How do I choose the right learning rate for my model?

What factors should I consider when choosing a learning rate for my model?

You should consider the model architecture, the dataset size, and the optimization algorithm you're using.

Is there a general rule of thumb for setting the learning rate?

A common starting point is to use a learning rate of 0.01, but it often requires tuning based on your specific problem.

How can I tell if my learning rate is too high or too low?

If the learning rate is too high, the model may diverge or oscillate. If it's too low, training will be very slow and may get stuck.

What techniques can I use to find the best learning rate?

You can use techniques like learning rate scheduling, grid search, or the learning rate range test to find the optimal value.