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🎯 [SFT] add token accuracy metric #2597
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
trl/trainer/sft_trainer.py
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shift_logits = outputs.logits[..., :-1, :].contiguous() | ||
shift_labels = inputs["labels"][..., 1:].contiguous() | ||
train_accuracy = compute_token_accuracy(shift_logits, shift_labels) | ||
self.log({"train_mean_token_accuracy": train_accuracy}) |
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Dors it work with multi gpu?
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i moved it to gather_for_metrics
@lewtun it is now logging to the terminal nicely too:
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mask = labels != ignore_index | ||
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# Calculate accuracy only on non-padding tokens | ||
correct_predictions = (predictions == labels) & mask |
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I thought this syntax was introduced in python3.10
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checking
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it shines ✨
What does this PR do?
Adds a
token_accuracy
metric for training and evaluation in the SFTTrainerBefore submitting
Pull Request section?
to it if that's the case.
documentation guidelines.
Who can review?
Anyone in the community is free to review the PR once the tests have passed. Feel free to tag
members/contributors who may be interested in your PR.