Crossentropy loss function - What is a good performance goal?

Understanding Cross-Entropy Loss in MATLAB

The cross-entropy operation is essential for computing the cross-entropy loss between network predictions and target values in both single-label and multi-label classification tasks.

Crossentropy Function with dlarray

The crossentropy function calculates the cross-entropy loss between predictions and targets represented as dlarray data in MATLAB. Using dlarray objects simplifies handling high-dimensional data by allowing dimension labeling. You can label dimensions for spatial, time, channel, and batch as "S", "T", "C", and "B", respectively. For unspecified dimensions, use the "U" label. When using dlarray functions that operate over specific dimensions, specify the labels directly within the dlarray object or by using the DataFormat option.