GaborMadarasz/ModernBERT-base-hungarian-POS_long

Model Card for Model ID

Hungarian long-context Part-of-speech tagger ModernBERT-base.

Model Description

The model performs POS tagging on long Hungarian texts. (8k context-window)

labels: ['ADJ', 'ADP', 'ADV', 'AUX', 'CCONJ', 'DET', 'INTJ', 'NOUN', 'NUM', 'PART', 'PRON', 'PROPN', 'PUNCT', 'SCONJ', 'VERB', 'X']

Accuracy on hu_szeged-ud-test (token-level): 88.12%

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• Developed by: Gábor Madarász
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• Finetuned from model [optional]: GaborMadarasz/ModernBERT-base-hungarian

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Uses

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Training Details

Training Data

Phase-1 finetune

UD Hungarian Szeged: https://universaldependencies.org/treebanks/hu_szeged/index.html

POS tagging performed with huSapcy (hu_core_news_lg) on Hungarian Wikipedia.

Phase-2 finetune

POS tagging performed with phase-1 fine-tuned ModernBERT on a subset of opensubtitles.

Phase-3 finetune

POS tagging long texts (6k-8k tokens) with stanza

Training Procedure

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Summary

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Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).

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