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@@ -17,8 +17,6 @@ The model is pre-trained on a machine-generated dataset for implicit hate speech
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  ## Model Details
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- ### Model Description
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-
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  <!-- Provide a longer summary of what this model is. -->
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  - **Base Model:** BERT-base-uncased
@@ -48,3 +46,10 @@ While these behavior can lead to social good e.g., constructing training data fo
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  **We strongly emphasize the need for careful handling to prevent unintentional misuse and warn against malicious exploitation of such behaviors.**
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  ## Model Details
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  <!-- Provide a longer summary of what this model is. -->
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  - **Base Model:** BERT-base-uncased
 
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  **We strongly emphasize the need for careful handling to prevent unintentional misuse and warn against malicious exploitation of such behaviors.**
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+ ## Acknowledgements
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+ - We use the [ToxiGen](https://huggingface.co/datasets/skg/toxigen-data) dataset as a pre-training source to pre-train our model. You can refer to the paper [here](https://aclanthology.org/2022.acl-long.234/).
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+ - We anonymize private information in the pre-training source following the code from https://github.com/dhfbk/hate-speech-artifacts.
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+ - Our pre-training code is based on the code from https://github.com/princeton-nlp/SimCSE with some modifications.
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+ - We use the code from https://github.com/youngwook06/ImpCon to fine-tune and evaluate our model.
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