@eqy, I tried again with random numbers like 3 and 454545 and also tried 79077, I still get result for the loss, the first one is like 11.3 and the rest is 0, and sometimes when I run it again the whole result becomes 0 for the losses
EDIT: Originally in the code for data loading the part where I load data it should be like this
def load_dataset(data_path):
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 # Split into training (70% and testing (30%) datasets)
    train_size = int(0.7 * len(full_dataset))
    test_size = len(full_dataset) - train_size

# use torch.utils.data.random_split for training/test split
    train_dataset, test_dataset = torch.utils.data.random_split(full_dataset, [train_size, test_size])
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where I have changed it to this because I have the images of the test and train data in their own separate folders
def load_dataset(data_path):
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 # Split into training (70% and testing (30%) datasets)
    train_dataset = full_dataset
    test_dataset = full_dataset_test

# use torch.utils.data.random_split for training/test split
# train_dataset, test_dataset = torch.utils.data.random_split(full_dataset, [train_size, test_size])
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EDIT 2: I tried changing the code back to the original form but now the values are way incorrect
Training on cpu
Epoch: 1
	Training batch 1 Loss: 3191074.500000
	Training batch 2 Loss: 46193868800.000000
	Training batch 3 Loss: 360812150784.000000
	Training batch 4 Loss: 154258833408.000000
	Training batch 5 Loss: 3475833356288.000000

EDIT 3: I figured why I was getting the initial value when training was 10 (model = LightCNN_9Layers(num_classes=len(classes)).to(device) classes was 10)) when I thought I had it 79077. I changed it to 79077, and now I got the initial value correct, but I am now still getting the exact same issue for values after the first loss, always 0