chunk_content:   labels = torch.tensor([example["label"] for example in examples])
      return {"pixel_values": pixel_values, "labels": labels}
  
  Train and evaluate
  	
  Bring everything together - model, training arguments, data, collation function, etc. Then, start the training!
  
  
  	Copied
  trainer = Trainer(
      lora_model,
      args,
      train_dataset=train_ds,
      eval_dataset=val_ds,
      tokenizer=image_processor,
      compute_metrics=compute_metrics,
      data_c