chunk_content: herefore, we should specify these names in the target_modules argument of LoraConfig.
  After we wrap our base model model with PeftModel along with the config, we get
  a new model where only the LoRA parameters are trainable (so-called “update matrices”) while the pre-trained parameters
  are kept frozen. These include the parameters of the randomly initialized classifier parameters too. This is NOT we want
  when fine-tuning the base model on our cu