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NITKurume-OdaLab/2023-SOFT-Kyushu-SSLsenti
2023-SOFT-Kyushu-SSLsenti is a machine learning model from NITKurume-OdaLab. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This repository is a model for paper. If you use STEP.2 and STEP.3 models like a paper, change branch of name.
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Updated Dec 8, 2023
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From the Hugging Face model README
This repository is a model for paper.
If you use STEP.2 and STEP.3 models like a paper, change branch of name.
@ARTICLE{Kondo2023-va,
title = "Evaluation of the {BERT} model which is fine-tuned by the
datasets including {Pseudo-Label} which is generated by
{Self-Training} for sentimental classification",
author = "Kondo, Aoi and Oda, Mikio",
abstract = "Recently, NLP tasks need many datasets because of the use of
transformer architecture. However, the amount of datasets is
limited since it is created by humans. So we strive to improve it
by using the Pseudo-Labeling approach in Semi-Supervised
learning. This paper creates the model of sentimental
classification by Fine-Tuning using the Pseudo-Label which is
generated by Self-Training, and evaluates it.",
journal = "第25回日本知能情報ファジィ学会九州支部学術講演会",
month = dec,
year = 2023
}