I recently need to train ResNet50 and do some experiments, I know there are bunch of pretrained models on github, but I feel more interested on the training process(like how to preprocess, set the LR and so on)…
The dataset I am using is standard CIFAR100. On github, few repo claim that they can achieve top-1 error of 22%(i.e. accuracy 78%) on ResNet50.
I just simply cannot get good results by using ResNet, my best record is only 66%, I read the paper, they warm up the learning rate, which I also do…I feel ResNet is really hard to train and get good results.
So I am wondering…it’s ok if we dont’t have any pretrained model on these kinds of datasets, but is it possible that pytorch can provide some training scirpts or preprocessing scripts for us on these datasets…we can modify and train on our own.