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--- |
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license: llama3 |
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datasets: |
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- silk-road/alpaca-data-gpt4-chinese |
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- TigerResearch/sft_zh |
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- LooksJuicy/ruozhiba |
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- leo009/alpaca-cleaned-zh-cn |
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- REILX/extracted_tagengo_gpt4 |
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language: |
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- en |
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- zh |
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--- |
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### 模型： |
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- https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct |
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### 数据集： |
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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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- https://huggingface.co/datasets/REILX/extracted_tagengo_gpt4 |
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- https://huggingface.co/datasets/LooksJuicy/ruozhiba |
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- https://huggingface.co/datasets/leo009/alpaca-cleaned-zh-cn |
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（使用langid清理以上数据集，删除其中非中文资料） |
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### 训练工具 |
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https://github.com/hiyouga/LLaMA-Factory |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 8 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 64 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 3.0 |
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