An experimental setup is essential for systematically evaluating the performance of a multimodal AI model. This setup outlines the procedures, tools, datasets, and configurations used to train and test the model, ensuring reproducibility and reliability of the results. This section provides a detailed overview of the experimental setup, including the environment, datasets, model configurations, and evaluation protocols.
The choice of hardware significantly impacts the training and evaluation process. High-performance GPUs are typically required for handling large-scale multimodal datasets and complex models.
The software environment includes operating systems, libraries, frameworks, and tools required for the experiment.
Selecting and preparing the appropriate datasets is crucial for training and evaluating the multimodal AI model.