safetensors generated_from_trainer base_model:distilbert-base-multilingual-cased license:apache-2.0 region:us
---
license: apache-2.0
base_model: distilbert-base-multilingual-cased
tags:
- generated_from_trainer
model-index:
- name: ai4privacy_v2_adapter_en
  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. -->

# 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
