mesdaq
commented
7 months ago 解决了吗，一样的问题，是输入的模型问题吗
Open LiBinNLP opened 7 months ago
mesdaq
commented
7 months ago 解决了吗，一样的问题，是输入的模型问题吗
LiBinNLP
commented
7 months ago 解决了吗，一样的问题，是输入的模型问题吗
没解决，用另一个仓库的代码就没问题了：https://github.com/tloen/alpaca-lora。
yangjianxin1
commented
6 months ago 遇到相同的问题
I met this issue when fine-tuning the LLaMa-7B-Chat-hf with example dataset:
Traceback (most recent call last): File "finetune-lora.py", line 656, in
train()
File "finetune-lora.py", line 622, in train
train_result = trainer.train(resume_from_checkpoint=checkpoint)
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/transformers/trainer.py", line 1537, in train
return inner_training_loop(
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/transformers/trainer.py", line 1854, in _inner_training_loop
tr_loss_step = self.training_step(model, inputs)
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/transformers/trainer.py", line 2732, in training_step
self.accelerator.backward(loss)
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/accelerate/accelerator.py", line 1905, in backward
loss.backward(kwargs)
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/torch/_tensor.py", line 488, in backward
torch.autograd.backward(
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/torch/autograd/init.py", line 197, in backward
Variable._execution_engine.run_backward( # Calls into the C++ engine to run the backward pass
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/torch/autograd/function.py", line 267, in apply
return user_fn(self, args)
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/torch/utils/checkpoint.py", line 141, in backward
outputs = ctx.run_function(detached_inputs)
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, *kwargs)
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/accelerate/hooks.py", line 165, in new_forward
output = module._old_forward(args, kwargs)
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/transformers/models/llama/modeling_llama.py", line 789, in forward
hidden_states, self_attn_weights, present_key_value = self.self_attn(
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1194, in _call_impl
return forward_call(*input, *kwargs)
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/accelerate/hooks.py", line 165, in new_forward
output = module._old_forward(args, **kwargs)
File "/sda/libin/anaconda3/envs/llama2/lib/python3.8/site-packages/transformers/models/llama/modeling_llama.py", line 423, in forward
raise ValueError(
ValueError: Attention mask should be of size (4, 1, 240, 480), but is torch.Size([4, 1, 240, 240])