Thank you @ptrblck for your suggestion, this is how I tried to split the validation data into two parts, and it worked, I hope it is ok.
indices = list(range(83258)) # 83258 is the total validation samples
np.random.shuffle(indices)
    
val1=indices[:41629]
val2=indices[41629:]
sampler1=SubsetRandomSampler(indices=val1)
sampler2=SubsetRandomSampler(indices=val2)

val_loader1 = torch.utils.data.DataLoader(
        datasets.ImageFolder(valdir, transform=transform),
        batch_size=32, shuffle=False,
        num_workers=args.workers, pin_memory=True, sampler=sampler1)
    
val_loader2 = torch.utils.data.DataLoader(
        datasets.ImageFolder(valdir, transform=transform),
        batch_size=32, shuffle=False,
        num_workers=args.workers, pin_memory=True, sampler=sampler2)