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2025-01-20 15:41:42.661505: Pseudo dice [np.float32(0.6662), np.float32(0.6805), np.float32(0.7999), np.float32(0.5949), np.float32(0.8292), np.float32(0.6886)] |
2025-01-20 15:41:42.661540: Epoch time: 47.73 s |
2025-01-20 15:41:42.661560: Yayy! New best EMA pseudo Dice: 0.3391999900341034 |
2025-01-20 15:41:43.519187: |
2025-01-20 15:41:43.523116: Epoch 10 |
2025-01-20 15:41:43.523222: Current learning rate: 0.00991 |
2025-01-20 15:42:31.191876: train_loss -0.5469 |
2025-01-20 15:42:31.224015: val_loss -0.5546 |
2025-01-20 15:42:31.224074: Pseudo dice [np.float32(0.6705), np.float32(0.6339), np.float32(0.8103), np.float32(0.5433), np.float32(0.8082), np.float32(0.6896)] |
2025-01-20 15:42:31.224110: Epoch time: 47.67 s |
2025-01-20 15:42:31.224173: Yayy! New best EMA pseudo Dice: 0.37450000643730164 |
2025-01-20 15:42:32.164343: |
2025-01-20 15:42:32.164400: Epoch 11 |
2025-01-20 15:42:32.164470: Current learning rate: 0.0099 |
2025-01-20 15:43:19.867610: train_loss -0.5583 |
2025-01-20 15:43:19.902778: val_loss -0.5753 |
2025-01-20 15:43:19.902835: Pseudo dice [np.float32(0.6725), np.float32(0.6576), np.float32(0.812), np.float32(0.6006), np.float32(0.8409), np.float32(0.6744)] |
2025-01-20 15:43:19.902885: Epoch time: 47.7 s |
2025-01-20 15:43:19.902906: Yayy! New best EMA pseudo Dice: 0.4081000089645386 |
2025-01-20 15:43:20.744930: |
2025-01-20 15:43:20.780175: Epoch 12 |
2025-01-20 15:43:20.780271: Current learning rate: 0.00989 |
2025-01-20 15:44:08.477949: train_loss -0.5651 |
2025-01-20 15:44:08.513060: val_loss -0.5803 |
2025-01-20 15:44:08.513115: Pseudo dice [np.float32(0.6816), np.float32(0.6857), np.float32(0.8033), np.float32(0.5985), np.float32(0.8475), np.float32(0.6952)] |
2025-01-20 15:44:08.513168: Epoch time: 47.73 s |
2025-01-20 15:44:08.513199: Yayy! New best EMA pseudo Dice: 0.4390999972820282 |
2025-01-20 15:44:09.355644: |
2025-01-20 15:44:09.359805: Epoch 13 |
2025-01-20 15:44:09.359881: Current learning rate: 0.00988 |
2025-01-20 15:44:57.023057: train_loss -0.5795 |
2025-01-20 15:44:57.023171: val_loss -0.5849 |
2025-01-20 15:44:57.023227: Pseudo dice [np.float32(0.6816), np.float32(0.6854), np.float32(0.8233), np.float32(0.598), np.float32(0.8364), np.float32(0.6509)] |
2025-01-20 15:44:57.023263: Epoch time: 47.67 s |
2025-01-20 15:44:57.023283: Yayy! New best EMA pseudo Dice: 0.46650001406669617 |
2025-01-20 15:44:57.808923: |
2025-01-20 15:44:57.812180: Epoch 14 |
2025-01-20 15:44:57.812270: Current learning rate: 0.00987 |
2025-01-20 15:45:45.468853: train_loss -0.5882 |
2025-01-20 15:45:45.468967: val_loss -0.5877 |
2025-01-20 15:45:45.469038: Pseudo dice [np.float32(0.6829), np.float32(0.7122), np.float32(0.8206), np.float32(0.5915), np.float32(0.8273), np.float32(0.6846)] |
2025-01-20 15:45:45.469082: Epoch time: 47.66 s |
2025-01-20 15:45:45.469101: Yayy! New best EMA pseudo Dice: 0.4918000102043152 |
2025-01-20 15:45:46.324024: |
2025-01-20 15:45:46.359415: Epoch 15 |
2025-01-20 15:45:46.359518: Current learning rate: 0.00986 |
2025-01-20 15:46:34.022295: train_loss -0.5877 |
2025-01-20 15:46:34.075548: val_loss -0.5809 |
2025-01-20 15:46:34.075604: Pseudo dice [np.float32(0.6757), np.float32(0.6699), np.float32(0.835), np.float32(0.5746), np.float32(0.8471), np.float32(0.7086)] |
2025-01-20 15:46:34.075641: Epoch time: 47.7 s |
2025-01-20 15:46:34.075662: Yayy! New best EMA pseudo Dice: 0.5145000219345093 |
2025-01-20 15:46:34.934271: |
2025-01-20 15:46:34.936938: Epoch 16 |
2025-01-20 15:46:34.937030: Current learning rate: 0.00986 |
2025-01-20 15:47:22.604002: train_loss -0.5969 |
2025-01-20 15:47:22.639189: val_loss -0.6204 |
2025-01-20 15:47:22.639246: Pseudo dice [np.float32(0.6913), np.float32(0.7071), np.float32(0.8261), np.float32(0.5947), np.float32(0.8406), np.float32(0.7112)] |
2025-01-20 15:47:22.639282: Epoch time: 47.67 s |
2025-01-20 15:47:22.639304: Yayy! New best EMA pseudo Dice: 0.5358999967575073 |
2025-01-20 15:47:23.491464: |
2025-01-20 15:47:23.494297: Epoch 17 |
2025-01-20 15:47:23.494387: Current learning rate: 0.00985 |
2025-01-20 15:48:11.178198: train_loss -0.6009 |
2025-01-20 15:48:11.213480: val_loss -0.6165 |
2025-01-20 15:48:11.213564: Pseudo dice [np.float32(0.6867), np.float32(0.727), np.float32(0.8184), np.float32(0.6427), np.float32(0.8439), np.float32(0.6984)] |
2025-01-20 15:48:11.213608: Epoch time: 47.69 s |
2025-01-20 15:48:11.213634: Yayy! New best EMA pseudo Dice: 0.555899977684021 |
2025-01-20 15:48:12.070802: |
2025-01-20 15:48:12.106088: Epoch 18 |
2025-01-20 15:48:12.106153: Current learning rate: 0.00984 |
2025-01-20 15:49:00.055808: train_loss -0.6084 |
2025-01-20 15:49:00.056000: val_loss -0.6148 |
2025-01-20 15:49:00.056059: Pseudo dice [np.float32(0.6865), np.float32(0.689), np.float32(0.8167), np.float32(0.6208), np.float32(0.8378), np.float32(0.7118)] |
2025-01-20 15:49:00.056095: Epoch time: 47.99 s |
2025-01-20 15:49:00.056136: Yayy! New best EMA pseudo Dice: 0.5730000138282776 |
2025-01-20 15:49:00.989646: |
2025-01-20 15:49:00.989701: Epoch 19 |
2025-01-20 15:49:00.989780: Current learning rate: 0.00983 |
2025-01-20 15:49:48.728596: train_loss -0.615 |
2025-01-20 15:49:48.763738: val_loss -0.6305 |
2025-01-20 15:49:48.763816: Pseudo dice [np.float32(0.713), np.float32(0.7058), np.float32(0.8239), np.float32(0.6407), np.float32(0.8525), np.float32(0.6969)] |
2025-01-20 15:49:48.763856: Epoch time: 47.74 s |
2025-01-20 15:49:48.763891: Yayy! New best EMA pseudo Dice: 0.5896000266075134 |
2025-01-20 15:49:49.612595: |
2025-01-20 15:49:49.647938: Epoch 20 |
2025-01-20 15:49:49.648021: Current learning rate: 0.00982 |
2025-01-20 15:50:37.306161: train_loss -0.6174 |
2025-01-20 15:50:37.306343: val_loss -0.642 |
2025-01-20 15:50:37.306388: Pseudo dice [np.float32(0.7253), np.float32(0.7126), np.float32(0.8322), np.float32(0.7268), np.float32(0.8446), np.float32(0.7215)] |
2025-01-20 15:50:37.306429: Epoch time: 47.69 s |
2025-01-20 15:50:37.306450: Yayy! New best EMA pseudo Dice: 0.6067000031471252 |
2025-01-20 15:50:38.161628: |
2025-01-20 15:50:38.164491: Epoch 21 |
2025-01-20 15:50:38.164574: Current learning rate: 0.00981 |
2025-01-20 15:51:25.796743: train_loss -0.6166 |
2025-01-20 15:51:25.831941: val_loss -0.5962 |
2025-01-20 15:51:25.832023: Pseudo dice [np.float32(0.6832), np.float32(0.6638), np.float32(0.825), np.float32(0.5606), np.float32(0.8444), np.float32(0.7129)] |
2025-01-20 15:51:25.832060: Epoch time: 47.64 s |
2025-01-20 15:51:25.832081: Yayy! New best EMA pseudo Dice: 0.6175000071525574 |
2025-01-20 15:51:26.659992: |