Benchmarking Low-Rank Adaptation for Enterprise LLM Fine-Tuning

research-article
Received: Jun 18, 2025
Published: Aug 2, 2025
Authors: Oliver Scott ✉ Aisha Khan

Abstract

We evaluate low-rank adaptation (LoRA) versus full fine-tuning across policy, customer support, and retrieval tasks. On three internal corpora (28M tokens), LoRA achieved within 1.5 BLEU/2 ROUGE of full FT while cutting GPU-hours by 73%.

⬇ Download

Cite this article

Scott, O. & Khan, A. (2025). Benchmarking Low-Rank Adaptation for Enterprise LLM Fine-Tuning. Research Explorations in Global Knowledge & Technology (REGKT), 3 (4). Retrieved from https://regkt.com/article.php?id=111&slug=benchmarking-lora-for-enterprise-llm-fine-tuning

Premium Membership Required

You need a premium account to view or download this article.

Become Premium