NVIDIA TAO model accuracy


I tried to train NVIDIA TAO model on my two class object detection model. Here’s a link to the project: mouse vs cup - Dashboard - Edge Impulse

The accuracy after fine tuning any model is pretty low. The best accuracy I could achieve is 49%(precision score mentioned on the training page after training). Am I doing something wrong? Is the model not pre-trained on any dataset? How can I increase the accuracy here?


Hi @karkapur,

I chatted with our ML team, and it seems there is an issue with pixel scaling that should be fixed soon.

@shawn_edgeimpulse got it!

Can I be notified when the error is fixed?

Hi @shawn_edgeimpulse

Any update on this topic?

Hi @karkapur,

This should be fixed now.

Hey @shawn_edgeimpulse

Here are the results on the TAO YOLOv4 for the mouse vs cup(438 samples in total). Are they not enough?

Hi @karkapur,

With such a low validation score, it probably means you need to train longer. Object detection models can be notorious on how many training cycles they require. Maybe try 500 epochs and see if that helps.

Hey @shawn_edgeimpulse

I tried training it for 400 epochs before but I noticed that the accuracy dropped even more. This shouldn’t happen because the platform chooses the best weights based on the best validation set accuracy, right?

Here’s validation score for 500 epochs. Same settings as before:

Perhaps a tutorial would be useful…