Datasets:
pyushkevich
/
crashs_template_package

Dataset card Data Studio Files
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1.22k
2023-08-04 07:13:47.770964: Current learning rate: 0.00106
2023-08-04 07:14:46.495410: train_loss -0.9513
2023-08-04 07:14:46.495550: val_loss -0.8892
2023-08-04 07:14:46.495592: Pseudo dice [0.9091]
2023-08-04 07:14:46.495636: Epoch time: 58.73 s
2023-08-04 07:14:47.262810:
2023-08-04 07:14:47.262915: Epoch 368
2023-08-04 07:14:47.263001: Current learning rate: 0.00103
2023-08-04 07:15:45.962574: train_loss -0.9517
2023-08-04 07:15:45.962722: val_loss -0.8901
2023-08-04 07:15:45.962764: Pseudo dice [0.91]
2023-08-04 07:15:45.962809: Epoch time: 58.7 s
2023-08-04 07:15:46.857587:
2023-08-04 07:15:46.857689: Epoch 369
2023-08-04 07:15:46.857770: Current learning rate: 0.001
2023-08-04 07:16:45.539227: train_loss -0.9492
2023-08-04 07:16:45.539375: val_loss -0.8896
2023-08-04 07:16:45.539415: Pseudo dice [0.9099]
2023-08-04 07:16:45.539460: Epoch time: 58.68 s
2023-08-04 07:16:46.310025:
2023-08-04 07:16:46.310140: Epoch 370
2023-08-04 07:16:46.310221: Current learning rate: 0.00097
2023-08-04 07:17:44.993732: train_loss -0.9504
2023-08-04 07:17:44.993879: val_loss -0.8841
2023-08-04 07:17:44.993920: Pseudo dice [0.9055]
2023-08-04 07:17:44.993965: Epoch time: 58.68 s
2023-08-04 07:17:45.771039:
2023-08-04 07:17:45.771145: Epoch 371
2023-08-04 07:17:45.771228: Current learning rate: 0.00094
2023-08-04 07:18:44.454387: train_loss -0.9485
2023-08-04 07:18:44.454543: val_loss -0.8828
2023-08-04 07:18:44.454584: Pseudo dice [0.9055]
2023-08-04 07:18:44.454630: Epoch time: 58.68 s
2023-08-04 07:18:45.241696:
2023-08-04 07:18:45.241798: Epoch 372
2023-08-04 07:18:45.241878: Current learning rate: 0.00091
2023-08-04 07:19:43.922614: train_loss -0.95
2023-08-04 07:19:43.922759: val_loss -0.8858
2023-08-04 07:19:43.922799: Pseudo dice [0.9076]
2023-08-04 07:19:43.922845: Epoch time: 58.68 s
2023-08-04 07:19:44.693714:
2023-08-04 07:19:44.693871: Epoch 373
2023-08-04 07:19:44.693953: Current learning rate: 0.00088
2023-08-04 07:20:43.374830: train_loss -0.9506
2023-08-04 07:20:43.374970: val_loss -0.8886
2023-08-04 07:20:43.375010: Pseudo dice [0.9085]
2023-08-04 07:20:43.375054: Epoch time: 58.68 s
2023-08-04 07:20:44.267331:
2023-08-04 07:20:44.267443: Epoch 374
2023-08-04 07:20:44.267530: Current learning rate: 0.00085
2023-08-04 07:21:42.991565: train_loss -0.9487
2023-08-04 07:21:42.991708: val_loss -0.8889
2023-08-04 07:21:42.991748: Pseudo dice [0.9092]
2023-08-04 07:21:42.991792: Epoch time: 58.72 s
2023-08-04 07:21:43.755793:
2023-08-04 07:21:43.755901: Epoch 375
2023-08-04 07:21:43.755983: Current learning rate: 0.00082
2023-08-04 07:22:42.469953: train_loss -0.9511
2023-08-04 07:22:42.470095: val_loss -0.8898
2023-08-04 07:22:42.470134: Pseudo dice [0.9099]
2023-08-04 07:22:42.470178: Epoch time: 58.71 s
2023-08-04 07:22:43.233960:
2023-08-04 07:22:43.234056: Epoch 376
2023-08-04 07:22:43.234133: Current learning rate: 0.00079
2023-08-04 07:23:41.977327: train_loss -0.9491
2023-08-04 07:23:41.977469: val_loss -0.8842
2023-08-04 07:23:41.977510: Pseudo dice [0.9065]
2023-08-04 07:23:41.977556: Epoch time: 58.74 s
2023-08-04 07:23:42.741620:
2023-08-04 07:23:42.741725: Epoch 377
2023-08-04 07:23:42.741805: Current learning rate: 0.00077
2023-08-04 07:24:41.487599: train_loss -0.9492
2023-08-04 07:24:41.487750: val_loss -0.8895
2023-08-04 07:24:41.487790: Pseudo dice [0.9102]
2023-08-04 07:24:41.487836: Epoch time: 58.75 s
2023-08-04 07:24:41.487873: Yayy! New best EMA pseudo Dice: 0.9079
2023-08-04 07:24:43.527019:
2023-08-04 07:24:43.527121: Epoch 378
2023-08-04 07:24:43.527202: Current learning rate: 0.00074
2023-08-04 07:25:42.264763: train_loss -0.9518
2023-08-04 07:25:42.264912: val_loss -0.8906
2023-08-04 07:25:42.264954: Pseudo dice [0.9109]
2023-08-04 07:25:42.265000: Epoch time: 58.74 s
2023-08-04 07:25:42.265037: Yayy! New best EMA pseudo Dice: 0.9082
2023-08-04 07:25:44.221008:
2023-08-04 07:25:44.221114: Epoch 379
2023-08-04 07:25:44.221194: Current learning rate: 0.0007
2023-08-04 07:26:42.923823: train_loss -0.9512
2023-08-04 07:26:42.923967: val_loss -0.8902
2023-08-04 07:26:42.924008: Pseudo dice [0.9105]
2023-08-04 07:26:42.924053: Epoch time: 58.7 s
2023-08-04 07:26:42.924089: Yayy! New best EMA pseudo Dice: 0.9085
2023-08-04 07:26:45.130617:
2023-08-04 07:26:45.130722: Epoch 380
2023-08-04 07:26:45.130801: Current learning rate: 0.00067
2023-08-04 07:27:43.864734: train_loss -0.9513
2023-08-04 07:27:43.864872: val_loss -0.8846
2023-08-04 07:27:43.864912: Pseudo dice [0.9068]
2023-08-04 07:27:43.864959: Epoch time: 58.73 s
2023-08-04 07:27:44.633632: