chunk_content: model, datasets, data collator, tokenizer, and callback to the Seq2SeqTrainer. You can optionally set model.config.use_cache = False to silence any warnings. Once everything is ready, call train to start training!
  
  
  	Copied
  from transformers import Seq2SeqTrainer, TrainerCallback, Seq2SeqTrainingArguments, TrainerState, TrainerControl
  
  trainer = Seq2SeqTrainer(
      args=training_args,
      model=model,
      train_dataset=common_voice["train"],
    