Papers › Large-Scale Contextualised Language Modelling for Norwegian

Large-Scale Contextualised Language Modelling for Norwegian

13 Apr 2021NoDaLiDa 2021 5arXiv:2104.06546archive 2025-07-28

Andrey Kutuzov, Jeremy Barnes, Erik Velldal, Lilja Øvrelid, Stephan Oepen

We present the ongoing NorLM initiative to support the creation and use of very large contextualised language models for Norwegian (and in principle other Nordic languages), including a ready-to-use software environment, as well as an experience report for data preparation and training. This paper introduces the first large-scale monolingual language models for Norwegian, based on both the ELMo and BERT frameworks. In addition to detailing the training process, we present contrastive benchmark results on a suite of NLP tasks for Norwegian. For additional background and access to the data, models, and software, please see http://norlm.nlpl.eu

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encoder ltgoslo/NorBERT/utils/finetuning_example.py official repository unverified CC0-1.0 (permissive) · 9fd7102d14d4b867 · report
multi_acc ltgoslo/NorBERT/utils/finetuning_example.py official repository unverified CC0-1.0 (permissive) · 9a450a0cc3ad60fb · report
zeropower_via_newtonschulz5 ltgoslo/NorBERT/norbert4/muon.py official repository unverified CC0-1.0 (permissive) · c98301effef79e18 · report

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Language Modelling

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AdamAttentionAttention DropoutBERTBiLSTMDense ConnectionsDropoutELMoLSTMLayer NormalizationLinear LayerLinear Warmup With Linear DecayMulti-Head AttentionResidual ConnectionSigmoid ActivationSoftmaxTanh ActivationWeight DecayWordPiece

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