| Train accuracy = 89.648% |
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| per_face_accuracy: 0.8964884874006657 |
| mean_confidence: 0.90162826 |
| class_0_acc: 0.8309014514896867 |
| class_1_acc: 0.9787369493251846 |
| class_2_acc: 0.9244204509368054 |
| class_3_acc: 0.9623172103487064 |
| class_4_acc: 0.9210676971518534 |
| class_5_acc: 0.8517195869885879 |
| class_6_acc: 0.9219792629093522 |
| per_class_accuracy: 0.9130203727357395 |
| IoU: 0.80784581826577 |
| 1515/1515 [00:53<00:00, 28.31it/s] |
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| Test Accuracy = 86.432% |
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| per_face_accuracy: 0.864323620706919 |
| mean_confidence: 0.89635736 |
| class_0_acc: 0.7909681833732467 |
| class_1_acc: 0.9679347826086957 |
| class_2_acc: 0.9298013245033112 |
| class_3_acc: 0.8977035490605428 |
| class_4_acc: 0.9051359516616314 |
| class_5_acc: 0.7790178571428571 |
| class_6_acc: 0.8698284561049445 |
| per_class_accuracy: 0.8771985863507469 |
| IoU: 0.7578926103706184 |
| 191/191 [00:10<00:00, 18.96it/s] |
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| Unseen Accuracy (Current AI Model) = 86.64% |
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| per_face_accuracy: 0.866403162055336 |
| mean_confidence: 0.8827821 |
| class_0_acc: 0.875 |
| class_1_acc: 0.9848156182212582 |
| class_2_acc: 0.839622641509434 |
| class_3_acc: 0.9245283018867925 |
| class_4_acc: 0.7870722433460076 |
| class_5_acc: 0.8002853067047075 |
| class_6_acc: 0.9120370370370371 |
| per_class_accuracy: 0.8747658783864625 |
| IoU: 0.7264917818820532 |
| 49/49 [00:03<00:00, 13.94it/s] |
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| Unseen Accuracy (Previous AI Model) = 64.15% |
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| per_face_accuracy: 0.6415019762845849 |
| mean_confidence: 0.79006696 |
| class_0_acc: 0.5881410256410257 |
| class_1_acc: 0.93058568329718 |
| class_2_acc: 0.38207547169811323 |
| class_3_acc: 0.22641509433962265 |
| class_4_acc: 0.6273764258555133 |
| class_5_acc: 0.6433666191155493 |
| class_6_acc: 0.5462962962962963 |
| per_class_accuracy: 0.5634652308919 |
| IoU: 0.40713622181722414 |
| 49/49 [00:08<00:00, 6.12it/s] |
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