Set batch instead of full train dataset on Trainer

trainer = Trainer(
    model=model,
    data_collator=data_collator,
    args=training_args,
    compute_metrics=compute_metrics,
    train_dataset=common_voice_train,
    eval_dataset=common_voice_test,
    tokenizer=processor.feature_extractor,
)

I would like to set batch in train_dataset, instead of the full set, because at the beginning take so much time to preprocess and load all the dataset when it could be done per batch inside the Train fuction, any help on how to do it?, also the same for the

 for param in model.base_model.parameters():
    param.requires_grad = False

I would like to set to true after n number of steps, but I cant figure out how to trigger that action from the Trainer

Did you find out how to load the data batch by batch?