Hello!
I am trying to do the validation on my dataset to obtain optimal number of channels in my neural network. I have the following code:
def train_during_validation():
for epoch in range (1, 201):
model.train()
optimizer.zero_grad()
out = model(data.x, data.edge_index)
loss = criterion(out[data.val_mask], data.y[data.val_mask])
loss.backward()
optimizer.step()
return loss
def validation():
loss_val = np.zeros(50, dtype = float)
model = GCN(hidden_channels = 1)
loss_val = train_during_validation()
print(loss_val)
validation()
In the code above I train previously defined model with 16 channels and I obtain a loss of 0.33. But as soon as I start doing validation on hidden_channel (see code below), my loss does not go down (it remains on 1.95). I do not understand why. Can somebody explain?
def train_during_validation(model):
print(f'Model:{model}')
for epoch in range (1, 201):
model.train()
optimizer.zero_grad()
out = model(data.x, data.edge_index)
loss = criterion(out[data.val_mask], data.y[data.val_mask])
loss.backward()
optimizer.step()
return loss
def validation():
loss_val = np.zeros(50, dtype = float)
model = GCN(hidden_channels = 1)
for i in range (50):
model = GCN(hidden_channels = i)
#print(model)
loss_val[i] = train_during_validation(model)
print(loss_val[i])
validation()
Thank you in advance!
Best regards