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lmv2-g-w2-300-doc-09-08

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+ ---
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+ license: cc-by-nc-sa-4.0
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: lmv2-g-w2-300-doc-09-08
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # lmv2-g-w2-300-doc-09-08
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+
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+ This model is a fine-tuned version of [microsoft/layoutlmv2-base-uncased](https://huggingface.co/microsoft/layoutlmv2-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0262
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+ - Control Number Precision: 1.0
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+ - Control Number Recall: 1.0
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+ - Control Number F1: 1.0
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+ - Control Number Number: 17
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+ - Ein Precision: 1.0
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+ - Ein Recall: 0.9833
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+ - Ein F1: 0.9916
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+ - Ein Number: 60
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+ - Employee’s Address Precision: 0.9667
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+ - Employee’s Address Recall: 0.9831
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+ - Employee’s Address F1: 0.9748
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+ - Employee’s Address Number: 59
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+ - Employee’s Name Precision: 0.9833
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+ - Employee’s Name Recall: 1.0
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+ - Employee’s Name F1: 0.9916
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+ - Employee’s Name Number: 59
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+ - Employee’s Ssn Precision: 0.9836
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+ - Employee’s Ssn Recall: 1.0
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+ - Employee’s Ssn F1: 0.9917
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+ - Employee’s Ssn Number: 60
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+ - Employer’s Address Precision: 0.9833
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+ - Employer’s Address Recall: 0.9672
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+ - Employer’s Address F1: 0.9752
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+ - Employer’s Address Number: 61
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+ - Employer’s Name Precision: 0.9833
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+ - Employer’s Name Recall: 0.9833
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+ - Employer’s Name F1: 0.9833
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+ - Employer’s Name Number: 60
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+ - Federal Income Tax Withheld Precision: 1.0
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+ - Federal Income Tax Withheld Recall: 1.0
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+ - Federal Income Tax Withheld F1: 1.0
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+ - Federal Income Tax Withheld Number: 60
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+ - Medicare Tax Withheld Precision: 1.0
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+ - Medicare Tax Withheld Recall: 1.0
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+ - Medicare Tax Withheld F1: 1.0
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+ - Medicare Tax Withheld Number: 60
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+ - Medicare Wages Tips Precision: 1.0
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+ - Medicare Wages Tips Recall: 1.0
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+ - Medicare Wages Tips F1: 1.0
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+ - Medicare Wages Tips Number: 60
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+ - Social Security Tax Withheld Precision: 1.0
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+ - Social Security Tax Withheld Recall: 0.9836
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+ - Social Security Tax Withheld F1: 0.9917
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+ - Social Security Tax Withheld Number: 61
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+ - Social Security Wages Precision: 0.9833
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+ - Social Security Wages Recall: 1.0
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+ - Social Security Wages F1: 0.9916
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+ - Social Security Wages Number: 59
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+ - Wages Tips Precision: 1.0
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+ - Wages Tips Recall: 0.9836
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+ - Wages Tips F1: 0.9917
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+ - Wages Tips Number: 61
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+ - Overall Precision: 0.9905
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+ - Overall Recall: 0.9905
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+ - Overall F1: 0.9905
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+ - Overall Accuracy: 0.9973
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 4e-05
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+ - train_batch_size: 1
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: constant
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+ - num_epochs: 30
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Control Number Precision | Control Number Recall | Control Number F1 | Control Number Number | Ein Precision | Ein Recall | Ein F1 | Ein Number | Employee’s Address Precision | Employee’s Address Recall | Employee’s Address F1 | Employee’s Address Number | Employee’s Name Precision | Employee’s Name Recall | Employee’s Name F1 | Employee’s Name Number | Employee’s Ssn Precision | Employee’s Ssn Recall | Employee’s Ssn F1 | Employee’s Ssn Number | Employer’s Address Precision | Employer’s Address Recall | Employer’s Address F1 | Employer’s Address Number | Employer’s Name Precision | Employer’s Name Recall | Employer’s Name F1 | Employer’s Name Number | Federal Income Tax Withheld Precision | Federal Income Tax Withheld Recall | Federal Income Tax Withheld F1 | Federal Income Tax Withheld Number | Medicare Tax Withheld Precision | Medicare Tax Withheld Recall | Medicare Tax Withheld F1 | Medicare Tax Withheld Number | Medicare Wages Tips Precision | Medicare Wages Tips Recall | Medicare Wages Tips F1 | Medicare Wages Tips Number | Social Security Tax Withheld Precision | Social Security Tax Withheld Recall | Social Security Tax Withheld F1 | Social Security Tax Withheld Number | Social Security Wages Precision | Social Security Wages Recall | Social Security Wages F1 | Social Security Wages Number | Wages Tips Precision | Wages Tips Recall | Wages Tips F1 | Wages Tips Number | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy |
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+ |:-------------:|:-----:|:----:|:---------------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:-------------:|:----------:|:------:|:----------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:------------------------:|:---------------------:|:-----------------:|:---------------------:|:----------------------------:|:-------------------------:|:---------------------:|:-------------------------:|:-------------------------:|:----------------------:|:------------------:|:----------------------:|:-------------------------------------:|:----------------------------------:|:------------------------------:|:----------------------------------:|:-------------------------------:|:----------------------------:|:------------------------:|:----------------------------:|:-----------------------------:|:--------------------------:|:----------------------:|:--------------------------:|:--------------------------------------:|:-----------------------------------:|:-------------------------------:|:-----------------------------------:|:-------------------------------:|:----------------------------:|:------------------------:|:----------------------------:|:--------------------:|:-----------------:|:-------------:|:-----------------:|:-----------------:|:--------------:|:----------:|:----------------:|
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+ | 1.7717 | 1.0 | 240 | 0.9856 | 0.0 | 0.0 | 0.0 | 17 | 0.9206 | 0.9667 | 0.9431 | 60 | 0.6824 | 0.9831 | 0.8056 | 59 | 0.2333 | 0.5932 | 0.3349 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.7609 | 0.5738 | 0.6542 | 61 | 0.3654 | 0.3167 | 0.3393 | 60 | 0.0 | 0.0 | 0.0 | 60 | 0.8194 | 0.9833 | 0.8939 | 60 | 0.6064 | 0.95 | 0.7403 | 60 | 0.5050 | 0.8361 | 0.6296 | 61 | 0.0 | 0.0 | 0.0 | 59 | 0.5859 | 0.9508 | 0.725 | 61 | 0.5954 | 0.6649 | 0.6282 | 0.9558 |
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+ | 0.5578 | 2.0 | 480 | 0.2957 | 0.8462 | 0.6471 | 0.7333 | 17 | 0.9831 | 0.9667 | 0.9748 | 60 | 0.9048 | 0.9661 | 0.9344 | 59 | 0.8358 | 0.9492 | 0.8889 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.8125 | 0.8525 | 0.8320 | 61 | 0.8462 | 0.9167 | 0.8800 | 60 | 0.9672 | 0.9833 | 0.9752 | 60 | 0.9524 | 1.0 | 0.9756 | 60 | 0.9194 | 0.95 | 0.9344 | 60 | 0.9833 | 0.9672 | 0.9752 | 61 | 0.9508 | 0.9831 | 0.9667 | 59 | 0.9516 | 0.9672 | 0.9593 | 61 | 0.9212 | 0.9512 | 0.9359 | 0.9891 |
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+ | 0.223 | 3.0 | 720 | 0.1626 | 0.5 | 0.6471 | 0.5641 | 17 | 0.9667 | 0.9667 | 0.9667 | 60 | 0.9355 | 0.9831 | 0.9587 | 59 | 0.9672 | 1.0 | 0.9833 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.8769 | 0.9344 | 0.9048 | 61 | 0.9508 | 0.9667 | 0.9587 | 60 | 0.9833 | 0.9833 | 0.9833 | 60 | 0.9836 | 1.0 | 0.9917 | 60 | 0.8769 | 0.95 | 0.912 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9355 | 0.9831 | 0.9587 | 59 | 0.9516 | 0.9672 | 0.9593 | 61 | 0.9370 | 0.9688 | 0.9526 | 0.9923 |
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+ | 0.1305 | 4.0 | 960 | 0.1025 | 0.9444 | 1.0 | 0.9714 | 17 | 0.9831 | 0.9667 | 0.9748 | 60 | 0.9194 | 0.9661 | 0.9421 | 59 | 0.9508 | 0.9831 | 0.9667 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9219 | 0.9672 | 0.944 | 61 | 0.9667 | 0.9667 | 0.9667 | 60 | 0.9833 | 0.9833 | 0.9833 | 60 | 0.9524 | 1.0 | 0.9756 | 60 | 0.8906 | 0.95 | 0.9194 | 60 | 0.9833 | 0.9672 | 0.9752 | 61 | 0.9355 | 0.9831 | 0.9587 | 59 | 0.9516 | 0.9672 | 0.9593 | 61 | 0.9511 | 0.9756 | 0.9632 | 0.9947 |
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+ | 0.0852 | 5.0 | 1200 | 0.0744 | 0.7391 | 1.0 | 0.85 | 17 | 0.9831 | 0.9667 | 0.9748 | 60 | 0.9667 | 0.9831 | 0.9748 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9344 | 0.9344 | 0.9344 | 61 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9365 | 0.9833 | 0.9593 | 60 | 0.9677 | 1.0 | 0.9836 | 60 | 0.95 | 0.95 | 0.9500 | 60 | 0.9836 | 0.9836 | 0.9836 | 61 | 0.9667 | 0.9831 | 0.9748 | 59 | 0.9833 | 0.9672 | 0.9752 | 61 | 0.9626 | 0.9783 | 0.9704 | 0.9953 |
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+ | 0.0583 | 6.0 | 1440 | 0.0554 | 0.7727 | 1.0 | 0.8718 | 17 | 0.9831 | 0.9667 | 0.9748 | 60 | 0.9667 | 0.9831 | 0.9748 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9048 | 0.9344 | 0.9194 | 61 | 1.0 | 0.9833 | 0.9916 | 60 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9833 | 0.9833 | 0.9833 | 60 | 0.9344 | 0.95 | 0.9421 | 60 | 1.0 | 0.9672 | 0.9833 | 61 | 0.9667 | 0.9831 | 0.9748 | 59 | 0.9833 | 0.9672 | 0.9752 | 61 | 0.9677 | 0.9756 | 0.9716 | 0.9957 |
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+ | 0.0431 | 7.0 | 1680 | 0.0471 | 0.9444 | 1.0 | 0.9714 | 17 | 0.9831 | 0.9667 | 0.9748 | 60 | 0.9016 | 0.9322 | 0.9167 | 59 | 0.95 | 0.9661 | 0.9580 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.8676 | 0.9672 | 0.9147 | 61 | 0.9831 | 0.9667 | 0.9748 | 60 | 1.0 | 0.9833 | 0.9916 | 60 | 1.0 | 1.0 | 1.0 | 60 | 0.9516 | 0.9833 | 0.9672 | 60 | 0.9836 | 0.9836 | 0.9836 | 61 | 0.9831 | 0.9831 | 0.9831 | 59 | 0.9833 | 0.9672 | 0.9752 | 61 | 0.9625 | 0.9756 | 0.9690 | 0.9947 |
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+ | 0.0314 | 8.0 | 1920 | 0.0359 | 1.0 | 1.0 | 1.0 | 17 | 0.9831 | 0.9667 | 0.9748 | 60 | 0.9355 | 0.9831 | 0.9587 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9516 | 0.9672 | 0.9593 | 61 | 1.0 | 0.9667 | 0.9831 | 60 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 1.0 | 1.0 | 60 | 0.9516 | 0.9833 | 0.9672 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9831 | 0.9831 | 0.9831 | 59 | 0.9672 | 0.9672 | 0.9672 | 61 | 0.9771 | 0.9824 | 0.9797 | 0.9969 |
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+ | 0.0278 | 9.0 | 2160 | 0.0338 | 0.8947 | 1.0 | 0.9444 | 17 | 0.9833 | 0.9833 | 0.9833 | 60 | 0.9355 | 0.9831 | 0.9587 | 59 | 0.9667 | 0.9831 | 0.9748 | 59 | 1.0 | 1.0 | 1.0 | 60 | 0.9365 | 0.9672 | 0.9516 | 61 | 0.9672 | 0.9833 | 0.9752 | 60 | 1.0 | 0.9833 | 0.9916 | 60 | 1.0 | 1.0 | 1.0 | 60 | 0.9516 | 0.9833 | 0.9672 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9667 | 0.9831 | 0.9748 | 59 | 0.9672 | 0.9672 | 0.9672 | 61 | 0.9705 | 0.9837 | 0.9771 | 0.9965 |
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+ | 0.0231 | 10.0 | 2400 | 0.0332 | 0.9444 | 1.0 | 0.9714 | 17 | 0.9831 | 0.9667 | 0.9748 | 60 | 0.9508 | 0.9831 | 0.9667 | 59 | 0.9048 | 0.9661 | 0.9344 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9667 | 0.9508 | 0.9587 | 61 | 0.9667 | 0.9667 | 0.9667 | 60 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9365 | 0.9833 | 0.9593 | 60 | 1.0 | 0.9672 | 0.9833 | 61 | 0.9831 | 0.9831 | 0.9831 | 59 | 0.9833 | 0.9672 | 0.9752 | 61 | 0.9690 | 0.9769 | 0.9730 | 0.9964 |
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+ | 0.0189 | 11.0 | 2640 | 0.0342 | 1.0 | 1.0 | 1.0 | 17 | 0.9667 | 0.9667 | 0.9667 | 60 | 0.8657 | 0.9831 | 0.9206 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.8594 | 0.9016 | 0.88 | 61 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9516 | 0.9672 | 0.9593 | 61 | 0.964 | 0.9810 | 0.9724 | 0.9958 |
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+ | 0.0187 | 12.0 | 2880 | 0.0255 | 1.0 | 1.0 | 1.0 | 17 | 0.9667 | 0.9667 | 0.9667 | 60 | 0.9508 | 0.9831 | 0.9667 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9667 | 0.9508 | 0.9587 | 61 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9672 | 0.9833 | 0.9752 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9833 | 0.9672 | 0.9752 | 61 | 0.9824 | 0.9851 | 0.9837 | 0.9976 |
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+ | 0.0126 | 13.0 | 3120 | 0.0257 | 1.0 | 1.0 | 1.0 | 17 | 0.9667 | 0.9667 | 0.9667 | 60 | 0.9344 | 0.9661 | 0.95 | 59 | 0.8889 | 0.9492 | 0.9180 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.8788 | 0.9508 | 0.9134 | 61 | 1.0 | 0.9833 | 0.9916 | 60 | 1.0 | 1.0 | 1.0 | 60 | 0.9836 | 1.0 | 0.9917 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9672 | 0.9833 | 61 | 0.9508 | 0.9831 | 0.9667 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9652 | 0.9796 | 0.9724 | 0.9971 |
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+ | 0.012 | 14.0 | 3360 | 0.0227 | 1.0 | 1.0 | 1.0 | 17 | 0.9667 | 0.9667 | 0.9667 | 60 | 0.9516 | 1.0 | 0.9752 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9194 | 0.9344 | 0.9268 | 61 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9672 | 0.9833 | 0.9752 | 60 | 1.0 | 0.9833 | 0.9916 | 60 | 1.0 | 1.0 | 1.0 | 60 | 0.9836 | 0.9836 | 0.9836 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9784 | 0.9851 | 0.9817 | 0.9977 |
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+ | 0.0119 | 15.0 | 3600 | 0.0284 | 1.0 | 1.0 | 1.0 | 17 | 1.0 | 1.0 | 1.0 | 60 | 0.9355 | 0.9831 | 0.9587 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 1.0 | 1.0 | 60 | 0.9167 | 0.9016 | 0.9091 | 61 | 0.9661 | 0.95 | 0.9580 | 60 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9810 | 0.9824 | 0.9817 | 0.9965 |
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+ | 0.0103 | 16.0 | 3840 | 0.0289 | 0.9444 | 1.0 | 0.9714 | 17 | 0.9672 | 0.9833 | 0.9752 | 60 | 0.9344 | 0.9661 | 0.95 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 1.0 | 1.0 | 60 | 0.8088 | 0.9016 | 0.8527 | 61 | 0.9667 | 0.9667 | 0.9667 | 60 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9666 | 0.9810 | 0.9737 | 0.9963 |
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+ | 0.01 | 17.0 | 4080 | 0.0305 | 0.8947 | 1.0 | 0.9444 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9355 | 0.9831 | 0.9587 | 59 | 0.9516 | 1.0 | 0.9752 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9355 | 0.9508 | 0.9431 | 61 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 0.8955 | 1.0 | 0.9449 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9694 | 0.9891 | 0.9792 | 0.9961 |
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+ | 0.0082 | 18.0 | 4320 | 0.0256 | 1.0 | 1.0 | 1.0 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9508 | 0.9831 | 0.9667 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.8636 | 0.9344 | 0.8976 | 61 | 0.9831 | 0.9667 | 0.9748 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9785 | 0.9864 | 0.9824 | 0.9970 |
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+ | 0.0059 | 19.0 | 4560 | 0.0255 | 1.0 | 1.0 | 1.0 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9667 | 0.9831 | 0.9748 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9355 | 0.9508 | 0.9431 | 61 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9865 | 0.9891 | 0.9878 | 0.9974 |
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+ | 0.0078 | 20.0 | 4800 | 0.0293 | 1.0 | 1.0 | 1.0 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9508 | 0.9831 | 0.9667 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9 | 0.8852 | 0.8926 | 61 | 0.9661 | 0.95 | 0.9580 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9810 | 0.9810 | 0.9810 | 0.9966 |
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+ | 0.009 | 21.0 | 5040 | 0.0264 | 1.0 | 1.0 | 1.0 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9206 | 0.9831 | 0.9508 | 59 | 0.9667 | 0.9831 | 0.9748 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.8889 | 0.9180 | 0.9032 | 61 | 0.9672 | 0.9833 | 0.9752 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 0.9836 | 0.9836 | 0.9836 | 61 | 0.9831 | 0.9831 | 0.9831 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9745 | 0.9837 | 0.9791 | 0.9969 |
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+ | 0.0046 | 22.0 | 5280 | 0.0271 | 1.0 | 1.0 | 1.0 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9355 | 0.9831 | 0.9587 | 59 | 0.9667 | 0.9831 | 0.9748 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9032 | 0.9180 | 0.9106 | 61 | 0.9672 | 0.9833 | 0.9752 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9784 | 0.9851 | 0.9817 | 0.9970 |
126
+ | 0.0087 | 23.0 | 5520 | 0.0278 | 0.9444 | 1.0 | 0.9714 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9194 | 0.9661 | 0.9421 | 59 | 0.9667 | 0.9831 | 0.9748 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.8657 | 0.9508 | 0.9062 | 61 | 0.9836 | 1.0 | 0.9917 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9733 | 0.9878 | 0.9805 | 0.9958 |
127
+ | 0.0054 | 24.0 | 5760 | 0.0276 | 0.9444 | 1.0 | 0.9714 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.95 | 0.9661 | 0.9580 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9355 | 0.9508 | 0.9431 | 61 | 0.9831 | 0.9667 | 0.9748 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 0.9355 | 0.9667 | 0.9508 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9784 | 0.9837 | 0.9811 | 0.9971 |
128
+ | 0.0057 | 25.0 | 6000 | 0.0260 | 1.0 | 1.0 | 1.0 | 17 | 1.0 | 0.9667 | 0.9831 | 60 | 0.9077 | 1.0 | 0.9516 | 59 | 0.95 | 0.9661 | 0.9580 | 59 | 0.9677 | 1.0 | 0.9836 | 60 | 0.9508 | 0.9508 | 0.9508 | 61 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9672 | 0.9833 | 61 | 0.9672 | 1.0 | 0.9833 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9771 | 0.9837 | 0.9804 | 0.9971 |
129
+ | 0.0074 | 26.0 | 6240 | 0.0340 | 1.0 | 1.0 | 1.0 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9180 | 0.9492 | 0.9333 | 59 | 0.9667 | 0.9831 | 0.9748 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.8906 | 0.9344 | 0.9120 | 61 | 0.9831 | 0.9667 | 0.9748 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 0.9836 | 0.9836 | 61 | 0.9757 | 0.9824 | 0.9790 | 0.9959 |
130
+ | 0.0047 | 27.0 | 6480 | 0.0306 | 1.0 | 1.0 | 1.0 | 17 | 1.0 | 1.0 | 1.0 | 60 | 0.8923 | 0.9831 | 0.9355 | 59 | 0.9672 | 1.0 | 0.9833 | 59 | 1.0 | 1.0 | 1.0 | 60 | 0.9016 | 0.9016 | 0.9016 | 61 | 0.9667 | 0.9667 | 0.9667 | 60 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9672 | 0.9833 | 61 | 0.8551 | 1.0 | 0.9219 | 59 | 1.0 | 0.8525 | 0.9204 | 61 | 0.9624 | 0.9715 | 0.9669 | 0.9961 |
131
+ | 0.0052 | 28.0 | 6720 | 0.0262 | 1.0 | 1.0 | 1.0 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9667 | 0.9831 | 0.9748 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9833 | 0.9672 | 0.9752 | 61 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9833 | 1.0 | 0.9916 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9905 | 0.9905 | 0.9905 | 0.9973 |
132
+ | 0.0033 | 29.0 | 6960 | 0.0320 | 0.9444 | 1.0 | 0.9714 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.8406 | 0.9831 | 0.9062 | 59 | 0.9672 | 1.0 | 0.9833 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.8852 | 0.8852 | 0.8852 | 61 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 0.9667 | 0.9831 | 60 | 1.0 | 1.0 | 1.0 | 60 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9365 | 1.0 | 0.9672 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9627 | 0.9796 | 0.9711 | 0.9960 |
133
+ | 0.0048 | 30.0 | 7200 | 0.0215 | 1.0 | 1.0 | 1.0 | 17 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9672 | 1.0 | 0.9833 | 59 | 0.9833 | 1.0 | 0.9916 | 59 | 0.9836 | 1.0 | 0.9917 | 60 | 0.9833 | 0.9672 | 0.9752 | 61 | 1.0 | 0.9833 | 0.9916 | 60 | 0.9833 | 0.9833 | 0.9833 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 1.0 | 1.0 | 60 | 1.0 | 0.9672 | 0.9833 | 61 | 0.9672 | 1.0 | 0.9833 | 59 | 1.0 | 0.9836 | 0.9917 | 61 | 0.9891 | 0.9891 | 0.9891 | 0.9980 |
134
+
135
+
136
+ ### Framework versions
137
+
138
+ - Transformers 4.22.0.dev0
139
+ - Pytorch 1.12.1+cu113
140
+ - Datasets 2.2.2
141
+ - Tokenizers 0.12.1