---
license: apache-2.0
base_model:
- Qwen/Qwen2.5-Math-1.5B
library_name: transformers
pipeline_tag: text-generation
tags:
- mathematical-reasoning
- reinforcement-learning
- grpo
---

# Model Card for DAPO w/ Prompt Augmentation

**If you are using the model, a star to our [github repo](https://github.com/wenquanlu/prompt-augmentation-GRPO) would be really appreciated! 😊**

This is the step 2720 checkpoint when training Qwen2.5-Math-1.5B on MATH Level-3-to-5 Dataset using DAPO (no dynamic sampling) with prompt augmentation. The training procedure is outlined in the paper [Prompt Augmentation Scales up GRPO Training on Mathematical Reasoning](https://huggingface.co/papers/2602.03190).

### Model Sources

- **Repository 🤖:** [https://github.com/wenquanlu/prompt-augmentation-GRPO](https://github.com/wenquanlu/prompt-augmentation-GRPO)
- **Paper 📝:** [Prompt Augmentation Scales up GRPO Training on Mathematical Reasoning](https://huggingface.co/papers/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

<p align="center">
<img src="https://raw.githubusercontent.com/wenquanlu/prompt-augmentation-GRPO/master/imgs/table_result.png">
</p>


## Citation
```bibtex
@misc{lu2026promptaugmentationscalesgrpo,
      title={Prompt Augmentation Scales up GRPO Training on Mathematical Reasoning}, 
      author={Wenquan Lu and Hai Huang and Randall Balestriero},
      journal={arXiv preprint arXiv:2602.03190},
      year={2026},
}
```