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add shufflenetv2 model  
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2023-06-27 21:15:39.051995  cuda
2023-06-27 21:15:53.452143  Train: epoch: 1 batch: 0/4, loss: 0.691736
2023-06-27 21:16:38.049762  Validation: avg loss: 0.6836, avg acc: 59.0476%
2023-06-27 21:16:52.185850  Train: epoch: 2 batch: 0/4, loss: 0.683868
2023-06-27 21:17:37.389718  Validation: avg loss: 0.6768, avg acc: 59.0476%
2023-06-27 21:17:51.753388  Train: epoch: 3 batch: 0/4, loss: 0.703129
2023-06-27 21:18:36.661202  Validation: avg loss: 0.6775, avg acc: 59.0476%
2023-06-27 21:18:50.934819  Train: epoch: 4 batch: 0/4, loss: 0.667924
2023-06-27 21:19:35.880084  Validation: avg loss: 0.6783, avg acc: 59.0476%
2023-06-27 21:19:49.920322  Train: epoch: 5 batch: 0/4, loss: 0.674128
2023-06-27 21:20:34.871162  Validation: avg loss: 0.6920, avg acc: 59.0476%
2023-06-27 21:20:49.132727  Train: epoch: 6 batch: 0/4, loss: 0.626494
2023-06-27 21:21:34.525190  Validation: avg loss: 0.7429, avg acc: 59.0476%
2023-06-27 21:21:48.751058  Train: epoch: 7 batch: 0/4, loss: 0.567501
2023-06-27 21:22:33.738745  Validation: avg loss: 0.7772, avg acc: 59.0476%
2023-06-27 21:22:47.951232  Train: epoch: 8 batch: 0/4, loss: 0.562780
2023-06-27 21:23:32.943781  Validation: avg loss: 0.8472, avg acc: 59.0476%
2023-06-27 21:23:47.254353  Train: epoch: 9 batch: 0/4, loss: 0.426511
2023-06-27 21:24:32.145615  Validation: avg loss: 0.9992, avg acc: 59.0476%
2023-06-27 21:24:46.344709  Train: epoch: 10 batch: 0/4, loss: 0.375800
2023-06-27 21:25:32.287260  Validation: avg loss: 1.1576, avg acc: 59.0476%
2023-06-27 21:25:47.115042  Train: epoch: 11 batch: 0/4, loss: 0.274453
2023-06-27 21:26:32.773379  Validation: avg loss: 1.2782, avg acc: 59.0476%
2023-06-27 21:26:47.355081  Train: epoch: 12 batch: 0/4, loss: 0.188514
2023-06-27 21:27:33.135887  Validation: avg loss: 1.3211, avg acc: 59.0476%
2023-06-27 21:27:47.506455  Train: epoch: 13 batch: 0/4, loss: 0.197023
2023-06-27 21:28:32.250146  Validation: avg loss: 1.3828, avg acc: 58.0952%
2023-06-27 21:28:46.293063  Train: epoch: 14 batch: 0/4, loss: 0.088516
2023-06-27 21:29:30.824847  Validation: avg loss: 1.3960, avg acc: 58.0952%
2023-06-27 21:29:44.970034  Train: epoch: 15 batch: 0/4, loss: 0.083743
2023-06-27 21:30:30.407492  Validation: avg loss: 1.2767, avg acc: 60.9524%
2023-06-27 21:30:44.778389  Train: epoch: 16 batch: 0/4, loss: 0.039141
2023-06-27 21:31:29.605076  Validation: avg loss: 1.0991, avg acc: 67.6190%
2023-06-27 21:31:43.679548  Train: epoch: 17 batch: 0/4, loss: 0.023605
2023-06-27 21:32:28.838137  Validation: avg loss: 1.1428, avg acc: 67.6190%
2023-06-27 21:32:43.063909  Train: epoch: 18 batch: 0/4, loss: 0.022332
2023-06-27 21:33:28.034252  Validation: avg loss: 1.0250, avg acc: 72.3810%
2023-06-27 21:33:42.076954  Train: epoch: 19 batch: 0/4, loss: 0.012294
2023-06-27 21:34:26.854922  Validation: avg loss: 0.9256, avg acc: 71.4286%
2023-06-27 21:34:40.932934  Train: epoch: 20 batch: 0/4, loss: 0.014384
2023-06-27 21:35:25.635924  Validation: avg loss: 0.9767, avg acc: 73.3333%
2023-06-27 21:35:39.737333  Train: epoch: 21 batch: 0/4, loss: 0.009487
2023-06-27 21:36:24.457411  Validation: avg loss: 0.9440, avg acc: 71.4286%
2023-06-27 21:36:38.586486  Train: epoch: 22 batch: 0/4, loss: 0.006818
2023-06-27 21:37:23.292082  Validation: avg loss: 0.9907, avg acc: 67.6190%
2023-06-27 21:37:37.449483  Train: epoch: 23 batch: 0/4, loss: 0.011777
2023-06-27 21:38:22.274693  Validation: avg loss: 1.1097, avg acc: 67.6190%
2023-06-27 21:38:36.552139  Train: epoch: 24 batch: 0/4, loss: 0.011297
2023-06-27 21:39:21.416102  Validation: avg loss: 1.1239, avg acc: 68.5714%
2023-06-27 21:39:35.577825  Train: epoch: 25 batch: 0/4, loss: 0.009228
2023-06-27 21:40:20.364479  Validation: avg loss: 1.0609, avg acc: 71.4286%
2023-06-27 21:40:34.524510  Train: epoch: 26 batch: 0/4, loss: 0.005655
2023-06-27 21:41:20.015263  Validation: avg loss: 1.0012, avg acc: 75.2381%
2023-06-27 21:41:34.185422  Train: epoch: 27 batch: 0/4, loss: 0.004269
2023-06-27 21:42:19.492635  Validation: avg loss: 0.9907, avg acc: 73.3333%
2023-06-27 21:42:33.711277  Train: epoch: 28 batch: 0/4, loss: 0.005315
2023-06-27 21:43:18.951514  Validation: avg loss: 0.9990, avg acc: 76.1905%
2023-06-27 21:43:33.226150  Train: epoch: 29 batch: 0/4, loss: 0.003101
2023-06-27 21:44:18.385598  Validation: avg loss: 1.0010, avg acc: 75.2381%
2023-06-27 21:44:32.557319  Train: epoch: 30 batch: 0/4, loss: 0.005050
2023-06-27 21:45:17.845059  Validation: avg loss: 0.9835, avg acc: 75.2381%
2023-06-27 21:45:32.311005  Train: epoch: 31 batch: 0/4, loss: 0.003702
2023-06-27 21:46:17.639080  Validation: avg loss: 1.0075, avg acc: 74.2857%
2023-06-27 21:46:32.011410  Train: epoch: 32 batch: 0/4, loss: 0.004959
2023-06-27 21:47:17.200451  Validation: avg loss: 1.0417, avg acc: 74.2857%
2023-06-27 21:47:31.743259  Train: epoch: 33 batch: 0/4, loss: 0.001638
2023-06-27 21:48:16.949034  Validation: avg loss: 1.0667, avg acc: 74.2857%
2023-06-27 21:48:31.370050  Train: epoch: 34 batch: 0/4, loss: 0.001611
2023-06-27 21:49:16.177922  Validation: avg loss: 1.0987, avg acc: 71.4286%
2023-06-27 21:49:30.724478  Train: epoch: 35 batch: 0/4, loss: 0.002110
2023-06-27 21:50:15.919399  Validation: avg loss: 1.1157, avg acc: 72.3810%
2023-06-27 21:50:30.599470  Train: epoch: 36 batch: 0/4, loss: 0.001120
2023-06-27 21:51:16.389382  Validation: avg loss: 1.1388, avg acc: 72.3810%
2023-06-27 21:51:30.679179  Train: epoch: 37 batch: 0/4, loss: 0.002431
2023-06-27 21:52:15.278430  Validation: avg loss: 1.1491, avg acc: 70.4762%
2023-06-27 21:52:29.639813  Train: epoch: 38 batch: 0/4, loss: 0.001873
2023-06-27 21:53:14.536530  Validation: avg loss: 1.1600, avg acc: 71.4286%
2023-06-27 21:53:28.745685  Train: epoch: 39 batch: 0/4, loss: 0.001235
2023-06-27 21:54:14.776436  Validation: avg loss: 1.1614, avg acc: 71.4286%
2023-06-27 21:54:31.605806  Train: epoch: 40 batch: 0/4, loss: 0.001205
2023-06-27 21:55:24.907567  Validation: avg loss: 1.1676, avg acc: 70.4762%
2023-06-27 21:55:42.329314  Train: epoch: 41 batch: 0/4, loss: 0.001023
2023-06-27 21:56:36.481476  Validation: avg loss: 1.1545, avg acc: 72.3810%
2023-06-27 21:56:53.250157  Train: epoch: 42 batch: 0/4, loss: 0.000928
2023-06-27 21:57:42.010911  Validation: avg loss: 1.1706, avg acc: 70.4762%
2023-06-27 21:57:56.068171  Train: epoch: 43 batch: 0/4, loss: 0.000772
2023-06-27 21:58:40.707347  Validation: avg loss: 1.1615, avg acc: 68.5714%
2023-06-27 21:58:54.865171  Train: epoch: 44 batch: 0/4, loss: 0.000777
2023-06-27 21:59:39.367311  Validation: avg loss: 1.1684, avg acc: 69.5238%
2023-06-27 21:59:53.743477  Train: epoch: 45 batch: 0/4, loss: 0.000864
2023-06-27 22:00:38.497434  Validation: avg loss: 1.1807, avg acc: 69.5238%
2023-06-27 22:00:52.622961  Train: epoch: 46 batch: 0/4, loss: 0.000633
2023-06-27 22:01:37.127766  Validation: avg loss: 1.1631, avg acc: 70.4762%
2023-06-27 22:01:51.245015  Train: epoch: 47 batch: 0/4, loss: 0.000731
2023-06-27 22:02:35.988887  Validation: avg loss: 1.1821, avg acc: 70.4762%
2023-06-27 22:02:50.288587  Train: epoch: 48 batch: 0/4, loss: 0.000860
2023-06-27 22:03:35.479524  Validation: avg loss: 1.1852, avg acc: 71.4286%
2023-06-27 22:03:49.693263  Train: epoch: 49 batch: 0/4, loss: 0.000542
2023-06-27 22:04:38.663734  Validation: avg loss: 1.1922, avg acc: 71.4286%
2023-06-27 22:04:55.610965  Train: epoch: 50 batch: 0/4, loss: 0.000765
2023-06-27 22:05:48.214104  Validation: avg loss: 1.1724, avg acc: 72.3810%