| | --- |
| | base_model: Qwen/Qwen2.5-7B |
| | library_name: transformers |
| | model_name: Qwen2.5-7B-Open-R1-GRPO-math-lighteval-noformat |
| | tags: |
| | - generated_from_trainer |
| | - trl |
| | - grpo |
| | licence: license |
| | --- |
| | |
| | # Model Card for Qwen2.5-7B-Open-R1-GRPO-math-lighteval-noformat |
| |
|
| | This model is a fine-tuned version of [Qwen/Qwen2.5-7B](https://huggingface.co/Qwen/Qwen2.5-7B). |
| | It has been trained using [TRL](https://github.com/huggingface/trl). |
| |
|
| | ## Quick start |
| |
|
| | ```python |
| | from transformers import pipeline |
| | |
| | question = "If you had a time machine, but could only go to the past or the future once and never return, which would you choose and why?" |
| | generator = pipeline("text-generation", model="Lansechen/Qwen2.5-7B-Open-R1-GRPO-math-lighteval-noformat", device="cuda") |
| | output = generator([{"role": "user", "content": question}], max_new_tokens=128, return_full_text=False)[0] |
| | print(output["generated_text"]) |
| | ``` |
| |
|
| | ## Training procedure |
| |
|
| | [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="150" height="24"/>](https://wandb.ai/chenran1995-the-chinese-university-of-hong-kong/huggingface/runs/1bx3u1ql) |
| |
|
| |
|
| | This model was trained with GRPO, a method introduced in [DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models](https://huggingface.co/papers/2402.03300). |
| |
|
| | ### Framework versions |
| |
|
| | - TRL: 0.16.0 |
| | - Transformers: 4.49.0 |
| | - Pytorch: 2.5.1+cu121 |
| | - Datasets: 3.3.1 |
| | - Tokenizers: 0.21.0 |
| |
|
| | ## Citations |
| |
|
| | Cite GRPO as: |
| |
|
| | ```bibtex |
| | @article{zhihong2024deepseekmath, |
| | title = {{DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models}}, |
| | author = {Zhihong Shao and Peiyi Wang and Qihao Zhu and Runxin Xu and Junxiao Song and Mingchuan Zhang and Y. K. Li and Y. Wu and Daya Guo}, |
| | year = 2024, |
| | eprint = {arXiv:2402.03300}, |
| | } |
| | |
| | ``` |
| |
|
| | Cite TRL as: |
| | |
| | ```bibtex |
| | @misc{vonwerra2022trl, |
| | title = {{TRL: Transformer Reinforcement Learning}}, |
| | author = {Leandro von Werra and Younes Belkada and Lewis Tunstall and Edward Beeching and Tristan Thrush and Nathan Lambert and Shengyi Huang and Kashif Rasul and Quentin Gallouédec}, |
| | year = 2020, |
| | journal = {GitHub repository}, |
| | publisher = {GitHub}, |
| | howpublished = {\url{https://github.com/huggingface/trl}} |
| | } |
| | ``` |