In [1]:from sklearn import datasets from sklearn import model_selection import tensorflow as tf import numpy as np import matplotlib.pyplot as plt %matplotlib inline iris = datasets.load_iris() X_train, X_test, y_train, y_test = model_selection.train_test_split( iris.data, iris.target, test_size=0.2, random_state=0) In [2]:model = tf.keras.models.Sequential([ tf.keras.layers.Dense(4, activation=tf.nn.relu), tf.keras.layers.Dense(3, activation=tf.nn.softmax) ]) In [3]:model.compile(optimizer="adam", loss="sparse_categorical_crossentropy", metrics=["accuracy"]) In [4]:model.fit(X_train, y_train, epochs=500) Epoch 1/500 120/120 [==============================] - 0s 1ms/step - loss: 4.1307 - acc: 0.3250 Epoch 2/500 120/120 [==============================] - 0s 49us/step - loss: 3.9718 - acc: 0.3250 Epoch 3/500 120/120 [==============================] - 0s 35us/step - loss: 3.8201 - acc: 0.3250 Epoch 4/500 120/120 [==============================] - 0s 44us/step - loss: 3.6876 - acc: 0.3333 Epoch 5/500 120/120 [==============================] - 0s 52us/step - loss: 3.5703 - acc: 0.3750 Epoch 6/500 120/120 [==============================] - 0s 31us/step - loss: 3.4718 - acc: 0.4750 Epoch 7/500 120/120 [==============================] - 0s 83us/step - loss: 3.3818 - acc: 0.6083 Epoch 8/500 120/120 [==============================] - 0s 32us/step - loss: 3.3135 - acc: 0.6750 Epoch 9/500 120/120 [==============================] - 0s 46us/step - loss: 3.2513 - acc: 0.6917 Epoch 10/500 120/120 [==============================] - 0s 41us/step - loss: 3.1975 - acc: 0.6917 Epoch 11/500 120/120 [==============================] - 0s 31us/step - loss: 3.1476 - acc: 0.6917 Epoch 12/500 120/120 [==============================] - 0s 28us/step - loss: 3.0975 - acc: 0.6917 Epoch 13/500 120/120 [==============================] - 0s 51us/step - loss: 3.0513 - acc: 0.6917 Epoch 14/500 120/120 [==============================] - 0s 42us/step - loss: 3.0033 - acc: 0.6917 Epoch 15/500 120/120 [==============================] - 0s 33us/step - loss: 2.9564 - acc: 0.6917 Epoch 16/500 120/120 [==============================] - 0s 68us/step - loss: 2.9112 - acc: 0.6917 Epoch 17/500 120/120 [==============================] - 0s 33us/step - loss: 2.8622 - acc: 0.6917 Epoch 18/500 120/120 [==============================] - 0s 29us/step - loss: 2.8142 - acc: 0.6917 Epoch 19/500 120/120 [==============================] - 0s 30us/step - loss: 2.7693 - acc: 0.6917 Epoch 20/500 120/120 [==============================] - 0s 63us/step - loss: 2.7225 - acc: 0.6917 Epoch 21/500 120/120 [==============================] - 0s 33us/step - loss: 2.6774 - acc: 0.6917 Epoch 22/500 120/120 [==============================] - 0s 35us/step - loss: 2.6304 - acc: 0.6917 Epoch 23/500 120/120 [==============================] - 0s 34us/step - loss: 2.5843 - acc: 0.6917 Epoch 24/500 120/120 [==============================] - 0s 45us/step - loss: 2.5364 - acc: 0.6917 Epoch 25/500 120/120 [==============================] - 0s 40us/step - loss: 2.4944 - acc: 0.6917 Epoch 26/500 120/120 [==============================] - 0s 33us/step - loss: 2.4512 - acc: 0.6917 Epoch 27/500 120/120 [==============================] - 0s 55us/step - loss: 2.4046 - acc: 0.6917 Epoch 28/500 120/120 [==============================] - 0s 35us/step - loss: 2.3645 - acc: 0.6917 Epoch 29/500 120/120 [==============================] - 0s 32us/step - loss: 2.3188 - acc: 0.6917 Epoch 30/500 120/120 [==============================] - 0s 51us/step - loss: 2.2744 - acc: 0.6917 Epoch 31/500 120/120 [==============================] - 0s 47us/step - loss: 2.2322 - acc: 0.6917 Epoch 32/500 120/120 [==============================] - 0s 37us/step - loss: 2.1908 - acc: 0.6917 Epoch 33/500 120/120 [==============================] - 0s 54us/step - loss: 2.1490 - acc: 0.6917 Epoch 34/500 120/120 [==============================] - 0s 40us/step - loss: 2.1072 - acc: 0.6917 Epoch 35/500 120/120 [==============================] - 0s 30us/step - loss: 2.0658 - acc: 0.6917 Epoch 36/500 120/120 [==============================] - 0s 35us/step - loss: 2.0288 - acc: 0.6917 Epoch 37/500 120/120 [==============================] - 0s 38us/step - loss: 1.9865 - acc: 0.6917 Epoch 38/500 120/120 [==============================] - 0s 44us/step - loss: 1.9470 - acc: 0.6917 Epoch 39/500 120/120 [==============================] - 0s 35us/step - loss: 1.9091 - acc: 0.6917 Epoch 40/500 120/120 [==============================] - 0s 36us/step - loss: 1.8710 - acc: 0.6917 Epoch 41/500 120/120 [==============================] - 0s 41us/step - loss: 1.8301 - acc: 0.6917 Epoch 42/500 120/120 [==============================] - 0s 38us/step - loss: 1.7926 - acc: 0.6917 Epoch 43/500 120/120 [==============================] - 0s 38us/step - loss: 1.7552 - acc: 0.6917 Epoch 44/500 120/120 [==============================] - 0s 39us/step - loss: 1.7169 - acc: 0.6917 Epoch 45/500 120/120 [==============================] - 0s 50us/step - loss: 1.6808 - acc: 0.6917 Epoch 46/500 120/120 [==============================] - 0s 45us/step - loss: 1.6453 - acc: 0.6917 Epoch 47/500 120/120 [==============================] - 0s 37us/step - loss: 1.6085 - acc: 0.6917 Epoch 48/500 120/120 [==============================] - 0s 40us/step - loss: 1.5743 - acc: 0.6917 Epoch 49/500 120/120 [==============================] - 0s 38us/step - loss: 1.5393 - acc: 0.6917 Epoch 50/500 120/120 [==============================] - 0s 37us/step - loss: 1.5049 - acc: 0.6917 Epoch 51/500 120/120 [==============================] - 0s 32us/step - loss: 1.4667 - acc: 0.6917 Epoch 52/500 120/120 [==============================] - 0s 51us/step - loss: 1.4360 - acc: 0.6917 Epoch 53/500 120/120 [==============================] - 0s 39us/step - loss: 1.4024 - acc: 0.6917 Epoch 54/500 120/120 [==============================] - 0s 33us/step - loss: 1.3697 - acc: 0.6917 Epoch 55/500 120/120 [==============================] - 0s 33us/step - loss: 1.3381 - acc: 0.6917 Epoch 56/500 120/120 [==============================] - 0s 40us/step - loss: 1.3067 - acc: 0.6917 Epoch 57/500 120/120 [==============================] - 0s 50us/step - loss: 1.2730 - acc: 0.6917 Epoch 58/500 120/120 [==============================] - 0s 33us/step - loss: 1.2441 - acc: 0.6917 Epoch 59/500 120/120 [==============================] - 0s 35us/step - loss: 1.2142 - acc: 0.6917 Epoch 60/500 120/120 [==============================] - 0s 37us/step - loss: 1.1853 - acc: 0.6917 Epoch 61/500 120/120 [==============================] - 0s 66us/step - loss: 1.1555 - acc: 0.6917 Epoch 62/500 120/120 [==============================] - 0s 35us/step - loss: 1.1288 - acc: 0.6917 Epoch 63/500 120/120 [==============================] - 0s 32us/step - loss: 1.1003 - acc: 0.6917 Epoch 64/500 120/120 [==============================] - 0s 31us/step - loss: 1.0739 - acc: 0.6917 Epoch 65/500 120/120 [==============================] - 0s 29us/step - loss: 1.0466 - acc: 0.6917 Epoch 66/500 120/120 [==============================] - 0s 73us/step - loss: 1.0232 - acc: 0.6917 Epoch 67/500 120/120 [==============================] - 0s 33us/step - loss: 0.9980 - acc: 0.6917 Epoch 68/500 120/120 [==============================] - 0s 34us/step - loss: 0.9732 - acc: 0.6917 Epoch 69/500 120/120 [==============================] - 0s 31us/step - loss: 0.9497 - acc: 0.6917 Epoch 70/500 120/120 [==============================] - 0s 30us/step - loss: 0.9276 - acc: 0.6917 Epoch 71/500 120/120 [==============================] - 0s 30us/step - loss: 0.9055 - acc: 0.6917 Epoch 72/500 120/120 [==============================] - 0s 31us/step - loss: 0.8852 - acc: 0.6917 Epoch 73/500 120/120 [==============================] - 0s 54us/step - loss: 0.8651 - acc: 0.6917 Epoch 74/500 120/120 [==============================] - 0s 282us/step - loss: 0.8441 - acc: 0.6917 Epoch 75/500 120/120 [==============================] - 0s 41us/step - loss: 0.8263 - acc: 0.6917 Epoch 76/500 120/120 [==============================] - 0s 42us/step - loss: 0.8097 - acc: 0.6917 Epoch 77/500 120/120 [==============================] - 0s 42us/step - loss: 0.7928 - acc: 0.6917 Epoch 78/500 120/120 [==============================] - 0s 44us/step - loss: 0.7765 - acc: 0.6917 Epoch 79/500 120/120 [==============================] - 0s 46us/step - loss: 0.7618 - acc: 0.6917 Epoch 80/500 120/120 [==============================] - 0s 50us/step - loss: 0.7465 - acc: 0.6917 Epoch 81/500 120/120 [==============================] - 0s 42us/step - loss: 0.7343 - acc: 0.6917 Epoch 82/500 120/120 [==============================] - 0s 28us/step - loss: 0.7211 - acc: 0.6917 Epoch 83/500 120/120 [==============================] - 0s 33us/step - loss: 0.7111 - acc: 0.6917 Epoch 84/500 120/120 [==============================] - 0s 32us/step - loss: 0.6992 - acc: 0.6917 Epoch 85/500 120/120 [==============================] - 0s 48us/step - loss: 0.6883 - acc: 0.6917 Epoch 86/500 120/120 [==============================] - 0s 39us/step - loss: 0.6800 - acc: 0.6917 Epoch 87/500 120/120 [==============================] - 0s 37us/step - loss: 0.6713 - acc: 0.6917 Epoch 88/500 120/120 [==============================] - 0s 36us/step - loss: 0.6620 - acc: 0.6917 Epoch 89/500 120/120 [==============================] - 0s 34us/step - loss: 0.6542 - acc: 0.6917 Epoch 90/500 120/120 [==============================] - 0s 39us/step - loss: 0.6482 - acc: 0.6917 Epoch 91/500 120/120 [==============================] - 0s 31us/step - loss: 0.6417 - acc: 0.7000 Epoch 92/500 120/120 [==============================] - 0s 28us/step - loss: 0.6358 - acc: 0.7000 Epoch 93/500 120/120 [==============================] - 0s 33us/step - loss: 0.6294 - acc: 0.7000 Epoch 94/500 120/120 [==============================] - 0s 43us/step - loss: 0.6238 - acc: 0.7000 Epoch 95/500 120/120 [==============================] - 0s 42us/step - loss: 0.6193 - acc: 0.7083 Epoch 96/500 120/120 [==============================] - 0s 42us/step - loss: 0.6151 - acc: 0.7167 Epoch 97/500 120/120 [==============================] - 0s 33us/step - loss: 0.6101 - acc: 0.7167 Epoch 98/500 120/120 [==============================] - 0s 34us/step - loss: 0.6060 - acc: 0.7250 Epoch 99/500 120/120 [==============================] - 0s 36us/step - loss: 0.6022 - acc: 0.7333 Epoch 100/500 120/120 [==============================] - 0s 34us/step - loss: 0.5985 - acc: 0.7333 Epoch 101/500 120/120 [==============================] - 0s 32us/step - loss: 0.5946 - acc: 0.7333 Epoch 102/500 120/120 [==============================] - 0s 42us/step - loss: 0.5912 - acc: 0.7333 Epoch 103/500 120/120 [==============================] - 0s 35us/step - loss: 0.5876 - acc: 0.7500 Epoch 104/500 120/120 [==============================] - 0s 33us/step - loss: 0.5846 - acc: 0.7667 Epoch 105/500 120/120 [==============================] - 0s 37us/step - loss: 0.5812 - acc: 0.7750 Epoch 106/500 120/120 [==============================] - 0s 30us/step - loss: 0.5780 - acc: 0.7750 Epoch 107/500 120/120 [==============================] - 0s 31us/step - loss: 0.5750 - acc: 0.7833 Epoch 108/500 120/120 [==============================] - 0s 34us/step - loss: 0.5720 - acc: 0.8000 Epoch 109/500 120/120 [==============================] - 0s 32us/step - loss: 0.5693 - acc: 0.8000 Epoch 110/500 120/120 [==============================] - 0s 32us/step - loss: 0.5662 - acc: 0.8000 Epoch 111/500 120/120 [==============================] - 0s 30us/step - loss: 0.5635 - acc: 0.8083 Epoch 112/500 120/120 [==============================] - 0s 33us/step - loss: 0.5605 - acc: 0.8083 Epoch 113/500 120/120 [==============================] - 0s 68us/step - loss: 0.5578 - acc: 0.8083 Epoch 114/500 120/120 [==============================] - 0s 61us/step - loss: 0.5551 - acc: 0.8167 Epoch 115/500 120/120 [==============================] - 0s 36us/step - loss: 0.5524 - acc: 0.8167 Epoch 116/500 120/120 [==============================] - 0s 58us/step - loss: 0.5496 - acc: 0.8167 Epoch 117/500 120/120 [==============================] - 0s 46us/step - loss: 0.5471 - acc: 0.8167 Epoch 118/500 120/120 [==============================] - 0s 35us/step - loss: 0.5443 - acc: 0.8167 Epoch 119/500 120/120 [==============================] - 0s 32us/step - loss: 0.5417 - acc: 0.8167 Epoch 120/500 120/120 [==============================] - 0s 51us/step - loss: 0.5394 - acc: 0.8333 Epoch 121/500 120/120 [==============================] - 0s 34us/step - loss: 0.5366 - acc: 0.8333 Epoch 122/500 120/120 [==============================] - 0s 55us/step - loss: 0.5341 - acc: 0.8333 Epoch 123/500 120/120 [==============================] - 0s 49us/step - loss: 0.5316 - acc: 0.8333 Epoch 124/500 120/120 [==============================] - 0s 46us/step - loss: 0.5292 - acc: 0.8333 Epoch 125/500 120/120 [==============================] - 0s 34us/step - loss: 0.5266 - acc: 0.8333 Epoch 126/500 120/120 [==============================] - 0s 40us/step - loss: 0.5242 - acc: 0.8333 Epoch 127/500 120/120 [==============================] - 0s 47us/step - loss: 0.5218 - acc: 0.8417 Epoch 128/500 120/120 [==============================] - 0s 34us/step - loss: 0.5194 - acc: 0.8500 Epoch 129/500 120/120 [==============================] - 0s 31us/step - loss: 0.5170 - acc: 0.8500 Epoch 130/500 120/120 [==============================] - 0s 46us/step - loss: 0.5147 - acc: 0.8500 Epoch 131/500 120/120 [==============================] - 0s 43us/step - loss: 0.5124 - acc: 0.8500 Epoch 132/500 120/120 [==============================] - 0s 40us/step - loss: 0.5100 - acc: 0.8500 Epoch 133/500 120/120 [==============================] - 0s 43us/step - loss: 0.5078 - acc: 0.8500 Epoch 134/500 120/120 [==============================] - 0s 33us/step - loss: 0.5057 - acc: 0.8500 Epoch 135/500 120/120 [==============================] - 0s 51us/step - loss: 0.5033 - acc: 0.8583 Epoch 136/500 120/120 [==============================] - 0s 41us/step - loss: 0.5011 - acc: 0.8583 Epoch 137/500 120/120 [==============================] - 0s 40us/step - loss: 0.4990 - acc: 0.8583 Epoch 138/500 120/120 [==============================] - 0s 45us/step - loss: 0.4967 - acc: 0.8583 Epoch 139/500 120/120 [==============================] - 0s 40us/step - loss: 0.4946 - acc: 0.8583 Epoch 140/500 120/120 [==============================] - 0s 31us/step - loss: 0.4925 - acc: 0.8667 Epoch 141/500 120/120 [==============================] - 0s 39us/step - loss: 0.4904 - acc: 0.8750 Epoch 142/500 120/120 [==============================] - 0s 45us/step - loss: 0.4882 - acc: 0.8833 Epoch 143/500 120/120 [==============================] - 0s 31us/step - loss: 0.4862 - acc: 0.8833 Epoch 144/500 120/120 [==============================] - 0s 34us/step - loss: 0.4840 - acc: 0.8833 Epoch 145/500 120/120 [==============================] - 0s 37us/step - loss: 0.4821 - acc: 0.8833 Epoch 146/500 120/120 [==============================] - 0s 31us/step - loss: 0.4801 - acc: 0.8833 Epoch 147/500 120/120 [==============================] - 0s 40us/step - loss: 0.4780 - acc: 0.8833 Epoch 148/500 120/120 [==============================] - 0s 48us/step - loss: 0.4760 - acc: 0.8833 Epoch 149/500 120/120 [==============================] - 0s 44us/step - loss: 0.4741 - acc: 0.8833 Epoch 150/500 120/120 [==============================] - 0s 38us/step - loss: 0.4722 - acc: 0.8833 Epoch 151/500 120/120 [==============================] - ETA: 0s - loss: 0.4303 - acc: 0.906 - 0s 46us/step - loss: 0.4702 - acc: 0.8917 Epoch 152/500 120/120 [==============================] - 0s 48us/step - loss: 0.4683 - acc: 0.8917 Epoch 153/500 120/120 [==============================] - 0s 52us/step - loss: 0.4664 - acc: 0.8917 Epoch 154/500 120/120 [==============================] - 0s 33us/step - loss: 0.4645 - acc: 0.8917 Epoch 155/500 120/120 [==============================] - 0s 52us/step - loss: 0.4628 - acc: 0.8917 Epoch 156/500 120/120 [==============================] - 0s 57us/step - loss: 0.4609 - acc: 0.8917 Epoch 157/500 120/120 [==============================] - 0s 73us/step - loss: 0.4590 - acc: 0.8917 Epoch 158/500 120/120 [==============================] - 0s 38us/step - loss: 0.4573 - acc: 0.8917 Epoch 159/500 120/120 [==============================] - 0s 38us/step - loss: 0.4555 - acc: 0.8917 Epoch 160/500 120/120 [==============================] - 0s 49us/step - loss: 0.4536 - acc: 0.8917 Epoch 161/500 120/120 [==============================] - 0s 37us/step - loss: 0.4518 - acc: 0.9000 Epoch 162/500 120/120 [==============================] - 0s 40us/step - loss: 0.4501 - acc: 0.9083 Epoch 163/500 120/120 [==============================] - 0s 46us/step - loss: 0.4484 - acc: 0.9083 Epoch 164/500 120/120 [==============================] - 0s 32us/step - loss: 0.4468 - acc: 0.9167 Epoch 165/500 120/120 [==============================] - 0s 30us/step - loss: 0.4451 - acc: 0.9167 Epoch 166/500 120/120 [==============================] - 0s 52us/step - loss: 0.4433 - acc: 0.9167 Epoch 167/500 120/120 [==============================] - 0s 38us/step - loss: 0.4416 - acc: 0.9167 Epoch 168/500 120/120 [==============================] - 0s 31us/step - loss: 0.4400 - acc: 0.9167 Epoch 169/500 120/120 [==============================] - ETA: 0s - loss: 0.4398 - acc: 0.937 - 0s 63us/step - loss: 0.4383 - acc: 0.9167 Epoch 170/500 120/120 [==============================] - 0s 45us/step - loss: 0.4368 - acc: 0.9167 Epoch 171/500 120/120 [==============================] - 0s 52us/step - loss: 0.4351 - acc: 0.9167 Epoch 172/500 120/120 [==============================] - 0s 44us/step - loss: 0.4335 - acc: 0.9167 Epoch 173/500 120/120 [==============================] - 0s 36us/step - loss: 0.4319 - acc: 0.9167 Epoch 174/500 120/120 [==============================] - 0s 44us/step - loss: 0.4304 - acc: 0.9167 Epoch 175/500 120/120 [==============================] - 0s 46us/step - loss: 0.4288 - acc: 0.9167 Epoch 176/500 120/120 [==============================] - 0s 46us/step - loss: 0.4272 - acc: 0.9167 Epoch 177/500 120/120 [==============================] - 0s 52us/step - loss: 0.4256 - acc: 0.9167 Epoch 178/500 120/120 [==============================] - 0s 41us/step - loss: 0.4242 - acc: 0.9167 Epoch 179/500 120/120 [==============================] - 0s 47us/step - loss: 0.4227 - acc: 0.9167 Epoch 180/500 120/120 [==============================] - 0s 48us/step - loss: 0.4211 - acc: 0.9250 Epoch 181/500 120/120 [==============================] - ETA: 0s - loss: 0.4199 - acc: 0.875 - 0s 39us/step - loss: 0.4196 - acc: 0.9250 Epoch 182/500 120/120 [==============================] - 0s 55us/step - loss: 0.4182 - acc: 0.9250 Epoch 183/500 120/120 [==============================] - 0s 35us/step - loss: 0.4168 - acc: 0.9333 Epoch 184/500 120/120 [==============================] - 0s 35us/step - loss: 0.4152 - acc: 0.9333 Epoch 185/500 120/120 [==============================] - 0s 48us/step - loss: 0.4138 - acc: 0.9333 Epoch 186/500 120/120 [==============================] - 0s 36us/step - loss: 0.4124 - acc: 0.9333 Epoch 187/500 120/120 [==============================] - 0s 46us/step - loss: 0.4110 - acc: 0.9333 Epoch 188/500 120/120 [==============================] - 0s 45us/step - loss: 0.4096 - acc: 0.9333 Epoch 189/500 120/120 [==============================] - 0s 39us/step - loss: 0.4081 - acc: 0.9333 Epoch 190/500 120/120 [==============================] - 0s 44us/step - loss: 0.4067 - acc: 0.9333 Epoch 191/500 120/120 [==============================] - 0s 41us/step - loss: 0.4053 - acc: 0.9333 Epoch 192/500 120/120 [==============================] - 0s 41us/step - loss: 0.4040 - acc: 0.9333 Epoch 193/500 120/120 [==============================] - 0s 40us/step - loss: 0.4028 - acc: 0.9333 Epoch 194/500 120/120 [==============================] - 0s 46us/step - loss: 0.4013 - acc: 0.9333 Epoch 195/500 120/120 [==============================] - 0s 38us/step - loss: 0.4000 - acc: 0.9333 Epoch 196/500 120/120 [==============================] - 0s 44us/step - loss: 0.3987 - acc: 0.9333 Epoch 197/500 120/120 [==============================] - 0s 42us/step - loss: 0.3973 - acc: 0.9333 Epoch 198/500 120/120 [==============================] - 0s 45us/step - loss: 0.3961 - acc: 0.9417 Epoch 199/500 120/120 [==============================] - 0s 45us/step - loss: 0.3946 - acc: 0.9417 Epoch 200/500 120/120 [==============================] - 0s 46us/step - loss: 0.3934 - acc: 0.9333 Epoch 201/500 120/120 [==============================] - 0s 39us/step - loss: 0.3921 - acc: 0.9333 Epoch 202/500 120/120 [==============================] - 0s 40us/step - loss: 0.3910 - acc: 0.9333 Epoch 203/500 120/120 [==============================] - 0s 37us/step - loss: 0.3896 - acc: 0.9333 Epoch 204/500 120/120 [==============================] - 0s 42us/step - loss: 0.3884 - acc: 0.9333 Epoch 205/500 120/120 [==============================] - 0s 38us/step - loss: 0.3872 - acc: 0.9333 Epoch 206/500 120/120 [==============================] - 0s 35us/step - loss: 0.3859 - acc: 0.9417 Epoch 207/500 120/120 [==============================] - 0s 33us/step - loss: 0.3846 - acc: 0.9417 Epoch 208/500 120/120 [==============================] - 0s 38us/step - loss: 0.3834 - acc: 0.9417 Epoch 209/500 120/120 [==============================] - 0s 37us/step - loss: 0.3823 - acc: 0.9417 Epoch 210/500 120/120 [==============================] - 0s 30us/step - loss: 0.3810 - acc: 0.9417 Epoch 211/500 120/120 [==============================] - 0s 33us/step - loss: 0.3801 - acc: 0.9417 Epoch 212/500 120/120 [==============================] - ETA: 0s - loss: 0.3309 - acc: 1.000 - 0s 39us/step - loss: 0.3786 - acc: 0.9417 Epoch 213/500 120/120 [==============================] - 0s 33us/step - loss: 0.3775 - acc: 0.9417 Epoch 214/500 120/120 [==============================] - 0s 28us/step - loss: 0.3763 - acc: 0.9417 Epoch 215/500 120/120 [==============================] - 0s 32us/step - loss: 0.3751 - acc: 0.9417 Epoch 216/500 120/120 [==============================] - 0s 48us/step - loss: 0.3740 - acc: 0.9417 Epoch 217/500 120/120 [==============================] - ETA: 0s - loss: 0.2860 - acc: 1.000 - 0s 37us/step - loss: 0.3731 - acc: 0.9417 Epoch 218/500 120/120 [==============================] - 0s 38us/step - loss: 0.3718 - acc: 0.9417 Epoch 219/500 120/120 [==============================] - 0s 53us/step - loss: 0.3706 - acc: 0.9417 Epoch 220/500 120/120 [==============================] - 0s 42us/step - loss: 0.3696 - acc: 0.9417 Epoch 221/500 120/120 [==============================] - 0s 46us/step - loss: 0.3685 - acc: 0.9417 Epoch 222/500 120/120 [==============================] - 0s 34us/step - loss: 0.3673 - acc: 0.9417 Epoch 223/500 120/120 [==============================] - 0s 41us/step - loss: 0.3662 - acc: 0.9417 Epoch 224/500 120/120 [==============================] - 0s 42us/step - loss: 0.3651 - acc: 0.9417 Epoch 225/500 120/120 [==============================] - 0s 38us/step - loss: 0.3640 - acc: 0.9500 Epoch 226/500 120/120 [==============================] - 0s 38us/step - loss: 0.3629 - acc: 0.9500 Epoch 227/500 120/120 [==============================] - 0s 49us/step - loss: 0.3619 - acc: 0.9500 Epoch 228/500 120/120 [==============================] - 0s 39us/step - loss: 0.3615 - acc: 0.9500 Epoch 229/500 120/120 [==============================] - 0s 34us/step - loss: 0.3597 - acc: 0.9500 Epoch 230/500 120/120 [==============================] - 0s 82us/step - loss: 0.3586 - acc: 0.9500 Epoch 231/500 120/120 [==============================] - 0s 36us/step - loss: 0.3577 - acc: 0.9500 Epoch 232/500 120/120 [==============================] - 0s 46us/step - loss: 0.3566 - acc: 0.9500 Epoch 233/500 120/120 [==============================] - 0s 43us/step - loss: 0.3557 - acc: 0.9500 Epoch 234/500 120/120 [==============================] - 0s 45us/step - loss: 0.3547 - acc: 0.9500 Epoch 235/500 120/120 [==============================] - 0s 37us/step - loss: 0.3535 - acc: 0.9500 Epoch 236/500 120/120 [==============================] - 0s 39us/step - loss: 0.3524 - acc: 0.9500 Epoch 237/500 120/120 [==============================] - 0s 41us/step - loss: 0.3514 - acc: 0.9500 Epoch 238/500 120/120 [==============================] - 0s 38us/step - loss: 0.3505 - acc: 0.9500 Epoch 239/500 120/120 [==============================] - 0s 37us/step - loss: 0.3495 - acc: 0.9500 Epoch 240/500 120/120 [==============================] - 0s 34us/step - loss: 0.3484 - acc: 0.9500 Epoch 241/500 120/120 [==============================] - 0s 38us/step - loss: 0.3474 - acc: 0.9500 Epoch 242/500 120/120 [==============================] - 0s 42us/step - loss: 0.3465 - acc: 0.9500 Epoch 243/500 120/120 [==============================] - 0s 40us/step - loss: 0.3455 - acc: 0.9500 Epoch 244/500 120/120 [==============================] - 0s 40us/step - loss: 0.3446 - acc: 0.9500 Epoch 245/500 120/120 [==============================] - 0s 31us/step - loss: 0.3436 - acc: 0.9500 Epoch 246/500 120/120 [==============================] - 0s 37us/step - loss: 0.3425 - acc: 0.9500 Epoch 247/500 120/120 [==============================] - 0s 32us/step - loss: 0.3416 - acc: 0.9500 Epoch 248/500 120/120 [==============================] - 0s 33us/step - loss: 0.3406 - acc: 0.9500 Epoch 249/500 120/120 [==============================] - 0s 37us/step - loss: 0.3397 - acc: 0.9500 Epoch 250/500 120/120 [==============================] - 0s 37us/step - loss: 0.3387 - acc: 0.9500 Epoch 251/500 120/120 [==============================] - 0s 33us/step - loss: 0.3378 - acc: 0.9500 Epoch 252/500 120/120 [==============================] - 0s 31us/step - loss: 0.3368 - acc: 0.9500 Epoch 253/500 120/120 [==============================] - 0s 36us/step - loss: 0.3358 - acc: 0.9500 Epoch 254/500 120/120 [==============================] - 0s 36us/step - loss: 0.3349 - acc: 0.9500 Epoch 255/500 120/120 [==============================] - 0s 50us/step - loss: 0.3340 - acc: 0.9500 Epoch 256/500 120/120 [==============================] - 0s 43us/step - loss: 0.3331 - acc: 0.9500 Epoch 257/500 120/120 [==============================] - 0s 35us/step - loss: 0.3322 - acc: 0.9500 Epoch 258/500 120/120 [==============================] - 0s 33us/step - loss: 0.3312 - acc: 0.9500 Epoch 259/500 120/120 [==============================] - 0s 40us/step - loss: 0.3305 - acc: 0.9500 Epoch 260/500 120/120 [==============================] - 0s 47us/step - loss: 0.3298 - acc: 0.9500 Epoch 261/500 120/120 [==============================] - 0s 42us/step - loss: 0.3286 - acc: 0.9500 Epoch 262/500 120/120 [==============================] - 0s 39us/step - loss: 0.3277 - acc: 0.9500 Epoch 263/500 120/120 [==============================] - 0s 46us/step - loss: 0.3268 - acc: 0.9500 Epoch 264/500 120/120 [==============================] - 0s 39us/step - loss: 0.3259 - acc: 0.9500 Epoch 265/500 120/120 [==============================] - 0s 33us/step - loss: 0.3250 - acc: 0.9500 Epoch 266/500 120/120 [==============================] - 0s 38us/step - loss: 0.3242 - acc: 0.9500 Epoch 267/500 120/120 [==============================] - 0s 35us/step - loss: 0.3232 - acc: 0.9500 Epoch 268/500 120/120 [==============================] - 0s 30us/step - loss: 0.3224 - acc: 0.9500 Epoch 269/500 120/120 [==============================] - 0s 40us/step - loss: 0.3215 - acc: 0.9500 Epoch 270/500 120/120 [==============================] - 0s 38us/step - loss: 0.3206 - acc: 0.9500 Epoch 271/500 120/120 [==============================] - 0s 36us/step - loss: 0.3198 - acc: 0.9500 Epoch 272/500 120/120 [==============================] - 0s 41us/step - loss: 0.3189 - acc: 0.9500 Epoch 273/500 120/120 [==============================] - 0s 52us/step - loss: 0.3181 - acc: 0.9500 Epoch 274/500 120/120 [==============================] - 0s 58us/step - loss: 0.3173 - acc: 0.9500 Epoch 275/500 120/120 [==============================] - 0s 46us/step - loss: 0.3165 - acc: 0.9500 Epoch 276/500 120/120 [==============================] - 0s 50us/step - loss: 0.3156 - acc: 0.9500 Epoch 277/500 120/120 [==============================] - 0s 52us/step - loss: 0.3147 - acc: 0.9500 Epoch 278/500 120/120 [==============================] - 0s 40us/step - loss: 0.3139 - acc: 0.9500 Epoch 279/500 120/120 [==============================] - 0s 31us/step - loss: 0.3132 - acc: 0.9500 Epoch 280/500 120/120 [==============================] - 0s 42us/step - loss: 0.3122 - acc: 0.9500 Epoch 281/500 120/120 [==============================] - 0s 42us/step - loss: 0.3114 - acc: 0.9500 Epoch 282/500 120/120 [==============================] - 0s 35us/step - loss: 0.3109 - acc: 0.9500 Epoch 283/500 120/120 [==============================] - 0s 46us/step - loss: 0.3098 - acc: 0.9500 Epoch 284/500 120/120 [==============================] - 0s 38us/step - loss: 0.3089 - acc: 0.9500 Epoch 285/500 120/120 [==============================] - 0s 51us/step - loss: 0.3081 - acc: 0.9500 Epoch 286/500 120/120 [==============================] - 0s 35us/step - loss: 0.3073 - acc: 0.9500 Epoch 287/500 120/120 [==============================] - 0s 36us/step - loss: 0.3066 - acc: 0.9500 Epoch 288/500 120/120 [==============================] - 0s 39us/step - loss: 0.3057 - acc: 0.9500 Epoch 289/500 120/120 [==============================] - 0s 42us/step - loss: 0.3049 - acc: 0.9500 Epoch 290/500 120/120 [==============================] - 0s 40us/step - loss: 0.3042 - acc: 0.9500 Epoch 291/500 120/120 [==============================] - 0s 49us/step - loss: 0.3034 - acc: 0.9500 Epoch 292/500 120/120 [==============================] - 0s 42us/step - loss: 0.3025 - acc: 0.9500 Epoch 293/500 120/120 [==============================] - 0s 36us/step - loss: 0.3019 - acc: 0.9500 Epoch 294/500 120/120 [==============================] - 0s 69us/step - loss: 0.3010 - acc: 0.9500 Epoch 295/500 120/120 [==============================] - 0s 52us/step - loss: 0.3002 - acc: 0.9500 Epoch 296/500 120/120 [==============================] - 0s 41us/step - loss: 0.2994 - acc: 0.9500 Epoch 297/500 120/120 [==============================] - 0s 39us/step - loss: 0.2987 - acc: 0.9500 Epoch 298/500 120/120 [==============================] - 0s 42us/step - loss: 0.2978 - acc: 0.9500 Epoch 299/500 120/120 [==============================] - 0s 42us/step - loss: 0.2972 - acc: 0.9500 Epoch 300/500 120/120 [==============================] - 0s 41us/step - loss: 0.2963 - acc: 0.9500 Epoch 301/500 120/120 [==============================] - 0s 54us/step - loss: 0.2957 - acc: 0.9500 Epoch 302/500 120/120 [==============================] - 0s 47us/step - loss: 0.2949 - acc: 0.9500 Epoch 303/500 120/120 [==============================] - 0s 39us/step - loss: 0.2940 - acc: 0.9500 Epoch 304/500 120/120 [==============================] - 0s 40us/step - loss: 0.2932 - acc: 0.9500 Epoch 305/500 120/120 [==============================] - 0s 38us/step - loss: 0.2925 - acc: 0.9500 Epoch 306/500 120/120 [==============================] - 0s 39us/step - loss: 0.2918 - acc: 0.9500 Epoch 307/500 120/120 [==============================] - 0s 41us/step - loss: 0.2910 - acc: 0.9583 Epoch 308/500 120/120 [==============================] - 0s 42us/step - loss: 0.2902 - acc: 0.9583 Epoch 309/500 120/120 [==============================] - 0s 40us/step - loss: 0.2895 - acc: 0.9500 Epoch 310/500 120/120 [==============================] - 0s 42us/step - loss: 0.2887 - acc: 0.9500 Epoch 311/500 120/120 [==============================] - 0s 35us/step - loss: 0.2880 - acc: 0.9500 Epoch 312/500 120/120 [==============================] - 0s 36us/step - loss: 0.2874 - acc: 0.9500 Epoch 313/500 120/120 [==============================] - 0s 37us/step - loss: 0.2865 - acc: 0.9500 Epoch 314/500 120/120 [==============================] - 0s 42us/step - loss: 0.2858 - acc: 0.9500 Epoch 315/500 120/120 [==============================] - 0s 32us/step - loss: 0.2851 - acc: 0.9500 Epoch 316/500 120/120 [==============================] - 0s 40us/step - loss: 0.2844 - acc: 0.9500 Epoch 317/500 120/120 [==============================] - 0s 40us/step - loss: 0.2836 - acc: 0.9500 Epoch 318/500 120/120 [==============================] - 0s 46us/step - loss: 0.2829 - acc: 0.9500 Epoch 319/500 120/120 [==============================] - 0s 88us/step - loss: 0.2821 - acc: 0.9500 Epoch 320/500 120/120 [==============================] - 0s 37us/step - loss: 0.2815 - acc: 0.9500 Epoch 321/500 120/120 [==============================] - 0s 42us/step - loss: 0.2808 - acc: 0.9583 Epoch 322/500 120/120 [==============================] - 0s 29us/step - loss: 0.2802 - acc: 0.9500 Epoch 323/500 120/120 [==============================] - 0s 51us/step - loss: 0.2793 - acc: 0.9500 Epoch 324/500 120/120 [==============================] - 0s 52us/step - loss: 0.2787 - acc: 0.9583 Epoch 325/500 120/120 [==============================] - 0s 35us/step - loss: 0.2779 - acc: 0.9583 Epoch 326/500 120/120 [==============================] - 0s 34us/step - loss: 0.2772 - acc: 0.9583 Epoch 327/500 120/120 [==============================] - 0s 42us/step - loss: 0.2765 - acc: 0.9583 Epoch 328/500 120/120 [==============================] - 0s 31us/step - loss: 0.2758 - acc: 0.9583 Epoch 329/500 120/120 [==============================] - 0s 35us/step - loss: 0.2750 - acc: 0.9583 Epoch 330/500 120/120 [==============================] - 0s 49us/step - loss: 0.2745 - acc: 0.9583 Epoch 331/500 120/120 [==============================] - 0s 37us/step - loss: 0.2736 - acc: 0.9583 Epoch 332/500 120/120 [==============================] - 0s 44us/step - loss: 0.2730 - acc: 0.9583 Epoch 333/500 120/120 [==============================] - 0s 58us/step - loss: 0.2723 - acc: 0.9583 Epoch 334/500 120/120 [==============================] - 0s 44us/step - loss: 0.2717 - acc: 0.9500 Epoch 335/500 120/120 [==============================] - 0s 42us/step - loss: 0.2709 - acc: 0.9500 Epoch 336/500 120/120 [==============================] - 0s 45us/step - loss: 0.2702 - acc: 0.9500 Epoch 337/500 120/120 [==============================] - 0s 34us/step - loss: 0.2695 - acc: 0.9500 Epoch 338/500 120/120 [==============================] - 0s 45us/step - loss: 0.2688 - acc: 0.9583 Epoch 339/500 120/120 [==============================] - 0s 55us/step - loss: 0.2682 - acc: 0.9583 Epoch 340/500 120/120 [==============================] - 0s 43us/step - loss: 0.2675 - acc: 0.9583 Epoch 341/500 120/120 [==============================] - 0s 43us/step - loss: 0.2668 - acc: 0.9667 Epoch 342/500 120/120 [==============================] - 0s 39us/step - loss: 0.2663 - acc: 0.9667 Epoch 343/500 120/120 [==============================] - 0s 39us/step - loss: 0.2655 - acc: 0.9667 Epoch 344/500 120/120 [==============================] - 0s 44us/step - loss: 0.2649 - acc: 0.9667 Epoch 345/500 120/120 [==============================] - 0s 38us/step - loss: 0.2642 - acc: 0.9583 Epoch 346/500 120/120 [==============================] - 0s 43us/step - loss: 0.2635 - acc: 0.9583 Epoch 347/500 120/120 [==============================] - 0s 44us/step - loss: 0.2628 - acc: 0.9583 Epoch 348/500 120/120 [==============================] - 0s 39us/step - loss: 0.2622 - acc: 0.9667 Epoch 349/500 120/120 [==============================] - 0s 46us/step - loss: 0.2616 - acc: 0.9667 Epoch 350/500 120/120 [==============================] - 0s 48us/step - loss: 0.2609 - acc: 0.9667 Epoch 351/500 120/120 [==============================] - 0s 38us/step - loss: 0.2604 - acc: 0.9667 Epoch 352/500 120/120 [==============================] - 0s 46us/step - loss: 0.2595 - acc: 0.9667 Epoch 353/500 120/120 [==============================] - 0s 39us/step - loss: 0.2589 - acc: 0.9583 Epoch 354/500 120/120 [==============================] - 0s 41us/step - loss: 0.2584 - acc: 0.9667 Epoch 355/500 120/120 [==============================] - 0s 54us/step - loss: 0.2576 - acc: 0.9667 Epoch 356/500 120/120 [==============================] - 0s 36us/step - loss: 0.2572 - acc: 0.9667 Epoch 357/500 120/120 [==============================] - 0s 39us/step - loss: 0.2564 - acc: 0.9583 Epoch 358/500 120/120 [==============================] - 0s 50us/step - loss: 0.2557 - acc: 0.9583 Epoch 359/500 120/120 [==============================] - 0s 39us/step - loss: 0.2554 - acc: 0.9500 Epoch 360/500 120/120 [==============================] - 0s 36us/step - loss: 0.2545 - acc: 0.9500 Epoch 361/500 120/120 [==============================] - 0s 54us/step - loss: 0.2539 - acc: 0.9667 Epoch 362/500 120/120 [==============================] - 0s 43us/step - loss: 0.2532 - acc: 0.9667 Epoch 363/500 120/120 [==============================] - 0s 55us/step - loss: 0.2526 - acc: 0.9667 Epoch 364/500 120/120 [==============================] - 0s 39us/step - loss: 0.2519 - acc: 0.9667 Epoch 365/500 120/120 [==============================] - 0s 35us/step - loss: 0.2513 - acc: 0.9667 Epoch 366/500 120/120 [==============================] - 0s 40us/step - loss: 0.2507 - acc: 0.9667 Epoch 367/500 120/120 [==============================] - 0s 42us/step - loss: 0.2501 - acc: 0.9667 Epoch 368/500 120/120 [==============================] - 0s 41us/step - loss: 0.2495 - acc: 0.9667 Epoch 369/500 120/120 [==============================] - 0s 38us/step - loss: 0.2489 - acc: 0.9667 Epoch 370/500 120/120 [==============================] - 0s 46us/step - loss: 0.2482 - acc: 0.9667 Epoch 371/500 120/120 [==============================] - 0s 51us/step - loss: 0.2476 - acc: 0.9667 Epoch 372/500 120/120 [==============================] - 0s 46us/step - loss: 0.2470 - acc: 0.9667 Epoch 373/500 120/120 [==============================] - 0s 37us/step - loss: 0.2464 - acc: 0.9667 Epoch 374/500 120/120 [==============================] - 0s 37us/step - loss: 0.2457 - acc: 0.9667 Epoch 375/500 120/120 [==============================] - 0s 34us/step - loss: 0.2454 - acc: 0.9667 Epoch 376/500 120/120 [==============================] - 0s 43us/step - loss: 0.2446 - acc: 0.9667 Epoch 377/500 120/120 [==============================] - 0s 40us/step - loss: 0.2440 - acc: 0.9667 Epoch 378/500 120/120 [==============================] - 0s 43us/step - loss: 0.2434 - acc: 0.9667 Epoch 379/500 120/120 [==============================] - 0s 33us/step - loss: 0.2428 - acc: 0.9667 Epoch 380/500 120/120 [==============================] - 0s 33us/step - loss: 0.2422 - acc: 0.9667 Epoch 381/500 120/120 [==============================] - 0s 31us/step - loss: 0.2416 - acc: 0.9667 Epoch 382/500 120/120 [==============================] - 0s 30us/step - loss: 0.2410 - acc: 0.9667 Epoch 383/500 120/120 [==============================] - 0s 46us/step - loss: 0.2404 - acc: 0.9667 Epoch 384/500 120/120 [==============================] - 0s 36us/step - loss: 0.2398 - acc: 0.9667 Epoch 385/500 120/120 [==============================] - 0s 36us/step - loss: 0.2396 - acc: 0.9667 Epoch 386/500 120/120 [==============================] - 0s 37us/step - loss: 0.2386 - acc: 0.9667 Epoch 387/500 120/120 [==============================] - 0s 36us/step - loss: 0.2382 - acc: 0.9667 Epoch 388/500 120/120 [==============================] - 0s 39us/step - loss: 0.2375 - acc: 0.9667 Epoch 389/500 120/120 [==============================] - 0s 36us/step - loss: 0.2369 - acc: 0.9667 Epoch 390/500 120/120 [==============================] - 0s 46us/step - loss: 0.2363 - acc: 0.9667 Epoch 391/500 120/120 [==============================] - ETA: 0s - loss: 0.2399 - acc: 1.000 - 0s 38us/step - loss: 0.2357 - acc: 0.9667 Epoch 392/500 120/120 [==============================] - 0s 48us/step - loss: 0.2352 - acc: 0.9667 Epoch 393/500 120/120 [==============================] - 0s 71us/step - loss: 0.2346 - acc: 0.9667 Epoch 394/500 120/120 [==============================] - 0s 48us/step - loss: 0.2341 - acc: 0.9667 Epoch 395/500 120/120 [==============================] - 0s 40us/step - loss: 0.2336 - acc: 0.9667 Epoch 396/500 120/120 [==============================] - 0s 33us/step - loss: 0.2330 - acc: 0.9667 Epoch 397/500 120/120 [==============================] - 0s 42us/step - loss: 0.2324 - acc: 0.9667 Epoch 398/500 120/120 [==============================] - 0s 47us/step - loss: 0.2318 - acc: 0.9667 Epoch 399/500 120/120 [==============================] - 0s 36us/step - loss: 0.2312 - acc: 0.9667 Epoch 400/500 120/120 [==============================] - 0s 38us/step - loss: 0.2308 - acc: 0.9667 Epoch 401/500 120/120 [==============================] - 0s 49us/step - loss: 0.2301 - acc: 0.9667 Epoch 402/500 120/120 [==============================] - 0s 35us/step - loss: 0.2295 - acc: 0.9667 Epoch 403/500 120/120 [==============================] - 0s 53us/step - loss: 0.2290 - acc: 0.9667 Epoch 404/500 120/120 [==============================] - 0s 39us/step - loss: 0.2284 - acc: 0.9667 Epoch 405/500 120/120 [==============================] - 0s 46us/step - loss: 0.2278 - acc: 0.9667 Epoch 406/500 120/120 [==============================] - 0s 45us/step - loss: 0.2273 - acc: 0.9667 Epoch 407/500 120/120 [==============================] - 0s 37us/step - loss: 0.2267 - acc: 0.9667 Epoch 408/500 120/120 [==============================] - 0s 48us/step - loss: 0.2262 - acc: 0.9667 Epoch 409/500 120/120 [==============================] - 0s 39us/step - loss: 0.2257 - acc: 0.9667 Epoch 410/500 120/120 [==============================] - 0s 33us/step - loss: 0.2251 - acc: 0.9667 Epoch 411/500 120/120 [==============================] - 0s 38us/step - loss: 0.2246 - acc: 0.9667 Epoch 412/500 120/120 [==============================] - 0s 42us/step - loss: 0.2241 - acc: 0.9667 Epoch 413/500 120/120 [==============================] - 0s 31us/step - loss: 0.2236 - acc: 0.9667 Epoch 414/500 120/120 [==============================] - 0s 39us/step - loss: 0.2231 - acc: 0.9667 Epoch 415/500 120/120 [==============================] - 0s 39us/step - loss: 0.2226 - acc: 0.9667 Epoch 416/500 120/120 [==============================] - 0s 40us/step - loss: 0.2221 - acc: 0.9667 Epoch 417/500 120/120 [==============================] - 0s 48us/step - loss: 0.2213 - acc: 0.9667 Epoch 418/500 120/120 [==============================] - 0s 48us/step - loss: 0.2209 - acc: 0.9667 Epoch 419/500 120/120 [==============================] - 0s 43us/step - loss: 0.2203 - acc: 0.9667 Epoch 420/500 120/120 [==============================] - 0s 40us/step - loss: 0.2198 - acc: 0.9667 Epoch 421/500 120/120 [==============================] - 0s 43us/step - loss: 0.2192 - acc: 0.9667 Epoch 422/500 120/120 [==============================] - 0s 36us/step - loss: 0.2189 - acc: 0.9667 Epoch 423/500 120/120 [==============================] - 0s 38us/step - loss: 0.2184 - acc: 0.9667 Epoch 424/500 120/120 [==============================] - 0s 39us/step - loss: 0.2177 - acc: 0.9667 Epoch 425/500 120/120 [==============================] - 0s 38us/step - loss: 0.2172 - acc: 0.9667 Epoch 426/500 120/120 [==============================] - 0s 40us/step - loss: 0.2166 - acc: 0.9667 Epoch 427/500 120/120 [==============================] - 0s 39us/step - loss: 0.2162 - acc: 0.9667 Epoch 428/500 120/120 [==============================] - 0s 33us/step - loss: 0.2156 - acc: 0.9667 Epoch 429/500 120/120 [==============================] - 0s 44us/step - loss: 0.2151 - acc: 0.9667 Epoch 430/500 120/120 [==============================] - 0s 41us/step - loss: 0.2147 - acc: 0.9667 Epoch 431/500 120/120 [==============================] - 0s 39us/step - loss: 0.2141 - acc: 0.9667 Epoch 432/500 120/120 [==============================] - 0s 50us/step - loss: 0.2137 - acc: 0.9667 Epoch 433/500 120/120 [==============================] - 0s 51us/step - loss: 0.2131 - acc: 0.9667 Epoch 434/500 120/120 [==============================] - 0s 56us/step - loss: 0.2127 - acc: 0.9667 Epoch 435/500 120/120 [==============================] - 0s 45us/step - loss: 0.2122 - acc: 0.9667 Epoch 436/500 120/120 [==============================] - 0s 40us/step - loss: 0.2118 - acc: 0.9667 Epoch 437/500 120/120 [==============================] - 0s 32us/step - loss: 0.2112 - acc: 0.9667 Epoch 438/500 120/120 [==============================] - 0s 36us/step - loss: 0.2106 - acc: 0.9667 Epoch 439/500 120/120 [==============================] - 0s 34us/step - loss: 0.2103 - acc: 0.9667 Epoch 440/500 120/120 [==============================] - 0s 53us/step - loss: 0.2096 - acc: 0.9667 Epoch 441/500 120/120 [==============================] - 0s 52us/step - loss: 0.2090 - acc: 0.9750 Epoch 442/500 120/120 [==============================] - 0s 38us/step - loss: 0.2087 - acc: 0.9750 Epoch 443/500 120/120 [==============================] - 0s 43us/step - loss: 0.2086 - acc: 0.9750 Epoch 444/500 120/120 [==============================] - 0s 45us/step - loss: 0.2077 - acc: 0.9750 Epoch 445/500 120/120 [==============================] - 0s 48us/step - loss: 0.2073 - acc: 0.9750 Epoch 446/500 120/120 [==============================] - 0s 49us/step - loss: 0.2067 - acc: 0.9750 Epoch 447/500 120/120 [==============================] - 0s 38us/step - loss: 0.2062 - acc: 0.9750 Epoch 448/500 120/120 [==============================] - 0s 36us/step - loss: 0.2060 - acc: 0.9667 Epoch 449/500 120/120 [==============================] - 0s 42us/step - loss: 0.2053 - acc: 0.9667 Epoch 450/500 120/120 [==============================] - 0s 41us/step - loss: 0.2048 - acc: 0.9667 Epoch 451/500 120/120 [==============================] - 0s 44us/step - loss: 0.2044 - acc: 0.9667 Epoch 452/500 120/120 [==============================] - 0s 41us/step - loss: 0.2038 - acc: 0.9750 Epoch 453/500 120/120 [==============================] - ETA: 0s - loss: 0.1737 - acc: 1.000 - 0s 45us/step - loss: 0.2033 - acc: 0.9750 Epoch 454/500 120/120 [==============================] - 0s 47us/step - loss: 0.2029 - acc: 0.9750 Epoch 455/500 120/120 [==============================] - 0s 44us/step - loss: 0.2024 - acc: 0.9750 Epoch 456/500 120/120 [==============================] - 0s 33us/step - loss: 0.2020 - acc: 0.9750 Epoch 457/500 120/120 [==============================] - 0s 50us/step - loss: 0.2017 - acc: 0.9750 Epoch 458/500 120/120 [==============================] - 0s 36us/step - loss: 0.2010 - acc: 0.9750 Epoch 459/500 120/120 [==============================] - 0s 37us/step - loss: 0.2007 - acc: 0.9750 Epoch 460/500 120/120 [==============================] - 0s 34us/step - loss: 0.2003 - acc: 0.9750 Epoch 461/500 120/120 [==============================] - 0s 37us/step - loss: 0.1997 - acc: 0.9750 Epoch 462/500 120/120 [==============================] - 0s 30us/step - loss: 0.1994 - acc: 0.9750 Epoch 463/500 120/120 [==============================] - 0s 29us/step - loss: 0.1988 - acc: 0.9750 Epoch 464/500 120/120 [==============================] - 0s 34us/step - loss: 0.1983 - acc: 0.9750 Epoch 465/500 120/120 [==============================] - 0s 83us/step - loss: 0.1980 - acc: 0.9750 Epoch 466/500 120/120 [==============================] - 0s 43us/step - loss: 0.1974 - acc: 0.9750 Epoch 467/500 120/120 [==============================] - 0s 45us/step - loss: 0.1969 - acc: 0.9750 Epoch 468/500 120/120 [==============================] - 0s 33us/step - loss: 0.1965 - acc: 0.9750 Epoch 469/500 120/120 [==============================] - 0s 30us/step - loss: 0.1960 - acc: 0.9750 Epoch 470/500 120/120 [==============================] - 0s 59us/step - loss: 0.1957 - acc: 0.9750 Epoch 471/500 120/120 [==============================] - 0s 33us/step - loss: 0.1951 - acc: 0.9750 Epoch 472/500 120/120 [==============================] - 0s 47us/step - loss: 0.1947 - acc: 0.9750 Epoch 473/500 120/120 [==============================] - 0s 41us/step - loss: 0.1943 - acc: 0.9750 Epoch 474/500 120/120 [==============================] - 0s 37us/step - loss: 0.1938 - acc: 0.9750 Epoch 475/500 120/120 [==============================] - 0s 48us/step - loss: 0.1936 - acc: 0.9750 Epoch 476/500 120/120 [==============================] - 0s 46us/step - loss: 0.1929 - acc: 0.9750 Epoch 477/500 120/120 [==============================] - 0s 46us/step - loss: 0.1925 - acc: 0.9750 Epoch 478/500 120/120 [==============================] - 0s 48us/step - loss: 0.1920 - acc: 0.9750 Epoch 479/500 120/120 [==============================] - ETA: 0s - loss: 0.1874 - acc: 1.000 - 0s 40us/step - loss: 0.1916 - acc: 0.9750 Epoch 480/500 120/120 [==============================] - 0s 45us/step - loss: 0.1919 - acc: 0.9750 Epoch 481/500 120/120 [==============================] - 0s 32us/step - loss: 0.1910 - acc: 0.9750 Epoch 482/500 120/120 [==============================] - 0s 37us/step - loss: 0.1904 - acc: 0.9750 Epoch 483/500 120/120 [==============================] - 0s 48us/step - loss: 0.1900 - acc: 0.9750 Epoch 484/500 120/120 [==============================] - 0s 35us/step - loss: 0.1896 - acc: 0.9750 Epoch 485/500 120/120 [==============================] - 0s 35us/step - loss: 0.1891 - acc: 0.9750 Epoch 486/500 120/120 [==============================] - 0s 48us/step - loss: 0.1886 - acc: 0.9750 Epoch 487/500 120/120 [==============================] - 0s 37us/step - loss: 0.1883 - acc: 0.9750 Epoch 488/500 120/120 [==============================] - 0s 69us/step - loss: 0.1878 - acc: 0.9750 Epoch 489/500 120/120 [==============================] - 0s 36us/step - loss: 0.1877 - acc: 0.9750 Epoch 490/500 120/120 [==============================] - 0s 34us/step - loss: 0.1871 - acc: 0.9750 Epoch 491/500 120/120 [==============================] - 0s 44us/step - loss: 0.1867 - acc: 0.9750 Epoch 492/500 120/120 [==============================] - 0s 37us/step - loss: 0.1862 - acc: 0.9750 Epoch 493/500 120/120 [==============================] - 0s 40us/step - loss: 0.1858 - acc: 0.9750 Epoch 494/500 120/120 [==============================] - 0s 42us/step - loss: 0.1854 - acc: 0.9750 Epoch 495/500 120/120 [==============================] - 0s 35us/step - loss: 0.1849 - acc: 0.9750 Epoch 496/500 120/120 [==============================] - 0s 42us/step - loss: 0.1846 - acc: 0.9750 Epoch 497/500 120/120 [==============================] - 0s 42us/step - loss: 0.1842 - acc: 0.9750 Epoch 498/500 120/120 [==============================] - 0s 38us/step - loss: 0.1838 - acc: 0.9750 Epoch 499/500 120/120 [==============================] - 0s 33us/step - loss: 0.1834 - acc: 0.9750 Epoch 500/500 120/120 [==============================] - 0s 41us/step - loss: 0.1829 - acc: 0.9750 Out [4]: In [5]:pred = model.predict(data_test).argmax(axis=1) pred Out [5]:array([2, 1, 0, 2, 0, 2, 0, 1, 1, 1, 2, 1, 1, 1, 1, 0, 1, 1, 0, 0, 2, 1, 0, 0, 2, 0, 0, 1, 1, 0]) In [6]:(pred == y_test).sum()/ len(pred) Out [6]:1.0 In [7]:(train_data, train_label), (test_data, test_label) \ = tf.keras.datasets.cifar10.load_data() train_data = train_data / 255 test_data = test_data / 255 train_label = train_label.ravel() test_label = test_label.ravel() train_data.shape Out [7]:(50000, 32, 32, 3) In [8]:label_names = ["airplane", "automobile", "bird", "cat", "deer", "dog", "frog", "horse", "ship", "truck"] In [9]:import matplotlib.pyplot as plt %matplotlib inline fig, axes = plt.subplots(10, figsize=(8, 15)) for i in range(10): imgs = train_data[train_label == i][:10] axes[i].imshow(imgs.transpose(1, 0, 2, 3).reshape(32, 10 * 32, 3)) axes[i].axis("off") axes[i].set_title(label_names[i]) In [10]:model = tf.keras.Sequential([ tf.keras.layers.Conv2D(16, (3, 3), input_shape=(32, 32, 3), activation="relu"), tf.keras.layers.MaxPool2D((2, 2)), tf.keras.layers.Conv2D(32, (3, 3), activation="relu"), tf.keras.layers.MaxPool2D((2, 2)), tf.keras.layers.Flatten(), tf.keras.layers.Dense(512), tf.keras.layers.Dense(10, activation="softmax") ]) In [11]:model.summary() _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= conv2d (Conv2D) (None, 30, 30, 16) 448 _________________________________________________________________ max_pooling2d (MaxPooling2D) (None, 15, 15, 16) 0 _________________________________________________________________ conv2d_1 (Conv2D) (None, 13, 13, 32) 4640 _________________________________________________________________ max_pooling2d_1 (MaxPooling2 (None, 6, 6, 32) 0 _________________________________________________________________ flatten (Flatten) (None, 1152) 0 _________________________________________________________________ dense_2 (Dense) (None, 512) 590336 _________________________________________________________________ dense_3 (Dense) (None, 10) 5130 ================================================================= Total params: 600,554 Trainable params: 600,554 Non-trainable params: 0 _________________________________________________________________ In [12]:model.compile(optimizer="adam", loss='sparse_categorical_crossentropy', metrics=["accuracy"]) In [13]:np.random.seed(1) tf.set_random_seed(2) model.fit(train_data,train_label, epochs=20) Epoch 1/20 50000/50000 [==============================] - 27s 535us/step - loss: 0.7800 - acc: 0.7290 Epoch 2/20 50000/50000 [==============================] - 27s 532us/step - loss: 0.7752 - acc: 0.7279 Epoch 3/20 50000/50000 [==============================] - 26s 523us/step - loss: 0.7709 - acc: 0.7303 Epoch 4/20 50000/50000 [==============================] - 26s 520us/step - loss: 0.7632 - acc: 0.7336 Epoch 5/20 50000/50000 [==============================] - 26s 518us/step - loss: 0.7641 - acc: 0.7335 Epoch 6/20 50000/50000 [==============================] - 26s 522us/step - loss: 0.7558 - acc: 0.7379 Epoch 7/20 50000/50000 [==============================] - 26s 520us/step - loss: 0.7522 - acc: 0.7380 Epoch 8/20 50000/50000 [==============================] - 26s 523us/step - loss: 0.7481 - acc: 0.7392 Epoch 9/20 50000/50000 [==============================] - 26s 524us/step - loss: 0.7443 - acc: 0.7400 Epoch 10/20 50000/50000 [==============================] - 26s 524us/step - loss: 0.7416 - acc: 0.7409 Epoch 11/20 50000/50000 [==============================] - 26s 527us/step - loss: 0.7365 - acc: 0.7415 Epoch 12/20 50000/50000 [==============================] - 26s 522us/step - loss: 0.7339 - acc: 0.7432 Epoch 13/20 50000/50000 [==============================] - 26s 520us/step - loss: 0.7292 - acc: 0.7452 Epoch 14/20 50000/50000 [==============================] - 26s 520us/step - loss: 0.7317 - acc: 0.7420 Epoch 15/20 50000/50000 [==============================] - 26s 520us/step - loss: 0.7259 - acc: 0.7471 Epoch 16/20 50000/50000 [==============================] - 26s 521us/step - loss: 0.7254 - acc: 0.7466 Epoch 17/20 50000/50000 [==============================] - 26s 520us/step - loss: 0.7211 - acc: 0.7470 Epoch 18/20 50000/50000 [==============================] - 26s 526us/step - loss: 0.7211 - acc: 0.7477 Epoch 19/20 50000/50000 [==============================] - 26s 522us/step - loss: 0.7158 - acc: 0.7479 Epoch 20/20 50000/50000 [==============================] - 27s 534us/step - loss: 0.7104 - acc: 0.7513 Out [13]: In [14]:model.save("cifar10.h5") In [15]:model_loaded=tf.keras.models.load_model("cifar10.h5") In [16]:pred = model_loaded.predict_classes(test_data) (pred == test_label).sum() / len(test_label) Out [16]:0.6778 In [17]:correct_data = test_data[pred == test_label] correct_label = pred[pred == test_label] fig, axes = plt.subplots(3, 10, figsize=(15, 5)) for i in range(30): ax = axes[i // 10][i % 10] ax.set_title(label_names[correct_label[i]]) ax.axis("off") ax.imshow(correct_data[i]) In [18]:incorrect_data = test_data[pred != test_label] incorrect_label = pred[pred != test_label] fig, axes = plt.subplots(3, 10, figsize=(15, 5)) for i in range(30): ax = axes[i // 10][i % 10] ax.set_title(label_names[incorrect_label[i]]) ax.axis("off") ax.imshow(incorrect_data[i])