@inproceedings{pruksachatkun-etal-2020-jiant,
title = "jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models",
author = "Pruksachatkun, Yada and
Yeres, Phil and
Liu, Haokun and
Phang, Jason and
Htut, Phu Mon and
Wang, Alex and
Tenney, Ian and
Bowman, Samuel R.",
editor = "Celikyilmaz, Asli and
Wen, Tsung-Hsien",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-demos.15",
doi = "10.18653/v1/2020.acl-demos.15",
pages = "109--117",
abstract = "We introduce jiant, an open source toolkit for conducting multitask and transfer learning experiments on English NLU tasks. jiant enables modular and configuration driven experimentation with state-of-the-art models and a broad set of tasks for probing, transfer learning, and multitask training experiments. jiant implements over 50 NLU tasks, including all GLUE and SuperGLUE benchmark tasks. We demonstrate that jiant reproduces published performance on a variety of tasks and models, e.g., RoBERTa and BERT.",
}
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<abstract>We introduce jiant, an open source toolkit for conducting multitask and transfer learning experiments on English NLU tasks. jiant enables modular and configuration driven experimentation with state-of-the-art models and a broad set of tasks for probing, transfer learning, and multitask training experiments. jiant implements over 50 NLU tasks, including all GLUE and SuperGLUE benchmark tasks. We demonstrate that jiant reproduces published performance on a variety of tasks and models, e.g., RoBERTa and BERT.</abstract>
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%0 Conference Proceedings
%T jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models
%A Pruksachatkun, Yada
%A Yeres, Phil
%A Liu, Haokun
%A Phang, Jason
%A Htut, Phu Mon
%A Wang, Alex
%A Tenney, Ian
%A Bowman, Samuel R.
%Y Celikyilmaz, Asli
%Y Wen, Tsung-Hsien
%S Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F pruksachatkun-etal-2020-jiant
%X We introduce jiant, an open source toolkit for conducting multitask and transfer learning experiments on English NLU tasks. jiant enables modular and configuration driven experimentation with state-of-the-art models and a broad set of tasks for probing, transfer learning, and multitask training experiments. jiant implements over 50 NLU tasks, including all GLUE and SuperGLUE benchmark tasks. We demonstrate that jiant reproduces published performance on a variety of tasks and models, e.g., RoBERTa and BERT.
%R 10.18653/v1/2020.acl-demos.15
%U https://aclanthology.org/2020.acl-demos.15
%U https://doi.org/10.18653/v1/2020.acl-demos.15
%P 109-117
Markdown (Informal)
[jiant: A Software Toolkit for Research on General-Purpose Text Understanding Models](https://aclanthology.org/2020.acl-demos.15) (Pruksachatkun et al., ACL 2020)
ACL