update Qwen3.5 grpo demo#124
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Summary of ChangesHello, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed! This pull request focuses on enhancing the Qwen3.5 GRPO demo by optimizing its training parameters and LoRA setup. It also significantly improves the robustness of the GSM8K dataset processing and reward calculation by introducing support for a new answer format. Furthermore, the changes streamline the internal weight management and synchronization processes across different model types, leading to a more efficient and maintainable codebase. Highlights
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Code Review
This pull request updates the GRPO demo for the Qwen3.5 model. The changes include updating default configurations, specifying LoRA target modules, adding checkpoint saving, and modifying the GSM8K prompt and reward logic. A significant and beneficial change is the refactoring of the weight synchronization mechanism, which moves weight name normalization from the sampler to the model side, simplifying the overall logic. I have one minor suggestion to improve code maintainability.
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