Early Stopping with Keras
Steps to train a model There are a number of things you have to do when working on a Machine Learning problem. Import your data and transform it as appropriate Define your model using something like Keras - this includes your chosen hyperparameter values Run the training phase Evaluate the model If at the end of this process the evaluation shows that your model is not sufficient for your needs you will need to make some changes and rerun the training. Ideally you should have a way to spot that training is not going as you want and stop it. This is one of the uses of early stopping. The other is if your model has reached a sufficient quality standard for you to use and further improvements have slowed, stopped altogether or an unnecessary. Early Stopping Keras provides a way of doing this using the EarlyStopping callback . There are a range of callbacks in Keras and you can define your own. Details are here . The EarlyStopping callback works by choosing a metric