手把手教你用Tunix GRPO和LoRA微调Gemma-3做GSM8K数学题，奖励函数设计得很清楚。
该教程展示了如何用Tunix框架和GRPO算法微调Gemma-3模型在GSM8K数学数据集上。首先配置环境并通过Hugging Face加载Gemma-3，将样本包装为推理加答案格式。定义格式正确性和数值正确性的奖励函数，并附加LoRA适配器以降低训练成本。最终通过GRPO分组采样改进策略，并导出合并后的模型。
Training Gemma-3 for Structured Mathematical Reasoning with Tunix GRPO, LoRA Adapters, and GSM8K Rewards
We build an end-to-end GRPO training workflow that teaches Gemma-3 to reason through GSM8K math problems. We prepare the environment, authenticate with Hugging Face, load Gemma-3, and wrap examples into a reasoning-plus-answer prompt format. We define reward functions for format adherence and numeric correctness, then attach LoRA adapters to keep training lightweight. We evaluate a baseline, run GRPO to improve the policy through group-sampled generations, and optionally export the merged model. The post Training Gemma-3 for Structured Mathematical Reasoning with Tunix GRPO, LoRA Adapters, and GSM8K Rewards appeared first on MarkTechPost .
- @koltregaskes07-07 09:00原文