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nohup_log4
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Namespace(batch_size=1, dB=['CASME2_TIM'], flag='sf', objective_flag=1, spatial_epochs=100, spatial_size=224, temporal_epochs=40, tensorboard=False, train='./train_spatial_only.py', train_id='default_test')
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CASME2_TIM
Loaded Images into the tray...
Loaded Labels into the tray...
Train_X_shape: (237, 9, 50176)
Train_Y_shape: (237, 5)
Test_X_shape: (9, 9, 50176)
Test_Y_shape: (9, 5)
X_shape: (2133, 1, 224, 224)
y_shape: (2133, 5)
test_X_shape: (81, 1, 224, 224)
test_y_shape: (81, 5)
(237, 9, 224, 224)
(9, 9, 224, 224)
b'GeForce GTX 850M': 2594.5 MB free, 1450.0 MB used, 4044.5 MB total
Epoch 1/100
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categorical_accuracy: 0.1429 22/237 [=>............................] - ETA: 121s - loss: 1.9960 - categorical_accuracy: 0.1818 23/237 [=>............................] - ETA: 120s - loss: 1.9643 - categorical_accuracy: 0.2174 24/237 [==>...........................] - ETA: 120s - loss: 1.9545 - categorical_accuracy: 0.2083 25/237 [==>...........................] - ETA: 119s - loss: 1.9413 - categorical_accuracy: 0.2000 26/237 [==>...........................] - ETA: 119s - loss: 1.9256 - categorical_accuracy: 0.1923 27/237 [==>...........................] - ETA: 118s - loss: 1.9154 - categorical_accuracy: 0.1852 28/237 [==>...........................] - ETA: 117s - loss: 1.9056 - categorical_accuracy: 0.1786 29/237 [==>...........................] - ETA: 117s - loss: 1.8926 - categorical_accuracy: 0.1724 30/237 [==>...........................] - ETA: 116s - loss: 1.8639 - categorical_accuracy: 0.2000 31/237 [==>...........................] - ETA: 115s - loss: 1.8258 - categorical_accuracy: 0.2258 32/237 [===>..........................] - 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categorical_accuracy: 0.1905 43/237 [====>.........................] - ETA: 108s - loss: 1.8095 - categorical_accuracy: 0.1860 44/237 [====>.........................] - ETA: 108s - loss: 1.7973 - categorical_accuracy: 0.1818 45/237 [====>.........................] - ETA: 107s - loss: 1.7747 - categorical_accuracy: 0.2000 46/237 [====>.........................] - ETA: 106s - loss: 1.7745 - categorical_accuracy: 0.1957 47/237 [====>.........................] - ETA: 106s - loss: 1.7526 - categorical_accuracy: 0.2128 48/237 [=====>........................] - ETA: 105s - loss: 1.7453 - categorical_accuracy: 0.2083 49/237 [=====>........................] - ETA: 105s - loss: 1.7300 - categorical_accuracy: 0.2041 50/237 [=====>........................] - ETA: 104s - loss: 1.7491 - categorical_accuracy: 0.2000 51/237 [=====>........................] - ETA: 104s - loss: 1.7441 - categorical_accuracy: 0.1961 52/237 [=====>........................] - ETA: 103s - loss: 1.7752 - categorical_accuracy: 0.1923 53/237 [=====>........................] - 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categorical_accuracy: 0.2063 64/237 [=======>......................] - ETA: 96s - loss: 1.7425 - categorical_accuracy: 0.2188 65/237 [=======>......................] - ETA: 96s - loss: 1.7337 - categorical_accuracy: 0.2154 66/237 [=======>......................] - ETA: 96s - loss: 1.7257 - categorical_accuracy: 0.2273 67/237 [=======>......................] - ETA: 95s - loss: 1.7395 - categorical_accuracy: 0.2239 68/237 [=======>......................] - ETA: 95s - loss: 1.7309 - categorical_accuracy: 0.2353 69/237 [=======>......................] - ETA: 95s - loss: 1.7211 - categorical_accuracy: 0.2464 70/237 [=======>......................] - ETA: 94s - loss: 1.7111 - categorical_accuracy: 0.2571 71/237 [=======>......................] - ETA: 94s - loss: 1.6991 - categorical_accuracy: 0.2676 72/237 [========>.....................] - ETA: 93s - loss: 1.6947 - categorical_accuracy: 0.2639 73/237 [========>.....................] - ETA: 93s - loss: 1.7145 - categorical_accuracy: 0.2603 74/237 [========>.....................] - 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