Datasets:
ngaggion
/
ChronoRoot_nnUNet

Dataset card Data Studio Files Community
1
text
stringlengths
0
1.16k
2025-01-20 16:54:34.596576: train_loss -0.672
2025-01-20 16:54:34.631681: val_loss -0.6837
2025-01-20 16:54:34.631742: Pseudo dice [np.float32(0.7369), np.float32(0.7164), np.float32(0.8489), np.float32(0.737), np.float32(0.8795), np.float32(0.7452)]
2025-01-20 16:54:34.631782: Epoch time: 47.84 s
2025-01-20 16:54:35.476124:
2025-01-20 16:54:35.476682: Epoch 100
2025-01-20 16:54:35.476743: Current learning rate: 0.0091
2025-01-20 16:55:23.250470: train_loss -0.6822
2025-01-20 16:55:23.285630: val_loss -0.7005
2025-01-20 16:55:23.285730: Pseudo dice [np.float32(0.7467), np.float32(0.7784), np.float32(0.8547), np.float32(0.739), np.float32(0.8785), np.float32(0.7576)]
2025-01-20 16:55:23.285769: Epoch time: 47.77 s
2025-01-20 16:55:23.744220:
2025-01-20 16:55:23.778661: Epoch 101
2025-01-20 16:55:23.778730: Current learning rate: 0.00909
2025-01-20 16:56:11.566579: train_loss -0.6988
2025-01-20 16:56:11.601715: val_loss -0.6863
2025-01-20 16:56:11.601771: Pseudo dice [np.float32(0.7403), np.float32(0.7738), np.float32(0.848), np.float32(0.7435), np.float32(0.8867), np.float32(0.774)]
2025-01-20 16:56:11.601815: Epoch time: 47.82 s
2025-01-20 16:56:12.062807:
2025-01-20 16:56:12.062863: Epoch 102
2025-01-20 16:56:12.062936: Current learning rate: 0.00908
2025-01-20 16:56:59.813256: train_loss -0.6875
2025-01-20 16:56:59.848395: val_loss -0.6765
2025-01-20 16:56:59.848450: Pseudo dice [np.float32(0.7464), np.float32(0.7575), np.float32(0.85), np.float32(0.7382), np.float32(0.8675), np.float32(0.7633)]
2025-01-20 16:56:59.848487: Epoch time: 47.75 s
2025-01-20 16:57:00.306044:
2025-01-20 16:57:00.340567: Epoch 103
2025-01-20 16:57:00.340629: Current learning rate: 0.00907
2025-01-20 16:57:48.082054: train_loss -0.7028
2025-01-20 16:57:48.117238: val_loss -0.6884
2025-01-20 16:57:48.117305: Pseudo dice [np.float32(0.7483), np.float32(0.7702), np.float32(0.8515), np.float32(0.6962), np.float32(0.8694), np.float32(0.771)]
2025-01-20 16:57:48.117358: Epoch time: 47.78 s
2025-01-20 16:57:48.574182:
2025-01-20 16:57:48.608664: Epoch 104
2025-01-20 16:57:48.608769: Current learning rate: 0.00906
2025-01-20 16:58:36.372906: train_loss -0.7015
2025-01-20 16:58:36.407905: val_loss -0.6877
2025-01-20 16:58:36.407971: Pseudo dice [np.float32(0.7544), np.float32(0.7483), np.float32(0.8573), np.float32(0.733), np.float32(0.8764), np.float32(0.7666)]
2025-01-20 16:58:36.408025: Epoch time: 47.8 s
2025-01-20 16:58:36.872016:
2025-01-20 16:58:36.906392: Epoch 105
2025-01-20 16:58:36.906456: Current learning rate: 0.00905
2025-01-20 16:59:24.672890: train_loss -0.6963
2025-01-20 16:59:24.708021: val_loss -0.6799
2025-01-20 16:59:24.708073: Pseudo dice [np.float32(0.7392), np.float32(0.759), np.float32(0.8483), np.float32(0.7365), np.float32(0.887), np.float32(0.7547)]
2025-01-20 16:59:24.708108: Epoch time: 47.8 s
2025-01-20 16:59:25.277136:
2025-01-20 16:59:25.311617: Epoch 106
2025-01-20 16:59:25.311710: Current learning rate: 0.00904
2025-01-20 17:00:13.116606: train_loss -0.6812
2025-01-20 17:00:13.151722: val_loss -0.6811
2025-01-20 17:00:13.151779: Pseudo dice [np.float32(0.7356), np.float32(0.7561), np.float32(0.8603), np.float32(0.7243), np.float32(0.8705), np.float32(0.7701)]
2025-01-20 17:00:13.151815: Epoch time: 47.84 s
2025-01-20 17:00:13.151835: Yayy! New best EMA pseudo Dice: 0.7853000164031982
2025-01-20 17:00:13.999862:
2025-01-20 17:00:14.035038: Epoch 107
2025-01-20 17:00:14.035141: Current learning rate: 0.00903
2025-01-20 17:01:01.840276: train_loss -0.6943
2025-01-20 17:01:01.875385: val_loss -0.6919
2025-01-20 17:01:01.875445: Pseudo dice [np.float32(0.752), np.float32(0.7328), np.float32(0.8497), np.float32(0.7327), np.float32(0.88), np.float32(0.7758)]
2025-01-20 17:01:01.875490: Epoch time: 47.84 s
2025-01-20 17:01:01.875519: Yayy! New best EMA pseudo Dice: 0.7854999899864197
2025-01-20 17:01:02.724027:
2025-01-20 17:01:02.726417: Epoch 108
2025-01-20 17:01:02.726486: Current learning rate: 0.00902
2025-01-20 17:01:50.555341: train_loss -0.7124
2025-01-20 17:01:50.590775: val_loss -0.701
2025-01-20 17:01:50.590830: Pseudo dice [np.float32(0.7515), np.float32(0.7545), np.float32(0.8516), np.float32(0.7216), np.float32(0.8917), np.float32(0.7729)]
2025-01-20 17:01:50.590878: Epoch time: 47.83 s
2025-01-20 17:01:50.590900: Yayy! New best EMA pseudo Dice: 0.7860000133514404
2025-01-20 17:01:51.434176:
2025-01-20 17:01:51.469531: Epoch 109
2025-01-20 17:01:51.469617: Current learning rate: 0.00901
2025-01-20 17:02:39.291720: train_loss -0.6953
2025-01-20 17:02:39.326807: val_loss -0.7007
2025-01-20 17:02:39.326863: Pseudo dice [np.float32(0.766), np.float32(0.772), np.float32(0.8608), np.float32(0.7682), np.float32(0.8627), np.float32(0.763)]
2025-01-20 17:02:39.326900: Epoch time: 47.86 s
2025-01-20 17:02:39.326921: Yayy! New best EMA pseudo Dice: 0.7872999906539917
2025-01-20 17:02:40.175803:
2025-01-20 17:02:40.176028: Epoch 110
2025-01-20 17:02:40.176079: Current learning rate: 0.009
2025-01-20 17:03:27.999637: train_loss -0.6892
2025-01-20 17:03:28.034794: val_loss -0.6671
2025-01-20 17:03:28.034849: Pseudo dice [np.float32(0.7485), np.float32(0.745), np.float32(0.8416), np.float32(0.7161), np.float32(0.8709), np.float32(0.7484)]
2025-01-20 17:03:28.034885: Epoch time: 47.82 s
2025-01-20 17:03:28.494196:
2025-01-20 17:03:28.528636: Epoch 111
2025-01-20 17:03:28.528698: Current learning rate: 0.009
2025-01-20 17:04:16.331258: train_loss -0.6888
2025-01-20 17:04:16.398711: val_loss -0.6934
2025-01-20 17:04:16.398779: Pseudo dice [np.float32(0.7431), np.float32(0.7543), np.float32(0.851), np.float32(0.7283), np.float32(0.8875), np.float32(0.7992)]
2025-01-20 17:04:16.398827: Epoch time: 47.84 s
2025-01-20 17:04:16.861200:
2025-01-20 17:04:16.895649: Epoch 112
2025-01-20 17:04:16.895718: Current learning rate: 0.00899
2025-01-20 17:05:04.704652: train_loss -0.7012
2025-01-20 17:05:04.780467: val_loss -0.7023
2025-01-20 17:05:04.780523: Pseudo dice [np.float32(0.749), np.float32(0.7325), np.float32(0.8496), np.float32(0.7588), np.float32(0.8953), np.float32(0.775)]
2025-01-20 17:05:04.780595: Epoch time: 47.84 s
2025-01-20 17:05:04.780615: Yayy! New best EMA pseudo Dice: 0.7878000140190125