cardiffnlp / twitter-roberta-base-hate-multiclass-latest

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Total runs: 1.0K
24-hour runs: 0
7-day runs: -125
30-day runs: -157
Model's Last Updated: July 06 2023
text-classification

Introduction of twitter-roberta-base-hate-multiclass-latest

Model Details of twitter-roberta-base-hate-multiclass-latest

cardiffnlp/twitter-roberta-base-hate-multiclass-latest

This model is a fine-tuned version of cardiffnlp/twitter-roberta-base-2022-154m for multiclass hate-speech classification. A combination of 13 different hate-speech datasets in the English language were used to fine-tune the model.

Classes available
{
  "sexism": 0,
  "racism": 1,
  "disability": 2,
  "sexual_orientation": 3,
  "religion": 4,
  "other": 5,
  "not_hate":6
}
Following metrics are achieved
  • Accuracy: 0.9419
  • Macro-F1: 0.5752
  • Weighted-F1: 0.9390
Usage

Install tweetnlp via pip.

pip install tweetnlp

Load the model in python.

import tweetnlp
model = tweetnlp.Classifier("cardiffnlp/twitter-roberta-base-hate-latest")
model.predict('Women are trash 2.')
>> {'label': 'sexism'}
model.predict('@user dear mongoloid respect sentiments & belief refrain totalitarianism. @user')
>> {'label': 'disability'}
Model based on:
@misc{antypas2023robust,
      title={Robust Hate Speech Detection in Social Media: A Cross-Dataset Empirical Evaluation}, 
      author={Dimosthenis Antypas and Jose Camacho-Collados},
      year={2023},
      eprint={2307.01680},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}

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7-day runs
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