|
--- |
|
language: |
|
- es |
|
|
|
tags: |
|
- sentiment-analysis |
|
|
|
--- |
|
|
|
# Sentiment Analysis in Spanish |
|
## beto-sentiment-analysis |
|
|
|
**NOTE: this model will be removed soon -- use [pysentimiento/robertuito-sentiment-analysis](https://huggingface.co/pysentimiento/robertuito-sentiment-analysis) instead** |
|
|
|
Repository: [https://github.com/finiteautomata/pysentimiento/](https://github.com/pysentimiento/pysentimiento/) |
|
|
|
|
|
Model trained with TASS 2020 corpus (around ~5k tweets) of several dialects of Spanish. Base model is [BETO](https://github.com/dccuchile/beto), a BERT model trained in Spanish. |
|
|
|
Uses `POS`, `NEG`, `NEU` labels. |
|
|
|
## License |
|
|
|
`pysentimiento` is an open-source library for non-commercial use and scientific research purposes only. Please be aware that models are trained with third-party datasets and are subject to their respective licenses. |
|
|
|
1. [TASS Dataset license](http://tass.sepln.org/tass_data/download.php) |
|
2. [SEMEval 2017 Dataset license]() |
|
|
|
## Citation |
|
|
|
If you use this model in your work, please cite the following papers: |
|
|
|
``` |
|
@misc{perez2021pysentimiento, |
|
title={pysentimiento: A Python Toolkit for Sentiment Analysis and SocialNLP tasks}, |
|
author={Juan Manuel Pérez and Juan Carlos Giudici and Franco Luque}, |
|
year={2021}, |
|
eprint={2106.09462}, |
|
archivePrefix={arXiv}, |
|
primaryClass={cs.CL} |
|
} |
|
|
|
@article{canete2020spanish, |
|
title={Spanish pre-trained bert model and evaluation data}, |
|
author={Ca{\~n}ete, Jos{\'e} and Chaperon, Gabriel and Fuentes, Rodrigo and Ho, Jou-Hui and Kang, Hojin and P{\'e}rez, Jorge}, |
|
journal={Pml4dc at iclr}, |
|
volume={2020}, |
|
number={2020}, |
|
pages={1--10}, |
|
year={2020} |
|
} |
|
``` |
|
|
|
Enjoy! 🤗 |
|
|
