Datasets:
pyushkevich
/
crashs_template_package

Dataset card Data Studio Files
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1.22k
2023-08-04 06:32:55.774204: val_loss -0.888
2023-08-04 06:32:55.774245: Pseudo dice [0.9085]
2023-08-04 06:32:55.774299: Epoch time: 58.73 s
2023-08-04 06:32:55.774340: Yayy! New best EMA pseudo Dice: 0.9067
2023-08-04 06:32:57.819174:
2023-08-04 06:32:57.819284: Epoch 326
2023-08-04 06:32:57.819364: Current learning rate: 0.00219
2023-08-04 06:33:56.531325: train_loss -0.947
2023-08-04 06:33:56.531487: val_loss -0.8902
2023-08-04 06:33:56.531529: Pseudo dice [0.9099]
2023-08-04 06:33:56.531574: Epoch time: 58.71 s
2023-08-04 06:33:56.531611: Yayy! New best EMA pseudo Dice: 0.907
2023-08-04 06:33:58.525717:
2023-08-04 06:33:58.525847: Epoch 327
2023-08-04 06:33:58.525928: Current learning rate: 0.00216
2023-08-04 06:34:57.220838: train_loss -0.9467
2023-08-04 06:34:57.220979: val_loss -0.8862
2023-08-04 06:34:57.221019: Pseudo dice [0.9071]
2023-08-04 06:34:57.221061: Epoch time: 58.7 s
2023-08-04 06:34:57.221096: Yayy! New best EMA pseudo Dice: 0.907
2023-08-04 06:34:59.325572:
2023-08-04 06:34:59.325680: Epoch 328
2023-08-04 06:34:59.325764: Current learning rate: 0.00214
2023-08-04 06:35:58.066213: train_loss -0.9441
2023-08-04 06:35:58.066360: val_loss -0.8901
2023-08-04 06:35:58.066400: Pseudo dice [0.9097]
2023-08-04 06:35:58.066444: Epoch time: 58.74 s
2023-08-04 06:35:58.066481: Yayy! New best EMA pseudo Dice: 0.9073
2023-08-04 06:36:00.156054:
2023-08-04 06:36:00.156174: Epoch 329
2023-08-04 06:36:00.156257: Current learning rate: 0.00211
2023-08-04 06:36:58.849303: train_loss -0.9463
2023-08-04 06:36:58.849446: val_loss -0.889
2023-08-04 06:36:58.849486: Pseudo dice [0.9094]
2023-08-04 06:36:58.849530: Epoch time: 58.69 s
2023-08-04 06:36:58.849567: Yayy! New best EMA pseudo Dice: 0.9075
2023-08-04 06:37:01.114221:
2023-08-04 06:37:01.114342: Epoch 330
2023-08-04 06:37:01.114423: Current learning rate: 0.00208
2023-08-04 06:37:59.854518: train_loss -0.9475
2023-08-04 06:37:59.854660: val_loss -0.8806
2023-08-04 06:37:59.854701: Pseudo dice [0.9031]
2023-08-04 06:37:59.854746: Epoch time: 58.74 s
2023-08-04 06:38:00.617214:
2023-08-04 06:38:00.617322: Epoch 331
2023-08-04 06:38:00.617402: Current learning rate: 0.00206
2023-08-04 06:38:59.328970: train_loss -0.9465
2023-08-04 06:38:59.329190: val_loss -0.887
2023-08-04 06:38:59.329231: Pseudo dice [0.9078]
2023-08-04 06:38:59.329277: Epoch time: 58.71 s
2023-08-04 06:39:00.091376:
2023-08-04 06:39:00.091471: Epoch 332
2023-08-04 06:39:00.091549: Current learning rate: 0.00203
2023-08-04 06:39:58.800364: train_loss -0.9477
2023-08-04 06:39:58.800501: val_loss -0.888
2023-08-04 06:39:58.800543: Pseudo dice [0.9077]
2023-08-04 06:39:58.800587: Epoch time: 58.71 s
2023-08-04 06:39:59.687002:
2023-08-04 06:39:59.687109: Epoch 333
2023-08-04 06:39:59.687188: Current learning rate: 0.002
2023-08-04 06:40:58.386130: train_loss -0.9473
2023-08-04 06:40:58.386273: val_loss -0.8844
2023-08-04 06:40:58.386316: Pseudo dice [0.9057]
2023-08-04 06:40:58.386361: Epoch time: 58.7 s
2023-08-04 06:40:59.138647:
2023-08-04 06:40:59.138780: Epoch 334
2023-08-04 06:40:59.138860: Current learning rate: 0.00198
2023-08-04 06:41:57.907928: train_loss -0.9451
2023-08-04 06:41:57.908073: val_loss -0.8865
2023-08-04 06:41:57.908113: Pseudo dice [0.9072]
2023-08-04 06:41:57.908157: Epoch time: 58.77 s
2023-08-04 06:41:58.678975:
2023-08-04 06:41:58.679083: Epoch 335
2023-08-04 06:41:58.679162: Current learning rate: 0.00195
2023-08-04 06:42:57.368583: train_loss -0.9457
2023-08-04 06:42:57.368721: val_loss -0.8832
2023-08-04 06:42:57.368760: Pseudo dice [0.9051]
2023-08-04 06:42:57.368804: Epoch time: 58.69 s
2023-08-04 06:42:58.137306:
2023-08-04 06:42:58.137408: Epoch 336
2023-08-04 06:42:58.137489: Current learning rate: 0.00192
2023-08-04 06:43:56.867608: train_loss -0.9467
2023-08-04 06:43:56.867751: val_loss -0.8873
2023-08-04 06:43:56.867792: Pseudo dice [0.9075]
2023-08-04 06:43:56.867838: Epoch time: 58.73 s
2023-08-04 06:43:57.640296:
2023-08-04 06:43:57.640404: Epoch 337
2023-08-04 06:43:57.640484: Current learning rate: 0.00189
2023-08-04 06:44:56.363827: train_loss -0.9478
2023-08-04 06:44:56.363969: val_loss -0.8866
2023-08-04 06:44:56.364009: Pseudo dice [0.9074]
2023-08-04 06:44:56.364052: Epoch time: 58.72 s
2023-08-04 06:44:57.257447:
2023-08-04 06:44:57.257562: Epoch 338
2023-08-04 06:44:57.257640: Current learning rate: 0.00187
2023-08-04 06:45:55.988295: train_loss -0.9484
2023-08-04 06:45:55.988655: val_loss -0.8863
2023-08-04 06:45:55.988697: Pseudo dice [0.9074]
2023-08-04 06:45:55.988744: Epoch time: 58.73 s
2023-08-04 06:45:56.759376: