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That's very interesting. Do the train and val set losses both show that behavior? I did a very similar experiment earlier this year - in my case it was a classifier where images could be categorized different ways, and my takeaway was making it predict more classes improved performance. I'll have to go back and look at the loss curves during training and see if the improvement is immediate as in your case


Before one epoch, both the train and eval curves look pretty much identical. Quite curious




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