Page 17 - Read Online

Page 12 Chazhoor et al. Intell Robot 2022;2:1-19 https://dx.doi.org/10.20517/ir.2021.15

Table 5. The mean training and validation accuracies and losses for Resnet-50 architecture for 20 epochs
Mean Resnet-50 values
Epoch
Training accuracy Validation accuracy Training loss Validation loss
1 0.5515 0.6706 1.12794 1.04068
2 0.69346 0.70782 0.81024 0.96718
3 0.7455 0.7691 0.66772 0.86036
4 0.77918 0.76568 0.5758 0.82058
5 0.80062 0.77648 0.52012 0.66052
6 0.8256 0.75932 0.44886 0.85278
7 0.83992 0.74364 0.42794 1.16314
8 0.87704 0.82598 0.32214 0.60218
9 0.89198 0.82254 0.2835 0.6571
10 0.90986 0.82942 0.24506 0.62152
11 0.90324 0.83382 0.2566 0.58042
12 0.91498 0.83234 0.23156 0.63032
13 0.91182 0.81626 0.23618 0.6429
14 0.91476 0.83726 0.23086 0.65462
15 0.9151 0.83484 0.2235 0.6636
16 0.91464 0.82894 0.22348 0.70444
17 0.91684 0.8343 0.21748 0.65494
18 0.91684 0.83776 0.21546 0.6189
19 0.91708 0.83482 0.22578 0.68982
20 0.91352 0.83922 0.22412 0.61236

Table 6. The mean training and validation accuracies and losses for ResNeXt architecture for 20 epochs
Mean ResNeXt values
Epoch
Training accuracy Validation accuracy Training loss Validation loss
1 0.57454 0.71078 1.09714 0.97576
2 0.69518 0.74312 0.8304 0.87308
3 0.752 0.67498 0.66784 1.3998
4 0.79228 0.76764 0.57174 0.93114
5 0.81336 0.78234 0.52164 0.7225
6 0.83306 0.83136 0.4542 0.70478
7 0.84494 0.81374 0.42144 0.7807
8 0.88366 0.8564 0.30548 0.5644
9 0.89836 0.85442 0.28038 0.64594
10 0.90642 0.85294 0.26156 0.62974
11 0.90826 0.85834 0.2503 0.65006
12 0.9145 0.85 0.2385 0.6518
13 0.9084 0.84118 0.2411 0.64972
14 0.91084 0.8544 0.24424 0.59668
15 0.91316 0.85246 0.2417 0.55656
16 0.92564 0.84854 0.2097 0.58186
17 0.91156 0.85882 0.23282 0.58778
18 0.916 0.85688 0.22358 0.63122
19 0.91598 0.84658 0.223 0.62936
20 0.92014 0.85246 0.21606 0.65276