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@@ -12,9 +12,8 @@ model-index:
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  - name: bertweet-base-finetuned-SARC-DS
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  results: []
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  ---
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-
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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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  # bertweet-base-finetuned-SARC-DS
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@@ -28,16 +27,13 @@ It achieves the following results on the evaluation set:
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  ## Model description
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- The given description for BERTweet by VinAI is as follows:
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  BERTweet is the first public large-scale language model pre-trained for English Tweets. BERTweet is trained based on the RoBERTa pre-training procedure. The corpus used to pre-train BERTweet consists of 850M English Tweets (16B word tokens ~ 80GB), containing 845M Tweets streamed from 01/2012 to 08/2019 and 5M Tweets related to the COVID-19 pandemic.
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- ## Intended uses & limitations
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-
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- More information needed
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  ## Training and evaluation data
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- More information needed
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  ## Training procedure
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  - name: bertweet-base-finetuned-SARC-DS
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  results: []
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  ---
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+ # Utilising Weak Supervision to Create S3D: A Sarcasm Annotated Dataset
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+ This is the repository for the S3D dataset published at EMNLP 2022. The dataset can help build sarcasm detection models.
 
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  # bertweet-base-finetuned-SARC-DS
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  ## Model description
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+ The given description for BERTweet by VinAI is as follows: <br>
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  BERTweet is the first public large-scale language model pre-trained for English Tweets. BERTweet is trained based on the RoBERTa pre-training procedure. The corpus used to pre-train BERTweet consists of 850M English Tweets (16B word tokens ~ 80GB), containing 845M Tweets streamed from 01/2012 to 08/2019 and 5M Tweets related to the COVID-19 pandemic.
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+ <br>
 
 
 
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  ## Training and evaluation data
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+ This [vinai/bertweet-base](https://huggingface.co/vinai/bertweet-base) model was finetuned on the [SARC](https://metatext.io/datasets/self-annotated-reddit-corpus-(sarc)) dataset. The dataset is intended to help build sarcasm detection models.
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  ## Training procedure
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