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Published 20 hours ago • verified publisher icon jaywonchung

The loss is nan

Open rabbicat30 opened this issue 1 year ago • 1 comments

In some cases, such as the sequence length is short or the value of mask_prob is small, there will be a situation where the whole training sequence is not masked, and the loss at this time will be the value of nan, how to solve this situation? I don't want the loss to be a nan value, can I only adjust the value of prob?

rabbicat30 avatar May 22 '23 05:05 rabbicat30

Because I want to do a comparison experiment, I want to make sure the value of mask_prob is the same

rabbicat30 avatar May 22 '23 06:05 rabbicat30