en_ner_prompting / README.md
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metadata
tags:
  - spacy
  - token-classification
language:
  - en
model-index:
  - name: en_ner_prompting
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.7517301038
          - name: NER Recall
            type: recall
            value: 0.7376910017
          - name: NER F Score
            type: f_score
            value: 0.7446443873
Feature Description
Name en_ner_prompting
Version 0.0.2
spaCy >=3.4.3,<3.5.0
Default Pipeline tok2vec, ner
Components tok2vec, ner
Vectors 514157 keys, 514157 unique vectors (300 dimensions)
Sources n/a
License MIT
Author Selas.ai(https://www.selas.ai/)

Label Scheme

View label scheme (1 labels for 1 components)
Component Labels
ner FASHION_BRAND

Accuracy

Type Score
ENTS_F 71.02
ENTS_P 73.76
ENTS_R 68.49
TOK2VEC_LOSS 2670.31
NER_LOSS 913.14