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deepaksiloka
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PII-Detection

Token Classification
Transformers
TensorBoard
Safetensors
distilbert
Generated from Trainer
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README.md ADDED
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+ ---
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+ library_name: transformers
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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: PII-Detection
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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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+ # PII-Detection
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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: 0.0643
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+ - Overall Precision: 0.9370
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+ - Overall Recall: 0.9502
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+ - Overall F1: 0.9436
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+ - Overall Accuracy: 0.9823
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+ - Accountname F1: 0.9835
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+ - Accountnumber F1: 0.9792
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+ - Amount F1: 0.9439
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+ - Bic F1: 0.8741
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+ - Bitcoinaddress F1: 0.9478
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+ - Buildingnumber F1: 0.6465
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+ - City F1: 0.9865
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+ - Company Name F1: 0.9583
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+ - County F1: 0.9811
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+ - Creditcardcvv F1: 0.9007
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+ - Creditcardissuer F1: 0.9302
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+ - Creditcardnumber F1: 0.8662
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+ - Currency F1: 0.7101
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+ - Currencycode F1: 0.7445
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+ - Currencyname F1: 0.4375
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+ - Currencysymbol F1: 0.5600
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+ - Date F1: 0.9873
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+ - Displayname F1: 0.4706
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+ - Email F1: 0.9991
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+ - Ethereumaddress F1: 0.9808
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+ - Firstname F1: 0.8912
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+ - Fullname F1: 0.9867
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+ - Gender F1: 0.8462
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+ - Iban F1: 0.9947
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+ - Ip F1: 0.2642
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+ - Ipv4 F1: 0.8165
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+ - Ipv6 F1: 0.6330
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+ - Jobarea F1: 0.9734
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+ - Jobdescriptor F1: 0.8723
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+ - Jobtitle F1: 0.9760
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+ - Jobtype F1: 0.9150
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+ - Lastname F1: 0.7589
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+ - Litecoinaddress F1: 0.9123
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+ - Mac F1: 1.0
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+ - Maskednumber F1: 0.8000
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+ - Middlename F1: 0.8033
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+ - Name F1: 0.9966
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+ - Nearbygpscoordinate F1: 1.0
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+ - Number F1: 0.9159
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+ - Ordinaldirection F1: 0.0
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+ - Password F1: 0.9497
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+ - Phoneimei F1: 0.9756
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+ - Phone Number F1: 0.9244
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+ - Pin F1: 0.8889
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+ - Prefix F1: 0.9009
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+ - Secondaryaddress F1: 0.9939
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+ - Sex F1: 0.9032
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+ - Sextype F1: 0.0
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+ - Ssn F1: 0.8992
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+ - State F1: 0.9931
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+ - Street F1: 0.6906
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+ - Streetaddress F1: 0.8523
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+ - Suffix F1: 0.9026
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+ - Time F1: 0.9796
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+ - Url F1: 0.9973
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+ - Useragent F1: 0.9839
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+ - Username F1: 0.8900
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+ - Vehiclevin F1: 0.9612
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+ - Vehiclevrm F1: 0.9697
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+ - Zipcode F1: 0.9387
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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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+ - 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 | 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 | Ordinaldirection 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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+ | 0.1445 | 1.0 | 1337 | 0.0873 | 0.8766 | 0.9038 | 0.8900 | 0.9710 | 0.9132 | 0.9245 | 0.8316 | 0.6260 | 0.7211 | 0.5392 | 0.9670 | 0.8041 | 0.9658 | 0.6462 | 0.7333 | 0.6833 | 0.5885 | 0.4341 | 0.016 | 0.0513 | 0.9726 | 0.0 | 0.9986 | 0.8778 | 0.7974 | 0.9812 | 0.5905 | 0.8744 | 0.0405 | 0.7125 | 0.7616 | 0.9148 | 0.0 | 0.7961 | 0.5644 | 0.5821 | 0.6442 | 0.9573 | 0.2375 | 0.1486 | 0.9865 | 0.3077 | 0.7009 | 0.0 | 0.8883 | 0.9697 | 0.7985 | 0.6387 | 0.8256 | 0.8772 | 0.8742 | 0.0 | 0.8593 | 0.9870 | 0.5492 | 0.8496 | 0.4966 | 0.9632 | 0.9754 | 0.9370 | 0.8839 | 0.8857 | 0.8 | 0.8691 |
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+ | 0.0599 | 2.0 | 2674 | 0.0573 | 0.9218 | 0.9369 | 0.9293 | 0.9786 | 0.9669 | 0.9679 | 0.9179 | 0.8429 | 0.78 | 0.4982 | 0.9831 | 0.9375 | 0.9774 | 0.8873 | 0.9153 | 0.8418 | 0.7326 | 0.6621 | 0.1102 | 0.5634 | 0.975 | 0.0 | 0.9972 | 0.9202 | 0.8603 | 0.9859 | 0.7925 | 0.9684 | 0.1164 | 0.7847 | 0.7129 | 0.9626 | 0.6752 | 0.9445 | 0.8734 | 0.6809 | 0.6931 | 0.9811 | 0.7468 | 0.6905 | 0.9943 | 1.0 | 0.8165 | 0.0 | 0.9385 | 0.9756 | 0.8465 | 0.8190 | 0.8899 | 0.9878 | 0.8861 | 0.0 | 0.8769 | 0.9905 | 0.6496 | 0.8784 | 0.8513 | 0.9662 | 0.9932 | 0.9490 | 0.9149 | 0.9394 | 0.9265 | 0.8732 |
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+ | 0.0411 | 3.0 | 4011 | 0.0517 | 0.9146 | 0.9444 | 0.9292 | 0.9804 | 0.9703 | 0.9837 | 0.9269 | 0.8939 | 0.8806 | 0.615 | 0.9837 | 0.9220 | 0.9811 | 0.8742 | 0.9249 | 0.8497 | 0.6351 | 0.6970 | 0.4037 | 0.5195 | 0.9824 | 0.3956 | 0.9989 | 0.9761 | 0.8779 | 0.9851 | 0.8081 | 0.9894 | 0.1043 | 0.8622 | 0.5398 | 0.9655 | 0.8333 | 0.9742 | 0.92 | 0.7368 | 0.8432 | 0.9905 | 0.7389 | 0.7661 | 0.9947 | 1.0 | 0.8505 | 0.0 | 0.9435 | 1.0 | 0.9204 | 0.8491 | 0.8920 | 0.9878 | 0.8889 | 0.0 | 0.9538 | 0.9896 | 0.6269 | 0.7057 | 0.8900 | 0.9796 | 0.9945 | 0.9641 | 0.8623 | 0.9606 | 0.9143 | 0.9672 |
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+ | 0.0226 | 4.0 | 5348 | 0.0599 | 0.9349 | 0.9482 | 0.9415 | 0.9824 | 0.9835 | 0.9746 | 0.9041 | 0.8939 | 0.8963 | 0.6707 | 0.9871 | 0.9141 | 0.9848 | 0.8707 | 0.9302 | 0.8702 | 0.6916 | 0.6618 | 0.3830 | 0.5195 | 0.9848 | 0.4651 | 0.9986 | 0.9581 | 0.8872 | 0.9862 | 0.8776 | 0.9892 | 0.2561 | 0.8682 | 0.7172 | 0.9726 | 0.8763 | 0.9814 | 0.9322 | 0.7266 | 0.7826 | 0.9952 | 0.8193 | 0.7256 | 0.9960 | 1.0 | 0.9014 | 0.0 | 0.9494 | 0.9816 | 0.9238 | 0.8462 | 0.9002 | 0.9939 | 0.8987 | 0.0 | 0.9091 | 0.9922 | 0.6997 | 0.8472 | 0.8821 | 0.9796 | 0.9973 | 0.9758 | 0.8940 | 0.9538 | 0.9624 | 0.9485 |
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+ | 0.0129 | 5.0 | 6685 | 0.0643 | 0.9370 | 0.9502 | 0.9436 | 0.9823 | 0.9835 | 0.9792 | 0.9439 | 0.8741 | 0.9478 | 0.6465 | 0.9865 | 0.9583 | 0.9811 | 0.9007 | 0.9302 | 0.8662 | 0.7101 | 0.7445 | 0.4375 | 0.5600 | 0.9873 | 0.4706 | 0.9991 | 0.9808 | 0.8912 | 0.9867 | 0.8462 | 0.9947 | 0.2642 | 0.8165 | 0.6330 | 0.9734 | 0.8723 | 0.9760 | 0.9150 | 0.7589 | 0.9123 | 1.0 | 0.8000 | 0.8033 | 0.9966 | 1.0 | 0.9159 | 0.0 | 0.9497 | 0.9756 | 0.9244 | 0.8889 | 0.9009 | 0.9939 | 0.9032 | 0.0 | 0.8992 | 0.9931 | 0.6906 | 0.8523 | 0.9026 | 0.9796 | 0.9973 | 0.9839 | 0.8900 | 0.9612 | 0.9697 | 0.9387 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.44.2
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+ - Pytorch 2.4.1+cu121
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+ - Datasets 3.0.1
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+ - Tokenizers 0.19.1
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