Kubord-fasttext - Göteborgsposten 2013–2024 - lemma
https://doi.org/10.23695/K91C-K507
Kubord-fasttext is a collection of fasttext models, developed within a collaboration between
KBLab and Språkbanken Text, that have
been trained on the same underlying data as Kubord 2.
The models have been trained on the token and the lemma level. The tool that has been used for the training is
Gensim, with the following parameter settings:
min_n 4, max_n 7, 20 epoker, dim 300, and lr .05.
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Opens in a new tabhttps://doi.org/10.23695/K91C-K507
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University of Gothenburg