How can you manage the different versions of fine-tuned models?

In this section, we will introduce a common technique in transfer learning: fine-tuning. As shown in Fig. 14.2.1, fine-tuning consists of the following four ... Jul 17, 2023 ... As a machine learning practitioner, you might often find yourself in a situation where you're fine-tuning a pre-trained model for your specific ... This FITML workshop aims to contribute to the recent radical paradigm shift for fine-tuning in modern machine learning, theoretically, computationally, and ... Feb 28, 2025 ... For the learning rate during fine-tuning, we often use a value up to 10 times smaller than usual. As a result, our model will try to adapt ... Deep neural networks have been highly successful across a multitude of domains, from computer vision [1, 2] and natural language processing [3, 4], to game ... Transfer learning, which aims to transfer knowledge from source tasks to a target task, is an effective solution to this problem. Fine-tuning is a popular ... Fine-Tuning in Modern Machine Learning: Principles and Scalability. Fanghui Liu, Grigorios Chrysos, Beidi Chen, Rebekka Burkholz, Saleh Soltan, Angeliki ... Deep learning practice is increasingly driven by powerful foundation models (FM), pre-trained at scale and then fine-tuned for specific tasks of interest. Oct 8, 2024 ... Advancements in Road Lane Mapping: Comparative Fine-Tuning Analysis of Deep Learning-based Semantic Segmentation Methods Using Aerial Imagery. Dec 17, 2024 ... Qualitative review clearly showed its insufficiency; prone to detect patients' faces as symmetric, and unable to detect closure of the eyes.