Navigating Model Evaluation
Caterina highlights the complexity of evaluating machine learning models through various leaderboards, noting discrepancies in evaluation criteria that can obscure understanding. She emphasizes the importance of considering both immediate and long-term perspectives when selecting models, advocating for a standardized approach to measurement. Ultimately, this could lead to framing challenges as prediction problems, opening up new avenues for exploration in the field.In this clip
From this podcast
Super Data Science: ML & AI Podcast with Jon Krohn
706: Large Language Model Leaderboards and Benchmarks — with Caterina Constantinescu
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