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mdeberta-v3-base-caresC
IIC/mdeberta-v3-base-caresC
mdeberta-v3-base-caresC is a text classification model from IIC. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
This model is a finetuned version of mdeberta-v3-base for the Cares Chapters dataset used in a benchmark in the paper A comparative analysis of Spanish Clinical encoder-based models on NER and classification tasks. Th…
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From the Hugging Face model README
mdeberta-v3-base-caresC
This model is a finetuned version of mdeberta-v3-base for the Cares Chapters 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 0.756
Please refer to the original publication for more information.
Parameters used
| parameter | Value |
|---|---|
| batch size | 16 |
| 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
@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
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Languages
- es
- Created
- Jun 20, 2023
- Updated
- Nov 25, 2024