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How Much Data Is Enough Data? Fine-tuning Large Language Models For In-house Translation: Performance Evaluation Across Multiple Dataset Sizes

Abstract

Decoder-only LLMs have shown impressive performance in MT due to their ability to learn from extensive datasets and generate high-quality translations. However, LLMs often struggle with the nuances and style required for organisation-specific translation. In this study, we explore the effectiveness of fine-tuning Large Language Models (LLMs), particularly Llama 3 8B Instruct, leveraging translatio

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