Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs

🖥️Code | 🤗Data | 📄Paper

This repo contains the Math-Step-DPO-10K dataset for our paper Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs, 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.

Math-Step-DPO-10K is a high-quality step-wise preference dataset for mathematical reasoning.

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