androidMotionLogger/julia/logs/log_30_09_2019.log

--------[30_09_2019 14:27:20]--------
second stage Hyperparameter Tuning with 1 net, reevaluation with fixed epochs now, using testset

Configuration learning_rate=0.03, decay_step=20
[14:29:16] INIT Loss(test): 0.191895 Accuarcy: 0.061824
[14:31:42] Epoch   1: Loss(train): 0.093080 Loss(val): 0.092508 acc(val): 0.274541
[14:32:12] Epoch   2: Loss(train): 0.069031 Loss(val): 0.067629 acc(val): 0.436054
[14:32:32] Epoch   3: Loss(train): 0.064291 Loss(val): 0.062943 acc(val): 0.508061
[14:32:52] Epoch   4: Loss(train): 0.060827 Loss(val): 0.059568 acc(val): 0.543418
[14:33:29] Epoch   5: Loss(train): 0.059301 Loss(val): 0.058460 acc(val): 0.555391
[14:33:58] Epoch   6: Loss(train): 0.058672 Loss(val): 0.057920 acc(val): 0.556820
[14:34:30] Epoch   7: Loss(train): 0.057834 Loss(val): 0.057255 acc(val): 0.570561
[14:34:56] Epoch   8: Loss(train): 0.057435 Loss(val): 0.057099 acc(val): 0.570017
[14:35:21] Epoch   9: Loss(train): 0.057113 Loss(val): 0.056812 acc(val): 0.573146
[14:35:39] Epoch  10: Loss(train): 0.057030 Loss(val): 0.056849 acc(val): 0.571531
[14:35:57] Epoch  11: Loss(train): 0.056916 Loss(val): 0.056893 acc(val): 0.572823
[14:36:15] Epoch  12: Loss(train): 0.056653 Loss(val): 0.056813 acc(val): 0.571803
[14:36:34] Epoch  13: Loss(train): 0.056223 Loss(val): 0.056521 acc(val): 0.577925
[14:36:52] Epoch  14: Loss(train): 0.055907 Loss(val): 0.056257 acc(val): 0.581054
[14:37:10] Epoch  15: Loss(train): 0.055811 Loss(val): 0.056153 acc(val): 0.581939
[14:37:29] Epoch  16: Loss(train): 0.055996 Loss(val): 0.056253 acc(val): 0.577585
[14:37:48] Epoch  17: Loss(train): 0.056509 Loss(val): 0.056749 acc(val): 0.566701
[14:38:09] Epoch  18: Loss(train): 0.056736 Loss(val): 0.057002 acc(val): 0.561259
[14:38:28] Epoch  19: Loss(train): 0.056825 Loss(val): 0.057148 acc(val): 0.557993
[14:38:47] Epoch  20: Loss(train): 0.056349 Loss(val): 0.056709 acc(val): 0.564524
[14:39:06] Epoch  21: Loss(train): 0.055339 Loss(val): 0.055721 acc(val): 0.583095
[14:39:25] Epoch  22: Loss(train): 0.054080 Loss(val): 0.054463 acc(val): 0.616633
[14:39:43] Epoch  23: Loss(train): 0.053393 Loss(val): 0.053672 acc(val): 0.634405
[14:40:01] Epoch  24: Loss(train): 0.053121 Loss(val): 0.053326 acc(val): 0.641888
[14:40:21] Epoch  25: Loss(train): 0.053043 Loss(val): 0.053181 acc(val): 0.640799
[14:40:45] Epoch  26: Loss(train): 0.052858 Loss(val): 0.053029 acc(val): 0.641956
[14:41:04] Epoch  27: Loss(train): 0.052826 Loss(val): 0.052986 acc(val): 0.641003
[14:41:23] Epoch  28: Loss(train): 0.052841 Loss(val): 0.053040 acc(val): 0.639337
[14:41:42] Epoch  29: Loss(train): 0.052777 Loss(val): 0.053036 acc(val): 0.638929
[14:42:01] Epoch  30: Loss(train): 0.052711 Loss(val): 0.052963 acc(val): 0.639813
[14:42:20] Epoch  31: Loss(train): 0.052688 Loss(val): 0.052891 acc(val): 0.640765
[14:42:39] Epoch  32: Loss(train): 0.052576 Loss(val): 0.052782 acc(val): 0.643214
[14:42:59] Epoch  33: Loss(train): 0.052667 Loss(val): 0.052730 acc(val): 0.642058
[14:43:17] Epoch  34: Loss(train): 0.052779 Loss(val): 0.052696 acc(val): 0.639490
[14:43:37] Epoch  35: Loss(train): 0.052854 Loss(val): 0.052653 acc(val): 0.637721
[14:43:55] Epoch  36: Loss(train): 0.053212 Loss(val): 0.052754 acc(val): 0.630391
[14:44:14] Epoch  37: Loss(train): 0.053448 Loss(val): 0.052824 acc(val): 0.625561
[14:44:33] Epoch  38: Loss(train): 0.053491 Loss(val): 0.052787 acc(val): 0.625153
[14:44:52] Epoch  39: Loss(train): 0.053333 Loss(val): 0.052663 acc(val): 0.629847
[14:45:11] Epoch  40: Loss(train): 0.052837 Loss(val): 0.052362 acc(val): 0.641480
[14:45:32] Epoch  41: Loss(train): 0.052389 Loss(val): 0.052117 acc(val): 0.649711
[14:45:51] Epoch  42: Loss(train): 0.052066 Loss(val): 0.051959 acc(val): 0.657534
[14:46:10] Epoch  43: Loss(train): 0.051788 Loss(val): 0.051844 acc(val): 0.663503
[14:46:29] Epoch  44: Loss(train): 0.051640 Loss(val): 0.051785 acc(val): 0.666020
[14:46:48] Epoch  45: Loss(train): 0.051530 Loss(val): 0.051748 acc(val): 0.668265
[14:47:07] Epoch  46: Loss(train): 0.051493 Loss(val): 0.051737 acc(val): 0.667857
[14:47:26] Epoch  47: Loss(train): 0.051452 Loss(val): 0.051726 acc(val): 0.668078
[14:47:46] Epoch  48: Loss(train): 0.051433 Loss(val): 0.051714 acc(val): 0.668486
[14:48:05] Epoch  49: Loss(train): 0.051401 Loss(val): 0.051703 acc(val): 0.668690
[14:48:25] Epoch  50: Loss(train): 0.051384 Loss(val): 0.051694 acc(val): 0.669235
[14:48:46] Epoch  51: Loss(train): 0.051362 Loss(val): 0.051680 acc(val): 0.669303
[14:49:05] Epoch  52: Loss(train): 0.051325 Loss(val): 0.051665 acc(val): 0.670527
[14:49:24] Epoch  53: Loss(train): 0.051259 Loss(val): 0.051651 acc(val): 0.670595
[14:49:43] Epoch  54: Loss(train): 0.051197 Loss(val): 0.051644 acc(val): 0.670867
[14:50:02] Epoch  55: Loss(train): 0.051136 Loss(val): 0.051634 acc(val): 0.671276
[14:50:21] Epoch  56: Loss(train): 0.051068 Loss(val): 0.051633 acc(val): 0.671871
[14:50:40] Epoch  57: Loss(train): 0.051019 Loss(val): 0.051637 acc(val): 0.674116
[14:50:59] Epoch  58: Loss(train): 0.050977 Loss(val): 0.051658 acc(val): 0.674456
[14:51:18] Epoch  59: Loss(train): 0.050942 Loss(val): 0.051691 acc(val): 0.673231
[14:51:37] Epoch  60: Loss(train): 0.050919 Loss(val): 0.051711 acc(val): 0.673248
[14:51:56] Epoch  61: Loss(train): 0.050904 Loss(val): 0.051738 acc(val): 0.672704
[14:52:15] Epoch  62: Loss(train): 0.050891 Loss(val): 0.051758 acc(val): 0.672432
[14:52:34] Epoch  63: Loss(train): 0.050875 Loss(val): 0.051761 acc(val): 0.672908
[14:52:53] Epoch  64: Loss(train): 0.050858 Loss(val): 0.051750 acc(val): 0.673248
[14:53:12] Epoch  65: Loss(train): 0.050837 Loss(val): 0.051725 acc(val): 0.674065
[14:53:30] Epoch  66: Loss(train): 0.050814 Loss(val): 0.051685 acc(val): 0.674201
[14:53:49] Epoch  67: Loss(train): 0.050799 Loss(val): 0.051681 acc(val): 0.674133
[14:54:08] Epoch  68: Loss(train): 0.050780 Loss(val): 0.051648 acc(val): 0.674269
[14:54:27] Epoch  69: Loss(train): 0.050765 Loss(val): 0.051627 acc(val): 0.674133
[14:54:46] Epoch  70: Loss(train): 0.050754 Loss(val): 0.051615 acc(val): 0.674133
[14:55:05] Epoch  71: Loss(train): 0.050742 Loss(val): 0.051595 acc(val): 0.674541
[14:55:24] Epoch  72: Loss(train): 0.050732 Loss(val): 0.051581 acc(val): 0.674745
[14:55:42] Epoch  73: Loss(train): 0.050722 Loss(val): 0.051563 acc(val): 0.675561
[14:56:01] Epoch  74: Loss(train): 0.050714 Loss(val): 0.051547 acc(val): 0.675833
[14:56:20] Epoch  75: Loss(train): 0.050708 Loss(val): 0.051543 acc(val): 0.675493
[14:56:38] Epoch  76: Loss(train): 0.050701 Loss(val): 0.051528 acc(val): 0.676446
[14:56:59] Epoch  77: Loss(train): 0.050696 Loss(val): 0.051524 acc(val): 0.676514
[14:57:19] Epoch  78: Loss(train): 0.050690 Loss(val): 0.051518 acc(val): 0.676718
[14:57:39] Epoch  79: Loss(train): 0.050685 Loss(val): 0.051510 acc(val): 0.676990
[14:57:59] Epoch  80: Loss(train): 0.050680 Loss(val): 0.051509 acc(val): 0.677126
[14:58:19] Epoch  81: Loss(train): 0.050676 Loss(val): 0.051503 acc(val): 0.677126
[14:58:39] Epoch  82: Loss(train): 0.050673 Loss(val): 0.051498 acc(val): 0.677398
[14:58:59] Epoch  83: Loss(train): 0.050669 Loss(val): 0.051496 acc(val): 0.677534
[14:59:19] Epoch  84: Loss(train): 0.050666 Loss(val): 0.051490 acc(val): 0.677602
[14:59:40] Epoch  85: Loss(train): 0.050663 Loss(val): 0.051489 acc(val): 0.677330
[15:00:01] Epoch  86: Loss(train): 0.050660 Loss(val): 0.051486 acc(val): 0.677534
[15:00:21] Epoch  87: Loss(train): 0.050657 Loss(val): 0.051482 acc(val): 0.677330
[15:00:41] Epoch  88: Loss(train): 0.050655 Loss(val): 0.051479 acc(val): 0.677602
[15:01:01] Epoch  89: Loss(train): 0.050653 Loss(val): 0.051477 acc(val): 0.677466
[15:01:21] Epoch  90: Loss(train): 0.050651 Loss(val): 0.051476 acc(val): 0.677466
[15:01:41] Epoch  91: Loss(train): 0.050649 Loss(val): 0.051473 acc(val): 0.677534
[15:02:01] Epoch  92: Loss(train): 0.050647 Loss(val): 0.051470 acc(val): 0.677534
[15:02:21] Epoch  93: Loss(train): 0.050646 Loss(val): 0.051464 acc(val): 0.677466
[15:02:41] Epoch  94: Loss(train): 0.050644 Loss(val): 0.051465 acc(val): 0.677534
[15:03:01] Epoch  95: Loss(train): 0.050643 Loss(val): 0.051466 acc(val): 0.677466
[15:03:21] Epoch  96: Loss(train): 0.050641 Loss(val): 0.051465 acc(val): 0.677398
[15:03:42] Epoch  97: Loss(train): 0.050640 Loss(val): 0.051461 acc(val): 0.677330
[15:04:02] Epoch  98: Loss(train): 0.050639 Loss(val): 0.051463 acc(val): 0.677466
[15:04:22] Epoch  99: Loss(train): 0.050638 Loss(val): 0.051463 acc(val): 0.677602
[15:04:43] Epoch 100: Loss(train): 0.050637 Loss(val): 0.051460
[15:04:46] FINAL(100) Loss(test): 0.051915 Accuarcy: 0.600135

Configuration learning_rate=0.03, decay_step=40
[15:04:52] INIT Loss(test): 0.133920 Accuarcy: 0.117973
[15:05:10] Epoch   1: Loss(train): 0.085145 Loss(val): 0.084277 acc(val): 0.303997
[15:05:31] Epoch   2: Loss(train): 0.068091 Loss(val): 0.066436 acc(val): 0.462330
[15:05:52] Epoch   3: Loss(train): 0.062043 Loss(val): 0.061092 acc(val): 0.528452
[15:06:12] Epoch   4: Loss(train): 0.059993 Loss(val): 0.059272 acc(val): 0.556088
[15:06:32] Epoch   5: Loss(train): 0.058545 Loss(val): 0.058204 acc(val): 0.572500
[15:06:53] Epoch   6: Loss(train): 0.057621 Loss(val): 0.057397 acc(val): 0.584167
[15:07:14] Epoch   7: Loss(train): 0.057388 Loss(val): 0.057294 acc(val): 0.581582
[15:07:35] Epoch   8: Loss(train): 0.057485 Loss(val): 0.057341 acc(val): 0.577262
[15:07:55] Epoch   9: Loss(train): 0.057354 Loss(val): 0.057369 acc(val): 0.581293
[15:08:16] Epoch  10: Loss(train): 0.056581 Loss(val): 0.056680 acc(val): 0.596803
[15:08:36] Epoch  11: Loss(train): 0.056511 Loss(val): 0.056548 acc(val): 0.596735
[15:08:56] Epoch  12: Loss(train): 0.056471 Loss(val): 0.056751 acc(val): 0.591293
[15:09:16] Epoch  13: Loss(train): 0.056514 Loss(val): 0.056947 acc(val): 0.584286
[15:09:35] Epoch  14: Loss(train): 0.056266 Loss(val): 0.056668 acc(val): 0.586871
[15:09:55] Epoch  15: Loss(train): 0.056044 Loss(val): 0.056443 acc(val): 0.589592
[15:10:16] Epoch  16: Loss(train): 0.056162 Loss(val): 0.056465 acc(val): 0.584524
[15:10:36] Epoch  17: Loss(train): 0.056294 Loss(val): 0.056613 acc(val): 0.581003
[15:10:56] Epoch  18: Loss(train): 0.056623 Loss(val): 0.056966 acc(val): 0.573537
[15:11:16] Epoch  19: Loss(train): 0.056799 Loss(val): 0.057218 acc(val): 0.571514
[15:11:37] Epoch  20: Loss(train): 0.056388 Loss(val): 0.056934 acc(val): 0.577432
[15:11:58] Epoch  21: Loss(train): 0.055646 Loss(val): 0.056139 acc(val): 0.588741
[15:12:19] Epoch  22: Loss(train): 0.054702 Loss(val): 0.055054 acc(val): 0.609184
[15:12:39] Epoch  23: Loss(train): 0.054107 Loss(val): 0.054288 acc(val): 0.625357
[15:12:59] Epoch  24: Loss(train): 0.053836 Loss(val): 0.053849 acc(val): 0.634252
[15:13:19] Epoch  25: Loss(train): 0.053429 Loss(val): 0.053493 acc(val): 0.643112
[15:13:40] Epoch  26: Loss(train): 0.053345 Loss(val): 0.053398 acc(val): 0.643912
[15:14:01] Epoch  27: Loss(train): 0.053229 Loss(val): 0.053307 acc(val): 0.645136
[15:14:21] Epoch  28: Loss(train): 0.053138 Loss(val): 0.053215 acc(val): 0.644388
[15:14:42] Epoch  29: Loss(train): 0.052939 Loss(val): 0.053058 acc(val): 0.649422
[15:15:03] Epoch  30: Loss(train): 0.052790 Loss(val): 0.052942 acc(val): 0.651071
[15:15:23] Epoch  31: Loss(train): 0.052683 Loss(val): 0.052816 acc(val): 0.653112
[15:15:44] Epoch  32: Loss(train): 0.052602 Loss(val): 0.052753 acc(val): 0.654065
[15:16:05] Epoch  33: Loss(train): 0.052579 Loss(val): 0.052674 acc(val): 0.654133
[15:16:26] Epoch  34: Loss(train): 0.052610 Loss(val): 0.052597 acc(val): 0.655085
[15:16:47] Epoch  35: Loss(train): 0.052611 Loss(val): 0.052530 acc(val): 0.655357
[15:17:11] Epoch  36: Loss(train): 0.052680 Loss(val): 0.052476 acc(val): 0.653639
[15:17:34] Epoch  37: Loss(train): 0.052791 Loss(val): 0.052449 acc(val): 0.653095
[15:17:58] Epoch  38: Loss(train): 0.052758 Loss(val): 0.052363 acc(val): 0.655340
[15:18:21] Epoch  39: Loss(train): 0.052682 Loss(val): 0.052269 acc(val): 0.656905
[15:18:43] Epoch  40: Loss(train): 0.052525 Loss(val): 0.052156 acc(val): 0.661003
[15:19:03] Epoch  41: Loss(train): 0.052267 Loss(val): 0.051996 acc(val): 0.665833
[15:19:24] Epoch  42: Loss(train): 0.051986 Loss(val): 0.051854 acc(val): 0.671139
[15:19:44] Epoch  43: Loss(train): 0.051762 Loss(val): 0.051751 acc(val): 0.675017
[15:20:04] Epoch  44: Loss(train): 0.051592 Loss(val): 0.051681 acc(val): 0.679235
[15:20:25] Epoch  45: Loss(train): 0.051479 Loss(val): 0.051643 acc(val): 0.680119
[15:20:45] Epoch  46: Loss(train): 0.051394 Loss(val): 0.051616 acc(val): 0.681071
[15:21:05] Epoch  47: Loss(train): 0.051367 Loss(val): 0.051600 acc(val): 0.680051
[15:21:25] Epoch  48: Loss(train): 0.051341 Loss(val): 0.051579 acc(val): 0.680867
[15:21:46] Epoch  49: Loss(train): 0.051304 Loss(val): 0.051564 acc(val): 0.681344
[15:22:06] Epoch  50: Loss(train): 0.051285 Loss(val): 0.051563 acc(val): 0.681003
[15:22:26] Epoch  51: Loss(train): 0.051286 Loss(val): 0.051553 acc(val): 0.681888
[15:22:50] Epoch  52: Loss(train): 0.051247 Loss(val): 0.051551 acc(val): 0.681548
[15:23:29] Epoch  53: Loss(train): 0.051221 Loss(val): 0.051543 acc(val): 0.681412
[15:24:06] Epoch  54: Loss(train): 0.051172 Loss(val): 0.051541 acc(val): 0.680663
[15:24:47] Epoch  55: Loss(train): 0.051131 Loss(val): 0.051537 acc(val): 0.679711
[15:25:26] Epoch  56: Loss(train): 0.051072 Loss(val): 0.051525 acc(val): 0.680459
[15:26:06] Epoch  57: Loss(train): 0.051019 Loss(val): 0.051529 acc(val): 0.679575
[15:26:46] Epoch  58: Loss(train): 0.050963 Loss(val): 0.051544 acc(val): 0.680816
[15:27:24] Epoch  59: Loss(train): 0.050920 Loss(val): 0.051560 acc(val): 0.680884
[15:28:03] Epoch  60: Loss(train): 0.050894 Loss(val): 0.051591 acc(val): 0.681429
[15:28:39] Epoch  61: Loss(train): 0.050878 Loss(val): 0.051636 acc(val): 0.680408
[15:29:12] Epoch  62: Loss(train): 0.050867 Loss(val): 0.051668 acc(val): 0.678844
[15:29:41] Epoch  63: Loss(train): 0.050860 Loss(val): 0.051702 acc(val): 0.676667
[15:30:06] Epoch  64: Loss(train): 0.050847 Loss(val): 0.051702 acc(val): 0.677619
[15:30:36] Epoch  65: Loss(train): 0.050832 Loss(val): 0.051699 acc(val): 0.677211
[15:30:56] Epoch  66: Loss(train): 0.050821 Loss(val): 0.051700 acc(val): 0.677687
[15:31:17] Epoch  67: Loss(train): 0.050801 Loss(val): 0.051675 acc(val): 0.678435
[15:31:38] Epoch  68: Loss(train): 0.050779 Loss(val): 0.051646 acc(val): 0.678980
[15:31:59] Epoch  69: Loss(train): 0.050759 Loss(val): 0.051619 acc(val): 0.679796
[15:32:20] Epoch  70: Loss(train): 0.050744 Loss(val): 0.051600 acc(val): 0.679796
[15:32:41] Epoch  71: Loss(train): 0.050733 Loss(val): 0.051590 acc(val): 0.680272
[15:33:02] Epoch  72: Loss(train): 0.050716 Loss(val): 0.051555 acc(val): 0.680748
[15:33:23] Epoch  73: Loss(train): 0.050704 Loss(val): 0.051538 acc(val): 0.681156
[15:33:44] Epoch  74: Loss(train): 0.050693 Loss(val): 0.051523 acc(val): 0.681156
[15:34:06] Epoch  75: Loss(train): 0.050684 Loss(val): 0.051510 acc(val): 0.681361
[15:34:29] Epoch  76: Loss(train): 0.050677 Loss(val): 0.051499 acc(val): 0.681905
[15:35:14] Epoch  77: Loss(train): 0.050668 Loss(val): 0.051481 acc(val): 0.682041
[15:35:46] Epoch  78: Loss(train): 0.050662 Loss(val): 0.051477 acc(val): 0.681769
[15:36:15] Epoch  79: Loss(train): 0.050656 Loss(val): 0.051464 acc(val): 0.682041
[15:36:43] Epoch  80: Loss(train): 0.050651 Loss(val): 0.051460 acc(val): 0.682177
[15:37:03] Epoch  81: Loss(train): 0.050647 Loss(val): 0.051460 acc(val): 0.681633
[15:37:24] Epoch  82: Loss(train): 0.050642 Loss(val): 0.051450 acc(val): 0.681633
[15:37:45] Epoch  83: Loss(train): 0.050638 Loss(val): 0.051445 acc(val): 0.681429
[15:38:07] Epoch  84: Loss(train): 0.050634 Loss(val): 0.051439 acc(val): 0.681293
[15:38:29] Epoch  85: Loss(train): 0.050631 Loss(val): 0.051434 acc(val): 0.681224
[15:38:50] Epoch  86: Loss(train): 0.050628 Loss(val): 0.051434 acc(val): 0.681497
[15:39:11] Epoch  87: Loss(train): 0.050625 Loss(val): 0.051429 acc(val): 0.681565
[15:39:32] Epoch  88: Loss(train): 0.050622 Loss(val): 0.051431 acc(val): 0.681633
[15:39:53] Epoch  89: Loss(train): 0.050619 Loss(val): 0.051418 acc(val): 0.681293
[15:40:18] Epoch  90: Loss(train): 0.050617 Loss(val): 0.051419 acc(val): 0.681361
[15:40:47] Epoch  91: Loss(train): 0.050615 Loss(val): 0.051416 acc(val): 0.681429
[15:41:10] Epoch  92: Loss(train): 0.050613 Loss(val): 0.051413 acc(val): 0.681429
[15:41:34] Epoch  93: Loss(train): 0.050611 Loss(val): 0.051410 acc(val): 0.681429
[15:41:55] Epoch  94: Loss(train): 0.050610 Loss(val): 0.051410 acc(val): 0.681497
[15:42:17] Epoch  95: Loss(train): 0.050608 Loss(val): 0.051405 acc(val): 0.681769
[15:42:38] Epoch  96: Loss(train): 0.050606 Loss(val): 0.051401 acc(val): 0.681905
[15:42:59] Epoch  97: Loss(train): 0.050605 Loss(val): 0.051403 acc(val): 0.681429
[15:43:20] Epoch  98: Loss(train): 0.050604 Loss(val): 0.051404 acc(val): 0.681361
[15:43:41] Epoch  99: Loss(train): 0.050603 Loss(val): 0.051399 acc(val): 0.681565
[15:44:02] Epoch 100: Loss(train): 0.050602 Loss(val): 0.051401
[15:44:05] FINAL(100) Loss(test): 0.051667 Accuarcy: 0.604730

Configuration learning_rate=0.03, decay_step=60
[15:44:11] INIT Loss(test): 0.142111 Accuarcy: 0.116081
[15:44:29] Epoch   1: Loss(train): 0.085466 Loss(val): 0.083448 acc(val): 0.324014
[15:44:52] Epoch   2: Loss(train): 0.067009 Loss(val): 0.065906 acc(val): 0.454150
[15:45:17] Epoch   3: Loss(train): 0.063191 Loss(val): 0.062418 acc(val): 0.506139
[15:45:38] Epoch   4: Loss(train): 0.059964 Loss(val): 0.059266 acc(val): 0.545680
[15:46:00] Epoch   5: Loss(train): 0.059229 Loss(val): 0.058537 acc(val): 0.556088
[15:46:21] Epoch   6: Loss(train): 0.059260 Loss(val): 0.058677 acc(val): 0.551599
[15:46:42] Epoch   7: Loss(train): 0.059613 Loss(val): 0.058838 acc(val): 0.540663
[15:47:04] Epoch   8: Loss(train): 0.058372 Loss(val): 0.057957 acc(val): 0.553929
[15:47:25] Epoch   9: Loss(train): 0.058023 Loss(val): 0.057690 acc(val): 0.559796
[15:47:47] Epoch  10: Loss(train): 0.058341 Loss(val): 0.057856 acc(val): 0.557891
[15:48:08] Epoch  11: Loss(train): 0.058291 Loss(val): 0.057867 acc(val): 0.555442
[15:48:29] Epoch  12: Loss(train): 0.057441 Loss(val): 0.057287 acc(val): 0.566054
[15:48:51] Epoch  13: Loss(train): 0.056272 Loss(val): 0.056194 acc(val): 0.584490
[15:49:13] Epoch  14: Loss(train): 0.055851 Loss(val): 0.055663 acc(val): 0.594898
[15:49:36] Epoch  15: Loss(train): 0.055405 Loss(val): 0.055219 acc(val): 0.603129
[15:49:58] Epoch  16: Loss(train): 0.055548 Loss(val): 0.055248 acc(val): 0.600952
[15:50:20] Epoch  17: Loss(train): 0.055654 Loss(val): 0.055321 acc(val): 0.599456
[15:50:41] Epoch  18: Loss(train): 0.055723 Loss(val): 0.055456 acc(val): 0.598384
[15:51:03] Epoch  19: Loss(train): 0.055744 Loss(val): 0.055502 acc(val): 0.597228
[15:51:25] Epoch  20: Loss(train): 0.055564 Loss(val): 0.055416 acc(val): 0.596956
[15:51:48] Epoch  21: Loss(train): 0.055276 Loss(val): 0.055244 acc(val): 0.600612
[15:52:11] Epoch  22: Loss(train): 0.054920 Loss(val): 0.054917 acc(val): 0.607024
[15:52:34] Epoch  23: Loss(train): 0.054450 Loss(val): 0.054397 acc(val): 0.612534
[15:52:57] Epoch  24: Loss(train): 0.054105 Loss(val): 0.053996 acc(val): 0.619677
[15:53:19] Epoch  25: Loss(train): 0.053674 Loss(val): 0.053549 acc(val): 0.630493
[15:53:42] Epoch  26: Loss(train): 0.053361 Loss(val): 0.053270 acc(val): 0.637772
[15:54:11] Epoch  27: Loss(train): 0.053233 Loss(val): 0.053125 acc(val): 0.640765
[15:54:50] Epoch  28: Loss(train): 0.053071 Loss(val): 0.053007 acc(val): 0.644643
[15:55:27] Epoch  29: Loss(train): 0.052948 Loss(val): 0.052935 acc(val): 0.644099
[15:56:04] Epoch  30: Loss(train): 0.052997 Loss(val): 0.052941 acc(val): 0.643214
[15:56:40] Epoch  31: Loss(train): 0.053064 Loss(val): 0.052970 acc(val): 0.639133
[15:57:17] Epoch  32: Loss(train): 0.053172 Loss(val): 0.052973 acc(val): 0.636888
[15:57:43] Epoch  33: Loss(train): 0.053340 Loss(val): 0.053012 acc(val): 0.632194
[15:58:05] Epoch  34: Loss(train): 0.053407 Loss(val): 0.053008 acc(val): 0.631173
[15:58:26] Epoch  35: Loss(train): 0.053488 Loss(val): 0.053011 acc(val): 0.630561
[15:58:48] Epoch  36: Loss(train): 0.053523 Loss(val): 0.052991 acc(val): 0.626956
[15:59:11] Epoch  37: Loss(train): 0.053434 Loss(val): 0.052903 acc(val): 0.629473
[15:59:39] Epoch  38: Loss(train): 0.053004 Loss(val): 0.052646 acc(val): 0.638656
[16:00:06] Epoch  39: Loss(train): 0.052548 Loss(val): 0.052387 acc(val): 0.650289
[16:00:30] Epoch  40: Loss(train): 0.052184 Loss(val): 0.052197 acc(val): 0.658656
[16:00:53] Epoch  41: Loss(train): 0.051921 Loss(val): 0.052086 acc(val): 0.663895
[16:01:25] Epoch  42: Loss(train): 0.051787 Loss(val): 0.052001 acc(val): 0.667024
[16:01:57] Epoch  43: Loss(train): 0.051664 Loss(val): 0.051921 acc(val): 0.669269
[16:02:21] Epoch  44: Loss(train): 0.051557 Loss(val): 0.051856 acc(val): 0.670272
[16:02:57] Epoch  45: Loss(train): 0.051499 Loss(val): 0.051807 acc(val): 0.671582
[16:03:22] Epoch  46: Loss(train): 0.051440 Loss(val): 0.051767 acc(val): 0.672058
[16:03:51] Epoch  47: Loss(train): 0.051405 Loss(val): 0.051744 acc(val): 0.672874
[16:04:31] Epoch  48: Loss(train): 0.051368 Loss(val): 0.051721 acc(val): 0.673146
[16:05:07] Epoch  49: Loss(train): 0.051326 Loss(val): 0.051705 acc(val): 0.673690
[16:05:30] Epoch  50: Loss(train): 0.051288 Loss(val): 0.051689 acc(val): 0.673759
[16:05:53] Epoch  51: Loss(train): 0.051239 Loss(val): 0.051667 acc(val): 0.674915
[16:06:16] Epoch  52: Loss(train): 0.051180 Loss(val): 0.051656 acc(val): 0.675595
[16:06:38] Epoch  53: Loss(train): 0.051117 Loss(val): 0.051658 acc(val): 0.677500
[16:07:00] Epoch  54: Loss(train): 0.051078 Loss(val): 0.051665 acc(val): 0.678044
[16:07:22] Epoch  55: Loss(train): 0.051036 Loss(val): 0.051678 acc(val): 0.677432
[16:07:45] Epoch  56: Loss(train): 0.051011 Loss(val): 0.051702 acc(val): 0.677636
[16:08:08] Epoch  57: Loss(train): 0.050990 Loss(val): 0.051737 acc(val): 0.676752
[16:08:31] Epoch  58: Loss(train): 0.050977 Loss(val): 0.051756 acc(val): 0.675323
[16:08:56] Epoch  59: Loss(train): 0.050971 Loss(val): 0.051791 acc(val): 0.675867
[16:09:23] Epoch  60: Loss(train): 0.050955 Loss(val): 0.051786 acc(val): 0.675272
[16:09:49] Epoch  61: Loss(train): 0.050941 Loss(val): 0.051792 acc(val): 0.675544
[16:10:14] Epoch  62: Loss(train): 0.050929 Loss(val): 0.051794 acc(val): 0.674864
[16:10:37] Epoch  63: Loss(train): 0.050904 Loss(val): 0.051764 acc(val): 0.674932
[16:10:59] Epoch  64: Loss(train): 0.050879 Loss(val): 0.051731 acc(val): 0.675476
[16:11:22] Epoch  65: Loss(train): 0.050859 Loss(val): 0.051707 acc(val): 0.676361
[16:11:44] Epoch  66: Loss(train): 0.050838 Loss(val): 0.051671 acc(val): 0.677857
[16:12:06] Epoch  67: Loss(train): 0.050822 Loss(val): 0.051655 acc(val): 0.678741
[16:12:28] Epoch  68: Loss(train): 0.050804 Loss(val): 0.051619 acc(val): 0.680238
[16:12:50] Epoch  69: Loss(train): 0.050792 Loss(val): 0.051603 acc(val): 0.680170
[16:13:14] Epoch  70: Loss(train): 0.050781 Loss(val): 0.051588 acc(val): 0.680510
[16:13:37] Epoch  71: Loss(train): 0.050770 Loss(val): 0.051567 acc(val): 0.681463
[16:14:00] Epoch  72: Loss(train): 0.050762 Loss(val): 0.051553 acc(val): 0.681463
[16:14:23] Epoch  73: Loss(train): 0.050755 Loss(val): 0.051545 acc(val): 0.681531
[16:14:47] Epoch  74: Loss(train): 0.050748 Loss(val): 0.051538 acc(val): 0.680986
[16:15:11] Epoch  75: Loss(train): 0.050742 Loss(val): 0.051527 acc(val): 0.681259
[16:15:33] Epoch  76: Loss(train): 0.050736 Loss(val): 0.051523 acc(val): 0.681054
[16:15:56] Epoch  77: Loss(train): 0.050731 Loss(val): 0.051517 acc(val): 0.681122
[16:16:19] Epoch  78: Loss(train): 0.050726 Loss(val): 0.051506 acc(val): 0.681463
[16:16:41] Epoch  79: Loss(train): 0.050722 Loss(val): 0.051507 acc(val): 0.681463
[16:17:04] Epoch  80: Loss(train): 0.050717 Loss(val): 0.051499 acc(val): 0.681259
[16:17:26] Epoch  81: Loss(train): 0.050713 Loss(val): 0.051492 acc(val): 0.681463
[16:17:49] Epoch  82: Loss(train): 0.050709 Loss(val): 0.051488 acc(val): 0.681122
[16:18:12] Epoch  83: Loss(train): 0.050706 Loss(val): 0.051491 acc(val): 0.681463
[16:18:35] Epoch  84: Loss(train): 0.050703 Loss(val): 0.051484 acc(val): 0.681463
[16:18:57] Epoch  85: Loss(train): 0.050700 Loss(val): 0.051476 acc(val): 0.681939
[16:19:20] Epoch  86: Loss(train): 0.050698 Loss(val): 0.051476 acc(val): 0.681803
[16:19:43] Epoch  87: Loss(train): 0.050695 Loss(val): 0.051471 acc(val): 0.682007
[16:20:05] Epoch  88: Loss(train): 0.050693 Loss(val): 0.051474 acc(val): 0.681735
[16:20:28] Epoch  89: Loss(train): 0.050691 Loss(val): 0.051469 acc(val): 0.681939
[16:20:51] Epoch  90: Loss(train): 0.050689 Loss(val): 0.051463 acc(val): 0.681803
[16:21:14] Epoch  91: Loss(train): 0.050687 Loss(val): 0.051464 acc(val): 0.681803
[16:21:37] Epoch  92: Loss(train): 0.050685 Loss(val): 0.051462 acc(val): 0.681667
[16:21:59] Epoch  93: Loss(train): 0.050683 Loss(val): 0.051460 acc(val): 0.681939
[16:22:22] Epoch  94: Loss(train): 0.050682 Loss(val): 0.051455 acc(val): 0.682007
[16:22:45] Epoch  95: Loss(train): 0.050681 Loss(val): 0.051457 acc(val): 0.681939
[16:23:08] Epoch  96: Loss(train): 0.050679 Loss(val): 0.051455 acc(val): 0.682007
[16:23:31] Epoch  97: Loss(train): 0.050678 Loss(val): 0.051454 acc(val): 0.682075
[16:23:54] Epoch  98: Loss(train): 0.050677 Loss(val): 0.051455 acc(val): 0.682211
[16:24:17] Epoch  99: Loss(train): 0.050676 Loss(val): 0.051454 acc(val): 0.682211
[16:24:40] Epoch 100: Loss(train): 0.050675 Loss(val): 0.051452
[16:24:43] FINAL(100) Loss(test): 0.051842 Accuarcy: 0.601622

Configuration learning_rate=0.01, decay_step=20
[16:24:49] INIT Loss(test): 0.123722 Accuarcy: 0.127973
[16:25:10] Epoch   1: Loss(train): 0.086237 Loss(val): 0.086168 acc(val): 0.291888
[16:25:47] Epoch   2: Loss(train): 0.066817 Loss(val): 0.065911 acc(val): 0.445901
[16:26:21] Epoch   3: Loss(train): 0.063177 Loss(val): 0.062407 acc(val): 0.499915
[16:26:54] Epoch   4: Loss(train): 0.061026 Loss(val): 0.060297 acc(val): 0.540425
[16:27:28] Epoch   5: Loss(train): 0.059943 Loss(val): 0.059473 acc(val): 0.551259
[16:28:03] Epoch   6: Loss(train): 0.058618 Loss(val): 0.058114 acc(val): 0.565204
[16:28:45] Epoch   7: Loss(train): 0.057991 Loss(val): 0.057816 acc(val): 0.570017
[16:29:12] Epoch   8: Loss(train): 0.057960 Loss(val): 0.057804 acc(val): 0.568316
[16:29:53] Epoch   9: Loss(train): 0.058586 Loss(val): 0.058320 acc(val): 0.558980
[16:31:02] Epoch  10: Loss(train): 0.058809 Loss(val): 0.058750 acc(val): 0.551156
[16:32:04] Epoch  11: Loss(train): 0.057933 Loss(val): 0.058105 acc(val): 0.555714
[16:33:09] Epoch  12: Loss(train): 0.057471 Loss(val): 0.057670 acc(val): 0.557619
[16:34:03] Epoch  13: Loss(train): 0.057318 Loss(val): 0.057520 acc(val): 0.555918
[16:34:45] Epoch  14: Loss(train): 0.057432 Loss(val): 0.057578 acc(val): 0.551905
[16:35:26] Epoch  15: Loss(train): 0.057712 Loss(val): 0.057838 acc(val): 0.549864
[16:36:24] Epoch  16: Loss(train): 0.058157 Loss(val): 0.058160 acc(val): 0.547075
[16:37:16] Epoch  17: Loss(train): 0.058045 Loss(val): 0.058048 acc(val): 0.550969
[16:38:01] Epoch  18: Loss(train): 0.057258 Loss(val): 0.057315 acc(val): 0.562279
[16:38:48] Epoch  19: Loss(train): 0.056103 Loss(val): 0.056101 acc(val): 0.582143
[16:39:35] Epoch  20: Loss(train): 0.055167 Loss(val): 0.055090 acc(val): 0.605000
[16:40:16] Epoch  21: Loss(train): 0.054440 Loss(val): 0.054323 acc(val): 0.621939
[16:40:59] Epoch  22: Loss(train): 0.053996 Loss(val): 0.053912 acc(val): 0.627585
[16:41:44] Epoch  23: Loss(train): 0.053813 Loss(val): 0.053733 acc(val): 0.627653
[16:42:31] Epoch  24: Loss(train): 0.053584 Loss(val): 0.053587 acc(val): 0.629626
[16:43:12] Epoch  25: Loss(train): 0.053363 Loss(val): 0.053465 acc(val): 0.630238
[16:43:56] Epoch  26: Loss(train): 0.053242 Loss(val): 0.053413 acc(val): 0.630306
[16:44:40] Epoch  27: Loss(train): 0.053028 Loss(val): 0.053261 acc(val): 0.634932
[16:45:23] Epoch  28: Loss(train): 0.052812 Loss(val): 0.053128 acc(val): 0.638197
[16:46:04] Epoch  29: Loss(train): 0.052652 Loss(val): 0.052984 acc(val): 0.642143
[16:46:49] Epoch  30: Loss(train): 0.052535 Loss(val): 0.052863 acc(val): 0.645680
[16:47:31] Epoch  31: Loss(train): 0.052439 Loss(val): 0.052725 acc(val): 0.649694
[16:48:14] Epoch  32: Loss(train): 0.052366 Loss(val): 0.052586 acc(val): 0.653844
[16:48:57] Epoch  33: Loss(train): 0.052277 Loss(val): 0.052462 acc(val): 0.655204
[16:49:39] Epoch  34: Loss(train): 0.052236 Loss(val): 0.052378 acc(val): 0.655340
[16:50:20] Epoch  35: Loss(train): 0.052206 Loss(val): 0.052301 acc(val): 0.656905
[16:51:02] Epoch  36: Loss(train): 0.052131 Loss(val): 0.052229 acc(val): 0.657262
[16:51:43] Epoch  37: Loss(train): 0.052080 Loss(val): 0.052175 acc(val): 0.659235
[16:52:26] Epoch  38: Loss(train): 0.051932 Loss(val): 0.052086 acc(val): 0.663112
[16:53:08] Epoch  39: Loss(train): 0.051834 Loss(val): 0.052032 acc(val): 0.663929
[16:53:52] Epoch  40: Loss(train): 0.051742 Loss(val): 0.051984 acc(val): 0.664745
[16:54:35] Epoch  41: Loss(train): 0.051577 Loss(val): 0.051924 acc(val): 0.668078
[16:55:19] Epoch  42: Loss(train): 0.051501 Loss(val): 0.051901 acc(val): 0.667466
[16:56:06] Epoch  43: Loss(train): 0.051449 Loss(val): 0.051876 acc(val): 0.668078
[16:57:15] Epoch  44: Loss(train): 0.051393 Loss(val): 0.051869 acc(val): 0.667721
[16:58:19] Epoch  45: Loss(train): 0.051368 Loss(val): 0.051851 acc(val): 0.666497
[16:59:26] Epoch  46: Loss(train): 0.051376 Loss(val): 0.051837 acc(val): 0.666241
[17:00:17] Epoch  47: Loss(train): 0.051365 Loss(val): 0.051807 acc(val): 0.667398
[17:01:31] Epoch  48: Loss(train): 0.051349 Loss(val): 0.051793 acc(val): 0.667262
[17:02:32] Epoch  49: Loss(train): 0.051350 Loss(val): 0.051774 acc(val): 0.667262
[17:03:24] Epoch  50: Loss(train): 0.051308 Loss(val): 0.051759 acc(val): 0.668622
[17:04:19] Epoch  51: Loss(train): 0.051285 Loss(val): 0.051734 acc(val): 0.669439
[17:05:10] Epoch  52: Loss(train): 0.051267 Loss(val): 0.051716 acc(val): 0.669847
[17:05:54] Epoch  53: Loss(train): 0.051197 Loss(val): 0.051707 acc(val): 0.670663
[17:06:43] Epoch  54: Loss(train): 0.051160 Loss(val): 0.051691 acc(val): 0.672432
[17:07:32] Epoch  55: Loss(train): 0.051111 Loss(val): 0.051690 acc(val): 0.672772
[17:08:29] Epoch  56: Loss(train): 0.051065 Loss(val): 0.051692 acc(val): 0.674269
[17:09:18] Epoch  57: Loss(train): 0.051019 Loss(val): 0.051708 acc(val): 0.672483
[17:10:05] Epoch  58: Loss(train): 0.050985 Loss(val): 0.051736 acc(val): 0.673231
[17:10:50] Epoch  59: Loss(train): 0.050964 Loss(val): 0.051761 acc(val): 0.673163
[17:11:38] Epoch  60: Loss(train): 0.050948 Loss(val): 0.051782 acc(val): 0.671667
[17:12:21] Epoch  61: Loss(train): 0.050943 Loss(val): 0.051836 acc(val): 0.671684
[17:13:13] Epoch  62: Loss(train): 0.050930 Loss(val): 0.051840 acc(val): 0.671412
[17:14:01] Epoch  63: Loss(train): 0.050921 Loss(val): 0.051851 acc(val): 0.671276
[17:14:46] Epoch  64: Loss(train): 0.050902 Loss(val): 0.051832 acc(val): 0.671956
[17:15:30] Epoch  65: Loss(train): 0.050885 Loss(val): 0.051809 acc(val): 0.672092
[17:16:19] Epoch  66: Loss(train): 0.050869 Loss(val): 0.051790 acc(val): 0.672024
[17:17:03] Epoch  67: Loss(train): 0.050854 Loss(val): 0.051774 acc(val): 0.673044
[17:17:51] Epoch  68: Loss(train): 0.050836 Loss(val): 0.051741 acc(val): 0.672891
[17:18:37] Epoch  69: Loss(train): 0.050824 Loss(val): 0.051727 acc(val): 0.673435
[17:19:23] Epoch  70: Loss(train): 0.050812 Loss(val): 0.051704 acc(val): 0.674116
[17:20:07] Epoch  71: Loss(train): 0.050800 Loss(val): 0.051679 acc(val): 0.673912
[17:20:53] Epoch  72: Loss(train): 0.050792 Loss(val): 0.051671 acc(val): 0.674388
[17:21:38] Epoch  73: Loss(train): 0.050785 Loss(val): 0.051665 acc(val): 0.673776
[17:22:24] Epoch  74: Loss(train): 0.050776 Loss(val): 0.051649 acc(val): 0.674116
[17:23:09] Epoch  75: Loss(train): 0.050770 Loss(val): 0.051641 acc(val): 0.674660
[17:23:55] Epoch  76: Loss(train): 0.050764 Loss(val): 0.051627 acc(val): 0.675544
[17:24:40] Epoch  77: Loss(train): 0.050759 Loss(val): 0.051624 acc(val): 0.675408
[17:25:26] Epoch  78: Loss(train): 0.050753 Loss(val): 0.051614 acc(val): 0.675952
[17:26:11] Epoch  79: Loss(train): 0.050748 Loss(val): 0.051609 acc(val): 0.675612
[17:27:19] Epoch  80: Loss(train): 0.050744 Loss(val): 0.051604 acc(val): 0.675884
[17:28:38] Epoch  81: Loss(train): 0.050740 Loss(val): 0.051599 acc(val): 0.675816
[17:29:45] Epoch  82: Loss(train): 0.050736 Loss(val): 0.051592 acc(val): 0.676020
[17:30:30] Epoch  83: Loss(train): 0.050733 Loss(val): 0.051590 acc(val): 0.676088
[17:31:31] Epoch  84: Loss(train): 0.050730 Loss(val): 0.051590 acc(val): 0.676020
[17:32:34] Epoch  85: Loss(train): 0.050727 Loss(val): 0.051587 acc(val): 0.676293
[17:33:24] Epoch  86: Loss(train): 0.050724 Loss(val): 0.051580 acc(val): 0.676429
[17:34:37] Epoch  87: Loss(train): 0.050721 Loss(val): 0.051575 acc(val): 0.676837
[17:35:41] Epoch  88: Loss(train): 0.050719 Loss(val): 0.051574 acc(val): 0.676769
[17:36:29] Epoch  89: Loss(train): 0.050717 Loss(val): 0.051573 acc(val): 0.676701
[17:37:33] Epoch  90: Loss(train): 0.050715 Loss(val): 0.051568 acc(val): 0.676701
[17:38:23] Epoch  91: Loss(train): 0.050713 Loss(val): 0.051565 acc(val): 0.676905
[17:39:10] Epoch  92: Loss(train): 0.050712 Loss(val): 0.051564 acc(val): 0.676837
[17:39:57] Epoch  93: Loss(train): 0.050710 Loss(val): 0.051562 acc(val): 0.677177
[17:40:43] Epoch  94: Loss(train): 0.050709 Loss(val): 0.051560 acc(val): 0.676973
[17:41:33] Epoch  95: Loss(train): 0.050707 Loss(val): 0.051559 acc(val): 0.676905
[17:42:22] Epoch  96: Loss(train): 0.050706 Loss(val): 0.051555 acc(val): 0.677177
[17:43:18] Epoch  97: Loss(train): 0.050705 Loss(val): 0.051552 acc(val): 0.677177
[17:44:05] Epoch  98: Loss(train): 0.050704 Loss(val): 0.051554 acc(val): 0.677041
[17:44:52] Epoch  99: Loss(train): 0.050703 Loss(val): 0.051554 acc(val): 0.677109
[17:45:40] Epoch 100: Loss(train): 0.050702 Loss(val): 0.051551
[17:45:47] FINAL(100) Loss(test): 0.052029 Accuarcy: 0.599189

Configuration learning_rate=0.01, decay_step=40
[17:46:00] INIT Loss(test): 0.176727 Accuarcy: 0.092973
[17:46:50] Epoch   1: Loss(train): 0.089826 Loss(val): 0.087610 acc(val): 0.284201
[17:47:38] Epoch   2: Loss(train): 0.067577 Loss(val): 0.066210 acc(val): 0.447466
[17:48:25] Epoch   3: Loss(train): 0.064038 Loss(val): 0.063006 acc(val): 0.497551
[17:49:13] Epoch   4: Loss(train): 0.060244 Loss(val): 0.059602 acc(val): 0.554031
[17:49:58] Epoch   5: Loss(train): 0.059227 Loss(val): 0.058822 acc(val): 0.565595
[17:50:47] Epoch   6: Loss(train): 0.058737 Loss(val): 0.058792 acc(val): 0.559677
[17:51:34] Epoch   7: Loss(train): 0.058215 Loss(val): 0.058426 acc(val): 0.559405
[17:52:21] Epoch   8: Loss(train): 0.057274 Loss(val): 0.057502 acc(val): 0.570986
[17:53:07] Epoch   9: Loss(train): 0.057132 Loss(val): 0.057426 acc(val): 0.570986
[17:53:55] Epoch  10: Loss(train): 0.056904 Loss(val): 0.057230 acc(val): 0.571310
[17:54:40] Epoch  11: Loss(train): 0.057148 Loss(val): 0.057484 acc(val): 0.560357
[17:55:27] Epoch  12: Loss(train): 0.057290 Loss(val): 0.057630 acc(val): 0.556003
[17:56:12] Epoch  13: Loss(train): 0.057313 Loss(val): 0.057586 acc(val): 0.550935
[17:56:59] Epoch  14: Loss(train): 0.056691 Loss(val): 0.056890 acc(val): 0.563316
[17:57:44] Epoch  15: Loss(train): 0.055783 Loss(val): 0.055999 acc(val): 0.579507
[17:58:36] Epoch  16: Loss(train): 0.055334 Loss(val): 0.055583 acc(val): 0.590187
[17:59:33] Epoch  17: Loss(train): 0.055496 Loss(val): 0.055625 acc(val): 0.587330
[18:00:46] Epoch  18: Loss(train): 0.055848 Loss(val): 0.055966 acc(val): 0.582908
[18:01:46] Epoch  19: Loss(train): 0.056469 Loss(val): 0.056572 acc(val): 0.573180
[18:02:41] Epoch  20: Loss(train): 0.057220 Loss(val): 0.057206 acc(val): 0.559711
[18:03:34] Epoch  21: Loss(train): 0.057383 Loss(val): 0.057452 acc(val): 0.557330
[18:04:45] Epoch  22: Loss(train): 0.056780 Loss(val): 0.056885 acc(val): 0.568622
[18:05:45] Epoch  23: Loss(train): 0.055630 Loss(val): 0.055793 acc(val): 0.584541
[18:06:40] Epoch  24: Loss(train): 0.054334 Loss(val): 0.054489 acc(val): 0.612364
[18:07:32] Epoch  25: Loss(train): 0.053592 Loss(val): 0.053724 acc(val): 0.624881
[18:08:31] Epoch  26: Loss(train): 0.053303 Loss(val): 0.053389 acc(val): 0.628095
[18:09:22] Epoch  27: Loss(train): 0.053062 Loss(val): 0.053169 acc(val): 0.633333
[18:10:13] Epoch  28: Loss(train): 0.053093 Loss(val): 0.053166 acc(val): 0.630663
[18:11:03] Epoch  29: Loss(train): 0.053281 Loss(val): 0.053265 acc(val): 0.624609
[18:12:01] Epoch  30: Loss(train): 0.053359 Loss(val): 0.053331 acc(val): 0.620595
[18:12:51] Epoch  31: Loss(train): 0.053417 Loss(val): 0.053345 acc(val): 0.619507
[18:13:42] Epoch  32: Loss(train): 0.053442 Loss(val): 0.053321 acc(val): 0.619847
[18:14:34] Epoch  33: Loss(train): 0.053280 Loss(val): 0.053169 acc(val): 0.622364
[18:15:26] Epoch  34: Loss(train): 0.053042 Loss(val): 0.052970 acc(val): 0.628282
[18:16:15] Epoch  35: Loss(train): 0.052677 Loss(val): 0.052694 acc(val): 0.637058
[18:17:06] Epoch  36: Loss(train): 0.052356 Loss(val): 0.052496 acc(val): 0.643793
[18:17:55] Epoch  37: Loss(train): 0.052130 Loss(val): 0.052343 acc(val): 0.649915
[18:18:48] Epoch  38: Loss(train): 0.051967 Loss(val): 0.052270 acc(val): 0.653044
[18:19:37] Epoch  39: Loss(train): 0.051858 Loss(val): 0.052225 acc(val): 0.655510
[18:20:28] Epoch  40: Loss(train): 0.051766 Loss(val): 0.052186 acc(val): 0.659609
[18:21:17] Epoch  41: Loss(train): 0.051688 Loss(val): 0.052134 acc(val): 0.661922
[18:22:09] Epoch  42: Loss(train): 0.051594 Loss(val): 0.052048 acc(val): 0.664235
[18:22:57] Epoch  43: Loss(train): 0.051490 Loss(val): 0.051962 acc(val): 0.665799
[18:23:47] Epoch  44: Loss(train): 0.051394 Loss(val): 0.051891 acc(val): 0.666956
[18:24:36] Epoch  45: Loss(train): 0.051314 Loss(val): 0.051834 acc(val): 0.670221
[18:25:27] Epoch  46: Loss(train): 0.051240 Loss(val): 0.051802 acc(val): 0.670544
[18:26:16] Epoch  47: Loss(train): 0.051188 Loss(val): 0.051788 acc(val): 0.671088
[18:27:07] Epoch  48: Loss(train): 0.051140 Loss(val): 0.051788 acc(val): 0.670680
[18:27:55] Epoch  49: Loss(train): 0.051096 Loss(val): 0.051787 acc(val): 0.670816
[18:28:45] Epoch  50: Loss(train): 0.051063 Loss(val): 0.051781 acc(val): 0.671497
[18:29:34] Epoch  51: Loss(train): 0.051026 Loss(val): 0.051795 acc(val): 0.670612
[18:30:36] Epoch  52: Loss(train): 0.050999 Loss(val): 0.051804 acc(val): 0.671769
[18:31:57] Epoch  53: Loss(train): 0.050980 Loss(val): 0.051816 acc(val): 0.671684
[18:32:49] Epoch  54: Loss(train): 0.050963 Loss(val): 0.051823 acc(val): 0.672500
[18:33:40] Epoch  55: Loss(train): 0.050948 Loss(val): 0.051837 acc(val): 0.672296
[18:34:51] Epoch  56: Loss(train): 0.050931 Loss(val): 0.051833 acc(val): 0.673112
[18:35:48] Epoch  57: Loss(train): 0.050918 Loss(val): 0.051838 acc(val): 0.672840
[18:36:51] Epoch  58: Loss(train): 0.050899 Loss(val): 0.051821 acc(val): 0.673520
[18:37:45] Epoch  59: Loss(train): 0.050875 Loss(val): 0.051788 acc(val): 0.674133
[18:39:01] Epoch  60: Loss(train): 0.050850 Loss(val): 0.051753 acc(val): 0.673861
[18:40:02] Epoch  61: Loss(train): 0.050831 Loss(val): 0.051731 acc(val): 0.673997
[18:40:53] Epoch  62: Loss(train): 0.050811 Loss(val): 0.051693 acc(val): 0.673997
[18:41:46] Epoch  63: Loss(train): 0.050796 Loss(val): 0.051672 acc(val): 0.674609
[18:42:42] Epoch  64: Loss(train): 0.050784 Loss(val): 0.051655 acc(val): 0.674813
[18:43:46] Epoch  65: Loss(train): 0.050771 Loss(val): 0.051625 acc(val): 0.675289
[18:44:43] Epoch  66: Loss(train): 0.050760 Loss(val): 0.051608 acc(val): 0.674745
[18:45:35] Epoch  67: Loss(train): 0.050751 Loss(val): 0.051598 acc(val): 0.675221
[18:46:26] Epoch  68: Loss(train): 0.050744 Loss(val): 0.051597 acc(val): 0.675289
[18:47:18] Epoch  69: Loss(train): 0.050736 Loss(val): 0.051580 acc(val): 0.675493
[18:48:13] Epoch  70: Loss(train): 0.050730 Loss(val): 0.051581 acc(val): 0.675425
[18:49:04] Epoch  71: Loss(train): 0.050723 Loss(val): 0.051565 acc(val): 0.675085
[18:50:03] Epoch  72: Loss(train): 0.050717 Loss(val): 0.051560 acc(val): 0.674881
[18:50:57] Epoch  73: Loss(train): 0.050711 Loss(val): 0.051549 acc(val): 0.675646
[18:51:50] Epoch  74: Loss(train): 0.050706 Loss(val): 0.051550 acc(val): 0.675153
[18:52:42] Epoch  75: Loss(train): 0.050702 Loss(val): 0.051542 acc(val): 0.675289
[18:53:33] Epoch  76: Loss(train): 0.050696 Loss(val): 0.051532 acc(val): 0.675714
[18:54:24] Epoch  77: Loss(train): 0.050693 Loss(val): 0.051534 acc(val): 0.675493
[18:55:16] Epoch  78: Loss(train): 0.050688 Loss(val): 0.051525 acc(val): 0.675493
[18:56:07] Epoch  79: Loss(train): 0.050684 Loss(val): 0.051525 acc(val): 0.675561
[18:57:00] Epoch  80: Loss(train): 0.050681 Loss(val): 0.051526 acc(val): 0.675561
[18:57:51] Epoch  81: Loss(train): 0.050677 Loss(val): 0.051521 acc(val): 0.675901
[18:58:44] Epoch  82: Loss(train): 0.050675 Loss(val): 0.051520 acc(val): 0.675629
[18:59:33] Epoch  83: Loss(train): 0.050671 Loss(val): 0.051510 acc(val): 0.675510
[19:00:25] Epoch  84: Loss(train): 0.050668 Loss(val): 0.051509 acc(val): 0.675085
[19:01:14] Epoch  85: Loss(train): 0.050666 Loss(val): 0.051507 acc(val): 0.675289
[19:02:05] Epoch  86: Loss(train): 0.050664 Loss(val): 0.051506 acc(val): 0.675357
[19:02:56] Epoch  87: Loss(train): 0.050661 Loss(val): 0.051503 acc(val): 0.675425
[19:03:52] Epoch  88: Loss(train): 0.050659 Loss(val): 0.051504 acc(val): 0.675289
[19:05:08] Epoch  89: Loss(train): 0.050657 Loss(val): 0.051499 acc(val): 0.675289
[19:06:39] Epoch  90: Loss(train): 0.050655 Loss(val): 0.051496 acc(val): 0.675425
[19:07:35] Epoch  91: Loss(train): 0.050654 Loss(val): 0.051497 acc(val): 0.675289
[19:08:29] Epoch  92: Loss(train): 0.050652 Loss(val): 0.051498 acc(val): 0.675425
[19:09:40] Epoch  93: Loss(train): 0.050650 Loss(val): 0.051495 acc(val): 0.675561
[19:10:33] Epoch  94: Loss(train): 0.050649 Loss(val): 0.051495 acc(val): 0.675425
[19:11:24] Epoch  95: Loss(train): 0.050648 Loss(val): 0.051491 acc(val): 0.675493
[19:12:25] Epoch  96: Loss(train): 0.050647 Loss(val): 0.051491 acc(val): 0.675629
[19:13:50] Epoch  97: Loss(train): 0.050646 Loss(val): 0.051491 acc(val): 0.675561
[19:14:53] Epoch  98: Loss(train): 0.050645 Loss(val): 0.051490 acc(val): 0.675425
[19:15:44] Epoch  99: Loss(train): 0.050644 Loss(val): 0.051491 acc(val): 0.675629
[19:16:42] Epoch 100: Loss(train): 0.050643 Loss(val): 0.051489
[19:16:51] FINAL(100) Loss(test): 0.051861 Accuarcy: 0.601014

Configuration learning_rate=0.01, decay_step=60
[19:17:05] INIT Loss(test): 0.146561 Accuarcy: 0.112095
[19:18:05] Epoch   1: Loss(train): 0.085300 Loss(val): 0.083685 acc(val): 0.301548
[19:19:02] Epoch   2: Loss(train): 0.066953 Loss(val): 0.065985 acc(val): 0.446310
[19:19:57] Epoch   3: Loss(train): 0.064071 Loss(val): 0.063177 acc(val): 0.500459
[19:20:56] Epoch   4: Loss(train): 0.061052 Loss(val): 0.060448 acc(val): 0.525357
[19:21:48] Epoch   5: Loss(train): 0.059383 Loss(val): 0.059186 acc(val): 0.546735
[19:22:43] Epoch   6: Loss(train): 0.058582 Loss(val): 0.058385 acc(val): 0.555374
[19:23:36] Epoch   7: Loss(train): 0.057840 Loss(val): 0.057679 acc(val): 0.568571
[19:24:32] Epoch   8: Loss(train): 0.057490 Loss(val): 0.057312 acc(val): 0.574575
[19:25:24] Epoch   9: Loss(train): 0.057308 Loss(val): 0.057126 acc(val): 0.578878
[19:26:21] Epoch  10: Loss(train): 0.056718 Loss(val): 0.056649 acc(val): 0.588265
[19:27:16] Epoch  11: Loss(train): 0.056284 Loss(val): 0.056397 acc(val): 0.592483
[19:28:11] Epoch  12: Loss(train): 0.055857 Loss(val): 0.056005 acc(val): 0.598810
[19:29:04] Epoch  13: Loss(train): 0.055451 Loss(val): 0.055661 acc(val): 0.603044
[19:29:59] Epoch  14: Loss(train): 0.055363 Loss(val): 0.055531 acc(val): 0.600935
[19:30:50] Epoch  15: Loss(train): 0.055445 Loss(val): 0.055545 acc(val): 0.597874
[19:31:43] Epoch  16: Loss(train): 0.055360 Loss(val): 0.055467 acc(val): 0.598963
[19:32:36] Epoch  17: Loss(train): 0.055204 Loss(val): 0.055398 acc(val): 0.599099
[19:33:31] Epoch  18: Loss(train): 0.054983 Loss(val): 0.055307 acc(val): 0.599456
[19:34:24] Epoch  19: Loss(train): 0.054601 Loss(val): 0.055000 acc(val): 0.606395
[19:35:21] Epoch  20: Loss(train): 0.054591 Loss(val): 0.054917 acc(val): 0.607279
[19:36:13] Epoch  21: Loss(train): 0.054396 Loss(val): 0.054738 acc(val): 0.610272
[19:37:07] Epoch  22: Loss(train): 0.054501 Loss(val): 0.054852 acc(val): 0.605850
[19:37:59] Epoch  23: Loss(train): 0.054861 Loss(val): 0.055244 acc(val): 0.594490
[19:38:53] Epoch  24: Loss(train): 0.055324 Loss(val): 0.055727 acc(val): 0.583316
[19:39:44] Epoch  25: Loss(train): 0.055759 Loss(val): 0.056135 acc(val): 0.574099
[19:40:46] Epoch  26: Loss(train): 0.056071 Loss(val): 0.056407 acc(val): 0.565527
[19:41:55] Epoch  27: Loss(train): 0.055936 Loss(val): 0.056284 acc(val): 0.567636
[19:43:12] Epoch  28: Loss(train): 0.055192 Loss(val): 0.055479 acc(val): 0.581173
[19:44:18] Epoch  29: Loss(train): 0.054194 Loss(val): 0.054437 acc(val): 0.602874
[19:45:41] Epoch  30: Loss(train): 0.053646 Loss(val): 0.053798 acc(val): 0.615340
[19:46:36] Epoch  31: Loss(train): 0.053466 Loss(val): 0.053572 acc(val): 0.619558
[19:47:32] Epoch  32: Loss(train): 0.053537 Loss(val): 0.053568 acc(val): 0.618214
[19:48:26] Epoch  33: Loss(train): 0.053592 Loss(val): 0.053585 acc(val): 0.616446
[19:49:32] Epoch  34: Loss(train): 0.053791 Loss(val): 0.053701 acc(val): 0.610850
[19:50:27] Epoch  35: Loss(train): 0.053868 Loss(val): 0.053710 acc(val): 0.609422
[19:51:33] Epoch  36: Loss(train): 0.053803 Loss(val): 0.053639 acc(val): 0.611122
[19:52:48] Epoch  37: Loss(train): 0.053587 Loss(val): 0.053460 acc(val): 0.617041
[19:53:47] Epoch  38: Loss(train): 0.053151 Loss(val): 0.053148 acc(val): 0.626616
[19:54:45] Epoch  39: Loss(train): 0.052732 Loss(val): 0.052863 acc(val): 0.636973
[19:55:43] Epoch  40: Loss(train): 0.052385 Loss(val): 0.052624 acc(val): 0.646854
[19:56:37] Epoch  41: Loss(train): 0.052123 Loss(val): 0.052437 acc(val): 0.653316
[19:57:42] Epoch  42: Loss(train): 0.051956 Loss(val): 0.052307 acc(val): 0.656922
[19:58:41] Epoch  43: Loss(train): 0.051858 Loss(val): 0.052221 acc(val): 0.658776
[19:59:43] Epoch  44: Loss(train): 0.051767 Loss(val): 0.052147 acc(val): 0.661769
[20:00:38] Epoch  45: Loss(train): 0.051678 Loss(val): 0.052093 acc(val): 0.663197
[20:01:37] Epoch  46: Loss(train): 0.051649 Loss(val): 0.052045 acc(val): 0.664422
[20:02:33] Epoch  47: Loss(train): 0.051587 Loss(val): 0.051998 acc(val): 0.664983
[20:03:31] Epoch  48: Loss(train): 0.051510 Loss(val): 0.051950 acc(val): 0.665595
[20:04:27] Epoch  49: Loss(train): 0.051464 Loss(val): 0.051920 acc(val): 0.665595
[20:05:24] Epoch  50: Loss(train): 0.051407 Loss(val): 0.051894 acc(val): 0.665867
[20:06:19] Epoch  51: Loss(train): 0.051346 Loss(val): 0.051874 acc(val): 0.665255
[20:07:15] Epoch  52: Loss(train): 0.051286 Loss(val): 0.051866 acc(val): 0.665391
[20:08:09] Epoch  53: Loss(train): 0.051240 Loss(val): 0.051856 acc(val): 0.665731
[20:09:05] Epoch  54: Loss(train): 0.051194 Loss(val): 0.051873 acc(val): 0.666939
[20:09:59] Epoch  55: Loss(train): 0.051154 Loss(val): 0.051884 acc(val): 0.668316
[20:10:57] Epoch  56: Loss(train): 0.051128 Loss(val): 0.051895 acc(val): 0.669065
[20:12:18] Epoch  57: Loss(train): 0.051107 Loss(val): 0.051928 acc(val): 0.669609
[20:13:30] Epoch  58: Loss(train): 0.051096 Loss(val): 0.051963 acc(val): 0.668571
[20:15:09] Epoch  59: Loss(train): 0.051089 Loss(val): 0.051990 acc(val): 0.666327
[20:16:36] Epoch  60: Loss(train): 0.051084 Loss(val): 0.052012 acc(val): 0.667007
[20:17:35] Epoch  61: Loss(train): 0.051071 Loss(val): 0.052018 acc(val): 0.667075
[20:18:56] Epoch  62: Loss(train): 0.051056 Loss(val): 0.052011 acc(val): 0.667279
[20:20:15] Epoch  63: Loss(train): 0.051039 Loss(val): 0.052001 acc(val): 0.667075
[20:21:25] Epoch  64: Loss(train): 0.051017 Loss(val): 0.051979 acc(val): 0.667347
[20:22:32] Epoch  65: Loss(train): 0.050996 Loss(val): 0.051954 acc(val): 0.668571
[20:23:39] Epoch  66: Loss(train): 0.050975 Loss(val): 0.051927 acc(val): 0.668639
[20:24:43] Epoch  67: Loss(train): 0.050955 Loss(val): 0.051898 acc(val): 0.669048
[20:25:45] Epoch  68: Loss(train): 0.050940 Loss(val): 0.051876 acc(val): 0.669864
[20:26:40] Epoch  69: Loss(train): 0.050923 Loss(val): 0.051856 acc(val): 0.670408
[20:27:41] Epoch  70: Loss(train): 0.050910 Loss(val): 0.051839 acc(val): 0.671361
[20:28:42] Epoch  71: Loss(train): 0.050899 Loss(val): 0.051830 acc(val): 0.670748
[20:29:47] Epoch  72: Loss(train): 0.050885 Loss(val): 0.051802 acc(val): 0.671769
[20:30:46] Epoch  73: Loss(train): 0.050876 Loss(val): 0.051789 acc(val): 0.671905
[20:31:45] Epoch  74: Loss(train): 0.050868 Loss(val): 0.051780 acc(val): 0.671769
[20:32:43] Epoch  75: Loss(train): 0.050859 Loss(val): 0.051767 acc(val): 0.672517
[20:33:43] Epoch  76: Loss(train): 0.050852 Loss(val): 0.051755 acc(val): 0.673061
[20:34:42] Epoch  77: Loss(train): 0.050847 Loss(val): 0.051750 acc(val): 0.672789
[20:35:42] Epoch  78: Loss(train): 0.050841 Loss(val): 0.051743 acc(val): 0.672653
[20:36:39] Epoch  79: Loss(train): 0.050836 Loss(val): 0.051736 acc(val): 0.672585
[20:37:39] Epoch  80: Loss(train): 0.050831 Loss(val): 0.051728 acc(val): 0.672245
[20:38:37] Epoch  81: Loss(train): 0.050826 Loss(val): 0.051721 acc(val): 0.672449
[20:39:38] Epoch  82: Loss(train): 0.050822 Loss(val): 0.051717 acc(val): 0.672517
[20:40:37] Epoch  83: Loss(train): 0.050818 Loss(val): 0.051712 acc(val): 0.672381
[20:41:36] Epoch  84: Loss(train): 0.050814 Loss(val): 0.051704 acc(val): 0.672925
[20:42:32] Epoch  85: Loss(train): 0.050811 Loss(val): 0.051707 acc(val): 0.672449
[20:44:12] Epoch  86: Loss(train): 0.050808 Loss(val): 0.051702 acc(val): 0.672449
[20:45:56] Epoch  87: Loss(train): 0.050805 Loss(val): 0.051700 acc(val): 0.672517
[20:47:19] Epoch  88: Loss(train): 0.050802 Loss(val): 0.051695 acc(val): 0.672653
[20:48:38] Epoch  89: Loss(train): 0.050800 Loss(val): 0.051694 acc(val): 0.672721
[20:49:47] Epoch  90: Loss(train): 0.050797 Loss(val): 0.051688 acc(val): 0.672993
[20:51:04] Epoch  91: Loss(train): 0.050796 Loss(val): 0.051688 acc(val): 0.672993
[20:52:29] Epoch  92: Loss(train): 0.050794 Loss(val): 0.051688 acc(val): 0.673129
[20:53:54] Epoch  93: Loss(train): 0.050792 Loss(val): 0.051685 acc(val): 0.673197
[20:54:59] Epoch  94: Loss(train): 0.050790 Loss(val): 0.051679 acc(val): 0.673129
[20:56:01] Epoch  95: Loss(train): 0.050788 Loss(val): 0.051678 acc(val): 0.673129
[20:57:04] Epoch  96: Loss(train): 0.050787 Loss(val): 0.051676 acc(val): 0.673197
[20:58:13] Epoch  97: Loss(train): 0.050786 Loss(val): 0.051680 acc(val): 0.673537
[20:59:20] Epoch  98: Loss(train): 0.050784 Loss(val): 0.051672 acc(val): 0.673265
[21:00:19] Epoch  99: Loss(train): 0.050783 Loss(val): 0.051673 acc(val): 0.673469
[21:01:21] Epoch 100: Loss(train): 0.050782 Loss(val): 0.051673
[21:01:28] FINAL(100) Loss(test): 0.051884 Accuarcy: 0.596351

Configuration learning_rate=0.003, decay_step=20
[21:01:44] INIT Loss(test): 0.158548 Accuarcy: 0.098919
[21:02:53] Epoch   1: Loss(train): 0.083241 Loss(val): 0.081338 acc(val): 0.315714
[21:03:52] Epoch   2: Loss(train): 0.068011 Loss(val): 0.066275 acc(val): 0.454677
[21:04:49] Epoch   3: Loss(train): 0.064500 Loss(val): 0.062939 acc(val): 0.506276
[21:05:51] Epoch   4: Loss(train): 0.062763 Loss(val): 0.061977 acc(val): 0.521054
[21:06:49] Epoch   5: Loss(train): 0.060735 Loss(val): 0.060340 acc(val): 0.539966
[21:07:50] Epoch   6: Loss(train): 0.059243 Loss(val): 0.058967 acc(val): 0.554847
[21:08:47] Epoch   7: Loss(train): 0.058659 Loss(val): 0.058494 acc(val): 0.556156
[21:09:46] Epoch   8: Loss(train): 0.058254 Loss(val): 0.058243 acc(val): 0.558197
[21:10:44] Epoch   9: Loss(train): 0.058391 Loss(val): 0.058417 acc(val): 0.550850
[21:11:44] Epoch  10: Loss(train): 0.058190 Loss(val): 0.058318 acc(val): 0.549354
[21:12:40] Epoch  11: Loss(train): 0.057913 Loss(val): 0.058267 acc(val): 0.551378
[21:14:00] Epoch  12: Loss(train): 0.057026 Loss(val): 0.057716 acc(val): 0.558044
[21:15:32] Epoch  13: Loss(train): 0.056899 Loss(val): 0.057677 acc(val): 0.556956
[21:16:50] Epoch  14: Loss(train): 0.056948 Loss(val): 0.057710 acc(val): 0.556480
[21:18:38] Epoch  15: Loss(train): 0.056834 Loss(val): 0.057578 acc(val): 0.559133
[21:20:31] Epoch  16: Loss(train): 0.056879 Loss(val): 0.057601 acc(val): 0.558929
[21:22:05] Epoch  17: Loss(train): 0.056644 Loss(val): 0.057316 acc(val): 0.562126
[21:23:53] Epoch  18: Loss(train): 0.056123 Loss(val): 0.056696 acc(val): 0.573963
[21:24:56] Epoch  19: Loss(train): 0.055539 Loss(val): 0.055993 acc(val): 0.589218
[21:25:58] Epoch  20: Loss(train): 0.054817 Loss(val): 0.055192 acc(val): 0.604456
[21:27:20] Epoch  21: Loss(train): 0.054251 Loss(val): 0.054556 acc(val): 0.617109
[21:28:24] Epoch  22: Loss(train): 0.053735 Loss(val): 0.054037 acc(val): 0.628810
[21:29:40] Epoch  23: Loss(train): 0.053590 Loss(val): 0.053807 acc(val): 0.629881
[21:30:46] Epoch  24: Loss(train): 0.053532 Loss(val): 0.053687 acc(val): 0.628997
[21:31:47] Epoch  25: Loss(train): 0.053535 Loss(val): 0.053628 acc(val): 0.628997
[21:32:51] Epoch  26: Loss(train): 0.053524 Loss(val): 0.053611 acc(val): 0.626071
[21:33:53] Epoch  27: Loss(train): 0.053373 Loss(val): 0.053523 acc(val): 0.628384
[21:35:07] Epoch  28: Loss(train): 0.053050 Loss(val): 0.053344 acc(val): 0.634711
[21:36:09] Epoch  29: Loss(train): 0.052943 Loss(val): 0.053259 acc(val): 0.636071
[21:37:08] Epoch  30: Loss(train): 0.052761 Loss(val): 0.053106 acc(val): 0.640153
[21:38:11] Epoch  31: Loss(train): 0.052696 Loss(val): 0.053025 acc(val): 0.642670
[21:39:12] Epoch  32: Loss(train): 0.052689 Loss(val): 0.052930 acc(val): 0.642330
[21:40:15] Epoch  33: Loss(train): 0.052740 Loss(val): 0.052846 acc(val): 0.641514
[21:41:14] Epoch  34: Loss(train): 0.052706 Loss(val): 0.052756 acc(val): 0.642058
[21:42:16] Epoch  35: Loss(train): 0.052765 Loss(val): 0.052704 acc(val): 0.640017
[21:43:14] Epoch  36: Loss(train): 0.052756 Loss(val): 0.052639 acc(val): 0.638180
[21:44:17] Epoch  37: Loss(train): 0.052711 Loss(val): 0.052555 acc(val): 0.640153
[21:45:17] Epoch  38: Loss(train): 0.052549 Loss(val): 0.052426 acc(val): 0.644031
[21:46:26] Epoch  39: Loss(train): 0.052322 Loss(val): 0.052297 acc(val): 0.650969
[21:48:10] Epoch  40: Loss(train): 0.052060 Loss(val): 0.052150 acc(val): 0.658333
[21:50:08] Epoch  41: Loss(train): 0.051793 Loss(val): 0.052026 acc(val): 0.665612
[21:51:53] Epoch  42: Loss(train): 0.051636 Loss(val): 0.051965 acc(val): 0.668197
[21:53:38] Epoch  43: Loss(train): 0.051514 Loss(val): 0.051931 acc(val): 0.670646
[21:55:21] Epoch  44: Loss(train): 0.051438 Loss(val): 0.051905 acc(val): 0.669966
[21:57:04] Epoch  45: Loss(train): 0.051403 Loss(val): 0.051888 acc(val): 0.670714
[21:58:07] Epoch  46: Loss(train): 0.051358 Loss(val): 0.051865 acc(val): 0.670918
[21:59:30] Epoch  47: Loss(train): 0.051337 Loss(val): 0.051848 acc(val): 0.670782
[22:00:47] Epoch  48: Loss(train): 0.051338 Loss(val): 0.051840 acc(val): 0.670714
[22:02:03] Epoch  49: Loss(train): 0.051314 Loss(val): 0.051821 acc(val): 0.670646
[22:03:13] Epoch  50: Loss(train): 0.051277 Loss(val): 0.051795 acc(val): 0.670782
[22:04:19] Epoch  51: Loss(train): 0.051270 Loss(val): 0.051777 acc(val): 0.671599
[22:05:26] Epoch  52: Loss(train): 0.051233 Loss(val): 0.051768 acc(val): 0.671259
[22:06:34] Epoch  53: Loss(train): 0.051212 Loss(val): 0.051756 acc(val): 0.671871
[22:07:37] Epoch  54: Loss(train): 0.051174 Loss(val): 0.051745 acc(val): 0.673163
[22:08:44] Epoch  55: Loss(train): 0.051122 Loss(val): 0.051735 acc(val): 0.673639
[22:09:47] Epoch  56: Loss(train): 0.051073 Loss(val): 0.051735 acc(val): 0.672959
[22:10:53] Epoch  57: Loss(train): 0.051029 Loss(val): 0.051744 acc(val): 0.672959
[22:11:53] Epoch  58: Loss(train): 0.051000 Loss(val): 0.051749 acc(val): 0.674252
[22:12:56] Epoch  59: Loss(train): 0.050973 Loss(val): 0.051769 acc(val): 0.674524
[22:13:57] Epoch  60: Loss(train): 0.050952 Loss(val): 0.051795 acc(val): 0.673231
[22:15:00] Epoch  61: Loss(train): 0.050937 Loss(val): 0.051807 acc(val): 0.673724
[22:16:02] Epoch  62: Loss(train): 0.050928 Loss(val): 0.051828 acc(val): 0.673588
[22:17:06] Epoch  63: Loss(train): 0.050916 Loss(val): 0.051835 acc(val): 0.673861
[22:18:08] Epoch  64: Loss(train): 0.050908 Loss(val): 0.051846 acc(val): 0.673452
[22:19:37] Epoch  65: Loss(train): 0.050891 Loss(val): 0.051827 acc(val): 0.673861
[22:21:30] Epoch  66: Loss(train): 0.050875 Loss(val): 0.051813 acc(val): 0.673861
[22:23:05] Epoch  67: Loss(train): 0.050859 Loss(val): 0.051792 acc(val): 0.674269
[22:24:45] Epoch  68: Loss(train): 0.050848 Loss(val): 0.051785 acc(val): 0.674065
[22:26:41] Epoch  69: Loss(train): 0.050833 Loss(val): 0.051761 acc(val): 0.675085
[22:28:20] Epoch  70: Loss(train): 0.050818 Loss(val): 0.051735 acc(val): 0.675425
[22:29:44] Epoch  71: Loss(train): 0.050805 Loss(val): 0.051714 acc(val): 0.676105
[22:31:19] Epoch  72: Loss(train): 0.050798 Loss(val): 0.051715 acc(val): 0.676037
[22:32:43] Epoch  73: Loss(train): 0.050788 Loss(val): 0.051700 acc(val): 0.676241
[22:33:55] Epoch  74: Loss(train): 0.050779 Loss(val): 0.051684 acc(val): 0.676786
[22:35:13] Epoch  75: Loss(train): 0.050772 Loss(val): 0.051674 acc(val): 0.676582
[22:36:24] Epoch  76: Loss(train): 0.050765 Loss(val): 0.051667 acc(val): 0.676718
[22:37:34] Epoch  77: Loss(train): 0.050759 Loss(val): 0.051653 acc(val): 0.677058
[22:38:41] Epoch  78: Loss(train): 0.050753 Loss(val): 0.051646 acc(val): 0.676990
[22:39:49] Epoch  79: Loss(train): 0.050748 Loss(val): 0.051638 acc(val): 0.677058
[22:41:00] Epoch  80: Loss(train): 0.050743 Loss(val): 0.051630 acc(val): 0.676990
[22:42:08] Epoch  81: Loss(train): 0.050740 Loss(val): 0.051629 acc(val): 0.677058
[22:43:14] Epoch  82: Loss(train): 0.050735 Loss(val): 0.051620 acc(val): 0.676650
[22:44:21] Epoch  83: Loss(train): 0.050732 Loss(val): 0.051618 acc(val): 0.676582
[22:45:26] Epoch  84: Loss(train): 0.050728 Loss(val): 0.051612 acc(val): 0.676922
[22:46:32] Epoch  85: Loss(train): 0.050725 Loss(val): 0.051609 acc(val): 0.676990
[22:47:37] Epoch  86: Loss(train): 0.050722 Loss(val): 0.051603 acc(val): 0.676854
[22:48:44] Epoch  87: Loss(train): 0.050719 Loss(val): 0.051599 acc(val): 0.677126
[22:49:47] Epoch  88: Loss(train): 0.050716 Loss(val): 0.051596 acc(val): 0.676990
[22:50:53] Epoch  89: Loss(train): 0.050714 Loss(val): 0.051596 acc(val): 0.676990
[22:51:58] Epoch  90: Loss(train): 0.050711 Loss(val): 0.051589 acc(val): 0.677398
[22:53:07] Epoch  91: Loss(train): 0.050710 Loss(val): 0.051587 acc(val): 0.677058
[22:54:13] Epoch  92: Loss(train): 0.050708 Loss(val): 0.051584 acc(val): 0.677534
[22:55:22] Epoch  93: Loss(train): 0.050706 Loss(val): 0.051585 acc(val): 0.677534
[22:56:28] Epoch  94: Loss(train): 0.050705 Loss(val): 0.051585 acc(val): 0.677466
[22:57:38] Epoch  95: Loss(train): 0.050703 Loss(val): 0.051586 acc(val): 0.677330
[22:58:44] Epoch  96: Loss(train): 0.050702 Loss(val): 0.051580 acc(val): 0.677466
[22:59:53] Epoch  97: Loss(train): 0.050700 Loss(val): 0.051578 acc(val): 0.677398
[23:00:59] Epoch  98: Loss(train): 0.050699 Loss(val): 0.051579 acc(val): 0.677466
[23:02:09] Epoch  99: Loss(train): 0.050698 Loss(val): 0.051577 acc(val): 0.677602
[23:03:16] Epoch 100: Loss(train): 0.050697 Loss(val): 0.051575
[23:03:25] FINAL(100) Loss(test): 0.051971 Accuarcy: 0.586486

Configuration learning_rate=0.003, decay_step=40
[23:03:43] INIT Loss(test): 0.119407 Accuarcy: 0.131892
[23:04:57] Epoch   1: Loss(train): 0.086009 Loss(val): 0.084843 acc(val): 0.304133
[23:06:07] Epoch   2: Loss(train): 0.068264 Loss(val): 0.066110 acc(val): 0.453316
[23:07:15] Epoch   3: Loss(train): 0.064122 Loss(val): 0.062628 acc(val): 0.517568
[23:08:25] Epoch   4: Loss(train): 0.060438 Loss(val): 0.059920 acc(val): 0.540153
[23:09:34] Epoch   5: Loss(train): 0.059801 Loss(val): 0.059508 acc(val): 0.544507
[23:10:47] Epoch   6: Loss(train): 0.059259 Loss(val): 0.058924 acc(val): 0.546412
[23:12:21] Epoch   7: Loss(train): 0.058629 Loss(val): 0.058101 acc(val): 0.558673
[23:13:41] Epoch   8: Loss(train): 0.058048 Loss(val): 0.057791 acc(val): 0.564099
[23:14:46] Epoch   9: Loss(train): 0.058454 Loss(val): 0.058416 acc(val): 0.551122
[23:15:55] Epoch  10: Loss(train): 0.058675 Loss(val): 0.058777 acc(val): 0.543724
[23:17:04] Epoch  11: Loss(train): 0.058370 Loss(val): 0.058430 acc(val): 0.546582
[23:19:16] Epoch  12: Loss(train): 0.057999 Loss(val): 0.058021 acc(val): 0.547126
[23:21:09] Epoch  13: Loss(train): 0.057656 Loss(val): 0.057744 acc(val): 0.555425
[23:23:13] Epoch  14: Loss(train): 0.057686 Loss(val): 0.057843 acc(val): 0.555289
[23:24:54] Epoch  15: Loss(train): 0.058182 Loss(val): 0.058384 acc(val): 0.554949
[23:26:00] Epoch  16: Loss(train): 0.058460 Loss(val): 0.058770 acc(val): 0.556037
[23:27:03] Epoch  17: Loss(train): 0.058416 Loss(val): 0.058736 acc(val): 0.558486
[23:28:10] Epoch  18: Loss(train): 0.057461 Loss(val): 0.057750 acc(val): 0.571888
[23:29:45] Epoch  19: Loss(train): 0.056130 Loss(val): 0.056310 acc(val): 0.588895
[23:31:09] Epoch  20: Loss(train): 0.054899 Loss(val): 0.055004 acc(val): 0.607738
[23:32:13] Epoch  21: Loss(train): 0.054311 Loss(val): 0.054304 acc(val): 0.618214
[23:33:22] Epoch  22: Loss(train): 0.054011 Loss(val): 0.053956 acc(val): 0.620323
[23:34:39] Epoch  23: Loss(train): 0.053804 Loss(val): 0.053789 acc(val): 0.625425
[23:35:56] Epoch  24: Loss(train): 0.053912 Loss(val): 0.053940 acc(val): 0.621361
[23:37:02] Epoch  25: Loss(train): 0.053980 Loss(val): 0.054102 acc(val): 0.616105
[23:38:12] Epoch  26: Loss(train): 0.054036 Loss(val): 0.054221 acc(val): 0.612364
[23:39:21] Epoch  27: Loss(train): 0.054032 Loss(val): 0.054174 acc(val): 0.612636
[23:40:32] Epoch  28: Loss(train): 0.053859 Loss(val): 0.053952 acc(val): 0.615374
[23:41:39] Epoch  29: Loss(train): 0.053869 Loss(val): 0.053855 acc(val): 0.616395
[23:42:47] Epoch  30: Loss(train): 0.053897 Loss(val): 0.053789 acc(val): 0.615714
[23:43:53] Epoch  31: Loss(train): 0.053977 Loss(val): 0.053684 acc(val): 0.612789
[23:45:01] Epoch  32: Loss(train): 0.054146 Loss(val): 0.053690 acc(val): 0.608929
[23:46:05] Epoch  33: Loss(train): 0.054114 Loss(val): 0.053585 acc(val): 0.607143
[23:47:12] Epoch  34: Loss(train): 0.053837 Loss(val): 0.053342 acc(val): 0.614286
[23:48:54] Epoch  35: Loss(train): 0.053427 Loss(val): 0.053079 acc(val): 0.621905
[23:51:05] Epoch  36: Loss(train): 0.052834 Loss(val): 0.052732 acc(val): 0.637143
[23:52:37] Epoch  37: Loss(train): 0.052377 Loss(val): 0.052473 acc(val): 0.647075
[23:53:55] Epoch  38: Loss(train): 0.052059 Loss(val): 0.052323 acc(val): 0.655765
[23:55:00] Epoch  39: Loss(train): 0.051822 Loss(val): 0.052194 acc(val): 0.659711
[23:56:37] Epoch  40: Loss(train): 0.051687 Loss(val): 0.052090 acc(val): 0.662432
[23:57:56] Epoch  41: Loss(train): 0.051599 Loss(val): 0.052035 acc(val): 0.663452
[23:59:27] Epoch  42: Loss(train): 0.051543 Loss(val): 0.052002 acc(val): 0.666105
[00:00:40] Epoch  43: Loss(train): 0.051492 Loss(val): 0.051979 acc(val): 0.665289
[00:01:55] Epoch  44: Loss(train): 0.051441 Loss(val): 0.051964 acc(val): 0.666514
[00:03:10] Epoch  45: Loss(train): 0.051421 Loss(val): 0.051940 acc(val): 0.668078
[00:04:31] Epoch  46: Loss(train): 0.051367 Loss(val): 0.051917 acc(val): 0.668827
[00:05:37] Epoch  47: Loss(train): 0.051326 Loss(val): 0.051903 acc(val): 0.669031
[00:06:46] Epoch  48: Loss(train): 0.051282 Loss(val): 0.051888 acc(val): 0.670119
[00:07:54] Epoch  49: Loss(train): 0.051247 Loss(val): 0.051872 acc(val): 0.670391
[00:09:08] Epoch  50: Loss(train): 0.051210 Loss(val): 0.051871 acc(val): 0.670391
[00:10:13] Epoch  51: Loss(train): 0.051175 Loss(val): 0.051883 acc(val): 0.670187
[00:11:22] Epoch  52: Loss(train): 0.051149 Loss(val): 0.051886 acc(val): 0.670051
[00:12:27] Epoch  53: Loss(train): 0.051129 Loss(val): 0.051913 acc(val): 0.669099
[00:13:37] Epoch  54: Loss(train): 0.051116 Loss(val): 0.051936 acc(val): 0.667330
[00:14:45] Epoch  55: Loss(train): 0.051102 Loss(val): 0.051941 acc(val): 0.667602
[00:15:57] Epoch  56: Loss(train): 0.051099 Loss(val): 0.051973 acc(val): 0.666718
[00:17:04] Epoch  57: Loss(train): 0.051085 Loss(val): 0.051980 acc(val): 0.666718
[00:18:26] Epoch  58: Loss(train): 0.051069 Loss(val): 0.051975 acc(val): 0.666650
[00:20:26] Epoch  59: Loss(train): 0.051041 Loss(val): 0.051938 acc(val): 0.667602
[00:21:56] Epoch  60: Loss(train): 0.051020 Loss(val): 0.051919 acc(val): 0.667738
[00:23:31] Epoch  61: Loss(train): 0.050994 Loss(val): 0.051884 acc(val): 0.668963
[00:24:50] Epoch  62: Loss(train): 0.050970 Loss(val): 0.051851 acc(val): 0.669915
[00:26:36] Epoch  63: Loss(train): 0.050952 Loss(val): 0.051824 acc(val): 0.670187
[00:27:56] Epoch  64: Loss(train): 0.050932 Loss(val): 0.051791 acc(val): 0.671207
[00:29:25] Epoch  65: Loss(train): 0.050915 Loss(val): 0.051762 acc(val): 0.671888
[00:30:38] Epoch  66: Loss(train): 0.050900 Loss(val): 0.051739 acc(val): 0.671820
[00:31:47] Epoch  67: Loss(train): 0.050888 Loss(val): 0.051720 acc(val): 0.671956
[00:33:12] Epoch  68: Loss(train): 0.050880 Loss(val): 0.051714 acc(val): 0.671956
[00:34:24] Epoch  69: Loss(train): 0.050870 Loss(val): 0.051703 acc(val): 0.672024
[00:35:42] Epoch  70: Loss(train): 0.050862 Loss(val): 0.051696 acc(val): 0.672636
[00:36:54] Epoch  71: Loss(train): 0.050854 Loss(val): 0.051680 acc(val): 0.673044
[00:38:13] Epoch  72: Loss(train): 0.050847 Loss(val): 0.051672 acc(val): 0.672840
[00:39:21] Epoch  73: Loss(train): 0.050842 Loss(val): 0.051672 acc(val): 0.671888
[00:40:37] Epoch  74: Loss(train): 0.050836 Loss(val): 0.051663 acc(val): 0.672364
[00:41:45] Epoch  75: Loss(train): 0.050830 Loss(val): 0.051650 acc(val): 0.672432
[00:43:00] Epoch  76: Loss(train): 0.050825 Loss(val): 0.051648 acc(val): 0.672840
[00:44:08] Epoch  77: Loss(train): 0.050820 Loss(val): 0.051643 acc(val): 0.672568
[00:45:20] Epoch  78: Loss(train): 0.050817 Loss(val): 0.051644 acc(val): 0.672500
[00:46:30] Epoch  79: Loss(train): 0.050812 Loss(val): 0.051636 acc(val): 0.672364
[00:47:41] Epoch  80: Loss(train): 0.050809 Loss(val): 0.051635 acc(val): 0.672704
[00:48:51] Epoch  81: Loss(train): 0.050805 Loss(val): 0.051629 acc(val): 0.672840
[00:50:33] Epoch  82: Loss(train): 0.050801 Loss(val): 0.051625 acc(val): 0.672704
[00:52:14] Epoch  83: Loss(train): 0.050798 Loss(val): 0.051623 acc(val): 0.672772
[00:53:55] Epoch  84: Loss(train): 0.050795 Loss(val): 0.051622 acc(val): 0.672704
[00:55:43] Epoch  85: Loss(train): 0.050792 Loss(val): 0.051617 acc(val): 0.673112
[00:57:16] Epoch  86: Loss(train): 0.050790 Loss(val): 0.051615 acc(val): 0.673248
[00:58:46] Epoch  87: Loss(train): 0.050787 Loss(val): 0.051613 acc(val): 0.673520
[01:00:14] Epoch  88: Loss(train): 0.050785 Loss(val): 0.051612 acc(val): 0.673248
[01:01:36] Epoch  89: Loss(train): 0.050783 Loss(val): 0.051612 acc(val): 0.673180
[01:02:53] Epoch  90: Loss(train): 0.050781 Loss(val): 0.051609 acc(val): 0.673248
[01:04:05] Epoch  91: Loss(train): 0.050779 Loss(val): 0.051608 acc(val): 0.673316
[01:05:24] Epoch  92: Loss(train): 0.050778 Loss(val): 0.051606 acc(val): 0.673384
[01:06:45] Epoch  93: Loss(train): 0.050776 Loss(val): 0.051605 acc(val): 0.673452
[01:07:59] Epoch  94: Loss(train): 0.050775 Loss(val): 0.051604 acc(val): 0.673588
[01:09:13] Epoch  95: Loss(train): 0.050774 Loss(val): 0.051602 acc(val): 0.673452
[01:10:25] Epoch  96: Loss(train): 0.050772 Loss(val): 0.051599 acc(val): 0.673316
[01:11:35] Epoch  97: Loss(train): 0.050771 Loss(val): 0.051599 acc(val): 0.673520
[01:12:45] Epoch  98: Loss(train): 0.050770 Loss(val): 0.051600 acc(val): 0.673588
[01:13:54] Epoch  99: Loss(train): 0.050769 Loss(val): 0.051597 acc(val): 0.673452
[01:15:04] Epoch 100: Loss(train): 0.050768 Loss(val): 0.051596
[01:15:13] FINAL(100) Loss(test): 0.052151 Accuarcy: 0.602703

Configuration learning_rate=0.003, decay_step=60
[01:15:31] INIT Loss(test): 0.118268 Accuarcy: 0.130541
[01:16:50] Epoch   1: Loss(train): 0.084326 Loss(val): 0.082111 acc(val): 0.317891
[01:18:01] Epoch   2: Loss(train): 0.067675 Loss(val): 0.066096 acc(val): 0.453265
[01:19:07] Epoch   3: Loss(train): 0.063037 Loss(val): 0.061884 acc(val): 0.512517
[01:20:51] Epoch   4: Loss(train): 0.060235 Loss(val): 0.059597 acc(val): 0.557024
[01:22:50] Epoch   5: Loss(train): 0.059429 Loss(val): 0.059154 acc(val): 0.559099
[01:24:33] Epoch   6: Loss(train): 0.059058 Loss(val): 0.058983 acc(val): 0.559303
[01:26:15] Epoch   7: Loss(train): 0.058302 Loss(val): 0.058147 acc(val): 0.566718
[01:27:41] Epoch   8: Loss(train): 0.058073 Loss(val): 0.057841 acc(val): 0.566241
[01:29:14] Epoch   9: Loss(train): 0.057751 Loss(val): 0.057718 acc(val): 0.568078
[01:30:49] Epoch  10: Loss(train): 0.057868 Loss(val): 0.057935 acc(val): 0.561003
[01:32:08] Epoch  11: Loss(train): 0.057844 Loss(val): 0.058059 acc(val): 0.559439
[01:33:28] Epoch  12: Loss(train): 0.057605 Loss(val): 0.057729 acc(val): 0.561207
[01:34:45] Epoch  13: Loss(train): 0.056757 Loss(val): 0.056798 acc(val): 0.574422
[01:36:09] Epoch  14: Loss(train): 0.056279 Loss(val): 0.056278 acc(val): 0.585034
[01:37:26] Epoch  15: Loss(train): 0.056084 Loss(val): 0.056146 acc(val): 0.587619
[01:38:40] Epoch  16: Loss(train): 0.056607 Loss(val): 0.056665 acc(val): 0.580119
[01:39:54] Epoch  17: Loss(train): 0.057447 Loss(val): 0.057562 acc(val): 0.563656
[01:41:13] Epoch  18: Loss(train): 0.057931 Loss(val): 0.058062 acc(val): 0.555493
[01:42:26] Epoch  19: Loss(train): 0.057932 Loss(val): 0.058026 acc(val): 0.556786
[01:43:42] Epoch  20: Loss(train): 0.056523 Loss(val): 0.056666 acc(val): 0.581956
[01:44:55] Epoch  21: Loss(train): 0.054813 Loss(val): 0.054965 acc(val): 0.613197
[01:46:10] Epoch  22: Loss(train): 0.053830 Loss(val): 0.054018 acc(val): 0.632517
[01:47:20] Epoch  23: Loss(train): 0.053511 Loss(val): 0.053685 acc(val): 0.635442
[01:48:35] Epoch  24: Loss(train): 0.053198 Loss(val): 0.053462 acc(val): 0.640272
[01:49:48] Epoch  25: Loss(train): 0.053054 Loss(val): 0.053336 acc(val): 0.642041
[01:51:41] Epoch  26: Loss(train): 0.052948 Loss(val): 0.053279 acc(val): 0.643265
[01:53:14] Epoch  27: Loss(train): 0.052850 Loss(val): 0.053252 acc(val): 0.644490
[01:54:52] Epoch  28: Loss(train): 0.052809 Loss(val): 0.053145 acc(val): 0.644626
[01:56:30] Epoch  29: Loss(train): 0.052700 Loss(val): 0.053007 acc(val): 0.646735
[01:58:28] Epoch  30: Loss(train): 0.052565 Loss(val): 0.052855 acc(val): 0.650000
[01:59:41] Epoch  31: Loss(train): 0.052525 Loss(val): 0.052728 acc(val): 0.651769
[02:01:14] Epoch  32: Loss(train): 0.052521 Loss(val): 0.052635 acc(val): 0.649660
[02:02:32] Epoch  33: Loss(train): 0.052542 Loss(val): 0.052554 acc(val): 0.649252
[02:04:04] Epoch  34: Loss(train): 0.052591 Loss(val): 0.052510 acc(val): 0.646463
[02:05:17] Epoch  35: Loss(train): 0.052629 Loss(val): 0.052478 acc(val): 0.645731
[02:06:41] Epoch  36: Loss(train): 0.052609 Loss(val): 0.052442 acc(val): 0.647160
[02:07:55] Epoch  37: Loss(train): 0.052505 Loss(val): 0.052344 acc(val): 0.649065
[02:09:16] Epoch  38: Loss(train): 0.052283 Loss(val): 0.052196 acc(val): 0.653827
[02:10:30] Epoch  39: Loss(train): 0.052129 Loss(val): 0.052099 acc(val): 0.656616
[02:11:46] Epoch  40: Loss(train): 0.051865 Loss(val): 0.051973 acc(val): 0.660901
[02:12:59] Epoch  41: Loss(train): 0.051727 Loss(val): 0.051912 acc(val): 0.664643
[02:14:16] Epoch  42: Loss(train): 0.051614 Loss(val): 0.051869 acc(val): 0.666888
[02:15:26] Epoch  43: Loss(train): 0.051569 Loss(val): 0.051843 acc(val): 0.666003
[02:16:41] Epoch  44: Loss(train): 0.051505 Loss(val): 0.051823 acc(val): 0.667024
[02:17:52] Epoch  45: Loss(train): 0.051464 Loss(val): 0.051800 acc(val): 0.667568
[02:19:07] Epoch  46: Loss(train): 0.051440 Loss(val): 0.051774 acc(val): 0.667432
[02:20:20] Epoch  47: Loss(train): 0.051418 Loss(val): 0.051756 acc(val): 0.667976
[02:22:02] Epoch  48: Loss(train): 0.051364 Loss(val): 0.051738 acc(val): 0.669813
[02:23:45] Epoch  49: Loss(train): 0.051345 Loss(val): 0.051721 acc(val): 0.669201
[02:25:46] Epoch  50: Loss(train): 0.051294 Loss(val): 0.051708 acc(val): 0.671037
[02:27:28] Epoch  51: Loss(train): 0.051244 Loss(val): 0.051699 acc(val): 0.670765
[02:29:26] Epoch  52: Loss(train): 0.051217 Loss(val): 0.051687 acc(val): 0.671241
[02:30:49] Epoch  53: Loss(train): 0.051168 Loss(val): 0.051685 acc(val): 0.671582
[02:32:24] Epoch  54: Loss(train): 0.051129 Loss(val): 0.051696 acc(val): 0.672262
[02:33:48] Epoch  55: Loss(train): 0.051096 Loss(val): 0.051717 acc(val): 0.670833
[02:35:18] Epoch  56: Loss(train): 0.051069 Loss(val): 0.051752 acc(val): 0.669609
[02:36:37] Epoch  57: Loss(train): 0.051054 Loss(val): 0.051791 acc(val): 0.668793
[02:38:02] Epoch  58: Loss(train): 0.051046 Loss(val): 0.051823 acc(val): 0.668793
[02:39:22] Epoch  59: Loss(train): 0.051033 Loss(val): 0.051830 acc(val): 0.668180
[02:40:42] Epoch  60: Loss(train): 0.051030 Loss(val): 0.051859 acc(val): 0.667296
[02:41:56] Epoch  61: Loss(train): 0.051019 Loss(val): 0.051869 acc(val): 0.666276
[02:43:18] Epoch  62: Loss(train): 0.051008 Loss(val): 0.051871 acc(val): 0.666003
[02:44:34] Epoch  63: Loss(train): 0.050986 Loss(val): 0.051852 acc(val): 0.665935
[02:45:51] Epoch  64: Loss(train): 0.050960 Loss(val): 0.051816 acc(val): 0.667364
[02:47:05] Epoch  65: Loss(train): 0.050938 Loss(val): 0.051782 acc(val): 0.668316
[02:48:24] Epoch  66: Loss(train): 0.050921 Loss(val): 0.051765 acc(val): 0.668793
[02:49:39] Epoch  67: Loss(train): 0.050905 Loss(val): 0.051737 acc(val): 0.669337
[02:51:00] Epoch  68: Loss(train): 0.050893 Loss(val): 0.051723 acc(val): 0.669745
[02:52:31] Epoch  69: Loss(train): 0.050879 Loss(val): 0.051702 acc(val): 0.670221
[02:54:48] Epoch  70: Loss(train): 0.050866 Loss(val): 0.051684 acc(val): 0.669813
[02:56:36] Epoch  71: Loss(train): 0.050855 Loss(val): 0.051657 acc(val): 0.670425
[02:58:05] Epoch  72: Loss(train): 0.050848 Loss(val): 0.051651 acc(val): 0.670357
[02:59:25] Epoch  73: Loss(train): 0.050842 Loss(val): 0.051645 acc(val): 0.670765
[03:01:09] Epoch  74: Loss(train): 0.050834 Loss(val): 0.051638 acc(val): 0.670901
[03:02:44] Epoch  75: Loss(train): 0.050828 Loss(val): 0.051627 acc(val): 0.671378
[03:04:13] Epoch  76: Loss(train): 0.050821 Loss(val): 0.051613 acc(val): 0.671582
[03:05:28] Epoch  77: Loss(train): 0.050817 Loss(val): 0.051616 acc(val): 0.671446
[03:07:01] Epoch  78: Loss(train): 0.050811 Loss(val): 0.051602 acc(val): 0.671446
[03:08:26] Epoch  79: Loss(train): 0.050808 Loss(val): 0.051602 acc(val): 0.671922
[03:09:55] Epoch  80: Loss(train): 0.050804 Loss(val): 0.051598 acc(val): 0.672262
[03:11:08] Epoch  81: Loss(train): 0.050800 Loss(val): 0.051593 acc(val): 0.671990
[03:12:34] Epoch  82: Loss(train): 0.050796 Loss(val): 0.051591 acc(val): 0.672398
[03:13:52] Epoch  83: Loss(train): 0.050792 Loss(val): 0.051581 acc(val): 0.672534
[03:15:11] Epoch  84: Loss(train): 0.050789 Loss(val): 0.051579 acc(val): 0.672466
[03:16:28] Epoch  85: Loss(train): 0.050786 Loss(val): 0.051579 acc(val): 0.672398
[03:17:47] Epoch  86: Loss(train): 0.050783 Loss(val): 0.051572 acc(val): 0.672398
[03:19:04] Epoch  87: Loss(train): 0.050781 Loss(val): 0.051570 acc(val): 0.672534
[03:20:23] Epoch  88: Loss(train): 0.050779 Loss(val): 0.051571 acc(val): 0.672602
[03:21:39] Epoch  89: Loss(train): 0.050777 Loss(val): 0.051571 acc(val): 0.672330
[03:23:02] Epoch  90: Loss(train): 0.050774 Loss(val): 0.051563 acc(val): 0.672534
[03:24:57] Epoch  91: Loss(train): 0.050773 Loss(val): 0.051561 acc(val): 0.672602
[03:27:00] Epoch  92: Loss(train): 0.050771 Loss(val): 0.051558 acc(val): 0.672670
[03:29:00] Epoch  93: Loss(train): 0.050769 Loss(val): 0.051557 acc(val): 0.672602
[03:31:00] Epoch  94: Loss(train): 0.050767 Loss(val): 0.051552 acc(val): 0.672738
[03:32:35] Epoch  95: Loss(train): 0.050766 Loss(val): 0.051551 acc(val): 0.672874
[03:34:01] Epoch  96: Loss(train): 0.050765 Loss(val): 0.051556 acc(val): 0.672670
[03:35:31] Epoch  97: Loss(train): 0.050764 Loss(val): 0.051553 acc(val): 0.673146
[03:37:11] Epoch  98: Loss(train): 0.050763 Loss(val): 0.051555 acc(val): 0.672942
[03:38:30] Epoch  99: Loss(train): 0.050762 Loss(val): 0.051552 acc(val): 0.673010
[03:39:58] Epoch 100: Loss(train): 0.050761 Loss(val): 0.051550
[03:40:09] FINAL(100) Loss(test): 0.051995 Accuarcy: 0.592703