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            ## Evaluation 
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            We test the performance of our model with [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness). The evaluation results on common datasets are shown below. We test on AI2 Reasoning Challenge (25-shot), HellaSwag (10-shot), MMLU (5-shot), and Winogrande (5-shot).
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            |          Models         | ARC-C | Hellaswag |  MMLU | WinoGrade |  Ave  |
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            | Moxin-7B-finetune 	|   80.03   	|   75.17   	| 82.24 	| 81.12 	| 58.64 	| 75.44 	|
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            ## Evaluation 
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            We test the performance of our model with [lm-evaluation-harness](https://github.com/EleutherAI/lm-evaluation-harness). The evaluation results on common datasets are shown below. We test on AI2 Reasoning Challenge (25-shot), HellaSwag (10-shot), MMLU (5-shot), and Winogrande (5-shot). We release the Moxin-7B-finetuned as our base model. We further finetune our base model on Tulu v2 to obtain our chat model.
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            |          Models         | ARC-C | Hellaswag |  MMLU | WinoGrade |  Ave  |
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            | Moxin-7B-finetune 	|   80.03   	|   75.17   	| 82.24 	| 81.12 	| 58.64 	| 75.44 	|
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            ## Citation
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            ```
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            @article{zhao2024fully,
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              title={Fully Open Source Moxin-7B Technical Report},
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              author={Zhao, Pu and Shen, Xuan and Kong, Zhenglun and Shen, Yixin and Chang, Sung-En and Rupprecht, Timothy and Lu, Lei and Nan, Enfu and Yang, Changdi and He, Yumei and others},
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              journal={arXiv preprint arXiv:2412.06845},
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              year={2024}
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            }
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            ```
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