OpenMed PII ClinicalE5 Small 33M v1 PII Detection Model 33M Parameters Open Source Model Description OpenMed PII ClinicalE5 Small 33M v1 is a transformer based token classification model fine tuned for Personally Identifiable Information (PII) detection in text. This model identifies and classifies 54 types of sensitive information including names, addresses, SSNs, medical record numbers, and more. Key Features High Accuracy : Achieves strong F1 scores across diverse PII categories Comprehensive Coverage : Detects 50+ entity types spanning personal, financial, medical, and contact information Privacy Focused : Designed for de identification and compliance with HIPAA, GDPR, and other privacy regulations Production Ready : Optimized for real world text processing pipelines Performance Evaluated on a stratified 2,000 sample test set from NVIDIA Nemotron PII: Metric Score : : : Micro F1 0.9306 Precision 0.9282 Recall 0.9330 Macro F1 0.9093 Weighted F1 0.9295 Accuracy 0.9919 Top 10 PII Models Rank Model F1 Precision Recall : : : : : : : : : 1 OpenMed PII SuperClinical Large 434M v1 0.9608 0.9685 0.9532 2 OpenMed PII BigMed Large 560M v1 0.9604 0.9644 0.9565 3 OpenMed PII EuroMed 210M v1…
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