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add shufflenetv2 model  
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2023-06-27 19:18:48.198217  cuda
2023-06-27 19:19:15.294061  Train: epoch: 1 batch: 0/4, loss: 0.692022
2023-06-27 19:20:41.277842  Validation: avg loss: 0.6873, avg acc: 58.0952%
2023-06-27 19:21:08.531033  Train: epoch: 2 batch: 0/4, loss: 0.678517
2023-06-27 19:22:34.606377  Validation: avg loss: 0.6854, avg acc: 58.0952%
2023-06-27 19:23:01.844717  Train: epoch: 3 batch: 0/4, loss: 0.670388
2023-06-27 19:24:27.983871  Validation: avg loss: 0.6884, avg acc: 58.0952%
2023-06-27 19:24:55.143142  Train: epoch: 4 batch: 0/4, loss: 0.697613
2023-06-27 19:26:21.439926  Validation: avg loss: 0.6845, avg acc: 58.0952%
2023-06-27 19:26:48.654835  Train: epoch: 5 batch: 0/4, loss: 0.643741
2023-06-27 19:28:14.701148  Validation: avg loss: 0.6798, avg acc: 58.0952%
2023-06-27 19:28:41.855906  Train: epoch: 6 batch: 0/4, loss: 0.639591
2023-06-27 19:30:08.016620  Validation: avg loss: 0.6894, avg acc: 58.0952%
2023-06-27 19:30:35.337619  Train: epoch: 7 batch: 0/4, loss: 0.604846
2023-06-27 19:32:01.530659  Validation: avg loss: 0.7069, avg acc: 41.9048%
2023-06-27 19:32:28.813132  Train: epoch: 8 batch: 0/4, loss: 0.574580
2023-06-27 19:33:55.009578  Validation: avg loss: 0.6978, avg acc: 42.8571%
2023-06-27 19:34:22.248886  Train: epoch: 9 batch: 0/4, loss: 0.520313
2023-06-27 19:35:48.574277  Validation: avg loss: 0.7286, avg acc: 41.9048%
2023-06-27 19:36:15.771553  Train: epoch: 10 batch: 0/4, loss: 0.508012
2023-06-27 19:37:42.066795  Validation: avg loss: 0.7102, avg acc: 42.8571%
2023-06-27 19:38:09.316067  Train: epoch: 11 batch: 0/4, loss: 0.445963
2023-06-27 19:39:35.463861  Validation: avg loss: 0.7605, avg acc: 42.8571%
2023-06-27 19:40:02.659232  Train: epoch: 12 batch: 0/4, loss: 0.274907
2023-06-27 19:41:28.589119  Validation: avg loss: 0.8236, avg acc: 44.7619%
2023-06-27 19:41:55.725336  Train: epoch: 13 batch: 0/4, loss: 0.229953
2023-06-27 19:43:21.862888  Validation: avg loss: 0.8172, avg acc: 50.4762%
2023-06-27 19:43:49.058039  Train: epoch: 14 batch: 0/4, loss: 0.142196
2023-06-27 19:45:15.064675  Validation: avg loss: 0.8579, avg acc: 53.3333%
2023-06-27 19:45:42.330094  Train: epoch: 15 batch: 0/4, loss: 0.099136
2023-06-27 19:47:08.432933  Validation: avg loss: 0.9230, avg acc: 54.2857%
2023-06-27 19:47:35.601256  Train: epoch: 16 batch: 0/4, loss: 0.065903
2023-06-27 19:49:01.525098  Validation: avg loss: 0.8951, avg acc: 62.8571%
2023-06-27 19:49:28.732127  Train: epoch: 17 batch: 0/4, loss: 0.034419
2023-06-27 19:50:54.735994  Validation: avg loss: 0.9322, avg acc: 66.6667%
2023-06-27 19:51:21.915114  Train: epoch: 18 batch: 0/4, loss: 0.031674
2023-06-27 19:52:47.963015  Validation: avg loss: 0.9627, avg acc: 67.6190%
2023-06-27 19:53:15.140215  Train: epoch: 19 batch: 0/4, loss: 0.035861
2023-06-27 19:54:41.236262  Validation: avg loss: 1.0616, avg acc: 64.7619%
2023-06-27 19:55:08.476282  Train: epoch: 20 batch: 0/4, loss: 0.017844
2023-06-27 19:56:34.404703  Validation: avg loss: 1.0661, avg acc: 64.7619%
2023-06-27 19:57:01.567031  Train: epoch: 21 batch: 0/4, loss: 0.028972
2023-06-27 19:58:27.737198  Validation: avg loss: 1.0875, avg acc: 66.6667%
2023-06-27 19:58:54.918224  Train: epoch: 22 batch: 0/4, loss: 0.022829
2023-06-27 20:00:20.949224  Validation: avg loss: 1.2039, avg acc: 64.7619%
2023-06-27 20:00:48.312823  Train: epoch: 23 batch: 0/4, loss: 0.010412
2023-06-27 20:02:14.748642  Validation: avg loss: 1.2402, avg acc: 66.6667%
2023-06-27 20:02:42.089930  Train: epoch: 24 batch: 0/4, loss: 0.017833
2023-06-27 20:04:08.397588  Validation: avg loss: 1.2312, avg acc: 69.5238%
2023-06-27 20:04:35.753850  Train: epoch: 25 batch: 0/4, loss: 0.007784
2023-06-27 20:06:02.120864  Validation: avg loss: 1.2695, avg acc: 67.6190%
2023-06-27 20:06:29.382582  Train: epoch: 26 batch: 0/4, loss: 0.007875
2023-06-27 20:07:55.777708  Validation: avg loss: 1.3071, avg acc: 70.4762%
2023-06-27 20:08:23.092892  Train: epoch: 27 batch: 0/4, loss: 0.004158
2023-06-27 20:09:49.568930  Validation: avg loss: 1.3470, avg acc: 68.5714%
2023-06-27 20:10:16.842231  Train: epoch: 28 batch: 0/4, loss: 0.004838
2023-06-27 20:11:43.335726  Validation: avg loss: 1.3752, avg acc: 69.5238%
2023-06-27 20:12:10.647031  Train: epoch: 29 batch: 0/4, loss: 0.002664
2023-06-27 20:13:36.900521  Validation: avg loss: 1.3785, avg acc: 69.5238%
2023-06-27 20:14:04.162619  Train: epoch: 30 batch: 0/4, loss: 0.002635
2023-06-27 20:15:30.427153  Validation: avg loss: 1.4110, avg acc: 69.5238%
2023-06-27 20:15:57.495602  Train: epoch: 31 batch: 0/4, loss: 0.002836
2023-06-27 20:17:23.502943  Validation: avg loss: 1.4009, avg acc: 67.6190%
2023-06-27 20:17:50.880211  Train: epoch: 32 batch: 0/4, loss: 0.003082
2023-06-27 20:19:17.376544  Validation: avg loss: 1.3800, avg acc: 66.6667%
2023-06-27 20:19:44.714264  Train: epoch: 33 batch: 0/4, loss: 0.002626
2023-06-27 20:21:10.996699  Validation: avg loss: 1.3879, avg acc: 65.7143%
2023-06-27 20:21:38.282961  Train: epoch: 34 batch: 0/4, loss: 0.003446
2023-06-27 20:23:04.636640  Validation: avg loss: 1.3688, avg acc: 65.7143%
2023-06-27 20:23:32.059078  Train: epoch: 35 batch: 0/4, loss: 0.004321
2023-06-27 20:24:58.438434  Validation: avg loss: 1.3742, avg acc: 64.7619%
2023-06-27 20:25:25.737069  Train: epoch: 36 batch: 0/4, loss: 0.001553
2023-06-27 20:26:52.131139  Validation: avg loss: 1.3750, avg acc: 64.7619%
2023-06-27 20:27:19.435960  Train: epoch: 37 batch: 0/4, loss: 0.001395
2023-06-27 20:28:45.787530  Validation: avg loss: 1.3801, avg acc: 65.7143%
2023-06-27 20:29:13.090991  Train: epoch: 38 batch: 0/4, loss: 0.001076
2023-06-27 20:30:39.336450  Validation: avg loss: 1.3961, avg acc: 65.7143%
2023-06-27 20:31:06.539441  Train: epoch: 39 batch: 0/4, loss: 0.001392
2023-06-27 20:32:32.702476  Validation: avg loss: 1.4081, avg acc: 65.7143%
2023-06-27 20:32:59.901209  Train: epoch: 40 batch: 0/4, loss: 0.000945
2023-06-27 20:34:25.891464  Validation: avg loss: 1.4195, avg acc: 65.7143%
2023-06-27 20:34:53.028886  Train: epoch: 41 batch: 0/4, loss: 0.000940
2023-06-27 20:36:19.227416  Validation: avg loss: 1.4202, avg acc: 64.7619%
2023-06-27 20:36:46.355918  Train: epoch: 42 batch: 0/4, loss: 0.000859
2023-06-27 20:38:12.345681  Validation: avg loss: 1.4267, avg acc: 65.7143%
2023-06-27 20:38:39.564975  Train: epoch: 43 batch: 0/4, loss: 0.000871
2023-06-27 20:40:05.590265  Validation: avg loss: 1.4332, avg acc: 64.7619%
2023-06-27 20:40:32.795884  Train: epoch: 44 batch: 0/4, loss: 0.002657
2023-06-27 20:41:58.871446  Validation: avg loss: 1.4451, avg acc: 66.6667%
2023-06-27 20:42:26.156905  Train: epoch: 45 batch: 0/4, loss: 0.000708
2023-06-27 20:43:52.503323  Validation: avg loss: 1.4392, avg acc: 67.6190%
2023-06-27 20:44:19.847648  Train: epoch: 46 batch: 0/4, loss: 0.000994
2023-06-27 20:45:46.028815  Validation: avg loss: 1.4327, avg acc: 67.6190%
2023-06-27 20:46:13.284179  Train: epoch: 47 batch: 0/4, loss: 0.000703
2023-06-27 20:47:39.801806  Validation: avg loss: 1.4274, avg acc: 67.6190%
2023-06-27 20:48:06.965401  Train: epoch: 48 batch: 0/4, loss: 0.000721
2023-06-27 20:49:33.322803  Validation: avg loss: 1.4285, avg acc: 67.6190%
2023-06-27 20:50:00.600342  Train: epoch: 49 batch: 0/4, loss: 0.001099
2023-06-27 20:51:27.066750  Validation: avg loss: 1.4424, avg acc: 66.6667%
2023-06-27 20:51:54.342141  Train: epoch: 50 batch: 0/4, loss: 0.001182
2023-06-27 20:53:20.596007  Validation: avg loss: 1.4568, avg acc: 65.7143%