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Use fewer iterations by default to avoid overfitting on blank model (resolves #1632)
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@ -73,7 +73,7 @@ TRAIN_DATA = [
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new_model_name=("New model name for model meta.", "option", "nm", str),
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output_dir=("Optional output directory", "option", "o", Path),
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n_iter=("Number of training iterations", "option", "n", int))
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def main(model=None, new_model_name='animal', output_dir=None, n_iter=50):
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def main(model=None, new_model_name='animal', output_dir=None, n_iter=20):
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"""Set up the pipeline and entity recognizer, and train the new entity."""
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if model is not None:
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nlp = spacy.load(model) # load existing spaCy model
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