en_generic_big / README.md
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metadata
tags:
  - spacy
  - token-classification
  - text-classification
language:
  - en
model-index:
  - name: en_generic_big
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.9469753547
          - name: NER Recall
            type: recall
            value: 0.9399555226
          - name: NER F Score
            type: f_score
            value: 0.943452381
Feature Description
Name en_generic_big
Version 0.0.1
spaCy >=3.7.5,<3.8.0
Default Pipeline tok2vec, ner, textcat
Components tok2vec, ner, textcat
Vectors 514157 keys, 514157 unique vectors (300 dimensions)
Sources n/a
License n/a
Author n/a

Label Scheme

View label scheme (35 labels for 2 components)
Component Labels
ner AGE, BRAND, CLOCK_SPEED, COLOR, CORE_COUNT, DECORATION, FEATURE, FIT, GENDER, GRAPHICS, GRAPHICS_RAM, MATERIAL, MEASUREMENT, MEASUREMENT_AREA, MEM_TYPE, MODEL_NUMBER, NECKLINE, OPERATING_SYSTEM, PROCESSOR, PROCESSOR_MODEL, PRODUCT_SERIES, RAM, RESOLUTION, SCREEN_SIZE, SCREEN_TYPE, SIZE, SLEEVE, STORAGE, STORAGE_TYPE, TAG, TYPE, ZIP
textcat 212, 297, 328

Accuracy

Type Score
ENTS_F 94.35
ENTS_P 94.70
ENTS_R 94.00
CATS_SCORE 100.00
CATS_MICRO_P 100.00
CATS_MICRO_R 100.00
CATS_MICRO_F 100.00
CATS_MACRO_P 100.00
CATS_MACRO_R 100.00
CATS_MACRO_F 100.00
CATS_MACRO_AUC 100.00
TOK2VEC_LOSS 28927.81
NER_LOSS 63903.29
TEXTCAT_LOSS 0.08