---
language: pl
license: apache-2.0
tags:
- ner
- anonymization
- rodo
- gdpr
- polish
- herbert
- medical
- privacy
---

# HerBERT NER – RODO / GDPR Anonymization (PL)

Fine-tuned **HerBERT** model for **Named Entity Recognition (NER)** focused on
automatic anonymization of **RODO / GDPR-sensitive data** in **Polish-language texts**,
with emphasis on medical and administrative documents.

The model is designed to detect personal data, sensitive attributes,
identifiers, and contact information to support downstream anonymization pipelines.

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## ✨ Use case

- Anonymization of medical documentation
- GDPR / RODO compliance
- Text preprocessing before analytics or ML
- Research on privacy-preserving NLP for Polish

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## 🧠 Model details

- Base model: **HerBERT (Polish BERT)**
- Task: Token classification (NER)
- Labeling scheme: **BIO**
- Training: Supervised fine-tuning
- Framework: 🤗 Transformers + PyTorch

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## 🏷️ Supported entity classes

### Personal identifiers
- `NAME` – first names  
- `SURNAME` – last names  
- `AGE` – age  
- `DATE_OF_BIRTH` – date of birth  
- `DATE` – other dates identifying events  
- `SEX` – sex / gender (explicit)  
- `RELIGION` – religion  
- `POLITICAL_VIEW` – political views  
- `ETHNICITY` – ethnicity / nationality  
- `SEXUAL_ORIENTATION` – sexual orientation  
- `HEALTH` – health-related information  
- `RELATIVE` – family relations revealing identity  

### Contact & location
- `CITY` – city (general context)  
- `ADDRESS` – full address  
- `EMAIL` – email addresses  
- `PHONE` – phone numbers  

### Identifiers
- `PESEL` – Polish national ID number  
- `DOCUMENT_NUMBER` – ID / passport / license numbers  

### Professional & education
- `COMPANY` – employer  
- `SCHOOL_NAME` – school name  
- `JOB_TITLE` – job position  

### Financial
- `BANK_ACCOUNT` – bank account numbers  
- `CREDIT_CARD_NUMBER` – payment cards  

### Digital identifiers
- `USERNAME` – usernames / logins  
- `SECRET` – passwords, API keys  

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## 📊 Evaluation

- Validation F1-score: **~0.80**
- Precision-oriented configuration (privacy-first)
- Evaluation performed on held-out validation set

> Note: For anonymization tasks, recall is prioritized to minimize data leakage.

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