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metadata
tags:
  - spacy
  - token-classification
  - text-classification
language:
  - en
model-index:
  - name: en_scispaCy_aaa_classification
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0
          - name: NER Recall
            type: recall
            value: 0
          - name: NER F Score
            type: f_score
            value: 0
      - task:
          name: TAG
          type: token-classification
        metrics:
          - name: TAG (XPOS) Accuracy
            type: accuracy
            value: 0
      - task:
          name: LEMMA
          type: token-classification
        metrics:
          - name: Lemma Accuracy
            type: accuracy
            value: 0
      - task:
          name: UNLABELED_DEPENDENCIES
          type: token-classification
        metrics:
          - name: Unlabeled Attachment Score (UAS)
            type: f_score
            value: 0
      - task:
          name: LABELED_DEPENDENCIES
          type: token-classification
        metrics:
          - name: Labeled Attachment Score (LAS)
            type: f_score
            value: 0
      - task:
          name: SENTS
          type: token-classification
        metrics:
          - name: Sentences F-Score
            type: f_score
            value: 0
Feature Description
Name en_scispaCy_aaa_classification
Version 1.0.0
spaCy >=3.7.4,<3.8.0
Default Pipeline tok2vec, tagger, attribute_ruler, lemmatizer, parser, ner, textcat_multilabel
Components tok2vec, tagger, attribute_ruler, lemmatizer, parser, ner, textcat_multilabel
Vectors 4087446 keys, 50000 unique vectors (200 dimensions)
Sources n/a
License GPL v3
Author Daniel C Thompson

Label Scheme

View label scheme (99 labels for 4 components)

| Component | Labels |

| textcat_multilabel | AAA |

Accuracy

Type Score
CATS_SCORE 99.46
CATS_MICRO_P 93.06
CATS_MICRO_R 99.26
CATS_MICRO_F 96.06
CATS_MACRO_P 93.06
CATS_MACRO_R 99.26
CATS_MACRO_F 96.06
CATS_MACRO_AUC 99.46
TOK2VEC_LOSS 76.75
TEXTCAT_MULTILABEL_LOSS 246.39