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.

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