en_predii_ner / README.md
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metadata
tags:
  - spacy
  - token-classification
language:
  - en
model-index:
  - name: en_predii_ner
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.8568965517
          - name: NER Recall
            type: recall
            value: 0.7729393468
          - name: NER F Score
            type: f_score
            value: 0.8127555192
widget:
  - text: >-
      conditions can result in the bottoming out the suspension and
      amplification of the stressplaced on the floor truss network.
    example_title: Entity recognition
  - text: >-
      the additional stress can result in the fracture of welds securing the
      floor truss network system to the chassis frame rail and/or fracture of
      the floor truss network support system.
    example_title: Entity recognition
  - text: >-
      the possibility exists that there could be damage to electrical wiring
      and/or fuel lines which could potentially lead to a fire.You could contact
      to the MONACO CORPORATION
    example_title: Entity recognition
Feature Description
Name en_predii_ner
Version 0.0.0
spaCy >=3.7.4,<3.8.0
Default Pipeline tok2vec, ner
Components tok2vec, ner
Vectors 0 keys, 0 unique vectors (0 dimensions)
Sources n/a
License n/a
Author n/a

Label Scheme

View label scheme (8 labels for 1 components)
Component Labels
ner CHASSIS TYPE, COMPONENT, CORRECTIVE ACTION, FAILURE ISSUE, MANUFACTURER, PARTS, PROCESS, VEHICLE MODEL

Accuracy

Type Score
ENTS_F 81.28
ENTS_P 85.69
ENTS_R 77.29
TOK2VEC_LOSS 74793.71
NER_LOSS 798047.72