2023-06-27 20:24:29.097284  cuda
2023-06-27 20:24:46.711510  Train: epoch: 1 batch: 0/4, loss: 0.691143
2023-06-27 20:25:32.785069  Validation: avg loss: 0.6893, avg acc: 57.1429%
2023-06-27 20:25:47.336659  Train: epoch: 2 batch: 0/4, loss: 0.685980
2023-06-27 20:26:32.734245  Validation: avg loss: 0.6867, avg acc: 57.1429%
2023-06-27 20:26:47.106466  Train: epoch: 3 batch: 0/4, loss: 0.672524
2023-06-27 20:27:32.526984  Validation: avg loss: 0.6864, avg acc: 57.1429%
2023-06-27 20:27:46.909404  Train: epoch: 4 batch: 0/4, loss: 0.644080
2023-06-27 20:28:33.568527  Validation: avg loss: 0.6929, avg acc: 57.1429%
2023-06-27 20:28:48.329049  Train: epoch: 5 batch: 0/4, loss: 0.644745
2023-06-27 20:29:34.213962  Validation: avg loss: 0.7186, avg acc: 42.8571%
2023-06-27 20:29:48.518932  Train: epoch: 6 batch: 0/4, loss: 0.647197
2023-06-27 20:30:34.266611  Validation: avg loss: 0.7420, avg acc: 42.8571%
2023-06-27 20:30:48.472798  Train: epoch: 7 batch: 0/4, loss: 0.603712
2023-06-27 20:31:33.716582  Validation: avg loss: 0.7435, avg acc: 42.8571%
2023-06-27 20:31:47.942766  Train: epoch: 8 batch: 0/4, loss: 0.557651
2023-06-27 20:32:33.315917  Validation: avg loss: 0.7444, avg acc: 42.8571%
2023-06-27 20:32:47.738961  Train: epoch: 9 batch: 0/4, loss: 0.537784
2023-06-27 20:33:33.803949  Validation: avg loss: 0.8276, avg acc: 42.8571%
2023-06-27 20:33:48.296666  Train: epoch: 10 batch: 0/4, loss: 0.456332
2023-06-27 20:34:35.173420  Validation: avg loss: 0.8768, avg acc: 42.8571%
2023-06-27 20:34:52.401751  Train: epoch: 11 batch: 0/4, loss: 0.332917
2023-06-27 20:35:47.800032  Validation: avg loss: 0.9420, avg acc: 42.8571%
2023-06-27 20:36:04.354299  Train: epoch: 12 batch: 0/4, loss: 0.285392
2023-06-27 20:36:49.498897  Validation: avg loss: 0.9740, avg acc: 42.8571%
2023-06-27 20:37:03.749654  Train: epoch: 13 batch: 0/4, loss: 0.266133
2023-06-27 20:37:48.830727  Validation: avg loss: 0.9945, avg acc: 47.6190%
2023-06-27 20:38:03.160350  Train: epoch: 14 batch: 0/4, loss: 0.131294
2023-06-27 20:38:48.501099  Validation: avg loss: 0.8946, avg acc: 49.5238%
2023-06-27 20:39:02.726512  Train: epoch: 15 batch: 0/4, loss: 0.118250
2023-06-27 20:39:47.995243  Validation: avg loss: 0.8834, avg acc: 54.2857%
2023-06-27 20:40:04.750322  Train: epoch: 16 batch: 0/4, loss: 0.065639
2023-06-27 20:40:59.221551  Validation: avg loss: 1.0354, avg acc: 49.5238%
2023-06-27 20:41:16.494496  Train: epoch: 17 batch: 0/4, loss: 0.091341
2023-06-27 20:42:11.264989  Validation: avg loss: 1.0501, avg acc: 50.4762%
2023-06-27 20:42:28.539772  Train: epoch: 18 batch: 0/4, loss: 0.025633
2023-06-27 20:43:23.100663  Validation: avg loss: 1.0062, avg acc: 59.0476%
2023-06-27 20:43:40.148723  Train: epoch: 19 batch: 0/4, loss: 0.036730
2023-06-27 20:44:34.538871  Validation: avg loss: 0.9890, avg acc: 60.9524%
2023-06-27 20:44:49.300661  Train: epoch: 20 batch: 0/4, loss: 0.014275
2023-06-27 20:45:35.217730  Validation: avg loss: 1.0903, avg acc: 61.9048%
2023-06-27 20:45:49.839872  Train: epoch: 21 batch: 0/4, loss: 0.014764
2023-06-27 20:46:35.720425  Validation: avg loss: 1.1801, avg acc: 61.9048%
2023-06-27 20:46:49.982285  Train: epoch: 22 batch: 0/4, loss: 0.007254
2023-06-27 20:47:35.058200  Validation: avg loss: 1.2001, avg acc: 64.7619%
2023-06-27 20:47:49.367503  Train: epoch: 23 batch: 0/4, loss: 0.007846
2023-06-27 20:48:34.741647  Validation: avg loss: 1.3219, avg acc: 65.7143%
2023-06-27 20:48:49.206170  Train: epoch: 24 batch: 0/4, loss: 0.006899
2023-06-27 20:49:34.938107  Validation: avg loss: 1.3289, avg acc: 65.7143%
2023-06-27 20:49:49.300229  Train: epoch: 25 batch: 0/4, loss: 0.009685
2023-06-27 20:50:34.859294  Validation: avg loss: 1.3377, avg acc: 62.8571%
2023-06-27 20:50:49.163374  Train: epoch: 26 batch: 0/4, loss: 0.013282
2023-06-27 20:51:34.162103  Validation: avg loss: 1.3314, avg acc: 62.8571%
2023-06-27 20:51:48.527172  Train: epoch: 27 batch: 0/4, loss: 0.009669
2023-06-27 20:52:34.520132  Validation: avg loss: 1.3528, avg acc: 63.8095%
2023-06-27 20:52:49.095199  Train: epoch: 28 batch: 0/4, loss: 0.010325
2023-06-27 20:53:34.230659  Validation: avg loss: 1.3256, avg acc: 66.6667%
2023-06-27 20:53:48.453604  Train: epoch: 29 batch: 0/4, loss: 0.004010
2023-06-27 20:54:33.935093  Validation: avg loss: 1.3582, avg acc: 64.7619%
2023-06-27 20:54:48.419516  Train: epoch: 30 batch: 0/4, loss: 0.003470
2023-06-27 20:55:35.252915  Validation: avg loss: 1.3894, avg acc: 63.8095%
2023-06-27 20:55:49.848116  Train: epoch: 31 batch: 0/4, loss: 0.005459
2023-06-27 20:56:35.907501  Validation: avg loss: 1.4114, avg acc: 64.7619%
2023-06-27 20:56:50.295728  Train: epoch: 32 batch: 0/4, loss: 0.003528
2023-06-27 20:57:36.702376  Validation: avg loss: 1.4297, avg acc: 65.7143%
2023-06-27 20:57:51.026266  Train: epoch: 33 batch: 0/4, loss: 0.006942
2023-06-27 20:58:36.208021  Validation: avg loss: 1.4177, avg acc: 64.7619%
2023-06-27 20:58:50.450671  Train: epoch: 34 batch: 0/4, loss: 0.002612
2023-06-27 20:59:35.726068  Validation: avg loss: 1.4280, avg acc: 64.7619%
2023-06-27 20:59:50.053097  Train: epoch: 35 batch: 0/4, loss: 0.002576
2023-06-27 21:00:35.161984  Validation: avg loss: 1.4479, avg acc: 65.7143%
2023-06-27 21:00:49.595550  Train: epoch: 36 batch: 0/4, loss: 0.007597
2023-06-27 21:01:35.293097  Validation: avg loss: 1.4474, avg acc: 65.7143%
2023-06-27 21:01:49.741054  Train: epoch: 37 batch: 0/4, loss: 0.002884
2023-06-27 21:02:35.435971  Validation: avg loss: 1.4477, avg acc: 64.7619%
2023-06-27 21:02:50.076695  Train: epoch: 38 batch: 0/4, loss: 0.006051
2023-06-27 21:03:35.825173  Validation: avg loss: 1.4994, avg acc: 64.7619%
2023-06-27 21:03:50.432057  Train: epoch: 39 batch: 0/4, loss: 0.001255
2023-06-27 21:04:36.140945  Validation: avg loss: 1.5201, avg acc: 64.7619%
2023-06-27 21:04:50.613230  Train: epoch: 40 batch: 0/4, loss: 0.002234
2023-06-27 21:05:36.480363  Validation: avg loss: 1.5425, avg acc: 64.7619%
2023-06-27 21:05:51.169549  Train: epoch: 41 batch: 0/4, loss: 0.001239
2023-06-27 21:06:37.757136  Validation: avg loss: 1.5486, avg acc: 65.7143%
2023-06-27 21:06:52.081432  Train: epoch: 42 batch: 0/4, loss: 0.001083
2023-06-27 21:07:37.749521  Validation: avg loss: 1.5343, avg acc: 65.7143%
2023-06-27 21:07:52.544739  Train: epoch: 43 batch: 0/4, loss: 0.001184
2023-06-27 21:08:37.779487  Validation: avg loss: 1.5527, avg acc: 65.7143%
2023-06-27 21:08:52.231289  Train: epoch: 44 batch: 0/4, loss: 0.001146
2023-06-27 21:09:38.142167  Validation: avg loss: 1.5314, avg acc: 65.7143%
2023-06-27 21:09:52.818703  Train: epoch: 45 batch: 0/4, loss: 0.000785
2023-06-27 21:10:38.542424  Validation: avg loss: 1.5186, avg acc: 65.7143%
2023-06-27 21:10:53.183909  Train: epoch: 46 batch: 0/4, loss: 0.001573
2023-06-27 21:11:38.626099  Validation: avg loss: 1.5108, avg acc: 65.7143%
2023-06-27 21:11:53.051555  Train: epoch: 47 batch: 0/4, loss: 0.000877
2023-06-27 21:12:38.247759  Validation: avg loss: 1.5156, avg acc: 65.7143%
2023-06-27 21:12:52.556644  Train: epoch: 48 batch: 0/4, loss: 0.001116
2023-06-27 21:13:38.527263  Validation: avg loss: 1.5247, avg acc: 65.7143%
2023-06-27 21:13:53.461653  Train: epoch: 49 batch: 0/4, loss: 0.000840
2023-06-27 21:14:39.023648  Validation: avg loss: 1.5159, avg acc: 65.7143%
2023-06-27 21:14:53.501405  Train: epoch: 50 batch: 0/4, loss: 0.000605
2023-06-27 21:15:38.909785  Validation: avg loss: 1.5166, avg acc: 65.7143%