Abstract
Several transformer-based language models for Serbian are developed, compared, and analyzed based on their performance across various NLP tasks.
The paper will briefly present the development history of transformer-based language models for the Serbian language. Several new models for text generation and vectorization, trained on the resources of the Society for Language Resources and Technologies, will also be presented. Ten selected vectorization models for Serbian, including two new ones, will be compared on four natural language processing tasks. Paper will analyze which models are the best for each selected task, how does their size and the size of their training sets affect the performance on those tasks, and what is the optimal setting to train the best language models for the Serbian language.
Models citing this paper 6
Browse 6 models citing this paperDatasets citing this paper 0
No dataset linking this paper
Spaces citing this paper 1
Collections including this paper 0
No Collection including this paper