llama-ai4privacy-english-anonymiser-openpii Open Source Model - Accurately Anonymize Personal Information in English Texts

Llama Ai4privacy English Anonymiser Openpii

Developed by ai4privacy

A model specifically designed for anonymizing Personally Identifiable Information (PII) in English text, fine-tuned on a dataset of 500,000 English PII entries, achieving a comprehensive F1 score of 98.82%.

Sequence Labeling

Transformers

EnglishOpen Source License:MIT #English PII Anonymization #High-Precision Anonymization #Financial Compliance Specialized

Downloads 6,159

Release Time : 2/27/2025

Model Overview

This model is used to identify and anonymize Personally Identifiable Information (PII) in English text, supporting recognition of 20+ PII types, including names, ID numbers, contact details, and other sensitive information.

Model Features

High-Precision PII Recognition

Achieves a comprehensive F1 score of 98.82%, with 100% accuracy in recognizing certain labels such as passport numbers and dates.

Extensive PII Type Coverage

Supports recognition of 20+ PII types, including ID numbers, contact details, addresses, and other sensitive information.

Legal Compliance Design

Developed specifically for data privacy protection scenarios, compliant with legal requirements for personal information processing.

Model Capabilities

Personally Identifiable Information Recognition

Sensitive Information Anonymization

Text Anonymization Processing

Multi-Type PII Classification

Use Cases

Data Privacy Protection

User Data Anonymization

Automatically anonymizes PII in user-submitted forms, logs, and other texts.

Reduces the risk of data breaches and complies with privacy regulations such as GDPR.

Enterprise Data Governance

Internal Document Anonymization

Automatically identifies and masks sensitive employee and customer information in corporate documents.

Protects personal privacy when securely sharing internal data.

🚀 English Anonymiser OpenPII (Ai4Privacy)

This model is crafted to redact Personally Identifiable Information (PII) from English text. It has been exclusively fine - tuned on the English subset of the open - pii - masking - 500k - ai4privacy dataset.

✨ Features

PII Redaction: Specifically designed to redact PII from English text.
Fine - Tuned: Fine - tuned on the English subset of a specific dataset for better performance.

📚 Documentation

🔍 Evaluation Metrics

The table below summarizes the detailed evaluation results per PII label:

Label	TP	FP	FN	Accuracy	Precision	Recall	F1 Score
SURNAME	3724	0	26	99.31%	100.0%	99.31%	99.65%
O (Non - PII)	0	368	0	99.36%	n/a	n/a	n/a
TIME	1934	0	2	99.90%	100.0%	99.90%	99.95%
DRIVERLICENSENUM	505	0	2	99.61%	100.0%	99.61%	99.80%
PASSPORTNUM	566	0	0	100.0%	100.0%	100.0%	100.0%
GIVENNAME	7557	0	163	97.89%	100.0%	97.89%	98.93%
TELEPHONENUM	3637	0	4	99.89%	100.0%	99.89%	99.95%
BUILDINGNUM	418	0	8	98.12%	100.0%	98.12%	99.05%
AGE	164	0	5	97.04%	100.0%	97.04%	98.50%
DATE	2335	0	0	100.0%	100.0%	100.0%	100.0%
CITY	1717	0	85	95.28%	100.0%	95.28%	97.58%
TITLE	363	0	21	94.53%	100.0%	94.53%	97.19%
IDCARDNUM	2008	0	12	99.41%	100.0%	99.41%	99.70%
GENDER	120	0	1	99.17%	100.0%	99.17%	99.59%
CREDITCARDNUMBER	555	0	3	99.46%	100.0%	99.46%	99.73%
SEX	77	0	2	97.47%	100.0%	97.47%	98.72%
STREET	1379	0	8	99.42%	100.0%	99.42%	99.71%
TAXNUM	343	0	14	96.08%	100.0%	96.08%	98.00%
EMAIL	2607	0	1	99.96%	100.0%	99.96%	99.98%
SOCIALNUM	421	0	1	99.76%	100.0%	99.76%	99.88%
ZIPCODE	418	0	8	98.12%	100.0%	98.12%	99.05%

Overall Evaluation:

Accuracy: 99.17%
Precision: 98.82%
Recall: 98.83%
F1 Score: 98.82%
Total True Positives (TP): 30,848
Total False Positives (FP): 368
Total False Negatives (FN): 366

Macro - Averaged Metrics:

Accuracy: 98.56%
Precision: 95.24%
Recall: 93.83%
F1 Score: 94.52%

🔧 Model Behavior & Limitations

Evaluation Focus:
The metrics shown above reflect performance on the test split of the open - pii - masking - 500k - ai4privacy dataset. Real - world performance may vary and requires additional measures. Feel free to contact support (at) ai4privacy.com

📄 Disclaimer

This model card details the evaluation metrics and fine - tuning parameters for the English anonymiser. Please note:

The model is provided as - is under the MIT License.
It is intended solely for redaction purposes and does not perform full PII classification
Users should carefully test and evaluate its performance on their own data before deploying in production environments.

Ai4Privacy – Committed to protecting personal data in the age of AI.

Featured Recommended AI Models

Empowering the Future, Your AI Solution Knowledge Base

English 简体中文繁體中文にほんご