微调百川模型出错：Target modules ['q_proj', 'v_proj'] not found in the base model

[intothephone]

是不是还不支持baichuan-7B基座模型，还是说我PEFT的版本有问题？

Traceback (most recent call last):
File "/home/jerome/github/LLaMA-Efficient-Tuning/src/train_sft.py", line 98, in
main()
File "/home/jerome/github/LLaMA-Efficient-Tuning/src/train_sft.py", line 26, in main
model, tokenizer = load_pretrained(model_args, finetuning_args, training_args.do_train, stage="sft")
File "/home/jerome/github/LLaMA-Efficient-Tuning/src/utils/common.py", line 216, in load_pretrained
model = _init_adapter(model, model_args, finetuning_args, is_trainable, is_mergeable)
File "/home/jerome/github/LLaMA-Efficient-Tuning/src/utils/common.py", line 133, in _init_adapter
model = get_peft_model(model, lora_config)
File "/home/jerome/anaconda3/envs/left/lib/python3.10/site-packages/peft/mapping.py", line 120, in get_peft_model
return MODEL_TYPE_TO_PEFT_MODEL_MAPPING[peft_config.task_type](model, peft_config)
File "/home/jerome/anaconda3/envs/left/lib/python3.10/site-packages/peft/peft_model.py", line 662, in init
super().init(model, peft_config, adapter_name)
File "/home/jerome/anaconda3/envs/left/lib/python3.10/site-packages/peft/peft_model.py", line 99, in init
self.base_model = PEFT_TYPE_TO_MODEL_MAPPING[peft_config.peft_type](
File "/home/jerome/anaconda3/envs/left/lib/python3.10/site-packages/peft/tuners/lora.py", line 154, in init
self.add_adapter(adapter_name, self.peft_config[adapter_name])
File "/home/jerome/anaconda3/envs/left/lib/python3.10/site-packages/peft/tuners/lora.py", line 161, in add_adapter
self._find_and_replace(adapter_name)
File "/home/jerome/anaconda3/envs/left/lib/python3.10/site-packages/peft/tuners/lora.py", line 254, in _find_and_replace
raise ValueError(
ValueError: Target modules ['q_proj', 'v_proj'] not found in the base model. Please check the target modules and try again.

[intothephone]

sorry, missing args, no issue

[hiyouga]

@yw2278 --lora_target W_pack

[zl1994]

@yw2278 `--lora_target W_pack
请问为什么baichuan的lora_target和其他模型不一样，lora_target有什么讲究？