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qgallouedec
commented
Dec 12, 2025
trl/trainer/rloo_trainer.py
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| from datasets import load_dataset | ||
| from trl import RLOOTrainer | ||
| from trl.rewards import accuracy_reward | ||
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| dataset = load_dataset("trl-lib/tldr", split="train") | ||
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| def reward_func(completions, **kwargs): | ||
| # Dummy reward function that rewards completions with more unique letters. | ||
| return [float(len(set(completion))) for completion in completions] | ||
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| dataset = load_dataset("trl-lib/DeepMath-103K", split="train") | ||
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| trainer = RLOOTrainer( | ||
| model="Qwen/Qwen2-0.5B-Instruct", | ||
| reward_funcs=reward_func, | ||
| reward_funcs=accuracy_reward, | ||
| train_dataset=dataset, | ||
| ) | ||
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| trainer.train() |
| model_name = model_name.split("/")[-1] | ||
| args = RLOOConfig(f"{model_name}-RLOO") | ||
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| # Models |
qgallouedec
requested review from
albertvillanova,
edbeeching,
kashif and
lewtun
kashif
approved these changes
Dec 16, 2025
…g`, `prepare_peft_model` to `experimental.utils` (#4686)
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GRPO recently benefited from some improvements in initialization that were not applied to RLOO. This PR aligns the two initializations.