Optimal Parameters Formula in Fine-Tuning
The optimal parameters, denoted as , obtained through fine-tuning are found by maximizing an objective function over the tuning dataset . This relationship is formally expressed as:
In this equation, represents the parameters being actively optimized, which are initialized from the pre-trained parameters , and calculates the objective value for a given sample.
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Foundations of Large Language Models
Ch.2 Generative Models - Foundations of Large Language Models
Foundations of Large Language Models Course
Computing Sciences
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Mathematical Formulation of the Supervised Fine-Tuning Objective
A machine learning engineer is performing supervised fine-tuning on a pre-trained language model. The process involves three distinct states for the model's parameters:
- The initial parameters loaded from the pre-trained model before any new training begins.
- The parameters as they are being iteratively updated by the optimization algorithm on the new dataset.
- The final, converged parameters after the fine-tuning process is complete.
Which option correctly maps the standard notation to these three states?
Notation for Predicted Output During Fine-Tuning
In the mathematical description of a model fine-tuning process, different symbols are used to represent the model's parameters at various stages. Match each symbol with its correct description.
Correcting Fine-Tuning Parameter Notation
Optimal Parameters Formula in Fine-Tuning