Hello! I am working on Neural Network for a regression problem. I have 4 inputs and 7 outputs. But it doesn’t learn at all anything. I am applying minmax normalization for input and output (0 to 1). Optimizer: Adam, learning rate = 0.0005. Do you have any suggestions, please? Thanks in advance!

This is the architecture I am using: class Net(nn.Module):

def **init**(self, n_in, n_out):

super(Net, self).**init**()

self.fc1 = nn.Linear(n_in, 32)

self.fc2 = nn.Linear(32, 64)

self.fc3 = nn.Linear(64, 128)

self.fc4 = nn.Linear(128, 64)

self.fc5 = nn.Linear(64, 32)

self.fc6 = nn.Linear(32, n_out)

```
def forward(self, x):
x = F.relu(self.fc1(x))
x = F.relu(self.fc2(x))
x = F.relu(self.fc3(x))
x = F.relu(self.fc4(x))
x = F.relu(self.fc5(x))
x = self.fc6(x)
return x
```