lmv2-g-passport-197-doc-09-13

This model is a fine-tuned version of microsoft/layoutlmv2-base-uncased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0438
• Country Code Precision: 0.9412
• Country Code Recall: 0.9697
• Country Code F1: 0.9552
• Country Code Number: 33
• Date Of Birth Precision: 0.9714
• Date Of Birth Recall: 1.0
• Date Of Birth F1: 0.9855
• Date Of Birth Number: 34
• Date Of Expiry Precision: 1.0
• Date Of Expiry Recall: 1.0
• Date Of Expiry F1: 1.0
• Date Of Expiry Number: 36
• Date Of Issue Precision: 1.0
• Date Of Issue Recall: 1.0
• Date Of Issue F1: 1.0
• Date Of Issue Number: 36
• Given Name Precision: 0.9444
• Given Name Recall: 1.0
• Given Name F1: 0.9714
• Given Name Number: 34
• Nationality Precision: 0.9714
• Nationality Recall: 1.0
• Nationality F1: 0.9855
• Nationality Number: 34
• Passport No Precision: 0.9118
• Passport No Recall: 0.9688
• Passport No F1: 0.9394
• Passport No Number: 32
• Place Of Birth Precision: 1.0
• Place Of Birth Recall: 0.9730
• Place Of Birth F1: 0.9863
• Place Of Birth Number: 37
• Place Of Issue Precision: 1.0
• Place Of Issue Recall: 0.9722
• Place Of Issue F1: 0.9859
• Place Of Issue Number: 36
• Sex Precision: 0.9655
• Sex Recall: 0.9333
• Sex F1: 0.9492
• Sex Number: 30
• Surname Precision: 0.9259
• Surname Recall: 1.0
• Surname F1: 0.9615
• Surname Number: 25
• Type Precision: 1.0
• Type Recall: 1.0
• Type F1: 1.0
• Type Number: 27
• Overall Precision: 0.97
• Overall Recall: 0.9848
• Overall F1: 0.9773
• Overall Accuracy: 0.9941

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

• learning_rate: 4e-05
• train_batch_size: 1
• eval_batch_size: 1
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: constant
• num_epochs: 30

Training results

Training Loss	Epoch	Step	Validation Loss	Country Code Precision	Country Code Recall	Country Code F1	Country Code Number	Date Of Birth Precision	Date Of Birth Recall	Date Of Birth F1	Date Of Birth Number	Date Of Expiry Precision	Date Of Expiry Recall	Date Of Expiry F1	Date Of Expiry Number	Date Of Issue Precision	Date Of Issue Recall	Date Of Issue F1	Date Of Issue Number	Given Name Precision	Given Name Recall	Given Name F1	Given Name Number	Nationality Precision	Nationality Recall	Nationality F1	Nationality Number	Passport No Precision	Passport No Recall	Passport No F1	Passport No Number	Place Of Birth Precision	Place Of Birth Recall	Place Of Birth F1	Place Of Birth Number	Place Of Issue Precision	Place Of Issue Recall	Place Of Issue F1	Place Of Issue Number	Sex Precision	Sex Recall	Sex F1	Sex Number	Surname Precision	Surname Recall	Surname F1	Surname Number	Type Precision	Type Recall	Type F1	Type Number	Overall Precision	Overall Recall	Overall F1	Overall Accuracy
1.6757	1.0	157	1.2569	0.0	0.0	0.0	33	0.0	0.0	0.0	34	0.2466	1.0	0.3956	36	0.0	0.0	0.0	36	0.0	0.0	0.0	34	0.0	0.0	0.0	34	0.0	0.0	0.0	32	0.0	0.0	0.0	37	0.0	0.0	0.0	36	0.0	0.0	0.0	30	0.0	0.0	0.0	25	0.0	0.0	0.0	27	0.2466	0.0914	0.1333	0.8446
0.9214	2.0	314	0.5683	0.9394	0.9394	0.9394	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.5625	0.5294	0.5455	34	0.9714	1.0	0.9855	34	0.6098	0.7812	0.6849	32	0.9394	0.8378	0.8857	37	0.8293	0.9444	0.8831	36	1.0	0.9333	0.9655	30	0.6129	0.76	0.6786	25	1.0	0.8889	0.9412	27	0.8642	0.8883	0.8761	0.9777
0.4452	3.0	471	0.3266	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.5556	0.4412	0.4918	34	0.9714	1.0	0.9855	34	0.625	0.7812	0.6944	32	1.0	0.8108	0.8955	37	0.7556	0.9444	0.8395	36	0.9655	0.9333	0.9492	30	0.5556	0.8	0.6557	25	1.0	0.7037	0.8261	27	0.8532	0.8706	0.8618	0.9784
0.2823	4.0	628	0.2215	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.75	0.8824	0.8108	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.8378	0.9118	37	0.9459	0.9722	0.9589	36	0.9333	0.9333	0.9333	30	0.75	0.96	0.8421	25	1.0	0.9630	0.9811	27	0.9286	0.9569	0.9425	0.9885
0.2092	5.0	785	0.1633	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.8889	0.9412	0.9143	34	0.9714	1.0	0.9855	34	0.8857	0.9688	0.9254	32	1.0	0.8649	0.9275	37	0.8974	0.9722	0.9333	36	1.0	0.9333	0.9655	30	0.8889	0.96	0.9231	25	1.0	1.0	1.0	27	0.9525	0.9670	0.9597	0.9918
0.1593	6.0	942	0.1331	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	0.9730	1.0	0.9863	36	0.8857	0.9118	0.8986	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	0.9722	0.9459	0.9589	37	0.9722	0.9722	0.9722	36	1.0	0.9	0.9474	30	0.8571	0.96	0.9057	25	1.0	0.9630	0.9811	27	0.9549	0.9670	0.9609	0.9908
0.1288	7.0	1099	0.1064	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9444	1.0	0.9714	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	0.9722	0.9859	36	1.0	0.9333	0.9655	30	0.92	0.92	0.92	25	1.0	1.0	1.0	27	0.9723	0.9797	0.9760	0.9941
0.1035	8.0	1256	0.1043	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9706	0.9706	0.9706	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	0.9231	0.9730	0.9474	37	0.75	1.0	0.8571	36	0.9032	0.9333	0.9180	30	0.6486	0.96	0.7742	25	1.0	1.0	1.0	27	0.9085	0.9822	0.9439	0.9856
0.0843	9.0	1413	0.0823	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9143	0.9412	0.9275	34	0.9714	1.0	0.9855	34	0.9394	0.9688	0.9538	32	0.9032	0.7568	0.8235	37	0.9211	0.9722	0.9459	36	0.9655	0.9333	0.9492	30	0.7059	0.96	0.8136	25	1.0	1.0	1.0	27	0.9355	0.9569	0.9460	0.9905
0.0733	10.0	1570	0.0738	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9714	1.0	0.9855	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	0.9459	0.9459	0.9459	37	1.0	0.9444	0.9714	36	0.8485	0.9333	0.8889	30	0.8333	1.0	0.9091	25	0.9643	1.0	0.9818	27	0.9484	0.9797	0.9638	0.9911
0.0614	11.0	1727	0.0661	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9714	1.0	0.9855	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	0.9459	0.9459	0.9459	37	1.0	0.9722	0.9859	36	0.9655	0.9333	0.9492	30	0.9231	0.96	0.9412	25	1.0	0.9630	0.9811	27	0.9673	0.9772	0.9722	0.9934
0.0548	12.0	1884	0.0637	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	0.9730	1.0	0.9863	36	0.9167	0.9706	0.9429	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	0.9459	0.9459	0.9459	37	1.0	0.9722	0.9859	36	0.875	0.9333	0.9032	30	0.9259	1.0	0.9615	25	0.9643	1.0	0.9818	27	0.9507	0.9797	0.965	0.9921
0.0515	13.0	2041	0.0562	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9714	1.0	0.9855	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	0.9730	0.9730	0.9730	37	1.0	1.0	1.0	36	0.9333	0.9333	0.9333	30	0.8621	1.0	0.9259	25	0.9643	1.0	0.9818	27	0.9605	0.9873	0.9737	0.9931
0.0431	14.0	2198	0.0513	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9444	1.0	0.9714	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	1.0	1.0	36	1.0	0.9333	0.9655	30	0.9231	0.96	0.9412	25	1.0	0.9630	0.9811	27	0.9724	0.9822	0.9773	0.9944
0.0413	15.0	2355	0.0582	0.9412	0.9697	0.9552	33	0.9706	0.9706	0.9706	34	0.9730	1.0	0.9863	36	0.9730	1.0	0.9863	36	0.9429	0.9706	0.9565	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	1.0	1.0	36	0.9655	0.9333	0.9492	30	0.8929	1.0	0.9434	25	1.0	1.0	1.0	27	0.9627	0.9822	0.9724	0.9934
0.035	16.0	2512	0.0556	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	0.9722	0.9859	36	0.8857	0.9118	0.8986	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	0.9730	0.9730	0.9730	37	1.0	0.9722	0.9859	36	0.9333	0.9333	0.9333	30	0.8621	1.0	0.9259	25	1.0	1.0	1.0	27	0.9552	0.9746	0.9648	0.9915
0.0316	17.0	2669	0.0517	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9167	0.9706	0.9429	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	0.9722	0.9859	36	0.875	0.9333	0.9032	30	0.8929	1.0	0.9434	25	1.0	1.0	1.0	27	0.9579	0.9822	0.9699	0.9928
0.027	18.0	2826	0.0502	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	0.9730	1.0	0.9863	36	1.0	1.0	1.0	36	0.9444	1.0	0.9714	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	0.9722	0.9859	36	0.9032	0.9333	0.9180	30	0.9259	1.0	0.9615	25	1.0	1.0	1.0	27	0.9628	0.9848	0.9737	0.9931
0.026	19.0	2983	0.0481	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9189	1.0	0.9577	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	1.0	1.0	36	0.9333	0.9333	0.9333	30	0.8333	1.0	0.9091	25	1.0	1.0	1.0	27	0.9581	0.9873	0.9725	0.9928
0.026	20.0	3140	0.0652	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	0.9730	1.0	0.9863	36	1.0	1.0	1.0	36	0.9714	1.0	0.9855	34	0.9714	1.0	0.9855	34	0.8611	0.9688	0.9118	32	0.9730	0.9730	0.9730	37	0.9730	1.0	0.9863	36	0.8235	0.9333	0.8750	30	0.8333	1.0	0.9091	25	1.0	1.0	1.0	27	0.9419	0.9873	0.9641	0.9882
0.0311	21.0	3297	0.0438	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9444	1.0	0.9714	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	0.9722	0.9859	36	0.9655	0.9333	0.9492	30	0.9259	1.0	0.9615	25	1.0	1.0	1.0	27	0.97	0.9848	0.9773	0.9941
0.0216	22.0	3454	0.0454	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9706	0.9706	0.9706	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	0.9722	0.9859	36	0.9333	0.9333	0.9333	30	0.9259	1.0	0.9615	25	1.0	1.0	1.0	27	0.9699	0.9822	0.9760	0.9941
0.0196	23.0	3611	0.0510	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9714	1.0	0.9855	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	0.8718	0.9189	0.8947	37	1.0	0.9722	0.9859	36	0.9655	0.9333	0.9492	30	0.9259	1.0	0.9615	25	1.0	1.0	1.0	27	0.9602	0.9797	0.9698	0.9934
0.0176	24.0	3768	0.0457	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9706	0.9706	0.9706	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	1.0	1.0	36	0.9333	0.9333	0.9333	30	0.8929	1.0	0.9434	25	1.0	1.0	1.0	27	0.9676	0.9848	0.9761	0.9938
0.0141	25.0	3925	0.0516	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9714	1.0	0.9855	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	0.9722	0.9459	0.9589	37	0.9730	1.0	0.9863	36	0.875	0.9333	0.9032	30	0.9231	0.96	0.9412	25	0.9643	1.0	0.9818	27	0.9579	0.9822	0.9699	0.9928
0.0129	26.0	4082	0.0508	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	0.9730	1.0	0.9863	36	1.0	1.0	1.0	36	0.9714	1.0	0.9855	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	1.0	1.0	36	0.875	0.9333	0.9032	30	0.9259	1.0	0.9615	25	1.0	1.0	1.0	27	0.9629	0.9873	0.9749	0.9934
0.0125	27.0	4239	0.0455	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9714	1.0	0.9855	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	0.9722	0.9859	36	1.0	0.9333	0.9655	30	0.9259	1.0	0.9615	25	0.8710	1.0	0.9310	27	0.9652	0.9848	0.9749	0.9934
0.0131	28.0	4396	0.0452	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	0.9722	0.9859	36	0.9429	0.9706	0.9565	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	1.0	0.9730	0.9863	37	1.0	0.9722	0.9859	36	1.0	0.9333	0.9655	30	0.9231	0.96	0.9412	25	1.0	1.0	1.0	27	0.9722	0.9772	0.9747	0.9941
0.0112	29.0	4553	0.0465	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.9714	1.0	0.9855	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	0.9459	0.9459	0.9459	37	0.9722	0.9722	0.9722	36	0.9333	0.9333	0.9333	30	0.9583	0.92	0.9388	25	1.0	1.0	1.0	27	0.9649	0.9772	0.9710	0.9931
0.0152	30.0	4710	0.0510	0.9412	0.9697	0.9552	33	0.9714	1.0	0.9855	34	1.0	1.0	1.0	36	1.0	1.0	1.0	36	0.8857	0.9118	0.8986	34	0.9714	1.0	0.9855	34	0.9118	0.9688	0.9394	32	0.9730	0.9730	0.9730	37	1.0	0.9722	0.9859	36	1.0	0.9333	0.9655	30	0.9231	0.96	0.9412	25	1.0	1.0	1.0	27	0.9648	0.9746	0.9697	0.9931

Framework versions

• Transformers 4.22.0.dev0
• Pytorch 1.12.1+cu113
• Datasets 2.2.2
• Tokenizers 0.12.1