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基于alpaca-data-gpt4-chinese、sft_zh数据集对Llama-3-8B-Instruct进行微调。

模型:

数据集:

训练工具

https://github.com/hiyouga/LLaMA-Factory

测评方式:

使用opencompass(https://github.com/open-compass/OpenCompass/ ), 测试工具基于CEval和MMLU对微调之后的模型和原始模型进行测试。
测试模型分别为:

  • Llama-3-8B
  • Llama-3-8B-Instruct
  • LLama3-Instruct-sft-lora-tigerbot-alpacadatagpt4,使用sft_zh、alpaca-data-gpt4-chinese数据对Llama-3-8B-Instruct使用sft方式lora微调

结果

模型名称 CEVAL MMLU
LLama3 49.91 66.62
LLama3-Instruct 50.55 67.15
LLama3-Instruct-sft-lora-tigerbot-alpacadatagpt4 53.65 68.09
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Datasets used to train REILX/Llama-3-8B-Instruct-Tiger-alpaca-chinese-lora

Collection including REILX/Llama-3-8B-Instruct-Tiger-alpaca-chinese-lora