Group Relative Policy Optimization (GRPO) is a reinforcement learning algorithm designed to enhance reasoning capabilities in large language models (LLMs). It operates without the need for a separate critic model by evaluating groups of responses relative to each other, which reduces computational costs and improves efficiency.
Table of contents
The Math Behind DeepSeek: A Deep Dive into Group Relative Policy Optimization (GRPO)The Foundation of GRPOUnderstanding the GRPO Objective FunctionUnderstanding the GRPO Objective Function in Simple TermsThe GoalStep-by-Step BreakdownPutting It All TogetherWhy GRPO is EffectiveReal-Life AnalogyComparison of GRPO and PPOGRPO in Action: DeepSeek’s SuccessSort: