diff --git a/main.c b/main.c
index d35d189..434c38b 100644
--- a/main.c
+++ b/main.c
@@ -7,18 +7,18 @@ int main() {
     Image** images = import_images("../data/train-images.idx3-ubyte", "../data/train-labels.idx1-ubyte", NULL, 60000);
 //    img_visualize(images[0]);
 
-    Neural_Network* nn = new_network(28*28, 32, 3, 10, 0.01);
-    randomize_network(nn, 1);
+    Neural_Network* nn = new_network(28*28, 100, 5, 10, 0.01);
+    randomize_network(nn, 10);
     //    save_network(nn);
     //    Neural_Network* nn = load_network("../networks/test1.txt");
 
-    for (int i = 0; i < 20000; ++i) {
+    for (int i = 0; i < 60000; ++i) {
         train_network(nn, images[i], images[i]->label);
     }
 
 //    train_network(nn, images[0], images[0]->label);
 //    train_network(nn, images[0], images[0]->label);
 
-    printf("%lf\n", measure_network_accuracy(nn, images, 1000));
+    printf("%lf\n", measure_network_accuracy(nn, images, 10000));
 
 }
\ No newline at end of file
diff --git a/neuronal_network.c b/neuronal_network.c
index b0285ff..fdcd032 100644
--- a/neuronal_network.c
+++ b/neuronal_network.c
@@ -210,7 +210,7 @@ void train_network(Neural_Network* network, Image *image, int label) {
     delta = calculate_delta_hidden(previous_delta, network->weights[1], output[0]);
     delta_weights[0] = calculate_weights_delta(image_data, delta);
 
-    for (int i = 0; i < network->hidden_size ; ++i) {
+    for (int i = 0; i < network->hidden_amount + 1; ++i) {
         apply_weights(network, delta_weights[i], i);
     }
 
@@ -264,7 +264,7 @@ Matrix* calculate_delta_hidden(Matrix* next_layer_delta, Matrix* weights, Matrix
 
 void apply_weights(Neural_Network* network, Matrix* delta_weights_matrix, int index) {
 
-    if(index > network->hidden_amount + 1 || index < 0) {
+    if(index > network->hidden_amount || index < 0) {
         printf("ERROR: Index out of range! (apply_weights)");
         exit(1);
     }
@@ -274,8 +274,8 @@ void apply_weights(Neural_Network* network, Matrix* delta_weights_matrix, int in
         exit(1);
     }
 
-    for (int i = 0; i < delta_weights_matrix->rows; ++i) {
-        for (int j = 0; j < delta_weights_matrix->columns; ++j) {
+    for (int i = 0; i < delta_weights_matrix->rows; i++) {
+        for (int j = 0; j < delta_weights_matrix->columns; j++) {
             network->weights[index]->numbers[i][j] += delta_weights_matrix->numbers[i][j];
         }
     }