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Besides often improving generalization, what other practical benefit does early stopping have?

It makes training deterministic, so that every single run can be reproduced exactly1
It removes the need for a separate validation set during training2
It allows much larger learning rates without any risk of divergence3
It saves compute, since training ends once the validation error stops improving4

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