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2025-01-20 15:51:26.660055: Epoch 22 |
2025-01-20 15:51:26.660140: Current learning rate: 0.0098 |
2025-01-20 15:52:14.264678: train_loss -0.6214 |
2025-01-20 15:52:14.299847: val_loss -0.6475 |
2025-01-20 15:52:14.299966: Pseudo dice [np.float32(0.7123), np.float32(0.7098), np.float32(0.8293), np.float32(0.6769), np.float32(0.8608), np.float32(0.7364)] |
2025-01-20 15:52:14.300035: Epoch time: 47.61 s |
2025-01-20 15:52:14.300070: Yayy! New best EMA pseudo Dice: 0.6312000155448914 |
2025-01-20 15:52:15.135537: |
2025-01-20 15:52:15.170798: Epoch 23 |
2025-01-20 15:52:15.170874: Current learning rate: 0.00979 |
2025-01-20 15:53:02.820495: train_loss -0.635 |
2025-01-20 15:53:02.855600: val_loss -0.6412 |
2025-01-20 15:53:02.855655: Pseudo dice [np.float32(0.7112), np.float32(0.7412), np.float32(0.8264), np.float32(0.6627), np.float32(0.8471), np.float32(0.7096)] |
2025-01-20 15:53:02.855694: Epoch time: 47.69 s |
2025-01-20 15:53:02.855722: Yayy! New best EMA pseudo Dice: 0.6430000066757202 |
2025-01-20 15:53:03.688585: |
2025-01-20 15:53:03.688769: Epoch 24 |
2025-01-20 15:53:03.688843: Current learning rate: 0.00978 |
2025-01-20 15:53:51.382452: train_loss -0.6228 |
2025-01-20 15:53:51.417610: val_loss -0.6369 |
2025-01-20 15:53:51.417665: Pseudo dice [np.float32(0.7176), np.float32(0.7145), np.float32(0.8351), np.float32(0.6745), np.float32(0.8647), np.float32(0.7008)] |
2025-01-20 15:53:51.417749: Epoch time: 47.69 s |
2025-01-20 15:53:51.417779: Yayy! New best EMA pseudo Dice: 0.6539000272750854 |
2025-01-20 15:53:52.259781: |
2025-01-20 15:53:52.295186: Epoch 25 |
2025-01-20 15:53:52.295275: Current learning rate: 0.00977 |
2025-01-20 15:54:39.975120: train_loss -0.6267 |
2025-01-20 15:54:40.010238: val_loss -0.6362 |
2025-01-20 15:54:40.010294: Pseudo dice [np.float32(0.7163), np.float32(0.7333), np.float32(0.8233), np.float32(0.6743), np.float32(0.8629), np.float32(0.7117)] |
2025-01-20 15:54:40.010331: Epoch time: 47.72 s |
2025-01-20 15:54:40.010352: Yayy! New best EMA pseudo Dice: 0.6638000011444092 |
2025-01-20 15:54:40.944248: |
2025-01-20 15:54:40.947342: Epoch 26 |
2025-01-20 15:54:40.947447: Current learning rate: 0.00977 |
2025-01-20 15:55:28.662801: train_loss -0.6286 |
2025-01-20 15:55:28.697967: val_loss -0.6251 |
2025-01-20 15:55:28.698028: Pseudo dice [np.float32(0.7059), np.float32(0.6835), np.float32(0.8284), np.float32(0.6223), np.float32(0.8581), np.float32(0.7055)] |
2025-01-20 15:55:28.698064: Epoch time: 47.72 s |
2025-01-20 15:55:28.698086: Yayy! New best EMA pseudo Dice: 0.670799970626831 |
2025-01-20 15:55:29.529037: |
2025-01-20 15:55:29.529130: Epoch 27 |
2025-01-20 15:55:29.529212: Current learning rate: 0.00976 |
2025-01-20 15:56:17.207110: train_loss -0.6346 |
2025-01-20 15:56:17.242345: val_loss -0.6465 |
2025-01-20 15:56:17.242488: Pseudo dice [np.float32(0.7221), np.float32(0.7626), np.float32(0.835), np.float32(0.6936), np.float32(0.866), np.float32(0.7492)] |
2025-01-20 15:56:17.242524: Epoch time: 47.68 s |
2025-01-20 15:56:17.242548: Yayy! New best EMA pseudo Dice: 0.680899977684021 |
2025-01-20 15:56:18.077879: |
2025-01-20 15:56:18.113196: Epoch 28 |
2025-01-20 15:56:18.113269: Current learning rate: 0.00975 |
2025-01-20 15:57:05.804224: train_loss -0.6328 |
2025-01-20 15:57:05.861735: val_loss -0.6195 |
2025-01-20 15:57:05.861793: Pseudo dice [np.float32(0.6927), np.float32(0.6873), np.float32(0.8378), np.float32(0.6513), np.float32(0.8538), np.float32(0.7119)] |
2025-01-20 15:57:05.861832: Epoch time: 47.73 s |
2025-01-20 15:57:05.861854: Yayy! New best EMA pseudo Dice: 0.6866999864578247 |
2025-01-20 15:57:06.702485: |
2025-01-20 15:57:06.703529: Epoch 29 |
2025-01-20 15:57:06.703617: Current learning rate: 0.00974 |
2025-01-20 15:57:54.382106: train_loss -0.6333 |
2025-01-20 15:57:54.382370: val_loss -0.6243 |
2025-01-20 15:57:54.382434: Pseudo dice [np.float32(0.718), np.float32(0.7634), np.float32(0.825), np.float32(0.6907), np.float32(0.866), np.float32(0.7469)] |
2025-01-20 15:57:54.382479: Epoch time: 47.68 s |
2025-01-20 15:57:54.382508: Yayy! New best EMA pseudo Dice: 0.6948999762535095 |
2025-01-20 15:57:55.233261: |
2025-01-20 15:57:55.268539: Epoch 30 |
2025-01-20 15:57:55.268612: Current learning rate: 0.00973 |
2025-01-20 15:58:42.946293: train_loss -0.6361 |
2025-01-20 15:58:42.981480: val_loss -0.6615 |
2025-01-20 15:58:42.981542: Pseudo dice [np.float32(0.73), np.float32(0.7726), np.float32(0.8298), np.float32(0.6995), np.float32(0.8574), np.float32(0.7477)] |
2025-01-20 15:58:42.981589: Epoch time: 47.71 s |
2025-01-20 15:58:42.981630: Yayy! New best EMA pseudo Dice: 0.7027000188827515 |
2025-01-20 15:58:43.829051: |
2025-01-20 15:58:43.831903: Epoch 31 |
2025-01-20 15:58:43.831976: Current learning rate: 0.00972 |
2025-01-20 15:59:31.490842: train_loss -0.6526 |
2025-01-20 15:59:31.490938: val_loss -0.6463 |
2025-01-20 15:59:31.490988: Pseudo dice [np.float32(0.7231), np.float32(0.7441), np.float32(0.8345), np.float32(0.7282), np.float32(0.8694), np.float32(0.7504)] |
2025-01-20 15:59:31.491041: Epoch time: 47.66 s |
2025-01-20 15:59:31.491077: Yayy! New best EMA pseudo Dice: 0.7099000215530396 |
2025-01-20 15:59:32.270681: |
2025-01-20 15:59:32.270921: Epoch 32 |
2025-01-20 15:59:32.270978: Current learning rate: 0.00971 |
2025-01-20 16:00:19.966604: train_loss -0.6428 |
2025-01-20 16:00:20.001844: val_loss -0.6424 |
2025-01-20 16:00:20.001918: Pseudo dice [np.float32(0.7292), np.float32(0.7306), np.float32(0.8297), np.float32(0.6996), np.float32(0.8674), np.float32(0.7486)] |
2025-01-20 16:00:20.001978: Epoch time: 47.7 s |
2025-01-20 16:00:20.002008: Yayy! New best EMA pseudo Dice: 0.7156999707221985 |
2025-01-20 16:00:20.849670: |
2025-01-20 16:00:20.853057: Epoch 33 |
2025-01-20 16:00:20.853143: Current learning rate: 0.0097 |
2025-01-20 16:01:08.561900: train_loss -0.6466 |
2025-01-20 16:01:08.639465: val_loss -0.6439 |
2025-01-20 16:01:08.639521: Pseudo dice [np.float32(0.717), np.float32(0.7181), np.float32(0.8348), np.float32(0.6454), np.float32(0.8569), np.float32(0.7258)] |
2025-01-20 16:01:08.639557: Epoch time: 47.71 s |
2025-01-20 16:01:08.639594: Yayy! New best EMA pseudo Dice: 0.7190999984741211 |
2025-01-20 16:01:09.587070: |
2025-01-20 16:01:09.622417: Epoch 34 |
2025-01-20 16:01:09.622521: Current learning rate: 0.00969 |
2025-01-20 16:01:57.316416: train_loss -0.649 |
2025-01-20 16:01:57.351414: val_loss -0.643 |