230628062032.log

2023-06-28 06:20:32.807694  cuda
2023-06-28 06:20:59.782142  Train: epoch: 1 batch: 0/4, loss: 0.694550
2023-06-28 06:22:25.049478  Validation: avg loss: 0.6866, avg acc: 58.0952%
2023-06-28 06:22:52.116647  Train: epoch: 2 batch: 0/4, loss: 0.685724
2023-06-28 06:24:17.492254  Validation: avg loss: 0.6806, avg acc: 58.0952%
2023-06-28 06:24:44.453486  Train: epoch: 3 batch: 0/4, loss: 0.669736
2023-06-28 06:26:09.939638  Validation: avg loss: 0.6800, avg acc: 58.0952%
2023-06-28 06:26:36.896435  Train: epoch: 4 batch: 0/4, loss: 0.655506
2023-06-28 06:28:02.373578  Validation: avg loss: 0.6801, avg acc: 58.0952%
2023-06-28 06:28:29.347816  Train: epoch: 5 batch: 0/4, loss: 0.642335
2023-06-28 06:29:55.096662  Validation: avg loss: 0.6809, avg acc: 58.0952%
2023-06-28 06:30:22.022250  Train: epoch: 6 batch: 0/4, loss: 0.609017
2023-06-28 06:31:47.601279  Validation: avg loss: 0.7002, avg acc: 58.0952%
2023-06-28 06:32:14.527985  Train: epoch: 7 batch: 0/4, loss: 0.583523
2023-06-28 06:33:40.148794  Validation: avg loss: 0.7076, avg acc: 58.0952%
2023-06-28 06:34:07.127858  Train: epoch: 8 batch: 0/4, loss: 0.529180
2023-06-28 06:35:32.700097  Validation: avg loss: 0.7478, avg acc: 58.0952%
2023-06-28 06:35:59.623205  Train: epoch: 9 batch: 0/4, loss: 0.425682
2023-06-28 06:37:25.177061  Validation: avg loss: 0.7770, avg acc: 58.0952%
2023-06-28 06:37:52.113537  Train: epoch: 10 batch: 0/4, loss: 0.342322
2023-06-28 06:39:17.709448  Validation: avg loss: 0.7617, avg acc: 58.0952%
2023-06-28 06:39:44.628067  Train: epoch: 11 batch: 0/4, loss: 0.290511
2023-06-28 06:41:10.138916  Validation: avg loss: 0.8174, avg acc: 58.0952%
2023-06-28 06:41:37.108045  Train: epoch: 12 batch: 0/4, loss: 0.171858
2023-06-28 06:43:02.531802  Validation: avg loss: 0.8176, avg acc: 59.0476%
2023-06-28 06:43:29.627408  Train: epoch: 13 batch: 0/4, loss: 0.111138
2023-06-28 06:44:55.170555  Validation: avg loss: 0.8509, avg acc: 60.9524%
2023-06-28 06:45:22.075733  Train: epoch: 14 batch: 0/4, loss: 0.138503
2023-06-28 06:46:47.720079  Validation: avg loss: 0.9241, avg acc: 60.0000%
2023-06-28 06:47:14.663116  Train: epoch: 15 batch: 0/4, loss: 0.098214
2023-06-28 06:48:40.200009  Validation: avg loss: 1.0118, avg acc: 57.1429%
2023-06-28 06:49:07.133194  Train: epoch: 16 batch: 0/4, loss: 0.033119
2023-06-28 06:50:32.840044  Validation: avg loss: 1.0273, avg acc: 58.0952%
2023-06-28 06:50:59.829902  Train: epoch: 17 batch: 0/4, loss: 0.025033
2023-06-28 06:52:25.411567  Validation: avg loss: 0.9969, avg acc: 60.9524%
2023-06-28 06:52:52.437438  Train: epoch: 18 batch: 0/4, loss: 0.017611
2023-06-28 06:54:18.105632  Validation: avg loss: 1.0427, avg acc: 67.6190%
2023-06-28 06:54:45.045750  Train: epoch: 19 batch: 0/4, loss: 0.019366
2023-06-28 06:56:10.681727  Validation: avg loss: 1.1259, avg acc: 63.8095%
2023-06-28 06:56:37.647528  Train: epoch: 20 batch: 0/4, loss: 0.010691
2023-06-28 06:58:03.195921  Validation: avg loss: 1.1928, avg acc: 66.6667%
2023-06-28 06:58:30.262874  Train: epoch: 21 batch: 0/4, loss: 0.014434
2023-06-28 06:59:55.963174  Validation: avg loss: 1.3022, avg acc: 64.7619%
2023-06-28 07:00:22.841666  Train: epoch: 22 batch: 0/4, loss: 0.006267
2023-06-28 07:01:48.442826  Validation: avg loss: 1.3515, avg acc: 62.8571%
2023-06-28 07:02:15.367444  Train: epoch: 23 batch: 0/4, loss: 0.006865
2023-06-28 07:03:40.894921  Validation: avg loss: 1.4161, avg acc: 61.9048%
2023-06-28 07:04:07.865326  Train: epoch: 24 batch: 0/4, loss: 0.005643
2023-06-28 07:05:33.452678  Validation: avg loss: 1.4647, avg acc: 61.9048%
2023-06-28 07:06:00.370655  Train: epoch: 25 batch: 0/4, loss: 0.003030
2023-06-28 07:07:25.879245  Validation: avg loss: 1.4783, avg acc: 64.7619%
2023-06-28 07:07:52.804435  Train: epoch: 26 batch: 0/4, loss: 0.002921
2023-06-28 07:09:18.368758  Validation: avg loss: 1.4957, avg acc: 64.7619%
2023-06-28 07:09:45.317592  Train: epoch: 27 batch: 0/4, loss: 0.002734
2023-06-28 07:11:10.909994  Validation: avg loss: 1.5322, avg acc: 62.8571%
2023-06-28 07:11:37.819938  Train: epoch: 28 batch: 0/4, loss: 0.003040
2023-06-28 07:13:03.543262  Validation: avg loss: 1.5551, avg acc: 61.9048%
2023-06-28 07:13:30.460248  Train: epoch: 29 batch: 0/4, loss: 0.008279
2023-06-28 07:14:55.920791  Validation: avg loss: 1.5932, avg acc: 60.0000%
2023-06-28 07:15:22.995582  Train: epoch: 30 batch: 0/4, loss: 0.001801
2023-06-28 07:16:48.598348  Validation: avg loss: 1.6062, avg acc: 60.0000%
2023-06-28 07:17:15.506477  Train: epoch: 31 batch: 0/4, loss: 0.003024
2023-06-28 07:18:41.037291  Validation: avg loss: 1.6190, avg acc: 59.0476%
2023-06-28 07:19:07.949540  Train: epoch: 32 batch: 0/4, loss: 0.001501
2023-06-28 07:20:33.640949  Validation: avg loss: 1.6265, avg acc: 59.0476%
2023-06-28 07:21:00.609931  Train: epoch: 33 batch: 0/4, loss: 0.001911
2023-06-28 07:22:26.299209  Validation: avg loss: 1.6330, avg acc: 59.0476%
2023-06-28 07:22:53.210851  Train: epoch: 34 batch: 0/4, loss: 0.005427
2023-06-28 07:24:18.718027  Validation: avg loss: 1.6348, avg acc: 59.0476%
2023-06-28 07:24:45.721371  Train: epoch: 35 batch: 0/4, loss: 0.001198
2023-06-28 07:26:11.348694  Validation: avg loss: 1.6311, avg acc: 59.0476%
2023-06-28 07:26:38.300474  Train: epoch: 36 batch: 0/4, loss: 0.001599
2023-06-28 07:28:03.959383  Validation: avg loss: 1.6419, avg acc: 60.9524%
2023-06-28 07:28:30.974336  Train: epoch: 37 batch: 0/4, loss: 0.001617
2023-06-28 07:29:56.486126  Validation: avg loss: 1.6435, avg acc: 60.9524%
2023-06-28 07:30:23.406303  Train: epoch: 38 batch: 0/4, loss: 0.001469
2023-06-28 07:31:49.062440  Validation: avg loss: 1.6537, avg acc: 60.9524%
2023-06-28 07:32:16.043402  Train: epoch: 39 batch: 0/4, loss: 0.001683
2023-06-28 07:33:41.521465  Validation: avg loss: 1.6615, avg acc: 61.9048%
2023-06-28 07:34:08.515651  Train: epoch: 40 batch: 0/4, loss: 0.001262
2023-06-28 07:35:34.061409  Validation: avg loss: 1.6703, avg acc: 61.9048%
2023-06-28 07:36:00.991426  Train: epoch: 41 batch: 0/4, loss: 0.001093
2023-06-28 07:37:26.675227  Validation: avg loss: 1.6685, avg acc: 61.9048%
2023-06-28 07:37:53.578362  Train: epoch: 42 batch: 0/4, loss: 0.001473
2023-06-28 07:39:19.158378  Validation: avg loss: 1.6740, avg acc: 60.9524%
2023-06-28 07:39:46.058494  Train: epoch: 43 batch: 0/4, loss: 0.001148
2023-06-28 07:41:11.848005  Validation: avg loss: 1.6666, avg acc: 60.0000%
2023-06-28 07:41:38.863473  Train: epoch: 44 batch: 0/4, loss: 0.000727
2023-06-28 07:43:04.378328  Validation: avg loss: 1.6574, avg acc: 60.0000%
2023-06-28 07:43:31.288581  Train: epoch: 45 batch: 0/4, loss: 0.000889
2023-06-28 07:44:56.999980  Validation: avg loss: 1.6633, avg acc: 60.0000%
2023-06-28 07:45:23.934487  Train: epoch: 46 batch: 0/4, loss: 0.000658
2023-06-28 07:46:49.564758  Validation: avg loss: 1.6701, avg acc: 60.9524%
2023-06-28 07:47:16.525807  Train: epoch: 47 batch: 0/4, loss: 0.000605
2023-06-28 07:48:42.126198  Validation: avg loss: 1.6665, avg acc: 59.0476%
2023-06-28 07:49:09.084892  Train: epoch: 48 batch: 0/4, loss: 0.001271
2023-06-28 07:50:34.841062  Validation: avg loss: 1.6740, avg acc: 60.0000%
2023-06-28 07:51:01.783708  Train: epoch: 49 batch: 0/4, loss: 0.001831
2023-06-28 07:52:27.407971  Validation: avg loss: 1.6820, avg acc: 59.0476%
2023-06-28 07:52:54.374783  Train: epoch: 50 batch: 0/4, loss: 0.000624
2023-06-28 07:54:20.183671  Validation: avg loss: 1.6893, avg acc: 60.0000%