How can I optimize my model architecture for better performance?

How can I optimize my model architecture for better performance?

To optimize your model architecture, consider techniques like pruning, quantization, and using more efficient layers.

What is pruning and how does it help?

Pruning involves removing less important weights from your model, which can reduce its size and improve inference speed.

Are there specific architectures that are better for certain tasks?

Yes, architectures like CNNs are great for image tasks, while RNNs or Transformers excel in sequential data tasks.

How can I evaluate the performance of my optimized model?

You can evaluate performance using metrics like accuracy, F1 score, or inference time on a validation dataset.