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arXiv · 2511.09213

Pretraining Finnish ModernBERTs

Akseli Reunamo·Laura-Maria Peltonen·Hans Moen·Sampo Pyysalo
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Abstract

This paper reports on pretraining ModernBERT encoder models in six different sizes, ranging from 51M to 475M parameters, with a focus on limited multilingualism, emphasizing languages relevant to Finland. Our models are competitive with, or superior to, existing multilingual models. They outperform monolingual models on tasks that require a context longer than 512 tokens. We present empirical results on using different data in the final stage of training. The code and models are publicly released.

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Akseli Reunamo, Laura-Maria Peltonen, Hans Moen, Sampo Pyysalo. 2025-11-12. Pretraining Finnish ModernBERTs. https://arxiv.org/abs/2511.09213

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