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How to retrain existing Syntaxnet model? #37
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'parser_trainer.py' has '--pretrained_params, --pretrained_params_names' parameters. https://github.com/tensorflow/models/blob/master/research/syntaxnet/g3doc/syntaxnet-tutorial.md
but i guess it could be used for retraining 'brain_tagger'.
and ran again, as you see, 'eval metric' is already 91.04% for epoch 1'
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Hi, Caused by op u'save/Assign_9', defined at: InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [1436,8] rhs shape= [1297,8] ` |
i guess there is a dimension mismatch.
what is the hidden layer size of the model you have? |
TAGGER_HIDDEN_LAYER_SIZES=64
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i just have done testing and got the same error.
it seems that "embedding_matrix_0,embedding_matrix_1,embedding_matrix_2" model parameters refer to the original corpus(dimension?);; so, i removed those parameters.
and then ran again
here is original one.
'86.80%' is a bit lower starting point but, it continues training after restoring 'bias_0,weights_0' parameters. |
Is there a way to retrain the syntaxnet POS tagger model with new dataset?
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