gmonsoon/Gemma3-Indonesia-energy-transition-v1

Model Card for Gemma3-Indonesia-energi-transation-v1

This model is fine-tuned to understand and generate content related to Indonesia’s renewable energy landscape, energy transition policies, and Net Zero Emission goals. It has been trained on a curated corpus of open-access academic papers, government regulations, research reports, and other domain-specific documents relevant to Indonesia’s energy sector. The model can answer questions, summarize regulations, and assist with policy analysis or educational content focused on Indonesia’s energy transition.

Model Details

Model Description

This is a transformer-based causal language model fine-tuned from Gemma-3 4B Instruct. It was trained on a specialized dataset assembled from open-access papers, Indonesian government regulations, research findings, and institutional guidelines related to renewable energy, energy transition strategies, Net Zero Emission frameworks, and other relevant topics in Indonesia. The dataset comprises question-answer pairs, document excerpts with annotations, and conversational prompts designed to teach the model both factual content and the appropriate tone for discourse in this domain.

• Developed by: Zulfikar Aji Kusworo (gmonsoon)

• Model Type: Causal Language Model (fine-tuned for domain-specific Q&A and summarization)

• Language(s): Indonesian (with occasional English technical terminology)

• License: Apache-2.0

• Finetuned From: Gemma-3 4B-Instruct

Training Data Sources:

• Open-access academic papers (e.g., Indonesian Journal of Renewable Energy, national research repositories)

• Government regulations and policy documents (e.g., Peraturan Menteri ESDM, Peraturan Presiden terkait Transisi Energi)

• Reports from research institutes (e.g., IESR)

• Technical guidelines from international organizations (e.g., IRENA, IEA)

Intended Uses

Direct Use

This model can be used to:

• Answer questions about specific regulations or policy frameworks for renewable energy in Indonesia (e.g., “What incentives does the 2023 Ministry of Energy Regulation provide for solar PV installations?”)

• Summarize academic papers or regulatory texts related to Net Zero Emission targets, carbon pricing, or energy transition roadmaps in Indonesia

• Generate educational content, such as lecture notes or FAQ pages, for university courses or workshop materials on Indonesian energy policy

• Assist researchers in drafting policy briefs or presentations by providing domain-appropriate language and up-to-date references within the Indonesian context

Out-of-Scope Use

This model is not suited for:

• Providing general financial or investment advice unrelated to Indonesia’s energy sector

• Offering medical, legal, or safety-critical recommendations

• Addressing energy topics outside the Indonesian context (e.g., U.S. shale gas policy, European Union emissions trading in detail)

• Making business decisions without human verification, as the model may not be aware of the very latest policy changes or proprietary data

Bias, Risks, and Limitations

• Data Biases: The model’s knowledge reflects the perspectives and priorities present in its training materials. Since much of the data comprises official government regulations and academic research, it may under-represent stakeholder viewpoints from local communities or informal sector actors.

• Temporal Limitations: Policies and regulations in the Indonesian energy sector evolve rapidly (e.g., updates to the 2023 ESDM regulations). The model’s training cutoff may not include the absolute most recent amendments released after the final data acquisition date.

• Terminology and Tone: While the model can generate formal policy analysis, it may occasionally conflate technical jargon with colloquial usage if prompted ambiguously.

• Generalization: Because the model is specialized for Indonesian energy content, it may produce incorrect or incomplete answers when asked about energy systems in other countries or unrelated domains.

Recommendations

• Verify Model Outputs: Always cross-check factual statements—especially numerical data, dates, and specific policy citations—against the original source documents or official government websites.

• Supplement with Expert Review: For high-stakes applications such as drafting official policy briefs or legal interpretations, seek review from domain experts (e.g., energy policy analysts, legal advisors).

• Update Training Data Periodically: Schedule periodic retraining or fine-tuning when significant new regulations, major research publications, or landmark policy shifts occur (e.g., updates to Indonesia’s National Energy Policy or new Net Zero Emission roadmaps).

• Understand Scope Boundaries: Refrain from using this model for domains beyond Indonesian renewable energy (e.g., international carbon trading schemes or non-energy environmental policies).

Environmental Impact

Carbon emissions can be estimated using the Machine Learning Impact calculator.

• Hardware Type: 4× NVIDIA RTX A6000 GPUs
• Hours used: not yet calculated, still continue
• Cloud Provider: Runpod
• Compute Region: Unknown
• Training Cost: not yet calculated
• Carbon Emitted: Not formally calculated

Citation

If you use this model in published work or official reports, please cite it as follows:

@misc{gemma3_indonesia_energy_transtition_v1,
      title={Gemma3-Indonesia-energi-transation-v1}, 
      author={Zulfikar Aji Kusworo},
      year={2025},
      note={Fine-tuned on Indonesian renewable energy and Net Zero Emission data},
      url={https://https://huggingface.co/gmonsoon/Gemma3-Indonesia-energy-transition-v1}, 
}