Hi everyone,
I’m a bit new to the world of object detection and I’m wondering if there is a way to see if my model is over- or underfitting during training? Similar to how you would do it for a classification model.
I’m following the tutorial on finetuning a detection model: 08. Finetune a pretrained detection model — gluoncv 0.11.0 documentation
But I’m slightly confused on how the training and validation splits are used during the training of the model.
Both the cross entropy loss and the smooth l1 loss is printed during training, but is that for the training data or the validation data?
Is there a conventional/standard way to visualize overfitting for detection models?
Thanks!