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Related Questions
- What are the key differences between perplexity and accuracy in evaluating LLM performance?
- How do perplexity and accuracy relate to each other in the context of LLMs?
- What are some common use cases where perplexity is a more suitable metric than accuracy?
- Can you explain how perplexity is calculated in LLMs, and what it represents?
- In what scenarios is accuracy a more reliable metric than perplexity for evaluating LLMs?
- How do perplexity and accuracy change as the model size and complexity increase in LLMs?
- What are some best practices for choosing between perplexity and accuracy as evaluation metrics for LLMs?
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