GAIR
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ReasonEval-34B

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 license: llama2
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-# ReasonEval-34B Model Card
-<!-- Provide a quick summary of what the model is/does. -->
-This modelcard aims to be a base template for new models. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/modelcard_template.md?plain=1).
-## Model Details
-### Model Description
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-## Uses
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 license: llama2
+language:
+- en
+pipeline_tag: text-classification
 ---
+# **ReasonEval-7B Model Card**
+## Model Description
+`ReasonEval-34B` is a 34B parameter decoder-only language model fine-tuned from [`llemma_34b`](https://huggingface.co/EleutherAI/llemma_34b).
+<p align="center">
+<img src="introduction.jpg" alt="error" style="width:95%;">
+</p>
+`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
+* **Model type**: `ReasonEval-34B`'s architecture is identical to [`llemma_34b`](https://huggingface.co/EleutherAI/llemma_34b), except that the
+classification head for next-token prediction is replaced with a classification head for outputting the
+possibilities of each class of reasong steps.
+* **Language(s)**: English
+* **Paper**: [Evaluating Mathematical Reasoning Beyond Accuracy](https://drive.google.com/file/d/1Lw1uGFzTUWxo3mB91sfdusSrxnCCO9mR/view?usp=sharing)
+* **Github**: [https://github.com/GAIR-NLP/ReasonEval](https://github.com/GAIR-NLP/ReasonEval)
+* **Finetuned from model**: [https://huggingface.co/EleutherAI/llemma_34b](https://huggingface.co/EleutherAI/llemma_34b)
+* **Fine-tuning Data**: [PRM800K](https://github.com/openai/prm800k)
+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).
+## How to Cite
+```bibtex
+```