metadata
tags:
- spacy
- token-classification
language:
- de
model-index:
- name: de_GERNERMEDpp_Slim
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.9020724569
- name: NER Recall
type: recall
value: 0.8881619938
- name: NER F Score
type: f_score
value: 0.8950631819
Slim model of the GERNERMED++ German NER model for medical entities.
| Feature | Description |
|---|---|
| Name | de_GERNERMEDpp_Slim |
| Version | 1.0.0 |
| spaCy | >=3.2.3,<3.3.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | Johann Frei |
Label Scheme
View label scheme (6 labels for 1 components)
| Component | Labels |
|---|---|
ner |
Dosage, Drug, Duration, Form, Frequency, Strength |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
89.51 |
ENTS_P |
90.21 |
ENTS_R |
88.82 |
TOK2VEC_LOSS |
129329.99 |
NER_LOSS |
603008.42 |