(not at the head of any monitored branch or PR)
2026-03-16 19:14.43: New job: test owl-opt.0.0.1 with dune-configurator.3.22.0~alpha2, using opam dev
                              from https://github.com/ocaml/opam-repository.git#refs/pull/29547/head (19c70fd6a788b154ec5e9fe26bca1d12fb2519be)
                              on debian-13-ocaml-5.4/amd64

To reproduce locally:

cd $(mktemp -d)
git clone --recursive "https://github.com/ocaml/opam-repository.git" && cd "opam-repository" && git fetch origin "refs/pull/29547/head" && git reset --hard 19c70fd6
git fetch origin master
git merge --no-edit 4f056bfedf536e66065c3783e694e6aa0b38261a
cat > ../Dockerfile <<'END-OF-DOCKERFILE'
FROM ocaml/opam:debian-13-ocaml-5.4@sha256:bd342cbd7766c453282fdafbc2e565ae3361320ec344722cf4372b782e4a97f6
USER 1000:1000
WORKDIR /home/opam
RUN sudo ln -f /usr/bin/opam-dev /usr/bin/opam
RUN opam init --reinit -ni
RUN opam option solver=builtin-0install && opam config report
ENV OPAMDOWNLOADJOBS="1"
ENV OPAMERRLOGLEN="0"
ENV OPAMPRECISETRACKING="1"
ENV CI="true"
ENV OPAM_REPO_CI="true"
RUN rm -rf opam-repository/
COPY --chown=1000:1000 . opam-repository/
RUN opam repository set-url --strict default opam-repository/
RUN opam update --depexts || true
RUN opam pin add -k version -yn dune-configurator.3.22.0~alpha2 3.22.0~alpha2
RUN opam reinstall dune-configurator.3.22.0~alpha2; \
    res=$?; \
    test "$res" != 31 && exit "$res"; \
    export OPAMCLI=2.0; \
    build_dir=$(opam var prefix)/.opam-switch/build; \
    failed=$(ls "$build_dir"); \
    partial_fails=""; \
    for pkg in $failed; do \
    if opam show -f x-ci-accept-failures: "$pkg" | grep -qF "\"debian-13\""; then \
    echo "A package failed and has been disabled for CI using the 'x-ci-accept-failures' field."; \
    fi; \
    test "$pkg" != 'dune-configurator.3.22.0~alpha2' && partial_fails="$partial_fails $pkg"; \
    done; \
    test "${partial_fails}" != "" && echo "opam-repo-ci detected dependencies failing: ${partial_fails}"; \
    exit 1
RUN opam reinstall owl-opt.0.0.1; \
    res=$?; \
    test "$res" != 31 && exit "$res"; \
    export OPAMCLI=2.0; \
    build_dir=$(opam var prefix)/.opam-switch/build; \
    failed=$(ls "$build_dir"); \
    partial_fails=""; \
    for pkg in $failed; do \
    if opam show -f x-ci-accept-failures: "$pkg" | grep -qF "\"debian-13\""; then \
    echo "A package failed and has been disabled for CI using the 'x-ci-accept-failures' field."; \
    fi; \
    test "$pkg" != 'owl-opt.0.0.1' && partial_fails="$partial_fails $pkg"; \
    done; \
    test "${partial_fails}" != "" && echo "opam-repo-ci detected dependencies failing: ${partial_fails}"; \
    exit 1
RUN (opam reinstall --with-test owl-opt.0.0.1) || true
RUN opam reinstall --with-test --verbose owl-opt.0.0.1; \
    res=$?; \
    test "$res" != 31 && exit "$res"; \
    export OPAMCLI=2.0; \
    build_dir=$(opam var prefix)/.opam-switch/build; \
    failed=$(ls "$build_dir"); \
    partial_fails=""; \
    for pkg in $failed; do \
    if opam show -f x-ci-accept-failures: "$pkg" | grep -qF "\"debian-13\""; then \
    echo "A package failed and has been disabled for CI using the 'x-ci-accept-failures' field."; \
    fi; \
    test "$pkg" != 'owl-opt.0.0.1' && partial_fails="$partial_fails $pkg"; \
    done; \
    test "${partial_fails}" != "" && echo "opam-repo-ci detected dependencies failing: ${partial_fails}"; \
    exit 1

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

2026-03-16 19:14.43: Using cache hint "ocaml/opam:debian-13-ocaml-5.4@sha256:bd342cbd7766c453282fdafbc2e565ae3361320ec344722cf4372b782e4a97f6-dune-configurator.3.22.0~alpha2-owl-opt.0.0.1-19c70fd6a788b154ec5e9fe26bca1d12fb2519be"
2026-03-16 19:14.43: Using OBuilder spec:
((from ocaml/opam:debian-13-ocaml-5.4@sha256:bd342cbd7766c453282fdafbc2e565ae3361320ec344722cf4372b782e4a97f6)
 (user (uid 1000) (gid 1000))
 (workdir /home/opam)
 (run (shell "sudo ln -f /usr/bin/opam-dev /usr/bin/opam"))
 (run (network host)
      (shell "opam init --reinit --config .opamrc-sandbox -ni"))
 (run (shell "opam option solver=builtin-0install && opam config report"))
 (env OPAMDOWNLOADJOBS 1)
 (env OPAMERRLOGLEN 0)
 (env OPAMPRECISETRACKING 1)
 (env CI true)
 (env OPAM_REPO_CI true)
 (run (shell "rm -rf opam-repository/"))
 (copy (src .) (dst opam-repository/))
 (run (shell "opam repository set-url --strict default opam-repository/"))
 (run (network host)
      (shell "opam update --depexts || true"))
 (run (shell "opam pin add -k version -yn dune-configurator.3.22.0~alpha2 3.22.0~alpha2"))
 (run (cache (opam-archives (target /home/opam/.opam/download-cache)))
      (network host)
      (shell  "opam reinstall dune-configurator.3.22.0~alpha2;\
             \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        partial_fails=\"\";\
             \n        for pkg in $failed; do\
             \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-13\\\"\"; then\
             \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
             \n          fi;\
             \n          test \"$pkg\" != 'dune-configurator.3.22.0~alpha2' && partial_fails=\"$partial_fails $pkg\";\
             \n        done;\
             \n        test \"${partial_fails}\" != \"\" && echo \"opam-repo-ci detected dependencies failing: ${partial_fails}\";\
             \n        exit 1"))
 (run (cache (opam-archives (target /home/opam/.opam/download-cache)))
      (network host)
      (shell  "opam reinstall owl-opt.0.0.1;\
             \n        res=$?;\
             \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        partial_fails=\"\";\
             \n        for pkg in $failed; do\
             \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-13\\\"\"; then\
             \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
             \n          fi;\
             \n          test \"$pkg\" != 'owl-opt.0.0.1' && partial_fails=\"$partial_fails $pkg\";\
             \n        done;\
             \n        test \"${partial_fails}\" != \"\" && echo \"opam-repo-ci detected dependencies failing: ${partial_fails}\";\
             \n        exit 1"))
 (run (network host)
      (shell "(opam reinstall --with-test owl-opt.0.0.1) || true"))
 (run (shell  "opam reinstall --with-test --verbose owl-opt.0.0.1;\
             \n        res=$?;\
             \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        partial_fails=\"\";\
             \n        for pkg in $failed; do\
             \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-13\\\"\"; then\
             \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
             \n          fi;\
             \n          test \"$pkg\" != 'owl-opt.0.0.1' && partial_fails=\"$partial_fails $pkg\";\
             \n        done;\
             \n        test \"${partial_fails}\" != \"\" && echo \"opam-repo-ci detected dependencies failing: ${partial_fails}\";\
             \n        exit 1"))
)

2026-03-16 19:14.43: Waiting for resource in pool OCluster
2026-03-16 20:48.17: Waiting for worker…
2026-03-16 20:49.53: Got resource from pool OCluster
Building on doris.caelum.ci.dev
All commits already cached
HEAD is now at 4f056bfedf Merge pull request #29543 from Zaneham/add-olint-0.1.0
Updating 4f056bfedf..19c70fd6a7
Fast-forward
 .../chrome-trace/chrome-trace.3.22.0~alpha2/opam   | 39 +++++++++++
 .../dune-action-plugin.3.22.0~alpha2/opam          | 52 +++++++++++++++
 .../dune-action-trace.3.22.0~alpha2/opam           | 39 +++++++++++
 .../dune-build-info.3.22.0~alpha2/opam             | 45 +++++++++++++
 .../dune-configurator.3.22.0~alpha2/opam           | 49 ++++++++++++++
 packages/dune-glob/dune-glob.3.22.0~alpha2/opam    | 42 ++++++++++++
 .../dune-private-libs.3.22.0~alpha2/opam           | 50 +++++++++++++++
 .../dune-rpc-lwt/dune-rpc-lwt.3.22.0~alpha2/opam   | 41 ++++++++++++
 packages/dune-rpc/dune-rpc.3.22.0~alpha2/opam      | 44 +++++++++++++
 packages/dune-site/dune-site.3.22.0~alpha2/opam    | 37 +++++++++++
 packages/dune/dune.3.22.0~alpha2/opam              | 75 ++++++++++++++++++++++
 packages/dyn/dyn.3.22.0~alpha2/opam                | 40 ++++++++++++
 packages/fs-io/fs-io.3.22.0~alpha2/opam            | 39 +++++++++++
 packages/ocamlc-loc/ocamlc-loc.3.22.0~alpha2/opam  | 43 +++++++++++++
 packages/ordering/ordering.3.22.0~alpha2/opam      | 38 +++++++++++
 packages/stdune/stdune.3.22.0~alpha2/opam          | 46 +++++++++++++
 .../top-closure/top-closure.3.22.0~alpha2/opam     | 38 +++++++++++
 packages/xdg/xdg.3.22.0~alpha2/opam                | 39 +++++++++++
 18 files changed, 796 insertions(+)
 create mode 100644 packages/chrome-trace/chrome-trace.3.22.0~alpha2/opam
 create mode 100644 packages/dune-action-plugin/dune-action-plugin.3.22.0~alpha2/opam
 create mode 100644 packages/dune-action-trace/dune-action-trace.3.22.0~alpha2/opam
 create mode 100644 packages/dune-build-info/dune-build-info.3.22.0~alpha2/opam
 create mode 100644 packages/dune-configurator/dune-configurator.3.22.0~alpha2/opam
 create mode 100644 packages/dune-glob/dune-glob.3.22.0~alpha2/opam
 create mode 100644 packages/dune-private-libs/dune-private-libs.3.22.0~alpha2/opam
 create mode 100644 packages/dune-rpc-lwt/dune-rpc-lwt.3.22.0~alpha2/opam
 create mode 100644 packages/dune-rpc/dune-rpc.3.22.0~alpha2/opam
 create mode 100644 packages/dune-site/dune-site.3.22.0~alpha2/opam
 create mode 100644 packages/dune/dune.3.22.0~alpha2/opam
 create mode 100644 packages/dyn/dyn.3.22.0~alpha2/opam
 create mode 100644 packages/fs-io/fs-io.3.22.0~alpha2/opam
 create mode 100644 packages/ocamlc-loc/ocamlc-loc.3.22.0~alpha2/opam
 create mode 100644 packages/ordering/ordering.3.22.0~alpha2/opam
 create mode 100644 packages/stdune/stdune.3.22.0~alpha2/opam
 create mode 100644 packages/top-closure/top-closure.3.22.0~alpha2/opam
 create mode 100644 packages/xdg/xdg.3.22.0~alpha2/opam

(from ocaml/opam:debian-13-ocaml-5.4@sha256:bd342cbd7766c453282fdafbc2e565ae3361320ec344722cf4372b782e4a97f6)
Unable to find image 'ocaml/opam:debian-13-ocaml-5.4@sha256:bd342cbd7766c453282fdafbc2e565ae3361320ec344722cf4372b782e4a97f6' locally
docker.io/ocaml/opam@sha256:bd342cbd7766c453282fdafbc2e565ae3361320ec344722cf4372b782e4a97f6: Pulling from ocaml/opam
866771c43bf5: Already exists
1e49bea09367: Already exists
e793768537e6: Already exists
ed323d3d481a: Already exists
7df34a5cd5f1: Already exists
fd712d3eb935: Already exists
4b9fb8c99118: Already exists
9d9a01948b94: Already exists
0f1514f90b32: Already exists
e1ec5a753447: Already exists
03cc323e2f71: Already exists
c09c08ea9749: Already exists
b36b619f8e6b: Already exists
195344ca5274: Already exists
228ee78582a6: Already exists
504bde1c25b3: Already exists
9d8b1356c89f: Already exists
9d8b1356c89f: Already exists
568fb6dda155: Already exists
c499c9198aea: Already exists
048e5e358118: Already exists
871ca48eb45d: Already exists
4f4fb700ef54: Already exists
a5a2568b9df9: Already exists
068cf3106ac8: Already exists
559f54ec9b29: Already exists
798ffd96fde5: Already exists
e9a891bf80d7: Already exists
d720cfe12674: Already exists
c81c932f4a91: Already exists
79f24fa3bb11: Already exists
8c1debcd8c20: Already exists
1bb2cfea7250: Already exists
2b3d3ca75e4c: Already exists
557cacaf263c: Already exists
d10483022eef: Already exists
7b62a90d8223: Already exists
28ce8ea66e72: Already exists
d975909ea717: Already exists
5c215c69c247: Already exists
e7c082452a54: Already exists
f6cbd774d654: Pulling fs layer
b40777a84cca: Pulling fs layer
7bb5edb9c889: Pulling fs layer
020670bcefab: Pulling fs layer
46df05d0db83: Pulling fs layer
020670bcefab: Waiting
45bde7b38933: Pulling fs layer
46df05d0db83: Waiting
b4d63fa01ada: Pulling fs layer
b4d63fa01ada: Waiting
45bde7b38933: Waiting
f6cbd774d654: Download complete
b40777a84cca: Verifying Checksum
b40777a84cca: Download complete
f6cbd774d654: Pull complete
7bb5edb9c889: Verifying Checksum
7bb5edb9c889: Download complete
b40777a84cca: Pull complete
7bb5edb9c889: Pull complete
46df05d0db83: Download complete
45bde7b38933: Verifying Checksum
45bde7b38933: Download complete
b4d63fa01ada: Download complete
020670bcefab: Verifying Checksum
020670bcefab: Download complete
020670bcefab: Pull complete
46df05d0db83: Pull complete
45bde7b38933: Pull complete
b4d63fa01ada: Pull complete
Digest: sha256:bd342cbd7766c453282fdafbc2e565ae3361320ec344722cf4372b782e4a97f6
Status: Downloaded newer image for ocaml/opam@sha256:bd342cbd7766c453282fdafbc2e565ae3361320ec344722cf4372b782e4a97f6
2026-03-16 20:49.57 ---> using "41eea30e3f639c18d8cf57c309ec76919ec7b2398036f7e41744cbce59a133d3" from cache

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

/: (workdir /home/opam)

/home/opam: (run (shell "sudo ln -f /usr/bin/opam-dev /usr/bin/opam"))
2026-03-16 20:49.57 ---> using "4ad7f430d684c40cedc651267e0edf890c044fe4e624255de377c471b4526bac" from cache

/home/opam: (run (network host)
                 (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 version of opam requires an update to the layout of /home/opam/.opam from version 2.0 to version 2.2, which can't be reverted.
You may want to back it up before going further.

Continue? [Y/n] y
[NOTE] The 'jobs' option was reset, its value was 71 and its new value will vary according to the current number of cores on your machine. You can restore the fixed value using:
           opam option jobs=71 --global
Format upgrade done.

<><> Updating repositories ><><><><><><><><><><><><><><><><><><><><><><><><><><>
[default] Initialised
2026-03-16 20:49.57 ---> using "71fa58e52457bf6a7eac317c6a6ef1e2bdf53e533a1e4fd04b90c9349347e038" from cache

/home/opam: (run (shell "opam option solver=builtin-0install && opam config report"))
Set to 'builtin-0install' the field solver in global configuration
# opam config report
# opam-version         2.5.0
# self-upgrade         no
# system               arch=x86_64 os=linux os-distribution=debian os-version=13
# solver               builtin-0install
# install-criteria     -changed,-count[avoid-version,solution]
# upgrade-criteria     -count[avoid-version,solution]
# jobs                 255
# repositories         1 (version-controlled)
# pinned               1 (version)
# current-switch       5.4
# invariant            ["ocaml-base-compiler" {= "5.4.0"}]
# compiler-packages    ocaml-base-compiler.5.4.0, ocaml-compiler.5.4.0, ocaml-options-vanilla.1
# ocaml:native         true
# ocaml:native-tools   true
# ocaml:native-dynlink true
# ocaml:stubsdir       /home/opam/.opam/5.4/lib/ocaml/stublibs:/home/opam/.opam/5.4/lib/ocaml
# ocaml:preinstalled   false
# ocaml:compiler       5.4.0
2026-03-16 20:49.57 ---> using "ed86081cb38ca125a920162bfe6a4bb7b1c27c6973c917551687c83cf44dbfdf" from cache

/home/opam: (env OPAMDOWNLOADJOBS 1)

/home/opam: (env OPAMERRLOGLEN 0)

/home/opam: (env OPAMPRECISETRACKING 1)

/home/opam: (env CI true)

/home/opam: (env OPAM_REPO_CI true)

/home/opam: (run (shell "rm -rf opam-repository/"))
2026-03-16 20:49.57 ---> using "04a48515eea40c32b96da0c71328b4bba0edb66eed83d4f78554b39097cf1f25" from cache

/home/opam: (copy (src .) (dst opam-repository/))
2026-03-16 20:49.58 ---> using "5aac9760b2a7888c5a0c51e12c4e2f8b78e92b665688f09ee1858f54c46e2fba" from cache

/home/opam: (run (shell "opam repository set-url --strict default opam-repository/"))
[default] Initialised
2026-03-16 20:49.58 ---> using "eb2bdb7d05f153d109c9af88f52221b082fcc4d1be6951027ec15e8041a9f010" from cache

/home/opam: (run (network host)
                 (shell "opam update --depexts || true"))
+ /usr/bin/sudo "apt-get" "update"
- Get:1 http://deb.debian.org/debian trixie InRelease [140 kB]
- Get:2 http://deb.debian.org/debian trixie-updates InRelease [47.3 kB]
- Get:3 http://deb.debian.org/debian-security trixie-security InRelease [43.4 kB]
- Get:4 http://deb.debian.org/debian trixie/main amd64 Packages [9671 kB]
- Get:5 http://deb.debian.org/debian-security trixie-security/main amd64 Packages [111 kB]
- Fetched 10.0 MB in 6s (1648 kB/s)
- Reading package lists...
2026-03-16 20:49.58 ---> using "44c5375013a613ff9fdb37faa9a067ee60e0498629acd41e746d1271325aac5f" from cache

/home/opam: (run (shell "opam pin add -k version -yn dune-configurator.3.22.0~alpha2 3.22.0~alpha2"))
dune-configurator is now pinned to version 3.22.0~alpha2
2026-03-16 20:49.58 ---> using "197f0d78eaf0695e2cc8ac58e9453f86b10186547feff37a463721ee9fe56ae6" from cache

/home/opam: (run (cache (opam-archives (target /home/opam/.opam/download-cache)))
                 (network host)
                 (shell  "opam reinstall dune-configurator.3.22.0~alpha2;\
                        \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        partial_fails=\"\";\
                        \n        for pkg in $failed; do\
                        \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-13\\\"\"; then\
                        \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
                        \n          fi;\
                        \n          test \"$pkg\" != 'dune-configurator.3.22.0~alpha2' && partial_fails=\"$partial_fails $pkg\";\
                        \n        done;\
                        \n        test \"${partial_fails}\" != \"\" && echo \"opam-repo-ci detected dependencies failing: ${partial_fails}\";\
                        \n        exit 1"))
dune-configurator.3.22.0~alpha2 is not installed. Install it? [Y/n] y
The following actions will be performed:
=== install 3 packages
  - install csexp             1.5.2                  [required by dune-configurator]
  - install dune              3.22.0~alpha2          [required by dune-configurator]
  - install dune-configurator 3.22.0~alpha2 (pinned)

<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>
-> retrieved csexp.1.5.2  (cached)
-> retrieved dune.3.22.0~alpha2, dune-configurator.3.22.0~alpha2  (cached)
-> installed dune.3.22.0~alpha2
-> installed csexp.1.5.2
-> installed dune-configurator.3.22.0~alpha2
Done.
# To update the current shell environment, run: eval $(opam env)
2026-03-16 20:49.58 ---> using "cdd15064528574bdfa1f696883f76464f9dcf852d7d4629ed5ae486775ee6ba0" from cache

/home/opam: (run (cache (opam-archives (target /home/opam/.opam/download-cache)))
                 (network host)
                 (shell  "opam reinstall 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        partial_fails=\"\";\
                        \n        for pkg in $failed; do\
                        \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-13\\\"\"; then\
                        \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
                        \n          fi;\
                        \n          test \"$pkg\" != 'owl-opt.0.0.1' && partial_fails=\"$partial_fails $pkg\";\
                        \n        done;\
                        \n        test \"${partial_fails}\" != \"\" && echo \"opam-repo-ci detected dependencies failing: ${partial_fails}\";\
                        \n        exit 1"))
owl-opt.0.0.1 is not installed. Install it? [Y/n] y
The following actions will be performed:
=== install 19 packages
  - install base                    v0.17.3 [required by owl, ppx-owl-opt]
  - install camlzip                 1.14    [required by npy]
  - install conf-openblas           0.2.3   [required by owl]
  - install conf-pkg-config         4       [required by conf-zlib]
  - install conf-zlib               1       [required by camlzip]
  - install ctypes                  0.24.0  [required by owl]
  - install integers                0.7.0   [required by ctypes]
  - install npy                     0.0.9   [required by owl]
  - install ocaml-compiler-libs     v0.17.0 [required by ppxlib]
  - install ocaml_intrinsics_kernel v0.17.1 [required by base]
  - install ocamlfind               1.9.8   [required by camlzip]
  - install owl                     1.2     [required by owl-opt]
  - install owl-base                1.2     [required by owl]
  - install owl-opt                 0.0.1
  - install ppx-owl-opt             0.0.1   [required by owl-opt]
  - install ppx_derivers            1.2.1   [required by ppxlib]
  - install ppxlib                  0.37.0  [required by ppx-owl-opt]
  - install sexplib0                v0.17.0 [required by base, ppxlib]
  - install stdlib-shims            0.3.0   [required by ppxlib]

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. Continue anyway, and, upon success, 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"
- Selecting previously unselected package libblas3: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 ... 20654 files and directories currently installed.)
- Preparing to unpack .../00-libblas3_3.12.1-6_amd64.deb ...
- Unpacking libblas3:amd64 (3.12.1-6) ...
- Selecting previously unselected package libblas-dev:amd64.
- Preparing to unpack .../01-libblas-dev_3.12.1-6_amd64.deb ...
- Unpacking libblas-dev:amd64 (3.12.1-6) ...
- Selecting previously unselected package libgfortran5:amd64.
- Preparing to unpack .../02-libgfortran5_14.2.0-19_amd64.deb ...
- Unpacking libgfortran5:amd64 (14.2.0-19) ...
- Selecting previously unselected package libopenblas0-pthread:amd64.
- Preparing to unpack .../03-libopenblas0-pthread_0.3.29+ds-3_amd64.deb ...
- Unpacking libopenblas0-pthread:amd64 (0.3.29+ds-3) ...
- Selecting previously unselected package liblapack3:amd64.
- Preparing to unpack .../04-liblapack3_3.12.1-6_amd64.deb ...
- Unpacking liblapack3:amd64 (3.12.1-6) ...
- Selecting previously unselected package libopenblas-pthread-dev:amd64.
- Preparing to unpack .../05-libopenblas-pthread-dev_0.3.29+ds-3_amd64.deb ...
- Unpacking libopenblas-pthread-dev:amd64 (0.3.29+ds-3) ...
- Selecting previously unselected package liblapack-dev:amd64.
- Preparing to unpack .../06-liblapack-dev_3.12.1-6_amd64.deb ...
- Unpacking liblapack-dev:amd64 (3.12.1-6) ...
- Selecting previously unselected package libtmglib3:amd64.
- Preparing to unpack .../07-libtmglib3_3.12.1-6_amd64.deb ...
- Unpacking libtmglib3:amd64 (3.12.1-6) ...
- Selecting previously unselected package liblapacke:amd64.
- Preparing to unpack .../08-liblapacke_3.12.1-6_amd64.deb ...
- Unpacking liblapacke:amd64 (3.12.1-6) ...
- Selecting previously unselected package libtmglib-dev:amd64.
- Preparing to unpack .../09-libtmglib-dev_3.12.1-6_amd64.deb ...
- Unpacking libtmglib-dev:amd64 (3.12.1-6) ...
- Selecting previously unselected package liblapacke-dev:amd64.
- Preparing to unpack .../10-liblapacke-dev_3.12.1-6_amd64.deb ...
- Unpacking liblapacke-dev:amd64 (3.12.1-6) ...
- Selecting previously unselected package libopenblas0:amd64.
- Preparing to unpack .../11-libopenblas0_0.3.29+ds-3_amd64.deb ...
- Unpacking libopenblas0:amd64 (0.3.29+ds-3) ...
- Selecting previously unselected package libopenblas-dev:amd64.
- Preparing to unpack .../12-libopenblas-dev_0.3.29+ds-3_amd64.deb ...
- Unpacking libopenblas-dev:amd64 (0.3.29+ds-3) ...
- Selecting previously unselected package libpkgconf3:amd64.
- Preparing to unpack .../13-libpkgconf3_1.8.1-4_amd64.deb ...
- Unpacking libpkgconf3:amd64 (1.8.1-4) ...
- Selecting previously unselected package pkgconf-bin.
- Preparing to unpack .../14-pkgconf-bin_1.8.1-4_amd64.deb ...
- Unpacking pkgconf-bin (1.8.1-4) ...
- Selecting previously unselected package pkgconf:amd64.
- Preparing to unpack .../15-pkgconf_1.8.1-4_amd64.deb ...
- Unpacking pkgconf:amd64 (1.8.1-4) ...
- Selecting previously unselected package pkg-config:amd64.
- Preparing to unpack .../16-pkg-config_1.8.1-4_amd64.deb ...
- Unpacking pkg-config:amd64 (1.8.1-4) ...
- Selecting previously unselected package zlib1g-dev:amd64.
- Preparing to unpack .../17-zlib1g-dev_1%3a1.3.dfsg+really1.3.1-1+b1_amd64.deb ...
- Unpacking zlib1g-dev:amd64 (1:1.3.dfsg+really1.3.1-1+b1) ...
- Setting up libblas3:amd64 (3.12.1-6) ...
- update-alternatives: using /usr/lib/x86_64-linux-gnu/blas/libblas.so.3 to provide /usr/lib/x86_64-linux-gnu/libblas.so.3 (libblas.so.3-x86_64-linux-gnu) in auto mode
- Setting up libpkgconf3:amd64 (1.8.1-4) ...
- Setting up pkgconf-bin (1.8.1-4) ...
- Setting up libgfortran5:amd64 (14.2.0-19) ...
- Setting up zlib1g-dev:amd64 (1:1.3.dfsg+really1.3.1-1+b1) ...
- Setting up libblas-dev:amd64 (3.12.1-6) ...
- update-alternatives: using /usr/lib/x86_64-linux-gnu/blas/libblas.so to provide /usr/lib/x86_64-linux-gnu/libblas.so (libblas.so-x86_64-linux-gnu) in auto mode
- Setting up liblapack3:amd64 (3.12.1-6) ...
- update-alternatives: using /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3 to provide /usr/lib/x86_64-linux-gnu/liblapack.so.3 (liblapack.so.3-x86_64-linux-gnu) in auto mode
- Setting up libopenblas0-pthread:amd64 (0.3.29+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 pkgconf:amd64 (1.8.1-4) ...
- Setting up libtmglib3:amd64 (3.12.1-6) ...
- Setting up liblapack-dev:amd64 (3.12.1-6) ...
- update-alternatives: using /usr/lib/x86_64-linux-gnu/lapack/liblapack.so to provide /usr/lib/x86_64-linux-gnu/liblapack.so (liblapack.so-x86_64-linux-gnu) in auto mode
- Setting up pkg-config:amd64 (1.8.1-4) ...
- Setting up libopenblas0:amd64 (0.3.29+ds-3) ...
- Setting up liblapacke:amd64 (3.12.1-6) ...
- Setting up libtmglib-dev:amd64 (3.12.1-6) ...
- Setting up libopenblas-pthread-dev:amd64 (0.3.29+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 liblapacke-dev:amd64 (3.12.1-6) ...
- Setting up libopenblas-dev:amd64 (0.3.29+ds-3) ...
- Processing triggers for libc-bin (2.41-12+deb13u1) ...

<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>
-> retrieved base.v0.17.3  (cached)
-> retrieved camlzip.1.14  (cached)
-> retrieved conf-openblas.0.2.3  (cached)
-> retrieved ctypes.0.24.0  (cached)
-> installed conf-pkg-config.4
-> retrieved integers.0.7.0  (cached)
-> retrieved npy.0.0.9  (cached)
-> retrieved ocaml-compiler-libs.v0.17.0  (cached)
-> retrieved ocaml_intrinsics_kernel.v0.17.1  (cached)
-> installed conf-zlib.1
-> retrieved ocamlfind.1.9.8  (cached)
-> installed conf-openblas.0.2.3
-> installed ocaml_intrinsics_kernel.v0.17.1
-> installed ocaml-compiler-libs.v0.17.0
-> retrieved owl.1.2, owl-base.1.2  (cached)
-> retrieved owl-opt.0.0.1, ppx-owl-opt.0.0.1  (cached)
-> retrieved ppx_derivers.1.2.1  (cached)
-> retrieved ppxlib.0.37.0  (cached)
-> installed ppx_derivers.1.2.1
-> retrieved sexplib0.v0.17.0  (cached)
-> retrieved stdlib-shims.0.3.0  (cached)
-> installed stdlib-shims.0.3.0
-> installed sexplib0.v0.17.0
-> installed integers.0.7.0
-> installed ocamlfind.1.9.8
-> installed owl-base.1.2
-> installed camlzip.1.14
-> installed npy.0.0.9
-> installed ctypes.0.24.0
-> installed base.v0.17.3
-> installed ppxlib.0.37.0
-> installed ppx-owl-opt.0.0.1
-> installed owl.1.2
-> installed owl-opt.0.0.1
Done.
# To update the current shell environment, run: eval $(opam env)
2026-03-16 20:53.13 ---> saved as "649a1ae58f143c43279a28532d91b3f17a2f6234e289dfda38694b1c78062398"

/home/opam: (run (network host)
                 (shell "(opam reinstall --with-test owl-opt.0.0.1) || true"))
The following actions will be performed:
=== recompile 1 package
  - recompile owl-opt 0.0.1

<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>
-> retrieved owl-opt.0.0.1  (https://opam.ocaml.org/cache)
-> removed   owl-opt.0.0.1
-> installed owl-opt.0.0.1
Done.
# To update the current shell environment, run: eval $(opam env)
2026-03-16 20:53.20 ---> saved as "48743bc78febaecb680849e89829b92c6974814547ba202407b42de4f552ac92"

/home/opam: (run (shell  "opam reinstall --with-test --verbose 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        partial_fails=\"\";\
                        \n        for pkg in $failed; do\
                        \n          if opam show -f x-ci-accept-failures: \"$pkg\" | grep -qF \"\\\"debian-13\\\"\"; then\
                        \n            echo \"A package failed and has been disabled for CI using the 'x-ci-accept-failures' field.\";\
                        \n          fi;\
                        \n          test \"$pkg\" != 'owl-opt.0.0.1' && partial_fails=\"$partial_fails $pkg\";\
                        \n        done;\
                        \n        test \"${partial_fails}\" != \"\" && echo \"opam-repo-ci detected dependencies failing: ${partial_fails}\";\
                        \n        exit 1"))
The following actions will be performed:
=== recompile 1 package
  - recompile owl-opt 0.0.1

<><> Processing actions <><><><><><><><><><><><><><><><><><><><><><><><><><><><>
Processing  1/4: [owl-opt.0.0.1: extract]
-> retrieved owl-opt.0.0.1  (cached)
Processing  2/4: [owl-opt: dune build]
+ /home/opam/.opam/opam-init/hooks/sandbox.sh "build" "dune" "build" "-p" "owl-opt" "-j" "255" (CWD=/home/opam/.opam/5.4/.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  2/4: [owl-opt: dune runtest]
+ /home/opam/.opam/opam-init/hooks/sandbox.sh "build" "dune" "runtest" "examples/opt" "-p" "owl-opt" "-j" "255" (CWD=/home/opam/.opam/5.4/.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 && ./gd.exe)
- 
iter: 0 | loss: 4.893540
iter: 1 | loss: 4.893540
iter: 2 | loss: 4.892925
iter: 3 | loss: 4.892310
iter: 4 | loss: 4.891695
iter: 5 | loss: 4.891080
iter: 6 | loss: 4.890465
iter: 7 | loss: 4.889850
iter: 8 | loss: 4.889235
iter: 9 | loss: 4.888620
iter: 10 | loss: 4.888005
iter: 11 | loss: 4.887390
iter: 12 | loss: 4.886775
iter: 13 | loss: 4.886159
iter: 14 | loss: 4.885544
iter: 15 | loss: 4.884929
iter: 16 | loss: 4.884314
iter: 17 | loss: 4.883699
iter: 18 | loss: 4.883084
iter: 19 | loss: 4.882469
iter: 20 | loss: 4.881854
iter: 21 | loss: 4.881239
iter: 22 | loss: 4.880624
iter: 23 | loss: 4.880009
iter: 24 | loss: 4.879394
iter: 25 | loss: 4.878779
iter: 26 | loss: 4.878164
iter: 27 | loss: 4.877549
iter: 28 | loss: 4.876934
iter: 29 | loss: 4.876318
iter: 30 | loss: 4.875703
iter: 31 | loss: 4.875088
iter: 32 | loss: 4.874473
iter: 33 | loss: 4.873858
iter: 34 | loss: 4.873243
iter: 35 | loss: 4.872628
iter: 36 | loss: 4.872013
iter: 37 | loss: 4.871398
iter: 38 | loss: 4.870783
iter: 39 | loss: 4.870168
iter: 40 | loss: 4.869553
iter: 41 | loss: 4.868938
iter: 42 | loss: 4.868323
iter: 43 | loss: 4.867708
iter: 44 | loss: 4.867093
iter: 45 | loss: 4.866477
iter: 46 | loss: 4.865862
iter: 47 | loss: 4.865247
iter: 48 | loss: 4.864632
iter: 49 | loss: 4.864017
iter: 50 | loss: 4.863402
iter: 51 | loss: 4.862787
iter: 52 | loss: 4.862172
iter: 53 | loss: 4.861557
iter: 54 | loss: 4.860942
iter: 55 | loss: 4.860327
iter: 56 | loss: 4.859712
iter: 57 | loss: 4.859097
iter: 58 | loss: 4.858482
iter: 59 | loss: 4.857867
iter: 60 | loss: 4.857252
iter: 61 | loss: 4.856636
iter: 62 | loss: 4.856021
iter: 63 | loss: 4.855406
iter: 64 | loss: 4.854791
iter: 65 | loss: 4.854176
iter: 66 | loss: 4.853561
iter: 67 | loss: 4.852946
iter: 68 | loss: 4.852331
iter: 69 | loss: 4.851716
iter: 70 | loss: 4.851101
iter: 71 | loss: 4.850486
iter: 72 | loss: 4.849871
iter: 73 | loss: 4.849256
iter: 74 | loss: 4.848641
iter: 75 | loss: 4.848026
iter: 76 | loss: 4.847410
iter: 77 | loss: 4.846795
iter: 78 | loss: 4.846180
iter: 79 | loss: 4.845565
iter: 80 | loss: 4.844950
iter: 81 | loss: 4.844335
iter: 82 | loss: 4.843720
iter: 83 | loss: 4.843105
iter: 84 | loss: 4.842490
iter: 85 | loss: 4.841875
iter: 86 | loss: 4.841260
iter: 87 | loss: 4.840645
iter: 88 | loss: 4.840030
iter: 89 | loss: 4.839415
iter: 90 | loss: 4.838800
iter: 91 | loss: 4.838185
iter: 92 | loss: 4.837569
iter: 93 | loss: 4.836954
iter: 94 | loss: 4.836339
iter: 95 | loss: 4.835724
iter: 96 | loss: 4.835109
iter: 97 | loss: 4.834494
iter: 98 | loss: 4.833879
iter: 99 | loss: 4.833264
iter: 100 | loss: 4.832649
iter: 101 | loss: 4.832034
iter: 102 | loss: 4.831419
iter: 103 | loss: 4.830804
iter: 104 | loss: 4.830189
iter: 105 | loss: 4.829574
iter: 106 | loss: 4.828959
iter: 107 | loss: 4.828344
iter: 108 | loss: 4.827728
iter: 109 | loss: 4.827113
iter: 110 | loss: 4.826498
iter: 111 | loss: 4.825883
iter: 112 | loss: 4.825268
iter: 113 | loss: 4.824653
iter: 114 | loss: 4.824038
iter: 115 | loss: 4.823423
iter: 116 | loss: 4.822808
iter: 117 | loss: 4.822193
iter: 118 | loss: 4.821578
iter: 119 | loss: 4.820963
iter: 120 | loss: 4.820348
iter: 121 | loss: 4.819733
iter: 122 | loss: 4.819118
iter: 123 | loss: 4.818503
iter: 124 | loss: 4.817887
iter: 125 | loss: 4.817272
iter: 126 | loss: 4.816657
iter: 127 | loss: 4.816042
iter: 128 | loss: 4.815427
iter: 129 | loss: 4.814812
iter: 130 | loss: 4.814197
iter: 131 | loss: 4.813582
iter: 132 | loss: 4.812967
iter: 133 | loss: 4.812352
iter: 134 | loss: 4.811737
iter: 135 | loss: 4.811122
iter: 136 | loss: 4.810507
iter: 137 | loss: 4.809892
iter: 138 | loss: 4.809277
iter: 139 | loss: 4.808661
iter: 140 | loss: 4.808046
iter: 141 | loss: 4.807431
iter: 142 | loss: 4.806816
iter: 143 | loss: 4.806201
iter: 144 | loss: 4.805586
iter: 145 | loss: 4.804971
iter: 146 | loss: 4.804356
iter: 147 | loss: 4.803741
iter: 148 | loss: 4.803126
iter: 149 | loss: 4.802511
iter: 150 | loss: 4.801896
iter: 151 | loss: 4.801281
iter: 152 | loss: 4.800666
iter: 153 | loss: 4.800051
iter: 154 | loss: 4.799436
iter: 155 | loss: 4.798820
iter: 156 | loss: 4.798205
iter: 157 | loss: 4.797590
iter: 158 | loss: 4.796975
iter: 159 | loss: 4.796360
iter: 160 | loss: 4.795745
iter: 161 | loss: 4.795130
iter: 162 | loss: 4.794515
iter: 163 | loss: 4.793900
iter: 164 | loss: 4.793285
iter: 165 | loss: 4.792670
iter: 166 | loss: 4.792055
iter: 167 | loss: 4.791440
iter: 168 | loss: 4.790825
iter: 169 | loss: 4.790210
iter: 170 | loss: 4.789595
iter: 171 | loss: 4.788979
iter: 172 | loss: 4.788364
iter: 173 | loss: 4.787749
iter: 174 | loss: 4.787134
iter: 175 | loss: 4.786519
iter: 176 | loss: 4.785904
iter: 177 | loss: 4.785289
iter: 178 | loss: 4.784674
iter: 179 | loss: 4.784059
iter: 180 | loss: 4.783444
iter: 181 | loss: 4.782829
iter: 182 | loss: 4.782214
iter: 183 | loss: 4.781599
iter: 184 | loss: 4.780984
iter: 185 | loss: 4.780369
iter: 186 | loss: 4.779754
iter: 187 | loss: 4.779138
iter: 188 | loss: 4.778523
iter: 189 | loss: 4.777908
iter: 190 | loss: 4.777293
iter: 191 | loss: 4.776678
iter: 192 | loss: 4.776063
iter: 193 | loss: 4.775448
iter: 194 | loss: 4.774833
iter: 195 | loss: 4.774218
iter: 196 | loss: 4.773603
iter: 197 | loss: 4.772988
iter: 198 | loss: 4.772373
iter: 199 | loss: 4.771758
iter: 200 | loss: 4.771143
iter: 201 | loss: 4.770528
iter: 202 | loss: 4.769912
iter: 203 | loss: 4.769297
iter: 204 | loss: 4.768682
iter: 205 | loss: 4.768067
iter: 206 | loss: 4.767452
iter: 207 | loss: 4.766837
iter: 208 | loss: 4.766222
iter: 209 | loss: 4.765607
iter: 210 | loss: 4.764992
iter: 211 | loss: 4.764377
iter: 212 | loss: 4.763762
iter: 213 | loss: 4.763147
iter: 214 | loss: 4.762532
iter: 215 | loss: 4.761917
iter: 216 | loss: 4.761302
iter: 217 | loss: 4.760687
iter: 218 | loss: 4.760071
iter: 219 | loss: 4.759456
iter: 220 | loss: 4.758841
iter: 221 | loss: 4.758226
iter: 222 | loss: 4.757611
iter: 223 | loss: 4.756996
iter: 224 | loss: 4.756381
iter: 225 | loss: 4.755766
iter: 226 | loss: 4.755151
iter: 227 | loss: 4.754536
iter: 228 | loss: 4.753921
iter: 229 | loss: 4.753306
iter: 230 | loss: 4.752691
iter: 231 | loss: 4.752076
iter: 232 | loss: 4.751461
iter: 233 | loss: 4.750846
iter: 234 | loss: 4.750230
iter: 235 | loss: 4.749615
iter: 236 | loss: 4.749000
iter: 237 | loss: 4.748385
iter: 238 | loss: 4.747770
iter: 239 | loss: 4.747155
iter: 240 | loss: 4.746540
iter: 241 | loss: 4.745925
iter: 242 | loss: 4.745310
iter: 243 | loss: 4.744695
iter: 244 | loss: 4.744080
iter: 245 | loss: 4.743465
iter: 246 | loss: 4.742850
iter: 247 | loss: 4.742235
iter: 248 | loss: 4.741620
iter: 249 | loss: 4.741004
iter: 250 | loss: 4.740389
iter: 251 | loss: 4.739774
iter: 252 | loss: 4.739159
iter: 253 | loss: 4.738544
iter: 254 | loss: 4.737929
iter: 255 | loss: 4.737314
iter: 256 | loss: 4.736699
iter: 257 | loss: 4.736084
iter: 258 | loss: 4.735469
iter: 259 | loss: 4.734854
iter: 260 | loss: 4.734239
iter: 261 | loss: 4.733624
iter: 262 | loss: 4.733009
iter: 263 | loss: 4.732394
iter: 264 | loss: 4.731779
iter: 265 | loss: 4.731163
iter: 266 | loss: 4.730548
iter: 267 | loss: 4.729933
iter: 268 | loss: 4.729318
iter: 269 | loss: 4.728703
iter: 270 | loss: 4.728088
iter: 271 | loss: 4.727473
iter: 272 | loss: 4.726858
iter: 273 | loss: 4.726243
iter: 274 | loss: 4.725628
iter: 275 | loss: 4.725013
iter: 276 | loss: 4.724398
iter: 277 | loss: 4.723783
iter: 278 | loss: 4.723168
iter: 279 | loss: 4.722553
iter: 280 | loss: 4.721938
iter: 281 | loss: 4.721322
iter: 282 | loss: 4.720707
iter: 283 | loss: 4.720092
iter: 284 | loss: 4.719477
iter: 285 | loss: 4.718862
iter: 286 | loss: 4.718247
iter: 287 | loss: 4.717632
iter: 288 | loss: 4.717017
iter: 289 | loss: 4.716402
iter: 290 | loss: 4.715787
iter: 291 | loss: 4.715172
iter: 292 | loss: 4.714557
iter: 293 | loss: 4.713942
iter: 294 | loss: 4.713327
iter: 295 | loss: 4.712712
iter: 296 | loss: 4.712097
iter: 297 | loss: 4.711481
iter: 298 | loss: 4.710866
iter: 299 | loss: 4.710251
iter: 300 | loss: 4.709636
iter: 301 | loss: 4.709021
iter: 302 | loss: 4.708406
iter: 303 | loss: 4.707791
iter: 304 | loss: 4.707176
iter: 305 | loss: 4.706561
iter: 306 | loss: 4.705946
iter: 307 | loss: 4.705331
iter: 308 | loss: 4.704716
iter: 309 | loss: 4.704101
iter: 310 | loss: 4.703486
iter: 311 | loss: 4.702871
iter: 312 | loss: 4.702255
iter: 313 | loss: 4.701640
iter: 314 | loss: 4.701025
iter: 315 | loss: 4.700410
iter: 316 | loss: 4.699795
iter: 317 | loss: 4.699180
iter: 318 | loss: 4.698565
iter: 319 | loss: 4.697950
iter: 320 | loss: 4.697335
iter: 321 | loss: 4.696720
iter: 322 | loss: 4.696105
iter: 323 | loss: 4.695490
iter: 324 | loss: 4.694875
iter: 325 | loss: 4.694260
iter: 326 | loss: 4.693645
iter: 327 | loss: 4.693030
iter: 328 | loss: 4.692414
iter: 329 | loss: 4.691799
iter: 330 | loss: 4.691184
iter: 331 | loss: 4.690569
iter: 332 | loss: 4.689954
iter: 333 | loss: 4.689339
iter: 334 | loss: 4.688724
iter: 335 | loss: 4.688109
iter: 336 | loss: 4.687494
iter: 337 | loss: 4.686879
iter: 338 | loss: 4.686264
iter: 339 | loss: 4.685649
iter: 340 | loss: 4.685034
iter: 341 | loss: 4.684419
iter: 342 | loss: 4.683804
iter: 343 | loss: 4.683189
iter: 344 | loss: 4.682573
iter: 345 | loss: 4.681958
iter: 346 | loss: 4.681343
iter: 347 | loss: 4.680728
iter: 348 | loss: 4.680113
iter: 349 | loss: 4.679498
iter: 350 | loss: 4.678883
iter: 351 | loss: 4.678268
iter: 352 | loss: 4.677653
iter: 353 | loss: 4.677038
iter: 354 | loss: 4.676423
iter: 355 | loss: 4.675808
iter: 356 | loss: 4.675193
iter: 357 | loss: 4.674578
iter: 358 | loss: 4.673963
iter: 359 | loss: 4.673348
iter: 360 | loss: 4.672732
iter: 361 | loss: 4.672117
iter: 362 | loss: 4.671502
iter: 363 | loss: 4.670887
iter: 364 | loss: 4.670272
iter: 365 | loss: 4.669657
iter: 366 | loss: 4.669042
iter: 367 | loss: 4.668427
iter: 368 | loss: 4.667812
iter: 369 | loss: 4.667197
iter: 370 | loss: 4.666582
iter: 371 | loss: 4.665967
iter: 372 | loss: 4.665352
iter: 373 | loss: 4.664737
iter: 374 | loss: 4.664122
iter: 375 | loss: 4.663506
iter: 376 | loss: 4.662891
iter: 377 | loss: 4.662276
iter: 378 | loss: 4.661661
iter: 379 | loss: 4.661046
iter: 380 | loss: 4.660431
iter: 381 | loss: 4.659816
iter: 382 | loss: 4.659201
iter: 383 | loss: 4.658586
iter: 384 | loss: 4.657971
iter: 385 | loss: 4.657356
iter: 386 | loss: 4.656741
iter: 387 | loss: 4.656126
iter: 388 | loss: 4.655511
iter: 389 | loss: 4.654896
iter: 390 | loss: 4.654281
iter: 391 | loss: 4.653665
iter: 392 | loss: 4.653050
iter: 393 | loss: 4.652435
iter: 394 | loss: 4.651820
iter: 395 | loss: 4.651205
iter: 396 | loss: 4.650590
iter: 397 | loss: 4.649975
iter: 398 | loss: 4.649360
iter: 399 | loss: 4.648745
iter: 400 | loss: 4.648130
iter: 401 | loss: 4.647515
iter: 402 | loss: 4.646900
iter: 403 | loss: 4.646285
iter: 404 | loss: 4.645670
iter: 405 | loss: 4.645055
iter: 406 | loss: 4.644440
iter: 407 | loss: 4.643824
iter: 408 | loss: 4.643209
iter: 409 | loss: 4.642594
iter: 410 | loss: 4.641979
iter: 411 | loss: 4.641364
iter: 412 | loss: 4.640749
iter: 413 | loss: 4.640134
iter: 414 | loss: 4.639519
iter: 415 | loss: 4.638904
iter: 416 | loss: 4.638289
iter: 417 | loss: 4.637674
iter: 418 | loss: 4.637059
iter: 419 | loss: 4.636444
iter: 420 | loss: 4.635829
iter: 421 | loss: 4.635214
iter: 422 | loss: 4.634598
iter: 423 | loss: 4.633983
iter: 424 | loss: 4.633368
iter: 425 | loss: 4.632753
iter: 426 | loss: 4.632138
iter: 427 | loss: 4.631523
iter: 428 | loss: 4.630908
iter: 429 | loss: 4.630293
iter: 430 | loss: 4.629678
iter: 431 | loss: 4.629063
iter: 432 | loss: 4.628448
iter: 433 | loss: 4.627833
iter: 434 | loss: 4.627218
iter: 435 | loss: 4.626603
iter: 436 | loss: 4.625988
iter: 437 | loss: 4.625373
iter: 438 | loss: 4.624757
iter: 439 | loss: 4.624142
iter: 440 | loss: 4.623527
iter: 441 | loss: 4.622912
iter: 442 | loss: 4.622297
iter: 443 | loss: 4.621682
iter: 444 | loss: 4.621067
iter: 445 | loss: 4.620452
iter: 446 | loss: 4.619837
iter: 447 | loss: 4.619222
iter: 448 | loss: 4.618607
iter: 449 | loss: 4.617992
iter: 450 | loss: 4.617377
iter: 451 | loss: 4.616762
iter: 452 | loss: 4.616147
iter: 453 | loss: 4.615532
iter: 454 | loss: 4.614916
iter: 455 | loss: 4.614301
iter: 456 | loss: 4.613686
iter: 457 | loss: 4.613071
iter: 458 | loss: 4.612456
iter: 459 | loss: 4.611841
iter: 460 | loss: 4.611226
iter: 461 | loss: 4.610611
iter: 462 | loss: 4.609996
iter: 463 | loss: 4.609381
iter: 464 | loss: 4.608766
iter: 465 | loss: 4.608151
iter: 466 | loss: 4.607536
iter: 467 | loss: 4.606921
iter: 468 | loss: 4.606306
iter: 469 | loss: 4.605691
iter: 470 | loss: 4.605075
iter: 471 | loss: 4.604460
iter: 472 | loss: 4.603845
iter: 473 | loss: 4.603230
iter: 474 | loss: 4.602615
iter: 475 | loss: 4.602000
iter: 476 | loss: 4.601385
iter: 477 | loss: 4.600770
iter: 478 | loss: 4.600155
iter: 479 | loss: 4.599540
iter: 480 | loss: 4.598925
iter: 481 | loss: 4.598310
iter: 482 | loss: 4.597695
iter: 483 | loss: 4.597080
iter: 484 | loss: 4.596465
iter: 485 | loss: 4.595849
iter: 486 | loss: 4.595234
iter: 487 | loss: 4.594619
iter: 488 | loss: 4.594004
iter: 489 | loss: 4.593389
iter: 490 | loss: 4.592774
iter: 491 | loss: 4.592159
iter: 492 | loss: 4.591544
iter: 493 | loss: 4.590929
iter: 494 | loss: 4.590314
iter: 495 | loss: 4.589699
iter: 496 | loss: 4.589084
iter: 497 | loss: 4.588469
iter: 498 | loss: 4.587854
iter: 499 | loss: 4.587239
iter: 500 | loss: 4.586624
iter: 501 | loss: 4.586008
iter: 502 | loss: 4.585393
iter: 503 | loss: 4.584778
iter: 504 | loss: 4.584163
iter: 505 | loss: 4.583548
iter: 506 | loss: 4.582933
iter: 507 | loss: 4.582318
iter: 508 | loss: 4.581703
iter: 509 | loss: 4.581088
iter: 510 | loss: 4.580473
iter: 511 | loss: 4.579858
iter: 512 | loss: 4.579243
iter: 513 | loss: 4.578628
iter: 514 | loss: 4.578013
iter: 515 | loss: 4.577398
iter: 516 | loss: 4.576783
iter: 517 | loss: 4.576167
iter: 518 | loss: 4.575552
iter: 519 | loss: 4.574937
iter: 520 | loss: 4.574322
iter: 521 | loss: 4.573707
iter: 522 | loss: 4.573092
iter: 523 | loss: 4.572477
iter: 524 | loss: 4.571862
iter: 525 | loss: 4.571247
iter: 526 | loss: 4.570632
iter: 527 | loss: 4.570017
iter: 528 | loss: 4.569402
iter: 529 | loss: 4.568787
iter: 530 | loss: 4.568172
iter: 531 | loss: 4.567557
iter: 532 | loss: 4.566942
iter: 533 | loss: 4.566326
iter: 534 | loss: 4.565711
iter: 535 | loss: 4.565096
iter: 536 | loss: 4.564481
iter: 537 | loss: 4.563866
iter: 538 | loss: 4.563251
iter: 539 | loss: 4.562636
iter: 540 | loss: 4.562021
iter: 541 | loss: 4.561406
iter: 542 | loss: 4.560791
iter: 543 | loss: 4.560176
iter: 544 | loss: 4.559561
iter: 545 | loss: 4.558946
iter: 546 | loss: 4.558331
iter: 547 | loss: 4.557716
iter: 548 | loss: 4.557100
iter: 549 | loss: 4.556485
iter: 550 | loss: 4.555870
iter: 551 | loss: 4.555255
iter: 552 | loss: 4.554640
iter: 553 | loss: 4.554025
iter: 554 | loss: 4.553410
iter: 555 | loss: 4.552795
iter: 556 | loss: 4.552180
iter: 557 | loss: 4.551565
iter: 558 | loss: 4.550950
iter: 559 | loss: 4.550335
iter: 560 | loss: 4.549720
iter: 561 | loss: 4.549105
iter: 562 | loss: 4.548490
iter: 563 | loss: 4.547875
iter: 564 | loss: 4.547259
iter: 565 | loss: 4.546644
iter: 566 | loss: 4.546029
iter: 567 | loss: 4.545414
iter: 568 | loss: 4.544799
iter: 569 | loss: 4.544184
iter: 570 | loss: 4.543569
iter: 571 | loss: 4.542954
iter: 572 | loss: 4.542339
iter: 573 | loss: 4.541724
iter: 574 | loss: 4.541109
iter: 575 | loss: 4.540494
iter: 576 | loss: 4.539879
iter: 577 | loss: 4.539264
iter: 578 | loss: 4.538649
iter: 579 | loss: 4.538034
iter: 580 | loss: 4.537418
iter: 581 | loss: 4.536803
iter: 582 | loss: 4.536188
iter: 583 | loss: 4.535573
iter: 584 | loss: 4.534958
iter: 585 | loss: 4.534343
iter: 586 | loss: 4.533728
iter: 587 | loss: 4.533113
iter: 588 | loss: 4.532498
iter: 589 | loss: 4.531883
iter: 590 | loss: 4.531268
iter: 591 | loss: 4.530653
iter: 592 | loss: 4.530038
iter: 593 | loss: 4.529423
iter: 594 | loss: 4.528808
iter: 595 | loss: 4.528193
iter: 596 | loss: 4.527577
iter: 597 | loss: 4.526962
iter: 598 | loss: 4.526347
iter: 599 | loss: 4.525732
iter: 600 | loss: 4.525117
iter: 601 | loss: 4.524502
iter: 602 | loss: 4.523887
iter: 603 | loss: 4.523272
iter: 604 | loss: 4.522657
iter: 605 | loss: 4.522042
iter: 606 | loss: 4.521427
iter: 607 | loss: 4.520812
iter: 608 | loss: 4.520197
iter: 609 | loss: 4.519582
iter: 610 | loss: 4.518967
iter: 611 | loss: 4.518351
iter: 612 | loss: 4.517736
iter: 613 | loss: 4.517121
iter: 614 | loss: 4.516506
iter: 615 | loss: 4.515891
iter: 616 | loss: 4.515276
iter: 617 | loss: 4.514661
iter: 618 | loss: 4.514046
iter: 619 | loss: 4.513431
iter: 620 | loss: 4.512816
iter: 621 | loss: 4.512201
iter: 622 | loss: 4.511586
iter: 623 | loss: 4.510971
iter: 624 | loss: 4.510356
iter: 625 | loss: 4.509741
iter: 626 | loss: 4.509126
iter: 627 | loss: 4.508510
iter: 628 | loss: 4.507895
iter: 629 | loss: 4.507280
iter: 630 | loss: 4.506665
iter: 631 | loss: 4.506050
iter: 632 | loss: 4.505435
iter: 633 | loss: 4.504820
iter: 634 | loss: 4.504205
iter: 635 | loss: 4.503590
iter: 636 | loss: 4.502975
iter: 637 | loss: 4.502360
iter: 638 | loss: 4.501745
iter: 639 | loss: 4.501130
iter: 640 | loss: 4.500515
iter: 641 | loss: 4.499900
iter: 642 | loss: 4.499285
iter: 643 | loss: 4.498669
iter: 644 | loss: 4.498054
iter: 645 | loss: 4.497439
iter: 646 | loss: 4.496824
iter: 647 | loss: 4.496209
iter: 648 | loss: 4.495594
iter: 649 | loss: 4.494979
iter: 650 | loss: 4.494364
iter: 651 | loss: 4.493749
iter: 652 | loss: 4.493134
iter: 653 | loss: 4.492519
iter: 654 | loss: 4.491904
iter: 655 | loss: 4.491289
iter: 656 | loss: 4.490674
iter: 657 | loss: 4.490059
iter: 658 | loss: 4.489443
iter: 659 | loss: 4.488828
iter: 660 | loss: 4.488213
iter: 661 | loss: 4.487598
iter: 662 | loss: 4.486983
iter: 663 | loss: 4.486368
iter: 664 | loss: 4.485753
iter: 665 | loss: 4.485138
iter: 666 | loss: 4.484523
iter: 667 | loss: 4.483908
iter: 668 | loss: 4.483293
iter: 669 | loss: 4.482678
iter: 670 | loss: 4.482063
iter: 671 | loss: 4.481448
iter: 672 | loss: 4.480833
iter: 673 | loss: 4.480218
iter: 674 | loss: 4.479602
iter: 675 | loss: 4.478987
iter: 676 | loss: 4.478372
iter: 677 | loss: 4.477757
iter: 678 | loss: 4.477142
iter: 679 | loss: 4.476527
iter: 680 | loss: 4.475912
iter: 681 | loss: 4.475297
iter: 682 | loss: 4.474682
iter: 683 | loss: 4.474067
iter: 684 | loss: 4.473452
iter: 685 | loss: 4.472837
iter: 686 | loss: 4.472222
iter: 687 | loss: 4.471607
iter: 688 | loss: 4.470992
iter: 689 | loss: 4.470377
iter: 690 | loss: 4.469761
iter: 691 | loss: 4.469146
iter: 692 | loss: 4.468531
iter: 693 | loss: 4.467916
iter: 694 | loss: 4.467301
iter: 695 | loss: 4.466686
iter: 696 | loss: 4.466071
iter: 697 | loss: 4.465456
iter: 698 | loss: 4.464841
iter: 699 | loss: 4.464226
iter: 700 | loss: 4.463611
iter: 701 | loss: 4.462996
iter: 702 | loss: 4.462381
iter: 703 | loss: 4.461766
iter: 704 | loss: 4.461151
iter: 705 | loss: 4.460536
iter: 706 | loss: 4.459920
iter: 707 | loss: 4.459305
iter: 708 | loss: 4.458690
iter: 709 | loss: 4.458075
iter: 710 | loss: 4.457460
iter: 711 | loss: 4.456845
iter: 712 | loss: 4.456230
iter: 713 | loss: 4.455615
iter: 714 | loss: 4.455000
iter: 715 | loss: 4.454385
iter: 716 | loss: 4.453770
iter: 717 | loss: 4.453155
iter: 718 | loss: 4.452540
iter: 719 | loss: 4.451925
iter: 720 | loss: 4.451310
iter: 721 | loss: 4.450694
iter: 722 | loss: 4.450079
iter: 723 | loss: 4.449464
iter: 724 | loss: 4.448849
iter: 725 | loss: 4.448234
iter: 726 | loss: 4.447619
iter: 727 | loss: 4.447004
iter: 728 | loss: 4.446389
iter: 729 | loss: 4.445774
iter: 730 | loss: 4.445159
iter: 731 | loss: 4.444544
iter: 732 | loss: 4.443929
iter: 733 | loss: 4.443314
iter: 734 | loss: 4.442699
iter: 735 | loss: 4.442084
iter: 736 | loss: 4.441469
iter: 737 | loss: 4.440853
iter: 738 | loss: 4.440238
iter: 739 | loss: 4.439623
iter: 740 | loss: 4.439008
iter: 741 | loss: 4.438393
iter: 742 | loss: 4.437778
iter: 743 | loss: 4.437163
iter: 744 | loss: 4.436548
iter: 745 | loss: 4.435933
iter: 746 | loss: 4.435318
iter: 747 | loss: 4.434703
iter: 748 | loss: 4.434088
iter: 749 | loss: 4.433473
iter: 750 | loss: 4.432858
iter: 751 | loss: 4.432243
iter: 752 | loss: 4.431628
iter: 753 | loss: 4.431012
iter: 754 | loss: 4.430397
iter: 755 | loss: 4.429782
iter: 756 | loss: 4.429167
iter: 757 | loss: 4.428552
iter: 758 | loss: 4.427937
iter: 759 | loss: 4.427322
iter: 760 | loss: 4.426707
iter: 761 | loss: 4.426092
iter: 762 | loss: 4.425477
iter: 763 | loss: 4.424862
iter: 764 | loss: 4.424247
iter: 765 | loss: 4.423632
iter: 766 | loss: 4.423017
iter: 767 | loss: 4.422402
iter: 768 | loss: 4.421787
iter: 769 | loss: 4.421171
iter: 770 | loss: 4.420556
iter: 771 | loss: 4.419941
iter: 772 | loss: 4.419326
iter: 773 | loss: 4.418711
iter: 774 | loss: 4.418096
iter: 775 | loss: 4.417481
iter: 776 | loss: 4.416866
iter: 777 | loss: 4.416251
iter: 778 | loss: 4.415636
iter: 779 | loss: 4.415021
iter: 780 | loss: 4.414406
iter: 781 | loss: 4.413791
iter: 782 | loss: 4.413176
iter: 783 | loss: 4.412561
iter: 784 | loss: 4.411945
iter: 785 | loss: 4.411330
iter: 786 | loss: 4.410715
iter: 787 | loss: 4.410100
iter: 788 | loss: 4.409485
iter: 789 | loss: 4.408870
iter: 790 | loss: 4.408255
iter: 791 | loss: 4.407640
iter: 792 | loss: 4.407025
iter: 793 | loss: 4.406410
iter: 794 | loss: 4.405795
iter: 795 | loss: 4.405180
iter: 796 | loss: 4.404565
iter: 797 | loss: 4.403950
iter: 798 | loss: 4.403335
iter: 799 | loss: 4.402720
iter: 800 | loss: 4.402104
iter: 801 | loss: 4.401489
iter: 802 | loss: 4.400874
iter: 803 | loss: 4.400259
iter: 804 | loss: 4.399644
iter: 805 | loss: 4.399029
iter: 806 | loss: 4.398414
iter: 807 | loss: 4.397799
iter: 808 | loss: 4.397184
iter: 809 | loss: 4.396569
iter: 810 | loss: 4.395954
iter: 811 | loss: 4.395339
iter: 812 | loss: 4.394724
iter: 813 | loss: 4.394109
iter: 814 | loss: 4.393494
iter: 815 | loss: 4.392879
iter: 816 | loss: 4.392263
iter: 817 | loss: 4.391648
iter: 818 | loss: 4.391033
iter: 819 | loss: 4.390418
iter: 820 | loss: 4.389803
iter: 821 | loss: 4.389188
iter: 822 | loss: 4.388573
iter: 823 | loss: 4.387958
iter: 824 | loss: 4.387343
iter: 825 | loss: 4.386728
iter: 826 | loss: 4.386113
iter: 827 | loss: 4.385498
iter: 828 | loss: 4.384883
iter: 829 | loss: 4.384268
iter: 830 | loss: 4.383653
iter: 831 | loss: 4.383037
iter: 832 | loss: 4.382422
iter: 833 | loss: 4.381807
iter: 834 | loss: 4.381192
iter: 835 | loss: 4.380577
iter: 836 | loss: 4.379962
iter: 837 | loss: 4.379347
iter: 838 | loss: 4.378732
iter: 839 | loss: 4.378117
iter: 840 | loss: 4.377502
iter: 841 | loss: 4.376887
iter: 842 | loss: 4.376272
iter: 843 | loss: 4.375657
iter: 844 | loss: 4.375042
iter: 845 | loss: 4.374427
iter: 846 | loss: 4.373812
iter: 847 | loss: 4.373196
iter: 848 | loss: 4.372581
iter: 849 | loss: 4.371966
iter: 850 | loss: 4.371351
iter: 851 | loss: 4.370736
iter: 852 | loss: 4.370121
iter: 853 | loss: 4.369506
iter: 854 | loss: 4.368891
iter: 855 | loss: 4.368276
iter: 856 | loss: 4.367661
iter: 857 | loss: 4.367046
iter: 858 | loss: 4.366431
iter: 859 | loss: 4.365816
iter: 860 | loss: 4.365201
iter: 861 | loss: 4.364586
iter: 862 | loss: 4.363971
iter: 863 | loss: 4.363355
iter: 864 | loss: 4.362740
iter: 865 | loss: 4.362125
iter: 866 | loss: 4.361510
iter: 867 | loss: 4.360895
iter: 868 | loss: 4.360280
iter: 869 | loss: 4.359665
iter: 870 | loss: 4.359050
iter: 871 | loss: 4.358435
iter: 872 | loss: 4.357820
iter: 873 | loss: 4.357205
iter: 874 | loss: 4.356590
iter: 875 | loss: 4.355975
iter: 876 | loss: 4.355360
iter: 877 | loss: 4.354745
iter: 878 | loss: 4.354130
iter: 879 | loss: 4.353514
iter: 880 | loss: 4.352899
iter: 881 | loss: 4.352284
iter: 882 | loss: 4.351669
iter: 883 | loss: 4.351054
iter: 884 | loss: 4.350439
iter: 885 | loss: 4.349824
iter: 886 | loss: 4.349209
iter: 887 | loss: 4.348594
iter: 888 | loss: 4.347979
iter: 889 | loss: 4.347364
iter: 890 | loss: 4.346749
iter: 891 | loss: 4.346134
iter: 892 | loss: 4.345519
iter: 893 | loss: 4.344904
iter: 894 | loss: 4.344288
iter: 895 | loss: 4.343673
iter: 896 | loss: 4.343058
iter: 897 | loss: 4.342443
iter: 898 | loss: 4.341828
iter: 899 | loss: 4.341213
iter: 900 | loss: 4.340598
iter: 901 | loss: 4.339983
iter: 902 | loss: 4.339368
iter: 903 | loss: 4.338753
iter: 904 | loss: 4.338138
iter: 905 | loss: 4.337523
iter: 906 | loss: 4.336908
iter: 907 | loss: 4.336293
iter: 908 | loss: 4.335678
iter: 909 | loss: 4.335063
iter: 910 | loss: 4.334447
iter: 911 | loss: 4.333832
iter: 912 | loss: 4.333217
iter: 913 | loss: 4.332602
iter: 914 | loss: 4.331987
iter: 915 | loss: 4.331372
iter: 916 | loss: 4.330757
iter: 917 | loss: 4.330142
iter: 918 | loss: 4.329527
iter: 919 | loss: 4.328912
iter: 920 | loss: 4.328297
iter: 921 | loss: 4.327682
iter: 922 | loss: 4.327067
iter: 923 | loss: 4.326452
iter: 924 | loss: 4.325837
iter: 925 | loss: 4.325222
iter: 926 | loss: 4.324606
iter: 927 | loss: 4.323991
iter: 928 | loss: 4.323376
iter: 929 | loss: 4.322761
iter: 930 | loss: 4.322146
iter: 931 | loss: 4.321531
iter: 932 | loss: 4.320916
iter: 933 | loss: 4.320301
iter: 934 | loss: 4.319686
iter: 935 | loss: 4.319071
iter: 936 | loss: 4.318456
iter: 937 | loss: 4.317841
iter: 938 | loss: 4.317226
iter: 939 | loss: 4.316611
iter: 940 | loss: 4.315996
iter: 941 | loss: 4.315381
iter: 942 | loss: 4.314765
iter: 943 | loss: 4.314150
iter: 944 | loss: 4.313535
iter: 945 | loss: 4.312920
iter: 946 | loss: 4.312305
iter: 947 | loss: 4.311690
iter: 948 | loss: 4.311075
iter: 949 | loss: 4.310460
iter: 950 | loss: 4.309845
iter: 951 | loss: 4.309230
iter: 952 | loss: 4.308615
iter: 953 | loss: 4.308000
iter: 954 | loss: 4.307385
iter: 955 | loss: 4.306770
iter: 956 | loss: 4.306155
iter: 957 | loss: 4.305539
iter: 958 | loss: 4.304924
iter: 959 | loss: 4.304309
iter: 960 | loss: 4.303694
iter: 961 | loss: 4.303079
iter: 962 | loss: 4.302464
iter: 963 | loss: 4.301849
iter: 964 | loss: 4.301234
iter: 965 | loss: 4.300619
iter: 966 | loss: 4.300004
iter: 967 | loss: 4.299389
iter: 968 | loss: 4.298774
iter: 969 | loss: 4.298159
iter: 970 | loss: 4.297544
iter: 971 | loss: 4.296929
iter: 972 | loss: 4.296314
iter: 973 | loss: 4.295698
iter: 974 | loss: 4.295083
iter: 975 | loss: 4.294468
iter: 976 | loss: 4.293853
iter: 977 | loss: 4.293238
iter: 978 | loss: 4.292623
iter: 979 | loss: 4.292008
iter: 980 | loss: 4.291393
iter: 981 | loss: 4.290778
iter: 982 | loss: 4.290163
iter: 983 | loss: 4.289548
iter: 984 | loss: 4.288933
iter: 985 | loss: 4.288318
iter: 986 | loss: 4.287703
iter: 987 | loss: 4.287088
iter: 988 | loss: 4.286473
iter: 989 | loss: 4.285857
iter: 990 | loss: 4.285242
iter: 991 | loss: 4.284627
iter: 992 | loss: 4.284012
iter: 993 | loss: 4.283397
iter: 994 | loss: 4.282782
iter: 995 | loss: 4.282167
iter: 996 | loss: 4.281552
iter: 997 | loss: 4.280937
iter: 998 | loss: 4.280322
iter: 999 | loss: 4.279707
iter: 1000 | loss: 4.279092
iter: 1001 | loss: 4.278477
iter: 1002 | loss: 4.277862
iter: 1003 | loss: 4.277247
iter: 1004 | loss: 4.276632
iter: 1005 | loss: 4.276016
iter: 1006 | loss: 4.275401
iter: 1007 | loss: 4.274786
iter: 1008 | loss: 4.274171
iter: 1009 | loss: 4.273556
iter: 1010 | loss: 4.272941
iter: 1011 | loss: 4.272326
iter: 1012 | loss: 4.271711
iter: 1013 | loss: 4.271096
iter: 1014 | loss: 4.270481
iter: 1015 | loss: 4.269866
iter: 1016 | loss: 4.269251
iter: 1017 | loss: 4.268636
iter: 1018 | loss: 4.268021
iter: 1019 | loss: 4.267406
iter: 1020 | loss: 4.266790
iter: 1021 | loss: 4.266175
iter: 1022 | loss: 4.265560
iter: 1023 | loss: 4.264945
iter: 1024 | loss: 4.264330
iter: 1025 | loss: 4.263715
iter: 1026 | loss: 4.263100
iter: 1027 | loss: 4.262485
iter: 1028 | loss: 4.261870
iter: 1029 | loss: 4.261255
iter: 1030 | loss: 4.260640
iter: 1031 | loss: 4.260025
iter: 1032 | loss: 4.259410
iter: 1033 | loss: 4.258795
iter: 1034 | loss: 4.258180
iter: 1035 | loss: 4.257565
iter: 1036 | loss: 4.256949
iter: 1037 | loss: 4.256334
iter: 1038 | loss: 4.255719
iter: 1039 | loss: 4.255104
iter: 1040 | loss: 4.254489
iter: 1041 | loss: 4.253874
iter: 1042 | loss: 4.253259
iter: 1043 | loss: 4.252644
iter: 1044 | loss: 4.252029
iter: 1045 | loss: 4.251414
iter: 1046 | loss: 4.250799
iter: 1047 | loss: 4.250184
iter: 1048 | loss: 4.249569
iter: 1049 | loss: 4.248954
iter: 1050 | loss: 4.248339
iter: 1051 | loss: 4.247724
iter: 1052 | loss: 4.247108
iter: 1053 | loss: 4.246493
iter: 1054 | loss: 4.245878
iter: 1055 | loss: 4.245263
iter: 1056 | loss: 4.244648
iter: 1057 | loss: 4.244033
iter: 1058 | loss: 4.243418
iter: 1059 | loss: 4.242803
iter: 1060 | loss: 4.242188
iter: 1061 | loss: 4.241573
iter: 1062 | loss: 4.240958
iter: 1063 | loss: 4.240343
iter: 1064 | loss: 4.239728
iter: 1065 | loss: 4.239113
iter: 1066 | loss: 4.238498
iter: 1067 | loss: 4.237882
iter: 1068 | loss: 4.237267
iter: 1069 | loss: 4.236652
iter: 1070 | loss: 4.236037
iter: 1071 | loss: 4.235422
iter: 1072 | loss: 4.234807
iter: 1073 | loss: 4.234192
iter: 1074 | loss: 4.233577
iter: 1075 | loss: 4.232962
iter: 1076 | loss: 4.232347
iter: 1077 | loss: 4.231732
iter: 1078 | loss: 4.231117
iter: 1079 | loss: 4.230502
iter: 1080 | loss: 4.229887
iter: 1081 | loss: 4.229272
iter: 1082 | loss: 4.228657
iter: 1083 | loss: 4.228041
iter: 1084 | loss: 4.227426
iter: 1085 | loss: 4.226811
iter: 1086 | loss: 4.226196
iter: 1087 | loss: 4.225581
iter: 1088 | loss: 4.224966
iter: 1089 | loss: 4.224351
iter: 1090 | loss: 4.223736
iter: 1091 | loss: 4.223121
iter: 1092 | loss: 4.222506
iter: 1093 | loss: 4.221891
iter: 1094 | loss: 4.221276
iter: 1095 | loss: 4.220661
iter: 1096 | loss: 4.220046
iter: 1097 | loss: 4.219431
iter: 1098 | loss: 4.218816
iter: 1099 | loss: 4.218200
iter: 1100 | loss: 4.217585
iter: 1101 | loss: 4.216970
iter: 1102 | loss: 4.216355
iter: 1103 | loss: 4.215740
iter: 1104 | loss: 4.215125
iter: 1105 | loss: 4.214510
iter: 1106 | loss: 4.213895
iter: 1107 | loss: 4.213280
iter: 1108 | loss: 4.212665
iter: 1109 | loss: 4.212050
iter: 1110 | loss: 4.211435
iter: 1111 | loss: 4.210820
iter: 1112 | loss: 4.210205
iter: 1113 | loss: 4.209590
iter: 1114 | loss: 4.208975
iter: 1115 | loss: 4.208359
iter: 1116 | loss: 4.207744
iter: 1117 | loss: 4.207129
iter: 1118 | loss: 4.206514
iter: 1119 | loss: 4.205899
iter: 1120 | loss: 4.205284
iter: 1121 | loss: 4.204669
iter: 1122 | loss: 4.204054
iter: 1123 | loss: 4.203439
iter: 1124 | loss: 4.202824
iter: 1125 | loss: 4.202209
iter: 1126 | loss: 4.201594
iter: 1127 | loss: 4.200979
iter: 1128 | loss: 4.200364
iter: 1129 | loss: 4.199749
iter: 1130 | loss: 4.199133
iter: 1131 | loss: 4.198518
iter: 1132 | loss: 4.197903
iter: 1133 | loss: 4.197288
iter: 1134 | loss: 4.196673
iter: 1135 | loss: 4.196058
iter: 1136 | loss: 4.195443
iter: 1137 | loss: 4.194828
iter: 1138 | loss: 4.194213
iter: 1139 | loss: 4.193598
iter: 1140 | loss: 4.192983
iter: 1141 | loss: 4.192368
iter: 1142 | loss: 4.191753
iter: 1143 | loss: 4.191138
iter: 1144 | loss: 4.190523
iter: 1145 | loss: 4.189908
iter: 1146 | loss: 4.189292
iter: 1147 | loss: 4.188677
iter: 1148 | loss: 4.188062
iter: 1149 | loss: 4.187447
iter: 1150 | loss: 4.186832
iter: 1151 | loss: 4.186217
iter: 1152 | loss: 4.185602
iter: 1153 | loss: 4.184987
iter: 1154 | loss: 4.184372
iter: 1155 | loss: 4.183757
iter: 1156 | loss: 4.183142
iter: 1157 | loss: 4.182527
iter: 1158 | loss: 4.181912
iter: 1159 | loss: 4.181297
iter: 1160 | loss: 4.180682
iter: 1161 | loss: 4.180067
iter: 1162 | loss: 4.179451
iter: 1163 | loss: 4.178836
iter: 1164 | loss: 4.178221
iter: 1165 | loss: 4.177606
iter: 1166 | loss: 4.176991
iter: 1167 | loss: 4.176376
iter: 1168 | loss: 4.175761
iter: 1169 | loss: 4.175146
iter: 1170 | loss: 4.174531
iter: 1171 | loss: 4.173916
iter: 1172 | loss: 4.173301
iter: 1173 | loss: 4.172686
iter: 1174 | loss: 4.172071
iter: 1175 | loss: 4.171456
iter: 1176 | loss: 4.170841
iter: 1177 | loss: 4.170226
iter: 1178 | loss: 4.169610
iter: 1179 | loss: 4.168995
iter: 1180 | loss: 4.168380
iter: 1181 | loss: 4.167765
iter: 1182 | loss: 4.167150
iter: 1183 | loss: 4.166535
iter: 1184 | loss: 4.165920
iter: 1185 | loss: 4.165305
iter: 1186 | loss: 4.164690
iter: 1187 | loss: 4.164075
iter: 1188 | loss: 4.163460
iter: 1189 | loss: 4.162845
iter: 1190 | loss: 4.162230
iter: 1191 | loss: 4.161615
iter: 1192 | loss: 4.161000
iter: 1193 | loss: 4.160384
iter: 1194 | loss: 4.159769
iter: 1195 | loss: 4.159154
iter: 1196 | loss: 4.158539
iter: 1197 | loss: 4.157924
iter: 1198 | loss: 4.157309
iter: 1199 | loss: 4.156694
iter: 1200 | loss: 4.156079
iter: 1201 | loss: 4.155464
iter: 1202 | loss: 4.154849
iter: 1203 | loss: 4.154234
iter: 1204 | loss: 4.153619
iter: 1205 | loss: 4.153004
iter: 1206 | loss: 4.152389
iter: 1207 | loss: 4.151774
iter: 1208 | loss: 4.151159
iter: 1209 | loss: 4.150543
iter: 1210 | loss: 4.149928
iter: 1211 | loss: 4.149313
iter: 1212 | loss: 4.148698
iter: 1213 | loss: 4.148083
iter: 1214 | loss: 4.147468
iter: 1215 | loss: 4.146853
iter: 1216 | loss: 4.146238
iter: 1217 | loss: 4.145623
iter: 1218 | loss: 4.145008
iter: 1219 | loss: 4.144393
iter: 1220 | loss: 4.143778
iter: 1221 | loss: 4.143163
iter: 1222 | loss: 4.142548
iter: 1223 | loss: 4.141933
iter: 1224 | loss: 4.141318
iter: 1225 | loss: 4.140702
iter: 1226 | loss: 4.140087
iter: 1227 | loss: 4.139472
iter: 1228 | loss: 4.138857
iter: 1229 | loss: 4.138242
iter: 1230 | loss: 4.137627
iter: 1231 | loss: 4.137012
iter: 1232 | loss: 4.136397
iter: 1233 | loss: 4.135782
iter: 1234 | loss: 4.135167
iter: 1235 | loss: 4.134552
iter: 1236 | loss: 4.133937
iter: 1237 | loss: 4.133322
iter: 1238 | loss: 4.132707
iter: 1239 | loss: 4.132092
iter: 1240 | loss: 4.131477
iter: 1241 | loss: 4.130861
iter: 1242 | loss: 4.130246
iter: 1243 | loss: 4.129631
iter: 1244 | loss: 4.129016
iter: 1245 | loss: 4.128401
iter: 1246 | loss: 4.127786
iter: 1247 | loss: 4.127171
iter: 1248 | loss: 4.126556
iter: 1249 | loss: 4.125941
iter: 1250 | loss: 4.125326
iter: 1251 | loss: 4.124711
iter: 1252 | loss: 4.124096
iter: 1253 | loss: 4.123481
iter: 1254 | loss: 4.122866
iter: 1255 | loss: 4.122251
iter: 1256 | loss: 4.121635
iter: 1257 | loss: 4.121020
iter: 1258 | loss: 4.120405
iter: 1259 | loss: 4.119790
iter: 1260 | loss: 4.119175
iter: 1261 | loss: 4.118560
iter: 1262 | loss: 4.117945
iter: 1263 | loss: 4.117330
iter: 1264 | loss: 4.116715
iter: 1265 | loss: 4.116100
iter: 1266 | loss: 4.115485
iter: 1267 | loss: 4.114870
iter: 1268 | loss: 4.114255
iter: 1269 | loss: 4.113640
iter: 1270 | loss: 4.113025
iter: 1271 | loss: 4.112410
iter: 1272 | loss: 4.111794
iter: 1273 | loss: 4.111179
iter: 1274 | loss: 4.110564
iter: 1275 | loss: 4.109949
iter: 1276 | loss: 4.109334
iter: 1277 | loss: 4.108719
iter: 1278 | loss: 4.108104
iter: 1279 | loss: 4.107489
iter: 1280 | loss: 4.106874
iter: 1281 | loss: 4.106259
iter: 1282 | loss: 4.105644
iter: 1283 | loss: 4.105029
iter: 1284 | loss: 4.104414
iter: 1285 | loss: 4.103799
iter: 1286 | loss: 4.103184
iter: 1287 | loss: 4.102569
iter: 1288 | loss: 4.101953
iter: 1289 | loss: 4.101338
iter: 1290 | loss: 4.100723
iter: 1291 | loss: 4.100108
iter: 1292 | loss: 4.099493
iter: 1293 | loss: 4.098878
iter: 1294 | loss: 4.098263
iter: 1295 | loss: 4.097648
iter: 1296 | loss: 4.097033
iter: 1297 | loss: 4.096418
iter: 1298 | loss: 4.095803
iter: 1299 | loss: 4.095188
iter: 1300 | loss: 4.094573
iter: 1301 | loss: 4.093958
iter: 1302 | loss: 4.093343
iter: 1303 | loss: 4.092727
iter: 1304 | loss: 4.092112
iter: 1305 | loss: 4.091497
iter: 1306 | loss: 4.090882
iter: 1307 | loss: 4.090267
iter: 1308 | loss: 4.089652
iter: 1309 | loss: 4.089037
iter: 1310 | loss: 4.088422
iter: 1311 | loss: 4.087807
iter: 1312 | loss: 4.087192
iter: 1313 | loss: 4.086577
iter: 1314 | loss: 4.085962
iter: 1315 | loss: 4.085347
iter: 1316 | loss: 4.084732
iter: 1317 | loss: 4.084117
iter: 1318 | loss: 4.083502
iter: 1319 | loss: 4.082886
iter: 1320 | loss: 4.082271
iter: 1321 | loss: 4.081656
iter: 1322 | loss: 4.081041
iter: 1323 | loss: 4.080426
iter: 1324 | loss: 4.079811
iter: 1325 | loss: 4.079196
iter: 1326 | loss: 4.078581
iter: 1327 | loss: 4.077966
iter: 1328 | loss: 4.077351
iter: 1329 | loss: 4.076736
iter: 1330 | loss: 4.076121
iter: 1331 | loss: 4.075506
iter: 1332 | loss: 4.074891
iter: 1333 | loss: 4.074276
iter: 1334 | loss: 4.073661
iter: 1335 | loss: 4.073045
iter: 1336 | loss: 4.072430
iter: 1337 | loss: 4.071815
iter: 1338 | loss: 4.071200
iter: 1339 | loss: 4.070585
iter: 1340 | loss: 4.069970
iter: 1341 | loss: 4.069355
iter: 1342 | loss: 4.068740
iter: 1343 | loss: 4.068125
iter: 1344 | loss: 4.067510
iter: 1345 | loss: 4.066895
iter: 1346 | loss: 4.066280
iter: 1347 | loss: 4.065665
iter: 1348 | loss: 4.065050
iter: 1349 | loss: 4.064435
iter: 1350 | loss: 4.063820
iter: 1351 | loss: 4.063204
iter: 1352 | loss: 4.062589
iter: 1353 | loss: 4.061974
iter: 1354 | loss: 4.061359
iter: 1355 | loss: 4.060744
iter: 1356 | loss: 4.060129
iter: 1357 | loss: 4.059514
iter: 1358 | loss: 4.058899
iter: 1359 | loss: 4.058284
iter: 1360 | loss: 4.057669
iter: 1361 | loss: 4.057054
iter: 1362 | loss: 4.056439
iter: 1363 | loss: 4.055824
iter: 1364 | loss: 4.055209
iter: 1365 | loss: 4.054594
iter: 1366 | loss: 4.053978
iter: 1367 | loss: 4.053363
iter: 1368 | loss: 4.052748
iter: 1369 | loss: 4.052133
iter: 1370 | loss: 4.051518
iter: 1371 | loss: 4.050903
iter: 1372 | loss: 4.050288
iter: 1373 | loss: 4.049673
iter: 1374 | loss: 4.049058
iter: 1375 | loss: 4.048443
iter: 1376 | loss: 4.047828
iter: 1377 | loss: 4.047213
iter: 1378 | loss: 4.046598
iter: 1379 | loss: 4.045983
iter: 1380 | loss: 4.045368
iter: 1381 | loss: 4.044753
iter: 1382 | loss: 4.044137
iter: 1383 | loss: 4.043522
iter: 1384 | loss: 4.042907
iter: 1385 | loss: 4.042292
iter: 1386 | loss: 4.041677
iter: 1387 | loss: 4.041062
iter: 1388 | loss: 4.040447
iter: 1389 | loss: 4.039832
iter: 1390 | loss: 4.039217
iter: 1391 | loss: 4.038602
iter: 1392 | loss: 4.037987
iter: 1393 | loss: 4.037372
iter: 1394 | loss: 4.036757
iter: 1395 | loss: 4.036142
iter: 1396 | loss: 4.035527
iter: 1397 | loss: 4.034912
iter: 1398 | loss: 4.034296
iter: 1399 | loss: 4.033681
iter: 1400 | loss: 4.033066
iter: 1401 | loss: 4.032451
iter: 1402 | loss: 4.031836
iter: 1403 | loss: 4.031221
iter: 1404 | loss: 4.030606
iter: 1405 | loss: 4.029991
iter: 1406 | loss: 4.029376
iter: 1407 | loss: 4.028761
iter: 1408 | loss: 4.028146
iter: 1409 | loss: 4.027531
iter: 1410 | loss: 4.026916
iter: 1411 | loss: 4.026301
iter: 1412 | loss: 4.025686
iter: 1413 | loss: 4.025071
iter: 1414 | loss: 4.024455
iter: 1415 | loss: 4.023840
iter: 1416 | loss: 4.023225
iter: 1417 | loss: 4.022610
iter: 1418 | loss: 4.021995
iter: 1419 | loss: 4.021380
iter: 1420 | loss: 4.020765
iter: 1421 | loss: 4.020150
iter: 1422 | loss: 4.019535
iter: 1423 | loss: 4.018920
iter: 1424 | loss: 4.018305
iter: 1425 | loss: 4.017690
iter: 1426 | loss: 4.017075
iter: 1427 | loss: 4.016460
iter: 1428 | loss: 4.015845
iter: 1429 | loss: 4.015229
iter: 1430 | loss: 4.014614
iter: 1431 | loss: 4.013999
iter: 1432 | loss: 4.013384
iter: 1433 | loss: 4.012769
iter: 1434 | loss: 4.012154
iter: 1435 | loss: 4.011539
iter: 1436 | loss: 4.010924
iter: 1437 | loss: 4.010309
iter: 1438 | loss: 4.009694
iter: 1439 | loss: 4.009079
iter: 1440 | loss: 4.008464
iter: 1441 | loss: 4.007849
iter: 1442 | loss: 4.007234
iter: 1443 | loss: 4.006619
iter: 1444 | loss: 4.006004
iter: 1445 | loss: 4.005388
iter: 1446 | loss: 4.004773
iter: 1447 | loss: 4.004158
iter: 1448 | loss: 4.003543
iter: 1449 | loss: 4.002928
iter: 1450 | loss: 4.002313
iter: 1451 | loss: 4.001698
iter: 1452 | loss: 4.001083
iter: 1453 | loss: 4.000468
iter: 1454 | loss: 3.999853
iter: 1455 | loss: 3.999238
iter: 1456 | loss: 3.998623
iter: 1457 | loss: 3.998008
iter: 1458 | loss: 3.997393
iter: 1459 | loss: 3.996778
iter: 1460 | loss: 3.996163
iter: 1461 | loss: 3.995547
iter: 1462 | loss: 3.994932
iter: 1463 | loss: 3.994317
iter: 1464 | loss: 3.993702
iter: 1465 | loss: 3.993087
iter: 1466 | loss: 3.992472
iter: 1467 | loss: 3.991857
iter: 1468 | loss: 3.991242
iter: 1469 | loss: 3.990627
iter: 1470 | loss: 3.990012
iter: 1471 | loss: 3.989397
iter: 1472 | loss: 3.988782
iter: 1473 | loss: 3.988167
iter: 1474 | loss: 3.987552
iter: 1475 | loss: 3.986937
iter: 1476 | loss: 3.986321
iter: 1477 | loss: 3.985706
iter: 1478 | loss: 3.985091
iter: 1479 | loss: 3.984476
iter: 1480 | loss: 3.983861
iter: 1481 | loss: 3.983246
iter: 1482 | loss: 3.982631
iter: 1483 | loss: 3.982016
iter: 1484 | loss: 3.981401
iter: 1485 | loss: 3.980786
iter: 1486 | loss: 3.980171
iter: 1487 | loss: 3.979556
iter: 1488 | loss: 3.978941
iter: 1489 | loss: 3.978326
iter: 1490 | loss: 3.977711
iter: 1491 | loss: 3.977096
iter: 1492 | loss: 3.976480
iter: 1493 | loss: 3.975865
iter: 1494 | loss: 3.975250
iter: 1495 | loss: 3.974635
iter: 1496 | loss: 3.974020
iter: 1497 | loss: 3.973405
iter: 1498 | loss: 3.972790
iter: 1499 | loss: 3.972175
iter: 1500 | loss: 3.971560
iter: 1501 | loss: 3.970945
iter: 1502 | loss: 3.970330
iter: 1503 | loss: 3.969715
iter: 1504 | loss: 3.969100
iter: 1505 | loss: 3.968485
iter: 1506 | loss: 3.967870
iter: 1507 | loss: 3.967255
iter: 1508 | loss: 3.966639
iter: 1509 | loss: 3.966024
iter: 1510 | loss: 3.965409
iter: 1511 | loss: 3.964794
iter: 1512 | loss: 3.964179
iter: 1513 | loss: 3.963564
iter: 1514 | loss: 3.962949
iter: 1515 | loss: 3.962334
iter: 1516 | loss: 3.961719
iter: 1517 | loss: 3.961104
iter: 1518 | loss: 3.960489
iter: 1519 | loss: 3.959874
iter: 1520 | loss: 3.959259
iter: 1521 | loss: 3.958644
iter: 1522 | loss: 3.958029
iter: 1523 | loss: 3.957414
iter: 1524 | loss: 3.956798
iter: 1525 | loss: 3.956183
iter: 1526 | loss: 3.955568
iter: 1527 | loss: 3.954953
iter: 1528 | loss: 3.954338
iter: 1529 | loss: 3.953723
iter: 1530 | loss: 3.953108
iter: 1531 | loss: 3.952493
iter: 1532 | loss: 3.951878
iter: 1533 | loss: 3.951263
iter: 1534 | loss: 3.950648
iter: 1535 | loss: 3.950033
iter: 1536 | loss: 3.949418
iter: 1537 | loss: 3.948803
iter: 1538 | loss: 3.948188
iter: 1539 | loss: 3.947572
iter: 1540 | loss: 3.946957
iter: 1541 | loss: 3.946342
iter: 1542 | loss: 3.945727
iter: 1543 | loss: 3.945112
iter: 1544 | loss: 3.944497
iter: 1545 | loss: 3.943882
iter: 1546 | loss: 3.943267
iter: 1547 | loss: 3.942652
iter: 1548 | loss: 3.942037
iter: 1549 | loss: 3.941422
iter: 1550 | loss: 3.940807
iter: 1551 | loss: 3.940192
iter: 1552 | loss: 3.939577
iter: 1553 | loss: 3.938962
iter: 1554 | loss: 3.938347
iter: 1555 | loss: 3.937731
iter: 1556 | loss: 3.937116
iter: 1557 | loss: 3.936501
iter: 1558 | loss: 3.935886
iter: 1559 | loss: 3.935271
iter: 1560 | loss: 3.934656
iter: 1561 | loss: 3.934041
iter: 1562 | loss: 3.933426
iter: 1563 | loss: 3.932811
iter: 1564 | loss: 3.932196
iter: 1565 | loss: 3.931581
iter: 1566 | loss: 3.930966
iter: 1567 | loss: 3.930351
iter: 1568 | loss: 3.929736
iter: 1569 | loss: 3.929121
iter: 1570 | loss: 3.928506
iter: 1571 | loss: 3.927890
iter: 1572 | loss: 3.927275
iter: 1573 | loss: 3.926660
iter: 1574 | loss: 3.926045
iter: 1575 | loss: 3.925430
iter: 1576 | loss: 3.924815
iter: 1577 | loss: 3.924200
iter: 1578 | loss: 3.923585
iter: 1579 | loss: 3.922970
iter: 1580 | loss: 3.922355
iter: 1581 | loss: 3.921740
iter: 1582 | loss: 3.921125
iter: 1583 | loss: 3.920510
iter: 1584 | loss: 3.919895
iter: 1585 | loss: 3.919280
iter: 1586 | loss: 3.918665
iter: 1587 | loss: 3.918049
iter: 1588 | loss: 3.917434
iter: 1589 | loss: 3.916819
iter: 1590 | loss: 3.916204
iter: 1591 | loss: 3.915589
iter: 1592 | loss: 3.914974
iter: 1593 | loss: 3.914359
iter: 1594 | loss: 3.913744
iter: 1595 | loss: 3.913129
iter: 1596 | loss: 3.912514
iter: 1597 | loss: 3.911899
iter: 1598 | loss: 3.911284
iter: 1599 | loss: 3.910669
iter: 1600 | loss: 3.910054
iter: 1601 | loss: 3.909439
iter: 1602 | loss: 3.908823
iter: 1603 | loss: 3.908208
iter: 1604 | loss: 3.907593
iter: 1605 | loss: 3.906978
iter: 1606 | loss: 3.906363
iter: 1607 | loss: 3.905748
iter: 1608 | loss: 3.905133
iter: 1609 | loss: 3.904518
iter: 1610 | loss: 3.903903
iter: 1611 | loss: 3.903288
iter: 1612 | loss: 3.902673
iter: 1613 | loss: 3.902058
iter: 1614 | loss: 3.901443
iter: 1615 | loss: 3.900828
iter: 1616 | loss: 3.900213
iter: 1617 | loss: 3.899598
iter: 1618 | loss: 3.898982
iter: 1619 | loss: 3.898367
iter: 1620 | loss: 3.897752
iter: 1621 | loss: 3.897137
iter: 1622 | loss: 3.896522
iter: 1623 | loss: 3.895907
iter: 1624 | loss: 3.895292
iter: 1625 | loss: 3.894677
iter: 1626 | loss: 3.894062
iter: 1627 | loss: 3.893447
iter: 1628 | loss: 3.892832
iter: 1629 | loss: 3.892217
iter: 1630 | loss: 3.891602
iter: 1631 | loss: 3.890987
iter: 1632 | loss: 3.890372
iter: 1633 | loss: 3.889757
iter: 1634 | loss: 3.889141
iter: 1635 | loss: 3.888526
iter: 1636 | loss: 3.887911
iter: 1637 | loss: 3.887296
iter: 1638 | loss: 3.886681
iter: 1639 | loss: 3.886066
iter: 1640 | loss: 3.885451
iter: 1641 | loss: 3.884836
iter: 1642 | loss: 3.884221
iter: 1643 | loss: 3.883606
iter: 1644 | loss: 3.882991
iter: 1645 | loss: 3.882376
iter: 1646 | loss: 3.881761
iter: 1647 | loss: 3.881146
iter: 1648 | loss: 3.880531
iter: 1649 | loss: 3.879916
iter: 1650 | loss: 3.879300
iter: 1651 | loss: 3.878685
iter: 1652 | loss: 3.878070
iter: 1653 | loss: 3.877455
iter: 1654 | loss: 3.876840
iter: 1655 | loss: 3.876225
iter: 1656 | loss: 3.875610
iter: 1657 | loss: 3.874995
iter: 1658 | loss: 3.874380
iter: 1659 | loss: 3.873765
iter: 1660 | loss: 3.873150
iter: 1661 | loss: 3.872535
iter: 1662 | loss: 3.871920
iter: 1663 | loss: 3.871305
iter: 1664 | loss: 3.870690
iter: 1665 | loss: 3.870074
iter: 1666 | loss: 3.869459
iter: 1667 | loss: 3.868844
iter: 1668 | loss: 3.868229
iter: 1669 | loss: 3.867614
iter: 1670 | loss: 3.866999
iter: 1671 | loss: 3.866384
iter: 1672 | loss: 3.865769
iter: 1673 | loss: 3.865154
iter: 1674 | loss: 3.864539
iter: 1675 | loss: 3.863924
iter: 1676 | loss: 3.863309
iter: 1677 | loss: 3.862694
iter: 1678 | loss: 3.862079
iter: 1679 | loss: 3.861464
iter: 1680 | loss: 3.860849
iter: 1681 | loss: 3.860233
iter: 1682 | loss: 3.859618
iter: 1683 | loss: 3.859003
iter: 1684 | loss: 3.858388
iter: 1685 | loss: 3.857773
iter: 1686 | loss: 3.857158
iter: 1687 | loss: 3.856543
iter: 1688 | loss: 3.855928
iter: 1689 | loss: 3.855313
iter: 1690 | loss: 3.854698
iter: 1691 | loss: 3.854083
iter: 1692 | loss: 3.853468
iter: 1693 | loss: 3.852853
iter: 1694 | loss: 3.852238
iter: 1695 | loss: 3.851623
iter: 1696 | loss: 3.851008
iter: 1697 | loss: 3.850392
iter: 1698 | loss: 3.849777
iter: 1699 | loss: 3.849162
iter: 1700 | loss: 3.848547
iter: 1701 | loss: 3.847932
iter: 1702 | loss: 3.847317
iter: 1703 | loss: 3.846702
iter: 1704 | loss: 3.846087
iter: 1705 | loss: 3.845472
iter: 1706 | loss: 3.844857
iter: 1707 | loss: 3.844242
iter: 1708 | loss: 3.843627
iter: 1709 | loss: 3.843012
iter: 1710 | loss: 3.842397
iter: 1711 | loss: 3.841782
iter: 1712 | loss: 3.841166
iter: 1713 | loss: 3.840551
iter: 1714 | loss: 3.839936
iter: 1715 | loss: 3.839321
iter: 1716 | loss: 3.838706
iter: 1717 | loss: 3.838091
iter: 1718 | loss: 3.837476
iter: 1719 | loss: 3.836861
iter: 1720 | loss: 3.836246
iter: 1721 | loss: 3.835631
iter: 1722 | loss: 3.835016
iter: 1723 | loss: 3.834401
iter: 1724 | loss: 3.833786
iter: 1725 | loss: 3.833171
iter: 1726 | loss: 3.832556
iter: 1727 | loss: 3.831941
iter: 1728 | loss: 3.831325
iter: 1729 | loss: 3.830710
iter: 1730 | loss: 3.830095
iter: 1731 | loss: 3.829480
iter: 1732 | loss: 3.828865
iter: 1733 | loss: 3.828250
iter: 1734 | loss: 3.827635
iter: 1735 | loss: 3.827020
iter: 1736 | loss: 3.826405
iter: 1737 | loss: 3.825790
iter: 1738 | loss: 3.825175
iter: 1739 | loss: 3.824560
iter: 1740 | loss: 3.823945
iter: 1741 | loss: 3.823330
iter: 1742 | loss: 3.822715
iter: 1743 | loss: 3.822100
iter: 1744 | loss: 3.821484
iter: 1745 | loss: 3.820869
iter: 1746 | loss: 3.820254
iter: 1747 | loss: 3.819639
iter: 1748 | loss: 3.819024
iter: 1749 | loss: 3.818409
iter: 1750 | loss: 3.817794
iter: 1751 | loss: 3.817179
iter: 1752 | loss: 3.816564
iter: 1753 | loss: 3.815949
iter: 1754 | loss: 3.815334
iter: 1755 | loss: 3.814719
iter: 1756 | loss: 3.814104
iter: 1757 | loss: 3.813489
iter: 1758 | loss: 3.812874
iter: 1759 | loss: 3.812259
iter: 1760 | loss: 3.811643
iter: 1761 | loss: 3.811028
iter: 1762 | loss: 3.810413
iter: 1763 | loss: 3.809798
iter: 1764 | loss: 3.809183
iter: 1765 | loss: 3.808568
iter: 1766 | loss: 3.807953
iter: 1767 | loss: 3.807338
iter: 1768 | loss: 3.806723
iter: 1769 | loss: 3.806108
iter: 1770 | loss: 3.805493
iter: 1771 | loss: 3.804878
iter: 1772 | loss: 3.804263
iter: 1773 | loss: 3.803648
iter: 1774 | loss: 3.803033
iter: 1775 | loss: 3.802417
iter: 1776 | loss: 3.801802
iter: 1777 | loss: 3.801187
iter: 1778 | loss: 3.800572
iter: 1779 | loss: 3.799957
iter: 1780 | loss: 3.799342
iter: 1781 | loss: 3.798727
iter: 1782 | loss: 3.798112
iter: 1783 | loss: 3.797497
iter: 1784 | loss: 3.796882
iter: 1785 | loss: 3.796267
iter: 1786 | loss: 3.795652
iter: 1787 | loss: 3.795037
iter: 1788 | loss: 3.794422
iter: 1789 | loss: 3.793807
iter: 1790 | loss: 3.793192
iter: 1791 | loss: 3.792576
iter: 1792 | loss: 3.791961
iter: 1793 | loss: 3.791346
iter: 1794 | loss: 3.790731
iter: 1795 | loss: 3.790116
iter: 1796 | loss: 3.789501
iter: 1797 | loss: 3.788886
iter: 1798 | loss: 3.788271
iter: 1799 | loss: 3.787656
iter: 1800 | loss: 3.787041
iter: 1801 | loss: 3.786426
iter: 1802 | loss: 3.785811
iter: 1803 | loss: 3.785196
iter: 1804 | loss: 3.784581
iter: 1805 | loss: 3.783966
iter: 1806 | loss: 3.783351
iter: 1807 | loss: 3.782735
iter: 1808 | loss: 3.782120
iter: 1809 | loss: 3.781505
iter: 1810 | loss: 3.780890
iter: 1811 | loss: 3.780275
iter: 1812 | loss: 3.779660
iter: 1813 | loss: 3.779045
iter: 1814 | loss: 3.778430
iter: 1815 | loss: 3.777815
iter: 1816 | loss: 3.777200
iter: 1817 | loss: 3.776585
iter: 1818 | loss: 3.775970
iter: 1819 | loss: 3.775355
iter: 1820 | loss: 3.774740
iter: 1821 | loss: 3.774125
iter: 1822 | loss: 3.773510
iter: 1823 | loss: 3.772894
iter: 1824 | loss: 3.772279
iter: 1825 | loss: 3.771664
iter: 1826 | loss: 3.771049
iter: 1827 | loss: 3.770434
iter: 1828 | loss: 3.769819
iter: 1829 | loss: 3.769204
iter: 1830 | loss: 3.768589
iter: 1831 | loss: 3.767974
iter: 1832 | loss: 3.767359
iter: 1833 | loss: 3.766744
iter: 1834 | loss: 3.766129
iter: 1835 | loss: 3.765514
iter: 1836 | loss: 3.764899
iter: 1837 | loss: 3.764284
iter: 1838 | loss: 3.763668
iter: 1839 | loss: 3.763053
iter: 1840 | loss: 3.762438
iter: 1841 | loss: 3.761823
iter: 1842 | loss: 3.761208
iter: 1843 | loss: 3.760593
iter: 1844 | loss: 3.759978
iter: 1845 | loss: 3.759363
iter: 1846 | loss: 3.758748
iter: 1847 | loss: 3.758133
iter: 1848 | loss: 3.757518
iter: 1849 | loss: 3.756903
iter: 1850 | loss: 3.756288
iter: 1851 | loss: 3.755673
iter: 1852 | loss: 3.755058
iter: 1853 | loss: 3.754443
iter: 1854 | loss: 3.753827
iter: 1855 | loss: 3.753212
iter: 1856 | loss: 3.752597
iter: 1857 | loss: 3.751982
iter: 1858 | loss: 3.751367
iter: 1859 | loss: 3.750752
iter: 1860 | loss: 3.750137
iter: 1861 | loss: 3.749522
iter: 1862 | loss: 3.748907
iter: 1863 | loss: 3.748292
iter: 1864 | loss: 3.747677
iter: 1865 | loss: 3.747062
iter: 1866 | loss: 3.746447
iter: 1867 | loss: 3.745832
iter: 1868 | loss: 3.745217
iter: 1869 | loss: 3.744602
iter: 1870 | loss: 3.743986
iter: 1871 | loss: 3.743371
iter: 1872 | loss: 3.742756
iter: 1873 | loss: 3.742141
iter: 1874 | loss: 3.741526
iter: 1875 | loss: 3.740911
iter: 1876 | loss: 3.740296
iter: 1877 | loss: 3.739681
iter: 1878 | loss: 3.739066
iter: 1879 | loss: 3.738451
iter: 1880 | loss: 3.737836
iter: 1881 | loss: 3.737221
iter: 1882 | loss: 3.736606
iter: 1883 | loss: 3.735991
iter: 1884 | loss: 3.735376
iter: 1885 | loss: 3.734761
iter: 1886 | loss: 3.734145
iter: 1887 | loss: 3.733530
iter: 1888 | loss: 3.732915
iter: 1889 | loss: 3.732300
iter: 1890 | loss: 3.731685
iter: 1891 | loss: 3.731070
iter: 1892 | loss: 3.730455
iter: 1893 | loss: 3.729840
iter: 1894 | loss: 3.729225
iter: 1895 | loss: 3.728610
iter: 1896 | loss: 3.727995
iter: 1897 | loss: 3.727380
iter: 1898 | loss: 3.726765
iter: 1899 | loss: 3.726150
iter: 1900 | loss: 3.725535
iter: 1901 | loss: 3.724919
iter: 1902 | loss: 3.724304
iter: 1903 | loss: 3.723689
iter: 1904 | loss: 3.723074
iter: 1905 | loss: 3.722459
iter: 1906 | loss: 3.721844
iter: 1907 | loss: 3.721229
iter: 1908 | loss: 3.720614
iter: 1909 | loss: 3.719999
iter: 1910 | loss: 3.719384
iter: 1911 | loss: 3.718769
iter: 1912 | loss: 3.718154
iter: 1913 | loss: 3.717539
iter: 1914 | loss: 3.716924
iter: 1915 | loss: 3.716309
iter: 1916 | loss: 3.715694
iter: 1917 | loss: 3.715078
iter: 1918 | loss: 3.714463
iter: 1919 | loss: 3.713848
iter: 1920 | loss: 3.713233
iter: 1921 | loss: 3.712618
iter: 1922 | loss: 3.712003
iter: 1923 | loss: 3.711388
iter: 1924 | loss: 3.710773
iter: 1925 | loss: 3.710158
iter: 1926 | loss: 3.709543
iter: 1927 | loss: 3.708928
iter: 1928 | loss: 3.708313
iter: 1929 | loss: 3.707698
iter: 1930 | loss: 3.707083
iter: 1931 | loss: 3.706468
iter: 1932 | loss: 3.705853
iter: 1933 | loss: 3.705237
iter: 1934 | loss: 3.704622
iter: 1935 | loss: 3.704007
iter: 1936 | loss: 3.703392
iter: 1937 | loss: 3.702777
iter: 1938 | loss: 3.702162
iter: 1939 | loss: 3.701547
iter: 1940 | loss: 3.700932
iter: 1941 | loss: 3.700317
iter: 1942 | loss: 3.699702
iter: 1943 | loss: 3.699087
iter: 1944 | loss: 3.698472
iter: 1945 | loss: 3.697857
iter: 1946 | loss: 3.697242
iter: 1947 | loss: 3.696627
iter: 1948 | loss: 3.696011
iter: 1949 | loss: 3.695396
iter: 1950 | loss: 3.694781
iter: 1951 | loss: 3.694166
iter: 1952 | loss: 3.693551
iter: 1953 | loss: 3.692936
iter: 1954 | loss: 3.692321
iter: 1955 | loss: 3.691706
iter: 1956 | loss: 3.691091
iter: 1957 | loss: 3.690476
iter: 1958 | loss: 3.689861
iter: 1959 | loss: 3.689246
iter: 1960 | loss: 3.688631
iter: 1961 | loss: 3.688016
iter: 1962 | loss: 3.687401
iter: 1963 | loss: 3.686786
iter: 1964 | loss: 3.686170
iter: 1965 | loss: 3.685555
iter: 1966 | loss: 3.684940
iter: 1967 | loss: 3.684325
iter: 1968 | loss: 3.683710
iter: 1969 | loss: 3.683095
iter: 1970 | loss: 3.682480
iter: 1971 | loss: 3.681865
iter: 1972 | loss: 3.681250
iter: 1973 | loss: 3.680635
iter: 1974 | loss: 3.680020
iter: 1975 | loss: 3.679405
iter: 1976 | loss: 3.678790
iter: 1977 | loss: 3.678175
iter: 1978 | loss: 3.677560
iter: 1979 | loss: 3.676945
iter: 1980 | loss: 3.676329
iter: 1981 | loss: 3.675714
iter: 1982 | loss: 3.675099
iter: 1983 | loss: 3.674484
iter: 1984 | loss: 3.673869
iter: 1985 | loss: 3.673254
iter: 1986 | loss: 3.672639
iter: 1987 | loss: 3.672024
iter: 1988 | loss: 3.671409
iter: 1989 | loss: 3.670794
iter: 1990 | loss: 3.670179
iter: 1991 | loss: 3.669564
iter: 1992 | loss: 3.668949
iter: 1993 | loss: 3.668334
iter: 1994 | loss: 3.667719
iter: 1995 | loss: 3.667104
iter: 1996 | loss: 3.666488
iter: 1997 | loss: 3.665873
iter: 1998 | loss: 3.665258
iter: 1999 | loss: 3.664643
iter: 2000 | loss: 3.664028
iter: 2001 | loss: 3.663413
iter: 2002 | loss: 3.662798
iter: 2003 | loss: 3.662183
iter: 2004 | loss: 3.661568
iter: 2005 | loss: 3.660953
iter: 2006 | loss: 3.660338
iter: 2007 | loss: 3.659723
iter: 2008 | loss: 3.659108
iter: 2009 | loss: 3.658493
iter: 2010 | loss: 3.657878
iter: 2011 | loss: 3.657262
iter: 2012 | loss: 3.656647
iter: 2013 | loss: 3.656032
iter: 2014 | loss: 3.655417
iter: 2015 | loss: 3.654802
iter: 2016 | loss: 3.654187
iter: 2017 | loss: 3.653572
iter: 2018 | loss: 3.652957
iter: 2019 | loss: 3.652342
iter: 2020 | loss: 3.651727
iter: 2021 | loss: 3.651112
iter: 2022 | loss: 3.650497
iter: 2023 | loss: 3.649882
iter: 2024 | loss: 3.649267
iter: 2025 | loss: 3.648652
iter: 2026 | loss: 3.648037
iter: 2027 | loss: 3.647421
iter: 2028 | loss: 3.646806
iter: 2029 | loss: 3.646191
iter: 2030 | loss: 3.645576
iter: 2031 | loss: 3.644961
iter: 2032 | loss: 3.644346
iter: 2033 | loss: 3.643731
iter: 2034 | loss: 3.643116
iter: 2035 | loss: 3.642501
iter: 2036 | loss: 3.641886
iter: 2037 | loss: 3.641271
iter: 2038 | loss: 3.640656
iter: 2039 | loss: 3.640041
iter: 2040 | loss: 3.639426
iter: 2041 | loss: 3.638811
iter: 2042 | loss: 3.638196
iter: 2043 | loss: 3.637580
iter: 2044 | loss: 3.636965
iter: 2045 | loss: 3.636350
iter: 2046 | loss: 3.635735
iter: 2047 | loss: 3.635120
iter: 2048 | loss: 3.634505
iter: 2049 | loss: 3.633890
iter: 2050 | loss: 3.633275
iter: 2051 | loss: 3.632660
iter: 2052 | loss: 3.632045
iter: 2053 | loss: 3.631430
iter: 2054 | loss: 3.630815
iter: 2055 | loss: 3.630200
iter: 2056 | loss: 3.629585
iter: 2057 | loss: 3.628970
iter: 2058 | loss: 3.628355
iter: 2059 | loss: 3.627739
iter: 2060 | loss: 3.627124
iter: 2061 | loss: 3.626509
iter: 2062 | loss: 3.625894
iter: 2063 | loss: 3.625279
iter: 2064 | loss: 3.624664
iter: 2065 | loss: 3.624049
iter: 2066 | loss: 3.623434
iter: 2067 | loss: 3.622819
iter: 2068 | loss: 3.622204
iter: 2069 | loss: 3.621589
iter: 2070 | loss: 3.620974
iter: 2071 | loss: 3.620359
iter: 2072 | loss: 3.619744
iter: 2073 | loss: 3.619129
iter: 2074 | loss: 3.618513
iter: 2075 | loss: 3.617898
iter: 2076 | loss: 3.617283
iter: 2077 | loss: 3.616668
iter: 2078 | loss: 3.616053
iter: 2079 | loss: 3.615438
iter: 2080 | loss: 3.614823
iter: 2081 | loss: 3.614208
iter: 2082 | loss: 3.613593
iter: 2083 | loss: 3.612978
iter: 2084 | loss: 3.612363
iter: 2085 | loss: 3.611748
iter: 2086 | loss: 3.611133
iter: 2087 | loss: 3.610518
iter: 2088 | loss: 3.609903
iter: 2089 | loss: 3.609288
iter: 2090 | loss: 3.608672
iter: 2091 | loss: 3.608057
iter: 2092 | loss: 3.607442
iter: 2093 | loss: 3.606827
iter: 2094 | loss: 3.606212
iter: 2095 | loss: 3.605597
iter: 2096 | loss: 3.604982
iter: 2097 | loss: 3.604367
iter: 2098 | loss: 3.603752
iter: 2099 | loss: 3.603137
iter: 2100 | loss: 3.602522
iter: 2101 | loss: 3.601907
iter: 2102 | loss: 3.601292
iter: 2103 | loss: 3.600677
iter: 2104 | loss: 3.600062
iter: 2105 | loss: 3.599447
iter: 2106 | loss: 3.598831
iter: 2107 | loss: 3.598216
iter: 2108 | loss: 3.597601
iter: 2109 | loss: 3.596986
iter: 2110 | loss: 3.596371
iter: 2111 | loss: 3.595756
iter: 2112 | loss: 3.595141
iter: 2113 | loss: 3.594526
iter: 2114 | loss: 3.593911
iter: 2115 | loss: 3.593296
iter: 2116 | loss: 3.592681
iter: 2117 | loss: 3.592066
iter: 2118 | loss: 3.591451
iter: 2119 | loss: 3.590836
iter: 2120 | loss: 3.590221
iter: 2121 | loss: 3.589605
iter: 2122 | loss: 3.588990
iter: 2123 | loss: 3.588375
iter: 2124 | loss: 3.587760
iter: 2125 | loss: 3.587145
iter: 2126 | loss: 3.586530
iter: 2127 | loss: 3.585915
iter: 2128 | loss: 3.585300
iter: 2129 | loss: 3.584685
iter: 2130 | loss: 3.584070
iter: 2131 | loss: 3.583455
iter: 2132 | loss: 3.582840
iter: 2133 | loss: 3.582225
iter: 2134 | loss: 3.581610
iter: 2135 | loss: 3.580995
iter: 2136 | loss: 3.580380
iter: 2137 | loss: 3.579764
iter: 2138 | loss: 3.579149
iter: 2139 | loss: 3.578534
iter: 2140 | loss: 3.577919
iter: 2141 | loss: 3.577304
iter: 2142 | loss: 3.576689
iter: 2143 | loss: 3.576074
iter: 2144 | loss: 3.575459
iter: 2145 | loss: 3.574844
iter: 2146 | loss: 3.574229
iter: 2147 | loss: 3.573614
iter: 2148 | loss: 3.572999
iter: 2149 | loss: 3.572384
iter: 2150 | loss: 3.571769
iter: 2151 | loss: 3.571154
iter: 2152 | loss: 3.570539
iter: 2153 | loss: 3.569923
iter: 2154 | loss: 3.569308
iter: 2155 | loss: 3.568693
iter: 2156 | loss: 3.568078
iter: 2157 | loss: 3.567463
iter: 2158 | loss: 3.566848
iter: 2159 | loss: 3.566233
iter: 2160 | loss: 3.565618
iter: 2161 | loss: 3.565003
iter: 2162 | loss: 3.564388
iter: 2163 | loss: 3.563773
iter: 2164 | loss: 3.563158
iter: 2165 | loss: 3.562543
iter: 2166 | loss: 3.561928
iter: 2167 | loss: 3.561313
iter: 2168 | loss: 3.560698
iter: 2169 | loss: 3.560082
iter: 2170 | loss: 3.559467
iter: 2171 | loss: 3.558852
iter: 2172 | loss: 3.558237
iter: 2173 | loss: 3.557622
iter: 2174 | loss: 3.557007
iter: 2175 | loss: 3.556392
iter: 2176 | loss: 3.555777
iter: 2177 | loss: 3.555162
iter: 2178 | loss: 3.554547
iter: 2179 | loss: 3.553932
iter: 2180 | loss: 3.553317
iter: 2181 | loss: 3.552702
iter: 2182 | loss: 3.552087
iter: 2183 | loss: 3.551472
iter: 2184 | loss: 3.550856
iter: 2185 | loss: 3.550241
iter: 2186 | loss: 3.549626
iter: 2187 | loss: 3.549011
iter: 2188 | loss: 3.548396
iter: 2189 | loss: 3.547781
iter: 2190 | loss: 3.547166
iter: 2191 | loss: 3.546551
iter: 2192 | loss: 3.545936
iter: 2193 | loss: 3.545321
iter: 2194 | loss: 3.544706
iter: 2195 | loss: 3.544091
iter: 2196 | loss: 3.543476
iter: 2197 | loss: 3.542861
iter: 2198 | loss: 3.542246
iter: 2199 | loss: 3.541631
iter: 2200 | loss: 3.541015
iter: 2201 | loss: 3.540400
iter: 2202 | loss: 3.539785
iter: 2203 | loss: 3.539170
iter: 2204 | loss: 3.538555
iter: 2205 | loss: 3.537940
iter: 2206 | loss: 3.537325
iter: 2207 | loss: 3.536710
iter: 2208 | loss: 3.536095
iter: 2209 | loss: 3.535480
iter: 2210 | loss: 3.534865
iter: 2211 | loss: 3.534250
iter: 2212 | loss: 3.533635
iter: 2213 | loss: 3.533020
iter: 2214 | loss: 3.532405
iter: 2215 | loss: 3.531790
iter: 2216 | loss: 3.531174
iter: 2217 | loss: 3.530559
iter: 2218 | loss: 3.529944
iter: 2219 | loss: 3.529329
iter: 2220 | loss: 3.528714
iter: 2221 | loss: 3.528099
iter: 2222 | loss: 3.527484
iter: 2223 | loss: 3.526869
iter: 2224 | loss: 3.526254
iter: 2225 | loss: 3.525639
iter: 2226 | loss: 3.525024
iter: 2227 | loss: 3.524409
iter: 2228 | loss: 3.523794
iter: 2229 | loss: 3.523179
iter: 2230 | loss: 3.522564
iter: 2231 | loss: 3.521949
iter: 2232 | loss: 3.521333
iter: 2233 | loss: 3.520718
iter: 2234 | loss: 3.520103
iter: 2235 | loss: 3.519488
iter: 2236 | loss: 3.518873
iter: 2237 | loss: 3.518258
iter: 2238 | loss: 3.517643
iter: 2239 | loss: 3.517028
iter: 2240 | loss: 3.516413
iter: 2241 | loss: 3.515798
iter: 2242 | loss: 3.515183
iter: 2243 | loss: 3.514568
iter: 2244 | loss: 3.513953
iter: 2245 | loss: 3.513338
iter: 2246 | loss: 3.512723
iter: 2247 | loss: 3.512107
iter: 2248 | loss: 3.511492
iter: 2249 | loss: 3.510877
iter: 2250 | loss: 3.510262
iter: 2251 | loss: 3.509647
iter: 2252 | loss: 3.509032
iter: 2253 | loss: 3.508417
iter: 2254 | loss: 3.507802
iter: 2255 | loss: 3.507187
iter: 2256 | loss: 3.506572
iter: 2257 | loss: 3.505957
iter: 2258 | loss: 3.505342
iter: 2259 | loss: 3.504727
iter: 2260 | loss: 3.504112
iter: 2261 | loss: 3.503497
iter: 2262 | loss: 3.502882
iter: 2263 | loss: 3.502266
iter: 2264 | loss: 3.501651
iter: 2265 | loss: 3.501036
iter: 2266 | loss: 3.500421
iter: 2267 | loss: 3.499806
iter: 2268 | loss: 3.499191
iter: 2269 | loss: 3.498576
iter: 2270 | loss: 3.497961
iter: 2271 | loss: 3.497346
iter: 2272 | loss: 3.496731
iter: 2273 | loss: 3.496116
iter: 2274 | loss: 3.495501
iter: 2275 | loss: 3.494886
iter: 2276 | loss: 3.494271
iter: 2277 | loss: 3.493656
iter: 2278 | loss: 3.493041
iter: 2279 | loss: 3.492425
iter: 2280 | loss: 3.491810
iter: 2281 | loss: 3.491195
iter: 2282 | loss: 3.490580
iter: 2283 | loss: 3.489965
iter: 2284 | loss: 3.489350
iter: 2285 | loss: 3.488735
iter: 2286 | loss: 3.488120
iter: 2287 | loss: 3.487505
iter: 2288 | loss: 3.486890
iter: 2289 | loss: 3.486275
iter: 2290 | loss: 3.485660
iter: 2291 | loss: 3.485045
iter: 2292 | loss: 3.484430
iter: 2293 | loss: 3.483815
iter: 2294 | loss: 3.483200
iter: 2295 | loss: 3.482584
iter: 2296 | loss: 3.481969
iter: 2297 | loss: 3.481354
iter: 2298 | loss: 3.480739
iter: 2299 | loss: 3.480124
iter: 2300 | loss: 3.479509
iter: 2301 | loss: 3.478894
iter: 2302 | loss: 3.478279
iter: 2303 | loss: 3.477664
iter: 2304 | loss: 3.477049
iter: 2305 | loss: 3.476434
iter: 2306 | loss: 3.475819
iter: 2307 | loss: 3.475204
iter: 2308 | loss: 3.474589
iter: 2309 | loss: 3.473974
iter: 2310 | loss: 3.473358
iter: 2311 | loss: 3.472743
iter: 2312 | loss: 3.472128
iter: 2313 | loss: 3.471513
iter: 2314 | loss: 3.470898
iter: 2315 | loss: 3.470283
iter: 2316 | loss: 3.469668
iter: 2317 | loss: 3.469053
iter: 2318 | loss: 3.468438
iter: 2319 | loss: 3.467823
iter: 2320 | loss: 3.467208
iter: 2321 | loss: 3.466593
iter: 2322 | loss: 3.465978
iter: 2323 | loss: 3.465363
iter: 2324 | loss: 3.464748
iter: 2325 | loss: 3.464133
iter: 2326 | loss: 3.463517
iter: 2327 | loss: 3.462902
iter: 2328 | loss: 3.462287
iter: 2329 | loss: 3.461672
iter: 2330 | loss: 3.461057
iter: 2331 | loss: 3.460442
iter: 2332 | loss: 3.459827
iter: 2333 | loss: 3.459212
iter: 2334 | loss: 3.458597
iter: 2335 | loss: 3.457982
iter: 2336 | loss: 3.457367
iter: 2337 | loss: 3.456752
iter: 2338 | loss: 3.456137
iter: 2339 | loss: 3.455522
iter: 2340 | loss: 3.454907
iter: 2341 | loss: 3.454292
iter: 2342 | loss: 3.453676
iter: 2343 | loss: 3.453061
iter: 2344 | loss: 3.452446
iter: 2345 | loss: 3.451831
iter: 2346 | loss: 3.451216
iter: 2347 | loss: 3.450601
iter: 2348 | loss: 3.449986
iter: 2349 | loss: 3.449371
iter: 2350 | loss: 3.448756
iter: 2351 | loss: 3.448141
iter: 2352 | loss: 3.447526
iter: 2353 | loss: 3.446911
iter: 2354 | loss: 3.446296
iter: 2355 | loss: 3.445681
iter: 2356 | loss: 3.445066
iter: 2357 | loss: 3.444450
iter: 2358 | loss: 3.443835
iter: 2359 | loss: 3.443220
iter: 2360 | loss: 3.442605
iter: 2361 | loss: 3.441990
iter: 2362 | loss: 3.441375
iter: 2363 | loss: 3.440760
iter: 2364 | loss: 3.440145
iter: 2365 | loss: 3.439530
iter: 2366 | loss: 3.438915
iter: 2367 | loss: 3.438300
iter: 2368 | loss: 3.437685
iter: 2369 | loss: 3.437070
iter: 2370 | loss: 3.436455
iter: 2371 | loss: 3.435840
iter: 2372 | loss: 3.435225
iter: 2373 | loss: 3.434609
iter: 2374 | loss: 3.433994
iter: 2375 | loss: 3.433379
iter: 2376 | loss: 3.432764
iter: 2377 | loss: 3.432149
iter: 2378 | loss: 3.431534
iter: 2379 | loss: 3.430919
iter: 2380 | loss: 3.430304
iter: 2381 | loss: 3.429689
iter: 2382 | loss: 3.429074
iter: 2383 | loss: 3.428459
iter: 2384 | loss: 3.427844
iter: 2385 | loss: 3.427229
iter: 2386 | loss: 3.426614
iter: 2387 | loss: 3.425999
iter: 2388 | loss: 3.425384
iter: 2389 | loss: 3.424768
iter: 2390 | loss: 3.424153
iter: 2391 | loss: 3.423538
iter: 2392 | loss: 3.422923
iter: 2393 | loss: 3.422308
iter: 2394 | loss: 3.421693
iter: 2395 | loss: 3.421078
iter: 2396 | loss: 3.420463
iter: 2397 | loss: 3.419848
iter: 2398 | loss: 3.419233
iter: 2399 | loss: 3.418618
iter: 2400 | loss: 3.418003
iter: 2401 | loss: 3.417388
iter: 2402 | loss: 3.416773
iter: 2403 | loss: 3.416158
iter: 2404 | loss: 3.415543
iter: 2405 | loss: 3.414927
iter: 2406 | loss: 3.414312
iter: 2407 | loss: 3.413697
iter: 2408 | loss: 3.413082
iter: 2409 | loss: 3.412467
iter: 2410 | loss: 3.411852
iter: 2411 | loss: 3.411237
iter: 2412 | loss: 3.410622
iter: 2413 | loss: 3.410007
iter: 2414 | loss: 3.409392
iter: 2415 | loss: 3.408777
iter: 2416 | loss: 3.408162
iter: 2417 | loss: 3.407547
iter: 2418 | loss: 3.406932
iter: 2419 | loss: 3.406317
iter: 2420 | loss: 3.405701
iter: 2421 | loss: 3.405086
iter: 2422 | loss: 3.404471
iter: 2423 | loss: 3.403856
iter: 2424 | loss: 3.403241
iter: 2425 | loss: 3.402626
iter: 2426 | loss: 3.402011
iter: 2427 | loss: 3.401396
iter: 2428 | loss: 3.400781
iter: 2429 | loss: 3.400166
iter: 2430 | loss: 3.399551
iter: 2431 | loss: 3.398936
iter: 2432 | loss: 3.398321
iter: 2433 | loss: 3.397706
iter: 2434 | loss: 3.397091
iter: 2435 | loss: 3.396476
iter: 2436 | loss: 3.395860
iter: 2437 | loss: 3.395245
iter: 2438 | loss: 3.394630
iter: 2439 | loss: 3.394015
iter: 2440 | loss: 3.393400
iter: 2441 | loss: 3.392785
iter: 2442 | loss: 3.392170
iter: 2443 | loss: 3.391555
iter: 2444 | loss: 3.390940
iter: 2445 | loss: 3.390325
iter: 2446 | loss: 3.389710
iter: 2447 | loss: 3.389095
iter: 2448 | loss: 3.388480
iter: 2449 | loss: 3.387865
iter: 2450 | loss: 3.387250
iter: 2451 | loss: 3.386635
iter: 2452 | loss: 3.386019
iter: 2453 | loss: 3.385404
iter: 2454 | loss: 3.384789
iter: 2455 | loss: 3.384174
iter: 2456 | loss: 3.383559
iter: 2457 | loss: 3.382944
iter: 2458 | loss: 3.382329
iter: 2459 | loss: 3.381714
iter: 2460 | loss: 3.381099
iter: 2461 | loss: 3.380484
iter: 2462 | loss: 3.379869
iter: 2463 | loss: 3.379254
iter: 2464 | loss: 3.378639
iter: 2465 | loss: 3.378024
iter: 2466 | loss: 3.377409
iter: 2467 | loss: 3.376794
iter: 2468 | loss: 3.376178
iter: 2469 | loss: 3.375563
iter: 2470 | loss: 3.374948
iter: 2471 | loss: 3.374333
iter: 2472 | loss: 3.373718
iter: 2473 | loss: 3.373103
iter: 2474 | loss: 3.372488
iter: 2475 | loss: 3.371873
iter: 2476 | loss: 3.371258
iter: 2477 | loss: 3.370643
iter: 2478 | loss: 3.370028
iter: 2479 | loss: 3.369413
iter: 2480 | loss: 3.368798
iter: 2481 | loss: 3.368183
iter: 2482 | loss: 3.367568
iter: 2483 | loss: 3.366952
iter: 2484 | loss: 3.366337
iter: 2485 | loss: 3.365722
iter: 2486 | loss: 3.365107
iter: 2487 | loss: 3.364492
iter: 2488 | loss: 3.363877
iter: 2489 | loss: 3.363262
iter: 2490 | loss: 3.362647
iter: 2491 | loss: 3.362032
iter: 2492 | loss: 3.361417
iter: 2493 | loss: 3.360802
iter: 2494 | loss: 3.360187
iter: 2495 | loss: 3.359572
iter: 2496 | loss: 3.358957
iter: 2497 | loss: 3.358342
iter: 2498 | loss: 3.357727
iter: 2499 | loss: 3.357111
iter: 2500 | loss: 3.356496
iter: 2501 | loss: 3.355881
iter: 2502 | loss: 3.355266
iter: 2503 | loss: 3.354651
iter: 2504 | loss: 3.354036
iter: 2505 | loss: 3.353421
iter: 2506 | loss: 3.352806
iter: 2507 | loss: 3.352191
iter: 2508 | loss: 3.351576
iter: 2509 | loss: 3.350961
iter: 2510 | loss: 3.350346
iter: 2511 | loss: 3.349731
iter: 2512 | loss: 3.349116
iter: 2513 | loss: 3.348501
iter: 2514 | loss: 3.347886
iter: 2515 | loss: 3.347270
iter: 2516 | loss: 3.346655
iter: 2517 | loss: 3.346040
iter: 2518 | loss: 3.345425
iter: 2519 | loss: 3.344810
iter: 2520 | loss: 3.344195
iter: 2521 | loss: 3.343580
iter: 2522 | loss: 3.342965
iter: 2523 | loss: 3.342350
iter: 2524 | loss: 3.341735
iter: 2525 | loss: 3.341120
iter: 2526 | loss: 3.340505
iter: 2527 | loss: 3.339890
iter: 2528 | loss: 3.339275
iter: 2529 | loss: 3.338660
iter: 2530 | loss: 3.338045
iter: 2531 | loss: 3.337429
iter: 2532 | loss: 3.336814
iter: 2533 | loss: 3.336199
iter: 2534 | loss: 3.335584
iter: 2535 | loss: 3.334969
iter: 2536 | loss: 3.334354
iter: 2537 | loss: 3.333739
iter: 2538 | loss: 3.333124
iter: 2539 | loss: 3.332509
iter: 2540 | loss: 3.331894
iter: 2541 | loss: 3.331279
iter: 2542 | loss: 3.330664
iter: 2543 | loss: 3.330049
iter: 2544 | loss: 3.329434
iter: 2545 | loss: 3.328819
iter: 2546 | loss: 3.328203
iter: 2547 | loss: 3.327588
iter: 2548 | loss: 3.326973
iter: 2549 | loss: 3.326358
iter: 2550 | loss: 3.325743
iter: 2551 | loss: 3.325128
iter: 2552 | loss: 3.324513
iter: 2553 | loss: 3.323898
iter: 2554 | loss: 3.323283
iter: 2555 | loss: 3.322668
iter: 2556 | loss: 3.322053
iter: 2557 | loss: 3.321438
iter: 2558 | loss: 3.320823
iter: 2559 | loss: 3.320208
iter: 2560 | loss: 3.319593
iter: 2561 | loss: 3.318978
iter: 2562 | loss: 3.318362
iter: 2563 | loss: 3.317747
iter: 2564 | loss: 3.317132
iter: 2565 | loss: 3.316517
iter: 2566 | loss: 3.315902
iter: 2567 | loss: 3.315287
iter: 2568 | loss: 3.314672
iter: 2569 | loss: 3.314057
iter: 2570 | loss: 3.313442
iter: 2571 | loss: 3.312827
iter: 2572 | loss: 3.312212
iter: 2573 | loss: 3.311597
iter: 2574 | loss: 3.310982
iter: 2575 | loss: 3.310367
iter: 2576 | loss: 3.309752
iter: 2577 | loss: 3.309137
iter: 2578 | loss: 3.308521
iter: 2579 | loss: 3.307906
iter: 2580 | loss: 3.307291
iter: 2581 | loss: 3.306676
iter: 2582 | loss: 3.306061
iter: 2583 | loss: 3.305446
iter: 2584 | loss: 3.304831
iter: 2585 | loss: 3.304216
iter: 2586 | loss: 3.303601
iter: 2587 | loss: 3.302986
iter: 2588 | loss: 3.302371
iter: 2589 | loss: 3.301756
iter: 2590 | loss: 3.301141
iter: 2591 | loss: 3.300526
iter: 2592 | loss: 3.299911
iter: 2593 | loss: 3.299295
iter: 2594 | loss: 3.298680
iter: 2595 | loss: 3.298065
iter: 2596 | loss: 3.297450
iter: 2597 | loss: 3.296835
iter: 2598 | loss: 3.296220
iter: 2599 | loss: 3.295605
iter: 2600 | loss: 3.294990
iter: 2601 | loss: 3.294375
iter: 2602 | loss: 3.293760
iter: 2603 | loss: 3.293145
iter: 2604 | loss: 3.292530
iter: 2605 | loss: 3.291915
iter: 2606 | loss: 3.291300
iter: 2607 | loss: 3.290685
iter: 2608 | loss: 3.290070
iter: 2609 | loss: 3.289454
iter: 2610 | loss: 3.288839
iter: 2611 | loss: 3.288224
iter: 2612 | loss: 3.287609
iter: 2613 | loss: 3.286994
iter: 2614 | loss: 3.286379
iter: 2615 | loss: 3.285764
iter: 2616 | loss: 3.285149
iter: 2617 | loss: 3.284534
iter: 2618 | loss: 3.283919
iter: 2619 | loss: 3.283304
iter: 2620 | loss: 3.282689
iter: 2621 | loss: 3.282074
iter: 2622 | loss: 3.281459
iter: 2623 | loss: 3.280844
iter: 2624 | loss: 3.280229
iter: 2625 | loss: 3.279613
iter: 2626 | loss: 3.278998
iter: 2627 | loss: 3.278383
iter: 2628 | loss: 3.277768
iter: 2629 | loss: 3.277153
iter: 2630 | loss: 3.276538
iter: 2631 | loss: 3.275923
iter: 2632 | loss: 3.275308
iter: 2633 | loss: 3.274693
iter: 2634 | loss: 3.274078
iter: 2635 | loss: 3.273463
iter: 2636 | loss: 3.272848
iter: 2637 | loss: 3.272233
iter: 2638 | loss: 3.271618
iter: 2639 | loss: 3.271003
iter: 2640 | loss: 3.270388
iter: 2641 | loss: 3.269772
iter: 2642 | loss: 3.269157
iter: 2643 | loss: 3.268542
iter: 2644 | loss: 3.267927
iter: 2645 | loss: 3.267312
iter: 2646 | loss: 3.266697
iter: 2647 | loss: 3.266082
iter: 2648 | loss: 3.265467
iter: 2649 | loss: 3.264852
iter: 2650 | loss: 3.264237
iter: 2651 | loss: 3.263622
iter: 2652 | loss: 3.263007
iter: 2653 | loss: 3.262392
iter: 2654 | loss: 3.261777
iter: 2655 | loss: 3.261162
iter: 2656 | loss: 3.260546
iter: 2657 | loss: 3.259931
iter: 2658 | loss: 3.259316
iter: 2659 | loss: 3.258701
iter: 2660 | loss: 3.258086
iter: 2661 | loss: 3.257471
iter: 2662 | loss: 3.256856
iter: 2663 | loss: 3.256241
iter: 2664 | loss: 3.255626
iter: 2665 | loss: 3.255011
iter: 2666 | loss: 3.254396
iter: 2667 | loss: 3.253781
iter: 2668 | loss: 3.253166
iter: 2669 | loss: 3.252551
iter: 2670 | loss: 3.251936
iter: 2671 | loss: 3.251321
iter: 2672 | loss: 3.250705
iter: 2673 | loss: 3.250090
iter: 2674 | loss: 3.249475
iter: 2675 | loss: 3.248860
iter: 2676 | loss: 3.248245
iter: 2677 | loss: 3.247630
iter: 2678 | loss: 3.247015
iter: 2679 | loss: 3.246400
iter: 2680 | loss: 3.245785
iter: 2681 | loss: 3.245170
iter: 2682 | loss: 3.244555
iter: 2683 | loss: 3.243940
iter: 2684 | loss: 3.243325
iter: 2685 | loss: 3.242710
iter: 2686 | loss: 3.242095
iter: 2687 | loss: 3.241480
iter: 2688 | loss: 3.240864
iter: 2689 | loss: 3.240249
iter: 2690 | loss: 3.239634
iter: 2691 | loss: 3.239019
iter: 2692 | loss: 3.238404
iter: 2693 | loss: 3.237789
iter: 2694 | loss: 3.237174
iter: 2695 | loss: 3.236559
iter: 2696 | loss: 3.235944
iter: 2697 | loss: 3.235329
iter: 2698 | loss: 3.234714
iter: 2699 | loss: 3.234099
iter: 2700 | loss: 3.233484
iter: 2701 | loss: 3.232869
iter: 2702 | loss: 3.232254
iter: 2703 | loss: 3.231639
iter: 2704 | loss: 3.231023
iter: 2705 | loss: 3.230408
iter: 2706 | loss: 3.229793
iter: 2707 | loss: 3.229178
iter: 2708 | loss: 3.228563
iter: 2709 | loss: 3.227948
iter: 2710 | loss: 3.227333
iter: 2711 | loss: 3.226718
iter: 2712 | loss: 3.226103
iter: 2713 | loss: 3.225488
iter: 2714 | loss: 3.224873
iter: 2715 | loss: 3.224258
iter: 2716 | loss: 3.223643
iter: 2717 | loss: 3.223028
iter: 2718 | loss: 3.222413
iter: 2719 | loss: 3.221797
iter: 2720 | loss: 3.221182
iter: 2721 | loss: 3.220567
iter: 2722 | loss: 3.219952
iter: 2723 | loss: 3.219337
iter: 2724 | loss: 3.218722
iter: 2725 | loss: 3.218107
iter: 2726 | loss: 3.217492
iter: 2727 | loss: 3.216877
iter: 2728 | loss: 3.216262
iter: 2729 | loss: 3.215647
iter: 2730 | loss: 3.215032
iter: 2731 | loss: 3.214417
iter: 2732 | loss: 3.213802
iter: 2733 | loss: 3.213187
iter: 2734 | loss: 3.212572
iter: 2735 | loss: 3.211956
iter: 2736 | loss: 3.211341
iter: 2737 | loss: 3.210726
iter: 2738 | loss: 3.210111
iter: 2739 | loss: 3.209496
iter: 2740 | loss: 3.208881
iter: 2741 | loss: 3.208266
iter: 2742 | loss: 3.207651
iter: 2743 | loss: 3.207036
iter: 2744 | loss: 3.206421
iter: 2745 | loss: 3.205806
iter: 2746 | loss: 3.205191
iter: 2747 | loss: 3.204576
iter: 2748 | loss: 3.203961
iter: 2749 | loss: 3.203346
iter: 2750 | loss: 3.202731
iter: 2751 | loss: 3.202115
iter: 2752 | loss: 3.201500
iter: 2753 | loss: 3.200885
iter: 2754 | loss: 3.200270
iter: 2755 | loss: 3.199655
iter: 2756 | loss: 3.199040
iter: 2757 | loss: 3.198425
iter: 2758 | loss: 3.197810
iter: 2759 | loss: 3.197195
iter: 2760 | loss: 3.196580
iter: 2761 | loss: 3.195965
iter: 2762 | loss: 3.195350
iter: 2763 | loss: 3.194735
iter: 2764 | loss: 3.194120
iter: 2765 | loss: 3.193505
iter: 2766 | loss: 3.192889
iter: 2767 | loss: 3.192274
iter: 2768 | loss: 3.191659
iter: 2769 | loss: 3.191044
iter: 2770 | loss: 3.190429
iter: 2771 | loss: 3.189814
iter: 2772 | loss: 3.189199
iter: 2773 | loss: 3.188584
iter: 2774 | loss: 3.187969
iter: 2775 | loss: 3.187354
iter: 2776 | loss: 3.186739
iter: 2777 | loss: 3.186124
iter: 2778 | loss: 3.185509
iter: 2779 | loss: 3.184894
iter: 2780 | loss: 3.184279
iter: 2781 | loss: 3.183664
iter: 2782 | loss: 3.183048
iter: 2783 | loss: 3.182433
iter: 2784 | loss: 3.181818
iter: 2785 | loss: 3.181203
iter: 2786 | loss: 3.180588
iter: 2787 | loss: 3.179973
iter: 2788 | loss: 3.179358
iter: 2789 | loss: 3.178743
iter: 2790 | loss: 3.178128
iter: 2791 | loss: 3.177513
iter: 2792 | loss: 3.176898
iter: 2793 | loss: 3.176283
iter: 2794 | loss: 3.175668
iter: 2795 | loss: 3.175053
iter: 2796 | loss: 3.174438
iter: 2797 | loss: 3.173823
iter: 2798 | loss: 3.173207
iter: 2799 | loss: 3.172592
iter: 2800 | loss: 3.171977
iter: 2801 | loss: 3.171362
iter: 2802 | loss: 3.170747
iter: 2803 | loss: 3.170132
iter: 2804 | loss: 3.169517
iter: 2805 | loss: 3.168902
iter: 2806 | loss: 3.168287
iter: 2807 | loss: 3.167672
iter: 2808 | loss: 3.167057
iter: 2809 | loss: 3.166442
iter: 2810 | loss: 3.165827
iter: 2811 | loss: 3.165212
iter: 2812 | loss: 3.164597
iter: 2813 | loss: 3.163982
iter: 2814 | loss: 3.163366
iter: 2815 | loss: 3.162751
iter: 2816 | loss: 3.162136
iter: 2817 | loss: 3.161521
iter: 2818 | loss: 3.160906
iter: 2819 | loss: 3.160291
iter: 2820 | loss: 3.159676
iter: 2821 | loss: 3.159061
iter: 2822 | loss: 3.158446
iter: 2823 | loss: 3.157831
iter: 2824 | loss: 3.157216
iter: 2825 | loss: 3.156601
iter: 2826 | loss: 3.155986
iter: 2827 | loss: 3.155371
iter: 2828 | loss: 3.154756
iter: 2829 | loss: 3.154140
iter: 2830 | loss: 3.153525
iter: 2831 | loss: 3.152910
iter: 2832 | loss: 3.152295
iter: 2833 | loss: 3.151680
iter: 2834 | loss: 3.151065
iter: 2835 | loss: 3.150450
iter: 2836 | loss: 3.149835
iter: 2837 | loss: 3.149220
iter: 2838 | loss: 3.148605
iter: 2839 | loss: 3.147990
iter: 2840 | loss: 3.147375
iter: 2841 | loss: 3.146760
iter: 2842 | loss: 3.146145
iter: 2843 | loss: 3.145530
iter: 2844 | loss: 3.144915
iter: 2845 | loss: 3.144299
iter: 2846 | loss: 3.143684
iter: 2847 | loss: 3.143069
iter: 2848 | loss: 3.142454
iter: 2849 | loss: 3.141839
iter: 2850 | loss: 3.141224
iter: 2851 | loss: 3.140609
iter: 2852 | loss: 3.139994
iter: 2853 | loss: 3.139379
iter: 2854 | loss: 3.138764
iter: 2855 | loss: 3.138149
iter: 2856 | loss: 3.137534
iter: 2857 | loss: 3.136919
iter: 2858 | loss: 3.136304
iter: 2859 | loss: 3.135689
iter: 2860 | loss: 3.135074
iter: 2861 | loss: 3.134458
iter: 2862 | loss: 3.133843
iter: 2863 | loss: 3.133228
iter: 2864 | loss: 3.132613
iter: 2865 | loss: 3.131998
iter: 2866 | loss: 3.131383
iter: 2867 | loss: 3.130768
iter: 2868 | loss: 3.130153
iter: 2869 | loss: 3.129538
iter: 2870 | loss: 3.128923
iter: 2871 | loss: 3.128308
iter: 2872 | loss: 3.127693
iter: 2873 | loss: 3.127078
iter: 2874 | loss: 3.126463
iter: 2875 | loss: 3.125848
iter: 2876 | loss: 3.125233
iter: 2877 | loss: 3.124617
iter: 2878 | loss: 3.124002
iter: 2879 | loss: 3.123387
iter: 2880 | loss: 3.122772
iter: 2881 | loss: 3.122157
iter: 2882 | loss: 3.121542
iter: 2883 | loss: 3.120927
iter: 2884 | loss: 3.120312
iter: 2885 | loss: 3.119697
iter: 2886 | loss: 3.119082
iter: 2887 | loss: 3.118467
iter: 2888 | loss: 3.117852
iter: 2889 | loss: 3.117237
iter: 2890 | loss: 3.116622
iter: 2891 | loss: 3.116007
iter: 2892 | loss: 3.115391
iter: 2893 | loss: 3.114776
iter: 2894 | loss: 3.114161
iter: 2895 | loss: 3.113546
iter: 2896 | loss: 3.112931
iter: 2897 | loss: 3.112316
iter: 2898 | loss: 3.111701
iter: 2899 | loss: 3.111086
iter: 2900 | loss: 3.110471
iter: 2901 | loss: 3.109856
iter: 2902 | loss: 3.109241
iter: 2903 | loss: 3.108626
iter: 2904 | loss: 3.108011
iter: 2905 | loss: 3.107396
iter: 2906 | loss: 3.106781
iter: 2907 | loss: 3.106166
iter: 2908 | loss: 3.105550
iter: 2909 | loss: 3.104935
iter: 2910 | loss: 3.104320
iter: 2911 | loss: 3.103705
iter: 2912 | loss: 3.103090
iter: 2913 | loss: 3.102475
iter: 2914 | loss: 3.101860
iter: 2915 | loss: 3.101245
iter: 2916 | loss: 3.100630
iter: 2917 | loss: 3.100015
iter: 2918 | loss: 3.099400
iter: 2919 | loss: 3.098785
iter: 2920 | loss: 3.098170
iter: 2921 | loss: 3.097555
iter: 2922 | loss: 3.096940
iter: 2923 | loss: 3.096325
iter: 2924 | loss: 3.095709
iter: 2925 | loss: 3.095094
iter: 2926 | loss: 3.094479
iter: 2927 | loss: 3.093864
iter: 2928 | loss: 3.093249
iter: 2929 | loss: 3.092634
iter: 2930 | loss: 3.092019
iter: 2931 | loss: 3.091404
iter: 2932 | loss: 3.090789
iter: 2933 | loss: 3.090174
iter: 2934 | loss: 3.089559
iter: 2935 | loss: 3.088944
iter: 2936 | loss: 3.088329
iter: 2937 | loss: 3.087714
iter: 2938 | loss: 3.087099
iter: 2939 | loss: 3.086484
iter: 2940 | loss: 3.085868
iter: 2941 | loss: 3.085253
iter: 2942 | loss: 3.084638
iter: 2943 | loss: 3.084023
iter: 2944 | loss: 3.083408
iter: 2945 | loss: 3.082793
iter: 2946 | loss: 3.082178
iter: 2947 | loss: 3.081563
iter: 2948 | loss: 3.080948
iter: 2949 | loss: 3.080333
iter: 2950 | loss: 3.079718
iter: 2951 | loss: 3.079103
iter: 2952 | loss: 3.078488
iter: 2953 | loss: 3.077873
iter: 2954 | loss: 3.077258
iter: 2955 | loss: 3.076642
iter: 2956 | loss: 3.076027
iter: 2957 | loss: 3.075412
iter: 2958 | loss: 3.074797
iter: 2959 | loss: 3.074182
iter: 2960 | loss: 3.073567
iter: 2961 | loss: 3.072952
iter: 2962 | loss: 3.072337
iter: 2963 | loss: 3.071722
iter: 2964 | loss: 3.071107
iter: 2965 | loss: 3.070492
iter: 2966 | loss: 3.069877
iter: 2967 | loss: 3.069262
iter: 2968 | loss: 3.068647
iter: 2969 | loss: 3.068032
iter: 2970 | loss: 3.067417
iter: 2971 | loss: 3.066801
iter: 2972 | loss: 3.066186
iter: 2973 | loss: 3.065571
iter: 2974 | loss: 3.064956
iter: 2975 | loss: 3.064341
iter: 2976 | loss: 3.063726
iter: 2977 | loss: 3.063111
iter: 2978 | loss: 3.062496
iter: 2979 | loss: 3.061881
iter: 2980 | loss: 3.061266
iter: 2981 | loss: 3.060651
iter: 2982 | loss: 3.060036
iter: 2983 | loss: 3.059421
iter: 2984 | loss: 3.058806
iter: 2985 | loss: 3.058191
iter: 2986 | loss: 3.057576
iter: 2987 | loss: 3.056960
iter: 2988 | loss: 3.056345
iter: 2989 | loss: 3.055730
iter: 2990 | loss: 3.055115
iter: 2991 | loss: 3.054500
iter: 2992 | loss: 3.053885
iter: 2993 | loss: 3.053270
iter: 2994 | loss: 3.052655
iter: 2995 | loss: 3.052040
iter: 2996 | loss: 3.051425
iter: 2997 | loss: 3.050810
iter: 2998 | loss: 3.050195
iter: 2999 | loss: 3.049580
iter: 3000 | loss: 3.048965
iter: 3001 | loss: 3.048350
iter: 3002 | loss: 3.047734
iter: 3003 | loss: 3.047119
iter: 3004 | loss: 3.046504
iter: 3005 | loss: 3.045889
iter: 3006 | loss: 3.045274
iter: 3007 | loss: 3.044659
iter: 3008 | loss: 3.044044
iter: 3009 | loss: 3.043429
iter: 3010 | loss: 3.042814
iter: 3011 | loss: 3.042199
iter: 3012 | loss: 3.041584
iter: 3013 | loss: 3.040969
iter: 3014 | loss: 3.040354
iter: 3015 | loss: 3.039739
iter: 3016 | loss: 3.039124
iter: 3017 | loss: 3.038509
iter: 3018 | loss: 3.037893
iter: 3019 | loss: 3.037278
iter: 3020 | loss: 3.036663
iter: 3021 | loss: 3.036048
iter: 3022 | loss: 3.035433
iter: 3023 | loss: 3.034818
iter: 3024 | loss: 3.034203
iter: 3025 | loss: 3.033588
iter: 3026 | loss: 3.032973
iter: 3027 | loss: 3.032358
iter: 3028 | loss: 3.031743
iter: 3029 | loss: 3.031128
iter: 3030 | loss: 3.030513
iter: 3031 | loss: 3.029898
iter: 3032 | loss: 3.029283
iter: 3033 | loss: 3.028668
iter: 3034 | loss: 3.028052
iter: 3035 | loss: 3.027437
iter: 3036 | loss: 3.026822
iter: 3037 | loss: 3.026207
iter: 3038 | loss: 3.025592
iter: 3039 | loss: 3.024977
iter: 3040 | loss: 3.024362
iter: 3041 | loss: 3.023747
iter: 3042 | loss: 3.023132
iter: 3043 | loss: 3.022517
iter: 3044 | loss: 3.021902
iter: 3045 | loss: 3.021287
iter: 3046 | loss: 3.020672
iter: 3047 | loss: 3.020057
iter: 3048 | loss: 3.019442
iter: 3049 | loss: 3.018827
iter: 3050 | loss: 3.018211
iter: 3051 | loss: 3.017596
iter: 3052 | loss: 3.016981
iter: 3053 | loss: 3.016366
iter: 3054 | loss: 3.015751
iter: 3055 | loss: 3.015136
iter: 3056 | loss: 3.014521
iter: 3057 | loss: 3.013906
iter: 3058 | loss: 3.013291
iter: 3059 | loss: 3.012676
iter: 3060 | loss: 3.012061
iter: 3061 | loss: 3.011446
iter: 3062 | loss: 3.010831
iter: 3063 | loss: 3.010216
iter: 3064 | loss: 3.009601
iter: 3065 | loss: 3.008985
iter: 3066 | loss: 3.008370
iter: 3067 | loss: 3.007755
iter: 3068 | loss: 3.007140
iter: 3069 | loss: 3.006525
iter: 3070 | loss: 3.005910
iter: 3071 | loss: 3.005295
iter: 3072 | loss: 3.004680
iter: 3073 | loss: 3.004065
iter: 3074 | loss: 3.003450
iter: 3075 | loss: 3.002835
iter: 3076 | loss: 3.002220
iter: 3077 | loss: 3.001605
iter: 3078 | loss: 3.000990
iter: 3079 | loss: 3.000375
iter: 3080 | loss: 2.999760
iter: 3081 | loss: 2.999144
iter: 3082 | loss: 2.998529
iter: 3083 | loss: 2.997914
iter: 3084 | loss: 2.997299
iter: 3085 | loss: 2.996684
iter: 3086 | loss: 2.996069
iter: 3087 | loss: 2.995454
iter: 3088 | loss: 2.994839
iter: 3089 | loss: 2.994224
iter: 3090 | loss: 2.993609
iter: 3091 | loss: 2.992994
iter: 3092 | loss: 2.992379
iter: 3093 | loss: 2.991764
iter: 3094 | loss: 2.991149
iter: 3095 | loss: 2.990534
iter: 3096 | loss: 2.989919
iter: 3097 | loss: 2.989303
iter: 3098 | loss: 2.988688
iter: 3099 | loss: 2.988073
iter: 3100 | loss: 2.987458
iter: 3101 | loss: 2.986843
iter: 3102 | loss: 2.986228
iter: 3103 | loss: 2.985613
iter: 3104 | loss: 2.984998
iter: 3105 | loss: 2.984383
iter: 3106 | loss: 2.983768
iter: 3107 | loss: 2.983153
iter: 3108 | loss: 2.982538
iter: 3109 | loss: 2.981923
iter: 3110 | loss: 2.981308
iter: 3111 | loss: 2.980693
iter: 3112 | loss: 2.980078
iter: 3113 | loss: 2.979462
iter: 3114 | loss: 2.978847
iter: 3115 | loss: 2.978232
iter: 3116 | loss: 2.977617
iter: 3117 | loss: 2.977002
iter: 3118 | loss: 2.976387
iter: 3119 | loss: 2.975772
iter: 3120 | loss: 2.975157
iter: 3121 | loss: 2.974542
iter: 3122 | loss: 2.973927
iter: 3123 | loss: 2.973312
iter: 3124 | loss: 2.972697
iter: 3125 | loss: 2.972082
iter: 3126 | loss: 2.971467
iter: 3127 | loss: 2.970852
iter: 3128 | loss: 2.970236
iter: 3129 | loss: 2.969621
iter: 3130 | loss: 2.969006
iter: 3131 | loss: 2.968391
iter: 3132 | loss: 2.967776
iter: 3133 | loss: 2.967161
iter: 3134 | loss: 2.966546
iter: 3135 | loss: 2.965931
iter: 3136 | loss: 2.965316
iter: 3137 | loss: 2.964701
iter: 3138 | loss: 2.964086
iter: 3139 | loss: 2.963471
iter: 3140 | loss: 2.962856
iter: 3141 | loss: 2.962241
iter: 3142 | loss: 2.961626
iter: 3143 | loss: 2.961011
iter: 3144 | loss: 2.960395
iter: 3145 | loss: 2.959780
iter: 3146 | loss: 2.959165
iter: 3147 | loss: 2.958550
iter: 3148 | loss: 2.957935
iter: 3149 | loss: 2.957320
iter: 3150 | loss: 2.956705
iter: 3151 | loss: 2.956090
iter: 3152 | loss: 2.955475
iter: 3153 | loss: 2.954860
iter: 3154 | loss: 2.954245
iter: 3155 | loss: 2.953630
iter: 3156 | loss: 2.953015
iter: 3157 | loss: 2.952400
iter: 3158 | loss: 2.951785
iter: 3159 | loss: 2.951170
iter: 3160 | loss: 2.950554
iter: 3161 | loss: 2.949939
iter: 3162 | loss: 2.949324
iter: 3163 | loss: 2.948709
iter: 3164 | loss: 2.948094
iter: 3165 | loss: 2.947479
iter: 3166 | loss: 2.946864
iter: 3167 | loss: 2.946249
iter: 3168 | loss: 2.945634
iter: 3169 | loss: 2.945019
iter: 3170 | loss: 2.944404
iter: 3171 | loss: 2.943789
iter: 3172 | loss: 2.943174
iter: 3173 | loss: 2.942559
iter: 3174 | loss: 2.941944
iter: 3175 | loss: 2.941328
iter: 3176 | loss: 2.940713
iter: 3177 | loss: 2.940098
iter: 3178 | loss: 2.939483
iter: 3179 | loss: 2.938868
iter: 3180 | loss: 2.938253
iter: 3181 | loss: 2.937638
iter: 3182 | loss: 2.937023
iter: 3183 | loss: 2.936408
iter: 3184 | loss: 2.935793
iter: 3185 | loss: 2.935178
iter: 3186 | loss: 2.934563
iter: 3187 | loss: 2.933948
iter: 3188 | loss: 2.933333
iter: 3189 | loss: 2.932718
iter: 3190 | loss: 2.932103
iter: 3191 | loss: 2.931487
iter: 3192 | loss: 2.930872
iter: 3193 | loss: 2.930257
iter: 3194 | loss: 2.929642
iter: 3195 | loss: 2.929027
iter: 3196 | loss: 2.928412
iter: 3197 | loss: 2.927797
iter: 3198 | loss: 2.927182
iter: 3199 | loss: 2.926567
iter: 3200 | loss: 2.925952
iter: 3201 | loss: 2.925337
iter: 3202 | loss: 2.924722
iter: 3203 | loss: 2.924107
iter: 3204 | loss: 2.923492
iter: 3205 | loss: 2.922877
iter: 3206 | loss: 2.922262
iter: 3207 | loss: 2.921646
iter: 3208 | loss: 2.921031
iter: 3209 | loss: 2.920416
iter: 3210 | loss: 2.919801
iter: 3211 | loss: 2.919186
iter: 3212 | loss: 2.918571
iter: 3213 | loss: 2.917956
iter: 3214 | loss: 2.917341
iter: 3215 | loss: 2.916726
iter: 3216 | loss: 2.916111
iter: 3217 | loss: 2.915496
iter: 3218 | loss: 2.914881
iter: 3219 | loss: 2.914266
iter: 3220 | loss: 2.913651
iter: 3221 | loss: 2.913036
iter: 3222 | loss: 2.912421
iter: 3223 | loss: 2.911805
iter: 3224 | loss: 2.911190
iter: 3225 | loss: 2.910575
iter: 3226 | loss: 2.909960
iter: 3227 | loss: 2.909345
iter: 3228 | loss: 2.908730
iter: 3229 | loss: 2.908115
iter: 3230 | loss: 2.907500
iter: 3231 | loss: 2.906885
iter: 3232 | loss: 2.906270
iter: 3233 | loss: 2.905655
iter: 3234 | loss: 2.905040
iter: 3235 | loss: 2.904425
iter: 3236 | loss: 2.903810
iter: 3237 | loss: 2.903195
iter: 3238 | loss: 2.902579
iter: 3239 | loss: 2.901964
iter: 3240 | loss: 2.901349
iter: 3241 | loss: 2.900734
iter: 3242 | loss: 2.900119
iter: 3243 | loss: 2.899504
iter: 3244 | loss: 2.898889
iter: 3245 | loss: 2.898274
iter: 3246 | loss: 2.897659
iter: 3247 | loss: 2.897044
iter: 3248 | loss: 2.896429
iter: 3249 | loss: 2.895814
iter: 3250 | loss: 2.895199
iter: 3251 | loss: 2.894584
iter: 3252 | loss: 2.893969
iter: 3253 | loss: 2.893354
iter: 3254 | loss: 2.892738
iter: 3255 | loss: 2.892123
iter: 3256 | loss: 2.891508
iter: 3257 | loss: 2.890893
iter: 3258 | loss: 2.890278
iter: 3259 | loss: 2.889663
iter: 3260 | loss: 2.889048
iter: 3261 | loss: 2.888433
iter: 3262 | loss: 2.887818
iter: 3263 | loss: 2.887203
iter: 3264 | loss: 2.886588
iter: 3265 | loss: 2.885973
iter: 3266 | loss: 2.885358
iter: 3267 | loss: 2.884743
iter: 3268 | loss: 2.884128
iter: 3269 | loss: 2.883513
iter: 3270 | loss: 2.882897
iter: 3271 | loss: 2.882282
iter: 3272 | loss: 2.881667
iter: 3273 | loss: 2.881052
iter: 3274 | loss: 2.880437
iter: 3275 | loss: 2.879822
iter: 3276 | loss: 2.879207
iter: 3277 | loss: 2.878592
iter: 3278 | loss: 2.877977
iter: 3279 | loss: 2.877362
iter: 3280 | loss: 2.876747
iter: 3281 | loss: 2.876132
iter: 3282 | loss: 2.875517
iter: 3283 | loss: 2.874902
iter: 3284 | loss: 2.874287
iter: 3285 | loss: 2.873672
iter: 3286 | loss: 2.873056
iter: 3287 | loss: 2.872441
iter: 3288 | loss: 2.871826
iter: 3289 | loss: 2.871211
iter: 3290 | loss: 2.870596
iter: 3291 | loss: 2.869981
iter: 3292 | loss: 2.869366
iter: 3293 | loss: 2.868751
iter: 3294 | loss: 2.868136
iter: 3295 | loss: 2.867521
iter: 3296 | loss: 2.866906
iter: 3297 | loss: 2.866291
iter: 3298 | loss: 2.865676
iter: 3299 | loss: 2.865061
iter: 3300 | loss: 2.864446
iter: 3301 | loss: 2.863830
iter: 3302 | loss: 2.863215
iter: 3303 | loss: 2.862600
iter: 3304 | loss: 2.861985
iter: 3305 | loss: 2.861370
iter: 3306 | loss: 2.860755
iter: 3307 | loss: 2.860140
iter: 3308 | loss: 2.859525
iter: 3309 | loss: 2.858910
iter: 3310 | loss: 2.858295
iter: 3311 | loss: 2.857680
iter: 3312 | loss: 2.857065
iter: 3313 | loss: 2.856450
iter: 3314 | loss: 2.855835
iter: 3315 | loss: 2.855220
iter: 3316 | loss: 2.854605
iter: 3317 | loss: 2.853989
iter: 3318 | loss: 2.853374
iter: 3319 | loss: 2.852759
iter: 3320 | loss: 2.852144
iter: 3321 | loss: 2.851529
iter: 3322 | loss: 2.850914
iter: 3323 | loss: 2.850299
iter: 3324 | loss: 2.849684
iter: 3325 | loss: 2.849069
iter: 3326 | loss: 2.848454
iter: 3327 | loss: 2.847839
iter: 3328 | loss: 2.847224
iter: 3329 | loss: 2.846609
iter: 3330 | loss: 2.845994
iter: 3331 | loss: 2.845379
iter: 3332 | loss: 2.844764
iter: 3333 | loss: 2.844148
iter: 3334 | loss: 2.843533
iter: 3335 | loss: 2.842918
iter: 3336 | loss: 2.842303
iter: 3337 | loss: 2.841688
iter: 3338 | loss: 2.841073
iter: 3339 | loss: 2.840458
iter: 3340 | loss: 2.839843
iter: 3341 | loss: 2.839228
iter: 3342 | loss: 2.838613
iter: 3343 | loss: 2.837998
iter: 3344 | loss: 2.837383
iter: 3345 | loss: 2.836768
iter: 3346 | loss: 2.836153
iter: 3347 | loss: 2.835538
iter: 3348 | loss: 2.834923
iter: 3349 | loss: 2.834307
iter: 3350 | loss: 2.833692
iter: 3351 | loss: 2.833077
iter: 3352 | loss: 2.832462
iter: 3353 | loss: 2.831847
iter: 3354 | loss: 2.831232
iter: 3355 | loss: 2.830617
iter: 3356 | loss: 2.830002
iter: 3357 | loss: 2.829387
iter: 3358 | loss: 2.828772
iter: 3359 | loss: 2.828157
iter: 3360 | loss: 2.827542
iter: 3361 | loss: 2.826927
iter: 3362 | loss: 2.826312
iter: 3363 | loss: 2.825697
iter: 3364 | loss: 2.825081
iter: 3365 | loss: 2.824466
iter: 3366 | loss: 2.823851
iter: 3367 | loss: 2.823236
iter: 3368 | loss: 2.822621
iter: 3369 | loss: 2.822006
iter: 3370 | loss: 2.821391
iter: 3371 | loss: 2.820776
iter: 3372 | loss: 2.820161
iter: 3373 | loss: 2.819546
iter: 3374 | loss: 2.818931
iter: 3375 | loss: 2.818316
iter: 3376 | loss: 2.817701
iter: 3377 | loss: 2.817086
iter: 3378 | loss: 2.816471
iter: 3379 | loss: 2.815856
iter: 3380 | loss: 2.815240
iter: 3381 | loss: 2.814625
iter: 3382 | loss: 2.814010
iter: 3383 | loss: 2.813395
iter: 3384 | loss: 2.812780
iter: 3385 | loss: 2.812165
iter: 3386 | loss: 2.811550
iter: 3387 | loss: 2.810935
iter: 3388 | loss: 2.810320
iter: 3389 | loss: 2.809705
iter: 3390 | loss: 2.809090
iter: 3391 | loss: 2.808475
iter: 3392 | loss: 2.807860
iter: 3393 | loss: 2.807245
iter: 3394 | loss: 2.806630
iter: 3395 | loss: 2.806015
iter: 3396 | loss: 2.805399
iter: 3397 | loss: 2.804784
iter: 3398 | loss: 2.804169
iter: 3399 | loss: 2.803554
iter: 3400 | loss: 2.802939
iter: 3401 | loss: 2.802324
iter: 3402 | loss: 2.801709
iter: 3403 | loss: 2.801094
iter: 3404 | loss: 2.800479
iter: 3405 | loss: 2.799864
iter: 3406 | loss: 2.799249
iter: 3407 | loss: 2.798634
iter: 3408 | loss: 2.798019
iter: 3409 | loss: 2.797404
iter: 3410 | loss: 2.796789
iter: 3411 | loss: 2.796173
iter: 3412 | loss: 2.795558
iter: 3413 | loss: 2.794943
iter: 3414 | loss: 2.794328
iter: 3415 | loss: 2.793713
iter: 3416 | loss: 2.793098
iter: 3417 | loss: 2.792483
iter: 3418 | loss: 2.791868
iter: 3419 | loss: 2.791253
iter: 3420 | loss: 2.790638
iter: 3421 | loss: 2.790023
iter: 3422 | loss: 2.789408
iter: 3423 | loss: 2.788793
iter: 3424 | loss: 2.788178
iter: 3425 | loss: 2.787563
iter: 3426 | loss: 2.786948
iter: 3427 | loss: 2.786332
iter: 3428 | loss: 2.785717
iter: 3429 | loss: 2.785102
iter: 3430 | loss: 2.784487
iter: 3431 | loss: 2.783872
iter: 3432 | loss: 2.783257
iter: 3433 | loss: 2.782642
iter: 3434 | loss: 2.782027
iter: 3435 | loss: 2.781412
iter: 3436 | loss: 2.780797
iter: 3437 | loss: 2.780182
iter: 3438 | loss: 2.779567
iter: 3439 | loss: 2.778952
iter: 3440 | loss: 2.778337
iter: 3441 | loss: 2.777722
iter: 3442 | loss: 2.777107
iter: 3443 | loss: 2.776491
iter: 3444 | loss: 2.775876
iter: 3445 | loss: 2.775261
iter: 3446 | loss: 2.774646
iter: 3447 | loss: 2.774031
iter: 3448 | loss: 2.773416
iter: 3449 | loss: 2.772801
iter: 3450 | loss: 2.772186
iter: 3451 | loss: 2.771571
iter: 3452 | loss: 2.770956
iter: 3453 | loss: 2.770341
iter: 3454 | loss: 2.769726
iter: 3455 | loss: 2.769111
iter: 3456 | loss: 2.768496
iter: 3457 | loss: 2.767881
iter: 3458 | loss: 2.767266
iter: 3459 | loss: 2.766650
iter: 3460 | loss: 2.766035
iter: 3461 | loss: 2.765420
iter: 3462 | loss: 2.764805
iter: 3463 | loss: 2.764190
iter: 3464 | loss: 2.763575
iter: 3465 | loss: 2.762960
iter: 3466 | loss: 2.762345
iter: 3467 | loss: 2.761730
iter: 3468 | loss: 2.761115
iter: 3469 | loss: 2.760500
iter: 3470 | loss: 2.759885
iter: 3471 | loss: 2.759270
iter: 3472 | loss: 2.758655
iter: 3473 | loss: 2.758040
iter: 3474 | loss: 2.757424
iter: 3475 | loss: 2.756809
iter: 3476 | loss: 2.756194
iter: 3477 | loss: 2.755579
iter: 3478 | loss: 2.754964
iter: 3479 | loss: 2.754349
iter: 3480 | loss: 2.753734
iter: 3481 | loss: 2.753119
iter: 3482 | loss: 2.752504
iter: 3483 | loss: 2.751889
iter: 3484 | loss: 2.751274
iter: 3485 | loss: 2.750659
iter: 3486 | loss: 2.750044
iter: 3487 | loss: 2.749429
iter: 3488 | loss: 2.748814
iter: 3489 | loss: 2.748199
iter: 3490 | loss: 2.747583
iter: 3491 | loss: 2.746968
iter: 3492 | loss: 2.746353
iter: 3493 | loss: 2.745738
iter: 3494 | loss: 2.745123
iter: 3495 | loss: 2.744508
iter: 3496 | loss: 2.743893
iter: 3497 | loss: 2.743278
iter: 3498 | loss: 2.742663
iter: 3499 | loss: 2.742048
iter: 3500 | loss: 2.741433
iter: 3501 | loss: 2.740818
iter: 3502 | loss: 2.740203
iter: 3503 | loss: 2.739588
iter: 3504 | loss: 2.738973
iter: 3505 | loss: 2.738358
iter: 3506 | loss: 2.737742
iter: 3507 | loss: 2.737127
iter: 3508 | loss: 2.736512
iter: 3509 | loss: 2.735897
iter: 3510 | loss: 2.735282
iter: 3511 | loss: 2.734667
iter: 3512 | loss: 2.734052
iter: 3513 | loss: 2.733437
iter: 3514 | loss: 2.732822
iter: 3515 | loss: 2.732207
iter: 3516 | loss: 2.731592
iter: 3517 | loss: 2.730977
iter: 3518 | loss: 2.730362
iter: 3519 | loss: 2.729747
iter: 3520 | loss: 2.729132
iter: 3521 | loss: 2.728517
iter: 3522 | loss: 2.727901
iter: 3523 | loss: 2.727286
iter: 3524 | loss: 2.726671
iter: 3525 | loss: 2.726056
iter: 3526 | loss: 2.725441
iter: 3527 | loss: 2.724826
iter: 3528 | loss: 2.724211
iter: 3529 | loss: 2.723596
iter: 3530 | loss: 2.722981
iter: 3531 | loss: 2.722366
iter: 3532 | loss: 2.721751
iter: 3533 | loss: 2.721136
iter: 3534 | loss: 2.720521
iter: 3535 | loss: 2.719906
iter: 3536 | loss: 2.719291
iter: 3537 | loss: 2.718675
iter: 3538 | loss: 2.718060
iter: 3539 | loss: 2.717445
iter: 3540 | loss: 2.716830
iter: 3541 | loss: 2.716215
iter: 3542 | loss: 2.715600
iter: 3543 | loss: 2.714985
iter: 3544 | loss: 2.714370
iter: 3545 | loss: 2.713755
iter: 3546 | loss: 2.713140
iter: 3547 | loss: 2.712525
iter: 3548 | loss: 2.711910
iter: 3549 | loss: 2.711295
iter: 3550 | loss: 2.710680
iter: 3551 | loss: 2.710065
iter: 3552 | loss: 2.709450
iter: 3553 | loss: 2.708834
iter: 3554 | loss: 2.708219
iter: 3555 | loss: 2.707604
iter: 3556 | loss: 2.706989
iter: 3557 | loss: 2.706374
iter: 3558 | loss: 2.705759
iter: 3559 | loss: 2.705144
iter: 3560 | loss: 2.704529
iter: 3561 | loss: 2.703914
iter: 3562 | loss: 2.703299
iter: 3563 | loss: 2.702684
iter: 3564 | loss: 2.702069
iter: 3565 | loss: 2.701454
iter: 3566 | loss: 2.700839
iter: 3567 | loss: 2.700224
iter: 3568 | loss: 2.699609
iter: 3569 | loss: 2.698993
iter: 3570 | loss: 2.698378
iter: 3571 | loss: 2.697763
iter: 3572 | loss: 2.697148
iter: 3573 | loss: 2.696533
iter: 3574 | loss: 2.695918
iter: 3575 | loss: 2.695303
iter: 3576 | loss: 2.694688
iter: 3577 | loss: 2.694073
iter: 3578 | loss: 2.693458
iter: 3579 | loss: 2.692843
iter: 3580 | loss: 2.692228
iter: 3581 | loss: 2.691613
iter: 3582 | loss: 2.690998
iter: 3583 | loss: 2.690383
iter: 3584 | loss: 2.689768
iter: 3585 | loss: 2.689152
iter: 3586 | loss: 2.688537
iter: 3587 | loss: 2.687922
iter: 3588 | loss: 2.687307
iter: 3589 | loss: 2.686692
iter: 3590 | loss: 2.686077
iter: 3591 | loss: 2.685462
iter: 3592 | loss: 2.684847
iter: 3593 | loss: 2.684232
iter: 3594 | loss: 2.683617
iter: 3595 | loss: 2.683002
iter: 3596 | loss: 2.682387
iter: 3597 | loss: 2.681772
iter: 3598 | loss: 2.681157
iter: 3599 | loss: 2.680542
iter: 3600 | loss: 2.679926
iter: 3601 | loss: 2.679311
iter: 3602 | loss: 2.678696
iter: 3603 | loss: 2.678081
iter: 3604 | loss: 2.677466
iter: 3605 | loss: 2.676851
iter: 3606 | loss: 2.676236
iter: 3607 | loss: 2.675621
iter: 3608 | loss: 2.675006
iter: 3609 | loss: 2.674391
iter
- ...TRUNCATED BY DUNE...
- (cd _build/default/examples/opt && ./rmsprop.exe)
- 
step: 0 | loss: 4.800058357
step: 10 | loss: 4.790948952
step: 20 | loss: 4.784492209
step: 30 | loss: 4.778593786
step: 40 | loss: 4.772855837
step: 50 | loss: 4.767170957
step: 60 | loss: 4.761504588
step: 70 | loss: 4.755845008
step: 80 | loss: 4.750188166
step: 90 | loss: 4.744532658
step: 100 | loss: 4.738877995
step: 110 | loss: 4.733224008
step: 120 | loss: 4.727570640
step: 130 | loss: 4.721917872
step: 140 | loss: 4.716265700
step: 150 | loss: 4.710614122
step: 160 | loss: 4.704963140
step: 170 | loss: 4.699312755
step: 180 | loss: 4.693662971
step: 190 | loss: 4.688013788
step: 200 | loss: 4.682365210
step: 210 | loss: 4.676717238
step: 220 | loss: 4.671069874
step: 230 | loss: 4.665423121
step: 240 | loss: 4.659776981
step: 250 | loss: 4.654131456
step: 260 | loss: 4.648486548
step: 270 | loss: 4.642842260
step: 280 | loss: 4.637198594
step: 290 | loss: 4.631555552
step: 300 | loss: 4.625913137
step: 310 | loss: 4.620271350
step: 320 | loss: 4.614630195
step: 330 | loss: 4.608989672
step: 340 | loss: 4.603349786
step: 350 | loss: 4.597710537
step: 360 | loss: 4.592071929
step: 370 | loss: 4.586433964
step: 380 | loss: 4.580796643
step: 390 | loss: 4.575159971
step: 400 | loss: 4.569523948
step: 410 | loss: 4.563888577
step: 420 | loss: 4.558253861
step: 430 | loss: 4.552619803
step: 440 | loss: 4.546986403
step: 450 | loss: 4.541353666
step: 460 | loss: 4.535721594
step: 470 | loss: 4.530090188
step: 480 | loss: 4.524459452
step: 490 | loss: 4.518829388
step: 500 | loss: 4.513199998
step: 510 | loss: 4.507571286
step: 520 | loss: 4.501943253
step: 530 | loss: 4.496315902
step: 540 | loss: 4.490689235
step: 550 | loss: 4.485063256
step: 560 | loss: 4.479437967
step: 570 | loss: 4.473813370
step: 580 | loss: 4.468189469
step: 590 | loss: 4.462566265
step: 600 | loss: 4.456943761
step: 610 | loss: 4.451321960
step: 620 | loss: 4.445700865
step: 630 | loss: 4.440080478
step: 640 | loss: 4.434460802
step: 650 | loss: 4.428841840
step: 660 | loss: 4.423223595
step: 670 | loss: 4.417606068
step: 680 | loss: 4.411989264
step: 690 | loss: 4.406373184
step: 700 | loss: 4.400757831
step: 710 | loss: 4.395143209
step: 720 | loss: 4.389529320
step: 730 | loss: 4.383916166
step: 740 | loss: 4.378303752
step: 750 | loss: 4.372692078
step: 760 | loss: 4.367081149
step: 770 | loss: 4.361470968
step: 780 | loss: 4.355861536
step: 790 | loss: 4.350252858
step: 800 | loss: 4.344644935
step: 810 | loss: 4.339037772
step: 820 | loss: 4.333431370
step: 830 | loss: 4.327825733
step: 840 | loss: 4.322220864
step: 850 | loss: 4.316616765
step: 860 | loss: 4.311013440
step: 870 | loss: 4.305410892
step: 880 | loss: 4.299809124
step: 890 | loss: 4.294208138
step: 900 | loss: 4.288607939
step: 910 | loss: 4.283008528
step: 920 | loss: 4.277409910
step: 930 | loss: 4.271812087
step: 940 | loss: 4.266215062
step: 950 | loss: 4.260618838
step: 960 | loss: 4.255023420
step: 970 | loss: 4.249428809
step: 980 | loss: 4.243835009
step: 990 | loss: 4.238242023
step: 1000 | loss: 4.232649855
step: 1010 | loss: 4.227058507
step: 1020 | loss: 4.221467983
step: 1030 | loss: 4.215878287
step: 1040 | loss: 4.210289421
step: 1050 | loss: 4.204701389
step: 1060 | loss: 4.199114194
step: 1070 | loss: 4.193527839
step: 1080 | loss: 4.187942329
step: 1090 | loss: 4.182357665
step: 1100 | loss: 4.176773852
step: 1110 | loss: 4.171190894
step: 1120 | loss: 4.165608792
step: 1130 | loss: 4.160027552
step: 1140 | loss: 4.154447176
step: 1150 | loss: 4.148867668
step: 1160 | loss: 4.143289031
step: 1170 | loss: 4.137711270
step: 1180 | loss: 4.132134386
step: 1190 | loss: 4.126558385
step: 1200 | loss: 4.120983269
step: 1210 | loss: 4.115409043
step: 1220 | loss: 4.109835709
step: 1230 | loss: 4.104263272
step: 1240 | loss: 4.098691734
step: 1250 | loss: 4.093121101
step: 1260 | loss: 4.087551375
step: 1270 | loss: 4.081982560
step: 1280 | loss: 4.076414660
step: 1290 | loss: 4.070847679
step: 1300 | loss: 4.065281620
step: 1310 | loss: 4.059716487
step: 1320 | loss: 4.054152284
step: 1330 | loss: 4.048589015
step: 1340 | loss: 4.043026684
step: 1350 | loss: 4.037465295
step: 1360 | loss: 4.031904850
step: 1370 | loss: 4.026345356
step: 1380 | loss: 4.020786814
step: 1390 | loss: 4.015229230
step: 1400 | loss: 4.009672607
step: 1410 | loss: 4.004116950
step: 1420 | loss: 3.998562261
step: 1430 | loss: 3.993008546
step: 1440 | loss: 3.987455809
step: 1450 | loss: 3.981904053
step: 1460 | loss: 3.976353282
step: 1470 | loss: 3.970803501
step: 1480 | loss: 3.965254714
step: 1490 | loss: 3.959706925
step: 1500 | loss: 3.954160138
step: 1510 | loss: 3.948614358
step: 1520 | loss: 3.943069588
step: 1530 | loss: 3.937525834
step: 1540 | loss: 3.931983098
step: 1550 | loss: 3.926441386
step: 1560 | loss: 3.920900702
step: 1570 | loss: 3.915361051
step: 1580 | loss: 3.909822436
step: 1590 | loss: 3.904284862
step: 1600 | loss: 3.898748333
step: 1610 | loss: 3.893212855
step: 1620 | loss: 3.887678430
step: 1630 | loss: 3.882145065
step: 1640 | loss: 3.876612764
step: 1650 | loss: 3.871081530
step: 1660 | loss: 3.865551369
step: 1670 | loss: 3.860022285
step: 1680 | loss: 3.854494283
step: 1690 | loss: 3.848967367
step: 1700 | loss: 3.843441543
step: 1710 | loss: 3.837916814
step: 1720 | loss: 3.832393186
step: 1730 | loss: 3.826870663
step: 1740 | loss: 3.821349251
step: 1750 | loss: 3.815828954
step: 1760 | loss: 3.810309776
step: 1770 | loss: 3.804791723
step: 1780 | loss: 3.799274800
step: 1790 | loss: 3.793759011
step: 1800 | loss: 3.788244362
step: 1810 | loss: 3.782730857
step: 1820 | loss: 3.777218502
step: 1830 | loss: 3.771707301
step: 1840 | loss: 3.766197259
step: 1850 | loss: 3.760688383
step: 1860 | loss: 3.755180676
step: 1870 | loss: 3.749674144
step: 1880 | loss: 3.744168792
step: 1890 | loss: 3.738664625
step: 1900 | loss: 3.733161649
step: 1910 | loss: 3.727659869
step: 1920 | loss: 3.722159290
step: 1930 | loss: 3.716659917
step: 1940 | loss: 3.711161756
step: 1950 | loss: 3.705664812
step: 1960 | loss: 3.700169091
step: 1970 | loss: 3.694674598
step: 1980 | loss: 3.689181338
step: 1990 | loss: 3.683689318
step: 2000 | loss: 3.678198542
step: 2010 | loss: 3.672709016
step: 2020 | loss: 3.667220746
step: 2030 | loss: 3.661733738
step: 2040 | loss: 3.656247996
step: 2050 | loss: 3.650763527
step: 2060 | loss: 3.645280337
step: 2070 | loss: 3.639798431
step: 2080 | loss: 3.634317816
step: 2090 | loss: 3.628838496
step: 2100 | loss: 3.623360478
step: 2110 | loss: 3.617883768
step: 2120 | loss: 3.612408371
step: 2130 | loss: 3.606934294
step: 2140 | loss: 3.601461543
step: 2150 | loss: 3.595990123
step: 2160 | loss: 3.590520042
step: 2170 | loss: 3.585051304
step: 2180 | loss: 3.579583916
step: 2190 | loss: 3.574117884
step: 2200 | loss: 3.568653215
step: 2210 | loss: 3.563189915
step: 2220 | loss: 3.557727990
step: 2230 | loss: 3.552267446
step: 2240 | loss: 3.546808289
step: 2250 | loss: 3.541350527
step: 2260 | loss: 3.535894166
step: 2270 | loss: 3.530439212
step: 2280 | loss: 3.524985671
step: 2290 | loss: 3.519533550
step: 2300 | loss: 3.514082856
step: 2310 | loss: 3.508633596
step: 2320 | loss: 3.503185776
step: 2330 | loss: 3.497739402
step: 2340 | loss: 3.492294482
step: 2350 | loss: 3.486851023
step: 2360 | loss: 3.481409030
step: 2370 | loss: 3.475968512
step: 2380 | loss: 3.470529475
step: 2390 | loss: 3.465091926
step: 2400 | loss: 3.459655871
step: 2410 | loss: 3.454221319
step: 2420 | loss: 3.448788276
step: 2430 | loss: 3.443356749
step: 2440 | loss: 3.437926746
step: 2450 | loss: 3.432498274
step: 2460 | loss: 3.427071339
step: 2470 | loss: 3.421645949
step: 2480 | loss: 3.416222113
step: 2490 | loss: 3.410799836
step: 2500 | loss: 3.405379126
step: 2510 | loss: 3.399959992
step: 2520 | loss: 3.394542440
step: 2530 | loss: 3.389126478
step: 2540 | loss: 3.383712113
step: 2550 | loss: 3.378299354
step: 2560 | loss: 3.372888208
step: 2570 | loss: 3.367478683
step: 2580 | loss: 3.362070787
step: 2590 | loss: 3.356664526
step: 2600 | loss: 3.351259911
step: 2610 | loss: 3.345856947
step: 2620 | loss: 3.340455644
step: 2630 | loss: 3.335056010
step: 2640 | loss: 3.329658052
step: 2650 | loss: 3.324261778
step: 2660 | loss: 3.318867198
step: 2670 | loss: 3.313474318
step: 2680 | loss: 3.308083148
step: 2690 | loss: 3.302693696
step: 2700 | loss: 3.297305970
step: 2710 | loss: 3.291919979
step: 2720 | loss: 3.286535731
step: 2730 | loss: 3.281153234
step: 2740 | loss: 3.275772498
step: 2750 | loss: 3.270393531
step: 2760 | loss: 3.265016342
step: 2770 | loss: 3.259640940
step: 2780 | loss: 3.254267332
step: 2790 | loss: 3.248895529
step: 2800 | loss: 3.243525540
step: 2810 | loss: 3.238157372
step: 2820 | loss: 3.232791036
step: 2830 | loss: 3.227426540
step: 2840 | loss: 3.222063894
step: 2850 | loss: 3.216703107
step: 2860 | loss: 3.211344188
step: 2870 | loss: 3.205987146
step: 2880 | loss: 3.200631991
step: 2890 | loss: 3.195278733
step: 2900 | loss: 3.189927380
step: 2910 | loss: 3.184577943
step: 2920 | loss: 3.179230431
step: 2930 | loss: 3.173884854
step: 2940 | loss: 3.168541221
step: 2950 | loss: 3.163199543
step: 2960 | loss: 3.157859830
step: 2970 | loss: 3.152522090
step: 2980 | loss: 3.147186335
step: 2990 | loss: 3.141852575
step: 3000 | loss: 3.136520819
step: 3010 | loss: 3.131191078
step: 3020 | loss: 3.125863362
step: 3030 | loss: 3.120537681
step: 3040 | loss: 3.115214046
step: 3050 | loss: 3.109892468
step: 3060 | loss: 3.104572956
step: 3070 | loss: 3.099255522
step: 3080 | loss: 3.093940177
step: 3090 | loss: 3.088626930
step: 3100 | loss: 3.083315793
step: 3110 | loss: 3.078006776
step: 3120 | loss: 3.072699892
step: 3130 | loss: 3.067395150
step: 3140 | loss: 3.062092562
step: 3150 | loss: 3.056792139
step: 3160 | loss: 3.051493892
step: 3170 | loss: 3.046197833
step: 3180 | loss: 3.040903973
step: 3190 | loss: 3.035612323
step: 3200 | loss: 3.030322895
step: 3210 | loss: 3.025035701
step: 3220 | loss: 3.019750753
step: 3230 | loss: 3.014468061
step: 3240 | loss: 3.009187638
step: 3250 | loss: 3.003909497
step: 3260 | loss: 2.998633648
step: 3270 | loss: 2.993360105
step: 3280 | loss: 2.988088879
step: 3290 | loss: 2.982819982
step: 3300 | loss: 2.977553427
step: 3310 | loss: 2.972289226
step: 3320 | loss: 2.967027392
step: 3330 | loss: 2.961767937
step: 3340 | loss: 2.956510875
step: 3350 | loss: 2.951256217
step: 3360 | loss: 2.946003976
step: 3370 | loss: 2.940754167
step: 3380 | loss: 2.935506800
step: 3390 | loss: 2.930261890
step: 3400 | loss: 2.925019450
step: 3410 | loss: 2.919779494
step: 3420 | loss: 2.914542033
step: 3430 | loss: 2.909307082
step: 3440 | loss: 2.904074655
step: 3450 | loss: 2.898844765
step: 3460 | loss: 2.893617425
step: 3470 | loss: 2.888392650
step: 3480 | loss: 2.883170454
step: 3490 | loss: 2.877950849
step: 3500 | loss: 2.872733852
step: 3510 | loss: 2.867519475
step: 3520 | loss: 2.862307733
step: 3530 | loss: 2.857098640
step: 3540 | loss: 2.851892212
step: 3550 | loss: 2.846688461
step: 3560 | loss: 2.841487404
step: 3570 | loss: 2.836289055
step: 3580 | loss: 2.831093428
step: 3590 | loss: 2.825900539
step: 3600 | loss: 2.820710403
step: 3610 | loss: 2.815523035
step: 3620 | loss: 2.810338450
step: 3630 | loss: 2.805156664
step: 3640 | loss: 2.799977692
step: 3650 | loss: 2.794801549
step: 3660 | loss: 2.789628252
step: 3670 | loss: 2.784457816
step: 3680 | loss: 2.779290257
step: 3690 | loss: 2.774125591
step: 3700 | loss: 2.768963835
step: 3710 | loss: 2.763805004
step: 3720 | loss: 2.758649115
step: 3730 | loss: 2.753496184
step: 3740 | loss: 2.748346229
step: 3750 | loss: 2.743199264
step: 3760 | loss: 2.738055309
step: 3770 | loss: 2.732914378
step: 3780 | loss: 2.727776490
step: 3790 | loss: 2.722641662
step: 3800 | loss: 2.717509910
step: 3810 | loss: 2.712381253
step: 3820 | loss: 2.707255707
step: 3830 | loss: 2.702133291
step: 3840 | loss: 2.697014022
step: 3850 | loss: 2.691897918
step: 3860 | loss: 2.686784997
step: 3870 | loss: 2.681675277
step: 3880 | loss: 2.676568776
step: 3890 | loss: 2.671465514
step: 3900 | loss: 2.666365508
step: 3910 | loss: 2.661268776
step: 3920 | loss: 2.656175339
step: 3930 | loss: 2.651085214
step: 3940 | loss: 2.645998421
step: 3950 | loss: 2.640914979
step: 3960 | loss: 2.635834906
step: 3970 | loss: 2.630758224
step: 3980 | loss: 2.625684951
step: 3990 | loss: 2.620615106
step: 4000 | loss: 2.615548710
step: 4010 | loss: 2.610485784
step: 4020 | loss: 2.605426345
step: 4030 | loss: 2.600370416
step: 4040 | loss: 2.595318017
step: 4050 | loss: 2.590269168
step: 4060 | loss: 2.585223889
step: 4070 | loss: 2.580182202
step: 4080 | loss: 2.575144128
step: 4090 | loss: 2.570109687
step: 4100 | loss: 2.565078902
step: 4110 | loss: 2.560051793
step: 4120 | loss: 2.555028382
step: 4130 | loss: 2.550008691
step: 4140 | loss: 2.544992742
step: 4150 | loss: 2.539980556
step: 4160 | loss: 2.534972157
step: 4170 | loss: 2.529967566
step: 4180 | loss: 2.524966805
step: 4190 | loss: 2.519969899
step: 4200 | loss: 2.514976868
step: 4210 | loss: 2.509987737
step: 4220 | loss: 2.505002529
step: 4230 | loss: 2.500021266
step: 4240 | loss: 2.495043973
step: 4250 | loss: 2.490070673
step: 4260 | loss: 2.485101390
step: 4270 | loss: 2.480136147
step: 4280 | loss: 2.475174970
step: 4290 | loss: 2.470217882
step: 4300 | loss: 2.465264908
step: 4310 | loss: 2.460316073
step: 4320 | loss: 2.455371401
step: 4330 | loss: 2.450430917
step: 4340 | loss: 2.445494647
step: 4350 | loss: 2.440562617
step: 4360 | loss: 2.435634851
step: 4370 | loss: 2.430711375
step: 4380 | loss: 2.425792216
step: 4390 | loss: 2.420877400
step: 4400 | loss: 2.415966952
step: 4410 | loss: 2.411060900
step: 4420 | loss: 2.406159269
step: 4430 | loss: 2.401262088
step: 4440 | loss: 2.396369383
step: 4450 | loss: 2.391481181
step: 4460 | loss: 2.386597509
step: 4470 | loss: 2.381718396
step: 4480 | loss: 2.376843870
step: 4490 | loss: 2.371973957
step: 4500 | loss: 2.367108687
step: 4510 | loss: 2.362248088
step: 4520 | loss: 2.357392189
step: 4530 | loss: 2.352541018
step: 4540 | loss: 2.347694605
step: 4550 | loss: 2.342852979
step: 4560 | loss: 2.338016169
step: 4570 | loss: 2.333184205
step: 4580 | loss: 2.328357117
step: 4590 | loss: 2.323534936
step: 4600 | loss: 2.318717690
step: 4610 | loss: 2.313905412
step: 4620 | loss: 2.309098131
step: 4630 | loss: 2.304295879
step: 4640 | loss: 2.299498686
step: 4650 | loss: 2.294706585
step: 4660 | loss: 2.289919607
step: 4670 | loss: 2.285137784
step: 4680 | loss: 2.280361148
step: 4690 | loss: 2.275589731
step: 4700 | loss: 2.270823566
step: 4710 | loss: 2.266062685
step: 4720 | loss: 2.261307122
step: 4730 | loss: 2.256556910
step: 4740 | loss: 2.251812082
step: 4750 | loss: 2.247072672
step: 4760 | loss: 2.242338714
step: 4770 | loss: 2.237610243
step: 4780 | loss: 2.232887292
step: 4790 | loss: 2.228169896
step: 4800 | loss: 2.223458091
step: 4810 | loss: 2.218751911
step: 4820 | loss: 2.214051392
step: 4830 | loss: 2.209356570
step: 4840 | loss: 2.204667479
step: 4850 | loss: 2.199984158
step: 4860 | loss: 2.195306642
step: 4870 | loss: 2.190634967
step: 4880 | loss: 2.185969171
step: 4890 | loss: 2.181309290
step: 4900 | loss: 2.176655363
step: 4910 | loss: 2.172007427
step: 4920 | loss: 2.167365520
step: 4930 | loss: 2.162729679
step: 4940 | loss: 2.158099945
step: 4950 | loss: 2.153476355
step: 4960 | loss: 2.148858948
step: 4970 | loss: 2.144247764
step: 4980 | loss: 2.139642842
step: 4990 | loss: 2.135044222
step: 5000 | loss: 2.130451944
step: 5010 | loss: 2.125866048
step: 5020 | loss: 2.121286576
step: 5030 | loss: 2.116713568
step: 5040 | loss: 2.112147065
step: 5050 | loss: 2.107587108
step: 5060 | loss: 2.103033740
step: 5070 | loss: 2.098487002
step: 5080 | loss: 2.093946937
step: 5090 | loss: 2.089413587
step: 5100 | loss: 2.084886996
step: 5110 | loss: 2.080367205
step: 5120 | loss: 2.075854259
step: 5130 | loss: 2.071348202
step: 5140 | loss: 2.066849076
step: 5150 | loss: 2.062356927
step: 5160 | loss: 2.057871800
step: 5170 | loss: 2.053393738
step: 5180 | loss: 2.048922787
step: 5190 | loss: 2.044458992
step: 5200 | loss: 2.040002399
step: 5210 | loss: 2.035553055
step: 5220 | loss: 2.031111004
step: 5230 | loss: 2.026676294
step: 5240 | loss: 2.022248971
step: 5250 | loss: 2.017829083
step: 5260 | loss: 2.013416677
step: 5270 | loss: 2.009011800
step: 5280 | loss: 2.004614500
step: 5290 | loss: 2.000224825
step: 5300 | loss: 1.995842824
step: 5310 | loss: 1.991468546
step: 5320 | loss: 1.987102039
step: 5330 | loss: 1.982743352
step: 5340 | loss: 1.978392536
step: 5350 | loss: 1.974049639
step: 5360 | loss: 1.969714711
step: 5370 | loss: 1.965387804
step: 5380 | loss: 1.961068966
step: 5390 | loss: 1.956758249
step: 5400 | loss: 1.952455703
step: 5410 | loss: 1.948161380
step: 5420 | loss: 1.943875331
step: 5430 | loss: 1.939597606
step: 5440 | loss: 1.935328258
step: 5450 | loss: 1.931067339
step: 5460 | loss: 1.926814899
step: 5470 | loss: 1.922570991
step: 5480 | loss: 1.918335668
step: 5490 | loss: 1.914108980
step: 5500 | loss: 1.909890980
step: 5510 | loss: 1.905681720
step: 5520 | loss: 1.901481253
step: 5530 | loss: 1.897289629
step: 5540 | loss: 1.893106901
step: 5550 | loss: 1.888933121
step: 5560 | loss: 1.884768338
step: 5570 | loss: 1.880612606
step: 5580 | loss: 1.876465973
step: 5590 | loss: 1.872328489
step: 5600 | loss: 1.868200204
step: 5610 | loss: 1.864081165
step: 5620 | loss: 1.859971419
step: 5630 | loss: 1.855871012
step: 5640 | loss: 1.851779986
step: 5650 | loss: 1.847698384
step: 5660 | loss: 1.843626242
step: 5670 | loss: 1.839563596
step: 5680 | loss: 1.835510475
step: 5690 | loss: 1.831466903
step: 5700 | loss: 1.827432895
step: 5710 | loss: 1.823408454
step: 5720 | loss: 1.819393569
step: 5730 | loss: 1.815388207
step: 5740 | loss: 1.811392301
step: 5750 | loss: 1.807405736
step: 5760 | loss: 1.803428323
step: 5770 | loss: 1.799459747
step: 5780 | loss: 1.795499521
step: 5790 | loss: 1.791546969
step: 5800 | loss: 1.787601462
step: 5810 | loss: 1.783662747
step: 5820 | loss: 1.779730829
step: 5830 | loss: 1.775805748
step: 5840 | loss: 1.771887547
step: 5850 | loss: 1.767976268
step: 5860 | loss: 1.764071953
step: 5870 | loss: 1.760174646
step: 5880 | loss: 1.756284387
step: 5890 | loss: 1.752401221
step: 5900 | loss: 1.748525190
step: 5910 | loss: 1.744656336
step: 5920 | loss: 1.740794702
step: 5930 | loss: 1.736940331
step: 5940 | loss: 1.733093265
step: 5950 | loss: 1.729253548
step: 5960 | loss: 1.725421220
step: 5970 | loss: 1.721596325
step: 5980 | loss: 1.717778904
step: 5990 | loss: 1.713968999
step: 6000 | loss: 1.710166651
step: 6010 | loss: 1.706371900
step: 6020 | loss: 1.702584786
step: 6030 | loss: 1.698805349
step: 6040 | loss: 1.695033627
step: 6050 | loss: 1.691269656
step: 6060 | loss: 1.687513473
step: 6070 | loss: 1.683765112
step: 6080 | loss: 1.680024604
step: 6090 | loss: 1.676291979
step: 6100 | loss: 1.672567262
step: 6110 | loss: 1.668850478
step: 6120 | loss: 1.665141641
step: 6130 | loss: 1.661440764
step: 6140 | loss: 1.657747847
step: 6150 | loss: 1.654062882
step: 6160 | loss: 1.650385843
step: 6170 | loss: 1.646716682
step: 6180 | loss: 1.643055321
step: 6190 | loss: 1.639401631
step: 6200 | loss: 1.635755411
step: 6210 | loss: 1.632116342
step: 6220 | loss: 1.628483928
step: 6230 | loss: 1.624857452
step: 6240 | loss: 1.621236139
step: 6250 | loss: 1.617619555
step: 6260 | loss: 1.614007636
step: 6270 | loss: 1.610400403
step: 6280 | loss: 1.606797878
step: 6290 | loss: 1.603200084
step: 6300 | loss: 1.599607042
step: 6310 | loss: 1.596018774
step: 6320 | loss: 1.592435298
step: 6330 | loss: 1.588856634
step: 6340 | loss: 1.585282798
step: 6350 | loss: 1.581713804
step: 6360 | loss: 1.578149665
step: 6370 | loss: 1.574590390
step: 6380 | loss: 1.571035985
step: 6390 | loss: 1.567486450
step: 6400 | loss: 1.563941781
step: 6410 | loss: 1.560401964
step: 6420 | loss: 1.556866976
step: 6430 | loss: 1.553336779
step: 6440 | loss: 1.549811318
step: 6450 | loss: 1.546290507
step: 6460 | loss: 1.542774221
step: 6470 | loss: 1.539262274
step: 6480 | loss: 1.535754380
step: 6490 | loss: 1.532250105
step: 6500 | loss: 1.528748791
step: 6510 | loss: 1.525249586
step: 6520 | loss: 1.521751764
step: 6530 | loss: 1.518255063
step: 6540 | loss: 1.514759463
step: 6550 | loss: 1.511264972
step: 6560 | loss: 1.507771597
step: 6570 | loss: 1.504279347
step: 6580 | loss: 1.500788228
step: 6590 | loss: 1.497298249
step: 6600 | loss: 1.493809418
step: 6610 | loss: 1.490321743
step: 6620 | loss: 1.486835232
step: 6630 | loss: 1.483349892
step: 6640 | loss: 1.479865733
step: 6650 | loss: 1.476382763
step: 6660 | loss: 1.472900990
step: 6670 | loss: 1.469420423
step: 6680 | loss: 1.465941070
step: 6690 | loss: 1.462462939
step: 6700 | loss: 1.458986041
step: 6710 | loss: 1.455510382
step: 6720 | loss: 1.452035973
step: 6730 | loss: 1.448562822
step: 6740 | loss: 1.445090938
step: 6750 | loss: 1.441620330
step: 6760 | loss: 1.438151008
step: 6770 | loss: 1.434682981
step: 6780 | loss: 1.431216258
step: 6790 | loss: 1.427750849
step: 6800 | loss: 1.424286763
step: 6810 | loss: 1.420824010
step: 6820 | loss: 1.417362600
step: 6830 | loss: 1.413902542
step: 6840 | loss: 1.410443847
step: 6850 | loss: 1.406986524
step: 6860 | loss: 1.403530584
step: 6870 | loss: 1.400076036
step: 6880 | loss: 1.396622892
step: 6890 | loss: 1.393171161
step: 6900 | loss: 1.389720853
step: 6910 | loss: 1.386271981
step: 6920 | loss: 1.382824553
step: 6930 | loss: 1.379378582
step: 6940 | loss: 1.375934078
step: 6950 | loss: 1.372491051
step: 6960 | loss: 1.369049514
step: 6970 | loss: 1.365609477
step: 6980 | loss: 1.362170951
step: 6990 | loss: 1.358733949
step: 7000 | loss: 1.355298481
step: 7010 | loss: 1.351864559
step: 7020 | loss: 1.348432196
step: 7030 | loss: 1.345001402
step: 7040 | loss: 1.341572190
step: 7050 | loss: 1.338144572
step: 7060 | loss: 1.334718560
step: 7070 | loss: 1.331294167
step: 7080 | loss: 1.327871405
step: 7090 | loss: 1.324450286
step: 7100 | loss: 1.321030824
step: 7110 | loss: 1.317613031
step: 7120 | loss: 1.314196921
step: 7130 | loss: 1.310782505
step: 7140 | loss: 1.307369798
step: 7150 | loss: 1.303958813
step: 7160 | loss: 1.300549563
step: 7170 | loss: 1.297142062
step: 7180 | loss: 1.293736324
step: 7190 | loss: 1.290332363
step: 7200 | loss: 1.286930192
step: 7210 | loss: 1.283529826
step: 7220 | loss: 1.280131279
step: 7230 | loss: 1.276734565
step: 7240 | loss: 1.273339700
step: 7250 | loss: 1.269946698
step: 7260 | loss: 1.266555573
step: 7270 | loss: 1.263166342
step: 7280 | loss: 1.259779018
step: 7290 | loss: 1.256393618
step: 7300 | loss: 1.253010157
step: 7310 | loss: 1.249628651
step: 7320 | loss: 1.246249115
step: 7330 | loss: 1.242871565
step: 7340 | loss: 1.239496018
step: 7350 | loss: 1.236122490
step: 7360 | loss: 1.232750997
step: 7370 | loss: 1.229381557
step: 7380 | loss: 1.226014185
step: 7390 | loss: 1.222648899
step: 7400 | loss: 1.219285716
step: 7410 | loss: 1.215924653
step: 7420 | loss: 1.212565729
step: 7430 | loss: 1.209208960
step: 7440 | loss: 1.205854364
step: 7450 | loss: 1.202501960
step: 7460 | loss: 1.199151766
step: 7470 | loss: 1.195803800
step: 7480 | loss: 1.192458081
step: 7490 | loss: 1.189114628
step: 7500 | loss: 1.185773460
step: 7510 | loss: 1.182434596
step: 7520 | loss: 1.179098055
step: 7530 | loss: 1.175763858
step: 7540 | loss: 1.172432023
step: 7550 | loss: 1.169102572
step: 7560 | loss: 1.165775524
step: 7570 | loss: 1.162450899
step: 7580 | loss: 1.159128720
step: 7590 | loss: 1.155809005
step: 7600 | loss: 1.152491778
step: 7610 | loss: 1.149177058
step: 7620 | loss: 1.145864868
step: 7630 | loss: 1.142555230
step: 7640 | loss: 1.139248164
step: 7650 | loss: 1.135943695
step: 7660 | loss: 1.132641844
step: 7670 | loss: 1.129342634
step: 7680 | loss: 1.126046088
step: 7690 | loss: 1.122752229
step: 7700 | loss: 1.119461082
step: 7710 | loss: 1.116172669
step: 7720 | loss: 1.112887014
step: 7730 | loss: 1.109604143
step: 7740 | loss: 1.106324079
step: 7750 | loss: 1.103046847
step: 7760 | loss: 1.099772473
step: 7770 | loss: 1.096500982
step: 7780 | loss: 1.093232398
step: 7790 | loss: 1.089966750
step: 7800 | loss: 1.086704061
step: 7810 | loss: 1.083444360
step: 7820 | loss: 1.080187672
step: 7830 | loss: 1.076934025
step: 7840 | loss: 1.073683447
step: 7850 | loss: 1.070435964
step: 7860 | loss: 1.067191604
step: 7870 | loss: 1.063950397
step: 7880 | loss: 1.060712370
step: 7890 | loss: 1.057477553
step: 7900 | loss: 1.054245974
step: 7910 | loss: 1.051017663
step: 7920 | loss: 1.047792651
step: 7930 | loss: 1.044570966
step: 7940 | loss: 1.041352640
step: 7950 | loss: 1.038137704
step: 7960 | loss: 1.034926188
step: 7970 | loss: 1.031718124
step: 7980 | loss: 1.028513544
step: 7990 | loss: 1.025312481
step: 8000 | loss: 1.022114966
step: 8010 | loss: 1.018921033
step: 8020 | loss: 1.015730715
step: 8030 | loss: 1.012544045
step: 8040 | loss: 1.009361059
step: 8050 | loss: 1.006181789
step: 8060 | loss: 1.003006272
step: 8070 | loss: 0.999834541
step: 8080 | loss: 0.996666633
step: 8090 | loss: 0.993502584
step: 8100 | loss: 0.990342429
step: 8110 | loss: 0.987186207
step: 8120 | loss: 0.984033953
step: 8130 | loss: 0.980885705
step: 8140 | loss: 0.977741502
step: 8150 | loss: 0.974601382
step: 8160 | loss: 0.971465383
step: 8170 | loss: 0.968333546
step: 8180 | loss: 0.965205908
step: 8190 | loss: 0.962082511
step: 8200 | loss: 0.958963396
step: 8210 | loss: 0.955848603
step: 8220 | loss: 0.952738173
step: 8230 | loss: 0.949632149
step: 8240 | loss: 0.946530573
step: 8250 | loss: 0.943433487
step: 8260 | loss: 0.940340935
step: 8270 | loss: 0.937252961
step: 8280 | loss: 0.934169609
step: 8290 | loss: 0.931090924
step: 8300 | loss: 0.928016951
step: 8310 | loss: 0.924947734
step: 8320 | loss: 0.921883322
step: 8330 | loss: 0.918823760
step: 8340 | loss: 0.915769095
step: 8350 | loss: 0.912719375
step: 8360 | loss: 0.909674648
step: 8370 | loss: 0.906634963
step: 8380 | loss: 0.903600369
step: 8390 | loss: 0.900570916
step: 8400 | loss: 0.897546653
step: 8410 | loss: 0.894527631
step: 8420 | loss: 0.891513902
step: 8430 | loss: 0.888505518
step: 8440 | loss: 0.885502529
step: 8450 | loss: 0.882504990
step: 8460 | loss: 0.879512954
step: 8470 | loss: 0.876526473
step: 8480 | loss: 0.873545604
step: 8490 | loss: 0.870570399
step: 8500 | loss: 0.867600915
step: 8510 | loss: 0.864637207
step: 8520 | loss: 0.861679332
step: 8530 | loss: 0.858727346
step: 8540 | loss: 0.855781307
step: 8550 | loss: 0.852841272
step: 8560 | loss: 0.849907300
step: 8570 | loss: 0.846979450
step: 8580 | loss: 0.844057780
step: 8590 | loss: 0.841142350
step: 8600 | loss: 0.838233220
step: 8610 | loss: 0.835330451
step: 8620 | loss: 0.832434103
step: 8630 | loss: 0.829544237
step: 8640 | loss: 0.826660915
step: 8650 | loss: 0.823784199
step: 8660 | loss: 0.820914150
step: 8670 | loss: 0.818050831
step: 8680 | loss: 0.815194303
step: 8690 | loss: 0.812344630
step: 8700 | loss: 0.809501874
step: 8710 | loss: 0.806666097
step: 8720 | loss: 0.803837361
step: 8730 | loss: 0.801015728
step: 8740 | loss: 0.798201260
step: 8750 | loss: 0.795394018
step: 8760 | loss: 0.792594061
step: 8770 | loss: 0.789801450
step: 8780 | loss: 0.787016242
step: 8790 | loss: 0.784238494
step: 8800 | loss: 0.781468261
step: 8810 | loss: 0.778705594
step: 8820 | loss: 0.775950544
step: 8830 | loss: 0.773203157
step: 8840 | loss: 0.770463473
step: 8850 | loss: 0.767731530
step: 8860 | loss: 0.765007354
step: 8870 | loss: 0.762290967
step: 8880 | loss: 0.759582377
step: 8890 | loss: 0.756881576
step: 8900 | loss: 0.754188539
step: 8910 | loss: 0.751503212
step: 8920 | loss: 0.748825504
step: 8930 | loss: 0.746155272
step: 8940 | loss: 0.743492296
step: 8950 | loss: 0.740836238
step: 8960 | loss: 0.738186581
step: 8970 | loss: 0.735542518
step: 8980 | loss: 0.732902813
step: 8990 | loss: 0.730265751
step: 9000 | loss: 0.727629629
step: 9010 | loss: 0.724993629
step: 9020 | loss: 0.722357633
step: 9030 | loss: 0.719721638
step: 9040 | loss: 0.717085643
step: 9050 | loss: 0.714449647
step: 9060 | loss: 0.711813652
step: 9070 | loss: 0.709177657
step: 9080 | loss: 0.706541662
step: 9090 | loss: 0.703905667
step: 9100 | loss: 0.701269671
step: 9110 | loss: 0.698633676
step: 9120 | loss: 0.695997681
step: 9130 | loss: 0.693361686
step: 9140 | loss: 0.690725691
step: 9150 | loss: 0.688089696
step: 9160 | loss: 0.685453700
step: 9170 | loss: 0.682817705
step: 9180 | loss: 0.680181710
step: 9190 | loss: 0.677545715
step: 9200 | loss: 0.674909720
step: 9210 | loss: 0.672273724
step: 9220 | loss: 0.669637729
step: 9230 | loss: 0.667001734
step: 9240 | loss: 0.664365739
step: 9250 | loss: 0.661729744
step: 9260 | loss: 0.659093748
step: 9270 | loss: 0.656457753
step: 9280 | loss: 0.653821758
step: 9290 | loss: 0.651185763
step: 9300 | loss: 0.648549768
step: 9310 | loss: 0.645913773
step: 9320 | loss: 0.643277777
step: 9330 | loss: 0.640641782
step: 9340 | loss: 0.638005787
step: 9350 | loss: 0.635369792
step: 9360 | loss: 0.632733797
step: 9370 | loss: 0.630097801
step: 9380 | loss: 0.627461806
step: 9390 | loss: 0.624825811
step: 9400 | loss: 0.622189816
step: 9410 | loss: 0.619553821
step: 9420 | loss: 0.616917826
step: 9430 | loss: 0.614281830
step: 9440 | loss: 0.611645835
step: 9450 | loss: 0.609009840
step: 9460 | loss: 0.606373845
step: 9470 | loss: 0.603737850
step: 9480 | loss: 0.601101854
step: 9490 | loss: 0.598465859
step: 9500 | loss: 0.595829864
step: 9510 | loss: 0.593193869
step: 9520 | loss: 0.590557874
step: 9530 | loss: 0.587921879
step: 9540 | loss: 0.585285883
step: 9550 | loss: 0.582649888
step: 9560 | loss: 0.580013893
step: 9570 | loss: 0.577377898
step: 9580 | loss: 0.574741903
step: 9590 | loss: 0.572105907
step: 9600 | loss: 0.569469912
step: 9610 | loss: 0.566833917
step: 9620 | loss: 0.564197922
step: 9630 | loss: 0.561561927
step: 9640 | loss: 0.558925931
step: 9650 | loss: 0.556289936
step: 9660 | loss: 0.553653941
step: 9670 | loss: 0.551017946
step: 9680 | loss: 0.548381951
step: 9690 | loss: 0.545745956
step: 9700 | loss: 0.543109960
step: 9710 | loss: 0.540473965
step: 9720 | loss: 0.537837970
step: 9730 | loss: 0.535201975
step: 9740 | loss: 0.532565980
step: 9750 | loss: 0.529929984
step: 9760 | loss: 0.527293989
step: 9770 | loss: 0.524657994
step: 9780 | loss: 0.522021999
step: 9790 | loss: 0.519386004
step: 9800 | loss: 0.516750009
step: 9810 | loss: 0.514114013
step: 9820 | loss: 0.511478018
step: 9830 | loss: 0.508842023
step: 9840 | loss: 0.506206028
step: 9850 | loss: 0.503570033
step: 9860 | loss: 0.500934037
step: 9870 | loss: 0.498298042
step: 9880 | loss: 0.495662047
step: 9890 | loss: 0.493026052
step: 9900 | loss: 0.490390057
step: 9910 | loss: 0.487754062
step: 9920 | loss: 0.485118066
step: 9930 | loss: 0.482482071
step: 9940 | loss: 0.479846076
step: 9950 | loss: 0.477210081
step: 9960 | loss: 0.474574086
step: 9970 | loss: 0.471938090
step: 9980 | loss: 0.469302095
step: 9990 | loss: 0.466666100
step: 10000 | loss: 0.464030105
step: 10010 | loss: 0.461394110
step: 10020 | loss: 0.458758114
step: 10030 | loss: 0.456122119
step: 10040 | loss: 0.453486124
step: 10050 | loss: 0.450850129
step: 10060 | loss: 0.448214134
step: 10070 | loss: 0.445578139
step: 10080 | loss: 0.442942143
step: 10090 | loss: 0.440306148
step: 10100 | loss: 0.437670153
step: 10110 | loss: 0.435034158
step: 10120 | loss: 0.432398163
step: 10130 | loss: 0.429762167
step: 10140 | loss: 0.427126172
step: 10150 | loss: 0.424490177
step: 10160 | loss: 0.421854182
step: 10170 | loss: 0.419218187
step: 10180 | loss: 0.416582192
step: 10190 | loss: 0.413946196
step: 10200 | loss: 0.411310201
step: 10210 | loss: 0.408674206
step: 10220 | loss: 0.406038211
step: 10230 | loss: 0.403402216
step: 10240 | loss: 0.400766220
step: 10250 | loss: 0.398130225
step: 10260 | loss: 0.395494230
step: 10270 | loss: 0.392858235
step: 10280 | loss: 0.390222240
step: 10290 | loss: 0.387586244
step: 10300 | loss: 0.384950249
step: 10310 | loss: 0.382314254
step: 10320 | loss: 0.379678259
step: 10330 | loss: 0.377042264
step: 10340 | loss: 0.374406269
step: 10350 | loss: 0.371770273
step: 10360 | loss: 0.369134278
step: 10370 | loss: 0.366498283
step: 10380 | loss: 0.363862288
step: 10390 | loss: 0.361226293
step: 10400 | loss: 0.358590297
step: 10410 | loss: 0.355954302
step: 10420 | loss: 0.353318307
step: 10430 | loss: 0.350682312
step: 10440 | loss: 0.348046317
step: 10450 | loss: 0.345410322
step: 10460 | loss: 0.342774326
step: 10470 | loss: 0.340138331
step: 10480 | loss: 0.337502336
step: 10490 | loss: 0.334866341
step: 10500 | loss: 0.332230346
step: 10510 | loss: 0.329594350
step: 10520 | loss: 0.326958355
step: 10530 | loss: 0.324322360
step: 10540 | loss: 0.321686365
step: 10550 | loss: 0.319050370
step: 10560 | loss: 0.316414375
step: 10570 | loss: 0.313778379
step: 10580 | loss: 0.311142384
step: 10590 | loss: 0.308506389
step: 10600 | loss: 0.305870394
step: 10610 | loss: 0.303234399
step: 10620 | loss: 0.300598403
step: 10630 | loss: 0.297962408
step: 10640 | loss: 0.295326413
step: 10650 | loss: 0.292690418
step: 10660 | loss: 0.290054423
step: 10670 | loss: 0.287418427
step: 10680 | loss: 0.284782432
step: 10690 | loss: 0.282146437
step: 10700 | loss: 0.279510442
step: 10710 | loss: 0.276874447
step: 10720 | loss: 0.274238452
step: 10730 | loss: 0.271602456
step: 10740 | loss: 0.268966461
step: 10750 | loss: 0.266330466
step: 10760 | loss: 0.263694471
step: 10770 | loss: 0.261058476
step: 10780 | loss: 0.258422480
step: 10790 | loss: 0.255786485
step: 10800 | loss: 0.253150490
step: 10810 | loss: 0.250514495
step: 10820 | loss: 0.247878500
step: 10830 | loss: 0.245242505
step: 10840 | loss: 0.242606509
step: 10850 | loss: 0.239970514
step: 10860 | loss: 0.237334519
step: 10870 | loss: 0.234698524
step: 10880 | loss: 0.232062529
step: 10890 | loss: 0.229426533
step: 10900 | loss: 0.226790538
step: 10910 | loss: 0.224154543
step: 10920 | loss: 0.221518548
step: 10930 | loss: 0.218882553
step: 10940 | loss: 0.216246558
step: 10950 | loss: 0.213610562
step: 10960 | loss: 0.210974567
step: 10970 | loss: 0.208338572
step: 10980 | loss: 0.205702577
step: 10990 | loss: 0.203066582
step: 11000 | loss: 0.200430586
step: 11010 | loss: 0.197794591
step: 11020 | loss: 0.195158596
step: 11030 | loss: 0.192522601
step: 11040 | loss: 0.189886606
step: 11050 | loss: 0.187250610
step: 11060 | loss: 0.184614615
step: 11070 | loss: 0.181978620
step: 11080 | loss: 0.179342625
step: 11090 | loss: 0.176706630
step: 11100 | loss: 0.174070635
step: 11110 | loss: 0.171434639
step: 11120 | loss: 0.168798644
step: 11130 | loss: 0.166162649
step: 11140 | loss: 0.163526654
step: 11150 | loss: 0.160890659
step: 11160 | loss: 0.158254663
step: 11170 | loss: 0.155618668
step: 11180 | loss: 0.152982673
step: 11190 | loss: 0.150346678
step: 11200 | loss: 0.147710683
step: 11210 | loss: 0.145074688
step: 11220 | loss: 0.142438692
step: 11230 | loss: 0.139802697
step: 11240 | loss: 0.137166702
step: 11250 | loss: 0.134530707
step: 11260 | loss: 0.131894712
step: 11270 | loss: 0.129258716
step: 11280 | loss: 0.126622721
step: 11290 | loss: 0.123986726
step: 11300 | loss: 0.121350731
step: 11310 | loss: 0.118714736
step: 11320 | loss: 0.116078741
step: 11330 | loss: 0.113442745
step: 11340 | loss: 0.110806750
step: 11350 | loss: 0.108170755
step: 11360 | loss: 0.105534760
step: 11370 | loss: 0.102898765
step: 11380 | loss: 0.100262769
step: 11390 | loss: 0.097626774
step: 11400 | loss: 0.094990779
step: 11410 | loss: 0.092354784
step: 11420 | loss: 0.089718789
step: 11430 | loss: 0.087082793
step: 11440 | loss: 0.084446798
step: 11450 | loss: 0.081810803
step: 11460 | loss: 0.079174808
step: 11470 | loss: 0.076538813
step: 11480 | loss: 0.073902818
step: 11490 | loss: 0.071266822
step: 11500 | loss: 0.068630827
step: 11510 | loss: 0.065994832
step: 11520 | loss: 0.063358837
step: 11530 | loss: 0.060722842
step: 11540 | loss: 0.058086846
step: 11550 | loss: 0.055450851
step: 11560 | loss: 0.052814856
step: 11570 | loss: 0.050178861
step: 11580 | loss: 0.047542866
step: 11590 | loss: 0.044906871
step: 11600 | loss: 0.042270875
step: 11610 | loss: 0.039634880
step: 11620 | loss: 0.036998885
step: 11630 | loss: 0.034362890
step: 11640 | loss: 0.031726895
step: 11650 | loss: 0.029090899
step: 11660 | loss: 0.026454904
step: 11670 | loss: 0.023818909
step: 11680 | loss: 0.021182914
step: 11690 | loss: 0.018546919
step: 11700 | loss: 0.015910924
step: 11710 | loss: 0.013274928
step: 11720 | loss: 0.010638933
step: 11730 | loss: 0.008002938
step: 11740 | loss: 0.005366943
step: 11750 | loss: 0.002730948
- final loss: 0.000886
- (cd _build/default/examples/opt && ./adam.exe)
- 
step: 0 | loss: 6.726415252
step: 10 | loss: 6.720622791
step: 20 | loss: 6.714192641
step: 30 | loss: 6.707769373
step: 40 | loss: 6.701353395
step: 50 | loss: 6.694944874
step: 60 | loss: 6.688543820
step: 70 | loss: 6.682150156
step: 80 | loss: 6.675763756
step: 90 | loss: 6.669384478
step: 100 | loss: 6.663012170
step: 110 | loss: 6.656646678
step: 120 | loss: 6.650287847
step: 130 | loss: 6.643935524
step: 140 | loss: 6.637589559
step: 150 | loss: 6.631249807
step: 160 | loss: 6.624916123
step: 170 | loss: 6.618588370
step: 180 | loss: 6.612266414
step: 190 | loss: 6.605950129
step: 200 | loss: 6.599639392
step: 210 | loss: 6.593334090
step: 220 | loss: 6.587034112
step: 230 | loss: 6.580739358
step: 240 | loss: 6.574449733
step: 250 | loss: 6.568165148
step: 260 | loss: 6.561885522
step: 270 | loss: 6.555610782
step: 280 | loss: 6.549340857
step: 290 | loss: 6.543075686
step: 300 | loss: 6.536815213
step: 310 | loss: 6.530559385
step: 320 | loss: 6.524308158
step: 330 | loss: 6.518061488
step: 340 | loss: 6.511819338
step: 350 | loss: 6.505581675
step: 360 | loss: 6.499348466
step: 370 | loss: 6.493119686
step: 380 | loss: 6.486895307
step: 390 | loss: 6.480675308
step: 400 | loss: 6.474459667
step: 410 | loss: 6.468248365
step: 420 | loss: 6.462041382
step: 430 | loss: 6.455838703
step: 440 | loss: 6.449640311
step: 450 | loss: 6.443446192
step: 460 | loss: 6.437256329
step: 470 | loss: 6.431070710
step: 480 | loss: 6.424889320
step: 490 | loss: 6.418712146
step: 500 | loss: 6.412539176
step: 510 | loss: 6.406370395
step: 520 | loss: 6.400205792
step: 530 | loss: 6.394045354
step: 540 | loss: 6.387889067
step: 550 | loss: 6.381736921
step: 560 | loss: 6.375588901
step: 570 | loss: 6.369444996
step: 580 | loss: 6.363305193
step: 590 | loss: 6.357169480
step: 600 | loss: 6.351037844
step: 610 | loss: 6.344910273
step: 620 | loss: 6.338786754
step: 630 | loss: 6.332667275
step: 640 | loss: 6.326551822
step: 650 | loss: 6.320440384
step: 660 | loss: 6.314332947
step: 670 | loss: 6.308229499
step: 680 | loss: 6.302130027
step: 690 | loss: 6.296034518
step: 700 | loss: 6.289942960
step: 710 | loss: 6.283855339
step: 720 | loss: 6.277771643
step: 730 | loss: 6.271691858
step: 740 | loss: 6.265615972
step: 750 | loss: 6.259543971
step: 760 | loss: 6.253475842
step: 770 | loss: 6.247411572
step: 780 | loss: 6.241351149
step: 790 | loss: 6.235294557
step: 800 | loss: 6.229241785
step: 810 | loss: 6.223192819
step: 820 | loss: 6.217147645
step: 830 | loss: 6.211106250
step: 840 | loss: 6.205068621
step: 850 | loss: 6.199034743
step: 860 | loss: 6.193004604
step: 870 | loss: 6.186978189
step: 880 | loss: 6.180955485
step: 890 | loss: 6.174936478
step: 900 | loss: 6.168921154
step: 910 | loss: 6.162909499
step: 920 | loss: 6.156901500
step: 930 | loss: 6.150897142
step: 940 | loss: 6.144896412
step: 950 | loss: 6.138899294
step: 960 | loss: 6.132905776
step: 970 | loss: 6.126915843
step: 980 | loss: 6.120929480
step: 990 | loss: 6.114946673
step: 1000 | loss: 6.108967409
step: 1010 | loss: 6.102991672
step: 1020 | loss: 6.097019448
step: 1030 | loss: 6.091050722
step: 1040 | loss: 6.085085481
step: 1050 | loss: 6.079123709
step: 1060 | loss: 6.073165391
step: 1070 | loss: 6.067210513
step: 1080 | loss: 6.061259061
step: 1090 | loss: 6.055311018
step: 1100 | loss: 6.049366371
step: 1110 | loss: 6.043425104
step: 1120 | loss: 6.037487203
step: 1130 | loss: 6.031552651
step: 1140 | loss: 6.025621435
step: 1150 | loss: 6.019693539
step: 1160 | loss: 6.013768947
step: 1170 | loss: 6.007847645
step: 1180 | loss: 6.001929617
step: 1190 | loss: 5.996014847
step: 1200 | loss: 5.990103321
step: 1210 | loss: 5.984195023
step: 1220 | loss: 5.978289936
step: 1230 | loss: 5.972388046
step: 1240 | loss: 5.966489337
step: 1250 | loss: 5.960593793
step: 1260 | loss: 5.954701399
step: 1270 | loss: 5.948812138
step: 1280 | loss: 5.942925995
step: 1290 | loss: 5.937042953
step: 1300 | loss: 5.931162997
step: 1310 | loss: 5.925286111
step: 1320 | loss: 5.919412279
step: 1330 | loss: 5.913541484
step: 1340 | loss: 5.907673711
step: 1350 | loss: 5.901808943
step: 1360 | loss: 5.895947163
step: 1370 | loss: 5.890088357
step: 1380 | loss: 5.884232506
step: 1390 | loss: 5.878379595
step: 1400 | loss: 5.872529608
step: 1410 | loss: 5.866682527
step: 1420 | loss: 5.860838337
step: 1430 | loss: 5.854997021
step: 1440 | loss: 5.849158561
step: 1450 | loss: 5.843322942
step: 1460 | loss: 5.837490147
step: 1470 | loss: 5.831660158
step: 1480 | loss: 5.825832960
step: 1490 | loss: 5.820008534
step: 1500 | loss: 5.814186866
step: 1510 | loss: 5.808367936
step: 1520 | loss: 5.802551730
step: 1530 | loss: 5.796738229
step: 1540 | loss: 5.790927416
step: 1550 | loss: 5.785119275
step: 1560 | loss: 5.779313788
step: 1570 | loss: 5.773510939
step: 1580 | loss: 5.767710709
step: 1590 | loss: 5.761913083
step: 1600 | loss: 5.756118042
step: 1610 | loss: 5.750325570
step: 1620 | loss: 5.744535649
step: 1630 | loss: 5.738748262
step: 1640 | loss: 5.732963391
step: 1650 | loss: 5.727181020
step: 1660 | loss: 5.721401131
step: 1670 | loss: 5.715623707
step: 1680 | loss: 5.709848729
step: 1690 | loss: 5.704076181
step: 1700 | loss: 5.698306046
step: 1710 | loss: 5.692538306
step: 1720 | loss: 5.686772943
step: 1730 | loss: 5.681009940
step: 1740 | loss: 5.675249279
step: 1750 | loss: 5.669490944
step: 1760 | loss: 5.663734915
step: 1770 | loss: 5.657981177
step: 1780 | loss: 5.652229712
step: 1790 | loss: 5.646480501
step: 1800 | loss: 5.640733528
step: 1810 | loss: 5.634988774
step: 1820 | loss: 5.629246223
step: 1830 | loss: 5.623505857
step: 1840 | loss: 5.617767658
step: 1850 | loss: 5.612031609
step: 1860 | loss: 5.606297693
step: 1870 | loss: 5.600565891
step: 1880 | loss: 5.594836187
step: 1890 | loss: 5.589108562
step: 1900 | loss: 5.583383000
step: 1910 | loss: 5.577659483
step: 1920 | loss: 5.571937994
step: 1930 | loss: 5.566218514
step: 1940 | loss: 5.560501028
step: 1950 | loss: 5.554785517
step: 1960 | loss: 5.549071963
step: 1970 | loss: 5.543360351
step: 1980 | loss: 5.537650662
step: 1990 | loss: 5.531942879
step: 2000 | loss: 5.526236985
step: 2010 | loss: 5.520532963
step: 2020 | loss: 5.514830795
step: 2030 | loss: 5.509130465
step: 2040 | loss: 5.503431955
step: 2050 | loss: 5.497735248
step: 2060 | loss: 5.492040328
step: 2070 | loss: 5.486347177
step: 2080 | loss: 5.480655778
step: 2090 | loss: 5.474966114
step: 2100 | loss: 5.469278169
step: 2110 | loss: 5.463591925
step: 2120 | loss: 5.457907367
step: 2130 | loss: 5.452224477
step: 2140 | loss: 5.446543238
step: 2150 | loss: 5.440863634
step: 2160 | loss: 5.435185649
step: 2170 | loss: 5.429509266
step: 2180 | loss: 5.423834468
step: 2190 | loss: 5.418161240
step: 2200 | loss: 5.412489564
step: 2210 | loss: 5.406819425
step: 2220 | loss: 5.401150806
step: 2230 | loss: 5.395483692
step: 2240 | loss: 5.389818066
step: 2250 | loss: 5.384153912
step: 2260 | loss: 5.378491214
step: 2270 | loss: 5.372829957
step: 2280 | loss: 5.367170125
step: 2290 | loss: 5.361511702
step: 2300 | loss: 5.355854672
step: 2310 | loss: 5.350199020
step: 2320 | loss: 5.344544730
step: 2330 | loss: 5.338891788
step: 2340 | loss: 5.333240177
step: 2350 | loss: 5.327589882
step: 2360 | loss: 5.321940889
step: 2370 | loss: 5.316293182
step: 2380 | loss: 5.310646747
step: 2390 | loss: 5.305001567
step: 2400 | loss: 5.299357629
step: 2410 | loss: 5.293714918
step: 2420 | loss: 5.288073419
step: 2430 | loss: 5.282433118
step: 2440 | loss: 5.276794000
step: 2450 | loss: 5.271156050
step: 2460 | loss: 5.265519255
step: 2470 | loss: 5.259883600
step: 2480 | loss: 5.254249072
step: 2490 | loss: 5.248615655
step: 2500 | loss: 5.242983337
step: 2510 | loss: 5.237352103
step: 2520 | loss: 5.231721940
step: 2530 | loss: 5.226092833
step: 2540 | loss: 5.220464771
step: 2550 | loss: 5.214837738
step: 2560 | loss: 5.209211722
step: 2570 | loss: 5.203586709
step: 2580 | loss: 5.197962687
step: 2590 | loss: 5.192339641
step: 2600 | loss: 5.186717560
step: 2610 | loss: 5.181096431
step: 2620 | loss: 5.175476240
step: 2630 | loss: 5.169856975
step: 2640 | loss: 5.164238623
step: 2650 | loss: 5.158621172
step: 2660 | loss: 5.153004610
step: 2670 | loss: 5.147388924
step: 2680 | loss: 5.141774102
step: 2690 | loss: 5.136160132
step: 2700 | loss: 5.130547002
step: 2710 | loss: 5.124934701
step: 2720 | loss: 5.119323216
step: 2730 | loss: 5.113712535
step: 2740 | loss: 5.108102648
step: 2750 | loss: 5.102493542
step: 2760 | loss: 5.096885207
step: 2770 | loss: 5.091277631
step: 2780 | loss: 5.085670803
step: 2790 | loss: 5.080064711
step: 2800 | loss: 5.074459346
step: 2810 | loss: 5.068854695
step: 2820 | loss: 5.063250749
step: 2830 | loss: 5.057647496
step: 2840 | loss: 5.052044926
step: 2850 | loss: 5.046443028
step: 2860 | loss: 5.040841793
step: 2870 | loss: 5.035241210
step: 2880 | loss: 5.029641268
step: 2890 | loss: 5.024041958
step: 2900 | loss: 5.018443269
step: 2910 | loss: 5.012845193
step: 2920 | loss: 5.007247718
step: 2930 | loss: 5.001650836
step: 2940 | loss: 4.996054536
step: 2950 | loss: 4.990458809
step: 2960 | loss: 4.984863647
step: 2970 | loss: 4.979269039
step: 2980 | loss: 4.973674976
step: 2990 | loss: 4.968081449
step: 3000 | loss: 4.962488450
step: 3010 | loss: 4.956895969
step: 3020 | loss: 4.951303998
step: 3030 | loss: 4.945712528
step: 3040 | loss: 4.940121549
step: 3050 | loss: 4.934531055
step: 3060 | loss: 4.928941036
step: 3070 | loss: 4.923351484
step: 3080 | loss: 4.917762390
step: 3090 | loss: 4.912173748
step: 3100 | loss: 4.906585548
step: 3110 | loss: 4.900997782
step: 3120 | loss: 4.895410443
step: 3130 | loss: 4.889823524
step: 3140 | loss: 4.884237015
step: 3150 | loss: 4.878650911
step: 3160 | loss: 4.873065202
step: 3170 | loss: 4.867479883
step: 3180 | loss: 4.861894946
step: 3190 | loss: 4.856310382
step: 3200 | loss: 4.850726187
step: 3210 | loss: 4.845142351
step: 3220 | loss: 4.839558869
step: 3230 | loss: 4.833975734
step: 3240 | loss: 4.828392938
step: 3250 | loss: 4.822810476
step: 3260 | loss: 4.817228340
step: 3270 | loss: 4.811646525
step: 3280 | loss: 4.806065023
step: 3290 | loss: 4.800483829
step: 3300 | loss: 4.794902936
step: 3310 | loss: 4.789322339
step: 3320 | loss: 4.783742031
step: 3330 | loss: 4.778162006
step: 3340 | loss: 4.772582258
step: 3350 | loss: 4.767002783
step: 3360 | loss: 4.761423573
step: 3370 | loss: 4.755844624
step: 3380 | loss: 4.750265930
step: 3390 | loss: 4.744687486
step: 3400 | loss: 4.739109285
step: 3410 | loss: 4.733531324
step: 3420 | loss: 4.727953597
step: 3430 | loss: 4.722376099
step: 3440 | loss: 4.716798825
step: 3450 | loss: 4.711221769
step: 3460 | loss: 4.705644928
step: 3470 | loss: 4.700068297
step: 3480 | loss: 4.694491870
step: 3490 | loss: 4.688915643
step: 3500 | loss: 4.683339613
step: 3510 | loss: 4.677763774
step: 3520 | loss: 4.672188122
step: 3530 | loss: 4.666612653
step: 3540 | loss: 4.661037362
step: 3550 | loss: 4.655462247
step: 3560 | loss: 4.649887302
step: 3570 | loss: 4.644312524
step: 3580 | loss: 4.638737908
step: 3590 | loss: 4.633163452
step: 3600 | loss: 4.627589152
step: 3610 | loss: 4.622015003
step: 3620 | loss: 4.616441002
step: 3630 | loss: 4.610867147
step: 3640 | loss: 4.605293433
step: 3650 | loss: 4.599719857
step: 3660 | loss: 4.594146416
step: 3670 | loss: 4.588573106
step: 3680 | loss: 4.582999926
step: 3690 | loss: 4.577426870
step: 3700 | loss: 4.571853938
step: 3710 | loss: 4.566281125
step: 3720 | loss: 4.560708429
step: 3730 | loss: 4.555135847
step: 3740 | loss: 4.549563376
step: 3750 | loss: 4.543991014
step: 3760 | loss: 4.538418759
step: 3770 | loss: 4.532846607
step: 3780 | loss: 4.527274556
step: 3790 | loss: 4.521702603
step: 3800 | loss: 4.516130748
step: 3810 | loss: 4.510558986
step: 3820 | loss: 4.504987316
step: 3830 | loss: 4.499415736
step: 3840 | loss: 4.493844244
step: 3850 | loss: 4.488272837
step: 3860 | loss: 4.482701514
step: 3870 | loss: 4.477130273
step: 3880 | loss: 4.471559111
step: 3890 | loss: 4.465988027
step: 3900 | loss: 4.460417020
step: 3910 | loss: 4.454846086
step: 3920 | loss: 4.449275225
step: 3930 | loss: 4.443704436
step: 3940 | loss: 4.438133715
step: 3950 | loss: 4.432563063
step: 3960 | loss: 4.426992477
step: 3970 | loss: 4.421421955
step: 3980 | loss: 4.415851497
step: 3990 | loss: 4.410281101
step: 4000 | loss: 4.404710766
step: 4010 | loss: 4.399140490
step: 4020 | loss: 4.393570272
step: 4030 | loss: 4.388000111
step: 4040 | loss: 4.382430006
step: 4050 | loss: 4.376859955
step: 4060 | loss: 4.371289958
step: 4070 | loss: 4.365720013
step: 4080 | loss: 4.360150119
step: 4090 | loss: 4.354580275
step: 4100 | loss: 4.349010480
step: 4110 | loss: 4.343440734
step: 4120 | loss: 4.337871035
step: 4130 | loss: 4.332301382
step: 4140 | loss: 4.326731775
step: 4150 | loss: 4.321162213
step: 4160 | loss: 4.315592695
step: 4170 | loss: 4.310023219
step: 4180 | loss: 4.304453786
step: 4190 | loss: 4.298884394
step: 4200 | loss: 4.293315044
step: 4210 | loss: 4.287745733
step: 4220 | loss: 4.282176462
step: 4230 | loss: 4.276607230
step: 4240 | loss: 4.271038035
step: 4250 | loss: 4.265468879
step: 4260 | loss: 4.259899759
step: 4270 | loss: 4.254330676
step: 4280 | loss: 4.248761628
step: 4290 | loss: 4.243192616
step: 4300 | loss: 4.237623638
step: 4310 | loss: 4.232054695
step: 4320 | loss: 4.226485786
step: 4330 | loss: 4.220916910
step: 4340 | loss: 4.215348066
step: 4350 | loss: 4.209779255
step: 4360 | loss: 4.204210476
step: 4370 | loss: 4.198641729
step: 4380 | loss: 4.193073013
step: 4390 | loss: 4.187504327
step: 4400 | loss: 4.181935672
step: 4410 | loss: 4.176367047
step: 4420 | loss: 4.170798451
step: 4430 | loss: 4.165229885
step: 4440 | loss: 4.159661348
step: 4450 | loss: 4.154092839
step: 4460 | loss: 4.148524359
step: 4470 | loss: 4.142955906
step: 4480 | loss: 4.137387482
step: 4490 | loss: 4.131819084
step: 4500 | loss: 4.126250714
step: 4510 | loss: 4.120682371
step: 4520 | loss: 4.115114054
step: 4530 | loss: 4.109545764
step: 4540 | loss: 4.103977500
step: 4550 | loss: 4.098409261
step: 4560 | loss: 4.092841048
step: 4570 | loss: 4.087272861
step: 4580 | loss: 4.081704699
step: 4590 | loss: 4.076136561
step: 4600 | loss: 4.070568449
step: 4610 | loss: 4.065000360
step: 4620 | loss: 4.059432296
step: 4630 | loss: 4.053864257
step: 4640 | loss: 4.048296241
step: 4650 | loss: 4.042728248
step: 4660 | loss: 4.037160280
step: 4670 | loss: 4.031592334
step: 4680 | loss: 4.026024412
step: 4690 | loss: 4.020456513
step: 4700 | loss: 4.014888636
step: 4710 | loss: 4.009320782
step: 4720 | loss: 4.003752951
step: 4730 | loss: 3.998185142
step: 4740 | loss: 3.992617355
step: 4750 | loss: 3.987049590
step: 4760 | loss: 3.981481847
step: 4770 | loss: 3.975914126
step: 4780 | loss: 3.970346426
step: 4790 | loss: 3.964778748
step: 4800 | loss: 3.959211091
step: 4810 | loss: 3.953643455
step: 4820 | loss: 3.948075841
step: 4830 | loss: 3.942508247
step: 4840 | loss: 3.936940673
step: 4850 | loss: 3.931373121
step: 4860 | loss: 3.925805589
step: 4870 | loss: 3.920238077
step: 4880 | loss: 3.914670586
step: 4890 | loss: 3.909103115
step: 4900 | loss: 3.903535664
step: 4910 | loss: 3.897968233
step: 4920 | loss: 3.892400821
step: 4930 | loss: 3.886833429
step: 4940 | loss: 3.881266057
step: 4950 | loss: 3.875698705
step: 4960 | loss: 3.870131372
step: 4970 | loss: 3.864564058
step: 4980 | loss: 3.858996763
step: 4990 | loss: 3.853429487
step: 5000 | loss: 3.847862231
step: 5010 | loss: 3.842294993
step: 5020 | loss: 3.836727774
step: 5030 | loss: 3.831160574
step: 5040 | loss: 3.825593392
step: 5050 | loss: 3.820026229
step: 5060 | loss: 3.814459084
step: 5070 | loss: 3.808891958
step: 5080 | loss: 3.803324850
step: 5090 | loss: 3.797757760
step: 5100 | loss: 3.792190688
step: 5110 | loss: 3.786623634
step: 5120 | loss: 3.781056598
step: 5130 | loss: 3.775489580
step: 5140 | loss: 3.769922580
step: 5150 | loss: 3.764355597
step: 5160 | loss: 3.758788633
step: 5170 | loss: 3.753221685
step: 5180 | loss: 3.747654755
step: 5190 | loss: 3.742087843
step: 5200 | loss: 3.736520948
step: 5210 | loss: 3.730954070
step: 5220 | loss: 3.725387209
step: 5230 | loss: 3.719820366
step: 5240 | loss: 3.714253540
step: 5250 | loss: 3.708686730
step: 5260 | loss: 3.703119938
step: 5270 | loss: 3.697553162
step: 5280 | loss: 3.691986404
step: 5290 | loss: 3.686419662
step: 5300 | loss: 3.680852937
step: 5310 | loss: 3.675286228
step: 5320 | loss: 3.669719536
step: 5330 | loss: 3.664152861
step: 5340 | loss: 3.658586202
step: 5350 | loss: 3.653019559
step: 5360 | loss: 3.647452933
step: 5370 | loss: 3.641886324
step: 5380 | loss: 3.636319730
step: 5390 | loss: 3.630753153
step: 5400 | loss: 3.625186592
step: 5410 | loss: 3.619620047
step: 5420 | loss: 3.614053519
step: 5430 | loss: 3.608487006
step: 5440 | loss: 3.602920509
step: 5450 | loss: 3.597354029
step: 5460 | loss: 3.591787564
step: 5470 | loss: 3.586221115
step: 5480 | loss: 3.580654682
step: 5490 | loss: 3.575088265
step: 5500 | loss: 3.569521864
step: 5510 | loss: 3.563955478
step: 5520 | loss: 3.558389108
step: 5530 | loss: 3.552822754
step: 5540 | loss: 3.547256416
step: 5550 | loss: 3.541690093
step: 5560 | loss: 3.536123785
step: 5570 | loss: 3.530557494
step: 5580 | loss: 3.524991217
step: 5590 | loss: 3.519424956
step: 5600 | loss: 3.513858711
step: 5610 | loss: 3.508292481
step: 5620 | loss: 3.502726267
step: 5630 | loss: 3.497160068
step: 5640 | loss: 3.491593884
step: 5650 | loss: 3.486027716
step: 5660 | loss: 3.480461563
step: 5670 | loss: 3.474895425
step: 5680 | loss: 3.469329302
step: 5690 | loss: 3.463763195
step: 5700 | loss: 3.458197103
step: 5710 | loss: 3.452631026
step: 5720 | loss: 3.447064965
step: 5730 | loss: 3.441498918
step: 5740 | loss: 3.435932887
step: 5750 | loss: 3.430366871
step: 5760 | loss: 3.424800870
step: 5770 | loss: 3.419234884
step: 5780 | loss: 3.413668913
step: 5790 | loss: 3.408102958
step: 5800 | loss: 3.402537017
step: 5810 | loss: 3.396971092
step: 5820 | loss: 3.391405182
step: 5830 | loss: 3.385839286
step: 5840 | loss: 3.380273406
step: 5850 | loss: 3.374707541
step: 5860 | loss: 3.369141691
step: 5870 | loss: 3.363575856
step: 5880 | loss: 3.358010036
step: 5890 | loss: 3.352444231
step: 5900 | loss: 3.346878441
step: 5910 | loss: 3.341312666
step: 5920 | loss: 3.335746906
step: 5930 | loss: 3.330181161
step: 5940 | loss: 3.324615431
step: 5950 | loss: 3.319049716
step: 5960 | loss: 3.313484017
step: 5970 | loss: 3.307918332
step: 5980 | loss: 3.302352662
step: 5990 | loss: 3.296787007
step: 6000 | loss: 3.291221368
step: 6010 | loss: 3.285655743
step: 6020 | loss: 3.280090134
step: 6030 | loss: 3.274524539
step: 6040 | loss: 3.268958960
step: 6050 | loss: 3.263393396
step: 6060 | loss: 3.257827847
step: 6070 | loss: 3.252262312
step: 6080 | loss: 3.246696793
step: 6090 | loss: 3.241131290
step: 6100 | loss: 3.235565801
step: 6110 | loss: 3.230000327
step: 6120 | loss: 3.224434869
step: 6130 | loss: 3.218869426
step: 6140 | loss: 3.213303998
step: 6150 | loss: 3.207738585
step: 6160 | loss: 3.202173188
step: 6170 | loss: 3.196607805
step: 6180 | loss: 3.191042438
step: 6190 | loss: 3.185477086
step: 6200 | loss: 3.179911750
step: 6210 | loss: 3.174346429
step: 6220 | loss: 3.168781123
step: 6230 | loss: 3.163215833
step: 6240 | loss: 3.157650558
step: 6250 | loss: 3.152085298
step: 6260 | loss: 3.146520054
step: 6270 | loss: 3.140954825
step: 6280 | loss: 3.135389612
step: 6290 | loss: 3.129824414
step: 6300 | loss: 3.124259232
step: 6310 | loss: 3.118694066
step: 6320 | loss: 3.113128915
step: 6330 | loss: 3.107563779
step: 6340 | loss: 3.101998660
step: 6350 | loss: 3.096433556
step: 6360 | loss: 3.090868468
step: 6370 | loss: 3.085303395
step: 6380 | loss: 3.079738338
step: 6390 | loss: 3.074173297
step: 6400 | loss: 3.068608272
step: 6410 | loss: 3.063043263
step: 6420 | loss: 3.057478270
step: 6430 | loss: 3.051913293
step: 6440 | loss: 3.046348332
step: 6450 | loss: 3.040783386
step: 6460 | loss: 3.035218457
step: 6470 | loss: 3.029653544
step: 6480 | loss: 3.024088647
step: 6490 | loss: 3.018523767
step: 6500 | loss: 3.012958902
step: 6510 | loss: 3.007394054
step: 6520 | loss: 3.001829222
step: 6530 | loss: 2.996264407
step: 6540 | loss: 2.990699607
step: 6550 | loss: 2.985134825
step: 6560 | loss: 2.979570059
step: 6570 | loss: 2.974005309
step: 6580 | loss: 2.968440576
step: 6590 | loss: 2.962875860
step: 6600 | loss: 2.957311160
step: 6610 | loss: 2.951746477
step: 6620 | loss: 2.946181811
step: 6630 | loss: 2.940617162
step: 6640 | loss: 2.935052530
step: 6650 | loss: 2.929487914
step: 6660 | loss: 2.923923316
step: 6670 | loss: 2.918358734
step: 6680 | loss: 2.912794170
step: 6690 | loss: 2.907229623
step: 6700 | loss: 2.901665093
step: 6710 | loss: 2.896100581
step: 6720 | loss: 2.890536085
step: 6730 | loss: 2.884971608
step: 6740 | loss: 2.879407147
step: 6750 | loss: 2.873842704
step: 6760 | loss: 2.868278279
step: 6770 | loss: 2.862713871
step: 6780 | loss: 2.857149481
step: 6790 | loss: 2.851585109
step: 6800 | loss: 2.846020755
step: 6810 | loss: 2.840456418
step: 6820 | loss: 2.834892100
step: 6830 | loss: 2.829327799
step: 6840 | loss: 2.823763517
step: 6850 | loss: 2.818199253
step: 6860 | loss: 2.812635007
step: 6870 | loss: 2.807070779
step: 6880 | loss: 2.801506570
step: 6890 | loss: 2.795942379
step: 6900 | loss: 2.790378207
step: 6910 | loss: 2.784814053
step: 6920 | loss: 2.779249918
step: 6930 | loss: 2.773685801
step: 6940 | loss: 2.768121704
step: 6950 | loss: 2.762557625
step: 6960 | loss: 2.756993565
step: 6970 | loss: 2.751429525
step: 6980 | loss: 2.745865503
step: 6990 | loss: 2.740301501
step: 7000 | loss: 2.734737518
step: 7010 | loss: 2.729173554
step: 7020 | loss: 2.723609610
step: 7030 | loss: 2.718045685
step: 7040 | loss: 2.712481780
step: 7050 | loss: 2.706917895
step: 7060 | loss: 2.701354029
step: 7070 | loss: 2.695790183
step: 7080 | loss: 2.690226358
step: 7090 | loss: 2.684662552
step: 7100 | loss: 2.679098766
step: 7110 | loss: 2.673535001
step: 7120 | loss: 2.667971256
step: 7130 | loss: 2.662407532
step: 7140 | loss: 2.656843827
step: 7150 | loss: 2.651280144
step: 7160 | loss: 2.645716481
step: 7170 | loss: 2.640152839
step: 7180 | loss: 2.634589218
step: 7190 | loss: 2.629025618
step: 7200 | loss: 2.623462039
step: 7210 | loss: 2.617898481
step: 7220 | loss: 2.612334945
step: 7230 | loss: 2.606771430
step: 7240 | loss: 2.601207936
step: 7250 | loss: 2.595644464
step: 7260 | loss: 2.590081014
step: 7270 | loss: 2.584517585
step: 7280 | loss: 2.578954179
step: 7290 | loss: 2.573390794
step: 7300 | loss: 2.567827432
step: 7310 | loss: 2.562264092
step: 7320 | loss: 2.556700774
step: 7330 | loss: 2.551137479
step: 7340 | loss: 2.545574206
step: 7350 | loss: 2.540010956
step: 7360 | loss: 2.534447729
step: 7370 | loss: 2.528884525
step: 7380 | loss: 2.523321344
step: 7390 | loss: 2.517758186
step: 7400 | loss: 2.512195051
step: 7410 | loss: 2.506631940
step: 7420 | loss: 2.501068852
step: 7430 | loss: 2.495505788
step: 7440 | loss: 2.489942748
step: 7450 | loss: 2.484379731
step: 7460 | loss: 2.478816739
step: 7470 | loss: 2.473253771
step: 7480 | loss: 2.467690827
step: 7490 | loss: 2.462127908
step: 7500 | loss: 2.456565013
step: 7510 | loss: 2.451002143
step: 7520 | loss: 2.445439298
step: 7530 | loss: 2.439876477
step: 7540 | loss: 2.434313682
step: 7550 | loss: 2.428750912
step: 7560 | loss: 2.423188168
step: 7570 | loss: 2.417625449
step: 7580 | loss: 2.412062755
step: 7590 | loss: 2.406500088
step: 7600 | loss: 2.400937446
step: 7610 | loss: 2.395374831
step: 7620 | loss: 2.389812242
step: 7630 | loss: 2.384249679
step: 7640 | loss: 2.378687143
step: 7650 | loss: 2.373124633
step: 7660 | loss: 2.367562151
step: 7670 | loss: 2.361999695
step: 7680 | loss: 2.356437267
step: 7690 | loss: 2.350874866
step: 7700 | loss: 2.345312492
step: 7710 | loss: 2.339750146
step: 7720 | loss: 2.334187828
step: 7730 | loss: 2.328625538
step: 7740 | loss: 2.323063276
step: 7750 | loss: 2.317501043
step: 7760 | loss: 2.311938838
step: 7770 | loss: 2.306376661
step: 7780 | loss: 2.300814514
step: 7790 | loss: 2.295252395
step: 7800 | loss: 2.289690306
step: 7810 | loss: 2.284128246
step: 7820 | loss: 2.278566215
step: 7830 | loss: 2.273004214
step: 7840 | loss: 2.267442243
step: 7850 | loss: 2.261880303
step: 7860 | loss: 2.256318392
step: 7870 | loss: 2.250756512
step: 7880 | loss: 2.245194663
step: 7890 | loss: 2.239632844
step: 7900 | loss: 2.234071056
step: 7910 | loss: 2.228509300
step: 7920 | loss: 2.222947575
step: 7930 | loss: 2.217385882
step: 7940 | loss: 2.211824220
step: 7950 | loss: 2.206262591
step: 7960 | loss: 2.200700994
step: 7970 | loss: 2.195139429
step: 7980 | loss: 2.189577897
step: 7990 | loss: 2.184016398
step: 8000 | loss: 2.178454931
step: 8010 | loss: 2.172893498
step: 8020 | loss: 2.167332099
step: 8030 | loss: 2.161770733
step: 8040 | loss: 2.156209401
step: 8050 | loss: 2.150648104
step: 8060 | loss: 2.145086840
step: 8070 | loss: 2.139525612
step: 8080 | loss: 2.133964418
step: 8090 | loss: 2.128403259
step: 8100 | loss: 2.122842136
step: 8110 | loss: 2.117281048
step: 8120 | loss: 2.111719996
step: 8130 | loss: 2.106158979
step: 8140 | loss: 2.100597999
step: 8150 | loss: 2.095037056
step: 8160 | loss: 2.089476149
step: 8170 | loss: 2.083915280
step: 8180 | loss: 2.078354447
step: 8190 | loss: 2.072793652
step: 8200 | loss: 2.067232895
step: 8210 | loss: 2.061672176
step: 8220 | loss: 2.056111495
step: 8230 | loss: 2.050550852
step: 8240 | loss: 2.044990249
step: 8250 | loss: 2.039429684
step: 8260 | loss: 2.033869159
step: 8270 | loss: 2.028308673
step: 8280 | loss: 2.022748228
step: 8290 | loss: 2.017187822
step: 8300 | loss: 2.011627457
step: 8310 | loss: 2.006067133
step: 8320 | loss: 2.000506850
step: 8330 | loss: 1.994946608
step: 8340 | loss: 1.989386408
step: 8350 | loss: 1.983826249
step: 8360 | loss: 1.978266133
step: 8370 | loss: 1.972706059
step: 8380 | loss: 1.967146029
step: 8390 | loss: 1.961586041
step: 8400 | loss: 1.956026097
step: 8410 | loss: 1.950466196
step: 8420 | loss: 1.944906340
step: 8430 | loss: 1.939346528
step: 8440 | loss: 1.933786761
step: 8450 | loss: 1.928227039
step: 8460 | loss: 1.922667362
step: 8470 | loss: 1.917107731
step: 8480 | loss: 1.911548146
step: 8490 | loss: 1.905988608
step: 8500 | loss: 1.900429116
step: 8510 | loss: 1.894869671
step: 8520 | loss: 1.889310274
step: 8530 | loss: 1.883750925
step: 8540 | loss: 1.878191624
step: 8550 | loss: 1.872632371
step: 8560 | loss: 1.867073167
step: 8570 | loss: 1.861514013
step: 8580 | loss: 1.855954908
step: 8590 | loss: 1.850395854
step: 8600 | loss: 1.844836849
step: 8610 | loss: 1.839277896
step: 8620 | loss: 1.833718994
step: 8630 | loss: 1.828160143
step: 8640 | loss: 1.822601344
step: 8650 | loss: 1.817042598
step: 8660 | loss: 1.811483905
step: 8670 | loss: 1.805925265
step: 8680 | loss: 1.800366678
step: 8690 | loss: 1.794808146
step: 8700 | loss: 1.789249668
step: 8710 | loss: 1.783691245
step: 8720 | loss: 1.778132877
step: 8730 | loss: 1.772574566
step: 8740 | loss: 1.767016310
step: 8750 | loss: 1.761458111
step: 8760 | loss: 1.755899970
step: 8770 | loss: 1.750341886
step: 8780 | loss: 1.744783860
step: 8790 | loss: 1.739225892
step: 8800 | loss: 1.733667984
step: 8810 | loss: 1.728110135
step: 8820 | loss: 1.722552347
step: 8830 | loss: 1.716994618
step: 8840 | loss: 1.711436951
step: 8850 | loss: 1.705879345
step: 8860 | loss: 1.700321802
step: 8870 | loss: 1.694764321
step: 8880 | loss: 1.689206902
step: 8890 | loss: 1.683649548
step: 8900 | loss: 1.678092258
step: 8910 | loss: 1.672535032
step: 8920 | loss: 1.666977871
step: 8930 | loss: 1.661420776
step: 8940 | loss: 1.655863748
step: 8950 | loss: 1.650306786
step: 8960 | loss: 1.644749892
step: 8970 | loss: 1.639193066
step: 8980 | loss: 1.633636308
step: 8990 | loss: 1.628079620
step: 9000 | loss: 1.622523001
step: 9010 | loss: 1.616966453
step: 9020 | loss: 1.611409976
step: 9030 | loss: 1.605853570
step: 9040 | loss: 1.600297237
step: 9050 | loss: 1.594740976
step: 9060 | loss: 1.589184790
step: 9070 | loss: 1.583628677
step: 9080 | loss: 1.578072639
step: 9090 | loss: 1.572516676
step: 9100 | loss: 1.566960790
step: 9110 | loss: 1.561404981
step: 9120 | loss: 1.555849249
step: 9130 | loss: 1.550293595
step: 9140 | loss: 1.544738021
step: 9150 | loss: 1.539182526
step: 9160 | loss: 1.533627111
step: 9170 | loss: 1.528071777
step: 9180 | loss: 1.522516526
step: 9190 | loss: 1.516961357
step: 9200 | loss: 1.511406271
step: 9210 | loss: 1.505851269
step: 9220 | loss: 1.500296352
step: 9230 | loss: 1.494741521
step: 9240 | loss: 1.489186777
step: 9250 | loss: 1.483632120
step: 9260 | loss: 1.478077550
step: 9270 | loss: 1.472523070
step: 9280 | loss: 1.466968680
step: 9290 | loss: 1.461414380
step: 9300 | loss: 1.455860172
step: 9310 | loss: 1.450306056
step: 9320 | loss: 1.444752033
step: 9330 | loss: 1.439198104
step: 9340 | loss: 1.433644271
step: 9350 | loss: 1.428090533
step: 9360 | loss: 1.422536893
step: 9370 | loss: 1.416983350
step: 9380 | loss: 1.411429906
step: 9390 | loss: 1.405876561
step: 9400 | loss: 1.400323318
step: 9410 | loss: 1.394770176
step: 9420 | loss: 1.389217137
step: 9430 | loss: 1.383664201
step: 9440 | loss: 1.378111370
step: 9450 | loss: 1.372558645
step: 9460 | loss: 1.367006027
step: 9470 | loss: 1.361453517
step: 9480 | loss: 1.355901116
step: 9490 | loss: 1.350348825
step: 9500 | loss: 1.344796646
step: 9510 | loss: 1.339244579
step: 9520 | loss: 1.333692625
step: 9530 | loss: 1.328140786
step: 9540 | loss: 1.322589063
step: 9550 | loss: 1.317037456
step: 9560 | loss: 1.311485969
step: 9570 | loss: 1.305934600
step: 9580 | loss: 1.300383353
step: 9590 | loss: 1.294832227
step: 9600 | loss: 1.289281225
step: 9610 | loss: 1.283730348
step: 9620 | loss: 1.278179596
step: 9630 | loss: 1.272628972
step: 9640 | loss: 1.267078476
step: 9650 | loss: 1.261528110
step: 9660 | loss: 1.255977876
step: 9670 | loss: 1.250427774
step: 9680 | loss: 1.244877807
step: 9690 | loss: 1.239327976
step: 9700 | loss: 1.233778281
step: 9710 | loss: 1.228228726
step: 9720 | loss: 1.222679310
step: 9730 | loss: 1.217130037
step: 9740 | loss: 1.211580906
step: 9750 | loss: 1.206031921
step: 9760 | loss: 1.200483082
step: 9770 | loss: 1.194934391
step: 9780 | loss: 1.189385851
step: 9790 | loss: 1.183837461
step: 9800 | loss: 1.178289225
step: 9810 | loss: 1.172741144
step: 9820 | loss: 1.167193220
step: 9830 | loss: 1.161645454
step: 9840 | loss: 1.156097849
step: 9850 | loss: 1.150550406
step: 9860 | loss: 1.145003127
step: 9870 | loss: 1.139456014
step: 9880 | loss: 1.133909069
step: 9890 | loss: 1.128362294
step: 9900 | loss: 1.122815691
step: 9910 | loss: 1.117269262
step: 9920 | loss: 1.111723009
step: 9930 | loss: 1.106176934
step: 9940 | loss: 1.100631039
step: 9950 | loss: 1.095085327
step: 9960 | loss: 1.089539799
step: 9970 | loss: 1.083994458
step: 9980 | loss: 1.078449307
step: 9990 | loss: 1.072904347
step: 10000 | loss: 1.067359580
step: 10010 | loss: 1.061815010
step: 10020 | loss: 1.056270639
step: 10030 | loss: 1.050726468
step: 10040 | loss: 1.045182501
step: 10050 | loss: 1.039638741
step: 10060 | loss: 1.034095189
step: 10070 | loss: 1.028551848
step: 10080 | loss: 1.023008722
step: 10090 | loss: 1.017465812
step: 10100 | loss: 1.011923122
step: 10110 | loss: 1.006380655
step: 10120 | loss: 1.000838412
step: 10130 | loss: 0.995296398
step: 10140 | loss: 0.989754615
step: 10150 | loss: 0.984213066
step: 10160 | loss: 0.978671755
step: 10170 | loss: 0.973130684
step: 10180 | loss: 0.967589856
step: 10190 | loss: 0.962049276
step: 10200 | loss: 0.956508945
step: 10210 | loss: 0.950968868
step: 10220 | loss: 0.945429048
step: 10230 | loss: 0.939889489
step: 10240 | loss: 0.934350194
step: 10250 | loss: 0.928811166
step: 10260 | loss: 0.923272409
step: 10270 | loss: 0.917733928
step: 10280 | loss: 0.912195725
step: 10290 | loss: 0.906657805
step: 10300 | loss: 0.901120172
step: 10310 | loss: 0.895582830
step: 10320 | loss: 0.890045783
step: 10330 | loss: 0.884509035
step: 10340 | loss: 0.878972590
step: 10350 | loss: 0.873436453
step: 10360 | loss: 0.867900629
step: 10370 | loss: 0.862365121
step: 10380 | loss: 0.856829935
step: 10390 | loss: 0.851295074
step: 10400 | loss: 0.845760545
step: 10410 | loss: 0.840226352
step: 10420 | loss: 0.834692499
step: 10430 | loss: 0.829158992
step: 10440 | loss: 0.823625837
step: 10450 | loss: 0.818093038
step: 10460 | loss: 0.812560601
step: 10470 | loss: 0.807028531
step: 10480 | loss: 0.801496835
step: 10490 | loss: 0.795965517
step: 10500 | loss: 0.790434585
step: 10510 | loss: 0.784904043
step: 10520 | loss: 0.779373898
step: 10530 | loss: 0.773844156
step: 10540 | loss: 0.768314824
step: 10550 | loss: 0.762785908
step: 10560 | loss: 0.757257415
step: 10570 | loss: 0.751729352
step: 10580 | loss: 0.746201726
step: 10590 | loss: 0.740674543
step: 10600 | loss: 0.735147811
step: 10610 | loss: 0.729621538
step: 10620 | loss: 0.724095732
step: 10630 | loss: 0.718570399
step: 10640 | loss: 0.713045548
step: 10650 | loss: 0.707521188
step: 10660 | loss: 0.701997326
step: 10670 | loss: 0.696473971
step: 10680 | loss: 0.690951132
step: 10690 | loss: 0.685428818
step: 10700 | loss: 0.679907038
step: 10710 | loss: 0.674385801
step: 10720 | loss: 0.668865117
step: 10730 | loss: 0.663344996
step: 10740 | loss: 0.657825447
step: 10750 | loss: 0.652306482
step: 10760 | loss: 0.646788110
step: 10770 | loss: 0.641270343
step: 10780 | loss: 0.635753191
step: 10790 | loss: 0.630236666
step: 10800 | loss: 0.624720780
step: 10810 | loss: 0.619205545
step: 10820 | loss: 0.613690972
step: 10830 | loss: 0.608177075
step: 10840 | loss: 0.602663866
step: 10850 | loss: 0.597151359
step: 10860 | loss: 0.591639566
step: 10870 | loss: 0.586128503
step: 10880 | loss: 0.580618183
step: 10890 | loss: 0.575108622
step: 10900 | loss: 0.569599833
step: 10910 | loss: 0.564091833
step: 10920 | loss: 0.558584638
step: 10930 | loss: 0.553078264
step: 10940 | loss: 0.547572728
step: 10950 | loss: 0.542068046
step: 10960 | loss: 0.536564238
step: 10970 | loss: 0.531061320
step: 10980 | loss: 0.525559313
step: 10990 | loss: 0.520058235
step: 11000 | loss: 0.514558106
step: 11010 | loss: 0.509058947
step: 11020 | loss: 0.503560779
step: 11030 | loss: 0.498063624
step: 11040 | loss: 0.492567503
step: 11050 | loss: 0.487072441
step: 11060 | loss: 0.481578461
step: 11070 | loss: 0.476085587
step: 11080 | loss: 0.470593844
step: 11090 | loss: 0.465103260
step: 11100 | loss: 0.459613860
step: 11110 | loss: 0.454125672
step: 11120 | loss: 0.448638726
step: 11130 | loss: 0.443153050
step: 11140 | loss: 0.437668676
step: 11150 | loss: 0.432185634
step: 11160 | loss: 0.426703958
step: 11170 | loss: 0.421223681
step: 11180 | loss: 0.415744838
step: 11190 | loss: 0.410267465
step: 11200 | loss: 0.404791599
step: 11210 | loss: 0.399317280
step: 11220 | loss: 0.393844547
step: 11230 | loss: 0.388373441
step: 11240 | loss: 0.382904005
step: 11250 | loss: 0.377436285
step: 11260 | loss: 0.371970325
step: 11270 | loss: 0.366506175
step: 11280 | loss: 0.361043883
step: 11290 | loss: 0.355583501
step: 11300 | loss: 0.350125083
step: 11310 | loss: 0.344668684
step: 11320 | loss: 0.339214362
step: 11330 | loss: 0.333762177
step: 11340 | loss: 0.328312191
step: 11350 | loss: 0.322864471
step: 11360 | loss: 0.317419082
step: 11370 | loss: 0.311976096
step: 11380 | loss: 0.306535587
step: 11390 | loss: 0.301097631
step: 11400 | loss: 0.295662307
step: 11410 | loss: 0.290229700
step: 11420 | loss: 0.284799896
step: 11430 | loss: 0.279372986
step: 11440 | loss: 0.273949066
step: 11450 | loss: 0.268528235
step: 11460 | loss: 0.263110597
step: 11470 | loss: 0.257696261
step: 11480 | loss: 0.252285342
step: 11490 | loss: 0.246877959
step: 11500 | loss: 0.241474238
step: 11510 | loss: 0.236074311
step: 11520 | loss: 0.230678317
step: 11530 | loss: 0.225286400
step: 11540 | loss: 0.219898716
step: 11550 | loss: 0.214515425
step: 11560 | loss: 0.209136698
step: 11570 | loss: 0.203762713
step: 11580 | loss: 0.198393662
step: 11590 | loss: 0.193029743
step: 11600 | loss: 0.187671168
step: 11610 | loss: 0.182318162
step: 11620 | loss: 0.176970962
step: 11630 | loss: 0.171629820
step: 11640 | loss: 0.166295002
step: 11650 | loss: 0.160966794
step: 11660 | loss: 0.155645497
step: 11670 | loss: 0.150331432
step: 11680 | loss: 0.145024945
step: 11690 | loss: 0.139726400
step: 11700 | loss: 0.134436190
step: 11710 | loss: 0.129154735
step: 11720 | loss: 0.123882485
step: 11730 | loss: 0.118619923
step: 11740 | loss: 0.113367569
step: 11750 | loss: 0.108125983
step: 11760 | loss: 0.102895769
step: 11770 | loss: 0.097677581
step: 11780 | loss: 0.092472127
step: 11790 | loss: 0.087280175
step: 11800 | loss: 0.082102562
step: 11810 | loss: 0.076940199
step: 11820 | loss: 0.071794083
step: 11830 | loss: 0.066665305
step: 11840 | loss: 0.061555066
step: 11850 | loss: 0.056464689
step: 11860 | loss: 0.051395637
step: 11870 | loss: 0.046349535
step: 11880 | loss: 0.041328193
step: 11890 | loss: 0.036333640
step: 11900 | loss: 0.031368160
step: 11910 | loss: 0.026434347
step: 11920 | loss: 0.021535172
step: 11930 | loss: 0.016674107
step: 11940 | loss: 0.011855351
step: 11950 | loss: 0.007084538
step: 11960 | loss: 0.002374105
- final loss: 0.000985
- (cd _build/default/examples/opt && ./single.exe)
- 
step: 0 | loss: 7.628919486
step: 10 | loss: 7.625013724
step: 20 | loss: 7.620675741
step: 30 | loss: 7.616339814
step: 40 | loss: 7.612006092
step: 50 | loss: 7.607674662
step: 60 | loss: 7.603345570
step: 70 | loss: 7.599018835
step: 80 | loss: 7.594694467
step: 90 | loss: 7.590372468
step: 100 | loss: 7.586052839
step: 110 | loss: 7.581735580
step: 120 | loss: 7.577420689
step: 130 | loss: 7.573108167
step: 140 | loss: 7.568798011
step: 150 | loss: 7.564490221
step: 160 | loss: 7.560184795
step: 170 | loss: 7.555881733
step: 180 | loss: 7.551581034
step: 190 | loss: 7.547282695
step: 200 | loss: 7.542986717
step: 210 | loss: 7.538693099
step: 220 | loss: 7.534401838
step: 230 | loss: 7.530112935
step: 240 | loss: 7.525826388
step: 250 | loss: 7.521542196
step: 260 | loss: 7.517260358
step: 270 | loss: 7.512980874
step: 280 | loss: 7.508703742
step: 290 | loss: 7.504428961
step: 300 | loss: 7.500156530
step: 310 | loss: 7.495886448
step: 320 | loss: 7.491618715
step: 330 | loss: 7.487353329
step: 340 | loss: 7.483090290
step: 350 | loss: 7.478829596
step: 360 | loss: 7.474571246
step: 370 | loss: 7.470315241
step: 380 | loss: 7.466061578
step: 390 | loss: 7.461810257
step: 400 | loss: 7.457561276
step: 410 | loss: 7.453314636
step: 420 | loss: 7.449070336
step: 430 | loss: 7.444828373
step: 440 | loss: 7.440588748
step: 450 | loss: 7.436351460
step: 460 | loss: 7.432116507
step: 470 | loss: 7.427883889
step: 480 | loss: 7.423653606
step: 490 | loss: 7.419425656
step: 500 | loss: 7.415200038
step: 510 | loss: 7.410976752
step: 520 | loss: 7.406755797
step: 530 | loss: 7.402537172
step: 540 | loss: 7.398320876
step: 550 | loss: 7.394106909
step: 560 | loss: 7.389895269
step: 570 | loss: 7.385685957
step: 580 | loss: 7.381478971
step: 590 | loss: 7.377274310
step: 600 | loss: 7.373071975
step: 610 | loss: 7.368871963
step: 620 | loss: 7.364674275
step: 630 | loss: 7.360478909
step: 640 | loss: 7.356285866
step: 650 | loss: 7.352095143
step: 660 | loss: 7.347906742
step: 670 | loss: 7.343720660
step: 680 | loss: 7.339536897
step: 690 | loss: 7.335355453
step: 700 | loss: 7.331176327
step: 710 | loss: 7.326999519
step: 720 | loss: 7.322825027
step: 730 | loss: 7.318652851
step: 740 | loss: 7.314482990
step: 750 | loss: 7.310315444
step: 760 | loss: 7.306150213
step: 770 | loss: 7.301987295
step: 780 | loss: 7.297826690
step: 790 | loss: 7.293668397
step: 800 | loss: 7.289512417
step: 810 | loss: 7.285358748
step: 820 | loss: 7.281207389
step: 830 | loss: 7.277058341
step: 840 | loss: 7.272911602
step: 850 | loss: 7.268767172
step: 860 | loss: 7.264625051
step: 870 | loss: 7.260485238
step: 880 | loss: 7.256347733
step: 890 | loss: 7.252212534
step: 900 | loss: 7.248079643
step: 910 | loss: 7.243949057
step: 920 | loss: 7.239820777
step: 930 | loss: 7.235694802
step: 940 | loss: 7.231571131
step: 950 | loss: 7.227449765
step: 960 | loss: 7.223330703
step: 970 | loss: 7.219213944
step: 980 | loss: 7.215099488
step: 990 | loss: 7.210987334
step: 1000 | loss: 7.206877482
step: 1010 | loss: 7.202769932
step: 1020 | loss: 7.198664683
step: 1030 | loss: 7.194561735
step: 1040 | loss: 7.190461088
step: 1050 | loss: 7.186362740
step: 1060 | loss: 7.182266692
step: 1070 | loss: 7.178172944
step: 1080 | loss: 7.174081494
step: 1090 | loss: 7.169992343
step: 1100 | loss: 7.165905490
step: 1110 | loss: 7.161820935
step: 1120 | loss: 7.157738678
step: 1130 | loss: 7.153658718
step: 1140 | loss: 7.149581055
step: 1150 | loss: 7.145505688
step: 1160 | loss: 7.141432618
step: 1170 | loss: 7.137361844
step: 1180 | loss: 7.133293366
step: 1190 | loss: 7.129227183
step: 1200 | loss: 7.125163295
step: 1210 | loss: 7.121101702
step: 1220 | loss: 7.117042404
step: 1230 | loss: 7.112985401
step: 1240 | loss: 7.108930691
step: 1250 | loss: 7.104878276
step: 1260 | loss: 7.100828154
step: 1270 | loss: 7.096780325
step: 1280 | loss: 7.092734790
step: 1290 | loss: 7.088691548
step: 1300 | loss: 7.084650599
step: 1310 | loss: 7.080611942
step: 1320 | loss: 7.076575578
step: 1330 | loss: 7.072541506
step: 1340 | loss: 7.068509726
step: 1350 | loss: 7.064480239
step: 1360 | loss: 7.060453043
step: 1370 | loss: 7.056428138
step: 1380 | loss: 7.052405525
step: 1390 | loss: 7.048385203
step: 1400 | loss: 7.044367173
step: 1410 | loss: 7.040351433
step: 1420 | loss: 7.036337985
step: 1430 | loss: 7.032326827
step: 1440 | loss: 7.028317960
step: 1450 | loss: 7.024311383
step: 1460 | loss: 7.020307097
step: 1470 | loss: 7.016305101
step: 1480 | loss: 7.012305396
step: 1490 | loss: 7.008307980
step: 1500 | loss: 7.004312855
step: 1510 | loss: 7.000320020
step: 1520 | loss: 6.996329475
step: 1530 | loss: 6.992341220
step: 1540 | loss: 6.988355255
step: 1550 | loss: 6.984371579
step: 1560 | loss: 6.980390194
step: 1570 | loss: 6.976411098
step: 1580 | loss: 6.972434292
step: 1590 | loss: 6.968459775
step: 1600 | loss: 6.964487549
step: 1610 | loss: 6.960517612
step: 1620 | loss: 6.956549964
step: 1630 | loss: 6.952584607
step: 1640 | loss: 6.948621539
step: 1650 | loss: 6.944660760
step: 1660 | loss: 6.940702272
step: 1670 | loss: 6.936746073
step: 1680 | loss: 6.932792164
step: 1690 | loss: 6.928840545
step: 1700 | loss: 6.924891215
step: 1710 | loss: 6.920944176
step: 1720 | loss: 6.916999426
step: 1730 | loss: 6.913056966
step: 1740 | loss: 6.909116797
step: 1750 | loss: 6.905178917
step: 1760 | loss: 6.901243328
step: 1770 | loss: 6.897310029
step: 1780 | loss: 6.893379020
step: 1790 | loss: 6.889450301
step: 1800 | loss: 6.885523873
step: 1810 | loss: 6.881599736
step: 1820 | loss: 6.877677889
step: 1830 | loss: 6.873758333
step: 1840 | loss: 6.869841068
step: 1850 | loss: 6.865926094
step: 1860 | loss: 6.862013411
step: 1870 | loss: 6.858103019
step: 1880 | loss: 6.854194919
step: 1890 | loss: 6.850289110
step: 1900 | loss: 6.846385592
step: 1910 | loss: 6.842484367
step: 1920 | loss: 6.838585433
step: 1930 | loss: 6.834688791
step: 1940 | loss: 6.830794442
step: 1950 | loss: 6.826902385
step: 1960 | loss: 6.823012620
step: 1970 | loss: 6.819125148
step: 1980 | loss: 6.815239969
step: 1990 | loss: 6.811357083
step: 2000 | loss: 6.807476490
step: 2010 | loss: 6.803598190
step: 2020 | loss: 6.799722184
step: 2030 | loss: 6.795848471
step: 2040 | loss: 6.791977052
step: 2050 | loss: 6.788107928
step: 2060 | loss: 6.784241097
step: 2070 | loss: 6.780376561
step: 2080 | loss: 6.776514320
step: 2090 | loss: 6.772654374
step: 2100 | loss: 6.768796723
step: 2110 | loss: 6.764941367
step: 2120 | loss: 6.761088306
step: 2130 | loss: 6.757237541
step: 2140 | loss: 6.753389072
step: 2150 | loss: 6.749542900
step: 2160 | loss: 6.745699023
step: 2170 | loss: 6.741857443
step: 2180 | loss: 6.738018160
step: 2190 | loss: 6.734181175
step: 2200 | loss: 6.730346486
step: 2210 | loss: 6.726514095
step: 2220 | loss: 6.722684002
step: 2230 | loss: 6.718856206
step: 2240 | loss: 6.715030709
step: 2250 | loss: 6.711207511
step: 2260 | loss: 6.707386611
step: 2270 | loss: 6.703568010
step: 2280 | loss: 6.699751709
step: 2290 | loss: 6.695937707
step: 2300 | loss: 6.692126004
step: 2310 | loss: 6.688316602
step: 2320 | loss: 6.684509500
step: 2330 | loss: 6.680704699
step: 2340 | loss: 6.676902198
step: 2350 | loss: 6.673101999
step: 2360 | loss: 6.669304100
step: 2370 | loss: 6.665508504
step: 2380 | loss: 6.661715209
step: 2390 | loss: 6.657924217
step: 2400 | loss: 6.654135526
step: 2410 | loss: 6.650349139
step: 2420 | loss: 6.646565054
step: 2430 | loss: 6.642783273
step: 2440 | loss: 6.639003796
step: 2450 | loss: 6.635226622
step: 2460 | loss: 6.631451752
step: 2470 | loss: 6.627679186
step: 2480 | loss: 6.623908925
step: 2490 | loss: 6.620140969
step: 2500 | loss: 6.616375318
step: 2510 | loss: 6.612611973
step: 2520 | loss: 6.608850934
step: 2530 | loss: 6.605092200
step: 2540 | loss: 6.601335773
step: 2550 | loss: 6.597581652
step: 2560 | loss: 6.593829838
step: 2570 | loss: 6.590080332
step: 2580 | loss: 6.586333132
step: 2590 | loss: 6.582588241
step: 2600 | loss: 6.578845657
step: 2610 | loss: 6.575105382
step: 2620 | loss: 6.571367415
step: 2630 | loss: 6.567631758
step: 2640 | loss: 6.563898409
step: 2650 | loss: 6.560167370
step: 2660 | loss: 6.556438640
step: 2670 | loss: 6.552712220
step: 2680 | loss: 6.548988111
step: 2690 | loss: 6.545266312
step: 2700 | loss: 6.541546824
step: 2710 | loss: 6.537829647
step: 2720 | loss: 6.534114781
step: 2730 | loss: 6.530402227
step: 2740 | loss: 6.526691984
step: 2750 | loss: 6.522984054
step: 2760 | loss: 6.519278436
step: 2770 | loss: 6.515575131
step: 2780 | loss: 6.511874139
step: 2790 | loss: 6.508175460
step: 2800 | loss: 6.504479094
step: 2810 | loss: 6.500785042
step: 2820 | loss: 6.497093304
step: 2830 | loss: 6.493403881
step: 2840 | loss: 6.489716771
step: 2850 | loss: 6.486031977
step: 2860 | loss: 6.482349497
step: 2870 | loss: 6.478669333
step: 2880 | loss: 6.474991484
step: 2890 | loss: 6.471315951
step: 2900 | loss: 6.467642733
step: 2910 | loss: 6.463971832
step: 2920 | loss: 6.460303248
step: 2930 | loss: 6.456636980
step: 2940 | loss: 6.452973028
step: 2950 | loss: 6.449311394
step: 2960 | loss: 6.445652077
step: 2970 | loss: 6.441995078
step: 2980 | loss: 6.438340396
step: 2990 | loss: 6.434688033
step: 3000 | loss: 6.431037987
step: 3010 | loss: 6.427390260
step: 3020 | loss: 6.423744851
step: 3030 | loss: 6.420101761
step: 3040 | loss: 6.416460990
step: 3050 | loss: 6.412822538
step: 3060 | loss: 6.409186406
step: 3070 | loss: 6.405552593
step: 3080 | loss: 6.401921099
step: 3090 | loss: 6.398291926
step: 3100 | loss: 6.394665072
step: 3110 | loss: 6.391040539
step: 3120 | loss: 6.387418326
step: 3130 | loss: 6.383798433
step: 3140 | loss: 6.380180861
step: 3150 | loss: 6.376565610
step: 3160 | loss: 6.372952680
step: 3170 | loss: 6.369342070
step: 3180 | loss: 6.365733782
step: 3190 | loss: 6.362127815
step: 3200 | loss: 6.358524170
step: 3210 | loss: 6.354922846
step: 3220 | loss: 6.351323844
step: 3230 | loss: 6.347727164
step: 3240 | loss: 6.344132805
step: 3250 | loss: 6.340540768
step: 3260 | loss: 6.336951054
step: 3270 | loss: 6.333363661
step: 3280 | loss: 6.329778591
step: 3290 | loss: 6.326195842
step: 3300 | loss: 6.322615417
step: 3310 | loss: 6.319037313
step: 3320 | loss: 6.315461532
step: 3330 | loss: 6.311888073
step: 3340 | loss: 6.308316937
step: 3350 | loss: 6.304748124
step: 3360 | loss: 6.301181633
step: 3370 | loss: 6.297617464
step: 3380 | loss: 6.294055618
step: 3390 | loss: 6.290496095
step: 3400 | loss: 6.286938894
step: 3410 | loss: 6.283384016
step: 3420 | loss: 6.279831461
step: 3430 | loss: 6.276281227
step: 3440 | loss: 6.272733317
step: 3450 | loss: 6.269187729
step: 3460 | loss: 6.265644463
step: 3470 | loss: 6.262103520
step: 3480 | loss: 6.258564899
step: 3490 | loss: 6.255028600
step: 3500 | loss: 6.251494623
step: 3510 | loss: 6.247962969
step: 3520 | loss: 6.244433636
step: 3530 | loss: 6.240906626
step: 3540 | loss: 6.237381937
step: 3550 | loss: 6.233859569
step: 3560 | loss: 6.230339524
step: 3570 | loss: 6.226821799
step: 3580 | loss: 6.223306396
step: 3590 | loss: 6.219793314
step: 3600 | loss: 6.216282553
step: 3610 | loss: 6.212774113
step: 3620 | loss: 6.209267993
step: 3630 | loss: 6.205764194
step: 3640 | loss: 6.202262715
step: 3650 | loss: 6.198763556
step: 3660 | loss: 6.195266716
step: 3670 | loss: 6.191772197
step: 3680 | loss: 6.188279996
step: 3690 | loss: 6.184790115
step: 3700 | loss: 6.181302553
step: 3710 | loss: 6.177817309
step: 3720 | loss: 6.174334383
step: 3730 | loss: 6.170853776
step: 3740 | loss: 6.167375486
step: 3750 | loss: 6.163899514
step: 3760 | loss: 6.160425859
step: 3770 | loss: 6.156954521
step: 3780 | loss: 6.153485499
step: 3790 | loss: 6.150018794
step: 3800 | loss: 6.146554404
step: 3810 | loss: 6.143092330
step: 3820 | loss: 6.139632570
step: 3830 | loss: 6.136175126
step: 3840 | loss: 6.132719996
step: 3850 | loss: 6.129267179
step: 3860 | loss: 6.125816677
step: 3870 | loss: 6.122368487
step: 3880 | loss: 6.118922610
step: 3890 | loss: 6.115479045
step: 3900 | loss: 6.112037792
step: 3910 | loss: 6.108598850
step: 3920 | loss: 6.105162219
step: 3930 | loss: 6.101727899
step: 3940 | loss: 6.098295888
step: 3950 | loss: 6.094866186
step: 3960 | loss: 6.091438794
step: 3970 | loss: 6.088013709
step: 3980 | loss: 6.084590932
step: 3990 | loss: 6.081170463
step: 4000 | loss: 6.077752300
step: 4010 | loss: 6.074336442
step: 4020 | loss: 6.070922891
step: 4030 | loss: 6.067511644
step: 4040 | loss: 6.064102701
step: 4050 | loss: 6.060696062
step: 4060 | loss: 6.057291726
step: 4070 | loss: 6.053889692
step: 4080 | loss: 6.050489960
step: 4090 | loss: 6.047092529
step: 4100 | loss: 6.043697397
step: 4110 | loss: 6.040304566
step: 4120 | loss: 6.036914033
step: 4130 | loss: 6.033525799
step: 4140 | loss: 6.030139862
step: 4150 | loss: 6.026756221
step: 4160 | loss: 6.023374876
step: 4170 | loss: 6.019995827
step: 4180 | loss: 6.016619072
step: 4190 | loss: 6.013244610
step: 4200 | loss: 6.009872441
step: 4210 | loss: 6.006502564
step: 4220 | loss: 6.003134978
step: 4230 | loss: 5.999769682
step: 4240 | loss: 5.996406675
step: 4250 | loss: 5.993045957
step: 4260 | loss: 5.989687527
step: 4270 | loss: 5.986331383
step: 4280 | loss: 5.982977525
step: 4290 | loss: 5.979625952
step: 4300 | loss: 5.976276663
step: 4310 | loss: 5.972929657
step: 4320 | loss: 5.969584932
step: 4330 | loss: 5.966242489
step: 4340 | loss: 5.962902326
step: 4350 | loss: 5.959564442
step: 4360 | loss: 5.956228836
step: 4370 | loss: 5.952895507
step: 4380 | loss: 5.949564454
step: 4390 | loss: 5.946235675
step: 4400 | loss: 5.942909171
step: 4410 | loss: 5.939584939
step: 4420 | loss: 5.936262979
step: 4430 | loss: 5.932943290
step: 4440 | loss: 5.929625870
step: 4450 | loss: 5.926310718
step: 4460 | loss: 5.922997834
step: 4470 | loss: 5.919687215
step: 4480 | loss: 5.916378862
step: 4490 | loss: 5.913072772
step: 4500 | loss: 5.909768944
step: 4510 | loss: 5.906467378
step: 4520 | loss: 5.903168072
step: 4530 | loss: 5.899871025
step: 4540 | loss: 5.896576235
step: 4550 | loss: 5.893283701
step: 4560 | loss: 5.889993423
step: 4570 | loss: 5.886705398
step: 4580 | loss: 5.883419626
step: 4590 | loss: 5.880136104
step: 4600 | loss: 5.876854833
step: 4610 | loss: 5.873575810
step: 4620 | loss: 5.870299034
step: 4630 | loss: 5.867024504
step: 4640 | loss: 5.863752219
step: 4650 | loss: 5.860482176
step: 4660 | loss: 5.857214375
step: 4670 | loss: 5.853948814
step: 4680 | loss: 5.850685492
step: 4690 | loss: 5.847424407
step: 4700 | loss: 5.844165558
step: 4710 | loss: 5.840908944
step: 4720 | loss: 5.837654563
step: 4730 | loss: 5.834402413
step: 4740 | loss: 5.831152492
step: 4750 | loss: 5.827904801
step: 4760 | loss: 5.824659336
step: 4770 | loss: 5.821416097
step: 4780 | loss: 5.818175082
step: 4790 | loss: 5.814936289
step: 4800 | loss: 5.811699716
step: 4810 | loss: 5.808465363
step: 4820 | loss: 5.805233228
step: 4830 | loss: 5.802003308
step: 4840 | loss: 5.798775603
step: 4850 | loss: 5.795550111
step: 4860 | loss: 5.792326829
step: 4870 | loss: 5.789105758
step: 4880 | loss: 5.785886893
step: 4890 | loss: 5.782670236
step: 4900 | loss: 5.779455782
step: 4910 | loss: 5.776243531
step: 4920 | loss: 5.773033482
step: 4930 | loss: 5.769825632
step: 4940 | loss: 5.766619979
step: 4950 | loss: 5.763416522
step: 4960 | loss: 5.760215260
step: 4970 | loss: 5.757016190
step: 4980 | loss: 5.753819310
step: 4990 | loss: 5.750624619
step: 5000 | loss: 5.747432116
step: 5010 | loss: 5.744241798
step: 5020 | loss: 5.741053663
step: 5030 | loss: 5.737867710
step: 5040 | loss: 5.734683937
step: 5050 | loss: 5.731502342
step: 5060 | loss: 5.728322924
step: 5070 | loss: 5.725145679
step: 5080 | loss: 5.721970607
step: 5090 | loss: 5.718797706
step: 5100 | loss: 5.715626974
step: 5110 | loss: 5.712458408
step: 5120 | loss: 5.709292008
step: 5130 | loss: 5.706127771
step: 5140 | loss: 5.702965695
step: 5150 | loss: 5.699805778
step: 5160 | loss: 5.696648018
step: 5170 | loss: 5.693492415
step: 5180 | loss: 5.690338964
step: 5190 | loss: 5.687187666
step: 5200 | loss: 5.684038516
step: 5210 | loss: 5.680891515
step: 5220 | loss: 5.677746659
step: 5230 | loss: 5.674603947
step: 5240 | loss: 5.671463377
step: 5250 | loss: 5.668324947
step: 5260 | loss: 5.665188655
step: 5270 | loss: 5.662054498
step: 5280 | loss: 5.658922475
step: 5290 | loss: 5.655792584
step: 5300 | loss: 5.652664823
step: 5310 | loss: 5.649539189
step: 5320 | loss: 5.646415681
step: 5330 | loss: 5.643294297
step: 5340 | loss: 5.640175035
step: 5350 | loss: 5.637057892
step: 5360 | loss: 5.633942867
step: 5370 | loss: 5.630829957
step: 5380 | loss: 5.627719161
step: 5390 | loss: 5.624610477
step: 5400 | loss: 5.621503901
step: 5410 | loss: 5.618399433
step: 5420 | loss: 5.615297071
step: 5430 | loss: 5.612196811
step: 5440 | loss: 5.609098652
step: 5450 | loss: 5.606002593
step: 5460 | loss: 5.602908630
step: 5470 | loss: 5.599816762
step: 5480 | loss: 5.596726987
step: 5490 | loss: 5.593639302
step: 5500 | loss: 5.590553706
step: 5510 | loss: 5.587470197
step: 5520 | loss: 5.584388771
step: 5530 | loss: 5.581309428
step: 5540 | loss: 5.578232165
step: 5550 | loss: 5.575156980
step: 5560 | loss: 5.572083870
step: 5570 | loss: 5.569012834
step: 5580 | loss: 5.565943870
step: 5590 | loss: 5.562876976
step: 5600 | loss: 5.559812148
step: 5610 | loss: 5.556749386
step: 5620 | loss: 5.553688687
step: 5630 | loss: 5.550630049
step: 5640 | loss: 5.547573469
step: 5650 | loss: 5.544518946
step: 5660 | loss: 5.541466478
step: 5670 | loss: 5.538416062
step: 5680 | loss: 5.535367696
step: 5690 | loss: 5.532321378
step: 5700 | loss: 5.529277107
step: 5710 | loss: 5.526234879
step: 5720 | loss: 5.523194692
step: 5730 | loss: 5.520156545
step: 5740 | loss: 5.517120435
step: 5750 | loss: 5.514086361
step: 5760 | loss: 5.511054319
step: 5770 | loss: 5.508024308
step: 5780 | loss: 5.504996326
step: 5790 | loss: 5.501970371
step: 5800 | loss: 5.498946439
step: 5810 | loss: 5.495924530
step: 5820 | loss: 5.492904641
step: 5830 | loss: 5.489886770
step: 5840 | loss: 5.486870914
step: 5850 | loss: 5.483857072
step: 5860 | loss: 5.480845241
step: 5870 | loss: 5.477835420
step: 5880 | loss: 5.474827605
step: 5890 | loss: 5.471821795
step: 5900 | loss: 5.468817988
step: 5910 | loss: 5.465816181
step: 5920 | loss: 5.462816373
step: 5930 | loss: 5.459818560
step: 5940 | loss: 5.456822742
step: 5950 | loss: 5.453828915
step: 5960 | loss: 5.450837078
step: 5970 | loss: 5.447847228
step: 5980 | loss: 5.444859363
step: 5990 | loss: 5.441873481
step: 6000 | loss: 5.438889580
step: 6010 | loss: 5.435907657
step: 6020 | loss: 5.432927711
step: 6030 | loss: 5.429949739
step: 6040 | loss: 5.426973739
step: 6050 | loss: 5.423999708
step: 6060 | loss: 5.421027645
step: 6070 | loss: 5.418057548
step: 6080 | loss: 5.415089413
step: 6090 | loss: 5.412123239
step: 6100 | loss: 5.409159024
step: 6110 | loss: 5.406196765
step: 6120 | loss: 5.403236461
step: 6130 | loss: 5.400278108
step: 6140 | loss: 5.397321705
step: 6150 | loss: 5.394367250
step: 6160 | loss: 5.391414739
step: 6170 | loss: 5.388464172
step: 6180 | loss: 5.385515545
step: 6190 | loss: 5.382568857
step: 6200 | loss: 5.379624104
step: 6210 | loss: 5.376681286
step: 6220 | loss: 5.373740399
step: 6230 | loss: 5.370801441
step: 6240 | loss: 5.367864410
step: 6250 | loss: 5.364929304
step: 6260 | loss: 5.361996121
step: 6270 | loss: 5.359064857
step: 6280 | loss: 5.356135511
step: 6290 | loss: 5.353208081
step: 6300 | loss: 5.350282563
step: 6310 | loss: 5.347358956
step: 6320 | loss: 5.344437258
step: 6330 | loss: 5.341517465
step: 6340 | loss: 5.338599576
step: 6350 | loss: 5.335683589
step: 6360 | loss: 5.332769500
step: 6370 | loss: 5.329857307
step: 6380 | loss: 5.326947009
step: 6390 | loss: 5.324038602
step: 6400 | loss: 5.321132085
step: 6410 | loss: 5.318227454
step: 6420 | loss: 5.315324707
step: 6430 | loss: 5.312423842
step: 6440 | loss: 5.309524857
step: 6450 | loss: 5.306627748
step: 6460 | loss: 5.303732514
step: 6470 | loss: 5.300839152
step: 6480 | loss: 5.297947659
step: 6490 | loss: 5.295058033
step: 6500 | loss: 5.292170271
step: 6510 | loss: 5.289284371
step: 6520 | loss: 5.286400330
step: 6530 | loss: 5.283518146
step: 6540 | loss: 5.280637815
step: 6550 | loss: 5.277759336
step: 6560 | loss: 5.274882705
step: 6570 | loss: 5.272007921
step: 6580 | loss: 5.269134980
step: 6590 | loss: 5.266263880
step: 6600 | loss: 5.263394618
step: 6610 | loss: 5.260527191
step: 6620 | loss: 5.257661597
step: 6630 | loss: 5.254797832
step: 6640 | loss: 5.251935895
step: 6650 | loss: 5.249075782
step: 6660 | loss: 5.246217491
step: 6670 | loss: 5.243361018
step: 6680 | loss: 5.240506362
step: 6690 | loss: 5.237653518
step: 6700 | loss: 5.234802485
step: 6710 | loss: 5.231953259
step: 6720 | loss: 5.229105837
step: 6730 | loss: 5.226260217
step: 6740 | loss: 5.223416396
step: 6750 | loss: 5.220574370
step: 6760 | loss: 5.217734137
step: 6770 | loss: 5.214895693
step: 6780 | loss: 5.212059036
step: 6790 | loss: 5.209224163
step: 6800 | loss: 5.206391070
step: 6810 | loss: 5.203559755
step: 6820 | loss: 5.200730214
step: 6830 | loss: 5.197902444
step: 6840 | loss: 5.195076443
step: 6850 | loss: 5.192252206
step: 6860 | loss: 5.189429731
step: 6870 | loss: 5.186609015
step: 6880 | loss: 5.183790054
step: 6890 | loss: 5.180972845
step: 6900 | loss: 5.178157384
step: 6910 | loss: 5.175343669
step: 6920 | loss: 5.172531697
step: 6930 | loss: 5.169721463
step: 6940 | loss: 5.166912964
step: 6950 | loss: 5.164106198
step: 6960 | loss: 5.161301160
step: 6970 | loss: 5.158497847
step: 6980 | loss: 5.155696256
step: 6990 | loss: 5.152896383
step: 7000 | loss: 5.150098225
step: 7010 | loss: 5.147301778
step: 7020 | loss: 5.144507039
step: 7030 | loss: 5.141714003
step: 7040 | loss: 5.138922668
step: 7050 | loss: 5.136133030
step: 7060 | loss: 5.133345084
step: 7070 | loss: 5.130558829
step: 7080 | loss: 5.127774258
step: 7090 | loss: 5.124991370
step: 7100 | loss: 5.122210159
step: 7110 | loss: 5.119430624
step: 7120 | loss: 5.116652758
step: 7130 | loss: 5.113876559
step: 7140 | loss: 5.111102023
step: 7150 | loss: 5.108329146
step: 7160 | loss: 5.105557924
step: 7170 | loss: 5.102788353
step: 7180 | loss: 5.100020429
step: 7190 | loss: 5.097254148
step: 7200 | loss: 5.094489506
step: 7210 | loss: 5.091726499
step: 7220 | loss: 5.088965123
step: 7230 | loss: 5.086205373
step: 7240 | loss: 5.083447247
step: 7250 | loss: 5.080690738
step: 7260 | loss: 5.077935844
step: 7270 | loss: 5.075182560
step: 7280 | loss: 5.072430882
step: 7290 | loss: 5.069680805
step: 7300 | loss: 5.066932326
step: 7310 | loss: 5.064185440
step: 7320 | loss: 5.061440142
step: 7330 | loss: 5.058696428
step: 7340 | loss: 5.055954294
step: 7350 | loss: 5.053213736
step: 7360 | loss: 5.050474748
step: 7370 | loss: 5.047737327
step: 7380 | loss: 5.045001468
step: 7390 | loss: 5.042267166
step: 7400 | loss: 5.039534417
step: 7410 | loss: 5.036803216
step: 7420 | loss: 5.034073559
step: 7430 | loss: 5.031345441
step: 7440 | loss: 5.028618857
step: 7450 | loss: 5.025893803
step: 7460 | loss: 5.023170274
step: 7470 | loss: 5.020448265
step: 7480 | loss: 5.017727772
step: 7490 | loss: 5.015008789
step: 7500 | loss: 5.012291312
step: 7510 | loss: 5.009575336
step: 7520 | loss: 5.006860856
step: 7530 | loss: 5.004147867
step: 7540 | loss: 5.001436365
step: 7550 | loss: 4.998726344
step: 7560 | loss: 4.996017800
step: 7570 | loss: 4.993310727
step: 7580 | loss: 4.990605121
step: 7590 | loss: 4.987900976
step: 7600 | loss: 4.985198287
step: 7610 | loss: 4.982497049
step: 7620 | loss: 4.979797258
step: 7630 | loss: 4.977098908
step: 7640 | loss: 4.974401994
step: 7650 | loss: 4.971706510
step: 7660 | loss: 4.969012452
step: 7670 | loss: 4.966319814
step: 7680 | loss: 4.963628591
step: 7690 | loss: 4.960938779
step: 7700 | loss: 4.958250370
step: 7710 | loss: 4.955563361
step: 7720 | loss: 4.952877746
step: 7730 | loss: 4.950193519
step: 7740 | loss: 4.947510676
step: 7750 | loss: 4.944829211
step: 7760 | loss: 4.942149117
step: 7770 | loss: 4.939470391
step: 7780 | loss: 4.936793027
step: 7790 | loss: 4.934117018
step: 7800 | loss: 4.931442360
step: 7810 | loss: 4.928769047
step: 7820 | loss: 4.926097074
step: 7830 | loss: 4.923426435
step: 7840 | loss: 4.920757125
step: 7850 | loss: 4.918089137
step: 7860 | loss: 4.915422467
step: 7870 | loss: 4.912757108
step: 7880 | loss: 4.910093055
step: 7890 | loss: 4.907430304
step: 7900 | loss: 4.904768846
step: 7910 | loss: 4.902108678
step: 7920 | loss: 4.899449794
step: 7930 | loss: 4.896792187
step: 7940 | loss: 4.894135853
step: 7950 | loss: 4.891480785
step: 7960 | loss: 4.888826977
step: 7970 | loss: 4.886174424
step: 7980 | loss: 4.883523121
step: 7990 | loss: 4.880873061
step: 8000 | loss: 4.878224238
step: 8010 | loss: 4.875576647
step: 8020 | loss: 4.872930282
step: 8030 | loss: 4.870285137
step: 8040 | loss: 4.867641207
step: 8050 | loss: 4.864998485
step: 8060 | loss: 4.862356965
step: 8070 | loss: 4.859716643
step: 8080 | loss: 4.857077511
step: 8090 | loss: 4.854439564
step: 8100 | loss: 4.851802796
step: 8110 | loss: 4.849167202
step: 8120 | loss: 4.846532775
step: 8130 | loss: 4.843899509
step: 8140 | loss: 4.841267399
step: 8150 | loss: 4.838636438
step: 8160 | loss: 4.836006622
step: 8170 | loss: 4.833377943
step: 8180 | loss: 4.830750395
step: 8190 | loss: 4.828123974
step: 8200 | loss: 4.825498673
step: 8210 | loss: 4.822874486
step: 8220 | loss: 4.820251406
step: 8230 | loss: 4.817629429
step: 8240 | loss: 4.815008549
step: 8250 | loss: 4.812388758
step: 8260 | loss: 4.809770052
step: 8270 | loss: 4.807152424
step: 8280 | loss: 4.804535869
step: 8290 | loss: 4.801920380
step: 8300 | loss: 4.799305951
step: 8310 | loss: 4.796692577
step: 8320 | loss: 4.794080252
step: 8330 | loss: 4.791468970
step: 8340 | loss: 4.788858724
step: 8350 | loss: 4.786249509
step: 8360 | loss: 4.783641320
step: 8370 | loss: 4.781034149
step: 8380 | loss: 4.778427991
step: 8390 | loss: 4.775822840
step: 8400 | loss: 4.773218691
step: 8410 | loss: 4.770615537
step: 8420 | loss: 4.768013373
step: 8430 | loss: 4.765412192
step: 8440 | loss: 4.762811989
step: 8450 | loss: 4.760212758
step: 8460 | loss: 4.757614493
step: 8470 | loss: 4.755017188
step: 8480 | loss: 4.752420838
step: 8490 | loss: 4.749825436
step: 8500 | loss: 4.747230976
step: 8510 | loss: 4.744637454
step: 8520 | loss: 4.742044863
step: 8530 | loss: 4.739453197
step: 8540 | loss: 4.736862450
step: 8550 | loss: 4.734272618
step: 8560 | loss: 4.731683693
step: 8570 | loss: 4.729095671
step: 8580 | loss: 4.726508545
step: 8590 | loss: 4.723922310
step: 8600 | loss: 4.721336961
step: 8610 | loss: 4.718752491
step: 8620 | loss: 4.716168895
step: 8630 | loss: 4.713586167
step: 8640 | loss: 4.711004302
step: 8650 | loss: 4.708423294
step: 8660 | loss: 4.705843137
step: 8670 | loss: 4.703263827
step: 8680 | loss: 4.700685356
step: 8690 | loss: 4.698107721
step: 8700 | loss: 4.695530914
step: 8710 | loss: 4.692954932
step: 8720 | loss: 4.690379768
step: 8730 | loss: 4.687805416
step: 8740 | loss: 4.685231873
step: 8750 | loss: 4.682659131
step: 8760 | loss: 4.680087186
step: 8770 | loss: 4.677516032
step: 8780 | loss: 4.674945664
step: 8790 | loss: 4.672376076
step: 8800 | loss: 4.669807264
step: 8810 | loss: 4.667239222
step: 8820 | loss: 4.664671944
step: 8830 | loss: 4.662105426
step: 8840 | loss: 4.659539662
step: 8850 | loss: 4.656974647
step: 8860 | loss: 4.654410377
step: 8870 | loss: 4.651846844
step: 8880 | loss: 4.649284046
step: 8890 | loss: 4.646721976
step: 8900 | loss: 4.644160629
step: 8910 | loss: 4.641600001
step: 8920 | loss: 4.639040086
step: 8930 | loss: 4.636480880
step: 8940 | loss: 4.633922377
step: 8950 | loss: 4.631364572
step: 8960 | loss: 4.628807461
step: 8970 | loss: 4.626251038
step: 8980 | loss: 4.623695299
step: 8990 | loss: 4.621140239
step: 9000 | loss: 4.618585853
step: 9010 | loss: 4.616032136
step: 9020 | loss: 4.613479083
step: 9030 | loss: 4.610926691
step: 9040 | loss: 4.608374953
step: 9050 | loss: 4.605823865
step: 9060 | loss: 4.603273423
step: 9070 | loss: 4.600723622
step: 9080 | loss: 4.598174457
step: 9090 | loss: 4.595625923
step: 9100 | loss: 4.593078017
step: 9110 | loss: 4.590530734
step: 9120 | loss: 4.587984068
step: 9130 | loss: 4.585438016
step: 9140 | loss: 4.582892573
step: 9150 | loss: 4.580347734
step: 9160 | loss: 4.577803496
step: 9170 | loss: 4.575259853
step: 9180 | loss: 4.572716802
step: 9190 | loss: 4.570174337
step: 9200 | loss: 4.567632456
step: 9210 | loss: 4.565091153
step: 9220 | loss: 4.562550424
step: 9230 | loss: 4.560010264
step: 9240 | loss: 4.557470671
step: 9250 | loss: 4.554931639
step: 9260 | loss: 4.552393164
step: 9270 | loss: 4.549855242
step: 9280 | loss: 4.547317869
step: 9290 | loss: 4.544781041
step: 9300 | loss: 4.542244754
step: 9310 | loss: 4.539709003
step: 9320 | loss: 4.537173785
step: 9330 | loss: 4.534639095
step: 9340 | loss: 4.532104930
step: 9350 | loss: 4.529571286
step: 9360 | loss: 4.527038159
step: 9370 | loss: 4.524505544
step: 9380 | loss: 4.521973438
step: 9390 | loss: 4.519441836
step: 9400 | loss: 4.516910736
step: 9410 | loss: 4.514380134
step: 9420 | loss: 4.511850024
step: 9430 | loss: 4.509320404
step: 9440 | loss: 4.506791270
step: 9450 | loss: 4.504262618
step: 9460 | loss: 4.501734444
step: 9470 | loss: 4.499206744
step: 9480 | loss: 4.496679516
step: 9490 | loss: 4.494152754
step: 9500 | loss: 4.491626456
step: 9510 | loss: 4.489100618
step: 9520 | loss: 4.486575236
step: 9530 | loss: 4.484050306
step: 9540 | loss: 4.481525826
step: 9550 | loss: 4.479001790
step: 9560 | loss: 4.476478197
step: 9570 | loss: 4.473955041
step: 9580 | loss: 4.471432320
step: 9590 | loss: 4.468910031
step: 9600 | loss: 4.466388169
step: 9610 | loss: 4.463866731
step: 9620 | loss: 4.461345714
step: 9630 | loss: 4.458825114
step: 9640 | loss: 4.456304927
step: 9650 | loss: 4.453785151
step: 9660 | loss: 4.451265782
step: 9670 | loss: 4.448746817
step: 9680 | loss: 4.446228252
step: 9690 | loss: 4.443710083
step: 9700 | loss: 4.441192308
step: 9710 | loss: 4.438674923
step: 9720 | loss: 4.436157924
step: 9730 | loss: 4.433641309
step: 9740 | loss: 4.431125074
step: 9750 | loss: 4.428609216
step: 9760 | loss: 4.426093732
step: 9770 | loss: 4.423578617
step: 9780 | loss: 4.421063870
step: 9790 | loss: 4.418549487
step: 9800 | loss: 4.416035464
step: 9810 | loss: 4.413521798
step: 9820 | loss: 4.411008486
step: 9830 | loss: 4.408495525
step: 9840 | loss: 4.405982912
step: 9850 | loss: 4.403470644
step: 9860 | loss: 4.400958717
step: 9870 | loss: 4.398447128
step: 9880 | loss: 4.395935874
step: 9890 | loss: 4.393424952
step: 9900 | loss: 4.390914359
step: 9910 | loss: 4.388404091
step: 9920 | loss: 4.385894147
step: 9930 | loss: 4.383384521
step: 9940 | loss: 4.380875212
step: 9950 | loss: 4.378366217
step: 9960 | loss: 4.375857532
step: 9970 | loss: 4.373349154
step: 9980 | loss: 4.370841080
step: 9990 | loss: 4.368333308
step: 10000 | loss: 4.365825834
step: 10010 | loss: 4.363318655
step: 10020 | loss: 4.360811768
step: 10030 | loss: 4.358305170
step: 10040 | loss: 4.355798859
step: 10050 | loss: 4.353292830
step: 10060 | loss: 4.350787082
step: 10070 | loss: 4.348281612
step: 10080 | loss: 4.345776416
step: 10090 | loss: 4.343271491
step: 10100 | loss: 4.340766835
step: 10110 | loss: 4.338262445
step: 10120 | loss: 4.335758317
step: 10130 | loss: 4.333254449
step: 10140 | loss: 4.330750839
step: 10150 | loss: 4.328247482
step: 10160 | loss: 4.325744377
step: 10170 | loss: 4.323241521
step: 10180 | loss: 4.320738910
step: 10190 | loss: 4.318236542
step: 10200 | loss: 4.315734414
step: 10210 | loss: 4.313232523
step: 10220 | loss: 4.310730867
step: 10230 | loss: 4.308229442
step: 10240 | loss: 4.305728246
step: 10250 | loss: 4.303227277
step: 10260 | loss: 4.300726531
step: 10270 | loss: 4.298226006
step: 10280 | loss: 4.295725699
step: 10290 | loss: 4.293225607
step: 10300 | loss: 4.290725728
step: 10310 | loss: 4.288226059
step: 10320 | loss: 4.285726597
step: 10330 | loss: 4.283227340
step: 10340 | loss: 4.280728285
step: 10350 | loss: 4.278229429
step: 10360 | loss: 4.275730771
step: 10370 | loss: 4.273232306
step: 10380 | loss: 4.270734034
step: 10390 | loss: 4.268235950
step: 10400 | loss: 4.265738053
step: 10410 | loss: 4.263240340
step: 10420 | loss: 4.260742809
step: 10430 | loss: 4.258245457
step: 10440 | loss: 4.255748281
step: 10450 | loss: 4.253251280
step: 10460 | loss: 4.250754450
step: 10470 | loss: 4.248257789
step: 10480 | loss: 4.245761295
step: 10490 | loss: 4.243264966
step: 10500 | loss: 4.240768798
step: 10510 | loss: 4.238272791
step: 10520 | loss: 4.235776940
step: 10530 | loss: 4.233281245
step: 10540 | loss: 4.230785702
step: 10550 | loss: 4.228290309
step: 10560 | loss: 4.225795064
step: 10570 | loss: 4.223299966
step: 10580 | loss: 4.220805010
step: 10590 | loss: 4.218310196
step: 10600 | loss: 4.215815521
step: 10610 | loss: 4.213320983
step: 10620 | loss: 4.210826580
step: 10630 | loss: 4.208332309
step: 10640 | loss: 4.205838169
step: 10650 | loss: 4.203344157
step: 10660 | loss: 4.200850271
step: 10670 | loss: 4.198356509
step: 10680 | loss: 4.195862869
step: 10690 | loss: 4.193369349
step: 10700 | loss: 4.190875948
step: 10710 | loss: 4.188382662
step: 10720 | loss: 4.185889490
step: 10730 | loss: 4.183396430
step: 10740 | loss: 4.180903480
step: 10750 | loss: 4.178410639
step: 10760 | loss: 4.175917904
step: 10770 | loss: 4.173425273
step: 10780 | loss: 4.170932744
step: 10790 | loss: 4.168440317
step: 10800 | loss: 4.165947988
step: 10810 | loss: 4.163455756
step: 10820 | loss: 4.160963619
step: 10830 | loss: 4.158471576
step: 10840 | loss: 4.155979625
step: 10850 | loss: 4.153487764
step: 10860 | loss: 4.150995991
step: 10870 | loss: 4.148504305
step: 10880 | loss: 4.146012704
step: 10890 | loss: 4.143521186
step: 10900 | loss: 4.141029750
step: 10910 | loss: 4.138538395
step: 10920 | loss: 4.136047118
step: 10930 | loss: 4.133555918
step: 10940 | loss: 4.131064794
step: 10950 | loss: 4.128573743
step: 10960 | loss: 4.126082766
step: 10970 | loss: 4.123591859
step: 10980 | loss: 4.121101022
step: 10990 | loss: 4.118610254
step: 11000 | loss: 4.116119552
step: 11010 | loss: 4.113628916
step: 11020 | loss: 4.111138344
step: 11030 | loss: 4.108647834
step: 11040 | loss: 4.106157387
step: 11050 | loss: 4.103666999
step: 11060 | loss: 4.101176670
step: 11070 | loss: 4.098686399
step: 11080 | loss: 4.096196185
step: 11090 | loss: 4.093706025
step: 11100 | loss: 4.091215920
step: 11110 | loss: 4.088725867
step: 11120 | loss: 4.086235866
step: 11130 | loss: 4.083745916
step: 11140 | loss: 4.081256015
step: 11150 | loss: 4.078766163
step: 11160 | loss: 4.076276358
step: 11170 | loss: 4.073786599
step: 11180 | loss: 4.071296885
step: 11190 | loss: 4.068807216
step: 11200 | loss: 4.066317589
step: 11210 | loss: 4.063828005
step: 11220 | loss: 4.061338462
step: 11230 | loss: 4.058848960
step: 11240 | loss: 4.056359497
step: 11250 | loss: 4.053870072
step: 11260 | loss: 4.051380685
step: 11270 | loss: 4.048891335
step: 11280 | loss: 4.046402020
step: 11290 | loss: 4.043912741
step: 11300 | loss: 4.041423496
step: 11310 | loss: 4.038934284
step: 11320 | loss: 4.036445105
step: 11330 | loss: 4.033955958
step: 11340 | loss: 4.031466842
step: 11350 | loss: 4.028977757
step: 11360 | loss: 4.026488701
step: 11370 | loss: 4.023999674
step: 11380 | loss: 4.021510676
step: 11390 | loss: 4.019021705
step: 11400 | loss: 4.016532761
step: 11410 | loss: 4.014043844
step: 11420 | loss: 4.011554952
step: 11430 | loss: 4.009066086
step: 11440 | loss: 4.006577244
step: 11450 | loss: 4.004088426
step: 11460 | loss: 4.001599631
step: 11470 | loss: 3.999110859
step: 11480 | loss: 3.996622109
step: 11490 | loss: 3.994133382
step: 11500 | loss: 3.991644675
step: 11510 | loss: 3.989155989
step: 11520 | loss: 3.986667324
step: 11530 | loss: 3.984178678
step: 11540 | loss: 3.981690052
step: 11550 | loss: 3.979201444
step: 11560 | loss: 3.976712855
step: 11570 | loss: 3.974224284
step: 11580 | loss: 3.971735730
step: 11590 | loss: 3.969247194
step: 11600 | loss: 3.966758674
step: 11610 | loss: 3.964270171
step: 11620 | loss: 3.961781684
step: 11630 | loss: 3.959293213
step: 11640 | loss: 3.956804756
step: 11650 | loss: 3.954316315
step: 11660 | loss: 3.951827888
step: 11670 | loss: 3.949339476
step: 11680 | loss: 3.946851077
step: 11690 | loss: 3.944362693
step: 11700 | loss: 3.941874321
step: 11710 | loss: 3.939385963
step: 11720 | loss: 3.936897617
step: 11730 | loss: 3.934409284
step: 11740 | loss: 3.931920963
step: 11750 | loss: 3.929432654
step: 11760 | loss: 3.926944357
step: 11770 | loss: 3.924456071
step: 11780 | loss: 3.921967796
step: 11790 | loss: 3.919479533
step: 11800 | loss: 3.916991280
step: 11810 | loss: 3.914503038
step: 11820 | loss: 3.912014806
step: 11830 | loss: 3.909526584
step: 11840 | loss: 3.907038372
step: 11850 | loss: 3.904550170
step: 11860 | loss: 3.902061977
step: 11870 | loss: 3.899573794
step: 11880 | loss: 3.897085620
step: 11890 | loss: 3.894597455
step: 11900 | loss: 3.892109298
step: 11910 | loss: 3.889621151
step: 11920 | loss: 3.887133011
step: 11930 | loss: 3.884644881
step: 11940 | loss: 3.882156758
step: 11950 | loss: 3.879668643
step: 11960 | loss: 3.877180537
step: 11970 | loss: 3.874692438
step: 11980 | loss: 3.872204346
step: 11990 | loss: 3.869716263
step: 12000 | loss: 3.867228186
step: 12010 | loss: 3.864740117
step: 12020 | loss: 3.862252055
step: 12030 | loss: 3.859764000
step: 12040 | loss: 3.857275952
step: 12050 | loss: 3.854787910
step: 12060 | loss: 3.852299876
step: 12070 | loss: 3.849811848
step: 12080 | loss: 3.847323826
step: 12090 | loss: 3.844835811
step: 12100 | loss: 3.842347802
step: 12110 | loss: 3.839859799
step: 12120 | loss: 3.837371802
step: 12130 | loss: 3.834883811
step: 12140 | loss: 3.832395827
step: 12150 | loss: 3.829907848
step: 12160 | loss: 3.827419875
step: 12170 | loss: 3.824931907
step: 12180 | loss: 3.822443945
step: 12190 | loss: 3.819955989
step: 12200 | loss: 3.817468038
step: 12210 | loss: 3.814980092
step: 12220 | loss: 3.812492152
step: 12230 | loss: 3.810004217
step: 12240 | loss: 3.807516287
step: 12250 | loss: 3.805028362
step: 12260 | loss: 3.802540442
step: 12270 | loss: 3.800052527
step: 12280 | loss: 3.797564617
step: 12290 | loss: 3.795076712
step: 12300 | loss: 3.792588812
step: 12310 | loss: 3.790100916
step: 12320 | loss: 3.787613025
step: 12330 | loss: 3.785125139
step: 12340 | loss: 3.782637257
step: 12350 | loss: 3.780149380
step: 12360 | loss: 3.777661507
step: 12370 | loss: 3.775173639
step: 12380 | loss: 3.772685775
step: 12390 | loss: 3.770197915
step: 12400 | loss: 3.767710059
step: 12410 | loss: 3.765222208
step: 12420 | loss: 3.762734361
step: 12430 | loss: 3.760246518
step: 12440 | loss: 3.757758679
step: 12450 | loss: 3.755270844
step: 12460 | loss: 3.752783013
step: 12470 | loss: 3.750295186
step: 12480 | loss: 3.747807362
step: 12490 | loss: 3.745319543
step: 12500 | loss: 3.742831727
step: 12510 | loss: 3.740343916
step: 12520 | loss: 3.737856107
step: 12530 | loss: 3.735368303
step: 12540 | loss: 3.732880502
step: 12550 | loss: 3.730392705
step: 12560 | loss: 3.727904911
step: 12570 | loss: 3.725417121
step: 12580 | loss: 3.722929335
step: 12590 | loss: 3.720441552
step: 12600 | loss: 3.717953772
step: 12610 | loss: 3.715465995
step: 12620 | loss: 3.712978222
step: 12630 | loss: 3.710490453
step: 12640 | loss: 3.708002686
step: 12650 | loss: 3.705514923
step: 12660 | loss: 3.703027163
step: 12670 | loss: 3.700539406
step: 12680 | loss: 3.698051653
step: 12690 | loss: 3.695563902
step: 12700 | loss: 3.693076155
step: 12710 | loss: 3.690588410
step: 12720 | loss: 3.688100669
step: 12730 | loss: 3.685612930
step: 12740 | loss: 3.683125195
step: 12750 | loss: 3.680637462
step: 12760 | loss: 3.678149733
step: 12770 | loss: 3.675662006
step: 12780 | loss: 3.673174282
step: 12790 | loss: 3.670686561
step: 12800 | loss: 3.668198843
step: 12810 | loss: 3.665711127
step: 12820 | loss: 3.663223414
step: 12830 | loss: 3.660735704
step: 12840 | loss: 3.658247997
step: 12850 | loss: 3.655760292
step: 12860 | loss: 3.653272590
step: 12870 | loss: 3.650784890
step: 12880 | loss: 3.648297193
step: 12890 | loss: 3.645809499
step: 12900 | loss: 3.643321807
step: 12910 | loss: 3.640834117
step: 12920 | loss: 3.638346430
step: 12930 | loss: 3.635858745
step: 12940 | loss: 3.633371063
step: 12950 | loss: 3.630883383
step: 12960 | loss: 3.628395706
step: 12970 | loss: 3.625908031
step: 12980 | loss: 3.623420358
step: 12990 | loss: 3.620932688
step: 13000 | loss: 3.618445020
step: 13010 | loss: 3.615957354
step: 13020 | loss: 3.613469690
step: 13030 | loss: 3.610982029
step: 13040 | loss: 3.608494369
step: 13050 | loss: 3.606006712
step: 13060 | loss: 3.603519057
step: 13070 | loss: 3.601031404
step: 13080 | loss: 3.598543753
step: 13090 | loss: 3.596056105
step: 13100 | loss: 3.593568458
step: 13110 | loss: 3.591080814
step: 13120 | loss: 3.588593171
step: 13130 | loss: 3.586105530
step: 13140 | loss: 3.583617892
step: 13150 | loss: 3.581130255
step: 13160 | loss: 3.578642620
step: 13170 | loss: 3.576154988
step: 13180 | loss: 3.573667357
step: 13190 | loss: 3.571179728
step: 13200 | loss: 3.568692101
step: 13210 | loss: 3.566204475
step: 13220 | loss: 3.563716852
step: 13230 | loss: 3.561229230
step: 13240 | loss: 3.558741610
step: 13250 | loss: 3.556253992
step: 13260 | loss: 3.553766376
step: 13270 | loss: 3.551278761
step: 13280 | loss: 3.548791148
step: 13290 | loss: 3.546303537
step: 13300 | loss: 3.543815928
step: 13310 | loss: 3.541328320
step: 13320 | loss: 3.538840714
step: 13330 | loss: 3.536353109
step: 13340 | loss: 3.533865506
step: 13350 | loss: 3.531377905
step: 13360 | loss: 3.528890305
step: 13370 | loss: 3.526402707
step: 13380 | loss: 3.523915110
step: 13390 | loss: 3.521427515
step: 13400 | loss: 3.518939922
step: 13410 | loss: 3.516452330
step: 13420 | loss: 3.513964739
step: 13430 | loss: 3.511477150
step: 13440 | loss: 3.508989562
step: 13450 | loss: 3.506501976
step: 13460 | loss: 3.504014391
step: 13470 | loss: 3.501526808
step: 13480 | loss: 3.499039226
step: 13490 | loss: 3.496551646
step: 13500 | loss: 3.494064067
step: 13510 | loss: 3.491576489
step: 13520 | loss: 3.489088912
step: 13530 | loss: 3.486601337
step: 13540 | loss: 3.484113764
step: 13550 | loss: 3.481626191
step: 13560 | loss: 3.479138620
step: 13570 | loss: 3.476651050
step: 13580 | loss: 3.474163482
step: 13590 | loss: 3.471675914
step: 13600 | loss: 3.469188348
step: 13610 | loss: 3.466700783
step: 13620 | loss: 3.464213220
step: 13630 | loss: 3.461725657
step: 13640 | loss: 3.459238096
step: 13650 | loss: 3.456750536
step: 13660 | loss: 3.454262977
step: 13670 | loss: 3.451775420
step: 13680 | loss: 3.449287863
step: 13690 | loss: 3.446800308
step: 13700 | loss: 3.444312754
step: 13710 | loss: 3.441825200
step: 13720 | loss: 3.439337648
step: 13730 | loss: 3.436850097
step: 13740 | loss: 3.434362548
step: 13750 | loss: 3.431874999
step: 13760 | loss: 3.429387451
step: 13770 | loss: 3.426899904
step: 13780 | loss: 3.424412359
step: 13790 | loss: 3.421924814
step: 13800 | loss: 3.419437271
step: 13810 | loss: 3.416949728
step: 13820 | loss: 3.414462187
step: 13830 | loss: 3.411974646
step: 13840 | loss: 3.409487106
step: 13850 | loss: 3.406999568
step: 13860 | loss: 3.404512030
step: 13870 | loss: 3.402024494
step: 13880 | loss: 3.399536958
step: 13890 | loss: 3.397049423
step: 13900 | loss: 3.394561889
step: 13910 | loss: 3.392074356
step: 13920 | loss: 3.389586824
step: 13930 | loss: 3.387099293
step: 13940 | loss: 3.384611763
step: 13950 | loss: 3.382124233
step: 13960 | loss: 3.379636705
step: 13970 | loss: 3.377149177
step: 13980 | loss: 3.374661650
step: 13990 | loss: 3.372174124
step: 14000 | loss: 3.369686599
step: 14010 | loss: 3.367199075
step: 14020 | loss: 3.364711551
step: 14030 | loss: 3.362224029
step: 14040 | loss: 3.359736507
step: 14050 | loss: 3.357248986
step: 14060 | loss: 3.354761465
step: 14070 | loss: 3.352273946
step: 14080 | loss: 3.349786427
step: 14090 | loss: 3.347298909
step: 14100 | loss: 3.344811392
step: 14110 | loss: 3.342323875
step: 14120 | loss: 3.339836360
step: 14130 | loss: 3.337348845
step: 14140 | loss: 3.334861330
step: 14150 | loss: 3.332373817
step: 14160 | loss: 3.329886304
step: 14170 | loss: 3.327398792
step: 14180 | loss: 3.324911281
step: 14190 | loss: 3.322423770
step: 14200 | loss: 3.319936260
step: 14210 | loss: 3.317448750
step: 14220 | loss: 3.314961242
step: 14230 | loss: 3.312473734
step: 14240 | loss: 3.309986226
step: 14250 | loss: 3.307498720
step: 14260 | loss: 3.305011213
step: 14270 | loss: 3.302523708
step: 14280 | loss: 3.300036203
step: 14290 | loss: 3.297548699
step: 14300 | loss: 3.295061195
step: 14310 | loss: 3.292573692
step: 14320 | loss: 3.290086190
step: 14330 | loss: 3.287598688
step: 14340 | loss: 3.285111187
step: 14350 | loss: 3.282623687
step: 14360 | loss: 3.280136187
step: 14370 | loss: 3.277648687
step: 14380 | loss: 3.275161188
step: 14390 | loss: 3.272673690
step: 14400 | loss: 3.270186192
step: 14410 | loss: 3.267698695
step: 14420 | loss: 3.265211199
step: 14430 | loss: 3.262723703
step: 14440 | loss: 3.260236207
step: 14450 | loss: 3.257748712
step: 14460 | loss: 3.255261218
step: 14470 | loss: 3.252773724
step: 14480 | loss: 3.250286230
step: 14490 | loss: 3.247798737
step: 14500 | loss: 3.245311245
step: 14510 | loss: 3.242823753
step: 14520 | loss: 3.240336262
step: 14530 | loss: 3.237848771
step: 14540 | loss: 3.235361280
step: 14550 | loss: 3.232873790
step: 14560 | loss: 3.230386301
step: 14570 | loss: 3.227898812
step: 14580 | loss: 3.225411324
step: 14590 | loss: 3.222923835
step: 14600 | loss: 3.220436348
step: 14610 | loss: 3.217948861
step: 14620 | loss: 3.215461374
step: 14630 | loss: 3.212973888
step: 14640 | loss: 3.210486402
step: 14650 | loss: 3.207998917
step: 14660 | loss: 3.205511432
step: 14670 | loss: 3.203023947
step: 14680 | loss: 3.200536463
step: 14690 | loss: 3.198048979
step: 14700 | loss: 3.195561496
step: 14710 | loss: 3.193074013
step: 14720 | loss: 3.190586531
step: 14730 | loss: 3.188099049
step: 14740 | loss: 3.185611567
step: 14750 | loss: 3.183124086
step: 14760 | loss: 3.180636605
step: 14770 | loss: 3.178149125
step: 14780 | loss: 3.175661645
step: 14790 | loss: 3.173174165
step: 14800 | loss: 3.170686686
step: 14810 | loss: 3.168199207
step: 14820 | loss: 3.165711728
step: 14830 | loss: 3.163224250
step: 14840 | loss: 3.160736772
step: 14850 | loss: 3.158249294
step: 14860 | loss: 3.155761817
step: 14870 | loss: 3.153274341
step: 14880 | loss: 3.150786864
step: 14890 | loss: 3.148299388
step: 14900 | loss: 3.145811912
step: 14910 | loss: 3.143324437
step: 14920 | loss: 3.140836962
step: 14930 | loss: 3.138349487
step: 14940 | loss: 3.135862012
step: 14950 | loss: 3.133374538
step: 14960 | loss: 3.130887065
step: 14970 | loss: 3.128399591
step: 14980 | loss: 3.125912118
step: 14990 | loss: 3.123424645
step: 15000 | loss: 3.120937173
step: 15010 | loss: 3.118449700
step: 15020 | loss: 3.115962228
step: 15030 | loss: 3.113474757
step: 15040 | loss: 3.110987285
step: 15050 | loss: 3.108499814
step: 15060 | loss: 3.106012344
step: 15070 | loss: 3.103524873
step: 15080 | loss: 3.101037403
step: 15090 | loss: 3.098549933
step: 15100 | loss: 3.096062463
step: 15110 | loss: 3.093574994
step: 15120 | loss: 3.091087525
step: 15130 | loss: 3.088600056
step: 15140 | loss: 3.086112587
step: 15150 | loss: 3.083625119
step: 15160 | loss: 3.081137651
step: 15170 | loss: 3.078650183
step: 15180 | loss: 3.076162716
step: 15190 | loss: 3.073675249
step: 15200 | loss: 3.071187782
step: 15210 | loss: 3.068700315
step: 15220 | loss: 3.066212848
step: 15230 | loss: 3.063725382
step: 15240 | loss: 3.061237916
step: 15250 | loss: 3.058750450
step: 15260 | loss: 3.056262985
step: 15270 | loss: 3.053775519
step: 15280 | loss: 3.051288054
step: 15290 | loss: 3.048800590
step: 15300 | loss: 3.046313125
step: 15310 | loss: 3.043825661
step: 15320 | loss: 3.041338196
step: 15330 | loss: 3.038850732
step: 15340 | loss: 3.036363269
step: 15350 | loss: 3.033875805
step: 15360 | loss: 3.031388342
step: 15370 | loss: 3.028900879
step: 15380 | loss: 3.026413416
step: 15390 | loss: 3.023925953
step: 15400 | loss: 3.021438491
step: 15410 | loss: 3.018951028
step: 15420 | loss: 3.016463566
step: 15430 | loss: 3.013976105
step: 15440 | loss: 3.011488643
step: 15450 | loss: 3.009001181
step: 15460 | loss: 3.006513720
step: 15470 | loss: 3.004026259
step: 15480 | loss: 3.001538798
step: 15490 | loss: 2.999051338
step: 15500 | loss: 2.996563877
step: 15510 | loss: 2.994076417
step: 15520 | loss: 2.991588957
step: 15530 | loss: 2.989101497
step: 15540 | loss: 2.986614037
step: 15550 | loss: 2.984126577
step: 15560 | loss: 2.981639118
step: 15570 | loss: 2.979151658
step: 15580 | loss: 2.976664199
step: 15590 | loss: 2.974176740
step: 15600 | loss: 2.971689282
step: 15610 | loss: 2.969201823
step: 15620 | loss: 2.966714365
step: 15630 | loss: 2.964226907
step: 15640 | loss: 2.961739448
step: 15650 | loss: 2.959251990
step: 15660 | loss: 2.956764533
step: 15670 | loss: 2.954277075
step: 15680 | loss: 2.951789618
step: 15690 | loss: 2.949302160
step: 15700 | loss: 2.946814703
step: 15710 | loss: 2.944327246
step: 15720 | loss: 2.941839789
step: 15730 | loss: 2.939352333
step: 15740 | loss: 2.936864876
step: 15750 | loss: 2.934377420
step: 15760 | loss: 2.931889963
step: 15770 | loss: 2.929402507
step: 15780 | loss: 2.926915051
step: 15790 | loss: 2.924427595
step: 15800 | loss: 2.921940140
step: 15810 | loss: 2.919452684
step: 15820 | loss: 2.916965229
step: 15830 | loss: 2.914477773
step: 15840 | loss: 2.911990318
step: 15850 | loss: 2.909502863
step: 15860 | loss: 2.907015408
step: 15870 | loss: 2.904527954
step: 15880 | loss: 2.902040499
step: 15890 | loss: 2.899553044
step: 15900 | loss: 2.897065590
step: 15910 | loss: 2.894578136
step: 15920 | loss: 2.892090682
step: 15930 | loss: 2.889603228
step: 15940 | loss: 2.887115774
step: 15950 | loss: 2.884628320
step: 15960 | loss: 2.882140866
step: 15970 | loss: 2.879653413
step: 15980 | loss: 2.877165959
step: 15990 | loss: 2.874678506
step: 16000 | loss: 2.872191053
step: 16010 | loss: 2.869703600
step: 16020 | loss: 2.867216147
step: 16030 | loss: 2.864728694
step: 16040 | loss: 2.862241241
step: 16050 | loss: 2.859753788
step: 16060 | loss: 2.857266336
step: 16070 | loss: 2.854778883
step: 16080 | loss: 2.852291431
step: 16090 | loss: 2.849803979
step: 16100 | loss: 2.847316527
step: 16110 | loss: 2.844829074
step: 16120 | loss: 2.842341623
step: 16130 | loss: 2.839854171
step: 16140 | loss: 2.837366719
step: 16150 | loss: 2.834879267
step: 16160 | loss: 2.832391816
step: 16170 | loss: 2.829904364
step: 16180 | loss: 2.827416913
step: 16190 | loss: 2.824929462
step: 16200 | loss: 2.822442011
step: 16210 | loss: 2.819954559
step: 16220 | loss: 2.817467108
step: 16230 | loss: 2.814979658
step: 16240 | loss: 2.812492207
step: 16250 | loss: 2.810004756
step: 16260 | loss: 2.807517305
step: 16270 | loss: 2.805029855
step: 16280 | loss: 2.802542404
step: 16290 | loss: 2.800054954
step: 16300 | loss: 2.797567504
step: 16310 | loss: 2.795080053
step: 16320 | loss: 2.792592603
step: 16330 | loss: 2.790105153
step: 16340 | loss: 2.787617703
step: 16350 | loss: 2.785130253
step: 16360 | loss: 2.782642804
step: 16370 | loss: 2.780155354
step: 16380 | loss: 2.777667904
step: 16390 | loss: 2.775180455
step: 16400 | loss: 2.772693005
step: 16410 | loss: 2.770205556
step: 16420 | loss: 2.767718106
step: 16430 | loss: 2.765230657
step: 16440 | loss: 2.762743208
step: 16450 | loss: 2.760255759
step: 16460 | loss: 2.757768310
step: 16470 | loss: 2.755280861
step: 16480 | loss: 2.752793412
step: 16490 | loss: 2.750305963
step: 16500 | loss: 2.747818514
step: 16510 | loss: 2.745331065
step: 16520 | loss: 2.742843617
step: 16530 | loss: 2.740356168
step: 16540 | loss: 2.737868720
step: 16550 | loss: 2.735381271
step: 16560 | loss: 2.732893823
step: 16570 | loss: 2.730406374
step: 16580 | loss: 2.727918926
step: 16590 | loss: 2.725431478
step: 16600 | loss: 2.722944030
step: 16610 | loss: 2.720456582
step: 16620 | loss: 2.717969134
step: 16630 | loss: 2.715481686
step: 16640 | loss: 2.712994238
step: 16650 | loss: 2.710506790
step: 16660 | loss: 2.708019342
step: 16670 | loss: 2.705531895
step: 16680 | loss: 2.703044447
step: 16690 | loss: 2.700556999
step: 16700 | loss: 2.698069552
step: 16710 | loss: 2.695582104
step: 16720 | loss: 2.693094657
step: 16730 | loss: 2.690607209
step: 16740 | loss: 2.688119762
step: 16750 | loss: 2.685632315
step: 16760 | loss: 2.683144868
step: 16770 | loss: 2.680657420
step: 16780 | loss: 2.678169973
step: 16790 | loss: 2.675682526
step: 16800 | loss: 2.673195079
step: 16810 | loss: 2.670707632
step: 16820 | loss: 2.668220185
step: 16830 | loss: 2.665732738
step: 16840 | loss: 2.663245292
step: 16850 | loss: 2.660757845
step: 16860 | loss: 2.658270398
step: 16870 | loss: 2.655782951
step: 16880 | loss: 2.653295505
step: 16890 | loss: 2.650808058
step: 16900 | loss: 2.648320612
step: 16910 | loss: 2.645833165
step: 16920 | loss: 2.643345719
step: 16930 | loss: 2.640858272
step: 16940 | loss: 2.638370826
step: 16950 | loss: 2.635883380
step: 16960 | loss: 2.633395933
step: 16970 | loss: 2.630908487
step: 16980 | loss: 2.628421041
step: 16990 | loss: 2.625933595
step: 17000 | loss: 2.623446149
step: 17010 | loss: 2.620958703
step: 17020 | loss: 2.618471257
step: 17030 | loss: 2.615983811
step: 17040 | loss: 2.613496365
step: 17050 | loss: 2.611008919
step: 17060 | loss: 2.608521473
step: 17070 | loss: 2.606034027
step: 17080 | loss: 2.603546581
step: 17090 | loss: 2.601059136
step: 17100 | loss: 2.598571690
step: 17110 | loss: 2.596084244
step: 17120 | loss: 2.593596799
step: 17130 | loss: 2.591109353
step: 17140 | loss: 2.588621907
step: 17150 | loss: 2.586134462
step: 17160 | loss: 2.583647016
step: 17170 | loss: 2.581159571
step: 17180 | loss: 2.578672126
step: 17190 | loss: 2.576184680
step: 17200 | loss: 2.573697235
step: 17210 | loss: 2.571209789
step: 17220 | loss: 2.568722344
step: 17230 | loss: 2.566234899
step: 17240 | loss: 2.563747454
step: 17250 | loss: 2.561260008
step: 17260 | loss: 2.558772563
step: 17270 | loss: 2.556285118
step: 17280 | loss: 2.553797673
step: 17290 | loss: 2.551310228
step: 17300 | loss: 2.548822783
step: 17310 | loss: 2.546335338
step: 17320 | loss: 2.543847893
step: 17330 | loss: 2.541360448
step: 17340 | loss: 2.538873003
step: 17350 | loss: 2.536385558
step: 17360 | loss: 2.533898113
step: 17370 | loss: 2.531410669
step: 17380 | loss: 2.528923224
step: 17390 | loss: 2.526435779
step: 17400 | loss: 2.523948334
step: 17410 | loss: 2.521460890
step: 17420 | loss: 2.518973445
step: 17430 | loss: 2.516486000
step: 17440 | loss: 2.513998556
step: 17450 | loss: 2.511511111
step: 17460 | loss: 2.509023666
step: 17470 | loss: 2.506536222
step: 17480 | loss: 2.504048777
step: 17490 | loss: 2.501561333
step: 17500 | loss: 2.499073888
step: 17510 | loss: 2.496586444
step: 17520 | loss: 2.494099000
step: 17530 | loss: 2.491611555
step: 17540 | loss: 2.489124111
step: 17550 | loss: 2.486636666
step: 17560 | loss: 2.484149222
step: 17570 | loss: 2.481661778
step: 17580 | loss: 2.479174333
step: 17590 | loss: 2.476686889
step: 17600 | loss: 2.474199445
step: 17610 | loss: 2.471712001
step: 17620 | loss: 2.469224557
step: 17630 | loss: 2.466737112
step: 17640 | loss: 2.464249668
step: 17650 | loss: 2.461762224
step: 17660 | loss: 2.459274780
step: 17670 | loss: 2.456787336
step: 17680 | loss: 2.454299892
step: 17690 | loss: 2.451812448
step: 17700 | loss: 2.449325004
step: 17710 | loss: 2.446837560
step: 17720 | loss: 2.444350116
step: 17730 | loss: 2.441862672
step: 17740 | loss: 2.439375228
step: 17750 | loss: 2.436887784
step: 17760 | loss: 2.434400340
step: 17770 | loss: 2.431912896
step: 17780 | loss: 2.429425452
step: 17790 | loss: 2.426938008
step: 17800 | loss: 2.424450565
step: 17810 | loss: 2.421963121
step: 17820 | loss: 2.419475677
step: 17830 | loss: 2.416988233
step: 17840 | loss: 2.414500790
step: 17850 | loss: 2.412013346
step: 17860 | loss: 2.409525902
step: 17870 | loss: 2.407038458
step: 17880 | loss: 2.404551015
step: 17890 | loss: 2.402063571
step: 17900 | loss: 2.399576127
step: 17910 | loss: 2.397088684
step: 17920 | loss: 2.394601240
step: 17930 | loss: 2.392113797
step: 17940 | loss: 2.389626353
step: 17950 | loss: 2.387138909
step: 17960 | loss: 2.384651466
step: 17970 | loss: 2.382164022
step: 17980 | loss: 2.379676579
step: 17990 | loss: 2.377189135
step: 18000 | loss: 2.374701692
step: 18010 | loss: 2.372214248
step: 18020 | loss: 2.369726805
step: 18030 | loss: 2.367239361
step: 18040 | loss: 2.364751918
step: 18050 | loss: 2.362264475
step: 18060 | loss: 2.359777031
step: 18070 | loss: 2.357289588
step: 18080 | loss: 2.354802144
step: 18090 | loss: 2.352314701
step: 18100 | loss: 2.349827258
step: 18110 | loss: 2.347339814
step: 18120 | loss: 2.344852371
step: 18130 | loss: 2.342364928
step: 18140 | loss: 2.339877484
step: 18150 | loss: 2.337390041
step: 18160 | loss: 2.334902598
step: 18170 | loss: 2.332415155
step: 18180 | loss: 2.329927711
step: 18190 | loss: 2.327440268
step: 18200 | loss: 2.324952825
step: 18210 | loss: 2.322465382
step: 18220 | loss: 2.319977939
step: 18230 | loss: 2.317490495
step: 18240 | loss: 2.315003052
step: 18250 | loss: 2.312515609
step: 18260 | loss: 2.310028166
step: 18270 | loss: 2.307540723
step: 18280 | loss: 2.305053280
step: 18290 | loss: 2.302565837
step: 18300 | loss: 2.300078394
step: 18310 | loss: 2.297590950
step: 18320 | loss: 2.295103507
step: 18330 | loss: 2.292616064
step: 18340 | loss: 2.290128621
step: 18350 | loss: 2.287641178
step: 18360 | loss: 2.285153735
step: 18370 | loss: 2.282666292
step: 18380 | loss: 2.280178849
step: 18390 | loss: 2.277691406
step: 18400 | loss: 2.275203963
step: 18410 | loss: 2.272716520
step: 18420 | loss: 2.270229077
step: 18430 | loss: 2.267741634
step: 18440 | loss: 2.265254191
step: 18450 | loss: 2.262766748
step: 18460 | loss: 2.260279305
step: 18470 | loss: 2.257791863
step: 18480 | loss: 2.255304420
step: 18490 | loss: 2.252816977
step: 18500 | loss: 2.250329534
step: 18510 | loss: 2.247842091
step: 18520 | loss: 2.245354648
step: 18530 | loss: 2.242867205
step: 18540 | loss: 2.240379762
step: 18550 | loss: 2.237892319
step: 18560 | loss: 2.235404877
step: 18570 | loss: 2.232917434
step: 18580 | loss: 2.230429991
step: 18590 | loss: 2.227942548
step: 18600 | loss: 2.225455105
step: 18610 | loss: 2.222967663
step: 18620 | loss: 2.220480220
step: 18630 | loss: 2.217992777
step: 18640 | loss: 2.215505334
step: 18650 | loss: 2.213017891
step: 18660 | loss: 2.210530449
step: 18670 | loss: 2.208043006
step: 18680 | loss: 2.205555563
step: 18690 | loss: 2.203068121
step: 18700 | loss: 2.200580678
step: 18710 | loss: 2.198093235
step: 18720 | loss: 2.195605792
step: 18730 | loss: 2.193118350
step: 18740 | loss: 2.190630907
step: 18750 | loss: 2.188143464
step: 18760 | loss: 2.185656022
step: 18770 | loss: 2.183168579
step: 18780 | loss: 2.180681136
step: 18790 | loss: 2.178193694
step: 18800 | loss: 2.175706251
step: 18810 | loss: 2.173218808
step: 18820 | loss: 2.170731366
step: 18830 | loss: 2.168243923
step: 18840 | loss: 2.165756480
step: 18850 | loss: 2.163269038
step: 18860 | loss: 2.160781595
step: 18870 | loss: 2.158294153
step: 18880 | loss: 2.155806710
step: 18890 | loss: 2.153319267
step: 18900 | loss: 2.150831825
step: 18910 | loss: 2.148344382
step: 18920 | loss: 2.145856940
step: 18930 | loss: 2.143369497
step: 18940 | loss: 2.140882055
step: 18950 | loss: 2.138394612
step: 18960 | loss: 2.135907169
step: 18970 | loss: 2.133419727
step: 18980 | loss: 2.130932284
step: 18990 | loss: 2.128444842
step: 19000 | loss: 2.125957399
step: 19010 | loss: 2.123469957
step: 19020 | loss: 2.120982514
step: 19030 | loss: 2.118495072
step: 19040 | loss: 2.116007629
step: 19050 | loss: 2.113520187
step: 19060 | loss: 2.111032744
step: 19070 | loss: 2.108545302
step: 19080 | loss: 2.106057859
step: 19090 | loss: 2.103570417
step: 19100 | loss: 2.101082974
step: 19110 | loss: 2.098595532
step: 19120 | loss: 2.096108089
step: 19130 | loss: 2.093620647
step: 19140 | loss: 2.091133204
step: 19150 | loss: 2.088645762
step: 19160 | loss: 2.086158320
step: 19170 | loss: 2.083670877
step: 19180 | loss: 2.081183435
step: 19190 | loss: 2.078695992
step: 19200 | loss: 2.076208550
step: 19210 | loss: 2.073721107
step: 19220 | loss: 2.071233665
step: 19230 | loss: 2.068746223
step: 19240 | loss: 2.066258780
step: 19250 | loss: 2.063771338
step: 19260 | loss: 2.061283895
step: 19270 | loss: 2.058796453
step: 19280 | loss: 2.056309011
step: 19290 | loss: 2.053821568
step: 19300 | loss: 2.051334126
step: 19310 | loss: 2.048846683
step: 19320 | loss: 2.046359241
step: 19330 | loss: 2.043871799
step: 19340 | loss: 2.041384356
step: 19350 | loss: 2.038896914
step: 19360 | loss: 2.036409472
step: 19370 | loss: 2.033922029
step: 19380 | loss: 2.031434587
step: 19390 | loss: 2.028947144
step: 19400 | loss: 2.026459702
step: 19410 | loss: 2.023972260
step: 19420 | loss: 2.021484817
step: 19430 | loss: 2.018997375
step: 19440 | loss: 2.016509933
step: 19450 | loss: 2.014022490
step: 19460 | loss: 2.011535048
step: 19470 | loss: 2.009047606
step: 19480 | loss: 2.006560164
step: 19490 | loss: 2.004072721
step: 19500 | loss: 2.001585279
step: 19510 | loss: 1.999097837
step: 19520 | loss: 1.996610394
step: 19530 | loss: 1.994122952
step: 19540 | loss: 1.991635510
step: 19550 | loss: 1.989148067
step: 19560 | loss: 1.986660625
step: 19570 | loss: 1.984173183
step: 19580 | loss: 1.981685741
step: 19590 | loss: 1.979198298
step: 19600 | loss: 1.976710856
step: 19610 | loss: 1.974223414
step: 19620 | loss: 1.971735971
step: 19630 | loss: 1.969248529
step: 19640 | loss: 1.966761087
step: 19650 | loss: 1.964273645
step: 19660 | loss: 1.961786202
step: 19670 | loss: 1.959298760
step: 19680 | loss: 1.956811318
step: 19690 | loss: 1.954323876
step: 19700 | loss: 1.951836433
step: 19710 | loss: 1.949348991
step: 19720 | loss: 1.946861549
step: 19730 | loss: 1.944374107
step: 19740 | loss: 1.941886664
step: 19750 | loss: 1.939399222
step: 19760 | loss: 1.936911780
step: 19770 | loss: 1.934424338
step: 19780 | loss: 1.931936896
step: 19790 | loss: 1.929449453
step: 19800 | loss: 1.926962011
step: 19810 | loss: 1.924474569
step: 19820 | loss: 1.921987127
step: 19830 | loss: 1.919499684
step: 19840 | loss: 1.917012242
step: 19850 | loss: 1.914524800
step: 19860 | loss: 1.912037358
step: 19870 | loss: 1.909549916
step: 19880 | loss: 1.907062473
step: 19890 | loss: 1.904575031
step: 19900 | loss: 1.902087589
step: 19910 | loss: 1.899600147
step: 19920 | loss: 1.897112705
step: 19930 | loss: 1.894625262
step: 19940 | loss: 1.892137820
step: 19950 | loss: 1.889650378
step: 19960 | loss: 1.887162936
step: 19970 | loss: 1.884675494
step: 19980 | loss: 1.882188051
step: 19990 | loss: 1.879700609
step: 20000 | loss: 1.877213167
step: 20010 | loss: 1.874725725
step: 20020 | loss: 1.872238283
step: 20030 | loss: 1.869750841
step: 20040 | loss: 1.867263398
step: 20050 | loss: 1.864775956
step: 20060 | loss: 1.862288514
step: 20070 | loss: 1.859801072
step: 20080 | loss: 1.857313630
step: 20090 | loss: 1.854826188
step: 20100 | loss: 1.852338746
step: 20110 | loss: 1.849851303
step: 20120 | loss: 1.847363861
step: 20130 | loss: 1.844876419
step: 20140 | loss: 1.842388977
step: 20150 | loss: 1.839901535
step: 20160 | loss: 1.837414093
step: 20170 | loss: 1.834926650
step: 20180 | loss: 1.832439208
step: 20190 | loss: 1.829951766
step: 20200 | loss: 1.827464324
step: 20210 | loss: 1.824976882
step: 20220 | loss: 1.822489440
step: 20230 | loss: 1.820001998
step: 20240 | loss: 1.817514556
step: 20250 | loss: 1.815027113
step: 20260 | loss: 1.812539671
step: 20270 | loss: 1.810052229
step: 20280 | loss: 1.807564787
step: 20290 | loss: 1.805077345
step: 20300 | loss: 1.802589903
step: 20310 | loss: 1.800102461
step: 20320 | loss: 1.797615019
step: 20330 | loss: 1.795127576
step: 20340 | loss: 1.792640134
step: 20350 | loss: 1.790152692
step: 20360 | loss: 1.787665250
step: 20370 | loss: 1.785177808
step: 20380 | loss: 1.782690366
step: 20390 | loss: 1.780202924
step: 20400 | loss: 1.777715482
step: 20410 | loss: 1.775228040
step: 20420 | loss: 1.772740597
step: 20430 | loss: 1.770253155
step: 20440 | loss: 1.767765713
step: 20450 | loss: 1.765278271
step: 20460 | loss: 1.762790829
step: 20470 | loss: 1.760303387
step: 20480 | loss: 1.757815945
step: 20490 | loss: 1.755328503
step: 20500 | loss: 1.752841061
step: 20510 | loss: 1.750353619
step: 20520 | loss: 1.747866176
step: 20530 | loss: 1.745378734
step: 20540 | loss: 1.742891292
step: 20550 | loss: 1.740403850
step: 20560 | loss: 1.737916408
step: 20570 | loss: 1.735428966
step: 20580 | loss: 1.732941524
step: 20590 | loss: 1.730454082
step: 20600 | loss: 1.727966640
step: 20610 | loss: 1.725479198
step: 20620 | loss: 1.722991756
step: 20630 | loss: 1.720504314
step: 20640 | loss: 1.718016871
step: 20650 | loss: 1.715529429
step: 20660 | loss: 1.713041987
step: 20670 | loss: 1.710554545
step: 20680 | loss: 1.708067103
step: 20690 | loss: 1.705579661
step: 20700 | loss: 1.703092219
step: 20710 | loss: 1.700604777
step: 20720 | loss: 1.698117335
step: 20730 | loss: 1.695629893
step: 20740 | loss: 1.693142451
step: 20750 | loss: 1.690655009
step: 20760 | loss: 1.688167567
step: 20770 | loss: 1.685680125
step: 20780 | loss: 1.683192682
step: 20790 | loss: 1.680705240
step: 20800 | loss: 1.678217798
step: 20810 | loss: 1.675730356
step: 20820 | loss: 1.673242914
step: 20830 | loss: 1.670755472
step: 20840 | loss: 1.668268030
step: 20850 | loss: 1.665780588
step: 20860 | loss: 1.663293146
step: 20870 | loss: 1.660805704
step: 20880 | loss: 1.658318262
step: 20890 | loss: 1.655830820
step: 20900 | loss: 1.653343378
step: 20910 | loss: 1.650855936
step: 20920 | loss: 1.648368494
step: 20930 | loss: 1.645881052
step: 20940 | loss: 1.643393610
step: 20950 | loss: 1.640906168
step: 20960 | loss: 1.638418725
step: 20970 | loss: 1.635931283
step: 20980 | loss: 1.633443841
step: 20990 | loss: 1.630956399
step: 21000 | loss: 1.628468957
step: 21010 | loss: 1.625981515
step: 21020 | loss: 1.623494073
step: 21030 | loss: 1.621006631
step: 21040 | loss: 1.618519189
step: 21050 | loss: 1.616031747
step: 21060 | loss: 1.613544305
step: 21070 | loss: 1.611056863
step: 21080 | loss: 1.608569421
step: 21090 | loss: 1.606081979
step: 21100 | loss: 1.603594537
step: 21110 | loss: 1.601107095
step: 21120 | loss: 1.598619653
step: 21130 | loss: 1.596132211
step: 21140 | loss: 1.593644769
step: 21150 | loss: 1.591157327
step: 21160 | loss: 1.588669885
step: 21170 | loss: 1.586182443
step: 21180 | loss: 1.583695001
step: 21190 | loss: 1.581207559
step: 21200 | loss: 1.578720117
step: 21210 | loss: 1.576232674
step: 21220 | loss: 1.573745232
step: 21230 | loss: 1.571257790
step: 21240 | loss: 1.568770348
step: 21250 | loss: 1.566282906
step: 21260 | loss: 1.563795464
step: 21270 | loss: 1.561308022
step: 21280 | loss: 1.558820580
step: 21290 | loss: 1.556333138
step: 21300 | loss: 1.553845696
step: 21310 | loss: 1.551358254
step: 21320 | loss: 1.548870812
step: 21330 | loss: 1.546383370
step: 21340 | loss: 1.543895928
step: 21350 | loss: 1.541408486
step: 21360 | loss: 1.538921044
step: 21370 | loss: 1.536433602
step: 21380 | loss: 1.533946160
step: 21390 | loss: 1.531458718
step: 21400 | loss: 1.528971276
step: 21410 | loss: 1.526483834
step: 21420 | loss: 1.523996392
step: 21430 | loss: 1.521508950
step: 21440 | loss: 1.519021508
step: 21450 | loss: 1.516534066
step: 21460 | loss: 1.514046624
step: 21470 | loss: 1.511559182
step: 21480 | loss: 1.509071740
step: 21490 | loss: 1.506584298
step: 21500 | loss: 1.504096856
step: 21510 | loss: 1.501609414
step: 21520 | loss: 1.499121972
step: 21530 | loss: 1.496634530
step: 21540 | loss: 1.494147088
step: 21550 | loss: 1.491659646
step: 21560 | loss: 1.489172204
step: 21570 | loss: 1.486684762
step: 21580 | loss: 1.484197320
step: 21590 | loss: 1.481709878
step: 21600 | loss: 1.479222436
step: 21610 | loss: 1.476734994
step: 21620 | loss: 1.474247552
step: 21630 | loss: 1.471760110
step: 21640 | loss: 1.469272668
step: 21650 | loss: 1.466785226
step: 21660 | loss: 1.464297784
step: 21670 | loss: 1.461810342
step: 21680 | loss: 1.459322900
step: 21690 | loss: 1.456835458
step: 21700 | loss: 1.454348016
step: 21710 | loss: 1.451860574
step: 21720 | loss: 1.449373132
step: 21730 | loss: 1.446885690
step: 21740 | loss: 1.444398248
step: 21750 | loss: 1.441910806
step: 21760 | loss: 1.439423364
step: 21770 | loss: 1.436935922
step: 21780 | loss: 1.434448480
step: 21790 | loss: 1.431961038
step: 21800 | loss: 1.429473596
step: 21810 | loss: 1.426986154
step: 21820 | loss: 1.424498712
step: 21830 | loss: 1.422011270
step: 21840 | loss: 1.419523828
step: 21850 | loss: 1.417036386
step: 21860 | loss: 1.414548944
step: 21870 | loss: 1.412061502
step: 21880 | loss: 1.409574060
step: 21890 | loss: 1.407086618
step: 21900 | loss: 1.404599176
step: 21910 | loss: 1.402111734
step: 21920 | loss: 1.399624292
step: 21930 | loss: 1.397136850
step: 21940 | loss: 1.394649408
step: 21950 | loss: 1.392161966
step: 21960 | loss: 1.389674524
step: 21970 | loss: 1.387187082
step: 21980 | loss: 1.384699640
step: 21990 | loss: 1.382212198
step: 22000 | loss: 1.379724756
step: 22010 | loss: 1.377237314
step: 22020 | loss: 1.374749872
step: 22030 | loss: 1.372262430
step: 22040 | loss: 1.369774988
step: 22050 | loss: 1.367287546
step: 22060 | loss: 1.364800104
step: 22070 | loss: 1.362312662
step: 22080 | loss: 1.359825220
step: 22090 | loss: 1.357337778
step: 22100 | loss: 1.354850336
step: 22110 | loss: 1.352362894
step: 22120 | loss: 1.349875452
step: 22130 | loss: 1.347388010
step: 22140 | loss: 1.344900568
step: 22150 | loss: 1.342413126
step: 22160 | loss: 1.339925684
step: 22170 | loss: 1.337438242
step: 22180 | loss: 1.334950800
step: 22190 | loss: 1.332463358
step: 22200 | loss: 1.329975916
step: 22210 | loss: 1.327488474
step: 22220 | loss: 1.325001032
step: 22230 | loss: 1.322513590
step: 22240 | loss: 1.320026148
step: 22250 | loss: 1.317538706
step: 22260 | loss: 1.315051264
step: 22270 | loss: 1.312563822
step: 22280 | loss: 1.310076380
step: 22290 | loss: 1.307588938
step: 22300 | loss: 1.305101496
step: 22310 | loss: 1.302614054
step: 22320 | loss: 1.300126612
step: 22330 | loss: 1.297639170
step: 22340 | loss: 1.295151728
step: 22350 | loss: 1.292664286
step: 22360 | loss: 1.290176844
step: 22370 | loss: 1.287689402
step: 22380 | loss: 1.285201960
step: 22390 | loss: 1.282714518
step: 22400 | loss: 1.280227076
step: 22410 | loss: 1.277739634
step: 22420 | loss: 1.275252192
step: 22430 | loss: 1.272764750
step: 22440 | loss: 1.270277308
step: 22450 | loss: 1.267789866
step: 22460 | loss: 1.265302424
step: 22470 | loss: 1.262814982
step: 22480 | loss: 1.260327540
step: 22490 | loss: 1.257840098
step: 22500 | loss: 1.255352656
step: 22510 | loss: 1.252865214
step: 22520 | loss: 1.250377772
step: 22530 | loss: 1.247890330
step: 22540 | loss: 1.245402888
step: 22550 | loss: 1.242915446
step: 22560 | loss: 1.240428004
step: 22570 | loss: 1.237940562
step: 22580 | loss: 1.235453120
step: 22590 | loss: 1.232965678
step: 22600 | loss: 1.230478236
step: 22610 | loss: 1.227990794
step: 22620 | loss: 1.225503352
step: 22630 | loss: 1.223015910
step: 22640 | loss: 1.220528468
step: 22650 | loss: 1.218041026
step: 22660 | loss: 1.215553584
step: 22670 | loss: 1.213066142
step: 22680 | loss: 1.210578700
step: 22690 | loss: 1.208091258
step: 22700 | loss: 1.205603816
step: 22710 | loss: 1.203116374
step: 22720 | loss: 1.200628932
step: 22730 | loss: 1.198141490
step: 22740 | loss: 1.195654048
step: 22750 | loss: 1.193166606
step: 22760 | loss: 1.190679164
step: 22770 | loss: 1.188191722
step: 22780 | loss: 1.185704280
step: 22790 | loss: 1.183216838
step: 22800 | loss: 1.180729396
step: 22810 | loss: 1.178241954
step: 22820 | loss: 1.175754513
step: 22830 | loss: 1.173267071
step: 22840 | loss: 1.170779629
step: 22850 | loss: 1.168292187
step: 22860 | loss: 1.165804745
step: 22870 | loss: 1.163317303
step: 22880 | loss: 1.160829861
step: 22890 | loss: 1.158342419
step: 22900 | loss: 1.155854977
step: 22910 | loss: 1.153367535
step: 22920 | loss: 1.150880093
step: 22930 | loss: 1.148392651
step: 22940 | loss: 1.145905209
step: 22950 | loss: 1.143417767
step: 22960 | loss: 1.140930325
step: 22970 | loss: 1.138442883
step: 22980 | loss: 1.135955441
step: 22990 | loss: 1.133467999
step: 23000 | loss: 1.130980557
step: 23010 | loss: 1.128493115
step: 23020 | loss: 1.126005673
step: 23030 | loss: 1.123518231
step: 23040 | loss: 1.121030789
step: 23050 | loss: 1.118543347
step: 23060 | loss: 1.116055905
step: 23070 | loss: 1.113568463
step: 23080 | loss: 1.111081021
step: 23090 | loss: 1.108593579
step: 23100 | loss: 1.106106137
step: 23110 | loss: 1.103618695
step: 23120 | loss: 1.101131253
step: 23130 | loss: 1.098643811
step: 23140 | loss: 1.096156369
step: 23150 | loss: 1.093668927
step: 23160 | loss: 1.091181485
step: 23170 | loss: 1.088694043
step: 23180 | loss: 1.086206601
step: 23190 | loss: 1.083719159
step: 23200 | loss: 1.081231717
step: 23210 | loss: 1.078744275
step: 23220 | loss: 1.076256833
step: 23230 | loss: 1.073769391
step: 23240 | loss: 1.071281949
step: 23250 | loss: 1.068794507
step: 23260 | loss: 1.066307065
step: 23270 | loss: 1.063819623
step: 23280 | loss: 1.061332181
step: 23290 | loss: 1.058844739
step: 23300 | loss: 1.056357298
step: 23310 | loss: 1.053869856
step: 23320 | loss: 1.051382414
step: 23330 | loss: 1.048894972
step: 23340 | loss: 1.046407530
step: 23350 | loss: 1.043920088
step: 23360 | loss: 1.041432646
step: 23370 | loss: 1.038945204
step: 23380 | loss: 1.036457762
step: 23390 | loss: 1.033970320
step: 23400 | loss: 1.031482878
step: 23410 | loss: 1.028995436
step: 23420 | loss: 1.026507994
step: 23430 | loss: 1.024020552
step: 23440 | loss: 1.021533110
step: 23450 | loss: 1.019045668
step: 23460 | loss: 1.016558226
step: 23470 | loss: 1.014070784
step: 23480 | loss: 1.011583342
step: 23490 | loss: 1.009095900
step: 23500 | loss: 1.006608458
step: 23510 | loss: 1.004121016
step: 23520 | loss: 1.001633574
step: 23530 | loss: 0.999146132
step: 23540 | loss: 0.996658690
step: 23550 | loss: 0.994171248
step: 23560 | loss: 0.991683806
step: 23570 | loss: 0.989196364
step: 23580 | loss: 0.986708922
step: 23590 | loss: 0.984221480
step: 23600 | loss: 0.981734038
step: 23610 | loss: 0.979246596
step: 23620 | loss: 0.976759154
step: 23630 | loss: 0.974271712
step: 23640 | loss: 0.971784270
step: 23650 | loss: 0.969296828
step: 23660 | loss: 0.966809386
step: 23670 | loss: 0.964321944
step: 23680 | loss: 0.961834502
step: 23690 | loss: 0.959347060
step: 23700 | loss: 0.956859618
step: 23710 | loss: 0.954372177
step: 23720 | loss: 0.951884735
step: 23730 | loss: 0.949397293
step: 23740 | loss: 0.946909851
step: 23750 | loss: 0.944422409
step: 23760 | loss: 0.941934967
step: 23770 | loss: 0.939447525
step: 23780 | loss: 0.936960083
step: 23790 | loss: 0.934472641
step: 23800 | loss: 0.931985199
step: 23810 | loss: 0.929497757
step: 23820 | loss: 0.927010315
step: 23830 | loss: 0.924522873
step: 23840 | loss: 0.922035431
step: 23850 | loss: 0.919547989
step: 23860 | loss: 0.917060547
step: 23870 | loss: 0.914573105
step: 23880 | loss: 0.912085663
step: 23890 | loss: 0.909598221
step: 23900 | loss: 0.907110779
step: 23910 | loss: 0.904623337
step: 23920 | loss: 0.902135895
step: 23930 | loss: 0.899648453
step: 23940 | loss: 0.897161011
step: 23950 | loss: 0.894673569
step: 23960 | loss: 0.892186127
step: 23970 | loss: 0.889698685
step: 23980 | loss: 0.887211243
step: 23990 | loss: 0.884723801
step: 24000 | loss: 0.882236359
step: 24010 | loss: 0.879748917
step: 24020 | loss: 0.877261475
step: 24030 | loss: 0.874774033
step: 24040 | loss: 0.872286591
step: 24050 | loss: 0.869799149
step: 24060 | loss: 0.867311707
step: 24070 | loss: 0.864824265
step: 24080 | loss: 0.862336823
step: 24090 | loss: 0.859849382
step: 24100 | loss: 0.857361940
step: 24110 | loss: 0.854874498
step: 24120 | loss: 0.852387056
step: 24130 | loss: 0.849899614
step: 24140 | loss: 0.847412172
step: 24150 | loss: 0.844924730
step: 24160 | loss: 0.842437288
step: 24170 | loss: 0.839949846
step: 24180 | loss: 0.837462404
step: 24190 | loss: 0.834974962
step: 24200 | loss: 0.832487520
step: 24210 | loss: 0.830000078
step: 24220 | loss: 0.827512636
step: 24230 | loss: 0.825025194
step: 24240 | loss: 0.822537752
step: 24250 | loss: 0.820050310
step: 24260 | loss: 0.817562868
step: 24270 | loss: 0.815075426
step: 24280 | loss: 0.812587984
step: 24290 | loss: 0.810100542
step: 24300 | loss: 0.807613100
step: 24310 | loss: 0.805125658
step: 24320 | loss: 0.802638216
step: 24330 | loss: 0.800150774
step: 24340 | loss: 0.797663332
step: 24350 | loss: 0.795175890
step: 24360 | loss: 0.792688448
step: 24370 | loss: 0.790201006
step: 24380 | loss: 0.787713564
step: 24390 | loss: 0.785226122
step: 24400 | loss: 0.782738680
step: 24410 | loss: 0.780251238
step: 24420 | loss: 0.777763796
step: 24430 | loss: 0.775276354
step: 24440 | loss: 0.772788912
step: 24450 | loss: 0.770301470
step: 24460 | loss: 0.767814029
step: 24470 | loss: 0.765326587
step: 24480 | loss: 0.762839145
step: 24490 | loss: 0.760351703
step: 24500 | loss: 0.757864261
step: 24510 | loss: 0.755376819
step: 24520 | loss: 0.752889377
step: 24530 | loss: 0.750401935
step: 24540 | loss: 0.747914493
step: 24550 | loss: 0.745427051
step: 24560 | loss: 0.742939609
step: 24570 | loss: 0.740452167
step: 24580 | loss: 0.737964725
step: 24590 | loss: 0.735477283
step: 24600 | loss: 0.732989841
step: 24610 | loss: 0.730502399
step: 24620 | loss: 0.728014957
step: 24630 | loss: 0.725527515
step: 24640 | loss: 0.723040073
step: 24650 | loss: 0.720552631
step: 24660 | loss: 0.718065189
step: 24670 | loss: 0.715577747
step: 24680 | loss: 0.713090305
step: 24690 | loss: 0.710602863
step: 24700 | loss: 0.708115421
step: 24710 | loss: 0.705627979
step: 24720 | loss: 0.703140537
step: 24730 | loss: 0.700653095
step: 24740 | loss: 0.698165653
step: 24750 | loss: 0.695678211
step: 24760 | loss: 0.693190769
step: 24770 | loss: 0.690703327
step: 24780 | loss: 0.688215885
step: 24790 | loss: 0.685728443
step: 24800 | loss: 0.683241001
step: 24810 | loss: 0.680753560
step: 24820 | loss: 0.678266118
step: 24830 | loss: 0.675778676
step: 24840 | loss: 0.673291234
step: 24850 | loss: 0.670803792
step: 24860 | loss: 0.668316350
step: 24870 | loss: 0.665828908
step: 24880 | loss: 0.663341466
step: 24890 | loss: 0.660854024
step: 24900 | loss: 0.658366582
step: 24910 | loss: 0.655879140
step: 24920 | loss: 0.653391698
step: 24930 | loss: 0.650904256
step: 24940 | loss: 0.648416814
step: 24950 | loss: 0.645929372
step: 24960 | loss: 0.643441930
step: 24970 | loss: 0.640954488
step: 24980 | loss: 0.638467046
step: 24990 | loss: 0.635979604
step: 25000 | loss: 0.633492162
step: 25010 | loss: 0.631004720
step: 25020 | loss: 0.628517278
step: 25030 | loss: 0.626029836
step: 25040 | loss: 0.623542394
step: 25050 | loss: 0.621054952
step: 25060 | loss: 0.618567510
step: 25070 | loss: 0.616080068
step: 25080 | loss: 0.613592626
step: 25090 | loss: 0.611105184
step: 25100 | loss: 0.608617742
step: 25110 | loss: 0.606130300
step: 25120 | loss: 0.603642858
step: 25130 | loss: 0.601155416
step: 25140 | loss: 0.598667974
step: 25150 | loss: 0.596180533
step: 25160 | loss: 0.593693091
step: 25170 | loss: 0.591205649
step: 25180 | loss: 0.588718207
step: 25190 | loss: 0.586230765
step: 25200 | loss: 0.583743323
step: 25210 | loss: 0.581255881
step: 25220 | loss: 0.578768439
step: 25230 | loss: 0.576280997
step: 25240 | loss: 0.573793555
step: 25250 | loss: 0.571306113
step: 25260 | loss: 0.568818671
step: 25270 | loss: 0.566331229
step: 25280 | loss: 0.563843787
step: 25290 | loss: 0.561356345
step: 25300 | loss: 0.558868903
step: 25310 | loss: 0.556381461
step: 25320 | loss: 0.553894019
step: 25330 | loss: 0.551406577
step: 25340 | loss: 0.548919135
step: 25350 | loss: 0.546431693
step: 25360 | loss: 0.543944251
step: 25370 | loss: 0.541456809
step: 25380 | loss: 0.538969367
step: 25390 | loss: 0.536481925
step: 25400 | loss: 0.533994483
step: 25410 | loss: 0.531507041
step: 25420 | loss: 0.529019599
step: 25430 | loss: 0.526532157
step: 25440 | loss: 0.524044715
step: 25450 | loss: 0.521557273
step: 25460 | loss: 0.519069831
step: 25470 | loss: 0.516582389
step: 25480 | loss: 0.514094947
step: 25490 | loss: 0.511607506
step: 25500 | loss: 0.509120064
step: 25510 | loss: 0.506632622
step: 25520 | loss: 0.504145180
step: 25530 | loss: 0.501657738
step: 25540 | loss: 0.499170296
step: 25550 | loss: 0.496682854
step: 25560 | loss: 0.494195412
step: 25570 | loss: 0.491707970
step: 25580 | loss: 0.489220528
step: 25590 | loss: 0.486733086
step: 25600 | loss: 0.484245644
step: 25610 | loss: 0.481758202
step: 25620 | loss: 0.479270760
step: 25630 | loss: 0.476783318
step: 25640 | loss: 0.474295876
step: 25650 | loss: 0.471808434
step: 25660 | loss: 0.469320992
step: 25670 | loss: 0.466833550
step: 25680 | loss: 0.464346108
step: 25690 | loss: 0.461858666
step: 25700 | loss: 0.459371224
step: 25710 | loss: 0.456883782
step: 25720 | loss: 0.454396340
step: 25730 | loss: 0.451908898
step: 25740 | loss: 0.449421456
step: 25750 | loss: 0.446934014
step: 25760 | loss: 0.444446572
step: 25770 | loss: 0.441959130
step: 25780 | loss: 0.439471688
step: 25790 | loss: 0.436984246
step: 25800 | loss: 0.434496804
step: 25810 | loss: 0.432009362
step: 25820 | loss: 0.429521920
step: 25830 | loss: 0.427034479
step: 25840 | loss: 0.424547037
step: 25850 | loss: 0.422059595
step: 25860 | loss: 0.419572153
step: 25870 | loss: 0.417084711
step: 25880 | loss: 0.414597269
step: 25890 | loss: 0.412109827
step: 25900 | loss: 0.409622385
step: 25910 | loss: 0.407134943
step: 25920 | loss: 0.404647501
step: 25930 | loss: 0.402160059
step: 25940 | loss: 0.399672617
step: 25950 | loss: 0.397185175
step: 25960 | loss: 0.394697733
step: 25970 | loss: 0.392210291
step: 25980 | loss: 0.389722849
step: 25990 | loss: 0.387235407
step: 26000 | loss: 0.384747965
step: 26010 | loss: 0.382260523
step: 26020 | loss: 0.379773081
step: 26030 | loss: 0.377285639
step: 26040 | loss: 0.374798197
step: 26050 | loss: 0.372310755
step: 26060 | loss: 0.369823313
step: 26070 | loss: 0.367335871
step: 26080 | loss: 0.364848429
step: 26090 | loss: 0.362360987
step: 26100 | loss: 0.359873545
step: 26110 | loss: 0.357386103
step: 26120 | loss: 0.354898661
step: 26130 | loss: 0.352411219
step: 26140 | loss: 0.349923777
step: 26150 | loss: 0.347436335
step: 26160 | loss: 0.344948894
step: 26170 | loss: 0.342461452
step: 26180 | loss: 0.339974010
step: 26190 | loss: 0.337486568
step: 26200 | loss: 0.334999126
step: 26210 | loss: 0.332511684
step: 26220 | loss: 0.330024242
step: 26230 | loss: 0.327536800
step: 26240 | loss: 0.325049358
step: 26250 | loss: 0.322561916
step: 26260 | loss: 0.320074474
step: 26270 | loss: 0.317587032
step: 26280 | loss: 0.315099590
step: 26290 | loss: 0.312612148
step: 26300 | loss: 0.310124706
step: 26310 | loss: 0.307637264
step: 26320 | loss: 0.305149822
step: 26330 | loss: 0.302662380
step: 26340 | loss: 0.300174938
step: 26350 | loss: 0.297687496
step: 26360 | loss: 0.295200054
step: 26370 | loss: 0.292712612
step: 26380 | loss: 0.290225170
step: 26390 | loss: 0.287737728
step: 26400 | loss: 0.285250286
step: 26410 | loss: 0.282762844
step: 26420 | loss: 0.280275402
step: 26430 | loss: 0.277787960
step: 26440 | loss: 0.275300518
step: 26450 | loss: 0.272813076
step: 26460 | loss: 0.270325634
step: 26470 | loss: 0.267838192
step: 26480 | loss: 0.265350750
step: 26490 | loss: 0.262863309
step: 26500 | loss: 0.260375867
step: 26510 | loss: 0.257888425
step: 26520 | loss: 0.255400983
step: 26530 | loss: 0.252913541
step: 26540 | loss: 0.250426099
step: 26550 | loss: 0.247938657
step: 26560 | loss: 0.245451215
step: 26570 | loss: 0.242963773
step: 26580 | loss: 0.240476331
step: 26590 | loss: 0.237988889
step: 26600 | loss: 0.235501447
step: 26610 | loss: 0.233014005
step: 26620 | loss: 0.230526563
step: 26630 | loss: 0.228039121
step: 26640 | loss: 0.225551679
step: 26650 | loss: 0.223064237
step: 26660 | loss: 0.220576795
step: 26670 | loss: 0.218089353
step: 26680 | loss: 0.215601911
step: 26690 | loss: 0.213114469
step: 26700 | loss: 0.210627027
step: 26710 | loss: 0.208139585
step: 26720 | loss: 0.205652143
step: 26730 | loss: 0.203164701
step: 26740 | loss: 0.200677259
step: 26750 | loss: 0.198189817
step: 26760 | loss: 0.195702375
step: 26770 | loss: 0.193214933
step: 26780 | loss: 0.190727491
step: 26790 | loss: 0.188240049
step: 26800 | loss: 0.185752607
step: 26810 | loss: 0.183265165
step: 26820 | loss: 0.180777723
step: 26830 | loss: 0.178290282
step: 26840 | loss: 0.175802840
step: 26850 | loss: 0.173315398
step: 26860 | loss: 0.170827956
step: 26870 | loss: 0.168340514
step: 26880 | loss: 0.165853072
step: 26890 | loss: 0.163365630
step: 26900 | loss: 0.160878188
step: 26910 | loss: 0.158390746
step: 26920 | loss: 0.155903304
step: 26930 | loss: 0.153415862
step: 26940 | loss: 0.150928420
step: 26950 | loss: 0.148440978
step: 26960 | loss: 0.145953536
step: 26970 | loss: 0.143466094
step: 26980 | loss: 0.140978652
step: 26990 | loss: 0.138491210
step: 27000 | loss: 0.136003768
step: 27010 | loss: 0.133516326
step: 27020 | loss: 0.131028884
step: 27030 | loss: 0.128541442
step: 27040 | loss: 0.126054000
step: 27050 | loss: 0.123566558
step: 27060 | loss: 0.121079116
step: 27070 | loss: 0.118591674
step: 27080 | loss: 0.116104232
step: 27090 | loss: 0.113616790
step: 27100 | loss: 0.111129348
step: 27110 | loss: 0.108641906
step: 27120 | loss: 0.106154464
step: 27130 | loss: 0.103667022
step: 27140 | loss: 0.101179580
step: 27150 | loss: 0.098692138
step: 27160 | loss: 0.096204697
step: 27170 | loss: 0.093717255
step: 27180 | loss: 0.091229813
step: 27190 | loss: 0.088742371
step: 27200 | loss: 0.086254929
step: 27210 | loss: 0.083767487
step: 27220 | loss: 0.081280045
step: 27230 | loss: 0.078792603
step: 27240 | loss: 0.076305161
step: 27250 | loss: 0.073817719
step: 27260 | loss: 0.071330277
step: 27270 | loss: 0.068842835
step: 27280 | loss: 0.066355393
step: 27290 | loss: 0.063867951
step: 27300 | loss: 0.061380509
step: 27310 | loss: 0.058893067
step: 27320 | loss: 0.056405625
step: 27330 | loss: 0.053918183
step: 27340 | loss: 0.051430741
step: 27350 | loss: 0.048943299
step: 27360 | loss: 0.046455857
step: 27370 | loss: 0.043968415
step: 27380 | loss: 0.041480973
step: 27390 | loss: 0.038993531
step: 27400 | loss: 0.036506089
step: 27410 | loss: 0.034018647
step: 27420 | loss: 0.031531205
step: 27430 | loss: 0.029043763
step: 27440 | loss: 0.026556321
step: 27450 | loss: 0.024068879
step: 27460 | loss: 0.021581437
step: 27470 | loss: 0.019093995
step: 27480 | loss: 0.016606553
step: 27490 | loss: 0.014119112
step: 27500 | loss: 0.011631670
step: 27510 | loss: 0.009144228
step: 27520 | loss: 0.006656786
step: 27530 | loss: 0.004169344
step: 27540 | loss: 0.001681902
- final loss: 0.000936
- (cd _build/default/examples/opt && ./pair.exe)
- 
step: 0 | loss: 12.586418414
step: 10 | loss: 12.579845811
step: 20 | loss: 12.572546202
step: 30 | loss: 12.565250436
step: 40 | loss: 12.557958787
step: 50 | loss: 12.550671409
step: 60 | loss: 12.543388378
step: 70 | loss: 12.536109724
step: 80 | loss: 12.528835452
step: 90 | loss: 12.521565561
step: 100 | loss: 12.514300040
step: 110 | loss: 12.507038880
step: 120 | loss: 12.499782070
step: 130 | loss: 12.492529598
step: 140 | loss: 12.485281454
step: 150 | loss: 12.478037626
step: 160 | loss: 12.470798102
step: 170 | loss: 12.463562871
step: 180 | loss: 12.456331922
step: 190 | loss: 12.449105243
step: 200 | loss: 12.441882823
step: 210 | loss: 12.434664650
step: 220 | loss: 12.427450714
step: 230 | loss: 12.420241004
step: 240 | loss: 12.413035506
step: 250 | loss: 12.405834212
step: 260 | loss: 12.398637109
step: 270 | loss: 12.391444185
step: 280 | loss: 12.384255431
step: 290 | loss: 12.377070834
step: 300 | loss: 12.369890384
step: 310 | loss: 12.362714069
step: 320 | loss: 12.355541878
step: 330 | loss: 12.348373800
step: 340 | loss: 12.341209823
step: 350 | loss: 12.334049938
step: 360 | loss: 12.326894132
step: 370 | loss: 12.319742395
step: 380 | loss: 12.312594714
step: 390 | loss: 12.305451081
step: 400 | loss: 12.298311482
step: 410 | loss: 12.291175908
step: 420 | loss: 12.284044346
step: 430 | loss: 12.276916787
step: 440 | loss: 12.269793219
step: 450 | loss: 12.262673631
step: 460 | loss: 12.255558012
step: 470 | loss: 12.248446350
step: 480 | loss: 12.241338636
step: 490 | loss: 12.234234858
step: 500 | loss: 12.227135005
step: 510 | loss: 12.220039065
step: 520 | loss: 12.212947029
step: 530 | loss: 12.205858885
step: 540 | loss: 12.198774622
step: 550 | loss: 12.191694230
step: 560 | loss: 12.184617696
step: 570 | loss: 12.177545011
step: 580 | loss: 12.170476163
step: 590 | loss: 12.163411142
step: 600 | loss: 12.156349936
step: 610 | loss: 12.149292535
step: 620 | loss: 12.142238927
step: 630 | loss: 12.135189102
step: 640 | loss: 12.128143049
step: 650 | loss: 12.121100757
step: 660 | loss: 12.114062215
step: 670 | loss: 12.107027413
step: 680 | loss: 12.099996338
step: 690 | loss: 12.092968981
step: 700 | loss: 12.085945330
step: 710 | loss: 12.078925375
step: 720 | loss: 12.071909105
step: 730 | loss: 12.064896508
step: 740 | loss: 12.057887574
step: 750 | loss: 12.050882293
step: 760 | loss: 12.043880652
step: 770 | loss: 12.036882642
step: 780 | loss: 12.029888251
step: 790 | loss: 12.022897469
step: 800 | loss: 12.015910284
step: 810 | loss: 12.008926686
step: 820 | loss: 12.001946664
step: 830 | loss: 11.994970206
step: 840 | loss: 11.987997303
step: 850 | loss: 11.981027943
step: 860 | loss: 11.974062115
step: 870 | loss: 11.967099809
step: 880 | loss: 11.960141013
step: 890 | loss: 11.953185717
step: 900 | loss: 11.946233909
step: 910 | loss: 11.939285580
step: 920 | loss: 11.932340717
step: 930 | loss: 11.925399310
step: 940 | loss: 11.918461348
step: 950 | loss: 11.911526821
step: 960 | loss: 11.904595716
step: 970 | loss: 11.897668024
step: 980 | loss: 11.890743733
step: 990 | loss: 11.883822833
step: 1000 | loss: 11.876905312
step: 1010 | loss: 11.869991160
step: 1020 | loss: 11.863080365
step: 1030 | loss: 11.856172917
step: 1040 | loss: 11.849268805
step: 1050 | loss: 11.842368018
step: 1060 | loss: 11.835470544
step: 1070 | loss: 11.828576373
step: 1080 | loss: 11.821685494
step: 1090 | loss: 11.814797896
step: 1100 | loss: 11.807913567
step: 1110 | loss: 11.801032498
step: 1120 | loss: 11.794154676
step: 1130 | loss: 11.787280091
step: 1140 | loss: 11.780408732
step: 1150 | loss: 11.773540588
step: 1160 | loss: 11.766675647
step: 1170 | loss: 11.759813900
step: 1180 | loss: 11.752955334
step: 1190 | loss: 11.746099938
step: 1200 | loss: 11.739247702
step: 1210 | loss: 11.732398615
step: 1220 | loss: 11.725552665
step: 1230 | loss: 11.718709842
step: 1240 | loss: 11.711870133
step: 1250 | loss: 11.705033529
step: 1260 | loss: 11.698200018
step: 1270 | loss: 11.691369589
step: 1280 | loss: 11.684542231
step: 1290 | loss: 11.677717932
step: 1300 | loss: 11.670896683
step: 1310 | loss: 11.664078470
step: 1320 | loss: 11.657263284
step: 1330 | loss: 11.650451113
step: 1340 | loss: 11.643641946
step: 1350 | loss: 11.636835772
step: 1360 | loss: 11.630032579
step: 1370 | loss: 11.623232357
step: 1380 | loss: 11.616435095
step: 1390 | loss: 11.609640780
step: 1400 | loss: 11.602849402
step: 1410 | loss: 11.596060950
step: 1420 | loss: 11.589275412
step: 1430 | loss: 11.582492777
step: 1440 | loss: 11.575713035
step: 1450 | loss: 11.568936173
step: 1460 | loss: 11.562162181
step: 1470 | loss: 11.555391046
step: 1480 | loss: 11.548622759
step: 1490 | loss: 11.541857308
step: 1500 | loss: 11.535094681
step: 1510 | loss: 11.528334867
step: 1520 | loss: 11.521577855
step: 1530 | loss: 11.514823633
step: 1540 | loss: 11.508072191
step: 1550 | loss: 11.501323517
step: 1560 | loss: 11.494577600
step: 1570 | loss: 11.487834427
step: 1580 | loss: 11.481093989
step: 1590 | loss: 11.474356274
step: 1600 | loss: 11.467621270
step: 1610 | loss: 11.460888966
step: 1620 | loss: 11.454159351
step: 1630 | loss: 11.447432413
step: 1640 | loss: 11.440708142
step: 1650 | loss: 11.433986525
step: 1660 | loss: 11.427267552
step: 1670 | loss: 11.420551210
step: 1680 | loss: 11.413837490
step: 1690 | loss: 11.407126378
step: 1700 | loss: 11.400417865
step: 1710 | loss: 11.393711939
step: 1720 | loss: 11.387008587
step: 1730 | loss: 11.380307800
step: 1740 | loss: 11.373609566
step: 1750 | loss: 11.366913872
step: 1760 | loss: 11.360220709
step: 1770 | loss: 11.353530064
step: 1780 | loss: 11.346841927
step: 1790 | loss: 11.340156286
step: 1800 | loss: 11.333473129
step: 1810 | loss: 11.326792445
step: 1820 | loss: 11.320114224
step: 1830 | loss: 11.313438453
step: 1840 | loss: 11.306765121
step: 1850 | loss: 11.300094218
step: 1860 | loss: 11.293425731
step: 1870 | loss: 11.286759650
step: 1880 | loss: 11.280095963
step: 1890 | loss: 11.273434658
step: 1900 | loss: 11.266775726
step: 1910 | loss: 11.260119153
step: 1920 | loss: 11.253464930
step: 1930 | loss: 11.246813045
step: 1940 | loss: 11.240163486
step: 1950 | loss: 11.233516243
step: 1960 | loss: 11.226871304
step: 1970 | loss: 11.220228658
step: 1980 | loss: 11.213588294
step: 1990 | loss: 11.206950201
step: 2000 | loss: 11.200314367
step: 2010 | loss: 11.193680782
step: 2020 | loss: 11.187049434
step: 2030 | loss: 11.180420313
step: 2040 | loss: 11.173793407
step: 2050 | loss: 11.167168704
step: 2060 | loss: 11.160546195
step: 2070 | loss: 11.153925869
step: 2080 | loss: 11.147307713
step: 2090 | loss: 11.140691717
step: 2100 | loss: 11.134077871
step: 2110 | loss: 11.127466163
step: 2120 | loss: 11.120856582
step: 2130 | loss: 11.114249118
step: 2140 | loss: 11.107643760
step: 2150 | loss: 11.101040497
step: 2160 | loss: 11.094439317
step: 2170 | loss: 11.087840211
step: 2180 | loss: 11.081243168
step: 2190 | loss: 11.074648177
step: 2200 | loss: 11.068055227
step: 2210 | loss: 11.061464308
step: 2220 | loss: 11.054875409
step: 2230 | loss: 11.048288519
step: 2240 | loss: 11.041703629
step: 2250 | loss: 11.035120727
step: 2260 | loss: 11.028539803
step: 2270 | loss: 11.021960847
step: 2280 | loss: 11.015383848
step: 2290 | loss: 11.008808796
step: 2300 | loss: 11.002235681
step: 2310 | loss: 10.995664493
step: 2320 | loss: 10.989095220
step: 2330 | loss: 10.982527854
step: 2340 | loss: 10.975962384
step: 2350 | loss: 10.969398800
step: 2360 | loss: 10.962837092
step: 2370 | loss: 10.956277250
step: 2380 | loss: 10.949719264
step: 2390 | loss: 10.943163124
step: 2400 | loss: 10.936608821
step: 2410 | loss: 10.930056344
step: 2420 | loss: 10.923505684
step: 2430 | loss: 10.916956832
step: 2440 | loss: 10.910409777
step: 2450 | loss: 10.903864510
step: 2460 | loss: 10.897321022
step: 2470 | loss: 10.890779304
step: 2480 | loss: 10.884239345
step: 2490 | loss: 10.877701137
step: 2500 | loss: 10.871164670
step: 2510 | loss: 10.864629935
step: 2520 | loss: 10.858096924
step: 2530 | loss: 10.851565626
step: 2540 | loss: 10.845036034
step: 2550 | loss: 10.838508137
step: 2560 | loss: 10.831981928
step: 2570 | loss: 10.825457397
step: 2580 | loss: 10.818934536
step: 2590 | loss: 10.812413336
step: 2600 | loss: 10.805893788
step: 2610 | loss: 10.799375885
step: 2620 | loss: 10.792859616
step: 2630 | loss: 10.786344975
step: 2640 | loss: 10.779831953
step: 2650 | loss: 10.773320542
step: 2660 | loss: 10.766810733
step: 2670 | loss: 10.760302518
step: 2680 | loss: 10.753795890
step: 2690 | loss: 10.747290840
step: 2700 | loss: 10.740787361
step: 2710 | loss: 10.734285445
step: 2720 | loss: 10.727785084
step: 2730 | loss: 10.721286271
step: 2740 | loss: 10.714788997
step: 2750 | loss: 10.708293257
step: 2760 | loss: 10.701799041
step: 2770 | loss: 10.695306344
step: 2780 | loss: 10.688815157
step: 2790 | loss: 10.682325474
step: 2800 | loss: 10.675837288
step: 2810 | loss: 10.669350592
step: 2820 | loss: 10.662865378
step: 2830 | loss: 10.656381640
step: 2840 | loss: 10.649899372
step: 2850 | loss: 10.643418566
step: 2860 | loss: 10.636939217
step: 2870 | loss: 10.630461318
step: 2880 | loss: 10.623984861
step: 2890 | loss: 10.617509843
step: 2900 | loss: 10.611036255
step: 2910 | loss: 10.604564092
step: 2920 | loss: 10.598093348
step: 2930 | loss: 10.591624017
step: 2940 | loss: 10.585156093
step: 2950 | loss: 10.578689570
step: 2960 | loss: 10.572224444
step: 2970 | loss: 10.565760707
step: 2980 | loss: 10.559298356
step: 2990 | loss: 10.552837384
step: 3000 | loss: 10.546377785
step: 3010 | loss: 10.539919556
step: 3020 | loss: 10.533462691
step: 3030 | loss: 10.527007184
step: 3040 | loss: 10.520553031
step: 3050 | loss: 10.514100227
step: 3060 | loss: 10.507648767
step: 3070 | loss: 10.501198646
step: 3080 | loss: 10.494749860
step: 3090 | loss: 10.488302405
step: 3100 | loss: 10.481856275
step: 3110 | loss: 10.475411468
step: 3120 | loss: 10.468967977
step: 3130 | loss: 10.462525800
step: 3140 | loss: 10.456084932
step: 3150 | loss: 10.449645368
step: 3160 | loss: 10.443207106
step: 3170 | loss: 10.436770142
step: 3180 | loss: 10.430334471
step: 3190 | loss: 10.423900090
step: 3200 | loss: 10.417466995
step: 3210 | loss: 10.411035184
step: 3220 | loss: 10.404604651
step: 3230 | loss: 10.398175395
step: 3240 | loss: 10.391747412
step: 3250 | loss: 10.385320698
step: 3260 | loss: 10.378895251
step: 3270 | loss: 10.372471068
step: 3280 | loss: 10.366048145
step: 3290 | loss: 10.359626480
step: 3300 | loss: 10.353206070
step: 3310 | loss: 10.346786912
step: 3320 | loss: 10.340369004
step: 3330 | loss: 10.333952343
step: 3340 | loss: 10.327536927
step: 3350 | loss: 10.321122753
step: 3360 | loss: 10.314709818
step: 3370 | loss: 10.308298121
step: 3380 | loss: 10.301887660
step: 3390 | loss: 10.295478431
step: 3400 | loss: 10.289070434
step: 3410 | loss: 10.282663666
step: 3420 | loss: 10.276258125
step: 3430 | loss: 10.269853809
step: 3440 | loss: 10.263450717
step: 3450 | loss: 10.257048846
step: 3460 | loss: 10.250648196
step: 3470 | loss: 10.244248764
step: 3480 | loss: 10.237850549
step: 3490 | loss: 10.231453549
step: 3500 | loss: 10.225057763
step: 3510 | loss: 10.218663190
step: 3520 | loss: 10.212269828
step: 3530 | loss: 10.205877676
step: 3540 | loss: 10.199486732
step: 3550 | loss: 10.193096996
step: 3560 | loss: 10.186708467
step: 3570 | loss: 10.180321143
step: 3580 | loss: 10.173935023
step: 3590 | loss: 10.167550107
step: 3600 | loss: 10.161166393
step: 3610 | loss: 10.154783881
step: 3620 | loss: 10.148402569
step: 3630 | loss: 10.142022458
step: 3640 | loss: 10.135643546
step: 3650 | loss: 10.129265832
step: 3660 | loss: 10.122889317
step: 3670 | loss: 10.116513999
step: 3680 | loss: 10.110139878
step: 3690 | loss: 10.103766953
step: 3700 | loss: 10.097395224
step: 3710 | loss: 10.091024690
step: 3720 | loss: 10.084655352
step: 3730 | loss: 10.078287208
step: 3740 | loss: 10.071920258
step: 3750 | loss: 10.065554502
step: 3760 | loss: 10.059189941
step: 3770 | loss: 10.052826572
step: 3780 | loss: 10.046464398
step: 3790 | loss: 10.040103416
step: 3800 | loss: 10.033743627
step: 3810 | loss: 10.027385031
step: 3820 | loss: 10.021027629
step: 3830 | loss: 10.014671419
step: 3840 | loss: 10.008316401
step: 3850 | loss: 10.001962577
step: 3860 | loss: 9.995609946
step: 3870 | loss: 9.989258507
step: 3880 | loss: 9.982908261
step: 3890 | loss: 9.976559209
step: 3900 | loss: 9.970211350
step: 3910 | loss: 9.963864684
step: 3920 | loss: 9.957519211
step: 3930 | loss: 9.951174933
step: 3940 | loss: 9.944831848
step: 3950 | loss: 9.938489957
step: 3960 | loss: 9.932149261
step: 3970 | loss: 9.925809760
step: 3980 | loss: 9.919471454
step: 3990 | loss: 9.913134342
step: 4000 | loss: 9.906798427
step: 4010 | loss: 9.900463707
step: 4020 | loss: 9.894130184
step: 4030 | loss: 9.887797857
step: 4040 | loss: 9.881466727
step: 4050 | loss: 9.875136795
step: 4060 | loss: 9.868808060
step: 4070 | loss: 9.862480524
step: 4080 | loss: 9.856154186
step: 4090 | loss: 9.849829047
step: 4100 | loss: 9.843505108
step: 4110 | loss: 9.837182368
step: 4120 | loss: 9.830860829
step: 4130 | loss: 9.824540491
step: 4140 | loss: 9.818221354
step: 4150 | loss: 9.811903419
step: 4160 | loss: 9.805586687
step: 4170 | loss: 9.799271157
step: 4180 | loss: 9.792956831
step: 4190 | loss: 9.786643708
step: 4200 | loss: 9.780331790
step: 4210 | loss: 9.774021076
step: 4220 | loss: 9.767711569
step: 4230 | loss: 9.761403267
step: 4240 | loss: 9.755096171
step: 4250 | loss: 9.748790283
step: 4260 | loss: 9.742485602
step: 4270 | loss: 9.736182130
step: 4280 | loss: 9.729879866
step: 4290 | loss: 9.723578812
step: 4300 | loss: 9.717278967
step: 4310 | loss: 9.710980333
step: 4320 | loss: 9.704682910
step: 4330 | loss: 9.698386699
step: 4340 | loss: 9.692091699
step: 4350 | loss: 9.685797913
step: 4360 | loss: 9.679505339
step: 4370 | loss: 9.673213980
step: 4380 | loss: 9.666923835
step: 4390 | loss: 9.660634905
step: 4400 | loss: 9.654347191
step: 4410 | loss: 9.648060693
step: 4420 | loss: 9.641775412
step: 4430 | loss: 9.635491348
step: 4440 | loss: 9.629208502
step: 4450 | loss: 9.622926875
step: 4460 | loss: 9.616646467
step: 4470 | loss: 9.610367279
step: 4480 | loss: 9.604089311
step: 4490 | loss: 9.597812564
step: 4500 | loss: 9.591537038
step: 4510 | loss: 9.585262734
step: 4520 | loss: 9.578989653
step: 4530 | loss: 9.572717795
step: 4540 | loss: 9.566447161
step: 4550 | loss: 9.560177751
step: 4560 | loss: 9.553909566
step: 4570 | loss: 9.547642607
step: 4580 | loss: 9.541376874
step: 4590 | loss: 9.535112367
step: 4600 | loss: 9.528849087
step: 4610 | loss: 9.522587035
step: 4620 | loss: 9.516326211
step: 4630 | loss: 9.510066616
step: 4640 | loss: 9.503808251
step: 4650 | loss: 9.497551115
step: 4660 | loss: 9.491295210
step: 4670 | loss: 9.485040535
step: 4680 | loss: 9.478787093
step: 4690 | loss: 9.472534882
step: 4700 | loss: 9.466283903
step: 4710 | loss: 9.460034158
step: 4720 | loss: 9.453785647
step: 4730 | loss: 9.447538369
step: 4740 | loss: 9.441292326
step: 4750 | loss: 9.435047519
step: 4760 | loss: 9.428803946
step: 4770 | loss: 9.422561610
step: 4780 | loss: 9.416320511
step: 4790 | loss: 9.410080649
step: 4800 | loss: 9.403842024
step: 4810 | loss: 9.397604637
step: 4820 | loss: 9.391368489
step: 4830 | loss: 9.385133580
step: 4840 | loss: 9.378899910
step: 4850 | loss: 9.372667481
step: 4860 | loss: 9.366436291
step: 4870 | loss: 9.360206343
step: 4880 | loss: 9.353977636
step: 4890 | loss: 9.347750170
step: 4900 | loss: 9.341523947
step: 4910 | loss: 9.335298966
step: 4920 | loss: 9.329075228
step: 4930 | loss: 9.322852734
step: 4940 | loss: 9.316631483
step: 4950 | loss: 9.310411477
step: 4960 | loss: 9.304192715
step: 4970 | loss: 9.297975198
step: 4980 | loss: 9.291758927
step: 4990 | loss: 9.285543901
step: 5000 | loss: 9.279330122
step: 5010 | loss: 9.273117589
step: 5020 | loss: 9.266906303
step: 5030 | loss: 9.260696264
step: 5040 | loss: 9.254487473
step: 5050 | loss: 9.248279929
step: 5060 | loss: 9.242073634
step: 5070 | loss: 9.235868588
step: 5080 | loss: 9.229664790
step: 5090 | loss: 9.223462242
step: 5100 | loss: 9.217260943
step: 5110 | loss: 9.211060893
step: 5120 | loss: 9.204862094
step: 5130 | loss: 9.198664546
step: 5140 | loss: 9.192468248
step: 5150 | loss: 9.186273200
step: 5160 | loss: 9.180079404
step: 5170 | loss: 9.173886860
step: 5180 | loss: 9.167695567
step: 5190 | loss: 9.161505526
step: 5200 | loss: 9.155316737
step: 5210 | loss: 9.149129200
step: 5220 | loss: 9.142942916
step: 5230 | loss: 9.136757885
step: 5240 | loss: 9.130574107
step: 5250 | loss: 9.124391582
step: 5260 | loss: 9.118210310
step: 5270 | loss: 9.112030292
step: 5280 | loss: 9.105851527
step: 5290 | loss: 9.099674016
step: 5300 | loss: 9.093497759
step: 5310 | loss: 9.087322756
step: 5320 | loss: 9.081149008
step: 5330 | loss: 9.074976513
step: 5340 | loss: 9.068805274
step: 5350 | loss: 9.062635288
step: 5360 | loss: 9.056466557
step: 5370 | loss: 9.050299081
step: 5380 | loss: 9.044132860
step: 5390 | loss: 9.037967893
step: 5400 | loss: 9.031804182
step: 5410 | loss: 9.025641725
step: 5420 | loss: 9.019480523
step: 5430 | loss: 9.013320576
step: 5440 | loss: 9.007161884
step: 5450 | loss: 9.001004447
step: 5460 | loss: 8.994848265
step: 5470 | loss: 8.988693338
step: 5480 | loss: 8.982539665
step: 5490 | loss: 8.976387248
step: 5500 | loss: 8.970236085
step: 5510 | loss: 8.964086177
step: 5520 | loss: 8.957937523
step: 5530 | loss: 8.951790124
step: 5540 | loss: 8.945643980
step: 5550 | loss: 8.939499090
step: 5560 | loss: 8.933355454
step: 5570 | loss: 8.927213072
step: 5580 | loss: 8.921071944
step: 5590 | loss: 8.914932070
step: 5600 | loss: 8.908793449
step: 5610 | loss: 8.902656082
step: 5620 | loss: 8.896519968
step: 5630 | loss: 8.890385107
step: 5640 | loss: 8.884251498
step: 5650 | loss: 8.878119143
step: 5660 | loss: 8.871988039
step: 5670 | loss: 8.865858188
step: 5680 | loss: 8.859729588
step: 5690 | loss: 8.853602240
step: 5700 | loss: 8.847476144
step: 5710 | loss: 8.841351298
step: 5720 | loss: 8.835227702
step: 5730 | loss: 8.829105357
step: 5740 | loss: 8.822984262
step: 5750 | loss: 8.816864417
step: 5760 | loss: 8.810745820
step: 5770 | loss: 8.804628473
step: 5780 | loss: 8.798512374
step: 5790 | loss: 8.792397522
step: 5800 | loss: 8.786283919
step: 5810 | loss: 8.780171562
step: 5820 | loss: 8.774060452
step: 5830 | loss: 8.767950588
step: 5840 | loss: 8.761841970
step: 5850 | loss: 8.755734598
step: 5860 | loss: 8.749628469
step: 5870 | loss: 8.743523585
step: 5880 | loss: 8.737419945
step: 5890 | loss: 8.731317548
step: 5900 | loss: 8.725216393
step: 5910 | loss: 8.719116480
step: 5920 | loss: 8.713017808
step: 5930 | loss: 8.706920377
step: 5940 | loss: 8.700824186
step: 5950 | loss: 8.694729235
step: 5960 | loss: 8.688635522
step: 5970 | loss: 8.682543047
step: 5980 | loss: 8.676451810
step: 5990 | loss: 8.670361809
step: 6000 | loss: 8.664273044
step: 6010 | loss: 8.658185515
step: 6020 | loss: 8.652099219
step: 6030 | loss: 8.646014158
step: 6040 | loss: 8.639930329
step: 6050 | loss: 8.633847732
step: 6060 | loss: 8.627766366
step: 6070 | loss: 8.621686231
step: 6080 | loss: 8.615607326
step: 6090 | loss: 8.609529648
step: 6100 | loss: 8.603453199
step: 6110 | loss: 8.597377976
step: 6120 | loss: 8.591303980
step: 6130 | loss: 8.585231208
step: 6140 | loss: 8.579159660
step: 6150 | loss: 8.573089336
step: 6160 | loss: 8.567020233
step: 6170 | loss: 8.560952351
step: 6180 | loss: 8.554885689
step: 6190 | loss: 8.548820246
step: 6200 | loss: 8.542756021
step: 6210 | loss: 8.536693013
step: 6220 | loss: 8.530631220
step: 6230 | loss: 8.524570642
step: 6240 | loss: 8.518511277
step: 6250 | loss: 8.512453124
step: 6260 | loss: 8.506396182
step: 6270 | loss: 8.500340450
step: 6280 | loss: 8.494285927
step: 6290 | loss: 8.488232611
step: 6300 | loss: 8.482180501
step: 6310 | loss: 8.476129596
step: 6320 | loss: 8.470079895
step: 6330 | loss: 8.464031395
step: 6340 | loss: 8.457984097
step: 6350 | loss: 8.451937998
step: 6360 | loss: 8.445893097
step: 6370 | loss: 8.439849393
step: 6380 | loss: 8.433806884
step: 6390 | loss: 8.427765569
step: 6400 | loss: 8.421725446
step: 6410 | loss: 8.415686515
step: 6420 | loss: 8.409648773
step: 6430 | loss: 8.403612219
step: 6440 | loss: 8.397576851
step: 6450 | loss: 8.391542668
step: 6460 | loss: 8.385509668
step: 6470 | loss: 8.379477850
step: 6480 | loss: 8.373447212
step: 6490 | loss: 8.367417753
step: 6500 | loss: 8.361389470
step: 6510 | loss: 8.355362362
step: 6520 | loss: 8.349336428
step: 6530 | loss: 8.343311665
step: 6540 | loss: 8.337288072
step: 6550 | loss: 8.331265648
step: 6560 | loss: 8.325244389
step: 6570 | loss: 8.319224295
step: 6580 | loss: 8.313205364
step: 6590 | loss: 8.307187594
step: 6600 | loss: 8.301170982
step: 6610 | loss: 8.295155528
step: 6620 | loss: 8.289141229
step: 6630 | loss: 8.283128083
step: 6640 | loss: 8.277116088
step: 6650 | loss: 8.271105242
step: 6660 | loss: 8.265095544
step: 6670 | loss: 8.259086991
step: 6680 | loss: 8.253079581
step: 6690 | loss: 8.247073312
step: 6700 | loss: 8.241068182
step: 6710 | loss: 8.235064189
step: 6720 | loss: 8.229061331
step: 6730 | loss: 8.223059605
step: 6740 | loss: 8.217059009
step: 6750 | loss: 8.211059542
step: 6760 | loss: 8.205061201
step: 6770 | loss: 8.199063983
step: 6780 | loss: 8.193067886
step: 6790 | loss: 8.187072909
step: 6800 | loss: 8.181079049
step: 6810 | loss: 8.175086303
step: 6820 | loss: 8.169094669
step: 6830 | loss: 8.163104144
step: 6840 | loss: 8.157114727
step: 6850 | loss: 8.151126415
step: 6860 | loss: 8.145139205
step: 6870 | loss: 8.139153094
step: 6880 | loss: 8.133168082
step: 6890 | loss: 8.127184164
step: 6900 | loss: 8.121201338
step: 6910 | loss: 8.115219602
step: 6920 | loss: 8.109238953
step: 6930 | loss: 8.103259388
step: 6940 | loss: 8.097280905
step: 6950 | loss: 8.091303502
step: 6960 | loss: 8.085327175
step: 6970 | loss: 8.079351921
step: 6980 | loss: 8.073377739
step: 6990 | loss: 8.067404625
step: 7000 | loss: 8.061432576
step: 7010 | loss: 8.055461590
step: 7020 | loss: 8.049491664
step: 7030 | loss: 8.043522795
step: 7040 | loss: 8.037554980
step: 7050 | loss: 8.031588216
step: 7060 | loss: 8.025622501
step: 7070 | loss: 8.019657831
step: 7080 | loss: 8.013694203
step: 7090 | loss: 8.007731615
step: 7100 | loss: 8.001770063
step: 7110 | loss: 7.995809544
step: 7120 | loss: 7.989850056
step: 7130 | loss: 7.983891595
step: 7140 | loss: 7.977934158
step: 7150 | loss: 7.971977742
step: 7160 | loss: 7.966022344
step: 7170 | loss: 7.960067961
step: 7180 | loss: 7.954114590
step: 7190 | loss: 7.948162226
step: 7200 | loss: 7.942210868
step: 7210 | loss: 7.936260512
step: 7220 | loss: 7.930311154
step: 7230 | loss: 7.924362792
step: 7240 | loss: 7.918415422
step: 7250 | loss: 7.912469040
step: 7260 | loss: 7.906523644
step: 7270 | loss: 7.900579229
step: 7280 | loss: 7.894635794
step: 7290 | loss: 7.888693333
step: 7300 | loss: 7.882751844
step: 7310 | loss: 7.876811323
step: 7320 | loss: 7.870871768
step: 7330 | loss: 7.864933173
step: 7340 | loss: 7.858995536
step: 7350 | loss: 7.853058854
step: 7360 | loss: 7.847123122
step: 7370 | loss: 7.841188337
step: 7380 | loss: 7.835254496
step: 7390 | loss: 7.829321595
step: 7400 | loss: 7.823389630
step: 7410 | loss: 7.817458598
step: 7420 | loss: 7.811528495
step: 7430 | loss: 7.805599318
step: 7440 | loss: 7.799671062
step: 7450 | loss: 7.793743724
step: 7460 | loss: 7.787817300
step: 7470 | loss: 7.781891787
step: 7480 | loss: 7.775967180
step: 7490 | loss: 7.770043476
step: 7500 | loss: 7.764120672
step: 7510 | loss: 7.758198763
step: 7520 | loss: 7.752277746
step: 7530 | loss: 7.746357616
step: 7540 | loss: 7.740438370
step: 7550 | loss: 7.734520004
step: 7560 | loss: 7.728602515
step: 7570 | loss: 7.722685898
step: 7580 | loss: 7.716770148
step: 7590 | loss: 7.710855264
step: 7600 | loss: 7.704941240
step: 7610 | loss: 7.699028072
step: 7620 | loss: 7.693115758
step: 7630 | loss: 7.687204291
step: 7640 | loss: 7.681293670
step: 7650 | loss: 7.675383889
step: 7660 | loss: 7.669474945
step: 7670 | loss: 7.663566834
step: 7680 | loss: 7.657659551
step: 7690 | loss: 7.651753093
step: 7700 | loss: 7.645847456
step: 7710 | loss: 7.639942635
step: 7720 | loss: 7.634038627
step: 7730 | loss: 7.628135428
step: 7740 | loss: 7.622233032
step: 7750 | loss: 7.616331438
step: 7760 | loss: 7.610430639
step: 7770 | loss: 7.604530633
step: 7780 | loss: 7.598631415
step: 7790 | loss: 7.592732981
step: 7800 | loss: 7.586835327
step: 7810 | loss: 7.580938449
step: 7820 | loss: 7.575042343
step: 7830 | loss: 7.569147004
step: 7840 | loss: 7.563252429
step: 7850 | loss: 7.557358613
step: 7860 | loss: 7.551465553
step: 7870 | loss: 7.545573244
step: 7880 | loss: 7.539681682
step: 7890 | loss: 7.533790863
step: 7900 | loss: 7.527900783
step: 7910 | loss: 7.522011438
step: 7920 | loss: 7.516122824
step: 7930 | loss: 7.510234936
step: 7940 | loss: 7.504347771
step: 7950 | loss: 7.498461324
step: 7960 | loss: 7.492575591
step: 7970 | loss: 7.486690569
step: 7980 | loss: 7.480806253
step: 7990 | loss: 7.474922639
step: 8000 | loss: 7.469039722
step: 8010 | loss: 7.463157500
step: 8020 | loss: 7.457275968
step: 8030 | loss: 7.451395121
step: 8040 | loss: 7.445514957
step: 8050 | loss: 7.439635470
step: 8060 | loss: 7.433756656
step: 8070 | loss: 7.427878513
step: 8080 | loss: 7.422001035
step: 8090 | loss: 7.416124219
step: 8100 | loss: 7.410248060
step: 8110 | loss: 7.404372555
step: 8120 | loss: 7.398497700
step: 8130 | loss: 7.392623491
step: 8140 | loss: 7.386749924
step: 8150 | loss: 7.380876995
step: 8160 | loss: 7.375004700
step: 8170 | loss: 7.369133035
step: 8180 | loss: 7.363261997
step: 8190 | loss: 7.357391581
step: 8200 | loss: 7.351521783
step: 8210 | loss: 7.345652601
step: 8220 | loss: 7.339784029
step: 8230 | loss: 7.333916065
step: 8240 | loss: 7.328048704
step: 8250 | loss: 7.322181944
step: 8260 | loss: 7.316315779
step: 8270 | loss: 7.310450206
step: 8280 | loss: 7.304585222
step: 8290 | loss: 7.298720824
step: 8300 | loss: 7.292857006
step: 8310 | loss: 7.286993767
step: 8320 | loss: 7.281131101
step: 8330 | loss: 7.275269007
step: 8340 | loss: 7.269407479
step: 8350 | loss: 7.263546515
step: 8360 | loss: 7.257686111
step: 8370 | loss: 7.251826264
step: 8380 | loss: 7.245966970
step: 8390 | loss: 7.240108226
step: 8400 | loss: 7.234250028
step: 8410 | loss: 7.228392374
step: 8420 | loss: 7.222535259
step: 8430 | loss: 7.216678681
step: 8440 | loss: 7.210822636
step: 8450 | loss: 7.204967121
step: 8460 | loss: 7.199112133
step: 8470 | loss: 7.193257669
step: 8480 | loss: 7.187403725
step: 8490 | loss: 7.181550298
step: 8500 | loss: 7.175697387
step: 8510 | loss: 7.169844986
step: 8520 | loss: 7.163993094
step: 8530 | loss: 7.158141707
step: 8540 | loss: 7.152290823
step: 8550 | loss: 7.146440438
step: 8560 | loss: 7.140590550
step: 8570 | loss: 7.134741155
step: 8580 | loss: 7.128892252
step: 8590 | loss: 7.123043837
step: 8600 | loss: 7.117195908
step: 8610 | loss: 7.111348462
step: 8620 | loss: 7.105501496
step: 8630 | loss: 7.099655007
step: 8640 | loss: 7.093808994
step: 8650 | loss: 7.087963453
step: 8660 | loss: 7.082118382
step: 8670 | loss: 7.076273779
step: 8680 | loss: 7.070429641
step: 8690 | loss: 7.064585966
step: 8700 | loss: 7.058742751
step: 8710 | loss: 7.052899994
step: 8720 | loss: 7.047057693
step: 8730 | loss: 7.041215846
step: 8740 | loss: 7.035374450
step: 8750 | loss: 7.029533504
step: 8760 | loss: 7.023693004
step: 8770 | loss: 7.017852950
step: 8780 | loss: 7.012013339
step: 8790 | loss: 7.006174169
step: 8800 | loss: 7.000335438
step: 8810 | loss: 6.994497144
step: 8820 | loss: 6.988659285
step: 8830 | loss: 6.982821860
step: 8840 | loss: 6.976984867
step: 8850 | loss: 6.971148303
step: 8860 | loss: 6.965312168
step: 8870 | loss: 6.959476459
step: 8880 | loss: 6.953641175
step: 8890 | loss: 6.947806315
step: 8900 | loss: 6.941971876
step: 8910 | loss: 6.936137857
step: 8920 | loss: 6.930304257
step: 8930 | loss: 6.924471075
step: 8940 | loss: 6.918638308
step: 8950 | loss: 6.912805956
step: 8960 | loss: 6.906974017
step: 8970 | loss: 6.901142490
step: 8980 | loss: 6.895311373
step: 8990 | loss: 6.889480667
step: 9000 | loss: 6.883650368
step: 9010 | loss: 6.877820476
step: 9020 | loss: 6.871990991
step: 9030 | loss: 6.866161910
step: 9040 | loss: 6.860333234
step: 9050 | loss: 6.854504960
step: 9060 | loss: 6.848677089
step: 9070 | loss: 6.842849618
step: 9080 | loss: 6.837022548
step: 9090 | loss: 6.831195877
step: 9100 | loss: 6.825369605
step: 9110 | loss: 6.819543731
step: 9120 | loss: 6.813718253
step: 9130 | loss: 6.807893172
step: 9140 | loss: 6.802068487
step: 9150 | loss: 6.796244197
step: 9160 | loss: 6.790420301
step: 9170 | loss: 6.784596799
step: 9180 | loss: 6.778773690
step: 9190 | loss: 6.772950975
step: 9200 | loss: 6.767128652
step: 9210 | loss: 6.761306720
step: 9220 | loss: 6.755485180
step: 9230 | loss: 6.749664032
step: 9240 | loss: 6.743843274
step: 9250 | loss: 6.738022906
step: 9260 | loss: 6.732202929
step: 9270 | loss: 6.726383342
step: 9280 | loss: 6.720564144
step: 9290 | loss: 6.714745336
step: 9300 | loss: 6.708926917
step: 9310 | loss: 6.703108888
step: 9320 | loss: 6.697291247
step: 9330 | loss: 6.691473996
step: 9340 | loss: 6.685657133
step: 9350 | loss: 6.679840660
step: 9360 | loss: 6.674024575
step: 9370 | loss: 6.668208879
step: 9380 | loss: 6.662393571
step: 9390 | loss: 6.656578653
step: 9400 | loss: 6.650764124
step: 9410 | loss: 6.644949984
step: 9420 | loss: 6.639136233
step: 9430 | loss: 6.633322872
step: 9440 | loss: 6.627509901
step: 9450 | loss: 6.621697319
step: 9460 | loss: 6.615885127
step: 9470 | loss: 6.610073325
step: 9480 | loss: 6.604261914
step: 9490 | loss: 6.598450894
step: 9500 | loss: 6.592640265
step: 9510 | loss: 6.586830027
step: 9520 | loss: 6.581020181
step: 9530 | loss: 6.575210728
step: 9540 | loss: 6.569401666
step: 9550 | loss: 6.563592998
step: 9560 | loss: 6.557784723
step: 9570 | loss: 6.551976842
step: 9580 | loss: 6.546169355
step: 9590 | loss: 6.540362262
step: 9600 | loss: 6.534555565
step: 9610 | loss: 6.528749263
step: 9620 | loss: 6.522943358
step: 9630 | loss: 6.517137849
step: 9640 | loss: 6.511332737
step: 9650 | loss: 6.505528023
step: 9660 | loss: 6.499723708
step: 9670 | loss: 6.493919791
step: 9680 | loss: 6.488116274
step: 9690 | loss: 6.482313157
step: 9700 | loss: 6.476510441
step: 9710 | loss: 6.470708126
step: 9720 | loss: 6.464906213
step: 9730 | loss: 6.459104703
step: 9740 | loss: 6.453303596
step: 9750 | loss: 6.447502893
step: 9760 | loss: 6.441702595
step: 9770 | loss: 6.435902703
step: 9780 | loss: 6.430103216
step: 9790 | loss: 6.424304137
step: 9800 | loss: 6.418505465
step: 9810 | loss: 6.412707202
step: 9820 | loss: 6.406909348
step: 9830 | loss: 6.401111904
step: 9840 | loss: 6.395314870
step: 9850 | loss: 6.389518248
step: 9860 | loss: 6.383722038
step: 9870 | loss: 6.377926241
step: 9880 | loss: 6.372130859
step: 9890 | loss: 6.366335891
step: 9900 | loss: 6.360541338
step: 9910 | loss: 6.354747202
step: 9920 | loss: 6.348953483
step: 9930 | loss: 6.343160183
step: 9940 | loss: 6.337367301
step: 9950 | loss: 6.331574839
step: 9960 | loss: 6.325782798
step: 9970 | loss: 6.319991179
step: 9980 | loss: 6.314199982
step: 9990 | loss: 6.308409208
step: 10000 | loss: 6.302618859
step: 10010 | loss: 6.296828935
step: 10020 | loss: 6.291039438
step: 10030 | loss: 6.285250367
step: 10040 | loss: 6.279461724
step: 10050 | loss: 6.273673511
step: 10060 | loss: 6.267885727
step: 10070 | loss: 6.262098374
step: 10080 | loss: 6.256311453
step: 10090 | loss: 6.250524965
step: 10100 | loss: 6.244738911
step: 10110 | loss: 6.238953291
step: 10120 | loss: 6.233168107
step: 10130 | loss: 6.227383360
step: 10140 | loss: 6.221599050
step: 10150 | loss: 6.215815180
step: 10160 | loss: 6.210031749
step: 10170 | loss: 6.204248758
step: 10180 | loss: 6.198466210
step: 10190 | loss: 6.192684104
step: 10200 | loss: 6.186902442
step: 10210 | loss: 6.181121225
step: 10220 | loss: 6.175340454
step: 10230 | loss: 6.169560130
step: 10240 | loss: 6.163780254
step: 10250 | loss: 6.158000827
step: 10260 | loss: 6.152221850
step: 10270 | loss: 6.146443324
step: 10280 | loss: 6.140665250
step: 10290 | loss: 6.134887630
step: 10300 | loss: 6.129110464
step: 10310 | loss: 6.123333754
step: 10320 | loss: 6.117557500
step: 10330 | loss: 6.111781704
step: 10340 | loss: 6.106006367
step: 10350 | loss: 6.100231489
step: 10360 | loss: 6.094457073
step: 10370 | loss: 6.088683118
step: 10380 | loss: 6.082909627
step: 10390 | loss: 6.077136600
step: 10400 | loss: 6.071364039
step: 10410 | loss: 6.065591944
step: 10420 | loss: 6.059820317
step: 10430 | loss: 6.054049159
step: 10440 | loss: 6.048278471
step: 10450 | loss: 6.042508254
step: 10460 | loss: 6.036738510
step: 10470 | loss: 6.030969239
step: 10480 | loss: 6.025200443
step: 10490 | loss: 6.019432123
step: 10500 | loss: 6.013664279
step: 10510 | loss: 6.007896914
step: 10520 | loss: 6.002130029
step: 10530 | loss: 5.996363624
step: 10540 | loss: 5.990597700
step: 10550 | loss: 5.984832260
step: 10560 | loss: 5.979067304
step: 10570 | loss: 5.973302834
step: 10580 | loss: 5.967538850
step: 10590 | loss: 5.961775354
step: 10600 | loss: 5.956012347
step: 10610 | loss: 5.950249830
step: 10620 | loss: 5.944487805
step: 10630 | loss: 5.938726273
step: 10640 | loss: 5.932965235
step: 10650 | loss: 5.927204692
step: 10660 | loss: 5.921444646
step: 10670 | loss: 5.915685098
step: 10680 | loss: 5.909926048
step: 10690 | loss: 5.904167499
step: 10700 | loss: 5.898409452
step: 10710 | loss: 5.892651908
step: 10720 | loss: 5.886894867
step: 10730 | loss: 5.881138333
step: 10740 | loss: 5.875382305
step: 10750 | loss: 5.869626785
step: 10760 | loss: 5.863871774
step: 10770 | loss: 5.858117275
step: 10780 | loss: 5.852363287
step: 10790 | loss: 5.846609813
step: 10800 | loss: 5.840856853
step: 10810 | loss: 5.835104409
step: 10820 | loss: 5.829352483
step: 10830 | loss: 5.823601075
step: 10840 | loss: 5.817850188
step: 10850 | loss: 5.812099822
step: 10860 | loss: 5.806349978
step: 10870 | loss: 5.800600659
step: 10880 | loss: 5.794851865
step: 10890 | loss: 5.789103598
step: 10900 | loss: 5.783355859
step: 10910 | loss: 5.777608650
step: 10920 | loss: 5.771861971
step: 10930 | loss: 5.766115825
step: 10940 | loss: 5.760370213
step: 10950 | loss: 5.754625136
step: 10960 | loss: 5.748880596
step: 10970 | loss: 5.743136594
step: 10980 | loss: 5.737393131
step: 10990 | loss: 5.731650209
step: 11000 | loss: 5.725907829
step: 11010 | loss: 5.720165993
step: 11020 | loss: 5.714424702
step: 11030 | loss: 5.708683958
step: 11040 | loss: 5.702943762
step: 11050 | loss: 5.697204115
step: 11060 | loss: 5.691465019
step: 11070 | loss: 5.685726476
step: 11080 | loss: 5.679988487
step: 11090 | loss: 5.674251053
step: 11100 | loss: 5.668514176
step: 11110 | loss: 5.662777857
step: 11120 | loss: 5.657042098
step: 11130 | loss: 5.651306901
step: 11140 | loss: 5.645572266
step: 11150 | loss: 5.639838196
step: 11160 | loss: 5.634104692
step: 11170 | loss: 5.628371755
step: 11180 | loss: 5.622639387
step: 11190 | loss: 5.616907590
step: 11200 | loss: 5.611176365
step: 11210 | loss: 5.605445713
step: 11220 | loss: 5.599715636
step: 11230 | loss: 5.593986136
step: 11240 | loss: 5.588257215
step: 11250 | loss: 5.582528873
step: 11260 | loss: 5.576801113
step: 11270 | loss: 5.571073935
step: 11280 | loss: 5.565347343
step: 11290 | loss: 5.559621336
step: 11300 | loss: 5.553895917
step: 11310 | loss: 5.548171088
step: 11320 | loss: 5.542446849
step: 11330 | loss: 5.536723203
step: 11340 | loss: 5.531000152
step: 11350 | loss: 5.525277696
step: 11360 | loss: 5.519555838
step: 11370 | loss: 5.513834578
step: 11380 | loss: 5.508113920
step: 11390 | loss: 5.502393864
step: 11400 | loss: 5.496674412
step: 11410 | loss: 5.490955566
step: 11420 | loss: 5.485237327
step: 11430 | loss: 5.479519698
step: 11440 | loss: 5.473802679
step: 11450 | loss: 5.468086273
step: 11460 | loss: 5.462370481
step: 11470 | loss: 5.456655305
step: 11480 | loss: 5.450940746
step: 11490 | loss: 5.445226807
step: 11500 | loss: 5.439513488
step: 11510 | loss: 5.433800793
step: 11520 | loss: 5.428088722
step: 11530 | loss: 5.422377277
step: 11540 | loss: 5.416666460
step: 11550 | loss: 5.410956273
step: 11560 | loss: 5.405246717
step: 11570 | loss: 5.399537795
step: 11580 | loss: 5.393829507
step: 11590 | loss: 5.388121857
step: 11600 | loss: 5.382414845
step: 11610 | loss: 5.376708473
step: 11620 | loss: 5.371002743
step: 11630 | loss: 5.365297658
step: 11640 | loss: 5.359593218
step: 11650 | loss: 5.353889426
step: 11660 | loss: 5.348186284
step: 11670 | loss: 5.342483792
step: 11680 | loss: 5.336781954
step: 11690 | loss: 5.331080771
step: 11700 | loss: 5.325380244
step: 11710 | loss: 5.319680377
step: 11720 | loss: 5.313981169
step: 11730 | loss: 5.308282624
step: 11740 | loss: 5.302584744
step: 11750 | loss: 5.296887529
step: 11760 | loss: 5.291190983
step: 11770 | loss: 5.285495107
step: 11780 | loss: 5.279799902
step: 11790 | loss: 5.274105371
step: 11800 | loss: 5.268411516
step: 11810 | loss: 5.262718339
step: 11820 | loss: 5.257025841
step: 11830 | loss: 5.251334025
step: 11840 | loss: 5.245642892
step: 11850 | loss: 5.239952445
step: 11860 | loss: 5.234262685
step: 11870 | loss: 5.228573614
step: 11880 | loss: 5.222885235
step: 11890 | loss: 5.217197549
step: 11900 | loss: 5.211510558
step: 11910 | loss: 5.205824265
step: 11920 | loss: 5.200138670
step: 11930 | loss: 5.194453778
step: 11940 | loss: 5.188769588
step: 11950 | loss: 5.183086104
step: 11960 | loss: 5.177403328
step: 11970 | loss: 5.171721261
step: 11980 | loss: 5.166039905
step: 11990 | loss: 5.160359263
step: 12000 | loss: 5.154679337
step: 12010 | loss: 5.149000128
step: 12020 | loss: 5.143321639
step: 12030 | loss: 5.137643872
step: 12040 | loss: 5.131966829
step: 12050 | loss: 5.126290512
step: 12060 | loss: 5.120614924
step: 12070 | loss: 5.114940065
step: 12080 | loss: 5.109265939
step: 12090 | loss: 5.103592548
step: 12100 | loss: 5.097919894
step: 12110 | loss: 5.092247978
step: 12120 | loss: 5.086576803
step: 12130 | loss: 5.080906372
step: 12140 | loss: 5.075236686
step: 12150 | loss: 5.069567748
step: 12160 | loss: 5.063899559
step: 12170 | loss: 5.058232122
step: 12180 | loss: 5.052565440
step: 12190 | loss: 5.046899514
step: 12200 | loss: 5.041234346
step: 12210 | loss: 5.035569939
step: 12220 | loss: 5.029906296
step: 12230 | loss: 5.024243418
step: 12240 | loss: 5.018581307
step: 12250 | loss: 5.012919966
step: 12260 | loss: 5.007259398
step: 12270 | loss: 5.001599603
step: 12280 | loss: 4.995940586
step: 12290 | loss: 4.990282347
step: 12300 | loss: 4.984624890
step: 12310 | loss: 4.978968217
step: 12320 | loss: 4.973312329
step: 12330 | loss: 4.967657230
step: 12340 | loss: 4.962002921
step: 12350 | loss: 4.956349405
step: 12360 | loss: 4.950696685
step: 12370 | loss: 4.945044762
step: 12380 | loss: 4.939393640
step: 12390 | loss: 4.933743319
step: 12400 | loss: 4.928093804
step: 12410 | loss: 4.922445096
step: 12420 | loss: 4.916797198
step: 12430 | loss: 4.911150112
step: 12440 | loss: 4.905503840
step: 12450 | loss: 4.899858385
step: 12460 | loss: 4.894213750
step: 12470 | loss: 4.888569936
step: 12480 | loss: 4.882926947
step: 12490 | loss: 4.877284784
step: 12500 | loss: 4.871643451
step: 12510 | loss: 4.866002950
step: 12520 | loss: 4.860363283
step: 12530 | loss: 4.854724453
step: 12540 | loss: 4.849086462
step: 12550 | loss: 4.843449312
step: 12560 | loss: 4.837813008
step: 12570 | loss: 4.832177550
step: 12580 | loss: 4.826542941
step: 12590 | loss: 4.820909185
step: 12600 | loss: 4.815276283
step: 12610 | loss: 4.809644239
step: 12620 | loss: 4.804013054
step: 12630 | loss: 4.798382732
step: 12640 | loss: 4.792753274
step: 12650 | loss: 4.787124685
step: 12660 | loss: 4.781496965
step: 12670 | loss: 4.775870119
step: 12680 | loss: 4.770244148
step: 12690 | loss: 4.764619055
step: 12700 | loss: 4.758994844
step: 12710 | loss: 4.753371515
step: 12720 | loss: 4.747749073
step: 12730 | loss: 4.742127520
step: 12740 | loss: 4.736506859
step: 12750 | loss: 4.730887092
step: 12760 | loss: 4.725268223
step: 12770 | loss: 4.719650253
step: 12780 | loss: 4.714033186
step: 12790 | loss: 4.708417024
step: 12800 | loss: 4.702801770
step: 12810 | loss: 4.697187428
step: 12820 | loss: 4.691573999
step: 12830 | loss: 4.685961487
step: 12840 | loss: 4.680349894
step: 12850 | loss: 4.674739223
step: 12860 | loss: 4.669129477
step: 12870 | loss: 4.663520659
step: 12880 | loss: 4.657912772
step: 12890 | loss: 4.652305819
step: 12900 | loss: 4.646699802
step: 12910 | loss: 4.641094724
step: 12920 | loss: 4.635490588
step: 12930 | loss: 4.629887398
step: 12940 | loss: 4.624285156
step: 12950 | loss: 4.618683865
step: 12960 | loss: 4.613083527
step: 12970 | loss: 4.607484147
step: 12980 | loss: 4.601885726
step: 12990 | loss: 4.596288269
step: 13000 | loss: 4.590691777
step: 13010 | loss: 4.585096254
step: 13020 | loss: 4.579501703
step: 13030 | loss: 4.573908126
step: 13040 | loss: 4.568315528
step: 13050 | loss: 4.562723910
step: 13060 | loss: 4.557133276
step: 13070 | loss: 4.551543630
step: 13080 | loss: 4.545954973
step: 13090 | loss: 4.540367310
step: 13100 | loss: 4.534780643
step: 13110 | loss: 4.529194975
step: 13120 | loss: 4.523610310
step: 13130 | loss: 4.518026650
step: 13140 | loss: 4.512443999
step: 13150 | loss: 4.506862360
step: 13160 | loss: 4.501281737
step: 13170 | loss: 4.495702131
step: 13180 | loss: 4.490123547
step: 13190 | loss: 4.484545987
step: 13200 | loss: 4.478969456
step: 13210 | loss: 4.473393955
step: 13220 | loss: 4.467819489
step: 13230 | loss: 4.462246060
step: 13240 | loss: 4.456673673
step: 13250 | loss: 4.451102329
step: 13260 | loss: 4.445532032
step: 13270 | loss: 4.439962787
step: 13280 | loss: 4.434394595
step: 13290 | loss: 4.428827461
step: 13300 | loss: 4.423261387
step: 13310 | loss: 4.417696377
step: 13320 | loss: 4.412132435
step: 13330 | loss: 4.406569563
step: 13340 | loss: 4.401007765
step: 13350 | loss: 4.395447045
step: 13360 | loss: 4.389887405
step: 13370 | loss: 4.384328850
step: 13380 | loss: 4.378771383
step: 13390 | loss: 4.373215007
step: 13400 | loss: 4.367659725
step: 13410 | loss: 4.362105542
step: 13420 | loss: 4.356552460
step: 13430 | loss: 4.351000483
step: 13440 | loss: 4.345449615
step: 13450 | loss: 4.339899859
step: 13460 | loss: 4.334351218
step: 13470 | loss: 4.328803697
step: 13480 | loss: 4.323257298
step: 13490 | loss: 4.317712026
step: 13500 | loss: 4.312167883
step: 13510 | loss: 4.306624874
step: 13520 | loss: 4.301083002
step: 13530 | loss: 4.295542271
step: 13540 | loss: 4.290002684
step: 13550 | loss: 4.284464245
step: 13560 | loss: 4.278926958
step: 13570 | loss: 4.273390826
step: 13580 | loss: 4.267855853
step: 13590 | loss: 4.262322043
step: 13600 | loss: 4.256789399
step: 13610 | loss: 4.251257925
step: 13620 | loss: 4.245727626
step: 13630 | loss: 4.240198504
step: 13640 | loss: 4.234670563
step: 13650 | loss: 4.229143808
step: 13660 | loss: 4.223618241
step: 13670 | loss: 4.218093868
step: 13680 | loss: 4.212570691
step: 13690 | loss: 4.207048715
step: 13700 | loss: 4.201527943
step: 13710 | loss: 4.196008379
step: 13720 | loss: 4.190490027
step: 13730 | loss: 4.184972891
step: 13740 | loss: 4.179456975
step: 13750 | loss: 4.173942283
step: 13760 | loss: 4.168428819
step: 13770 | loss: 4.162916587
step: 13780 | loss: 4.157405590
step: 13790 | loss: 4.151895832
step: 13800 | loss: 4.146387319
step: 13810 | loss: 4.140880053
step: 13820 | loss: 4.135374039
step: 13830 | loss: 4.129869280
step: 13840 | loss: 4.124365781
step: 13850 | loss: 4.118863546
step: 13860 | loss: 4.113362579
step: 13870 | loss: 4.107862884
step: 13880 | loss: 4.102364466
step: 13890 | loss: 4.096867327
step: 13900 | loss: 4.091371473
step: 13910 | loss: 4.085876907
step: 13920 | loss: 4.080383634
step: 13930 | loss: 4.074891658
step: 13940 | loss: 4.069400983
step: 13950 | loss: 4.063911613
step: 13960 | loss: 4.058423552
step: 13970 | loss: 4.052936806
step: 13980 | loss: 4.047451378
step: 13990 | loss: 4.041967271
step: 14000 | loss: 4.036484492
step: 14010 | loss: 4.031003043
step: 14020 | loss: 4.025522930
step: 14030 | loss: 4.020044156
step: 14040 | loss: 4.014566726
step: 14050 | loss: 4.009090644
step: 14060 | loss: 4.003615915
step: 14070 | loss: 3.998142542
step: 14080 | loss: 3.992670532
step: 14090 | loss: 3.987199887
step: 14100 | loss: 3.981730612
step: 14110 | loss: 3.976262713
step: 14120 | loss: 3.970796192
step: 14130 | loss: 3.965331055
step: 14140 | loss: 3.959867307
step: 14150 | loss: 3.954404951
step: 14160 | loss: 3.948943992
step: 14170 | loss: 3.943484435
step: 14180 | loss: 3.938026285
step: 14190 | loss: 3.932569546
step: 14200 | loss: 3.927114222
step: 14210 | loss: 3.921660318
step: 14220 | loss: 3.916207840
step: 14230 | loss: 3.910756790
step: 14240 | loss: 3.905307175
step: 14250 | loss: 3.899858999
step: 14260 | loss: 3.894412266
step: 14270 | loss: 3.888966981
step: 14280 | loss: 3.883523149
step: 14290 | loss: 3.878080775
step: 14300 | loss: 3.872639864
step: 14310 | loss: 3.867200419
step: 14320 | loss: 3.861762447
step: 14330 | loss: 3.856325951
step: 14340 | loss: 3.850890937
step: 14350 | loss: 3.845457409
step: 14360 | loss: 3.840025373
step: 14370 | loss: 3.834594833
step: 14380 | loss: 3.829165794
step: 14390 | loss: 3.823738261
step: 14400 | loss: 3.818312239
step: 14410 | loss: 3.812887733
step: 14420 | loss: 3.807464747
step: 14430 | loss: 3.802043287
step: 14440 | loss: 3.796623359
step: 14450 | loss: 3.791204965
step: 14460 | loss: 3.785788113
step: 14470 | loss: 3.780372806
step: 14480 | loss: 3.774959050
step: 14490 | loss: 3.769546851
step: 14500 | loss: 3.764136212
step: 14510 | loss: 3.758727139
step: 14520 | loss: 3.753319638
step: 14530 | loss: 3.747913713
step: 14540 | loss: 3.742509369
step: 14550 | loss: 3.737106612
step: 14560 | loss: 3.731705447
step: 14570 | loss: 3.726305879
step: 14580 | loss: 3.720907914
step: 14590 | loss: 3.715511556
step: 14600 | loss: 3.710116810
step: 14610 | loss: 3.704723683
step: 14620 | loss: 3.699332180
step: 14630 | loss: 3.693942304
step: 14640 | loss: 3.688554063
step: 14650 | loss: 3.683167461
step: 14660 | loss: 3.677782504
step: 14670 | loss: 3.672399197
step: 14680 | loss: 3.667017545
step: 14690 | loss: 3.661637554
step: 14700 | loss: 3.656259230
step: 14710 | loss: 3.650882577
step: 14720 | loss: 3.645507601
step: 14730 | loss: 3.640134308
step: 14740 | loss: 3.634762703
step: 14750 | loss: 3.629392792
step: 14760 | loss: 3.624024579
step: 14770 | loss: 3.618658072
step: 14780 | loss: 3.613293275
step: 14790 | loss: 3.607930193
step: 14800 | loss: 3.602568833
step: 14810 | loss: 3.597209200
step: 14820 | loss: 3.591851300
step: 14830 | loss: 3.586495138
step: 14840 | loss: 3.581140719
step: 14850 | loss: 3.575788051
step: 14860 | loss: 3.570437138
step: 14870 | loss: 3.565087985
step: 14880 | loss: 3.559740600
step: 14890 | loss: 3.554394987
step: 14900 | loss: 3.549051152
step: 14910 | loss: 3.543709101
step: 14920 | loss: 3.538368840
step: 14930 | loss: 3.533030375
step: 14940 | loss: 3.527693711
step: 14950 | loss: 3.522358855
step: 14960 | loss: 3.517025811
step: 14970 | loss: 3.511694587
step: 14980 | loss: 3.506365188
step: 14990 | loss: 3.501037619
step: 15000 | loss: 3.495711887
step: 15010 | loss: 3.490387998
step: 15020 | loss: 3.485065957
step: 15030 | loss: 3.479745772
step: 15040 | loss: 3.474427446
step: 15050 | loss: 3.469110988
step: 15060 | loss: 3.463796402
step: 15070 | loss: 3.458483695
step: 15080 | loss: 3.453172872
step: 15090 | loss: 3.447863940
step: 15100 | loss: 3.442556906
step: 15110 | loss: 3.437251774
step: 15120 | loss: 3.431948551
step: 15130 | loss: 3.426647244
step: 15140 | loss: 3.421347858
step: 15150 | loss: 3.416050400
step: 15160 | loss: 3.410754875
step: 15170 | loss: 3.405461291
step: 15180 | loss: 3.400169652
step: 15190 | loss: 3.394879966
step: 15200 | loss: 3.389592239
step: 15210 | loss: 3.384306477
step: 15220 | loss: 3.379022686
step: 15230 | loss: 3.373740872
step: 15240 | loss: 3.368461042
step: 15250 | loss: 3.363183203
step: 15260 | loss: 3.357907360
step: 15270 | loss: 3.352633519
step: 15280 | loss: 3.347361688
step: 15290 | loss: 3.342091873
step: 15300 | loss: 3.336824079
step: 15310 | loss: 3.331558314
step: 15320 | loss: 3.326294584
step: 15330 | loss: 3.321032895
step: 15340 | loss: 3.315773253
step: 15350 | loss: 3.310515666
step: 15360 | loss: 3.305260140
step: 15370 | loss: 3.300006680
step: 15380 | loss: 3.294755295
step: 15390 | loss: 3.289505989
step: 15400 | loss: 3.284258771
step: 15410 | loss: 3.279013645
step: 15420 | loss: 3.273770620
step: 15430 | loss: 3.268529701
step: 15440 | loss: 3.263290895
step: 15450 | loss: 3.258054208
step: 15460 | loss: 3.252819648
step: 15470 | loss: 3.247587221
step: 15480 | loss: 3.242356934
step: 15490 | loss: 3.237128792
step: 15500 | loss: 3.231902804
step: 15510 | loss: 3.226678975
step: 15520 | loss: 3.221457312
step: 15530 | loss: 3.216237822
step: 15540 | loss: 3.211020512
step: 15550 | loss: 3.205805388
step: 15560 | loss: 3.200592458
step: 15570 | loss: 3.195381727
step: 15580 | loss: 3.190173203
step: 15590 | loss: 3.184966893
step: 15600 | loss: 3.179762803
step: 15610 | loss: 3.174560939
step: 15620 | loss: 3.169361310
step: 15630 | loss: 3.164163921
step: 15640 | loss: 3.158968780
step: 15650 | loss: 3.153775893
step: 15660 | loss: 3.148585267
step: 15670 | loss: 3.143396909
step: 15680 | loss: 3.138210826
step: 15690 | loss: 3.133027025
step: 15700 | loss: 3.127845512
step: 15710 | loss: 3.122666295
step: 15720 | loss: 3.117489381
step: 15730 | loss: 3.112314775
step: 15740 | loss: 3.107142486
step: 15750 | loss: 3.101972520
step: 15760 | loss: 3.096804884
step: 15770 | loss: 3.091639586
step: 15780 | loss: 3.086476631
step: 15790 | loss: 3.081316027
step: 15800 | loss: 3.076157781
step: 15810 | loss: 3.071001900
step: 15820 | loss: 3.065848390
step: 15830 | loss: 3.060697260
step: 15840 | loss: 3.055548515
step: 15850 | loss: 3.050402163
step: 15860 | loss: 3.045258211
step: 15870 | loss: 3.040116665
step: 15880 | loss: 3.034977533
step: 15890 | loss: 3.029840822
step: 15900 | loss: 3.024706539
step: 15910 | loss: 3.019574690
step: 15920 | loss: 3.014445284
step: 15930 | loss: 3.009318326
step: 15940 | loss: 3.004193823
step: 15950 | loss: 2.999071784
step: 15960 | loss: 2.993952214
step: 15970 | loss: 2.988835121
step: 15980 | loss: 2.983720512
step: 15990 | loss: 2.978608394
step: 16000 | loss: 2.973498774
step: 16010 | loss: 2.968391659
step: 16020 | loss: 2.963287056
step: 16030 | loss: 2.958184972
step: 16040 | loss: 2.953085413
step: 16050 | loss: 2.947988388
step: 16060 | loss: 2.942893903
step: 16070 | loss: 2.937801964
step: 16080 | loss: 2.932712580
step: 16090 | loss: 2.927625757
step: 16100 | loss: 2.922541502
step: 16110 | loss: 2.917459821
step: 16120 | loss: 2.912380723
step: 16130 | loss: 2.907304214
step: 16140 | loss: 2.902230301
step: 16150 | loss: 2.897158991
step: 16160 | loss: 2.892090290
step: 16170 | loss: 2.887024207
step: 16180 | loss: 2.881960747
step: 16190 | loss: 2.876899919
step: 16200 | loss: 2.871841727
step: 16210 | loss: 2.866786181
step: 16220 | loss: 2.861733286
step: 16230 | loss: 2.856683049
step: 16240 | loss: 2.851635478
step: 16250 | loss: 2.846590579
step: 16260 | loss: 2.841548359
step: 16270 | loss: 2.836508825
step: 16280 | loss: 2.831471984
step: 16290 | loss: 2.826437843
step: 16300 | loss: 2.821406408
step: 16310 | loss: 2.816377686
step: 16320 | loss: 2.811351684
step: 16330 | loss: 2.806328409
step: 16340 | loss: 2.801307868
step: 16350 | loss: 2.796290066
step: 16360 | loss: 2.791275012
step: 16370 | loss: 2.786262712
step: 16380 | loss: 2.781253172
step: 16390 | loss: 2.776246399
step: 16400 | loss: 2.771242400
step: 16410 | loss: 2.766241181
step: 16420 | loss: 2.761242749
step: 16430 | loss: 2.756247110
step: 16440 | loss: 2.751254272
step: 16450 | loss: 2.746264240
step: 16460 | loss: 2.741277021
step: 16470 | loss: 2.736292622
step: 16480 | loss: 2.731311048
step: 16490 | loss: 2.726332308
step: 16500 | loss: 2.721356406
step: 16510 | loss: 2.716383349
step: 16520 | loss: 2.711413144
step: 16530 | loss: 2.706445796
step: 16540 | loss: 2.701481313
step: 16550 | loss: 2.696519700
step: 16560 | loss: 2.691560964
step: 16570 | loss: 2.686605111
step: 16580 | loss: 2.681652146
step: 16590 | loss: 2.676702077
step: 16600 | loss: 2.671754908
step: 16610 | loss: 2.666810647
step: 16620 | loss: 2.661869299
step: 16630 | loss: 2.656930870
step: 16640 | loss: 2.651995367
step: 16650 | loss: 2.647062794
step: 16660 | loss: 2.642133158
step: 16670 | loss: 2.637206464
step: 16680 | loss: 2.632282719
step: 16690 | loss: 2.627361928
step: 16700 | loss: 2.622444097
step: 16710 | loss: 2.617529231
step: 16720 | loss: 2.612617337
step: 16730 | loss: 2.607708418
step: 16740 | loss: 2.602802482
step: 16750 | loss: 2.597899533
step: 16760 | loss: 2.592999577
step: 16770 | loss: 2.588102619
step: 16780 | loss: 2.583208664
step: 16790 | loss: 2.578317718
step: 16800 | loss: 2.573429786
step: 16810 | loss: 2.568544873
step: 16820 | loss: 2.563662983
step: 16830 | loss: 2.558784123
step: 16840 | loss: 2.553908296
step: 16850 | loss: 2.549035509
step: 16860 | loss: 2.544165765
step: 16870 | loss: 2.539299069
step: 16880 | loss: 2.534435426
step: 16890 | loss: 2.529574841
step: 16900 | loss: 2.524717318
step: 16910 | loss: 2.519862862
step: 16920 | loss: 2.515011477
step: 16930 | loss: 2.510163168
step: 16940 | loss: 2.505317938
step: 16950 | loss: 2.500475792
step: 16960 | loss: 2.495636735
step: 16970 | loss: 2.490800769
step: 16980 | loss: 2.485967900
step: 16990 | loss: 2.481138131
step: 17000 | loss: 2.476311466
step: 17010 | loss: 2.471487908
step: 17020 | loss: 2.466667461
step: 17030 | loss: 2.461850130
step: 17040 | loss: 2.457035917
step: 17050 | loss: 2.452224826
step: 17060 | loss: 2.447416860
step: 17070 | loss: 2.442612022
step: 17080 | loss: 2.437810316
step: 17090 | loss: 2.433011744
step: 17100 | loss: 2.428216310
step: 17110 | loss: 2.423424017
step: 17120 | loss: 2.418634867
step: 17130 | loss: 2.413848862
step: 17140 | loss: 2.409066007
step: 17150 | loss: 2.404286302
step: 17160 | loss: 2.399509750
step: 17170 | loss: 2.394736355
step: 17180 | loss: 2.389966117
step: 17190 | loss: 2.385199039
step: 17200 | loss: 2.380435123
step: 17210 | loss: 2.375674371
step: 17220 | loss: 2.370916785
step: 17230 | loss: 2.366162366
step: 17240 | loss: 2.361411115
step: 17250 | loss: 2.356663035
step: 17260 | loss: 2.351918126
step: 17270 | loss: 2.347176390
step: 17280 | loss: 2.342437828
step: 17290 | loss: 2.337702440
step: 17300 | loss: 2.332970228
step: 17310 | loss: 2.328241192
step: 17320 | loss: 2.323515333
step: 17330 | loss: 2.318792652
step: 17340 | loss: 2.314073148
step: 17350 | loss: 2.309356822
step: 17360 | loss: 2.304643674
step: 17370 | loss: 2.299933703
step: 17380 | loss: 2.295226911
step: 17390 | loss: 2.290523296
step: 17400 | loss: 2.285822858
step: 17410 | loss: 2.281125596
step: 17420 | loss: 2.276431510
step: 17430 | loss: 2.271740598
step: 17440 | loss: 2.267052860
step: 17450 | loss: 2.262368295
step: 17460 | loss: 2.257686901
step: 17470 | loss: 2.253008677
step: 17480 | loss: 2.248333621
step: 17490 | loss: 2.243661732
step: 17500 | loss: 2.238993007
step: 17510 | loss: 2.234327445
step: 17520 | loss: 2.229665043
step: 17530 | loss: 2.225005799
step: 17540 | loss: 2.220349710
step: 17550 | loss: 2.215696774
step: 17560 | loss: 2.211046989
step: 17570 | loss: 2.206400350
step: 17580 | loss: 2.201756854
step: 17590 | loss: 2.197116499
step: 17600 | loss: 2.192479282
step: 17610 | loss: 2.187845197
step: 17620 | loss: 2.183214242
step: 17630 | loss: 2.178586412
step: 17640 | loss: 2.173961704
step: 17650 | loss: 2.169340112
step: 17660 | loss: 2.164721633
step: 17670 | loss: 2.160106262
step: 17680 | loss: 2.155493993
step: 17690 | loss: 2.150884823
step: 17700 | loss: 2.146278745
step: 17710 | loss: 2.141675754
step: 17720 | loss: 2.137075845
step: 17730 | loss: 2.132479012
step: 17740 | loss: 2.127885248
step: 17750 | loss: 2.123294549
step: 17760 | loss: 2.118706907
step: 17770 | loss: 2.114122315
step: 17780 | loss: 2.109540768
step: 17790 | loss: 2.104962259
step: 17800 | loss: 2.100386779
step: 17810 | loss: 2.095814323
step: 17820 | loss: 2.091244882
step: 17830 | loss: 2.086678449
step: 17840 | loss: 2.082115017
step: 17850 | loss: 2.077554576
step: 17860 | loss: 2.072997119
step: 17870 | loss: 2.068442637
step: 17880 | loss: 2.063891122
step: 17890 | loss: 2.059342565
step: 17900 | loss: 2.054796957
step: 17910 | loss: 2.050254289
step: 17920 | loss: 2.045714551
step: 17930 | loss: 2.041177733
step: 17940 | loss: 2.036643826
step: 17950 | loss: 2.032112820
step: 17960 | loss: 2.027584705
step: 17970 | loss: 2.023059470
step: 17980 | loss: 2.018537104
step: 17990 | loss: 2.014017597
step: 18000 | loss: 2.009500938
step: 18010 | loss: 2.004987115
step: 18020 | loss: 2.000476117
step: 18030 | loss: 1.995967933
step: 18040 | loss: 1.991462551
step: 18050 | loss: 1.986959957
step: 18060 | loss: 1.982460142
step: 18070 | loss: 1.977963091
step: 18080 | loss: 1.973468792
step: 18090 | loss: 1.968977233
step: 18100 | loss: 1.964488401
step: 18110 | loss: 1.960002281
step: 18120 | loss: 1.955518862
step: 18130 | loss: 1.951038128
step: 18140 | loss: 1.946560067
step: 18150 | loss: 1.942084665
step: 18160 | loss: 1.937611906
step: 18170 | loss: 1.933141778
step: 18180 | loss: 1.928674264
step: 18190 | loss: 1.924209351
step: 18200 | loss: 1.919747023
step: 18210 | loss: 1.915287266
step: 18220 | loss: 1.910830063
step: 18230 | loss: 1.906375400
step: 18240 | loss: 1.901923261
step: 18250 | loss: 1.897473629
step: 18260 | loss: 1.893026490
step: 18270 | loss: 1.888581825
step: 18280 | loss: 1.884139620
step: 18290 | loss: 1.879699858
step: 18300 | loss: 1.875262521
step: 18310 | loss: 1.870827592
step: 18320 | loss: 1.866395056
step: 18330 | loss: 1.861964894
step: 18340 | loss: 1.857537088
step: 18350 | loss: 1.853111623
step: 18360 | loss: 1.848688478
step: 18370 | loss: 1.844267638
step: 18380 | loss: 1.839849083
step: 18390 | loss: 1.835432795
step: 18400 | loss: 1.831018757
step: 18410 | loss: 1.826606949
step: 18420 | loss: 1.822197353
step: 18430 | loss: 1.817789951
step: 18440 | loss: 1.813384722
step: 18450 | loss: 1.808981649
step: 18460 | loss: 1.804580712
step: 18470 | loss: 1.800181892
step: 18480 | loss: 1.795785169
step: 18490 | loss: 1.791390524
step: 18500 | loss: 1.786997938
step: 18510 | loss: 1.782607390
step: 18520 | loss: 1.778218861
step: 18530 | loss: 1.773832330
step: 18540 | loss: 1.769447779
step: 18550 | loss: 1.765065186
step: 18560 | loss: 1.760684532
step: 18570 | loss: 1.756305796
step: 18580 | loss: 1.751928957
step: 18590 | loss: 1.747553997
step: 18600 | loss: 1.743180893
step: 18610 | loss: 1.738809626
step: 18620 | loss: 1.734440175
step: 18630 | loss: 1.730072518
step: 18640 | loss: 1.725706637
step: 18650 | loss: 1.721342509
step: 18660 | loss: 1.716980114
step: 18670 | loss: 1.712619431
step: 18680 | loss: 1.708260440
step: 18690 | loss: 1.703903119
step: 18700 | loss: 1.699547448
step: 18710 | loss: 1.695193405
step: 18720 | loss: 1.690840970
step: 18730 | loss: 1.686490123
step: 18740 | loss: 1.682140841
step: 18750 | loss: 1.677793105
step: 18760 | loss: 1.673446893
step: 18770 | loss: 1.669102184
step: 18780 | loss: 1.664758959
step: 18790 | loss: 1.660417195
step: 18800 | loss: 1.656076873
step: 18810 | loss: 1.651737971
step: 18820 | loss: 1.647400469
step: 18830 | loss: 1.643064346
step: 18840 | loss: 1.638729583
step: 18850 | loss: 1.634396158
step: 18860 | loss: 1.630064051
step: 18870 | loss: 1.625733241
step: 18880 | loss: 1.621403710
step: 18890 | loss: 1.617075435
step: 18900 | loss: 1.612748398
step: 18910 | loss: 1.608422579
step: 18920 | loss: 1.604097957
step: 18930 | loss: 1.599774514
step: 18940 | loss: 1.595452228
step: 18950 | loss: 1.591131082
step: 18960 | loss: 1.586811055
step: 18970 | loss: 1.582492129
step: 18980 | loss: 1.578174283
step: 18990 | loss: 1.573857500
step: 19000 | loss: 1.569541761
step: 19010 | loss: 1.565227046
step: 19020 | loss: 1.560913338
step: 19030 | loss: 1.556600618
step: 19040 | loss: 1.552288868
step: 19050 | loss: 1.547978070
step: 19060 | loss: 1.543668205
step: 19070 | loss: 1.539359257
step: 19080 | loss: 1.535051208
step: 19090 | loss: 1.530744041
step: 19100 | loss: 1.526437738
step: 19110 | loss: 1.522132283
step: 19120 | loss: 1.517827659
step: 19130 | loss: 1.513523849
step: 19140 | loss: 1.509220837
step: 19150 | loss: 1.504918607
step: 19160 | loss: 1.500617144
step: 19170 | loss: 1.496316430
step: 19180 | loss: 1.492016451
step: 19190 | loss: 1.487717192
step: 19200 | loss: 1.483418638
step: 19210 | loss: 1.479120773
step: 19220 | loss: 1.474823583
step: 19230 | loss: 1.470527054
step: 19240 | loss: 1.466231171
step: 19250 | loss: 1.461935920
step: 19260 | loss: 1.457641289
step: 19270 | loss: 1.453347262
step: 19280 | loss: 1.449053828
step: 19290 | loss: 1.444760973
step: 19300 | loss: 1.440468683
step: 19310 | loss: 1.436176947
step: 19320 | loss: 1.431885753
step: 19330 | loss: 1.427595087
step: 19340 | loss: 1.423304939
step: 19350 | loss: 1.419015296
step: 19360 | loss: 1.414726147
step: 19370 | loss: 1.410437481
step: 19380 | loss: 1.406149287
step: 19390 | loss: 1.401861554
step: 19400 | loss: 1.397574271
step: 19410 | loss: 1.393287429
step: 19420 | loss: 1.389001017
step: 19430 | loss: 1.384715025
step: 19440 | loss: 1.380429444
step: 19450 | loss: 1.376144264
step: 19460 | loss: 1.371859476
step: 19470 | loss: 1.367575072
step: 19480 | loss: 1.363291041
step: 19490 | loss: 1.359007377
step: 19500 | loss: 1.354724069
step: 19510 | loss: 1.350441111
step: 19520 | loss: 1.346158494
step: 19530 | loss: 1.341876211
step: 19540 | loss: 1.337594254
step: 19550 | loss: 1.333312615
step: 19560 | loss: 1.329031288
step: 19570 | loss: 1.324750266
step: 19580 | loss: 1.320469541
step: 19590 | loss: 1.316189107
step: 19600 | loss: 1.311908958
step: 19610 | loss: 1.307629088
step: 19620 | loss: 1.303349490
step: 19630 | loss: 1.299070158
step: 19640 | loss: 1.294791088
step: 19650 | loss: 1.290512272
step: 19660 | loss: 1.286233707
step: 19670 | loss: 1.281955386
step: 19680 | loss: 1.277677305
step: 19690 | loss: 1.273399458
step: 19700 | loss: 1.269121841
step: 19710 | loss: 1.264844449
step: 19720 | loss: 1.260567277
step: 19730 | loss: 1.256290322
step: 19740 | loss: 1.252013579
step: 19750 | loss: 1.247737044
step: 19760 | loss: 1.243460713
step: 19770 | loss: 1.239184581
step: 19780 | loss: 1.234908646
step: 19790 | loss: 1.230632904
step: 19800 | loss: 1.226357350
step: 19810 | loss: 1.222081983
step: 19820 | loss: 1.217806797
step: 19830 | loss: 1.213531791
step: 19840 | loss: 1.209256961
step: 19850 | loss: 1.204982304
step: 19860 | loss: 1.200707817
step: 19870 | loss: 1.196433497
step: 19880 | loss: 1.192159342
step: 19890 | loss: 1.187885349
step: 19900 | loss: 1.183611515
step: 19910 | loss: 1.179337838
step: 19920 | loss: 1.175064315
step: 19930 | loss: 1.170790944
step: 19940 | loss: 1.166517723
step: 19950 | loss: 1.162244649
step: 19960 | loss: 1.157971720
step: 19970 | loss: 1.153698935
step: 19980 | loss: 1.149426291
step: 19990 | loss: 1.145153786
step: 20000 | loss: 1.140881418
step: 20010 | loss: 1.136609185
step: 20020 | loss: 1.132337087
step: 20030 | loss: 1.128065119
step: 20040 | loss: 1.123793282
step: 20050 | loss: 1.119521573
step: 20060 | loss: 1.115249991
step: 20070 | loss: 1.110978534
step: 20080 | loss: 1.106707200
step: 20090 | loss: 1.102435988
step: 20100 | loss: 1.098164897
step: 20110 | loss: 1.093893925
step: 20120 | loss: 1.089623070
step: 20130 | loss: 1.085352332
step: 20140 | loss: 1.081081708
step: 20150 | loss: 1.076811198
step: 20160 | loss: 1.072540800
step: 20170 | loss: 1.068270512
step: 20180 | loss: 1.064000335
step: 20190 | loss: 1.059730265
step: 20200 | loss: 1.055460303
step: 20210 | loss: 1.051190447
step: 20220 | loss: 1.046920696
step: 20230 | loss: 1.042651048
step: 20240 | loss: 1.038381503
step: 20250 | loss: 1.034112060
step: 20260 | loss: 1.029842716
step: 20270 | loss: 1.025573472
step: 20280 | loss: 1.021304326
step: 20290 | loss: 1.017035278
step: 20300 | loss: 1.012766325
step: 20310 | loss: 1.008497468
step: 20320 | loss: 1.004228704
step: 20330 | loss: 0.999960034
step: 20340 | loss: 0.995691456
step: 20350 | loss: 0.991422970
step: 20360 | loss: 0.987154573
step: 20370 | loss: 0.982886266
step: 20380 | loss: 0.978618047
step: 20390 | loss: 0.974349916
step: 20400 | loss: 0.970081872
step: 20410 | loss: 0.965813913
step: 20420 | loss: 0.961546039
step: 20430 | loss: 0.957278249
step: 20440 | loss: 0.953010542
step: 20450 | loss: 0.948742918
step: 20460 | loss: 0.944475375
step: 20470 | loss: 0.940207913
step: 20480 | loss: 0.935940530
step: 20490 | loss: 0.931673227
step: 20500 | loss: 0.927406002
step: 20510 | loss: 0.923138854
step: 20520 | loss: 0.918871783
step: 20530 | loss: 0.914604788
step: 20540 | loss: 0.910337868
step: 20550 | loss: 0.906071022
step: 20560 | loss: 0.901804250
step: 20570 | loss: 0.897537551
step: 20580 | loss: 0.893270924
step: 20590 | loss: 0.889004369
step: 20600 | loss: 0.884737884
step: 20610 | loss: 0.880471469
step: 20620 | loss: 0.876205124
step: 20630 | loss: 0.871938847
step: 20640 | loss: 0.867672638
step: 20650 | loss: 0.863406497
step: 20660 | loss: 0.859140422
step: 20670 | loss: 0.854874412
step: 20680 | loss: 0.850608469
step: 20690 | loss: 0.846342589
step: 20700 | loss: 0.842076774
step: 20710 | loss: 0.837811022
step: 20720 | loss: 0.833545333
step: 20730 | loss: 0.829279705
step: 20740 | loss: 0.825014139
step: 20750 | loss: 0.820748634
step: 20760 | loss: 0.816483190
step: 20770 | loss: 0.812217804
step: 20780 | loss: 0.807952478
step: 20790 | loss: 0.803687210
step: 20800 | loss: 0.799422000
step: 20810 | loss: 0.795156848
step: 20820 | loss: 0.790891752
step: 20830 | loss: 0.786626712
step: 20840 | loss: 0.782361728
step: 20850 | loss: 0.778096798
step: 20860 | loss: 0.773831923
step: 20870 | loss: 0.769567102
step: 20880 | loss: 0.765302335
step: 20890 | loss: 0.761037620
step: 20900 | loss: 0.756772958
step: 20910 | loss: 0.752508347
step: 20920 | loss: 0.748243788
step: 20930 | loss: 0.743979279
step: 20940 | loss: 0.739714821
step: 20950 | loss: 0.735450412
step: 20960 | loss: 0.731186053
step: 20970 | loss: 0.726921742
step: 20980 | loss: 0.722657480
step: 20990 | loss: 0.718393265
step: 21000 | loss: 0.714129098
step: 21010 | loss: 0.709864978
step: 21020 | loss: 0.705600904
step: 21030 | loss: 0.701336876
step: 21040 | loss: 0.697072893
step: 21050 | loss: 0.692808955
step: 21060 | loss: 0.688545062
step: 21070 | loss: 0.684281213
step: 21080 | loss: 0.680017408
step: 21090 | loss: 0.675753646
step: 21100 | loss: 0.671489926
step: 21110 | loss: 0.667226250
step: 21120 | loss: 0.662962615
step: 21130 | loss: 0.658699021
step: 21140 | loss: 0.654435469
step: 21150 | loss: 0.650171957
step: 21160 | loss: 0.645908486
step: 21170 | loss: 0.641645054
step: 21180 | loss: 0.637381662
step: 21190 | loss: 0.633118309
step: 21200 | loss: 0.628854995
step: 21210 | loss: 0.624591719
step: 21220 | loss: 0.620328481
step: 21230 | loss: 0.616065281
step: 21240 | loss: 0.611802118
step: 21250 | loss: 0.607538992
step: 21260 | loss: 0.603275902
step: 21270 | loss: 0.599012848
step: 21280 | loss: 0.594749830
step: 21290 | loss: 0.590486847
step: 21300 | loss: 0.586223899
step: 21310 | loss: 0.581960986
step: 21320 | loss: 0.577698108
step: 21330 | loss: 0.573435263
step: 21340 | loss: 0.569172452
step: 21350 | loss: 0.564909674
step: 21360 | loss: 0.560646929
step: 21370 | loss: 0.556384217
step: 21380 | loss: 0.552121537
step: 21390 | loss: 0.547858889
step: 21400 | loss: 0.543596273
step: 21410 | loss: 0.539333688
step: 21420 | loss: 0.535071135
step: 21430 | loss: 0.530808611
step: 21440 | loss: 0.526546119
step: 21450 | loss: 0.522283656
step: 21460 | loss: 0.518021224
step: 21470 | loss: 0.513758821
step: 21480 | loss: 0.509496447
step: 21490 | loss: 0.505234102
step: 21500 | loss: 0.500971785
step: 21510 | loss: 0.496709497
step: 21520 | loss: 0.492447238
step: 21530 | loss: 0.488185005
step: 21540 | loss: 0.483922801
step: 21550 | loss: 0.479660624
step: 21560 | loss: 0.475398473
step: 21570 | loss: 0.471136350
step: 21580 | loss: 0.466874253
step: 21590 | loss: 0.462612182
step: 21600 | loss: 0.458350137
step: 21610 | loss: 0.454088117
step: 21620 | loss: 0.449826123
step: 21630 | loss: 0.445564154
step: 21640 | loss: 0.441302210
step: 21650 | loss: 0.437040291
step: 21660 | loss: 0.432778396
step: 21670 | loss: 0.428516525
step: 21680 | loss: 0.424254679
step: 21690 | loss: 0.419992856
step: 21700 | loss: 0.415731056
step: 21710 | loss: 0.411469279
step: 21720 | loss: 0.407207526
step: 21730 | loss: 0.402945795
step: 21740 | loss: 0.398684087
step: 21750 | loss: 0.394422401
step: 21760 | loss: 0.390160737
step: 21770 | loss: 0.385899096
step: 21780 | loss: 0.381637475
step: 21790 | loss: 0.377375876
step: 21800 | loss: 0.373114299
step: 21810 | loss: 0.368852742
step: 21820 | loss: 0.364591206
step: 21830 | loss: 0.360329691
step: 21840 | loss: 0.356068196
step: 21850 | loss: 0.351806721
step: 21860 | loss: 0.347545266
step: 21870 | loss: 0.343283831
step: 21880 | loss: 0.339022416
step: 21890 | loss: 0.334761020
step: 21900 | loss: 0.330499643
step: 21910 | loss: 0.326238285
step: 21920 | loss: 0.321976946
step: 21930 | loss: 0.317715626
step: 21940 | loss: 0.313454324
step: 21950 | loss: 0.309193040
step: 21960 | loss: 0.304931775
step: 21970 | loss: 0.300670527
step: 21980 | loss: 0.296409297
step: 21990 | loss: 0.292148084
step: 22000 | loss: 0.287886889
step: 22010 | loss: 0.283625711
step: 22020 | loss: 0.279364550
step: 22030 | loss: 0.275103406
step: 22040 | loss: 0.270842279
step: 22050 | loss: 0.266581168
step: 22060 | loss: 0.262320073
step: 22070 | loss: 0.258058995
step: 22080 | loss: 0.253797933
step: 22090 | loss: 0.249536886
step: 22100 | loss: 0.245275855
step: 22110 | loss: 0.241014840
step: 22120 | loss: 0.236753840
step: 22130 | loss: 0.232492856
step: 22140 | loss: 0.228231886
step: 22150 | loss: 0.223970932
step: 22160 | loss: 0.219709992
step: 22170 | loss: 0.215449067
step: 22180 | loss: 0.211188156
step: 22190 | loss: 0.206927260
step: 22200 | loss: 0.202666378
step: 22210 | loss: 0.198405510
step: 22220 | loss: 0.194144656
step: 22230 | loss: 0.189883815
step: 22240 | loss: 0.185622989
step: 22250 | loss: 0.181362175
step: 22260 | loss: 0.177101376
step: 22270 | loss: 0.172840589
step: 22280 | loss: 0.168579816
step: 22290 | loss: 0.164319055
step: 22300 | loss: 0.160058308
step: 22310 | loss: 0.155797573
step: 22320 | loss: 0.151536851
step: 22330 | loss: 0.147276141
step: 22340 | loss: 0.143015444
step: 22350 | loss: 0.138754758
step: 22360 | loss: 0.134494085
step: 22370 | loss: 0.130233424
step: 22380 | loss: 0.125972775
step: 22390 | loss: 0.121712138
step: 22400 | loss: 0.117451512
step: 22410 | loss: 0.113190897
step: 22420 | loss: 0.108930295
step: 22430 | loss: 0.104669703
step: 22440 | loss: 0.100409122
step: 22450 | loss: 0.096148553
step: 22460 | loss: 0.091887995
step: 22470 | loss: 0.087627447
step: 22480 | loss: 0.083366910
step: 22490 | loss: 0.079106384
step: 22500 | loss: 0.074845868
step: 22510 | loss: 0.070585363
step: 22520 | loss: 0.066324868
step: 22530 | loss: 0.062064383
step: 22540 | loss: 0.057803908
step: 22550 | loss: 0.053543444
step: 22560 | loss: 0.049282989
step: 22570 | loss: 0.045022544
step: 22580 | loss: 0.040762109
step: 22590 | loss: 0.036501683
step: 22600 | loss: 0.032241267
step: 22610 | loss: 0.027980860
step: 22620 | loss: 0.023720463
step: 22630 | loss: 0.019460075
step: 22640 | loss: 0.015199696
step: 22650 | loss: 0.010939326
step: 22660 | loss: 0.006678965
step: 22670 | loss: 0.002418613
- final loss: 0.000714
-> compiled  owl-opt.0.0.1
-> removed   owl-opt.0.0.1
-> installed owl-opt.0.0.1
Done.
# To update the current shell environment, run: eval $(opam env)
2026-03-16 20:53.28 ---> saved as "43b163d799d194f7f0828789c8180863ba1daad00e6796cb5b8f51814343b932"
Job succeeded
2026-03-16 20:53.37: Job succeeded