Fine Tuning Insights
Joseph challenges the conventional wisdom around model hallucinations, emphasizing the importance of aligning with specific domains to avoid generating incorrect outputs. He reflects on his initial skepticism towards fine tuning, ultimately recognizing its value in adapting models to particular vocabularies and contexts, which significantly enhances the quality of responses. Lukas adds to the discussion by questioning the varying intuitions surrounding fine tuning's effectiveness in machine learning tasks.In this clip
From this podcast
Gradient Dissent - A Machine Learning Podcast
Evaluating LLMs with Chatbot Arena and Joseph E. Gonzalez
Related Questions