2.065222
iter: 14326 | loss: 2.065029
iter: 14327 | loss: 2.064835
iter: 14328 | loss: 2.064642
iter: 14329 | loss: 2.064449
iter: 14330 | loss: 2.064255
iter: 14331 | loss: 2.064062
iter: 14332 | loss: 2.063869
iter: 14333 | loss: 2.063675
iter: 14334 | loss: 2.063482
iter: 14335 | loss: 2.063288
iter: 14336 | loss: 2.063095
iter: 14337 | loss: 2.062902
iter: 14338 | loss: 2.062708
iter: 14339 | loss: 2.062515
iter: 14340 | loss: 2.062321
iter: 14341 | loss: 2.062128
iter: 14342 | loss: 2.061935
iter: 14343 | loss: 2.061741
iter: 14344 | loss: 2.061548
iter: 14345 | loss: 2.061355
iter: 14346 | loss: 2.061161
iter: 14347 | loss: 2.060968
iter: 14348 | loss: 2.060774
iter: 14349 | loss: 2.060581
iter: 14350 | loss: 2.060388
iter: 14351 | loss: 2.060194
iter: 14352 | loss: 2.060001
iter: 14353 | loss: 2.059807
iter: 14354 | loss: 2.059614
iter: 14355 | loss: 2.059421
iter: 14356 | loss: 2.059227
iter: 14357 | loss: 2.059034
iter: 14358 | loss: 2.058840
iter: 14359 | loss: 2.058647
iter: 14360 | loss: 2.058454
iter: 14361 | loss: 2.058260
iter: 14362 | loss: 2.058067
iter: 14363 | loss: 2.057874
iter: 14364 | loss: 2.057680
iter: 14365 | loss: 2.057487
iter: 14366 | loss: 2.057293
iter: 14367 | loss: 2.057100
iter: 14368 | loss: 2.056907
iter: 14369 | loss: 2.056713
iter: 14370 | loss: 2.056520
iter: 14371 | loss: 2.056326
iter: 14372 | loss: 2.056133
iter: 14373 | loss: 2.055940
iter: 14374 | loss: 2.055746
iter: 14375 | loss: 2.055553
iter: 14376 | loss: 2.055360
iter: 14377 | loss: 2.055166
iter: 14378 | loss: 2.054973
iter: 14379 | loss: 2.054779
iter: 14380 | loss: 2.054586
iter: 14381 | loss: 2.054393
iter: 14382 | loss: 2.054199
iter: 14383 | loss: 2.054006
iter: 14384 | loss: 2.053812
iter: 14385 | loss: 2.053619
iter: 14386 | loss: 2.053426
iter: 14387 | loss: 2.053232
iter: 14388 | loss: 2.053039
iter: 14389 | loss: 2.052845
iter: 14390 | loss: 2.052652
iter: 14391 | loss: 2.052459
iter: 14392 | loss: 2.052265
iter: 14393 | loss: 2.052072
iter: 14394 | loss: 2.051879
iter: 14395 | loss: 2.051685
iter: 14396 | loss: 2.051492
iter: 14397 | loss: 2.051298
iter: 14398 | loss: 2.051105
iter: 14399 | loss: 2.050912
iter: 14400 | loss: 2.050718
iter: 14401 | loss: 2.050525
iter: 14402 | loss: 2.050331
iter: 14403 | loss: 2.050138
iter: 14404 | loss: 2.049945
iter: 14405 | loss: 2.049751
iter: 14406 | loss: 2.049558
iter: 14407 | loss: 2.049365
iter: 14408 | loss: 2.049171
iter: 14409 | loss: 2.048978
iter: 14410 | loss: 2.048784
iter: 14411 | loss: 2.048591
iter: 14412 | loss: 2.048398
iter: 14413 | loss: 2.048204
iter: 14414 | loss: 2.048011
iter: 14415 | loss: 2.047817
iter: 14416 | loss: 2.047624
iter: 14417 | loss: 2.047431
iter: 14418 | loss: 2.047237
iter: 14419 | loss: 2.047044
iter: 14420 | loss: 2.046850
iter: 14421 | loss: 2.046657
iter: 14422 | loss: 2.046464
iter: 14423 | loss: 2.046270
iter: 14424 | loss: 2.046077
iter: 14425 | loss: 2.045884
iter: 14426 | loss: 2.045690
iter: 14427 | loss: 2.045497
iter: 14428 | loss: 2.045303
iter: 14429 | loss: 2.045110
iter: 14430 | loss: 2.044917
iter: 14431 | loss: 2.044723
iter: 14432 | loss: 2.044530
iter: 14433 | loss: 2.044336
iter: 14434 | loss: 2.044143
iter: 14435 | loss: 2.043950
iter: 14436 | loss: 2.043756
iter: 14437 | loss: 2.043563
iter: 14438 | loss: 2.043370
iter: 14439 | loss: 2.043176
iter: 14440 | loss: 2.042983
iter: 14441 | loss: 2.042789
iter: 14442 | loss: 2.042596
iter: 14443 | loss: 2.042403
iter: 14444 | loss: 2.042209
iter: 14445 | loss: 2.042016
iter: 14446 | loss: 2.041822
iter: 14447 | loss: 2.041629
iter: 14448 | loss: 2.041436
iter: 14449 | loss: 2.041242
iter: 14450 | loss: 2.041049
iter: 14451 | loss: 2.040855
iter: 14452 | loss: 2.040662
iter: 14453 | loss: 2.040469
iter: 14454 | loss: 2.040275
iter: 14455 | loss: 2.040082
iter: 14456 | loss: 2.039889
iter: 14457 | loss: 2.039695
iter: 14458 | loss: 2.039502
iter: 14459 | loss: 2.039308
iter: 14460 | loss: 2.039115
iter: 14461 | loss: 2.038922
iter: 14462 | loss: 2.038728
iter: 14463 | loss: 2.038535
iter: 14464 | loss: 2.038341
iter: 14465 | loss: 2.038148
iter: 14466 | loss: 2.037955
iter: 14467 | loss: 2.037761
iter: 14468 | loss: 2.037568
iter: 14469 | loss: 2.037375
iter: 14470 | loss: 2.037181
iter: 14471 | loss: 2.036988
iter: 14472 | loss: 2.036794
iter: 14473 | loss: 2.036601
iter: 14474 | loss: 2.036408
iter: 14475 | loss: 2.036214
iter: 14476 | loss: 2.036021
iter: 14477 | loss: 2.035827
iter: 14478 | loss: 2.035634
iter: 14479 | loss: 2.035441
iter: 14480 | loss: 2.035247
iter: 14481 | loss: 2.035054
iter: 14482 | loss: 2.034860
iter: 14483 | loss: 2.034667
iter: 14484 | loss: 2.034474
iter: 14485 | loss: 2.034280
iter: 14486 | loss: 2.034087
iter: 14487 | loss: 2.033894
iter: 14488 | loss: 2.033700
iter: 14489 | loss: 2.033507
iter: 14490 | loss: 2.033313
iter: 14491 | loss: 2.033120
iter: 14492 | loss: 2.032927
iter: 14493 | loss: 2.032733
iter: 14494 | loss: 2.032540
iter: 14495 | loss: 2.032346
iter: 14496 | loss: 2.032153
iter: 14497 | loss: 2.031960
iter: 14498 | loss: 2.031766
iter: 14499 | loss: 2.031573
iter: 14500 | loss: 2.031380
iter: 14501 | loss: 2.031186
iter: 14502 | loss: 2.030993
iter: 14503 | loss: 2.030799
iter: 14504 | loss: 2.030606
iter: 14505 | loss: 2.030413
iter: 14506 | loss: 2.030219
iter: 14507 | loss: 2.030026
iter: 14508 | loss: 2.029832
iter: 14509 | loss: 2.029639
iter: 14510 | loss: 2.029446
iter: 14511 | loss: 2.029252
iter: 14512 | loss: 2.029059
iter: 14513 | loss: 2.028865
iter: 14514 | loss: 2.028672
iter: 14515 | loss: 2.028479
iter: 14516 | loss: 2.028285
iter: 14517 | loss: 2.028092
iter: 14518 | loss: 2.027899
iter: 14519 | loss: 2.027705
iter: 14520 | loss: 2.027512
iter: 14521 | loss: 2.027318
iter: 14522 | loss: 2.027125
iter: 14523 | loss: 2.026932
iter: 14524 | loss: 2.026738
iter: 14525 | loss: 2.026545
iter: 14526 | loss: 2.026351
iter: 14527 | loss: 2.026158
iter: 14528 | loss: 2.025965
iter: 14529 | loss: 2.025771
iter: 14530 | loss: 2.025578
iter: 14531 | loss: 2.025385
iter: 14532 | loss: 2.025191
iter: 14533 | loss: 2.024998
iter: 14534 | loss: 2.024804
iter: 14535 | loss: 2.024611
iter: 14536 | loss: 2.024418
iter: 14537 | loss: 2.024224
iter: 14538 | loss: 2.024031
iter: 14539 | loss: 2.023837
iter: 14540 | loss: 2.023644
iter: 14541 | loss: 2.023451
iter: 14542 | loss: 2.023257
iter: 14543 | loss: 2.023064
iter: 14544 | loss: 2.022871
iter: 14545 | loss: 2.022677
iter: 14546 | loss: 2.022484
iter: 14547 | loss: 2.022290
iter: 14548 | loss: 2.022097
iter: 14549 | loss: 2.021904
iter: 14550 | loss: 2.021710
iter: 14551 | loss: 2.021517
iter: 14552 | loss: 2.021323
iter: 14553 | loss: 2.021130
iter: 14554 | loss: 2.020937
iter: 14555 | loss: 2.020743
iter: 14556 | loss: 2.020550
iter: 14557 | loss: 2.020356
iter: 14558 | loss: 2.020163
iter: 14559 | loss: 2.019970
iter: 14560 | loss: 2.019776
iter: 14561 | loss: 2.019583
iter: 14562 | loss: 2.019390
iter: 14563 | loss: 2.019196
iter: 14564 | loss: 2.019003
iter: 14565 | loss: 2.018809
iter: 14566 | loss: 2.018616
iter: 14567 | loss: 2.018423
iter: 14568 | loss: 2.018229
iter: 14569 | loss: 2.018036
iter: 14570 | loss: 2.017842
iter: 14571 | loss: 2.017649
iter: 14572 | loss: 2.017456
iter: 14573 | loss: 2.017262
iter: 14574 | loss: 2.017069
iter: 14575 | loss: 2.016876
iter: 14576 | loss: 2.016682
iter: 14577 | loss: 2.016489
iter: 14578 | loss: 2.016295
iter: 14579 | loss: 2.016102
iter: 14580 | loss: 2.015909
iter: 14581 | loss: 2.015715
iter: 14582 | loss: 2.015522
iter: 14583 | loss: 2.015328
iter: 14584 | loss: 2.015135
iter: 14585 | loss: 2.014942
iter: 14586 | loss: 2.014748
iter: 14587 | loss: 2.014555
iter: 14588 | loss: 2.014361
iter: 14589 | loss: 2.014168
iter: 14590 | loss: 2.013975
iter: 14591 | loss: 2.013781
iter: 14592 | loss: 2.013588
iter: 14593 | loss: 2.013395
iter: 14594 | loss: 2.013201
iter: 14595 | loss: 2.013008
iter: 14596 | loss: 2.012814
iter: 14597 | loss: 2.012621
iter: 14598 | loss: 2.012428
iter: 14599 | loss: 2.012234
iter: 14600 | loss: 2.012041
iter: 14601 | loss: 2.011847
iter: 14602 | loss: 2.011654
iter: 14603 | loss: 2.011461
iter: 14604 | loss: 2.011267
iter: 14605 | loss: 2.011074
iter: 14606 | loss: 2.010881
iter: 14607 | loss: 2.010687
iter: 14608 | loss: 2.010494
iter: 14609 | loss: 2.010300
iter: 14610 | loss: 2.010107
iter: 14611 | loss: 2.009914
iter: 14612 | loss: 2.009720
iter: 14613 | loss: 2.009527
iter: 14614 | loss: 2.009333
iter: 14615 | loss: 2.009140
iter: 14616 | loss: 2.008947
iter: 14617 | loss: 2.008753
iter: 14618 | loss: 2.008560
iter: 14619 | loss: 2.008366
iter: 14620 | loss: 2.008173
iter: 14621 | loss: 2.007980
iter: 14622 | loss: 2.007786
iter: 14623 | loss: 2.007593
iter: 14624 | loss: 2.007400
iter: 14625 | loss: 2.007206
iter: 14626 | loss: 2.007013
iter: 14627 | loss: 2.006819
iter: 14628 | loss: 2.006626
iter: 14629 | loss: 2.006433
iter: 14630 | loss: 2.006239
iter: 14631 | loss: 2.006046
iter: 14632 | loss: 2.005852
iter: 14633 | loss: 2.005659
iter: 14634 | loss: 2.005466
iter: 14635 | loss: 2.005272
iter: 14636 | loss: 2.005079
iter: 14637 | loss: 2.004886
iter: 14638 | loss: 2.004692
iter: 14639 | loss: 2.004499
iter: 14640 | loss: 2.004305
iter: 14641 | loss: 2.004112
iter: 14642 | loss: 2.003919
iter: 14643 | loss: 2.003725
iter: 14644 | loss: 2.003532
iter: 14645 | loss: 2.003338
iter: 14646 | loss: 2.003145
iter: 14647 | loss: 2.002952
iter: 14648 | loss: 2.002758
iter: 14649 | loss: 2.002565
iter: 14650 | loss: 2.002371
iter: 14651 | loss: 2.002178
iter: 14652 | loss: 2.001985
iter: 14653 | loss: 2.001791
iter: 14654 | loss: 2.001598
iter: 14655 | loss: 2.001405
iter: 14656 | loss: 2.001211
iter: 14657 | loss: 2.001018
iter: 14658 | loss: 2.000824
iter: 14659 | loss: 2.000631
iter: 14660 | loss: 2.000438
iter: 14661 | loss: 2.000244
iter: 14662 | loss: 2.000051
iter: 14663 | loss: 1.999857
iter: 14664 | loss: 1.999664
iter: 14665 | loss: 1.999471
iter: 14666 | loss: 1.999277
iter: 14667 | loss: 1.999084
iter: 14668 | loss: 1.998891
iter: 14669 | loss: 1.998697
iter: 14670 | loss: 1.998504
iter: 14671 | loss: 1.998310
iter: 14672 | loss: 1.998117
iter: 14673 | loss: 1.997924
iter: 14674 | loss: 1.997730
iter: 14675 | loss: 1.997537
iter: 14676 | loss: 1.997343
iter: 14677 | loss: 1.997150
iter: 14678 | loss: 1.996957
iter: 14679 | loss: 1.996763
iter: 14680 | loss: 1.996570
iter: 14681 | loss: 1.996376
iter: 14682 | loss: 1.996183
iter: 14683 | loss: 1.995990
iter: 14684 | loss: 1.995796
iter: 14685 | loss: 1.995603
iter: 14686 | loss: 1.995410
iter: 14687 | loss: 1.995216
iter: 14688 | loss: 1.995023
iter: 14689 | loss: 1.994829
iter: 14690 | loss: 1.994636
iter: 14691 | loss: 1.994443
iter: 14692 | loss: 1.994249
iter: 14693 | loss: 1.994056
iter: 14694 | loss: 1.993862
iter: 14695 | loss: 1.993669
iter: 14696 | loss: 1.993476
iter: 14697 | loss: 1.993282
iter: 14698 | loss: 1.993089
iter: 14699 | loss: 1.992896
iter: 14700 | loss: 1.992702
iter: 14701 | loss: 1.992509
iter: 14702 | loss: 1.992315
iter: 14703 | loss: 1.992122
iter: 14704 | loss: 1.991929
iter: 14705 | loss: 1.991735
iter: 14706 | loss: 1.991542
iter: 14707 | loss: 1.991348
iter: 14708 | loss: 1.991155
iter: 14709 | loss: 1.990962
iter: 14710 | loss: 1.990768
iter: 14711 | loss: 1.990575
iter: 14712 | loss: 1.990381
iter: 14713 | loss: 1.990188
iter: 14714 | loss: 1.989995
iter: 14715 | loss: 1.989801
iter: 14716 | loss: 1.989608
iter: 14717 | loss: 1.989415
iter: 14718 | loss: 1.989221
iter: 14719 | loss: 1.989028
iter: 14720 | loss: 1.988834
iter: 14721 | loss: 1.988641
iter: 14722 | loss: 1.988448
iter: 14723 | loss: 1.988254
iter: 14724 | loss: 1.988061
iter: 14725 | loss: 1.987867
iter: 14726 | loss: 1.987674
iter: 14727 | loss: 1.987481
iter: 14728 | loss: 1.987287
iter: 14729 | loss: 1.987094
iter: 14730 | loss: 1.986901
iter: 14731 | loss: 1.986707
iter: 14732 | loss: 1.986514
iter: 14733 | loss: 1.986320
iter: 14734 | loss: 1.986127
iter: 14735 | loss: 1.985934
iter: 14736 | loss: 1.985740
iter: 14737 | loss: 1.985547
iter: 14738 | loss: 1.985353
iter: 14739 | loss: 1.985160
iter: 14740 | loss: 1.984967
iter: 14741 | loss: 1.984773
iter: 14742 | loss: 1.984580
iter: 14743 | loss: 1.984386
iter: 14744 | loss: 1.984193
iter: 14745 | loss: 1.984000
iter: 14746 | loss: 1.983806
iter: 14747 | loss: 1.983613
iter: 14748 | loss: 1.983420
iter: 14749 | loss: 1.983226
iter: 14750 | loss: 1.983033
iter: 14751 | loss: 1.982839
iter: 14752 | loss: 1.982646
iter: 14753 | loss: 1.982453
iter: 14754 | loss: 1.982259
iter: 14755 | loss: 1.982066
iter: 14756 | loss: 1.981872
iter: 14757 | loss: 1.981679
iter: 14758 | loss: 1.981486
iter: 14759 | loss: 1.981292
iter: 14760 | loss: 1.981099
iter: 14761 | loss: 1.980906
iter: 14762 | loss: 1.980712
iter: 14763 | loss: 1.980519
iter: 14764 | loss: 1.980325
iter: 14765 | loss: 1.980132
iter: 14766 | loss: 1.979939
iter: 14767 | loss: 1.979745
iter: 14768 | loss: 1.979552
iter: 14769 | loss: 1.979358
iter: 14770 | loss: 1.979165
iter: 14771 | loss: 1.978972
iter: 14772 | loss: 1.978778
iter: 14773 | loss: 1.978585
iter: 14774 | loss: 1.978391
iter: 14775 | loss: 1.978198
iter: 14776 | loss: 1.978005
iter: 14777 | loss: 1.977811
iter: 14778 | loss: 1.977618
iter: 14779 | loss: 1.977425
iter: 14780 | loss: 1.977231
iter: 14781 | loss: 1.977038
iter: 14782 | loss: 1.976844
iter: 14783 | loss: 1.976651
iter: 14784 | loss: 1.976458
iter: 14785 | loss: 1.976264
iter: 14786 | loss: 1.976071
iter: 14787 | loss: 1.975877
iter: 14788 | loss: 1.975684
iter: 14789 | loss: 1.975491
iter: 14790 | loss: 1.975297
iter: 14791 | loss: 1.975104
iter: 14792 | loss: 1.974911
iter: 14793 | loss: 1.974717
iter: 14794 | loss: 1.974524
iter: 14795 | loss: 1.974330
iter: 14796 | loss: 1.974137
iter: 14797 | loss: 1.973944
iter: 14798 | loss: 1.973750
iter: 14799 | loss: 1.973557
iter: 14800 | loss: 1.973363
iter: 14801 | loss: 1.973170
iter: 14802 | loss: 1.972977
iter: 14803 | loss: 1.972783
iter: 14804 | loss: 1.972590
iter: 14805 | loss: 1.972396
iter: 14806 | loss: 1.972203
iter: 14807 | loss: 1.972010
iter: 14808 | loss: 1.971816
iter: 14809 | loss: 1.971623
iter: 14810 | loss: 1.971430
iter: 14811 | loss: 1.971236
iter: 14812 | loss: 1.971043
iter: 14813 | loss: 1.970849
iter: 14814 | loss: 1.970656
iter: 14815 | loss: 1.970463
iter: 14816 | loss: 1.970269
iter: 14817 | loss: 1.970076
iter: 14818 | loss: 1.969882
iter: 14819 | loss: 1.969689
iter: 14820 | loss: 1.969496
iter: 14821 | loss: 1.969302
iter: 14822 | loss: 1.969109
iter: 14823 | loss: 1.968916
iter: 14824 | loss: 1.968722
iter: 14825 | loss: 1.968529
iter: 14826 | loss: 1.968335
iter: 14827 | loss: 1.968142
iter: 14828 | loss: 1.967949
iter: 14829 | loss: 1.967755
iter: 14830 | loss: 1.967562
iter: 14831 | loss: 1.967368
iter: 14832 | loss: 1.967175
iter: 14833 | loss: 1.966982
iter: 14834 | loss: 1.966788
iter: 14835 | loss: 1.966595
iter: 14836 | loss: 1.966401
iter: 14837 | loss: 1.966208
iter: 14838 | loss: 1.966015
iter: 14839 | loss: 1.965821
iter: 14840 | loss: 1.965628
iter: 14841 | loss: 1.965435
iter: 14842 | loss: 1.965241
iter: 14843 | loss: 1.965048
iter: 14844 | loss: 1.964854
iter: 14845 | loss: 1.964661
iter: 14846 | loss: 1.964468
iter: 14847 | loss: 1.964274
iter: 14848 | loss: 1.964081
iter: 14849 | loss: 1.963887
iter: 14850 | loss: 1.963694
iter: 14851 | loss: 1.963501
iter: 14852 | loss: 1.963307
iter: 14853 | loss: 1.963114
iter: 14854 | loss: 1.962921
iter: 14855 | loss: 1.962727
iter: 14856 | loss: 1.962534
iter: 14857 | loss: 1.962340
iter: 14858 | loss: 1.962147
iter: 14859 | loss: 1.961954
iter: 14860 | loss: 1.961760
iter: 14861 | loss: 1.961567
iter: 14862 | loss: 1.961373
iter: 14863 | loss: 1.961180
iter: 14864 | loss: 1.960987
iter: 14865 | loss: 1.960793
iter: 14866 | loss: 1.960600
iter: 14867 | loss: 1.960407
iter: 14868 | loss: 1.960213
iter: 14869 | loss: 1.960020
iter: 14870 | loss: 1.959826
iter: 14871 | loss: 1.959633
iter: 14872 | loss: 1.959440
iter: 14873 | loss: 1.959246
iter: 14874 | loss: 1.959053
iter: 14875 | loss: 1.958859
iter: 14876 | loss: 1.958666
iter: 14877 | loss: 1.958473
iter: 14878 | loss: 1.958279
iter: 14879 | loss: 1.958086
iter: 14880 | loss: 1.957892
iter: 14881 | loss: 1.957699
iter: 14882 | loss: 1.957506
iter: 14883 | loss: 1.957312
iter: 14884 | loss: 1.957119
iter: 14885 | loss: 1.956926
iter: 14886 | loss: 1.956732
iter: 14887 | loss: 1.956539
iter: 14888 | loss: 1.956345
iter: 14889 | loss: 1.956152
iter: 14890 | loss: 1.955959
iter: 14891 | loss: 1.955765
iter: 14892 | loss: 1.955572
iter: 14893 | loss: 1.955378
iter: 14894 | loss: 1.955185
iter: 14895 | loss: 1.954992
iter: 14896 | loss: 1.954798
iter: 14897 | loss: 1.954605
iter: 14898 | loss: 1.954412
iter: 14899 | loss: 1.954218
iter: 14900 | loss: 1.954025
iter: 14901 | loss: 1.953831
iter: 14902 | loss: 1.953638
iter: 14903 | loss: 1.953445
iter: 14904 | loss: 1.953251
iter: 14905 | loss: 1.953058
iter: 14906 | loss: 1.952864
iter: 14907 | loss: 1.952671
iter: 14908 | loss: 1.952478
iter: 14909 | loss: 1.952284
iter: 14910 | loss: 1.952091
iter: 14911 | loss: 1.951897
iter: 14912 | loss: 1.951704
iter: 14913 | loss: 1.951511
iter: 14914 | loss: 1.951317
iter: 14915 | loss: 1.951124
iter: 14916 | loss: 1.950931
iter: 14917 | loss: 1.950737
iter: 14918 | loss: 1.950544
iter: 14919 | loss: 1.950350
iter: 14920 | loss: 1.950157
iter: 14921 | loss: 1.949964
iter: 14922 | loss: 1.949770
iter: 14923 | loss: 1.949577
iter: 14924 | loss: 1.949383
iter: 14925 | loss: 1.949190
iter: 14926 | loss: 1.948997
iter: 14927 | loss: 1.948803
iter: 14928 | loss: 1.948610
iter: 14929 | loss: 1.948417
iter: 14930 | loss: 1.948223
iter: 14931 | loss: 1.948030
iter: 14932 | loss: 1.947836
iter: 14933 | loss: 1.947643
iter: 14934 | loss: 1.947450
iter: 14935 | loss: 1.947256
iter: 14936 | loss: 1.947063
iter: 14937 | loss: 1.946869
iter: 14938 | loss: 1.946676
iter: 14939 | loss: 1.946483
iter: 14940 | loss: 1.946289
iter: 14941 | loss: 1.946096
iter: 14942 | loss: 1.945902
iter: 14943 | loss: 1.945709
iter: 14944 | loss: 1.945516
iter: 14945 | loss: 1.945322
iter: 14946 | loss: 1.945129
iter: 14947 | loss: 1.944936
iter: 14948 | loss: 1.944742
iter: 14949 | loss: 1.944549
iter: 14950 | loss: 1.944355
iter: 14951 | loss: 1.944162
iter: 14952 | loss: 1.943969
iter: 14953 | loss: 1.943775
iter: 14954 | loss: 1.943582
iter: 14955 | loss: 1.943388
iter: 14956 | loss: 1.943195
iter: 14957 | loss: 1.943002
iter: 14958 | loss: 1.942808
iter: 14959 | loss: 1.942615
iter: 14960 | loss: 1.942422
iter: 14961 | loss: 1.942228
iter: 14962 | loss: 1.942035
iter: 14963 | loss: 1.941841
iter: 14964 | loss: 1.941648
iter: 14965 | loss: 1.941455
iter: 14966 | loss: 1.941261
iter: 14967 | loss: 1.941068
iter: 14968 | loss: 1.940874
iter: 14969 | loss: 1.940681
iter: 14970 | loss: 1.940488
iter: 14971 | loss: 1.940294
iter: 14972 | loss: 1.940101
iter: 14973 | loss: 1.939907
iter: 14974 | loss: 1.939714
iter: 14975 | loss: 1.939521
iter: 14976 | loss: 1.939327
iter: 14977 | loss: 1.939134
iter: 14978 | loss: 1.938941
iter: 14979 | loss: 1.938747
iter: 14980 | loss: 1.938554
iter: 14981 | loss: 1.938360
iter: 14982 | loss: 1.938167
iter: 14983 | loss: 1.937974
iter: 14984 | loss: 1.937780
iter: 14985 | loss: 1.937587
iter: 14986 | loss: 1.937393
iter: 14987 | loss: 1.937200
iter: 14988 | loss: 1.937007
iter: 14989 | loss: 1.936813
iter: 14990 | loss: 1.936620
iter: 14991 | loss: 1.936427
iter: 14992 | loss: 1.936233
iter: 14993 | loss: 1.936040
iter: 14994 | loss: 1.935846
iter: 14995 | loss: 1.935653
iter: 14996 | loss: 1.935460
iter: 14997 | loss: 1.935266
iter: 14998 | loss: 1.935073
iter: 14999 | loss: 1.934879
iter: 15000 | loss: 1.934686
iter: 15001 | loss: 1.934493
iter: 15002 | loss: 1.934299
iter: 15003 | loss: 1.934106
iter: 15004 | loss: 1.933912
iter: 15005 | loss: 1.933719
iter: 15006 | loss: 1.933526
iter: 15007 | loss: 1.933332
iter: 15008 | loss: 1.933139
iter: 15009 | loss: 1.932946
iter: 15010 | loss: 1.932752
iter: 15011 | loss: 1.932559
iter: 15012 | loss: 1.932365
iter: 15013 | loss: 1.932172
iter: 15014 | loss: 1.931979
iter: 15015 | loss: 1.931785
iter: 15016 | loss: 1.931592
iter: 15017 | loss: 1.931398
iter: 15018 | loss: 1.931205
iter: 15019 | loss: 1.931012
iter: 15020 | loss: 1.930818
iter: 15021 | loss: 1.930625
iter: 15022 | loss: 1.930432
iter: 15023 | loss: 1.930238
iter: 15024 | loss: 1.930045
iter: 15025 | loss: 1.929851
iter: 15026 | loss: 1.929658
iter: 15027 | loss: 1.929465
iter: 15028 | loss: 1.929271
iter: 15029 | loss: 1.929078
iter: 15030 | loss: 1.928884
iter: 15031 | loss: 1.928691
iter: 15032 | loss: 1.928498
iter: 15033 | loss: 1.928304
iter: 15034 | loss: 1.928111
iter: 15035 | loss: 1.927917
iter: 15036 | loss: 1.927724
iter: 15037 | loss: 1.927531
iter: 15038 | loss: 1.927337
iter: 15039 | loss: 1.927144
iter: 15040 | loss: 1.926951
iter: 15041 | loss: 1.926757
iter: 15042 | loss: 1.926564
iter: 15043 | loss: 1.926370
iter: 15044 | loss: 1.926177
iter: 15045 | loss: 1.925984
iter: 15046 | loss: 1.925790
iter: 15047 | loss: 1.925597
iter: 15048 | loss: 1.925403
iter: 15049 | loss: 1.925210
iter: 15050 | loss: 1.925017
iter: 15051 | loss: 1.924823
iter: 15052 | loss: 1.924630
iter: 15053 | loss: 1.924437
iter: 15054 | loss: 1.924243
iter: 15055 | loss: 1.924050
iter: 15056 | loss: 1.923856
iter: 15057 | loss: 1.923663
iter: 15058 | loss: 1.923470
iter: 15059 | loss: 1.923276
iter: 15060 | loss: 1.923083
iter: 15061 | loss: 1.922889
iter: 15062 | loss: 1.922696
iter: 15063 | loss: 1.922503
iter: 15064 | loss: 1.922309
iter: 15065 | loss: 1.922116
iter: 15066 | loss: 1.921922
iter: 15067 | loss: 1.921729
iter: 15068 | loss: 1.921536
iter: 15069 | loss: 1.921342
iter: 15070 | loss: 1.921149
iter: 15071 | loss: 1.920956
iter: 15072 | loss: 1.920762
iter: 15073 | loss: 1.920569
iter: 15074 | loss: 1.920375
iter: 15075 | loss: 1.920182
iter: 15076 | loss: 1.919989
iter: 15077 | loss: 1.919795
iter: 15078 | loss: 1.919602
iter: 15079 | loss: 1.919408
iter: 15080 | loss: 1.919215
iter: 15081 | loss: 1.919022
iter: 15082 | loss: 1.918828
iter: 15083 | loss: 1.918635
iter: 15084 | loss: 1.918442
iter: 15085 | loss: 1.918248
iter: 15086 | loss: 1.918055
iter: 15087 | loss: 1.917861
iter: 15088 | loss: 1.917668
iter: 15089 | loss: 1.917475
iter: 15090 | loss: 1.917281
iter: 15091 | loss: 1.917088
iter: 15092 | loss: 1.916894
iter: 15093 | loss: 1.916701
iter: 15094 | loss: 1.916508
iter: 15095 | loss: 1.916314
iter: 15096 | loss: 1.916121
iter: 15097 | loss: 1.915927
iter: 15098 | loss: 1.915734
iter: 15099 | loss: 1.915541
iter: 15100 | loss: 1.915347
iter: 15101 | loss: 1.915154
iter: 15102 | loss: 1.914961
iter: 15103 | loss: 1.914767
iter: 15104 | loss: 1.914574
iter: 15105 | loss: 1.914380
iter: 15106 | loss: 1.914187
iter: 15107 | loss: 1.913994
iter: 15108 | loss: 1.913800
iter: 15109 | loss: 1.913607
iter: 15110 | loss: 1.913413
iter: 15111 | loss: 1.913220
iter: 15112 | loss: 1.913027
iter: 15113 | loss: 1.912833
iter: 15114 | loss: 1.912640
iter: 15115 | loss: 1.912447
iter: 15116 | loss: 1.912253
iter: 15117 | loss: 1.912060
iter: 15118 | loss: 1.911866
iter: 15119 | loss: 1.911673
iter: 15120 | loss: 1.911480
iter: 15121 | loss: 1.911286
iter: 15122 | loss: 1.911093
iter: 15123 | loss: 1.910899
iter: 15124 | loss: 1.910706
iter: 15125 | loss: 1.910513
iter: 15126 | loss: 1.910319
iter: 15127 | loss: 1.910126
iter: 15128 | loss: 1.909932
iter: 15129 | loss: 1.909739
iter: 15130 | loss: 1.909546
iter: 15131 | loss: 1.909352
iter: 15132 | loss: 1.909159
iter: 15133 | loss: 1.908966
iter: 15134 | loss: 1.908772
iter: 15135 | loss: 1.908579
iter: 15136 | loss: 1.908385
iter: 15137 | loss: 1.908192
iter: 15138 | loss: 1.907999
iter: 15139 | loss: 1.907805
iter: 15140 | loss: 1.907612
iter: 15141 | loss: 1.907418
iter: 15142 | loss: 1.907225
iter: 15143 | loss: 1.907032
iter: 15144 | loss: 1.906838
iter: 15145 | loss: 1.906645
iter: 15146 | loss: 1.906452
iter: 15147 | loss: 1.906258
iter: 15148 | loss: 1.906065
iter: 15149 | loss: 1.905871
iter: 15150 | loss: 1.905678
iter: 15151 | loss: 1.905485
iter: 15152 | loss: 1.905291
iter: 15153 | loss: 1.905098
iter: 15154 | loss: 1.904904
iter: 15155 | loss: 1.904711
iter: 15156 | loss: 1.904518
iter: 15157 | loss: 1.904324
iter: 15158 | loss: 1.904131
iter: 15159 | loss: 1.903937
iter: 15160 | loss: 1.903744
iter: 15161 | loss: 1.903551
iter: 15162 | loss: 1.903357
iter: 15163 | loss: 1.903164
iter: 15164 | loss: 1.902971
iter: 15165 | loss: 1.902777
iter: 15166 | loss: 1.902584
iter: 15167 | loss: 1.902390
iter: 15168 | loss: 1.902197
iter: 15169 | loss: 1.902004
iter: 15170 | loss: 1.901810
iter: 15171 | loss: 1.901617
iter: 15172 | loss: 1.901423
iter: 15173 | loss: 1.901230
iter: 15174 | loss: 1.901037
iter: 15175 | loss: 1.900843
iter: 15176 | loss: 1.900650
iter: 15177 | loss: 1.900457
iter: 15178 | loss: 1.900263
iter: 15179 | loss: 1.900070
iter: 15180 | loss: 1.899876
iter: 15181 | loss: 1.899683
iter: 15182 | loss: 1.899490
iter: 15183 | loss: 1.899296
iter: 15184 | loss: 1.899103
iter: 15185 | loss: 1.898909
iter: 15186 | loss: 1.898716
iter: 15187 | loss: 1.898523
iter: 15188 | loss: 1.898329
iter: 15189 | loss: 1.898136
iter: 15190 | loss: 1.897943
iter: 15191 | loss: 1.897749
iter: 15192 | loss: 1.897556
iter: 15193 | loss: 1.897362
iter: 15194 | loss: 1.897169
iter: 15195 | loss: 1.896976
iter: 15196 | loss: 1.896782
iter: 15197 | loss: 1.896589
iter: 15198 | loss: 1.896395
iter: 15199 | loss: 1.896202
iter: 15200 | loss: 1.896009
iter: 15201 | loss: 1.895815
iter: 15202 | loss: 1.895622
iter: 15203 | loss: 1.895428
iter: 15204 | loss: 1.895235
iter: 15205 | loss: 1.895042
iter: 15206 | loss: 1.894848
iter: 15207 | loss: 1.894655
iter: 15208 | loss: 1.894462
iter: 15209 | loss: 1.894268
iter: 15210 | loss: 1.894075
iter: 15211 | loss: 1.893881
iter: 15212 | loss: 1.893688
iter: 15213 | loss: 1.893495
iter: 15214 | loss: 1.893301
iter: 15215 | loss: 1.893108
iter: 15216 | loss: 1.892914
iter: 15217 | loss: 1.892721
iter: 15218 | loss: 1.892528
iter: 15219 | loss: 1.892334
iter: 15220 | loss: 1.892141
iter: 15221 | loss: 1.891948
iter: 15222 | loss: 1.891754
iter: 15223 | loss: 1.891561
iter: 15224 | loss: 1.891367
iter: 15225 | loss: 1.891174
iter: 15226 | loss: 1.890981
iter: 15227 | loss: 1.890787
iter: 15228 | loss: 1.890594
iter: 15229 | loss: 1.890400
iter: 15230 | loss: 1.890207
iter: 15231 | loss: 1.890014
iter: 15232 | loss: 1.889820
iter: 15233 | loss: 1.889627
iter: 15234 | loss: 1.889433
iter: 15235 | loss: 1.889240
iter: 15236 | loss: 1.889047
iter: 15237 | loss: 1.888853
iter: 15238 | loss: 1.888660
iter: 15239 | loss: 1.888467
iter: 15240 | loss: 1.888273
iter: 15241 | loss: 1.888080
iter: 15242 | loss: 1.887886
iter: 15243 | loss: 1.887693
iter: 15244 | loss: 1.887500
iter: 15245 | loss: 1.887306
iter: 15246 | loss: 1.887113
iter: 15247 | loss: 1.886919
iter: 15248 | loss: 1.886726
iter: 15249 | loss: 1.886533
iter: 15250 | loss: 1.886339
iter: 15251 | loss: 1.886146
iter: 15252 | loss: 1.885953
iter: 15253 | loss: 1.885759
iter: 15254 | loss: 1.885566
iter: 15255 | loss: 1.885372
iter: 15256 | loss: 1.885179
iter: 15257 | loss: 1.884986
iter: 15258 | loss: 1.884792
iter: 15259 | loss: 1.884599
iter: 15260 | loss: 1.884405
iter: 15261 | loss: 1.884212
iter: 15262 | loss: 1.884019
iter: 15263 | loss: 1.883825
iter: 15264 | loss: 1.883632
iter: 15265 | loss: 1.883438
iter: 15266 | loss: 1.883245
iter: 15267 | loss: 1.883052
iter: 15268 | loss: 1.882858
iter: 15269 | loss: 1.882665
iter: 15270 | loss: 1.882472
iter: 15271 | loss: 1.882278
iter: 15272 | loss: 1.882085
iter: 15273 | loss: 1.881891
iter: 15274 | loss: 1.881698
iter: 15275 | loss: 1.881505
iter: 15276 | loss: 1.881311
iter: 15277 | loss: 1.881118
iter: 15278 | loss: 1.880924
iter: 15279 | loss: 1.880731
iter: 15280 | loss: 1.880538
iter: 15281 | loss: 1.880344
iter: 15282 | loss: 1.880151
iter: 15283 | loss: 1.879958
iter: 15284 | loss: 1.879764
iter: 15285 | loss: 1.879571
iter: 15286 | loss: 1.879377
iter: 15287 | loss: 1.879184
iter: 15288 | loss: 1.878991
iter: 15289 | loss: 1.878797
iter: 15290 | loss: 1.878604
iter: 15291 | loss: 1.878410
iter: 15292 | loss: 1.878217
iter: 15293 | loss: 1.878024
iter: 15294 | loss: 1.877830
iter: 15295 | loss: 1.877637
iter: 15296 | loss: 1.877443
iter: 15297 | loss: 1.877250
iter: 15298 | loss: 1.877057
iter: 15299 | loss: 1.876863
iter: 15300 | loss: 1.876670
iter: 15301 | loss: 1.876477
iter: 15302 | loss: 1.876283
iter: 15303 | loss: 1.876090
iter: 15304 | loss: 1.875896
iter: 15305 | loss: 1.875703
iter: 15306 | loss: 1.875510
iter: 15307 | loss: 1.875316
iter: 15308 | loss: 1.875123
iter: 15309 | loss: 1.874929
iter: 15310 | loss: 1.874736
iter: 15311 | loss: 1.874543
iter: 15312 | loss: 1.874349
iter: 15313 | loss: 1.874156
iter: 15314 | loss: 1.873963
iter: 15315 | loss: 1.873769
iter: 15316 | loss: 1.873576
iter: 15317 | loss: 1.873382
iter: 15318 | loss: 1.873189
iter: 15319 | loss: 1.872996
iter: 15320 | loss: 1.872802
iter: 15321 | loss: 1.872609
iter: 15322 | loss: 1.872415
iter: 15323 | loss: 1.872222
iter: 15324 | loss: 1.872029
iter: 15325 | loss: 1.871835
iter: 15326 | loss: 1.871642
iter: 15327 | loss: 1.871448
iter: 15328 | loss: 1.871255
iter: 15329 | loss: 1.871062
iter: 15330 | loss: 1.870868
iter: 15331 | loss: 1.870675
iter: 15332 | loss: 1.870482
iter: 15333 | loss: 1.870288
iter: 15334 | loss: 1.870095
iter: 15335 | loss: 1.869901
iter: 15336 | loss: 1.869708
iter: 15337 | loss: 1.869515
iter: 15338 | loss: 1.869321
iter: 15339 | loss: 1.869128
iter: 15340 | loss: 1.868934
iter: 15341 | loss: 1.868741
iter: 15342 | loss: 1.868548
iter: 15343 | loss: 1.868354
iter: 15344 | loss: 1.868161
iter: 15345 | loss: 1.867968
iter: 15346 | loss: 1.867774
iter: 15347 | loss: 1.867581
iter: 15348 | loss: 1.867387
iter: 15349 | loss: 1.867194
iter: 15350 | loss: 1.867001
iter: 15351 | loss: 1.866807
iter: 15352 | loss: 1.866614
iter: 15353 | loss: 1.866420
iter: 15354 | loss: 1.866227
iter: 15355 | loss: 1.866034
iter: 15356 | loss: 1.865840
iter: 15357 | loss: 1.865647
iter: 15358 | loss: 1.865453
iter: 15359 | loss: 1.865260
iter: 15360 | loss: 1.865067
iter: 15361 | loss: 1.864873
iter: 15362 | loss: 1.864680
iter: 15363 | loss: 1.864487
iter: 15364 | loss: 1.864293
iter: 15365 | loss: 1.864100
iter: 15366 | loss: 1.863906
iter: 15367 | loss: 1.863713
iter: 15368 | loss: 1.863520
iter: 15369 | loss: 1.863326
iter: 15370 | loss: 1.863133
iter: 15371 | loss: 1.862939
iter: 15372 | loss: 1.862746
iter: 15373 | loss: 1.862553
iter: 15374 | loss: 1.862359
iter: 15375 | loss: 1.862166
iter: 15376 | loss: 1.861973
iter: 15377 | loss: 1.861779
iter: 15378 | loss: 1.861586
iter: 15379 | loss: 1.861392
iter: 15380 | loss: 1.861199
iter: 15381 | loss: 1.861006
iter: 15382 | loss: 1.860812
iter: 15383 | loss: 1.860619
iter: 15384 | loss: 1.860425
iter: 15385 | loss: 1.860232
iter: 15386 | loss: 1.860039
iter: 15387 | loss: 1.859845
iter: 15388 | loss: 1.859652
iter: 15389 | loss: 1.859458
iter: 15390 | loss: 1.859265
iter: 15391 | loss: 1.859072
iter: 15392 | loss: 1.858878
iter: 15393 | loss: 1.858685
iter: 15394 | loss: 1.858492
iter: 15395 | loss: 1.858298
iter: 15396 | loss: 1.858105
iter: 15397 | loss: 1.857911
iter: 15398 | loss: 1.857718
iter: 15399 | loss: 1.857525
iter: 15400 | loss: 1.857331
iter: 15401 | loss: 1.857138
iter: 15402 | loss: 1.856944
iter: 15403 | loss: 1.856751
iter: 15404 | loss: 1.856558
iter: 15405 | loss: 1.856364
iter: 15406 | loss: 1.856171
iter: 15407 | loss: 1.855978
iter: 15408 | loss: 1.855784
iter: 15409 | loss: 1.855591
iter: 15410 | loss: 1.855397
iter: 15411 | loss: 1.855204
iter: 15412 | loss: 1.855011
iter: 15413 | loss: 1.854817
iter: 15414 | loss: 1.854624
iter: 15415 | loss: 1.854430
iter: 15416 | loss: 1.854237
iter: 15417 | loss: 1.854044
iter: 15418 | loss: 1.853850
iter: 15419 | loss: 1.853657
iter: 15420 | loss: 1.853463
iter: 15421 | loss: 1.853270
iter: 15422 | loss: 1.853077
iter: 15423 | loss: 1.852883
iter: 15424 | loss: 1.852690
iter: 15425 | loss: 1.852497
iter: 15426 | loss: 1.852303
iter: 15427 | loss: 1.852110
iter: 15428 | loss: 1.851916
iter: 15429 | loss: 1.851723
iter: 15430 | loss: 1.851530
iter: 15431 | loss: 1.851336
iter: 15432 | loss: 1.851143
iter: 15433 | loss: 1.850949
iter: 15434 | loss: 1.850756
iter: 15435 | loss: 1.850563
iter: 15436 | loss: 1.850369
iter: 15437 | loss: 1.850176
iter: 15438 | loss: 1.849983
iter: 15439 | loss: 1.849789
iter: 15440 | loss: 1.849596
iter: 15441 | loss: 1.849402
iter: 15442 | loss: 1.849209
iter: 15443 | loss: 1.849016
iter: 15444 | loss: 1.848822
iter: 15445 | loss: 1.848629
iter: 15446 | loss: 1.848435
iter: 15447 | loss: 1.848242
iter: 15448 | loss: 1.848049
iter: 15449 | loss: 1.847855
iter: 15450 | loss: 1.847662
iter: 15451 | loss: 1.847468
iter: 15452 | loss: 1.847275
iter: 15453 | loss: 1.847082
iter: 15454 | loss: 1.846888
iter: 15455 | loss: 1.846695
iter: 15456 | loss: 1.846502
iter: 15457 | loss: 1.846308
iter: 15458 | loss: 1.846115
iter: 15459 | loss: 1.845921
iter: 15460 | loss: 1.845728
iter: 15461 | loss: 1.845535
iter: 15462 | loss: 1.845341
iter: 15463 | loss: 1.845148
iter: 15464 | loss: 1.844954
iter: 15465 | loss: 1.844761
iter: 15466 | loss: 1.844568
iter: 15467 | loss: 1.844374
iter: 15468 | loss: 1.844181
iter: 15469 | loss: 1.843988
iter: 15470 | loss: 1.843794
iter: 15471 | loss: 1.843601
iter: 15472 | loss: 1.843407
iter: 15473 | loss: 1.843214
iter: 15474 | loss: 1.843021
iter: 15475 | loss: 1.842827
iter: 15476 | loss: 1.842634
iter: 15477 | loss: 1.842440
iter: 15478 | loss: 1.842247
iter: 15479 | loss: 1.842054
iter: 15480 | loss: 1.841860
iter: 15481 | loss: 1.841667
iter: 15482 | loss: 1.841473
iter: 15483 | loss: 1.841280
iter: 15484 | loss: 1.841087
iter: 15485 | loss: 1.840893
iter: 15486 | loss: 1.840700
iter: 15487 | loss: 1.840507
iter: 15488 | loss: 1.840313
iter: 15489 | loss: 1.840120
iter: 15490 | loss: 1.839926
iter: 15491 | loss: 1.839733
iter: 15492 | loss: 1.839540
iter: 15493 | loss: 1.839346
iter: 15494 | loss: 1.839153
iter: 15495 | loss: 1.838959
iter: 15496 | loss: 1.838766
iter: 15497 | loss: 1.838573
iter: 15498 | loss: 1.838379
iter: 15499 | loss: 1.838186
iter: 15500 | loss: 1.837993
iter: 15501 | loss: 1.837799
iter: 15502 | loss: 1.837606
iter: 15503 | loss: 1.837412
iter: 15504 | loss: 1.837219
iter: 15505 | loss: 1.837026
iter: 15506 | loss: 1.836832
iter: 15507 | loss: 1.836639
iter: 15508 | loss: 1.836445
iter: 15509 | loss: 1.836252
iter: 15510 | loss: 1.836059
iter: 15511 | loss: 1.835865
iter: 15512 | loss: 1.835672
iter: 15513 | loss: 1.835479
iter: 15514 | loss: 1.835285
iter: 15515 | loss: 1.835092
iter: 15516 | loss: 1.834898
iter: 15517 | loss: 1.834705
iter: 15518 | loss: 1.834512
iter: 15519 | loss: 1.834318
iter: 15520 | loss: 1.834125
iter: 15521 | loss: 1.833931
iter: 15522 | loss: 1.833738
iter: 15523 | loss: 1.833545
iter: 15524 | loss: 1.833351
iter: 15525 | loss: 1.833158
iter: 15526 | loss: 1.832964
iter: 15527 | loss: 1.832771
iter: 15528 | loss: 1.832578
iter: 15529 | loss: 1.832384
iter: 15530 | loss: 1.832191
iter: 15531 | loss: 1.831998
iter: 15532 | loss: 1.831804
iter: 15533 | loss: 1.831611
iter: 15534 | loss: 1.831417
iter: 15535 | loss: 1.831224
iter: 15536 | loss: 1.831031
iter: 15537 | loss: 1.830837
iter: 15538 | loss: 1.830644
iter: 15539 | loss: 1.830450
iter: 15540 | loss: 1.830257
iter: 15541 | loss: 1.830064
iter: 15542 | loss: 1.829870
iter: 15543 | loss: 1.829677
iter: 15544 | loss: 1.829484
iter: 15545 | loss: 1.829290
iter: 15546 | loss: 1.829097
iter: 15547 | loss: 1.828903
iter: 15548 | loss: 1.828710
iter: 15549 | loss: 1.828517
iter: 15550 | loss: 1.828323
iter: 15551 | loss: 1.828130
iter: 15552 | loss: 1.827936
iter: 15553 | loss: 1.827743
iter: 15554 | loss: 1.827550
iter: 15555 | loss: 1.827356
iter: 15556 | loss: 1.827163
iter: 15557 | loss: 1.826969
iter: 15558 | loss: 1.826776
iter: 15559 | loss: 1.826583
iter: 15560 | loss: 1.826389
iter: 15561 | loss: 1.826196
iter: 15562 | loss: 1.826003
iter: 15563 | loss: 1.825809
iter: 15564 | loss: 1.825616
iter: 15565 | loss: 1.825422
iter: 15566 | loss: 1.825229
iter: 15567 | loss: 1.825036
iter: 15568 | loss: 1.824842
iter: 15569 | loss: 1.824649
iter: 15570 | loss: 1.824455
iter: 15571 | loss: 1.824262
iter: 15572 | loss: 1.824069
iter: 15573 | loss: 1.823875
iter: 15574 | loss: 1.823682
iter: 15575 | loss: 1.823489
iter: 15576 | loss: 1.823295
iter: 15577 | loss: 1.823102
iter: 15578 | loss: 1.822908
iter: 15579 | loss: 1.822715
iter: 15580 | loss: 1.822522
iter: 15581 | loss: 1.822328
iter: 15582 | loss: 1.822135
iter: 15583 | loss: 1.821941
iter: 15584 | loss: 1.821748
iter: 15585 | loss: 1.821555
iter: 15586 | loss: 1.821361
iter: 15587 | loss: 1.821168
iter: 15588 | loss: 1.820974
iter: 15589 | loss: 1.820781
iter: 15590 | loss: 1.820588
iter: 15591 | loss: 1.820394
iter: 15592 | loss: 1.820201
iter: 15593 | loss: 1.820008
iter: 15594 | loss: 1.819814
iter: 15595 | loss: 1.819621
iter: 15596 | loss: 1.819427
iter: 15597 | loss: 1.819234
iter: 15598 | loss: 1.819041
iter: 15599 | loss: 1.818847
iter: 15600 | loss: 1.818654
iter: 15601 | loss: 1.818460
iter: 15602 | loss: 1.818267
iter: 15603 | loss: 1.818074
iter: 15604 | loss: 1.817880
iter: 15605 | loss: 1.817687
iter: 15606 | loss: 1.817494
iter: 15607 | loss: 1.817300
iter: 15608 | loss: 1.817107
iter: 15609 | loss: 1.816913
iter: 15610 | loss: 1.816720
iter: 15611 | loss: 1.816527
iter: 15612 | loss: 1.816333
iter: 15613 | loss: 1.816140
iter: 15614 | loss: 1.815946
iter: 15615 | loss: 1.815753
iter: 15616 | loss: 1.815560
iter: 15617 | loss: 1.815366
iter: 15618 | loss: 1.815173
iter: 15619 | loss: 1.814979
iter: 15620 | loss: 1.814786
iter: 15621 | loss: 1.814593
iter: 15622 | loss: 1.814399
iter: 15623 | loss: 1.814206
iter: 15624 | loss: 1.814013
iter: 15625 | loss: 1.813819
iter: 15626 | loss: 1.813626
iter: 15627 | loss: 1.813432
iter: 15628 | loss: 1.813239
iter: 15629 | loss: 1.813046
iter: 15630 | loss: 1.812852
iter: 15631 | loss: 1.812659
iter: 15632 | loss: 1.812465
iter: 15633 | loss: 1.812272
iter: 15634 | loss: 1.812079
iter: 15635 | loss: 1.811885
iter: 15636 | loss: 1.811692
iter: 15637 | loss: 1.811499
iter: 15638 | loss: 1.811305
iter: 15639 | loss: 1.811112
iter: 15640 | loss: 1.810918
iter: 15641 | loss: 1.810725
iter: 15642 | loss: 1.810532
iter: 15643 | loss: 1.810338
iter: 15644 | loss: 1.810145
iter: 15645 | loss: 1.809951
iter: 15646 | loss: 1.809758
iter: 15647 | loss: 1.809565
iter: 15648 | loss: 1.809371
iter: 15649 | loss: 1.809178
iter: 15650 | loss: 1.808984
iter: 15651 | loss: 1.808791
iter: 15652 | loss: 1.808598
iter: 15653 | loss: 1.808404
iter: 15654 | loss: 1.808211
iter: 15655 | loss: 1.808018
iter: 15656 | loss: 1.807824
iter: 15657 | loss: 1.807631
iter: 15658 | loss: 1.807437
iter: 15659 | loss: 1.807244
iter: 15660 | loss: 1.807051
iter: 15661 | loss: 1.806857
iter: 15662 | loss: 1.806664
iter: 15663 | loss: 1.806470
iter: 15664 | loss: 1.806277
iter: 15665 | loss: 1.806084
iter: 15666 | loss: 1.805890
iter: 15667 | loss: 1.805697
iter: 15668 | loss: 1.805504
iter: 15669 | loss: 1.805310
iter: 15670 | loss: 1.805117
iter: 15671 | loss: 1.804923
iter: 15672 | loss: 1.804730
iter: 15673 | loss: 1.804537
iter: 15674 | loss: 1.804343
iter: 15675 | loss: 1.804150
iter: 15676 | loss: 1.803956
iter: 15677 | loss: 1.803763
iter: 15678 | loss: 1.803570
iter: 15679 | loss: 1.803376
iter: 15680 | loss: 1.803183
iter: 15681 | loss: 1.802989
iter: 15682 | loss: 1.802796
iter: 15683 | loss: 1.802603
iter: 15684 | loss: 1.802409
iter: 15685 | loss: 1.802216
iter: 15686 | loss: 1.802023
iter: 15687 | loss: 1.801829
iter: 15688 | loss: 1.801636
iter: 15689 | loss: 1.801442
iter: 15690 | loss: 1.801249
iter: 15691 | loss: 1.801056
iter: 15692 | loss: 1.800862
iter: 15693 | loss: 1.800669
iter: 15694 | loss: 1.800475
iter: 15695 | loss: 1.800282
iter: 15696 | loss: 1.800089
iter: 15697 | loss: 1.799895
iter: 15698 | loss: 1.799702
iter: 15699 | loss: 1.799509
iter: 15700 | loss: 1.799315
iter: 15701 | loss: 1.799122
iter: 15702 | loss: 1.798928
iter: 15703 | loss: 1.798735
iter: 15704 | loss: 1.798542
iter: 15705 | loss: 1.798348
iter: 15706 | loss: 1.798155
iter: 15707 | loss: 1.797961
iter: 15708 | loss: 1.797768
iter: 15709 | loss: 1.797575
iter: 15710 | loss: 1.797381
iter: 15711 | loss: 1.797188
iter: 15712 | loss: 1.796994
iter: 15713 | loss: 1.796801
iter: 15714 | loss: 1.796608
iter: 15715 | loss: 1.796414
iter: 15716 | loss: 1.796221
iter: 15717 | loss: 1.796028
iter: 15718 | loss: 1.795834
iter: 15719 | loss: 1.795641
iter: 15720 | loss: 1.795447
iter: 15721 | loss: 1.795254
iter: 15722 | loss: 1.795061
iter: 15723 | loss: 1.794867
iter: 15724 | loss: 1.794674
iter: 15725 | loss: 1.794480
iter: 15726 | loss: 1.794287
iter: 15727 | loss: 1.794094
iter: 15728 | loss: 1.793900
iter: 15729 | loss: 1.793707
iter: 15730 | loss: 1.793514
iter: 15731 | loss: 1.793320
iter: 15732 | loss: 1.793127
iter: 15733 | loss: 1.792933
iter: 15734 | loss: 1.792740
iter: 15735 | loss: 1.792547
iter: 15736 | loss: 1.792353
iter: 15737 | loss: 1.792160
iter: 15738 | loss: 1.791966
iter: 15739 | loss: 1.791773
iter: 15740 | loss: 1.791580
iter: 15741 | loss: 1.791386
iter: 15742 | loss: 1.791193
iter: 15743 | loss: 1.790999
iter: 15744 | loss: 1.790806
iter: 15745 | loss: 1.790613
iter: 15746 | loss: 1.790419
iter: 15747 | loss: 1.790226
iter: 15748 | loss: 1.790033
iter: 15749 | loss: 1.789839
iter: 15750 | loss: 1.789646
iter: 15751 | loss: 1.789452
iter: 15752 | loss: 1.789259
iter: 15753 | loss: 1.789066
iter: 15754 | loss: 1.788872
iter: 15755 | loss: 1.788679
iter: 15756 | loss: 1.788485
iter: 15757 | loss: 1.788292
iter: 15758 | loss: 1.788099
iter: 15759 | loss: 1.787905
iter: 15760 | loss: 1.787712
iter: 15761 | loss: 1.787519
iter: 15762 | loss: 1.787325
iter: 15763 | loss: 1.787132
iter: 15764 | loss: 1.786938
iter: 15765 | loss: 1.786745
iter: 15766 | loss: 1.786552
iter: 15767 | loss: 1.786358
iter: 15768 | loss: 1.786165
iter: 15769 | loss: 1.785971
iter: 15770 | loss: 1.785778
iter: 15771 | loss: 1.785585
iter: 15772 | loss: 1.785391
iter: 15773 | loss: 1.785198
iter: 15774 | loss: 1.785004
iter: 15775 | loss: 1.784811
iter: 15776 | loss: 1.784618
iter: 15777 | loss: 1.784424
iter: 15778 | loss: 1.784231
iter: 15779 | loss: 1.784038
iter: 15780 | loss: 1.783844
iter: 15781 | loss: 1.783651
iter: 15782 | loss: 1.783457
iter: 15783 | loss: 1.783264
iter: 15784 | loss: 1.783071
iter: 15785 | loss: 1.782877
iter: 15786 | loss: 1.782684
iter: 15787 | loss: 1.782490
iter: 15788 | loss: 1.782297
iter: 15789 | loss: 1.782104
iter: 15790 | loss: 1.781910
iter: 15791 | loss: 1.781717
iter: 15792 | loss: 1.781524
iter: 15793 | loss: 1.781330
iter: 15794 | loss: 1.781137
iter: 15795 | loss: 1.780943
iter: 15796 | loss: 1.780750
iter: 15797 | loss: 1.780557
iter: 15798 | loss: 1.780363
iter: 15799 | loss: 1.780170
iter: 15800 | loss: 1.779976
iter: 15801 | loss: 1.779783
iter: 15802 | loss: 1.779590
iter: 15803 | loss: 1.779396
iter: 15804 | loss: 1.779203
iter: 15805 | loss: 1.779009
iter: 15806 | loss: 1.778816
iter: 15807 | loss: 1.778623
iter: 15808 | loss: 1.778429
iter: 15809 | loss: 1.778236
iter: 15810 | loss: 1.778043
iter: 15811 | loss: 1.777849
iter: 15812 | loss: 1.777656
iter: 15813 | loss: 1.777462
iter: 15814 | loss: 1.777269
iter: 15815 | loss: 1.777076
iter: 15816 | loss: 1.776882
iter: 15817 | loss: 1.776689
iter: 15818 | loss: 1.776495
iter: 15819 | loss: 1.776302
iter: 15820 | loss: 1.776109
iter: 15821 | loss: 1.775915
iter: 15822 | loss: 1.775722
iter: 15823 | loss: 1.775529
iter: 15824 | loss: 1.775335
iter: 15825 | loss: 1.775142
iter: 15826 | loss: 1.774948
iter: 15827 | loss: 1.774755
iter: 15828 | loss: 1.774562
iter: 15829 | loss: 1.774368
iter: 15830 | loss: 1.774175
iter: 15831 | loss: 1.773981
iter: 15832 | loss: 1.773788
iter: 15833 | loss: 1.773595
iter: 15834 | loss: 1.773401
iter: 15835 | loss: 1.773208
iter: 15836 | loss: 1.773015
iter: 15837 | loss: 1.772821
iter: 15838 | loss: 1.772628
iter: 15839 | loss: 1.772434
iter: 15840 | loss: 1.772241
iter: 15841 | loss: 1.772048
iter: 15842 | loss: 1.771854
iter: 15843 | loss: 1.771661
iter: 15844 | loss: 1.771467
iter: 15845 | loss: 1.771274
iter: 15846 | loss: 1.771081
iter: 15847 | loss: 1.770887
iter: 15848 | loss: 1.770694
iter: 15849 | loss: 1.770500
iter: 15850 | loss: 1.770307
iter: 15851 | loss: 1.770114
iter: 15852 | loss: 1.769920
iter: 15853 | loss: 1.769727
iter: 15854 | loss: 1.769534
iter: 15855 | loss: 1.769340
iter: 15856 | loss: 1.769147
iter: 15857 | loss: 1.768953
iter: 15858 | loss: 1.768760
iter: 15859 | loss: 1.768567
iter: 15860 | loss: 1.768373
iter: 15861 | loss: 1.768180
iter: 15862 | loss: 1.767986
iter: 15863 | loss: 1.767793
iter: 15864 | loss: 1.767600
iter: 15865 | loss: 1.767406
iter: 15866 | loss: 1.767213
iter: 15867 | loss: 1.767020
iter: 15868 | loss: 1.766826
iter: 15869 | loss: 1.766633
iter: 15870 | loss: 1.766439
iter: 15871 | loss: 1.766246
iter: 15872 | loss: 1.766053
iter: 15873 | loss: 1.765859
iter: 15874 | loss: 1.765666
iter: 15875 | loss: 1.765472
iter: 15876 | loss: 1.765279
iter: 15877 | loss: 1.765086
iter: 15878 | loss: 1.764892
iter: 15879 | loss: 1.764699
iter: 15880 | loss: 1.764505
iter: 15881 | loss: 1.764312
iter: 15882 | loss: 1.764119
iter: 15883 | loss: 1.763925
iter: 15884 | loss: 1.763732
iter: 15885 | loss: 1.763539
iter: 15886 | loss: 1.763345
iter: 15887 | loss: 1.763152
iter: 15888 | loss: 1.762958
iter: 15889 | loss: 1.762765
iter: 15890 | loss: 1.762572
iter: 15891 | loss: 1.762378
iter: 15892 | loss: 1.762185
iter: 15893 | loss: 1.761991
iter: 15894 | loss: 1.761798
iter: 15895 | loss: 1.761605
iter: 15896 | loss: 1.761411
iter: 15897 | loss: 1.761218
iter: 15898 | loss: 1.761025
iter: 15899 | loss: 1.760831
iter: 15900 | loss: 1.760638
iter: 15901 | loss: 1.760444
iter: 15902 | loss: 1.760251
iter: 15903 | loss: 1.760058
iter: 15904 | loss: 1.759864
iter: 15905 | loss: 1.759671
iter: 15906 | loss: 1.759477
iter: 15907 | loss: 1.759284
iter: 15908 | loss: 1.759091
iter: 15909 | loss: 1.758897
iter: 15910 | loss: 1.758704
iter: 15911 | loss: 1.758510
iter: 15912 | loss: 1.758317
iter: 15913 | loss: 1.758124
iter: 15914 | loss: 1.757930
iter: 15915 | loss: 1.757737
iter: 15916 | loss: 1.757544
iter: 15917 | loss: 1.757350
iter: 15918 | loss: 1.757157
iter: 15919 | loss: 1.756963
iter: 15920 | loss: 1.756770
iter: 15921 | loss: 1.756577
iter: 15922 | loss: 1.756383
iter: 15923 | loss: 1.756190
iter: 15924 | loss: 1.755996
iter: 15925 | loss: 1.755803
iter: 15926 | loss: 1.755610
iter: 15927 | loss: 1.755416
iter: 15928 | loss: 1.755223
iter: 15929 | loss: 1.755030
iter: 15930 | loss: 1.754836
iter: 15931 | loss: 1.754643
iter: 15932 | loss: 1.754449
iter: 15933 | loss: 1.754256
iter: 15934 | loss: 1.754063
iter: 15935 | loss: 1.753869
iter: 15936 | loss: 1.753676
iter: 15937 | loss: 1.753482
iter: 15938 | loss: 1.753289
iter: 15939 | loss: 1.753096
iter: 15940 | loss: 1.752902
iter: 15941 | loss: 1.752709
iter: 15942 | loss: 1.752515
iter: 15943 | loss: 1.752322
iter: 15944 | loss: 1.752129
iter: 15945 | loss: 1.751935
iter: 15946 | loss: 1.751742
iter: 15947 | loss: 1.751549
iter: 15948 | loss: 1.751355
iter: 15949 | loss: 1.751162
iter: 15950 | loss: 1.750968
iter: 15951 | loss: 1.750775
iter: 15952 | loss: 1.750582
iter: 15953 | loss: 1.750388
iter: 15954 | loss: 1.750195
iter: 15955 | loss: 1.750001
iter: 15956 | loss: 1.749808
iter: 15957 | loss: 1.749615
iter: 15958 | loss: 1.749421
iter: 15959 | loss: 1.749228
iter: 15960 | loss: 1.749035
iter: 15961 | loss: 1.748841
iter: 15962 | loss: 1.748648
iter: 15963 | loss: 1.748454
iter: 15964 | loss: 1.748261
iter: 15965 | loss: 1.748068
iter: 15966 | loss: 1.747874
iter: 15967 | loss: 1.747681
iter: 15968 | loss: 1.747487
iter: 15969 | loss: 1.747294
iter: 15970 | loss: 1.747101
iter: 15971 | loss: 1.746907
iter: 15972 | loss: 1.746714
iter: 15973 | loss: 1.746520
iter: 15974 | loss: 1.746327
iter: 15975 | loss: 1.746134
iter: 15976 | loss: 1.745940
iter: 15977 | loss: 1.745747
iter: 15978 | loss: 1.745554
iter: 15979 | loss: 1.745360
iter: 15980 | loss: 1.745167
iter: 15981 | loss: 1.744973
iter: 15982 | loss: 1.744780
iter: 15983 | loss: 1.744587
iter: 15984 | loss: 1.744393
iter: 15985 | loss: 1.744200
iter: 15986 | loss: 1.744006
iter: 15987 | loss: 1.743813
iter: 15988 | loss: 1.743620
iter: 15989 | loss: 1.743426
iter: 15990 | loss: 1.743233
iter: 15991 | loss: 1.743040
iter: 15992 | loss: 1.742846
iter: 15993 | loss: 1.742653
iter: 15994 | loss: 1.742459
iter: 15995 | loss: 1.742266
iter: 15996 | loss: 1.742073
iter: 15997 | loss: 1.741879
iter: 15998 | loss: 1.741686
iter: 15999 | loss: 1.741492
iter: 16000 | loss: 1.741299
iter: 16001 | loss: 1.741106
iter: 16002 | loss: 1.740912
iter: 16003 | loss: 1.740719
iter: 16004 | loss: 1.740525
iter: 16005 | loss: 1.740332
iter: 16006 | loss: 1.740139
iter: 16007 | loss: 1.739945
iter: 16008 | loss: 1.739752
iter: 16009 | loss: 1.739559
iter: 16010 | loss: 1.739365
iter: 16011 | loss: 1.739172
iter: 16012 | loss: 1.738978
iter: 16013 | loss: 1.738785
iter: 16014 | loss: 1.738592
iter: 16015 | loss: 1.738398
iter: 16016 | loss: 1.738205
iter: 16017 | loss: 1.738011
iter: 16018 | loss: 1.737818
iter: 16019 | loss: 1.737625
iter: 16020 | loss: 1.737431
iter: 16021 | loss: 1.737238
iter: 16022 | loss: 1.737045
iter: 16023 | loss: 1.736851
iter: 16024 | loss: 1.736658
iter: 16025 | loss: 1.736464
iter: 16026 | loss: 1.736271
iter: 16027 | loss: 1.736078
iter: 16028 | loss: 1.735884
iter: 16029 | loss: 1.735691
iter: 16030 | loss: 1.735497
iter: 16031 | loss: 1.735304
iter: 16032 | loss: 1.735111
iter: 16033 | loss: 1.734917
iter: 16034 | loss: 1.734724
iter: 16035 | loss: 1.734530
iter: 16036 | loss: 1.734337
iter: 16037 | loss: 1.734144
iter: 16038 | loss: 1.733950
iter: 16039 | loss: 1.733757
iter: 16040 | loss: 1.733564
iter: 16041 | loss: 1.733370
iter: 16042 | loss: 1.733177
iter: 16043 | loss: 1.732983
iter: 16044 | loss: 1.732790
iter: 16045 | loss: 1.732597
iter: 16046 | loss: 1.732403
iter: 16047 | loss: 1.732210
iter: 16048 | loss: 1.732016
iter: 16049 | loss: 1.731823
iter: 16050 | loss: 1.731630
iter: 16051 | loss: 1.731436
iter: 16052 | loss: 1.731243
iter: 16053 | loss: 1.731050
iter: 16054 | loss: 1.730856
iter: 16055 | loss: 1.730663
iter: 16056 | loss: 1.730469
iter: 16057 | loss: 1.730276
iter: 16058 | loss: 1.730083
iter: 16059 | loss: 1.729889
iter: 16060 | loss: 1.729696
iter: 16061 | loss: 1.729502
iter: 16062 | loss: 1.729309
iter: 16063 | loss: 1.729116
iter: 16064 | loss: 1.728922
iter: 16065 | loss: 1.728729
iter: 16066 | loss: 1.728535
iter: 16067 | loss: 1.728342
iter: 16068 | loss: 1.728149
iter: 16069 | loss: 1.727955
iter: 16070 | loss: 1.727762
iter: 16071 | loss: 1.727569
iter: 16072 | loss: 1.727375
iter: 16073 | loss: 1.727182
iter: 16074 | loss: 1.726988
iter: 16075 | loss: 1.726795
iter: 16076 | loss: 1.726602
iter: 16077 | loss: 1.726408
iter: 16078 | loss: 1.726215
iter: 16079 | loss: 1.726021
iter: 16080 | loss: 1.725828
iter: 16081 | loss: 1.725635
iter: 16082 | loss: 1.725441
iter: 16083 | loss: 1.725248
iter: 16084 | loss: 1.725055
iter: 16085 | loss: 1.724861
iter: 16086 | loss: 1.724668
iter: 16087 | loss: 1.724474
iter: 16088 | loss: 1.724281
iter: 16089 | loss: 1.724088
iter: 16090 | loss: 1.723894
iter: 16091 | loss: 1.723701
iter: 16092 | loss: 1.723507
iter: 16093 | loss: 1.723314
iter: 16094 | loss: 1.723121
iter: 16095 | loss: 1.722927
iter: 16096 | loss: 1.722734
iter: 16097 | loss: 1.722540
iter: 16098 | loss: 1.722347
iter: 16099 | loss: 1.722154
iter: 16100 | loss: 1.721960
iter: 16101 | loss: 1.721767
iter: 16102 | loss: 1.721574
iter: 16103 | loss: 1.721380
iter: 16104 | loss: 1.721187
iter: 16105 | loss: 1.720993
iter: 16106 | loss: 1.720800
iter: 16107 | loss: 1.720607
iter: 16108 | loss: 1.720413
iter: 16109 | loss: 1.720220
iter: 16110 | loss: 1.720026
iter: 16111 | loss: 1.719833
iter: 16112 | loss: 1.719640
iter: 16113 | loss: 1.719446
iter: 16114 | loss: 1.719253
iter: 16115 | loss: 1.719060
iter: 16116 | loss: 1.718866
iter: 16117 | loss: 1.718673
iter: 16118 | loss: 1.718479
iter: 16119 | loss: 1.718286
iter: 16120 | loss: 1.718093
iter: 16121 | loss: 1.717899
iter: 16122 | loss: 1.717706
iter: 16123 | loss: 1.717512
iter: 16124 | loss: 1.717319
iter: 16125 | loss: 1.717126
iter: 16126 | loss: 1.716932
iter: 16127 | loss: 1.716739
iter: 16128 | loss: 1.716546
iter: 16129 | loss: 1.716352
iter: 16130 | loss: 1.716159
iter: 16131 | loss: 1.715965
iter: 16132 | loss: 1.715772
iter: 16133 | loss: 1.715579
iter: 16134 | loss: 1.715385
iter: 16135 | loss: 1.715192
iter: 16136 | loss: 1.714998
iter: 16137 | loss: 1.714805
iter: 16138 | loss: 1.714612
iter: 16139 | loss: 1.714418
iter: 16140 | loss: 1.714225
iter: 16141 | loss: 1.714031
iter: 16142 | loss: 1.713838
iter: 16143 | loss: 1.713645
iter: 16144 | loss: 1.713451
iter: 16145 | loss: 1.713258
iter: 16146 | loss: 1.713065
iter: 16147 | loss: 1.712871
iter: 16148 | loss: 1.712678
iter: 16149 | loss: 1.712484
iter: 16150 | loss: 1.712291
iter: 16151 | loss: 1.712098
iter: 16152 | loss: 1.711904
iter: 16153 | loss: 1.711711
iter: 16154 | loss: 1.711517
iter: 16155 | loss: 1.711324
iter: 16156 | loss: 1.711131
iter: 16157 | loss: 1.710937
iter: 16158 | loss: 1.710744
iter: 16159 | loss: 1.710551
iter: 16160 | loss: 1.710357
iter: 16161 | loss: 1.710164
iter: 16162 | loss: 1.709970
iter: 16163 | loss: 1.709777
iter: 16164 | loss: 1.709584
iter: 16165 | loss: 1.709390
iter: 16166 | loss: 1.709197
iter: 16167 | loss: 1.709003
iter: 16168 | loss: 1.708810
iter: 16169 | loss: 1.708617
iter: 16170 | loss: 1.708423
iter: 16171 | loss: 1.708230
iter: 16172 | loss: 1.708036
iter: 16173 | loss: 1.707843
iter: 16174 | loss: 1.707650
iter: 16175 | loss: 1.707456
iter: 16176 | loss: 1.707263
iter: 16177 | loss: 1.707070
iter: 16178 | loss: 1.706876
iter: 16179 | loss: 1.706683
iter: 16180 | loss: 1.706489
iter: 16181 | loss: 1.706296
iter: 16182 | loss: 1.706103
iter: 16183 | loss: 1.705909
iter: 16184 | loss: 1.705716
iter: 16185 | loss: 1.705522
iter: 16186 | loss: 1.705329
iter: 16187 | loss: 1.705136
iter: 16188 | loss: 1.704942
iter: 16189 | loss: 1.704749
iter: 16190 | loss: 1.704556
iter: 16191 | loss: 1.704362
iter: 16192 | loss: 1.704169
iter: 16193 | loss: 1.703975
iter: 16194 | loss: 1.703782
iter: 16195 | loss: 1.703589
iter: 16196 | loss: 1.703395
iter: 16197 | loss: 1.703202
iter: 16198 | loss: 1.703008
iter: 16199 | loss: 1.702815
iter: 16200 | loss: 1.702622
iter: 16201 | loss: 1.702428
iter: 16202 | loss: 1.702235
iter: 16203 | loss: 1.702041
iter: 16204 | loss: 1.701848
iter: 16205 | loss: 1.701655
iter: 16206 | loss: 1.701461
iter: 16207 | loss: 1.701268
iter: 16208 | loss: 1.701075
iter: 16209 | loss: 1.700881
iter: 16210 | loss: 1.700688
iter: 16211 | loss: 1.700494
iter: 16212 | loss: 1.700301
iter: 16213 | loss: 1.700108
iter: 16214 | loss: 1.699914
iter: 16215 | loss: 1.699721
iter: 16216 | loss: 1.699527
iter: 16217 | loss: 1.699334
iter: 16218 | loss: 1.699141
iter: 16219 | loss: 1.698947
iter: 16220 | loss: 1.698754
iter: 16221 | loss: 1.698561
iter: 16222 | loss: 1.698367
iter: 16223 | loss: 1.698174
iter: 16224 | loss: 1.697980
iter: 16225 | loss: 1.697787
iter: 16226 | loss: 1.697594
iter: 16227 | loss: 1.697400
iter: 16228 | loss: 1.697207
iter: 16229 | loss: 1.697013
iter: 16230 | loss: 1.696820
iter: 16231 | loss: 1.696627
iter: 16232 | loss: 1.696433
iter: 16233 | loss: 1.696240
iter: 16234 | loss: 1.696046
iter: 16235 | loss: 1.695853
iter: 16236 | loss: 1.695660
iter: 16237 | loss: 1.695466
iter: 16238 | loss: 1.695273
iter: 16239 | loss: 1.695080
iter: 16240 | loss: 1.694886
iter: 16241 | loss: 1.694693
iter: 16242 | loss: 1.694499
iter: 16243 | loss: 1.694306
iter: 16244 | loss: 1.694113
iter: 16245 | loss: 1.693919
iter: 16246 | loss: 1.693726
iter: 16247 | loss: 1.693532
iter: 16248 | loss: 1.693339
iter: 16249 | loss: 1.693146
iter: 16250 | loss: 1.692952
iter: 16251 | loss: 1.692759
iter: 16252 | loss: 1.692566
iter: 16253 | loss: 1.692372
iter: 16254 | loss: 1.692179
iter: 16255 | loss: 1.691985
iter: 16256 | loss: 1.691792
iter: 16257 | loss: 1.691599
iter: 16258 | loss: 1.691405
iter: 16259 | loss: 1.691212
iter: 16260 | loss: 1.691018
iter: 16261 | loss: 1.690825
iter: 16262 | loss: 1.690632
iter: 16263 | loss: 1.690438
iter: 16264 | loss: 1.690245
iter: 16265 | loss: 1.690051
iter: 16266 | loss: 1.689858
iter: 16267 | loss: 1.689665
iter: 16268 | loss: 1.689471
iter: 16269 | loss: 1.689278
iter: 16270 | loss: 1.689085
iter: 16271 | loss: 1.688891
iter: 16272 | loss: 1.688698
iter: 16273 | loss: 1.688504
iter: 16274 | loss: 1.688311
iter: 16275 | loss: 1.688118
iter: 16276 | loss: 1.687924
iter: 16277 | loss: 1.687731
iter: 16278 | loss: 1.687537
iter: 16279 | loss: 1.687344
iter: 16280 | loss: 1.687151
iter: 16281 | loss: 1.686957
iter: 16282 | loss: 1.686764
iter: 16283 | loss: 1.686571
iter: 16284 | loss: 1.686377
iter: 16285 | loss: 1.686184
iter: 16286 | loss: 1.685990
iter: 16287 | loss: 1.685797
iter: 16288 | loss: 1.685604
iter: 16289 | loss: 1.685410
iter: 16290 | loss: 1.685217
iter: 16291 | loss: 1.685023
iter: 16292 | loss: 1.684830
iter: 16293 | loss: 1.684637
iter: 16294 | loss: 1.684443
iter: 16295 | loss: 1.684250
iter: 16296 | loss: 1.684056
iter: 16297 | loss: 1.683863
iter: 16298 | loss: 1.683670
iter: 16299 | loss: 1.683476
iter: 16300 | loss: 1.683283
iter: 16301 | loss: 1.683090
iter: 16302 | loss: 1.682896
iter: 16303 | loss: 1.682703
iter: 16304 | loss: 1.682509
iter: 16305 | loss: 1.682316
iter: 16306 | loss: 1.682123
iter: 16307 | loss: 1.681929
iter: 16308 | loss: 1.681736
iter: 16309 | loss: 1.681542
iter: 16310 | loss: 1.681349
iter: 16311 | loss: 1.681156
iter: 16312 | loss: 1.680962
iter: 16313 | loss: 1.680769
iter: 16314 | loss: 1.680576
iter: 16315 | loss: 1.680382
iter: 16316 | loss: 1.680189
iter: 16317 | loss: 1.679995
iter: 16318 | loss: 1.679802
iter: 16319 | loss: 1.679609
iter: 16320 | loss: 1.679415
iter: 16321 | loss: 1.679222
iter: 16322 | loss: 1.679028
iter: 16323 | loss: 1.678835
iter: 16324 | loss: 1.678642
iter: 16325 | loss: 1.678448
iter: 16326 | loss: 1.678255
iter: 16327 | loss: 1.678061
iter: 16328 | loss: 1.677868
iter: 16329 | loss: 1.677675
iter: 16330 | loss: 1.677481
iter: 16331 | loss: 1.677288
iter: 16332 | loss: 1.677095
iter: 16333 | loss: 1.676901
iter: 16334 | loss: 1.676708
iter: 16335 | loss: 1.676514
iter: 16336 | loss: 1.676321
iter: 16337 | loss: 1.676128
iter: 16338 | loss: 1.675934
iter: 16339 | loss: 1.675741
iter: 16340 | loss: 1.675547
iter: 16341 | loss: 1.675354
iter: 16342 | loss: 1.675161
iter: 16343 | loss: 1.674967
iter: 16344 | loss: 1.674774
iter: 16345 | loss: 1.674581
iter: 16346 | loss: 1.674387
iter: 16347 | loss: 1.674194
iter: 16348 | loss: 1.674000
iter: 16349 | loss: 1.673807
iter: 16350 | loss: 1.673614
iter: 16351 | loss: 1.673420
iter: 16352 | loss: 1.673227
iter: 16353 | loss: 1.673033
iter: 16354 | loss: 1.672840
iter: 16355 | loss: 1.672647
iter: 16356 | loss: 1.672453
iter: 16357 | loss: 1.672260
iter: 16358 | loss: 1.672066
iter: 16359 | loss: 1.671873
iter: 16360 | loss: 1.671680
iter: 16361 | loss: 1.671486
iter: 16362 | loss: 1.671293
iter: 16363 | loss: 1.671100
iter: 16364 | loss: 1.670906
iter: 16365 | loss: 1.670713
iter: 16366 | loss: 1.670519
iter: 16367 | loss: 1.670326
iter: 16368 | loss: 1.670133
iter: 16369 | loss: 1.669939
iter: 16370 | loss: 1.669746
iter: 16371 | loss: 1.669552
iter: 16372 | loss: 1.669359
iter: 16373 | loss: 1.669166
iter: 16374 | loss: 1.668972
iter: 16375 | loss: 1.668779
iter: 16376 | loss: 1.668586
iter: 16377 | loss: 1.668392
iter: 16378 | loss: 1.668199
iter: 16379 | loss: 1.668005
iter: 16380 | loss: 1.667812
iter: 16381 | loss: 1.667619
iter: 16382 | loss: 1.667425
iter: 16383 | loss: 1.667232
iter: 16384 | loss: 1.667038
iter: 16385 | loss: 1.666845
iter: 16386 | loss: 1.666652
iter: 16387 | loss: 1.666458
iter: 16388 | loss: 1.666265
iter: 16389 | loss: 1.666071
iter: 16390 | loss: 1.665878
iter: 16391 | loss: 1.665685
iter: 16392 | loss: 1.665491
iter: 16393 | loss: 1.665298
iter: 16394 | loss: 1.665105
iter: 16395 | loss: 1.664911
iter: 16396 | loss: 1.664718
iter: 16397 | loss: 1.664524
iter: 16398 | loss: 1.664331
iter: 16399 | loss: 1.664138
iter: 16400 | loss: 1.663944
iter: 16401 | loss: 1.663751
iter: 16402 | loss: 1.663557
iter: 16403 | loss: 1.663364
iter: 16404 | loss: 1.663171
iter: 16405 | loss: 1.662977
iter: 16406 | loss: 1.662784
iter: 16407 | loss: 1.662591
iter: 16408 | loss: 1.662397
iter: 16409 | loss: 1.662204
iter: 16410 | loss: 1.662010
iter: 16411 | loss: 1.661817
iter: 16412 | loss: 1.661624
iter: 16413 | loss: 1.661430
iter: 16414 | loss: 1.661237
iter: 16415 | loss: 1.661043
iter: 16416 | loss: 1.660850
iter: 16417 | loss: 1.660657
iter: 16418 | loss: 1.660463
iter: 16419 | loss: 1.660270
iter: 16420 | loss: 1.660076
iter: 16421 | loss: 1.659883
iter: 16422 | loss: 1.659690
iter: 16423 | loss: 1.659496
iter: 16424 | loss: 1.659303
iter: 16425 | loss: 1.659110
iter: 16426 | loss: 1.658916
iter: 16427 | loss: 1.658723
iter: 16428 | loss: 1.658529
iter: 16429 | loss: 1.658336
iter: 16430 | loss: 1.658143
iter: 16431 | loss: 1.657949
iter: 16432 | loss: 1.657756
iter: 16433 | loss: 1.657562
iter: 16434 | loss: 1.657369
iter: 16435 | loss: 1.657176
iter: 16436 | loss: 1.656982
iter: 16437 | loss: 1.656789
iter: 16438 | loss: 1.656596
iter: 16439 | loss: 1.656402
iter: 16440 | loss: 1.656209
iter: 16441 | loss: 1.656015
iter: 16442 | loss: 1.655822
iter: 16443 | loss: 1.655629
iter: 16444 | loss: 1.655435
iter: 16445 | loss: 1.655242
iter: 16446 | loss: 1.655048
iter: 16447 | loss: 1.654855
iter: 16448 | loss: 1.654662
iter: 16449 | loss: 1.654468
iter: 16450 | loss: 1.654275
iter: 16451 | loss: 1.654082
iter: 16452 | loss: 1.653888
iter: 16453 | loss: 1.653695
iter: 16454 | loss: 1.653501
iter: 16455 | loss: 1.653308
iter: 16456 | loss: 1.653115
iter: 16457 | loss: 1.652921
iter: 16458 | loss: 1.652728
iter: 16459 | loss: 1.652534
iter: 16460 | loss: 1.652341
iter: 16461 | loss: 1.652148
iter: 16462 | loss: 1.651954
iter: 16463 | loss: 1.651761
iter: 16464 | loss: 1.651567
iter: 16465 | loss: 1.651374
iter: 16466 | loss: 1.651181
iter: 16467 | loss: 1.650987
iter: 16468 | loss: 1.650794
iter: 16469 | loss: 1.650601
iter: 16470 | loss: 1.650407
iter: 16471 | loss: 1.650214
iter: 16472 | loss: 1.650020
iter: 16473 | loss: 1.649827
iter: 16474 | loss: 1.649634
iter: 16475 | loss: 1.649440
iter: 16476 | loss: 1.649247
iter: 16477 | loss: 1.649053
iter: 16478 | loss: 1.648860
iter: 16479 | loss: 1.648667
iter: 16480 | loss: 1.648473
iter: 16481 | loss: 1.648280
iter: 16482 | loss: 1.648087
iter: 16483 | loss: 1.647893
iter: 16484 | loss: 1.647700
iter: 16485 | loss: 1.647506
iter: 16486 | loss: 1.647313
iter: 16487 | loss: 1.647120
iter: 16488 | loss: 1.646926
iter: 16489 | loss: 1.646733
iter: 16490 | loss: 1.646539
iter: 16491 | loss: 1.646346
iter: 16492 | loss: 1.646153
iter: 16493 | loss: 1.645959
iter: 16494 | loss: 1.645766
iter: 16495 | loss: 1.645572
iter: 16496 | loss: 1.645379
iter: 16497 | loss: 1.645186
iter: 16498 | loss: 1.644992
iter: 16499 | loss: 1.644799
iter: 16500 | loss: 1.644606
iter: 16501 | loss: 1.644412
iter: 16502 | loss: 1.644219
iter: 16503 | loss: 1.644025
iter: 16504 | loss: 1.643832
iter: 16505 | loss: 1.643639
iter: 16506 | loss: 1.643445
iter: 16507 | loss: 1.643252
iter: 16508 | loss: 1.643058
iter: 16509 | loss: 1.642865
iter: 16510 | loss: 1.642672
iter: 16511 | loss: 1.642478
iter: 16512 | loss: 1.642285
iter: 16513 | loss: 1.642092
iter: 16514 | loss: 1.641898
iter: 16515 | loss: 1.641705
iter: 16516 | loss: 1.641511
iter: 16517 | loss: 1.641318
iter: 16518 | loss: 1.641125
iter: 16519 | loss: 1.640931
iter: 16520 | loss: 1.640738
iter: 16521 | loss: 1.640544
iter: 16522 | loss: 1.640351
iter: 16523 | loss: 1.640158
iter: 16524 | loss: 1.639964
iter: 16525 | loss: 1.639771
iter: 16526 | loss: 1.639577
iter: 16527 | loss: 1.639384
iter: 16528 | loss: 1.639191
iter: 16529 | loss: 1.638997
iter: 16530 | loss: 1.638804
iter: 16531 | loss: 1.638611
iter: 16532 | loss: 1.638417
iter: 16533 | loss: 1.638224
iter: 16534 | loss: 1.638030
iter: 16535 | loss: 1.637837
iter: 16536 | loss: 1.637644
iter: 16537 | loss: 1.637450
iter: 16538 | loss: 1.637257
iter: 16539 | loss: 1.637063
iter: 16540 | loss: 1.636870
iter: 16541 | loss: 1.636677
iter: 16542 | loss: 1.636483
iter: 16543 | loss: 1.636290
iter: 16544 | loss: 1.636097
iter: 16545 | loss: 1.635903
iter: 16546 | loss: 1.635710
iter: 16547 | loss: 1.635516
iter: 16548 | loss: 1.635323
iter: 16549 | loss: 1.635130
iter: 16550 | loss: 1.634936
iter: 16551 | loss: 1.634743
iter: 16552 | loss: 1.634549
iter: 16553 | loss: 1.634356
iter: 16554 | loss: 1.634163
iter: 16555 | loss: 1.633969
iter: 16556 | loss: 1.633776
iter: 16557 | loss: 1.633582
iter: 16558 | loss: 1.633389
iter: 16559 | loss: 1.633196
iter: 16560 | loss: 1.633002
iter: 16561 | loss: 1.632809
iter: 16562 | loss: 1.632616
iter: 16563 | loss: 1.632422
iter: 16564 | loss: 1.632229
iter: 16565 | loss: 1.632035
iter: 16566 | loss: 1.631842
iter: 16567 | loss: 1.631649
iter: 16568 | loss: 1.631455
iter: 16569 | loss: 1.631262
iter: 16570 | loss: 1.631068
iter: 16571 | loss: 1.630875
iter: 16572 | loss: 1.630682
iter: 16573 | loss: 1.630488
iter: 16574 | loss: 1.630295
iter: 16575 | loss: 1.630102
iter: 16576 | loss: 1.629908
iter: 16577 | loss: 1.629715
iter: 16578 | loss: 1.629521
iter: 16579 | loss: 1.629328
iter: 16580 | loss: 1.629135
iter: 16581 | loss: 1.628941
iter: 16582 | loss: 1.628748
iter: 16583 | loss: 1.628554
iter: 16584 | loss: 1.628361
iter: 16585 | loss: 1.628168
iter: 16586 | loss: 1.627974
iter: 16587 | loss: 1.627781
iter: 16588 | loss: 1.627587
iter: 16589 | loss: 1.627394
iter: 16590 | loss: 1.627201
iter: 16591 | loss: 1.627007
iter: 16592 | loss: 1.626814
iter: 16593 | loss: 1.626621
iter: 16594 | loss: 1.626427
iter: 16595 | loss: 1.626234
iter: 16596 | loss: 1.626040
iter: 16597 | loss: 1.625847
iter: 16598 | loss: 1.625654
iter: 16599 | loss: 1.625460
iter: 16600 | loss: 1.625267
iter: 16601 | loss: 1.625073
iter: 16602 | loss: 1.624880
iter: 16603 | loss: 1.624687
iter: 16604 | loss: 1.624493
iter: 16605 | loss: 1.624300
iter: 16606 | loss: 1.624107
iter: 16607 | loss: 1.623913
iter: 16608 | loss: 1.623720
iter: 16609 | loss: 1.623526
iter: 16610 | loss: 1.623333
iter: 16611 | loss: 1.623140
iter: 16612 | loss: 1.622946
iter: 16613 | loss: 1.622753
iter: 16614 | loss: 1.622559
iter: 16615 | loss: 1.622366
iter: 16616 | loss: 1.622173
iter: 16617 | loss: 1.621979
iter: 16618 | loss: 1.621786
iter: 16619 | loss: 1.621592
iter: 16620 | loss: 1.621399
iter: 16621 | loss: 1.621206
iter: 16622 | loss: 1.621012
iter: 16623 | loss: 1.620819
iter: 16624 | loss: 1.620626
iter: 16625 | loss: 1.620432
iter: 16626 | loss: 1.620239
iter: 16627 | loss: 1.620045
iter: 16628 | loss: 1.619852
iter: 16629 | loss: 1.619659
iter: 16630 | loss: 1.619465
iter: 16631 | loss: 1.619272
iter: 16632 | loss: 1.619078
iter: 16633 | loss: 1.618885
iter: 16634 | loss: 1.618692
iter: 16635 | loss: 1.618498
iter: 16636 | loss: 1.618305
iter: 16637 | loss: 1.618112
iter: 16638 | loss: 1.617918
iter: 16639 | loss: 1.617725
iter: 16640 | loss: 1.617531
iter: 16641 | loss: 1.617338
iter: 16642 | loss: 1.617145
iter: 16643 | loss: 1.616951
iter: 16644 | loss: 1.616758
iter: 16645 | loss: 1.616564
iter: 16646 | loss: 1.616371
iter: 16647 | loss: 1.616178
iter: 16648 | loss: 1.615984
iter: 16649 | loss: 1.615791
iter: 16650 | loss: 1.615597
iter: 16651 | loss: 1.615404
iter: 16652 | loss: 1.615211
iter: 16653 | loss: 1.615017
iter: 16654 | loss: 1.614824
iter: 16655 | loss: 1.614631
iter: 16656 | loss: 1.614437
iter: 16657 | loss: 1.614244
iter: 16658 | loss: 1.614050
iter: 16659 | loss: 1.613857
iter: 16660 | loss: 1.613664
iter: 16661 | loss: 1.613470
iter: 16662 | loss: 1.613277
iter: 16663 | loss: 1.613083
iter: 16664 | loss: 1.612890
iter: 16665 | loss: 1.612697
iter: 16666 | loss: 1.612503
iter: 16667 | loss: 1.612310
iter: 16668 | loss: 1.612117
iter: 16669 | loss: 1.611923
iter: 16670 | loss: 1.611730
iter: 16671 | loss: 1.611536
iter: 16672 | loss: 1.611343
iter: 16673 | loss: 1.611150
iter: 16674 | loss: 1.610956
iter: 16675 | loss: 1.610763
iter: 16676 | loss: 1.610569
iter: 16677 | loss: 1.610376
iter: 16678 | loss: 1.610183
iter: 16679 | loss: 1.609989
iter: 16680 | loss: 1.609796
iter: 16681 | loss: 1.609602
iter: 16682 | loss: 1.609409
iter: 16683 | loss: 1.609216
iter: 16684 | loss: 1.609022
iter: 16685 | loss: 1.608829
iter: 16686 | loss: 1.608636
iter: 16687 | loss: 1.608442
iter: 16688 | loss: 1.608249
iter: 16689 | loss: 1.608055
iter: 16690 | loss: 1.607862
iter: 16691 | loss: 1.607669
iter: 16692 | loss: 1.607475
iter: 16693 | loss: 1.607282
iter: 16694 | loss: 1.607088
iter: 16695 | loss: 1.606895
iter: 16696 | loss: 1.606702
iter: 16697 | loss: 1.606508
iter: 16698 | loss: 1.606315
iter: 16699 | loss: 1.606122
iter: 16700 | loss: 1.605928
iter: 16701 | loss: 1.605735
iter: 16702 | loss: 1.605541
iter: 16703 | loss: 1.605348
iter: 16704 | loss: 1.605155
iter: 16705 | loss: 1.604961
iter: 16706 | loss: 1.604768
iter: 16707 | loss: 1.604574
iter: 16708 | loss: 1.604381
iter: 16709 | loss: 1.604188
iter: 16710 | loss: 1.603994
iter: 16711 | loss: 1.603801
iter: 16712 | loss: 1.603607
iter: 16713 | loss: 1.603414
iter: 16714 | loss: 1.603221
iter: 16715 | loss: 1.603027
iter: 16716 | loss: 1.602834
iter: 16717 | loss: 1.602641
iter: 16718 | loss: 1.602447
iter: 16719 | loss: 1.602254
iter: 16720 | loss: 1.602060
iter: 16721 | loss: 1.601867
iter: 16722 | loss: 1.601674
iter: 16723 | loss: 1.601480
iter: 16724 | loss: 1.601287
iter: 16725 | loss: 1.601093
iter: 16726 | loss: 1.600900
iter: 16727 | loss: 1.600707
iter: 16728 | loss: 1.600513
iter: 16729 | loss: 1.600320
iter: 16730 | loss: 1.600127
iter: 16731 | loss: 1.599933
iter: 16732 | loss: 1.599740
iter: 16733 | loss: 1.599546
iter: 16734 | loss: 1.599353
iter: 16735 | loss: 1.599160
iter: 16736 | loss: 1.598966
iter: 16737 | loss: 1.598773
iter: 16738 | loss: 1.598579
iter: 16739 | loss: 1.598386
iter: 16740 | loss: 1.598193
iter: 16741 | loss: 1.597999
iter: 16742 | loss: 1.597806
iter: 16743 | loss: 1.597612
iter: 16744 | loss: 1.597419
iter: 16745 | loss: 1.597226
iter: 16746 | loss: 1.597032
iter: 16747 | loss: 1.596839
iter: 16748 | loss: 1.596646
iter: 16749 | loss: 1.596452
iter: 16750 | loss: 1.596259
iter: 16751 | loss: 1.596065
iter: 16752 | loss: 1.595872
iter: 16753 | loss: 1.595679
iter: 16754 | loss: 1.595485
iter: 16755 | loss: 1.595292
iter: 16756 | loss: 1.595098
iter: 16757 | loss: 1.594905
iter: 16758 | loss: 1.594712
iter: 16759 | loss: 1.594518
iter: 16760 | loss: 1.594325
iter: 16761 | loss: 1.594132
iter: 16762 | loss: 1.593938
iter: 16763 | loss: 1.593745
iter: 16764 | loss: 1.593551
iter: 16765 | loss: 1.593358
iter: 16766 | loss: 1.593165
iter: 16767 | loss: 1.592971
iter: 16768 | loss: 1.592778
iter: 16769 | loss: 1.592584
iter: 16770 | loss: 1.592391
iter: 16771 | loss: 1.592198
iter: 16772 | loss: 1.592004
iter: 16773 | loss: 1.591811
iter: 16774 | loss: 1.591618
iter: 16775 | loss: 1.591424
iter: 16776 | loss: 1.591231
iter: 16777 | loss: 1.591037
iter: 16778 | loss: 1.590844
iter: 16779 | loss: 1.590651
iter: 16780 | loss: 1.590457
iter: 16781 | loss: 1.590264
iter: 16782 | loss: 1.590070
iter: 16783 | loss: 1.589877
iter: 16784 | loss: 1.589684
iter: 16785 | loss: 1.589490
iter: 16786 | loss: 1.589297
iter: 16787 | loss: 1.589103
iter: 16788 | loss: 1.588910
iter: 16789 | loss: 1.588717
iter: 16790 | loss: 1.588523
iter: 16791 | loss: 1.588330
iter: 16792 | loss: 1.588137
iter: 16793 | loss: 1.587943
iter: 16794 | loss: 1.587750
iter: 16795 | loss: 1.587556
iter: 16796 | loss: 1.587363
iter: 16797 | loss: 1.587170
iter: 16798 | loss: 1.586976
iter: 16799 | loss: 1.586783
iter: 16800 | loss: 1.586589
iter: 16801 | loss: 1.586396
iter: 16802 | loss: 1.586203
iter: 16803 | loss: 1.586009
iter: 16804 | loss: 1.585816
iter: 16805 | loss: 1.585623
iter: 16806 | loss: 1.585429
iter: 16807 | loss: 1.585236
iter: 16808 | loss: 1.585042
iter: 16809 | loss: 1.584849
iter: 16810 | loss: 1.584656
iter: 16811 | loss: 1.584462
iter: 16812 | loss: 1.584269
iter: 16813 | loss: 1.584075
iter: 16814 | loss: 1.583882
iter: 16815 | loss: 1.583689
iter: 16816 | loss: 1.583495
iter: 16817 | loss: 1.583302
iter: 16818 | loss: 1.583108
iter: 16819 | loss: 1.582915
iter: 16820 | loss: 1.582722
iter: 16821 | loss: 1.582528
iter: 16822 | loss: 1.582335
iter: 16823 | loss: 1.582142
iter: 16824 | loss: 1.581948
iter: 16825 | loss: 1.581755
iter: 16826 | loss: 1.581561
iter: 16827 | loss: 1.581368
iter: 16828 | loss: 1.581175
iter: 16829 | loss: 1.580981
iter: 16830 | loss: 1.580788
iter: 16831 | loss: 1.580594
iter: 16832 | loss: 1.580401
iter: 16833 | loss: 1.580208
iter: 16834 | loss: 1.580014
iter: 16835 | loss: 1.579821
iter: 16836 | loss: 1.579628
iter: 16837 | loss: 1.579434
iter: 16838 | loss: 1.579241
iter: 16839 | loss: 1.579047
iter: 16840 | loss: 1.578854
iter: 16841 | loss: 1.578661
iter: 16842 | loss: 1.578467
iter: 16843 | loss: 1.578274
iter: 16844 | loss: 1.578080
iter: 16845 | loss: 1.577887
iter: 16846 | loss: 1.577694
iter: 16847 | loss: 1.577500
iter: 16848 | loss: 1.577307
iter: 16849 | loss: 1.577113
iter: 16850 | loss: 1.576920
iter: 16851 | loss: 1.576727
iter: 16852 | loss: 1.576533
iter: 16853 | loss: 1.576340
iter: 16854 | loss: 1.576147
iter: 16855 | loss: 1.575953
iter: 16856 | loss: 1.575760
iter: 16857 | loss: 1.575566
iter: 16858 | loss: 1.575373
iter: 16859 | loss: 1.575180
iter: 16860 | loss: 1.574986
iter: 16861 | loss: 1.574793
iter: 16862 | loss: 1.574599
iter: 16863 | loss: 1.574406
iter: 16864 | loss: 1.574213
iter: 16865 | loss: 1.574019
iter: 16866 | loss: 1.573826
iter: 16867 | loss: 1.573633
iter: 16868 | loss: 1.573439
iter: 16869 | loss: 1.573246
iter: 16870 | loss: 1.573052
iter: 16871 | loss: 1.572859
iter: 16872 | loss: 1.572666
iter: 16873 | loss: 1.572472
iter: 16874 | loss: 1.572279
iter: 16875 | loss: 1.572085
iter: 16876 | loss: 1.571892
iter: 16877 | loss: 1.571699
iter: 16878 | loss: 1.571505
iter: 16879 | loss: 1.571312
iter: 16880 | loss: 1.571118
iter: 16881 | loss: 1.570925
iter: 16882 | loss: 1.570732
iter: 16883 | loss: 1.570538
iter: 16884 | loss: 1.570345
iter: 16885 | loss: 1.570152
iter: 16886 | loss: 1.569958
iter: 16887 | loss: 1.569765
iter: 16888 | loss: 1.569571
iter: 16889 | loss: 1.569378
iter: 16890 | loss: 1.569185
iter: 16891 | loss: 1.568991
iter: 16892 | loss: 1.568798
iter: 16893 | loss: 1.568604
iter: 16894 | loss: 1.568411
iter: 16895 | loss: 1.568218
iter: 16896 | loss: 1.568024
iter: 16897 | loss: 1.567831
iter: 16898 | loss: 1.567638
iter: 16899 | loss: 1.567444
iter: 16900 | loss: 1.567251
iter: 16901 | loss: 1.567057
iter: 16902 | loss: 1.566864
iter: 16903 | loss: 1.566671
iter: 16904 | loss: 1.566477
iter: 16905 | loss: 1.566284
iter: 16906 | loss: 1.566090
iter: 16907 | loss: 1.565897
iter: 16908 | loss: 1.565704
iter: 16909 | loss: 1.565510
iter: 16910 | loss: 1.565317
iter: 16911 | loss: 1.565123
iter: 16912 | loss: 1.564930
iter: 16913 | loss: 1.564737
iter: 16914 | loss: 1.564543
iter: 16915 | loss: 1.564350
iter: 16916 | loss: 1.564157
iter: 16917 | loss: 1.563963
iter: 16918 | loss: 1.563770
iter: 16919 | loss: 1.563576
iter: 16920 | loss: 1.563383
iter: 16921 | loss: 1.563190
iter: 16922 | loss: 1.562996
iter: 16923 | loss: 1.562803
iter: 16924 | loss: 1.562609
iter: 16925 | loss: 1.562416
iter: 16926 | loss: 1.562223
iter: 16927 | loss: 1.562029
iter: 16928 | loss: 1.561836
iter: 16929 | loss: 1.561643
iter: 16930 | loss: 1.561449
iter: 16931 | loss: 1.561256
iter: 16932 | loss: 1.561062
iter: 16933 | loss: 1.560869
iter: 16934 | loss: 1.560676
iter: 16935 | loss: 1.560482
iter: 16936 | loss: 1.560289
iter: 16937 | loss: 1.560095
iter: 16938 | loss: 1.559902
iter: 16939 | loss: 1.559709
iter: 16940 | loss: 1.559515
iter: 16941 | loss: 1.559322
iter: 16942 | loss: 1.559128
iter: 16943 | loss: 1.558935
iter: 16944 | loss: 1.558742
iter: 16945 | loss: 1.558548
iter: 16946 | loss: 1.558355
iter: 16947 | loss: 1.558162
iter: 16948 | loss: 1.557968
iter: 16949 | loss: 1.557775
iter: 16950 | loss: 1.557581
iter: 16951 | loss: 1.557388
iter: 16952 | loss: 1.557195
iter: 16953 | loss: 1.557001
iter: 16954 | loss: 1.556808
iter: 16955 | loss: 1.556614
iter: 16956 | loss: 1.556421
iter: 16957 | loss: 1.556228
iter: 16958 | loss: 1.556034
iter: 16959 | loss: 1.555841
iter: 16960 | loss: 1.555648
iter: 16961 | loss: 1.555454
iter: 16962 | loss: 1.555261
iter: 16963 | loss: 1.555067
iter: 16964 | loss: 1.554874
iter: 16965 | loss: 1.554681
iter: 16966 | loss: 1.554487
iter: 16967 | loss: 1.554294
iter: 16968 | loss: 1.554100
iter: 16969 | loss: 1.553907
iter: 16970 | loss: 1.553714
iter: 16971 | loss: 1.553520
iter: 16972 | loss: 1.553327
iter: 16973 | loss: 1.553133
iter: 16974 | loss: 1.552940
iter: 16975 | loss: 1.552747
iter: 16976 | loss: 1.552553
iter: 16977 | loss: 1.552360
iter: 16978 | loss: 1.552167
iter: 16979 | loss: 1.551973
iter: 16980 | loss: 1.551780
iter: 16981 | loss: 1.551586
iter: 16982 | loss: 1.551393
iter: 16983 | loss: 1.551200
iter: 16984 | loss: 1.551006
iter: 16985 | loss: 1.550813
iter: 16986 | loss: 1.550619
iter: 16987 | loss: 1.550426
iter: 16988 | loss: 1.550233
iter: 16989 | loss: 1.550039
iter: 16990 | loss: 1.549846
iter: 16991 | loss: 1.549653
iter: 16992 | loss: 1.549459
iter: 16993 | loss: 1.549266
iter: 16994 | loss: 1.549072
iter: 16995 | loss: 1.548879
iter: 16996 | loss: 1.548686
iter: 16997 | loss: 1.548492
iter: 16998 | loss: 1.548299
iter: 16999 | loss: 1.548105
iter: 17000 | loss: 1.547912
iter: 17001 | loss: 1.547719
iter: 17002 | loss: 1.547525
iter: 17003 | loss: 1.547332
iter: 17004 | loss: 1.547138
iter: 17005 | loss: 1.546945
iter: 17006 | loss: 1.546752
iter: 17007 | loss: 1.546558
iter: 17008 | loss: 1.546365
iter: 17009 | loss: 1.546172
iter: 17010 | loss: 1.545978
iter: 17011 | loss: 1.545785
iter: 17012 | loss: 1.545591
iter: 17013 | loss: 1.545398
iter: 17014 | loss: 1.545205
iter: 17015 | loss: 1.545011
iter: 17016 | loss: 1.544818
iter: 17017 | loss: 1.544624
iter: 17018 | loss: 1.544431
iter: 17019 | loss: 1.544238
iter: 17020 | loss: 1.544044
iter: 17021 | loss: 1.543851
iter: 17022 | loss: 1.543658
iter: 17023 | loss: 1.543464
iter: 17024 | loss: 1.543271
iter: 17025 | loss: 1.543077
iter: 17026 | loss: 1.542884
iter: 17027 | loss: 1.542691
iter: 17028 | loss: 1.542497
iter: 17029 | loss: 1.542304
iter: 17030 | loss: 1.542110
iter: 17031 | loss: 1.541917
iter: 17032 | loss: 1.541724
iter: 17033 | loss: 1.541530
iter: 17034 | loss: 1.541337
iter: 17035 | loss: 1.541143
iter: 17036 | loss: 1.540950
iter: 17037 | loss: 1.540757
iter: 17038 | loss: 1.540563
iter: 17039 | loss: 1.540370
iter: 17040 | loss: 1.540177
iter: 17041 | loss: 1.539983
iter: 17042 | loss: 1.539790
iter: 17043 | loss: 1.539596
iter: 17044 | loss: 1.539403
iter: 17045 | loss: 1.539210
iter: 17046 | loss: 1.539016
iter: 17047 | loss: 1.538823
iter: 17048 | loss: 1.538629
iter: 17049 | loss: 1.538436
iter: 17050 | loss: 1.538243
iter: 17051 | loss: 1.538049
iter: 17052 | loss: 1.537856
iter: 17053 | loss: 1.537663
iter: 17054 | loss: 1.537469
iter: 17055 | loss: 1.537276
iter: 17056 | loss: 1.537082
iter: 17057 | loss: 1.536889
iter: 17058 | loss: 1.536696
iter: 17059 | loss: 1.536502
iter: 17060 | loss: 1.536309
iter: 17061 | loss: 1.536115
iter: 17062 | loss: 1.535922
iter: 17063 | loss: 1.535729
iter: 17064 | loss: 1.535535
iter: 17065 | loss: 1.535342
iter: 17066 | loss: 1.535148
iter: 17067 | loss: 1.534955
iter: 17068 | loss: 1.534762
iter: 17069 | loss: 1.534568
iter: 17070 | loss: 1.534375
iter: 17071 | loss: 1.534182
iter: 17072 | loss: 1.533988
iter: 17073 | loss: 1.533795
iter: 17074 | loss: 1.533601
iter: 17075 | loss: 1.533408
iter: 17076 | loss: 1.533215
iter: 17077 | loss: 1.533021
iter: 17078 | loss: 1.532828
iter: 17079 | loss: 1.532634
iter: 17080 | loss: 1.532441
iter: 17081 | loss: 1.532248
iter: 17082 | loss: 1.532054
iter: 17083 | loss: 1.531861
iter: 17084 | loss: 1.531668
iter: 17085 | loss: 1.531474
iter: 17086 | loss: 1.531281
iter: 17087 | loss: 1.531087
iter: 17088 | loss: 1.530894
iter: 17089 | loss: 1.530701
iter: 17090 | loss: 1.530507
iter: 17091 | loss: 1.530314
iter: 17092 | loss: 1.530120
iter: 17093 | loss: 1.529927
iter: 17094 | loss: 1.529734
iter: 17095 | loss: 1.529540
iter: 17096 | loss: 1.529347
iter: 17097 | loss: 1.529154
iter: 17098 | loss: 1.528960
iter: 17099 | loss: 1.528767
iter: 17100 | loss: 1.528573
iter: 17101 | loss: 1.528380
iter: 17102 | loss: 1.528187
iter: 17103 | loss: 1.527993
iter: 17104 | loss: 1.527800
iter: 17105 | loss: 1.527606
iter: 17106 | loss: 1.527413
iter: 17107 | loss: 1.527220
iter: 17108 | loss: 1.527026
iter: 17109 | loss: 1.526833
iter: 17110 | loss: 1.526639
iter: 17111 | loss: 1.526446
iter: 17112 | loss: 1.526253
iter: 17113 | loss: 1.526059
iter: 17114 | loss: 1.525866
iter: 17115 | loss: 1.525673
iter: 17116 | loss: 1.525479
iter: 17117 | loss: 1.525286
iter: 17118 | loss: 1.525092
iter: 17119 | loss: 1.524899
iter: 17120 | loss: 1.524706
iter: 17121 | loss: 1.524512
iter: 17122 | loss: 1.524319
iter: 17123 | loss: 1.524125
iter: 17124 | loss: 1.523932
iter: 17125 | loss: 1.523739
iter: 17126 | loss: 1.523545
iter: 17127 | loss: 1.523352
iter: 17128 | loss: 1.523159
iter: 17129 | loss: 1.522965
iter: 17130 | loss: 1.522772
iter: 17131 | loss: 1.522578
iter: 17132 | loss: 1.522385
iter: 17133 | loss: 1.522192
iter: 17134 | loss: 1.521998
iter: 17135 | loss: 1.521805
iter: 17136 | loss: 1.521611
iter: 17137 | loss: 1.521418
iter: 17138 | loss: 1.521225
iter: 17139 | loss: 1.521031
iter: 17140 | loss: 1.520838
iter: 17141 | loss: 1.520644
iter: 17142 | loss: 1.520451
iter: 17143 | loss: 1.520258
iter: 17144 | loss: 1.520064
iter: 17145 | loss: 1.519871
iter: 17146 | loss: 1.519678
iter: 17147 | loss: 1.519484
iter: 17148 | loss: 1.519291
iter: 17149 | loss: 1.519097
iter: 17150 | loss: 1.518904
iter: 17151 | loss: 1.518711
iter: 17152 | loss: 1.518517
iter: 17153 | loss: 1.518324
iter: 17154 | loss: 1.518130
iter: 17155 | loss: 1.517937
iter: 17156 | loss: 1.517744
iter: 17157 | loss: 1.517550
iter: 17158 | loss: 1.517357
iter: 17159 | loss: 1.517164
iter: 17160 | loss: 1.516970
iter: 17161 | loss: 1.516777
iter: 17162 | loss: 1.516583
iter: 17163 | loss: 1.516390
iter: 17164 | loss: 1.516197
iter: 17165 | loss: 1.516003
iter: 17166 | loss: 1.515810
iter: 17167 | loss: 1.515616
iter: 17168 | loss: 1.515423
iter: 17169 | loss: 1.515230
iter: 17170 | loss: 1.515036
iter: 17171 | loss: 1.514843
iter: 17172 | loss: 1.514649
iter: 17173 | loss: 1.514456
iter: 17174 | loss: 1.514263
iter: 17175 | loss: 1.514069
iter: 17176 | loss: 1.513876
iter: 17177 | loss: 1.513683
iter: 17178 | loss: 1.513489
iter: 17179 | loss: 1.513296
iter: 17180 | loss: 1.513102
iter: 17181 | loss: 1.512909
iter: 17182 | loss: 1.512716
iter: 17183 | loss: 1.512522
iter: 17184 | loss: 1.512329
iter: 17185 | loss: 1.512135
iter: 17186 | loss: 1.511942
iter: 17187 | loss: 1.511749
iter: 17188 | loss: 1.511555
iter: 17189 | loss: 1.511362
iter: 17190 | loss: 1.511169
iter: 17191 | loss: 1.510975
iter: 17192 | loss: 1.510782
iter: 17193 | loss: 1.510588
iter: 17194 | loss: 1.510395
iter: 17195 | loss: 1.510202
iter: 17196 | loss: 1.510008
iter: 17197 | loss: 1.509815
iter: 17198 | loss: 1.509621
iter: 17199 | loss: 1.509428
iter: 17200 | loss: 1.509235
iter: 17201 | loss: 1.509041
iter: 17202 | loss: 1.508848
iter: 17203 | loss: 1.508654
iter: 17204 | loss: 1.508461
iter: 17205 | loss: 1.508268
iter: 17206 | loss: 1.508074
iter: 17207 | loss: 1.507881
iter: 17208 | loss: 1.507688
iter: 17209 | loss: 1.507494
iter: 17210 | loss: 1.507301
iter: 17211 | loss: 1.507107
iter: 17212 | loss: 1.506914
iter: 17213 | loss: 1.506721
iter: 17214 | loss: 1.506527
iter: 17215 | loss: 1.506334
iter: 17216 | loss: 1.506140
iter: 17217 | loss: 1.505947
iter: 17218 | loss: 1.505754
iter: 17219 | loss: 1.505560
iter: 17220 | loss: 1.505367
iter: 17221 | loss: 1.505174
iter: 17222 | loss: 1.504980
iter: 17223 | loss: 1.504787
iter: 17224 | loss: 1.504593
iter: 17225 | loss: 1.504400
iter: 17226 | loss: 1.504207
iter: 17227 | loss: 1.504013
iter: 17228 | loss: 1.503820
iter: 17229 | loss: 1.503626
iter: 17230 | loss: 1.503433
iter: 17231 | loss: 1.503240
iter: 17232 | loss: 1.503046
iter: 17233 | loss: 1.502853
iter: 17234 | loss: 1.502659
iter: 17235 | loss: 1.502466
iter: 17236 | loss: 1.502273
iter: 17237 | loss: 1.502079
iter: 17238 | loss: 1.501886
iter: 17239 | loss: 1.501693
iter: 17240 | loss: 1.501499
iter: 17241 | loss: 1.501306
iter: 17242 | loss: 1.501112
iter: 17243 | loss: 1.500919
iter: 17244 | loss: 1.500726
iter: 17245 | loss: 1.500532
iter: 17246 | loss: 1.500339
iter: 17247 | loss: 1.500145
iter: 17248 | loss: 1.499952
iter: 17249 | loss: 1.499759
iter: 17250 | loss: 1.499565
iter: 17251 | loss: 1.499372
iter: 17252 | loss: 1.499179
iter: 17253 | loss: 1.498985
iter: 17254 | loss: 1.498792
iter: 17255 | loss: 1.498598
iter: 17256 | loss: 1.498405
iter: 17257 | loss: 1.498212
iter: 17258 | loss: 1.498018
iter: 17259 | loss: 1.497825
iter: 17260 | loss: 1.497631
iter: 17261 | loss: 1.497438
iter: 17262 | loss: 1.497245
iter: 17263 | loss: 1.497051
iter: 17264 | loss: 1.496858
iter: 17265 | loss: 1.496664
iter: 17266 | loss: 1.496471
iter: 17267 | loss: 1.496278
iter: 17268 | loss: 1.496084
iter: 17269 | loss: 1.495891
iter: 17270 | loss: 1.495698
iter: 17271 | loss: 1.495504
iter: 17272 | loss: 1.495311
iter: 17273 | loss: 1.495117
iter: 17274 | loss: 1.494924
iter: 17275 | loss: 1.494731
iter: 17276 | loss: 1.494537
iter: 17277 | loss: 1.494344
iter: 17278 | loss: 1.494150
iter: 17279 | loss: 1.493957
iter: 17280 | loss: 1.493764
iter: 17281 | loss: 1.493570
iter: 17282 | loss: 1.493377
iter: 17283 | loss: 1.493184
iter: 17284 | loss: 1.492990
iter: 17285 | loss: 1.492797
iter: 17286 | loss: 1.492603
iter: 17287 | loss: 1.492410
iter: 17288 | loss: 1.492217
iter: 17289 | loss: 1.492023
iter: 17290 | loss: 1.491830
iter: 17291 | loss: 1.491636
iter: 17292 | loss: 1.491443
iter: 17293 | loss: 1.491250
iter: 17294 | loss: 1.491056
iter: 17295 | loss: 1.490863
iter: 17296 | loss: 1.490669
iter: 17297 | loss: 1.490476
iter: 17298 | loss: 1.490283
iter: 17299 | loss: 1.490089
iter: 17300 | loss: 1.489896
iter: 17301 | loss: 1.489703
iter: 17302 | loss: 1.489509
iter: 17303 | loss: 1.489316
iter: 17304 | loss: 1.489122
iter: 17305 | loss: 1.488929
iter: 17306 | loss: 1.488736
iter: 17307 | loss: 1.488542
iter: 17308 | loss: 1.488349
iter: 17309 | loss: 1.488155
iter: 17310 | loss: 1.487962
iter: 17311 | loss: 1.487769
iter: 17312 | loss: 1.487575
iter: 17313 | loss: 1.487382
iter: 17314 | loss: 1.487189
iter: 17315 | loss: 1.486995
iter: 17316 | loss: 1.486802
iter: 17317 | loss: 1.486608
iter: 17318 | loss: 1.486415
iter: 17319 | loss: 1.486222
iter: 17320 | loss: 1.486028
iter: 17321 | loss: 1.485835
iter: 17322 | loss: 1.485641
iter: 17323 | loss: 1.485448
iter: 17324 | loss: 1.485255
iter: 17325 | loss: 1.485061
iter: 17326 | loss: 1.484868
iter: 17327 | loss: 1.484674
iter: 17328 | loss: 1.484481
iter: 17329 | loss: 1.484288
iter: 17330 | loss: 1.484094
iter: 17331 | loss: 1.483901
iter: 17332 | loss: 1.483708
iter: 17333 | loss: 1.483514
iter: 17334 | loss: 1.483321
iter: 17335 | loss: 1.483127
iter: 17336 | loss: 1.482934
iter: 17337 | loss: 1.482741
iter: 17338 | loss: 1.482547
iter: 17339 | loss: 1.482354
iter: 17340 | loss: 1.482160
iter: 17341 | loss: 1.481967
iter: 17342 | loss: 1.481774
iter: 17343 | loss: 1.481580
iter: 17344 | loss: 1.481387
iter: 17345 | loss: 1.481194
iter: 17346 | loss: 1.481000
iter: 17347 | loss: 1.480807
iter: 17348 | loss: 1.480613
iter: 17349 | loss: 1.480420
iter: 17350 | loss: 1.480227
iter: 17351 | loss: 1.480033
iter: 17352 | loss: 1.479840
iter: 17353 | loss: 1.479646
iter: 17354 | loss: 1.479453
iter: 17355 | loss: 1.479260
iter: 17356 | loss: 1.479066
iter: 17357 | loss: 1.478873
iter: 17358 | loss: 1.478679
iter: 17359 | loss: 1.478486
iter: 17360 | loss: 1.478293
iter: 17361 | loss: 1.478099
iter: 17362 | loss: 1.477906
iter: 17363 | loss: 1.477713
iter: 17364 | loss: 1.477519
iter: 17365 | loss: 1.477326
iter: 17366 | loss: 1.477132
iter: 17367 | loss: 1.476939
iter: 17368 | loss: 1.476746
iter: 17369 | loss: 1.476552
iter: 17370 | loss: 1.476359
iter: 17371 | loss: 1.476165
iter: 17372 | loss: 1.475972
iter: 17373 | loss: 1.475779
iter: 17374 | loss: 1.475585
iter: 17375 | loss: 1.475392
iter: 17376 | loss: 1.475199
iter: 17377 | loss: 1.475005
iter: 17378 | loss: 1.474812
iter: 17379 | loss: 1.474618
iter: 17380 | loss: 1.474425
iter: 17381 | loss: 1.474232
iter: 17382 | loss: 1.474038
iter: 17383 | loss: 1.473845
iter: 17384 | loss: 1.473651
iter: 17385 | loss: 1.473458
iter: 17386 | loss: 1.473265
iter: 17387 | loss: 1.473071
iter: 17388 | loss: 1.472878
iter: 17389 | loss: 1.472684
iter: 17390 | loss: 1.472491
iter: 17391 | loss: 1.472298
iter: 17392 | loss: 1.472104
iter: 17393 | loss: 1.471911
iter: 17394 | loss: 1.471718
iter: 17395 | loss: 1.471524
iter: 17396 | loss: 1.471331
iter: 17397 | loss: 1.471137
iter: 17398 | loss: 1.470944
iter: 17399 | loss: 1.470751
iter: 17400 | loss: 1.470557
iter: 17401 | loss: 1.470364
iter: 17402 | loss: 1.470170
iter: 17403 | loss: 1.469977
iter: 17404 | loss: 1.469784
iter: 17405 | loss: 1.469590
iter: 17406 | loss: 1.469397
iter: 17407 | loss: 1.469204
iter: 17408 | loss: 1.469010
iter: 17409 | loss: 1.468817
iter: 17410 | loss: 1.468623
iter: 17411 | loss: 1.468430
iter: 17412 | loss: 1.468237
iter: 17413 | loss: 1.468043
iter: 17414 | loss: 1.467850
iter: 17415 | loss: 1.467656
iter: 17416 | loss: 1.467463
iter: 17417 | loss: 1.467270
iter: 17418 | loss: 1.467076
iter: 17419 | loss: 1.466883
iter: 17420 | loss: 1.466690
iter: 17421 | loss: 1.466496
iter: 17422 | loss: 1.466303
iter: 17423 | loss: 1.466109
iter: 17424 | loss: 1.465916
iter: 17425 | loss: 1.465723
iter: 17426 | loss: 1.465529
iter: 17427 | loss: 1.465336
iter: 17428 | loss: 1.465142
iter: 17429 | loss: 1.464949
iter: 17430 | loss: 1.464756
iter: 17431 | loss: 1.464562
iter: 17432 | loss: 1.464369
iter: 17433 | loss: 1.464175
iter: 17434 | loss: 1.463982
iter: 17435 | loss: 1.463789
iter: 17436 | loss: 1.463595
iter: 17437 | loss: 1.463402
iter: 17438 | loss: 1.463209
iter: 17439 | loss: 1.463015
iter: 17440 | loss: 1.462822
iter: 17441 | loss: 1.462628
iter: 17442 | loss: 1.462435
iter: 17443 | loss: 1.462242
iter: 17444 | loss: 1.462048
iter: 17445 | loss: 1.461855
iter: 17446 | loss: 1.461661
iter: 17447 | loss: 1.461468
iter: 17448 | loss: 1.461275
iter: 17449 | loss: 1.461081
iter: 17450 | loss: 1.460888
iter: 17451 | loss: 1.460695
iter: 17452 | loss: 1.460501
iter: 17453 | loss: 1.460308
iter: 17454 | loss: 1.460114
iter: 17455 | loss: 1.459921
iter: 17456 | loss: 1.459728
iter: 17457 | loss: 1.459534
iter: 17458 | loss: 1.459341
iter: 17459 | loss: 1.459147
iter: 17460 | loss: 1.458954
iter: 17461 | loss: 1.458761
iter: 17462 | loss: 1.458567
iter: 17463 | loss: 1.458374
iter: 17464 | loss: 1.458180
iter: 17465 | loss: 1.457987
iter: 17466 | loss: 1.457794
iter: 17467 | loss: 1.457600
iter: 17468 | loss: 1.457407
iter: 17469 | loss: 1.457214
iter: 17470 | loss: 1.457020
iter: 17471 | loss: 1.456827
iter: 17472 | loss: 1.456633
iter: 17473 | loss: 1.456440
iter: 17474 | loss: 1.456247
iter: 17475 | loss: 1.456053
iter: 17476 | loss: 1.455860
iter: 17477 | loss: 1.455666
iter: 17478 | loss: 1.455473
iter: 17479 | loss: 1.455280
iter: 17480 | loss: 1.455086
iter: 17481 | loss: 1.454893
iter: 17482 | loss: 1.454700
iter: 17483 | loss: 1.454506
iter: 17484 | loss: 1.454313
iter: 17485 | loss: 1.454119
iter: 17486 | loss: 1.453926
iter: 17487 | loss: 1.453733
iter: 17488 | loss: 1.453539
iter: 17489 | loss: 1.453346
iter: 17490 | loss: 1.453152
iter: 17491 | loss: 1.452959
iter: 17492 | loss: 1.452766
iter: 17493 | loss: 1.452572
iter: 17494 | loss: 1.452379
iter: 17495 | loss: 1.452185
iter: 17496 | loss: 1.451992
iter: 17497 | loss: 1.451799
iter: 17498 | loss: 1.451605
iter: 17499 | loss: 1.451412
iter: 17500 | loss: 1.451219
iter: 17501 | loss: 1.451025
iter: 17502 | loss: 1.450832
iter: 17503 | loss: 1.450638
iter: 17504 | loss: 1.450445
iter: 17505 | loss: 1.450252
iter: 17506 | loss: 1.450058
iter: 17507 | loss: 1.449865
iter: 17508 | loss: 1.449671
iter: 17509 | loss: 1.449478
iter: 17510 | loss: 1.449285
iter: 17511 | loss: 1.449091
iter: 17512 | loss: 1.448898
iter: 17513 | loss: 1.448705
iter: 17514 | loss: 1.448511
iter: 17515 | loss: 1.448318
iter: 17516 | loss: 1.448124
iter: 17517 | loss: 1.447931
iter: 17518 | loss: 1.447738
iter: 17519 | loss: 1.447544
iter: 17520 | loss: 1.447351
iter: 17521 | loss: 1.447157
iter: 17522 | loss: 1.446964
iter: 17523 | loss: 1.446771
iter: 17524 | loss: 1.446577
iter: 17525 | loss: 1.446384
iter: 17526 | loss: 1.446190
iter: 17527 | loss: 1.445997
iter: 17528 | loss: 1.445804
iter: 17529 | loss: 1.445610
iter: 17530 | loss: 1.445417
iter: 17531 | loss: 1.445224
iter: 17532 | loss: 1.445030
iter: 17533 | loss: 1.444837
iter: 17534 | loss: 1.444643
iter: 17535 | loss: 1.444450
iter: 17536 | loss: 1.444257
iter: 17537 | loss: 1.444063
iter: 17538 | loss: 1.443870
iter: 17539 | loss: 1.443676
iter: 17540 | loss: 1.443483
iter: 17541 | loss: 1.443290
iter: 17542 | loss: 1.443096
iter: 17543 | loss: 1.442903
iter: 17544 | loss: 1.442710
iter: 17545 | loss: 1.442516
iter: 17546 | loss: 1.442323
iter: 17547 | loss: 1.442129
iter: 17548 | loss: 1.441936
iter: 17549 | loss: 1.441743
iter: 17550 | loss: 1.441549
iter: 17551 | loss: 1.441356
iter: 17552 | loss: 1.441162
iter: 17553 | loss: 1.440969
iter: 17554 | loss: 1.440776
iter: 17555 | loss: 1.440582
iter: 17556 | loss: 1.440389
iter: 17557 | loss: 1.440195
iter: 17558 | loss: 1.440002
iter: 17559 | loss: 1.439809
iter: 17560 | loss: 1.439615
iter: 17561 | loss: 1.439422
iter: 17562 | loss: 1.439229
iter: 17563 | loss: 1.439035
iter: 17564 | loss: 1.438842
iter: 17565 | loss: 1.438648
iter: 17566 | loss: 1.438455
iter: 17567 | loss: 1.438262
iter: 17568 | loss: 1.438068
iter: 17569 | loss: 1.437875
iter: 17570 | loss: 1.437681
iter: 17571 | loss: 1.437488
iter: 17572 | loss: 1.437295
iter: 17573 | loss: 1.437101
iter: 17574 | loss: 1.436908
iter: 17575 | loss: 1.436715
iter: 17576 | loss: 1.436521
iter: 17577 | loss: 1.436328
iter: 17578 | loss: 1.436134
iter: 17579 | loss: 1.435941
iter: 17580 | loss: 1.435748
iter: 17581 | loss: 1.435554
iter: 17582 | loss: 1.435361
iter: 17583 | loss: 1.435167
iter: 17584 | loss: 1.434974
iter: 17585 | loss: 1.434781
iter: 17586 | loss: 1.434587
iter: 17587 | loss: 1.434394
iter: 17588 | loss: 1.434200
iter: 17589 | loss: 1.434007
iter: 17590 | loss: 1.433814
iter: 17591 | loss: 1.433620
iter: 17592 | loss: 1.433427
iter: 17593 | loss: 1.433234
iter: 17594 | loss: 1.433040
iter: 17595 | loss: 1.432847
iter: 17596 | loss: 1.432653
iter: 17597 | loss: 1.432460
iter: 17598 | loss: 1.432267
iter: 17599 | loss: 1.432073
iter: 17600 | loss: 1.431880
iter: 17601 | loss: 1.431686
iter: 17602 | loss: 1.431493
iter: 17603 | loss: 1.431300
iter: 17604 | loss: 1.431106
iter: 17605 | loss: 1.430913
iter: 17606 | loss: 1.430720
iter: 17607 | loss: 1.430526
iter: 17608 | loss: 1.430333
iter: 17609 | loss: 1.430139
iter: 17610 | loss: 1.429946
iter: 17611 | loss: 1.429753
iter: 17612 | loss: 1.429559
iter: 17613 | loss: 1.429366
iter: 17614 | loss: 1.429172
iter: 17615 | loss: 1.428979
iter: 17616 | loss: 1.428786
iter: 17617 | loss: 1.428592
iter: 17618 | loss: 1.428399
iter: 17619 | loss: 1.428205
iter: 17620 | loss: 1.428012
iter: 17621 | loss: 1.427819
iter: 17622 | loss: 1.427625
iter: 17623 | loss: 1.427432
iter: 17624 | loss: 1.427239
iter: 17625 | loss: 1.427045
iter: 17626 | loss: 1.426852
iter: 17627 | loss: 1.426658
iter: 17628 | loss: 1.426465
iter: 17629 | loss: 1.426272
iter: 17630 | loss: 1.426078
iter: 17631 | loss: 1.425885
iter: 17632 | loss: 1.425691
iter: 17633 | loss: 1.425498
iter: 17634 | loss: 1.425305
iter: 17635 | loss: 1.425111
iter: 17636 | loss: 1.424918
iter: 17637 | loss: 1.424725
iter: 17638 | loss: 1.424531
iter: 17639 | loss: 1.424338
iter: 17640 | loss: 1.424144
iter: 17641 | loss: 1.423951
iter: 17642 | loss: 1.423758
iter: 17643 | loss: 1.423564
iter: 17644 | loss: 1.423371
iter: 17645 | loss: 1.423177
iter: 17646 | loss: 1.422984
iter: 17647 | loss: 1.422791
iter: 17648 | loss: 1.422597
iter: 17649 | loss: 1.422404
iter: 17650 | loss: 1.422210
iter: 17651 | loss: 1.422017
iter: 17652 | loss: 1.421824
iter: 17653 | loss: 1.421630
iter: 17654 | loss: 1.421437
iter: 17655 | loss: 1.421244
iter: 17656 | loss: 1.421050
iter: 17657 | loss: 1.420857
iter: 17658 | loss: 1.420663
iter: 17659 | loss: 1.420470
iter: 17660 | loss: 1.420277
iter: 17661 | loss: 1.420083
iter: 17662 | loss: 1.419890
iter: 17663 | loss: 1.419696
iter: 17664 | loss: 1.419503
iter: 17665 | loss: 1.419310
iter: 17666 | loss: 1.419116
iter: 17667 | loss: 1.418923
iter: 17668 | loss: 1.418730
iter: 17669 | loss: 1.418536
iter: 17670 | loss: 1.418343
iter: 17671 | loss: 1.418149
iter: 17672 | loss: 1.417956
iter: 17673 | loss: 1.417763
iter: 17674 | loss: 1.417569
iter: 17675 | loss: 1.417376
iter: 17676 | loss: 1.417182
iter: 17677 | loss: 1.416989
iter: 17678 | loss: 1.416796
iter: 17679 | loss: 1.416602
iter: 17680 | loss: 1.416409
iter: 17681 | loss: 1.416215
iter: 17682 | loss: 1.416022
iter: 17683 | loss: 1.415829
iter: 17684 | loss: 1.415635
iter: 17685 | loss: 1.415442
iter: 17686 | loss: 1.415249
iter: 17687 | loss: 1.415055
iter: 17688 | loss: 1.414862
iter: 17689 | loss: 1.414668
iter: 17690 | loss: 1.414475
iter: 17691 | loss: 1.414282
iter: 17692 | loss: 1.414088
iter: 17693 | loss: 1.413895
iter: 17694 | loss: 1.413701
iter: 17695 | loss: 1.413508
iter: 17696 | loss: 1.413315
iter: 17697 | loss: 1.413121
iter: 17698 | loss: 1.412928
iter: 17699 | loss: 1.412735
iter: 17700 | loss: 1.412541
iter: 17701 | loss: 1.412348
iter: 17702 | loss: 1.412154
iter: 17703 | loss: 1.411961
iter: 17704 | loss: 1.411768
iter: 17705 | loss: 1.411574
iter: 17706 | loss: 1.411381
iter: 17707 | loss: 1.411187
iter: 17708 | loss: 1.410994
iter: 17709 | loss: 1.410801
iter: 17710 | loss: 1.410607
iter: 17711 | loss: 1.410414
iter: 17712 | loss: 1.410220
iter: 17713 | loss: 1.410027
iter: 17714 | loss: 1.409834
iter: 17715 | loss: 1.409640
iter: 17716 | loss: 1.409447
iter: 17717 | loss: 1.409254
iter: 17718 | loss: 1.409060
iter: 17719 | loss: 1.408867
iter: 17720 | loss: 1.408673
iter: 17721 | loss: 1.408480
iter: 17722 | loss: 1.408287
iter: 17723 | loss: 1.408093
iter: 17724 | loss: 1.407900
iter: 17725 | loss: 1.407706
iter: 17726 | loss: 1.407513
iter: 17727 | loss: 1.407320
iter: 17728 | loss: 1.407126
iter: 17729 | loss: 1.406933
iter: 17730 | loss: 1.406740
iter: 17731 | loss: 1.406546
iter: 17732 | loss: 1.406353
iter: 17733 | loss: 1.406159
iter: 17734 | loss: 1.405966
iter: 17735 | loss: 1.405773
iter: 17736 | loss: 1.405579
iter: 17737 | loss: 1.405386
iter: 17738 | loss: 1.405192
iter: 17739 | loss: 1.404999
iter: 17740 | loss: 1.404806
iter: 17741 | loss: 1.404612
iter: 17742 | loss: 1.404419
iter: 17743 | loss: 1.404226
iter: 17744 | loss: 1.404032
iter: 17745 | loss: 1.403839
iter: 17746 | loss: 1.403645
iter: 17747 | loss: 1.403452
iter: 17748 | loss: 1.403259
iter: 17749 | loss: 1.403065
iter: 17750 | loss: 1.402872
iter: 17751 | loss: 1.402678
iter: 17752 | loss: 1.402485
iter: 17753 | loss: 1.402292
iter: 17754 | loss: 1.402098
iter: 17755 | loss: 1.401905
iter: 17756 | loss: 1.401711
iter: 17757 | loss: 1.401518
iter: 17758 | loss: 1.401325
iter: 17759 | loss: 1.401131
iter: 17760 | loss: 1.400938
iter: 17761 | loss: 1.400745
iter: 17762 | loss: 1.400551
iter: 17763 | loss: 1.400358
iter: 17764 | loss: 1.400164
iter: 17765 | loss: 1.399971
iter: 17766 | loss: 1.399778
iter: 17767 | loss: 1.399584
iter: 17768 | loss: 1.399391
iter: 17769 | loss: 1.399197
iter: 17770 | loss: 1.399004
iter: 17771 | loss: 1.398811
iter: 17772 | loss: 1.398617
iter: 17773 | loss: 1.398424
iter: 17774 | loss: 1.398231
iter: 17775 | loss: 1.398037
iter: 17776 | loss: 1.397844
iter: 17777 | loss: 1.397650
iter: 17778 | loss: 1.397457
iter: 17779 | loss: 1.397264
iter: 17780 | loss: 1.397070
iter: 17781 | loss: 1.396877
iter: 17782 | loss: 1.396683
iter: 17783 | loss: 1.396490
iter: 17784 | loss: 1.396297
iter: 17785 | loss: 1.396103
iter: 17786 | loss: 1.395910
iter: 17787 | loss: 1.395716
iter: 17788 | loss: 1.395523
iter: 17789 | loss: 1.395330
iter: 17790 | loss: 1.395136
iter: 17791 | loss: 1.394943
iter: 17792 | loss: 1.394750
iter: 17793 | loss: 1.394556
iter: 17794 | loss: 1.394363
iter: 17795 | loss: 1.394169
iter: 17796 | loss: 1.393976
iter: 17797 | loss: 1.393783
iter: 17798 | loss: 1.393589
iter: 17799 | loss: 1.393396
iter: 17800 | loss: 1.393202
iter: 17801 | loss: 1.393009
iter: 17802 | loss: 1.392816
iter: 17803 | loss: 1.392622
iter: 17804 | loss: 1.392429
iter: 17805 | loss: 1.392236
iter: 17806 | loss: 1.392042
iter: 17807 | loss: 1.391849
iter: 17808 | loss: 1.391655
iter: 17809 | loss: 1.391462
iter: 17810 | loss: 1.391269
iter: 17811 | loss: 1.391075
iter: 17812 | loss: 1.390882
iter: 17813 | loss: 1.390688
iter: 17814 | loss: 1.390495
iter: 17815 | loss: 1.390302
iter: 17816 | loss: 1.390108
iter: 17817 | loss: 1.389915
iter: 17818 | loss: 1.389721
iter: 17819 | loss: 1.389528
iter: 17820 | loss: 1.389335
iter: 17821 | loss: 1.389141
iter: 17822 | loss: 1.388948
iter: 17823 | loss: 1.388755
iter: 17824 | loss: 1.388561
iter: 17825 | loss: 1.388368
iter: 17826 | loss: 1.388174
iter: 17827 | loss: 1.387981
iter: 17828 | loss: 1.387788
iter: 17829 | loss: 1.387594
iter: 17830 | loss: 1.387401
iter: 17831 | loss: 1.387207
iter: 17832 | loss: 1.387014
iter: 17833 | loss: 1.386821
iter: 17834 | loss: 1.386627
iter: 17835 | loss: 1.386434
iter: 17836 | loss: 1.386241
iter: 17837 | loss: 1.386047
iter: 17838 | loss: 1.385854
iter: 17839 | loss: 1.385660
iter: 17840 | loss: 1.385467
iter: 17841 | loss: 1.385274
iter: 17842 | loss: 1.385080
iter: 17843 | loss: 1.384887
iter: 17844 | loss: 1.384693
iter: 17845 | loss: 1.384500
iter: 17846 | loss: 1.384307
iter: 17847 | loss: 1.384113
iter: 17848 | loss: 1.383920
iter: 17849 | loss: 1.383726
iter: 17850 | loss: 1.383533
iter: 17851 | loss: 1.383340
iter: 17852 | loss: 1.383146
iter: 17853 | loss: 1.382953
iter: 17854 | loss: 1.382760
iter: 17855 | loss: 1.382566
iter: 17856 | loss: 1.382373
iter: 17857 | loss: 1.382179
iter: 17858 | loss: 1.381986
iter: 17859 | loss: 1.381793
iter: 17860 | loss: 1.381599
iter: 17861 | loss: 1.381406
iter: 17862 | loss: 1.381212
iter: 17863 | loss: 1.381019
iter: 17864 | loss: 1.380826
iter: 17865 | loss: 1.380632
iter: 17866 | loss: 1.380439
iter: 17867 | loss: 1.380246
iter: 17868 | loss: 1.380052
iter: 17869 | loss: 1.379859
iter: 17870 | loss: 1.379665
iter: 17871 | loss: 1.379472
iter: 17872 | loss: 1.379279
iter: 17873 | loss: 1.379085
iter: 17874 | loss: 1.378892
iter: 17875 | loss: 1.378698
iter: 17876 | loss: 1.378505
iter: 17877 | loss: 1.378312
iter: 17878 | loss: 1.378118
iter: 17879 | loss: 1.377925
iter: 17880 | loss: 1.377731
iter: 17881 | loss: 1.377538
iter: 17882 | loss: 1.377345
iter: 17883 | loss: 1.377151
iter: 17884 | loss: 1.376958
iter: 17885 | loss: 1.376765
iter: 17886 | loss: 1.376571
iter: 17887 | loss: 1.376378
iter: 17888 | loss: 1.376184
iter: 17889 | loss: 1.375991
iter: 17890 | loss: 1.375798
iter: 17891 | loss: 1.375604
iter: 17892 | loss: 1.375411
iter: 17893 | loss: 1.375217
iter: 17894 | loss: 1.375024
iter: 17895 | loss: 1.374831
iter: 17896 | loss: 1.374637
iter: 17897 | loss: 1.374444
iter: 17898 | loss: 1.374251
iter: 17899 | loss: 1.374057
iter: 17900 | loss: 1.373864
iter: 17901 | loss: 1.373670
iter: 17902 | loss: 1.373477
iter: 17903 | loss: 1.373284
iter: 17904 | loss: 1.373090
iter: 17905 | loss: 1.372897
iter: 17906 | loss: 1.372703
iter: 17907 | loss: 1.372510
iter: 17908 | loss: 1.372317
iter: 17909 | loss: 1.372123
iter: 17910 | loss: 1.371930
iter: 17911 | loss: 1.371736
iter: 17912 | loss: 1.371543
iter: 17913 | loss: 1.371350
iter: 17914 | loss: 1.371156
iter: 17915 | loss: 1.370963
iter: 17916 | loss: 1.370770
iter: 17917 | loss: 1.370576
iter: 17918 | loss: 1.370383
iter: 17919 | loss: 1.370189
iter: 17920 | loss: 1.369996
iter: 17921 | loss: 1.369803
iter: 17922 | loss: 1.369609
iter: 17923 | loss: 1.369416
iter: 17924 | loss: 1.369222
iter: 17925 | loss: 1.369029
iter: 17926 | loss: 1.368836
iter: 17927 | loss: 1.368642
iter: 17928 | loss: 1.368449
iter: 17929 | loss: 1.368256
iter: 17930 | loss: 1.368062
iter: 17931 | loss: 1.367869
iter: 17932 | loss: 1.367675
iter: 17933 | loss: 1.367482
iter: 17934 | loss: 1.367289
iter: 17935 | loss: 1.367095
iter: 17936 | loss: 1.366902
iter: 17937 | loss: 1.366708
iter: 17938 | loss: 1.366515
iter: 17939 | loss: 1.366322
iter: 17940 | loss: 1.366128
iter: 17941 | loss: 1.365935
iter: 17942 | loss: 1.365741
iter: 17943 | loss: 1.365548
iter: 17944 | loss: 1.365355
iter: 17945 | loss: 1.365161
iter: 17946 | loss: 1.364968
iter: 17947 | loss: 1.364775
iter: 17948 | loss: 1.364581
iter: 17949 | loss: 1.364388
iter: 17950 | loss: 1.364194
iter: 17951 | loss: 1.364001
iter: 17952 | loss: 1.363808
iter: 17953 | loss: 1.363614
iter: 17954 | loss: 1.363421
iter: 17955 | loss: 1.363227
iter: 17956 | loss: 1.363034
iter: 17957 | loss: 1.362841
iter: 17958 | loss: 1.362647
iter: 17959 | loss: 1.362454
iter: 17960 | loss: 1.362261
iter: 17961 | loss: 1.362067
iter: 17962 | loss: 1.361874
iter: 17963 | loss: 1.361680
iter: 17964 | loss: 1.361487
iter: 17965 | loss: 1.361294
iter: 17966 | loss: 1.361100
iter: 17967 | loss: 1.360907
iter: 17968 | loss: 1.360713
iter: 17969 | loss: 1.360520
iter: 17970 | loss: 1.360327
iter: 17971 | loss: 1.360133
iter: 17972 | loss: 1.359940
iter: 17973 | loss: 1.359746
iter: 17974 | loss: 1.359553
iter: 17975 | loss: 1.359360
iter: 17976 | loss: 1.359166
iter: 17977 | loss: 1.358973
iter: 17978 | loss: 1.358780
iter: 17979 | loss: 1.358586
iter: 17980 | loss: 1.358393
iter: 17981 | loss: 1.358199
iter: 17982 | loss: 1.358006
iter: 17983 | loss: 1.357813
iter: 17984 | loss: 1.357619
iter: 17985 | loss: 1.357426
iter: 17986 | loss: 1.357232
iter: 17987 | loss: 1.357039
iter: 17988 | loss: 1.356846
iter: 17989 | loss: 1.356652
iter: 17990 | loss: 1.356459
iter: 17991 | loss: 1.356266
iter: 17992 | loss: 1.356072
iter: 17993 | loss: 1.355879
iter: 17994 | loss: 1.355685
iter: 17995 | loss: 1.355492
iter: 17996 | loss: 1.355299
iter: 17997 | loss: 1.355105
iter: 17998 | loss: 1.354912
iter: 17999 | loss: 1.354718
iter: 18000 | loss: 1.354525
iter: 18001 | loss: 1.354332
iter: 18002 | loss: 1.354138
iter: 18003 | loss: 1.353945
iter: 18004 | loss: 1.353751
iter: 18005 | loss: 1.353558
iter: 18006 | loss: 1.353365
iter: 18007 | loss: 1.353171
iter: 18008 | loss: 1.352978
iter: 18009 | loss: 1.352785
iter: 18010 | loss: 1.352591
iter: 18011 | loss: 1.352398
iter: 18012 | loss: 1.352204
iter: 18013 | loss: 1.352011
iter: 18014 | loss: 1.351818
iter: 18015 | loss: 1.351624
iter: 18016 | loss: 1.351431
iter: 18017 | loss: 1.351237
iter: 18018 | loss: 1.351044
iter: 18019 | loss: 1.350851
iter: 18020 | loss: 1.350657
iter: 18021 | loss: 1.350464
iter: 18022 | loss: 1.350271
iter: 18023 | loss: 1.350077
iter: 18024 | loss: 1.349884
iter: 18025 | loss: 1.349690
iter: 18026 | loss: 1.349497
iter: 18027 | loss: 1.349304
iter: 18028 | loss: 1.349110
iter: 18029 | loss: 1.348917
iter: 18030 | loss: 1.348723
iter: 18031 | loss: 1.348530
iter: 18032 | loss: 1.348337
iter: 18033 | loss: 1.348143
iter: 18034 | loss: 1.347950
iter: 18035 | loss: 1.347756
iter: 18036 | loss: 1.347563
iter: 18037 | loss: 1.347370
iter: 18038 | loss: 1.347176
iter: 18039 | loss: 1.346983
iter: 18040 | loss: 1.346790
iter: 18041 | loss: 1.346596
iter: 18042 | loss: 1.346403
iter: 18043 | loss: 1.346209
iter: 18044 | loss: 1.346016
iter: 18045 | loss: 1.345823
iter: 18046 | loss: 1.345629
iter: 18047 | loss: 1.345436
iter: 18048 | loss: 1.345242
iter: 18049 | loss: 1.345049
iter: 18050 | loss: 1.344856
iter: 18051 | loss: 1.344662
iter: 18052 | loss: 1.344469
iter: 18053 | loss: 1.344276
iter: 18054 | loss: 1.344082
iter: 18055 | loss: 1.343889
iter: 18056 | loss: 1.343695
iter: 18057 | loss: 1.343502
iter: 18058 | loss: 1.343309
iter: 18059 | loss: 1.343115
iter: 18060 | loss: 1.342922
iter: 18061 | loss: 1.342728
iter: 18062 | loss: 1.342535
iter: 18063 | loss: 1.342342
iter: 18064 | loss: 1.342148
iter: 18065 | loss: 1.341955
iter: 18066 | loss: 1.341762
iter: 18067 | loss: 1.341568
iter: 18068 | loss: 1.341375
iter: 18069 | loss: 1.341181
iter: 18070 | loss: 1.340988
iter: 18071 | loss: 1.340795
iter: 18072 | loss: 1.340601
iter: 18073 | loss: 1.340408
iter: 18074 | loss: 1.340214
iter: 18075 | loss: 1.340021
iter: 18076 | loss: 1.339828
iter: 18077 | loss: 1.339634
iter: 18078 | loss: 1.339441
iter: 18079 | loss: 1.339247
iter: 18080 | loss: 1.339054
iter: 18081 | loss: 1.338861
iter: 18082 | loss: 1.338667
iter: 18083 | loss: 1.338474
iter: 18084 | loss: 1.338281
iter: 18085 | loss: 1.338087
iter: 18086 | loss: 1.337894
iter: 18087 | loss: 1.337700
iter: 18088 | loss: 1.337507
iter: 18089 | loss: 1.337314
iter: 18090 | loss: 1.337120
iter: 18091 | loss: 1.336927
iter: 18092 | loss: 1.336733
iter: 18093 | loss: 1.336540
iter: 18094 | loss: 1.336347
iter: 18095 | loss: 1.336153
iter: 18096 | loss: 1.335960
iter: 18097 | loss: 1.335767
iter: 18098 | loss: 1.335573
iter: 18099 | loss: 1.335380
iter: 18100 | loss: 1.335186
iter: 18101 | loss: 1.334993
iter: 18102 | loss: 1.334800
iter: 18103 | loss: 1.334606
iter: 18104 | loss: 1.334413
iter: 18105 | loss: 1.334219
iter: 18106 | loss: 1.334026
iter: 18107 | loss: 1.333833
iter: 18108 | loss: 1.333639
iter: 18109 | loss: 1.333446
iter: 18110 | loss: 1.333252
iter: 18111 | loss: 1.333059
iter: 18112 | loss: 1.332866
iter: 18113 | loss: 1.332672
iter: 18114 | loss: 1.332479
iter: 18115 | loss: 1.332286
iter: 18116 | loss: 1.332092
iter: 18117 | loss: 1.331899
iter: 18118 | loss: 1.331705
iter: 18119 | loss: 1.331512
iter: 18120 | loss: 1.331319
iter: 18121 | loss: 1.331125
iter: 18122 | loss: 1.330932
iter: 18123 | loss: 1.330738
iter: 18124 | loss: 1.330545
iter: 18125 | loss: 1.330352
iter: 18126 | loss: 1.330158
iter: 18127 | loss: 1.329965
iter: 18128 | loss: 1.329772
iter: 18129 | loss: 1.329578
iter: 18130 | loss: 1.329385
iter: 18131 | loss: 1.329191
iter: 18132 | loss: 1.328998
iter: 18133 | loss: 1.328805
iter: 18134 | loss: 1.328611
iter: 18135 | loss: 1.328418
iter: 18136 | loss: 1.328224
iter: 18137 | loss: 1.328031
iter: 18138 | loss: 1.327838
iter: 18139 | loss: 1.327644
iter: 18140 | loss: 1.327451
iter: 18141 | loss: 1.327257
iter: 18142 | loss: 1.327064
iter: 18143 | loss: 1.326871
iter: 18144 | loss: 1.326677
iter: 18145 | loss: 1.326484
iter: 18146 | loss: 1.326291
iter: 18147 | loss: 1.326097
iter: 18148 | loss: 1.325904
iter: 18149 | loss: 1.325710
iter: 18150 | loss: 1.325517
iter: 18151 | loss: 1.325324
iter: 18152 | loss: 1.325130
iter: 18153 | loss: 1.324937
iter: 18154 | loss: 1.324743
iter: 18155 | loss: 1.324550
iter: 18156 | loss: 1.324357
iter: 18157 | loss: 1.324163
iter: 18158 | loss: 1.323970
iter: 18159 | loss: 1.323777
iter: 18160 | loss: 1.323583
iter: 18161 | loss: 1.323390
iter: 18162 | loss: 1.323196
iter: 18163 | loss: 1.323003
iter: 18164 | loss: 1.322810
iter: 18165 | loss: 1.322616
iter: 18166 | loss: 1.322423
iter: 18167 | loss: 1.322229
iter: 18168 | loss: 1.322036
iter: 18169 | loss: 1.321843
iter: 18170 | loss: 1.321649
iter: 18171 | loss: 1.321456
iter: 18172 | loss: 1.321262
iter: 18173 | loss: 1.321069
iter: 18174 | loss: 1.320876
iter: 18175 | loss: 1.320682
iter: 18176 | loss: 1.320489
iter: 18177 | loss: 1.320296
iter: 18178 | loss: 1.320102
iter: 18179 | loss: 1.319909
iter: 18180 | loss: 1.319715
iter: 18181 | loss: 1.319522
iter: 18182 | loss: 1.319329
iter: 18183 | loss: 1.319135
iter: 18184 | loss: 1.318942
iter: 18185 | loss: 1.318748
iter: 18186 | loss: 1.318555
iter: 18187 | loss: 1.318362
iter: 18188 | loss: 1.318168
iter: 18189 | loss: 1.317975
iter: 18190 | loss: 1.317782
iter: 18191 | loss: 1.317588
iter: 18192 | loss: 1.317395
iter: 18193 | loss: 1.317201
iter: 18194 | loss: 1.317008
iter: 18195 | loss: 1.316815
iter: 18196 | loss: 1.316621
iter: 18197 | loss: 1.316428
iter: 18198 | loss: 1.316234
iter: 18199 | loss: 1.316041
iter: 18200 | loss: 1.315848
iter: 18201 | loss: 1.315654
iter: 18202 | loss: 1.315461
iter: 18203 | loss: 1.315267
iter: 18204 | loss: 1.315074
iter: 18205 | loss: 1.314881
iter: 18206 | loss: 1.314687
iter: 18207 | loss: 1.314494
iter: 18208 | loss: 1.314301
iter: 18209 | loss: 1.314107
iter: 18210 | loss: 1.313914
iter: 18211 | loss: 1.313720
iter: 18212 | loss: 1.313527
iter: 18213 | loss: 1.313334
iter: 18214 | loss: 1.313140
iter: 18215 | loss: 1.312947
iter: 18216 | loss: 1.312753
iter: 18217 | loss: 1.312560
iter: 18218 | loss: 1.312367
iter: 18219 | loss: 1.312173
iter: 18220 | loss: 1.311980
iter: 18221 | loss: 1.311787
iter: 18222 | loss: 1.311593
iter: 18223 | loss: 1.311400
iter: 18224 | loss: 1.311206
iter: 18225 | loss: 1.311013
iter: 18226 | loss: 1.310820
iter: 18227 | loss: 1.310626
iter: 18228 | loss: 1.310433
iter: 18229 | loss: 1.310239
iter: 18230 | loss: 1.310046
iter: 18231 | loss: 1.309853
iter: 18232 | loss: 1.309659
iter: 18233 | loss: 1.309466
iter: 18234 | loss: 1.309272
iter: 18235 | loss: 1.309079
iter: 18236 | loss: 1.308886
iter: 18237 | loss: 1.308692
iter: 18238 | loss: 1.308499
iter: 18239 | loss: 1.308306
iter: 18240 | loss: 1.308112
iter: 18241 | loss: 1.307919
iter: 18242 | loss: 1.307725
iter: 18243 | loss: 1.307532
iter: 18244 | loss: 1.307339
iter: 18245 | loss: 1.307145
iter: 18246 | loss: 1.306952
iter: 18247 | loss: 1.306758
iter: 18248 | loss: 1.306565
iter: 18249 | loss: 1.306372
iter: 18250 | loss: 1.306178
iter: 18251 | loss: 1.305985
iter: 18252 | loss: 1.305792
iter: 18253 | loss: 1.305598
iter: 18254 | loss: 1.305405
iter: 18255 | loss: 1.305211
iter: 18256 | loss: 1.305018
iter: 18257 | loss: 1.304825
iter: 18258 | loss: 1.304631
iter: 18259 | loss: 1.304438
iter: 18260 | loss: 1.304244
iter: 18261 | loss: 1.304051
iter: 18262 | loss: 1.303858
iter: 18263 | loss: 1.303664
iter: 18264 | loss: 1.303471
iter: 18265 | loss: 1.303277
iter: 18266 | loss: 1.303084
iter: 18267 | loss: 1.302891
iter: 18268 | loss: 1.302697
iter: 18269 | loss: 1.302504
iter: 18270 | loss: 1.302311
iter: 18271 | loss: 1.302117
iter: 18272 | loss: 1.301924
iter: 18273 | loss: 1.301730
iter: 18274 | loss: 1.301537
iter: 18275 | loss: 1.301344
iter: 18276 | loss: 1.301150
iter: 18277 | loss: 1.300957
iter: 18278 | loss: 1.300763
iter: 18279 | loss: 1.300570
iter: 18280 | loss: 1.300377
iter: 18281 | loss: 1.300183
iter: 18282 | loss: 1.299990
iter: 18283 | loss: 1.299797
iter: 18284 | loss: 1.299603
iter: 18285 | loss: 1.299410
iter: 18286 | loss: 1.299216
iter: 18287 | loss: 1.299023
iter: 18288 | loss: 1.298830
iter: 18289 | loss: 1.298636
iter: 18290 | loss: 1.298443
iter: 18291 | loss: 1.298249
iter: 18292 | loss: 1.298056
iter: 18293 | loss: 1.297863
iter: 18294 | loss: 1.297669
iter: 18295 | loss: 1.297476
iter: 18296 | loss: 1.297282
iter: 18297 | loss: 1.297089
iter: 18298 | loss: 1.296896
iter: 18299 | loss: 1.296702
iter: 18300 | loss: 1.296509
iter: 18301 | loss: 1.296316
iter: 18302 | loss: 1.296122
iter: 18303 | loss: 1.295929
iter: 18304 | loss: 1.295735
iter: 18305 | loss: 1.295542
iter: 18306 | loss: 1.295349
iter: 18307 | loss: 1.295155
iter: 18308 | loss: 1.294962
iter: 18309 | loss: 1.294768
iter: 18310 | loss: 1.294575
iter: 18311 | loss: 1.294382
iter: 18312 | loss: 1.294188
iter: 18313 | loss: 1.293995
iter: 18314 | loss: 1.293802
iter: 18315 | loss: 1.293608
iter: 18316 | loss: 1.293415
iter: 18317 | loss: 1.293221
iter: 18318 | loss: 1.293028
iter: 18319 | loss: 1.292835
iter: 18320 | loss: 1.292641
iter: 18321 | loss: 1.292448
iter: 18322 | loss: 1.292254
iter: 18323 | loss: 1.292061
iter: 18324 | loss: 1.291868
iter: 18325 | loss: 1.291674
iter: 18326 | loss: 1.291481
iter: 18327 | loss: 1.291287
iter: 18328 | loss: 1.291094
iter: 18329 | loss: 1.290901
iter: 18330 | loss: 1.290707
iter: 18331 | loss: 1.290514
iter: 18332 | loss: 1.290321
iter: 18333 | loss: 1.290127
iter: 18334 | loss: 1.289934
iter: 18335 | loss: 1.289740
iter: 18336 | loss: 1.289547
iter: 18337 | loss: 1.289354
iter: 18338 | loss: 1.289160
iter: 18339 | loss: 1.288967
iter: 18340 | loss: 1.288773
iter: 18341 | loss: 1.288580
iter: 18342 | loss: 1.288387
iter: 18343 | loss: 1.288193
iter: 18344 | loss: 1.288000
iter: 18345 | loss: 1.287807
iter: 18346 | loss: 1.287613
iter: 18347 | loss: 1.287420
iter: 18348 | loss: 1.287226
iter: 18349 | loss: 1.287033
iter: 18350 | loss: 1.286840
iter: 18351 | loss: 1.286646
iter: 18352 | loss: 1.286453
iter: 18353 | loss: 1.286259
iter: 18354 | loss: 1.286066
iter: 18355 | loss: 1.285873
iter: 18356 | loss: 1.285679
iter: 18357 | loss: 1.285486
iter: 18358 | loss: 1.285292
iter: 18359 | loss: 1.285099
iter: 18360 | loss: 1.284906
iter: 18361 | loss: 1.284712
iter: 18362 | loss: 1.284519
iter: 18363 | loss: 1.284326
iter: 18364 | loss: 1.284132
iter: 18365 | loss: 1.283939
iter: 18366 | loss: 1.283745
iter: 18367 | loss: 1.283552
iter: 18368 | loss: 1.283359
iter: 18369 | loss: 1.283165
iter: 18370 | loss: 1.282972
iter: 18371 | loss: 1.282778
iter: 18372 | loss: 1.282585
iter: 18373 | loss: 1.282392
iter: 18374 | loss: 1.282198
iter: 18375 | loss: 1.282005
iter: 18376 | loss: 1.281812
iter: 18377 | loss: 1.281618
iter: 18378 | loss: 1.281425
iter: 18379 | loss: 1.281231
iter: 18380 | loss: 1.281038
iter: 18381 | loss: 1.280845
iter: 18382 | loss: 1.280651
iter: 18383 | loss: 1.280458
iter: 18384 | loss: 1.280264
iter: 18385 | loss: 1.280071
iter: 18386 | loss: 1.279878
iter: 18387 | loss: 1.279684
iter: 18388 | loss: 1.279491
iter: 18389 | loss: 1.279298
iter: 18390 | loss: 1.279104
iter: 18391 | loss: 1.278911
iter: 18392 | loss: 1.278717
iter: 18393 | loss: 1.278524
iter: 18394 | loss: 1.278331
iter: 18395 | loss: 1.278137
iter: 18396 | loss: 1.277944
iter: 18397 | loss: 1.277750
iter: 18398 | loss: 1.277557
iter: 18399 | loss: 1.277364
iter: 18400 | loss: 1.277170
iter: 18401 | loss: 1.276977
iter: 18402 | loss: 1.276783
iter: 18403 | loss: 1.276590
iter: 18404 | loss: 1.276397
iter: 18405 | loss: 1.276203
iter: 18406 | loss: 1.276010
iter: 18407 | loss: 1.275817
iter: 18408 | loss: 1.275623
iter: 18409 | loss: 1.275430
iter: 18410 | loss: 1.275236
iter: 18411 | loss: 1.275043
iter: 18412 | loss: 1.274850
iter: 18413 | loss: 1.274656
iter: 18414 | loss: 1.274463
iter: 18415 | loss: 1.274269
iter: 18416 | loss: 1.274076
iter: 18417 | loss: 1.273883
iter: 18418 | loss: 1.273689
iter: 18419 | loss: 1.273496
iter: 18420 | loss: 1.273303
iter: 18421 | loss: 1.273109
iter: 18422 | loss: 1.272916
iter: 18423 | loss: 1.272722
iter: 18424 | loss: 1.272529
iter: 18425 | loss: 1.272336
iter: 18426 | loss: 1.272142
iter: 18427 | loss: 1.271949
iter: 18428 | loss: 1.271755
iter: 18429 | loss: 1.271562
iter: 18430 | loss: 1.271369
iter: 18431 | loss: 1.271175
iter: 18432 | loss: 1.270982
iter: 18433 | loss: 1.270788
iter: 18434 | loss: 1.270595
iter: 18435 | loss: 1.270402
iter: 18436 | loss: 1.270208
iter: 18437 | loss: 1.270015
iter: 18438 | loss: 1.269822
iter: 18439 | loss: 1.269628
iter: 18440 | loss: 1.269435
iter: 18441 | loss: 1.269241
iter: 18442 | loss: 1.269048
iter: 18443 | loss: 1.268855
iter: 18444 | loss: 1.268661
iter: 18445 | loss: 1.268468
iter: 18446 | loss: 1.268274
iter: 18447 | loss: 1.268081
iter: 18448 | loss: 1.267888
iter: 18449 | loss: 1.267694
iter: 18450 | loss: 1.267501
iter: 18451 | loss: 1.267308
iter: 18452 | loss: 1.267114
iter: 18453 | loss: 1.266921
iter: 18454 | loss: 1.266727
iter: 18455 | loss: 1.266534
iter: 18456 | loss: 1.266341
iter: 18457 | loss: 1.266147
iter: 18458 | loss: 1.265954
iter: 18459 | loss: 1.265760
iter: 18460 | loss: 1.265567
iter: 18461 | loss: 1.265374
iter: 18462 | loss: 1.265180
iter: 18463 | loss: 1.264987
iter: 18464 | loss: 1.264793
iter: 18465 | loss: 1.264600
iter: 18466 | loss: 1.264407
iter: 18467 | loss: 1.264213
iter: 18468 | loss: 1.264020
iter: 18469 | loss: 1.263827
iter: 18470 | loss: 1.263633
iter: 18471 | loss: 1.263440
iter: 18472 | loss: 1.263246
iter: 18473 | loss: 1.263053
iter: 18474 | loss: 1.262860
iter: 18475 | loss: 1.262666
iter: 18476 | loss: 1.262473
iter: 18477 | loss: 1.262279
iter: 18478 | loss: 1.262086
iter: 18479 | loss: 1.261893
iter: 18480 | loss: 1.261699
iter: 18481 | loss: 1.261506
iter: 18482 | loss: 1.261313
iter: 18483 | loss: 1.261119
iter: 18484 | loss: 1.260926
iter: 18485 | loss: 1.260732
iter: 18486 | loss: 1.260539
iter: 18487 | loss: 1.260346
iter: 18488 | loss: 1.260152
iter: 18489 | loss: 1.259959
iter: 18490 | loss: 1.259765
iter: 18491 | loss: 1.259572
iter: 18492 | loss: 1.259379
iter: 18493 | loss: 1.259185
iter: 18494 | loss: 1.258992
iter: 18495 | loss: 1.258798
iter: 18496 | loss: 1.258605
iter: 18497 | loss: 1.258412
iter: 18498 | loss: 1.258218
iter: 18499 | loss: 1.258025
iter: 18500 | loss: 1.257832
iter: 18501 | loss: 1.257638
iter: 18502 | loss: 1.257445
iter: 18503 | loss: 1.257251
iter: 18504 | loss: 1.257058
iter: 18505 | loss: 1.256865
iter: 18506 | loss: 1.256671
iter: 18507 | loss: 1.256478
iter: 18508 | loss: 1.256284
iter: 18509 | loss: 1.256091
iter: 18510 | loss: 1.255898
iter: 18511 | loss: 1.255704
iter: 18512 | loss: 1.255511
iter: 18513 | loss: 1.255318
iter: 18514 | loss: 1.255124
iter: 18515 | loss: 1.254931
iter: 18516 | loss: 1.254737
iter: 18517 | loss: 1.254544
iter: 18518 | loss: 1.254351
iter: 18519 | loss: 1.254157
iter: 18520 | loss: 1.253964
iter: 18521 | loss: 1.253770
iter: 18522 | loss: 1.253577
iter: 18523 | loss: 1.253384
iter: 18524 | loss: 1.253190
iter: 18525 | loss: 1.252997
iter: 18526 | loss: 1.252803
iter: 18527 | loss: 1.252610
iter: 18528 | loss: 1.252417
iter: 18529 | loss: 1.252223
iter: 18530 | loss: 1.252030
iter: 18531 | loss: 1.251837
iter: 18532 | loss: 1.251643
iter: 18533 | loss: 1.251450
iter: 18534 | loss: 1.251256
iter: 18535 | loss: 1.251063
iter: 18536 | loss: 1.250870
iter: 18537 | loss: 1.250676
iter: 18538 | loss: 1.250483
iter: 18539 | loss: 1.250289
iter: 18540 | loss: 1.250096
iter: 18541 | loss: 1.249903
iter: 18542 | loss: 1.249709
iter: 18543 | loss: 1.249516
iter: 18544 | loss: 1.249323
iter: 18545 | loss: 1.249129
iter: 18546 | loss: 1.248936
iter: 18547 | loss: 1.248742
iter: 18548 | loss: 1.248549
iter: 18549 | loss: 1.248356
iter: 18550 | loss: 1.248162
iter: 18551 | loss: 1.247969
iter: 18552 | loss: 1.247775
iter: 18553 | loss: 1.247582
iter: 18554 | loss: 1.247389
iter: 18555 | loss: 1.247195
iter: 18556 | loss: 1.247002
iter: 18557 | loss: 1.246808
iter: 18558 | loss: 1.246615
iter: 18559 | loss: 1.246422
iter: 18560 | loss: 1.246228
iter: 18561 | loss: 1.246035
iter: 18562 | loss: 1.245842
iter: 18563 | loss: 1.245648
iter: 18564 | loss: 1.245455
iter: 18565 | loss: 1.245261
iter: 18566 | loss: 1.245068
iter: 18567 | loss: 1.244875
iter: 18568 | loss: 1.244681
iter: 18569 | loss: 1.244488
iter: 18570 | loss: 1.244294
iter: 18571 | loss: 1.244101
iter: 18572 | loss: 1.243908
iter: 18573 | loss: 1.243714
iter: 18574 | loss: 1.243521
iter: 18575 | loss: 1.243328
iter: 18576 | loss: 1.243134
iter: 18577 | loss: 1.242941
iter: 18578 | loss: 1.242747
iter: 18579 | loss: 1.242554
iter: 18580 | loss: 1.242361
iter: 18581 | loss: 1.242167
iter: 18582 | loss: 1.241974
iter: 18583 | loss: 1.241780
iter: 18584 | loss: 1.241587
iter: 18585 | loss: 1.241394
iter: 18586 | loss: 1.241200
iter: 18587 | loss: 1.241007
iter: 18588 | loss: 1.240813
iter: 18589 | loss: 1.240620
iter: 18590 | loss: 1.240427
iter: 18591 | loss: 1.240233
iter: 18592 | loss: 1.240040
iter: 18593 | loss: 1.239847
iter: 18594 | loss: 1.239653
iter: 18595 | loss: 1.239460
iter: 18596 | loss: 1.239266
iter: 18597 | loss: 1.239073
iter: 18598 | loss: 1.238880
iter: 18599 | loss: 1.238686
iter: 18600 | loss: 1.238493
iter: 18601 | loss: 1.238299
iter: 18602 | loss: 1.238106
iter: 18603 | loss: 1.237913
iter: 18604 | loss: 1.237719
iter: 18605 | loss: 1.237526
iter: 18606 | loss: 1.237333
iter: 18607 | loss: 1.237139
iter: 18608 | loss: 1.236946
iter: 18609 | loss: 1.236752
iter: 18610 | loss: 1.236559
iter: 18611 | loss: 1.236366
iter: 18612 | loss: 1.236172
iter: 18613 | loss: 1.235979
iter: 18614 | loss: 1.235785
iter: 18615 | loss: 1.235592
iter: 18616 | loss: 1.235399
iter: 18617 | loss: 1.235205
iter: 18618 | loss: 1.235012
iter: 18619 | loss: 1.234818
iter: 18620 | loss: 1.234625
iter: 18621 | loss: 1.234432
iter: 18622 | loss: 1.234238
iter: 18623 | loss: 1.234045
iter: 18624 | loss: 1.233852
iter: 18625 | loss: 1.233658
iter: 18626 | loss: 1.233465
iter: 18627 | loss: 1.233271
iter: 18628 | loss: 1.233078
iter: 18629 | loss: 1.232885
iter: 18630 | loss: 1.232691
iter: 18631 | loss: 1.232498
iter: 18632 | loss: 1.232304
iter: 18633 | loss: 1.232111
iter: 18634 | loss: 1.231918
iter: 18635 | loss: 1.231724
iter: 18636 | loss: 1.231531
iter: 18637 | loss: 1.231338
iter: 18638 | loss: 1.231144
iter: 18639 | loss: 1.230951
iter: 18640 | loss: 1.230757
iter: 18641 | loss: 1.230564
iter: 18642 | loss: 1.230371
iter: 18643 | loss: 1.230177
iter: 18644 | loss: 1.229984
iter: 18645 | loss: 1.229790
iter: 18646 | loss: 1.229597
iter: 18647 | loss: 1.229404
iter: 18648 | loss: 1.229210
iter: 18649 | loss: 1.229017
iter: 18650 | loss: 1.228823
iter: 18651 | loss: 1.228630
iter: 18652 | loss: 1.228437
iter: 18653 | loss: 1.228243
iter: 18654 | loss: 1.228050
iter: 18655 | loss: 1.227857
iter: 18656 | loss: 1.227663
iter: 18657 | loss: 1.227470
iter: 18658 | loss: 1.227276
iter: 18659 | loss: 1.227083
iter: 18660 | loss: 1.226890
iter: 18661 | loss: 1.226696
iter: 18662 | loss: 1.226503
iter: 18663 | loss: 1.226309
iter: 18664 | loss: 1.226116
iter: 18665 | loss: 1.225923
iter: 18666 | loss: 1.225729
iter: 18667 | loss: 1.225536
iter: 18668 | loss: 1.225343
iter: 18669 | loss: 1.225149
iter: 18670 | loss: 1.224956
iter: 18671 | loss: 1.224762
iter: 18672 | loss: 1.224569
iter: 18673 | loss: 1.224376
iter: 18674 | loss: 1.224182
iter: 18675 | loss: 1.223989
iter: 18676 | loss: 1.223795
iter: 18677 | loss: 1.223602
iter: 18678 | loss: 1.223409
iter: 18679 | loss: 1.223215
iter: 18680 | loss: 1.223022
iter: 18681 | loss: 1.222828
iter: 18682 | loss: 1.222635
iter: 18683 | loss: 1.222442
iter: 18684 | loss: 1.222248
iter: 18685 | loss: 1.222055
iter: 18686 | loss: 1.221862
iter: 18687 | loss: 1.221668
iter: 18688 | loss: 1.221475
iter: 18689 | loss: 1.221281
iter: 18690 | loss: 1.221088
iter: 18691 | loss: 1.220895
iter: 18692 | loss: 1.220701
iter: 18693 | loss: 1.220508
iter: 18694 | loss: 1.220314
iter: 18695 | loss: 1.220121
iter: 18696 | loss: 1.219928
iter: 18697 | loss: 1.219734
iter: 18698 | loss: 1.219541
iter: 18699 | loss: 1.219348
iter: 18700 | loss: 1.219154
iter: 18701 | loss: 1.218961
iter: 18702 | loss: 1.218767
iter: 18703 | loss: 1.218574
iter: 18704 | loss: 1.218381
iter: 18705 | loss: 1.218187
iter: 18706 | loss: 1.217994
iter: 18707 | loss: 1.217800
iter: 18708 | loss: 1.217607
iter: 18709 | loss: 1.217414
iter: 18710 | loss: 1.217220
iter: 18711 | loss: 1.217027
iter: 18712 | loss: 1.216834
iter: 18713 | loss: 1.216640
iter: 18714 | loss: 1.216447
iter: 18715 | loss: 1.216253
iter: 18716 | loss: 1.216060
iter: 18717 | loss: 1.215867
iter: 18718 | loss: 1.215673
iter: 18719 | loss: 1.215480
iter: 18720 | loss: 1.215286
iter: 18721 | loss: 1.215093
iter: 18722 | loss: 1.214900
iter: 18723 | loss: 1.214706
iter: 18724 | loss: 1.214513
iter: 18725 | loss: 1.214319
iter: 18726 | loss: 1.214126
iter: 18727 | loss: 1.213933
iter: 18728 | loss: 1.213739
iter: 18729 | loss: 1.213546
iter: 18730 | loss: 1.213353
iter: 18731 | loss: 1.213159
iter: 18732 | loss: 1.212966
iter: 18733 | loss: 1.212772
iter: 18734 | loss: 1.212579
iter: 18735 | loss: 1.212386
iter: 18736 | loss: 1.212192
iter: 18737 | loss: 1.211999
iter: 18738 | loss: 1.211805
iter: 18739 | loss: 1.211612
iter: 18740 | loss: 1.211419
iter: 18741 | loss: 1.211225
iter: 18742 | loss: 1.211032
iter: 18743 | loss: 1.210839
iter: 18744 | loss: 1.210645
iter: 18745 | loss: 1.210452
iter: 18746 | loss: 1.210258
iter: 18747 | loss: 1.210065
iter: 18748 | loss: 1.209872
iter: 18749 | loss: 1.209678
iter: 18750 | loss: 1.209485
iter: 18751 | loss: 1.209291
iter: 18752 | loss: 1.209098
iter: 18753 | loss: 1.208905
iter: 18754 | loss: 1.208711
iter: 18755 | loss: 1.208518
iter: 18756 | loss: 1.208324
iter: 18757 | loss: 1.208131
iter: 18758 | loss: 1.207938
iter: 18759 | loss: 1.207744
iter: 18760 | loss: 1.207551
iter: 18761 | loss: 1.207358
iter: 18762 | loss: 1.207164
iter: 18763 | loss: 1.206971
iter: 18764 | loss: 1.206777
iter: 18765 | loss: 1.206584
iter: 18766 | loss: 1.206391
iter: 18767 | loss: 1.206197
iter: 18768 | loss: 1.206004
iter: 18769 | loss: 1.205810
iter: 18770 | loss: 1.205617
iter: 18771 | loss: 1.205424
iter: 18772 | loss: 1.205230
iter: 18773 | loss: 1.205037
iter: 18774 | loss: 1.204844
iter: 18775 | loss: 1.204650
iter: 18776 | loss: 1.204457
iter: 18777 | loss: 1.204263
iter: 18778 | loss: 1.204070
iter: 18779 | loss: 1.203877
iter: 18780 | loss: 1.203683
iter: 18781 | loss: 1.203490
iter: 18782 | loss: 1.203296
iter: 18783 | loss: 1.203103
iter: 18784 | loss: 1.202910
iter: 18785 | loss: 1.202716
iter: 18786 | loss: 1.202523
iter: 18787 | loss: 1.202329
iter: 18788 | loss: 1.202136
iter: 18789 | loss: 1.201943
iter: 18790 | loss: 1.201749
iter: 18791 | loss: 1.201556
iter: 18792 | loss: 1.201363
iter: 18793 | loss: 1.201169
iter: 18794 | loss: 1.200976
iter: 18795 | loss: 1.200782
iter: 18796 | loss: 1.200589
iter: 18797 | loss: 1.200396
iter: 18798 | loss: 1.200202
iter: 18799 | loss: 1.200009
iter: 18800 | loss: 1.199815
iter: 18801 | loss: 1.199622
iter: 18802 | loss: 1.199429
iter: 18803 | loss: 1.199235
iter: 18804 | loss: 1.199042
iter: 18805 | loss: 1.198849
iter: 18806 | loss: 1.198655
iter: 18807 | loss: 1.198462
iter: 18808 | loss: 1.198268
iter: 18809 | loss: 1.198075
iter: 18810 | loss: 1.197882
iter: 18811 | loss: 1.197688
iter: 18812 | loss: 1.197495
iter: 18813 | loss: 1.197301
iter: 18814 | loss: 1.197108
iter: 18815 | loss: 1.196915
iter: 18816 | loss: 1.196721
iter: 18817 | loss: 1.196528
iter: 18818 | loss: 1.196334
iter: 18819 | loss: 1.196141
iter: 18820 | loss: 1.195948
iter: 18821 | loss: 1.195754
iter: 18822 | loss: 1.195561
iter: 18823 | loss: 1.195368
iter: 18824 | loss: 1.195174
iter: 18825 | loss: 1.194981
iter: 18826 | loss: 1.194787
iter: 18827 | loss: 1.194594
iter: 18828 | loss: 1.194401
iter: 18829 | loss: 1.194207
iter: 18830 | loss: 1.194014
iter: 18831 | loss: 1.193820
iter: 18832 | loss: 1.193627
iter: 18833 | loss: 1.193434
iter: 18834 | loss: 1.193240
iter: 18835 | loss: 1.193047
iter: 18836 | loss: 1.192854
iter: 18837 | loss: 1.192660
iter: 18838 | loss: 1.192467
iter: 18839 | loss: 1.192273
iter: 18840 | loss: 1.192080
iter: 18841 | loss: 1.191887
iter: 18842 | loss: 1.191693
iter: 18843 | loss: 1.191500
iter: 18844 | loss: 1.191306
iter: 18845 | loss: 1.191113
iter: 18846 | loss: 1.190920
iter: 18847 | loss: 1.190726
iter: 18848 | loss: 1.190533
iter: 18849 | loss: 1.190339
iter: 18850 | loss: 1.190146
iter: 18851 | loss: 1.189953
iter: 18852 | loss: 1.189759
iter: 18853 | loss: 1.189566
iter: 18854 | loss: 1.189373
iter: 18855 | loss: 1.189179
iter: 18856 | loss: 1.188986
iter: 18857 | loss: 1.188792
iter: 18858 | loss: 1.188599
iter: 18859 | loss: 1.188406
iter: 18860 | loss: 1.188212
iter: 18861 | loss: 1.188019
iter: 18862 | loss: 1.187825
iter: 18863 | loss: 1.187632
iter: 18864 | loss: 1.187439
iter: 18865 | loss: 1.187245
iter: 18866 | loss: 1.187052
iter: 18867 | loss: 1.186859
iter: 18868 | loss: 1.186665
iter: 18869 | loss: 1.186472
iter: 18870 | loss: 1.186278
iter: 18871 | loss: 1.186085
iter: 18872 | loss: 1.185892
iter: 18873 | loss: 1.185698
iter: 18874 | loss: 1.185505
iter: 18875 | loss: 1.185311
iter: 18876 | loss: 1.185118
iter: 18877 | loss: 1.184925
iter: 18878 | loss: 1.184731
iter: 18879 | loss: 1.184538
iter: 18880 | loss: 1.184344
iter: 18881 | loss: 1.184151
iter: 18882 | loss: 1.183958
iter: 18883 | loss: 1.183764
iter: 18884 | loss: 1.183571
iter: 18885 | loss: 1.183378
iter: 18886 | loss: 1.183184
iter: 18887 | loss: 1.182991
iter: 18888 | loss: 1.182797
iter: 18889 | loss: 1.182604
iter: 18890 | loss: 1.182411
iter: 18891 | loss: 1.182217
iter: 18892 | loss: 1.182024
iter: 18893 | loss: 1.181830
iter: 18894 | loss: 1.181637
iter: 18895 | loss: 1.181444
iter: 18896 | loss: 1.181250
iter: 18897 | loss: 1.181057
iter: 18898 | loss: 1.180864
iter: 18899 | loss: 1.180670
iter: 18900 | loss: 1.180477
iter: 18901 | loss: 1.180283
iter: 18902 | loss: 1.180090
iter: 18903 | loss: 1.179897
iter: 18904 | loss: 1.179703
iter: 18905 | loss: 1.179510
iter: 18906 | loss: 1.179316
iter: 18907 | loss: 1.179123
iter: 18908 | loss: 1.178930
iter: 18909 | loss: 1.178736
iter: 18910 | loss: 1.178543
iter: 18911 | loss: 1.178349
iter: 18912 | loss: 1.178156
iter: 18913 | loss: 1.177963
iter: 18914 | loss: 1.177769
iter: 18915 | loss: 1.177576
iter: 18916 | loss: 1.177383
iter: 18917 | loss: 1.177189
iter: 18918 | loss: 1.176996
iter: 18919 | loss: 1.176802
iter: 18920 | loss: 1.176609
iter: 18921 | loss: 1.176416
iter: 18922 | loss: 1.176222
iter: 18923 | loss: 1.176029
iter: 18924 | loss: 1.175835
iter: 18925 | loss: 1.175642
iter: 18926 | loss: 1.175449
iter: 18927 | loss: 1.175255
iter: 18928 | loss: 1.175062
iter: 18929 | loss: 1.174869
iter: 18930 | loss: 1.174675
iter: 18931 | loss: 1.174482
iter: 18932 | loss: 1.174288
iter: 18933 | loss: 1.174095
iter: 18934 | loss: 1.173902
iter: 18935 | loss: 1.173708
iter: 18936 | loss: 1.173515
iter: 18937 | loss: 1.173321
iter: 18938 | loss: 1.173128
iter: 18939 | loss: 1.172935
iter: 18940 | loss: 1.172741
iter: 18941 | loss: 1.172548
iter: 18942 | loss: 1.172354
iter: 18943 | loss: 1.172161
iter: 18944 | loss: 1.171968
iter: 18945 | loss: 1.171774
iter: 18946 | loss: 1.171581
iter: 18947 | loss: 1.171388
iter: 18948 | loss: 1.171194
iter: 18949 | loss: 1.171001
iter: 18950 | loss: 1.170807
iter: 18951 | loss: 1.170614
iter: 18952 | loss: 1.170421
iter: 18953 | loss: 1.170227
iter: 18954 | loss: 1.170034
iter: 18955 | loss: 1.169840
iter: 18956 | loss: 1.169647
iter: 18957 | loss: 1.169454
iter: 18958 | loss: 1.169260
iter: 18959 | loss: 1.169067
iter: 18960 | loss: 1.168874
iter: 18961 | loss: 1.168680
iter: 18962 | loss: 1.168487
iter: 18963 | loss: 1.168293
iter: 18964 | loss: 1.168100
iter: 18965 | loss: 1.167907
iter: 18966 | loss: 1.167713
iter: 18967 | loss: 1.167520
iter: 18968 | loss: 1.167326
iter: 18969 | loss: 1.167133
iter: 18970 | loss: 1.166940
iter: 18971 | loss: 1.166746
iter: 18972 | loss: 1.166553
iter: 18973 | loss: 1.166359
iter: 18974 | loss: 1.166166
iter: 18975 | loss: 1.165973
iter: 18976 | loss: 1.165779
iter: 18977 | loss: 1.165586
iter: 18978 | loss: 1.165393
iter: 18979 | loss: 1.165199
iter: 18980 | loss: 1.165006
iter: 18981 | loss: 1.164812
iter: 18982 | loss: 1.164619
iter: 18983 | loss: 1.164426
iter: 18984 | loss: 1.164232
iter: 18985 | loss: 1.164039
iter: 18986 | loss: 1.163845
iter: 18987 | loss: 1.163652
iter: 18988 | loss: 1.163459
iter: 18989 | loss: 1.163265
iter: 18990 | loss: 1.163072
iter: 18991 | loss: 1.162879
iter: 18992 | loss: 1.162685
iter: 18993 | loss: 1.162492
iter: 18994 | loss: 1.162298
iter: 18995 | loss: 1.162105
iter: 18996 | loss: 1.161912
iter: 18997 | loss: 1.161718
iter: 18998 | loss: 1.161525
iter: 18999 | loss: 1.161331
iter: 19000 | loss: 1.161138
iter: 19001 | loss: 1.160945
iter: 19002 | loss: 1.160751
iter: 19003 | loss: 1.160558
iter: 19004 | loss: 1.160364
iter: 19005 | loss: 1.160171
iter: 19006 | loss: 1.159978
iter: 19007 | loss: 1.159784
iter: 19008 | loss: 1.159591
iter: 19009 | loss: 1.159398
iter: 19010 | loss: 1.159204
iter: 19011 | loss: 1.159011
iter: 19012 | loss: 1.158817
iter: 19013 | loss: 1.158624
iter: 19014 | loss: 1.158431
iter: 19015 | loss: 1.158237
iter: 19016 | loss: 1.158044
iter: 19017 | loss: 1.157850
iter: 19018 | loss: 1.157657
iter: 19019 | loss: 1.157464
iter: 19020 | loss: 1.157270
iter: 19021 | loss: 1.157077
iter: 19022 | loss: 1.156884
iter: 19023 | loss: 1.156690
iter: 19024 | loss: 1.156497
iter: 19025 | loss: 1.156303
iter: 19026 | loss: 1.156110
iter: 19027 | loss: 1.155917
iter: 19028 | loss: 1.155723
iter: 19029 | loss: 1.155530
iter: 19030 | loss: 1.155336
iter: 19031 | loss: 1.155143
iter: 19032 | loss: 1.154950
iter: 19033 | loss: 1.154756
iter: 19034 | loss: 1.154563
iter: 19035 | loss: 1.154370
iter: 19036 | loss: 1.154176
iter: 19037 | loss: 1.153983
iter: 19038 | loss: 1.153789
iter: 19039 | loss: 1.153596
iter: 19040 | loss: 1.153403
iter: 19041 | loss: 1.153209
iter: 19042 | loss: 1.153016
iter: 19043 | loss: 1.152822
iter: 19044 | loss: 1.152629
iter: 19045 | loss: 1.152436
iter: 19046 | loss: 1.152242
iter: 19047 | loss: 1.152049
iter: 19048 | loss: 1.151855
iter: 19049 | loss: 1.151662
iter: 19050 | loss: 1.151469
iter: 19051 | loss: 1.151275
iter: 19052 | loss: 1.151082
iter: 19053 | loss: 1.150889
iter: 19054 | loss: 1.150695
iter: 19055 | loss: 1.150502
iter: 19056 | loss: 1.150308
iter: 19057 | loss: 1.150115
iter: 19058 | loss: 1.149922
iter: 19059 | loss: 1.149728
iter: 19060 | loss: 1.149535
iter: 19061 | loss: 1.149341
iter: 19062 | loss: 1.149148
iter: 19063 | loss: 1.148955
iter: 19064 | loss: 1.148761
iter: 19065 | loss: 1.148568
iter: 19066 | loss: 1.148375
iter: 19067 | loss: 1.148181
iter: 19068 | loss: 1.147988
iter: 19069 | loss: 1.147794
iter: 19070 | loss: 1.147601
iter: 19071 | loss: 1.147408
iter: 19072 | loss: 1.147214
iter: 19073 | loss: 1.147021
iter: 19074 | loss: 1.146827
iter: 19075 | loss: 1.146634
iter: 19076 | loss: 1.146441
iter: 19077 | loss: 1.146247
iter: 19078 | loss: 1.146054
iter: 19079 | loss: 1.145860
iter: 19080 | loss: 1.145667
iter: 19081 | loss: 1.145474
iter: 19082 | loss: 1.145280
iter: 19083 | loss: 1.145087
iter: 19084 | loss: 1.144894
iter: 19085 | loss: 1.144700
iter: 19086 | loss: 1.144507
iter: 19087 | loss: 1.144313
iter: 19088 | loss: 1.144120
iter: 19089 | loss: 1.143927
iter: 19090 | loss: 1.143733
iter: 19091 | loss: 1.143540
iter: 19092 | loss: 1.143346
iter: 19093 | loss: 1.143153
iter: 19094 | loss: 1.142960
iter: 19095 | loss: 1.142766
iter: 19096 | loss: 1.142573
iter: 19097 | loss: 1.142380
iter: 19098 | loss: 1.142186
iter: 19099 | loss: 1.141993
iter: 19100 | loss: 1.141799
iter: 19101 | loss: 1.141606
iter: 19102 | loss: 1.141413
iter: 19103 | loss: 1.141219
iter: 19104 | loss: 1.141026
iter: 19105 | loss: 1.140832
iter: 19106 | loss: 1.140639
iter: 19107 | loss: 1.140446
iter: 19108 | loss: 1.140252
iter: 19109 | loss: 1.140059
iter: 19110 | loss: 1.139865
iter: 19111 | loss: 1.139672
iter: 19112 | loss: 1.139479
iter: 19113 | loss: 1.139285
iter: 19114 | loss: 1.139092
iter: 19115 | loss: 1.138899
iter: 19116 | loss: 1.138705
iter: 19117 | loss: 1.138512
iter: 19118 | loss: 1.138318
iter: 19119 | loss: 1.138125
iter: 19120 | loss: 1.137932
iter: 19121 | loss: 1.137738
iter: 19122 | loss: 1.137545
iter: 19123 | loss: 1.137351
iter: 19124 | loss: 1.137158
iter: 19125 | loss: 1.136965
iter: 19126 | loss: 1.136771
iter: 19127 | loss: 1.136578
iter: 19128 | loss: 1.136385
iter: 19129 | loss: 1.136191
iter: 19130 | loss: 1.135998
iter: 19131 | loss: 1.135804
iter: 19132 | loss: 1.135611
iter: 19133 | loss: 1.135418
iter: 19134 | loss: 1.135224
iter: 19135 | loss: 1.135031
iter: 19136 | loss: 1.134837
iter: 19137 | loss: 1.134644
iter: 19138 | loss: 1.134451
iter: 19139 | loss: 1.134257
iter: 19140 | loss: 1.134064
iter: 19141 | loss: 1.133870
iter: 19142 | loss: 1.133677
iter: 19143 | loss: 1.133484
iter: 19144 | loss: 1.133290
iter: 19145 | loss: 1.133097
iter: 19146 | loss: 1.132904
iter: 19147 | loss: 1.132710
iter: 19148 | loss: 1.132517
iter: 19149 | loss: 1.132323
iter: 19150 | loss: 1.132130
iter: 19151 | loss: 1.131937
iter: 19152 | loss: 1.131743
iter: 19153 | loss: 1.131550
iter: 19154 | loss: 1.131356
iter: 19155 | loss: 1.131163
iter: 19156 | loss: 1.130970
iter: 19157 | loss: 1.130776
iter: 19158 | loss: 1.130583
iter: 19159 | loss: 1.130390
iter: 19160 | loss: 1.130196
iter: 19161 | loss: 1.130003
iter: 19162 | loss: 1.129809
iter: 19163 | loss: 1.129616
iter: 19164 | loss: 1.129423
iter: 19165 | loss: 1.129229
iter: 19166 | loss: 1.129036
iter: 19167 | loss: 1.128842
iter: 19168 | loss: 1.128649
iter: 19169 | loss: 1.128456
iter: 19170 | loss: 1.128262
iter: 19171 | loss: 1.128069
iter: 19172 | loss: 1.127875
iter: 19173 | loss: 1.127682
iter: 19174 | loss: 1.127489
iter: 19175 | loss: 1.127295
iter: 19176 | loss: 1.127102
iter: 19177 | loss: 1.126909
iter: 19178 | loss: 1.126715
iter: 19179 | loss: 1.126522
iter: 19180 | loss: 1.126328
iter: 19181 | loss: 1.126135
iter: 19182 | loss: 1.125942
iter: 19183 | loss: 1.125748
iter: 19184 | loss: 1.125555
iter: 19185 | loss: 1.125361
iter: 19186 | loss: 1.125168
iter: 19187 | loss: 1.124975
iter: 19188 | loss: 1.124781
iter: 19189 | loss: 1.124588
iter: 19190 | loss: 1.124395
iter: 19191 | loss: 1.124201
iter: 19192 | loss: 1.124008
iter: 19193 | loss: 1.123814
iter: 19194 | loss: 1.123621
iter: 19195 | loss: 1.123428
iter: 19196 | loss: 1.123234
iter: 19197 | loss: 1.123041
iter: 19198 | loss: 1.122847
iter: 19199 | loss: 1.122654
iter: 19200 | loss: 1.122461
iter: 19201 | loss: 1.122267
iter: 19202 | loss: 1.122074
iter: 19203 | loss: 1.121880
iter: 19204 | loss: 1.121687
iter: 19205 | loss: 1.121494
iter: 19206 | loss: 1.121300
iter: 19207 | loss: 1.121107
iter: 19208 | loss: 1.120914
iter: 19209 | loss: 1.120720
iter: 19210 | loss: 1.120527
iter: 19211 | loss: 1.120333
iter: 19212 | loss: 1.120140
iter: 19213 | loss: 1.119947
iter: 19214 | loss: 1.119753
iter: 19215 | loss: 1.119560
iter: 19216 | loss: 1.119366
iter: 19217 | loss: 1.119173
iter: 19218 | loss: 1.118980
iter: 19219 | loss: 1.118786
iter: 19220 | loss: 1.118593
iter: 19221 | loss: 1.118400
iter: 19222 | loss: 1.118206
iter: 19223 | loss: 1.118013
iter: 19224 | loss: 1.117819
iter: 19225 | loss: 1.117626
iter: 19226 | loss: 1.117433
iter: 19227 | loss: 1.117239
iter: 19228 | loss: 1.117046
iter: 19229 | loss: 1.116852
iter: 19230 | loss: 1.116659
iter: 19231 | loss: 1.116466
iter: 19232 | loss: 1.116272
iter: 19233 | loss: 1.116079
iter: 19234 | loss: 1.115885
iter: 19235 | loss: 1.115692
iter: 19236 | loss: 1.115499
iter: 19237 | loss: 1.115305
iter: 19238 | loss: 1.115112
iter: 19239 | loss: 1.114919
iter: 19240 | loss: 1.114725
iter: 19241 | loss: 1.114532
iter: 19242 | loss: 1.114338
iter: 19243 | loss: 1.114145
iter: 19244 | loss: 1.113952
iter: 19245 | loss: 1.113758
iter: 19246 | loss: 1.113565
iter: 19247 | loss: 1.113371
iter: 19248 | loss: 1.113178
iter: 19249 | loss: 1.112985
iter: 19250 | loss: 1.112791
iter: 19251 | loss: 1.112598
iter: 19252 | loss: 1.112405
iter: 19253 | loss: 1.112211
iter: 19254 | loss: 1.112018
iter: 19255 | loss: 1.111824
iter: 19256 | loss: 1.111631
iter: 19257 | loss: 1.111438
iter: 19258 | loss: 1.111244
iter: 19259 | loss: 1.111051
iter: 19260 | loss: 1.110857
iter: 19261 | loss: 1.110664
iter: 19262 | loss: 1.110471
iter: 19263 | loss: 1.110277
iter: 19264 | loss: 1.110084
iter: 19265 | loss: 1.109890
iter: 19266 | loss: 1.109697
iter: 19267 | loss: 1.109504
iter: 19268 | loss: 1.109310
iter: 19269 | loss: 1.109117
iter: 19270 | loss: 1.108924
iter: 19271 | loss: 1.108730
iter: 19272 | loss: 1.108537
iter: 19273 | loss: 1.108343
iter: 19274 | loss: 1.108150
iter: 19275 | loss: 1.107957
iter: 19276 | loss: 1.107763
iter: 19277 | loss: 1.107570
iter: 19278 | loss: 1.107376
iter: 19279 | loss: 1.107183
iter: 19280 | loss: 1.106990
iter: 19281 | loss: 1.106796
iter: 19282 | loss: 1.106603
iter: 19283 | loss: 1.106410
iter: 19284 | loss: 1.106216
iter: 19285 | loss: 1.106023
iter: 19286 | loss: 1.105829
iter: 19287 | loss: 1.105636
iter: 19288 | loss: 1.105443
iter: 19289 | loss: 1.105249
iter: 19290 | loss: 1.105056
iter: 19291 | loss: 1.104862
iter: 19292 | loss: 1.104669
iter: 19293 | loss: 1.104476
iter: 19294 | loss: 1.104282
iter: 19295 | loss: 1.104089
iter: 19296 | loss: 1.103895
iter: 19297 | loss: 1.103702
iter: 19298 | loss: 1.103509
iter: 19299 | loss: 1.103315
iter: 19300 | loss: 1.103122
iter: 19301 | loss: 1.102929
iter: 19302 | loss: 1.102735
iter: 19303 | loss: 1.102542
iter: 19304 | loss: 1.102348
iter: 19305 | loss: 1.102155
iter: 19306 | loss: 1.101962
iter: 19307 | loss: 1.101768
iter: 19308 | loss: 1.101575
iter: 19309 | loss: 1.101381
iter: 19310 | loss: 1.101188
iter: 19311 | loss: 1.100995
iter: 19312 | loss: 1.100801
iter: 19313 | loss: 1.100608
iter: 19314 | loss: 1.100415
iter: 19315 | loss: 1.100221
iter: 19316 | loss: 1.100028
iter: 19317 | loss: 1.099834
iter: 19318 | loss: 1.099641
iter: 19319 | loss: 1.099448
iter: 19320 | loss: 1.099254
iter: 19321 | loss: 1.099061
iter: 19322 | loss: 1.098867
iter: 19323 | loss: 1.098674
iter: 19324 | loss: 1.098481
iter: 19325 | loss: 1.098287
iter: 19326 | loss: 1.098094
iter: 19327 | loss: 1.097900
iter: 19328 | loss: 1.097707
iter: 19329 | loss: 1.097514
iter: 19330 | loss: 1.097320
iter: 19331 | loss: 1.097127
iter: 19332 | loss: 1.096934
iter: 19333 | loss: 1.096740
iter: 19334 | loss: 1.096547
iter: 19335 | loss: 1.096353
iter: 19336 | loss: 1.096160
iter: 19337 | loss: 1.095967
iter: 19338 | loss: 1.095773
iter: 19339 | loss: 1.095580
iter: 19340 | loss: 1.095386
iter: 19341 | loss: 1.095193
iter: 19342 | loss: 1.095000
iter: 19343 | loss: 1.094806
iter: 19344 | loss: 1.094613
iter: 19345 | loss: 1.094420
iter: 19346 | loss: 1.094226
iter: 19347 | loss: 1.094033
iter: 19348 | loss: 1.093839
iter: 19349 | loss: 1.093646
iter: 19350 | loss: 1.093453
iter: 19351 | loss: 1.093259
iter: 19352 | loss: 1.093066
iter: 19353 | loss: 1.092872
iter: 19354 | loss: 1.092679
iter: 19355 | loss: 1.092486
iter: 19356 | loss: 1.092292
iter: 19357 | loss: 1.092099
iter: 19358 | loss: 1.091906
iter: 19359 | loss: 1.091712
iter: 19360 | loss: 1.091519
iter: 19361 | loss: 1.091325
iter: 19362 | loss: 1.091132
iter: 19363 | loss: 1.090939
iter: 19364 | loss: 1.090745
iter: 19365 | loss: 1.090552
iter: 19366 | loss: 1.090358
iter: 19367 | loss: 1.090165
iter: 19368 | loss: 1.089972
iter: 19369 | loss: 1.089778
iter: 19370 | loss: 1.089585
iter: 19371 | loss: 1.089391
iter: 19372 | loss: 1.089198
iter: 19373 | loss: 1.089005
iter: 19374 | loss: 1.088811
iter: 19375 | loss: 1.088618
iter: 19376 | loss: 1.088425
iter: 19377 | loss: 1.088231
iter: 19378 | loss: 1.088038
iter: 19379 | loss: 1.087844
iter: 19380 | loss: 1.087651
iter: 19381 | loss: 1.087458
iter: 19382 | loss: 1.087264
iter: 19383 | loss: 1.087071
iter: 19384 | loss: 1.086877
iter: 19385 | loss: 1.086684
iter: 19386 | loss: 1.086491
iter: 19387 | loss: 1.086297
iter: 19388 | loss: 1.086104
iter: 19389 | loss: 1.085911
iter: 19390 | loss: 1.085717
iter: 19391 | loss: 1.085524
iter: 19392 | loss: 1.085330
iter: 19393 | loss: 1.085137
iter: 19394 | loss: 1.084944
iter: 19395 | loss: 1.084750
iter: 19396 | loss: 1.084557
iter: 19397 | loss: 1.084363
iter: 19398 | loss: 1.084170
iter: 19399 | loss: 1.083977
iter: 19400 | loss: 1.083783
iter: 19401 | loss: 1.083590
iter: 19402 | loss: 1.083396
iter: 19403 | loss: 1.083203
iter: 19404 | loss: 1.083010
iter: 19405 | loss: 1.082816
iter: 19406 | loss: 1.082623
iter: 19407 | loss: 1.082430
iter: 19408 | loss: 1.082236
iter: 19409 | loss: 1.082043
iter: 19410 | loss: 1.081849
iter: 19411 | loss: 1.081656
iter: 19412 | loss: 1.081463
iter: 19413 | loss: 1.081269
iter: 19414 | loss: 1.081076
iter: 19415 | loss: 1.080882
iter: 19416 | loss: 1.080689
iter: 19417 | loss: 1.080496
iter: 19418 | loss: 1.080302
iter: 19419 | loss: 1.080109
iter: 19420 | loss: 1.079916
iter: 19421 | loss: 1.079722
iter: 19422 | loss: 1.079529
iter: 19423 | loss: 1.079335
iter: 19424 | loss: 1.079142
iter: 19425 | loss: 1.078949
iter: 19426 | loss: 1.078755
iter: 19427 | loss: 1.078562
iter: 19428 | loss: 1.078368
iter: 19429 | loss: 1.078175
iter: 19430 | loss: 1.077982
iter: 19431 | loss: 1.077788
iter: 19432 | loss: 1.077595
iter: 19433 | loss: 1.077401
iter: 19434 | loss: 1.077208
iter: 19435 | loss: 1.077015
iter: 19436 | loss: 1.076821
iter: 19437 | loss: 1.076628
iter: 19438 | loss: 1.076435
iter: 19439 | loss: 1.076241
iter: 19440 | loss: 1.076048
iter: 19441 | loss: 1.075854
iter: 19442 | loss: 1.075661
iter: 19443 | loss: 1.075468
iter: 19444 | loss: 1.075274
iter: 19445 | loss: 1.075081
iter: 19446 | loss: 1.074887
iter: 19447 | loss: 1.074694
iter: 19448 | loss: 1.074501
iter: 19449 | loss: 1.074307
iter: 19450 | loss: 1.074114
iter: 19451 | loss: 1.073921
iter: 19452 | loss: 1.073727
iter: 19453 | loss: 1.073534
iter: 19454 | loss: 1.073340
iter: 19455 | loss: 1.073147
iter: 19456 | loss: 1.072954
iter: 19457 | loss: 1.072760
iter: 19458 | loss: 1.072567
iter: 19459 | loss: 1.072373
iter: 19460 | loss: 1.072180
iter: 19461 | loss: 1.071987
iter: 19462 | loss: 1.071793
iter: 19463 | loss: 1.071600
iter: 19464 | loss: 1.071406
iter: 19465 | loss: 1.071213
iter: 19466 | loss: 1.071020
iter: 19467 | loss: 1.070826
iter: 19468 | loss: 1.070633
iter: 19469 | loss: 1.070440
iter: 19470 | loss: 1.070246
iter: 19471 | loss: 1.070053
iter: 19472 | loss: 1.069859
iter: 19473 | loss: 1.069666
iter: 19474 | loss: 1.069473
iter: 19475 | loss: 1.069279
iter: 19476 | loss: 1.069086
iter: 19477 | loss: 1.068892
iter: 19478 | loss: 1.068699
iter: 19479 | loss: 1.068506
iter: 19480 | loss: 1.068312
iter: 19481 | loss: 1.068119
iter: 19482 | loss: 1.067926
iter: 19483 | loss: 1.067732
iter: 19484 | loss: 1.067539
iter: 19485 | loss: 1.067345
iter: 19486 | loss: 1.067152
iter: 19487 | loss: 1.066959
iter: 19488 | loss: 1.066765
iter: 19489 | loss: 1.066572
iter: 19490 | loss: 1.066378
iter: 19491 | loss: 1.066185
iter: 19492 | loss: 1.065992
iter: 19493 | loss: 1.065798
iter: 19494 | loss: 1.065605
iter: 19495 | loss: 1.065411
iter: 19496 | loss: 1.065218
iter: 19497 | loss: 1.065025
iter: 19498 | loss: 1.064831
iter: 19499 | loss: 1.064638
iter: 19500 | loss: 1.064445
iter: 19501 | loss: 1.064251
iter: 19502 | loss: 1.064058
iter: 19503 | loss: 1.063864
iter: 19504 | loss: 1.063671
iter: 19505 | loss: 1.063478
iter: 19506 | loss: 1.063284
iter: 19507 | loss: 1.063091
iter: 19508 | loss: 1.062897
iter: 19509 | loss: 1.062704
iter: 19510 | loss: 1.062511
iter: 19511 | loss: 1.062317
iter: 19512 | loss: 1.062124
iter: 19513 | loss: 1.061931
iter: 19514 | loss: 1.061737
iter: 19515 | loss: 1.061544
iter: 19516 | loss: 1.061350
iter: 19517 | loss: 1.061157
iter: 19518 | loss: 1.060964
iter: 19519 | loss: 1.060770
iter: 19520 | loss: 1.060577
iter: 19521 | loss: 1.060383
iter: 19522 | loss: 1.060190
iter: 19523 | loss: 1.059997
iter: 19524 | loss: 1.059803
iter: 19525 | loss: 1.059610
iter: 19526 | loss: 1.059416
iter: 19527 | loss: 1.059223
iter: 19528 | loss: 1.059030
iter: 19529 | loss: 1.058836
iter: 19530 | loss: 1.058643
iter: 19531 | loss: 1.058450
iter: 19532 | loss: 1.058256
iter: 19533 | loss: 1.058063
iter: 19534 | loss: 1.057869
iter: 19535 | loss: 1.057676
iter: 19536 | loss: 1.057483
iter: 19537 | loss: 1.057289
iter: 19538 | loss: 1.057096
iter: 19539 | loss: 1.056902
iter: 19540 | loss: 1.056709
iter: 19541 | loss: 1.056516
iter: 19542 | loss: 1.056322
iter: 19543 | loss: 1.056129
iter: 19544 | loss: 1.055936
iter: 19545 | loss: 1.055742
iter: 19546 | loss: 1.055549
iter: 19547 | loss: 1.055355
iter: 19548 | loss: 1.055162
iter: 19549 | loss: 1.054969
iter: 19550 | loss: 1.054775
iter: 19551 | loss: 1.054582
iter: 19552 | loss: 1.054388
iter: 19553 | loss: 1.054195
iter: 19554 | loss: 1.054002
iter: 19555 | loss: 1.053808
iter: 19556 | loss: 1.053615
iter: 19557 | loss: 1.053421
iter: 19558 | loss: 1.053228
iter: 19559 | loss: 1.053035
iter: 19560 | loss: 1.052841
iter: 19561 | loss: 1.052648
iter: 19562 | loss: 1.052455
iter: 19563 | loss: 1.052261
iter: 19564 | loss: 1.052068
iter: 19565 | loss: 1.051874
iter: 19566 | loss: 1.051681
iter: 19567 | loss: 1.051488
iter: 19568 | loss: 1.051294
iter: 19569 | loss: 1.051101
iter: 19570 | loss: 1.050907
iter: 19571 | loss: 1.050714
iter: 19572 | loss: 1.050521
iter: 19573 | loss: 1.050327
iter: 19574 | loss: 1.050134
iter: 19575 | loss: 1.049941
iter: 19576 | loss: 1.049747
iter: 19577 | loss: 1.049554
iter: 19578 | loss: 1.049360
iter: 19579 | loss: 1.049167
iter: 19580 | loss: 1.048974
iter: 19581 | loss: 1.048780
iter: 19582 | loss: 1.048587
iter: 19583 | loss: 1.048393
iter: 19584 | loss: 1.048200
iter: 19585 | loss: 1.048007
iter: 19586 | loss: 1.047813
iter: 19587 | loss: 1.047620
iter: 19588 | loss: 1.047426
iter: 19589 | loss: 1.047233
iter: 19590 | loss: 1.047040
iter: 19591 | loss: 1.046846
iter: 19592 | loss: 1.046653
iter: 19593 | loss: 1.046460
iter: 19594 | loss: 1.046266
iter: 19595 | loss: 1.046073
iter: 19596 | loss: 1.045879
iter: 19597 | loss: 1.045686
iter: 19598 | loss: 1.045493
iter: 19599 | loss: 1.045299
iter: 19600 | loss: 1.045106
iter: 19601 | loss: 1.044912
iter: 19602 | loss: 1.044719
iter: 19603 | loss: 1.044526
iter: 19604 | loss: 1.044332
iter: 19605 | loss: 1.044139
iter: 19606 | loss: 1.043946
iter: 19607 | loss: 1.043752
iter: 19608 | loss: 1.043559
iter: 19609 | loss: 1.043365
iter: 19610 | loss: 1.043172
iter: 19611 | loss: 1.042979
iter: 19612 | loss: 1.042785
iter: 19613 | loss: 1.042592
iter: 19614 | loss: 1.042398
iter: 19615 | loss: 1.042205
iter: 19616 | loss: 1.042012
iter: 19617 | loss: 1.041818
iter: 19618 | loss: 1.041625
iter: 19619 | loss: 1.041431
iter: 19620 | loss: 1.041238
iter: 19621 | loss: 1.041045
iter: 19622 | loss: 1.040851
iter: 19623 | loss: 1.040658
iter: 19624 | loss: 1.040465
iter: 19625 | loss: 1.040271
iter: 19626 | loss: 1.040078
iter: 19627 | loss: 1.039884
iter: 19628 | loss: 1.039691
iter: 19629 | loss: 1.039498
iter: 19630 | loss: 1.039304
iter: 19631 | loss: 1.039111
iter: 19632 | loss: 1.038917
iter: 19633 | loss: 1.038724
iter: 19634 | loss: 1.038531
iter: 19635 | loss: 1.038337
iter: 19636 | loss: 1.038144
iter: 19637 | loss: 1.037951
iter: 19638 | loss: 1.037757
iter: 19639 | loss: 1.037564
iter: 19640 | loss: 1.037370
iter: 19641 | loss: 1.037177
iter: 19642 | loss: 1.036984
iter: 19643 | loss: 1.036790
iter: 19644 | loss: 1.036597
iter: 19645 | loss: 1.036403
iter: 19646 | loss: 1.036210
iter: 19647 | loss: 1.036017
iter: 19648 | loss: 1.035823
iter: 19649 | loss: 1.035630
iter: 19650 | loss: 1.035436
iter: 19651 | loss: 1.035243
iter: 19652 | loss: 1.035050
iter: 19653 | loss: 1.034856
iter: 19654 | loss: 1.034663
iter: 19655 | loss: 1.034470
iter: 19656 | loss: 1.034276
iter: 19657 | loss: 1.034083
iter: 19658 | loss: 1.033889
iter: 19659 | loss: 1.033696
iter: 19660 | loss: 1.033503
iter: 19661 | loss: 1.033309
iter: 19662 | loss: 1.033116
iter: 19663 | loss: 1.032922
iter: 19664 | loss: 1.032729
iter: 19665 | loss: 1.032536
iter: 19666 | loss: 1.032342
iter: 19667 | loss: 1.032149
iter: 19668 | loss: 1.031956
iter: 19669 | loss: 1.031762
iter: 19670 | loss: 1.031569
iter: 19671 | loss: 1.031375
iter: 19672 | loss: 1.031182
iter: 19673 | loss: 1.030989
iter: 19674 | loss: 1.030795
iter: 19675 | loss: 1.030602
iter: 19676 | loss: 1.030408
iter: 19677 | loss: 1.030215
iter: 19678 | loss: 1.030022
iter: 19679 | loss: 1.029828
iter: 19680 | loss: 1.029635
iter: 19681 | loss: 1.029442
iter: 19682 | loss: 1.029248
iter: 19683 | loss: 1.029055
iter: 19684 | loss: 1.028861
iter: 19685 | loss: 1.028668
iter: 19686 | loss: 1.028475
iter: 19687 | loss: 1.028281
iter: 19688 | loss: 1.028088
iter: 19689 | loss: 1.027894
iter: 19690 | loss: 1.027701
iter: 19691 | loss: 1.027508
iter: 19692 | loss: 1.027314
iter: 19693 | loss: 1.027121
iter: 19694 | loss: 1.026927
iter: 19695 | loss: 1.026734
iter: 19696 | loss: 1.026541
iter: 19697 | loss: 1.026347
iter: 19698 | loss: 1.026154
iter: 19699 | loss: 1.025961
iter: 19700 | loss: 1.025767
iter: 19701 | loss: 1.025574
iter: 19702 | loss: 1.025380
iter: 19703 | loss: 1.025187
iter: 19704 | loss: 1.024994
iter: 19705 | loss: 1.024800
iter: 19706 | loss: 1.024607
iter: 19707 | loss: 1.024413
iter: 19708 | loss: 1.024220
iter: 19709 | loss: 1.024027
iter: 19710 | loss: 1.023833
iter: 19711 | loss: 1.023640
iter: 19712 | loss: 1.023447
iter: 19713 | loss: 1.023253
iter: 19714 | loss: 1.023060
iter: 19715 | loss: 1.022866
iter: 19716 | loss: 1.022673
iter: 19717 | loss: 1.022480
iter: 19718 | loss: 1.022286
iter: 19719 | loss: 1.022093
iter: 19720 | loss: 1.021899
iter: 19721 | loss: 1.021706
iter: 19722 | loss: 1.021513
iter: 19723 | loss: 1.021319
iter: 19724 | loss: 1.021126
iter: 19725 | loss: 1.020932
iter: 19726 | loss: 1.020739
iter: 19727 | loss: 1.020546
iter: 19728 | loss: 1.020352
iter: 19729 | loss: 1.020159
iter: 19730 | loss: 1.019966
iter: 19731 | loss: 1.019772
iter: 19732 | loss: 1.019579
iter: 19733 | loss: 1.019385
iter: 19734 | loss: 1.019192
iter: 19735 | loss: 1.018999
iter: 19736 | loss: 1.018805
iter: 19737 | loss: 1.018612
iter: 19738 | loss: 1.018418
iter: 19739 | loss: 1.018225
iter: 19740 | loss: 1.018032
iter: 19741 | loss: 1.017838
iter: 19742 | loss: 1.017645
iter: 19743 | loss: 1.017452
iter: 19744 | loss: 1.017258
iter: 19745 | loss: 1.017065
iter: 19746 | loss: 1.016871
iter: 19747 | loss: 1.016678
iter: 19748 | loss: 1.016485
iter: 19749 | loss: 1.016291
iter: 19750 | loss: 1.016098
iter: 19751 | loss: 1.015904
iter: 19752 | loss: 1.015711
iter: 19753 | loss: 1.015518
iter: 19754 | loss: 1.015324
iter: 19755 | loss: 1.015131
iter: 19756 | loss: 1.014937
iter: 19757 | loss: 1.014744
iter: 19758 | loss: 1.014551
iter: 19759 | loss: 1.014357
iter: 19760 | loss: 1.014164
iter: 19761 | loss: 1.013971
iter: 19762 | loss: 1.013777
iter: 19763 | loss: 1.013584
iter: 19764 | loss: 1.013390
iter: 19765 | loss: 1.013197
iter: 19766 | loss: 1.013004
iter: 19767 | loss: 1.012810
iter: 19768 | loss: 1.012617
iter: 19769 | loss: 1.012423
iter: 19770 | loss: 1.012230
iter: 19771 | loss: 1.012037
iter: 19772 | loss: 1.011843
iter: 19773 | loss: 1.011650
iter: 19774 | loss: 1.011457
iter: 19775 | loss: 1.011263
iter: 19776 | loss: 1.011070
iter: 19777 | loss: 1.010876
iter: 19778 | loss: 1.010683
iter: 19779 | loss: 1.010490
iter: 19780 | loss: 1.010296
iter: 19781 | loss: 1.010103
iter: 19782 | loss: 1.009909
iter: 19783 | loss: 1.009716
iter: 19784 | loss: 1.009523
iter: 19785 | loss: 1.009329
iter: 19786 | loss: 1.009136
iter: 19787 | loss: 1.008942
iter: 19788 | loss: 1.008749
iter: 19789 | loss: 1.008556
iter: 19790 | loss: 1.008362
iter: 19791 | loss: 1.008169
iter: 19792 | loss: 1.007976
iter: 19793 | loss: 1.007782
iter: 19794 | loss: 1.007589
iter: 19795 | loss: 1.007395
iter: 19796 | loss: 1.007202
iter: 19797 | loss: 1.007009
iter: 19798 | loss: 1.006815
iter: 19799 | loss: 1.006622
iter: 19800 | loss: 1.006428
iter: 19801 | loss: 1.006235
iter: 19802 | loss: 1.006042
iter: 19803 | loss: 1.005848
iter: 19804 | loss: 1.005655
iter: 19805 | loss: 1.005462
iter: 19806 | loss: 1.005268
iter: 19807 | loss: 1.005075
iter: 19808 | loss: 1.004881
iter: 19809 | loss: 1.004688
iter: 19810 | loss: 1.004495
iter: 19811 | loss: 1.004301
iter: 19812 | loss: 1.004108
iter: 19813 | loss: 1.003914
iter: 19814 | loss: 1.003721
iter: 19815 | loss: 1.003528
iter: 19816 | loss: 1.003334
iter: 19817 | loss: 1.003141
iter: 19818 | loss: 1.002947
iter: 19819 | loss: 1.002754
iter: 19820 | loss: 1.002561
iter: 19821 | loss: 1.002367
iter: 19822 | loss: 1.002174
iter: 19823 | loss: 1.001981
iter: 19824 | loss: 1.001787
iter: 19825 | loss: 1.001594
iter: 19826 | loss: 1.001400
iter: 19827 | loss: 1.001207
iter: 19828 | loss: 1.001014
iter: 19829 | loss: 1.000820
iter: 19830 | loss: 1.000627
iter: 19831 | loss: 1.000433
iter: 19832 | loss: 1.000240
iter: 19833 | loss: 1.000047
iter: 19834 | loss: 0.999853
iter: 19835 | loss: 0.999660
iter: 19836 | loss: 0.999467
iter: 19837 | loss: 0.999273
iter: 19838 | loss: 0.999080
iter: 19839 | loss: 0.998886
iter: 19840 | loss: 0.998693
iter: 19841 | loss: 0.998500
iter: 19842 | loss: 0.998306
iter: 19843 | loss: 0.998113
iter: 19844 | loss: 0.997919
iter: 19845 | loss: 0.997726
iter: 19846 | loss: 0.997533
iter: 19847 | loss: 0.997339
iter: 19848 | loss: 0.997146
iter: 19849 | loss: 0.996952
iter: 19850 | loss: 0.996759
iter: 19851 | loss: 0.996566
iter: 19852 | loss: 0.996372
iter: 19853 | loss: 0.996179
iter: 19854 | loss: 0.995986
iter: 19855 | loss: 0.995792
iter: 19856 | loss: 0.995599
iter: 19857 | loss: 0.995405
iter: 19858 | loss: 0.995212
iter: 19859 | loss: 0.995019
iter: 19860 | loss: 0.994825
iter: 19861 | loss: 0.994632
iter: 19862 | loss: 0.994438
iter: 19863 | loss: 0.994245
iter: 19864 | loss: 0.994052
iter: 19865 | loss: 0.993858
iter: 19866 | loss: 0.993665
iter: 19867 | loss: 0.993472
iter: 19868 | loss: 0.993278
iter: 19869 | loss: 0.993085
iter: 19870 | loss: 0.992891
iter: 19871 | loss: 0.992698
iter: 19872 | loss: 0.992505
iter: 19873 | loss: 0.992311
iter: 19874 | loss: 0.992118
iter: 19875 | loss: 0.991924
iter: 19876 | loss: 0.991731
iter: 19877 | loss: 0.991538
iter: 19878 | loss: 0.991344
iter: 19879 | loss: 0.991151
iter: 19880 | loss: 0.990957
iter: 19881 | loss: 0.990764
iter: 19882 | loss: 0.990571
iter: 19883 | loss: 0.990377
iter: 19884 | loss: 0.990184
iter: 19885 | loss: 0.989991
iter: 19886 | loss: 0.989797
iter: 19887 | loss: 0.989604
iter: 19888 | loss: 0.989410
iter: 19889 | loss: 0.989217
iter: 19890 | loss: 0.989024
iter: 19891 | loss: 0.988830
iter: 19892 | loss: 0.988637
iter: 19893 | loss: 0.988443
iter: 19894 | loss: 0.988250
iter: 19895 | loss: 0.988057
iter: 19896 | loss: 0.987863
iter: 19897 | loss: 0.987670
iter: 19898 | loss: 0.987477
iter: 19899 | loss: 0.987283
iter: 19900 | loss: 0.987090
iter: 19901 | loss: 0.986896
iter: 19902 | loss: 0.986703
iter: 19903 | loss: 0.986510
iter: 19904 | loss: 0.986316
iter: 19905 | loss: 0.986123
iter: 19906 | loss: 0.985929
iter: 19907 | loss: 0.985736
iter: 19908 | loss: 0.985543
iter: 19909 | loss: 0.985349
iter: 19910 | loss: 0.985156
iter: 19911 | loss: 0.984962
iter: 19912 | loss: 0.984769
iter: 19913 | loss: 0.984576
iter: 19914 | loss: 0.984382
iter: 19915 | loss: 0.984189
iter: 19916 | loss: 0.983996
iter: 19917 | loss: 0.983802
iter: 19918 | loss: 0.983609
iter: 19919 | loss: 0.983415
iter: 19920 | loss: 0.983222
iter: 19921 | loss: 0.983029
iter: 19922 | loss: 0.982835
iter: 19923 | loss: 0.982642
iter: 19924 | loss: 0.982448
iter: 19925 | loss: 0.982255
iter: 19926 | loss: 0.982062
iter: 19927 | loss: 0.981868
iter: 19928 | loss: 0.981675
iter: 19929 | loss: 0.981482
iter: 19930 | loss: 0.981288
iter: 19931 | loss: 0.981095
iter: 19932 | loss: 0.980901
iter: 19933 | loss: 0.980708
iter: 19934 | loss: 0.980515
iter: 19935 | loss: 0.980321
iter: 19936 | loss: 0.980128
iter: 19937 | loss: 0.979934
iter: 19938 | loss: 0.979741
iter: 19939 | loss: 0.979548
iter: 19940 | loss: 0.979354
iter: 19941 | loss: 0.979161
iter: 19942 | loss: 0.978967
iter: 19943 | loss: 0.978774
iter: 19944 | loss: 0.978581
iter: 19945 | loss: 0.978387
iter: 19946 | loss: 0.978194
iter: 19947 | loss: 0.978001
iter: 19948 | loss: 0.977807
iter: 19949 | loss: 0.977614
iter: 19950 | loss: 0.977420
iter: 19951 | loss: 0.977227
iter: 19952 | loss: 0.977034
iter: 19953 | loss: 0.976840
iter: 19954 | loss: 0.976647
iter: 19955 | loss: 0.976453
iter: 19956 | loss: 0.976260
iter: 19957 | loss: 0.976067
iter: 19958 | loss: 0.975873
iter: 19959 | loss: 0.975680
iter: 19960 | loss: 0.975487
iter: 19961 | loss: 0.975293
iter: 19962 | loss: 0.975100
iter: 19963 | loss: 0.974906
iter: 19964 | loss: 0.974713
iter: 19965 | loss: 0.974520
iter: 19966 | loss: 0.974326
iter: 19967 | loss: 0.974133
iter: 19968 | loss: 0.973939
iter: 19969 | loss: 0.973746
iter: 19970 | loss: 0.973553
iter: 19971 | loss: 0.973359
iter: 19972 | loss: 0.973166
iter: 19973 | loss: 0.972972
iter: 19974 | loss: 0.972779
iter: 19975 | loss: 0.972586
iter: 19976 | loss: 0.972392
iter: 19977 | loss: 0.972199
iter: 19978 | loss: 0.972006
iter: 19979 | loss: 0.971812
iter: 19980 | loss: 0.971619
iter: 19981 | loss: 0.971425
iter: 19982 | loss: 0.971232
iter: 19983 | loss: 0.971039
iter: 19984 | loss: 0.970845
iter: 19985 | loss: 0.970652
iter: 19986 | loss: 0.970458
iter: 19987 | loss: 0.970265
iter: 19988 | loss: 0.970072
iter: 19989 | loss: 0.969878
iter: 19990 | loss: 0.969685
iter: 19991 | loss: 0.969492
iter: 19992 | loss: 0.969298
iter: 19993 | loss: 0.969105
iter: 19994 | loss: 0.968911
iter: 19995 | loss: 0.968718
iter: 19996 | loss: 0.968525
iter: 19997 | loss: 0.968331
iter: 19998 | loss: 0.968138
iter: 19999 | loss: 0.967944
iter: 20000 | loss: 0.967751
iter: 20001 | loss: 0.967558
iter: 20002 | loss: 0.967364
iter: 20003 | loss: 0.967171
iter: 20004 | loss: 0.966978
iter: 20005 | loss: 0.966784
iter: 20006 | loss: 0.966591
iter: 20007 | loss: 0.966397
iter: 20008 | loss: 0.966204
iter: 20009 | loss: 0.966011
iter: 20010 | loss: 0.965817
iter: 20011 | loss: 0.965624
iter: 20012 | loss: 0.965430
iter: 20013 | loss: 0.965237
iter: 20014 | loss: 0.965044
iter: 20015 | loss: 0.964850
iter: 20016 | loss: 0.964657
iter: 20017 | loss: 0.964463
iter: 20018 | loss: 0.964270
iter: 20019 | loss: 0.964077
iter: 20020 | loss: 0.963883
iter: 20021 | loss: 0.963690
iter: 20022 | loss: 0.963497
iter: 20023 | loss: 0.963303
iter: 20024 | loss: 0.963110
iter: 20025 | loss: 0.962916
iter: 20026 | loss: 0.962723
iter: 20027 | loss: 0.962530
iter: 20028 | loss: 0.962336
iter: 20029 | loss: 0.962143
iter: 20030 | loss: 0.961949
iter: 20031 | loss: 0.961756
iter: 20032 | loss: 0.961563
iter: 20033 | loss: 0.961369
iter: 20034 | loss: 0.961176
iter: 20035 | loss: 0.960983
iter: 20036 | loss: 0.960789
iter: 20037 | loss: 0.960596
iter: 20038 | loss: 0.960402
iter: 20039 | loss: 0.960209
iter: 20040 | loss: 0.960016
iter: 20041 | loss: 0.959822
iter: 20042 | loss: 0.959629
iter: 20043 | loss: 0.959435
iter: 20044 | loss: 0.959242
iter: 20045 | loss: 0.959049
iter: 20046 | loss: 0.958855
iter: 20047 | loss: 0.958662
iter: 20048 | loss: 0.958468
iter: 20049 | loss: 0.958275
iter: 20050 | loss: 0.958082
iter: 20051 | loss: 0.957888
iter: 20052 | loss: 0.957695
iter: 20053 | loss: 0.957502
iter: 20054 | loss: 0.957308
iter: 20055 | loss: 0.957115
iter: 20056 | loss: 0.956921
iter: 20057 | loss: 0.956728
iter: 20058 | loss: 0.956535
iter: 20059 | loss: 0.956341
iter: 20060 | loss: 0.956148
iter: 20061 | loss: 0.955954
iter: 20062 | loss: 0.955761
iter: 20063 | loss: 0.955568
iter: 20064 | loss: 0.955374
iter: 20065 | loss: 0.955181
iter: 20066 | loss: 0.954988
iter: 20067 | loss: 0.954794
iter: 20068 | loss: 0.954601
iter: 20069 | loss: 0.954407
iter: 20070 | loss: 0.954214
iter: 20071 | loss: 0.954021
iter: 20072 | loss: 0.953827
iter: 20073 | loss: 0.953634
iter: 20074 | loss: 0.953440
iter: 20075 | loss: 0.953247
iter: 20076 | loss: 0.953054
iter: 20077 | loss: 0.952860
iter: 20078 | loss: 0.952667
iter: 20079 | loss: 0.952473
iter: 20080 | loss: 0.952280
iter: 20081 | loss: 0.952087
iter: 20082 | loss: 0.951893
iter: 20083 | loss: 0.951700
iter: 20084 | loss: 0.951507
iter: 20085 | loss: 0.951313
iter: 20086 | loss: 0.951120
iter: 20087 | loss: 0.950926
iter: 20088 | loss: 0.950733
iter: 20089 | loss: 0.950540
iter: 20090 | loss: 0.950346
iter: 20091 | loss: 0.950153
iter: 20092 | loss: 0.949959
iter: 20093 | loss: 0.949766
iter: 20094 | loss: 0.949573
iter: 20095 | loss: 0.949379
iter: 20096 | loss: 0.949186
iter: 20097 | loss: 0.948993
iter: 20098 | loss: 0.948799
iter: 20099 | loss: 0.948606
iter: 20100 | loss: 0.948412
iter: 20101 | loss: 0.948219
iter: 20102 | loss: 0.948026
iter: 20103 | loss: 0.947832
iter: 20104 | loss: 0.947639
iter: 20105 | loss: 0.947445
iter: 20106 | loss: 0.947252
iter: 20107 | loss: 0.947059
iter: 20108 | loss: 0.946865
iter: 20109 | loss: 0.946672
iter: 20110 | loss: 0.946478
iter: 20111 | loss: 0.946285
iter: 20112 | loss: 0.946092
iter: 20113 | loss: 0.945898
iter: 20114 | loss: 0.945705
iter: 20115 | loss: 0.945512
iter: 20116 | loss: 0.945318
iter: 20117 | loss: 0.945125
iter: 20118 | loss: 0.944931
iter: 20119 | loss: 0.944738
iter: 20120 | loss: 0.944545
iter: 20121 | loss: 0.944351
iter: 20122 | loss: 0.944158
iter: 20123 | loss: 0.943964
iter: 20124 | loss: 0.943771
iter: 20125 | loss: 0.943578
iter: 20126 | loss: 0.943384
iter: 20127 | loss: 0.943191
iter: 20128 | loss: 0.942998
iter: 20129 | loss: 0.942804
iter: 20130 | loss: 0.942611
iter: 20131 | loss: 0.942417
iter: 20132 | loss: 0.942224
iter: 20133 | loss: 0.942031
iter: 20134 | loss: 0.941837
iter: 20135 | loss: 0.941644
iter: 20136 | loss: 0.941450
iter: 20137 | loss: 0.941257
iter: 20138 | loss: 0.941064
iter: 20139 | loss: 0.940870
iter: 20140 | loss: 0.940677
iter: 20141 | loss: 0.940483
iter: 20142 | loss: 0.940290
iter: 20143 | loss: 0.940097
iter: 20144 | loss: 0.939903
iter: 20145 | loss: 0.939710
iter: 20146 | loss: 0.939517
iter: 20147 | loss: 0.939323
iter: 20148 | loss: 0.939130
iter: 20149 | loss: 0.938936
iter: 20150 | loss: 0.938743
iter: 20151 | loss: 0.938550
iter: 20152 | loss: 0.938356
iter: 20153 | loss: 0.938163
iter: 20154 | loss: 0.937969
iter: 20155 | loss: 0.937776
iter: 20156 | loss: 0.937583
iter: 20157 | loss: 0.937389
iter: 20158 | loss: 0.937196
iter: 20159 | loss: 0.937003
iter: 20160 | loss: 0.936809
iter: 20161 | loss: 0.936616
iter: 20162 | loss: 0.936422
iter: 20163 | loss: 0.936229
iter: 20164 | loss: 0.936036
iter: 20165 | loss: 0.935842
iter: 20166 | loss: 0.935649
iter: 20167 | loss: 0.935455
iter: 20168 | loss: 0.935262
iter: 20169 | loss: 0.935069
iter: 20170 | loss: 0.934875
iter: 20171 | loss: 0.934682
iter: 20172 | loss: 0.934488
iter: 20173 | loss: 0.934295
iter: 20174 | loss: 0.934102
iter: 20175 | loss: 0.933908
iter: 20176 | loss: 0.933715
iter: 20177 | loss: 0.933522
iter: 20178 | loss: 0.933328
iter: 20179 | loss: 0.933135
iter: 20180 | loss: 0.932941
iter: 20181 | loss: 0.932748
iter: 20182 | loss: 0.932555
iter: 20183 | loss: 0.932361
iter: 20184 | loss: 0.932168
iter: 20185 | loss: 0.931974
iter: 20186 | loss: 0.931781
iter: 20187 | loss: 0.931588
iter: 20188 | loss: 0.931394
iter: 20189 | loss: 0.931201
iter: 20190 | loss: 0.931008
iter: 20191 | loss: 0.930814
iter: 20192 | loss: 0.930621
iter: 20193 | loss: 0.930427
iter: 20194 | loss: 0.930234
iter: 20195 | loss: 0.930041
iter: 20196 | loss: 0.929847
iter: 20197 | loss: 0.929654
iter: 20198 | loss: 0.929460
iter: 20199 | loss: 0.929267
iter: 20200 | loss: 0.929074
iter: 20201 | loss: 0.928880
iter: 20202 | loss: 0.928687
iter: 20203 | loss: 0.928493
iter: 20204 | loss: 0.928300
iter: 20205 | loss: 0.928107
iter: 20206 | loss: 0.927913
iter: 20207 | loss: 0.927720
iter: 20208 | loss: 0.927527
iter: 20209 | loss: 0.927333
iter: 20210 | loss: 0.927140
iter: 20211 | loss: 0.926946
iter: 20212 | loss: 0.926753
iter: 20213 | loss: 0.926560
iter: 20214 | loss: 0.926366
iter: 20215 | loss: 0.926173
iter: 20216 | loss: 0.925979
iter: 20217 | loss: 0.925786
iter: 20218 | loss: 0.925593
iter: 20219 | loss: 0.925399
iter: 20220 | loss: 0.925206
iter: 20221 | loss: 0.925013
iter: 20222 | loss: 0.924819
iter: 20223 | loss: 0.924626
iter: 20224 | loss: 0.924432
iter: 20225 | loss: 0.924239
iter: 20226 | loss: 0.924046
iter: 20227 | loss: 0.923852
iter: 20228 | loss: 0.923659
iter: 20229 | loss: 0.923465
iter: 20230 | loss: 0.923272
iter: 20231 | loss: 0.923079
iter: 20232 | loss: 0.922885
iter: 20233 | loss: 0.922692
iter: 20234 | loss: 0.922498
iter: 20235 | loss: 0.922305
iter: 20236 | loss: 0.922112
iter: 20237 | loss: 0.921918
iter: 20238 | loss: 0.921725
iter: 20239 | loss: 0.921532
iter: 20240 | loss: 0.921338
iter: 20241 | loss: 0.921145
iter: 20242 | loss: 0.920951
iter: 20243 | loss: 0.920758
iter: 20244 | loss: 0.920565
iter: 20245 | loss: 0.920371
iter: 20246 | loss: 0.920178
iter: 20247 | loss: 0.919984
iter: 20248 | loss: 0.919791
iter: 20249 | loss: 0.919598
iter: 20250 | loss: 0.919404
iter: 20251 | loss: 0.919211
iter: 20252 | loss: 0.919018
iter: 20253 | loss: 0.918824
iter: 20254 | loss: 0.918631
iter: 20255 | loss: 0.918437
iter: 20256 | loss: 0.918244
iter: 20257 | loss: 0.918051
iter: 20258 | loss: 0.917857
iter: 20259 | loss: 0.917664
iter: 20260 | loss: 0.917470
iter: 20261 | loss: 0.917277
iter: 20262 | loss: 0.917084
iter: 20263 | loss: 0.916890
iter: 20264 | loss: 0.916697
iter: 20265 | loss: 0.916503
iter: 20266 | loss: 0.916310
iter: 20267 | loss: 0.916117
iter: 20268 | loss: 0.915923
iter: 20269 | loss: 0.915730
iter: 20270 | loss: 0.915537
iter: 20271 | loss: 0.915343
iter: 20272 | loss: 0.915150
iter: 20273 | loss: 0.914956
iter: 20274 | loss: 0.914763
iter: 20275 | loss: 0.914570
iter: 20276 | loss: 0.914376
iter: 20277 | loss: 0.914183
iter: 20278 | loss: 0.913989
iter: 20279 | loss: 0.913796
iter: 20280 | loss: 0.913603
iter: 20281 | loss: 0.913409
iter: 20282 | loss: 0.913216
iter: 20283 | loss: 0.913023
iter: 20284 | loss: 0.912829
iter: 20285 | loss: 0.912636
iter: 20286 | loss: 0.912442
iter: 20287 | loss: 0.912249
iter: 20288 | loss: 0.912056
iter: 20289 | loss: 0.911862
iter: 20290 | loss: 0.911669
iter: 20291 | loss: 0.911475
iter: 20292 | loss: 0.911282
iter: 20293 | loss: 0.911089
iter: 20294 | loss: 0.910895
iter: 20295 | loss: 0.910702
iter: 20296 | loss: 0.910508
iter: 20297 | loss: 0.910315
iter: 20298 | loss: 0.910122
iter: 20299 | loss: 0.909928
iter: 20300 | loss: 0.909735
iter: 20301 | loss: 0.909542
iter: 20302 | loss: 0.909348
iter: 20303 | loss: 0.909155
iter: 20304 | loss: 0.908961
iter: 20305 | loss: 0.908768
iter: 20306 | loss: 0.908575
iter: 20307 | loss: 0.908381
iter: 20308 | loss: 0.908188
iter: 20309 | loss: 0.907994
iter: 20310 | loss: 0.907801
iter: 20311 | loss: 0.907608
iter: 20312 | loss: 0.907414
iter: 20313 | loss: 0.907221
iter: 20314 | loss: 0.907028
iter: 20315 | loss: 0.906834
iter: 20316 | loss: 0.906641
iter: 20317 | loss: 0.906447
iter: 20318 | loss: 0.906254
iter: 20319 | loss: 0.906061
iter: 20320 | loss: 0.905867
iter: 20321 | loss: 0.905674
iter: 20322 | loss: 0.905480
iter: 20323 | loss: 0.905287
iter: 20324 | loss: 0.905094
iter: 20325 | loss: 0.904900
iter: 20326 | loss: 0.904707
iter: 20327 | loss: 0.904514
iter: 20328 | loss: 0.904320
iter: 20329 | loss: 0.904127
iter: 20330 | loss: 0.903933
iter: 20331 | loss: 0.903740
iter: 20332 | loss: 0.903547
iter: 20333 | loss: 0.903353
iter: 20334 | loss: 0.903160
iter: 20335 | loss: 0.902966
iter: 20336 | loss: 0.902773
iter: 20337 | loss: 0.902580
iter: 20338 | loss: 0.902386
iter: 20339 | loss: 0.902193
iter: 20340 | loss: 0.901999
iter: 20341 | loss: 0.901806
iter: 20342 | loss: 0.901613
iter: 20343 | loss: 0.901419
iter: 20344 | loss: 0.901226
iter: 20345 | loss: 0.901033
iter: 20346 | loss: 0.900839
iter: 20347 | loss: 0.900646
iter: 20348 | loss: 0.900452
iter: 20349 | loss: 0.900259
iter: 20350 | loss: 0.900066
iter: 20351 | loss: 0.899872
iter: 20352 | loss: 0.899679
iter: 20353 | loss: 0.899485
iter: 20354 | loss: 0.899292
iter: 20355 | loss: 0.899099
iter: 20356 | loss: 0.898905
iter: 20357 | loss: 0.898712
iter: 20358 | loss: 0.898519
iter: 20359 | loss: 0.898325
iter: 20360 | loss: 0.898132
iter: 20361 | loss: 0.897938
iter: 20362 | loss: 0.897745
iter: 20363 | loss: 0.897552
iter: 20364 | loss: 0.897358
iter: 20365 | loss: 0.897165
iter: 20366 | loss: 0.896971
iter: 20367 | loss: 0.896778
iter: 20368 | loss: 0.896585
iter: 20369 | loss: 0.896391
iter: 20370 | loss: 0.896198
iter: 20371 | loss: 0.896004
iter: 20372 | loss: 0.895811
iter: 20373 | loss: 0.895618
iter: 20374 | loss: 0.895424
iter: 20375 | loss: 0.895231
iter: 20376 | loss: 0.895038
iter: 20377 | loss: 0.894844
iter: 20378 | loss: 0.894651
iter: 20379 | loss: 0.894457
iter: 20380 | loss: 0.894264
iter: 20381 | loss: 0.894071
iter: 20382 | loss: 0.893877
iter: 20383 | loss: 0.893684
iter: 20384 | loss: 0.893490
iter: 20385 | loss: 0.893297
iter: 20386 | loss: 0.893104
iter: 20387 | loss: 0.892910
iter: 20388 | loss: 0.892717
iter: 20389 | loss: 0.892524
iter: 20390 | loss: 0.892330
iter: 20391 | loss: 0.892137
iter: 20392 | loss: 0.891943
iter: 20393 | loss: 0.891750
iter: 20394 | loss: 0.891557
iter: 20395 | loss: 0.891363
iter: 20396 | loss: 0.891170
iter: 20397 | loss: 0.890976
iter: 20398 | loss: 0.890783
iter: 20399 | loss: 0.890590
iter: 20400 | loss: 0.890396
iter: 20401 | loss: 0.890203
iter: 20402 | loss: 0.890009
iter: 20403 | loss: 0.889816
iter: 20404 | loss: 0.889623
iter: 20405 | loss: 0.889429
iter: 20406 | loss: 0.889236
iter: 20407 | loss: 0.889043
iter: 20408 | loss: 0.888849
iter: 20409 | loss: 0.888656
iter: 20410 | loss: 0.888462
iter: 20411 | loss: 0.888269
iter: 20412 | loss: 0.888076
iter: 20413 | loss: 0.887882
iter: 20414 | loss: 0.887689
iter: 20415 | loss: 0.887495
iter: 20416 | loss: 0.887302
iter: 20417 | loss: 0.887109
iter: 20418 | loss: 0.886915
iter: 20419 | loss: 0.886722
iter: 20420 | loss: 0.886529
iter: 20421 | loss: 0.886335
iter: 20422 | loss: 0.886142
iter: 20423 | loss: 0.885948
iter: 20424 | loss: 0.885755
iter: 20425 | loss: 0.885562
iter: 20426 | loss: 0.885368
iter: 20427 | loss: 0.885175
iter: 20428 | loss: 0.884981
iter: 20429 | loss: 0.884788
iter: 20430 | loss: 0.884595
iter: 20431 | loss: 0.884401
iter: 20432 | loss: 0.884208
iter: 20433 | loss: 0.884014
iter: 20434 | loss: 0.883821
iter: 20435 | loss: 0.883628
iter: 20436 | loss: 0.883434
iter: 20437 | loss: 0.883241
iter: 20438 | loss: 0.883048
iter: 20439 | loss: 0.882854
iter: 20440 | loss: 0.882661
iter: 20441 | loss: 0.882467
iter: 20442 | loss: 0.882274
iter: 20443 | loss: 0.882081
iter: 20444 | loss: 0.881887
iter: 20445 | loss: 0.881694
iter: 20446 | loss: 0.881500
iter: 20447 | loss: 0.881307
iter: 20448 | loss: 0.881114
iter: 20449 | loss: 0.880920
iter: 20450 | loss: 0.880727
iter: 20451 | loss: 0.880534
iter: 20452 | loss: 0.880340
iter: 20453 | loss: 0.880147
iter: 20454 | loss: 0.879953
iter: 20455 | loss: 0.879760
iter: 20456 | loss: 0.879567
iter: 20457 | loss: 0.879373
iter: 20458 | loss: 0.879180
iter: 20459 | loss: 0.878986
iter: 20460 | loss: 0.878793
iter: 20461 | loss: 0.878600
iter: 20462 | loss: 0.878406
iter: 20463 | loss: 0.878213
iter: 20464 | loss: 0.878019
iter: 20465 | loss: 0.877826
iter: 20466 | loss: 0.877633
iter: 20467 | loss: 0.877439
iter: 20468 | loss: 0.877246
iter: 20469 | loss: 0.877053
iter: 20470 | loss: 0.876859
iter: 20471 | loss: 0.876666
iter: 20472 | loss: 0.876472
iter: 20473 | loss: 0.876279
iter: 20474 | loss: 0.876086
iter: 20475 | loss: 0.875892
iter: 20476 | loss: 0.875699
iter: 20477 | loss: 0.875505
iter: 20478 | loss: 0.875312
iter: 20479 | loss: 0.875119
iter: 20480 | loss: 0.874925
iter: 20481 | loss: 0.874732
iter: 20482 | loss: 0.874539
iter: 20483 | loss: 0.874345
iter: 20484 | loss: 0.874152
iter: 20485 | loss: 0.873958
iter: 20486 | loss: 0.873765
iter: 20487 | loss: 0.873572
iter: 20488 | loss: 0.873378
iter: 20489 | loss: 0.873185
iter: 20490 | loss: 0.872991
iter: 20491 | loss: 0.872798
iter: 20492 | loss: 0.872605
iter: 20493 | loss: 0.872411
iter: 20494 | loss: 0.872218
iter: 20495 | loss: 0.872024
iter: 20496 | loss: 0.871831
iter: 20497 | loss: 0.871638
iter: 20498 | loss: 0.871444
iter: 20499 | loss: 0.871251
iter: 20500 | loss: 0.871058
iter: 20501 | loss: 0.870864
iter: 20502 | loss: 0.870671
iter: 20503 | loss: 0.870477
iter: 20504 | loss: 0.870284
iter: 20505 | loss: 0.870091
iter: 20506 | loss: 0.869897
iter: 20507 | loss: 0.869704
iter: 20508 | loss: 0.869510
iter: 20509 | loss: 0.869317
iter: 20510 | loss: 0.869124
iter: 20511 | loss: 0.868930
iter: 20512 | loss: 0.868737
iter: 20513 | loss: 0.868544
iter: 20514 | loss: 0.868350
iter: 20515 | loss: 0.868157
iter: 20516 | loss: 0.867963
iter: 20517 | loss: 0.867770
iter: 20518 | loss: 0.867577
iter: 20519 | loss: 0.867383
iter: 20520 | loss: 0.867190
iter: 20521 | loss: 0.866996
iter: 20522 | loss: 0.866803
iter: 20523 | loss: 0.866610
iter: 20524 | loss: 0.866416
iter: 20525 | loss: 0.866223
iter: 20526 | loss: 0.866029
iter: 20527 | loss: 0.865836
iter: 20528 | loss: 0.865643
iter: 20529 | loss: 0.865449
iter: 20530 | loss: 0.865256
iter: 20531 | loss: 0.865063
iter: 20532 | loss: 0.864869
iter: 20533 | loss: 0.864676
iter: 20534 | loss: 0.864482
iter: 20535 | loss: 0.864289
iter: 20536 | loss: 0.864096
iter: 20537 | loss: 0.863902
iter: 20538 | loss: 0.863709
iter: 20539 | loss: 0.863515
iter: 20540 | loss: 0.863322
iter: 20541 | loss: 0.863129
iter: 20542 | loss: 0.862935
iter: 20543 | loss: 0.862742
iter: 20544 | loss: 0.862549
iter: 20545 | loss: 0.862355
iter: 20546 | loss: 0.862162
iter: 20547 | loss: 0.861968
iter: 20548 | loss: 0.861775
iter: 20549 | loss: 0.861582
iter: 20550 | loss: 0.861388
iter: 20551 | loss: 0.861195
iter: 20552 | loss: 0.861001
iter: 20553 | loss: 0.860808
iter: 20554 | loss: 0.860615
iter: 20555 | loss: 0.860421
iter: 20556 | loss: 0.860228
iter: 20557 | loss: 0.860034
iter: 20558 | loss: 0.859841
iter: 20559 | loss: 0.859648
iter: 20560 | loss: 0.859454
iter: 20561 | loss: 0.859261
iter: 20562 | loss: 0.859068
iter: 20563 | loss: 0.858874
iter: 20564 | loss: 0.858681
iter: 20565 | loss: 0.858487
iter: 20566 | loss: 0.858294
iter: 20567 | loss: 0.858101
iter: 20568 | loss: 0.857907
iter: 20569 | loss: 0.857714
iter: 20570 | loss: 0.857520
iter: 20571 | loss: 0.857327
iter: 20572 | loss: 0.857134
iter: 20573 | loss: 0.856940
iter: 20574 | loss: 0.856747
iter: 20575 | loss: 0.856554
iter: 20576 | loss: 0.856360
iter: 20577 | loss: 0.856167
iter: 20578 | loss: 0.855973
iter: 20579 | loss: 0.855780
iter: 20580 | loss: 0.855587
iter: 20581 | loss: 0.855393
iter: 20582 | loss: 0.855200
iter: 20583 | loss: 0.855006
iter: 20584 | loss: 0.854813
iter: 20585 | loss: 0.854620
iter: 20586 | loss: 0.854426
iter: 20587 | loss: 0.854233
iter: 20588 | loss: 0.854039
iter: 20589 | loss: 0.853846
iter: 20590 | loss: 0.853653
iter: 20591 | loss: 0.853459
iter: 20592 | loss: 0.853266
iter: 20593 | loss: 0.853073
iter: 20594 | loss: 0.852879
iter: 20595 | loss: 0.852686
iter: 20596 | loss: 0.852492
iter: 20597 | loss: 0.852299
iter: 20598 | loss: 0.852106
iter: 20599 | loss: 0.851912
iter: 20600 | loss: 0.851719
iter: 20601 | loss: 0.851525
iter: 20602 | loss: 0.851332
iter: 20603 | loss: 0.851139
iter: 20604 | loss: 0.850945
iter: 20605 | loss: 0.850752
iter: 20606 | loss: 0.850559
iter: 20607 | loss: 0.850365
iter: 20608 | loss: 0.850172
iter: 20609 | loss: 0.849978
iter: 20610 | loss: 0.849785
iter: 20611 | loss: 0.849592
iter: 20612 | loss: 0.849398
iter: 20613 | loss: 0.849205
iter: 20614 | loss: 0.849011
iter: 20615 | loss: 0.848818
iter: 20616 | loss: 0.848625
iter: 20617 | loss: 0.848431
iter: 20618 | loss: 0.848238
iter: 20619 | loss: 0.848044
iter: 20620 | loss: 0.847851
iter: 20621 | loss: 0.847658
iter: 20622 | loss: 0.847464
iter: 20623 | loss: 0.847271
iter: 20624 | loss: 0.847078
iter: 20625 | loss: 0.846884
iter: 20626 | loss: 0.846691
iter: 20627 | loss: 0.846497
iter: 20628 | loss: 0.846304
iter: 20629 | loss: 0.846111
iter: 20630 | loss: 0.845917
iter: 20631 | loss: 0.845724
iter: 20632 | loss: 0.845530
iter: 20633 | loss: 0.845337
iter: 20634 | loss: 0.845144
iter: 20635 | loss: 0.844950
iter: 20636 | loss: 0.844757
iter: 20637 | loss: 0.844564
iter: 20638 | loss: 0.844370
iter: 20639 | loss: 0.844177
iter: 20640 | loss: 0.843983
iter: 20641 | loss: 0.843790
iter: 20642 | loss: 0.843597
iter: 20643 | loss: 0.843403
iter: 20644 | loss: 0.843210
iter: 20645 | loss: 0.843016
iter: 20646 | loss: 0.842823
iter: 20647 | loss: 0.842630
iter: 20648 | loss: 0.842436
iter: 20649 | loss: 0.842243
iter: 20650 | loss: 0.842050
iter: 20651 | loss: 0.841856
iter: 20652 | loss: 0.841663
iter: 20653 | loss: 0.841469
iter: 20654 | loss: 0.841276
iter: 20655 | loss: 0.841083
iter: 20656 | loss: 0.840889
iter: 20657 | loss: 0.840696
iter: 20658 | loss: 0.840502
iter: 20659 | loss: 0.840309
iter: 20660 | loss: 0.840116
iter: 20661 | loss: 0.839922
iter: 20662 | loss: 0.839729
iter: 20663 | loss: 0.839535
iter: 20664 | loss: 0.839342
iter: 20665 | loss: 0.839149
iter: 20666 | loss: 0.838955
iter: 20667 | loss: 0.838762
iter: 20668 | loss: 0.838569
iter: 20669 | loss: 0.838375
iter: 20670 | loss: 0.838182
iter: 20671 | loss: 0.837988
iter: 20672 | loss: 0.837795
iter: 20673 | loss: 0.837602
iter: 20674 | loss: 0.837408
iter: 20675 | loss: 0.837215
iter: 20676 | loss: 0.837021
iter: 20677 | loss: 0.836828
iter: 20678 | loss: 0.836635
iter: 20679 | loss: 0.836441
iter: 20680 | loss: 0.836248
iter: 20681 | loss: 0.836055
iter: 20682 | loss: 0.835861
iter: 20683 | loss: 0.835668
iter: 20684 | loss: 0.835474
iter: 20685 | loss: 0.835281
iter: 20686 | loss: 0.835088
iter: 20687 | loss: 0.834894
iter: 20688 | loss: 0.834701
iter: 20689 | loss: 0.834507
iter: 20690 | loss: 0.834314
iter: 20691 | loss: 0.834121
iter: 20692 | loss: 0.833927
iter: 20693 | loss: 0.833734
iter: 20694 | loss: 0.833540
iter: 20695 | loss: 0.833347
iter: 20696 | loss: 0.833154
iter: 20697 | loss: 0.832960
iter: 20698 | loss: 0.832767
iter: 20699 | loss: 0.832574
iter: 20700 | loss: 0.832380
iter: 20701 | loss: 0.832187
iter: 20702 | loss: 0.831993
iter: 20703 | loss: 0.831800
iter: 20704 | loss: 0.831607
iter: 20705 | loss: 0.831413
iter: 20706 | loss: 0.831220
iter: 20707 | loss: 0.831026
iter: 20708 | loss: 0.830833
iter: 20709 | loss: 0.830640
iter: 20710 | loss: 0.830446
iter: 20711 | loss: 0.830253
iter: 20712 | loss: 0.830060
iter: 20713 | loss: 0.829866
iter: 20714 | loss: 0.829673
iter: 20715 | loss: 0.829479
iter: 20716 | loss: 0.829286
iter: 20717 | loss: 0.829093
iter: 20718 | loss: 0.828899
iter: 20719 | loss: 0.828706
iter: 20720 | loss: 0.828512
iter: 20721 | loss: 0.828319
iter: 20722 | loss: 0.828126
iter: 20723 | loss: 0.827932
iter: 20724 | loss: 0.827739
iter: 20725 | loss: 0.827545
iter: 20726 | loss: 0.827352
iter: 20727 | loss: 0.827159
iter: 20728 | loss: 0.826965
iter: 20729 | loss: 0.826772
iter: 20730 | loss: 0.826579
iter: 20731 | loss: 0.826385
iter: 20732 | loss: 0.826192
iter: 20733 | loss: 0.825998
iter: 20734 | loss: 0.825805
iter: 20735 | loss: 0.825612
iter: 20736 | loss: 0.825418
iter: 20737 | loss: 0.825225
iter: 20738 | loss: 0.825031
iter: 20739 | loss: 0.824838
iter: 20740 | loss: 0.824645
iter: 20741 | loss: 0.824451
iter: 20742 | loss: 0.824258
iter: 20743 | loss: 0.824065
iter: 20744 | loss: 0.823871
iter: 20745 | loss: 0.823678
iter: 20746 | loss: 0.823484
iter: 20747 | loss: 0.823291
iter: 20748 | loss: 0.823098
iter: 20749 | loss: 0.822904
iter: 20750 | loss: 0.822711
iter: 20751 | loss: 0.822517
iter: 20752 | loss: 0.822324
iter: 20753 | loss: 0.822131
iter: 20754 | loss: 0.821937
iter: 20755 | loss: 0.821744
iter: 20756 | loss: 0.821550
iter: 20757 | loss: 0.821357
iter: 20758 | loss: 0.821164
iter: 20759 | loss: 0.820970
iter: 20760 | loss: 0.820777
iter: 20761 | loss: 0.820584
iter: 20762 | loss: 0.820390
iter: 20763 | loss: 0.820197
iter: 20764 | loss: 0.820003
iter: 20765 | loss: 0.819810
iter: 20766 | loss: 0.819617
iter: 20767 | loss: 0.819423
iter: 20768 | loss: 0.819230
iter: 20769 | loss: 0.819036
iter: 20770 | loss: 0.818843
iter: 20771 | loss: 0.818650
iter: 20772 | loss: 0.818456
iter: 20773 | loss: 0.818263
iter: 20774 | loss: 0.818070
iter: 20775 | loss: 0.817876
iter: 20776 | loss: 0.817683
iter: 20777 | loss: 0.817489
iter: 20778 | loss: 0.817296
iter: 20779 | loss: 0.817103
iter: 20780 | loss: 0.816909
iter: 20781 | loss: 0.816716
iter: 20782 | loss: 0.816522
iter: 20783 | loss: 0.816329
iter: 20784 | loss: 0.816136
iter: 20785 | loss: 0.815942
iter: 20786 | loss: 0.815749
iter: 20787 | loss: 0.815555
iter: 20788 | loss: 0.815362
iter: 20789 | loss: 0.815169
iter: 20790 | loss: 0.814975
iter: 20791 | loss: 0.814782
iter: 20792 | loss: 0.814589
iter: 20793 | loss: 0.814395
iter: 20794 | loss: 0.814202
iter: 20795 | loss: 0.814008
iter: 20796 | loss: 0.813815
iter: 20797 | loss: 0.813622
iter: 20798 | loss: 0.813428
iter: 20799 | loss: 0.813235
iter: 20800 | loss: 0.813041
iter: 20801 | loss: 0.812848
iter: 20802 | loss: 0.812655
iter: 20803 | loss: 0.812461
iter: 20804 | loss: 0.812268
iter: 20805 | loss: 0.812075
iter: 20806 | loss: 0.811881
iter: 20807 | loss: 0.811688
iter: 20808 | loss: 0.811494
iter: 20809 | loss: 0.811301
iter: 20810 | loss: 0.811108
iter: 20811 | loss: 0.810914
iter: 20812 | loss: 0.810721
iter: 20813 | loss: 0.810527
iter: 20814 | loss: 0.810334
iter: 20815 | loss: 0.810141
iter: 20816 | loss: 0.809947
iter: 20817 | loss: 0.809754
iter: 20818 | loss: 0.809560
iter: 20819 | loss: 0.809367
iter: 20820 | loss: 0.809174
iter: 20821 | loss: 0.808980
iter: 20822 | loss: 0.808787
iter: 20823 | loss: 0.808594
iter: 20824 | loss: 0.808400
iter: 20825 | loss: 0.808207
iter: 20826 | loss: 0.808013
iter: 20827 | loss: 0.807820
iter: 20828 | loss: 0.807627
iter: 20829 | loss: 0.807433
iter: 20830 | loss: 0.807240
iter: 20831 | loss: 0.807046
iter: 20832 | loss: 0.806853
iter: 20833 | loss: 0.806660
iter: 20834 | loss: 0.806466
iter: 20835 | loss: 0.806273
iter: 20836 | loss: 0.806080
iter: 20837 | loss: 0.805886
iter: 20838 | loss: 0.805693
iter: 20839 | loss: 0.805499
iter: 20840 | loss: 0.805306
iter: 20841 | loss: 0.805113
iter: 20842 | loss: 0.804919
iter: 20843 | loss: 0.804726
iter: 20844 | loss: 0.804532
iter: 20845 | loss: 0.804339
iter: 20846 | loss: 0.804146
iter: 20847 | loss: 0.803952
iter: 20848 | loss: 0.803759
iter: 20849 | loss: 0.803565
iter: 20850 | loss: 0.803372
iter: 20851 | loss: 0.803179
iter: 20852 | loss: 0.802985
iter: 20853 | loss: 0.802792
iter: 20854 | loss: 0.802599
iter: 20855 | loss: 0.802405
iter: 20856 | loss: 0.802212
iter: 20857 | loss: 0.802018
iter: 20858 | loss: 0.801825
iter: 20859 | loss: 0.801632
iter: 20860 | loss: 0.801438
iter: 20861 | loss: 0.801245
iter: 20862 | loss: 0.801051
iter: 20863 | loss: 0.800858
iter: 20864 | loss: 0.800665
iter: 20865 | loss: 0.800471
iter: 20866 | loss: 0.800278
iter: 20867 | loss: 0.800085
iter: 20868 | loss: 0.799891
iter: 20869 | loss: 0.799698
iter: 20870 | loss: 0.799504
iter: 20871 | loss: 0.799311
iter: 20872 | loss: 0.799118
iter: 20873 | loss: 0.798924
iter: 20874 | loss: 0.798731
iter: 20875 | loss: 0.798537
iter: 20876 | loss: 0.798344
iter: 20877 | loss: 0.798151
iter: 20878 | loss: 0.797957
iter: 20879 | loss: 0.797764
iter: 20880 | loss: 0.797570
iter: 20881 | loss: 0.797377
iter: 20882 | loss: 0.797184
iter: 20883 | loss: 0.796990
iter: 20884 | loss: 0.796797
iter: 20885 | loss: 0.796604
iter: 20886 | loss: 0.796410
iter: 20887 | loss: 0.796217
iter: 20888 | loss: 0.796023
iter: 20889 | loss: 0.795830
iter: 20890 | loss: 0.795637
iter: 20891 | loss: 0.795443
iter: 20892 | loss: 0.795250
iter: 20893 | loss: 0.795056
iter: 20894 | loss: 0.794863
iter: 20895 | loss: 0.794670
iter: 20896 | loss: 0.794476
iter: 20897 | loss: 0.794283
iter: 20898 | loss: 0.794090
iter: 20899 | loss: 0.793896
iter: 20900 | loss: 0.793703
iter: 20901 | loss: 0.793509
iter: 20902 | loss: 0.793316
iter: 20903 | loss: 0.793123
iter: 20904 | loss: 0.792929
iter: 20905 | loss: 0.792736
iter: 20906 | loss: 0.792542
iter: 20907 | loss: 0.792349
iter: 20908 | loss: 0.792156
iter: 20909 | loss: 0.791962
iter: 20910 | loss: 0.791769
iter: 20911 | loss: 0.791575
iter: 20912 | loss: 0.791382
iter: 20913 | loss: 0.791189
iter: 20914 | loss: 0.790995
iter: 20915 | loss: 0.790802
iter: 20916 | loss: 0.790609
iter: 20917 | loss: 0.790415
iter: 20918 | loss: 0.790222
iter: 20919 | loss: 0.790028
iter: 20920 | loss: 0.789835
iter: 20921 | loss: 0.789642
iter: 20922 | loss: 0.789448
iter: 20923 | loss: 0.789255
iter: 20924 | loss: 0.789061
iter: 20925 | loss: 0.788868
iter: 20926 | loss: 0.788675
iter: 20927 | loss: 0.788481
iter: 20928 | loss: 0.788288
iter: 20929 | loss: 0.788095
iter: 20930 | loss: 0.787901
iter: 20931 | loss: 0.787708
iter: 20932 | loss: 0.787514
iter: 20933 | loss: 0.787321
iter: 20934 | loss: 0.787128
iter: 20935 | loss: 0.786934
iter: 20936 | loss: 0.786741
iter: 20937 | loss: 0.786547
iter: 20938 | loss: 0.786354
iter: 20939 | loss: 0.786161
iter: 20940 | loss: 0.785967
iter: 20941 | loss: 0.785774
iter: 20942 | loss: 0.785580
iter: 20943 | loss: 0.785387
iter: 20944 | loss: 0.785194
iter: 20945 | loss: 0.785000
iter: 20946 | loss: 0.784807
iter: 20947 | loss: 0.784614
iter: 20948 | loss: 0.784420
iter: 20949 | loss: 0.784227
iter: 20950 | loss: 0.784033
iter: 20951 | loss: 0.783840
iter: 20952 | loss: 0.783647
iter: 20953 | loss: 0.783453
iter: 20954 | loss: 0.783260
iter: 20955 | loss: 0.783066
iter: 20956 | loss: 0.782873
iter: 20957 | loss: 0.782680
iter: 20958 | loss: 0.782486
iter: 20959 | loss: 0.782293
iter: 20960 | loss: 0.782100
iter: 20961 | loss: 0.781906
iter: 20962 | loss: 0.781713
iter: 20963 | loss: 0.781519
iter: 20964 | loss: 0.781326
iter: 20965 | loss: 0.781133
iter: 20966 | loss: 0.780939
iter: 20967 | loss: 0.780746
iter: 20968 | loss: 0.780552
iter: 20969 | loss: 0.780359
iter: 20970 | loss: 0.780166
iter: 20971 | loss: 0.779972
iter: 20972 | loss: 0.779779
iter: 20973 | loss: 0.779586
iter: 20974 | loss: 0.779392
iter: 20975 | loss: 0.779199
iter: 20976 | loss: 0.779005
iter: 20977 | loss: 0.778812
iter: 20978 | loss: 0.778619
iter: 20979 | loss: 0.778425
iter: 20980 | loss: 0.778232
iter: 20981 | loss: 0.778038
iter: 20982 | loss: 0.777845
iter: 20983 | loss: 0.777652
iter: 20984 | loss: 0.777458
iter: 20985 | loss: 0.777265
iter: 20986 | loss: 0.777071
iter: 20987 | loss: 0.776878
iter: 20988 | loss: 0.776685
iter: 20989 | loss: 0.776491
iter: 20990 | loss: 0.776298
iter: 20991 | loss: 0.776105
iter: 20992 | loss: 0.775911
iter: 20993 | loss: 0.775718
iter: 20994 | loss: 0.775524
iter: 20995 | loss: 0.775331
iter: 20996 | loss: 0.775138
iter: 20997 | loss: 0.774944
iter: 20998 | loss: 0.774751
iter: 20999 | loss: 0.774557
iter: 21000 | loss: 0.774364
iter: 21001 | loss: 0.774171
iter: 21002 | loss: 0.773977
iter: 21003 | loss: 0.773784
iter: 21004 | loss: 0.773591
iter: 21005 | loss: 0.773397
iter: 21006 | loss: 0.773204
iter: 21007 | loss: 0.773010
iter: 21008 | loss: 0.772817
iter: 21009 | loss: 0.772624
iter: 21010 | loss: 0.772430
iter: 21011 | loss: 0.772237
iter: 21012 | loss: 0.772043
iter: 21013 | loss: 0.771850
iter: 21014 | loss: 0.771657
iter: 21015 | loss: 0.771463
iter: 21016 | loss: 0.771270
iter: 21017 | loss: 0.771076
iter: 21018 | loss: 0.770883
iter: 21019 | loss: 0.770690
iter: 21020 | loss: 0.770496
iter: 21021 | loss: 0.770303
iter: 21022 | loss: 0.770110
iter: 21023 | loss: 0.769916
iter: 21024 | loss: 0.769723
iter: 21025 | loss: 0.769529
iter: 21026 | loss: 0.769336
iter: 21027 | loss: 0.769143
iter: 21028 | loss: 0.768949
iter: 21029 | loss: 0.768756
iter: 21030 | loss: 0.768562
iter: 21031 | loss: 0.768369
iter: 21032 | loss: 0.768176
iter: 21033 | loss: 0.767982
iter: 21034 | loss: 0.767789
iter: 21035 | loss: 0.767596
iter: 21036 | loss: 0.767402
iter: 21037 | loss: 0.767209
iter: 21038 | loss: 0.767015
iter: 21039 | loss: 0.766822
iter: 21040 | loss: 0.766629
iter: 21041 | loss: 0.766435
iter: 21042 | loss: 0.766242
iter: 21043 | loss: 0.766048
iter: 21044 | loss: 0.765855
iter: 21045 | loss: 0.765662
iter: 21046 | loss: 0.765468
iter: 21047 | loss: 0.765275
iter: 21048 | loss: 0.765081
iter: 21049 | loss: 0.764888
iter: 21050 | loss: 0.764695
iter: 21051 | loss: 0.764501
iter: 21052 | loss: 0.764308
iter: 21053 | loss: 0.764115
iter: 21054 | loss: 0.763921
iter: 21055 | loss: 0.763728
iter: 21056 | loss: 0.763534
iter: 21057 | loss: 0.763341
iter: 21058 | loss: 0.763148
iter: 21059 | loss: 0.762954
iter: 21060 | loss: 0.762761
iter: 21061 | loss: 0.762567
iter: 21062 | loss: 0.762374
iter: 21063 | loss: 0.762181
iter: 21064 | loss: 0.761987
iter: 21065 | loss: 0.761794
iter: 21066 | loss: 0.761601
iter: 21067 | loss: 0.761407
iter: 21068 | loss: 0.761214
iter: 21069 | loss: 0.761020
iter: 21070 | loss: 0.760827
iter: 21071 | loss: 0.760634
iter: 21072 | loss: 0.760440
iter: 21073 | loss: 0.760247
iter: 21074 | loss: 0.760053
iter: 21075 | loss: 0.759860
iter: 21076 | loss: 0.759667
iter: 21077 | loss: 0.759473
iter: 21078 | loss: 0.759280
iter: 21079 | loss: 0.759086
iter: 21080 | loss: 0.758893
iter: 21081 | loss: 0.758700
iter: 21082 | loss: 0.758506
iter: 21083 | loss: 0.758313
iter: 21084 | loss: 0.758120
iter: 21085 | loss: 0.757926
iter: 21086 | loss: 0.757733
iter: 21087 | loss: 0.757539
iter: 21088 | loss: 0.757346
iter: 21089 | loss: 0.757153
iter: 21090 | loss: 0.756959
iter: 21091 | loss: 0.756766
iter: 21092 | loss: 0.756572
iter: 21093 | loss: 0.756379
iter: 21094 | loss: 0.756186
iter: 21095 | loss: 0.755992
iter: 21096 | loss: 0.755799
iter: 21097 | loss: 0.755606
iter: 21098 | loss: 0.755412
iter: 21099 | loss: 0.755219
iter: 21100 | loss: 0.755025
iter: 21101 | loss: 0.754832
iter: 21102 | loss: 0.754639
iter: 21103 | loss: 0.754445
iter: 21104 | loss: 0.754252
iter: 21105 | loss: 0.754058
iter: 21106 | loss: 0.753865
iter: 21107 | loss: 0.753672
iter: 21108 | loss: 0.753478
iter: 21109 | loss: 0.753285
iter: 21110 | loss: 0.753091
iter: 21111 | loss: 0.752898
iter: 21112 | loss: 0.752705
iter: 21113 | loss: 0.752511
iter: 21114 | loss: 0.752318
iter: 21115 | loss: 0.752125
iter: 21116 | loss: 0.751931
iter: 21117 | loss: 0.751738
iter: 21118 | loss: 0.751544
iter: 21119 | loss: 0.751351
iter: 21120 | loss: 0.751158
iter: 21121 | loss: 0.750964
iter: 21122 | loss: 0.750771
iter: 21123 | loss: 0.750577
iter: 21124 | loss: 0.750384
iter: 21125 | loss: 0.750191
iter: 21126 | loss: 0.749997
iter: 21127 | loss: 0.749804
iter: 21128 | loss: 0.749611
iter: 21129 | loss: 0.749417
iter: 21130 | loss: 0.749224
iter: 21131 | loss: 0.749030
iter: 21132 | loss: 0.748837
iter: 21133 | loss: 0.748644
iter: 21134 | loss: 0.748450
iter: 21135 | loss: 0.748257
iter: 21136 | loss: 0.748063
iter: 21137 | loss: 0.747870
iter: 21138 | loss: 0.747677
iter: 21139 | loss: 0.747483
iter: 21140 | loss: 0.747290
iter: 21141 | loss: 0.747096
iter: 21142 | loss: 0.746903
iter: 21143 | loss: 0.746710
iter: 21144 | loss: 0.746516
iter: 21145 | loss: 0.746323
iter: 21146 | loss: 0.746130
iter: 21147 | loss: 0.745936
iter: 21148 | loss: 0.745743
iter: 21149 | loss: 0.745549
iter: 21150 | loss: 0.745356
iter: 21151 | loss: 0.745163
iter: 21152 | loss: 0.744969
iter: 21153 | loss: 0.744776
iter: 21154 | loss: 0.744582
iter: 21155 | loss: 0.744389
iter: 21156 | loss: 0.744196
iter: 21157 | loss: 0.744002
iter: 21158 | loss: 0.743809
iter: 21159 | loss: 0.743616
iter: 21160 | loss: 0.743422
iter: 21161 | loss: 0.743229
iter: 21162 | loss: 0.743035
iter: 21163 | loss: 0.742842
iter: 21164 | loss: 0.742649
iter: 21165 | loss: 0.742455
iter: 21166 | loss: 0.742262
iter: 21167 | loss: 0.742068
iter: 21168 | loss: 0.741875
iter: 21169 | loss: 0.741682
iter: 21170 | loss: 0.741488
iter: 21171 | loss: 0.741295
iter: 21172 | loss: 0.741101
iter: 21173 | loss: 0.740908
iter: 21174 | loss: 0.740715
iter: 21175 | loss: 0.740521
iter: 21176 | loss: 0.740328
iter: 21177 | loss: 0.740135
iter: 21178 | loss: 0.739941
iter: 21179 | loss: 0.739748
iter: 21180 | loss: 0.739554
iter: 21181 | loss: 0.739361
iter: 21182 | loss: 0.739168
iter: 21183 | loss: 0.738974
iter: 21184 | loss: 0.738781
iter: 21185 | loss: 0.738587
iter: 21186 | loss: 0.738394
iter: 21187 | loss: 0.738201
iter: 21188 | loss: 0.738007
iter: 21189 | loss: 0.737814
iter: 21190 | loss: 0.737621
iter: 21191 | loss: 0.737427
iter: 21192 | loss: 0.737234
iter: 21193 | loss: 0.737040
iter: 21194 | loss: 0.736847
iter: 21195 | loss: 0.736654
iter: 21196 | loss: 0.736460
iter: 21197 | loss: 0.736267
iter: 21198 | loss: 0.736073
iter: 21199 | loss: 0.735880
iter: 21200 | loss: 0.735687
iter: 21201 | loss: 0.735493
iter: 21202 | loss: 0.735300
iter: 21203 | loss: 0.735106
iter: 21204 | loss: 0.734913
iter: 21205 | loss: 0.734720
iter: 21206 | loss: 0.734526
iter: 21207 | loss: 0.734333
iter: 21208 | loss: 0.734140
iter: 21209 | loss: 0.733946
iter: 21210 | loss: 0.733753
iter: 21211 | loss: 0.733559
iter: 21212 | loss: 0.733366
iter: 21213 | loss: 0.733173
iter: 21214 | loss: 0.732979
iter: 21215 | loss: 0.732786
iter: 21216 | loss: 0.732592
iter: 21217 | loss: 0.732399
iter: 21218 | loss: 0.732206
iter: 21219 | loss: 0.732012
iter: 21220 | loss: 0.731819
iter: 21221 | loss: 0.731626
iter: 21222 | loss: 0.731432
iter: 21223 | loss: 0.731239
iter: 21224 | loss: 0.731045
iter: 21225 | loss: 0.730852
iter: 21226 | loss: 0.730659
iter: 21227 | loss: 0.730465
iter: 21228 | loss: 0.730272
iter: 21229 | loss: 0.730078
iter: 21230 | loss: 0.729885
iter: 21231 | loss: 0.729692
iter: 21232 | loss: 0.729498
iter: 21233 | loss: 0.729305
iter: 21234 | loss: 0.729111
iter: 21235 | loss: 0.728918
iter: 21236 | loss: 0.728725
iter: 21237 | loss: 0.728531
iter: 21238 | loss: 0.728338
iter: 21239 | loss: 0.728145
iter: 21240 | loss: 0.727951
iter: 21241 | loss: 0.727758
iter: 21242 | loss: 0.727564
iter: 21243 | loss: 0.727371
iter: 21244 | loss: 0.727178
iter: 21245 | loss: 0.726984
iter: 21246 | loss: 0.726791
iter: 21247 | loss: 0.726597
iter: 21248 | loss: 0.726404
iter: 21249 | loss: 0.726211
iter: 21250 | loss: 0.726017
iter: 21251 | loss: 0.725824
iter: 21252 | loss: 0.725631
iter: 21253 | loss: 0.725437
iter: 21254 | loss: 0.725244
iter: 21255 | loss: 0.725050
iter: 21256 | loss: 0.724857
iter: 21257 | loss: 0.724664
iter: 21258 | loss: 0.724470
iter: 21259 | loss: 0.724277
iter: 21260 | loss: 0.724083
iter: 21261 | loss: 0.723890
iter: 21262 | loss: 0.723697
iter: 21263 | loss: 0.723503
iter: 21264 | loss: 0.723310
iter: 21265 | loss: 0.723116
iter: 21266 | loss: 0.722923
iter: 21267 | loss: 0.722730
iter: 21268 | loss: 0.722536
iter: 21269 | loss: 0.722343
iter: 21270 | loss: 0.722150
iter: 21271 | loss: 0.721956
iter: 21272 | loss: 0.721763
iter: 21273 | loss: 0.721569
iter: 21274 | loss: 0.721376
iter: 21275 | loss: 0.721183
iter: 21276 | loss: 0.720989
iter: 21277 | loss: 0.720796
iter: 21278 | loss: 0.720602
iter: 21279 | loss: 0.720409
iter: 21280 | loss: 0.720216
iter: 21281 | loss: 0.720022
iter: 21282 | loss: 0.719829
iter: 21283 | loss: 0.719636
iter: 21284 | loss: 0.719442
iter: 21285 | loss: 0.719249
iter: 21286 | loss: 0.719055
iter: 21287 | loss: 0.718862
iter: 21288 | loss: 0.718669
iter: 21289 | loss: 0.718475
iter: 21290 | loss: 0.718282
iter: 21291 | loss: 0.718088
iter: 21292 | loss: 0.717895
iter: 21293 | loss: 0.717702
iter: 21294 | loss: 0.717508
iter: 21295 | loss: 0.717315
iter: 21296 | loss: 0.717122
iter: 21297 | loss: 0.716928
iter: 21298 | loss: 0.716735
iter: 21299 | loss: 0.716541
iter: 21300 | loss: 0.716348
iter: 21301 | loss: 0.716155
iter: 21302 | loss: 0.715961
iter: 21303 | loss: 0.715768
iter: 21304 | loss: 0.715574
iter: 21305 | loss: 0.715381
iter: 21306 | loss: 0.715188
iter: 21307 | loss: 0.714994
iter: 21308 | loss: 0.714801
iter: 21309 | loss: 0.714607
iter: 21310 | loss: 0.714414
iter: 21311 | loss: 0.714221
iter: 21312 | loss: 0.714027
iter: 21313 | loss: 0.713834
iter: 21314 | loss: 0.713641
iter: 21315 | loss: 0.713447
iter: 21316 | loss: 0.713254
iter: 21317 | loss: 0.713060
iter: 21318 | loss: 0.712867
iter: 21319 | loss: 0.712674
iter: 21320 | loss: 0.712480
iter: 21321 | loss: 0.712287
iter: 21322 | loss: 0.712093
iter: 21323 | loss: 0.711900
iter: 21324 | loss: 0.711707
iter: 21325 | loss: 0.711513
iter: 21326 | loss: 0.711320
iter: 21327 | loss: 0.711127
iter: 21328 | loss: 0.710933
iter: 21329 | loss: 0.710740
iter: 21330 | loss: 0.710546
iter: 21331 | loss: 0.710353
iter: 21332 | loss: 0.710160
iter: 21333 | loss: 0.709966
iter: 21334 | loss: 0.709773
iter: 21335 | loss: 0.709579
iter: 21336 | loss: 0.709386
iter: 21337 | loss: 0.709193
iter: 21338 | loss: 0.708999
iter: 21339 | loss: 0.708806
iter: 21340 | loss: 0.708612
iter: 21341 | loss: 0.708419
iter: 21342 | loss: 0.708226
iter: 21343 | loss: 0.708032
iter: 21344 | loss: 0.707839
iter: 21345 | loss: 0.707646
iter: 21346 | loss: 0.707452
iter: 21347 | loss: 0.707259
iter: 21348 | loss: 0.707065
iter: 21349 | loss: 0.706872
iter: 21350 | loss: 0.706679
iter: 21351 | loss: 0.706485
iter: 21352 | loss: 0.706292
iter: 21353 | loss: 0.706098
iter: 21354 | loss: 0.705905
iter: 21355 | loss: 0.705712
iter: 21356 | loss: 0.705518
iter: 21357 | loss: 0.705325
iter: 21358 | loss: 0.705132
iter: 21359 | loss: 0.704938
iter: 21360 | loss: 0.704745
iter: 21361 | loss: 0.704551
iter: 21362 | loss: 0.704358
iter: 21363 | loss: 0.704165
iter: 21364 | loss: 0.703971
iter: 21365 | loss: 0.703778
iter: 21366 | loss: 0.703584
iter: 21367 | loss: 0.703391
iter: 21368 | loss: 0.703198
iter: 21369 | loss: 0.703004
iter: 21370 | loss: 0.702811
iter: 21371 | loss: 0.702617
iter: 21372 | loss: 0.702424
iter: 21373 | loss: 0.702231
iter: 21374 | loss: 0.702037
iter: 21375 | loss: 0.701844
iter: 21376 | loss: 0.701651
iter: 21377 | loss: 0.701457
iter: 21378 | loss: 0.701264
iter: 21379 | loss: 0.701070
iter: 21380 | loss: 0.700877
iter: 21381 | loss: 0.700684
iter: 21382 | loss: 0.700490
iter: 21383 | loss: 0.700297
iter: 21384 | loss: 0.700103
iter: 21385 | loss: 0.699910
iter: 21386 | loss: 0.699717
iter: 21387 | loss: 0.699523
iter: 21388 | loss: 0.699330
iter: 21389 | loss: 0.699137
iter: 21390 | loss: 0.698943
iter: 21391 | loss: 0.698750
iter: 21392 | loss: 0.698556
iter: 21393 | loss: 0.698363
iter: 21394 | loss: 0.698170
iter: 21395 | loss: 0.697976
iter: 21396 | loss: 0.697783
iter: 21397 | loss: 0.697589
iter: 21398 | loss: 0.697396
iter: 21399 | loss: 0.697203
iter: 21400 | loss: 0.697009
iter: 21401 | loss: 0.696816
iter: 21402 | loss: 0.696622
iter: 21403 | loss: 0.696429
iter: 21404 | loss: 0.696236
iter: 21405 | loss: 0.696042
iter: 21406 | loss: 0.695849
iter: 21407 | loss: 0.695656
iter: 21408 | loss: 0.695462
iter: 21409 | loss: 0.695269
iter: 21410 | loss: 0.695075
iter: 21411 | loss: 0.694882
iter: 21412 | loss: 0.694689
iter: 21413 | loss: 0.694495
iter: 21414 | loss: 0.694302
iter: 21415 | loss: 0.694108
iter: 21416 | loss: 0.693915
iter: 21417 | loss: 0.693722
iter: 21418 | loss: 0.693528
iter: 21419 | loss: 0.693335
iter: 21420 | loss: 0.693142
iter: 21421 | loss: 0.692948
iter: 21422 | loss: 0.692755
iter: 21423 | loss: 0.692561
iter: 21424 | loss: 0.692368
iter: 21425 | loss: 0.692175
iter: 21426 | loss: 0.691981
iter: 21427 | loss: 0.691788
iter: 21428 | loss: 0.691594
iter: 21429 | loss: 0.691401
iter: 21430 | loss: 0.691208
iter: 21431 | loss: 0.691014
iter: 21432 | loss: 0.690821
iter: 21433 | loss: 0.690627
iter: 21434 | loss: 0.690434
iter: 21435 | loss: 0.690241
iter: 21436 | loss: 0.690047
iter: 21437 | loss: 0.689854
iter: 21438 | loss: 0.689661
iter: 21439 | loss: 0.689467
iter: 21440 | loss: 0.689274
iter: 21441 | loss: 0.689080
iter: 21442 | loss: 0.688887
iter: 21443 | loss: 0.688694
iter: 21444 | loss: 0.688500
iter: 21445 | loss: 0.688307
iter: 21446 | loss: 0.688113
iter: 21447 | loss: 0.687920
iter: 21448 | loss: 0.687727
iter: 21449 | loss: 0.687533
iter: 21450 | loss: 0.687340
iter: 21451 | loss: 0.687147
iter: 21452 | loss: 0.686953
iter: 21453 | loss: 0.686760
iter: 21454 | loss: 0.686566
iter: 21455 | loss: 0.686373
iter: 21456 | loss: 0.686180
iter: 21457 | loss: 0.685986
iter: 21458 | loss: 0.685793
iter: 21459 | loss: 0.685599
iter: 21460 | loss: 0.685406
iter: 21461 | loss: 0.685213
iter: 21462 | loss: 0.685019
iter: 21463 | loss: 0.684826
iter: 21464 | loss: 0.684632
iter: 21465 | loss: 0.684439
iter: 21466 | loss: 0.684246
iter: 21467 | loss: 0.684052
iter: 21468 | loss: 0.683859
iter: 21469 | loss: 0.683666
iter: 21470 | loss: 0.683472
iter: 21471 | loss: 0.683279
iter: 21472 | loss: 0.683085
iter: 21473 | loss: 0.682892
iter: 21474 | loss: 0.682699
iter: 21475 | loss: 0.682505
iter: 21476 | loss: 0.682312
iter: 21477 | loss: 0.682118
iter: 21478 | loss: 0.681925
iter: 21479 | loss: 0.681732
iter: 21480 | loss: 0.681538
iter: 21481 | loss: 0.681345
iter: 21482 | loss: 0.681152
iter: 21483 | loss: 0.680958
iter: 21484 | loss: 0.680765
iter: 21485 | loss: 0.680571
iter: 21486 | loss: 0.680378
iter: 21487 | loss: 0.680185
iter: 21488 | loss: 0.679991
iter: 21489 | loss: 0.679798
iter: 21490 | loss: 0.679604
iter: 21491 | loss: 0.679411
iter: 21492 | loss: 0.679218
iter: 21493 | loss: 0.679024
iter: 21494 | loss: 0.678831
iter: 21495 | loss: 0.678637
iter: 21496 | loss: 0.678444
iter: 21497 | loss: 0.678251
iter: 21498 | loss: 0.678057
iter: 21499 | loss: 0.677864
iter: 21500 | loss: 0.677671
iter: 21501 | loss: 0.677477
iter: 21502 | loss: 0.677284
iter: 21503 | loss: 0.677090
iter: 21504 | loss: 0.676897
iter: 21505 | loss: 0.676704
iter: 21506 | loss: 0.676510
iter: 21507 | loss: 0.676317
iter: 21508 | loss: 0.676123
iter: 21509 | loss: 0.675930
iter: 21510 | loss: 0.675737
iter: 21511 | loss: 0.675543
iter: 21512 | loss: 0.675350
iter: 21513 | loss: 0.675157
iter: 21514 | loss: 0.674963
iter: 21515 | loss: 0.674770
iter: 21516 | loss: 0.674576
iter: 21517 | loss: 0.674383
iter: 21518 | loss: 0.674190
iter: 21519 | loss: 0.673996
iter: 21520 | loss: 0.673803
iter: 21521 | loss: 0.673609
iter: 21522 | loss: 0.673416
iter: 21523 | loss: 0.673223
iter: 21524 | loss: 0.673029
iter: 21525 | loss: 0.672836
iter: 21526 | loss: 0.672642
iter: 21527 | loss: 0.672449
iter: 21528 | loss: 0.672256
iter: 21529 | loss: 0.672062
iter: 21530 | loss: 0.671869
iter: 21531 | loss: 0.671676
iter: 21532 | loss: 0.671482
iter: 21533 | loss: 0.671289
iter: 21534 | loss: 0.671095
iter: 21535 | loss: 0.670902
iter: 21536 | loss: 0.670709
iter: 21537 | loss: 0.670515
iter: 21538 | loss: 0.670322
iter: 21539 | loss: 0.670128
iter: 21540 | loss: 0.669935
iter: 21541 | loss: 0.669742
iter: 21542 | loss: 0.669548
iter: 21543 | loss: 0.669355
iter: 21544 | loss: 0.669162
iter: 21545 | loss: 0.668968
iter: 21546 | loss: 0.668775
iter: 21547 | loss: 0.668581
iter: 21548 | loss: 0.668388
iter: 21549 | loss: 0.668195
iter: 21550 | loss: 0.668001
iter: 21551 | loss: 0.667808
iter: 21552 | loss: 0.667614
iter: 21553 | loss: 0.667421
iter: 21554 | loss: 0.667228
iter: 21555 | loss: 0.667034
iter: 21556 | loss: 0.666841
iter: 21557 | loss: 0.666647
iter: 21558 | loss: 0.666454
iter: 21559 | loss: 0.666261
iter: 21560 | loss: 0.666067
iter: 21561 | loss: 0.665874
iter: 21562 | loss: 0.665681
iter: 21563 | loss: 0.665487
iter: 21564 | loss: 0.665294
iter: 21565 | loss: 0.665100
iter: 21566 | loss: 0.664907
iter: 21567 | loss: 0.664714
iter: 21568 | loss: 0.664520
iter: 21569 | loss: 0.664327
iter: 21570 | loss: 0.664133
iter: 21571 | loss: 0.663940
iter: 21572 | loss: 0.663747
iter: 21573 | loss: 0.663553
iter: 21574 | loss: 0.663360
iter: 21575 | loss: 0.663167
iter: 21576 | loss: 0.662973
iter: 21577 | loss: 0.662780
iter: 21578 | loss: 0.662586
iter: 21579 | loss: 0.662393
iter: 21580 | loss: 0.662200
iter: 21581 | loss: 0.662006
iter: 21582 | loss: 0.661813
iter: 21583 | loss: 0.661619
iter: 21584 | loss: 0.661426
iter: 21585 | loss: 0.661233
iter: 21586 | loss: 0.661039
iter: 21587 | loss: 0.660846
iter: 21588 | loss: 0.660652
iter: 21589 | loss: 0.660459
iter: 21590 | loss: 0.660266
iter: 21591 | loss: 0.660072
iter: 21592 | loss: 0.659879
iter: 21593 | loss: 0.659686
iter: 21594 | loss: 0.659492
iter: 21595 | loss: 0.659299
iter: 21596 | loss: 0.659105
iter: 21597 | loss: 0.658912
iter: 21598 | loss: 0.658719
iter: 21599 | loss: 0.658525
iter: 21600 | loss: 0.658332
iter: 21601 | loss: 0.658138
iter: 21602 | loss: 0.657945
iter: 21603 | loss: 0.657752
iter: 21604 | loss: 0.657558
iter: 21605 | loss: 0.657365
iter: 21606 | loss: 0.657172
iter: 21607 | loss: 0.656978
iter: 21608 | loss: 0.656785
iter: 21609 | loss: 0.656591
iter: 21610 | loss: 0.656398
iter: 21611 | loss: 0.656205
iter: 21612 | loss: 0.656011
iter: 21613 | loss: 0.655818
iter: 21614 | loss: 0.655624
iter: 21615 | loss: 0.655431
iter: 21616 | loss: 0.655238
iter: 21617 | loss: 0.655044
iter: 21618 | loss: 0.654851
iter: 21619 | loss: 0.654658
iter: 21620 | loss: 0.654464
iter: 21621 | loss: 0.654271
iter: 21622 | loss: 0.654077
iter: 21623 | loss: 0.653884
iter: 21624 | loss: 0.653691
iter: 21625 | loss: 0.653497
iter: 21626 | loss: 0.653304
iter: 21627 | loss: 0.653110
iter: 21628 | loss: 0.652917
iter: 21629 | loss: 0.652724
iter: 21630 | loss: 0.652530
iter: 21631 | loss: 0.652337
iter: 21632 | loss: 0.652143
iter: 21633 | loss: 0.651950
iter: 21634 | loss: 0.651757
iter: 21635 | loss: 0.651563
iter: 21636 | loss: 0.651370
iter: 21637 | loss: 0.651177
iter: 21638 | loss: 0.650983
iter: 21639 | loss: 0.650790
iter: 21640 | loss: 0.650596
iter: 21641 | loss: 0.650403
iter: 21642 | loss: 0.650210
iter: 21643 | loss: 0.650016
iter: 21644 | loss: 0.649823
iter: 21645 | loss: 0.649629
iter: 21646 | loss: 0.649436
iter: 21647 | loss: 0.649243
iter: 21648 | loss: 0.649049
iter: 21649 | loss: 0.648856
iter: 21650 | loss: 0.648663
iter: 21651 | loss: 0.648469
iter: 21652 | loss: 0.648276
iter: 21653 | loss: 0.648082
iter: 21654 | loss: 0.647889
iter: 21655 | loss: 0.647696
iter: 21656 | loss: 0.647502
iter: 21657 | loss: 0.647309
iter: 21658 | loss: 0.647115
iter: 21659 | loss: 0.646922
iter: 21660 | loss: 0.646729
iter: 21661 | loss: 0.646535
iter: 21662 | loss: 0.646342
iter: 21663 | loss: 0.646148
iter: 21664 | loss: 0.645955
iter: 21665 | loss: 0.645762
iter: 21666 | loss: 0.645568
iter: 21667 | loss: 0.645375
iter: 21668 | loss: 0.645182
iter: 21669 | loss: 0.644988
iter: 21670 | loss: 0.644795
iter: 21671 | loss: 0.644601
iter: 21672 | loss: 0.644408
iter: 21673 | loss: 0.644215
iter: 21674 | loss: 0.644021
iter: 21675 | loss: 0.643828
iter: 21676 | loss: 0.643634
iter: 21677 | loss: 0.643441
iter: 21678 | loss: 0.643248
iter: 21679 | loss: 0.643054
iter: 21680 | loss: 0.642861
iter: 21681 | loss: 0.642668
iter: 21682 | loss: 0.642474
iter: 21683 | loss: 0.642281
iter: 21684 | loss: 0.642087
iter: 21685 | loss: 0.641894
iter: 21686 | loss: 0.641701
iter: 21687 | loss: 0.641507
iter: 21688 | loss: 0.641314
iter: 21689 | loss: 0.641120
iter: 21690 | loss: 0.640927
iter: 21691 | loss: 0.640734
iter: 21692 | loss: 0.640540
iter: 21693 | loss: 0.640347
iter: 21694 | loss: 0.640153
iter: 21695 | loss: 0.639960
iter: 21696 | loss: 0.639767
iter: 21697 | loss: 0.639573
iter: 21698 | loss: 0.639380
iter: 21699 | loss: 0.639187
iter: 21700 | loss: 0.638993
iter: 21701 | loss: 0.638800
iter: 21702 | loss: 0.638606
iter: 21703 | loss: 0.638413
iter: 21704 | loss: 0.638220
iter: 21705 | loss: 0.638026
iter: 21706 | loss: 0.637833
iter: 21707 | loss: 0.637639
iter: 21708 | loss: 0.637446
iter: 21709 | loss: 0.637253
iter: 21710 | loss: 0.637059
iter: 21711 | loss: 0.636866
iter: 21712 | loss: 0.636673
iter: 21713 | loss: 0.636479
iter: 21714 | loss: 0.636286
iter: 21715 | loss: 0.636092
iter: 21716 | loss: 0.635899
iter: 21717 | loss: 0.635706
iter: 21718 | loss: 0.635512
iter: 21719 | loss: 0.635319
iter: 21720 | loss: 0.635125
iter: 21721 | loss: 0.634932
iter: 21722 | loss: 0.634739
iter: 21723 | loss: 0.634545
iter: 21724 | loss: 0.634352
iter: 21725 | loss: 0.634158
iter: 21726 | loss: 0.633965
iter: 21727 | loss: 0.633772
iter: 21728 | loss: 0.633578
iter: 21729 | loss: 0.633385
iter: 21730 | loss: 0.633192
iter: 21731 | loss: 0.632998
iter: 21732 | loss: 0.632805
iter: 21733 | loss: 0.632611
iter: 21734 | loss: 0.632418
iter: 21735 | loss: 0.632225
iter: 21736 | loss: 0.632031
iter: 21737 | loss: 0.631838
iter: 21738 | loss: 0.631644
iter: 21739 | loss: 0.631451
iter: 21740 | loss: 0.631258
iter: 21741 | loss: 0.631064
iter: 21742 | loss: 0.630871
iter: 21743 | loss: 0.630678
iter: 21744 | loss: 0.630484
iter: 21745 | loss: 0.630291
iter: 21746 | loss: 0.630097
iter: 21747 | loss: 0.629904
iter: 21748 | loss: 0.629711
iter: 21749 | loss: 0.629517
iter: 21750 | loss: 0.629324
iter: 21751 | loss: 0.629130
iter: 21752 | loss: 0.628937
iter: 21753 | loss: 0.628744
iter: 21754 | loss: 0.628550
iter: 21755 | loss: 0.628357
iter: 21756 | loss: 0.628163
iter: 21757 | loss: 0.627970
iter: 21758 | loss: 0.627777
iter: 21759 | loss: 0.627583
iter: 21760 | loss: 0.627390
iter: 21761 | loss: 0.627197
iter: 21762 | loss: 0.627003
iter: 21763 | loss: 0.626810
iter: 21764 | loss: 0.626616
iter: 21765 | loss: 0.626423
iter: 21766 | loss: 0.626230
iter: 21767 | loss: 0.626036
iter: 21768 | loss: 0.625843
iter: 21769 | loss: 0.625649
iter: 21770 | loss: 0.625456
iter: 21771 | loss: 0.625263
iter: 21772 | loss: 0.625069
iter: 21773 | loss: 0.624876
iter: 21774 | loss: 0.624683
iter: 21775 | loss: 0.624489
iter: 21776 | loss: 0.624296
iter: 21777 | loss: 0.624102
iter: 21778 | loss: 0.623909
iter: 21779 | loss: 0.623716
iter: 21780 | loss: 0.623522
iter: 21781 | loss: 0.623329
iter: 21782 | loss: 0.623135
iter: 21783 | loss: 0.622942
iter: 21784 | loss: 0.622749
iter: 21785 | loss: 0.622555
iter: 21786 | loss: 0.622362
iter: 21787 | loss: 0.622168
iter: 21788 | loss: 0.621975
iter: 21789 | loss: 0.621782
iter: 21790 | loss: 0.621588
iter: 21791 | loss: 0.621395
iter: 21792 | loss: 0.621202
iter: 21793 | loss: 0.621008
iter: 21794 | loss: 0.620815
iter: 21795 | loss: 0.620621
iter: 21796 | loss: 0.620428
iter: 21797 | loss: 0.620235
iter: 21798 | loss: 0.620041
iter: 21799 | loss: 0.619848
iter: 21800 | loss: 0.619654
iter: 21801 | loss: 0.619461
iter: 21802 | loss: 0.619268
iter: 21803 | loss: 0.619074
iter: 21804 | loss: 0.618881
iter: 21805 | loss: 0.618688
iter: 21806 | loss: 0.618494
iter: 21807 | loss: 0.618301
iter: 21808 | loss: 0.618107
iter: 21809 | loss: 0.617914
iter: 21810 | loss: 0.617721
iter: 21811 | loss: 0.617527
iter: 21812 | loss: 0.617334
iter: 21813 | loss: 0.617140
iter: 21814 | loss: 0.616947
iter: 21815 | loss: 0.616754
iter: 21816 | loss: 0.616560
iter: 21817 | loss: 0.616367
iter: 21818 | loss: 0.616173
iter: 21819 | loss: 0.615980
iter: 21820 | loss: 0.615787
iter: 21821 | loss: 0.615593
iter: 21822 | loss: 0.615400
iter: 21823 | loss: 0.615207
iter: 21824 | loss: 0.615013
iter: 21825 | loss: 0.614820
iter: 21826 | loss: 0.614626
iter: 21827 | loss: 0.614433
iter: 21828 | loss: 0.614240
iter: 21829 | loss: 0.614046
iter: 21830 | loss: 0.613853
iter: 21831 | loss: 0.613659
iter: 21832 | loss: 0.613466
iter: 21833 | loss: 0.613273
iter: 21834 | loss: 0.613079
iter: 21835 | loss: 0.612886
iter: 21836 | loss: 0.612693
iter: 21837 | loss: 0.612499
iter: 21838 | loss: 0.612306
iter: 21839 | loss: 0.612112
iter: 21840 | loss: 0.611919
iter: 21841 | loss: 0.611726
iter: 21842 | loss: 0.611532
iter: 21843 | loss: 0.611339
iter: 21844 | loss: 0.611145
iter: 21845 | loss: 0.610952
iter: 21846 | loss: 0.610759
iter: 21847 | loss: 0.610565
iter: 21848 | loss: 0.610372
iter: 21849 | loss: 0.610178
iter: 21850 | loss: 0.609985
iter: 21851 | loss: 0.609792
iter: 21852 | loss: 0.609598
iter: 21853 | loss: 0.609405
iter: 21854 | loss: 0.609212
iter: 21855 | loss: 0.609018
iter: 21856 | loss: 0.608825
iter: 21857 | loss: 0.608631
iter: 21858 | loss: 0.608438
iter: 21859 | loss: 0.608245
iter: 21860 | loss: 0.608051
iter: 21861 | loss: 0.607858
iter: 21862 | loss: 0.607664
iter: 21863 | loss: 0.607471
iter: 21864 | loss: 0.607278
iter: 21865 | loss: 0.607084
iter: 21866 | loss: 0.606891
iter: 21867 | loss: 0.606698
iter: 21868 | loss: 0.606504
iter: 21869 | loss: 0.606311
iter: 21870 | loss: 0.606117
iter: 21871 | loss: 0.605924
iter: 21872 | loss: 0.605731
iter: 21873 | loss: 0.605537
iter: 21874 | loss: 0.605344
iter: 21875 | loss: 0.605150
iter: 21876 | loss: 0.604957
iter: 21877 | loss: 0.604764
iter: 21878 | loss: 0.604570
iter: 21879 | loss: 0.604377
iter: 21880 | loss: 0.604183
iter: 21881 | loss: 0.603990
iter: 21882 | loss: 0.603797
iter: 21883 | loss: 0.603603
iter: 21884 | loss: 0.603410
iter: 21885 | loss: 0.603217
iter: 21886 | loss: 0.603023
iter: 21887 | loss: 0.602830
iter: 21888 | loss: 0.602636
iter: 21889 | loss: 0.602443
iter: 21890 | loss: 0.602250
iter: 21891 | loss: 0.602056
iter: 21892 | loss: 0.601863
iter: 21893 | loss: 0.601669
iter: 21894 | loss: 0.601476
iter: 21895 | loss: 0.601283
iter: 21896 | loss: 0.601089
iter: 21897 | loss: 0.600896
iter: 21898 | loss: 0.600703
iter: 21899 | loss: 0.600509
iter: 21900 | loss: 0.600316
iter: 21901 | loss: 0.600122
iter: 21902 | loss: 0.599929
iter: 21903 | loss: 0.599736
iter: 21904 | loss: 0.599542
iter: 21905 | loss: 0.599349
iter: 21906 | loss: 0.599155
iter: 21907 | loss: 0.598962
iter: 21908 | loss: 0.598769
iter: 21909 | loss: 0.598575
iter: 21910 | loss: 0.598382
iter: 21911 | loss: 0.598189
iter: 21912 | loss: 0.597995
iter: 21913 | loss: 0.597802
iter: 21914 | loss: 0.597608
iter: 21915 | loss: 0.597415
iter: 21916 | loss: 0.597222
iter: 21917 | loss: 0.597028
iter: 21918 | loss: 0.596835
iter: 21919 | loss: 0.596641
iter: 21920 | loss: 0.596448
iter: 21921 | loss: 0.596255
iter: 21922 | loss: 0.596061
iter: 21923 | loss: 0.595868
iter: 21924 | loss: 0.595674
iter: 21925 | loss: 0.595481
iter: 21926 | loss: 0.595288
iter: 21927 | loss: 0.595094
iter: 21928 | loss: 0.594901
iter: 21929 | loss: 0.594708
iter: 21930 | loss: 0.594514
iter: 21931 | loss: 0.594321
iter: 21932 | loss: 0.594127
iter: 21933 | loss: 0.593934
iter: 21934 | loss: 0.593741
iter: 21935 | loss: 0.593547
iter: 21936 | loss: 0.593354
iter: 21937 | loss: 0.593160
iter: 21938 | loss: 0.592967
iter: 21939 | loss: 0.592774
iter: 21940 | loss: 0.592580
iter: 21941 | loss: 0.592387
iter: 21942 | loss: 0.592194
iter: 21943 | loss: 0.592000
iter: 21944 | loss: 0.591807
iter: 21945 | loss: 0.591613
iter: 21946 | loss: 0.591420
iter: 21947 | loss: 0.591227
iter: 21948 | loss: 0.591033
iter: 21949 | loss: 0.590840
iter: 21950 | loss: 0.590646
iter: 21951 | loss: 0.590453
iter: 21952 | loss: 0.590260
iter: 21953 | loss: 0.590066
iter: 21954 | loss: 0.589873
iter: 21955 | loss: 0.589679
iter: 21956 | loss: 0.589486
iter: 21957 | loss: 0.589293
iter: 21958 | loss: 0.589099
iter: 21959 | loss: 0.588906
iter: 21960 | loss: 0.588713
iter: 21961 | loss: 0.588519
iter: 21962 | loss: 0.588326
iter: 21963 | loss: 0.588132
iter: 21964 | loss: 0.587939
iter: 21965 | loss: 0.587746
iter: 21966 | loss: 0.587552
iter: 21967 | loss: 0.587359
iter: 21968 | loss: 0.587165
iter: 21969 | loss: 0.586972
iter: 21970 | loss: 0.586779
iter: 21971 | loss: 0.586585
iter: 21972 | loss: 0.586392
iter: 21973 | loss: 0.586199
iter: 21974 | loss: 0.586005
iter: 21975 | loss: 0.585812
iter: 21976 | loss: 0.585618
iter: 21977 | loss: 0.585425
iter: 21978 | loss: 0.585232
iter: 21979 | loss: 0.585038
iter: 21980 | loss: 0.584845
iter: 21981 | loss: 0.584651
iter: 21982 | loss: 0.584458
iter: 21983 | loss: 0.584265
iter: 21984 | loss: 0.584071
iter: 21985 | loss: 0.583878
iter: 21986 | loss: 0.583684
iter: 21987 | loss: 0.583491
iter: 21988 | loss: 0.583298
iter: 21989 | loss: 0.583104
iter: 21990 | loss: 0.582911
iter: 21991 | loss: 0.582718
iter: 21992 | loss: 0.582524
iter: 21993 | loss: 0.582331
iter: 21994 | loss: 0.582137
iter: 21995 | loss: 0.581944
iter: 21996 | loss: 0.581751
iter: 21997 | loss: 0.581557
iter: 21998 | loss: 0.581364
iter: 21999 | loss: 0.581170
iter: 22000 | loss: 0.580977
iter: 22001 | loss: 0.580784
iter: 22002 | loss: 0.580590
iter: 22003 | loss: 0.580397
iter: 22004 | loss: 0.580204
iter: 22005 | loss: 0.580010
iter: 22006 | loss: 0.579817
iter: 22007 | loss: 0.579623
iter: 22008 | loss: 0.579430
iter: 22009 | loss: 0.579237
iter: 22010 | loss: 0.579043
iter: 22011 | loss: 0.578850
iter: 22012 | loss: 0.578656
iter: 22013 | loss: 0.578463
iter: 22014 | loss: 0.578270
iter: 22015 | loss: 0.578076
iter: 22016 | loss: 0.577883
iter: 22017 | loss: 0.577689
iter: 22018 | loss: 0.577496
iter: 22019 | loss: 0.577303
iter: 22020 | loss: 0.577109
iter: 22021 | loss: 0.576916
iter: 22022 | loss: 0.576723
iter: 22023 | loss: 0.576529
iter: 22024 | loss: 0.576336
iter: 22025 | loss: 0.576142
iter: 22026 | loss: 0.575949
iter: 22027 | loss: 0.575756
iter: 22028 | loss: 0.575562
iter: 22029 | loss: 0.575369
iter: 22030 | loss: 0.575175
iter: 22031 | loss: 0.574982
iter: 22032 | loss: 0.574789
iter: 22033 | loss: 0.574595
iter: 22034 | loss: 0.574402
iter: 22035 | loss: 0.574209
iter: 22036 | loss: 0.574015
iter: 22037 | loss: 0.573822
iter: 22038 | loss: 0.573628
iter: 22039 | loss: 0.573435
iter: 22040 | loss: 0.573242
iter: 22041 | loss: 0.573048
iter: 22042 | loss: 0.572855
iter: 22043 | loss: 0.572661
iter: 22044 | loss: 0.572468
iter: 22045 | loss: 0.572275
iter: 22046 | loss: 0.572081
iter: 22047 | loss: 0.571888
iter: 22048 | loss: 0.571694
iter: 22049 | loss: 0.571501
iter: 22050 | loss: 0.571308
iter: 22051 | loss: 0.571114
iter: 22052 | loss: 0.570921
iter: 22053 | loss: 0.570728
iter: 22054 | loss: 0.570534
iter: 22055 | loss: 0.570341
iter: 22056 | loss: 0.570147
iter: 22057 | loss: 0.569954
iter: 22058 | loss: 0.569761
iter: 22059 | loss: 0.569567
iter: 22060 | loss: 0.569374
iter: 22061 | loss: 0.569180
iter: 22062 | loss: 0.568987
iter: 22063 | loss: 0.568794
iter: 22064 | loss: 0.568600
iter: 22065 | loss: 0.568407
iter: 22066 | loss: 0.568214
iter: 22067 | loss: 0.568020
iter: 22068 | loss: 0.567827
iter: 22069 | loss: 0.567633
iter: 22070 | loss: 0.567440
iter: 22071 | loss: 0.567247
iter: 22072 | loss: 0.567053
iter: 22073 | loss: 0.566860
iter: 22074 | loss: 0.566666
iter: 22075 | loss: 0.566473
iter: 22076 | loss: 0.566280
iter: 22077 | loss: 0.566086
iter: 22078 | loss: 0.565893
iter: 22079 | loss: 0.565699
iter: 22080 | loss: 0.565506
iter: 22081 | loss: 0.565313
iter: 22082 | loss: 0.565119
iter: 22083 | loss: 0.564926
iter: 22084 | loss: 0.564733
iter: 22085 | loss: 0.564539
iter: 22086 | loss: 0.564346
iter: 22087 | loss: 0.564152
iter: 22088 | loss: 0.563959
iter: 22089 | loss: 0.563766
iter: 22090 | loss: 0.563572
iter: 22091 | loss: 0.563379
iter: 22092 | loss: 0.563185
iter: 22093 | loss: 0.562992
iter: 22094 | loss: 0.562799
iter: 22095 | loss: 0.562605
iter: 22096 | loss: 0.562412
iter: 22097 | loss: 0.562219
iter: 22098 | loss: 0.562025
iter: 22099 | loss: 0.561832
iter: 22100 | loss: 0.561638
iter: 22101 | loss: 0.561445
iter: 22102 | loss: 0.561252
iter: 22103 | loss: 0.561058
iter: 22104 | loss: 0.560865
iter: 22105 | loss: 0.560671
iter: 22106 | loss: 0.560478
iter: 22107 | loss: 0.560285
iter: 22108 | loss: 0.560091
iter: 22109 | loss: 0.559898
iter: 22110 | loss: 0.559704
iter: 22111 | loss: 0.559511
iter: 22112 | loss: 0.559318
iter: 22113 | loss: 0.559124
iter: 22114 | loss: 0.558931
iter: 22115 | loss: 0.558738
iter: 22116 | loss: 0.558544
iter: 22117 | loss: 0.558351
iter: 22118 | loss: 0.558157
iter: 22119 | loss: 0.557964
iter: 22120 | loss: 0.557771
iter: 22121 | loss: 0.557577
iter: 22122 | loss: 0.557384
iter: 22123 | loss: 0.557190
iter: 22124 | loss: 0.556997
iter: 22125 | loss: 0.556804
iter: 22126 | loss: 0.556610
iter: 22127 | loss: 0.556417
iter: 22128 | loss: 0.556224
iter: 22129 | loss: 0.556030
iter: 22130 | loss: 0.555837
iter: 22131 | loss: 0.555643
iter: 22132 | loss: 0.555450
iter: 22133 | loss: 0.555257
iter: 22134 | loss: 0.555063
iter: 22135 | loss: 0.554870
iter: 22136 | loss: 0.554676
iter: 22137 | loss: 0.554483
iter: 22138 | loss: 0.554290
iter: 22139 | loss: 0.554096
iter: 22140 | loss: 0.553903
iter: 22141 | loss: 0.553709
iter: 22142 | loss: 0.553516
iter: 22143 | loss: 0.553323
iter: 22144 | loss: 0.553129
iter: 22145 | loss: 0.552936
iter: 22146 | loss: 0.552743
iter: 22147 | loss: 0.552549
iter: 22148 | loss: 0.552356
iter: 22149 | loss: 0.552162
iter: 22150 | loss: 0.551969
iter: 22151 | loss: 0.551776
iter: 22152 | loss: 0.551582
iter: 22153 | loss: 0.551389
iter: 22154 | loss: 0.551195
iter: 22155 | loss: 0.551002
iter: 22156 | loss: 0.550809
iter: 22157 | loss: 0.550615
iter: 22158 | loss: 0.550422
iter: 22159 | loss: 0.550229
iter: 22160 | loss: 0.550035
iter: 22161 | loss: 0.549842
iter: 22162 | loss: 0.549648
iter: 22163 | loss: 0.549455
iter: 22164 | loss: 0.549262
iter: 22165 | loss: 0.549068
iter: 22166 | loss: 0.548875
iter: 22167 | loss: 0.548681
iter: 22168 | loss: 0.548488
iter: 22169 | loss: 0.548295
iter: 22170 | loss: 0.548101
iter: 22171 | loss: 0.547908
iter: 22172 | loss: 0.547714
iter: 22173 | loss: 0.547521
iter: 22174 | loss: 0.547328
iter: 22175 | loss: 0.547134
iter: 22176 | loss: 0.546941
iter: 22177 | loss: 0.546748
iter: 22178 | loss: 0.546554
iter: 22179 | loss: 0.546361
iter: 22180 | loss: 0.546167
iter: 22181 | loss: 0.545974
iter: 22182 | loss: 0.545781
iter: 22183 | loss: 0.545587
iter: 22184 | loss: 0.545394
iter: 22185 | loss: 0.545200
iter: 22186 | loss: 0.545007
iter: 22187 | loss: 0.544814
iter: 22188 | loss: 0.544620
iter: 22189 | loss: 0.544427
iter: 22190 | loss: 0.544234
iter: 22191 | loss: 0.544040
iter: 22192 | loss: 0.543847
iter: 22193 | loss: 0.543653
iter: 22194 | loss: 0.543460
iter: 22195 | loss: 0.543267
iter: 22196 | loss: 0.543073
iter: 22197 | loss: 0.542880
iter: 22198 | loss: 0.542686
iter: 22199 | loss: 0.542493
iter: 22200 | loss: 0.542300
iter: 22201 | loss: 0.542106
iter: 22202 | loss: 0.541913
iter: 22203 | loss: 0.541719
iter: 22204 | loss: 0.541526
iter: 22205 | loss: 0.541333
iter: 22206 | loss: 0.541139
iter: 22207 | loss: 0.540946
iter: 22208 | loss: 0.540753
iter: 22209 | loss: 0.540559
iter: 22210 | loss: 0.540366
iter: 22211 | loss: 0.540172
iter: 22212 | loss: 0.539979
iter: 22213 | loss: 0.539786
iter: 22214 | loss: 0.539592
iter: 22215 | loss: 0.539399
iter: 22216 | loss: 0.539205
iter: 22217 | loss: 0.539012
iter: 22218 | loss: 0.538819
iter: 22219 | loss: 0.538625
iter: 22220 | loss: 0.538432
iter: 22221 | loss: 0.538239
iter: 22222 | loss: 0.538045
iter: 22223 | loss: 0.537852
iter: 22224 | loss: 0.537658
iter: 22225 | loss: 0.537465
iter: 22226 | loss: 0.537272
iter: 22227 | loss: 0.537078
iter: 22228 | loss: 0.536885
iter: 22229 | loss: 0.536691
iter: 22230 | loss: 0.536498
iter: 22231 | loss: 0.536305
iter: 22232 | loss: 0.536111
iter: 22233 | loss: 0.535918
iter: 22234 | loss: 0.535725
iter: 22235 | loss: 0.535531
iter: 22236 | loss: 0.535338
iter: 22237 | loss: 0.535144
iter: 22238 | loss: 0.534951
iter: 22239 | loss: 0.534758
iter: 22240 | loss: 0.534564
iter: 22241 | loss: 0.534371
iter: 22242 | loss: 0.534177
iter: 22243 | loss: 0.533984
iter: 22244 | loss: 0.533791
iter: 22245 | loss: 0.533597
iter: 22246 | loss: 0.533404
iter: 22247 | loss: 0.533210
iter: 22248 | loss: 0.533017
iter: 22249 | loss: 0.532824
iter: 22250 | loss: 0.532630
iter: 22251 | loss: 0.532437
iter: 22252 | loss: 0.532244
iter: 22253 | loss: 0.532050
iter: 22254 | loss: 0.531857
iter: 22255 | loss: 0.531663
iter: 22256 | loss: 0.531470
iter: 22257 | loss: 0.531277
iter: 22258 | loss: 0.531083
iter: 22259 | loss: 0.530890
iter: 22260 | loss: 0.530696
iter: 22261 | loss: 0.530503
iter: 22262 | loss: 0.530310
iter: 22263 | loss: 0.530116
iter: 22264 | loss: 0.529923
iter: 22265 | loss: 0.529730
iter: 22266 | loss: 0.529536
iter: 22267 | loss: 0.529343
iter: 22268 | loss: 0.529149
iter: 22269 | loss: 0.528956
iter: 22270 | loss: 0.528763
iter: 22271 | loss: 0.528569
iter: 22272 | loss: 0.528376
iter: 22273 | loss: 0.528182
iter: 22274 | loss: 0.527989
iter: 22275 | loss: 0.527796
iter: 22276 | loss: 0.527602
iter: 22277 | loss: 0.527409
iter: 22278 | loss: 0.527215
iter: 22279 | loss: 0.527022
iter: 22280 | loss: 0.526829
iter: 22281 | loss: 0.526635
iter: 22282 | loss: 0.526442
iter: 22283 | loss: 0.526249
iter: 22284 | loss: 0.526055
iter: 22285 | loss: 0.525862
iter: 22286 | loss: 0.525668
iter: 22287 | loss: 0.525475
iter: 22288 | loss: 0.525282
iter: 22289 | loss: 0.525088
iter: 22290 | loss: 0.524895
iter: 22291 | loss: 0.524701
iter: 22292 | loss: 0.524508
iter: 22293 | loss: 0.524315
iter: 22294 | loss: 0.524121
iter: 22295 | loss: 0.523928
iter: 22296 | loss: 0.523735
iter: 22297 | loss: 0.523541
iter: 22298 | loss: 0.523348
iter: 22299 | loss: 0.523154
iter: 22300 | loss: 0.522961
iter: 22301 | loss: 0.522768
iter: 22302 | loss: 0.522574
iter: 22303 | loss: 0.522381
iter: 22304 | loss: 0.522187
iter: 22305 | loss: 0.521994
iter: 22306 | loss: 0.521801
iter: 22307 | loss: 0.521607
iter: 22308 | loss: 0.521414
iter: 22309 | loss: 0.521220
iter: 22310 | loss: 0.521027
iter: 22311 | loss: 0.520834
iter: 22312 | loss: 0.520640
iter: 22313 | loss: 0.520447
iter: 22314 | loss: 0.520254
iter: 22315 | loss: 0.520060
iter: 22316 | loss: 0.519867
iter: 22317 | loss: 0.519673
iter: 22318 | loss: 0.519480
iter: 22319 | loss: 0.519287
iter: 22320 | loss: 0.519093
iter: 22321 | loss: 0.518900
iter: 22322 | loss: 0.518706
iter: 22323 | loss: 0.518513
iter: 22324 | loss: 0.518320
iter: 22325 | loss: 0.518126
iter: 22326 | loss: 0.517933
iter: 22327 | loss: 0.517740
iter: 22328 | loss: 0.517546
iter: 22329 | loss: 0.517353
iter: 22330 | loss: 0.517159
iter: 22331 | loss: 0.516966
iter: 22332 | loss: 0.516773
iter: 22333 | loss: 0.516579
iter: 22334 | loss: 0.516386
iter: 22335 | loss: 0.516192
iter: 22336 | loss: 0.515999
iter: 22337 | loss: 0.515806
iter: 22338 | loss: 0.515612
iter: 22339 | loss: 0.515419
iter: 22340 | loss: 0.515225
iter: 22341 | loss: 0.515032
iter: 22342 | loss: 0.514839
iter: 22343 | loss: 0.514645
iter: 22344 | loss: 0.514452
iter: 22345 | loss: 0.514259
iter: 22346 | loss: 0.514065
iter: 22347 | loss: 0.513872
iter: 22348 | loss: 0.513678
iter: 22349 | loss: 0.513485
iter: 22350 | loss: 0.513292
iter: 22351 | loss: 0.513098
iter: 22352 | loss: 0.512905
iter: 22353 | loss: 0.512711
iter: 22354 | loss: 0.512518
iter: 22355 | loss: 0.512325
iter: 22356 | loss: 0.512131
iter: 22357 | loss: 0.511938
iter: 22358 | loss: 0.511745
iter: 22359 | loss: 0.511551
iter: 22360 | loss: 0.511358
iter: 22361 | loss: 0.511164
iter: 22362 | loss: 0.510971
iter: 22363 | loss: 0.510778
iter: 22364 | loss: 0.510584
iter: 22365 | loss: 0.510391
iter: 22366 | loss: 0.510197
iter: 22367 | loss: 0.510004
iter: 22368 | loss: 0.509811
iter: 22369 | loss: 0.509617
iter: 22370 | loss: 0.509424
iter: 22371 | loss: 0.509230
iter: 22372 | loss: 0.509037
iter: 22373 | loss: 0.508844
iter: 22374 | loss: 0.508650
iter: 22375 | loss: 0.508457
iter: 22376 | loss: 0.508264
iter: 22377 | loss: 0.508070
iter: 22378 | loss: 0.507877
iter: 22379 | loss: 0.507683
iter: 22380 | loss: 0.507490
iter: 22381 | loss: 0.507297
iter: 22382 | loss: 0.507103
iter: 22383 | loss: 0.506910
iter: 22384 | loss: 0.506716
iter: 22385 | loss: 0.506523
iter: 22386 | loss: 0.506330
iter: 22387 | loss: 0.506136
iter: 22388 | loss: 0.505943
iter: 22389 | loss: 0.505750
iter: 22390 | loss: 0.505556
iter: 22391 | loss: 0.505363
iter: 22392 | loss: 0.505169
iter: 22393 | loss: 0.504976
iter: 22394 | loss: 0.504783
iter: 22395 | loss: 0.504589
iter: 22396 | loss: 0.504396
iter: 22397 | loss: 0.504202
iter: 22398 | loss: 0.504009
iter: 22399 | loss: 0.503816
iter: 22400 | loss: 0.503622
iter: 22401 | loss: 0.503429
iter: 22402 | loss: 0.503235
iter: 22403 | loss: 0.503042
iter: 22404 | loss: 0.502849
iter: 22405 | loss: 0.502655
iter: 22406 | loss: 0.502462
iter: 22407 | loss: 0.502269
iter: 22408 | loss: 0.502075
iter: 22409 | loss: 0.501882
iter: 22410 | loss: 0.501688
iter: 22411 | loss: 0.501495
iter: 22412 | loss: 0.501302
iter: 22413 | loss: 0.501108
iter: 22414 | loss: 0.500915
iter: 22415 | loss: 0.500721
iter: 22416 | loss: 0.500528
iter: 22417 | loss: 0.500335
iter: 22418 | loss: 0.500141
iter: 22419 | loss: 0.499948
iter: 22420 | loss: 0.499755
iter: 22421 | loss: 0.499561
iter: 22422 | loss: 0.499368
iter: 22423 | loss: 0.499174
iter: 22424 | loss: 0.498981
iter: 22425 | loss: 0.498788
iter: 22426 | loss: 0.498594
iter: 22427 | loss: 0.498401
iter: 22428 | loss: 0.498207
iter: 22429 | loss: 0.498014
iter: 22430 | loss: 0.497821
iter: 22431 | loss: 0.497627
iter: 22432 | loss: 0.497434
iter: 22433 | loss: 0.497240
iter: 22434 | loss: 0.497047
iter: 22435 | loss: 0.496854
iter: 22436 | loss: 0.496660
iter: 22437 | loss: 0.496467
iter: 22438 | loss: 0.496274
iter: 22439 | loss: 0.496080
iter: 22440 | loss: 0.495887
iter: 22441 | loss: 0.495693
iter: 22442 | loss: 0.495500
iter: 22443 | loss: 0.495307
iter: 22444 | loss: 0.495113
iter: 22445 | loss: 0.494920
iter: 22446 | loss: 0.494726
iter: 22447 | loss: 0.494533
iter: 22448 | loss: 0.494340
iter: 22449 | loss: 0.494146
iter: 22450 | loss: 0.493953
iter: 22451 | loss: 0.493760
iter: 22452 | loss: 0.493566
iter: 22453 | loss: 0.493373
iter: 22454 | loss: 0.493179
iter: 22455 | loss: 0.492986
iter: 22456 | loss: 0.492793
iter: 22457 | loss: 0.492599
iter: 22458 | loss: 0.492406
iter: 22459 | loss: 0.492212
iter: 22460 | loss: 0.492019
iter: 22461 | loss: 0.491826
iter: 22462 | loss: 0.491632
iter: 22463 | loss: 0.491439
iter: 22464 | loss: 0.491245
iter: 22465 | loss: 0.491052
iter: 22466 | loss: 0.490859
iter: 22467 | loss: 0.490665
iter: 22468 | loss: 0.490472
iter: 22469 | loss: 0.490279
iter: 22470 | loss: 0.490085
iter: 22471 | loss: 0.489892
iter: 22472 | loss: 0.489698
iter: 22473 | loss: 0.489505
iter: 22474 | loss: 0.489312
iter: 22475 | loss: 0.489118
iter: 22476 | loss: 0.488925
iter: 22477 | loss: 0.488731
iter: 22478 | loss: 0.488538
iter: 22479 | loss: 0.488345
iter: 22480 | loss: 0.488151
iter: 22481 | loss: 0.487958
iter: 22482 | loss: 0.487765
iter: 22483 | loss: 0.487571
iter: 22484 | loss: 0.487378
iter: 22485 | loss: 0.487184
iter: 22486 | loss: 0.486991
iter: 22487 | loss: 0.486798
iter: 22488 | loss: 0.486604
iter: 22489 | loss: 0.486411
iter: 22490 | loss: 0.486217
iter: 22491 | loss: 0.486024
iter: 22492 | loss: 0.485831
iter: 22493 | loss: 0.485637
iter: 22494 | loss: 0.485444
iter: 22495 | loss: 0.485250
iter: 22496 | loss: 0.485057
iter: 22497 | loss: 0.484864
iter: 22498 | loss: 0.484670
iter: 22499 | loss: 0.484477
iter: 22500 | loss: 0.484284
iter: 22501 | loss: 0.484090
iter: 22502 | loss: 0.483897
iter: 22503 | loss: 0.483703
iter: 22504 | loss: 0.483510
iter: 22505 | loss: 0.483317
iter: 22506 | loss: 0.483123
iter: 22507 | loss: 0.482930
iter: 22508 | loss: 0.482736
iter: 22509 | loss: 0.482543
iter: 22510 | loss: 0.482350
iter: 22511 | loss: 0.482156
iter: 22512 | loss: 0.481963
iter: 22513 | loss: 0.481770
iter: 22514 | loss: 0.481576
iter: 22515 | loss: 0.481383
iter: 22516 | loss: 0.481189
iter: 22517 | loss: 0.480996
iter: 22518 | loss: 0.480803
iter: 22519 | loss: 0.480609
iter: 22520 | loss: 0.480416
iter: 22521 | loss: 0.480222
iter: 22522 | loss: 0.480029
iter: 22523 | loss: 0.479836
iter: 22524 | loss: 0.479642
iter: 22525 | loss: 0.479449
iter: 22526 | loss: 0.479255
iter: 22527 | loss: 0.479062
iter: 22528 | loss: 0.478869
iter: 22529 | loss: 0.478675
iter: 22530 | loss: 0.478482
iter: 22531 | loss: 0.478289
iter: 22532 | loss: 0.478095
iter: 22533 | loss: 0.477902
iter: 22534 | loss: 0.477708
iter: 22535 | loss: 0.477515
iter: 22536 | loss: 0.477322
iter: 22537 | loss: 0.477128
iter: 22538 | loss: 0.476935
iter: 22539 | loss: 0.476741
iter: 22540 | loss: 0.476548
iter: 22541 | loss: 0.476355
iter: 22542 | loss: 0.476161
iter: 22543 | loss: 0.475968
iter: 22544 | loss: 0.475775
iter: 22545 | loss: 0.475581
iter: 22546 | loss: 0.475388
iter: 22547 | loss: 0.475194
iter: 22548 | loss: 0.475001
iter: 22549 | loss: 0.474808
iter: 22550 | loss: 0.474614
iter: 22551 | loss: 0.474421
iter: 22552 | loss: 0.474227
iter: 22553 | loss: 0.474034
iter: 22554 | loss: 0.473841
iter: 22555 | loss: 0.473647
iter: 22556 | loss: 0.473454
iter: 22557 | loss: 0.473261
iter: 22558 | loss: 0.473067
iter: 22559 | loss: 0.472874
iter: 22560 | loss: 0.472680
iter: 22561 | loss: 0.472487
iter: 22562 | loss: 0.472294
iter: 22563 | loss: 0.472100
iter: 22564 | loss: 0.471907
iter: 22565 | loss: 0.471713
iter: 22566 | loss: 0.471520
iter: 22567 | loss: 0.471327
iter: 22568 | loss: 0.471133
iter: 22569 | loss: 0.470940
iter: 22570 | loss: 0.470746
iter: 22571 | loss: 0.470553
iter: 22572 | loss: 0.470360
iter: 22573 | loss: 0.470166
iter: 22574 | loss: 0.469973
iter: 22575 | loss: 0.469780
iter: 22576 | loss: 0.469586
iter: 22577 | loss: 0.469393
iter: 22578 | loss: 0.469199
iter: 22579 | loss: 0.469006
iter: 22580 | loss: 0.468813
iter: 22581 | loss: 0.468619
iter: 22582 | loss: 0.468426
iter: 22583 | loss: 0.468232
iter: 22584 | loss: 0.468039
iter: 22585 | loss: 0.467846
iter: 22586 | loss: 0.467652
iter: 22587 | loss: 0.467459
iter: 22588 | loss: 0.467266
iter: 22589 | loss: 0.467072
iter: 22590 | loss: 0.466879
iter: 22591 | loss: 0.466685
iter: 22592 | loss: 0.466492
iter: 22593 | loss: 0.466299
iter: 22594 | loss: 0.466105
iter: 22595 | loss: 0.465912
iter: 22596 | loss: 0.465718
iter: 22597 | loss: 0.465525
iter: 22598 | loss: 0.465332
iter: 22599 | loss: 0.465138
iter: 22600 | loss: 0.464945
iter: 22601 | loss: 0.464751
iter: 22602 | loss: 0.464558
iter: 22603 | loss: 0.464365
iter: 22604 | loss: 0.464171
iter: 22605 | loss: 0.463978
iter: 22606 | loss: 0.463785
iter: 22607 | loss: 0.463591
iter: 22608 | loss: 0.463398
iter: 22609 | loss: 0.463204
iter: 22610 | loss: 0.463011
iter: 22611 | loss: 0.462818
iter: 22612 | loss: 0.462624
iter: 22613 | loss: 0.462431
iter: 22614 | loss: 0.462237
iter: 22615 | loss: 0.462044
iter: 22616 | loss: 0.461851
iter: 22617 | loss: 0.461657
iter: 22618 | loss: 0.461464
iter: 22619 | loss: 0.461271
iter: 22620 | loss: 0.461077
iter: 22621 | loss: 0.460884
iter: 22622 | loss: 0.460690
iter: 22623 | loss: 0.460497
iter: 22624 | loss: 0.460304
iter: 22625 | loss: 0.460110
iter: 22626 | loss: 0.459917
iter: 22627 | loss: 0.459723
iter: 22628 | loss: 0.459530
iter: 22629 | loss: 0.459337
iter: 22630 | loss: 0.459143
iter: 22631 | loss: 0.458950
iter: 22632 | loss: 0.458756
iter: 22633 | loss: 0.458563
iter: 22634 | loss: 0.458370
iter: 22635 | loss: 0.458176
iter: 22636 | loss: 0.457983
iter: 22637 | loss: 0.457790
iter: 22638 | loss: 0.457596
iter: 22639 | loss: 0.457403
iter: 22640 | loss: 0.457209
iter: 22641 | loss: 0.457016
iter: 22642 | loss: 0.456823
iter: 22643 | loss: 0.456629
iter: 22644 | loss: 0.456436
iter: 22645 | loss: 0.456242
iter: 22646 | loss: 0.456049
iter: 22647 | loss: 0.455856
iter: 22648 | loss: 0.455662
iter: 22649 | loss: 0.455469
iter: 22650 | loss: 0.455276
iter: 22651 | loss: 0.455082
iter: 22652 | loss: 0.454889
iter: 22653 | loss: 0.454695
iter: 22654 | loss: 0.454502
iter: 22655 | loss: 0.454309
iter: 22656 | loss: 0.454115
iter: 22657 | loss: 0.453922
iter: 22658 | loss: 0.453728
iter: 22659 | loss: 0.453535
iter: 22660 | loss: 0.453342
iter: 22661 | loss: 0.453148
iter: 22662 | loss: 0.452955
iter: 22663 | loss: 0.452761
iter: 22664 | loss: 0.452568
iter: 22665 | loss: 0.452375
iter: 22666 | loss: 0.452181
iter: 22667 | loss: 0.451988
iter: 22668 | loss: 0.451795
iter: 22669 | loss: 0.451601
iter: 22670 | loss: 0.451408
iter: 22671 | loss: 0.451214
iter: 22672 | loss: 0.451021
iter: 22673 | loss: 0.450828
iter: 22674 | loss: 0.450634
iter: 22675 | loss: 0.450441
iter: 22676 | loss: 0.450247
iter: 22677 | loss: 0.450054
iter: 22678 | loss: 0.449861
iter: 22679 | loss: 0.449667
iter: 22680 | loss: 0.449474
iter: 22681 | loss: 0.449281
iter: 22682 | loss: 0.449087
iter: 22683 | loss: 0.448894
iter: 22684 | loss: 0.448700
iter: 22685 | loss: 0.448507
iter: 22686 | loss: 0.448314
iter: 22687 | loss: 0.448120
iter: 22688 | loss: 0.447927
iter: 22689 | loss: 0.447733
iter: 22690 | loss: 0.447540
iter: 22691 | loss: 0.447347
iter: 22692 | loss: 0.447153
iter: 22693 | loss: 0.446960
iter: 22694 | loss: 0.446766
iter: 22695 | loss: 0.446573
iter: 22696 | loss: 0.446380
iter: 22697 | loss: 0.446186
iter: 22698 | loss: 0.445993
iter: 22699 | loss: 0.445800
iter: 22700 | loss: 0.445606
iter: 22701 | loss: 0.445413
iter: 22702 | loss: 0.445219
iter: 22703 | loss: 0.445026
iter: 22704 | loss: 0.444833
iter: 22705 | loss: 0.444639
iter: 22706 | loss: 0.444446
iter: 22707 | loss: 0.444252
iter: 22708 | loss: 0.444059
iter: 22709 | loss: 0.443866
iter: 22710 | loss: 0.443672
iter: 22711 | loss: 0.443479
iter: 22712 | loss: 0.443286
iter: 22713 | loss: 0.443092
iter: 22714 | loss: 0.442899
iter: 22715 | loss: 0.442705
iter: 22716 | loss: 0.442512
iter: 22717 | loss: 0.442319
iter: 22718 | loss: 0.442125
iter: 22719 | loss: 0.441932
iter: 22720 | loss: 0.441738
iter: 22721 | loss: 0.441545
iter: 22722 | loss: 0.441352
iter: 22723 | loss: 0.441158
iter: 22724 | loss: 0.440965
iter: 22725 | loss: 0.440771
iter: 22726 | loss: 0.440578
iter: 22727 | loss: 0.440385
iter: 22728 | loss: 0.440191
iter: 22729 | loss: 0.439998
iter: 22730 | loss: 0.439805
iter: 22731 | loss: 0.439611
iter: 22732 | loss: 0.439418
iter: 22733 | loss: 0.439224
iter: 22734 | loss: 0.439031
iter: 22735 | loss: 0.438838
iter: 22736 | loss: 0.438644
iter: 22737 | loss: 0.438451
iter: 22738 | loss: 0.438257
iter: 22739 | loss: 0.438064
iter: 22740 | loss: 0.437871
iter: 22741 | loss: 0.437677
iter: 22742 | loss: 0.437484
iter: 22743 | loss: 0.437291
iter: 22744 | loss: 0.437097
iter: 22745 | loss: 0.436904
iter: 22746 | loss: 0.436710
iter: 22747 | loss: 0.436517
iter: 22748 | loss: 0.436324
iter: 22749 | loss: 0.436130
iter: 22750 | loss: 0.435937
iter: 22751 | loss: 0.435743
iter: 22752 | loss: 0.435550
iter: 22753 | loss: 0.435357
iter: 22754 | loss: 0.435163
iter: 22755 | loss: 0.434970
iter: 22756 | loss: 0.434776
iter: 22757 | loss: 0.434583
iter: 22758 | loss: 0.434390
iter: 22759 | loss: 0.434196
iter: 22760 | loss: 0.434003
iter: 22761 | loss: 0.433810
iter: 22762 | loss: 0.433616
iter: 22763 | loss: 0.433423
iter: 22764 | loss: 0.433229
iter: 22765 | loss: 0.433036
iter: 22766 | loss: 0.432843
iter: 22767 | loss: 0.432649
iter: 22768 | loss: 0.432456
iter: 22769 | loss: 0.432262
iter: 22770 | loss: 0.432069
iter: 22771 | loss: 0.431876
iter: 22772 | loss: 0.431682
iter: 22773 | loss: 0.431489
iter: 22774 | loss: 0.431296
iter: 22775 | loss: 0.431102
iter: 22776 | loss: 0.430909
iter: 22777 | loss: 0.430715
iter: 22778 | loss: 0.430522
iter: 22779 | loss: 0.430329
iter: 22780 | loss: 0.430135
iter: 22781 | loss: 0.429942
iter: 22782 | loss: 0.429748
iter: 22783 | loss: 0.429555
iter: 22784 | loss: 0.429362
iter: 22785 | loss: 0.429168
iter: 22786 | loss: 0.428975
iter: 22787 | loss: 0.428781
iter: 22788 | loss: 0.428588
iter: 22789 | loss: 0.428395
iter: 22790 | loss: 0.428201
iter: 22791 | loss: 0.428008
iter: 22792 | loss: 0.427815
iter: 22793 | loss: 0.427621
iter: 22794 | loss: 0.427428
iter: 22795 | loss: 0.427234
iter: 22796 | loss: 0.427041
iter: 22797 | loss: 0.426848
iter: 22798 | loss: 0.426654
iter: 22799 | loss: 0.426461
iter: 22800 | loss: 0.426267
iter: 22801 | loss: 0.426074
iter: 22802 | loss: 0.425881
iter: 22803 | loss: 0.425687
iter: 22804 | loss: 0.425494
iter: 22805 | loss: 0.425301
iter: 22806 | loss: 0.425107
iter: 22807 | loss: 0.424914
iter: 22808 | loss: 0.424720
iter: 22809 | loss: 0.424527
iter: 22810 | loss: 0.424334
iter: 22811 | loss: 0.424140
iter: 22812 | loss: 0.423947
iter: 22813 | loss: 0.423753
iter: 22814 | loss: 0.423560
iter: 22815 | loss: 0.423367
iter: 22816 | loss: 0.423173
iter: 22817 | loss: 0.422980
iter: 22818 | loss: 0.422786
iter: 22819 | loss: 0.422593
iter: 22820 | loss: 0.422400
iter: 22821 | loss: 0.422206
iter: 22822 | loss: 0.422013
iter: 22823 | loss: 0.421820
iter: 22824 | loss: 0.421626
iter: 22825 | loss: 0.421433
iter: 22826 | loss: 0.421239
iter: 22827 | loss: 0.421046
iter: 22828 | loss: 0.420853
iter: 22829 | loss: 0.420659
iter: 22830 | loss: 0.420466
iter: 22831 | loss: 0.420272
iter: 22832 | loss: 0.420079
iter: 22833 | loss: 0.419886
iter: 22834 | loss: 0.419692
iter: 22835 | loss: 0.419499
iter: 22836 | loss: 0.419306
iter: 22837 | loss: 0.419112
iter: 22838 | loss: 0.418919
iter: 22839 | loss: 0.418725
iter: 22840 | loss: 0.418532
iter: 22841 | loss: 0.418339
iter: 22842 | loss: 0.418145
iter: 22843 | loss: 0.417952
iter: 22844 | loss: 0.417758
iter: 22845 | loss: 0.417565
iter: 22846 | loss: 0.417372
iter: 22847 | loss: 0.417178
iter: 22848 | loss: 0.416985
iter: 22849 | loss: 0.416791
iter: 22850 | loss: 0.416598
iter: 22851 | loss: 0.416405
iter: 22852 | loss: 0.416211
iter: 22853 | loss: 0.416018
iter: 22854 | loss: 0.415825
iter: 22855 | loss: 0.415631
iter: 22856 | loss: 0.415438
iter: 22857 | loss: 0.415244
iter: 22858 | loss: 0.415051
iter: 22859 | loss: 0.414858
iter: 22860 | loss: 0.414664
iter: 22861 | loss: 0.414471
iter: 22862 | loss: 0.414277
iter: 22863 | loss: 0.414084
iter: 22864 | loss: 0.413891
iter: 22865 | loss: 0.413697
iter: 22866 | loss: 0.413504
iter: 22867 | loss: 0.413311
iter: 22868 | loss: 0.413117
iter: 22869 | loss: 0.412924
iter: 22870 | loss: 0.412730
iter: 22871 | loss: 0.412537
iter: 22872 | loss: 0.412344
iter: 22873 | loss: 0.412150
iter: 22874 | loss: 0.411957
iter: 22875 | loss: 0.411763
iter: 22876 | loss: 0.411570
iter: 22877 | loss: 0.411377
iter: 22878 | loss: 0.411183
iter: 22879 | loss: 0.410990
iter: 22880 | loss: 0.410797
iter: 22881 | loss: 0.410603
iter: 22882 | loss: 0.410410
iter: 22883 | loss: 0.410216
iter: 22884 | loss: 0.410023
iter: 22885 | loss: 0.409830
iter: 22886 | loss: 0.409636
iter: 22887 | loss: 0.409443
iter: 22888 | loss: 0.409249
iter: 22889 | loss: 0.409056
iter: 22890 | loss: 0.408863
iter: 22891 | loss: 0.408669
iter: 22892 | loss: 0.408476
iter: 22893 | loss: 0.408282
iter: 22894 | loss: 0.408089
iter: 22895 | loss: 0.407896
iter: 22896 | loss: 0.407702
iter: 22897 | loss: 0.407509
iter: 22898 | loss: 0.407316
iter: 22899 | loss: 0.407122
iter: 22900 | loss: 0.406929
iter: 22901 | loss: 0.406735
iter: 22902 | loss: 0.406542
iter: 22903 | loss: 0.406349
iter: 22904 | loss: 0.406155
iter: 22905 | loss: 0.405962
iter: 22906 | loss: 0.405768
iter: 22907 | loss: 0.405575
iter: 22908 | loss: 0.405382
iter: 22909 | loss: 0.405188
iter: 22910 | loss: 0.404995
iter: 22911 | loss: 0.404802
iter: 22912 | loss: 0.404608
iter: 22913 | loss: 0.404415
iter: 22914 | loss: 0.404221
iter: 22915 | loss: 0.404028
iter: 22916 | loss: 0.403835
iter: 22917 | loss: 0.403641
iter: 22918 | loss: 0.403448
iter: 22919 | loss: 0.403254
iter: 22920 | loss: 0.403061
iter: 22921 | loss: 0.402868
iter: 22922 | loss: 0.402674
iter: 22923 | loss: 0.402481
iter: 22924 | loss: 0.402287
iter: 22925 | loss: 0.402094
iter: 22926 | loss: 0.401901
iter: 22927 | loss: 0.401707
iter: 22928 | loss: 0.401514
iter: 22929 | loss: 0.401321
iter: 22930 | loss: 0.401127
iter: 22931 | loss: 0.400934
iter: 22932 | loss: 0.400740
iter: 22933 | loss: 0.400547
iter: 22934 | loss: 0.400354
iter: 22935 | loss: 0.400160
iter: 22936 | loss: 0.399967
iter: 22937 | loss: 0.399773
iter: 22938 | loss: 0.399580
iter: 22939 | loss: 0.399387
iter: 22940 | loss: 0.399193
iter: 22941 | loss: 0.399000
iter: 22942 | loss: 0.398807
iter: 22943 | loss: 0.398613
iter: 22944 | loss: 0.398420
iter: 22945 | loss: 0.398226
iter: 22946 | loss: 0.398033
iter: 22947 | loss: 0.397840
iter: 22948 | loss: 0.397646
iter: 22949 | loss: 0.397453
iter: 22950 | loss: 0.397259
iter: 22951 | loss: 0.397066
iter: 22952 | loss: 0.396873
iter: 22953 | loss: 0.396679
iter: 22954 | loss: 0.396486
iter: 22955 | loss: 0.396292
iter: 22956 | loss: 0.396099
iter: 22957 | loss: 0.395906
iter: 22958 | loss: 0.395712
iter: 22959 | loss: 0.395519
iter: 22960 | loss: 0.395326
iter: 22961 | loss: 0.395132
iter: 22962 | loss: 0.394939
iter: 22963 | loss: 0.394745
iter: 22964 | loss: 0.394552
iter: 22965 | loss: 0.394359
iter: 22966 | loss: 0.394165
iter: 22967 | loss: 0.393972
iter: 22968 | loss: 0.393778
iter: 22969 | loss: 0.393585
iter: 22970 | loss: 0.393392
iter: 22971 | loss: 0.393198
iter: 22972 | loss: 0.393005
iter: 22973 | loss: 0.392812
iter: 22974 | loss: 0.392618
iter: 22975 | loss: 0.392425
iter: 22976 | loss: 0.392231
iter: 22977 | loss: 0.392038
iter: 22978 | loss: 0.391845
iter: 22979 | loss: 0.391651
iter: 22980 | loss: 0.391458
iter: 22981 | loss: 0.391264
iter: 22982 | loss: 0.391071
iter: 22983 | loss: 0.390878
iter: 22984 | loss: 0.390684
iter: 22985 | loss: 0.390491
iter: 22986 | loss: 0.390297
iter: 22987 | loss: 0.390104
iter: 22988 | loss: 0.389911
iter: 22989 | loss: 0.389717
iter: 22990 | loss: 0.389524
iter: 22991 | loss: 0.389331
iter: 22992 | loss: 0.389137
iter: 22993 | loss: 0.388944
iter: 22994 | loss: 0.388750
iter: 22995 | loss: 0.388557
iter: 22996 | loss: 0.388364
iter: 22997 | loss: 0.388170
iter: 22998 | loss: 0.387977
iter: 22999 | loss: 0.387783
iter: 23000 | loss: 0.387590
iter: 23001 | loss: 0.387397
iter: 23002 | loss: 0.387203
iter: 23003 | loss: 0.387010
iter: 23004 | loss: 0.386817
iter: 23005 | loss: 0.386623
iter: 23006 | loss: 0.386430
iter: 23007 | loss: 0.386236
iter: 23008 | loss: 0.386043
iter: 23009 | loss: 0.385850
iter: 23010 | loss: 0.385656
iter: 23011 | loss: 0.385463
iter: 23012 | loss: 0.385269
iter: 23013 | loss: 0.385076
iter: 23014 | loss: 0.384883
iter: 23015 | loss: 0.384689
iter: 23016 | loss: 0.384496
iter: 23017 | loss: 0.384302
iter: 23018 | loss: 0.384109
iter: 23019 | loss: 0.383916
iter: 23020 | loss: 0.383722
iter: 23021 | loss: 0.383529
iter: 23022 | loss: 0.383336
iter: 23023 | loss: 0.383142
iter: 23024 | loss: 0.382949
iter: 23025 | loss: 0.382755
iter: 23026 | loss: 0.382562
iter: 23027 | loss: 0.382369
iter: 23028 | loss: 0.382175
iter: 23029 | loss: 0.381982
iter: 23030 | loss: 0.381788
iter: 23031 | loss: 0.381595
iter: 23032 | loss: 0.381402
iter: 23033 | loss: 0.381208
iter: 23034 | loss: 0.381015
iter: 23035 | loss: 0.380822
iter: 23036 | loss: 0.380628
iter: 23037 | loss: 0.380435
iter: 23038 | loss: 0.380241
iter: 23039 | loss: 0.380048
iter: 23040 | loss: 0.379855
iter: 23041 | loss: 0.379661
iter: 23042 | loss: 0.379468
iter: 23043 | loss: 0.379274
iter: 23044 | loss: 0.379081
iter: 23045 | loss: 0.378888
iter: 23046 | loss: 0.378694
iter: 23047 | loss: 0.378501
iter: 23048 | loss: 0.378307
iter: 23049 | loss: 0.378114
iter: 23050 | loss: 0.377921
iter: 23051 | loss: 0.377727
iter: 23052 | loss: 0.377534
iter: 23053 | loss: 0.377341
iter: 23054 | loss: 0.377147
iter: 23055 | loss: 0.376954
iter: 23056 | loss: 0.376760
iter: 23057 | loss: 0.376567
iter: 23058 | loss: 0.376374
iter: 23059 | loss: 0.376180
iter: 23060 | loss: 0.375987
iter: 23061 | loss: 0.375793
iter: 23062 | loss: 0.375600
iter: 23063 | loss: 0.375407
iter: 23064 | loss: 0.375213
iter: 23065 | loss: 0.375020
iter: 23066 | loss: 0.374827
iter: 23067 | loss: 0.374633
iter: 23068 | loss: 0.374440
iter: 23069 | loss: 0.374246
iter: 23070 | loss: 0.374053
iter: 23071 | loss: 0.373860
iter: 23072 | loss: 0.373666
iter: 23073 | loss: 0.373473
iter: 23074 | loss: 0.373279
iter: 23075 | loss: 0.373086
iter: 23076 | loss: 0.372893
iter: 23077 | loss: 0.372699
iter: 23078 | loss: 0.372506
iter: 23079 | loss: 0.372312
iter: 23080 | loss: 0.372119
iter: 23081 | loss: 0.371926
iter: 23082 | loss: 0.371732
iter: 23083 | loss: 0.371539
iter: 23084 | loss: 0.371346
iter: 23085 | loss: 0.371152
iter: 23086 | loss: 0.370959
iter: 23087 | loss: 0.370765
iter: 23088 | loss: 0.370572
iter: 23089 | loss: 0.370379
iter: 23090 | loss: 0.370185
iter: 23091 | loss: 0.369992
iter: 23092 | loss: 0.369798
iter: 23093 | loss: 0.369605
iter: 23094 | loss: 0.369412
iter: 23095 | loss: 0.369218
iter: 23096 | loss: 0.369025
iter: 23097 | loss: 0.368832
iter: 23098 | loss: 0.368638
iter: 23099 | loss: 0.368445
iter: 23100 | loss: 0.368251
iter: 23101 | loss: 0.368058
iter: 23102 | loss: 0.367865
iter: 23103 | loss: 0.367671
iter: 23104 | loss: 0.367478
iter: 23105 | loss: 0.367284
iter: 23106 | loss: 0.367091
iter: 23107 | loss: 0.366898
iter: 23108 | loss: 0.366704
iter: 23109 | loss: 0.366511
iter: 23110 | loss: 0.366317
iter: 23111 | loss: 0.366124
iter: 23112 | loss: 0.365931
iter: 23113 | loss: 0.365737
iter: 23114 | loss: 0.365544
iter: 23115 | loss: 0.365351
iter: 23116 | loss: 0.365157
iter: 23117 | loss: 0.364964
iter: 23118 | loss: 0.364770
iter: 23119 | loss: 0.364577
iter: 23120 | loss: 0.364384
iter: 23121 | loss: 0.364190
iter: 23122 | loss: 0.363997
iter: 23123 | loss: 0.363803
iter: 23124 | loss: 0.363610
iter: 23125 | loss: 0.363417
iter: 23126 | loss: 0.363223
iter: 23127 | loss: 0.363030
iter: 23128 | loss: 0.362837
iter: 23129 | loss: 0.362643
iter: 23130 | loss: 0.362450
iter: 23131 | loss: 0.362256
iter: 23132 | loss: 0.362063
iter: 23133 | loss: 0.361870
iter: 23134 | loss: 0.361676
iter: 23135 | loss: 0.361483
iter: 23136 | loss: 0.361289
iter: 23137 | loss: 0.361096
iter: 23138 | loss: 0.360903
iter: 23139 | loss: 0.360709
iter: 23140 | loss: 0.360516
iter: 23141 | loss: 0.360322
iter: 23142 | loss: 0.360129
iter: 23143 | loss: 0.359936
iter: 23144 | loss: 0.359742
iter: 23145 | loss: 0.359549
iter: 23146 | loss: 0.359356
iter: 23147 | loss: 0.359162
iter: 23148 | loss: 0.358969
iter: 23149 | loss: 0.358775
iter: 23150 | loss: 0.358582
iter: 23151 | loss: 0.358389
iter: 23152 | loss: 0.358195
iter: 23153 | loss: 0.358002
iter: 23154 | loss: 0.357808
iter: 23155 | loss: 0.357615
iter: 23156 | loss: 0.357422
iter: 23157 | loss: 0.357228
iter: 23158 | loss: 0.357035
iter: 23159 | loss: 0.356842
iter: 23160 | loss: 0.356648
iter: 23161 | loss: 0.356455
iter: 23162 | loss: 0.356261
iter: 23163 | loss: 0.356068
iter: 23164 | loss: 0.355875
iter: 23165 | loss: 0.355681
iter: 23166 | loss: 0.355488
iter: 23167 | loss: 0.355294
iter: 23168 | loss: 0.355101
iter: 23169 | loss: 0.354908
iter: 23170 | loss: 0.354714
iter: 23171 | loss: 0.354521
iter: 23172 | loss: 0.354327
iter: 23173 | loss: 0.354134
iter: 23174 | loss: 0.353941
iter: 23175 | loss: 0.353747
iter: 23176 | loss: 0.353554
iter: 23177 | loss: 0.353361
iter: 23178 | loss: 0.353167
iter: 23179 | loss: 0.352974
iter: 23180 | loss: 0.352780
iter: 23181 | loss: 0.352587
iter: 23182 | loss: 0.352394
iter: 23183 | loss: 0.352200
iter: 23184 | loss: 0.352007
iter: 23185 | loss: 0.351813
iter: 23186 | loss: 0.351620
iter: 23187 | loss: 0.351427
iter: 23188 | loss: 0.351233
iter: 23189 | loss: 0.351040
iter: 23190 | loss: 0.350847
iter: 23191 | loss: 0.350653
iter: 23192 | loss: 0.350460
iter: 23193 | loss: 0.350266
iter: 23194 | loss: 0.350073
iter: 23195 | loss: 0.349880
iter: 23196 | loss: 0.349686
iter: 23197 | loss: 0.349493
iter: 23198 | loss: 0.349299
iter: 23199 | loss: 0.349106
iter: 23200 | loss: 0.348913
iter: 23201 | loss: 0.348719
iter: 23202 | loss: 0.348526
iter: 23203 | loss: 0.348333
iter: 23204 | loss: 0.348139
iter: 23205 | loss: 0.347946
iter: 23206 | loss: 0.347752
iter: 23207 | loss: 0.347559
iter: 23208 | loss: 0.347366
iter: 23209 | loss: 0.347172
iter: 23210 | loss: 0.346979
iter: 23211 | loss: 0.346785
iter: 23212 | loss: 0.346592
iter: 23213 | loss: 0.346399
iter: 23214 | loss: 0.346205
iter: 23215 | loss: 0.346012
iter: 23216 | loss: 0.345818
iter: 23217 | loss: 0.345625
iter: 23218 | loss: 0.345432
iter: 23219 | loss: 0.345238
iter: 23220 | loss: 0.345045
iter: 23221 | loss: 0.344852
iter: 23222 | loss: 0.344658
iter: 23223 | loss: 0.344465
iter: 23224 | loss: 0.344271
iter: 23225 | loss: 0.344078
iter: 23226 | loss: 0.343885
iter: 23227 | loss: 0.343691
iter: 23228 | loss: 0.343498
iter: 23229 | loss: 0.343304
iter: 23230 | loss: 0.343111
iter: 23231 | loss: 0.342918
iter: 23232 | loss: 0.342724
iter: 23233 | loss: 0.342531
iter: 23234 | loss: 0.342338
iter: 23235 | loss: 0.342144
iter: 23236 | loss: 0.341951
iter: 23237 | loss: 0.341757
iter: 23238 | loss: 0.341564
iter: 23239 | loss: 0.341371
iter: 23240 | loss: 0.341177
iter: 23241 | loss: 0.340984
iter: 23242 | loss: 0.340790
iter: 23243 | loss: 0.340597
iter: 23244 | loss: 0.340404
iter: 23245 | loss: 0.340210
iter: 23246 | loss: 0.340017
iter: 23247 | loss: 0.339823
iter: 23248 | loss: 0.339630
iter: 23249 | loss: 0.339437
iter: 23250 | loss: 0.339243
iter: 23251 | loss: 0.339050
iter: 23252 | loss: 0.338857
iter: 23253 | loss: 0.338663
iter: 23254 | loss: 0.338470
iter: 23255 | loss: 0.338276
iter: 23256 | loss: 0.338083
iter: 23257 | loss: 0.337890
iter: 23258 | loss: 0.337696
iter: 23259 | loss: 0.337503
iter: 23260 | loss: 0.337309
iter: 23261 | loss: 0.337116
iter: 23262 | loss: 0.336923
iter: 23263 | loss: 0.336729
iter: 23264 | loss: 0.336536
iter: 23265 | loss: 0.336343
iter: 23266 | loss: 0.336149
iter: 23267 | loss: 0.335956
iter: 23268 | loss: 0.335762
iter: 23269 | loss: 0.335569
iter: 23270 | loss: 0.335376
iter: 23271 | loss: 0.335182
iter: 23272 | loss: 0.334989
iter: 23273 | loss: 0.334795
iter: 23274 | loss: 0.334602
iter: 23275 | loss: 0.334409
iter: 23276 | loss: 0.334215
iter: 23277 | loss: 0.334022
iter: 23278 | loss: 0.333828
iter: 23279 | loss: 0.333635
iter: 23280 | loss: 0.333442
iter: 23281 | loss: 0.333248
iter: 23282 | loss: 0.333055
iter: 23283 | loss: 0.332862
iter: 23284 | loss: 0.332668
iter: 23285 | loss: 0.332475
iter: 23286 | loss: 0.332281
iter: 23287 | loss: 0.332088
iter: 23288 | loss: 0.331895
iter: 23289 | loss: 0.331701
iter: 23290 | loss: 0.331508
iter: 23291 | loss: 0.331314
iter: 23292 | loss: 0.331121
iter: 23293 | loss: 0.330928
iter: 23294 | loss: 0.330734
iter: 23295 | loss: 0.330541
iter: 23296 | loss: 0.330348
iter: 23297 | loss: 0.330154
iter: 23298 | loss: 0.329961
iter: 23299 | loss: 0.329767
iter: 23300 | loss: 0.329574
iter: 23301 | loss: 0.329381
iter: 23302 | loss: 0.329187
iter: 23303 | loss: 0.328994
iter: 23304 | loss: 0.328800
iter: 23305 | loss: 0.328607
iter: 23306 | loss: 0.328414
iter: 23307 | loss: 0.328220
iter: 23308 | loss: 0.328027
iter: 23309 | loss: 0.327833
iter: 23310 | loss: 0.327640
iter: 23311 | loss: 0.327447
iter: 23312 | loss: 0.327253
iter: 23313 | loss: 0.327060
iter: 23314 | loss: 0.326867
iter: 23315 | loss: 0.326673
iter: 23316 | loss: 0.326480
iter: 23317 | loss: 0.326286
iter: 23318 | loss: 0.326093
iter: 23319 | loss: 0.325900
iter: 23320 | loss: 0.325706
iter: 23321 | loss: 0.325513
iter: 23322 | loss: 0.325319
iter: 23323 | loss: 0.325126
iter: 23324 | loss: 0.324933
iter: 23325 | loss: 0.324739
iter: 23326 | loss: 0.324546
iter: 23327 | loss: 0.324353
iter: 23328 | loss: 0.324159
iter: 23329 | loss: 0.323966
iter: 23330 | loss: 0.323772
iter: 23331 | loss: 0.323579
iter: 23332 | loss: 0.323386
iter: 23333 | loss: 0.323192
iter: 23334 | loss: 0.322999
iter: 23335 | loss: 0.322805
iter: 23336 | loss: 0.322612
iter: 23337 | loss: 0.322419
iter: 23338 | loss: 0.322225
iter: 23339 | loss: 0.322032
iter: 23340 | loss: 0.321838
iter: 23341 | loss: 0.321645
iter: 23342 | loss: 0.321452
iter: 23343 | loss: 0.321258
iter: 23344 | loss: 0.321065
iter: 23345 | loss: 0.320872
iter: 23346 | loss: 0.320678
iter: 23347 | loss: 0.320485
iter: 23348 | loss: 0.320291
iter: 23349 | loss: 0.320098
iter: 23350 | loss: 0.319905
iter: 23351 | loss: 0.319711
iter: 23352 | loss: 0.319518
iter: 23353 | loss: 0.319324
iter: 23354 | loss: 0.319131
iter: 23355 | loss: 0.318938
iter: 23356 | loss: 0.318744
iter: 23357 | loss: 0.318551
iter: 23358 | loss: 0.318358
iter: 23359 | loss: 0.318164
iter: 23360 | loss: 0.317971
iter: 23361 | loss: 0.317777
iter: 23362 | loss: 0.317584
iter: 23363 | loss: 0.317391
iter: 23364 | loss: 0.317197
iter: 23365 | loss: 0.317004
iter: 23366 | loss: 0.316810
iter: 23367 | loss: 0.316617
iter: 23368 | loss: 0.316424
iter: 23369 | loss: 0.316230
iter: 23370 | loss: 0.316037
iter: 23371 | loss: 0.315843
iter: 23372 | loss: 0.315650
iter: 23373 | loss: 0.315457
iter: 23374 | loss: 0.315263
iter: 23375 | loss: 0.315070
iter: 23376 | loss: 0.314877
iter: 23377 | loss: 0.314683
iter: 23378 | loss: 0.314490
iter: 23379 | loss: 0.314296
iter: 23380 | loss: 0.314103
iter: 23381 | loss: 0.313910
iter: 23382 | loss: 0.313716
iter: 23383 | loss: 0.313523
iter: 23384 | loss: 0.313329
iter: 23385 | loss: 0.313136
iter: 23386 | loss: 0.312943
iter: 23387 | loss: 0.312749
iter: 23388 | loss: 0.312556
iter: 23389 | loss: 0.312363
iter: 23390 | loss: 0.312169
iter: 23391 | loss: 0.311976
iter: 23392 | loss: 0.311782
iter: 23393 | loss: 0.311589
iter: 23394 | loss: 0.311396
iter: 23395 | loss: 0.311202
iter: 23396 | loss: 0.311009
iter: 23397 | loss: 0.310815
iter: 23398 | loss: 0.310622
iter: 23399 | loss: 0.310429
iter: 23400 | loss: 0.310235
iter: 23401 | loss: 0.310042
iter: 23402 | loss: 0.309848
iter: 23403 | loss: 0.309655
iter: 23404 | loss: 0.309462
iter: 23405 | loss: 0.309268
iter: 23406 | loss: 0.309075
iter: 23407 | loss: 0.308882
iter: 23408 | loss: 0.308688
iter: 23409 | loss: 0.308495
iter: 23410 | loss: 0.308301
iter: 23411 | loss: 0.308108
iter: 23412 | loss: 0.307915
iter: 23413 | loss: 0.307721
iter: 23414 | loss: 0.307528
iter: 23415 | loss: 0.307334
iter: 23416 | loss: 0.307141
iter: 23417 | loss: 0.306948
iter: 23418 | loss: 0.306754
iter: 23419 | loss: 0.306561
iter: 23420 | loss: 0.306368
iter: 23421 | loss: 0.306174
iter: 23422 | loss: 0.305981
iter: 23423 | loss: 0.305787
iter: 23424 | loss: 0.305594
iter: 23425 | loss: 0.305401
iter: 23426 | loss: 0.305207
iter: 23427 | loss: 0.305014
iter: 23428 | loss: 0.304820
iter: 23429 | loss: 0.304627
iter: 23430 | loss: 0.304434
iter: 23431 | loss: 0.304240
iter: 23432 | loss: 0.304047
iter: 23433 | loss: 0.303853
iter: 23434 | loss: 0.303660
iter: 23435 | loss: 0.303467
iter: 23436 | loss: 0.303273
iter: 23437 | loss: 0.303080
iter: 23438 | loss: 0.302887
iter: 23439 | loss: 0.302693
iter: 23440 | loss: 0.302500
iter: 23441 | loss: 0.302306
iter: 23442 | loss: 0.302113
iter: 23443 | loss: 0.301920
iter: 23444 | loss: 0.301726
iter: 23445 | loss: 0.301533
iter: 23446 | loss: 0.301339
iter: 23447 | loss: 0.301146
iter: 23448 | loss: 0.300953
iter: 23449 | loss: 0.300759
iter: 23450 | loss: 0.300566
iter: 23451 | loss: 0.300373
iter: 23452 | loss: 0.300179
iter: 23453 | loss: 0.299986
iter: 23454 | loss: 0.299792
iter: 23455 | loss: 0.299599
iter: 23456 | loss: 0.299406
iter: 23457 | loss: 0.299212
iter: 23458 | loss: 0.299019
iter: 23459 | loss: 0.298825
iter: 23460 | loss: 0.298632
iter: 23461 | loss: 0.298439
iter: 23462 | loss: 0.298245
iter: 23463 | loss: 0.298052
iter: 23464 | loss: 0.297858
iter: 23465 | loss: 0.297665
iter: 23466 | loss: 0.297472
iter: 23467 | loss: 0.297278
iter: 23468 | loss: 0.297085
iter: 23469 | loss: 0.296892
iter: 23470 | loss: 0.296698
iter: 23471 | loss: 0.296505
iter: 23472 | loss: 0.296311
iter: 23473 | loss: 0.296118
iter: 23474 | loss: 0.295925
iter: 23475 | loss: 0.295731
iter: 23476 | loss: 0.295538
iter: 23477 | loss: 0.295344
iter: 23478 | loss: 0.295151
iter: 23479 | loss: 0.294958
iter: 23480 | loss: 0.294764
iter: 23481 | loss: 0.294571
iter: 23482 | loss: 0.294378
iter: 23483 | loss: 0.294184
iter: 23484 | loss: 0.293991
iter: 23485 | loss: 0.293797
iter: 23486 | loss: 0.293604
iter: 23487 | loss: 0.293411
iter: 23488 | loss: 0.293217
iter: 23489 | loss: 0.293024
iter: 23490 | loss: 0.292830
iter: 23491 | loss: 0.292637
iter: 23492 | loss: 0.292444
iter: 23493 | loss: 0.292250
iter: 23494 | loss: 0.292057
iter: 23495 | loss: 0.291863
iter: 23496 | loss: 0.291670
iter: 23497 | loss: 0.291477
iter: 23498 | loss: 0.291283
iter: 23499 | loss: 0.291090
iter: 23500 | loss: 0.290897
iter: 23501 | loss: 0.290703
iter: 23502 | loss: 0.290510
iter: 23503 | loss: 0.290316
iter: 23504 | loss: 0.290123
iter: 23505 | loss: 0.289930
iter: 23506 | loss: 0.289736
iter: 23507 | loss: 0.289543
iter: 23508 | loss: 0.289349
iter: 23509 | loss: 0.289156
iter: 23510 | loss: 0.288963
iter: 23511 | loss: 0.288769
iter: 23512 | loss: 0.288576
iter: 23513 | loss: 0.288383
iter: 23514 | loss: 0.288189
iter: 23515 | loss: 0.287996
iter: 23516 | loss: 0.287802
iter: 23517 | loss: 0.287609
iter: 23518 | loss: 0.287416
iter: 23519 | loss: 0.287222
iter: 23520 | loss: 0.287029
iter: 23521 | loss: 0.286835
iter: 23522 | loss: 0.286642
iter: 23523 | loss: 0.286449
iter: 23524 | loss: 0.286255
iter: 23525 | loss: 0.286062
iter: 23526 | loss: 0.285869
iter: 23527 | loss: 0.285675
iter: 23528 | loss: 0.285482
iter: 23529 | loss: 0.285288
iter: 23530 | loss: 0.285095
iter: 23531 | loss: 0.284902
iter: 23532 | loss: 0.284708
iter: 23533 | loss: 0.284515
iter: 23534 | loss: 0.284321
iter: 23535 | loss: 0.284128
iter: 23536 | loss: 0.283935
iter: 23537 | loss: 0.283741
iter: 23538 | loss: 0.283548
iter: 23539 | loss: 0.283354
iter: 23540 | loss: 0.283161
iter: 23541 | loss: 0.282968
iter: 23542 | loss: 0.282774
iter: 23543 | loss: 0.282581
iter: 23544 | loss: 0.282388
iter: 23545 | loss: 0.282194
iter: 23546 | loss: 0.282001
iter: 23547 | loss: 0.281807
iter: 23548 | loss: 0.281614
iter: 23549 | loss: 0.281421
iter: 23550 | loss: 0.281227
iter: 23551 | loss: 0.281034
iter: 23552 | loss: 0.280840
iter: 23553 | loss: 0.280647
iter: 23554 | loss: 0.280454
iter: 23555 | loss: 0.280260
iter: 23556 | loss: 0.280067
iter: 23557 | loss: 0.279874
iter: 23558 | loss: 0.279680
iter: 23559 | loss: 0.279487
iter: 23560 | loss: 0.279293
iter: 23561 | loss: 0.279100
iter: 23562 | loss: 0.278907
iter: 23563 | loss: 0.278713
iter: 23564 | loss: 0.278520
iter: 23565 | loss: 0.278326
iter: 23566 | loss: 0.278133
iter: 23567 | loss: 0.277940
iter: 23568 | loss: 0.277746
iter: 23569 | loss: 0.277553
iter: 23570 | loss: 0.277359
iter: 23571 | loss: 0.277166
iter: 23572 | loss: 0.276973
iter: 23573 | loss: 0.276779
iter: 23574 | loss: 0.276586
iter: 23575 | loss: 0.276393
iter: 23576 | loss: 0.276199
iter: 23577 | loss: 0.276006
iter: 23578 | loss: 0.275812
iter: 23579 | loss: 0.275619
iter: 23580 | loss: 0.275426
iter: 23581 | loss: 0.275232
iter: 23582 | loss: 0.275039
iter: 23583 | loss: 0.274845
iter: 23584 | loss: 0.274652
iter: 23585 | loss: 0.274459
iter: 23586 | loss: 0.274265
iter: 23587 | loss: 0.274072
iter: 23588 | loss: 0.273879
iter: 23589 | loss: 0.273685
iter: 23590 | loss: 0.273492
iter: 23591 | loss: 0.273298
iter: 23592 | loss: 0.273105
iter: 23593 | loss: 0.272912
iter: 23594 | loss: 0.272718
iter: 23595 | loss: 0.272525
iter: 23596 | loss: 0.272331
iter: 23597 | loss: 0.272138
iter: 23598 | loss: 0.271945
iter: 23599 | loss: 0.271751
iter: 23600 | loss: 0.271558
iter: 23601 | loss: 0.271364
iter: 23602 | loss: 0.271171
iter: 23603 | loss: 0.270978
iter: 23604 | loss: 0.270784
iter: 23605 | loss: 0.270591
iter: 23606 | loss: 0.270398
iter: 23607 | loss: 0.270204
iter: 23608 | loss: 0.270011
iter: 23609 | loss: 0.269817
iter: 23610 | loss: 0.269624
iter: 23611 | loss: 0.269431
iter: 23612 | loss: 0.269237
iter: 23613 | loss: 0.269044
iter: 23614 | loss: 0.268850
iter: 23615 | loss: 0.268657
iter: 23616 | loss: 0.268464
iter: 23617 | loss: 0.268270
iter: 23618 | loss: 0.268077
iter: 23619 | loss: 0.267884
iter: 23620 | loss: 0.267690
iter: 23621 | loss: 0.267497
iter: 23622 | loss: 0.267303
iter: 23623 | loss: 0.267110
iter: 23624 | loss: 0.266917
iter: 23625 | loss: 0.266723
iter: 23626 | loss: 0.266530
iter: 23627 | loss: 0.266336
iter: 23628 | loss: 0.266143
iter: 23629 | loss: 0.265950
iter: 23630 | loss: 0.265756
iter: 23631 | loss: 0.265563
iter: 23632 | loss: 0.265369
iter: 23633 | loss: 0.265176
iter: 23634 | loss: 0.264983
iter: 23635 | loss: 0.264789
iter: 23636 | loss: 0.264596
iter: 23637 | loss: 0.264403
iter: 23638 | loss: 0.264209
iter: 23639 | loss: 0.264016
iter: 23640 | loss: 0.263822
iter: 23641 | loss: 0.263629
iter: 23642 | loss: 0.263436
iter: 23643 | loss: 0.263242
iter: 23644 | loss: 0.263049
iter: 23645 | loss: 0.262855
iter: 23646 | loss: 0.262662
iter: 23647 | loss: 0.262469
iter: 23648 | loss: 0.262275
iter: 23649 | loss: 0.262082
iter: 23650 | loss: 0.261889
iter: 23651 | loss: 0.261695
iter: 23652 | loss: 0.261502
iter: 23653 | loss: 0.261308
iter: 23654 | loss: 0.261115
iter: 23655 | loss: 0.260922
iter: 23656 | loss: 0.260728
iter: 23657 | loss: 0.260535
iter: 23658 | loss: 0.260341
iter: 23659 | loss: 0.260148
iter: 23660 | loss: 0.259955
iter: 23661 | loss: 0.259761
iter: 23662 | loss: 0.259568
iter: 23663 | loss: 0.259374
iter: 23664 | loss: 0.259181
iter: 23665 | loss: 0.258988
iter: 23666 | loss: 0.258794
iter: 23667 | loss: 0.258601
iter: 23668 | loss: 0.258408
iter: 23669 | loss: 0.258214
iter: 23670 | loss: 0.258021
iter: 23671 | loss: 0.257827
iter: 23672 | loss: 0.257634
iter: 23673 | loss: 0.257441
iter: 23674 | loss: 0.257247
iter: 23675 | loss: 0.257054
iter: 23676 | loss: 0.256860
iter: 23677 | loss: 0.256667
iter: 23678 | loss: 0.256474
iter: 23679 | loss: 0.256280
iter: 23680 | loss: 0.256087
iter: 23681 | loss: 0.255894
iter: 23682 | loss: 0.255700
iter: 23683 | loss: 0.255507
iter: 23684 | loss: 0.255313
iter: 23685 | loss: 0.255120
iter: 23686 | loss: 0.254927
iter: 23687 | loss: 0.254733
iter: 23688 | loss: 0.254540
iter: 23689 | loss: 0.254346
iter: 23690 | loss: 0.254153
iter: 23691 | loss: 0.253960
iter: 23692 | loss: 0.253766
iter: 23693 | loss: 0.253573
iter: 23694 | loss: 0.253379
iter: 23695 | loss: 0.253186
iter: 23696 | loss: 0.252993
iter: 23697 | loss: 0.252799
iter: 23698 | loss: 0.252606
iter: 23699 | loss: 0.252413
iter: 23700 | loss: 0.252219
iter: 23701 | loss: 0.252026
iter: 23702 | loss: 0.251832
iter: 23703 | loss: 0.251639
iter: 23704 | loss: 0.251446
iter: 23705 | loss: 0.251252
iter: 23706 | loss: 0.251059
iter: 23707 | loss: 0.250865
iter: 23708 | loss: 0.250672
iter: 23709 | loss: 0.250479
iter: 23710 | loss: 0.250285
iter: 23711 | loss: 0.250092
iter: 23712 | loss: 0.249899
iter: 23713 | loss: 0.249705
iter: 23714 | loss: 0.249512
iter: 23715 | loss: 0.249318
iter: 23716 | loss: 0.249125
iter: 23717 | loss: 0.248932
iter: 23718 | loss: 0.248738
iter: 23719 | loss: 0.248545
iter: 23720 | loss: 0.248351
iter: 23721 | loss: 0.248158
iter: 23722 | loss: 0.247965
iter: 23723 | loss: 0.247771
iter: 23724 | loss: 0.247578
iter: 23725 | loss: 0.247384
iter: 23726 | loss: 0.247191
iter: 23727 | loss: 0.246998
iter: 23728 | loss: 0.246804
iter: 23729 | loss: 0.246611
iter: 23730 | loss: 0.246418
iter: 23731 | loss: 0.246224
iter: 23732 | loss: 0.246031
iter: 23733 | loss: 0.245837
iter: 23734 | loss: 0.245644
iter: 23735 | loss: 0.245451
iter: 23736 | loss: 0.245257
iter: 23737 | loss: 0.245064
iter: 23738 | loss: 0.244870
iter: 23739 | loss: 0.244677
iter: 23740 | loss: 0.244484
iter: 23741 | loss: 0.244290
iter: 23742 | loss: 0.244097
iter: 23743 | loss: 0.243904
iter: 23744 | loss: 0.243710
iter: 23745 | loss: 0.243517
iter: 23746 | loss: 0.243323
iter: 23747 | loss: 0.243130
iter: 23748 | loss: 0.242937
iter: 23749 | loss: 0.242743
iter: 23750 | loss: 0.242550
iter: 23751 | loss: 0.242356
iter: 23752 | loss: 0.242163
iter: 23753 | loss: 0.241970
iter: 23754 | loss: 0.241776
iter: 23755 | loss: 0.241583
iter: 23756 | loss: 0.241389
iter: 23757 | loss: 0.241196
iter: 23758 | loss: 0.241003
iter: 23759 | loss: 0.240809
iter: 23760 | loss: 0.240616
iter: 23761 | loss: 0.240423
iter: 23762 | loss: 0.240229
iter: 23763 | loss: 0.240036
iter: 23764 | loss: 0.239842
iter: 23765 | loss: 0.239649
iter: 23766 | loss: 0.239456
iter: 23767 | loss: 0.239262
iter: 23768 | loss: 0.239069
iter: 23769 | loss: 0.238875
iter: 23770 | loss: 0.238682
iter: 23771 | loss: 0.238489
iter: 23772 | loss: 0.238295
iter: 23773 | loss: 0.238102
iter: 23774 | loss: 0.237909
iter: 23775 | loss: 0.237715
iter: 23776 | loss: 0.237522
iter: 23777 | loss: 0.237328
iter: 23778 | loss: 0.237135
iter: 23779 | loss: 0.236942
iter: 23780 | loss: 0.236748
iter: 23781 | loss: 0.236555
iter: 23782 | loss: 0.236361
iter: 23783 | loss: 0.236168
iter: 23784 | loss: 0.235975
iter: 23785 | loss: 0.235781
iter: 23786 | loss: 0.235588
iter: 23787 | loss: 0.235394
iter: 23788 | loss: 0.235201
iter: 23789 | loss: 0.235008
iter: 23790 | loss: 0.234814
iter: 23791 | loss: 0.234621
iter: 23792 | loss: 0.234428
iter: 23793 | loss: 0.234234
iter: 23794 | loss: 0.234041
iter: 23795 | loss: 0.233847
iter: 23796 | loss: 0.233654
iter: 23797 | loss: 0.233461
iter: 23798 | loss: 0.233267
iter: 23799 | loss: 0.233074
iter: 23800 | loss: 0.232880
iter: 23801 | loss: 0.232687
iter: 23802 | loss: 0.232494
iter: 23803 | loss: 0.232300
iter: 23804 | loss: 0.232107
iter: 23805 | loss: 0.231914
iter: 23806 | loss: 0.231720
iter: 23807 | loss: 0.231527
iter: 23808 | loss: 0.231333
iter: 23809 | loss: 0.231140
iter: 23810 | loss: 0.230947
iter: 23811 | loss: 0.230753
iter: 23812 | loss: 0.230560
iter: 23813 | loss: 0.230366
iter: 23814 | loss: 0.230173
iter: 23815 | loss: 0.229980
iter: 23816 | loss: 0.229786
iter: 23817 | loss: 0.229593
iter: 23818 | loss: 0.229399
iter: 23819 | loss: 0.229206
iter: 23820 | loss: 0.229013
iter: 23821 | loss: 0.228819
iter: 23822 | loss: 0.228626
iter: 23823 | loss: 0.228433
iter: 23824 | loss: 0.228239
iter: 23825 | loss: 0.228046
iter: 23826 | loss: 0.227852
iter: 23827 | loss: 0.227659
iter: 23828 | loss: 0.227466
iter: 23829 | loss: 0.227272
iter: 23830 | loss: 0.227079
iter: 23831 | loss: 0.226885
iter: 23832 | loss: 0.226692
iter: 23833 | loss: 0.226499
iter: 23834 | loss: 0.226305
iter: 23835 | loss: 0.226112
iter: 23836 | loss: 0.225919
iter: 23837 | loss: 0.225725
iter: 23838 | loss: 0.225532
iter: 23839 | loss: 0.225338
iter: 23840 | loss: 0.225145
iter: 23841 | loss: 0.224952
iter: 23842 | loss: 0.224758
iter: 23843 | loss: 0.224565
iter: 23844 | loss: 0.224371
iter: 23845 | loss: 0.224178
iter: 23846 | loss: 0.223985
iter: 23847 | loss: 0.223791
iter: 23848 | loss: 0.223598
iter: 23849 | loss: 0.223405
iter: 23850 | loss: 0.223211
iter: 23851 | loss: 0.223018
iter: 23852 | loss: 0.222824
iter: 23853 | loss: 0.222631
iter: 23854 | loss: 0.222438
iter: 23855 | loss: 0.222244
iter: 23856 | loss: 0.222051
iter: 23857 | loss: 0.221857
iter: 23858 | loss: 0.221664
iter: 23859 | loss: 0.221471
iter: 23860 | loss: 0.221277
iter: 23861 | loss: 0.221084
iter: 23862 | loss: 0.220890
iter: 23863 | loss: 0.220697
iter: 23864 | loss: 0.220504
iter: 23865 | loss: 0.220310
iter: 23866 | loss: 0.220117
iter: 23867 | loss: 0.219924
iter: 23868 | loss: 0.219730
iter: 23869 | loss: 0.219537
iter: 23870 | loss: 0.219343
iter: 23871 | loss: 0.219150
iter: 23872 | loss: 0.218957
iter: 23873 | loss: 0.218763
iter: 23874 | loss: 0.218570
iter: 23875 | loss: 0.218376
iter: 23876 | loss: 0.218183
iter: 23877 | loss: 0.217990
iter: 23878 | loss: 0.217796
iter: 23879 | loss: 0.217603
iter: 23880 | loss: 0.217410
iter: 23881 | loss: 0.217216
iter: 23882 | loss: 0.217023
iter: 23883 | loss: 0.216829
iter: 23884 | loss: 0.216636
iter: 23885 | loss: 0.216443
iter: 23886 | loss: 0.216249
iter: 23887 | loss: 0.216056
iter: 23888 | loss: 0.215862
iter: 23889 | loss: 0.215669
iter: 23890 | loss: 0.215476
iter: 23891 | loss: 0.215282
iter: 23892 | loss: 0.215089
iter: 23893 | loss: 0.214895
iter: 23894 | loss: 0.214702
iter: 23895 | loss: 0.214509
iter: 23896 | loss: 0.214315
iter: 23897 | loss: 0.214122
iter: 23898 | loss: 0.213929
iter: 23899 | loss: 0.213735
iter: 23900 | loss: 0.213542
iter: 23901 | loss: 0.213348
iter: 23902 | loss: 0.213155
iter: 23903 | loss: 0.212962
iter: 23904 | loss: 0.212768
iter: 23905 | loss: 0.212575
iter: 23906 | loss: 0.212381
iter: 23907 | loss: 0.212188
iter: 23908 | loss: 0.211995
iter: 23909 | loss: 0.211801
iter: 23910 | loss: 0.211608
iter: 23911 | loss: 0.211415
iter: 23912 | loss: 0.211221
iter: 23913 | loss: 0.211028
iter: 23914 | loss: 0.210834
iter: 23915 | loss: 0.210641
iter: 23916 | loss: 0.210448
iter: 23917 | loss: 0.210254
iter: 23918 | loss: 0.210061
iter: 23919 | loss: 0.209867
iter: 23920 | loss: 0.209674
iter: 23921 | loss: 0.209481
iter: 23922 | loss: 0.209287
iter: 23923 | loss: 0.209094
iter: 23924 | loss: 0.208900
iter: 23925 | loss: 0.208707
iter: 23926 | loss: 0.208514
iter: 23927 | loss: 0.208320
iter: 23928 | loss: 0.208127
iter: 23929 | loss: 0.207934
iter: 23930 | loss: 0.207740
iter: 23931 | loss: 0.207547
iter: 23932 | loss: 0.207353
iter: 23933 | loss: 0.207160
iter: 23934 | loss: 0.206967
iter: 23935 | loss: 0.206773
iter: 23936 | loss: 0.206580
iter: 23937 | loss: 0.206386
iter: 23938 | loss: 0.206193
iter: 23939 | loss: 0.206000
iter: 23940 | loss: 0.205806
iter: 23941 | loss: 0.205613
iter: 23942 | loss: 0.205420
iter: 23943 | loss: 0.205226
iter: 23944 | loss: 0.205033
iter: 23945 | loss: 0.204839
iter: 23946 | loss: 0.204646
iter: 23947 | loss: 0.204453
iter: 23948 | loss: 0.204259
iter: 23949 | loss: 0.204066
iter: 23950 | loss: 0.203872
iter: 23951 | loss: 0.203679
iter: 23952 | loss: 0.203486
iter: 23953 | loss: 0.203292
iter: 23954 | loss: 0.203099
iter: 23955 | loss: 0.202905
iter: 23956 | loss: 0.202712
iter: 23957 | loss: 0.202519
iter: 23958 | loss: 0.202325
iter: 23959 | loss: 0.202132
iter: 23960 | loss: 0.201939
iter: 23961 | loss: 0.201745
iter: 23962 | loss: 0.201552
iter: 23963 | loss: 0.201358
iter: 23964 | loss: 0.201165
iter: 23965 | loss: 0.200972
iter: 23966 | loss: 0.200778
iter: 23967 | loss: 0.200585
iter: 23968 | loss: 0.200391
iter: 23969 | loss: 0.200198
iter: 23970 | loss: 0.200005
iter: 23971 | loss: 0.199811
iter: 23972 | loss: 0.199618
iter: 23973 | loss: 0.199425
iter: 23974 | loss: 0.199231
iter: 23975 | loss: 0.199038
iter: 23976 | loss: 0.198844
iter: 23977 | loss: 0.198651
iter: 23978 | loss: 0.198458
iter: 23979 | loss: 0.198264
iter: 23980 | loss: 0.198071
iter: 23981 | loss: 0.197877
iter: 23982 | loss: 0.197684
iter: 23983 | loss: 0.197491
iter: 23984 | loss: 0.197297
iter: 23985 | loss: 0.197104
iter: 23986 | loss: 0.196910
iter: 23987 | loss: 0.196717
iter: 23988 | loss: 0.196524
iter: 23989 | loss: 0.196330
iter: 23990 | loss: 0.196137
iter: 23991 | loss: 0.195944
iter: 23992 | loss: 0.195750
iter: 23993 | loss: 0.195557
iter: 23994 | loss: 0.195363
iter: 23995 | loss: 0.195170
iter: 23996 | loss: 0.194977
iter: 23997 | loss: 0.194783
iter: 23998 | loss: 0.194590
iter: 23999 | loss: 0.194396
iter: 24000 | loss: 0.194203
iter: 24001 | loss: 0.194010
iter: 24002 | loss: 0.193816
iter: 24003 | loss: 0.193623
iter: 24004 | loss: 0.193430
iter: 24005 | loss: 0.193236
iter: 24006 | loss: 0.193043
iter: 24007 | loss: 0.192849
iter: 24008 | loss: 0.192656
iter: 24009 | loss: 0.192463
iter: 24010 | loss: 0.192269
iter: 24011 | loss: 0.192076
iter: 24012 | loss: 0.191882
iter: 24013 | loss: 0.191689
iter: 24014 | loss: 0.191496
iter: 24015 | loss: 0.191302
iter: 24016 | loss: 0.191109
iter: 24017 | loss: 0.190915
iter: 24018 | loss: 0.190722
iter: 24019 | loss: 0.190529
iter: 24020 | loss: 0.190335
iter: 24021 | loss: 0.190142
iter: 24022 | loss: 0.189949
iter: 24023 | loss: 0.189755
iter: 24024 | loss: 0.189562
iter: 24025 | loss: 0.189368
iter: 24026 | loss: 0.189175
iter: 24027 | loss: 0.188982
iter: 24028 | loss: 0.188788
iter: 24029 | loss: 0.188595
iter: 24030 | loss: 0.188401
iter: 24031 | loss: 0.188208
iter: 24032 | loss: 0.188015
iter: 24033 | loss: 0.187821
iter: 24034 | loss: 0.187628
iter: 24035 | loss: 0.187435
iter: 24036 | loss: 0.187241
iter: 24037 | loss: 0.187048
iter: 24038 | loss: 0.186854
iter: 24039 | loss: 0.186661
iter: 24040 | loss: 0.186468
iter: 24041 | loss: 0.186274
iter: 24042 | loss: 0.186081
iter: 24043 | loss: 0.185887
iter: 24044 | loss: 0.185694
iter: 24045 | loss: 0.185501
iter: 24046 | loss: 0.185307
iter: 24047 | loss: 0.185114
iter: 24048 | loss: 0.184920
iter: 24049 | loss: 0.184727
iter: 24050 | loss: 0.184534
iter: 24051 | loss: 0.184340
iter: 24052 | loss: 0.184147
iter: 24053 | loss: 0.183954
iter: 24054 | loss: 0.183760
iter: 24055 | loss: 0.183567
iter: 24056 | loss: 0.183373
iter: 24057 | loss: 0.183180
iter: 24058 | loss: 0.182987
iter: 24059 | loss: 0.182793
iter: 24060 | loss: 0.182600
iter: 24061 | loss: 0.182406
iter: 24062 | loss: 0.182213
iter: 24063 | loss: 0.182020
iter: 24064 | loss: 0.181826
iter: 24065 | loss: 0.181633
iter: 24066 | loss: 0.181440
iter: 24067 | loss: 0.181246
iter: 24068 | loss: 0.181053
iter: 24069 | loss: 0.180859
iter: 24070 | loss: 0.180666
iter: 24071 | loss: 0.180473
iter: 24072 | loss: 0.180279
iter: 24073 | loss: 0.180086
iter: 24074 | loss: 0.179892
iter: 24075 | loss: 0.179699
iter: 24076 | loss: 0.179506
iter: 24077 | loss: 0.179312
iter: 24078 | loss: 0.179119
iter: 24079 | loss: 0.178925
iter: 24080 | loss: 0.178732
iter: 24081 | loss: 0.178539
iter: 24082 | loss: 0.178345
iter: 24083 | loss: 0.178152
iter: 24084 | loss: 0.177959
iter: 24085 | loss: 0.177765
iter: 24086 | loss: 0.177572
iter: 24087 | loss: 0.177378
iter: 24088 | loss: 0.177185
iter: 24089 | loss: 0.176992
iter: 24090 | loss: 0.176798
iter: 24091 | loss: 0.176605
iter: 24092 | loss: 0.176411
iter: 24093 | loss: 0.176218
iter: 24094 | loss: 0.176025
iter: 24095 | loss: 0.175831
iter: 24096 | loss: 0.175638
iter: 24097 | loss: 0.175445
iter: 24098 | loss: 0.175251
iter: 24099 | loss: 0.175058
iter: 24100 | loss: 0.174864
iter: 24101 | loss: 0.174671
iter: 24102 | loss: 0.174478
iter: 24103 | loss: 0.174284
iter: 24104 | loss: 0.174091
iter: 24105 | loss: 0.173897
iter: 24106 | loss: 0.173704
iter: 24107 | loss: 0.173511
iter: 24108 | loss: 0.173317
iter: 24109 | loss: 0.173124
iter: 24110 | loss: 0.172930
iter: 24111 | loss: 0.172737
iter: 24112 | loss: 0.172544
iter: 24113 | loss: 0.172350
iter: 24114 | loss: 0.172157
iter: 24115 | loss: 0.171964
iter: 24116 | loss: 0.171770
iter: 24117 | loss: 0.171577
iter: 24118 | loss: 0.171383
iter: 24119 | loss: 0.171190
iter: 24120 | loss: 0.170997
iter: 24121 | loss: 0.170803
iter: 24122 | loss: 0.170610
iter: 24123 | loss: 0.170416
iter: 24124 | loss: 0.170223
iter: 24125 | loss: 0.170030
iter: 24126 | loss: 0.169836
iter: 24127 | loss: 0.169643
iter: 24128 | loss: 0.169450
iter: 24129 | loss: 0.169256
iter: 24130 | loss: 0.169063
iter: 24131 | loss: 0.168869
iter: 24132 | loss: 0.168676
iter: 24133 | loss: 0.168483
iter: 24134 | loss: 0.168289
iter: 24135 | loss: 0.168096
iter: 24136 | loss: 0.167902
iter: 24137 | loss: 0.167709
iter: 24138 | loss: 0.167516
iter: 24139 | loss: 0.167322
iter: 24140 | loss: 0.167129
iter: 24141 | loss: 0.166935
iter: 24142 | loss: 0.166742
iter: 24143 | loss: 0.166549
iter: 24144 | loss: 0.166355
iter: 24145 | loss: 0.166162
iter: 24146 | loss: 0.165969
iter: 24147 | loss: 0.165775
iter: 24148 | loss: 0.165582
iter: 24149 | loss: 0.165388
iter: 24150 | loss: 0.165195
iter: 24151 | loss: 0.165002
iter: 24152 | loss: 0.164808
iter: 24153 | loss: 0.164615
iter: 24154 | loss: 0.164421
iter: 24155 | loss: 0.164228
iter: 24156 | loss: 0.164035
iter: 24157 | loss: 0.163841
iter: 24158 | loss: 0.163648
iter: 24159 | loss: 0.163455
iter: 24160 | loss: 0.163261
iter: 24161 | loss: 0.163068
iter: 24162 | loss: 0.162874
iter: 24163 | loss: 0.162681
iter: 24164 | loss: 0.162488
iter: 24165 | loss: 0.162294
iter: 24166 | loss: 0.162101
iter: 24167 | loss: 0.161907
iter: 24168 | loss: 0.161714
iter: 24169 | loss: 0.161521
iter: 24170 | loss: 0.161327
iter: 24171 | loss: 0.161134
iter: 24172 | loss: 0.160941
iter: 24173 | loss: 0.160747
iter: 24174 | loss: 0.160554
iter: 24175 | loss: 0.160360
iter: 24176 | loss: 0.160167
iter: 24177 | loss: 0.159974
iter: 24178 | loss: 0.159780
iter: 24179 | loss: 0.159587
iter: 24180 | loss: 0.159393
iter: 24181 | loss: 0.159200
iter: 24182 | loss: 0.159007
iter: 24183 | loss: 0.158813
iter: 24184 | loss: 0.158620
iter: 24185 | loss: 0.158426
iter: 24186 | loss: 0.158233
iter: 24187 | loss: 0.158040
iter: 24188 | loss: 0.157846
iter: 24189 | loss: 0.157653
iter: 24190 | loss: 0.157460
iter: 24191 | loss: 0.157266
iter: 24192 | loss: 0.157073
iter: 24193 | loss: 0.156879
iter: 24194 | loss: 0.156686
iter: 24195 | loss: 0.156493
iter: 24196 | loss: 0.156299
iter: 24197 | loss: 0.156106
iter: 24198 | loss: 0.155912
iter: 24199 | loss: 0.155719
iter: 24200 | loss: 0.155526
iter: 24201 | loss: 0.155332
iter: 24202 | loss: 0.155139
iter: 24203 | loss: 0.154946
iter: 24204 | loss: 0.154752
iter: 24205 | loss: 0.154559
iter: 24206 | loss: 0.154365
iter: 24207 | loss: 0.154172
iter: 24208 | loss: 0.153979
iter: 24209 | loss: 0.153785
iter: 24210 | loss: 0.153592
iter: 24211 | loss: 0.153398
iter: 24212 | loss: 0.153205
iter: 24213 | loss: 0.153012
iter: 24214 | loss: 0.152818
iter: 24215 | loss: 0.152625
iter: 24216 | loss: 0.152431
iter: 24217 | loss: 0.152238
iter: 24218 | loss: 0.152045
iter: 24219 | loss: 0.151851
iter: 24220 | loss: 0.151658
iter: 24221 | loss: 0.151465
iter: 24222 | loss: 0.151271
iter: 24223 | loss: 0.151078
iter: 24224 | loss: 0.150884
iter: 24225 | loss: 0.150691
iter: 24226 | loss: 0.150498
iter: 24227 | loss: 0.150304
iter: 24228 | loss: 0.150111
iter: 24229 | loss: 0.149917
iter: 24230 | loss: 0.149724
iter: 24231 | loss: 0.149531
iter: 24232 | loss: 0.149337
iter: 24233 | loss: 0.149144
iter: 24234 | loss: 0.148951
iter: 24235 | loss: 0.148757
iter: 24236 | loss: 0.148564
iter: 24237 | loss: 0.148370
iter: 24238 | loss: 0.148177
iter: 24239 | loss: 0.147984
iter: 24240 | loss: 0.147790
iter: 24241 | loss: 0.147597
iter: 24242 | loss: 0.147403
iter: 24243 | loss: 0.147210
iter: 24244 | loss: 0.147017
iter: 24245 | loss: 0.146823
iter: 24246 | loss: 0.146630
iter: 24247 | loss: 0.146436
iter: 24248 | loss: 0.146243
iter: 24249 | loss: 0.146050
iter: 24250 | loss: 0.145856
iter: 24251 | loss: 0.145663
iter: 24252 | loss: 0.145470
iter: 24253 | loss: 0.145276
iter: 24254 | loss: 0.145083
iter: 24255 | loss: 0.144889
iter: 24256 | loss: 0.144696
iter: 24257 | loss: 0.144503
iter: 24258 | loss: 0.144309
iter: 24259 | loss: 0.144116
iter: 24260 | loss: 0.143922
iter: 24261 | loss: 0.143729
iter: 24262 | loss: 0.143536
iter: 24263 | loss: 0.143342
iter: 24264 | loss: 0.143149
iter: 24265 | loss: 0.142956
iter: 24266 | loss: 0.142762
iter: 24267 | loss: 0.142569
iter: 24268 | loss: 0.142375
iter: 24269 | loss: 0.142182
iter: 24270 | loss: 0.141989
iter: 24271 | loss: 0.141795
iter: 24272 | loss: 0.141602
iter: 24273 | loss: 0.141408
iter: 24274 | loss: 0.141215
iter: 24275 | loss: 0.141022
iter: 24276 | loss: 0.140828
iter: 24277 | loss: 0.140635
iter: 24278 | loss: 0.140441
iter: 24279 | loss: 0.140248
iter: 24280 | loss: 0.140055
iter: 24281 | loss: 0.139861
iter: 24282 | loss: 0.139668
iter: 24283 | loss: 0.139475
iter: 24284 | loss: 0.139281
iter: 24285 | loss: 0.139088
iter: 24286 | loss: 0.138894
iter: 24287 | loss: 0.138701
iter: 24288 | loss: 0.138508
iter: 24289 | loss: 0.138314
iter: 24290 | loss: 0.138121
iter: 24291 | loss: 0.137927
iter: 24292 | loss: 0.137734
iter: 24293 | loss: 0.137541
iter: 24294 | loss: 0.137347
iter: 24295 | loss: 0.137154
iter: 24296 | loss: 0.136961
iter: 24297 | loss: 0.136767
iter: 24298 | loss: 0.136574
iter: 24299 | loss: 0.136380
iter: 24300 | loss: 0.136187
iter: 24301 | loss: 0.135994
iter: 24302 | loss: 0.135800
iter: 24303 | loss: 0.135607
iter: 24304 | loss: 0.135413
iter: 24305 | loss: 0.135220
iter: 24306 | loss: 0.135027
iter: 24307 | loss: 0.134833
iter: 24308 | loss: 0.134640
iter: 24309 | loss: 0.134446
iter: 24310 | loss: 0.134253
iter: 24311 | loss: 0.134060
iter: 24312 | loss: 0.133866
iter: 24313 | loss: 0.133673
iter: 24314 | loss: 0.133480
iter: 24315 | loss: 0.133286
iter: 24316 | loss: 0.133093
iter: 24317 | loss: 0.132899
iter: 24318 | loss: 0.132706
iter: 24319 | loss: 0.132513
iter: 24320 | loss: 0.132319
iter: 24321 | loss: 0.132126
iter: 24322 | loss: 0.131932
iter: 24323 | loss: 0.131739
iter: 24324 | loss: 0.131546
iter: 24325 | loss: 0.131352
iter: 24326 | loss: 0.131159
iter: 24327 | loss: 0.130966
iter: 24328 | loss: 0.130772
iter: 24329 | loss: 0.130579
iter: 24330 | loss: 0.130385
iter: 24331 | loss: 0.130192
iter: 24332 | loss: 0.129999
iter: 24333 | loss: 0.129805
iter: 24334 | loss: 0.129612
iter: 24335 | loss: 0.129418
iter: 24336 | loss: 0.129225
iter: 24337 | loss: 0.129032
iter: 24338 | loss: 0.128838
iter: 24339 | loss: 0.128645
iter: 24340 | loss: 0.128451
iter: 24341 | loss: 0.128258
iter: 24342 | loss: 0.128065
iter: 24343 | loss: 0.127871
iter: 24344 | loss: 0.127678
iter: 24345 | loss: 0.127485
iter: 24346 | loss: 0.127291
iter: 24347 | loss: 0.127098
iter: 24348 | loss: 0.126904
iter: 24349 | loss: 0.126711
iter: 24350 | loss: 0.126518
iter: 24351 | loss: 0.126324
iter: 24352 | loss: 0.126131
iter: 24353 | loss: 0.125937
iter: 24354 | loss: 0.125744
iter: 24355 | loss: 0.125551
iter: 24356 | loss: 0.125357
iter: 24357 | loss: 0.125164
iter: 24358 | loss: 0.124971
iter: 24359 | loss: 0.124777
iter: 24360 | loss: 0.124584
iter: 24361 | loss: 0.124390
iter: 24362 | loss: 0.124197
iter: 24363 | loss: 0.124004
iter: 24364 | loss: 0.123810
iter: 24365 | loss: 0.123617
iter: 24366 | loss: 0.123423
iter: 24367 | loss: 0.123230
iter: 24368 | loss: 0.123037
iter: 24369 | loss: 0.122843
iter: 24370 | loss: 0.122650
iter: 24371 | loss: 0.122456
iter: 24372 | loss: 0.122263
iter: 24373 | loss: 0.122070
iter: 24374 | loss: 0.121876
iter: 24375 | loss: 0.121683
iter: 24376 | loss: 0.121490
iter: 24377 | loss: 0.121296
iter: 24378 | loss: 0.121103
iter: 24379 | loss: 0.120909
iter: 24380 | loss: 0.120716
iter: 24381 | loss: 0.120523
iter: 24382 | loss: 0.120329
iter: 24383 | loss: 0.120136
iter: 24384 | loss: 0.119942
iter: 24385 | loss: 0.119749
iter: 24386 | loss: 0.119556
iter: 24387 | loss: 0.119362
iter: 24388 | loss: 0.119169
iter: 24389 | loss: 0.118976
iter: 24390 | loss: 0.118782
iter: 24391 | loss: 0.118589
iter: 24392 | loss: 0.118395
iter: 24393 | loss: 0.118202
iter: 24394 | loss: 0.118009
iter: 24395 | loss: 0.117815
iter: 24396 | loss: 0.117622
iter: 24397 | loss: 0.117428
iter: 24398 | loss: 0.117235
iter: 24399 | loss: 0.117042
iter: 24400 | loss: 0.116848
iter: 24401 | loss: 0.116655
iter: 24402 | loss: 0.116461
iter: 24403 | loss: 0.116268
iter: 24404 | loss: 0.116075
iter: 24405 | loss: 0.115881
iter: 24406 | loss: 0.115688
iter: 24407 | loss: 0.115495
iter: 24408 | loss: 0.115301
iter: 24409 | loss: 0.115108
iter: 24410 | loss: 0.114914
iter: 24411 | loss: 0.114721
iter: 24412 | loss: 0.114528
iter: 24413 | loss: 0.114334
iter: 24414 | loss: 0.114141
iter: 24415 | loss: 0.113947
iter: 24416 | loss: 0.113754
iter: 24417 | loss: 0.113561
iter: 24418 | loss: 0.113367
iter: 24419 | loss: 0.113174
iter: 24420 | loss: 0.112981
iter: 24421 | loss: 0.112787
iter: 24422 | loss: 0.112594
iter: 24423 | loss: 0.112400
iter: 24424 | loss: 0.112207
iter: 24425 | loss: 0.112014
iter: 24426 | loss: 0.111820
iter: 24427 | loss: 0.111627
iter: 24428 | loss: 0.111433
iter: 24429 | loss: 0.111240
iter: 24430 | loss: 0.111047
iter: 24431 | loss: 0.110853
iter: 24432 | loss: 0.110660
iter: 24433 | loss: 0.110466
iter: 24434 | loss: 0.110273
iter: 24435 | loss: 0.110080
iter: 24436 | loss: 0.109886
iter: 24437 | loss: 0.109693
iter: 24438 | loss: 0.109500
iter: 24439 | loss: 0.109306
iter: 24440 | loss: 0.109113
iter: 24441 | loss: 0.108919
iter: 24442 | loss: 0.108726
iter: 24443 | loss: 0.108533
iter: 24444 | loss: 0.108339
iter: 24445 | loss: 0.108146
iter: 24446 | loss: 0.107952
iter: 24447 | loss: 0.107759
iter: 24448 | loss: 0.107566
iter: 24449 | loss: 0.107372
iter: 24450 | loss: 0.107179
iter: 24451 | loss: 0.106986
iter: 24452 | loss: 0.106792
iter: 24453 | loss: 0.106599
iter: 24454 | loss: 0.106405
iter: 24455 | loss: 0.106212
iter: 24456 | loss: 0.106019
iter: 24457 | loss: 0.105825
iter: 24458 | loss: 0.105632
iter: 24459 | loss: 0.105438
iter: 24460 | loss: 0.105245
iter: 24461 | loss: 0.105052
iter: 24462 | loss: 0.104858
iter: 24463 | loss: 0.104665
iter: 24464 | loss: 0.104471
iter: 24465 | loss: 0.104278
iter: 24466 | loss: 0.104085
iter: 24467 | loss: 0.103891
iter: 24468 | loss: 0.103698
iter: 24469 | loss: 0.103505
iter: 24470 | loss: 0.103311
iter: 24471 | loss: 0.103118
iter: 24472 | loss: 0.102924
iter: 24473 | loss: 0.102731
iter: 24474 | loss: 0.102538
iter: 24475 | loss: 0.102344
iter: 24476 | loss: 0.102151
iter: 24477 | loss: 0.101957
iter: 24478 | loss: 0.101764
iter: 24479 | loss: 0.101571
iter: 24480 | loss: 0.101377
iter: 24481 | loss: 0.101184
iter: 24482 | loss: 0.100991
iter: 24483 | loss: 0.100797
iter: 24484 | loss: 0.100604
iter: 24485 | loss: 0.100410
iter: 24486 | loss: 0.100217
iter: 24487 | loss: 0.100024
iter: 24488 | loss: 0.099830
iter: 24489 | loss: 0.099637
iter: 24490 | loss: 0.099443
iter: 24491 | loss: 0.099250
iter: 24492 | loss: 0.099057
iter: 24493 | loss: 0.098863
iter: 24494 | loss: 0.098670
iter: 24495 | loss: 0.098477
iter: 24496 | loss: 0.098283
iter: 24497 | loss: 0.098090
iter: 24498 | loss: 0.097896
iter: 24499 | loss: 0.097703
iter: 24500 | loss: 0.097510
iter: 24501 | loss: 0.097316
iter: 24502 | loss: 0.097123
iter: 24503 | loss: 0.096929
iter: 24504 | loss: 0.096736
iter: 24505 | loss: 0.096543
iter: 24506 | loss: 0.096349
iter: 24507 | loss: 0.096156
iter: 24508 | loss: 0.095962
iter: 24509 | loss: 0.095769
iter: 24510 | loss: 0.095576
iter: 24511 | loss: 0.095382
iter: 24512 | loss: 0.095189
iter: 24513 | loss: 0.094996
iter: 24514 | loss: 0.094802
iter: 24515 | loss: 0.094609
iter: 24516 | loss: 0.094415
iter: 24517 | loss: 0.094222
iter: 24518 | loss: 0.094029
iter: 24519 | loss: 0.093835
iter: 24520 | loss: 0.093642
iter: 24521 | loss: 0.093448
iter: 24522 | loss: 0.093255
iter: 24523 | loss: 0.093062
iter: 24524 | loss: 0.092868
iter: 24525 | loss: 0.092675
iter: 24526 | loss: 0.092482
iter: 24527 | loss: 0.092288
iter: 24528 | loss: 0.092095
iter: 24529 | loss: 0.091901
iter: 24530 | loss: 0.091708
iter: 24531 | loss: 0.091515
iter: 24532 | loss: 0.091321
iter: 24533 | loss: 0.091128
iter: 24534 | loss: 0.090934
iter: 24535 | loss: 0.090741
iter: 24536 | loss: 0.090548
iter: 24537 | loss: 0.090354
iter: 24538 | loss: 0.090161
iter: 24539 | loss: 0.089967
iter: 24540 | loss: 0.089774
iter: 24541 | loss: 0.089581
iter: 24542 | loss: 0.089387
iter: 24543 | loss: 0.089194
iter: 24544 | loss: 0.089001
iter: 24545 | loss: 0.088807
iter: 24546 | loss: 0.088614
iter: 24547 | loss: 0.088420
iter: 24548 | loss: 0.088227
iter: 24549 | loss: 0.088034
iter: 24550 | loss: 0.087840
iter: 24551 | loss: 0.087647
iter: 24552 | loss: 0.087453
iter: 24553 | loss: 0.087260
iter: 24554 | loss: 0.087067
iter: 24555 | loss: 0.086873
iter: 24556 | loss: 0.086680
iter: 24557 | loss: 0.086487
iter: 24558 | loss: 0.086293
iter: 24559 | loss: 0.086100
iter: 24560 | loss: 0.085906
iter: 24561 | loss: 0.085713
iter: 24562 | loss: 0.085520
iter: 24563 | loss: 0.085326
iter: 24564 | loss: 0.085133
iter: 24565 | loss: 0.084939
iter: 24566 | loss: 0.084746
iter: 24567 | loss: 0.084553
iter: 24568 | loss: 0.084359
iter: 24569 | loss: 0.084166
iter: 24570 | loss: 0.083972
iter: 24571 | loss: 0.083779
iter: 24572 | loss: 0.083586
iter: 24573 | loss: 0.083392
iter: 24574 | loss: 0.083199
iter: 24575 | loss: 0.083006
iter: 24576 | loss: 0.082812
iter: 24577 | loss: 0.082619
iter: 24578 | loss: 0.082425
iter: 24579 | loss: 0.082232
iter: 24580 | loss: 0.082039
iter: 24581 | loss: 0.081845
iter: 24582 | loss: 0.081652
iter: 24583 | loss: 0.081458
iter: 24584 | loss: 0.081265
iter: 24585 | loss: 0.081072
iter: 24586 | loss: 0.080878
iter: 24587 | loss: 0.080685
iter: 24588 | loss: 0.080492
iter: 24589 | loss: 0.080298
iter: 24590 | loss: 0.080105
iter: 24591 | loss: 0.079911
iter: 24592 | loss: 0.079718
iter: 24593 | loss: 0.079525
iter: 24594 | loss: 0.079331
iter: 24595 | loss: 0.079138
iter: 24596 | loss: 0.078944
iter: 24597 | loss: 0.078751
iter: 24598 | loss: 0.078558
iter: 24599 | loss: 0.078364
iter: 24600 | loss: 0.078171
iter: 24601 | loss: 0.077977
iter: 24602 | loss: 0.077784
iter: 24603 | loss: 0.077591
iter: 24604 | loss: 0.077397
iter: 24605 | loss: 0.077204
iter: 24606 | loss: 0.077011
iter: 24607 | loss: 0.076817
iter: 24608 | loss: 0.076624
iter: 24609 | loss: 0.076430
iter: 24610 | loss: 0.076237
iter: 24611 | loss: 0.076044
iter: 24612 | loss: 0.075850
iter: 24613 | loss: 0.075657
iter: 24614 | loss: 0.075463
iter: 24615 | loss: 0.075270
iter: 24616 | loss: 0.075077
iter: 24617 | loss: 0.074883
iter: 24618 | loss: 0.074690
iter: 24619 | loss: 0.074497
iter: 24620 | loss: 0.074303
iter: 24621 | loss: 0.074110
iter: 24622 | loss: 0.073916
iter: 24623 | loss: 0.073723
iter: 24624 | loss: 0.073530
iter: 24625 | loss: 0.073336
iter: 24626 | loss: 0.073143
iter: 24627 | loss: 0.072949
iter: 24628 | loss: 0.072756
iter: 24629 | loss: 0.072563
iter: 24630 | loss: 0.072369
iter: 24631 | loss: 0.072176
iter: 24632 | loss: 0.071982
iter: 24633 | loss: 0.071789
iter: 24634 | loss: 0.071596
iter: 24635 | loss: 0.071402
iter: 24636 | loss: 0.071209
iter: 24637 | loss: 0.071016
iter: 24638 | loss: 0.070822
iter: 24639 | loss: 0.070629
iter: 24640 | loss: 0.070435
iter: 24641 | loss: 0.070242
iter: 24642 | loss: 0.070049
iter: 24643 | loss: 0.069855
iter: 24644 | loss: 0.069662
iter: 24645 | loss: 0.069468
iter: 24646 | loss: 0.069275
iter: 24647 | loss: 0.069082
iter: 24648 | loss: 0.068888
iter: 24649 | loss: 0.068695
iter: 24650 | loss: 0.068502
iter: 24651 | loss: 0.068308
iter: 24652 | loss: 0.068115
iter: 24653 | loss: 0.067921
iter: 24654 | loss: 0.067728
iter: 24655 | loss: 0.067535
iter: 24656 | loss: 0.067341
iter: 24657 | loss: 0.067148
iter: 24658 | loss: 0.066954
iter: 24659 | loss: 0.066761
iter: 24660 | loss: 0.066568
iter: 24661 | loss: 0.066374
iter: 24662 | loss: 0.066181
iter: 24663 | loss: 0.065987
iter: 24664 | loss: 0.065794
iter: 24665 | loss: 0.065601
iter: 24666 | loss: 0.065407
iter: 24667 | loss: 0.065214
iter: 24668 | loss: 0.065021
iter: 24669 | loss: 0.064827
iter: 24670 | loss: 0.064634
iter: 24671 | loss: 0.064440
iter: 24672 | loss: 0.064247
iter: 24673 | loss: 0.064054
iter: 24674 | loss: 0.063860
iter: 24675 | loss: 0.063667
iter: 24676 | loss: 0.063473
iter: 24677 | loss: 0.063280
iter: 24678 | loss: 0.063087
iter: 24679 | loss: 0.062893
iter: 24680 | loss: 0.062700
iter: 24681 | loss: 0.062507
iter: 24682 | loss: 0.062313
iter: 24683 | loss: 0.062120
iter: 24684 | loss: 0.061926
iter: 24685 | loss: 0.061733
iter: 24686 | loss: 0.061540
iter: 24687 | loss: 0.061346
iter: 24688 | loss: 0.061153
iter: 24689 | loss: 0.060959
iter: 24690 | loss: 0.060766
iter: 24691 | loss: 0.060573
iter: 24692 | loss: 0.060379
iter: 24693 | loss: 0.060186
iter: 24694 | loss: 0.059992
iter: 24695 | loss: 0.059799
iter: 24696 | loss: 0.059606
iter: 24697 | loss: 0.059412
iter: 24698 | loss: 0.059219
iter: 24699 | loss: 0.059026
iter: 24700 | loss: 0.058832
iter: 24701 | loss: 0.058639
iter: 24702 | loss: 0.058445
iter: 24703 | loss: 0.058252
iter: 24704 | loss: 0.058059
iter: 24705 | loss: 0.057865
iter: 24706 | loss: 0.057672
iter: 24707 | loss: 0.057478
iter: 24708 | loss: 0.057285
iter: 24709 | loss: 0.057092
iter: 24710 | loss: 0.056898
iter: 24711 | loss: 0.056705
iter: 24712 | loss: 0.056512
iter: 24713 | loss: 0.056318
iter: 24714 | loss: 0.056125
iter: 24715 | loss: 0.055931
iter: 24716 | loss: 0.055738
iter: 24717 | loss: 0.055545
iter: 24718 | loss: 0.055351
iter: 24719 | loss: 0.055158
iter: 24720 | loss: 0.054964
iter: 24721 | loss: 0.054771
iter: 24722 | loss: 0.054578
iter: 24723 | loss: 0.054384
iter: 24724 | loss: 0.054191
iter: 24725 | loss: 0.053997
iter: 24726 | loss: 0.053804
iter: 24727 | loss: 0.053611
iter: 24728 | loss: 0.053417
iter: 24729 | loss: 0.053224
iter: 24730 | loss: 0.053031
iter: 24731 | loss: 0.052837
iter: 24732 | loss: 0.052644
iter: 24733 | loss: 0.052450
iter: 24734 | loss: 0.052257
iter: 24735 | loss: 0.052064
iter: 24736 | loss: 0.051870
iter: 24737 | loss: 0.051677
iter: 24738 | loss: 0.051483
iter: 24739 | loss: 0.051290
iter: 24740 | loss: 0.051097
iter: 24741 | loss: 0.050903
iter: 24742 | loss: 0.050710
iter: 24743 | loss: 0.050517
iter: 24744 | loss: 0.050323
iter: 24745 | loss: 0.050130
iter: 24746 | loss: 0.049936
iter: 24747 | loss: 0.049743
iter: 24748 | loss: 0.049550
iter: 24749 | loss: 0.049356
iter: 24750 | loss: 0.049163
iter: 24751 | loss: 0.048969
iter: 24752 | loss: 0.048776
iter: 24753 | loss: 0.048583
iter: 24754 | loss: 0.048389
iter: 24755 | loss: 0.048196
iter: 24756 | loss: 0.048002
iter: 24757 | loss: 0.047809
iter: 24758 | loss: 0.047616
iter: 24759 | loss: 0.047422
iter: 24760 | loss: 0.047229
iter: 24761 | loss: 0.047036
iter: 24762 | loss: 0.046842
iter: 24763 | loss: 0.046649
iter: 24764 | loss: 0.046455
iter: 24765 | loss: 0.046262
iter: 24766 | loss: 0.046069
iter: 24767 | loss: 0.045875
iter: 24768 | loss: 0.045682
iter: 24769 | loss: 0.045488
iter: 24770 | loss: 0.045295
iter: 24771 | loss: 0.045102
iter: 24772 | loss: 0.044908
iter: 24773 | loss: 0.044715
iter: 24774 | loss: 0.044522
iter: 24775 | loss: 0.044328
iter: 24776 | loss: 0.044135
iter: 24777 | loss: 0.043941
iter: 24778 | loss: 0.043748
iter: 24779 | loss: 0.043555
iter: 24780 | loss: 0.043361
iter: 24781 | loss: 0.043168
iter: 24782 | loss: 0.042974
iter: 24783 | loss: 0.042781
iter: 24784 | loss: 0.042588
iter: 24785 | loss: 0.042394
iter: 24786 | loss: 0.042201
iter: 24787 | loss: 0.042007
iter: 24788 | loss: 0.041814
iter: 24789 | loss: 0.041621
iter: 24790 | loss: 0.041427
iter: 24791 | loss: 0.041234
iter: 24792 | loss: 0.041041
iter: 24793 | loss: 0.040847
iter: 24794 | loss: 0.040654
iter: 24795 | loss: 0.040460
iter: 24796 | loss: 0.040267
iter: 24797 | loss: 0.040074
iter: 24798 | loss: 0.039880
iter: 24799 | loss: 0.039687
iter: 24800 | loss: 0.039493
iter: 24801 | loss: 0.039300
iter: 24802 | loss: 0.039107
iter: 24803 | loss: 0.038913
iter: 24804 | loss: 0.038720
iter: 24805 | loss: 0.038527
iter: 24806 | loss: 0.038333
iter: 24807 | loss: 0.038140
iter: 24808 | loss: 0.037946
iter: 24809 | loss: 0.037753
iter: 24810 | loss: 0.037560
iter: 24811 | loss: 0.037366
iter: 24812 | loss: 0.037173
iter: 24813 | loss: 0.036979
iter: 24814 | loss: 0.036786
iter: 24815 | loss: 0.036593
iter: 24816 | loss: 0.036399
iter: 24817 | loss: 0.036206
iter: 24818 | loss: 0.036013
iter: 24819 | loss: 0.035819
iter: 24820 | loss: 0.035626
iter: 24821 | loss: 0.035432
iter: 24822 | loss: 0.035239
iter: 24823 | loss: 0.035046
iter: 24824 | loss: 0.034852
iter: 24825 | loss: 0.034659
iter: 24826 | loss: 0.034465
iter: 24827 | loss: 0.034272
iter: 24828 | loss: 0.034079
iter: 24829 | loss: 0.033885
iter: 24830 | loss: 0.033692
iter: 24831 | loss: 0.033498
iter: 24832 | loss: 0.033305
iter: 24833 | loss: 0.033112
iter: 24834 | loss: 0.032918
iter: 24835 | loss: 0.032725
iter: 24836 | loss: 0.032532
iter: 24837 | loss: 0.032338
iter: 24838 | loss: 0.032145
iter: 24839 | loss: 0.031951
iter: 24840 | loss: 0.031758
iter: 24841 | loss: 0.031565
iter: 24842 | loss: 0.031371
iter: 24843 | loss: 0.031178
iter: 24844 | loss: 0.030984
iter: 24845 | loss: 0.030791
iter: 24846 | loss: 0.030598
iter: 24847 | loss: 0.030404
iter: 24848 | loss: 0.030211
iter: 24849 | loss: 0.030018
iter: 24850 | loss: 0.029824
iter: 24851 | loss: 0.029631
iter: 24852 | loss: 0.029437
iter: 24853 | loss: 0.029244
iter: 24854 | loss: 0.029051
iter: 24855 | loss: 0.028857
iter: 24856 | loss: 0.028664
iter: 24857 | loss: 0.028470
iter: 24858 | loss: 0.028277
iter: 24859 | loss: 0.028084
iter: 24860 | loss: 0.027890
iter: 24861 | loss: 0.027697
iter: 24862 | loss: 0.027503
iter: 24863 | loss: 0.027310
iter: 24864 | loss: 0.027117
iter: 24865 | loss: 0.026923
iter: 24866 | loss: 0.026730
iter: 24867 | loss: 0.026537
iter: 24868 | loss: 0.026343
iter: 24869 | loss: 0.026150
iter: 24870 | loss: 0.025956
iter: 24871 | loss: 0.025763
iter: 24872 | loss: 0.025570
iter: 24873 | loss: 0.025376
iter: 24874 | loss: 0.025183
iter: 24875 | loss: 0.024989
iter: 24876 | loss: 0.024796
iter: 24877 | loss: 0.024603
iter: 24878 | loss: 0.024409
iter: 24879 | loss: 0.024216
iter: 24880 | loss: 0.024023
iter: 24881 | loss: 0.023829
iter: 24882 | loss: 0.023636
iter: 24883 | loss: 0.023442
iter: 24884 | loss: 0.023249
iter: 24885 | loss: 0.023056
iter: 24886 | loss: 0.022862
iter: 24887 | loss: 0.022669
iter: 24888 | loss: 0.022475
iter: 24889 | loss: 0.022282
iter: 24890 | loss: 0.022089
iter: 24891 | loss: 0.021895
iter: 24892 | loss: 0.021702
iter: 24893 | loss: 0.021508
iter: 24894 | loss: 0.021315
iter: 24895 | loss: 0.021122
iter: 24896 | loss: 0.020928
iter: 24897 | loss: 0.020735
iter: 24898 | loss: 0.020542
iter: 24899 | loss: 0.020348
iter: 24900 | loss: 0.020155
iter: 24901 | loss: 0.019961
iter: 24902 | loss: 0.019768
iter: 24903 | loss: 0.019575
iter: 24904 | loss: 0.019381
iter: 24905 | loss: 0.019188
iter: 24906 | loss: 0.018994
iter: 24907 | loss: 0.018801
iter: 24908 | loss: 0.018608
iter: 24909 | loss: 0.018414
iter: 24910 | loss: 0.018221
iter: 24911 | loss: 0.018028
iter: 24912 | loss: 0.017834
iter: 24913 | loss: 0.017641
iter: 24914 | loss: 0.017447
iter: 24915 | loss: 0.017254
iter: 24916 | loss: 0.017061
iter: 24917 | loss: 0.016867
iter: 24918 | loss: 0.016674
iter: 24919 | loss: 0.016480
iter: 24920 | loss: 0.016287
iter: 24921 | loss: 0.016094
iter: 24922 | loss: 0.015900
iter: 24923 | loss: 0.015707
iter: 24924 | loss: 0.015513
iter: 24925 | loss: 0.015320
iter: 24926 | loss: 0.015127
iter: 24927 | loss: 0.014933
iter: 24928 | loss: 0.014740
iter: 24929 | loss: 0.014547
iter: 24930 | loss: 0.014353
iter: 24931 | loss: 0.014160
iter: 24932 | loss: 0.013966
iter: 24933 | loss: 0.013773
iter: 24934 | loss: 0.013580
iter: 24935 | loss: 0.013386
iter: 24936 | loss: 0.013193
iter: 24937 | loss: 0.012999
iter: 24938 | loss: 0.012806
iter: 24939 | loss: 0.012613
iter: 24940 | loss: 0.012419
iter: 24941 | loss: 0.012226
iter: 24942 | loss: 0.012033
iter: 24943 | loss: 0.011839
iter: 24944 | loss: 0.011646
iter: 24945 | loss: 0.011452
iter: 24946 | loss: 0.011259
iter: 24947 | loss: 0.011066
iter: 24948 | loss: 0.010872
iter: 24949 | loss: 0.010679
iter: 24950 | loss: 0.010485
iter: 24951 | loss: 0.010292
iter: 24952 | loss: 0.010099
iter: 24953 | loss: 0.009905
iter: 24954 | loss: 0.009712
iter: 24955 | loss: 0.009518
iter: 24956 | loss: 0.009325
iter: 24957 | loss: 0.009132
iter: 24958 | loss: 0.008938
iter: 24959 | loss: 0.008745
iter: 24960 | loss: 0.008552
iter: 24961 | loss: 0.008358
iter: 24962 | loss: 0.008165
iter: 24963 | loss: 0.007971
iter: 24964 | loss: 0.007778
iter: 24965 | loss: 0.007585
iter: 24966 | loss: 0.007391
iter: 24967 | loss: 0.007198
iter: 24968 | loss: 0.007004
iter: 24969 | loss: 0.006811
iter: 24970 | loss: 0.006618
iter: 24971 | loss: 0.006424
iter: 24972 | loss: 0.006231
iter: 24973 | loss: 0.006038
iter: 24974 | loss: 0.005844
iter: 24975 | loss: 0.005651
iter: 24976 | loss: 0.005457
iter: 24977 | loss: 0.005264
iter: 24978 | loss: 0.005071
iter: 24979 | loss: 0.004877
iter: 24980 | loss: 0.004684
iter: 24981 | loss: 0.004490
iter: 24982 | loss: 0.004297
iter: 24983 | loss: 0.004104
iter: 24984 | loss: 0.003910
iter: 24985 | loss: 0.003717
iter: 24986 | loss: 0.003523
iter: 24987 | loss: 0.003330
iter: 24988 | loss: 0.003137
iter: 24989 | loss: 0.002943
iter: 24990 | loss: 0.002750
iter: 24991 | loss: 0.002557
iter: 24992 | loss: 0.002363
iter: 24993 | loss: 0.002170
iter: 24994 | loss: 0.001976
iter: 24995 | loss: 0.001783
iter: 24996 | loss: 0.001590
iter: 24997 | loss: 0.001396
iter: 24998 | loss: 0.001203
iter: 24999 | loss: 0.001009
iter: 25000 | loss: 0.000816
- final loss: 0.000816
- (cd _build/default/examples/opt && ./pair.exe)
- 
step: 0 | loss: 6.298968841
step: 10 | loss: 6.292675339
step: 20 | loss: 6.285689562
step: 30 | loss: 6.278711954
step: 40 | loss: 6.271743041
step: 50 | loss: 6.264783076
step: 60 | loss: 6.257832135
step: 70 | loss: 6.250890188
step: 80 | loss: 6.243957155
step: 90 | loss: 6.237032931
step: 100 | loss: 6.230117402
step: 110 | loss: 6.223210449
step: 120 | loss: 6.216311949
step: 130 | loss: 6.209421780
step: 140 | loss: 6.202539820
step: 150 | loss: 6.195665946
step: 160 | loss: 6.188800037
step: 170 | loss: 6.181941970
step: 180 | loss: 6.175091626
step: 190 | loss: 6.168248885
step: 200 | loss: 6.161413629
step: 210 | loss: 6.154585743
step: 220 | loss: 6.147765110
step: 230 | loss: 6.140951620
step: 240 | loss: 6.134145162
step: 250 | loss: 6.127345628
step: 260 | loss: 6.120552914
step: 270 | loss: 6.113766917
step: 280 | loss: 6.106987538
step: 290 | loss: 6.100214681
step: 300 | loss: 6.093448255
step: 310 | loss: 6.086688169
step: 320 | loss: 6.079934338
step: 330 | loss: 6.073186680
step: 340 | loss: 6.066445116
step: 350 | loss: 6.059709572
step: 360 | loss: 6.052979976
step: 370 | loss: 6.046256261
step: 380 | loss: 6.039538362
step: 390 | loss: 6.032826220
step: 400 | loss: 6.026119777
step: 410 | loss: 6.019418979
step: 420 | loss: 6.012723776
step: 430 | loss: 6.006034121
step: 440 | loss: 5.999349969
step: 450 | loss: 5.992671278
step: 460 | loss: 5.985998011
step: 470 | loss: 5.979330129
step: 480 | loss: 5.972667600
step: 490 | loss: 5.966010392
step: 500 | loss: 5.959358475
step: 510 | loss: 5.952711822
step: 520 | loss: 5.946070407
step: 530 | loss: 5.939434205
step: 540 | loss: 5.932803194
step: 550 | loss: 5.926177352
step: 560 | loss: 5.919556660
step: 570 | loss: 5.912941098
step: 580 | loss: 5.906330648
step: 590 | loss: 5.899725293
step: 600 | loss: 5.893125016
step: 610 | loss: 5.886529803
step: 620 | loss: 5.879939638
step: 630 | loss: 5.873354506
step: 640 | loss: 5.866774393
step: 650 | loss: 5.860199286
step: 660 | loss: 5.853629172
step: 670 | loss: 5.847064037
step: 680 | loss: 5.840503869
step: 690 | loss: 5.833948655
step: 700 | loss: 5.827398383
step: 710 | loss: 5.820853040
step: 720 | loss: 5.814312615
step: 730 | loss: 5.807777096
step: 740 | loss: 5.801246469
step: 750 | loss: 5.794720725
step: 760 | loss: 5.788199850
step: 770 | loss: 5.781683833
step: 780 | loss: 5.775172662
step: 790 | loss: 5.768666325
step: 800 | loss: 5.762164810
step: 810 | loss: 5.755668106
step: 820 | loss: 5.749176200
step: 830 | loss: 5.742689081
step: 840 | loss: 5.736206737
step: 850 | loss: 5.729729155
step: 860 | loss: 5.723256323
step: 870 | loss: 5.716788230
step: 880 | loss: 5.710324864
step: 890 | loss: 5.703866211
step: 900 | loss: 5.697412261
step: 910 | loss: 5.690963000
step: 920 | loss: 5.684518416
step: 930 | loss: 5.678078498
step: 940 | loss: 5.671643232
step: 950 | loss: 5.665212606
step: 960 | loss: 5.658786607
step: 970 | loss: 5.652365224
step: 980 | loss: 5.645948443
step: 990 | loss: 5.639536252
step: 1000 | loss: 5.633128637
step: 1010 | loss: 5.626725587
step: 1020 | loss: 5.620327088
step: 1030 | loss: 5.613933128
step: 1040 | loss: 5.607543693
step: 1050 | loss: 5.601158771
step: 1060 | loss: 5.594778349
step: 1070 | loss: 5.588402414
step: 1080 | loss: 5.582030951
step: 1090 | loss: 5.575663950
step: 1100 | loss: 5.569301395
step: 1110 | loss: 5.562943275
step: 1120 | loss: 5.556589575
step: 1130 | loss: 5.550240283
step: 1140 | loss: 5.543895385
step: 1150 | loss: 5.537554868
step: 1160 | loss: 5.531218718
step: 1170 | loss: 5.524886922
step: 1180 | loss: 5.518559467
step: 1190 | loss: 5.512236338
step: 1200 | loss: 5.505917523
step: 1210 | loss: 5.499603007
step: 1220 | loss: 5.493292778
step: 1230 | loss: 5.486986821
step: 1240 | loss: 5.480685123
step: 1250 | loss: 5.474387671
step: 1260 | loss: 5.468094450
step: 1270 | loss: 5.461805446
step: 1280 | loss: 5.455520647
step: 1290 | loss: 5.449240037
step: 1300 | loss: 5.442963604
step: 1310 | loss: 5.436691334
step: 1320 | loss: 5.430423212
step: 1330 | loss: 5.424159226
step: 1340 | loss: 5.417899360
step: 1350 | loss: 5.411643601
step: 1360 | loss: 5.405391936
step: 1370 | loss: 5.399144350
step: 1380 | loss: 5.392900830
step: 1390 | loss: 5.386661361
step: 1400 | loss: 5.380425930
step: 1410 | loss: 5.374194523
step: 1420 | loss: 5.367967126
step: 1430 | loss: 5.361743725
step: 1440 | loss: 5.355524306
step: 1450 | loss: 5.349308855
step: 1460 | loss: 5.343097359
step: 1470 | loss: 5.336889803
step: 1480 | loss: 5.330686174
step: 1490 | loss: 5.324486458
step: 1500 | loss: 5.318290641
step: 1510 | loss: 5.312098709
step: 1520 | loss: 5.305910649
step: 1530 | loss: 5.299726446
step: 1540 | loss: 5.293546088
step: 1550 | loss: 5.287369560
step: 1560 | loss: 5.281196848
step: 1570 | loss: 5.275027940
step: 1580 | loss: 5.268862822
step: 1590 | loss: 5.262701479
step: 1600 | loss: 5.256543899
step: 1610 | loss: 5.250390068
step: 1620 | loss: 5.244239972
step: 1630 | loss: 5.238093599
step: 1640 | loss: 5.231950934
step: 1650 | loss: 5.225811966
step: 1660 | loss: 5.219676679
step: 1670 | loss: 5.213545062
step: 1680 | loss: 5.207417101
step: 1690 | loss: 5.201292783
step: 1700 | loss: 5.195172096
step: 1710 | loss: 5.189055025
step: 1720 | loss: 5.182941559
step: 1730 | loss: 5.176831684
step: 1740 | loss: 5.170725389
step: 1750 | loss: 5.164622659
step: 1760 | loss: 5.158523483
step: 1770 | loss: 5.152427849
step: 1780 | loss: 5.146335743
step: 1790 | loss: 5.140247154
step: 1800 | loss: 5.134162069
step: 1810 | loss: 5.128080475
step: 1820 | loss: 5.122002362
step: 1830 | loss: 5.115927717
step: 1840 | loss: 5.109856529
step: 1850 | loss: 5.103788784
step: 1860 | loss: 5.097724472
step: 1870 | loss: 5.091663582
step: 1880 | loss: 5.085606101
step: 1890 | loss: 5.079552018
step: 1900 | loss: 5.073501322
step: 1910 | loss: 5.067454002
step: 1920 | loss: 5.061410046
step: 1930 | loss: 5.055369444
step: 1940 | loss: 5.049332185
step: 1950 | loss: 5.043298258
step: 1960 | loss: 5.037267652
step: 1970 | loss: 5.031240358
step: 1980 | loss: 5.025216363
step: 1990 | loss: 5.019195659
step: 2000 | loss: 5.013178235
step: 2010 | loss: 5.007164080
step: 2020 | loss: 5.001153186
step: 2030 | loss: 4.995145541
step: 2040 | loss: 4.989141137
step: 2050 | loss: 4.983139964
step: 2060 | loss: 4.977142012
step: 2070 | loss: 4.971147272
step: 2080 | loss: 4.965155735
step: 2090 | loss: 4.959167391
step: 2100 | loss: 4.953182232
step: 2110 | loss: 4.947200248
step: 2120 | loss: 4.941221432
step: 2130 | loss: 4.935245773
step: 2140 | loss: 4.929273265
step: 2150 | loss: 4.923303898
step: 2160 | loss: 4.917337665
step: 2170 | loss: 4.911374556
step: 2180 | loss: 4.905414565
step: 2190 | loss: 4.899457682
step: 2200 | loss: 4.893503902
step: 2210 | loss: 4.887553215
step: 2220 | loss: 4.881605614
step: 2230 | loss: 4.875661092
step: 2240 | loss: 4.869719642
step: 2250 | loss: 4.863781256
step: 2260 | loss: 4.857845927
step: 2270 | loss: 4.851913649
step: 2280 | loss: 4.845984414
step: 2290 | loss: 4.840058217
step: 2300 | loss: 4.834135049
step: 2310 | loss: 4.828214906
step: 2320 | loss: 4.822297780
step: 2330 | loss: 4.816383665
step: 2340 | loss: 4.810472555
step: 2350 | loss: 4.804564444
step: 2360 | loss: 4.798659326
step: 2370 | loss: 4.792757196
step: 2380 | loss: 4.786858046
step: 2390 | loss: 4.780961873
step: 2400 | loss: 4.775068670
step: 2410 | loss: 4.769178432
step: 2420 | loss: 4.763291153
step: 2430 | loss: 4.757406829
step: 2440 | loss: 4.751525454
step: 2450 | loss: 4.745647022
step: 2460 | loss: 4.739771530
step: 2470 | loss: 4.733898972
step: 2480 | loss: 4.728029343
step: 2490 | loss: 4.722162638
step: 2500 | loss: 4.716298853
step: 2510 | loss: 4.710437984
step: 2520 | loss: 4.704580025
step: 2530 | loss: 4.698724973
step: 2540 | loss: 4.692872822
step: 2550 | loss: 4.687023569
step: 2560 | loss: 4.681177210
step: 2570 | loss: 4.675333739
step: 2580 | loss: 4.669493153
step: 2590 | loss: 4.663655449
step: 2600 | loss: 4.657820621
step: 2610 | loss: 4.651988666
step: 2620 | loss: 4.646159580
step: 2630 | loss: 4.640333359
step: 2640 | loss: 4.634510000
step: 2650 | loss: 4.628689498
step: 2660 | loss: 4.622871850
step: 2670 | loss: 4.617057052
step: 2680 | loss: 4.611245100
step: 2690 | loss: 4.605435991
step: 2700 | loss: 4.599629721
step: 2710 | loss: 4.593826287
step: 2720 | loss: 4.588025685
step: 2730 | loss: 4.582227911
step: 2740 | loss: 4.576432962
step: 2750 | loss: 4.570640835
step: 2760 | loss: 4.564851526
step: 2770 | loss: 4.559065031
step: 2780 | loss: 4.553281348
step: 2790 | loss: 4.547500473
step: 2800 | loss: 4.541722401
step: 2810 | loss: 4.535947131
step: 2820 | loss: 4.530174658
step: 2830 | loss: 4.524404980
step: 2840 | loss: 4.518638092
step: 2850 | loss: 4.512873991
step: 2860 | loss: 4.507112674
step: 2870 | loss: 4.501354138
step: 2880 | loss: 4.495598379
step: 2890 | loss: 4.489845394
step: 2900 | loss: 4.484095179
step: 2910 | loss: 4.478347731
step: 2920 | loss: 4.472603046
step: 2930 | loss: 4.466861122
step: 2940 | loss: 4.461121953
step: 2950 | loss: 4.455385538
step: 2960 | loss: 4.449651872
step: 2970 | loss: 4.443920952
step: 2980 | loss: 4.438192775
step: 2990 | loss: 4.432467337
step: 3000 | loss: 4.426744633
step: 3010 | loss: 4.421024662
step: 3020 | loss: 4.415307418
step: 3030 | loss: 4.409592898
step: 3040 | loss: 4.403881100
step: 3050 | loss: 4.398172018
step: 3060 | loss: 4.392465649
step: 3070 | loss: 4.386761990
step: 3080 | loss: 4.381061036
step: 3090 | loss: 4.375362783
step: 3100 | loss: 4.369667229
step: 3110 | loss: 4.363974368
step: 3120 | loss: 4.358284198
step: 3130 | loss: 4.352596713
step: 3140 | loss: 4.346911910
step: 3150 | loss: 4.341229785
step: 3160 | loss: 4.335550334
step: 3170 | loss: 4.329873552
step: 3180 | loss: 4.324199436
step: 3190 | loss: 4.318527981
step: 3200 | loss: 4.312859183
step: 3210 | loss: 4.307193038
step: 3220 | loss: 4.301529541
step: 3230 | loss: 4.295868688
step: 3240 | loss: 4.290210475
step: 3250 | loss: 4.284554897
step: 3260 | loss: 4.278901950
step: 3270 | loss: 4.273251628
step: 3280 | loss: 4.267603929
step: 3290 | loss: 4.261958846
step: 3300 | loss: 4.256316375
step: 3310 | loss: 4.250676512
step: 3320 | loss: 4.245039252
step: 3330 | loss: 4.239404590
step: 3340 | loss: 4.233772522
step: 3350 | loss: 4.228143042
step: 3360 | loss: 4.222516145
step: 3370 | loss: 4.216891827
step: 3380 | loss: 4.211270083
step: 3390 | loss: 4.205650908
step: 3400 | loss: 4.200034296
step: 3410 | loss: 4.194420242
step: 3420 | loss: 4.188808742
step: 3430 | loss: 4.183199790
step: 3440 | loss: 4.177593382
step: 3450 | loss: 4.171989511
step: 3460 | loss: 4.166388173
step: 3470 | loss: 4.160789362
step: 3480 | loss: 4.155193072
step: 3490 | loss: 4.149599300
step: 3500 | loss: 4.144008038
step: 3510 | loss: 4.138419283
step: 3520 | loss: 4.132833027
step: 3530 | loss: 4.127249267
step: 3540 | loss: 4.121667995
step: 3550 | loss: 4.116089207
step: 3560 | loss: 4.110512897
step: 3570 | loss: 4.104939060
step: 3580 | loss: 4.099367689
step: 3590 | loss: 4.093798779
step: 3600 | loss: 4.088232325
step: 3610 | loss: 4.082668321
step: 3620 | loss: 4.077106760
step: 3630 | loss: 4.071547638
step: 3640 | loss: 4.065990948
step: 3650 | loss: 4.060436684
step: 3660 | loss: 4.054884842
step: 3670 | loss: 4.049335414
step: 3680 | loss: 4.043788395
step: 3690 | loss: 4.038243779
step: 3700 | loss: 4.032701561
step: 3710 | loss: 4.027161733
step: 3720 | loss: 4.021624292
step: 3730 | loss: 4.016089229
step: 3740 | loss: 4.010556540
step: 3750 | loss: 4.005026219
step: 3760 | loss: 3.999498259
step: 3770 | loss: 3.993972655
step: 3780 | loss: 3.988449401
step: 3790 | loss: 3.982928490
step: 3800 | loss: 3.977409917
step: 3810 | loss: 3.971893676
step: 3820 | loss: 3.966379760
step: 3830 | loss: 3.960868164
step: 3840 | loss: 3.955358882
step: 3850 | loss: 3.949851908
step: 3860 | loss: 3.944347235
step: 3870 | loss: 3.938844859
step: 3880 | loss: 3.933344772
step: 3890 | loss: 3.927846970
step: 3900 | loss: 3.922351445
step: 3910 | loss: 3.916858193
step: 3920 | loss: 3.911367207
step: 3930 | loss: 3.905878482
step: 3940 | loss: 3.900392011
step: 3950 | loss: 3.894907789
step: 3960 | loss: 3.889425810
step: 3970 | loss: 3.883946068
step: 3980 | loss: 3.878468557
step: 3990 | loss: 3.872993272
step: 4000 | loss: 3.867520208
step: 4010 | loss: 3.862049357
step: 4020 | loss: 3.856580715
step: 4030 | loss: 3.851114277
step: 4040 | loss: 3.845650036
step: 4050 | loss: 3.840187987
step: 4060 | loss: 3.834728124
step: 4070 | loss: 3.829270443
step: 4080 | loss: 3.823814937
step: 4090 | loss: 3.818361602
step: 4100 | loss: 3.812910431
step: 4110 | loss: 3.807461421
step: 4120 | loss: 3.802014565
step: 4130 | loss: 3.796569858
step: 4140 | loss: 3.791127296
step: 4150 | loss: 3.785686873
step: 4160 | loss: 3.780248584
step: 4170 | loss: 3.774812424
step: 4180 | loss: 3.769378389
step: 4190 | loss: 3.763946473
step: 4200 | loss: 3.758516673
step: 4210 | loss: 3.753088983
step: 4220 | loss: 3.747663398
step: 4230 | loss: 3.742239914
step: 4240 | loss: 3.736818527
step: 4250 | loss: 3.731399232
step: 4260 | loss: 3.725982025
step: 4270 | loss: 3.720566901
step: 4280 | loss: 3.715153857
step: 4290 | loss: 3.709742888
step: 4300 | loss: 3.704333990
step: 4310 | loss: 3.698927160
step: 4320 | loss: 3.693522393
step: 4330 | loss: 3.688119686
step: 4340 | loss: 3.682719035
step: 4350 | loss: 3.677320436
step: 4360 | loss: 3.671923887
step: 4370 | loss: 3.666529382
step: 4380 | loss: 3.661136920
step: 4390 | loss: 3.655746497
step: 4400 | loss: 3.650358110
step: 4410 | loss: 3.644971755
step: 4420 | loss: 3.639587430
step: 4430 | loss: 3.634205132
step: 4440 | loss: 3.628824858
step: 4450 | loss: 3.623446606
step: 4460 | loss: 3.618070372
step: 4470 | loss: 3.612696155
step: 4480 | loss: 3.607323952
step: 4490 | loss: 3.601953761
step: 4500 | loss: 3.596585579
step: 4510 | loss: 3.591219405
step: 4520 | loss: 3.585855237
step: 4530 | loss: 3.580493073
step: 4540 | loss: 3.575132911
step: 4550 | loss: 3.569774749
step: 4560 | loss: 3.564418586
step: 4570 | loss: 3.559064421
step: 4580 | loss: 3.553712252
step: 4590 | loss: 3.548362078
step: 4600 | loss: 3.543013898
step: 4610 | loss: 3.537667711
step: 4620 | loss: 3.532323516
step: 4630 | loss: 3.526981313
step: 4640 | loss: 3.521641100
step: 4650 | loss: 3.516302878
step: 4660 | loss: 3.510966645
step: 4670 | loss: 3.505632402
step: 4680 | loss: 3.500300148
step: 4690 | loss: 3.494969883
step: 4700 | loss: 3.489641608
step: 4710 | loss: 3.484315322
step: 4720 | loss: 3.478991026
step: 4730 | loss: 3.473668720
step: 4740 | loss: 3.468348404
step: 4750 | loss: 3.463030080
step: 4760 | loss: 3.457713747
step: 4770 | loss: 3.452399406
step: 4780 | loss: 3.447087060
step: 4790 | loss: 3.441776707
step: 4800 | loss: 3.436468351
step: 4810 | loss: 3.431161991
step: 4820 | loss: 3.425857629
step: 4830 | loss: 3.420555268
step: 4840 | loss: 3.415254907
step: 4850 | loss: 3.409956550
step: 4860 | loss: 3.404660197
step: 4870 | loss: 3.399365850
step: 4880 | loss: 3.394073513
step: 4890 | loss: 3.388783185
step: 4900 | loss: 3.383494871
step: 4910 | loss: 3.378208572
step: 4920 | loss: 3.372924290
step: 4930 | loss: 3.367642029
step: 4940 | loss: 3.362361789
step: 4950 | loss: 3.357083576
step: 4960 | loss: 3.351807390
step: 4970 | loss: 3.346533235
step: 4980 | loss: 3.341261114
step: 4990 | loss: 3.335991030
step: 5000 | loss: 3.330722986
step: 5010 | loss: 3.325456985
step: 5020 | loss: 3.320193031
step: 5030 | loss: 3.314931127
step: 5040 | loss: 3.309671277
step: 5050 | loss: 3.304413484
step: 5060 | loss: 3.299157752
step: 5070 | loss: 3.293904084
step: 5080 | loss: 3.288652485
step: 5090 | loss: 3.283402959
step: 5100 | loss: 3.278155509
step: 5110 | loss: 3.272910139
step: 5120 | loss: 3.267666854
step: 5130 | loss: 3.262425658
step: 5140 | loss: 3.257186556
step: 5150 | loss: 3.251949551
step: 5160 | loss: 3.246714648
step: 5170 | loss: 3.241481852
step: 5180 | loss: 3.236251167
step: 5190 | loss: 3.231022598
step: 5200 | loss: 3.225796149
step: 5210 | loss: 3.220571826
step: 5220 | loss: 3.215349634
step: 5230 | loss: 3.210129577
step: 5240 | loss: 3.204911660
step: 5250 | loss: 3.199695889
step: 5260 | loss: 3.194482268
step: 5270 | loss: 3.189270802
step: 5280 | loss: 3.184061498
step: 5290 | loss: 3.178854360
step: 5300 | loss: 3.173649393
step: 5310 | loss: 3.168446604
step: 5320 | loss: 3.163245996
step: 5330 | loss: 3.158047577
step: 5340 | loss: 3.152851351
step: 5350 | loss: 3.147657324
step: 5360 | loss: 3.142465502
step: 5370 | loss: 3.137275891
step: 5380 | loss: 3.132088495
step: 5390 | loss: 3.126903321
step: 5400 | loss: 3.121720376
step: 5410 | loss: 3.116539664
step: 5420 | loss: 3.111361191
step: 5430 | loss: 3.106184964
step: 5440 | loss: 3.101010989
step: 5450 | loss: 3.095839271
step: 5460 | loss: 3.090669817
step: 5470 | loss: 3.085502632
step: 5480 | loss: 3.080337723
step: 5490 | loss: 3.075175097
step: 5500 | loss: 3.070014758
step: 5510 | loss: 3.064856715
step: 5520 | loss: 3.059700972
step: 5530 | loss: 3.054547536
step: 5540 | loss: 3.049396413
step: 5550 | loss: 3.044247610
step: 5560 | loss: 3.039101133
step: 5570 | loss: 3.033956989
step: 5580 | loss: 3.028815184
step: 5590 | loss: 3.023675725
step: 5600 | loss: 3.018538617
step: 5610 | loss: 3.013403868
step: 5620 | loss: 3.008271484
step: 5630 | loss: 3.003141471
step: 5640 | loss: 2.998013837
step: 5650 | loss: 2.992888587
step: 5660 | loss: 2.987765729
step: 5670 | loss: 2.982645268
step: 5680 | loss: 2.977527213
step: 5690 | loss: 2.972411568
step: 5700 | loss: 2.967298342
step: 5710 | loss: 2.962187541
step: 5720 | loss: 2.957079171
step: 5730 | loss: 2.951973239
step: 5740 | loss: 2.946869752
step: 5750 | loss: 2.941768717
step: 5760 | loss: 2.936670140
step: 5770 | loss: 2.931574029
step: 5780 | loss: 2.926480390
step: 5790 | loss: 2.921389230
step: 5800 | loss: 2.916300556
step: 5810 | loss: 2.911214374
step: 5820 | loss: 2.906130692
step: 5830 | loss: 2.901049516
step: 5840 | loss: 2.895970853
step: 5850 | loss: 2.890894710
step: 5860 | loss: 2.885821095
step: 5870 | loss: 2.880750013
step: 5880 | loss: 2.875681472
step: 5890 | loss: 2.870615478
step: 5900 | loss: 2.865552039
step: 5910 | loss: 2.860491161
step: 5920 | loss: 2.855432852
step: 5930 | loss: 2.850377118
step: 5940 | loss: 2.845323967
step: 5950 | loss: 2.840273404
step: 5960 | loss: 2.835225437
step: 5970 | loss: 2.830180074
step: 5980 | loss: 2.825137320
step: 5990 | loss: 2.820097183
step: 6000 | loss: 2.815059670
step: 6010 | loss: 2.810024788
step: 6020 | loss: 2.804992543
step: 6030 | loss: 2.799962942
step: 6040 | loss: 2.794935993
step: 6050 | loss: 2.789911703
step: 6060 | loss: 2.784890077
step: 6070 | loss: 2.779871124
step: 6080 | loss: 2.774854850
step: 6090 | loss: 2.769841262
step: 6100 | loss: 2.764830366
step: 6110 | loss: 2.759822170
step: 6120 | loss: 2.754816681
step: 6130 | loss: 2.749813906
step: 6140 | loss: 2.744813850
step: 6150 | loss: 2.739816522
step: 6160 | loss: 2.734821928
step: 6170 | loss: 2.729830074
step: 6180 | loss: 2.724840968
step: 6190 | loss: 2.719854617
step: 6200 | loss: 2.714871026
step: 6210 | loss: 2.709890204
step: 6220 | loss: 2.704912156
step: 6230 | loss: 2.699936890
step: 6240 | loss: 2.694964412
step: 6250 | loss: 2.689994729
step: 6260 | loss: 2.685027848
step: 6270 | loss: 2.680063775
step: 6280 | loss: 2.675102517
step: 6290 | loss: 2.670144080
step: 6300 | loss: 2.665188472
step: 6310 | loss: 2.660235698
step: 6320 | loss: 2.655285766
step: 6330 | loss: 2.650338682
step: 6340 | loss: 2.645394452
step: 6350 | loss: 2.640453084
step: 6360 | loss: 2.635514582
step: 6370 | loss: 2.630578955
step: 6380 | loss: 2.625646208
step: 6390 | loss: 2.620716348
step: 6400 | loss: 2.615789381
step: 6410 | loss: 2.610865313
step: 6420 | loss: 2.605944151
step: 6430 | loss: 2.601025902
step: 6440 | loss: 2.596110570
step: 6450 | loss: 2.591198164
step: 6460 | loss: 2.586288688
step: 6470 | loss: 2.581382149
step: 6480 | loss: 2.576478553
step: 6490 | loss: 2.571577906
step: 6500 | loss: 2.566680214
step: 6510 | loss: 2.561785484
step: 6520 | loss: 2.556893721
step: 6530 | loss: 2.552004931
step: 6540 | loss: 2.547119120
step: 6550 | loss: 2.542236293
step: 6560 | loss: 2.537356458
step: 6570 | loss: 2.532479619
step: 6580 | loss: 2.527605782
step: 6590 | loss: 2.522734953
step: 6600 | loss: 2.517867137
step: 6610 | loss: 2.513002340
step: 6620 | loss: 2.508140568
step: 6630 | loss: 2.503281826
step: 6640 | loss: 2.498426120
step: 6650 | loss: 2.493573454
step: 6660 | loss: 2.488723834
step: 6670 | loss: 2.483877266
step: 6680 | loss: 2.479033755
step: 6690 | loss: 2.474193305
step: 6700 | loss: 2.469355922
step: 6710 | loss: 2.464521611
step: 6720 | loss: 2.459690377
step: 6730 | loss: 2.454862225
step: 6740 | loss: 2.450037160
step: 6750 | loss: 2.445215186
step: 6760 | loss: 2.440396308
step: 6770 | loss: 2.435580531
step: 6780 | loss: 2.430767860
step: 6790 | loss: 2.425958298
step: 6800 | loss: 2.421151851
step: 6810 | loss: 2.416348522
step: 6820 | loss: 2.411548317
step: 6830 | loss: 2.406751239
step: 6840 | loss: 2.401957293
step: 6850 | loss: 2.397166482
step: 6860 | loss: 2.392378810
step: 6870 | loss: 2.387594282
step: 6880 | loss: 2.382812902
step: 6890 | loss: 2.378034672
step: 6900 | loss: 2.373259597
step: 6910 | loss: 2.368487680
step: 6920 | loss: 2.363718926
step: 6930 | loss: 2.358953336
step: 6940 | loss: 2.354190915
step: 6950 | loss: 2.349431666
step: 6960 | loss: 2.344675591
step: 6970 | loss: 2.339922695
step: 6980 | loss: 2.335172979
step: 6990 | loss: 2.330426448
step: 7000 | loss: 2.325683102
step: 7010 | loss: 2.320942946
step: 7020 | loss: 2.316205982
step: 7030 | loss: 2.311472212
step: 7040 | loss: 2.306741638
step: 7050 | loss: 2.302014263
step: 7060 | loss: 2.297290089
step: 7070 | loss: 2.292569118
step: 7080 | loss: 2.287851351
step: 7090 | loss: 2.283136791
step: 7100 | loss: 2.278425440
step: 7110 | loss: 2.273717298
step: 7120 | loss: 2.269012368
step: 7130 | loss: 2.264310650
step: 7140 | loss: 2.259612146
step: 7150 | loss: 2.254916858
step: 7160 | loss: 2.250224785
step: 7170 | loss: 2.245535929
step: 7180 | loss: 2.240850290
step: 7190 | loss: 2.236167869
step: 7200 | loss: 2.231488667
step: 7210 | loss: 2.226812684
step: 7220 | loss: 2.222139920
step: 7230 | loss: 2.217470375
step: 7240 | loss: 2.212804049
step: 7250 | loss: 2.208140942
step: 7260 | loss: 2.203481054
step: 7270 | loss: 2.198824383
step: 7280 | loss: 2.194170930
step: 7290 | loss: 2.189520694
step: 7300 | loss: 2.184873673
step: 7310 | loss: 2.180229866
step: 7320 | loss: 2.175589273
step: 7330 | loss: 2.170951892
step: 7340 | loss: 2.166317722
step: 7350 | loss: 2.161686760
step: 7360 | loss: 2.157059006
step: 7370 | loss: 2.152434456
step: 7380 | loss: 2.147813109
step: 7390 | loss: 2.143194962
step: 7400 | loss: 2.138580014
step: 7410 | loss: 2.133968261
step: 7420 | loss: 2.129359701
step: 7430 | loss: 2.124754330
step: 7440 | loss: 2.120152145
step: 7450 | loss: 2.115553144
step: 7460 | loss: 2.110957323
step: 7470 | loss: 2.106364677
step: 7480 | loss: 2.101775204
step: 7490 | loss: 2.097188899
step: 7500 | loss: 2.092605758
step: 7510 | loss: 2.088025777
step: 7520 | loss: 2.083448951
step: 7530 | loss: 2.078875275
step: 7540 | loss: 2.074304745
step: 7550 | loss: 2.069737355
step: 7560 | loss: 2.065173100
step: 7570 | loss: 2.060611975
step: 7580 | loss: 2.056053974
step: 7590 | loss: 2.051499092
step: 7600 | loss: 2.046947321
step: 7610 | loss: 2.042398657
step: 7620 | loss: 2.037853092
step: 7630 | loss: 2.033310620
step: 7640 | loss: 2.028771235
step: 7650 | loss: 2.024234928
step: 7660 | loss: 2.019701694
step: 7670 | loss: 2.015171524
step: 7680 | loss: 2.010644411
step: 7690 | loss: 2.006120347
step: 7700 | loss: 2.001599325
step: 7710 | loss: 1.997081335
step: 7720 | loss: 1.992566370
step: 7730 | loss: 1.988054422
step: 7740 | loss: 1.983545480
step: 7750 | loss: 1.979039537
step: 7760 | loss: 1.974536582
step: 7770 | loss: 1.970036608
step: 7780 | loss: 1.965539603
step: 7790 | loss: 1.961045558
step: 7800 | loss: 1.956554464
step: 7810 | loss: 1.952066309
step: 7820 | loss: 1.947581084
step: 7830 | loss: 1.943098777
step: 7840 | loss: 1.938619378
step: 7850 | loss: 1.934142876
step: 7860 | loss: 1.929669259
step: 7870 | loss: 1.925198516
step: 7880 | loss: 1.920730636
step: 7890 | loss: 1.916265606
step: 7900 | loss: 1.911803413
step: 7910 | loss: 1.907344047
step: 7920 | loss: 1.902887494
step: 7930 | loss: 1.898433742
step: 7940 | loss: 1.893982777
step: 7950 | loss: 1.889534586
step: 7960 | loss: 1.885089156
step: 7970 | loss: 1.880646474
step: 7980 | loss: 1.876206526
step: 7990 | loss: 1.871769297
step: 8000 | loss: 1.867334773
step: 8010 | loss: 1.862902940
step: 8020 | loss: 1.858473784
step: 8030 | loss: 1.854047290
step: 8040 | loss: 1.849623442
step: 8050 | loss: 1.845202225
step: 8060 | loss: 1.840783625
step: 8070 | loss: 1.836367624
step: 8080 | loss: 1.831954209
step: 8090 | loss: 1.827543362
step: 8100 | loss: 1.823135067
step: 8110 | loss: 1.818729309
step: 8120 | loss: 1.814326070
step: 8130 | loss: 1.809925334
step: 8140 | loss: 1.805527084
step: 8150 | loss: 1.801131303
step: 8160 | loss: 1.796737973
step: 8170 | loss: 1.792347078
step: 8180 | loss: 1.787958599
step: 8190 | loss: 1.783572518
step: 8200 | loss: 1.779188819
step: 8210 | loss: 1.774807482
step: 8220 | loss: 1.770428489
step: 8230 | loss: 1.766051822
step: 8240 | loss: 1.761677463
step: 8250 | loss: 1.757305392
step: 8260 | loss: 1.752935591
step: 8270 | loss: 1.748568040
step: 8280 | loss: 1.744202721
step: 8290 | loss: 1.739839614
step: 8300 | loss: 1.735478700
step: 8310 | loss: 1.731119958
step: 8320 | loss: 1.726763370
step: 8330 | loss: 1.722408916
step: 8340 | loss: 1.718056575
step: 8350 | loss: 1.713706327
step: 8360 | loss: 1.709358153
step: 8370 | loss: 1.705012031
step: 8380 | loss: 1.700667942
step: 8390 | loss: 1.696325865
step: 8400 | loss: 1.691985780
step: 8410 | loss: 1.687647665
step: 8420 | loss: 1.683311500
step: 8430 | loss: 1.678977265
step: 8440 | loss: 1.674644937
step: 8450 | loss: 1.670314497
step: 8460 | loss: 1.665985923
step: 8470 | loss: 1.661659194
step: 8480 | loss: 1.657334289
step: 8490 | loss: 1.653011187
step: 8500 | loss: 1.648689866
step: 8510 | loss: 1.644370305
step: 8520 | loss: 1.640052483
step: 8530 | loss: 1.635736378
step: 8540 | loss: 1.631421970
step: 8550 | loss: 1.627109236
step: 8560 | loss: 1.622798155
step: 8570 | loss: 1.618488706
step: 8580 | loss: 1.614180868
step: 8590 | loss: 1.609874618
step: 8600 | loss: 1.605569937
step: 8610 | loss: 1.601266801
step: 8620 | loss: 1.596965190
step: 8630 | loss: 1.592665083
step: 8640 | loss: 1.588366458
step: 8650 | loss: 1.584069295
step: 8660 | loss: 1.579773571
step: 8670 | loss: 1.575479265
step: 8680 | loss: 1.571186358
step: 8690 | loss: 1.566894827
step: 8700 | loss: 1.562604652
step: 8710 | loss: 1.558315811
step: 8720 | loss: 1.554028285
step: 8730 | loss: 1.549742052
step: 8740 | loss: 1.545457091
step: 8750 | loss: 1.541173383
step: 8760 | loss: 1.536890907
step: 8770 | loss: 1.532609642
step: 8780 | loss: 1.528329568
step: 8790 | loss: 1.524050666
step: 8800 | loss: 1.519772915
step: 8810 | loss: 1.515496296
step: 8820 | loss: 1.511220789
step: 8830 | loss: 1.506946374
step: 8840 | loss: 1.502673032
step: 8850 | loss: 1.498400744
step: 8860 | loss: 1.494129491
step: 8870 | loss: 1.489859254
step: 8880 | loss: 1.485590014
step: 8890 | loss: 1.481321753
step: 8900 | loss: 1.477054452
step: 8910 | loss: 1.472788092
step: 8920 | loss: 1.468522657
step: 8930 | loss: 1.464258129
step: 8940 | loss: 1.459994488
step: 8950 | loss: 1.455731719
step: 8960 | loss: 1.451469804
step: 8970 | loss: 1.447208726
step: 8980 | loss: 1.442948468
step: 8990 | loss: 1.438689013
step: 9000 | loss: 1.434430346
step: 9010 | loss: 1.430172449
step: 9020 | loss: 1.425915307
step: 9030 | loss: 1.421658905
step: 9040 | loss: 1.417403226
step: 9050 | loss: 1.413148255
step: 9060 | loss: 1.408893977
step: 9070 | loss: 1.404640378
step: 9080 | loss: 1.400387443
step: 9090 | loss: 1.396135157
step: 9100 | loss: 1.391883507
step: 9110 | loss: 1.387632478
step: 9120 | loss: 1.383382056
step: 9130 | loss: 1.379132229
step: 9140 | loss: 1.374882983
step: 9150 | loss: 1.370634305
step: 9160 | loss: 1.366386182
step: 9170 | loss: 1.362138603
step: 9180 | loss: 1.357891553
step: 9190 | loss: 1.353645023
step: 9200 | loss: 1.349399000
step: 9210 | loss: 1.345153471
step: 9220 | loss: 1.340908427
step: 9230 | loss: 1.336663856
step: 9240 | loss: 1.332419747
step: 9250 | loss: 1.328176090
step: 9260 | loss: 1.323932873
step: 9270 | loss: 1.319690088
step: 9280 | loss: 1.315447724
step: 9290 | loss: 1.311205772
step: 9300 | loss: 1.306964222
step: 9310 | loss: 1.302723064
step: 9320 | loss: 1.298482290
step: 9330 | loss: 1.294241892
step: 9340 | loss: 1.290001859
step: 9350 | loss: 1.285762185
step: 9360 | loss: 1.281522861
step: 9370 | loss: 1.277283879
step: 9380 | loss: 1.273045231
step: 9390 | loss: 1.268806911
step: 9400 | loss: 1.264568909
step: 9410 | loss: 1.260331220
step: 9420 | loss: 1.256093836
step: 9430 | loss: 1.251856751
step: 9440 | loss: 1.247619958
step: 9450 | loss: 1.243383451
step: 9460 | loss: 1.239147223
step: 9470 | loss: 1.234911268
step: 9480 | loss: 1.230675582
step: 9490 | loss: 1.226440157
step: 9500 | loss: 1.222204989
step: 9510 | loss: 1.217970071
step: 9520 | loss: 1.213735400
step: 9530 | loss: 1.209500969
step: 9540 | loss: 1.205266775
step: 9550 | loss: 1.201032812
step: 9560 | loss: 1.196799075
step: 9570 | loss: 1.192565560
step: 9580 | loss: 1.188332264
step: 9590 | loss: 1.184099180
step: 9600 | loss: 1.179866307
step: 9610 | loss: 1.175633639
step: 9620 | loss: 1.171401173
step: 9630 | loss: 1.167168905
step: 9640 | loss: 1.162936832
step: 9650 | loss: 1.158704949
step: 9660 | loss: 1.154473255
step: 9670 | loss: 1.150241744
step: 9680 | loss: 1.146010415
step: 9690 | loss: 1.141779265
step: 9700 | loss: 1.137548289
step: 9710 | loss: 1.133317486
step: 9720 | loss: 1.129086852
step: 9730 | loss: 1.124856386
step: 9740 | loss: 1.120626083
step: 9750 | loss: 1.116395942
step: 9760 | loss: 1.112165960
step: 9770 | loss: 1.107936135
step: 9780 | loss: 1.103706465
step: 9790 | loss: 1.099476947
step: 9800 | loss: 1.095247579
step: 9810 | loss: 1.091018358
step: 9820 | loss: 1.086789284
step: 9830 | loss: 1.082560353
step: 9840 | loss: 1.078331564
step: 9850 | loss: 1.074102915
step: 9860 | loss: 1.069874404
step: 9870 | loss: 1.065646029
step: 9880 | loss: 1.061417788
step: 9890 | loss: 1.057189680
step: 9900 | loss: 1.052961704
step: 9910 | loss: 1.048733856
step: 9920 | loss: 1.044506137
step: 9930 | loss: 1.040278544
step: 9940 | loss: 1.036051075
step: 9950 | loss: 1.031823730
step: 9960 | loss: 1.027596506
step: 9970 | loss: 1.023369403
step: 9980 | loss: 1.019142418
step: 9990 | loss: 1.014915552
step: 10000 | loss: 1.010688801
step: 10010 | loss: 1.006462165
step: 10020 | loss: 1.002235643
step: 10030 | loss: 0.998009233
step: 10040 | loss: 0.993782935
step: 10050 | loss: 0.989556746
step: 10060 | loss: 0.985330666
step: 10070 | loss: 0.981104693
step: 10080 | loss: 0.976878827
step: 10090 | loss: 0.972653066
step: 10100 | loss: 0.968427409
step: 10110 | loss: 0.964201854
step: 10120 | loss: 0.959976402
step: 10130 | loss: 0.955751051
step: 10140 | loss: 0.951525799
step: 10150 | loss: 0.947300646
step: 10160 | loss: 0.943075591
step: 10170 | loss: 0.938850632
step: 10180 | loss: 0.934625769
step: 10190 | loss: 0.930401001
step: 10200 | loss: 0.926176326
step: 10210 | loss: 0.921951744
step: 10220 | loss: 0.917727254
step: 10230 | loss: 0.913502854
step: 10240 | loss: 0.909278545
step: 10250 | loss: 0.905054325
step: 10260 | loss: 0.900830192
step: 10270 | loss: 0.896606147
step: 10280 | loss: 0.892382188
step: 10290 | loss: 0.888158315
step: 10300 | loss: 0.883934526
step: 10310 | loss: 0.879710821
step: 10320 | loss: 0.875487199
step: 10330 | loss: 0.871263659
step: 10340 | loss: 0.867040200
step: 10350 | loss: 0.862816822
step: 10360 | loss: 0.858593523
step: 10370 | loss: 0.854370303
step: 10380 | loss: 0.850147161
step: 10390 | loss: 0.845924096
step: 10400 | loss: 0.841701107
step: 10410 | loss: 0.837478195
step: 10420 | loss: 0.833255357
step: 10430 | loss: 0.829032593
step: 10440 | loss: 0.824809903
step: 10450 | loss: 0.820587285
step: 10460 | loss: 0.816364740
step: 10470 | loss: 0.812142266
step: 10480 | loss: 0.807919862
step: 10490 | loss: 0.803697528
step: 10500 | loss: 0.799475263
step: 10510 | loss: 0.795253066
step: 10520 | loss: 0.791030938
step: 10530 | loss: 0.786808876
step: 10540 | loss: 0.782586881
step: 10550 | loss: 0.778364951
step: 10560 | loss: 0.774143087
step: 10570 | loss: 0.769921287
step: 10580 | loss: 0.765699550
step: 10590 | loss: 0.761477877
step: 10600 | loss: 0.757256267
step: 10610 | loss: 0.753034718
step: 10620 | loss: 0.748813230
step: 10630 | loss: 0.744591804
step: 10640 | loss: 0.740370437
step: 10650 | loss: 0.736149129
step: 10660 | loss: 0.731927881
step: 10670 | loss: 0.727706691
step: 10680 | loss: 0.723485558
step: 10690 | loss: 0.719264483
step: 10700 | loss: 0.715043464
step: 10710 | loss: 0.710822501
step: 10720 | loss: 0.706601593
step: 10730 | loss: 0.702380741
step: 10740 | loss: 0.698159942
step: 10750 | loss: 0.693939198
step: 10760 | loss: 0.689718506
step: 10770 | loss: 0.685497868
step: 10780 | loss: 0.681277281
step: 10790 | loss: 0.677056746
step: 10800 | loss: 0.672836262
step: 10810 | loss: 0.668615829
step: 10820 | loss: 0.664395446
step: 10830 | loss: 0.660175113
step: 10840 | loss: 0.655954828
step: 10850 | loss: 0.651734593
step: 10860 | loss: 0.647514405
step: 10870 | loss: 0.643294265
step: 10880 | loss: 0.639074173
step: 10890 | loss: 0.634854127
step: 10900 | loss: 0.630634127
step: 10910 | loss: 0.626414173
step: 10920 | loss: 0.622194264
step: 10930 | loss: 0.617974400
step: 10940 | loss: 0.613754581
step: 10950 | loss: 0.609534806
step: 10960 | loss: 0.605315074
step: 10970 | loss: 0.601095385
step: 10980 | loss: 0.596875739
step: 10990 | loss: 0.592656135
step: 11000 | loss: 0.588436573
step: 11010 | loss: 0.584217053
step: 11020 | loss: 0.579997573
step: 11030 | loss: 0.575778134
step: 11040 | loss: 0.571558736
step: 11050 | loss: 0.567339377
step: 11060 | loss: 0.563120057
step: 11070 | loss: 0.558900776
step: 11080 | loss: 0.554681534
step: 11090 | loss: 0.550462331
step: 11100 | loss: 0.546243165
step: 11110 | loss: 0.542024036
step: 11120 | loss: 0.537804945
step: 11130 | loss: 0.533585890
step: 11140 | loss: 0.529366872
step: 11150 | loss: 0.525147889
step: 11160 | loss: 0.520928943
step: 11170 | loss: 0.516710031
step: 11180 | loss: 0.512491155
step: 11190 | loss: 0.508272313
step: 11200 | loss: 0.504053505
step: 11210 | loss: 0.499834731
step: 11220 | loss: 0.495615991
step: 11230 | loss: 0.491397283
step: 11240 | loss: 0.487178609
step: 11250 | loss: 0.482959968
step: 11260 | loss: 0.478741358
step: 11270 | loss: 0.474522781
step: 11280 | loss: 0.470304235
step: 11290 | loss: 0.466085720
step: 11300 | loss: 0.461867236
step: 11310 | loss: 0.457648783
step: 11320 | loss: 0.453430360
step: 11330 | loss: 0.449211968
step: 11340 | loss: 0.444993605
step: 11350 | loss: 0.440775271
step: 11360 | loss: 0.436556967
step: 11370 | loss: 0.432338691
step: 11380 | loss: 0.428120444
step: 11390 | loss: 0.423902226
step: 11400 | loss: 0.419684035
step: 11410 | loss: 0.415465872
step: 11420 | loss: 0.411247736
step: 11430 | loss: 0.407029628
step: 11440 | loss: 0.402811547
step: 11450 | loss: 0.398593492
step: 11460 | loss: 0.394375464
step: 11470 | loss: 0.390157461
step: 11480 | loss: 0.385939485
step: 11490 | loss: 0.381721534
step: 11500 | loss: 0.377503609
step: 11510 | loss: 0.373285708
step: 11520 | loss: 0.369067833
step: 11530 | loss: 0.364849982
step: 11540 | loss: 0.360632155
step: 11550 | loss: 0.356414352
step: 11560 | loss: 0.352196574
step: 11570 | loss: 0.347978818
step: 11580 | loss: 0.343761087
step: 11590 | loss: 0.339543378
step: 11600 | loss: 0.335325692
step: 11610 | loss: 0.331108030
step: 11620 | loss: 0.326890389
step: 11630 | loss: 0.322672771
step: 11640 | loss: 0.318455175
step: 11650 | loss: 0.314237600
step: 11660 | loss: 0.310020047
step: 11670 | loss: 0.305802516
step: 11680 | loss: 0.301585005
step: 11690 | loss: 0.297367516
step: 11700 | loss: 0.293150047
step: 11710 | loss: 0.288932599
step: 11720 | loss: 0.284715171
step: 11730 | loss: 0.280497764
step: 11740 | loss: 0.276280376
step: 11750 | loss: 0.272063008
step: 11760 | loss: 0.267845659
step: 11770 | loss: 0.263628330
step: 11780 | loss: 0.259411020
step: 11790 | loss: 0.255193729
step: 11800 | loss: 0.250976456
step: 11810 | loss: 0.246759203
step: 11820 | loss: 0.242541967
step: 11830 | loss: 0.238324750
step: 11840 | loss: 0.234107551
step: 11850 | loss: 0.229890369
step: 11860 | loss: 0.225673206
step: 11870 | loss: 0.221456059
step: 11880 | loss: 0.217238930
step: 11890 | loss: 0.213021819
step: 11900 | loss: 0.208804724
step: 11910 | loss: 0.204587646
step: 11920 | loss: 0.200370585
step: 11930 | loss: 0.196153540
step: 11940 | loss: 0.191936511
step: 11950 | loss: 0.187719499
step: 11960 | loss: 0.183502502
step: 11970 | loss: 0.179285521
step: 11980 | loss: 0.175068556
step: 11990 | loss: 0.170851607
step: 12000 | loss: 0.166634673
step: 12010 | loss: 0.162417754
step: 12020 | loss: 0.158200850
step: 12030 | loss: 0.153983961
step: 12040 | loss: 0.149767087
step: 12050 | loss: 0.145550227
step: 12060 | loss: 0.141333382
step: 12070 | loss: 0.137116551
step: 12080 | loss: 0.132899734
step: 12090 | loss: 0.128682932
step: 12100 | loss: 0.124466143
step: 12110 | loss: 0.120249368
step: 12120 | loss: 0.116032606
step: 12130 | loss: 0.111815858
step: 12140 | loss: 0.107599124
step: 12150 | loss: 0.103382402
step: 12160 | loss: 0.099165694
step: 12170 | loss: 0.094948999
step: 12180 | loss: 0.090732316
step: 12190 | loss: 0.086515646
step: 12200 | loss: 0.082298989
step: 12210 | loss: 0.078082344
step: 12220 | loss: 0.073865711
step: 12230 | loss: 0.069649091
step: 12240 | loss: 0.065432483
step: 12250 | loss: 0.061215886
step: 12260 | loss: 0.056999302
step: 12270 | loss: 0.052782729
step: 12280 | loss: 0.048566168
step: 12290 | loss: 0.044349618
step: 12300 | loss: 0.040133080
step: 12310 | loss: 0.035916553
step: 12320 | loss: 0.031700037
step: 12330 | loss: 0.027483532
step: 12340 | loss: 0.023267038
step: 12350 | loss: 0.019050555
step: 12360 | loss: 0.014834082
step: 12370 | loss: 0.010617620
step: 12380 | loss: 0.006401169
step: 12390 | loss: 0.002184728
- final loss: 0.000513
-> compiled  owl-opt.0.0.1
-> installed owl-opt.0.0.1
Done.
# Run eval $(opam env) to update the current shell environment
2022-07-27 05:01.52 ---> saved as "cda88ae7c208bacd8eccdbc6731b8b8cba9f233850f925dd5b5ff7b15d18efd8"
Job succeeded
2022-07-27 05:02.57: Job succeeded