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[09/17 15:09:31] VideoClip INFO: ------------------------------------
[09/17 15:09:31] VideoClip INFO: Environment Versions:
[09/17 15:09:31] VideoClip INFO: - Python: 3.7.6 (default, Jan 8 2020, 19:59:22)
[GCC 7.3.0]
[09/17 15:09:31] VideoClip INFO: - PyTorch: 1.8.1+cu111
[09/17 15:09:31] VideoClip INFO: - TorchVison: 0.9.1+cu111
[09/17 15:09:31] VideoClip INFO: ------------------------------------
[09/17 15:09:31] VideoClip INFO: { 'data': { 'batch_size': 4,
'dataset': 'hmdb51',
'image_tmpl': 'image_{:06d}.jpg',
'input_size': 224,
'label_list': 'lists/hmdb51_labels.csv',
'modality': 'RGB',
'num_classes': 51,
'num_segments': 16,
'random_shift': True,
'seg_length': 1,
'train_list': 'lists/hmdb51/train_rgb_split_1.txt',
'train_root': '/bpfs/v2_mnt/VIS/wuwenhao/hmdb51_rgb_img_256_340',
'val_list': 'lists/hmdb51/val_rgb_split_1.txt',
'val_root': '/bpfs/v2_mnt/VIS/wuwenhao/hmdb51_rgb_img_256_340',
'workers': 4},
'logging': {'eval_freq': 5, 'print_freq': 10},
'network': { 'arch': 'ViT-L/14',
'drop': 0,
'drop_out': 0.0,
'emb_dropout': 0.0,
'init': True,
'n_emb': 768,
'sim_header': 'Transf',
'type': 'clip_hmdb'},
'pretrain': 'exp_sota/kinetics400/ViT-L/14/f16/last_model.pt',
'resume': None,
'seed': 1024,
'solver': { 'clip_ratio': 0.1,
'epochs': 30,
'evaluate': False,
'grad_accumulation_steps': 2,
'loss_type': 'CE',
'lr': 5e-05,
'lr_warmup_step': 5,
'momentum': 0.9,
'optim': 'adamw',
'start_epoch': 0,
'type': 'cosine',
'weight_decay': 0.2}}
[09/17 15:09:31] VideoClip INFO: ------------------------------------
[09/17 15:09:31] VideoClip INFO: storing name: ./exp_revision/hmdb51/ViT-L/14/001
[09/17 15:09:47] VideoClip INFO: train transforms: [Compose(
<datasets.transforms_ss.GroupScale object at 0x7f8fb37a0d10>
Compose(
<datasets.transforms_ss.GroupRandomSizedCrop object at 0x7f8fb37a0c90>
<datasets.transforms_ss.GroupRandomHorizontalFlip object at 0x7f8fb37a0690>
)
<datasets.transforms_ss.GroupRandomGrayscale object at 0x7f8fb37a0990>
<datasets.transforms_ss.GroupGaussianBlur object at 0x7f8fb37a0b50>
<datasets.transforms_ss.GroupSolarization object at 0x7f8fb378aed0>
), Compose(
<datasets.transforms_ss.Stack object at 0x7f8fb378ae10>
<datasets.transforms_ss.ToTorchFormatTensor object at 0x7f8fb378a9d0>
<datasets.transforms_ss.GroupNormalize object at 0x7f8fb37a0e10>
)]
[09/17 15:09:47] VideoClip INFO: val transforms: [Compose(
<datasets.transforms_ss.GroupScale object at 0x7f8fb378a790>
<datasets.transforms_ss.GroupCenterCrop object at 0x7f8fb378a590>
), Compose(
<datasets.transforms_ss.Stack object at 0x7f8fb378a250>
<datasets.transforms_ss.ToTorchFormatTensor object at 0x7f8fb37871d0>
<datasets.transforms_ss.GroupNormalize object at 0x7f8fb378ac10>
)]
[09/17 15:09:47] VideoClip INFO: => load classes features from text_feats_hmdb51_ViT-L14.pt
[09/17 15:09:47] VideoClip INFO: => loading checkpoint 'exp_sota/kinetics400/ViT-L/14/f16/last_model.pt'
[09/17 15:10:27] VideoClip INFO: Epoch: [0][0/28], lr: 0.00e+00, eta: 3:04:36 Time 13.171 (13.171) Data 3.500 (3.500) Loss 1.5121 (1.5121)
[09/17 15:10:37] VideoClip INFO: Epoch: [0][10/28], lr: 3.21e-06, eta: 0:28:27 Time 0.814 (2.055) Data 0.011 (0.329) Loss 0.1599 (1.0788)
[09/17 15:10:44] VideoClip INFO: Epoch: [0][20/28], lr: 6.79e-06, eta: 0:19:25 Time 0.696 (1.419) Data 0.017 (0.178) Loss 1.0566 (0.9338)
[09/17 15:10:56] VideoClip INFO: Epoch: [1][0/28], lr: 1.00e-05, eta: 1:25:06 Time 6.281 (6.281) Data 3.634 (3.634) Loss 0.5209 (0.5209)
[09/17 15:11:03] VideoClip INFO: Epoch: [1][10/28], lr: 1.32e-05, eta: 0:16:29 Time 0.728 (1.232) Data 0.018 (0.344) Loss 0.5185 (0.5547)
[09/17 15:11:10] VideoClip INFO: Epoch: [1][20/28], lr: 1.68e-05, eta: 0:13:06 Time 0.716 (0.992) Data 0.014 (0.187) Loss 0.5710 (0.5145)
[09/17 15:11:24] VideoClip INFO: Epoch: [2][0/28], lr: 2.00e-05, eta: 1:34:41 Time 7.238 (7.238) Data 6.491 (6.491) Loss 0.7710 (0.7710)
[09/17 15:11:31] VideoClip INFO: Epoch: [2][10/28], lr: 2.32e-05, eta: 0:17:00 Time 0.731 (1.317) Data 0.012 (0.601) Loss 0.3805 (0.5649)
[09/17 15:11:38] VideoClip INFO: Epoch: [2][20/28], lr: 2.68e-05, eta: 0:13:13 Time 0.711 (1.037) Data 0.009 (0.321) Loss 0.5887 (0.5191)
[09/17 15:11:51] VideoClip INFO: Epoch: [3][0/28], lr: 3.00e-05, eta: 1:25:41 Time 6.792 (6.792) Data 3.888 (3.888) Loss 0.2907 (0.2907)
[09/17 15:11:58] VideoClip INFO: Epoch: [3][10/28], lr: 3.32e-05, eta: 0:15:55 Time 0.745 (1.279) Data 0.019 (0.367) Loss 0.6368 (0.4600)
[09/17 15:12:05] VideoClip INFO: Epoch: [3][20/28], lr: 3.68e-05, eta: 0:12:27 Time 0.698 (1.014) Data 0.009 (0.198) Loss 0.2492 (0.3602)
[09/17 15:12:18] VideoClip INFO: Epoch: [4][0/28], lr: 4.00e-05, eta: 1:27:36 Time 7.210 (7.210) Data 3.659 (3.659) Loss 0.1263 (0.1263)
[09/17 15:12:26] VideoClip INFO: Epoch: [4][10/28], lr: 4.32e-05, eta: 0:15:47 Time 0.731 (1.318) Data 0.018 (0.345) Loss 0.5754 (0.2555)
[09/17 15:12:33] VideoClip INFO: Epoch: [4][20/28], lr: 4.68e-05, eta: 0:12:15 Time 0.720 (1.037) Data 0.011 (0.187) Loss 0.2374 (0.2318)
[09/17 15:12:48] VideoClip INFO: Test: [0/12] Prec@1 85.938 (85.938) Prec@5 98.438 (98.438)
[09/17 15:12:50] VideoClip INFO: Test: [10/12] Prec@1 75.000 (80.469) Prec@5 93.750 (96.520)
[09/17 15:12:51] VideoClip INFO: Testing Results: Prec@1 79.818 Prec@5 96.224
[09/17 15:12:51] VideoClip INFO: Testing: 79.81770833333333/79.81770833333333
[09/17 15:12:51] VideoClip INFO: Saving:
[09/17 15:14:39] VideoClip INFO: Epoch: [5][0/28], lr: 5.00e-05, eta: 0:25:28 Time 2.180 (2.180) Data 1.437 (1.437) Loss 0.3311 (0.3311)
[09/17 15:14:47] VideoClip INFO: Epoch: [5][10/28], lr: 5.00e-05, eta: 0:09:56 Time 0.689 (0.864) Data 0.017 (0.145) Loss 0.9773 (0.2395)
[09/17 15:14:54] VideoClip INFO: Epoch: [5][20/28], lr: 4.99e-05, eta: 0:09:04 Time 0.721 (0.800) Data 0.019 (0.083) Loss 0.5129 (0.1816)
[09/17 15:15:06] VideoClip INFO: Epoch: [6][0/28], lr: 4.98e-05, eta: 1:11:41 Time 6.392 (6.392) Data 3.862 (3.862) Loss 0.9287 (0.9287)
[09/17 15:15:13] VideoClip INFO: Epoch: [6][10/28], lr: 4.97e-05, eta: 0:13:43 Time 0.707 (1.242) Data 0.009 (0.364) Loss 0.7130 (0.2546)
[09/17 15:15:21] VideoClip INFO: Epoch: [6][20/28], lr: 4.94e-05, eta: 0:10:50 Time 0.709 (0.997) Data 0.017 (0.197) Loss 0.0010 (0.2120)
[09/17 15:15:33] VideoClip INFO: Epoch: [7][0/28], lr: 4.92e-05, eta: 1:10:47 Time 6.586 (6.586) Data 3.606 (3.606) Loss 0.1408 (0.1408)
[09/17 15:15:40] VideoClip INFO: Epoch: [7][10/28], lr: 4.89e-05, eta: 0:13:17 Time 0.715 (1.256) Data 0.010 (0.337) Loss 0.4097 (0.2087)
[09/17 15:15:47] VideoClip INFO: Epoch: [7][20/28], lr: 4.86e-05, eta: 0:10:26 Time 0.703 (1.002) Data 0.016 (0.182) Loss 0.1547 (0.1458)
[09/17 15:15:59] VideoClip INFO: Epoch: [8][0/28], lr: 4.82e-05, eta: 0:56:48 Time 5.525 (5.525) Data 4.655 (4.655) Loss 0.1377 (0.1377)
[09/17 15:16:06] VideoClip INFO: Epoch: [8][10/28], lr: 4.79e-05, eta: 0:11:46 Time 0.706 (1.164) Data 0.009 (0.433) Loss 0.0048 (0.1987)
[09/17 15:16:13] VideoClip INFO: Epoch: [8][20/28], lr: 4.74e-05, eta: 0:09:31 Time 0.680 (0.958) Data 0.010 (0.231) Loss 0.0120 (0.1512)
[09/17 15:16:27] VideoClip INFO: Epoch: [9][0/28], lr: 4.69e-05, eta: 1:11:44 Time 7.309 (7.309) Data 3.983 (3.983) Loss 0.0254 (0.0254)
[09/17 15:16:34] VideoClip INFO: Epoch: [9][10/28], lr: 4.64e-05, eta: 0:12:48 Time 0.720 (1.327) Data 0.010 (0.373) Loss 0.4388 (0.0593)
[09/17 15:16:41] VideoClip INFO: Epoch: [9][20/28], lr: 4.58e-05, eta: 0:09:51 Time 0.694 (1.040) Data 0.008 (0.201) Loss 0.0136 (0.0695)
[09/17 15:16:52] VideoClip INFO: Test: [0/12] Prec@1 79.688 (79.688) Prec@5 98.438 (98.438)
[09/17 15:16:55] VideoClip INFO: Test: [10/12] Prec@1 78.906 (79.972) Prec@5 95.312 (97.514)
[09/17 15:16:56] VideoClip INFO: Testing Results: Prec@1 79.622 Prec@5 97.070
[09/17 15:16:56] VideoClip INFO: Testing: 79.62239583333333/79.81770833333333
[09/17 15:16:56] VideoClip INFO: Saving:
[09/17 15:17:53] VideoClip INFO: Epoch: [10][0/28], lr: 4.52e-05, eta: 0:21:47 Time 2.331 (2.331) Data 1.653 (1.653) Loss 0.0040 (0.0040)
[09/17 15:18:00] VideoClip INFO: Epoch: [10][10/28], lr: 4.46e-05, eta: 0:08:01 Time 0.734 (0.874) Data 0.016 (0.162) Loss 0.1929 (0.0995)
[09/17 15:18:08] VideoClip INFO: Epoch: [10][20/28], lr: 4.39e-05, eta: 0:07:14 Time 0.725 (0.803) Data 0.009 (0.093) Loss 0.0251 (0.1523)
[09/17 15:18:20] VideoClip INFO: Epoch: [11][0/28], lr: 4.32e-05, eta: 0:59:57 Time 6.749 (6.749) Data 4.493 (4.493) Loss 0.2491 (0.2491)
[09/17 15:18:27] VideoClip INFO: Epoch: [11][10/28], lr: 4.25e-05, eta: 0:11:07 Time 0.718 (1.276) Data 0.008 (0.419) Loss 0.0901 (0.0487)
[09/17 15:18:35] VideoClip INFO: Epoch: [11][20/28], lr: 4.17e-05, eta: 0:08:39 Time 0.706 (1.012) Data 0.010 (0.225) Loss 0.0028 (0.0477)
[09/17 15:18:47] VideoClip INFO: Epoch: [12][0/28], lr: 4.09e-05, eta: 0:57:00 Time 6.774 (6.774) Data 4.194 (4.194) Loss 0.0062 (0.0062)
[09/17 15:18:55] VideoClip INFO: Epoch: [12][10/28], lr: 4.01e-05, eta: 0:10:30 Time 0.709 (1.273) Data 0.009 (0.390) Loss 0.0306 (0.0506)
[09/17 15:19:02] VideoClip INFO: Epoch: [12][20/28], lr: 3.92e-05, eta: 0:08:09 Time 0.730 (1.010) Data 0.009 (0.209) Loss 0.5124 (0.0896)
[09/17 15:19:14] VideoClip INFO: Epoch: [13][0/28], lr: 3.84e-05, eta: 0:53:44 Time 6.760 (6.760) Data 4.534 (4.534) Loss 0.0236 (0.0236)
[09/17 15:19:22] VideoClip INFO: Epoch: [13][10/28], lr: 3.75e-05, eta: 0:09:55 Time 0.716 (1.274) Data 0.010 (0.421) Loss 0.0009 (0.1581)
[09/17 15:19:29] VideoClip INFO: Epoch: [13][20/28], lr: 3.65e-05, eta: 0:07:42 Time 0.695 (1.012) Data 0.011 (0.226) Loss 0.0658 (0.1090)
[09/17 15:19:41] VideoClip INFO: Epoch: [14][0/28], lr: 3.56e-05, eta: 0:50:43 Time 6.778 (6.778) Data 5.261 (5.261) Loss 0.0046 (0.0046)
[09/17 15:19:49] VideoClip INFO: Epoch: [14][10/28], lr: 3.47e-05, eta: 0:09:19 Time 0.698 (1.273) Data 0.012 (0.487) Loss 0.0931 (0.0704)
[09/17 15:19:56] VideoClip INFO: Epoch: [14][20/28], lr: 3.37e-05, eta: 0:07:14 Time 0.723 (1.012) Data 0.009 (0.261) Loss 0.0097 (0.0949)
[09/17 15:20:08] VideoClip INFO: Test: [0/12] Prec@1 78.906 (78.906) Prec@5 98.438 (98.438)
[09/17 15:20:11] VideoClip INFO: Test: [10/12] Prec@1 80.469 (79.332) Prec@5 94.531 (97.017)
[09/17 15:20:12] VideoClip INFO: Testing Results: Prec@1 79.102 Prec@5 96.875
[09/17 15:20:12] VideoClip INFO: Testing: 79.1015625/79.81770833333333
[09/17 15:20:12] VideoClip INFO: Saving:
[09/17 15:21:09] VideoClip INFO: Epoch: [15][0/28], lr: 3.27e-05, eta: 0:15:16 Time 2.176 (2.176) Data 1.499 (1.499) Loss 0.1097 (0.1097)
[09/17 15:21:17] VideoClip INFO: Epoch: [15][10/28], lr: 3.18e-05, eta: 0:05:55 Time 0.728 (0.864) Data 0.010 (0.145) Loss 0.3450 (0.0859)
[09/17 15:21:24] VideoClip INFO: Epoch: [15][20/28], lr: 3.07e-05, eta: 0:05:19 Time 0.706 (0.796) Data 0.011 (0.081) Loss 0.0072 (0.1035)
[09/17 15:21:37] VideoClip INFO: Epoch: [16][0/28], lr: 2.97e-05, eta: 0:50:05 Time 7.647 (7.647) Data 3.150 (3.150) Loss 0.0090 (0.0090)
[09/17 15:21:45] VideoClip INFO: Epoch: [16][10/28], lr: 2.87e-05, eta: 0:08:40 Time 0.713 (1.358) Data 0.022 (0.299) Loss 0.0042 (0.1246)
[09/17 15:21:52] VideoClip INFO: Epoch: [16][20/28], lr: 2.76e-05, eta: 0:06:34 Time 0.744 (1.059) Data 0.017 (0.162) Loss 0.0000 (0.0708)
[09/17 15:22:04] VideoClip INFO: Epoch: [17][0/28], lr: 2.66e-05, eta: 0:36:44 Time 6.040 (6.040) Data 3.949 (3.949) Loss 0.0049 (0.0049)
[09/17 15:22:11] VideoClip INFO: Epoch: [17][10/28], lr: 2.56e-05, eta: 0:07:09 Time 0.694 (1.210) Data 0.015 (0.370) Loss 0.0596 (0.0852)
[09/17 15:22:18] VideoClip INFO: Epoch: [17][20/28], lr: 2.44e-05, eta: 0:05:38 Time 0.705 (0.980) Data 0.021 (0.200) Loss 0.2798 (0.0880)
[09/17 15:22:30] VideoClip INFO: Epoch: [18][0/28], lr: 2.34e-05, eta: 0:34:24 Time 6.127 (6.127) Data 5.125 (5.125) Loss 0.0626 (0.0626)
[09/17 15:22:37] VideoClip INFO: Epoch: [18][10/28], lr: 2.24e-05, eta: 0:06:37 Time 0.722 (1.216) Data 0.010 (0.476) Loss 0.2615 (0.0533)
[09/17 15:22:45] VideoClip INFO: Epoch: [18][20/28], lr: 2.13e-05, eta: 0:05:11 Time 0.737 (0.983) Data 0.007 (0.254) Loss 0.0048 (0.0613)
[09/17 15:22:57] VideoClip INFO: Epoch: [19][0/28], lr: 2.03e-05, eta: 0:33:38 Time 6.534 (6.534) Data 4.466 (4.466) Loss 0.0098 (0.0098)
[09/17 15:23:04] VideoClip INFO: Epoch: [19][10/28], lr: 1.93e-05, eta: 0:06:14 Time 0.716 (1.254) Data 0.011 (0.415) Loss 0.0758 (0.0449)
[09/17 15:23:12] VideoClip INFO: Epoch: [19][20/28], lr: 1.82e-05, eta: 0:04:49 Time 0.721 (1.003) Data 0.008 (0.222) Loss 0.0496 (0.0506)
[09/17 15:23:24] VideoClip INFO: Test: [0/12] Prec@1 84.375 (84.375) Prec@5 97.656 (97.656)
[09/17 15:23:26] VideoClip INFO: Test: [10/12] Prec@1 78.125 (81.250) Prec@5 93.750 (96.591)
[09/17 15:23:27] VideoClip INFO: Testing Results: Prec@1 81.250 Prec@5 96.224
[09/17 15:23:27] VideoClip INFO: Testing: 81.25/81.25
[09/17 15:23:27] VideoClip INFO: Saving:
[09/17 15:25:16] VideoClip INFO: Epoch: [20][0/28], lr: 1.73e-05, eta: 0:10:45 Time 2.299 (2.299) Data 1.628 (1.628) Loss 0.0360 (0.0360)
[09/17 15:25:23] VideoClip INFO: Epoch: [20][10/28], lr: 1.63e-05, eta: 0:03:55 Time 0.720 (0.871) Data 0.009 (0.157) Loss 0.0069 (0.0677)
[09/17 15:25:31] VideoClip INFO: Epoch: [20][20/28], lr: 1.53e-05, eta: 0:03:29 Time 0.712 (0.801) Data 0.010 (0.087) Loss 0.2264 (0.0861)
[09/17 15:25:42] VideoClip INFO: Epoch: [21][0/28], lr: 1.44e-05, eta: 0:25:45 Time 6.108 (6.108) Data 4.510 (4.510) Loss 0.1959 (0.1959)
[09/17 15:25:50] VideoClip INFO: Epoch: [21][10/28], lr: 1.35e-05, eta: 0:04:55 Time 0.707 (1.215) Data 0.018 (0.420) Loss 0.1792 (0.0663)
[09/17 15:25:57] VideoClip INFO: Epoch: [21][20/28], lr: 1.25e-05, eta: 0:03:48 Time 0.715 (0.982) Data 0.010 (0.224) Loss 0.1458 (0.0499)
[09/17 15:26:10] VideoClip INFO: Epoch: [22][0/28], lr: 1.16e-05, eta: 0:26:42 Time 7.121 (7.121) Data 4.273 (4.273) Loss 0.0002 (0.0002)
[09/17 15:26:17] VideoClip INFO: Epoch: [22][10/28], lr: 1.08e-05, eta: 0:04:41 Time 0.731 (1.307) Data 0.008 (0.400) Loss 0.0176 (0.0262)
[09/17 15:26:24] VideoClip INFO: Epoch: [22][20/28], lr: 9.86e-06, eta: 0:03:31 Time 0.731 (1.031) Data 0.009 (0.215) Loss 0.0003 (0.0439)
[09/17 15:26:37] VideoClip INFO: Epoch: [23][0/28], lr: 9.06e-06, eta: 0:22:14 Time 6.775 (6.775) Data 3.415 (3.415) Loss 0.0507 (0.0507)
[09/17 15:26:44] VideoClip INFO: Epoch: [23][10/28], lr: 8.30e-06, eta: 0:03:58 Time 0.702 (1.273) Data 0.014 (0.324) Loss 0.1661 (0.0365)
[09/17 15:26:52] VideoClip INFO: Epoch: [23][20/28], lr: 7.48e-06, eta: 0:02:59 Time 0.721 (1.013) Data 0.014 (0.177) Loss 0.0002 (0.0480)
[09/17 15:27:04] VideoClip INFO: Epoch: [24][0/28], lr: 6.78e-06, eta: 0:17:27 Time 6.196 (6.196) Data 4.462 (4.462) Loss 0.3338 (0.3338)
[09/17 15:27:11] VideoClip INFO: Epoch: [24][10/28], lr: 6.10e-06, eta: 0:03:14 Time 0.696 (1.221) Data 0.010 (0.417) Loss 0.0672 (0.0472)
[09/17 15:27:18] VideoClip INFO: Epoch: [24][20/28], lr: 5.38e-06, eta: 0:02:26 Time 0.708 (0.984) Data 0.013 (0.226) Loss 0.0977 (0.0441)
[09/17 15:27:30] VideoClip INFO: Test: [0/12] Prec@1 81.250 (81.250) Prec@5 98.438 (98.438)
[09/17 15:27:33] VideoClip INFO: Test: [10/12] Prec@1 80.469 (80.753) Prec@5 92.969 (96.804)
[09/17 15:27:34] VideoClip INFO: Testing Results: Prec@1 80.599 Prec@5 96.549
[09/17 15:27:34] VideoClip INFO: Testing: 80.59895833333333/81.25
[09/17 15:27:34] VideoClip INFO: Saving:
[09/17 15:28:26] VideoClip INFO: Epoch: [25][0/28], lr: 4.77e-06, eta: 0:05:15 Time 2.239 (2.239) Data 1.573 (1.573) Loss 0.3312 (0.3312)
[09/17 15:28:34] VideoClip INFO: Epoch: [25][10/28], lr: 4.20e-06, eta: 0:01:54 Time 0.748 (0.873) Data 0.009 (0.151) Loss 0.0874 (0.0769)
[09/17 15:28:41] VideoClip INFO: Epoch: [25][20/28], lr: 3.60e-06, eta: 0:01:37 Time 0.704 (0.803) Data 0.010 (0.084) Loss 0.1511 (0.0954)
[09/17 15:28:53] VideoClip INFO: Epoch: [26][0/28], lr: 3.09e-06, eta: 0:11:17 Time 6.000 (6.000) Data 3.739 (3.739) Loss 0.0022 (0.0022)
[09/17 15:29:00] VideoClip INFO: Epoch: [26][10/28], lr: 2.62e-06, eta: 0:02:04 Time 0.707 (1.207) Data 0.016 (0.353) Loss 0.0009 (0.0654)
[09/17 15:29:07] VideoClip INFO: Epoch: [26][20/28], lr: 2.15e-06, eta: 0:01:30 Time 0.709 (0.977) Data 0.009 (0.192) Loss 0.0968 (0.0806)
[09/17 15:29:20] VideoClip INFO: Epoch: [27][0/28], lr: 1.76e-06, eta: 0:09:07 Time 6.437 (6.437) Data 3.839 (3.839) Loss 0.0067 (0.0067)
[09/17 15:29:27] VideoClip INFO: Epoch: [27][10/28], lr: 1.40e-06, eta: 0:01:33 Time 0.698 (1.242) Data 0.016 (0.359) Loss 0.0017 (0.0269)
[09/17 15:29:34] VideoClip INFO: Epoch: [27][20/28], lr: 1.06e-06, eta: 0:01:04 Time 0.727 (0.996) Data 0.008 (0.193) Loss 0.0007 (0.0178)
[09/17 15:29:46] VideoClip INFO: Epoch: [28][0/28], lr: 7.85e-07, eta: 0:06:07 Time 6.446 (6.446) Data 4.189 (4.189) Loss 0.0012 (0.0012)
[09/17 15:29:54] VideoClip INFO: Epoch: [28][10/28], lr: 5.54e-07, eta: 0:00:58 Time 0.742 (1.254) Data 0.010 (0.391) Loss 0.0011 (0.0027)
[09/17 15:30:01] VideoClip INFO: Epoch: [28][20/28], lr: 3.44e-07, eta: 0:00:37 Time 0.712 (1.003) Data 0.008 (0.210) Loss 0.0011 (0.0494)
[09/17 15:30:13] VideoClip INFO: Epoch: [29][0/28], lr: 1.97e-07, eta: 0:03:03 Time 6.337 (6.337) Data 3.777 (3.777) Loss 0.0001 (0.0001)
[09/17 15:30:20] VideoClip INFO: Epoch: [29][10/28], lr: 9.08e-08, eta: 0:00:23 Time 0.717 (1.237) Data 0.008 (0.354) Loss 0.0037 (0.0347)
[09/17 15:30:28] VideoClip INFO: Epoch: [29][20/28], lr: 2.04e-08, eta: 0:00:08 Time 0.707 (0.991) Data 0.008 (0.189) Loss 0.0396 (0.0297)
[09/17 15:30:39] VideoClip INFO: Test: [0/12] Prec@1 82.812 (82.812) Prec@5 98.438 (98.438)
[09/17 15:30:42] VideoClip INFO: Test: [10/12] Prec@1 78.906 (80.966) Prec@5 94.531 (96.804)
[09/17 15:30:43] VideoClip INFO: Testing Results: Prec@1 80.859 Prec@5 96.484
[09/17 15:30:43] VideoClip INFO: Testing: 80.859375/81.25
[09/17 15:30:43] VideoClip INFO: Saving: