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IceBERT was trained with fairseq using the RoBERTa-base architecture. The training data used is shown in the table below.

Dataset Size Tokens
Icelandic Gigaword Corpus v20.05 (IGC) 8.2 GB 1,388M
Icelandic Common Crawl Corpus (IC3) 4.9 GB 824M
Greynir News articles 456 MB 76M
Icelandic Sagas 9 MB 1.7M
Open Icelandic e-books (Rafbókavefurinn) 14 MB 2.6M
Data from the medical library of Landspitali 33 MB 5.2M
Student theses from Icelandic universities (Skemman) 2.2 GB 367M
Total 15.8 GB 2,664M

If you find this model useful, please cite

    title = "A Warm Start and a Clean Crawled Corpus - A Recipe for Good Language Models",
    author = "Sn{\ae}bjarnarson, V{\'e}steinn  and
      S{\'\i}monarson, Haukur Barri  and
      Ragnarsson, P{\'e}tur Orri  and
      Ing{\'o}lfsd{\'o}ttir, Svanhv{\'\i}t Lilja  and
      J{\'o}nsson, Haukur  and
      Thorsteinsson, Vilhjalmur  and
      Einarsson, Hafsteinn",
    booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference",
    month = jun,
    year = "2022",
    address = "Marseille, France",
    publisher = "European Language Resources Association",
    url = "https://aclanthology.org/2022.lrec-1.464",
    pages = "4356--4366",
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Dataset used to train vesteinn/IceBERT