Hi and thank you so much for answering so quickly!
The data set I used was photos of my two family members. Each person had 100 training samples, 40 validation samples, and 30 test samples.
The current training situation is as follows:
-Training accuracy can reach: 90% +
-Highest verification accuracy: 67%
-Highest test accuracy: 74%
I use the code provided below and then use the inception model and feature extraction
https://pytorch.apachecn.org/docs/1.0/finetuning_torchvision_models_tutorial.html 8
The training hyperparameters are as follows:
Model: inception
SGD: lr = 0.001, momentum = 0.9
LR Decay: update step = 7, gamma = 0.1
Epoch: 200
My problem is, what aspects can be optimized to improve the generalization ability of the model, and I hope the test accuracy can reach 90%