chunk_content: 
  -
  -
  0.68
  PEFT
  1.73
  64
  0.787
  Full Fine-Tuning
  2.33
  32
  0.7969
  The PEFT-LoRA model trains 1.35X faster and can fit 2X batch size compared to the fully fine-tuned model, and the performance of PEFT-LoRA is comparable to the fully fine-tuned model with a relative drop of -1.24% in ROC-AUC. This gap can probably be closed with bigger models as mentioned in The Power of Scale for Parameter-Efficient Prompt Tuning
  .
  
  Inference
  	
  Let’s go! Now we have 