Quantifying the Carbon Emissions of Machine Learning
Paper • 1910.09700 • Published • 61
Model Card for Model ID
This model is a fine-tuned version of Llama-3-8B developed as a domain-specific AI assistant for 7th-grade science education. The model is designed to answer curriculum-aligned science questions using concise and accurate explanations.
Model Details
- Base Model: Meta-Llama-3-8B
- Fine-Tuning Method: LoRA (Low-Rank Adaptation)
- Library: Unsloth
- Quantization: 4-bit
- Environment: Google Colab (GPU)
Model Description
The model specializes in basic science concepts taught in the 7th-grade curriculum, including matter, atoms, molecules, states of matter, mixtures, and physical and chemical changes. It is optimized to provide short, clear, and educational responses.
Dataset Source and Authenticity
The training dataset consists of question–answer pairs manually extracted from a 7th-grade science textbook. All data was collected from real educational sources and was not generated using any AI system. A PDF reference of the original source is included in the project submission for verification.
Evaluation Summary
Before fine-tuning, the base model produced general and sometimes overly verbose answers. After fine-tuning, the model demonstrated improved accuracy and consistency by generating responses closely aligned with the training data and curriculum content.
Intended Use
This model is intended for educational assistance only. It can be used by students and teachers to review and explain basic science concepts at the middle school level.
Limitations
- The model is limited to the scope of the 7th-grade science curriculum.
- It may not perform well on topics outside the training domain.
- The model should not be used as a replacement for formal education.
Uses
Direct Use
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Out-of-Scope Use
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Bias, Risks, and Limitations
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Recommendations
Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
How to Get Started with the Model
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Training Details
Training Data
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Training Procedure
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Evaluation
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Results
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Summary
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Environmental Impact
Carbon emissions can be estimated using the Machine Learning Impact calculator presented in Lacoste et al. (2019).
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