Nimbus Coffee Assistant (3B)
A fine-tuned Qwen 2.5 3B model trained to answer customer support questions for Nimbus Coffee Roasters with high accuracy.
Model Details
- Base Model: Qwen/Qwen2.5-3B
- Fine-tuning Method: LoRA
- Dataset: 80 Q&A pairs covering products, pricing, shipping, and policies
- Epochs: 25
- Final Loss: 0.04
- Trainable Params: 1.8M (0.06% of total)
Training Progression
| Model | Dataset | Epochs | Final Loss |
|---|---|---|---|
| 0.5B | 20 examples | 5 | 1.32 |
| 1.5B | 50 examples | 15 | 0.24 |
| 3B (this model) | 80 examples | 25 | 0.04 |
Results
This model achieves exact match accuracy on domain-specific test questions. Before fine-tuning, the base model gave generic or incorrect answers. After training, it correctly answers questions about:
- Products and pricing
- Shipping policies
- Cafe hours
- Refund policies
- Sourcing and roasting details
Intended Use
This model serves as the primary showcase of fine-tuning capability. It demonstrates that LoRA fine-tuning on a small curated dataset can produce highly accurate domain-specific responses.
Limitations
- Trained on a small dataset (80 examples)
- May not handle out-of-scope questions well
- Designed as a proof of concept, not production use
Deployment
A smaller 0.5B variant is deployed live for low-latency inference. This 3B model is hosted as the reference implementation.
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support