Trainer has stuck during the code block of "Trainer.train" in Jupyter Notebook 
Author: ericininder
Pull request: no
Labels: name: bug

### System Info

- `transformers` version: 4.44.2
- Platform: Linux-5.4.0-187-generic-x86_64-with-glibc2.31
- Python version: 3.10.13
- Huggingface_hub version: 0.23.4
- Safetensors version: 0.4.3
- Accelerate version: 0.33.0
- Accelerate config:    not found
- PyTorch version (GPU?): 2.2.0+cu118 (True)
- Tensorflow version (GPU?): 2.17.0 (False)
- Flax version (CPU?/GPU?/TPU?): not installed (NA)
- Jax version: not installed
- JaxLib version: not installed
- Using distributed or parallel set-up in script?: <fill in>
- Using GPU in script?: <fill in>
- GPU type: NVIDIA A100-SXM4-80GB


### Who can help?

@sanchit-gandhi @muellerz 
the following is my TrainerArguments & Trainer：
```
training_args = TrainingArguments(
    output_dir="semi_structured_wav2vec2_model",
    per_device_train_batch_size=64,
    gradient_accumulation_steps=2,
    learning_rate=1e-5,
    warmup_steps=500,
    max_steps=2000,
    gradient_checkpointing=True,
    fp16=True,
    group_by_length=True,
    eval_strategy="steps",
    per_device_eval_batch_size=64,
    save_steps=1000,
    eval_steps=1000,
    dataloader_num_workers = 32,
    dataloader_pin_memory = True,
    dataloader_persistent_workers = True,
    dataloader_prefetch_factor = 2,
    logging_steps=25,
    load_best_model_at_end=True,
    metric_for_best_model="wer",
    greater_is_better=False,
    disable_tqdm=False,
    push_to_hub=False,
)

trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=encoded_train,
    eval_dataset=encoded_valid,
    tokenizer=processor,
    data_collator=data_collator,
    compute_metrics=compute_metrics,
)
```
I would like to give it a try of finetuning wav2vec2.0 model ("facebook/wav2vec2-base") with the dataset of LibriSpeech (I know there's the version which has been finetuned already, but I would like to know how to manipulate trainer.train()). Considering the enormous data of the librispeech dataset, I set the larger num_worker (32, there's 128 logical cpus in A100 server)to pre-load the data, but I have stuck at the trainer.train for more than 20 minutes, and there's no any logs showing up.
![image](https://github.com/user-attachments/assets/92d71599-ed93-4a6d-a6cf-2e78ae21ec65)
GPU isn't work at all, however, when I use the command of htop, I can see  that CPU is working for transfering data I thought(btw, there's on;y one user, me, in the server)
![image](https://github.com/user-attachments/assets/cf45ad3c-13e1-4c20-a0f0-eed3c6a10d69)
![image](https://github.com/user-attachments/assets/e2a97496-347b-4323-97aa-2ea3a3c52aa8)

what's wrong for trainer.train() or do I need to set the special arguments for distributed data parallel training?

### Information

- [X] The official example scripts
- [ ] My own modified scripts

### Tasks

- [X] An officially supported task in the `examples` folder (such as GLUE/SQuAD, ...)
- [ ] My own task or dataset (give details below)

### Reproduction

the links for colab
https://colab.research.google.com/drive/1n4JiRejsSdaPGPRPI2pFQCBXeaVLm4Ok?usp=sharing


### Expected behavior

1. trainer.train() works well
2. there's progress bar for trainer.train()

Comments:
Hey! This looks like potentially NCCL issues (communication). There are a few similar issues, but @muellerzr will know better

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.

#10477 or #26724 #28283 

This issue has been automatically marked as stale because it has not had recent activity. If you think this still needs to be addressed please comment on this thread.

Please note that issues that do not follow the [contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) are likely to be ignored.