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--- |
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license: llama2 |
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language: |
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- en |
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pipeline_tag: text-classification |
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--- |
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# **ReasonEval-34B Model Card** |
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## Model Description |
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`ReasonEval-34B` is a 34B parameter decoder-only language model fine-tuned from [`llemma_34b`](https://huggingface.co/EleutherAI/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: |
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- **Validity**: The step contains no mistakes in calculation and logic. |
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- **Redundancy**: The step lacks utility in solving the problem but is still valid. |
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With ReasonEval, you can |
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- 📏 quantify the quality of reasoning steps free of human or close-source models. |
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- 🤖 find the potential invalid or redundant steps in the solutions even with the correct results. |
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- 🛠️ select high-quality training data for downstream tasks (e.g., fine-tuning). |
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## Model Details |
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* **Model type**: `ReasonEval-34B`'s architecture is identical to [`llemma_34b`](https://huggingface.co/EleutherAI/llemma_34b), except that the |
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classification head for next-token prediction is replaced with a classification head for outputting the |
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possibilities of each class of reasong steps. |
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* **Language(s)**: English |
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* **Paper**: [Evaluating Mathematical Reasoning Beyond Accuracy](https://arxiv.org/pdf/2404.05692.pdf) |
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* **Github**: [https://github.com/GAIR-NLP/ReasonEval](https://github.com/GAIR-NLP/ReasonEval) |
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* **Finetuned from model**: [https://huggingface.co/EleutherAI/llemma_34b](https://huggingface.co/EleutherAI/llemma_34b) |
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* **Fine-tuning Data**: [PRM800K](https://github.com/openai/prm800k) |
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For detailed instructions on how to use the ReasonEval-34B model, visit our GitHub repository at [https://github.com/GAIR-NLP/ReasonEval](https://github.com/GAIR-NLP/ReasonEval). |
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## How to Cite |
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```bibtex |
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@article{xia2024evaluating, |
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title={Evaluating Mathematical Reasoning Beyond Accuracy}, |
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author={Xia, Shijie and Li, Xuefeng and Liu, Yixin and Wu, Tongshuang and Liu, Pengfei}, |
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journal={arXiv preprint arXiv:2404.05692}, |
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year={2024}, |
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} |
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``` |
