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phi-detector-model
lethalantidote/phi-detector-model
phi-detector-model is a token classification model from lethalantidote. Use it when you need labels on individual words, such as names. It is set up for transformers.
This token-classification model was fine-tuned from StanfordAIMI/stanford-deidentifier-base using Synthetic Synthea-derived clinical templates. It recognizes three entity types with the BIO labels stored in config.json.
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At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Aug 6, 2026
- Updated
- Aug 7, 2026
- SHA
- 99b85aa2
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Base models
Model card
From the Hugging Face model README
Synthetic PHI Detector
This token-classification model was fine-tuned from StanfordAIMI/stanford-deidentifier-base using
Synthetic Synthea-derived clinical templates. It recognizes three entity types
with the BIO labels stored in config.json.
Training examples: 5997
| Entity | Strict seqeval F1 |
|---|---|
| MEDICAL_RECORD | 1.0000 |
| DIAGNOSIS | 1.0000 |
| MEDICATION | 1.0000 |
Overall strict seqeval F1: 1.0000
Limitations
Synthetic templates do not represent every institution, document style, or identifier format. False negatives and false positives are expected. This model assists PHI detection and is not a compliance guarantee or substitute for human review and layered detection controls.
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- Languages
- en
- Created
- Aug 6, 2026
- Updated
- Aug 7, 2026