Very HIgh MSE Loss

Epoch [95/100], Loss: 15795335555002138624.0000
Epoch [96/100], Loss: 15947571735960748032.0000
Epoch [97/100], Loss: 22230783709444833280.0000
Epoch [98/100], Loss: 24243408957763223552.0000
Epoch [99/100], Loss: 20029352523428003840.0000
Epoch [100/100], Loss: 26956084463393570816.0000
Mean Squared Error: 20261864048330539008.0000

I trained a simple neural network with 3 linear layers, relu and a dropout and Adam optimizer
class Net(nn.Module):
def __init__(self):
super(Net, self).__init__()
self.fc1 = Linear(12, 128)
self.fc2 = Linear(128, 64)
self.fc3 = Linear(64, 32)
self.fc4 = Linear(32, 1)
self.dropout = nn.Dropout(0.2)

def forward(self, x):
x = torch.relu(self.fc1(x))
x = self.dropout(x)
x = torch.relu(self.fc2(x))
x = self.dropout(x)
x = torch.relu(self.fc3(x))
x = self.dropout(x)
x = self.fc4(x)
return x

The error seems to be very high.

Something is unique about the dataset.
A custom model tailored for this dataset is required