RuntimeError: 'weight' must be 2-D During Fine-Tuning with Single GPU

[ouerwt]

I only have one GPU, so I used the command python finetune.py --config-name=finetune.yaml during the first step of fine-tuning. However, I encountered the error RuntimeError: 'weight' must be 2-D. Below is the detailed error message, and I have failed to resolve the issue on my own. I hope to get some help. (Additionally, this is my first time asking a question related to research work, so if there's anything lacking, please let me know.)

[2024-09-12 23:49:01,206] [INFO] [partition_parameters.py:348:__exit__] finished initializing model - num_params = 291, num_elems = 6.74B
Loading checkpoint shards: 100%|████████████████████████████████████████████████████████| 2/2 [00:04<00:00,  2.05s/it]generation_config.json: 100%|████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 1.84MB/s]max_steps is given, it will override any value given in num_train_epochs
  0%|                                                                                        | 0/1250 [00:00<?, ?it/s]Error executing job with overrides: []
Traceback (most recent call last):
  File "/root/tofu-main/finetune.py", line 125, in main
    trainer.train()
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/transformers/trainer.py", line 1938, in train
    return inner_training_loop(
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/transformers/trainer.py", line 2279, in _inner_training_loop
    tr_loss_step = self.training_step(model, inputs)
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/transformers/trainer.py", line 3318, in training_step
    loss = self.compute_loss(model, inputs)
  File "/root/tofu-main/dataloader.py", line 26, in compute_loss
    outputs = model(input_ids,labels=labels, attention_mask=attention_mask)
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1562, in _call_impl
    return forward_call(*args, **kwargs)
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/accelerate/utils/operations.py", line 820, in forward
    return model_forward(*args, **kwargs)
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/accelerate/utils/operations.py", line 808, in __call__    return convert_to_fp32(self.model_forward(*args, **kwargs))
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/torch/amp/autocast_mode.py", line 43, in decorate_autocast
    return func(*args, **kwargs)
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py", line 1189, in forward
    outputs = self.model(
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1562, in _call_impl
    return forward_call(*args, **kwargs)
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/transformers/models/llama/modeling_llama.py", line 950, in forward
    inputs_embeds = self.embed_tokens(input_ids)
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1553, in _wrapped_call_impl
    return self._call_impl(*args, **kwargs)
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1562, in _call_impl
    return forward_call(*args, **kwargs)
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/torch/nn/modules/sparse.py", line 164, in forward
    return F.embedding(
  File "/root/miniconda3/envs/tofu/lib/python3.10/site-packages/torch/nn/functional.py", line 2267, in embedding
    return torch.embedding(weight, input, padding_idx, scale_grad_by_freq, sparse)
RuntimeError: 'weight' must be 2-D

Set the environment variable HYDRA_FULL_ERROR=1 for a complete stack trace.