A team is fine-tuning a large, powerful model to perform a specific task. Instead of using a dataset with pre-defined correct answers, they use a smaller, weaker model as a live supervisor. For each input, the large model generates an output, and the weaker model also generates an output. A loss value is then calculated based on the difference between these two outputs. What is the direct and immediate purpose of this calculated loss value within the training loop?
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Ch.4 Alignment - Foundations of Large Language Models
Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
Analysis in Bloom's Taxonomy
Cognitive Psychology
Psychology
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Combined Loss Objective in Weak-to-Strong Training
A team is fine-tuning a large, powerful model to perform a specific task. Instead of using a dataset with pre-defined correct answers, they use a smaller, weaker model as a live supervisor. For each input, the large model generates an output, and the weaker model also generates an output. A loss value is then calculated based on the difference between these two outputs. What is the direct and immediate purpose of this calculated loss value within the training loop?
Transferring a Specialized Skill