2023-06-27 14:34:58.219015  cuda
2023-06-27 14:35:25.429647  Train: epoch: 1 batch: 0/4, loss: 0.692641
2023-06-27 14:36:52.028023  Validation: avg loss: 0.6886, avg acc: 58.0952%
2023-06-27 14:37:19.371470  Train: epoch: 2 batch: 0/4, loss: 0.679666
2023-06-27 14:38:45.994577  Validation: avg loss: 0.6812, avg acc: 58.0952%
2023-06-27 14:39:13.268237  Train: epoch: 3 batch: 0/4, loss: 0.679477
2023-06-27 14:40:39.747142  Validation: avg loss: 0.6885, avg acc: 58.0952%
2023-06-27 14:41:07.096706  Train: epoch: 4 batch: 0/4, loss: 0.671980
2023-06-27 14:42:33.828256  Validation: avg loss: 0.6863, avg acc: 58.0952%
2023-06-27 14:43:01.088619  Train: epoch: 5 batch: 0/4, loss: 0.650531
2023-06-27 14:44:27.638675  Validation: avg loss: 0.6861, avg acc: 58.0952%
2023-06-27 14:44:54.990063  Train: epoch: 6 batch: 0/4, loss: 0.641892
2023-06-27 14:46:21.588466  Validation: avg loss: 0.6821, avg acc: 58.0952%
2023-06-27 14:46:48.886209  Train: epoch: 7 batch: 0/4, loss: 0.600969
2023-06-27 14:48:15.496536  Validation: avg loss: 0.7011, avg acc: 41.9048%
2023-06-27 14:48:42.770579  Train: epoch: 8 batch: 0/4, loss: 0.602727
2023-06-27 14:50:09.541234  Validation: avg loss: 0.7364, avg acc: 41.9048%
2023-06-27 14:50:36.771359  Train: epoch: 9 batch: 0/4, loss: 0.546539
2023-06-27 14:52:03.483383  Validation: avg loss: 0.7714, avg acc: 41.9048%
2023-06-27 14:52:30.907359  Train: epoch: 10 batch: 0/4, loss: 0.477320
2023-06-27 14:53:57.804455  Validation: avg loss: 0.8625, avg acc: 41.9048%
2023-06-27 14:54:25.187596  Train: epoch: 11 batch: 0/4, loss: 0.415886
2023-06-27 14:55:51.722946  Validation: avg loss: 0.8547, avg acc: 42.8571%
2023-06-27 14:56:19.059857  Train: epoch: 12 batch: 0/4, loss: 0.343199
2023-06-27 14:57:45.474514  Validation: avg loss: 0.9023, avg acc: 42.8571%
2023-06-27 14:58:12.630153  Train: epoch: 13 batch: 0/4, loss: 0.291277
2023-06-27 14:59:38.986668  Validation: avg loss: 1.0237, avg acc: 41.9048%
2023-06-27 15:00:06.121183  Train: epoch: 14 batch: 0/4, loss: 0.198794
2023-06-27 15:01:32.539287  Validation: avg loss: 0.9636, avg acc: 52.3810%
2023-06-27 15:01:59.739159  Train: epoch: 15 batch: 0/4, loss: 0.120545
2023-06-27 15:03:26.027892  Validation: avg loss: 0.8863, avg acc: 54.2857%
2023-06-27 15:03:53.279023  Train: epoch: 16 batch: 0/4, loss: 0.111169
2023-06-27 15:05:19.701211  Validation: avg loss: 0.9601, avg acc: 54.2857%
2023-06-27 15:05:46.913710  Train: epoch: 17 batch: 0/4, loss: 0.048385
2023-06-27 15:07:13.367950  Validation: avg loss: 0.9682, avg acc: 55.2381%
2023-06-27 15:07:40.522977  Train: epoch: 18 batch: 0/4, loss: 0.034194
2023-06-27 15:09:06.797498  Validation: avg loss: 0.9487, avg acc: 61.9048%
2023-06-27 15:09:33.996084  Train: epoch: 19 batch: 0/4, loss: 0.041916
2023-06-27 15:11:00.495380  Validation: avg loss: 0.9886, avg acc: 60.0000%
2023-06-27 15:11:27.700340  Train: epoch: 20 batch: 0/4, loss: 0.018873
2023-06-27 15:12:54.125217  Validation: avg loss: 1.0086, avg acc: 62.8571%
2023-06-27 15:13:21.393051  Train: epoch: 21 batch: 0/4, loss: 0.013758
2023-06-27 15:14:47.845321  Validation: avg loss: 1.0361, avg acc: 62.8571%
2023-06-27 15:15:15.068215  Train: epoch: 22 batch: 0/4, loss: 0.024895
2023-06-27 15:16:41.458406  Validation: avg loss: 1.0681, avg acc: 56.1905%
2023-06-27 15:17:08.797059  Train: epoch: 23 batch: 0/4, loss: 0.010909
2023-06-27 15:18:35.072484  Validation: avg loss: 1.1441, avg acc: 57.1429%
2023-06-27 15:19:02.312870  Train: epoch: 24 batch: 0/4, loss: 0.021563
2023-06-27 15:20:28.638937  Validation: avg loss: 1.1544, avg acc: 55.2381%
2023-06-27 15:20:55.877058  Train: epoch: 25 batch: 0/4, loss: 0.011905
2023-06-27 15:22:22.190719  Validation: avg loss: 1.1842, avg acc: 61.9048%
2023-06-27 15:22:49.392648  Train: epoch: 26 batch: 0/4, loss: 0.005870
2023-06-27 15:24:15.761457  Validation: avg loss: 1.2231, avg acc: 60.0000%
2023-06-27 15:24:43.009076  Train: epoch: 27 batch: 0/4, loss: 0.007372
2023-06-27 15:26:09.389701  Validation: avg loss: 1.1673, avg acc: 60.0000%
2023-06-27 15:26:36.607810  Train: epoch: 28 batch: 0/4, loss: 0.008340
2023-06-27 15:28:03.076340  Validation: avg loss: 1.1514, avg acc: 60.9524%
2023-06-27 15:28:30.257499  Train: epoch: 29 batch: 0/4, loss: 0.009561
2023-06-27 15:29:56.482834  Validation: avg loss: 1.1984, avg acc: 60.9524%
2023-06-27 15:30:23.675110  Train: epoch: 30 batch: 0/4, loss: 0.003211
2023-06-27 15:31:50.080039  Validation: avg loss: 1.2334, avg acc: 58.0952%
2023-06-27 15:32:17.220022  Train: epoch: 31 batch: 0/4, loss: 0.002422
2023-06-27 15:33:43.538192  Validation: avg loss: 1.3136, avg acc: 57.1429%
2023-06-27 15:34:10.747774  Train: epoch: 32 batch: 0/4, loss: 0.003088
2023-06-27 15:35:37.043014  Validation: avg loss: 1.3489, avg acc: 58.0952%
2023-06-27 15:36:04.215670  Train: epoch: 33 batch: 0/4, loss: 0.004744
2023-06-27 15:37:30.760332  Validation: avg loss: 1.3694, avg acc: 60.0000%
2023-06-27 15:37:57.990235  Train: epoch: 34 batch: 0/4, loss: 0.004681
2023-06-27 15:39:24.331682  Validation: avg loss: 1.3740, avg acc: 58.0952%
2023-06-27 15:39:51.540222  Train: epoch: 35 batch: 0/4, loss: 0.002820
2023-06-27 15:41:17.787803  Validation: avg loss: 1.3670, avg acc: 60.0000%
2023-06-27 15:41:44.972450  Train: epoch: 36 batch: 0/4, loss: 0.002842
2023-06-27 15:43:11.465767  Validation: avg loss: 1.3616, avg acc: 60.0000%
2023-06-27 15:43:38.697617  Train: epoch: 37 batch: 0/4, loss: 0.002162
2023-06-27 15:45:05.077605  Validation: avg loss: 1.3509, avg acc: 60.9524%
2023-06-27 15:45:32.325796  Train: epoch: 38 batch: 0/4, loss: 0.003326
2023-06-27 15:46:58.706066  Validation: avg loss: 1.3512, avg acc: 60.9524%
2023-06-27 15:47:25.910792  Train: epoch: 39 batch: 0/4, loss: 0.001938
2023-06-27 15:48:52.278203  Validation: avg loss: 1.3603, avg acc: 59.0476%
2023-06-27 15:49:19.535554  Train: epoch: 40 batch: 0/4, loss: 0.003635
2023-06-27 15:50:45.837145  Validation: avg loss: 1.3606, avg acc: 59.0476%
2023-06-27 15:51:12.981343  Train: epoch: 41 batch: 0/4, loss: 0.005210
2023-06-27 15:52:39.442147  Validation: avg loss: 1.3714, avg acc: 60.9524%
2023-06-27 15:53:06.657741  Train: epoch: 42 batch: 0/4, loss: 0.002000
2023-06-27 15:54:32.994759  Validation: avg loss: 1.3837, avg acc: 60.9524%
2023-06-27 15:55:00.231831  Train: epoch: 43 batch: 0/4, loss: 0.002722
2023-06-27 15:56:26.472286  Validation: avg loss: 1.3989, avg acc: 60.9524%
2023-06-27 15:56:53.745332  Train: epoch: 44 batch: 0/4, loss: 0.001284
2023-06-27 15:58:20.247427  Validation: avg loss: 1.4101, avg acc: 60.9524%
2023-06-27 15:58:47.411493  Train: epoch: 45 batch: 0/4, loss: 0.001307
2023-06-27 16:00:13.673967  Validation: avg loss: 1.4165, avg acc: 62.8571%
2023-06-27 16:00:40.902848  Train: epoch: 46 batch: 0/4, loss: 0.001449
2023-06-27 16:02:07.334373  Validation: avg loss: 1.4139, avg acc: 62.8571%
2023-06-27 16:02:34.513168  Train: epoch: 47 batch: 0/4, loss: 0.000836
2023-06-27 16:04:00.916745  Validation: avg loss: 1.4183, avg acc: 62.8571%
2023-06-27 16:04:28.157483  Train: epoch: 48 batch: 0/4, loss: 0.000725
2023-06-27 16:05:54.661361  Validation: avg loss: 1.4129, avg acc: 62.8571%
2023-06-27 16:06:21.930959  Train: epoch: 49 batch: 0/4, loss: 0.001346
2023-06-27 16:07:48.387457  Validation: avg loss: 1.4078, avg acc: 62.8571%
2023-06-27 16:08:15.553523  Train: epoch: 50 batch: 0/4, loss: 0.001285
2023-06-27 16:09:42.001568  Validation: avg loss: 1.4038, avg acc: 62.8571%