chunk_content: {id2label[i]}": v for i, v in enumerate(per_category_accuracy)})
          metrics.update({f"iou_{id2label[i]}": v for i, v in enumerate(per_category_iou)})
  
          return metrics
  
  Load a base model 
  	
  Before loading a base model, let’s define a helper function to check the total number of parameters a model has, as well
  as how many of them are trainable.
  
  
  	Copied
  def print_trainable_parameters(model):
      """
      Prints the number of trainable