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+ ---
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+ datasets:
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+ - PlanTL-GOB-ES/SQAC
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+ language:
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+ - es
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+ metrics:
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+ - bleu
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+ - meteor
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+ - rouge
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+ - sari
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+ - google_bleu
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+ - wer
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+ base_model:
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+ - bigscience/mt0-base
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+ pipeline_tag: text2text-generation
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+ library_name: transformers
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+ tags:
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+ - AnswerExtraction
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+ license: gpl-3.0
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+ ---
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+ # Citation
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+ If you use this model in your research, please cite the following paper: [Evaluating the performance of multilingual models in answer extraction and question generation.](https://www.nature.com/articles/s41598-024-66472-5)
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+
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+ ```
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+ @article{moreno-cediel_evaluating_2024,
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+ title = {Evaluating the performance of multilingual models in answer extraction and question generation},
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+ volume = {14},
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+ copyright = {2024 The Author(s)},
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+ issn = {2045-2322},
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+ url = {https://www.nature.com/articles/s41598-024-66472-5},
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+ doi = {10.1038/s41598-024-66472-5},
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+ language = {en},
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+ number = {1},
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+ urldate = {2025-01-10},
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+ journal = {Scientific Reports},
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+ author = {Moreno-Cediel, Antonio and del-Hoyo-Gabaldon, Jesus-Angel and Garcia-Lopez, Eva and Garcia-Cabot, Antonio and de-Fitero-Dominguez, David},
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+ month = jul,
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+ year = {2024},
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+ note = {Publisher: Nature Publishing Group},
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+ keywords = {Computer science, Software},
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+ pages = {15477},
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+ }
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+ ```