How can I fix issues related to model overfitting when training on small generative datasets

Question

With the help of Python programming, can you explain How I can fix issues related to model overfitting when training on small generative datasets?

Answer 1

To fix overfitting on small generative datasets, you can use techniques like data augmentation, regularization, and early stopping. 

Here is the code reference using tensorflow:

Hence, this approach combines data augmentation, dropout, L2 regularization, and early stopping to reduce overfitting.