A machine learning team is developing a model to classify medical research abstracts into different fields of study. They use a large, pre-trained language model as a foundation. Their complete system is represented by the function $Classifier_{\tilde{\omega}}(Embedder_{\tilde{\theta}}(text))$, where $Embedder_{\tilde{\theta}}$ is the pre-trained model and $Classifier_{\tilde{\omega}}$ is a new component. During training on their specific dataset of abstracts, the team chooses to only update the parameters $\tilde{\omega}$ and keep the parameters $\tilde{\theta}$ fixed. Which statement best analyzes the rationale behind this training strategy?

Sentiment Analysis System Design

Component Roles in a Two-Stage Prediction Model