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Make training test expectations more robust (less precision)
Signed-off-by: Lukasz Stafiniak <lukstafi@gmail.com>
1 parent 8c221e5 commit 69eb133

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8 files changed

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‎test/training/bigram.expected‎

Lines changed: 124 additions & 124 deletions
Original file line numberDiff line numberDiff line change
@@ -2,130 +2,130 @@ Retrieving commandline, environment, or config file variable ocannl_log_level
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Found 0, in the config file
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bigrams: 228146
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input_size: 229000
5-
Epoch 0, batch 0, loss=3.384207
6-
Epoch 0, batch 100, loss=2.709038
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Epoch 0, batch 200, loss=2.945771
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Epoch 0, epoch loss=680.202888
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Epoch 1, batch 0, loss=2.788706
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Epoch 1, batch 100, loss=2.425731
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Epoch 1, batch 200, loss=2.814660
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Epoch 1, epoch loss=616.822069
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Epoch 2, batch 0, loss=2.649548
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Epoch 2, batch 100, loss=2.358366
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Epoch 2, batch 200, loss=2.755350
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Epoch 2, epoch loss=597.546664
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Epoch 3, batch 0, loss=2.588842
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Epoch 3, batch 100, loss=2.329691
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Epoch 3, batch 200, loss=2.721706
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Epoch 3, epoch loss=588.281096
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Epoch 4, batch 0, loss=2.554565
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Epoch 4, batch 100, loss=2.313664
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Epoch 4, batch 200, loss=2.700217
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Epoch 4, epoch loss=582.759826
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Epoch 5, batch 0, loss=2.532644
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Epoch 5, batch 100, loss=2.303379
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Epoch 5, batch 200, loss=2.685341
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Epoch 5, epoch loss=579.075711
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Epoch 6, batch 0, loss=2.517525
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Epoch 6, batch 100, loss=2.296246
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Epoch 6, batch 200, loss=2.674406
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Epoch 6, epoch loss=576.441672
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Epoch 7, batch 0, loss=2.506522
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Epoch 7, batch 100, loss=2.291044
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Epoch 7, batch 200, loss=2.666012
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Epoch 7, epoch loss=574.466705
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Epoch 8, batch 0, loss=2.498178
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Epoch 8, batch 100, loss=2.287141
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Epoch 8, batch 200, loss=2.659344
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Epoch 8, epoch loss=572.932843
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Epoch 9, batch 0, loss=2.491635
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Epoch 9, batch 100, loss=2.284144
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Epoch 9, batch 200, loss=2.653916
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Epoch 9, epoch loss=571.708377
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Epoch 10, batch 0, loss=2.486362
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Epoch 10, batch 100, loss=2.281802
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Epoch 10, batch 200, loss=2.649396
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Epoch 10, epoch loss=570.709282
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Epoch 11, batch 0, loss=2.482021
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Epoch 11, batch 100, loss=2.279949
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Epoch 11, batch 200, loss=2.645595
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Epoch 11, epoch loss=569.879609
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Epoch 12, batch 0, loss=2.478378
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Epoch 12, batch 100, loss=2.278475
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Epoch 12, batch 200, loss=2.642342
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Epoch 12, epoch loss=569.180244
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Epoch 13, batch 0, loss=2.475274
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Epoch 13, batch 100, loss=2.277280
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Epoch 13, batch 200, loss=2.639534
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Epoch 13, epoch loss=568.582958
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Epoch 14, batch 0, loss=2.472606
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Epoch 14, batch 100, loss=2.276310
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Epoch 14, batch 200, loss=2.637096
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Epoch 14, epoch loss=568.067485
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Epoch 15, batch 0, loss=2.470286
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Epoch 15, batch 100, loss=2.275532
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Epoch 15, batch 200, loss=2.634959
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Epoch 15, epoch loss=567.618418
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Epoch 16, batch 0, loss=2.468248
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Epoch 16, batch 100, loss=2.274891
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Epoch 16, batch 200, loss=2.633074
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Epoch 16, epoch loss=567.223836
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Epoch 17, batch 0, loss=2.466446
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Epoch 17, batch 100, loss=2.274361
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Epoch 17, batch 200, loss=2.631402
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Epoch 17, epoch loss=566.874570
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Epoch 18, batch 0, loss=2.464850
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Epoch 18, batch 100, loss=2.273928
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Epoch 18, batch 200, loss=2.629910
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Epoch 18, epoch loss=566.563456
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Epoch 19, batch 0, loss=2.463427
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Epoch 19, batch 100, loss=2.273579
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Epoch 19, batch 200, loss=2.628594
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Epoch 19, epoch loss=566.284741
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Epoch 20, batch 0, loss=2.462142
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Epoch 20, batch 100, loss=2.273286
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Epoch 20, batch 200, loss=2.627399
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Epoch 20, epoch loss=566.033497
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Epoch 21, batch 0, loss=2.460989
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Epoch 21, batch 100, loss=2.273043
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Epoch 21, batch 200, loss=2.626322
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Epoch 21, epoch loss=565.806087
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Epoch 22, batch 0, loss=2.459947
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Epoch 22, batch 100, loss=2.272847
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Epoch 22, batch 200, loss=2.625357
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Epoch 22, epoch loss=565.599298
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Epoch 23, batch 0, loss=2.459003
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Epoch 23, batch 100, loss=2.272677
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Epoch 23, batch 200, loss=2.624472
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Epoch 23, epoch loss=565.410496
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Epoch 24, batch 0, loss=2.458137
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Epoch 24, batch 100, loss=2.272539
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Epoch 24, batch 200, loss=2.623674
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Epoch 24, epoch loss=565.237560
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Epoch 25, batch 0, loss=2.457346
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Epoch 25, batch 100, loss=2.272424
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Epoch 25, batch 200, loss=2.622964
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Epoch 25, epoch loss=565.078496
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Epoch 26, batch 0, loss=2.456622
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Epoch 26, batch 100, loss=2.272328
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Epoch 26, batch 200, loss=2.622294
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Epoch 26, epoch loss=564.931741
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Epoch 27, batch 0, loss=2.455961
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Epoch 27, batch 100, loss=2.272249
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Epoch 27, batch 200, loss=2.621692
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Epoch 27, epoch loss=564.795990
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Epoch 28, batch 0, loss=2.455342
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Epoch 28, batch 100, loss=2.272188
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Epoch 28, batch 200, loss=2.621143
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Epoch 28, epoch loss=564.670042
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Epoch 29, batch 0, loss=2.454777
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Epoch 29, batch 100, loss=2.272128
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Epoch 29, batch 200, loss=2.620651
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Epoch 29, epoch loss=564.552950
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Epoch 30, batch 0, loss=2.454257
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Epoch 30, batch 100, loss=2.272082
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Epoch 30, batch 200, loss=2.620183
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Epoch 30, epoch loss=564.443695
5+
Epoch 0, batch 0, loss=3.38421
6+
Epoch 0, batch 100, loss=2.70904
7+
Epoch 0, batch 200, loss=2.94577
8+
Epoch 0, epoch loss=680.203
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Epoch 1, batch 0, loss=2.78871
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Epoch 1, batch 100, loss=2.42573
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Epoch 1, batch 200, loss=2.81466
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Epoch 1, epoch loss=616.822
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Epoch 2, batch 0, loss=2.64955
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Epoch 2, batch 100, loss=2.35837
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Epoch 2, batch 200, loss=2.75535
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Epoch 2, epoch loss=597.547
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Epoch 3, batch 0, loss=2.58884
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Epoch 3, batch 100, loss=2.32969
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Epoch 3, batch 200, loss=2.72171
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Epoch 3, epoch loss=588.281
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Epoch 4, batch 0, loss=2.55456
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Epoch 4, batch 100, loss=2.31366
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Epoch 4, batch 200, loss=2.70022
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Epoch 4, epoch loss=582.76
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Epoch 5, batch 0, loss=2.53264
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Epoch 5, batch 100, loss=2.30338
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Epoch 5, batch 200, loss=2.68534
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Epoch 5, epoch loss=579.076
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Epoch 6, batch 0, loss=2.51753
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Epoch 6, batch 100, loss=2.29625
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Epoch 6, batch 200, loss=2.67441
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Epoch 6, epoch loss=576.442
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Epoch 7, batch 0, loss=2.50652
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Epoch 7, batch 100, loss=2.29104
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Epoch 7, batch 200, loss=2.66601
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Epoch 7, epoch loss=574.467
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Epoch 8, batch 0, loss=2.49818
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Epoch 8, batch 100, loss=2.28714
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Epoch 8, batch 200, loss=2.65934
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Epoch 8, epoch loss=572.933
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Epoch 9, batch 0, loss=2.49164
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Epoch 9, batch 100, loss=2.28414
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Epoch 9, batch 200, loss=2.65392
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Epoch 9, epoch loss=571.708
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Epoch 10, batch 0, loss=2.48636
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Epoch 10, batch 100, loss=2.2818
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Epoch 10, batch 200, loss=2.6494
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Epoch 10, epoch loss=570.709
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Epoch 11, batch 0, loss=2.48202
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Epoch 11, batch 100, loss=2.27995
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Epoch 11, batch 200, loss=2.6456
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Epoch 11, epoch loss=569.88
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Epoch 12, batch 0, loss=2.47838
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Epoch 12, batch 100, loss=2.27847
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Epoch 12, batch 200, loss=2.64234
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Epoch 12, epoch loss=569.18
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Epoch 13, batch 0, loss=2.47527
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Epoch 13, batch 100, loss=2.27728
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Epoch 13, batch 200, loss=2.63953
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Epoch 13, epoch loss=568.583
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Epoch 14, batch 0, loss=2.47261
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Epoch 14, batch 100, loss=2.27631
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Epoch 14, batch 200, loss=2.6371
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Epoch 14, epoch loss=568.067
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Epoch 15, batch 0, loss=2.47029
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Epoch 15, batch 100, loss=2.27553
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Epoch 15, batch 200, loss=2.63496
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Epoch 15, epoch loss=567.618
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Epoch 16, batch 0, loss=2.46825
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Epoch 16, batch 100, loss=2.27489
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Epoch 16, batch 200, loss=2.63307
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Epoch 16, epoch loss=567.224
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Epoch 17, batch 0, loss=2.46645
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Epoch 17, batch 100, loss=2.27436
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Epoch 17, batch 200, loss=2.6314
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Epoch 17, epoch loss=566.875
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Epoch 18, batch 0, loss=2.46485
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Epoch 18, batch 100, loss=2.27393
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Epoch 18, batch 200, loss=2.62991
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Epoch 18, epoch loss=566.563
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Epoch 19, batch 0, loss=2.46343
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Epoch 19, batch 100, loss=2.27358
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Epoch 19, batch 200, loss=2.62859
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Epoch 19, epoch loss=566.285
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Epoch 20, batch 0, loss=2.46214
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Epoch 20, batch 100, loss=2.27329
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Epoch 20, batch 200, loss=2.6274
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Epoch 20, epoch loss=566.033
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Epoch 21, batch 0, loss=2.46099
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Epoch 21, batch 100, loss=2.27304
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Epoch 21, batch 200, loss=2.62632
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Epoch 21, epoch loss=565.806
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Epoch 22, batch 0, loss=2.45995
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Epoch 22, batch 100, loss=2.27285
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Epoch 22, batch 200, loss=2.62536
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Epoch 22, epoch loss=565.599
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Epoch 23, batch 0, loss=2.459
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Epoch 23, batch 100, loss=2.27268
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Epoch 23, batch 200, loss=2.62447
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Epoch 23, epoch loss=565.41
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Epoch 24, batch 0, loss=2.45814
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Epoch 24, batch 100, loss=2.27254
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Epoch 24, batch 200, loss=2.62367
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Epoch 24, epoch loss=565.238
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Epoch 25, batch 0, loss=2.45735
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Epoch 25, batch 100, loss=2.27242
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Epoch 25, batch 200, loss=2.62296
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Epoch 25, epoch loss=565.078
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Epoch 26, batch 0, loss=2.45662
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Epoch 26, batch 100, loss=2.27233
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Epoch 26, batch 200, loss=2.62229
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Epoch 26, epoch loss=564.932
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Epoch 27, batch 0, loss=2.45596
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Epoch 27, batch 100, loss=2.27225
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Epoch 27, batch 200, loss=2.62169
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Epoch 27, epoch loss=564.796
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Epoch 28, batch 0, loss=2.45534
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Epoch 28, batch 100, loss=2.27219
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Epoch 28, batch 200, loss=2.62114
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Epoch 28, epoch loss=564.67
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Epoch 29, batch 0, loss=2.45478
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Epoch 29, batch 100, loss=2.27213
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Epoch 29, batch 200, loss=2.62065
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Epoch 29, epoch loss=564.553
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Epoch 30, batch 0, loss=2.45426
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Epoch 30, batch 100, loss=2.27208
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Epoch 30, batch 200, loss=2.62018
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Epoch 30, epoch loss=564.444
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prerofaers

‎test/training/bigram.ml‎

Lines changed: 2 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -79,9 +79,9 @@ let () =
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Train.run sgd_step;
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let loss = batch_loss.@[0] in
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epoch_loss := !epoch_loss +. loss;
82-
if batch % 100 = 0 then Stdio.printf "Epoch %d, batch %d, loss=%f\n%!" epoch batch loss;
82+
if batch % 100 = 0 then Stdio.printf "Epoch %d, batch %d, loss=%.6g\n%!" epoch batch loss;
8383
done;
84-
Stdio.printf "Epoch %d, epoch loss=%f\n%!" epoch !epoch_loss
84+
Stdio.printf "Epoch %d, epoch loss=%.6g\n%!" epoch !epoch_loss
8585
done;
8686
(* Train.printf_tree batch_loss; *)
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