Keras Learning Rate Finder - PyImageSearch

In this tutorial, you will learn how to automatically find learning rates using Keras. Last week we discussed Cyclical Learning Rates (CLRs) and how they can be used to obtain high accuracy models with fewer experiments and limited hyperparameter tuning. The CLR method allows our learning rate to cyclically oscillate between a lower and upper bound; however, the question still remains, how do we know what are good choices for our learning rates? Today I'll be answering that question. And by the time you have completed this tutorial, you will understand how to automatically find optimal learning rates for your neural network, saving you 10s, 100s or even 1000s of hours in compute time running experiments to tune your hyperparameters.