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--- |
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license: mit |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: deberta-v3-base_ai4privacy_en |
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results: [] |
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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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# deberta-v3-base_ai4privacy_en |
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This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1055 |
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- Overall Precision: 0.8683 |
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- Overall Recall: 0.8949 |
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- Overall F1: 0.8814 |
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- Overall Accuracy: 0.9609 |
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- Accountname F1: 0.9898 |
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- Accountnumber F1: 0.9939 |
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- Age F1: 0.8397 |
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- Amount F1: 0.9169 |
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- Bic F1: 0.9012 |
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- Bitcoinaddress F1: 0.9583 |
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- Buildingnumber F1: 0.8109 |
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- City F1: 0.8011 |
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- Companyname F1: 0.9437 |
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- County F1: 0.8752 |
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- Creditcardcvv F1: 0.8635 |
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- Creditcardissuer F1: 0.9738 |
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- Creditcardnumber F1: 0.8771 |
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- Currency F1: 0.6542 |
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- Currencycode F1: 0.5566 |
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- Currencyname F1: 0.2214 |
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- Currencysymbol F1: 0.8640 |
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- Date F1: 0.8365 |
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- Dob F1: 0.5696 |
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- Email F1: 0.9914 |
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- Ethereumaddress F1: 0.9903 |
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- Eyecolor F1: 0.9076 |
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- Firstname F1: 0.8759 |
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- Gender F1: 0.9324 |
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- Height F1: 0.9046 |
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- Iban F1: 0.9899 |
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- Ip F1: 0.1137 |
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- Ipv4 F1: 0.8118 |
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- Ipv6 F1: 0.8091 |
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- Jobarea F1: 0.7895 |
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- Jobtitle F1: 0.9806 |
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- Jobtype F1: 0.9056 |
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- Lastname F1: 0.8179 |
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- Litecoinaddress F1: 0.8739 |
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- Mac F1: 1.0 |
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- Maskednumber F1: 0.8319 |
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- Middlename F1: 0.8419 |
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- Nearbygpscoordinate F1: 1.0 |
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- Ordinaldirection F1: 0.9682 |
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- Password F1: 0.9595 |
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- Phoneimei F1: 0.9930 |
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- Phonenumber F1: 0.9807 |
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- Pin F1: 0.7868 |
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- Prefix F1: 0.9355 |
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- Secondaryaddress F1: 0.9967 |
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- Sex F1: 0.9692 |
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- Ssn F1: 0.9898 |
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- State F1: 0.7407 |
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- Street F1: 0.7823 |
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- Time F1: 0.9500 |
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- Url F1: 0.9936 |
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- Useragent F1: 0.9976 |
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- Username F1: 0.9331 |
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- Vehiclevin F1: 0.9713 |
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- Vehiclevrm F1: 0.9493 |
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- Zipcode F1: 0.8634 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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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: cosine_with_restarts |
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- lr_scheduler_warmup_ratio: 0.2 |
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- num_epochs: 5 |
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### Training results |
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| 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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:--------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:------:|:--------:|:------------------:|:-----------:|:------------:|:---------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:----------------------:|:-------------------:|:-----------:|:------------:|:--------------:|:------:|:---------:|:-------------------:|:------:|:------:|:--------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:| |
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| 0.463 | 1.0 | 4350 | 0.3229 | 0.5378 | 0.5277 | 0.5327 | 0.8941 | 0.8722 | 0.7667 | 0.5849 | 0.2284 | 0.5391 | 0.7502 | 0.3143 | 0.1514 | 0.2844 | 0.2640 | 0.0086 | 0.5288 | 0.0 | 0.0956 | 0.0 | 0.0 | 0.3410 | 0.7146 | 0.0169 | 0.8043 | 0.9458 | 0.0090 | 0.4894 | 0.1550 | 0.0 | 0.8653 | 0.0 | 0.8168 | 0.7474 | 0.1611 | 0.4548 | 0.0035 | 0.3781 | 0.1472 | 0.8989 | 0.4641 | 0.0035 | 0.9955 | 0.0 | 0.7959 | 0.9464 | 0.7831 | 0.2258 | 0.7847 | 0.8639 | 0.5481 | 0.7480 | 0.0643 | 0.1795 | 0.7463 | 0.9683 | 0.9080 | 0.4569 | 0.8724 | 0.5152 | 0.5458 | |
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| 0.1944 | 2.0 | 8700 | 0.1709 | 0.7179 | 0.7495 | 0.7334 | 0.9387 | 0.9789 | 0.9718 | 0.6535 | 0.4640 | 0.6039 | 0.9240 | 0.6723 | 0.4777 | 0.8654 | 0.6234 | 0.7241 | 0.8713 | 0.6077 | 0.4598 | 0.0698 | 0.0104 | 0.6163 | 0.7518 | 0.4439 | 0.9803 | 0.9848 | 0.6276 | 0.6714 | 0.7937 | 0.6295 | 0.9538 | 0.0 | 0.8285 | 0.7976 | 0.5304 | 0.9253 | 0.6957 | 0.4694 | 0.7181 | 0.9892 | 0.6301 | 0.2027 | 0.9865 | 0.8016 | 0.7931 | 0.9888 | 0.9658 | 0.3231 | 0.8959 | 0.9721 | 0.8506 | 0.9692 | 0.3841 | 0.4389 | 0.9064 | 0.9905 | 0.9670 | 0.8341 | 0.9563 | 0.8449 | 0.7487 | |
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| 0.1275 | 3.0 | 13050 | 0.1174 | 0.8276 | 0.8506 | 0.8390 | 0.9559 | 0.9881 | 0.9896 | 0.7347 | 0.8484 | 0.8214 | 0.9571 | 0.7815 | 0.7437 | 0.9289 | 0.7794 | 0.8323 | 0.9754 | 0.8624 | 0.4890 | 0.4318 | 0.2006 | 0.8043 | 0.8066 | 0.5459 | 0.9858 | 0.9903 | 0.8511 | 0.8071 | 0.8187 | 0.8657 | 0.9486 | 0.0 | 0.8396 | 0.8049 | 0.7326 | 0.9720 | 0.8699 | 0.6714 | 0.8655 | 0.9957 | 0.8194 | 0.6478 | 1.0 | 0.9660 | 0.9331 | 0.9916 | 0.9711 | 0.6899 | 0.9302 | 0.9902 | 0.9413 | 0.9847 | 0.5684 | 0.7259 | 0.9381 | 0.9929 | 0.9953 | 0.9094 | 0.9598 | 0.9115 | 0.8324 | |
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| 0.0976 | 4.0 | 17400 | 0.1065 | 0.8624 | 0.8877 | 0.8749 | 0.9598 | 0.9907 | 0.9939 | 0.8312 | 0.9141 | 0.8689 | 0.9511 | 0.8027 | 0.8014 | 0.9538 | 0.8827 | 0.8599 | 0.9701 | 0.8634 | 0.6637 | 0.5488 | 0.1181 | 0.8541 | 0.8224 | 0.5333 | 0.9926 | 0.9876 | 0.9041 | 0.8664 | 0.9303 | 0.9207 | 0.9861 | 0.0591 | 0.8174 | 0.8098 | 0.7798 | 0.9686 | 0.9013 | 0.7845 | 0.8661 | 1.0 | 0.8091 | 0.8103 | 1.0 | 0.9785 | 0.9430 | 0.9916 | 0.9806 | 0.7778 | 0.9354 | 0.9913 | 0.9692 | 0.9885 | 0.7476 | 0.7658 | 0.9427 | 0.9889 | 0.9976 | 0.9346 | 0.9797 | 0.9570 | 0.8362 | |
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| 0.0886 | 5.0 | 21750 | 0.1055 | 0.8683 | 0.8949 | 0.8814 | 0.9609 | 0.9898 | 0.9939 | 0.8397 | 0.9169 | 0.9012 | 0.9583 | 0.8109 | 0.8011 | 0.9437 | 0.8752 | 0.8635 | 0.9738 | 0.8771 | 0.6542 | 0.5566 | 0.2214 | 0.8640 | 0.8365 | 0.5696 | 0.9914 | 0.9903 | 0.9076 | 0.8759 | 0.9324 | 0.9046 | 0.9899 | 0.1137 | 0.8118 | 0.8091 | 0.7895 | 0.9806 | 0.9056 | 0.8179 | 0.8739 | 1.0 | 0.8319 | 0.8419 | 1.0 | 0.9682 | 0.9595 | 0.9930 | 0.9807 | 0.7868 | 0.9355 | 0.9967 | 0.9692 | 0.9898 | 0.7407 | 0.7823 | 0.9500 | 0.9936 | 0.9976 | 0.9331 | 0.9713 | 0.9493 | 0.8634 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.0.0.post101 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.3 |
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