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
| { | |
| "epoch": 3.0, | |
| "eval_accuracy": 0.9842943279055494, | |
| "eval_f1": 0.8435847481213471, | |
| "eval_loss": 0.17255768179893494, | |
| "eval_macro_f1": 0.8089460904188281, | |
| "eval_precision": 0.8249863908546543, | |
| "eval_recall": 0.8630410022779044, | |
| "eval_runtime": 1.3375, | |
| "eval_samples_per_second": 2326.734, | |
| "eval_steps_per_second": 18.692, | |
| "eval_weighted_f1": 0.8423394137472547, | |
| "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, | |
| "total_flos": 1230730906566656.0, | |
| "train_loss": 0.9405548764090252, | |
| "train_runtime": 76.6415, | |
| "train_samples_per_second": 974.589, | |
| "train_steps_per_second": 15.266 | |
| } |