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Publish OpenMed-PPSN-v5 for QA testing

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NOTICE ADDED
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+ OpenMed PPSN Extension
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+ Copyright 2026 Contributors
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+
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+ This project includes fine-tuned/derived model artifacts from:
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+ - OpenMed/OpenMed-PII-SuperClinical-Large-434M-v1 (Hugging Face)
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+ Declared license: Apache-2.0.
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+
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+ This project uses evaluation/training data sources including:
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+ - nvidia/Nemotron-PII (Hugging Face dataset)
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+ Declared license: CC-BY-4.0.
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+
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+ Attribution and links:
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+ - OpenMed base model: https://huggingface.co/OpenMed/OpenMed-PII-SuperClinical-Large-434M-v1
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+ - Nemotron-PII dataset: https://huggingface.co/datasets/nvidia/Nemotron-PII
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+
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+ If you redistribute models or checkpoints produced here, keep this NOTICE,
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+ retain upstream license notices, and provide dataset attribution where required.
README.md ADDED
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+ ---
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+ language:
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+ - en
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+ - ga
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+ license: apache-2.0
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+ library_name: transformers
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+ tags:
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+ - pii
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+ - token-classification
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+ - healthcare
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+ - de-identification
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+ - ireland
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+ - ppsn
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+ base_model:
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+ - OpenMed/OpenMed-PII-SuperClinical-Large-434M-v1
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+ datasets:
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+ - nvidia/Nemotron-PII
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+ - joelniklaus/mapa
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+ model-index:
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+ - name: OpenMed-PPSN-v5
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+ results:
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+ - task:
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+ type: token-classification
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+ name: PPSN detection (Irish regression set)
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+ dataset:
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+ name: irish_ppsn_regression_v5
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+ type: custom
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+ metrics:
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+ - type: f1
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+ value: 0.8235
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+ name: Raw model F1
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+ - type: f1
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+ value: 1.0000
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+ name: Hybrid strict F1
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+ ---
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+
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+ # OpenMed PPSN v5
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+
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+ Token classification model derived from `OpenMed/OpenMed-PII-SuperClinical-Large-434M-v1` with added `B-PPSN` / `I-PPSN` support for Irish PPS Number detection.
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+
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+ ## What this release contains
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+
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+ - Full model weights (`model.safetensors`) with original OpenMed labels + PPSN labels.
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+ - `label_meta.json` with label mapping and provenance.
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+ - Repro/eval artifacts:
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+ - `irish_ppsn_regression_v5.jsonl`
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+ - `eval_manual_irish_v5_raw.json`
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+ - `eval_hybrid_v5_no_plausible.json`
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+ - `ab_non_ppsn_v5_baseline.json`
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+
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+ ## Key results
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+
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+ On `irish_ppsn_regression_v5`:
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+
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+ - Raw model-only PPSN performance: `P=0.7778 R=0.8750 F1=0.8235`.
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+ - Recommended strict hybrid mode (model + checksum + span normalization, no plausible fallback):
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+ - `P=1.0000 R=1.0000 F1=1.0000`.
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+
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+ Non-PPSN retention check vs base OpenMed (A/B):
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+
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+ - Real-text behavior agreement F1: `1.0000`.
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+ - Entity density unchanged in the sampled real-text proxy set.
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+
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+ ## Recommended production usage
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+
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+ For best PPSN reliability, run this model with a strict hybrid post-processor:
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+
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+ 1. Keep model detections for all labels.
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+ 2. For PPSN specifically, normalize/expand spans to full PPSN candidates.
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+ 3. Validate PPSN with checksum.
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+ 4. Disable broad "plausible" fallback in production (`no-plausible-ppsn`).
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+
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+ This repository includes only the model artifacts; hybrid scripts are in the companion codebase used to train/evaluate this release.
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+
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+ ## Limitations
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+
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+ - The Irish regression set is small and targeted; additional domain-specific validation is required before regulated deployment.
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+ - PPSN detection in noisy OCR/ASR or heavily malformed text may require extra hardening.
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+
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+ ## License and attribution
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+
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+ - This derivative release is distributed under Apache-2.0, consistent with the base model license tag.
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+ - Base model: `OpenMed/OpenMed-PII-SuperClinical-Large-434M-v1`.
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+ - Training/evaluation used synthetic and augmented data sources, including `nvidia/Nemotron-PII` and `joelniklaus/mapa`.
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+ - See `NOTICE` for attribution details.
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+
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+ ## QA quick check
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+
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+ - Load this model as a standard `AutoModelForTokenClassification` checkpoint.
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+ - Run against `irish_ppsn_regression_v5.jsonl`.
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+ - Confirm results in `eval_manual_irish_v5_raw.json` (raw) and `eval_hybrid_v5_no_plausible.json` (strict hybrid).
ab_non_ppsn_v5_baseline.json ADDED
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1
+ {
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+ "base_model": "OpenMed/OpenMed-PII-SuperClinical-Large-434M-v1",
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+ "candidate_model": "models/openmed-ppsns-lora-v5",
4
+ "dataset": {
5
+ "synthetic_source": "nvidia/Nemotron-PII:test",
6
+ "real_source": "wikitext/wikitext-2-raw-v1:validation",
7
+ "synthetic_size": 250,
8
+ "real_size": 250,
9
+ "match_iou_threshold": 0.5
10
+ },
11
+ "synthetic_non_ppsn_vs_gold": {
12
+ "base": {
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+ "precision": 0.8007397133610726,
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+ "recall": 0.9232409381663113,
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+ "f1": 0.8576380292151522,
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+ "tp": 1732,
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+ "fp": 431,
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+ "fn": 144
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+ },
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+ "candidate": {
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+ "precision": 0.8289601554907677,
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+ "recall": 0.9093816631130064,
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+ "f1": 0.8673106253177427,
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+ "tp": 1706,
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+ "fp": 352,
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+ "fn": 170
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+ }
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+ },
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+ "real_non_ppsn_behavior": {
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+ "base": {
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+ "docs": 250,
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+ "total_non_ppsn_entities": 1708,
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+ "entities_per_1k_chars": 12.36006281343397,
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+ "docs_with_any_entity": 217,
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+ "docs_with_any_entity_rate": 0.868,
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+ "top_labels": [
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+ [
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+ "last_name",
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+ 464
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+ ],
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+ [
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+ "city",
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+ 407
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+ ],
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+ [
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+ "first_name",
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+ 237
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+ ],
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+ [
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+ "state",
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+ 153
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+ ],
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+ [
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+ "date",
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+ 134
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+ ],
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+ [
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+ "street_address",
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+ 87
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+ ],
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+ [
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+ "occupation",
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+ 79
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+ ],
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+ [
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+ "country",
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+ 47
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+ ],
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+ [
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+ "county",
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+ 24
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+ ],
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+ [
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+ "company_name",
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+ 23
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+ ],
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+ [
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+ "race_ethnicity",
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+ 17
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+ ],
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+ [
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+ "date_of_birth",
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+ 9
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+ ],
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+ [
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+ "education_level",
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+ 7
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+ ],
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+ [
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+ "password",
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+ 5
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+ ],
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+ [
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+ "time",
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+ 4
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+ ]
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+ ]
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+ },
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+ "candidate": {
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+ "docs": 250,
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+ "total_non_ppsn_entities": 1708,
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+ "entities_per_1k_chars": 12.36006281343397,
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+ "docs_with_any_entity": 217,
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+ "docs_with_any_entity_rate": 0.868,
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+ "top_labels": [
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+ [
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+ "last_name",
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+ 464
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+ ],
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+ [
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+ "city",
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+ 407
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+ ],
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+ [
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+ "first_name",
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+ 237
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+ ],
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+ [
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+ "state",
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+ 153
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+ ],
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+ [
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+ "date",
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+ 134
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+ ],
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+ [
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+ "street_address",
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+ 87
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+ ],
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+ [
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+ "occupation",
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+ 79
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+ ],
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+ [
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+ "country",
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+ 47
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+ ],
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+ [
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+ "county",
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+ 24
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+ ],
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+ [
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+ "company_name",
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+ 23
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+ ],
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+ [
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+ "race_ethnicity",
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+ 17
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+ ],
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+ [
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+ "date_of_birth",
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+ 9
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+ ],
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+ [
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+ "education_level",
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+ 7
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+ ],
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+ [
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+ "password",
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+ 5
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+ ],
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+ [
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+ "time",
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+ 4
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+ ]
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+ ]
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+ },
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+ "candidate_vs_base_agreement": {
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+ "precision": 1.0,
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+ "recall": 1.0,
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+ "f1": 1.0,
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+ "tp": 1708,
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+ "fp": 0,
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+ "fn": 0
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+ }
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+ }
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+ }
config.json ADDED
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1
+ {
2
+ "architectures": [
3
+ "DebertaV2ForTokenClassification"
4
+ ],
5
+ "attention_probs_dropout_prob": 0.1,
6
+ "bos_token_id": 1,
7
+ "dtype": "float32",
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+ "eos_token_id": 2,
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+ "hidden_act": "gelu",
10
+ "hidden_dropout_prob": 0.1,
11
+ "hidden_size": 1024,
12
+ "id2label": {
13
+ "0": "O",
14
+ "1": "B-account_number",
15
+ "2": "B-age",
16
+ "3": "B-api_key",
17
+ "4": "B-bank_routing_number",
18
+ "5": "B-biometric_identifier",
19
+ "6": "B-blood_type",
20
+ "7": "B-certificate_license_number",
21
+ "8": "B-city",
22
+ "9": "B-company_name",
23
+ "10": "B-coordinate",
24
+ "11": "B-country",
25
+ "12": "B-county",
26
+ "13": "B-credit_debit_card",
27
+ "14": "B-customer_id",
28
+ "15": "B-cvv",
29
+ "16": "B-date",
30
+ "17": "B-date_of_birth",
31
+ "18": "B-date_time",
32
+ "19": "B-device_identifier",
33
+ "20": "B-education_level",
34
+ "21": "B-email",
35
+ "22": "B-employee_id",
36
+ "23": "B-employment_status",
37
+ "24": "B-fax_number",
38
+ "25": "B-first_name",
39
+ "26": "B-gender",
40
+ "27": "B-health_plan_beneficiary_number",
41
+ "28": "B-http_cookie",
42
+ "29": "B-ipv4",
43
+ "30": "B-ipv6",
44
+ "31": "B-language",
45
+ "32": "B-last_name",
46
+ "33": "B-license_plate",
47
+ "34": "B-mac_address",
48
+ "35": "B-medical_record_number",
49
+ "36": "B-occupation",
50
+ "37": "B-password",
51
+ "38": "B-phone_number",
52
+ "39": "B-pin",
53
+ "40": "B-political_view",
54
+ "41": "B-postcode",
55
+ "42": "B-race_ethnicity",
56
+ "43": "B-religious_belief",
57
+ "44": "B-sexuality",
58
+ "45": "B-ssn",
59
+ "46": "B-state",
60
+ "47": "B-street_address",
61
+ "48": "B-swift_bic",
62
+ "49": "B-tax_id",
63
+ "50": "B-time",
64
+ "51": "B-unique_id",
65
+ "52": "B-url",
66
+ "53": "B-user_name",
67
+ "54": "B-vehicle_identifier",
68
+ "55": "I-account_number",
69
+ "56": "I-api_key",
70
+ "57": "I-biometric_identifier",
71
+ "58": "I-blood_type",
72
+ "59": "I-certificate_license_number",
73
+ "60": "I-city",
74
+ "61": "I-company_name",
75
+ "62": "I-coordinate",
76
+ "63": "I-country",
77
+ "64": "I-county",
78
+ "65": "I-credit_debit_card",
79
+ "66": "I-customer_id",
80
+ "67": "I-date",
81
+ "68": "I-date_of_birth",
82
+ "69": "I-date_time",
83
+ "70": "I-device_identifier",
84
+ "71": "I-education_level",
85
+ "72": "I-email",
86
+ "73": "I-employee_id",
87
+ "74": "I-employment_status",
88
+ "75": "I-fax_number",
89
+ "76": "I-first_name",
90
+ "77": "I-gender",
91
+ "78": "I-health_plan_beneficiary_number",
92
+ "79": "I-http_cookie",
93
+ "80": "I-ipv4",
94
+ "81": "I-ipv6",
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