If you like, you can create a smaller subset of the full dataset to fine-tune on to reduce the time it takes:

small_train_dataset = tokenized_datasets["train"].shuffle(seed=42).select(range(1000))
small_eval_dataset = tokenized_datasets["test"].shuffle(seed=42).select(range(1000))