Token Classification
Transformers
Safetensors
PyTorch
German
modernbert
ner
pii
pii-detection
de-identification
privacy
healthcare
medical
clinical
phi
german
openmed
Eval Results (legacy)
Instructions to use OpenMed/OpenMed-PII-German-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-German-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-German-BioClinicalModern-Base-149M-v1")# Load model directly from transformers import AutoTokenizer, AutoModelForTokenClassification tokenizer = AutoTokenizer.from_pretrained("OpenMed/OpenMed-PII-German-BioClinicalModern-Base-149M-v1") model = AutoModelForTokenClassification.from_pretrained("OpenMed/OpenMed-PII-German-BioClinicalModern-Base-149M-v1") - Notebooks
- Google Colab
- Kaggle
Upload German PII detection model OpenMed-PII-German-BioClinicalModern-Base-149M-v1
43de4f2 verified | { | |
| "epoch": 3.0, | |
| "eval_accuracy": 0.991053304838722, | |
| "eval_f1": 0.9406067422751274, | |
| "eval_loss": 0.026045439764857292, | |
| "eval_macro_f1": 0.930472408317985, | |
| "eval_precision": 0.937706347723167, | |
| "eval_recall": 0.943525134762442, | |
| "eval_runtime": 4.4636, | |
| "eval_samples_per_second": 1184.458, | |
| "eval_steps_per_second": 18.595, | |
| "eval_weighted_f1": 0.9404808074926294, | |
| "test_accuracy": 0.9917773414943989, | |
| "test_f1": 0.945584635661834, | |
| "test_loss": 0.024625767022371292, | |
| "test_macro_f1": 0.9371948372440537, | |
| "test_precision": 0.9426265406994933, | |
| "test_recall": 0.948561354907763, | |
| "test_runtime": 4.3462, | |
| "test_samples_per_second": 1214.867, | |
| "test_steps_per_second": 19.097, | |
| "test_weighted_f1": 0.9458602106779083, | |
| "total_flos": 6792784958717952.0, | |
| "train_loss": 0.14640237264000763, | |
| "train_runtime": 369.2245, | |
| "train_samples_per_second": 343.287, | |
| "train_steps_per_second": 5.371 | |
| } |