Create README.md
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README.md
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---
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language:
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- pl
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license: mit
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tags:
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- token-classification
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- named-entity-recognition
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- polish
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- anonymization
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- privacy
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- gdpr
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datasets:
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- custom
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metrics:
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- f1
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- precision
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- recall
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base_model: allegro/herbert-base-cased
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model-index:
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- name: AnonBERT-ENR
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results:
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- task:
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type: token-classification
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name: Named Entity Recognition
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metrics:
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- type: f1
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value: 0.84
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name: F1 Score
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widget:
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- text: "Nazywam się Jan Kowalski i mieszkam w Warszawie przy ulicy Marszałkowskiej 1. Mój email to jan.kowalski@example.com, a numer telefonu +48 123 456 789."
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example_title: "Personal Data Example"
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- text: "PESEL: 12345678901, dowód osobisty: ABC123456. Data urodzenia: 1990-05-20."
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example_title: "ID Numbers Example"
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---
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# AnonBERT-ENR: Polish Personal Data Anonymization Model
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**Fine-tuned HerBERT model for Named Entity Recognition and anonymization of sensitive personal information in Polish text.**
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> Achieves **84% F1 score** on test set for identifying and anonymizing 25+ types of personal data entities.
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## Model Description
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AnonBERT-ENR is a specialized NER model fine-tuned on [allegro/herbert-base-cased](https://huggingface.co/allegro/herbert-base-cased) for detecting and anonymizing personal data in Polish documents. The model is designed to help organizations comply with GDPR and other privacy regulations by automatically identifying sensitive information.
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### Key Features
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- ✅ **High Accuracy**: 84% F1 score on diverse test data
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- 🇵🇱 **Polish Language**: Optimized for Polish text and naming conventions
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- 🔒 **Privacy-Focused**: Detects 25+ types of sensitive personal information
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- 🚀 **Production Ready**: Includes complete anonymization pipeline
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- 📊 **Comprehensive Coverage**: Names, IDs, contact info, health data, political views, and more
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## Supported Entity Types
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The model can identify the following types of personal information:
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| Entity Type | Description | Example |
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|------------|-------------|---------|
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| `NAME` | First name | Jan |
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| `SURNAME` | Last name | Kowalski |
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| `EMAIL` | Email address | jan@example.pl |
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| `PHONE` | Phone number | +48 123 456 789 |
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| `PESEL` | National ID number | 12345678901 |
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| `DOCUMENT` | ID document number | ABC123456 |
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| `ADDRESS` | Street address | ul. Marszałkowska 1 |
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| `CITY` | City name | Warszawa |
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| `BANK_ACCOUNT` | Bank account number | PL61109010140000071219812874 |
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| `CREDIT_CARD` | Credit card number | 1234-5678-9012-3456 |
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| `DATE_BIRTH` | Date of birth | 1990-05-20 |
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| `DATE` | General date | 2024-01-15 |
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| `AGE` | Age | 25 lat |
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| `SEX` | Gender/sex | Mężczyzna, Kobieta |
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| `COMPANY` | Company name | Allegro |
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| `SCHOOL` | School name | Uniwersytet Warszawski |
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| `JOB` | Job title | Dyrektor |
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| `USERNAME` | Username/login | jan.kowalski |
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| `HEALTH` | Health information | cukrzyca |
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| `RELIGION` | Religious affiliation | katolik |
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| `POLITICAL` | Political views | liberalny |
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| `ETHNICITY` | Ethnicity | polska |
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| `ORIENTATION` | Sexual orientation | heteroseksualny |
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| `RELATIVE` | Family relation | matka |
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| `SECRET` | Secret/confidential info | hasło: abc123 |
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