metadata
tags:
- spacy
- token-classification
language:
- da
model-index:
- name: da_ner
results:
- task:
name: NER
type: token-classification
metrics:
- name: NER Precision
type: precision
value: 0.9393939394
- name: NER Recall
type: recall
value: 0.9165571616
- name: NER F Score
type: f_score
value: 0.9278350515
| Feature | Description |
|---|---|
| Name | da_ner |
| Version | 0.0.0 |
| spaCy | >=3.5.1,<3.6.0 |
| Default Pipeline | tok2vec, ner |
| Components | tok2vec, ner |
| Vectors | 500000 keys, 20000 unique vectors (300 dimensions) |
| Sources | n/a |
| License | n/a |
| Author | n/a |
Label Scheme
View label scheme (36 labels for 1 components)
| Component | Labels |
|---|---|
ner |
ADVERTISING, AMOUNTS_OF_THE_PRODUCT, AVAILABILITY, BRANDING, CUSTOMERS, DISCOUNTS_AND_OFFERS, DOCUMENTATION, EMPLOYEES, EXTERNAL_SUPPLIER, FACILITIES, FINANCING, HANDLING_OF_SERVICE, LEASING, LEGAL, LOCATIONS, LOCATION_IN_THE_STORE, LOGISTICS, MARKETING, MARKET_COVERAGE, MEDIA, MESSAGES, ORGANIZATIONAL_STRUCTURE, PAYMENT_TERMS, PR, PRICE, PRICE_STRATEGIES, PRODUCT_PROPERTIES, PRODUCT_TYPE, PRODUCT_WARRANTY, REFERENCES, RETURN_ON_INVESTMENT, SALES_PROCESS, SHOWROOM, THE_MANAGEMENT, UNIFORMITY_IN_DELIVERIES, USE_OF_THE_PRODUCT |
Accuracy
| Type | Score |
|---|---|
ENTS_F |
92.78 |
ENTS_P |
93.94 |
ENTS_R |
91.66 |
TOK2VEC_LOSS |
46222.48 |
NER_LOSS |
80475.28 |