Training Arguments - eval_step vs save_step

I am confused a little bit about these two arguments and I did read the documentation here. So my question is as follows:

  • when eval_step is less than save_step and if the best eval_step results does not correspond to the save_step, which step is saved?

For example --eval_step= 200 and --save_step=400.

300th step loss: 0.4
400th step loss: 0.5

So, obviously 300th is better than 400th in terms of loss. Which step’s weights would be saved?

Thank you in advance.

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Unless you are using another argument, the save doesn’t care about the best model, so will just save every save_steps regardless of which step had the better loss.

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Oh I see, I misinterpret :grinning_face_with_smiling_eyes: thanks a lot

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