explosion/en_healthsea

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

View label scheme (6 labels for 2 components)

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

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