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I know that overfitting occurs when the accuracy on the training set improves but the accuracy on the validation set decrease. So, we must stop the training. I would like to know if this is a rule that more epochs always decrease the accuracy on the training set. In other words, is the accuracy function over epochs a non-ascending function? If not, then why?

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Yes, accuracy measured on the training set over epochs is not monotonically decreasing.

Possible reasons:

  1. Software bug
  2. Nan due to division by zero / log (0) / overflow
  3. Too big learning rate
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