2023-06-28 07:54:20.219034  cuda
2023-06-28 07:54:47.323627  Train: epoch: 1 batch: 0/4, loss: 0.692011
2023-06-28 07:56:13.040178  Validation: avg loss: 0.6885, avg acc: 58.0952%
2023-06-28 07:56:40.122822  Train: epoch: 2 batch: 0/4, loss: 0.702609
2023-06-28 07:58:05.821483  Validation: avg loss: 0.6800, avg acc: 58.0952%
2023-06-28 07:58:32.914604  Train: epoch: 3 batch: 0/4, loss: 0.672602
2023-06-28 07:59:58.593179  Validation: avg loss: 0.6867, avg acc: 58.0952%
2023-06-28 08:00:25.746637  Train: epoch: 4 batch: 0/4, loss: 0.685599
2023-06-28 08:01:51.502271  Validation: avg loss: 0.6925, avg acc: 58.0952%
2023-06-28 08:02:18.553333  Train: epoch: 5 batch: 0/4, loss: 0.657828
2023-06-28 08:03:44.253610  Validation: avg loss: 0.7163, avg acc: 58.0952%
2023-06-28 08:04:11.348557  Train: epoch: 6 batch: 0/4, loss: 0.654859
2023-06-28 08:05:37.074056  Validation: avg loss: 0.7808, avg acc: 58.0952%
2023-06-28 08:06:04.181792  Train: epoch: 7 batch: 0/4, loss: 0.598809
2023-06-28 08:07:29.794384  Validation: avg loss: 0.8542, avg acc: 58.0952%
2023-06-28 08:07:56.910271  Train: epoch: 8 batch: 0/4, loss: 0.550983
2023-06-28 08:09:22.715247  Validation: avg loss: 0.9253, avg acc: 58.0952%
2023-06-28 08:09:49.823062  Train: epoch: 9 batch: 0/4, loss: 0.517771
2023-06-28 08:11:15.500013  Validation: avg loss: 1.0595, avg acc: 58.0952%
2023-06-28 08:11:42.652989  Train: epoch: 10 batch: 0/4, loss: 0.420894
2023-06-28 08:13:08.239842  Validation: avg loss: 1.1794, avg acc: 58.0952%
2023-06-28 08:13:35.331913  Train: epoch: 11 batch: 0/4, loss: 0.390708
2023-06-28 08:15:01.095686  Validation: avg loss: 1.2828, avg acc: 58.0952%
2023-06-28 08:15:28.156232  Train: epoch: 12 batch: 0/4, loss: 0.231362
2023-06-28 08:16:53.950080  Validation: avg loss: 1.1883, avg acc: 57.1429%
2023-06-28 08:17:21.026497  Train: epoch: 13 batch: 0/4, loss: 0.189501
2023-06-28 08:18:46.792051  Validation: avg loss: 1.0645, avg acc: 58.0952%
2023-06-28 08:19:13.901087  Train: epoch: 14 batch: 0/4, loss: 0.130682
2023-06-28 08:20:39.635420  Validation: avg loss: 1.0291, avg acc: 60.0000%
2023-06-28 08:21:06.671067  Train: epoch: 15 batch: 0/4, loss: 0.077287
2023-06-28 08:22:32.381361  Validation: avg loss: 1.0741, avg acc: 58.0952%
2023-06-28 08:22:59.471764  Train: epoch: 16 batch: 0/4, loss: 0.081006
2023-06-28 08:24:25.295718  Validation: avg loss: 0.9612, avg acc: 60.0000%
2023-06-28 08:24:52.401168  Train: epoch: 17 batch: 0/4, loss: 0.029166
2023-06-28 08:26:18.141239  Validation: avg loss: 0.9213, avg acc: 63.8095%
2023-06-28 08:26:45.228603  Train: epoch: 18 batch: 0/4, loss: 0.044118
2023-06-28 08:28:10.966862  Validation: avg loss: 0.9131, avg acc: 64.7619%
2023-06-28 08:28:38.049080  Train: epoch: 19 batch: 0/4, loss: 0.019182
2023-06-28 08:30:03.801301  Validation: avg loss: 0.9653, avg acc: 64.7619%
2023-06-28 08:30:30.984530  Train: epoch: 20 batch: 0/4, loss: 0.013524
2023-06-28 08:31:57.261869  Validation: avg loss: 1.0524, avg acc: 62.8571%
2023-06-28 08:32:24.455277  Train: epoch: 21 batch: 0/4, loss: 0.009294
2023-06-28 08:33:50.701421  Validation: avg loss: 1.1149, avg acc: 62.8571%
2023-06-28 08:34:17.907725  Train: epoch: 22 batch: 0/4, loss: 0.018284
2023-06-28 08:35:44.043447  Validation: avg loss: 1.1322, avg acc: 61.9048%
2023-06-28 08:36:11.277808  Train: epoch: 23 batch: 0/4, loss: 0.006030
2023-06-28 08:37:37.472454  Validation: avg loss: 1.1997, avg acc: 60.0000%
2023-06-28 08:38:04.659598  Train: epoch: 24 batch: 0/4, loss: 0.006223
2023-06-28 08:39:30.832079  Validation: avg loss: 1.3104, avg acc: 60.0000%
2023-06-28 08:39:58.095516  Train: epoch: 25 batch: 0/4, loss: 0.004612
2023-06-28 08:41:24.255853  Validation: avg loss: 1.3862, avg acc: 61.9048%
2023-06-28 08:41:51.480207  Train: epoch: 26 batch: 0/4, loss: 0.008557
2023-06-28 08:43:17.613646  Validation: avg loss: 1.2588, avg acc: 65.7143%
2023-06-28 08:43:44.926389  Train: epoch: 27 batch: 0/4, loss: 0.004575
2023-06-28 08:45:11.144766  Validation: avg loss: 1.2543, avg acc: 67.6190%
2023-06-28 08:45:38.375967  Train: epoch: 28 batch: 0/4, loss: 0.015793
2023-06-28 08:47:04.518903  Validation: avg loss: 1.2829, avg acc: 64.7619%
2023-06-28 08:47:31.768712  Train: epoch: 29 batch: 0/4, loss: 0.004682
2023-06-28 08:48:57.967912  Validation: avg loss: 1.2949, avg acc: 61.9048%
2023-06-28 08:49:25.148991  Train: epoch: 30 batch: 0/4, loss: 0.005337
2023-06-28 08:50:51.379151  Validation: avg loss: 1.3249, avg acc: 60.9524%
2023-06-28 08:51:18.575106  Train: epoch: 31 batch: 0/4, loss: 0.004917
2023-06-28 08:52:44.716013  Validation: avg loss: 1.3321, avg acc: 60.0000%
2023-06-28 08:53:11.941541  Train: epoch: 32 batch: 0/4, loss: 0.001858
2023-06-28 08:54:38.113950  Validation: avg loss: 1.3518, avg acc: 59.0476%
2023-06-28 08:55:05.368780  Train: epoch: 33 batch: 0/4, loss: 0.004981
2023-06-28 08:56:31.534083  Validation: avg loss: 1.3334, avg acc: 59.0476%
2023-06-28 08:56:58.736317  Train: epoch: 34 batch: 0/4, loss: 0.001875
2023-06-28 08:58:24.921176  Validation: avg loss: 1.3402, avg acc: 60.0000%
2023-06-28 08:58:52.217676  Train: epoch: 35 batch: 0/4, loss: 0.001703
2023-06-28 09:00:18.351915  Validation: avg loss: 1.3444, avg acc: 60.9524%
2023-06-28 09:00:45.580462  Train: epoch: 36 batch: 0/4, loss: 0.002229
2023-06-28 09:02:11.684169  Validation: avg loss: 1.3526, avg acc: 64.7619%
2023-06-28 09:02:38.904778  Train: epoch: 37 batch: 0/4, loss: 0.001279
2023-06-28 09:04:05.204570  Validation: avg loss: 1.3614, avg acc: 64.7619%
2023-06-28 09:04:32.417097  Train: epoch: 38 batch: 0/4, loss: 0.000850
2023-06-28 09:05:58.589090  Validation: avg loss: 1.3760, avg acc: 64.7619%
2023-06-28 09:06:25.828678  Train: epoch: 39 batch: 0/4, loss: 0.001662
2023-06-28 09:07:52.148092  Validation: avg loss: 1.3815, avg acc: 64.7619%
2023-06-28 09:08:19.406891  Train: epoch: 40 batch: 0/4, loss: 0.001392
2023-06-28 09:09:45.619191  Validation: avg loss: 1.3960, avg acc: 63.8095%
2023-06-28 09:10:12.860133  Train: epoch: 41 batch: 0/4, loss: 0.002310
2023-06-28 09:11:39.072431  Validation: avg loss: 1.4089, avg acc: 63.8095%
2023-06-28 09:12:06.351316  Train: epoch: 42 batch: 0/4, loss: 0.000786
2023-06-28 09:13:32.427274  Validation: avg loss: 1.4184, avg acc: 62.8571%
2023-06-28 09:13:59.661877  Train: epoch: 43 batch: 0/4, loss: 0.001685
2023-06-28 09:15:25.888399  Validation: avg loss: 1.4266, avg acc: 61.9048%
2023-06-28 09:15:53.171462  Train: epoch: 44 batch: 0/4, loss: 0.001640
2023-06-28 09:17:19.262170  Validation: avg loss: 1.4425, avg acc: 60.9524%
2023-06-28 09:17:46.526654  Train: epoch: 45 batch: 0/4, loss: 0.001274
2023-06-28 09:19:12.704281  Validation: avg loss: 1.4459, avg acc: 61.9048%
2023-06-28 09:19:39.967872  Train: epoch: 46 batch: 0/4, loss: 0.001791
2023-06-28 09:21:06.099777  Validation: avg loss: 1.4501, avg acc: 62.8571%
2023-06-28 09:21:33.314902  Train: epoch: 47 batch: 0/4, loss: 0.000593
2023-06-28 09:22:59.414822  Validation: avg loss: 1.4475, avg acc: 62.8571%
2023-06-28 09:23:26.633884  Train: epoch: 48 batch: 0/4, loss: 0.000778
2023-06-28 09:24:52.704704  Validation: avg loss: 1.4512, avg acc: 62.8571%
2023-06-28 09:25:19.932972  Train: epoch: 49 batch: 0/4, loss: 0.001332
2023-06-28 09:26:45.943631  Validation: avg loss: 1.4538, avg acc: 63.8095%
2023-06-28 09:27:13.207584  Train: epoch: 50 batch: 0/4, loss: 0.000809
2023-06-28 09:28:39.203569  Validation: avg loss: 1.4621, avg acc: 62.8571%