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2025-01-20 16:01:57.351502: Pseudo dice [np.float32(0.6977), np.float32(0.6961), np.float32(0.8466), np.float32(0.6303), np.float32(0.8571), np.float32(0.7252)] |
2025-01-20 16:01:57.351536: Epoch time: 47.73 s |
2025-01-20 16:01:57.351556: Yayy! New best EMA pseudo Dice: 0.7214000225067139 |
2025-01-20 16:01:58.201844: |
2025-01-20 16:01:58.201900: Epoch 35 |
2025-01-20 16:01:58.201970: Current learning rate: 0.00968 |
2025-01-20 16:02:45.923149: train_loss -0.6514 |
2025-01-20 16:02:45.958350: val_loss -0.6545 |
2025-01-20 16:02:45.958426: Pseudo dice [np.float32(0.701), np.float32(0.7355), np.float32(0.8405), np.float32(0.7013), np.float32(0.8467), np.float32(0.7281)] |
2025-01-20 16:02:45.958484: Epoch time: 47.72 s |
2025-01-20 16:02:45.958518: Yayy! New best EMA pseudo Dice: 0.7250999808311462 |
2025-01-20 16:02:46.801467: |
2025-01-20 16:02:46.836858: Epoch 36 |
2025-01-20 16:02:46.836950: Current learning rate: 0.00968 |
2025-01-20 16:03:34.540359: train_loss -0.646 |
2025-01-20 16:03:34.575465: val_loss -0.6594 |
2025-01-20 16:03:34.575524: Pseudo dice [np.float32(0.7224), np.float32(0.7359), np.float32(0.8364), np.float32(0.6825), np.float32(0.8481), np.float32(0.7275)] |
2025-01-20 16:03:34.575567: Epoch time: 47.74 s |
2025-01-20 16:03:34.575594: Yayy! New best EMA pseudo Dice: 0.7285000085830688 |
2025-01-20 16:03:35.421541: |
2025-01-20 16:03:35.424612: Epoch 37 |
2025-01-20 16:03:35.424695: Current learning rate: 0.00967 |
2025-01-20 16:04:23.151501: train_loss -0.6575 |
2025-01-20 16:04:23.151774: val_loss -0.6467 |
2025-01-20 16:04:23.151829: Pseudo dice [np.float32(0.7156), np.float32(0.739), np.float32(0.8333), np.float32(0.7073), np.float32(0.8708), np.float32(0.7406)] |
2025-01-20 16:04:23.151888: Epoch time: 47.73 s |
2025-01-20 16:04:23.151922: Yayy! New best EMA pseudo Dice: 0.7324000000953674 |
2025-01-20 16:04:24.011777: |
2025-01-20 16:04:24.046946: Epoch 38 |
2025-01-20 16:04:24.047036: Current learning rate: 0.00966 |
2025-01-20 16:05:11.765677: train_loss -0.6571 |
2025-01-20 16:05:11.800823: val_loss -0.6643 |
2025-01-20 16:05:11.800904: Pseudo dice [np.float32(0.7212), np.float32(0.7249), np.float32(0.8375), np.float32(0.7208), np.float32(0.8738), np.float32(0.7341)] |
2025-01-20 16:05:11.800941: Epoch time: 47.75 s |
2025-01-20 16:05:11.800961: Yayy! New best EMA pseudo Dice: 0.7361000180244446 |
2025-01-20 16:05:12.650535: |
2025-01-20 16:05:12.650725: Epoch 39 |
2025-01-20 16:05:12.650786: Current learning rate: 0.00965 |
2025-01-20 16:06:00.381109: train_loss -0.6512 |
2025-01-20 16:06:00.381346: val_loss -0.6657 |
2025-01-20 16:06:00.381388: Pseudo dice [np.float32(0.7263), np.float32(0.7316), np.float32(0.8317), np.float32(0.6926), np.float32(0.8668), np.float32(0.7438)] |
2025-01-20 16:06:00.381443: Epoch time: 47.73 s |
2025-01-20 16:06:00.381474: Yayy! New best EMA pseudo Dice: 0.7390000224113464 |
2025-01-20 16:06:01.236791: |
2025-01-20 16:06:01.272063: Epoch 40 |
2025-01-20 16:06:01.272124: Current learning rate: 0.00964 |
2025-01-20 16:06:48.988377: train_loss -0.663 |
2025-01-20 16:06:48.988547: val_loss -0.6406 |
2025-01-20 16:06:48.988598: Pseudo dice [np.float32(0.7179), np.float32(0.7224), np.float32(0.8444), np.float32(0.7241), np.float32(0.8564), np.float32(0.7457)] |
2025-01-20 16:06:48.988634: Epoch time: 47.75 s |
2025-01-20 16:06:48.988659: Yayy! New best EMA pseudo Dice: 0.7419000267982483 |
2025-01-20 16:06:49.846577: |
2025-01-20 16:06:49.881884: Epoch 41 |
2025-01-20 16:06:49.881964: Current learning rate: 0.00963 |
2025-01-20 16:07:37.546313: train_loss -0.6536 |
2025-01-20 16:07:37.581426: val_loss -0.64 |
2025-01-20 16:07:37.581512: Pseudo dice [np.float32(0.7273), np.float32(0.7306), np.float32(0.84), np.float32(0.6601), np.float32(0.8742), np.float32(0.759)] |
2025-01-20 16:07:37.581582: Epoch time: 47.7 s |
2025-01-20 16:07:37.581655: Yayy! New best EMA pseudo Dice: 0.7443000078201294 |
2025-01-20 16:07:38.522135: |
2025-01-20 16:07:38.524122: Epoch 42 |
2025-01-20 16:07:38.524213: Current learning rate: 0.00962 |
2025-01-20 16:08:26.239573: train_loss -0.6753 |
2025-01-20 16:08:26.274759: val_loss -0.6618 |
2025-01-20 16:08:26.274822: Pseudo dice [np.float32(0.7248), np.float32(0.7225), np.float32(0.8424), np.float32(0.7133), np.float32(0.8529), np.float32(0.7441)] |
2025-01-20 16:08:26.274862: Epoch time: 47.72 s |
2025-01-20 16:08:26.274882: Yayy! New best EMA pseudo Dice: 0.7465000152587891 |
2025-01-20 16:08:27.109404: |
2025-01-20 16:08:27.113837: Epoch 43 |
2025-01-20 16:08:27.113927: Current learning rate: 0.00961 |
2025-01-20 16:09:14.880189: train_loss -0.6537 |
2025-01-20 16:09:14.915407: val_loss -0.6509 |
2025-01-20 16:09:14.915475: Pseudo dice [np.float32(0.7298), np.float32(0.7314), np.float32(0.845), np.float32(0.7297), np.float32(0.8691), np.float32(0.7497)] |
2025-01-20 16:09:14.915519: Epoch time: 47.77 s |
2025-01-20 16:09:14.915552: Yayy! New best EMA pseudo Dice: 0.7494000196456909 |
2025-01-20 16:09:15.764732: |
2025-01-20 16:09:15.800120: Epoch 44 |
2025-01-20 16:09:15.800219: Current learning rate: 0.0096 |
2025-01-20 16:10:03.578339: train_loss -0.6613 |
2025-01-20 16:10:03.578424: val_loss -0.6454 |
2025-01-20 16:10:03.578488: Pseudo dice [np.float32(0.7417), np.float32(0.7671), np.float32(0.8439), np.float32(0.7153), np.float32(0.8666), np.float32(0.7379)] |
2025-01-20 16:10:03.578524: Epoch time: 47.81 s |
2025-01-20 16:10:03.578544: Yayy! New best EMA pseudo Dice: 0.7523999810218811 |
2025-01-20 16:10:04.360697: |
2025-01-20 16:10:04.362422: Epoch 45 |
2025-01-20 16:10:04.362483: Current learning rate: 0.00959 |
2025-01-20 16:10:52.105711: train_loss -0.666 |
2025-01-20 16:10:52.107986: val_loss -0.6394 |
2025-01-20 16:10:52.108044: Pseudo dice [np.float32(0.7206), np.float32(0.7197), np.float32(0.8386), np.float32(0.7273), np.float32(0.8661), np.float32(0.7264)] |
2025-01-20 16:10:52.108093: Epoch time: 47.75 s |
2025-01-20 16:10:52.108115: Yayy! New best EMA pseudo Dice: 0.7537999749183655 |
2025-01-20 16:10:52.943268: |
2025-01-20 16:10:52.978643: Epoch 46 |
2025-01-20 16:10:52.978724: Current learning rate: 0.00959 |
2025-01-20 16:11:40.749856: train_loss -0.6556 |
2025-01-20 16:11:40.784957: val_loss -0.6564 |
2025-01-20 16:11:40.785040: Pseudo dice [np.float32(0.7284), np.float32(0.734), np.float32(0.8369), np.float32(0.7127), np.float32(0.8698), np.float32(0.7462)] |
2025-01-20 16:11:40.785076: Epoch time: 47.81 s |
2025-01-20 16:11:40.785097: Yayy! New best EMA pseudo Dice: 0.7555000185966492 |
2025-01-20 16:11:41.613911: |