As described in Keras documentation, the verbose=1 asks the keras to print out results in a progress bar. But sometimes keras prints out the results of every batch, which makes a very messy printout report (see below). I wonder why is that? I mean, the only setup is the parameter of verbose, isn't it?
My code is simple:
history = model.fit(X_shuffle, y_scores_one_hot, validation_split=0.2, verbose = 1, epochs = 100, batch_size = 50)
Wrong printout:
Epoch 1/100 5750/8107 [====================>.........] - ETA: 5:03 - loss: 1.3690 - acc: 0.520 - ETA: 1:42 - loss: 1.3600 - acc: 0.533 - ETA: 1:02 - loss: 1.3994 - acc: 0.500 - ETA: 39s - loss: 1.4173 - acc: 0.482 - ETA: 29s - loss: 1.4189 - acc: 0.47 - ETA: 23s - loss: 1.4320 - acc: 0.46 - ETA: 19s - loss: 1.4432 - acc: 0.46 - ETA: 16s - loss: 1.4373 - acc: 0.46 - ETA: 14s - loss: 1.4318 - acc: 0.46 - ETA: 12s - loss: 1.4322 - acc: 0.46 - ETA: 11s - loss: 1.4314 - acc: 0.46 - ETA: 10s - loss: 1.4342 - acc: 0.46 - ETA: 10s - loss: 1.4386 - acc: 0.45 - ETA: 9s - loss: 1.4399 - acc: 0.4557 - ETA: 8s - loss: 1.4373 - acc: 0.458 - ETA: 7s - loss: 1.4418 - acc: 0.453 - ETA: 7s - loss: 1.4419 - acc: 0.454 - ETA: 6s - loss: 1.4435 - acc: 0.453 - ETA: 6s - loss: 1.4421 - acc: 0.453 - ETA: 6s - loss: 1.4439 - acc: 0.451 - ETA: 5s - loss: 1.4437 - acc: 0.452 - ETA: 5s - loss: 1.4388 - acc: 0.456 - ETA: 5s - loss: 1.4430 - acc: 0.453 - ETA: 4s - loss: 1.4440 - acc: 0.452 - ETA: 4s - loss: 1.4428 - acc: 0.452 - ETA: 4s - loss: 1.4469 - acc: 0.449 - ETA: 4s - loss: 1.4471 - acc: 0.450 - ETA: 3s - loss: 1.4517 - acc: 0.445 - ETA: 3s - loss: 1.4489
I expected something like:
Epoch 1/100 3009/3009 [==============================] - 30s 10ms/step - loss: 1.5875 - acc: 0.2795 - val_loss: 1.5542 - val_acc: 0.4130
Epoch 2/100 3009/3009 [==============================] - 27s 9ms/step - loss: 1.5049 - acc: 0.4403 - val_loss: 1.4963 - val_acc: 0.4130
