FENet_imagenet.log

[2021-12-06 12:11:58,842] Namespace(auto_augment=False, batch_size=1024, cutout=False, data_dir='/dataset/public/ImageNetOrigin/', epoch=480, lr=0.6, nesterov=True, reduction=1.0, results_dir='./results/', resume='/data1/2021code/step2/FENet/results/04133134/FENet_imagenet.t7')
[2021-12-06 12:11:58,842] ==> Preparing data..
[2021-12-06 12:12:03,803] Training / Testing data number: 50000 / 1281167
[2021-12-06 12:12:03,803] Using path: ./results/06121158/
[2021-12-06 12:12:03,803] ==> Resuming from checkpoint.. /data1/2021code/step2/FENet/results/04133134/FENet_imagenet.t7
[2021-12-06 12:12:06,192] DataParallel(
  (module): FENet(
    (conv1): Conv2d(3, 16, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1), bias=False)
    (bn1): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (ibssl): IBSSL(
      (conv1): Conv2d(16, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
      (bn1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (shift2): SSL2d()
      (conv2): Conv2d(64, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)
      (bn2): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (ibpool): IBPool(
      (conv1): Conv2d(16, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)
      (bn1): BatchNorm2d(160, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      (shift2): AvgPool2d(kernel_size=2, stride=2, padding=0)
      (conv2): Conv2d(160, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
      (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    )
    (feblock1): FEBlock3n2s(
      (resibssl_1): ResIBSSL(
        (conv1): Conv2d(8, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(48, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(48, 8, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(8, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (resibssl_2): ResIBSSL(
        (conv1): Conv2d(16, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(96, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (ibpool): IBPool(
        (conv1): Conv2d(32, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): AvgPool2d(kernel_size=2, stride=2, padding=0)
        (conv2): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (feblock2): FEBlock4n2s(
      (resibssl_1): ResIBSSL(
        (conv1): Conv2d(8, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(48, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(48, 8, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(8, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (resibssl_2): ResIBSSL(
        (conv1): Conv2d(16, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(96, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (resibssl_3): ResIBSSL(
        (conv1): Conv2d(32, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(192, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (ibpool): IBPool(
        (conv1): Conv2d(64, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): AvgPool2d(kernel_size=2, stride=2, padding=0)
        (conv2): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (feblock3): FEBlock4n1s(
      (resibssl_1): ResIBSSL(
        (conv1): Conv2d(16, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(96, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (resibssl_2): ResIBSSL(
        (conv1): Conv2d(32, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(192, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (resibssl_3): ResIBSSL(
        (conv1): Conv2d(64, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (ibssl): IBSSL(
        (conv1): Conv2d(128, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (feblock4): FEBlock4n2s(
      (resibssl_1): ResIBSSL(
        (conv1): Conv2d(16, 96, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(96, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(96, 16, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(16, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (resibssl_2): ResIBSSL(
        (conv1): Conv2d(32, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(192, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(192, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (resibssl_3): ResIBSSL(
        (conv1): Conv2d(64, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (ibpool): IBPool(
        (conv1): Conv2d(128, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(1536, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): AvgPool2d(kernel_size=2, stride=2, padding=0)
        (conv2): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (feblock5): FEBlock3n1s(
      (resibssl_1): ResIBSSL(
        (conv1): Conv2d(64, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(384, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(384, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (resibssl_2): ResIBSSL(
        (conv1): Conv2d(128, 768, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(768, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
      (ibssl): IBSSL(
        (conv1): Conv2d(256, 1536, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn1): BatchNorm2d(1536, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
        (shift2): SSL2d()
        (conv2): Conv2d(1536, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
        (bn2): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
      )
    )
    (conv2): Conv2d(256, 1380, kernel_size=(1, 1), stride=(1, 1), bias=False)
    (bn2): BatchNorm2d(1380, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
    (gap): AdaptiveAvgPool2d(output_size=(1, 1))
    (dropout): Dropout(p=0.2, inplace=False)
    (fc): Conv2d(1380, 1000, kernel_size=(1, 1), stride=(1, 1))
  )
)
[2021-12-06 12:12:06,202] Epoch: 240
[2021-12-06 12:22:36,134] Train: Loss: 1.942 | Acc: 55.592 (712225/1281167) | Lr: 0.30000499999999974
[2021-12-06 12:23:18,439] Test: Loss: 1.881 | Acc: 55.736 (27868/50000)
[2021-12-06 12:23:18,439] Epoch: 241
[2021-12-06 12:33:28,467] Train: Loss: 1.937 | Acc: 55.701 (713626/1281167) | Lr: 0.29804155133448396
[2021-12-06 12:34:10,718] Test: Loss: 2.078 | Acc: 52.178 (26089/50000)
[2021-12-06 12:34:10,719] Epoch: 242
[2021-12-06 12:44:25,098] Train: Loss: 1.938 | Acc: 55.726 (713948/1281167) | Lr: 0.29607818677657416
[2021-12-06 12:45:08,406] Test: Loss: 1.809 | Acc: 57.002 (28501/50000)
[2021-12-06 12:45:08,406] Epoch: 243
[2021-12-06 12:55:17,826] Train: Loss: 1.932 | Acc: 55.776 (714580/1281167) | Lr: 0.29411499043027345
[2021-12-06 12:56:00,725] Test: Loss: 1.913 | Acc: 54.864 (27432/50000)
[2021-12-06 12:56:00,726] Epoch: 244
[2021-12-06 13:06:17,161] Train: Loss: 1.923 | Acc: 55.948 (716785/1281167) | Lr: 0.2921520463923793
[2021-12-06 13:06:59,613] Test: Loss: 1.925 | Acc: 54.710 (27355/50000)
[2021-12-06 13:06:59,614] Epoch: 245
[2021-12-06 13:17:10,970] Train: Loss: 1.919 | Acc: 56.074 (718397/1281167) | Lr: 0.290189438748881
[2021-12-06 13:17:52,985] Test: Loss: 1.750 | Acc: 58.304 (29152/50000)
[2021-12-06 13:17:52,986] Saving..
[2021-12-06 13:17:53,060] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-06 13:17:53,060] Epoch: 246
[2021-12-06 13:28:15,490] Train: Loss: 1.917 | Acc: 56.068 (718325/1281167) | Lr: 0.2882272515713579
[2021-12-06 13:28:56,787] Test: Loss: 1.788 | Acc: 57.380 (28690/50000)
[2021-12-06 13:28:56,787] Epoch: 247
[2021-12-06 13:39:13,625] Train: Loss: 1.912 | Acc: 56.195 (719952/1281167) | Lr: 0.2862655689133781
[2021-12-06 13:39:54,858] Test: Loss: 1.888 | Acc: 55.618 (27809/50000)
[2021-12-06 13:39:54,858] Epoch: 248
[2021-12-06 13:50:13,995] Train: Loss: 1.910 | Acc: 56.216 (720224/1281167) | Lr: 0.2843044748068978
[2021-12-06 13:50:58,833] Test: Loss: 1.951 | Acc: 54.706 (27353/50000)
[2021-12-06 13:50:58,834] Epoch: 249
[2021-12-06 14:01:14,480] Train: Loss: 1.902 | Acc: 56.421 (722852/1281167) | Lr: 0.2823440532586613
[2021-12-06 14:01:58,403] Test: Loss: 1.772 | Acc: 57.720 (28860/50000)
[2021-12-06 14:01:58,403] Epoch: 250
[2021-12-06 14:12:14,622] Train: Loss: 1.904 | Acc: 56.361 (722079/1281167) | Lr: 0.280384388246603
[2021-12-06 14:12:57,845] Test: Loss: 1.855 | Acc: 56.158 (28079/50000)
[2021-12-06 14:12:57,845] Epoch: 251
[2021-12-06 14:23:37,686] Train: Loss: 1.905 | Acc: 56.349 (721924/1281167) | Lr: 0.27842556371624966
[2021-12-06 14:24:21,335] Test: Loss: 1.850 | Acc: 56.368 (28184/50000)
[2021-12-06 14:24:21,336] Epoch: 252
[2021-12-06 14:34:56,054] Train: Loss: 1.897 | Acc: 56.482 (723628/1281167) | Lr: 0.27646766357712493
[2021-12-06 14:35:38,845] Test: Loss: 1.754 | Acc: 58.136 (29068/50000)
[2021-12-06 14:35:38,846] Epoch: 253
[2021-12-06 14:46:14,716] Train: Loss: 1.897 | Acc: 56.527 (724202/1281167) | Lr: 0.2745107716991541
[2021-12-06 14:46:56,852] Test: Loss: 1.824 | Acc: 56.802 (28401/50000)
[2021-12-06 14:46:56,852] Epoch: 254
[2021-12-06 14:57:38,552] Train: Loss: 1.893 | Acc: 56.548 (724479/1281167) | Lr: 0.27255497190907235
[2021-12-06 14:58:20,182] Test: Loss: 1.709 | Acc: 59.164 (29582/50000)
[2021-12-06 14:58:20,183] Saving..
[2021-12-06 14:58:20,240] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-06 14:58:20,241] Epoch: 255
[2021-12-06 15:08:58,841] Train: Loss: 1.891 | Acc: 56.580 (724887/1281167) | Lr: 0.2706003479868332
[2021-12-06 15:09:40,192] Test: Loss: 1.832 | Acc: 56.768 (28384/50000)
[2021-12-06 15:09:40,193] Epoch: 256
[2021-12-06 15:19:50,449] Train: Loss: 1.889 | Acc: 56.609 (725255/1281167) | Lr: 0.2686469836620201
[2021-12-06 15:20:31,644] Test: Loss: 1.787 | Acc: 57.680 (28840/50000)
[2021-12-06 15:20:31,644] Epoch: 257
[2021-12-06 15:30:26,533] Train: Loss: 1.883 | Acc: 56.697 (726380/1281167) | Lr: 0.26669496261025927
[2021-12-06 15:31:06,367] Test: Loss: 1.804 | Acc: 57.718 (28859/50000)
[2021-12-06 15:31:06,368] Epoch: 258
[2021-12-06 15:41:10,108] Train: Loss: 1.883 | Acc: 56.744 (726989/1281167) | Lr: 0.2647443684496358
[2021-12-06 15:41:52,470] Test: Loss: 1.862 | Acc: 56.186 (28093/50000)
[2021-12-06 15:41:52,470] Epoch: 259
[2021-12-06 15:51:50,129] Train: Loss: 1.879 | Acc: 56.821 (727966/1281167) | Lr: 0.2627952847371114
[2021-12-06 15:52:33,161] Test: Loss: 1.848 | Acc: 56.254 (28127/50000)
[2021-12-06 15:52:33,162] Epoch: 260
[2021-12-06 16:02:31,908] Train: Loss: 1.877 | Acc: 56.874 (728657/1281167) | Lr: 0.2608477949649454
[2021-12-06 16:03:14,385] Test: Loss: 1.812 | Acc: 57.194 (28597/50000)
[2021-12-06 16:03:14,386] Epoch: 261
[2021-12-06 16:13:14,922] Train: Loss: 1.875 | Acc: 56.910 (729112/1281167) | Lr: 0.25890198255711777
[2021-12-06 16:13:58,055] Test: Loss: 1.858 | Acc: 56.508 (28254/50000)
[2021-12-06 16:13:58,055] Epoch: 262
[2021-12-06 16:24:00,684] Train: Loss: 1.869 | Acc: 56.978 (729978/1281167) | Lr: 0.25695793086575586
[2021-12-06 16:24:44,219] Test: Loss: 1.980 | Acc: 54.080 (27040/50000)
[2021-12-06 16:24:44,220] Epoch: 263
[2021-12-06 16:34:43,751] Train: Loss: 1.870 | Acc: 57.031 (730665/1281167) | Lr: 0.25501572316756393
[2021-12-06 16:35:27,700] Test: Loss: 1.914 | Acc: 55.498 (27749/50000)
[2021-12-06 16:35:27,701] Epoch: 264
[2021-12-06 16:45:27,619] Train: Loss: 1.869 | Acc: 57.019 (730503/1281167) | Lr: 0.25307544266025567
[2021-12-06 16:46:09,875] Test: Loss: 1.812 | Acc: 57.164 (28582/50000)
[2021-12-06 16:46:09,876] Epoch: 265
[2021-12-06 16:56:11,474] Train: Loss: 1.862 | Acc: 57.137 (732024/1281167) | Lr: 0.2511371724589901
[2021-12-06 16:56:52,773] Test: Loss: 1.748 | Acc: 58.420 (29210/50000)
[2021-12-06 16:56:52,773] Epoch: 266
[2021-12-06 17:06:58,688] Train: Loss: 1.860 | Acc: 57.213 (732996/1281167) | Lr: 0.24920099559281159
[2021-12-06 17:07:40,234] Test: Loss: 1.731 | Acc: 58.728 (29364/50000)
[2021-12-06 17:07:40,234] Epoch: 267
[2021-12-06 17:19:24,106] Train: Loss: 1.862 | Acc: 57.187 (732657/1281167) | Lr: 0.2472669950010931
[2021-12-06 17:20:06,769] Test: Loss: 1.841 | Acc: 56.886 (28443/50000)
[2021-12-06 17:20:06,770] Epoch: 268
[2021-12-06 17:29:59,512] Train: Loss: 1.854 | Acc: 57.307 (734200/1281167) | Lr: 0.245335253529983
[2021-12-06 17:30:40,672] Test: Loss: 1.914 | Acc: 55.270 (27635/50000)
[2021-12-06 17:30:40,672] Epoch: 269
[2021-12-06 17:40:43,411] Train: Loss: 1.853 | Acc: 57.377 (735097/1281167) | Lr: 0.24340585392885664
[2021-12-06 17:41:25,042] Test: Loss: 1.889 | Acc: 55.802 (27901/50000)
[2021-12-06 17:41:25,042] Epoch: 270
[2021-12-06 17:53:09,708] Train: Loss: 1.849 | Acc: 57.408 (735486/1281167) | Lr: 0.24147887884677136
[2021-12-06 17:53:51,902] Test: Loss: 1.756 | Acc: 58.378 (29189/50000)
[2021-12-06 17:53:51,903] Epoch: 271
[2021-12-06 18:03:58,700] Train: Loss: 1.848 | Acc: 57.481 (736432/1281167) | Lr: 0.23955441082892628
[2021-12-06 18:04:40,860] Test: Loss: 1.647 | Acc: 60.444 (30222/50000)
[2021-12-06 18:04:40,860] Saving..
[2021-12-06 18:04:40,919] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-06 18:04:40,919] Epoch: 272
[2021-12-06 18:14:44,516] Train: Loss: 1.846 | Acc: 57.528 (737035/1281167) | Lr: 0.237632532313126
[2021-12-06 18:15:25,867] Test: Loss: 1.685 | Acc: 59.802 (29901/50000)
[2021-12-06 18:15:25,867] Epoch: 273
[2021-12-06 18:25:29,131] Train: Loss: 1.838 | Acc: 57.689 (739091/1281167) | Lr: 0.2357133256262498
[2021-12-06 18:26:12,581] Test: Loss: 1.692 | Acc: 59.972 (29986/50000)
[2021-12-06 18:26:12,582] Epoch: 274
[2021-12-06 18:36:22,696] Train: Loss: 1.843 | Acc: 57.547 (737278/1281167) | Lr: 0.23379687298072446
[2021-12-06 18:37:06,374] Test: Loss: 1.811 | Acc: 57.616 (28808/50000)
[2021-12-06 18:37:06,374] Epoch: 275
[2021-12-06 18:47:09,043] Train: Loss: 1.837 | Acc: 57.698 (739210/1281167) | Lr: 0.23188325647100297
[2021-12-06 18:47:51,711] Test: Loss: 2.026 | Acc: 53.572 (26786/50000)
[2021-12-06 18:47:51,711] Epoch: 276
[2021-12-06 18:57:55,025] Train: Loss: 1.834 | Acc: 57.743 (739781/1281167) | Lr: 0.2299725580700474
[2021-12-06 18:58:41,303] Test: Loss: 1.733 | Acc: 58.990 (29495/50000)
[2021-12-06 18:58:41,303] Epoch: 277
[2021-12-06 19:08:49,480] Train: Loss: 1.833 | Acc: 57.722 (739514/1281167) | Lr: 0.22806485962581804
[2021-12-06 19:09:32,048] Test: Loss: 1.655 | Acc: 60.750 (30375/50000)
[2021-12-06 19:09:32,049] Saving..
[2021-12-06 19:09:32,152] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-06 19:09:32,152] Epoch: 278
[2021-12-06 19:19:34,624] Train: Loss: 1.831 | Acc: 57.838 (740995/1281167) | Lr: 0.22616024285776695
[2021-12-06 19:20:15,849] Test: Loss: 2.288 | Acc: 48.972 (24486/50000)
[2021-12-06 19:20:15,849] Epoch: 279
[2021-12-06 19:30:18,881] Train: Loss: 1.827 | Acc: 57.846 (741098/1281167) | Lr: 0.22425878935333746
[2021-12-06 19:31:02,418] Test: Loss: 1.704 | Acc: 59.488 (29744/50000)
[2021-12-06 19:31:02,419] Epoch: 280
[2021-12-06 19:41:13,086] Train: Loss: 1.822 | Acc: 58.007 (743169/1281167) | Lr: 0.22236058056446906
[2021-12-06 19:41:55,310] Test: Loss: 1.632 | Acc: 61.076 (30538/50000)
[2021-12-06 19:41:55,310] Saving..
[2021-12-06 19:41:55,418] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-06 19:41:55,418] Epoch: 281
[2021-12-06 19:52:05,781] Train: Loss: 1.817 | Acc: 58.111 (744496/1281167) | Lr: 0.22046569780410857
[2021-12-06 19:52:48,742] Test: Loss: 1.740 | Acc: 58.814 (29407/50000)
[2021-12-06 19:52:48,742] Epoch: 282
[2021-12-06 20:02:56,540] Train: Loss: 1.818 | Acc: 58.052 (743747/1281167) | Lr: 0.2185742222427268
[2021-12-06 20:03:41,807] Test: Loss: 1.658 | Acc: 60.274 (30137/50000)
[2021-12-06 20:03:41,808] Epoch: 283
[2021-12-06 20:13:54,759] Train: Loss: 1.816 | Acc: 58.071 (743982/1281167) | Lr: 0.2166862349048415
[2021-12-06 20:14:38,365] Test: Loss: 1.790 | Acc: 57.668 (28834/50000)
[2021-12-06 20:14:38,366] Epoch: 284
[2021-12-06 20:25:00,059] Train: Loss: 1.813 | Acc: 58.157 (745093/1281167) | Lr: 0.21480181666554649
[2021-12-06 20:25:44,356] Test: Loss: 1.638 | Acc: 60.718 (30359/50000)
[2021-12-06 20:25:44,356] Epoch: 285
[2021-12-06 20:36:09,728] Train: Loss: 1.809 | Acc: 58.257 (746374/1281167) | Lr: 0.21292104824704733
[2021-12-06 20:36:53,471] Test: Loss: 1.782 | Acc: 57.746 (28873/50000)
[2021-12-06 20:36:53,472] Epoch: 286
[2021-12-06 20:47:15,583] Train: Loss: 1.806 | Acc: 58.298 (746893/1281167) | Lr: 0.21104401021520333
[2021-12-06 20:48:01,001] Test: Loss: 1.799 | Acc: 57.330 (28665/50000)
[2021-12-06 20:48:01,002] Epoch: 287
[2021-12-06 20:58:17,241] Train: Loss: 1.805 | Acc: 58.340 (747429/1281167) | Lr: 0.20917078297607666
[2021-12-06 20:59:00,948] Test: Loss: 1.622 | Acc: 60.998 (30499/50000)
[2021-12-06 20:59:00,950] Epoch: 288
[2021-12-06 21:09:16,995] Train: Loss: 1.804 | Acc: 58.314 (747102/1281167) | Lr: 0.20730144677248746
[2021-12-06 21:10:02,438] Test: Loss: 1.653 | Acc: 60.476 (30238/50000)
[2021-12-06 21:10:02,439] Epoch: 289
[2021-12-06 21:20:06,336] Train: Loss: 1.797 | Acc: 58.466 (749051/1281167) | Lr: 0.20543608168057714
[2021-12-06 21:20:51,444] Test: Loss: 1.712 | Acc: 59.060 (29530/50000)
[2021-12-06 21:20:51,444] Epoch: 290
[2021-12-06 21:31:03,480] Train: Loss: 1.795 | Acc: 58.531 (749874/1281167) | Lr: 0.2035747676063779
[2021-12-06 21:31:48,404] Test: Loss: 1.855 | Acc: 56.668 (28334/50000)
[2021-12-06 21:31:48,405] Epoch: 291
[2021-12-06 21:41:53,218] Train: Loss: 1.793 | Acc: 58.615 (750962/1281167) | Lr: 0.2017175842823896
[2021-12-06 21:42:37,975] Test: Loss: 1.623 | Acc: 61.030 (30515/50000)
[2021-12-06 21:42:37,975] Epoch: 292
[2021-12-06 21:52:41,394] Train: Loss: 1.793 | Acc: 58.542 (750015/1281167) | Lr: 0.1998646112641647
[2021-12-06 21:53:28,464] Test: Loss: 1.636 | Acc: 60.698 (30349/50000)
[2021-12-06 21:53:28,464] Epoch: 293
[2021-12-06 22:03:36,145] Train: Loss: 1.788 | Acc: 58.671 (751673/1281167) | Lr: 0.1980159279269002
[2021-12-06 22:04:25,191] Test: Loss: 1.637 | Acc: 60.694 (30347/50000)
[2021-12-06 22:04:25,192] Epoch: 294
[2021-12-06 22:14:27,434] Train: Loss: 1.789 | Acc: 58.572 (750400/1281167) | Lr: 0.1961716134620373
[2021-12-06 22:15:12,646] Test: Loss: 1.642 | Acc: 60.676 (30338/50000)
[2021-12-06 22:15:12,646] Epoch: 295
[2021-12-06 22:25:13,628] Train: Loss: 1.780 | Acc: 58.830 (753707/1281167) | Lr: 0.19433174687386934
[2021-12-06 22:25:58,917] Test: Loss: 1.687 | Acc: 60.076 (30038/50000)
[2021-12-06 22:25:58,918] Epoch: 296
[2021-12-06 22:36:06,887] Train: Loss: 1.782 | Acc: 58.802 (753351/1281167) | Lr: 0.19249640697615744
[2021-12-06 22:36:52,910] Test: Loss: 1.720 | Acc: 59.136 (29568/50000)
[2021-12-06 22:36:52,910] Epoch: 297
[2021-12-06 22:46:57,423] Train: Loss: 1.773 | Acc: 59.014 (756065/1281167) | Lr: 0.1906656723887543
[2021-12-06 22:47:46,927] Test: Loss: 1.675 | Acc: 60.132 (30066/50000)
[2021-12-06 22:47:46,927] Epoch: 298
[2021-12-06 22:57:49,013] Train: Loss: 1.771 | Acc: 58.960 (755382/1281167) | Lr: 0.1888396215342365
[2021-12-06 22:58:35,124] Test: Loss: 1.757 | Acc: 58.558 (29279/50000)
[2021-12-06 22:58:35,125] Epoch: 299
[2021-12-06 23:08:42,542] Train: Loss: 1.766 | Acc: 59.098 (757148/1281167) | Lr: 0.18701833263454504
[2021-12-06 23:09:28,551] Test: Loss: 1.589 | Acc: 61.708 (30854/50000)
[2021-12-06 23:09:28,551] Saving..
[2021-12-06 23:09:28,627] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-06 23:09:28,627] Epoch: 300
[2021-12-06 23:19:30,321] Train: Loss: 1.765 | Acc: 59.162 (757968/1281167) | Lr: 0.1852018837076347
[2021-12-06 23:20:21,930] Test: Loss: 1.707 | Acc: 59.258 (29629/50000)
[2021-12-06 23:20:21,930] Epoch: 301
[2021-12-06 23:30:29,364] Train: Loss: 1.767 | Acc: 59.119 (757415/1281167) | Lr: 0.1833903525641319
[2021-12-06 23:31:18,724] Test: Loss: 1.576 | Acc: 61.928 (30964/50000)
[2021-12-06 23:31:18,724] Saving..
[2021-12-06 23:31:18,821] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-06 23:31:18,821] Epoch: 302
[2021-12-06 23:41:24,149] Train: Loss: 1.761 | Acc: 59.202 (758477/1281167) | Lr: 0.1815838168040016
[2021-12-06 23:42:16,922] Test: Loss: 1.572 | Acc: 62.056 (31028/50000)
[2021-12-06 23:42:16,923] Saving..
[2021-12-06 23:42:16,998] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-06 23:42:16,998] Epoch: 303
[2021-12-06 23:52:23,595] Train: Loss: 1.759 | Acc: 59.301 (759749/1281167) | Lr: 0.17978235381322308
[2021-12-06 23:53:13,690] Test: Loss: 1.555 | Acc: 62.548 (31274/50000)
[2021-12-06 23:53:13,690] Saving..
[2021-12-06 23:53:13,747] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-06 23:53:13,747] Epoch: 304
[2021-12-07 00:03:14,878] Train: Loss: 1.754 | Acc: 59.344 (760294/1281167) | Lr: 0.17798604076047517
[2021-12-07 00:04:02,506] Test: Loss: 1.594 | Acc: 61.554 (30777/50000)
[2021-12-07 00:04:02,506] Epoch: 305
[2021-12-07 00:14:12,222] Train: Loss: 1.753 | Acc: 59.390 (760886/1281167) | Lr: 0.17619495459383036
[2021-12-07 00:14:58,623] Test: Loss: 1.583 | Acc: 61.872 (30936/50000)
[2021-12-07 00:14:58,624] Epoch: 306
[2021-12-07 00:24:58,742] Train: Loss: 1.753 | Acc: 59.395 (760955/1281167) | Lr: 0.17440917203745904
[2021-12-07 00:25:43,414] Test: Loss: 1.609 | Acc: 61.332 (30666/50000)
[2021-12-07 00:25:43,415] Epoch: 307
[2021-12-07 00:35:54,943] Train: Loss: 1.747 | Acc: 59.464 (761827/1281167) | Lr: 0.17262876958834228
[2021-12-07 00:36:41,638] Test: Loss: 1.552 | Acc: 62.482 (31241/50000)
[2021-12-07 00:36:41,639] Epoch: 308
[2021-12-07 00:46:52,383] Train: Loss: 1.746 | Acc: 59.563 (763102/1281167) | Lr: 0.1708538235129954
[2021-12-07 00:47:38,019] Test: Loss: 1.782 | Acc: 58.170 (29085/50000)
[2021-12-07 00:47:38,019] Epoch: 309
[2021-12-07 00:57:52,478] Train: Loss: 1.738 | Acc: 59.685 (764664/1281167) | Lr: 0.16908440984420062
[2021-12-07 00:58:39,269] Test: Loss: 1.646 | Acc: 60.680 (30340/50000)
[2021-12-07 00:58:39,270] Epoch: 310
[2021-12-07 01:08:55,204] Train: Loss: 1.737 | Acc: 59.702 (764881/1281167) | Lr: 0.16732060437775062
[2021-12-07 01:09:43,522] Test: Loss: 1.579 | Acc: 61.660 (30830/50000)
[2021-12-07 01:09:43,523] Epoch: 311
[2021-12-07 01:19:54,339] Train: Loss: 1.733 | Acc: 59.808 (766237/1281167) | Lr: 0.16556248266920107
[2021-12-07 01:20:45,101] Test: Loss: 1.656 | Acc: 60.590 (30295/50000)
[2021-12-07 01:20:45,101] Epoch: 312
[2021-12-07 01:31:03,445] Train: Loss: 1.731 | Acc: 59.838 (766620/1281167) | Lr: 0.16381012003063453
[2021-12-07 01:31:50,998] Test: Loss: 1.743 | Acc: 58.930 (29465/50000)
[2021-12-07 01:31:50,998] Epoch: 313
[2021-12-07 01:42:08,283] Train: Loss: 1.729 | Acc: 59.885 (767233/1281167) | Lr: 0.16206359152743416
[2021-12-07 01:42:51,940] Test: Loss: 1.606 | Acc: 61.604 (30802/50000)
[2021-12-07 01:42:51,940] Epoch: 314
[2021-12-07 01:52:47,261] Train: Loss: 1.725 | Acc: 59.974 (768361/1281167) | Lr: 0.1603229719750681
[2021-12-07 01:53:47,554] Test: Loss: 1.520 | Acc: 63.364 (31682/50000)
[2021-12-07 01:53:47,555] Saving..
[2021-12-07 01:53:47,613] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 01:53:47,613] Epoch: 315
[2021-12-07 02:03:48,605] Train: Loss: 1.724 | Acc: 59.929 (767796/1281167) | Lr: 0.1585883359358847
[2021-12-07 02:04:45,868] Test: Loss: 1.594 | Acc: 61.606 (30803/50000)
[2021-12-07 02:04:45,868] Epoch: 316
[2021-12-07 02:14:44,220] Train: Loss: 1.719 | Acc: 60.051 (769354/1281167) | Lr: 0.15685975771591865
[2021-12-07 02:15:46,818] Test: Loss: 1.643 | Acc: 60.760 (30380/50000)
[2021-12-07 02:15:46,819] Epoch: 317
[2021-12-07 02:25:50,981] Train: Loss: 1.718 | Acc: 60.094 (769901/1281167) | Lr: 0.15513731136170764
[2021-12-07 02:26:49,426] Test: Loss: 1.597 | Acc: 61.698 (30849/50000)
[2021-12-07 02:26:49,426] Epoch: 318
[2021-12-07 02:36:50,411] Train: Loss: 1.714 | Acc: 60.169 (770864/1281167) | Lr: 0.15342107065712082
[2021-12-07 02:37:53,944] Test: Loss: 1.611 | Acc: 61.392 (30696/50000)
[2021-12-07 02:37:53,945] Epoch: 319
[2021-12-07 02:47:57,591] Train: Loss: 1.709 | Acc: 60.267 (772122/1281167) | Lr: 0.151711109120198
[2021-12-07 02:48:56,643] Test: Loss: 1.736 | Acc: 59.188 (29594/50000)
[2021-12-07 02:48:56,643] Epoch: 320
[2021-12-07 02:59:07,176] Train: Loss: 1.706 | Acc: 60.303 (772588/1281167) | Lr: 0.15000749999999993
[2021-12-07 03:00:06,066] Test: Loss: 1.589 | Acc: 62.140 (31070/50000)
[2021-12-07 03:00:06,067] Epoch: 321
[2021-12-07 03:10:06,128] Train: Loss: 1.702 | Acc: 60.380 (773567/1281167) | Lr: 0.14831031627347144
[2021-12-07 03:10:55,889] Test: Loss: 1.570 | Acc: 62.208 (31104/50000)
[2021-12-07 03:10:55,890] Epoch: 322
[2021-12-07 03:20:56,551] Train: Loss: 1.702 | Acc: 60.435 (774274/1281167) | Lr: 0.1466196306423147
[2021-12-07 03:21:46,841] Test: Loss: 1.640 | Acc: 60.510 (30255/50000)
[2021-12-07 03:21:46,842] Epoch: 323
[2021-12-07 03:31:56,491] Train: Loss: 1.700 | Acc: 60.455 (774533/1281167) | Lr: 0.14493551552987505
[2021-12-07 03:32:43,282] Test: Loss: 1.543 | Acc: 62.610 (31305/50000)
[2021-12-07 03:32:43,282] Epoch: 324
[2021-12-07 03:42:46,948] Train: Loss: 1.694 | Acc: 60.547 (775702/1281167) | Lr: 0.14325804307803883
[2021-12-07 03:43:35,152] Test: Loss: 1.587 | Acc: 62.152 (31076/50000)
[2021-12-07 03:43:35,153] Epoch: 325
[2021-12-07 03:53:45,648] Train: Loss: 1.688 | Acc: 60.668 (777255/1281167) | Lr: 0.14158728514414276
[2021-12-07 03:54:33,973] Test: Loss: 1.614 | Acc: 61.022 (30511/50000)
[2021-12-07 03:54:33,973] Epoch: 326
[2021-12-07 04:04:43,322] Train: Loss: 1.687 | Acc: 60.739 (778165/1281167) | Lr: 0.13992331329789603
[2021-12-07 04:05:31,489] Test: Loss: 1.642 | Acc: 60.936 (30468/50000)
[2021-12-07 04:05:31,489] Epoch: 327
[2021-12-07 04:15:37,407] Train: Loss: 1.683 | Acc: 60.794 (778870/1281167) | Lr: 0.13826619881831437
[2021-12-07 04:16:25,568] Test: Loss: 1.657 | Acc: 60.828 (30414/50000)
[2021-12-07 04:16:25,569] Epoch: 328
[2021-12-07 04:26:36,296] Train: Loss: 1.681 | Acc: 60.824 (779253/1281167) | Lr: 0.13661601269066695
[2021-12-07 04:27:19,766] Test: Loss: 1.566 | Acc: 62.124 (31062/50000)
[2021-12-07 04:27:19,766] Epoch: 329
[2021-12-07 04:37:33,426] Train: Loss: 1.676 | Acc: 60.907 (780322/1281167) | Lr: 0.13497282560343488
[2021-12-07 04:38:15,309] Test: Loss: 1.514 | Acc: 63.342 (31671/50000)
[2021-12-07 04:38:15,309] Epoch: 330
[2021-12-07 04:48:21,506] Train: Loss: 1.676 | Acc: 60.957 (780955/1281167) | Lr: 0.1333367079452844
[2021-12-07 04:49:02,763] Test: Loss: 1.512 | Acc: 63.574 (31787/50000)
[2021-12-07 04:49:02,764] Saving..
[2021-12-07 04:49:02,829] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 04:49:02,829] Epoch: 331
[2021-12-07 04:59:04,330] Train: Loss: 1.677 | Acc: 60.924 (780540/1281167) | Lr: 0.13170772980205034
[2021-12-07 04:59:45,188] Test: Loss: 1.567 | Acc: 62.108 (31054/50000)
[2021-12-07 04:59:45,188] Epoch: 332
[2021-12-07 05:09:48,327] Train: Loss: 1.670 | Acc: 61.050 (782157/1281167) | Lr: 0.13008596095373462
[2021-12-07 05:10:32,529] Test: Loss: 1.514 | Acc: 63.482 (31741/50000)
[2021-12-07 05:10:32,529] Epoch: 333
[2021-12-07 05:20:41,048] Train: Loss: 1.667 | Acc: 61.152 (783461/1281167) | Lr: 0.12847147087151742
[2021-12-07 05:21:25,639] Test: Loss: 1.502 | Acc: 63.836 (31918/50000)
[2021-12-07 05:21:25,639] Saving..
[2021-12-07 05:21:25,763] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 05:21:25,764] Epoch: 334
[2021-12-07 05:31:30,604] Train: Loss: 1.662 | Acc: 61.248 (784686/1281167) | Lr: 0.12686432871477996
[2021-12-07 05:32:14,062] Test: Loss: 1.542 | Acc: 62.716 (31358/50000)
[2021-12-07 05:32:14,063] Epoch: 335
[2021-12-07 05:42:11,840] Train: Loss: 1.660 | Acc: 61.233 (784493/1281167) | Lr: 0.12526460332814365
[2021-12-07 05:42:58,237] Test: Loss: 1.517 | Acc: 63.582 (31791/50000)
[2021-12-07 05:42:58,237] Epoch: 336
[2021-12-07 05:52:58,192] Train: Loss: 1.657 | Acc: 61.279 (785084/1281167) | Lr: 0.12367236323851946
[2021-12-07 05:53:45,624] Test: Loss: 1.514 | Acc: 63.328 (31664/50000)
[2021-12-07 05:53:45,625] Epoch: 337
[2021-12-07 06:03:55,684] Train: Loss: 1.654 | Acc: 61.418 (786861/1281167) | Lr: 0.12208767665217356
[2021-12-07 06:04:42,038] Test: Loss: 1.477 | Acc: 64.120 (32060/50000)
[2021-12-07 06:04:42,039] Saving..
[2021-12-07 06:04:42,101] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 06:04:42,101] Epoch: 338
[2021-12-07 06:14:37,818] Train: Loss: 1.652 | Acc: 61.417 (786855/1281167) | Lr: 0.12051061145180504
[2021-12-07 06:15:17,209] Test: Loss: 1.608 | Acc: 61.050 (30525/50000)
[2021-12-07 06:15:17,210] Epoch: 339
[2021-12-07 06:25:06,787] Train: Loss: 1.648 | Acc: 61.534 (788359/1281167) | Lr: 0.11894123519363835
[2021-12-07 06:25:46,031] Test: Loss: 1.542 | Acc: 63.034 (31517/50000)
[2021-12-07 06:25:46,032] Epoch: 340
[2021-12-07 06:35:41,542] Train: Loss: 1.644 | Acc: 61.634 (789636/1281167) | Lr: 0.11737961510452875
[2021-12-07 06:36:21,262] Test: Loss: 1.499 | Acc: 63.412 (31706/50000)
[2021-12-07 06:36:21,262] Epoch: 341
[2021-12-07 06:46:18,308] Train: Loss: 1.644 | Acc: 61.643 (789747/1281167) | Lr: 0.1158258180790838
[2021-12-07 06:46:58,000] Test: Loss: 1.438 | Acc: 64.990 (32495/50000)
[2021-12-07 06:46:58,000] Saving..
[2021-12-07 06:46:58,076] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 06:46:58,076] Epoch: 342
[2021-12-07 06:56:53,394] Train: Loss: 1.633 | Acc: 61.824 (792069/1281167) | Lr: 0.11427991067679634
[2021-12-07 06:57:34,409] Test: Loss: 1.466 | Acc: 64.452 (32226/50000)
[2021-12-07 06:57:34,409] Epoch: 343
[2021-12-07 07:07:31,330] Train: Loss: 1.636 | Acc: 61.721 (790743/1281167) | Lr: 0.1127419591191943
[2021-12-07 07:08:10,219] Test: Loss: 1.446 | Acc: 64.852 (32426/50000)
[2021-12-07 07:08:10,219] Epoch: 344
[2021-12-07 07:18:03,710] Train: Loss: 1.629 | Acc: 61.951 (793691/1281167) | Lr: 0.11121202928700398
[2021-12-07 07:18:42,643] Test: Loss: 1.452 | Acc: 64.666 (32333/50000)
[2021-12-07 07:18:42,643] Epoch: 345
[2021-12-07 07:28:41,293] Train: Loss: 1.627 | Acc: 61.953 (793725/1281167) | Lr: 0.10969018671732703
[2021-12-07 07:29:21,336] Test: Loss: 1.459 | Acc: 64.492 (32246/50000)
[2021-12-07 07:29:21,337] Epoch: 346
[2021-12-07 07:39:40,120] Train: Loss: 1.623 | Acc: 62.076 (795300/1281167) | Lr: 0.10817649660083442
[2021-12-07 07:40:19,243] Test: Loss: 1.447 | Acc: 64.900 (32450/50000)
[2021-12-07 07:40:19,244] Epoch: 347
[2021-12-07 07:50:49,942] Train: Loss: 1.624 | Acc: 62.033 (794751/1281167) | Lr: 0.10667102377897254
[2021-12-07 07:51:29,397] Test: Loss: 1.446 | Acc: 64.790 (32395/50000)
[2021-12-07 07:51:29,398] Epoch: 348
[2021-12-07 08:02:16,217] Train: Loss: 1.615 | Acc: 62.210 (797017/1281167) | Lr: 0.10517383274118651
[2021-12-07 08:02:54,580] Test: Loss: 1.401 | Acc: 65.736 (32868/50000)
[2021-12-07 08:02:54,580] Saving..
[2021-12-07 08:02:54,642] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 08:02:54,642] Epoch: 349
[2021-12-07 08:13:41,258] Train: Loss: 1.613 | Acc: 62.197 (796851/1281167) | Lr: 0.10368498762215736
[2021-12-07 08:14:21,954] Test: Loss: 1.434 | Acc: 65.144 (32572/50000)
[2021-12-07 08:14:21,955] Epoch: 350
[2021-12-07 08:25:11,309] Train: Loss: 1.608 | Acc: 62.370 (799060/1281167) | Lr: 0.10220455219905486
[2021-12-07 08:25:50,470] Test: Loss: 1.469 | Acc: 64.666 (32333/50000)
[2021-12-07 08:25:50,471] Epoch: 351
[2021-12-07 08:36:45,464] Train: Loss: 1.604 | Acc: 62.443 (799995/1281167) | Lr: 0.10073258988880494
[2021-12-07 08:37:25,147] Test: Loss: 1.402 | Acc: 65.812 (32906/50000)
[2021-12-07 08:37:25,148] Saving..
[2021-12-07 08:37:25,242] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 08:37:25,243] Epoch: 352
[2021-12-07 08:48:14,457] Train: Loss: 1.603 | Acc: 62.439 (799954/1281167) | Lr: 0.09926916374537434
[2021-12-07 08:48:53,973] Test: Loss: 1.421 | Acc: 65.192 (32596/50000)
[2021-12-07 08:48:53,973] Epoch: 353
[2021-12-07 08:59:39,605] Train: Loss: 1.600 | Acc: 62.559 (801487/1281167) | Lr: 0.09781433645706791
[2021-12-07 09:00:22,894] Test: Loss: 1.436 | Acc: 65.024 (32512/50000)
[2021-12-07 09:00:22,894] Epoch: 354
[2021-12-07 09:11:06,186] Train: Loss: 1.595 | Acc: 62.639 (802509/1281167) | Lr: 0.09636817034384504
[2021-12-07 09:11:46,006] Test: Loss: 1.608 | Acc: 61.848 (30924/50000)
[2021-12-07 09:11:46,006] Epoch: 355
[2021-12-07 09:22:32,700] Train: Loss: 1.591 | Acc: 62.645 (802584/1281167) | Lr: 0.09493072735464868
[2021-12-07 09:23:11,542] Test: Loss: 1.439 | Acc: 64.882 (32441/50000)
[2021-12-07 09:23:11,543] Epoch: 356
[2021-12-07 09:33:55,507] Train: Loss: 1.588 | Acc: 62.764 (804106/1281167) | Lr: 0.09350206906475214
[2021-12-07 09:34:33,797] Test: Loss: 1.436 | Acc: 65.120 (32560/50000)
[2021-12-07 09:34:33,798] Epoch: 357
[2021-12-07 09:45:30,535] Train: Loss: 1.587 | Acc: 62.783 (804360/1281167) | Lr: 0.09208225667312192
[2021-12-07 09:46:09,415] Test: Loss: 1.513 | Acc: 63.476 (31738/50000)
[2021-12-07 09:46:09,416] Epoch: 358
[2021-12-07 09:56:50,423] Train: Loss: 1.580 | Acc: 62.948 (806470/1281167) | Lr: 0.09067135099979513
[2021-12-07 09:57:29,376] Test: Loss: 1.412 | Acc: 65.600 (32800/50000)
[2021-12-07 09:57:29,377] Epoch: 359
[2021-12-07 10:08:19,883] Train: Loss: 1.579 | Acc: 62.982 (806904/1281167) | Lr: 0.08926941248327502
[2021-12-07 10:08:58,610] Test: Loss: 1.448 | Acc: 65.070 (32535/50000)
[2021-12-07 10:08:58,611] Epoch: 360
[2021-12-07 10:19:37,608] Train: Loss: 1.575 | Acc: 63.069 (808022/1281167) | Lr: 0.08787650117794162
[2021-12-07 10:20:16,558] Test: Loss: 1.379 | Acc: 66.292 (33146/50000)
[2021-12-07 10:20:16,558] Saving..
[2021-12-07 10:20:16,659] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 10:20:16,659] Epoch: 361
[2021-12-07 10:30:58,133] Train: Loss: 1.572 | Acc: 63.104 (808469/1281167) | Lr: 0.08649267675147938
[2021-12-07 10:31:40,089] Test: Loss: 1.382 | Acc: 66.186 (33093/50000)
[2021-12-07 10:31:40,089] Epoch: 362
[2021-12-07 10:41:31,886] Train: Loss: 1.565 | Acc: 63.181 (809454/1281167) | Lr: 0.08511799848232077
[2021-12-07 10:42:10,984] Test: Loss: 1.380 | Acc: 66.310 (33155/50000)
[2021-12-07 10:42:10,985] Saving..
[2021-12-07 10:42:11,085] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 10:42:11,085] Epoch: 363
[2021-12-07 10:52:22,560] Train: Loss: 1.568 | Acc: 63.160 (809179/1281167) | Lr: 0.08375252525710779
[2021-12-07 10:53:02,292] Test: Loss: 1.492 | Acc: 63.980 (31990/50000)
[2021-12-07 10:53:02,292] Epoch: 364
[2021-12-07 11:03:20,083] Train: Loss: 1.559 | Acc: 63.301 (810996/1281167) | Lr: 0.08239631556816869
[2021-12-07 11:04:01,162] Test: Loss: 1.417 | Acc: 65.428 (32714/50000)
[2021-12-07 11:04:01,162] Epoch: 365
[2021-12-07 11:14:11,274] Train: Loss: 1.552 | Acc: 63.464 (813086/1281167) | Lr: 0.0810494275110127
[2021-12-07 11:14:52,202] Test: Loss: 1.366 | Acc: 66.454 (33227/50000)
[2021-12-07 11:14:52,203] Saving..
[2021-12-07 11:14:52,278] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 11:14:52,278] Epoch: 366
[2021-12-07 11:26:16,389] Train: Loss: 1.553 | Acc: 63.473 (813189/1281167) | Lr: 0.0797119187818415
[2021-12-07 11:26:55,968] Test: Loss: 1.390 | Acc: 65.970 (32985/50000)
[2021-12-07 11:26:55,969] Epoch: 367
[2021-12-07 11:36:48,279] Train: Loss: 1.547 | Acc: 63.616 (815030/1281167) | Lr: 0.07838384667507721
[2021-12-07 11:37:27,894] Test: Loss: 1.427 | Acc: 65.194 (32597/50000)
[2021-12-07 11:37:27,894] Epoch: 368
[2021-12-07 11:47:14,156] Train: Loss: 1.542 | Acc: 63.664 (815645/1281167) | Lr: 0.07706526808090909
[2021-12-07 11:47:53,658] Test: Loss: 1.365 | Acc: 66.578 (33289/50000)
[2021-12-07 11:47:53,658] Saving..
[2021-12-07 11:47:53,741] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 11:47:53,741] Epoch: 369
[2021-12-07 11:59:19,261] Train: Loss: 1.541 | Acc: 63.739 (816605/1281167) | Lr: 0.07575623948285524
[2021-12-07 11:59:59,310] Test: Loss: 1.371 | Acc: 66.574 (33287/50000)
[2021-12-07 11:59:59,311] Epoch: 370
[2021-12-07 12:11:09,331] Train: Loss: 1.538 | Acc: 63.779 (817115/1281167) | Lr: 0.07445681695534413
[2021-12-07 12:11:47,910] Test: Loss: 1.385 | Acc: 65.800 (32900/50000)
[2021-12-07 12:11:47,911] Epoch: 371
[2021-12-07 12:23:09,653] Train: Loss: 1.535 | Acc: 63.897 (818622/1281167) | Lr: 0.073167056161312
[2021-12-07 12:23:49,925] Test: Loss: 1.389 | Acc: 66.018 (33009/50000)
[2021-12-07 12:23:49,925] Epoch: 372
[2021-12-07 12:33:35,323] Train: Loss: 1.532 | Acc: 63.889 (818523/1281167) | Lr: 0.07188701234981865
[2021-12-07 12:34:13,914] Test: Loss: 1.456 | Acc: 64.664 (32332/50000)
[2021-12-07 12:34:13,915] Epoch: 373
[2021-12-07 12:44:08,856] Train: Loss: 1.525 | Acc: 64.084 (821018/1281167) | Lr: 0.07061674035368062
[2021-12-07 12:44:47,675] Test: Loss: 1.353 | Acc: 66.838 (33419/50000)
[2021-12-07 12:44:47,675] Saving..
[2021-12-07 12:44:47,766] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 12:44:47,766] Epoch: 374
[2021-12-07 12:54:38,223] Train: Loss: 1.525 | Acc: 64.076 (820923/1281167) | Lr: 0.06935629458712246
[2021-12-07 12:55:20,463] Test: Loss: 1.422 | Acc: 65.570 (32785/50000)
[2021-12-07 12:55:20,463] Epoch: 375
[2021-12-07 13:05:13,091] Train: Loss: 1.517 | Acc: 64.203 (822543/1281167) | Lr: 0.06810572904344565
[2021-12-07 13:05:52,455] Test: Loss: 1.334 | Acc: 67.358 (33679/50000)
[2021-12-07 13:05:52,455] Saving..
[2021-12-07 13:05:52,639] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 13:05:52,640] Epoch: 376
[2021-12-07 13:15:44,135] Train: Loss: 1.514 | Acc: 64.298 (823771/1281167) | Lr: 0.06686509729271595
[2021-12-07 13:16:23,266] Test: Loss: 1.330 | Acc: 67.450 (33725/50000)
[2021-12-07 13:16:23,266] Saving..
[2021-12-07 13:16:23,336] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 13:16:23,337] Epoch: 377
[2021-12-07 13:26:13,135] Train: Loss: 1.512 | Acc: 64.331 (824187/1281167) | Lr: 0.06563445247946846
[2021-12-07 13:27:04,507] Test: Loss: 1.357 | Acc: 66.910 (33455/50000)
[2021-12-07 13:27:04,507] Epoch: 378
[2021-12-07 13:36:47,334] Train: Loss: 1.506 | Acc: 64.447 (825670/1281167) | Lr: 0.06441384732043082
[2021-12-07 13:37:25,764] Test: Loss: 1.345 | Acc: 67.224 (33612/50000)
[2021-12-07 13:37:25,764] Epoch: 379
[2021-12-07 13:47:12,236] Train: Loss: 1.502 | Acc: 64.541 (826875/1281167) | Lr: 0.06320333410226592
[2021-12-07 13:47:51,100] Test: Loss: 1.331 | Acc: 67.566 (33783/50000)
[2021-12-07 13:47:51,101] Saving..
[2021-12-07 13:47:51,167] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 13:47:51,167] Epoch: 380
[2021-12-07 13:57:39,094] Train: Loss: 1.497 | Acc: 64.610 (827761/1281167) | Lr: 0.06200296467933081
[2021-12-07 13:58:18,006] Test: Loss: 1.314 | Acc: 67.654 (33827/50000)
[2021-12-07 13:58:18,006] Saving..
[2021-12-07 13:58:18,072] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 13:58:18,073] Epoch: 381
[2021-12-07 14:08:11,915] Train: Loss: 1.492 | Acc: 64.767 (829775/1281167) | Lr: 0.0608127904714567
[2021-12-07 14:08:49,953] Test: Loss: 1.354 | Acc: 67.032 (33516/50000)
[2021-12-07 14:08:49,954] Epoch: 382
[2021-12-07 14:18:36,112] Train: Loss: 1.489 | Acc: 64.842 (830731/1281167) | Lr: 0.05963286246174523
[2021-12-07 14:19:24,758] Test: Loss: 1.564 | Acc: 62.860 (31430/50000)
[2021-12-07 14:19:24,759] Epoch: 383
[2021-12-07 14:29:22,080] Train: Loss: 1.487 | Acc: 64.890 (831351/1281167) | Lr: 0.0584632311943853
[2021-12-07 14:30:00,201] Test: Loss: 1.329 | Acc: 67.424 (33712/50000)
[2021-12-07 14:30:00,201] Epoch: 384
[2021-12-07 14:39:50,076] Train: Loss: 1.481 | Acc: 65.002 (832781/1281167) | Lr: 0.05730394677248761
[2021-12-07 14:40:28,856] Test: Loss: 1.308 | Acc: 67.828 (33914/50000)
[2021-12-07 14:40:28,857] Saving..
[2021-12-07 14:40:28,939] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 14:40:28,939] Epoch: 385
[2021-12-07 14:50:18,489] Train: Loss: 1.478 | Acc: 65.037 (833227/1281167) | Lr: 0.056155058855938356
[2021-12-07 14:50:57,386] Test: Loss: 1.371 | Acc: 66.630 (33315/50000)
[2021-12-07 14:50:57,386] Epoch: 386
[2021-12-07 15:00:46,304] Train: Loss: 1.479 | Acc: 65.024 (833066/1281167) | Lr: 0.05501661665927207
[2021-12-07 15:01:25,056] Test: Loss: 1.431 | Acc: 65.216 (32608/50000)
[2021-12-07 15:01:25,056] Epoch: 387
[2021-12-07 15:11:08,828] Train: Loss: 1.472 | Acc: 65.155 (834741/1281167) | Lr: 0.05388866894956349
[2021-12-07 15:11:52,044] Test: Loss: 1.320 | Acc: 67.590 (33795/50000)
[2021-12-07 15:11:52,044] Epoch: 388
[2021-12-07 15:21:36,165] Train: Loss: 1.466 | Acc: 65.278 (836315/1281167) | Lr: 0.052771264044338406
[2021-12-07 15:22:15,686] Test: Loss: 1.291 | Acc: 68.182 (34091/50000)
[2021-12-07 15:22:15,687] Saving..
[2021-12-07 15:22:15,762] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 15:22:15,762] Epoch: 389
[2021-12-07 15:32:04,324] Train: Loss: 1.463 | Acc: 65.419 (838124/1281167) | Lr: 0.05166444980950378
[2021-12-07 15:32:43,540] Test: Loss: 1.297 | Acc: 68.458 (34229/50000)
[2021-12-07 15:32:43,540] Saving..
[2021-12-07 15:32:43,606] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 15:32:43,606] Epoch: 390
[2021-12-07 15:43:56,723] Train: Loss: 1.458 | Acc: 65.530 (839545/1281167) | Lr: 0.050568273657297956
[2021-12-07 15:44:36,038] Test: Loss: 1.355 | Acc: 67.068 (33534/50000)
[2021-12-07 15:44:36,038] Epoch: 391
[2021-12-07 15:54:59,464] Train: Loss: 1.459 | Acc: 65.454 (838581/1281167) | Lr: 0.04948278254425858
[2021-12-07 15:55:37,962] Test: Loss: 1.318 | Acc: 67.694 (33847/50000)
[2021-12-07 15:55:37,963] Epoch: 392
[2021-12-07 16:05:33,852] Train: Loss: 1.451 | Acc: 65.669 (841331/1281167) | Lr: 0.04840802296921249
[2021-12-07 16:06:14,874] Test: Loss: 1.298 | Acc: 68.164 (34082/50000)
[2021-12-07 16:06:14,874] Epoch: 393
[2021-12-07 16:16:04,912] Train: Loss: 1.444 | Acc: 65.821 (843273/1281167) | Lr: 0.0473440409712826
[2021-12-07 16:16:44,012] Test: Loss: 1.281 | Acc: 68.692 (34346/50000)
[2021-12-07 16:16:44,012] Saving..
[2021-12-07 16:16:44,078] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 16:16:44,078] Epoch: 394
[2021-12-07 16:26:32,763] Train: Loss: 1.442 | Acc: 65.800 (843008/1281167) | Lr: 0.04629088212791651
[2021-12-07 16:27:11,030] Test: Loss: 1.285 | Acc: 68.526 (34263/50000)
[2021-12-07 16:27:11,030] Epoch: 395
[2021-12-07 16:36:58,890] Train: Loss: 1.438 | Acc: 65.910 (844411/1281167) | Lr: 0.04524859155293395
[2021-12-07 16:37:37,094] Test: Loss: 1.373 | Acc: 66.514 (33257/50000)
[2021-12-07 16:37:37,094] Epoch: 396
[2021-12-07 16:47:24,351] Train: Loss: 1.433 | Acc: 66.023 (845871/1281167) | Lr: 0.04421721389459408
[2021-12-07 16:48:03,896] Test: Loss: 1.283 | Acc: 68.438 (34219/50000)
[2021-12-07 16:48:03,896] Epoch: 397
[2021-12-07 16:57:49,182] Train: Loss: 1.428 | Acc: 66.085 (846661/1281167) | Lr: 0.04319679333368313
[2021-12-07 16:58:28,137] Test: Loss: 1.280 | Acc: 68.646 (34323/50000)
[2021-12-07 16:58:28,137] Epoch: 398
[2021-12-07 17:08:19,225] Train: Loss: 1.422 | Acc: 66.244 (848695/1281167) | Lr: 0.04218737358162167
[2021-12-07 17:08:57,925] Test: Loss: 1.286 | Acc: 68.552 (34276/50000)
[2021-12-07 17:08:57,925] Epoch: 399
[2021-12-07 17:19:46,950] Train: Loss: 1.421 | Acc: 66.262 (848933/1281167) | Lr: 0.04118899787859231
[2021-12-07 17:20:26,774] Test: Loss: 1.326 | Acc: 67.946 (33973/50000)
[2021-12-07 17:20:26,775] Epoch: 400
[2021-12-07 17:30:15,074] Train: Loss: 1.417 | Acc: 66.380 (850442/1281167) | Lr: 0.040201708991687284
[2021-12-07 17:30:53,653] Test: Loss: 1.243 | Acc: 69.478 (34739/50000)
[2021-12-07 17:30:53,653] Saving..
[2021-12-07 17:30:53,738] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 17:30:53,738] Epoch: 401
[2021-12-07 17:40:41,832] Train: Loss: 1.413 | Acc: 66.443 (851240/1281167) | Lr: 0.039225549213076645
[2021-12-07 17:41:21,599] Test: Loss: 1.263 | Acc: 68.844 (34422/50000)
[2021-12-07 17:41:21,600] Epoch: 402
[2021-12-07 17:51:07,594] Train: Loss: 1.409 | Acc: 66.534 (852407/1281167) | Lr: 0.03826056035819619
[2021-12-07 17:51:45,879] Test: Loss: 1.258 | Acc: 69.052 (34526/50000)
[2021-12-07 17:51:45,879] Epoch: 403
[2021-12-07 18:01:30,078] Train: Loss: 1.402 | Acc: 66.677 (854243/1281167) | Lr: 0.037306783763956984
[2021-12-07 18:02:09,233] Test: Loss: 1.268 | Acc: 68.708 (34354/50000)
[2021-12-07 18:02:09,233] Epoch: 404
[2021-12-07 18:11:52,731] Train: Loss: 1.400 | Acc: 66.735 (854989/1281167) | Lr: 0.036364260286973704
[2021-12-07 18:12:30,943] Test: Loss: 1.237 | Acc: 69.596 (34798/50000)
[2021-12-07 18:12:30,943] Saving..
[2021-12-07 18:12:31,001] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 18:12:31,001] Epoch: 405
[2021-12-07 18:22:20,935] Train: Loss: 1.396 | Acc: 66.870 (856712/1281167) | Lr: 0.03543303030181524
[2021-12-07 18:23:01,461] Test: Loss: 1.266 | Acc: 68.792 (34396/50000)
[2021-12-07 18:23:01,461] Epoch: 406
[2021-12-07 18:32:51,631] Train: Loss: 1.391 | Acc: 66.908 (857205/1281167) | Lr: 0.034513133699274764
[2021-12-07 18:33:29,598] Test: Loss: 1.236 | Acc: 69.488 (34744/50000)
[2021-12-07 18:33:29,599] Epoch: 407
[2021-12-07 18:43:25,283] Train: Loss: 1.385 | Acc: 67.059 (859142/1281167) | Lr: 0.03360460988466101
[2021-12-07 18:44:03,847] Test: Loss: 1.256 | Acc: 69.114 (34557/50000)
[2021-12-07 18:44:03,847] Epoch: 408
[2021-12-07 18:53:55,670] Train: Loss: 1.381 | Acc: 67.084 (859462/1281167) | Lr: 0.03270749777611059
[2021-12-07 18:54:33,820] Test: Loss: 1.226 | Acc: 69.862 (34931/50000)
[2021-12-07 18:54:33,820] Saving..
[2021-12-07 18:54:33,902] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 18:54:33,903] Epoch: 409
[2021-12-07 19:04:21,056] Train: Loss: 1.376 | Acc: 67.251 (861593/1281167) | Lr: 0.0318218358029202
[2021-12-07 19:04:59,441] Test: Loss: 1.241 | Acc: 69.292 (34646/50000)
[2021-12-07 19:04:59,442] Epoch: 410
[2021-12-07 19:14:48,116] Train: Loss: 1.371 | Acc: 67.372 (863152/1281167) | Lr: 0.030947661903901174
[2021-12-07 19:15:27,328] Test: Loss: 1.228 | Acc: 69.640 (34820/50000)
[2021-12-07 19:15:27,328] Epoch: 411
[2021-12-07 19:25:15,678] Train: Loss: 1.368 | Acc: 67.380 (863253/1281167) | Lr: 0.030085013525753792
[2021-12-07 19:25:54,445] Test: Loss: 1.219 | Acc: 70.046 (35023/50000)
[2021-12-07 19:25:54,446] Saving..
[2021-12-07 19:25:54,535] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 19:25:54,536] Epoch: 412
[2021-12-07 19:35:42,553] Train: Loss: 1.362 | Acc: 67.498 (864756/1281167) | Lr: 0.029233927621463613
[2021-12-07 19:36:22,127] Test: Loss: 1.228 | Acc: 69.774 (34887/50000)
[2021-12-07 19:36:22,128] Epoch: 413
[2021-12-07 19:46:18,754] Train: Loss: 1.357 | Acc: 67.627 (866418/1281167) | Lr: 0.02839444064871788
[2021-12-07 19:46:56,398] Test: Loss: 1.235 | Acc: 69.734 (34867/50000)
[2021-12-07 19:46:56,398] Epoch: 414
[2021-12-07 19:56:49,857] Train: Loss: 1.355 | Acc: 67.673 (867003/1281167) | Lr: 0.02756658856834477
[2021-12-07 19:57:28,930] Test: Loss: 1.232 | Acc: 69.830 (34915/50000)
[2021-12-07 19:57:28,930] Epoch: 415
[2021-12-07 20:07:18,265] Train: Loss: 1.351 | Acc: 67.815 (868827/1281167) | Lr: 0.026750406842771888
[2021-12-07 20:07:57,497] Test: Loss: 1.202 | Acc: 70.412 (35206/50000)
[2021-12-07 20:07:57,498] Saving..
[2021-12-07 20:07:57,570] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 20:07:57,571] Epoch: 416
[2021-12-07 20:17:46,651] Train: Loss: 1.343 | Acc: 67.944 (870478/1281167) | Lr: 0.025945930434507904
[2021-12-07 20:18:25,860] Test: Loss: 1.205 | Acc: 70.418 (35209/50000)
[2021-12-07 20:18:25,860] Saving..
[2021-12-07 20:18:25,916] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 20:18:25,916] Epoch: 417
[2021-12-07 20:28:19,572] Train: Loss: 1.340 | Acc: 67.981 (870947/1281167) | Lr: 0.025153193804644813
[2021-12-07 20:28:58,703] Test: Loss: 1.196 | Acc: 70.596 (35298/50000)
[2021-12-07 20:28:58,703] Saving..
[2021-12-07 20:28:58,811] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 20:28:58,812] Epoch: 418
[2021-12-07 20:38:47,737] Train: Loss: 1.337 | Acc: 68.121 (872739/1281167) | Lr: 0.024372230911381205
[2021-12-07 20:39:27,370] Test: Loss: 1.201 | Acc: 70.608 (35304/50000)
[2021-12-07 20:39:27,370] Saving..
[2021-12-07 20:39:27,434] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 20:39:27,434] Epoch: 419
[2021-12-07 20:49:14,840] Train: Loss: 1.329 | Acc: 68.183 (873541/1281167) | Lr: 0.02360307520856838
[2021-12-07 20:49:53,764] Test: Loss: 1.197 | Acc: 70.406 (35203/50000)
[2021-12-07 20:49:53,764] Epoch: 420
[2021-12-07 20:59:38,042] Train: Loss: 1.329 | Acc: 68.298 (875008/1281167) | Lr: 0.02284575964427652
[2021-12-07 21:00:16,907] Test: Loss: 1.194 | Acc: 70.556 (35278/50000)
[2021-12-07 21:00:16,907] Epoch: 421
[2021-12-07 21:10:08,629] Train: Loss: 1.322 | Acc: 68.368 (875909/1281167) | Lr: 0.02210031665938393
[2021-12-07 21:10:47,519] Test: Loss: 1.188 | Acc: 70.688 (35344/50000)
[2021-12-07 21:10:47,520] Saving..
[2021-12-07 21:10:47,586] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 21:10:47,586] Epoch: 422
[2021-12-07 21:20:35,380] Train: Loss: 1.318 | Acc: 68.513 (877765/1281167) | Lr: 0.021366778186187076
[2021-12-07 21:21:14,939] Test: Loss: 1.163 | Acc: 71.170 (35585/50000)
[2021-12-07 21:21:14,940] Saving..
[2021-12-07 21:21:15,011] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 21:21:15,011] Epoch: 423
[2021-12-07 21:31:06,826] Train: Loss: 1.314 | Acc: 68.594 (878804/1281167) | Lr: 0.02064517564703278
[2021-12-07 21:31:46,992] Test: Loss: 1.192 | Acc: 70.808 (35404/50000)
[2021-12-07 21:31:46,993] Epoch: 424
[2021-12-07 21:41:37,780] Train: Loss: 1.309 | Acc: 68.667 (879738/1281167) | Lr: 0.019935539952971953
[2021-12-07 21:42:17,077] Test: Loss: 1.160 | Acc: 71.450 (35725/50000)
[2021-12-07 21:42:17,078] Saving..
[2021-12-07 21:42:17,214] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 21:42:17,214] Epoch: 425
[2021-12-07 21:52:06,813] Train: Loss: 1.303 | Acc: 68.850 (882081/1281167) | Lr: 0.019237901502436115
[2021-12-07 21:52:45,703] Test: Loss: 1.179 | Acc: 71.262 (35631/50000)
[2021-12-07 21:52:45,703] Epoch: 426
[2021-12-07 22:02:34,522] Train: Loss: 1.294 | Acc: 68.959 (883479/1281167) | Lr: 0.018552290179934355
[2021-12-07 22:03:14,159] Test: Loss: 1.184 | Acc: 70.868 (35434/50000)
[2021-12-07 22:03:14,160] Epoch: 427
[2021-12-07 22:13:04,054] Train: Loss: 1.292 | Acc: 69.019 (884245/1281167) | Lr: 0.017878735354773998
[2021-12-07 22:13:43,474] Test: Loss: 1.180 | Acc: 70.952 (35476/50000)
[2021-12-07 22:13:43,475] Epoch: 428
[2021-12-07 22:23:32,436] Train: Loss: 1.288 | Acc: 69.132 (885698/1281167) | Lr: 0.017217265879801952
[2021-12-07 22:24:14,733] Test: Loss: 1.189 | Acc: 70.748 (35374/50000)
[2021-12-07 22:24:14,733] Epoch: 429
[2021-12-07 22:34:06,341] Train: Loss: 1.283 | Acc: 69.177 (886270/1281167) | Lr: 0.01656791009016891
[2021-12-07 22:34:45,294] Test: Loss: 1.167 | Acc: 71.096 (35548/50000)
[2021-12-07 22:34:45,294] Epoch: 430
[2021-12-07 22:44:30,501] Train: Loss: 1.279 | Acc: 69.315 (888038/1281167) | Lr: 0.015930695802115792
[2021-12-07 22:45:10,488] Test: Loss: 1.164 | Acc: 71.474 (35737/50000)
[2021-12-07 22:45:10,488] Saving..
[2021-12-07 22:45:10,544] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 22:45:10,545] Epoch: 431
[2021-12-07 22:54:59,483] Train: Loss: 1.274 | Acc: 69.458 (889871/1281167) | Lr: 0.015305650311781776
[2021-12-07 22:55:38,067] Test: Loss: 1.175 | Acc: 71.012 (35506/50000)
[2021-12-07 22:55:38,068] Epoch: 432
[2021-12-07 23:05:29,195] Train: Loss: 1.270 | Acc: 69.576 (891385/1281167) | Lr: 0.014692800394035406
[2021-12-07 23:06:08,248] Test: Loss: 1.148 | Acc: 71.698 (35849/50000)
[2021-12-07 23:06:08,248] Saving..
[2021-12-07 23:06:08,316] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 23:06:08,316] Epoch: 433
[2021-12-07 23:15:57,887] Train: Loss: 1.267 | Acc: 69.606 (891765/1281167) | Lr: 0.01409217230132743
[2021-12-07 23:16:40,685] Test: Loss: 1.159 | Acc: 71.660 (35830/50000)
[2021-12-07 23:16:40,686] Epoch: 434
[2021-12-07 23:26:32,840] Train: Loss: 1.259 | Acc: 69.774 (893921/1281167) | Lr: 0.01350379176256632
[2021-12-07 23:27:11,753] Test: Loss: 1.153 | Acc: 71.506 (35753/50000)
[2021-12-07 23:27:11,753] Epoch: 435
[2021-12-07 23:37:01,103] Train: Loss: 1.259 | Acc: 69.760 (893741/1281167) | Lr: 0.012927683982016004
[2021-12-07 23:37:39,305] Test: Loss: 1.144 | Acc: 71.766 (35883/50000)
[2021-12-07 23:37:39,305] Saving..
[2021-12-07 23:37:39,380] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 23:37:39,380] Epoch: 436
[2021-12-07 23:47:29,957] Train: Loss: 1.247 | Acc: 70.024 (897125/1281167) | Lr: 0.01236387363821645
[2021-12-07 23:48:09,169] Test: Loss: 1.141 | Acc: 71.972 (35986/50000)
[2021-12-07 23:48:09,169] Saving..
[2021-12-07 23:48:09,226] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-07 23:48:09,226] Epoch: 437
[2021-12-07 23:57:59,030] Train: Loss: 1.247 | Acc: 70.078 (897819/1281167) | Lr: 0.011812384882926191
[2021-12-07 23:58:37,598] Test: Loss: 1.141 | Acc: 71.932 (35966/50000)
[2021-12-07 23:58:37,599] Epoch: 438
[2021-12-08 00:08:22,936] Train: Loss: 1.244 | Acc: 70.062 (897611/1281167) | Lr: 0.011273241340088076
[2021-12-08 00:09:04,471] Test: Loss: 1.131 | Acc: 72.124 (36062/50000)
[2021-12-08 00:09:04,471] Saving..
[2021-12-08 00:09:04,547] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 00:09:04,547] Epoch: 439
[2021-12-08 00:18:50,629] Train: Loss: 1.236 | Acc: 70.298 (900638/1281167) | Lr: 0.01074646610481706
[2021-12-08 00:19:28,602] Test: Loss: 1.137 | Acc: 72.090 (36045/50000)
[2021-12-08 00:19:28,602] Epoch: 440
[2021-12-08 00:29:19,225] Train: Loss: 1.230 | Acc: 70.393 (901854/1281167) | Lr: 0.010232081742410942
[2021-12-08 00:29:59,138] Test: Loss: 1.132 | Acc: 72.134 (36067/50000)
[2021-12-08 00:29:59,139] Saving..
[2021-12-08 00:29:59,197] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 00:29:59,197] Epoch: 441
[2021-12-08 00:39:51,977] Train: Loss: 1.228 | Acc: 70.510 (903347/1281167) | Lr: 0.009730110287383863
[2021-12-08 00:40:30,994] Test: Loss: 1.127 | Acc: 72.312 (36156/50000)
[2021-12-08 00:40:30,994] Saving..
[2021-12-08 00:40:31,082] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 00:40:31,082] Epoch: 442
[2021-12-08 00:50:20,797] Train: Loss: 1.220 | Acc: 70.625 (904830/1281167) | Lr: 0.009240573242522235
[2021-12-08 00:50:59,577] Test: Loss: 1.123 | Acc: 72.334 (36167/50000)
[2021-12-08 00:50:59,578] Saving..
[2021-12-08 00:50:59,729] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 00:50:59,729] Epoch: 443
[2021-12-08 01:01:48,476] Train: Loss: 1.216 | Acc: 70.721 (906054/1281167) | Lr: 0.008763491577963696
[2021-12-08 01:02:27,016] Test: Loss: 1.123 | Acc: 72.392 (36196/50000)
[2021-12-08 01:02:27,016] Saving..
[2021-12-08 01:02:27,080] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 01:02:27,080] Epoch: 444
[2021-12-08 01:12:14,572] Train: Loss: 1.215 | Acc: 70.718 (906014/1281167) | Lr: 0.008298885730299011
[2021-12-08 01:12:53,233] Test: Loss: 1.121 | Acc: 72.372 (36186/50000)
[2021-12-08 01:12:53,233] Epoch: 445
[2021-12-08 01:22:42,514] Train: Loss: 1.208 | Acc: 70.902 (908376/1281167) | Lr: 0.007846775601696289
[2021-12-08 01:23:22,024] Test: Loss: 1.133 | Acc: 72.128 (36064/50000)
[2021-12-08 01:23:22,024] Epoch: 446
[2021-12-08 01:33:17,263] Train: Loss: 1.205 | Acc: 70.976 (909327/1281167) | Lr: 0.007407180559048736
[2021-12-08 01:33:55,653] Test: Loss: 1.104 | Acc: 72.580 (36290/50000)
[2021-12-08 01:33:55,653] Saving..
[2021-12-08 01:33:55,729] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 01:33:55,729] Epoch: 447
[2021-12-08 01:43:43,746] Train: Loss: 1.203 | Acc: 71.017 (909852/1281167) | Lr: 0.006980119433144881
[2021-12-08 01:44:22,181] Test: Loss: 1.110 | Acc: 72.626 (36313/50000)
[2021-12-08 01:44:22,181] Saving..
[2021-12-08 01:44:22,262] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 01:44:22,262] Epoch: 448
[2021-12-08 01:54:13,562] Train: Loss: 1.194 | Acc: 71.236 (912649/1281167) | Lr: 0.006565610517861955
[2021-12-08 01:54:52,892] Test: Loss: 1.113 | Acc: 72.496 (36248/50000)
[2021-12-08 01:54:52,892] Epoch: 449
[2021-12-08 02:04:36,543] Train: Loss: 1.193 | Acc: 71.242 (912725/1281167) | Lr: 0.006163671569382373
[2021-12-08 02:05:14,797] Test: Loss: 1.107 | Acc: 72.738 (36369/50000)
[2021-12-08 02:05:14,797] Saving..
[2021-12-08 02:05:14,866] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 02:05:14,866] Epoch: 450
[2021-12-08 02:15:03,016] Train: Loss: 1.187 | Acc: 71.352 (914142/1281167) | Lr: 0.005774319805432881
[2021-12-08 02:15:41,573] Test: Loss: 1.102 | Acc: 72.842 (36421/50000)
[2021-12-08 02:15:41,574] Saving..
[2021-12-08 02:15:41,630] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 02:15:41,630] Epoch: 451
[2021-12-08 02:25:28,323] Train: Loss: 1.182 | Acc: 71.479 (915759/1281167) | Lr: 0.005397571904547165
[2021-12-08 02:26:07,637] Test: Loss: 1.100 | Acc: 72.794 (36397/50000)
[2021-12-08 02:26:07,638] Epoch: 452
[2021-12-08 02:35:56,738] Train: Loss: 1.179 | Acc: 71.552 (916703/1281167) | Lr: 0.005033444005351463
[2021-12-08 02:36:35,687] Test: Loss: 1.099 | Acc: 72.990 (36495/50000)
[2021-12-08 02:36:35,687] Saving..
[2021-12-08 02:36:35,753] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 02:36:35,753] Epoch: 453
[2021-12-08 02:46:28,197] Train: Loss: 1.178 | Acc: 71.563 (916842/1281167) | Lr: 0.004681951705872932
[2021-12-08 02:47:07,577] Test: Loss: 1.097 | Acc: 72.812 (36406/50000)
[2021-12-08 02:47:07,577] Epoch: 454
[2021-12-08 02:56:55,122] Train: Loss: 1.173 | Acc: 71.672 (918234/1281167) | Lr: 0.004343110062871961
[2021-12-08 02:57:34,072] Test: Loss: 1.101 | Acc: 72.906 (36453/50000)
[2021-12-08 02:57:34,073] Epoch: 455
[2021-12-08 03:07:21,161] Train: Loss: 1.167 | Acc: 71.784 (919673/1281167) | Lr: 0.004016933591196727
[2021-12-08 03:08:00,205] Test: Loss: 1.089 | Acc: 73.090 (36545/50000)
[2021-12-08 03:08:00,205] Saving..
[2021-12-08 03:08:00,264] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 03:08:00,264] Epoch: 456
[2021-12-08 03:17:47,112] Train: Loss: 1.161 | Acc: 71.947 (921758/1281167) | Lr: 0.003703436263161675
[2021-12-08 03:18:26,029] Test: Loss: 1.091 | Acc: 73.022 (36511/50000)
[2021-12-08 03:18:26,029] Epoch: 457
[2021-12-08 03:28:13,551] Train: Loss: 1.159 | Acc: 71.998 (922409/1281167) | Lr: 0.0034026315079488997
[2021-12-08 03:28:53,022] Test: Loss: 1.090 | Acc: 73.158 (36579/50000)
[2021-12-08 03:28:53,022] Saving..
[2021-12-08 03:28:53,079] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 03:28:53,079] Epoch: 458
[2021-12-08 03:38:38,173] Train: Loss: 1.160 | Acc: 72.004 (922486/1281167) | Lr: 0.0031145322110330566
[2021-12-08 03:39:16,685] Test: Loss: 1.087 | Acc: 73.178 (36589/50000)
[2021-12-08 03:39:16,686] Saving..
[2021-12-08 03:39:16,837] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 03:39:16,837] Epoch: 459
[2021-12-08 03:49:04,943] Train: Loss: 1.157 | Acc: 72.055 (923149/1281167) | Lr: 0.0028391507136290403
[2021-12-08 03:49:43,158] Test: Loss: 1.084 | Acc: 73.258 (36629/50000)
[2021-12-08 03:49:43,159] Saving..
[2021-12-08 03:49:43,237] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 03:49:43,237] Epoch: 460
[2021-12-08 03:59:35,378] Train: Loss: 1.151 | Acc: 72.173 (924660/1281167) | Lr: 0.0025764988121637525
[2021-12-08 04:00:13,956] Test: Loss: 1.085 | Acc: 73.224 (36612/50000)
[2021-12-08 04:00:13,956] Epoch: 461
[2021-12-08 04:10:12,017] Train: Loss: 1.149 | Acc: 72.247 (925603/1281167) | Lr: 0.0023265877577704455
[2021-12-08 04:10:50,572] Test: Loss: 1.083 | Acc: 73.230 (36615/50000)
[2021-12-08 04:10:50,572] Epoch: 462
[2021-12-08 04:20:38,228] Train: Loss: 1.145 | Acc: 72.310 (926410/1281167) | Lr: 0.002089428255806885
[2021-12-08 04:21:16,245] Test: Loss: 1.080 | Acc: 73.360 (36680/50000)
[2021-12-08 04:21:16,245] Saving..
[2021-12-08 04:21:16,307] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 04:21:16,308] Epoch: 463
[2021-12-08 04:31:02,006] Train: Loss: 1.144 | Acc: 72.284 (926073/1281167) | Lr: 0.0018650304653968564
[2021-12-08 04:31:40,242] Test: Loss: 1.081 | Acc: 73.318 (36659/50000)
[2021-12-08 04:31:40,242] Epoch: 464
[2021-12-08 04:41:33,327] Train: Loss: 1.140 | Acc: 72.434 (927999/1281167) | Lr: 0.00165340399899482
[2021-12-08 04:42:11,614] Test: Loss: 1.076 | Acc: 73.422 (36711/50000)
[2021-12-08 04:42:11,614] Saving..
[2021-12-08 04:42:11,682] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 04:42:11,683] Epoch: 465
[2021-12-08 04:52:05,857] Train: Loss: 1.138 | Acc: 72.478 (928569/1281167) | Lr: 0.0014545579219743146
[2021-12-08 04:52:44,469] Test: Loss: 1.080 | Acc: 73.368 (36684/50000)
[2021-12-08 04:52:44,469] Epoch: 466
[2021-12-08 05:02:34,769] Train: Loss: 1.136 | Acc: 72.556 (929559/1281167) | Lr: 0.001268500752239375
[2021-12-08 05:03:13,502] Test: Loss: 1.074 | Acc: 73.564 (36782/50000)
[2021-12-08 05:03:13,502] Saving..
[2021-12-08 05:03:13,565] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 05:03:13,565] Epoch: 467
[2021-12-08 05:13:11,731] Train: Loss: 1.134 | Acc: 72.536 (929306/1281167) | Lr: 0.001095240459859929
[2021-12-08 05:13:51,096] Test: Loss: 1.073 | Acc: 73.460 (36730/50000)
[2021-12-08 05:13:51,096] Epoch: 468
[2021-12-08 05:23:43,347] Train: Loss: 1.132 | Acc: 72.627 (930475/1281167) | Lr: 0.000934784466730276
[2021-12-08 05:24:23,129] Test: Loss: 1.072 | Acc: 73.530 (36765/50000)
[2021-12-08 05:24:23,129] Epoch: 469
[2021-12-08 05:34:12,760] Train: Loss: 1.130 | Acc: 72.678 (931129/1281167) | Lr: 0.0007871396462511146
[2021-12-08 05:34:52,404] Test: Loss: 1.075 | Acc: 73.446 (36723/50000)
[2021-12-08 05:34:52,404] Epoch: 470
[2021-12-08 05:44:41,342] Train: Loss: 1.130 | Acc: 72.708 (931515/1281167) | Lr: 0.0006523123230351489
[2021-12-08 05:45:19,892] Test: Loss: 1.073 | Acc: 73.470 (36735/50000)
[2021-12-08 05:45:19,892] Epoch: 471
[2021-12-08 05:55:05,675] Train: Loss: 1.130 | Acc: 72.701 (931421/1281167) | Lr: 0.0005303082726361429
[2021-12-08 05:55:43,655] Test: Loss: 1.071 | Acc: 73.690 (36845/50000)
[2021-12-08 05:55:43,655] Saving..
[2021-12-08 05:55:43,776] * Saved checkpoint to ./results/06121158/FENet_imagenet.t7
[2021-12-08 05:55:43,776] Epoch: 472
[2021-12-08 06:05:35,527] Train: Loss: 1.126 | Acc: 72.767 (932263/1281167) | Lr: 0.00042113272130162266
[2021-12-08 06:06:13,584] Test: Loss: 1.072 | Acc: 73.582 (36791/50000)
[2021-12-08 06:06:13,584] Epoch: 473
[2021-12-08 06:15:56,329] Train: Loss: 1.127 | Acc: 72.723 (931698/1281167) | Lr: 0.0003247903457487596
[2021-12-08 06:16:34,428] Test: Loss: 1.071 | Acc: 73.594 (36797/50000)
[2021-12-08 06:16:34,429] Epoch: 474
[2021-12-08 06:26:25,111] Train: Loss: 1.127 | Acc: 72.725 (931735/1281167) | Lr: 0.0002412852729643332
[2021-12-08 06:27:05,920] Test: Loss: 1.068 | Acc: 73.538 (36769/50000)
[2021-12-08 06:27:05,920] Epoch: 475
[2021-12-08 06:36:55,486] Train: Loss: 1.123 | Acc: 72.858 (933431/1281167) | Lr: 0.00017062108002767639
[2021-12-08 06:37:34,129] Test: Loss: 1.067 | Acc: 73.600 (36800/50000)
[2021-12-08 06:37:34,129] Epoch: 476
[2021-12-08 06:47:23,150] Train: Loss: 1.124 | Acc: 72.800 (932695/1281167) | Lr: 0.00011280079395769976
[2021-12-08 06:48:02,885] Test: Loss: 1.071 | Acc: 73.580 (36790/50000)
[2021-12-08 06:48:02,885] Epoch: 477
[2021-12-08 06:57:52,681] Train: Loss: 1.126 | Acc: 72.786 (932506/1281167) | Lr: 6.782689158296475e-05
[2021-12-08 06:58:31,088] Test: Loss: 1.068 | Acc: 73.652 (36826/50000)
[2021-12-08 06:58:31,088] Epoch: 478
[2021-12-08 07:08:23,913] Train: Loss: 1.122 | Acc: 72.801 (932704/1281167) | Lr: 3.5701299435769944e-05
[2021-12-08 07:09:02,224] Test: Loss: 1.067 | Acc: 73.586 (36793/50000)
[2021-12-08 07:09:02,225] Epoch: 479
[2021-12-08 07:18:54,616] Train: Loss: 1.121 | Acc: 72.883 (933757/1281167) | Lr: 1.642539366955192e-05
[2021-12-08 07:19:33,522] Test: Loss: 1.069 | Acc: 73.586 (36793/50000)