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add shufflenetv2 model  
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2023-06-27 22:56:27.225385  cuda
2023-06-27 22:56:41.667818  Train: epoch: 1 batch: 0/4, loss: 0.692002
2023-06-27 22:57:26.874897  Validation: avg loss: 0.6831, avg acc: 60.9524%
2023-06-27 22:57:41.358237  Train: epoch: 2 batch: 0/4, loss: 0.698575
2023-06-27 22:58:26.379618  Validation: avg loss: 0.6732, avg acc: 60.9524%
2023-06-27 22:58:40.809971  Train: epoch: 3 batch: 0/4, loss: 0.667633
2023-06-27 22:59:25.992367  Validation: avg loss: 0.6817, avg acc: 60.9524%
2023-06-27 22:59:40.568559  Train: epoch: 4 batch: 0/4, loss: 0.679582
2023-06-27 23:00:26.298536  Validation: avg loss: 0.6736, avg acc: 60.9524%
2023-06-27 23:00:40.815317  Train: epoch: 5 batch: 0/4, loss: 0.648631
2023-06-27 23:01:26.485894  Validation: avg loss: 0.6695, avg acc: 60.9524%
2023-06-27 23:01:40.843563  Train: epoch: 6 batch: 0/4, loss: 0.635978
2023-06-27 23:02:29.786361  Validation: avg loss: 0.6708, avg acc: 60.9524%
2023-06-27 23:02:44.489382  Train: epoch: 7 batch: 0/4, loss: 0.661664
2023-06-27 23:03:30.037811  Validation: avg loss: 0.6677, avg acc: 60.9524%
2023-06-27 23:03:47.009587  Train: epoch: 8 batch: 0/4, loss: 0.542907
2023-06-27 23:04:32.865509  Validation: avg loss: 0.6692, avg acc: 60.9524%
2023-06-27 23:04:47.364673  Train: epoch: 9 batch: 0/4, loss: 0.522208
2023-06-27 23:05:31.970194  Validation: avg loss: 0.6648, avg acc: 60.9524%
2023-06-27 23:05:46.158624  Train: epoch: 10 batch: 0/4, loss: 0.416084
2023-06-27 23:06:31.870999  Validation: avg loss: 0.6632, avg acc: 60.9524%
2023-06-27 23:06:46.130888  Train: epoch: 11 batch: 0/4, loss: 0.351118
2023-06-27 23:07:31.221879  Validation: avg loss: 0.6562, avg acc: 60.0000%
2023-06-27 23:07:45.620858  Train: epoch: 12 batch: 0/4, loss: 0.248121
2023-06-27 23:08:30.712929  Validation: avg loss: 0.6558, avg acc: 63.8095%
2023-06-27 23:08:45.170842  Train: epoch: 13 batch: 0/4, loss: 0.178588
2023-06-27 23:09:30.276789  Validation: avg loss: 0.6722, avg acc: 61.9048%
2023-06-27 23:09:44.853074  Train: epoch: 14 batch: 0/4, loss: 0.138953
2023-06-27 23:10:30.888671  Validation: avg loss: 0.7421, avg acc: 60.9524%
2023-06-27 23:10:45.386170  Train: epoch: 15 batch: 0/4, loss: 0.071094
2023-06-27 23:11:30.634682  Validation: avg loss: 0.7772, avg acc: 64.7619%
2023-06-27 23:11:44.951292  Train: epoch: 16 batch: 0/4, loss: 0.050339
2023-06-27 23:12:30.229361  Validation: avg loss: 0.8185, avg acc: 66.6667%
2023-06-27 23:12:44.429996  Train: epoch: 17 batch: 0/4, loss: 0.034063
2023-06-27 23:13:29.440894  Validation: avg loss: 0.8194, avg acc: 66.6667%
2023-06-27 23:13:43.809310  Train: epoch: 18 batch: 0/4, loss: 0.023794
2023-06-27 23:14:28.850536  Validation: avg loss: 0.8726, avg acc: 68.5714%
2023-06-27 23:14:43.125232  Train: epoch: 19 batch: 0/4, loss: 0.023007
2023-06-27 23:15:28.506826  Validation: avg loss: 0.9418, avg acc: 68.5714%
2023-06-27 23:15:42.724516  Train: epoch: 20 batch: 0/4, loss: 0.015237
2023-06-27 23:16:28.095369  Validation: avg loss: 0.9700, avg acc: 67.6190%
2023-06-27 23:16:42.467405  Train: epoch: 21 batch: 0/4, loss: 0.018638
2023-06-27 23:17:27.392373  Validation: avg loss: 1.0220, avg acc: 67.6190%
2023-06-27 23:17:41.575813  Train: epoch: 22 batch: 0/4, loss: 0.019878
2023-06-27 23:18:27.590927  Validation: avg loss: 1.1214, avg acc: 67.6190%
2023-06-27 23:18:41.640636  Train: epoch: 23 batch: 0/4, loss: 0.015436
2023-06-27 23:19:28.790967  Validation: avg loss: 1.2076, avg acc: 69.5238%
2023-06-27 23:19:45.854187  Train: epoch: 24 batch: 0/4, loss: 0.008988
2023-06-27 23:20:39.596887  Validation: avg loss: 1.3185, avg acc: 67.6190%
2023-06-27 23:20:56.522372  Train: epoch: 25 batch: 0/4, loss: 0.010765
2023-06-27 23:21:49.772384  Validation: avg loss: 1.4392, avg acc: 65.7143%
2023-06-27 23:22:06.752625  Train: epoch: 26 batch: 0/4, loss: 0.008803
2023-06-27 23:23:00.704419  Validation: avg loss: 1.5443, avg acc: 64.7619%
2023-06-27 23:23:17.697921  Train: epoch: 27 batch: 0/4, loss: 0.010919
2023-06-27 23:24:11.634059  Validation: avg loss: 1.5816, avg acc: 62.8571%
2023-06-27 23:24:28.635486  Train: epoch: 28 batch: 0/4, loss: 0.020247
2023-06-27 23:25:13.610646  Validation: avg loss: 1.5745, avg acc: 64.7619%
2023-06-27 23:25:27.762826  Train: epoch: 29 batch: 0/4, loss: 0.010510
2023-06-27 23:26:12.795590  Validation: avg loss: 1.5999, avg acc: 61.9048%
2023-06-27 23:26:27.565790  Train: epoch: 30 batch: 0/4, loss: 0.006730
2023-06-27 23:27:17.502410  Validation: avg loss: 1.5201, avg acc: 66.6667%
2023-06-27 23:27:34.741583  Train: epoch: 31 batch: 0/4, loss: 0.012892
2023-06-27 23:28:28.530721  Validation: avg loss: 1.5273, avg acc: 66.6667%
2023-06-27 23:28:45.886919  Train: epoch: 32 batch: 0/4, loss: 0.007448
2023-06-27 23:29:39.793679  Validation: avg loss: 1.5663, avg acc: 65.7143%
2023-06-27 23:29:56.559218  Train: epoch: 33 batch: 0/4, loss: 0.007973
2023-06-27 23:30:49.808918  Validation: avg loss: 1.6759, avg acc: 64.7619%
2023-06-27 23:31:06.749643  Train: epoch: 34 batch: 0/4, loss: 0.010191
2023-06-27 23:32:00.240737  Validation: avg loss: 1.7061, avg acc: 64.7619%
2023-06-27 23:32:17.436448  Train: epoch: 35 batch: 0/4, loss: 0.009669
2023-06-27 23:33:11.917138  Validation: avg loss: 1.6786, avg acc: 65.7143%
2023-06-27 23:33:29.083028  Train: epoch: 36 batch: 0/4, loss: 0.005688
2023-06-27 23:34:22.249065  Validation: avg loss: 1.6233, avg acc: 64.7619%
2023-06-27 23:34:36.440779  Train: epoch: 37 batch: 0/4, loss: 0.011351
2023-06-27 23:35:21.608001  Validation: avg loss: 1.4958, avg acc: 64.7619%
2023-06-27 23:35:35.757051  Train: epoch: 38 batch: 0/4, loss: 0.013235
2023-06-27 23:36:21.070012  Validation: avg loss: 1.4995, avg acc: 65.7143%
2023-06-27 23:36:35.183467  Train: epoch: 39 batch: 0/4, loss: 0.004506
2023-06-27 23:37:19.755812  Validation: avg loss: 1.5822, avg acc: 66.6667%
2023-06-27 23:37:33.834424  Train: epoch: 40 batch: 0/4, loss: 0.004020
2023-06-27 23:38:18.418379  Validation: avg loss: 1.5952, avg acc: 65.7143%
2023-06-27 23:38:32.532155  Train: epoch: 41 batch: 0/4, loss: 0.006036
2023-06-27 23:39:17.399217  Validation: avg loss: 1.5330, avg acc: 64.7619%
2023-06-27 23:39:31.655960  Train: epoch: 42 batch: 0/4, loss: 0.002260
2023-06-27 23:40:16.697558  Validation: avg loss: 1.5543, avg acc: 63.8095%
2023-06-27 23:40:31.012751  Train: epoch: 43 batch: 0/4, loss: 0.001725
2023-06-27 23:41:16.613344  Validation: avg loss: 1.6196, avg acc: 61.9048%
2023-06-27 23:41:31.058310  Train: epoch: 44 batch: 0/4, loss: 0.002373
2023-06-27 23:42:16.007442  Validation: avg loss: 2.0231, avg acc: 64.7619%
2023-06-27 23:42:30.329439  Train: epoch: 45 batch: 0/4, loss: 0.003343
2023-06-27 23:43:15.956035  Validation: avg loss: 2.3722, avg acc: 61.9048%
2023-06-27 23:43:30.537132  Train: epoch: 46 batch: 0/4, loss: 0.020183
2023-06-27 23:44:15.327968  Validation: avg loss: 1.6412, avg acc: 63.8095%
2023-06-27 23:44:29.571036  Train: epoch: 47 batch: 0/4, loss: 0.005822
2023-06-27 23:45:14.703431  Validation: avg loss: 1.7010, avg acc: 62.8571%
2023-06-27 23:45:28.895749  Train: epoch: 48 batch: 0/4, loss: 0.009988
2023-06-27 23:46:14.372640  Validation: avg loss: 1.6787, avg acc: 64.7619%
2023-06-27 23:46:28.549947  Train: epoch: 49 batch: 0/4, loss: 0.004813
2023-06-27 23:47:13.802909  Validation: avg loss: 1.7751, avg acc: 64.7619%
2023-06-27 23:47:27.910214  Train: epoch: 50 batch: 0/4, loss: 0.005619
2023-06-27 23:48:12.643633  Validation: avg loss: 1.8753, avg acc: 60.9524%