diff --git a/README.md b/README.md
index ac023cd08508b7e9502d9c256cd521df4bcf9d59..2906428c1223088c834db5b6c75aca9e592e2ed9 100644
--- a/README.md
+++ b/README.md
@@ -364,4 +364,5 @@ def plot_graph(data_train, labels_train, data_test, labels_test, d_h, learning_r
 
 The accuracy is increasing with each epochs without converging, we could increase the learning rate to speed up the training and inscrease the numbers of epoch to see what would be our maximum accuracy.
 For 100 epochs and a learning rate of 0.1 we got a test accuracy of 0.13.
-For 300 epochs and a learning rate of 0.1 we increased the training accuracy to 0.15991 and we got a test accuracy of 0.155
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+For 300 epochs and a learning rate of 0.1 we increased the training accuracy to 0.15991 and we got a test accuracy of 0.155
+The result is dissapointing, the MLP as a lower accuracy than the KNN model...
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