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bert-base-uncased-rte
yoshitomo-matsubara/bert-base-uncased-rte
bert-base-uncased-rte is a text classification model from yoshitomo-matsubara. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
bert-base-uncased fine-tuned on RTE dataset, using torchdistill and Google Colab. The hyperparameters are the same as those in Hugging Face's example and/or the paper of BERT, and the training configuration (including…
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From the Hugging Face model README
bert-base-uncased fine-tuned on RTE dataset, using torchdistill and Google Colab.
The hyperparameters are the same as those in Hugging Face's example and/or the paper of BERT, and the training configuration (including hyperparameters) is available here.
I submitted prediction files to the GLUE leaderboard, and the overall GLUE score was 77.9.
Yoshitomo Matsubara: "torchdistill Meets Hugging Face Libraries for Reproducible, Coding-Free Deep Learning Studies: A Case Study on NLP" at EMNLP 2023 Workshop for Natural Language Processing Open Source Software (NLP-OSS)
[Paper] [OpenReview] [Preprint]
@inproceedings{matsubara2023torchdistill,
title={{torchdistill Meets Hugging Face Libraries for Reproducible, Coding-Free Deep Learning Studies: A Case Study on NLP}},
author={Matsubara, Yoshitomo},
booktitle={Proceedings of the 3rd Workshop for Natural Language Processing Open Source Software (NLP-OSS 2023)},
publisher={Empirical Methods in Natural Language Processing},
pages={153--164},
year={2023}
}
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Languages
- en
- Created
- Mar 2, 2022
- Updated
- Feb 10, 2025