这是一个没有法罗群岛数据和不同的子词tokenizer训练的ScandiBERT模型版本。
该模型是在下表所示的数据上进行训练的。批次大小为8.8k,模型在24个V100卡上进行了72个epoch的训练,大约耗时2周。
| Language | Data | Size |
|---|---|---|
| Icelandic | See IceBERT paper | 16 GB |
| Danish | Danish Gigaword Corpus (incl Twitter) | 4,7 GB |
| Norwegian | NCC corpus | 42 GB |
| Swedish | Swedish Gigaword Corpus | 3,4 GB |
如果您发现该模型有用,请引用
@inproceedings{snaebjarnarson-etal-2023-transfer,
title = "{T}ransfer to a Low-Resource Language via Close Relatives: The Case Study on Faroese",
author = "Snæbjarnarson, Vésteinn and
Simonsen, Annika and
Glavaš, Goran and
Vulić, Ivan",
booktitle = "Proceedings of the 24th Nordic Conference on Computational Linguistics (NoDaLiDa)",
month = "may 22--24",
year = "2023",
address = "Tórshavn, Faroe Islands",
publisher = {Link{\"o}ping University Electronic Press, Sweden},
}