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This is a model released for our paper: [REBEL: Reinforcement Learning via Regressing Relative Rewards](https://arxiv.org/abs/2404.16767).
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# REBEL-Llama-3
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This model is developed with REBEL based on [Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) with [FsfairX-LLaMA3-RM-v0.1](https://huggingface.co/sfairXC/FsfairX-LLaMA3-RM-v0.1) as the reward model and [UltraFeedback](https://huggingface.co/datasets/openbmb/UltraFeedback) dataset.
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The training code is available at https://github.com/ZhaolinGao/REBEL.
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### Links to Other Model
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[REBEL-Llama-3](https://huggingface.co/Cornell-AGI/REBEL-Llama-3)
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## Citation
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Please cite our paper if you use this model in your own work:
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archivePrefix={arXiv},
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primaryClass={cs.LG}
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}
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```
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---
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This is a model released for our paper: [REBEL: Reinforcement Learning via Regressing Relative Rewards](https://arxiv.org/abs/2404.16767).
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# REBEL-Llama-3-epoch_2
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This model is developed with REBEL based on [Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) with [FsfairX-LLaMA3-RM-v0.1](https://huggingface.co/sfairXC/FsfairX-LLaMA3-RM-v0.1) as the reward model and [UltraFeedback](https://huggingface.co/datasets/openbmb/UltraFeedback) dataset.
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The training code is available at https://github.com/ZhaolinGao/REBEL. We collect online generations during each iteration with a batch size of 32.
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### Links to Other Model
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[REBEL-Llama-3](https://huggingface.co/Cornell-AGI/REBEL-Llama-3)
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[REBEL-Llama-3-Armo-iter_1](https://huggingface.co/Cornell-AGI/REBEL-Llama-3-Armo-iter_1)
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[REBEL-Llama-3-Armo-iter_2](https://huggingface.co/Cornell-AGI/REBEL-Llama-3-Armo-iter_2)
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[REBEL-Llama-3-Armo-iter_3](https://huggingface.co/Cornell-AGI/REBEL-Llama-3-Armo-iter_3)
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### Evaluations
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| Model | AlpacaEval 2.0<br>LC Win Rate | AlpacaEval 2.0<br>Win Rate | MT-Bench<br>Average | MMLU<br>(5-shot) | GSM8K<br>(5-shot) |
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| :--------: | :--------: | :--------: | :--------: | :--------: | :--------: |
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| REBEL-OpenChat-3.5| 17.3 | 12.8 | 8.06 | 63.7 | 68.8 |
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| REBEL-Llama-3 | 30.1 | 32.6 | 8.16 | 65.8 | 75.6 |
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| REBEL-Llama-3-epoch_2| 31.3 | 34.2 | 7.83 | 65.4 | 75.4 |
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| REBEL-Llama-3-Armo-iter_1| 48.3 | 41.8 | 8.13 | 66.3 | 75.8 |
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| REBEL-Llama-3-Armo-iter_2| 50.0 | 48.5 | 8.07 | 65.9 | 75.4 |
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| REBEL-Llama-3-Armo-iter_3| 49.7 | 48.1 | 8.01 | 66.0 | 75.7 |
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## Citation
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Please cite our paper if you use this model in your own work:
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archivePrefix={arXiv},
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primaryClass={cs.LG}
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}
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```
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