So I trained CNN model for people detection on caltech-pedestrian dataset: Then I was curious and evaluated the model in every 1000th iteration on Evaluation toolbox(I guarantee, there is no bug in evaluation).
However, plot of the performance does not look so good. The miss rate spikes between 20K(20,000) and 30K iterations.
I am confused what does that mean. I mean usually we would expect the miss rate to decrease as we train the model more.
I am using yolo object detection network https://github.com/AlexeyAB/darknet/blob/master/cfg/tiny-yolo-voc.cfg
So learning options are the same as https://github.com/AlexeyAB/darknet/blob/master/src