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README.md

Evaluation

Iter 100 time=0.50  loss=13041.66 active=44611 precision=0.825  recall=0.821  F1=0.823  Acc(item/seq)=0.985 0.685  feature_norm=244.48
================================================
Label      Precision    Recall     F1    Support
-------  -----------  --------  -----  ---------
+              0.000     0.000  0.000          1
.              1.000     0.999  0.999       6497
1              0.875     0.865  0.870       1204
a              0.931     0.914  0.922       5998
n              0.984     0.990  0.987      36536
o              0.993     0.990  0.991      18203
v              0.992     0.991  0.992      28678
------------------------------------------------
Total seconds required for training: 55.427
Number of active features: 44611 (229357)
Number of active attributes: 26337 (169958)
Number of active labels: 7 (7)
Train set num sentences: 14914
Performance on training set: 0.9954870609388043
Test set num sentences: 3729
Performance on test set: 0.9846267903662592