frequent checkpoints have worse performance
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Hi All, I often notice an issue when training a model and evaluate on dev set.
Usually we may evaluate on the dev after each epoch, let's call this as setting A;
But we often want to check the system more often on the dev set, so we may evaluate for example 1/5 epoch; let's call this as setting B.

What I noticed is that A and B will get totally different performance in the end.  Since B checks more often, I supposed that B can get the same or at least very close performance with A then evaluate at 5/5 of the training set, 10/5 of the training set, etc. But they are very different. For example, when I train textual entailment model on RTE dataset, A can give me about 86% accuracy on dev, but B can only give about 80%.

What's the issue here? thanks


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**A link to original question on the forum/Stack Overflow**:
hi, can you post the link on stackoverflow

Btw, I also face this issue when working with an RTE dataset and have raised an issue here..[https://github.com/huggingface/transformers/issues/5863](url). My dev values after each epoch don't match up when the total number of epoch changes.  Now its making me wonder if its RTE specific. <|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
