Set learning rate to 10^-3
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train.py
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train.py
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@ -61,7 +61,7 @@ scheduler = torch.optim.lr_scheduler.ReduceLROnPlateau(
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threshold=1e-8
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)
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while total_change >= 1e-4:
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while total_change >= 1e-3:
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# Shuffle training data and convert to one-hot encoding
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classes_dataset = classes_ordered[torch.randperm(len(classes_ordered))]
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onehot_dataset = util.messages_to_onehot(classes_dataset, order)
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