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SZTAKI-HLT/
Bert2Bert-HunSum-1

Name: Bert2Bert-HunSum-1
Availability: InStock

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Model Card for Bert2Bert-HunSum-1

The Bert2Bert-HunSum-1 is a Hungarian abstractive summarization model, which was trained on the SZTAKI-HLT/HunSum-1 dataset. The model is based on SZTAKI-HLT/hubert-base-cc.

Intended uses & limitations

Model type: Text Summarization
Language(s) (NLP): Hungarian
Resource(s) for more information:
- GitHub Repo

Parameters

Batch Size: 13
Learning Rate: 5e-5
Weight Decay: 0.01
Warmup Steps: 16000
Epochs: 15
no_repeat_ngram_size: 3
num_beams: 5
early_stopping: True

Results

Metric	Value
ROUGE-1	28.52
ROUGE-2	10.35
ROUGE-L	20.07

Citation

If you use our model, please cite the following paper:

@inproceedings {HunSum-1,
    title = {{HunSum-1: an Abstractive Summarization Dataset for Hungarian}},
	booktitle = {XIX. Magyar Számítógépes Nyelvészeti Konferencia (MSZNY 2023)},
	year = {2023},
	publisher = {Szegedi Tudományegyetem, Informatikai Intézet},
	address = {Szeged, Magyarország},
	author = {Barta, Botond and Lakatos, Dorina and Nagy, Attila and Nyist, Mil{\'{a}}n Konor and {\'{A}}cs, Judit},
	pages = {231--243}
}

SZTAKI-HLT/Bert2Bert-HunSum-1