Model Analysis

This lecture delves into the analysis of neural models in natural language processing, exploring topics such as model evaluation, linguistic test subjects, probing neural networks, and ablation analysis. It covers the importance of understanding model behavior, the emergence of interpretable architecture components, and the layerwise trends in probing accuracy. The instructor discusses the significance of probing studies, correlation analyses, and the impact of attention heads in transformer models. The lecture concludes with insights on the complexity of neural models and the critical approach needed in model interpretation.