NCA-GENM Exam Dumps | You are tasked with building a multimodal generative AI model to create marketing content from product

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Question 80/192

You are tasked with building a multimodal generative AI model to create marketing content from product images and descriptions. The image encoder uses a pre-trained ResNet50 model, and the text encoder uses a pre-trained BERT model. After initial training, the generated content frequently misinterprets the image. Which of the following strategies is MOST effective in improving the model's ability to correctly interpret the image within the multimodal context?

A. Freeze the weights of both the ResNet50 and BERT models to prevent overfitting.

B. Fine-tune the ResNet50 model with a dataset of images specifically related to the product domain, using a contrastive loss function that encourages representations of images and corresponding text to be close in the embedding space.

C. Increase the learning rate for the BERT model to prioritize text-based information.

D. Replace ResNet50 with a simpler image encoder like a shallow CNN to reduce computational complexity.

E. Decrease the batch size during training.

Question 80/192

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