readme: ---
  language:
  - hu
  pipeline_tag: summarization
  inference:
    parameters:
      num_beams: 5
      length_penalty: 2
      max_length: 128
      encoder_no_repeat_ngram_size: 4
      no_repeat_ngram_size: 3
  datasets:
  - SZTAKI-HLT/HunSum-1
  metrics:
  - rouge
  license: apache-2.0
  ---
  
  # Model Card for mT5-base-HunSum-1
  
  The mT5-base-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 [google/mt5-base](https://huggingface.co/google/mt5-base).
  
  ## 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:** 12
  - **Learning Rate:** 5e-5
  - **Weight Decay:** 0.01
  - **Warmup Steps:** 3000
  - **Epochs:** 10
  - **no_repeat_ngram_size:** 3
  - **num_beams:** 5
  - **early_stopping:** False
  - **encoder_no_repeat_ngram_size:** 4
  
  ## Results
  
  | Metric        | Value                                       |
  | :------------ | :------------------------------------------ |
  | ROUGE-1       | 37.70                                       |
  | ROUGE-2       | 11.22                                       |
  | ROUGE-L       | 24.37                                       |
  
  ## 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}
  }
  ```