pallgeuer/model_testbed repository overview

Container for running the Deep Learning Model Testbed⁠ GitHub repository, which provides flexible and user-extensible training scripts for computer vision (e.g. image classification) tasks on standard benchmarks. Designed as a stable and reproducible testbed, it allows rapid experimentation with different model architectures, datasets, optimizers, learning rate schedules, gradient accumulation strategies, and other training strategies and hyperparameters. The goal is to streamline the process of testing new training ideas and techniques in a controlled environment, enabling fair comparisons and insightful evaluations of their impact on model performance. It includes seamless integration with Weights & Biases (wandb)⁠ for powerful experiment tracking, live monitoring, and in-depth analysis of training runs and results.