da_ner / README.md
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Update spaCy pipeline
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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: 0.9453630482
          - name: NER Recall
            type: recall
            value: 0.9094052559
          - name: NER F Score
            type: f_score
            value: 0.927035601
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 92.70
ENTS_P 94.54
ENTS_R 90.94
TOK2VEC_LOSS 50522.21
NER_LOSS 55212.43