GottBERT-based model of the GPTNERMED German NER model for medical entities.
See our published paper at: https://doi.org/10.1016/j.jbi.2023.104478
The preprint paper is available at: https://arxiv.org/abs/2208.14493
If you like our work, give us a star on our GitHub repository: https://github.com/frankkramer-lab/GPTNERMED
| Feature | Description |
|---|---|
| Name | de_GPTNERMED_GottBERT |
| Version | 1.0.0 |
| spaCy | >=3.4.1,<3.5.0 |
| Default Pipeline | transformer, ner |
| Components | transformer, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | Johann Frei |
Label Scheme
View label scheme (3 labels for 1 components)
| Component | Labels |
|---|---|
ner |
Diagnose, Dosis, Medikation |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
91.62 |
ENTS_P |
91.74 |
ENTS_R |
91.50 |
TRANSFORMER_LOSS |
31366.36 |
NER_LOSS |
50306.02 |
- Downloads last month
- 1
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.
Evaluation results
- NER Precisionself-reported0.917
- NER Recallself-reported0.915
- NER F Scoreself-reported0.916