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2023-06-01 16:38:57.712064: Current learning rate: 0.0004 |
2023-06-01 16:39:56.893131: train_loss -0.8766 |
2023-06-01 16:39:56.893327: val_loss -0.8909 |
2023-06-01 16:39:56.893417: Pseudo dice [0.9076] |
2023-06-01 16:39:56.893500: Epoch time: 59.18 s |
2023-06-01 16:39:57.988633: |
2023-06-01 16:39:57.988727: Epoch 973 |
2023-06-01 16:39:57.988808: Current learning rate: 0.00039 |
2023-06-01 16:40:57.131798: train_loss -0.8777 |
2023-06-01 16:40:57.132013: val_loss -0.8775 |
2023-06-01 16:40:57.132121: Pseudo dice [0.8955] |
2023-06-01 16:40:57.132230: Epoch time: 59.14 s |
2023-06-01 16:40:58.201570: |
2023-06-01 16:40:58.201667: Epoch 974 |
2023-06-01 16:40:58.201750: Current learning rate: 0.00037 |
2023-06-01 16:41:57.376637: train_loss -0.878 |
2023-06-01 16:41:57.376822: val_loss -0.8854 |
2023-06-01 16:41:57.376923: Pseudo dice [0.9024] |
2023-06-01 16:41:57.377009: Epoch time: 59.18 s |
2023-06-01 16:41:58.606337: |
2023-06-01 16:41:58.606440: Epoch 975 |
2023-06-01 16:41:58.606527: Current learning rate: 0.00036 |
2023-06-01 16:42:57.815907: train_loss -0.8775 |
2023-06-01 16:42:57.816049: val_loss -0.8781 |
2023-06-01 16:42:57.816128: Pseudo dice [0.8967] |
2023-06-01 16:42:57.816222: Epoch time: 59.21 s |
2023-06-01 16:42:58.866508: |
2023-06-01 16:42:58.866611: Epoch 976 |
2023-06-01 16:42:58.866750: Current learning rate: 0.00035 |
2023-06-01 16:43:58.071027: train_loss -0.8795 |
2023-06-01 16:43:58.071271: val_loss -0.8709 |
2023-06-01 16:43:58.071358: Pseudo dice [0.8937] |
2023-06-01 16:43:58.071444: Epoch time: 59.21 s |
2023-06-01 16:43:59.134953: |
2023-06-01 16:43:59.135083: Epoch 977 |
2023-06-01 16:43:59.135194: Current learning rate: 0.00034 |
2023-06-01 16:44:58.328298: train_loss -0.8761 |
2023-06-01 16:44:58.328432: val_loss -0.8798 |
2023-06-01 16:44:58.328515: Pseudo dice [0.8982] |
2023-06-01 16:44:58.328611: Epoch time: 59.19 s |
2023-06-01 16:44:59.374923: |
2023-06-01 16:44:59.375201: Epoch 978 |
2023-06-01 16:44:59.375353: Current learning rate: 0.00032 |
2023-06-01 16:45:58.605832: train_loss -0.8782 |
2023-06-01 16:45:58.605988: val_loss -0.8839 |
2023-06-01 16:45:58.606064: Pseudo dice [0.8995] |
2023-06-01 16:45:58.606143: Epoch time: 59.23 s |
2023-06-01 16:45:59.688164: |
2023-06-01 16:45:59.688394: Epoch 979 |
2023-06-01 16:45:59.688499: Current learning rate: 0.00031 |
2023-06-01 16:46:58.875169: train_loss -0.879 |
2023-06-01 16:46:58.875365: val_loss -0.883 |
2023-06-01 16:46:58.875461: Pseudo dice [0.9043] |
2023-06-01 16:46:58.875553: Epoch time: 59.19 s |
2023-06-01 16:46:58.875635: Yayy! New best EMA pseudo Dice: 0.8985 |
2023-06-01 16:47:02.169361: |
2023-06-01 16:47:02.169444: Epoch 980 |
2023-06-01 16:47:02.169545: Current learning rate: 0.0003 |
2023-06-01 16:48:01.233223: train_loss -0.8774 |
2023-06-01 16:48:01.233377: val_loss -0.889 |
2023-06-01 16:48:01.233458: Pseudo dice [0.9066] |
2023-06-01 16:48:01.233553: Epoch time: 59.06 s |
2023-06-01 16:48:01.233627: Yayy! New best EMA pseudo Dice: 0.8993 |
2023-06-01 16:48:04.224960: |
2023-06-01 16:48:04.225114: Epoch 981 |
2023-06-01 16:48:04.225197: Current learning rate: 0.00028 |
2023-06-01 16:49:03.337906: train_loss -0.8736 |
2023-06-01 16:49:03.338061: val_loss -0.8883 |
2023-06-01 16:49:03.338138: Pseudo dice [0.9048] |
2023-06-01 16:49:03.338217: Epoch time: 59.11 s |
2023-06-01 16:49:03.338290: Yayy! New best EMA pseudo Dice: 0.8999 |
2023-06-01 16:49:06.238531: |
2023-06-01 16:49:06.238622: Epoch 982 |
2023-06-01 16:49:06.238721: Current learning rate: 0.00027 |
2023-06-01 16:50:05.332272: train_loss -0.8778 |
2023-06-01 16:50:05.332407: val_loss -0.8874 |
2023-06-01 16:50:05.332487: Pseudo dice [0.9022] |
2023-06-01 16:50:05.332582: Epoch time: 59.09 s |
2023-06-01 16:50:05.332661: Yayy! New best EMA pseudo Dice: 0.9001 |
2023-06-01 16:50:08.274321: |
2023-06-01 16:50:08.274425: Epoch 983 |
2023-06-01 16:50:08.274507: Current learning rate: 0.00026 |
2023-06-01 16:51:07.342933: train_loss -0.8821 |
2023-06-01 16:51:07.343068: val_loss -0.8724 |
2023-06-01 16:51:07.343211: Pseudo dice [0.8926] |
2023-06-01 16:51:07.343334: Epoch time: 59.07 s |
2023-06-01 16:51:08.458734: |
2023-06-01 16:51:08.458835: Epoch 984 |
2023-06-01 16:51:08.458916: Current learning rate: 0.00024 |
2023-06-01 16:52:07.678760: train_loss -0.8782 |
2023-06-01 16:52:07.678910: val_loss -0.8816 |
2023-06-01 16:52:07.678990: Pseudo dice [0.8996] |
2023-06-01 16:52:07.679082: Epoch time: 59.22 s |
2023-06-01 16:52:08.725795: |
2023-06-01 16:52:08.725975: Epoch 985 |
2023-06-01 16:52:08.726120: Current learning rate: 0.00023 |
2023-06-01 16:53:07.975400: train_loss -0.8796 |
2023-06-01 16:53:07.975533: val_loss -0.8781 |
2023-06-01 16:53:07.975592: Pseudo dice [0.897] |
2023-06-01 16:53:07.975654: Epoch time: 59.25 s |
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