train_model.py

BATCH_SIZE = 64

my_checkpointer = [
                EarlyStopping(monitor='val_loss', patience=5, verbose=0),
                ModelCheckpoint(filepath="License_character_recognition.h5", verbose=1, save_weights_only=True)
                ]

result = model.fit(image_gen.flow(trainX, trainY, batch_size=BATCH_SIZE), 
                   steps_per_epoch=len(trainX) // BATCH_SIZE, 
                   validation_data=(testX, testY), 
                   validation_steps=len(testX) // BATCH_SIZE, 
                   epochs=EPOCHS, callbacks=my_checkpointer)