metadata
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_legal_ner_pipeline
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.7563683867
- name: NER Recall
type: recall
value: 0.7121771218
- name: NER F Score
type: f_score
value: 0.7336078556
| Feature | Description |
|---|---|
| Name | en_legal_ner_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.7.6,<3.8.0 |
| 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 (14 labels for 1 components)
| Component | Labels |
|---|---|
ner |
CASE_NUMBER, COURT, DATE, GPE, JUDGE, LAWYER, ORG, OTHER_PERSON, PETITIONER, PRECEDENT, PROVISION, RESPONDENT, STATUTE, WITNESS |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
73.36 |
ENTS_P |
75.64 |
ENTS_R |
71.22 |
TOK2VEC_LOSS |
488439.50 |
NER_LOSS |
548698.80 |