diff --git a/I2_NeuronalerAbsturz/Start_Mac/neuralNetworkTests.c b/I2_NeuronalerAbsturz/Start_Mac/neuralNetworkTests.c
index 1096e2b..c11aa00 100644
--- a/I2_NeuronalerAbsturz/Start_Mac/neuralNetworkTests.c
+++ b/I2_NeuronalerAbsturz/Start_Mac/neuralNetworkTests.c
@@ -55,27 +55,18 @@ static void prepareNeuralNetworkFile(const char *path, const NeuralNetwork nn)
 
         // input und output dimension schreiben
         int inputDim = nn.layers[0].weights.cols;
-        int outputDim = nn.layers[0].weights.rows;
         fwrite(&inputDim, sizeof(int), 1, file);
-        fwrite(&outputDim, sizeof(int), 1, file);
-
-        // erstes Layer schreiben
-        int weightCount = nn.layers[0].weights.rows * nn.layers[0].weights.cols;
-        fwrite(nn.layers[0].weights.buffer, sizeof(MatrixType), weightCount, file);
-
-        int biasesCount = nn.layers[0].biases.rows * nn.layers[0].biases.cols;
-        fwrite(nn.layers[0].biases.buffer, sizeof(MatrixType), biasesCount, file);
 
         // für weiter Layer nur outputDimension schreiben
-        for (unsigned int i = 1; i < nn.numberOfLayers; i++)
+        for (unsigned int i = 0; i < nn.numberOfLayers; i++)
         {
-            outputDim = nn.layers[i].weights.rows;
+            int outputDim = nn.layers[i].weights.rows;
             fwrite(&outputDim, sizeof(int), 1, file);
 
-            weightCount = nn.layers[i].weights.rows * nn.layers[i].weights.cols;
+            int weightCount = nn.layers[i].weights.rows * nn.layers[i].weights.cols;
             fwrite(nn.layers[i].weights.buffer, sizeof(MatrixType), weightCount, file);
 
-            biasesCount = nn.layers[i].biases.rows * nn.layers[i].biases.cols;
+            int biasesCount = nn.layers[i].biases.rows * nn.layers[i].biases.cols;
             fwrite(nn.layers[i].biases.buffer, sizeof(MatrixType), biasesCount, file);
         }