If you are interested in learning more about artificial intelligence applications and development you may be interested in the NVIDIA TAO Transfer Learning Toolkit (TLT) a core component of the NVIDIA Train, Adapt, and Optimize (TAO) platform. TLT comes with a set of ready-to-use Jupyter notebooks, Python scripts, and configuration specifications with default parameter values that enable you to start training and fine-tuning your datasets quickly and easily, following the zero-coding paradigm tofast-track AI development.
“The approach taken focuses on minimizing both development time and tuning time while ensuring that the accuracy is applicable for a production environment. TLT was used in combination with the standard configuration files shipped with the example notebooks. The setup, training, and tuning was done in under 8 hours.
We conducted parameter sweeps regarding network depth and the number of training epochs. We observed that changing the learning rate from its default did not improve the results, so we did not investigate this further and left it at the default. The best results were obtained with a pretrained ResNet-18 model obtained from the NGC catalog after 30 epochs of training with a learning rate of 0.006.”
To learn more about the NVIDIA TAO Transfer Learning Toolkit jump over to the official NVIDIA developer website by following the link below.
Source : NVIDIA
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