SSD based on ResNet-101 doesn't improve over SSD-VGGNet

I am training a SSD model for detecting mobile cranes. The training dataset contains 1,000 images and test set over 400 images. About 200 epochs gave mAP 83%, but my target is 90%. So I trained SSD-ResNet-101 and it gave less accuracy.

I assume that it is because ResNet-101 is too deep for the size of my dataset. I consider using ResNet-50 and Inception. But I don't have time to experiment all the models with different parameter settings.

Is there anyone who has experience in this direction? Any advice is welcome.

Thanks in advance.