en_healthsea

explosion/en_healthsea

en_healthsea is a text classification model from explosion. Use it when you need a label for a piece of text. It is set up for spacy.

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At a glance

Task: Text Classification
Library: spacy
Access: Public
Created: Mar 2, 2022
Updated: Feb 15, 2022
SHA: e43ca230

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zevilife/health

Model card

From the Hugging Face model README

Welcome to Healthsea ✨

Create better access to health with machine learning and natural language processing. This is the trained healthsea pipeline for analyzing user reviews to supplements by extracting their effects on health. This pipeline features a trained NER model and a custom Text Classification model with Clause Segmentation and Blinding capabilities.

Read more in the blog post and visit the healthsea repository for all training workflows, custom components and training data.

Feature	Description
Name	`en_healthsea`
Version	`0.0.0`
spaCy	`>=3.2.0,<3.3.0`
Default Pipeline	`sentencizer`, `tok2vec`, `ner`, `benepar`, `segmentation`, `clausecat`, `aggregation`
Components	`sentencizer`, `tok2vec`, `ner`, `benepar`, `segmentation`, `clausecat`, `aggregation`
Vectors	684830 keys, 684830 unique vectors (300 dimensions)
Sources	n/a
License	MIT
Author	Explosion

Label Scheme

<details> <summary>View label scheme (6 labels for 2 components)</summary>

Component	Labels
`ner`	`BENEFIT`, `CONDITION`
`clausecat`	`POSITIVE`, `NEUTRAL`, `NEGATIVE`, `ANAMNESIS`

</details>

Accuracy

Type	Score
`ENTS_F`	80.34
`ENTS_P`	80.77
`ENTS_R`	79.92
`CATS_SCORE`	74.87
`CATS_MICRO_P`	82.17
`CATS_MICRO_R`	80.85
`CATS_MICRO_F`	81.51
`CATS_MACRO_P`	78.01
`CATS_MACRO_R`	72.41
`CATS_MACRO_F`	74.87
`CATS_MACRO_AUC`	92.76
`CATS_LOSS`	297.22

Task: Text Classification
Library: spacy
Languages: en
Created: Mar 2, 2022
Updated: Feb 15, 2022