--- license: apache-2.0 base_model: - Qwen/Qwen3-1.7B library_name: transformers pipeline_tag: text-generation tags: - mathematical-reasoning - reinforcement-learning - grpo --- # Model Card for PrAg-PO Qwen3-1.7B step720 **If you are using the model, a star to our [github repo](https://github.com/wenquanlu/PrAg-PO) would be really appreciated! 😊** This is the step 720 checkpoint when training Qwen3-1.7B on MATH Level-3-to-5 Dataset using PrAg-PO. The training procedure is outlined in the paper [PrAg-PO: Prompt Augmented Policy Optimization for Robust and Diverse Mathematical Reasoning](https://arxiv.org/abs/2602.03190). ### Model Sources - **Repository 🤖:** [https://github.com/wenquanlu/PrAg-PO](https://github.com/wenquanlu/PrAg-PO) - **Paper 📝:** [PrAg-PO: Prompt Augmented Policy Optimization for Robust and Diverse Mathematical Reasoning](https://arxiv.org/abs/2602.03190) ## Uses This model is intended for mathematical reasoning tasks. It leverages prompt augmentation to generate reasoning traces under diverse templates, increasing rollout diversity and stability during RL training. ### Results ## Citation ```bibtex @misc{lu2026pragpopromptaugmentedpolicy, title={PrAg-PO: Prompt Augmented Policy Optimization for Robust and Diverse Mathematical Reasoning}, author={Wenquan Lu and Hai Huang and Enqi Liu and Randall Balestriero}, journal={arXiv preprint arXiv:2602.03190}, url={https://arxiv.org/abs/2602.03190}, year={2026}, } ```
