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}
}