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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ # Monitoring Harmful Text in Online Platforms
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+ ## Overview
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+ This repository hosts the RandomForest classifier model designed for detecting harmful text AGAINST GROUPS.
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+ The model classifies text into one of three categories: "Offensive or Hateful", "Neutral or Ambiguous", and "Not Hate".
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+ Achieving an accuracy of 92.5%, this model was developed through the combination of three distinct datasets, ensuring robustness and reliability in varied contexts.
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+ It was presented at the prestigious annual Gulf Coast Conference & Expo on AI.
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+ Model Details
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+ Model Type: RandomForest Classifier
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+ Accuracy: 92.5%
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+ Labels:
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+ 0: Neutral or Ambiguous
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+ 1: Not Hate
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+ 2: Offensive or Hateful
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+ Training Data: Augmented version of [this dataset](TLeonidas/twitter-hate-speech-en-240ksamples) (279k+ rows)
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