chunk_content: inal model
  which is indeed the case here.
  You can also manually verify what modules are trainable in the lora_model.
  
  
  	Copied
  for name, param in lora_model.named_parameters():
      if param.requires_grad:
          print(name, param.shape)
  This confirms that only the LoRA parameters appended to the attention blocks and the decode_head parameters are trainable.
  
  Train the model
  	
  Start by defining your training hyperparameters in TrainingArguments