Description
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In this module, you will learn how to evaluate LLMs by exploring benchmark datasets like MMLU and HELM, which evaluate LLMs across various tasks. You will then explore how to assess LLM quality and performance using metrics like BLEU, ROUGE, and RAGAs. Through real-world tasks and hands-on exercises, you’ll apply these metrics to evaluate LLMs effectively.
What you'll learn
- Understand the importance of evaluating LLMs for ensuring reliability, safety, and alignment with business and ethical standards.
- Analyze the rationale and challenges in evaluating LLMs to ensure accuracy, fairness, and robustness.
- Identify key metrics and explore benchmark datasets to assess LLM performance across diverse tasks and domains.
- Apply evaluation techniques through practical exercises to gain hands-on experience in assessing LLMs.
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