Datasets:
ngaggion
/
ChronoRoot_nnUNet

Dataset card Data Studio Files Community
1
text
stringlengths
0
1.16k
2025-01-20 19:52:50.826296: Epoch 321
2025-01-20 19:52:50.826357: Current learning rate: 0.00706
2025-01-20 19:53:38.531677: train_loss -0.7093
2025-01-20 19:53:38.566863: val_loss -0.7036
2025-01-20 19:53:38.566917: Pseudo dice [np.float32(0.7619), np.float32(0.7683), np.float32(0.8656), np.float32(0.7641), np.float32(0.8884), np.float32(0.7619)]
2025-01-20 19:53:38.566954: Epoch time: 47.74 s
2025-01-20 19:53:39.034679:
2025-01-20 19:53:39.069236: Epoch 322
2025-01-20 19:53:39.069297: Current learning rate: 0.00705
2025-01-20 19:54:26.774404: train_loss -0.7083
2025-01-20 19:54:26.809507: val_loss -0.7226
2025-01-20 19:54:26.809563: Pseudo dice [np.float32(0.7661), np.float32(0.7342), np.float32(0.8545), np.float32(0.7477), np.float32(0.8829), np.float32(0.7728)]
2025-01-20 19:54:26.809599: Epoch time: 47.74 s
2025-01-20 19:54:27.275973:
2025-01-20 19:54:27.310468: Epoch 323
2025-01-20 19:54:27.310532: Current learning rate: 0.00704
2025-01-20 19:55:14.982511: train_loss -0.7065
2025-01-20 19:55:15.017609: val_loss -0.7074
2025-01-20 19:55:15.017664: Pseudo dice [np.float32(0.7661), np.float32(0.7516), np.float32(0.8513), np.float32(0.749), np.float32(0.8873), np.float32(0.7695)]
2025-01-20 19:55:15.017715: Epoch time: 47.71 s
2025-01-20 19:55:15.596039:
2025-01-20 19:55:15.630505: Epoch 324
2025-01-20 19:55:15.630584: Current learning rate: 0.00703
2025-01-20 19:56:03.301215: train_loss -0.7272
2025-01-20 19:56:03.336351: val_loss -0.7013
2025-01-20 19:56:03.336432: Pseudo dice [np.float32(0.7573), np.float32(0.7479), np.float32(0.8589), np.float32(0.7545), np.float32(0.8886), np.float32(0.7658)]
2025-01-20 19:56:03.336471: Epoch time: 47.71 s
2025-01-20 19:56:03.805047:
2025-01-20 19:56:03.839493: Epoch 325
2025-01-20 19:56:03.839553: Current learning rate: 0.00702
2025-01-20 19:56:51.560287: train_loss -0.7345
2025-01-20 19:56:51.595285: val_loss -0.7033
2025-01-20 19:56:51.595385: Pseudo dice [np.float32(0.7554), np.float32(0.73), np.float32(0.8638), np.float32(0.7557), np.float32(0.8925), np.float32(0.7755)]
2025-01-20 19:56:51.595434: Epoch time: 47.76 s
2025-01-20 19:56:52.063876:
2025-01-20 19:56:52.098357: Epoch 326
2025-01-20 19:56:52.098418: Current learning rate: 0.00701
2025-01-20 19:57:39.772969: train_loss -0.7197
2025-01-20 19:57:39.808145: val_loss -0.7211
2025-01-20 19:57:39.808210: Pseudo dice [np.float32(0.7623), np.float32(0.7917), np.float32(0.8622), np.float32(0.7485), np.float32(0.8883), np.float32(0.7809)]
2025-01-20 19:57:39.808253: Epoch time: 47.71 s
2025-01-20 19:57:40.278143:
2025-01-20 19:57:40.312614: Epoch 327
2025-01-20 19:57:40.312675: Current learning rate: 0.007
2025-01-20 19:58:27.945904: train_loss -0.7217
2025-01-20 19:58:27.981011: val_loss -0.7225
2025-01-20 19:58:27.981089: Pseudo dice [np.float32(0.7685), np.float32(0.7837), np.float32(0.8651), np.float32(0.7596), np.float32(0.8873), np.float32(0.7772)]
2025-01-20 19:58:27.981127: Epoch time: 47.67 s
2025-01-20 19:58:28.447441:
2025-01-20 19:58:28.481919: Epoch 328
2025-01-20 19:58:28.482008: Current learning rate: 0.00699
2025-01-20 19:59:16.124772: train_loss -0.7192
2025-01-20 19:59:16.159889: val_loss -0.7277
2025-01-20 19:59:16.159945: Pseudo dice [np.float32(0.7682), np.float32(0.7883), np.float32(0.8555), np.float32(0.7609), np.float32(0.8865), np.float32(0.779)]
2025-01-20 19:59:16.159982: Epoch time: 47.68 s
2025-01-20 19:59:16.625448:
2025-01-20 19:59:16.659950: Epoch 329
2025-01-20 19:59:16.660014: Current learning rate: 0.00698
2025-01-20 20:00:04.312173: train_loss -0.712
2025-01-20 20:00:04.347285: val_loss -0.714
2025-01-20 20:00:04.347338: Pseudo dice [np.float32(0.7607), np.float32(0.7663), np.float32(0.8526), np.float32(0.746), np.float32(0.871), np.float32(0.7639)]
2025-01-20 20:00:04.347373: Epoch time: 47.69 s
2025-01-20 20:00:04.814072:
2025-01-20 20:00:04.848570: Epoch 330
2025-01-20 20:00:04.848657: Current learning rate: 0.00697
2025-01-20 20:00:52.482624: train_loss -0.7236
2025-01-20 20:00:52.517887: val_loss -0.7137
2025-01-20 20:00:52.517946: Pseudo dice [np.float32(0.7681), np.float32(0.7663), np.float32(0.8656), np.float32(0.739), np.float32(0.9012), np.float32(0.7762)]
2025-01-20 20:00:52.517994: Epoch time: 47.67 s
2025-01-20 20:00:53.094784:
2025-01-20 20:00:53.094923: Epoch 331
2025-01-20 20:00:53.095007: Current learning rate: 0.00696
2025-01-20 20:01:40.774951: train_loss -0.7176
2025-01-20 20:01:40.810055: val_loss -0.7174
2025-01-20 20:01:40.810119: Pseudo dice [np.float32(0.7623), np.float32(0.7865), np.float32(0.858), np.float32(0.7491), np.float32(0.8968), np.float32(0.7849)]
2025-01-20 20:01:40.810154: Epoch time: 47.68 s
2025-01-20 20:01:41.277490:
2025-01-20 20:01:41.311970: Epoch 332
2025-01-20 20:01:41.312031: Current learning rate: 0.00696
2025-01-20 20:02:28.968795: train_loss -0.7202
2025-01-20 20:02:29.003938: val_loss -0.6926
2025-01-20 20:02:29.003994: Pseudo dice [np.float32(0.7514), np.float32(0.7463), np.float32(0.856), np.float32(0.7548), np.float32(0.8884), np.float32(0.7785)]
2025-01-20 20:02:29.004030: Epoch time: 47.69 s
2025-01-20 20:02:29.469563:
2025-01-20 20:02:29.504023: Epoch 333
2025-01-20 20:02:29.504112: Current learning rate: 0.00695
2025-01-20 20:03:17.207313: train_loss -0.7146
2025-01-20 20:03:17.242452: val_loss -0.7107
2025-01-20 20:03:17.242518: Pseudo dice [np.float32(0.7707), np.float32(0.7826), np.float32(0.8625), np.float32(0.7591), np.float32(0.8943), np.float32(0.7886)]
2025-01-20 20:03:17.242556: Epoch time: 47.74 s
2025-01-20 20:03:17.707509:
2025-01-20 20:03:17.742023: Epoch 334
2025-01-20 20:03:17.742098: Current learning rate: 0.00694
2025-01-20 20:04:05.404299: train_loss -0.7203
2025-01-20 20:04:05.439390: val_loss -0.703
2025-01-20 20:04:05.439444: Pseudo dice [np.float32(0.75), np.float32(0.7204), np.float32(0.8593), np.float32(0.7434), np.float32(0.9039), np.float32(0.7905)]
2025-01-20 20:04:05.439482: Epoch time: 47.7 s
2025-01-20 20:04:05.910469:
2025-01-20 20:04:05.945044: Epoch 335
2025-01-20 20:04:05.945118: Current learning rate: 0.00693