diff --git a/Train.ipynb b/Train.ipynb
index f3ed067..2d01740 100644
--- a/Train.ipynb
+++ b/Train.ipynb
@@ -444,133 +444,6 @@
    "source": [
     "--------------------------------------------------"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Save MinMaxScaler in path: ./scaler/minmax_scaler_x_repr.pkl\n"
-     ]
-    }
-   ],
-   "source": [
-    "# load representation data\n",
-    "data_root_dir = './data/'\n",
-    "train_x, train_y, test_x, test_y = utils.load_data(data_root_dir, model_name='FC')  # shape=(num_of_instance, embedding_dim)\n",
-    "\n",
-    "# split train data into train/valiation data\n",
-    "# train data를 랜덤으로 test_size=split_ratio에 대하여 train/validation set으로 분할\n",
-    "split_ratio = 0.2\n",
-    "train_x, valid_x, train_y, valid_y = train_test_split(train_x, train_y, test_size=split_ratio, shuffle=True)\n",
-    "\n",
-    "# normalization\n",
-    "scaler_x_path = './scaler/minmax_scaler_x_repr.pkl'\n",
-    "train_x, valid_x = utils.get_train_val_data(train_x, valid_x, scaler_x_path)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "metadata": {
-    "scrolled": true
-   },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Start training model: FC\n",
-      "\n",
-      "Epoch 1/150\n",
-      "train Loss: 1.7845 Acc: 0.1682\n",
-      "val Loss: 1.7542 Acc: 0.2345\n",
-      "\n",
-      "Epoch 10/150\n",
-      "train Loss: 1.2704 Acc: 0.6596\n",
-      "val Loss: 1.2287 Acc: 0.6737\n",
-      "\n",
-      "Epoch 20/150\n",
-      "train Loss: 0.8235 Acc: 0.7495\n",
-      "val Loss: 0.7868 Acc: 0.8389\n",
-      "\n",
-      "Epoch 30/150\n",
-      "train Loss: 0.6276 Acc: 0.8051\n",
-      "val Loss: 0.5940 Acc: 0.8742\n",
-      "\n",
-      "Epoch 40/150\n",
-      "train Loss: 0.5202 Acc: 0.8373\n",
-      "val Loss: 0.4832 Acc: 0.8926\n",
-      "\n",
-      "Epoch 50/150\n",
-      "train Loss: 0.4367 Acc: 0.8708\n",
-      "val Loss: 0.4038 Acc: 0.9028\n",
-      "\n",
-      "Epoch 60/150\n",
-      "train Loss: 0.3723 Acc: 0.8912\n",
-      "val Loss: 0.3447 Acc: 0.9164\n",
-      "\n",
-      "Epoch 70/150\n",
-      "train Loss: 0.3287 Acc: 0.8978\n",
-      "val Loss: 0.2992 Acc: 0.9211\n",
-      "\n",
-      "Epoch 80/150\n",
-      "train Loss: 0.2944 Acc: 0.9112\n",
-      "val Loss: 0.2645 Acc: 0.9259\n",
-      "\n",
-      "Epoch 90/150\n",
-      "train Loss: 0.2663 Acc: 0.9170\n",
-      "val Loss: 0.2383 Acc: 0.9320\n",
-      "\n",
-      "Epoch 100/150\n",
-      "train Loss: 0.2400 Acc: 0.9267\n",
-      "val Loss: 0.2173 Acc: 0.9334\n",
-      "\n",
-      "Epoch 110/150\n",
-      "train Loss: 0.2243 Acc: 0.9286\n",
-      "val Loss: 0.2009 Acc: 0.9368\n",
-      "\n",
-      "Epoch 120/150\n",
-      "train Loss: 0.2131 Acc: 0.9289\n",
-      "val Loss: 0.1885 Acc: 0.9402\n",
-      "\n",
-      "Epoch 130/150\n",
-      "train Loss: 0.2020 Acc: 0.9303\n",
-      "val Loss: 0.1785 Acc: 0.9443\n",
-      "\n",
-      "Epoch 140/150\n",
-      "train Loss: 0.1910 Acc: 0.9335\n",
-      "val Loss: 0.1705 Acc: 0.9456\n",
-      "\n",
-      "Epoch 150/150\n",
-      "train Loss: 0.1821 Acc: 0.9362\n",
-      "val Loss: 0.1633 Acc: 0.9456\n",
-      "\n",
-      "Training complete in 0m 17s\n",
-      "Best val Acc: 0.947655\n"
-     ]
-    }
-   ],
-   "source": [
-    "# Case 5. fully-connected layers (w/ data representation)\n",
-    "model_name = 'FC'\n",
-    "model_params = config.model_config[model_name]\n",
-    "\n",
-    "data_cls = mc.Classification(model_params)\n",
-    "best_model = data_cls.train_model(train_x, train_y, valid_x, valid_y)  # 모델 학습\n",
-    "data_cls.save_model(best_model, best_model_path=model_params[\"best_model_path\"])  # 모델 저장"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {