Cornell-AGI/REBEL-Llama-3-epoch_2

This is a model released for our paper: REBEL: Reinforcement Learning via Regressing Relative Rewards.

REBEL-Llama-3

This model is developed with REBEL based on Meta-Llama-3-8B-Instruct with FsfairX-LLaMA3-RM-v0.1 as the reward model and UltraFeedback dataset. The training code is available at https://github.com/ZhaolinGao/REBEL. This is the checkpoint that achieves the highest AlpacaEval 2.0 scores.

Links to Other Model

REBEL-OpenChat-3.5

REBEL-Llama-3

AlpacaEval 2.0 Evaluations

Model	AlpacaEval 2.0 LC Win Rate	AlpacaEval 2.0 Win Rate
REBEL-OpenChat-3.5	17.3	12.8
REBEL-Llama-3	30.1	32.6
REBEL-Llama-3-epoch_2	31.33	34.22

Citation

Please cite our paper if you use this model in your own work:

@misc{gao2024rebel,
      title={REBEL: Reinforcement Learning via Regressing Relative Rewards}, 
      author={Zhaolin Gao and Jonathan D. Chang and Wenhao Zhan and Owen Oertell and Gokul Swamy and Kianté Brantley and Thorsten Joachims and J. Andrew Bagnell and Jason D. Lee and Wen Sun},
      year={2024},
      eprint={2404.16767},
      archivePrefix={arXiv},
      primaryClass={cs.LG}
}