cff-version: 1.2.0
abstract: "<p>Trained models for the paper "What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric", published at ACL '23. The models were trained on the MFTC datasets with the sequential paradigm. Each of the seven models was trained on six MFTC datasets and continued training on a portion of the seventh. The code that contains instructions on how to use the models is available at this DOI: 10.4121/1e71138c-be26-4652-971a-48a84837df8e</p>"
authors:
  - family-names: Liscio
    given-names: Enrico
    orcid: "https://orcid.org/0000-0002-8285-5867"
  - family-names: Araque
    given-names: Oscar
    orcid: "https://orcid.org/0000-0003-3224-0001"
  - family-names: Gatti
    given-names: Lorenzo
    orcid: "https://orcid.org/0000-0003-2422-5055"
  - family-names: Constantinescu
    given-names: Ionut
    orcid: "https://orcid.org/0009-0003-5494-0161"
  - family-names: Jonker
    given-names: C.M. (Catholijn)
    orcid: "https://orcid.org/0000-0003-4780-7461"
  - family-names: Kalimeri
    given-names: Kyriaki
    orcid: "https://orcid.org/0000-0001-8068-5916"
  - family-names: Murukannaiah
    given-names: Pradeep K.
    orcid: "https://orcid.org/0000-0002-1261-6908"
title: "What does a Text Classifier Learn about Morality? An Explainable Method for Cross-Domain Comparison of Moral Rhetoric - models"
keywords:
version: 1
identifiers:
  - type: doi
    value: 10.4121/646b20e3-e24f-452d-938a-bcb6ce30913c.v1
license: CC BY 4.0
date-released: 2023-12-18