Are Fine Tuning & Pre-Training referring to the similar process?
Though the process may appear similar, there exists a fundamental distinction in how the model is trained and the type of dataset utilized. Fine-tuning predominantly focuses on training the model within a confined context using either labeled or unstructured data within that context. As a result, it demands less computational power. On the other hand, pre-training necessitates an extensive dataset with the objective of creating an entirely foundational model and thus it requires massive usage of computational power during the training.
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