What steps would you take to resolve generator instability in a GAN for text generation tasks

Question

With the help of code snippets, can you tell me What steps you would take to resolve generator instability in a GAN for text generation tasks?

Answer 1

To address generator instability, use techniques like pre-training, gradient clipping, and scheduled updates for balanced training dynamics in text-based GANs. You can follow the following steps:

In the above code, we are using:

• Pre-training: Start with a pre-trained model to provide a stable baseline for the generator.
• Gradient Clipping: Limits gradient magnitudes to stabilize updates during training.
• Scheduled Updates: Train the generator intermittently to allow the discriminator to improve concurrently.

Hence, by referring to above, you can resolve generator instability in a GAN for text generation tasks