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vesteinn/ScandiBERT
ScandiBERT is a fill-mask model from vesteinn. Use it when you need the model to fill a missing word. It is set up for transformers. The card lists the license as agpl-3.0.
Note note: The model has been updated on 2022-09-27
Downloads · 30 days
1.1K
7% of all-time downloads
All-time downloads
16K
Public
Parameters
125M
1.5 GB on disk
Likes
5
Public
Click a slice to open those files.
.bin498 MB · 50%
How the weights are stored.
F32125M · 100%
From the Hugging Face model README
Note note: The model has been updated on 2022-09-27
The model was trained on the data shown in the table below. Batch size was 8.8k, the model was trained for 72 epochs on 24 V100 cards for about 2 weeks.
| 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 |
| Faroese | FC3 + Sosialurinn + Bible | 69 MB |
Note: At an earlier date a half trained model went up here, it has since been removed. The model has since been updated.
This is a Scandinavian BERT model trained on a large collection of Danish, Faroese, Icelandic, Norwegian and Swedish text. It is currently the highest ranking model on the ScandEval leaderbord https://scandeval.github.io/pretrained/
If you find this model useful, please cite
@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},
}