This is a custom named entity recognition model for clinical data. Inorder to see the real usage of the model,
please enter clinical text in the text field.
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.5.0,<3.6.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 514157 keys, 514157 unique vectors (300 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (3 labels for 1 components)
| Component | Labels |
|---|---|
ner |
MEDICALCONDITION, MEDICINE, PATHOGEN |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
98.82 |
ENTS_P |
98.82 |
ENTS_R |
98.82 |
TOK2VEC_LOSS |
4597.80 |
NER_LOSS |
29304.32 |
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Space using nepalprabin/en_pipeline 1
Evaluation results
- NER Precisionself-reported0.988
- NER Recallself-reported0.988
- NER F Scoreself-reported0.988