What steps can be taken to fix dead neurons during training of a text generation model

Question

Can i know What steps can be taken to fix dead neurons during training of a text generation model?

Answer 1

Dead neurons in a text generation model can be mitigated by using proper weight initialization, lower learning rates, ReLU alternatives, and techniques like batch normalization and dropout adjustment.

Here is the code snippet you can refer to:

In the above code we are using the following key points:

• Uses LeakyReLU to avoid dead neurons by allowing small gradients for negative inputs.
• Adjusts dropout rate to prevent excessive neuron deactivation.
• Ensures proper weight updates with Adam optimizer and a reasonable learning rate.

Hence, dead neurons in a text generation model can be avoided by using alternative activation functions, tuning dropout, and careful optimization, ensuring better learning and performance.