README.md

metadata

tags:
  - spacy
  - token-classification
language:
  - en
model-index:
  - name: en_pipeline
    results:
      - task:
          name: NER
          type: token-classification
        metrics:
          - name: NER Precision
            type: precision
            value: 0.9881889764
          - name: NER Recall
            type: recall
            value: 0.9881889764
          - name: NER F Score
            type: f_score
            value: 0.9881889764

This is a custom named entity recognition model for clinical data. Inorder to see the real usage of the model,
please enter clinical text in the text field.

Feature	Description
Name	en_pipeline
Version	0.0.0
spaCy	>=3.5.0,<3.6.0
Default Pipeline	tok2vec, ner
Components	tok2vec, ner
Vectors	514157 keys, 514157 unique vectors (300 dimensions)
Sources	n/a
License	n/a
Author	n/a

Label Scheme

View label scheme (3 labels for 1 components)

Component	Labels
ner	MEDICALCONDITION, MEDICINE, PATHOGEN

Accuracy

Type	Score
ENTS_F	98.82
ENTS_P	98.82
ENTS_R	98.82
TOK2VEC_LOSS	4597.80
NER_LOSS	29304.32