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