903: LLM Benchmarks Are Lying to You (And What to Do Instead), with Sinan Ozdemir
Super Data Science: ML & AI Podcast with Jon Krohn
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Evaluating Language Models: Temperature and Benchmarks
This chapter explores how adjusting the 'temperature' setting in language models can significantly impact the variability of generated responses. It also critiques the reliability of traditional benchmarks in assessing machine learning models, particularly regarding their tendency to hallucinate. The chapter advocates for innovative evaluation methods, such as 'Chatbot Arena', that prioritize human judgment while addressing the challenges of benchmark contamination and assessment subjectivity.
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