230628031141.log

2023-06-28 03:11:41.369838  cuda
2023-06-28 03:12:08.489829  Train: epoch: 1 batch: 0/4, loss: 0.693009
2023-06-28 03:13:35.046750  Validation: avg loss: 0.6857, avg acc: 59.0476%
2023-06-28 03:14:02.248611  Train: epoch: 2 batch: 0/4, loss: 0.660941
2023-06-28 03:15:28.672696  Validation: avg loss: 0.6814, avg acc: 59.0476%
2023-06-28 03:15:55.889171  Train: epoch: 3 batch: 0/4, loss: 0.677196
2023-06-28 03:17:22.246065  Validation: avg loss: 0.6786, avg acc: 59.0476%
2023-06-28 03:17:49.559499  Train: epoch: 4 batch: 0/4, loss: 0.658742
2023-06-28 03:19:15.996798  Validation: avg loss: 0.6773, avg acc: 59.0476%
2023-06-28 03:19:43.304110  Train: epoch: 5 batch: 0/4, loss: 0.639081
2023-06-28 03:21:09.730463  Validation: avg loss: 0.6766, avg acc: 59.0476%
2023-06-28 03:21:36.976033  Train: epoch: 6 batch: 0/4, loss: 0.644215
2023-06-28 03:23:03.375505  Validation: avg loss: 0.6785, avg acc: 59.0476%
2023-06-28 03:23:30.700397  Train: epoch: 7 batch: 0/4, loss: 0.589882
2023-06-28 03:24:57.368440  Validation: avg loss: 0.6840, avg acc: 59.0476%
2023-06-28 03:25:24.609371  Train: epoch: 8 batch: 0/4, loss: 0.598612
2023-06-28 03:26:51.153481  Validation: avg loss: 0.6744, avg acc: 59.0476%
2023-06-28 03:27:18.453132  Train: epoch: 9 batch: 0/4, loss: 0.535064
2023-06-28 03:28:45.049005  Validation: avg loss: 0.6742, avg acc: 59.0476%
2023-06-28 03:29:12.429540  Train: epoch: 10 batch: 0/4, loss: 0.445725
2023-06-28 03:30:39.157958  Validation: avg loss: 0.6635, avg acc: 59.0476%
2023-06-28 03:31:06.510547  Train: epoch: 11 batch: 0/4, loss: 0.404390
2023-06-28 03:32:33.136095  Validation: avg loss: 0.6513, avg acc: 60.9524%
2023-06-28 03:33:00.548645  Train: epoch: 12 batch: 0/4, loss: 0.299564
2023-06-28 03:34:27.188458  Validation: avg loss: 0.6300, avg acc: 66.6667%
2023-06-28 03:34:54.497327  Train: epoch: 13 batch: 0/4, loss: 0.214730
2023-06-28 03:36:20.982842  Validation: avg loss: 0.5986, avg acc: 70.4762%
2023-06-28 03:36:48.279724  Train: epoch: 14 batch: 0/4, loss: 0.139650
2023-06-28 03:38:14.780257  Validation: avg loss: 0.5917, avg acc: 70.4762%
2023-06-28 03:38:42.185034  Train: epoch: 15 batch: 0/4, loss: 0.095805
2023-06-28 03:40:08.762359  Validation: avg loss: 0.6035, avg acc: 70.4762%
2023-06-28 03:40:36.014349  Train: epoch: 16 batch: 0/4, loss: 0.117713
2023-06-28 03:42:02.806398  Validation: avg loss: 0.6005, avg acc: 74.2857%
2023-06-28 03:42:30.083217  Train: epoch: 17 batch: 0/4, loss: 0.053618
2023-06-28 03:43:56.560993  Validation: avg loss: 0.6274, avg acc: 73.3333%
2023-06-28 03:44:23.921173  Train: epoch: 18 batch: 0/4, loss: 0.031614
2023-06-28 03:45:50.567906  Validation: avg loss: 0.6853, avg acc: 73.3333%
2023-06-28 03:46:17.900417  Train: epoch: 19 batch: 0/4, loss: 0.020584
2023-06-28 03:47:44.369591  Validation: avg loss: 0.7224, avg acc: 74.2857%
2023-06-28 03:48:11.683537  Train: epoch: 20 batch: 0/4, loss: 0.016825
2023-06-28 03:49:38.121020  Validation: avg loss: 0.7518, avg acc: 77.1429%
2023-06-28 03:50:05.533161  Train: epoch: 21 batch: 0/4, loss: 0.025432
2023-06-28 03:51:32.061008  Validation: avg loss: 0.7888, avg acc: 75.2381%
2023-06-28 03:51:59.383920  Train: epoch: 22 batch: 0/4, loss: 0.043029
2023-06-28 03:53:25.981256  Validation: avg loss: 0.8037, avg acc: 74.2857%
2023-06-28 03:53:53.353953  Train: epoch: 23 batch: 0/4, loss: 0.008785
2023-06-28 03:55:19.878661  Validation: avg loss: 0.8034, avg acc: 73.3333%
2023-06-28 03:55:47.181928  Train: epoch: 24 batch: 0/4, loss: 0.005627
2023-06-28 03:57:13.741347  Validation: avg loss: 0.8422, avg acc: 75.2381%
2023-06-28 03:57:41.055459  Train: epoch: 25 batch: 0/4, loss: 0.011560
2023-06-28 03:59:07.539045  Validation: avg loss: 0.8324, avg acc: 74.2857%
2023-06-28 03:59:34.906505  Train: epoch: 26 batch: 0/4, loss: 0.005340
2023-06-28 04:01:01.156838  Validation: avg loss: 0.8390, avg acc: 74.2857%
2023-06-28 04:01:28.310528  Train: epoch: 27 batch: 0/4, loss: 0.003994
2023-06-28 04:02:54.549754  Validation: avg loss: 0.8549, avg acc: 76.1905%
2023-06-28 04:03:21.745650  Train: epoch: 28 batch: 0/4, loss: 0.004037
2023-06-28 04:04:47.978870  Validation: avg loss: 0.9414, avg acc: 75.2381%
2023-06-28 04:05:15.077678  Train: epoch: 29 batch: 0/4, loss: 0.003525
2023-06-28 04:06:41.253870  Validation: avg loss: 0.7540, avg acc: 76.1905%
2023-06-28 04:07:08.447299  Train: epoch: 30 batch: 0/4, loss: 0.010938
2023-06-28 04:08:34.678209  Validation: avg loss: 0.7487, avg acc: 75.2381%
2023-06-28 04:09:01.850756  Train: epoch: 31 batch: 0/4, loss: 0.008799
2023-06-28 04:10:27.965042  Validation: avg loss: 0.7571, avg acc: 76.1905%
2023-06-28 04:10:55.161585  Train: epoch: 32 batch: 0/4, loss: 0.009438
2023-06-28 04:12:21.369456  Validation: avg loss: 0.8214, avg acc: 78.0952%
2023-06-28 04:12:48.557866  Train: epoch: 33 batch: 0/4, loss: 0.010469
2023-06-28 04:14:14.817327  Validation: avg loss: 0.7763, avg acc: 80.0000%
2023-06-28 04:14:42.017780  Train: epoch: 34 batch: 0/4, loss: 0.010956
2023-06-28 04:16:08.324725  Validation: avg loss: 0.7527, avg acc: 77.1429%
2023-06-28 04:16:35.565484  Train: epoch: 35 batch: 0/4, loss: 0.004107
2023-06-28 04:18:01.747081  Validation: avg loss: 0.7567, avg acc: 78.0952%
2023-06-28 04:18:29.006570  Train: epoch: 36 batch: 0/4, loss: 0.005303
2023-06-28 04:19:55.293630  Validation: avg loss: 0.7849, avg acc: 78.0952%
2023-06-28 04:20:22.566884  Train: epoch: 37 batch: 0/4, loss: 0.004355
2023-06-28 04:21:48.913328  Validation: avg loss: 0.8529, avg acc: 74.2857%
2023-06-28 04:22:16.123283  Train: epoch: 38 batch: 0/4, loss: 0.002653
2023-06-28 04:23:42.314617  Validation: avg loss: 0.9147, avg acc: 72.3810%
2023-06-28 04:24:09.540944  Train: epoch: 39 batch: 0/4, loss: 0.003798
2023-06-28 04:25:35.801392  Validation: avg loss: 0.9432, avg acc: 73.3333%
2023-06-28 04:26:03.093014  Train: epoch: 40 batch: 0/4, loss: 0.004928
2023-06-28 04:27:29.335487  Validation: avg loss: 0.9504, avg acc: 74.2857%
2023-06-28 04:27:56.595927  Train: epoch: 41 batch: 0/4, loss: 0.003297
2023-06-28 04:29:22.829464  Validation: avg loss: 0.9514, avg acc: 74.2857%
2023-06-28 04:29:50.060556  Train: epoch: 42 batch: 0/4, loss: 0.008558
2023-06-28 04:31:16.227639  Validation: avg loss: 0.9680, avg acc: 75.2381%
2023-06-28 04:31:43.403653  Train: epoch: 43 batch: 0/4, loss: 0.003308
2023-06-28 04:33:09.493717  Validation: avg loss: 0.9591, avg acc: 75.2381%
2023-06-28 04:33:36.739152  Train: epoch: 44 batch: 0/4, loss: 0.001741
2023-06-28 04:35:02.790738  Validation: avg loss: 0.9662, avg acc: 76.1905%
2023-06-28 04:35:30.000194  Train: epoch: 45 batch: 0/4, loss: 0.005446
2023-06-28 04:36:56.137687  Validation: avg loss: 0.9592, avg acc: 77.1429%
2023-06-28 04:37:23.365801  Train: epoch: 46 batch: 0/4, loss: 0.001942
2023-06-28 04:38:49.522040  Validation: avg loss: 0.9543, avg acc: 76.1905%
2023-06-28 04:39:16.764699  Train: epoch: 47 batch: 0/4, loss: 0.001761
2023-06-28 04:40:42.896181  Validation: avg loss: 0.9601, avg acc: 75.2381%
2023-06-28 04:41:10.053471  Train: epoch: 48 batch: 0/4, loss: 0.003969
2023-06-28 04:42:36.352263  Validation: avg loss: 0.9548, avg acc: 76.1905%
2023-06-28 04:43:03.630201  Train: epoch: 49 batch: 0/4, loss: 0.000910
2023-06-28 04:44:29.912814  Validation: avg loss: 0.9550, avg acc: 75.2381%
2023-06-28 04:44:57.209325  Train: epoch: 50 batch: 0/4, loss: 0.002676
2023-06-28 04:46:23.407038  Validation: avg loss: 0.9544, avg acc: 78.0952%