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--- |
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license: mit |
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language: |
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- en |
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base_model: |
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- NLP-LTU/bertweet-large-sexism-detector |
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pipeline_tag: text-classification |
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--- |
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# Target-Group Classifier |
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<!-- Provide a quick summary of what the model is/does. --> |
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The BERT-based target-demographic classifier is finetuned on the combined dataset of [CONAN](https://github.com/marcoguerini/CONAN) and [CrowdCounter](https://github.com/hate-alert/crowdcounter) for classifying whether a sequence is about one or multiple of the 8 target group, based on the sexism detector [NLP-LTU/bertweet-large-sexism-detector](https://huggingface.co./NLP-LTU/bertweet-large-sexism-detector) |
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Currently trained for the following classes: |
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["MIGRANTS", "POC", "LGBT+", "MUSLIMS", "WOMEN", "JEWS", "other", "DISABLED"] |
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## Uses |
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<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. --> |
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The model is intended for classifying LM-generated dialogue responses, and evaluating their relevancy to the given input sequence. |
