| license: apache-2.0 | |
| # Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs | |
| 🖥️[Code](https://github.com/dvlab-research/Step-DPO) | 🤗[Data](https://huggingface.co/datasets/xinlai/Math-Step-DPO-10K) | 📄[Paper](https://arxiv.org/pdf/2406.18629) | |
| This repo contains the **DeepSeekMath-RL-Step-DPO** model. It is obtained by performing **Step-DPO** on [**DeepSeekMath-RL**](https://huggingface.co/deepseek-ai/deepseek-math-7b-rl). | |
| **Step-DPO** is a simple, effective, and data-efficient method for boosting the mathematical reasoning ability of LLMs. Notably, Step-DPO, when applied to Qwen2-72B-Instruct, achieves scores of **70.8%** and **94.0%** on the test sets of **MATH** and **GSM8K** without bells and wistles, respectively, surpassing a series of closed-source models, including GPT-4-1106, Claude-3-Opus, and Gemini-1.5-Pro. | |
| ## Contact | |
| Please submit an issue [here](https://github.com/dvlab-research/Step-DPO) or send me an email [here](mailto:[email protected]). |