I’m trying to load data from my dataset to the DataLoader class, but when I do, the values explode. None of the numbers in my CSV are anywhere near this large, and as I train, the values become even greater (around 8*e19). How can I avoid this?
Dataset Class:
class myData(Dataset):
    def __init__(self, 
                 path,
                 train_size: float = 0.8,
                 val_size: float = 0.1,
                 test_size: float = 0.1):
        self.dataframe = pd.read_csv(path)

        self.train_dataset = self.dataframe[0:int(len(self.dataframe) * train_size)].values
        self.test_dataset = self.dataframe[int(len(self.dataframe) * train_size):
                                           int(len(self.dataframe) * (train_size + val_size))].values
        self.val_dataset = self.dataframe[int(len(self.dataframe) * (train_size + val_size)):
                                          int(len(self.dataframe) * (train_size + val_size + test_size))].values

    def get_train_dataset(self):
        return self.train_dataset

    def get_test_dataset(self):
        return self.test_dataset

    def get_val_dataset(self):
        return self.val_dataset

    def __len__(self):
        return len(self.dataframe)

    def __getitem__(self, idx):
        return self.dataframe[idx]

DataLoader:
from torch.utils.data import DataLoader
....
train_loader = DataLoader(train_dataset,
                          batch_size=batch_size,
                          shuffle=False,
                          num_workers=0)

The input tensor for training:
tensor([[1.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 1.4504e+02, 4.0524e+02,
         4.0524e+02],
        [2.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 1.4504e+02, 4.0524e+02,
         4.0524e+02],
        [3.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 1.4504e+02, 4.0524e+02,
         4.0524e+02],
        ...,
        [1.4080e+03, 0.0000e+00, 0.0000e+00,  ..., 1.4504e+02, 3.9697e+02,
         4.0524e+02],
        [1.4090e+03, 0.0000e+00, 0.0000e+00,  ..., 1.4504e+02, 3.9697e+02,
         4.0524e+02],
        [1.4100e+03, 0.0000e+00, 0.0000e+00,  ..., 1.4504e+02, 3.9697e+02,
         4.0524e+02]], device='cuda:0', dtype=torch.float64)