en_covid19_ner

tsantosh7/en_covid19_ner

en_covid19_ner is a token classification model from tsantosh7. Use it when you need labels on individual words, such as names. It is set up for spacy.

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At a glance

Task: Token Classification
Library: spacy
Access: Public
Created: Apr 21, 2022
Updated: Apr 21, 2022
SHA: 09aa1494

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Model card

From the Hugging Face model README

COVID 19 Bio Annotations

The dataset was taken from https://github.com/davidcampos/covid19-corpus

Dataset The dataset was then split into several datasets each one representing one entity. Namely, Disorder, Species, Chemical or Drug, Gene and Protein, Enzyme, Anatomy, Biological Process, Molecular Function, Cellular Component, Pathway and microRNA. Moreover, another dataset is also created with all those aforementioned that are non-overlapping in nature.

Other Dataset Formats The datasets are available in two formats IOB and Spacy's JSONL format.

IOB: https://github.com/tsantosh7/COVID-19-Named-Entity-Recognition/tree/master/Datasets/BIO

SpaCy JSONL: https://github.com/tsantosh7/COVID-19-Named-Entity-Recognition/tree/master/Datasets/SpaCy

Feature	Description
Name	`en_covid19_ner`
Version	`0.0.0`
spaCy	`>=3.2.4,<3.3.0`
Default Pipeline	`transformer`, `ner`
Components	`transformer`, `ner`
Vectors	0 keys, 0 unique vectors (0 dimensions)
Sources	n/a
License	n/a
Author	Santosh Tirunagai

Label Scheme

<details> <summary>View label scheme (10 labels for 1 components)</summary>

Component	Labels
`ner`	`ANAT`, `CHED`, `COMP`, `DISO`, `ENZY`, `FUNC`, `PATH`, `PRGE`, `PROC`, `SPEC`

</details>

Accuracy

Type	Score
`ENTS_F`	92.50
`ENTS_P`	91.40
`ENTS_R`	93.62
`TRANSFORMER_LOSS`	311768.03
`NER_LOSS`	371171.50

Task: Token Classification
Library: spacy
Languages: en
Created: Apr 21, 2022
Updated: Apr 21, 2022