en_tech_model / README.md
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metadata
tags:
  - spacy
  - token-classification
  - text-classification
language:
  - en
model-index:
  - name: en_tech_model
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.9530851606
          - name: NER Recall
            type: recall
            value: 0.9504195271
          - name: NER F Score
            type: f_score
            value: 0.9517504774
Feature Description
Name en_tech_model
Version 0.0.4
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 (32 labels for 2 components)
Component Labels
ner BATTERY, BRAND, CACHE, CAM_RES, CHARGE, CLOCK_SPEED, COLOR, CORE_COUNT, FEATURE, GEN, GRAPHICS, GRAPHICS_RAM, MEM_TYPE, MODEL_NUMBER, OPERATING_SYSTEM, PROCESSOR, PROCESSOR_MODEL, PRODUCT_SERIES, RAM, RESOLUTION, SCREEN_SIZE, SCREEN_TYPE, SOCKET, STORAGE, STORAGE_TYPE, TAG, TYPE
textcat 267, 292, 297, 325, 328

Accuracy

Type Score
ENTS_F 95.18
ENTS_P 95.31
ENTS_R 95.04
CATS_SCORE 99.51
CATS_MICRO_P 99.52
CATS_MICRO_R 99.52
CATS_MICRO_F 99.52
CATS_MACRO_P 99.55
CATS_MACRO_R 99.48
CATS_MACRO_F 99.51
CATS_MACRO_AUC 100.00
TOK2VEC_LOSS 1022799.22
NER_LOSS 52929.76
TEXTCAT_LOSS 4.84