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    <abstract>We train and evaluate Norwegian sentence embedding models using the contrastive learning methodology SimCSE. We start from pre-trained Norwegian encoder models and train both unsupervised and supervised models. The models are evaluated on a machine-translated version of semantic textual similarity datasets, as well as binary classification tasks. We show that we can train good Norwegian sentence embedding models, that clearly outperform the pre-trained encoder models, as well as the multilingual mBERT, on the task of sentence similarity.</abstract>
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%0 Conference Proceedings
%T Training and Evaluating Norwegian Sentence Embedding Models
%A Nødland, Bernt Ivar Utstøl
%Y Alumäe, Tanel
%Y Fishel, Mark
%S Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)
%D 2023
%8 May
%I University of Tartu Library
%C Tórshavn, Faroe Islands
%F nodland-2023-training
%X We train and evaluate Norwegian sentence embedding models using the contrastive learning methodology SimCSE. We start from pre-trained Norwegian encoder models and train both unsupervised and supervised models. The models are evaluated on a machine-translated version of semantic textual similarity datasets, as well as binary classification tasks. We show that we can train good Norwegian sentence embedding models, that clearly outperform the pre-trained encoder models, as well as the multilingual mBERT, on the task of sentence similarity.
%U https://aclanthology.org/2023.nodalida-1.23
%P 228-237

Markdown (Informal)

[Training and Evaluating Norwegian Sentence Embedding Models](https://aclanthology.org/2023.nodalida-1.23) (Nødland, NoDaLiDa 2023)

• Training and Evaluating Norwegian Sentence Embedding Models (Nødland, NoDaLiDa 2023)

ACL

• Bernt Ivar Utstøl Nødland. 2023. Training and Evaluating Norwegian Sentence Embedding Models. In Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa), pages 228–237, Tórshavn, Faroe Islands. University of Tartu Library.