Description:

I have been trying to build a simple linear regression model with the neural network with 4 features and one output. The loss function used is mse loss. It is returning loss as Nan. Learning rate is 1e-3.

I trying tuning the lr but I didn’t see any change in it. Would appreciate your help in the same.

Thanks in advance!

Training Loop

```
epochs=100
for epoch in range(epochs):
for inputs,targets in training_data:
y_pred=model(inputs.float())
y_pred=y_pred.squeeze(1)
#print(y_pred.shape)
#print(inputs.dtype)
#print(targets.dtype)
#print(y_pred.dtype)
y_pred=y_pred.double()
loss=mse(y_pred,targets)
loss.backward() #computing gradients
opt.step() #updating parameters
opt.zero_grad() #setting the grads back to zero
if epoch%10==0:
print(f'Epoch:{epoch}/{epochs} | Loss:{loss.item()}')
```

**Output**

```
Epoch:0/100 | Loss:nan
Epoch:10/100 | Loss:nan
Epoch:20/100 | Loss:nan
Epoch:30/100 | Loss:nan
Epoch:40/100 | Loss:nan
Epoch:50/100 | Loss:nan
Epoch:60/100 | Loss:nan
Epoch:70/100 | Loss:nan
Epoch:80/100 | Loss:nan
Epoch:90/100 | Loss:nan
```