Fine-Tuned Model Evaluation Quiz

5 questions • Pass: 70% • +25 pts

Quiz covering Fine-Tuning Language Models

Fine-Tuned Model Evaluation 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

    Which of the following is the most effective way to evaluate a fine-tuned model's performance on a specific downstream task?

  2. 2

    You notice your model performs perfectly on the training data but produces poor results on new, unseen prompts. What is the most likely cause?

  3. 3

    When fine-tuning a model for a classification task, why is accuracy alone often an insufficient metric?

  4. 4

    If you fine-tune a model to follow instructions but find that it starts to lose its ability to perform general tasks (like basic summarization), what is this phenomenon called?

  5. 5

    You are evaluating a fine-tuned LLM using a reference-based metric like ROUGE or BLEU. What is a major limitation of these metrics for creative writing tasks?