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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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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