--- license: apache-2.0 base_model: distilbert-base-multilingual-cased tags: - generated_from_trainer model-index: - name: ai4privacy_v2_adapter_en results: [] --- # ai4privacy_v2_adapter_en This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.1079 - Overall Precision: 0.8136 - Overall Recall: 0.8836 - Overall F1: 0.8472 - Overall Accuracy: 0.9560 - Accountname F1: 0.9712 - Accountnumber F1: 0.9677 - Age F1: 0.8432 - Amount F1: 0.7929 - Bic F1: 0.9689 - Bitcoinaddress F1: 0.9343 - Buildingnumber F1: 0.8405 - City F1: 0.8139 - Companyname F1: 0.9310 - County F1: 0.8406 - Creditcardcvv F1: 0.8889 - Creditcardissuer F1: 0.9661 - Creditcardnumber F1: 0.8404 - Currency F1: 0.5968 - Currencycode F1: 0.6556 - Currencyname F1: 0.0182 - Currencysymbol F1: 0.8176 - Date F1: 0.7858 - Dob F1: 0.4636 - Email F1: 0.9928 - Ethereumaddress F1: 0.9941 - Eyecolor F1: 0.7859 - Firstname F1: 0.8699 - Gender F1: 0.8945 - Height F1: 0.9227 - Iban F1: 0.9730 - Ip F1: 0.0497 - Ipv4 F1: 0.8345 - Ipv6 F1: 0.4659 - Jobarea F1: 0.9131 - Jobtitle F1: 0.9599 - Jobtype F1: 0.9303 - Lastname F1: 0.8016 - Litecoinaddress F1: 0.8483 - Mac F1: 0.9817 - Maskednumber F1: 0.7049 - Middlename F1: 0.5006 - Nearbygpscoordinate F1: 0.9969 - Ordinaldirection F1: 0.9519 - Password F1: 0.9780 - Phoneimei F1: 0.9928 - Phonenumber F1: 0.9752 - Pin F1: 0.7525 - Prefix F1: 0.9121 - Secondaryaddress F1: 0.9474 - Sex F1: 0.9770 - Ssn F1: 0.9771 - State F1: 0.8680 - Street F1: 0.8677 - Time F1: 0.9516 - Url F1: 0.9975 - Useragent F1: 0.9844 - Username F1: 0.9669 - Vehiclevin F1: 0.9775 - Vehiclevrm F1: 0.9888 - Zipcode F1: 0.8203 ## 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: 32 - eval_batch_size: 32 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.2 - num_epochs: 6 ### 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 | |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:--------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:------:|:--------:|:------------------:|:-----------:|:------------:|:---------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:----------------------:|:-------------------:|:-----------:|:------------:|:--------------:|:------:|:---------:|:-------------------:|:------:|:------:|:--------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:| | 0.9109 | 1.0 | 1088 | 0.5093 | 0.2688 | 0.3282 | 0.2956 | 0.8499 | 0.2034 | 0.3040 | 0.0752 | 0.1147 | 0.0935 | 0.5972 | 0.0673 | 0.0 | 0.0024 | 0.0 | 0.0 | 0.0 | 0.1141 | 0.0 | 0.0 | 0.0 | 0.0112 | 0.7137 | 0.0 | 0.9095 | 0.9119 | 0.0 | 0.3152 | 0.0 | 0.0 | 0.8248 | 0.0 | 0.6785 | 0.4199 | 0.0 | 0.0475 | 0.0 | 0.0167 | 0.0907 | 0.6333 | 0.0011 | 0.0 | 0.9525 | 0.0 | 0.6438 | 0.3918 | 0.2703 | 0.0 | 0.0099 | 0.2395 | 0.0 | 0.0220 | 0.0 | 0.0276 | 0.5557 | 0.9658 | 0.8157 | 0.0415 | 0.3955 | 0.0106 | 0.0181 | | 0.2793 | 2.0 | 2176 | 0.1903 | 0.6974 | 0.7582 | 0.7265 | 0.9309 | 0.9684 | 0.8789 | 0.7561 | 0.3604 | 0.7609 | 0.8715 | 0.6492 | 0.4956 | 0.8028 | 0.5558 | 0.7756 | 0.6575 | 0.5363 | 0.4671 | 0.128 | 0.0 | 0.5910 | 0.7731 | 0.0186 | 0.9838 | 0.9465 | 0.4482 | 0.7689 | 0.5160 | 0.7446 | 0.9234 | 0.0 | 0.8226 | 0.8007 | 0.5589 | 0.8712 | 0.6553 | 0.6634 | 0.7056 | 0.9315 | 0.0382 | 0.0661 | 0.9954 | 0.8828 | 0.9270 | 0.9693 | 0.8621 | 0.1481 | 0.8783 | 0.9120 | 0.9262 | 0.8707 | 0.6693 | 0.7378 | 0.9152 | 0.9886 | 0.9524 | 0.8859 | 0.8352 | 0.8976 | 0.6466 | | 0.1707 | 3.0 | 3264 | 0.1388 | 0.7704 | 0.8319 | 0.8000 | 0.9467 | 0.9702 | 0.9396 | 0.8120 | 0.6102 | 0.9298 | 0.9034 | 0.7409 | 0.6205 | 0.8922 | 0.7128 | 0.8446 | 0.9218 | 0.6983 | 0.5504 | 0.5380 | 0.0106 | 0.6877 | 0.6125 | 0.3259 | 0.9892 | 0.9956 | 0.6647 | 0.8358 | 0.7540 | 0.8859 | 0.9430 | 0.0 | 0.8313 | 0.7993 | 0.8235 | 0.9241 | 0.8191 | 0.7504 | 0.7882 | 0.9412 | 0.5129 | 0.4005 | 0.9969 | 0.9452 | 0.9618 | 0.9900 | 0.9452 | 0.5018 | 0.8959 | 0.9348 | 0.9406 | 0.9524 | 0.7643 | 0.7747 | 0.9497 | 0.9943 | 0.9714 | 0.9274 | 0.9048 | 0.9646 | 0.7387 | | 0.1373 | 4.0 | 4352 | 0.1197 | 0.7751 | 0.8645 | 0.8174 | 0.9509 | 0.9651 | 0.9510 | 0.8263 | 0.7169 | 0.9592 | 0.9254 | 0.8151 | 0.7795 | 0.9148 | 0.8060 | 0.8808 | 0.9524 | 0.8007 | 0.5676 | 0.5656 | 0.0249 | 0.8000 | 0.7858 | 0.3425 | 0.9910 | 0.9869 | 0.7552 | 0.8609 | 0.8397 | 0.8981 | 0.9779 | 0.0278 | 0.8309 | 0.3179 | 0.8643 | 0.9475 | 0.9000 | 0.7812 | 0.8415 | 0.9749 | 0.6191 | 0.4617 | 0.9969 | 0.9519 | 0.9711 | 0.9914 | 0.9700 | 0.6733 | 0.9088 | 0.9421 | 0.9732 | 0.9671 | 0.8360 | 0.8494 | 0.9442 | 0.9943 | 0.9618 | 0.9487 | 0.9838 | 0.9672 | 0.8093 | | 0.1202 | 5.0 | 5440 | 0.1106 | 0.8264 | 0.8796 | 0.8522 | 0.9564 | 0.9720 | 0.9634 | 0.8360 | 0.7423 | 0.9756 | 0.9327 | 0.8268 | 0.8031 | 0.9134 | 0.8404 | 0.8792 | 0.9660 | 0.7957 | 0.5723 | 0.6159 | 0.0167 | 0.8132 | 0.7914 | 0.4301 | 0.9928 | 0.9941 | 0.7544 | 0.8659 | 0.8871 | 0.9121 | 0.9695 | 0.0137 | 0.8361 | 0.7008 | 0.9108 | 0.9623 | 0.9126 | 0.7783 | 0.8459 | 0.9749 | 0.6770 | 0.4944 | 0.9985 | 0.9519 | 0.9754 | 0.9900 | 0.9673 | 0.7647 | 0.9115 | 0.9484 | 0.9760 | 0.9771 | 0.8588 | 0.8590 | 0.9526 | 0.9975 | 0.9820 | 0.9547 | 0.9871 | 0.9916 | 0.8133 | | 0.1065 | 6.0 | 6528 | 0.1079 | 0.8136 | 0.8836 | 0.8472 | 0.9560 | 0.9712 | 0.9677 | 0.8432 | 0.7929 | 0.9689 | 0.9343 | 0.8405 | 0.8139 | 0.9310 | 0.8406 | 0.8889 | 0.9661 | 0.8404 | 0.5968 | 0.6556 | 0.0182 | 0.8176 | 0.7858 | 0.4636 | 0.9928 | 0.9941 | 0.7859 | 0.8699 | 0.8945 | 0.9227 | 0.9730 | 0.0497 | 0.8345 | 0.4659 | 0.9131 | 0.9599 | 0.9303 | 0.8016 | 0.8483 | 0.9817 | 0.7049 | 0.5006 | 0.9969 | 0.9519 | 0.9780 | 0.9928 | 0.9752 | 0.7525 | 0.9121 | 0.9474 | 0.9770 | 0.9771 | 0.8680 | 0.8677 | 0.9516 | 0.9975 | 0.9844 | 0.9669 | 0.9775 | 0.9888 | 0.8203 | ### Framework versions - Transformers 4.35.2 - Pytorch 2.1.0+cu121 - Datasets 2.17.0 - Tokenizers 0.15.1