What is the impact of the optimizer's hyperparameters on the fine-tuning process?

We investigate generalization properties of fine-tuning to understand the problem of overfitting, which often happens in practice. Jan 25, 2024 ... Learn Machine Learning. Welcome to r/learnmachinelearning - a community of learners and educators passionate about machine learning! This is ... Jul 3, 2023 ... Proposed CNN Based Deep Learning Approach for House Number Detection with Spatial Location in Real-Time Experimental Evaluations Dec 5, 2023 ... 1. Hyperparameter Tuning. This involves adjusting the model's parameters to improve performance. · 2. Transfer Learning. Leveraging pre-trained ... Nov 7, 2023 ... When fine-tuning, it's common to adjust the deeper layers of the model while keeping the initial layers fixed. The rationale is that the initial ... 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. Dec 4, 2024 ... Ahmet Sarigün: CompassDock: Comprehensive Accurate Assessment Approach for Deep Learning-Based Molecular Docking in Inference and Fine-Tuning. Jan 24, 2022 ... Create training data · With your imagery selected in the Contents pane, go to the Imagery tab on the top ribbon and click Classification Tools > ... Jun 26, 2024 ... PDF | Tasks like SAR ship classification suffer in deep learning due to data scarcity and class imbalance. To overcome these challenges, ... After pre-training the network, we use the spike-based gradient descent BP algorithm to fine-tune the synaptic weights end-to-end in a manner that minimizes ...