finomhangolásban
Finomhangolásban refers to the process of fine-tuning in the context of machine learning models, particularly large language models. It involves taking a pre-trained model, which has already learned general language patterns from a massive dataset, and further training it on a smaller, more specific dataset. This specialized training aims to adapt the model's behavior and knowledge to a particular task, domain, or style.
The core idea behind finomhangolásban is to leverage the broad understanding of language acquired during pre-training
Common applications of finomhangolásban include sentiment analysis, text summarization, question answering, and translation for specific industries