Epoch 1/6

  1/469 [..............................] - ETA: 15:11 - loss: 2.3392 - sparse_categorical_accuracy: 0.0859
 14/469 [..............................] - ETA: 1s - loss: 1.7136 - sparse_categorical_accuracy: 0.5312   
 27/469 [>.............................] - ETA: 1s - loss: 1.3064 - sparse_categorical_accuracy: 0.6632
 38/469 [=>............................] - ETA: 1s - loss: 1.1110 - sparse_categorical_accuracy: 0.7120
 49/469 [==>...........................] - ETA: 1s - loss: 0.9774 - sparse_categorical_accuracy: 0.7439
 60/469 [==>...........................] - ETA: 1s - loss: 0.8821 - sparse_categorical_accuracy: 0.7685
 72/469 [===>..........................] - ETA: 1s - loss: 0.8086 - sparse_categorical_accuracy: 0.7879
 84/469 [====>.........................] - ETA: 1s - loss: 0.7500 - sparse_categorical_accuracy: 0.8022
 96/469 [=====>........................] - ETA: 1s - loss: 0.7048 - sparse_categorical_accuracy: 0.8136
107/469 [=====>........................] - ETA: 1s - loss: 0.6692 - sparse_categorical_accuracy: 0.8221
118/469 [======>.......................] - ETA: 1s - loss: 0.6403 - sparse_categorical_accuracy: 0.8296
129/469 [=======>......................] - ETA: 1s - loss: 0.6181 - sparse_categorical_accuracy: 0.8352
142/469 [========>.....................] - ETA: 1s - loss: 0.5931 - sparse_categorical_accuracy: 0.8418
150/469 [========>.....................] - ETA: 1s - loss: 0.5783 - sparse_categorical_accuracy: 0.8459
161/469 [=========>....................] - ETA: 1s - loss: 0.5575 - sparse_categorical_accuracy: 0.8512
171/469 [=========>....................] - ETA: 1s - loss: 0.5417 - sparse_categorical_accuracy: 0.8548
181/469 [==========>...................] - ETA: 1s - loss: 0.5275 - sparse_categorical_accuracy: 0.8587
191/469 [===========>..................] - ETA: 1s - loss: 0.5132 - sparse_categorical_accuracy: 0.8625
202/469 [===========>..................] - ETA: 1s - loss: 0.5012 - sparse_categorical_accuracy: 0.8658
212/469 [============>.................] - ETA: 1s - loss: 0.4904 - sparse_categorical_accuracy: 0.8689
221/469 [=============>................] - ETA: 1s - loss: 0.4814 - sparse_categorical_accuracy: 0.8711
229/469 [=============>................] - ETA: 1s - loss: 0.4751 - sparse_categorical_accuracy: 0.8724
237/469 [==============>...............] - ETA: 1s - loss: 0.4691 - sparse_categorical_accuracy: 0.8739
245/469 [==============>...............] - ETA: 1s - loss: 0.4639 - sparse_categorical_accuracy: 0.8754
253/469 [===============>..............] - ETA: 1s - loss: 0.4587 - sparse_categorical_accuracy: 0.8767
262/469 [===============>..............] - ETA: 1s - loss: 0.4525 - sparse_categorical_accuracy: 0.8782
271/469 [================>.............] - ETA: 1s - loss: 0.4448 - sparse_categorical_accuracy: 0.8803
283/469 [=================>............] - ETA: 0s - loss: 0.4372 - sparse_categorical_accuracy: 0.8823
295/469 [=================>............] - ETA: 0s - loss: 0.4293 - sparse_categorical_accuracy: 0.8842
304/469 [==================>...........] - ETA: 0s - loss: 0.4243 - sparse_categorical_accuracy: 0.8854Randomfd.txt
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313/469 [===================>..........] - ETA: 0s - loss: 0.4189 - sparse_categorical_accuracy: 0.8867
325/469 [===================>..........] - ETA: 0s - loss: 0.4125 - sparse_categorical_accuracy: 0.8884
337/469 [====================>.........] - ETA: 0s - loss: 0.4056 - sparse_categorical_accuracy: 0.8900
349/469 [=====================>........] - ETA: 0s - loss: 0.4011 - sparse_categorical_accuracy: 0.8912
361/469 [======================>.......] - ETA: 0s - loss: 0.3949 - sparse_categorical_accuracy: 0.8928
373/469 [======================>.......] - ETA: 0s - loss: 0.3903 - sparse_categorical_accuracy: 0.8941
384/469 [=======================>......] - ETA: 0s - loss: 0.3859 - sparse_categorical_accuracy: 0.8952
394/469 [========================>.....] - ETA: 0s - loss: 0.3816 - sparse_categorical_accuracy: 0.8964
403/469 [========================>.....] - ETA: 0s - loss: 0.3781 - sparse_categorical_accuracy: 0.8975
413/469 [=========================>....] - ETA: 0s - loss: 0.3742 - sparse_categorical_accuracy: 0.8985
423/469 [==========================>...] - ETA: 0s - loss: 0.3704 - sparse_categorical_accuracy: 0.8993
433/469 [==========================>...] - ETA: 0s - loss: 0.3669 - sparse_categorical_accuracy: 0.9002
443/469 [===========================>..] - ETA: 0s - loss: 0.3631 - sparse_categorical_accuracy: 0.9011
453/469 [===========================>..] - ETA: 0s - loss: 0.3599 - sparse_categorical_accuracy: 0.9020
465/469 [============================>.] - ETA: 0s - loss: 0.3557 - sparse_categorical_accuracy: 0.9030
469/469 [==============================] - 5s 6ms/step - loss: 0.3546 - sparse_categorical_accuracy: 0.9033 - val_loss: 0.1926 - val_sparse_categorical_accuracy: 0.9469
Epoch 2/6

  1/469 [..............................] - ETA: 28s - loss: 0.1450 - sparse_categorical_accuracy: 0.9609
 13/469 [..............................] - ETA: 2s - loss: 0.2114 - sparse_categorical_accuracy: 0.9405 Randomfd.txt
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 24/469 [>.............................] - ETA: 2s - loss: 0.1960 - sparse_categorical_accuracy: 0.9473
 34/469 [=>............................] - ETA: 2s - loss: 0.1953 - sparse_categorical_accuracy: 0.9476
 46/469 [=>............................] - ETA: 2s - loss: 0.2006 - sparse_categorical_accuracy: 0.9448
 57/469 [==>...........................] - ETA: 1s - loss: 0.1956 - sparse_categorical_accuracy: 0.9463
 69/469 [===>..........................] - ETA: 1s - loss: 0.1963 - sparse_categorical_accuracy: 0.9451
 80/469 [====>.........................] - ETA: 1s - loss: 0.1963 - sparse_categorical_accuracy: 0.9451
 90/469 [====>.........................] - ETA: 1s - loss: 0.1920 - sparse_categorical_accuracy: 0.9464
100/469 [=====>........................] - ETA: 1s - loss: 0.1906 - sparse_categorical_accuracy: 0.9465
111/469 [======>.......................] - ETA: 1s - loss: 0.1850 - sparse_categorical_accuracy: 0.9482
120/469 [======>.......................] - ETA: 1s - loss: 0.1826 - sparse_categorical_accuracy: 0.9492
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141/469 [========>.....................] - ETA: 1s - loss: 0.1802 - sparse_categorical_accuracy: 0.9496
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161/469 [=========>....................] - ETA: 1s - loss: 0.1804 - sparse_categorical_accuracy: 0.9493
171/469 [=========>....................] - ETA: 1s - loss: 0.1800 - sparse_categorical_accuracy: 0.9492
181/469 [==========>...................] - ETA: 1s - loss: 0.1800 - sparse_categorical_accuracy: 0.9489
191/469 [===========>..................] - ETA: 1s - loss: 0.1789 - sparse_categorical_accuracy: 0.9494
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211/469 [============>.................] - ETA: 1s - loss: 0.1782 - sparse_categorical_accuracy: 0.9495
222/469 [=============>................] - ETA: 1s - loss: 0.1762 - sparse_categorical_accuracy: 0.9500
232/469 [=============>................] - ETA: 1s - loss: 0.1753 - sparse_categorical_accuracy: 0.9501
242/469 [==============>...............] - ETA: 1s - loss: 0.1749 - sparse_categorical_accuracy: 0.9500
252/469 [===============>..............] - ETA: 1s - loss: 0.1735 - sparse_categorical_accuracy: 0.9504
263/469 [===============>..............] - ETA: 1s - loss: 0.1737 - sparse_categorical_accuracy: 0.9501
274/469 [================>.............] - ETA: 0s - loss: 0.1723 - sparse_categorical_accuracy: 0.9504
285/469 [=================>............] - ETA: 0s - loss: 0.1721 - sparse_categorical_accuracy: 0.9504
296/469 [=================>............] - ETA: 0s - loss: 0.1713 - sparse_categorical_accuracy: 0.9507
306/469 [==================>...........] - ETA: 0s - loss: 0.1716 - sparse_categorical_accuracy: 0.9505
316/469 [===================>..........] - ETA: 0s - loss: 0.1709 - sparse_categorical_accuracy: 0.9508
325/469 [===================>..........] - ETA: 0s - loss: 0.1696 - sparse_categorical_accuracy: 0.9512
335/469 [====================>.........] - ETA: 0s - loss: 0.1705 - sparse_categorical_accuracy: 0.9512
346/469 [=====================>........] - ETA: 0s - loss: 0.1699 - sparse_categorical_accuracy: 0.9514
359/469 [=====================>........] - ETA: 0s - loss: 0.1691 - sparse_categorical_accuracy: 0.9515
373/469 [======================>.......] - ETA: 0s - loss: 0.1687 - sparse_categorical_accuracy: 0.9514
384/469 [=======================>......] - ETA: 0s - loss: 0.1678 - sparse_categorical_accuracy: 0.9518
393/469 [========================>.....] - ETA: 0s - loss: 0.1677 - sparse_categorical_accuracy: 0.9519
400/469 [========================>.....] - ETA: 0s - loss: 0.1674 - sparse_categorical_accuracy: 0.9520
415/469 [=========================>....] - ETA: 0s - loss: 0.1670 - sparse_categorical_accuracy: 0.9521
423/469 [==========================>...] - ETA: 0s - loss: 0.1671 - sparse_categorical_accuracy: 0.9522
431/469 [==========================>...] - ETA: 0s - loss: 0.1662 - sparse_categorical_accuracy: 0.9524
438/469 [===========================>..] - ETA: 0s - loss: 0.1661 - sparse_categorical_accuracy: 0.9525
446/469 [===========================>..] - ETA: 0s - loss: 0.1659 - sparse_categorical_accuracy: 0.9526
453/469 [===========================>..] - ETA: 0s - loss: 0.1651 - sparse_categorical_accuracy: 0.9528
461/469 [============================>.] - ETA: 0s - loss: 0.1644 - sparse_categorical_accuracy: 0.9531
469/469 [==============================] - 3s 6ms/step - loss: 0.1640 - sparse_categorical_accuracy: 0.9531 - val_loss: 0.1406 - val_sparse_categorical_accuracy: 0.9580
Epoch 3/6

  1/469 [..............................] - ETA: 25s - loss: 0.1722 - sparse_categorical_accuracy: 0.9375
 17/469 [>.............................] - ETA: 1s - loss: 0.1352 - sparse_categorical_accuracy: 0.9596 
 28/469 [>.............................] - ETA: 1s - loss: 0.1370 - sparse_categorical_accuracy: 0.9598
 36/469 [=>............................] - ETA: 1s - loss: 0.1425 - sparse_categorical_accuracy: 0.9599
 46/469 [=>............................] - ETA: 1s - loss: 0.1328 - sparse_categorical_accuracy: 0.9638
 55/469 [==>...........................] - ETA: 2s - loss: 0.1312 - sparse_categorical_accuracy: 0.9643
 63/469 [===>..........................] - ETA: 2s - loss: 0.1282 - sparse_categorical_accuracy: 0.9653
 69/469 [===>..........................] - ETA: 2s - loss: 0.1280 - sparse_categorical_accuracy: 0.9657
 75/469 [===>..........................] - ETA: 2s - loss: 0.1270 - sparse_categorical_accuracy: 0.9658
 80/469 [====>.........................] - ETA: 2s - loss: 0.1270 - sparse_categorical_accuracy: 0.9653
 87/469 [====>.........................] - ETA: 2s - loss: 0.1301 - sparse_categorical_accuracy: 0.9644
 92/469 [====>.........................] - ETA: 2s - loss: 0.1317 - sparse_categorical_accuracy: 0.9635
105/469 [=====>........................] - ETA: 2s - loss: 0.1325 - sparse_categorical_accuracy: 0.9639
118/469 [======>.......................] - ETA: 2s - loss: 0.1321 - sparse_categorical_accuracy: 0.9632
127/469 [=======>......................] - ETA: 2s - loss: 0.1311 - sparse_categorical_accuracy: 0.9631
139/469 [=======>......................] - ETA: 1s - loss: 0.1320 - sparse_categorical_accuracy: 0.9627
154/469 [========>.....................] - ETA: 1s - loss: 0.1323 - sparse_categorical_accuracy: 0.9627
169/469 [=========>....................] - ETA: 1s - loss: 0.1308 - sparse_categorical_accuracy: 0.9630
178/469 [==========>...................] - ETA: 1s - loss: 0.1307 - sparse_categorical_accuracy: 0.9627
185/469 [==========>...................] - ETA: 1s - loss: 0.1302 - sparse_categorical_accuracy: 0.9628
194/469 [===========>..................] - ETA: 1s - loss: 0.1304 - sparse_categorical_accuracy: 0.9626
206/469 [============>.................] - ETA: 1s - loss: 0.1286 - sparse_categorical_accuracy: 0.9631
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272/469 [================>.............] - ETA: 1s - loss: 0.1250 - sparse_categorical_accuracy: 0.9645
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287/469 [=================>............] - ETA: 1s - loss: 0.1243 - sparse_categorical_accuracy: 0.9647
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300/469 [==================>...........] - ETA: 0s - loss: 0.1234 - sparse_categorical_accuracy: 0.9651
306/469 [==================>...........] - ETA: 0s - loss: 0.1236 - sparse_categorical_accuracy: 0.9649
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319/469 [===================>..........] - ETA: 0s - loss: 0.1227 - sparse_categorical_accuracy: 0.9651
322/469 [===================>..........] - ETA: 0s - loss: 0.1224 - sparse_categorical_accuracy: 0.9652
335/469 [====================>.........] - ETA: 0s - loss: 0.1216 - sparse_categorical_accuracy: 0.9654
352/469 [=====================>........] - ETA: 0s - loss: 0.1200 - sparse_categorical_accuracy: 0.9657
363/469 [======================>.......] - ETA: 0s - loss: 0.1201 - sparse_categorical_accuracy: 0.9656
371/469 [======================>.......] - ETA: 0s - loss: 0.1197 - sparse_categorical_accuracy: 0.9657
384/469 [=======================>......] - ETA: 0s - loss: 0.1195 - sparse_categorical_accuracy: 0.9657
399/469 [========================>.....] - ETA: 0s - loss: 0.1193 - sparse_categorical_accuracy: 0.9659
408/469 [=========================>....] - ETA: 0s - loss: 0.1192 - sparse_categorical_accuracy: 0.9658
415/469 [=========================>....] - ETA: 0s - loss: 0.1191 - sparse_categorical_accuracy: 0.9659
423/469 [==========================>...] - ETA: 0s - loss: 0.1193 - sparse_categorical_accuracy: 0.9657
438/469 [===========================>..] - ETA: 0s - loss: 0.1194 - sparse_categorical_accuracy: 0.9658
454/469 [============================>.] - ETA: 0s - loss: 0.1193 - sparse_categorical_accuracy: 0.9658
465/469 [============================>.] - ETA: 0s - loss: 0.1192 - sparse_categorical_accuracy: 0.9658
469/469 [==============================] - 3s 6ms/step - loss: 0.1192 - sparse_categorical_accuracy: 0.9659 - val_loss: 0.1123 - val_sparse_categorical_accuracy: 0.9663
Epoch 4/6

  1/469 [..............................] - ETA: 27s - loss: 0.0512 - sparse_categorical_accuracy: 0.9844
 18/469 [>.............................] - ETA: 1s - loss: 0.0869 - sparse_categorical_accuracy: 0.9783 
 31/469 [>.............................] - ETA: 1s - loss: 0.0943 - sparse_categorical_accuracy: 0.9738
 43/469 [=>............................] - ETA: 1s - loss: 0.1001 - sparse_categorical_accuracy: 0.9718
 59/469 [==>...........................] - ETA: 1s - loss: 0.1007 - sparse_categorical_accuracy: 0.9719
 73/469 [===>..........................] - ETA: 1s - loss: 0.0993 - sparse_categorical_accuracy: 0.9719
 90/469 [====>.........................] - ETA: 1s - loss: 0.0970 - sparse_categorical_accuracy: 0.9723
103/469 [=====>........................] - ETA: 1s - loss: 0.0969 - sparse_categorical_accuracy: 0.9724
112/469 [======>.......................] - ETA: 1s - loss: 0.0965 - sparse_categorical_accuracy: 0.9727
118/469 [======>.......................] - ETA: 1s - loss: 0.0975 - sparse_categorical_accuracy: 0.9727
124/469 [======>.......................] - ETA: 1s - loss: 0.0965 - sparse_categorical_accuracy: 0.9728
136/469 [=======>......................] - ETA: 1s - loss: 0.0955 - sparse_categorical_accuracy: 0.9731
152/469 [========>.....................] - ETA: 1s - loss: 0.0972 - sparse_categorical_accuracy: 0.9725
169/469 [=========>....................] - ETA: 1s - loss: 0.0967 - sparse_categorical_accuracy: 0.9727
186/469 [==========>...................] - ETA: 1s - loss: 0.0964 - sparse_categorical_accuracy: 0.9728
202/469 [===========>..................] - ETA: 1s - loss: 0.0968 - sparse_categorical_accuracy: 0.9727
218/469 [============>.................] - ETA: 0s - loss: 0.0962 - sparse_categorical_accuracy: 0.9729
229/469 [=============>................] - ETA: 0s - loss: 0.0956 - sparse_categorical_accuracy: 0.9732
245/469 [==============>...............] - ETA: 0s - loss: 0.0960 - sparse_categorical_accuracy: 0.9733
262/469 [===============>..............] - ETA: 0s - loss: 0.0962 - sparse_categorical_accuracy: 0.9730
279/469 [================>.............] - ETA: 0s - loss: 0.0962 - sparse_categorical_accuracy: 0.9732
294/469 [=================>............] - ETA: 0s - loss: 0.0960 - sparse_categorical_accuracy: 0.9732
308/469 [==================>...........] - ETA: 0s - loss: 0.0957 - sparse_categorical_accuracy: 0.9733
321/469 [===================>..........] - ETA: 0s - loss: 0.0954 - sparse_categorical_accuracy: 0.9733
335/469 [====================>.........] - ETA: 0s - loss: 0.0953 - sparse_categorical_accuracy: 0.9733
350/469 [=====================>........] - ETA: 0s - loss: 0.0946 - sparse_categorical_accuracy: 0.9734
365/469 [======================>.......] - ETA: 0s - loss: 0.0940 - sparse_categorical_accuracy: 0.9736
381/469 [=======================>......] - ETA: 0s - loss: 0.0936 - sparse_categorical_accuracy: 0.9735
395/469 [========================>.....] - ETA: 0s - loss: 0.0932 - sparse_categorical_accuracy: 0.9738
410/469 [=========================>....] - ETA: 0s - loss: 0.0927 - sparse_categorical_accuracy: 0.9738
421/469 [=========================>....] - ETA: 0s - loss: 0.0927 - sparse_categorical_accuracy: 0.9737
432/469 [==========================>...] - ETA: 0s - loss: 0.0923 - sparse_categorical_accuracy: 0.9739
443/469 [===========================>..] - ETA: 0s - loss: 0.0922 - sparse_categorical_accuracy: 0.9740
455/469 [============================>.] - ETA: 0s - loss: 0.0919 - sparse_categorical_accuracy: 0.9741
467/469 [============================>.] - ETA: 0s - loss: 0.0914 - sparse_categorical_accuracy: 0.9742
469/469 [==============================] - 2s 4ms/step - loss: 0.0913 - sparse_categorical_accuracy: 0.9742 - val_loss: 0.0958 - val_sparse_categorical_accuracy: 0.9715
Epoch 5/6

  1/469 [..............................] - ETA: 28s - loss: 0.0287 - sparse_categorical_accuracy: 1.0000
 13/469 [..............................] - ETA: 2s - loss: 0.0824 - sparse_categorical_accuracy: 0.9766 
 24/469 [>.............................] - ETA: 2s - loss: 0.0898 - sparse_categorical_accuracy: 0.9756
 37/469 [=>............................] - ETA: 1s - loss: 0.0825 - sparse_categorical_accuracy: 0.9776
 49/469 [==>...........................] - ETA: 1s - loss: 0.0828 - sparse_categorical_accuracy: 0.9774
 60/469 [==>...........................] - ETA: 1s - loss: 0.0800 - sparse_categorical_accuracy: 0.9784
 72/469 [===>..........................] - ETA: 1s - loss: 0.0812 - sparse_categorical_accuracy: 0.9784
 85/469 [====>.........................] - ETA: 1s - loss: 0.0830 - sparse_categorical_accuracy: 0.9772
 98/469 [=====>........................] - ETA: 1s - loss: 0.0818 - sparse_categorical_accuracy: 0.9777
112/469 [======>.......................] - ETA: 1s - loss: 0.0811 - sparse_categorical_accuracy: 0.9778
125/469 [======>.......................] - ETA: 1s - loss: 0.0787 - sparse_categorical_accuracy: 0.9786
138/469 [=======>......................] - ETA: 1s - loss: 0.0772 - sparse_categorical_accuracy: 0.9789
151/469 [========>.....................] - ETA: 1s - loss: 0.0779 - sparse_categorical_accuracy: 0.9784
165/469 [=========>....................] - ETA: 1s - loss: 0.0775 - sparse_categorical_accuracy: 0.9782
180/469 [==========>...................] - ETA: 1s - loss: 0.0766 - sparse_categorical_accuracy: 0.9782
195/469 [===========>..................] - ETA: 1s - loss: 0.0765 - sparse_categorical_accuracy: 0.9780
209/469 [============>.................] - ETA: 1s - loss: 0.0767 - sparse_categorical_accuracy: 0.9778
223/469 [=============>................] - ETA: 0s - loss: 0.0765 - sparse_categorical_accuracy: 0.9779
236/469 [==============>...............] - ETA: 0s - loss: 0.0762 - sparse_categorical_accuracy: 0.9782
249/469 [==============>...............] - ETA: 0s - loss: 0.0759 - sparse_categorical_accuracy: 0.9783
260/469 [===============>..............] - ETA: 0s - loss: 0.0760 - sparse_categorical_accuracy: 0.9783
274/469 [================>.............] - ETA: 0s - loss: 0.0753 - sparse_categorical_accuracy: 0.9785
286/469 [=================>............] - ETA: 0s - loss: 0.0753 - sparse_categorical_accuracy: 0.9786
299/469 [==================>...........] - ETA: 0s - loss: 0.0750 - sparse_categorical_accuracy: 0.9785
312/469 [==================>...........] - ETA: 0s - loss: 0.0749 - sparse_categorical_accuracy: 0.9785
325/469 [===================>..........] - ETA: 0s - loss: 0.0753 - sparse_categorical_accuracy: 0.9785
337/469 [====================>.........] - ETA: 0s - loss: 0.0755 - sparse_categorical_accuracy: 0.9783
348/469 [=====================>........] - ETA: 0s - loss: 0.0749 - sparse_categorical_accuracy: 0.9785
358/469 [=====================>........] - ETA: 0s - loss: 0.0746 - sparse_categorical_accuracy: 0.9786
369/469 [======================>.......] - ETA: 0s - loss: 0.0742 - sparse_categorical_accuracy: 0.9787
381/469 [=======================>......] - ETA: 0s - loss: 0.0742 - sparse_categorical_accuracy: 0.9788
393/469 [========================>.....] - ETA: 0s - loss: 0.0737 - sparse_categorical_accuracy: 0.9789
405/469 [========================>.....] - ETA: 0s - loss: 0.0739 - sparse_categorical_accuracy: 0.9789
418/469 [=========================>....] - ETA: 0s - loss: 0.0738 - sparse_categorical_accuracy: 0.9788
430/469 [==========================>...] - ETA: 0s - loss: 0.0735 - sparse_categorical_accuracy: 0.9788
442/469 [===========================>..] - ETA: 0s - loss: 0.0737 - sparse_categorical_accuracy: 0.9788
454/469 [============================>.] - ETA: 0s - loss: 0.0735 - sparse_categorical_accuracy: 0.9788
464/469 [============================>.] - ETA: 0s - loss: 0.0735 - sparse_categorical_accuracy: 0.9788
469/469 [==============================] - 2s 5ms/step - loss: 0.0737 - sparse_categorical_accuracy: 0.9788 - val_loss: 0.0925 - val_sparse_categorical_accuracy: 0.9704
Epoch 6/6

  1/469 [..............................] - ETA: 32s - loss: 0.0402 - sparse_categorical_accuracy: 0.9844
 13/469 [..............................] - ETA: 1s - loss: 0.0595 - sparse_categorical_accuracy: 0.9826 
 29/469 [>.............................] - ETA: 1s - loss: 0.0568 - sparse_categorical_accuracy: 0.9844
 44/469 [=>............................] - ETA: 1s - loss: 0.0546 - sparse_categorical_accuracy: 0.9853
 59/469 [==>...........................] - ETA: 1s - loss: 0.0558 - sparse_categorical_accuracy: 0.9856
 72/469 [===>..........................] - ETA: 1s - loss: 0.0577 - sparse_categorical_accuracy: 0.9850
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172/469 [==========>...................] - ETA: 1s - loss: 0.0590 - sparse_categorical_accuracy: 0.9834
181/469 [==========>...................] - ETA: 1s - loss: 0.0594 - sparse_categorical_accuracy: 0.9834
190/469 [===========>..................] - ETA: 1s - loss: 0.0600 - sparse_categorical_accuracy: 0.9833
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246/469 [==============>...............] - ETA: 1s - loss: 0.0590 - sparse_categorical_accuracy: 0.9834
255/469 [===============>..............] - ETA: 1s - loss: 0.0597 - sparse_categorical_accuracy: 0.9833
264/469 [===============>..............] - ETA: 0s - loss: 0.0595 - sparse_categorical_accuracy: 0.9833
270/469 [================>.............] - ETA: 0s - loss: 0.0591 - sparse_categorical_accuracy: 0.9834
279/469 [================>.............] - ETA: 0s - loss: 0.0590 - sparse_categorical_accuracy: 0.9835
288/469 [=================>............] - ETA: 0s - loss: 0.0592 - sparse_categorical_accuracy: 0.9834
298/469 [==================>...........] - ETA: 0s - loss: 0.0595 - sparse_categorical_accuracy: 0.9832
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318/469 [===================>..........] - ETA: 0s - loss: 0.0594 - sparse_categorical_accuracy: 0.9831
330/469 [====================>.........] - ETA: 0s - loss: 0.0599 - sparse_categorical_accuracy: 0.9831
342/469 [====================>.........] - ETA: 0s - loss: 0.0603 - sparse_categorical_accuracy: 0.9828
352/469 [=====================>........] - ETA: 0s - loss: 0.0607 - sparse_categorical_accuracy: 0.9827
362/469 [======================>.......] - ETA: 0s - loss: 0.0612 - sparse_categorical_accuracy: 0.9824
373/469 [======================>.......] - ETA: 0s - loss: 0.0608 - sparse_categorical_accuracy: 0.9825
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403/469 [========================>.....] - ETA: 0s - loss: 0.0611 - sparse_categorical_accuracy: 0.9828
413/469 [=========================>....] - ETA: 0s - loss: 0.0612 - sparse_categorical_accuracy: 0.9827
424/469 [==========================>...] - ETA: 0s - loss: 0.0613 - sparse_categorical_accuracy: 0.9826
434/469 [==========================>...] - ETA: 0s - loss: 0.0614 - sparse_categorical_accuracy: 0.9826
444/469 [===========================>..] - ETA: 0s - loss: 0.0614 - sparse_categorical_accuracy: 0.9826
454/469 [============================>.] - ETA: 0s - loss: 0.0612 - sparse_categorical_accuracy: 0.9827
464/469 [============================>.] - ETA: 0s - loss: 0.0614 - sparse_categorical_accuracy: 0.9826
469/469 [==============================] - 3s 6ms/step - loss: 0.0617 - sparse_categorical_accuracy: 0.9825 - val_loss: 0.0876 - val_sparse_categorical_accuracy: 0.9734
