Gbert-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_gbert |
| 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 |
91.15 |
ENTS_P |
90.22 |
ENTS_R |
92.10 |
TRANSFORMER_LOSS |
32882.59 |
NER_LOSS |
56921.35 |
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Evaluation results
- NER Precisionself-reported0.902
- NER Recallself-reported0.921
- NER F Scoreself-reported0.911