---
base_model: unsloth/gemma-3-4b-it-unsloth-bnb-4bit
license: cc
language:
- en
tags:
- evacuation
- safety
- emergency-planning
- fire-safety
datasets:
- pozapas/evacuation-safety-qa
---
# Gemma-3-Evacuation (4B)

This model is a fine-tuned version of [Google's Gemma-3-4B-it](https://huggingface.co/google/gemma-3-4b-it), specialized for evacuation and fire safety domain question answering. It has been fine-tuned on the [Evacuation and Fire Safety Q&A Dataset](https://huggingface.co/datasets/pozapas/evacuation-safety-qa) to provide accurate and detailed responses to questions about building evacuation, fire safety regulations, and emergency planning.

## Model Details

- **Model Type:** Gemma-3 (4B parameters)
- **Training Method:** Fine-tuned using Parameter-Efficient Fine-Tuning (PEFT) with Low-Rank Adaptation (LoRA)
- **Training Library:** [Unsloth](https://github.com/unslothai/unsloth)
- **Context Length:** 2048 tokens
- **Training Date:** June 2025
- **Languages:** English
- **License:** [CC BY-NC-SA 4.0](https://creativecommons.org/licenses/by-nc-sa/4.0/)
- **Quantization:** Available in Q8_0 GGUF format for efficient inference

## Intended Use

This model is designed to:

1. Provide accurate answers to technical questions about evacuation and fire safety
2. Support emergency planning professionals in decision-making
3. Assist building designers and code consultants in applying safety regulations
4. Educate stakeholders about fire safety requirements and best practices

## Training Details

The model was fine-tuned using the Unsloth library with the following configuration:

- **Base Model:** Gemma-3-4B-IT (Instruction-tuned version of Gemma 3)
- **Training Method:** LoRA (Low-Rank Adaptation)
- **LoRA Configuration:**
  - Rank (r): 16
  - Alpha: 16
  - Dropout: 0.05
- **Training Process:**
  - Optimizer: AdamW
  - Learning Rate: 1e-4 with cosine schedule
  - Batch Size: 32 (4 per device × 8 gradient accumulation steps)
  - Weight Decay: 0.01
  - Loss Function: Trained on responses only (masked loss on user prompts)

## Performance and Evaluation

The model demonstrates significant improvements over the base model in domain-specific knowledge about evacuation and fire safety. Key performance metrics include:

- **ROUGE-L F1:** 0.72
- **BERTScore F1:** 0.89
- **Domain-specific accuracy:** 
  - Source citation accuracy: 83%
  - Numerical value accuracy: 91%
  - Regulatory compliance: 87%

Performance across different question categories:

| Category | ROUGE-L | BERTScore F1 | Accuracy |
|----------|---------|-------------|----------|
| Occupant Load | 0.74 | 0.91 | 93% |
| Egress | 0.73 | 0.90 | 89% |
| Fire Protection | 0.71 | 0.88 | 85% |
| Accessibility | 0.68 | 0.85 | 82% |
| Emergency Planning | 0.72 | 0.89 | 84% |

## Limitations

- The model's knowledge is limited to regulations and standards covered in the training dataset
- Responses may not reflect the most recent code changes after the knowledge cutoff
- Regional variations in building codes are not fully covered
- The model should not be used as a substitute for professional engineering judgment or official code interpretation

## Usage

### Inference with llama.cpp

This model is available in GGUF format for efficient local inference with [llama.cpp](https://github.com/ggerganov/llama.cpp):

```bash
# Download the model file
# Run with llama.cpp
./main -m gemma-3-evacuation.Q8_0.gguf -n 512 --repeat_penalty 1.1 --color -i -r "USER: " -f prompts/chat-with-gemma-3.txt
```

## Acknowledgements

- Google for the Gemma 3 base model
- Unsloth team for their efficient fine-tuning library
- NFPA, IBC, and other authoritative sources whose content informed the training dataset

## Citation

If you use this model in your research or applications, please cite:

```bibtex
@misc{amir_rafe_2025,
  author       = { Amir Rafe },
  title        = { gemma-3-evacuation (Revision f6f6773) },
  year         = 2025,
  url          = { https://huggingface.co/pozapas/gemma-3-evacuation },
  doi          = { 10.57967/hf/5794 },
  publisher    = { Hugging Face }
}
```

And the original dataset:

```bibtex
@misc{amir_rafe_2025,
  author       = { Amir Rafe },
  title        = { evacuation-safety-qa (Revision 1b09761) },
  year         = 2025,
  url          = { https://huggingface.co/datasets/pozapas/evacuation-safety-qa },
  doi          = { 10.57967/hf/5599 },
  publisher    = { Hugging Face }
}
```

## Contact

For questions or inquiries about this model, please contact Amir Rafe (amir.rafe@usu.edu)