def evaluate(model):

    model.eval()
    correct, total = 0, 0
    
    with torch.no_grad():
        for data in testloader:
            inputs, labels = data
            outputs = model(inputs)
            _, predicted = torch.max(outputs.data, 1)
            total += labels.size(0)
            correct += (predicted == labels).sum().item()
            
    return correct / total