230627220548.log

2023-06-27 22:05:48.247922  cuda
2023-06-27 22:06:02.700087  Train: epoch: 1 batch: 0/4, loss: 0.694332
2023-06-27 22:06:49.134593  Validation: avg loss: 0.6871, avg acc: 57.1429%
2023-06-27 22:07:03.694375  Train: epoch: 2 batch: 0/4, loss: 0.664086
2023-06-27 22:07:49.773964  Validation: avg loss: 0.6849, avg acc: 57.1429%
2023-06-27 22:08:04.264858  Train: epoch: 3 batch: 0/4, loss: 0.680979
2023-06-27 22:08:49.287316  Validation: avg loss: 0.6857, avg acc: 57.1429%
2023-06-27 22:09:03.568651  Train: epoch: 4 batch: 0/4, loss: 0.660581
2023-06-27 22:09:48.550393  Validation: avg loss: 0.6835, avg acc: 57.1429%
2023-06-27 22:10:02.639012  Train: epoch: 5 batch: 0/4, loss: 0.647255
2023-06-27 22:10:47.197546  Validation: avg loss: 0.6823, avg acc: 57.1429%
2023-06-27 22:11:01.412408  Train: epoch: 6 batch: 0/4, loss: 0.614855
2023-06-27 22:11:46.503837  Validation: avg loss: 0.6813, avg acc: 57.1429%
2023-06-27 22:12:00.867246  Train: epoch: 7 batch: 0/4, loss: 0.581202
2023-06-27 22:12:46.349701  Validation: avg loss: 0.6812, avg acc: 57.1429%
2023-06-27 22:13:00.941791  Train: epoch: 8 batch: 0/4, loss: 0.570684
2023-06-27 22:13:46.248950  Validation: avg loss: 0.6799, avg acc: 60.0000%
2023-06-27 22:14:00.818297  Train: epoch: 9 batch: 0/4, loss: 0.483673
2023-06-27 22:14:46.800237  Validation: avg loss: 0.6701, avg acc: 60.0000%
2023-06-27 22:15:01.432393  Train: epoch: 10 batch: 0/4, loss: 0.420846
2023-06-27 22:15:47.795169  Validation: avg loss: 0.6588, avg acc: 71.4286%
2023-06-27 22:16:02.066573  Train: epoch: 11 batch: 0/4, loss: 0.349698
2023-06-27 22:16:47.069922  Validation: avg loss: 0.6403, avg acc: 67.6190%
2023-06-27 22:17:01.212362  Train: epoch: 12 batch: 0/4, loss: 0.290924
2023-06-27 22:17:46.767356  Validation: avg loss: 0.5999, avg acc: 71.4286%
2023-06-27 22:18:01.308525  Train: epoch: 13 batch: 0/4, loss: 0.210976
2023-06-27 22:18:47.025021  Validation: avg loss: 0.5615, avg acc: 71.4286%
2023-06-27 22:19:01.268115  Train: epoch: 14 batch: 0/4, loss: 0.151887
2023-06-27 22:19:46.249894  Validation: avg loss: 0.5789, avg acc: 70.4762%
2023-06-27 22:20:00.317073  Train: epoch: 15 batch: 0/4, loss: 0.091754
2023-06-27 22:20:44.853358  Validation: avg loss: 0.5884, avg acc: 68.5714%
2023-06-27 22:20:59.252199  Train: epoch: 16 batch: 0/4, loss: 0.064195
2023-06-27 22:21:43.926641  Validation: avg loss: 0.6605, avg acc: 67.6190%
2023-06-27 22:21:58.093871  Train: epoch: 17 batch: 0/4, loss: 0.058442
2023-06-27 22:22:42.867910  Validation: avg loss: 0.7124, avg acc: 68.5714%
2023-06-27 22:22:57.267821  Train: epoch: 18 batch: 0/4, loss: 0.034886
2023-06-27 22:23:42.369799  Validation: avg loss: 0.7680, avg acc: 67.6190%
2023-06-27 22:23:56.549715  Train: epoch: 19 batch: 0/4, loss: 0.021634
2023-06-27 22:24:41.550506  Validation: avg loss: 0.8190, avg acc: 65.7143%
2023-06-27 22:24:55.913941  Train: epoch: 20 batch: 0/4, loss: 0.041213
2023-06-27 22:25:40.883883  Validation: avg loss: 0.8872, avg acc: 70.4762%
2023-06-27 22:25:55.354460  Train: epoch: 21 batch: 0/4, loss: 0.037327
2023-06-27 22:26:39.808208  Validation: avg loss: 0.9775, avg acc: 66.6667%
2023-06-27 22:26:54.000967  Train: epoch: 22 batch: 0/4, loss: 0.007783
2023-06-27 22:27:38.436922  Validation: avg loss: 1.0206, avg acc: 65.7143%
2023-06-27 22:27:52.713763  Train: epoch: 23 batch: 0/4, loss: 0.009117
2023-06-27 22:28:37.844541  Validation: avg loss: 1.0509, avg acc: 64.7619%
2023-06-27 22:28:52.372054  Train: epoch: 24 batch: 0/4, loss: 0.004930
2023-06-27 22:29:38.195225  Validation: avg loss: 1.0375, avg acc: 66.6667%
2023-06-27 22:29:52.833951  Train: epoch: 25 batch: 0/4, loss: 0.006854
2023-06-27 22:30:42.418617  Validation: avg loss: 1.0135, avg acc: 70.4762%
2023-06-27 22:30:59.826240  Train: epoch: 26 batch: 0/4, loss: 0.005497
2023-06-27 22:31:53.313775  Validation: avg loss: 0.9878, avg acc: 69.5238%
2023-06-27 22:32:10.441642  Train: epoch: 27 batch: 0/4, loss: 0.013207
2023-06-27 22:33:03.727428  Validation: avg loss: 0.9929, avg acc: 68.5714%
2023-06-27 22:33:20.489639  Train: epoch: 28 batch: 0/4, loss: 0.007555
2023-06-27 22:34:14.171016  Validation: avg loss: 1.0352, avg acc: 63.8095%
2023-06-27 22:34:31.007619  Train: epoch: 29 batch: 0/4, loss: 0.015213
2023-06-27 22:35:24.970835  Validation: avg loss: 1.0920, avg acc: 67.6190%
2023-06-27 22:35:42.393896  Train: epoch: 30 batch: 0/4, loss: 0.005064
2023-06-27 22:36:37.084491  Validation: avg loss: 1.1553, avg acc: 65.7143%
2023-06-27 22:36:54.262733  Train: epoch: 31 batch: 0/4, loss: 0.004100
2023-06-27 22:37:40.496946  Validation: avg loss: 1.1604, avg acc: 64.7619%
2023-06-27 22:37:54.785895  Train: epoch: 32 batch: 0/4, loss: 0.007035
2023-06-27 22:38:39.997172  Validation: avg loss: 1.1841, avg acc: 64.7619%
2023-06-27 22:38:54.265682  Train: epoch: 33 batch: 0/4, loss: 0.002913
2023-06-27 22:39:39.297686  Validation: avg loss: 1.2217, avg acc: 66.6667%
2023-06-27 22:39:53.662343  Train: epoch: 34 batch: 0/4, loss: 0.003259
2023-06-27 22:40:39.630910  Validation: avg loss: 1.2292, avg acc: 67.6190%
2023-06-27 22:40:53.932959  Train: epoch: 35 batch: 0/4, loss: 0.004313
2023-06-27 22:41:39.521995  Validation: avg loss: 1.2720, avg acc: 66.6667%
2023-06-27 22:41:54.010133  Train: epoch: 36 batch: 0/4, loss: 0.006060
2023-06-27 22:42:38.895880  Validation: avg loss: 1.2800, avg acc: 66.6667%
2023-06-27 22:42:53.040187  Train: epoch: 37 batch: 0/4, loss: 0.003258
2023-06-27 22:43:37.680677  Validation: avg loss: 1.3244, avg acc: 68.5714%
2023-06-27 22:43:51.744750  Train: epoch: 38 batch: 0/4, loss: 0.002319
2023-06-27 22:44:36.460156  Validation: avg loss: 1.3268, avg acc: 66.6667%
2023-06-27 22:44:50.518069  Train: epoch: 39 batch: 0/4, loss: 0.002890
2023-06-27 22:45:35.154920  Validation: avg loss: 1.2941, avg acc: 67.6190%
2023-06-27 22:45:49.264716  Train: epoch: 40 batch: 0/4, loss: 0.002698
2023-06-27 22:46:34.424544  Validation: avg loss: 1.2796, avg acc: 65.7143%
2023-06-27 22:46:48.850944  Train: epoch: 41 batch: 0/4, loss: 0.002646
2023-06-27 22:47:34.845515  Validation: avg loss: 1.2635, avg acc: 64.7619%
2023-06-27 22:47:49.211660  Train: epoch: 42 batch: 0/4, loss: 0.001491
2023-06-27 22:48:34.132406  Validation: avg loss: 1.2806, avg acc: 64.7619%
2023-06-27 22:48:48.271090  Train: epoch: 43 batch: 0/4, loss: 0.002615
2023-06-27 22:49:33.343224  Validation: avg loss: 1.2766, avg acc: 65.7143%
2023-06-27 22:49:47.878757  Train: epoch: 44 batch: 0/4, loss: 0.001109
2023-06-27 22:50:32.900879  Validation: avg loss: 1.2934, avg acc: 64.7619%
2023-06-27 22:50:47.024931  Train: epoch: 45 batch: 0/4, loss: 0.001578
2023-06-27 22:51:32.653596  Validation: avg loss: 1.2984, avg acc: 66.6667%
2023-06-27 22:51:46.814239  Train: epoch: 46 batch: 0/4, loss: 0.000983
2023-06-27 22:52:31.790379  Validation: avg loss: 1.3014, avg acc: 67.6190%
2023-06-27 22:52:45.959176  Train: epoch: 47 batch: 0/4, loss: 0.001445
2023-06-27 22:53:30.927607  Validation: avg loss: 1.2994, avg acc: 66.6667%
2023-06-27 22:53:45.037631  Train: epoch: 48 batch: 0/4, loss: 0.001244
2023-06-27 22:54:29.540818  Validation: avg loss: 1.2992, avg acc: 66.6667%
2023-06-27 22:54:43.669885  Train: epoch: 49 batch: 0/4, loss: 0.000969
2023-06-27 22:55:28.244709  Validation: avg loss: 1.2983, avg acc: 65.7143%
2023-06-27 22:55:42.328411  Train: epoch: 50 batch: 0/4, loss: 0.000754
2023-06-27 22:56:27.191368  Validation: avg loss: 1.3086, avg acc: 65.7143%