NAO_Roboter_Erkennung/yolo_training/NAO_detector3/results.csv

1	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
2	1	140.47	1.11402	2.41714	1.20281	1	0.37601	0.79951	0.55456	0.87553	2.60439	1.01905	0.00026	0.00026	0.00026
3	2	316.983	0.99575	1.51901	1.10586	1	0.45683	0.90108	0.57564	1.10253	2.54986	1.13344	0.000529308	0.000529308	0.000529308
4	3	512.153	0.99078	1.43238	1.14146	0.93389	0.35323	0.7206	0.43569	1.22903	2.64606	1.23865	0.000787528	0.000787528	0.000787528
5	4	644.94	1.0202	1.33932	1.15516	0.61359	0.3	0.34609	0.22426	1.32221	2.85182	1.39251	0.00103466	0.00103466	0.00103466
6	5	772.698	1.04289	1.31	1.17156	0.475	0.45	0.4433	0.29879	1.17274	2.54752	1.27816	0.0012707	0.0012707	0.0012707
7	6	899.988	1.0882	1.2972	1.2043	0.7555	0.2875	0.31395	0.19236	1.42954	3.42743	1.67074	0.00149566	0.00149566	0.00149566
8	7	1025.24	1.05137	1.28863	1.18317	0.4076	0.45	0.36035	0.2224	1.21401	3.12466	1.48008	0.00170953	0.00170953	0.00170953