chunk_content: ng/loading utilities.
  
  Results
  	
  The table below compares the training time, the batch size that could be fit in Colab, and the best ROC-AUC scores between a PEFT model and a fully fine-tuned model:
  Training Type
  Training time per epoch (Hrs)
  Batch Size that fits
  ROC-AUC score (higher is better)
  Pre-Trained e5-large-v2
  -
  -
  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 c