IceBERT-xlmr-ic3
This model was trained with fairseq using the RoBERTa-base architecture. The model xlm-roberta-base
was used as a starting point. It is one of many models we have trained for Icelandic, see the paper referenced below for further details. The training data used is shown in the table below.
Dataset | Size | Tokens |
---|---|---|
Icelandic Common Crawl Corpus (IC3) | 4.9 GB | 824M |
Citation
The model is described in this paper https://arxiv.org/abs/2201.05601. Please cite the paper if you make use of the model.
@article{DBLP:journals/corr/abs-2201-05601,
author = {V{\'{e}}steinn Sn{\ae}bjarnarson and
Haukur Barri S{\'{\i}}monarson and
P{\'{e}}tur Orri Ragnarsson and
Svanhv{\'{\i}}t Lilja Ing{\'{o}}lfsd{\'{o}}ttir and
Haukur P{\'{a}}ll J{\'{o}}nsson and
Vilhj{\'{a}}lmur {\TH}orsteinsson and
Hafsteinn Einarsson},
title = {A Warm Start and a Clean Crawled Corpus - {A} Recipe for Good Language
Models},
journal = {CoRR},
volume = {abs/2201.05601},
year = {2022},
url = {https://arxiv.org/abs/2201.05601},
eprinttype = {arXiv},
eprint = {2201.05601},
timestamp = {Thu, 20 Jan 2022 14:21:35 +0100},
biburl = {https://dblp.org/rec/journals/corr/abs-2201-05601.bib},
bibsource = {dblp computer science bibliography, https://dblp.org}
}
- Downloads last month
- 49
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.