ikhlamal/sahabat-ai-indonesian-news-analytics

Sahabat-AI Indonesian News Analytics

Model fine-tuned untuk analisis teks komentar berita bahasa Indonesia dengan tiga tugas utama:

Tasks

1. 1.Sentiment Analysis - klasifikasi sentimen: positif, negatif, netral
2. 2.Hate Speech Detection - deteksi ujaran kebencian: hate, not_hate
3. 3.Stance Detection - deteksi sikap: favor, against, neutral

Model Details

• —Base model: GoToCompany/gemma2-9b-cpt-sahabatai-v1-instruct
• —Fine-tuning method: LoRA (r=16, alpha=16, dropout=0.1)
• —Quantization: 4-bit (NF4)

Datasets Used

1. 1.NusaX — Sentiment analysis
2. 2.IndoLEM — Sentiment analysis
3. 3.Ialfina — Hate speech detection
4. 4.Okky Ibrohim — Hate speech detection
5. 5.Indonesian COVID-19 Vaccination Stance — Stance detection

Training Configuration

• —Epochs: 5 per dataset
• —Batch size: 2
• —Gradient accumulation steps: 4
• —Learning rate: 2e-4
• —Optimizer: AdamW 8-bit
• —Weight decay: 0.01
• —LR scheduler: Linear
• —Warmup steps: 5
• —Seed: 3407

Intended Use

Model ini dirancang untuk:

• —Analisis sentimen berita dan opini publik berbahasa Indonesia
• —Moderasi konten (deteksi ujaran kebencian)
• —Analisis stance dalam diskusi publik
• —Penelitian NLP bahasa Indonesia

Citation

@misc{sahabat-ai-news-analytics-2024,
  author = {Ikhlamal},
  title = {Sahabat-AI Indonesian News Analytics: Multi-task Text Classification for Indonesian},
  year = {2024},
  publisher = {HuggingFace},
  howpublished = {\url{https://huggingface.co/ikhlamal/sahabat-ai-indonesian-news-analytics}}
}

Acknowledgments

• —Base model: Sahabat-AI team (GoToCompany)
• —Dataset contributors: NusaX, IndoLEM, Ialfina, Okky Ibrohim, dan Indonesian COVID-19 Vaccination Stance authors

License

Apache 2.0

Contact

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