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Reduce batch size during pretrain
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@ -110,7 +110,7 @@ def pretrain(
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msg.row(("#", "# Words", "Total Loss", "Loss", "w/s"), **row_settings)
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msg.row(("#", "# Words", "Total Loss", "Loss", "w/s"), **row_settings)
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for epoch in range(nr_iter):
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for epoch in range(nr_iter):
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for batch in util.minibatch_by_words(
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for batch in util.minibatch_by_words(
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((text, None) for text in texts), size=5000
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((text, None) for text in texts), size=3000
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):
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):
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docs = make_docs(nlp, [text for (text, _) in batch])
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docs = make_docs(nlp, [text for (text, _) in batch])
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loss = make_update(model, docs, optimizer, drop=dropout)
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loss = make_update(model, docs, optimizer, drop=dropout)
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