What is the purpose of the Teach Label training mode?

The Teach Label training mode is designed specifically to address instances where the model experiences uncertainty regarding the application of labels to certain data entries, referred to as verbatims. This mode allows users to review these ambiguous cases and provide the necessary labeling instructions, correcting the model's predictions. By focusing on the most uncertain examples, Teach Label essentially enhances the model's understanding and accuracy in labeling by incorporating human expertise where needed.

This targeted approach is crucial in improving the model's performance on complex or nuanced data points that may not fit neatly into predefined categories, allowing it to learn through corrective feedback.