Openray-ai/naija-privacy-filter
Domaine:
natural language processingType de record:
model
Créateur:
Ope
Hôte:
LoRA adapter for openai/privacy-filter on Nigerian-domain PII detection.
# Naija Privacy Filter
`naija-privacy-filter` is a v0.1 research preview for running and adapting
`openai/privacy-filter` on Nigerian-domain PII detection tasks.
This repo includes:
- a local CLI and FastAPI wrapper for privacy-filter inference
- deterministic span postprocessing for common boundary and formatting issues
- a tiny synthetic example dataset in `data/examples`
- a LoRA finetuning and eval-only workflow for `openai/privacy-filter`
- release documentation for publishing the adapter, dataset, and eval artifacts
Published artifacts:
- Adapter: `iamSamurai/privacy-filter-nigeria`
- Eval artifacts: `iamSamurai/openai-privacy-filter-naija-eval-artifacts`
## Release Status
Latest v5 eval against the internal stage2 v5 private mixed dataset, after
deterministic span postprocessing:
| Split | Typed span F1 | Precision | Recall | TP | FP | FN |
| --- | ---: | ---: | ---: | ---: | ---: | ---: |
| Validation | 0.9763 | 0.9707 | 0.9820 | 762 | 23 | 14 |
| Test | 0.9640 | 0.9593 | 0.9688 | 777 | 33 | 25 |
The v5 challenge split is hard-negative-only. Typed F1 is therefore not a
meaningful challenge metric. Use the false-positive diagnostics instead:
| Challenge diagnostic | Value |
| --- | ---: |
| Examples | 250 |
| Examples with predictions | 180 |
| False-positive example rate | 0.72 |
| Predicted false-positive spans | 456 |
This is a recall-oriented research adapter. Downstream users should expect to
tune thresholds, add deterministic filters, or finetune further for
precision-sensitive use cases. See MODEL_CARD.md,
DATASET_CARD.md, and the release workflow docs in
`naija-privacy-data/docs/` before publishing a release.
## Research Preview Scope
This project is intended for research, prototyping, and reproducible evaluation
of Nigerian-domain PII span detection. It is not a complete privacy product and
should not be used as the only control for regulatory, legal, medical,
financial, or irreversible privacy decisions.
The included public dataset is …