metadata
language: es
tags:
- biomedical
- clinical
- spanish
- mdeberta-v3-base
license: mit
datasets:
- bigbio/distemist
metrics:
- f1
model-index:
- name: IIC/mdeberta-v3-base-distemist
results:
- task:
type: token-classification
dataset:
name: distemist
type: bigbio/distemist
split: test
metrics:
- name: f1
type: f1
value: 0.844
pipeline_tag: token-classification
mdeberta-v3-base-distemist
This model is a finetuned version of mdeberta-v3-base for the distemist dataset used in a benchmark in the paper TODO. The model has a F1 of 0.844
Please refer to the original publication for more information TODO LINK
Parameters used
parameter | Value |
---|---|
batch size | 32 |
learning rate | 3e-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