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--- |
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library_name: transformers |
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license: apache-2.0 |
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language: |
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- id |
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--- |
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## Model Details |
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### Model Description |
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<!-- Provide a longer summary of what this model is. --> |
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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. |
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This model is developed using the [NusaBERT-base](https://huggingface.co/LazarusNLP/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. |
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### Bias |
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<!-- This section is meant to convey both technical and sociotechnical limitations. --> |
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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. |
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### Evaluation Results |
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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. |
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* Average loss from Cross-Validation 0.11578517705202103 |
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* Evaluation Details on the Last Fold: |
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* Evaluation Loss 0.01048247329890728 |
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* Evaluation Time (seconds) 1.9982 |
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* Samples per Second 382,352 |
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* Steps per Second 24,022 |
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* Epoch 3 |
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<!-- This section describes the evaluation protocols and provides the results. --> |
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## Citation |
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``` |
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@misc{Ardiyanto_Mikhael_2024, |
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author = {Mikhael Ardiyanto}, |
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title = {NusaBERT-base-Indonesian-Plutchik-emotion-analysis }, |
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year = {2024}, |
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URL = {https://huggingface.co/Aardiiiiy/NusaBERT-base-Indonesian-Plutchik-emotion-analysis}, |
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publisher = {Hugging Face} |
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} |
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``` |
