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---
license: mit
base_model: microsoft/deberta-v3-base
tags:
- generated_from_trainer
model-index:
- name: deberta-v3-base_finetuned_ai4privacy_v2
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# deberta-v3-base_finetuned_ai4privacy_v2
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0693
- Overall Precision: 0.9664
- Overall Recall: 0.9732
- Overall F1: 0.9698
- Overall Accuracy: 0.9728
- Accountname F1: 1.0
- Accountnumber F1: 1.0
- Age F1: 0.9760
- Amount F1: 0.9897
- Bic F1: 0.9978
- Bitcoinaddress F1: 0.9907
- Buildingnumber F1: 0.9906
- City F1: 0.9930
- Companyname F1: 0.9994
- County F1: 0.9939
- Creditcardcvv F1: 1.0
- Creditcardissuer F1: 0.9891
- Creditcardnumber F1: 0.9590
- Currency F1: 0.9052
- Currencycode F1: 0.9875
- Currencyname F1: 0.7022
- Currencysymbol F1: 0.9892
- Date F1: 0.9126
- Dob F1: 0.7438
- Email F1: 1.0
- Ethereumaddress F1: 1.0
- Eyecolor F1: 1.0
- Firstname F1: 0.9934
- Gender F1: 0.9991
- Height F1: 1.0
- Iban F1: 1.0
- Ip F1: 0.1551
- Ipv4 F1: 0.8393
- Ipv6 F1: 0.8034
- Jobarea F1: 0.9942
- Jobtitle F1: 0.9993
- Jobtype F1: 0.9928
- Lastname F1: 0.9877
- Litecoinaddress F1: 0.9770
- Mac F1: 1.0
- Maskednumber F1: 0.9451
- Middlename F1: 0.9773
- Nearbygpscoordinate F1: 1.0
- Ordinaldirection F1: 0.9924
- Password F1: 1.0
- Phoneimei F1: 1.0
- Phonenumber F1: 1.0
- Pin F1: 0.9929
- Prefix F1: 0.9722
- Secondaryaddress F1: 0.9974
- Sex F1: 0.9949
- Ssn F1: 0.9970
- State F1: 0.9941
- Street F1: 0.9972
- Time F1: 0.9967
- Url F1: 1.0
- Useragent F1: 1.0
- Username F1: 0.9991
- Vehiclevin F1: 1.0
- Vehiclevrm F1: 1.0
- Zipcode F1: 0.9890
## 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: 5e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_ratio: 0.2
- num_epochs: 7
### Training results
| Training Loss | Epoch | Step | Validation Loss | Overall Precision | Overall Recall | Overall F1 | Overall Accuracy | Accountname F1 | Accountnumber F1 | Age F1 | Amount F1 | Bic F1 | Bitcoinaddress F1 | Buildingnumber F1 | City F1 | Companyname F1 | County F1 | Creditcardcvv F1 | Creditcardissuer F1 | Creditcardnumber F1 | Currency F1 | Currencycode F1 | Currencyname F1 | Currencysymbol F1 | Date F1 | Dob F1 | Email F1 | Ethereumaddress F1 | Eyecolor F1 | Firstname F1 | Gender F1 | Height F1 | Iban F1 | Ip F1 | Ipv4 F1 | Ipv6 F1 | Jobarea F1 | Jobtitle F1 | Jobtype F1 | Lastname F1 | Litecoinaddress F1 | Mac F1 | Maskednumber F1 | Middlename F1 | Nearbygpscoordinate F1 | Ordinaldirection F1 | Password F1 | Phoneimei F1 | Phonenumber F1 | Pin F1 | Prefix F1 | Secondaryaddress F1 | Sex F1 | Ssn F1 | State F1 | Street F1 | Time F1 | Url F1 | Useragent F1 | Username F1 | Vehiclevin F1 | Vehiclevrm F1 | Zipcode F1 |
|:-------------:|:-----:|:-----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:--------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:------:|:--------:|:------------------:|:-----------:|:------------:|:---------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:----------------------:|:-------------------:|:-----------:|:------------:|:--------------:|:------:|:---------:|:-------------------:|:------:|:------:|:--------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:|
| 0.3984 | 1.0 | 2393 | 0.5120 | 0.7268 | 0.7819 | 0.7533 | 0.8741 | 0.9265 | 0.9819 | 0.8237 | 0.5053 | 0.2315 | 0.8197 | 0.7840 | 0.4886 | 0.8657 | 0.6338 | 0.8775 | 0.8575 | 0.7152 | 0.4533 | 0.0959 | 0.0 | 0.6480 | 0.7621 | 0.1884 | 0.9840 | 1.0 | 0.6194 | 0.8740 | 0.6610 | 0.9642 | 0.9039 | 0.0 | 0.8500 | 0.0220 | 0.6325 | 0.7840 | 0.6899 | 0.7667 | 0.0 | 0.2966 | 0.0 | 0.3682 | 0.9986 | 0.9387 | 0.8558 | 0.9879 | 0.9687 | 0.7455 | 0.9252 | 0.9661 | 0.9110 | 0.9771 | 0.5282 | 0.7988 | 0.8453 | 0.9648 | 0.9804 | 0.9356 | 0.7741 | 0.6780 | 0.7915 |
| 0.2097 | 2.0 | 4786 | 0.1406 | 0.8392 | 0.8913 | 0.8645 | 0.9509 | 0.9760 | 0.9114 | 0.9227 | 0.7647 | 0.9190 | 0.9554 | 0.8975 | 0.8881 | 0.9535 | 0.8414 | 0.9114 | 0.9820 | 0.8503 | 0.7525 | 0.6171 | 0.0077 | 0.8787 | 0.3161 | 0.2847 | 0.9924 | 0.9918 | 0.9495 | 0.9076 | 0.9625 | 0.9890 | 0.9870 | 0.0 | 0.8484 | 0.8007 | 0.8651 | 0.9660 | 0.9164 | 0.8695 | 0.8756 | 0.9685 | 0.7768 | 0.6697 | 0.9956 | 0.9754 | 0.9652 | 0.9976 | 0.9849 | 0.7977 | 0.9373 | 0.9923 | 0.9815 | 0.9828 | 0.8093 | 0.9445 | 0.9735 | 0.9933 | 0.9651 | 0.9854 | 0.9843 | 0.975 | 0.8123 |
| 0.1271 | 3.0 | 7179 | 0.1049 | 0.9218 | 0.9312 | 0.9265 | 0.9618 | 0.9950 | 0.9880 | 0.9172 | 0.9309 | 0.9652 | 0.8222 | 0.9160 | 0.9364 | 0.9749 | 0.9556 | 0.9211 | 0.9856 | 0.8939 | 0.8237 | 0.76 | 0.0080 | 0.9360 | 0.8735 | 0.5567 | 0.9993 | 0.9973 | 0.9872 | 0.9547 | 0.9773 | 0.9574 | 0.9694 | 0.0 | 0.8510 | 0.8032 | 0.9404 | 0.9844 | 0.9522 | 0.9294 | 0.8584 | 1.0 | 0.8603 | 0.8908 | 1.0 | 0.9829 | 0.9513 | 1.0 | 0.9792 | 0.8579 | 0.9413 | 0.9968 | 0.9513 | 0.9929 | 0.9278 | 0.9484 | 0.9862 | 0.9940 | 0.8884 | 0.9943 | 0.9616 | 0.9648 | 0.9395 |
| 0.1345 | 4.0 | 9572 | 0.0941 | 0.9463 | 0.9580 | 0.9521 | 0.9659 | 0.9975 | 0.9979 | 0.9356 | 0.9597 | 0.9084 | 0.9569 | 0.9827 | 0.9734 | 0.9835 | 0.9780 | 0.9634 | 0.9904 | 0.9393 | 0.8542 | 0.8915 | 0.4069 | 0.9636 | 0.8873 | 0.6572 | 0.9993 | 1.0 | 0.9923 | 0.9796 | 0.9983 | 0.9917 | 0.9972 | 0.0 | 0.8515 | 0.8027 | 0.9689 | 0.9943 | 0.9685 | 0.9668 | 0.8162 | 0.9912 | 0.9110 | 0.9364 | 1.0 | 0.9848 | 0.9734 | 0.9976 | 0.9949 | 0.9739 | 0.9609 | 0.9968 | 0.9906 | 0.9899 | 0.9772 | 0.9875 | 0.9855 | 0.9978 | 1.0 | 0.9972 | 0.9867 | 0.9817 | 0.9780 |
| 0.1067 | 5.0 | 11965 | 0.0724 | 0.9556 | 0.9659 | 0.9607 | 0.9699 | 0.9967 | 0.9965 | 0.9705 | 0.9742 | 0.9892 | 0.9736 | 0.9891 | 0.9794 | 0.9951 | 0.9860 | 0.9897 | 0.9892 | 0.9517 | 0.8386 | 0.9770 | 0.4186 | 0.9822 | 0.8869 | 0.7016 | 1.0 | 1.0 | 0.9949 | 0.9859 | 0.9983 | 1.0 | 0.9954 | 0.0075 | 0.8569 | 0.8012 | 0.9819 | 0.9979 | 0.9856 | 0.9843 | 0.9383 | 1.0 | 0.9318 | 0.9461 | 1.0 | 0.9905 | 1.0 | 1.0 | 0.9978 | 0.9906 | 0.9646 | 0.9981 | 0.9924 | 0.9970 | 0.9862 | 0.9966 | 0.9951 | 0.9970 | 1.0 | 0.9981 | 0.9933 | 1.0 | 0.9913 |
| 0.0808 | 6.0 | 14358 | 0.0693 | 0.9664 | 0.9732 | 0.9698 | 0.9728 | 1.0 | 1.0 | 0.9760 | 0.9897 | 0.9978 | 0.9907 | 0.9906 | 0.9930 | 0.9994 | 0.9939 | 1.0 | 0.9891 | 0.9590 | 0.9052 | 0.9875 | 0.7022 | 0.9892 | 0.9126 | 0.7438 | 1.0 | 1.0 | 1.0 | 0.9934 | 0.9991 | 1.0 | 1.0 | 0.1551 | 0.8393 | 0.8034 | 0.9942 | 0.9993 | 0.9928 | 0.9877 | 0.9770 | 1.0 | 0.9451 | 0.9773 | 1.0 | 0.9924 | 1.0 | 1.0 | 1.0 | 0.9929 | 0.9722 | 0.9974 | 0.9949 | 0.9970 | 0.9941 | 0.9972 | 0.9967 | 1.0 | 1.0 | 0.9991 | 1.0 | 1.0 | 0.9890 |
| 0.0779 | 7.0 | 16751 | 0.0697 | 0.9698 | 0.9756 | 0.9727 | 0.9739 | 0.9983 | 1.0 | 0.9815 | 0.9904 | 1.0 | 0.9938 | 0.9935 | 0.9930 | 0.9994 | 0.9935 | 1.0 | 0.9903 | 0.9584 | 0.9206 | 0.9917 | 0.7753 | 0.9914 | 0.9315 | 0.8305 | 1.0 | 1.0 | 1.0 | 0.9939 | 1.0 | 1.0 | 1.0 | 0.1404 | 0.8382 | 0.8029 | 0.9958 | 1.0 | 0.9944 | 0.9910 | 0.9875 | 1.0 | 0.9480 | 0.9788 | 1.0 | 0.9924 | 1.0 | 1.0 | 1.0 | 0.9929 | 0.9747 | 0.9961 | 0.9949 | 0.9970 | 0.9925 | 0.9983 | 0.9967 | 1.0 | 1.0 | 0.9991 | 1.0 | 1.0 | 0.9953 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0
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