AIBullisharXiv – CS AI · 18h ago7/10
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How Small Can You Go? LoRA Fine-Tuning 270M-8B Models for Merchant Information Extraction in Financial Transactions
Researchers demonstrate that smaller language models (270M-8B parameters) can match or nearly match the performance of larger models for merchant information extraction in financial transactions through strategic fine-tuning techniques. The study identifies Qwen 3.5 4B as achieving 96.60% F1 score with half the parameters of the baseline LLaMA 3.1-8B model, offering significant cost and latency improvements for production deployment.