Table 4

Dynamic hyperparameter for Task2.

Input 5200 image (ACA & SCC) (4160 image for training & 1040 for validation) (balanced training samples 1120 image)

Epoch Train loss Train accuracy Test loss Test accuracy Test precision Test recall Test F1-score EWC penalty EWC lambda Learning rate Time
1 14864.484 74.6% 0.2973 92.21% 92% 92% 92% 743.193338 14863.866752 0.0001 29s
2 14443.382 89.2% 0.1494 94.9% 95% 95% 95% 722.157739 14443.154785 0.0001 29s
3 14037.938 89.91% 0.1677 90.0% 93% 90% 91% 701.888331 14037.766619 0.0001 29s
4 13645.523 90.89% 0.1263 92.69% 95% 95% 95% 682.268936 13645.378714 0.0001 30s
5 13264.492 90.8% 0.1095 94.71% 95% 94% 95% 663.243091 13264.861816 0.0001 30s
6 12895.49 90.89% 0.1087 93.65% 95% 94% 94% 644.768311 12895.366228 0.0001 31s
7 12536.491 92.28% 0.151 91.06% 94% 94% 94% 626.818920 12536.378409 0.0001 31s
8 12187.493 92.01% 0.0972 93.75% 95% 94% 94% 609.369034 12187.380676 0.0001 30s
9 11848.141 91.62% 0.1574 92.8% 94% 91% 92% 592.401342 11848.026838 0.0001 30s
10 11517.868 92.99% 0.1226 92.02% 94% 92% 94% 575.888551 11517.771014 0.0001 30s
11 11196.358 92.68% 0.108 93.56% 95% 94% 94% 559.812961 11196.259225 0.00005 30s
12 10959.762 92.93% 0.1084 96.44% 96% 95% 96% 547.982710 10959.654201 0.00005 30s
13 10804.506 93.12% 0.0942 94.52% 95% 95% 95% 540.222128 10804.424360 0.00005 31s
14 10650.548 93.12% 0.1069 92.88% 94% 93% 93% 532.524924 10650.498483 0.00005 31s
15 10497.975 93.21% 0.1076 95.87% 96% 95% 96% 524.898781 10497.975612 0.000025 32s
16 10384.153 93.75% 0.096 95.19% 96% 95% 96% 519.202675 10384.053502 0.000025 31s
17 10308.631 94.73% 0.0724 96.15% 97% 96% 96% 515.428555 10308.571097 0.000025 31s

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