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: 0.934169279
- name: NER Recall
type: recall
value: 0.9445324881
- name: NER F Score
type: f_score
value: 0.939322301
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.4.1,<3.5.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (20 labels for 1 components)
| Component | Labels |
|---|---|
ner |
APPLICATIONS, COLLEGE, COMMENT, CURRENCY, FIGURE, FURNITURE, GADGET, GPE, INSTITUITIONS, LOCATION, ORG, PEOPLE, PERIOD, PERSON, PROGRAM, SHELTER, SKILL, TIME, WEATHER CONDITION, YEAR |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
93.93 |
ENTS_P |
93.42 |
ENTS_R |
94.45 |
TOK2VEC_LOSS |
25728.50 |
NER_LOSS |
421749.70 |