I have model a neural network in Keras which attains a train set accuracy of 1 at epoch 1000 (on the used hyperparameters), yet the validation accuracy keeps fluctuating between 0.78 and 0.8.
I would like an Early Stopping command which monitors the validation accuracy but only starts after the 1000th epoch because, before the 1000th epoch, the validation accuracy keeps highly fluctuating. So my strategy is to maximize training set accuracy and then stop the learning as soon, as we encounter a high value for validation accuracy. (The theoretical best is 1.0 for training and 0.8 for validation)
Is such a callback function possible?