chunk_content:  indeed the case here.
  
  Define training arguments
  	
  For model fine-tuning, use Trainer. It accepts
  several arguments which you can wrap using TrainingArguments.
  
  
  	Copied
  from transformers import TrainingArguments, Trainer
  
  
  model_name = model_checkpoint.split("/")[-1]
  batch_size = 128
  
  args = TrainingArguments(
      f"{model_name}-finetuned-lora-food101",
      remove_unused_columns=False,
      evaluation_strategy="epoch",
      save_strategy="epoch