Fine-tuning pre-trained language models is often desirable instead of training a new model from scratch due to the computational resources required to pre-train a model from scratch. Fine-tuning allows for faster and more efficient training, utilizing pre-learned representations that can be optimized for a specific task and achieve state-of-the-art results with less data.