You are optimizing a generative AI model's performance by tuning hyperparameters. Which of the following strategies is most likely to improve the model's training efficiency without compromising its ability to generalize?
A.
Reducing the Batch Size
B.
Increasing the Learning Rate Significantly
C.
Using a Lower Precision for Computation
D.
Applying Regularization Techniques
Correct Answer: D
Explanation:
Applying regularization techniques like L2 regularization or dropout helps prevent overfitting, improving
the model's generalization ability while maintaining training efficiency.