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: 0.9848121503
- name: NER Recall
type: recall
value: 0.9828480255
- name: NER F Score
type: f_score
value: 0.9838291076
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.7.5,<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 (26 labels for 1 components)
| Component | Labels |
|---|---|
ner |
ANGLE, CHEMICAL TERM, COUNTABLE, DECIMAL, EQU, EQUATION CITATION, FIGURE CITATION, FRACTION, GREEK VARIABLE, LEADING ZERO, NAMEDATE REF. CITATION, NUMBER, OPERATOR, ORDINAL, ORIENTATION, PERCENTAGE, RANGE, RATIO, ROMAN NUMBER, SI UNIT, SI UNIT , TABLE CITATION, THOUSANDS OPERATOR, THOUSANDS SEPARATOR, TIME UNIT, YEAR |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
98.38 |
ENTS_P |
98.48 |
ENTS_R |
98.28 |
TOK2VEC_LOSS |
34785.41 |
NER_LOSS |
84008.34 |