File size: 9,639 Bytes
128d970 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 |
---
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: PII-Detection
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. -->
# PII-Detection
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0643
- Overall Precision: 0.9370
- Overall Recall: 0.9502
- Overall F1: 0.9436
- Overall Accuracy: 0.9823
- Accountname F1: 0.9835
- Accountnumber F1: 0.9792
- Amount F1: 0.9439
- Bic F1: 0.8741
- Bitcoinaddress F1: 0.9478
- Buildingnumber F1: 0.6465
- City F1: 0.9865
- Company Name F1: 0.9583
- County F1: 0.9811
- Creditcardcvv F1: 0.9007
- Creditcardissuer F1: 0.9302
- Creditcardnumber F1: 0.8662
- Currency F1: 0.7101
- Currencycode F1: 0.7445
- Currencyname F1: 0.4375
- Currencysymbol F1: 0.5600
- Date F1: 0.9873
- Displayname F1: 0.4706
- Email F1: 0.9991
- Ethereumaddress F1: 0.9808
- Firstname F1: 0.8912
- Fullname F1: 0.9867
- Gender F1: 0.8462
- Iban F1: 0.9947
- Ip F1: 0.2642
- Ipv4 F1: 0.8165
- Ipv6 F1: 0.6330
- Jobarea F1: 0.9734
- Jobdescriptor F1: 0.8723
- Jobtitle F1: 0.9760
- Jobtype F1: 0.9150
- Lastname F1: 0.7589
- Litecoinaddress F1: 0.9123
- Mac F1: 1.0
- Maskednumber F1: 0.8000
- Middlename F1: 0.8033
- Name F1: 0.9966
- Nearbygpscoordinate F1: 1.0
- Number F1: 0.9159
- Ordinaldirection F1: 0.0
- Password F1: 0.9497
- Phoneimei F1: 0.9756
- Phone Number F1: 0.9244
- Pin F1: 0.8889
- Prefix F1: 0.9009
- Secondaryaddress F1: 0.9939
- Sex F1: 0.9032
- Sextype F1: 0.0
- Ssn F1: 0.8992
- State F1: 0.9931
- Street F1: 0.6906
- Streetaddress F1: 0.8523
- Suffix F1: 0.9026
- Time F1: 0.9796
- Url F1: 0.9973
- Useragent F1: 0.9839
- Username F1: 0.8900
- Vehiclevin F1: 0.9612
- Vehiclevrm F1: 0.9697
- Zipcode F1: 0.9387
## 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
- num_epochs: 5
### Training results
| 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:---------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:--------------:|:--------:|:------------------:|:------------:|:-----------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:----------------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:-------:|:----------------------:|:---------:|:-------------------:|:-----------:|:------------:|:---------------:|:------:|:---------:|:-------------------:|:------:|:----------:|:------:|:--------:|:---------:|:----------------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:|
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
|