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  ### 数据集
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  使用以下8个数据集
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/636f54b95d2050767e4a6317/maYhXsWKddThOBRvU5HtZ.png)
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- 对Qwen1.5-7B-Chat微调,测试结果显示CEVAL和MMLU分数均有上升
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- ### 模型:
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  - https://huggingface.co/Qwen/Qwen1.5-7B-Chat
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- ### 数据集:
 
 
 
 
 
 
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  - https://huggingface.co/datasets/REILX/extracted_tagengo_gpt4
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  - https://huggingface.co/datasets/TigerResearch/sft_zh
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  - https://huggingface.co/datasets/silk-road/alpaca-data-gpt4-chinese
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  | 模型名称 | CEVAL | MMLU |
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  |------------------------ |-------|------|
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  | Qwen1.5-7B-Chat | 68.61 | 61.56 |
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- | Qwen1.5-7B-Chat-sft-lora-tigerbot-alpacadatagpt4-ruozhiba-1epoch | 71.36 | |
 
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  ### License
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  This project utilizes certain datasets and checkpoints that are subject to their respective original licenses. Users must comply with all terms and conditions of these original licenses. The content of this project itself is licensed under the Apache license 2.0.
 
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  ### 数据集
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  使用以下8个数据集
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  ![image/png](https://cdn-uploads.huggingface.co/production/uploads/636f54b95d2050767e4a6317/maYhXsWKddThOBRvU5HtZ.png)
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+ 对Qwen1.5-7B-Chat进行微调并测试,结果显示,使用三个数据集微调后的模型在CEVAL和MMLU的评分上均有所提升,而且这个模型的表现优于使用八个数据集微调后的模型。
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+ ### 基础模型:
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  - https://huggingface.co/Qwen/Qwen1.5-7B-Chat
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+ ### 3DataSets数据集:
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+ - https://huggingface.co/datasets/LooksJuicy/ruozhiba
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+ - https://huggingface.co/datasets/TigerResearch/sft_zh
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+ - https://huggingface.co/datasets/silk-road/alpaca-data-gpt4-chinese
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+ ### 8DataSets数据集:
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+ 大约750Mb的微调数据集
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  - https://huggingface.co/datasets/REILX/extracted_tagengo_gpt4
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  - https://huggingface.co/datasets/TigerResearch/sft_zh
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  - https://huggingface.co/datasets/silk-road/alpaca-data-gpt4-chinese
 
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  | 模型名称 | CEVAL | MMLU |
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  |------------------------ |-------|------|
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  | Qwen1.5-7B-Chat | 68.61 | 61.56 |
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+ | Qwen1.5-7B-Chat-sft-lora-3DataSets-1epoch | 71.75 | 62.43 |
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+ | Qwen1.5-7B-Chat-sft-lora-8DataSets-1epoch | 71.36 | 61.78 |
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  ### License
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  This project utilizes certain datasets and checkpoints that are subject to their respective original licenses. Users must comply with all terms and conditions of these original licenses. The content of this project itself is licensed under the Apache license 2.0.