metadata
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_spacy_ner_finetuned_news_article
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.9865652034
- name: NER Recall
type: recall
value: 0.9823041611
- name: NER F Score
type: f_score
value: 0.9844300714
| Feature | Description |
|---|---|
| Name | en_spacy_ner_finetuned_news_article |
| Version | 0.0.0 |
| spaCy | >=3.5.2,<3.6.0 |
| Default Pipeline | transformer, ner |
| Components | transformer, ner |
| Vectors | 0 keys, 0 unique vectors (0 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (15 labels for 1 components)
| Component | Labels |
|---|---|
ner |
EVENT, FAC, GPE, LAW, LOC, MONEY, NORP, ORDINAL, ORG, PERCENT, PERSON, PRODUCT, QUANTITY, TIME, WORK_OF_ART |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
98.44 |
ENTS_P |
98.66 |
ENTS_R |
98.23 |
TRANSFORMER_LOSS |
18923.26 |
NER_LOSS |
21258.62 |