Change hyperparameters between epochs

I know about training functions with adaptive learning rates, but I need a fine control of the hyperparameters. From my experiments, it appears that all trainable parameters of a model is reset when calling 'train', but I could be doing this too simplistic. Is there a way of training for N epoch, modify the hyperparameters of the model and repeat until some end criterion decided by me?