Token Classification
Transformers
Safetensors
deberta-v2
question-answering
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metadata
license: apache-2.0
base_model: microsoft/mdeberta-v3-base
datasets:
  - HiTZ/casimedicos-squad
language:
  - en
  - es
  - fr
  - it
metrics:
  - f1
pipeline_tag: question-answering
library_name: transformers
widget:
  - text: >-
      In osteoporosis, one of the main risks associated with the increased risk
      of fracture is low adherence to treatment, so answer 1 is correct. Answer
      2 is found in the SER guidelines, which confirm that some studies conclude
      that bone remodeling markers can be useful for early monitoring of
      adherence and response to treatment. Answer 4 is correct because again in
      the SER 2019 guidelines they quote: "The current scientific evidence
      allows us to affirm that neither increasing dietary calcium nor taking
      calcium supplements alone protects against the appearance of fractures".
      Therefore, the correct answer to this question is option 3. Patients on
      pharmacological treatment for OP should use calcium and vitamin D
      supplements because practically all clinical trials that have demonstrated
      efficacy of antiosteoporotic drugs routinely include calcium supplements
      and cholecalciferol (vitamin D3), but not in monotherapy.
  - text: >-
      La disuria se resolvió más rápidamente en los pacientes implantados con
      103Pd, pero no se vio afectada por el uso de radioterapia suplementaria
      y/o terapia de privación de andrógenos.
  - text: >-
      La dysurie s'est résorbée plus rapidement chez les patients implantés avec
      du 103Pd, mais n'a pas été affectée par l'utilisation d'une radiothérapie
      complémentaire et/ou d'une thérapie de privation d'androgènes.
  - text: >-
      La disuria si è risolta più rapidamente nei pazienti impiantati con 103Pd,
      ma non è stata influenzata dall'uso della radioterapia supplementare e/o
      della terapia di deprivazione androgenica.


mDeBERTa-base for Multilingual Correct Explanation Extraction in the Medical Domain

This model is a fine-tuned version of mdeberta-v3-base for a novel extractive task which consists of identifying the explanation of the correct answer written by medical doctors. The model has been fine-tuned using the multilingual https://huggingface.co/datasets/HiTZ/casimedicos-squad dataset.

Performance

F1 partial match scores (as defined in SQuAD extractive QA task are reported in the following table:

Training hyperparameters

The following hyperparameters were used during training:

  • learning_rate: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 3.0

Framework versions

  • Transformers 4.40.0.dev0
  • Pytorch 2.1.2+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.2

Contact: Anar Yeginbergen and Rodrigo Agerri HiTZ Center - Ixa, University of the Basque Country UPV/EHU