ArcherCodeR-Dataset / README.md
wizardII's picture
Update README.md
46a73cf verified
---
license: mit
language:
- en
tags:
- code
pretty_name: ' ArcherCodeR'
size_categories:
- 1K<n<10K
task_categories:
- text-generation
viewer: false
---
<div align="center">
# ✨ ArcherCodeR
<div>
🏹️ Reinforcement Learning for Enhanced Code Reasoning in LLMs 🎯
</div>
</div>
<div>
<br>
<div align="center">
[![Github](https://img.shields.io/badge/Code-000000?style=for-the-badge&logo=github&logoColor=000&logoColor=white)](https://github.com/wizard-III/ArcherCodeR)
[![Model](https://img.shields.io/badge/Model-fcd022?style=for-the-badge&logo=huggingface&logoColor=000&labelColor)](https://huggingface.co/wizardII/ArcherCodeR-1.5B)
[![Data](https://img.shields.io/badge/Data-fcd022?style=for-the-badge&logo=huggingface&logoColor=000&labelColor)](https://huggingface.co/datasets/wizardII/ArcherCodeR-Dataset)
[![Wandb](https://img.shields.io/badge/Wandb-000000?style=for-the-badge&logo=Wandb&logoColor=000&labelColor)](https://wandb.ai/wangjkpkucs-peking-university/ArcherCodeR?nw=nwuserwangjkpkucs)
[![知乎](https://img.shields.io/badge/知乎-0084FF?style=for-the-badge&logo=zhihu&logoColor=white)](https://zhuanlan.zhihu.com/p/1918765619614057424)
</div>
## Overview
[`ArcherCodeR-Dataset`](https://huggingface.co/datasets/wizardII/ArcherCodeR-Dataset) is **a dataset of verifiable, challenging, and diverse coding questions (6.7K)**. This dataset is used to train the **`ArcherCodeR`** model series, which consists of code reasoning models trained using large-scale rule-based reinforcement learning with carefully designed datasets and training recipes.
We select, clean, and curate coding problems from open-source datasets, including
- [agentica-org/DeepScaleR-Preview-Dataset](https://huggingface.co/datasets/agentica-org/DeepScaleR-Preview-Dataset)
- [deepmind/code_contests](https://huggingface.co/datasets/deepmind/code_contests)
- [open-r1/codeforces](https://huggingface.co/datasets/open-r1/codeforces)
### 🔍 Key Notes:
- Both code_contests (DeepMind) and codeforces (Open-r1) datasets include regenerated test cases to mitigate false positives.
- Significant prompt duplication exists across sources. When duplicates occur, code_contests or codeforces data takes priority.
For more details on data processing, please refer to our [Zhihu article](https://zhuanlan.zhihu.com/p/1918765619614057424).
## Technical Report
The technical report will be released soon.