metadata

language: es
tags:
  - biomedical
  - clinical
  - eHR
  - spanish
  - xlm-roberta-large
license: mit
datasets:
  - PlanTL-GOB-ES/cantemist-ner
metrics:
  - f1
model-index:
  - name: IIC/xlm-roberta-large-cantemist
    results:
      - task:
          type: token-classification
        dataset:
          name: cantemist-ner
          type: PlanTL-GOB-ES/cantemist-ner
        metrics:
          - name: f1
            type: f1
            value: 0.904
widget:
  - text: >-
      El diagnóstico definitivo de nuestro paciente fue de un Adenocarcinoma de
      pulmón cT2a cN3 cM1a Estadio IV (por una única lesión pulmonar
      contralateral) PD-L1 90%, EGFR negativo, ALK negativo y ROS-1 negativo.
  - text: >-
      Durante el ingreso se realiza una TC, observándose un nódulo pulmonar en
      el LII y una masa renal derecha indeterminada. Se realiza punción biopsia
      del nódulo pulmonar, con hallazgos altamente sospechosos de carcinoma.
  - text: >-
      Trombosis paraneoplásica con sospecha de hepatocarcinoma por imagen, sobre
      hígado cirrótico, en paciente con índice Child-Pugh B.

xlm-roberta-large-cantemist

This model is a finetuned version of xlm-roberta-large for the cantemist dataset used in a benchmark in the paper A comparative analysis of Spanish Clinical encoder-based models on NER and classification tasks. The model has a F1 of 0.904

Please refer to the original publication for more information.

Parameters used

parameter	Value
batch size	16
learning rate	2e05
classifier dropout	0.1
warmup ratio	0
warmup steps	0
weight decay	0
optimizer	AdamW
epochs	10
early stopping patience	3

BibTeX entry and citation info

@article{10.1093/jamia/ocae054,
    author = {García Subies, Guillem and Barbero Jiménez, Álvaro and Martínez Fernández, Paloma},
    title = {A comparative analysis of Spanish Clinical encoder-based models on NER and classification tasks},
    journal = {Journal of the American Medical Informatics Association},
    volume = {31},
    number = {9},
    pages = {2137-2146},
    year = {2024},
    month = {03},
    issn = {1527-974X},
    doi = {10.1093/jamia/ocae054},
    url = {https://doi.org/10.1093/jamia/ocae054},
}