ServerRun 8222
Creatorinternal
Programcrfsgd
DatasetNikhilDatasetTokenWithPTBT
Task typeSequenceTagging
Created6y349d ago
Done! Flag_green
9s
39M
SequenceTagging
0.991
0
0.957
0

Log file

===== MAIN: learn based on training data =====
=== START program1: ./run learn ../dataset2/train
Reading template file featureTemplates.
  u-templates: 19  b-templates: 1
Scanning ../dataset2/train to build dictionary.
  sentences: 268  outputs: 4
  cutoff: 3  features: 3617  parameters: 14480
  duration: 0.11 seconds.
Using c=1, i.e. lambda=0.00373134
Reading and preprocessing ../dataset2/train.
  processed: 268 sentences.
  duration: 0.12 seconds.
[Calibrating] --  1000 samples
  initial objective: 6726.3
  trying eta=0.1  obj=505.194 (possible)
  trying eta=0.2  obj=652.972 (possible)
  trying eta=0.4  obj=1289.61 (possible)
  trying eta=0.8  obj=2557.46 (possible)
  trying eta=1.6  obj=6129.06 (possible)
  trying eta=3.2  obj=13334 (too large)
  trying eta=0.05  obj=514.298 (possible)
  trying eta=0.025  obj=600.601 (possible)
  trying eta=0.0125  obj=715.62 (possible)
  trying eta=0.00625  obj=855.223 (possible)
  trying eta=0.003125  obj=1020.55 (possible)
  taking eta=0.05  t0=5360  total time: 0.59 seconds
[Epoch 1] --  wnorm: 33.4746  total time: 0.62 seconds
[Epoch 2] --  wnorm: 54.7124  total time: 0.65 seconds
[Epoch 3] --  wnorm: 72.8826  total time: 0.68 seconds
[Epoch 4] --  wnorm: 89.1604  total time: 0.73 seconds
[Epoch 5] --  wnorm: 103.091  total time: 0.76 seconds
[Epoch 6] --  wnorm: 114.661  total time: 0.8 seconds
[Epoch 7] --  wnorm: 126.009  total time: 0.83 seconds
[Epoch 8] --  wnorm: 135.124  total time: 0.87 seconds
[Epoch 9] --  wnorm: 144.249  total time: 0.9 seconds
[Epoch 10] --  wnorm: 151.371  total time: 0.94 seconds
Training perf:  sentences: 268  loss: 218.5  objective*n: 294.185
  misclassifications: 86(1.77246%)
accuracy:  98.23%; precision:   0.00%; recall:   0.00%; FB1:   0.00
[Epoch 11] --  wnorm: 157.845  total time: 0.98 seconds
[Epoch 12] --  wnorm: 164.429  total time: 1.02 seconds
[Epoch 13] --  wnorm: 169.779  total time: 1.05 seconds
[Epoch 14] --  wnorm: 174.898  total time: 1.09 seconds
[Epoch 15] --  wnorm: 178.97  total time: 1.13 seconds
[Epoch 16] --  wnorm: 182.69  total time: 1.16 seconds
[Epoch 17] --  wnorm: 186.387  total time: 1.2 seconds
[Epoch 18] --  wnorm: 189.648  total time: 1.23 seconds
[Epoch 19] --  wnorm: 193.047  total time: 1.27 seconds
[Epoch 20] --  wnorm: 195.911  total time: 1.3 seconds
Training perf:  sentences: 268  loss: 170.393  objective*n: 268.349
  misclassifications: 49(1.00989%)
accuracy:  98.99%; precision:   0.00%; recall:   0.00%; FB1:   0.00
[Epoch 21] --  wnorm: 198.085  total time: 1.34 seconds
[Epoch 22] --  wnorm: 200.386  total time: 1.37 seconds
[Epoch 23] --  wnorm: 202.494  total time: 1.4 seconds
[Epoch 24] --  wnorm: 204.785  total time: 1.44 seconds
[Epoch 25] --  wnorm: 206.646  total time: 1.47 seconds
[Epoch 26] --  wnorm: 208.334  total time: 1.52 seconds
[Epoch 27] --  wnorm: 209.89  total time: 1.54 seconds
[Epoch 28] --  wnorm: 211.418  total time: 1.58 seconds
[Epoch 29] --  wnorm: 212.38  total time: 1.61 seconds
[Epoch 30] --  wnorm: 213.819  total time: 1.65 seconds
Training perf:  sentences: 268  loss: 158.501  objective*n: 265.411
  misclassifications: 38(0.783182%)
accuracy:  99.22%; precision:   0.00%; recall:   0.00%; FB1:   0.00
[Epoch 31] --  wnorm: 215.089  total time: 1.68 seconds
[Epoch 32] --  wnorm: 215.929  total time: 1.71 seconds
[Epoch 33] --  wnorm: 216.909  total time: 1.75 seconds
[Epoch 34] --  wnorm: 217.985  total time: 1.79 seconds
[Epoch 35] --  wnorm: 218.919  total time: 1.81 seconds
[Epoch 36] --  wnorm: 219.841  total time: 1.85 seconds
[Epoch 37] --  wnorm: 220.615  total time: 1.89 seconds
[Epoch 38] --  wnorm: 221.52  total time: 1.93 seconds
[Epoch 39] --  wnorm: 222.183  total time: 1.95 seconds
[Epoch 40] --  wnorm: 222.982  total time: 1.99 seconds
Training perf:  sentences: 268  loss: 153.334  objective*n: 264.825
  misclassifications: 43(0.886232%)
accuracy:  99.11%; precision:   0.00%; recall:   0.00%; FB1:   0.00
[Epoch 41] --  wnorm: 223.706  total time: 2.03 seconds
[Epoch 42] --  wnorm: 224.21  total time: 2.05 seconds
[Epoch 43] --  wnorm: 224.704  total time: 2.1 seconds
[Epoch 44] --  wnorm: 225.172  total time: 2.13 seconds
[Epoch 45] --  wnorm: 225.569  total time: 2.17 seconds
[Epoch 46] --  wnorm: 226.055  total time: 2.21 seconds
[Epoch 47] --  wnorm: 226.572  total time: 2.23 seconds
[Epoch 48] --  wnorm: 227.044  total time: 2.27 seconds
[Epoch 49] --  wnorm: 227.291  total time: 2.31 seconds
[Epoch 50] --  wnorm: 227.773  total time: 2.35 seconds
Training perf:  sentences: 268  loss: 150.623  objective*n: 264.509
  misclassifications: 42(0.865622%)
accuracy:  99.13%; precision:   0.00%; recall:   0.00%; FB1:   0.00
Saving model file model.
Done!  2.35 seconds.
=== END program1: ./run learn ../dataset2/train --- OK [8s]

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


real	0m10.242s
user	0m4.188s
sys	0m0.172s

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