Datasets:
pyushkevich
/
crashs_template_package

Dataset card Data Studio Files Community
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1.22k
2023-08-04 07:27:44.633738: Epoch 381
2023-08-04 07:27:44.633818: Current learning rate: 0.00064
2023-08-04 07:28:43.361497: train_loss -0.9491
2023-08-04 07:28:43.361642: val_loss -0.8873
2023-08-04 07:28:43.361681: Pseudo dice [0.9087]
2023-08-04 07:28:43.361725: Epoch time: 58.73 s
2023-08-04 07:28:44.137272:
2023-08-04 07:28:44.137379: Epoch 382
2023-08-04 07:28:44.137461: Current learning rate: 0.00061
2023-08-04 07:29:42.834518: train_loss -0.9505
2023-08-04 07:29:42.834671: val_loss -0.8851
2023-08-04 07:29:42.834711: Pseudo dice [0.9073]
2023-08-04 07:29:42.834758: Epoch time: 58.7 s
2023-08-04 07:29:43.608900:
2023-08-04 07:29:43.609008: Epoch 383
2023-08-04 07:29:43.609087: Current learning rate: 0.00058
2023-08-04 07:30:42.332400: train_loss -0.9505
2023-08-04 07:30:42.332554: val_loss -0.8838
2023-08-04 07:30:42.332614: Pseudo dice [0.9064]
2023-08-04 07:30:42.332660: Epoch time: 58.72 s
2023-08-04 07:30:43.107871:
2023-08-04 07:30:43.107976: Epoch 384
2023-08-04 07:30:43.108056: Current learning rate: 0.00055
2023-08-04 07:31:41.827814: train_loss -0.951
2023-08-04 07:31:41.827955: val_loss -0.8915
2023-08-04 07:31:41.827994: Pseudo dice [0.9119]
2023-08-04 07:31:41.828037: Epoch time: 58.72 s
2023-08-04 07:31:42.720367:
2023-08-04 07:31:42.720479: Epoch 385
2023-08-04 07:31:42.720557: Current learning rate: 0.00052
2023-08-04 07:32:41.418311: train_loss -0.9538
2023-08-04 07:32:41.418457: val_loss -0.8839
2023-08-04 07:32:41.418498: Pseudo dice [0.9058]
2023-08-04 07:32:41.418542: Epoch time: 58.7 s
2023-08-04 07:32:42.202622:
2023-08-04 07:32:42.202727: Epoch 386
2023-08-04 07:32:42.202806: Current learning rate: 0.00049
2023-08-04 07:33:40.921396: train_loss -0.954
2023-08-04 07:33:40.921536: val_loss -0.8873
2023-08-04 07:33:40.921575: Pseudo dice [0.9088]
2023-08-04 07:33:40.921619: Epoch time: 58.72 s
2023-08-04 07:33:41.695507:
2023-08-04 07:33:41.695621: Epoch 387
2023-08-04 07:33:41.695699: Current learning rate: 0.00046
2023-08-04 07:34:40.403565: train_loss -0.9501
2023-08-04 07:34:40.403708: val_loss -0.885
2023-08-04 07:34:40.403750: Pseudo dice [0.9069]
2023-08-04 07:34:40.403796: Epoch time: 58.71 s
2023-08-04 07:34:41.188709:
2023-08-04 07:34:41.188824: Epoch 388
2023-08-04 07:34:41.188943: Current learning rate: 0.00043
2023-08-04 07:35:39.916924: train_loss -0.9514
2023-08-04 07:35:39.917065: val_loss -0.8862
2023-08-04 07:35:39.917104: Pseudo dice [0.9075]
2023-08-04 07:35:39.917148: Epoch time: 58.73 s
2023-08-04 07:35:40.704922:
2023-08-04 07:35:40.705022: Epoch 389
2023-08-04 07:35:40.705100: Current learning rate: 0.00039
2023-08-04 07:36:39.417642: train_loss -0.9504
2023-08-04 07:36:39.417786: val_loss -0.8813
2023-08-04 07:36:39.417827: Pseudo dice [0.9043]
2023-08-04 07:36:39.417874: Epoch time: 58.71 s
2023-08-04 07:36:40.317936:
2023-08-04 07:36:40.318052: Epoch 390
2023-08-04 07:36:40.318132: Current learning rate: 0.00036
2023-08-04 07:37:39.048777: train_loss -0.9528
2023-08-04 07:37:39.048922: val_loss -0.8864
2023-08-04 07:37:39.048962: Pseudo dice [0.9081]
2023-08-04 07:37:39.049006: Epoch time: 58.73 s
2023-08-04 07:37:39.826051:
2023-08-04 07:37:39.826159: Epoch 391
2023-08-04 07:37:39.826241: Current learning rate: 0.00033
2023-08-04 07:38:38.535689: train_loss -0.9517
2023-08-04 07:38:38.536100: val_loss -0.8864
2023-08-04 07:38:38.536140: Pseudo dice [0.9081]
2023-08-04 07:38:38.536187: Epoch time: 58.71 s
2023-08-04 07:38:39.321640:
2023-08-04 07:38:39.321748: Epoch 392
2023-08-04 07:38:39.321831: Current learning rate: 0.0003
2023-08-04 07:39:38.027032: train_loss -0.9512
2023-08-04 07:39:38.027170: val_loss -0.8843
2023-08-04 07:39:38.027209: Pseudo dice [0.9069]
2023-08-04 07:39:38.027253: Epoch time: 58.71 s
2023-08-04 07:39:38.809826:
2023-08-04 07:39:38.809932: Epoch 393
2023-08-04 07:39:38.810010: Current learning rate: 0.00026
2023-08-04 07:40:37.531125: train_loss -0.9524
2023-08-04 07:40:37.531262: val_loss -0.883
2023-08-04 07:40:37.531303: Pseudo dice [0.9058]
2023-08-04 07:40:37.531348: Epoch time: 58.72 s
2023-08-04 07:40:38.347410:
2023-08-04 07:40:38.347516: Epoch 394
2023-08-04 07:40:38.347595: Current learning rate: 0.00023
2023-08-04 07:41:37.071893: train_loss -0.9492
2023-08-04 07:41:37.072039: val_loss -0.8833
2023-08-04 07:41:37.072079: Pseudo dice [0.9054]
2023-08-04 07:41:37.072125: Epoch time: 58.73 s
2023-08-04 07:41:37.974929:
2023-08-04 07:41:37.975038: Epoch 395
2023-08-04 07:41:37.975116: Current learning rate: 0.00019