| | --- |
| | license: mit |
| | language: |
| | - en |
| | base_model: |
| | - ThinkCERCA/counterargument_hugging |
| | pipeline_tag: text-classification |
| | --- |
| | # Target-Group Classifier |
| |
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| | <!-- Provide a quick summary of what the model is/does. --> |
| |
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| | The BERT-based counter-argument 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 [ThinkCERCA/counterargument_hugging](https://huggingface.co/ThinkCERCA/counterargument_hugging) |
| |
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| | It classifies either a given sentence is a valid counter-narrative. |
| |
|
| | ## 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. --> |
| | The model is intended for classifying LM-generated dialogue responses, and evaluating their validity as counter-narrative. |
