230628030937.log

2023-06-28 03:09:37.154578  cuda
2023-06-28 03:09:51.449183  Train: epoch: 1 batch: 0/4, loss: 0.693002
2023-06-28 03:10:37.293540  Validation: avg loss: 0.6892, avg acc: 58.0952%
2023-06-28 03:10:51.688451  Train: epoch: 2 batch: 0/4, loss: 0.687561
2023-06-28 03:11:36.852454  Validation: avg loss: 0.6810, avg acc: 58.0952%
2023-06-28 03:11:50.960553  Train: epoch: 3 batch: 0/4, loss: 0.681805
2023-06-28 03:12:36.129192  Validation: avg loss: 0.6913, avg acc: 58.0952%
2023-06-28 03:12:50.476572  Train: epoch: 4 batch: 0/4, loss: 0.665961
2023-06-28 03:13:35.487521  Validation: avg loss: 0.6886, avg acc: 58.0952%
2023-06-28 03:13:49.861003  Train: epoch: 5 batch: 0/4, loss: 0.644194
2023-06-28 03:14:35.147609  Validation: avg loss: 0.6877, avg acc: 58.0952%
2023-06-28 03:14:49.535890  Train: epoch: 6 batch: 0/4, loss: 0.622670
2023-06-28 03:15:34.784671  Validation: avg loss: 0.6870, avg acc: 58.0952%
2023-06-28 03:15:49.337855  Train: epoch: 7 batch: 0/4, loss: 0.599810
2023-06-28 03:16:34.214166  Validation: avg loss: 0.6969, avg acc: 41.9048%
2023-06-28 03:16:48.536066  Train: epoch: 8 batch: 0/4, loss: 0.545521
2023-06-28 03:17:33.960131  Validation: avg loss: 0.6841, avg acc: 55.2381%
2023-06-28 03:17:48.281651  Train: epoch: 9 batch: 0/4, loss: 0.452313
2023-06-28 03:18:33.276105  Validation: avg loss: 0.6612, avg acc: 72.3810%
2023-06-28 03:18:47.585477  Train: epoch: 10 batch: 0/4, loss: 0.390662
2023-06-28 03:19:32.407151  Validation: avg loss: 0.6701, avg acc: 50.4762%
2023-06-28 03:19:46.747612  Train: epoch: 11 batch: 0/4, loss: 0.324581
2023-06-28 03:20:31.709394  Validation: avg loss: 0.5978, avg acc: 67.6190%
2023-06-28 03:20:45.958098  Train: epoch: 12 batch: 0/4, loss: 0.254065
2023-06-28 03:21:31.222952  Validation: avg loss: 0.5616, avg acc: 68.5714%
2023-06-28 03:21:45.962876  Train: epoch: 13 batch: 0/4, loss: 0.200924
2023-06-28 03:22:31.271403  Validation: avg loss: 0.5085, avg acc: 71.4286%
2023-06-28 03:22:45.628448  Train: epoch: 14 batch: 0/4, loss: 0.124987
2023-06-28 03:23:32.817547  Validation: avg loss: 0.4824, avg acc: 75.2381%
2023-06-28 03:23:47.162008  Train: epoch: 15 batch: 0/4, loss: 0.090232
2023-06-28 03:24:32.146921  Validation: avg loss: 0.5138, avg acc: 70.4762%
2023-06-28 03:24:46.642517  Train: epoch: 16 batch: 0/4, loss: 0.083759
2023-06-28 03:25:32.353083  Validation: avg loss: 0.5420, avg acc: 69.5238%
2023-06-28 03:25:47.131522  Train: epoch: 17 batch: 0/4, loss: 0.066651
2023-06-28 03:26:32.781357  Validation: avg loss: 0.5527, avg acc: 73.3333%
2023-06-28 03:26:47.379127  Train: epoch: 18 batch: 0/4, loss: 0.024152
2023-06-28 03:27:33.147812  Validation: avg loss: 0.5908, avg acc: 71.4286%
2023-06-28 03:27:47.568344  Train: epoch: 19 batch: 0/4, loss: 0.017142
2023-06-28 03:28:33.092234  Validation: avg loss: 0.5997, avg acc: 70.4762%
2023-06-28 03:28:47.603911  Train: epoch: 20 batch: 0/4, loss: 0.012679
2023-06-28 03:29:33.533011  Validation: avg loss: 0.6142, avg acc: 76.1905%
2023-06-28 03:29:48.120699  Train: epoch: 21 batch: 0/4, loss: 0.019406
2023-06-28 03:30:33.497260  Validation: avg loss: 0.6960, avg acc: 74.2857%
2023-06-28 03:30:47.796580  Train: epoch: 22 batch: 0/4, loss: 0.023462
2023-06-28 03:31:32.909514  Validation: avg loss: 0.7432, avg acc: 73.3333%
2023-06-28 03:31:47.165250  Train: epoch: 23 batch: 0/4, loss: 0.010763
2023-06-28 03:32:31.899234  Validation: avg loss: 0.7907, avg acc: 72.3810%
2023-06-28 03:32:46.438450  Train: epoch: 24 batch: 0/4, loss: 0.013663
2023-06-28 03:33:31.940938  Validation: avg loss: 0.7950, avg acc: 68.5714%
2023-06-28 03:33:46.516226  Train: epoch: 25 batch: 0/4, loss: 0.006725
2023-06-28 03:34:32.670997  Validation: avg loss: 0.8249, avg acc: 69.5238%
2023-06-28 03:34:47.337794  Train: epoch: 26 batch: 0/4, loss: 0.004846
2023-06-28 03:35:33.504480  Validation: avg loss: 0.8479, avg acc: 72.3810%
2023-06-28 03:35:47.772504  Train: epoch: 27 batch: 0/4, loss: 0.005277
2023-06-28 03:36:32.575498  Validation: avg loss: 0.8493, avg acc: 72.3810%
2023-06-28 03:36:46.665919  Train: epoch: 28 batch: 0/4, loss: 0.011446
2023-06-28 03:37:31.196006  Validation: avg loss: 0.8339, avg acc: 71.4286%
2023-06-28 03:37:45.377302  Train: epoch: 29 batch: 0/4, loss: 0.003922
2023-06-28 03:38:30.580648  Validation: avg loss: 0.8505, avg acc: 72.3810%
2023-06-28 03:38:44.775296  Train: epoch: 30 batch: 0/4, loss: 0.002529
2023-06-28 03:39:29.493308  Validation: avg loss: 0.8773, avg acc: 71.4286%
2023-06-28 03:39:43.608244  Train: epoch: 31 batch: 0/4, loss: 0.001875
2023-06-28 03:40:28.207967  Validation: avg loss: 0.8870, avg acc: 70.4762%
2023-06-28 03:40:42.352605  Train: epoch: 32 batch: 0/4, loss: 0.002372
2023-06-28 03:41:27.482733  Validation: avg loss: 0.8911, avg acc: 72.3810%
2023-06-28 03:41:41.670935  Train: epoch: 33 batch: 0/4, loss: 0.003411
2023-06-28 03:42:26.716992  Validation: avg loss: 0.8858, avg acc: 72.3810%
2023-06-28 03:42:41.008464  Train: epoch: 34 batch: 0/4, loss: 0.002562
2023-06-28 03:43:26.039612  Validation: avg loss: 0.8796, avg acc: 72.3810%
2023-06-28 03:43:40.260189  Train: epoch: 35 batch: 0/4, loss: 0.003069
2023-06-28 03:44:25.722423  Validation: avg loss: 0.8868, avg acc: 72.3810%
2023-06-28 03:44:39.923484  Train: epoch: 36 batch: 0/4, loss: 0.001231
2023-06-28 03:45:25.127050  Validation: avg loss: 0.8910, avg acc: 73.3333%
2023-06-28 03:45:39.527841  Train: epoch: 37 batch: 0/4, loss: 0.001668
2023-06-28 03:46:24.319152  Validation: avg loss: 0.8928, avg acc: 73.3333%
2023-06-28 03:46:38.520530  Train: epoch: 38 batch: 0/4, loss: 0.001577
2023-06-28 03:47:23.353992  Validation: avg loss: 0.8915, avg acc: 73.3333%
2023-06-28 03:47:37.434393  Train: epoch: 39 batch: 0/4, loss: 0.001705
2023-06-28 03:48:22.834245  Validation: avg loss: 0.8936, avg acc: 73.3333%
2023-06-28 03:48:37.254894  Train: epoch: 40 batch: 0/4, loss: 0.001388
2023-06-28 03:49:22.471289  Validation: avg loss: 0.9009, avg acc: 73.3333%
2023-06-28 03:49:36.564547  Train: epoch: 41 batch: 0/4, loss: 0.000861
2023-06-28 03:50:21.412126  Validation: avg loss: 0.9012, avg acc: 74.2857%
2023-06-28 03:50:35.489009  Train: epoch: 42 batch: 0/4, loss: 0.001102
2023-06-28 03:51:20.143782  Validation: avg loss: 0.9065, avg acc: 74.2857%
2023-06-28 03:51:34.559930  Train: epoch: 43 batch: 0/4, loss: 0.000969
2023-06-28 03:52:19.340878  Validation: avg loss: 0.9071, avg acc: 74.2857%
2023-06-28 03:52:33.401578  Train: epoch: 44 batch: 0/4, loss: 0.000865
2023-06-28 03:53:18.033301  Validation: avg loss: 0.9177, avg acc: 73.3333%
2023-06-28 03:53:32.150168  Train: epoch: 45 batch: 0/4, loss: 0.000941
2023-06-28 03:54:17.146896  Validation: avg loss: 0.9327, avg acc: 74.2857%
2023-06-28 03:54:31.352235  Train: epoch: 46 batch: 0/4, loss: 0.000957
2023-06-28 03:55:17.407628  Validation: avg loss: 0.9416, avg acc: 74.2857%
2023-06-28 03:55:31.626750  Train: epoch: 47 batch: 0/4, loss: 0.000746
2023-06-28 03:56:16.058637  Validation: avg loss: 0.9409, avg acc: 74.2857%
2023-06-28 03:56:30.100803  Train: epoch: 48 batch: 0/4, loss: 0.001412
2023-06-28 03:57:14.611239  Validation: avg loss: 0.9413, avg acc: 73.3333%
2023-06-28 03:57:28.762473  Train: epoch: 49 batch: 0/4, loss: 0.000834
2023-06-28 03:58:13.474519  Validation: avg loss: 0.9323, avg acc: 75.2381%
2023-06-28 03:58:27.820951  Train: epoch: 50 batch: 0/4, loss: 0.000935
2023-06-28 03:59:12.546035  Validation: avg loss: 0.9237, avg acc: 74.2857%