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: 0.9851430668
- name: NER Recall
type: recall
value: 0.9871347179
- name: NER F Score
type: f_score
value: 0.9861378867
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.7.2,<3.8.0 |
| 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 (16 labels for 1 components)
| Component | Labels |
|---|---|
ner |
AGE GROUP, BENCHMARKS, CADAVERS/BIOMECHANICAL/NONCLINICAL, DEVICE, FOLLOW UP, INDICATION, LEVEL OF EVIDENCE , MANAGEMENT, PERFORMANCE OUTCOMES, RISK FACTORS, SAFETY OUTCOMES, SCORES, SEX, STATISTICAL SIGNIFICANCE, STRYKER, STUDY TYPE |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
98.61 |
ENTS_P |
98.51 |
ENTS_R |
98.71 |
TOK2VEC_LOSS |
44342.33 |
NER_LOSS |
204832.98 |