File size: 1,402 Bytes
7275d66 089e97a 7275d66 089e97a 7275d66 b0dca04 7275d66 089e97a 7275d66 089e97a |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 |
---
library_name: transformers
tags: []
---
This is the SFT checkpoint used for the project [RLHFlow/Online-RLHF](https://github.com/RLHFlow/Online-RLHF)
* **Paper**: [RLHF Workflow: From Reward Modeling to Online RLHF](https://arxiv.org/pdf/2405.07863) (Published in TMLR, 2024)
* **Authors**: Hanze Dong*, Wei Xiong*, Bo Pang*, Haoxiang Wang*, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
* **Code**: https://github.com/RLHFlow/Online-RLHF
The model is trained from [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on [RLHFlow/RLHFlow-SFT-Dataset-ver2](https://huggingface.co/datasets/RLHFlow/RLHFlow-SFT-Dataset-ver2) for 1 epoch. We use a global batch size of 128 and a learning rate of 2e-5, where we pack the samples and split them into chunks of 8192 token. See more training details at https://github.com/RLHFlow/Online-RLHF/blob/main/sft/llama3-8b-it.yaml .
## Citation
Please cite our techical report if you find our model is useful for your research or product.
```
@misc{dong2024rlhf,
title={RLHF Workflow: From Reward Modeling to Online RLHF},
author={Hanze Dong and Wei Xiong and Bo Pang and Haoxiang Wang and Han Zhao and Yingbo Zhou and Nan Jiang and Doyen Sahoo and Caiming Xiong and Tong Zhang},
year={2024},
eprint={2405.07863},
archivePrefix={arXiv},
primaryClass={cs.LG}
}
``` |