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deberta-v3-base_ai4privacy_en

Token Classification
Transformers
PyTorch
deberta-v2
Generated from Trainer
Inference Endpoints
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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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+
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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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+ # deberta-v3-base_ai4privacy_en
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+
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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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+
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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: 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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+
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+ ### Training results
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+
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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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+
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+
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+ ### Framework versions
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+
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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