Can I train additional data on my trained model?


I am using Deepstream 4.0.1 version and tlt-v1 on Jetson Nano.

I am training using Detectnet-v2_resnet18 in tlt-v1.

The tlt-train showed that the training time increased as the number of training data increased.

It takes a lot of time when I need to learn more data from existing data.

I don’t know much about transfer-learning-toolkit…

Is there a way to shorten the training time by learning only additional data from the model that was previously trained?

Yes, you can train additional data on your model which was previously trained.
For detectnet_v2 network, TLT provides pretrained model(hdf5 file) in NGC, you can set it as the pretrained model and run training.
Also, if you already trained a tlt model, you can set it as the pretrained model and run training too.

Hi, Morganh.

Thank you so much for the kind answer.

Could you tell me the location of the manual of the information I want?

See tlt user guide. Transfer Learning Toolkit — Transfer Learning Toolkit 3.0 documentation