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Model: swift/qwen2-7b-classical-zh-instruct Source: Original Platform
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README.md
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---
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frameworks:
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- Pytorch
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license: Apache License 2.0
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tasks:
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- text-generation
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#model-type:
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##如 gpt、phi、llama、chatglm、baichuan 等
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#- gpt
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#domain:
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##如 nlp、cv、audio、multi-modal
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#- nlp
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#language:
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##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
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#- cn
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#metrics:
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##如 CIDEr、Blue、ROUGE 等
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#- CIDEr
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#tags:
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##各种自定义,包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
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#- pretrained
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#tools:
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##如 vllm、fastchat、llamacpp、AdaSeq 等
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#- vllm
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---
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模型由SWIFT框架训练,命令:
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```shell
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CUDA_VISIBLE_DEVICES=0 \
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swift sft \
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--model_type qwen2-7b-instruct \
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--sft_type lora \
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--output_dir output \
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--dataset classical-chinese-translate \
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--num_train_epochs 1 \
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--max_length 1024 \
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--check_dataset_strategy warning \
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--lora_rank 8 \
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--lora_alpha 32 \
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--lora_dropout_p 0.05 \
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--lora_target_modules ALL \
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--gradient_checkpointing true \
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--batch_size 1 \
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--weight_decay 0.1 \
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--learning_rate 5e-5 \
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--gradient_accumulation_steps 16 \
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--max_grad_norm 1.0 \
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--warmup_ratio 0.03 \
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--eval_steps 100 \
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--save_steps 100 \
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--save_total_limit 2 \
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--logging_steps 10
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```
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数据集使用的是[古文翻译腔数据集](https://www.modelscope.cn/datasets/swift/classical_chinese_translate)
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用来生成古文翻译调调的回复:
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```text
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Q: 树上有十只鸟,用枪打死一只,还剩多少只?
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A: 我听说在大自然中,鸟儿们总是成群结队地飞翔,枪声一响,它们便会四散而逃。如今打死一只,其余的鸟儿岂能不惊慌失措?恐怕连一只也剩不下啊!世间万物,岂能不互相影响?这难道不是显而易见的道理吗?
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```
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<p style="color: lightgrey;">如果您是本模型的贡献者,我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>,及时完善模型卡片内容。</p>
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