Datasets:
pyushkevich
/
crashs_template_package

Dataset card Data Studio Files
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1.22k
2023-08-04 06:05:00.976439: Epoch time: 58.69 s
2023-08-04 06:05:01.848470:
2023-08-04 06:05:01.848586: Epoch 298
2023-08-04 06:05:01.848663: Current learning rate: 0.00292
2023-08-04 06:06:00.557283: train_loss -0.9431
2023-08-04 06:06:00.557427: val_loss -0.8845
2023-08-04 06:06:00.557469: Pseudo dice [0.9056]
2023-08-04 06:06:00.557515: Epoch time: 58.71 s
2023-08-04 06:06:01.314903:
2023-08-04 06:06:01.315020: Epoch 299
2023-08-04 06:06:01.315099: Current learning rate: 0.0029
2023-08-04 06:07:00.029296: train_loss -0.942
2023-08-04 06:07:00.029444: val_loss -0.8818
2023-08-04 06:07:00.029483: Pseudo dice [0.9041]
2023-08-04 06:07:00.029527: Epoch time: 58.72 s
2023-08-04 06:07:01.965614:
2023-08-04 06:07:01.965728: Epoch 300
2023-08-04 06:07:01.965805: Current learning rate: 0.00287
2023-08-04 06:08:00.663132: train_loss -0.9444
2023-08-04 06:08:00.663499: val_loss -0.8851
2023-08-04 06:08:00.663540: Pseudo dice [0.906]
2023-08-04 06:08:00.663586: Epoch time: 58.7 s
2023-08-04 06:08:01.431058:
2023-08-04 06:08:01.431169: Epoch 301
2023-08-04 06:08:01.431250: Current learning rate: 0.00285
2023-08-04 06:09:00.143244: train_loss -0.9449
2023-08-04 06:09:00.143386: val_loss -0.8851
2023-08-04 06:09:00.143425: Pseudo dice [0.906]
2023-08-04 06:09:00.143469: Epoch time: 58.71 s
2023-08-04 06:09:00.904585:
2023-08-04 06:09:00.904682: Epoch 302
2023-08-04 06:09:00.904761: Current learning rate: 0.00282
2023-08-04 06:09:59.624081: train_loss -0.9472
2023-08-04 06:09:59.624224: val_loss -0.8828
2023-08-04 06:09:59.624265: Pseudo dice [0.9047]
2023-08-04 06:09:59.624310: Epoch time: 58.72 s
2023-08-04 06:10:00.498833:
2023-08-04 06:10:00.498948: Epoch 303
2023-08-04 06:10:00.499024: Current learning rate: 0.00279
2023-08-04 06:10:59.217797: train_loss -0.9438
2023-08-04 06:10:59.217940: val_loss -0.884
2023-08-04 06:10:59.217979: Pseudo dice [0.9063]
2023-08-04 06:10:59.218022: Epoch time: 58.72 s
2023-08-04 06:10:59.985701:
2023-08-04 06:10:59.985811: Epoch 304
2023-08-04 06:10:59.985893: Current learning rate: 0.00277
2023-08-04 06:11:58.675657: train_loss -0.9434
2023-08-04 06:11:58.675808: val_loss -0.8827
2023-08-04 06:11:58.675847: Pseudo dice [0.9043]
2023-08-04 06:11:58.675892: Epoch time: 58.69 s
2023-08-04 06:11:59.433425:
2023-08-04 06:11:59.433532: Epoch 305
2023-08-04 06:11:59.433611: Current learning rate: 0.00274
2023-08-04 06:12:58.113970: train_loss -0.9428
2023-08-04 06:12:58.114114: val_loss -0.8797
2023-08-04 06:12:58.114154: Pseudo dice [0.9029]
2023-08-04 06:12:58.114198: Epoch time: 58.68 s
2023-08-04 06:12:58.895064:
2023-08-04 06:12:58.895280: Epoch 306
2023-08-04 06:12:58.895381: Current learning rate: 0.00272
2023-08-04 06:13:57.607367: train_loss -0.9418
2023-08-04 06:13:57.607506: val_loss -0.8833
2023-08-04 06:13:57.607545: Pseudo dice [0.9056]
2023-08-04 06:13:57.607589: Epoch time: 58.71 s
2023-08-04 06:13:58.357217:
2023-08-04 06:13:58.357322: Epoch 307
2023-08-04 06:13:58.357403: Current learning rate: 0.00269
2023-08-04 06:14:57.071742: train_loss -0.9451
2023-08-04 06:14:57.071873: val_loss -0.8843
2023-08-04 06:14:57.071911: Pseudo dice [0.9048]
2023-08-04 06:14:57.071954: Epoch time: 58.72 s
2023-08-04 06:14:57.946727:
2023-08-04 06:14:57.946827: Epoch 308
2023-08-04 06:14:57.946907: Current learning rate: 0.00266
2023-08-04 06:15:56.691149: train_loss -0.9432
2023-08-04 06:15:56.691293: val_loss -0.8813
2023-08-04 06:15:56.691335: Pseudo dice [0.9035]
2023-08-04 06:15:56.691380: Epoch time: 58.75 s
2023-08-04 06:15:57.446619:
2023-08-04 06:15:57.446726: Epoch 309
2023-08-04 06:15:57.446802: Current learning rate: 0.00264
2023-08-04 06:16:56.172401: train_loss -0.9446
2023-08-04 06:16:56.172545: val_loss -0.8867
2023-08-04 06:16:56.172584: Pseudo dice [0.9078]
2023-08-04 06:16:56.172628: Epoch time: 58.73 s
2023-08-04 06:16:56.925250:
2023-08-04 06:16:56.925412: Epoch 310
2023-08-04 06:16:56.925492: Current learning rate: 0.00261
2023-08-04 06:17:55.631989: train_loss -0.9458
2023-08-04 06:17:55.632134: val_loss -0.8825
2023-08-04 06:17:55.632174: Pseudo dice [0.9042]
2023-08-04 06:17:55.632232: Epoch time: 58.71 s
2023-08-04 06:17:56.387998:
2023-08-04 06:17:56.388103: Epoch 311
2023-08-04 06:17:56.388185: Current learning rate: 0.00259
2023-08-04 06:18:55.106832: train_loss -0.943
2023-08-04 06:18:55.106980: val_loss -0.8861
2023-08-04 06:18:55.107019: Pseudo dice [0.9068]
2023-08-04 06:18:55.107064: Epoch time: 58.72 s
2023-08-04 06:18:55.882744: