README.md

metadata

tags:
  - spacy
  - token-classification
language:
  - en
model-index:
  - name: en_engagement_LSTM_f2
    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: 0.9228764982

Feature	Description
Name	en_engagement_LSTM_f2
Version	1.0.0
spaCy	>=3.4.4,<3.5.0
Default Pipeline	transformer, parser, tagger, ner, attribute_ruler, lemmatizer, trainable_transformer, spancat
Components	transformer, parser, tagger, ner, attribute_ruler, lemmatizer, trainable_transformer, spancat
Vectors	0 keys, 0 unique vectors (0 dimensions)
Sources	n/a
License	n/a
Author	n/a

Label Scheme

View label scheme (122 labels for 4 components)

Component	Labels
parser	ROOT, acl, acomp, advcl, advmod, agent, amod, appos, attr, aux, auxpass, case, cc, ccomp, compound, conj, csubj, csubjpass, dative, dep, det, dobj, expl, intj, mark, meta, neg, nmod, npadvmod, nsubj, nsubjpass, nummod, oprd, parataxis, pcomp, pobj, poss, preconj, predet, prep, prt, punct, quantmod, relcl, xcomp
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, ````
ner	CARDINAL, DATE, EVENT, FAC, GPE, LANGUAGE, LAW, LOC, MONEY, NORP, ORDINAL, ORG, PERCENT, PERSON, PRODUCT, QUANTITY, TIME, WORK_OF_ART
spancat	ATTRIBUTION, COUNTER, SOURCES, CITATION, DENY, ENTERTAIN, MONOGLOSS, PROCLAIM, ENDOPHORIC, JUSTIFYING

Accuracy

Type	Score
DEP_UAS	0.00
DEP_LAS	0.00
DEP_LAS_PER_TYPE	0.00
SENTS_P	91.43
SENTS_R	93.16
SENTS_F	92.29
TAG_ACC	0.00
ENTS_F	0.00
ENTS_P	0.00
ENTS_R	0.00
LEMMA_ACC	0.00
SPANS_SC_F	74.80
SPANS_SC_P	75.85
SPANS_SC_R	73.77
TRAINABLE_TRANSFORMER_LOSS	226.60
SPANCAT_LOSS	81318.13