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AIF-C01 Practice Question: Evaluating the performance of their…
A company is evaluating the performance of their question-answering model using Amazon Bedrock's model evaluation feature. They want to assess both the factual accuracy and the fluency of the generated answers. Which THREE metrics should they choose? (Select THREE.)
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
ROUGE
ROUGE measures overlap for summarization/QA; BERTScore measures semantic similarity; and human evaluation is the gold standard for fluency and factual accuracy. BLEU is for translation; exact match is too strict for open-ended QA.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
ROUGE
Why this is correct
ROUGE measures n-gram recall, useful for factual overlap in QA.
- ✗
BLEU
Why it's wrong here
BLEU is primarily for machine translation, not QA.
- ✓
BERTScore
Why this is correct
BERTScore captures semantic similarity between generated and reference answers.
- ✓
Human evaluation
Why this is correct
Human evaluation can assess factual accuracy, fluency, and overall quality.
- ✗
Exact match
Why it's wrong here
Exact match is too rigid for open-ended QA where multiple correct phrasings exist.
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Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AIF-C01 practice question is part of Courseiva's free Amazon Web Services certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AIF-C01 exam.