metadata
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_pipeline
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.6956521739
- name: NER Recall
type: recall
value: 0.6666666667
- name: NER F Score
type: f_score
value: 0.6808510638
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.7.4,<3.8.0 |
| Default Pipeline | transformer, ner |
| Components | transformer, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (18 labels for 1 components)
| Component | Labels |
|---|---|
ner |
AGREE, ALLERGY, ANTIBIOTIC, BETA-BLOCKERS, BLOOD LOSS, CONSENT, DURATION, FIRE RISK, GREETING, MEDICAL_PROCEDURE, MEDICAL_ROLE, MEDS/EQUIPMENT, MRN, NAME, POSITION, RADIOLOGY, READY, SITES |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
68.09 |
ENTS_P |
69.57 |
ENTS_R |
66.67 |
TRANSFORMER_LOSS |
0.00 |
NER_LOSS |
0.00 |