# When should I stop the object detection model training while mAP are not stable?

I am re-training the SSD MobileNet with 900 images from the Berkeley Deep Drive dataset, and eval towards 100 images from that dataset.

The problem is that after about 24 hours of training, the totalloss seems unable to go below 2.0:

And the corresponding mAP score is quite unstable:

In fact, I have actually tried to train for about 48 hours, and the TotoalLoss just cannot go below 2.0, something ranging from 2.5~3.0. And during that time, mAP is even lower..

So here is my question, given my situation (I really don't need any "high-precision" model, as you can see, I pick 900 images for training and would like to simply do a PoC model training/predication and that's it), when should I stop the training and obtain a reasonably performed model?