How can you document the fine-tuning process and the characteristics of the resulting model?

Apr 18, 2022 ... In this article, we investigate the transfer learning of deep convolutional neural networks for the detection of maize leaf diseases. In this paper, we demonstrate that transfer learning and fine-tuning can significantly improve the accuracy of liver lesion classification, especially for small ... Aug 30, 2018 ... How a TPU works. When Google designed the TPU, we built a domain-specific architecture. That means, instead of designing a general purpose ... 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 ... Fine-tuning (deep learning) ... In deep learning, fine-tuning is an approach to transfer learning in which the parameters of a pre-trained neural network model ... One of the major challenges currently facing researchers in applying deep learning (DL) models to medical image analysis is the limited amount of annotated ... May 24, 2019 ... It integrates the huggingface library with the fastai library to fine-tune the BERT model, with an application on an old Kaggle competition. 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 ... Jun 1, 2022 ... Award Share. Community Info Section. r/deeplearning. Join. Deep Learning. 192K Members. 56 Online. Top 1% Rank by size. More posts you may like.