File size: 11,694 Bytes
fff7200 901b9c1 fff7200 d2b485d fff7200 c404a5e fff7200 d3c5cb0 fff7200 901b9c1 |
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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 |
---
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: distilbert_finetuned_ai4privacy
results: []
datasets:
- ai4privacy/pii-masking-65k
- ai4privacy/pii-masking-43k
language:
- en
metrics:
- f1
- precision
- recall
library_name: transformers
pipeline_tag: token-classification
---
<!-- 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. -->
# distilbert_finetuned_ai4privacy
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the english only section of ai4privacy/pii-masking-65k dataset.
## Useage
GitHub Implementation: [Ai4Privacy](https://github.com/Sripaad/ai4privacy)
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
### 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: 7
## Class wise metrics
It achieves the following results on the evaluation set:
- Loss: 0.0106
- Overall Precision: 0.9760
- Overall Recall: 0.9801
- Overall F1: 0.9780
- Overall Accuracy: 0.9977
- Accountname F1: 1.0
- Accountnumber F1: 1.0
- Amount F1: 0.9565
- Bic F1: 1.0
- Bitcoinaddress F1: 1.0
- Buildingnumber F1: 0.9753
- City F1: 0.9987
- Company Name F1: 1.0
- County F1: 1.0
- Creditcardcvv F1: 0.9701
- Creditcardissuer F1: 0.9939
- Creditcardnumber F1: 1.0
- Currency F1: 0.8668
- Currencycode F1: 0.8662
- Currencyname F1: 0.7582
- Currencysymbol F1: 0.36
- Date F1: 0.9944
- Displayname F1: 0.5970
- Email F1: 1.0
- Ethereumaddress F1: 1.0
- Firstname F1: 0.9493
- Fullname F1: 0.9982
- Gender F1: 0.9524
- Iban F1: 1.0
- Ip F1: 0.5543
- Ipv4 F1: 0.8700
- Ipv6 F1: 0.8863
- Jobarea F1: 0.9806
- Jobdescriptor F1: 0.6875
- Jobtitle F1: 0.9424
- Jobtype F1: 0.8811
- Lastname F1: 0.9052
- Litecoinaddress F1: 0.9848
- Mac F1: 1.0
- Maskednumber F1: 1.0
- Middlename F1: 0.7364
- Name F1: 0.9994
- Nearbygpscoordinate F1: 0.5
- Number F1: 1.0
- Password F1: 1.0
- Phoneimei F1: 1.0
- Phone Number F1: 1.0
- Pin F1: 0.9697
- Prefix F1: 0.9540
- Secondaryaddress F1: 0.9947
- Sex F1: 0.9650
- Sextype F1: 0.0
- Ssn F1: 1.0
- State F1: 0.9965
- Street F1: 0.9810
- Streetaddress F1: 0.9832
- Suffix F1: 0.7928
- Time F1: 0.9880
- Url F1: 0.9974
- Useragent F1: 1.0
- Username F1: 0.9746
- Vehiclevin F1: 1.0
- Vehiclevrm F1: 1.0
- Zipcode F1: 0.9969
## 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 | 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 |
|:-------------:|:-----:|:----:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:--------------:|:----------------:|:---------:|:------:|:-----------------:|:-----------------:|:-------:|:---------------:|:---------:|:----------------:|:-------------------:|:-------------------:|:-----------:|:---------------:|:---------------:|:-----------------:|:-------:|:--------------:|:--------:|:------------------:|:------------:|:-----------:|:---------:|:-------:|:------:|:-------:|:-------:|:----------:|:----------------:|:-----------:|:----------:|:-----------:|:------------------:|:------:|:---------------:|:-------------:|:-------:|:----------------------:|:---------:|:-----------:|:------------:|:---------------:|:------:|:---------:|:-------------------:|:------:|:----------:|:------:|:--------:|:---------:|:----------------:|:---------:|:-------:|:------:|:------------:|:-----------:|:-------------:|:-------------:|:----------:|
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
| 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 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3 |