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: 0.9907407407
- name: NER Recall
type: recall
value: 0.9960106383
- name: NER F Score
type: f_score
value: 0.9933687003
| Feature | Description |
|---|---|
| Name | en_pipeline |
| Version | 0.0.0 |
| spaCy | >=3.5.1,<3.6.0 |
| 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 |
BOOK, COMODITY, CONTAINER COUNT, CONTAINER SIZE, CONTAINER SIZE-COUNT, DESTINATION, ENQUIRY, HELP, INCOTERM, KYC, ORIGIN, SEARCH RATES, SHIP, SHIPMENT TYPE |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
99.34 |
ENTS_P |
99.07 |
ENTS_R |
99.60 |
TOK2VEC_LOSS |
6119.15 |
NER_LOSS |
67099.47 |