Hi there I was trying to use nn.Sequential module in a simple regression problem, just a line. The thing is that I print MSELoss every iteration and it is trying to converge at 1, intead of the values I am wondering.

Here is the code:

```
NN = nn.Sequential(
nn.Linear(1,3),
nn.Sigmoid(),
nn.Linear(3,4),
nn.Sigmoid(),
nn.Linear(4,7),
nn.Sigmoid(),
nn.Linear(7,1),
nn.Sigmoid()
)
criterion = nn.MSELoss()
optimizer = optim.Adam(NN.parameters(), lr=0.01)
X = torch.rand(200,1)
y = 2*X + 3
print(X.shape,y.shape)
for i in range(1000):
NN.train()
optimizer.zero_grad()
out = NN(X)
#print(out,y)
loss = criterion(y,out)
loss.backward()
optimizer.step()
with torch.no_grad():
print ("#" + str(i) + " Loss: " + str(loss.item()))
```

If I try this to check the results:

```
newX = []
newY = []
for i in range(5):
r = random.uniform(0, 1)
newX.append(r)
newY.append(NN(torch.tensor([r])).item())
```

I get `[0.9996629953384399, 0.9996600151062012, 0.9996635913848877, 0.9996637105941772, 0.9996615648269653]`

.

I have tryed lot of things changing every on the network but don’t know what is happening.