ServerRun 8237
Creatorinternal
Programcrfsgd-notemplate
DatasetNikhilDatasetTokenWithPTBT
Task typeSequenceTagging
Created6y349d ago
Done! Flag_green
1s
30M
SequenceTagging
0.944
0
0.943
0

Log file

===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
Reading template file featureTemplates.
  u-templates: 2  b-templates: 1
Scanning ../dataset2/train to build dictionary.
  sentences: 268  outputs: 4
  cutoff: 3  features: 259  parameters: 1048
  duration: 0.01 seconds.
Using c=1, i.e. lambda=0.00373134
Reading and preprocessing ../dataset2/train.
  processed: 268 sentences.
  duration: 0.03 seconds.
[Calibrating] --  1000 samples
  initial objective: 6726.3
  trying eta=0.1  obj=758.905 (possible)
  trying eta=0.2  obj=785.666 (possible)
  trying eta=0.4  obj=965.928 (possible)
  trying eta=0.8  obj=1510.35 (possible)
  trying eta=1.6  obj=3958.11 (possible)
  trying eta=3.2  obj=19310.3 (too large)
  trying eta=0.05  obj=794.889 (possible)
  trying eta=0.025  obj=870.817 (possible)
  trying eta=0.0125  obj=984.192 (possible)
  trying eta=0.00625  obj=1127.46 (possible)
  trying eta=0.003125  obj=1238.73 (possible)
  taking eta=0.05  t0=5360  total time: 0.38 seconds
[Epoch 1] --  wnorm: 27.5064  total time: 0.41 seconds
[Epoch 2] --  wnorm: 43.3048  total time: 0.43 seconds
[Epoch 3] --  wnorm: 54.2945  total time: 0.45 seconds
[Epoch 4] --  wnorm: 62.5801  total time: 0.48 seconds
[Epoch 5] --  wnorm: 70.2239  total time: 0.5 seconds
[Epoch 6] --  wnorm: 75.6817  total time: 0.52 seconds
[Epoch 7] --  wnorm: 82.633  total time: 0.54 seconds
[Epoch 8] --  wnorm: 87.9322  total time: 0.57 seconds
[Epoch 9] --  wnorm: 91.7784  total time: 0.59 seconds
[Epoch 10] --  wnorm: 96.0617  total time: 0.61 seconds
Training perf:  sentences: 268  loss: 623.108  objective*n: 671.139
  misclassifications: 271(5.58533%)
accuracy:  94.41%; precision:   0.00%; recall:   0.00%; FB1:   0.00
[Epoch 11] --  wnorm: 99.1956  total time: 0.63 seconds
[Epoch 12] --  wnorm: 102.814  total time: 0.66 seconds
[Epoch 13] --  wnorm: 105.637  total time: 0.68 seconds
[Epoch 14] --  wnorm: 108.861  total time: 0.7 seconds
[Epoch 15] --  wnorm: 111.344  total time: 0.72 seconds
[Epoch 16] --  wnorm: 112.31  total time: 0.74 seconds
[Epoch 17] --  wnorm: 114.826  total time: 0.76 seconds
[Epoch 18] --  wnorm: 117.15  total time: 0.79 seconds
[Epoch 19] --  wnorm: 118.522  total time: 0.82 seconds
[Epoch 20] --  wnorm: 120.447  total time: 0.83 seconds
Training perf:  sentences: 268  loss: 593.908  objective*n: 654.131
  misclassifications: 247(5.09068%)
accuracy:  94.91%; precision:   0.00%; recall:   0.00%; FB1:   0.00
[Epoch 21] --  wnorm: 121.513  total time: 0.86 seconds
[Epoch 22] --  wnorm: 122.534  total time: 0.88 seconds
[Epoch 23] --  wnorm: 123.708  total time: 0.9 seconds
[Epoch 24] --  wnorm: 125.573  total time: 0.92 seconds
[Epoch 25] --  wnorm: 126.666  total time: 0.95 seconds
[Epoch 26] --  wnorm: 127.146  total time: 0.97 seconds
[Epoch 27] --  wnorm: 128.254  total time: 1 seconds
[Epoch 28] --  wnorm: 129.33  total time: 1.02 seconds
[Epoch 29] --  wnorm: 129.343  total time: 1.04 seconds
[Epoch 30] --  wnorm: 130.381  total time: 1.06 seconds
Training perf:  sentences: 268  loss: 589.477  objective*n: 654.668
  misclassifications: 250(5.15251%)
accuracy:  94.85%; precision:   0.00%; recall:   0.00%; FB1:   0.00
[Epoch 31] --  wnorm: 131.132  total time: 1.08 seconds
[Epoch 32] --  wnorm: 131.038  total time: 1.1 seconds
[Epoch 33] --  wnorm: 131.73  total time: 1.12 seconds
[Epoch 34] --  wnorm: 132.899  total time: 1.16 seconds
[Epoch 35] --  wnorm: 133.251  total time: 1.18 seconds
[Epoch 36] --  wnorm: 133.85  total time: 1.2 seconds
[Epoch 37] --  wnorm: 134.013  total time: 1.22 seconds
[Epoch 38] --  wnorm: 134.843  total time: 1.24 seconds
[Epoch 39] --  wnorm: 135.097  total time: 1.26 seconds
[Epoch 40] --  wnorm: 135.408  total time: 1.29 seconds
Training perf:  sentences: 268  loss: 587.083  objective*n: 654.787
  misclassifications: 249(5.1319%)
accuracy:  94.87%; precision:   0.00%; recall:   0.00%; FB1:   0.00
[Epoch 41] --  wnorm: 135.893  total time: 1.31 seconds
[Epoch 42] --  wnorm: 136.39  total time: 1.33 seconds
[Epoch 43] --  wnorm: 136.529  total time: 1.35 seconds
[Epoch 44] --  wnorm: 137.088  total time: 1.38 seconds
[Epoch 45] --  wnorm: 137.057  total time: 1.4 seconds
[Epoch 46] --  wnorm: 137.274  total time: 1.43 seconds
[Epoch 47] --  wnorm: 137.612  total time: 1.44 seconds
[Epoch 48] --  wnorm: 138.373  total time: 1.47 seconds
[Epoch 49] --  wnorm: 138.089  total time: 1.5 seconds
[Epoch 50] --  wnorm: 138.587  total time: 1.52 seconds
Training perf:  sentences: 268  loss: 584.268  objective*n: 653.562
  misclassifications: 273(5.62655%)
accuracy:  94.37%; precision:   0.00%; recall:   0.00%; FB1:   0.00
Saving model file model.
Done!  1.52 seconds.
=== END program1: ./run learn ../dataset2/train --- OK [6s]

===== MAIN: predict/evaluate on train data =====
=== START program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in
=== END program3: ./run stripLabels ../dataset2/train ../program0/evalTrain.in --- OK [0s]
=== START program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out
=== END program1: ./run predict ../program0/evalTrain.in ../program0/evalTrain.out --- OK [0s]
=== START program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out
=== END program4: ./run evaluate ../dataset2/train ../program0/evalTrain.out --- OK [0s]

===== MAIN: predict/evaluate on test data =====
=== START program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in
=== END program3: ./run stripLabels ../dataset2/test ../program0/evalTest.in --- OK [1s]
=== START program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out
=== END program1: ./run predict ../program0/evalTest.in ../program0/evalTest.out --- OK [0s]
=== START program4: ./run evaluate ../dataset2/test ../program0/evalTest.out
=== END program4: ./run evaluate ../dataset2/test ../program0/evalTest.out --- OK [0s]


real	0m7.575s
user	0m2.544s
sys	0m0.168s

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