How does learning rate affect training?

What is the learning rate in machine learning?

The learning rate is a hyperparameter that controls how much to change the model in response to the estimated error each time the model weights are updated.

How does a high learning rate affect training?

A high learning rate can lead to faster convergence, but it may also cause the model to overshoot the optimal solution, resulting in instability.

What about a low learning rate?

A low learning rate ensures more precise updates, but it can make the training process very slow and may get stuck in local minima.

How do I choose the right learning rate?

You can start with common values like 0.01 or 0.001 and use techniques like learning rate schedules or grid search to find the best one.