What are the common mistakes in setting the learning rate?

What are the common mistakes in setting the learning rate?

Common mistakes include setting the learning rate too high, which can cause divergence, or too low, leading to slow convergence.

How do I know if my learning rate is too high?

If your loss function fluctuates wildly or increases instead of decreasing, your learning rate might be too high.

What is a good starting point for the learning rate?

A common starting point is 0.01, but it can vary based on the model and dataset. Experimentation is key.

Can I use learning rate schedules to improve training?

Yes, learning rate schedules can help adjust the learning rate during training, improving convergence and performance.

What tools can I use to visualize the learning rate effect?

You can use tools like TensorBoard or Matplotlib to visualize loss curves and see the effects of different learning rates.