diff --git a/CMakeLists.txt b/CMakeLists.txt
index 4bf691c..159f426 100644
--- a/CMakeLists.txt
+++ b/CMakeLists.txt
@@ -1,5 +1,5 @@
 cmake_minimum_required(VERSION 3.25)
-project(COSC-4P80-Assignment-2 VERSION 0.0.10)
+project(COSC-4P80-Assignment-2 VERSION 0.0.11)
 
 option(ENABLE_ADDRSAN "Enable the address sanitizer" OFF)
 option(ENABLE_UBSAN "Enable the ub sanitizer" OFF)
diff --git a/include/assign2/layer.h b/include/assign2/layer.h
index 2165b69..07596dd 100644
--- a/include/assign2/layer.h
+++ b/include/assign2/layer.h
@@ -57,19 +57,19 @@ namespace assign2
             {
                 // delta for weights
                 error = act->derivative(z) * next_error;
-                db = learn_rate * error;
+                db = -learn_rate * error;
                 BLT_ASSERT(previous_outputs.size() == dw.size());
                 for (auto [prev_out, d_weight] : blt::zip(previous_outputs, dw))
                 {
                     // dw
-                    d_weight = -learn_rate * prev_out * error;
+                    d_weight = learn_rate * prev_out * error;
                 }
             }
             
             void update(float omega, bool reset)
             {
                 // if omega is zero we are not using momentum.
-                if (reset || omega == 0)
+                if (omega == 0)
                 {
 //                    BLT_TRACE("Momentum Reset");
 //                    for (auto& v : momentum)
@@ -165,7 +165,7 @@ namespace assign2
                         [this, &prev_layer_output, &total_error, &total_derivative](const std::vector<Scalar>& expected) {
                             for (auto [i, n] : blt::enumerate(neurons))
                             {
-                                auto d = outputs[i] - expected[i];
+                                auto d = expected[i] - outputs[i];
 //                                if (outputs[0] > 0.3 && outputs[1] > 0.3)
 //                                    d *= 10 * (outputs[0] + outputs[1]);
                                 auto d2 = 0.5f * (d * d);
diff --git a/include/assign2/network.h b/include/assign2/network.h
index a43865c..0b2af84 100644
--- a/include/assign2/network.h
+++ b/include/assign2/network.h
@@ -98,7 +98,7 @@ namespace assign2
                     BLT_ASSERT(out.size() == expected.size());
                     for (auto [o, e] : blt::in_pairs(out, expected))
                     {
-                        auto d_error = o - e;
+                        auto d_error = e - o;
                         
                         auto error = 0.5f * (d_error * d_error);
                         
diff --git a/src/main.cpp b/src/main.cpp
index 4c10455..65eba44 100644
--- a/src/main.cpp
+++ b/src/main.cpp
@@ -34,8 +34,8 @@ network_t create_network(blt::i32 input, blt::i32 hidden)
     const auto inner_mul = 0.25;
     auto layer1 = std::make_unique<layer_t>(input, hidden * mul, &sig, randomizer, empty);
     auto layer2 = std::make_unique<layer_t>(hidden * mul, hidden * inner_mul, &sig, randomizer, empty);
-//    auto layer3 = std::make_unique<layer_t>(hidden * mul, hidden * mul, &sig, randomizer, empty);
-//    auto layer4 = std::make_unique<layer_t>(hidden * mul, hidden * mul, &sig, randomizer, empty);
+//    auto layer3 = std::make_unique<layer_t>(hidden * inner_mul, hidden * inner_mul, &sig, randomizer, empty);
+//    auto layer4 = std::make_unique<layer_t>(hidden * inner_mul, hidden * inner_mul, &sig, randomizer, empty);
     auto layer_output = std::make_unique<layer_t>(hidden * inner_mul, 2, &sig, randomizer, empty);
     
     std::vector<std::unique_ptr<layer_t>> vec;
@@ -215,7 +215,7 @@ void init(const blt::gfx::window_data&)
                 
                 auto error = errors_over_time.back();
 //                error = std::sqrt(error * error + error + 0.01f);
-                error = std::max(0.0f, std::min(1.0f, error));
+//                error = std::max(0.0f, std::min(1.0f, error));
                 learn_rate = error * init_learn;
                 omega = error * init_momentum;
                 
@@ -605,7 +605,7 @@ int main(int argc, const char** argv)
         int input = static_cast<int>(f.data_points.begin()->bins.size());
         int hidden = input;
         
-        if (input != 32)
+        if (input != 64)
             continue;
         
         BLT_INFO("-----------------");
@@ -616,8 +616,8 @@ int main(int argc, const char** argv)
         network_t network = create_network(input, hidden);
         
         float o = 0.00001;
-        network.with_momentum(&o);
-        for (blt::size_t i = 0; i < 300; i++)
+//        network.with_momentum(&o);
+        for (blt::size_t i = 0; i < 10000; i++)
             network.train_epoch(f, 1);
         
         BLT_INFO("Test Cases:");