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@@ -9,7 +9,7 @@ This is the SFT checkpoint used for the project [RLHFlow/Online-RLHF](https://gi
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  * **Authors**: Hanze Dong*, Wei Xiong*, Bo Pang*, Haoxiang Wang*, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
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  * **Code**: https://github.com/RLHFlow/Online-RLHF
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- 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 2 epochs. We use a global batch size of 128 and a learning rate of 2e-6, 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 .
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  ## Academic Benchmarks
 
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  * **Authors**: Hanze Dong*, Wei Xiong*, Bo Pang*, Haoxiang Wang*, Han Zhao, Yingbo Zhou, Nan Jiang, Doyen Sahoo, Caiming Xiong, Tong Zhang
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  * **Code**: https://github.com/RLHFlow/Online-RLHF
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+ 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 2 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 .
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  ## Academic Benchmarks