| --- |
| license: llama2 |
| datasets: |
| - gair-prox/open-web-math-pro |
| language: |
| - en |
| base_model: |
| - codellama/CodeLlama-7b-hf |
| --- |
| |
|
|
|
|
| # CodeLlama-7B-ProXMath |
|
|
| <p align="center"> |
| <img src="prox-teaser.png"> |
| </p> |
|
|
| [ArXiv](http://arxiv.org/abs/2409.17115) | [Data: OpenWebMath-Pro](https://huggingface.co/datasets/gair-prox/open-web-math-pro) | [Code](https://github.com/GAIR-NLP/program-every-example) |
|
|
| **CodeLlama-7B-ProXMath** is a math-adapted language model that is continually pre-trained on [OpenWebMath-Pro](https://huggingface.co/datasets/gair-prox/open-web-math-pro) (a refined version by ProX) for **10**B tokens. |
|
|
| ## Evaluations |
|
|
| ProX models are evaluated on 9 common math reasoning benchmarks. |
|
|
| | Model | asdiv | gsm8k | mathqa | mawps | minerva_math | mmlu_stem | sat_math | svamp | tabmwp | average | |
| |-----------------------|:--------:|:--------:|:--------:|:--------:|:------------:|:---------:|:--------:|:--------:|:--------:|:--------:| |
| | CodeLlama-7B | 50.7 | 11.8 | 14.3 | 62.6 | 5.0 | 20.4 | 21.9 | 44.2 | 30.6 | 29.1 | |
| | CodeLlama-7B-ProXMath | **67.9** | **35.6** | **38.9** | **82.7** | **17.6** | **42.6** | **62.5** | **55.8** | **41.3** | **49.4** | |
| |
| ### Citation |
| ``` |
| @article{zhou2024programming, |
| title={Programming Every Example: Lifting Pre-training Data Quality like Experts at Scale}, |
| author={Zhou, Fan and Wang, Zengzhi and Liu, Qian and Li, Junlong and Liu, Pengfei}, |
| journal={arXiv preprint arXiv:2409.17115}, |
| year={2024} |
| } |
| ``` |
| |
