AnonBERT-ENR is a specialized NER model fine-tuned on 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.

Key Features

✅ High Accuracy: 84% F1 score on diverse test data
🇵🇱 Polish Language: Optimized for Polish text and naming conventions
🔒 Privacy-Focused: Detects 25+ types of sensitive personal information
🚀 Production Ready: Includes complete anonymization pipeline
📊 Comprehensive Coverage: Names, IDs, contact info, health data, political views, and more

Supported Entity Types

The model can identify the following types of personal information:

Entity Type	Description	Example
`NAME`	First name	Jan
`SURNAME`	Last name	Kowalski
`EMAIL`	Email address	jan@example.pl
`PHONE`	Phone number	+48 123 456 789
`PESEL`	National ID number	12345678901
`DOCUMENT`	ID document number	ABC123456
`ADDRESS`	Street address	ul. Marszałkowska 1
`CITY`	City name	Warszawa
`BANK_ACCOUNT`	Bank account number	PL61109010140000071219812874
`CREDIT_CARD`	Credit card number	1234-5678-9012-3456
`DATE_BIRTH`	Date of birth	1990-05-20
`DATE`	General date	2024-01-15
`AGE`	Age	25 lat
`SEX`	Gender/sex	Mężczyzna, Kobieta
`COMPANY`	Company name	Allegro
`SCHOOL`	School name	Uniwersytet Warszawski
`JOB`	Job title	Dyrektor
`USERNAME`	Username/login	jan.kowalski
`HEALTH`	Health information	cukrzyca
`RELIGION`	Religious affiliation	katolik
`POLITICAL`	Political views	liberalny
`ETHNICITY`	Ethnicity	polska
`ORIENTATION`	Sexual orientation	heteroseksualny
`RELATIVE`	Family relation	matka
`SECRET`	Secret/confidential info	hasło: abc123

Matela7/AnonBert-ENR

AnonBERT-ENR: Polish Personal Data Anonymization Model

Model Description

Key Features

Supported Entity Types

Matela7/
AnonBert-ENR