WBC's Object Detection Using YOLO 11



Here are links to the project's key components:


Detailed Epoch Training Metrics and Performance:



Error

Error Error

Error Error


Training Table:



epoch time train/box_loss train/cls_loss train/dfl_loss metrics/precision(B) metrics/recall(B) metrics/mAP50(B) metrics/mAP50-95(B) val/box_loss val/cls_loss val/dfl_loss lr/pg0 lr/pg1 lr/pg2
1 1225.8 0.5785 1.75297 1.08068 0.6 0.62972 0.61453 0.55067 0.4199 1.05484 0.95511 0.0033326 0.0033326 0.0033326
2 2403.03 0.59321 1.23248 1.05358 0.71724 0.65277 0.67417 0.61082 0.39979 0.8582 0.94748 0.00644596 0.00644596 0.00644596
3 3568.61 0.62203 1.25773 1.06832 0.64469 0.6843 0.67317 0.60835 0.40479 0.86759 0.94739 0.00933931 0.00933931 0.00933931
4 4728.7 0.6031 1.22644 1.0543 0.64325 0.73177 0.7123 0.65285 0.36712 0.77695 0.91692 0.00901 0.00901 0.00901
5 5891.02 0.55723 1.10351 1.02558 0.67826 0.76898 0.76784 0.7113 0.36538 0.6962 0.91117 0.00868 0.00868 0.00868
6 7050.42 0.53511 1.02332 1.01353 0.71972 0.75886 0.7828 0.72744 0.34963 0.66328 0.90228 0.00835 0.00835 0.00835
7 8210.83 0.52106 0.97748 1.00739 0.75721 0.78366 0.80938 0.75452 0.34386 0.61477 0.89701 0.00802 0.00802 0.00802
8 9370.44 0.50547 0.92887 0.99863 0.75901 0.78151 0.816 0.76511 0.33969 0.58727 0.89309 0.00769 0.00769 0.00769
9 10530.5 0.5004 0.88841 0.99572 0.7864 0.79446 0.83539 0.78426 0.33478 0.55494 0.88795 0.00736 0.00736 0.00736
10 11690.0 0.49209 0.86371 0.98957 0.79387 0.79622 0.84387 0.79363 0.32919 0.53887 0.8845 0.00703 0.00703 0.00703
11 12849.8 0.48302 0.83302 0.98588 0.79866 0.81537 0.85989 0.81009 0.32787 0.51316 0.8848 0.0067 0.0067 0.0067
12 14010.8 0.47592 0.81387 0.98145 0.81196 0.81733 0.8645 0.81516 0.32715 0.50135 0.88487 0.00637 0.00637 0.00637
13 15171.5 0.47145 0.78607 0.9793 0.82138 0.82008 0.87186 0.8235 0.32388 0.48497 0.88204 0.00604 0.00604 0.00604
14 16332.8 0.46274 0.77234 0.97432 0.83155 0.81772 0.87905 0.83021 0.32209 0.4753 0.87996 0.00571 0.00571 0.00571
15 17494.5 0.46113 0.75605 0.97323 0.83902 0.82531 0.88466 0.83662 0.31954 0.46565 0.87837 0.00538 0.00538 0.00538
16 18654.4 0.45568 0.72811 0.97247 0.83884 0.82721 0.88786 0.84115 0.31728 0.45373 0.87953 0.00505 0.00505 0.00505
17 19817.9 0.45402 0.71188 0.97277 0.84373 0.83899 0.89273 0.84548 0.31625 0.44539 0.87759 0.00472 0.00472 0.00472
18 20978.4 0.44381 0.68987 0.96636 0.84334 0.84417 0.89781 0.85109 0.31435 0.43436 0.87417 0.00439 0.00439 0.00439
19 22136.6 0.44103 0.67166 0.96534 0.84546 0.85127 0.90165 0.85569 0.31233 0.42721 0.87207 0.00406 0.00406 0.00406
20 23297.2 0.44011 0.65134 0.96436 0.85408 0.8512 0.90539 0.85951 0.31186 0.41928 0.8712 0.00373 0.00373 0.00373
21 24452.3 0.3374 0.51952 0.88793 0.85541 0.8536 0.90766 0.86252 0.3116 0.41254 0.87067 0.0034 0.0034 0.0034
22 25608.9 0.33233 0.49012 0.88616 0.85654 0.85508 0.9097 0.86515 0.3099 0.4062 0.86978 0.00307 0.00307 0.00307
23 26761.6 0.33018 0.47189 0.88277 0.85916 0.85264 0.91176 0.86739 0.30958 0.40253 0.86942 0.00274 0.00274 0.00274
24 27913.6 0.32448 0.45399 0.87815 0.85568 0.86282 0.91376 0.8693 0.30865 0.40008 0.8684 0.00241 0.00241 0.00241
25 29066.3 0.31904 0.43523 0.87707 0.85736 0.86565 0.91517 0.8707 0.30757 0.39642 0.8676 0.00208 0.00208 0.00208
26 30219.9 0.31889 0.41156 0.87743 0.85879 0.86718 0.91639 0.87241 0.30656 0.39346 0.86704 0.00175 0.00175 0.00175
27 31373.1 0.3096 0.39341 0.87017 0.86007 0.87011 0.91793 0.87395 0.30596 0.38956 0.8665 0.00142 0.00142 0.00142
28 32526.4 0.31067 0.37626 0.8704 0.86056 0.87339 0.919 0.8752 0.30521 0.38661 0.86574 0.00109 0.00109 0.00109
29 33680.2 0.30541 0.36083 0.8675 0.86259 0.87401 0.91994 0.87604 0.30477 0.3845 0.86533 0.00076 0.00076 0.00076
30 34834.5 0.30304 0.34296 0.86638 0.86295 0.87539 0.92061 0.87694 0.30432 0.38219 0.86491 0.00043 0.00043 0.00043