Chapter 7 of Reasoning From Scratch analyzes a GRPO implementation with limited policy ratios, a KL term, format rewards, and other improvements.
Chapter 7 of Reasoning From Scratch presents a PyTorch notebook examining improvements to a GRPO implementation, a method used in training reasoning models.
The elements analyzed include limited policy ratios, a KL term, and format rewards. The material lets readers follow the implementation step by step, but it does not claim these changes solve every training challenge.
If using AI to study or apply the notebook, avoid entering personal data, credentials, or confidential code. Use synthetic or de-identified examples, and check your organization’s policies before sending material to any service.
When adapting the experiments, change one variable at a time and record settings and results so you can compare effects. Validate conclusions in your own context; the notebook is technical material, not a performance guarantee.