Token Classification
Transformers
Safetensors
PyTorch
Dutch
roberta
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
dutch
openmed
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-Dutch-FastClinical-Small-82M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-Dutch-FastClinical-Small-82M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-Dutch-FastClinical-Small-82M-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-Dutch-FastClinical-Small-82M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-Dutch-FastClinical-Small-82M-v1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "test_accuracy": 0.9839181808446079, | |
| "test_f1": 0.8276060388209922, | |
| "test_loss": 0.1771344542503357, | |
| "test_macro_f1": 0.791315789641642, | |
| "test_precision": 0.8068404821979255, | |
| "test_recall": 0.8494687131050768, | |
| "test_runtime": 2.1506, | |
| "test_samples_per_second": 1447.044, | |
| "test_steps_per_second": 11.625, | |
| "test_weighted_f1": 0.825178867844929 | |
| } |