CNN-BiLSTM reaches 83.8% accuracy and 81.2% F1 on a 13k Indonesian tweet hate-speech dataset, beating PyCaret's best model (Random Forest at 77.2% accuracy, 77.0% F1) by 6.6 and 4.2 points.
Hate speech detection in
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A Comparative Study of PyCaret AutoML and CNN-BiLSTM for Binary Hate Speech Detection in Indonesian Twitter
CNN-BiLSTM reaches 83.8% accuracy and 81.2% F1 on a 13k Indonesian tweet hate-speech dataset, beating PyCaret's best model (Random Forest at 77.2% accuracy, 77.0% F1) by 6.6 and 4.2 points.