The evolution of Large Language Models (LLMs) toward multilingual capabilities reflects the urgent need to accommodate linguistic diversity, moving beyond predominantly English datasets.
The fine-tuned GPT-3.5 model's performance was evaluated using M-IoU scores across multiple random seeds, demonstrating its efficacy in identifying praise in tutor responses with limited training data.