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de_GPTNERMED_GottBERT
jfrei/de_GPTNERMED_GottBERT
de_GPTNERMED_GottBERT is a token classification model from jfrei. Use it when you need labels on individual words, such as names. It is set up for spacy.
GottBERT-based model of the GPTNERMED German NER model for medical entities.
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360
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Repo size
977 MB
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1
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Other508 MB · 52%
At a glance
- Task
- Token Classification
- Library
- spacy
- Access
- Public
- Created
- Oct 5, 2023
- Updated
- Oct 5, 2023
- SHA
- 74a3f4f6
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Model card
From the Hugging Face model README
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
<details> <summary>View label scheme (3 labels for 1 components)</summary>| 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 |
- Task
- Token Classification
- Library
- spacy
- Languages
- de
- Created
- Oct 5, 2023
- Updated
- Oct 5, 2023