xlm-roberta-large-meddocan

This model is a finetuned version of xlm-roberta-large for the meddocan dataset used in a benchmark in the paper TODO. The model has a F1 of 0.978

Please refer to the original publication for more information TODO LINK

Parameters used

parameter	Value
batch size	16
learning rate	4e-05
classifier dropout	0.2
warmup ratio	0
warmup steps	0
weight decay	0
optimizer	AdamW
epochs	10
early stopping patience	3

BibTeX entry and citation info

TODO

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Token Classification

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Dataset used to train IIC/xlm-roberta-large-meddocan

Collection including IIC/xlm-roberta-large-meddocan

👨🏻‍⚕️ Spanish Clinical Encoders Analysis

Collection

Models and datasets used in the paper `A comparative analysis of Spanish Clinical encoder-based models on NER and classification tasks` • 92 items • Updated Jan 23 • 1

Evaluation results

f1 on meddocan
test set self-reported

0.978

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