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
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