chunk_content:  parameters of the randomly initialized classifier parameters too. This is NOT we want
  when fine-tuning the base model on our custom dataset. To ensure that the classifier parameters are also trained, we
  specify modules_to_save. This also ensures that these modules are serialized alongside the LoRA trainable parameters
  when using utilities like save_pretrained() and push_to_hub().
  In addition to specifying the target_modules within LoraConfig, 