Datasets:
ngaggion
/
ChronoRoot_nnUNet

Dataset card Data Studio Files
xet
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1.16k
2025-01-20 20:27:24.796848: Pseudo dice [np.float32(0.7595), np.float32(0.7706), np.float32(0.8548), np.float32(0.7546), np.float32(0.899), np.float32(0.7919)]
2025-01-20 20:27:24.796885: Epoch time: 47.69 s
2025-01-20 20:27:25.275854:
2025-01-20 20:27:25.310322: Epoch 364
2025-01-20 20:27:25.310411: Current learning rate: 0.00665
2025-01-20 20:28:12.993261: train_loss -0.7321
2025-01-20 20:28:13.028384: val_loss -0.7087
2025-01-20 20:28:13.028464: Pseudo dice [np.float32(0.7606), np.float32(0.7677), np.float32(0.8495), np.float32(0.7747), np.float32(0.8808), np.float32(0.7431)]
2025-01-20 20:28:13.028504: Epoch time: 47.72 s
2025-01-20 20:28:13.502157:
2025-01-20 20:28:13.536620: Epoch 365
2025-01-20 20:28:13.536750: Current learning rate: 0.00665
2025-01-20 20:29:01.223642: train_loss -0.7281
2025-01-20 20:29:01.258754: val_loss -0.7178
2025-01-20 20:29:01.258825: Pseudo dice [np.float32(0.7636), np.float32(0.7476), np.float32(0.8645), np.float32(0.7444), np.float32(0.8981), np.float32(0.7854)]
2025-01-20 20:29:01.258870: Epoch time: 47.72 s
2025-01-20 20:29:01.728979:
2025-01-20 20:29:01.763523: Epoch 366
2025-01-20 20:29:01.763623: Current learning rate: 0.00664
2025-01-20 20:29:49.415378: train_loss -0.7388
2025-01-20 20:29:49.450490: val_loss -0.7278
2025-01-20 20:29:49.450545: Pseudo dice [np.float32(0.7677), np.float32(0.7712), np.float32(0.8641), np.float32(0.7721), np.float32(0.8978), np.float32(0.7839)]
2025-01-20 20:29:49.450589: Epoch time: 47.69 s
2025-01-20 20:29:49.920981:
2025-01-20 20:29:49.955431: Epoch 367
2025-01-20 20:29:49.955493: Current learning rate: 0.00663
2025-01-20 20:30:37.613612: train_loss -0.7355
2025-01-20 20:30:37.648756: val_loss -0.7242
2025-01-20 20:30:37.648813: Pseudo dice [np.float32(0.7652), np.float32(0.7721), np.float32(0.8663), np.float32(0.7565), np.float32(0.8944), np.float32(0.7886)]
2025-01-20 20:30:37.648850: Epoch time: 47.69 s
2025-01-20 20:30:38.122056:
2025-01-20 20:30:38.156514: Epoch 368
2025-01-20 20:30:38.156600: Current learning rate: 0.00662
2025-01-20 20:31:25.772090: train_loss -0.7237
2025-01-20 20:31:25.807196: val_loss -0.7126
2025-01-20 20:31:25.807253: Pseudo dice [np.float32(0.7415), np.float32(0.7516), np.float32(0.8531), np.float32(0.7113), np.float32(0.8937), np.float32(0.7921)]
2025-01-20 20:31:25.807297: Epoch time: 47.65 s
2025-01-20 20:31:26.279028:
2025-01-20 20:31:26.313550: Epoch 369
2025-01-20 20:31:26.313624: Current learning rate: 0.00661
2025-01-20 20:32:13.942597: train_loss -0.7219
2025-01-20 20:32:13.977716: val_loss -0.7179
2025-01-20 20:32:13.977776: Pseudo dice [np.float32(0.7731), np.float32(0.7784), np.float32(0.8659), np.float32(0.7584), np.float32(0.8832), np.float32(0.7918)]
2025-01-20 20:32:13.977823: Epoch time: 47.66 s
2025-01-20 20:32:14.449963:
2025-01-20 20:32:14.484424: Epoch 370
2025-01-20 20:32:14.484485: Current learning rate: 0.0066
2025-01-20 20:33:02.104475: train_loss -0.7268
2025-01-20 20:33:02.139583: val_loss -0.7351
2025-01-20 20:33:02.139662: Pseudo dice [np.float32(0.7658), np.float32(0.7585), np.float32(0.8687), np.float32(0.7514), np.float32(0.8973), np.float32(0.7848)]
2025-01-20 20:33:02.139699: Epoch time: 47.66 s
2025-01-20 20:33:02.730762:
2025-01-20 20:33:02.765138: Epoch 371
2025-01-20 20:33:02.765231: Current learning rate: 0.00659
2025-01-20 20:33:50.421375: train_loss -0.7221
2025-01-20 20:33:50.456480: val_loss -0.722
2025-01-20 20:33:50.456546: Pseudo dice [np.float32(0.7642), np.float32(0.7529), np.float32(0.8565), np.float32(0.7859), np.float32(0.8931), np.float32(0.7673)]
2025-01-20 20:33:50.456583: Epoch time: 47.69 s
2025-01-20 20:33:50.929313:
2025-01-20 20:33:50.963794: Epoch 372
2025-01-20 20:33:50.963874: Current learning rate: 0.00658
2025-01-20 20:34:38.632641: train_loss -0.723
2025-01-20 20:34:38.668014: val_loss -0.6988
2025-01-20 20:34:38.668094: Pseudo dice [np.float32(0.7536), np.float32(0.7587), np.float32(0.8524), np.float32(0.7441), np.float32(0.896), np.float32(0.7807)]
2025-01-20 20:34:38.668132: Epoch time: 47.7 s
2025-01-20 20:34:39.140512:
2025-01-20 20:34:39.175023: Epoch 373
2025-01-20 20:34:39.175123: Current learning rate: 0.00657
2025-01-20 20:35:26.826299: train_loss -0.7232
2025-01-20 20:35:26.861398: val_loss -0.7155
2025-01-20 20:35:26.861452: Pseudo dice [np.float32(0.7652), np.float32(0.7607), np.float32(0.8616), np.float32(0.7581), np.float32(0.902), np.float32(0.7879)]
2025-01-20 20:35:26.861487: Epoch time: 47.69 s
2025-01-20 20:35:27.333295:
2025-01-20 20:35:27.367784: Epoch 374
2025-01-20 20:35:27.367846: Current learning rate: 0.00656
2025-01-20 20:36:15.058274: train_loss -0.7177
2025-01-20 20:36:15.093420: val_loss -0.7072
2025-01-20 20:36:15.093492: Pseudo dice [np.float32(0.7672), np.float32(0.7446), np.float32(0.8624), np.float32(0.7612), np.float32(0.8944), np.float32(0.7949)]
2025-01-20 20:36:15.093546: Epoch time: 47.73 s
2025-01-20 20:36:15.566558:
2025-01-20 20:36:15.600919: Epoch 375
2025-01-20 20:36:15.600999: Current learning rate: 0.00655
2025-01-20 20:37:03.269469: train_loss -0.7242
2025-01-20 20:37:03.304571: val_loss -0.7298
2025-01-20 20:37:03.304640: Pseudo dice [np.float32(0.7675), np.float32(0.7737), np.float32(0.8636), np.float32(0.743), np.float32(0.9037), np.float32(0.784)]
2025-01-20 20:37:03.304691: Epoch time: 47.7 s
2025-01-20 20:37:03.781465:
2025-01-20 20:37:03.815821: Epoch 376
2025-01-20 20:37:03.815918: Current learning rate: 0.00654
2025-01-20 20:37:51.474879: train_loss -0.727
2025-01-20 20:37:51.510036: val_loss -0.6895
2025-01-20 20:37:51.510090: Pseudo dice [np.float32(0.766), np.float32(0.7733), np.float32(0.8614), np.float32(0.7424), np.float32(0.8794), np.float32(0.7744)]
2025-01-20 20:37:51.510126: Epoch time: 47.69 s
2025-01-20 20:37:51.980750:
2025-01-20 20:37:52.015201: Epoch 377
2025-01-20 20:37:52.015273: Current learning rate: 0.00653
2025-01-20 20:38:39.646264: train_loss -0.6991
2025-01-20 20:38:39.681370: val_loss -0.6947
2025-01-20 20:38:39.681425: Pseudo dice [np.float32(0.7513), np.float32(0.7503), np.float32(0.8518), np.float32(0.7406), np.float32(0.8805), np.float32(0.771)]
2025-01-20 20:38:39.681462: Epoch time: 47.67 s