informationAboutTraining

Summary

Describes relevant information about different steps of the training process.

A detailed explanation of the training process, including the specific techniques, algorithms, and methods employed.

Examples include:

training data used to train the AI model, along with any relevant details about its source, quality, and pre-processing steps;
specific training algorithms employed, including stochastic gradient descent, backpropagation, and reinforcement learning.
specific training techniques used to improve the performance or accuracy of the AI model, such as transfer learning, fine-tuning, or active learning; and
any evaluation metrics used to assess the performance of the AI model during the training process, including accuracy, precision, recall, and F1 score.

https://spdx.org/rdf/3.0.0/terms/AI/informationAboutTraining