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  1. README.md +94 -0
  2. model.safetensors +1 -1
  3. trainer_state.json +0 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: distilbert-base-multilingual-cased
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: privacy-masknig
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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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+ # privacy-masknig
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+
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+ This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.3686
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+ - Overall Precision: 0.2885
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+ - Overall Recall: 0.2143
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+ - Overall F1: 0.2459
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+ - Overall Accuracy: 0.8688
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+ - Bod F1: 0.2375
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+ - Building F1: 0.2871
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+ - Cardissuer F1: 0.0
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+ - City F1: 0.2540
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+ - Country F1: 0.3055
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+ - Date F1: 0.2341
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+ - Driverlicense F1: 0.2233
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+ - Email F1: 0.2654
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+ - Geocoord F1: 0.1603
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+ - Givenname1 F1: 0.2161
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+ - Givenname2 F1: 0.1507
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+ - Idcard F1: 0.2472
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+ - Ip F1: 0.1851
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+ - Lastname1 F1: 0.2296
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+ - Lastname2 F1: 0.1305
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+ - Lastname3 F1: 0.1245
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+ - Pass F1: 0.1980
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+ - Passport F1: 0.2792
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+ - Postcode F1: 0.2794
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+ - Secaddress F1: 0.2486
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+ - Sex F1: 0.2933
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+ - Socialnumber F1: 0.2258
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+ - State F1: 0.2921
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+ - Street F1: 0.2177
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+ - Tel F1: 0.2409
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+ - Time F1: 0.2893
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+ - Title F1: 0.2814
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+ - Username F1: 0.2368
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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: 2
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+ - eval_batch_size: 2
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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_with_restarts
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+ - lr_scheduler_warmup_ratio: 0.2
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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 | 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 |
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+ |:-------------:|:-----:|:------:|:---------------:|:-----------------:|:--------------:|:----------:|:----------------:|:------:|:-----------:|:-------------:|:-------:|:----------:|:-------:|:----------------:|:--------:|:-----------:|:-------------:|:-------------:|:---------:|:------:|:------------:|:------------:|:------------:|:-------:|:-----------:|:-----------:|:-------------:|:------:|:---------------:|:--------:|:---------:|:------:|:-------:|:--------:|:-----------:|
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+ | 0.4774 | 1.0 | 62187 | 0.4611 | 0.1764 | 0.1017 | 0.1291 | 0.8380 | 0.1353 | 0.1842 | 0.0 | 0.1255 | 0.2337 | 0.1185 | 0.0936 | 0.1261 | 0.0500 | 0.0893 | 0.0506 | 0.1041 | 0.1122 | 0.1241 | 0.0463 | 0.0020 | 0.0486 | 0.1080 | 0.1726 | 0.1540 | 0.2044 | 0.0886 | 0.1588 | 0.1239 | 0.1406 | 0.1667 | 0.1583 | 0.1386 |
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+ | 0.4205 | 2.0 | 124374 | 0.4272 | 0.2372 | 0.1567 | 0.1887 | 0.8542 | 0.1831 | 0.2706 | 0.0 | 0.1923 | 0.2819 | 0.1821 | 0.1521 | 0.1863 | 0.1197 | 0.0997 | 0.0662 | 0.1473 | 0.1512 | 0.1443 | 0.0955 | 0.0527 | 0.1678 | 0.1997 | 0.2469 | 0.2066 | 0.2641 | 0.1827 | 0.2266 | 0.1602 | 0.1879 | 0.2372 | 0.2202 | 0.2069 |
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+ | 0.3367 | 3.0 | 186561 | 0.3686 | 0.2885 | 0.2143 | 0.2459 | 0.8688 | 0.2375 | 0.2871 | 0.0 | 0.2540 | 0.3055 | 0.2341 | 0.2233 | 0.2654 | 0.1603 | 0.2161 | 0.1507 | 0.2472 | 0.1851 | 0.2296 | 0.1305 | 0.1245 | 0.1980 | 0.2792 | 0.2794 | 0.2486 | 0.2933 | 0.2258 | 0.2921 | 0.2177 | 0.2409 | 0.2893 | 0.2814 | 0.2368 |
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+ | 0.301 | 4.0 | 248748 | 0.3734 | 0.3073 | 0.2484 | 0.2747 | 0.8737 | 0.2565 | 0.3272 | 0.1429 | 0.2634 | 0.3355 | 0.2707 | 0.2591 | 0.3032 | 0.2153 | 0.2458 | 0.1847 | 0.2757 | 0.2252 | 0.2594 | 0.1680 | 0.1551 | 0.2410 | 0.3080 | 0.2945 | 0.2488 | 0.3139 | 0.2522 | 0.3007 | 0.2447 | 0.2584 | 0.3107 | 0.2933 | 0.2880 |
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+ | 0.2451 | 5.0 | 310935 | 0.3895 | 0.3091 | 0.2664 | 0.2862 | 0.8744 | 0.2720 | 0.3313 | 0.0 | 0.2773 | 0.3470 | 0.2803 | 0.2732 | 0.3109 | 0.2202 | 0.2554 | 0.1945 | 0.2899 | 0.2382 | 0.2539 | 0.1800 | 0.1651 | 0.2514 | 0.3156 | 0.2982 | 0.2720 | 0.3364 | 0.2695 | 0.3196 | 0.2561 | 0.2732 | 0.3169 | 0.3054 | 0.3020 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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trainer_state.json ADDED
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