seti19.py

class EpochModelSaver(keras.callbacks.Callback):
    def on_epoch_end(self, epoch, logs={}):
        self.model.save('resnet50_finetune_full_seti_epoch_{}.h5'.format(epoch+1))

ms_epoch = EpochModelSaver()
csv_logger = keras.callbacks.CSVLogger('resnet50_finetune_full_seti_log.csv', append=True, separator=',')    

history3 = model.fit_generator(
  train_generator,
  steps_per_epoch=math.ceil(5600 / TRAIN_BATCH_SIZE),
  epochs=500,
  validation_data=val_generator,
  validation_steps=math.ceil(700 / VAL_BATCH_SIZE),
  callbacks=[ms_epoch, csv_logger], verbose=1,
)