230628021810.log

2023-06-28 02:18:10.191347  cuda
2023-06-28 02:18:24.590105  Train: epoch: 1 batch: 0/4, loss: 0.690249
2023-06-28 02:19:09.969172  Validation: avg loss: 0.6905, avg acc: 58.0952%
2023-06-28 02:19:24.498012  Train: epoch: 2 batch: 0/4, loss: 0.682551
2023-06-28 02:20:12.924872  Validation: avg loss: 0.6843, avg acc: 58.0952%
2023-06-28 02:20:27.411335  Train: epoch: 3 batch: 0/4, loss: 0.691065
2023-06-28 02:21:12.226704  Validation: avg loss: 0.6844, avg acc: 58.0952%
2023-06-28 02:21:26.494891  Train: epoch: 4 batch: 0/4, loss: 0.656486
2023-06-28 02:22:11.201627  Validation: avg loss: 0.6885, avg acc: 58.0952%
2023-06-28 02:22:25.324919  Train: epoch: 5 batch: 0/4, loss: 0.641778
2023-06-28 02:23:10.589578  Validation: avg loss: 0.6955, avg acc: 41.9048%
2023-06-28 02:23:24.986591  Train: epoch: 6 batch: 0/4, loss: 0.635714
2023-06-28 02:24:09.995102  Validation: avg loss: 0.6892, avg acc: 58.0952%
2023-06-28 02:24:24.299061  Train: epoch: 7 batch: 0/4, loss: 0.588812
2023-06-28 02:25:09.383180  Validation: avg loss: 0.7100, avg acc: 41.9048%
2023-06-28 02:25:23.459523  Train: epoch: 8 batch: 0/4, loss: 0.580687
2023-06-28 02:26:08.476721  Validation: avg loss: 0.6989, avg acc: 43.8095%
2023-06-28 02:26:22.636932  Train: epoch: 9 batch: 0/4, loss: 0.538401
2023-06-28 02:27:07.755846  Validation: avg loss: 0.7032, avg acc: 44.7619%
2023-06-28 02:27:22.308433  Train: epoch: 10 batch: 0/4, loss: 0.479063
2023-06-28 02:28:08.023222  Validation: avg loss: 0.7259, avg acc: 43.8095%
2023-06-28 02:28:22.212473  Train: epoch: 11 batch: 0/4, loss: 0.399180
2023-06-28 02:29:07.187142  Validation: avg loss: 0.6419, avg acc: 66.6667%
2023-06-28 02:29:21.459886  Train: epoch: 12 batch: 0/4, loss: 0.374041
2023-06-28 02:30:06.783311  Validation: avg loss: 0.6404, avg acc: 63.8095%
2023-06-28 02:30:20.925891  Train: epoch: 13 batch: 0/4, loss: 0.199607
2023-06-28 02:31:09.303999  Validation: avg loss: 0.6425, avg acc: 64.7619%
2023-06-28 02:31:26.317069  Train: epoch: 14 batch: 0/4, loss: 0.210665
2023-06-28 02:32:14.248001  Validation: avg loss: 0.6495, avg acc: 64.7619%
2023-06-28 02:32:28.770466  Train: epoch: 15 batch: 0/4, loss: 0.094463
2023-06-28 02:33:13.835456  Validation: avg loss: 0.6781, avg acc: 64.7619%
2023-06-28 02:33:28.075316  Train: epoch: 16 batch: 0/4, loss: 0.071825
2023-06-28 02:34:13.056136  Validation: avg loss: 0.6933, avg acc: 66.6667%
2023-06-28 02:34:27.574360  Train: epoch: 17 batch: 0/4, loss: 0.075157
2023-06-28 02:35:12.945181  Validation: avg loss: 0.7505, avg acc: 64.7619%
2023-06-28 02:35:27.190267  Train: epoch: 18 batch: 0/4, loss: 0.035870
2023-06-28 02:36:12.281194  Validation: avg loss: 0.8531, avg acc: 64.7619%
2023-06-28 02:36:26.858452  Train: epoch: 19 batch: 0/4, loss: 0.024990
2023-06-28 02:37:12.890268  Validation: avg loss: 0.9023, avg acc: 64.7619%
2023-06-28 02:37:27.425535  Train: epoch: 20 batch: 0/4, loss: 0.019082
2023-06-28 02:38:12.722207  Validation: avg loss: 0.9582, avg acc: 66.6667%
2023-06-28 02:38:27.265360  Train: epoch: 21 batch: 0/4, loss: 0.010728
2023-06-28 02:39:12.364647  Validation: avg loss: 0.9925, avg acc: 65.7143%
2023-06-28 02:39:26.689739  Train: epoch: 22 batch: 0/4, loss: 0.023405
2023-06-28 02:40:11.877307  Validation: avg loss: 1.0391, avg acc: 63.8095%
2023-06-28 02:40:26.261142  Train: epoch: 23 batch: 0/4, loss: 0.006633
2023-06-28 02:41:11.681557  Validation: avg loss: 1.0852, avg acc: 64.7619%
2023-06-28 02:41:25.847109  Train: epoch: 24 batch: 0/4, loss: 0.015039
2023-06-28 02:42:10.949129  Validation: avg loss: 1.2231, avg acc: 66.6667%
2023-06-28 02:42:25.108043  Train: epoch: 25 batch: 0/4, loss: 0.017307
2023-06-28 02:43:10.040710  Validation: avg loss: 1.1383, avg acc: 62.8571%
2023-06-28 02:43:24.367214  Train: epoch: 26 batch: 0/4, loss: 0.009442
2023-06-28 02:44:10.201937  Validation: avg loss: 1.1565, avg acc: 64.7619%
2023-06-28 02:44:24.655029  Train: epoch: 27 batch: 0/4, loss: 0.008642
2023-06-28 02:45:16.466766  Validation: avg loss: 1.2177, avg acc: 65.7143%
2023-06-28 02:45:34.059083  Train: epoch: 28 batch: 0/4, loss: 0.004727
2023-06-28 02:46:26.336540  Validation: avg loss: 1.2653, avg acc: 63.8095%
2023-06-28 02:46:43.131403  Train: epoch: 29 batch: 0/4, loss: 0.003736
2023-06-28 02:47:36.324387  Validation: avg loss: 1.3018, avg acc: 64.7619%
2023-06-28 02:47:53.401691  Train: epoch: 30 batch: 0/4, loss: 0.004438
2023-06-28 02:48:48.112933  Validation: avg loss: 1.3224, avg acc: 63.8095%
2023-06-28 02:49:05.076562  Train: epoch: 31 batch: 0/4, loss: 0.004074
2023-06-28 02:49:58.477870  Validation: avg loss: 1.3503, avg acc: 62.8571%
2023-06-28 02:50:15.549796  Train: epoch: 32 batch: 0/4, loss: 0.005016
2023-06-28 02:51:08.879135  Validation: avg loss: 1.3151, avg acc: 61.9048%
2023-06-28 02:51:25.677918  Train: epoch: 33 batch: 0/4, loss: 0.002044
2023-06-28 02:52:20.105423  Validation: avg loss: 1.2926, avg acc: 62.8571%
2023-06-28 02:52:37.041849  Train: epoch: 34 batch: 0/4, loss: 0.002703
2023-06-28 02:53:31.706319  Validation: avg loss: 1.2878, avg acc: 63.8095%
2023-06-28 02:53:49.176129  Train: epoch: 35 batch: 0/4, loss: 0.003849
2023-06-28 02:54:42.142647  Validation: avg loss: 1.3129, avg acc: 63.8095%
2023-06-28 02:54:56.427546  Train: epoch: 36 batch: 0/4, loss: 0.001835
2023-06-28 02:55:41.494277  Validation: avg loss: 1.3500, avg acc: 61.9048%
2023-06-28 02:55:55.778091  Train: epoch: 37 batch: 0/4, loss: 0.002286
2023-06-28 02:56:41.046795  Validation: avg loss: 1.3715, avg acc: 62.8571%
2023-06-28 02:56:55.370527  Train: epoch: 38 batch: 0/4, loss: 0.001753
2023-06-28 02:57:40.945144  Validation: avg loss: 1.3863, avg acc: 64.7619%
2023-06-28 02:57:55.244577  Train: epoch: 39 batch: 0/4, loss: 0.001636
2023-06-28 02:58:40.557081  Validation: avg loss: 1.4102, avg acc: 64.7619%
2023-06-28 02:58:54.994770  Train: epoch: 40 batch: 0/4, loss: 0.001649
2023-06-28 02:59:39.954962  Validation: avg loss: 1.4169, avg acc: 63.8095%
2023-06-28 02:59:54.214338  Train: epoch: 41 batch: 0/4, loss: 0.001002
2023-06-28 03:00:39.437733  Validation: avg loss: 1.4182, avg acc: 62.8571%
2023-06-28 03:00:53.650708  Train: epoch: 42 batch: 0/4, loss: 0.001196
2023-06-28 03:01:39.005193  Validation: avg loss: 1.4063, avg acc: 62.8571%
2023-06-28 03:01:53.324523  Train: epoch: 43 batch: 0/4, loss: 0.000889
2023-06-28 03:02:38.746603  Validation: avg loss: 1.4078, avg acc: 63.8095%
2023-06-28 03:02:52.879053  Train: epoch: 44 batch: 0/4, loss: 0.001685
2023-06-28 03:03:37.789140  Validation: avg loss: 1.3901, avg acc: 63.8095%
2023-06-28 03:03:51.837770  Train: epoch: 45 batch: 0/4, loss: 0.001467
2023-06-28 03:04:37.321315  Validation: avg loss: 1.4143, avg acc: 63.8095%
2023-06-28 03:04:51.924517  Train: epoch: 46 batch: 0/4, loss: 0.001200
2023-06-28 03:05:37.733740  Validation: avg loss: 1.4240, avg acc: 63.8095%
2023-06-28 03:05:51.972393  Train: epoch: 47 batch: 0/4, loss: 0.000806
2023-06-28 03:06:39.101561  Validation: avg loss: 1.4204, avg acc: 63.8095%
2023-06-28 03:06:53.373502  Train: epoch: 48 batch: 0/4, loss: 0.000644
2023-06-28 03:07:38.640922  Validation: avg loss: 1.4185, avg acc: 62.8571%
2023-06-28 03:07:53.026508  Train: epoch: 49 batch: 0/4, loss: 0.000653
2023-06-28 03:08:38.046226  Validation: avg loss: 1.3947, avg acc: 62.8571%
2023-06-28 03:08:52.122996  Train: epoch: 50 batch: 0/4, loss: 0.000570
2023-06-28 03:09:37.119446  Validation: avg loss: 1.3931, avg acc: 62.8571%