What is the primary output of a Train Run in the AI Center?

The primary output of a Train Run in the AI Center is a new model version. During the training process, the system utilizes the provided training data to develop and refine a machine learning model. Once the training run is complete, it generates an updated model version that captures the learned patterns and knowledge from the dataset.

This model version serves as a crucial deliverable because it can be deployed for inference or integrated into applications to perform predictions based on new input data. While evaluation metrics and logs provide insights into the training process's performance and the model's effectiveness, they are secondary outputs meant for analysis and oversight rather than serving as the end product of the training run.

Data labeling results refer to the annotations made on datasets before training, which are also not outcomes of the Train Run itself. Raw input data serves as the foundation for the training but does not represent the culmination of a training process. The new model version, therefore, stands out as the main result of the training effort, emphasizing the goal of developing a functional and improved model.