A Cross-model Study on Learning Romanian Parts of Speech with Transformer Models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3A6GQFRL3K" target="_blank" >RIV/00216208:11320/25:6GQFRL3K - isvavai.cz</a>

Výsledek na webu

<a href="https://aclanthology.org/2024.clib-1.1" target="_blank" >https://aclanthology.org/2024.clib-1.1</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

A Cross-model Study on Learning Romanian Parts of Speech with Transformer Models

Popis výsledku v původním jazyce

This paper will attempt to determine experimentally if POS tagging of unseen words produces comparable performance, in terms of accuracy, as for words that were rarely seen in the training set (i.e. frequency less than 5), or more frequently seen (i.e. frequency greater than 10). To compare accuracies objectively, we will use the odds ratio statistic and its confidence interval testing to show that odds of being correct on unseen words are close to odds of being correct on rarely seen words. For the training of the POS taggers, we use different Romanian BERT models that are freely available on HuggingFace.

Název v anglickém jazyce

A Cross-model Study on Learning Romanian Parts of Speech with Transformer Models

Popis výsledku anglicky

This paper will attempt to determine experimentally if POS tagging of unseen words produces comparable performance, in terms of accuracy, as for words that were rarely seen in the training set (i.e. frequency less than 5), or more frequently seen (i.e. frequency greater than 10). To compare accuracies objectively, we will use the odds ratio statistic and its confidence interval testing to show that odds of being correct on unseen words are close to odds of being correct on rarely seen words. For the training of the POS taggers, we use different Romanian BERT models that are freely available on HuggingFace.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

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Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the Sixth International Conference on Computational Linguistics in Bulgaria (CLIB 2024)

ISBN

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ISSN

2367-5578

e-ISSN

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Počet stran výsledku

8

Strana od-do

6-13

Název nakladatele

Department of Computational Linguistics, Institute for Bulgarian Language, Bulgarian Academy of Sciences

Místo vydání

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Místo konání akce

Sofia, Bulgaria

Datum konání akce

1. 1. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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