Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 96 discussion

C: F1 score Explanation: The F1 score is a balanced metric that combines precision and recall to evaluate the accuracy of a model, particularly in scenarios like question-answering, where both correctness (precision) and completeness (recall) matter. The F1 score is particularly useful when there is an uneven distribution of classes or when the model's ability to retrieve relevant and accurate answers is being assessed.

The correct answer is C. F1 score combines precision and recall, making it ideal for question-answering evaluation.

The F1 score provides a balanced evaluation of the model's ability to give both relevant and accurate answers, making it the most suitable metric for assessing the fine-tuned model’s performance in answering help desk questions.

F1 score is a metric that combines precision and recall to evaluate the balance between correctly identified outputs and missed or irrelevant outputs. It is particularly useful for tasks like question answering, where both accuracy and completeness are critical. In this help desk scenario, the F1 score helps assess whether the model consistently provides correct and relevant answers to user queries, reflecting the effectiveness of fine-tuning.