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Exam AWS Certified AI Practitioner AIF-C01 topic 1 question 79 discussion

Exam question from Amazon's AWS Certified AI Practitioner AIF-C01
Question #: 79
Topic #: 1
[All AWS Certified AI Practitioner AIF-C01 Questions]

A company has built a solution by using generative AI. The solution uses large language models (LLMs) to translate training manuals from English into other languages. The company wants to evaluate the accuracy of the solution by examining the text generated for the manuals.
Which model evaluation strategy meets these requirements?

  • A. Bilingual Evaluation Understudy (BLEU)
  • B. Root mean squared error (RMSE)
  • C. Recall-Oriented Understudy for Gisting Evaluation (ROUGE)
  • D. F1 score
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Suggested Answer: A 🗳️
by Amitst at Dec. 5, 2024, 9:05 a.m.
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Moon
3 weeks, 1 day ago
Selected Answer: A
A. Bilingual Evaluation Understudy (BLEU): This is the correct answer. BLEU is a common metric for evaluating machine translation quality. It compares the generated text to one or more reference translations and measures the n-gram overlap.
upvoted 1 times
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may2021_r
3 weeks, 4 days ago
Selected Answer: A
The correct answer is A. BLEU is specifically designed to evaluate machine translation quality.
upvoted 1 times
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Dandelion2025
1 month, 2 weeks ago
Selected Answer: A
BLEU is specifically designed to measure the quality of machine translations by comparing them to human-created reference translations
upvoted 2 times
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aws4myself
1 month, 2 weeks ago
Selected Answer: C
C. Recall-Oriented Understudy for Gisting Evaluation (ROUGE) ROUGE is a popular metric for evaluating the quality of text summarization and machine translation systems. It focuses on recall, measuring how well the generated text covers the relevant information from the reference text. In this case, ROUGE can be used to assess how accurately the LLM-generated translations capture the meaning and content of the original English manuals.
upvoted 1 times
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Amitst
1 month, 2 weeks ago
Selected Answer: A
BLEU (bilingual evaluation understudy) is an algorithm for evaluating the quality of text which has been machine-translated from one natural language to another.
upvoted 2 times
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