Training Loss	Epoch	Step	Validation Loss	Dob Precision	Dob Recall	Dob F1	Dob Number	Fname Precision	Fname Recall	Fname F1	Fname Number	Name Precision	Name Recall	Name F1	Name Number	Pan Precision	Pan Recall	Pan F1	Pan Number	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
2.1195	1.0	6	1.7519	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	0.7857
1.6994	2.0	12	1.5117	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	0.7857
1.5521	3.0	18	1.4130	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	0.7857
1.4726	4.0	24	1.3410	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	0.7857
1.395	5.0	30	1.2693	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.0	0.0	0.0	0.7857
1.3131	6.0	36	1.2079	1.0	1.0	1.0	2	0.1667	0.5	0.25	2	0.0	0.0	0.0	2	0.0	0.0	0.0	2	0.3	0.375	0.3333	0.8929
1.2474	7.0	42	1.1495	1.0	1.0	1.0	2	0.2	0.5	0.2857	2	0.0	0.0	0.0	2	1.0	1.0	1.0	2	0.4167	0.625	0.5	0.9286
1.1869	8.0	48	1.0942	1.0	1.0	1.0	2	0.2	0.5	0.2857	2	0.0	0.0	0.0	2	1.0	1.0	1.0	2	0.4167	0.625	0.5	0.9286
1.1369	9.0	54	1.0453	1.0	1.0	1.0	2	0.4	1.0	0.5714	2	0.0	0.0	0.0	2	1.0	1.0	1.0	2	0.5455	0.75	0.6316	0.9464
1.0882	10.0	60	1.0054	1.0	1.0	1.0	2	0.5	1.0	0.6667	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.7	0.875	0.7778	0.9643
1.0482	11.0	66	0.9633	1.0	1.0	1.0	2	0.6667	1.0	0.8	2	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.8889	1.0	0.9412	0.9821
1.017	12.0	72	0.9368	1.0	1.0	1.0	2	0.6667	1.0	0.8	2	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.8889	1.0	0.9412	0.9643
0.9825	13.0	78	0.9139	1.0	1.0	1.0	2	0.6667	1.0	0.8	2	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.8889	1.0	0.9412	0.9821
0.9459	14.0	84	0.8837	1.0	1.0	1.0	2	0.6667	1.0	0.8	2	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.8889	1.0	0.9412	0.9643
0.9155	15.0	90	0.8472	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.8819	16.0	96	0.8231	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.8523	17.0	102	0.7957	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.6667	1.0	0.8	2	1.0	1.0	1.0	2	0.8889	1.0	0.9412	0.9821
0.8251	18.0	108	0.7681	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.7982	19.0	114	0.7533	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.7762	20.0	120	0.7283	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.7558	21.0	126	0.7114	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.7346	22.0	132	0.6889	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.7116	23.0	138	0.6697	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.6898	24.0	144	0.6593	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.6748	25.0	150	0.6356	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.6487	26.0	156	0.6142	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.6312	27.0	162	0.6008	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.6156	28.0	168	0.5855	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.5961	29.0	174	0.5625	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643
0.5781	30.0	180	0.5553	1.0	1.0	1.0	2	1.0	1.0	1.0	2	0.5	0.5	0.5	2	1.0	1.0	1.0	2	0.875	0.875	0.875	0.9643

Framework versions

Transformers 4.20.0.dev0
Pytorch 1.11.0+cu113
Datasets 2.2.2
Tokenizers 0.12.1

Sebabrata/lmv2ubiai-pan8doc-06-11

lmv2ubiai-pan8doc-06-11

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Sebabrata/
lmv2ubiai-pan8doc-06-11