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* Ensure tagger and NER are trained, even if non-projective problem

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Matthew Honnibal 2015-05-27 03:16:21 +02:00
parent f69fe6a635
commit 895060e774
1 changed files with 3 additions and 5 deletions
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8
bin/parser/train.py
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@ -84,15 +84,13 @@ def train(Language, gold_tuples, model_dir, n_iter=15, feat_set=u'basic', seed=0
loss += nlp.parser.train(tokens, gold) loss += nlp.parser.train(tokens, gold)
except AssertionError: except AssertionError:
# TODO: Do something about non-projective sentences # TODO: Do something about non-projective sentences
continue pass
if gold.ents: nlp.entity.train(tokens, gold)
nlp.entity.train(tokens, gold)
nlp.tagger.train(tokens, gold.tags) nlp.tagger.train(tokens, gold.tags)
random.shuffle(gold_tuples)
print '%d:\t%d\t%.3f\t%.3f\t%.3f\t%.3f' % (itn, loss, scorer.uas, scorer.ents_f, print '%d:\t%d\t%.3f\t%.3f\t%.3f\t%.3f' % (itn, loss, scorer.uas, scorer.ents_f,
scorer.tags_acc, scorer.tags_acc,
scorer.token_acc) scorer.token_acc)
random.shuffle(gold_tuples)
nlp.parser.model.end_training() nlp.parser.model.end_training()
nlp.entity.model.end_training() nlp.entity.model.end_training()
nlp.tagger.model.end_training() nlp.tagger.model.end_training()