📎 Fix is_clipped to compute the effective clip_ratio #3175
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qgallouedec
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Mar 30, 2025
qgallouedec
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Mar 30, 2025
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@qgallouedec if the situation is per_token_loss1 == per_token_loss2 or advantage == 0, your code will trigger the clip operation. If you really and definitely want to make such a modification, it should be is_clipped = (per_token_loss == -per_token_loss2) & (per_token_loss1 != per_token_loss2). However, I don't recommend doing this because it will obscure your judgment process, especially the influence of the "advantage" on the judgment. |
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Ah yes good point |
qgallouedec
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Mar 31, 2025
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what is clip_radio? |
qgallouedec
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Mar 31, 2025
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Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com> Co-authored-by: Quentin Gallouédec <gallouedec.quentin@gmail.com>
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…ggingface#3131) Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com> Co-authored-by: Quentin Gallouédec <gallouedec.quentin@gmail.com> log answer key to wandb all Table HTML logging table bump patch hmm formatting html esacape reward isnt string [Liger] Liger KTO support (huggingface#2812) Co-authored-by: Kashif Rasul <kashif.rasul@gmail.com> Co-authored-by: Quentin Gallouédec <gallouedec.quentin@gmail.com> 🏃 Migrate CI to self-hosted runners (huggingface#3174) ❤️🩹 [CI] fix transformers dev CI failure (huggingface#3176) Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com> ⏯️ Fix: handle None inputs when resuming GRPO Trainer from checkpoint (huggingface#3148) Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com> 📎 Fix is_clipped to compute the effective clip_ratio (huggingface#3175) Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com> Co-authored-by: Quentin Gallouédec <gallouedec.quentin@gmail.com> Fix breaking typo for flash_attention reducing_memory_usage.md (huggingface#3190) Show unique prompts in GRPO WandB tables (huggingface#3191) 🐗 [CI] Fix trufflehog false positives (huggingface#3192) [GRPO] Improve completion length logging (huggingface#3188) preliminary openai compatible endpoint early concept, needs refining dedupe debug print some slop to work on unslop, missing hist almost valid pseudocode middle-ware monkey patch in mp.Pool()... remove unused More accurate .md need gpu renting lambda again much nicer small aider-chat and datasets conflict risky reqs change should work, but hacky some insights, but monkeypatching probably wont suffice refactor: Rewrite test script to use SWE-bench dataset with MultiProcessAider refactor: Remove logging statements from test.py one step closer finally, the correct abstraction doc todo unslop unslop undo accidental black cleaner abstraction new abstraction
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Co-authored-by: Quentin Gallouédec <45557362+qgallouedec@users.noreply.github.com> Co-authored-by: Quentin Gallouédec <gallouedec.quentin@gmail.com>
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What does this PR do?
Below, let me briefly explain my motives and reasons, the code mainly uses the part marked in the figure.
if (coef_1 < (1 - self.epsilon_low) and advantage > 0) or (coef_1 > (1 + self.epsilon_high) and advantage < 0)
then coef_1 * advantage < (1 - self.epsilon_low) * advantage
coef_1 * advantage < (1 + self.epsilon_high) * advantage
min(per_token_loss1, per_token_loss2) = per_token_loss1
From the perspective of loss, it is actually not clipped.
clip_ratio = (is_clipped * completion_mask).sum() / completion_mask.sum()And this code also calculates an effective clip_ratio
original code:
is_clipped = (coef_1 < (1 - self.epsilon_low)) | (coef_1 > (1 + self.epsilon_high))Therefore, we must combine the sign of the advantage with the original code to calculate is_clipped, thereby computing an effective clip_ratio
As follows
is_clipped = (coef_1 < (1 - self.epsilon_low) and advantage < 0) or (coef_1 > (1 + self.epsilon_high) and advantage > 0)if (coef_1 < (1 - self.epsilon_low) and advantage < 0) or (coef_1 > (1 + self.epsilon_high) and advantage > 0)
then coef_1 * advantage > (1 - self.epsilon_low) * advantage
coef_1 * advantage > (1 + self.epsilon_high) * advantage
min(per_token_loss1, per_token_loss2) = per_token_loss2
Therefore, by modifying is_clipped as described above, the effective clip_ratio can be correctly calculated