fix chosen_nll_loss in chunked losses#486
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shivam15s
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Great catch, and thanks for the quick PR! With the TRL fixes we discussed today, we should be able to closely match the loss curve obtained from TRL Trainer
| compute_nll_loss=compute_nll_loss, | ||
| is_encoder_decoder=is_encoder_decoder, | ||
| ) | ||
| chosen_nll_loss = ( |
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I believe we also have to fix how we do normalization. My hunch is that's the reason for failing tests
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| if not is_encoder_decoder: | ||
| shifted_logits = log_probs_chunk[:len_chosen_chunk, :-1].contiguous() | ||
| shifted_target = target_chunk[:len_chosen_chunk, 1:].contiguous() | ||
| else: | ||
| shifted_logits = log_probs_chunk[:len_chosen_chunk].contiguous() | ||
| shifted_target = target_chunk[:len_chosen_chunk].contiguous() | ||
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The shifted logits/target should also be used to calculate chosen/rejected logps and in general for everything that follows to compute the loss.
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Dec 19, 2024
This reverts commit 61eefe9.
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This reverts commit 61eefe9. ## Summary <!--- This is a required section; please describe the main purpose of this proposed code change. ---> <!--- ## Details This is an optional section; is there anything specific that reviewers should be aware of? ---> ## Testing Done <!--- This is a required section; please describe how this change was tested. ---> <!-- Replace BLANK with your device type. For example, A100-80G-PCIe Complete the following tasks before sending your PR, and replace `[ ]` with `[x]` to indicate you have done them. --> - Hardware Type: <BLANK> - [ ] run `make test` to ensure correctness - [ ] run `make checkstyle` to ensure code style - [ ] run `make test-convergence` to ensure convergence
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Summary
Fix the nll loss in the the chunked loses when the model is a decoder only model, by shifting the logits and targets
make testto ensure correctnessmake checkstyleto ensure code stylemake test-convergenceto ensure convergence