What are the best practices for setting a learning rate in machine learning?

What are the best practices for setting a learning rate in machine learning?

Setting a learning rate is crucial for training models effectively. Best practices include starting with a small value, using learning rate schedules, and experimenting with different rates.

What is a learning rate schedule?

A learning rate schedule adjusts the learning rate during training. Common types include step decay, exponential decay, and cyclical learning rates.

How do I know 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 slow and may get stuck in local minima.

Can you recommend any tools to help with tuning the learning rate?

Yes! Tools like Optuna, Ray Tune, and Keras Tuner can help automate the process of hyperparameter tuning, including learning rates.