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metadata
language: es
tags:
  - biomedical
  - clinical
  - spanish
  - mdeberta-v3-base
license: mit
datasets:
  - IIC/socialdisner
metrics:
  - f1
model-index:
  - name: IIC/mdeberta-v3-base-socialdisner
    results:
      - task:
          type: token-classification
        dataset:
          name: socialdisner
          type: IIC/socialdisner
          split: test
        metrics:
          - name: f1
            type: f1
            value: 0.935
pipeline_tag: token-classification

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