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--- |
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language: |
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- hu |
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pipeline_tag: summarization |
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inference: |
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parameters: |
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num_beams: 5 |
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length_penalty: 2 |
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max_length: 128 |
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encoder_no_repeat_ngram_size: 4 |
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no_repeat_ngram_size: 3 |
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datasets: |
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- SZTAKI-HLT/HunSum-1 |
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metrics: |
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- rouge |
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--- |
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# Model Card for mT5-small-HunSum-1 |
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The mT5-small-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). |
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The model is based on [google/mt5-small]([google/mt5-small](https://huggingface.co/google/mt5-small)). |
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## Intended uses & limitations |
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- **Model type:** Text Summarization |
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- **Language(s) (NLP):** Hungarian |
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- **Resource(s) for more information:** |
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- [GitHub Repo](https://github.com/dorinapetra/summarization) |
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## Parameters |
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- **Batch Size:** 16 |
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- **Learning Rate:** 5e-5 |
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- **Weight Decay:** 0.01 |
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- **Warmup Steps:** 3000 |
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- **Epochs:** 10 |
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- **no_repeat_ngram_size:** 3 |
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- **num_beams:** 5 |
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- **early_stopping:** False |
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- **encoder_no_repeat_ngram_size:** 4 |
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## Results |
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| Metric | Value | |
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| :------------ | :------------------------------------------ | |
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| ROUGE-1 | 36.49 | |
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| ROUGE-2 | 9.50 | |
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| ROUGE-L | 23.48 | |
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## Citation |
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If you use our model, please cite the following paper: |
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``` |
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@inproceedings {mt5-small-HunSum-1, |
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title = {{HunSum-1: an Abstractive Summarization Dataset for Hungarian}}, |
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booktitle = {XIX. Magyar Számítógépes Nyelvészeti Konferencia (MSZNY 2023)}, |
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year = {2023}, |
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publisher = {Szegedi Tudományegyetem, Informatikai Intézet}, |
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address = {Szeged, Magyarország}, |
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author = {Barta, Botond and Lakatos, Dorina and Nagy, Attila and Nyist, Mil{\'{a}}n Konor and {\'{A}}cs, Judit}, |
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pages = {231--243} |
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} |
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``` |
