learning_rate: 1e-05
train_batch_size: 2
eval_batch_size: 2
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
training_steps: 2000

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	2.0	100	0.1316	0.872	0.8844	0.8781	0.9865
No log	4.0	200	0.0248	0.972	0.9858	0.9789	0.9971
No log	6.0	300	0.0167	0.972	0.9858	0.9789	0.9971
No log	8.0	400	0.0134	0.972	0.9858	0.9789	0.9971
0.1408	10.0	500	0.0066	0.9899	0.9980	0.9939	0.9989
0.1408	12.0	600	0.0034	1.0	1.0	1.0	1.0
0.1408	14.0	700	0.0027	1.0	1.0	1.0	1.0
0.1408	16.0	800	0.0024	1.0	1.0	1.0	1.0
0.1408	18.0	900	0.0150	0.9897	0.9777	0.9837	0.9977
0.0051	20.0	1000	0.0030	1.0	0.9980	0.9990	0.9998
0.0051	22.0	1100	0.0035	0.9980	0.9959	0.9970	0.9996
0.0051	24.0	1200	0.0017	0.9980	0.9980	0.9980	0.9998
0.0051	26.0	1300	0.0023	0.9980	0.9980	0.9980	0.9998
0.0051	28.0	1400	0.0024	0.9960	0.9980	0.9970	0.9996
0.0028	30.0	1500	0.0023	0.9960	0.9980	0.9970	0.9996
0.0028	32.0	1600	0.0024	0.9960	0.9980	0.9970	0.9996
0.0028	34.0	1700	0.0026	0.9960	0.9980	0.9970	0.9996
0.0028	36.0	1800	0.0027	0.9960	0.9980	0.9970	0.9996
0.0028	38.0	1900	0.0026	0.9960	0.9980	0.9970	0.9996
0.0019	40.0	2000	0.0026	0.9960	0.9980	0.9970	0.9996

HChaurasia/layoutlmv3-finetuned-invoice

layoutlmv3-finetuned-invoice