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@ -78,11 +78,11 @@ def train(cmd, lang, output_dir, train_data, dev_data, n_iter=10, n_sents=0,
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# starts high and decays sharply, to force the optimizer to explore.
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# Batch size starts at 1 and grows, so that we make updates quickly
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# at the beginning of training.
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dropout_rates = util.decaying(util.env_opt('dropout_from', 0.6),
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util.env_opt('dropout_to', 0.1),
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util.env_opt('dropout_decay', 1e-5))
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dropout_rates = util.decaying(util.env_opt('dropout_from', 0.2),
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util.env_opt('dropout_to', 0.2),
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util.env_opt('dropout_decay', 0.0))
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batch_sizes = util.compounding(util.env_opt('batch_from', 1),
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util.env_opt('batch_to', 4),
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util.env_opt('batch_to', 16),
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util.env_opt('batch_compound', 1.001))
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corpus = GoldCorpus(train_path, dev_path, limit=n_sents)
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n_train_words = corpus.count_train()
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