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add shufflenetv2 model  
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2023-06-27 13:00:26.176732  cuda
2023-06-27 13:00:53.363334  Train: epoch: 1 batch: 0/4, loss: 0.691868
2023-06-27 13:02:19.586241  Validation: avg loss: 0.6879, avg acc: 57.1429%
2023-06-27 13:02:46.901065  Train: epoch: 2 batch: 0/4, loss: 0.667772
2023-06-27 13:04:13.269972  Validation: avg loss: 0.6835, avg acc: 57.1429%
2023-06-27 13:04:40.613288  Train: epoch: 3 batch: 0/4, loss: 0.684359
2023-06-27 13:06:06.965697  Validation: avg loss: 0.6853, avg acc: 57.1429%
2023-06-27 13:06:34.320390  Train: epoch: 4 batch: 0/4, loss: 0.664518
2023-06-27 13:08:00.635158  Validation: avg loss: 0.6830, avg acc: 57.1429%
2023-06-27 13:08:27.965382  Train: epoch: 5 batch: 0/4, loss: 0.648012
2023-06-27 13:09:54.395378  Validation: avg loss: 0.6834, avg acc: 57.1429%
2023-06-27 13:10:21.695506  Train: epoch: 6 batch: 0/4, loss: 0.622020
2023-06-27 13:11:47.946932  Validation: avg loss: 0.6859, avg acc: 57.1429%
2023-06-27 13:12:15.181922  Train: epoch: 7 batch: 0/4, loss: 0.609585
2023-06-27 13:13:41.561458  Validation: avg loss: 0.6824, avg acc: 57.1429%
2023-06-27 13:14:08.777052  Train: epoch: 8 batch: 0/4, loss: 0.554784
2023-06-27 13:15:35.155008  Validation: avg loss: 0.6889, avg acc: 48.5714%
2023-06-27 13:16:02.400262  Train: epoch: 9 batch: 0/4, loss: 0.496770
2023-06-27 13:17:28.802709  Validation: avg loss: 0.6760, avg acc: 65.7143%
2023-06-27 13:17:56.148338  Train: epoch: 10 batch: 0/4, loss: 0.441182
2023-06-27 13:19:22.260881  Validation: avg loss: 0.6602, avg acc: 67.6190%
2023-06-27 13:19:49.537218  Train: epoch: 11 batch: 0/4, loss: 0.355155
2023-06-27 13:21:15.720325  Validation: avg loss: 0.6404, avg acc: 64.7619%
2023-06-27 13:21:42.980084  Train: epoch: 12 batch: 0/4, loss: 0.252484
2023-06-27 13:23:09.091058  Validation: avg loss: 0.5940, avg acc: 71.4286%
2023-06-27 13:23:36.276716  Train: epoch: 13 batch: 0/4, loss: 0.208692
2023-06-27 13:25:02.313005  Validation: avg loss: 0.5678, avg acc: 73.3333%
2023-06-27 13:25:29.525993  Train: epoch: 14 batch: 0/4, loss: 0.123566
2023-06-27 13:26:55.587109  Validation: avg loss: 0.5313, avg acc: 71.4286%
2023-06-27 13:27:22.752260  Train: epoch: 15 batch: 0/4, loss: 0.094163
2023-06-27 13:28:48.798156  Validation: avg loss: 0.5629, avg acc: 73.3333%
2023-06-27 13:29:15.918495  Train: epoch: 16 batch: 0/4, loss: 0.128869
2023-06-27 13:30:42.177941  Validation: avg loss: 0.4869, avg acc: 74.2857%
2023-06-27 13:31:09.371665  Train: epoch: 17 batch: 0/4, loss: 0.052145
2023-06-27 13:32:35.288189  Validation: avg loss: 0.4811, avg acc: 77.1429%
2023-06-27 13:33:02.526205  Train: epoch: 18 batch: 0/4, loss: 0.081217
2023-06-27 13:34:28.685232  Validation: avg loss: 0.5027, avg acc: 79.0476%
2023-06-27 13:34:55.827462  Train: epoch: 19 batch: 0/4, loss: 0.037434
2023-06-27 13:36:21.995335  Validation: avg loss: 0.5522, avg acc: 75.2381%
2023-06-27 13:36:49.182171  Train: epoch: 20 batch: 0/4, loss: 0.018138
2023-06-27 13:38:15.321220  Validation: avg loss: 0.5970, avg acc: 73.3333%
2023-06-27 13:38:42.563163  Train: epoch: 21 batch: 0/4, loss: 0.046510
2023-06-27 13:40:08.856619  Validation: avg loss: 0.6442, avg acc: 76.1905%
2023-06-27 13:40:36.011785  Train: epoch: 22 batch: 0/4, loss: 0.012692
2023-06-27 13:42:02.041543  Validation: avg loss: 0.6929, avg acc: 76.1905%
2023-06-27 13:42:29.300622  Train: epoch: 23 batch: 0/4, loss: 0.012382
2023-06-27 13:43:55.469573  Validation: avg loss: 0.7413, avg acc: 71.4286%
2023-06-27 13:44:22.657185  Train: epoch: 24 batch: 0/4, loss: 0.011344
2023-06-27 13:45:48.869449  Validation: avg loss: 0.7875, avg acc: 73.3333%
2023-06-27 13:46:16.075639  Train: epoch: 25 batch: 0/4, loss: 0.022635
2023-06-27 13:47:42.235744  Validation: avg loss: 0.7924, avg acc: 73.3333%
2023-06-27 13:48:09.432941  Train: epoch: 26 batch: 0/4, loss: 0.009560
2023-06-27 13:49:35.588933  Validation: avg loss: 0.7965, avg acc: 74.2857%
2023-06-27 13:50:02.731198  Train: epoch: 27 batch: 0/4, loss: 0.006484
2023-06-27 13:51:28.970791  Validation: avg loss: 0.8587, avg acc: 74.2857%
2023-06-27 13:51:56.247704  Train: epoch: 28 batch: 0/4, loss: 0.004506
2023-06-27 13:53:22.570553  Validation: avg loss: 0.9319, avg acc: 73.3333%
2023-06-27 13:53:49.732500  Train: epoch: 29 batch: 0/4, loss: 0.004227
2023-06-27 13:55:15.890086  Validation: avg loss: 0.8644, avg acc: 74.2857%
2023-06-27 13:55:43.166997  Train: epoch: 30 batch: 0/4, loss: 0.004787
2023-06-27 13:57:09.235315  Validation: avg loss: 0.8508, avg acc: 72.3810%
2023-06-27 13:57:36.386078  Train: epoch: 31 batch: 0/4, loss: 0.002624
2023-06-27 13:59:02.482710  Validation: avg loss: 0.8385, avg acc: 75.2381%
2023-06-27 13:59:29.719151  Train: epoch: 32 batch: 0/4, loss: 0.003996
2023-06-27 14:00:55.748644  Validation: avg loss: 0.8409, avg acc: 74.2857%
2023-06-27 14:01:22.921139  Train: epoch: 33 batch: 0/4, loss: 0.005487
2023-06-27 14:02:48.968525  Validation: avg loss: 0.8594, avg acc: 74.2857%
2023-06-27 14:03:16.144621  Train: epoch: 34 batch: 0/4, loss: 0.003296
2023-06-27 14:04:42.352338  Validation: avg loss: 0.8764, avg acc: 73.3333%
2023-06-27 14:05:09.507317  Train: epoch: 35 batch: 0/4, loss: 0.005862
2023-06-27 14:06:35.551024  Validation: avg loss: 0.8320, avg acc: 73.3333%
2023-06-27 14:07:02.704332  Train: epoch: 36 batch: 0/4, loss: 0.002351
2023-06-27 14:08:28.965811  Validation: avg loss: 0.8140, avg acc: 73.3333%
2023-06-27 14:08:56.202001  Train: epoch: 37 batch: 0/4, loss: 0.002389
2023-06-27 14:10:22.374434  Validation: avg loss: 0.8012, avg acc: 71.4286%
2023-06-27 14:10:49.581906  Train: epoch: 38 batch: 0/4, loss: 0.002360
2023-06-27 14:12:15.699183  Validation: avg loss: 0.7955, avg acc: 73.3333%
2023-06-27 14:12:42.882802  Train: epoch: 39 batch: 0/4, loss: 0.005763
2023-06-27 14:14:08.871220  Validation: avg loss: 0.7908, avg acc: 72.3810%
2023-06-27 14:14:36.148245  Train: epoch: 40 batch: 0/4, loss: 0.002953
2023-06-27 14:16:02.167597  Validation: avg loss: 0.8192, avg acc: 72.3810%
2023-06-27 14:16:29.353076  Train: epoch: 41 batch: 0/4, loss: 0.001854
2023-06-27 14:17:55.580920  Validation: avg loss: 0.8337, avg acc: 72.3810%
2023-06-27 14:18:22.841567  Train: epoch: 42 batch: 0/4, loss: 0.000968
2023-06-27 14:19:49.351311  Validation: avg loss: 0.8357, avg acc: 73.3333%
2023-06-27 14:20:16.702014  Train: epoch: 43 batch: 0/4, loss: 0.001232
2023-06-27 14:21:42.954946  Validation: avg loss: 0.8496, avg acc: 73.3333%
2023-06-27 14:22:10.272910  Train: epoch: 44 batch: 0/4, loss: 0.001958
2023-06-27 14:23:36.654827  Validation: avg loss: 0.8383, avg acc: 72.3810%
2023-06-27 14:24:03.851239  Train: epoch: 45 batch: 0/4, loss: 0.001643
2023-06-27 14:25:30.184931  Validation: avg loss: 0.8326, avg acc: 71.4286%
2023-06-27 14:25:57.497775  Train: epoch: 46 batch: 0/4, loss: 0.002304
2023-06-27 14:27:23.878822  Validation: avg loss: 0.8342, avg acc: 71.4286%
2023-06-27 14:27:51.095171  Train: epoch: 47 batch: 0/4, loss: 0.001024
2023-06-27 14:29:17.481154  Validation: avg loss: 0.8329, avg acc: 71.4286%
2023-06-27 14:29:44.770846  Train: epoch: 48 batch: 0/4, loss: 0.001529
2023-06-27 14:31:11.200693  Validation: avg loss: 0.8283, avg acc: 70.4762%
2023-06-27 14:31:38.445203  Train: epoch: 49 batch: 0/4, loss: 0.000885
2023-06-27 14:33:04.914596  Validation: avg loss: 0.8007, avg acc: 73.3333%
2023-06-27 14:33:32.124726  Train: epoch: 50 batch: 0/4, loss: 0.000966
2023-06-27 14:34:58.186159  Validation: avg loss: 0.7996, avg acc: 72.3810%