chunk_content: iner.evaluate(val_ds)
  {
      "eval_loss": 0.14475855231285095,
      "eval_accuracy": 0.96,
      "eval_runtime": 3.5725,
      "eval_samples_per_second": 139.958,
      "eval_steps_per_second": 1.12,
      "epoch": 5.0,
  }
  
  Share your model and run inference
  	
  Once the fine-tuning is done, share the LoRA parameters with the community like so:
  
  
  	Copied
  repo_name = f"sayakpaul/{model_name}-finetuned-lora-food101"
  lora_model.push_to_hub(repo_name)
  When call