Hamming Loss: 0.2948
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Hate Speech Detection
Hate speech detection is the task of detecting if communication such as text, audio, and so on contains hatred and or encourages violence towards a person or a group of people. This is usually based on prejudice against 'protected characteristics' such as their ethnicity, gender, sexual orientation, religion, age et al. Some example benchmarks are ETHOS and HateXplain. Models can be evaluated with metrics like the F-score or F-measure.
논문
Macro F1: 0.494
F1-score: 0.759
AAA: 50.94F1 (micro): 84.42
F1: 0.8549
F1: 0.77
F1-score: 0.7971Classification Accuracy: 0.8015Precision: 0.8037
TEST F1 (macro): 0.79
Macro F1: 80.7
F1: 0.70
TEST F1 (macro): 0.848