Training Details
Upon completion of model training, you can click on the model in the models table to access the details view. Here, you’ll find comprehensive information about the model’s training configuration and evaluation metrics:
Training Configuration
The training configuration section outlines the parameters and settings used during model training. This includes details such as the dataset used, training epochs, batch size, learning rate, and model architecture.Evaluation Metrics
Classification Accuracy
This metric measures the proportion of correctly classified images inimage classification models
. It indicates the model’s overall accuracy in predicting the correct class label for input images.
Mean Average Precision (mAP)
mAP is a commonly used metric forobject detection models
. It evaluates the precision-recall curve across different object categories, providing a comprehensive measure of the model’s detection performance.