le-yolo/runs/detect/train17/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	6.67757	3.41272	37.2256	2.01665	0	0	0	0	4.2041	8.06057	2.58386	6e-05	6e-05	6e-05
3	2	12.5336	3.27761	33.1783	2.20473	0	0	0	0	2.56033	8.53504	1.93074	0.000139307	0.000139307	0.000139307
4	3	18.7343	2.74757	31.0758	1.49544	0	0	0	0	2.96839	7.66473	2.03012	0.000217822	0.000217822	0.000217822
5	4	25.6422	3.44972	18.4159	2.02705	0	0	0	0	3.26736	7.65502	2.15388	0.000295545	0.000295545	0.000295545
6	5	32.6041	2.69962	37.0182	1.43514	0	0	0	0	3.74408	8.39783	2.37401	0.000372476	0.000372476	0.000372476
7	6	39.2909	3.50874	22.7099	1.76584	0	0	0	0	4.09483	9.41836	2.60875	0.000448615	0.000448615	0.000448615
8	7	45.999	3.46468	21.5369	1.78773	0	0	0	0	4.37917	10.7141	3.12062	0.000523962	0.000523962	0.000523962
9	8	52.4319	3.30664	18.5804	1.6821	0	0	0	0	4.47329	13.4159	3.74995	0.000598517	0.000598517	0.000598517
10	9	59.1523	2.21643	27.0262	1.19613	0	0	0	0	6.53216	16.1783	7.59617	0.00067228	0.00067228	0.00067228
11	10	65.9499	4.07007	24.105	1.93188	0	0	0	0	5.4014	12.0196	3.76315	0.000745251	0.000745251	0.000745251
12	11	73.1327	3.66771	18.0016	1.68001	0	0	0	0	3.97001	10.2793	2.46107	0.00081743	0.00081743	0.00081743
13	12	81.6521	3.22916	29.223	1.26397	0	0	0	0	4.35561	9.96756	2.58913	0.000888817	0.000888817	0.000888817
14	13	88.8871	3.6894	19.045	1.5285	0	0	0	0	4.16609	9.73185	2.59994	0.000959412	0.000959412	0.000959412
15	14	95.7164	3.88197	22.6651	1.88752	0	0	0	0	4.32821	8.99355	2.8688	0.00102922	0.00102922	0.00102922
16	15	102.553	4.14758	14.2765	2.13574	0	0	0	0	4.14828	9.40865	3.58418	0.00109823	0.00109823	0.00109823