diff --git a/.gitignore b/.gitignore
index b79ceae..00a2a2a 100644
--- a/.gitignore
+++ b/.gitignore
@@ -140,4 +140,6 @@ Temporary Items
 outputs/*
 inputs/mnist
 inputs/audio*
+logs/*
+models/*
 *.pkl
diff --git a/Siamese.ipynb b/Siamese.ipynb
index 2859429..93dcb05 100644
--- a/Siamese.ipynb
+++ b/Siamese.ipynb
@@ -175,7 +175,22 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Using TensorFlow backend.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Train on 36252 samples, validate on 4028 samples\n"
+     ]
+    }
+   ],
    "source": [
     "'''Train a Siamese MLP on pairs of digits from the MNIST dataset.\n",
     "\n",
@@ -294,7 +309,7 @@
     "\n",
     "model = Model([input_a, input_b], distance)\n",
     "\n",
-    "tb_cb = TensorBoard(log_dir='./siamese_logs', histogram_freq=1, batch_size=32,\n",
+    "tb_cb = TensorBoard(log_dir='./logs/siamese_logs', histogram_freq=1, batch_size=32,\n",
     "                    write_graph=True, write_grads=True, write_images=True,\n",
     "                    embeddings_freq=0, embeddings_layer_names=None,\n",
     "                    embeddings_metadata=None)\n",
@@ -308,7 +323,7 @@
     "          validation_data=([te_pairs[:, 0], te_pairs[:, 1]], te_y),\n",
     "          callbacks=[tb_cb])\n",
     "\n",
-    "model.save('./siamese_speech_model.h5')\n",
+    "model.save('./models/siamese_speech_model.h5')\n",
     "# compute final accuracy on training and test sets\n",
     "y_pred = model.predict([tr_pairs[:, 0], tr_pairs[:, 1]])\n",
     "tr_acc = compute_accuracy(tr_y, y_pred)\n",
@@ -318,13 +333,6 @@
     "print('* Accuracy on training set: %0.2f%%' % (100 * tr_acc))\n",
     "print('* Accuracy on test set: %0.2f%%' % (100 * te_acc))"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {