Token Classification
Transformers
Safetensors
PyTorch
Dutch
modernbert
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
dutch
openmed
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-Dutch-BioClinicalModern-Base-149M-v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenMed/OpenMed-PII-Dutch-BioClinicalModern-Base-149M-v1 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("token-classification", model="OpenMed/OpenMed-PII-Dutch-BioClinicalModern-Base-149M-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-Dutch-BioClinicalModern-Base-149M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-Dutch-BioClinicalModern-Base-149M-v1") - Notebooks
- Google Colab
- Kaggle
| { | |
| "epoch": 3.0, | |
| "eval_accuracy": 0.9863342600281619, | |
| "eval_f1": 0.86317006212975, | |
| "eval_loss": 0.16574643552303314, | |
| "eval_macro_f1": 0.843794595271581, | |
| "eval_precision": 0.8762100322675271, | |
| "eval_recall": 0.8505125284738041, | |
| "eval_runtime": 2.3596, | |
| "eval_samples_per_second": 1318.883, | |
| "eval_steps_per_second": 20.766, | |
| "eval_weighted_f1": 0.861430607083511, | |
| "test_accuracy": 0.9868810909220719, | |
| "test_f1": 0.8531468531468532, | |
| "test_loss": 0.15482933819293976, | |
| "test_macro_f1": 0.8394856888609218, | |
| "test_precision": 0.8601860186018602, | |
| "test_recall": 0.8462219598583235, | |
| "test_runtime": 3.1081, | |
| "test_samples_per_second": 1001.269, | |
| "test_steps_per_second": 15.765, | |
| "test_weighted_f1": 0.8517472751090946, | |
| "total_flos": 3084843971772416.0, | |
| "train_loss": 1.2889738227567102, | |
| "train_runtime": 210.5158, | |
| "train_samples_per_second": 354.814, | |
| "train_steps_per_second": 5.558 | |
| } |