metadata
tags:
- spacy
- token-classification
language:
- en
model-index:
- name: en_Spacy_Custom_ner
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.9918793503
- name: NER Recall
type: recall
value: 0.9965034965
- name: NER F Score
type: f_score
value: 0.9941860465
| Feature | Description |
|---|---|
| Name | en_Spacy_Custom_ner |
| Version | 0.0.0 |
| spaCy | >=3.5.3,<3.6.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 514157 keys, 514157 unique vectors (300 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (16 labels for 1 components)
| Component | Labels |
|---|---|
ner |
AGENT_FALLBACK, BOOK, COMODITY, CONTAINER COUNT, CONTAINER SIZE, CONTAINER SIZE-COUNT, DESTINATION, ENQUIRY, HELP, INCOTERM, KYC, ORIGIN, SEARCH RATES, SHIP, SHIPMENT TYPE, WELCOME_MSG |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
99.42 |
ENTS_P |
99.19 |
ENTS_R |
99.65 |
TOK2VEC_LOSS |
1794.25 |
NER_LOSS |
53209.43 |