How do I tune GRU and LSTM models for better performance?

How do I tune GRU and LSTM models for better performance?

Tuning GRU and LSTM models involves adjusting hyperparameters like learning rate, batch size, and number of layers. What specific aspect are you interested in?

I'm particularly interested in the learning rate and batch size.

For learning rate, a common approach is to start with 0.001 and adjust based on performance. For batch size, try values like 32, 64, or 128. Have you tried using a learning rate scheduler?

No, I haven't. How does that work?

A learning rate scheduler adjusts the learning rate during training, often reducing it when the model's performance plateaus. This can help achieve better convergence.