Fine-Tuning Generative Models Quiz

5 questions • Pass: 70% • +25 pts

Quiz covering Optimizing Generative AI

Fine-Tuning Generative Models Quiz

5 questions | Pass: 70% | Earn 25 points

Questions in this quiz

A preview of the 5 questions covered. Start the quiz above to answer them, check your score, and read the explanations.

  1. 1

    What is the primary goal of fine-tuning a pre-trained generative model?

  2. 2

    When fine-tuning a model, what is the main risk associated with using a dataset that is too small or lacks diversity?

  3. 3

    Which of the following describes the 'Parameter-Efficient Fine-Tuning' (PEFT) approach, such as LoRA?

  4. 4

    In the context of fine-tuning, what is 'Catastrophic Forgetting'?

  5. 5

    You are fine-tuning a model for a highly specific technical domain. Your training loss is decreasing, but your validation loss is increasing significantly. Which strategy is most effective to resolve this?