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--- |
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license: cc-by-sa-4.0 |
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base_model: indobenchmark/indobert-large-p2 |
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language: |
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- min |
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- ban |
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- bug |
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- id |
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pretty_name: IndoBERTNusa |
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tags: |
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- generated_from_trainer |
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datasets: |
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- prosa-text/nusa-dialogue |
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- indonlp/NusaX-MT |
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pipeline_tag: fill-mask |
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--- |
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# IndoBERTNusa (IndoBERT Adapted for Balinese, Buginese, and Minangkabau) |
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This repository contains a language adaptation and fine-tuning of the Indobenchmark IndoBERT language model for three specific languages: Balinese, Buginese, and Minangkabau. |
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The adaptation was performed using [nusa-translation](https://huggingface.co/datasets/prosa-text/nusa-translation) dataset. |
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## Model Details |
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- **Base Model**: [indobenchmark/indobert-large-p2](https://huggingface.co/indobenchmark/indobert-large-p2) |
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- **Adaptation Data**: [nusa-translation](https://huggingface.co/datasets/prosa-text/nusa-translation) |
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## Performance Comparison / Benchmark |
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### Topic Classification |
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We tested the model after it was fine-tuned for topic classification using [nusa-dialogue](https://huggingface.co/datasets/prosa-text/nusa-dialogue) dataset. |
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| Language | indobert-large-p2 (F1) | indobert-nusa (F1) | |
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|-------------|------------------------|------------------------| |
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| Balinese | 82.37 | **84.23** | |
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| Buginese | 80.53 | **82.03** | |
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| Minangkabau | 84.49 | **86.30** | |
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### Language Identification |
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We also tested the model after it was fine-tuned for language identification using [nusaX](https://github.com/IndoNLP/nusax) dataset. |
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| Model | F1-score | |
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|----------------------|--------------| |
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| indobert-large-p2 | 98.21 | |
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| **indober-nusa** | **98.45** | |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 3.0 |
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### Framework versions |
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- Transformers 4.33.1 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.13.3 |
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## Additional Information |
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### Licensing Information |
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The dataset is released under the terms of **CC-BY-SA 4.0**. |
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By using this model, you are also bound to the respective Terms of Use and License of the dataset. |
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For commercial use in small businesses and startups, please contact us ([email protected]) for permission to use the datasets by informing company profile and propose of usage. |
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### Acknowledgement |
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This research work is funded and supported by The Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH and FAIR Forward - Artificial Intelligence for all. We thank Direktorat Jenderal Pendidikan Tinggi, Riset, dan Teknologi Kementerian Pendidikan, Kebudayaan, Riset, dan Teknologi (Ditjen DIKTI) for providing the computing resources for this project. |
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### Contact Us |
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If you have any question please contact our support team at `[email protected]`. |
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