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_it
  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_it

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: 0.0807
- Overall Precision: 0.8556
- Overall Recall: 0.8901
- Overall F1: 0.8725
- Overall Accuracy: 0.9669
- Accountname F1: 0.9869
- Accountnumber F1: 0.9762
- Age F1: 0.9719
- Amount F1: 0.7971
- Bic F1: 0.9536
- Bitcoinaddress F1: 0.9092
- Buildingnumber F1: 0.8371
- City F1: 0.8562
- Companyname F1: 0.9699
- County F1: 0.8920
- Creditcardcvv F1: 0.8794
- Creditcardissuer F1: 0.9681
- Creditcardnumber F1: 0.8276
- Currency F1: 0.5914
- Currencycode F1: 0.6059
- Currencyname F1: 0.0
- Currencysymbol F1: 0.8541
- Date F1: 0.6932
- Dob F1: 0.4620
- Email F1: 0.9911
- Ethereumaddress F1: 0.9856
- Eyecolor F1: 0.9257
- Firstname F1: 0.8746
- Gender F1: 0.9656
- Height F1: 0.9689
- Iban F1: 0.9936
- Ip F1: 0.0
- Ipv4 F1: 0.8059
- Ipv6 F1: 0.7656
- Jobarea F1: 0.9611
- Jobtitle F1: 0.9633
- Jobtype F1: 0.9625
- Lastname F1: 0.8054
- Litecoinaddress F1: 0.7454
- Mac F1: 0.9646
- Maskednumber F1: 0.7425
- Middlename F1: 0.4467
- Nearbygpscoordinate F1: 0.9989
- Ordinaldirection F1: 0.9868
- Password F1: 0.9839
- Phoneimei F1: 0.9878
- Phonenumber F1: 0.9787
- Pin F1: 0.6881
- Prefix F1: 0.9727
- Secondaryaddress F1: 0.9697
- Sex F1: 0.9858
- Ssn F1: 0.9778
- State F1: 0.8914
- Street F1: 0.8813
- Time F1: 0.9567
- Url F1: 0.9915
- Useragent F1: 0.9769
- Username F1: 0.9686
- Vehiclevin F1: 0.9635
- Vehiclevrm F1: 0.9747
- Zipcode F1: 0.8485

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:--------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:------:|:--------:|:------------------:|:-----------:|:------------:|:---------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:----------------------:|:-------------------:|:-----------:|:------------:|:--------------:|:------:|:---------:|:-------------------:|:------:|:------:|:--------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:|
| 0.7047        | 1.0   | 1275 | 0.3394          | 0.3552            | 0.4679         | 0.4038     | 0.8991           | 0.7758         | 0.6518           | 0.8829 | 0.1009    | 0.3687 | 0.7553            | 0.3720            | 0.0     | 0.1118         | 0.0698    | 0.0              | 0.0                 | 0.5544              | 0.0         | 0.0             | 0.0             | 0.2279            | 0.3929  | 0.0953 | 0.9181   | 0.8440             | 0.0         | 0.3652       | 0.1346    | 0.1034    | 0.8137  | 0.0    | 0.7184  | 0.6402  | 0.0143     | 0.5859      | 0.0        | 0.0661      | 0.0                | 0.7596 | 0.0112          | 0.0           | 0.9590                 | 0.0                 | 0.7307      | 0.9290       | 0.4443         | 0.0    | 0.0132    | 0.5173              | 0.6060 | 0.1941 | 0.0113   | 0.1307    | 0.7603  | 0.9491 | 0.8830       | 0.0048      | 0.4413        | 0.1774        | 0.3969     |
| 0.16          | 2.0   | 2550 | 0.1239          | 0.7404            | 0.8016         | 0.7698     | 0.9550           | 0.9820         | 0.9461           | 0.9464 | 0.4123    | 0.6098 | 0.8438            | 0.7318            | 0.5930  | 0.9095         | 0.6646    | 0.7774           | 0.9154              | 0.6495              | 0.4255      | 0.3522          | 0.0             | 0.6151            | 0.5260  | 0.1902 | 0.9729   | 0.9601             | 0.6775      | 0.8040       | 0.7830    | 0.8411    | 0.9417  | 0.0    | 0.8056  | 0.7966  | 0.8342     | 0.9225      | 0.7701     | 0.6583      | 0.5681             | 0.9002 | 0.6007          | 0.0633        | 0.9935                 | 0.9803              | 0.9649      | 0.9900       | 0.9462         | 0.0103 | 0.9599    | 0.9538              | 0.9509 | 0.9607 | 0.7129   | 0.7718    | 0.9339  | 0.9847 | 0.9481       | 0.8711      | 0.9539        | 0.8225        | 0.6985     |
| 0.1169        | 3.0   | 3825 | 0.1027          | 0.7616            | 0.8481         | 0.8025     | 0.9573           | 0.9836         | 0.9518           | 0.9628 | 0.5499    | 0.9358 | 0.9409            | 0.7946            | 0.7442  | 0.9514         | 0.8136    | 0.8579           | 0.9422              | 0.7882              | 0.5091      | 0.5460          | 0.0             | 0.6629            | 0.7015  | 0.3203 | 0.9834   | 0.9885             | 0.8499      | 0.8486       | 0.9179    | 0.9423    | 0.9465  | 0.0086 | 0.8009  | 0.3113  | 0.9312     | 0.9444      | 0.9125     | 0.7483      | 0.7813             | 0.9513 | 0.6076          | 0.3184        | 0.9957                 | 0.9837              | 0.9646      | 0.9911       | 0.9541         | 0.3744 | 0.9662    | 0.9657              | 0.9781 | 0.9667 | 0.7927   | 0.8152    | 0.9317  | 0.9890 | 0.9595       | 0.9338      | 0.9545        | 0.9578        | 0.7431     |
| 0.0928        | 4.0   | 5100 | 0.0893          | 0.8261            | 0.8714         | 0.8482     | 0.9647           | 0.9861         | 0.9574           | 0.9691 | 0.6684    | 0.9497 | 0.9340            | 0.8159            | 0.8093  | 0.9498         | 0.8534    | 0.87             | 0.9569              | 0.7950              | 0.5274      | 0.5591          | 0.0             | 0.7556            | 0.5915  | 0.4577 | 0.9893   | 0.9828             | 0.8894      | 0.8577       | 0.9431    | 0.9630    | 0.9801  | 0.0    | 0.8068  | 0.8130  | 0.9414     | 0.9530      | 0.9425     | 0.7637      | 0.8190             | 0.9515 | 0.6809          | 0.4021        | 0.9989                 | 0.9868              | 0.9747      | 0.9878       | 0.9736         | 0.6169 | 0.9639    | 0.9649              | 0.9851 | 0.9778 | 0.8287   | 0.8536    | 0.9459  | 0.9890 | 0.9567       | 0.9385      | 0.9408        | 0.9531        | 0.8158     |
| 0.0827        | 5.0   | 6375 | 0.0821          | 0.8531            | 0.8845         | 0.8685     | 0.9666           | 0.9885         | 0.9687           | 0.9712 | 0.7602    | 0.9500 | 0.9053            | 0.8303            | 0.8370  | 0.9699         | 0.8782    | 0.8691           | 0.9709              | 0.8098              | 0.5908      | 0.6369          | 0.0             | 0.8270            | 0.6587  | 0.4759 | 0.9881   | 0.9871             | 0.9303      | 0.8716       | 0.9633    | 0.9727    | 0.9810  | 0.0    | 0.8149  | 0.8104  | 0.9588     | 0.9655      | 0.9573     | 0.8000      | 0.7339             | 0.9690 | 0.7423          | 0.4433        | 0.9989                 | 0.9868              | 0.9831      | 0.9944       | 0.9787         | 0.6794 | 0.9735    | 0.9681              | 0.9858 | 0.9787 | 0.8805   | 0.8731    | 0.9544  | 0.9907 | 0.9740       | 0.9616      | 0.9536        | 0.9650        | 0.8385     |
| 0.077         | 6.0   | 7650 | 0.0807          | 0.8556            | 0.8901         | 0.8725     | 0.9669           | 0.9869         | 0.9762           | 0.9719 | 0.7971    | 0.9536 | 0.9092            | 0.8371            | 0.8562  | 0.9699         | 0.8920    | 0.8794           | 0.9681              | 0.8276              | 0.5914      | 0.6059          | 0.0             | 0.8541            | 0.6932  | 0.4620 | 0.9911   | 0.9856             | 0.9257      | 0.8746       | 0.9656    | 0.9689    | 0.9936  | 0.0    | 0.8059  | 0.7656  | 0.9611     | 0.9633      | 0.9625     | 0.8054      | 0.7454             | 0.9646 | 0.7425          | 0.4467        | 0.9989                 | 0.9868              | 0.9839      | 0.9878       | 0.9787         | 0.6881 | 0.9727    | 0.9697              | 0.9858 | 0.9778 | 0.8914   | 0.8813    | 0.9567  | 0.9915 | 0.9769       | 0.9686      | 0.9635        | 0.9747        | 0.8485     |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
