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distilbert_finetuned_ai4privacy

Token Classification
Transformers
PyTorch
ONNX
Safetensors
English
distilbert
Generated from Trainer
Inference Endpoints
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+ ---
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+ license: apache-2.0
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+ base_model: distilbert-base-uncased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: distilbert_finetuned_ai4privacy
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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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+ # distilbert_finetuned_ai4privacy
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+
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+ This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.0106
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+ - Overall Precision: 0.9760
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+ - Overall Recall: 0.9801
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+ - Overall F1: 0.9780
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+ - Overall Accuracy: 0.9977
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+ - Accountname F1: 1.0
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+ - Accountnumber F1: 1.0
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+ - Amount F1: 0.9565
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+ - Bic F1: 1.0
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+ - Bitcoinaddress F1: 1.0
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+ - Buildingnumber F1: 0.9753
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+ - City F1: 0.9987
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+ - Company Name F1: 1.0
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+ - County F1: 1.0
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+ - Creditcardcvv F1: 0.9701
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+ - Creditcardissuer F1: 0.9939
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+ - Creditcardnumber F1: 1.0
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+ - Currency F1: 0.8668
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+ - Currencycode F1: 0.8662
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+ - Currencyname F1: 0.7582
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+ - Currencysymbol F1: 0.36
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+ - Date F1: 0.9944
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+ - Displayname F1: 0.5970
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+ - Email F1: 1.0
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+ - Ethereumaddress F1: 1.0
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+ - Firstname F1: 0.9493
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+ - Fullname F1: 0.9982
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+ - Gender F1: 0.9524
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+ - Iban F1: 1.0
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+ - Ip F1: 0.5543
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+ - Ipv4 F1: 0.8700
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+ - Ipv6 F1: 0.8863
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+ - Jobarea F1: 0.9806
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+ - Jobdescriptor F1: 0.6875
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+ - Jobtitle F1: 0.9424
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+ - Jobtype F1: 0.8811
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+ - Lastname F1: 0.9052
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+ - Litecoinaddress F1: 0.9848
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+ - Mac F1: 1.0
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+ - Maskednumber F1: 1.0
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+ - Middlename F1: 0.7364
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+ - Name F1: 0.9994
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+ - Nearbygpscoordinate F1: 0.5
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+ - Number F1: 1.0
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+ - Password F1: 1.0
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+ - Phoneimei F1: 1.0
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+ - Phone Number F1: 1.0
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+ - Pin F1: 0.9697
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+ - Prefix F1: 0.9540
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+ - Secondaryaddress F1: 0.9947
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+ - Sex F1: 0.9650
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+ - Sextype F1: 0.0
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+ - Ssn F1: 1.0
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+ - State F1: 0.9965
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+ - Street F1: 0.9810
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+ - Streetaddress F1: 0.9832
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+ - Suffix F1: 0.7928
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+ - Time F1: 0.9880
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+ - Url F1: 0.9974
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+ - Useragent F1: 1.0
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+ - Username F1: 0.9746
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+ - Vehiclevin F1: 1.0
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+ - Vehiclevrm F1: 1.0
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+ - Zipcode F1: 0.9969
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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: 32
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+ - eval_batch_size: 32
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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: linear
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+ - lr_scheduler_warmup_ratio: 0.2
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+ - num_epochs: 7
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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 | Amount F1 | Bic F1 | Bitcoinaddress F1 | Buildingnumber F1 | City F1 | Company Name F1 | County F1 | Creditcardcvv F1 | Creditcardissuer F1 | Creditcardnumber F1 | Currency F1 | Currencycode F1 | Currencyname F1 | Currencysymbol F1 | Date F1 | Displayname F1 | Email F1 | Ethereumaddress F1 | Firstname F1 | Fullname F1 | Gender F1 | Iban F1 | Ip F1 | Ipv4 F1 | Ipv6 F1 | Jobarea F1 | Jobdescriptor F1 | Jobtitle F1 | Jobtype F1 | Lastname F1 | Litecoinaddress F1 | Mac F1 | Maskednumber F1 | Middlename F1 | Name F1 | Nearbygpscoordinate F1 | Number F1 | Password F1 | Phoneimei F1 | Phone Number F1 | Pin F1 | Prefix F1 | Secondaryaddress F1 | Sex F1 | Sextype F1 | Ssn F1 | State F1 | Street F1 | Streetaddress F1 | Suffix F1 | Time F1 | Url F1 | Useragent F1 | Username F1 | Vehiclevin F1 | Vehiclevrm F1 | Zipcode F1 |
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+ |:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:---------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:--------------:|:--------:|:------------------:|:------------:|:-----------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:----------------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:-------:|:----------------------:|:---------:|:-----------:|:------------:|:---------------:|:------:|:---------:|:-------------------:|:------:|:----------:|:------:|:--------:|:---------:|:----------------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:|
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+ | No log | 1.0 | 335 | 0.3836 | 0.6166 | 0.6314 | 0.6239 | 0.9080 | 0.0 | 0.5534 | 0.1940 | 0.0 | 0.4890 | 0.0 | 0.6856 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.3306 | 0.0 | 0.9420 | 0.4869 | 0.0704 | 0.9094 | 0.0 | 0.0877 | 0.0 | 0.6112 | 0.6779 | 0.0 | 0.0 | 0.0066 | 0.0 | 0.0 | 0.0 | 0.5589 | 0.3733 | 0.0 | 0.8152 | 0.0 | 0.0137 | 0.4013 | 0.3786 | 0.1117 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0104 | 0.0 | 0.5657 | 0.0 | 0.1786 | 0.7969 | 0.7734 | 0.0710 | 0.2662 | 0.0 | 0.2335 |
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+ | 1.2518 | 2.0 | 670 | 0.1360 | 0.7806 | 0.8283 | 0.8037 | 0.9571 | 0.7286 | 0.6427 | 0.6429 | 0.5102 | 0.6207 | 0.1322 | 0.9476 | 0.1031 | 0.7823 | 0.0303 | 0.0 | 0.4403 | 0.5190 | 0.0 | 0.0144 | 0.0 | 0.9125 | 0.0 | 0.9908 | 0.7273 | 0.7199 | 0.9762 | 0.0 | 0.2890 | 0.0 | 0.8519 | 0.5472 | 0.8354 | 0.0 | 0.7228 | 0.0 | 0.3513 | 0.0 | 0.8381 | 0.0117 | 0.0 | 0.9740 | 0.0 | 0.3070 | 0.7378 | 0.8857 | 0.4724 | 0.0 | 0.3978 | 0.4541 | 0.0278 | 0.0 | 0.2254 | 0.7361 | 0.0205 | 0.7132 | 0.0 | 0.9032 | 0.9870 | 0.9540 | 0.7943 | 0.6036 | 0.6184 | 0.6923 |
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+ | 0.1589 | 3.0 | 1005 | 0.0721 | 0.8615 | 0.9008 | 0.8807 | 0.9770 | 0.9164 | 0.9765 | 0.8283 | 0.5200 | 0.8077 | 0.6461 | 0.9790 | 0.6881 | 0.9592 | 0.5217 | 0.6769 | 0.5950 | 0.4094 | 0.5758 | 0.2397 | 0.0 | 0.9672 | 0.0 | 0.9994 | 0.9484 | 0.8170 | 0.9836 | 0.6437 | 0.9492 | 0.0 | 0.8424 | 0.8056 | 0.8999 | 0.0 | 0.7921 | 0.2667 | 0.5761 | 0.0 | 0.9841 | 0.0103 | 0.2147 | 0.9880 | 0.0 | 0.8051 | 0.8299 | 0.9947 | 0.7793 | 0.5161 | 0.7444 | 0.9894 | 0.7692 | 0.0 | 0.8182 | 0.9939 | 0.5244 | 0.4451 | 0.0 | 0.9762 | 0.9896 | 1.0 | 0.9008 | 0.9349 | 0.9605 | 0.9337 |
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+ | 0.1589 | 4.0 | 1340 | 0.0386 | 0.9175 | 0.9445 | 0.9308 | 0.9876 | 0.9597 | 0.9921 | 0.9041 | 0.9691 | 0.7944 | 0.7662 | 0.9940 | 0.9864 | 0.9801 | 0.7463 | 0.9560 | 0.8562 | 0.7383 | 0.7308 | 0.4286 | 0.0 | 0.9861 | 0.0 | 1.0 | 1.0 | 0.8726 | 0.9916 | 0.8434 | 0.9884 | 0.0382 | 0.8700 | 0.4811 | 0.9517 | 0.0741 | 0.8927 | 0.6732 | 0.7251 | 0.5629 | 1.0 | 0.6341 | 0.3353 | 0.9968 | 0.0 | 0.9648 | 0.9532 | 0.9947 | 0.9725 | 0.7719 | 0.8683 | 0.9947 | 0.9028 | 0.0 | 0.9302 | 0.9957 | 0.8287 | 0.8698 | 0.1389 | 0.9841 | 0.9974 | 0.9832 | 0.9303 | 0.9639 | 0.9673 | 0.9573 |
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+ | 0.0637 | 5.0 | 1675 | 0.0226 | 0.9402 | 0.9627 | 0.9513 | 0.9936 | 1.0 | 1.0 | 0.9355 | 0.9796 | 0.9813 | 0.8643 | 0.9987 | 0.9640 | 1.0 | 0.9197 | 0.9693 | 0.9368 | 0.7273 | 0.8052 | 0.5455 | 0.1395 | 0.9916 | 0.0615 | 1.0 | 0.9952 | 0.9051 | 0.9933 | 0.9048 | 1.0 | 0.2069 | 0.8700 | 0.5124 | 0.9728 | 0.4444 | 0.9107 | 0.7753 | 0.8147 | 0.9023 | 0.9741 | 0.8521 | 0.5990 | 0.9978 | 0.0 | 1.0 | 0.9970 | 1.0 | 0.9953 | 0.8713 | 0.8913 | 0.9735 | 0.9583 | 0.0 | 0.9924 | 0.9974 | 0.9041 | 0.9192 | 0.5053 | 0.9801 | 0.9974 | 1.0 | 0.9521 | 1.0 | 0.9934 | 0.975 |
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+ | 0.0333 | 6.0 | 2010 | 0.0136 | 0.9683 | 0.9774 | 0.9728 | 0.9966 | 0.9963 | 1.0 | 0.9454 | 1.0 | 1.0 | 0.9670 | 0.9987 | 1.0 | 1.0 | 0.9481 | 0.9880 | 1.0 | 0.8475 | 0.8701 | 0.7174 | 0.36 | 0.9944 | 0.4776 | 1.0 | 1.0 | 0.9441 | 0.9982 | 0.9398 | 1.0 | 0.3661 | 0.8519 | 0.7309 | 0.9785 | 0.7108 | 0.9474 | 0.8722 | 0.8909 | 0.9848 | 0.9895 | 1.0 | 0.7 | 0.9994 | 0.5 | 1.0 | 1.0 | 1.0 | 1.0 | 0.96 | 0.9535 | 0.9947 | 0.9718 | 0.0 | 1.0 | 0.9974 | 0.9810 | 0.9815 | 0.7037 | 0.9880 | 0.9974 | 1.0 | 0.9681 | 1.0 | 1.0 | 0.9938 |
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+ | 0.0333 | 7.0 | 2345 | 0.0106 | 0.9760 | 0.9801 | 0.9780 | 0.9977 | 1.0 | 1.0 | 0.9565 | 1.0 | 1.0 | 0.9753 | 0.9987 | 1.0 | 1.0 | 0.9701 | 0.9939 | 1.0 | 0.8668 | 0.8662 | 0.7582 | 0.36 | 0.9944 | 0.5970 | 1.0 | 1.0 | 0.9493 | 0.9982 | 0.9524 | 1.0 | 0.5543 | 0.8700 | 0.8863 | 0.9806 | 0.6875 | 0.9424 | 0.8811 | 0.9052 | 0.9848 | 1.0 | 1.0 | 0.7364 | 0.9994 | 0.5 | 1.0 | 1.0 | 1.0 | 1.0 | 0.9697 | 0.9540 | 0.9947 | 0.9650 | 0.0 | 1.0 | 0.9965 | 0.9810 | 0.9832 | 0.7928 | 0.9880 | 0.9974 | 1.0 | 0.9746 | 1.0 | 1.0 | 0.9969 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.31.0
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.13.1
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+ - Tokenizers 0.13.3