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BETO_Galen-ehealth_kd
IIC/BETO_Galen-ehealth_kd
BETO_Galen-ehealth_kd is a token classification model from IIC. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as mit.
This model is a finetuned version of BETOGalen for the eHealth-KD 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…
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From the Hugging Face model README
BETO_Galen-ehealth_kd
This model is a finetuned version of BETO_Galen for the eHealth-KD 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 0.658
Please refer to the original publication for more information.
Parameters used
| parameter | Value |
|---|---|
| batch size | 32 |
| 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
@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},
}
- Task
- Token Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Languages
- es
- Created
- Jun 21, 2023
- Updated
- Jan 17, 2025