The NusaBERT-base-Indonesian-Plutchik-emotion-analysis is a model designed to identify and analyze emotions in Indonesian texts based on Plutchik's eight basic emotions: Anticipation, Anger, Disgust, Fear, Joy, Sadness, Surprise, and Trust.
This model is developed using the NusaBERT-base architecture and trained using Indonesian tweets categorized into eight emotion categories. The evaluation results of this model can be utilized to analyze emotions in social media, providing insights into users' emotional responses.
Bias
Keep in mind that this model is trained using certain data which may cause bias in the emotion classification process. Therefore, it is important to consider and account for such biases when using this model.
Evaluation Results
The training was conducted using a 5-fold cross-validation k-fold technique. The data is divided into five equal parts in this process, and the model is trained and tested repeatedly. Each time, four parts are used for training, and one part is used for testing.
Average loss from Cross-Validation 0.11578517705202103
Evaluation Details on the Last Fold:
Evaluation Loss 0.01048247329890728
Evaluation Time (seconds) 1.9982
Samples per Second 382,352
Steps per Second 24,022
Epoch 3
Citation
@misc{Ardiyanto_Mikhael_2024,
author = {Mikhael Ardiyanto},
title = {NusaBERT-base-Indonesian-Plutchik-emotion-analysis },
year = {2024},
URL = {https://huggingface.co/Aardiiiiy/NusaBERT-base-Indonesian-Plutchik-emotion-analysis},
publisher = {Hugging Face}
}
