Kick off Nova customization experiments using Nova Forge SDK

This article demonstrates how to use the Nova Forge SDK to customize Amazon Nova models through a Stack Overflow question classification case study, achieving significant performance improvements through iterative fine-tuning.

• Nova Forge SDK simplifies LLM customization by handling infrastructure, dependency management, and recipe configuration automatically
• Baseline model achieved only 13% accuracy on 3-class classification task, establishing clear improvement opportunity
• Supervised Fine-Tuning (SFT) improved exact-match accuracy to 77.2%, teaching format requirements and domain patterns
• Reinforcement Fine-Tuning (RFT) with binary reward function (+1 correct, -1 incorrect) further improved accuracy to 78.8%
• Combined SFT+RFT approach achieved 80.6% quasi-exact-match accuracy, a 65% improvement over baseline
• SDK supports deployment to Amazon Bedrock (on-demand or provisioned) or Amazon SageMaker inference endpoints
• Built-in data validation, log monitoring, and job serialization streamline the entire customization workflow

The Nova Forge SDK makes enterprise LLM customization accessible by automating infrastructure provisioning, training orchestration, and deployment, enabling organizations to build domain-specialized models without extensive technical expertise.