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ReasonEval-34B Model Card

Model Description

ReasonEval-34B is a 34B parameter decoder-only language model fine-tuned from llemma_34b. Given a mathematical problem and the solution, ReasonEval-34B assesses the problem-solving process in a step-by-step format from the following perspectives:

  • Validity: The step contains no mistakes in calculation and logic.
  • Redundancy: The step lacks utility in solving the problem but is still valid.

With ReasonEval, you can

  • 📏 quantify the quality of reasoning steps free of human or close-source models.

  • 🤖 find the potential invalid or redundant steps in the solutions even with the correct results.

  • 🛠️ select high-quality training data for downstream tasks (e.g., fine-tuning).

Model Details

For detailed instructions on how to use the ReasonEval-34B model, visit our GitHub repository at https://github.com/GAIR-NLP/ReasonEval.

How to Cite

@article{xia2024evaluating,
        title={Evaluating Mathematical Reasoning Beyond Accuracy}, 
        author={Xia, Shijie and Li, Xuefeng and Liu, Yixin and Wu, Tongshuang and Liu, Pengfei},
        journal={arXiv preprint arXiv:2404.05692},
        year={2024},
}
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