# Medical Text Understanding

RigoBERTa Clinical Edition is the state-of-the-art encoder language model for the Spanish clinical domain, developed through domain-adaptive pretraining on the largest publicly available Spanish clinical corpus, ClinText-SP.

A BERT-based fine-tuned Turkish medical QA model specialized in extracting answers from medical texts

A multi-domain language model fine-tuned on the Hyperion-v2.0 dataset, excelling in scientific reasoning and complex task processing.

A model fine-tuned based on microsoft/deberta-large for specific task processing

A model fine-tuned based on roberta-large for specific task processing, with an evaluation loss value of 0.7825

This model is a Q&A model fine-tuned on the SQuAD2.0 and COVID-QA datasets based on the ALBERT-xxlarge-v2 architecture

This model is a fine-tuned version of DistilBERT on a COVID-19 Q&A dataset, specifically designed to answer questions related to COVID-19.

A question-answering system fine-tuned on the COVID-19 Q&A dataset based on the DistilBERT-base-uncased model, specifically designed to answer COVID-19 related questions.