It is important to realize that, when saving a model, the model that gets saved is the one that is built on the training data corresponding to that entry in the history list. If performing an evaluation where some of the data is held out as a separate test set (see below in Section 3.2) then the model saved has only been trained on part of the available data. It is a good idea to turn off hold-out evaluation and construct a model on all the available data before saving the model.