---
license: apache-2.0
base_model: openai/privacy-filter
pipeline_tag: token-classification
tags:
  - privacy
  - pii
  - token-classification
  - privacy-filter
  - partial-ssn
library_name: transformers
---

# PrivacyFilterTuned

PrivacyFilterTuned is a finetuned version of
[openai/privacy-filter](https://huggingface.co/openai/privacy-filter). It is
adapted for privacy filtering workflows where partial SSNs and related compact
identifiers should be captured more consistently.

The main target behavior is improved detection of account-number style spans
such as:

- `SSN ending 1234`
- `SSN last four are 1234`
- `partial SSN 1234`
- nearby MRN, member ID, student ID, and similar identifier patterns

The model keeps the original Privacy Filter label space. Partial SSNs are
labeled as `account_number`.

## Base Model

This checkpoint is based on `openai/privacy-filter`, a bidirectional token
classification model for PII detection and masking. The base model detects the
following span categories:

- `account_number`
- `private_address`
- `private_date`
- `private_email`
- `private_person`
- `private_phone`
- `private_url`
- `secret`

## Finetuning

This checkpoint was finetuned locally on a small targeted dataset of healthcare,
education, and finance-style prompts. The data focuses on partial SSNs and
identifier boundary cases.

## Limitations

This model is a privacy-filtering aid, not an anonymization or compliance
guarantee. It may still miss sensitive spans or redact spans that should remain
visible. Evaluate it on your own in-domain data before production use, and keep
human review paths for high-sensitivity workflows.

The finetuning set is small and targeted, so improvements are expected mainly
around partial SSNs and similar compact identifiers rather than broad PII
coverage.

## Usage

With this repository downloaded locally:

```bash
python -m opf "Patient Alice Smith has SSN ending 1234." \
  --checkpoint /path/to/privacyfiltertuned \
  --device cpu
```

For evaluation:

```bash
python -m opf eval /path/to/eval.jsonl \
  --checkpoint /path/to/privacyfiltertuned \
  --device cpu
```