You should be able to get the same results between runs, at least I’m pretty sure of that. What did you set seed on? I tried with
import torch
import torchvision.models as models
seed=42
torch.manual_seed(seed)
resnet18 = models.resnet18(pretrained=False)
x = torch.randn((1, 3, 224, 224))
print(resnet18(x)[0:10])

And I seem to get same results on different runs. If you are running on CUDA then you should add
torch.cuda.manual_seed_all(seed)
torch.backends.cudnn.deterministic = True
torch.backends.cudnn.benchmark = False

When training I think it is also important to send seed to DataLoader. Perhaps you could share some small code that give you different results?