train.log

W1126 23:14:48.356578 30632 device_context.cc:447] Please NOTE: device: 0, GPU Compute Capability: 7.0, Driver API Version: 10.1, Runtime API Version: 10.1
W1126 23:14:48.361518 30632 device_context.cc:465] device: 0, cuDNN Version: 7.6.
Loading pretrained model from ../c3d.pdparams
cls_head.fc_cls.weight is not in pretrained model
cls_head.fc_cls.bias is not in pretrained model
There are 20/22 variables loaded into Recognizer3D.
/home/aistudio/paddle_c3d/datasets/pipelines/transforms.py:432: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  results['frame_inds'] = frame_inds.astype(np.int)
[TRAIN] epoch=1, batch_id=10, loss=4.791237, lr=0.000033,acc=0.003 ETA 12:08:23
[TRAIN] epoch=1, batch_id=20, loss=4.811666, lr=0.000067,acc=0.006 ETA 08:21:20
[TRAIN] epoch=1, batch_id=30, loss=4.790960, lr=0.000100,acc=0.006 ETA 08:04:30
[TRAIN] epoch=1, batch_id=40, loss=4.776621, lr=0.000133,acc=0.008 ETA 08:05:42
[TRAIN] epoch=1, batch_id=50, loss=4.765997, lr=0.000167,acc=0.006 ETA 07:58:49
[TRAIN] epoch=1, batch_id=60, loss=4.765493, lr=0.000200,acc=0.006 ETA 08:15:29
[TRAIN] epoch=1, batch_id=70, loss=4.756604, lr=0.000233,acc=0.008 ETA 08:12:09
[TRAIN] epoch=1, batch_id=80, loss=4.744222, lr=0.000267,acc=0.009 ETA 08:07:18
[TRAIN] epoch=1, batch_id=90, loss=4.735130, lr=0.000300,acc=0.010 ETA 08:16:59
[TRAIN] epoch=1, batch_id=100, loss=4.725593, lr=0.000333,acc=0.010 ETA 08:15:58
[TRAIN] epoch=1, batch_id=110, loss=4.724042, lr=0.000367,acc=0.010 ETA 08:28:37
[TRAIN] epoch=1, batch_id=120, loss=4.712107, lr=0.000400,acc=0.010 ETA 08:12:15
[TRAIN] epoch=1, batch_id=130, loss=4.701779, lr=0.000433,acc=0.011 ETA 09:16:16
[TRAIN] epoch=1, batch_id=140, loss=4.692621, lr=0.000467,acc=0.012 ETA 08:19:08
[TRAIN] epoch=1, batch_id=150, loss=4.682652, lr=0.000500,acc=0.014 ETA 08:23:37
[TRAIN] epoch=1, batch_id=160, loss=4.670393, lr=0.000533,acc=0.015 ETA 08:03:30
[TRAIN] epoch=1, batch_id=170, loss=4.658613, lr=0.000567,acc=0.017 ETA 08:22:51
[TRAIN] epoch=1, batch_id=180, loss=4.647335, lr=0.000600,acc=0.018 ETA 08:03:57
[TRAIN] epoch=1, batch_id=190, loss=4.635028, lr=0.000633,acc=0.020 ETA 08:17:57
[TRAIN] epoch=1, batch_id=200, loss=4.622623, lr=0.000667,acc=0.022 ETA 08:36:11
[TRAIN] epoch=1, batch_id=210, loss=4.609976, lr=0.000700,acc=0.024 ETA 09:25:32
[TRAIN] epoch=1, batch_id=220, loss=4.594133, lr=0.000733,acc=0.027 ETA 07:57:42
[TRAIN] epoch=1, batch_id=230, loss=4.576608, lr=0.000767,acc=0.030 ETA 08:08:10
[TRAIN] epoch=1, batch_id=240, loss=4.560827, lr=0.000800,acc=0.033 ETA 08:13:09
[TRAIN] epoch=1, batch_id=250, loss=4.539785, lr=0.000833,acc=0.037 ETA 08:17:50
[TRAIN] epoch=1, batch_id=260, loss=4.517671, lr=0.000867,acc=0.041 ETA 08:07:24
[TRAIN] epoch=1, batch_id=270, loss=4.494965, lr=0.000900,acc=0.045 ETA 08:34:48
[TRAIN] epoch=1, batch_id=280, loss=4.466347, lr=0.000933,acc=0.050 ETA 08:17:18
[TRAIN] epoch=1, batch_id=290, loss=4.440546, lr=0.000967,acc=0.055 ETA 08:08:48
/home/aistudio/paddle_c3d/datasets/pipelines/transforms.py:376: DeprecationWarning: `np.int` is a deprecated alias for the builtin `int`. To silence this warning, use `int` by itself. Doing this will not modify any behavior and is safe. When replacing `np.int`, you may wish to use e.g. `np.int64` or `np.int32` to specify the precision. If you wish to review your current use, check the release note link for additional information.
Deprecated in NumPy 1.20; for more details and guidance: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations
  clip_offsets = (base_offsets + avg_interval / 2.0).astype(np.int)
[EVAL] epoch=1

Evaluating top_k_accuracy ...

top1_acc	0.3127
top5_acc	0.5490

Evaluating mean_class_accuracy ...

mean_acc	0.3055
Save best model
[TRAIN] epoch=2, batch_id=2, loss=3.734788, lr=0.001000,acc=0.188 ETA 123:55:46
[TRAIN] epoch=2, batch_id=12, loss=3.487500, lr=0.001000,acc=0.232 ETA 09:21:12
[TRAIN] epoch=2, batch_id=22, loss=3.409628, lr=0.001000,acc=0.256 ETA 09:07:10
[TRAIN] epoch=2, batch_id=32, loss=3.316549, lr=0.001000,acc=0.262 ETA 09:57:56
[TRAIN] epoch=2, batch_id=42, loss=3.181418, lr=0.001000,acc=0.290 ETA 10:17:45
[TRAIN] epoch=2, batch_id=52, loss=3.123313, lr=0.000999,acc=0.295 ETA 08:47:02
[TRAIN] epoch=2, batch_id=62, loss=3.081933, lr=0.000999,acc=0.298 ETA 08:07:29
[TRAIN] epoch=2, batch_id=72, loss=3.018050, lr=0.000999,acc=0.307 ETA 07:57:01
[TRAIN] epoch=2, batch_id=82, loss=2.935335, lr=0.000998,acc=0.317 ETA 08:20:32
[TRAIN] epoch=2, batch_id=92, loss=2.879711, lr=0.000998,acc=0.327 ETA 08:03:25
[TRAIN] epoch=2, batch_id=102, loss=2.832116, lr=0.000997,acc=0.333 ETA 07:56:46
[TRAIN] epoch=2, batch_id=112, loss=2.770930, lr=0.000997,acc=0.344 ETA 07:53:51
[TRAIN] epoch=2, batch_id=122, loss=2.718168, lr=0.000996,acc=0.357 ETA 10:15:25
[TRAIN] epoch=2, batch_id=132, loss=2.664087, lr=0.000995,acc=0.367 ETA 07:55:39
[TRAIN] epoch=2, batch_id=142, loss=2.624147, lr=0.000995,acc=0.373 ETA 08:27:56
[TRAIN] epoch=2, batch_id=152, loss=2.582077, lr=0.000994,acc=0.380 ETA 08:57:41
[TRAIN] epoch=2, batch_id=162, loss=2.542423, lr=0.000993,acc=0.387 ETA 08:03:17
[TRAIN] epoch=2, batch_id=172, loss=2.508694, lr=0.000992,acc=0.394 ETA 08:05:11
[TRAIN] epoch=2, batch_id=182, loss=2.475284, lr=0.000991,acc=0.401 ETA 08:07:07
[TRAIN] epoch=2, batch_id=192, loss=2.439874, lr=0.000990,acc=0.407 ETA 07:59:54
[TRAIN] epoch=2, batch_id=202, loss=2.407565, lr=0.000989,acc=0.412 ETA 08:03:53
[TRAIN] epoch=2, batch_id=212, loss=2.369697, lr=0.000988,acc=0.420 ETA 08:39:36
[TRAIN] epoch=2, batch_id=222, loss=2.335994, lr=0.000987,acc=0.426 ETA 08:06:10
[TRAIN] epoch=2, batch_id=232, loss=2.303747, lr=0.000985,acc=0.431 ETA 07:59:51
[TRAIN] epoch=2, batch_id=242, loss=2.272900, lr=0.000984,acc=0.437 ETA 07:59:17
[TRAIN] epoch=2, batch_id=252, loss=2.247078, lr=0.000983,acc=0.441 ETA 07:56:34
[TRAIN] epoch=2, batch_id=262, loss=2.215213, lr=0.000981,acc=0.447 ETA 07:54:45
[TRAIN] epoch=2, batch_id=272, loss=2.194565, lr=0.000980,acc=0.451 ETA 07:56:54
[TRAIN] epoch=2, batch_id=282, loss=2.166194, lr=0.000978,acc=0.456 ETA 08:22:26
[TRAIN] epoch=2, batch_id=292, loss=2.140809, lr=0.000977,acc=0.461 ETA 08:01:41
[EVAL] epoch=2

Evaluating top_k_accuracy ...

top1_acc	0.6564
top5_acc	0.8990

Evaluating mean_class_accuracy ...

mean_acc	0.6566
Save best model
[TRAIN] epoch=3, batch_id=4, loss=1.445334, lr=0.000975,acc=0.609 ETA 121:03:51
[TRAIN] epoch=3, batch_id=14, loss=1.292282, lr=0.000974,acc=0.661 ETA 08:27:07
[TRAIN] epoch=3, batch_id=24, loss=1.202732, lr=0.000972,acc=0.676 ETA 08:54:16
[TRAIN] epoch=3, batch_id=34, loss=1.235790, lr=0.000970,acc=0.656 ETA 10:05:49
[TRAIN] epoch=3, batch_id=44, loss=1.224124, lr=0.000968,acc=0.663 ETA 13:18:08
[TRAIN] epoch=3, batch_id=54, loss=1.254602, lr=0.000966,acc=0.657 ETA 11:26:00
[TRAIN] epoch=3, batch_id=64, loss=1.254296, lr=0.000964,acc=0.663 ETA 12:18:18
[TRAIN] epoch=3, batch_id=74, loss=1.236945, lr=0.000962,acc=0.660 ETA 09:57:58
[TRAIN] epoch=3, batch_id=84, loss=1.240300, lr=0.000960,acc=0.655 ETA 08:34:14
[TRAIN] epoch=3, batch_id=94, loss=1.228664, lr=0.000958,acc=0.657 ETA 08:05:21
[TRAIN] epoch=3, batch_id=104, loss=1.216440, lr=0.000956,acc=0.660 ETA 08:22:33
[TRAIN] epoch=3, batch_id=114, loss=1.202007, lr=0.000954,acc=0.665 ETA 08:03:40
[TRAIN] epoch=3, batch_id=124, loss=1.200702, lr=0.000952,acc=0.665 ETA 08:04:01
[TRAIN] epoch=3, batch_id=134, loss=1.193584, lr=0.000949,acc=0.668 ETA 07:59:28
[TRAIN] epoch=3, batch_id=144, loss=1.193210, lr=0.000947,acc=0.669 ETA 08:58:12
[TRAIN] epoch=3, batch_id=154, loss=1.189883, lr=0.000945,acc=0.671 ETA 09:10:06
[TRAIN] epoch=3, batch_id=164, loss=1.184111, lr=0.000942,acc=0.672 ETA 08:27:08
[TRAIN] epoch=3, batch_id=174, loss=1.180603, lr=0.000940,acc=0.672 ETA 09:22:36
[TRAIN] epoch=3, batch_id=184, loss=1.174168, lr=0.000937,acc=0.673 ETA 08:42:38
[TRAIN] epoch=3, batch_id=194, loss=1.165488, lr=0.000935,acc=0.675 ETA 09:06:07
[TRAIN] epoch=3, batch_id=204, loss=1.157009, lr=0.000932,acc=0.677 ETA 08:14:59
[TRAIN] epoch=3, batch_id=214, loss=1.155848, lr=0.000929,acc=0.677 ETA 08:15:13
[TRAIN] epoch=3, batch_id=224, loss=1.148713, lr=0.000927,acc=0.679 ETA 07:58:50
[TRAIN] epoch=3, batch_id=234, loss=1.148924, lr=0.000924,acc=0.680 ETA 07:59:45
[TRAIN] epoch=3, batch_id=244, loss=1.134637, lr=0.000921,acc=0.684 ETA 08:01:27
[TRAIN] epoch=3, batch_id=254, loss=1.128396, lr=0.000918,acc=0.685 ETA 08:07:51
[TRAIN] epoch=3, batch_id=264, loss=1.120293, lr=0.000915,acc=0.685 ETA 08:19:39
[TRAIN] epoch=3, batch_id=274, loss=1.116256, lr=0.000912,acc=0.687 ETA 08:12:39
[TRAIN] epoch=3, batch_id=284, loss=1.109380, lr=0.000909,acc=0.689 ETA 08:15:49
[TRAIN] epoch=3, batch_id=294, loss=1.104269, lr=0.000906,acc=0.690 ETA 08:10:48
[EVAL] epoch=3

Evaluating top_k_accuracy ...

top1_acc	0.7219
top5_acc	0.9270

Evaluating mean_class_accuracy ...

mean_acc	0.7236
Save best model
[TRAIN] epoch=4, batch_id=6, loss=0.886744, lr=0.000903,acc=0.734 ETA 117:33:23
[TRAIN] epoch=4, batch_id=16, loss=0.806944, lr=0.000900,acc=0.760 ETA 08:02:16
[TRAIN] epoch=4, batch_id=26, loss=0.755020, lr=0.000897,acc=0.775 ETA 08:12:32
[TRAIN] epoch=4, batch_id=36, loss=0.769667, lr=0.000894,acc=0.767 ETA 07:58:37
[TRAIN] epoch=4, batch_id=46, loss=0.765340, lr=0.000890,acc=0.774 ETA 07:56:41
[TRAIN] epoch=4, batch_id=56, loss=0.756646, lr=0.000887,acc=0.776 ETA 07:53:32
[TRAIN] epoch=4, batch_id=66, loss=0.757443, lr=0.000884,acc=0.774 ETA 07:48:23
[TRAIN] epoch=4, batch_id=76, loss=0.773645, lr=0.000880,acc=0.771 ETA 07:53:53
[TRAIN] epoch=4, batch_id=86, loss=0.775843, lr=0.000877,acc=0.770 ETA 07:46:12
[TRAIN] epoch=4, batch_id=96, loss=0.776113, lr=0.000873,acc=0.771 ETA 08:22:52
[TRAIN] epoch=4, batch_id=106, loss=0.772025, lr=0.000870,acc=0.771 ETA 07:57:39
[TRAIN] epoch=4, batch_id=116, loss=0.780451, lr=0.000866,acc=0.769 ETA 10:45:51
[TRAIN] epoch=4, batch_id=126, loss=0.782507, lr=0.000863,acc=0.768 ETA 16:32:45
[TRAIN] epoch=4, batch_id=136, loss=0.781408, lr=0.000859,acc=0.768 ETA 22:36:23
[TRAIN] epoch=4, batch_id=146, loss=0.774383, lr=0.000855,acc=0.770 ETA 08:23:50
[TRAIN] epoch=4, batch_id=156, loss=0.766319, lr=0.000852,acc=0.772 ETA 07:41:22
[TRAIN] epoch=4, batch_id=166, loss=0.773566, lr=0.000848,acc=0.769 ETA 08:58:29
[TRAIN] epoch=4, batch_id=176, loss=0.774077, lr=0.000844,acc=0.768 ETA 07:51:53
[TRAIN] epoch=4, batch_id=186, loss=0.766670, lr=0.000840,acc=0.770 ETA 10:43:06
[TRAIN] epoch=4, batch_id=196, loss=0.765275, lr=0.000836,acc=0.771 ETA 07:54:03
[TRAIN] epoch=4, batch_id=206, loss=0.760338, lr=0.000832,acc=0.773 ETA 09:37:17
[TRAIN] epoch=4, batch_id=216, loss=0.762304, lr=0.000829,acc=0.773 ETA 07:50:33
[TRAIN] epoch=4, batch_id=226, loss=0.760363, lr=0.000825,acc=0.774 ETA 11:05:42
[TRAIN] epoch=4, batch_id=236, loss=0.755649, lr=0.000820,acc=0.775 ETA 09:14:36
[TRAIN] epoch=4, batch_id=246, loss=0.751069, lr=0.000816,acc=0.777 ETA 08:35:27
[TRAIN] epoch=4, batch_id=256, loss=0.749761, lr=0.000812,acc=0.777 ETA 08:38:06
[TRAIN] epoch=4, batch_id=266, loss=0.746896, lr=0.000808,acc=0.778 ETA 07:50:22
[TRAIN] epoch=4, batch_id=276, loss=0.742315, lr=0.000804,acc=0.779 ETA 08:02:56
[TRAIN] epoch=4, batch_id=286, loss=0.738742, lr=0.000800,acc=0.780 ETA 07:50:15
[TRAIN] epoch=4, batch_id=296, loss=0.737706, lr=0.000796,acc=0.779 ETA 07:49:32
[EVAL] epoch=4

Evaluating top_k_accuracy ...

top1_acc	0.7417
top5_acc	0.9334

Evaluating mean_class_accuracy ...

mean_acc	0.7406
Save best model
[TRAIN] epoch=5, batch_id=8, loss=0.582154, lr=0.000791,acc=0.812 ETA 118:02:58
[TRAIN] epoch=5, batch_id=18, loss=0.631918, lr=0.000787,acc=0.793 ETA 08:08:35
[TRAIN] epoch=5, batch_id=28, loss=0.657649, lr=0.000783,acc=0.787 ETA 08:27:33
[TRAIN] epoch=5, batch_id=38, loss=0.641144, lr=0.000778,acc=0.799 ETA 08:56:29
[TRAIN] epoch=5, batch_id=48, loss=0.645664, lr=0.000774,acc=0.799 ETA 08:06:54
[TRAIN] epoch=5, batch_id=58, loss=0.648959, lr=0.000770,acc=0.799 ETA 11:58:29
[TRAIN] epoch=5, batch_id=68, loss=0.634153, lr=0.000765,acc=0.807 ETA 14:35:28
[TRAIN] epoch=5, batch_id=78, loss=0.627604, lr=0.000761,acc=0.807 ETA 12:12:02
[TRAIN] epoch=5, batch_id=88, loss=0.626540, lr=0.000756,acc=0.807 ETA 08:49:32
[TRAIN] epoch=5, batch_id=98, loss=0.621903, lr=0.000752,acc=0.809 ETA 07:39:28
[TRAIN] epoch=5, batch_id=108, loss=0.621579, lr=0.000747,acc=0.812 ETA 07:51:53
[TRAIN] epoch=5, batch_id=118, loss=0.624073, lr=0.000742,acc=0.812 ETA 07:41:38
[TRAIN] epoch=5, batch_id=128, loss=0.624468, lr=0.000738,acc=0.812 ETA 07:53:52
[TRAIN] epoch=5, batch_id=138, loss=0.622746, lr=0.000733,acc=0.811 ETA 07:43:14
[TRAIN] epoch=5, batch_id=148, loss=0.617212, lr=0.000728,acc=0.813 ETA 07:34:45
[TRAIN] epoch=5, batch_id=158, loss=0.611579, lr=0.000724,acc=0.815 ETA 07:42:24
[TRAIN] epoch=5, batch_id=168, loss=0.610227, lr=0.000719,acc=0.815 ETA 07:43:12
[TRAIN] epoch=5, batch_id=178, loss=0.605161, lr=0.000714,acc=0.817 ETA 08:23:39
[TRAIN] epoch=5, batch_id=188, loss=0.603904, lr=0.000709,acc=0.818 ETA 07:49:36
[TRAIN] epoch=5, batch_id=198, loss=0.602152, lr=0.000705,acc=0.818 ETA 10:12:15
[TRAIN] epoch=5, batch_id=208, loss=0.600705, lr=0.000700,acc=0.820 ETA 08:00:13
[TRAIN] epoch=5, batch_id=218, loss=0.600071, lr=0.000695,acc=0.821 ETA 08:00:22
[TRAIN] epoch=5, batch_id=228, loss=0.596345, lr=0.000690,acc=0.822 ETA 07:33:56
[TRAIN] epoch=5, batch_id=238, loss=0.595880, lr=0.000685,acc=0.821 ETA 08:04:52
[TRAIN] epoch=5, batch_id=248, loss=0.592635, lr=0.000680,acc=0.821 ETA 07:38:07
[TRAIN] epoch=5, batch_id=258, loss=0.590285, lr=0.000675,acc=0.822 ETA 07:42:09
[TRAIN] epoch=5, batch_id=268, loss=0.587840, lr=0.000670,acc=0.823 ETA 07:39:14
[TRAIN] epoch=5, batch_id=278, loss=0.585394, lr=0.000665,acc=0.824 ETA 07:47:21
[TRAIN] epoch=5, batch_id=288, loss=0.586994, lr=0.000661,acc=0.824 ETA 07:38:33
[TRAIN] epoch=5, batch_id=298, loss=0.585526, lr=0.000656,acc=0.825 ETA 09:30:23
[EVAL] epoch=5

Evaluating top_k_accuracy ...

top1_acc	0.7523
top5_acc	0.9403

Evaluating mean_class_accuracy ...

mean_acc	0.7508
Save best model
[TRAIN] epoch=6, batch_id=10, loss=0.425241, lr=0.000650,acc=0.847 ETA 114:37:22
[TRAIN] epoch=6, batch_id=20, loss=0.466748, lr=0.000645,acc=0.855 ETA 07:55:07
[TRAIN] epoch=6, batch_id=30, loss=0.485524, lr=0.000640,acc=0.848 ETA 07:55:06
[TRAIN] epoch=6, batch_id=40, loss=0.489117, lr=0.000635,acc=0.846 ETA 09:25:55
[TRAIN] epoch=6, batch_id=50, loss=0.499492, lr=0.000630,acc=0.846 ETA 07:45:57
[TRAIN] epoch=6, batch_id=60, loss=0.521216, lr=0.000625,acc=0.838 ETA 08:09:03
[TRAIN] epoch=6, batch_id=70, loss=0.531599, lr=0.000620,acc=0.836 ETA 07:41:51
[TRAIN] epoch=6, batch_id=80, loss=0.510377, lr=0.000615,acc=0.841 ETA 07:45:59
[TRAIN] epoch=6, batch_id=90, loss=0.502563, lr=0.000610,acc=0.842 ETA 07:34:17
[TRAIN] epoch=6, batch_id=100, loss=0.502669, lr=0.000605,acc=0.844 ETA 08:29:26
[TRAIN] epoch=6, batch_id=110, loss=0.492140, lr=0.000599,acc=0.847 ETA 07:39:20
[TRAIN] epoch=6, batch_id=120, loss=0.492856, lr=0.000594,acc=0.847 ETA 08:33:08
[TRAIN] epoch=6, batch_id=130, loss=0.493138, lr=0.000589,acc=0.848 ETA 08:11:59
[TRAIN] epoch=6, batch_id=140, loss=0.487700, lr=0.000584,acc=0.848 ETA 07:47:31
[TRAIN] epoch=6, batch_id=150, loss=0.490060, lr=0.000579,acc=0.849 ETA 07:48:28
[TRAIN] epoch=6, batch_id=160, loss=0.492550, lr=0.000574,acc=0.849 ETA 07:49:25
[TRAIN] epoch=6, batch_id=170, loss=0.488786, lr=0.000568,acc=0.850 ETA 07:48:44
[TRAIN] epoch=6, batch_id=180, loss=0.492927, lr=0.000563,acc=0.849 ETA 08:08:49
[TRAIN] epoch=6, batch_id=190, loss=0.492410, lr=0.000558,acc=0.849 ETA 09:21:09
[TRAIN] epoch=6, batch_id=200, loss=0.491508, lr=0.000553,acc=0.850 ETA 07:46:47
[TRAIN] epoch=6, batch_id=210, loss=0.490364, lr=0.000547,acc=0.850 ETA 09:10:54
[TRAIN] epoch=6, batch_id=220, loss=0.490463, lr=0.000542,acc=0.851 ETA 07:58:30
[TRAIN] epoch=6, batch_id=230, loss=0.489062, lr=0.000537,acc=0.851 ETA 08:40:11
[TRAIN] epoch=6, batch_id=240, loss=0.485800, lr=0.000532,acc=0.851 ETA 08:39:53
[TRAIN] epoch=6, batch_id=250, loss=0.487983, lr=0.000526,acc=0.850 ETA 08:38:54
[TRAIN] epoch=6, batch_id=260, loss=0.487528, lr=0.000521,acc=0.851 ETA 07:48:55
[TRAIN] epoch=6, batch_id=270, loss=0.485724, lr=0.000516,acc=0.852 ETA 08:50:57
[TRAIN] epoch=6, batch_id=280, loss=0.482534, lr=0.000511,acc=0.852 ETA 07:45:45
[TRAIN] epoch=6, batch_id=290, loss=0.479242, lr=0.000505,acc=0.854 ETA 07:40:54
[EVAL] epoch=6

Evaluating top_k_accuracy ...

top1_acc	0.7621
top5_acc	0.9461

Evaluating mean_class_accuracy ...

mean_acc	0.7611
Save best model
[TRAIN] epoch=7, batch_id=2, loss=0.377763, lr=0.000500,acc=0.891 ETA 113:01:45
[TRAIN] epoch=7, batch_id=12, loss=0.339160, lr=0.000495,acc=0.901 ETA 08:08:54
[TRAIN] epoch=7, batch_id=22, loss=0.349695, lr=0.000489,acc=0.898 ETA 08:09:02
[TRAIN] epoch=7, batch_id=32, loss=0.382337, lr=0.000484,acc=0.882 ETA 08:26:46
[TRAIN] epoch=7, batch_id=42, loss=0.395068, lr=0.000479,acc=0.875 ETA 08:19:53
[TRAIN] epoch=7, batch_id=52, loss=0.374991, lr=0.000474,acc=0.882 ETA 07:56:49
[TRAIN] epoch=7, batch_id=62, loss=0.403624, lr=0.000468,acc=0.874 ETA 07:50:09
[TRAIN] epoch=7, batch_id=72, loss=0.402673, lr=0.000463,acc=0.874 ETA 07:54:20
[TRAIN] epoch=7, batch_id=82, loss=0.406572, lr=0.000458,acc=0.871 ETA 07:55:36
[TRAIN] epoch=7, batch_id=92, loss=0.403054, lr=0.000453,acc=0.872 ETA 07:36:21
[TRAIN] epoch=7, batch_id=102, loss=0.414546, lr=0.000447,acc=0.872 ETA 08:58:42
[TRAIN] epoch=7, batch_id=112, loss=0.411942, lr=0.000442,acc=0.872 ETA 07:42:10
[TRAIN] epoch=7, batch_id=122, loss=0.411575, lr=0.000437,acc=0.871 ETA 07:54:19
[TRAIN] epoch=7, batch_id=132, loss=0.406324, lr=0.000432,acc=0.875 ETA 08:24:27
[TRAIN] epoch=7, batch_id=142, loss=0.405387, lr=0.000426,acc=0.875 ETA 07:52:50
[TRAIN] epoch=7, batch_id=152, loss=0.406678, lr=0.000421,acc=0.874 ETA 07:39:17
[TRAIN] epoch=7, batch_id=162, loss=0.406803, lr=0.000416,acc=0.875 ETA 07:58:32
[TRAIN] epoch=7, batch_id=172, loss=0.405324, lr=0.000411,acc=0.876 ETA 07:40:25
[TRAIN] epoch=7, batch_id=182, loss=0.407414, lr=0.000406,acc=0.874 ETA 07:51:56
[TRAIN] epoch=7, batch_id=192, loss=0.403131, lr=0.000401,acc=0.876 ETA 07:48:27
[TRAIN] epoch=7, batch_id=202, loss=0.406363, lr=0.000395,acc=0.876 ETA 08:13:12
[TRAIN] epoch=7, batch_id=212, loss=0.406471, lr=0.000390,acc=0.876 ETA 07:50:46
[TRAIN] epoch=7, batch_id=222, loss=0.407253, lr=0.000385,acc=0.876 ETA 09:29:27
[TRAIN] epoch=7, batch_id=232, loss=0.408912, lr=0.000380,acc=0.876 ETA 07:49:31
[TRAIN] epoch=7, batch_id=242, loss=0.411240, lr=0.000375,acc=0.875 ETA 09:38:44
[TRAIN] epoch=7, batch_id=252, loss=0.411205, lr=0.000370,acc=0.875 ETA 08:06:14
[TRAIN] epoch=7, batch_id=262, loss=0.410942, lr=0.000365,acc=0.876 ETA 07:58:41
[TRAIN] epoch=7, batch_id=272, loss=0.409585, lr=0.000360,acc=0.877 ETA 08:19:09
[TRAIN] epoch=7, batch_id=282, loss=0.410560, lr=0.000355,acc=0.877 ETA 08:05:32
[TRAIN] epoch=7, batch_id=292, loss=0.408817, lr=0.000350,acc=0.878 ETA 08:04:53
[EVAL] epoch=7

Evaluating top_k_accuracy ...

top1_acc	0.7624
top5_acc	0.9403

Evaluating mean_class_accuracy ...

mean_acc	0.7640
Save best model
[TRAIN] epoch=8, batch_id=4, loss=0.330796, lr=0.000344,acc=0.891 ETA 114:53:06
[TRAIN] epoch=8, batch_id=14, loss=0.428012, lr=0.000339,acc=0.882 ETA 08:59:16
[TRAIN] epoch=8, batch_id=24, loss=0.384444, lr=0.000335,acc=0.884 ETA 10:07:24
[TRAIN] epoch=8, batch_id=34, loss=0.377979, lr=0.000330,acc=0.885 ETA 10:28:07
[TRAIN] epoch=8, batch_id=44, loss=0.372613, lr=0.000325,acc=0.887 ETA 08:00:11
[TRAIN] epoch=8, batch_id=54, loss=0.394203, lr=0.000320,acc=0.881 ETA 08:31:54
[TRAIN] epoch=8, batch_id=64, loss=0.389506, lr=0.000315,acc=0.883 ETA 07:56:59
[TRAIN] epoch=8, batch_id=74, loss=0.398303, lr=0.000310,acc=0.880 ETA 08:27:19
[TRAIN] epoch=8, batch_id=84, loss=0.398856, lr=0.000305,acc=0.879 ETA 07:47:27
[TRAIN] epoch=8, batch_id=94, loss=0.391835, lr=0.000300,acc=0.881 ETA 08:23:25
[TRAIN] epoch=8, batch_id=104, loss=0.390016, lr=0.000295,acc=0.883 ETA 09:33:47
[TRAIN] epoch=8, batch_id=114, loss=0.392416, lr=0.000291,acc=0.883 ETA 07:46:44
[TRAIN] epoch=8, batch_id=124, loss=0.388445, lr=0.000286,acc=0.885 ETA 08:35:32
[TRAIN] epoch=8, batch_id=134, loss=0.384685, lr=0.000281,acc=0.886 ETA 08:12:26
[TRAIN] epoch=8, batch_id=144, loss=0.378573, lr=0.000276,acc=0.888 ETA 08:42:12
[TRAIN] epoch=8, batch_id=154, loss=0.379597, lr=0.000272,acc=0.889 ETA 07:52:17
[TRAIN] epoch=8, batch_id=164, loss=0.376665, lr=0.000267,acc=0.889 ETA 08:39:56
[TRAIN] epoch=8, batch_id=174, loss=0.372386, lr=0.000262,acc=0.891 ETA 07:53:02
[TRAIN] epoch=8, batch_id=184, loss=0.370826, lr=0.000258,acc=0.891 ETA 08:33:44
[TRAIN] epoch=8, batch_id=194, loss=0.370375, lr=0.000253,acc=0.891 ETA 07:52:59
[TRAIN] epoch=8, batch_id=204, loss=0.370081, lr=0.000248,acc=0.891 ETA 08:42:23
[TRAIN] epoch=8, batch_id=214, loss=0.367459, lr=0.000244,acc=0.891 ETA 07:38:23
[TRAIN] epoch=8, batch_id=224, loss=0.367507, lr=0.000239,acc=0.891 ETA 08:32:48
[TRAIN] epoch=8, batch_id=234, loss=0.364413, lr=0.000235,acc=0.892 ETA 07:36:18
[TRAIN] epoch=8, batch_id=244, loss=0.366223, lr=0.000230,acc=0.891 ETA 08:23:20
[TRAIN] epoch=8, batch_id=254, loss=0.364950, lr=0.000226,acc=0.892 ETA 07:57:05
[TRAIN] epoch=8, batch_id=264, loss=0.360990, lr=0.000222,acc=0.893 ETA 08:41:37
[TRAIN] epoch=8, batch_id=274, loss=0.359169, lr=0.000217,acc=0.893 ETA 07:49:45
[TRAIN] epoch=8, batch_id=284, loss=0.361477, lr=0.000213,acc=0.892 ETA 07:43:24
[TRAIN] epoch=8, batch_id=294, loss=0.361567, lr=0.000209,acc=0.892 ETA 07:41:10
[EVAL] epoch=8

Evaluating top_k_accuracy ...

top1_acc	0.7706
top5_acc	0.9445

Evaluating mean_class_accuracy ...

mean_acc	0.7704
Save best model
[TRAIN] epoch=9, batch_id=6, loss=0.309368, lr=0.000204,acc=0.917 ETA 113:30:19
[TRAIN] epoch=9, batch_id=16, loss=0.301736, lr=0.000200,acc=0.916 ETA 07:49:15
[TRAIN] epoch=9, batch_id=26, loss=0.300604, lr=0.000196,acc=0.910 ETA 12:12:57
[TRAIN] epoch=9, batch_id=36, loss=0.337108, lr=0.000192,acc=0.897 ETA 08:36:18
[TRAIN] epoch=9, batch_id=46, loss=0.332327, lr=0.000188,acc=0.897 ETA 07:39:48
[TRAIN] epoch=9, batch_id=56, loss=0.340249, lr=0.000184,acc=0.897 ETA 07:48:07
[TRAIN] epoch=9, batch_id=66, loss=0.338336, lr=0.000180,acc=0.899 ETA 07:48:33
[TRAIN] epoch=9, batch_id=76, loss=0.335788, lr=0.000175,acc=0.898 ETA 08:43:10
[TRAIN] epoch=9, batch_id=86, loss=0.337280, lr=0.000171,acc=0.901 ETA 07:24:03
[TRAIN] epoch=9, batch_id=96, loss=0.328025, lr=0.000168,acc=0.903 ETA 07:33:09
[TRAIN] epoch=9, batch_id=106, loss=0.335145, lr=0.000164,acc=0.901 ETA 07:27:08
[TRAIN] epoch=9, batch_id=116, loss=0.340509, lr=0.000160,acc=0.901 ETA 11:13:21
[TRAIN] epoch=9, batch_id=126, loss=0.340696, lr=0.000156,acc=0.901 ETA 15:22:42
[TRAIN] epoch=9, batch_id=136, loss=0.337495, lr=0.000152,acc=0.902 ETA 11:01:41
[TRAIN] epoch=9, batch_id=146, loss=0.342444, lr=0.000148,acc=0.900 ETA 11:38:15
[TRAIN] epoch=9, batch_id=156, loss=0.346404, lr=0.000145,acc=0.898 ETA 07:36:08
[TRAIN] epoch=9, batch_id=166, loss=0.345658, lr=0.000141,acc=0.898 ETA 07:29:56
[TRAIN] epoch=9, batch_id=176, loss=0.345038, lr=0.000137,acc=0.898 ETA 07:44:22
[TRAIN] epoch=9, batch_id=186, loss=0.342876, lr=0.000134,acc=0.899 ETA 07:20:31
[TRAIN] epoch=9, batch_id=196, loss=0.339204, lr=0.000130,acc=0.900 ETA 07:32:44
[TRAIN] epoch=9, batch_id=206, loss=0.336830, lr=0.000127,acc=0.900 ETA 07:26:02
[TRAIN] epoch=9, batch_id=216, loss=0.334462, lr=0.000123,acc=0.901 ETA 07:57:48
[TRAIN] epoch=9, batch_id=226, loss=0.335398, lr=0.000120,acc=0.900 ETA 07:22:16
[TRAIN] epoch=9, batch_id=236, loss=0.334683, lr=0.000116,acc=0.900 ETA 08:43:34
[TRAIN] epoch=9, batch_id=246, loss=0.334675, lr=0.000113,acc=0.900 ETA 07:33:00
[TRAIN] epoch=9, batch_id=256, loss=0.335239, lr=0.000110,acc=0.900 ETA 07:30:10
[TRAIN] epoch=9, batch_id=266, loss=0.334259, lr=0.000106,acc=0.900 ETA 08:26:50
[TRAIN] epoch=9, batch_id=276, loss=0.335878, lr=0.000103,acc=0.900 ETA 07:39:54
[TRAIN] epoch=9, batch_id=286, loss=0.335610, lr=0.000100,acc=0.900 ETA 08:30:31
[TRAIN] epoch=9, batch_id=296, loss=0.336482, lr=0.000097,acc=0.900 ETA 08:21:26
[EVAL] epoch=9

Evaluating top_k_accuracy ...

top1_acc	0.7756
top5_acc	0.9466

Evaluating mean_class_accuracy ...

mean_acc	0.7759
Save best model
[TRAIN] epoch=10, batch_id=8, loss=0.251427, lr=0.000094,acc=0.930 ETA 113:55:28
[TRAIN] epoch=10, batch_id=18, loss=0.316339, lr=0.000091,acc=0.899 ETA 07:50:28
[TRAIN] epoch=10, batch_id=28, loss=0.334128, lr=0.000088,acc=0.897 ETA 10:50:00
[TRAIN] epoch=10, batch_id=38, loss=0.311916, lr=0.000085,acc=0.904 ETA 08:51:29
[TRAIN] epoch=10, batch_id=48, loss=0.303772, lr=0.000082,acc=0.905 ETA 08:28:24
[TRAIN] epoch=10, batch_id=58, loss=0.308682, lr=0.000079,acc=0.905 ETA 07:41:06
[TRAIN] epoch=10, batch_id=68, loss=0.330732, lr=0.000076,acc=0.900 ETA 07:24:20
[TRAIN] epoch=10, batch_id=78, loss=0.332513, lr=0.000073,acc=0.899 ETA 07:29:40
[TRAIN] epoch=10, batch_id=88, loss=0.335433, lr=0.000071,acc=0.900 ETA 10:58:40
[TRAIN] epoch=10, batch_id=98, loss=0.340635, lr=0.000068,acc=0.897 ETA 12:52:12
[TRAIN] epoch=10, batch_id=108, loss=0.337134, lr=0.000065,acc=0.898 ETA 07:22:59
[TRAIN] epoch=10, batch_id=118, loss=0.332007, lr=0.000063,acc=0.899 ETA 08:55:41
[TRAIN] epoch=10, batch_id=128, loss=0.333939, lr=0.000060,acc=0.897 ETA 07:45:24
[TRAIN] epoch=10, batch_id=138, loss=0.332413, lr=0.000058,acc=0.899 ETA 08:49:12
[TRAIN] epoch=10, batch_id=148, loss=0.326756, lr=0.000055,acc=0.900 ETA 09:03:25
[TRAIN] epoch=10, batch_id=158, loss=0.324395, lr=0.000053,acc=0.901 ETA 07:57:05
[TRAIN] epoch=10, batch_id=168, loss=0.321920, lr=0.000051,acc=0.901 ETA 07:17:33
[TRAIN] epoch=10, batch_id=178, loss=0.320117, lr=0.000048,acc=0.902 ETA 07:24:33
[TRAIN] epoch=10, batch_id=188, loss=0.321391, lr=0.000046,acc=0.901 ETA 07:33:30
[TRAIN] epoch=10, batch_id=198, loss=0.318198, lr=0.000044,acc=0.902 ETA 07:49:17
[TRAIN] epoch=10, batch_id=208, loss=0.318744, lr=0.000042,acc=0.901 ETA 07:59:08
[TRAIN] epoch=10, batch_id=218, loss=0.318945, lr=0.000040,acc=0.901 ETA 09:07:46
[TRAIN] epoch=10, batch_id=228, loss=0.320051, lr=0.000038,acc=0.900 ETA 12:42:02
[TRAIN] epoch=10, batch_id=238, loss=0.318011, lr=0.000036,acc=0.900 ETA 10:40:23
[TRAIN] epoch=10, batch_id=248, loss=0.317414, lr=0.000034,acc=0.900 ETA 07:22:09
[TRAIN] epoch=10, batch_id=258, loss=0.317688, lr=0.000032,acc=0.900 ETA 07:29:49
[TRAIN] epoch=10, batch_id=268, loss=0.315845, lr=0.000030,acc=0.901 ETA 07:26:11
[TRAIN] epoch=10, batch_id=278, loss=0.313585, lr=0.000028,acc=0.901 ETA 11:04:19
[TRAIN] epoch=10, batch_id=288, loss=0.315297, lr=0.000026,acc=0.901 ETA 07:42:20
[TRAIN] epoch=10, batch_id=298, loss=0.318789, lr=0.000025,acc=0.900 ETA 08:53:27
[EVAL] epoch=10

Evaluating top_k_accuracy ...

top1_acc	0.7782
top5_acc	0.9495

Evaluating mean_class_accuracy ...

mean_acc	0.7782
Save best model
[TRAIN] epoch=11, batch_id=10, loss=0.325004, lr=0.000023,acc=0.906 ETA 111:26:57
[TRAIN] epoch=11, batch_id=20, loss=0.272827, lr=0.000022,acc=0.917 ETA 08:01:37
[TRAIN] epoch=11, batch_id=30, loss=0.280245, lr=0.000020,acc=0.910 ETA 07:50:12
[TRAIN] epoch=11, batch_id=40, loss=0.298265, lr=0.000019,acc=0.903 ETA 07:30:02
[TRAIN] epoch=11, batch_id=50, loss=0.301923, lr=0.000017,acc=0.901 ETA 07:34:42
[TRAIN] epoch=11, batch_id=60, loss=0.296235, lr=0.000016,acc=0.906 ETA 07:45:31
[TRAIN] epoch=11, batch_id=70, loss=0.297927, lr=0.000015,acc=0.905 ETA 11:13:22
[TRAIN] epoch=11, batch_id=80, loss=0.299705, lr=0.000013,acc=0.906 ETA 10:37:29
[TRAIN] epoch=11, batch_id=90, loss=0.303301, lr=0.000012,acc=0.906 ETA 07:26:34
[TRAIN] epoch=11, batch_id=100, loss=0.300440, lr=0.000011,acc=0.908 ETA 07:07:33
[TRAIN] epoch=11, batch_id=110, loss=0.307589, lr=0.000010,acc=0.907 ETA 08:14:55
[TRAIN] epoch=11, batch_id=120, loss=0.305477, lr=0.000009,acc=0.908 ETA 07:19:14
[TRAIN] epoch=11, batch_id=130, loss=0.308509, lr=0.000008,acc=0.909 ETA 09:07:09
[TRAIN] epoch=11, batch_id=140, loss=0.308889, lr=0.000007,acc=0.909 ETA 07:22:51
[TRAIN] epoch=11, batch_id=150, loss=0.307994, lr=0.000006,acc=0.909 ETA 07:55:22
[TRAIN] epoch=11, batch_id=160, loss=0.311006, lr=0.000005,acc=0.910 ETA 07:23:03
[TRAIN] epoch=11, batch_id=170, loss=0.314251, lr=0.000005,acc=0.908 ETA 07:59:18
[TRAIN] epoch=11, batch_id=180, loss=0.309963, lr=0.000004,acc=0.910 ETA 07:23:26
[TRAIN] epoch=11, batch_id=190, loss=0.307194, lr=0.000003,acc=0.911 ETA 09:21:44
[TRAIN] epoch=11, batch_id=200, loss=0.305981, lr=0.000003,acc=0.912 ETA 07:16:06
[TRAIN] epoch=11, batch_id=210, loss=0.307780, lr=0.000002,acc=0.911 ETA 07:41:05
[TRAIN] epoch=11, batch_id=220, loss=0.310999, lr=0.000002,acc=0.910 ETA 07:22:21
[TRAIN] epoch=11, batch_id=230, loss=0.308919, lr=0.000001,acc=0.911 ETA 07:40:39
[TRAIN] epoch=11, batch_id=240, loss=0.312519, lr=0.000001,acc=0.910 ETA 07:14:55
[TRAIN] epoch=11, batch_id=250, loss=0.312192, lr=0.000001,acc=0.910 ETA 09:06:32
[TRAIN] epoch=11, batch_id=260, loss=0.313695, lr=0.000000,acc=0.909 ETA 07:08:46
[TRAIN] epoch=11, batch_id=270, loss=0.314367, lr=0.000000,acc=0.909 ETA 07:33:34
[TRAIN] epoch=11, batch_id=280, loss=0.313260, lr=0.000000,acc=0.909 ETA 07:17:31
[TRAIN] epoch=11, batch_id=290, loss=0.311644, lr=0.000000,acc=0.909 ETA 07:22:52
[EVAL] epoch=11

Evaluating top_k_accuracy ...

top1_acc	0.7774
top5_acc	0.9495

Evaluating mean_class_accuracy ...

mean_acc	0.7774
[TRAIN] epoch=12, batch_id=2, loss=0.164214, lr=0.000000,acc=0.969 ETA 106:51:46
[TRAIN] epoch=12, batch_id=12, loss=0.303883, lr=0.000000,acc=0.914 ETA 07:59:15
[TRAIN] epoch=12, batch_id=22, loss=0.293154, lr=0.000000,acc=0.918 ETA 07:30:39
[TRAIN] epoch=12, batch_id=32, loss=0.318384, lr=0.000000,acc=0.905 ETA 08:28:53
[TRAIN] epoch=12, batch_id=42, loss=0.328279, lr=0.000000,acc=0.903 ETA 07:20:46
[TRAIN] epoch=12, batch_id=52, loss=0.321869, lr=0.000001,acc=0.904 ETA 07:32:58
[TRAIN] epoch=12, batch_id=62, loss=0.324996, lr=0.000001,acc=0.903 ETA 07:17:13
[TRAIN] epoch=12, batch_id=72, loss=0.325243, lr=0.000001,acc=0.902 ETA 07:28:41
[TRAIN] epoch=12, batch_id=82, loss=0.324002, lr=0.000002,acc=0.904 ETA 07:38:56
[TRAIN] epoch=12, batch_id=92, loss=0.327094, lr=0.000002,acc=0.900 ETA 08:40:54
[TRAIN] epoch=12, batch_id=102, loss=0.326476, lr=0.000003,acc=0.900 ETA 07:28:30
[TRAIN] epoch=12, batch_id=112, loss=0.330565, lr=0.000003,acc=0.898 ETA 08:59:01
[TRAIN] epoch=12, batch_id=122, loss=0.329308, lr=0.000004,acc=0.898 ETA 07:21:37
[TRAIN] epoch=12, batch_id=132, loss=0.323328, lr=0.000005,acc=0.900 ETA 09:06:24
[TRAIN] epoch=12, batch_id=142, loss=0.324947, lr=0.000005,acc=0.900 ETA 07:20:11
[TRAIN] epoch=12, batch_id=152, loss=0.324736, lr=0.000006,acc=0.900 ETA 07:55:19
[TRAIN] epoch=12, batch_id=162, loss=0.322854, lr=0.000007,acc=0.900 ETA 07:29:21
[TRAIN] epoch=12, batch_id=172, loss=0.319563, lr=0.000008,acc=0.902 ETA 07:32:39
[TRAIN] epoch=12, batch_id=182, loss=0.319408, lr=0.000009,acc=0.902 ETA 11:14:39
[TRAIN] epoch=12, batch_id=192, loss=0.323115, lr=0.000010,acc=0.900 ETA 09:24:34
[TRAIN] epoch=12, batch_id=202, loss=0.321884, lr=0.000011,acc=0.901 ETA 07:28:21
[TRAIN] epoch=12, batch_id=212, loss=0.322569, lr=0.000012,acc=0.901 ETA 08:02:03
[TRAIN] epoch=12, batch_id=222, loss=0.322953, lr=0.000013,acc=0.901 ETA 07:34:42
[TRAIN] epoch=12, batch_id=232, loss=0.321154, lr=0.000015,acc=0.902 ETA 07:25:07
[TRAIN] epoch=12, batch_id=242, loss=0.322172, lr=0.000016,acc=0.901 ETA 08:57:25
[TRAIN] epoch=12, batch_id=252, loss=0.320705, lr=0.000017,acc=0.902 ETA 11:31:36
[TRAIN] epoch=12, batch_id=262, loss=0.319420, lr=0.000019,acc=0.903 ETA 09:22:52
[TRAIN] epoch=12, batch_id=272, loss=0.323168, lr=0.000020,acc=0.902 ETA 08:22:18
[TRAIN] epoch=12, batch_id=282, loss=0.323918, lr=0.000022,acc=0.902 ETA 07:52:24
[TRAIN] epoch=12, batch_id=292, loss=0.322064, lr=0.000023,acc=0.903 ETA 07:44:48
[EVAL] epoch=12

Evaluating top_k_accuracy ...

top1_acc	0.7772
top5_acc	0.9477

Evaluating mean_class_accuracy ...

mean_acc	0.7768
[TRAIN] epoch=13, batch_id=4, loss=0.348384, lr=0.000025,acc=0.883 ETA 107:49:17
[TRAIN] epoch=13, batch_id=14, loss=0.300856, lr=0.000026,acc=0.900 ETA 07:14:21
[TRAIN] epoch=13, batch_id=24, loss=0.303893, lr=0.000028,acc=0.895 ETA 09:51:15
[TRAIN] epoch=13, batch_id=34, loss=0.289672, lr=0.000030,acc=0.905 ETA 07:46:01
[TRAIN] epoch=13, batch_id=44, loss=0.280990, lr=0.000032,acc=0.905 ETA 08:20:40
[TRAIN] epoch=13, batch_id=54, loss=0.282568, lr=0.000034,acc=0.909 ETA 07:09:38
[TRAIN] epoch=13, batch_id=64, loss=0.286755, lr=0.000036,acc=0.906 ETA 07:17:37
[TRAIN] epoch=13, batch_id=74, loss=0.295805, lr=0.000038,acc=0.905 ETA 07:09:45
[TRAIN] epoch=13, batch_id=84, loss=0.291652, lr=0.000040,acc=0.906 ETA 08:14:35
[TRAIN] epoch=13, batch_id=94, loss=0.296769, lr=0.000042,acc=0.906 ETA 07:09:31
[TRAIN] epoch=13, batch_id=104, loss=0.299537, lr=0.000044,acc=0.906 ETA 08:45:20
[TRAIN] epoch=13, batch_id=114, loss=0.293643, lr=0.000046,acc=0.907 ETA 07:07:30
[TRAIN] epoch=13, batch_id=124, loss=0.289488, lr=0.000048,acc=0.909 ETA 08:56:07
[TRAIN] epoch=13, batch_id=134, loss=0.289233, lr=0.000051,acc=0.909 ETA 07:12:27
[TRAIN] epoch=13, batch_id=144, loss=0.292194, lr=0.000053,acc=0.907 ETA 09:01:31
[TRAIN] epoch=13, batch_id=154, loss=0.292939, lr=0.000055,acc=0.906 ETA 07:12:50
[TRAIN] epoch=13, batch_id=164, loss=0.290169, lr=0.000058,acc=0.907 ETA 08:46:00
[TRAIN] epoch=13, batch_id=174, loss=0.289043, lr=0.000060,acc=0.907 ETA 09:01:14
[TRAIN] epoch=13, batch_id=184, loss=0.287317, lr=0.000063,acc=0.907 ETA 07:07:39
[TRAIN] epoch=13, batch_id=194, loss=0.284369, lr=0.000065,acc=0.908 ETA 10:40:44
[TRAIN] epoch=13, batch_id=204, loss=0.287442, lr=0.000068,acc=0.907 ETA 07:25:31
[TRAIN] epoch=13, batch_id=214, loss=0.290715, lr=0.000071,acc=0.906 ETA 07:35:19
[TRAIN] epoch=13, batch_id=224, loss=0.296952, lr=0.000073,acc=0.904 ETA 07:08:59
[TRAIN] epoch=13, batch_id=234, loss=0.299107, lr=0.000076,acc=0.903 ETA 07:09:52
[TRAIN] epoch=13, batch_id=244, loss=0.299680, lr=0.000079,acc=0.904 ETA 10:43:25
[TRAIN] epoch=13, batch_id=254, loss=0.299873, lr=0.000082,acc=0.904 ETA 07:24:39
[TRAIN] epoch=13, batch_id=264, loss=0.303009, lr=0.000085,acc=0.903 ETA 07:30:54
[TRAIN] epoch=13, batch_id=274, loss=0.302170, lr=0.000088,acc=0.904 ETA 09:12:40
[TRAIN] epoch=13, batch_id=284, loss=0.301618, lr=0.000091,acc=0.904 ETA 10:10:36
[TRAIN] epoch=13, batch_id=294, loss=0.300242, lr=0.000094,acc=0.905 ETA 08:03:01
[EVAL] epoch=13

Evaluating top_k_accuracy ...

top1_acc	0.7740
top5_acc	0.9466

Evaluating mean_class_accuracy ...

mean_acc	0.7748
[TRAIN] epoch=14, batch_id=6, loss=0.200602, lr=0.000097,acc=0.932 ETA 110:28:03
[TRAIN] epoch=14, batch_id=16, loss=0.280895, lr=0.000100,acc=0.908 ETA 07:16:32
[TRAIN] epoch=14, batch_id=26, loss=0.293733, lr=0.000103,acc=0.901 ETA 07:16:04
[TRAIN] epoch=14, batch_id=36, loss=0.304284, lr=0.000106,acc=0.905 ETA 07:15:45
[TRAIN] epoch=14, batch_id=46, loss=0.312319, lr=0.000110,acc=0.903 ETA 07:38:20
[TRAIN] epoch=14, batch_id=56, loss=0.305898, lr=0.000113,acc=0.907 ETA 07:10:48
[TRAIN] epoch=14, batch_id=66, loss=0.312040, lr=0.000116,acc=0.907 ETA 07:15:15
[TRAIN] epoch=14, batch_id=76, loss=0.318426, lr=0.000120,acc=0.907 ETA 07:14:42
[TRAIN] epoch=14, batch_id=86, loss=0.310671, lr=0.000123,acc=0.908 ETA 07:33:19
[TRAIN] epoch=14, batch_id=96, loss=0.319051, lr=0.000127,acc=0.905 ETA 08:33:42
[TRAIN] epoch=14, batch_id=106, loss=0.319887, lr=0.000130,acc=0.903 ETA 07:05:27
[TRAIN] epoch=14, batch_id=116, loss=0.320654, lr=0.000134,acc=0.902 ETA 07:08:12
[TRAIN] epoch=14, batch_id=126, loss=0.316268, lr=0.000137,acc=0.903 ETA 07:16:04
[TRAIN] epoch=14, batch_id=136, loss=0.315078, lr=0.000141,acc=0.903 ETA 08:14:01
[TRAIN] epoch=14, batch_id=146, loss=0.312804, lr=0.000145,acc=0.904 ETA 07:00:35
[TRAIN] epoch=14, batch_id=156, loss=0.312128, lr=0.000148,acc=0.904 ETA 07:12:14
[TRAIN] epoch=14, batch_id=166, loss=0.305232, lr=0.000152,acc=0.906 ETA 06:57:29
[TRAIN] epoch=14, batch_id=176, loss=0.305722, lr=0.000156,acc=0.906 ETA 08:47:13
[TRAIN] epoch=14, batch_id=186, loss=0.307307, lr=0.000160,acc=0.905 ETA 07:08:59
[TRAIN] epoch=14, batch_id=196, loss=0.307936, lr=0.000164,acc=0.905 ETA 07:09:27
[TRAIN] epoch=14, batch_id=206, loss=0.308418, lr=0.000168,acc=0.905 ETA 06:58:03
[TRAIN] epoch=14, batch_id=216, loss=0.306102, lr=0.000171,acc=0.906 ETA 07:08:18
[TRAIN] epoch=14, batch_id=226, loss=0.310587, lr=0.000175,acc=0.905 ETA 07:08:08
[TRAIN] epoch=14, batch_id=236, loss=0.310207, lr=0.000180,acc=0.905 ETA 07:20:00
[TRAIN] epoch=14, batch_id=246, loss=0.312128, lr=0.000184,acc=0.904 ETA 06:58:34
[TRAIN] epoch=14, batch_id=256, loss=0.313241, lr=0.000188,acc=0.903 ETA 07:11:43
[TRAIN] epoch=14, batch_id=266, loss=0.309997, lr=0.000192,acc=0.905 ETA 06:56:00
[TRAIN] epoch=14, batch_id=276, loss=0.307864, lr=0.000196,acc=0.906 ETA 07:02:38
[TRAIN] epoch=14, batch_id=286, loss=0.307018, lr=0.000200,acc=0.906 ETA 07:00:53
[TRAIN] epoch=14, batch_id=296, loss=0.305906, lr=0.000204,acc=0.906 ETA 07:19:51
[EVAL] epoch=14

Evaluating top_k_accuracy ...

top1_acc	0.7774
top5_acc	0.9466

Evaluating mean_class_accuracy ...

mean_acc	0.7770
[TRAIN] epoch=15, batch_id=8, loss=0.341426, lr=0.000209,acc=0.898 ETA 104:02:23
[TRAIN] epoch=15, batch_id=18, loss=0.331310, lr=0.000213,acc=0.901 ETA 07:37:20
[TRAIN] epoch=15, batch_id=28, loss=0.327162, lr=0.000217,acc=0.901 ETA 06:52:54
[TRAIN] epoch=15, batch_id=38, loss=0.303413, lr=0.000222,acc=0.906 ETA 06:52:57
[TRAIN] epoch=15, batch_id=48, loss=0.304901, lr=0.000226,acc=0.905 ETA 06:52:59
[TRAIN] epoch=15, batch_id=58, loss=0.315755, lr=0.000230,acc=0.900 ETA 08:26:15
[TRAIN] epoch=15, batch_id=68, loss=0.319918, lr=0.000235,acc=0.899 ETA 07:08:32
[TRAIN] epoch=15, batch_id=78, loss=0.322953, lr=0.000239,acc=0.902 ETA 07:11:00
[TRAIN] epoch=15, batch_id=88, loss=0.316028, lr=0.000244,acc=0.904 ETA 06:56:50
[TRAIN] epoch=15, batch_id=98, loss=0.316418, lr=0.000248,acc=0.904 ETA 07:23:00
[TRAIN] epoch=15, batch_id=108, loss=0.310076, lr=0.000253,acc=0.906 ETA 06:52:27
[TRAIN] epoch=15, batch_id=118, loss=0.306779, lr=0.000258,acc=0.906 ETA 07:28:22
[TRAIN] epoch=15, batch_id=128, loss=0.306195, lr=0.000262,acc=0.905 ETA 07:01:46
[TRAIN] epoch=15, batch_id=138, loss=0.308234, lr=0.000267,acc=0.904 ETA 09:00:21
[TRAIN] epoch=15, batch_id=148, loss=0.307636, lr=0.000272,acc=0.904 ETA 07:32:31
[TRAIN] epoch=15, batch_id=158, loss=0.307642, lr=0.000276,acc=0.905 ETA 06:57:27
[TRAIN] epoch=15, batch_id=168, loss=0.306969, lr=0.000281,acc=0.905 ETA 06:56:57
[TRAIN] epoch=15, batch_id=178, loss=0.307450, lr=0.000286,acc=0.905 ETA 08:17:40
[TRAIN] epoch=15, batch_id=188, loss=0.307676, lr=0.000291,acc=0.905 ETA 07:08:10
[TRAIN] epoch=15, batch_id=198, loss=0.309124, lr=0.000295,acc=0.905 ETA 07:13:30
[TRAIN] epoch=15, batch_id=208, loss=0.311279, lr=0.000300,acc=0.904 ETA 07:12:16
[TRAIN] epoch=15, batch_id=218, loss=0.313000, lr=0.000305,acc=0.903 ETA 08:03:39
[TRAIN] epoch=15, batch_id=228, loss=0.312163, lr=0.000310,acc=0.904 ETA 07:03:43
[TRAIN] epoch=15, batch_id=238, loss=0.312110, lr=0.000315,acc=0.904 ETA 07:05:01
[TRAIN] epoch=15, batch_id=248, loss=0.313910, lr=0.000320,acc=0.904 ETA 06:59:13
[TRAIN] epoch=15, batch_id=258, loss=0.311035, lr=0.000325,acc=0.905 ETA 07:02:02
[TRAIN] epoch=15, batch_id=268, loss=0.308128, lr=0.000330,acc=0.906 ETA 07:03:51
[TRAIN] epoch=15, batch_id=278, loss=0.305748, lr=0.000335,acc=0.906 ETA 07:43:11
[TRAIN] epoch=15, batch_id=288, loss=0.306211, lr=0.000339,acc=0.907 ETA 08:29:09
[TRAIN] epoch=15, batch_id=298, loss=0.307490, lr=0.000344,acc=0.907 ETA 07:57:19
[EVAL] epoch=15

Evaluating top_k_accuracy ...

top1_acc	0.7684
top5_acc	0.9471

Evaluating mean_class_accuracy ...

mean_acc	0.7690
[TRAIN] epoch=16, batch_id=10, loss=0.288843, lr=0.000350,acc=0.928 ETA 101:43:14
[TRAIN] epoch=16, batch_id=20, loss=0.288927, lr=0.000355,acc=0.916 ETA 09:21:44
[TRAIN] epoch=16, batch_id=30, loss=0.298006, lr=0.000360,acc=0.916 ETA 07:43:03
[TRAIN] epoch=16, batch_id=40, loss=0.299046, lr=0.000365,acc=0.908 ETA 06:57:11
[TRAIN] epoch=16, batch_id=50, loss=0.313552, lr=0.000370,acc=0.905 ETA 06:52:18
[TRAIN] epoch=16, batch_id=60, loss=0.309531, lr=0.000375,acc=0.907 ETA 07:17:30
[TRAIN] epoch=16, batch_id=70, loss=0.303007, lr=0.000380,acc=0.909 ETA 06:54:18
[TRAIN] epoch=16, batch_id=80, loss=0.292359, lr=0.000385,acc=0.913 ETA 06:53:36
[TRAIN] epoch=16, batch_id=90, loss=0.293821, lr=0.000390,acc=0.911 ETA 07:07:59
[TRAIN] epoch=16, batch_id=100, loss=0.299195, lr=0.000395,acc=0.910 ETA 08:05:41
[TRAIN] epoch=16, batch_id=110, loss=0.298064, lr=0.000401,acc=0.909 ETA 07:39:04
[TRAIN] epoch=16, batch_id=120, loss=0.307182, lr=0.000406,acc=0.907 ETA 06:57:47
[TRAIN] epoch=16, batch_id=130, loss=0.304637, lr=0.000411,acc=0.909 ETA 06:56:29
[TRAIN] epoch=16, batch_id=140, loss=0.305220, lr=0.000416,acc=0.910 ETA 07:45:23
[TRAIN] epoch=16, batch_id=150, loss=0.308067, lr=0.000421,acc=0.910 ETA 07:44:28
[TRAIN] epoch=16, batch_id=160, loss=0.309520, lr=0.000426,acc=0.910 ETA 06:50:23
[TRAIN] epoch=16, batch_id=170, loss=0.307587, lr=0.000432,acc=0.911 ETA 06:52:19
[TRAIN] epoch=16, batch_id=180, loss=0.311792, lr=0.000437,acc=0.908 ETA 07:46:32
[TRAIN] epoch=16, batch_id=190, loss=0.306846, lr=0.000442,acc=0.909 ETA 08:43:46
[TRAIN] epoch=16, batch_id=200, loss=0.306539, lr=0.000447,acc=0.909 ETA 08:04:11
[TRAIN] epoch=16, batch_id=210, loss=0.308052, lr=0.000453,acc=0.907 ETA 08:09:04
[TRAIN] epoch=16, batch_id=220, loss=0.307102, lr=0.000458,acc=0.907 ETA 07:59:23
[TRAIN] epoch=16, batch_id=230, loss=0.305860, lr=0.000463,acc=0.907 ETA 07:34:07
[TRAIN] epoch=16, batch_id=240, loss=0.308753, lr=0.000468,acc=0.907 ETA 08:20:26
[TRAIN] epoch=16, batch_id=250, loss=0.311066, lr=0.000474,acc=0.906 ETA 07:59:41
[TRAIN] epoch=16, batch_id=260, loss=0.311945, lr=0.000479,acc=0.906 ETA 10:07:15
[TRAIN] epoch=16, batch_id=270, loss=0.308472, lr=0.000484,acc=0.907 ETA 06:51:06
[TRAIN] epoch=16, batch_id=280, loss=0.308371, lr=0.000489,acc=0.907 ETA 07:07:36
[TRAIN] epoch=16, batch_id=290, loss=0.310214, lr=0.000495,acc=0.906 ETA 06:43:35
[EVAL] epoch=16

Evaluating top_k_accuracy ...

top1_acc	0.7698
top5_acc	0.9440

Evaluating mean_class_accuracy ...

mean_acc	0.7692
[TRAIN] epoch=17, batch_id=2, loss=0.355433, lr=0.000500,acc=0.922 ETA 103:02:56
[TRAIN] epoch=17, batch_id=12, loss=0.253237, lr=0.000505,acc=0.914 ETA 07:52:12
[TRAIN] epoch=17, batch_id=22, loss=0.239010, lr=0.000511,acc=0.925 ETA 10:49:27
[TRAIN] epoch=17, batch_id=32, loss=0.228271, lr=0.000516,acc=0.929 ETA 08:07:48
[TRAIN] epoch=17, batch_id=42, loss=0.240738, lr=0.000521,acc=0.922 ETA 06:49:11
[TRAIN] epoch=17, batch_id=52, loss=0.241654, lr=0.000526,acc=0.922 ETA 07:46:31
[TRAIN] epoch=17, batch_id=62, loss=0.249054, lr=0.000532,acc=0.920 ETA 07:01:56
[TRAIN] epoch=17, batch_id=72, loss=0.248563, lr=0.000537,acc=0.921 ETA 06:54:51
[TRAIN] epoch=17, batch_id=82, loss=0.263657, lr=0.000542,acc=0.920 ETA 07:46:30
[TRAIN] epoch=17, batch_id=92, loss=0.261911, lr=0.000547,acc=0.918 ETA 10:42:22
[TRAIN] epoch=17, batch_id=102, loss=0.268627, lr=0.000553,acc=0.916 ETA 10:39:53
[TRAIN] epoch=17, batch_id=112, loss=0.284226, lr=0.000558,acc=0.912 ETA 10:45:58
[TRAIN] epoch=17, batch_id=122, loss=0.286761, lr=0.000563,acc=0.911 ETA 09:39:56
[TRAIN] epoch=17, batch_id=132, loss=0.294829, lr=0.000568,acc=0.909 ETA 07:27:47
[TRAIN] epoch=17, batch_id=142, loss=0.297579, lr=0.000574,acc=0.908 ETA 20:40:12
[TRAIN] epoch=17, batch_id=152, loss=0.294388, lr=0.000579,acc=0.909 ETA 09:45:36
[TRAIN] epoch=17, batch_id=162, loss=0.289006, lr=0.000584,acc=0.911 ETA 06:58:20
[TRAIN] epoch=17, batch_id=172, loss=0.291091, lr=0.000589,acc=0.909 ETA 06:56:24
[TRAIN] epoch=17, batch_id=182, loss=0.295032, lr=0.000594,acc=0.907 ETA 06:55:20
[TRAIN] epoch=17, batch_id=192, loss=0.297697, lr=0.000599,acc=0.907 ETA 06:55:41
[TRAIN] epoch=17, batch_id=202, loss=0.297316, lr=0.000605,acc=0.907 ETA 06:39:59
[TRAIN] epoch=17, batch_id=212, loss=0.296561, lr=0.000610,acc=0.908 ETA 06:41:44
[TRAIN] epoch=17, batch_id=222, loss=0.297428, lr=0.000615,acc=0.908 ETA 06:48:39
[TRAIN] epoch=17, batch_id=232, loss=0.293834, lr=0.000620,acc=0.909 ETA 06:58:54
[TRAIN] epoch=17, batch_id=242, loss=0.292732, lr=0.000625,acc=0.909 ETA 06:51:40
[TRAIN] epoch=17, batch_id=252, loss=0.294105, lr=0.000630,acc=0.909 ETA 07:27:46
[TRAIN] epoch=17, batch_id=262, loss=0.294155, lr=0.000635,acc=0.909 ETA 09:02:59
[TRAIN] epoch=17, batch_id=272, loss=0.292347, lr=0.000640,acc=0.910 ETA 11:14:30
[TRAIN] epoch=17, batch_id=282, loss=0.291988, lr=0.000645,acc=0.910 ETA 07:49:31
[TRAIN] epoch=17, batch_id=292, loss=0.291824, lr=0.000650,acc=0.910 ETA 06:42:37
[EVAL] epoch=17

Evaluating top_k_accuracy ...

top1_acc	0.7613
top5_acc	0.9437

Evaluating mean_class_accuracy ...

mean_acc	0.7615
[TRAIN] epoch=18, batch_id=4, loss=0.300230, lr=0.000656,acc=0.914 ETA 101:31:25
[TRAIN] epoch=18, batch_id=14, loss=0.274951, lr=0.000661,acc=0.913 ETA 09:51:01
[TRAIN] epoch=18, batch_id=24, loss=0.251220, lr=0.000665,acc=0.913 ETA 07:31:46
[TRAIN] epoch=18, batch_id=34, loss=0.243721, lr=0.000670,acc=0.916 ETA 07:47:15
[TRAIN] epoch=18, batch_id=44, loss=0.253392, lr=0.000675,acc=0.915 ETA 08:18:24
[TRAIN] epoch=18, batch_id=54, loss=0.261465, lr=0.000680,acc=0.914 ETA 07:26:15
[TRAIN] epoch=18, batch_id=64, loss=0.264377, lr=0.000685,acc=0.914 ETA 07:05:39
[TRAIN] epoch=18, batch_id=74, loss=0.260810, lr=0.000690,acc=0.914 ETA 06:41:20
[TRAIN] epoch=18, batch_id=84, loss=0.265073, lr=0.000695,acc=0.916 ETA 06:45:36
[TRAIN] epoch=18, batch_id=94, loss=0.264773, lr=0.000700,acc=0.916 ETA 06:50:08
[TRAIN] epoch=18, batch_id=104, loss=0.263410, lr=0.000705,acc=0.915 ETA 08:52:11
[TRAIN] epoch=18, batch_id=114, loss=0.266030, lr=0.000709,acc=0.914 ETA 06:41:19
[TRAIN] epoch=18, batch_id=124, loss=0.263548, lr=0.000714,acc=0.916 ETA 06:40:55
[TRAIN] epoch=18, batch_id=134, loss=0.266026, lr=0.000719,acc=0.916 ETA 06:42:22
[TRAIN] epoch=18, batch_id=144, loss=0.262356, lr=0.000724,acc=0.916 ETA 08:38:36
[TRAIN] epoch=18, batch_id=154, loss=0.265804, lr=0.000728,acc=0.914 ETA 08:02:55
[TRAIN] epoch=18, batch_id=164, loss=0.273502, lr=0.000733,acc=0.912 ETA 06:43:01
[TRAIN] epoch=18, batch_id=174, loss=0.274770, lr=0.000738,acc=0.912 ETA 06:43:11
[TRAIN] epoch=18, batch_id=184, loss=0.270318, lr=0.000742,acc=0.914 ETA 08:25:55
[TRAIN] epoch=18, batch_id=194, loss=0.275679, lr=0.000747,acc=0.912 ETA 13:06:49
[TRAIN] epoch=18, batch_id=204, loss=0.275022, lr=0.000752,acc=0.913 ETA 10:04:56
[TRAIN] epoch=18, batch_id=214, loss=0.274887, lr=0.000756,acc=0.913 ETA 06:45:14
[TRAIN] epoch=18, batch_id=224, loss=0.276491, lr=0.000761,acc=0.913 ETA 06:43:58
[TRAIN] epoch=18, batch_id=234, loss=0.276894, lr=0.000765,acc=0.913 ETA 07:26:24
[TRAIN] epoch=18, batch_id=244, loss=0.274204, lr=0.000770,acc=0.914 ETA 07:36:40
[TRAIN] epoch=18, batch_id=254, loss=0.277193, lr=0.000774,acc=0.914 ETA 06:45:20
[TRAIN] epoch=18, batch_id=264, loss=0.274888, lr=0.000778,acc=0.914 ETA 07:00:54
[TRAIN] epoch=18, batch_id=274, loss=0.279248, lr=0.000783,acc=0.912 ETA 07:44:39
[TRAIN] epoch=18, batch_id=284, loss=0.279372, lr=0.000787,acc=0.912 ETA 06:53:39
[TRAIN] epoch=18, batch_id=294, loss=0.277496, lr=0.000791,acc=0.913 ETA 06:46:45
[EVAL] epoch=18

Evaluating top_k_accuracy ...

top1_acc	0.7740
top5_acc	0.9471

Evaluating mean_class_accuracy ...

mean_acc	0.7716
[TRAIN] epoch=19, batch_id=6, loss=0.385077, lr=0.000796,acc=0.880 ETA 99:17:24
[TRAIN] epoch=19, batch_id=16, loss=0.317654, lr=0.000800,acc=0.910 ETA 07:24:11
[TRAIN] epoch=19, batch_id=26, loss=0.292255, lr=0.000804,acc=0.919 ETA 06:42:10
[TRAIN] epoch=19, batch_id=36, loss=0.298100, lr=0.000808,acc=0.916 ETA 07:33:58
[TRAIN] epoch=19, batch_id=46, loss=0.319758, lr=0.000812,acc=0.910 ETA 07:02:13
[TRAIN] epoch=19, batch_id=56, loss=0.313117, lr=0.000816,acc=0.909 ETA 08:10:07
[TRAIN] epoch=19, batch_id=66, loss=0.295683, lr=0.000820,acc=0.915 ETA 06:58:29
[TRAIN] epoch=19, batch_id=76, loss=0.295852, lr=0.000825,acc=0.912 ETA 09:53:04
[TRAIN] epoch=19, batch_id=86, loss=0.304471, lr=0.000829,acc=0.908 ETA 07:03:26
[TRAIN] epoch=19, batch_id=96, loss=0.296968, lr=0.000832,acc=0.910 ETA 08:17:24
[TRAIN] epoch=19, batch_id=106, loss=0.287516, lr=0.000836,acc=0.913 ETA 07:00:38
[TRAIN] epoch=19, batch_id=116, loss=0.282738, lr=0.000840,acc=0.915 ETA 07:48:15
[TRAIN] epoch=19, batch_id=126, loss=0.280502, lr=0.000844,acc=0.915 ETA 07:36:05
[TRAIN] epoch=19, batch_id=136, loss=0.276853, lr=0.000848,acc=0.916 ETA 06:44:44
[TRAIN] epoch=19, batch_id=146, loss=0.277144, lr=0.000852,acc=0.916 ETA 06:58:30
[TRAIN] epoch=19, batch_id=156, loss=0.273197, lr=0.000855,acc=0.917 ETA 06:43:50
[TRAIN] epoch=19, batch_id=166, loss=0.272937, lr=0.000859,acc=0.917 ETA 06:48:49
[TRAIN] epoch=19, batch_id=176, loss=0.274538, lr=0.000863,acc=0.917 ETA 06:39:51
[TRAIN] epoch=19, batch_id=186, loss=0.272426, lr=0.000866,acc=0.917 ETA 08:16:11
[TRAIN] epoch=19, batch_id=196, loss=0.272090, lr=0.000870,acc=0.918 ETA 10:32:31
[TRAIN] epoch=19, batch_id=206, loss=0.272797, lr=0.000873,acc=0.917 ETA 08:51:58
[TRAIN] epoch=19, batch_id=216, loss=0.271663, lr=0.000877,acc=0.918 ETA 06:37:45
[TRAIN] epoch=19, batch_id=226, loss=0.267709, lr=0.000880,acc=0.919 ETA 06:40:15
[TRAIN] epoch=19, batch_id=236, loss=0.266685, lr=0.000884,acc=0.919 ETA 06:32:30
[TRAIN] epoch=19, batch_id=246, loss=0.263462, lr=0.000887,acc=0.920 ETA 06:53:48
[TRAIN] epoch=19, batch_id=256, loss=0.263650, lr=0.000890,acc=0.920 ETA 06:38:58
[TRAIN] epoch=19, batch_id=266, loss=0.260501, lr=0.000894,acc=0.921 ETA 07:17:09
[TRAIN] epoch=19, batch_id=276, loss=0.261750, lr=0.000897,acc=0.920 ETA 06:37:38
[TRAIN] epoch=19, batch_id=286, loss=0.259785, lr=0.000900,acc=0.921 ETA 08:14:44
[TRAIN] epoch=19, batch_id=296, loss=0.264138, lr=0.000903,acc=0.920 ETA 06:32:33
[EVAL] epoch=19

Evaluating top_k_accuracy ...

top1_acc	0.7626
top5_acc	0.9426

Evaluating mean_class_accuracy ...

mean_acc	0.7637
[TRAIN] epoch=20, batch_id=8, loss=0.206808, lr=0.000906,acc=0.922 ETA 97:12:27
[TRAIN] epoch=20, batch_id=18, loss=0.234353, lr=0.000909,acc=0.920 ETA 06:48:04
[TRAIN] epoch=20, batch_id=28, loss=0.250796, lr=0.000912,acc=0.920 ETA 06:37:03
[TRAIN] epoch=20, batch_id=38, loss=0.255537, lr=0.000915,acc=0.920 ETA 06:30:03
[TRAIN] epoch=20, batch_id=48, loss=0.253489, lr=0.000918,acc=0.921 ETA 08:01:56
[TRAIN] epoch=20, batch_id=58, loss=0.252870, lr=0.000921,acc=0.921 ETA 07:01:25
[TRAIN] epoch=20, batch_id=68, loss=0.251301, lr=0.000924,acc=0.922 ETA 07:34:30
[TRAIN] epoch=20, batch_id=78, loss=0.265661, lr=0.000927,acc=0.918 ETA 06:38:14
[TRAIN] epoch=20, batch_id=88, loss=0.257858, lr=0.000929,acc=0.919 ETA 07:30:41
[TRAIN] epoch=20, batch_id=98, loss=0.251846, lr=0.000932,acc=0.922 ETA 06:44:51
[TRAIN] epoch=20, batch_id=108, loss=0.256343, lr=0.000935,acc=0.920 ETA 08:07:37
[TRAIN] epoch=20, batch_id=118, loss=0.257903, lr=0.000937,acc=0.919 ETA 16:54:15
[TRAIN] epoch=20, batch_id=128, loss=0.253746, lr=0.000940,acc=0.921 ETA 07:58:20
[TRAIN] epoch=20, batch_id=138, loss=0.253185, lr=0.000942,acc=0.921 ETA 06:38:22
[TRAIN] epoch=20, batch_id=148, loss=0.254619, lr=0.000945,acc=0.920 ETA 06:37:40
[TRAIN] epoch=20, batch_id=158, loss=0.254344, lr=0.000947,acc=0.920 ETA 06:35:26
[TRAIN] epoch=20, batch_id=168, loss=0.249719, lr=0.000949,acc=0.922 ETA 06:36:06
[TRAIN] epoch=20, batch_id=178, loss=0.249624, lr=0.000952,acc=0.923 ETA 07:06:21
[TRAIN] epoch=20, batch_id=188, loss=0.247183, lr=0.000954,acc=0.924 ETA 08:16:44
[TRAIN] epoch=20, batch_id=198, loss=0.247478, lr=0.000956,acc=0.922 ETA 06:41:47
[TRAIN] epoch=20, batch_id=208, loss=0.251945, lr=0.000958,acc=0.921 ETA 06:39:09
[TRAIN] epoch=20, batch_id=218, loss=0.255283, lr=0.000960,acc=0.920 ETA 06:32:47
[TRAIN] epoch=20, batch_id=228, loss=0.257109, lr=0.000962,acc=0.919 ETA 06:25:02
[TRAIN] epoch=20, batch_id=238, loss=0.257837, lr=0.000964,acc=0.919 ETA 06:27:09
[TRAIN] epoch=20, batch_id=248, loss=0.257210, lr=0.000966,acc=0.919 ETA 06:27:14
[TRAIN] epoch=20, batch_id=258, loss=0.255608, lr=0.000968,acc=0.920 ETA 07:44:44
[TRAIN] epoch=20, batch_id=268, loss=0.255888, lr=0.000970,acc=0.920 ETA 07:16:52
[TRAIN] epoch=20, batch_id=278, loss=0.257873, lr=0.000972,acc=0.919 ETA 06:37:46
[TRAIN] epoch=20, batch_id=288, loss=0.253970, lr=0.000974,acc=0.920 ETA 06:37:11
[TRAIN] epoch=20, batch_id=298, loss=0.252213, lr=0.000975,acc=0.921 ETA 06:33:06
[EVAL] epoch=20

Evaluating top_k_accuracy ...

top1_acc	0.7713
top5_acc	0.9418

Evaluating mean_class_accuracy ...

mean_acc	0.7713
[TRAIN] epoch=21, batch_id=10, loss=0.214578, lr=0.000977,acc=0.944 ETA 99:03:16
[TRAIN] epoch=21, batch_id=20, loss=0.225195, lr=0.000978,acc=0.936 ETA 07:34:43
[TRAIN] epoch=21, batch_id=30, loss=0.201169, lr=0.000980,acc=0.943 ETA 06:27:55
[TRAIN] epoch=21, batch_id=40, loss=0.206890, lr=0.000981,acc=0.941 ETA 06:32:36
[TRAIN] epoch=21, batch_id=50, loss=0.212969, lr=0.000983,acc=0.938 ETA 08:05:46
[TRAIN] epoch=21, batch_id=60, loss=0.215872, lr=0.000984,acc=0.939 ETA 06:30:44
[TRAIN] epoch=21, batch_id=70, loss=0.216684, lr=0.000985,acc=0.937 ETA 06:41:03
[TRAIN] epoch=21, batch_id=80, loss=0.222474, lr=0.000987,acc=0.932 ETA 06:32:56
[TRAIN] epoch=21, batch_id=90, loss=0.222331, lr=0.000988,acc=0.932 ETA 06:56:02
[TRAIN] epoch=21, batch_id=100, loss=0.224717, lr=0.000989,acc=0.931 ETA 06:38:31
[TRAIN] epoch=21, batch_id=110, loss=0.221067, lr=0.000990,acc=0.931 ETA 06:30:57
[TRAIN] epoch=21, batch_id=120, loss=0.222516, lr=0.000991,acc=0.930 ETA 06:35:27
[TRAIN] epoch=21, batch_id=130, loss=0.221794, lr=0.000992,acc=0.930 ETA 08:40:47
[TRAIN] epoch=21, batch_id=140, loss=0.221037, lr=0.000993,acc=0.930 ETA 07:22:18
[TRAIN] epoch=21, batch_id=150, loss=0.222582, lr=0.000994,acc=0.931 ETA 06:42:05
[TRAIN] epoch=21, batch_id=160, loss=0.220718, lr=0.000995,acc=0.931 ETA 06:31:08
[TRAIN] epoch=21, batch_id=170, loss=0.228991, lr=0.000995,acc=0.928 ETA 09:08:38
[TRAIN] epoch=21, batch_id=180, loss=0.229311, lr=0.000996,acc=0.929 ETA 09:42:28
[TRAIN] epoch=21, batch_id=190, loss=0.228032, lr=0.000997,acc=0.929 ETA 06:50:58
[TRAIN] epoch=21, batch_id=200, loss=0.228764, lr=0.000997,acc=0.929 ETA 06:54:33
[TRAIN] epoch=21, batch_id=210, loss=0.227579, lr=0.000998,acc=0.929 ETA 07:18:52
[TRAIN] epoch=21, batch_id=220, loss=0.225867, lr=0.000998,acc=0.930 ETA 06:40:06
[TRAIN] epoch=21, batch_id=230, loss=0.225564, lr=0.000999,acc=0.930 ETA 06:44:26
[TRAIN] epoch=21, batch_id=240, loss=0.224819, lr=0.000999,acc=0.931 ETA 06:33:27
[TRAIN] epoch=21, batch_id=250, loss=0.220708, lr=0.000999,acc=0.932 ETA 09:30:19
[TRAIN] epoch=21, batch_id=260, loss=0.221907, lr=0.001000,acc=0.932 ETA 11:06:01
[TRAIN] epoch=21, batch_id=270, loss=0.222008, lr=0.001000,acc=0.932 ETA 06:25:01
[TRAIN] epoch=21, batch_id=280, loss=0.218210, lr=0.001000,acc=0.933 ETA 06:25:51
[TRAIN] epoch=21, batch_id=290, loss=0.220747, lr=0.001000,acc=0.933 ETA 06:18:14
[EVAL] epoch=21

Evaluating top_k_accuracy ...

top1_acc	0.7687
top5_acc	0.9508

Evaluating mean_class_accuracy ...

mean_acc	0.7689
[TRAIN] epoch=22, batch_id=2, loss=0.158926, lr=0.001000,acc=0.938 ETA 96:36:03
[TRAIN] epoch=22, batch_id=12, loss=0.197735, lr=0.001000,acc=0.951 ETA 06:45:21
[TRAIN] epoch=22, batch_id=22, loss=0.254828, lr=0.001000,acc=0.922 ETA 09:20:14
[TRAIN] epoch=22, batch_id=32, loss=0.230623, lr=0.001000,acc=0.928 ETA 11:31:33
[TRAIN] epoch=22, batch_id=42, loss=0.216872, lr=0.001000,acc=0.932 ETA 06:42:28
[TRAIN] epoch=22, batch_id=52, loss=0.219011, lr=0.000999,acc=0.931 ETA 06:37:22
[TRAIN] epoch=22, batch_id=62, loss=0.214754, lr=0.000999,acc=0.932 ETA 06:30:35
[TRAIN] epoch=22, batch_id=72, loss=0.217218, lr=0.000999,acc=0.934 ETA 06:23:28
[TRAIN] epoch=22, batch_id=82, loss=0.222175, lr=0.000998,acc=0.932 ETA 06:26:35
[TRAIN] epoch=22, batch_id=92, loss=0.218123, lr=0.000998,acc=0.933 ETA 06:43:05
[TRAIN] epoch=22, batch_id=102, loss=0.210286, lr=0.000997,acc=0.937 ETA 06:49:48
[TRAIN] epoch=22, batch_id=112, loss=0.211797, lr=0.000997,acc=0.937 ETA 06:55:44
[TRAIN] epoch=22, batch_id=122, loss=0.215008, lr=0.000996,acc=0.936 ETA 08:55:26
[TRAIN] epoch=22, batch_id=132, loss=0.216055, lr=0.000995,acc=0.935 ETA 07:45:25
[TRAIN] epoch=22, batch_id=142, loss=0.214650, lr=0.000995,acc=0.935 ETA 06:42:30
[TRAIN] epoch=22, batch_id=152, loss=0.214062, lr=0.000994,acc=0.936 ETA 06:34:52
[TRAIN] epoch=22, batch_id=162, loss=0.212959, lr=0.000993,acc=0.936 ETA 07:15:22
[TRAIN] epoch=22, batch_id=172, loss=0.214573, lr=0.000992,acc=0.935 ETA 06:33:41
[TRAIN] epoch=22, batch_id=182, loss=0.215358, lr=0.000991,acc=0.935 ETA 08:20:56
[TRAIN] epoch=22, batch_id=192, loss=0.213629, lr=0.000990,acc=0.935 ETA 07:48:36
[TRAIN] epoch=22, batch_id=202, loss=0.210171, lr=0.000989,acc=0.936 ETA 06:51:49
[TRAIN] epoch=22, batch_id=212, loss=0.210449, lr=0.000988,acc=0.935 ETA 06:38:11
[TRAIN] epoch=22, batch_id=222, loss=0.212145, lr=0.000987,acc=0.936 ETA 06:34:04
[TRAIN] epoch=22, batch_id=232, loss=0.213474, lr=0.000985,acc=0.935 ETA 06:27:27
[TRAIN] epoch=22, batch_id=242, loss=0.212488, lr=0.000984,acc=0.935 ETA 07:15:43
[TRAIN] epoch=22, batch_id=252, loss=0.213719, lr=0.000983,acc=0.935 ETA 07:07:04
[TRAIN] epoch=22, batch_id=262, loss=0.214428, lr=0.000981,acc=0.935 ETA 06:59:08
[TRAIN] epoch=22, batch_id=272, loss=0.212208, lr=0.000980,acc=0.935 ETA 07:29:15
[TRAIN] epoch=22, batch_id=282, loss=0.210646, lr=0.000978,acc=0.935 ETA 06:25:07
[TRAIN] epoch=22, batch_id=292, loss=0.207597, lr=0.000977,acc=0.936 ETA 06:27:42
[EVAL] epoch=22

Evaluating top_k_accuracy ...

top1_acc	0.7743
top5_acc	0.9426

Evaluating mean_class_accuracy ...

mean_acc	0.7733
[TRAIN] epoch=23, batch_id=4, loss=0.187292, lr=0.000975,acc=0.930 ETA 93:59:36
[TRAIN] epoch=23, batch_id=14, loss=0.184298, lr=0.000974,acc=0.946 ETA 06:18:23
[TRAIN] epoch=23, batch_id=24, loss=0.168246, lr=0.000972,acc=0.949 ETA 06:17:34
[TRAIN] epoch=23, batch_id=34, loss=0.170755, lr=0.000970,acc=0.947 ETA 06:15:12
[TRAIN] epoch=23, batch_id=44, loss=0.172888, lr=0.000968,acc=0.946 ETA 09:27:40
[TRAIN] epoch=23, batch_id=54, loss=0.175795, lr=0.000966,acc=0.946 ETA 06:53:20
[TRAIN] epoch=23, batch_id=64, loss=0.163407, lr=0.000964,acc=0.949 ETA 06:41:24
[TRAIN] epoch=23, batch_id=74, loss=0.159621, lr=0.000962,acc=0.951 ETA 06:52:44
[TRAIN] epoch=23, batch_id=84, loss=0.165504, lr=0.000960,acc=0.949 ETA 06:30:49
[TRAIN] epoch=23, batch_id=94, loss=0.166646, lr=0.000958,acc=0.949 ETA 06:28:10
[TRAIN] epoch=23, batch_id=104, loss=0.164146, lr=0.000956,acc=0.950 ETA 07:01:54
[TRAIN] epoch=23, batch_id=114, loss=0.164500, lr=0.000954,acc=0.949 ETA 06:22:28
[TRAIN] epoch=23, batch_id=124, loss=0.169447, lr=0.000952,acc=0.946 ETA 06:31:40
[TRAIN] epoch=23, batch_id=134, loss=0.170176, lr=0.000949,acc=0.946 ETA 07:04:36
[TRAIN] epoch=23, batch_id=144, loss=0.170423, lr=0.000947,acc=0.946 ETA 06:39:26
[TRAIN] epoch=23, batch_id=154, loss=0.169556, lr=0.000945,acc=0.946 ETA 06:56:40
[TRAIN] epoch=23, batch_id=164, loss=0.169485, lr=0.000942,acc=0.946 ETA 07:19:55
[TRAIN] epoch=23, batch_id=174, loss=0.176368, lr=0.000940,acc=0.944 ETA 06:23:33
[TRAIN] epoch=23, batch_id=184, loss=0.179050, lr=0.000937,acc=0.944 ETA 09:18:41
[TRAIN] epoch=23, batch_id=194, loss=0.181982, lr=0.000935,acc=0.944 ETA 09:14:12
[TRAIN] epoch=23, batch_id=204, loss=0.178681, lr=0.000932,acc=0.945 ETA 06:22:20
[TRAIN] epoch=23, batch_id=214, loss=0.179351, lr=0.000929,acc=0.945 ETA 06:21:49
[TRAIN] epoch=23, batch_id=224, loss=0.180778, lr=0.000927,acc=0.944 ETA 06:23:32
[TRAIN] epoch=23, batch_id=234, loss=0.183368, lr=0.000924,acc=0.942 ETA 06:29:01
[TRAIN] epoch=23, batch_id=244, loss=0.182419, lr=0.000921,acc=0.943 ETA 08:03:26
[TRAIN] epoch=23, batch_id=254, loss=0.182382, lr=0.000918,acc=0.943 ETA 06:25:49
[TRAIN] epoch=23, batch_id=264, loss=0.185386, lr=0.000915,acc=0.942 ETA 06:21:03
[TRAIN] epoch=23, batch_id=274, loss=0.185389, lr=0.000912,acc=0.942 ETA 06:18:46
[TRAIN] epoch=23, batch_id=284, loss=0.186570, lr=0.000909,acc=0.941 ETA 06:15:15
[TRAIN] epoch=23, batch_id=294, loss=0.185803, lr=0.000906,acc=0.941 ETA 06:13:36
[EVAL] epoch=23

Evaluating top_k_accuracy ...

top1_acc	0.7780
top5_acc	0.9477

Evaluating mean_class_accuracy ...

mean_acc	0.7756
[TRAIN] epoch=24, batch_id=6, loss=0.136942, lr=0.000903,acc=0.958 ETA 94:28:26
[TRAIN] epoch=24, batch_id=16, loss=0.151347, lr=0.000900,acc=0.947 ETA 06:35:21
[TRAIN] epoch=24, batch_id=26, loss=0.145004, lr=0.000897,acc=0.954 ETA 06:28:51
[TRAIN] epoch=24, batch_id=36, loss=0.148963, lr=0.000894,acc=0.951 ETA 06:33:24
[TRAIN] epoch=24, batch_id=46, loss=0.154384, lr=0.000890,acc=0.952 ETA 06:22:52
[TRAIN] epoch=24, batch_id=56, loss=0.158993, lr=0.000887,acc=0.951 ETA 06:27:39
[TRAIN] epoch=24, batch_id=66, loss=0.153428, lr=0.000884,acc=0.954 ETA 06:30:33
[TRAIN] epoch=24, batch_id=76, loss=0.155390, lr=0.000880,acc=0.950 ETA 06:25:11
[TRAIN] epoch=24, batch_id=86, loss=0.161516, lr=0.000877,acc=0.949 ETA 07:14:52
[TRAIN] epoch=24, batch_id=96, loss=0.164150, lr=0.000873,acc=0.949 ETA 08:42:54
[TRAIN] epoch=24, batch_id=106, loss=0.163657, lr=0.000870,acc=0.949 ETA 07:52:41
[TRAIN] epoch=24, batch_id=116, loss=0.163412, lr=0.000866,acc=0.950 ETA 06:32:41
[TRAIN] epoch=24, batch_id=126, loss=0.161380, lr=0.000863,acc=0.951 ETA 08:14:36
[TRAIN] epoch=24, batch_id=136, loss=0.162039, lr=0.000859,acc=0.949 ETA 06:21:49
[TRAIN] epoch=24, batch_id=146, loss=0.162750, lr=0.000855,acc=0.950 ETA 09:30:38
[TRAIN] epoch=24, batch_id=156, loss=0.166855, lr=0.000852,acc=0.949 ETA 07:27:16
[TRAIN] epoch=24, batch_id=166, loss=0.163757, lr=0.000848,acc=0.950 ETA 07:25:24
[TRAIN] epoch=24, batch_id=176, loss=0.162123, lr=0.000844,acc=0.951 ETA 06:36:22
[TRAIN] epoch=24, batch_id=186, loss=0.162109, lr=0.000840,acc=0.951 ETA 06:16:19
[TRAIN] epoch=24, batch_id=196, loss=0.160552, lr=0.000836,acc=0.951 ETA 06:25:40
[TRAIN] epoch=24, batch_id=206, loss=0.161810, lr=0.000832,acc=0.951 ETA 06:18:59
[TRAIN] epoch=24, batch_id=216, loss=0.160484, lr=0.000829,acc=0.952 ETA 07:20:13
[TRAIN] epoch=24, batch_id=226, loss=0.158668, lr=0.000825,acc=0.952 ETA 06:42:45
[TRAIN] epoch=24, batch_id=236, loss=0.159277, lr=0.000820,acc=0.952 ETA 06:30:07
[TRAIN] epoch=24, batch_id=246, loss=0.160024, lr=0.000816,acc=0.952 ETA 06:29:08
[TRAIN] epoch=24, batch_id=256, loss=0.160377, lr=0.000812,acc=0.952 ETA 06:32:03
[TRAIN] epoch=24, batch_id=266, loss=0.160485, lr=0.000808,acc=0.952 ETA 09:36:42
[TRAIN] epoch=24, batch_id=276, loss=0.161814, lr=0.000804,acc=0.952 ETA 08:33:21
[TRAIN] epoch=24, batch_id=286, loss=0.160946, lr=0.000800,acc=0.952 ETA 06:42:59
[TRAIN] epoch=24, batch_id=296, loss=0.161919, lr=0.000796,acc=0.952 ETA 07:12:17
[EVAL] epoch=24

Evaluating top_k_accuracy ...

top1_acc	0.7811
top5_acc	0.9437

Evaluating mean_class_accuracy ...

mean_acc	0.7805
Save best model
[TRAIN] epoch=25, batch_id=8, loss=0.152026, lr=0.000791,acc=0.941 ETA 92:31:09
[TRAIN] epoch=25, batch_id=18, loss=0.128497, lr=0.000787,acc=0.953 ETA 06:25:33
[TRAIN] epoch=25, batch_id=28, loss=0.137082, lr=0.000783,acc=0.954 ETA 06:25:31
[TRAIN] epoch=25, batch_id=38, loss=0.129432, lr=0.000778,acc=0.957 ETA 06:39:27
[TRAIN] epoch=25, batch_id=48, loss=0.140683, lr=0.000774,acc=0.953 ETA 06:59:22
[TRAIN] epoch=25, batch_id=58, loss=0.141955, lr=0.000770,acc=0.955 ETA 06:44:05
[TRAIN] epoch=25, batch_id=68, loss=0.137038, lr=0.000765,acc=0.956 ETA 06:49:53
[TRAIN] epoch=25, batch_id=78, loss=0.133437, lr=0.000761,acc=0.959 ETA 06:45:26
[TRAIN] epoch=25, batch_id=88, loss=0.129000, lr=0.000756,acc=0.960 ETA 06:11:05
[TRAIN] epoch=25, batch_id=98, loss=0.126170, lr=0.000752,acc=0.962 ETA 06:06:22
[TRAIN] epoch=25, batch_id=108, loss=0.127224, lr=0.000747,acc=0.962 ETA 06:16:37
[TRAIN] epoch=25, batch_id=118, loss=0.131691, lr=0.000742,acc=0.961 ETA 06:14:34
[TRAIN] epoch=25, batch_id=128, loss=0.134629, lr=0.000738,acc=0.959 ETA 06:11:59
[TRAIN] epoch=25, batch_id=138, loss=0.134181, lr=0.000733,acc=0.959 ETA 06:09:27
[TRAIN] epoch=25, batch_id=148, loss=0.135750, lr=0.000728,acc=0.958 ETA 06:48:43
[TRAIN] epoch=25, batch_id=158, loss=0.132848, lr=0.000724,acc=0.959 ETA 06:10:46
[TRAIN] epoch=25, batch_id=168, loss=0.133853, lr=0.000719,acc=0.959 ETA 06:14:33
[TRAIN] epoch=25, batch_id=178, loss=0.134229, lr=0.000714,acc=0.959 ETA 06:17:29
[TRAIN] epoch=25, batch_id=188, loss=0.132229, lr=0.000709,acc=0.959 ETA 06:34:51
[TRAIN] epoch=25, batch_id=198, loss=0.132545, lr=0.000705,acc=0.960 ETA 06:13:21
[TRAIN] epoch=25, batch_id=208, loss=0.132882, lr=0.000700,acc=0.959 ETA 06:14:53
[TRAIN] epoch=25, batch_id=218, loss=0.133581, lr=0.000695,acc=0.959 ETA 06:11:34
[TRAIN] epoch=25, batch_id=228, loss=0.134216, lr=0.000690,acc=0.959 ETA 06:13:36
[TRAIN] epoch=25, batch_id=238, loss=0.135754, lr=0.000685,acc=0.959 ETA 06:18:42
[TRAIN] epoch=25, batch_id=248, loss=0.136743, lr=0.000680,acc=0.958 ETA 06:07:58
[TRAIN] epoch=25, batch_id=258, loss=0.135438, lr=0.000675,acc=0.958 ETA 06:15:54
[TRAIN] epoch=25, batch_id=268, loss=0.137743, lr=0.000670,acc=0.958 ETA 06:31:49
[TRAIN] epoch=25, batch_id=278, loss=0.136694, lr=0.000665,acc=0.958 ETA 06:15:12
[TRAIN] epoch=25, batch_id=288, loss=0.136366, lr=0.000661,acc=0.959 ETA 06:17:32
[TRAIN] epoch=25, batch_id=298, loss=0.135258, lr=0.000656,acc=0.959 ETA 06:17:02
[EVAL] epoch=25

Evaluating top_k_accuracy ...

top1_acc	0.7822
top5_acc	0.9429

Evaluating mean_class_accuracy ...

mean_acc	0.7820
Save best model
[TRAIN] epoch=26, batch_id=10, loss=0.119726, lr=0.000650,acc=0.969 ETA 90:43:15
[TRAIN] epoch=26, batch_id=20, loss=0.129000, lr=0.000645,acc=0.964 ETA 06:22:42
[TRAIN] epoch=26, batch_id=30, loss=0.123814, lr=0.000640,acc=0.965 ETA 07:14:03
[TRAIN] epoch=26, batch_id=40, loss=0.125377, lr=0.000635,acc=0.963 ETA 06:20:08
[TRAIN] epoch=26, batch_id=50, loss=0.119553, lr=0.000630,acc=0.964 ETA 06:14:12
[TRAIN] epoch=26, batch_id=60, loss=0.115806, lr=0.000625,acc=0.966 ETA 06:18:33
[TRAIN] epoch=26, batch_id=70, loss=0.114581, lr=0.000620,acc=0.966 ETA 06:22:19
[TRAIN] epoch=26, batch_id=80, loss=0.113285, lr=0.000615,acc=0.965 ETA 06:08:12
[TRAIN] epoch=26, batch_id=90, loss=0.117001, lr=0.000610,acc=0.964 ETA 06:22:43
[TRAIN] epoch=26, batch_id=100, loss=0.114434, lr=0.000605,acc=0.965 ETA 05:58:30
[TRAIN] epoch=26, batch_id=110, loss=0.117015, lr=0.000599,acc=0.964 ETA 06:41:05
[TRAIN] epoch=26, batch_id=120, loss=0.114589, lr=0.000594,acc=0.965 ETA 06:08:29
[TRAIN] epoch=26, batch_id=130, loss=0.115939, lr=0.000589,acc=0.964 ETA 06:26:19
[TRAIN] epoch=26, batch_id=140, loss=0.117108, lr=0.000584,acc=0.964 ETA 06:03:08
[TRAIN] epoch=26, batch_id=150, loss=0.115066, lr=0.000579,acc=0.965 ETA 06:08:52
[TRAIN] epoch=26, batch_id=160, loss=0.116779, lr=0.000574,acc=0.964 ETA 05:56:16
[TRAIN] epoch=26, batch_id=170, loss=0.115995, lr=0.000568,acc=0.965 ETA 06:03:55
[TRAIN] epoch=26, batch_id=180, loss=0.116489, lr=0.000563,acc=0.965 ETA 06:10:23
[TRAIN] epoch=26, batch_id=190, loss=0.118837, lr=0.000558,acc=0.963 ETA 06:15:09
[TRAIN] epoch=26, batch_id=200, loss=0.119303, lr=0.000553,acc=0.963 ETA 06:20:53
[TRAIN] epoch=26, batch_id=210, loss=0.119008, lr=0.000547,acc=0.963 ETA 06:11:01
[TRAIN] epoch=26, batch_id=220, loss=0.118718, lr=0.000542,acc=0.963 ETA 06:24:32
[TRAIN] epoch=26, batch_id=230, loss=0.117978, lr=0.000537,acc=0.963 ETA 06:31:26
[TRAIN] epoch=26, batch_id=240, loss=0.119456, lr=0.000532,acc=0.963 ETA 06:30:51
[TRAIN] epoch=26, batch_id=250, loss=0.119396, lr=0.000526,acc=0.963 ETA 07:02:16
[TRAIN] epoch=26, batch_id=260, loss=0.117341, lr=0.000521,acc=0.963 ETA 08:13:17
[TRAIN] epoch=26, batch_id=270, loss=0.115362, lr=0.000516,acc=0.964 ETA 07:01:34
[TRAIN] epoch=26, batch_id=280, loss=0.114582, lr=0.000511,acc=0.964 ETA 12:06:33
[TRAIN] epoch=26, batch_id=290, loss=0.114035, lr=0.000505,acc=0.964 ETA 07:11:57
[EVAL] epoch=26

Evaluating top_k_accuracy ...

top1_acc	0.7790
top5_acc	0.9411

Evaluating mean_class_accuracy ...

mean_acc	0.7790
[TRAIN] epoch=27, batch_id=2, loss=0.155435, lr=0.000500,acc=0.938 ETA 92:04:40
[TRAIN] epoch=27, batch_id=12, loss=0.171790, lr=0.000495,acc=0.951 ETA 06:34:46
[TRAIN] epoch=27, batch_id=22, loss=0.153113, lr=0.000489,acc=0.953 ETA 06:04:50
[TRAIN] epoch=27, batch_id=32, loss=0.142271, lr=0.000484,acc=0.955 ETA 06:00:15
[TRAIN] epoch=27, batch_id=42, loss=0.144317, lr=0.000479,acc=0.952 ETA 06:05:41
[TRAIN] epoch=27, batch_id=52, loss=0.140852, lr=0.000474,acc=0.954 ETA 05:59:12
[TRAIN] epoch=27, batch_id=62, loss=0.141968, lr=0.000468,acc=0.953 ETA 06:28:53
[TRAIN] epoch=27, batch_id=72, loss=0.137541, lr=0.000463,acc=0.955 ETA 07:15:47
[TRAIN] epoch=27, batch_id=82, loss=0.138497, lr=0.000458,acc=0.955 ETA 05:57:42
[TRAIN] epoch=27, batch_id=92, loss=0.135475, lr=0.000453,acc=0.958 ETA 06:03:40
[TRAIN] epoch=27, batch_id=102, loss=0.133943, lr=0.000447,acc=0.959 ETA 05:58:54
[TRAIN] epoch=27, batch_id=112, loss=0.134192, lr=0.000442,acc=0.959 ETA 05:55:56
[TRAIN] epoch=27, batch_id=122, loss=0.131880, lr=0.000437,acc=0.960 ETA 05:57:47
[TRAIN] epoch=27, batch_id=132, loss=0.132162, lr=0.000432,acc=0.960 ETA 06:04:18
[TRAIN] epoch=27, batch_id=142, loss=0.133549, lr=0.000426,acc=0.959 ETA 05:57:16
[TRAIN] epoch=27, batch_id=152, loss=0.135092, lr=0.000421,acc=0.959 ETA 06:05:00
[TRAIN] epoch=27, batch_id=162, loss=0.133699, lr=0.000416,acc=0.959 ETA 05:56:03
[TRAIN] epoch=27, batch_id=172, loss=0.130081, lr=0.000411,acc=0.961 ETA 07:19:51
[TRAIN] epoch=27, batch_id=182, loss=0.129753, lr=0.000406,acc=0.961 ETA 05:55:14
[TRAIN] epoch=27, batch_id=192, loss=0.127423, lr=0.000401,acc=0.962 ETA 06:36:47
[TRAIN] epoch=27, batch_id=202, loss=0.125940, lr=0.000395,acc=0.962 ETA 05:57:13
[TRAIN] epoch=27, batch_id=212, loss=0.126519, lr=0.000390,acc=0.962 ETA 06:03:29
[TRAIN] epoch=27, batch_id=222, loss=0.126182, lr=0.000385,acc=0.961 ETA 05:59:07
[TRAIN] epoch=27, batch_id=232, loss=0.125440, lr=0.000380,acc=0.962 ETA 06:06:59
[TRAIN] epoch=27, batch_id=242, loss=0.125312, lr=0.000375,acc=0.962 ETA 06:03:50
[TRAIN] epoch=27, batch_id=252, loss=0.124747, lr=0.000370,acc=0.962 ETA 06:03:44
[TRAIN] epoch=27, batch_id=262, loss=0.124337, lr=0.000365,acc=0.962 ETA 06:09:08
[TRAIN] epoch=27, batch_id=272, loss=0.124679, lr=0.000360,acc=0.962 ETA 06:09:52
[TRAIN] epoch=27, batch_id=282, loss=0.124144, lr=0.000355,acc=0.962 ETA 06:03:16
[TRAIN] epoch=27, batch_id=292, loss=0.124079, lr=0.000350,acc=0.962 ETA 06:00:36
[EVAL] epoch=27

Evaluating top_k_accuracy ...

top1_acc	0.7843
top5_acc	0.9485

Evaluating mean_class_accuracy ...

mean_acc	0.7832
Save best model
[TRAIN] epoch=28, batch_id=4, loss=0.128172, lr=0.000344,acc=0.953 ETA 91:09:07
[TRAIN] epoch=28, batch_id=14, loss=0.114024, lr=0.000339,acc=0.960 ETA 06:54:19
[TRAIN] epoch=28, batch_id=24, loss=0.097324, lr=0.000335,acc=0.966 ETA 07:03:02
[TRAIN] epoch=28, batch_id=34, loss=0.097954, lr=0.000330,acc=0.969 ETA 06:44:31
[TRAIN] epoch=28, batch_id=44, loss=0.105728, lr=0.000325,acc=0.965 ETA 06:14:54
[TRAIN] epoch=28, batch_id=54, loss=0.100035, lr=0.000320,acc=0.968 ETA 06:04:02
[TRAIN] epoch=28, batch_id=64, loss=0.102779, lr=0.000315,acc=0.966 ETA 06:25:21
[TRAIN] epoch=28, batch_id=74, loss=0.102267, lr=0.000310,acc=0.967 ETA 06:11:20
[TRAIN] epoch=28, batch_id=84, loss=0.103745, lr=0.000305,acc=0.965 ETA 06:38:55
[TRAIN] epoch=28, batch_id=94, loss=0.100630, lr=0.000300,acc=0.965 ETA 05:54:15
[TRAIN] epoch=28, batch_id=104, loss=0.098502, lr=0.000295,acc=0.966 ETA 06:36:49
[TRAIN] epoch=28, batch_id=114, loss=0.093731, lr=0.000291,acc=0.969 ETA 05:50:48
[TRAIN] epoch=28, batch_id=124, loss=0.095168, lr=0.000286,acc=0.968 ETA 06:34:15
[TRAIN] epoch=28, batch_id=134, loss=0.094853, lr=0.000281,acc=0.968 ETA 06:22:29
[TRAIN] epoch=28, batch_id=144, loss=0.095626, lr=0.000276,acc=0.968 ETA 06:40:11
[TRAIN] epoch=28, batch_id=154, loss=0.095937, lr=0.000272,acc=0.969 ETA 05:54:45
[TRAIN] epoch=28, batch_id=164, loss=0.095443, lr=0.000267,acc=0.969 ETA 06:35:26
[TRAIN] epoch=28, batch_id=174, loss=0.094785, lr=0.000262,acc=0.969 ETA 06:00:33
[TRAIN] epoch=28, batch_id=184, loss=0.095297, lr=0.000258,acc=0.969 ETA 06:22:05
[TRAIN] epoch=28, batch_id=194, loss=0.094391, lr=0.000253,acc=0.969 ETA 06:14:17
[TRAIN] epoch=28, batch_id=204, loss=0.093124, lr=0.000248,acc=0.970 ETA 06:12:44
[TRAIN] epoch=28, batch_id=214, loss=0.093019, lr=0.000244,acc=0.970 ETA 05:53:29
[TRAIN] epoch=28, batch_id=224, loss=0.091989, lr=0.000239,acc=0.970 ETA 05:55:04
[TRAIN] epoch=28, batch_id=234, loss=0.094046, lr=0.000235,acc=0.969 ETA 07:42:09
[TRAIN] epoch=28, batch_id=244, loss=0.094725, lr=0.000230,acc=0.969 ETA 06:10:56
[TRAIN] epoch=28, batch_id=254, loss=0.094990, lr=0.000226,acc=0.969 ETA 06:07:01
[TRAIN] epoch=28, batch_id=264, loss=0.094856, lr=0.000222,acc=0.969 ETA 06:28:53
[TRAIN] epoch=28, batch_id=274, loss=0.096448, lr=0.000217,acc=0.969 ETA 05:59:24
[TRAIN] epoch=28, batch_id=284, loss=0.095925, lr=0.000213,acc=0.969 ETA 05:58:06
[TRAIN] epoch=28, batch_id=294, loss=0.096752, lr=0.000209,acc=0.968 ETA 06:50:31
[EVAL] epoch=28

Evaluating top_k_accuracy ...

top1_acc	0.7896
top5_acc	0.9463

Evaluating mean_class_accuracy ...

mean_acc	0.7902
Save best model
[TRAIN] epoch=29, batch_id=6, loss=0.102034, lr=0.000204,acc=0.969 ETA 88:25:18
[TRAIN] epoch=29, batch_id=16, loss=0.076266, lr=0.000200,acc=0.980 ETA 07:58:20
[TRAIN] epoch=29, batch_id=26, loss=0.072083, lr=0.000196,acc=0.980 ETA 06:10:12
[TRAIN] epoch=29, batch_id=36, loss=0.073597, lr=0.000192,acc=0.980 ETA 06:24:21
[TRAIN] epoch=29, batch_id=46, loss=0.080116, lr=0.000188,acc=0.976 ETA 08:26:14
[TRAIN] epoch=29, batch_id=56, loss=0.084871, lr=0.000184,acc=0.974 ETA 07:09:40
[TRAIN] epoch=29, batch_id=66, loss=0.092663, lr=0.000180,acc=0.972 ETA 06:07:28
[TRAIN] epoch=29, batch_id=76, loss=0.091432, lr=0.000175,acc=0.973 ETA 06:10:19
[TRAIN] epoch=29, batch_id=86, loss=0.092212, lr=0.000171,acc=0.973 ETA 05:59:09
[TRAIN] epoch=29, batch_id=96, loss=0.090215, lr=0.000168,acc=0.974 ETA 05:56:41
[TRAIN] epoch=29, batch_id=106, loss=0.088169, lr=0.000164,acc=0.975 ETA 05:58:38
[TRAIN] epoch=29, batch_id=116, loss=0.089768, lr=0.000160,acc=0.974 ETA 05:56:00
[TRAIN] epoch=29, batch_id=126, loss=0.090564, lr=0.000156,acc=0.973 ETA 06:01:13
[TRAIN] epoch=29, batch_id=136, loss=0.089627, lr=0.000152,acc=0.974 ETA 06:09:52
[TRAIN] epoch=29, batch_id=146, loss=0.090498, lr=0.000148,acc=0.973 ETA 05:56:36
[TRAIN] epoch=29, batch_id=156, loss=0.092265, lr=0.000145,acc=0.972 ETA 05:58:24
[TRAIN] epoch=29, batch_id=166, loss=0.091439, lr=0.000141,acc=0.972 ETA 05:59:47
[TRAIN] epoch=29, batch_id=176, loss=0.091255, lr=0.000137,acc=0.972 ETA 05:51:27
[TRAIN] epoch=29, batch_id=186, loss=0.091420, lr=0.000134,acc=0.972 ETA 07:21:08
[TRAIN] epoch=29, batch_id=196, loss=0.092960, lr=0.000130,acc=0.971 ETA 06:13:27
[TRAIN] epoch=29, batch_id=206, loss=0.093457, lr=0.000127,acc=0.971 ETA 06:09:01
[TRAIN] epoch=29, batch_id=216, loss=0.092121, lr=0.000123,acc=0.971 ETA 06:06:20
[TRAIN] epoch=29, batch_id=226, loss=0.092511, lr=0.000120,acc=0.971 ETA 06:00:32
[TRAIN] epoch=29, batch_id=236, loss=0.092823, lr=0.000116,acc=0.971 ETA 06:16:05
[TRAIN] epoch=29, batch_id=246, loss=0.092459, lr=0.000113,acc=0.972 ETA 06:25:21
[TRAIN] epoch=29, batch_id=256, loss=0.090815, lr=0.000110,acc=0.972 ETA 06:25:29
[TRAIN] epoch=29, batch_id=266, loss=0.090428, lr=0.000106,acc=0.972 ETA 06:08:15
[TRAIN] epoch=29, batch_id=276, loss=0.089223, lr=0.000103,acc=0.973 ETA 05:54:02
[TRAIN] epoch=29, batch_id=286, loss=0.089066, lr=0.000100,acc=0.972 ETA 05:57:53
[TRAIN] epoch=29, batch_id=296, loss=0.089211, lr=0.000097,acc=0.972 ETA 06:03:07
[EVAL] epoch=29

Evaluating top_k_accuracy ...

top1_acc	0.7914
top5_acc	0.9469

Evaluating mean_class_accuracy ...

mean_acc	0.7905
Save best model
[TRAIN] epoch=30, batch_id=8, loss=0.067801, lr=0.000094,acc=0.973 ETA 88:19:16
[TRAIN] epoch=30, batch_id=18, loss=0.097342, lr=0.000091,acc=0.969 ETA 06:04:46
[TRAIN] epoch=30, batch_id=28, loss=0.094642, lr=0.000088,acc=0.970 ETA 05:52:51
[TRAIN] epoch=30, batch_id=38, loss=0.095882, lr=0.000085,acc=0.970 ETA 05:51:05
[TRAIN] epoch=30, batch_id=48, loss=0.096613, lr=0.000082,acc=0.971 ETA 06:11:46
[TRAIN] epoch=30, batch_id=58, loss=0.101859, lr=0.000079,acc=0.969 ETA 06:22:48
[TRAIN] epoch=30, batch_id=68, loss=0.096951, lr=0.000076,acc=0.972 ETA 06:02:18
[TRAIN] epoch=30, batch_id=78, loss=0.096805, lr=0.000073,acc=0.971 ETA 05:59:55
[TRAIN] epoch=30, batch_id=88, loss=0.097476, lr=0.000071,acc=0.971 ETA 06:24:38
[TRAIN] epoch=30, batch_id=98, loss=0.098575, lr=0.000068,acc=0.972 ETA 08:03:27
[TRAIN] epoch=30, batch_id=108, loss=0.096004, lr=0.000065,acc=0.973 ETA 05:51:05
[TRAIN] epoch=30, batch_id=118, loss=0.093291, lr=0.000063,acc=0.974 ETA 05:39:46
[TRAIN] epoch=30, batch_id=128, loss=0.095916, lr=0.000060,acc=0.973 ETA 05:48:06
[TRAIN] epoch=30, batch_id=138, loss=0.094417, lr=0.000058,acc=0.973 ETA 08:59:40
[TRAIN] epoch=30, batch_id=148, loss=0.093513, lr=0.000055,acc=0.973 ETA 08:24:21
[TRAIN] epoch=30, batch_id=158, loss=0.094875, lr=0.000053,acc=0.972 ETA 09:06:39
[TRAIN] epoch=30, batch_id=168, loss=0.095676, lr=0.000051,acc=0.972 ETA 06:38:30
[TRAIN] epoch=30, batch_id=178, loss=0.097948, lr=0.000048,acc=0.971 ETA 05:45:48
[TRAIN] epoch=30, batch_id=188, loss=0.097996, lr=0.000046,acc=0.971 ETA 06:22:26
[TRAIN] epoch=30, batch_id=198, loss=0.096275, lr=0.000044,acc=0.971 ETA 05:52:23
[TRAIN] epoch=30, batch_id=208, loss=0.097503, lr=0.000042,acc=0.971 ETA 05:54:38
[TRAIN] epoch=30, batch_id=218, loss=0.098648, lr=0.000040,acc=0.970 ETA 05:42:24
[TRAIN] epoch=30, batch_id=228, loss=0.098679, lr=0.000038,acc=0.971 ETA 05:43:45
[TRAIN] epoch=30, batch_id=238, loss=0.097344, lr=0.000036,acc=0.971 ETA 05:47:30
[TRAIN] epoch=30, batch_id=248, loss=0.097918, lr=0.000034,acc=0.971 ETA 06:21:19
[TRAIN] epoch=30, batch_id=258, loss=0.096637, lr=0.000032,acc=0.971 ETA 05:54:40
[TRAIN] epoch=30, batch_id=268, loss=0.095617, lr=0.000030,acc=0.971 ETA 06:57:14
[TRAIN] epoch=30, batch_id=278, loss=0.094319, lr=0.000028,acc=0.972 ETA 05:51:53
[TRAIN] epoch=30, batch_id=288, loss=0.093618, lr=0.000026,acc=0.972 ETA 06:20:41
[TRAIN] epoch=30, batch_id=298, loss=0.092979, lr=0.000025,acc=0.972 ETA 05:44:21
[EVAL] epoch=30

Evaluating top_k_accuracy ...

top1_acc	0.7898
top5_acc	0.9466

Evaluating mean_class_accuracy ...

mean_acc	0.7892
[TRAIN] epoch=31, batch_id=10, loss=0.080327, lr=0.000023,acc=0.975 ETA 84:16:33
[TRAIN] epoch=31, batch_id=20, loss=0.078966, lr=0.000022,acc=0.981 ETA 05:50:35
[TRAIN] epoch=31, batch_id=30, loss=0.077610, lr=0.000020,acc=0.982 ETA 05:41:15
[TRAIN] epoch=31, batch_id=40, loss=0.078462, lr=0.000019,acc=0.983 ETA 05:41:03
[TRAIN] epoch=31, batch_id=50, loss=0.080426, lr=0.000017,acc=0.981 ETA 06:21:42
[TRAIN] epoch=31, batch_id=60, loss=0.081305, lr=0.000016,acc=0.979 ETA 05:35:32
[TRAIN] epoch=31, batch_id=70, loss=0.080811, lr=0.000015,acc=0.979 ETA 07:25:53
[TRAIN] epoch=31, batch_id=80, loss=0.079098, lr=0.000013,acc=0.979 ETA 08:28:53
[TRAIN] epoch=31, batch_id=90, loss=0.080114, lr=0.000012,acc=0.978 ETA 07:00:11
[TRAIN] epoch=31, batch_id=100, loss=0.081180, lr=0.000011,acc=0.977 ETA 05:41:19
[TRAIN] epoch=31, batch_id=110, loss=0.084945, lr=0.000010,acc=0.976 ETA 05:41:40
[TRAIN] epoch=31, batch_id=120, loss=0.084774, lr=0.000009,acc=0.976 ETA 05:42:32
[TRAIN] epoch=31, batch_id=130, loss=0.084809, lr=0.000008,acc=0.975 ETA 05:44:21
[TRAIN] epoch=31, batch_id=140, loss=0.083533, lr=0.000007,acc=0.976 ETA 05:46:02
[TRAIN] epoch=31, batch_id=150, loss=0.084003, lr=0.000006,acc=0.975 ETA 05:40:37
[TRAIN] epoch=31, batch_id=160, loss=0.085763, lr=0.000005,acc=0.974 ETA 06:23:08
[TRAIN] epoch=31, batch_id=170, loss=0.085252, lr=0.000005,acc=0.975 ETA 05:45:55
[TRAIN] epoch=31, batch_id=180, loss=0.085639, lr=0.000004,acc=0.975 ETA 05:47:46
[TRAIN] epoch=31, batch_id=190, loss=0.085899, lr=0.000003,acc=0.975 ETA 05:48:40
[TRAIN] epoch=31, batch_id=200, loss=0.084832, lr=0.000003,acc=0.975 ETA 05:49:11
[TRAIN] epoch=31, batch_id=210, loss=0.084223, lr=0.000002,acc=0.975 ETA 05:46:52
[TRAIN] epoch=31, batch_id=220, loss=0.084930, lr=0.000002,acc=0.975 ETA 05:44:47
[TRAIN] epoch=31, batch_id=230, loss=0.084663, lr=0.000001,acc=0.974 ETA 05:47:16
[TRAIN] epoch=31, batch_id=240, loss=0.084904, lr=0.000001,acc=0.974 ETA 05:59:35
[TRAIN] epoch=31, batch_id=250, loss=0.084527, lr=0.000001,acc=0.974 ETA 05:40:37
[TRAIN] epoch=31, batch_id=260, loss=0.084407, lr=0.000000,acc=0.974 ETA 06:00:45
[TRAIN] epoch=31, batch_id=270, loss=0.084521, lr=0.000000,acc=0.974 ETA 05:55:18
[TRAIN] epoch=31, batch_id=280, loss=0.085291, lr=0.000000,acc=0.974 ETA 05:45:10
[TRAIN] epoch=31, batch_id=290, loss=0.086188, lr=0.000000,acc=0.974 ETA 05:43:15
[EVAL] epoch=31

Evaluating top_k_accuracy ...

top1_acc	0.7893
top5_acc	0.9458

Evaluating mean_class_accuracy ...

mean_acc	0.7889
[TRAIN] epoch=32, batch_id=2, loss=0.043603, lr=0.000000,acc=0.984 ETA 83:37:46
[TRAIN] epoch=32, batch_id=12, loss=0.066982, lr=0.000000,acc=0.984 ETA 05:44:51
[TRAIN] epoch=32, batch_id=22, loss=0.066504, lr=0.000000,acc=0.984 ETA 05:47:06
[TRAIN] epoch=32, batch_id=32, loss=0.075827, lr=0.000000,acc=0.979 ETA 07:59:06
[TRAIN] epoch=32, batch_id=42, loss=0.078623, lr=0.000000,acc=0.978 ETA 05:43:10
[TRAIN] epoch=32, batch_id=52, loss=0.082308, lr=0.000001,acc=0.974 ETA 05:35:27
[TRAIN] epoch=32, batch_id=62, loss=0.078380, lr=0.000001,acc=0.975 ETA 05:35:29
[TRAIN] epoch=32, batch_id=72, loss=0.088175, lr=0.000001,acc=0.973 ETA 05:33:53
[TRAIN] epoch=32, batch_id=82, loss=0.088426, lr=0.000002,acc=0.974 ETA 05:50:55
[TRAIN] epoch=32, batch_id=92, loss=0.093652, lr=0.000002,acc=0.971 ETA 05:44:56
[TRAIN] epoch=32, batch_id=102, loss=0.093724, lr=0.000003,acc=0.972 ETA 05:54:27
[TRAIN] epoch=32, batch_id=112, loss=0.094087, lr=0.000003,acc=0.972 ETA 05:38:30
[TRAIN] epoch=32, batch_id=122, loss=0.092581, lr=0.000004,acc=0.973 ETA 05:50:19
[TRAIN] epoch=32, batch_id=132, loss=0.089689, lr=0.000005,acc=0.974 ETA 05:40:01
[TRAIN] epoch=32, batch_id=142, loss=0.093675, lr=0.000005,acc=0.972 ETA 05:50:49
[TRAIN] epoch=32, batch_id=152, loss=0.093325, lr=0.000006,acc=0.973 ETA 05:45:11
[TRAIN] epoch=32, batch_id=162, loss=0.090589, lr=0.000007,acc=0.974 ETA 05:37:58
[TRAIN] epoch=32, batch_id=172, loss=0.091622, lr=0.000008,acc=0.972 ETA 05:35:38
[TRAIN] epoch=32, batch_id=182, loss=0.094543, lr=0.000009,acc=0.972 ETA 05:33:29
[TRAIN] epoch=32, batch_id=192, loss=0.095131, lr=0.000010,acc=0.972 ETA 06:21:10
[TRAIN] epoch=32, batch_id=202, loss=0.095095, lr=0.000011,acc=0.972 ETA 05:38:27
[TRAIN] epoch=32, batch_id=212, loss=0.096300, lr=0.000012,acc=0.972 ETA 05:44:01
[TRAIN] epoch=32, batch_id=222, loss=0.095091, lr=0.000013,acc=0.973 ETA 05:29:05
[TRAIN] epoch=32, batch_id=232, loss=0.096199, lr=0.000015,acc=0.973 ETA 05:35:24
[TRAIN] epoch=32, batch_id=242, loss=0.094266, lr=0.000016,acc=0.974 ETA 05:36:13
[TRAIN] epoch=32, batch_id=252, loss=0.094340, lr=0.000017,acc=0.974 ETA 05:39:45
[TRAIN] epoch=32, batch_id=262, loss=0.094314, lr=0.000019,acc=0.974 ETA 05:35:24
[TRAIN] epoch=32, batch_id=272, loss=0.093985, lr=0.000020,acc=0.974 ETA 05:42:42
[TRAIN] epoch=32, batch_id=282, loss=0.093486, lr=0.000022,acc=0.974 ETA 05:46:38
[TRAIN] epoch=32, batch_id=292, loss=0.093395, lr=0.000023,acc=0.974 ETA 05:39:05
[EVAL] epoch=32

Evaluating top_k_accuracy ...

top1_acc	0.7912
top5_acc	0.9455

Evaluating mean_class_accuracy ...

mean_acc	0.7905
[TRAIN] epoch=33, batch_id=4, loss=0.086794, lr=0.000025,acc=0.961 ETA 85:31:42
[TRAIN] epoch=33, batch_id=14, loss=0.077200, lr=0.000026,acc=0.971 ETA 05:28:33
[TRAIN] epoch=33, batch_id=24, loss=0.071849, lr=0.000028,acc=0.974 ETA 05:43:22
[TRAIN] epoch=33, batch_id=34, loss=0.067710, lr=0.000030,acc=0.977 ETA 05:53:34
[TRAIN] epoch=33, batch_id=44, loss=0.073676, lr=0.000032,acc=0.976 ETA 05:54:55
[TRAIN] epoch=33, batch_id=54, loss=0.074092, lr=0.000034,acc=0.977 ETA 08:10:39
[TRAIN] epoch=33, batch_id=64, loss=0.075706, lr=0.000036,acc=0.977 ETA 10:51:32
[TRAIN] epoch=33, batch_id=74, loss=0.074385, lr=0.000038,acc=0.978 ETA 05:29:21
[TRAIN] epoch=33, batch_id=84, loss=0.077336, lr=0.000040,acc=0.977 ETA 05:52:18
[TRAIN] epoch=33, batch_id=94, loss=0.082676, lr=0.000042,acc=0.974 ETA 05:26:46
[TRAIN] epoch=33, batch_id=104, loss=0.081135, lr=0.000044,acc=0.975 ETA 05:29:06
[TRAIN] epoch=33, batch_id=114, loss=0.080077, lr=0.000046,acc=0.975 ETA 05:35:36
[TRAIN] epoch=33, batch_id=124, loss=0.082379, lr=0.000048,acc=0.974 ETA 05:44:40
[TRAIN] epoch=33, batch_id=134, loss=0.081407, lr=0.000051,acc=0.974 ETA 05:30:51
[TRAIN] epoch=33, batch_id=144, loss=0.081848, lr=0.000053,acc=0.974 ETA 05:26:45
[TRAIN] epoch=33, batch_id=154, loss=0.083299, lr=0.000055,acc=0.973 ETA 05:49:26
[TRAIN] epoch=33, batch_id=164, loss=0.081984, lr=0.000058,acc=0.973 ETA 05:34:01
[TRAIN] epoch=33, batch_id=174, loss=0.080946, lr=0.000060,acc=0.974 ETA 05:28:02
[TRAIN] epoch=33, batch_id=184, loss=0.081446, lr=0.000063,acc=0.974 ETA 05:24:57
[TRAIN] epoch=33, batch_id=194, loss=0.081006, lr=0.000065,acc=0.974 ETA 06:25:13
[TRAIN] epoch=33, batch_id=204, loss=0.083436, lr=0.000068,acc=0.974 ETA 05:46:25
[TRAIN] epoch=33, batch_id=214, loss=0.084997, lr=0.000071,acc=0.974 ETA 06:23:06
[TRAIN] epoch=33, batch_id=224, loss=0.086063, lr=0.000073,acc=0.974 ETA 05:58:34
[TRAIN] epoch=33, batch_id=234, loss=0.085498, lr=0.000076,acc=0.974 ETA 05:59:01
[TRAIN] epoch=33, batch_id=244, loss=0.087233, lr=0.000079,acc=0.974 ETA 05:56:39
[TRAIN] epoch=33, batch_id=254, loss=0.086653, lr=0.000082,acc=0.974 ETA 06:17:57
[TRAIN] epoch=33, batch_id=264, loss=0.086547, lr=0.000085,acc=0.974 ETA 05:44:10
[TRAIN] epoch=33, batch_id=274, loss=0.085787, lr=0.000088,acc=0.975 ETA 05:48:02
[TRAIN] epoch=33, batch_id=284, loss=0.085743, lr=0.000091,acc=0.975 ETA 05:28:29
[TRAIN] epoch=33, batch_id=294, loss=0.085319, lr=0.000094,acc=0.975 ETA 05:30:28
[EVAL] epoch=33

Evaluating top_k_accuracy ...

top1_acc	0.7914
top5_acc	0.9466

Evaluating mean_class_accuracy ...

mean_acc	0.7907
[TRAIN] epoch=34, batch_id=6, loss=0.097432, lr=0.000097,acc=0.953 ETA 81:02:20
[TRAIN] epoch=34, batch_id=16, loss=0.090337, lr=0.000100,acc=0.971 ETA 05:38:50
[TRAIN] epoch=34, batch_id=26, loss=0.093902, lr=0.000103,acc=0.968 ETA 05:34:25
[TRAIN] epoch=34, batch_id=36, loss=0.098366, lr=0.000106,acc=0.966 ETA 05:40:53
[TRAIN] epoch=34, batch_id=46, loss=0.093642, lr=0.000110,acc=0.968 ETA 05:43:55
[TRAIN] epoch=34, batch_id=56, loss=0.095221, lr=0.000113,acc=0.968 ETA 05:40:19
[TRAIN] epoch=34, batch_id=66, loss=0.094987, lr=0.000116,acc=0.969 ETA 05:39:05
[TRAIN] epoch=34, batch_id=76, loss=0.102833, lr=0.000120,acc=0.967 ETA 05:33:02
[TRAIN] epoch=34, batch_id=86, loss=0.101588, lr=0.000123,acc=0.968 ETA 05:29:00
[TRAIN] epoch=34, batch_id=96, loss=0.103202, lr=0.000127,acc=0.967 ETA 05:36:03
[TRAIN] epoch=34, batch_id=106, loss=0.097317, lr=0.000130,acc=0.969 ETA 05:55:58
[TRAIN] epoch=34, batch_id=116, loss=0.095600, lr=0.000134,acc=0.970 ETA 05:36:06
[TRAIN] epoch=34, batch_id=126, loss=0.096093, lr=0.000137,acc=0.970 ETA 05:35:35
[TRAIN] epoch=34, batch_id=136, loss=0.096471, lr=0.000141,acc=0.970 ETA 05:37:16
[TRAIN] epoch=34, batch_id=146, loss=0.095660, lr=0.000145,acc=0.971 ETA 05:36:38
[TRAIN] epoch=34, batch_id=156, loss=0.097140, lr=0.000148,acc=0.970 ETA 05:43:51
[TRAIN] epoch=34, batch_id=166, loss=0.094812, lr=0.000152,acc=0.971 ETA 05:57:07
[TRAIN] epoch=34, batch_id=176, loss=0.097116, lr=0.000156,acc=0.971 ETA 05:50:43
[TRAIN] epoch=34, batch_id=186, loss=0.095867, lr=0.000160,acc=0.971 ETA 05:30:14
[TRAIN] epoch=34, batch_id=196, loss=0.096977, lr=0.000164,acc=0.971 ETA 05:35:14
[TRAIN] epoch=34, batch_id=206, loss=0.095994, lr=0.000168,acc=0.971 ETA 05:24:22
[TRAIN] epoch=34, batch_id=216, loss=0.094477, lr=0.000171,acc=0.972 ETA 05:51:25
[TRAIN] epoch=34, batch_id=226, loss=0.093764, lr=0.000175,acc=0.972 ETA 05:55:57
[TRAIN] epoch=34, batch_id=236, loss=0.094632, lr=0.000180,acc=0.972 ETA 05:39:03
[TRAIN] epoch=34, batch_id=246, loss=0.095478, lr=0.000184,acc=0.972 ETA 05:39:46
[TRAIN] epoch=34, batch_id=256, loss=0.093605, lr=0.000188,acc=0.972 ETA 05:38:34
[TRAIN] epoch=34, batch_id=266, loss=0.093198, lr=0.000192,acc=0.972 ETA 07:37:49
[TRAIN] epoch=34, batch_id=276, loss=0.095041, lr=0.000196,acc=0.972 ETA 06:39:45
[TRAIN] epoch=34, batch_id=286, loss=0.095760, lr=0.000200,acc=0.971 ETA 06:10:01
[TRAIN] epoch=34, batch_id=296, loss=0.095144, lr=0.000204,acc=0.971 ETA 05:48:27
[EVAL] epoch=34

Evaluating top_k_accuracy ...

top1_acc	0.7901
top5_acc	0.9485

Evaluating mean_class_accuracy ...

mean_acc	0.7895
[TRAIN] epoch=35, batch_id=8, loss=0.090953, lr=0.000209,acc=0.969 ETA 80:56:43
[TRAIN] epoch=35, batch_id=18, loss=0.083621, lr=0.000213,acc=0.972 ETA 05:29:26
[TRAIN] epoch=35, batch_id=28, loss=0.090481, lr=0.000217,acc=0.973 ETA 05:23:50
[TRAIN] epoch=35, batch_id=38, loss=0.083556, lr=0.000222,acc=0.977 ETA 05:27:16
[TRAIN] epoch=35, batch_id=48, loss=0.084165, lr=0.000226,acc=0.977 ETA 06:06:38
[TRAIN] epoch=35, batch_id=58, loss=0.084632, lr=0.000230,acc=0.977 ETA 06:19:28
[TRAIN] epoch=35, batch_id=68, loss=0.081849, lr=0.000235,acc=0.978 ETA 05:59:09
[TRAIN] epoch=35, batch_id=78, loss=0.087367, lr=0.000239,acc=0.977 ETA 06:05:39
[TRAIN] epoch=35, batch_id=88, loss=0.085388, lr=0.000244,acc=0.977 ETA 06:04:39
[TRAIN] epoch=35, batch_id=98, loss=0.082606, lr=0.000248,acc=0.978 ETA 08:28:22
[TRAIN] epoch=35, batch_id=108, loss=0.084376, lr=0.000253,acc=0.977 ETA 08:41:10
[TRAIN] epoch=35, batch_id=118, loss=0.083045, lr=0.000258,acc=0.977 ETA 05:29:15
[TRAIN] epoch=35, batch_id=128, loss=0.085307, lr=0.000262,acc=0.977 ETA 06:31:53
[TRAIN] epoch=35, batch_id=138, loss=0.085651, lr=0.000267,acc=0.975 ETA 05:20:46
[TRAIN] epoch=35, batch_id=148, loss=0.085547, lr=0.000272,acc=0.975 ETA 05:26:38
[TRAIN] epoch=35, batch_id=158, loss=0.086547, lr=0.000276,acc=0.975 ETA 05:29:37
[TRAIN] epoch=35, batch_id=168, loss=0.084251, lr=0.000281,acc=0.975 ETA 05:23:30
[TRAIN] epoch=35, batch_id=178, loss=0.084353, lr=0.000286,acc=0.975 ETA 05:19:55
[TRAIN] epoch=35, batch_id=188, loss=0.084717, lr=0.000291,acc=0.975 ETA 05:22:29
[TRAIN] epoch=35, batch_id=198, loss=0.084260, lr=0.000295,acc=0.974 ETA 05:16:44
[TRAIN] epoch=35, batch_id=208, loss=0.085089, lr=0.000300,acc=0.974 ETA 05:24:08
[TRAIN] epoch=35, batch_id=218, loss=0.084432, lr=0.000305,acc=0.975 ETA 05:18:41
[TRAIN] epoch=35, batch_id=228, loss=0.086075, lr=0.000310,acc=0.974 ETA 05:36:02
[TRAIN] epoch=35, batch_id=238, loss=0.086340, lr=0.000315,acc=0.974 ETA 05:27:26
[TRAIN] epoch=35, batch_id=248, loss=0.087165, lr=0.000320,acc=0.974 ETA 05:23:12
[TRAIN] epoch=35, batch_id=258, loss=0.088057, lr=0.000325,acc=0.974 ETA 05:15:52
[TRAIN] epoch=35, batch_id=268, loss=0.090746, lr=0.000330,acc=0.973 ETA 05:22:48
[TRAIN] epoch=35, batch_id=278, loss=0.091910, lr=0.000335,acc=0.972 ETA 05:16:06
[TRAIN] epoch=35, batch_id=288, loss=0.090631, lr=0.000339,acc=0.972 ETA 06:05:31
[TRAIN] epoch=35, batch_id=298, loss=0.090176, lr=0.000344,acc=0.973 ETA 05:24:33
[EVAL] epoch=35

Evaluating top_k_accuracy ...

top1_acc	0.7864
top5_acc	0.9474

Evaluating mean_class_accuracy ...

mean_acc	0.7862
[TRAIN] epoch=36, batch_id=10, loss=0.107312, lr=0.000350,acc=0.963 ETA 78:28:51
[TRAIN] epoch=36, batch_id=20, loss=0.106224, lr=0.000355,acc=0.966 ETA 06:11:39
[TRAIN] epoch=36, batch_id=30, loss=0.093434, lr=0.000360,acc=0.970 ETA 05:48:13
[TRAIN] epoch=36, batch_id=40, loss=0.085959, lr=0.000365,acc=0.972 ETA 06:01:22
[TRAIN] epoch=36, batch_id=50, loss=0.097261, lr=0.000370,acc=0.968 ETA 05:30:05
[TRAIN] epoch=36, batch_id=60, loss=0.090672, lr=0.000375,acc=0.971 ETA 06:13:23
[TRAIN] epoch=36, batch_id=70, loss=0.088219, lr=0.000380,acc=0.972 ETA 05:12:58
[TRAIN] epoch=36, batch_id=80, loss=0.087737, lr=0.000385,acc=0.972 ETA 07:54:37
[TRAIN] epoch=36, batch_id=90, loss=0.089616, lr=0.000390,acc=0.971 ETA 05:39:01
[TRAIN] epoch=36, batch_id=100, loss=0.091784, lr=0.000395,acc=0.971 ETA 06:30:10
[TRAIN] epoch=36, batch_id=110, loss=0.095025, lr=0.000401,acc=0.970 ETA 05:23:05
[TRAIN] epoch=36, batch_id=120, loss=0.095995, lr=0.000406,acc=0.970 ETA 05:17:42
[TRAIN] epoch=36, batch_id=130, loss=0.098903, lr=0.000411,acc=0.969 ETA 05:14:39
[TRAIN] epoch=36, batch_id=140, loss=0.098789, lr=0.000416,acc=0.969 ETA 05:18:39
[TRAIN] epoch=36, batch_id=150, loss=0.095857, lr=0.000421,acc=0.970 ETA 05:22:31
[TRAIN] epoch=36, batch_id=160, loss=0.095732, lr=0.000426,acc=0.970 ETA 05:26:26
[TRAIN] epoch=36, batch_id=170, loss=0.095589, lr=0.000432,acc=0.970 ETA 05:37:46
[TRAIN] epoch=36, batch_id=180, loss=0.093989, lr=0.000437,acc=0.970 ETA 06:59:57
[TRAIN] epoch=36, batch_id=190, loss=0.095462, lr=0.000442,acc=0.970 ETA 06:13:01
[TRAIN] epoch=36, batch_id=200, loss=0.095494, lr=0.000447,acc=0.970 ETA 06:34:59
[TRAIN] epoch=36, batch_id=210, loss=0.094498, lr=0.000453,acc=0.970 ETA 06:14:06
[TRAIN] epoch=36, batch_id=220, loss=0.094481, lr=0.000458,acc=0.970 ETA 06:10:19
[TRAIN] epoch=36, batch_id=230, loss=0.094273, lr=0.000463,acc=0.970 ETA 06:03:18
[TRAIN] epoch=36, batch_id=240, loss=0.094717, lr=0.000468,acc=0.970 ETA 06:54:53
[TRAIN] epoch=36, batch_id=250, loss=0.093746, lr=0.000474,acc=0.970 ETA 07:36:53
[TRAIN] epoch=36, batch_id=260, loss=0.094039, lr=0.000479,acc=0.970 ETA 05:20:20
[TRAIN] epoch=36, batch_id=270, loss=0.093670, lr=0.000484,acc=0.970 ETA 05:59:59
[TRAIN] epoch=36, batch_id=280, loss=0.094389, lr=0.000489,acc=0.970 ETA 05:19:47
[TRAIN] epoch=36, batch_id=290, loss=0.094654, lr=0.000495,acc=0.971 ETA 07:38:46
[EVAL] epoch=36

Evaluating top_k_accuracy ...

top1_acc	0.7856
top5_acc	0.9445

Evaluating mean_class_accuracy ...

mean_acc	0.7878
[TRAIN] epoch=37, batch_id=2, loss=0.121052, lr=0.000500,acc=0.969 ETA 83:12:45
[TRAIN] epoch=37, batch_id=12, loss=0.100183, lr=0.000505,acc=0.969 ETA 05:20:51
[TRAIN] epoch=37, batch_id=22, loss=0.088943, lr=0.000511,acc=0.972 ETA 05:24:55
[TRAIN] epoch=37, batch_id=32, loss=0.097277, lr=0.000516,acc=0.969 ETA 05:15:58
[TRAIN] epoch=37, batch_id=42, loss=0.102977, lr=0.000521,acc=0.968 ETA 05:13:04
[TRAIN] epoch=37, batch_id=52, loss=0.095104, lr=0.000526,acc=0.970 ETA 05:07:42
[TRAIN] epoch=37, batch_id=62, loss=0.095702, lr=0.000532,acc=0.970 ETA 05:10:08
[TRAIN] epoch=37, batch_id=72, loss=0.099105, lr=0.000537,acc=0.969 ETA 05:16:42
[TRAIN] epoch=37, batch_id=82, loss=0.098534, lr=0.000542,acc=0.969 ETA 05:18:04
[TRAIN] epoch=37, batch_id=92, loss=0.101557, lr=0.000547,acc=0.968 ETA 05:47:06
[TRAIN] epoch=37, batch_id=102, loss=0.099734, lr=0.000553,acc=0.968 ETA 06:09:57
[TRAIN] epoch=37, batch_id=112, loss=0.103741, lr=0.000558,acc=0.968 ETA 05:31:43
[TRAIN] epoch=37, batch_id=122, loss=0.102763, lr=0.000563,acc=0.968 ETA 05:17:10
[TRAIN] epoch=37, batch_id=132, loss=0.104381, lr=0.000568,acc=0.967 ETA 05:34:22
[TRAIN] epoch=37, batch_id=142, loss=0.104287, lr=0.000574,acc=0.967 ETA 05:33:35
[TRAIN] epoch=37, batch_id=152, loss=0.106810, lr=0.000579,acc=0.966 ETA 05:38:21
[TRAIN] epoch=37, batch_id=162, loss=0.104119, lr=0.000584,acc=0.968 ETA 05:36:48
[TRAIN] epoch=37, batch_id=172, loss=0.103235, lr=0.000589,acc=0.968 ETA 05:10:11
[TRAIN] epoch=37, batch_id=182, loss=0.104106, lr=0.000594,acc=0.968 ETA 05:14:59
[TRAIN] epoch=37, batch_id=192, loss=0.102292, lr=0.000599,acc=0.968 ETA 05:09:07
[TRAIN] epoch=37, batch_id=202, loss=0.102085, lr=0.000605,acc=0.968 ETA 05:14:36
[TRAIN] epoch=37, batch_id=212, loss=0.102832, lr=0.000610,acc=0.967 ETA 05:22:31
[TRAIN] epoch=37, batch_id=222, loss=0.100348, lr=0.000615,acc=0.968 ETA 05:13:20
[TRAIN] epoch=37, batch_id=232, loss=0.098814, lr=0.000620,acc=0.969 ETA 05:08:30
[TRAIN] epoch=37, batch_id=242, loss=0.099211, lr=0.000625,acc=0.969 ETA 05:13:13
[TRAIN] epoch=37, batch_id=252, loss=0.101043, lr=0.000630,acc=0.969 ETA 05:10:39
[TRAIN] epoch=37, batch_id=262, loss=0.101923, lr=0.000635,acc=0.969 ETA 07:49:47
[TRAIN] epoch=37, batch_id=272, loss=0.100983, lr=0.000640,acc=0.969 ETA 05:50:28
[TRAIN] epoch=37, batch_id=282, loss=0.101418, lr=0.000645,acc=0.969 ETA 05:58:19
[TRAIN] epoch=37, batch_id=292, loss=0.103041, lr=0.000650,acc=0.968 ETA 05:16:27
[EVAL] epoch=37

Evaluating top_k_accuracy ...

top1_acc	0.7830
top5_acc	0.9492

Evaluating mean_class_accuracy ...

mean_acc	0.7818
[TRAIN] epoch=38, batch_id=4, loss=0.104911, lr=0.000656,acc=0.953 ETA 75:41:17
[TRAIN] epoch=38, batch_id=14, loss=0.092491, lr=0.000661,acc=0.973 ETA 05:46:10
[TRAIN] epoch=38, batch_id=24, loss=0.091992, lr=0.000665,acc=0.975 ETA 05:06:54
[TRAIN] epoch=38, batch_id=34, loss=0.106558, lr=0.000670,acc=0.967 ETA 05:18:56
[TRAIN] epoch=38, batch_id=44, loss=0.110754, lr=0.000675,acc=0.967 ETA 05:09:56
[TRAIN] epoch=38, batch_id=54, loss=0.105487, lr=0.000680,acc=0.969 ETA 05:10:17
[TRAIN] epoch=38, batch_id=64, loss=0.100950, lr=0.000685,acc=0.971 ETA 05:04:08
[TRAIN] epoch=38, batch_id=74, loss=0.105500, lr=0.000690,acc=0.970 ETA 05:11:00
[TRAIN] epoch=38, batch_id=84, loss=0.104265, lr=0.000695,acc=0.970 ETA 05:05:20
[TRAIN] epoch=38, batch_id=94, loss=0.109526, lr=0.000700,acc=0.967 ETA 05:47:56
[TRAIN] epoch=38, batch_id=104, loss=0.107110, lr=0.000705,acc=0.968 ETA 05:11:38
[TRAIN] epoch=38, batch_id=114, loss=0.105897, lr=0.000709,acc=0.968 ETA 05:57:58
[TRAIN] epoch=38, batch_id=124, loss=0.103456, lr=0.000714,acc=0.969 ETA 05:04:21
[TRAIN] epoch=38, batch_id=134, loss=0.102954, lr=0.000719,acc=0.969 ETA 06:06:26
[TRAIN] epoch=38, batch_id=144, loss=0.101972, lr=0.000724,acc=0.969 ETA 05:00:57
[TRAIN] epoch=38, batch_id=154, loss=0.102881, lr=0.000728,acc=0.969 ETA 05:04:06
[TRAIN] epoch=38, batch_id=164, loss=0.101995, lr=0.000733,acc=0.969 ETA 05:04:59
[TRAIN] epoch=38, batch_id=174, loss=0.100820, lr=0.000738,acc=0.970 ETA 05:27:36
[TRAIN] epoch=38, batch_id=184, loss=0.101196, lr=0.000742,acc=0.970 ETA 05:05:46
[TRAIN] epoch=38, batch_id=194, loss=0.102256, lr=0.000747,acc=0.970 ETA 07:13:02
[TRAIN] epoch=38, batch_id=204, loss=0.101808, lr=0.000752,acc=0.970 ETA 05:02:31
[TRAIN] epoch=38, batch_id=214, loss=0.102661, lr=0.000756,acc=0.970 ETA 05:07:34
[TRAIN] epoch=38, batch_id=224, loss=0.102894, lr=0.000761,acc=0.970 ETA 05:06:02
[TRAIN] epoch=38, batch_id=234, loss=0.102127, lr=0.000765,acc=0.971 ETA 05:36:59
[TRAIN] epoch=38, batch_id=244, loss=0.101531, lr=0.000770,acc=0.971 ETA 05:07:44
[TRAIN] epoch=38, batch_id=254, loss=0.101751, lr=0.000774,acc=0.970 ETA 06:20:23
[TRAIN] epoch=38, batch_id=264, loss=0.101931, lr=0.000778,acc=0.971 ETA 04:59:00
[TRAIN] epoch=38, batch_id=274, loss=0.104351, lr=0.000783,acc=0.970 ETA 06:17:57
[TRAIN] epoch=38, batch_id=284, loss=0.105367, lr=0.000787,acc=0.970 ETA 05:15:50
[TRAIN] epoch=38, batch_id=294, loss=0.104323, lr=0.000791,acc=0.970 ETA 05:24:40
[EVAL] epoch=38

Evaluating top_k_accuracy ...

top1_acc	0.7777
top5_acc	0.9458

Evaluating mean_class_accuracy ...

mean_acc	0.7768
[TRAIN] epoch=39, batch_id=6, loss=0.113744, lr=0.000796,acc=0.974 ETA 76:05:37
[TRAIN] epoch=39, batch_id=16, loss=0.114749, lr=0.000800,acc=0.961 ETA 05:12:36
[TRAIN] epoch=39, batch_id=26, loss=0.107186, lr=0.000804,acc=0.965 ETA 05:14:56
[TRAIN] epoch=39, batch_id=36, loss=0.103241, lr=0.000808,acc=0.967 ETA 05:45:44
[TRAIN] epoch=39, batch_id=46, loss=0.098066, lr=0.000812,acc=0.967 ETA 05:18:53
[TRAIN] epoch=39, batch_id=56, loss=0.100996, lr=0.000816,acc=0.967 ETA 05:14:01
[TRAIN] epoch=39, batch_id=66, loss=0.098028, lr=0.000820,acc=0.969 ETA 05:13:03
[TRAIN] epoch=39, batch_id=76, loss=0.101482, lr=0.000825,acc=0.968 ETA 05:29:34
[TRAIN] epoch=39, batch_id=86, loss=0.110234, lr=0.000829,acc=0.965 ETA 05:12:44
[TRAIN] epoch=39, batch_id=96, loss=0.109784, lr=0.000832,acc=0.964 ETA 05:28:33
[TRAIN] epoch=39, batch_id=106, loss=0.112227, lr=0.000836,acc=0.964 ETA 08:30:31
[TRAIN] epoch=39, batch_id=116, loss=0.110401, lr=0.000840,acc=0.964 ETA 07:52:39
[TRAIN] epoch=39, batch_id=126, loss=0.110519, lr=0.000844,acc=0.963 ETA 08:11:08
[TRAIN] epoch=39, batch_id=136, loss=0.111436, lr=0.000848,acc=0.963 ETA 06:18:14
[TRAIN] epoch=39, batch_id=146, loss=0.110316, lr=0.000852,acc=0.964 ETA 05:40:12
[TRAIN] epoch=39, batch_id=156, loss=0.107966, lr=0.000855,acc=0.965 ETA 05:16:31
[TRAIN] epoch=39, batch_id=166, loss=0.107191, lr=0.000859,acc=0.965 ETA 05:11:55
[TRAIN] epoch=39, batch_id=176, loss=0.107864, lr=0.000863,acc=0.964 ETA 05:22:55
[TRAIN] epoch=39, batch_id=186, loss=0.107385, lr=0.000866,acc=0.965 ETA 05:05:56
[TRAIN] epoch=39, batch_id=196, loss=0.108131, lr=0.000870,acc=0.964 ETA 06:03:33
[TRAIN] epoch=39, batch_id=206, loss=0.109159, lr=0.000873,acc=0.964 ETA 05:26:07
[TRAIN] epoch=39, batch_id=216, loss=0.109888, lr=0.000877,acc=0.963 ETA 05:09:07
[TRAIN] epoch=39, batch_id=226, loss=0.111347, lr=0.000880,acc=0.963 ETA 04:57:07
[TRAIN] epoch=39, batch_id=236, loss=0.110308, lr=0.000884,acc=0.963 ETA 05:00:16
[TRAIN] epoch=39, batch_id=246, loss=0.110548, lr=0.000887,acc=0.963 ETA 04:55:45
[TRAIN] epoch=39, batch_id=256, loss=0.110176, lr=0.000890,acc=0.964 ETA 05:08:21
[TRAIN] epoch=39, batch_id=266, loss=0.109317, lr=0.000894,acc=0.964 ETA 05:07:32
[TRAIN] epoch=39, batch_id=276, loss=0.109977, lr=0.000897,acc=0.964 ETA 05:15:18
[TRAIN] epoch=39, batch_id=286, loss=0.108086, lr=0.000900,acc=0.965 ETA 05:10:57
[TRAIN] epoch=39, batch_id=296, loss=0.108521, lr=0.000903,acc=0.965 ETA 05:14:44
[EVAL] epoch=39

Evaluating top_k_accuracy ...

top1_acc	0.7846
top5_acc	0.9455

Evaluating mean_class_accuracy ...

mean_acc	0.7845
[TRAIN] epoch=40, batch_id=8, loss=0.134804, lr=0.000906,acc=0.949 ETA 74:34:38
[TRAIN] epoch=40, batch_id=18, loss=0.113125, lr=0.000909,acc=0.962 ETA 05:05:21
[TRAIN] epoch=40, batch_id=28, loss=0.111452, lr=0.000912,acc=0.958 ETA 05:07:17
[TRAIN] epoch=40, batch_id=38, loss=0.110743, lr=0.000915,acc=0.960 ETA 05:05:57
[TRAIN] epoch=40, batch_id=48, loss=0.126113, lr=0.000918,acc=0.957 ETA 05:06:20
[TRAIN] epoch=40, batch_id=58, loss=0.122223, lr=0.000921,acc=0.960 ETA 05:33:08
[TRAIN] epoch=40, batch_id=68, loss=0.118856, lr=0.000924,acc=0.961 ETA 05:00:11
[TRAIN] epoch=40, batch_id=78, loss=0.118538, lr=0.000927,acc=0.961 ETA 04:59:59
[TRAIN] epoch=40, batch_id=88, loss=0.113546, lr=0.000929,acc=0.963 ETA 04:58:33
[TRAIN] epoch=40, batch_id=98, loss=0.111276, lr=0.000932,acc=0.965 ETA 06:30:54
[TRAIN] epoch=40, batch_id=108, loss=0.113101, lr=0.000935,acc=0.965 ETA 05:22:54
[TRAIN] epoch=40, batch_id=118, loss=0.113796, lr=0.000937,acc=0.966 ETA 07:03:10
[TRAIN] epoch=40, batch_id=128, loss=0.109862, lr=0.000940,acc=0.966 ETA 05:25:49
[TRAIN] epoch=40, batch_id=138, loss=0.106677, lr=0.000942,acc=0.967 ETA 04:57:40
[TRAIN] epoch=40, batch_id=148, loss=0.110383, lr=0.000945,acc=0.966 ETA 05:38:12
[TRAIN] epoch=40, batch_id=158, loss=0.109020, lr=0.000947,acc=0.967 ETA 05:02:04
[TRAIN] epoch=40, batch_id=168, loss=0.107978, lr=0.000949,acc=0.968 ETA 05:29:33
[TRAIN] epoch=40, batch_id=178, loss=0.105137, lr=0.000952,acc=0.969 ETA 05:01:35
[TRAIN] epoch=40, batch_id=188, loss=0.104550, lr=0.000954,acc=0.969 ETA 05:26:16
[TRAIN] epoch=40, batch_id=198, loss=0.106008, lr=0.000956,acc=0.969 ETA 04:57:59
[TRAIN] epoch=40, batch_id=208, loss=0.105029, lr=0.000958,acc=0.969 ETA 04:57:25
[TRAIN] epoch=40, batch_id=218, loss=0.104515, lr=0.000960,acc=0.969 ETA 05:04:46
[TRAIN] epoch=40, batch_id=228, loss=0.103130, lr=0.000962,acc=0.969 ETA 04:54:52
[TRAIN] epoch=40, batch_id=238, loss=0.103109, lr=0.000964,acc=0.969 ETA 04:54:19
[TRAIN] epoch=40, batch_id=248, loss=0.102372, lr=0.000966,acc=0.969 ETA 05:06:45
[TRAIN] epoch=40, batch_id=258, loss=0.104402, lr=0.000968,acc=0.968 ETA 05:19:55
[TRAIN] epoch=40, batch_id=268, loss=0.102365, lr=0.000970,acc=0.969 ETA 04:56:59
[TRAIN] epoch=40, batch_id=278, loss=0.101480, lr=0.000972,acc=0.969 ETA 05:11:00
[TRAIN] epoch=40, batch_id=288, loss=0.103171, lr=0.000974,acc=0.968 ETA 05:21:43
[TRAIN] epoch=40, batch_id=298, loss=0.103125, lr=0.000975,acc=0.968 ETA 04:56:45
[EVAL] epoch=40

Evaluating top_k_accuracy ...

top1_acc	0.7827
top5_acc	0.9448

Evaluating mean_class_accuracy ...

mean_acc	0.7817
[TRAIN] epoch=41, batch_id=10, loss=0.130784, lr=0.000977,acc=0.953 ETA 73:40:32
[TRAIN] epoch=41, batch_id=20, loss=0.110213, lr=0.000978,acc=0.966 ETA 05:04:47
[TRAIN] epoch=41, batch_id=30, loss=0.108491, lr=0.000980,acc=0.963 ETA 05:19:48
[TRAIN] epoch=41, batch_id=40, loss=0.096114, lr=0.000981,acc=0.967 ETA 05:09:23
[TRAIN] epoch=41, batch_id=50, loss=0.099953, lr=0.000983,acc=0.967 ETA 05:01:58
[TRAIN] epoch=41, batch_id=60, loss=0.098530, lr=0.000984,acc=0.968 ETA 05:48:58
[TRAIN] epoch=41, batch_id=70, loss=0.093858, lr=0.000985,acc=0.970 ETA 05:05:31
[TRAIN] epoch=41, batch_id=80, loss=0.091589, lr=0.000987,acc=0.971 ETA 04:58:52
[TRAIN] epoch=41, batch_id=90, loss=0.094387, lr=0.000988,acc=0.970 ETA 04:54:53
[TRAIN] epoch=41, batch_id=100, loss=0.098711, lr=0.000989,acc=0.968 ETA 05:01:10
[TRAIN] epoch=41, batch_id=110, loss=0.096568, lr=0.000990,acc=0.970 ETA 05:00:05
[TRAIN] epoch=41, batch_id=120, loss=0.096962, lr=0.000991,acc=0.969 ETA 04:56:00
[TRAIN] epoch=41, batch_id=130, loss=0.093255, lr=0.000992,acc=0.971 ETA 05:02:58
[TRAIN] epoch=41, batch_id=140, loss=0.093314, lr=0.000993,acc=0.970 ETA 05:04:44
[TRAIN] epoch=41, batch_id=150, loss=0.093711, lr=0.000994,acc=0.970 ETA 05:33:49
[TRAIN] epoch=41, batch_id=160, loss=0.098247, lr=0.000995,acc=0.969 ETA 05:04:13
[TRAIN] epoch=41, batch_id=170, loss=0.097171, lr=0.000995,acc=0.969 ETA 04:48:33
[TRAIN] epoch=41, batch_id=180, loss=0.096706, lr=0.000996,acc=0.969 ETA 04:49:33
[TRAIN] epoch=41, batch_id=190, loss=0.095567, lr=0.000997,acc=0.970 ETA 05:52:17
[TRAIN] epoch=41, batch_id=200, loss=0.099113, lr=0.000997,acc=0.969 ETA 05:26:36
[TRAIN] epoch=41, batch_id=210, loss=0.097981, lr=0.000998,acc=0.969 ETA 05:31:47
[TRAIN] epoch=41, batch_id=220, loss=0.097436, lr=0.000998,acc=0.969 ETA 05:17:41
[TRAIN] epoch=41, batch_id=230, loss=0.099158, lr=0.000999,acc=0.969 ETA 05:00:13
[TRAIN] epoch=41, batch_id=240, loss=0.098383, lr=0.000999,acc=0.969 ETA 04:58:06
[TRAIN] epoch=41, batch_id=250, loss=0.098942, lr=0.000999,acc=0.970 ETA 05:00:27
[TRAIN] epoch=41, batch_id=260, loss=0.099628, lr=0.001000,acc=0.969 ETA 05:26:51
[TRAIN] epoch=41, batch_id=270, loss=0.098684, lr=0.001000,acc=0.969 ETA 05:25:49
[TRAIN] epoch=41, batch_id=280, loss=0.098997, lr=0.001000,acc=0.969 ETA 05:35:13
[TRAIN] epoch=41, batch_id=290, loss=0.098326, lr=0.001000,acc=0.969 ETA 06:20:41
[EVAL] epoch=41

Evaluating top_k_accuracy ...

top1_acc	0.7748
top5_acc	0.9389

Evaluating mean_class_accuracy ...

mean_acc	0.7743
[TRAIN] epoch=42, batch_id=2, loss=0.103186, lr=0.001000,acc=0.969 ETA 76:18:40
[TRAIN] epoch=42, batch_id=12, loss=0.090585, lr=0.001000,acc=0.974 ETA 05:23:36
[TRAIN] epoch=42, batch_id=22, loss=0.096556, lr=0.001000,acc=0.970 ETA 04:48:05
[TRAIN] epoch=42, batch_id=32, loss=0.105838, lr=0.001000,acc=0.967 ETA 05:00:38
[TRAIN] epoch=42, batch_id=42, loss=0.100870, lr=0.001000,acc=0.969 ETA 04:56:10
[TRAIN] epoch=42, batch_id=52, loss=0.097056, lr=0.000999,acc=0.971 ETA 07:01:54
[TRAIN] epoch=42, batch_id=62, loss=0.099628, lr=0.000999,acc=0.969 ETA 06:54:31
[TRAIN] epoch=42, batch_id=72, loss=0.096717, lr=0.000999,acc=0.970 ETA 05:24:43
[TRAIN] epoch=42, batch_id=82, loss=0.096877, lr=0.000998,acc=0.971 ETA 05:26:53
[TRAIN] epoch=42, batch_id=92, loss=0.096107, lr=0.000998,acc=0.971 ETA 05:02:41
[TRAIN] epoch=42, batch_id=102, loss=0.094576, lr=0.000997,acc=0.971 ETA 05:59:39
[TRAIN] epoch=42, batch_id=112, loss=0.095336, lr=0.000997,acc=0.970 ETA 07:17:02
[TRAIN] epoch=42, batch_id=122, loss=0.093801, lr=0.000996,acc=0.971 ETA 04:53:26
[TRAIN] epoch=42, batch_id=132, loss=0.093791, lr=0.000995,acc=0.971 ETA 05:10:57
[TRAIN] epoch=42, batch_id=142, loss=0.093993, lr=0.000995,acc=0.971 ETA 05:48:26
[TRAIN] epoch=42, batch_id=152, loss=0.095766, lr=0.000994,acc=0.970 ETA 04:41:16
[TRAIN] epoch=42, batch_id=162, loss=0.093792, lr=0.000993,acc=0.971 ETA 06:47:53
[TRAIN] epoch=42, batch_id=172, loss=0.093592, lr=0.000992,acc=0.971 ETA 10:24:59
[TRAIN] epoch=42, batch_id=182, loss=0.097072, lr=0.000991,acc=0.970 ETA 09:32:36
[TRAIN] epoch=42, batch_id=192, loss=0.097940, lr=0.000990,acc=0.970 ETA 07:01:23
[TRAIN] epoch=42, batch_id=202, loss=0.098687, lr=0.000989,acc=0.970 ETA 04:53:33
[TRAIN] epoch=42, batch_id=212, loss=0.098067, lr=0.000988,acc=0.970 ETA 05:00:15
[TRAIN] epoch=42, batch_id=222, loss=0.097051, lr=0.000987,acc=0.970 ETA 05:02:28
[TRAIN] epoch=42, batch_id=232, loss=0.096454, lr=0.000985,acc=0.970 ETA 04:47:48
[TRAIN] epoch=42, batch_id=242, loss=0.096230, lr=0.000984,acc=0.970 ETA 05:15:29
[TRAIN] epoch=42, batch_id=252, loss=0.095127, lr=0.000983,acc=0.970 ETA 04:53:10
[TRAIN] epoch=42, batch_id=262, loss=0.095431, lr=0.000981,acc=0.970 ETA 04:46:02
[TRAIN] epoch=42, batch_id=272, loss=0.095800, lr=0.000980,acc=0.970 ETA 04:47:23
[TRAIN] epoch=42, batch_id=282, loss=0.095828, lr=0.000978,acc=0.970 ETA 06:46:54
[TRAIN] epoch=42, batch_id=292, loss=0.094480, lr=0.000977,acc=0.970 ETA 06:45:39
[EVAL] epoch=42

Evaluating top_k_accuracy ...

top1_acc	0.7727
top5_acc	0.9411

Evaluating mean_class_accuracy ...

mean_acc	0.7721
[TRAIN] epoch=43, batch_id=4, loss=0.082103, lr=0.000975,acc=0.977 ETA 68:55:18
[TRAIN] epoch=43, batch_id=14, loss=0.096790, lr=0.000974,acc=0.969 ETA 05:00:12
[TRAIN] epoch=43, batch_id=24, loss=0.082173, lr=0.000972,acc=0.977 ETA 04:43:15
[TRAIN] epoch=43, batch_id=34, loss=0.085518, lr=0.000970,acc=0.974 ETA 05:02:46
[TRAIN] epoch=43, batch_id=44, loss=0.088145, lr=0.000968,acc=0.974 ETA 04:44:20
[TRAIN] epoch=43, batch_id=54, loss=0.085950, lr=0.000966,acc=0.975 ETA 04:43:17
[TRAIN] epoch=43, batch_id=64, loss=0.085355, lr=0.000964,acc=0.976 ETA 04:44:47
[TRAIN] epoch=43, batch_id=74, loss=0.083778, lr=0.000962,acc=0.976 ETA 06:57:13
[TRAIN] epoch=43, batch_id=84, loss=0.080754, lr=0.000960,acc=0.977 ETA 04:39:12
[TRAIN] epoch=43, batch_id=94, loss=0.081002, lr=0.000958,acc=0.975 ETA 04:46:20
[TRAIN] epoch=43, batch_id=104, loss=0.081543, lr=0.000956,acc=0.976 ETA 04:44:33
[TRAIN] epoch=43, batch_id=114, loss=0.084840, lr=0.000954,acc=0.975 ETA 04:41:52
[TRAIN] epoch=43, batch_id=124, loss=0.084182, lr=0.000952,acc=0.975 ETA 04:43:01
[TRAIN] epoch=43, batch_id=134, loss=0.085428, lr=0.000949,acc=0.974 ETA 04:51:24
[TRAIN] epoch=43, batch_id=144, loss=0.085139, lr=0.000947,acc=0.974 ETA 04:38:03
[TRAIN] epoch=43, batch_id=154, loss=0.083462, lr=0.000945,acc=0.974 ETA 04:43:06
[TRAIN] epoch=43, batch_id=164, loss=0.083069, lr=0.000942,acc=0.974 ETA 04:38:09
[TRAIN] epoch=43, batch_id=174, loss=0.081823, lr=0.000940,acc=0.974 ETA 04:45:27
[TRAIN] epoch=43, batch_id=184, loss=0.080711, lr=0.000937,acc=0.974 ETA 04:44:27
[TRAIN] epoch=43, batch_id=194, loss=0.079842, lr=0.000935,acc=0.975 ETA 05:48:56
[TRAIN] epoch=43, batch_id=204, loss=0.079249, lr=0.000932,acc=0.974 ETA 04:41:27
[TRAIN] epoch=43, batch_id=214, loss=0.079618, lr=0.000929,acc=0.974 ETA 05:58:27
[TRAIN] epoch=43, batch_id=224, loss=0.078477, lr=0.000927,acc=0.975 ETA 04:37:56
[TRAIN] epoch=43, batch_id=234, loss=0.078298, lr=0.000924,acc=0.975 ETA 05:53:37
[TRAIN] epoch=43, batch_id=244, loss=0.076871, lr=0.000921,acc=0.976 ETA 04:58:32
[TRAIN] epoch=43, batch_id=254, loss=0.078679, lr=0.000918,acc=0.975 ETA 05:36:02
[TRAIN] epoch=43, batch_id=264, loss=0.079003, lr=0.000915,acc=0.974 ETA 05:07:36
[TRAIN] epoch=43, batch_id=274, loss=0.078218, lr=0.000912,acc=0.974 ETA 06:33:26
[TRAIN] epoch=43, batch_id=284, loss=0.077454, lr=0.000909,acc=0.975 ETA 05:26:24
[TRAIN] epoch=43, batch_id=294, loss=0.079946, lr=0.000906,acc=0.974 ETA 05:59:36
[EVAL] epoch=43

Evaluating top_k_accuracy ...

top1_acc	0.7790
top5_acc	0.9403

Evaluating mean_class_accuracy ...

mean_acc	0.7799
[TRAIN] epoch=44, batch_id=6, loss=0.078100, lr=0.000903,acc=0.974 ETA 69:48:19
[TRAIN] epoch=44, batch_id=16, loss=0.071123, lr=0.000900,acc=0.971 ETA 05:05:23
[TRAIN] epoch=44, batch_id=26, loss=0.071954, lr=0.000897,acc=0.972 ETA 07:24:27
[TRAIN] epoch=44, batch_id=36, loss=0.084787, lr=0.000894,acc=0.971 ETA 05:08:17
[TRAIN] epoch=44, batch_id=46, loss=0.091643, lr=0.000890,acc=0.969 ETA 04:40:03
[TRAIN] epoch=44, batch_id=56, loss=0.099707, lr=0.000887,acc=0.966 ETA 04:49:12
[TRAIN] epoch=44, batch_id=66, loss=0.099673, lr=0.000884,acc=0.966 ETA 08:53:48
[TRAIN] epoch=44, batch_id=76, loss=0.097284, lr=0.000880,acc=0.966 ETA 06:03:13
[TRAIN] epoch=44, batch_id=86, loss=0.092662, lr=0.000877,acc=0.968 ETA 04:38:08
[TRAIN] epoch=44, batch_id=96, loss=0.097302, lr=0.000873,acc=0.966 ETA 04:37:21
[TRAIN] epoch=44, batch_id=106, loss=0.094776, lr=0.000870,acc=0.968 ETA 04:49:23
[TRAIN] epoch=44, batch_id=116, loss=0.094429, lr=0.000866,acc=0.968 ETA 04:56:11
[TRAIN] epoch=44, batch_id=126, loss=0.095359, lr=0.000863,acc=0.968 ETA 04:51:09
[TRAIN] epoch=44, batch_id=136, loss=0.095909, lr=0.000859,acc=0.969 ETA 05:00:36
[TRAIN] epoch=44, batch_id=146, loss=0.095148, lr=0.000855,acc=0.969 ETA 04:42:23
[TRAIN] epoch=44, batch_id=156, loss=0.093341, lr=0.000852,acc=0.970 ETA 04:41:12
[TRAIN] epoch=44, batch_id=166, loss=0.093676, lr=0.000848,acc=0.970 ETA 04:42:05
[TRAIN] epoch=44, batch_id=176, loss=0.092185, lr=0.000844,acc=0.971 ETA 05:26:12
[TRAIN] epoch=44, batch_id=186, loss=0.094380, lr=0.000840,acc=0.970 ETA 04:38:20
[TRAIN] epoch=44, batch_id=196, loss=0.093473, lr=0.000836,acc=0.970 ETA 05:02:42
[TRAIN] epoch=44, batch_id=206, loss=0.091989, lr=0.000832,acc=0.971 ETA 04:38:53
[TRAIN] epoch=44, batch_id=216, loss=0.090817, lr=0.000829,acc=0.971 ETA 04:44:20
[TRAIN] epoch=44, batch_id=226, loss=0.088681, lr=0.000825,acc=0.972 ETA 04:38:18
[TRAIN] epoch=44, batch_id=236, loss=0.086660, lr=0.000820,acc=0.973 ETA 04:46:36
[TRAIN] epoch=44, batch_id=246, loss=0.085651, lr=0.000816,acc=0.973 ETA 04:37:53
[TRAIN] epoch=44, batch_id=256, loss=0.086190, lr=0.000812,acc=0.973 ETA 04:41:36
[TRAIN] epoch=44, batch_id=266, loss=0.087226, lr=0.000808,acc=0.972 ETA 04:36:38
[TRAIN] epoch=44, batch_id=276, loss=0.087607, lr=0.000804,acc=0.972 ETA 04:36:23
[TRAIN] epoch=44, batch_id=286, loss=0.086968, lr=0.000800,acc=0.972 ETA 04:39:36
[TRAIN] epoch=44, batch_id=296, loss=0.085936, lr=0.000796,acc=0.972 ETA 04:47:52
[EVAL] epoch=44

Evaluating top_k_accuracy ...

top1_acc	0.7859
top5_acc	0.9487

Evaluating mean_class_accuracy ...

mean_acc	0.7843
[TRAIN] epoch=45, batch_id=8, loss=0.089324, lr=0.000791,acc=0.977 ETA 68:44:04
[TRAIN] epoch=45, batch_id=18, loss=0.072117, lr=0.000787,acc=0.981 ETA 06:19:43
[TRAIN] epoch=45, batch_id=28, loss=0.081791, lr=0.000783,acc=0.975 ETA 05:30:13
[TRAIN] epoch=45, batch_id=38, loss=0.078638, lr=0.000778,acc=0.976 ETA 04:51:04
[TRAIN] epoch=45, batch_id=48, loss=0.070155, lr=0.000774,acc=0.980 ETA 05:47:05
[TRAIN] epoch=45, batch_id=58, loss=0.066273, lr=0.000770,acc=0.981 ETA 04:41:46
[TRAIN] epoch=45, batch_id=68, loss=0.069268, lr=0.000765,acc=0.980 ETA 05:18:48
[TRAIN] epoch=45, batch_id=78, loss=0.071433, lr=0.000761,acc=0.980 ETA 04:33:54
[TRAIN] epoch=45, batch_id=88, loss=0.071620, lr=0.000756,acc=0.979 ETA 05:11:42
[TRAIN] epoch=45, batch_id=98, loss=0.073382, lr=0.000752,acc=0.979 ETA 04:37:06
[TRAIN] epoch=45, batch_id=108, loss=0.076601, lr=0.000747,acc=0.977 ETA 06:46:51
[TRAIN] epoch=45, batch_id=118, loss=0.075976, lr=0.000742,acc=0.978 ETA 05:02:00
[TRAIN] epoch=45, batch_id=128, loss=0.074302, lr=0.000738,acc=0.979 ETA 04:24:37
[TRAIN] epoch=45, batch_id=138, loss=0.074985, lr=0.000733,acc=0.979 ETA 05:42:06
[TRAIN] epoch=45, batch_id=148, loss=0.074316, lr=0.000728,acc=0.979 ETA 05:33:42
[TRAIN] epoch=45, batch_id=158, loss=0.075868, lr=0.000724,acc=0.979 ETA 04:49:17
[TRAIN] epoch=45, batch_id=168, loss=0.076359, lr=0.000719,acc=0.978 ETA 04:37:11
[TRAIN] epoch=45, batch_id=178, loss=0.076440, lr=0.000714,acc=0.978 ETA 05:30:33
[TRAIN] epoch=45, batch_id=188, loss=0.075103, lr=0.000709,acc=0.979 ETA 04:32:30
[TRAIN] epoch=45, batch_id=198, loss=0.076487, lr=0.000705,acc=0.978 ETA 06:29:08
[TRAIN] epoch=45, batch_id=208, loss=0.078731, lr=0.000700,acc=0.977 ETA 04:47:46
[TRAIN] epoch=45, batch_id=218, loss=0.077413, lr=0.000695,acc=0.978 ETA 04:36:46
[TRAIN] epoch=45, batch_id=228, loss=0.076194, lr=0.000690,acc=0.978 ETA 04:47:13
[TRAIN] epoch=45, batch_id=238, loss=0.075025, lr=0.000685,acc=0.978 ETA 04:40:17
[TRAIN] epoch=45, batch_id=248, loss=0.075265, lr=0.000680,acc=0.978 ETA 04:34:23
[TRAIN] epoch=45, batch_id=258, loss=0.074129, lr=0.000675,acc=0.978 ETA 04:34:58
[TRAIN] epoch=45, batch_id=268, loss=0.073563, lr=0.000670,acc=0.978 ETA 04:34:44
[TRAIN] epoch=45, batch_id=278, loss=0.073625, lr=0.000665,acc=0.978 ETA 04:31:52
[TRAIN] epoch=45, batch_id=288, loss=0.073065, lr=0.000661,acc=0.979 ETA 04:31:43
[TRAIN] epoch=45, batch_id=298, loss=0.072224, lr=0.000656,acc=0.979 ETA 05:40:13
[EVAL] epoch=45

Evaluating top_k_accuracy ...

top1_acc	0.7864
top5_acc	0.9469

Evaluating mean_class_accuracy ...

mean_acc	0.7862
[TRAIN] epoch=46, batch_id=10, loss=0.068215, lr=0.000650,acc=0.975 ETA 67:30:38
[TRAIN] epoch=46, batch_id=20, loss=0.069218, lr=0.000645,acc=0.977 ETA 04:43:54
[TRAIN] epoch=46, batch_id=30, loss=0.073816, lr=0.000640,acc=0.976 ETA 04:51:08
[TRAIN] epoch=46, batch_id=40, loss=0.077914, lr=0.000635,acc=0.974 ETA 04:35:35
[TRAIN] epoch=46, batch_id=50, loss=0.075349, lr=0.000630,acc=0.975 ETA 04:39:51
[TRAIN] epoch=46, batch_id=60, loss=0.070845, lr=0.000625,acc=0.978 ETA 04:33:05
[TRAIN] epoch=46, batch_id=70, loss=0.070389, lr=0.000620,acc=0.979 ETA 04:37:00
[TRAIN] epoch=46, batch_id=80, loss=0.067628, lr=0.000615,acc=0.979 ETA 04:27:59
[TRAIN] epoch=46, batch_id=90, loss=0.070439, lr=0.000610,acc=0.978 ETA 05:57:06
[TRAIN] epoch=46, batch_id=100, loss=0.071702, lr=0.000605,acc=0.977 ETA 04:29:17
[TRAIN] epoch=46, batch_id=110, loss=0.069432, lr=0.000599,acc=0.977 ETA 05:38:21
[TRAIN] epoch=46, batch_id=120, loss=0.069647, lr=0.000594,acc=0.978 ETA 04:45:43
[TRAIN] epoch=46, batch_id=130, loss=0.069008, lr=0.000589,acc=0.977 ETA 06:24:17
[TRAIN] epoch=46, batch_id=140, loss=0.067753, lr=0.000584,acc=0.978 ETA 05:23:10
[TRAIN] epoch=46, batch_id=150, loss=0.071029, lr=0.000579,acc=0.976 ETA 04:37:36
[TRAIN] epoch=46, batch_id=160, loss=0.069290, lr=0.000574,acc=0.978 ETA 06:03:44
[TRAIN] epoch=46, batch_id=170, loss=0.070095, lr=0.000568,acc=0.977 ETA 07:07:21
[TRAIN] epoch=46, batch_id=180, loss=0.071826, lr=0.000563,acc=0.976 ETA 06:32:23
[TRAIN] epoch=46, batch_id=190, loss=0.073207, lr=0.000558,acc=0.976 ETA 08:02:13
[TRAIN] epoch=46, batch_id=200, loss=0.071209, lr=0.000553,acc=0.977 ETA 04:40:29
[TRAIN] epoch=46, batch_id=210, loss=0.070713, lr=0.000547,acc=0.977 ETA 04:30:38
[TRAIN] epoch=46, batch_id=220, loss=0.071078, lr=0.000542,acc=0.977 ETA 04:35:09
[TRAIN] epoch=46, batch_id=230, loss=0.070383, lr=0.000537,acc=0.977 ETA 04:26:15
[TRAIN] epoch=46, batch_id=240, loss=0.070988, lr=0.000532,acc=0.977 ETA 04:41:36
[TRAIN] epoch=46, batch_id=250, loss=0.070734, lr=0.000526,acc=0.977 ETA 04:24:35
[TRAIN] epoch=46, batch_id=260, loss=0.070975, lr=0.000521,acc=0.977 ETA 05:33:05
[TRAIN] epoch=46, batch_id=270, loss=0.069783, lr=0.000516,acc=0.977 ETA 04:34:29
[TRAIN] epoch=46, batch_id=280, loss=0.069670, lr=0.000511,acc=0.977 ETA 04:47:42
[TRAIN] epoch=46, batch_id=290, loss=0.068505, lr=0.000505,acc=0.978 ETA 04:22:42
[EVAL] epoch=46

Evaluating top_k_accuracy ...

top1_acc	0.7904
top5_acc	0.9434

Evaluating mean_class_accuracy ...

mean_acc	0.7898
[TRAIN] epoch=47, batch_id=2, loss=0.058407, lr=0.000500,acc=0.969 ETA 64:35:50
[TRAIN] epoch=47, batch_id=12, loss=0.057962, lr=0.000495,acc=0.982 ETA 04:29:54
[TRAIN] epoch=47, batch_id=22, loss=0.061619, lr=0.000489,acc=0.979 ETA 04:26:03
[TRAIN] epoch=47, batch_id=32, loss=0.066083, lr=0.000484,acc=0.977 ETA 06:32:23
[TRAIN] epoch=47, batch_id=42, loss=0.063211, lr=0.000479,acc=0.978 ETA 04:35:56
[TRAIN] epoch=47, batch_id=52, loss=0.063497, lr=0.000474,acc=0.979 ETA 05:15:25
[TRAIN] epoch=47, batch_id=62, loss=0.057710, lr=0.000468,acc=0.981 ETA 04:45:43
[TRAIN] epoch=47, batch_id=72, loss=0.060672, lr=0.000463,acc=0.981 ETA 04:23:04
[TRAIN] epoch=47, batch_id=82, loss=0.057506, lr=0.000458,acc=0.982 ETA 04:24:21
[TRAIN] epoch=47, batch_id=92, loss=0.057698, lr=0.000453,acc=0.981 ETA 04:25:28
[TRAIN] epoch=47, batch_id=102, loss=0.056047, lr=0.000447,acc=0.982 ETA 05:25:29
[TRAIN] epoch=47, batch_id=112, loss=0.054919, lr=0.000442,acc=0.982 ETA 06:55:29
[TRAIN] epoch=47, batch_id=122, loss=0.055342, lr=0.000437,acc=0.982 ETA 06:30:22
[TRAIN] epoch=47, batch_id=132, loss=0.054781, lr=0.000432,acc=0.982 ETA 07:00:48
[TRAIN] epoch=47, batch_id=142, loss=0.053538, lr=0.000426,acc=0.983 ETA 06:00:51
[TRAIN] epoch=47, batch_id=152, loss=0.055916, lr=0.000421,acc=0.983 ETA 04:21:38
[TRAIN] epoch=47, batch_id=162, loss=0.056391, lr=0.000416,acc=0.982 ETA 04:22:08
[TRAIN] epoch=47, batch_id=172, loss=0.055086, lr=0.000411,acc=0.982 ETA 04:21:50
[TRAIN] epoch=47, batch_id=182, loss=0.054369, lr=0.000406,acc=0.983 ETA 04:48:43
[TRAIN] epoch=47, batch_id=192, loss=0.054865, lr=0.000401,acc=0.982 ETA 04:20:19
[TRAIN] epoch=47, batch_id=202, loss=0.053140, lr=0.000395,acc=0.983 ETA 04:42:59
[TRAIN] epoch=47, batch_id=212, loss=0.054303, lr=0.000390,acc=0.983 ETA 04:34:51
[TRAIN] epoch=47, batch_id=222, loss=0.056026, lr=0.000385,acc=0.983 ETA 05:14:23
[TRAIN] epoch=47, batch_id=232, loss=0.055566, lr=0.000380,acc=0.983 ETA 04:23:52
[TRAIN] epoch=47, batch_id=242, loss=0.055911, lr=0.000375,acc=0.983 ETA 04:52:38
[TRAIN] epoch=47, batch_id=252, loss=0.055351, lr=0.000370,acc=0.983 ETA 04:14:52
[TRAIN] epoch=47, batch_id=262, loss=0.054511, lr=0.000365,acc=0.983 ETA 04:33:12
[TRAIN] epoch=47, batch_id=272, loss=0.054807, lr=0.000360,acc=0.983 ETA 04:20:33
[TRAIN] epoch=47, batch_id=282, loss=0.054667, lr=0.000355,acc=0.983 ETA 04:59:40
[TRAIN] epoch=47, batch_id=292, loss=0.056255, lr=0.000350,acc=0.983 ETA 04:21:09
[EVAL] epoch=47

Evaluating top_k_accuracy ...

top1_acc	0.7898
top5_acc	0.9455

Evaluating mean_class_accuracy ...

mean_acc	0.7902
[TRAIN] epoch=48, batch_id=4, loss=0.047397, lr=0.000344,acc=0.992 ETA 63:10:33
[TRAIN] epoch=48, batch_id=14, loss=0.052746, lr=0.000339,acc=0.989 ETA 04:19:24
[TRAIN] epoch=48, batch_id=24, loss=0.054906, lr=0.000335,acc=0.986 ETA 04:23:36
[TRAIN] epoch=48, batch_id=34, loss=0.060324, lr=0.000330,acc=0.983 ETA 04:28:47
[TRAIN] epoch=48, batch_id=44, loss=0.064694, lr=0.000325,acc=0.979 ETA 04:19:13
[TRAIN] epoch=48, batch_id=54, loss=0.063774, lr=0.000320,acc=0.980 ETA 04:20:14
[TRAIN] epoch=48, batch_id=64, loss=0.059637, lr=0.000315,acc=0.980 ETA 04:22:30
[TRAIN] epoch=48, batch_id=74, loss=0.057505, lr=0.000310,acc=0.982 ETA 04:23:22
[TRAIN] epoch=48, batch_id=84, loss=0.056841, lr=0.000305,acc=0.983 ETA 07:36:01
[TRAIN] epoch=48, batch_id=94, loss=0.056742, lr=0.000300,acc=0.983 ETA 06:25:34
[TRAIN] epoch=48, batch_id=104, loss=0.057201, lr=0.000295,acc=0.983 ETA 06:44:04
[TRAIN] epoch=48, batch_id=114, loss=0.055900, lr=0.000291,acc=0.984 ETA 05:18:26
[TRAIN] epoch=48, batch_id=124, loss=0.056399, lr=0.000286,acc=0.984 ETA 04:12:42
[TRAIN] epoch=48, batch_id=134, loss=0.055482, lr=0.000281,acc=0.983 ETA 04:30:32
[TRAIN] epoch=48, batch_id=144, loss=0.056302, lr=0.000276,acc=0.984 ETA 04:23:24
[TRAIN] epoch=48, batch_id=154, loss=0.057138, lr=0.000272,acc=0.983 ETA 04:14:21
[TRAIN] epoch=48, batch_id=164, loss=0.056106, lr=0.000267,acc=0.983 ETA 04:20:10
[TRAIN] epoch=48, batch_id=174, loss=0.056442, lr=0.000262,acc=0.983 ETA 04:23:29
[TRAIN] epoch=48, batch_id=184, loss=0.056007, lr=0.000258,acc=0.983 ETA 04:19:07
[TRAIN] epoch=48, batch_id=194, loss=0.056163, lr=0.000253,acc=0.982 ETA 04:19:58
[TRAIN] epoch=48, batch_id=204, loss=0.055095, lr=0.000248,acc=0.983 ETA 05:26:49
[TRAIN] epoch=48, batch_id=214, loss=0.054988, lr=0.000244,acc=0.983 ETA 04:18:35
[TRAIN] epoch=48, batch_id=224, loss=0.056669, lr=0.000239,acc=0.982 ETA 04:21:26
[TRAIN] epoch=48, batch_id=234, loss=0.057175, lr=0.000235,acc=0.982 ETA 04:18:11
[TRAIN] epoch=48, batch_id=244, loss=0.056593, lr=0.000230,acc=0.983 ETA 04:28:09
[TRAIN] epoch=48, batch_id=254, loss=0.057785, lr=0.000226,acc=0.983 ETA 04:22:25
[TRAIN] epoch=48, batch_id=264, loss=0.057223, lr=0.000222,acc=0.983 ETA 04:27:06
[TRAIN] epoch=48, batch_id=274, loss=0.057283, lr=0.000217,acc=0.983 ETA 04:32:59
[TRAIN] epoch=48, batch_id=284, loss=0.058581, lr=0.000213,acc=0.982 ETA 04:31:14
[TRAIN] epoch=48, batch_id=294, loss=0.057911, lr=0.000209,acc=0.983 ETA 04:22:05
[EVAL] epoch=48

Evaluating top_k_accuracy ...

top1_acc	0.7909
top5_acc	0.9485

Evaluating mean_class_accuracy ...

mean_acc	0.7908
[TRAIN] epoch=49, batch_id=6, loss=0.066678, lr=0.000204,acc=0.974 ETA 65:14:13
[TRAIN] epoch=49, batch_id=16, loss=0.044986, lr=0.000200,acc=0.984 ETA 04:41:20
[TRAIN] epoch=49, batch_id=26, loss=0.055909, lr=0.000196,acc=0.984 ETA 04:36:23
[TRAIN] epoch=49, batch_id=36, loss=0.052049, lr=0.000192,acc=0.984 ETA 04:18:38
[TRAIN] epoch=49, batch_id=46, loss=0.048046, lr=0.000188,acc=0.986 ETA 04:11:57
[TRAIN] epoch=49, batch_id=56, loss=0.046549, lr=0.000184,acc=0.987 ETA 05:18:37
[TRAIN] epoch=49, batch_id=66, loss=0.048433, lr=0.000180,acc=0.985 ETA 04:08:23
[TRAIN] epoch=49, batch_id=76, loss=0.052781, lr=0.000175,acc=0.984 ETA 04:13:30
[TRAIN] epoch=49, batch_id=86, loss=0.049831, lr=0.000171,acc=0.985 ETA 04:14:34
[TRAIN] epoch=49, batch_id=96, loss=0.048345, lr=0.000168,acc=0.985 ETA 04:12:07
[TRAIN] epoch=49, batch_id=106, loss=0.046290, lr=0.000164,acc=0.986 ETA 04:09:18
[TRAIN] epoch=49, batch_id=116, loss=0.051046, lr=0.000160,acc=0.984 ETA 04:13:36
[TRAIN] epoch=49, batch_id=126, loss=0.049650, lr=0.000156,acc=0.984 ETA 04:09:29
[TRAIN] epoch=49, batch_id=136, loss=0.050831, lr=0.000152,acc=0.984 ETA 04:09:59
[TRAIN] epoch=49, batch_id=146, loss=0.050585, lr=0.000148,acc=0.984 ETA 04:06:18
[TRAIN] epoch=49, batch_id=156, loss=0.052526, lr=0.000145,acc=0.984 ETA 04:19:13
[TRAIN] epoch=49, batch_id=166, loss=0.051349, lr=0.000141,acc=0.985 ETA 04:13:01
[TRAIN] epoch=49, batch_id=176, loss=0.050784, lr=0.000137,acc=0.985 ETA 05:24:57
[TRAIN] epoch=49, batch_id=186, loss=0.052078, lr=0.000134,acc=0.984 ETA 05:01:34
[TRAIN] epoch=49, batch_id=196, loss=0.053977, lr=0.000130,acc=0.984 ETA 04:10:39
[TRAIN] epoch=49, batch_id=206, loss=0.053660, lr=0.000127,acc=0.984 ETA 04:09:19
[TRAIN] epoch=49, batch_id=216, loss=0.053465, lr=0.000123,acc=0.984 ETA 04:28:41
[TRAIN] epoch=49, batch_id=226, loss=0.053760, lr=0.000120,acc=0.984 ETA 04:35:47
[TRAIN] epoch=49, batch_id=236, loss=0.054810, lr=0.000116,acc=0.983 ETA 04:25:46
[TRAIN] epoch=49, batch_id=246, loss=0.053119, lr=0.000113,acc=0.984 ETA 04:13:24
[TRAIN] epoch=49, batch_id=256, loss=0.053048, lr=0.000110,acc=0.984 ETA 04:57:38
[TRAIN] epoch=49, batch_id=266, loss=0.053861, lr=0.000106,acc=0.984 ETA 05:32:08
[TRAIN] epoch=49, batch_id=276, loss=0.054273, lr=0.000103,acc=0.984 ETA 05:43:29
[TRAIN] epoch=49, batch_id=286, loss=0.053312, lr=0.000100,acc=0.984 ETA 04:09:57
[TRAIN] epoch=49, batch_id=296, loss=0.053757, lr=0.000097,acc=0.984 ETA 05:07:00
[EVAL] epoch=49

Evaluating top_k_accuracy ...

top1_acc	0.7888
top5_acc	0.9482

Evaluating mean_class_accuracy ...

mean_acc	0.7885
[TRAIN] epoch=50, batch_id=8, loss=0.048441, lr=0.000094,acc=0.984 ETA 61:44:50
[TRAIN] epoch=50, batch_id=18, loss=0.047340, lr=0.000091,acc=0.988 ETA 04:09:02
[TRAIN] epoch=50, batch_id=28, loss=0.049318, lr=0.000088,acc=0.985 ETA 04:12:46
[TRAIN] epoch=50, batch_id=38, loss=0.055713, lr=0.000085,acc=0.984 ETA 04:10:38
[TRAIN] epoch=50, batch_id=48, loss=0.053709, lr=0.000082,acc=0.985 ETA 04:46:27
[TRAIN] epoch=50, batch_id=58, loss=0.057677, lr=0.000079,acc=0.984 ETA 04:45:11
[TRAIN] epoch=50, batch_id=68, loss=0.058147, lr=0.000076,acc=0.983 ETA 04:04:53
[TRAIN] epoch=50, batch_id=78, loss=0.054340, lr=0.000073,acc=0.984 ETA 04:07:17
[TRAIN] epoch=50, batch_id=88, loss=0.052654, lr=0.000071,acc=0.984 ETA 05:07:11
[TRAIN] epoch=50, batch_id=98, loss=0.054343, lr=0.000068,acc=0.983 ETA 04:13:37
[TRAIN] epoch=50, batch_id=108, loss=0.053193, lr=0.000065,acc=0.984 ETA 04:23:18
[TRAIN] epoch=50, batch_id=118, loss=0.050325, lr=0.000063,acc=0.985 ETA 04:44:26
[TRAIN] epoch=50, batch_id=128, loss=0.048761, lr=0.000060,acc=0.985 ETA 04:15:52
[TRAIN] epoch=50, batch_id=138, loss=0.048803, lr=0.000058,acc=0.985 ETA 04:10:12
[TRAIN] epoch=50, batch_id=148, loss=0.047493, lr=0.000055,acc=0.985 ETA 04:18:39
[TRAIN] epoch=50, batch_id=158, loss=0.047184, lr=0.000053,acc=0.986 ETA 04:22:18
[TRAIN] epoch=50, batch_id=168, loss=0.048374, lr=0.000051,acc=0.985 ETA 04:10:02
[TRAIN] epoch=50, batch_id=178, loss=0.046982, lr=0.000048,acc=0.986 ETA 04:12:26
[TRAIN] epoch=50, batch_id=188, loss=0.047211, lr=0.000046,acc=0.986 ETA 04:08:49
[TRAIN] epoch=50, batch_id=198, loss=0.047211, lr=0.000044,acc=0.986 ETA 04:09:40
[TRAIN] epoch=50, batch_id=208, loss=0.046909, lr=0.000042,acc=0.986 ETA 04:06:18
[TRAIN] epoch=50, batch_id=218, loss=0.047617, lr=0.000040,acc=0.986 ETA 04:16:05
[TRAIN] epoch=50, batch_id=228, loss=0.046698, lr=0.000038,acc=0.986 ETA 04:16:28
[TRAIN] epoch=50, batch_id=238, loss=0.047140, lr=0.000036,acc=0.986 ETA 04:37:39
[TRAIN] epoch=50, batch_id=248, loss=0.045941, lr=0.000034,acc=0.987 ETA 04:06:08
[TRAIN] epoch=50, batch_id=258, loss=0.045533, lr=0.000032,acc=0.987 ETA 06:05:08
[TRAIN] epoch=50, batch_id=268, loss=0.044892, lr=0.000030,acc=0.987 ETA 04:11:58
[TRAIN] epoch=50, batch_id=278, loss=0.044300, lr=0.000028,acc=0.987 ETA 04:22:55
[TRAIN] epoch=50, batch_id=288, loss=0.043400, lr=0.000026,acc=0.987 ETA 04:09:41
[TRAIN] epoch=50, batch_id=298, loss=0.043145, lr=0.000025,acc=0.987 ETA 04:04:25
[EVAL] epoch=50

Evaluating top_k_accuracy ...

top1_acc	0.7904
top5_acc	0.9495

Evaluating mean_class_accuracy ...

mean_acc	0.7900
[TRAIN] epoch=51, batch_id=10, loss=0.053800, lr=0.000023,acc=0.981 ETA 61:40:15
[TRAIN] epoch=51, batch_id=20, loss=0.054162, lr=0.000022,acc=0.984 ETA 04:40:11
[TRAIN] epoch=51, batch_id=30, loss=0.054909, lr=0.000020,acc=0.982 ETA 04:06:34
[TRAIN] epoch=51, batch_id=40, loss=0.050885, lr=0.000019,acc=0.984 ETA 04:24:25
[TRAIN] epoch=51, batch_id=50, loss=0.050929, lr=0.000017,acc=0.983 ETA 04:09:13
[TRAIN] epoch=51, batch_id=60, loss=0.046012, lr=0.000016,acc=0.985 ETA 04:49:59
[TRAIN] epoch=51, batch_id=70, loss=0.043615, lr=0.000015,acc=0.986 ETA 04:10:14
[TRAIN] epoch=51, batch_id=80, loss=0.047569, lr=0.000013,acc=0.986 ETA 04:52:24
[TRAIN] epoch=51, batch_id=90, loss=0.046718, lr=0.000012,acc=0.986 ETA 04:00:57
[TRAIN] epoch=51, batch_id=100, loss=0.047308, lr=0.000011,acc=0.986 ETA 04:57:33
[TRAIN] epoch=51, batch_id=110, loss=0.046771, lr=0.000010,acc=0.986 ETA 04:06:19
[TRAIN] epoch=51, batch_id=120, loss=0.047134, lr=0.000009,acc=0.986 ETA 05:59:49
[TRAIN] epoch=51, batch_id=130, loss=0.046040, lr=0.000008,acc=0.986 ETA 04:10:51
[TRAIN] epoch=51, batch_id=140, loss=0.046199, lr=0.000007,acc=0.986 ETA 04:04:41
[TRAIN] epoch=51, batch_id=150, loss=0.045639, lr=0.000006,acc=0.986 ETA 04:03:24
[TRAIN] epoch=51, batch_id=160, loss=0.045838, lr=0.000005,acc=0.986 ETA 04:12:42
[TRAIN] epoch=51, batch_id=170, loss=0.045386, lr=0.000005,acc=0.986 ETA 04:07:45
[TRAIN] epoch=51, batch_id=180, loss=0.045209, lr=0.000004,acc=0.986 ETA 05:39:57
[TRAIN] epoch=51, batch_id=190, loss=0.045379, lr=0.000003,acc=0.986 ETA 08:22:12
[TRAIN] epoch=51, batch_id=200, loss=0.044814, lr=0.000003,acc=0.986 ETA 04:45:21
[TRAIN] epoch=51, batch_id=210, loss=0.045504, lr=0.000002,acc=0.986 ETA 04:06:50
[TRAIN] epoch=51, batch_id=220, loss=0.045536, lr=0.000002,acc=0.986 ETA 04:01:20
[TRAIN] epoch=51, batch_id=230, loss=0.046814, lr=0.000001,acc=0.986 ETA 03:57:25
[TRAIN] epoch=51, batch_id=240, loss=0.045712, lr=0.000001,acc=0.986 ETA 03:58:22
[TRAIN] epoch=51, batch_id=250, loss=0.046011, lr=0.000001,acc=0.986 ETA 03:57:15
[TRAIN] epoch=51, batch_id=260, loss=0.046024, lr=0.000000,acc=0.986 ETA 04:02:23
[TRAIN] epoch=51, batch_id=270, loss=0.047488, lr=0.000000,acc=0.986 ETA 03:55:52
[TRAIN] epoch=51, batch_id=280, loss=0.047944, lr=0.000000,acc=0.985 ETA 04:05:49
[TRAIN] epoch=51, batch_id=290, loss=0.047629, lr=0.000000,acc=0.985 ETA 03:56:25
[EVAL] epoch=51

Evaluating top_k_accuracy ...

top1_acc	0.7914
top5_acc	0.9492

Evaluating mean_class_accuracy ...

mean_acc	0.7910
[TRAIN] epoch=52, batch_id=2, loss=0.050603, lr=0.000000,acc=0.984 ETA 60:12:14
[TRAIN] epoch=52, batch_id=12, loss=0.045994, lr=0.000000,acc=0.990 ETA 03:56:41
[TRAIN] epoch=52, batch_id=22, loss=0.034769, lr=0.000000,acc=0.991 ETA 03:55:03
[TRAIN] epoch=52, batch_id=32, loss=0.032327, lr=0.000000,acc=0.992 ETA 04:16:22
[TRAIN] epoch=52, batch_id=42, loss=0.028906, lr=0.000000,acc=0.993 ETA 03:54:21
[TRAIN] epoch=52, batch_id=52, loss=0.036448, lr=0.000001,acc=0.991 ETA 04:33:04
[TRAIN] epoch=52, batch_id=62, loss=0.036064, lr=0.000001,acc=0.991 ETA 03:54:14
[TRAIN] epoch=52, batch_id=72, loss=0.038395, lr=0.000001,acc=0.990 ETA 04:48:17
[TRAIN] epoch=52, batch_id=82, loss=0.037970, lr=0.000002,acc=0.990 ETA 03:56:11
[TRAIN] epoch=52, batch_id=92, loss=0.041811, lr=0.000002,acc=0.988 ETA 03:57:31
[TRAIN] epoch=52, batch_id=102, loss=0.039555, lr=0.000003,acc=0.989 ETA 03:58:03
[TRAIN] epoch=52, batch_id=112, loss=0.041673, lr=0.000003,acc=0.989 ETA 04:39:56
[TRAIN] epoch=52, batch_id=122, loss=0.042350, lr=0.000004,acc=0.988 ETA 03:52:56
[TRAIN] epoch=52, batch_id=132, loss=0.045968, lr=0.000005,acc=0.988 ETA 03:54:25
[TRAIN] epoch=52, batch_id=142, loss=0.046462, lr=0.000005,acc=0.988 ETA 03:50:35
[TRAIN] epoch=52, batch_id=152, loss=0.045730, lr=0.000006,acc=0.988 ETA 04:54:53
[TRAIN] epoch=52, batch_id=162, loss=0.045113, lr=0.000007,acc=0.988 ETA 03:59:38
[TRAIN] epoch=52, batch_id=172, loss=0.045508, lr=0.000008,acc=0.988 ETA 03:59:28
[TRAIN] epoch=52, batch_id=182, loss=0.045052, lr=0.000009,acc=0.988 ETA 03:57:56
[TRAIN] epoch=52, batch_id=192, loss=0.044484, lr=0.000010,acc=0.988 ETA 03:50:01
[TRAIN] epoch=52, batch_id=202, loss=0.044663, lr=0.000011,acc=0.987 ETA 04:01:58
[TRAIN] epoch=52, batch_id=212, loss=0.045168, lr=0.000012,acc=0.987 ETA 03:55:41
[TRAIN] epoch=52, batch_id=222, loss=0.045601, lr=0.000013,acc=0.986 ETA 04:04:36
[TRAIN] epoch=52, batch_id=232, loss=0.046703, lr=0.000015,acc=0.986 ETA 04:01:26
[TRAIN] epoch=52, batch_id=242, loss=0.047548, lr=0.000016,acc=0.986 ETA 04:05:00
[TRAIN] epoch=52, batch_id=252, loss=0.046379, lr=0.000017,acc=0.986 ETA 04:03:35
[TRAIN] epoch=52, batch_id=262, loss=0.046241, lr=0.000019,acc=0.986 ETA 03:54:51
[TRAIN] epoch=52, batch_id=272, loss=0.045863, lr=0.000020,acc=0.986 ETA 03:54:30
[TRAIN] epoch=52, batch_id=282, loss=0.045382, lr=0.000022,acc=0.986 ETA 03:57:03
[TRAIN] epoch=52, batch_id=292, loss=0.045534, lr=0.000023,acc=0.986 ETA 04:07:00
[EVAL] epoch=52

Evaluating top_k_accuracy ...

top1_acc	0.7898
top5_acc	0.9492

Evaluating mean_class_accuracy ...

mean_acc	0.7893
[TRAIN] epoch=53, batch_id=4, loss=0.016892, lr=0.000025,acc=1.000 ETA 59:23:40
[TRAIN] epoch=53, batch_id=14, loss=0.027020, lr=0.000026,acc=0.996 ETA 03:49:25
[TRAIN] epoch=53, batch_id=24, loss=0.039391, lr=0.000028,acc=0.991 ETA 04:49:37
[TRAIN] epoch=53, batch_id=34, loss=0.047287, lr=0.000030,acc=0.986 ETA 03:55:57
[TRAIN] epoch=53, batch_id=44, loss=0.046617, lr=0.000032,acc=0.986 ETA 04:07:58
[TRAIN] epoch=53, batch_id=54, loss=0.044603, lr=0.000034,acc=0.987 ETA 03:53:26
[TRAIN] epoch=53, batch_id=64, loss=0.044551, lr=0.000036,acc=0.987 ETA 05:15:40
[TRAIN] epoch=53, batch_id=74, loss=0.048984, lr=0.000038,acc=0.986 ETA 03:56:49
[TRAIN] epoch=53, batch_id=84, loss=0.046880, lr=0.000040,acc=0.986 ETA 03:58:39
[TRAIN] epoch=53, batch_id=94, loss=0.044509, lr=0.000042,acc=0.987 ETA 03:54:05
[TRAIN] epoch=53, batch_id=104, loss=0.042621, lr=0.000044,acc=0.988 ETA 03:58:27
[TRAIN] epoch=53, batch_id=114, loss=0.042337, lr=0.000046,acc=0.987 ETA 03:58:29
[TRAIN] epoch=53, batch_id=124, loss=0.044069, lr=0.000048,acc=0.987 ETA 03:56:12
[TRAIN] epoch=53, batch_id=134, loss=0.043602, lr=0.000051,acc=0.987 ETA 03:49:32
[TRAIN] epoch=53, batch_id=144, loss=0.044969, lr=0.000053,acc=0.987 ETA 03:54:38
[TRAIN] epoch=53, batch_id=154, loss=0.046222, lr=0.000055,acc=0.986 ETA 03:49:25
[TRAIN] epoch=53, batch_id=164, loss=0.045909, lr=0.000058,acc=0.986 ETA 03:57:38
[TRAIN] epoch=53, batch_id=174, loss=0.044741, lr=0.000060,acc=0.987 ETA 03:51:52
[TRAIN] epoch=53, batch_id=184, loss=0.043815, lr=0.000063,acc=0.987 ETA 03:54:18
[TRAIN] epoch=53, batch_id=194, loss=0.042722, lr=0.000065,acc=0.987 ETA 03:49:01
[TRAIN] epoch=53, batch_id=204, loss=0.042348, lr=0.000068,acc=0.987 ETA 04:39:42
[TRAIN] epoch=53, batch_id=214, loss=0.042999, lr=0.000071,acc=0.987 ETA 03:59:47
[TRAIN] epoch=53, batch_id=224, loss=0.043312, lr=0.000073,acc=0.987 ETA 03:50:54
[TRAIN] epoch=53, batch_id=234, loss=0.043353, lr=0.000076,acc=0.987 ETA 03:49:39
[TRAIN] epoch=53, batch_id=244, loss=0.044388, lr=0.000079,acc=0.987 ETA 04:09:36
[TRAIN] epoch=53, batch_id=254, loss=0.044016, lr=0.000082,acc=0.987 ETA 03:56:59
[TRAIN] epoch=53, batch_id=264, loss=0.044991, lr=0.000085,acc=0.986 ETA 03:47:26
[TRAIN] epoch=53, batch_id=274, loss=0.045736, lr=0.000088,acc=0.986 ETA 03:45:46
[TRAIN] epoch=53, batch_id=284, loss=0.046152, lr=0.000091,acc=0.986 ETA 04:22:24
[TRAIN] epoch=53, batch_id=294, loss=0.046313, lr=0.000094,acc=0.986 ETA 04:13:55
[EVAL] epoch=53

Evaluating top_k_accuracy ...

top1_acc	0.7896
top5_acc	0.9485

Evaluating mean_class_accuracy ...

mean_acc	0.7881
[TRAIN] epoch=54, batch_id=6, loss=0.034724, lr=0.000097,acc=0.990 ETA 57:20:08
[TRAIN] epoch=54, batch_id=16, loss=0.054107, lr=0.000100,acc=0.986 ETA 03:51:00
[TRAIN] epoch=54, batch_id=26, loss=0.045697, lr=0.000103,acc=0.989 ETA 03:50:02
[TRAIN] epoch=54, batch_id=36, loss=0.042381, lr=0.000106,acc=0.990 ETA 03:49:14
[TRAIN] epoch=54, batch_id=46, loss=0.050350, lr=0.000110,acc=0.988 ETA 03:48:57
[TRAIN] epoch=54, batch_id=56, loss=0.055582, lr=0.000113,acc=0.986 ETA 03:53:16
[TRAIN] epoch=54, batch_id=66, loss=0.059181, lr=0.000116,acc=0.984 ETA 04:13:52
[TRAIN] epoch=54, batch_id=76, loss=0.056484, lr=0.000120,acc=0.985 ETA 03:50:26
[TRAIN] epoch=54, batch_id=86, loss=0.055443, lr=0.000123,acc=0.985 ETA 03:51:23
[TRAIN] epoch=54, batch_id=96, loss=0.053767, lr=0.000127,acc=0.985 ETA 05:13:32
[TRAIN] epoch=54, batch_id=106, loss=0.051970, lr=0.000130,acc=0.986 ETA 05:44:03
[TRAIN] epoch=54, batch_id=116, loss=0.051391, lr=0.000134,acc=0.986 ETA 06:04:15
[TRAIN] epoch=54, batch_id=126, loss=0.053943, lr=0.000137,acc=0.985 ETA 04:33:30
[TRAIN] epoch=54, batch_id=136, loss=0.057805, lr=0.000141,acc=0.983 ETA 03:43:41
[TRAIN] epoch=54, batch_id=146, loss=0.057098, lr=0.000145,acc=0.984 ETA 03:51:36
[TRAIN] epoch=54, batch_id=156, loss=0.056492, lr=0.000148,acc=0.983 ETA 03:46:50
[TRAIN] epoch=54, batch_id=166, loss=0.056068, lr=0.000152,acc=0.982 ETA 04:24:49
[TRAIN] epoch=54, batch_id=176, loss=0.055588, lr=0.000156,acc=0.983 ETA 04:07:43
[TRAIN] epoch=54, batch_id=186, loss=0.055882, lr=0.000160,acc=0.983 ETA 03:53:00
[TRAIN] epoch=54, batch_id=196, loss=0.054847, lr=0.000164,acc=0.983 ETA 04:02:41
[TRAIN] epoch=54, batch_id=206, loss=0.054001, lr=0.000168,acc=0.983 ETA 04:07:14
[TRAIN] epoch=54, batch_id=216, loss=0.054202, lr=0.000171,acc=0.983 ETA 03:54:16
[TRAIN] epoch=54, batch_id=226, loss=0.053269, lr=0.000175,acc=0.983 ETA 03:51:22
[TRAIN] epoch=54, batch_id=236, loss=0.052387, lr=0.000180,acc=0.984 ETA 04:04:44
[TRAIN] epoch=54, batch_id=246, loss=0.052060, lr=0.000184,acc=0.984 ETA 04:03:59
[TRAIN] epoch=54, batch_id=256, loss=0.051665, lr=0.000188,acc=0.984 ETA 04:01:43
[TRAIN] epoch=54, batch_id=266, loss=0.053068, lr=0.000192,acc=0.984 ETA 03:59:57
[TRAIN] epoch=54, batch_id=276, loss=0.052107, lr=0.000196,acc=0.984 ETA 03:45:43
[TRAIN] epoch=54, batch_id=286, loss=0.052135, lr=0.000200,acc=0.984 ETA 03:45:02
[TRAIN] epoch=54, batch_id=296, loss=0.051486, lr=0.000204,acc=0.984 ETA 03:46:58
[EVAL] epoch=54

Evaluating top_k_accuracy ...

top1_acc	0.7973
top5_acc	0.9527

Evaluating mean_class_accuracy ...

mean_acc	0.7977
Save best model
[TRAIN] epoch=55, batch_id=8, loss=0.044395, lr=0.000209,acc=0.984 ETA 56:12:23
[TRAIN] epoch=55, batch_id=18, loss=0.033126, lr=0.000213,acc=0.991 ETA 03:47:38
[TRAIN] epoch=55, batch_id=28, loss=0.035129, lr=0.000217,acc=0.992 ETA 03:50:08
[TRAIN] epoch=55, batch_id=38, loss=0.031759, lr=0.000222,acc=0.993 ETA 03:54:24
[TRAIN] epoch=55, batch_id=48, loss=0.036392, lr=0.000226,acc=0.993 ETA 03:49:10
[TRAIN] epoch=55, batch_id=58, loss=0.038042, lr=0.000230,acc=0.992 ETA 05:14:35
[TRAIN] epoch=55, batch_id=68, loss=0.040283, lr=0.000235,acc=0.991 ETA 03:45:54
[TRAIN] epoch=55, batch_id=78, loss=0.040117, lr=0.000239,acc=0.990 ETA 03:44:26
[TRAIN] epoch=55, batch_id=88, loss=0.040228, lr=0.000244,acc=0.990 ETA 03:54:01
[TRAIN] epoch=55, batch_id=98, loss=0.043088, lr=0.000248,acc=0.988 ETA 03:47:58
[TRAIN] epoch=55, batch_id=108, loss=0.041766, lr=0.000253,acc=0.989 ETA 03:44:43
[TRAIN] epoch=55, batch_id=118, loss=0.043684, lr=0.000258,acc=0.989 ETA 03:44:54
[TRAIN] epoch=55, batch_id=128, loss=0.042729, lr=0.000262,acc=0.989 ETA 04:01:39
[TRAIN] epoch=55, batch_id=138, loss=0.041419, lr=0.000267,acc=0.989 ETA 03:55:34
[TRAIN] epoch=55, batch_id=148, loss=0.043407, lr=0.000272,acc=0.988 ETA 03:56:25
[TRAIN] epoch=55, batch_id=158, loss=0.042245, lr=0.000276,acc=0.989 ETA 04:05:23
[TRAIN] epoch=55, batch_id=168, loss=0.042610, lr=0.000281,acc=0.988 ETA 03:47:55
[TRAIN] epoch=55, batch_id=178, loss=0.042228, lr=0.000286,acc=0.988 ETA 03:45:42
[TRAIN] epoch=55, batch_id=188, loss=0.042668, lr=0.000291,acc=0.988 ETA 03:57:58
[TRAIN] epoch=55, batch_id=198, loss=0.042624, lr=0.000295,acc=0.989 ETA 03:40:07
[TRAIN] epoch=55, batch_id=208, loss=0.043062, lr=0.000300,acc=0.988 ETA 03:44:06
[TRAIN] epoch=55, batch_id=218, loss=0.043038, lr=0.000305,acc=0.988 ETA 03:44:32
[TRAIN] epoch=55, batch_id=228, loss=0.042742, lr=0.000310,acc=0.988 ETA 03:43:24
[TRAIN] epoch=55, batch_id=238, loss=0.042311, lr=0.000315,acc=0.989 ETA 03:36:08
[TRAIN] epoch=55, batch_id=248, loss=0.042900, lr=0.000320,acc=0.989 ETA 03:43:55
[TRAIN] epoch=55, batch_id=258, loss=0.045115, lr=0.000325,acc=0.988 ETA 03:44:14
[TRAIN] epoch=55, batch_id=268, loss=0.045537, lr=0.000330,acc=0.988 ETA 03:40:50
[TRAIN] epoch=55, batch_id=278, loss=0.046868, lr=0.000335,acc=0.987 ETA 03:42:08
[TRAIN] epoch=55, batch_id=288, loss=0.046644, lr=0.000339,acc=0.987 ETA 03:39:21
[TRAIN] epoch=55, batch_id=298, loss=0.046814, lr=0.000344,acc=0.987 ETA 03:39:20
[EVAL] epoch=55

Evaluating top_k_accuracy ...

top1_acc	0.7891
top5_acc	0.9463

Evaluating mean_class_accuracy ...

mean_acc	0.7874
[TRAIN] epoch=56, batch_id=10, loss=0.046837, lr=0.000350,acc=0.988 ETA 55:24:35
[TRAIN] epoch=56, batch_id=20, loss=0.050427, lr=0.000355,acc=0.986 ETA 04:41:38
[TRAIN] epoch=56, batch_id=30, loss=0.063776, lr=0.000360,acc=0.981 ETA 04:08:31
[TRAIN] epoch=56, batch_id=40, loss=0.068962, lr=0.000365,acc=0.980 ETA 03:44:47
[TRAIN] epoch=56, batch_id=50, loss=0.063449, lr=0.000370,acc=0.981 ETA 03:48:48
[TRAIN] epoch=56, batch_id=60, loss=0.058943, lr=0.000375,acc=0.983 ETA 03:54:32
[TRAIN] epoch=56, batch_id=70, loss=0.055584, lr=0.000380,acc=0.983 ETA 04:24:50
[TRAIN] epoch=56, batch_id=80, loss=0.059903, lr=0.000385,acc=0.982 ETA 04:04:34
[TRAIN] epoch=56, batch_id=90, loss=0.058045, lr=0.000390,acc=0.983 ETA 04:03:30
[TRAIN] epoch=56, batch_id=100, loss=0.055121, lr=0.000395,acc=0.984 ETA 04:05:03
[TRAIN] epoch=56, batch_id=110, loss=0.057098, lr=0.000401,acc=0.984 ETA 04:40:03
[TRAIN] epoch=56, batch_id=120, loss=0.056605, lr=0.000406,acc=0.985 ETA 04:25:19
[TRAIN] epoch=56, batch_id=130, loss=0.057053, lr=0.000411,acc=0.984 ETA 03:47:15
[TRAIN] epoch=56, batch_id=140, loss=0.056133, lr=0.000416,acc=0.984 ETA 03:38:51
[TRAIN] epoch=56, batch_id=150, loss=0.055360, lr=0.000421,acc=0.984 ETA 05:55:44
[TRAIN] epoch=56, batch_id=160, loss=0.056536, lr=0.000426,acc=0.984 ETA 06:12:51
[TRAIN] epoch=56, batch_id=170, loss=0.057033, lr=0.000432,acc=0.983 ETA 07:51:38
[TRAIN] epoch=56, batch_id=180, loss=0.055646, lr=0.000437,acc=0.984 ETA 03:38:26
[TRAIN] epoch=56, batch_id=190, loss=0.055440, lr=0.000442,acc=0.984 ETA 03:39:00
[TRAIN] epoch=56, batch_id=200, loss=0.055374, lr=0.000447,acc=0.984 ETA 03:39:58
[TRAIN] epoch=56, batch_id=210, loss=0.055634, lr=0.000453,acc=0.984 ETA 03:37:48
[TRAIN] epoch=56, batch_id=220, loss=0.055950, lr=0.000458,acc=0.984 ETA 03:57:42
[TRAIN] epoch=56, batch_id=230, loss=0.058566, lr=0.000463,acc=0.983 ETA 03:36:02
[TRAIN] epoch=56, batch_id=240, loss=0.057925, lr=0.000468,acc=0.983 ETA 05:17:44
[TRAIN] epoch=56, batch_id=250, loss=0.057658, lr=0.000474,acc=0.983 ETA 03:32:40
[TRAIN] epoch=56, batch_id=260, loss=0.057963, lr=0.000479,acc=0.983 ETA 03:35:29
[TRAIN] epoch=56, batch_id=270, loss=0.057128, lr=0.000484,acc=0.983 ETA 03:32:34
[TRAIN] epoch=56, batch_id=280, loss=0.057050, lr=0.000489,acc=0.983 ETA 05:02:44
[TRAIN] epoch=56, batch_id=290, loss=0.057394, lr=0.000495,acc=0.983 ETA 03:37:54
[EVAL] epoch=56

Evaluating top_k_accuracy ...

top1_acc	0.7819
top5_acc	0.9416

Evaluating mean_class_accuracy ...

mean_acc	0.7826
[TRAIN] epoch=57, batch_id=2, loss=0.033000, lr=0.000500,acc=1.000 ETA 53:02:03
[TRAIN] epoch=57, batch_id=12, loss=0.043760, lr=0.000505,acc=0.992 ETA 03:36:39
[TRAIN] epoch=57, batch_id=22, loss=0.056161, lr=0.000511,acc=0.984 ETA 03:51:23
[TRAIN] epoch=57, batch_id=32, loss=0.055003, lr=0.000516,acc=0.985 ETA 04:11:59
[TRAIN] epoch=57, batch_id=42, loss=0.052856, lr=0.000521,acc=0.985 ETA 05:39:28
[TRAIN] epoch=57, batch_id=52, loss=0.052463, lr=0.000526,acc=0.984 ETA 03:57:04
[TRAIN] epoch=57, batch_id=62, loss=0.051532, lr=0.000532,acc=0.984 ETA 03:33:29
[TRAIN] epoch=57, batch_id=72, loss=0.052160, lr=0.000537,acc=0.984 ETA 03:37:16
[TRAIN] epoch=57, batch_id=82, loss=0.048508, lr=0.000542,acc=0.986 ETA 03:31:57
[TRAIN] epoch=57, batch_id=92, loss=0.054038, lr=0.000547,acc=0.984 ETA 03:35:42
[TRAIN] epoch=57, batch_id=102, loss=0.053514, lr=0.000553,acc=0.984 ETA 03:32:51
[TRAIN] epoch=57, batch_id=112, loss=0.053904, lr=0.000558,acc=0.985 ETA 03:45:02
[TRAIN] epoch=57, batch_id=122, loss=0.053321, lr=0.000563,acc=0.985 ETA 03:34:45
[TRAIN] epoch=57, batch_id=132, loss=0.053484, lr=0.000568,acc=0.985 ETA 04:17:02
[TRAIN] epoch=57, batch_id=142, loss=0.054362, lr=0.000574,acc=0.985 ETA 05:28:37
[TRAIN] epoch=57, batch_id=152, loss=0.055142, lr=0.000579,acc=0.985 ETA 04:18:31
[TRAIN] epoch=57, batch_id=162, loss=0.054927, lr=0.000584,acc=0.985 ETA 03:31:20
[TRAIN] epoch=57, batch_id=172, loss=0.055312, lr=0.000589,acc=0.984 ETA 04:14:01
[TRAIN] epoch=57, batch_id=182, loss=0.055462, lr=0.000594,acc=0.984 ETA 07:39:53
[TRAIN] epoch=57, batch_id=192, loss=0.057996, lr=0.000599,acc=0.984 ETA 06:07:03
[TRAIN] epoch=57, batch_id=202, loss=0.059957, lr=0.000605,acc=0.983 ETA 05:57:50
[TRAIN] epoch=57, batch_id=212, loss=0.058125, lr=0.000610,acc=0.984 ETA 03:48:10
[TRAIN] epoch=57, batch_id=222, loss=0.058452, lr=0.000615,acc=0.984 ETA 03:30:02
[TRAIN] epoch=57, batch_id=232, loss=0.058700, lr=0.000620,acc=0.984 ETA 03:31:45
[TRAIN] epoch=57, batch_id=242, loss=0.059036, lr=0.000625,acc=0.983 ETA 03:29:40
[TRAIN] epoch=57, batch_id=252, loss=0.059552, lr=0.000630,acc=0.983 ETA 03:44:07
[TRAIN] epoch=57, batch_id=262, loss=0.057950, lr=0.000635,acc=0.983 ETA 03:28:24
[TRAIN] epoch=57, batch_id=272, loss=0.057475, lr=0.000640,acc=0.983 ETA 03:37:13
[TRAIN] epoch=57, batch_id=282, loss=0.058585, lr=0.000645,acc=0.983 ETA 03:34:41
[TRAIN] epoch=57, batch_id=292, loss=0.060803, lr=0.000650,acc=0.982 ETA 05:11:11
[EVAL] epoch=57

Evaluating top_k_accuracy ...

top1_acc	0.7806
top5_acc	0.9448

Evaluating mean_class_accuracy ...

mean_acc	0.7804
[TRAIN] epoch=58, batch_id=4, loss=0.054676, lr=0.000656,acc=0.984 ETA 52:18:38
[TRAIN] epoch=58, batch_id=14, loss=0.057291, lr=0.000661,acc=0.984 ETA 03:28:51
[TRAIN] epoch=58, batch_id=24, loss=0.053082, lr=0.000665,acc=0.984 ETA 03:39:22
[TRAIN] epoch=58, batch_id=34, loss=0.064047, lr=0.000670,acc=0.984 ETA 03:34:17
[TRAIN] epoch=58, batch_id=44, loss=0.062916, lr=0.000675,acc=0.984 ETA 03:39:13
[TRAIN] epoch=58, batch_id=54, loss=0.063512, lr=0.000680,acc=0.983 ETA 03:30:04
[TRAIN] epoch=58, batch_id=64, loss=0.057054, lr=0.000685,acc=0.985 ETA 03:30:50
[TRAIN] epoch=58, batch_id=74, loss=0.054554, lr=0.000690,acc=0.986 ETA 03:29:55
[TRAIN] epoch=58, batch_id=84, loss=0.054909, lr=0.000695,acc=0.985 ETA 04:06:42
[TRAIN] epoch=58, batch_id=94, loss=0.057211, lr=0.000700,acc=0.984 ETA 03:43:53
[TRAIN] epoch=58, batch_id=104, loss=0.059668, lr=0.000705,acc=0.983 ETA 03:34:14
[TRAIN] epoch=58, batch_id=114, loss=0.059051, lr=0.000709,acc=0.984 ETA 03:28:08
[TRAIN] epoch=58, batch_id=124, loss=0.058107, lr=0.000714,acc=0.984 ETA 03:27:57
[TRAIN] epoch=58, batch_id=134, loss=0.058325, lr=0.000719,acc=0.984 ETA 03:26:10
[TRAIN] epoch=58, batch_id=144, loss=0.056815, lr=0.000724,acc=0.985 ETA 03:27:06
[TRAIN] epoch=58, batch_id=154, loss=0.055776, lr=0.000728,acc=0.985 ETA 06:49:48
[TRAIN] epoch=58, batch_id=164, loss=0.055405, lr=0.000733,acc=0.985 ETA 03:30:43
[TRAIN] epoch=58, batch_id=174, loss=0.056843, lr=0.000738,acc=0.984 ETA 03:24:29
[TRAIN] epoch=58, batch_id=184, loss=0.056622, lr=0.000742,acc=0.984 ETA 03:26:54
[TRAIN] epoch=58, batch_id=194, loss=0.056351, lr=0.000747,acc=0.984 ETA 03:25:47
[TRAIN] epoch=58, batch_id=204, loss=0.054220, lr=0.000752,acc=0.985 ETA 03:25:34
[TRAIN] epoch=58, batch_id=214, loss=0.053459, lr=0.000756,acc=0.985 ETA 03:23:20
[TRAIN] epoch=58, batch_id=224, loss=0.052113, lr=0.000761,acc=0.985 ETA 03:29:38
[TRAIN] epoch=58, batch_id=234, loss=0.053453, lr=0.000765,acc=0.985 ETA 03:27:45
[TRAIN] epoch=58, batch_id=244, loss=0.052570, lr=0.000770,acc=0.985 ETA 03:53:49
[TRAIN] epoch=58, batch_id=254, loss=0.052264, lr=0.000774,acc=0.985 ETA 03:42:30
[TRAIN] epoch=58, batch_id=264, loss=0.052424, lr=0.000778,acc=0.985 ETA 03:24:42
[TRAIN] epoch=58, batch_id=274, loss=0.052982, lr=0.000783,acc=0.984 ETA 03:52:47
[TRAIN] epoch=58, batch_id=284, loss=0.053689, lr=0.000787,acc=0.984 ETA 03:25:52
[TRAIN] epoch=58, batch_id=294, loss=0.054997, lr=0.000791,acc=0.984 ETA 04:28:32
[EVAL] epoch=58

Evaluating top_k_accuracy ...

top1_acc	0.7798
top5_acc	0.9421

Evaluating mean_class_accuracy ...

mean_acc	0.7788
[TRAIN] epoch=59, batch_id=6, loss=0.057710, lr=0.000796,acc=0.979 ETA 53:45:55
[TRAIN] epoch=59, batch_id=16, loss=0.056288, lr=0.000800,acc=0.980 ETA 03:37:18
[TRAIN] epoch=59, batch_id=26, loss=0.052780, lr=0.000804,acc=0.981 ETA 04:09:21
[TRAIN] epoch=59, batch_id=36, loss=0.046960, lr=0.000808,acc=0.984 ETA 03:53:00
[TRAIN] epoch=59, batch_id=46, loss=0.042360, lr=0.000812,acc=0.986 ETA 05:07:05
[TRAIN] epoch=59, batch_id=56, loss=0.047115, lr=0.000816,acc=0.985 ETA 04:50:20
[TRAIN] epoch=59, batch_id=66, loss=0.047250, lr=0.000820,acc=0.986 ETA 04:38:25
[TRAIN] epoch=59, batch_id=76, loss=0.047765, lr=0.000825,acc=0.987 ETA 03:27:55
[TRAIN] epoch=59, batch_id=86, loss=0.049148, lr=0.000829,acc=0.986 ETA 03:23:42
[TRAIN] epoch=59, batch_id=96, loss=0.048121, lr=0.000832,acc=0.985 ETA 03:30:41
[TRAIN] epoch=59, batch_id=106, loss=0.048603, lr=0.000836,acc=0.985 ETA 05:01:45
[TRAIN] epoch=59, batch_id=116, loss=0.049208, lr=0.000840,acc=0.985 ETA 04:17:46
[TRAIN] epoch=59, batch_id=126, loss=0.050999, lr=0.000844,acc=0.985 ETA 03:24:08
[TRAIN] epoch=59, batch_id=136, loss=0.049029, lr=0.000848,acc=0.985 ETA 03:23:34
[TRAIN] epoch=59, batch_id=146, loss=0.049924, lr=0.000852,acc=0.985 ETA 03:23:10
[TRAIN] epoch=59, batch_id=156, loss=0.050141, lr=0.000855,acc=0.984 ETA 03:54:42
[TRAIN] epoch=59, batch_id=166, loss=0.051715, lr=0.000859,acc=0.983 ETA 05:09:43
[TRAIN] epoch=59, batch_id=176, loss=0.051041, lr=0.000863,acc=0.984 ETA 04:25:13
[TRAIN] epoch=59, batch_id=186, loss=0.051949, lr=0.000866,acc=0.984 ETA 03:20:20
[TRAIN] epoch=59, batch_id=196, loss=0.051590, lr=0.000870,acc=0.984 ETA 03:26:21
[TRAIN] epoch=59, batch_id=206, loss=0.052415, lr=0.000873,acc=0.984 ETA 03:23:51
[TRAIN] epoch=59, batch_id=216, loss=0.055423, lr=0.000877,acc=0.983 ETA 03:44:26
[TRAIN] epoch=59, batch_id=226, loss=0.055193, lr=0.000880,acc=0.983 ETA 05:10:05
[TRAIN] epoch=59, batch_id=236, loss=0.055776, lr=0.000884,acc=0.983 ETA 05:05:37
[TRAIN] epoch=59, batch_id=246, loss=0.056042, lr=0.000887,acc=0.983 ETA 08:36:08
[TRAIN] epoch=59, batch_id=256, loss=0.055910, lr=0.000890,acc=0.983 ETA 08:22:15
[TRAIN] epoch=59, batch_id=266, loss=0.057610, lr=0.000894,acc=0.983 ETA 04:37:42
[TRAIN] epoch=59, batch_id=276, loss=0.057934, lr=0.000897,acc=0.983 ETA 03:21:19
[TRAIN] epoch=59, batch_id=286, loss=0.056824, lr=0.000900,acc=0.983 ETA 03:26:14
[TRAIN] epoch=59, batch_id=296, loss=0.057726, lr=0.000903,acc=0.983 ETA 03:28:41
[EVAL] epoch=59

Evaluating top_k_accuracy ...

top1_acc	0.7787
top5_acc	0.9429

Evaluating mean_class_accuracy ...

mean_acc	0.7780
[TRAIN] epoch=60, batch_id=8, loss=0.063641, lr=0.000906,acc=0.980 ETA 49:06:54
[TRAIN] epoch=60, batch_id=18, loss=0.078994, lr=0.000909,acc=0.974 ETA 04:43:50
[TRAIN] epoch=60, batch_id=28, loss=0.064357, lr=0.000912,acc=0.980 ETA 04:41:13
[TRAIN] epoch=60, batch_id=38, loss=0.067482, lr=0.000915,acc=0.979 ETA 03:48:27
[TRAIN] epoch=60, batch_id=48, loss=0.067679, lr=0.000918,acc=0.978 ETA 03:22:08
[TRAIN] epoch=60, batch_id=58, loss=0.064566, lr=0.000921,acc=0.980 ETA 04:09:42
[TRAIN] epoch=60, batch_id=68, loss=0.065253, lr=0.000924,acc=0.979 ETA 03:18:48
[TRAIN] epoch=60, batch_id=78, loss=0.071539, lr=0.000927,acc=0.978 ETA 03:24:30
[TRAIN] epoch=60, batch_id=88, loss=0.068638, lr=0.000929,acc=0.978 ETA 03:21:04
[TRAIN] epoch=60, batch_id=98, loss=0.071342, lr=0.000932,acc=0.978 ETA 03:32:02
[TRAIN] epoch=60, batch_id=108, loss=0.073694, lr=0.000935,acc=0.978 ETA 03:23:08
[TRAIN] epoch=60, batch_id=118, loss=0.072421, lr=0.000937,acc=0.978 ETA 03:30:35
[TRAIN] epoch=60, batch_id=128, loss=0.073567, lr=0.000940,acc=0.978 ETA 03:21:16
[TRAIN] epoch=60, batch_id=138, loss=0.072214, lr=0.000942,acc=0.978 ETA 03:24:01
[TRAIN] epoch=60, batch_id=148, loss=0.073513, lr=0.000945,acc=0.977 ETA 03:15:31
[TRAIN] epoch=60, batch_id=158, loss=0.072088, lr=0.000947,acc=0.978 ETA 03:35:38
[TRAIN] epoch=60, batch_id=168, loss=0.073358, lr=0.000949,acc=0.977 ETA 07:25:58
[TRAIN] epoch=60, batch_id=178, loss=0.072110, lr=0.000952,acc=0.978 ETA 06:05:04
[TRAIN] epoch=60, batch_id=188, loss=0.072775, lr=0.000954,acc=0.977 ETA 03:28:00
[TRAIN] epoch=60, batch_id=198, loss=0.072640, lr=0.000956,acc=0.977 ETA 03:17:11
[TRAIN] epoch=60, batch_id=208, loss=0.075280, lr=0.000958,acc=0.977 ETA 03:19:10
[TRAIN] epoch=60, batch_id=218, loss=0.073168, lr=0.000960,acc=0.977 ETA 03:20:18
[TRAIN] epoch=60, batch_id=228, loss=0.073127, lr=0.000962,acc=0.978 ETA 03:16:46
[TRAIN] epoch=60, batch_id=238, loss=0.072190, lr=0.000964,acc=0.978 ETA 03:15:41
[TRAIN] epoch=60, batch_id=248, loss=0.070542, lr=0.000966,acc=0.979 ETA 03:12:37
[TRAIN] epoch=60, batch_id=258, loss=0.070324, lr=0.000968,acc=0.979 ETA 03:17:24
[TRAIN] epoch=60, batch_id=268, loss=0.069378, lr=0.000970,acc=0.979 ETA 03:19:57
[TRAIN] epoch=60, batch_id=278, loss=0.068845, lr=0.000972,acc=0.979 ETA 03:16:03
[TRAIN] epoch=60, batch_id=288, loss=0.070370, lr=0.000974,acc=0.979 ETA 03:15:34
[TRAIN] epoch=60, batch_id=298, loss=0.071551, lr=0.000975,acc=0.979 ETA 03:16:24
[EVAL] epoch=60

Evaluating top_k_accuracy ...

top1_acc	0.7777
top5_acc	0.9434

Evaluating mean_class_accuracy ...

mean_acc	0.7759
[TRAIN] epoch=61, batch_id=10, loss=0.071618, lr=0.000977,acc=0.978 ETA 47:32:07
[TRAIN] epoch=61, batch_id=20, loss=0.074408, lr=0.000978,acc=0.977 ETA 03:22:27
[TRAIN] epoch=61, batch_id=30, loss=0.070610, lr=0.000980,acc=0.976 ETA 03:32:40
[TRAIN] epoch=61, batch_id=40, loss=0.064835, lr=0.000981,acc=0.977 ETA 03:18:17
[TRAIN] epoch=61, batch_id=50, loss=0.062411, lr=0.000983,acc=0.979 ETA 03:11:46
[TRAIN] epoch=61, batch_id=60, loss=0.061167, lr=0.000984,acc=0.980 ETA 03:32:59
[TRAIN] epoch=61, batch_id=70, loss=0.070634, lr=0.000985,acc=0.979 ETA 03:12:45
[TRAIN] epoch=61, batch_id=80, loss=0.074812, lr=0.000987,acc=0.977 ETA 03:57:47
[TRAIN] epoch=61, batch_id=90, loss=0.080390, lr=0.000988,acc=0.976 ETA 03:13:59
[TRAIN] epoch=61, batch_id=100, loss=0.080457, lr=0.000989,acc=0.977 ETA 03:44:45
[TRAIN] epoch=61, batch_id=110, loss=0.076634, lr=0.000990,acc=0.978 ETA 03:36:11
[TRAIN] epoch=61, batch_id=120, loss=0.073396, lr=0.000991,acc=0.978 ETA 03:23:54
[TRAIN] epoch=61, batch_id=130, loss=0.074854, lr=0.000992,acc=0.978 ETA 03:13:58
[TRAIN] epoch=61, batch_id=140, loss=0.074749, lr=0.000993,acc=0.977 ETA 03:21:28
[TRAIN] epoch=61, batch_id=150, loss=0.073527, lr=0.000994,acc=0.978 ETA 03:19:34
[TRAIN] epoch=61, batch_id=160, loss=0.073483, lr=0.000995,acc=0.978 ETA 03:12:22
[TRAIN] epoch=61, batch_id=170, loss=0.071542, lr=0.000995,acc=0.978 ETA 03:15:57
[TRAIN] epoch=61, batch_id=180, loss=0.068818, lr=0.000996,acc=0.979 ETA 03:10:52
[TRAIN] epoch=61, batch_id=190, loss=0.068756, lr=0.000997,acc=0.979 ETA 03:22:36
[TRAIN] epoch=61, batch_id=200, loss=0.070761, lr=0.000997,acc=0.979 ETA 03:09:57
[TRAIN] epoch=61, batch_id=210, loss=0.070060, lr=0.000998,acc=0.979 ETA 03:27:54
[TRAIN] epoch=61, batch_id=220, loss=0.069005, lr=0.000998,acc=0.980 ETA 03:08:10
[TRAIN] epoch=61, batch_id=230, loss=0.068226, lr=0.000999,acc=0.980 ETA 03:12:49
[TRAIN] epoch=61, batch_id=240, loss=0.068180, lr=0.000999,acc=0.979 ETA 03:17:34
[TRAIN] epoch=61, batch_id=250, loss=0.068346, lr=0.000999,acc=0.979 ETA 03:46:54
[TRAIN] epoch=61, batch_id=260, loss=0.068504, lr=0.001000,acc=0.979 ETA 03:08:02
[TRAIN] epoch=61, batch_id=270, loss=0.068041, lr=0.001000,acc=0.979 ETA 03:16:29
[TRAIN] epoch=61, batch_id=280, loss=0.068249, lr=0.001000,acc=0.979 ETA 03:08:20
[TRAIN] epoch=61, batch_id=290, loss=0.068088, lr=0.001000,acc=0.979 ETA 03:50:03
[EVAL] epoch=61

Evaluating top_k_accuracy ...

top1_acc	0.7748
top5_acc	0.9408

Evaluating mean_class_accuracy ...

mean_acc	0.7745
[TRAIN] epoch=62, batch_id=2, loss=0.022584, lr=0.001000,acc=1.000 ETA 47:15:28
[TRAIN] epoch=62, batch_id=12, loss=0.053896, lr=0.001000,acc=0.984 ETA 03:20:18
[TRAIN] epoch=62, batch_id=22, loss=0.045002, lr=0.001000,acc=0.984 ETA 03:13:18
[TRAIN] epoch=62, batch_id=32, loss=0.047754, lr=0.001000,acc=0.982 ETA 03:15:53
[TRAIN] epoch=62, batch_id=42, loss=0.057333, lr=0.001000,acc=0.980 ETA 03:11:50
[TRAIN] epoch=62, batch_id=52, loss=0.062633, lr=0.000999,acc=0.979 ETA 03:11:52
[TRAIN] epoch=62, batch_id=62, loss=0.063252, lr=0.000999,acc=0.978 ETA 03:12:23
[TRAIN] epoch=62, batch_id=72, loss=0.065623, lr=0.000999,acc=0.978 ETA 03:06:37
[TRAIN] epoch=62, batch_id=82, loss=0.066687, lr=0.000998,acc=0.978 ETA 04:42:25
[TRAIN] epoch=62, batch_id=92, loss=0.067327, lr=0.000998,acc=0.978 ETA 03:30:42
[TRAIN] epoch=62, batch_id=102, loss=0.067666, lr=0.000997,acc=0.978 ETA 03:07:13
[TRAIN] epoch=62, batch_id=112, loss=0.066065, lr=0.000997,acc=0.979 ETA 03:07:32
[TRAIN] epoch=62, batch_id=122, loss=0.066292, lr=0.000996,acc=0.980 ETA 03:37:42
[TRAIN] epoch=62, batch_id=132, loss=0.068004, lr=0.000995,acc=0.979 ETA 04:36:35
[TRAIN] epoch=62, batch_id=142, loss=0.066592, lr=0.000995,acc=0.980 ETA 05:18:41
[TRAIN] epoch=62, batch_id=152, loss=0.066204, lr=0.000994,acc=0.980 ETA 06:08:06
[TRAIN] epoch=62, batch_id=162, loss=0.064329, lr=0.000993,acc=0.981 ETA 03:12:54
[TRAIN] epoch=62, batch_id=172, loss=0.067102, lr=0.000992,acc=0.981 ETA 03:15:28
[TRAIN] epoch=62, batch_id=182, loss=0.067161, lr=0.000991,acc=0.980 ETA 03:16:30
[TRAIN] epoch=62, batch_id=192, loss=0.066889, lr=0.000990,acc=0.980 ETA 03:11:09
[TRAIN] epoch=62, batch_id=202, loss=0.065629, lr=0.000989,acc=0.981 ETA 04:29:44
[TRAIN] epoch=62, batch_id=212, loss=0.065412, lr=0.000988,acc=0.981 ETA 03:15:07
[TRAIN] epoch=62, batch_id=222, loss=0.065918, lr=0.000987,acc=0.981 ETA 03:08:06
[TRAIN] epoch=62, batch_id=232, loss=0.065080, lr=0.000985,acc=0.981 ETA 03:08:45
[TRAIN] epoch=62, batch_id=242, loss=0.065708, lr=0.000984,acc=0.981 ETA 03:15:35
[TRAIN] epoch=62, batch_id=252, loss=0.065295, lr=0.000983,acc=0.981 ETA 03:22:12
[TRAIN] epoch=62, batch_id=262, loss=0.065148, lr=0.000981,acc=0.981 ETA 03:08:04
[TRAIN] epoch=62, batch_id=272, loss=0.065632, lr=0.000980,acc=0.981 ETA 03:19:41
[TRAIN] epoch=62, batch_id=282, loss=0.065005, lr=0.000978,acc=0.981 ETA 03:16:39
[TRAIN] epoch=62, batch_id=292, loss=0.064831, lr=0.000977,acc=0.981 ETA 03:11:31
[EVAL] epoch=62

Evaluating top_k_accuracy ...

top1_acc	0.7793
top5_acc	0.9437

Evaluating mean_class_accuracy ...

mean_acc	0.7788
[TRAIN] epoch=63, batch_id=4, loss=0.042637, lr=0.000975,acc=0.977 ETA 47:20:49
[TRAIN] epoch=63, batch_id=14, loss=0.040317, lr=0.000974,acc=0.984 ETA 03:05:57
[TRAIN] epoch=63, batch_id=24, loss=0.052651, lr=0.000972,acc=0.979 ETA 03:04:40
[TRAIN] epoch=63, batch_id=34, loss=0.050550, lr=0.000970,acc=0.980 ETA 03:02:31
[TRAIN] epoch=63, batch_id=44, loss=0.052152, lr=0.000968,acc=0.979 ETA 03:01:54
[TRAIN] epoch=63, batch_id=54, loss=0.047095, lr=0.000966,acc=0.981 ETA 04:00:21
[TRAIN] epoch=63, batch_id=64, loss=0.050486, lr=0.000964,acc=0.981 ETA 03:04:19
[TRAIN] epoch=63, batch_id=74, loss=0.053520, lr=0.000962,acc=0.981 ETA 03:04:52
[TRAIN] epoch=63, batch_id=84, loss=0.054377, lr=0.000960,acc=0.980 ETA 02:59:29
[TRAIN] epoch=63, batch_id=94, loss=0.053170, lr=0.000958,acc=0.980 ETA 03:06:03
[TRAIN] epoch=63, batch_id=104, loss=0.054736, lr=0.000956,acc=0.980 ETA 03:00:12
[TRAIN] epoch=63, batch_id=114, loss=0.057190, lr=0.000954,acc=0.979 ETA 03:06:46
[TRAIN] epoch=63, batch_id=124, loss=0.057050, lr=0.000952,acc=0.980 ETA 02:59:16
[TRAIN] epoch=63, batch_id=134, loss=0.060227, lr=0.000949,acc=0.979 ETA 03:03:23
[TRAIN] epoch=63, batch_id=144, loss=0.059647, lr=0.000947,acc=0.979 ETA 06:29:27
[TRAIN] epoch=63, batch_id=154, loss=0.059581, lr=0.000945,acc=0.980 ETA 04:14:12
[TRAIN] epoch=63, batch_id=164, loss=0.058866, lr=0.000942,acc=0.980 ETA 03:08:28
[TRAIN] epoch=63, batch_id=174, loss=0.060405, lr=0.000940,acc=0.980 ETA 03:09:07
[TRAIN] epoch=63, batch_id=184, loss=0.059844, lr=0.000937,acc=0.980 ETA 03:03:53
[TRAIN] epoch=63, batch_id=194, loss=0.060740, lr=0.000935,acc=0.980 ETA 03:04:28
[TRAIN] epoch=63, batch_id=204, loss=0.060000, lr=0.000932,acc=0.981 ETA 04:24:14
[TRAIN] epoch=63, batch_id=214, loss=0.059675, lr=0.000929,acc=0.980 ETA 04:11:03
[TRAIN] epoch=63, batch_id=224, loss=0.059371, lr=0.000927,acc=0.980 ETA 03:06:09
[TRAIN] epoch=63, batch_id=234, loss=0.059490, lr=0.000924,acc=0.981 ETA 03:02:41
[TRAIN] epoch=63, batch_id=244, loss=0.059593, lr=0.000921,acc=0.981 ETA 03:00:19
[TRAIN] epoch=63, batch_id=254, loss=0.060094, lr=0.000918,acc=0.981 ETA 03:07:40
[TRAIN] epoch=63, batch_id=264, loss=0.059264, lr=0.000915,acc=0.981 ETA 03:05:44
[TRAIN] epoch=63, batch_id=274, loss=0.059560, lr=0.000912,acc=0.981 ETA 03:13:25
[TRAIN] epoch=63, batch_id=284, loss=0.058788, lr=0.000909,acc=0.981 ETA 03:19:07
[TRAIN] epoch=63, batch_id=294, loss=0.058028, lr=0.000906,acc=0.982 ETA 03:02:09
[EVAL] epoch=63

Evaluating top_k_accuracy ...

top1_acc	0.7835
top5_acc	0.9482

Evaluating mean_class_accuracy ...

mean_acc	0.7851
[TRAIN] epoch=64, batch_id=6, loss=0.099545, lr=0.000903,acc=0.974 ETA 45:13:40
[TRAIN] epoch=64, batch_id=16, loss=0.071867, lr=0.000900,acc=0.980 ETA 03:00:29
[TRAIN] epoch=64, batch_id=26, loss=0.060908, lr=0.000897,acc=0.980 ETA 03:02:06
[TRAIN] epoch=64, batch_id=36, loss=0.058860, lr=0.000894,acc=0.980 ETA 03:04:53
[TRAIN] epoch=64, batch_id=46, loss=0.056446, lr=0.000890,acc=0.980 ETA 03:12:15
[TRAIN] epoch=64, batch_id=56, loss=0.057379, lr=0.000887,acc=0.980 ETA 04:12:19
[TRAIN] epoch=64, batch_id=66, loss=0.055862, lr=0.000884,acc=0.980 ETA 03:26:44
[TRAIN] epoch=64, batch_id=76, loss=0.057437, lr=0.000880,acc=0.980 ETA 03:16:18
[TRAIN] epoch=64, batch_id=86, loss=0.056077, lr=0.000877,acc=0.981 ETA 04:30:35
[TRAIN] epoch=64, batch_id=96, loss=0.052370, lr=0.000873,acc=0.983 ETA 03:06:30
[TRAIN] epoch=64, batch_id=106, loss=0.051128, lr=0.000870,acc=0.983 ETA 04:42:58
[TRAIN] epoch=64, batch_id=116, loss=0.050765, lr=0.000866,acc=0.983 ETA 05:56:00
[TRAIN] epoch=64, batch_id=126, loss=0.051220, lr=0.000863,acc=0.983 ETA 07:26:26
[TRAIN] epoch=64, batch_id=136, loss=0.052037, lr=0.000859,acc=0.983 ETA 04:40:33
[TRAIN] epoch=64, batch_id=146, loss=0.051528, lr=0.000855,acc=0.983 ETA 04:41:19
[TRAIN] epoch=64, batch_id=156, loss=0.050948, lr=0.000852,acc=0.984 ETA 04:05:50
[TRAIN] epoch=64, batch_id=166, loss=0.050549, lr=0.000848,acc=0.984 ETA 03:01:03
[TRAIN] epoch=64, batch_id=176, loss=0.049140, lr=0.000844,acc=0.984 ETA 03:15:24
[TRAIN] epoch=64, batch_id=186, loss=0.048669, lr=0.000840,acc=0.984 ETA 02:59:49
[TRAIN] epoch=64, batch_id=196, loss=0.048245, lr=0.000836,acc=0.984 ETA 04:06:02
[TRAIN] epoch=64, batch_id=206, loss=0.048389, lr=0.000832,acc=0.984 ETA 02:59:36
[TRAIN] epoch=64, batch_id=216, loss=0.047434, lr=0.000829,acc=0.985 ETA 03:19:22
[TRAIN] epoch=64, batch_id=226, loss=0.047118, lr=0.000825,acc=0.985 ETA 03:01:50
[TRAIN] epoch=64, batch_id=236, loss=0.046610, lr=0.000820,acc=0.985 ETA 03:00:04
[TRAIN] epoch=64, batch_id=246, loss=0.045930, lr=0.000816,acc=0.986 ETA 02:58:38
[TRAIN] epoch=64, batch_id=256, loss=0.045461, lr=0.000812,acc=0.986 ETA 03:01:55
[TRAIN] epoch=64, batch_id=266, loss=0.044854, lr=0.000808,acc=0.986 ETA 03:03:46
[TRAIN] epoch=64, batch_id=276, loss=0.046132, lr=0.000804,acc=0.985 ETA 03:02:32
[TRAIN] epoch=64, batch_id=286, loss=0.046406, lr=0.000800,acc=0.985 ETA 03:13:12
[TRAIN] epoch=64, batch_id=296, loss=0.046269, lr=0.000796,acc=0.985 ETA 02:58:53
[EVAL] epoch=64

Evaluating top_k_accuracy ...

top1_acc	0.7737
top5_acc	0.9426

Evaluating mean_class_accuracy ...

mean_acc	0.7734
[TRAIN] epoch=65, batch_id=8, loss=0.084626, lr=0.000791,acc=0.980 ETA 44:43:42
[TRAIN] epoch=65, batch_id=18, loss=0.077770, lr=0.000787,acc=0.981 ETA 02:52:23
[TRAIN] epoch=65, batch_id=28, loss=0.062544, lr=0.000783,acc=0.984 ETA 02:53:35
[TRAIN] epoch=65, batch_id=38, loss=0.051916, lr=0.000778,acc=0.987 ETA 02:53:27
[TRAIN] epoch=65, batch_id=48, loss=0.049947, lr=0.000774,acc=0.986 ETA 03:16:44
[TRAIN] epoch=65, batch_id=58, loss=0.050791, lr=0.000770,acc=0.986 ETA 03:00:36
[TRAIN] epoch=65, batch_id=68, loss=0.052321, lr=0.000765,acc=0.985 ETA 02:58:21
[TRAIN] epoch=65, batch_id=78, loss=0.054475, lr=0.000761,acc=0.984 ETA 02:52:14
[TRAIN] epoch=65, batch_id=88, loss=0.051486, lr=0.000756,acc=0.985 ETA 03:14:29
[TRAIN] epoch=65, batch_id=98, loss=0.050530, lr=0.000752,acc=0.985 ETA 03:54:57
[TRAIN] epoch=65, batch_id=108, loss=0.049753, lr=0.000747,acc=0.985 ETA 03:44:30
[TRAIN] epoch=65, batch_id=118, loss=0.049447, lr=0.000742,acc=0.984 ETA 03:31:33
[TRAIN] epoch=65, batch_id=128, loss=0.051978, lr=0.000738,acc=0.983 ETA 02:58:18
[TRAIN] epoch=65, batch_id=138, loss=0.049541, lr=0.000733,acc=0.984 ETA 02:54:35
[TRAIN] epoch=65, batch_id=148, loss=0.048171, lr=0.000728,acc=0.985 ETA 03:31:48
[TRAIN] epoch=65, batch_id=158, loss=0.047647, lr=0.000724,acc=0.985 ETA 02:51:08
[TRAIN] epoch=65, batch_id=168, loss=0.046234, lr=0.000719,acc=0.986 ETA 03:11:01
[TRAIN] epoch=65, batch_id=178, loss=0.046387, lr=0.000714,acc=0.986 ETA 02:55:02
[TRAIN] epoch=65, batch_id=188, loss=0.047029, lr=0.000709,acc=0.986 ETA 03:11:19
[TRAIN] epoch=65, batch_id=198, loss=0.047441, lr=0.000705,acc=0.985 ETA 03:03:19
[TRAIN] epoch=65, batch_id=208, loss=0.049899, lr=0.000700,acc=0.984 ETA 02:53:14
[TRAIN] epoch=65, batch_id=218, loss=0.050072, lr=0.000695,acc=0.984 ETA 03:14:15
[TRAIN] epoch=65, batch_id=228, loss=0.049112, lr=0.000690,acc=0.984 ETA 02:52:00
[TRAIN] epoch=65, batch_id=238, loss=0.047970, lr=0.000685,acc=0.984 ETA 02:51:48
[TRAIN] epoch=65, batch_id=248, loss=0.047958, lr=0.000680,acc=0.984 ETA 02:58:13
[TRAIN] epoch=65, batch_id=258, loss=0.047894, lr=0.000675,acc=0.984 ETA 04:07:04
[TRAIN] epoch=65, batch_id=268, loss=0.047894, lr=0.000670,acc=0.984 ETA 02:55:36
[TRAIN] epoch=65, batch_id=278, loss=0.048638, lr=0.000665,acc=0.984 ETA 02:51:40
[TRAIN] epoch=65, batch_id=288, loss=0.049256, lr=0.000661,acc=0.984 ETA 02:53:53
[TRAIN] epoch=65, batch_id=298, loss=0.049521, lr=0.000656,acc=0.984 ETA 02:51:50
[EVAL] epoch=65

Evaluating top_k_accuracy ...

top1_acc	0.7761
top5_acc	0.9392

Evaluating mean_class_accuracy ...

mean_acc	0.7751
[TRAIN] epoch=66, batch_id=10, loss=0.057925, lr=0.000650,acc=0.981 ETA 42:10:47
[TRAIN] epoch=66, batch_id=20, loss=0.042939, lr=0.000645,acc=0.988 ETA 02:47:57
[TRAIN] epoch=66, batch_id=30, loss=0.046771, lr=0.000640,acc=0.985 ETA 02:57:58
[TRAIN] epoch=66, batch_id=40, loss=0.039289, lr=0.000635,acc=0.987 ETA 02:53:12
[TRAIN] epoch=66, batch_id=50, loss=0.044166, lr=0.000630,acc=0.984 ETA 04:16:20
[TRAIN] epoch=66, batch_id=60, loss=0.041097, lr=0.000625,acc=0.986 ETA 02:57:51
[TRAIN] epoch=66, batch_id=70, loss=0.039051, lr=0.000620,acc=0.988 ETA 02:51:16
[TRAIN] epoch=66, batch_id=80, loss=0.041609, lr=0.000615,acc=0.987 ETA 02:48:47
[TRAIN] epoch=66, batch_id=90, loss=0.045876, lr=0.000610,acc=0.986 ETA 03:04:33
[TRAIN] epoch=66, batch_id=100, loss=0.049749, lr=0.000605,acc=0.983 ETA 02:46:20
[TRAIN] epoch=66, batch_id=110, loss=0.048562, lr=0.000599,acc=0.984 ETA 04:05:48
[TRAIN] epoch=66, batch_id=120, loss=0.048640, lr=0.000594,acc=0.985 ETA 02:59:33
[TRAIN] epoch=66, batch_id=130, loss=0.048936, lr=0.000589,acc=0.985 ETA 03:17:16
[TRAIN] epoch=66, batch_id=140, loss=0.048105, lr=0.000584,acc=0.985 ETA 02:48:23
[TRAIN] epoch=66, batch_id=150, loss=0.047274, lr=0.000579,acc=0.985 ETA 02:52:16
[TRAIN] epoch=66, batch_id=160, loss=0.045867, lr=0.000574,acc=0.986 ETA 02:51:30
[TRAIN] epoch=66, batch_id=170, loss=0.045098, lr=0.000568,acc=0.986 ETA 04:13:13
[TRAIN] epoch=66, batch_id=180, loss=0.043908, lr=0.000563,acc=0.986 ETA 04:18:59
[TRAIN] epoch=66, batch_id=190, loss=0.042591, lr=0.000558,acc=0.987 ETA 02:49:49
[TRAIN] epoch=66, batch_id=200, loss=0.041140, lr=0.000553,acc=0.987 ETA 02:58:12
[TRAIN] epoch=66, batch_id=210, loss=0.040767, lr=0.000547,acc=0.988 ETA 03:23:42
[TRAIN] epoch=66, batch_id=220, loss=0.041132, lr=0.000542,acc=0.987 ETA 03:04:34
[TRAIN] epoch=66, batch_id=230, loss=0.040665, lr=0.000537,acc=0.987 ETA 03:06:51
[TRAIN] epoch=66, batch_id=240, loss=0.041613, lr=0.000532,acc=0.987 ETA 02:44:53
[TRAIN] epoch=66, batch_id=250, loss=0.040536, lr=0.000526,acc=0.988 ETA 02:44:13
[TRAIN] epoch=66, batch_id=260, loss=0.041214, lr=0.000521,acc=0.987 ETA 03:08:41
[TRAIN] epoch=66, batch_id=270, loss=0.041032, lr=0.000516,acc=0.987 ETA 03:41:41
[TRAIN] epoch=66, batch_id=280, loss=0.041547, lr=0.000511,acc=0.987 ETA 02:48:10
[TRAIN] epoch=66, batch_id=290, loss=0.040866, lr=0.000505,acc=0.988 ETA 02:43:08
[EVAL] epoch=66

Evaluating top_k_accuracy ...

top1_acc	0.7904
top5_acc	0.9485

Evaluating mean_class_accuracy ...

mean_acc	0.7900
[TRAIN] epoch=67, batch_id=2, loss=0.034700, lr=0.000500,acc=0.984 ETA 40:46:39
[TRAIN] epoch=67, batch_id=12, loss=0.053567, lr=0.000495,acc=0.982 ETA 02:49:49
[TRAIN] epoch=67, batch_id=22, loss=0.049786, lr=0.000489,acc=0.984 ETA 02:57:56
[TRAIN] epoch=67, batch_id=32, loss=0.044698, lr=0.000484,acc=0.986 ETA 02:44:52
[TRAIN] epoch=67, batch_id=42, loss=0.045645, lr=0.000479,acc=0.987 ETA 02:42:26
[TRAIN] epoch=67, batch_id=52, loss=0.050771, lr=0.000474,acc=0.986 ETA 02:43:19
[TRAIN] epoch=67, batch_id=62, loss=0.047401, lr=0.000468,acc=0.987 ETA 02:44:01
[TRAIN] epoch=67, batch_id=72, loss=0.049052, lr=0.000463,acc=0.987 ETA 02:45:18
[TRAIN] epoch=67, batch_id=82, loss=0.048304, lr=0.000458,acc=0.986 ETA 02:46:45
[TRAIN] epoch=67, batch_id=92, loss=0.046675, lr=0.000453,acc=0.986 ETA 02:41:25
[TRAIN] epoch=67, batch_id=102, loss=0.046273, lr=0.000447,acc=0.986 ETA 03:23:32
[TRAIN] epoch=67, batch_id=112, loss=0.049146, lr=0.000442,acc=0.985 ETA 02:41:21
[TRAIN] epoch=67, batch_id=122, loss=0.049531, lr=0.000437,acc=0.985 ETA 03:12:37
[TRAIN] epoch=67, batch_id=132, loss=0.047056, lr=0.000432,acc=0.986 ETA 02:43:36
[TRAIN] epoch=67, batch_id=142, loss=0.047092, lr=0.000426,acc=0.986 ETA 02:44:39
[TRAIN] epoch=67, batch_id=152, loss=0.046453, lr=0.000421,acc=0.986 ETA 02:41:08
[TRAIN] epoch=67, batch_id=162, loss=0.046678, lr=0.000416,acc=0.985 ETA 02:42:55
[TRAIN] epoch=67, batch_id=172, loss=0.045169, lr=0.000411,acc=0.986 ETA 02:41:45
[TRAIN] epoch=67, batch_id=182, loss=0.045323, lr=0.000406,acc=0.986 ETA 02:43:13
[TRAIN] epoch=67, batch_id=192, loss=0.044190, lr=0.000401,acc=0.986 ETA 02:40:41
[TRAIN] epoch=67, batch_id=202, loss=0.043517, lr=0.000395,acc=0.987 ETA 03:23:46
[TRAIN] epoch=67, batch_id=212, loss=0.043171, lr=0.000390,acc=0.987 ETA 03:17:01
[TRAIN] epoch=67, batch_id=222, loss=0.044130, lr=0.000385,acc=0.986 ETA 02:42:37
[TRAIN] epoch=67, batch_id=232, loss=0.045544, lr=0.000380,acc=0.986 ETA 02:44:34
[TRAIN] epoch=67, batch_id=242, loss=0.045472, lr=0.000375,acc=0.986 ETA 02:54:04
[TRAIN] epoch=67, batch_id=252, loss=0.044155, lr=0.000370,acc=0.986 ETA 02:43:00
[TRAIN] epoch=67, batch_id=262, loss=0.043818, lr=0.000365,acc=0.986 ETA 02:47:13
[TRAIN] epoch=67, batch_id=272, loss=0.043492, lr=0.000360,acc=0.986 ETA 02:43:05
[TRAIN] epoch=67, batch_id=282, loss=0.044177, lr=0.000355,acc=0.986 ETA 02:43:00
[TRAIN] epoch=67, batch_id=292, loss=0.044158, lr=0.000350,acc=0.986 ETA 02:39:24
[EVAL] epoch=67

Evaluating top_k_accuracy ...

top1_acc	0.7859
top5_acc	0.9485

Evaluating mean_class_accuracy ...

mean_acc	0.7867
[TRAIN] epoch=68, batch_id=4, loss=0.062132, lr=0.000344,acc=0.969 ETA 39:20:45
[TRAIN] epoch=68, batch_id=14, loss=0.061915, lr=0.000339,acc=0.980 ETA 03:02:14
[TRAIN] epoch=68, batch_id=24, loss=0.050129, lr=0.000335,acc=0.987 ETA 02:39:34
[TRAIN] epoch=68, batch_id=34, loss=0.046036, lr=0.000330,acc=0.988 ETA 03:06:52
[TRAIN] epoch=68, batch_id=44, loss=0.043079, lr=0.000325,acc=0.989 ETA 02:40:31
[TRAIN] epoch=68, batch_id=54, loss=0.042366, lr=0.000320,acc=0.990 ETA 03:31:03
[TRAIN] epoch=68, batch_id=64, loss=0.040757, lr=0.000315,acc=0.990 ETA 03:08:57
[TRAIN] epoch=68, batch_id=74, loss=0.044663, lr=0.000310,acc=0.989 ETA 02:41:51
[TRAIN] epoch=68, batch_id=84, loss=0.048598, lr=0.000305,acc=0.988 ETA 02:39:37
[TRAIN] epoch=68, batch_id=94, loss=0.049518, lr=0.000300,acc=0.988 ETA 02:39:27
[TRAIN] epoch=68, batch_id=104, loss=0.047832, lr=0.000295,acc=0.988 ETA 02:38:19
[TRAIN] epoch=68, batch_id=114, loss=0.046050, lr=0.000291,acc=0.988 ETA 02:44:01
[TRAIN] epoch=68, batch_id=124, loss=0.044906, lr=0.000286,acc=0.989 ETA 02:43:39
[TRAIN] epoch=68, batch_id=134, loss=0.043690, lr=0.000281,acc=0.989 ETA 02:46:53
[TRAIN] epoch=68, batch_id=144, loss=0.042347, lr=0.000276,acc=0.989 ETA 02:39:06
[TRAIN] epoch=68, batch_id=154, loss=0.043084, lr=0.000272,acc=0.988 ETA 02:36:38
[TRAIN] epoch=68, batch_id=164, loss=0.041470, lr=0.000267,acc=0.989 ETA 02:38:30
[TRAIN] epoch=68, batch_id=174, loss=0.041340, lr=0.000262,acc=0.989 ETA 02:39:59
[TRAIN] epoch=68, batch_id=184, loss=0.041033, lr=0.000258,acc=0.989 ETA 03:13:22
[TRAIN] epoch=68, batch_id=194, loss=0.043714, lr=0.000253,acc=0.989 ETA 02:49:19
[TRAIN] epoch=68, batch_id=204, loss=0.042783, lr=0.000248,acc=0.989 ETA 02:42:03
[TRAIN] epoch=68, batch_id=214, loss=0.041815, lr=0.000244,acc=0.989 ETA 02:51:22
[TRAIN] epoch=68, batch_id=224, loss=0.042780, lr=0.000239,acc=0.989 ETA 03:39:59
[TRAIN] epoch=68, batch_id=234, loss=0.041880, lr=0.000235,acc=0.989 ETA 02:59:47
[TRAIN] epoch=68, batch_id=244, loss=0.041636, lr=0.000230,acc=0.989 ETA 03:28:58
[TRAIN] epoch=68, batch_id=254, loss=0.041479, lr=0.000226,acc=0.989 ETA 02:41:45
[TRAIN] epoch=68, batch_id=264, loss=0.042070, lr=0.000222,acc=0.988 ETA 02:39:51
[TRAIN] epoch=68, batch_id=274, loss=0.041094, lr=0.000217,acc=0.989 ETA 03:51:52
[TRAIN] epoch=68, batch_id=284, loss=0.040992, lr=0.000213,acc=0.989 ETA 02:38:51
[TRAIN] epoch=68, batch_id=294, loss=0.039956, lr=0.000209,acc=0.989 ETA 02:53:32
[EVAL] epoch=68

Evaluating top_k_accuracy ...

top1_acc	0.7883
top5_acc	0.9485

Evaluating mean_class_accuracy ...

mean_acc	0.7885
[TRAIN] epoch=69, batch_id=6, loss=0.044836, lr=0.000204,acc=0.990 ETA 37:59:36
[TRAIN] epoch=69, batch_id=16, loss=0.033919, lr=0.000200,acc=0.992 ETA 02:33:18
[TRAIN] epoch=69, batch_id=26, loss=0.028757, lr=0.000196,acc=0.994 ETA 02:35:33
[TRAIN] epoch=69, batch_id=36, loss=0.028424, lr=0.000192,acc=0.993 ETA 02:37:38
[TRAIN] epoch=69, batch_id=46, loss=0.026064, lr=0.000188,acc=0.994 ETA 02:35:25
[TRAIN] epoch=69, batch_id=56, loss=0.026734, lr=0.000184,acc=0.993 ETA 02:37:44
[TRAIN] epoch=69, batch_id=66, loss=0.030261, lr=0.000180,acc=0.992 ETA 02:44:07
[TRAIN] epoch=69, batch_id=76, loss=0.029675, lr=0.000175,acc=0.992 ETA 02:36:50
[TRAIN] epoch=69, batch_id=86, loss=0.029997, lr=0.000171,acc=0.992 ETA 02:47:18
[TRAIN] epoch=69, batch_id=96, loss=0.030116, lr=0.000168,acc=0.992 ETA 02:59:57
[TRAIN] epoch=69, batch_id=106, loss=0.030481, lr=0.000164,acc=0.991 ETA 02:31:00
[TRAIN] epoch=69, batch_id=116, loss=0.029211, lr=0.000160,acc=0.991 ETA 02:36:36
[TRAIN] epoch=69, batch_id=126, loss=0.029893, lr=0.000156,acc=0.991 ETA 02:37:29
[TRAIN] epoch=69, batch_id=136, loss=0.031520, lr=0.000152,acc=0.991 ETA 02:42:55
[TRAIN] epoch=69, batch_id=146, loss=0.030230, lr=0.000148,acc=0.991 ETA 02:38:00
[TRAIN] epoch=69, batch_id=156, loss=0.029689, lr=0.000145,acc=0.991 ETA 02:36:17
[TRAIN] epoch=69, batch_id=166, loss=0.028653, lr=0.000141,acc=0.992 ETA 02:34:26
[TRAIN] epoch=69, batch_id=176, loss=0.028939, lr=0.000137,acc=0.991 ETA 02:35:01
[TRAIN] epoch=69, batch_id=186, loss=0.029039, lr=0.000134,acc=0.991 ETA 02:37:46
[TRAIN] epoch=69, batch_id=196, loss=0.028564, lr=0.000130,acc=0.992 ETA 03:02:00
[TRAIN] epoch=69, batch_id=206, loss=0.029195, lr=0.000127,acc=0.991 ETA 03:16:30
[TRAIN] epoch=69, batch_id=216, loss=0.029699, lr=0.000123,acc=0.991 ETA 02:34:19
[TRAIN] epoch=69, batch_id=226, loss=0.029607, lr=0.000120,acc=0.991 ETA 02:54:57
[TRAIN] epoch=69, batch_id=236, loss=0.030394, lr=0.000116,acc=0.991 ETA 03:45:40
[TRAIN] epoch=69, batch_id=246, loss=0.029882, lr=0.000113,acc=0.991 ETA 02:56:09
[TRAIN] epoch=69, batch_id=256, loss=0.029932, lr=0.000110,acc=0.991 ETA 03:37:53
[TRAIN] epoch=69, batch_id=266, loss=0.030859, lr=0.000106,acc=0.991 ETA 03:22:44
[TRAIN] epoch=69, batch_id=276, loss=0.031315, lr=0.000103,acc=0.991 ETA 03:34:07
[TRAIN] epoch=69, batch_id=286, loss=0.031275, lr=0.000100,acc=0.991 ETA 03:01:19
[TRAIN] epoch=69, batch_id=296, loss=0.031054, lr=0.000097,acc=0.991 ETA 02:34:44
[EVAL] epoch=69

Evaluating top_k_accuracy ...

top1_acc	0.7917
top5_acc	0.9490

Evaluating mean_class_accuracy ...

mean_acc	0.7914
[TRAIN] epoch=70, batch_id=8, loss=0.037218, lr=0.000094,acc=0.988 ETA 41:05:15
[TRAIN] epoch=70, batch_id=18, loss=0.033649, lr=0.000091,acc=0.988 ETA 03:46:59
[TRAIN] epoch=70, batch_id=28, loss=0.033201, lr=0.000088,acc=0.989 ETA 03:04:25
[TRAIN] epoch=70, batch_id=38, loss=0.036994, lr=0.000085,acc=0.988 ETA 02:29:09
[TRAIN] epoch=70, batch_id=48, loss=0.035505, lr=0.000082,acc=0.988 ETA 02:27:35
[TRAIN] epoch=70, batch_id=58, loss=0.037921, lr=0.000079,acc=0.987 ETA 02:32:54
[TRAIN] epoch=70, batch_id=68, loss=0.036520, lr=0.000076,acc=0.988 ETA 02:31:41
[TRAIN] epoch=70, batch_id=78, loss=0.035493, lr=0.000073,acc=0.989 ETA 02:32:18
[TRAIN] epoch=70, batch_id=88, loss=0.036052, lr=0.000071,acc=0.989 ETA 02:30:43
[TRAIN] epoch=70, batch_id=98, loss=0.034138, lr=0.000068,acc=0.989 ETA 02:30:10
[TRAIN] epoch=70, batch_id=108, loss=0.033081, lr=0.000065,acc=0.990 ETA 02:28:38
[TRAIN] epoch=70, batch_id=118, loss=0.031791, lr=0.000063,acc=0.990 ETA 02:30:55
[TRAIN] epoch=70, batch_id=128, loss=0.030887, lr=0.000060,acc=0.991 ETA 02:29:14
[TRAIN] epoch=70, batch_id=138, loss=0.029744, lr=0.000058,acc=0.991 ETA 02:27:04
[TRAIN] epoch=70, batch_id=148, loss=0.029041, lr=0.000055,acc=0.991 ETA 02:29:30
[TRAIN] epoch=70, batch_id=158, loss=0.028270, lr=0.000053,acc=0.991 ETA 02:43:12
[TRAIN] epoch=70, batch_id=168, loss=0.028166, lr=0.000051,acc=0.992 ETA 05:39:11
[TRAIN] epoch=70, batch_id=178, loss=0.028361, lr=0.000048,acc=0.992 ETA 04:28:59
[TRAIN] epoch=70, batch_id=188, loss=0.028806, lr=0.000046,acc=0.992 ETA 03:55:08
[TRAIN] epoch=70, batch_id=198, loss=0.029499, lr=0.000044,acc=0.992 ETA 02:39:13
[TRAIN] epoch=70, batch_id=208, loss=0.029164, lr=0.000042,acc=0.992 ETA 02:29:00
[TRAIN] epoch=70, batch_id=218, loss=0.029394, lr=0.000040,acc=0.992 ETA 02:31:36
[TRAIN] epoch=70, batch_id=228, loss=0.028949, lr=0.000038,acc=0.992 ETA 03:42:26
[TRAIN] epoch=70, batch_id=238, loss=0.028677, lr=0.000036,acc=0.992 ETA 02:57:25
[TRAIN] epoch=70, batch_id=248, loss=0.029287, lr=0.000034,acc=0.991 ETA 02:30:35
[TRAIN] epoch=70, batch_id=258, loss=0.029095, lr=0.000032,acc=0.991 ETA 02:27:22
[TRAIN] epoch=70, batch_id=268, loss=0.029261, lr=0.000030,acc=0.991 ETA 02:25:31
[TRAIN] epoch=70, batch_id=278, loss=0.029835, lr=0.000028,acc=0.991 ETA 02:50:13
[TRAIN] epoch=70, batch_id=288, loss=0.029400, lr=0.000026,acc=0.991 ETA 02:35:36
[TRAIN] epoch=70, batch_id=298, loss=0.030390, lr=0.000025,acc=0.991 ETA 02:26:34
[EVAL] epoch=70

Evaluating top_k_accuracy ...

top1_acc	0.7917
top5_acc	0.9503

Evaluating mean_class_accuracy ...

mean_acc	0.7912
[TRAIN] epoch=71, batch_id=10, loss=0.029229, lr=0.000023,acc=0.988 ETA 35:18:40
[TRAIN] epoch=71, batch_id=20, loss=0.029088, lr=0.000022,acc=0.989 ETA 02:24:18
[TRAIN] epoch=71, batch_id=30, loss=0.025539, lr=0.000020,acc=0.992 ETA 02:23:37
[TRAIN] epoch=71, batch_id=40, loss=0.023680, lr=0.000019,acc=0.991 ETA 03:09:44
[TRAIN] epoch=71, batch_id=50, loss=0.031076, lr=0.000017,acc=0.989 ETA 02:23:33
[TRAIN] epoch=71, batch_id=60, loss=0.031879, lr=0.000016,acc=0.989 ETA 02:24:22
[TRAIN] epoch=71, batch_id=70, loss=0.031535, lr=0.000015,acc=0.989 ETA 02:25:23
[TRAIN] epoch=71, batch_id=80, loss=0.032603, lr=0.000013,acc=0.989 ETA 02:25:05
[TRAIN] epoch=71, batch_id=90, loss=0.032903, lr=0.000012,acc=0.990 ETA 02:23:52
[TRAIN] epoch=71, batch_id=100, loss=0.034200, lr=0.000011,acc=0.990 ETA 02:26:11
[TRAIN] epoch=71, batch_id=110, loss=0.034586, lr=0.000010,acc=0.990 ETA 02:28:43
[TRAIN] epoch=71, batch_id=120, loss=0.035219, lr=0.000009,acc=0.990 ETA 02:25:55
[TRAIN] epoch=71, batch_id=130, loss=0.035005, lr=0.000008,acc=0.989 ETA 02:23:00
[TRAIN] epoch=71, batch_id=140, loss=0.034005, lr=0.000007,acc=0.990 ETA 02:23:01
[TRAIN] epoch=71, batch_id=150, loss=0.034190, lr=0.000006,acc=0.990 ETA 02:22:31
[TRAIN] epoch=71, batch_id=160, loss=0.032853, lr=0.000005,acc=0.990 ETA 02:23:56
[TRAIN] epoch=71, batch_id=170, loss=0.032150, lr=0.000005,acc=0.990 ETA 02:25:12
[TRAIN] epoch=71, batch_id=180, loss=0.032471, lr=0.000004,acc=0.990 ETA 02:25:05
[TRAIN] epoch=71, batch_id=190, loss=0.031368, lr=0.000003,acc=0.990 ETA 02:20:05
[TRAIN] epoch=71, batch_id=200, loss=0.030510, lr=0.000003,acc=0.991 ETA 03:06:24
[TRAIN] epoch=71, batch_id=210, loss=0.030029, lr=0.000002,acc=0.991 ETA 02:37:59
[TRAIN] epoch=71, batch_id=220, loss=0.029253, lr=0.000002,acc=0.992 ETA 02:23:42
[TRAIN] epoch=71, batch_id=230, loss=0.028718, lr=0.000001,acc=0.992 ETA 02:23:28
[TRAIN] epoch=71, batch_id=240, loss=0.028748, lr=0.000001,acc=0.992 ETA 02:23:06
[TRAIN] epoch=71, batch_id=250, loss=0.028184, lr=0.000001,acc=0.992 ETA 02:32:22
[TRAIN] epoch=71, batch_id=260, loss=0.028056, lr=0.000000,acc=0.992 ETA 02:24:40
[TRAIN] epoch=71, batch_id=270, loss=0.028033, lr=0.000000,acc=0.992 ETA 02:23:41
[TRAIN] epoch=71, batch_id=280, loss=0.027772, lr=0.000000,acc=0.992 ETA 02:26:05
[TRAIN] epoch=71, batch_id=290, loss=0.027546, lr=0.000000,acc=0.992 ETA 02:26:41
[EVAL] epoch=71

Evaluating top_k_accuracy ...

top1_acc	0.7917
top5_acc	0.9495

Evaluating mean_class_accuracy ...

mean_acc	0.7911
[TRAIN] epoch=72, batch_id=2, loss=0.031229, lr=0.000000,acc=0.984 ETA 36:13:06
[TRAIN] epoch=72, batch_id=12, loss=0.027747, lr=0.000000,acc=0.987 ETA 02:30:14
[TRAIN] epoch=72, batch_id=22, loss=0.037921, lr=0.000000,acc=0.986 ETA 02:47:48
[TRAIN] epoch=72, batch_id=32, loss=0.032143, lr=0.000000,acc=0.989 ETA 02:29:29
[TRAIN] epoch=72, batch_id=42, loss=0.030813, lr=0.000000,acc=0.990 ETA 02:38:14
[TRAIN] epoch=72, batch_id=52, loss=0.034992, lr=0.000001,acc=0.990 ETA 02:21:46
[TRAIN] epoch=72, batch_id=62, loss=0.033839, lr=0.000001,acc=0.990 ETA 02:20:57
[TRAIN] epoch=72, batch_id=72, loss=0.033493, lr=0.000001,acc=0.990 ETA 02:35:17
[TRAIN] epoch=72, batch_id=82, loss=0.031849, lr=0.000002,acc=0.990 ETA 02:36:49
[TRAIN] epoch=72, batch_id=92, loss=0.034066, lr=0.000002,acc=0.990 ETA 02:18:33
[TRAIN] epoch=72, batch_id=102, loss=0.032833, lr=0.000003,acc=0.991 ETA 02:19:42
[TRAIN] epoch=72, batch_id=112, loss=0.033884, lr=0.000003,acc=0.990 ETA 02:22:07
[TRAIN] epoch=72, batch_id=122, loss=0.034559, lr=0.000004,acc=0.990 ETA 02:21:12
[TRAIN] epoch=72, batch_id=132, loss=0.033513, lr=0.000005,acc=0.990 ETA 02:28:11
[TRAIN] epoch=72, batch_id=142, loss=0.033250, lr=0.000005,acc=0.990 ETA 02:50:13
[TRAIN] epoch=72, batch_id=152, loss=0.033731, lr=0.000006,acc=0.990 ETA 02:19:37
[TRAIN] epoch=72, batch_id=162, loss=0.032541, lr=0.000007,acc=0.990 ETA 04:33:32
[TRAIN] epoch=72, batch_id=172, loss=0.032425, lr=0.000008,acc=0.990 ETA 03:01:58
[TRAIN] epoch=72, batch_id=182, loss=0.033160, lr=0.000009,acc=0.990 ETA 02:17:02
[TRAIN] epoch=72, batch_id=192, loss=0.032735, lr=0.000010,acc=0.990 ETA 03:02:58
[TRAIN] epoch=72, batch_id=202, loss=0.031756, lr=0.000011,acc=0.991 ETA 04:05:02
[TRAIN] epoch=72, batch_id=212, loss=0.031158, lr=0.000012,acc=0.991 ETA 06:40:38
[TRAIN] epoch=72, batch_id=222, loss=0.031801, lr=0.000013,acc=0.991 ETA 05:34:45
[TRAIN] epoch=72, batch_id=232, loss=0.031806, lr=0.000015,acc=0.991 ETA 04:40:00
[TRAIN] epoch=72, batch_id=242, loss=0.031273, lr=0.000016,acc=0.991 ETA 02:18:20
[TRAIN] epoch=72, batch_id=252, loss=0.031410, lr=0.000017,acc=0.991 ETA 02:59:51
[TRAIN] epoch=72, batch_id=262, loss=0.031686, lr=0.000019,acc=0.991 ETA 03:58:02
[TRAIN] epoch=72, batch_id=272, loss=0.031498, lr=0.000020,acc=0.991 ETA 04:09:31
[TRAIN] epoch=72, batch_id=282, loss=0.030892, lr=0.000022,acc=0.991 ETA 03:34:32
[TRAIN] epoch=72, batch_id=292, loss=0.030868, lr=0.000023,acc=0.991 ETA 02:29:52
[EVAL] epoch=72

Evaluating top_k_accuracy ...

top1_acc	0.7922
top5_acc	0.9498

Evaluating mean_class_accuracy ...

mean_acc	0.7916
[TRAIN] epoch=73, batch_id=4, loss=0.010528, lr=0.000025,acc=1.000 ETA 33:41:42
[TRAIN] epoch=73, batch_id=14, loss=0.030785, lr=0.000026,acc=0.996 ETA 03:45:04
[TRAIN] epoch=73, batch_id=24, loss=0.029472, lr=0.000028,acc=0.995 ETA 02:26:38
[TRAIN] epoch=73, batch_id=34, loss=0.030041, lr=0.000030,acc=0.993 ETA 02:16:18
[TRAIN] epoch=73, batch_id=44, loss=0.027996, lr=0.000032,acc=0.993 ETA 03:03:59
[TRAIN] epoch=73, batch_id=54, loss=0.027430, lr=0.000034,acc=0.993 ETA 03:36:22
[TRAIN] epoch=73, batch_id=64, loss=0.028561, lr=0.000036,acc=0.992 ETA 03:19:29
[TRAIN] epoch=73, batch_id=74, loss=0.030617, lr=0.000038,acc=0.991 ETA 02:54:52
[TRAIN] epoch=73, batch_id=84, loss=0.033437, lr=0.000040,acc=0.989 ETA 03:20:33
[TRAIN] epoch=73, batch_id=94, loss=0.035225, lr=0.000042,acc=0.989 ETA 03:30:16
[TRAIN] epoch=73, batch_id=104, loss=0.036410, lr=0.000044,acc=0.989 ETA 03:25:04
[TRAIN] epoch=73, batch_id=114, loss=0.035788, lr=0.000046,acc=0.989 ETA 03:26:29
[TRAIN] epoch=73, batch_id=124, loss=0.034142, lr=0.000048,acc=0.990 ETA 02:15:45
[TRAIN] epoch=73, batch_id=134, loss=0.033065, lr=0.000051,acc=0.990 ETA 02:15:38
[TRAIN] epoch=73, batch_id=144, loss=0.033173, lr=0.000053,acc=0.989 ETA 02:17:17
[TRAIN] epoch=73, batch_id=154, loss=0.033840, lr=0.000055,acc=0.989 ETA 02:13:44
[TRAIN] epoch=73, batch_id=164, loss=0.033591, lr=0.000058,acc=0.990 ETA 02:32:31
[TRAIN] epoch=73, batch_id=174, loss=0.035538, lr=0.000060,acc=0.989 ETA 02:14:18
[TRAIN] epoch=73, batch_id=184, loss=0.035212, lr=0.000063,acc=0.989 ETA 02:26:46
[TRAIN] epoch=73, batch_id=194, loss=0.034306, lr=0.000065,acc=0.990 ETA 02:14:09
[TRAIN] epoch=73, batch_id=204, loss=0.033955, lr=0.000068,acc=0.990 ETA 02:15:59
[TRAIN] epoch=73, batch_id=214, loss=0.035183, lr=0.000071,acc=0.990 ETA 02:14:53
[TRAIN] epoch=73, batch_id=224, loss=0.035628, lr=0.000073,acc=0.989 ETA 02:37:44
[TRAIN] epoch=73, batch_id=234, loss=0.035230, lr=0.000076,acc=0.989 ETA 02:14:16
[TRAIN] epoch=73, batch_id=244, loss=0.035768, lr=0.000079,acc=0.989 ETA 02:36:02
[TRAIN] epoch=73, batch_id=254, loss=0.035889, lr=0.000082,acc=0.989 ETA 02:12:06
[TRAIN] epoch=73, batch_id=264, loss=0.035544, lr=0.000085,acc=0.989 ETA 02:29:52
[TRAIN] epoch=73, batch_id=274, loss=0.035757, lr=0.000088,acc=0.989 ETA 03:30:26
[TRAIN] epoch=73, batch_id=284, loss=0.035102, lr=0.000091,acc=0.989 ETA 02:33:23
[TRAIN] epoch=73, batch_id=294, loss=0.035153, lr=0.000094,acc=0.989 ETA 02:08:59
[EVAL] epoch=73

Evaluating top_k_accuracy ...

top1_acc	0.7912
top5_acc	0.9500

Evaluating mean_class_accuracy ...

mean_acc	0.7909
[TRAIN] epoch=74, batch_id=6, loss=0.020791, lr=0.000097,acc=0.995 ETA 32:44:33
[TRAIN] epoch=74, batch_id=16, loss=0.030201, lr=0.000100,acc=0.988 ETA 02:13:43
[TRAIN] epoch=74, batch_id=26, loss=0.031540, lr=0.000103,acc=0.988 ETA 02:12:31
[TRAIN] epoch=74, batch_id=36, loss=0.031493, lr=0.000106,acc=0.989 ETA 02:10:45
[TRAIN] epoch=74, batch_id=46, loss=0.028819, lr=0.000110,acc=0.990 ETA 02:13:35
[TRAIN] epoch=74, batch_id=56, loss=0.030676, lr=0.000113,acc=0.989 ETA 02:20:32
[TRAIN] epoch=74, batch_id=66, loss=0.029416, lr=0.000116,acc=0.990 ETA 02:12:24
[TRAIN] epoch=74, batch_id=76, loss=0.034173, lr=0.000120,acc=0.989 ETA 02:13:35
[TRAIN] epoch=74, batch_id=86, loss=0.032215, lr=0.000123,acc=0.990 ETA 02:11:09
[TRAIN] epoch=74, batch_id=96, loss=0.031187, lr=0.000127,acc=0.991 ETA 02:26:45
[TRAIN] epoch=74, batch_id=106, loss=0.030448, lr=0.000130,acc=0.991 ETA 03:06:18
[TRAIN] epoch=74, batch_id=116, loss=0.030358, lr=0.000134,acc=0.991 ETA 02:40:33
[TRAIN] epoch=74, batch_id=126, loss=0.031756, lr=0.000137,acc=0.990 ETA 02:10:56
[TRAIN] epoch=74, batch_id=136, loss=0.033244, lr=0.000141,acc=0.990 ETA 02:38:02
[TRAIN] epoch=74, batch_id=146, loss=0.033308, lr=0.000145,acc=0.990 ETA 02:08:19
[TRAIN] epoch=74, batch_id=156, loss=0.033078, lr=0.000148,acc=0.990 ETA 02:14:10
[TRAIN] epoch=74, batch_id=166, loss=0.033708, lr=0.000152,acc=0.990 ETA 02:10:36
[TRAIN] epoch=74, batch_id=176, loss=0.034262, lr=0.000156,acc=0.989 ETA 02:33:32
[TRAIN] epoch=74, batch_id=186, loss=0.034212, lr=0.000160,acc=0.989 ETA 02:49:21
[TRAIN] epoch=74, batch_id=196, loss=0.032926, lr=0.000164,acc=0.990 ETA 02:29:59
[TRAIN] epoch=74, batch_id=206, loss=0.033092, lr=0.000168,acc=0.990 ETA 02:09:36
[TRAIN] epoch=74, batch_id=216, loss=0.033050, lr=0.000171,acc=0.990 ETA 02:34:19
[TRAIN] epoch=74, batch_id=226, loss=0.033742, lr=0.000175,acc=0.990 ETA 02:10:33
[TRAIN] epoch=74, batch_id=236, loss=0.032858, lr=0.000180,acc=0.990 ETA 02:11:46
[TRAIN] epoch=74, batch_id=246, loss=0.032204, lr=0.000184,acc=0.990 ETA 02:36:08
[TRAIN] epoch=74, batch_id=256, loss=0.031836, lr=0.000188,acc=0.991 ETA 03:09:03
[TRAIN] epoch=74, batch_id=266, loss=0.032530, lr=0.000192,acc=0.990 ETA 03:11:41
[TRAIN] epoch=74, batch_id=276, loss=0.031983, lr=0.000196,acc=0.990 ETA 02:07:21
[TRAIN] epoch=74, batch_id=286, loss=0.031897, lr=0.000200,acc=0.990 ETA 02:11:54
[TRAIN] epoch=74, batch_id=296, loss=0.031497, lr=0.000204,acc=0.991 ETA 02:14:55
[EVAL] epoch=74

Evaluating top_k_accuracy ...

top1_acc	0.7920
top5_acc	0.9490

Evaluating mean_class_accuracy ...

mean_acc	0.7921
[TRAIN] epoch=75, batch_id=8, loss=0.032141, lr=0.000209,acc=0.988 ETA 32:35:31
[TRAIN] epoch=75, batch_id=18, loss=0.023468, lr=0.000213,acc=0.991 ETA 02:04:26
[TRAIN] epoch=75, batch_id=28, loss=0.033692, lr=0.000217,acc=0.985 ETA 02:06:25
[TRAIN] epoch=75, batch_id=38, loss=0.032667, lr=0.000222,acc=0.987 ETA 02:10:17
[TRAIN] epoch=75, batch_id=48, loss=0.030272, lr=0.000226,acc=0.988 ETA 02:06:52
[TRAIN] epoch=75, batch_id=58, loss=0.029891, lr=0.000230,acc=0.988 ETA 02:06:53
[TRAIN] epoch=75, batch_id=68, loss=0.030195, lr=0.000235,acc=0.988 ETA 02:08:12
[TRAIN] epoch=75, batch_id=78, loss=0.033825, lr=0.000239,acc=0.987 ETA 02:04:11
[TRAIN] epoch=75, batch_id=88, loss=0.033254, lr=0.000244,acc=0.988 ETA 02:05:43
[TRAIN] epoch=75, batch_id=98, loss=0.034865, lr=0.000248,acc=0.987 ETA 02:08:35
[TRAIN] epoch=75, batch_id=108, loss=0.035096, lr=0.000253,acc=0.988 ETA 02:05:35
[TRAIN] epoch=75, batch_id=118, loss=0.033422, lr=0.000258,acc=0.988 ETA 03:03:48
[TRAIN] epoch=75, batch_id=128, loss=0.033161, lr=0.000262,acc=0.989 ETA 02:10:05
[TRAIN] epoch=75, batch_id=138, loss=0.031317, lr=0.000267,acc=0.989 ETA 02:56:49
[TRAIN] epoch=75, batch_id=148, loss=0.031314, lr=0.000272,acc=0.989 ETA 02:10:43
[TRAIN] epoch=75, batch_id=158, loss=0.030048, lr=0.000276,acc=0.990 ETA 02:05:43
[TRAIN] epoch=75, batch_id=168, loss=0.029257, lr=0.000281,acc=0.991 ETA 02:03:38
[TRAIN] epoch=75, batch_id=178, loss=0.028614, lr=0.000286,acc=0.991 ETA 02:03:17
[TRAIN] epoch=75, batch_id=188, loss=0.029021, lr=0.000291,acc=0.991 ETA 02:05:17
[TRAIN] epoch=75, batch_id=198, loss=0.030667, lr=0.000295,acc=0.990 ETA 02:03:16
[TRAIN] epoch=75, batch_id=208, loss=0.030562, lr=0.000300,acc=0.990 ETA 02:26:08
[TRAIN] epoch=75, batch_id=218, loss=0.030831, lr=0.000305,acc=0.990 ETA 02:07:29
[TRAIN] epoch=75, batch_id=228, loss=0.031228, lr=0.000310,acc=0.990 ETA 02:03:27
[TRAIN] epoch=75, batch_id=238, loss=0.032376, lr=0.000315,acc=0.989 ETA 02:07:14
[TRAIN] epoch=75, batch_id=248, loss=0.032503, lr=0.000320,acc=0.989 ETA 02:01:21
[TRAIN] epoch=75, batch_id=258, loss=0.032426, lr=0.000325,acc=0.990 ETA 02:03:43
[TRAIN] epoch=75, batch_id=268, loss=0.032137, lr=0.000330,acc=0.990 ETA 02:02:17
[TRAIN] epoch=75, batch_id=278, loss=0.032990, lr=0.000335,acc=0.989 ETA 02:11:05
[TRAIN] epoch=75, batch_id=288, loss=0.033788, lr=0.000339,acc=0.989 ETA 02:05:03
[TRAIN] epoch=75, batch_id=298, loss=0.033934, lr=0.000344,acc=0.989 ETA 02:04:06
[EVAL] epoch=75

Evaluating top_k_accuracy ...

top1_acc	0.7898
top5_acc	0.9466

Evaluating mean_class_accuracy ...

mean_acc	0.7887
[TRAIN] epoch=76, batch_id=10, loss=0.016404, lr=0.000350,acc=0.994 ETA 29:56:32
[TRAIN] epoch=76, batch_id=20, loss=0.021825, lr=0.000355,acc=0.991 ETA 02:23:08
[TRAIN] epoch=76, batch_id=30, loss=0.029247, lr=0.000360,acc=0.990 ETA 02:03:36
[TRAIN] epoch=76, batch_id=40, loss=0.030330, lr=0.000365,acc=0.990 ETA 02:07:52
[TRAIN] epoch=76, batch_id=50, loss=0.032604, lr=0.000370,acc=0.989 ETA 02:06:23
[TRAIN] epoch=76, batch_id=60, loss=0.031487, lr=0.000375,acc=0.989 ETA 02:06:38
[TRAIN] epoch=76, batch_id=70, loss=0.031937, lr=0.000380,acc=0.988 ETA 02:05:10
[TRAIN] epoch=76, batch_id=80, loss=0.030664, lr=0.000385,acc=0.989 ETA 02:04:29
[TRAIN] epoch=76, batch_id=90, loss=0.029888, lr=0.000390,acc=0.989 ETA 02:03:59
[TRAIN] epoch=76, batch_id=100, loss=0.029829, lr=0.000395,acc=0.989 ETA 02:17:50
[TRAIN] epoch=76, batch_id=110, loss=0.028477, lr=0.000401,acc=0.990 ETA 02:04:04
[TRAIN] epoch=76, batch_id=120, loss=0.029916, lr=0.000406,acc=0.989 ETA 02:05:53
[TRAIN] epoch=76, batch_id=130, loss=0.030742, lr=0.000411,acc=0.989 ETA 02:03:51
[TRAIN] epoch=76, batch_id=140, loss=0.032178, lr=0.000416,acc=0.988 ETA 02:03:21
[TRAIN] epoch=76, batch_id=150, loss=0.032237, lr=0.000421,acc=0.989 ETA 02:03:28
[TRAIN] epoch=76, batch_id=160, loss=0.032467, lr=0.000426,acc=0.988 ETA 02:28:46
[TRAIN] epoch=76, batch_id=170, loss=0.034257, lr=0.000432,acc=0.988 ETA 04:03:23
[TRAIN] epoch=76, batch_id=180, loss=0.035252, lr=0.000437,acc=0.988 ETA 03:58:41
[TRAIN] epoch=76, batch_id=190, loss=0.036260, lr=0.000442,acc=0.987 ETA 03:52:43
[TRAIN] epoch=76, batch_id=200, loss=0.035070, lr=0.000447,acc=0.987 ETA 03:11:56
[TRAIN] epoch=76, batch_id=210, loss=0.035292, lr=0.000453,acc=0.988 ETA 02:56:38
[TRAIN] epoch=76, batch_id=220, loss=0.035420, lr=0.000458,acc=0.988 ETA 01:59:29
[TRAIN] epoch=76, batch_id=230, loss=0.036247, lr=0.000463,acc=0.988 ETA 02:29:41
[TRAIN] epoch=76, batch_id=240, loss=0.037274, lr=0.000468,acc=0.988 ETA 01:58:00
[TRAIN] epoch=76, batch_id=250, loss=0.036596, lr=0.000474,acc=0.988 ETA 02:03:00
[TRAIN] epoch=76, batch_id=260, loss=0.036303, lr=0.000479,acc=0.988 ETA 01:59:44
[TRAIN] epoch=76, batch_id=270, loss=0.036349, lr=0.000484,acc=0.988 ETA 02:30:25
[TRAIN] epoch=76, batch_id=280, loss=0.035837, lr=0.000489,acc=0.988 ETA 01:59:45
[TRAIN] epoch=76, batch_id=290, loss=0.035791, lr=0.000495,acc=0.988 ETA 02:00:18
[EVAL] epoch=76

Evaluating top_k_accuracy ...

top1_acc	0.7840
top5_acc	0.9463

Evaluating mean_class_accuracy ...

mean_acc	0.7839
[TRAIN] epoch=77, batch_id=2, loss=0.157179, lr=0.000500,acc=0.953 ETA 28:26:13
[TRAIN] epoch=77, batch_id=12, loss=0.055027, lr=0.000505,acc=0.987 ETA 01:54:51
[TRAIN] epoch=77, batch_id=22, loss=0.060372, lr=0.000511,acc=0.986 ETA 02:32:29
[TRAIN] epoch=77, batch_id=32, loss=0.055857, lr=0.000516,acc=0.985 ETA 01:58:50
[TRAIN] epoch=77, batch_id=42, loss=0.048319, lr=0.000521,acc=0.987 ETA 02:08:07
[TRAIN] epoch=77, batch_id=52, loss=0.045860, lr=0.000526,acc=0.987 ETA 02:03:22
[TRAIN] epoch=77, batch_id=62, loss=0.044715, lr=0.000532,acc=0.987 ETA 02:44:21
[TRAIN] epoch=77, batch_id=72, loss=0.043819, lr=0.000537,acc=0.987 ETA 01:59:48
[TRAIN] epoch=77, batch_id=82, loss=0.042051, lr=0.000542,acc=0.987 ETA 01:56:17
[TRAIN] epoch=77, batch_id=92, loss=0.041807, lr=0.000547,acc=0.987 ETA 01:57:02
[TRAIN] epoch=77, batch_id=102, loss=0.038961, lr=0.000553,acc=0.988 ETA 01:54:24
[TRAIN] epoch=77, batch_id=112, loss=0.038075, lr=0.000558,acc=0.988 ETA 02:03:16
[TRAIN] epoch=77, batch_id=122, loss=0.038833, lr=0.000563,acc=0.988 ETA 01:58:48
[TRAIN] epoch=77, batch_id=132, loss=0.037675, lr=0.000568,acc=0.988 ETA 02:01:18
[TRAIN] epoch=77, batch_id=142, loss=0.036707, lr=0.000574,acc=0.989 ETA 01:59:31
[TRAIN] epoch=77, batch_id=152, loss=0.038570, lr=0.000579,acc=0.988 ETA 02:03:15
[TRAIN] epoch=77, batch_id=162, loss=0.039147, lr=0.000584,acc=0.988 ETA 01:58:01
[TRAIN] epoch=77, batch_id=172, loss=0.039004, lr=0.000589,acc=0.988 ETA 02:00:51
[TRAIN] epoch=77, batch_id=182, loss=0.037846, lr=0.000594,acc=0.988 ETA 01:57:08
[TRAIN] epoch=77, batch_id=192, loss=0.038111, lr=0.000599,acc=0.988 ETA 01:56:38
[TRAIN] epoch=77, batch_id=202, loss=0.037718, lr=0.000605,acc=0.989 ETA 02:02:05
[TRAIN] epoch=77, batch_id=212, loss=0.037646, lr=0.000610,acc=0.989 ETA 01:57:55
[TRAIN] epoch=77, batch_id=222, loss=0.037103, lr=0.000615,acc=0.989 ETA 02:39:44
[TRAIN] epoch=77, batch_id=232, loss=0.038226, lr=0.000620,acc=0.988 ETA 01:57:08
[TRAIN] epoch=77, batch_id=242, loss=0.037116, lr=0.000625,acc=0.989 ETA 01:57:52
[TRAIN] epoch=77, batch_id=252, loss=0.036772, lr=0.000630,acc=0.989 ETA 01:55:43
[TRAIN] epoch=77, batch_id=262, loss=0.035939, lr=0.000635,acc=0.989 ETA 02:23:25
[TRAIN] epoch=77, batch_id=272, loss=0.035688, lr=0.000640,acc=0.989 ETA 01:56:15
[TRAIN] epoch=77, batch_id=282, loss=0.035069, lr=0.000645,acc=0.989 ETA 01:54:52
[TRAIN] epoch=77, batch_id=292, loss=0.034774, lr=0.000650,acc=0.989 ETA 01:53:31
[EVAL] epoch=77

Evaluating top_k_accuracy ...

top1_acc	0.7856
top5_acc	0.9469

Evaluating mean_class_accuracy ...

mean_acc	0.7840
[TRAIN] epoch=78, batch_id=4, loss=0.010999, lr=0.000656,acc=1.000 ETA 29:12:01
[TRAIN] epoch=78, batch_id=14, loss=0.017648, lr=0.000661,acc=0.996 ETA 01:57:06
[TRAIN] epoch=78, batch_id=24, loss=0.033229, lr=0.000665,acc=0.991 ETA 01:51:02
[TRAIN] epoch=78, batch_id=34, loss=0.037223, lr=0.000670,acc=0.990 ETA 01:54:38
[TRAIN] epoch=78, batch_id=44, loss=0.032048, lr=0.000675,acc=0.991 ETA 01:52:03
[TRAIN] epoch=78, batch_id=54, loss=0.036459, lr=0.000680,acc=0.990 ETA 01:59:03
[TRAIN] epoch=78, batch_id=64, loss=0.036013, lr=0.000685,acc=0.990 ETA 01:52:28
[TRAIN] epoch=78, batch_id=74, loss=0.037003, lr=0.000690,acc=0.989 ETA 01:59:16
[TRAIN] epoch=78, batch_id=84, loss=0.036439, lr=0.000695,acc=0.989 ETA 01:53:33
[TRAIN] epoch=78, batch_id=94, loss=0.036485, lr=0.000700,acc=0.989 ETA 02:27:33
[TRAIN] epoch=78, batch_id=104, loss=0.038884, lr=0.000705,acc=0.989 ETA 02:06:36
[TRAIN] epoch=78, batch_id=114, loss=0.037101, lr=0.000709,acc=0.989 ETA 02:48:18
[TRAIN] epoch=78, batch_id=124, loss=0.036174, lr=0.000714,acc=0.989 ETA 01:54:11
[TRAIN] epoch=78, batch_id=134, loss=0.035843, lr=0.000719,acc=0.989 ETA 01:58:47
[TRAIN] epoch=78, batch_id=144, loss=0.035476, lr=0.000724,acc=0.989 ETA 01:55:13
[TRAIN] epoch=78, batch_id=154, loss=0.035152, lr=0.000728,acc=0.989 ETA 01:52:43
[TRAIN] epoch=78, batch_id=164, loss=0.034647, lr=0.000733,acc=0.989 ETA 01:51:56
[TRAIN] epoch=78, batch_id=174, loss=0.035364, lr=0.000738,acc=0.989 ETA 02:13:32
[TRAIN] epoch=78, batch_id=184, loss=0.035679, lr=0.000742,acc=0.989 ETA 01:48:14
[TRAIN] epoch=78, batch_id=194, loss=0.035849, lr=0.000747,acc=0.989 ETA 02:18:15
[TRAIN] epoch=78, batch_id=204, loss=0.036555, lr=0.000752,acc=0.988 ETA 02:43:56
[TRAIN] epoch=78, batch_id=214, loss=0.036813, lr=0.000756,acc=0.988 ETA 01:49:58
[TRAIN] epoch=78, batch_id=224, loss=0.037061, lr=0.000761,acc=0.988 ETA 01:53:20
[TRAIN] epoch=78, batch_id=234, loss=0.036518, lr=0.000765,acc=0.988 ETA 01:48:02
[TRAIN] epoch=78, batch_id=244, loss=0.036190, lr=0.000770,acc=0.988 ETA 01:53:24
[TRAIN] epoch=78, batch_id=254, loss=0.039501, lr=0.000774,acc=0.987 ETA 01:58:20
[TRAIN] epoch=78, batch_id=264, loss=0.038999, lr=0.000778,acc=0.988 ETA 01:50:06
[TRAIN] epoch=78, batch_id=274, loss=0.038342, lr=0.000783,acc=0.988 ETA 01:52:13
[TRAIN] epoch=78, batch_id=284, loss=0.037966, lr=0.000787,acc=0.988 ETA 01:52:00
[TRAIN] epoch=78, batch_id=294, loss=0.038064, lr=0.000791,acc=0.988 ETA 01:54:20
[EVAL] epoch=78

Evaluating top_k_accuracy ...

top1_acc	0.7793
top5_acc	0.9421

Evaluating mean_class_accuracy ...

mean_acc	0.7786
[TRAIN] epoch=79, batch_id=6, loss=0.019143, lr=0.000796,acc=0.995 ETA 27:15:37
[TRAIN] epoch=79, batch_id=16, loss=0.031831, lr=0.000800,acc=0.990 ETA 01:49:12
[TRAIN] epoch=79, batch_id=26, loss=0.030088, lr=0.000804,acc=0.990 ETA 01:46:38
[TRAIN] epoch=79, batch_id=36, loss=0.033670, lr=0.000808,acc=0.989 ETA 01:47:50
[TRAIN] epoch=79, batch_id=46, loss=0.034972, lr=0.000812,acc=0.988 ETA 01:47:47
[TRAIN] epoch=79, batch_id=56, loss=0.041131, lr=0.000816,acc=0.987 ETA 01:46:58
[TRAIN] epoch=79, batch_id=66, loss=0.040531, lr=0.000820,acc=0.988 ETA 01:46:29
[TRAIN] epoch=79, batch_id=76, loss=0.042380, lr=0.000825,acc=0.987 ETA 01:50:24
[TRAIN] epoch=79, batch_id=86, loss=0.042281, lr=0.000829,acc=0.987 ETA 01:47:30
[TRAIN] epoch=79, batch_id=96, loss=0.039490, lr=0.000832,acc=0.988 ETA 01:47:37
[TRAIN] epoch=79, batch_id=106, loss=0.038504, lr=0.000836,acc=0.989 ETA 01:44:28
[TRAIN] epoch=79, batch_id=116, loss=0.037234, lr=0.000840,acc=0.989 ETA 01:45:56
[TRAIN] epoch=79, batch_id=126, loss=0.038266, lr=0.000844,acc=0.989 ETA 01:45:19
[TRAIN] epoch=79, batch_id=136, loss=0.038713, lr=0.000848,acc=0.989 ETA 02:03:24
[TRAIN] epoch=79, batch_id=146, loss=0.039605, lr=0.000852,acc=0.989 ETA 01:53:54
[TRAIN] epoch=79, batch_id=156, loss=0.038897, lr=0.000855,acc=0.989 ETA 01:48:37
[TRAIN] epoch=79, batch_id=166, loss=0.039558, lr=0.000859,acc=0.989 ETA 01:47:40
[TRAIN] epoch=79, batch_id=176, loss=0.039177, lr=0.000863,acc=0.989 ETA 01:47:58
[TRAIN] epoch=79, batch_id=186, loss=0.040529, lr=0.000866,acc=0.987 ETA 01:46:25
[TRAIN] epoch=79, batch_id=196, loss=0.040816, lr=0.000870,acc=0.987 ETA 01:44:20
[TRAIN] epoch=79, batch_id=206, loss=0.041759, lr=0.000873,acc=0.987 ETA 01:51:24
[TRAIN] epoch=79, batch_id=216, loss=0.041936, lr=0.000877,acc=0.987 ETA 01:43:27
[TRAIN] epoch=79, batch_id=226, loss=0.044101, lr=0.000880,acc=0.986 ETA 01:44:43
[TRAIN] epoch=79, batch_id=236, loss=0.044457, lr=0.000884,acc=0.986 ETA 01:45:13
[TRAIN] epoch=79, batch_id=246, loss=0.045646, lr=0.000887,acc=0.986 ETA 01:45:30
[TRAIN] epoch=79, batch_id=256, loss=0.045624, lr=0.000890,acc=0.985 ETA 01:44:06
[TRAIN] epoch=79, batch_id=266, loss=0.045462, lr=0.000894,acc=0.986 ETA 01:49:14
[TRAIN] epoch=79, batch_id=276, loss=0.045737, lr=0.000897,acc=0.986 ETA 01:45:58
[TRAIN] epoch=79, batch_id=286, loss=0.046088, lr=0.000900,acc=0.986 ETA 01:52:10
[TRAIN] epoch=79, batch_id=296, loss=0.045616, lr=0.000903,acc=0.986 ETA 02:50:22
[EVAL] epoch=79

Evaluating top_k_accuracy ...

top1_acc	0.7896
top5_acc	0.9482

Evaluating mean_class_accuracy ...

mean_acc	0.7899
[TRAIN] epoch=80, batch_id=8, loss=0.046628, lr=0.000906,acc=0.984 ETA 27:17:35
[TRAIN] epoch=80, batch_id=18, loss=0.043310, lr=0.000909,acc=0.986 ETA 02:58:51
[TRAIN] epoch=80, batch_id=28, loss=0.039458, lr=0.000912,acc=0.984 ETA 01:54:02
[TRAIN] epoch=80, batch_id=38, loss=0.045826, lr=0.000915,acc=0.983 ETA 02:41:45
[TRAIN] epoch=80, batch_id=48, loss=0.046268, lr=0.000918,acc=0.984 ETA 03:00:32
[TRAIN] epoch=80, batch_id=58, loss=0.046566, lr=0.000921,acc=0.984 ETA 01:44:32
[TRAIN] epoch=80, batch_id=68, loss=0.044204, lr=0.000924,acc=0.985 ETA 01:44:26
[TRAIN] epoch=80, batch_id=78, loss=0.043248, lr=0.000927,acc=0.986 ETA 01:43:25
[TRAIN] epoch=80, batch_id=88, loss=0.043111, lr=0.000929,acc=0.986 ETA 01:57:59
[TRAIN] epoch=80, batch_id=98, loss=0.040875, lr=0.000932,acc=0.987 ETA 01:54:10
[TRAIN] epoch=80, batch_id=108, loss=0.039391, lr=0.000935,acc=0.987 ETA 01:53:24
[TRAIN] epoch=80, batch_id=118, loss=0.038563, lr=0.000937,acc=0.987 ETA 01:50:42
[TRAIN] epoch=80, batch_id=128, loss=0.038991, lr=0.000940,acc=0.987 ETA 01:52:38
[TRAIN] epoch=80, batch_id=138, loss=0.039555, lr=0.000942,acc=0.987 ETA 01:41:52
[TRAIN] epoch=80, batch_id=148, loss=0.040094, lr=0.000945,acc=0.986 ETA 01:47:35
[TRAIN] epoch=80, batch_id=158, loss=0.040530, lr=0.000947,acc=0.986 ETA 01:40:55
[TRAIN] epoch=80, batch_id=168, loss=0.040832, lr=0.000949,acc=0.986 ETA 01:45:42
[TRAIN] epoch=80, batch_id=178, loss=0.041214, lr=0.000952,acc=0.985 ETA 01:41:42
[TRAIN] epoch=80, batch_id=188, loss=0.040868, lr=0.000954,acc=0.986 ETA 01:51:21
[TRAIN] epoch=80, batch_id=198, loss=0.039871, lr=0.000956,acc=0.986 ETA 02:02:04
[TRAIN] epoch=80, batch_id=208, loss=0.040603, lr=0.000958,acc=0.986 ETA 01:39:31
[TRAIN] epoch=80, batch_id=218, loss=0.040543, lr=0.000960,acc=0.986 ETA 01:38:26
[TRAIN] epoch=80, batch_id=228, loss=0.040379, lr=0.000962,acc=0.986 ETA 01:47:57
[TRAIN] epoch=80, batch_id=238, loss=0.040176, lr=0.000964,acc=0.986 ETA 01:40:25
[TRAIN] epoch=80, batch_id=248, loss=0.039762, lr=0.000966,acc=0.986 ETA 02:02:58
[TRAIN] epoch=80, batch_id=258, loss=0.039222, lr=0.000968,acc=0.986 ETA 01:39:38
[TRAIN] epoch=80, batch_id=268, loss=0.039402, lr=0.000970,acc=0.986 ETA 01:54:49
[TRAIN] epoch=80, batch_id=278, loss=0.040199, lr=0.000972,acc=0.986 ETA 01:40:44
[TRAIN] epoch=80, batch_id=288, loss=0.039620, lr=0.000974,acc=0.986 ETA 02:05:23
[TRAIN] epoch=80, batch_id=298, loss=0.039379, lr=0.000975,acc=0.986 ETA 01:38:54
[EVAL] epoch=80

Evaluating top_k_accuracy ...

top1_acc	0.7822
top5_acc	0.9485

Evaluating mean_class_accuracy ...

mean_acc	0.7813
[TRAIN] epoch=81, batch_id=10, loss=0.049039, lr=0.000977,acc=0.984 ETA 24:30:25
[TRAIN] epoch=81, batch_id=20, loss=0.057509, lr=0.000978,acc=0.981 ETA 01:36:25
[TRAIN] epoch=81, batch_id=30, loss=0.043034, lr=0.000980,acc=0.986 ETA 01:34:19
[TRAIN] epoch=81, batch_id=40, loss=0.042030, lr=0.000981,acc=0.987 ETA 02:07:06
[TRAIN] epoch=81, batch_id=50, loss=0.037696, lr=0.000983,acc=0.988 ETA 01:49:53
[TRAIN] epoch=81, batch_id=60, loss=0.038030, lr=0.000984,acc=0.988 ETA 02:01:02
[TRAIN] epoch=81, batch_id=70, loss=0.039774, lr=0.000985,acc=0.986 ETA 01:34:48
[TRAIN] epoch=81, batch_id=80, loss=0.039268, lr=0.000987,acc=0.986 ETA 02:04:49
[TRAIN] epoch=81, batch_id=90, loss=0.041554, lr=0.000988,acc=0.986 ETA 01:40:12
[TRAIN] epoch=81, batch_id=100, loss=0.041569, lr=0.000989,acc=0.987 ETA 02:20:50
[TRAIN] epoch=81, batch_id=110, loss=0.040392, lr=0.000990,acc=0.987 ETA 01:43:11
[TRAIN] epoch=81, batch_id=120, loss=0.040722, lr=0.000991,acc=0.987 ETA 01:52:11
[TRAIN] epoch=81, batch_id=130, loss=0.042402, lr=0.000992,acc=0.987 ETA 01:40:21
[TRAIN] epoch=81, batch_id=140, loss=0.043236, lr=0.000993,acc=0.987 ETA 01:44:48
[TRAIN] epoch=81, batch_id=150, loss=0.042963, lr=0.000994,acc=0.987 ETA 01:33:45
[TRAIN] epoch=81, batch_id=160, loss=0.041175, lr=0.000995,acc=0.988 ETA 01:36:21
[TRAIN] epoch=81, batch_id=170, loss=0.040090, lr=0.000995,acc=0.988 ETA 01:32:53
[TRAIN] epoch=81, batch_id=180, loss=0.041101, lr=0.000996,acc=0.988 ETA 01:42:24
[TRAIN] epoch=81, batch_id=190, loss=0.040414, lr=0.000997,acc=0.988 ETA 01:34:47
[TRAIN] epoch=81, batch_id=200, loss=0.041810, lr=0.000997,acc=0.987 ETA 01:56:08
[TRAIN] epoch=81, batch_id=210, loss=0.042460, lr=0.000998,acc=0.987 ETA 01:34:53
[TRAIN] epoch=81, batch_id=220, loss=0.042981, lr=0.000998,acc=0.987 ETA 01:53:37
[TRAIN] epoch=81, batch_id=230, loss=0.042220, lr=0.000999,acc=0.987 ETA 01:36:42
[TRAIN] epoch=81, batch_id=240, loss=0.041936, lr=0.000999,acc=0.987 ETA 02:16:16
[TRAIN] epoch=81, batch_id=250, loss=0.041477, lr=0.000999,acc=0.988 ETA 01:33:49
[TRAIN] epoch=81, batch_id=260, loss=0.041880, lr=0.001000,acc=0.987 ETA 01:34:01
[TRAIN] epoch=81, batch_id=270, loss=0.041655, lr=0.001000,acc=0.987 ETA 01:35:33
[TRAIN] epoch=81, batch_id=280, loss=0.041870, lr=0.001000,acc=0.987 ETA 01:35:24
[TRAIN] epoch=81, batch_id=290, loss=0.042340, lr=0.001000,acc=0.987 ETA 01:37:10
[EVAL] epoch=81

Evaluating top_k_accuracy ...

top1_acc	0.7819
top5_acc	0.9440

Evaluating mean_class_accuracy ...

mean_acc	0.7813
[TRAIN] epoch=82, batch_id=2, loss=0.047081, lr=0.001000,acc=0.984 ETA 23:52:01
[TRAIN] epoch=82, batch_id=12, loss=0.049933, lr=0.001000,acc=0.982 ETA 01:50:03
[TRAIN] epoch=82, batch_id=22, loss=0.045464, lr=0.001000,acc=0.983 ETA 01:32:39
[TRAIN] epoch=82, batch_id=32, loss=0.040699, lr=0.001000,acc=0.986 ETA 02:20:46
[TRAIN] epoch=82, batch_id=42, loss=0.038572, lr=0.001000,acc=0.987 ETA 01:31:30
[TRAIN] epoch=82, batch_id=52, loss=0.038906, lr=0.000999,acc=0.987 ETA 02:15:46
[TRAIN] epoch=82, batch_id=62, loss=0.045507, lr=0.000999,acc=0.985 ETA 01:31:14
[TRAIN] epoch=82, batch_id=72, loss=0.042160, lr=0.000999,acc=0.987 ETA 01:33:33
[TRAIN] epoch=82, batch_id=82, loss=0.039851, lr=0.000998,acc=0.988 ETA 01:35:41
[TRAIN] epoch=82, batch_id=92, loss=0.042806, lr=0.000998,acc=0.986 ETA 01:42:15
[TRAIN] epoch=82, batch_id=102, loss=0.042929, lr=0.000997,acc=0.986 ETA 01:30:41
[TRAIN] epoch=82, batch_id=112, loss=0.044447, lr=0.000997,acc=0.986 ETA 01:31:54
[TRAIN] epoch=82, batch_id=122, loss=0.045020, lr=0.000996,acc=0.986 ETA 01:30:19
[TRAIN] epoch=82, batch_id=132, loss=0.043175, lr=0.000995,acc=0.987 ETA 01:30:27
[TRAIN] epoch=82, batch_id=142, loss=0.043140, lr=0.000995,acc=0.987 ETA 01:30:59
[TRAIN] epoch=82, batch_id=152, loss=0.044152, lr=0.000994,acc=0.986 ETA 01:29:37
[TRAIN] epoch=82, batch_id=162, loss=0.042275, lr=0.000993,acc=0.987 ETA 01:28:45
[TRAIN] epoch=82, batch_id=172, loss=0.041392, lr=0.000992,acc=0.987 ETA 01:45:33
[TRAIN] epoch=82, batch_id=182, loss=0.039961, lr=0.000991,acc=0.988 ETA 01:28:38
[TRAIN] epoch=82, batch_id=192, loss=0.040862, lr=0.000990,acc=0.988 ETA 01:31:20
[TRAIN] epoch=82, batch_id=202, loss=0.041192, lr=0.000989,acc=0.988 ETA 01:28:36
[TRAIN] epoch=82, batch_id=212, loss=0.040685, lr=0.000988,acc=0.988 ETA 01:30:56
[TRAIN] epoch=82, batch_id=222, loss=0.041384, lr=0.000987,acc=0.988 ETA 01:27:06
[TRAIN] epoch=82, batch_id=232, loss=0.040330, lr=0.000985,acc=0.988 ETA 01:43:36
[TRAIN] epoch=82, batch_id=242, loss=0.040466, lr=0.000984,acc=0.988 ETA 01:27:51
[TRAIN] epoch=82, batch_id=252, loss=0.040149, lr=0.000983,acc=0.988 ETA 01:39:19
[TRAIN] epoch=82, batch_id=262, loss=0.039853, lr=0.000981,acc=0.988 ETA 01:29:40
[TRAIN] epoch=82, batch_id=272, loss=0.040682, lr=0.000980,acc=0.988 ETA 01:59:47
[TRAIN] epoch=82, batch_id=282, loss=0.040633, lr=0.000978,acc=0.988 ETA 01:43:14
[TRAIN] epoch=82, batch_id=292, loss=0.041499, lr=0.000977,acc=0.987 ETA 01:33:06
[EVAL] epoch=82

Evaluating top_k_accuracy ...

top1_acc	0.7780
top5_acc	0.9455

Evaluating mean_class_accuracy ...

mean_acc	0.7789
[TRAIN] epoch=83, batch_id=4, loss=0.010472, lr=0.000975,acc=1.000 ETA 22:18:26
[TRAIN] epoch=83, batch_id=14, loss=0.024120, lr=0.000974,acc=0.993 ETA 01:31:35
[TRAIN] epoch=83, batch_id=24, loss=0.029422, lr=0.000972,acc=0.991 ETA 01:27:04
[TRAIN] epoch=83, batch_id=34, loss=0.029370, lr=0.000970,acc=0.992 ETA 01:26:25
[TRAIN] epoch=83, batch_id=44, loss=0.028581, lr=0.000968,acc=0.991 ETA 01:26:46
[TRAIN] epoch=83, batch_id=54, loss=0.029570, lr=0.000966,acc=0.990 ETA 01:27:23
[TRAIN] epoch=83, batch_id=64, loss=0.031107, lr=0.000964,acc=0.990 ETA 01:33:19
[TRAIN] epoch=83, batch_id=74, loss=0.029946, lr=0.000962,acc=0.991 ETA 01:39:48
[TRAIN] epoch=83, batch_id=84, loss=0.032271, lr=0.000960,acc=0.990 ETA 01:29:09
[TRAIN] epoch=83, batch_id=94, loss=0.030676, lr=0.000958,acc=0.991 ETA 01:29:43
[TRAIN] epoch=83, batch_id=104, loss=0.030078, lr=0.000956,acc=0.992 ETA 01:51:56
[TRAIN] epoch=83, batch_id=114, loss=0.029756, lr=0.000954,acc=0.992 ETA 01:43:25
[TRAIN] epoch=83, batch_id=124, loss=0.028245, lr=0.000952,acc=0.992 ETA 01:47:25
[TRAIN] epoch=83, batch_id=134, loss=0.029098, lr=0.000949,acc=0.992 ETA 01:24:53
[TRAIN] epoch=83, batch_id=144, loss=0.030323, lr=0.000947,acc=0.991 ETA 01:26:23
[TRAIN] epoch=83, batch_id=154, loss=0.031498, lr=0.000945,acc=0.991 ETA 01:25:32
[TRAIN] epoch=83, batch_id=164, loss=0.032498, lr=0.000942,acc=0.991 ETA 02:35:38
[TRAIN] epoch=83, batch_id=174, loss=0.034626, lr=0.000940,acc=0.990 ETA 02:56:12
[TRAIN] epoch=83, batch_id=184, loss=0.034066, lr=0.000937,acc=0.990 ETA 02:13:38
[TRAIN] epoch=83, batch_id=194, loss=0.035429, lr=0.000935,acc=0.989 ETA 02:45:27
[TRAIN] epoch=83, batch_id=204, loss=0.036630, lr=0.000932,acc=0.988 ETA 02:13:28
[TRAIN] epoch=83, batch_id=214, loss=0.036685, lr=0.000929,acc=0.988 ETA 02:09:23
[TRAIN] epoch=83, batch_id=224, loss=0.035762, lr=0.000927,acc=0.988 ETA 01:49:32
[TRAIN] epoch=83, batch_id=234, loss=0.035880, lr=0.000924,acc=0.988 ETA 01:23:46
[TRAIN] epoch=83, batch_id=244, loss=0.034985, lr=0.000921,acc=0.989 ETA 01:22:36
[TRAIN] epoch=83, batch_id=254, loss=0.034538, lr=0.000918,acc=0.989 ETA 01:48:21
[TRAIN] epoch=83, batch_id=264, loss=0.035487, lr=0.000915,acc=0.988 ETA 01:42:29
[TRAIN] epoch=83, batch_id=274, loss=0.035271, lr=0.000912,acc=0.989 ETA 01:28:53
[TRAIN] epoch=83, batch_id=284, loss=0.034462, lr=0.000909,acc=0.989 ETA 01:24:06
[TRAIN] epoch=83, batch_id=294, loss=0.034668, lr=0.000906,acc=0.989 ETA 01:22:30
[EVAL] epoch=83

Evaluating top_k_accuracy ...

top1_acc	0.7872
top5_acc	0.9440

Evaluating mean_class_accuracy ...

mean_acc	0.7853
[TRAIN] epoch=84, batch_id=6, loss=0.048342, lr=0.000903,acc=0.974 ETA 20:36:19
[TRAIN] epoch=84, batch_id=16, loss=0.043992, lr=0.000900,acc=0.982 ETA 01:31:46
[TRAIN] epoch=84, batch_id=26, loss=0.039379, lr=0.000897,acc=0.987 ETA 01:24:39
[TRAIN] epoch=84, batch_id=36, loss=0.038524, lr=0.000894,acc=0.987 ETA 01:31:49
[TRAIN] epoch=84, batch_id=46, loss=0.041132, lr=0.000890,acc=0.987 ETA 01:23:35
[TRAIN] epoch=84, batch_id=56, loss=0.038014, lr=0.000887,acc=0.988 ETA 01:39:32
[TRAIN] epoch=84, batch_id=66, loss=0.037581, lr=0.000884,acc=0.987 ETA 01:22:08
[TRAIN] epoch=84, batch_id=76, loss=0.034880, lr=0.000880,acc=0.988 ETA 01:21:14
[TRAIN] epoch=84, batch_id=86, loss=0.037473, lr=0.000877,acc=0.988 ETA 01:22:20
[TRAIN] epoch=84, batch_id=96, loss=0.035366, lr=0.000873,acc=0.989 ETA 01:20:46
[TRAIN] epoch=84, batch_id=106, loss=0.037619, lr=0.000870,acc=0.989 ETA 01:22:37
[TRAIN] epoch=84, batch_id=116, loss=0.036681, lr=0.000866,acc=0.989 ETA 01:21:08
[TRAIN] epoch=84, batch_id=126, loss=0.036732, lr=0.000863,acc=0.990 ETA 01:22:09
[TRAIN] epoch=84, batch_id=136, loss=0.036267, lr=0.000859,acc=0.990 ETA 01:25:35
[TRAIN] epoch=84, batch_id=146, loss=0.035665, lr=0.000855,acc=0.990 ETA 01:53:04
[TRAIN] epoch=84, batch_id=156, loss=0.035079, lr=0.000852,acc=0.990 ETA 01:31:50
[TRAIN] epoch=84, batch_id=166, loss=0.034076, lr=0.000848,acc=0.990 ETA 01:28:01
[TRAIN] epoch=84, batch_id=176, loss=0.034520, lr=0.000844,acc=0.990 ETA 01:21:25
[TRAIN] epoch=84, batch_id=186, loss=0.035028, lr=0.000840,acc=0.990 ETA 01:20:50
[TRAIN] epoch=84, batch_id=196, loss=0.034721, lr=0.000836,acc=0.990 ETA 01:20:59
[TRAIN] epoch=84, batch_id=206, loss=0.035721, lr=0.000832,acc=0.990 ETA 01:21:04
[TRAIN] epoch=84, batch_id=216, loss=0.037404, lr=0.000829,acc=0.989 ETA 01:23:06
[TRAIN] epoch=84, batch_id=226, loss=0.037768, lr=0.000825,acc=0.989 ETA 01:19:59
[TRAIN] epoch=84, batch_id=236, loss=0.037760, lr=0.000820,acc=0.989 ETA 01:23:17
[TRAIN] epoch=84, batch_id=246, loss=0.037019, lr=0.000816,acc=0.989 ETA 01:19:50
[TRAIN] epoch=84, batch_id=256, loss=0.036701, lr=0.000812,acc=0.989 ETA 01:18:04
[TRAIN] epoch=84, batch_id=266, loss=0.037624, lr=0.000808,acc=0.989 ETA 01:19:20
[TRAIN] epoch=84, batch_id=276, loss=0.037569, lr=0.000804,acc=0.989 ETA 01:18:09
[TRAIN] epoch=84, batch_id=286, loss=0.037317, lr=0.000800,acc=0.989 ETA 01:35:59
[TRAIN] epoch=84, batch_id=296, loss=0.037704, lr=0.000796,acc=0.989 ETA 01:21:27
[EVAL] epoch=84

Evaluating top_k_accuracy ...

top1_acc	0.7803
top5_acc	0.9448

Evaluating mean_class_accuracy ...

mean_acc	0.7802
[TRAIN] epoch=85, batch_id=8, loss=0.055199, lr=0.000791,acc=0.980 ETA 20:16:04
[TRAIN] epoch=85, batch_id=18, loss=0.033273, lr=0.000787,acc=0.990 ETA 01:24:18
[TRAIN] epoch=85, batch_id=28, loss=0.030612, lr=0.000783,acc=0.990 ETA 01:18:48
[TRAIN] epoch=85, batch_id=38, loss=0.032927, lr=0.000778,acc=0.989 ETA 01:38:22
[TRAIN] epoch=85, batch_id=48, loss=0.035383, lr=0.000774,acc=0.988 ETA 01:24:30
[TRAIN] epoch=85, batch_id=58, loss=0.036531, lr=0.000770,acc=0.989 ETA 01:54:18
[TRAIN] epoch=85, batch_id=68, loss=0.036934, lr=0.000765,acc=0.988 ETA 01:21:53
[TRAIN] epoch=85, batch_id=78, loss=0.034813, lr=0.000761,acc=0.990 ETA 01:19:32
[TRAIN] epoch=85, batch_id=88, loss=0.034200, lr=0.000756,acc=0.990 ETA 01:20:52
[TRAIN] epoch=85, batch_id=98, loss=0.033721, lr=0.000752,acc=0.990 ETA 01:20:07
[TRAIN] epoch=85, batch_id=108, loss=0.032974, lr=0.000747,acc=0.991 ETA 01:22:13
[TRAIN] epoch=85, batch_id=118, loss=0.031126, lr=0.000742,acc=0.991 ETA 01:19:01
[TRAIN] epoch=85, batch_id=128, loss=0.030744, lr=0.000738,acc=0.992 ETA 01:22:59
[TRAIN] epoch=85, batch_id=138, loss=0.031328, lr=0.000733,acc=0.991 ETA 01:18:45
[TRAIN] epoch=85, batch_id=148, loss=0.031869, lr=0.000728,acc=0.991 ETA 01:17:49
[TRAIN] epoch=85, batch_id=158, loss=0.031858, lr=0.000724,acc=0.991 ETA 01:21:03
[TRAIN] epoch=85, batch_id=168, loss=0.032614, lr=0.000719,acc=0.990 ETA 01:18:40
[TRAIN] epoch=85, batch_id=178, loss=0.032403, lr=0.000714,acc=0.991 ETA 01:17:48
[TRAIN] epoch=85, batch_id=188, loss=0.032476, lr=0.000709,acc=0.991 ETA 01:18:33
[TRAIN] epoch=85, batch_id=198, loss=0.032311, lr=0.000705,acc=0.991 ETA 01:39:33
[TRAIN] epoch=85, batch_id=208, loss=0.031716, lr=0.000700,acc=0.991 ETA 01:23:30
[TRAIN] epoch=85, batch_id=218, loss=0.030906, lr=0.000695,acc=0.991 ETA 01:29:40
[TRAIN] epoch=85, batch_id=228, loss=0.030682, lr=0.000690,acc=0.991 ETA 01:17:02
[TRAIN] epoch=85, batch_id=238, loss=0.030649, lr=0.000685,acc=0.991 ETA 01:18:46
[TRAIN] epoch=85, batch_id=248, loss=0.032316, lr=0.000680,acc=0.990 ETA 01:16:33
[TRAIN] epoch=85, batch_id=258, loss=0.032538, lr=0.000675,acc=0.990 ETA 01:15:05
[TRAIN] epoch=85, batch_id=268, loss=0.032916, lr=0.000670,acc=0.990 ETA 01:15:12
[TRAIN] epoch=85, batch_id=278, loss=0.032742, lr=0.000665,acc=0.990 ETA 01:15:33
[TRAIN] epoch=85, batch_id=288, loss=0.033737, lr=0.000661,acc=0.989 ETA 01:15:47
[TRAIN] epoch=85, batch_id=298, loss=0.033143, lr=0.000656,acc=0.990 ETA 01:15:50
[EVAL] epoch=85

Evaluating top_k_accuracy ...

top1_acc	0.7843
top5_acc	0.9479

Evaluating mean_class_accuracy ...

mean_acc	0.7843
[TRAIN] epoch=86, batch_id=10, loss=0.049700, lr=0.000650,acc=0.988 ETA 17:50:42
[TRAIN] epoch=86, batch_id=20, loss=0.036038, lr=0.000645,acc=0.991 ETA 01:33:04
[TRAIN] epoch=86, batch_id=30, loss=0.033526, lr=0.000640,acc=0.991 ETA 01:17:27
[TRAIN] epoch=86, batch_id=40, loss=0.033378, lr=0.000635,acc=0.990 ETA 01:25:48
[TRAIN] epoch=86, batch_id=50, loss=0.033607, lr=0.000630,acc=0.991 ETA 01:15:54
[TRAIN] epoch=86, batch_id=60, loss=0.031584, lr=0.000625,acc=0.991 ETA 01:12:25
[TRAIN] epoch=86, batch_id=70, loss=0.033498, lr=0.000620,acc=0.990 ETA 01:15:48
[TRAIN] epoch=86, batch_id=80, loss=0.031731, lr=0.000615,acc=0.991 ETA 01:11:26
[TRAIN] epoch=86, batch_id=90, loss=0.031719, lr=0.000610,acc=0.991 ETA 01:10:38
[TRAIN] epoch=86, batch_id=100, loss=0.031505, lr=0.000605,acc=0.992 ETA 01:12:45
[TRAIN] epoch=86, batch_id=110, loss=0.032483, lr=0.000599,acc=0.991 ETA 01:13:43
[TRAIN] epoch=86, batch_id=120, loss=0.031054, lr=0.000594,acc=0.992 ETA 01:40:35
[TRAIN] epoch=86, batch_id=130, loss=0.032339, lr=0.000589,acc=0.992 ETA 01:41:24
[TRAIN] epoch=86, batch_id=140, loss=0.032152, lr=0.000584,acc=0.992 ETA 01:11:38
[TRAIN] epoch=86, batch_id=150, loss=0.030698, lr=0.000579,acc=0.992 ETA 01:10:29
[TRAIN] epoch=86, batch_id=160, loss=0.030803, lr=0.000574,acc=0.992 ETA 01:11:14
[TRAIN] epoch=86, batch_id=170, loss=0.031034, lr=0.000568,acc=0.992 ETA 01:09:54
[TRAIN] epoch=86, batch_id=180, loss=0.031239, lr=0.000563,acc=0.992 ETA 01:11:31
[TRAIN] epoch=86, batch_id=190, loss=0.031769, lr=0.000558,acc=0.992 ETA 01:08:45
[TRAIN] epoch=86, batch_id=200, loss=0.030984, lr=0.000553,acc=0.992 ETA 01:13:17
[TRAIN] epoch=86, batch_id=210, loss=0.030699, lr=0.000547,acc=0.992 ETA 01:09:54
[TRAIN] epoch=86, batch_id=220, loss=0.029738, lr=0.000542,acc=0.992 ETA 01:16:04
[TRAIN] epoch=86, batch_id=230, loss=0.029597, lr=0.000537,acc=0.992 ETA 01:08:46
[TRAIN] epoch=86, batch_id=240, loss=0.030850, lr=0.000532,acc=0.992 ETA 01:27:44
[TRAIN] epoch=86, batch_id=250, loss=0.030194, lr=0.000526,acc=0.992 ETA 01:07:54
[TRAIN] epoch=86, batch_id=260, loss=0.029891, lr=0.000521,acc=0.992 ETA 01:12:33
[TRAIN] epoch=86, batch_id=270, loss=0.029848, lr=0.000516,acc=0.992 ETA 01:08:02
[TRAIN] epoch=86, batch_id=280, loss=0.031022, lr=0.000511,acc=0.992 ETA 01:25:00
[TRAIN] epoch=86, batch_id=290, loss=0.031335, lr=0.000505,acc=0.992 ETA 01:08:09
[EVAL] epoch=86

Evaluating top_k_accuracy ...

top1_acc	0.7838
top5_acc	0.9424

Evaluating mean_class_accuracy ...

mean_acc	0.7830
[TRAIN] epoch=87, batch_id=2, loss=0.033836, lr=0.000500,acc=0.984 ETA 17:07:03
[TRAIN] epoch=87, batch_id=12, loss=0.042389, lr=0.000495,acc=0.987 ETA 01:09:04
[TRAIN] epoch=87, batch_id=22, loss=0.046347, lr=0.000489,acc=0.990 ETA 01:07:42
[TRAIN] epoch=87, batch_id=32, loss=0.039413, lr=0.000484,acc=0.990 ETA 01:08:46
[TRAIN] epoch=87, batch_id=42, loss=0.033830, lr=0.000479,acc=0.991 ETA 01:08:18
[TRAIN] epoch=87, batch_id=52, loss=0.035060, lr=0.000474,acc=0.990 ETA 01:13:42
[TRAIN] epoch=87, batch_id=62, loss=0.034510, lr=0.000468,acc=0.989 ETA 01:08:30
[TRAIN] epoch=87, batch_id=72, loss=0.031748, lr=0.000463,acc=0.991 ETA 01:07:32
[TRAIN] epoch=87, batch_id=82, loss=0.030689, lr=0.000458,acc=0.991 ETA 01:09:01
[TRAIN] epoch=87, batch_id=92, loss=0.031636, lr=0.000453,acc=0.990 ETA 01:06:31
[TRAIN] epoch=87, batch_id=102, loss=0.030897, lr=0.000447,acc=0.991 ETA 01:07:11
[TRAIN] epoch=87, batch_id=112, loss=0.030273, lr=0.000442,acc=0.991 ETA 01:06:31
[TRAIN] epoch=87, batch_id=122, loss=0.030316, lr=0.000437,acc=0.991 ETA 01:45:10
[TRAIN] epoch=87, batch_id=132, loss=0.031838, lr=0.000432,acc=0.991 ETA 01:41:40
[TRAIN] epoch=87, batch_id=142, loss=0.031090, lr=0.000426,acc=0.991 ETA 01:14:35
[TRAIN] epoch=87, batch_id=152, loss=0.030858, lr=0.000421,acc=0.991 ETA 01:05:13
[TRAIN] epoch=87, batch_id=162, loss=0.030973, lr=0.000416,acc=0.991 ETA 01:42:43
[TRAIN] epoch=87, batch_id=172, loss=0.030623, lr=0.000411,acc=0.991 ETA 01:06:11
[TRAIN] epoch=87, batch_id=182, loss=0.030735, lr=0.000406,acc=0.991 ETA 01:07:42
[TRAIN] epoch=87, batch_id=192, loss=0.030213, lr=0.000401,acc=0.991 ETA 01:10:34
[TRAIN] epoch=87, batch_id=202, loss=0.029657, lr=0.000395,acc=0.991 ETA 01:07:24
[TRAIN] epoch=87, batch_id=212, loss=0.030402, lr=0.000390,acc=0.991 ETA 01:11:58
[TRAIN] epoch=87, batch_id=222, loss=0.030133, lr=0.000385,acc=0.991 ETA 01:05:20
[TRAIN] epoch=87, batch_id=232, loss=0.029219, lr=0.000380,acc=0.991 ETA 01:12:23
[TRAIN] epoch=87, batch_id=242, loss=0.029051, lr=0.000375,acc=0.991 ETA 01:09:02
[TRAIN] epoch=87, batch_id=252, loss=0.029295, lr=0.000370,acc=0.991 ETA 01:04:02
[TRAIN] epoch=87, batch_id=262, loss=0.029336, lr=0.000365,acc=0.991 ETA 01:14:30
[TRAIN] epoch=87, batch_id=272, loss=0.029106, lr=0.000360,acc=0.992 ETA 01:06:55
[TRAIN] epoch=87, batch_id=282, loss=0.028969, lr=0.000355,acc=0.992 ETA 01:04:33
[TRAIN] epoch=87, batch_id=292, loss=0.029074, lr=0.000350,acc=0.992 ETA 01:05:05
[EVAL] epoch=87

Evaluating top_k_accuracy ...

top1_acc	0.7883
top5_acc	0.9442

Evaluating mean_class_accuracy ...

mean_acc	0.7876
[TRAIN] epoch=88, batch_id=4, loss=0.021343, lr=0.000344,acc=0.992 ETA 16:08:01
[TRAIN] epoch=88, batch_id=14, loss=0.014050, lr=0.000339,acc=0.998 ETA 01:19:46
[TRAIN] epoch=88, batch_id=24, loss=0.017544, lr=0.000335,acc=0.995 ETA 01:02:42
[TRAIN] epoch=88, batch_id=34, loss=0.019213, lr=0.000330,acc=0.994 ETA 01:07:05
[TRAIN] epoch=88, batch_id=44, loss=0.020479, lr=0.000325,acc=0.993 ETA 01:03:08
[TRAIN] epoch=88, batch_id=54, loss=0.022708, lr=0.000320,acc=0.992 ETA 01:31:54
[TRAIN] epoch=88, batch_id=64, loss=0.024453, lr=0.000315,acc=0.992 ETA 01:04:08
[TRAIN] epoch=88, batch_id=74, loss=0.024196, lr=0.000310,acc=0.993 ETA 01:18:44
[TRAIN] epoch=88, batch_id=84, loss=0.023339, lr=0.000305,acc=0.993 ETA 01:02:30
[TRAIN] epoch=88, batch_id=94, loss=0.025913, lr=0.000300,acc=0.993 ETA 01:04:24
[TRAIN] epoch=88, batch_id=104, loss=0.027390, lr=0.000295,acc=0.992 ETA 01:02:18
[TRAIN] epoch=88, batch_id=114, loss=0.030260, lr=0.000291,acc=0.992 ETA 01:02:55
[TRAIN] epoch=88, batch_id=124, loss=0.029467, lr=0.000286,acc=0.992 ETA 01:01:49
[TRAIN] epoch=88, batch_id=134, loss=0.031128, lr=0.000281,acc=0.991 ETA 01:01:37
[TRAIN] epoch=88, batch_id=144, loss=0.029974, lr=0.000276,acc=0.991 ETA 01:01:26
[TRAIN] epoch=88, batch_id=154, loss=0.029662, lr=0.000272,acc=0.991 ETA 01:02:50
[TRAIN] epoch=88, batch_id=164, loss=0.028405, lr=0.000267,acc=0.992 ETA 01:01:20
[TRAIN] epoch=88, batch_id=174, loss=0.027221, lr=0.000262,acc=0.992 ETA 01:03:58
[TRAIN] epoch=88, batch_id=184, loss=0.026667, lr=0.000258,acc=0.992 ETA 01:02:42
[TRAIN] epoch=88, batch_id=194, loss=0.026561, lr=0.000253,acc=0.992 ETA 01:04:05
[TRAIN] epoch=88, batch_id=204, loss=0.026201, lr=0.000248,acc=0.992 ETA 01:00:42
[TRAIN] epoch=88, batch_id=214, loss=0.025921, lr=0.000244,acc=0.993 ETA 01:01:04
[TRAIN] epoch=88, batch_id=224, loss=0.026761, lr=0.000239,acc=0.992 ETA 02:34:00
[TRAIN] epoch=88, batch_id=234, loss=0.026154, lr=0.000235,acc=0.992 ETA 02:19:47
[TRAIN] epoch=88, batch_id=244, loss=0.025645, lr=0.000230,acc=0.992 ETA 02:00:46
[TRAIN] epoch=88, batch_id=254, loss=0.025395, lr=0.000226,acc=0.992 ETA 01:43:47
[TRAIN] epoch=88, batch_id=264, loss=0.026431, lr=0.000222,acc=0.992 ETA 01:26:52
[TRAIN] epoch=88, batch_id=274, loss=0.025857, lr=0.000217,acc=0.992 ETA 01:00:21
[TRAIN] epoch=88, batch_id=284, loss=0.025641, lr=0.000213,acc=0.992 ETA 01:00:26
[TRAIN] epoch=88, batch_id=294, loss=0.025443, lr=0.000209,acc=0.992 ETA 00:59:51
[EVAL] epoch=88

Evaluating top_k_accuracy ...

top1_acc	0.7896
top5_acc	0.9434

Evaluating mean_class_accuracy ...

mean_acc	0.7889
[TRAIN] epoch=89, batch_id=6, loss=0.022595, lr=0.000204,acc=0.995 ETA 14:23:37
[TRAIN] epoch=89, batch_id=16, loss=0.016961, lr=0.000200,acc=0.996 ETA 01:00:31
[TRAIN] epoch=89, batch_id=26, loss=0.022003, lr=0.000196,acc=0.993 ETA 00:58:05
[TRAIN] epoch=89, batch_id=36, loss=0.019520, lr=0.000192,acc=0.995 ETA 01:03:53
[TRAIN] epoch=89, batch_id=46, loss=0.019187, lr=0.000188,acc=0.995 ETA 00:58:34
[TRAIN] epoch=89, batch_id=56, loss=0.020366, lr=0.000184,acc=0.994 ETA 01:01:59
[TRAIN] epoch=89, batch_id=66, loss=0.025335, lr=0.000180,acc=0.993 ETA 01:00:28
[TRAIN] epoch=89, batch_id=76, loss=0.023742, lr=0.000175,acc=0.994 ETA 00:57:25
[TRAIN] epoch=89, batch_id=86, loss=0.023216, lr=0.000171,acc=0.993 ETA 00:57:04
[TRAIN] epoch=89, batch_id=96, loss=0.023329, lr=0.000168,acc=0.993 ETA 00:56:40
[TRAIN] epoch=89, batch_id=106, loss=0.023642, lr=0.000164,acc=0.994 ETA 00:57:57
[TRAIN] epoch=89, batch_id=116, loss=0.023805, lr=0.000160,acc=0.993 ETA 01:00:49
[TRAIN] epoch=89, batch_id=126, loss=0.025895, lr=0.000156,acc=0.993 ETA 00:59:03
[TRAIN] epoch=89, batch_id=136, loss=0.025952, lr=0.000152,acc=0.993 ETA 00:59:31
[TRAIN] epoch=89, batch_id=146, loss=0.026206, lr=0.000148,acc=0.993 ETA 01:07:02
[TRAIN] epoch=89, batch_id=156, loss=0.025729, lr=0.000145,acc=0.993 ETA 00:56:49
[TRAIN] epoch=89, batch_id=166, loss=0.025813, lr=0.000141,acc=0.993 ETA 00:57:34
[TRAIN] epoch=89, batch_id=176, loss=0.026166, lr=0.000137,acc=0.993 ETA 00:57:21
[TRAIN] epoch=89, batch_id=186, loss=0.025575, lr=0.000134,acc=0.993 ETA 00:59:22
[TRAIN] epoch=89, batch_id=196, loss=0.025785, lr=0.000130,acc=0.993 ETA 00:56:14
[TRAIN] epoch=89, batch_id=206, loss=0.026511, lr=0.000127,acc=0.993 ETA 00:56:15
[TRAIN] epoch=89, batch_id=216, loss=0.026097, lr=0.000123,acc=0.993 ETA 00:54:49
[TRAIN] epoch=89, batch_id=226, loss=0.025356, lr=0.000120,acc=0.993 ETA 00:56:30
[TRAIN] epoch=89, batch_id=236, loss=0.025767, lr=0.000116,acc=0.993 ETA 00:55:16
[TRAIN] epoch=89, batch_id=246, loss=0.025278, lr=0.000113,acc=0.993 ETA 00:57:47
[TRAIN] epoch=89, batch_id=256, loss=0.025485, lr=0.000110,acc=0.993 ETA 01:11:05
[TRAIN] epoch=89, batch_id=266, loss=0.025483, lr=0.000106,acc=0.993 ETA 00:56:00
[TRAIN] epoch=89, batch_id=276, loss=0.025102, lr=0.000103,acc=0.993 ETA 00:54:45
[TRAIN] epoch=89, batch_id=286, loss=0.024522, lr=0.000100,acc=0.994 ETA 01:00:05
[TRAIN] epoch=89, batch_id=296, loss=0.024364, lr=0.000097,acc=0.994 ETA 00:55:40
[EVAL] epoch=89

Evaluating top_k_accuracy ...

top1_acc	0.7925
top5_acc	0.9434

Evaluating mean_class_accuracy ...

mean_acc	0.7917
[TRAIN] epoch=90, batch_id=8, loss=0.023386, lr=0.000094,acc=0.992 ETA 13:55:17
[TRAIN] epoch=90, batch_id=18, loss=0.024277, lr=0.000091,acc=0.991 ETA 00:54:19
[TRAIN] epoch=90, batch_id=28, loss=0.023295, lr=0.000088,acc=0.993 ETA 00:54:29
[TRAIN] epoch=90, batch_id=38, loss=0.029264, lr=0.000085,acc=0.992 ETA 00:54:27
[TRAIN] epoch=90, batch_id=48, loss=0.035159, lr=0.000082,acc=0.990 ETA 01:04:11
[TRAIN] epoch=90, batch_id=58, loss=0.034447, lr=0.000079,acc=0.990 ETA 00:53:42
[TRAIN] epoch=90, batch_id=68, loss=0.035425, lr=0.000076,acc=0.989 ETA 01:15:15
[TRAIN] epoch=90, batch_id=78, loss=0.034064, lr=0.000073,acc=0.989 ETA 00:54:09
[TRAIN] epoch=90, batch_id=88, loss=0.032075, lr=0.000071,acc=0.990 ETA 01:02:00
[TRAIN] epoch=90, batch_id=98, loss=0.030260, lr=0.000068,acc=0.990 ETA 00:52:52
[TRAIN] epoch=90, batch_id=108, loss=0.029110, lr=0.000065,acc=0.991 ETA 00:54:27
[TRAIN] epoch=90, batch_id=118, loss=0.030380, lr=0.000063,acc=0.991 ETA 00:54:35
[TRAIN] epoch=90, batch_id=128, loss=0.028870, lr=0.000060,acc=0.992 ETA 01:18:19
[TRAIN] epoch=90, batch_id=138, loss=0.028622, lr=0.000058,acc=0.992 ETA 01:15:45
[TRAIN] epoch=90, batch_id=148, loss=0.029173, lr=0.000055,acc=0.992 ETA 00:53:23
[TRAIN] epoch=90, batch_id=158, loss=0.029894, lr=0.000053,acc=0.992 ETA 00:52:36
[TRAIN] epoch=90, batch_id=168, loss=0.028901, lr=0.000051,acc=0.992 ETA 00:59:14
[TRAIN] epoch=90, batch_id=178, loss=0.028553, lr=0.000048,acc=0.992 ETA 00:51:04
[TRAIN] epoch=90, batch_id=188, loss=0.027754, lr=0.000046,acc=0.992 ETA 01:03:02
[TRAIN] epoch=90, batch_id=198, loss=0.026939, lr=0.000044,acc=0.992 ETA 00:51:54
[TRAIN] epoch=90, batch_id=208, loss=0.027056, lr=0.000042,acc=0.992 ETA 00:54:20
[TRAIN] epoch=90, batch_id=218, loss=0.026755, lr=0.000040,acc=0.992 ETA 00:50:32
[TRAIN] epoch=90, batch_id=228, loss=0.026474, lr=0.000038,acc=0.992 ETA 00:50:51
[TRAIN] epoch=90, batch_id=238, loss=0.026018, lr=0.000036,acc=0.992 ETA 00:50:50
[TRAIN] epoch=90, batch_id=248, loss=0.025657, lr=0.000034,acc=0.992 ETA 00:51:51
[TRAIN] epoch=90, batch_id=258, loss=0.026008, lr=0.000032,acc=0.992 ETA 00:50:02
[TRAIN] epoch=90, batch_id=268, loss=0.026458, lr=0.000030,acc=0.992 ETA 00:56:07
[TRAIN] epoch=90, batch_id=278, loss=0.025935, lr=0.000028,acc=0.992 ETA 00:49:31
[TRAIN] epoch=90, batch_id=288, loss=0.025755, lr=0.000026,acc=0.992 ETA 00:49:30
[TRAIN] epoch=90, batch_id=298, loss=0.025451, lr=0.000025,acc=0.992 ETA 00:48:45
[EVAL] epoch=90

Evaluating top_k_accuracy ...

top1_acc	0.7928
top5_acc	0.9455

Evaluating mean_class_accuracy ...

mean_acc	0.7920
[TRAIN] epoch=91, batch_id=10, loss=0.019637, lr=0.000023,acc=0.997 ETA 12:19:01
[TRAIN] epoch=91, batch_id=20, loss=0.023290, lr=0.000022,acc=0.994 ETA 00:50:47
[TRAIN] epoch=91, batch_id=30, loss=0.024850, lr=0.000020,acc=0.992 ETA 00:51:25
[TRAIN] epoch=91, batch_id=40, loss=0.025781, lr=0.000019,acc=0.990 ETA 00:49:40
[TRAIN] epoch=91, batch_id=50, loss=0.022614, lr=0.000017,acc=0.992 ETA 00:59:35
[TRAIN] epoch=91, batch_id=60, loss=0.025992, lr=0.000016,acc=0.991 ETA 00:47:56
[TRAIN] epoch=91, batch_id=70, loss=0.027867, lr=0.000015,acc=0.991 ETA 00:50:12
[TRAIN] epoch=91, batch_id=80, loss=0.026049, lr=0.000013,acc=0.991 ETA 00:48:24
[TRAIN] epoch=91, batch_id=90, loss=0.024935, lr=0.000012,acc=0.991 ETA 00:56:09
[TRAIN] epoch=91, batch_id=100, loss=0.024295, lr=0.000011,acc=0.992 ETA 00:47:49
[TRAIN] epoch=91, batch_id=110, loss=0.023180, lr=0.000010,acc=0.992 ETA 00:56:54
[TRAIN] epoch=91, batch_id=120, loss=0.022594, lr=0.000009,acc=0.992 ETA 00:47:00
[TRAIN] epoch=91, batch_id=130, loss=0.023904, lr=0.000008,acc=0.992 ETA 01:08:48
[TRAIN] epoch=91, batch_id=140, loss=0.024449, lr=0.000007,acc=0.992 ETA 01:12:41
[TRAIN] epoch=91, batch_id=150, loss=0.024060, lr=0.000006,acc=0.992 ETA 00:46:53
[TRAIN] epoch=91, batch_id=160, loss=0.024047, lr=0.000005,acc=0.992 ETA 00:45:59
[TRAIN] epoch=91, batch_id=170, loss=0.024306, lr=0.000005,acc=0.992 ETA 00:47:05
[TRAIN] epoch=91, batch_id=180, loss=0.024177, lr=0.000004,acc=0.992 ETA 00:47:11
[TRAIN] epoch=91, batch_id=190, loss=0.024432, lr=0.000003,acc=0.992 ETA 00:46:31
[TRAIN] epoch=91, batch_id=200, loss=0.024383, lr=0.000003,acc=0.992 ETA 00:46:06
[TRAIN] epoch=91, batch_id=210, loss=0.024036, lr=0.000002,acc=0.993 ETA 01:12:45
[TRAIN] epoch=91, batch_id=220, loss=0.024773, lr=0.000002,acc=0.992 ETA 01:32:47
[TRAIN] epoch=91, batch_id=230, loss=0.024806, lr=0.000001,acc=0.992 ETA 01:16:47
[TRAIN] epoch=91, batch_id=240, loss=0.024704, lr=0.000001,acc=0.992 ETA 01:28:47
[TRAIN] epoch=91, batch_id=250, loss=0.023933, lr=0.000001,acc=0.993 ETA 00:46:37
[TRAIN] epoch=91, batch_id=260, loss=0.023513, lr=0.000000,acc=0.993 ETA 00:46:55
[TRAIN] epoch=91, batch_id=270, loss=0.023312, lr=0.000000,acc=0.993 ETA 00:48:04
[TRAIN] epoch=91, batch_id=280, loss=0.022846, lr=0.000000,acc=0.993 ETA 00:44:42
[TRAIN] epoch=91, batch_id=290, loss=0.022895, lr=0.000000,acc=0.993 ETA 00:48:09
[EVAL] epoch=91

Evaluating top_k_accuracy ...

top1_acc	0.7930
top5_acc	0.9442

Evaluating mean_class_accuracy ...

mean_acc	0.7922
[TRAIN] epoch=92, batch_id=2, loss=0.004152, lr=0.000000,acc=1.000 ETA 10:54:14
[TRAIN] epoch=92, batch_id=12, loss=0.040841, lr=0.000000,acc=0.987 ETA 00:46:12
[TRAIN] epoch=92, batch_id=22, loss=0.033694, lr=0.000000,acc=0.989 ETA 00:50:04
[TRAIN] epoch=92, batch_id=32, loss=0.033464, lr=0.000000,acc=0.988 ETA 00:45:03
[TRAIN] epoch=92, batch_id=42, loss=0.028655, lr=0.000000,acc=0.991 ETA 00:45:10
[TRAIN] epoch=92, batch_id=52, loss=0.026522, lr=0.000001,acc=0.991 ETA 01:03:20
[TRAIN] epoch=92, batch_id=62, loss=0.027914, lr=0.000001,acc=0.990 ETA 01:06:58
[TRAIN] epoch=92, batch_id=72, loss=0.026934, lr=0.000001,acc=0.990 ETA 01:08:30
[TRAIN] epoch=92, batch_id=82, loss=0.024463, lr=0.000002,acc=0.992 ETA 01:03:32
[TRAIN] epoch=92, batch_id=92, loss=0.024042, lr=0.000002,acc=0.992 ETA 01:08:00
[TRAIN] epoch=92, batch_id=102, loss=0.024040, lr=0.000003,acc=0.992 ETA 00:47:00
[TRAIN] epoch=92, batch_id=112, loss=0.023351, lr=0.000003,acc=0.993 ETA 00:43:40
[TRAIN] epoch=92, batch_id=122, loss=0.022426, lr=0.000004,acc=0.993 ETA 00:43:29
[TRAIN] epoch=92, batch_id=132, loss=0.022173, lr=0.000005,acc=0.993 ETA 00:42:09
[TRAIN] epoch=92, batch_id=142, loss=0.021305, lr=0.000005,acc=0.994 ETA 00:43:12
[TRAIN] epoch=92, batch_id=152, loss=0.020561, lr=0.000006,acc=0.994 ETA 00:41:41
[TRAIN] epoch=92, batch_id=162, loss=0.019918, lr=0.000007,acc=0.994 ETA 00:44:35
[TRAIN] epoch=92, batch_id=172, loss=0.020200, lr=0.000008,acc=0.994 ETA 00:40:58
[TRAIN] epoch=92, batch_id=182, loss=0.020153, lr=0.000009,acc=0.994 ETA 00:44:37
[TRAIN] epoch=92, batch_id=192, loss=0.020045, lr=0.000010,acc=0.994 ETA 00:41:29
[TRAIN] epoch=92, batch_id=202, loss=0.019710, lr=0.000011,acc=0.994 ETA 00:56:48
[TRAIN] epoch=92, batch_id=212, loss=0.019865, lr=0.000012,acc=0.994 ETA 00:46:09
[TRAIN] epoch=92, batch_id=222, loss=0.020209, lr=0.000013,acc=0.994 ETA 00:55:53
[TRAIN] epoch=92, batch_id=232, loss=0.020139, lr=0.000015,acc=0.994 ETA 01:40:00
[TRAIN] epoch=92, batch_id=242, loss=0.019670, lr=0.000016,acc=0.994 ETA 00:40:28
[TRAIN] epoch=92, batch_id=252, loss=0.019472, lr=0.000017,acc=0.994 ETA 00:41:22
[TRAIN] epoch=92, batch_id=262, loss=0.018908, lr=0.000019,acc=0.995 ETA 00:44:34
[TRAIN] epoch=92, batch_id=272, loss=0.019760, lr=0.000020,acc=0.994 ETA 00:40:24
[TRAIN] epoch=92, batch_id=282, loss=0.019333, lr=0.000022,acc=0.995 ETA 00:40:11
[TRAIN] epoch=92, batch_id=292, loss=0.020494, lr=0.000023,acc=0.994 ETA 00:39:42
[EVAL] epoch=92

Evaluating top_k_accuracy ...

top1_acc	0.7933
top5_acc	0.9442

Evaluating mean_class_accuracy ...

mean_acc	0.7925
[TRAIN] epoch=93, batch_id=4, loss=0.006277, lr=0.000025,acc=1.000 ETA 10:24:20
[TRAIN] epoch=93, batch_id=14, loss=0.017793, lr=0.000026,acc=0.993 ETA 00:42:17
[TRAIN] epoch=93, batch_id=24, loss=0.019134, lr=0.000028,acc=0.992 ETA 00:40:41
[TRAIN] epoch=93, batch_id=34, loss=0.022812, lr=0.000030,acc=0.990 ETA 00:40:31
[TRAIN] epoch=93, batch_id=44, loss=0.023679, lr=0.000032,acc=0.989 ETA 00:40:55
[TRAIN] epoch=93, batch_id=54, loss=0.021162, lr=0.000034,acc=0.991 ETA 00:55:57
[TRAIN] epoch=93, batch_id=64, loss=0.020927, lr=0.000036,acc=0.992 ETA 00:48:40
[TRAIN] epoch=93, batch_id=74, loss=0.019708, lr=0.000038,acc=0.992 ETA 00:44:16
[TRAIN] epoch=93, batch_id=84, loss=0.020073, lr=0.000040,acc=0.992 ETA 00:42:43
[TRAIN] epoch=93, batch_id=94, loss=0.019783, lr=0.000042,acc=0.992 ETA 00:45:46
[TRAIN] epoch=93, batch_id=104, loss=0.022010, lr=0.000044,acc=0.992 ETA 00:40:15
[TRAIN] epoch=93, batch_id=114, loss=0.026031, lr=0.000046,acc=0.990 ETA 00:39:14
[TRAIN] epoch=93, batch_id=124, loss=0.025926, lr=0.000048,acc=0.991 ETA 00:39:19
[TRAIN] epoch=93, batch_id=134, loss=0.024637, lr=0.000051,acc=0.991 ETA 00:39:51
[TRAIN] epoch=93, batch_id=144, loss=0.024335, lr=0.000053,acc=0.991 ETA 00:38:45
[TRAIN] epoch=93, batch_id=154, loss=0.024916, lr=0.000055,acc=0.991 ETA 00:38:50
[TRAIN] epoch=93, batch_id=164, loss=0.024213, lr=0.000058,acc=0.991 ETA 00:38:38
[TRAIN] epoch=93, batch_id=174, loss=0.023385, lr=0.000060,acc=0.992 ETA 00:46:32
[TRAIN] epoch=93, batch_id=184, loss=0.022846, lr=0.000063,acc=0.992 ETA 00:38:47
[TRAIN] epoch=93, batch_id=194, loss=0.022599, lr=0.000065,acc=0.992 ETA 00:44:15
[TRAIN] epoch=93, batch_id=204, loss=0.023928, lr=0.000068,acc=0.992 ETA 00:37:37
[TRAIN] epoch=93, batch_id=214, loss=0.023563, lr=0.000071,acc=0.992 ETA 00:48:44
[TRAIN] epoch=93, batch_id=224, loss=0.023693, lr=0.000073,acc=0.992 ETA 00:37:21
[TRAIN] epoch=93, batch_id=234, loss=0.023787, lr=0.000076,acc=0.992 ETA 00:44:01
[TRAIN] epoch=93, batch_id=244, loss=0.024572, lr=0.000079,acc=0.992 ETA 00:37:03
[TRAIN] epoch=93, batch_id=254, loss=0.024609, lr=0.000082,acc=0.992 ETA 00:37:46
[TRAIN] epoch=93, batch_id=264, loss=0.023804, lr=0.000085,acc=0.992 ETA 00:35:42
[TRAIN] epoch=93, batch_id=274, loss=0.023240, lr=0.000088,acc=0.992 ETA 00:36:01
[TRAIN] epoch=93, batch_id=284, loss=0.022776, lr=0.000091,acc=0.993 ETA 00:36:12
[TRAIN] epoch=93, batch_id=294, loss=0.022398, lr=0.000094,acc=0.993 ETA 00:36:53
[EVAL] epoch=93

Evaluating top_k_accuracy ...

top1_acc	0.7914
top5_acc	0.9458

Evaluating mean_class_accuracy ...

mean_acc	0.7908
[TRAIN] epoch=94, batch_id=6, loss=0.011889, lr=0.000097,acc=0.995 ETA 08:32:20
[TRAIN] epoch=94, batch_id=16, loss=0.012474, lr=0.000100,acc=0.994 ETA 00:34:30
[TRAIN] epoch=94, batch_id=26, loss=0.014686, lr=0.000103,acc=0.994 ETA 00:42:41
[TRAIN] epoch=94, batch_id=36, loss=0.020974, lr=0.000106,acc=0.992 ETA 00:35:48
[TRAIN] epoch=94, batch_id=46, loss=0.017950, lr=0.000110,acc=0.994 ETA 00:37:06
[TRAIN] epoch=94, batch_id=56, loss=0.020955, lr=0.000113,acc=0.993 ETA 00:47:32
[TRAIN] epoch=94, batch_id=66, loss=0.021926, lr=0.000116,acc=0.992 ETA 00:35:47
[TRAIN] epoch=94, batch_id=76, loss=0.020102, lr=0.000120,acc=0.993 ETA 00:34:55
[TRAIN] epoch=94, batch_id=86, loss=0.019765, lr=0.000123,acc=0.993 ETA 00:33:11
[TRAIN] epoch=94, batch_id=96, loss=0.021081, lr=0.000127,acc=0.993 ETA 00:34:40
[TRAIN] epoch=94, batch_id=106, loss=0.020918, lr=0.000130,acc=0.993 ETA 00:34:30
[TRAIN] epoch=94, batch_id=116, loss=0.020217, lr=0.000134,acc=0.994 ETA 00:33:41
[TRAIN] epoch=94, batch_id=126, loss=0.020654, lr=0.000137,acc=0.994 ETA 00:32:47
[TRAIN] epoch=94, batch_id=136, loss=0.020132, lr=0.000141,acc=0.994 ETA 00:34:25
[TRAIN] epoch=94, batch_id=146, loss=0.021967, lr=0.000145,acc=0.993 ETA 00:32:31
[TRAIN] epoch=94, batch_id=156, loss=0.022643, lr=0.000148,acc=0.993 ETA 00:32:59
[TRAIN] epoch=94, batch_id=166, loss=0.022228, lr=0.000152,acc=0.993 ETA 00:32:30
[TRAIN] epoch=94, batch_id=176, loss=0.021713, lr=0.000156,acc=0.993 ETA 00:32:40
[TRAIN] epoch=94, batch_id=186, loss=0.021045, lr=0.000160,acc=0.993 ETA 00:31:25
[TRAIN] epoch=94, batch_id=196, loss=0.021100, lr=0.000164,acc=0.993 ETA 00:33:31
[TRAIN] epoch=94, batch_id=206, loss=0.020958, lr=0.000168,acc=0.993 ETA 00:31:19
[TRAIN] epoch=94, batch_id=216, loss=0.020629, lr=0.000171,acc=0.993 ETA 00:30:59
[TRAIN] epoch=94, batch_id=226, loss=0.021126, lr=0.000175,acc=0.993 ETA 00:31:24
[TRAIN] epoch=94, batch_id=236, loss=0.020696, lr=0.000180,acc=0.993 ETA 00:30:53
[TRAIN] epoch=94, batch_id=246, loss=0.020528, lr=0.000184,acc=0.993 ETA 00:31:40
[TRAIN] epoch=94, batch_id=256, loss=0.020719, lr=0.000188,acc=0.993 ETA 00:34:45
[TRAIN] epoch=94, batch_id=266, loss=0.020404, lr=0.000192,acc=0.993 ETA 00:35:55
[TRAIN] epoch=94, batch_id=276, loss=0.020590, lr=0.000196,acc=0.993 ETA 00:30:12
[TRAIN] epoch=94, batch_id=286, loss=0.020684, lr=0.000200,acc=0.993 ETA 00:30:26
[TRAIN] epoch=94, batch_id=296, loss=0.020546, lr=0.000204,acc=0.993 ETA 00:31:29
[EVAL] epoch=94

Evaluating top_k_accuracy ...

top1_acc	0.7933
top5_acc	0.9471

Evaluating mean_class_accuracy ...

mean_acc	0.7922
[TRAIN] epoch=95, batch_id=8, loss=0.015221, lr=0.000209,acc=1.000 ETA 07:36:31
[TRAIN] epoch=95, batch_id=18, loss=0.023386, lr=0.000213,acc=0.990 ETA 00:45:56
[TRAIN] epoch=95, batch_id=28, loss=0.020580, lr=0.000217,acc=0.991 ETA 00:43:00
[TRAIN] epoch=95, batch_id=38, loss=0.019800, lr=0.000222,acc=0.992 ETA 00:56:22
[TRAIN] epoch=95, batch_id=48, loss=0.022886, lr=0.000226,acc=0.991 ETA 00:31:10
[TRAIN] epoch=95, batch_id=58, loss=0.026888, lr=0.000230,acc=0.991 ETA 00:32:35
[TRAIN] epoch=95, batch_id=68, loss=0.024889, lr=0.000235,acc=0.992 ETA 00:29:14
[TRAIN] epoch=95, batch_id=78, loss=0.025867, lr=0.000239,acc=0.991 ETA 00:28:23
[TRAIN] epoch=95, batch_id=88, loss=0.026412, lr=0.000244,acc=0.990 ETA 00:28:24
[TRAIN] epoch=95, batch_id=98, loss=0.025438, lr=0.000248,acc=0.991 ETA 00:27:40
[TRAIN] epoch=95, batch_id=108, loss=0.025388, lr=0.000253,acc=0.990 ETA 00:28:27
[TRAIN] epoch=95, batch_id=118, loss=0.026285, lr=0.000258,acc=0.991 ETA 00:29:31
[TRAIN] epoch=95, batch_id=128, loss=0.025094, lr=0.000262,acc=0.991 ETA 00:27:38
[TRAIN] epoch=95, batch_id=138, loss=0.023726, lr=0.000267,acc=0.992 ETA 00:27:16
[TRAIN] epoch=95, batch_id=148, loss=0.023433, lr=0.000272,acc=0.992 ETA 00:30:33
[TRAIN] epoch=95, batch_id=158, loss=0.023133, lr=0.000276,acc=0.993 ETA 00:27:07
[TRAIN] epoch=95, batch_id=168, loss=0.022468, lr=0.000281,acc=0.993 ETA 00:29:10
[TRAIN] epoch=95, batch_id=178, loss=0.022391, lr=0.000286,acc=0.993 ETA 00:39:08
[TRAIN] epoch=95, batch_id=188, loss=0.022097, lr=0.000291,acc=0.993 ETA 00:44:28
[TRAIN] epoch=95, batch_id=198, loss=0.022873, lr=0.000295,acc=0.993 ETA 00:26:18
[TRAIN] epoch=95, batch_id=208, loss=0.022726, lr=0.000300,acc=0.993 ETA 00:32:14
[TRAIN] epoch=95, batch_id=218, loss=0.022318, lr=0.000305,acc=0.993 ETA 00:25:49
[TRAIN] epoch=95, batch_id=228, loss=0.021916, lr=0.000310,acc=0.993 ETA 00:31:40
[TRAIN] epoch=95, batch_id=238, loss=0.022250, lr=0.000315,acc=0.993 ETA 00:25:33
[TRAIN] epoch=95, batch_id=248, loss=0.022498, lr=0.000320,acc=0.993 ETA 00:26:55
[TRAIN] epoch=95, batch_id=258, loss=0.022093, lr=0.000325,acc=0.993 ETA 00:25:19
[TRAIN] epoch=95, batch_id=268, loss=0.021925, lr=0.000330,acc=0.993 ETA 00:25:25
[TRAIN] epoch=95, batch_id=278, loss=0.022345, lr=0.000335,acc=0.993 ETA 00:24:53
[TRAIN] epoch=95, batch_id=288, loss=0.022091, lr=0.000339,acc=0.993 ETA 00:24:30
[TRAIN] epoch=95, batch_id=298, loss=0.022116, lr=0.000344,acc=0.993 ETA 00:24:49
[EVAL] epoch=95

Evaluating top_k_accuracy ...

top1_acc	0.7906
top5_acc	0.9458

Evaluating mean_class_accuracy ...

mean_acc	0.7897
[TRAIN] epoch=96, batch_id=10, loss=0.031480, lr=0.000350,acc=0.991 ETA 06:01:19
[TRAIN] epoch=96, batch_id=20, loss=0.027861, lr=0.000355,acc=0.991 ETA 00:24:04
[TRAIN] epoch=96, batch_id=30, loss=0.021807, lr=0.000360,acc=0.993 ETA 00:23:46
[TRAIN] epoch=96, batch_id=40, loss=0.020708, lr=0.000365,acc=0.994 ETA 00:27:53
[TRAIN] epoch=96, batch_id=50, loss=0.021085, lr=0.000370,acc=0.994 ETA 00:25:09
[TRAIN] epoch=96, batch_id=60, loss=0.023187, lr=0.000375,acc=0.994 ETA 00:25:12
[TRAIN] epoch=96, batch_id=70, loss=0.023105, lr=0.000380,acc=0.994 ETA 00:23:42
[TRAIN] epoch=96, batch_id=80, loss=0.022438, lr=0.000385,acc=0.994 ETA 00:25:21
[TRAIN] epoch=96, batch_id=90, loss=0.022164, lr=0.000390,acc=0.994 ETA 00:22:58
[TRAIN] epoch=96, batch_id=100, loss=0.025708, lr=0.000395,acc=0.993 ETA 00:23:12
[TRAIN] epoch=96, batch_id=110, loss=0.024604, lr=0.000401,acc=0.993 ETA 00:22:47
[TRAIN] epoch=96, batch_id=120, loss=0.025854, lr=0.000406,acc=0.992 ETA 00:27:13
[TRAIN] epoch=96, batch_id=130, loss=0.027048, lr=0.000411,acc=0.992 ETA 00:22:27
[TRAIN] epoch=96, batch_id=140, loss=0.028877, lr=0.000416,acc=0.992 ETA 00:23:00
[TRAIN] epoch=96, batch_id=150, loss=0.028760, lr=0.000421,acc=0.992 ETA 00:24:12
[TRAIN] epoch=96, batch_id=160, loss=0.028258, lr=0.000426,acc=0.992 ETA 00:26:19
[TRAIN] epoch=96, batch_id=170, loss=0.028559, lr=0.000432,acc=0.992 ETA 00:40:24
[TRAIN] epoch=96, batch_id=180, loss=0.028241, lr=0.000437,acc=0.992 ETA 00:35:28
[TRAIN] epoch=96, batch_id=190, loss=0.027337, lr=0.000442,acc=0.992 ETA 00:41:17
[TRAIN] epoch=96, batch_id=200, loss=0.027514, lr=0.000447,acc=0.992 ETA 00:32:16
[TRAIN] epoch=96, batch_id=210, loss=0.026584, lr=0.000453,acc=0.992 ETA 00:21:12
[TRAIN] epoch=96, batch_id=220, loss=0.026585, lr=0.000458,acc=0.992 ETA 00:21:22
[TRAIN] epoch=96, batch_id=230, loss=0.026673, lr=0.000463,acc=0.992 ETA 00:20:44
[TRAIN] epoch=96, batch_id=240, loss=0.026501, lr=0.000468,acc=0.992 ETA 00:20:40
[TRAIN] epoch=96, batch_id=250, loss=0.026531, lr=0.000474,acc=0.992 ETA 00:20:39
[TRAIN] epoch=96, batch_id=260, loss=0.026160, lr=0.000479,acc=0.992 ETA 00:20:53
[TRAIN] epoch=96, batch_id=270, loss=0.025816, lr=0.000484,acc=0.992 ETA 00:20:08
[TRAIN] epoch=96, batch_id=280, loss=0.026502, lr=0.000489,acc=0.992 ETA 00:23:16
[TRAIN] epoch=96, batch_id=290, loss=0.026342, lr=0.000495,acc=0.992 ETA 00:21:30
[EVAL] epoch=96

Evaluating top_k_accuracy ...

top1_acc	0.7888
top5_acc	0.9469

Evaluating mean_class_accuracy ...

mean_acc	0.7892
[TRAIN] epoch=97, batch_id=2, loss=0.010754, lr=0.000500,acc=1.000 ETA 04:49:53
[TRAIN] epoch=97, batch_id=12, loss=0.016916, lr=0.000505,acc=0.995 ETA 00:19:39
[TRAIN] epoch=97, batch_id=22, loss=0.026801, lr=0.000511,acc=0.990 ETA 00:19:04
[TRAIN] epoch=97, batch_id=32, loss=0.022973, lr=0.000516,acc=0.992 ETA 00:19:15
[TRAIN] epoch=97, batch_id=42, loss=0.021385, lr=0.000521,acc=0.993 ETA 00:19:07
[TRAIN] epoch=97, batch_id=52, loss=0.023009, lr=0.000526,acc=0.992 ETA 00:20:42
[TRAIN] epoch=97, batch_id=62, loss=0.025642, lr=0.000532,acc=0.992 ETA 00:25:12
[TRAIN] epoch=97, batch_id=72, loss=0.028775, lr=0.000537,acc=0.991 ETA 00:21:41
[TRAIN] epoch=97, batch_id=82, loss=0.027239, lr=0.000542,acc=0.992 ETA 00:19:54
[TRAIN] epoch=97, batch_id=92, loss=0.026220, lr=0.000547,acc=0.992 ETA 00:18:09
[TRAIN] epoch=97, batch_id=102, loss=0.025440, lr=0.000553,acc=0.992 ETA 00:18:07
[TRAIN] epoch=97, batch_id=112, loss=0.025282, lr=0.000558,acc=0.992 ETA 00:20:54
[TRAIN] epoch=97, batch_id=122, loss=0.025354, lr=0.000563,acc=0.993 ETA 00:28:17
[TRAIN] epoch=97, batch_id=132, loss=0.024784, lr=0.000568,acc=0.993 ETA 00:20:24
[TRAIN] epoch=97, batch_id=142, loss=0.023686, lr=0.000574,acc=0.993 ETA 00:17:41
[TRAIN] epoch=97, batch_id=152, loss=0.023987, lr=0.000579,acc=0.993 ETA 00:17:22
[TRAIN] epoch=97, batch_id=162, loss=0.025623, lr=0.000584,acc=0.992 ETA 00:17:32
[TRAIN] epoch=97, batch_id=172, loss=0.025035, lr=0.000589,acc=0.992 ETA 00:20:45
[TRAIN] epoch=97, batch_id=182, loss=0.026232, lr=0.000594,acc=0.992 ETA 00:16:45
[TRAIN] epoch=97, batch_id=192, loss=0.025921, lr=0.000599,acc=0.992 ETA 00:16:35
[TRAIN] epoch=97, batch_id=202, loss=0.026069, lr=0.000605,acc=0.992 ETA 00:16:31
[TRAIN] epoch=97, batch_id=212, loss=0.025748, lr=0.000610,acc=0.992 ETA 00:18:03
[TRAIN] epoch=97, batch_id=222, loss=0.026090, lr=0.000615,acc=0.992 ETA 00:16:30
[TRAIN] epoch=97, batch_id=232, loss=0.026902, lr=0.000620,acc=0.992 ETA 00:15:56
[TRAIN] epoch=97, batch_id=242, loss=0.026824, lr=0.000625,acc=0.992 ETA 00:22:24
[TRAIN] epoch=97, batch_id=252, loss=0.026939, lr=0.000630,acc=0.992 ETA 00:22:06
[TRAIN] epoch=97, batch_id=262, loss=0.027780, lr=0.000635,acc=0.991 ETA 00:16:18
[TRAIN] epoch=97, batch_id=272, loss=0.027435, lr=0.000640,acc=0.991 ETA 00:18:44
[TRAIN] epoch=97, batch_id=282, loss=0.027002, lr=0.000645,acc=0.991 ETA 00:16:04
[TRAIN] epoch=97, batch_id=292, loss=0.026399, lr=0.000650,acc=0.992 ETA 00:14:59
[EVAL] epoch=97

Evaluating top_k_accuracy ...

top1_acc	0.7936
top5_acc	0.9442

Evaluating mean_class_accuracy ...

mean_acc	0.7923
[TRAIN] epoch=98, batch_id=4, loss=0.017221, lr=0.000656,acc=0.992 ETA 03:36:45
[TRAIN] epoch=98, batch_id=14, loss=0.013889, lr=0.000661,acc=0.996 ETA 00:15:00
[TRAIN] epoch=98, batch_id=24, loss=0.017886, lr=0.000665,acc=0.996 ETA 00:15:10
[TRAIN] epoch=98, batch_id=34, loss=0.017724, lr=0.000670,acc=0.995 ETA 00:14:38
[TRAIN] epoch=98, batch_id=44, loss=0.016902, lr=0.000675,acc=0.996 ETA 00:15:18
[TRAIN] epoch=98, batch_id=54, loss=0.017533, lr=0.000680,acc=0.995 ETA 00:14:26
[TRAIN] epoch=98, batch_id=64, loss=0.018335, lr=0.000685,acc=0.995 ETA 00:14:26
[TRAIN] epoch=98, batch_id=74, loss=0.021080, lr=0.000690,acc=0.994 ETA 00:14:08
[TRAIN] epoch=98, batch_id=84, loss=0.024066, lr=0.000695,acc=0.993 ETA 00:13:49
[TRAIN] epoch=98, batch_id=94, loss=0.028005, lr=0.000700,acc=0.992 ETA 00:13:35
[TRAIN] epoch=98, batch_id=104, loss=0.028519, lr=0.000705,acc=0.992 ETA 00:13:33
[TRAIN] epoch=98, batch_id=114, loss=0.028842, lr=0.000709,acc=0.992 ETA 00:13:10
[TRAIN] epoch=98, batch_id=124, loss=0.029489, lr=0.000714,acc=0.991 ETA 00:13:37
[TRAIN] epoch=98, batch_id=134, loss=0.027972, lr=0.000719,acc=0.992 ETA 00:13:22
[TRAIN] epoch=98, batch_id=144, loss=0.027274, lr=0.000724,acc=0.992 ETA 00:14:38
[TRAIN] epoch=98, batch_id=154, loss=0.028609, lr=0.000728,acc=0.991 ETA 00:12:57
[TRAIN] epoch=98, batch_id=164, loss=0.028260, lr=0.000733,acc=0.991 ETA 00:12:21
[TRAIN] epoch=98, batch_id=174, loss=0.027508, lr=0.000738,acc=0.992 ETA 00:15:00
[TRAIN] epoch=98, batch_id=184, loss=0.027410, lr=0.000742,acc=0.992 ETA 00:12:26
[TRAIN] epoch=98, batch_id=194, loss=0.027332, lr=0.000747,acc=0.992 ETA 00:12:05
[TRAIN] epoch=98, batch_id=204, loss=0.027602, lr=0.000752,acc=0.991 ETA 00:12:26
[TRAIN] epoch=98, batch_id=214, loss=0.026705, lr=0.000756,acc=0.992 ETA 00:11:21
[TRAIN] epoch=98, batch_id=224, loss=0.026668, lr=0.000761,acc=0.992 ETA 00:12:09
[TRAIN] epoch=98, batch_id=234, loss=0.026459, lr=0.000765,acc=0.992 ETA 00:15:22
[TRAIN] epoch=98, batch_id=244, loss=0.026334, lr=0.000770,acc=0.992 ETA 00:11:17
[TRAIN] epoch=98, batch_id=254, loss=0.025801, lr=0.000774,acc=0.992 ETA 00:10:56
[TRAIN] epoch=98, batch_id=264, loss=0.025093, lr=0.000778,acc=0.993 ETA 00:12:19
[TRAIN] epoch=98, batch_id=274, loss=0.025284, lr=0.000783,acc=0.992 ETA 00:11:24
[TRAIN] epoch=98, batch_id=284, loss=0.026523, lr=0.000787,acc=0.992 ETA 00:11:47
[TRAIN] epoch=98, batch_id=294, loss=0.027397, lr=0.000791,acc=0.991 ETA 00:10:34
[EVAL] epoch=98

Evaluating top_k_accuracy ...

top1_acc	0.7869
top5_acc	0.9445

Evaluating mean_class_accuracy ...

mean_acc	0.7870
[TRAIN] epoch=99, batch_id=6, loss=0.018584, lr=0.000796,acc=0.995 ETA 02:26:05
[TRAIN] epoch=99, batch_id=16, loss=0.026798, lr=0.000800,acc=0.992 ETA 00:12:12
[TRAIN] epoch=99, batch_id=26, loss=0.027323, lr=0.000804,acc=0.992 ETA 00:11:24
[TRAIN] epoch=99, batch_id=36, loss=0.039243, lr=0.000808,acc=0.988 ETA 00:09:15
[TRAIN] epoch=99, batch_id=46, loss=0.034341, lr=0.000812,acc=0.990 ETA 00:09:04
[TRAIN] epoch=99, batch_id=56, loss=0.036601, lr=0.000816,acc=0.989 ETA 00:09:17
[TRAIN] epoch=99, batch_id=66, loss=0.033958, lr=0.000820,acc=0.990 ETA 00:08:51
[TRAIN] epoch=99, batch_id=76, loss=0.030507, lr=0.000825,acc=0.991 ETA 00:08:40
[TRAIN] epoch=99, batch_id=86, loss=0.029262, lr=0.000829,acc=0.992 ETA 00:08:35
[TRAIN] epoch=99, batch_id=96, loss=0.029041, lr=0.000832,acc=0.992 ETA 00:08:12
[TRAIN] epoch=99, batch_id=106, loss=0.031792, lr=0.000836,acc=0.991 ETA 00:08:18
[TRAIN] epoch=99, batch_id=116, loss=0.030139, lr=0.000840,acc=0.992 ETA 00:07:57
[TRAIN] epoch=99, batch_id=126, loss=0.029357, lr=0.000844,acc=0.992 ETA 00:10:15
[TRAIN] epoch=99, batch_id=136, loss=0.029295, lr=0.000848,acc=0.992 ETA 00:12:04
[TRAIN] epoch=99, batch_id=146, loss=0.029513, lr=0.000852,acc=0.992 ETA 00:08:05
[TRAIN] epoch=99, batch_id=156, loss=0.029759, lr=0.000855,acc=0.992 ETA 00:07:19
[TRAIN] epoch=99, batch_id=166, loss=0.029829, lr=0.000859,acc=0.992 ETA 00:07:25
[TRAIN] epoch=99, batch_id=176, loss=0.029174, lr=0.000863,acc=0.992 ETA 00:06:50
[TRAIN] epoch=99, batch_id=186, loss=0.028673, lr=0.000866,acc=0.992 ETA 00:06:45
[TRAIN] epoch=99, batch_id=196, loss=0.028184, lr=0.000870,acc=0.992 ETA 00:06:34
[TRAIN] epoch=99, batch_id=206, loss=0.028835, lr=0.000873,acc=0.992 ETA 00:06:35
[TRAIN] epoch=99, batch_id=216, loss=0.028428, lr=0.000877,acc=0.992 ETA 00:06:16
[TRAIN] epoch=99, batch_id=226, loss=0.027893, lr=0.000880,acc=0.992 ETA 00:06:08
[TRAIN] epoch=99, batch_id=236, loss=0.027665, lr=0.000884,acc=0.992 ETA 00:06:05
[TRAIN] epoch=99, batch_id=246, loss=0.027164, lr=0.000887,acc=0.992 ETA 00:06:15
[TRAIN] epoch=99, batch_id=256, loss=0.027625, lr=0.000890,acc=0.992 ETA 00:06:16
[TRAIN] epoch=99, batch_id=266, loss=0.027272, lr=0.000894,acc=0.992 ETA 00:05:26
[TRAIN] epoch=99, batch_id=276, loss=0.028768, lr=0.000897,acc=0.991 ETA 00:05:32
[TRAIN] epoch=99, batch_id=286, loss=0.028818, lr=0.000900,acc=0.991 ETA 00:05:17
[TRAIN] epoch=99, batch_id=296, loss=0.029960, lr=0.000903,acc=0.991 ETA 00:05:12
[EVAL] epoch=99

Evaluating top_k_accuracy ...

top1_acc	0.7840
top5_acc	0.9440

Evaluating mean_class_accuracy ...

mean_acc	0.7832
[TRAIN] epoch=100, batch_id=8, loss=0.050718, lr=0.000906,acc=0.977 ETA 01:10:00
[TRAIN] epoch=100, batch_id=18, loss=0.042977, lr=0.000909,acc=0.986 ETA 00:04:40
[TRAIN] epoch=100, batch_id=28, loss=0.038501, lr=0.000912,acc=0.987 ETA 00:04:23
[TRAIN] epoch=100, batch_id=38, loss=0.040188, lr=0.000915,acc=0.988 ETA 00:05:01
[TRAIN] epoch=100, batch_id=48, loss=0.036744, lr=0.000918,acc=0.989 ETA 00:04:12
[TRAIN] epoch=100, batch_id=58, loss=0.039964, lr=0.000921,acc=0.987 ETA 00:04:00
[TRAIN] epoch=100, batch_id=68, loss=0.036276, lr=0.000924,acc=0.988 ETA 00:03:42
[TRAIN] epoch=100, batch_id=78, loss=0.039290, lr=0.000927,acc=0.988 ETA 00:03:45
[TRAIN] epoch=100, batch_id=88, loss=0.038702, lr=0.000929,acc=0.987 ETA 00:03:30
[TRAIN] epoch=100, batch_id=98, loss=0.037567, lr=0.000932,acc=0.988 ETA 00:03:20
[TRAIN] epoch=100, batch_id=108, loss=0.035972, lr=0.000935,acc=0.988 ETA 00:03:09
[TRAIN] epoch=100, batch_id=118, loss=0.037299, lr=0.000937,acc=0.988 ETA 00:03:03
[TRAIN] epoch=100, batch_id=128, loss=0.036763, lr=0.000940,acc=0.988 ETA 00:02:52
[TRAIN] epoch=100, batch_id=138, loss=0.037389, lr=0.000942,acc=0.988 ETA 00:02:44
[TRAIN] epoch=100, batch_id=148, loss=0.037713, lr=0.000945,acc=0.989 ETA 00:02:28
[TRAIN] epoch=100, batch_id=158, loss=0.036803, lr=0.000947,acc=0.989 ETA 00:02:30
[TRAIN] epoch=100, batch_id=168, loss=0.036978, lr=0.000949,acc=0.988 ETA 00:02:07
[TRAIN] epoch=100, batch_id=178, loss=0.036051, lr=0.000952,acc=0.989 ETA 00:02:04
[TRAIN] epoch=100, batch_id=188, loss=0.034704, lr=0.000954,acc=0.989 ETA 00:02:05
[TRAIN] epoch=100, batch_id=198, loss=0.034448, lr=0.000956,acc=0.989 ETA 00:01:50
[TRAIN] epoch=100, batch_id=208, loss=0.033668, lr=0.000958,acc=0.990 ETA 00:01:31
[TRAIN] epoch=100, batch_id=218, loss=0.033182, lr=0.000960,acc=0.990 ETA 00:01:20
[TRAIN] epoch=100, batch_id=228, loss=0.034015, lr=0.000962,acc=0.990 ETA 00:01:47
[TRAIN] epoch=100, batch_id=238, loss=0.033980, lr=0.000964,acc=0.990 ETA 00:01:23
[TRAIN] epoch=100, batch_id=248, loss=0.033944, lr=0.000966,acc=0.990 ETA 00:00:52
[TRAIN] epoch=100, batch_id=258, loss=0.033505, lr=0.000968,acc=0.990 ETA 00:00:39
[TRAIN] epoch=100, batch_id=268, loss=0.033504, lr=0.000970,acc=0.989 ETA 00:00:29
[TRAIN] epoch=100, batch_id=278, loss=0.033080, lr=0.000972,acc=0.990 ETA 00:00:19
[TRAIN] epoch=100, batch_id=288, loss=0.032564, lr=0.000974,acc=0.990 ETA 00:00:10
[TRAIN] epoch=100, batch_id=298, loss=0.032346, lr=0.000975,acc=0.990 ETA 00:00:00
[EVAL] epoch=100

Evaluating top_k_accuracy ...

top1_acc	0.7766
top5_acc	0.9434

Evaluating mean_class_accuracy ...

mean_acc	0.7777