ANN_Basic_airfoil_dataset.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "642a186d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Import modules\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "from sklearn.model_selection import train_test_split\n",
    "from sklearn.preprocessing import StandardScaler, QuantileTransformer, MaxAbsScaler\n",
    "from sklearn.metrics import r2_score, mean_absolute_error"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "02aa147b",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow.keras.models import Sequential\n",
    "from tensorflow.keras.layers import Input, Dense"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "3e30b9cb",
   "metadata": {},
   "outputs": [],
   "source": [
    "url_file = 'https://archive.ics.uci.edu/ml/machine-learning-databases/00291/airfoil_self_noise.dat'\n",
    "columns = ['frequency',\n",
    "           'angle_of_attack', \n",
    "           'chord_length', \n",
    "           'free_stream_velocity',\n",
    "           'suction_side_displacement_thickness',\n",
    "           'scaled_sound_pressure_level']\n",
    "\n",
    "df = pd.read_csv(url_file, sep='\\t', header=None, names=columns)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "247676c6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frequency</th>\n",
       "      <th>angle_of_attack</th>\n",
       "      <th>chord_length</th>\n",
       "      <th>free_stream_velocity</th>\n",
       "      <th>suction_side_displacement_thickness</th>\n",
       "      <th>scaled_sound_pressure_level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>800</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3048</td>\n",
       "      <td>71.3</td>\n",
       "      <td>0.002663</td>\n",
       "      <td>126.201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3048</td>\n",
       "      <td>71.3</td>\n",
       "      <td>0.002663</td>\n",
       "      <td>125.201</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1250</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3048</td>\n",
       "      <td>71.3</td>\n",
       "      <td>0.002663</td>\n",
       "      <td>125.951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1600</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3048</td>\n",
       "      <td>71.3</td>\n",
       "      <td>0.002663</td>\n",
       "      <td>127.591</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.3048</td>\n",
       "      <td>71.3</td>\n",
       "      <td>0.002663</td>\n",
       "      <td>127.461</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   frequency  angle_of_attack  chord_length  free_stream_velocity   \n",
       "0        800              0.0        0.3048                  71.3  \\\n",
       "1       1000              0.0        0.3048                  71.3   \n",
       "2       1250              0.0        0.3048                  71.3   \n",
       "3       1600              0.0        0.3048                  71.3   \n",
       "4       2000              0.0        0.3048                  71.3   \n",
       "\n",
       "   suction_side_displacement_thickness  scaled_sound_pressure_level  \n",
       "0                             0.002663                      126.201  \n",
       "1                             0.002663                      125.201  \n",
       "2                             0.002663                      125.951  \n",
       "3                             0.002663                      127.591  \n",
       "4                             0.002663                      127.461  "
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "06983f73",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frequency</th>\n",
       "      <th>angle_of_attack</th>\n",
       "      <th>chord_length</th>\n",
       "      <th>free_stream_velocity</th>\n",
       "      <th>suction_side_displacement_thickness</th>\n",
       "      <th>scaled_sound_pressure_level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1498</th>\n",
       "      <td>2500</td>\n",
       "      <td>15.6</td>\n",
       "      <td>0.1016</td>\n",
       "      <td>39.6</td>\n",
       "      <td>0.052849</td>\n",
       "      <td>110.264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1499</th>\n",
       "      <td>3150</td>\n",
       "      <td>15.6</td>\n",
       "      <td>0.1016</td>\n",
       "      <td>39.6</td>\n",
       "      <td>0.052849</td>\n",
       "      <td>109.254</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1500</th>\n",
       "      <td>4000</td>\n",
       "      <td>15.6</td>\n",
       "      <td>0.1016</td>\n",
       "      <td>39.6</td>\n",
       "      <td>0.052849</td>\n",
       "      <td>106.604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1501</th>\n",
       "      <td>5000</td>\n",
       "      <td>15.6</td>\n",
       "      <td>0.1016</td>\n",
       "      <td>39.6</td>\n",
       "      <td>0.052849</td>\n",
       "      <td>106.224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1502</th>\n",
       "      <td>6300</td>\n",
       "      <td>15.6</td>\n",
       "      <td>0.1016</td>\n",
       "      <td>39.6</td>\n",
       "      <td>0.052849</td>\n",
       "      <td>104.204</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      frequency  angle_of_attack  chord_length  free_stream_velocity   \n",
       "1498       2500             15.6        0.1016                  39.6  \\\n",
       "1499       3150             15.6        0.1016                  39.6   \n",
       "1500       4000             15.6        0.1016                  39.6   \n",
       "1501       5000             15.6        0.1016                  39.6   \n",
       "1502       6300             15.6        0.1016                  39.6   \n",
       "\n",
       "      suction_side_displacement_thickness  scaled_sound_pressure_level  \n",
       "1498                             0.052849                      110.264  \n",
       "1499                             0.052849                      109.254  \n",
       "1500                             0.052849                      106.604  \n",
       "1501                             0.052849                      106.224  \n",
       "1502                             0.052849                      104.204  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1ac6c61d",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>frequency</th>\n",
       "      <th>angle_of_attack</th>\n",
       "      <th>chord_length</th>\n",
       "      <th>free_stream_velocity</th>\n",
       "      <th>suction_side_displacement_thickness</th>\n",
       "      <th>scaled_sound_pressure_level</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1503.000000</td>\n",
       "      <td>1503.000000</td>\n",
       "      <td>1503.000000</td>\n",
       "      <td>1503.000000</td>\n",
       "      <td>1503.000000</td>\n",
       "      <td>1503.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>2886.380572</td>\n",
       "      <td>6.782302</td>\n",
       "      <td>0.136548</td>\n",
       "      <td>50.860745</td>\n",
       "      <td>0.011140</td>\n",
       "      <td>124.835943</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3152.573137</td>\n",
       "      <td>5.918128</td>\n",
       "      <td>0.093541</td>\n",
       "      <td>15.572784</td>\n",
       "      <td>0.013150</td>\n",
       "      <td>6.898657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>200.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.025400</td>\n",
       "      <td>31.700000</td>\n",
       "      <td>0.000401</td>\n",
       "      <td>103.380000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>800.000000</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>0.050800</td>\n",
       "      <td>39.600000</td>\n",
       "      <td>0.002535</td>\n",
       "      <td>120.191000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>1600.000000</td>\n",
       "      <td>5.400000</td>\n",
       "      <td>0.101600</td>\n",
       "      <td>39.600000</td>\n",
       "      <td>0.004957</td>\n",
       "      <td>125.721000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>4000.000000</td>\n",
       "      <td>9.900000</td>\n",
       "      <td>0.228600</td>\n",
       "      <td>71.300000</td>\n",
       "      <td>0.015576</td>\n",
       "      <td>129.995500</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>20000.000000</td>\n",
       "      <td>22.200000</td>\n",
       "      <td>0.304800</td>\n",
       "      <td>71.300000</td>\n",
       "      <td>0.058411</td>\n",
       "      <td>140.987000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          frequency  angle_of_attack  chord_length  free_stream_velocity   \n",
       "count   1503.000000      1503.000000   1503.000000           1503.000000  \\\n",
       "mean    2886.380572         6.782302      0.136548             50.860745   \n",
       "std     3152.573137         5.918128      0.093541             15.572784   \n",
       "min      200.000000         0.000000      0.025400             31.700000   \n",
       "25%      800.000000         2.000000      0.050800             39.600000   \n",
       "50%     1600.000000         5.400000      0.101600             39.600000   \n",
       "75%     4000.000000         9.900000      0.228600             71.300000   \n",
       "max    20000.000000        22.200000      0.304800             71.300000   \n",
       "\n",
       "       suction_side_displacement_thickness  scaled_sound_pressure_level  \n",
       "count                          1503.000000                  1503.000000  \n",
       "mean                              0.011140                   124.835943  \n",
       "std                               0.013150                     6.898657  \n",
       "min                               0.000401                   103.380000  \n",
       "25%                               0.002535                   120.191000  \n",
       "50%                               0.004957                   125.721000  \n",
       "75%                               0.015576                   129.995500  \n",
       "max                               0.058411                   140.987000  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "e0161967",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 1503 entries, 0 to 1502\n",
      "Data columns (total 6 columns):\n",
      " #   Column                               Non-Null Count  Dtype  \n",
      "---  ------                               --------------  -----  \n",
      " 0   frequency                            1503 non-null   int64  \n",
      " 1   angle_of_attack                      1503 non-null   float64\n",
      " 2   chord_length                         1503 non-null   float64\n",
      " 3   free_stream_velocity                 1503 non-null   float64\n",
      " 4   suction_side_displacement_thickness  1503 non-null   float64\n",
      " 5   scaled_sound_pressure_level          1503 non-null   float64\n",
      "dtypes: float64(5), int64(1)\n",
      "memory usage: 70.6 KB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e4107562",
   "metadata": {},
   "outputs": [],
   "source": [
    "def preprocess_input(df):\n",
    "    \n",
    "    train_data = df.copy()\n",
    "    train_set = train_data.drop(\"scaled_sound_pressure_level\", axis = 1)\n",
    "    train_labels = train_data[\"scaled_sound_pressure_level\"].copy()\n",
    "    \n",
    "    train_set = QuantileTransformer(random_state=0).fit_transform(train_set)\n",
    "    train_set = MaxAbsScaler().fit_transform(train_set)\n",
    "    train_set = StandardScaler().fit_transform(train_set)\n",
    "    \n",
    "    # Train-test split\n",
    "    X_train, X_test, y_train, y_test = train_test_split(train_set, train_labels, test_size=0.3)\n",
    "    \n",
    "    return X_train, X_test, y_train, y_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "e25cbe89",
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, X_test, y_train, y_test = preprocess_input(df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "201a7672",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(1052, 5)\n",
      "(451, 5)\n",
      "(1052,)\n",
      "(451,)\n"
     ]
    }
   ],
   "source": [
    "print(X_train.shape)\n",
    "print(X_test.shape)\n",
    "print(y_train.shape)\n",
    "print(y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "be16b271",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " dense (Dense)               (None, 48)                288       \n",
      "                                                                 \n",
      " dense_1 (Dense)             (None, 1)                 49        \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 337 (1.32 KB)\n",
      "Trainable params: 337 (1.32 KB)\n",
      "Non-trainable params: 0 (0.00 Byte)\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model = Sequential()\n",
    "\n",
    "model.add(Input(X_train.shape[1],))\n",
    "\n",
    "model.add(Dense(48, activation = 'relu'))\n",
    "\n",
    "model.add(Dense(1))\n",
    "\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "6c427f8b",
   "metadata": {},
   "outputs": [],
   "source": [
    "model.compile(optimizer = 'adam', loss = 'mean_squared_error', metrics = [tf.keras.metrics.RootMeanSquaredError()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2326d76e",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1000\n",
      "17/17 [==============================] - 1s 9ms/step - loss: 15529.8271 - root_mean_squared_error: 124.6187 - val_loss: 15455.0410 - val_root_mean_squared_error: 124.3183\n",
      "Epoch 2/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 15441.4160 - root_mean_squared_error: 124.2635 - val_loss: 15364.7969 - val_root_mean_squared_error: 123.9548\n",
      "Epoch 3/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 15349.0479 - root_mean_squared_error: 123.8913 - val_loss: 15270.0146 - val_root_mean_squared_error: 123.5719\n",
      "Epoch 4/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 15251.1240 - root_mean_squared_error: 123.4954 - val_loss: 15167.4658 - val_root_mean_squared_error: 123.1563\n",
      "Epoch 5/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 15144.5674 - root_mean_squared_error: 123.0633 - val_loss: 15056.3291 - val_root_mean_squared_error: 122.7042\n",
      "Epoch 6/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 15028.2637 - root_mean_squared_error: 122.5898 - val_loss: 14935.3525 - val_root_mean_squared_error: 122.2103\n",
      "Epoch 7/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 14901.0420 - root_mean_squared_error: 122.0698 - val_loss: 14801.4248 - val_root_mean_squared_error: 121.6611\n",
      "Epoch 8/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 14760.4121 - root_mean_squared_error: 121.4924 - val_loss: 14653.9414 - val_root_mean_squared_error: 121.0535\n",
      "Epoch 9/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 14605.9902 - root_mean_squared_error: 120.8552 - val_loss: 14491.9023 - val_root_mean_squared_error: 120.3823\n",
      "Epoch 10/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 14436.9355 - root_mean_squared_error: 120.1538 - val_loss: 14314.8994 - val_root_mean_squared_error: 119.6449\n",
      "Epoch 11/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 14252.2559 - root_mean_squared_error: 119.3828 - val_loss: 14123.3936 - val_root_mean_squared_error: 118.8419\n",
      "Epoch 12/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 14052.5176 - root_mean_squared_error: 118.5433 - val_loss: 13916.9268 - val_root_mean_squared_error: 117.9700\n",
      "Epoch 13/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 13837.6270 - root_mean_squared_error: 117.6334 - val_loss: 13693.8330 - val_root_mean_squared_error: 117.0207\n",
      "Epoch 14/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 13606.8252 - root_mean_squared_error: 116.6483 - val_loss: 13455.5840 - val_root_mean_squared_error: 115.9982\n",
      "Epoch 15/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 13360.6143 - root_mean_squared_error: 115.5881 - val_loss: 13203.5195 - val_root_mean_squared_error: 114.9066\n",
      "Epoch 16/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 13100.6348 - root_mean_squared_error: 114.4580 - val_loss: 12935.3936 - val_root_mean_squared_error: 113.7339\n",
      "Epoch 17/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 12825.5684 - root_mean_squared_error: 113.2500 - val_loss: 12653.2686 - val_root_mean_squared_error: 112.4867\n",
      "Epoch 18/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 12535.4209 - root_mean_squared_error: 111.9617 - val_loss: 12359.2412 - val_root_mean_squared_error: 111.1721\n",
      "Epoch 19/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 12233.1270 - root_mean_squared_error: 110.6035 - val_loss: 12049.9854 - val_root_mean_squared_error: 109.7724\n",
      "Epoch 20/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 11917.7793 - root_mean_squared_error: 109.1686 - val_loss: 11726.8584 - val_root_mean_squared_error: 108.2906\n",
      "Epoch 21/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 11588.6963 - root_mean_squared_error: 107.6508 - val_loss: 11394.5352 - val_root_mean_squared_error: 106.7452\n",
      "Epoch 22/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 11250.5615 - root_mean_squared_error: 106.0687 - val_loss: 11051.1406 - val_root_mean_squared_error: 105.1244\n",
      "Epoch 23/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 10901.7656 - root_mean_squared_error: 104.4115 - val_loss: 10699.1328 - val_root_mean_squared_error: 103.4366\n",
      "Epoch 24/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10544.5977 - root_mean_squared_error: 102.6869 - val_loss: 10338.2852 - val_root_mean_squared_error: 101.6774\n",
      "Epoch 25/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 10179.1299 - root_mean_squared_error: 100.8917 - val_loss: 9969.8066 - val_root_mean_squared_error: 99.8489\n",
      "Epoch 26/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9806.8096 - root_mean_squared_error: 99.0293 - val_loss: 9594.9297 - val_root_mean_squared_error: 97.9537\n",
      "Epoch 27/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9429.6914 - root_mean_squared_error: 97.1066 - val_loss: 9216.5020 - val_root_mean_squared_error: 96.0026\n",
      "Epoch 28/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9049.6494 - root_mean_squared_error: 95.1296 - val_loss: 8836.8994 - val_root_mean_squared_error: 94.0048\n",
      "Epoch 29/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8668.8584 - root_mean_squared_error: 93.1067 - val_loss: 8457.8125 - val_root_mean_squared_error: 91.9664\n",
      "Epoch 30/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8289.3838 - root_mean_squared_error: 91.0461 - val_loss: 8079.3428 - val_root_mean_squared_error: 89.8852\n",
      "Epoch 31/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7910.8804 - root_mean_squared_error: 88.9431 - val_loss: 7702.7271 - val_root_mean_squared_error: 87.7652\n",
      "Epoch 32/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7535.0835 - root_mean_squared_error: 86.8049 - val_loss: 7330.5049 - val_root_mean_squared_error: 85.6184\n",
      "Epoch 33/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7163.9731 - root_mean_squared_error: 84.6403 - val_loss: 6962.6064 - val_root_mean_squared_error: 83.4422\n",
      "Epoch 34/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 6798.0273 - root_mean_squared_error: 82.4501 - val_loss: 6601.0425 - val_root_mean_squared_error: 81.2468\n",
      "Epoch 35/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 6438.6235 - root_mean_squared_error: 80.2410 - val_loss: 6246.4351 - val_root_mean_squared_error: 79.0344\n",
      "Epoch 36/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 6087.3296 - root_mean_squared_error: 78.0213 - val_loss: 5899.6436 - val_root_mean_squared_error: 76.8091\n",
      "Epoch 37/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 5744.3853 - root_mean_squared_error: 75.7917 - val_loss: 5563.3926 - val_root_mean_squared_error: 74.5882\n",
      "Epoch 38/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 5412.1011 - root_mean_squared_error: 73.5670 - val_loss: 5236.2876 - val_root_mean_squared_error: 72.3622\n",
      "Epoch 39/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 5090.5059 - root_mean_squared_error: 71.3478 - val_loss: 4922.1362 - val_root_mean_squared_error: 70.1579\n",
      "Epoch 40/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 4781.6572 - root_mean_squared_error: 69.1495 - val_loss: 4620.2886 - val_root_mean_squared_error: 67.9727\n",
      "Epoch 41/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 4485.0088 - root_mean_squared_error: 66.9702 - val_loss: 4331.3911 - val_root_mean_squared_error: 65.8133\n",
      "Epoch 42/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 4202.1904 - root_mean_squared_error: 64.8243 - val_loss: 4055.2466 - val_root_mean_squared_error: 63.6808\n",
      "Epoch 43/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 3933.1479 - root_mean_squared_error: 62.7148 - val_loss: 3792.8169 - val_root_mean_squared_error: 61.5858\n",
      "Epoch 44/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 3678.1929 - root_mean_squared_error: 60.6481 - val_loss: 3544.7783 - val_root_mean_squared_error: 59.5380\n",
      "Epoch 45/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 3436.3486 - root_mean_squared_error: 58.6204 - val_loss: 3312.3113 - val_root_mean_squared_error: 57.5527\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 46/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 3210.8108 - root_mean_squared_error: 56.6640 - val_loss: 3092.3398 - val_root_mean_squared_error: 55.6088\n",
      "Epoch 47/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 2997.7546 - root_mean_squared_error: 54.7518 - val_loss: 2886.8232 - val_root_mean_squared_error: 53.7292\n",
      "Epoch 48/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 2799.2278 - root_mean_squared_error: 52.9077 - val_loss: 2695.5403 - val_root_mean_squared_error: 51.9186\n",
      "Epoch 49/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 2614.9492 - root_mean_squared_error: 51.1366 - val_loss: 2516.2559 - val_root_mean_squared_error: 50.1623\n",
      "Epoch 50/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 2442.6780 - root_mean_squared_error: 49.4235 - val_loss: 2351.4858 - val_root_mean_squared_error: 48.4921\n",
      "Epoch 51/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 2284.1719 - root_mean_squared_error: 47.7930 - val_loss: 2197.4573 - val_root_mean_squared_error: 46.8770\n",
      "Epoch 52/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 2136.6655 - root_mean_squared_error: 46.2241 - val_loss: 2056.6492 - val_root_mean_squared_error: 45.3503\n",
      "Epoch 53/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 2003.0813 - root_mean_squared_error: 44.7558 - val_loss: 1926.2012 - val_root_mean_squared_error: 43.8885\n",
      "Epoch 54/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 1879.2332 - root_mean_squared_error: 43.3501 - val_loss: 1808.1182 - val_root_mean_squared_error: 42.5220\n",
      "Epoch 55/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 1767.0109 - root_mean_squared_error: 42.0358 - val_loss: 1699.8667 - val_root_mean_squared_error: 41.2294\n",
      "Epoch 56/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 1663.0632 - root_mean_squared_error: 40.7807 - val_loss: 1600.8589 - val_root_mean_squared_error: 40.0107\n",
      "Epoch 57/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 1568.6976 - root_mean_squared_error: 39.6068 - val_loss: 1510.3254 - val_root_mean_squared_error: 38.8629\n",
      "Epoch 58/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 1482.7340 - root_mean_squared_error: 38.5063 - val_loss: 1427.4335 - val_root_mean_squared_error: 37.7814\n",
      "Epoch 59/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 1404.9465 - root_mean_squared_error: 37.4826 - val_loss: 1352.0430 - val_root_mean_squared_error: 36.7701\n",
      "Epoch 60/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 1333.8452 - root_mean_squared_error: 36.5218 - val_loss: 1283.0679 - val_root_mean_squared_error: 35.8199\n",
      "Epoch 61/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 1268.8589 - root_mean_squared_error: 35.6210 - val_loss: 1222.0618 - val_root_mean_squared_error: 34.9580\n",
      "Epoch 62/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 1211.0975 - root_mean_squared_error: 34.8008 - val_loss: 1165.6312 - val_root_mean_squared_error: 34.1413\n",
      "Epoch 63/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 1158.3981 - root_mean_squared_error: 34.0352 - val_loss: 1114.5167 - val_root_mean_squared_error: 33.3844\n",
      "Epoch 64/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 1110.3357 - root_mean_squared_error: 33.3217 - val_loss: 1068.2390 - val_root_mean_squared_error: 32.6839\n",
      "Epoch 65/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 1066.7524 - root_mean_squared_error: 32.6612 - val_loss: 1025.4854 - val_root_mean_squared_error: 32.0232\n",
      "Epoch 66/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 1026.9366 - root_mean_squared_error: 32.0459 - val_loss: 987.2414 - val_root_mean_squared_error: 31.4204\n",
      "Epoch 67/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 990.5477 - root_mean_squared_error: 31.4730 - val_loss: 952.1926 - val_root_mean_squared_error: 30.8576\n",
      "Epoch 68/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 957.4703 - root_mean_squared_error: 30.9430 - val_loss: 919.0809 - val_root_mean_squared_error: 30.3163\n",
      "Epoch 69/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 926.1381 - root_mean_squared_error: 30.4325 - val_loss: 889.0022 - val_root_mean_squared_error: 29.8161\n",
      "Epoch 70/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 897.8128 - root_mean_squared_error: 29.9635 - val_loss: 860.8176 - val_root_mean_squared_error: 29.3397\n",
      "Epoch 71/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 871.0209 - root_mean_squared_error: 29.5131 - val_loss: 835.3215 - val_root_mean_squared_error: 28.9019\n",
      "Epoch 72/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 846.0233 - root_mean_squared_error: 29.0865 - val_loss: 811.6510 - val_root_mean_squared_error: 28.4895\n",
      "Epoch 73/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 823.3236 - root_mean_squared_error: 28.6936 - val_loss: 788.1786 - val_root_mean_squared_error: 28.0745\n",
      "Epoch 74/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 800.9214 - root_mean_squared_error: 28.3006 - val_loss: 766.6966 - val_root_mean_squared_error: 27.6893\n",
      "Epoch 75/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 780.3269 - root_mean_squared_error: 27.9343 - val_loss: 746.0705 - val_root_mean_squared_error: 27.3143\n",
      "Epoch 76/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 760.3815 - root_mean_squared_error: 27.5750 - val_loss: 726.9499 - val_root_mean_squared_error: 26.9620\n",
      "Epoch 77/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 741.6395 - root_mean_squared_error: 27.2331 - val_loss: 708.2032 - val_root_mean_squared_error: 26.6121\n",
      "Epoch 78/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 723.5529 - root_mean_squared_error: 26.8989 - val_loss: 690.5922 - val_root_mean_squared_error: 26.2791\n",
      "Epoch 79/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 706.4612 - root_mean_squared_error: 26.5793 - val_loss: 673.4119 - val_root_mean_squared_error: 25.9502\n",
      "Epoch 80/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 689.6142 - root_mean_squared_error: 26.2605 - val_loss: 656.9422 - val_root_mean_squared_error: 25.6309\n",
      "Epoch 81/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 673.4135 - root_mean_squared_error: 25.9502 - val_loss: 641.5377 - val_root_mean_squared_error: 25.3286\n",
      "Epoch 82/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 658.1380 - root_mean_squared_error: 25.6542 - val_loss: 626.0789 - val_root_mean_squared_error: 25.0216\n",
      "Epoch 83/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 643.1367 - root_mean_squared_error: 25.3601 - val_loss: 611.3408 - val_root_mean_squared_error: 24.7253\n",
      "Epoch 84/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 628.3358 - root_mean_squared_error: 25.0666 - val_loss: 597.1653 - val_root_mean_squared_error: 24.4370\n",
      "Epoch 85/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 614.1197 - root_mean_squared_error: 24.7814 - val_loss: 583.2382 - val_root_mean_squared_error: 24.1503\n",
      "Epoch 86/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 600.2875 - root_mean_squared_error: 24.5008 - val_loss: 569.5616 - val_root_mean_squared_error: 23.8655\n",
      "Epoch 87/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 586.7161 - root_mean_squared_error: 24.2222 - val_loss: 556.4385 - val_root_mean_squared_error: 23.5889\n",
      "Epoch 88/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 573.7317 - root_mean_squared_error: 23.9527 - val_loss: 543.4702 - val_root_mean_squared_error: 23.3124\n",
      "Epoch 89/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 560.8416 - root_mean_squared_error: 23.6821 - val_loss: 530.7939 - val_root_mean_squared_error: 23.0390\n",
      "Epoch 90/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 548.2751 - root_mean_squared_error: 23.4153 - val_loss: 518.7853 - val_root_mean_squared_error: 22.7769\n",
      "Epoch 91/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 536.3410 - root_mean_squared_error: 23.1590 - val_loss: 506.8298 - val_root_mean_squared_error: 22.5129\n",
      "Epoch 92/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 524.1667 - root_mean_squared_error: 22.8947 - val_loss: 495.3973 - val_root_mean_squared_error: 22.2575\n",
      "Epoch 93/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 512.6812 - root_mean_squared_error: 22.6425 - val_loss: 484.4347 - val_root_mean_squared_error: 22.0099\n",
      "Epoch 94/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 501.6065 - root_mean_squared_error: 22.3966 - val_loss: 472.9701 - val_root_mean_squared_error: 21.7479\n",
      "Epoch 95/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 490.2788 - root_mean_squared_error: 22.1422 - val_loss: 462.4759 - val_root_mean_squared_error: 21.5053\n",
      "Epoch 96/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 479.6818 - root_mean_squared_error: 21.9016 - val_loss: 452.0559 - val_root_mean_squared_error: 21.2616\n",
      "Epoch 97/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 469.0954 - root_mean_squared_error: 21.6586 - val_loss: 441.9777 - val_root_mean_squared_error: 21.0233\n",
      "Epoch 98/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 459.0683 - root_mean_squared_error: 21.4259 - val_loss: 431.7322 - val_root_mean_squared_error: 20.7782\n",
      "Epoch 99/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 449.1439 - root_mean_squared_error: 21.1930 - val_loss: 422.2628 - val_root_mean_squared_error: 20.5490\n",
      "Epoch 100/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 439.6019 - root_mean_squared_error: 20.9667 - val_loss: 412.6599 - val_root_mean_squared_error: 20.3140\n",
      "Epoch 101/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 429.9865 - root_mean_squared_error: 20.7361 - val_loss: 403.5358 - val_root_mean_squared_error: 20.0882\n",
      "Epoch 102/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 420.9799 - root_mean_squared_error: 20.5178 - val_loss: 394.4729 - val_root_mean_squared_error: 19.8613\n",
      "Epoch 103/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 411.9665 - root_mean_squared_error: 20.2970 - val_loss: 385.8962 - val_root_mean_squared_error: 19.6442\n",
      "Epoch 104/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 403.3692 - root_mean_squared_error: 20.0841 - val_loss: 377.5135 - val_root_mean_squared_error: 19.4297\n",
      "Epoch 105/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 394.9755 - root_mean_squared_error: 19.8740 - val_loss: 369.2408 - val_root_mean_squared_error: 19.2156\n",
      "Epoch 106/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 386.6021 - root_mean_squared_error: 19.6622 - val_loss: 361.3084 - val_root_mean_squared_error: 19.0081\n",
      "Epoch 107/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 378.6366 - root_mean_squared_error: 19.4586 - val_loss: 353.4668 - val_root_mean_squared_error: 18.8007\n",
      "Epoch 108/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 370.8003 - root_mean_squared_error: 19.2562 - val_loss: 345.8230 - val_root_mean_squared_error: 18.5963\n",
      "Epoch 109/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 363.3824 - root_mean_squared_error: 19.0626 - val_loss: 338.4424 - val_root_mean_squared_error: 18.3968\n",
      "Epoch 110/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 355.9515 - root_mean_squared_error: 18.8667 - val_loss: 331.5132 - val_root_mean_squared_error: 18.2075\n",
      "Epoch 111/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 348.8659 - root_mean_squared_error: 18.6780 - val_loss: 324.6449 - val_root_mean_squared_error: 18.0179\n",
      "Epoch 112/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 341.9528 - root_mean_squared_error: 18.4920 - val_loss: 317.8710 - val_root_mean_squared_error: 17.8289\n",
      "Epoch 113/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 335.1435 - root_mean_squared_error: 18.3069 - val_loss: 311.4402 - val_root_mean_squared_error: 17.6477\n",
      "Epoch 114/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 328.4948 - root_mean_squared_error: 18.1244 - val_loss: 305.3426 - val_root_mean_squared_error: 17.4741\n",
      "Epoch 115/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 322.1100 - root_mean_squared_error: 17.9474 - val_loss: 299.0836 - val_root_mean_squared_error: 17.2940\n",
      "Epoch 116/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 315.9268 - root_mean_squared_error: 17.7743 - val_loss: 293.0619 - val_root_mean_squared_error: 17.1191\n",
      "Epoch 117/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 309.8734 - root_mean_squared_error: 17.6032 - val_loss: 287.2861 - val_root_mean_squared_error: 16.9495\n",
      "Epoch 118/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 304.0269 - root_mean_squared_error: 17.4364 - val_loss: 281.6430 - val_root_mean_squared_error: 16.7822\n",
      "Epoch 119/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 298.2989 - root_mean_squared_error: 17.2713 - val_loss: 276.2545 - val_root_mean_squared_error: 16.6209\n",
      "Epoch 120/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 292.7559 - root_mean_squared_error: 17.1101 - val_loss: 270.8811 - val_root_mean_squared_error: 16.4585\n",
      "Epoch 121/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 287.4041 - root_mean_squared_error: 16.9530 - val_loss: 265.5010 - val_root_mean_squared_error: 16.2942\n",
      "Epoch 122/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 282.1127 - root_mean_squared_error: 16.7962 - val_loss: 260.5659 - val_root_mean_squared_error: 16.1421\n",
      "Epoch 123/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 277.0896 - root_mean_squared_error: 16.6460 - val_loss: 255.7249 - val_root_mean_squared_error: 15.9914\n",
      "Epoch 124/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 272.0782 - root_mean_squared_error: 16.4948 - val_loss: 251.0567 - val_root_mean_squared_error: 15.8448\n",
      "Epoch 125/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 267.2201 - root_mean_squared_error: 16.3469 - val_loss: 246.4267 - val_root_mean_squared_error: 15.6980\n",
      "Epoch 126/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 262.4868 - root_mean_squared_error: 16.2014 - val_loss: 242.1144 - val_root_mean_squared_error: 15.5600\n",
      "Epoch 127/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 257.9254 - root_mean_squared_error: 16.0601 - val_loss: 237.7796 - val_root_mean_squared_error: 15.4201\n",
      "Epoch 128/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 253.5140 - root_mean_squared_error: 15.9221 - val_loss: 233.7056 - val_root_mean_squared_error: 15.2874\n",
      "Epoch 129/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 249.1551 - root_mean_squared_error: 15.7846 - val_loss: 229.5721 - val_root_mean_squared_error: 15.1516\n",
      "Epoch 130/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 244.9029 - root_mean_squared_error: 15.6494 - val_loss: 225.7591 - val_root_mean_squared_error: 15.0253\n",
      "Epoch 131/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 240.8531 - root_mean_squared_error: 15.5194 - val_loss: 221.7754 - val_root_mean_squared_error: 14.8921\n",
      "Epoch 132/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 236.8690 - root_mean_squared_error: 15.3905 - val_loss: 217.9626 - val_root_mean_squared_error: 14.7636\n",
      "Epoch 133/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 232.9338 - root_mean_squared_error: 15.2622 - val_loss: 214.3223 - val_root_mean_squared_error: 14.6398\n",
      "Epoch 134/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 229.1264 - root_mean_squared_error: 15.1369 - val_loss: 210.8438 - val_root_mean_squared_error: 14.5205\n",
      "Epoch 135/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 225.4690 - root_mean_squared_error: 15.0156 - val_loss: 207.3573 - val_root_mean_squared_error: 14.3999\n",
      "Epoch 136/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 221.8508 - root_mean_squared_error: 14.8947 - val_loss: 204.0852 - val_root_mean_squared_error: 14.2858\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 137/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 218.4005 - root_mean_squared_error: 14.7784 - val_loss: 200.8270 - val_root_mean_squared_error: 14.1713\n",
      "Epoch 138/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 215.0818 - root_mean_squared_error: 14.6657 - val_loss: 197.7008 - val_root_mean_squared_error: 14.0606\n",
      "Epoch 139/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 211.7239 - root_mean_squared_error: 14.5507 - val_loss: 194.5571 - val_root_mean_squared_error: 13.9484\n",
      "Epoch 140/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 208.4378 - root_mean_squared_error: 14.4374 - val_loss: 191.6579 - val_root_mean_squared_error: 13.8441\n",
      "Epoch 141/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 205.3250 - root_mean_squared_error: 14.3292 - val_loss: 188.7632 - val_root_mean_squared_error: 13.7391\n",
      "Epoch 142/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 202.1837 - root_mean_squared_error: 14.2191 - val_loss: 186.0757 - val_root_mean_squared_error: 13.6410\n",
      "Epoch 143/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 199.2689 - root_mean_squared_error: 14.1163 - val_loss: 183.0198 - val_root_mean_squared_error: 13.5285\n",
      "Epoch 144/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 196.2929 - root_mean_squared_error: 14.0105 - val_loss: 180.2276 - val_root_mean_squared_error: 13.4249\n",
      "Epoch 145/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 193.4094 - root_mean_squared_error: 13.9072 - val_loss: 177.7773 - val_root_mean_squared_error: 13.3333\n",
      "Epoch 146/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 190.6855 - root_mean_squared_error: 13.8089 - val_loss: 175.3051 - val_root_mean_squared_error: 13.2403\n",
      "Epoch 147/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 188.0625 - root_mean_squared_error: 13.7136 - val_loss: 172.7945 - val_root_mean_squared_error: 13.1451\n",
      "Epoch 148/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 185.3784 - root_mean_squared_error: 13.6154 - val_loss: 170.4493 - val_root_mean_squared_error: 13.0556\n",
      "Epoch 149/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 182.8026 - root_mean_squared_error: 13.5205 - val_loss: 168.0606 - val_root_mean_squared_error: 12.9638\n",
      "Epoch 150/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 180.2865 - root_mean_squared_error: 13.4271 - val_loss: 165.6936 - val_root_mean_squared_error: 12.8722\n",
      "Epoch 151/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 177.8975 - root_mean_squared_error: 13.3378 - val_loss: 163.3773 - val_root_mean_squared_error: 12.7819\n",
      "Epoch 152/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 175.3352 - root_mean_squared_error: 13.2414 - val_loss: 161.3043 - val_root_mean_squared_error: 12.7006\n",
      "Epoch 153/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 172.9895 - root_mean_squared_error: 13.1525 - val_loss: 159.1481 - val_root_mean_squared_error: 12.6154\n",
      "Epoch 154/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 170.6728 - root_mean_squared_error: 13.0642 - val_loss: 157.0175 - val_root_mean_squared_error: 12.5307\n",
      "Epoch 155/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 168.3933 - root_mean_squared_error: 12.9766 - val_loss: 154.9513 - val_root_mean_squared_error: 12.4479\n",
      "Epoch 156/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 166.2064 - root_mean_squared_error: 12.8921 - val_loss: 153.0371 - val_root_mean_squared_error: 12.3708\n",
      "Epoch 157/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 164.0528 - root_mean_squared_error: 12.8083 - val_loss: 150.9960 - val_root_mean_squared_error: 12.2880\n",
      "Epoch 158/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 161.9299 - root_mean_squared_error: 12.7252 - val_loss: 149.1447 - val_root_mean_squared_error: 12.2125\n",
      "Epoch 159/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 159.8400 - root_mean_squared_error: 12.6428 - val_loss: 147.3311 - val_root_mean_squared_error: 12.1380\n",
      "Epoch 160/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 157.9658 - root_mean_squared_error: 12.5684 - val_loss: 145.4167 - val_root_mean_squared_error: 12.0589\n",
      "Epoch 161/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 155.8909 - root_mean_squared_error: 12.4856 - val_loss: 143.6101 - val_root_mean_squared_error: 11.9837\n",
      "Epoch 162/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 154.0154 - root_mean_squared_error: 12.4103 - val_loss: 141.9908 - val_root_mean_squared_error: 11.9160\n",
      "Epoch 163/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 152.0793 - root_mean_squared_error: 12.3320 - val_loss: 140.1566 - val_root_mean_squared_error: 11.8388\n",
      "Epoch 164/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 150.2745 - root_mean_squared_error: 12.2586 - val_loss: 138.6046 - val_root_mean_squared_error: 11.7730\n",
      "Epoch 165/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 148.4047 - root_mean_squared_error: 12.1821 - val_loss: 136.8505 - val_root_mean_squared_error: 11.6983\n",
      "Epoch 166/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 146.6387 - root_mean_squared_error: 12.1094 - val_loss: 135.2717 - val_root_mean_squared_error: 11.6306\n",
      "Epoch 167/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 144.9123 - root_mean_squared_error: 12.0380 - val_loss: 133.6662 - val_root_mean_squared_error: 11.5614\n",
      "Epoch 168/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 143.1842 - root_mean_squared_error: 11.9660 - val_loss: 132.1963 - val_root_mean_squared_error: 11.4977\n",
      "Epoch 169/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 141.4997 - root_mean_squared_error: 11.8954 - val_loss: 130.7256 - val_root_mean_squared_error: 11.4335\n",
      "Epoch 170/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 139.8673 - root_mean_squared_error: 11.8266 - val_loss: 129.1368 - val_root_mean_squared_error: 11.3638\n",
      "Epoch 171/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 138.2143 - root_mean_squared_error: 11.7565 - val_loss: 127.7980 - val_root_mean_squared_error: 11.3048\n",
      "Epoch 172/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 136.6399 - root_mean_squared_error: 11.6893 - val_loss: 126.3549 - val_root_mean_squared_error: 11.2408\n",
      "Epoch 173/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 135.0633 - root_mean_squared_error: 11.6217 - val_loss: 125.0084 - val_root_mean_squared_error: 11.1807\n",
      "Epoch 174/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 133.5254 - root_mean_squared_error: 11.5553 - val_loss: 123.5541 - val_root_mean_squared_error: 11.1155\n",
      "Epoch 175/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 132.0171 - root_mean_squared_error: 11.4899 - val_loss: 122.0763 - val_root_mean_squared_error: 11.0488\n",
      "Epoch 176/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 130.5310 - root_mean_squared_error: 11.4250 - val_loss: 120.8281 - val_root_mean_squared_error: 10.9922\n",
      "Epoch 177/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 129.1213 - root_mean_squared_error: 11.3632 - val_loss: 119.4869 - val_root_mean_squared_error: 10.9310\n",
      "Epoch 178/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 127.6622 - root_mean_squared_error: 11.2988 - val_loss: 118.1396 - val_root_mean_squared_error: 10.8692\n",
      "Epoch 179/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 126.1907 - root_mean_squared_error: 11.2335 - val_loss: 117.0040 - val_root_mean_squared_error: 10.8168\n",
      "Epoch 180/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 124.8173 - root_mean_squared_error: 11.1722 - val_loss: 115.7656 - val_root_mean_squared_error: 10.7594\n",
      "Epoch 181/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 123.4896 - root_mean_squared_error: 11.1126 - val_loss: 114.5147 - val_root_mean_squared_error: 10.7012\n",
      "Epoch 182/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 122.1037 - root_mean_squared_error: 11.0501 - val_loss: 113.3199 - val_root_mean_squared_error: 10.6452\n",
      "Epoch 183/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 120.7204 - root_mean_squared_error: 10.9873 - val_loss: 112.0367 - val_root_mean_squared_error: 10.5847\n",
      "Epoch 184/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 119.4201 - root_mean_squared_error: 10.9279 - val_loss: 110.7907 - val_root_mean_squared_error: 10.5257\n",
      "Epoch 185/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 118.0737 - root_mean_squared_error: 10.8662 - val_loss: 109.6662 - val_root_mean_squared_error: 10.4722\n",
      "Epoch 186/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 116.8152 - root_mean_squared_error: 10.8081 - val_loss: 108.4662 - val_root_mean_squared_error: 10.4147\n",
      "Epoch 187/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 115.5112 - root_mean_squared_error: 10.7476 - val_loss: 107.3725 - val_root_mean_squared_error: 10.3621\n",
      "Epoch 188/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 114.2915 - root_mean_squared_error: 10.6907 - val_loss: 106.0255 - val_root_mean_squared_error: 10.2969\n",
      "Epoch 189/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 113.0421 - root_mean_squared_error: 10.6321 - val_loss: 104.9560 - val_root_mean_squared_error: 10.2448\n",
      "Epoch 190/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 111.8560 - root_mean_squared_error: 10.5762 - val_loss: 103.8926 - val_root_mean_squared_error: 10.1928\n",
      "Epoch 191/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 110.7172 - root_mean_squared_error: 10.5222 - val_loss: 102.8960 - val_root_mean_squared_error: 10.1438\n",
      "Epoch 192/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 109.5217 - root_mean_squared_error: 10.4653 - val_loss: 101.8175 - val_root_mean_squared_error: 10.0905\n",
      "Epoch 193/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 108.3435 - root_mean_squared_error: 10.4088 - val_loss: 100.7705 - val_root_mean_squared_error: 10.0385\n",
      "Epoch 194/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 107.2206 - root_mean_squared_error: 10.3547 - val_loss: 99.8461 - val_root_mean_squared_error: 9.9923\n",
      "Epoch 195/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 106.0924 - root_mean_squared_error: 10.3001 - val_loss: 98.8511 - val_root_mean_squared_error: 9.9424\n",
      "Epoch 196/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 104.9901 - root_mean_squared_error: 10.2465 - val_loss: 97.7967 - val_root_mean_squared_error: 9.8892\n",
      "Epoch 197/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 103.9199 - root_mean_squared_error: 10.1941 - val_loss: 96.7363 - val_root_mean_squared_error: 9.8355\n",
      "Epoch 198/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 102.8333 - root_mean_squared_error: 10.1407 - val_loss: 95.8074 - val_root_mean_squared_error: 9.7881\n",
      "Epoch 199/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 101.8938 - root_mean_squared_error: 10.0942 - val_loss: 94.8636 - val_root_mean_squared_error: 9.7398\n",
      "Epoch 200/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 100.7544 - root_mean_squared_error: 10.0377 - val_loss: 93.9969 - val_root_mean_squared_error: 9.6952\n",
      "Epoch 201/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 99.7585 - root_mean_squared_error: 9.9879 - val_loss: 93.0937 - val_root_mean_squared_error: 9.6485\n",
      "Epoch 202/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 98.7727 - root_mean_squared_error: 9.9384 - val_loss: 92.1912 - val_root_mean_squared_error: 9.6016\n",
      "Epoch 203/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 97.7802 - root_mean_squared_error: 9.8884 - val_loss: 91.2118 - val_root_mean_squared_error: 9.5505\n",
      "Epoch 204/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 96.7912 - root_mean_squared_error: 9.8383 - val_loss: 90.3074 - val_root_mean_squared_error: 9.5030\n",
      "Epoch 205/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 95.7933 - root_mean_squared_error: 9.7874 - val_loss: 89.4739 - val_root_mean_squared_error: 9.4591\n",
      "Epoch 206/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 94.8509 - root_mean_squared_error: 9.7391 - val_loss: 88.6461 - val_root_mean_squared_error: 9.4152\n",
      "Epoch 207/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 93.9236 - root_mean_squared_error: 9.6914 - val_loss: 87.9304 - val_root_mean_squared_error: 9.3771\n",
      "Epoch 208/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 92.9927 - root_mean_squared_error: 9.6433 - val_loss: 87.1025 - val_root_mean_squared_error: 9.3329\n",
      "Epoch 209/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 92.0892 - root_mean_squared_error: 9.5963 - val_loss: 86.1693 - val_root_mean_squared_error: 9.2827\n",
      "Epoch 210/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 91.2001 - root_mean_squared_error: 9.5499 - val_loss: 85.2516 - val_root_mean_squared_error: 9.2332\n",
      "Epoch 211/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 90.2916 - root_mean_squared_error: 9.5022 - val_loss: 84.4870 - val_root_mean_squared_error: 9.1917\n",
      "Epoch 212/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 89.3460 - root_mean_squared_error: 9.4523 - val_loss: 83.7907 - val_root_mean_squared_error: 9.1537\n",
      "Epoch 213/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 88.5135 - root_mean_squared_error: 9.4082 - val_loss: 82.9397 - val_root_mean_squared_error: 9.1071\n",
      "Epoch 214/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 87.6622 - root_mean_squared_error: 9.3628 - val_loss: 82.2242 - val_root_mean_squared_error: 9.0678\n",
      "Epoch 215/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 86.8615 - root_mean_squared_error: 9.3200 - val_loss: 81.3743 - val_root_mean_squared_error: 9.0208\n",
      "Epoch 216/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 85.9523 - root_mean_squared_error: 9.2710 - val_loss: 80.7670 - val_root_mean_squared_error: 8.9870\n",
      "Epoch 217/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 85.2095 - root_mean_squared_error: 9.2309 - val_loss: 79.9688 - val_root_mean_squared_error: 8.9425\n",
      "Epoch 218/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 84.4022 - root_mean_squared_error: 9.1871 - val_loss: 79.2429 - val_root_mean_squared_error: 8.9018\n",
      "Epoch 219/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 83.5530 - root_mean_squared_error: 9.1407 - val_loss: 78.5324 - val_root_mean_squared_error: 8.8618\n",
      "Epoch 220/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 82.7831 - root_mean_squared_error: 9.0985 - val_loss: 77.7733 - val_root_mean_squared_error: 8.8189\n",
      "Epoch 221/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 81.9851 - root_mean_squared_error: 9.0546 - val_loss: 76.9984 - val_root_mean_squared_error: 8.7749\n",
      "Epoch 222/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 81.2121 - root_mean_squared_error: 9.0118 - val_loss: 76.2378 - val_root_mean_squared_error: 8.7314\n",
      "Epoch 223/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 80.4596 - root_mean_squared_error: 8.9699 - val_loss: 75.6657 - val_root_mean_squared_error: 8.6986\n",
      "Epoch 224/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 79.6841 - root_mean_squared_error: 8.9266 - val_loss: 74.9768 - val_root_mean_squared_error: 8.6589\n",
      "Epoch 225/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 78.9220 - root_mean_squared_error: 8.8838 - val_loss: 74.2313 - val_root_mean_squared_error: 8.6158\n",
      "Epoch 226/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 78.2492 - root_mean_squared_error: 8.8459 - val_loss: 73.5148 - val_root_mean_squared_error: 8.5741\n",
      "Epoch 227/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 77.5017 - root_mean_squared_error: 8.8035 - val_loss: 72.9085 - val_root_mean_squared_error: 8.5386\n",
      "Epoch 228/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17/17 [==============================] - 0s 3ms/step - loss: 76.7900 - root_mean_squared_error: 8.7630 - val_loss: 72.2635 - val_root_mean_squared_error: 8.5008\n",
      "Epoch 229/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 76.0641 - root_mean_squared_error: 8.7215 - val_loss: 71.6051 - val_root_mean_squared_error: 8.4620\n",
      "Epoch 230/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 75.3736 - root_mean_squared_error: 8.6818 - val_loss: 71.0424 - val_root_mean_squared_error: 8.4287\n",
      "Epoch 231/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 74.7095 - root_mean_squared_error: 8.6435 - val_loss: 70.3156 - val_root_mean_squared_error: 8.3854\n",
      "Epoch 232/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 74.0125 - root_mean_squared_error: 8.6031 - val_loss: 69.7360 - val_root_mean_squared_error: 8.3508\n",
      "Epoch 233/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 73.3330 - root_mean_squared_error: 8.5635 - val_loss: 68.9644 - val_root_mean_squared_error: 8.3045\n",
      "Epoch 234/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 72.6717 - root_mean_squared_error: 8.5248 - val_loss: 68.3932 - val_root_mean_squared_error: 8.2700\n",
      "Epoch 235/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 72.0196 - root_mean_squared_error: 8.4864 - val_loss: 67.8825 - val_root_mean_squared_error: 8.2391\n",
      "Epoch 236/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 71.3775 - root_mean_squared_error: 8.4485 - val_loss: 67.3099 - val_root_mean_squared_error: 8.2043\n",
      "Epoch 237/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 70.7436 - root_mean_squared_error: 8.4109 - val_loss: 66.5832 - val_root_mean_squared_error: 8.1599\n",
      "Epoch 238/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 70.1746 - root_mean_squared_error: 8.3770 - val_loss: 66.1029 - val_root_mean_squared_error: 8.1304\n",
      "Epoch 239/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 69.4616 - root_mean_squared_error: 8.3344 - val_loss: 65.4229 - val_root_mean_squared_error: 8.0884\n",
      "Epoch 240/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 68.9032 - root_mean_squared_error: 8.3008 - val_loss: 64.9166 - val_root_mean_squared_error: 8.0571\n",
      "Epoch 241/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 68.2593 - root_mean_squared_error: 8.2619 - val_loss: 64.4638 - val_root_mean_squared_error: 8.0289\n",
      "Epoch 242/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 67.6634 - root_mean_squared_error: 8.2258 - val_loss: 63.8876 - val_root_mean_squared_error: 7.9930\n",
      "Epoch 243/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 67.0396 - root_mean_squared_error: 8.1878 - val_loss: 63.2237 - val_root_mean_squared_error: 7.9513\n",
      "Epoch 244/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 66.5046 - root_mean_squared_error: 8.1550 - val_loss: 62.5915 - val_root_mean_squared_error: 7.9115\n",
      "Epoch 245/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 65.8723 - root_mean_squared_error: 8.1162 - val_loss: 62.1610 - val_root_mean_squared_error: 7.8842\n",
      "Epoch 246/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 65.3044 - root_mean_squared_error: 8.0811 - val_loss: 61.6879 - val_root_mean_squared_error: 7.8542\n",
      "Epoch 247/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 64.7233 - root_mean_squared_error: 8.0451 - val_loss: 61.1454 - val_root_mean_squared_error: 7.8196\n",
      "Epoch 248/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 64.1865 - root_mean_squared_error: 8.0116 - val_loss: 60.6397 - val_root_mean_squared_error: 7.7871\n",
      "Epoch 249/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 63.6042 - root_mean_squared_error: 7.9752 - val_loss: 60.0745 - val_root_mean_squared_error: 7.7508\n",
      "Epoch 250/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 63.0599 - root_mean_squared_error: 7.9410 - val_loss: 59.5604 - val_root_mean_squared_error: 7.7175\n",
      "Epoch 251/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 62.4977 - root_mean_squared_error: 7.9056 - val_loss: 59.1434 - val_root_mean_squared_error: 7.6905\n",
      "Epoch 252/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 61.9533 - root_mean_squared_error: 7.8710 - val_loss: 58.6070 - val_root_mean_squared_error: 7.6555\n",
      "Epoch 253/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 61.4504 - root_mean_squared_error: 7.8390 - val_loss: 58.2021 - val_root_mean_squared_error: 7.6290\n",
      "Epoch 254/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 60.9564 - root_mean_squared_error: 7.8075 - val_loss: 57.5916 - val_root_mean_squared_error: 7.5889\n",
      "Epoch 255/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 60.3840 - root_mean_squared_error: 7.7707 - val_loss: 57.2122 - val_root_mean_squared_error: 7.5639\n",
      "Epoch 256/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 59.9109 - root_mean_squared_error: 7.7402 - val_loss: 56.7607 - val_root_mean_squared_error: 7.5340\n",
      "Epoch 257/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 59.3951 - root_mean_squared_error: 7.7068 - val_loss: 56.1992 - val_root_mean_squared_error: 7.4966\n",
      "Epoch 258/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 58.9283 - root_mean_squared_error: 7.6765 - val_loss: 55.8622 - val_root_mean_squared_error: 7.4741\n",
      "Epoch 259/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 58.4089 - root_mean_squared_error: 7.6426 - val_loss: 55.3256 - val_root_mean_squared_error: 7.4381\n",
      "Epoch 260/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 57.9373 - root_mean_squared_error: 7.6117 - val_loss: 54.9266 - val_root_mean_squared_error: 7.4112\n",
      "Epoch 261/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 57.4663 - root_mean_squared_error: 7.5807 - val_loss: 54.4903 - val_root_mean_squared_error: 7.3818\n",
      "Epoch 262/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 57.0815 - root_mean_squared_error: 7.5552 - val_loss: 53.9187 - val_root_mean_squared_error: 7.3429\n",
      "Epoch 263/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 56.6063 - root_mean_squared_error: 7.5237 - val_loss: 53.7034 - val_root_mean_squared_error: 7.3283\n",
      "Epoch 264/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 56.0832 - root_mean_squared_error: 7.4889 - val_loss: 53.1933 - val_root_mean_squared_error: 7.2934\n",
      "Epoch 265/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 55.6466 - root_mean_squared_error: 7.4597 - val_loss: 52.7421 - val_root_mean_squared_error: 7.2624\n",
      "Epoch 266/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 55.1833 - root_mean_squared_error: 7.4285 - val_loss: 52.2478 - val_root_mean_squared_error: 7.2283\n",
      "Epoch 267/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 54.7385 - root_mean_squared_error: 7.3985 - val_loss: 51.8841 - val_root_mean_squared_error: 7.2031\n",
      "Epoch 268/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 54.3343 - root_mean_squared_error: 7.3712 - val_loss: 51.4387 - val_root_mean_squared_error: 7.1721\n",
      "Epoch 269/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 53.9210 - root_mean_squared_error: 7.3431 - val_loss: 51.1191 - val_root_mean_squared_error: 7.1498\n",
      "Epoch 270/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 53.4978 - root_mean_squared_error: 7.3142 - val_loss: 50.6564 - val_root_mean_squared_error: 7.1173\n",
      "Epoch 271/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 53.0486 - root_mean_squared_error: 7.2834 - val_loss: 50.3893 - val_root_mean_squared_error: 7.0985\n",
      "Epoch 272/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 52.6518 - root_mean_squared_error: 7.2562 - val_loss: 49.9818 - val_root_mean_squared_error: 7.0698\n",
      "Epoch 273/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 52.2258 - root_mean_squared_error: 7.2267 - val_loss: 49.5172 - val_root_mean_squared_error: 7.0368\n",
      "Epoch 274/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 51.8969 - root_mean_squared_error: 7.2040 - val_loss: 49.0568 - val_root_mean_squared_error: 7.0041\n",
      "Epoch 275/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 51.4379 - root_mean_squared_error: 7.1720 - val_loss: 48.8753 - val_root_mean_squared_error: 6.9911\n",
      "Epoch 276/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 51.0511 - root_mean_squared_error: 7.1450 - val_loss: 48.4603 - val_root_mean_squared_error: 6.9613\n",
      "Epoch 277/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 50.6599 - root_mean_squared_error: 7.1176 - val_loss: 48.0386 - val_root_mean_squared_error: 6.9310\n",
      "Epoch 278/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 50.2809 - root_mean_squared_error: 7.0909 - val_loss: 47.6521 - val_root_mean_squared_error: 6.9031\n",
      "Epoch 279/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 49.9255 - root_mean_squared_error: 7.0658 - val_loss: 47.2663 - val_root_mean_squared_error: 6.8751\n",
      "Epoch 280/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 49.5718 - root_mean_squared_error: 7.0407 - val_loss: 46.9142 - val_root_mean_squared_error: 6.8494\n",
      "Epoch 281/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 49.1770 - root_mean_squared_error: 7.0126 - val_loss: 46.6421 - val_root_mean_squared_error: 6.8295\n",
      "Epoch 282/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 48.8239 - root_mean_squared_error: 6.9874 - val_loss: 46.2408 - val_root_mean_squared_error: 6.8001\n",
      "Epoch 283/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 48.4821 - root_mean_squared_error: 6.9629 - val_loss: 46.0253 - val_root_mean_squared_error: 6.7842\n",
      "Epoch 284/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 48.1305 - root_mean_squared_error: 6.9376 - val_loss: 45.5851 - val_root_mean_squared_error: 6.7517\n",
      "Epoch 285/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 47.7572 - root_mean_squared_error: 6.9107 - val_loss: 45.2686 - val_root_mean_squared_error: 6.7282\n",
      "Epoch 286/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 47.4372 - root_mean_squared_error: 6.8875 - val_loss: 44.9200 - val_root_mean_squared_error: 6.7022\n",
      "Epoch 287/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 47.0913 - root_mean_squared_error: 6.8623 - val_loss: 44.5336 - val_root_mean_squared_error: 6.6733\n",
      "Epoch 288/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 46.7849 - root_mean_squared_error: 6.8400 - val_loss: 44.2639 - val_root_mean_squared_error: 6.6531\n",
      "Epoch 289/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 46.4544 - root_mean_squared_error: 6.8157 - val_loss: 43.9967 - val_root_mean_squared_error: 6.6330\n",
      "Epoch 290/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 46.1299 - root_mean_squared_error: 6.7919 - val_loss: 43.5851 - val_root_mean_squared_error: 6.6019\n",
      "Epoch 291/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 45.7910 - root_mean_squared_error: 6.7669 - val_loss: 43.2810 - val_root_mean_squared_error: 6.5788\n",
      "Epoch 292/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 45.4527 - root_mean_squared_error: 6.7419 - val_loss: 43.1305 - val_root_mean_squared_error: 6.5674\n",
      "Epoch 293/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 45.1210 - root_mean_squared_error: 6.7172 - val_loss: 42.7989 - val_root_mean_squared_error: 6.5421\n",
      "Epoch 294/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 44.8324 - root_mean_squared_error: 6.6957 - val_loss: 42.5362 - val_root_mean_squared_error: 6.5220\n",
      "Epoch 295/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 44.5672 - root_mean_squared_error: 6.6759 - val_loss: 42.1661 - val_root_mean_squared_error: 6.4935\n",
      "Epoch 296/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 44.2318 - root_mean_squared_error: 6.6507 - val_loss: 41.9760 - val_root_mean_squared_error: 6.4789\n",
      "Epoch 297/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 43.9257 - root_mean_squared_error: 6.6276 - val_loss: 41.6022 - val_root_mean_squared_error: 6.4500\n",
      "Epoch 298/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 43.6414 - root_mean_squared_error: 6.6062 - val_loss: 41.3045 - val_root_mean_squared_error: 6.4269\n",
      "Epoch 299/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 43.4018 - root_mean_squared_error: 6.5880 - val_loss: 41.0883 - val_root_mean_squared_error: 6.4100\n",
      "Epoch 300/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 43.0932 - root_mean_squared_error: 6.5645 - val_loss: 40.8125 - val_root_mean_squared_error: 6.3885\n",
      "Epoch 301/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 42.7860 - root_mean_squared_error: 6.5411 - val_loss: 40.5931 - val_root_mean_squared_error: 6.3713\n",
      "Epoch 302/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 42.5418 - root_mean_squared_error: 6.5224 - val_loss: 40.1862 - val_root_mean_squared_error: 6.3393\n",
      "Epoch 303/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 42.2923 - root_mean_squared_error: 6.5033 - val_loss: 40.0047 - val_root_mean_squared_error: 6.3249\n",
      "Epoch 304/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 42.0152 - root_mean_squared_error: 6.4819 - val_loss: 39.7133 - val_root_mean_squared_error: 6.3018\n",
      "Epoch 305/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 41.7126 - root_mean_squared_error: 6.4585 - val_loss: 39.5592 - val_root_mean_squared_error: 6.2896\n",
      "Epoch 306/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 41.4447 - root_mean_squared_error: 6.4378 - val_loss: 39.3163 - val_root_mean_squared_error: 6.2703\n",
      "Epoch 307/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 41.1692 - root_mean_squared_error: 6.4163 - val_loss: 39.0697 - val_root_mean_squared_error: 6.2506\n",
      "Epoch 308/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 40.9230 - root_mean_squared_error: 6.3971 - val_loss: 38.6941 - val_root_mean_squared_error: 6.2205\n",
      "Epoch 309/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 40.7645 - root_mean_squared_error: 6.3847 - val_loss: 38.6289 - val_root_mean_squared_error: 6.2152\n",
      "Epoch 310/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 40.4720 - root_mean_squared_error: 6.3618 - val_loss: 38.5505 - val_root_mean_squared_error: 6.2089\n",
      "Epoch 311/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 40.2132 - root_mean_squared_error: 6.3414 - val_loss: 38.0962 - val_root_mean_squared_error: 6.1722\n",
      "Epoch 312/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 39.9732 - root_mean_squared_error: 6.3224 - val_loss: 37.8803 - val_root_mean_squared_error: 6.1547\n",
      "Epoch 313/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 39.7093 - root_mean_squared_error: 6.3015 - val_loss: 37.5872 - val_root_mean_squared_error: 6.1308\n",
      "Epoch 314/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 39.5029 - root_mean_squared_error: 6.2851 - val_loss: 37.4308 - val_root_mean_squared_error: 6.1181\n",
      "Epoch 315/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 39.2405 - root_mean_squared_error: 6.2642 - val_loss: 37.1144 - val_root_mean_squared_error: 6.0922\n",
      "Epoch 316/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 39.0031 - root_mean_squared_error: 6.2452 - val_loss: 36.8649 - val_root_mean_squared_error: 6.0716\n",
      "Epoch 317/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 38.8304 - root_mean_squared_error: 6.2314 - val_loss: 36.5893 - val_root_mean_squared_error: 6.0489\n",
      "Epoch 318/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 38.5306 - root_mean_squared_error: 6.2073 - val_loss: 36.4397 - val_root_mean_squared_error: 6.0365\n",
      "Epoch 319/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 38.3594 - root_mean_squared_error: 6.1935 - val_loss: 36.2855 - val_root_mean_squared_error: 6.0237\n",
      "Epoch 320/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17/17 [==============================] - 0s 2ms/step - loss: 38.0861 - root_mean_squared_error: 6.1714 - val_loss: 35.9703 - val_root_mean_squared_error: 5.9975\n",
      "Epoch 321/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 37.8726 - root_mean_squared_error: 6.1541 - val_loss: 35.9314 - val_root_mean_squared_error: 5.9943\n",
      "Epoch 322/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 37.6228 - root_mean_squared_error: 6.1337 - val_loss: 35.6366 - val_root_mean_squared_error: 5.9696\n",
      "Epoch 323/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 37.3803 - root_mean_squared_error: 6.1139 - val_loss: 35.3911 - val_root_mean_squared_error: 5.9490\n",
      "Epoch 324/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 37.1997 - root_mean_squared_error: 6.0992 - val_loss: 35.0781 - val_root_mean_squared_error: 5.9227\n",
      "Epoch 325/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 36.9105 - root_mean_squared_error: 6.0754 - val_loss: 34.8809 - val_root_mean_squared_error: 5.9060\n",
      "Epoch 326/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 36.6868 - root_mean_squared_error: 6.0570 - val_loss: 34.7056 - val_root_mean_squared_error: 5.8911\n",
      "Epoch 327/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 36.3847 - root_mean_squared_error: 6.0320 - val_loss: 34.4727 - val_root_mean_squared_error: 5.8713\n",
      "Epoch 328/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 36.1595 - root_mean_squared_error: 6.0133 - val_loss: 34.2891 - val_root_mean_squared_error: 5.8557\n",
      "Epoch 329/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 35.9406 - root_mean_squared_error: 5.9951 - val_loss: 34.0220 - val_root_mean_squared_error: 5.8328\n",
      "Epoch 330/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 35.7192 - root_mean_squared_error: 5.9766 - val_loss: 33.7722 - val_root_mean_squared_error: 5.8114\n",
      "Epoch 331/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 35.4862 - root_mean_squared_error: 5.9570 - val_loss: 33.5233 - val_root_mean_squared_error: 5.7899\n",
      "Epoch 332/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 35.2115 - root_mean_squared_error: 5.9339 - val_loss: 33.2542 - val_root_mean_squared_error: 5.7666\n",
      "Epoch 333/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 34.9926 - root_mean_squared_error: 5.9155 - val_loss: 33.0236 - val_root_mean_squared_error: 5.7466\n",
      "Epoch 334/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 34.7753 - root_mean_squared_error: 5.8971 - val_loss: 32.9130 - val_root_mean_squared_error: 5.7370\n",
      "Epoch 335/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 34.5522 - root_mean_squared_error: 5.8781 - val_loss: 32.6822 - val_root_mean_squared_error: 5.7168\n",
      "Epoch 336/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 34.3107 - root_mean_squared_error: 5.8575 - val_loss: 32.3756 - val_root_mean_squared_error: 5.6900\n",
      "Epoch 337/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 34.1139 - root_mean_squared_error: 5.8407 - val_loss: 32.0900 - val_root_mean_squared_error: 5.6648\n",
      "Epoch 338/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 33.9243 - root_mean_squared_error: 5.8245 - val_loss: 32.0348 - val_root_mean_squared_error: 5.6599\n",
      "Epoch 339/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 33.6390 - root_mean_squared_error: 5.7999 - val_loss: 31.9144 - val_root_mean_squared_error: 5.6493\n",
      "Epoch 340/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 33.4649 - root_mean_squared_error: 5.7849 - val_loss: 31.5995 - val_root_mean_squared_error: 5.6213\n",
      "Epoch 341/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 33.1629 - root_mean_squared_error: 5.7587 - val_loss: 31.3025 - val_root_mean_squared_error: 5.5949\n",
      "Epoch 342/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 32.9315 - root_mean_squared_error: 5.7386 - val_loss: 31.0444 - val_root_mean_squared_error: 5.5718\n",
      "Epoch 343/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 32.7193 - root_mean_squared_error: 5.7201 - val_loss: 30.8891 - val_root_mean_squared_error: 5.5578\n",
      "Epoch 344/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 32.4797 - root_mean_squared_error: 5.6991 - val_loss: 30.6889 - val_root_mean_squared_error: 5.5398\n",
      "Epoch 345/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 32.3557 - root_mean_squared_error: 5.6882 - val_loss: 30.3805 - val_root_mean_squared_error: 5.5119\n",
      "Epoch 346/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 31.9864 - root_mean_squared_error: 5.6557 - val_loss: 30.2248 - val_root_mean_squared_error: 5.4977\n",
      "Epoch 347/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 31.7781 - root_mean_squared_error: 5.6372 - val_loss: 29.9938 - val_root_mean_squared_error: 5.4767\n",
      "Epoch 348/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 31.5335 - root_mean_squared_error: 5.6155 - val_loss: 29.8740 - val_root_mean_squared_error: 5.4657\n",
      "Epoch 349/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 31.3311 - root_mean_squared_error: 5.5974 - val_loss: 29.5981 - val_root_mean_squared_error: 5.4404\n",
      "Epoch 350/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 31.0635 - root_mean_squared_error: 5.5735 - val_loss: 29.3075 - val_root_mean_squared_error: 5.4136\n",
      "Epoch 351/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 30.8764 - root_mean_squared_error: 5.5567 - val_loss: 29.1683 - val_root_mean_squared_error: 5.4008\n",
      "Epoch 352/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 30.6865 - root_mean_squared_error: 5.5395 - val_loss: 28.9846 - val_root_mean_squared_error: 5.3837\n",
      "Epoch 353/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 30.4071 - root_mean_squared_error: 5.5143 - val_loss: 28.5410 - val_root_mean_squared_error: 5.3424\n",
      "Epoch 354/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 30.1726 - root_mean_squared_error: 5.4930 - val_loss: 28.4170 - val_root_mean_squared_error: 5.3308\n",
      "Epoch 355/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 29.9404 - root_mean_squared_error: 5.4718 - val_loss: 28.1473 - val_root_mean_squared_error: 5.3054\n",
      "Epoch 356/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 29.6500 - root_mean_squared_error: 5.4452 - val_loss: 27.9971 - val_root_mean_squared_error: 5.2912\n",
      "Epoch 357/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 29.4294 - root_mean_squared_error: 5.4249 - val_loss: 27.7718 - val_root_mean_squared_error: 5.2699\n",
      "Epoch 358/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 29.1954 - root_mean_squared_error: 5.4033 - val_loss: 27.5512 - val_root_mean_squared_error: 5.2489\n",
      "Epoch 359/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 28.9630 - root_mean_squared_error: 5.3817 - val_loss: 27.1913 - val_root_mean_squared_error: 5.2145\n",
      "Epoch 360/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 28.7330 - root_mean_squared_error: 5.3603 - val_loss: 27.1560 - val_root_mean_squared_error: 5.2111\n",
      "Epoch 361/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 28.4718 - root_mean_squared_error: 5.3359 - val_loss: 26.8825 - val_root_mean_squared_error: 5.1848\n",
      "Epoch 362/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 28.2656 - root_mean_squared_error: 5.3165 - val_loss: 26.6868 - val_root_mean_squared_error: 5.1659\n",
      "Epoch 363/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 28.0420 - root_mean_squared_error: 5.2955 - val_loss: 26.4475 - val_root_mean_squared_error: 5.1427\n",
      "Epoch 364/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 27.7829 - root_mean_squared_error: 5.2710 - val_loss: 26.2734 - val_root_mean_squared_error: 5.1258\n",
      "Epoch 365/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 27.6101 - root_mean_squared_error: 5.2545 - val_loss: 25.9762 - val_root_mean_squared_error: 5.0967\n",
      "Epoch 366/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 27.3333 - root_mean_squared_error: 5.2281 - val_loss: 25.8135 - val_root_mean_squared_error: 5.0807\n",
      "Epoch 367/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 27.1439 - root_mean_squared_error: 5.2100 - val_loss: 25.6378 - val_root_mean_squared_error: 5.0634\n",
      "Epoch 368/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 26.9243 - root_mean_squared_error: 5.1889 - val_loss: 25.3060 - val_root_mean_squared_error: 5.0305\n",
      "Epoch 369/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 26.6740 - root_mean_squared_error: 5.1647 - val_loss: 25.1255 - val_root_mean_squared_error: 5.0125\n",
      "Epoch 370/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 26.4340 - root_mean_squared_error: 5.1414 - val_loss: 24.8825 - val_root_mean_squared_error: 4.9882\n",
      "Epoch 371/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 26.2275 - root_mean_squared_error: 5.1213 - val_loss: 24.7749 - val_root_mean_squared_error: 4.9774\n",
      "Epoch 372/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 26.0274 - root_mean_squared_error: 5.1017 - val_loss: 24.6318 - val_root_mean_squared_error: 4.9630\n",
      "Epoch 373/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 25.7904 - root_mean_squared_error: 5.0784 - val_loss: 24.3437 - val_root_mean_squared_error: 4.9339\n",
      "Epoch 374/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 25.6071 - root_mean_squared_error: 5.0603 - val_loss: 24.1750 - val_root_mean_squared_error: 4.9168\n",
      "Epoch 375/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 25.4490 - root_mean_squared_error: 5.0447 - val_loss: 23.8107 - val_root_mean_squared_error: 4.8796\n",
      "Epoch 376/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 25.1569 - root_mean_squared_error: 5.0157 - val_loss: 23.6897 - val_root_mean_squared_error: 4.8672\n",
      "Epoch 377/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 24.9483 - root_mean_squared_error: 4.9948 - val_loss: 23.5541 - val_root_mean_squared_error: 4.8533\n",
      "Epoch 378/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 24.7701 - root_mean_squared_error: 4.9770 - val_loss: 23.2231 - val_root_mean_squared_error: 4.8190\n",
      "Epoch 379/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 24.4968 - root_mean_squared_error: 4.9494 - val_loss: 23.1807 - val_root_mean_squared_error: 4.8146\n",
      "Epoch 380/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 24.3584 - root_mean_squared_error: 4.9354 - val_loss: 22.9814 - val_root_mean_squared_error: 4.7939\n",
      "Epoch 381/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 24.3057 - root_mean_squared_error: 4.9301 - val_loss: 22.7222 - val_root_mean_squared_error: 4.7668\n",
      "Epoch 382/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 23.9562 - root_mean_squared_error: 4.8945 - val_loss: 22.5956 - val_root_mean_squared_error: 4.7535\n",
      "Epoch 383/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 23.7429 - root_mean_squared_error: 4.8727 - val_loss: 22.4239 - val_root_mean_squared_error: 4.7354\n",
      "Epoch 384/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 23.5414 - root_mean_squared_error: 4.8519 - val_loss: 22.0930 - val_root_mean_squared_error: 4.7003\n",
      "Epoch 385/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 23.3216 - root_mean_squared_error: 4.8292 - val_loss: 21.9561 - val_root_mean_squared_error: 4.6857\n",
      "Epoch 386/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 23.1783 - root_mean_squared_error: 4.8144 - val_loss: 21.8101 - val_root_mean_squared_error: 4.6701\n",
      "Epoch 387/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 22.9536 - root_mean_squared_error: 4.7910 - val_loss: 21.5916 - val_root_mean_squared_error: 4.6467\n",
      "Epoch 388/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 22.7998 - root_mean_squared_error: 4.7749 - val_loss: 21.4179 - val_root_mean_squared_error: 4.6279\n",
      "Epoch 389/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 22.6394 - root_mean_squared_error: 4.7581 - val_loss: 21.1877 - val_root_mean_squared_error: 4.6030\n",
      "Epoch 390/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 22.4128 - root_mean_squared_error: 4.7342 - val_loss: 21.1483 - val_root_mean_squared_error: 4.5987\n",
      "Epoch 391/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 22.2109 - root_mean_squared_error: 4.7128 - val_loss: 20.9163 - val_root_mean_squared_error: 4.5734\n",
      "Epoch 392/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 22.0346 - root_mean_squared_error: 4.6941 - val_loss: 20.7169 - val_root_mean_squared_error: 4.5516\n",
      "Epoch 393/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 21.8675 - root_mean_squared_error: 4.6763 - val_loss: 20.5527 - val_root_mean_squared_error: 4.5335\n",
      "Epoch 394/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 21.6880 - root_mean_squared_error: 4.6570 - val_loss: 20.2734 - val_root_mean_squared_error: 4.5026\n",
      "Epoch 395/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 21.5220 - root_mean_squared_error: 4.6392 - val_loss: 20.2019 - val_root_mean_squared_error: 4.4946\n",
      "Epoch 396/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 21.3479 - root_mean_squared_error: 4.6204 - val_loss: 19.9067 - val_root_mean_squared_error: 4.4617\n",
      "Epoch 397/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 21.1847 - root_mean_squared_error: 4.6027 - val_loss: 19.9380 - val_root_mean_squared_error: 4.4652\n",
      "Epoch 398/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 20.9956 - root_mean_squared_error: 4.5821 - val_loss: 19.7083 - val_root_mean_squared_error: 4.4394\n",
      "Epoch 399/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 20.8665 - root_mean_squared_error: 4.5680 - val_loss: 19.4708 - val_root_mean_squared_error: 4.4126\n",
      "Epoch 400/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 20.6901 - root_mean_squared_error: 4.5486 - val_loss: 19.3869 - val_root_mean_squared_error: 4.4031\n",
      "Epoch 401/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 20.5071 - root_mean_squared_error: 4.5285 - val_loss: 19.2385 - val_root_mean_squared_error: 4.3862\n",
      "Epoch 402/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 20.3495 - root_mean_squared_error: 4.5110 - val_loss: 18.9986 - val_root_mean_squared_error: 4.3587\n",
      "Epoch 403/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 20.2279 - root_mean_squared_error: 4.4975 - val_loss: 18.9028 - val_root_mean_squared_error: 4.3477\n",
      "Epoch 404/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 20.1155 - root_mean_squared_error: 4.4850 - val_loss: 18.7930 - val_root_mean_squared_error: 4.3351\n",
      "Epoch 405/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 19.8837 - root_mean_squared_error: 4.4591 - val_loss: 18.5745 - val_root_mean_squared_error: 4.3098\n",
      "Epoch 406/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 19.6964 - root_mean_squared_error: 4.4381 - val_loss: 18.4566 - val_root_mean_squared_error: 4.2961\n",
      "Epoch 407/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 19.5614 - root_mean_squared_error: 4.4228 - val_loss: 18.3375 - val_root_mean_squared_error: 4.2822\n",
      "Epoch 408/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 19.4503 - root_mean_squared_error: 4.4103 - val_loss: 18.1981 - val_root_mean_squared_error: 4.2659\n",
      "Epoch 409/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 19.2854 - root_mean_squared_error: 4.3915 - val_loss: 18.1459 - val_root_mean_squared_error: 4.2598\n",
      "Epoch 410/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 19.1262 - root_mean_squared_error: 4.3733 - val_loss: 17.8373 - val_root_mean_squared_error: 4.2234\n",
      "Epoch 411/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 19.0500 - root_mean_squared_error: 4.3646 - val_loss: 17.8881 - val_root_mean_squared_error: 4.2294\n",
      "Epoch 412/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17/17 [==============================] - 0s 2ms/step - loss: 18.8182 - root_mean_squared_error: 4.3380 - val_loss: 17.5505 - val_root_mean_squared_error: 4.1893\n",
      "Epoch 413/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 18.6967 - root_mean_squared_error: 4.3240 - val_loss: 17.6260 - val_root_mean_squared_error: 4.1983\n",
      "Epoch 414/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 18.5187 - root_mean_squared_error: 4.3033 - val_loss: 17.3590 - val_root_mean_squared_error: 4.1664\n",
      "Epoch 415/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 18.3827 - root_mean_squared_error: 4.2875 - val_loss: 17.1960 - val_root_mean_squared_error: 4.1468\n",
      "Epoch 416/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 18.2344 - root_mean_squared_error: 4.2702 - val_loss: 17.0465 - val_root_mean_squared_error: 4.1287\n",
      "Epoch 417/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 18.1193 - root_mean_squared_error: 4.2567 - val_loss: 16.9816 - val_root_mean_squared_error: 4.1209\n",
      "Epoch 418/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 17.9524 - root_mean_squared_error: 4.2370 - val_loss: 16.8045 - val_root_mean_squared_error: 4.0993\n",
      "Epoch 419/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 17.9008 - root_mean_squared_error: 4.2309 - val_loss: 16.6791 - val_root_mean_squared_error: 4.0840\n",
      "Epoch 420/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 17.6684 - root_mean_squared_error: 4.2034 - val_loss: 16.6448 - val_root_mean_squared_error: 4.0798\n",
      "Epoch 421/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 17.6406 - root_mean_squared_error: 4.2001 - val_loss: 16.5946 - val_root_mean_squared_error: 4.0736\n",
      "Epoch 422/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 17.4171 - root_mean_squared_error: 4.1734 - val_loss: 16.3420 - val_root_mean_squared_error: 4.0425\n",
      "Epoch 423/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 17.2944 - root_mean_squared_error: 4.1587 - val_loss: 16.2130 - val_root_mean_squared_error: 4.0265\n",
      "Epoch 424/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 17.1561 - root_mean_squared_error: 4.1420 - val_loss: 16.1133 - val_root_mean_squared_error: 4.0141\n",
      "Epoch 425/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 17.0853 - root_mean_squared_error: 4.1334 - val_loss: 16.0458 - val_root_mean_squared_error: 4.0057\n",
      "Epoch 426/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 16.9039 - root_mean_squared_error: 4.1114 - val_loss: 15.7767 - val_root_mean_squared_error: 3.9720\n",
      "Epoch 427/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 16.8125 - root_mean_squared_error: 4.1003 - val_loss: 15.7746 - val_root_mean_squared_error: 3.9717\n",
      "Epoch 428/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 16.8189 - root_mean_squared_error: 4.1011 - val_loss: 15.8099 - val_root_mean_squared_error: 3.9762\n",
      "Epoch 429/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 16.6187 - root_mean_squared_error: 4.0766 - val_loss: 15.5918 - val_root_mean_squared_error: 3.9486\n",
      "Epoch 430/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 16.4458 - root_mean_squared_error: 4.0553 - val_loss: 15.5296 - val_root_mean_squared_error: 3.9408\n",
      "Epoch 431/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 16.3778 - root_mean_squared_error: 4.0470 - val_loss: 15.3306 - val_root_mean_squared_error: 3.9154\n",
      "Epoch 432/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 16.2317 - root_mean_squared_error: 4.0289 - val_loss: 15.2915 - val_root_mean_squared_error: 3.9104\n",
      "Epoch 433/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 16.1217 - root_mean_squared_error: 4.0152 - val_loss: 15.1377 - val_root_mean_squared_error: 3.8907\n",
      "Epoch 434/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 16.1088 - root_mean_squared_error: 4.0136 - val_loss: 15.1509 - val_root_mean_squared_error: 3.8924\n",
      "Epoch 435/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 15.9326 - root_mean_squared_error: 3.9916 - val_loss: 15.0352 - val_root_mean_squared_error: 3.8775\n",
      "Epoch 436/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 15.8640 - root_mean_squared_error: 3.9830 - val_loss: 14.8187 - val_root_mean_squared_error: 3.8495\n",
      "Epoch 437/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 15.6794 - root_mean_squared_error: 3.9597 - val_loss: 14.8732 - val_root_mean_squared_error: 3.8566\n",
      "Epoch 438/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 15.6429 - root_mean_squared_error: 3.9551 - val_loss: 14.6938 - val_root_mean_squared_error: 3.8333\n",
      "Epoch 439/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 15.5269 - root_mean_squared_error: 3.9404 - val_loss: 14.7120 - val_root_mean_squared_error: 3.8356\n",
      "Epoch 440/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 15.3988 - root_mean_squared_error: 3.9241 - val_loss: 14.5238 - val_root_mean_squared_error: 3.8110\n",
      "Epoch 441/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 15.3321 - root_mean_squared_error: 3.9156 - val_loss: 14.5252 - val_root_mean_squared_error: 3.8112\n",
      "Epoch 442/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 15.2171 - root_mean_squared_error: 3.9009 - val_loss: 14.3558 - val_root_mean_squared_error: 3.7889\n",
      "Epoch 443/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 15.1437 - root_mean_squared_error: 3.8915 - val_loss: 14.3423 - val_root_mean_squared_error: 3.7871\n",
      "Epoch 444/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 15.0219 - root_mean_squared_error: 3.8758 - val_loss: 14.2178 - val_root_mean_squared_error: 3.7707\n",
      "Epoch 445/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 15.0302 - root_mean_squared_error: 3.8769 - val_loss: 14.0615 - val_root_mean_squared_error: 3.7499\n",
      "Epoch 446/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 14.9661 - root_mean_squared_error: 3.8686 - val_loss: 14.1278 - val_root_mean_squared_error: 3.7587\n",
      "Epoch 447/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 14.8128 - root_mean_squared_error: 3.8487 - val_loss: 13.9078 - val_root_mean_squared_error: 3.7293\n",
      "Epoch 448/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 14.7244 - root_mean_squared_error: 3.8372 - val_loss: 14.0056 - val_root_mean_squared_error: 3.7424\n",
      "Epoch 449/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 14.5899 - root_mean_squared_error: 3.8197 - val_loss: 13.7533 - val_root_mean_squared_error: 3.7085\n",
      "Epoch 450/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 14.5371 - root_mean_squared_error: 3.8128 - val_loss: 13.7156 - val_root_mean_squared_error: 3.7035\n",
      "Epoch 451/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 14.4664 - root_mean_squared_error: 3.8035 - val_loss: 13.7517 - val_root_mean_squared_error: 3.7083\n",
      "Epoch 452/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 14.3766 - root_mean_squared_error: 3.7917 - val_loss: 13.5653 - val_root_mean_squared_error: 3.6831\n",
      "Epoch 453/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 14.2658 - root_mean_squared_error: 3.7770 - val_loss: 13.6224 - val_root_mean_squared_error: 3.6909\n",
      "Epoch 454/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 14.1916 - root_mean_squared_error: 3.7672 - val_loss: 13.4473 - val_root_mean_squared_error: 3.6671\n",
      "Epoch 455/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 14.1417 - root_mean_squared_error: 3.7605 - val_loss: 13.4156 - val_root_mean_squared_error: 3.6627\n",
      "Epoch 456/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 14.0484 - root_mean_squared_error: 3.7481 - val_loss: 13.2843 - val_root_mean_squared_error: 3.6448\n",
      "Epoch 457/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.9829 - root_mean_squared_error: 3.7394 - val_loss: 13.2608 - val_root_mean_squared_error: 3.6415\n",
      "Epoch 458/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.8700 - root_mean_squared_error: 3.7242 - val_loss: 13.2122 - val_root_mean_squared_error: 3.6349\n",
      "Epoch 459/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.8164 - root_mean_squared_error: 3.7170 - val_loss: 13.1375 - val_root_mean_squared_error: 3.6246\n",
      "Epoch 460/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.7636 - root_mean_squared_error: 3.7099 - val_loss: 13.0287 - val_root_mean_squared_error: 3.6095\n",
      "Epoch 461/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.7055 - root_mean_squared_error: 3.7021 - val_loss: 13.0716 - val_root_mean_squared_error: 3.6155\n",
      "Epoch 462/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.5708 - root_mean_squared_error: 3.6839 - val_loss: 12.8368 - val_root_mean_squared_error: 3.5828\n",
      "Epoch 463/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.5142 - root_mean_squared_error: 3.6762 - val_loss: 12.8458 - val_root_mean_squared_error: 3.5841\n",
      "Epoch 464/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.4599 - root_mean_squared_error: 3.6688 - val_loss: 12.8689 - val_root_mean_squared_error: 3.5873\n",
      "Epoch 465/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.3514 - root_mean_squared_error: 3.6540 - val_loss: 12.7637 - val_root_mean_squared_error: 3.5726\n",
      "Epoch 466/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.3581 - root_mean_squared_error: 3.6549 - val_loss: 12.6739 - val_root_mean_squared_error: 3.5600\n",
      "Epoch 467/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.3285 - root_mean_squared_error: 3.6508 - val_loss: 12.6494 - val_root_mean_squared_error: 3.5566\n",
      "Epoch 468/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.2117 - root_mean_squared_error: 3.6348 - val_loss: 12.6132 - val_root_mean_squared_error: 3.5515\n",
      "Epoch 469/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.1428 - root_mean_squared_error: 3.6253 - val_loss: 12.5241 - val_root_mean_squared_error: 3.5389\n",
      "Epoch 470/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 13.0487 - root_mean_squared_error: 3.6123 - val_loss: 12.4469 - val_root_mean_squared_error: 3.5280\n",
      "Epoch 471/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 13.0280 - root_mean_squared_error: 3.6094 - val_loss: 12.4936 - val_root_mean_squared_error: 3.5346\n",
      "Epoch 472/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.9622 - root_mean_squared_error: 3.6003 - val_loss: 12.3372 - val_root_mean_squared_error: 3.5124\n",
      "Epoch 473/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.8701 - root_mean_squared_error: 3.5875 - val_loss: 12.2655 - val_root_mean_squared_error: 3.5022\n",
      "Epoch 474/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.8286 - root_mean_squared_error: 3.5817 - val_loss: 12.2231 - val_root_mean_squared_error: 3.4962\n",
      "Epoch 475/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.7315 - root_mean_squared_error: 3.5681 - val_loss: 12.1817 - val_root_mean_squared_error: 3.4902\n",
      "Epoch 476/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.6738 - root_mean_squared_error: 3.5600 - val_loss: 12.0801 - val_root_mean_squared_error: 3.4756\n",
      "Epoch 477/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.6342 - root_mean_squared_error: 3.5545 - val_loss: 12.0393 - val_root_mean_squared_error: 3.4698\n",
      "Epoch 478/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.6235 - root_mean_squared_error: 3.5530 - val_loss: 12.0763 - val_root_mean_squared_error: 3.4751\n",
      "Epoch 479/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.4804 - root_mean_squared_error: 3.5328 - val_loss: 11.9545 - val_root_mean_squared_error: 3.4575\n",
      "Epoch 480/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.5121 - root_mean_squared_error: 3.5373 - val_loss: 11.9485 - val_root_mean_squared_error: 3.4567\n",
      "Epoch 481/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.4659 - root_mean_squared_error: 3.5307 - val_loss: 11.9422 - val_root_mean_squared_error: 3.4558\n",
      "Epoch 482/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.3169 - root_mean_squared_error: 3.5095 - val_loss: 11.8303 - val_root_mean_squared_error: 3.4395\n",
      "Epoch 483/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.2918 - root_mean_squared_error: 3.5060 - val_loss: 11.8605 - val_root_mean_squared_error: 3.4439\n",
      "Epoch 484/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.2548 - root_mean_squared_error: 3.5007 - val_loss: 11.7732 - val_root_mean_squared_error: 3.4312\n",
      "Epoch 485/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.2159 - root_mean_squared_error: 3.4951 - val_loss: 11.8052 - val_root_mean_squared_error: 3.4359\n",
      "Epoch 486/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.1364 - root_mean_squared_error: 3.4837 - val_loss: 11.6401 - val_root_mean_squared_error: 3.4118\n",
      "Epoch 487/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 12.0844 - root_mean_squared_error: 3.4763 - val_loss: 11.6208 - val_root_mean_squared_error: 3.4089\n",
      "Epoch 488/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.0312 - root_mean_squared_error: 3.4686 - val_loss: 11.6002 - val_root_mean_squared_error: 3.4059\n",
      "Epoch 489/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 12.0042 - root_mean_squared_error: 3.4647 - val_loss: 11.5139 - val_root_mean_squared_error: 3.3932\n",
      "Epoch 490/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.9327 - root_mean_squared_error: 3.4544 - val_loss: 11.6288 - val_root_mean_squared_error: 3.4101\n",
      "Epoch 491/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.9471 - root_mean_squared_error: 3.4565 - val_loss: 11.5133 - val_root_mean_squared_error: 3.3931\n",
      "Epoch 492/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.8639 - root_mean_squared_error: 3.4444 - val_loss: 11.4337 - val_root_mean_squared_error: 3.3814\n",
      "Epoch 493/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.7871 - root_mean_squared_error: 3.4332 - val_loss: 11.4431 - val_root_mean_squared_error: 3.3828\n",
      "Epoch 494/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.8224 - root_mean_squared_error: 3.4384 - val_loss: 11.4160 - val_root_mean_squared_error: 3.3788\n",
      "Epoch 495/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 11.7549 - root_mean_squared_error: 3.4285 - val_loss: 11.2815 - val_root_mean_squared_error: 3.3588\n",
      "Epoch 496/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.6580 - root_mean_squared_error: 3.4144 - val_loss: 11.2883 - val_root_mean_squared_error: 3.3598\n",
      "Epoch 497/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.6493 - root_mean_squared_error: 3.4131 - val_loss: 11.3768 - val_root_mean_squared_error: 3.3730\n",
      "Epoch 498/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.6177 - root_mean_squared_error: 3.4085 - val_loss: 11.1158 - val_root_mean_squared_error: 3.3340\n",
      "Epoch 499/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.6302 - root_mean_squared_error: 3.4103 - val_loss: 11.1841 - val_root_mean_squared_error: 3.3443\n",
      "Epoch 500/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.5211 - root_mean_squared_error: 3.3943 - val_loss: 11.1163 - val_root_mean_squared_error: 3.3341\n",
      "Epoch 501/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.4495 - root_mean_squared_error: 3.3837 - val_loss: 11.1389 - val_root_mean_squared_error: 3.3375\n",
      "Epoch 502/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.3949 - root_mean_squared_error: 3.3756 - val_loss: 11.0521 - val_root_mean_squared_error: 3.3245\n",
      "Epoch 503/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.3773 - root_mean_squared_error: 3.3730 - val_loss: 11.0221 - val_root_mean_squared_error: 3.3200\n",
      "Epoch 504/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17/17 [==============================] - 0s 2ms/step - loss: 11.3502 - root_mean_squared_error: 3.3690 - val_loss: 11.0603 - val_root_mean_squared_error: 3.3257\n",
      "Epoch 505/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.3024 - root_mean_squared_error: 3.3619 - val_loss: 10.9502 - val_root_mean_squared_error: 3.3091\n",
      "Epoch 506/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.2739 - root_mean_squared_error: 3.3577 - val_loss: 10.9551 - val_root_mean_squared_error: 3.3098\n",
      "Epoch 507/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.1866 - root_mean_squared_error: 3.3446 - val_loss: 10.8271 - val_root_mean_squared_error: 3.2905\n",
      "Epoch 508/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.1915 - root_mean_squared_error: 3.3454 - val_loss: 10.8652 - val_root_mean_squared_error: 3.2962\n",
      "Epoch 509/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.1487 - root_mean_squared_error: 3.3390 - val_loss: 10.8257 - val_root_mean_squared_error: 3.2902\n",
      "Epoch 510/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.0679 - root_mean_squared_error: 3.3268 - val_loss: 10.7940 - val_root_mean_squared_error: 3.2854\n",
      "Epoch 511/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.0430 - root_mean_squared_error: 3.3231 - val_loss: 10.7732 - val_root_mean_squared_error: 3.2823\n",
      "Epoch 512/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 11.0028 - root_mean_squared_error: 3.3170 - val_loss: 10.7021 - val_root_mean_squared_error: 3.2714\n",
      "Epoch 513/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.9709 - root_mean_squared_error: 3.3122 - val_loss: 10.6783 - val_root_mean_squared_error: 3.2678\n",
      "Epoch 514/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.9417 - root_mean_squared_error: 3.3078 - val_loss: 10.6481 - val_root_mean_squared_error: 3.2631\n",
      "Epoch 515/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.8970 - root_mean_squared_error: 3.3011 - val_loss: 10.6309 - val_root_mean_squared_error: 3.2605\n",
      "Epoch 516/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.9108 - root_mean_squared_error: 3.3031 - val_loss: 10.6112 - val_root_mean_squared_error: 3.2575\n",
      "Epoch 517/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 10.8217 - root_mean_squared_error: 3.2896 - val_loss: 10.5860 - val_root_mean_squared_error: 3.2536\n",
      "Epoch 518/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.8179 - root_mean_squared_error: 3.2891 - val_loss: 10.5573 - val_root_mean_squared_error: 3.2492\n",
      "Epoch 519/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.7926 - root_mean_squared_error: 3.2852 - val_loss: 10.4928 - val_root_mean_squared_error: 3.2393\n",
      "Epoch 520/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.7601 - root_mean_squared_error: 3.2803 - val_loss: 10.5795 - val_root_mean_squared_error: 3.2526\n",
      "Epoch 521/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.7258 - root_mean_squared_error: 3.2750 - val_loss: 10.4501 - val_root_mean_squared_error: 3.2327\n",
      "Epoch 522/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.6910 - root_mean_squared_error: 3.2697 - val_loss: 10.3817 - val_root_mean_squared_error: 3.2221\n",
      "Epoch 523/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.6776 - root_mean_squared_error: 3.2677 - val_loss: 10.3355 - val_root_mean_squared_error: 3.2149\n",
      "Epoch 524/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.5717 - root_mean_squared_error: 3.2514 - val_loss: 10.5008 - val_root_mean_squared_error: 3.2405\n",
      "Epoch 525/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 10.5894 - root_mean_squared_error: 3.2541 - val_loss: 10.3279 - val_root_mean_squared_error: 3.2137\n",
      "Epoch 526/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.5407 - root_mean_squared_error: 3.2466 - val_loss: 10.3484 - val_root_mean_squared_error: 3.2169\n",
      "Epoch 527/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.4855 - root_mean_squared_error: 3.2381 - val_loss: 10.2647 - val_root_mean_squared_error: 3.2039\n",
      "Epoch 528/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.4786 - root_mean_squared_error: 3.2371 - val_loss: 10.2525 - val_root_mean_squared_error: 3.2020\n",
      "Epoch 529/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 10.5092 - root_mean_squared_error: 3.2418 - val_loss: 10.3000 - val_root_mean_squared_error: 3.2094\n",
      "Epoch 530/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.4243 - root_mean_squared_error: 3.2287 - val_loss: 10.1692 - val_root_mean_squared_error: 3.1889\n",
      "Epoch 531/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.3796 - root_mean_squared_error: 3.2217 - val_loss: 10.2436 - val_root_mean_squared_error: 3.2006\n",
      "Epoch 532/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.3935 - root_mean_squared_error: 3.2239 - val_loss: 10.2483 - val_root_mean_squared_error: 3.2013\n",
      "Epoch 533/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 10.3371 - root_mean_squared_error: 3.2151 - val_loss: 10.2443 - val_root_mean_squared_error: 3.2007\n",
      "Epoch 534/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.3284 - root_mean_squared_error: 3.2138 - val_loss: 10.1047 - val_root_mean_squared_error: 3.1788\n",
      "Epoch 535/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.2911 - root_mean_squared_error: 3.2080 - val_loss: 10.1533 - val_root_mean_squared_error: 3.1864\n",
      "Epoch 536/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.2286 - root_mean_squared_error: 3.1982 - val_loss: 10.0612 - val_root_mean_squared_error: 3.1719\n",
      "Epoch 537/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.2176 - root_mean_squared_error: 3.1965 - val_loss: 10.1095 - val_root_mean_squared_error: 3.1795\n",
      "Epoch 538/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.2131 - root_mean_squared_error: 3.1958 - val_loss: 10.0392 - val_root_mean_squared_error: 3.1685\n",
      "Epoch 539/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.1805 - root_mean_squared_error: 3.1907 - val_loss: 10.0555 - val_root_mean_squared_error: 3.1710\n",
      "Epoch 540/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.1807 - root_mean_squared_error: 3.1907 - val_loss: 10.0156 - val_root_mean_squared_error: 3.1647\n",
      "Epoch 541/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.1299 - root_mean_squared_error: 3.1827 - val_loss: 9.9818 - val_root_mean_squared_error: 3.1594\n",
      "Epoch 542/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.0982 - root_mean_squared_error: 3.1778 - val_loss: 9.9502 - val_root_mean_squared_error: 3.1544\n",
      "Epoch 543/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.0871 - root_mean_squared_error: 3.1760 - val_loss: 10.0118 - val_root_mean_squared_error: 3.1641\n",
      "Epoch 544/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.0322 - root_mean_squared_error: 3.1674 - val_loss: 9.9440 - val_root_mean_squared_error: 3.1534\n",
      "Epoch 545/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.0132 - root_mean_squared_error: 3.1644 - val_loss: 9.8975 - val_root_mean_squared_error: 3.1460\n",
      "Epoch 546/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.0949 - root_mean_squared_error: 3.1772 - val_loss: 9.9512 - val_root_mean_squared_error: 3.1546\n",
      "Epoch 547/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.0263 - root_mean_squared_error: 3.1664 - val_loss: 9.9620 - val_root_mean_squared_error: 3.1563\n",
      "Epoch 548/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 10.0009 - root_mean_squared_error: 3.1624 - val_loss: 9.8184 - val_root_mean_squared_error: 3.1334\n",
      "Epoch 549/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.9824 - root_mean_squared_error: 3.1595 - val_loss: 9.9563 - val_root_mean_squared_error: 3.1554\n",
      "Epoch 550/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.9625 - root_mean_squared_error: 3.1563 - val_loss: 9.7710 - val_root_mean_squared_error: 3.1259\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 551/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.8766 - root_mean_squared_error: 3.1427 - val_loss: 9.8159 - val_root_mean_squared_error: 3.1330\n",
      "Epoch 552/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.8379 - root_mean_squared_error: 3.1365 - val_loss: 9.7784 - val_root_mean_squared_error: 3.1270\n",
      "Epoch 553/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.8858 - root_mean_squared_error: 3.1442 - val_loss: 9.8057 - val_root_mean_squared_error: 3.1314\n",
      "Epoch 554/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9.8873 - root_mean_squared_error: 3.1444 - val_loss: 9.7294 - val_root_mean_squared_error: 3.1192\n",
      "Epoch 555/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.8366 - root_mean_squared_error: 3.1363 - val_loss: 9.7256 - val_root_mean_squared_error: 3.1186\n",
      "Epoch 556/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.7641 - root_mean_squared_error: 3.1248 - val_loss: 9.8109 - val_root_mean_squared_error: 3.1322\n",
      "Epoch 557/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9.7843 - root_mean_squared_error: 3.1280 - val_loss: 9.7200 - val_root_mean_squared_error: 3.1177\n",
      "Epoch 558/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9.7409 - root_mean_squared_error: 3.1210 - val_loss: 9.6136 - val_root_mean_squared_error: 3.1006\n",
      "Epoch 559/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.7220 - root_mean_squared_error: 3.1180 - val_loss: 9.7418 - val_root_mean_squared_error: 3.1212\n",
      "Epoch 560/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.7263 - root_mean_squared_error: 3.1187 - val_loss: 9.6052 - val_root_mean_squared_error: 3.0992\n",
      "Epoch 561/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.6803 - root_mean_squared_error: 3.1113 - val_loss: 9.6403 - val_root_mean_squared_error: 3.1049\n",
      "Epoch 562/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9.6659 - root_mean_squared_error: 3.1090 - val_loss: 9.6758 - val_root_mean_squared_error: 3.1106\n",
      "Epoch 563/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.6467 - root_mean_squared_error: 3.1059 - val_loss: 9.6970 - val_root_mean_squared_error: 3.1140\n",
      "Epoch 564/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.6544 - root_mean_squared_error: 3.1072 - val_loss: 9.5495 - val_root_mean_squared_error: 3.0902\n",
      "Epoch 565/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.5535 - root_mean_squared_error: 3.0909 - val_loss: 9.6284 - val_root_mean_squared_error: 3.1030\n",
      "Epoch 566/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.6070 - root_mean_squared_error: 3.0995 - val_loss: 9.5837 - val_root_mean_squared_error: 3.0958\n",
      "Epoch 567/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.6289 - root_mean_squared_error: 3.1030 - val_loss: 9.5666 - val_root_mean_squared_error: 3.0930\n",
      "Epoch 568/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.5394 - root_mean_squared_error: 3.0886 - val_loss: 9.4551 - val_root_mean_squared_error: 3.0749\n",
      "Epoch 569/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.4962 - root_mean_squared_error: 3.0816 - val_loss: 9.5918 - val_root_mean_squared_error: 3.0971\n",
      "Epoch 570/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.5020 - root_mean_squared_error: 3.0825 - val_loss: 9.4956 - val_root_mean_squared_error: 3.0815\n",
      "Epoch 571/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.5424 - root_mean_squared_error: 3.0891 - val_loss: 9.4908 - val_root_mean_squared_error: 3.0807\n",
      "Epoch 572/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.6897 - root_mean_squared_error: 3.1128 - val_loss: 9.5411 - val_root_mean_squared_error: 3.0889\n",
      "Epoch 573/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.5144 - root_mean_squared_error: 3.0845 - val_loss: 9.4078 - val_root_mean_squared_error: 3.0672\n",
      "Epoch 574/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9.4000 - root_mean_squared_error: 3.0659 - val_loss: 9.4934 - val_root_mean_squared_error: 3.0811\n",
      "Epoch 575/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.4251 - root_mean_squared_error: 3.0700 - val_loss: 9.4827 - val_root_mean_squared_error: 3.0794\n",
      "Epoch 576/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9.4555 - root_mean_squared_error: 3.0750 - val_loss: 9.4483 - val_root_mean_squared_error: 3.0738\n",
      "Epoch 577/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.4667 - root_mean_squared_error: 3.0768 - val_loss: 9.4066 - val_root_mean_squared_error: 3.0670\n",
      "Epoch 578/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.4205 - root_mean_squared_error: 3.0693 - val_loss: 9.3707 - val_root_mean_squared_error: 3.0612\n",
      "Epoch 579/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9.3918 - root_mean_squared_error: 3.0646 - val_loss: 9.3957 - val_root_mean_squared_error: 3.0652\n",
      "Epoch 580/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.3431 - root_mean_squared_error: 3.0566 - val_loss: 9.4401 - val_root_mean_squared_error: 3.0725\n",
      "Epoch 581/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.3262 - root_mean_squared_error: 3.0539 - val_loss: 9.4376 - val_root_mean_squared_error: 3.0721\n",
      "Epoch 582/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.3182 - root_mean_squared_error: 3.0526 - val_loss: 9.3480 - val_root_mean_squared_error: 3.0574\n",
      "Epoch 583/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.4426 - root_mean_squared_error: 3.0729 - val_loss: 9.3136 - val_root_mean_squared_error: 3.0518\n",
      "Epoch 584/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.4014 - root_mean_squared_error: 3.0662 - val_loss: 9.3502 - val_root_mean_squared_error: 3.0578\n",
      "Epoch 585/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9.2465 - root_mean_squared_error: 3.0408 - val_loss: 9.3619 - val_root_mean_squared_error: 3.0597\n",
      "Epoch 586/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.2484 - root_mean_squared_error: 3.0411 - val_loss: 9.3694 - val_root_mean_squared_error: 3.0609\n",
      "Epoch 587/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.2126 - root_mean_squared_error: 3.0352 - val_loss: 9.2693 - val_root_mean_squared_error: 3.0446\n",
      "Epoch 588/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.2065 - root_mean_squared_error: 3.0342 - val_loss: 9.2944 - val_root_mean_squared_error: 3.0487\n",
      "Epoch 589/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.1796 - root_mean_squared_error: 3.0298 - val_loss: 9.3216 - val_root_mean_squared_error: 3.0531\n",
      "Epoch 590/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.2102 - root_mean_squared_error: 3.0348 - val_loss: 9.2877 - val_root_mean_squared_error: 3.0476\n",
      "Epoch 591/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.2139 - root_mean_squared_error: 3.0354 - val_loss: 9.2283 - val_root_mean_squared_error: 3.0378\n",
      "Epoch 592/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.1584 - root_mean_squared_error: 3.0263 - val_loss: 9.2139 - val_root_mean_squared_error: 3.0354\n",
      "Epoch 593/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9.1442 - root_mean_squared_error: 3.0239 - val_loss: 9.2312 - val_root_mean_squared_error: 3.0383\n",
      "Epoch 594/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.1304 - root_mean_squared_error: 3.0217 - val_loss: 9.2740 - val_root_mean_squared_error: 3.0453\n",
      "Epoch 595/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.1121 - root_mean_squared_error: 3.0186 - val_loss: 9.1847 - val_root_mean_squared_error: 3.0306\n",
      "Epoch 596/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.1288 - root_mean_squared_error: 3.0214 - val_loss: 9.2468 - val_root_mean_squared_error: 3.0408\n",
      "Epoch 597/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.1665 - root_mean_squared_error: 3.0276 - val_loss: 9.0836 - val_root_mean_squared_error: 3.0139\n",
      "Epoch 598/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17/17 [==============================] - 0s 2ms/step - loss: 9.0948 - root_mean_squared_error: 3.0158 - val_loss: 9.2755 - val_root_mean_squared_error: 3.0456\n",
      "Epoch 599/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.0585 - root_mean_squared_error: 3.0097 - val_loss: 9.1292 - val_root_mean_squared_error: 3.0215\n",
      "Epoch 600/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9.0642 - root_mean_squared_error: 3.0107 - val_loss: 9.0826 - val_root_mean_squared_error: 3.0137\n",
      "Epoch 601/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.0555 - root_mean_squared_error: 3.0092 - val_loss: 9.1081 - val_root_mean_squared_error: 3.0180\n",
      "Epoch 602/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.0292 - root_mean_squared_error: 3.0049 - val_loss: 9.1633 - val_root_mean_squared_error: 3.0271\n",
      "Epoch 603/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 9.0016 - root_mean_squared_error: 3.0003 - val_loss: 9.0753 - val_root_mean_squared_error: 3.0125\n",
      "Epoch 604/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.0431 - root_mean_squared_error: 3.0072 - val_loss: 9.1394 - val_root_mean_squared_error: 3.0232\n",
      "Epoch 605/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.9851 - root_mean_squared_error: 2.9975 - val_loss: 9.1457 - val_root_mean_squared_error: 3.0242\n",
      "Epoch 606/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.9804 - root_mean_squared_error: 2.9967 - val_loss: 9.0325 - val_root_mean_squared_error: 3.0054\n",
      "Epoch 607/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.9880 - root_mean_squared_error: 2.9980 - val_loss: 9.1285 - val_root_mean_squared_error: 3.0213\n",
      "Epoch 608/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.9411 - root_mean_squared_error: 2.9902 - val_loss: 9.0176 - val_root_mean_squared_error: 3.0029\n",
      "Epoch 609/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.0128 - root_mean_squared_error: 3.0021 - val_loss: 8.9941 - val_root_mean_squared_error: 2.9990\n",
      "Epoch 610/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 9.0022 - root_mean_squared_error: 3.0004 - val_loss: 9.0402 - val_root_mean_squared_error: 3.0067\n",
      "Epoch 611/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.9579 - root_mean_squared_error: 2.9930 - val_loss: 9.0134 - val_root_mean_squared_error: 3.0022\n",
      "Epoch 612/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.9299 - root_mean_squared_error: 2.9883 - val_loss: 8.9418 - val_root_mean_squared_error: 2.9903\n",
      "Epoch 613/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.9756 - root_mean_squared_error: 2.9959 - val_loss: 8.9784 - val_root_mean_squared_error: 2.9964\n",
      "Epoch 614/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.8636 - root_mean_squared_error: 2.9772 - val_loss: 8.9913 - val_root_mean_squared_error: 2.9985\n",
      "Epoch 615/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.8982 - root_mean_squared_error: 2.9830 - val_loss: 8.9614 - val_root_mean_squared_error: 2.9936\n",
      "Epoch 616/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.8557 - root_mean_squared_error: 2.9759 - val_loss: 8.9841 - val_root_mean_squared_error: 2.9974\n",
      "Epoch 617/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.8818 - root_mean_squared_error: 2.9802 - val_loss: 8.9623 - val_root_mean_squared_error: 2.9937\n",
      "Epoch 618/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.8571 - root_mean_squared_error: 2.9761 - val_loss: 8.9227 - val_root_mean_squared_error: 2.9871\n",
      "Epoch 619/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.8980 - root_mean_squared_error: 2.9829 - val_loss: 8.8729 - val_root_mean_squared_error: 2.9787\n",
      "Epoch 620/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.8603 - root_mean_squared_error: 2.9766 - val_loss: 9.0742 - val_root_mean_squared_error: 3.0123\n",
      "Epoch 621/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.8501 - root_mean_squared_error: 2.9749 - val_loss: 8.8885 - val_root_mean_squared_error: 2.9814\n",
      "Epoch 622/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.7927 - root_mean_squared_error: 2.9652 - val_loss: 8.9341 - val_root_mean_squared_error: 2.9890\n",
      "Epoch 623/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.8084 - root_mean_squared_error: 2.9679 - val_loss: 8.8978 - val_root_mean_squared_error: 2.9829\n",
      "Epoch 624/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.7839 - root_mean_squared_error: 2.9638 - val_loss: 8.8728 - val_root_mean_squared_error: 2.9787\n",
      "Epoch 625/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.8333 - root_mean_squared_error: 2.9721 - val_loss: 8.8643 - val_root_mean_squared_error: 2.9773\n",
      "Epoch 626/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.7905 - root_mean_squared_error: 2.9649 - val_loss: 8.8339 - val_root_mean_squared_error: 2.9722\n",
      "Epoch 627/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.8009 - root_mean_squared_error: 2.9666 - val_loss: 8.8840 - val_root_mean_squared_error: 2.9806\n",
      "Epoch 628/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.7944 - root_mean_squared_error: 2.9655 - val_loss: 8.8675 - val_root_mean_squared_error: 2.9778\n",
      "Epoch 629/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.7817 - root_mean_squared_error: 2.9634 - val_loss: 8.7703 - val_root_mean_squared_error: 2.9615\n",
      "Epoch 630/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.7030 - root_mean_squared_error: 2.9501 - val_loss: 8.8527 - val_root_mean_squared_error: 2.9753\n",
      "Epoch 631/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.7364 - root_mean_squared_error: 2.9557 - val_loss: 8.8172 - val_root_mean_squared_error: 2.9694\n",
      "Epoch 632/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.7198 - root_mean_squared_error: 2.9529 - val_loss: 8.8166 - val_root_mean_squared_error: 2.9693\n",
      "Epoch 633/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.7344 - root_mean_squared_error: 2.9554 - val_loss: 8.8117 - val_root_mean_squared_error: 2.9684\n",
      "Epoch 634/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.8236 - root_mean_squared_error: 2.9705 - val_loss: 8.8177 - val_root_mean_squared_error: 2.9695\n",
      "Epoch 635/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.7636 - root_mean_squared_error: 2.9603 - val_loss: 8.7732 - val_root_mean_squared_error: 2.9620\n",
      "Epoch 636/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6940 - root_mean_squared_error: 2.9486 - val_loss: 8.7487 - val_root_mean_squared_error: 2.9578\n",
      "Epoch 637/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6756 - root_mean_squared_error: 2.9454 - val_loss: 8.7687 - val_root_mean_squared_error: 2.9612\n",
      "Epoch 638/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6502 - root_mean_squared_error: 2.9411 - val_loss: 8.7160 - val_root_mean_squared_error: 2.9523\n",
      "Epoch 639/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6168 - root_mean_squared_error: 2.9354 - val_loss: 8.8208 - val_root_mean_squared_error: 2.9700\n",
      "Epoch 640/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6147 - root_mean_squared_error: 2.9351 - val_loss: 8.7160 - val_root_mean_squared_error: 2.9523\n",
      "Epoch 641/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6547 - root_mean_squared_error: 2.9419 - val_loss: 8.6939 - val_root_mean_squared_error: 2.9485\n",
      "Epoch 642/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6623 - root_mean_squared_error: 2.9432 - val_loss: 8.7555 - val_root_mean_squared_error: 2.9590\n",
      "Epoch 643/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6193 - root_mean_squared_error: 2.9359 - val_loss: 8.6781 - val_root_mean_squared_error: 2.9459\n",
      "Epoch 644/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6224 - root_mean_squared_error: 2.9364 - val_loss: 8.6855 - val_root_mean_squared_error: 2.9471\n",
      "Epoch 645/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6536 - root_mean_squared_error: 2.9417 - val_loss: 8.7484 - val_root_mean_squared_error: 2.9578\n",
      "Epoch 646/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.6084 - root_mean_squared_error: 2.9340 - val_loss: 8.5902 - val_root_mean_squared_error: 2.9309\n",
      "Epoch 647/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.5770 - root_mean_squared_error: 2.9286 - val_loss: 8.6887 - val_root_mean_squared_error: 2.9477\n",
      "Epoch 648/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6176 - root_mean_squared_error: 2.9356 - val_loss: 8.6710 - val_root_mean_squared_error: 2.9447\n",
      "Epoch 649/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.6220 - root_mean_squared_error: 2.9363 - val_loss: 8.6543 - val_root_mean_squared_error: 2.9418\n",
      "Epoch 650/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.5485 - root_mean_squared_error: 2.9238 - val_loss: 8.7030 - val_root_mean_squared_error: 2.9501\n",
      "Epoch 651/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.5439 - root_mean_squared_error: 2.9230 - val_loss: 8.5900 - val_root_mean_squared_error: 2.9309\n",
      "Epoch 652/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.5765 - root_mean_squared_error: 2.9286 - val_loss: 8.6621 - val_root_mean_squared_error: 2.9431\n",
      "Epoch 653/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.5119 - root_mean_squared_error: 2.9175 - val_loss: 8.6818 - val_root_mean_squared_error: 2.9465\n",
      "Epoch 654/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.5441 - root_mean_squared_error: 2.9230 - val_loss: 8.7012 - val_root_mean_squared_error: 2.9498\n",
      "Epoch 655/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.4817 - root_mean_squared_error: 2.9123 - val_loss: 8.5780 - val_root_mean_squared_error: 2.9288\n",
      "Epoch 656/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.5123 - root_mean_squared_error: 2.9176 - val_loss: 8.5818 - val_root_mean_squared_error: 2.9295\n",
      "Epoch 657/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.4864 - root_mean_squared_error: 2.9131 - val_loss: 8.6514 - val_root_mean_squared_error: 2.9413\n",
      "Epoch 658/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.4918 - root_mean_squared_error: 2.9141 - val_loss: 8.5673 - val_root_mean_squared_error: 2.9270\n",
      "Epoch 659/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.5481 - root_mean_squared_error: 2.9237 - val_loss: 8.6001 - val_root_mean_squared_error: 2.9326\n",
      "Epoch 660/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.4821 - root_mean_squared_error: 2.9124 - val_loss: 8.5898 - val_root_mean_squared_error: 2.9308\n",
      "Epoch 661/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.4836 - root_mean_squared_error: 2.9127 - val_loss: 8.5560 - val_root_mean_squared_error: 2.9251\n",
      "Epoch 662/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.4510 - root_mean_squared_error: 2.9071 - val_loss: 8.6214 - val_root_mean_squared_error: 2.9362\n",
      "Epoch 663/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.4415 - root_mean_squared_error: 2.9054 - val_loss: 8.5193 - val_root_mean_squared_error: 2.9188\n",
      "Epoch 664/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.4731 - root_mean_squared_error: 2.9109 - val_loss: 8.6454 - val_root_mean_squared_error: 2.9403\n",
      "Epoch 665/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.4439 - root_mean_squared_error: 2.9058 - val_loss: 8.4986 - val_root_mean_squared_error: 2.9152\n",
      "Epoch 666/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.4100 - root_mean_squared_error: 2.9000 - val_loss: 8.6126 - val_root_mean_squared_error: 2.9347\n",
      "Epoch 667/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3927 - root_mean_squared_error: 2.8970 - val_loss: 8.4858 - val_root_mean_squared_error: 2.9130\n",
      "Epoch 668/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.4340 - root_mean_squared_error: 2.9041 - val_loss: 8.5473 - val_root_mean_squared_error: 2.9236\n",
      "Epoch 669/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3933 - root_mean_squared_error: 2.8971 - val_loss: 8.5075 - val_root_mean_squared_error: 2.9168\n",
      "Epoch 670/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3731 - root_mean_squared_error: 2.8936 - val_loss: 8.5267 - val_root_mean_squared_error: 2.9201\n",
      "Epoch 671/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.3849 - root_mean_squared_error: 2.8957 - val_loss: 8.5757 - val_root_mean_squared_error: 2.9284\n",
      "Epoch 672/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.4261 - root_mean_squared_error: 2.9028 - val_loss: 8.5180 - val_root_mean_squared_error: 2.9186\n",
      "Epoch 673/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3579 - root_mean_squared_error: 2.8910 - val_loss: 8.5523 - val_root_mean_squared_error: 2.9244\n",
      "Epoch 674/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.4191 - root_mean_squared_error: 2.9016 - val_loss: 8.5146 - val_root_mean_squared_error: 2.9180\n",
      "Epoch 675/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3709 - root_mean_squared_error: 2.8932 - val_loss: 8.5096 - val_root_mean_squared_error: 2.9171\n",
      "Epoch 676/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3640 - root_mean_squared_error: 2.8921 - val_loss: 8.4284 - val_root_mean_squared_error: 2.9032\n",
      "Epoch 677/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3541 - root_mean_squared_error: 2.8904 - val_loss: 8.4599 - val_root_mean_squared_error: 2.9086\n",
      "Epoch 678/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3506 - root_mean_squared_error: 2.8897 - val_loss: 8.5029 - val_root_mean_squared_error: 2.9160\n",
      "Epoch 679/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.4716 - root_mean_squared_error: 2.9106 - val_loss: 8.5129 - val_root_mean_squared_error: 2.9177\n",
      "Epoch 680/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3267 - root_mean_squared_error: 2.8856 - val_loss: 8.5143 - val_root_mean_squared_error: 2.9179\n",
      "Epoch 681/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2950 - root_mean_squared_error: 2.8801 - val_loss: 8.4184 - val_root_mean_squared_error: 2.9014\n",
      "Epoch 682/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3468 - root_mean_squared_error: 2.8891 - val_loss: 8.4902 - val_root_mean_squared_error: 2.9138\n",
      "Epoch 683/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3941 - root_mean_squared_error: 2.8973 - val_loss: 8.3993 - val_root_mean_squared_error: 2.8982\n",
      "Epoch 684/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.4490 - root_mean_squared_error: 2.9067 - val_loss: 8.6550 - val_root_mean_squared_error: 2.9419\n",
      "Epoch 685/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.3587 - root_mean_squared_error: 2.8911 - val_loss: 8.4087 - val_root_mean_squared_error: 2.8998\n",
      "Epoch 686/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2862 - root_mean_squared_error: 2.8786 - val_loss: 8.4805 - val_root_mean_squared_error: 2.9121\n",
      "Epoch 687/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2761 - root_mean_squared_error: 2.8768 - val_loss: 8.3866 - val_root_mean_squared_error: 2.8960\n",
      "Epoch 688/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2849 - root_mean_squared_error: 2.8783 - val_loss: 8.4004 - val_root_mean_squared_error: 2.8983\n",
      "Epoch 689/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.2460 - root_mean_squared_error: 2.8716 - val_loss: 8.3875 - val_root_mean_squared_error: 2.8961\n",
      "Epoch 690/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2479 - root_mean_squared_error: 2.8719 - val_loss: 8.3762 - val_root_mean_squared_error: 2.8942\n",
      "Epoch 691/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2519 - root_mean_squared_error: 2.8726 - val_loss: 8.4196 - val_root_mean_squared_error: 2.9017\n",
      "Epoch 692/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2146 - root_mean_squared_error: 2.8661 - val_loss: 8.3111 - val_root_mean_squared_error: 2.8829\n",
      "Epoch 693/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2739 - root_mean_squared_error: 2.8764 - val_loss: 8.3663 - val_root_mean_squared_error: 2.8925\n",
      "Epoch 694/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2161 - root_mean_squared_error: 2.8664 - val_loss: 8.3481 - val_root_mean_squared_error: 2.8893\n",
      "Epoch 695/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2343 - root_mean_squared_error: 2.8696 - val_loss: 8.3041 - val_root_mean_squared_error: 2.8817\n",
      "Epoch 696/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.1936 - root_mean_squared_error: 2.8624 - val_loss: 8.3732 - val_root_mean_squared_error: 2.8936\n",
      "Epoch 697/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.2062 - root_mean_squared_error: 2.8646 - val_loss: 8.3791 - val_root_mean_squared_error: 2.8947\n",
      "Epoch 698/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2112 - root_mean_squared_error: 2.8655 - val_loss: 8.3574 - val_root_mean_squared_error: 2.8909\n",
      "Epoch 699/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.1884 - root_mean_squared_error: 2.8615 - val_loss: 8.3594 - val_root_mean_squared_error: 2.8913\n",
      "Epoch 700/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.2229 - root_mean_squared_error: 2.8676 - val_loss: 8.3963 - val_root_mean_squared_error: 2.8976\n",
      "Epoch 701/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2378 - root_mean_squared_error: 2.8702 - val_loss: 8.2841 - val_root_mean_squared_error: 2.8782\n",
      "Epoch 702/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2203 - root_mean_squared_error: 2.8671 - val_loss: 8.3111 - val_root_mean_squared_error: 2.8829\n",
      "Epoch 703/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.1599 - root_mean_squared_error: 2.8565 - val_loss: 8.2688 - val_root_mean_squared_error: 2.8756\n",
      "Epoch 704/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.1880 - root_mean_squared_error: 2.8615 - val_loss: 8.3465 - val_root_mean_squared_error: 2.8890\n",
      "Epoch 705/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.1585 - root_mean_squared_error: 2.8563 - val_loss: 8.2928 - val_root_mean_squared_error: 2.8797\n",
      "Epoch 706/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.1398 - root_mean_squared_error: 2.8530 - val_loss: 8.2844 - val_root_mean_squared_error: 2.8783\n",
      "Epoch 707/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.1777 - root_mean_squared_error: 2.8597 - val_loss: 8.4045 - val_root_mean_squared_error: 2.8991\n",
      "Epoch 708/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.1548 - root_mean_squared_error: 2.8557 - val_loss: 8.3099 - val_root_mean_squared_error: 2.8827\n",
      "Epoch 709/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.1509 - root_mean_squared_error: 2.8550 - val_loss: 8.2981 - val_root_mean_squared_error: 2.8806\n",
      "Epoch 710/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.2450 - root_mean_squared_error: 2.8714 - val_loss: 8.2233 - val_root_mean_squared_error: 2.8676\n",
      "Epoch 711/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.1842 - root_mean_squared_error: 2.8608 - val_loss: 8.2411 - val_root_mean_squared_error: 2.8707\n",
      "Epoch 712/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.1103 - root_mean_squared_error: 2.8479 - val_loss: 8.2303 - val_root_mean_squared_error: 2.8689\n",
      "Epoch 713/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.1110 - root_mean_squared_error: 2.8480 - val_loss: 8.2426 - val_root_mean_squared_error: 2.8710\n",
      "Epoch 714/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.1523 - root_mean_squared_error: 2.8552 - val_loss: 8.3038 - val_root_mean_squared_error: 2.8816\n",
      "Epoch 715/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.1247 - root_mean_squared_error: 2.8504 - val_loss: 8.2675 - val_root_mean_squared_error: 2.8753\n",
      "Epoch 716/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.0960 - root_mean_squared_error: 2.8454 - val_loss: 8.3025 - val_root_mean_squared_error: 2.8814\n",
      "Epoch 717/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.0942 - root_mean_squared_error: 2.8450 - val_loss: 8.1966 - val_root_mean_squared_error: 2.8630\n",
      "Epoch 718/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.1259 - root_mean_squared_error: 2.8506 - val_loss: 8.3461 - val_root_mean_squared_error: 2.8890\n",
      "Epoch 719/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.0275 - root_mean_squared_error: 2.8333 - val_loss: 8.2403 - val_root_mean_squared_error: 2.8706\n",
      "Epoch 720/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.0562 - root_mean_squared_error: 2.8383 - val_loss: 8.2979 - val_root_mean_squared_error: 2.8806\n",
      "Epoch 721/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.0476 - root_mean_squared_error: 2.8368 - val_loss: 8.2393 - val_root_mean_squared_error: 2.8704\n",
      "Epoch 722/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.0366 - root_mean_squared_error: 2.8349 - val_loss: 8.1712 - val_root_mean_squared_error: 2.8585\n",
      "Epoch 723/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.0477 - root_mean_squared_error: 2.8369 - val_loss: 8.2459 - val_root_mean_squared_error: 2.8716\n",
      "Epoch 724/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 8.0152 - root_mean_squared_error: 2.8311 - val_loss: 8.2569 - val_root_mean_squared_error: 2.8735\n",
      "Epoch 725/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.1009 - root_mean_squared_error: 2.8462 - val_loss: 8.2387 - val_root_mean_squared_error: 2.8703\n",
      "Epoch 726/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.0876 - root_mean_squared_error: 2.8439 - val_loss: 8.2952 - val_root_mean_squared_error: 2.8801\n",
      "Epoch 727/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.0016 - root_mean_squared_error: 2.8287 - val_loss: 8.2060 - val_root_mean_squared_error: 2.8646\n",
      "Epoch 728/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.0479 - root_mean_squared_error: 2.8369 - val_loss: 8.2524 - val_root_mean_squared_error: 2.8727\n",
      "Epoch 729/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.0215 - root_mean_squared_error: 2.8322 - val_loss: 8.1758 - val_root_mean_squared_error: 2.8593\n",
      "Epoch 730/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.9951 - root_mean_squared_error: 2.8276 - val_loss: 8.1650 - val_root_mean_squared_error: 2.8574\n",
      "Epoch 731/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.9959 - root_mean_squared_error: 2.8277 - val_loss: 8.2039 - val_root_mean_squared_error: 2.8642\n",
      "Epoch 732/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9904 - root_mean_squared_error: 2.8267 - val_loss: 8.1639 - val_root_mean_squared_error: 2.8572\n",
      "Epoch 733/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9772 - root_mean_squared_error: 2.8244 - val_loss: 8.2078 - val_root_mean_squared_error: 2.8649\n",
      "Epoch 734/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9494 - root_mean_squared_error: 2.8195 - val_loss: 8.1890 - val_root_mean_squared_error: 2.8617\n",
      "Epoch 735/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.9526 - root_mean_squared_error: 2.8200 - val_loss: 8.1986 - val_root_mean_squared_error: 2.8633\n",
      "Epoch 736/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9568 - root_mean_squared_error: 2.8208 - val_loss: 8.2468 - val_root_mean_squared_error: 2.8717\n",
      "Epoch 737/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.9249 - root_mean_squared_error: 2.8151 - val_loss: 8.1518 - val_root_mean_squared_error: 2.8551\n",
      "Epoch 738/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9408 - root_mean_squared_error: 2.8179 - val_loss: 8.1847 - val_root_mean_squared_error: 2.8609\n",
      "Epoch 739/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9158 - root_mean_squared_error: 2.8135 - val_loss: 8.1536 - val_root_mean_squared_error: 2.8554\n",
      "Epoch 740/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9693 - root_mean_squared_error: 2.8230 - val_loss: 8.3037 - val_root_mean_squared_error: 2.8816\n",
      "Epoch 741/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9302 - root_mean_squared_error: 2.8161 - val_loss: 8.1077 - val_root_mean_squared_error: 2.8474\n",
      "Epoch 742/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.9698 - root_mean_squared_error: 2.8231 - val_loss: 8.2317 - val_root_mean_squared_error: 2.8691\n",
      "Epoch 743/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 8.0037 - root_mean_squared_error: 2.8291 - val_loss: 8.1415 - val_root_mean_squared_error: 2.8533\n",
      "Epoch 744/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9049 - root_mean_squared_error: 2.8116 - val_loss: 8.1717 - val_root_mean_squared_error: 2.8586\n",
      "Epoch 745/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9061 - root_mean_squared_error: 2.8118 - val_loss: 8.1678 - val_root_mean_squared_error: 2.8579\n",
      "Epoch 746/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8719 - root_mean_squared_error: 2.8057 - val_loss: 8.1503 - val_root_mean_squared_error: 2.8549\n",
      "Epoch 747/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8965 - root_mean_squared_error: 2.8101 - val_loss: 8.1851 - val_root_mean_squared_error: 2.8610\n",
      "Epoch 748/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8764 - root_mean_squared_error: 2.8065 - val_loss: 8.1914 - val_root_mean_squared_error: 2.8621\n",
      "Epoch 749/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9064 - root_mean_squared_error: 2.8118 - val_loss: 8.1685 - val_root_mean_squared_error: 2.8581\n",
      "Epoch 750/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.8495 - root_mean_squared_error: 2.8017 - val_loss: 8.1260 - val_root_mean_squared_error: 2.8506\n",
      "Epoch 751/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8718 - root_mean_squared_error: 2.8057 - val_loss: 8.1621 - val_root_mean_squared_error: 2.8569\n",
      "Epoch 752/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8548 - root_mean_squared_error: 2.8026 - val_loss: 8.1239 - val_root_mean_squared_error: 2.8502\n",
      "Epoch 753/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9627 - root_mean_squared_error: 2.8218 - val_loss: 8.2105 - val_root_mean_squared_error: 2.8654\n",
      "Epoch 754/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9281 - root_mean_squared_error: 2.8157 - val_loss: 8.1280 - val_root_mean_squared_error: 2.8510\n",
      "Epoch 755/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8599 - root_mean_squared_error: 2.8036 - val_loss: 8.1108 - val_root_mean_squared_error: 2.8479\n",
      "Epoch 756/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8448 - root_mean_squared_error: 2.8009 - val_loss: 8.1144 - val_root_mean_squared_error: 2.8486\n",
      "Epoch 757/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.9522 - root_mean_squared_error: 2.8200 - val_loss: 8.1414 - val_root_mean_squared_error: 2.8533\n",
      "Epoch 758/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8252 - root_mean_squared_error: 2.7973 - val_loss: 8.1471 - val_root_mean_squared_error: 2.8543\n",
      "Epoch 759/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8605 - root_mean_squared_error: 2.8037 - val_loss: 8.1716 - val_root_mean_squared_error: 2.8586\n",
      "Epoch 760/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8334 - root_mean_squared_error: 2.7988 - val_loss: 8.0998 - val_root_mean_squared_error: 2.8460\n",
      "Epoch 761/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8176 - root_mean_squared_error: 2.7960 - val_loss: 8.1258 - val_root_mean_squared_error: 2.8506\n",
      "Epoch 762/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7951 - root_mean_squared_error: 2.7920 - val_loss: 8.1745 - val_root_mean_squared_error: 2.8591\n",
      "Epoch 763/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7981 - root_mean_squared_error: 2.7925 - val_loss: 8.2103 - val_root_mean_squared_error: 2.8654\n",
      "Epoch 764/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8627 - root_mean_squared_error: 2.8041 - val_loss: 8.0978 - val_root_mean_squared_error: 2.8457\n",
      "Epoch 765/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7731 - root_mean_squared_error: 2.7880 - val_loss: 8.0990 - val_root_mean_squared_error: 2.8459\n",
      "Epoch 766/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7986 - root_mean_squared_error: 2.7926 - val_loss: 8.1023 - val_root_mean_squared_error: 2.8465\n",
      "Epoch 767/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.9134 - root_mean_squared_error: 2.8131 - val_loss: 8.1094 - val_root_mean_squared_error: 2.8477\n",
      "Epoch 768/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8726 - root_mean_squared_error: 2.8058 - val_loss: 8.1248 - val_root_mean_squared_error: 2.8504\n",
      "Epoch 769/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8475 - root_mean_squared_error: 2.8013 - val_loss: 8.0667 - val_root_mean_squared_error: 2.8402\n",
      "Epoch 770/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7689 - root_mean_squared_error: 2.7873 - val_loss: 8.0707 - val_root_mean_squared_error: 2.8409\n",
      "Epoch 771/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7617 - root_mean_squared_error: 2.7860 - val_loss: 8.2183 - val_root_mean_squared_error: 2.8668\n",
      "Epoch 772/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.8075 - root_mean_squared_error: 2.7942 - val_loss: 8.0527 - val_root_mean_squared_error: 2.8377\n",
      "Epoch 773/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7343 - root_mean_squared_error: 2.7811 - val_loss: 8.2458 - val_root_mean_squared_error: 2.8716\n",
      "Epoch 774/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7116 - root_mean_squared_error: 2.7770 - val_loss: 8.0557 - val_root_mean_squared_error: 2.8383\n",
      "Epoch 775/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7640 - root_mean_squared_error: 2.7864 - val_loss: 8.1309 - val_root_mean_squared_error: 2.8515\n",
      "Epoch 776/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7459 - root_mean_squared_error: 2.7831 - val_loss: 8.1771 - val_root_mean_squared_error: 2.8596\n",
      "Epoch 777/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.7303 - root_mean_squared_error: 2.7803 - val_loss: 8.0385 - val_root_mean_squared_error: 2.8352\n",
      "Epoch 778/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6844 - root_mean_squared_error: 2.7721 - val_loss: 8.1833 - val_root_mean_squared_error: 2.8606\n",
      "Epoch 779/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7081 - root_mean_squared_error: 2.7764 - val_loss: 8.0413 - val_root_mean_squared_error: 2.8357\n",
      "Epoch 780/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7694 - root_mean_squared_error: 2.7874 - val_loss: 8.1974 - val_root_mean_squared_error: 2.8631\n",
      "Epoch 781/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7659 - root_mean_squared_error: 2.7867 - val_loss: 8.0327 - val_root_mean_squared_error: 2.8342\n",
      "Epoch 782/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6836 - root_mean_squared_error: 2.7719 - val_loss: 8.0827 - val_root_mean_squared_error: 2.8430\n",
      "Epoch 783/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7037 - root_mean_squared_error: 2.7756 - val_loss: 8.0625 - val_root_mean_squared_error: 2.8394\n",
      "Epoch 784/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.7659 - root_mean_squared_error: 2.7867 - val_loss: 8.1181 - val_root_mean_squared_error: 2.8492\n",
      "Epoch 785/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.6979 - root_mean_squared_error: 2.7745 - val_loss: 8.0407 - val_root_mean_squared_error: 2.8356\n",
      "Epoch 786/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17/17 [==============================] - 0s 3ms/step - loss: 7.6474 - root_mean_squared_error: 2.7654 - val_loss: 8.1151 - val_root_mean_squared_error: 2.8487\n",
      "Epoch 787/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6499 - root_mean_squared_error: 2.7658 - val_loss: 8.0433 - val_root_mean_squared_error: 2.8361\n",
      "Epoch 788/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6850 - root_mean_squared_error: 2.7722 - val_loss: 8.1237 - val_root_mean_squared_error: 2.8502\n",
      "Epoch 789/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6756 - root_mean_squared_error: 2.7705 - val_loss: 8.0220 - val_root_mean_squared_error: 2.8323\n",
      "Epoch 790/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.7229 - root_mean_squared_error: 2.7790 - val_loss: 8.0787 - val_root_mean_squared_error: 2.8423\n",
      "Epoch 791/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6543 - root_mean_squared_error: 2.7666 - val_loss: 8.0190 - val_root_mean_squared_error: 2.8318\n",
      "Epoch 792/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6845 - root_mean_squared_error: 2.7721 - val_loss: 8.1133 - val_root_mean_squared_error: 2.8484\n",
      "Epoch 793/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6471 - root_mean_squared_error: 2.7653 - val_loss: 7.9571 - val_root_mean_squared_error: 2.8208\n",
      "Epoch 794/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6599 - root_mean_squared_error: 2.7676 - val_loss: 8.0539 - val_root_mean_squared_error: 2.8379\n",
      "Epoch 795/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.7311 - root_mean_squared_error: 2.7805 - val_loss: 8.0902 - val_root_mean_squared_error: 2.8443\n",
      "Epoch 796/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6131 - root_mean_squared_error: 2.7592 - val_loss: 8.1276 - val_root_mean_squared_error: 2.8509\n",
      "Epoch 797/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.6633 - root_mean_squared_error: 2.7683 - val_loss: 8.0474 - val_root_mean_squared_error: 2.8368\n",
      "Epoch 798/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6207 - root_mean_squared_error: 2.7606 - val_loss: 8.0066 - val_root_mean_squared_error: 2.8296\n",
      "Epoch 799/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6048 - root_mean_squared_error: 2.7577 - val_loss: 8.1075 - val_root_mean_squared_error: 2.8474\n",
      "Epoch 800/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6367 - root_mean_squared_error: 2.7635 - val_loss: 8.0077 - val_root_mean_squared_error: 2.8298\n",
      "Epoch 801/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6530 - root_mean_squared_error: 2.7664 - val_loss: 8.0143 - val_root_mean_squared_error: 2.8309\n",
      "Epoch 802/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6145 - root_mean_squared_error: 2.7594 - val_loss: 8.0290 - val_root_mean_squared_error: 2.8335\n",
      "Epoch 803/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6547 - root_mean_squared_error: 2.7667 - val_loss: 7.9581 - val_root_mean_squared_error: 2.8210\n",
      "Epoch 804/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6742 - root_mean_squared_error: 2.7702 - val_loss: 8.1000 - val_root_mean_squared_error: 2.8461\n",
      "Epoch 805/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5984 - root_mean_squared_error: 2.7565 - val_loss: 8.0218 - val_root_mean_squared_error: 2.8323\n",
      "Epoch 806/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5781 - root_mean_squared_error: 2.7528 - val_loss: 7.9957 - val_root_mean_squared_error: 2.8277\n",
      "Epoch 807/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5761 - root_mean_squared_error: 2.7525 - val_loss: 8.0494 - val_root_mean_squared_error: 2.8371\n",
      "Epoch 808/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.5637 - root_mean_squared_error: 2.7502 - val_loss: 8.0048 - val_root_mean_squared_error: 2.8293\n",
      "Epoch 809/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.5840 - root_mean_squared_error: 2.7539 - val_loss: 7.9822 - val_root_mean_squared_error: 2.8253\n",
      "Epoch 810/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5679 - root_mean_squared_error: 2.7510 - val_loss: 7.9787 - val_root_mean_squared_error: 2.8247\n",
      "Epoch 811/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5746 - root_mean_squared_error: 2.7522 - val_loss: 8.0285 - val_root_mean_squared_error: 2.8335\n",
      "Epoch 812/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5625 - root_mean_squared_error: 2.7500 - val_loss: 7.9817 - val_root_mean_squared_error: 2.8252\n",
      "Epoch 813/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5720 - root_mean_squared_error: 2.7517 - val_loss: 8.0609 - val_root_mean_squared_error: 2.8392\n",
      "Epoch 814/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5782 - root_mean_squared_error: 2.7529 - val_loss: 7.9371 - val_root_mean_squared_error: 2.8173\n",
      "Epoch 815/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5635 - root_mean_squared_error: 2.7502 - val_loss: 7.9355 - val_root_mean_squared_error: 2.8170\n",
      "Epoch 816/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5708 - root_mean_squared_error: 2.7515 - val_loss: 8.0296 - val_root_mean_squared_error: 2.8336\n",
      "Epoch 817/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.5793 - root_mean_squared_error: 2.7531 - val_loss: 7.9475 - val_root_mean_squared_error: 2.8191\n",
      "Epoch 818/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5561 - root_mean_squared_error: 2.7488 - val_loss: 8.0664 - val_root_mean_squared_error: 2.8401\n",
      "Epoch 819/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.5288 - root_mean_squared_error: 2.7439 - val_loss: 7.9486 - val_root_mean_squared_error: 2.8193\n",
      "Epoch 820/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5572 - root_mean_squared_error: 2.7490 - val_loss: 7.9659 - val_root_mean_squared_error: 2.8224\n",
      "Epoch 821/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.5317 - root_mean_squared_error: 2.7444 - val_loss: 7.9603 - val_root_mean_squared_error: 2.8214\n",
      "Epoch 822/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.5339 - root_mean_squared_error: 2.7448 - val_loss: 7.9639 - val_root_mean_squared_error: 2.8220\n",
      "Epoch 823/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5309 - root_mean_squared_error: 2.7442 - val_loss: 7.9213 - val_root_mean_squared_error: 2.8145\n",
      "Epoch 824/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4974 - root_mean_squared_error: 2.7381 - val_loss: 8.0076 - val_root_mean_squared_error: 2.8298\n",
      "Epoch 825/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4994 - root_mean_squared_error: 2.7385 - val_loss: 7.8972 - val_root_mean_squared_error: 2.8102\n",
      "Epoch 826/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.4926 - root_mean_squared_error: 2.7373 - val_loss: 8.0300 - val_root_mean_squared_error: 2.8337\n",
      "Epoch 827/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5215 - root_mean_squared_error: 2.7425 - val_loss: 7.9707 - val_root_mean_squared_error: 2.8232\n",
      "Epoch 828/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.5044 - root_mean_squared_error: 2.7394 - val_loss: 7.9670 - val_root_mean_squared_error: 2.8226\n",
      "Epoch 829/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4998 - root_mean_squared_error: 2.7386 - val_loss: 7.9210 - val_root_mean_squared_error: 2.8144\n",
      "Epoch 830/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.5962 - root_mean_squared_error: 2.7561 - val_loss: 8.1271 - val_root_mean_squared_error: 2.8508\n",
      "Epoch 831/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.6541 - root_mean_squared_error: 2.7666 - val_loss: 7.9223 - val_root_mean_squared_error: 2.8147\n",
      "Epoch 832/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4887 - root_mean_squared_error: 2.7365 - val_loss: 7.9809 - val_root_mean_squared_error: 2.8250\n",
      "Epoch 833/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5020 - root_mean_squared_error: 2.7390 - val_loss: 7.9258 - val_root_mean_squared_error: 2.8153\n",
      "Epoch 834/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4890 - root_mean_squared_error: 2.7366 - val_loss: 7.9432 - val_root_mean_squared_error: 2.8184\n",
      "Epoch 835/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4950 - root_mean_squared_error: 2.7377 - val_loss: 7.9967 - val_root_mean_squared_error: 2.8278\n",
      "Epoch 836/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4854 - root_mean_squared_error: 2.7359 - val_loss: 7.9373 - val_root_mean_squared_error: 2.8173\n",
      "Epoch 837/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5026 - root_mean_squared_error: 2.7391 - val_loss: 7.8824 - val_root_mean_squared_error: 2.8076\n",
      "Epoch 838/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.4840 - root_mean_squared_error: 2.7357 - val_loss: 8.0124 - val_root_mean_squared_error: 2.8306\n",
      "Epoch 839/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5526 - root_mean_squared_error: 2.7482 - val_loss: 7.9476 - val_root_mean_squared_error: 2.8191\n",
      "Epoch 840/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.4781 - root_mean_squared_error: 2.7346 - val_loss: 7.8845 - val_root_mean_squared_error: 2.8079\n",
      "Epoch 841/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4378 - root_mean_squared_error: 2.7272 - val_loss: 7.9766 - val_root_mean_squared_error: 2.8243\n",
      "Epoch 842/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4609 - root_mean_squared_error: 2.7315 - val_loss: 7.9154 - val_root_mean_squared_error: 2.8134\n",
      "Epoch 843/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.4639 - root_mean_squared_error: 2.7320 - val_loss: 7.9189 - val_root_mean_squared_error: 2.8141\n",
      "Epoch 844/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4709 - root_mean_squared_error: 2.7333 - val_loss: 7.9335 - val_root_mean_squared_error: 2.8166\n",
      "Epoch 845/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4623 - root_mean_squared_error: 2.7317 - val_loss: 7.8636 - val_root_mean_squared_error: 2.8042\n",
      "Epoch 846/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4833 - root_mean_squared_error: 2.7356 - val_loss: 7.9912 - val_root_mean_squared_error: 2.8269\n",
      "Epoch 847/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4953 - root_mean_squared_error: 2.7378 - val_loss: 7.9258 - val_root_mean_squared_error: 2.8153\n",
      "Epoch 848/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.4646 - root_mean_squared_error: 2.7321 - val_loss: 7.9089 - val_root_mean_squared_error: 2.8123\n",
      "Epoch 849/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4691 - root_mean_squared_error: 2.7330 - val_loss: 7.8747 - val_root_mean_squared_error: 2.8062\n",
      "Epoch 850/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5275 - root_mean_squared_error: 2.7436 - val_loss: 7.9046 - val_root_mean_squared_error: 2.8115\n",
      "Epoch 851/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5052 - root_mean_squared_error: 2.7396 - val_loss: 7.9217 - val_root_mean_squared_error: 2.8146\n",
      "Epoch 852/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.5058 - root_mean_squared_error: 2.7397 - val_loss: 8.0811 - val_root_mean_squared_error: 2.8427\n",
      "Epoch 853/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4912 - root_mean_squared_error: 2.7370 - val_loss: 7.8788 - val_root_mean_squared_error: 2.8069\n",
      "Epoch 854/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4466 - root_mean_squared_error: 2.7288 - val_loss: 7.9641 - val_root_mean_squared_error: 2.8221\n",
      "Epoch 855/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4259 - root_mean_squared_error: 2.7250 - val_loss: 7.8828 - val_root_mean_squared_error: 2.8076\n",
      "Epoch 856/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3927 - root_mean_squared_error: 2.7189 - val_loss: 7.9400 - val_root_mean_squared_error: 2.8178\n",
      "Epoch 857/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4228 - root_mean_squared_error: 2.7245 - val_loss: 7.8620 - val_root_mean_squared_error: 2.8039\n",
      "Epoch 858/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3955 - root_mean_squared_error: 2.7195 - val_loss: 7.8566 - val_root_mean_squared_error: 2.8030\n",
      "Epoch 859/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4169 - root_mean_squared_error: 2.7234 - val_loss: 7.8936 - val_root_mean_squared_error: 2.8096\n",
      "Epoch 860/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4292 - root_mean_squared_error: 2.7257 - val_loss: 7.8294 - val_root_mean_squared_error: 2.7981\n",
      "Epoch 861/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3981 - root_mean_squared_error: 2.7199 - val_loss: 7.9481 - val_root_mean_squared_error: 2.8192\n",
      "Epoch 862/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4363 - root_mean_squared_error: 2.7270 - val_loss: 7.8465 - val_root_mean_squared_error: 2.8012\n",
      "Epoch 863/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4646 - root_mean_squared_error: 2.7321 - val_loss: 7.9038 - val_root_mean_squared_error: 2.8114\n",
      "Epoch 864/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.4201 - root_mean_squared_error: 2.7240 - val_loss: 7.8003 - val_root_mean_squared_error: 2.7929\n",
      "Epoch 865/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4477 - root_mean_squared_error: 2.7290 - val_loss: 7.8971 - val_root_mean_squared_error: 2.8102\n",
      "Epoch 866/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4047 - root_mean_squared_error: 2.7212 - val_loss: 7.8323 - val_root_mean_squared_error: 2.7986\n",
      "Epoch 867/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3845 - root_mean_squared_error: 2.7174 - val_loss: 7.8181 - val_root_mean_squared_error: 2.7961\n",
      "Epoch 868/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3750 - root_mean_squared_error: 2.7157 - val_loss: 7.8357 - val_root_mean_squared_error: 2.7992\n",
      "Epoch 869/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3884 - root_mean_squared_error: 2.7182 - val_loss: 7.8551 - val_root_mean_squared_error: 2.8027\n",
      "Epoch 870/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4120 - root_mean_squared_error: 2.7225 - val_loss: 7.8192 - val_root_mean_squared_error: 2.7963\n",
      "Epoch 871/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4070 - root_mean_squared_error: 2.7216 - val_loss: 7.9183 - val_root_mean_squared_error: 2.8140\n",
      "Epoch 872/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3887 - root_mean_squared_error: 2.7182 - val_loss: 7.8398 - val_root_mean_squared_error: 2.8000\n",
      "Epoch 873/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3712 - root_mean_squared_error: 2.7150 - val_loss: 7.8173 - val_root_mean_squared_error: 2.7959\n",
      "Epoch 874/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3666 - root_mean_squared_error: 2.7141 - val_loss: 7.8321 - val_root_mean_squared_error: 2.7986\n",
      "Epoch 875/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3805 - root_mean_squared_error: 2.7167 - val_loss: 7.8062 - val_root_mean_squared_error: 2.7940\n",
      "Epoch 876/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3548 - root_mean_squared_error: 2.7120 - val_loss: 7.8270 - val_root_mean_squared_error: 2.7977\n",
      "Epoch 877/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.4382 - root_mean_squared_error: 2.7273 - val_loss: 7.8018 - val_root_mean_squared_error: 2.7932\n",
      "Epoch 878/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3511 - root_mean_squared_error: 2.7113 - val_loss: 7.8043 - val_root_mean_squared_error: 2.7936\n",
      "Epoch 879/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3632 - root_mean_squared_error: 2.7135 - val_loss: 7.8207 - val_root_mean_squared_error: 2.7966\n",
      "Epoch 880/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17/17 [==============================] - 0s 2ms/step - loss: 7.4381 - root_mean_squared_error: 2.7273 - val_loss: 7.8658 - val_root_mean_squared_error: 2.8046\n",
      "Epoch 881/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3729 - root_mean_squared_error: 2.7153 - val_loss: 7.8060 - val_root_mean_squared_error: 2.7939\n",
      "Epoch 882/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3593 - root_mean_squared_error: 2.7128 - val_loss: 7.8445 - val_root_mean_squared_error: 2.8008\n",
      "Epoch 883/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3574 - root_mean_squared_error: 2.7125 - val_loss: 7.8818 - val_root_mean_squared_error: 2.8075\n",
      "Epoch 884/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3546 - root_mean_squared_error: 2.7119 - val_loss: 7.7830 - val_root_mean_squared_error: 2.7898\n",
      "Epoch 885/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3752 - root_mean_squared_error: 2.7157 - val_loss: 7.8626 - val_root_mean_squared_error: 2.8040\n",
      "Epoch 886/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3061 - root_mean_squared_error: 2.7030 - val_loss: 7.7719 - val_root_mean_squared_error: 2.7878\n",
      "Epoch 887/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3264 - root_mean_squared_error: 2.7067 - val_loss: 7.8353 - val_root_mean_squared_error: 2.7992\n",
      "Epoch 888/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3389 - root_mean_squared_error: 2.7090 - val_loss: 7.7728 - val_root_mean_squared_error: 2.7880\n",
      "Epoch 889/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3370 - root_mean_squared_error: 2.7087 - val_loss: 7.8074 - val_root_mean_squared_error: 2.7942\n",
      "Epoch 890/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3270 - root_mean_squared_error: 2.7068 - val_loss: 7.7848 - val_root_mean_squared_error: 2.7901\n",
      "Epoch 891/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3548 - root_mean_squared_error: 2.7120 - val_loss: 7.8638 - val_root_mean_squared_error: 2.8043\n",
      "Epoch 892/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3376 - root_mean_squared_error: 2.7088 - val_loss: 7.8105 - val_root_mean_squared_error: 2.7947\n",
      "Epoch 893/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3447 - root_mean_squared_error: 2.7101 - val_loss: 7.8088 - val_root_mean_squared_error: 2.7944\n",
      "Epoch 894/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3260 - root_mean_squared_error: 2.7066 - val_loss: 7.8088 - val_root_mean_squared_error: 2.7944\n",
      "Epoch 895/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3332 - root_mean_squared_error: 2.7080 - val_loss: 7.7988 - val_root_mean_squared_error: 2.7926\n",
      "Epoch 896/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3580 - root_mean_squared_error: 2.7126 - val_loss: 7.7247 - val_root_mean_squared_error: 2.7793\n",
      "Epoch 897/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3070 - root_mean_squared_error: 2.7032 - val_loss: 7.8943 - val_root_mean_squared_error: 2.8097\n",
      "Epoch 898/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3255 - root_mean_squared_error: 2.7066 - val_loss: 7.7214 - val_root_mean_squared_error: 2.7787\n",
      "Epoch 899/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3453 - root_mean_squared_error: 2.7102 - val_loss: 7.8210 - val_root_mean_squared_error: 2.7966\n",
      "Epoch 900/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3338 - root_mean_squared_error: 2.7081 - val_loss: 7.8125 - val_root_mean_squared_error: 2.7951\n",
      "Epoch 901/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3462 - root_mean_squared_error: 2.7104 - val_loss: 7.7648 - val_root_mean_squared_error: 2.7865\n",
      "Epoch 902/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3819 - root_mean_squared_error: 2.7170 - val_loss: 7.8597 - val_root_mean_squared_error: 2.8035\n",
      "Epoch 903/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3669 - root_mean_squared_error: 2.7142 - val_loss: 7.7883 - val_root_mean_squared_error: 2.7907\n",
      "Epoch 904/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2820 - root_mean_squared_error: 2.6985 - val_loss: 7.7501 - val_root_mean_squared_error: 2.7839\n",
      "Epoch 905/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.2846 - root_mean_squared_error: 2.6990 - val_loss: 7.7145 - val_root_mean_squared_error: 2.7775\n",
      "Epoch 906/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.3171 - root_mean_squared_error: 2.7050 - val_loss: 7.7961 - val_root_mean_squared_error: 2.7921\n",
      "Epoch 907/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.2861 - root_mean_squared_error: 2.6993 - val_loss: 7.7667 - val_root_mean_squared_error: 2.7869\n",
      "Epoch 908/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2660 - root_mean_squared_error: 2.6956 - val_loss: 7.7383 - val_root_mean_squared_error: 2.7818\n",
      "Epoch 909/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2812 - root_mean_squared_error: 2.6984 - val_loss: 7.8125 - val_root_mean_squared_error: 2.7951\n",
      "Epoch 910/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2997 - root_mean_squared_error: 2.7018 - val_loss: 7.7026 - val_root_mean_squared_error: 2.7754\n",
      "Epoch 911/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2446 - root_mean_squared_error: 2.6916 - val_loss: 7.7531 - val_root_mean_squared_error: 2.7844\n",
      "Epoch 912/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2692 - root_mean_squared_error: 2.6961 - val_loss: 7.6907 - val_root_mean_squared_error: 2.7732\n",
      "Epoch 913/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2743 - root_mean_squared_error: 2.6971 - val_loss: 7.7240 - val_root_mean_squared_error: 2.7792\n",
      "Epoch 914/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2688 - root_mean_squared_error: 2.6961 - val_loss: 7.7519 - val_root_mean_squared_error: 2.7842\n",
      "Epoch 915/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.2925 - root_mean_squared_error: 2.7005 - val_loss: 7.7016 - val_root_mean_squared_error: 2.7752\n",
      "Epoch 916/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2512 - root_mean_squared_error: 2.6928 - val_loss: 7.7992 - val_root_mean_squared_error: 2.7927\n",
      "Epoch 917/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.2641 - root_mean_squared_error: 2.6952 - val_loss: 7.7278 - val_root_mean_squared_error: 2.7799\n",
      "Epoch 918/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2545 - root_mean_squared_error: 2.6934 - val_loss: 7.7575 - val_root_mean_squared_error: 2.7852\n",
      "Epoch 919/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2528 - root_mean_squared_error: 2.6931 - val_loss: 7.7282 - val_root_mean_squared_error: 2.7800\n",
      "Epoch 920/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2803 - root_mean_squared_error: 2.6982 - val_loss: 7.6869 - val_root_mean_squared_error: 2.7725\n",
      "Epoch 921/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.2495 - root_mean_squared_error: 2.6925 - val_loss: 7.7383 - val_root_mean_squared_error: 2.7818\n",
      "Epoch 922/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2347 - root_mean_squared_error: 2.6897 - val_loss: 7.6796 - val_root_mean_squared_error: 2.7712\n",
      "Epoch 923/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2767 - root_mean_squared_error: 2.6975 - val_loss: 7.8133 - val_root_mean_squared_error: 2.7952\n",
      "Epoch 924/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.2433 - root_mean_squared_error: 2.6913 - val_loss: 7.6553 - val_root_mean_squared_error: 2.7668\n",
      "Epoch 925/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2640 - root_mean_squared_error: 2.6952 - val_loss: 7.7147 - val_root_mean_squared_error: 2.7775\n",
      "Epoch 926/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.2488 - root_mean_squared_error: 2.6924 - val_loss: 7.6662 - val_root_mean_squared_error: 2.7688\n",
      "Epoch 927/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2328 - root_mean_squared_error: 2.6894 - val_loss: 7.7730 - val_root_mean_squared_error: 2.7880\n",
      "Epoch 928/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.2536 - root_mean_squared_error: 2.6932 - val_loss: 7.6702 - val_root_mean_squared_error: 2.7695\n",
      "Epoch 929/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2359 - root_mean_squared_error: 2.6900 - val_loss: 7.7421 - val_root_mean_squared_error: 2.7825\n",
      "Epoch 930/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2573 - root_mean_squared_error: 2.6939 - val_loss: 7.7177 - val_root_mean_squared_error: 2.7781\n",
      "Epoch 931/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2258 - root_mean_squared_error: 2.6881 - val_loss: 7.7013 - val_root_mean_squared_error: 2.7751\n",
      "Epoch 932/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2186 - root_mean_squared_error: 2.6867 - val_loss: 7.7212 - val_root_mean_squared_error: 2.7787\n",
      "Epoch 933/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2371 - root_mean_squared_error: 2.6902 - val_loss: 7.6848 - val_root_mean_squared_error: 2.7721\n",
      "Epoch 934/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2092 - root_mean_squared_error: 2.6850 - val_loss: 7.6744 - val_root_mean_squared_error: 2.7703\n",
      "Epoch 935/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.3078 - root_mean_squared_error: 2.7033 - val_loss: 7.7258 - val_root_mean_squared_error: 2.7795\n",
      "Epoch 936/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2302 - root_mean_squared_error: 2.6889 - val_loss: 7.7051 - val_root_mean_squared_error: 2.7758\n",
      "Epoch 937/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1807 - root_mean_squared_error: 2.6797 - val_loss: 7.7241 - val_root_mean_squared_error: 2.7792\n",
      "Epoch 938/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1914 - root_mean_squared_error: 2.6817 - val_loss: 7.7704 - val_root_mean_squared_error: 2.7875\n",
      "Epoch 939/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1943 - root_mean_squared_error: 2.6822 - val_loss: 7.6343 - val_root_mean_squared_error: 2.7630\n",
      "Epoch 940/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2326 - root_mean_squared_error: 2.6893 - val_loss: 7.7689 - val_root_mean_squared_error: 2.7873\n",
      "Epoch 941/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1698 - root_mean_squared_error: 2.6777 - val_loss: 7.6066 - val_root_mean_squared_error: 2.7580\n",
      "Epoch 942/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2127 - root_mean_squared_error: 2.6857 - val_loss: 7.8031 - val_root_mean_squared_error: 2.7934\n",
      "Epoch 943/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2165 - root_mean_squared_error: 2.6863 - val_loss: 7.6662 - val_root_mean_squared_error: 2.7688\n",
      "Epoch 944/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1877 - root_mean_squared_error: 2.6810 - val_loss: 7.6958 - val_root_mean_squared_error: 2.7741\n",
      "Epoch 945/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1963 - root_mean_squared_error: 2.6826 - val_loss: 7.6968 - val_root_mean_squared_error: 2.7743\n",
      "Epoch 946/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.2225 - root_mean_squared_error: 2.6875 - val_loss: 7.5930 - val_root_mean_squared_error: 2.7555\n",
      "Epoch 947/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1479 - root_mean_squared_error: 2.6735 - val_loss: 7.6692 - val_root_mean_squared_error: 2.7693\n",
      "Epoch 948/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1633 - root_mean_squared_error: 2.6764 - val_loss: 7.6893 - val_root_mean_squared_error: 2.7730\n",
      "Epoch 949/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1641 - root_mean_squared_error: 2.6766 - val_loss: 7.6325 - val_root_mean_squared_error: 2.7627\n",
      "Epoch 950/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1692 - root_mean_squared_error: 2.6775 - val_loss: 7.6393 - val_root_mean_squared_error: 2.7639\n",
      "Epoch 951/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.2028 - root_mean_squared_error: 2.6838 - val_loss: 7.7573 - val_root_mean_squared_error: 2.7852\n",
      "Epoch 952/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1670 - root_mean_squared_error: 2.6771 - val_loss: 7.6339 - val_root_mean_squared_error: 2.7629\n",
      "Epoch 953/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.2340 - root_mean_squared_error: 2.6896 - val_loss: 7.6481 - val_root_mean_squared_error: 2.7655\n",
      "Epoch 954/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2212 - root_mean_squared_error: 2.6872 - val_loss: 7.6402 - val_root_mean_squared_error: 2.7641\n",
      "Epoch 955/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1663 - root_mean_squared_error: 2.6770 - val_loss: 7.6770 - val_root_mean_squared_error: 2.7707\n",
      "Epoch 956/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1653 - root_mean_squared_error: 2.6768 - val_loss: 7.6228 - val_root_mean_squared_error: 2.7609\n",
      "Epoch 957/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1468 - root_mean_squared_error: 2.6733 - val_loss: 7.7379 - val_root_mean_squared_error: 2.7817\n",
      "Epoch 958/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1682 - root_mean_squared_error: 2.6773 - val_loss: 7.5754 - val_root_mean_squared_error: 2.7523\n",
      "Epoch 959/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1984 - root_mean_squared_error: 2.6830 - val_loss: 7.6809 - val_root_mean_squared_error: 2.7714\n",
      "Epoch 960/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1353 - root_mean_squared_error: 2.6712 - val_loss: 7.6312 - val_root_mean_squared_error: 2.7625\n",
      "Epoch 961/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1187 - root_mean_squared_error: 2.6681 - val_loss: 7.6050 - val_root_mean_squared_error: 2.7577\n",
      "Epoch 962/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1580 - root_mean_squared_error: 2.6755 - val_loss: 7.5777 - val_root_mean_squared_error: 2.7528\n",
      "Epoch 963/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.2064 - root_mean_squared_error: 2.6845 - val_loss: 7.8008 - val_root_mean_squared_error: 2.7930\n",
      "Epoch 964/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1284 - root_mean_squared_error: 2.6699 - val_loss: 7.5620 - val_root_mean_squared_error: 2.7499\n",
      "Epoch 965/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1654 - root_mean_squared_error: 2.6768 - val_loss: 7.6921 - val_root_mean_squared_error: 2.7735\n",
      "Epoch 966/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1597 - root_mean_squared_error: 2.6758 - val_loss: 7.6150 - val_root_mean_squared_error: 2.7595\n",
      "Epoch 967/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1326 - root_mean_squared_error: 2.6707 - val_loss: 7.6010 - val_root_mean_squared_error: 2.7570\n",
      "Epoch 968/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0919 - root_mean_squared_error: 2.6631 - val_loss: 7.6329 - val_root_mean_squared_error: 2.7628\n",
      "Epoch 969/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1335 - root_mean_squared_error: 2.6709 - val_loss: 7.5911 - val_root_mean_squared_error: 2.7552\n",
      "Epoch 970/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1194 - root_mean_squared_error: 2.6682 - val_loss: 7.6024 - val_root_mean_squared_error: 2.7573\n",
      "Epoch 971/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1046 - root_mean_squared_error: 2.6655 - val_loss: 7.6078 - val_root_mean_squared_error: 2.7582\n",
      "Epoch 972/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1098 - root_mean_squared_error: 2.6664 - val_loss: 7.5640 - val_root_mean_squared_error: 2.7503\n",
      "Epoch 973/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0904 - root_mean_squared_error: 2.6628 - val_loss: 7.6291 - val_root_mean_squared_error: 2.7621\n",
      "Epoch 974/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1180 - root_mean_squared_error: 2.6680 - val_loss: 7.5603 - val_root_mean_squared_error: 2.7496\n",
      "Epoch 975/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1195 - root_mean_squared_error: 2.6682 - val_loss: 7.6317 - val_root_mean_squared_error: 2.7625\n",
      "Epoch 976/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1491 - root_mean_squared_error: 2.6738 - val_loss: 7.6665 - val_root_mean_squared_error: 2.7688\n",
      "Epoch 977/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1213 - root_mean_squared_error: 2.6686 - val_loss: 7.6370 - val_root_mean_squared_error: 2.7635\n",
      "Epoch 978/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0896 - root_mean_squared_error: 2.6626 - val_loss: 7.6447 - val_root_mean_squared_error: 2.7649\n",
      "Epoch 979/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.1020 - root_mean_squared_error: 2.6650 - val_loss: 7.6010 - val_root_mean_squared_error: 2.7570\n",
      "Epoch 980/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0814 - root_mean_squared_error: 2.6611 - val_loss: 7.6110 - val_root_mean_squared_error: 2.7588\n",
      "Epoch 981/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.0509 - root_mean_squared_error: 2.6554 - val_loss: 7.5427 - val_root_mean_squared_error: 2.7464\n",
      "Epoch 982/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.0808 - root_mean_squared_error: 2.6610 - val_loss: 7.6263 - val_root_mean_squared_error: 2.7616\n",
      "Epoch 983/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1406 - root_mean_squared_error: 2.6722 - val_loss: 7.5716 - val_root_mean_squared_error: 2.7516\n",
      "Epoch 984/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.0782 - root_mean_squared_error: 2.6605 - val_loss: 7.6053 - val_root_mean_squared_error: 2.7578\n",
      "Epoch 985/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0697 - root_mean_squared_error: 2.6589 - val_loss: 7.5328 - val_root_mean_squared_error: 2.7446\n",
      "Epoch 986/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.0513 - root_mean_squared_error: 2.6554 - val_loss: 7.5608 - val_root_mean_squared_error: 2.7497\n",
      "Epoch 987/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0607 - root_mean_squared_error: 2.6572 - val_loss: 7.5426 - val_root_mean_squared_error: 2.7464\n",
      "Epoch 988/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0567 - root_mean_squared_error: 2.6564 - val_loss: 7.5955 - val_root_mean_squared_error: 2.7560\n",
      "Epoch 989/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0560 - root_mean_squared_error: 2.6563 - val_loss: 7.5250 - val_root_mean_squared_error: 2.7432\n",
      "Epoch 990/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0801 - root_mean_squared_error: 2.6608 - val_loss: 7.5691 - val_root_mean_squared_error: 2.7512\n",
      "Epoch 991/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0389 - root_mean_squared_error: 2.6531 - val_loss: 7.5415 - val_root_mean_squared_error: 2.7462\n",
      "Epoch 992/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0320 - root_mean_squared_error: 2.6518 - val_loss: 7.5525 - val_root_mean_squared_error: 2.7482\n",
      "Epoch 993/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.0475 - root_mean_squared_error: 2.6547 - val_loss: 7.5415 - val_root_mean_squared_error: 2.7462\n",
      "Epoch 994/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0552 - root_mean_squared_error: 2.6562 - val_loss: 7.5541 - val_root_mean_squared_error: 2.7485\n",
      "Epoch 995/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0804 - root_mean_squared_error: 2.6609 - val_loss: 7.5777 - val_root_mean_squared_error: 2.7528\n",
      "Epoch 996/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0846 - root_mean_squared_error: 2.6617 - val_loss: 7.5571 - val_root_mean_squared_error: 2.7490\n",
      "Epoch 997/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.1096 - root_mean_squared_error: 2.6664 - val_loss: 7.5433 - val_root_mean_squared_error: 2.7465\n",
      "Epoch 998/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0219 - root_mean_squared_error: 2.6499 - val_loss: 7.5671 - val_root_mean_squared_error: 2.7508\n",
      "Epoch 999/1000\n",
      "17/17 [==============================] - 0s 2ms/step - loss: 7.0397 - root_mean_squared_error: 2.6532 - val_loss: 7.5097 - val_root_mean_squared_error: 2.7404\n",
      "Epoch 1000/1000\n",
      "17/17 [==============================] - 0s 3ms/step - loss: 7.0758 - root_mean_squared_error: 2.6600 - val_loss: 7.5032 - val_root_mean_squared_error: 2.7392\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.History at 0x21983815940>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(x=X_train, y=y_train, epochs=1000, batch_size=64, validation_data=(X_test,y_test))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "122ecafc",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<keras.src.callbacks.History at 0x21983815940>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.history"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "56171b26",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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2Wnz66afYvHkzoqNdT8NYsGABSktL0aNHD3Tq1Mnv+XOmKQgpwjsDZYDawqaJiIjarnvvvbfZCuAZGRnIyMi4aPyYMWMwZsyYS443cOBAFBQUIDw8vOPdPbd9+3aMHj0a8fHxEAQBH3744SVjp0yZAkEQsGLFCrftVqsV06ZNQ0xMDEJCQpCVlYXjx4+7xVRWViI7OxtGoxFGoxHZ2dmoqqpyiyktLcXo0aMREhKCmJgYTJ8+HTabTaYjlZcm8ioAgMHKpomIiMhfAto01dXVoV+/fli1atVl4z788EPs2rUL8fHN16bIycnBpk2bsGHDBhQUFKC2thaZmZluF4qNHz8excXFyM3NRW5uLoqLi5GdnS3tdzgcGDVqFOrq6lBQUIANGzbggw8+wKxZs+Q7WBmFRncBAEQ6zqLBHrgL4oiIiDqSgJ6eGzlyJEaOHHnZmBMnTuDhhx/Gf/7zH4waNcptn9lsxhtvvIG1a9di+PDhAIB169YhISEBW7duRUZGBg4ePIjc3Fzs3LkTAwYMAACsXr0aaWlpKCkpQXJyMvLy8nDgwAEcO3ZMasyWLl2Ke++9FwsXLkR4eLgPjr7l9NGumaY4oRInqxvQNTp476QgIiIKFm36mian04ns7Gw8+uij6NOnT7P9RUVFsNvtSE9Pl7bFx8cjJSUFhYWFyMjIwI4dO2A0GqWGCXCdEzUajSgsLERycjJ27NiBlJQUt5msjIwMWK1WFBUV4ZZbbrloflarFVarVXpdXV0NALDb7bDb7a0+/iZNY0lj6jtBDSBWqMK+s3WID9fI9lkdWbM6k8+w1v7BOvuHr+pst9shiiKcTiecTqesYwcrURSlf72tidPphCiKsNvtUCqVbvs8/dm16abpb3/7G1QqlfSwvguVl5dDo9EgMjLSbXtcXBzKy8ulmNjY2GbvjY2NdYuJi4tz2x8ZGQmNRiPFXMzixYuxYMGCZtvz8vJgMMizENj58vPzAQAqhwWjAIQL9fjsiy9wKlYr+2d1ZE11Jt9jrf2DdfYPueusUqlgMplQU1PTZq+xDZSamhqv32O1WmGxWLB9+/Zmq4zX13v2PL822zQVFRXhxRdfxJ49e7x+krEoim7vudj7WxJzoblz52LmzJnS6+rqaiQkJCA9PV3WU3p2ux35+fkYMWKEa0VUUYR17wxoxQYkXRWD20f8RrbP6sia1Zl8hrX2D9bZP3xVZ4fDgcOHD0OhULS5y0QCRRRF1NTUICwszOve4MyZM9Dr9Rg2bFizmaamM0VX0mabpi+//BIVFRVITEyUtjkcDsyaNQsrVqzATz/9BJPJBJvNhsrKSrfZpoqKCgwaNAgAYDKZcPLkyWbjnzp1SppdMplM2LVrl9v+yspK2O32ZjNQ59NqtdBqm8/yqNVqn/wH6vxxz2g6QWs9hkZzGf9jKDNf/fyoOdbaP1hn/5C7zmq1GpGRkTh9+jQUCgUMBoPXjUJ743Q6YbPZYLVaPV5yQBRF1NfX4/Tp04iMjIROp2sW4+nPrc02TdnZ2dLF3U0yMjKQnZ2N++67DwCQmpoKtVqN/Px8jB07FgBQVlaGffv24fnnnwcApKWlwWw2Y/fu3dKTknft2gWz2Sw1VmlpaVi4cCHKysrQubPrWW55eXnQarVITU31y/F6y6bvBFiPwWEuC3QqRETkIyaTCYBrMoBcDZDFYoFer/e6gYyIiJDq2VIBbZpqa2vxww8/SK+PHDmC4uJiREVFITExUVoBtIlarYbJZEJycjIAwGg0YtKkSZg1axaio6MRFRWF2bNno2/fvlLD1atXL9x2222YPHkyXnvtNQDAAw88gMzMTGmc9PR09O7dG9nZ2ViyZAnOnj2L2bNnY/LkyW12StQRYgKqABUXuCQiarcEQUDnzp0RGxvLC/rhOhW6fft23HzzzV7N6qnV6man5FoioE3T119/7XZnWtP1QRMnTsSaNWs8GmP58uVQqVQYO3YsLBYLhg0bhjVr1rgV5+2338b06dOlu+yysrLc1oZSKpXYsmULpk6disGDB0Ov12P8+PF44YUXZDhK3xDCXDNiOjZNRETtnlKplOWPfrBTKpVobGyETqcLyCnngDZNQ4cOlW4f9MRPP/3UbJtOp8PKlSuxcuXKS74vKioK69atu+zYiYmJ+Pjjjz3OJdCUEa6mKdR+KsCZEBERdQx8YG+QMkS4zsuGOargdHreeBIREVHLsGkKUoZI1119UahBlYXnuYmIiHyNTVOQUoV1AgBECdU4U2u9QjQRERG1FpumYGWIAQBEoRqna9g0ERER+RqbpmAV4mqaNIID1eazAU6GiIio/WPTFKzUejQIrlVN6ysv/Xw8IiIikgebpiBWr3Y9OqbBzLWaiIiIfI1NUxCzaVxNU2MN12oiIiLyNTZNQaxR53rMjFDHpomIiMjX2DQFMfHcHXQKy5kAZ0JERNT+sWkKYopQ11pNaivvniMiIvI1Nk1BTBPuapr09soAZ0JERNT+sWkKYvoI16NUwhxm2B3OAGdDRETUvrFpCmL6iFgArkepmPn8OSIiIp9i0xTElKFNTVMNqurZNBEREfkSm6ZgFuJaciAa1aiq4/PniIiIfIlNUzAzuJomnWBHdU11gJMhIiJq39g0BTNNKBqhAgDUm7nAJRERkS+xaQpmgoB6ZRgAwFbDBS6JiIh8iU1TkGtQGwEA9loucElERORLbJqCnP1c0+SoY9NERETkS2yagpxDGwEAEC1cFZyIiMiX2DQFO30kAEDRwKaJiIjIl9g0BTnB4Gqa1DZzgDMhIiJq39g0BTlVqGutJo2dTRMREZEvsWkKcppzTZO+kYtbEhER+RKbpiCnD48BAISJNbA1OgOcDRERUfvFpinI6c41TUbUospiC3A2RERE7RebpiCnCHFdCB4h1KGq3h7gbIiIiNovNk3B7tySAxGoZdNERETkQ2yagt25pkkv2GCu4cXgREREvsKmKdhpw+E492O0mPnQXiIiIl9h0xTsBAEWZRgAwF7LpomIiMhXAto0bd++HaNHj0Z8fDwEQcCHH34o7bPb7XjsscfQt29fhISEID4+HhMmTMDPP//sNobVasW0adMQExODkJAQZGVl4fjx424xlZWVyM7OhtFohNFoRHZ2NqqqqtxiSktLMXr0aISEhCAmJgbTp0+HzRYcd6NZVK6H9jbyob1EREQ+E9Cmqa6uDv369cOqVaua7auvr8eePXvw17/+FXv27MHGjRtx6NAhZGVlucXl5ORg06ZN2LBhAwoKClBbW4vMzEw4HA4pZvz48SguLkZubi5yc3NRXFyM7Oxsab/D4cCoUaNQV1eHgoICbNiwAR988AFmzZrlu4OXkU3taprEejZNREREvqIK5IePHDkSI0eOvOg+o9GI/Px8t20rV67Er3/9a5SWliIxMRFmsxlvvPEG1q5di+HDhwMA1q1bh4SEBGzduhUZGRk4ePAgcnNzsXPnTgwYMAAAsHr1aqSlpaGkpATJycnIy8vDgQMHcOzYMcTHxwMAli5dinvvvRcLFy5EeHj4RXO0Wq2wWq3S6+pq14XYdrsddrt8d7I1jXWpMRs15/KrPyPr53Y0V6ozyYe19g/W2T9YZ//xVa09HS+gTZO3zGYzBEFAREQEAKCoqAh2ux3p6elSTHx8PFJSUlBYWIiMjAzs2LEDRqNRapgAYODAgTAajSgsLERycjJ27NiBlJQUqWECgIyMDFitVhQVFeGWW265aD6LFy/GggULmm3Py8uDwWCQ6ah/cWET2STR4kRXALWnf8Ynn3wi++d2NJeqM8mPtfYP1tk/WGf/kbvW9fX1HsUFTdPU0NCAxx9/HOPHj5dmfsrLy6HRaBAZGekWGxcXh/LycikmNja22XixsbFuMXFxcW77IyMjodFopJiLmTt3LmbOnCm9rq6uRkJCAtLT0y85O9USdrsd+fn5GDFiBNRqdbP9xys/AX7aAaMWuP3222X73I7mSnUm+bDW/sE6+wfr7D++qnXTmaIrCYqmyW63449//COcTidefvnlK8aLoghBEKTX53/fmpgLabVaaLXaZtvVarVPfnEuNa7y3KrgansNf2Fl4KufHzXHWvsH6+wfrLP/yF1rT8dq80sO2O12jB07FkeOHEF+fr7bDI7JZILNZkNlZaXbeyoqKqSZI5PJhJMnTzYb99SpU24xF84oVVZWwm63N5uBaotUhggAgLaxJrCJEBERtWNtumlqapi+//57bN26FdHR0W77U1NToVar3c5tlpWVYd++fRg0aBAAIC0tDWazGbt375Zidu3aBbPZ7Bazb98+lJWVSTF5eXnQarVITU315SHKQnNupknnqA1wJkRERO1XQE/P1dbW4ocffpBeHzlyBMXFxYiKikJ8fDx+//vfY8+ePfj444/hcDik2aCoqChoNBoYjUZMmjQJs2bNQnR0NKKiojB79mz07dtXupuuV69euO222zB58mS89tprAIAHHngAmZmZSE5OBgCkp6ejd+/eyM7OxpIlS3D27FnMnj0bkydPlvXaJF/Rhp57lIpYB4dThFJx6VOKRERE1DIBbZq+/vprtzvTmi6qnjhxIubPn4+PPvoIAHDddde5ve/zzz/H0KFDAQDLly+HSqXC2LFjYbFYMGzYMKxZswZKpVKKf/vttzF9+nTpLrusrCy3taGUSiW2bNmCqVOnYvDgwdDr9Rg/fjxeeOEFXxy27HRhUQCAcNSjtqERRgPPqRMREcktoE3T0KFDIYriJfdfbl8TnU6HlStXYuXKlZeMiYqKwrp16y47TmJiIj7++OMrfl5bpD53ei5cqEN1g51NExERkQ+06WuayEM614rg4aiH2cLF1YiIiHyBTVN7oHNddxUKC6rrrVcIJiIiopZg09QeaF1Nk0IQUV9bFdhciIiI2ik2Te2BWgeboAEANFRXXiGYiIiIWoJNUzthUYQCAGx1ZwOcCRERUfvEpqmdsKnCAACNdVWBTYSIiKidYtPUTtjVrqbJYakKbCJERETtFJumdsKhcTVNosUc4EyIiIjaJzZN7YRT61qrSbBWBzgTIiKi9olNUzshnFvgUmFj00REROQLbJraCUEfAQBQ29k0ERER+QKbpnZCZXDNNGnsNQHOhIiIqH1i09ROaM49tFfrqA1wJkRERO0Tm6Z2QhsWBQAwOOvQ6HAGOBsiIqL2h01TO6ELc800hQt1qLU2BjgbIiKi9odNUzuhMpxrmlCPagubJiIiIrl51TQ1NjZiwYIFOHbsmK/yoZbShgMAwoV6VDfYA5wMERFR++NV06RSqbBkyRI4HA5f5UMtdW6dpjDUo8bCpomIiEhuXp+eGz58OL744gsfpEKtcq5pUglOWOq4VhMREZHcVN6+YeTIkZg7dy727duH1NRUhISEuO3PysqSLTnyglqPRqigQiOstWcBJAU6IyIionbF66bpz3/+MwBg2bJlzfYJgsBTd4EiCLAoQxDmMMNeVxnobIiIiNodr5smp5NrALVVVmWoq2mq5+k5IiIiuXHJgXbErnKdKm20sGkiIiKSW4uapm3btmH06NHo3r07evTogaysLHz55Zdy50ZealSFAQDEBnOAMyEiImp/vG6a1q1bh+HDh8NgMGD69Ol4+OGHodfrMWzYMKxfv94XOZKHnJpQ1zdWPrSXiIhIbl5f07Rw4UI8//zzeOSRR6RtM2bMwLJly/DMM89g/PjxsiZInhO1rpkmgU0TERGR7LyeaTp8+DBGjx7dbHtWVhaOHDkiS1LUQudWBVfYagOcCBERUfvjddOUkJCATz/9tNn2Tz/9FAkJCbIkRS2j0LmaJnUjZ5qIiIjk5vXpuVmzZmH69OkoLi7GoEGDIAgCCgoKsGbNGrz44ou+yJE8pNQ3NU2caSIiIpJbixa3NJlMWLp0Kd577z0AQK9evfDuu+/ijjvukD1B8pza4HqUisZRF+BMiIiI2h+vmqbGxkYsXLgQ999/PwoKCnyVE7WQJiQCAKB31kEURQiCENiEiIiI2hGvrmlSqVRYsmQJH5XSRmlDIwAAobCgwc6V24mIiOTk9YXgw4cPxxdffCHLh2/fvh2jR49GfHw8BEHAhx9+6LZfFEXMnz8f8fHx0Ov1GDp0KPbv3+8WY7VaMW3aNMTExCAkJARZWVk4fvy4W0xlZSWys7NhNBphNBqRnZ2Nqqoqt5jS0lKMHj0aISEhiImJwfTp02Gz2WQ5Tn/Rnjs9FwoLaqz2AGdDRETUvnh9TdPIkSMxd+5c7Nu3D6mpqQgJCXHbn5WV5fFYdXV16NevH+677z787ne/a7b/+eefx7Jly7BmzRpcc801ePbZZzFixAiUlJQgLMy1JlFOTg42b96MDRs2IDo6GrNmzUJmZiaKioqgVCoBAOPHj8fx48eRm5sLAHjggQeQnZ2NzZs3AwAcDgdGjRqFTp06oaCgAGfOnMHEiRMhiiJWrlzpbYkCRnHuQvBQwYLahkbEhgU4ISIiovZE9JIgCJf8UigU3g4nASBu2rRJeu10OkWTySQ+99xz0raGhgbRaDSKr776qiiKolhVVSWq1Wpxw4YNUsyJEydEhUIh5ubmiqIoigcOHBABiDt37pRiduzYIQIQ//e//4miKIqffPKJqFAoxBMnTkgx77zzjqjVakWz2ezxMZjNZhGAV+/xhM1mEz/88EPRZrNdPvDMYVF8KlysfbKTWFxaKWsOHYHHdaZWY639g3X2D9bZf3xVa0//fns90+R0+udamSNHjqC8vBzp6enSNq1WiyFDhqCwsBBTpkxBUVER7Ha7W0x8fDxSUlJQWFiIjIwM7NixA0ajEQMGDJBiBg4cCKPRiMLCQiQnJ2PHjh1ISUlBfHy8FJORkQGr1YqioiLccsstF83RarXCarVKr6urXQ/KtdvtsNvlOz3WNNYVx1TqoQYQIlhRVVMHuz3k8vHkxuM6U6ux1v7BOvsH6+w/vqq1p+N5ffecTqdDcXExUlJSWpSYp8rLywEAcXFxbtvj4uJw9OhRKUaj0SAyMrJZTNP7y8vLERsb22z82NhYt5gLPycyMhIajUaKuZjFixdjwYIFzbbn5eXBYDBc6RC9lp+ff9n9grMRTSdHdxZuR9X38ufQEVypziQf1to/WGf/YJ39R+5a19fXexTnVdOkUqnQtWtXv949d+Ft86IHt9JfGHOx+JbEXGju3LmYOXOm9Lq6uhoJCQlIT09HeHj4ZXP0ht1uR35+PkaMGAG1Wn3ZWNt3GmhEG3p174qRg2+ULYeOwJs6U+uw1v7BOvsH6+w/vqp105miK/H69Nxf/vIXzJ07F+vWrUNUVJTXiXnKZDIBcM0Cde7cWdpeUVEhzQqZTCbYbDZUVla6zTZVVFRg0KBBUszJkyebjX/q1Cm3cXbt2uW2v7KyEna7vdkM1Pm0Wi20Wm2z7Wq12ie/OJ6MW60IgcZhg6Ohlr+8LeSrnx81x1r7B+vsH6yz/8hda0/H8nrJgZdeeglffvkl4uPjkZycjBtuuMHtSy7dunWDyWRym4Kz2WzYtm2b1BClpqZCrVa7xZSVlWHfvn1STFpaGsxmM3bv3i3F7Nq1C2az2S1m3759KCsrk2Ly8vKg1WqRmpoq2zH5g03puo6psd4c4EyIiIjaF69nmsaMGSPbh9fW1uKHH36QXh85cgTFxcWIiopCYmIicnJysGjRIvTo0QM9evTAokWLYDAYMH78eACA0WjEpEmTMGvWLERHRyMqKgqzZ89G3759MXz4cACuR7zcdtttmDx5Ml577TUAriUHMjMzkZycDABIT09H7969kZ2djSVLluDs2bOYPXs2Jk+eLOtpNn+wq0IAG+Bo8GyqkYiIiDzjddP01FNPyfbhX3/9tdudaU3XB02cOBFr1qzBnDlzYLFYMHXqVFRWVmLAgAHIy8uT1mgCgOXLl0OlUmHs2LGwWCwYNmwY1qxZI63RBABvv/02pk+fLt1ll5WVhVWrVkn7lUoltmzZgqlTp2Lw4MHQ6/UYP348XnjhBdmO1V8a1a7aiA2caSIiIpKTx03T7t27kZqaKjUjF14kbbVa8e9//xtjx471+MOHDh0KURQvuV8QBMyfPx/z58+/ZIxOp8PKlSsvuwhlVFQU1q1bd9lcEhMT8fHHH18x57bOqQl1fdNQE9hEiIiI2hmPr2lKS0vDmTNnpNdGoxGHDx+WXldVVWHcuHHyZkdeEzWumSbBVhvgTIiIiNoXj5umC2eELjZDdLlZI/IPQee6Bktp50wTERGRnLy+e+5yrrR+Evle0/PnVHbONBEREclJ1qaJAk+pMwIANI1smoiIiOTk1d1zBw4ckB4rIooi/ve//6G21vXH+fTp0/JnR15Th7hmmjTOugBnQkRE1L541TQNGzbM7bqlzMxMAK7Tcp483oR8TxMSAQDQO+vgdIpQKPgzISIikoPHTdORI0d8mQfJRBfiepxMKCyotzsQqvV6KS4iIiK6CI//onbt2tWXeZBMNOdOz4XBgpoGO5smIiIimfBC8HZGOHcheJhgQW1DY4CzISIiaj/YNLU3WtfilqGwoMbKpomIiEgubJraG63r9JxBsKKmviHAyRAREbUfbJraG+0vDzNuqOVDe4mIiOTCpqm9UaphFbQAAFttZYCTISIiaj88urXq+uuv93gNpj179rQqIWo9q8IArcMKWz1nmoiIiOTiUdM0ZswY6fuGhga8/PLL6N27N9LS0gAAO3fuxP79+zF16lSfJEnesSlDAEclGi3VgU6FiIio3fCoaXrqqaek7//0pz9h+vTpeOaZZ5rFHDt2TN7sqEXs6jDABjjYNBEREcnG62ua/vWvf2HChAnNtt9zzz344IMPZEmKWsehDnV908DTc0RERHLxumnS6/UoKChotr2goAA6nU6WpKh1nBpX0yRaawKcCRERUfvh9TM2cnJy8Oc//xlFRUUYOHAgANc1Tf/4xz/w5JNPyp4geU/UuJYdUNjYNBEREcnF66bp8ccfR1JSEl588UWsX78eANCrVy+sWbMGY8eOlT1BaoFzj1JR2tk0ERERyaVFT3MdO3YsG6Q2TKlzrQqustcGOBMiIqL2o0WLW1ZVVeHvf/87nnjiCZw9exaAa32mEydOyJoctYzK4GqaNI66AGdCRETUfng90/Tdd99h+PDhMBqN+Omnn/CnP/0JUVFR2LRpE44ePYp//vOfvsiTvKAOiQAAaNk0ERERycbrmaaZM2fi3nvvxffff+92t9zIkSOxfft2WZOjltEYXNc0GZz1cDjFAGdDRETUPnjdNH311VeYMmVKs+1XXXUVysvLZUmKWkcXGgEACBUsqG1oDGwyRERE7YTXTZNOp0N1dfOVpktKStCpUydZkqLWUZ+baQpDPWqs9gBnQ0RE1D543TTdcccdePrpp2G3u/4YC4KA0tJSPP744/jd734ne4LUAlrXheBhggW1Vs40ERERycHrpumFF17AqVOnEBsbC4vFgiFDhqB79+4ICwvDwoULfZEjeUvrWtwyDPWo4ek5IiIiWXh991x4eDgKCgrw2WefYc+ePXA6nbjhhhswfPhwX+RHLXFunSadYEddXT2AqMDmQ0RE1A541TQ1NjZCp9OhuLgYt956K2699VZf5UWtce4xKgBgqa0C0CVgqRAREbUXXp2eU6lU6Nq1KxwOh6/yITkoVWgQXMtB2OrNAU6GiIioffD6mqa//OUvmDt3rrQSOLVNVmUoAMBeVxXYRIiIiNoJr5uml156CV9++SXi4+ORnJyMG264we1LTo2NjfjLX/6Cbt26Qa/XIykpCU8//TScTqcUI4oi5s+fj/j4eOj1egwdOhT79+93G8dqtWLatGmIiYlBSEgIsrKycPz4cbeYyspKZGdnw2g0wmg0Ijs7G1VVVbIejz/ZlCEAAAdnmoiIiGTh9YXgY8aM8UEaF/e3v/0Nr776Kt566y306dMHX3/9Ne677z4YjUbMmDEDAPD8889j2bJlWLNmDa655ho8++yzGDFiBEpKShAW5rq2JycnB5s3b8aGDRsQHR2NWbNmITMzE0VFRVAqlQCA8ePH4/jx48jNzQUAPPDAA8jOzsbmzZv9drxysqtDASvgbGi+phYRERF5z+um6amnnvJFHhe1Y8cO3HHHHRg1ahQA4Oqrr8Y777yDr7/+GoBrlmnFihWYN28e7rzzTgDAW2+9hbi4OKxfvx5TpkyB2WzGG2+8gbVr10p3+K1btw4JCQnYunUrMjIycPDgQeTm5mLnzp0YMGAAAGD16tVIS0tDSUkJkpOT/XbMcnGoXQ2js4EzTURERHLwumnyp5tuugmvvvoqDh06hGuuuQbffvstCgoKsGLFCgDAkSNHUF5ejvT0dOk9Wq0WQ4YMQWFhIaZMmYKioiLY7Xa3mPj4eKSkpKCwsBAZGRnYsWMHjEaj1DABwMCBA2E0GlFYWHjJpslqtcJqtUqvm1ZKt9vt0uKfcmgay5sxHerQc0nWyJpLe9aSOlPLsNb+wTr7B+vsP76qtafjed00ORwOLF++HO+99x5KS0ths9nc9st5gfhjjz0Gs9mMnj17QqlUwuFwYOHChRg3bhwASM+6i4uLc3tfXFwcjh49KsVoNBpERkY2i2l6f3l5OWJjY5t9fmxs7GWfp7d48WIsWLCg2fa8vDwYDAYvjtQz+fn5Hsd2qbPjagDWqnJ88sknsufSnnlTZ2od1to/WGf/YJ39R+5a19fXexTnddO0YMEC/P3vf8fMmTPx17/+FfPmzcNPP/2EDz/8EE8++aTXiV7Ou+++i3Xr1mH9+vXo06cPiouLkZOTg/j4eEycOFGKEwTB7X2iKDbbdqELYy4Wf6Vx5s6di5kzZ0qvq6urkZCQgPT0dISHh1/x+Dxlt9uRn5+PESNGQK1We/SeE7WfAt9vQ7jaidtvv122XNqzltSZWoa19g/W2T9YZ//xVa0v9kzdi/G6aXr77bexevVqjBo1CgsWLMC4cePwq1/9Ctdeey127tyJ6dOne53spTz66KN4/PHH8cc//hEA0LdvXxw9ehSLFy/GxIkTYTKZALhmijp37iy9r6KiQpp9MplMsNlsqKysdJttqqiowKBBg6SYkydPNvv8U6dONZvFOp9Wq4VWq222Xa1W++QXx5tx1SGuY1U31vGX2Eu++vlRc6y1f7DO/sE6+4/ctfZ0LK+XHCgvL0ffvn0BAKGhoTCbXRcaZ2ZmYsuWLd4Od1n19fVQKNxTVCqV0pID3bp1g8lkcpums9ls2LZtm9QQpaamQq1Wu8WUlZVh3759UkxaWhrMZjN2794txezatQtms1mKCTZKvREAoHXUBjgTIiKi9sHrmaYuXbqgrKwMiYmJ6N69O/Ly8nDDDTfgq6++uuisS2uMHj0aCxcuRGJiIvr06YNvvvkGy5Ytw/333w/AdUotJycHixYtQo8ePdCjRw8sWrQIBoMB48ePBwAYjUZMmjQJs2bNQnR0NKKiojB79mz07dtXupuuV69euO222zB58mS89tprAFxLDmRmZgblnXMAoDG4miadoy7AmRAREbUPXjdNv/3tb/Hpp59iwIABmDFjBsaNG4c33ngDpaWleOSRR2RNbuXKlfjrX/+KqVOnoqKiAvHx8ZgyZYrbtVNz5syBxWLB1KlTUVlZiQEDBiAvL09aowkAli9fDpVKhbFjx8JisWDYsGFYs2aNtEYT4DrtOH36dOkuu6ysLKxatUrW4/Enbajr9JwB9bA1OqFReT2pSEREROfxuml67rnnpO9///vfo0uXLigsLET37t2RlZUla3JhYWFYsWKFtMTAxQiCgPnz52P+/PmXjNHpdFi5ciVWrlx5yZioqCisW7euFdm2LbpQ10xTGOpRa21ElEoT4IyIiIiCW6vXaRo4cCAGDhwoRy4kI6U+AgAQJlhQ29CIqBA2TURERK3hddP0z3/+87L7J0yY0OJkSEY615IHYajHsQYuuEZERNRaXjdNTc98a2K321FfXw+NRgODwcCmqa3Quq7pCoUFtWyaiIiIWs3rq4MrKyvdvmpra1FSUoKbbroJ77zzji9ypJbQumaalIKI+lo+tJeIiKi1ZLmlqkePHnjuueeazUJRAKn1cJz78VrrKgOcDBERUfCT7T50pVKJn3/+Wa7hqLUEARaF66G9tjpzgJMhIiIKfl5f0/TRRx+5vRZFEWVlZVi1ahUGDx4sW2LUelZlCEKd1bDXs2kiIiJqLa+bpjFjxri9FgQBnTp1wq233oqlS5fKlRfJwK4KBeyA08KmiYiIqLW8bpqanvtGbV+jOhSwAI4GNk1EREStxWdrtGNOjWvZAaGBd88RERG1ltczTTNnzvQ4dtmyZd4OTzKSmiZbbYAzISIiCn5eN03ffPMN9uzZg8bGRiQnJwMADh06BKVSiRtuuEGKEwRBviypZc6tCq6w1QQ4ESIiouDnddM0evRohIWF4a233kJkZCQA14KX9913H37zm99g1qxZsidJLaM41zSp7WyaiIiIWsvra5qWLl2KxYsXSw0TAERGRuLZZ5/l3XNtjEJvBACoG3l6joiIqLW8bpqqq6tx8uTJZtsrKipQU8MZjbZEY4gAAOgcdYFNhIiIqB3wumn67W9/i/vuuw/vv/8+jh8/juPHj+P999/HpEmTcOedd/oiR2ohdYhrpknnrIMoigHOhoiIKLh5fU3Tq6++itmzZ+Oee+6B3W53DaJSYdKkSViyZInsCVLLaUMjAAAhqIe10QmdWhnYhIiIiIKY102TwWDAyy+/jCVLluDHH3+EKIro3r07QkJCfJEftYIuJAIAEAYLahoa2TQRERG1QosXtwwJCcG1116LiIgIHD16lCuFt0FNF4KHCRbUNNgDnA0REVFw87hpeuutt7BixQq3bQ888ACSkpLQt29fpKSk4NixY3LnR62hdS05EIZ61FobA5wMERFRcPO4aXr11VdhNBql17m5uXjzzTfxz3/+E1999RUiIiKwYMECnyRJLaR1rQiuF2yorbcEOBkiIqLg5vE1TYcOHUL//v2l1//+97+RlZWFu+++GwCwaNEi3HffffJnSC13bqYJACw1VQA6BywVIiKiYOfxTJPFYkF4+C9/hAsLC3HzzTdLr5OSklBeXi5vdtQ6ShWsgg4AYKurCmwuREREQc7jpqlr164oKioCAJw+fRr79+/HTTfdJO0vLy93O31HbYNF4bqr0VZfFdhEiIiIgpzHp+cmTJiAhx56CPv378dnn32Gnj17IjU1VdpfWFiIlJQUnyRJLWdThQKOM2isMwc6FSIioqDmcdP02GOPob6+Hhs3boTJZMK//vUvt/3//e9/MW7cONkTpNaxq0IAK+BsYNNERETUGh43TQqFAs888wyeeeaZi+6/sImitsGhdt1B52zgcwGJiIhao8WLW1JwcGhcTZNgrQ5wJkRERMGNTVN7d26tJsHGmSYiIqLWYNPUzgk61zIRKjZNRERErcKmqZ1T6FzLQKgbawOcCRERUXBj09TOKQ2upknTWBfgTIiIiIKbx3fPNXE4HFizZg0+/fRTVFRUwOl0uu3/7LPPZEuOWk99rmnSOjnTRERE1BpezzTNmDEDM2bMgMPhQEpKCvr16+f2JbcTJ07gnnvuQXR0NAwGA6677jppZXIAEEUR8+fPR3x8PPR6PYYOHYr9+/e7jWG1WjFt2jTExMQgJCQEWVlZOH78uFtMZWUlsrOzYTQaYTQakZ2djaqqKtmPx9+0oREAAIOzDqIoBjYZIiKiIOb1TNOGDRvw3nvv4fbbb/dFPm4qKysxePBg3HLLLfi///s/xMbG4scff0RERIQU8/zzz2PZsmVYs2YNrrnmGjz77LMYMWIESkpKEBbmunMsJycHmzdvxoYNGxAdHY1Zs2YhMzMTRUVFUCqVAIDx48fj+PHjyM3NBQA88MADyM7OxubNm31+nL6kD40EAITCglprI8J06gBnREREFJy8bpo0Gg26d+/ui1ya+dvf/oaEhAS8+eab0rarr75a+l4URaxYsQLz5s3DnXfeCQB46623EBcXh/Xr12PKlCkwm8144403sHbtWgwfPhwAsG7dOiQkJGDr1q3IyMjAwYMHkZubi507d2LAgAEAgNWrVyMtLQ0lJSVITk6+aH5WqxVWq1V6XV3tWgvJbrfDbrfLVoemsVoypqBxPXsuTKhHZW0DdErZ0mp3WlNn8g5r7R+ss3+wzv7jq1p7Op4gennOZunSpTh8+DBWrVoFQRBalJynevfujYyMDBw/fhzbtm3DVVddhalTp2Ly5MkAgMOHD+NXv/oV9uzZg+uvv1563x133IGIiAi89dZb+OyzzzBs2DCcPXsWkZGRUky/fv0wZswYLFiwAP/4xz8wc+bMZqfjIiIisHz5ctx3330XzW/+/PlYsGBBs+3r16+HwWCQoQKtF9rwM4YdfBxVYgjWJ7+Cq0ICnREREVHbUl9fj/Hjx8NsNiM8PPyScV7PNBUUFODzzz/H//3f/6FPnz5Qq91P92zcuNH7bC/h8OHDeOWVVzBz5kw88cQT2L17N6ZPnw6tVosJEyagvLwcABAXF+f2vri4OBw9ehQAUF5eDo1G49YwNcU0vb+8vByxsbHNPj82NlaKuZi5c+di5syZ0uvq6mokJCQgPT39skX3lt1uR35+PkaMGNGs3ldUUw4cfByhsKBf/wH4dbdo2fJqb1pVZ/IKa+0frLN/sM7+46taN50puhKvm6aIiAj89re/9TqhlnA6nejfvz8WLVoEALj++uuxf/9+vPLKK5gwYYIUd+GMlyiKV5wFuzDmYvFXGker1UKr1TbbrlarffKL06JxQ11Nkkpwwmqpg1ptkj2v9sZXPz9qjrX2D9bZP1hn/5G71p6O5XXTdP71Rb7WuXNn9O7d221br1698MEHHwAATCZXA1BeXo7OnTtLMRUVFdLsk8lkgs1mQ2VlpdtsU0VFBQYNGiTFnDx5stnnnzp1qtksVtBR69EIFVRohKXmLIBfBTojIiKioNSmF7ccPHgwSkpK3LYdOnQIXbt2BQB069YNJpMJ+fn50n6bzYZt27ZJDVFqairUarVbTFlZGfbt2yfFpKWlwWw2Y/fu3VLMrl27YDabpZigJQioV7ruIrTVVgY4GSIiouDl9UwTALz//vt47733UFpaCpvN5rZvz549siQGAI888ggGDRqERYsWYezYsdi9ezdef/11vP766wBcp9RycnKwaNEi9OjRAz169MCiRYtgMBgwfvx4AIDRaMSkSZMwa9YsREdHIyoqCrNnz0bfvn2lu+l69eqF2267DZMnT8Zrr70GwLXkQGZm5iXvnAsmVlUo4KhEY93ZQKdCREQUtLyeaXrppZdw3333ITY2Ft988w1+/etfIzo6GocPH8bIkSNlTe7GG2/Epk2b8M477yAlJQXPPPMMVqxYgbvvvluKmTNnDnJycjB16lT0798fJ06cQF5enrRGEwAsX74cY8aMwdixYzF48GAYDAZs3rxZWqMJAN5++2307dsX6enpSE9Px7XXXou1a9fKejyBYle7Lkp31HOmiYiIqKW8nml6+eWX8frrr2PcuHF46623MGfOHCQlJeHJJ5/E2bPyz2RkZmYiMzPzkvsFQcD8+fMxf/78S8bodDqsXLkSK1euvGRMVFQU1q1b15pU26xGjetRKqLFHOBMiIiIgpfXM02lpaXSdT56vR41NTUAgOzsbLzzzjvyZkeycGpdTZNgZdNERETUUl43TSaTCWfOnAEAdO3aFTt37gQAHDlyhM82a6t0rqZJyaaJiIioxbxumm699VbpeWyTJk3CI488ghEjRuCuu+7y2/pN5B2FwbXUgsbGpomIiKilvL6m6fXXX4fT6QQAPPjgg4iKikJBQQFGjx6NBx98UPYEqfVUhggAgKaxNrCJEBERBTGvmyaFQgGF4pcJqrFjx2Ls2LGyJkXyUodGAQD0Ds+WiSciIqLmWrS45Zdffol77rkHaWlpOHHiBABg7dq1KCgokDU5kocuzPUolRCxFo0OZ4CzISIiCk5eN00ffPABMjIyoNfr8c0338BqtQIAampqpGfEUduiD3fNNIWjHrXWxgBnQ0REFJy8bpqeffZZvPrqq1i9erXbA+4GDRok62rgJB/VuQvBjUIdzBZ7gLMhIiIKTl43TSUlJbj55pubbQ8PD0dVVZUcOZHc9BEAACPqUG3hTBMREVFLeN00de7cGT/88EOz7QUFBUhKSpIlKZLZuXWa9IIN1bW8g46IiKglvG6apkyZghkzZmDXrl0QBAE///wz3n77bcyePRtTp071RY7UWlojnBAAAJYaPrSXiIioJbxecmDOnDkwm8245ZZb0NDQgJtvvhlarRazZ8/Gww8/7IscqbUUClgUIQhx1sJacybQ2RAREQUlr5smAFi4cCHmzZuHAwcOwOl0onfv3ggNDZU7N5JRgzIUIc5a2GorA50KERFRUGpR0wQABoMB/fv3lzMX8iGbKhywl8NRz6aJiIioJTxumu6//36P4v7xj3+0OBnyHbsmHLAAoqUq0KkQEREFJY+bpjVr1qBr1664/vrrIYqiL3MiH3BowgEAooUP7SUiImoJj5umBx98EBs2bMDhw4dx//3345577kFUVJQvcyMZiboIAIDSVhXQPIiIiIKVx0sOvPzyyygrK8Njjz2GzZs3IyEhAWPHjsV//vMfzjwFAeHcApcqKx/aS0RE1BJerdOk1Woxbtw45Ofn48CBA+jTpw+mTp2Krl27opaLJrZpynOPUtE0smkiIiJqCa8Xt2wiCAIEQYAoinA6nXLmRD6gCT3XNNlrApwJERFRcPKqabJarXjnnXcwYsQIJCcnY+/evVi1ahVKS0u5TlMbpwuLBgAYnDU8nUpERNQCHl8IPnXqVGzYsAGJiYm47777sGHDBkRHR/syN5KRwej6WYWjDtUNjTDq1QHOiIiIKLh43DS9+uqrSExMRLdu3bBt2zZs27btonEbN26ULTmSjybU1TQZhTpU1dvYNBEREXnJ46ZpwoQJEATBl7mQLxlcy0NEogY/1NvRlZOEREREXvFqcUsKYnpX0xQiWGGuqQEQEdB0iIiIgk2L756jIKMzwnHux11fdSrAyRAREQUfNk0dhSCgTmkEADRUs2kiIiLyFpumDqRB5Wqa7DWnA5wJERFR8GHT1IHYNK6myVl3JsCZEBERBR82TR1Io851MbhoORvgTIiIiIIPm6YORDx3B52KTRMREZHX2DR1IIpzazWpbFWBTYSIiCgIBVXTtHjxYgiCgJycHGmbKIqYP38+4uPjodfrMXToUOzfv9/tfVarFdOmTUNMTAxCQkKQlZWF48ePu8VUVlYiOzsbRqMRRqMR2dnZqKqq8sNR+Y8yLAYAoGPTRERE5LWgaZq++uorvP7667j22mvdtj///PNYtmwZVq1aha+++gomkwkjRoxATU2NFJOTk4NNmzZhw4YNKCgoQG1tLTIzM+FwOKSY8ePHo7i4GLm5ucjNzUVxcTGys7P9dnz+oD3XNBkc5gBnQkREFHw8XhE8kGpra3H33Xdj9erVePbZZ6XtoihixYoVmDdvHu68804AwFtvvYW4uDisX78eU6ZMgdlsxhtvvIG1a9di+PDhAIB169YhISEBW7duRUZGBg4ePIjc3Fzs3LkTAwYMAACsXr0aaWlpKCkpQXJy8kXzslqtsFqt0uvq6moAgN1uh91ul+34m8Zq7ZjqUNfpuXCxBnUWKzSqoOmZ/UKuOtOVsdb+wTr7B+vsP76qtafjBUXT9NBDD2HUqFEYPny4W9N05MgRlJeXIz09Xdqm1WoxZMgQFBYWYsqUKSgqKoLdbneLiY+PR0pKCgoLC5GRkYEdO3bAaDRKDRMADBw4EEajEYWFhZdsmhYvXowFCxY0256XlweDwSDHobvJz89v1fsjan7EELieP7fx41yEa+TJq71pbZ3Jc6y1f7DO/sE6+4/cta6vr/cors03TRs2bMCePXvw1VdfNdtXXl4OAIiLi3PbHhcXh6NHj0oxGo0GkZGRzWKa3l9eXo7Y2Nhm48fGxkoxFzN37lzMnDlTel1dXY2EhASkp6cjPDzcwyO8Mrvdjvz8fIwYMQJqtbrlA53uAfzwLCKFWqSm3YwecaGy5dgeyFZnuiLW2j9YZ/9gnf3HV7VuOlN0JW26aTp27BhmzJiBvLw86HS6S8YJguD2WhTFZtsudGHMxeKvNI5Wq4VWq222Xa1W++QXp9Xjhruay3ChHtUWK9TqyCu8oWPy1c+PmmOt/YN19g/W2X/krrWnY7Xpi1qKiopQUVGB1NRUqFQqqFQqbNu2DS+99BJUKpU0w3ThbFBFRYW0z2QywWazobKy8rIxJ0+ebPb5p06dajaLFdT0EXDC1QRWV1YEOBkiIqLg0qabpmHDhmHv3r0oLi6Wvvr374+7774bxcXFSEpKgslkcju3abPZsG3bNgwaNAgAkJqaCrVa7RZTVlaGffv2STFpaWkwm83YvXu3FLNr1y6YzWYppl1QKGFRuE7JWarYNBEREXmjTZ+eCwsLQ0pKitu2kJAQREdHS9tzcnKwaNEi9OjRAz169MCiRYtgMBgwfvx4AIDRaMSkSZMwa9YsREdHIyoqCrNnz0bfvn2lu+l69eqF2267DZMnT8Zrr70GAHjggQeQmZl5yYvAg5VFHYEQaw2sZjZNRERE3mjTTZMn5syZA4vFgqlTp6KyshIDBgxAXl4ewsLCpJjly5dDpVJh7NixsFgsGDZsGNasWQOlUinFvP3225g+fbp0l11WVhZWrVrl9+PxtQZtDGA9BkcNmyYiIiJvBF3T9MUXX7i9FgQB8+fPx/z58y/5Hp1Oh5UrV2LlypWXjImKisK6detkyrLtcuhjgGpAqGPTRERE5I02fU0T+UBIJwCAquFMgBMhIiIKLmyaOhjluWUHdFY2TURERN5g09TBaI2upinEfjbAmRAREQUXNk0djCEqHgAQKVahwe64QjQRERE1YdPUwRgiTQCAGMGMs3W2AGdDREQUPNg0dTBCqOsZezEw40yNNcDZEBERBQ82TR3NuaZJJ9hRWcXrmoiIiDzFpqmj0YSgQXA9/Lj2bFmAkyEiIgoebJo6oFpVFADAVlV+hUgiIiJqwqapA2rQuJome/XJAGdCREQUPNg0dUCN+hgAgJPPnyMiIvIYm6YOqOkOOgWfP0dEROQxNk0dkMrYGQCgtZ4KcCZERETBg01TB6SP7gIACLOdgiiKAc6GiIgoOLBp6oDCYhMBAHE4i6p6e4CzISIiCg5smjogdWQCAMAknEF5dUOAsyEiIgoObJo6onDXQ3ujhFpUnK0KbC5ERERBgk1TR6SLgFXQAgBqKkoDnAwREVFwYNPUEQkCqtWdAAANZ48HOBkiIqLgwKapg7LoTQAAR9WJAGdCREQUHNg0dVCOUNdaTYranwOcCRERUXBg09RBKcKvAgBo6/nQXiIiIk+waeqgNFGupinUyof2EhEReYJNUwdljOsKAIhynkGttTHA2RAREbV9bJo6KEOMa1Xwq4QzOHa2PsDZEBERtX1smjqqCNdMUyfBjBMVZwKcDBERUdvHpqmjMkShXhEKAKgu+yHAyRAREbV9bJo6sGqd62JwawWbJiIioith09SBWcNdp+gUlT8FNhEiIqIgwKapA1NEdQMA6Gr5/DkiIqIrYdPUgenjugMAIm0nIIpigLMhIiJq29g0dWDGq5IBAF3EkzhVaw1wNkRERG1bm26aFi9ejBtvvBFhYWGIjY3FmDFjUFJS4hYjiiLmz5+P+Ph46PV6DB06FPv373eLsVqtmDZtGmJiYhASEoKsrCwcP37cLaayshLZ2dkwGo0wGo3Izs5GVVWVrw8xoNQxSQCALsIpHDtdE+BsiIiI2rY23TRt27YNDz30EHbu3In8/Hw0NjYiPT0ddXV1Uszzzz+PZcuWYdWqVfjqq69gMpkwYsQI1NT80gTk5ORg06ZN2LBhAwoKClBbW4vMzEw4HA4pZvz48SguLkZubi5yc3NRXFyM7Oxsvx6v34XHww41NIIDP5fyDjoiIqLLUQU6gcvJzc11e/3mm28iNjYWRUVFuPnmmyGKIlasWIF58+bhzjvvBAC89dZbiIuLw/r16zFlyhSYzWa88cYbWLt2LYYPHw4AWLduHRISErB161ZkZGTg4MGDyM3Nxc6dOzFgwAAAwOrVq5GWloaSkhIkJyf798D9RaGEWdsZMdZSmE+UAEgLdEZERERtVptumi5kNpsBAFFRUQCAI0eOoLy8HOnp6VKMVqvFkCFDUFhYiClTpqCoqAh2u90tJj4+HikpKSgsLERGRgZ27NgBo9EoNUwAMHDgQBiNRhQWFl6yabJarbBaf7kWqLq6GgBgt9tht9tlO+6mseQcs4nF+CugohTOk//zyfjBxJd1JnestX+wzv7BOvuPr2rt6XhB0zSJooiZM2fipptuQkpKCgCgvLwcABAXF+cWGxcXh6NHj0oxGo0GkZGRzWKa3l9eXo7Y2NhmnxkbGyvFXMzixYuxYMGCZtvz8vJgMBi8ODrP5Ofnyz5mZ3sYEgAYKkvwySefyD5+MPJFneniWGv/YJ39g3X2H7lrXV/v2TNYg6Zpevjhh/Hdd9+hoKCg2T5BENxei6LYbNuFLoy5WPyVxpk7dy5mzpwpva6urkZCQgLS09MRHh5+2c/3ht1uR35+PkaMGAG1Wi3buABg/aYO+OQjdMVxJN0yAuF6eccPJr6sM7ljrf2DdfYP1tl/fFXrpjNFVxIUTdO0adPw0UcfYfv27ejSpYu03WQyAXDNFHXu3FnaXlFRIc0+mUwm2Gw2VFZWus02VVRUYNCgQVLMyZMnm33uqVOnms1inU+r1UKr1TbbrlarffKL44tx1YnXAgCuEY7j+zMW9O8m/wxZsPHVz4+aY639g3X2D9bZf+Sutadjtem750RRxMMPP4yNGzfis88+Q7du3dz2d+vWDSaTyW2azmazYdu2bVJDlJqaCrVa7RZTVlaGffv2STFpaWkwm83YvXu3FLNr1y6YzWYppt2K6QEHFDAK9Sgt/THQ2RAREbVZbXqm6aGHHsL69evx73//G2FhYdL1RUajEXq9HoIgICcnB4sWLUKPHj3Qo0cPLFq0CAaDAePHj5diJ02ahFmzZiE6OhpRUVGYPXs2+vbtK91N16tXL9x2222YPHkyXnvtNQDAAw88gMzMzPZ751wTlRZn9Vejk+UwLEf3APh1oDMiIiJqk9p00/TKK68AAIYOHeq2/c0338S9994LAJgzZw4sFgumTp2KyspKDBgwAHl5eQgLC5Pily9fDpVKhbFjx8JisWDYsGFYs2YNlEqlFPP2229j+vTp0l12WVlZWLVqlW8PsI2o79QPKD0MTfk3gU6FiIiozWrTTZMnz0MTBAHz58/H/PnzLxmj0+mwcuVKrFy58pIxUVFRWLduXUvSDHohSQOA0k0w1R6A3eGEWtmmz9oSEREFBP86EqKvGQgA6Cv8iJIyz+4gICIi6mjYNBGEuBTYoEaEUIcfSvYGOh0iIqI2iU0TAUo1Tof1BABU/7AzwMkQERG1TWyaCAAgXJUKADCc/Mqja8mIiIg6GjZNBACIThkGALi+8TscPl0X4GyIiIjaHjZNBADQ/OpmOKHArxRl2LN3X6DTISIianPYNJGLPgKnwnoDAKr2/ifAyRAREbU9bJpIou7pWtiz25ltqG6wBzgbIiKitoVNE0miUn8HAPiN8B0+/+5wgLMhIiJqW9g00S/i+qBKlwCtYMfRwvcDnQ0REVGbwqaJfiEIUF43FgCQemYLDp+qDXBCREREbQebJnITNvBeOCFgsHI//m/bfwOdDhERUZvBponcRSTibPwQAEDcd6+goqYhwAkRERG1DWyaqJno254AANwhbMf63IIAZ0NERNQ2sGmiZoTEAajqfBPUggNJe5fhwM/VgU6JiIgo4Ng00UVFZD4DJwRkKf6L9ev/AVujM9ApERERBRSbJrq4q25Aww0PAACm1ryIpZt4mo6IiDo2Nk10SYaMJ1EX1g3xwlncuvdRvLn9UKBTIiIiChg2TXRp2lCETHgXNmUIBij+h075D2Ptf38IdFZEREQBwaaJLq9TMtR//CccggqZyl2Izv0zXthSDKdTDHRmREREfsWmia5I6DEcirFr4BBUuF25G8N33Y/Za/JhtvChvkRE1HGwaSKPCL1GQznxI9jURlyn+BFzjj6Ap5a9hMIfTgc6NSIiIr9g00Seu3owNA9+joaI7jAJlVhhfxola6Zi4YdFqG7grBMREbVvbJrIO9G/gm7ql7Cn/gkAcJ/qP5j4zVg88/xzeG93Ka91IiKidotNE3lPY4B69FLgng/QYOiMLsJpLHG+gM6bx2H2i2/i85IKiCKbJyIial/YNFHLdR8OXc4eOG6ajUaFBr9R7sMy8yPAut9jzov/wP/tLUOjgyuJExFR+8CmiVpHY4By+F+heng3GvrcBSeUuEX5LZZUzUT4e7/DU4sX4tXPDqKipiHQmRIREbWKKtAJUDsR1Q26P7wO3PoYLJ89D+3+f2Gwcj8GN+5Hxba/Y+Nnv8Hxq25Dv/43I71PZxgN6kBnTERE5BU2TSSv6F9B/4fXgBHz0PjVGjR+vQax1jN4ULUZOLkZpZs74V8f/RplMYMRmzIEg3smoKcpDColJz2JiKhtY9NEvhGRCNWIJ6G6dS5Q8gnqi96F+shWJOIU/oQtQOUWNGxX46svkvGK0Bv1sdciPGkAev7qavQyhSMuXAtBEAJ9FERERBI2TeRbSjXQ+w4Yet8B2OqA7/NQt+8TCIe/gMFagd8o9+E32Aecfg84DRzb2Qnfil1xXNkFDRHdoYnrCUN8T8THxSEx2oAukXpoVcpAHxUREXVAbJrIfzQhQJ/fIqTPbwFRBE4fgvPHz1Hz407gxB4Y648iQXEKCTgF4GugCq6vEsAsGvCzGI3/itGo1sSiTtcZtpDOUBjjoTXGIjTShMgYEzpFhCIqRAOjXg01T/kREZGM2DRd4OWXX8aSJUtQVlaGPn36YMWKFfjNb34T6LTaH0EAOiVD0SkZxoEPurY1mIGfi2EvP4Dq4wfgOPk/6KsPI8x+GkahHkahHr1wDHAAqDv3VeE+rFk04IwYjp8QjnohBDZlCOzqUDjVoXBqwyFow6DQG6EyhEOhC4dKHwF1iBEaQwSUulCcrBdRZm5ARCgQolFBqeApQiIicmHTdJ53330XOTk5ePnllzF48GC89tprGDlyJA4cOIDExMRAp9f+6YxA0hCok4Yg+vzt1lqg+gTEqmOoqfgJtaeOwll5HIqaE9BYKqC1VSLEUQ0FnFJzlYRy13udAKznvmqvnEI/UUDD/zRogAZl0MIGDeyCBnaFFnZBC7tCh0aFFo1KLZwKHRwqLZxKPUSVDqJKB4VSDUGlhkKlhUKlhlKlgUKthUqlhkqtgVKlgaDSQGjap9JAqdRAoVZDpdae26aGSq2DUq2GWq2FSqWCUqmAWqlgE0dEFEBsms6zbNkyTJo0CX/6k+sRIStWrMB//vMfvPLKK1i8eHGAs+vAtKFAp2QInZIR3gMIv1iM0wFYqoD603DUnoKlqgKWmkpY66pgqzfDUW+Gs6EaaKiGwl4Llb0GmsY66Jy10DnroRctUECEUhARAitCYAVQc9745/51+PxoL8oqqtAAJRqhhB1qNEIJh6CECAEiFK5/BQWcTa8F9+1N/wICnFAAgvs+CIpm36PpPee9lr6/YL/7l3CRba4vQfocQHPmLL6t/C8UShWg+GU/BAWE817/8r3yEmMLwPn7FAoAzf8VFE1x5+eodN1wIAiuz7piT+oK8DQOwkW3XjBW88HO3yKe23+xjxSkz7l4Xo2NjbCdOYzD334JpeqX/9xfLH9prPM+qVmc0Oyb8953XthF4y56AFcs5i9DXX4sQRBc//u92Hs92NrsYzy6EcUV0+hoRKP5OMp++AZqZfPlVMRLDOW22eMbXzyI8yJ3f4514c+nJZ/naGyE09Ho0ef5Apumc2w2G4qKivD444+7bU9PT0dhYeFF32O1WmG1WqXX1dXVAAC73Q67Xb4H2DaNJeeY7ZIm3PUVkQRtF0DrxVsdohMNdVX48tP/w28G3gg4bLBY6mG11MLaUA97Qz0ctnqItno4bQ0Q7RaIjQ0Q7PVAYwOEc19w2gFnIwSHHYLTDsHZCEFshNJpd/177kslNrpaINEBFRrPfTlc24Xmj6DRCo3Q4gr/oRAv8X1bVhfoBNq/ZAAoDXQW7V8iABwOdBYdw46kv8n+99DT8dg0nXP69Gk4HA7ExcW5bY+Li0N5eflF37N48WIsWLCg2fa8vDwYDAbZc8zPz5d9TLqAOhL5RT9csFEBIPTcF1y/Nb78zRGdUIiNEJwOiE4HRGcj4HRAFB2uf6XXTjhFEaLodF1YL4oAmr8+f7tw7rUoihBwfpz7ewTRCREihPP2CefmtSA6pXEFKd4V1zS+cN57ml6f/34Bv7xPgPPcv7+MIUif5/5aAfexzptbk8Y6N4fm9r0CV953JdL//71CQypcIkD0IOaSn+nB511uRF983qWIHsZ5+nmejiXnOP7OXa7jk/vz5Pjfg7dxnhAhyP73sL6+3qM4Nk0XuHCqXBTFS64XNHfuXMycOVN6XV1djYSEBKSnpyM8/KInkVrEbrcjPz8fI0aMgFrNlbR9hXX2H9baP1hn/2Cd/cdut0Png1o3nSm6EjZN58TExECpVDabVaqoqGg2+9REq9VCq21+EkitVvvkF8dX45I71tl/WGv/YJ39g3X2H7lr7elYXMjmHI1Gg9TU1GZTfvn5+Rg0aFCAsiIiIqK2gjNN55k5cyays7PRv39/pKWl4fXXX0dpaSkefPDBQKdGREREAcam6Tx33XUXzpw5g6effhplZWVISUnBJ598gq5duwY6NSIiIgowNk0XmDp1KqZOnRroNIiIiKiN4TVNRERERB5g00RERETkATZNRERERB5g00RERETkATZNRERERB5g00RERETkATZNRERERB5g00RERETkATZNRERERB7giuAyEkURAFBdXS3ruHa7HfX19aiuruYTtH2IdfYf1to/WGf/YJ39x1e1bvq73fR3/FLYNMmopqYGAJCQkBDgTIiIiMhbNTU1MBqNl9wviFdqq8hjTqcTP//8M8LCwiAIgmzjVldXIyEhAceOHUN4eLhs45I71tl/WGv/YJ39g3X2H1/VWhRF1NTUID4+HgrFpa9c4kyTjBQKBbp06eKz8cPDw/kL6Qess/+w1v7BOvsH6+w/vqj15WaYmvBCcCIiIiIPsGkiIiIi8gCbpiCg1Wrx1FNPQavVBjqVdo119h/W2j9YZ/9gnf0n0LXmheBEREREHuBMExEREZEH2DQREREReYBNExEREZEH2DQREREReYBNUxB4+eWX0a1bN+h0OqSmpuLLL78MdEpBY/HixbjxxhsRFhaG2NhYjBkzBiUlJW4xoihi/vz5iI+Ph16vx9ChQ7F//363GKvVimnTpiEmJgYhISHIysrC8ePH/XkoQWXx4sUQBAE5OTnSNtZZPidOnMA999yD6OhoGAwGXHfddSgqKpL2s9at19jYiL/85S/o1q0b9Ho9kpKS8PTTT8PpdEoxrLP3tm/fjtGjRyM+Ph6CIODDDz902y9XTSsrK5GdnQ2j0Qij0Yjs7GxUVVW1/gBEatM2bNggqtVqcfXq1eKBAwfEGTNmiCEhIeLRo0cDnVpQyMjIEN98801x3759YnFxsThq1CgxMTFRrK2tlWKee+45MSwsTPzggw/EvXv3infddZfYuXNnsbq6Wop58MEHxauuukrMz88X9+zZI95yyy1iv379xMbGxkAcVpu2e/du8eqrrxavvfZaccaMGdJ21lkeZ8+eFbt27Sree++94q5du8QjR46IW7duFX/44QcphrVuvWeffVaMjo4WP/74Y/HIkSPiv/71LzE0NFRcsWKFFMM6e++TTz4R582bJ37wwQciAHHTpk1u++Wq6W233SampKSIhYWFYmFhoZiSkiJmZma2On82TW3cr3/9a/HBBx9029azZ0/x8ccfD1BGwa2iokIEIG7btk0URVF0Op2iyWQSn3vuOSmmoaFBNBqN4quvviqKoihWVVWJarVa3LBhgxRz4sQJUaFQiLm5uf49gDaupqZG7NGjh5ifny8OGTJEappYZ/k89thj4k033XTJ/ay1PEaNGiXef//9btvuvPNO8Z577hFFkXWWw4VNk1w1PXDggAhA3LlzpxSzY8cOEYD4v//9r1U58/RcG2az2VBUVIT09HS37enp6SgsLAxQVsHNbDYDAKKiogAAR44cQXl5uVuNtVothgwZItW4qKgIdrvdLSY+Ph4pKSn8OVzgoYcewqhRozB8+HC37ayzfD766CP0798ff/jDHxAbG4vrr78eq1evlvaz1vK46aab8Omnn+LQoUMAgG+//RYFBQW4/fbbAbDOviBXTXfs2AGj0YgBAwZIMQMHDoTRaGx13fnA3jbs9OnTcDgciIuLc9seFxeH8vLyAGUVvERRxMyZM3HTTTchJSUFAKQ6XqzGR48elWI0Gg0iIyObxfDn8IsNGzZgz549+Oqrr5rtY53lc/jwYbzyyiuYOXMmnnjiCezevRvTp0+HVqvFhAkTWGuZPPbYYzCbzejZsyeUSiUcDgcWLlyIcePGAeD/pn1BrpqWl5cjNja22fixsbGtrjubpiAgCILba1EUm22jK3v44Yfx3XffoaCgoNm+ltSYP4dfHDt2DDNmzEBeXh50Ot0l41jn1nM6nejfvz8WLVoEALj++uuxf/9+vPLKK5gwYYIUx1q3zrvvvot169Zh/fr16NOnD4qLi5GTk4P4+HhMnDhRimOd5SdHTS8WL0fdeXquDYuJiYFSqWzWGVdUVDTrxOnypk2bho8++giff/45unTpIm03mUwAcNkam0wm2Gw2VFZWXjKmoysqKkJFRQVSU1OhUqmgUqmwbds2vPTSS1CpVFKdWOfW69y5M3r37u22rVevXigtLQXA/03L5dFHH8Xjjz+OP/7xj+jbty+ys7PxyCOPYPHixQBYZ1+Qq6YmkwknT55sNv6pU6daXXc2TW2YRqNBamoq8vPz3bbn5+dj0KBBAcoquIiiiIcffhgbN27EZ599hm7durnt79atG0wmk1uNbTYbtm3bJtU4NTUVarXaLaasrAz79u3jz+GcYcOGYe/evSguLpa++vfvj7vvvhvFxcVISkpinWUyePDgZstmHDp0CF27dgXA/03Lpb6+HgqF+59IpVIpLTnAOstPrpqmpaXBbDZj9+7dUsyuXbtgNptbX/dWXUZOPte05MAbb7whHjhwQMzJyRFDQkLEn376KdCpBYU///nPotFoFL/44guxrKxM+qqvr5dinnvuOdFoNIobN24U9+7dK44bN+6it7h26dJF3Lp1q7hnzx7x1ltv7dC3DXvi/LvnRJF1lsvu3btFlUolLly4UPz+++/Ft99+WzQYDOK6deukGNa69SZOnCheddVV0pIDGzduFGNiYsQ5c+ZIMayz92pqasRvvvlG/Oabb0QA4rJly8RvvvlGWkZHrpredttt4rXXXivu2LFD3LFjh9i3b18uOdBR/L//9//Erl27ihqNRrzhhhuk2+XpygBc9OvNN9+UYpxOp/jUU0+JJpNJ1Gq14s033yzu3bvXbRyLxSI+/PDDYlRUlKjX68XMzEyxtLTUz0cTXC5smlhn+WzevFlMSUkRtVqt2LNnT/H11193289at151dbU4Y8YMMTExUdTpdGJSUpI4b9480Wq1SjGss/c+//zzi/43eeLEiaIoylfTM2fOiHfffbcYFhYmhoWFiXfffbdYWVnZ6vwFURTF1s1VEREREbV/vKaJiIiIyANsmoiIiIg8wKaJiIiIyANsmoiIiIg8wKaJiIiIyANsmoiIiIg8wKaJiIiIyANsmoiIiIg8wKaJiEhGX3zxBQRBQFVVVaBTISKZsWkiIiIi8gCbJiIiIiIPsGkionZFFEU8//zzSEpKgl6vR79+/fD+++8D+OXU2ZYtW9CvXz/odDoMGDAAe/fudRvjgw8+QJ8+faDVanH11Vdj6dKlbvutVivmzJmDhIQEaLVa9OjRA2+88YZbTFFREfr37w+DwYBBgwahpKRE2vftt9/illtuQVhYGMLDw5Gamoqvv/7aRxUhIrmoAp0AEZGc/vKXv2Djxo145ZVX0KNHD2zfvh333HMPOnXqJMU8+uijePHFF2EymfDEE08gKysLhw4dglqtRlFREcaOHYv58+fjrrvuQmFhIaZOnYro6Gjce++9AIAJEyZgx44deOmll9CvXz8cOXIEp0+fdstj3rx5WLp0KTp16oQHH3wQ999/P/773/8CAO6++25cf/31eOWVV6BUKlFcXAy1Wu23GhFRC4lERO1EbW2tqNPpxMLCQrftkyZNEseNGyd+/vnnIgBxw4YN0r4zZ86Ier1efPfdd0VRFMXx48eLI0aMcHv/o48+Kvbu3VsURVEsKSkRAYj5+fkXzaHpM7Zu3Spt27JliwhAtFgsoiiKYlhYmLhmzZrWHzAR+RVPzxFRu3HgwAE0NDRgxIgRCA0Nlb7++c9/4scff5Ti0tLSpO+joqKQnJyMgwcPAgAOHjyIwYMHu407ePBgfP/993A4HCguLoZSqcSQIUMum8u1114rfd+5c2cAQEVFBQBg5syZ+NOf/oThw4fjueeec8uNiNouNk1E1G44nU4AwJYtW1BcXCx9HThwQLqu6VIEQQDguiaq6fsmoihK3+v1eo9yOf90W9N4TfnNnz8f+/fvx6hRo/DZZ5+hd+/e2LRpk0fjElHgsGkionajd+/e0Gq1KC0tRffu3d2+EhISpLidO3dK31dWVuLQoUPo2bOnNEZBQYHbuIWFhbjmmmugVCrRt29fOJ1ObNu2rVW5XnPNNXjkkUeQl5eHO++8E2+++WarxiMi3+OF4ETUboSFhWH27Nl45JFH4HQ6cdNNN6G6uhqFhYUIDQ1F165dAQBPP/00oqOjERcXh3nz5iEmJgZjxowBAMyaNQs33ngjnnnmGdx1113YsWMHVq1ahZdffhkAcPXVV2PixIm4//77pQvBjx49ioqKCowdO/aKOVosFjz66KP4/e9/j27duuH48eP46quv8Lvf/c5ndSEimQT6oioiIjk5nU7xxRdfFJOTk0W1Wi126tRJzMjIELdt2yZdpL1582axT58+okajEW+88UaxuLjYbYz3339f7N27t6hWq8XExERxyZIlbvstFov4yCOPiJ07dxY1Go3YvXt38R//+Icoir9cCF5ZWSnFf/PNNyIA8ciRI6LVahX/+Mc/igkJCaJGoxHj4+PFhx9+WLpInIjaLkEUzztZT0TUjn3xxRe45ZZbUFlZiYiIiECnQ0RBhtc0EREREXmATRMRERGRB3h6joiIiMgDnGkiIiIi8gCbJiIiIiIPsGkiIiIi8gCbJiIiIiIPsGkiIiIi8gCbJiIiIiIPsGkiIiIi8gCbJiIiIiIP/H8rPp9OcQSyKgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_loss = model.history.history['loss']\n",
    "val_loss = model.history.history[\"val_loss\"]\n",
    "plt.plot(train_loss)\n",
    "plt.plot(val_loss)\n",
    "plt.xlabel(\"epochs\")\n",
    "plt.ylabel(\"Mean Squared Error\")\n",
    "plt.legend([\"Train\", \"Test\"])\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "736100f6",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "train_loss = model.history.history[\"root_mean_squared_error\"]\n",
    "val_loss = model.history.history[\"val_root_mean_squared_error\"]\n",
    "plt.plot(train_loss)\n",
    "plt.plot(val_loss)\n",
    "plt.xlabel(\"epochs\")\n",
    "plt.ylabel(\"Root Mean Squared Error\")\n",
    "plt.legend([\"Train\", \"Test\"])\n",
    "plt.grid()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "d9e062ca",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33/33 [==============================] - 0s 841us/step - loss: 6.9912 - root_mean_squared_error: 2.6441\n",
      "15/15 [==============================] - 0s 997us/step - loss: 7.5032 - root_mean_squared_error: 2.7392\n",
      "Train RMSE =  2.644089698791504\n",
      "Test RMSE =  2.73919677734375\n",
      "---------------------------\n",
      "Train MSE =  6.991209983825684\n",
      "Test MSE =  7.503198623657227\n",
      "---------------------------\n",
      "33/33 [==============================] - 0s 714us/step\n",
      "15/15 [==============================] - 0s 714us/step\n",
      "Train R2 =  0.8517349567779868\n",
      "Test R2 =  0.845275417862849\n",
      "-----------------------------\n",
      "Train MAE =  2.0001840028363937\n",
      "Test MAE =  2.0746783145473167\n"
     ]
    }
   ],
   "source": [
    "# RMSE\n",
    "score = model.evaluate(X_train, y_train)\n",
    "train_rmse, train_mse = score[1], score[0]\n",
    "\n",
    "score = model.evaluate(X_test, y_test)\n",
    "test_rmse, test_mse = score[1], score[0]\n",
    "\n",
    "print(\"Train RMSE = \", train_rmse)\n",
    "print(\"Test RMSE = \", test_rmse)\n",
    "print(\"---------------------------\")\n",
    "\n",
    "#MSE\n",
    "print(\"Train MSE = \", train_mse)\n",
    "print(\"Test MSE = \", test_mse)\n",
    "print(\"---------------------------\")\n",
    "\n",
    "#R2 Score\n",
    "y_train_pred = model.predict(X_train)\n",
    "y_test_pred = model.predict(X_test)\n",
    "train_r2_score = r2_score(y_train, y_train_pred)\n",
    "test_r2_score = r2_score(y_test, y_test_pred)\n",
    "\n",
    "print(\"Train R2 = \", train_r2_score)\n",
    "print(\"Test R2 = \", test_r2_score)\n",
    "print(\"-----------------------------\")\n",
    "\n",
    "# MAE\n",
    "train_mae = mean_absolute_error(y_train, y_train_pred)\n",
    "test_mae = mean_absolute_error(y_test, y_test_pred)\n",
    "print(\"Train MAE = \", train_mae)\n",
    "print(\"Test MAE = \", test_mae)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cb9c8950",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.11.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}