Fine-tuned model weights for Stance Detection Benchmark System

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datacite.relation.isCitedBy https://arxiv.org/abs/2001.01565
datacite.relation.isCitedBy https://doi.org/10.1007/s13218-021-00714-w
dc.contributor.author Schiller, Benjamin
dc.contributor.author Daxenberger, Johannes
dc.contributor.author Gurevych, Iryna
dc.date.accessioned 2021-07-03T22:09:32Z
dc.date.available 2021-07-03T22:09:32Z
dc.date.created 2019
dc.date.issued 2021-07-03
dc.description This collection includes model weights (BERT-based), fine-tuned in a multi-task setting on 10 heterogeneous stance detection datasets. For more information, please refer to the paper and the GitHub repository linked in the paper. DISCLAIMER: The user acknowledges and agrees that the data is provided on an “as­-is” basis and that the licensor makes no representations or warranties of any kind. en_US
dc.identifier.uri https://tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/2848
dc.language.iso en en_US
dc.rights.licenseIn Copyright (https://rightsstatements.org/vocab/InC/1.0/)
dc.subject Stance Detection en_US
dc.subject Benchmark en_US
dc.subject Model weights en_US
dc.subject.classification 4.43-04
dc.subject.classification 4.43-05
dc.subject.ddc 004
dc.title Fine-tuned model weights for Stance Detection Benchmark System en_US
dc.type Model en_US
dcterms.accessRights openAccess
person.identifier.orcid #PLACEHOLDER_PARENT_METADATA_VALUE#
person.identifier.orcid 0000-0002-7385-5654
person.identifier.orcid 0000-0003-2187-7621
tuda.history.classification Version=2016-2020;409-05 Interaktive und intelligente Systeme, Bild- und Sprachverarbeitung, Computergraphik und Visualisierung
tuda.project PTJ | 03VP02540 | ArgumenText
tuda.unit TUDa

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