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README.md
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license: cc-by-4.0
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---
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# Hatemoji Model
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For the round-specific test sets, we used a weighted F1-score across them to choose the final model in each round. For more details, see our [paper](https://arxiv.org/abs/2108.05921)
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## Evaluation results
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We compare our model
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* **P-IA**: the identity attack attribute from Perspective API
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* **P-TX**: the toxicity attribute from Perspective API
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* **B-D**: A BERT model trained on the [Davidson et al. (2017)](https://github.com/t-davidson/hate-speech-and-offensive-language) dataset
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license: cc-by-4.0
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language:
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- en
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tags:
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- text-classification
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- pytorch
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- hate-speech-detection
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datasets:
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- HatemojiBuild
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- HatemojiCheck
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metrics:
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- Accuracy, F1 Score
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---
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# Hatemoji Model
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For the round-specific test sets, we used a weighted F1-score across them to choose the final model in each round. For more details, see our [paper](https://arxiv.org/abs/2108.05921)
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## Evaluation results
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We compare our model to:
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* **P-IA**: the identity attack attribute from Perspective API
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* **P-TX**: the toxicity attribute from Perspective API
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* **B-D**: A BERT model trained on the [Davidson et al. (2017)](https://github.com/t-davidson/hate-speech-and-offensive-language) dataset
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