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README.md
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library_name: transformers
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# Descliption
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Now we are working on preparing the Model card. Please wait for a few days.
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The model trained from [bert-large-uncased](https://huggingface.co/bert-large-uncased]) on the dataset published in the paper
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The dataset to make this model is based on English Wikipedia data and has 20 labels. However, this model will classify into 14 labels. This is because the 20-class data set was restructured to 14 classes to suit our research objective of "automatic slide generation. This distribution is shown below.
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library_name: transformers
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# bert-large-relation14
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Finetuned BERT model for 14-class classification. It was introduced in the paper: [Automatic Slide Generation Using Discourse Relations](https://link.springer.com/chapter/10.1007/978-3-031-36336-8_61) and first released in this repository. This model is uncased: it does not make a difference between english and English.
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# Descliption
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Now we are working on preparing the Model card. Please wait for a few days.
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The model trained from [bert-large-uncased](https://huggingface.co/bert-large-uncased]) on the dataset published in the paper: [Automatic Prediction of Discourse Connectives](https://arxiv.org/abs/1702.00992).
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The dataset to make this model is based on English Wikipedia data and has 20 labels. However, this model will classify into 14 labels. This is because the 20-class data set was restructured to 14 classes to suit our research objective of "automatic slide generation. This distribution is shown below.
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