Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	2.0	100	0.1164	0.902	0.9148	0.9084	0.9897
No log	4.0	200	0.0262	0.972	0.9858	0.9789	0.9971
No log	6.0	300	0.0157	0.972	0.9858	0.9789	0.9971
No log	8.0	400	0.0097	0.9877	0.9797	0.9837	0.9979
0.1294	10.0	500	0.0065	0.9939	0.9959	0.9949	0.9994
0.1294	12.0	600	0.0042	0.9960	0.9980	0.9970	0.9996
0.1294	14.0	700	0.0048	0.9960	0.9980	0.9970	0.9996
0.1294	16.0	800	0.0047	0.9960	0.9980	0.9970	0.9996
0.1294	18.0	900	0.0045	0.9960	0.9980	0.9970	0.9996
0.0051	20.0	1000	0.0042	0.9960	0.9980	0.9970	0.9996
0.0051	22.0	1100	0.0041	0.9960	0.9980	0.9970	0.9996
0.0051	24.0	1200	0.0041	0.9960	0.9980	0.9970	0.9996
0.0051	26.0	1300	0.0040	0.9960	0.9980	0.9970	0.9996
0.0051	28.0	1400	0.0040	0.9960	0.9980	0.9970	0.9996
0.0024	30.0	1500	0.0040	0.9960	0.9980	0.9970	0.9996
0.0024	32.0	1600	0.0040	0.9960	0.9980	0.9970	0.9996
0.0024	34.0	1700	0.0039	0.9960	0.9980	0.9970	0.9996
0.0024	36.0	1800	0.0039	0.9960	0.9980	0.9970	0.9996
0.0024	38.0	1900	0.0039	0.9960	0.9980	0.9970	0.9996
0.0018	40.0	2000	0.0039	0.9960	0.9980	0.9970	0.9996

pradyumna0/layoutlmv3-finetuned-invoice

layoutlmv3-finetuned-invoice