Training Gemma-3 for Structured Mathematical Reasoning with Tunix GRPO, LoRA Adapters, and GSM8K Rewards

Researchers have developed a training workflow for the Gemma-3 model that utilizes Group Relative Policy Optimization and LoRA adapters to improve structured mathematical reasoning. By applying specific reward functions based on the GSM8K dataset, this approach helps the model better adhere to formatting requirements while generating accurate numerical solutions.