metadata
language: es
tags:
- biomedical
- clinical
- spanish
- XLM_R_Galen
license: mit
datasets:
- IIC/livingner3
metrics:
- f1
model-index:
- name: IIC/XLM_R_Galen-livingner3
results:
- task:
type: multi-label-classification
dataset:
name: livingner3
type: IIC/livingner3
split: test
metrics:
- name: f1
type: f1
value: 0.5
pipeline_tag: text-classification
XLM_R_Galen-livingner3
This model is a finetuned version of XLM_R_Galen for the livingner3 dataset used in a benchmark in the paper TODO. The model has a F1 of 0.5
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 |
| warmup ratio | 0 |
| warmup steps | 0 |
| weight decay | 0 |
| optimizer | AdamW |
| epochs | 10 |
| early stopping patience | 3 |
BibTeX entry and citation info
TODO