Trainer stuck mid epoch
Good evening.Trainer has a behavior I do not fully understand (I am a beginner) and it gets stuck for a lot of time after a fixed number of steps, and does not proceed in training.Here code and output at which it gets stuck.code snippet:training_args = TrainingArguments(
    output_dir=f"{'dataset.coco'.replace(' ', '-')}-finetune",
    num_train_epochs=20,
    max_grad_norm=0.1,
    learning_rate=5e-5,
    #warmup_steps=300,
    per_device_train_batch_size=1,
    #gradient_accumulation_steps=4,
    dataloader_num_workers=0,
    metric_for_best_model="eval_map",
    greater_is_better=True,
    load_best_model_at_end=True,
    eval_strategy="epoch",
    save_strategy="epoch",
    save_total_limit=2,
    remove_unused_columns=False,
    eval_do_concat_batches=False,
)

trainer = Trainer(
    model=model,
    args=training_args,
    train_dataset=pytorch_dataset_train,
    eval_dataset=pytorch_dataset_valid,
    tokenizer=processor,
    data_collator=collate_fn,
    compute_metrics=eval_compute_metrics_fn,
)

trainer.train()output:5%|▍         | 500/10320 [02:01<46:19,  3.53it/s]{‘loss’: 56.0595, ‘grad_norm’: 163.28176879882812, ‘learning_rate’: 4.757751937984497e-05, ‘epoch’: 0.97}5%|▌         | 516/10320 [02:06<45:03,  3.63it/s]0%|          | 0/19 [00:00<?, ?it/s]11%|█         | 2/19 [00:00<00:03,  4.37it/s]16%|█▌        | 3/19 [00:00<00:05,  3.12it/s]21%|██        | 4/19 [00:01<00:05,  2.73it/s]26%|██▋       | 5/19 [00:01<00:05,  2.53it/s]32%|███▏      | 6/19 [00:02<00:05,  2.41it/s]37%|███▋      | 7/19 [00:02<00:05,  2.35it/s]42%|████▏     | 8/19 [00:03<00:04,  2.32it/s]47%|████▋     | 9/19 [00:03<00:04,  2.29it/s]53%|█████▎    | 10/19 [00:04<00:03,  2.28it/s]58%|█████▊    | 11/19 [00:04<00:03,  2.27it/s]63%|██████▎   | 12/19 [00:04<00:03,  2.25it/s]68%|██████▊   | 13/19 [00:05<00:02,  2.24it/s]74%|███████▎  | 14/19 [00:05<00:02,  2.24it/s]79%|███████▉  | 15/19 [00:06<00:01,  2.24it/s]84%|████████▍ | 16/19 [00:06<00:01,  2.24it/s]89%|████████▉ | 17/19 [00:07<00:00,  2.23it/s]95%|█████████▍| 18/19 [00:07<00:00,  2.36it/s]100%|██████████| 19/19 [00:07<00:00,  2.89it/s]I thank you all in advance.