This repository was archived by the owner on Jul 27, 2022. It is now read-only.
-
Notifications
You must be signed in to change notification settings - Fork 7
Expand file tree
/
Copy pathcollapse.out
More file actions
1794 lines (1794 loc) · 120 KB
/
collapse.out
File metadata and controls
1794 lines (1794 loc) · 120 KB
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
nohup: ignoring input
PID: 50001
Requested load from: cl_traintest_collapse.ini
Config files found: ['debug.ini', 'test_enfnet.ini', 'dcgan.ini', 'test_resnet.ini', 'best_resnet_traintest_hitarray.ini', 'best_resnet_traintest_hitarray_egammaonly.ini', 'cl_traintest_collapse.ini', 'test.ini', 'test_convnet.ini', 'best_resnet_long_test.ini', 'test_kazunet.ini', 'best_resnet_traintest_hitarray_postveto.ini', 'best_resnet_traintest.ini', 'best_resnet.ini']
Loading from cl_traintest_collapse.ini
cl_traintest_collapse.ini loaded!
Params OK: {'num_input_channels': 19, 'num_latent_dims': 128, 'arch_key': 1, 'arch_depth': 18, 'num_classes': 2, 'train_all': 1}
Requesting GPUs. GPU list : [0, 1]
Main GPU : cuda:0
Using DataParallel on these devices: ['cuda:0', 'cuda:1']
CUDA is available
Loading training indices from: /fast_scratch/WatChMaL/data/IWCD_fulltank_300_post_veto_nomichel_pe_idxs.npz
Loading validation indices from: /fast_scratch/WatChMaL/data/IWCD_fulltank_300_post_veto_nomichel_pe_idxs.npz
Loading test indices from: /fast_scratch/WatChMaL/data/IWCD_fulltank_300_post_veto_nomichel_pe_idxs.npz
Creating a directory for run dump at : dumps/20200731_151243/
Saving config file as dumps/20200731_151243/config_file.ini
Config file saved at dumps/20200731_151243/config_file.ini
Entire model parameters passed to the optimizer
Validation Interval: 10
Epoch 0 Starting @ 2020-07-31 15:12:44
... Iteration 10 ... Epoch 0.00 ... Loss 0.645 ... Accuracy 0.676
... Iteration 20 ... Epoch 0.00 ... Loss 0.632 ... Accuracy 0.701
... Iteration 30 ... Epoch 0.01 ... Loss 0.625 ... Accuracy 0.697
... Iteration 40 ... Epoch 0.01 ... Loss 0.615 ... Accuracy 0.711
... Iteration 50 ... Epoch 0.01 ... Loss 0.592 ... Accuracy 0.754
... Iteration 60 ... Epoch 0.01 ... Loss 0.588 ... Accuracy 0.713
... Iteration 70 ... Epoch 0.01 ... Loss 0.568 ... Accuracy 0.715
... Iteration 80 ... Epoch 0.01 ... Loss 0.535 ... Accuracy 0.725
... Iteration 90 ... Epoch 0.02 ... Loss 0.460 ... Accuracy 0.766
... Iteration 100 ... Epoch 0.02 ... Loss 0.480 ... Accuracy 0.723
... Iteration 110 ... Epoch 0.02 ... Loss 0.448 ... Accuracy 0.697
... Iteration 120 ... Epoch 0.02 ... Loss 0.407 ... Accuracy 0.732
... Iteration 130 ... Epoch 0.02 ... Loss 0.449 ... Accuracy 0.688
... Iteration 140 ... Epoch 0.03 ... Loss 0.375 ... Accuracy 0.734
... Iteration 150 ... Epoch 0.03 ... Loss 0.378 ... Accuracy 0.709
... Iteration 160 ... Epoch 0.03 ... Loss 0.411 ... Accuracy 0.711
... Iteration 170 ... Epoch 0.03 ... Loss 0.346 ... Accuracy 0.711
... Iteration 180 ... Epoch 0.03 ... Loss 0.372 ... Accuracy 0.695
... Iteration 190 ... Epoch 0.03 ... Loss 0.352 ... Accuracy 0.732
... Iteration 200 ... Epoch 0.04 ... Loss 0.339 ... Accuracy 0.719
... Iteration 210 ... Epoch 0.04 ... Loss 0.323 ... Accuracy 0.715
... Iteration 220 ... Epoch 0.04 ... Loss 0.345 ... Accuracy 0.705
... Iteration 230 ... Epoch 0.04 ... Loss 0.361 ... Accuracy 0.695
... Iteration 240 ... Epoch 0.04 ... Loss 0.336 ... Accuracy 0.719
... Iteration 250 ... Epoch 0.05 ... Loss 0.365 ... Accuracy 0.676
... Iteration 260 ... Epoch 0.05 ... Loss 0.284 ... Accuracy 0.748
... Iteration 270 ... Epoch 0.05 ... Loss 0.293 ... Accuracy 0.738
... Iteration 280 ... Epoch 0.05 ... Loss 0.311 ... Accuracy 0.744
... Iteration 290 ... Epoch 0.05 ... Loss 0.295 ... Accuracy 0.857
... Iteration 300 ... Epoch 0.06 ... Loss 0.256 ... Accuracy 0.914
... Iteration 310 ... Epoch 0.06 ... Loss 0.287 ... Accuracy 0.912
... Iteration 320 ... Epoch 0.06 ... Loss 0.244 ... Accuracy 0.924
... Iteration 330 ... Epoch 0.06 ... Loss 0.237 ... Accuracy 0.912
... Iteration 340 ... Epoch 0.06 ... Loss 0.224 ... Accuracy 0.918
... Iteration 350 ... Epoch 0.06 ... Loss 0.208 ... Accuracy 0.949
... Iteration 360 ... Epoch 0.07 ... Loss 0.184 ... Accuracy 0.934
... Iteration 370 ... Epoch 0.07 ... Loss 0.170 ... Accuracy 0.939
... Iteration 380 ... Epoch 0.07 ... Loss 0.143 ... Accuracy 0.943
... Iteration 390 ... Epoch 0.07 ... Loss 0.142 ... Accuracy 0.938
... Iteration 400 ... Epoch 0.07 ... Loss 0.129 ... Accuracy 0.949
... Iteration 410 ... Epoch 0.08 ... Loss 0.136 ... Accuracy 0.936
... Iteration 420 ... Epoch 0.08 ... Loss 0.112 ... Accuracy 0.957
... Iteration 430 ... Epoch 0.08 ... Loss 0.149 ... Accuracy 0.939
... Iteration 440 ... Epoch 0.08 ... Loss 0.124 ... Accuracy 0.949
... Iteration 450 ... Epoch 0.08 ... Loss 0.170 ... Accuracy 0.926
... Iteration 460 ... Epoch 0.08 ... Loss 0.105 ... Accuracy 0.967
... Iteration 470 ... Epoch 0.09 ... Loss 0.104 ... Accuracy 0.967
... Iteration 480 ... Epoch 0.09 ... Loss 0.127 ... Accuracy 0.943
... Iteration 490 ... Epoch 0.09 ... Loss 0.101 ... Accuracy 0.963
... Iteration 500 ... Epoch 0.09 ... Loss 0.126 ... Accuracy 0.955
... Iteration 510 ... Epoch 0.09 ... Loss 0.111 ... Accuracy 0.949
... Iteration 520 ... Epoch 0.10 ... Loss 0.100 ... Accuracy 0.961
... Iteration 530 ... Epoch 0.10 ... Loss 0.083 ... Accuracy 0.969
... Iteration 540 ... Epoch 0.10 ... Loss 0.095 ... Accuracy 0.961
... Iteration 550 ... Epoch 0.10 ... Loss 0.112 ... Accuracy 0.953
... Iteration 560 ... Epoch 0.10 ... Loss 0.081 ... Accuracy 0.971
... Iteration 570 ... Epoch 0.10 ... Loss 0.100 ... Accuracy 0.961
... Iteration 580 ... Epoch 0.11 ... Loss 0.147 ... Accuracy 0.934
... Iteration 590 ... Epoch 0.11 ... Loss 0.108 ... Accuracy 0.961
... Iteration 600 ... Epoch 0.11 ... Loss 0.132 ... Accuracy 0.945
... Iteration 610 ... Epoch 0.11 ... Loss 0.111 ... Accuracy 0.949
... Iteration 620 ... Epoch 0.11 ... Loss 0.126 ... Accuracy 0.953
... Iteration 630 ... Epoch 0.12 ... Loss 0.127 ... Accuracy 0.947
... Iteration 640 ... Epoch 0.12 ... Loss 0.111 ... Accuracy 0.951
... Iteration 650 ... Epoch 0.12 ... Loss 0.113 ... Accuracy 0.947
... Iteration 660 ... Epoch 0.12 ... Loss 0.122 ... Accuracy 0.955
... Iteration 670 ... Epoch 0.12 ... Loss 0.118 ... Accuracy 0.957
... Iteration 680 ... Epoch 0.13 ... Loss 0.123 ... Accuracy 0.947
... Iteration 690 ... Epoch 0.13 ... Loss 0.132 ... Accuracy 0.945
... Iteration 700 ... Epoch 0.13 ... Loss 0.090 ... Accuracy 0.965
... Iteration 710 ... Epoch 0.13 ... Loss 0.126 ... Accuracy 0.955
... Iteration 720 ... Epoch 0.13 ... Loss 0.097 ... Accuracy 0.969
... Iteration 730 ... Epoch 0.13 ... Loss 0.093 ... Accuracy 0.973
... Iteration 740 ... Epoch 0.14 ... Loss 0.099 ... Accuracy 0.969
... Iteration 750 ... Epoch 0.14 ... Loss 0.075 ... Accuracy 0.980
... Iteration 760 ... Epoch 0.14 ... Loss 0.088 ... Accuracy 0.967
... Iteration 770 ... Epoch 0.14 ... Loss 0.125 ... Accuracy 0.945
... Iteration 780 ... Epoch 0.14 ... Loss 0.117 ... Accuracy 0.947
... Iteration 790 ... Epoch 0.15 ... Loss 0.100 ... Accuracy 0.961
... Iteration 800 ... Epoch 0.15 ... Loss 0.098 ... Accuracy 0.959
... Iteration 810 ... Epoch 0.15 ... Loss 0.111 ... Accuracy 0.953
... Iteration 820 ... Epoch 0.15 ... Loss 0.118 ... Accuracy 0.949
... Iteration 830 ... Epoch 0.15 ... Loss 0.084 ... Accuracy 0.969
... Iteration 840 ... Epoch 0.15 ... Loss 0.100 ... Accuracy 0.953
... Iteration 850 ... Epoch 0.16 ... Loss 0.117 ... Accuracy 0.949
... Iteration 860 ... Epoch 0.16 ... Loss 0.068 ... Accuracy 0.982
... Iteration 870 ... Epoch 0.16 ... Loss 0.107 ... Accuracy 0.953
... Iteration 880 ... Epoch 0.16 ... Loss 0.094 ... Accuracy 0.959
... Iteration 890 ... Epoch 0.16 ... Loss 0.091 ... Accuracy 0.959
... Iteration 900 ... Epoch 0.17 ... Loss 0.118 ... Accuracy 0.953
... Iteration 910 ... Epoch 0.17 ... Loss 0.105 ... Accuracy 0.953
... Iteration 920 ... Epoch 0.17 ... Loss 0.119 ... Accuracy 0.947
... Iteration 930 ... Epoch 0.17 ... Loss 0.083 ... Accuracy 0.973
... Iteration 940 ... Epoch 0.17 ... Loss 0.107 ... Accuracy 0.953
... Iteration 950 ... Epoch 0.17 ... Loss 0.104 ... Accuracy 0.963
... Iteration 960 ... Epoch 0.18 ... Loss 0.094 ... Accuracy 0.959
... Iteration 970 ... Epoch 0.18 ... Loss 0.083 ... Accuracy 0.963
... Iteration 980 ... Epoch 0.18 ... Loss 0.097 ... Accuracy 0.955
... Iteration 990 ... Epoch 0.18 ... Loss 0.107 ... Accuracy 0.955
... Iteration 1000 ... Epoch 0.18 ... Loss 0.128 ... Accuracy 0.949
... Iteration 1010 ... Epoch 0.19 ... Loss 0.138 ... Accuracy 0.936
... Iteration 1020 ... Epoch 0.19 ... Loss 0.076 ... Accuracy 0.967
... Iteration 1030 ... Epoch 0.19 ... Loss 0.078 ... Accuracy 0.967
... Iteration 1040 ... Epoch 0.19 ... Loss 0.077 ... Accuracy 0.973
... Iteration 1050 ... Epoch 0.19 ... Loss 0.104 ... Accuracy 0.957
... Iteration 1060 ... Epoch 0.20 ... Loss 0.062 ... Accuracy 0.975
... Iteration 1070 ... Epoch 0.20 ... Loss 0.102 ... Accuracy 0.957
... Iteration 1080 ... Epoch 0.20 ... Loss 0.139 ... Accuracy 0.934
... Iteration 1090 ... Epoch 0.20 ... Loss 0.103 ... Accuracy 0.957
... Iteration 1100 ... Epoch 0.20 ... Loss 0.084 ... Accuracy 0.965
... Iteration 1110 ... Epoch 0.20 ... Loss 0.111 ... Accuracy 0.955
... Iteration 1120 ... Epoch 0.21 ... Loss 0.083 ... Accuracy 0.977
... Iteration 1130 ... Epoch 0.21 ... Loss 0.078 ... Accuracy 0.965
... Iteration 1140 ... Epoch 0.21 ... Loss 0.120 ... Accuracy 0.949
... Iteration 1150 ... Epoch 0.21 ... Loss 0.108 ... Accuracy 0.955
... Iteration 1160 ... Epoch 0.21 ... Loss 0.093 ... Accuracy 0.963
... Iteration 1170 ... Epoch 0.22 ... Loss 0.109 ... Accuracy 0.955
... Iteration 1180 ... Epoch 0.22 ... Loss 0.077 ... Accuracy 0.969
... Iteration 1190 ... Epoch 0.22 ... Loss 0.078 ... Accuracy 0.973
... Iteration 1200 ... Epoch 0.22 ... Loss 0.108 ... Accuracy 0.951
... Iteration 1210 ... Epoch 0.22 ... Loss 0.080 ... Accuracy 0.971
... Iteration 1220 ... Epoch 0.22 ... Loss 0.080 ... Accuracy 0.969
... Iteration 1230 ... Epoch 0.23 ... Loss 0.128 ... Accuracy 0.957
... Iteration 1240 ... Epoch 0.23 ... Loss 0.102 ... Accuracy 0.953
... Iteration 1250 ... Epoch 0.23 ... Loss 0.072 ... Accuracy 0.967
... Iteration 1260 ... Epoch 0.23 ... Loss 0.116 ... Accuracy 0.961
... Iteration 1270 ... Epoch 0.23 ... Loss 0.067 ... Accuracy 0.977
... Iteration 1280 ... Epoch 0.24 ... Loss 0.077 ... Accuracy 0.969
... Iteration 1290 ... Epoch 0.24 ... Loss 0.051 ... Accuracy 0.979
... Iteration 1300 ... Epoch 0.24 ... Loss 0.105 ... Accuracy 0.959
... Iteration 1310 ... Epoch 0.24 ... Loss 0.103 ... Accuracy 0.957
... Iteration 1320 ... Epoch 0.24 ... Loss 0.122 ... Accuracy 0.955
... Iteration 1330 ... Epoch 0.24 ... Loss 0.089 ... Accuracy 0.955
... Iteration 1340 ... Epoch 0.25 ... Loss 0.130 ... Accuracy 0.953
... Iteration 1350 ... Epoch 0.25 ... Loss 0.084 ... Accuracy 0.965
... Iteration 1360 ... Epoch 0.25 ... Loss 0.075 ... Accuracy 0.969
... Iteration 1370 ... Epoch 0.25 ... Loss 0.081 ... Accuracy 0.963
... Iteration 1380 ... Epoch 0.25 ... Loss 0.082 ... Accuracy 0.967
... Iteration 1390 ... Epoch 0.26 ... Loss 0.071 ... Accuracy 0.975
... Iteration 1400 ... Epoch 0.26 ... Loss 0.077 ... Accuracy 0.969
... Iteration 1410 ... Epoch 0.26 ... Loss 0.080 ... Accuracy 0.969
... Iteration 1420 ... Epoch 0.26 ... Loss 0.092 ... Accuracy 0.957
... Iteration 1430 ... Epoch 0.26 ... Loss 0.091 ... Accuracy 0.955
... Iteration 1440 ... Epoch 0.27 ... Loss 0.067 ... Accuracy 0.975
... Iteration 1450 ... Epoch 0.27 ... Loss 0.075 ... Accuracy 0.971
... Iteration 1460 ... Epoch 0.27 ... Loss 0.094 ... Accuracy 0.971
... Iteration 1470 ... Epoch 0.27 ... Loss 0.063 ... Accuracy 0.977
... Iteration 1480 ... Epoch 0.27 ... Loss 0.102 ... Accuracy 0.971
... Iteration 1490 ... Epoch 0.27 ... Loss 0.100 ... Accuracy 0.959
... Iteration 1500 ... Epoch 0.28 ... Loss 0.095 ... Accuracy 0.961
... Iteration 1510 ... Epoch 0.28 ... Loss 0.073 ... Accuracy 0.977
... Iteration 1520 ... Epoch 0.28 ... Loss 0.096 ... Accuracy 0.961
... Iteration 1530 ... Epoch 0.28 ... Loss 0.086 ... Accuracy 0.969
... Iteration 1540 ... Epoch 0.28 ... Loss 0.093 ... Accuracy 0.955
... Iteration 1550 ... Epoch 0.29 ... Loss 0.093 ... Accuracy 0.965
... Iteration 1560 ... Epoch 0.29 ... Loss 0.085 ... Accuracy 0.971
... Iteration 1570 ... Epoch 0.29 ... Loss 0.101 ... Accuracy 0.957
... Iteration 1580 ... Epoch 0.29 ... Loss 0.117 ... Accuracy 0.961
... Iteration 1590 ... Epoch 0.29 ... Loss 0.090 ... Accuracy 0.963
... Iteration 1600 ... Epoch 0.29 ... Loss 0.063 ... Accuracy 0.969
... Iteration 1610 ... Epoch 0.30 ... Loss 0.066 ... Accuracy 0.979
... Iteration 1620 ... Epoch 0.30 ... Loss 0.093 ... Accuracy 0.959
... Iteration 1630 ... Epoch 0.30 ... Loss 0.128 ... Accuracy 0.955
... Iteration 1640 ... Epoch 0.30 ... Loss 0.123 ... Accuracy 0.951
... Iteration 1650 ... Epoch 0.30 ... Loss 0.095 ... Accuracy 0.967
... Iteration 1660 ... Epoch 0.31 ... Loss 0.072 ... Accuracy 0.975
... Iteration 1670 ... Epoch 0.31 ... Loss 0.095 ... Accuracy 0.955
... Iteration 1680 ... Epoch 0.31 ... Loss 0.107 ... Accuracy 0.955
... Iteration 1690 ... Epoch 0.31 ... Loss 0.092 ... Accuracy 0.963
... Iteration 1700 ... Epoch 0.31 ... Loss 0.078 ... Accuracy 0.967
... Iteration 1710 ... Epoch 0.31 ... Loss 0.094 ... Accuracy 0.953
... Iteration 1720 ... Epoch 0.32 ... Loss 0.068 ... Accuracy 0.973
... Iteration 1730 ... Epoch 0.32 ... Loss 0.054 ... Accuracy 0.980
... Iteration 1740 ... Epoch 0.32 ... Loss 0.095 ... Accuracy 0.969
... Iteration 1750 ... Epoch 0.32 ... Loss 0.102 ... Accuracy 0.959
... Iteration 1760 ... Epoch 0.32 ... Loss 0.081 ... Accuracy 0.975
... Iteration 1770 ... Epoch 0.33 ... Loss 0.075 ... Accuracy 0.973
... Iteration 1780 ... Epoch 0.33 ... Loss 0.088 ... Accuracy 0.965
... Iteration 1790 ... Epoch 0.33 ... Loss 0.072 ... Accuracy 0.973
... Iteration 1800 ... Epoch 0.33 ... Loss 0.066 ... Accuracy 0.975
... Iteration 1810 ... Epoch 0.33 ... Loss 0.075 ... Accuracy 0.971
... Iteration 1820 ... Epoch 0.34 ... Loss 0.078 ... Accuracy 0.975
... Iteration 1830 ... Epoch 0.34 ... Loss 0.080 ... Accuracy 0.965
... Iteration 1840 ... Epoch 0.34 ... Loss 0.074 ... Accuracy 0.975
... Iteration 1850 ... Epoch 0.34 ... Loss 0.082 ... Accuracy 0.971
... Iteration 1860 ... Epoch 0.34 ... Loss 0.053 ... Accuracy 0.982
... Iteration 1870 ... Epoch 0.34 ... Loss 0.062 ... Accuracy 0.977
... Iteration 1880 ... Epoch 0.35 ... Loss 0.062 ... Accuracy 0.980
... Iteration 1890 ... Epoch 0.35 ... Loss 0.079 ... Accuracy 0.967
... Iteration 1900 ... Epoch 0.35 ... Loss 0.091 ... Accuracy 0.953
... Iteration 1910 ... Epoch 0.35 ... Loss 0.077 ... Accuracy 0.969
... Iteration 1920 ... Epoch 0.35 ... Loss 0.073 ... Accuracy 0.971
... Iteration 1930 ... Epoch 0.36 ... Loss 0.092 ... Accuracy 0.963
... Iteration 1940 ... Epoch 0.36 ... Loss 0.082 ... Accuracy 0.973
... Iteration 1950 ... Epoch 0.36 ... Loss 0.072 ... Accuracy 0.965
... Iteration 1960 ... Epoch 0.36 ... Loss 0.079 ... Accuracy 0.977
... Iteration 1970 ... Epoch 0.36 ... Loss 0.104 ... Accuracy 0.949
... Iteration 1980 ... Epoch 0.36 ... Loss 0.070 ... Accuracy 0.971
... Iteration 1990 ... Epoch 0.37 ... Loss 0.082 ... Accuracy 0.963
... Iteration 2000 ... Epoch 0.37 ... Loss 0.089 ... Accuracy 0.965
... Iteration 2010 ... Epoch 0.37 ... Loss 0.118 ... Accuracy 0.957
... Iteration 2020 ... Epoch 0.37 ... Loss 0.075 ... Accuracy 0.967
... Iteration 2030 ... Epoch 0.37 ... Loss 0.065 ... Accuracy 0.971
... Iteration 2040 ... Epoch 0.38 ... Loss 0.064 ... Accuracy 0.975
... Iteration 2050 ... Epoch 0.38 ... Loss 0.066 ... Accuracy 0.977
... Iteration 2060 ... Epoch 0.38 ... Loss 0.068 ... Accuracy 0.975
... Iteration 2070 ... Epoch 0.38 ... Loss 0.069 ... Accuracy 0.977
... Iteration 2080 ... Epoch 0.38 ... Loss 0.090 ... Accuracy 0.965
... Iteration 2090 ... Epoch 0.38 ... Loss 0.089 ... Accuracy 0.963
... Iteration 2100 ... Epoch 0.39 ... Loss 0.062 ... Accuracy 0.979
... Iteration 2110 ... Epoch 0.39 ... Loss 0.067 ... Accuracy 0.975
... Iteration 2120 ... Epoch 0.39 ... Loss 0.076 ... Accuracy 0.980
... Iteration 2130 ... Epoch 0.39 ... Loss 0.070 ... Accuracy 0.979
... Iteration 2140 ... Epoch 0.39 ... Loss 0.086 ... Accuracy 0.969
... Iteration 2150 ... Epoch 0.40 ... Loss 0.065 ... Accuracy 0.979
... Iteration 2160 ... Epoch 0.40 ... Loss 0.061 ... Accuracy 0.971
... Iteration 2170 ... Epoch 0.40 ... Loss 0.089 ... Accuracy 0.963
... Iteration 2180 ... Epoch 0.40 ... Loss 0.085 ... Accuracy 0.975
... Iteration 2190 ... Epoch 0.40 ... Loss 0.067 ... Accuracy 0.980
... Iteration 2200 ... Epoch 0.41 ... Loss 0.052 ... Accuracy 0.982
... Iteration 2210 ... Epoch 0.41 ... Loss 0.066 ... Accuracy 0.975
... Iteration 2220 ... Epoch 0.41 ... Loss 0.105 ... Accuracy 0.955
... Iteration 2230 ... Epoch 0.41 ... Loss 0.092 ... Accuracy 0.961
... Iteration 2240 ... Epoch 0.41 ... Loss 0.049 ... Accuracy 0.986
... Iteration 2250 ... Epoch 0.41 ... Loss 0.079 ... Accuracy 0.973
... Iteration 2260 ... Epoch 0.42 ... Loss 0.069 ... Accuracy 0.980
... Iteration 2270 ... Epoch 0.42 ... Loss 0.067 ... Accuracy 0.975
... Iteration 2280 ... Epoch 0.42 ... Loss 0.095 ... Accuracy 0.967
... Iteration 2290 ... Epoch 0.42 ... Loss 0.075 ... Accuracy 0.963
... Iteration 2300 ... Epoch 0.42 ... Loss 0.073 ... Accuracy 0.967
... Iteration 2310 ... Epoch 0.43 ... Loss 0.053 ... Accuracy 0.979
... Iteration 2320 ... Epoch 0.43 ... Loss 0.072 ... Accuracy 0.975
... Iteration 2330 ... Epoch 0.43 ... Loss 0.081 ... Accuracy 0.971
... Iteration 2340 ... Epoch 0.43 ... Loss 0.084 ... Accuracy 0.959
... Iteration 2350 ... Epoch 0.43 ... Loss 0.066 ... Accuracy 0.969
... Iteration 2360 ... Epoch 0.43 ... Loss 0.062 ... Accuracy 0.977
... Iteration 2370 ... Epoch 0.44 ... Loss 0.083 ... Accuracy 0.961
... Iteration 2380 ... Epoch 0.44 ... Loss 0.085 ... Accuracy 0.969
... Iteration 2390 ... Epoch 0.44 ... Loss 0.057 ... Accuracy 0.980
... Iteration 2400 ... Epoch 0.44 ... Loss 0.058 ... Accuracy 0.969
... Iteration 2410 ... Epoch 0.44 ... Loss 0.077 ... Accuracy 0.969
... Iteration 2420 ... Epoch 0.45 ... Loss 0.080 ... Accuracy 0.963
... Iteration 2430 ... Epoch 0.45 ... Loss 0.103 ... Accuracy 0.959
... Iteration 2440 ... Epoch 0.45 ... Loss 0.100 ... Accuracy 0.953
... Iteration 2450 ... Epoch 0.45 ... Loss 0.069 ... Accuracy 0.971
... Iteration 2460 ... Epoch 0.45 ... Loss 0.088 ... Accuracy 0.975
... Iteration 2470 ... Epoch 0.45 ... Loss 0.083 ... Accuracy 0.963
... Iteration 2480 ... Epoch 0.46 ... Loss 0.076 ... Accuracy 0.965
... Iteration 2490 ... Epoch 0.46 ... Loss 0.116 ... Accuracy 0.957
... Iteration 2500 ... Epoch 0.46 ... Loss 0.099 ... Accuracy 0.967
... Iteration 2510 ... Epoch 0.46 ... Loss 0.082 ... Accuracy 0.967
... Iteration 2520 ... Epoch 0.46 ... Loss 0.064 ... Accuracy 0.982
... Iteration 2530 ... Epoch 0.47 ... Loss 0.105 ... Accuracy 0.963
... Iteration 2540 ... Epoch 0.47 ... Loss 0.083 ... Accuracy 0.967
... Iteration 2550 ... Epoch 0.47 ... Loss 0.061 ... Accuracy 0.979
... Iteration 2560 ... Epoch 0.47 ... Loss 0.084 ... Accuracy 0.961
... Iteration 2570 ... Epoch 0.47 ... Loss 0.097 ... Accuracy 0.971
... Iteration 2580 ... Epoch 0.48 ... Loss 0.047 ... Accuracy 0.986
... Iteration 2590 ... Epoch 0.48 ... Loss 0.086 ... Accuracy 0.969
... Iteration 2600 ... Epoch 0.48 ... Loss 0.069 ... Accuracy 0.969
... Iteration 2610 ... Epoch 0.48 ... Loss 0.051 ... Accuracy 0.977
... Iteration 2620 ... Epoch 0.48 ... Loss 0.081 ... Accuracy 0.973
... Iteration 2630 ... Epoch 0.48 ... Loss 0.054 ... Accuracy 0.982
... Iteration 2640 ... Epoch 0.49 ... Loss 0.086 ... Accuracy 0.967
... Iteration 2650 ... Epoch 0.49 ... Loss 0.082 ... Accuracy 0.971
... Iteration 2660 ... Epoch 0.49 ... Loss 0.067 ... Accuracy 0.982
... Iteration 2670 ... Epoch 0.49 ... Loss 0.058 ... Accuracy 0.979
... Iteration 2680 ... Epoch 0.49 ... Loss 0.077 ... Accuracy 0.975
... Iteration 2690 ... Epoch 0.50 ... Loss 0.067 ... Accuracy 0.971
... Iteration 2700 ... Epoch 0.50 ... Loss 0.090 ... Accuracy 0.967
... Iteration 2710 ... Epoch 0.50 ... Loss 0.077 ... Accuracy 0.969
... Iteration 2720 ... Epoch 0.50 ... Loss 0.043 ... Accuracy 0.980
... Iteration 2730 ... Epoch 0.50 ... Loss 0.063 ... Accuracy 0.977
... Iteration 2740 ... Epoch 0.50 ... Loss 0.064 ... Accuracy 0.973
... Iteration 2750 ... Epoch 0.51 ... Loss 0.095 ... Accuracy 0.957
... Iteration 2760 ... Epoch 0.51 ... Loss 0.076 ... Accuracy 0.979
... Iteration 2770 ... Epoch 0.51 ... Loss 0.059 ... Accuracy 0.984
... Iteration 2780 ... Epoch 0.51 ... Loss 0.080 ... Accuracy 0.963
... Iteration 2790 ... Epoch 0.51 ... Loss 0.083 ... Accuracy 0.969
... Iteration 2800 ... Epoch 0.52 ... Loss 0.082 ... Accuracy 0.965
... Iteration 2810 ... Epoch 0.52 ... Loss 0.089 ... Accuracy 0.973
... Iteration 2820 ... Epoch 0.52 ... Loss 0.058 ... Accuracy 0.986
... Iteration 2830 ... Epoch 0.52 ... Loss 0.047 ... Accuracy 0.986
... Iteration 2840 ... Epoch 0.52 ... Loss 0.068 ... Accuracy 0.977
... Iteration 2850 ... Epoch 0.52 ... Loss 0.076 ... Accuracy 0.969
... Iteration 2860 ... Epoch 0.53 ... Loss 0.075 ... Accuracy 0.967
... Iteration 2870 ... Epoch 0.53 ... Loss 0.070 ... Accuracy 0.969
... Iteration 2880 ... Epoch 0.53 ... Loss 0.092 ... Accuracy 0.959
... Iteration 2890 ... Epoch 0.53 ... Loss 0.063 ... Accuracy 0.977
... Iteration 2900 ... Epoch 0.53 ... Loss 0.071 ... Accuracy 0.965
... Iteration 2910 ... Epoch 0.54 ... Loss 0.061 ... Accuracy 0.973
... Iteration 2920 ... Epoch 0.54 ... Loss 0.064 ... Accuracy 0.973
... Iteration 2930 ... Epoch 0.54 ... Loss 0.087 ... Accuracy 0.969
... Iteration 2940 ... Epoch 0.54 ... Loss 0.084 ... Accuracy 0.959
... Iteration 2950 ... Epoch 0.54 ... Loss 0.083 ... Accuracy 0.967
... Iteration 2960 ... Epoch 0.55 ... Loss 0.052 ... Accuracy 0.982
... Iteration 2970 ... Epoch 0.55 ... Loss 0.104 ... Accuracy 0.953
... Iteration 2980 ... Epoch 0.55 ... Loss 0.062 ... Accuracy 0.969
... Iteration 2990 ... Epoch 0.55 ... Loss 0.062 ... Accuracy 0.973
... Iteration 3000 ... Epoch 0.55 ... Loss 0.047 ... Accuracy 0.988
... Iteration 3010 ... Epoch 0.55 ... Loss 0.063 ... Accuracy 0.977
... Iteration 3020 ... Epoch 0.56 ... Loss 0.037 ... Accuracy 0.992
... Iteration 3030 ... Epoch 0.56 ... Loss 0.081 ... Accuracy 0.967
... Iteration 3040 ... Epoch 0.56 ... Loss 0.057 ... Accuracy 0.971
... Iteration 3050 ... Epoch 0.56 ... Loss 0.070 ... Accuracy 0.973
... Iteration 3060 ... Epoch 0.56 ... Loss 0.066 ... Accuracy 0.971
... Iteration 3070 ... Epoch 0.57 ... Loss 0.069 ... Accuracy 0.973
... Iteration 3080 ... Epoch 0.57 ... Loss 0.094 ... Accuracy 0.965
... Iteration 3090 ... Epoch 0.57 ... Loss 0.058 ... Accuracy 0.980
... Iteration 3100 ... Epoch 0.57 ... Loss 0.047 ... Accuracy 0.980
... Iteration 3110 ... Epoch 0.57 ... Loss 0.073 ... Accuracy 0.973
... Iteration 3120 ... Epoch 0.57 ... Loss 0.076 ... Accuracy 0.971
... Iteration 3130 ... Epoch 0.58 ... Loss 0.079 ... Accuracy 0.973
... Iteration 3140 ... Epoch 0.58 ... Loss 0.090 ... Accuracy 0.959
... Iteration 3150 ... Epoch 0.58 ... Loss 0.062 ... Accuracy 0.975
... Iteration 3160 ... Epoch 0.58 ... Loss 0.070 ... Accuracy 0.975
... Iteration 3170 ... Epoch 0.58 ... Loss 0.067 ... Accuracy 0.980
... Iteration 3180 ... Epoch 0.59 ... Loss 0.061 ... Accuracy 0.977
... Iteration 3190 ... Epoch 0.59 ... Loss 0.069 ... Accuracy 0.963
... Iteration 3200 ... Epoch 0.59 ... Loss 0.055 ... Accuracy 0.979
... Iteration 3210 ... Epoch 0.59 ... Loss 0.081 ... Accuracy 0.971
... Iteration 3220 ... Epoch 0.59 ... Loss 0.068 ... Accuracy 0.979
... Iteration 3230 ... Epoch 0.59 ... Loss 0.091 ... Accuracy 0.959
... Iteration 3240 ... Epoch 0.60 ... Loss 0.069 ... Accuracy 0.975
... Iteration 3250 ... Epoch 0.60 ... Loss 0.076 ... Accuracy 0.967
... Iteration 3260 ... Epoch 0.60 ... Loss 0.095 ... Accuracy 0.965
... Iteration 3270 ... Epoch 0.60 ... Loss 0.070 ... Accuracy 0.967
... Iteration 3280 ... Epoch 0.60 ... Loss 0.045 ... Accuracy 0.982
... Iteration 3290 ... Epoch 0.61 ... Loss 0.072 ... Accuracy 0.973
... Iteration 3300 ... Epoch 0.61 ... Loss 0.083 ... Accuracy 0.967
... Iteration 3310 ... Epoch 0.61 ... Loss 0.070 ... Accuracy 0.975
... Iteration 3320 ... Epoch 0.61 ... Loss 0.091 ... Accuracy 0.957
... Iteration 3330 ... Epoch 0.61 ... Loss 0.079 ... Accuracy 0.967
... Iteration 3340 ... Epoch 0.61 ... Loss 0.113 ... Accuracy 0.955
... Iteration 3350 ... Epoch 0.62 ... Loss 0.093 ... Accuracy 0.967
... Iteration 3360 ... Epoch 0.62 ... Loss 0.087 ... Accuracy 0.963
... Iteration 3370 ... Epoch 0.62 ... Loss 0.052 ... Accuracy 0.979
... Iteration 3380 ... Epoch 0.62 ... Loss 0.063 ... Accuracy 0.979
... Iteration 3390 ... Epoch 0.62 ... Loss 0.065 ... Accuracy 0.979
... Iteration 3400 ... Epoch 0.63 ... Loss 0.072 ... Accuracy 0.973
... Iteration 3410 ... Epoch 0.63 ... Loss 0.049 ... Accuracy 0.979
... Iteration 3420 ... Epoch 0.63 ... Loss 0.055 ... Accuracy 0.980
... Iteration 3430 ... Epoch 0.63 ... Loss 0.073 ... Accuracy 0.965
... Iteration 3440 ... Epoch 0.63 ... Loss 0.093 ... Accuracy 0.959
... Iteration 3450 ... Epoch 0.64 ... Loss 0.066 ... Accuracy 0.977
... Iteration 3460 ... Epoch 0.64 ... Loss 0.085 ... Accuracy 0.965
... Iteration 3470 ... Epoch 0.64 ... Loss 0.062 ... Accuracy 0.977
... Iteration 3480 ... Epoch 0.64 ... Loss 0.065 ... Accuracy 0.975
... Iteration 3490 ... Epoch 0.64 ... Loss 0.095 ... Accuracy 0.957
... Iteration 3500 ... Epoch 0.64 ... Loss 0.037 ... Accuracy 0.986
... Iteration 3510 ... Epoch 0.65 ... Loss 0.077 ... Accuracy 0.967
... Iteration 3520 ... Epoch 0.65 ... Loss 0.066 ... Accuracy 0.979
... Iteration 3530 ... Epoch 0.65 ... Loss 0.067 ... Accuracy 0.969
... Iteration 3540 ... Epoch 0.65 ... Loss 0.048 ... Accuracy 0.977
... Iteration 3550 ... Epoch 0.65 ... Loss 0.073 ... Accuracy 0.979
... Iteration 3560 ... Epoch 0.66 ... Loss 0.112 ... Accuracy 0.959
... Iteration 3570 ... Epoch 0.66 ... Loss 0.081 ... Accuracy 0.975
... Iteration 3580 ... Epoch 0.66 ... Loss 0.059 ... Accuracy 0.979
... Iteration 3590 ... Epoch 0.66 ... Loss 0.070 ... Accuracy 0.969
... Iteration 3600 ... Epoch 0.66 ... Loss 0.062 ... Accuracy 0.971
... Iteration 3610 ... Epoch 0.66 ... Loss 0.094 ... Accuracy 0.971
... Iteration 3620 ... Epoch 0.67 ... Loss 0.065 ... Accuracy 0.965
... Iteration 3630 ... Epoch 0.67 ... Loss 0.067 ... Accuracy 0.973
... Iteration 3640 ... Epoch 0.67 ... Loss 0.068 ... Accuracy 0.979
... Iteration 3650 ... Epoch 0.67 ... Loss 0.051 ... Accuracy 0.979
... Iteration 3660 ... Epoch 0.67 ... Loss 0.088 ... Accuracy 0.967
... Iteration 3670 ... Epoch 0.68 ... Loss 0.080 ... Accuracy 0.971
... Iteration 3680 ... Epoch 0.68 ... Loss 0.064 ... Accuracy 0.979
... Iteration 3690 ... Epoch 0.68 ... Loss 0.045 ... Accuracy 0.982
... Iteration 3700 ... Epoch 0.68 ... Loss 0.068 ... Accuracy 0.980
... Iteration 3710 ... Epoch 0.68 ... Loss 0.073 ... Accuracy 0.973
... Iteration 3720 ... Epoch 0.68 ... Loss 0.060 ... Accuracy 0.977
... Iteration 3730 ... Epoch 0.69 ... Loss 0.096 ... Accuracy 0.953
... Iteration 3740 ... Epoch 0.69 ... Loss 0.061 ... Accuracy 0.980
... Iteration 3750 ... Epoch 0.69 ... Loss 0.073 ... Accuracy 0.971
... Iteration 3760 ... Epoch 0.69 ... Loss 0.035 ... Accuracy 0.988
... Iteration 3770 ... Epoch 0.69 ... Loss 0.088 ... Accuracy 0.965
... Iteration 3780 ... Epoch 0.70 ... Loss 0.064 ... Accuracy 0.975
... Iteration 3790 ... Epoch 0.70 ... Loss 0.072 ... Accuracy 0.971
... Iteration 3800 ... Epoch 0.70 ... Loss 0.043 ... Accuracy 0.982
... Iteration 3810 ... Epoch 0.70 ... Loss 0.075 ... Accuracy 0.969
... Iteration 3820 ... Epoch 0.70 ... Loss 0.089 ... Accuracy 0.957
... Iteration 3830 ... Epoch 0.71 ... Loss 0.059 ... Accuracy 0.975
... Iteration 3840 ... Epoch 0.71 ... Loss 0.065 ... Accuracy 0.975
... Iteration 3850 ... Epoch 0.71 ... Loss 0.102 ... Accuracy 0.961
... Iteration 3860 ... Epoch 0.71 ... Loss 0.093 ... Accuracy 0.967
... Iteration 3870 ... Epoch 0.71 ... Loss 0.053 ... Accuracy 0.986
... Iteration 3880 ... Epoch 0.71 ... Loss 0.068 ... Accuracy 0.977
... Iteration 3890 ... Epoch 0.72 ... Loss 0.053 ... Accuracy 0.977
... Iteration 3900 ... Epoch 0.72 ... Loss 0.060 ... Accuracy 0.977
... Iteration 3910 ... Epoch 0.72 ... Loss 0.069 ... Accuracy 0.971
... Iteration 3920 ... Epoch 0.72 ... Loss 0.091 ... Accuracy 0.959
... Iteration 3930 ... Epoch 0.72 ... Loss 0.064 ... Accuracy 0.977
... Iteration 3940 ... Epoch 0.73 ... Loss 0.050 ... Accuracy 0.980
... Iteration 3950 ... Epoch 0.73 ... Loss 0.064 ... Accuracy 0.971
... Iteration 3960 ... Epoch 0.73 ... Loss 0.058 ... Accuracy 0.969
... Iteration 3970 ... Epoch 0.73 ... Loss 0.061 ... Accuracy 0.971
... Iteration 3980 ... Epoch 0.73 ... Loss 0.047 ... Accuracy 0.980
... Iteration 3990 ... Epoch 0.73 ... Loss 0.064 ... Accuracy 0.979
... Iteration 4000 ... Epoch 0.74 ... Loss 0.063 ... Accuracy 0.980
... Iteration 4010 ... Epoch 0.74 ... Loss 0.072 ... Accuracy 0.961
... Iteration 4020 ... Epoch 0.74 ... Loss 0.044 ... Accuracy 0.986
... Iteration 4030 ... Epoch 0.74 ... Loss 0.065 ... Accuracy 0.973
... Iteration 4040 ... Epoch 0.74 ... Loss 0.097 ... Accuracy 0.965
... Iteration 4050 ... Epoch 0.75 ... Loss 0.081 ... Accuracy 0.967
... Iteration 4060 ... Epoch 0.75 ... Loss 0.066 ... Accuracy 0.971
... Iteration 4070 ... Epoch 0.75 ... Loss 0.067 ... Accuracy 0.969
... Iteration 4080 ... Epoch 0.75 ... Loss 0.063 ... Accuracy 0.971
... Iteration 4090 ... Epoch 0.75 ... Loss 0.075 ... Accuracy 0.969
... Iteration 4100 ... Epoch 0.75 ... Loss 0.052 ... Accuracy 0.979
... Iteration 4110 ... Epoch 0.76 ... Loss 0.063 ... Accuracy 0.975
... Iteration 4120 ... Epoch 0.76 ... Loss 0.072 ... Accuracy 0.963
... Iteration 4130 ... Epoch 0.76 ... Loss 0.081 ... Accuracy 0.963
... Iteration 4140 ... Epoch 0.76 ... Loss 0.061 ... Accuracy 0.977
... Iteration 4150 ... Epoch 0.76 ... Loss 0.048 ... Accuracy 0.984
... Iteration 4160 ... Epoch 0.77 ... Loss 0.061 ... Accuracy 0.979
... Iteration 4170 ... Epoch 0.77 ... Loss 0.088 ... Accuracy 0.963
... Iteration 4180 ... Epoch 0.77 ... Loss 0.062 ... Accuracy 0.973
... Iteration 4190 ... Epoch 0.77 ... Loss 0.072 ... Accuracy 0.969
... Iteration 4200 ... Epoch 0.77 ... Loss 0.070 ... Accuracy 0.965
... Iteration 4210 ... Epoch 0.78 ... Loss 0.051 ... Accuracy 0.988
... Iteration 4220 ... Epoch 0.78 ... Loss 0.065 ... Accuracy 0.971
... Iteration 4230 ... Epoch 0.78 ... Loss 0.056 ... Accuracy 0.984
... Iteration 4240 ... Epoch 0.78 ... Loss 0.058 ... Accuracy 0.977
... Iteration 4250 ... Epoch 0.78 ... Loss 0.064 ... Accuracy 0.977
... Iteration 4260 ... Epoch 0.78 ... Loss 0.050 ... Accuracy 0.982
... Iteration 4270 ... Epoch 0.79 ... Loss 0.056 ... Accuracy 0.971
... Iteration 4280 ... Epoch 0.79 ... Loss 0.061 ... Accuracy 0.971
... Iteration 4290 ... Epoch 0.79 ... Loss 0.067 ... Accuracy 0.977
... Iteration 4300 ... Epoch 0.79 ... Loss 0.090 ... Accuracy 0.959
... Iteration 4310 ... Epoch 0.79 ... Loss 0.100 ... Accuracy 0.959
... Iteration 4320 ... Epoch 0.80 ... Loss 0.071 ... Accuracy 0.971
... Iteration 4330 ... Epoch 0.80 ... Loss 0.057 ... Accuracy 0.979
... Iteration 4340 ... Epoch 0.80 ... Loss 0.058 ... Accuracy 0.975
... Iteration 4350 ... Epoch 0.80 ... Loss 0.062 ... Accuracy 0.977
... Iteration 4360 ... Epoch 0.80 ... Loss 0.063 ... Accuracy 0.977
... Iteration 4370 ... Epoch 0.80 ... Loss 0.070 ... Accuracy 0.973
... Iteration 4380 ... Epoch 0.81 ... Loss 0.064 ... Accuracy 0.977
... Iteration 4390 ... Epoch 0.81 ... Loss 0.067 ... Accuracy 0.971
... Iteration 4400 ... Epoch 0.81 ... Loss 0.046 ... Accuracy 0.982
... Iteration 4410 ... Epoch 0.81 ... Loss 0.043 ... Accuracy 0.984
... Iteration 4420 ... Epoch 0.81 ... Loss 0.096 ... Accuracy 0.959
... Iteration 4430 ... Epoch 0.82 ... Loss 0.061 ... Accuracy 0.979
... Iteration 4440 ... Epoch 0.82 ... Loss 0.059 ... Accuracy 0.980
... Iteration 4450 ... Epoch 0.82 ... Loss 0.085 ... Accuracy 0.961
... Iteration 4460 ... Epoch 0.82 ... Loss 0.056 ... Accuracy 0.980
... Iteration 4470 ... Epoch 0.82 ... Loss 0.096 ... Accuracy 0.963
... Iteration 4480 ... Epoch 0.82 ... Loss 0.052 ... Accuracy 0.977
... Iteration 4490 ... Epoch 0.83 ... Loss 0.077 ... Accuracy 0.967
... Iteration 4500 ... Epoch 0.83 ... Loss 0.066 ... Accuracy 0.969
... Iteration 4510 ... Epoch 0.83 ... Loss 0.065 ... Accuracy 0.975
... Iteration 4520 ... Epoch 0.83 ... Loss 0.074 ... Accuracy 0.969
... Iteration 4530 ... Epoch 0.83 ... Loss 0.056 ... Accuracy 0.975
... Iteration 4540 ... Epoch 0.84 ... Loss 0.070 ... Accuracy 0.975
... Iteration 4550 ... Epoch 0.84 ... Loss 0.045 ... Accuracy 0.982
... Iteration 4560 ... Epoch 0.84 ... Loss 0.048 ... Accuracy 0.982
... Iteration 4570 ... Epoch 0.84 ... Loss 0.074 ... Accuracy 0.975
... Iteration 4580 ... Epoch 0.84 ... Loss 0.049 ... Accuracy 0.984
... Iteration 4590 ... Epoch 0.85 ... Loss 0.048 ... Accuracy 0.986
... Iteration 4600 ... Epoch 0.85 ... Loss 0.069 ... Accuracy 0.967
... Iteration 4610 ... Epoch 0.85 ... Loss 0.072 ... Accuracy 0.969
... Iteration 4620 ... Epoch 0.85 ... Loss 0.058 ... Accuracy 0.977
... Iteration 4630 ... Epoch 0.85 ... Loss 0.053 ... Accuracy 0.977
... Iteration 4640 ... Epoch 0.85 ... Loss 0.072 ... Accuracy 0.969
... Iteration 4650 ... Epoch 0.86 ... Loss 0.045 ... Accuracy 0.980
... Iteration 4660 ... Epoch 0.86 ... Loss 0.081 ... Accuracy 0.973
... Iteration 4670 ... Epoch 0.86 ... Loss 0.072 ... Accuracy 0.973
... Iteration 4680 ... Epoch 0.86 ... Loss 0.088 ... Accuracy 0.973
... Iteration 4690 ... Epoch 0.86 ... Loss 0.049 ... Accuracy 0.984
... Iteration 4700 ... Epoch 0.87 ... Loss 0.048 ... Accuracy 0.979
... Iteration 4710 ... Epoch 0.87 ... Loss 0.057 ... Accuracy 0.979
... Iteration 4720 ... Epoch 0.87 ... Loss 0.079 ... Accuracy 0.967
... Iteration 4730 ... Epoch 0.87 ... Loss 0.061 ... Accuracy 0.975
... Iteration 4740 ... Epoch 0.87 ... Loss 0.080 ... Accuracy 0.965
... Iteration 4750 ... Epoch 0.87 ... Loss 0.111 ... Accuracy 0.953
... Iteration 4760 ... Epoch 0.88 ... Loss 0.060 ... Accuracy 0.969
... Iteration 4770 ... Epoch 0.88 ... Loss 0.055 ... Accuracy 0.979
... Iteration 4780 ... Epoch 0.88 ... Loss 0.056 ... Accuracy 0.977
... Iteration 4790 ... Epoch 0.88 ... Loss 0.058 ... Accuracy 0.979
... Iteration 4800 ... Epoch 0.88 ... Loss 0.068 ... Accuracy 0.975
... Iteration 4810 ... Epoch 0.89 ... Loss 0.062 ... Accuracy 0.977
... Iteration 4820 ... Epoch 0.89 ... Loss 0.058 ... Accuracy 0.982
... Iteration 4830 ... Epoch 0.89 ... Loss 0.054 ... Accuracy 0.984
... Iteration 4840 ... Epoch 0.89 ... Loss 0.080 ... Accuracy 0.967
... Iteration 4850 ... Epoch 0.89 ... Loss 0.062 ... Accuracy 0.977
... Iteration 4860 ... Epoch 0.89 ... Loss 0.065 ... Accuracy 0.967
... Iteration 4870 ... Epoch 0.90 ... Loss 0.072 ... Accuracy 0.980
... Iteration 4880 ... Epoch 0.90 ... Loss 0.073 ... Accuracy 0.971
... Iteration 4890 ... Epoch 0.90 ... Loss 0.049 ... Accuracy 0.982
... Iteration 4900 ... Epoch 0.90 ... Loss 0.074 ... Accuracy 0.975
... Iteration 4910 ... Epoch 0.90 ... Loss 0.072 ... Accuracy 0.967
... Iteration 4920 ... Epoch 0.91 ... Loss 0.071 ... Accuracy 0.973
... Iteration 4930 ... Epoch 0.91 ... Loss 0.077 ... Accuracy 0.967
... Iteration 4940 ... Epoch 0.91 ... Loss 0.052 ... Accuracy 0.982
... Iteration 4950 ... Epoch 0.91 ... Loss 0.072 ... Accuracy 0.977
... Iteration 4960 ... Epoch 0.91 ... Loss 0.052 ... Accuracy 0.982
... Iteration 4970 ... Epoch 0.92 ... Loss 0.068 ... Accuracy 0.975
... Iteration 4980 ... Epoch 0.92 ... Loss 0.103 ... Accuracy 0.961
... Iteration 4990 ... Epoch 0.92 ... Loss 0.047 ... Accuracy 0.979
... Iteration 5000 ... Epoch 0.92 ... Loss 0.052 ... Accuracy 0.986
... Iteration 5010 ... Epoch 0.92 ... Loss 0.060 ... Accuracy 0.979
... Iteration 5020 ... Epoch 0.92 ... Loss 0.063 ... Accuracy 0.973
... Iteration 5030 ... Epoch 0.93 ... Loss 0.077 ... Accuracy 0.971
... Iteration 5040 ... Epoch 0.93 ... Loss 0.054 ... Accuracy 0.984
... Iteration 5050 ... Epoch 0.93 ... Loss 0.067 ... Accuracy 0.984
... Iteration 5060 ... Epoch 0.93 ... Loss 0.027 ... Accuracy 0.996
... Iteration 5070 ... Epoch 0.93 ... Loss 0.057 ... Accuracy 0.971
... Iteration 5080 ... Epoch 0.94 ... Loss 0.072 ... Accuracy 0.975
... Iteration 5090 ... Epoch 0.94 ... Loss 0.051 ... Accuracy 0.986
... Iteration 5100 ... Epoch 0.94 ... Loss 0.073 ... Accuracy 0.979
... Iteration 5110 ... Epoch 0.94 ... Loss 0.063 ... Accuracy 0.973
... Iteration 5120 ... Epoch 0.94 ... Loss 0.063 ... Accuracy 0.977
... Iteration 5130 ... Epoch 0.94 ... Loss 0.078 ... Accuracy 0.967
... Iteration 5140 ... Epoch 0.95 ... Loss 0.078 ... Accuracy 0.975
... Iteration 5150 ... Epoch 0.95 ... Loss 0.059 ... Accuracy 0.982
... Iteration 5160 ... Epoch 0.95 ... Loss 0.048 ... Accuracy 0.984
... Iteration 5170 ... Epoch 0.95 ... Loss 0.093 ... Accuracy 0.965
... Iteration 5180 ... Epoch 0.95 ... Loss 0.064 ... Accuracy 0.975
... Iteration 5190 ... Epoch 0.96 ... Loss 0.065 ... Accuracy 0.975
... Iteration 5200 ... Epoch 0.96 ... Loss 0.062 ... Accuracy 0.971
... Iteration 5210 ... Epoch 0.96 ... Loss 0.052 ... Accuracy 0.979
... Iteration 5220 ... Epoch 0.96 ... Loss 0.078 ... Accuracy 0.971
... Iteration 5230 ... Epoch 0.96 ... Loss 0.052 ... Accuracy 0.984
... Iteration 5240 ... Epoch 0.96 ... Loss 0.048 ... Accuracy 0.982
... Iteration 5250 ... Epoch 0.97 ... Loss 0.064 ... Accuracy 0.980
... Iteration 5260 ... Epoch 0.97 ... Loss 0.089 ... Accuracy 0.961
... Iteration 5270 ... Epoch 0.97 ... Loss 0.042 ... Accuracy 0.986
... Iteration 5280 ... Epoch 0.97 ... Loss 0.095 ... Accuracy 0.967
... Iteration 5290 ... Epoch 0.97 ... Loss 0.059 ... Accuracy 0.969
... Iteration 5300 ... Epoch 0.98 ... Loss 0.070 ... Accuracy 0.975
... Iteration 5310 ... Epoch 0.98 ... Loss 0.064 ... Accuracy 0.979
... Iteration 5320 ... Epoch 0.98 ... Loss 0.051 ... Accuracy 0.984
... Iteration 5330 ... Epoch 0.98 ... Loss 0.075 ... Accuracy 0.963
... Iteration 5340 ... Epoch 0.98 ... Loss 0.074 ... Accuracy 0.963
... Iteration 5350 ... Epoch 0.99 ... Loss 0.087 ... Accuracy 0.971
... Iteration 5360 ... Epoch 0.99 ... Loss 0.050 ... Accuracy 0.982
... Iteration 5370 ... Epoch 0.99 ... Loss 0.073 ... Accuracy 0.965
... Iteration 5380 ... Epoch 0.99 ... Loss 0.061 ... Accuracy 0.977
... Iteration 5390 ... Epoch 0.99 ... Loss 0.076 ... Accuracy 0.969
... Iteration 5400 ... Epoch 0.99 ... Loss 0.095 ... Accuracy 0.963
... Iteration 5410 ... Epoch 1.00 ... Loss 0.065 ... Accuracy 0.975
... Iteration 5420 ... Epoch 1.00 ... Loss 0.081 ... Accuracy 0.975
... Iteration 5430 ... Epoch 1.00 ... Loss 0.067 ... Accuracy 0.977
... Iteration 5431 ... Epoch 1.00 ... Loss 0.054 ... Accuracy 0.958
Epoch 0 Starting @ 2020-07-31 15:50:47
... Iteration 5440 ... Epoch 1.00 ... Loss 0.062 ... Accuracy 0.977
... Iteration 5450 ... Epoch 1.00 ... Loss 0.037 ... Accuracy 0.984
... Iteration 5460 ... Epoch 1.01 ... Loss 0.047 ... Accuracy 0.979
... Iteration 5470 ... Epoch 1.01 ... Loss 0.088 ... Accuracy 0.969
... Iteration 5480 ... Epoch 1.01 ... Loss 0.031 ... Accuracy 0.990
... Iteration 5490 ... Epoch 1.01 ... Loss 0.048 ... Accuracy 0.984
... Iteration 5500 ... Epoch 1.01 ... Loss 0.053 ... Accuracy 0.975
... Iteration 5510 ... Epoch 1.01 ... Loss 0.056 ... Accuracy 0.975
... Iteration 5520 ... Epoch 1.02 ... Loss 0.080 ... Accuracy 0.969
... Iteration 5530 ... Epoch 1.02 ... Loss 0.048 ... Accuracy 0.982
... Iteration 5540 ... Epoch 1.02 ... Loss 0.063 ... Accuracy 0.973
... Iteration 5550 ... Epoch 1.02 ... Loss 0.068 ... Accuracy 0.982
... Iteration 5560 ... Epoch 1.02 ... Loss 0.048 ... Accuracy 0.986
... Iteration 5570 ... Epoch 1.03 ... Loss 0.069 ... Accuracy 0.977
... Iteration 5580 ... Epoch 1.03 ... Loss 0.061 ... Accuracy 0.977
... Iteration 5590 ... Epoch 1.03 ... Loss 0.076 ... Accuracy 0.973
... Iteration 5600 ... Epoch 1.03 ... Loss 0.073 ... Accuracy 0.963
... Iteration 5610 ... Epoch 1.03 ... Loss 0.083 ... Accuracy 0.965
... Iteration 5620 ... Epoch 1.03 ... Loss 0.048 ... Accuracy 0.975
... Iteration 5630 ... Epoch 1.04 ... Loss 0.056 ... Accuracy 0.977
... Iteration 5640 ... Epoch 1.04 ... Loss 0.047 ... Accuracy 0.982
... Iteration 5650 ... Epoch 1.04 ... Loss 0.061 ... Accuracy 0.973
... Iteration 5660 ... Epoch 1.04 ... Loss 0.079 ... Accuracy 0.969
... Iteration 5670 ... Epoch 1.04 ... Loss 0.060 ... Accuracy 0.982
... Iteration 5680 ... Epoch 1.05 ... Loss 0.057 ... Accuracy 0.973
... Iteration 5690 ... Epoch 1.05 ... Loss 0.055 ... Accuracy 0.971
... Iteration 5700 ... Epoch 1.05 ... Loss 0.051 ... Accuracy 0.980
... Iteration 5710 ... Epoch 1.05 ... Loss 0.058 ... Accuracy 0.973
... Iteration 5720 ... Epoch 1.05 ... Loss 0.060 ... Accuracy 0.980
... Iteration 5730 ... Epoch 1.06 ... Loss 0.059 ... Accuracy 0.973
... Iteration 5740 ... Epoch 1.06 ... Loss 0.061 ... Accuracy 0.971
... Iteration 5750 ... Epoch 1.06 ... Loss 0.041 ... Accuracy 0.986
... Iteration 5760 ... Epoch 1.06 ... Loss 0.050 ... Accuracy 0.980
... Iteration 5770 ... Epoch 1.06 ... Loss 0.061 ... Accuracy 0.971
... Iteration 5780 ... Epoch 1.06 ... Loss 0.075 ... Accuracy 0.971
... Iteration 5790 ... Epoch 1.07 ... Loss 0.056 ... Accuracy 0.980
... Iteration 5800 ... Epoch 1.07 ... Loss 0.077 ... Accuracy 0.965
... Iteration 5810 ... Epoch 1.07 ... Loss 0.088 ... Accuracy 0.971
... Iteration 5820 ... Epoch 1.07 ... Loss 0.053 ... Accuracy 0.980
... Iteration 5830 ... Epoch 1.07 ... Loss 0.071 ... Accuracy 0.971
... Iteration 5840 ... Epoch 1.08 ... Loss 0.065 ... Accuracy 0.969
... Iteration 5850 ... Epoch 1.08 ... Loss 0.057 ... Accuracy 0.971
... Iteration 5860 ... Epoch 1.08 ... Loss 0.048 ... Accuracy 0.977
... Iteration 5870 ... Epoch 1.08 ... Loss 0.053 ... Accuracy 0.979
... Iteration 5880 ... Epoch 1.08 ... Loss 0.079 ... Accuracy 0.963
... Iteration 5890 ... Epoch 1.08 ... Loss 0.050 ... Accuracy 0.986
... Iteration 5900 ... Epoch 1.09 ... Loss 0.055 ... Accuracy 0.975
... Iteration 5910 ... Epoch 1.09 ... Loss 0.057 ... Accuracy 0.973
... Iteration 5920 ... Epoch 1.09 ... Loss 0.063 ... Accuracy 0.975
... Iteration 5930 ... Epoch 1.09 ... Loss 0.076 ... Accuracy 0.969
... Iteration 5940 ... Epoch 1.09 ... Loss 0.044 ... Accuracy 0.980
... Iteration 5950 ... Epoch 1.10 ... Loss 0.073 ... Accuracy 0.971
... Iteration 5960 ... Epoch 1.10 ... Loss 0.045 ... Accuracy 0.984
... Iteration 5970 ... Epoch 1.10 ... Loss 0.077 ... Accuracy 0.969
... Iteration 5980 ... Epoch 1.10 ... Loss 0.036 ... Accuracy 0.982
... Iteration 5990 ... Epoch 1.10 ... Loss 0.066 ... Accuracy 0.967
... Iteration 6000 ... Epoch 1.10 ... Loss 0.070 ... Accuracy 0.973
... Iteration 6010 ... Epoch 1.11 ... Loss 0.048 ... Accuracy 0.982
... Iteration 6020 ... Epoch 1.11 ... Loss 0.056 ... Accuracy 0.977
... Iteration 6030 ... Epoch 1.11 ... Loss 0.050 ... Accuracy 0.980
... Iteration 6040 ... Epoch 1.11 ... Loss 0.053 ... Accuracy 0.982
... Iteration 6050 ... Epoch 1.11 ... Loss 0.102 ... Accuracy 0.955
... Iteration 6060 ... Epoch 1.12 ... Loss 0.047 ... Accuracy 0.980
... Iteration 6070 ... Epoch 1.12 ... Loss 0.045 ... Accuracy 0.982
... Iteration 6080 ... Epoch 1.12 ... Loss 0.046 ... Accuracy 0.982
... Iteration 6090 ... Epoch 1.12 ... Loss 0.057 ... Accuracy 0.977
... Iteration 6100 ... Epoch 1.12 ... Loss 0.059 ... Accuracy 0.971
... Iteration 6110 ... Epoch 1.13 ... Loss 0.057 ... Accuracy 0.977
... Iteration 6120 ... Epoch 1.13 ... Loss 0.054 ... Accuracy 0.967
... Iteration 6130 ... Epoch 1.13 ... Loss 0.064 ... Accuracy 0.977
... Iteration 6140 ... Epoch 1.13 ... Loss 0.045 ... Accuracy 0.984
... Iteration 6150 ... Epoch 1.13 ... Loss 0.073 ... Accuracy 0.969
... Iteration 6160 ... Epoch 1.13 ... Loss 0.065 ... Accuracy 0.977
... Iteration 6170 ... Epoch 1.14 ... Loss 0.040 ... Accuracy 0.980
... Iteration 6180 ... Epoch 1.14 ... Loss 0.072 ... Accuracy 0.967
... Iteration 6190 ... Epoch 1.14 ... Loss 0.050 ... Accuracy 0.975
... Iteration 6200 ... Epoch 1.14 ... Loss 0.072 ... Accuracy 0.967
... Iteration 6210 ... Epoch 1.14 ... Loss 0.061 ... Accuracy 0.977
... Iteration 6220 ... Epoch 1.15 ... Loss 0.073 ... Accuracy 0.969
... Iteration 6230 ... Epoch 1.15 ... Loss 0.056 ... Accuracy 0.979
... Iteration 6240 ... Epoch 1.15 ... Loss 0.052 ... Accuracy 0.980
... Iteration 6250 ... Epoch 1.15 ... Loss 0.050 ... Accuracy 0.980
... Iteration 6260 ... Epoch 1.15 ... Loss 0.071 ... Accuracy 0.973
... Iteration 6270 ... Epoch 1.15 ... Loss 0.058 ... Accuracy 0.975
... Iteration 6280 ... Epoch 1.16 ... Loss 0.064 ... Accuracy 0.982
... Iteration 6290 ... Epoch 1.16 ... Loss 0.066 ... Accuracy 0.969
... Iteration 6300 ... Epoch 1.16 ... Loss 0.061 ... Accuracy 0.973
... Iteration 6310 ... Epoch 1.16 ... Loss 0.054 ... Accuracy 0.975
... Iteration 6320 ... Epoch 1.16 ... Loss 0.056 ... Accuracy 0.979
... Iteration 6330 ... Epoch 1.17 ... Loss 0.044 ... Accuracy 0.984
... Iteration 6340 ... Epoch 1.17 ... Loss 0.058 ... Accuracy 0.980
... Iteration 6350 ... Epoch 1.17 ... Loss 0.060 ... Accuracy 0.977
... Iteration 6360 ... Epoch 1.17 ... Loss 0.054 ... Accuracy 0.982
... Iteration 6370 ... Epoch 1.17 ... Loss 0.033 ... Accuracy 0.990
... Iteration 6380 ... Epoch 1.17 ... Loss 0.061 ... Accuracy 0.982
... Iteration 6390 ... Epoch 1.18 ... Loss 0.066 ... Accuracy 0.973
... Iteration 6400 ... Epoch 1.18 ... Loss 0.047 ... Accuracy 0.980
... Iteration 6410 ... Epoch 1.18 ... Loss 0.053 ... Accuracy 0.984
... Iteration 6420 ... Epoch 1.18 ... Loss 0.050 ... Accuracy 0.986
... Iteration 6430 ... Epoch 1.18 ... Loss 0.042 ... Accuracy 0.988
... Iteration 6440 ... Epoch 1.19 ... Loss 0.049 ... Accuracy 0.982
... Iteration 6450 ... Epoch 1.19 ... Loss 0.093 ... Accuracy 0.959
... Iteration 6460 ... Epoch 1.19 ... Loss 0.088 ... Accuracy 0.967
... Iteration 6470 ... Epoch 1.19 ... Loss 0.060 ... Accuracy 0.980
... Iteration 6480 ... Epoch 1.19 ... Loss 0.038 ... Accuracy 0.986
... Iteration 6490 ... Epoch 1.19 ... Loss 0.056 ... Accuracy 0.979
... Iteration 6500 ... Epoch 1.20 ... Loss 0.062 ... Accuracy 0.977
... Iteration 6510 ... Epoch 1.20 ... Loss 0.061 ... Accuracy 0.979
... Iteration 6520 ... Epoch 1.20 ... Loss 0.043 ... Accuracy 0.982
... Iteration 6530 ... Epoch 1.20 ... Loss 0.048 ... Accuracy 0.979
... Iteration 6540 ... Epoch 1.20 ... Loss 0.044 ... Accuracy 0.986
... Iteration 6550 ... Epoch 1.21 ... Loss 0.055 ... Accuracy 0.979
... Iteration 6560 ... Epoch 1.21 ... Loss 0.053 ... Accuracy 0.979
... Iteration 6570 ... Epoch 1.21 ... Loss 0.052 ... Accuracy 0.977
... Iteration 6580 ... Epoch 1.21 ... Loss 0.064 ... Accuracy 0.980
... Iteration 6590 ... Epoch 1.21 ... Loss 0.063 ... Accuracy 0.971
... Iteration 6600 ... Epoch 1.22 ... Loss 0.049 ... Accuracy 0.982
... Iteration 6610 ... Epoch 1.22 ... Loss 0.066 ... Accuracy 0.969
... Iteration 6620 ... Epoch 1.22 ... Loss 0.061 ... Accuracy 0.980
... Iteration 6630 ... Epoch 1.22 ... Loss 0.065 ... Accuracy 0.971
... Iteration 6640 ... Epoch 1.22 ... Loss 0.067 ... Accuracy 0.975
... Iteration 6650 ... Epoch 1.22 ... Loss 0.036 ... Accuracy 0.988
... Iteration 6660 ... Epoch 1.23 ... Loss 0.061 ... Accuracy 0.979
... Iteration 6670 ... Epoch 1.23 ... Loss 0.056 ... Accuracy 0.979
... Iteration 6680 ... Epoch 1.23 ... Loss 0.078 ... Accuracy 0.965
... Iteration 6690 ... Epoch 1.23 ... Loss 0.039 ... Accuracy 0.990
... Iteration 6700 ... Epoch 1.23 ... Loss 0.104 ... Accuracy 0.963
... Iteration 6710 ... Epoch 1.24 ... Loss 0.065 ... Accuracy 0.979
... Iteration 6720 ... Epoch 1.24 ... Loss 0.060 ... Accuracy 0.969
... Iteration 6730 ... Epoch 1.24 ... Loss 0.068 ... Accuracy 0.975
... Iteration 6740 ... Epoch 1.24 ... Loss 0.063 ... Accuracy 0.977
... Iteration 6750 ... Epoch 1.24 ... Loss 0.095 ... Accuracy 0.969
... Iteration 6760 ... Epoch 1.24 ... Loss 0.071 ... Accuracy 0.969
... Iteration 6770 ... Epoch 1.25 ... Loss 0.048 ... Accuracy 0.982
... Iteration 6780 ... Epoch 1.25 ... Loss 0.050 ... Accuracy 0.980
... Iteration 6790 ... Epoch 1.25 ... Loss 0.052 ... Accuracy 0.975
... Iteration 6800 ... Epoch 1.25 ... Loss 0.051 ... Accuracy 0.979
... Iteration 6810 ... Epoch 1.25 ... Loss 0.058 ... Accuracy 0.971
... Iteration 6820 ... Epoch 1.26 ... Loss 0.047 ... Accuracy 0.979
... Iteration 6830 ... Epoch 1.26 ... Loss 0.054 ... Accuracy 0.980
... Iteration 6840 ... Epoch 1.26 ... Loss 0.061 ... Accuracy 0.977
... Iteration 6850 ... Epoch 1.26 ... Loss 0.050 ... Accuracy 0.982
... Iteration 6860 ... Epoch 1.26 ... Loss 0.079 ... Accuracy 0.973
... Iteration 6870 ... Epoch 1.26 ... Loss 0.033 ... Accuracy 0.990
... Iteration 6880 ... Epoch 1.27 ... Loss 0.061 ... Accuracy 0.973
... Iteration 6890 ... Epoch 1.27 ... Loss 0.078 ... Accuracy 0.965
... Iteration 6900 ... Epoch 1.27 ... Loss 0.060 ... Accuracy 0.975
... Iteration 6910 ... Epoch 1.27 ... Loss 0.059 ... Accuracy 0.973
... Iteration 6920 ... Epoch 1.27 ... Loss 0.050 ... Accuracy 0.986
... Iteration 6930 ... Epoch 1.28 ... Loss 0.064 ... Accuracy 0.975
... Iteration 6940 ... Epoch 1.28 ... Loss 0.053 ... Accuracy 0.980
... Iteration 6950 ... Epoch 1.28 ... Loss 0.049 ... Accuracy 0.982
... Iteration 6960 ... Epoch 1.28 ... Loss 0.077 ... Accuracy 0.971
... Iteration 6970 ... Epoch 1.28 ... Loss 0.046 ... Accuracy 0.982
... Iteration 6980 ... Epoch 1.29 ... Loss 0.039 ... Accuracy 0.982
... Iteration 6990 ... Epoch 1.29 ... Loss 0.052 ... Accuracy 0.977
... Iteration 7000 ... Epoch 1.29 ... Loss 0.085 ... Accuracy 0.973
... Iteration 7010 ... Epoch 1.29 ... Loss 0.064 ... Accuracy 0.973
... Iteration 7020 ... Epoch 1.29 ... Loss 0.051 ... Accuracy 0.982
... Iteration 7030 ... Epoch 1.29 ... Loss 0.065 ... Accuracy 0.973
... Iteration 7040 ... Epoch 1.30 ... Loss 0.049 ... Accuracy 0.979
... Iteration 7050 ... Epoch 1.30 ... Loss 0.087 ... Accuracy 0.965
... Iteration 7060 ... Epoch 1.30 ... Loss 0.048 ... Accuracy 0.982
... Iteration 7070 ... Epoch 1.30 ... Loss 0.054 ... Accuracy 0.980
... Iteration 7080 ... Epoch 1.30 ... Loss 0.048 ... Accuracy 0.980
... Iteration 7090 ... Epoch 1.31 ... Loss 0.045 ... Accuracy 0.982
... Iteration 7100 ... Epoch 1.31 ... Loss 0.075 ... Accuracy 0.971
... Iteration 7110 ... Epoch 1.31 ... Loss 0.058 ... Accuracy 0.979
... Iteration 7120 ... Epoch 1.31 ... Loss 0.053 ... Accuracy 0.973
... Iteration 7130 ... Epoch 1.31 ... Loss 0.076 ... Accuracy 0.969
... Iteration 7140 ... Epoch 1.31 ... Loss 0.055 ... Accuracy 0.980
... Iteration 7150 ... Epoch 1.32 ... Loss 0.056 ... Accuracy 0.977
... Iteration 7160 ... Epoch 1.32 ... Loss 0.071 ... Accuracy 0.971
... Iteration 7170 ... Epoch 1.32 ... Loss 0.088 ... Accuracy 0.961
... Iteration 7180 ... Epoch 1.32 ... Loss 0.056 ... Accuracy 0.979
... Iteration 7190 ... Epoch 1.32 ... Loss 0.034 ... Accuracy 0.990
... Iteration 7200 ... Epoch 1.33 ... Loss 0.103 ... Accuracy 0.961
... Iteration 7210 ... Epoch 1.33 ... Loss 0.084 ... Accuracy 0.963
... Iteration 7220 ... Epoch 1.33 ... Loss 0.049 ... Accuracy 0.982
... Iteration 7230 ... Epoch 1.33 ... Loss 0.063 ... Accuracy 0.969
... Iteration 7240 ... Epoch 1.33 ... Loss 0.046 ... Accuracy 0.975
... Iteration 7250 ... Epoch 1.33 ... Loss 0.051 ... Accuracy 0.986
... Iteration 7260 ... Epoch 1.34 ... Loss 0.053 ... Accuracy 0.982
... Iteration 7270 ... Epoch 1.34 ... Loss 0.050 ... Accuracy 0.979
... Iteration 7280 ... Epoch 1.34 ... Loss 0.077 ... Accuracy 0.967
... Iteration 7290 ... Epoch 1.34 ... Loss 0.046 ... Accuracy 0.982
... Iteration 7300 ... Epoch 1.34 ... Loss 0.061 ... Accuracy 0.979
... Iteration 7310 ... Epoch 1.35 ... Loss 0.073 ... Accuracy 0.969
... Iteration 7320 ... Epoch 1.35 ... Loss 0.061 ... Accuracy 0.979
... Iteration 7330 ... Epoch 1.35 ... Loss 0.048 ... Accuracy 0.986
... Iteration 7340 ... Epoch 1.35 ... Loss 0.073 ... Accuracy 0.977
... Iteration 7350 ... Epoch 1.35 ... Loss 0.036 ... Accuracy 0.988
... Iteration 7360 ... Epoch 1.36 ... Loss 0.061 ... Accuracy 0.969
... Iteration 7370 ... Epoch 1.36 ... Loss 0.037 ... Accuracy 0.988
... Iteration 7380 ... Epoch 1.36 ... Loss 0.064 ... Accuracy 0.973
... Iteration 7390 ... Epoch 1.36 ... Loss 0.085 ... Accuracy 0.965
... Iteration 7400 ... Epoch 1.36 ... Loss 0.058 ... Accuracy 0.973
... Iteration 7410 ... Epoch 1.36 ... Loss 0.035 ... Accuracy 0.990
... Iteration 7420 ... Epoch 1.37 ... Loss 0.061 ... Accuracy 0.980
... Iteration 7430 ... Epoch 1.37 ... Loss 0.086 ... Accuracy 0.977
... Iteration 7440 ... Epoch 1.37 ... Loss 0.077 ... Accuracy 0.969
... Iteration 7450 ... Epoch 1.37 ... Loss 0.084 ... Accuracy 0.967
... Iteration 7460 ... Epoch 1.37 ... Loss 0.040 ... Accuracy 0.984
... Iteration 7470 ... Epoch 1.38 ... Loss 0.061 ... Accuracy 0.973
... Iteration 7480 ... Epoch 1.38 ... Loss 0.056 ... Accuracy 0.979
... Iteration 7490 ... Epoch 1.38 ... Loss 0.056 ... Accuracy 0.969
... Iteration 7500 ... Epoch 1.38 ... Loss 0.045 ... Accuracy 0.979
... Iteration 7510 ... Epoch 1.38 ... Loss 0.058 ... Accuracy 0.969
... Iteration 7520 ... Epoch 1.38 ... Loss 0.061 ... Accuracy 0.980
... Iteration 7530 ... Epoch 1.39 ... Loss 0.057 ... Accuracy 0.979
... Iteration 7540 ... Epoch 1.39 ... Loss 0.069 ... Accuracy 0.971
... Iteration 7550 ... Epoch 1.39 ... Loss 0.057 ... Accuracy 0.979
... Iteration 7560 ... Epoch 1.39 ... Loss 0.058 ... Accuracy 0.975
... Iteration 7570 ... Epoch 1.39 ... Loss 0.080 ... Accuracy 0.969
... Iteration 7580 ... Epoch 1.40 ... Loss 0.074 ... Accuracy 0.973
... Iteration 7590 ... Epoch 1.40 ... Loss 0.057 ... Accuracy 0.979
... Iteration 7600 ... Epoch 1.40 ... Loss 0.045 ... Accuracy 0.982
... Iteration 7610 ... Epoch 1.40 ... Loss 0.052 ... Accuracy 0.982
... Iteration 7620 ... Epoch 1.40 ... Loss 0.041 ... Accuracy 0.984
... Iteration 7630 ... Epoch 1.40 ... Loss 0.052 ... Accuracy 0.975
... Iteration 7640 ... Epoch 1.41 ... Loss 0.098 ... Accuracy 0.961
... Iteration 7650 ... Epoch 1.41 ... Loss 0.064 ... Accuracy 0.969
... Iteration 7660 ... Epoch 1.41 ... Loss 0.053 ... Accuracy 0.979
... Iteration 7670 ... Epoch 1.41 ... Loss 0.059 ... Accuracy 0.977
... Iteration 7680 ... Epoch 1.41 ... Loss 0.057 ... Accuracy 0.984
... Iteration 7690 ... Epoch 1.42 ... Loss 0.042 ... Accuracy 0.984
... Iteration 7700 ... Epoch 1.42 ... Loss 0.067 ... Accuracy 0.971
... Iteration 7710 ... Epoch 1.42 ... Loss 0.070 ... Accuracy 0.979
... Iteration 7720 ... Epoch 1.42 ... Loss 0.059 ... Accuracy 0.980
... Iteration 7730 ... Epoch 1.42 ... Loss 0.051 ... Accuracy 0.982
... Iteration 7740 ... Epoch 1.43 ... Loss 0.062 ... Accuracy 0.975
... Iteration 7750 ... Epoch 1.43 ... Loss 0.055 ... Accuracy 0.980
... Iteration 7760 ... Epoch 1.43 ... Loss 0.041 ... Accuracy 0.982
... Iteration 7770 ... Epoch 1.43 ... Loss 0.055 ... Accuracy 0.982
... Iteration 7780 ... Epoch 1.43 ... Loss 0.068 ... Accuracy 0.979
... Iteration 7790 ... Epoch 1.43 ... Loss 0.055 ... Accuracy 0.977
... Iteration 7800 ... Epoch 1.44 ... Loss 0.056 ... Accuracy 0.979
... Iteration 7810 ... Epoch 1.44 ... Loss 0.068 ... Accuracy 0.973
... Iteration 7820 ... Epoch 1.44 ... Loss 0.059 ... Accuracy 0.973
... Iteration 7830 ... Epoch 1.44 ... Loss 0.072 ... Accuracy 0.971
... Iteration 7840 ... Epoch 1.44 ... Loss 0.050 ... Accuracy 0.982
... Iteration 7850 ... Epoch 1.45 ... Loss 0.059 ... Accuracy 0.973
... Iteration 7860 ... Epoch 1.45 ... Loss 0.057 ... Accuracy 0.975
... Iteration 7870 ... Epoch 1.45 ... Loss 0.038 ... Accuracy 0.992
... Iteration 7880 ... Epoch 1.45 ... Loss 0.077 ... Accuracy 0.971
... Iteration 7890 ... Epoch 1.45 ... Loss 0.058 ... Accuracy 0.980
... Iteration 7900 ... Epoch 1.45 ... Loss 0.059 ... Accuracy 0.979
... Iteration 7910 ... Epoch 1.46 ... Loss 0.061 ... Accuracy 0.975
... Iteration 7920 ... Epoch 1.46 ... Loss 0.058 ... Accuracy 0.979
... Iteration 7930 ... Epoch 1.46 ... Loss 0.067 ... Accuracy 0.977
... Iteration 7940 ... Epoch 1.46 ... Loss 0.059 ... Accuracy 0.982
... Iteration 7950 ... Epoch 1.46 ... Loss 0.041 ... Accuracy 0.980
... Iteration 7960 ... Epoch 1.47 ... Loss 0.053 ... Accuracy 0.977
... Iteration 7970 ... Epoch 1.47 ... Loss 0.028 ... Accuracy 0.990
... Iteration 7980 ... Epoch 1.47 ... Loss 0.066 ... Accuracy 0.971
... Iteration 7990 ... Epoch 1.47 ... Loss 0.031 ... Accuracy 0.994
... Iteration 8000 ... Epoch 1.47 ... Loss 0.058 ... Accuracy 0.971
... Iteration 8010 ... Epoch 1.47 ... Loss 0.049 ... Accuracy 0.980
... Iteration 8020 ... Epoch 1.48 ... Loss 0.062 ... Accuracy 0.979
... Iteration 8030 ... Epoch 1.48 ... Loss 0.046 ... Accuracy 0.984
... Iteration 8040 ... Epoch 1.48 ... Loss 0.041 ... Accuracy 0.982
... Iteration 8050 ... Epoch 1.48 ... Loss 0.051 ... Accuracy 0.986
... Iteration 8060 ... Epoch 1.48 ... Loss 0.051 ... Accuracy 0.986
... Iteration 8070 ... Epoch 1.49 ... Loss 0.048 ... Accuracy 0.986
... Iteration 8080 ... Epoch 1.49 ... Loss 0.055 ... Accuracy 0.975
... Iteration 8090 ... Epoch 1.49 ... Loss 0.058 ... Accuracy 0.980
... Iteration 8100 ... Epoch 1.49 ... Loss 0.055 ... Accuracy 0.977
... Iteration 8110 ... Epoch 1.49 ... Loss 0.045 ... Accuracy 0.980
... Iteration 8120 ... Epoch 1.50 ... Loss 0.070 ... Accuracy 0.977
... Iteration 8130 ... Epoch 1.50 ... Loss 0.049 ... Accuracy 0.984
... Iteration 8140 ... Epoch 1.50 ... Loss 0.057 ... Accuracy 0.977
... Iteration 8150 ... Epoch 1.50 ... Loss 0.046 ... Accuracy 0.984
... Iteration 8160 ... Epoch 1.50 ... Loss 0.060 ... Accuracy 0.980
... Iteration 8170 ... Epoch 1.50 ... Loss 0.049 ... Accuracy 0.980
... Iteration 8180 ... Epoch 1.51 ... Loss 0.078 ... Accuracy 0.961
... Iteration 8190 ... Epoch 1.51 ... Loss 0.062 ... Accuracy 0.975
... Iteration 8200 ... Epoch 1.51 ... Loss 0.059 ... Accuracy 0.979
... Iteration 8210 ... Epoch 1.51 ... Loss 0.049 ... Accuracy 0.980
... Iteration 8220 ... Epoch 1.51 ... Loss 0.041 ... Accuracy 0.984
... Iteration 8230 ... Epoch 1.52 ... Loss 0.065 ... Accuracy 0.973
... Iteration 8240 ... Epoch 1.52 ... Loss 0.040 ... Accuracy 0.984
... Iteration 8250 ... Epoch 1.52 ... Loss 0.042 ... Accuracy 0.980
... Iteration 8260 ... Epoch 1.52 ... Loss 0.062 ... Accuracy 0.977
... Iteration 8270 ... Epoch 1.52 ... Loss 0.093 ... Accuracy 0.965
... Iteration 8280 ... Epoch 1.52 ... Loss 0.053 ... Accuracy 0.979
... Iteration 8290 ... Epoch 1.53 ... Loss 0.052 ... Accuracy 0.984
... Iteration 8300 ... Epoch 1.53 ... Loss 0.041 ... Accuracy 0.982
... Iteration 8310 ... Epoch 1.53 ... Loss 0.048 ... Accuracy 0.979
... Iteration 8320 ... Epoch 1.53 ... Loss 0.061 ... Accuracy 0.975
... Iteration 8330 ... Epoch 1.53 ... Loss 0.056 ... Accuracy 0.979
... Iteration 8340 ... Epoch 1.54 ... Loss 0.056 ... Accuracy 0.973
... Iteration 8350 ... Epoch 1.54 ... Loss 0.066 ... Accuracy 0.973
... Iteration 8360 ... Epoch 1.54 ... Loss 0.048 ... Accuracy 0.984
... Iteration 8370 ... Epoch 1.54 ... Loss 0.035 ... Accuracy 0.992
... Iteration 8380 ... Epoch 1.54 ... Loss 0.052 ... Accuracy 0.980
... Iteration 8390 ... Epoch 1.54 ... Loss 0.051 ... Accuracy 0.979
... Iteration 8400 ... Epoch 1.55 ... Loss 0.058 ... Accuracy 0.979
... Iteration 8410 ... Epoch 1.55 ... Loss 0.050 ... Accuracy 0.982
... Iteration 8420 ... Epoch 1.55 ... Loss 0.042 ... Accuracy 0.980
... Iteration 8430 ... Epoch 1.55 ... Loss 0.088 ... Accuracy 0.957
... Iteration 8440 ... Epoch 1.55 ... Loss 0.050 ... Accuracy 0.980
... Iteration 8450 ... Epoch 1.56 ... Loss 0.081 ... Accuracy 0.961
... Iteration 8460 ... Epoch 1.56 ... Loss 0.046 ... Accuracy 0.980
... Iteration 8470 ... Epoch 1.56 ... Loss 0.067 ... Accuracy 0.971
... Iteration 8480 ... Epoch 1.56 ... Loss 0.055 ... Accuracy 0.977
... Iteration 8490 ... Epoch 1.56 ... Loss 0.045 ... Accuracy 0.982
... Iteration 8500 ... Epoch 1.57 ... Loss 0.055 ... Accuracy 0.984
... Iteration 8510 ... Epoch 1.57 ... Loss 0.055 ... Accuracy 0.984
... Iteration 8520 ... Epoch 1.57 ... Loss 0.048 ... Accuracy 0.988
... Iteration 8530 ... Epoch 1.57 ... Loss 0.042 ... Accuracy 0.980
... Iteration 8540 ... Epoch 1.57 ... Loss 0.051 ... Accuracy 0.980
... Iteration 8550 ... Epoch 1.57 ... Loss 0.038 ... Accuracy 0.982
... Iteration 8560 ... Epoch 1.58 ... Loss 0.040 ... Accuracy 0.984
... Iteration 8570 ... Epoch 1.58 ... Loss 0.047 ... Accuracy 0.982
... Iteration 8580 ... Epoch 1.58 ... Loss 0.052 ... Accuracy 0.975
... Iteration 8590 ... Epoch 1.58 ... Loss 0.034 ... Accuracy 0.994
... Iteration 8600 ... Epoch 1.58 ... Loss 0.046 ... Accuracy 0.982
... Iteration 8610 ... Epoch 1.59 ... Loss 0.062 ... Accuracy 0.975
... Iteration 8620 ... Epoch 1.59 ... Loss 0.062 ... Accuracy 0.973
... Iteration 8630 ... Epoch 1.59 ... Loss 0.039 ... Accuracy 0.990
... Iteration 8640 ... Epoch 1.59 ... Loss 0.042 ... Accuracy 0.984
... Iteration 8650 ... Epoch 1.59 ... Loss 0.071 ... Accuracy 0.975
... Iteration 8660 ... Epoch 1.59 ... Loss 0.051 ... Accuracy 0.982
... Iteration 8670 ... Epoch 1.60 ... Loss 0.051 ... Accuracy 0.980
... Iteration 8680 ... Epoch 1.60 ... Loss 0.087 ... Accuracy 0.971
... Iteration 8690 ... Epoch 1.60 ... Loss 0.035 ... Accuracy 0.986
... Iteration 8700 ... Epoch 1.60 ... Loss 0.038 ... Accuracy 0.988
... Iteration 8710 ... Epoch 1.60 ... Loss 0.042 ... Accuracy 0.984
... Iteration 8720 ... Epoch 1.61 ... Loss 0.059 ... Accuracy 0.977
... Iteration 8730 ... Epoch 1.61 ... Loss 0.050 ... Accuracy 0.982
... Iteration 8740 ... Epoch 1.61 ... Loss 0.041 ... Accuracy 0.986
... Iteration 8750 ... Epoch 1.61 ... Loss 0.045 ... Accuracy 0.982
... Iteration 8760 ... Epoch 1.61 ... Loss 0.053 ... Accuracy 0.980
... Iteration 8770 ... Epoch 1.61 ... Loss 0.031 ... Accuracy 0.992
... Iteration 8780 ... Epoch 1.62 ... Loss 0.050 ... Accuracy 0.980
... Iteration 8790 ... Epoch 1.62 ... Loss 0.040 ... Accuracy 0.980
... Iteration 8800 ... Epoch 1.62 ... Loss 0.050 ... Accuracy 0.982
... Iteration 8810 ... Epoch 1.62 ... Loss 0.050 ... Accuracy 0.980
... Iteration 8820 ... Epoch 1.62 ... Loss 0.056 ... Accuracy 0.980
... Iteration 8830 ... Epoch 1.63 ... Loss 0.072 ... Accuracy 0.971
... Iteration 8840 ... Epoch 1.63 ... Loss 0.053 ... Accuracy 0.980
... Iteration 8850 ... Epoch 1.63 ... Loss 0.065 ... Accuracy 0.977
... Iteration 8860 ... Epoch 1.63 ... Loss 0.059 ... Accuracy 0.977
... Iteration 8870 ... Epoch 1.63 ... Loss 0.034 ... Accuracy 0.984
... Iteration 8880 ... Epoch 1.64 ... Loss 0.059 ... Accuracy 0.986
... Iteration 8890 ... Epoch 1.64 ... Loss 0.045 ... Accuracy 0.982
... Iteration 8900 ... Epoch 1.64 ... Loss 0.054 ... Accuracy 0.984
... Iteration 8910 ... Epoch 1.64 ... Loss 0.039 ... Accuracy 0.982
... Iteration 8920 ... Epoch 1.64 ... Loss 0.047 ... Accuracy 0.979
... Iteration 8930 ... Epoch 1.64 ... Loss 0.046 ... Accuracy 0.986
... Iteration 8940 ... Epoch 1.65 ... Loss 0.051 ... Accuracy 0.975
... Iteration 8950 ... Epoch 1.65 ... Loss 0.063 ... Accuracy 0.969
... Iteration 8960 ... Epoch 1.65 ... Loss 0.058 ... Accuracy 0.975
... Iteration 8970 ... Epoch 1.65 ... Loss 0.048 ... Accuracy 0.977
... Iteration 8980 ... Epoch 1.65 ... Loss 0.049 ... Accuracy 0.977
... Iteration 8990 ... Epoch 1.66 ... Loss 0.038 ... Accuracy 0.986
... Iteration 9000 ... Epoch 1.66 ... Loss 0.049 ... Accuracy 0.982
... Iteration 9010 ... Epoch 1.66 ... Loss 0.056 ... Accuracy 0.980
... Iteration 9020 ... Epoch 1.66 ... Loss 0.051 ... Accuracy 0.977
... Iteration 9030 ... Epoch 1.66 ... Loss 0.040 ... Accuracy 0.986
... Iteration 9040 ... Epoch 1.66 ... Loss 0.056 ... Accuracy 0.979
... Iteration 9050 ... Epoch 1.67 ... Loss 0.049 ... Accuracy 0.980
... Iteration 9060 ... Epoch 1.67 ... Loss 0.034 ... Accuracy 0.982
... Iteration 9070 ... Epoch 1.67 ... Loss 0.059 ... Accuracy 0.980
... Iteration 9080 ... Epoch 1.67 ... Loss 0.060 ... Accuracy 0.977
... Iteration 9090 ... Epoch 1.67 ... Loss 0.057 ... Accuracy 0.971
... Iteration 9100 ... Epoch 1.68 ... Loss 0.057 ... Accuracy 0.982
... Iteration 9110 ... Epoch 1.68 ... Loss 0.042 ... Accuracy 0.988
... Iteration 9120 ... Epoch 1.68 ... Loss 0.057 ... Accuracy 0.984
... Iteration 9130 ... Epoch 1.68 ... Loss 0.054 ... Accuracy 0.979
... Iteration 9140 ... Epoch 1.68 ... Loss 0.045 ... Accuracy 0.990
... Iteration 9150 ... Epoch 1.68 ... Loss 0.044 ... Accuracy 0.979
... Iteration 9160 ... Epoch 1.69 ... Loss 0.047 ... Accuracy 0.980
... Iteration 9170 ... Epoch 1.69 ... Loss 0.058 ... Accuracy 0.980
... Iteration 9180 ... Epoch 1.69 ... Loss 0.034 ... Accuracy 0.992
... Iteration 9190 ... Epoch 1.69 ... Loss 0.067 ... Accuracy 0.973
... Iteration 9200 ... Epoch 1.69 ... Loss 0.041 ... Accuracy 0.984
... Iteration 9210 ... Epoch 1.70 ... Loss 0.046 ... Accuracy 0.982
... Iteration 9220 ... Epoch 1.70 ... Loss 0.077 ... Accuracy 0.969
... Iteration 9230 ... Epoch 1.70 ... Loss 0.034 ... Accuracy 0.988
... Iteration 9240 ... Epoch 1.70 ... Loss 0.049 ... Accuracy 0.979
... Iteration 9250 ... Epoch 1.70 ... Loss 0.062 ... Accuracy 0.977
... Iteration 9260 ... Epoch 1.71 ... Loss 0.057 ... Accuracy 0.979
... Iteration 9270 ... Epoch 1.71 ... Loss 0.038 ... Accuracy 0.986
... Iteration 9280 ... Epoch 1.71 ... Loss 0.052 ... Accuracy 0.982
... Iteration 9290 ... Epoch 1.71 ... Loss 0.079 ... Accuracy 0.973
... Iteration 9300 ... Epoch 1.71 ... Loss 0.066 ... Accuracy 0.980
... Iteration 9310 ... Epoch 1.71 ... Loss 0.058 ... Accuracy 0.979
... Iteration 9320 ... Epoch 1.72 ... Loss 0.071 ... Accuracy 0.975
... Iteration 9330 ... Epoch 1.72 ... Loss 0.096 ... Accuracy 0.967
... Iteration 9340 ... Epoch 1.72 ... Loss 0.055 ... Accuracy 0.979
... Iteration 9350 ... Epoch 1.72 ... Loss 0.040 ... Accuracy 0.986
... Iteration 9360 ... Epoch 1.72 ... Loss 0.067 ... Accuracy 0.971
... Iteration 9370 ... Epoch 1.73 ... Loss 0.037 ... Accuracy 0.988
... Iteration 9380 ... Epoch 1.73 ... Loss 0.038 ... Accuracy 0.982
... Iteration 9390 ... Epoch 1.73 ... Loss 0.030 ... Accuracy 0.990
... Iteration 9400 ... Epoch 1.73 ... Loss 0.027 ... Accuracy 0.992
... Iteration 9410 ... Epoch 1.73 ... Loss 0.027 ... Accuracy 0.990
... Iteration 9420 ... Epoch 1.73 ... Loss 0.041 ... Accuracy 0.979
... Iteration 9430 ... Epoch 1.74 ... Loss 0.050 ... Accuracy 0.979
... Iteration 9440 ... Epoch 1.74 ... Loss 0.045 ... Accuracy 0.980
... Iteration 9450 ... Epoch 1.74 ... Loss 0.047 ... Accuracy 0.980
... Iteration 9460 ... Epoch 1.74 ... Loss 0.054 ... Accuracy 0.980
... Iteration 9470 ... Epoch 1.74 ... Loss 0.042 ... Accuracy 0.984
... Iteration 9480 ... Epoch 1.75 ... Loss 0.093 ... Accuracy 0.971
... Iteration 9490 ... Epoch 1.75 ... Loss 0.062 ... Accuracy 0.971
... Iteration 9500 ... Epoch 1.75 ... Loss 0.050 ... Accuracy 0.984
... Iteration 9510 ... Epoch 1.75 ... Loss 0.039 ... Accuracy 0.982
... Iteration 9520 ... Epoch 1.75 ... Loss 0.037 ... Accuracy 0.984
... Iteration 9530 ... Epoch 1.75 ... Loss 0.052 ... Accuracy 0.980
... Iteration 9540 ... Epoch 1.76 ... Loss 0.061 ... Accuracy 0.971
... Iteration 9550 ... Epoch 1.76 ... Loss 0.056 ... Accuracy 0.977
... Iteration 9560 ... Epoch 1.76 ... Loss 0.052 ... Accuracy 0.980
... Iteration 9570 ... Epoch 1.76 ... Loss 0.050 ... Accuracy 0.979
... Iteration 9580 ... Epoch 1.76 ... Loss 0.078 ... Accuracy 0.967
... Iteration 9590 ... Epoch 1.77 ... Loss 0.036 ... Accuracy 0.990
... Iteration 9600 ... Epoch 1.77 ... Loss 0.048 ... Accuracy 0.980
... Iteration 9610 ... Epoch 1.77 ... Loss 0.060 ... Accuracy 0.979
... Iteration 9620 ... Epoch 1.77 ... Loss 0.051 ... Accuracy 0.975
... Iteration 9630 ... Epoch 1.77 ... Loss 0.063 ... Accuracy 0.980
... Iteration 9640 ... Epoch 1.77 ... Loss 0.049 ... Accuracy 0.988
... Iteration 9650 ... Epoch 1.78 ... Loss 0.046 ... Accuracy 0.986
... Iteration 9660 ... Epoch 1.78 ... Loss 0.036 ... Accuracy 0.984
... Iteration 9670 ... Epoch 1.78 ... Loss 0.067 ... Accuracy 0.973
... Iteration 9680 ... Epoch 1.78 ... Loss 0.049 ... Accuracy 0.984
... Iteration 9690 ... Epoch 1.78 ... Loss 0.037 ... Accuracy 0.988
... Iteration 9700 ... Epoch 1.79 ... Loss 0.054 ... Accuracy 0.979
... Iteration 9710 ... Epoch 1.79 ... Loss 0.056 ... Accuracy 0.977
... Iteration 9720 ... Epoch 1.79 ... Loss 0.047 ... Accuracy 0.984
... Iteration 9730 ... Epoch 1.79 ... Loss 0.052 ... Accuracy 0.982
... Iteration 9740 ... Epoch 1.79 ... Loss 0.032 ... Accuracy 0.986
... Iteration 9750 ... Epoch 1.80 ... Loss 0.032 ... Accuracy 0.990
... Iteration 9760 ... Epoch 1.80 ... Loss 0.041 ... Accuracy 0.986
... Iteration 9770 ... Epoch 1.80 ... Loss 0.037 ... Accuracy 0.984
... Iteration 9780 ... Epoch 1.80 ... Loss 0.055 ... Accuracy 0.979