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nahiar/xlm-roberta-indonesian-languages

sourceHugging Faceapache-2.0updated 10mo agoView on Hugging Face

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Model Card

Indonesian Regional Languages Identifier

Fine-tuned XLM-RoBERTa model for identifying 11 Indonesian regional languages + English.

Supported Languages

—🇮🇩 Indonesian (Bahasa Indonesia)
—Acehnese (Bahasa Aceh)
—Balinese (Basa Bali)
—Banjarese (Bahasa Banjar)
—Buginese (Basa Ugi)
—Javanese (Basa Jawa)
—Madurese (Basa Madhura)
—Minangkabau (Baso Minang)
—Ngaju (Basa Ngaju)
—Sundanese (Basa Sunda)
—Toba Batak (Hata Batak Toba)
—🇬🇧 English

Model Performance

—Accuracy: 0.9783
—F1 Macro: 0.9783
—F1 Weighted: 0.9783
—Precision: 0.9785
—Recall: 0.9783

Usage

python

from transformers import pipeline

# Load model
classifier = pipeline("text-classification", model="YOUR_USERNAME/xlm-roberta-indonesian-languages")

# Single prediction
result = classifier("Sugeng enjing, piye kabare?")
print(result)
# Output: [{'label': 'javanese', 'score': 0.9876}]

# Batch prediction
texts = [
    "Selamat pagi, apa kabar?",
    "Wilujeng enjing, kumaha damang?",
    "Good morning, how are you?"
]

results = classifier(texts)
for text, result in zip(texts, results):
    print(f"{text} -> {result['label']} ({result['score']:.4f})")

Training Details

—Base Model: xlm-roberta-base
—Training Samples: 6000
—Validation Samples: 1200
—Epochs: 5
—Learning Rate: 2e-05
—Batch Size: 16
—Training Date: 20251124_070409

Citation

If you use this model, please cite:

@misc{indonesian-language-id,
    author = {Raihan Hidayatullah Djunaedi},
    title = {Indonesian Regional Languages Identifier},
    year = {2025},
    publisher = {Hugging Face},
    url = {https://huggingface.co/nahiar/xlm-roberta-indonesian-languages}
}