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--- |
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license: apache-2.0 |
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base_model: distilbert-base-cased |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: distilbert-base-cased-pii-en |
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results: [] |
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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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# distilbert-base-cased-pii-en |
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This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0412 |
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- Bod F1: 0.9572 |
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- Building F1: 0.9765 |
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- Cardissuer F1: 0.0 |
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- City F1: 0.9467 |
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- Country F1: 0.9664 |
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- Date F1: 0.9008 |
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- Driverlicense F1: 0.9304 |
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- Email F1: 0.9844 |
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- Geocoord F1: 0.9655 |
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- Givenname1 F1: 0.8097 |
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- Givenname2 F1: 0.5922 |
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- Idcard F1: 0.9202 |
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- Ip F1: 0.9807 |
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- Lastname1 F1: 0.7518 |
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- Lastname2 F1: 0.4932 |
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- Lastname3 F1: 0.0948 |
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- Pass F1: 0.8835 |
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- Passport F1: 0.9392 |
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- Postcode F1: 0.9766 |
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- Secaddress F1: 0.9749 |
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- Sex F1: 0.9687 |
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- Socialnumber F1: 0.9334 |
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- State F1: 0.9744 |
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- Street F1: 0.9534 |
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- Tel F1: 0.9553 |
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- Time F1: 0.9619 |
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- Title F1: 0.9502 |
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- Username F1: 0.9495 |
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- Precision: 0.9163 |
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- Recall: 0.9342 |
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- F1: 0.9252 |
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- Accuracy: 0.9903 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 64 |
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- eval_batch_size: 128 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.2 |
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- lr_scheduler_warmup_steps: 3000 |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Bod F1 | Building F1 | Cardissuer F1 | City F1 | Country F1 | Date F1 | Driverlicense F1 | Email F1 | Geocoord F1 | Givenname1 F1 | Givenname2 F1 | Idcard F1 | Ip F1 | Lastname1 F1 | Lastname2 F1 | Lastname3 F1 | Pass F1 | Passport F1 | Postcode F1 | Secaddress F1 | Sex F1 | Socialnumber F1 | State F1 | Street F1 | Tel F1 | Time F1 | Title F1 | Username F1 | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:-----------:|:-------------:|:-------:|:----------:|:-------:|:----------------:|:--------:|:-----------:|:-------------:|:-------------:|:---------:|:------:|:------------:|:------------:|:------------:|:-------:|:-----------:|:-----------:|:-------------:|:------:|:---------------:|:--------:|:---------:|:------:|:-------:|:--------:|:-----------:|:---------:|:------:|:------:|:--------:| |
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| 0.2231 | 2.1368 | 1000 | 0.1075 | 0.8895 | 0.9243 | 0.0 | 0.6385 | 0.8816 | 0.7987 | 0.6178 | 0.9512 | 0.6982 | 0.4720 | 0.0 | 0.5863 | 0.9082 | 0.5397 | 0.0 | 0.0 | 0.6402 | 0.6167 | 0.7858 | 0.6568 | 0.8626 | 0.7003 | 0.8859 | 0.6843 | 0.8146 | 0.9158 | 0.7302 | 0.8258 | 0.7239 | 0.7677 | 0.7452 | 0.9739 | |
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| 0.069 | 4.2735 | 2000 | 0.0540 | 0.9478 | 0.9698 | 0.0 | 0.9055 | 0.9433 | 0.8854 | 0.8801 | 0.9783 | 0.9676 | 0.7201 | 0.2896 | 0.8815 | 0.9731 | 0.6380 | 0.1939 | 0.0 | 0.8266 | 0.8883 | 0.9592 | 0.9645 | 0.9370 | 0.8931 | 0.9390 | 0.9237 | 0.9386 | 0.9455 | 0.9087 | 0.9195 | 0.8707 | 0.9044 | 0.8872 | 0.9865 | |
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| 0.0447 | 6.4103 | 3000 | 0.0455 | 0.9537 | 0.9756 | 0.0 | 0.9327 | 0.9593 | 0.9007 | 0.9030 | 0.9792 | 0.9633 | 0.7860 | 0.4337 | 0.9056 | 0.9747 | 0.7205 | 0.3587 | 0.0 | 0.8557 | 0.9144 | 0.9712 | 0.9732 | 0.9661 | 0.9204 | 0.9689 | 0.9426 | 0.9552 | 0.9588 | 0.9374 | 0.9413 | 0.9011 | 0.9232 | 0.9120 | 0.9887 | |
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| 0.0293 | 8.5470 | 4000 | 0.0412 | 0.9572 | 0.9765 | 0.0 | 0.9467 | 0.9664 | 0.9008 | 0.9304 | 0.9844 | 0.9655 | 0.8097 | 0.5922 | 0.9202 | 0.9807 | 0.7518 | 0.4932 | 0.0948 | 0.8835 | 0.9392 | 0.9766 | 0.9749 | 0.9687 | 0.9334 | 0.9744 | 0.9534 | 0.9553 | 0.9619 | 0.9502 | 0.9495 | 0.9163 | 0.9342 | 0.9252 | 0.9903 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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