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  results: []
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- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- should probably proofread and complete it, then remove this comment. -->
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  # Clickbait1
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  This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the [Webis-Clickbait-17](https://zenodo.org/record/5530410) dataset.
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  ## Intended uses & limitations
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- Model was designed to work on Transformers (like in the paper "Predicting Clickbait Strength in Online Social Media" by Indurthi Vijayasaradhi, Syed Bakhtiyar, Gupta Manish, Varma Vasudeva).
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- The model wa trained with english titles.
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  ## Training and evaluation data
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- We trained the model with the official training data for the chalenge, plus another set that was just available after the end of the challenge.
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  ## Training procedure
 
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  ### Training hyperparameters
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  results: []
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  # Clickbait1
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  This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the [Webis-Clickbait-17](https://zenodo.org/record/5530410) dataset.
 
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  ## Intended uses & limitations
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+ Model looks like the model described in the paper [Predicting Clickbait Strength in Online Social Media](https://aclanthology.org/2020.coling-main.425/) by Indurthi Vijayasaradhi, Syed Bakhtiyar, Gupta Manish, Varma Vasudeva.
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+ The model was trained with english titles.
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  ## Training and evaluation data
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+ We trained the model with the official training data for the chalenge (clickbait17-train-170630.zip (894 MiB, 19538 posts), plus another set that was just available after the end of the challenge (clickbait17-train-170331.zip (157 MiB, 2459 posts).
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  ## Training procedure
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+ Code can be find in [Github](https://github.com/caush/Clickbait).
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  ### Training hyperparameters
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