在 Amazon SageMaker HyperPod 上微调 GPT-OSS-20B 的多语言推理教程
Fine-tuning GPT-OSS-20B for multilingual reasoning on Amazon SageMaker HyperPod
精选理由
AWS 放出的实操教程：微调 GPT-OSS-20B 做多语言推理，SFT 直接把准确率从 22% 拉到 100%，还教你什么时候该用 GRPO。
AWS 发布教程，演示如何在 Amazon SageMaker HyperPod 上微调 GPT-OSS-20B 以提升多语言推理能力。教程对比了监督微调（SFT）和 GRPO 强化学习两种路径的适用场景。文中给出的数据显示 SFT 将推理任务的准确率从 22% 提升到 100%，而 GRPO 在仍有提升空间的场景带来可衡量的额外收益。内容覆盖完整流程，可直接照做复现。
原文 · AWS Machine Learning Blog
Fine-tuning GPT-OSS-20B for multilingual reasoning on Amazon SageMaker HyperPod
Learn how we fine-tuned GPT-OSS-20B for multilingual reasoning on Amazon SageMaker HyperPod, and how to decide between supervised fine-tuning (SFT) and reinforcement learning with GRPO. SFT took reasoning-language accuracy from 22% to 100%, and GRPO added measurable gains where headroom existed.
