Domain Fine-Tuning with Synthetic Training Data

Healthcare & Life Sciences: General-purpose models missed domain terminology, and there wasn't enough labelled data to fine-tune one. Task Accuracy +27%,…

Client: Healthcare Documentation Company. Industry: Healthcare & Life Sciences.

Challenge: General-purpose models missed domain terminology, and there wasn't enough labelled data to fine-tune one.

Solution: Generated and human-reviewed a synthetic instruction dataset from the client's guidelines, fine-tuned a small open model with LoRA, and gated every release with an evaluation harness against a frozen test set.

Technologies: LoRA / QLoRA, Synthetic Data Generation, Evaluation Harness, Hugging Face.

• Task Accuracy: +27%
• Training Examples: 40K+
• Model Size: 8B
• Serving Cost: -70%

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