NCA-GENM Question 161
Select 3You are tasked with improving the performance of a generative AI multimodal model that processes both text and images. During training, the model shows signs of overfitting, and its validation accuracy plateaus. Which steps should you take to optimize the model's performance?
- A
Reduce the learning rate to allow for finer adjustments during training.
- B
Increase the batch size to stabilize gradient updates.
- C
Apply dropout regularization to prevent overfitting.
- D
Use a larger dataset to provide the model with more diverse training samples.
- E
Increase the number of layers in the model to improve its capacity.
Show answer and explanation
Correct answers: A, C, D
Explanation
When optimizing a generative AI multimodal model, addressing overfitting and plateauing validation performance requires a combination of strategies. Reducing the learning rate can improve fine-tuning, dropout regularization can mitigate overfitting, and expanding the dataset enhances generalization. Simply increasing batch size or model complexity may not resolve overfitting and could worsen the issue without additional safeguards or data.
- A. Correct.
Reducing the learning rate can help fine-tune the model and prevent large oscillations during training, which can lead to better generalization.
- B. Incorrect.
Increasing the batch size alone may stabilize gradients but can also lead to less frequent updates, which might not address overfitting or improve validation performance.
- C. Correct.
Applying dropout is a common technique to prevent overfitting by randomly deactivating neurons during training, forcing the model to generalize better.
- D. Correct.
Using a larger dataset can help reduce overfitting by exposing the model to more diverse examples, improving its ability to generalize to unseen data.
- E. Incorrect.
While increasing the number of layers might improve the model's capacity, it can also exacerbate overfitting if the underlying issue is lack of regularization or insufficient data.