@inproceedings{al-jarrah-etal-2020-hr,
title = "{HR}@{JUST} Team at {S}em{E}val-2020 Task 4: The Impact of {R}o{BERT}a Transformer for Evaluation Common Sense Understanding",
author = "Al-Jarrah, Heba and
Al-Hamouri, Rahaf and
AL-Smadi, Mohammad",
editor = "Herbelot, Aurelie and
Zhu, Xiaodan and
Palmer, Alexis and
Schneider, Nathan and
May, Jonathan and
Shutova, Ekaterina",
booktitle = "Proceedings of the Fourteenth Workshop on Semantic Evaluation",
month = dec,
year = "2020",
address = "Barcelona (online)",
publisher = "International Committee for Computational Linguistics",
url = "https://aclanthology.org/2020.semeval-1.64",
doi = "10.18653/v1/2020.semeval-1.64",
pages = "521--526",
abstract = "This paper describes the results of our team HR@JUST participation at SemEval-2020 Task 4 - Commonsense Validation and Explanation (ComVE) for POST evaluation period. The provided task consists of three sub-tasks, we participate in task A. We considered a state-of-the-art approach for solving this task by performing RoBERTa model with no Next Sentences Prediction (NSP), dynamic masking, larger training data, and larger batch size. The achieved results show that we got the 11th rank on the final test set leaderboard with an accuracy of 91.3{\%}.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="al-jarrah-etal-2020-hr">
<titleInfo>
<title>HR@JUST Team at SemEval-2020 Task 4: The Impact of RoBERTa Transformer for Evaluation Common Sense Understanding</title>
</titleInfo>
<name type="personal">
<namePart type="given">Heba</namePart>
<namePart type="family">Al-Jarrah</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Rahaf</namePart>
<namePart type="family">Al-Hamouri</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Mohammad</namePart>
<namePart type="family">AL-Smadi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2020-12</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the Fourteenth Workshop on Semantic Evaluation</title>
</titleInfo>
<name type="personal">
<namePart type="given">Aurelie</namePart>
<namePart type="family">Herbelot</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Xiaodan</namePart>
<namePart type="family">Zhu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alexis</namePart>
<namePart type="family">Palmer</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Nathan</namePart>
<namePart type="family">Schneider</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Jonathan</namePart>
<namePart type="family">May</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ekaterina</namePart>
<namePart type="family">Shutova</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>International Committee for Computational Linguistics</publisher>
<place>
<placeTerm type="text">Barcelona (online)</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>This paper describes the results of our team HR@JUST participation at SemEval-2020 Task 4 - Commonsense Validation and Explanation (ComVE) for POST evaluation period. The provided task consists of three sub-tasks, we participate in task A. We considered a state-of-the-art approach for solving this task by performing RoBERTa model with no Next Sentences Prediction (NSP), dynamic masking, larger training data, and larger batch size. The achieved results show that we got the 11th rank on the final test set leaderboard with an accuracy of 91.3%.</abstract>
<identifier type="citekey">al-jarrah-etal-2020-hr</identifier>
<identifier type="doi">10.18653/v1/2020.semeval-1.64</identifier>
<location>
<url>https://aclanthology.org/2020.semeval-1.64</url>
</location>
<part>
<date>2020-12</date>
<extent unit="page">
<start>521</start>
<end>526</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T HR@JUST Team at SemEval-2020 Task 4: The Impact of RoBERTa Transformer for Evaluation Common Sense Understanding
%A Al-Jarrah, Heba
%A Al-Hamouri, Rahaf
%A AL-Smadi, Mohammad
%Y Herbelot, Aurelie
%Y Zhu, Xiaodan
%Y Palmer, Alexis
%Y Schneider, Nathan
%Y May, Jonathan
%Y Shutova, Ekaterina
%S Proceedings of the Fourteenth Workshop on Semantic Evaluation
%D 2020
%8 December
%I International Committee for Computational Linguistics
%C Barcelona (online)
%F al-jarrah-etal-2020-hr
%X This paper describes the results of our team HR@JUST participation at SemEval-2020 Task 4 - Commonsense Validation and Explanation (ComVE) for POST evaluation period. The provided task consists of three sub-tasks, we participate in task A. We considered a state-of-the-art approach for solving this task by performing RoBERTa model with no Next Sentences Prediction (NSP), dynamic masking, larger training data, and larger batch size. The achieved results show that we got the 11th rank on the final test set leaderboard with an accuracy of 91.3%.
%R 10.18653/v1/2020.semeval-1.64
%U https://aclanthology.org/2020.semeval-1.64
%U https://doi.org/10.18653/v1/2020.semeval-1.64
%P 521-526
Markdown (Informal)
[HR@JUST Team at SemEval-2020 Task 4: The Impact of RoBERTa Transformer for Evaluation Common Sense Understanding](https://aclanthology.org/2020.semeval-1.64) (Al-Jarrah et al., SemEval 2020)
ACL