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This is the SFT checkpoint used for the project RLHFlow/Online-RLHF

The model is trained from meta-llama/Meta-Llama-3-8B on RLHFlow/RLHFlow-SFT-Dataset-ver2 for 3 epochs. 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}
}
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