[disearchai]

Evaluating large language models (LLMs) presents challenges due to the complexity and diversity of evaluation metrics. Metrics like accuracy, F1 score, and perplexity may not fully capture an LLM’s performance across various tasks. Methodologies must adapt to the context and goals of the application, requiring a nuanced approach to evaluation metrics for LLMs.

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