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: 0.9945750452
- name: NER Recall
type: recall
value: 0.998185118
- name: NER F Score
type: f_score
value: 0.9963768116
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.6.0,<3.7.0 |
| Default Pipeline | tok2vec, entity_ruler, ner |
| Components | tok2vec, entity_ruler, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (6 labels for 2 components)
| Component | Labels |
|---|---|
entity_ruler |
STATE, STATE_CODE, ZIPCODE |
ner |
CITY, STATE, VERTICAL |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
99.64 |
ENTS_P |
99.46 |
ENTS_R |
99.82 |
TOK2VEC_LOSS |
748.20 |
NER_LOSS |
227.50 |