Edit model card

Based ob the paper: "UmlsBERT: Augmenting Contextual Embeddings with a Clinical Metathesaurus" (https://aclanthology.org/2021.naacl-main.139.pdf).

and the github repo: https://github.com/gmichalo/UmlsBERT

Changing base model to SpanBert instead of Bert.

Trained from scratch on MIMIC dataset, using the UMLS dataset to mask words within the text.

We achived better accuracy on MedNLI dataset.

Bert Model accuracy: 83%

SpanBert Model accuracy: 86%

Downloads last month: 356

Safetensors

Model size

334M params

Tensor type

F32

Inference Examples

Text Classification

This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.