Package evaluation of SDeMo on Julia 1.10.9 (96dc2d8c45*) started at 2025-06-06T16:11:54.278


################################################################################
# Set-up
#

Installing PkgEval dependencies (TestEnv)...

Set-up completed after 4.93s


################################################################################
# Installation
#

Installing SDeMo...
   Resolving package versions...
    Updating `~/.julia/environments/v1.10/Project.toml`
  [3e5feb82] + SDeMo v1.4.0
    Updating `~/.julia/environments/v1.10/Manifest.toml`
  [66dad0bd] + AliasTables v1.1.3
  [7d9fca2a] + Arpack v0.5.4
  [34da2185] + Compat v4.16.0
  [9a962f9c] + DataAPI v1.16.0
  [864edb3b] + DataStructures v0.18.22
  [31c24e10] + Distributions v0.25.120
  [ffbed154] + DocStringExtensions v0.9.4
  [1a297f60] + FillArrays v1.13.0
  [34004b35] + HypergeometricFunctions v0.3.28
  [92d709cd] + IrrationalConstants v0.2.4
  [692b3bcd] + JLLWrappers v1.7.0
  [682c06a0] + JSON v0.21.4
  [2ab3a3ac] + LogExpFunctions v0.3.29
  [e1d29d7a] + Missings v1.2.0
  [6f286f6a] + MultivariateStats v0.10.3
  [bac558e1] + OrderedCollections v1.8.1
  [90014a1f] + PDMats v0.11.35
  [69de0a69] + Parsers v2.8.3
⌅ [aea7be01] + PrecompileTools v1.2.1
  [21216c6a] + Preferences v1.4.3
  [43287f4e] + PtrArrays v1.3.0
  [1fd47b50] + QuadGK v2.11.2
  [189a3867] + Reexport v1.2.2
  [79098fc4] + Rmath v0.8.0
  [3e5feb82] + SDeMo v1.4.0
  [a2af1166] + SortingAlgorithms v1.2.1
  [276daf66] + SpecialFunctions v2.5.1
  [82ae8749] + StatsAPI v1.7.1
  [2913bbd2] + StatsBase v0.34.5
  [4c63d2b9] + StatsFuns v1.5.0
  [1c621080] + TestItems v1.0.0
⌅ [68821587] + Arpack_jll v3.5.1+1
  [efe28fd5] + OpenSpecFun_jll v0.5.6+0
  [f50d1b31] + Rmath_jll v0.5.1+0
  [0dad84c5] + ArgTools v1.1.1
  [56f22d72] + Artifacts
  [2a0f44e3] + Base64
  [ade2ca70] + Dates
  [f43a241f] + Downloads v1.6.0
  [7b1f6079] + FileWatching
  [b77e0a4c] + InteractiveUtils
  [b27032c2] + LibCURL v0.6.4
  [76f85450] + LibGit2
  [8f399da3] + Libdl
  [37e2e46d] + LinearAlgebra
  [56ddb016] + Logging
  [d6f4376e] + Markdown
  [a63ad114] + Mmap
  [ca575930] + NetworkOptions v1.2.0
  [44cfe95a] + Pkg v1.10.0
  [de0858da] + Printf
  [3fa0cd96] + REPL
  [9a3f8284] + Random
  [ea8e919c] + SHA v0.7.0
  [9e88b42a] + Serialization
  [6462fe0b] + Sockets
  [2f01184e] + SparseArrays v1.10.0
  [10745b16] + Statistics v1.10.0
  [4607b0f0] + SuiteSparse
  [fa267f1f] + TOML v1.0.3
  [a4e569a6] + Tar v1.10.0
  [cf7118a7] + UUIDs
  [4ec0a83e] + Unicode
  [e66e0078] + CompilerSupportLibraries_jll v1.1.1+0
  [deac9b47] + LibCURL_jll v8.4.0+0
  [e37daf67] + LibGit2_jll v1.6.4+0
  [29816b5a] + LibSSH2_jll v1.11.0+1
  [c8ffd9c3] + MbedTLS_jll v2.28.2+1
  [14a3606d] + MozillaCACerts_jll v2023.1.10
  [4536629a] + OpenBLAS_jll v0.3.23+4
  [05823500] + OpenLibm_jll v0.8.5+0
  [bea87d4a] + SuiteSparse_jll v7.2.1+1
  [83775a58] + Zlib_jll v1.2.13+1
  [8e850b90] + libblastrampoline_jll v5.11.0+0
  [8e850ede] + nghttp2_jll v1.52.0+1
  [3f19e933] + p7zip_jll v17.4.0+2
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading. To see why use `status --outdated -m`

Installation completed after 8.33s


################################################################################
# Precompilation
#

Precompiling PkgEval dependencies...

Precompiling package dependencies...

Precompilation completed after 22.7s


################################################################################
# Testing
#

     Testing SDeMo
      Status `/tmp/jl_t4xOfv/Project.toml`
  [3e5feb82] SDeMo v1.4.0
  [f8b46487] TestItemRunner v1.1.0
  [10745b16] Statistics v1.10.0
  [8dfed614] Test
      Status `/tmp/jl_t4xOfv/Manifest.toml`
  [66dad0bd] AliasTables v1.1.3
  [7d9fca2a] Arpack v0.5.4
  [34da2185] Compat v4.16.0
  [9a962f9c] DataAPI v1.16.0
  [864edb3b] DataStructures v0.18.22
  [31c24e10] Distributions v0.25.120
  [ffbed154] DocStringExtensions v0.9.4
  [1a297f60] FillArrays v1.13.0
  [34004b35] HypergeometricFunctions v0.3.28
  [92d709cd] IrrationalConstants v0.2.4
  [692b3bcd] JLLWrappers v1.7.0
  [682c06a0] JSON v0.21.4
  [2ab3a3ac] LogExpFunctions v0.3.29
  [e1d29d7a] Missings v1.2.0
  [6f286f6a] MultivariateStats v0.10.3
  [bac558e1] OrderedCollections v1.8.1
  [90014a1f] PDMats v0.11.35
  [69de0a69] Parsers v2.8.3
⌅ [aea7be01] PrecompileTools v1.2.1
  [21216c6a] Preferences v1.4.3
  [43287f4e] PtrArrays v1.3.0
  [1fd47b50] QuadGK v2.11.2
  [189a3867] Reexport v1.2.2
  [79098fc4] Rmath v0.8.0
  [3e5feb82] SDeMo v1.4.0
  [a2af1166] SortingAlgorithms v1.2.1
  [276daf66] SpecialFunctions v2.5.1
  [82ae8749] StatsAPI v1.7.1
  [2913bbd2] StatsBase v0.34.5
  [4c63d2b9] StatsFuns v1.5.0
  [f8b46487] TestItemRunner v1.1.0
  [1c621080] TestItems v1.0.0
⌅ [68821587] Arpack_jll v3.5.1+1
  [efe28fd5] OpenSpecFun_jll v0.5.6+0
  [f50d1b31] Rmath_jll v0.5.1+0
  [0dad84c5] ArgTools v1.1.1
  [56f22d72] Artifacts
  [2a0f44e3] Base64
  [ade2ca70] Dates
  [f43a241f] Downloads v1.6.0
  [7b1f6079] FileWatching
  [b77e0a4c] InteractiveUtils
  [b27032c2] LibCURL v0.6.4
  [76f85450] LibGit2
  [8f399da3] Libdl
  [37e2e46d] LinearAlgebra
  [56ddb016] Logging
  [d6f4376e] Markdown
  [a63ad114] Mmap
  [ca575930] NetworkOptions v1.2.0
  [44cfe95a] Pkg v1.10.0
  [de0858da] Printf
  [3fa0cd96] REPL
  [9a3f8284] Random
  [ea8e919c] SHA v0.7.0
  [9e88b42a] Serialization
  [6462fe0b] Sockets
  [2f01184e] SparseArrays v1.10.0
  [10745b16] Statistics v1.10.0
  [4607b0f0] SuiteSparse
  [fa267f1f] TOML v1.0.3
  [a4e569a6] Tar v1.10.0
  [8dfed614] Test
  [cf7118a7] UUIDs
  [4ec0a83e] Unicode
  [e66e0078] CompilerSupportLibraries_jll v1.1.1+0
  [deac9b47] LibCURL_jll v8.4.0+0
  [e37daf67] LibGit2_jll v1.6.4+0
  [29816b5a] LibSSH2_jll v1.11.0+1
  [c8ffd9c3] MbedTLS_jll v2.28.2+1
  [14a3606d] MozillaCACerts_jll v2023.1.10
  [4536629a] OpenBLAS_jll v0.3.23+4
  [05823500] OpenLibm_jll v0.8.5+0
  [bea87d4a] SuiteSparse_jll v7.2.1+1
  [83775a58] Zlib_jll v1.2.13+1
  [8e850b90] libblastrampoline_jll v5.11.0+0
  [8e850ede] nghttp2_jll v1.52.0+1
  [3f19e933] p7zip_jll v17.4.0+2
        Info Packages marked with ⌅ have new versions available but compatibility constraints restrict them from upgrading.
     Testing Running tests...
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:90
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.564
[ Info: Optimal var. pool: [1, 12, 19]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:44
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:44
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.786
[ Info: [ 2 vars.] MCC val. ≈ 0.814
[ Info: Optimal var. pool: [5, 2]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:44
[ Info: [19 vars.] MCC val. ≈ -0.0
[ Info: [18 vars.] MCC val. ≈ 0.464
[ Info: [17 vars.] MCC val. ≈ 0.74
[ Info: Optimal var. pool: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18]
┌ Warning: backwardselection! will be deprecated - use variables! with BackwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:44
[ Info: [ 9 vars.] MCC val. ≈ -0.0
[ Info: [ 8 vars.] MCC val. ≈ 0.714
[ Info: [ 7 vars.] MCC val. ≈ 0.72
[ Info: Optimal var. pool: [2, 3, 4, 5, 7, 8, 9]
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:90
[ Info: [ 2 vars.] MCC val. ≈ -0.0
[ Info: [ 3 vars.] MCC val. ≈ 0.412
[ Info: Optimal var. pool: [12, 13, 1]
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: forwardselection! will be deprecated - use variables! with ForwardSelection instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/selection.jl:90
[ Info: [ 0 vars.] MCC val. ≈ -0.0
[ Info: [ 1 vars.] MCC val. ≈ 0.773
[ Info: [ 2 vars.] MCC val. ≈ 0.786
[ Info: [ 3 vars.] MCC val. ≈ 0.787
[ Info: [ 4 vars.] MCC val. ≈ 0.795
[ Info: Optimal var. pool: [5, 15, 4, 14]
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
┌ Warning: stepwisevif! will be deprecated - use variables! with VarianceInflationFactor instead
└ @ SDeMo ~/.julia/packages/SDeMo/WBmCZ/src/variables/vif.jl:24
[ Info: Baseline mcc: -2.8367742685852565e-17
[ Info: Optimal 1 variables model - mcc ≈ 0.7311
[ Info: Optimal 2 variables model - mcc ≈ 0.7615
[ Info: Optimal 3 variables model - mcc ≈ 0.7779
[ Info: Returning model with 4 variables - mcc ≈ 0.7779
[ Info: [  0%] LOSS: training ≈ 0.4952 validation ≈ 0.4905 ( 99%)
[ Info: [  1%] LOSS: training ≈ 0.4232 validation ≈ 0.42   ( 99%)
[ Info: [  2%] LOSS: training ≈ 0.3881 validation ≈ 0.3836 ( 99%)
[ Info: [  2%] LOSS: training ≈ 0.3672 validation ≈ 0.3613 ( 98%)
[ Info: [  2%] LOSS: training ≈ 0.3533 validation ≈ 0.3463 ( 98%)
[ Info: [  3%] LOSS: training ≈ 0.3432 validation ≈ 0.3354 ( 98%)
[ Info: [  4%] LOSS: training ≈ 0.3355 validation ≈ 0.3271 ( 97%)
[ Info: [  4%] LOSS: training ≈ 0.3293 validation ≈ 0.3205 ( 97%)
[ Info: [  4%] LOSS: training ≈ 0.3243 validation ≈ 0.3151 ( 97%)
[ Info: [  5%] LOSS: training ≈ 0.32   validation ≈ 0.3106 ( 97%)
[ Info: [  6%] LOSS: training ≈ 0.3163 validation ≈ 0.3067 ( 97%)
[ Info: [  6%] LOSS: training ≈ 0.3131 validation ≈ 0.3033 ( 97%)
[ Info: [  6%] LOSS: training ≈ 0.3103 validation ≈ 0.3004 ( 97%)
[ Info: [  7%] LOSS: training ≈ 0.3078 validation ≈ 0.2977 ( 97%)
[ Info: [  8%] LOSS: training ≈ 0.3055 validation ≈ 0.2954 ( 97%)
[ Info: [  8%] LOSS: training ≈ 0.3034 validation ≈ 0.2932 ( 97%)
[ Info: [  8%] LOSS: training ≈ 0.3015 validation ≈ 0.2912 ( 97%)
[ Info: [  9%] LOSS: training ≈ 0.2997 validation ≈ 0.2894 ( 97%)
[ Info: [ 10%] LOSS: training ≈ 0.2981 validation ≈ 0.2877 ( 97%)
[ Info: [ 10%] LOSS: training ≈ 0.2966 validation ≈ 0.2861 ( 96%)
[ Info: [ 10%] LOSS: training ≈ 0.2952 validation ≈ 0.2846 ( 96%)
[ Info: [ 11%] LOSS: training ≈ 0.2938 validation ≈ 0.2833 ( 96%)
[ Info: [ 12%] LOSS: training ≈ 0.2926 validation ≈ 0.2819 ( 96%)
[ Info: [ 12%] LOSS: training ≈ 0.2914 validation ≈ 0.2807 ( 96%)
[ Info: [ 12%] LOSS: training ≈ 0.2903 validation ≈ 0.2795 ( 96%)
[ Info: [ 13%] LOSS: training ≈ 0.2893 validation ≈ 0.2784 ( 96%)
[ Info: [ 14%] LOSS: training ≈ 0.2883 validation ≈ 0.2773 ( 96%)
[ Info: [ 14%] LOSS: training ≈ 0.2873 validation ≈ 0.2763 ( 96%)
[ Info: [ 14%] LOSS: training ≈ 0.2864 validation ≈ 0.2753 ( 96%)
[ Info: [ 15%] LOSS: training ≈ 0.2855 validation ≈ 0.2744 ( 96%)
[ Info: [ 16%] LOSS: training ≈ 0.2847 validation ≈ 0.2735 ( 96%)
[ Info: [ 16%] LOSS: training ≈ 0.2839 validation ≈ 0.2726 ( 96%)
[ Info: [ 16%] LOSS: training ≈ 0.2832 validation ≈ 0.2718 ( 96%)
[ Info: [ 17%] LOSS: training ≈ 0.2825 validation ≈ 0.271  ( 96%)
[ Info: [ 18%] LOSS: training ≈ 0.2818 validation ≈ 0.2702 ( 96%)
[ Info: [ 18%] LOSS: training ≈ 0.2811 validation ≈ 0.2694 ( 96%)
[ Info: [ 18%] LOSS: training ≈ 0.2804 validation ≈ 0.2687 ( 96%)
[ Info: [ 19%] LOSS: training ≈ 0.2798 validation ≈ 0.268  ( 96%)
[ Info: [ 20%] LOSS: training ≈ 0.2792 validation ≈ 0.2673 ( 96%)
[ Info: [ 20%] LOSS: training ≈ 0.2787 validation ≈ 0.2667 ( 96%)
[ Info: [ 20%] LOSS: training ≈ 0.2781 validation ≈ 0.266  ( 96%)
[ Info: [ 21%] LOSS: training ≈ 0.2776 validation ≈ 0.2654 ( 96%)
[ Info: [ 22%] LOSS: training ≈ 0.2771 validation ≈ 0.2648 ( 96%)
[ Info: [ 22%] LOSS: training ≈ 0.2766 validation ≈ 0.2642 ( 96%)
[ Info: [ 22%] LOSS: training ≈ 0.2761 validation ≈ 0.2637 ( 96%)
[ Info: [ 23%] LOSS: training ≈ 0.2756 validation ≈ 0.2631 ( 95%)
[ Info: [ 24%] LOSS: training ≈ 0.2752 validation ≈ 0.2626 ( 95%)
[ Info: [ 24%] LOSS: training ≈ 0.2747 validation ≈ 0.2621 ( 95%)
[ Info: [ 24%] LOSS: training ≈ 0.2743 validation ≈ 0.2616 ( 95%)
[ Info: [ 25%] LOSS: training ≈ 0.2739 validation ≈ 0.2611 ( 95%)
[ Info: [ 26%] LOSS: training ≈ 0.2735 validation ≈ 0.2606 ( 95%)
[ Info: [ 26%] LOSS: training ≈ 0.2731 validation ≈ 0.2601 ( 95%)
[ Info: [ 26%] LOSS: training ≈ 0.2727 validation ≈ 0.2597 ( 95%)
[ Info: [ 27%] LOSS: training ≈ 0.2724 validation ≈ 0.2592 ( 95%)
[ Info: [ 28%] LOSS: training ≈ 0.272  validation ≈ 0.2588 ( 95%)
[ Info: [ 28%] LOSS: training ≈ 0.2717 validation ≈ 0.2584 ( 95%)
[ Info: [ 28%] LOSS: training ≈ 0.2714 validation ≈ 0.258  ( 95%)
[ Info: [ 29%] LOSS: training ≈ 0.271  validation ≈ 0.2576 ( 95%)
[ Info: [ 30%] LOSS: training ≈ 0.2707 validation ≈ 0.2572 ( 95%)
[ Info: [ 30%] LOSS: training ≈ 0.2704 validation ≈ 0.2568 ( 95%)
[ Info: [ 30%] LOSS: training ≈ 0.2701 validation ≈ 0.2564 ( 95%)
[ Info: [ 31%] LOSS: training ≈ 0.2699 validation ≈ 0.2561 ( 95%)
[ Info: [ 32%] LOSS: training ≈ 0.2696 validation ≈ 0.2557 ( 95%)
[ Info: [ 32%] LOSS: training ≈ 0.2693 validation ≈ 0.2554 ( 95%)
[ Info: [ 32%] LOSS: training ≈ 0.2691 validation ≈ 0.255  ( 95%)
[ Info: [ 33%] LOSS: training ≈ 0.2688 validation ≈ 0.2547 ( 95%)
[ Info: [ 34%] LOSS: training ≈ 0.2686 validation ≈ 0.2544 ( 95%)
[ Info: [ 34%] LOSS: training ≈ 0.2683 validation ≈ 0.2541 ( 95%)
[ Info: [ 34%] LOSS: training ≈ 0.2681 validation ≈ 0.2538 ( 95%)
[ Info: [ 35%] LOSS: training ≈ 0.2679 validation ≈ 0.2535 ( 95%)
[ Info: [ 36%] LOSS: training ≈ 0.2676 validation ≈ 0.2532 ( 95%)
[ Info: [ 36%] LOSS: training ≈ 0.2674 validation ≈ 0.2529 ( 95%)
[ Info: [ 36%] LOSS: training ≈ 0.2672 validation ≈ 0.2526 ( 95%)
[ Info: [ 37%] LOSS: training ≈ 0.267  validation ≈ 0.2523 ( 95%)
[ Info: [ 38%] LOSS: training ≈ 0.2668 validation ≈ 0.2521 ( 94%)
[ Info: [ 38%] LOSS: training ≈ 0.2666 validation ≈ 0.2518 ( 94%)
[ Info: [ 38%] LOSS: training ≈ 0.2664 validation ≈ 0.2516 ( 94%)
[ Info: [ 39%] LOSS: training ≈ 0.2663 validation ≈ 0.2513 ( 94%)
[ Info: [ 40%] LOSS: training ≈ 0.2661 validation ≈ 0.2511 ( 94%)
[ Info: [ 40%] LOSS: training ≈ 0.2659 validation ≈ 0.2508 ( 94%)
[ Info: [ 40%] LOSS: training ≈ 0.2657 validation ≈ 0.2506 ( 94%)
[ Info: [ 41%] LOSS: training ≈ 0.2656 validation ≈ 0.2504 ( 94%)
[ Info: [ 42%] LOSS: training ≈ 0.2654 validation ≈ 0.2502 ( 94%)
[ Info: [ 42%] LOSS: training ≈ 0.2653 validation ≈ 0.2499 ( 94%)
[ Info: [ 42%] LOSS: training ≈ 0.2651 validation ≈ 0.2497 ( 94%)
[ Info: [ 43%] LOSS: training ≈ 0.265  validation ≈ 0.2495 ( 94%)
[ Info: [ 44%] LOSS: training ≈ 0.2648 validation ≈ 0.2493 ( 94%)
[ Info: [ 44%] LOSS: training ≈ 0.2647 validation ≈ 0.2491 ( 94%)
[ Info: [ 44%] LOSS: training ≈ 0.2645 validation ≈ 0.2489 ( 94%)
[ Info: [ 45%] LOSS: training ≈ 0.2644 validation ≈ 0.2487 ( 94%)
[ Info: [ 46%] LOSS: training ≈ 0.2643 validation ≈ 0.2485 ( 94%)
[ Info: [ 46%] LOSS: training ≈ 0.2641 validation ≈ 0.2483 ( 94%)
[ Info: [ 46%] LOSS: training ≈ 0.264  validation ≈ 0.2482 ( 94%)
[ Info: [ 47%] LOSS: training ≈ 0.2639 validation ≈ 0.248  ( 94%)
[ Info: [ 48%] LOSS: training ≈ 0.2638 validation ≈ 0.2478 ( 94%)
[ Info: [ 48%] LOSS: training ≈ 0.2637 validation ≈ 0.2476 ( 94%)
[ Info: [ 48%] LOSS: training ≈ 0.2636 validation ≈ 0.2475 ( 94%)
[ Info: [ 49%] LOSS: training ≈ 0.2634 validation ≈ 0.2473 ( 94%)
[ Info: [ 50%] LOSS: training ≈ 0.2633 validation ≈ 0.2472 ( 94%)
[ Info: [ 50%] LOSS: training ≈ 0.2632 validation ≈ 0.247  ( 94%)
[ Info: [ 50%] LOSS: training ≈ 0.2631 validation ≈ 0.2468 ( 94%)
[ Info: [ 51%] LOSS: training ≈ 0.263  validation ≈ 0.2467 ( 94%)
[ Info: [ 52%] LOSS: training ≈ 0.2629 validation ≈ 0.2465 ( 94%)
[ Info: [ 52%] LOSS: training ≈ 0.2628 validation ≈ 0.2464 ( 94%)
[ Info: [ 52%] LOSS: training ≈ 0.2627 validation ≈ 0.2463 ( 94%)
[ Info: [ 53%] LOSS: training ≈ 0.2626 validation ≈ 0.2461 ( 94%)
[ Info: [ 54%] LOSS: training ≈ 0.2625 validation ≈ 0.246  ( 94%)
[ Info: [ 54%] LOSS: training ≈ 0.2625 validation ≈ 0.2458 ( 94%)
[ Info: [ 55%] LOSS: training ≈ 0.2624 validation ≈ 0.2457 ( 94%)
[ Info: [ 55%] LOSS: training ≈ 0.2623 validation ≈ 0.2456 ( 94%)
[ Info: [ 56%] LOSS: training ≈ 0.2622 validation ≈ 0.2455 ( 94%)
[ Info: [ 56%] LOSS: training ≈ 0.2621 validation ≈ 0.2453 ( 94%)
[ Info: [ 56%] LOSS: training ≈ 0.262  validation ≈ 0.2452 ( 94%)
[ Info: [ 57%] LOSS: training ≈ 0.262  validation ≈ 0.2451 ( 94%)
[ Info: [ 57%] LOSS: training ≈ 0.2619 validation ≈ 0.245  ( 94%)
[ Info: [ 58%] LOSS: training ≈ 0.2618 validation ≈ 0.2449 ( 94%)
[ Info: [ 58%] LOSS: training ≈ 0.2618 validation ≈ 0.2447 ( 94%)
[ Info: [ 59%] LOSS: training ≈ 0.2617 validation ≈ 0.2446 ( 93%)
[ Info: [ 60%] LOSS: training ≈ 0.2616 validation ≈ 0.2445 ( 93%)
[ Info: [ 60%] LOSS: training ≈ 0.2615 validation ≈ 0.2444 ( 93%)
[ Info: [ 60%] LOSS: training ≈ 0.2615 validation ≈ 0.2443 ( 93%)
[ Info: [ 61%] LOSS: training ≈ 0.2614 validation ≈ 0.2442 ( 93%)
[ Info: [ 62%] LOSS: training ≈ 0.2613 validation ≈ 0.2441 ( 93%)
[ Info: [ 62%] LOSS: training ≈ 0.2613 validation ≈ 0.244  ( 93%)
[ Info: [ 62%] LOSS: training ≈ 0.2612 validation ≈ 0.2439 ( 93%)
[ Info: [ 63%] LOSS: training ≈ 0.2612 validation ≈ 0.2438 ( 93%)
[ Info: [ 64%] LOSS: training ≈ 0.2611 validation ≈ 0.2437 ( 93%)
[ Info: [ 64%] LOSS: training ≈ 0.261  validation ≈ 0.2436 ( 93%)
[ Info: [ 64%] LOSS: training ≈ 0.261  validation ≈ 0.2435 ( 93%)
[ Info: [ 65%] LOSS: training ≈ 0.2609 validation ≈ 0.2434 ( 93%)
[ Info: [ 66%] LOSS: training ≈ 0.2609 validation ≈ 0.2433 ( 93%)
[ Info: [ 66%] LOSS: training ≈ 0.2608 validation ≈ 0.2432 ( 93%)
[ Info: [ 66%] LOSS: training ≈ 0.2608 validation ≈ 0.2432 ( 93%)
[ Info: [ 67%] LOSS: training ≈ 0.2607 validation ≈ 0.2431 ( 93%)
[ Info: [ 68%] LOSS: training ≈ 0.2607 validation ≈ 0.243  ( 93%)
[ Info: [ 68%] LOSS: training ≈ 0.2606 validation ≈ 0.2429 ( 93%)
[ Info: [ 68%] LOSS: training ≈ 0.2606 validation ≈ 0.2428 ( 93%)
[ Info: [ 69%] LOSS: training ≈ 0.2605 validation ≈ 0.2427 ( 93%)
[ Info: [ 70%] LOSS: training ≈ 0.2605 validation ≈ 0.2427 ( 93%)
[ Info: [ 70%] LOSS: training ≈ 0.2604 validation ≈ 0.2426 ( 93%)
[ Info: [ 70%] LOSS: training ≈ 0.2604 validation ≈ 0.2425 ( 93%)
[ Info: [ 71%] LOSS: training ≈ 0.2604 validation ≈ 0.2424 ( 93%)
[ Info: [ 72%] LOSS: training ≈ 0.2603 validation ≈ 0.2424 ( 93%)
[ Info: [ 72%] LOSS: training ≈ 0.2603 validation ≈ 0.2423 ( 93%)
[ Info: [ 72%] LOSS: training ≈ 0.2602 validation ≈ 0.2422 ( 93%)
[ Info: [ 73%] LOSS: training ≈ 0.2602 validation ≈ 0.2421 ( 93%)
[ Info: [ 74%] LOSS: training ≈ 0.2601 validation ≈ 0.2421 ( 93%)
[ Info: [ 74%] LOSS: training ≈ 0.2601 validation ≈ 0.242  ( 93%)
[ Info: [ 74%] LOSS: training ≈ 0.2601 validation ≈ 0.2419 ( 93%)
[ Info: [ 75%] LOSS: training ≈ 0.26   validation ≈ 0.2419 ( 93%)
[ Info: [ 76%] LOSS: training ≈ 0.26   validation ≈ 0.2418 ( 93%)
[ Info: [ 76%] LOSS: training ≈ 0.26   validation ≈ 0.2417 ( 93%)
[ Info: [ 76%] LOSS: training ≈ 0.2599 validation ≈ 0.2417 ( 93%)
[ Info: [ 77%] LOSS: training ≈ 0.2599 validation ≈ 0.2416 ( 93%)
[ Info: [ 78%] LOSS: training ≈ 0.2599 validation ≈ 0.2416 ( 93%)
[ Info: [ 78%] LOSS: training ≈ 0.2598 validation ≈ 0.2415 ( 93%)
[ Info: [ 78%] LOSS: training ≈ 0.2598 validation ≈ 0.2414 ( 93%)
[ Info: [ 79%] LOSS: training ≈ 0.2598 validation ≈ 0.2414 ( 93%)
[ Info: [ 80%] LOSS: training ≈ 0.2597 validation ≈ 0.2413 ( 93%)
[ Info: [ 80%] LOSS: training ≈ 0.2597 validation ≈ 0.2413 ( 93%)
[ Info: [ 80%] LOSS: training ≈ 0.2597 validation ≈ 0.2412 ( 93%)
[ Info: [ 81%] LOSS: training ≈ 0.2596 validation ≈ 0.2412 ( 93%)
[ Info: [ 82%] LOSS: training ≈ 0.2596 validation ≈ 0.2411 ( 93%)
[ Info: [ 82%] LOSS: training ≈ 0.2596 validation ≈ 0.241  ( 93%)
[ Info: [ 82%] LOSS: training ≈ 0.2595 validation ≈ 0.241  ( 93%)
[ Info: [ 83%] LOSS: training ≈ 0.2595 validation ≈ 0.2409 ( 93%)
[ Info: [ 84%] LOSS: training ≈ 0.2595 validation ≈ 0.2409 ( 93%)
[ Info: [ 84%] LOSS: training ≈ 0.2595 validation ≈ 0.2408 ( 93%)
[ Info: [ 84%] LOSS: training ≈ 0.2594 validation ≈ 0.2408 ( 93%)
[ Info: [ 85%] LOSS: training ≈ 0.2594 validation ≈ 0.2407 ( 93%)
[ Info: [ 86%] LOSS: training ≈ 0.2594 validation ≈ 0.2407 ( 93%)
[ Info: [ 86%] LOSS: training ≈ 0.2594 validation ≈ 0.2406 ( 93%)
[ Info: [ 86%] LOSS: training ≈ 0.2593 validation ≈ 0.2406 ( 93%)
[ Info: [ 87%] LOSS: training ≈ 0.2593 validation ≈ 0.2405 ( 93%)
[ Info: [ 88%] LOSS: training ≈ 0.2593 validation ≈ 0.2405 ( 93%)
[ Info: [ 88%] LOSS: training ≈ 0.2593 validation ≈ 0.2404 ( 93%)
[ Info: [ 88%] LOSS: training ≈ 0.2592 validation ≈ 0.2404 ( 93%)
[ Info: [ 89%] LOSS: training ≈ 0.2592 validation ≈ 0.2404 ( 93%)
[ Info: [ 90%] LOSS: training ≈ 0.2592 validation ≈ 0.2403 ( 93%)
[ Info: [ 90%] LOSS: training ≈ 0.2592 validation ≈ 0.2403 ( 93%)
[ Info: [ 90%] LOSS: training ≈ 0.2592 validation ≈ 0.2402 ( 93%)
[ Info: [ 91%] LOSS: training ≈ 0.2591 validation ≈ 0.2402 ( 93%)
[ Info: [ 92%] LOSS: training ≈ 0.2591 validation ≈ 0.2401 ( 93%)
[ Info: [ 92%] LOSS: training ≈ 0.2591 validation ≈ 0.2401 ( 93%)
[ Info: [ 92%] LOSS: training ≈ 0.2591 validation ≈ 0.2401 ( 93%)
[ Info: [ 93%] LOSS: training ≈ 0.259  validation ≈ 0.24   ( 93%)
[ Info: [ 94%] LOSS: training ≈ 0.259  validation ≈ 0.24   ( 93%)
[ Info: [ 94%] LOSS: training ≈ 0.259  validation ≈ 0.2399 ( 93%)
[ Info: [ 94%] LOSS: training ≈ 0.259  validation ≈ 0.2399 ( 93%)
[ Info: [ 95%] LOSS: training ≈ 0.259  validation ≈ 0.2399 ( 93%)
[ Info: [ 96%] LOSS: training ≈ 0.259  validation ≈ 0.2398 ( 93%)
[ Info: [ 96%] LOSS: training ≈ 0.2589 validation ≈ 0.2398 ( 93%)
[ Info: [ 96%] LOSS: training ≈ 0.2589 validation ≈ 0.2397 ( 93%)
[ Info: [ 97%] LOSS: training ≈ 0.2589 validation ≈ 0.2397 ( 93%)
[ Info: [ 98%] LOSS: training ≈ 0.2589 validation ≈ 0.2397 ( 93%)
[ Info: [ 98%] LOSS: training ≈ 0.2589 validation ≈ 0.2396 ( 93%)
[ Info: [ 98%] LOSS: training ≈ 0.2588 validation ≈ 0.2396 ( 93%)
[ Info: [ 99%] LOSS: training ≈ 0.2588 validation ≈ 0.2396 ( 93%)
[ Info: [100%] LOSS: training ≈ 0.2588 validation ≈ 0.2395 ( 93%)
[ Info: [100%] LOSS: training ≈ 0.2588 validation ≈ 0.2395 ( 93%)
[ Info: [  0%] LOSS: training ≈ 0.4215
[ Info: [  1%] LOSS: training ≈ 0.3806
[ Info: [  2%] LOSS: training ≈ 0.3564
[ Info: [  2%] LOSS: training ≈ 0.3399
[ Info: [  2%] LOSS: training ≈ 0.3279
[ Info: [  3%] LOSS: training ≈ 0.3185
[ Info: [  4%] LOSS: training ≈ 0.311 
[ Info: [  4%] LOSS: training ≈ 0.3048
[ Info: [  4%] LOSS: training ≈ 0.2996
[ Info: [  5%] LOSS: training ≈ 0.2952
[ Info: [  6%] LOSS: training ≈ 0.2914
[ Info: [  6%] LOSS: training ≈ 0.2881
[ Info: [  6%] LOSS: training ≈ 0.2852
[ Info: [  7%] LOSS: training ≈ 0.2826
[ Info: [  8%] LOSS: training ≈ 0.2802
[ Info: [  8%] LOSS: training ≈ 0.2782
[ Info: [  8%] LOSS: training ≈ 0.2763
[ Info: [  9%] LOSS: training ≈ 0.2746
[ Info: [ 10%] LOSS: training ≈ 0.2731
[ Info: [ 10%] LOSS: training ≈ 0.2717
[ Info: [ 10%] LOSS: training ≈ 0.2704
[ Info: [ 11%] LOSS: training ≈ 0.2692
[ Info: [ 12%] LOSS: training ≈ 0.2681
[ Info: [ 12%] LOSS: training ≈ 0.2671
[ Info: [ 12%] LOSS: training ≈ 0.2662
[ Info: [ 13%] LOSS: training ≈ 0.2654
[ Info: [ 14%] LOSS: training ≈ 0.2646
[ Info: [ 14%] LOSS: training ≈ 0.2639
[ Info: [ 14%] LOSS: training ≈ 0.2632
[ Info: [ 15%] LOSS: training ≈ 0.2626
[ Info: [ 16%] LOSS: training ≈ 0.262 
[ Info: [ 16%] LOSS: training ≈ 0.2614
[ Info: [ 16%] LOSS: training ≈ 0.2609
[ Info: [ 17%] LOSS: training ≈ 0.2605
[ Info: [ 18%] LOSS: training ≈ 0.26  
[ Info: [ 18%] LOSS: training ≈ 0.2596
[ Info: [ 18%] LOSS: training ≈ 0.2592
[ Info: [ 19%] LOSS: training ≈ 0.2589
[ Info: [ 20%] LOSS: training ≈ 0.2585
[ Info: [ 20%] LOSS: training ≈ 0.2582
[ Info: [ 20%] LOSS: training ≈ 0.2579
[ Info: [ 21%] LOSS: training ≈ 0.2576
[ Info: [ 22%] LOSS: training ≈ 0.2573
[ Info: [ 22%] LOSS: training ≈ 0.2571
[ Info: [ 22%] LOSS: training ≈ 0.2568
[ Info: [ 23%] LOSS: training ≈ 0.2566
[ Info: [ 24%] LOSS: training ≈ 0.2564
[ Info: [ 24%] LOSS: training ≈ 0.2562
[ Info: [ 24%] LOSS: training ≈ 0.256 
[ Info: [ 25%] LOSS: training ≈ 0.2558
[ Info: [ 26%] LOSS: training ≈ 0.2557
[ Info: [ 26%] LOSS: training ≈ 0.2555
[ Info: [ 26%] LOSS: training ≈ 0.2554
[ Info: [ 27%] LOSS: training ≈ 0.2552
[ Info: [ 28%] LOSS: training ≈ 0.2551
[ Info: [ 28%] LOSS: training ≈ 0.255 
[ Info: [ 28%] LOSS: training ≈ 0.2548
[ Info: [ 29%] LOSS: training ≈ 0.2547
[ Info: [ 30%] LOSS: training ≈ 0.2546
[ Info: [ 30%] LOSS: training ≈ 0.2545
[ Info: [ 30%] LOSS: training ≈ 0.2544
[ Info: [ 31%] LOSS: training ≈ 0.2543
[ Info: [ 32%] LOSS: training ≈ 0.2542
[ Info: [ 32%] LOSS: training ≈ 0.2541
[ Info: [ 32%] LOSS: training ≈ 0.2541
[ Info: [ 33%] LOSS: training ≈ 0.254 
[ Info: [ 34%] LOSS: training ≈ 0.2539
[ Info: [ 34%] LOSS: training ≈ 0.2538
[ Info: [ 34%] LOSS: training ≈ 0.2538
[ Info: [ 35%] LOSS: training ≈ 0.2537
[ Info: [ 36%] LOSS: training ≈ 0.2536
[ Info: [ 36%] LOSS: training ≈ 0.2536
[ Info: [ 36%] LOSS: training ≈ 0.2535
[ Info: [ 37%] LOSS: training ≈ 0.2535
[ Info: [ 38%] LOSS: training ≈ 0.2534
[ Info: [ 38%] LOSS: training ≈ 0.2534
[ Info: [ 38%] LOSS: training ≈ 0.2533
[ Info: [ 39%] LOSS: training ≈ 0.2533
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 40%] LOSS: training ≈ 0.2532
[ Info: [ 41%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.2531
[ Info: [ 42%] LOSS: training ≈ 0.253 
[ Info: [ 43%] LOSS: training ≈ 0.253 
[ Info: [ 44%] LOSS: training ≈ 0.253 
[ Info: [ 44%] LOSS: training ≈ 0.2529
[ Info: [ 44%] LOSS: training ≈ 0.2529
[ Info: [ 45%] LOSS: training ≈ 0.2529
[ Info: [ 46%] LOSS: training ≈ 0.2529
[ Info: [ 46%] LOSS: training ≈ 0.2528
[ Info: [ 46%] LOSS: training ≈ 0.2528
[ Info: [ 47%] LOSS: training ≈ 0.2528
[ Info: [ 48%] LOSS: training ≈ 0.2528
[ Info: [ 48%] LOSS: training ≈ 0.2527
[ Info: [ 48%] LOSS: training ≈ 0.2527
[ Info: [ 49%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 50%] LOSS: training ≈ 0.2527
[ Info: [ 51%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 52%] LOSS: training ≈ 0.2526
[ Info: [ 53%] LOSS: training ≈ 0.2526
[ Info: [ 54%] LOSS: training ≈ 0.2526
[ Info: [ 54%] LOSS: training ≈ 0.2525
[ Info: [ 55%] LOSS: training ≈ 0.2525
[ Info: [ 55%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 56%] LOSS: training ≈ 0.2525
[ Info: [ 57%] LOSS: training ≈ 0.2525
[ Info: [ 57%] LOSS: training ≈ 0.2525
[ Info: [ 58%] LOSS: training ≈ 0.2525
[ Info: [ 58%] LOSS: training ≈ 0.2525
[ Info: [ 59%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 60%] LOSS: training ≈ 0.2524
[ Info: [ 61%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 62%] LOSS: training ≈ 0.2524
[ Info: [ 63%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 64%] LOSS: training ≈ 0.2524
[ Info: [ 65%] LOSS: training ≈ 0.2524
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 66%] LOSS: training ≈ 0.2523
[ Info: [ 67%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 68%] LOSS: training ≈ 0.2523
[ Info: [ 69%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 70%] LOSS: training ≈ 0.2523
[ Info: [ 71%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 72%] LOSS: training ≈ 0.2523
[ Info: [ 73%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 74%] LOSS: training ≈ 0.2523
[ Info: [ 75%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 76%] LOSS: training ≈ 0.2523
[ Info: [ 77%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2523
[ Info: [ 78%] LOSS: training ≈ 0.2522
[ Info: [ 79%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 80%] LOSS: training ≈ 0.2522
[ Info: [ 81%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 82%] LOSS: training ≈ 0.2522
[ Info: [ 83%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 84%] LOSS: training ≈ 0.2522
[ Info: [ 85%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 86%] LOSS: training ≈ 0.2522
[ Info: [ 87%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 88%] LOSS: training ≈ 0.2522
[ Info: [ 89%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 90%] LOSS: training ≈ 0.2522
[ Info: [ 91%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 92%] LOSS: training ≈ 0.2522
[ Info: [ 93%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 94%] LOSS: training ≈ 0.2522
[ Info: [ 95%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 96%] LOSS: training ≈ 0.2522
[ Info: [ 97%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 98%] LOSS: training ≈ 0.2522
[ Info: [ 99%] LOSS: training ≈ 0.2522
[ Info: [100%] LOSS: training ≈ 0.2522
[ Info: [100%] LOSS: training ≈ 0.2522
Test Summary: | Pass  Total      Time
Package       |  297    297  19m04.6s
     Testing SDeMo tests passed 

Testing completed after 1169.04s

PkgEval succeeded after 1217.94s