mdeberta-v3-base-socialdisner

This model is a finetuned version of mdeberta-v3-base for the socialdisner dataset used in a benchmark in the paper TODO. The model has a F1 of 0.935

Please refer to the original publication for more information TODO LINK

Parameters used

parameter	Value
batch size	16
learning rate	1e-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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Dataset used to train IIC/mdeberta-v3-base-socialdisner

Collection including IIC/mdeberta-v3-base-socialdisner

👨🏻‍⚕️ 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, 2024 • 1

Evaluation results

f1 on socialdisner
test set self-reported

0.935

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