Datasets:
KagglingFace
/
nnUNet-KiTS19-3d-lowres-50epochs

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2024-03-24 17:24:31.765050: Current learning rate: 0.0098
2024-03-24 17:27:07.101698: train_loss -0.6396
2024-03-24 17:27:07.102085: val_loss -0.6363
2024-03-24 17:27:07.102265: Pseudo dice [0.9242, 0.7644]
2024-03-24 17:27:07.102405: Epoch time: 155.34 s
2024-03-24 17:27:07.102529: Yayy! New best EMA pseudo Dice: 0.6961
2024-03-24 17:27:10.690684:
2024-03-24 17:27:10.690935: Epoch 23
2024-03-24 17:27:10.691099: Current learning rate: 0.00979
2024-03-24 17:29:52.807175: train_loss -0.6246
2024-03-24 17:29:52.807483: val_loss -0.5582
2024-03-24 17:29:52.807616: Pseudo dice [0.8975, 0.5508]
2024-03-24 17:29:52.807734: Epoch time: 162.12 s
2024-03-24 17:29:52.807864: Yayy! New best EMA pseudo Dice: 0.6989
2024-03-24 17:29:55.919362:
2024-03-24 17:29:55.919549: Epoch 24
2024-03-24 17:29:55.919679: Current learning rate: 0.00978
2024-03-24 17:32:21.213422: train_loss -0.6326
2024-03-24 17:32:21.224927: val_loss -0.5734
2024-03-24 17:32:21.225207: Pseudo dice [0.8678, 0.6751]
2024-03-24 17:32:21.225402: Epoch time: 145.3 s
2024-03-24 17:32:21.225546: Yayy! New best EMA pseudo Dice: 0.7062
2024-03-24 17:32:24.952741:
2024-03-24 17:32:24.952924: Epoch 25
2024-03-24 17:32:24.953063: Current learning rate: 0.00977
2024-03-24 17:35:00.083333: train_loss -0.6297
2024-03-24 17:35:00.092985: val_loss -0.6285
2024-03-24 17:35:00.093256: Pseudo dice [0.9056, 0.5654]
2024-03-24 17:35:00.093443: Epoch time: 155.13 s
2024-03-24 17:35:00.093562: Yayy! New best EMA pseudo Dice: 0.7091
2024-03-24 17:35:04.695292:
2024-03-24 17:35:04.695712: Epoch 26
2024-03-24 17:35:04.695882: Current learning rate: 0.00977
2024-03-24 17:37:33.213282: train_loss -0.6428
2024-03-24 17:37:33.213826: val_loss -0.6534
2024-03-24 17:37:33.214120: Pseudo dice [0.9134, 0.7726]
2024-03-24 17:37:33.214360: Epoch time: 148.52 s
2024-03-24 17:37:33.214575: Yayy! New best EMA pseudo Dice: 0.7225
2024-03-24 17:37:36.967520:
2024-03-24 17:37:36.967698: Epoch 27
2024-03-24 17:37:36.967870: Current learning rate: 0.00976
2024-03-24 17:40:03.240283: train_loss -0.6422
2024-03-24 17:40:03.240664: val_loss -0.6623
2024-03-24 17:40:03.240916: Pseudo dice [0.9224, 0.6762]
2024-03-24 17:40:03.241077: Epoch time: 146.27 s
2024-03-24 17:40:03.241195: Yayy! New best EMA pseudo Dice: 0.7302
2024-03-24 17:40:07.784885:
2024-03-24 17:40:07.785062: Epoch 28
2024-03-24 17:40:07.785181: Current learning rate: 0.00975
2024-03-24 17:42:45.246249: train_loss -0.6792
2024-03-24 17:42:45.258902: val_loss -0.644
2024-03-24 17:42:45.259162: Pseudo dice [0.926, 0.6137]
2024-03-24 17:42:45.259296: Epoch time: 157.46 s
2024-03-24 17:42:45.259393: Yayy! New best EMA pseudo Dice: 0.7341
2024-03-24 17:42:49.411126:
2024-03-24 17:42:49.411351: Epoch 29
2024-03-24 17:42:49.411508: Current learning rate: 0.00974
2024-03-24 17:45:21.697652: train_loss -0.6855
2024-03-24 17:45:21.710905: val_loss -0.6629
2024-03-24 17:45:21.711262: Pseudo dice [0.9226, 0.828]
2024-03-24 17:45:21.711468: Epoch time: 152.29 s
2024-03-24 17:45:21.711608: Yayy! New best EMA pseudo Dice: 0.7482
2024-03-24 17:45:25.588032:
2024-03-24 17:45:25.588205: Epoch 30
2024-03-24 17:45:25.588335: Current learning rate: 0.00973
2024-03-24 17:47:56.901990: train_loss -0.6531
2024-03-24 17:47:56.914922: val_loss -0.6493
2024-03-24 17:47:56.915318: Pseudo dice [0.9209, 0.8032]
2024-03-24 17:47:56.915476: Epoch time: 151.32 s
2024-03-24 17:47:56.915586: Yayy! New best EMA pseudo Dice: 0.7596
2024-03-24 17:48:01.144379:
2024-03-24 17:48:01.144643: Epoch 31
2024-03-24 17:48:01.144810: Current learning rate: 0.00972
2024-03-24 17:50:45.331283: train_loss -0.6687
2024-03-24 17:50:45.333100: val_loss -0.6676
2024-03-24 17:50:45.333262: Pseudo dice [0.9313, 0.7864]
2024-03-24 17:50:45.333392: Epoch time: 164.19 s
2024-03-24 17:50:45.333489: Yayy! New best EMA pseudo Dice: 0.7695
2024-03-24 17:50:49.335135:
2024-03-24 17:50:49.335504: Epoch 32
2024-03-24 17:50:49.335670: Current learning rate: 0.00971
2024-03-24 17:53:28.292631: train_loss -0.6772
2024-03-24 17:53:28.293018: val_loss -0.6724
2024-03-24 17:53:28.293171: Pseudo dice [0.9397, 0.8128]
2024-03-24 17:53:28.293307: Epoch time: 158.96 s
2024-03-24 17:53:28.293426: Yayy! New best EMA pseudo Dice: 0.7802
2024-03-24 17:53:33.057241:
2024-03-24 17:53:33.057488: Epoch 33
2024-03-24 17:53:33.057646: Current learning rate: 0.0097
2024-03-24 17:56:12.431175: train_loss -0.6802
2024-03-24 17:56:12.431581: val_loss -0.6749
2024-03-24 17:56:12.431789: Pseudo dice [0.9277, 0.7985]
2024-03-24 17:56:12.431956: Epoch time: 159.38 s
2024-03-24 17:56:12.432090: Yayy! New best EMA pseudo Dice: 0.7885
2024-03-24 17:56:16.827172:
2024-03-24 17:56:16.827693: Epoch 34
2024-03-24 17:56:16.827952: Current learning rate: 0.00969
2024-03-24 17:58:37.047956: train_loss -0.6737
2024-03-24 17:58:37.048465: val_loss -0.6594
2024-03-24 17:58:37.048687: Pseudo dice [0.92, 0.7868]