MLS-C01 Question #235: Real Exam Question with Answer & Explanation

Question

A company is building an application that can predict spam email messages based on email text. The company can generate a few thousand human-labeled datasets that contain a list of email messages and a label of "spam" or "not spam" for each email message. A machine learning (ML) specialist wants to use transfer learning with a Bidirectional Encoder Representations from Transformers (BERT) model that is trained on English Wikipedia text data. What should the ML specialist do to initialize the model to fine-tune the model with the custom data?

Options

• AInitialize the model with pretrained weights in all layers except the last fully connected layer.
• BInitialize the model with pretrained weights in all layers. Stack a classifier on top of the first output
• CInitialize the model with random weights in all layers. Replace the last fully connected layer with a
• DInitialize the model with pretrained weights in all layers. Replace the last fully connected layer with