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--- |
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language: id |
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tags: |
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- indonesian-roberta-base-sentiment-classifier |
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license: mit |
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datasets: |
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- indonlu |
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widget: |
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- text: "Jangan sampai saya telpon bos saya ya!" |
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--- |
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## Indonesian RoBERTa Base Sentiment Classifier |
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Indonesian RoBERTa Base Sentiment Classifier is a sentiment-text-classification model based on the [RoBERTa](https://arxiv.org/abs/1907.11692) model. The model was originally the pre-trained [Indonesian RoBERTa Base](https://hf.co/flax-community/indonesian-roberta-base) model, which is then fine-tuned on [`indonlu`](https://hf.co/datasets/indonlu)'s `SmSA` dataset consisting of Indonesian comments and reviews. |
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After training, the model achieved an evaluation accuracy of 94.36% and F1-macro of 92.42%. On the benchmark test set, the model achieved an accuracy of 93.2% and F1-macro of 91.02%. |
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Hugging Face's `Trainer` class from the [Transformers](https://huggingface.co/transformers) library was used to train the model. PyTorch was used as the backend framework during training, but the model remains compatible with other frameworks nonetheless. |
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## Model |
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| Model | #params | Arch. | Training/Validation data (text) | |
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| ---------------------------------------------- | ------- | ------------ | ------------------------------- | |
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| `indonesian-roberta-base-sentiment-classifier` | 124M | RoBERTa Base | `SmSA` | |
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## Evaluation Results |
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The model was trained for 5 epochs and the best model was loaded at the end. |
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| Epoch | Training Loss | Validation Loss | Accuracy | F1 | Precision | Recall | |
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| ----- | ------------- | --------------- | -------- | -------- | --------- | -------- | |
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| 1 | 0.342600 | 0.213551 | 0.928571 | 0.898539 | 0.909803 | 0.890694 | |
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| 2 | 0.190700 | 0.213466 | 0.934127 | 0.901135 | 0.925297 | 0.882757 | |
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| 3 | 0.125500 | 0.219539 | 0.942857 | 0.920901 | 0.927511 | 0.915193 | |
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| 4 | 0.083600 | 0.235232 | 0.943651 | 0.924227 | 0.926494 | 0.922048 | |
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| 5 | 0.059200 | 0.262473 | 0.942063 | 0.920583 | 0.924084 | 0.917351 | |
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## How to Use |
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### As Text Classifier |
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```python |
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from transformers import pipeline |
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pretrained_name = "w11wo/indonesian-roberta-base-sentiment-classifier" |
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nlp = pipeline( |
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"sentiment-analysis", |
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model=pretrained_name, |
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tokenizer=pretrained_name |
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) |
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nlp("Jangan sampai saya telpon bos saya ya!") |
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``` |
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## Disclaimer |
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Do consider the biases which come from both the pre-trained RoBERTa model and the `SmSA` dataset that may be carried over into the results of this model. |
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## Author |
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Indonesian RoBERTa Base Sentiment Classifier was trained and evaluated by [Wilson Wongso](https://w11wo.github.io/). All computation and development are done on Google Colaboratory using their free GPU access. |
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## Citation |
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If used, please cite the following: |
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```bibtex |
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@misc {wilson_wongso_2023, |
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author = { {Wilson Wongso} }, |
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title = { indonesian-roberta-base-sentiment-classifier (Revision e402e46) }, |
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year = 2023, |
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url = { https://huggingface.co/w11wo/indonesian-roberta-base-sentiment-classifier }, |
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doi = { 10.57967/hf/0644 }, |
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publisher = { Hugging Face } |
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} |
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``` |
