I trained a faster-rcnn model on the tensorflow object detection API on a custom dataset. I found that the loss is ~2 after 3.5k steps. However, when I ran eval.py, the mAP scores are all almost 0 as shown below.
I do not understand why this is the case. However, when I look at the images at 3.5k steps, the model has captured some of the boxes as shown below
Can someone please explain why the mAP scores are close to zero, even though the model has learned to output quite a few boxes?