16. Tensorflow使用TensorBoard可视化查看指标.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tensorflow使用TensorBoard可视化查看指标"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "使用TensorBoard可以打开一个网页：\n",
    "1. 查看指标随着batch的训练不断变化\n",
    "2. 查看网络结构图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from tensorflow import keras\n",
    "\n",
    "# 使用sklearn现成的波斯顿房价数据集\n",
    "from sklearn.datasets import fetch_california_housing\n",
    "\n",
    "# 做训练集测试集验证集拆分\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "# 对数值数据归一化\n",
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. 下载sklearn的波士顿房价数据集"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用这个函数下载波斯顿房价数据集\n",
    "housing = fetch_california_housing()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 分割训练集、测试集、验证集\n",
    "X_train_full, X_test, y_train_full, y_test = train_test_split(housing.data, housing.target)\n",
    "X_train, X_valid, y_train, y_valid = train_test_split(X_train_full, y_train_full)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 使用sklearn对数值数据做归一化\n",
    "scaler = StandardScaler()\n",
    "# 在训练集上做fit和transform\n",
    "X_train = scaler.fit_transform(X_train)\n",
    "\n",
    "# 在测试集和验证集上做transform\n",
    "X_valid = scaler.transform(X_valid)\n",
    "X_test = scaler.transform(X_test)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. 把数据分割为Wide部分输入和Deep部分输入"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# A是0~4共5列，B是2~7共6列\n",
    "X_train_A, X_train_B = X_train[:, :5], X_train[:, 2:]\n",
    "\n",
    "# valid和test做同样的处理\n",
    "X_valid_A, X_valid_B = X_valid[:, :5], X_valid[:, 2:]\n",
    "X_test_A, X_test_B = X_test[:, :5], X_test[:, 2:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. 搭建WideDeep模型"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 输入：wide和deep\n",
    "input_A = keras.layers.Input(shape=[5], name=\"wide_input\")\n",
    "input_B = keras.layers.Input(shape=[6], name=\"deep_input\")\n",
    "\n",
    "# 构造deep部分\n",
    "hidden1 = keras.layers.Dense(30, activation=\"relu\")(input_B)\n",
    "hidden2 = keras.layers.Dense(30, activation=\"relu\")(hidden1)\n",
    "hidden3 = keras.layers.Dense(30, activation=\"relu\")(hidden2)\n",
    "\n",
    "# 合并wide和deep\n",
    "concat = keras.layers.concatenate([input_A, hidden3])\n",
    "\n",
    "# 输出层\n",
    "output = keras.layers.Dense(1, name=\"output\")(concat)\n",
    "\n",
    "# 构造model，注意多输入，单输出\n",
    "model = keras.models.Model(inputs=[input_A, input_B], outputs=[output])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. 模型编译、训练"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 模型编译，指定多个指标\n",
    "model.compile(\n",
    "    loss=\"mse\", \n",
    "    optimizer=keras.optimizers.SGD(lr=1e-3),\n",
    "    metrics=[tf.keras.metrics.MeanSquaredError(),\n",
    "             tf.keras.metrics.RootMeanSquaredError(),\n",
    "             tf.keras.metrics.MeanAbsoluteError()]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# TensorBoard\n",
    "!rm -rf ./logs/*\n",
    "tensorboard_cb = tf.keras.callbacks.TensorBoard(\"./logs\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 启动方法：tensorboard --logdir=./logs --port=9998 --bind_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 1.6456 - mean_squared_error: 1.6456 - root_mean_squared_error: 1.2828 - mean_absolute_error: 0.8964 - val_loss: 0.8725 - val_mean_squared_error: 0.8725 - val_root_mean_squared_error: 0.9341 - val_mean_absolute_error: 0.6844\n",
      "Epoch 2/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.8109 - mean_squared_error: 0.8109 - root_mean_squared_error: 0.9005 - mean_absolute_error: 0.6621 - val_loss: 0.7463 - val_mean_squared_error: 0.7463 - val_root_mean_squared_error: 0.8639 - val_mean_absolute_error: 0.6398\n",
      "Epoch 3/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.7250 - mean_squared_error: 0.7250 - root_mean_squared_error: 0.8515 - mean_absolute_error: 0.6291 - val_loss: 0.6903 - val_mean_squared_error: 0.6903 - val_root_mean_squared_error: 0.8308 - val_mean_absolute_error: 0.6085\n",
      "Epoch 4/1000\n",
      "363/363 [==============================] - 2s 4ms/step - loss: 0.6796 - mean_squared_error: 0.6796 - root_mean_squared_error: 0.8244 - mean_absolute_error: 0.6084 - val_loss: 0.6581 - val_mean_squared_error: 0.6581 - val_root_mean_squared_error: 0.8112 - val_mean_absolute_error: 0.5931\n",
      "Epoch 5/1000\n",
      "363/363 [==============================] - 2s 6ms/step - loss: 0.6501 - mean_squared_error: 0.6501 - root_mean_squared_error: 0.8063 - mean_absolute_error: 0.5945 - val_loss: 0.6346 - val_mean_squared_error: 0.6346 - val_root_mean_squared_error: 0.7966 - val_mean_absolute_error: 0.5843\n",
      "Epoch 6/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.6275 - mean_squared_error: 0.6275 - root_mean_squared_error: 0.7922 - mean_absolute_error: 0.5839 - val_loss: 0.6151 - val_mean_squared_error: 0.6151 - val_root_mean_squared_error: 0.7843 - val_mean_absolute_error: 0.5712\n",
      "Epoch 7/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.6087 - mean_squared_error: 0.6087 - root_mean_squared_error: 0.7802 - mean_absolute_error: 0.5742 - val_loss: 0.6000 - val_mean_squared_error: 0.6000 - val_root_mean_squared_error: 0.7746 - val_mean_absolute_error: 0.5646\n",
      "Epoch 8/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.5926 - mean_squared_error: 0.5926 - root_mean_squared_error: 0.7698 - mean_absolute_error: 0.5654 - val_loss: 0.5860 - val_mean_squared_error: 0.5860 - val_root_mean_squared_error: 0.7655 - val_mean_absolute_error: 0.5587\n",
      "Epoch 9/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.5805 - mean_squared_error: 0.5805 - root_mean_squared_error: 0.7619 - mean_absolute_error: 0.5602 - val_loss: 0.5752 - val_mean_squared_error: 0.5752 - val_root_mean_squared_error: 0.7584 - val_mean_absolute_error: 0.5518\n",
      "Epoch 10/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.5689 - mean_squared_error: 0.5689 - root_mean_squared_error: 0.7542 - mean_absolute_error: 0.5538 - val_loss: 0.5657 - val_mean_squared_error: 0.5657 - val_root_mean_squared_error: 0.7521 - val_mean_absolute_error: 0.5442\n",
      "Epoch 11/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.5592 - mean_squared_error: 0.5592 - root_mean_squared_error: 0.7478 - mean_absolute_error: 0.5483 - val_loss: 0.5564 - val_mean_squared_error: 0.5564 - val_root_mean_squared_error: 0.7459 - val_mean_absolute_error: 0.5390\n",
      "Epoch 12/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.5508 - mean_squared_error: 0.5508 - root_mean_squared_error: 0.7422 - mean_absolute_error: 0.5445 - val_loss: 0.5490 - val_mean_squared_error: 0.5490 - val_root_mean_squared_error: 0.7410 - val_mean_absolute_error: 0.5353\n",
      "Epoch 13/1000\n",
      "363/363 [==============================] - 2s 5ms/step - loss: 0.5436 - mean_squared_error: 0.5436 - root_mean_squared_error: 0.7373 - mean_absolute_error: 0.5403 - val_loss: 0.5444 - val_mean_squared_error: 0.5444 - val_root_mean_squared_error: 0.7379 - val_mean_absolute_error: 0.5338\n",
      "Epoch 14/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.5368 - mean_squared_error: 0.5368 - root_mean_squared_error: 0.7327 - mean_absolute_error: 0.5371 - val_loss: 0.5379 - val_mean_squared_error: 0.5379 - val_root_mean_squared_error: 0.7334 - val_mean_absolute_error: 0.5301\n",
      "Epoch 15/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.5312 - mean_squared_error: 0.5312 - root_mean_squared_error: 0.7288 - mean_absolute_error: 0.5341 - val_loss: 0.5315 - val_mean_squared_error: 0.5315 - val_root_mean_squared_error: 0.7290 - val_mean_absolute_error: 0.5233\n",
      "Epoch 16/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.5259 - mean_squared_error: 0.5259 - root_mean_squared_error: 0.7252 - mean_absolute_error: 0.5313 - val_loss: 0.5268 - val_mean_squared_error: 0.5268 - val_root_mean_squared_error: 0.7258 - val_mean_absolute_error: 0.5231\n",
      "Epoch 17/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.5207 - mean_squared_error: 0.5207 - root_mean_squared_error: 0.7216 - mean_absolute_error: 0.5286 - val_loss: 0.5247 - val_mean_squared_error: 0.5247 - val_root_mean_squared_error: 0.7244 - val_mean_absolute_error: 0.5269\n",
      "Epoch 18/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.5156 - mean_squared_error: 0.5156 - root_mean_squared_error: 0.7180 - mean_absolute_error: 0.5260 - val_loss: 0.5176 - val_mean_squared_error: 0.5176 - val_root_mean_squared_error: 0.7194 - val_mean_absolute_error: 0.5190\n",
      "Epoch 19/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.5115 - mean_squared_error: 0.5115 - root_mean_squared_error: 0.7152 - mean_absolute_error: 0.5237 - val_loss: 0.5140 - val_mean_squared_error: 0.5140 - val_root_mean_squared_error: 0.7169 - val_mean_absolute_error: 0.5189\n",
      "Epoch 20/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.5069 - mean_squared_error: 0.5069 - root_mean_squared_error: 0.7120 - mean_absolute_error: 0.5206 - val_loss: 0.5085 - val_mean_squared_error: 0.5085 - val_root_mean_squared_error: 0.7131 - val_mean_absolute_error: 0.5170\n",
      "Epoch 21/1000\n",
      "363/363 [==============================] - 1s 1ms/step - loss: 0.5020 - mean_squared_error: 0.5020 - root_mean_squared_error: 0.7085 - mean_absolute_error: 0.5189 - val_loss: 0.5050 - val_mean_squared_error: 0.5050 - val_root_mean_squared_error: 0.7106 - val_mean_absolute_error: 0.5099\n",
      "Epoch 22/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4975 - mean_squared_error: 0.4975 - root_mean_squared_error: 0.7053 - mean_absolute_error: 0.5163 - val_loss: 0.5003 - val_mean_squared_error: 0.5003 - val_root_mean_squared_error: 0.7073 - val_mean_absolute_error: 0.5085\n",
      "Epoch 23/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4933 - mean_squared_error: 0.4933 - root_mean_squared_error: 0.7024 - mean_absolute_error: 0.5133 - val_loss: 0.4973 - val_mean_squared_error: 0.4973 - val_root_mean_squared_error: 0.7052 - val_mean_absolute_error: 0.5038\n",
      "Epoch 24/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4892 - mean_squared_error: 0.4892 - root_mean_squared_error: 0.6994 - mean_absolute_error: 0.5105 - val_loss: 0.4926 - val_mean_squared_error: 0.4926 - val_root_mean_squared_error: 0.7018 - val_mean_absolute_error: 0.5087\n",
      "Epoch 25/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4847 - mean_squared_error: 0.4847 - root_mean_squared_error: 0.6962 - mean_absolute_error: 0.5087 - val_loss: 0.4883 - val_mean_squared_error: 0.4883 - val_root_mean_squared_error: 0.6988 - val_mean_absolute_error: 0.5009\n",
      "Epoch 26/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4804 - mean_squared_error: 0.4804 - root_mean_squared_error: 0.6931 - mean_absolute_error: 0.5051 - val_loss: 0.4841 - val_mean_squared_error: 0.4841 - val_root_mean_squared_error: 0.6958 - val_mean_absolute_error: 0.4997\n",
      "Epoch 27/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4769 - mean_squared_error: 0.4769 - root_mean_squared_error: 0.6906 - mean_absolute_error: 0.5036 - val_loss: 0.4816 - val_mean_squared_error: 0.4816 - val_root_mean_squared_error: 0.6940 - val_mean_absolute_error: 0.4962\n",
      "Epoch 28/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 1s 2ms/step - loss: 0.4725 - mean_squared_error: 0.4725 - root_mean_squared_error: 0.6874 - mean_absolute_error: 0.4997 - val_loss: 0.4777 - val_mean_squared_error: 0.4777 - val_root_mean_squared_error: 0.6912 - val_mean_absolute_error: 0.4929\n",
      "Epoch 29/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4691 - mean_squared_error: 0.4691 - root_mean_squared_error: 0.6849 - mean_absolute_error: 0.4983 - val_loss: 0.4745 - val_mean_squared_error: 0.4745 - val_root_mean_squared_error: 0.6888 - val_mean_absolute_error: 0.4961\n",
      "Epoch 30/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4652 - mean_squared_error: 0.4652 - root_mean_squared_error: 0.6821 - mean_absolute_error: 0.4957 - val_loss: 0.4711 - val_mean_squared_error: 0.4711 - val_root_mean_squared_error: 0.6863 - val_mean_absolute_error: 0.4944\n",
      "Epoch 31/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4624 - mean_squared_error: 0.4624 - root_mean_squared_error: 0.6800 - mean_absolute_error: 0.4946 - val_loss: 0.4684 - val_mean_squared_error: 0.4684 - val_root_mean_squared_error: 0.6844 - val_mean_absolute_error: 0.4872\n",
      "Epoch 32/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4591 - mean_squared_error: 0.4591 - root_mean_squared_error: 0.6776 - mean_absolute_error: 0.4915 - val_loss: 0.4654 - val_mean_squared_error: 0.4654 - val_root_mean_squared_error: 0.6822 - val_mean_absolute_error: 0.4863\n",
      "Epoch 33/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.4561 - mean_squared_error: 0.4561 - root_mean_squared_error: 0.6754 - mean_absolute_error: 0.4894 - val_loss: 0.4637 - val_mean_squared_error: 0.4637 - val_root_mean_squared_error: 0.6810 - val_mean_absolute_error: 0.4947\n",
      "Epoch 34/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.4536 - mean_squared_error: 0.4536 - root_mean_squared_error: 0.6735 - mean_absolute_error: 0.4888 - val_loss: 0.4602 - val_mean_squared_error: 0.4602 - val_root_mean_squared_error: 0.6784 - val_mean_absolute_error: 0.4883\n",
      "Epoch 35/1000\n",
      "363/363 [==============================] - 1s 1ms/step - loss: 0.4508 - mean_squared_error: 0.4508 - root_mean_squared_error: 0.6714 - mean_absolute_error: 0.4873 - val_loss: 0.4593 - val_mean_squared_error: 0.4593 - val_root_mean_squared_error: 0.6777 - val_mean_absolute_error: 0.4831\n",
      "Epoch 36/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4487 - mean_squared_error: 0.4487 - root_mean_squared_error: 0.6699 - mean_absolute_error: 0.4848 - val_loss: 0.4556 - val_mean_squared_error: 0.4556 - val_root_mean_squared_error: 0.6750 - val_mean_absolute_error: 0.4848\n",
      "Epoch 37/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4459 - mean_squared_error: 0.4459 - root_mean_squared_error: 0.6677 - mean_absolute_error: 0.4836 - val_loss: 0.4536 - val_mean_squared_error: 0.4536 - val_root_mean_squared_error: 0.6735 - val_mean_absolute_error: 0.4817\n",
      "Epoch 38/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4437 - mean_squared_error: 0.4437 - root_mean_squared_error: 0.6661 - mean_absolute_error: 0.4819 - val_loss: 0.4513 - val_mean_squared_error: 0.4513 - val_root_mean_squared_error: 0.6718 - val_mean_absolute_error: 0.4851\n",
      "Epoch 39/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4413 - mean_squared_error: 0.4413 - root_mean_squared_error: 0.6643 - mean_absolute_error: 0.4807 - val_loss: 0.4485 - val_mean_squared_error: 0.4485 - val_root_mean_squared_error: 0.6697 - val_mean_absolute_error: 0.4795\n",
      "Epoch 40/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4392 - mean_squared_error: 0.4392 - root_mean_squared_error: 0.6627 - mean_absolute_error: 0.4797 - val_loss: 0.4466 - val_mean_squared_error: 0.4466 - val_root_mean_squared_error: 0.6683 - val_mean_absolute_error: 0.4778\n",
      "Epoch 41/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4370 - mean_squared_error: 0.4370 - root_mean_squared_error: 0.6611 - mean_absolute_error: 0.4776 - val_loss: 0.4444 - val_mean_squared_error: 0.4444 - val_root_mean_squared_error: 0.6667 - val_mean_absolute_error: 0.4802\n",
      "Epoch 42/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4353 - mean_squared_error: 0.4353 - root_mean_squared_error: 0.6597 - mean_absolute_error: 0.4768 - val_loss: 0.4425 - val_mean_squared_error: 0.4425 - val_root_mean_squared_error: 0.6652 - val_mean_absolute_error: 0.4778\n",
      "Epoch 43/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4329 - mean_squared_error: 0.4329 - root_mean_squared_error: 0.6579 - mean_absolute_error: 0.4756 - val_loss: 0.4434 - val_mean_squared_error: 0.4434 - val_root_mean_squared_error: 0.6659 - val_mean_absolute_error: 0.4834\n",
      "Epoch 44/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4310 - mean_squared_error: 0.4310 - root_mean_squared_error: 0.6565 - mean_absolute_error: 0.4751 - val_loss: 0.4393 - val_mean_squared_error: 0.4393 - val_root_mean_squared_error: 0.6628 - val_mean_absolute_error: 0.4714\n",
      "Epoch 45/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4299 - mean_squared_error: 0.4299 - root_mean_squared_error: 0.6556 - mean_absolute_error: 0.4734 - val_loss: 0.4364 - val_mean_squared_error: 0.4364 - val_root_mean_squared_error: 0.6606 - val_mean_absolute_error: 0.4716\n",
      "Epoch 46/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4272 - mean_squared_error: 0.4272 - root_mean_squared_error: 0.6536 - mean_absolute_error: 0.4722 - val_loss: 0.4370 - val_mean_squared_error: 0.4370 - val_root_mean_squared_error: 0.6610 - val_mean_absolute_error: 0.4769\n",
      "Epoch 47/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4256 - mean_squared_error: 0.4256 - root_mean_squared_error: 0.6524 - mean_absolute_error: 0.4707 - val_loss: 0.4327 - val_mean_squared_error: 0.4327 - val_root_mean_squared_error: 0.6578 - val_mean_absolute_error: 0.4732\n",
      "Epoch 48/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4235 - mean_squared_error: 0.4235 - root_mean_squared_error: 0.6507 - mean_absolute_error: 0.4694 - val_loss: 0.4311 - val_mean_squared_error: 0.4311 - val_root_mean_squared_error: 0.6566 - val_mean_absolute_error: 0.4728\n",
      "Epoch 49/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4217 - mean_squared_error: 0.4217 - root_mean_squared_error: 0.6494 - mean_absolute_error: 0.4685 - val_loss: 0.4305 - val_mean_squared_error: 0.4305 - val_root_mean_squared_error: 0.6561 - val_mean_absolute_error: 0.4735\n",
      "Epoch 50/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4202 - mean_squared_error: 0.4202 - root_mean_squared_error: 0.6482 - mean_absolute_error: 0.4678 - val_loss: 0.4270 - val_mean_squared_error: 0.4270 - val_root_mean_squared_error: 0.6535 - val_mean_absolute_error: 0.4656\n",
      "Epoch 51/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4179 - mean_squared_error: 0.4179 - root_mean_squared_error: 0.6464 - mean_absolute_error: 0.4660 - val_loss: 0.4270 - val_mean_squared_error: 0.4270 - val_root_mean_squared_error: 0.6534 - val_mean_absolute_error: 0.4734\n",
      "Epoch 52/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4165 - mean_squared_error: 0.4165 - root_mean_squared_error: 0.6454 - mean_absolute_error: 0.4654 - val_loss: 0.4236 - val_mean_squared_error: 0.4236 - val_root_mean_squared_error: 0.6508 - val_mean_absolute_error: 0.4665\n",
      "Epoch 53/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4147 - mean_squared_error: 0.4147 - root_mean_squared_error: 0.6440 - mean_absolute_error: 0.4645 - val_loss: 0.4234 - val_mean_squared_error: 0.4234 - val_root_mean_squared_error: 0.6507 - val_mean_absolute_error: 0.4590\n",
      "Epoch 54/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4133 - mean_squared_error: 0.4133 - root_mean_squared_error: 0.6429 - mean_absolute_error: 0.4628 - val_loss: 0.4201 - val_mean_squared_error: 0.4201 - val_root_mean_squared_error: 0.6482 - val_mean_absolute_error: 0.4625\n",
      "Epoch 55/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4116 - mean_squared_error: 0.4116 - root_mean_squared_error: 0.6415 - mean_absolute_error: 0.4619 - val_loss: 0.4193 - val_mean_squared_error: 0.4193 - val_root_mean_squared_error: 0.6476 - val_mean_absolute_error: 0.4622\n",
      "Epoch 56/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4102 - mean_squared_error: 0.4102 - root_mean_squared_error: 0.6405 - mean_absolute_error: 0.4608 - val_loss: 0.4211 - val_mean_squared_error: 0.4211 - val_root_mean_squared_error: 0.6489 - val_mean_absolute_error: 0.4707\n",
      "Epoch 57/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4083 - mean_squared_error: 0.4083 - root_mean_squared_error: 0.6390 - mean_absolute_error: 0.4603 - val_loss: 0.4162 - val_mean_squared_error: 0.4162 - val_root_mean_squared_error: 0.6451 - val_mean_absolute_error: 0.4573\n",
      "Epoch 58/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.4069 - mean_squared_error: 0.4069 - root_mean_squared_error: 0.6379 - mean_absolute_error: 0.4589 - val_loss: 0.4141 - val_mean_squared_error: 0.4141 - val_root_mean_squared_error: 0.6435 - val_mean_absolute_error: 0.4615\n",
      "Epoch 59/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4053 - mean_squared_error: 0.4053 - root_mean_squared_error: 0.6366 - mean_absolute_error: 0.4586 - val_loss: 0.4125 - val_mean_squared_error: 0.4125 - val_root_mean_squared_error: 0.6422 - val_mean_absolute_error: 0.4565\n",
      "Epoch 60/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4039 - mean_squared_error: 0.4039 - root_mean_squared_error: 0.6355 - mean_absolute_error: 0.4564 - val_loss: 0.4126 - val_mean_squared_error: 0.4126 - val_root_mean_squared_error: 0.6424 - val_mean_absolute_error: 0.4619\n",
      "Epoch 61/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4025 - mean_squared_error: 0.4025 - root_mean_squared_error: 0.6344 - mean_absolute_error: 0.4563 - val_loss: 0.4093 - val_mean_squared_error: 0.4093 - val_root_mean_squared_error: 0.6397 - val_mean_absolute_error: 0.4556\n",
      "Epoch 62/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.4008 - mean_squared_error: 0.4008 - root_mean_squared_error: 0.6331 - mean_absolute_error: 0.4550 - val_loss: 0.4102 - val_mean_squared_error: 0.4102 - val_root_mean_squared_error: 0.6405 - val_mean_absolute_error: 0.4628\n",
      "Epoch 63/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3996 - mean_squared_error: 0.3996 - root_mean_squared_error: 0.6321 - mean_absolute_error: 0.4546 - val_loss: 0.4087 - val_mean_squared_error: 0.4087 - val_root_mean_squared_error: 0.6393 - val_mean_absolute_error: 0.4592\n",
      "Epoch 64/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3979 - mean_squared_error: 0.3979 - root_mean_squared_error: 0.6308 - mean_absolute_error: 0.4534 - val_loss: 0.4053 - val_mean_squared_error: 0.4053 - val_root_mean_squared_error: 0.6366 - val_mean_absolute_error: 0.4561\n",
      "Epoch 65/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3966 - mean_squared_error: 0.3966 - root_mean_squared_error: 0.6298 - mean_absolute_error: 0.4524 - val_loss: 0.4057 - val_mean_squared_error: 0.4057 - val_root_mean_squared_error: 0.6370 - val_mean_absolute_error: 0.4589\n",
      "Epoch 66/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3956 - mean_squared_error: 0.3956 - root_mean_squared_error: 0.6290 - mean_absolute_error: 0.4516 - val_loss: 0.4043 - val_mean_squared_error: 0.4043 - val_root_mean_squared_error: 0.6359 - val_mean_absolute_error: 0.4589\n",
      "Epoch 67/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3945 - mean_squared_error: 0.3945 - root_mean_squared_error: 0.6281 - mean_absolute_error: 0.4511 - val_loss: 0.4013 - val_mean_squared_error: 0.4013 - val_root_mean_squared_error: 0.6335 - val_mean_absolute_error: 0.4527\n",
      "Epoch 68/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3927 - mean_squared_error: 0.3927 - root_mean_squared_error: 0.6266 - mean_absolute_error: 0.4501 - val_loss: 0.4020 - val_mean_squared_error: 0.4020 - val_root_mean_squared_error: 0.6341 - val_mean_absolute_error: 0.4567\n",
      "Epoch 69/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3913 - mean_squared_error: 0.3913 - root_mean_squared_error: 0.6256 - mean_absolute_error: 0.4490 - val_loss: 0.3987 - val_mean_squared_error: 0.3987 - val_root_mean_squared_error: 0.6314 - val_mean_absolute_error: 0.4517\n",
      "Epoch 70/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3903 - mean_squared_error: 0.3903 - root_mean_squared_error: 0.6247 - mean_absolute_error: 0.4481 - val_loss: 0.3983 - val_mean_squared_error: 0.3983 - val_root_mean_squared_error: 0.6311 - val_mean_absolute_error: 0.4491\n",
      "Epoch 71/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3891 - mean_squared_error: 0.3891 - root_mean_squared_error: 0.6238 - mean_absolute_error: 0.4479 - val_loss: 0.3964 - val_mean_squared_error: 0.3964 - val_root_mean_squared_error: 0.6296 - val_mean_absolute_error: 0.4464\n",
      "Epoch 72/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3874 - mean_squared_error: 0.3874 - root_mean_squared_error: 0.6224 - mean_absolute_error: 0.4467 - val_loss: 0.3952 - val_mean_squared_error: 0.3952 - val_root_mean_squared_error: 0.6287 - val_mean_absolute_error: 0.4446\n",
      "Epoch 73/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3869 - mean_squared_error: 0.3869 - root_mean_squared_error: 0.6220 - mean_absolute_error: 0.4457 - val_loss: 0.3938 - val_mean_squared_error: 0.3938 - val_root_mean_squared_error: 0.6275 - val_mean_absolute_error: 0.4442\n",
      "Epoch 74/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3852 - mean_squared_error: 0.3852 - root_mean_squared_error: 0.6207 - mean_absolute_error: 0.4449 - val_loss: 0.3940 - val_mean_squared_error: 0.3940 - val_root_mean_squared_error: 0.6277 - val_mean_absolute_error: 0.4436\n",
      "Epoch 75/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3842 - mean_squared_error: 0.3842 - root_mean_squared_error: 0.6199 - mean_absolute_error: 0.4434 - val_loss: 0.3932 - val_mean_squared_error: 0.3932 - val_root_mean_squared_error: 0.6271 - val_mean_absolute_error: 0.4480\n",
      "Epoch 76/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3836 - mean_squared_error: 0.3836 - root_mean_squared_error: 0.6194 - mean_absolute_error: 0.4438 - val_loss: 0.3902 - val_mean_squared_error: 0.3902 - val_root_mean_squared_error: 0.6247 - val_mean_absolute_error: 0.4438\n",
      "Epoch 77/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3819 - mean_squared_error: 0.3819 - root_mean_squared_error: 0.6180 - mean_absolute_error: 0.4425 - val_loss: 0.3889 - val_mean_squared_error: 0.3889 - val_root_mean_squared_error: 0.6236 - val_mean_absolute_error: 0.4410\n",
      "Epoch 78/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3808 - mean_squared_error: 0.3808 - root_mean_squared_error: 0.6171 - mean_absolute_error: 0.4412 - val_loss: 0.3881 - val_mean_squared_error: 0.3881 - val_root_mean_squared_error: 0.6230 - val_mean_absolute_error: 0.4440\n",
      "Epoch 79/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3799 - mean_squared_error: 0.3799 - root_mean_squared_error: 0.6164 - mean_absolute_error: 0.4408 - val_loss: 0.3883 - val_mean_squared_error: 0.3883 - val_root_mean_squared_error: 0.6231 - val_mean_absolute_error: 0.4446\n",
      "Epoch 80/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3784 - mean_squared_error: 0.3784 - root_mean_squared_error: 0.6151 - mean_absolute_error: 0.4401 - val_loss: 0.3851 - val_mean_squared_error: 0.3851 - val_root_mean_squared_error: 0.6206 - val_mean_absolute_error: 0.4369\n",
      "Epoch 81/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3770 - mean_squared_error: 0.3770 - root_mean_squared_error: 0.6140 - mean_absolute_error: 0.4392 - val_loss: 0.3843 - val_mean_squared_error: 0.3843 - val_root_mean_squared_error: 0.6199 - val_mean_absolute_error: 0.4373\n",
      "Epoch 82/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3758 - mean_squared_error: 0.3758 - root_mean_squared_error: 0.6130 - mean_absolute_error: 0.4376 - val_loss: 0.3832 - val_mean_squared_error: 0.3832 - val_root_mean_squared_error: 0.6190 - val_mean_absolute_error: 0.4405\n",
      "Epoch 83/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3747 - mean_squared_error: 0.3747 - root_mean_squared_error: 0.6121 - mean_absolute_error: 0.4375 - val_loss: 0.3831 - val_mean_squared_error: 0.3831 - val_root_mean_squared_error: 0.6190 - val_mean_absolute_error: 0.4381\n",
      "Epoch 84/1000\n",
      "363/363 [==============================] - 1s 4ms/step - loss: 0.3739 - mean_squared_error: 0.3739 - root_mean_squared_error: 0.6115 - mean_absolute_error: 0.4368 - val_loss: 0.3808 - val_mean_squared_error: 0.3808 - val_root_mean_squared_error: 0.6171 - val_mean_absolute_error: 0.4324\n",
      "Epoch 85/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3727 - mean_squared_error: 0.3727 - root_mean_squared_error: 0.6105 - mean_absolute_error: 0.4358 - val_loss: 0.3807 - val_mean_squared_error: 0.3807 - val_root_mean_squared_error: 0.6170 - val_mean_absolute_error: 0.4397\n",
      "Epoch 86/1000\n",
      "363/363 [==============================] - 1s 1ms/step - loss: 0.3712 - mean_squared_error: 0.3712 - root_mean_squared_error: 0.6093 - mean_absolute_error: 0.4347 - val_loss: 0.3796 - val_mean_squared_error: 0.3796 - val_root_mean_squared_error: 0.6161 - val_mean_absolute_error: 0.4395\n",
      "Epoch 87/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3707 - mean_squared_error: 0.3707 - root_mean_squared_error: 0.6088 - mean_absolute_error: 0.4344 - val_loss: 0.3774 - val_mean_squared_error: 0.3774 - val_root_mean_squared_error: 0.6143 - val_mean_absolute_error: 0.4307\n",
      "Epoch 88/1000\n",
      "363/363 [==============================] - 1s 1ms/step - loss: 0.3692 - mean_squared_error: 0.3692 - root_mean_squared_error: 0.6076 - mean_absolute_error: 0.4333 - val_loss: 0.3769 - val_mean_squared_error: 0.3769 - val_root_mean_squared_error: 0.6140 - val_mean_absolute_error: 0.4342\n",
      "Epoch 89/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3684 - mean_squared_error: 0.3684 - root_mean_squared_error: 0.6070 - mean_absolute_error: 0.4331 - val_loss: 0.3748 - val_mean_squared_error: 0.3748 - val_root_mean_squared_error: 0.6122 - val_mean_absolute_error: 0.4303\n",
      "Epoch 90/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3672 - mean_squared_error: 0.3672 - root_mean_squared_error: 0.6060 - mean_absolute_error: 0.4317 - val_loss: 0.3747 - val_mean_squared_error: 0.3747 - val_root_mean_squared_error: 0.6122 - val_mean_absolute_error: 0.4312\n",
      "Epoch 91/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3661 - mean_squared_error: 0.3661 - root_mean_squared_error: 0.6050 - mean_absolute_error: 0.4307 - val_loss: 0.3734 - val_mean_squared_error: 0.3734 - val_root_mean_squared_error: 0.6111 - val_mean_absolute_error: 0.4310\n",
      "Epoch 92/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3664 - mean_squared_error: 0.3664 - root_mean_squared_error: 0.6053 - mean_absolute_error: 0.4307 - val_loss: 0.3727 - val_mean_squared_error: 0.3727 - val_root_mean_squared_error: 0.6105 - val_mean_absolute_error: 0.4335\n",
      "Epoch 93/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3647 - mean_squared_error: 0.3647 - root_mean_squared_error: 0.6039 - mean_absolute_error: 0.4301 - val_loss: 0.3711 - val_mean_squared_error: 0.3711 - val_root_mean_squared_error: 0.6092 - val_mean_absolute_error: 0.4307\n",
      "Epoch 94/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3637 - mean_squared_error: 0.3637 - root_mean_squared_error: 0.6031 - mean_absolute_error: 0.4297 - val_loss: 0.3724 - val_mean_squared_error: 0.3724 - val_root_mean_squared_error: 0.6103 - val_mean_absolute_error: 0.4322\n",
      "Epoch 95/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3630 - mean_squared_error: 0.3630 - root_mean_squared_error: 0.6025 - mean_absolute_error: 0.4286 - val_loss: 0.3690 - val_mean_squared_error: 0.3690 - val_root_mean_squared_error: 0.6075 - val_mean_absolute_error: 0.4254\n",
      "Epoch 96/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3624 - mean_squared_error: 0.3624 - root_mean_squared_error: 0.6020 - mean_absolute_error: 0.4282 - val_loss: 0.3688 - val_mean_squared_error: 0.3688 - val_root_mean_squared_error: 0.6073 - val_mean_absolute_error: 0.4306\n",
      "Epoch 97/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3612 - mean_squared_error: 0.3612 - root_mean_squared_error: 0.6010 - mean_absolute_error: 0.4269 - val_loss: 0.3701 - val_mean_squared_error: 0.3701 - val_root_mean_squared_error: 0.6084 - val_mean_absolute_error: 0.4355\n",
      "Epoch 98/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3608 - mean_squared_error: 0.3608 - root_mean_squared_error: 0.6007 - mean_absolute_error: 0.4276 - val_loss: 0.3662 - val_mean_squared_error: 0.3662 - val_root_mean_squared_error: 0.6052 - val_mean_absolute_error: 0.4251\n",
      "Epoch 99/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3599 - mean_squared_error: 0.3599 - root_mean_squared_error: 0.5999 - mean_absolute_error: 0.4266 - val_loss: 0.3663 - val_mean_squared_error: 0.3663 - val_root_mean_squared_error: 0.6053 - val_mean_absolute_error: 0.4268\n",
      "Epoch 100/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3588 - mean_squared_error: 0.3588 - root_mean_squared_error: 0.5990 - mean_absolute_error: 0.4253 - val_loss: 0.3646 - val_mean_squared_error: 0.3646 - val_root_mean_squared_error: 0.6038 - val_mean_absolute_error: 0.4240\n",
      "Epoch 101/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3581 - mean_squared_error: 0.3581 - root_mean_squared_error: 0.5984 - mean_absolute_error: 0.4249 - val_loss: 0.3637 - val_mean_squared_error: 0.3637 - val_root_mean_squared_error: 0.6031 - val_mean_absolute_error: 0.4239\n",
      "Epoch 102/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3575 - mean_squared_error: 0.3575 - root_mean_squared_error: 0.5980 - mean_absolute_error: 0.4248 - val_loss: 0.3648 - val_mean_squared_error: 0.3648 - val_root_mean_squared_error: 0.6040 - val_mean_absolute_error: 0.4306\n",
      "Epoch 103/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3565 - mean_squared_error: 0.3565 - root_mean_squared_error: 0.5971 - mean_absolute_error: 0.4241 - val_loss: 0.3628 - val_mean_squared_error: 0.3628 - val_root_mean_squared_error: 0.6023 - val_mean_absolute_error: 0.4215\n",
      "Epoch 104/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3561 - mean_squared_error: 0.3561 - root_mean_squared_error: 0.5968 - mean_absolute_error: 0.4236 - val_loss: 0.3631 - val_mean_squared_error: 0.3631 - val_root_mean_squared_error: 0.6026 - val_mean_absolute_error: 0.4264\n",
      "Epoch 105/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3550 - mean_squared_error: 0.3550 - root_mean_squared_error: 0.5958 - mean_absolute_error: 0.4233 - val_loss: 0.3610 - val_mean_squared_error: 0.3610 - val_root_mean_squared_error: 0.6008 - val_mean_absolute_error: 0.4238\n",
      "Epoch 106/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3543 - mean_squared_error: 0.3543 - root_mean_squared_error: 0.5952 - mean_absolute_error: 0.4224 - val_loss: 0.3606 - val_mean_squared_error: 0.3606 - val_root_mean_squared_error: 0.6005 - val_mean_absolute_error: 0.4197\n",
      "Epoch 107/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3536 - mean_squared_error: 0.3536 - root_mean_squared_error: 0.5947 - mean_absolute_error: 0.4219 - val_loss: 0.3621 - val_mean_squared_error: 0.3621 - val_root_mean_squared_error: 0.6017 - val_mean_absolute_error: 0.4229\n",
      "Epoch 108/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3530 - mean_squared_error: 0.3530 - root_mean_squared_error: 0.5941 - mean_absolute_error: 0.4216 - val_loss: 0.3598 - val_mean_squared_error: 0.3598 - val_root_mean_squared_error: 0.5998 - val_mean_absolute_error: 0.4222\n",
      "Epoch 109/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3523 - mean_squared_error: 0.3523 - root_mean_squared_error: 0.5936 - mean_absolute_error: 0.4213 - val_loss: 0.3581 - val_mean_squared_error: 0.3581 - val_root_mean_squared_error: 0.5984 - val_mean_absolute_error: 0.4173\n",
      "Epoch 110/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3520 - mean_squared_error: 0.3520 - root_mean_squared_error: 0.5933 - mean_absolute_error: 0.4209 - val_loss: 0.3578 - val_mean_squared_error: 0.3578 - val_root_mean_squared_error: 0.5981 - val_mean_absolute_error: 0.4164\n",
      "Epoch 111/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3517 - mean_squared_error: 0.3517 - root_mean_squared_error: 0.5931 - mean_absolute_error: 0.4207 - val_loss: 0.3566 - val_mean_squared_error: 0.3566 - val_root_mean_squared_error: 0.5971 - val_mean_absolute_error: 0.4199\n",
      "Epoch 112/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3506 - mean_squared_error: 0.3506 - root_mean_squared_error: 0.5921 - mean_absolute_error: 0.4194 - val_loss: 0.3567 - val_mean_squared_error: 0.3567 - val_root_mean_squared_error: 0.5973 - val_mean_absolute_error: 0.4228\n",
      "Epoch 113/1000\n",
      "363/363 [==============================] - 2s 6ms/step - loss: 0.3493 - mean_squared_error: 0.3493 - root_mean_squared_error: 0.5911 - mean_absolute_error: 0.4189 - val_loss: 0.3554 - val_mean_squared_error: 0.3554 - val_root_mean_squared_error: 0.5961 - val_mean_absolute_error: 0.4202\n",
      "Epoch 114/1000\n",
      "363/363 [==============================] - 2s 5ms/step - loss: 0.3493 - mean_squared_error: 0.3493 - root_mean_squared_error: 0.5910 - mean_absolute_error: 0.4193 - val_loss: 0.3573 - val_mean_squared_error: 0.3573 - val_root_mean_squared_error: 0.5978 - val_mean_absolute_error: 0.4220\n",
      "Epoch 115/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3489 - mean_squared_error: 0.3489 - root_mean_squared_error: 0.5906 - mean_absolute_error: 0.4180 - val_loss: 0.3545 - val_mean_squared_error: 0.3545 - val_root_mean_squared_error: 0.5954 - val_mean_absolute_error: 0.4189\n",
      "Epoch 116/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3482 - mean_squared_error: 0.3482 - root_mean_squared_error: 0.5900 - mean_absolute_error: 0.4185 - val_loss: 0.3546 - val_mean_squared_error: 0.3546 - val_root_mean_squared_error: 0.5955 - val_mean_absolute_error: 0.4176\n",
      "Epoch 117/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3479 - mean_squared_error: 0.3479 - root_mean_squared_error: 0.5898 - mean_absolute_error: 0.4176 - val_loss: 0.3555 - val_mean_squared_error: 0.3555 - val_root_mean_squared_error: 0.5962 - val_mean_absolute_error: 0.4244\n",
      "Epoch 118/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3472 - mean_squared_error: 0.3472 - root_mean_squared_error: 0.5893 - mean_absolute_error: 0.4175 - val_loss: 0.3532 - val_mean_squared_error: 0.3532 - val_root_mean_squared_error: 0.5943 - val_mean_absolute_error: 0.4136\n",
      "Epoch 119/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3465 - mean_squared_error: 0.3465 - root_mean_squared_error: 0.5886 - mean_absolute_error: 0.4165 - val_loss: 0.3519 - val_mean_squared_error: 0.3519 - val_root_mean_squared_error: 0.5932 - val_mean_absolute_error: 0.4154\n",
      "Epoch 120/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3458 - mean_squared_error: 0.3458 - root_mean_squared_error: 0.5881 - mean_absolute_error: 0.4167 - val_loss: 0.3518 - val_mean_squared_error: 0.3518 - val_root_mean_squared_error: 0.5931 - val_mean_absolute_error: 0.4130\n",
      "Epoch 121/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3457 - mean_squared_error: 0.3457 - root_mean_squared_error: 0.5880 - mean_absolute_error: 0.4168 - val_loss: 0.3505 - val_mean_squared_error: 0.3505 - val_root_mean_squared_error: 0.5921 - val_mean_absolute_error: 0.4124\n",
      "Epoch 122/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3449 - mean_squared_error: 0.3449 - root_mean_squared_error: 0.5873 - mean_absolute_error: 0.4154 - val_loss: 0.3510 - val_mean_squared_error: 0.3510 - val_root_mean_squared_error: 0.5925 - val_mean_absolute_error: 0.4177\n",
      "Epoch 123/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3444 - mean_squared_error: 0.3444 - root_mean_squared_error: 0.5868 - mean_absolute_error: 0.4151 - val_loss: 0.3492 - val_mean_squared_error: 0.3492 - val_root_mean_squared_error: 0.5910 - val_mean_absolute_error: 0.4133\n",
      "Epoch 124/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3440 - mean_squared_error: 0.3440 - root_mean_squared_error: 0.5865 - mean_absolute_error: 0.4153 - val_loss: 0.3504 - val_mean_squared_error: 0.3504 - val_root_mean_squared_error: 0.5920 - val_mean_absolute_error: 0.4143\n",
      "Epoch 125/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3438 - mean_squared_error: 0.3438 - root_mean_squared_error: 0.5863 - mean_absolute_error: 0.4144 - val_loss: 0.3483 - val_mean_squared_error: 0.3483 - val_root_mean_squared_error: 0.5902 - val_mean_absolute_error: 0.4116\n",
      "Epoch 126/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3426 - mean_squared_error: 0.3426 - root_mean_squared_error: 0.5853 - mean_absolute_error: 0.4137 - val_loss: 0.3491 - val_mean_squared_error: 0.3491 - val_root_mean_squared_error: 0.5909 - val_mean_absolute_error: 0.4151\n",
      "Epoch 127/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3416 - mean_squared_error: 0.3416 - root_mean_squared_error: 0.5844 - mean_absolute_error: 0.4130 - val_loss: 0.3481 - val_mean_squared_error: 0.3481 - val_root_mean_squared_error: 0.5900 - val_mean_absolute_error: 0.4146\n",
      "Epoch 128/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3415 - mean_squared_error: 0.3415 - root_mean_squared_error: 0.5844 - mean_absolute_error: 0.4134 - val_loss: 0.3493 - val_mean_squared_error: 0.3493 - val_root_mean_squared_error: 0.5910 - val_mean_absolute_error: 0.4152\n",
      "Epoch 129/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3417 - mean_squared_error: 0.3417 - root_mean_squared_error: 0.5845 - mean_absolute_error: 0.4127 - val_loss: 0.3472 - val_mean_squared_error: 0.3472 - val_root_mean_squared_error: 0.5892 - val_mean_absolute_error: 0.4137\n",
      "Epoch 130/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3405 - mean_squared_error: 0.3405 - root_mean_squared_error: 0.5836 - mean_absolute_error: 0.4127 - val_loss: 0.3477 - val_mean_squared_error: 0.3477 - val_root_mean_squared_error: 0.5897 - val_mean_absolute_error: 0.4139\n",
      "Epoch 131/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3406 - mean_squared_error: 0.3406 - root_mean_squared_error: 0.5836 - mean_absolute_error: 0.4123 - val_loss: 0.3477 - val_mean_squared_error: 0.3477 - val_root_mean_squared_error: 0.5897 - val_mean_absolute_error: 0.4113\n",
      "Epoch 132/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3397 - mean_squared_error: 0.3397 - root_mean_squared_error: 0.5828 - mean_absolute_error: 0.4116 - val_loss: 0.3453 - val_mean_squared_error: 0.3453 - val_root_mean_squared_error: 0.5876 - val_mean_absolute_error: 0.4104\n",
      "Epoch 133/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3389 - mean_squared_error: 0.3389 - root_mean_squared_error: 0.5821 - mean_absolute_error: 0.4112 - val_loss: 0.3456 - val_mean_squared_error: 0.3456 - val_root_mean_squared_error: 0.5878 - val_mean_absolute_error: 0.4085\n",
      "Epoch 134/1000\n",
      "363/363 [==============================] - 2s 4ms/step - loss: 0.3412 - mean_squared_error: 0.3412 - root_mean_squared_error: 0.5841 - mean_absolute_error: 0.4117 - val_loss: 0.3460 - val_mean_squared_error: 0.3460 - val_root_mean_squared_error: 0.5883 - val_mean_absolute_error: 0.4121\n",
      "Epoch 135/1000\n",
      "363/363 [==============================] - 2s 6ms/step - loss: 0.3384 - mean_squared_error: 0.3384 - root_mean_squared_error: 0.5817 - mean_absolute_error: 0.4106 - val_loss: 0.3468 - val_mean_squared_error: 0.3468 - val_root_mean_squared_error: 0.5889 - val_mean_absolute_error: 0.4163\n",
      "Epoch 136/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3378 - mean_squared_error: 0.3378 - root_mean_squared_error: 0.5812 - mean_absolute_error: 0.4106 - val_loss: 0.3462 - val_mean_squared_error: 0.3462 - val_root_mean_squared_error: 0.5884 - val_mean_absolute_error: 0.4118\n",
      "Epoch 137/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3382 - mean_squared_error: 0.3382 - root_mean_squared_error: 0.5816 - mean_absolute_error: 0.4103 - val_loss: 0.3471 - val_mean_squared_error: 0.3471 - val_root_mean_squared_error: 0.5891 - val_mean_absolute_error: 0.4183\n",
      "Epoch 138/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3372 - mean_squared_error: 0.3372 - root_mean_squared_error: 0.5807 - mean_absolute_error: 0.4099 - val_loss: 0.3449 - val_mean_squared_error: 0.3449 - val_root_mean_squared_error: 0.5873 - val_mean_absolute_error: 0.4155\n",
      "Epoch 139/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3370 - mean_squared_error: 0.3370 - root_mean_squared_error: 0.5805 - mean_absolute_error: 0.4095 - val_loss: 0.3497 - val_mean_squared_error: 0.3497 - val_root_mean_squared_error: 0.5913 - val_mean_absolute_error: 0.4233\n",
      "Epoch 140/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3360 - mean_squared_error: 0.3360 - root_mean_squared_error: 0.5796 - mean_absolute_error: 0.4088 - val_loss: 0.3460 - val_mean_squared_error: 0.3460 - val_root_mean_squared_error: 0.5882 - val_mean_absolute_error: 0.4151\n",
      "Epoch 141/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3364 - mean_squared_error: 0.3364 - root_mean_squared_error: 0.5800 - mean_absolute_error: 0.4094 - val_loss: 0.3452 - val_mean_squared_error: 0.3452 - val_root_mean_squared_error: 0.5875 - val_mean_absolute_error: 0.4166\n",
      "Epoch 142/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3359 - mean_squared_error: 0.3359 - root_mean_squared_error: 0.5796 - mean_absolute_error: 0.4093 - val_loss: 0.3420 - val_mean_squared_error: 0.3420 - val_root_mean_squared_error: 0.5848 - val_mean_absolute_error: 0.4044\n",
      "Epoch 143/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3350 - mean_squared_error: 0.3350 - root_mean_squared_error: 0.5788 - mean_absolute_error: 0.4079 - val_loss: 0.3429 - val_mean_squared_error: 0.3429 - val_root_mean_squared_error: 0.5855 - val_mean_absolute_error: 0.4115\n",
      "Epoch 144/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3350 - mean_squared_error: 0.3350 - root_mean_squared_error: 0.5788 - mean_absolute_error: 0.4081 - val_loss: 0.3412 - val_mean_squared_error: 0.3412 - val_root_mean_squared_error: 0.5841 - val_mean_absolute_error: 0.4103\n",
      "Epoch 145/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3359 - mean_squared_error: 0.3359 - root_mean_squared_error: 0.5795 - mean_absolute_error: 0.4085 - val_loss: 0.3422 - val_mean_squared_error: 0.3422 - val_root_mean_squared_error: 0.5850 - val_mean_absolute_error: 0.4026\n",
      "Epoch 146/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3353 - mean_squared_error: 0.3353 - root_mean_squared_error: 0.5790 - mean_absolute_error: 0.4072 - val_loss: 0.3425 - val_mean_squared_error: 0.3425 - val_root_mean_squared_error: 0.5852 - val_mean_absolute_error: 0.4084\n",
      "Epoch 147/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3348 - mean_squared_error: 0.3348 - root_mean_squared_error: 0.5786 - mean_absolute_error: 0.4077 - val_loss: 0.3405 - val_mean_squared_error: 0.3405 - val_root_mean_squared_error: 0.5835 - val_mean_absolute_error: 0.4062\n",
      "Epoch 148/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3358 - mean_squared_error: 0.3358 - root_mean_squared_error: 0.5795 - mean_absolute_error: 0.4078 - val_loss: 0.3416 - val_mean_squared_error: 0.3416 - val_root_mean_squared_error: 0.5845 - val_mean_absolute_error: 0.4122\n",
      "Epoch 149/1000\n",
      "363/363 [==============================] - 1s 1ms/step - loss: 0.3329 - mean_squared_error: 0.3329 - root_mean_squared_error: 0.5770 - mean_absolute_error: 0.4066 - val_loss: 0.3396 - val_mean_squared_error: 0.3396 - val_root_mean_squared_error: 0.5827 - val_mean_absolute_error: 0.4097\n",
      "Epoch 150/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3339 - mean_squared_error: 0.3339 - root_mean_squared_error: 0.5778 - mean_absolute_error: 0.4063 - val_loss: 0.3412 - val_mean_squared_error: 0.3412 - val_root_mean_squared_error: 0.5842 - val_mean_absolute_error: 0.4134\n",
      "Epoch 151/1000\n",
      "363/363 [==============================] - 2s 5ms/step - loss: 0.3332 - mean_squared_error: 0.3332 - root_mean_squared_error: 0.5773 - mean_absolute_error: 0.4069 - val_loss: 0.3407 - val_mean_squared_error: 0.3407 - val_root_mean_squared_error: 0.5837 - val_mean_absolute_error: 0.4089\n",
      "Epoch 152/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3326 - mean_squared_error: 0.3326 - root_mean_squared_error: 0.5767 - mean_absolute_error: 0.4061 - val_loss: 0.3386 - val_mean_squared_error: 0.3386 - val_root_mean_squared_error: 0.5819 - val_mean_absolute_error: 0.4047\n",
      "Epoch 153/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3318 - mean_squared_error: 0.3318 - root_mean_squared_error: 0.5760 - mean_absolute_error: 0.4050 - val_loss: 0.3391 - val_mean_squared_error: 0.3391 - val_root_mean_squared_error: 0.5823 - val_mean_absolute_error: 0.4068\n",
      "Epoch 154/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3322 - mean_squared_error: 0.3322 - root_mean_squared_error: 0.5764 - mean_absolute_error: 0.4060 - val_loss: 0.3381 - val_mean_squared_error: 0.3381 - val_root_mean_squared_error: 0.5815 - val_mean_absolute_error: 0.4052\n",
      "Epoch 155/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3308 - mean_squared_error: 0.3308 - root_mean_squared_error: 0.5751 - mean_absolute_error: 0.4042 - val_loss: 0.3393 - val_mean_squared_error: 0.3393 - val_root_mean_squared_error: 0.5825 - val_mean_absolute_error: 0.4108\n",
      "Epoch 156/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3313 - mean_squared_error: 0.3313 - root_mean_squared_error: 0.5756 - mean_absolute_error: 0.4048 - val_loss: 0.3402 - val_mean_squared_error: 0.3402 - val_root_mean_squared_error: 0.5833 - val_mean_absolute_error: 0.4100\n",
      "Epoch 157/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3310 - mean_squared_error: 0.3310 - root_mean_squared_error: 0.5754 - mean_absolute_error: 0.4040 - val_loss: 0.3389 - val_mean_squared_error: 0.3389 - val_root_mean_squared_error: 0.5821 - val_mean_absolute_error: 0.4087\n",
      "Epoch 158/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3299 - mean_squared_error: 0.3299 - root_mean_squared_error: 0.5743 - mean_absolute_error: 0.4044 - val_loss: 0.3379 - val_mean_squared_error: 0.3379 - val_root_mean_squared_error: 0.5813 - val_mean_absolute_error: 0.4030\n",
      "Epoch 159/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3304 - mean_squared_error: 0.3304 - root_mean_squared_error: 0.5748 - mean_absolute_error: 0.4039 - val_loss: 0.3374 - val_mean_squared_error: 0.3374 - val_root_mean_squared_error: 0.5809 - val_mean_absolute_error: 0.4037\n",
      "Epoch 160/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3300 - mean_squared_error: 0.3300 - root_mean_squared_error: 0.5745 - mean_absolute_error: 0.4037 - val_loss: 0.3405 - val_mean_squared_error: 0.3405 - val_root_mean_squared_error: 0.5835 - val_mean_absolute_error: 0.4075\n",
      "Epoch 161/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3311 - mean_squared_error: 0.3311 - root_mean_squared_error: 0.5754 - mean_absolute_error: 0.4038 - val_loss: 0.3372 - val_mean_squared_error: 0.3372 - val_root_mean_squared_error: 0.5807 - val_mean_absolute_error: 0.4024\n",
      "Epoch 162/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3296 - mean_squared_error: 0.3296 - root_mean_squared_error: 0.5741 - mean_absolute_error: 0.4031 - val_loss: 0.3381 - val_mean_squared_error: 0.3381 - val_root_mean_squared_error: 0.5815 - val_mean_absolute_error: 0.4098\n",
      "Epoch 163/1000\n"
     ]
    },
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     "text": [
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3298 - mean_squared_error: 0.3298 - root_mean_squared_error: 0.5742 - mean_absolute_error: 0.4032 - val_loss: 0.3376 - val_mean_squared_error: 0.3376 - val_root_mean_squared_error: 0.5810 - val_mean_absolute_error: 0.4021\n",
      "Epoch 164/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3290 - mean_squared_error: 0.3290 - root_mean_squared_error: 0.5736 - mean_absolute_error: 0.4031 - val_loss: 0.3362 - val_mean_squared_error: 0.3362 - val_root_mean_squared_error: 0.5798 - val_mean_absolute_error: 0.4049\n",
      "Epoch 165/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3285 - mean_squared_error: 0.3285 - root_mean_squared_error: 0.5732 - mean_absolute_error: 0.4029 - val_loss: 0.3367 - val_mean_squared_error: 0.3367 - val_root_mean_squared_error: 0.5802 - val_mean_absolute_error: 0.4084\n",
      "Epoch 166/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3289 - mean_squared_error: 0.3289 - root_mean_squared_error: 0.5735 - mean_absolute_error: 0.4024 - val_loss: 0.3352 - val_mean_squared_error: 0.3352 - val_root_mean_squared_error: 0.5790 - val_mean_absolute_error: 0.4030\n",
      "Epoch 167/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3276 - mean_squared_error: 0.3276 - root_mean_squared_error: 0.5724 - mean_absolute_error: 0.4024 - val_loss: 0.3356 - val_mean_squared_error: 0.3356 - val_root_mean_squared_error: 0.5793 - val_mean_absolute_error: 0.4017\n",
      "Epoch 168/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3276 - mean_squared_error: 0.3276 - root_mean_squared_error: 0.5724 - mean_absolute_error: 0.4018 - val_loss: 0.3373 - val_mean_squared_error: 0.3373 - val_root_mean_squared_error: 0.5808 - val_mean_absolute_error: 0.4105\n",
      "Epoch 169/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3284 - mean_squared_error: 0.3284 - root_mean_squared_error: 0.5731 - mean_absolute_error: 0.4024 - val_loss: 0.3369 - val_mean_squared_error: 0.3369 - val_root_mean_squared_error: 0.5805 - val_mean_absolute_error: 0.4062\n",
      "Epoch 170/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3273 - mean_squared_error: 0.3273 - root_mean_squared_error: 0.5721 - mean_absolute_error: 0.4018 - val_loss: 0.3346 - val_mean_squared_error: 0.3346 - val_root_mean_squared_error: 0.5785 - val_mean_absolute_error: 0.3986\n",
      "Epoch 171/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3275 - mean_squared_error: 0.3275 - root_mean_squared_error: 0.5723 - mean_absolute_error: 0.4013 - val_loss: 0.3351 - val_mean_squared_error: 0.3351 - val_root_mean_squared_error: 0.5789 - val_mean_absolute_error: 0.3998\n",
      "Epoch 172/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3268 - mean_squared_error: 0.3268 - root_mean_squared_error: 0.5716 - mean_absolute_error: 0.4013 - val_loss: 0.3354 - val_mean_squared_error: 0.3354 - val_root_mean_squared_error: 0.5792 - val_mean_absolute_error: 0.4007\n",
      "Epoch 173/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3268 - mean_squared_error: 0.3268 - root_mean_squared_error: 0.5717 - mean_absolute_error: 0.4018 - val_loss: 0.3342 - val_mean_squared_error: 0.3342 - val_root_mean_squared_error: 0.5781 - val_mean_absolute_error: 0.4014\n",
      "Epoch 174/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3257 - mean_squared_error: 0.3257 - root_mean_squared_error: 0.5707 - mean_absolute_error: 0.4000 - val_loss: 0.3372 - val_mean_squared_error: 0.3372 - val_root_mean_squared_error: 0.5807 - val_mean_absolute_error: 0.4089\n",
      "Epoch 175/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3257 - mean_squared_error: 0.3257 - root_mean_squared_error: 0.5707 - mean_absolute_error: 0.4003 - val_loss: 0.3404 - val_mean_squared_error: 0.3404 - val_root_mean_squared_error: 0.5835 - val_mean_absolute_error: 0.4153\n",
      "Epoch 176/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3268 - mean_squared_error: 0.3268 - root_mean_squared_error: 0.5717 - mean_absolute_error: 0.4016 - val_loss: 0.3397 - val_mean_squared_error: 0.3397 - val_root_mean_squared_error: 0.5829 - val_mean_absolute_error: 0.4046\n",
      "Epoch 177/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3262 - mean_squared_error: 0.3262 - root_mean_squared_error: 0.5711 - mean_absolute_error: 0.4003 - val_loss: 0.3335 - val_mean_squared_error: 0.3335 - val_root_mean_squared_error: 0.5775 - val_mean_absolute_error: 0.4010\n",
      "Epoch 178/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3262 - mean_squared_error: 0.3262 - root_mean_squared_error: 0.5712 - mean_absolute_error: 0.4009 - val_loss: 0.3330 - val_mean_squared_error: 0.3330 - val_root_mean_squared_error: 0.5770 - val_mean_absolute_error: 0.4023\n",
      "Epoch 179/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3266 - mean_squared_error: 0.3266 - root_mean_squared_error: 0.5715 - mean_absolute_error: 0.4010 - val_loss: 0.3377 - val_mean_squared_error: 0.3377 - val_root_mean_squared_error: 0.5811 - val_mean_absolute_error: 0.4073\n",
      "Epoch 180/1000\n",
      "363/363 [==============================] - 1s 1ms/step - loss: 0.3250 - mean_squared_error: 0.3250 - root_mean_squared_error: 0.5701 - mean_absolute_error: 0.4006 - val_loss: 0.3325 - val_mean_squared_error: 0.3325 - val_root_mean_squared_error: 0.5766 - val_mean_absolute_error: 0.4012\n",
      "Epoch 181/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3254 - mean_squared_error: 0.3254 - root_mean_squared_error: 0.5704 - mean_absolute_error: 0.4001 - val_loss: 0.3348 - val_mean_squared_error: 0.3348 - val_root_mean_squared_error: 0.5786 - val_mean_absolute_error: 0.4069\n",
      "Epoch 182/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3243 - mean_squared_error: 0.3243 - root_mean_squared_error: 0.5694 - mean_absolute_error: 0.3997 - val_loss: 0.3352 - val_mean_squared_error: 0.3352 - val_root_mean_squared_error: 0.5790 - val_mean_absolute_error: 0.3955\n",
      "Epoch 183/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3254 - mean_squared_error: 0.3254 - root_mean_squared_error: 0.5704 - mean_absolute_error: 0.3999 - val_loss: 0.3320 - val_mean_squared_error: 0.3320 - val_root_mean_squared_error: 0.5762 - val_mean_absolute_error: 0.4002\n",
      "Epoch 184/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3259 - mean_squared_error: 0.3259 - root_mean_squared_error: 0.5709 - mean_absolute_error: 0.4003 - val_loss: 0.3325 - val_mean_squared_error: 0.3325 - val_root_mean_squared_error: 0.5766 - val_mean_absolute_error: 0.3980\n",
      "Epoch 185/1000\n",
      "363/363 [==============================] - 1s 4ms/step - loss: 0.3260 - mean_squared_error: 0.3260 - root_mean_squared_error: 0.5709 - mean_absolute_error: 0.3998 - val_loss: 0.3325 - val_mean_squared_error: 0.3325 - val_root_mean_squared_error: 0.5767 - val_mean_absolute_error: 0.4023\n",
      "Epoch 186/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3238 - mean_squared_error: 0.3238 - root_mean_squared_error: 0.5690 - mean_absolute_error: 0.3989 - val_loss: 0.3330 - val_mean_squared_error: 0.3330 - val_root_mean_squared_error: 0.5771 - val_mean_absolute_error: 0.3977\n",
      "Epoch 187/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3235 - mean_squared_error: 0.3235 - root_mean_squared_error: 0.5687 - mean_absolute_error: 0.3986 - val_loss: 0.3317 - val_mean_squared_error: 0.3317 - val_root_mean_squared_error: 0.5760 - val_mean_absolute_error: 0.4001\n",
      "Epoch 188/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3235 - mean_squared_error: 0.3235 - root_mean_squared_error: 0.5687 - mean_absolute_error: 0.3988 - val_loss: 0.3337 - val_mean_squared_error: 0.3337 - val_root_mean_squared_error: 0.5776 - val_mean_absolute_error: 0.4060\n",
      "Epoch 189/1000\n",
      "363/363 [==============================] - 2s 4ms/step - loss: 0.3232 - mean_squared_error: 0.3232 - root_mean_squared_error: 0.5685 - mean_absolute_error: 0.3985 - val_loss: 0.3347 - val_mean_squared_error: 0.3347 - val_root_mean_squared_error: 0.5786 - val_mean_absolute_error: 0.4067\n",
      "Epoch 190/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3239 - mean_squared_error: 0.3239 - root_mean_squared_error: 0.5691 - mean_absolute_error: 0.3992 - val_loss: 0.3318 - val_mean_squared_error: 0.3318 - val_root_mean_squared_error: 0.5760 - val_mean_absolute_error: 0.3981\n",
      "Epoch 191/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3234 - mean_squared_error: 0.3234 - root_mean_squared_error: 0.5687 - mean_absolute_error: 0.3987 - val_loss: 0.3311 - val_mean_squared_error: 0.3311 - val_root_mean_squared_error: 0.5754 - val_mean_absolute_error: 0.3999\n",
      "Epoch 192/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3228 - mean_squared_error: 0.3228 - root_mean_squared_error: 0.5682 - mean_absolute_error: 0.3982 - val_loss: 0.3320 - val_mean_squared_error: 0.3320 - val_root_mean_squared_error: 0.5762 - val_mean_absolute_error: 0.4018\n",
      "Epoch 193/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3221 - mean_squared_error: 0.3221 - root_mean_squared_error: 0.5675 - mean_absolute_error: 0.3978 - val_loss: 0.3309 - val_mean_squared_error: 0.3309 - val_root_mean_squared_error: 0.5752 - val_mean_absolute_error: 0.3956\n",
      "Epoch 194/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3218 - mean_squared_error: 0.3218 - root_mean_squared_error: 0.5673 - mean_absolute_error: 0.3974 - val_loss: 0.3341 - val_mean_squared_error: 0.3341 - val_root_mean_squared_error: 0.5780 - val_mean_absolute_error: 0.4060\n",
      "Epoch 195/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3228 - mean_squared_error: 0.3228 - root_mean_squared_error: 0.5682 - mean_absolute_error: 0.3983 - val_loss: 0.3337 - val_mean_squared_error: 0.3337 - val_root_mean_squared_error: 0.5776 - val_mean_absolute_error: 0.4075\n",
      "Epoch 196/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3213 - mean_squared_error: 0.3213 - root_mean_squared_error: 0.5668 - mean_absolute_error: 0.3975 - val_loss: 0.3324 - val_mean_squared_error: 0.3324 - val_root_mean_squared_error: 0.5765 - val_mean_absolute_error: 0.4048\n",
      "Epoch 197/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3221 - mean_squared_error: 0.3221 - root_mean_squared_error: 0.5675 - mean_absolute_error: 0.3979 - val_loss: 0.3308 - val_mean_squared_error: 0.3308 - val_root_mean_squared_error: 0.5751 - val_mean_absolute_error: 0.3954\n",
      "Epoch 198/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3210 - mean_squared_error: 0.3210 - root_mean_squared_error: 0.5666 - mean_absolute_error: 0.3968 - val_loss: 0.3381 - val_mean_squared_error: 0.3381 - val_root_mean_squared_error: 0.5815 - val_mean_absolute_error: 0.4133\n",
      "Epoch 199/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3210 - mean_squared_error: 0.3210 - root_mean_squared_error: 0.5666 - mean_absolute_error: 0.3972 - val_loss: 0.3298 - val_mean_squared_error: 0.3298 - val_root_mean_squared_error: 0.5743 - val_mean_absolute_error: 0.3981\n",
      "Epoch 200/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3210 - mean_squared_error: 0.3210 - root_mean_squared_error: 0.5666 - mean_absolute_error: 0.3967 - val_loss: 0.3313 - val_mean_squared_error: 0.3313 - val_root_mean_squared_error: 0.5756 - val_mean_absolute_error: 0.4001\n",
      "Epoch 201/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3211 - mean_squared_error: 0.3211 - root_mean_squared_error: 0.5666 - mean_absolute_error: 0.3972 - val_loss: 0.3298 - val_mean_squared_error: 0.3298 - val_root_mean_squared_error: 0.5743 - val_mean_absolute_error: 0.3970\n",
      "Epoch 202/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3225 - mean_squared_error: 0.3225 - root_mean_squared_error: 0.5679 - mean_absolute_error: 0.3968 - val_loss: 0.3313 - val_mean_squared_error: 0.3313 - val_root_mean_squared_error: 0.5756 - val_mean_absolute_error: 0.4020\n",
      "Epoch 203/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3212 - mean_squared_error: 0.3212 - root_mean_squared_error: 0.5667 - mean_absolute_error: 0.3967 - val_loss: 0.3305 - val_mean_squared_error: 0.3305 - val_root_mean_squared_error: 0.5749 - val_mean_absolute_error: 0.3996\n",
      "Epoch 204/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3209 - mean_squared_error: 0.3209 - root_mean_squared_error: 0.5665 - mean_absolute_error: 0.3969 - val_loss: 0.3313 - val_mean_squared_error: 0.3313 - val_root_mean_squared_error: 0.5756 - val_mean_absolute_error: 0.3956\n",
      "Epoch 205/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3199 - mean_squared_error: 0.3199 - root_mean_squared_error: 0.5656 - mean_absolute_error: 0.3955 - val_loss: 0.3301 - val_mean_squared_error: 0.3301 - val_root_mean_squared_error: 0.5746 - val_mean_absolute_error: 0.4003\n",
      "Epoch 206/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3206 - mean_squared_error: 0.3206 - root_mean_squared_error: 0.5662 - mean_absolute_error: 0.3965 - val_loss: 0.3323 - val_mean_squared_error: 0.3323 - val_root_mean_squared_error: 0.5764 - val_mean_absolute_error: 0.4067\n",
      "Epoch 207/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3196 - mean_squared_error: 0.3196 - root_mean_squared_error: 0.5653 - mean_absolute_error: 0.3957 - val_loss: 0.3306 - val_mean_squared_error: 0.3306 - val_root_mean_squared_error: 0.5750 - val_mean_absolute_error: 0.4023\n",
      "Epoch 208/1000\n",
      "363/363 [==============================] - 2s 6ms/step - loss: 0.3192 - mean_squared_error: 0.3192 - root_mean_squared_error: 0.5650 - mean_absolute_error: 0.3959 - val_loss: 0.3315 - val_mean_squared_error: 0.3315 - val_root_mean_squared_error: 0.5757 - val_mean_absolute_error: 0.4004\n",
      "Epoch 209/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3202 - mean_squared_error: 0.3202 - root_mean_squared_error: 0.5659 - mean_absolute_error: 0.3960 - val_loss: 0.3290 - val_mean_squared_error: 0.3290 - val_root_mean_squared_error: 0.5736 - val_mean_absolute_error: 0.3957\n",
      "Epoch 210/1000\n",
      "363/363 [==============================] - 1s 4ms/step - loss: 0.3197 - mean_squared_error: 0.3197 - root_mean_squared_error: 0.5654 - mean_absolute_error: 0.3959 - val_loss: 0.3295 - val_mean_squared_error: 0.3295 - val_root_mean_squared_error: 0.5740 - val_mean_absolute_error: 0.3981\n",
      "Epoch 211/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3201 - mean_squared_error: 0.3201 - root_mean_squared_error: 0.5657 - mean_absolute_error: 0.3961 - val_loss: 0.3308 - val_mean_squared_error: 0.3308 - val_root_mean_squared_error: 0.5751 - val_mean_absolute_error: 0.4015\n",
      "Epoch 212/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3192 - mean_squared_error: 0.3192 - root_mean_squared_error: 0.5650 - mean_absolute_error: 0.3956 - val_loss: 0.3294 - val_mean_squared_error: 0.3294 - val_root_mean_squared_error: 0.5740 - val_mean_absolute_error: 0.3934\n",
      "Epoch 213/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3189 - mean_squared_error: 0.3189 - root_mean_squared_error: 0.5647 - mean_absolute_error: 0.3950 - val_loss: 0.3290 - val_mean_squared_error: 0.3290 - val_root_mean_squared_error: 0.5736 - val_mean_absolute_error: 0.3953\n",
      "Epoch 214/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3187 - mean_squared_error: 0.3187 - root_mean_squared_error: 0.5646 - mean_absolute_error: 0.3951 - val_loss: 0.3330 - val_mean_squared_error: 0.3330 - val_root_mean_squared_error: 0.5770 - val_mean_absolute_error: 0.4065\n",
      "Epoch 215/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3188 - mean_squared_error: 0.3188 - root_mean_squared_error: 0.5646 - mean_absolute_error: 0.3951 - val_loss: 0.3278 - val_mean_squared_error: 0.3278 - val_root_mean_squared_error: 0.5726 - val_mean_absolute_error: 0.3956\n",
      "Epoch 216/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3189 - mean_squared_error: 0.3189 - root_mean_squared_error: 0.5647 - mean_absolute_error: 0.3948 - val_loss: 0.3346 - val_mean_squared_error: 0.3346 - val_root_mean_squared_error: 0.5785 - val_mean_absolute_error: 0.4113\n",
      "Epoch 217/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3181 - mean_squared_error: 0.3181 - root_mean_squared_error: 0.5640 - mean_absolute_error: 0.3953 - val_loss: 0.3324 - val_mean_squared_error: 0.3324 - val_root_mean_squared_error: 0.5765 - val_mean_absolute_error: 0.4045\n",
      "Epoch 218/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3175 - mean_squared_error: 0.3175 - root_mean_squared_error: 0.5635 - mean_absolute_error: 0.3947 - val_loss: 0.3283 - val_mean_squared_error: 0.3283 - val_root_mean_squared_error: 0.5730 - val_mean_absolute_error: 0.3961\n",
      "Epoch 219/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3187 - mean_squared_error: 0.3187 - root_mean_squared_error: 0.5645 - mean_absolute_error: 0.3947 - val_loss: 0.3294 - val_mean_squared_error: 0.3294 - val_root_mean_squared_error: 0.5739 - val_mean_absolute_error: 0.4010\n",
      "Epoch 220/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3173 - mean_squared_error: 0.3173 - root_mean_squared_error: 0.5633 - mean_absolute_error: 0.3943 - val_loss: 0.3292 - val_mean_squared_error: 0.3292 - val_root_mean_squared_error: 0.5737 - val_mean_absolute_error: 0.3949\n",
      "Epoch 221/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3173 - mean_squared_error: 0.3173 - root_mean_squared_error: 0.5633 - mean_absolute_error: 0.3942 - val_loss: 0.3294 - val_mean_squared_error: 0.3294 - val_root_mean_squared_error: 0.5739 - val_mean_absolute_error: 0.4007\n",
      "Epoch 222/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3172 - mean_squared_error: 0.3172 - root_mean_squared_error: 0.5632 - mean_absolute_error: 0.3938 - val_loss: 0.3321 - val_mean_squared_error: 0.3321 - val_root_mean_squared_error: 0.5763 - val_mean_absolute_error: 0.4027\n",
      "Epoch 223/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3177 - mean_squared_error: 0.3177 - root_mean_squared_error: 0.5637 - mean_absolute_error: 0.3943 - val_loss: 0.3288 - val_mean_squared_error: 0.3288 - val_root_mean_squared_error: 0.5734 - val_mean_absolute_error: 0.3947\n",
      "Epoch 224/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3171 - mean_squared_error: 0.3171 - root_mean_squared_error: 0.5632 - mean_absolute_error: 0.3935 - val_loss: 0.3274 - val_mean_squared_error: 0.3274 - val_root_mean_squared_error: 0.5722 - val_mean_absolute_error: 0.3954\n",
      "Epoch 225/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3173 - mean_squared_error: 0.3173 - root_mean_squared_error: 0.5633 - mean_absolute_error: 0.3939 - val_loss: 0.3300 - val_mean_squared_error: 0.3300 - val_root_mean_squared_error: 0.5745 - val_mean_absolute_error: 0.3907\n",
      "Epoch 226/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3168 - mean_squared_error: 0.3168 - root_mean_squared_error: 0.5628 - mean_absolute_error: 0.3929 - val_loss: 0.3305 - val_mean_squared_error: 0.3305 - val_root_mean_squared_error: 0.5749 - val_mean_absolute_error: 0.4030\n",
      "Epoch 227/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3172 - mean_squared_error: 0.3172 - root_mean_squared_error: 0.5632 - mean_absolute_error: 0.3941 - val_loss: 0.3273 - val_mean_squared_error: 0.3273 - val_root_mean_squared_error: 0.5721 - val_mean_absolute_error: 0.3945\n",
      "Epoch 228/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3163 - mean_squared_error: 0.3163 - root_mean_squared_error: 0.5624 - mean_absolute_error: 0.3934 - val_loss: 0.3286 - val_mean_squared_error: 0.3286 - val_root_mean_squared_error: 0.5733 - val_mean_absolute_error: 0.3907\n",
      "Epoch 229/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3169 - mean_squared_error: 0.3169 - root_mean_squared_error: 0.5630 - mean_absolute_error: 0.3933 - val_loss: 0.3273 - val_mean_squared_error: 0.3273 - val_root_mean_squared_error: 0.5721 - val_mean_absolute_error: 0.3961\n",
      "Epoch 230/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3164 - mean_squared_error: 0.3164 - root_mean_squared_error: 0.5625 - mean_absolute_error: 0.3930 - val_loss: 0.3268 - val_mean_squared_error: 0.3268 - val_root_mean_squared_error: 0.5717 - val_mean_absolute_error: 0.3918\n",
      "Epoch 231/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3166 - mean_squared_error: 0.3166 - root_mean_squared_error: 0.5626 - mean_absolute_error: 0.3935 - val_loss: 0.3276 - val_mean_squared_error: 0.3276 - val_root_mean_squared_error: 0.5724 - val_mean_absolute_error: 0.3947\n",
      "Epoch 232/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3164 - mean_squared_error: 0.3164 - root_mean_squared_error: 0.5625 - mean_absolute_error: 0.3931 - val_loss: 0.3295 - val_mean_squared_error: 0.3295 - val_root_mean_squared_error: 0.5740 - val_mean_absolute_error: 0.3997\n",
      "Epoch 233/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3162 - mean_squared_error: 0.3162 - root_mean_squared_error: 0.5623 - mean_absolute_error: 0.3932 - val_loss: 0.3295 - val_mean_squared_error: 0.3295 - val_root_mean_squared_error: 0.5740 - val_mean_absolute_error: 0.4000\n",
      "Epoch 234/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3156 - mean_squared_error: 0.3156 - root_mean_squared_error: 0.5618 - mean_absolute_error: 0.3925 - val_loss: 0.3320 - val_mean_squared_error: 0.3320 - val_root_mean_squared_error: 0.5762 - val_mean_absolute_error: 0.4042\n",
      "Epoch 235/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3152 - mean_squared_error: 0.3152 - root_mean_squared_error: 0.5615 - mean_absolute_error: 0.3926 - val_loss: 0.3270 - val_mean_squared_error: 0.3270 - val_root_mean_squared_error: 0.5718 - val_mean_absolute_error: 0.3930\n",
      "Epoch 236/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3146 - mean_squared_error: 0.3146 - root_mean_squared_error: 0.5609 - mean_absolute_error: 0.3923 - val_loss: 0.3308 - val_mean_squared_error: 0.3308 - val_root_mean_squared_error: 0.5752 - val_mean_absolute_error: 0.3928\n",
      "Epoch 237/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3154 - mean_squared_error: 0.3154 - root_mean_squared_error: 0.5616 - mean_absolute_error: 0.3922 - val_loss: 0.3275 - val_mean_squared_error: 0.3275 - val_root_mean_squared_error: 0.5723 - val_mean_absolute_error: 0.3983\n",
      "Epoch 238/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3159 - mean_squared_error: 0.3159 - root_mean_squared_error: 0.5620 - mean_absolute_error: 0.3931 - val_loss: 0.3267 - val_mean_squared_error: 0.3267 - val_root_mean_squared_error: 0.5716 - val_mean_absolute_error: 0.3956\n",
      "Epoch 239/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3147 - mean_squared_error: 0.3147 - root_mean_squared_error: 0.5610 - mean_absolute_error: 0.3919 - val_loss: 0.3292 - val_mean_squared_error: 0.3292 - val_root_mean_squared_error: 0.5738 - val_mean_absolute_error: 0.4001\n",
      "Epoch 240/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3155 - mean_squared_error: 0.3155 - root_mean_squared_error: 0.5617 - mean_absolute_error: 0.3923 - val_loss: 0.3259 - val_mean_squared_error: 0.3259 - val_root_mean_squared_error: 0.5709 - val_mean_absolute_error: 0.3920\n",
      "Epoch 241/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3145 - mean_squared_error: 0.3145 - root_mean_squared_error: 0.5608 - mean_absolute_error: 0.3920 - val_loss: 0.3311 - val_mean_squared_error: 0.3311 - val_root_mean_squared_error: 0.5754 - val_mean_absolute_error: 0.4050\n",
      "Epoch 242/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3149 - mean_squared_error: 0.3149 - root_mean_squared_error: 0.5612 - mean_absolute_error: 0.3921 - val_loss: 0.3265 - val_mean_squared_error: 0.3265 - val_root_mean_squared_error: 0.5714 - val_mean_absolute_error: 0.3943\n",
      "Epoch 243/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3142 - mean_squared_error: 0.3142 - root_mean_squared_error: 0.5606 - mean_absolute_error: 0.3909 - val_loss: 0.3290 - val_mean_squared_error: 0.3290 - val_root_mean_squared_error: 0.5736 - val_mean_absolute_error: 0.4001\n",
      "Epoch 244/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3139 - mean_squared_error: 0.3139 - root_mean_squared_error: 0.5603 - mean_absolute_error: 0.3914 - val_loss: 0.3271 - val_mean_squared_error: 0.3271 - val_root_mean_squared_error: 0.5719 - val_mean_absolute_error: 0.3952\n",
      "Epoch 245/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3145 - mean_squared_error: 0.3145 - root_mean_squared_error: 0.5608 - mean_absolute_error: 0.3916 - val_loss: 0.3252 - val_mean_squared_error: 0.3252 - val_root_mean_squared_error: 0.5703 - val_mean_absolute_error: 0.3925\n",
      "Epoch 246/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3140 - mean_squared_error: 0.3140 - root_mean_squared_error: 0.5604 - mean_absolute_error: 0.3914 - val_loss: 0.3278 - val_mean_squared_error: 0.3278 - val_root_mean_squared_error: 0.5725 - val_mean_absolute_error: 0.3976\n",
      "Epoch 247/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3168 - mean_squared_error: 0.3168 - root_mean_squared_error: 0.5629 - mean_absolute_error: 0.3922 - val_loss: 0.3258 - val_mean_squared_error: 0.3258 - val_root_mean_squared_error: 0.5708 - val_mean_absolute_error: 0.3901\n",
      "Epoch 248/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3149 - mean_squared_error: 0.3149 - root_mean_squared_error: 0.5612 - mean_absolute_error: 0.3917 - val_loss: 0.3303 - val_mean_squared_error: 0.3303 - val_root_mean_squared_error: 0.5747 - val_mean_absolute_error: 0.4045\n",
      "Epoch 249/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3142 - mean_squared_error: 0.3142 - root_mean_squared_error: 0.5605 - mean_absolute_error: 0.3918 - val_loss: 0.3248 - val_mean_squared_error: 0.3248 - val_root_mean_squared_error: 0.5699 - val_mean_absolute_error: 0.3919\n",
      "Epoch 250/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3137 - mean_squared_error: 0.3137 - root_mean_squared_error: 0.5601 - mean_absolute_error: 0.3911 - val_loss: 0.3268 - val_mean_squared_error: 0.3268 - val_root_mean_squared_error: 0.5716 - val_mean_absolute_error: 0.3969\n",
      "Epoch 251/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3131 - mean_squared_error: 0.3131 - root_mean_squared_error: 0.5595 - mean_absolute_error: 0.3910 - val_loss: 0.3288 - val_mean_squared_error: 0.3288 - val_root_mean_squared_error: 0.5734 - val_mean_absolute_error: 0.3899\n",
      "Epoch 252/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3139 - mean_squared_error: 0.3139 - root_mean_squared_error: 0.5603 - mean_absolute_error: 0.3909 - val_loss: 0.3246 - val_mean_squared_error: 0.3246 - val_root_mean_squared_error: 0.5697 - val_mean_absolute_error: 0.3909\n",
      "Epoch 253/1000\n",
      "363/363 [==============================] - 1s 4ms/step - loss: 0.3136 - mean_squared_error: 0.3136 - root_mean_squared_error: 0.5600 - mean_absolute_error: 0.3909 - val_loss: 0.3268 - val_mean_squared_error: 0.3268 - val_root_mean_squared_error: 0.5717 - val_mean_absolute_error: 0.3947\n",
      "Epoch 254/1000\n",
      "363/363 [==============================] - 1s 4ms/step - loss: 0.3133 - mean_squared_error: 0.3133 - root_mean_squared_error: 0.5598 - mean_absolute_error: 0.3908 - val_loss: 0.3280 - val_mean_squared_error: 0.3280 - val_root_mean_squared_error: 0.5727 - val_mean_absolute_error: 0.4017\n",
      "Epoch 255/1000\n",
      "363/363 [==============================] - 1s 4ms/step - loss: 0.3133 - mean_squared_error: 0.3133 - root_mean_squared_error: 0.5598 - mean_absolute_error: 0.3910 - val_loss: 0.3255 - val_mean_squared_error: 0.3255 - val_root_mean_squared_error: 0.5705 - val_mean_absolute_error: 0.3958\n",
      "Epoch 256/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3126 - mean_squared_error: 0.3126 - root_mean_squared_error: 0.5591 - mean_absolute_error: 0.3901 - val_loss: 0.3250 - val_mean_squared_error: 0.3250 - val_root_mean_squared_error: 0.5701 - val_mean_absolute_error: 0.3949\n",
      "Epoch 257/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3126 - mean_squared_error: 0.3126 - root_mean_squared_error: 0.5591 - mean_absolute_error: 0.3895 - val_loss: 0.3265 - val_mean_squared_error: 0.3265 - val_root_mean_squared_error: 0.5714 - val_mean_absolute_error: 0.3960\n",
      "Epoch 258/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3126 - mean_squared_error: 0.3126 - root_mean_squared_error: 0.5591 - mean_absolute_error: 0.3900 - val_loss: 0.3260 - val_mean_squared_error: 0.3260 - val_root_mean_squared_error: 0.5709 - val_mean_absolute_error: 0.3982\n",
      "Epoch 259/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3128 - mean_squared_error: 0.3128 - root_mean_squared_error: 0.5593 - mean_absolute_error: 0.3906 - val_loss: 0.3243 - val_mean_squared_error: 0.3243 - val_root_mean_squared_error: 0.5694 - val_mean_absolute_error: 0.3910\n",
      "Epoch 260/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3125 - mean_squared_error: 0.3125 - root_mean_squared_error: 0.5590 - mean_absolute_error: 0.3899 - val_loss: 0.3285 - val_mean_squared_error: 0.3285 - val_root_mean_squared_error: 0.5732 - val_mean_absolute_error: 0.3992\n",
      "Epoch 261/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3130 - mean_squared_error: 0.3130 - root_mean_squared_error: 0.5595 - mean_absolute_error: 0.3907 - val_loss: 0.3250 - val_mean_squared_error: 0.3250 - val_root_mean_squared_error: 0.5701 - val_mean_absolute_error: 0.3951\n",
      "Epoch 262/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3125 - mean_squared_error: 0.3125 - root_mean_squared_error: 0.5590 - mean_absolute_error: 0.3903 - val_loss: 0.3253 - val_mean_squared_error: 0.3253 - val_root_mean_squared_error: 0.5703 - val_mean_absolute_error: 0.3940\n",
      "Epoch 263/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3125 - mean_squared_error: 0.3125 - root_mean_squared_error: 0.5590 - mean_absolute_error: 0.3902 - val_loss: 0.3248 - val_mean_squared_error: 0.3248 - val_root_mean_squared_error: 0.5699 - val_mean_absolute_error: 0.3937\n",
      "Epoch 264/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3124 - mean_squared_error: 0.3124 - root_mean_squared_error: 0.5589 - mean_absolute_error: 0.3901 - val_loss: 0.3251 - val_mean_squared_error: 0.3251 - val_root_mean_squared_error: 0.5702 - val_mean_absolute_error: 0.3879\n",
      "Epoch 265/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3135 - mean_squared_error: 0.3135 - root_mean_squared_error: 0.5599 - mean_absolute_error: 0.3900 - val_loss: 0.3234 - val_mean_squared_error: 0.3234 - val_root_mean_squared_error: 0.5687 - val_mean_absolute_error: 0.3893\n",
      "Epoch 266/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3121 - mean_squared_error: 0.3121 - root_mean_squared_error: 0.5586 - mean_absolute_error: 0.3898 - val_loss: 0.3327 - val_mean_squared_error: 0.3327 - val_root_mean_squared_error: 0.5768 - val_mean_absolute_error: 0.4022\n",
      "Epoch 267/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3124 - mean_squared_error: 0.3124 - root_mean_squared_error: 0.5589 - mean_absolute_error: 0.3901 - val_loss: 0.3239 - val_mean_squared_error: 0.3239 - val_root_mean_squared_error: 0.5691 - val_mean_absolute_error: 0.3894\n",
      "Epoch 268/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3116 - mean_squared_error: 0.3116 - root_mean_squared_error: 0.5582 - mean_absolute_error: 0.3893 - val_loss: 0.3233 - val_mean_squared_error: 0.3233 - val_root_mean_squared_error: 0.5686 - val_mean_absolute_error: 0.3926\n",
      "Epoch 269/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3118 - mean_squared_error: 0.3118 - root_mean_squared_error: 0.5584 - mean_absolute_error: 0.3895 - val_loss: 0.3263 - val_mean_squared_error: 0.3263 - val_root_mean_squared_error: 0.5712 - val_mean_absolute_error: 0.3943\n",
      "Epoch 270/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3115 - mean_squared_error: 0.3115 - root_mean_squared_error: 0.5581 - mean_absolute_error: 0.3897 - val_loss: 0.3243 - val_mean_squared_error: 0.3243 - val_root_mean_squared_error: 0.5695 - val_mean_absolute_error: 0.3891\n",
      "Epoch 271/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3113 - mean_squared_error: 0.3113 - root_mean_squared_error: 0.5579 - mean_absolute_error: 0.3888 - val_loss: 0.3234 - val_mean_squared_error: 0.3234 - val_root_mean_squared_error: 0.5687 - val_mean_absolute_error: 0.3921\n",
      "Epoch 272/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3119 - mean_squared_error: 0.3119 - root_mean_squared_error: 0.5585 - mean_absolute_error: 0.3895 - val_loss: 0.3239 - val_mean_squared_error: 0.3239 - val_root_mean_squared_error: 0.5691 - val_mean_absolute_error: 0.3943\n",
      "Epoch 273/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3110 - mean_squared_error: 0.3110 - root_mean_squared_error: 0.5576 - mean_absolute_error: 0.3893 - val_loss: 0.3262 - val_mean_squared_error: 0.3262 - val_root_mean_squared_error: 0.5711 - val_mean_absolute_error: 0.3916\n",
      "Epoch 274/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3112 - mean_squared_error: 0.3112 - root_mean_squared_error: 0.5579 - mean_absolute_error: 0.3888 - val_loss: 0.3255 - val_mean_squared_error: 0.3255 - val_root_mean_squared_error: 0.5706 - val_mean_absolute_error: 0.3891\n",
      "Epoch 275/1000\n",
      "363/363 [==============================] - 1s 4ms/step - loss: 0.3105 - mean_squared_error: 0.3105 - root_mean_squared_error: 0.5572 - mean_absolute_error: 0.3882 - val_loss: 0.3271 - val_mean_squared_error: 0.3271 - val_root_mean_squared_error: 0.5720 - val_mean_absolute_error: 0.3979\n",
      "Epoch 276/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3107 - mean_squared_error: 0.3107 - root_mean_squared_error: 0.5574 - mean_absolute_error: 0.3894 - val_loss: 0.3238 - val_mean_squared_error: 0.3238 - val_root_mean_squared_error: 0.5691 - val_mean_absolute_error: 0.3893\n",
      "Epoch 277/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3123 - mean_squared_error: 0.3123 - root_mean_squared_error: 0.5588 - mean_absolute_error: 0.3891 - val_loss: 0.3246 - val_mean_squared_error: 0.3246 - val_root_mean_squared_error: 0.5697 - val_mean_absolute_error: 0.3961\n",
      "Epoch 278/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3105 - mean_squared_error: 0.3105 - root_mean_squared_error: 0.5572 - mean_absolute_error: 0.3888 - val_loss: 0.3222 - val_mean_squared_error: 0.3222 - val_root_mean_squared_error: 0.5676 - val_mean_absolute_error: 0.3886\n",
      "Epoch 279/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3102 - mean_squared_error: 0.3102 - root_mean_squared_error: 0.5570 - mean_absolute_error: 0.3884 - val_loss: 0.3276 - val_mean_squared_error: 0.3276 - val_root_mean_squared_error: 0.5724 - val_mean_absolute_error: 0.3971\n",
      "Epoch 280/1000\n",
      "363/363 [==============================] - 1s 1ms/step - loss: 0.3104 - mean_squared_error: 0.3104 - root_mean_squared_error: 0.5571 - mean_absolute_error: 0.3886 - val_loss: 0.3270 - val_mean_squared_error: 0.3270 - val_root_mean_squared_error: 0.5719 - val_mean_absolute_error: 0.3904\n",
      "Epoch 281/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3105 - mean_squared_error: 0.3105 - root_mean_squared_error: 0.5572 - mean_absolute_error: 0.3881 - val_loss: 0.3294 - val_mean_squared_error: 0.3294 - val_root_mean_squared_error: 0.5740 - val_mean_absolute_error: 0.4045\n",
      "Epoch 282/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3107 - mean_squared_error: 0.3107 - root_mean_squared_error: 0.5574 - mean_absolute_error: 0.3887 - val_loss: 0.3247 - val_mean_squared_error: 0.3247 - val_root_mean_squared_error: 0.5698 - val_mean_absolute_error: 0.3968\n",
      "Epoch 283/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3107 - mean_squared_error: 0.3107 - root_mean_squared_error: 0.5574 - mean_absolute_error: 0.3884 - val_loss: 0.3221 - val_mean_squared_error: 0.3221 - val_root_mean_squared_error: 0.5675 - val_mean_absolute_error: 0.3907\n",
      "Epoch 284/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3102 - mean_squared_error: 0.3102 - root_mean_squared_error: 0.5570 - mean_absolute_error: 0.3878 - val_loss: 0.3248 - val_mean_squared_error: 0.3248 - val_root_mean_squared_error: 0.5699 - val_mean_absolute_error: 0.3959\n",
      "Epoch 285/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3092 - mean_squared_error: 0.3092 - root_mean_squared_error: 0.5560 - mean_absolute_error: 0.3874 - val_loss: 0.3241 - val_mean_squared_error: 0.3241 - val_root_mean_squared_error: 0.5693 - val_mean_absolute_error: 0.3933\n",
      "Epoch 286/1000\n",
      "363/363 [==============================] - ETA: 0s - loss: 0.3098 - mean_squared_error: 0.3098 - root_mean_squared_error: 0.5566 - mean_absolute_error: 0.38 - 0s 1ms/step - loss: 0.3100 - mean_squared_error: 0.3100 - root_mean_squared_error: 0.5568 - mean_absolute_error: 0.3881 - val_loss: 0.3252 - val_mean_squared_error: 0.3252 - val_root_mean_squared_error: 0.5702 - val_mean_absolute_error: 0.3951\n",
      "Epoch 287/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3090 - mean_squared_error: 0.3090 - root_mean_squared_error: 0.5559 - mean_absolute_error: 0.3881 - val_loss: 0.3253 - val_mean_squared_error: 0.3253 - val_root_mean_squared_error: 0.5703 - val_mean_absolute_error: 0.3951\n",
      "Epoch 288/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3092 - mean_squared_error: 0.3092 - root_mean_squared_error: 0.5561 - mean_absolute_error: 0.3877 - val_loss: 0.3243 - val_mean_squared_error: 0.3243 - val_root_mean_squared_error: 0.5694 - val_mean_absolute_error: 0.3898\n",
      "Epoch 289/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3092 - mean_squared_error: 0.3092 - root_mean_squared_error: 0.5561 - mean_absolute_error: 0.3876 - val_loss: 0.3229 - val_mean_squared_error: 0.3229 - val_root_mean_squared_error: 0.5683 - val_mean_absolute_error: 0.3869\n",
      "Epoch 290/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3094 - mean_squared_error: 0.3094 - root_mean_squared_error: 0.5562 - mean_absolute_error: 0.3877 - val_loss: 0.3241 - val_mean_squared_error: 0.3241 - val_root_mean_squared_error: 0.5693 - val_mean_absolute_error: 0.3936\n",
      "Epoch 291/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3091 - mean_squared_error: 0.3091 - root_mean_squared_error: 0.5560 - mean_absolute_error: 0.3871 - val_loss: 0.3231 - val_mean_squared_error: 0.3231 - val_root_mean_squared_error: 0.5684 - val_mean_absolute_error: 0.3943\n",
      "Epoch 292/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3089 - mean_squared_error: 0.3089 - root_mean_squared_error: 0.5558 - mean_absolute_error: 0.3875 - val_loss: 0.3257 - val_mean_squared_error: 0.3257 - val_root_mean_squared_error: 0.5707 - val_mean_absolute_error: 0.3950\n",
      "Epoch 293/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3092 - mean_squared_error: 0.3092 - root_mean_squared_error: 0.5561 - mean_absolute_error: 0.3875 - val_loss: 0.3221 - val_mean_squared_error: 0.3221 - val_root_mean_squared_error: 0.5675 - val_mean_absolute_error: 0.3922\n",
      "Epoch 294/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3083 - mean_squared_error: 0.3083 - root_mean_squared_error: 0.5552 - mean_absolute_error: 0.3871 - val_loss: 0.3231 - val_mean_squared_error: 0.3231 - val_root_mean_squared_error: 0.5684 - val_mean_absolute_error: 0.3954\n",
      "Epoch 295/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3090 - mean_squared_error: 0.3090 - root_mean_squared_error: 0.5558 - mean_absolute_error: 0.3875 - val_loss: 0.3261 - val_mean_squared_error: 0.3261 - val_root_mean_squared_error: 0.5711 - val_mean_absolute_error: 0.3994\n",
      "Epoch 296/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3087 - mean_squared_error: 0.3087 - root_mean_squared_error: 0.5556 - mean_absolute_error: 0.3871 - val_loss: 0.3212 - val_mean_squared_error: 0.3212 - val_root_mean_squared_error: 0.5668 - val_mean_absolute_error: 0.3891\n",
      "Epoch 297/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3089 - mean_squared_error: 0.3089 - root_mean_squared_error: 0.5558 - mean_absolute_error: 0.3874 - val_loss: 0.3220 - val_mean_squared_error: 0.3220 - val_root_mean_squared_error: 0.5675 - val_mean_absolute_error: 0.3873\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "Epoch 298/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3084 - mean_squared_error: 0.3084 - root_mean_squared_error: 0.5553 - mean_absolute_error: 0.3867 - val_loss: 0.3255 - val_mean_squared_error: 0.3255 - val_root_mean_squared_error: 0.5706 - val_mean_absolute_error: 0.3957\n",
      "Epoch 299/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3082 - mean_squared_error: 0.3082 - root_mean_squared_error: 0.5551 - mean_absolute_error: 0.3867 - val_loss: 0.3220 - val_mean_squared_error: 0.3220 - val_root_mean_squared_error: 0.5675 - val_mean_absolute_error: 0.3899\n",
      "Epoch 300/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3078 - mean_squared_error: 0.3078 - root_mean_squared_error: 0.5548 - mean_absolute_error: 0.3865 - val_loss: 0.3222 - val_mean_squared_error: 0.3222 - val_root_mean_squared_error: 0.5676 - val_mean_absolute_error: 0.3849\n",
      "Epoch 301/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3077 - mean_squared_error: 0.3077 - root_mean_squared_error: 0.5547 - mean_absolute_error: 0.3860 - val_loss: 0.3244 - val_mean_squared_error: 0.3244 - val_root_mean_squared_error: 0.5696 - val_mean_absolute_error: 0.3958\n",
      "Epoch 302/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3079 - mean_squared_error: 0.3079 - root_mean_squared_error: 0.5549 - mean_absolute_error: 0.3863 - val_loss: 0.3212 - val_mean_squared_error: 0.3212 - val_root_mean_squared_error: 0.5667 - val_mean_absolute_error: 0.3900\n",
      "Epoch 303/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3086 - mean_squared_error: 0.3086 - root_mean_squared_error: 0.5555 - mean_absolute_error: 0.3867 - val_loss: 0.3209 - val_mean_squared_error: 0.3209 - val_root_mean_squared_error: 0.5665 - val_mean_absolute_error: 0.3869\n",
      "Epoch 304/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3076 - mean_squared_error: 0.3076 - root_mean_squared_error: 0.5546 - mean_absolute_error: 0.3865 - val_loss: 0.3203 - val_mean_squared_error: 0.3203 - val_root_mean_squared_error: 0.5659 - val_mean_absolute_error: 0.3870\n",
      "Epoch 305/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3079 - mean_squared_error: 0.3079 - root_mean_squared_error: 0.5549 - mean_absolute_error: 0.3866 - val_loss: 0.3275 - val_mean_squared_error: 0.3275 - val_root_mean_squared_error: 0.5723 - val_mean_absolute_error: 0.3978\n",
      "Epoch 306/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3084 - mean_squared_error: 0.3084 - root_mean_squared_error: 0.5553 - mean_absolute_error: 0.3864 - val_loss: 0.3199 - val_mean_squared_error: 0.3199 - val_root_mean_squared_error: 0.5656 - val_mean_absolute_error: 0.3866\n",
      "Epoch 307/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3085 - mean_squared_error: 0.3085 - root_mean_squared_error: 0.5554 - mean_absolute_error: 0.3865 - val_loss: 0.3230 - val_mean_squared_error: 0.3230 - val_root_mean_squared_error: 0.5683 - val_mean_absolute_error: 0.3961\n",
      "Epoch 308/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3076 - mean_squared_error: 0.3076 - root_mean_squared_error: 0.5546 - mean_absolute_error: 0.3863 - val_loss: 0.3209 - val_mean_squared_error: 0.3209 - val_root_mean_squared_error: 0.5665 - val_mean_absolute_error: 0.3857\n",
      "Epoch 309/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3076 - mean_squared_error: 0.3076 - root_mean_squared_error: 0.5546 - mean_absolute_error: 0.3859 - val_loss: 0.3202 - val_mean_squared_error: 0.3202 - val_root_mean_squared_error: 0.5659 - val_mean_absolute_error: 0.3882\n",
      "Epoch 310/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3074 - mean_squared_error: 0.3074 - root_mean_squared_error: 0.5545 - mean_absolute_error: 0.3858 - val_loss: 0.3208 - val_mean_squared_error: 0.3208 - val_root_mean_squared_error: 0.5663 - val_mean_absolute_error: 0.3898\n",
      "Epoch 311/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3081 - mean_squared_error: 0.3081 - root_mean_squared_error: 0.5551 - mean_absolute_error: 0.3863 - val_loss: 0.3206 - val_mean_squared_error: 0.3206 - val_root_mean_squared_error: 0.5662 - val_mean_absolute_error: 0.3868\n",
      "Epoch 312/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3072 - mean_squared_error: 0.3072 - root_mean_squared_error: 0.5543 - mean_absolute_error: 0.3858 - val_loss: 0.3197 - val_mean_squared_error: 0.3197 - val_root_mean_squared_error: 0.5654 - val_mean_absolute_error: 0.3859\n",
      "Epoch 313/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3066 - mean_squared_error: 0.3066 - root_mean_squared_error: 0.5538 - mean_absolute_error: 0.3855 - val_loss: 0.3220 - val_mean_squared_error: 0.3220 - val_root_mean_squared_error: 0.5675 - val_mean_absolute_error: 0.3912\n",
      "Epoch 314/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3065 - mean_squared_error: 0.3065 - root_mean_squared_error: 0.5536 - mean_absolute_error: 0.3860 - val_loss: 0.3226 - val_mean_squared_error: 0.3226 - val_root_mean_squared_error: 0.5680 - val_mean_absolute_error: 0.3922\n",
      "Epoch 315/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3064 - mean_squared_error: 0.3064 - root_mean_squared_error: 0.5535 - mean_absolute_error: 0.3855 - val_loss: 0.3211 - val_mean_squared_error: 0.3211 - val_root_mean_squared_error: 0.5667 - val_mean_absolute_error: 0.3866\n",
      "Epoch 316/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3069 - mean_squared_error: 0.3069 - root_mean_squared_error: 0.5540 - mean_absolute_error: 0.3855 - val_loss: 0.3192 - val_mean_squared_error: 0.3192 - val_root_mean_squared_error: 0.5650 - val_mean_absolute_error: 0.3865\n",
      "Epoch 317/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3063 - mean_squared_error: 0.3063 - root_mean_squared_error: 0.5534 - mean_absolute_error: 0.3848 - val_loss: 0.3217 - val_mean_squared_error: 0.3217 - val_root_mean_squared_error: 0.5672 - val_mean_absolute_error: 0.3927\n",
      "Epoch 318/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3064 - mean_squared_error: 0.3064 - root_mean_squared_error: 0.5535 - mean_absolute_error: 0.3851 - val_loss: 0.3197 - val_mean_squared_error: 0.3197 - val_root_mean_squared_error: 0.5654 - val_mean_absolute_error: 0.3857\n",
      "Epoch 319/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3069 - mean_squared_error: 0.3069 - root_mean_squared_error: 0.5540 - mean_absolute_error: 0.3858 - val_loss: 0.3213 - val_mean_squared_error: 0.3213 - val_root_mean_squared_error: 0.5668 - val_mean_absolute_error: 0.3862\n",
      "Epoch 320/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3059 - mean_squared_error: 0.3059 - root_mean_squared_error: 0.5531 - mean_absolute_error: 0.3849 - val_loss: 0.3238 - val_mean_squared_error: 0.3238 - val_root_mean_squared_error: 0.5690 - val_mean_absolute_error: 0.3839\n",
      "Epoch 321/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3058 - mean_squared_error: 0.3058 - root_mean_squared_error: 0.5530 - mean_absolute_error: 0.3843 - val_loss: 0.3213 - val_mean_squared_error: 0.3213 - val_root_mean_squared_error: 0.5668 - val_mean_absolute_error: 0.3917\n",
      "Epoch 322/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3059 - mean_squared_error: 0.3059 - root_mean_squared_error: 0.5531 - mean_absolute_error: 0.3851 - val_loss: 0.3193 - val_mean_squared_error: 0.3193 - val_root_mean_squared_error: 0.5651 - val_mean_absolute_error: 0.3858\n",
      "Epoch 323/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3057 - mean_squared_error: 0.3057 - root_mean_squared_error: 0.5529 - mean_absolute_error: 0.3847 - val_loss: 0.3216 - val_mean_squared_error: 0.3216 - val_root_mean_squared_error: 0.5671 - val_mean_absolute_error: 0.3846\n",
      "Epoch 324/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3064 - mean_squared_error: 0.3064 - root_mean_squared_error: 0.5535 - mean_absolute_error: 0.3849 - val_loss: 0.3200 - val_mean_squared_error: 0.3200 - val_root_mean_squared_error: 0.5657 - val_mean_absolute_error: 0.3887\n",
      "Epoch 325/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3052 - mean_squared_error: 0.3052 - root_mean_squared_error: 0.5524 - mean_absolute_error: 0.3850 - val_loss: 0.3203 - val_mean_squared_error: 0.3203 - val_root_mean_squared_error: 0.5660 - val_mean_absolute_error: 0.3886\n",
      "Epoch 326/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3058 - mean_squared_error: 0.3058 - root_mean_squared_error: 0.5530 - mean_absolute_error: 0.3845 - val_loss: 0.3197 - val_mean_squared_error: 0.3197 - val_root_mean_squared_error: 0.5654 - val_mean_absolute_error: 0.3869\n",
      "Epoch 327/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3060 - mean_squared_error: 0.3060 - root_mean_squared_error: 0.5531 - mean_absolute_error: 0.3845 - val_loss: 0.3189 - val_mean_squared_error: 0.3189 - val_root_mean_squared_error: 0.5647 - val_mean_absolute_error: 0.3847\n",
      "Epoch 328/1000\n",
      "363/363 [==============================] - 1s 1ms/step - loss: 0.3063 - mean_squared_error: 0.3063 - root_mean_squared_error: 0.5534 - mean_absolute_error: 0.3847 - val_loss: 0.3189 - val_mean_squared_error: 0.3189 - val_root_mean_squared_error: 0.5647 - val_mean_absolute_error: 0.3854\n",
      "Epoch 329/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3050 - mean_squared_error: 0.3050 - root_mean_squared_error: 0.5523 - mean_absolute_error: 0.3842 - val_loss: 0.3207 - val_mean_squared_error: 0.3207 - val_root_mean_squared_error: 0.5663 - val_mean_absolute_error: 0.3845\n",
      "Epoch 330/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3055 - mean_squared_error: 0.3055 - root_mean_squared_error: 0.5528 - mean_absolute_error: 0.3843 - val_loss: 0.3210 - val_mean_squared_error: 0.3210 - val_root_mean_squared_error: 0.5666 - val_mean_absolute_error: 0.3834\n",
      "Epoch 331/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3062 - mean_squared_error: 0.3062 - root_mean_squared_error: 0.5534 - mean_absolute_error: 0.3847 - val_loss: 0.3195 - val_mean_squared_error: 0.3195 - val_root_mean_squared_error: 0.5652 - val_mean_absolute_error: 0.3842\n",
      "Epoch 332/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3051 - mean_squared_error: 0.3051 - root_mean_squared_error: 0.5524 - mean_absolute_error: 0.3847 - val_loss: 0.3213 - val_mean_squared_error: 0.3213 - val_root_mean_squared_error: 0.5668 - val_mean_absolute_error: 0.3925\n",
      "Epoch 333/1000\n",
      "363/363 [==============================] - 1s 1ms/step - loss: 0.3051 - mean_squared_error: 0.3051 - root_mean_squared_error: 0.5523 - mean_absolute_error: 0.3839 - val_loss: 0.3192 - val_mean_squared_error: 0.3192 - val_root_mean_squared_error: 0.5650 - val_mean_absolute_error: 0.3884\n",
      "Epoch 334/1000\n",
      "363/363 [==============================] - 1s 1ms/step - loss: 0.3048 - mean_squared_error: 0.3048 - root_mean_squared_error: 0.5521 - mean_absolute_error: 0.3840 - val_loss: 0.3190 - val_mean_squared_error: 0.3190 - val_root_mean_squared_error: 0.5648 - val_mean_absolute_error: 0.3888\n",
      "Epoch 335/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3045 - mean_squared_error: 0.3045 - root_mean_squared_error: 0.5518 - mean_absolute_error: 0.3836 - val_loss: 0.3211 - val_mean_squared_error: 0.3211 - val_root_mean_squared_error: 0.5666 - val_mean_absolute_error: 0.3889\n",
      "Epoch 336/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3047 - mean_squared_error: 0.3047 - root_mean_squared_error: 0.5520 - mean_absolute_error: 0.3845 - val_loss: 0.3217 - val_mean_squared_error: 0.3217 - val_root_mean_squared_error: 0.5672 - val_mean_absolute_error: 0.3834\n",
      "Epoch 337/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3051 - mean_squared_error: 0.3051 - root_mean_squared_error: 0.5523 - mean_absolute_error: 0.3838 - val_loss: 0.3196 - val_mean_squared_error: 0.3196 - val_root_mean_squared_error: 0.5653 - val_mean_absolute_error: 0.3891\n",
      "Epoch 338/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3045 - mean_squared_error: 0.3045 - root_mean_squared_error: 0.5518 - mean_absolute_error: 0.3837 - val_loss: 0.3191 - val_mean_squared_error: 0.3191 - val_root_mean_squared_error: 0.5649 - val_mean_absolute_error: 0.3859\n",
      "Epoch 339/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3052 - mean_squared_error: 0.3052 - root_mean_squared_error: 0.5524 - mean_absolute_error: 0.3839 - val_loss: 0.3192 - val_mean_squared_error: 0.3192 - val_root_mean_squared_error: 0.5650 - val_mean_absolute_error: 0.3844\n",
      "Epoch 340/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3052 - mean_squared_error: 0.3052 - root_mean_squared_error: 0.5524 - mean_absolute_error: 0.3834 - val_loss: 0.3188 - val_mean_squared_error: 0.3188 - val_root_mean_squared_error: 0.5646 - val_mean_absolute_error: 0.3893\n",
      "Epoch 341/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3047 - mean_squared_error: 0.3047 - root_mean_squared_error: 0.5520 - mean_absolute_error: 0.3833 - val_loss: 0.3190 - val_mean_squared_error: 0.3190 - val_root_mean_squared_error: 0.5648 - val_mean_absolute_error: 0.3887\n",
      "Epoch 342/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3041 - mean_squared_error: 0.3041 - root_mean_squared_error: 0.5514 - mean_absolute_error: 0.3832 - val_loss: 0.3204 - val_mean_squared_error: 0.3204 - val_root_mean_squared_error: 0.5660 - val_mean_absolute_error: 0.3911\n",
      "Epoch 343/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3035 - mean_squared_error: 0.3035 - root_mean_squared_error: 0.5509 - mean_absolute_error: 0.3834 - val_loss: 0.3185 - val_mean_squared_error: 0.3185 - val_root_mean_squared_error: 0.5643 - val_mean_absolute_error: 0.3844\n",
      "Epoch 344/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3036 - mean_squared_error: 0.3036 - root_mean_squared_error: 0.5510 - mean_absolute_error: 0.3830 - val_loss: 0.3179 - val_mean_squared_error: 0.3179 - val_root_mean_squared_error: 0.5638 - val_mean_absolute_error: 0.3862\n",
      "Epoch 345/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3044 - mean_squared_error: 0.3044 - root_mean_squared_error: 0.5518 - mean_absolute_error: 0.3830 - val_loss: 0.3195 - val_mean_squared_error: 0.3195 - val_root_mean_squared_error: 0.5652 - val_mean_absolute_error: 0.3878\n",
      "Epoch 346/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3036 - mean_squared_error: 0.3036 - root_mean_squared_error: 0.5510 - mean_absolute_error: 0.3837 - val_loss: 0.3182 - val_mean_squared_error: 0.3182 - val_root_mean_squared_error: 0.5641 - val_mean_absolute_error: 0.3843\n",
      "Epoch 347/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3029 - mean_squared_error: 0.3029 - root_mean_squared_error: 0.5503 - mean_absolute_error: 0.3827 - val_loss: 0.3195 - val_mean_squared_error: 0.3195 - val_root_mean_squared_error: 0.5653 - val_mean_absolute_error: 0.3868\n",
      "Epoch 348/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3037 - mean_squared_error: 0.3037 - root_mean_squared_error: 0.5511 - mean_absolute_error: 0.3827 - val_loss: 0.3198 - val_mean_squared_error: 0.3198 - val_root_mean_squared_error: 0.5655 - val_mean_absolute_error: 0.3877\n",
      "Epoch 349/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3034 - mean_squared_error: 0.3034 - root_mean_squared_error: 0.5508 - mean_absolute_error: 0.3828 - val_loss: 0.3229 - val_mean_squared_error: 0.3229 - val_root_mean_squared_error: 0.5682 - val_mean_absolute_error: 0.3803\n",
      "Epoch 350/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3035 - mean_squared_error: 0.3035 - root_mean_squared_error: 0.5509 - mean_absolute_error: 0.3826 - val_loss: 0.3272 - val_mean_squared_error: 0.3272 - val_root_mean_squared_error: 0.5720 - val_mean_absolute_error: 0.3998\n",
      "Epoch 351/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3033 - mean_squared_error: 0.3033 - root_mean_squared_error: 0.5507 - mean_absolute_error: 0.3824 - val_loss: 0.3188 - val_mean_squared_error: 0.3188 - val_root_mean_squared_error: 0.5647 - val_mean_absolute_error: 0.3886\n",
      "Epoch 352/1000\n"
     ]
    },
    {
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     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3021 - mean_squared_error: 0.3021 - root_mean_squared_error: 0.5497 - mean_absolute_error: 0.3822 - val_loss: 0.3200 - val_mean_squared_error: 0.3200 - val_root_mean_squared_error: 0.5657 - val_mean_absolute_error: 0.3905\n",
      "Epoch 353/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3034 - mean_squared_error: 0.3034 - root_mean_squared_error: 0.5508 - mean_absolute_error: 0.3828 - val_loss: 0.3197 - val_mean_squared_error: 0.3197 - val_root_mean_squared_error: 0.5654 - val_mean_absolute_error: 0.3909\n",
      "Epoch 354/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3029 - mean_squared_error: 0.3029 - root_mean_squared_error: 0.5503 - mean_absolute_error: 0.3822 - val_loss: 0.3182 - val_mean_squared_error: 0.3182 - val_root_mean_squared_error: 0.5641 - val_mean_absolute_error: 0.3862\n",
      "Epoch 355/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3032 - mean_squared_error: 0.3032 - root_mean_squared_error: 0.5506 - mean_absolute_error: 0.3820 - val_loss: 0.3175 - val_mean_squared_error: 0.3175 - val_root_mean_squared_error: 0.5635 - val_mean_absolute_error: 0.3852\n",
      "Epoch 356/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3034 - mean_squared_error: 0.3034 - root_mean_squared_error: 0.5508 - mean_absolute_error: 0.3820 - val_loss: 0.3255 - val_mean_squared_error: 0.3255 - val_root_mean_squared_error: 0.5705 - val_mean_absolute_error: 0.3997\n",
      "Epoch 357/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3025 - mean_squared_error: 0.3025 - root_mean_squared_error: 0.5500 - mean_absolute_error: 0.3821 - val_loss: 0.3193 - val_mean_squared_error: 0.3193 - val_root_mean_squared_error: 0.5650 - val_mean_absolute_error: 0.3866\n",
      "Epoch 358/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3045 - mean_squared_error: 0.3045 - root_mean_squared_error: 0.5518 - mean_absolute_error: 0.3829 - val_loss: 0.3190 - val_mean_squared_error: 0.3190 - val_root_mean_squared_error: 0.5648 - val_mean_absolute_error: 0.3831\n",
      "Epoch 359/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3031 - mean_squared_error: 0.3031 - root_mean_squared_error: 0.5506 - mean_absolute_error: 0.3825 - val_loss: 0.3228 - val_mean_squared_error: 0.3228 - val_root_mean_squared_error: 0.5681 - val_mean_absolute_error: 0.3926\n",
      "Epoch 360/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3026 - mean_squared_error: 0.3026 - root_mean_squared_error: 0.5500 - mean_absolute_error: 0.3817 - val_loss: 0.3216 - val_mean_squared_error: 0.3216 - val_root_mean_squared_error: 0.5671 - val_mean_absolute_error: 0.3937\n",
      "Epoch 361/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3026 - mean_squared_error: 0.3026 - root_mean_squared_error: 0.5501 - mean_absolute_error: 0.3820 - val_loss: 0.3174 - val_mean_squared_error: 0.3174 - val_root_mean_squared_error: 0.5633 - val_mean_absolute_error: 0.3862\n",
      "Epoch 362/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3023 - mean_squared_error: 0.3023 - root_mean_squared_error: 0.5498 - mean_absolute_error: 0.3818 - val_loss: 0.3169 - val_mean_squared_error: 0.3169 - val_root_mean_squared_error: 0.5630 - val_mean_absolute_error: 0.3817\n",
      "Epoch 363/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3024 - mean_squared_error: 0.3024 - root_mean_squared_error: 0.5499 - mean_absolute_error: 0.3816 - val_loss: 0.3255 - val_mean_squared_error: 0.3255 - val_root_mean_squared_error: 0.5705 - val_mean_absolute_error: 0.4020\n",
      "Epoch 364/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3019 - mean_squared_error: 0.3019 - root_mean_squared_error: 0.5495 - mean_absolute_error: 0.3819 - val_loss: 0.3184 - val_mean_squared_error: 0.3184 - val_root_mean_squared_error: 0.5643 - val_mean_absolute_error: 0.3884\n",
      "Epoch 365/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3019 - mean_squared_error: 0.3019 - root_mean_squared_error: 0.5495 - mean_absolute_error: 0.3817 - val_loss: 0.3190 - val_mean_squared_error: 0.3190 - val_root_mean_squared_error: 0.5648 - val_mean_absolute_error: 0.3867\n",
      "Epoch 366/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3019 - mean_squared_error: 0.3019 - root_mean_squared_error: 0.5494 - mean_absolute_error: 0.3816 - val_loss: 0.3194 - val_mean_squared_error: 0.3194 - val_root_mean_squared_error: 0.5652 - val_mean_absolute_error: 0.3899\n",
      "Epoch 367/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3018 - mean_squared_error: 0.3018 - root_mean_squared_error: 0.5493 - mean_absolute_error: 0.3817 - val_loss: 0.3200 - val_mean_squared_error: 0.3200 - val_root_mean_squared_error: 0.5657 - val_mean_absolute_error: 0.3922\n",
      "Epoch 368/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3015 - mean_squared_error: 0.3015 - root_mean_squared_error: 0.5491 - mean_absolute_error: 0.3814 - val_loss: 0.3187 - val_mean_squared_error: 0.3187 - val_root_mean_squared_error: 0.5645 - val_mean_absolute_error: 0.3806\n",
      "Epoch 369/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3018 - mean_squared_error: 0.3018 - root_mean_squared_error: 0.5494 - mean_absolute_error: 0.3816 - val_loss: 0.3173 - val_mean_squared_error: 0.3173 - val_root_mean_squared_error: 0.5633 - val_mean_absolute_error: 0.3817\n",
      "Epoch 370/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3022 - mean_squared_error: 0.3022 - root_mean_squared_error: 0.5498 - mean_absolute_error: 0.3816 - val_loss: 0.3176 - val_mean_squared_error: 0.3176 - val_root_mean_squared_error: 0.5635 - val_mean_absolute_error: 0.3877\n",
      "Epoch 371/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3008 - mean_squared_error: 0.3008 - root_mean_squared_error: 0.5484 - mean_absolute_error: 0.3811 - val_loss: 0.3167 - val_mean_squared_error: 0.3167 - val_root_mean_squared_error: 0.5628 - val_mean_absolute_error: 0.3827\n",
      "Epoch 372/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3023 - mean_squared_error: 0.3023 - root_mean_squared_error: 0.5498 - mean_absolute_error: 0.3822 - val_loss: 0.3169 - val_mean_squared_error: 0.3169 - val_root_mean_squared_error: 0.5630 - val_mean_absolute_error: 0.3840\n",
      "Epoch 373/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3014 - mean_squared_error: 0.3014 - root_mean_squared_error: 0.5490 - mean_absolute_error: 0.3816 - val_loss: 0.3208 - val_mean_squared_error: 0.3208 - val_root_mean_squared_error: 0.5664 - val_mean_absolute_error: 0.3864\n",
      "Epoch 374/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3011 - mean_squared_error: 0.3011 - root_mean_squared_error: 0.5487 - mean_absolute_error: 0.3808 - val_loss: 0.3182 - val_mean_squared_error: 0.3182 - val_root_mean_squared_error: 0.5641 - val_mean_absolute_error: 0.3864\n",
      "Epoch 375/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3009 - mean_squared_error: 0.3009 - root_mean_squared_error: 0.5485 - mean_absolute_error: 0.3809 - val_loss: 0.3210 - val_mean_squared_error: 0.3210 - val_root_mean_squared_error: 0.5666 - val_mean_absolute_error: 0.3932\n",
      "Epoch 376/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3005 - mean_squared_error: 0.3005 - root_mean_squared_error: 0.5482 - mean_absolute_error: 0.3814 - val_loss: 0.3175 - val_mean_squared_error: 0.3175 - val_root_mean_squared_error: 0.5635 - val_mean_absolute_error: 0.3817\n",
      "Epoch 377/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3013 - mean_squared_error: 0.3013 - root_mean_squared_error: 0.5489 - mean_absolute_error: 0.3807 - val_loss: 0.3203 - val_mean_squared_error: 0.3203 - val_root_mean_squared_error: 0.5659 - val_mean_absolute_error: 0.3905\n",
      "Epoch 378/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3021 - mean_squared_error: 0.3021 - root_mean_squared_error: 0.5496 - mean_absolute_error: 0.3813 - val_loss: 0.3163 - val_mean_squared_error: 0.3163 - val_root_mean_squared_error: 0.5624 - val_mean_absolute_error: 0.3841\n",
      "Epoch 379/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3001 - mean_squared_error: 0.3001 - root_mean_squared_error: 0.5478 - mean_absolute_error: 0.3797 - val_loss: 0.3163 - val_mean_squared_error: 0.3163 - val_root_mean_squared_error: 0.5624 - val_mean_absolute_error: 0.3823\n",
      "Epoch 380/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3016 - mean_squared_error: 0.3016 - root_mean_squared_error: 0.5492 - mean_absolute_error: 0.3805 - val_loss: 0.3223 - val_mean_squared_error: 0.3223 - val_root_mean_squared_error: 0.5677 - val_mean_absolute_error: 0.3956\n",
      "Epoch 381/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3009 - mean_squared_error: 0.3009 - root_mean_squared_error: 0.5485 - mean_absolute_error: 0.3805 - val_loss: 0.3233 - val_mean_squared_error: 0.3233 - val_root_mean_squared_error: 0.5686 - val_mean_absolute_error: 0.3942\n",
      "Epoch 382/1000\n",
      "363/363 [==============================] - 2s 5ms/step - loss: 0.3006 - mean_squared_error: 0.3006 - root_mean_squared_error: 0.5483 - mean_absolute_error: 0.3802 - val_loss: 0.3178 - val_mean_squared_error: 0.3178 - val_root_mean_squared_error: 0.5638 - val_mean_absolute_error: 0.3841\n",
      "Epoch 383/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.3012 - mean_squared_error: 0.3012 - root_mean_squared_error: 0.5488 - mean_absolute_error: 0.3808 - val_loss: 0.3178 - val_mean_squared_error: 0.3178 - val_root_mean_squared_error: 0.5637 - val_mean_absolute_error: 0.3866\n",
      "Epoch 384/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3006 - mean_squared_error: 0.3006 - root_mean_squared_error: 0.5483 - mean_absolute_error: 0.3806 - val_loss: 0.3166 - val_mean_squared_error: 0.3166 - val_root_mean_squared_error: 0.5627 - val_mean_absolute_error: 0.3855\n",
      "Epoch 385/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3009 - mean_squared_error: 0.3009 - root_mean_squared_error: 0.5485 - mean_absolute_error: 0.3806 - val_loss: 0.3153 - val_mean_squared_error: 0.3153 - val_root_mean_squared_error: 0.5615 - val_mean_absolute_error: 0.3835\n",
      "Epoch 386/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3005 - mean_squared_error: 0.3005 - root_mean_squared_error: 0.5481 - mean_absolute_error: 0.3800 - val_loss: 0.3191 - val_mean_squared_error: 0.3191 - val_root_mean_squared_error: 0.5648 - val_mean_absolute_error: 0.3905\n",
      "Epoch 387/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3002 - mean_squared_error: 0.3002 - root_mean_squared_error: 0.5479 - mean_absolute_error: 0.3802 - val_loss: 0.3170 - val_mean_squared_error: 0.3170 - val_root_mean_squared_error: 0.5630 - val_mean_absolute_error: 0.3854\n",
      "Epoch 388/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.2994 - mean_squared_error: 0.2994 - root_mean_squared_error: 0.5472 - mean_absolute_error: 0.3794 - val_loss: 0.3157 - val_mean_squared_error: 0.3157 - val_root_mean_squared_error: 0.5619 - val_mean_absolute_error: 0.3845\n",
      "Epoch 389/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.2998 - mean_squared_error: 0.2998 - root_mean_squared_error: 0.5476 - mean_absolute_error: 0.3798 - val_loss: 0.3203 - val_mean_squared_error: 0.3203 - val_root_mean_squared_error: 0.5660 - val_mean_absolute_error: 0.3841\n",
      "Epoch 390/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.3000 - mean_squared_error: 0.3000 - root_mean_squared_error: 0.5478 - mean_absolute_error: 0.3793 - val_loss: 0.3161 - val_mean_squared_error: 0.3161 - val_root_mean_squared_error: 0.5623 - val_mean_absolute_error: 0.3824\n",
      "Epoch 391/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2999 - mean_squared_error: 0.2999 - root_mean_squared_error: 0.5476 - mean_absolute_error: 0.3796 - val_loss: 0.3165 - val_mean_squared_error: 0.3165 - val_root_mean_squared_error: 0.5625 - val_mean_absolute_error: 0.3814\n",
      "Epoch 392/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2990 - mean_squared_error: 0.2990 - root_mean_squared_error: 0.5468 - mean_absolute_error: 0.3793 - val_loss: 0.3183 - val_mean_squared_error: 0.3183 - val_root_mean_squared_error: 0.5642 - val_mean_absolute_error: 0.3809\n",
      "Epoch 393/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.2992 - mean_squared_error: 0.2992 - root_mean_squared_error: 0.5470 - mean_absolute_error: 0.3792 - val_loss: 0.3175 - val_mean_squared_error: 0.3175 - val_root_mean_squared_error: 0.5634 - val_mean_absolute_error: 0.3842\n",
      "Epoch 394/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2989 - mean_squared_error: 0.2989 - root_mean_squared_error: 0.5467 - mean_absolute_error: 0.3789 - val_loss: 0.3188 - val_mean_squared_error: 0.3188 - val_root_mean_squared_error: 0.5646 - val_mean_absolute_error: 0.3899\n",
      "Epoch 395/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2985 - mean_squared_error: 0.2985 - root_mean_squared_error: 0.5464 - mean_absolute_error: 0.3788 - val_loss: 0.3189 - val_mean_squared_error: 0.3189 - val_root_mean_squared_error: 0.5647 - val_mean_absolute_error: 0.3867\n",
      "Epoch 396/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2994 - mean_squared_error: 0.2994 - root_mean_squared_error: 0.5472 - mean_absolute_error: 0.3798 - val_loss: 0.3148 - val_mean_squared_error: 0.3148 - val_root_mean_squared_error: 0.5611 - val_mean_absolute_error: 0.3818\n",
      "Epoch 397/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.2999 - mean_squared_error: 0.2999 - root_mean_squared_error: 0.5476 - mean_absolute_error: 0.3797 - val_loss: 0.3191 - val_mean_squared_error: 0.3191 - val_root_mean_squared_error: 0.5649 - val_mean_absolute_error: 0.3853\n",
      "Epoch 398/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2990 - mean_squared_error: 0.2990 - root_mean_squared_error: 0.5468 - mean_absolute_error: 0.3791 - val_loss: 0.3160 - val_mean_squared_error: 0.3160 - val_root_mean_squared_error: 0.5622 - val_mean_absolute_error: 0.3846\n",
      "Epoch 399/1000\n",
      "363/363 [==============================] - 1s 2ms/step - loss: 0.2985 - mean_squared_error: 0.2985 - root_mean_squared_error: 0.5464 - mean_absolute_error: 0.3791 - val_loss: 0.3146 - val_mean_squared_error: 0.3146 - val_root_mean_squared_error: 0.5609 - val_mean_absolute_error: 0.3820\n",
      "Epoch 400/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2990 - mean_squared_error: 0.2990 - root_mean_squared_error: 0.5468 - mean_absolute_error: 0.3791 - val_loss: 0.3150 - val_mean_squared_error: 0.3150 - val_root_mean_squared_error: 0.5613 - val_mean_absolute_error: 0.3842\n",
      "Epoch 401/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2987 - mean_squared_error: 0.2987 - root_mean_squared_error: 0.5466 - mean_absolute_error: 0.3793 - val_loss: 0.3157 - val_mean_squared_error: 0.3157 - val_root_mean_squared_error: 0.5619 - val_mean_absolute_error: 0.3799\n",
      "Epoch 402/1000\n",
      "363/363 [==============================] - 1s 3ms/step - loss: 0.2989 - mean_squared_error: 0.2989 - root_mean_squared_error: 0.5467 - mean_absolute_error: 0.3788 - val_loss: 0.3150 - val_mean_squared_error: 0.3150 - val_root_mean_squared_error: 0.5612 - val_mean_absolute_error: 0.3822\n",
      "Epoch 403/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2989 - mean_squared_error: 0.2989 - root_mean_squared_error: 0.5468 - mean_absolute_error: 0.3795 - val_loss: 0.3154 - val_mean_squared_error: 0.3154 - val_root_mean_squared_error: 0.5616 - val_mean_absolute_error: 0.3812\n",
      "Epoch 404/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2988 - mean_squared_error: 0.2988 - root_mean_squared_error: 0.5467 - mean_absolute_error: 0.3787 - val_loss: 0.3166 - val_mean_squared_error: 0.3166 - val_root_mean_squared_error: 0.5627 - val_mean_absolute_error: 0.3864\n",
      "Epoch 405/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.3024 - mean_squared_error: 0.3024 - root_mean_squared_error: 0.5499 - mean_absolute_error: 0.3806 - val_loss: 0.3179 - val_mean_squared_error: 0.3179 - val_root_mean_squared_error: 0.5638 - val_mean_absolute_error: 0.3909\n",
      "Epoch 406/1000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2996 - mean_squared_error: 0.2996 - root_mean_squared_error: 0.5474 - mean_absolute_error: 0.3792 - val_loss: 0.3165 - val_mean_squared_error: 0.3165 - val_root_mean_squared_error: 0.5626 - val_mean_absolute_error: 0.3881\n",
      "Epoch 407/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2989 - mean_squared_error: 0.2989 - root_mean_squared_error: 0.5468 - mean_absolute_error: 0.3789 - val_loss: 0.3139 - val_mean_squared_error: 0.3139 - val_root_mean_squared_error: 0.5603 - val_mean_absolute_error: 0.3806\n",
      "Epoch 408/1000\n",
      "363/363 [==============================] - 0s 1ms/step - loss: 0.2988 - mean_squared_error: 0.2988 - root_mean_squared_error: 0.5466 - mean_absolute_error: 0.3783 - val_loss: 0.3155 - val_mean_squared_error: 0.3155 - val_root_mean_squared_error: 0.5617 - val_mean_absolute_error: 0.3867\n",
      "Epoch 409/1000\n",
      "363/363 [==============================] - 1s 1ms/step - loss: 0.2976 - mean_squared_error: 0.2976 - root_mean_squared_error: 0.5456 - mean_absolute_error: 0.3778 - val_loss: 0.3176 - val_mean_squared_error: 0.3176 - val_root_mean_squared_error: 0.5636 - val_mean_absolute_error: 0.3915\n",
      "Epoch 410/1000\n",
      " 31/363 [=>............................] - ETA: 0s - loss: 0.3077 - mean_squared_error: 0.3077 - root_mean_squared_error: 0.5547 - mean_absolute_error: 0.3808"
     ]
    }
   ],
   "source": [
    "# 模型训练\n",
    "model.fit(\n",
    "    (X_train_A, X_train_B), \n",
    "    y_train, \n",
    "    epochs=1000,\n",
    "    validation_data=((X_valid_A, X_valid_B), y_valid),\n",
    "    callbacks=[tensorboard_cb]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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