What are the best practices for managing and tracking fine-tuning experiments?

Oct 8, 2024 ... Advancements in Road Lane Mapping: Comparative Fine-Tuning Analysis of Deep Learning-based Semantic Segmentation Methods Using Aerial Imagery. May 14, 2020 ... This paper utilizes transfer learning and fine tuning deep convolutional neural networks (CNN) to improve the accuracy of recognizing 32 hand gestures from the ... 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 ... 1. Robot Workflow: Machine Learning Extractor Trainer activity · 2. Document Manager: Schedule Export feature · 3. AI Center: Scheduled Auto-retraining Pipeline. Chong Zhang 1, (张翀) Student Member, CCF,; Hong-Zhi Wang 1, (王宏志) Senior Member, IEEE, Member, CCF,; Hong-Wei Liu 1, , (刘宏伟) Member, CCF, ... The comparative analysis attempts to find which approach is more efficient to be used for fine-tuning of pretrained BERT family transformer to deal with a ... Nov 21, 2017 ... Fine-tuning is a way of applying or utilizing transfer learning. Specifically, fine-tuning is a process that takes a model that has already been ... Jun 26, 2024 ... PDF | Tasks like SAR ship classification suffer in deep learning due to data scarcity and class imbalance. To overcome these challenges, ... 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 ... Mar 15, 2024 ... Fine-tuning in machine learning is the process of adapting a pre-trained model for specific tasks or use cases.