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  ---
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  license: mit
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- pipeline_tag: fill-mask
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  tags:
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  - code
 
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  ---
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  # Zero-shot text classification (base-sized model) trained with self-supervised tuning
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@@ -15,6 +15,7 @@ The model backbone is RoBERTa-base.
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  ## Model description
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  The model is tuned with unlabeled data using a learning objective called first sentence prediction (FSP).
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  The FSP task is designed by considering both the nature of the unlabeled corpus and the input/output format of classification tasks.
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  The training and validation sets are constructed from the unlabeled corpus using FSP.
 
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  ---
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  license: mit
 
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  tags:
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  - code
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+ - Zero-Shot Classification
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  ---
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  # Zero-shot text classification (base-sized model) trained with self-supervised tuning
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  ## Model description
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+
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  The model is tuned with unlabeled data using a learning objective called first sentence prediction (FSP).
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  The FSP task is designed by considering both the nature of the unlabeled corpus and the input/output format of classification tasks.
21
  The training and validation sets are constructed from the unlabeled corpus using FSP.