Surpassing the Supervisor
A large, sophisticated language model is fine-tuned using labels generated by a much smaller, less accurate model. Despite the 'teacher' model's known flaws, the larger 'student' model achieves a final performance on the task that is significantly better than the teacher's. Explain the mechanism that allows the student model to surpass its flawed supervisor.
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Computing Sciences
Foundations of Large Language Models Course
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
Social Science
Empirical Science
Science
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A research team fine-tunes a very capable, state-of-the-art model using labels generated by a much older, less powerful model. The team's goal is for the capable model to learn the underlying task better than its less powerful supervisor. However, after training, the capable model's performance on a standard evaluation set is worse than before the fine-tuning. What is the most likely reason for this failure?
Predicting Outcomes of Cross-Model Supervision
Surpassing the Supervisor