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---
datasets:
- SZTAKI-HLT/HunSum-1
language:
- hu
metrics:
- rouge
pipeline_tag: text2text-generation
inference:
parameters:
num_beams: 5
length_penalty: 2
max_length: 128
no_repeat_ngram_size: 3
early_stopping: True
tags:
- hubert
- bert
- summarization
---
# 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](https://huggingface.co/datasets/SZTAKI-HLT/HunSum-1).
The model is based on [SZTAKI-HLT/hubert-base-cc](https://huggingface.co/SZTAKI-HLT/hubert-base-cc).
## Intended uses & limitations
- **Model type:** Text Summarization
- **Language(s) (NLP):** Hungarian
- **Resource(s) for more information:**
- [GitHub Repo](https://github.com/dorinapetra/summarization)
## 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}
}
``` |