Daniel Thompson
Update spaCy pipeline
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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 0.0.0
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 n/a
Author n/a

Label Scheme

View label scheme (99 labels for 4 components)
Component Labels
tagger $, '', ,, -LRB-, -RRB-, ., :, ADD, AFX, CC, CD, DT, EX, FW, HYPH, IN, JJ, JJR, JJS, LS, MD, NFP, NN, NNP, NNPS, NNS, PDT, POS, PRP, PRP$, RB, RBR, RBS, RP, SYM, TO, UH, VB, VBD, VBG, VBN, VBP, VBZ, WDT, WP, WP$, WRB, XX, ````
parser ROOT, acl, acl:relcl, acomp, advcl, advmod, amod, amod@nmod, appos, attr, aux, auxpass, case, cc, cc:preconj, ccomp, compound, compound:prt, conj, cop, csubj, dative, dep, det, det:predet, dobj, expl, intj, mark, meta, mwe, neg, nmod, nmod:npmod, nmod:poss, nmod:tmod, nsubj, nsubjpass, nummod, parataxis, pcomp, pobj, preconj, predet, prep, punct, quantmod, xcomp
ner ENTITY
textcat_multilabel AAA

Accuracy

Type Score
TAG_ACC 0.00
LEMMA_ACC 0.00
DEP_UAS 0.00
DEP_LAS 0.00
DEP_LAS_PER_TYPE 0.00
SENTS_P 0.00
SENTS_R 0.00
SENTS_F 0.00
ENTS_F 0.00
ENTS_P 0.00
ENTS_R 0.00
ENTS_PER_TYPE 0.00
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