urbanclap_audio_classification.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "# importing necessary libraries and dependencies\n",
    "import os\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import librosa\n",
    "from sklearn.preprocessing import LabelEncoder\n",
    "from keras.utils.np_utils import to_categorical\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Dropout, Activation\n",
    "from keras.optimizers import Adam\n",
    "from sklearn.cross_validation import train_test_split\n",
    "from sklearn import metrics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "train_data_dir = 'sounds/train/train_sound/'\n",
    "test_data_dir = 'sounds/test/test_sound/'\n",
    "\n",
    "# reading the labels\n",
    "train = pd.read_csv('sounds/labels/train.csv')\n",
    "test  = pd.read_csv('sounds/labels/test.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# function to load files and extract features\n",
    "def parser(row, data_dir):\n",
    "    # setting path\n",
    "    file_name = os.path.join(data_dir,str(row.ID)+'.wav')\n",
    "    print(file_name)\n",
    "    # check if the file is corrupted\n",
    "    try:\n",
    "        # here kaiser_fast is a technique used for faster extraction\n",
    "        # X-> audio_time_series_data; sample_rate-> sampling rate\n",
    "        X, sample_rate = librosa.load(file_name, res_type='kaiser_fast')\n",
    "        \n",
    "        # extraccting Mel-Frequeny Cepstral Coeficients feature from data\n",
    "        # y -> accepts time-series audio data; sr -> accepts sampling rate\n",
    "        # n_mfccs -> no. of MFCCs to return\n",
    "        mfccs = np.mean(librosa.feature.mfcc(y=X, sr=sample_rate, n_mfcc=40).T, axis = 0)\n",
    "    \n",
    "    except Exception as e:\n",
    "        print(\"Error encountered while parsing file: \", e)\n",
    "        return None, None\n",
    "    \n",
    "    # store mfccs features\n",
    "    feature = mfccs\n",
    "    # store the respective id\n",
    "    data_id = row.ID\n",
    "    \n",
    "    return [data_id, feature]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Reading train.csv and storing into temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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      "sounds/train/train_sound/8706.wav\n",
      "sounds/train/train_sound/8707.wav\n",
      "sounds/train/train_sound/8709.wav\n",
      "sounds/train/train_sound/8710.wav\n",
      "sounds/train/train_sound/8711.wav\n",
      "sounds/train/train_sound/8712.wav\n",
      "sounds/train/train_sound/8713.wav\n",
      "sounds/train/train_sound/8714.wav\n",
      "sounds/train/train_sound/8715.wav\n",
      "sounds/train/train_sound/8716.wav\n",
      "sounds/train/train_sound/8717.wav\n",
      "sounds/train/train_sound/8720.wav\n",
      "sounds/train/train_sound/8721.wav\n",
      "sounds/train/train_sound/8722.wav\n",
      "sounds/train/train_sound/8723.wav\n",
      "sounds/train/train_sound/8724.wav\n",
      "sounds/train/train_sound/8725.wav\n",
      "sounds/train/train_sound/8726.wav\n",
      "sounds/train/train_sound/8727.wav\n",
      "sounds/train/train_sound/8728.wav\n",
      "sounds/train/train_sound/8729.wav\n"
     ]
    }
   ],
   "source": [
    "# parsing train\n",
    "temp = train.apply(parser,axis=1,data_dir=train_data_dir)\n",
    "temp.columns = ['ID','feature']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# adding Class to 'temp'\n",
    "temp['Class'] = train['Class']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(temp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "###  Reading test.csv and storing into temp_test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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     ]
    }
   ],
   "source": [
    "# parsing test\n",
    "temp_test = test.apply(parser, axis=1,data_dir=test_data_dir)\n",
    "temp_test.columns = ['ID', 'feature']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.frame.DataFrame"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_test = pd.DataFrame(temp_test)\n",
    "type(temp_test)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_test.columns = ['mix']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['mix'], dtype='object')"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp_test.keys()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_test[['ID','feature']] = temp_test['mix'].apply(pd.Series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp_test.drop('mix',axis=1,inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "---------------------train data---------------------\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "   ID                                            feature         Class\n",
      "0   0  [-82.11494596426586, 139.47317581320874, -42.4...         siren\n",
      "1   1  [-15.769894612414987, 124.14436573811095, -29....  street_music\n",
      "2   2  [-123.38022506442273, 15.143098452630438, -50....      drilling\n",
      "3   3  [-213.30328286853114, 89.27180753632311, -55.2...         siren\n",
      "4   4  [-237.93349628536635, 135.8918560563283, 39.25...      dog_bark\n",
      "\n",
      "---------------------test data---------------------\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "   ID                                            feature\n",
      "0   5  [-76.30322382549225, 20.438902210198894, -17.5...\n",
      "1   7  [-375.73865925201886, 149.91996781459662, -21....\n",
      "2   8  [-150.59951603149054, -26.28008708595475, -24....\n",
      "3   9  [-233.5587138519643, 99.5196021234489, -39.738...\n",
      "4  13  [-74.35735593750343, 107.86107593374763, -15.9...\n",
      "---------------------Checking for NONE values---------------------\n",
      "Series([], Name: ID, dtype: int64)\n"
     ]
    }
   ],
   "source": [
    "print(\"\\n---------------------train data---------------------\")\n",
    "print(type(temp))\n",
    "print(temp.head())\n",
    "\n",
    "print(\"\\n---------------------test data---------------------\")\n",
    "print(type(temp_test))\n",
    "print(temp_test.head())\n",
    "\n",
    "\n",
    "print('---------------------Checking for NONE values---------------------')\n",
    "# checking for NONE values\n",
    "print(temp[temp.Class.isnull()])\n",
    "\n",
    "# removing NONE values from temp\n",
    "temp = temp[temp.Class.notnull()]\n",
    "temp_test = temp_test[temp_test.notnull()]\n",
    "#print(temp.ID[temp.label.isnull()])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['siren', 'street_music', 'drilling', 'dog_bark',\n",
       "       'children_playing', 'gun_shot', 'engine_idling', 'air_conditioner',\n",
       "       'jackhammer', 'car_horn'], dtype=object)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.Class.unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "10"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "temp.Class.nunique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Label Encoding the audio data\n",
    "lb = LabelEncoder()\n",
    "\n",
    "# converting pd.series into np.array for faster processing\n",
    "X = np.array(temp.feature.tolist())\n",
    "y = np.array(temp.Class.tolist())\n",
    "\n",
    "\n",
    "y = to_categorical(lb.fit_transform(y))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_train,x_test,y_train,y_test = train_test_split(X,y, test_size=0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Building a deep learning model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "num_labels = y.shape[1]\n",
    "filter_size = 2\n",
    "\n",
    "def categorical_classifier():\n",
    "    model = Sequential()\n",
    "\n",
    "    # input and first hidden layer\n",
    "    model.add(Dense(input_shape=(40,), units=256, activation='relu', kernel_initializer='uniform'))\n",
    "    model.add(Dropout(0.5))\n",
    "\n",
    "    # second hidden layer\n",
    "    model.add(Dense(units=256,activation='relu',kernel_initializer='uniform'))\n",
    "    model.add(Dropout(0.5))\n",
    "\n",
    "    # output layer\n",
    "    model.add(Dense(units=num_labels, activation='softmax'))\n",
    "\n",
    "    # compiling our model\n",
    "    model.compile(loss='categorical_crossentropy', metrics=['accuracy'], optimizer='adam')\n",
    "\n",
    "    # training the data\n",
    "    #model.fit(X,y, batch_size=32, epochs=500, validation_split=0.3)\n",
    "    return model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 3804 samples, validate on 1631 samples\n",
      "Epoch 1/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.4426 - acc: 0.8906 - val_loss: 0.1756 - val_acc: 0.9546\n",
      "Epoch 2/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.4362 - acc: 0.8891 - val_loss: 0.1726 - val_acc: 0.9577\n",
      "Epoch 3/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.4362 - acc: 0.8925 - val_loss: 0.1761 - val_acc: 0.9522\n",
      "Epoch 4/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.3841 - acc: 0.9017 - val_loss: 0.1761 - val_acc: 0.9595\n",
      "Epoch 5/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.4232 - acc: 0.8862 - val_loss: 0.1723 - val_acc: 0.9583\n",
      "Epoch 6/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.3695 - acc: 0.8970 - val_loss: 0.1870 - val_acc: 0.9522\n",
      "Epoch 7/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.3631 - acc: 0.8914 - val_loss: 0.1781 - val_acc: 0.9540\n",
      "Epoch 8/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.3526 - acc: 0.8954 - val_loss: 0.1670 - val_acc: 0.9565\n",
      "Epoch 9/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.3957 - acc: 0.8856 - val_loss: 0.1752 - val_acc: 0.9608\n",
      "Epoch 10/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.3671 - acc: 0.8948 - val_loss: 0.1718 - val_acc: 0.9589\n",
      "Epoch 11/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.3752 - acc: 0.8922 - val_loss: 0.1848 - val_acc: 0.9522\n",
      "Epoch 12/650\n",
      "3804/3804 [==============================] - 1s 155us/step - loss: 0.3821 - acc: 0.8922 - val_loss: 0.1713 - val_acc: 0.9546\n",
      "Epoch 13/650\n",
      "3804/3804 [==============================] - 1s 141us/step - loss: 0.3455 - acc: 0.8967 - val_loss: 0.1741 - val_acc: 0.9559\n",
      "Epoch 14/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.3324 - acc: 0.9017 - val_loss: 0.1734 - val_acc: 0.9565\n",
      "Epoch 15/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.3351 - acc: 0.9035 - val_loss: 0.1701 - val_acc: 0.9608\n",
      "Epoch 16/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.3375 - acc: 0.9056 - val_loss: 0.1739 - val_acc: 0.9583\n",
      "Epoch 17/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.3402 - acc: 0.9014 - val_loss: 0.1755 - val_acc: 0.9601\n",
      "Epoch 18/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.3045 - acc: 0.9109 - val_loss: 0.1762 - val_acc: 0.9534\n",
      "Epoch 19/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.3211 - acc: 0.9006 - val_loss: 0.1660 - val_acc: 0.9571\n",
      "Epoch 20/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.3003 - acc: 0.9117 - val_loss: 0.1653 - val_acc: 0.9552\n",
      "Epoch 21/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.3394 - acc: 0.9004 - val_loss: 0.1686 - val_acc: 0.9497\n",
      "Epoch 22/650\n",
      "3804/3804 [==============================] - 1s 149us/step - loss: 0.3631 - acc: 0.8956 - val_loss: 0.1965 - val_acc: 0.9479\n",
      "Epoch 23/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.3626 - acc: 0.8933 - val_loss: 0.1787 - val_acc: 0.9528\n",
      "Epoch 24/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.3293 - acc: 0.9040 - val_loss: 0.1675 - val_acc: 0.9540\n",
      "Epoch 25/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2862 - acc: 0.9151 - val_loss: 0.1635 - val_acc: 0.9577\n",
      "Epoch 26/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.3008 - acc: 0.9093 - val_loss: 0.1783 - val_acc: 0.9552\n",
      "Epoch 27/650\n",
      "3804/3804 [==============================] - 1s 150us/step - loss: 0.3372 - acc: 0.9019 - val_loss: 0.1876 - val_acc: 0.9418\n",
      "Epoch 28/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.3369 - acc: 0.9006 - val_loss: 0.1680 - val_acc: 0.9595\n",
      "Epoch 29/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.3329 - acc: 0.9059 - val_loss: 0.1731 - val_acc: 0.9534\n",
      "Epoch 30/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.3469 - acc: 0.9030 - val_loss: 0.1738 - val_acc: 0.9559\n",
      "Epoch 31/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.3013 - acc: 0.9122 - val_loss: 0.1643 - val_acc: 0.9571\n",
      "Epoch 32/650\n",
      "3804/3804 [==============================] - 1s 145us/step - loss: 0.3095 - acc: 0.9104 - val_loss: 0.1625 - val_acc: 0.9589\n",
      "Epoch 33/650\n",
      "3804/3804 [==============================] - 1s 144us/step - loss: 0.3017 - acc: 0.9119 - val_loss: 0.1493 - val_acc: 0.9583\n",
      "Epoch 34/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.3070 - acc: 0.9030 - val_loss: 0.1682 - val_acc: 0.9552\n",
      "Epoch 35/650\n",
      "3804/3804 [==============================] - 1s 149us/step - loss: 0.3052 - acc: 0.9101 - val_loss: 0.1787 - val_acc: 0.9467\n",
      "Epoch 36/650\n",
      "3804/3804 [==============================] - 1s 153us/step - loss: 0.3146 - acc: 0.9077 - val_loss: 0.1694 - val_acc: 0.9595\n",
      "Epoch 37/650\n",
      "3804/3804 [==============================] - 1s 167us/step - loss: 0.3382 - acc: 0.8988 - val_loss: 0.1717 - val_acc: 0.9546\n",
      "Epoch 38/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.3279 - acc: 0.8996 - val_loss: 0.1757 - val_acc: 0.9546\n",
      "Epoch 39/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2844 - acc: 0.9098 - val_loss: 0.1613 - val_acc: 0.9552\n",
      "Epoch 40/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.3194 - acc: 0.9067 - val_loss: 0.1623 - val_acc: 0.9552\n",
      "Epoch 41/650\n",
      "3804/3804 [==============================] - 1s 159us/step - loss: 0.3107 - acc: 0.9043 - val_loss: 0.1570 - val_acc: 0.9577\n",
      "Epoch 42/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.3009 - acc: 0.9043 - val_loss: 0.1873 - val_acc: 0.9552\n",
      "Epoch 43/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.3351 - acc: 0.9033 - val_loss: 0.1798 - val_acc: 0.9485\n",
      "Epoch 44/650\n",
      "3804/3804 [==============================] - 0s 123us/step - loss: 0.3302 - acc: 0.9046 - val_loss: 0.1679 - val_acc: 0.9595\n",
      "Epoch 45/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2822 - acc: 0.9132 - val_loss: 0.1624 - val_acc: 0.9565\n",
      "Epoch 46/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2875 - acc: 0.9185 - val_loss: 0.1722 - val_acc: 0.9571\n",
      "Epoch 47/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2975 - acc: 0.9090 - val_loss: 0.1668 - val_acc: 0.9528\n",
      "Epoch 48/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2693 - acc: 0.9177 - val_loss: 0.1794 - val_acc: 0.9540\n",
      "Epoch 49/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.3236 - acc: 0.8988 - val_loss: 0.1780 - val_acc: 0.9559\n",
      "Epoch 50/650\n",
      "3804/3804 [==============================] - 1s 156us/step - loss: 0.2953 - acc: 0.9138 - val_loss: 0.1696 - val_acc: 0.9552\n",
      "Epoch 51/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2851 - acc: 0.9109 - val_loss: 0.1747 - val_acc: 0.9534\n",
      "Epoch 52/650\n",
      "3804/3804 [==============================] - 0s 123us/step - loss: 0.2768 - acc: 0.9111 - val_loss: 0.1667 - val_acc: 0.9546\n",
      "Epoch 53/650\n",
      "3804/3804 [==============================] - 0s 122us/step - loss: 0.3134 - acc: 0.9019 - val_loss: 0.1637 - val_acc: 0.9583\n",
      "Epoch 54/650\n",
      "3804/3804 [==============================] - 0s 123us/step - loss: 0.3177 - acc: 0.9043 - val_loss: 0.1590 - val_acc: 0.9589\n",
      "Epoch 55/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2793 - acc: 0.9151 - val_loss: 0.1605 - val_acc: 0.9552\n",
      "Epoch 56/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2913 - acc: 0.9125 - val_loss: 0.1766 - val_acc: 0.9516\n",
      "Epoch 57/650\n",
      "3804/3804 [==============================] - 0s 121us/step - loss: 0.2771 - acc: 0.9132 - val_loss: 0.1661 - val_acc: 0.9522\n",
      "Epoch 58/650\n",
      "3804/3804 [==============================] - 0s 121us/step - loss: 0.2673 - acc: 0.9169 - val_loss: 0.1625 - val_acc: 0.9565\n",
      "Epoch 59/650\n",
      "3804/3804 [==============================] - 0s 120us/step - loss: 0.2813 - acc: 0.9177 - val_loss: 0.1675 - val_acc: 0.9546\n",
      "Epoch 60/650\n",
      "3804/3804 [==============================] - 1s 153us/step - loss: 0.2987 - acc: 0.9104 - val_loss: 0.1526 - val_acc: 0.9571\n",
      "Epoch 61/650\n",
      "3804/3804 [==============================] - 1s 152us/step - loss: 0.3190 - acc: 0.9051 - val_loss: 0.1685 - val_acc: 0.9479\n",
      "Epoch 62/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.2963 - acc: 0.9109 - val_loss: 0.1658 - val_acc: 0.9528\n",
      "Epoch 63/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.3276 - acc: 0.9035 - val_loss: 0.1569 - val_acc: 0.9522\n",
      "Epoch 64/650\n",
      "3804/3804 [==============================] - 0s 126us/step - loss: 0.2918 - acc: 0.9180 - val_loss: 0.1713 - val_acc: 0.9510\n",
      "Epoch 65/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2811 - acc: 0.9148 - val_loss: 0.1749 - val_acc: 0.9534\n",
      "Epoch 66/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2858 - acc: 0.9090 - val_loss: 0.1656 - val_acc: 0.9565\n",
      "Epoch 67/650\n",
      "3804/3804 [==============================] - 0s 120us/step - loss: 0.2884 - acc: 0.9125 - val_loss: 0.1728 - val_acc: 0.9546\n",
      "Epoch 68/650\n",
      "3804/3804 [==============================] - 0s 122us/step - loss: 0.2959 - acc: 0.9164 - val_loss: 0.1691 - val_acc: 0.9534\n",
      "Epoch 69/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2679 - acc: 0.9072 - val_loss: 0.1770 - val_acc: 0.9540\n",
      "Epoch 70/650\n",
      "3804/3804 [==============================] - 0s 123us/step - loss: 0.3126 - acc: 0.9085 - val_loss: 0.1709 - val_acc: 0.9546\n",
      "Epoch 71/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2919 - acc: 0.9119 - val_loss: 0.1702 - val_acc: 0.9559\n",
      "Epoch 72/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2704 - acc: 0.9185 - val_loss: 0.1545 - val_acc: 0.9534\n",
      "Epoch 73/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2817 - acc: 0.9143 - val_loss: 0.1525 - val_acc: 0.9577\n",
      "Epoch 74/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2882 - acc: 0.9130 - val_loss: 0.1665 - val_acc: 0.9528\n",
      "Epoch 75/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2525 - acc: 0.9169 - val_loss: 0.1657 - val_acc: 0.9522\n",
      "Epoch 76/650\n",
      "3804/3804 [==============================] - 1s 131us/step - loss: 0.3008 - acc: 0.9104 - val_loss: 0.1631 - val_acc: 0.9510\n",
      "Epoch 77/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.2846 - acc: 0.9146 - val_loss: 0.1763 - val_acc: 0.9528\n",
      "Epoch 78/650\n",
      "3804/3804 [==============================] - 0s 120us/step - loss: 0.2946 - acc: 0.9188 - val_loss: 0.1737 - val_acc: 0.9534\n",
      "Epoch 79/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2573 - acc: 0.9135 - val_loss: 0.1685 - val_acc: 0.9503\n",
      "Epoch 80/650\n",
      "3804/3804 [==============================] - 0s 122us/step - loss: 0.2455 - acc: 0.9246 - val_loss: 0.1732 - val_acc: 0.9467\n",
      "Epoch 81/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2861 - acc: 0.9148 - val_loss: 0.1756 - val_acc: 0.9503\n",
      "Epoch 82/650\n",
      "3804/3804 [==============================] - 1s 155us/step - loss: 0.3129 - acc: 0.9062 - val_loss: 0.1697 - val_acc: 0.9559\n",
      "Epoch 83/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2721 - acc: 0.9172 - val_loss: 0.1708 - val_acc: 0.9485\n",
      "Epoch 84/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.3072 - acc: 0.9054 - val_loss: 0.1804 - val_acc: 0.9485\n",
      "Epoch 85/650\n",
      "3804/3804 [==============================] - 1s 161us/step - loss: 0.2669 - acc: 0.9146 - val_loss: 0.1719 - val_acc: 0.9510\n",
      "Epoch 86/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2874 - acc: 0.9180 - val_loss: 0.1686 - val_acc: 0.9503\n",
      "Epoch 87/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.3019 - acc: 0.9119 - val_loss: 0.1913 - val_acc: 0.9430\n",
      "Epoch 88/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2884 - acc: 0.9172 - val_loss: 0.1868 - val_acc: 0.9442\n",
      "Epoch 89/650\n",
      "3804/3804 [==============================] - 0s 123us/step - loss: 0.2955 - acc: 0.9119 - val_loss: 0.1799 - val_acc: 0.9503\n",
      "Epoch 90/650\n",
      "3804/3804 [==============================] - 0s 122us/step - loss: 0.2765 - acc: 0.9198 - val_loss: 0.1800 - val_acc: 0.9516\n",
      "Epoch 91/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.3261 - acc: 0.9085 - val_loss: 0.1961 - val_acc: 0.9491\n",
      "Epoch 92/650\n",
      "3804/3804 [==============================] - 0s 120us/step - loss: 0.3089 - acc: 0.9040 - val_loss: 0.1865 - val_acc: 0.9399\n",
      "Epoch 93/650\n",
      "3804/3804 [==============================] - 0s 122us/step - loss: 0.3176 - acc: 0.9069 - val_loss: 0.1774 - val_acc: 0.9510\n",
      "Epoch 94/650\n",
      "3804/3804 [==============================] - 0s 122us/step - loss: 0.2659 - acc: 0.9188 - val_loss: 0.1824 - val_acc: 0.9424\n",
      "Epoch 95/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.2631 - acc: 0.9177 - val_loss: 0.1859 - val_acc: 0.9448\n",
      "Epoch 96/650\n",
      "3804/3804 [==============================] - 0s 126us/step - loss: 0.2874 - acc: 0.9156 - val_loss: 0.1706 - val_acc: 0.9497\n",
      "Epoch 97/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2521 - acc: 0.9274 - val_loss: 0.1808 - val_acc: 0.9497\n",
      "Epoch 98/650\n",
      "3804/3804 [==============================] - 0s 121us/step - loss: 0.2624 - acc: 0.9161 - val_loss: 0.1822 - val_acc: 0.9528\n",
      "Epoch 99/650\n",
      "3804/3804 [==============================] - 0s 122us/step - loss: 0.2891 - acc: 0.9188 - val_loss: 0.1797 - val_acc: 0.9485\n",
      "Epoch 100/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2972 - acc: 0.9122 - val_loss: 0.1813 - val_acc: 0.9436\n",
      "Epoch 101/650\n",
      "3804/3804 [==============================] - 1s 142us/step - loss: 0.3014 - acc: 0.9143 - val_loss: 0.1856 - val_acc: 0.9460\n",
      "Epoch 102/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2823 - acc: 0.9146 - val_loss: 0.1984 - val_acc: 0.9442\n",
      "Epoch 103/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.3318 - acc: 0.9059 - val_loss: 0.1803 - val_acc: 0.9510\n",
      "Epoch 104/650\n",
      "3804/3804 [==============================] - 1s 157us/step - loss: 0.2886 - acc: 0.9172 - val_loss: 0.1693 - val_acc: 0.9473\n",
      "Epoch 105/650\n",
      "3804/3804 [==============================] - 1s 184us/step - loss: 0.2766 - acc: 0.9232 - val_loss: 0.1873 - val_acc: 0.9497\n",
      "Epoch 106/650\n",
      "3804/3804 [==============================] - 1s 193us/step - loss: 0.2680 - acc: 0.9206 - val_loss: 0.1737 - val_acc: 0.9460\n",
      "Epoch 107/650\n",
      "3804/3804 [==============================] - 1s 154us/step - loss: 0.2866 - acc: 0.9201 - val_loss: 0.1673 - val_acc: 0.9497\n",
      "Epoch 108/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2718 - acc: 0.9188 - val_loss: 0.1851 - val_acc: 0.9473\n",
      "Epoch 109/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2661 - acc: 0.9185 - val_loss: 0.1813 - val_acc: 0.9497\n",
      "Epoch 110/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2851 - acc: 0.9159 - val_loss: 0.1751 - val_acc: 0.9503\n",
      "Epoch 111/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2808 - acc: 0.9209 - val_loss: 0.1751 - val_acc: 0.9454\n",
      "Epoch 112/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2945 - acc: 0.9101 - val_loss: 0.1777 - val_acc: 0.9491\n",
      "Epoch 113/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2712 - acc: 0.9222 - val_loss: 0.1753 - val_acc: 0.9546\n",
      "Epoch 114/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.3163 - acc: 0.9151 - val_loss: 0.1713 - val_acc: 0.9522\n",
      "Epoch 115/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2652 - acc: 0.9175 - val_loss: 0.1672 - val_acc: 0.9534\n",
      "Epoch 116/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.3056 - acc: 0.9117 - val_loss: 0.1830 - val_acc: 0.9442\n",
      "Epoch 117/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2607 - acc: 0.9185 - val_loss: 0.1656 - val_acc: 0.9571\n",
      "Epoch 118/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2494 - acc: 0.9261 - val_loss: 0.1723 - val_acc: 0.9546\n",
      "Epoch 119/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.2721 - acc: 0.9203 - val_loss: 0.1651 - val_acc: 0.9510\n",
      "Epoch 120/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2540 - acc: 0.9238 - val_loss: 0.1668 - val_acc: 0.9516\n",
      "Epoch 121/650\n",
      "3804/3804 [==============================] - 0s 122us/step - loss: 0.2378 - acc: 0.9285 - val_loss: 0.1789 - val_acc: 0.9473\n",
      "Epoch 122/650\n",
      "3804/3804 [==============================] - 0s 126us/step - loss: 0.2905 - acc: 0.9164 - val_loss: 0.1792 - val_acc: 0.9479\n",
      "Epoch 123/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2809 - acc: 0.9148 - val_loss: 0.1850 - val_acc: 0.9479\n",
      "Epoch 124/650\n",
      "3804/3804 [==============================] - 0s 126us/step - loss: 0.3221 - acc: 0.9085 - val_loss: 0.1718 - val_acc: 0.9510\n",
      "Epoch 125/650\n",
      "3804/3804 [==============================] - 0s 123us/step - loss: 0.2775 - acc: 0.9167 - val_loss: 0.1820 - val_acc: 0.9528\n",
      "Epoch 126/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2735 - acc: 0.9125 - val_loss: 0.1699 - val_acc: 0.9491\n",
      "Epoch 127/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2953 - acc: 0.9172 - val_loss: 0.1796 - val_acc: 0.9503\n",
      "Epoch 128/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2819 - acc: 0.9146 - val_loss: 0.1811 - val_acc: 0.9540\n",
      "Epoch 129/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2942 - acc: 0.9146 - val_loss: 0.1848 - val_acc: 0.9424\n",
      "Epoch 130/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.3230 - acc: 0.9072 - val_loss: 0.1882 - val_acc: 0.9454\n",
      "Epoch 131/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2571 - acc: 0.9190 - val_loss: 0.1764 - val_acc: 0.9479\n",
      "Epoch 132/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2776 - acc: 0.9240 - val_loss: 0.1891 - val_acc: 0.9430\n",
      "Epoch 133/650\n",
      "3804/3804 [==============================] - 0s 122us/step - loss: 0.2694 - acc: 0.9167 - val_loss: 0.1710 - val_acc: 0.9534\n",
      "Epoch 134/650\n",
      "3804/3804 [==============================] - 0s 123us/step - loss: 0.2418 - acc: 0.9282 - val_loss: 0.1701 - val_acc: 0.9534\n",
      "Epoch 135/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2803 - acc: 0.9180 - val_loss: 0.1834 - val_acc: 0.9485\n",
      "Epoch 136/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2781 - acc: 0.9135 - val_loss: 0.1753 - val_acc: 0.9479\n",
      "Epoch 137/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2778 - acc: 0.9156 - val_loss: 0.1814 - val_acc: 0.9516\n",
      "Epoch 138/650\n",
      "3804/3804 [==============================] - 1s 145us/step - loss: 0.2809 - acc: 0.9148 - val_loss: 0.1767 - val_acc: 0.9528\n",
      "Epoch 139/650\n",
      "3804/3804 [==============================] - 1s 168us/step - loss: 0.2660 - acc: 0.9177 - val_loss: 0.1699 - val_acc: 0.9528\n",
      "Epoch 140/650\n",
      "3804/3804 [==============================] - 1s 153us/step - loss: 0.2771 - acc: 0.9159 - val_loss: 0.1697 - val_acc: 0.9491\n",
      "Epoch 141/650\n",
      "3804/3804 [==============================] - 1s 146us/step - loss: 0.2483 - acc: 0.9246 - val_loss: 0.1721 - val_acc: 0.9546\n",
      "Epoch 142/650\n",
      "3804/3804 [==============================] - 1s 164us/step - loss: 0.2615 - acc: 0.9201 - val_loss: 0.1896 - val_acc: 0.9497\n",
      "Epoch 143/650\n",
      "3804/3804 [==============================] - 1s 164us/step - loss: 0.2549 - acc: 0.9330 - val_loss: 0.1674 - val_acc: 0.9522\n",
      "Epoch 144/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2675 - acc: 0.9267 - val_loss: 0.1926 - val_acc: 0.9473\n",
      "Epoch 145/650\n",
      "3804/3804 [==============================] - 1s 146us/step - loss: 0.2754 - acc: 0.9127 - val_loss: 0.1793 - val_acc: 0.9497\n",
      "Epoch 146/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2824 - acc: 0.9156 - val_loss: 0.1788 - val_acc: 0.9503\n",
      "Epoch 147/650\n",
      "3804/3804 [==============================] - 1s 149us/step - loss: 0.2657 - acc: 0.9154 - val_loss: 0.1728 - val_acc: 0.9473\n",
      "Epoch 148/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2887 - acc: 0.9167 - val_loss: 0.1784 - val_acc: 0.9460\n",
      "Epoch 149/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2719 - acc: 0.9230 - val_loss: 0.1774 - val_acc: 0.9454\n",
      "Epoch 150/650\n",
      "3804/3804 [==============================] - 1s 153us/step - loss: 0.2882 - acc: 0.9138 - val_loss: 0.1698 - val_acc: 0.9467\n",
      "Epoch 151/650\n",
      "3804/3804 [==============================] - 1s 161us/step - loss: 0.2591 - acc: 0.9209 - val_loss: 0.1893 - val_acc: 0.9522\n",
      "Epoch 152/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2720 - acc: 0.9159 - val_loss: 0.1734 - val_acc: 0.9571\n",
      "Epoch 153/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2585 - acc: 0.9209 - val_loss: 0.1917 - val_acc: 0.9497\n",
      "Epoch 154/650\n",
      "3804/3804 [==============================] - 1s 141us/step - loss: 0.2973 - acc: 0.9151 - val_loss: 0.1861 - val_acc: 0.9522\n",
      "Epoch 155/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2998 - acc: 0.9180 - val_loss: 0.1815 - val_acc: 0.9497\n",
      "Epoch 156/650\n",
      "3804/3804 [==============================] - 1s 179us/step - loss: 0.3099 - acc: 0.9104 - val_loss: 0.1825 - val_acc: 0.9516\n",
      "Epoch 157/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2556 - acc: 0.9219 - val_loss: 0.1904 - val_acc: 0.9381\n",
      "Epoch 158/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2407 - acc: 0.9219 - val_loss: 0.1956 - val_acc: 0.9381\n",
      "Epoch 159/650\n",
      "3804/3804 [==============================] - 1s 168us/step - loss: 0.2626 - acc: 0.9180 - val_loss: 0.1801 - val_acc: 0.9485\n",
      "Epoch 160/650\n",
      "3804/3804 [==============================] - 1s 166us/step - loss: 0.2690 - acc: 0.9238 - val_loss: 0.1865 - val_acc: 0.9467\n",
      "Epoch 161/650\n",
      "3804/3804 [==============================] - 1s 145us/step - loss: 0.2720 - acc: 0.9209 - val_loss: 0.1816 - val_acc: 0.9503\n",
      "Epoch 162/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2799 - acc: 0.9151 - val_loss: 0.1760 - val_acc: 0.9503\n",
      "Epoch 163/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2621 - acc: 0.9217 - val_loss: 0.1706 - val_acc: 0.9510\n",
      "Epoch 164/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2560 - acc: 0.9243 - val_loss: 0.1769 - val_acc: 0.9516\n",
      "Epoch 165/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2729 - acc: 0.9235 - val_loss: 0.1860 - val_acc: 0.9430\n",
      "Epoch 166/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2743 - acc: 0.9222 - val_loss: 0.1708 - val_acc: 0.9534\n",
      "Epoch 167/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2360 - acc: 0.9311 - val_loss: 0.1736 - val_acc: 0.9503\n",
      "Epoch 168/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2679 - acc: 0.9196 - val_loss: 0.1845 - val_acc: 0.9454\n",
      "Epoch 169/650\n",
      "3804/3804 [==============================] - 1s 148us/step - loss: 0.2855 - acc: 0.9167 - val_loss: 0.1908 - val_acc: 0.9485\n",
      "Epoch 170/650\n",
      "3804/3804 [==============================] - 1s 184us/step - loss: 0.3111 - acc: 0.9104 - val_loss: 0.2009 - val_acc: 0.9460\n",
      "Epoch 171/650\n",
      "3804/3804 [==============================] - 1s 143us/step - loss: 0.2886 - acc: 0.9106 - val_loss: 0.1896 - val_acc: 0.9448\n",
      "Epoch 172/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2523 - acc: 0.9185 - val_loss: 0.1901 - val_acc: 0.9491\n",
      "Epoch 173/650\n",
      "3804/3804 [==============================] - 1s 178us/step - loss: 0.2792 - acc: 0.9154 - val_loss: 0.1821 - val_acc: 0.9485\n",
      "Epoch 174/650\n",
      "3804/3804 [==============================] - 1s 144us/step - loss: 0.2832 - acc: 0.9159 - val_loss: 0.1832 - val_acc: 0.9497\n",
      "Epoch 175/650\n",
      "3804/3804 [==============================] - 1s 142us/step - loss: 0.2633 - acc: 0.9267 - val_loss: 0.1823 - val_acc: 0.9473\n",
      "Epoch 176/650\n",
      "3804/3804 [==============================] - 1s 164us/step - loss: 0.2713 - acc: 0.9188 - val_loss: 0.1766 - val_acc: 0.9491\n",
      "Epoch 177/650\n",
      "3804/3804 [==============================] - 1s 169us/step - loss: 0.2969 - acc: 0.9154 - val_loss: 0.1950 - val_acc: 0.9411\n",
      "Epoch 178/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2368 - acc: 0.9240 - val_loss: 0.1934 - val_acc: 0.9497\n",
      "Epoch 179/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2639 - acc: 0.9201 - val_loss: 0.1930 - val_acc: 0.9552\n",
      "Epoch 180/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2779 - acc: 0.9159 - val_loss: 0.1840 - val_acc: 0.9497\n",
      "Epoch 181/650\n",
      "3804/3804 [==============================] - 1s 145us/step - loss: 0.2803 - acc: 0.9209 - val_loss: 0.1908 - val_acc: 0.9411\n",
      "Epoch 182/650\n",
      "3804/3804 [==============================] - 1s 184us/step - loss: 0.2774 - acc: 0.9180 - val_loss: 0.1752 - val_acc: 0.9540\n",
      "Epoch 183/650\n",
      "3804/3804 [==============================] - 1s 147us/step - loss: 0.2375 - acc: 0.9264 - val_loss: 0.1759 - val_acc: 0.9503\n",
      "Epoch 184/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2293 - acc: 0.9322 - val_loss: 0.1955 - val_acc: 0.9485\n",
      "Epoch 185/650\n",
      "3804/3804 [==============================] - 1s 154us/step - loss: 0.2714 - acc: 0.9201 - val_loss: 0.1829 - val_acc: 0.9479\n",
      "Epoch 186/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2442 - acc: 0.9227 - val_loss: 0.1875 - val_acc: 0.9411\n",
      "Epoch 187/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2556 - acc: 0.9248 - val_loss: 0.1803 - val_acc: 0.9522\n",
      "Epoch 188/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2369 - acc: 0.9285 - val_loss: 0.1753 - val_acc: 0.9540\n",
      "Epoch 189/650\n",
      "3804/3804 [==============================] - 1s 150us/step - loss: 0.2557 - acc: 0.9209 - val_loss: 0.1842 - val_acc: 0.9516\n",
      "Epoch 190/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2796 - acc: 0.9230 - val_loss: 0.1825 - val_acc: 0.9503\n",
      "Epoch 191/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.3069 - acc: 0.9238 - val_loss: 0.1746 - val_acc: 0.9540\n",
      "Epoch 192/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2600 - acc: 0.9277 - val_loss: 0.1875 - val_acc: 0.9503\n",
      "Epoch 193/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2660 - acc: 0.9227 - val_loss: 0.1757 - val_acc: 0.9467\n",
      "Epoch 194/650\n",
      "3804/3804 [==============================] - 0s 126us/step - loss: 0.2346 - acc: 0.9290 - val_loss: 0.1732 - val_acc: 0.9503\n",
      "Epoch 195/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.2610 - acc: 0.9277 - val_loss: 0.1941 - val_acc: 0.9405\n",
      "Epoch 196/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2863 - acc: 0.9211 - val_loss: 0.1834 - val_acc: 0.9460\n",
      "Epoch 197/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2854 - acc: 0.9132 - val_loss: 0.1838 - val_acc: 0.9503\n",
      "Epoch 198/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2848 - acc: 0.9164 - val_loss: 0.1853 - val_acc: 0.9497\n",
      "Epoch 199/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2601 - acc: 0.9185 - val_loss: 0.1845 - val_acc: 0.9522\n",
      "Epoch 200/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2413 - acc: 0.9293 - val_loss: 0.1978 - val_acc: 0.9424\n",
      "Epoch 201/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2882 - acc: 0.9175 - val_loss: 0.2105 - val_acc: 0.9436\n",
      "Epoch 202/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2669 - acc: 0.9235 - val_loss: 0.1818 - val_acc: 0.9534\n",
      "Epoch 203/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2768 - acc: 0.9227 - val_loss: 0.1800 - val_acc: 0.9516\n",
      "Epoch 204/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2844 - acc: 0.9214 - val_loss: 0.1938 - val_acc: 0.9485\n",
      "Epoch 205/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2270 - acc: 0.9256 - val_loss: 0.1868 - val_acc: 0.9460\n",
      "Epoch 206/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2572 - acc: 0.9238 - val_loss: 0.1992 - val_acc: 0.9454\n",
      "Epoch 207/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2554 - acc: 0.9219 - val_loss: 0.1927 - val_acc: 0.9485\n",
      "Epoch 208/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2567 - acc: 0.9290 - val_loss: 0.1848 - val_acc: 0.9516\n",
      "Epoch 209/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2580 - acc: 0.9269 - val_loss: 0.1922 - val_acc: 0.9460\n",
      "Epoch 210/650\n",
      "3804/3804 [==============================] - 1s 142us/step - loss: 0.2632 - acc: 0.9246 - val_loss: 0.1832 - val_acc: 0.9491\n",
      "Epoch 211/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2331 - acc: 0.9253 - val_loss: 0.1907 - val_acc: 0.9503\n",
      "Epoch 212/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2149 - acc: 0.9327 - val_loss: 0.1743 - val_acc: 0.9479\n",
      "Epoch 213/650\n",
      "3804/3804 [==============================] - 1s 141us/step - loss: 0.2514 - acc: 0.9253 - val_loss: 0.2002 - val_acc: 0.9393\n",
      "Epoch 214/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2909 - acc: 0.9180 - val_loss: 0.1941 - val_acc: 0.9485\n",
      "Epoch 215/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2088 - acc: 0.9322 - val_loss: 0.2040 - val_acc: 0.9424\n",
      "Epoch 216/650\n",
      "3804/3804 [==============================] - 1s 151us/step - loss: 0.2479 - acc: 0.9288 - val_loss: 0.1906 - val_acc: 0.9467\n",
      "Epoch 217/650\n",
      "3804/3804 [==============================] - 1s 141us/step - loss: 0.2847 - acc: 0.9188 - val_loss: 0.1945 - val_acc: 0.9473\n",
      "Epoch 218/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2614 - acc: 0.9219 - val_loss: 0.2121 - val_acc: 0.9405\n",
      "Epoch 219/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2963 - acc: 0.9148 - val_loss: 0.2203 - val_acc: 0.9473\n",
      "Epoch 220/650\n",
      "3804/3804 [==============================] - 1s 146us/step - loss: 0.2747 - acc: 0.9193 - val_loss: 0.2107 - val_acc: 0.9399\n",
      "Epoch 221/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2766 - acc: 0.9146 - val_loss: 0.2065 - val_acc: 0.9460\n",
      "Epoch 222/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2788 - acc: 0.9182 - val_loss: 0.2034 - val_acc: 0.9362\n",
      "Epoch 223/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2806 - acc: 0.9143 - val_loss: 0.1941 - val_acc: 0.9436\n",
      "Epoch 224/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2572 - acc: 0.9290 - val_loss: 0.1857 - val_acc: 0.9460\n",
      "Epoch 225/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2554 - acc: 0.9248 - val_loss: 0.1882 - val_acc: 0.9460\n",
      "Epoch 226/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2593 - acc: 0.9246 - val_loss: 0.1960 - val_acc: 0.9430\n",
      "Epoch 227/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2489 - acc: 0.9264 - val_loss: 0.1994 - val_acc: 0.9448\n",
      "Epoch 228/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2659 - acc: 0.9243 - val_loss: 0.2034 - val_acc: 0.9430\n",
      "Epoch 229/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.2633 - acc: 0.9264 - val_loss: 0.1916 - val_acc: 0.9510\n",
      "Epoch 230/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2686 - acc: 0.9211 - val_loss: 0.1961 - val_acc: 0.9448\n",
      "Epoch 231/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2540 - acc: 0.9246 - val_loss: 0.1867 - val_acc: 0.9473\n",
      "Epoch 232/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2624 - acc: 0.9253 - val_loss: 0.2041 - val_acc: 0.9418\n",
      "Epoch 233/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2806 - acc: 0.9177 - val_loss: 0.2079 - val_acc: 0.9375\n",
      "Epoch 234/650\n",
      "3804/3804 [==============================] - 1s 148us/step - loss: 0.2558 - acc: 0.9238 - val_loss: 0.1887 - val_acc: 0.9473\n",
      "Epoch 235/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2335 - acc: 0.9256 - val_loss: 0.1925 - val_acc: 0.9436\n",
      "Epoch 236/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2559 - acc: 0.9232 - val_loss: 0.2038 - val_acc: 0.9399\n",
      "Epoch 237/650\n",
      "3804/3804 [==============================] - 0s 126us/step - loss: 0.2956 - acc: 0.9159 - val_loss: 0.2297 - val_acc: 0.9381\n",
      "Epoch 238/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2870 - acc: 0.9203 - val_loss: 0.2052 - val_acc: 0.9436\n",
      "Epoch 239/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2586 - acc: 0.9269 - val_loss: 0.2109 - val_acc: 0.9418\n",
      "Epoch 240/650\n",
      "3804/3804 [==============================] - 0s 126us/step - loss: 0.2552 - acc: 0.9248 - val_loss: 0.2075 - val_acc: 0.9460\n",
      "Epoch 241/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2740 - acc: 0.9198 - val_loss: 0.1949 - val_acc: 0.9454\n",
      "Epoch 242/650\n",
      "3804/3804 [==============================] - 0s 126us/step - loss: 0.2624 - acc: 0.9214 - val_loss: 0.2120 - val_acc: 0.9430\n",
      "Epoch 243/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.2795 - acc: 0.9235 - val_loss: 0.2023 - val_acc: 0.9375\n",
      "Epoch 244/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2648 - acc: 0.9240 - val_loss: 0.2057 - val_acc: 0.9405\n",
      "Epoch 245/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2384 - acc: 0.9314 - val_loss: 0.1999 - val_acc: 0.9491\n",
      "Epoch 246/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2544 - acc: 0.9227 - val_loss: 0.1873 - val_acc: 0.9485\n",
      "Epoch 247/650\n",
      "3804/3804 [==============================] - 1s 141us/step - loss: 0.3011 - acc: 0.9177 - val_loss: 0.1989 - val_acc: 0.9418\n",
      "Epoch 248/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2597 - acc: 0.9235 - val_loss: 0.1979 - val_acc: 0.9442\n",
      "Epoch 249/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2348 - acc: 0.9311 - val_loss: 0.2048 - val_acc: 0.9424\n",
      "Epoch 250/650\n",
      "3804/3804 [==============================] - 1s 149us/step - loss: 0.2530 - acc: 0.9219 - val_loss: 0.1897 - val_acc: 0.9479\n",
      "Epoch 251/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2754 - acc: 0.9238 - val_loss: 0.1902 - val_acc: 0.9497\n",
      "Epoch 252/650\n",
      "3804/3804 [==============================] - 1s 161us/step - loss: 0.2448 - acc: 0.9277 - val_loss: 0.1905 - val_acc: 0.9411\n",
      "Epoch 253/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2496 - acc: 0.9293 - val_loss: 0.1965 - val_acc: 0.9436\n",
      "Epoch 254/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2559 - acc: 0.9232 - val_loss: 0.1849 - val_acc: 0.9485\n",
      "Epoch 255/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2583 - acc: 0.9253 - val_loss: 0.1964 - val_acc: 0.9479\n",
      "Epoch 256/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2635 - acc: 0.9293 - val_loss: 0.2172 - val_acc: 0.9424\n",
      "Epoch 257/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2635 - acc: 0.9235 - val_loss: 0.2077 - val_acc: 0.9430\n",
      "Epoch 258/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2905 - acc: 0.9169 - val_loss: 0.2054 - val_acc: 0.9418\n",
      "Epoch 259/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2694 - acc: 0.9261 - val_loss: 0.2266 - val_acc: 0.9368\n",
      "Epoch 260/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2846 - acc: 0.9172 - val_loss: 0.1996 - val_acc: 0.9497\n",
      "Epoch 261/650\n",
      "3804/3804 [==============================] - 1s 145us/step - loss: 0.2302 - acc: 0.9303 - val_loss: 0.2081 - val_acc: 0.9436\n",
      "Epoch 262/650\n",
      "3804/3804 [==============================] - 1s 147us/step - loss: 0.2534 - acc: 0.9295 - val_loss: 0.2190 - val_acc: 0.9424\n",
      "Epoch 263/650\n",
      "3804/3804 [==============================] - 1s 142us/step - loss: 0.2303 - acc: 0.9285 - val_loss: 0.2126 - val_acc: 0.9467\n",
      "Epoch 264/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2212 - acc: 0.9327 - val_loss: 0.2075 - val_acc: 0.9448\n",
      "Epoch 265/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2690 - acc: 0.9301 - val_loss: 0.2194 - val_acc: 0.9405\n",
      "Epoch 266/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2348 - acc: 0.9301 - val_loss: 0.2030 - val_acc: 0.9467\n",
      "Epoch 267/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2511 - acc: 0.9303 - val_loss: 0.2001 - val_acc: 0.9485\n",
      "Epoch 268/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2520 - acc: 0.9214 - val_loss: 0.2175 - val_acc: 0.9418\n",
      "Epoch 269/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2436 - acc: 0.9259 - val_loss: 0.2094 - val_acc: 0.9448\n",
      "Epoch 270/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2937 - acc: 0.9185 - val_loss: 0.2153 - val_acc: 0.9479\n",
      "Epoch 271/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2444 - acc: 0.9272 - val_loss: 0.2192 - val_acc: 0.9430\n",
      "Epoch 272/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.3134 - acc: 0.9143 - val_loss: 0.2230 - val_acc: 0.9448\n",
      "Epoch 273/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2442 - acc: 0.9274 - val_loss: 0.2135 - val_acc: 0.9473\n",
      "Epoch 274/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2532 - acc: 0.9293 - val_loss: 0.2287 - val_acc: 0.9436\n",
      "Epoch 275/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2282 - acc: 0.9306 - val_loss: 0.2125 - val_acc: 0.9516\n",
      "Epoch 276/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2665 - acc: 0.9261 - val_loss: 0.2209 - val_acc: 0.9454\n",
      "Epoch 277/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2498 - acc: 0.9235 - val_loss: 0.2329 - val_acc: 0.9411\n",
      "Epoch 278/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.3381 - acc: 0.9080 - val_loss: 0.2151 - val_acc: 0.9460\n",
      "Epoch 279/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2421 - acc: 0.9314 - val_loss: 0.2201 - val_acc: 0.9454\n",
      "Epoch 280/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2621 - acc: 0.9235 - val_loss: 0.2179 - val_acc: 0.9418\n",
      "Epoch 281/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2452 - acc: 0.9251 - val_loss: 0.2030 - val_acc: 0.9473\n",
      "Epoch 282/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2773 - acc: 0.9274 - val_loss: 0.2137 - val_acc: 0.9424\n",
      "Epoch 283/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2428 - acc: 0.9319 - val_loss: 0.2021 - val_acc: 0.9473\n",
      "Epoch 284/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2643 - acc: 0.9232 - val_loss: 0.2138 - val_acc: 0.9436\n",
      "Epoch 285/650\n",
      "3804/3804 [==============================] - 0s 126us/step - loss: 0.2555 - acc: 0.9280 - val_loss: 0.1940 - val_acc: 0.9534\n",
      "Epoch 286/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2266 - acc: 0.9303 - val_loss: 0.2135 - val_acc: 0.9393\n",
      "Epoch 287/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2953 - acc: 0.9182 - val_loss: 0.2043 - val_acc: 0.9430\n",
      "Epoch 288/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2898 - acc: 0.9211 - val_loss: 0.2143 - val_acc: 0.9436\n",
      "Epoch 289/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2434 - acc: 0.9261 - val_loss: 0.2089 - val_acc: 0.9497\n",
      "Epoch 290/650\n",
      "3804/3804 [==============================] - 0s 124us/step - loss: 0.2532 - acc: 0.9274 - val_loss: 0.1983 - val_acc: 0.9491\n",
      "Epoch 291/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2715 - acc: 0.9251 - val_loss: 0.2033 - val_acc: 0.9485\n",
      "Epoch 292/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2305 - acc: 0.9309 - val_loss: 0.2133 - val_acc: 0.9473\n",
      "Epoch 293/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2236 - acc: 0.9335 - val_loss: 0.2159 - val_acc: 0.9467\n",
      "Epoch 294/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2259 - acc: 0.9345 - val_loss: 0.2310 - val_acc: 0.9430\n",
      "Epoch 295/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2665 - acc: 0.9261 - val_loss: 0.2108 - val_acc: 0.9436\n",
      "Epoch 296/650\n",
      "3804/3804 [==============================] - 1s 141us/step - loss: 0.2984 - acc: 0.9190 - val_loss: 0.2120 - val_acc: 0.9460\n",
      "Epoch 297/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2377 - acc: 0.9267 - val_loss: 0.2119 - val_acc: 0.9454\n",
      "Epoch 298/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2615 - acc: 0.9303 - val_loss: 0.2236 - val_acc: 0.9436\n",
      "Epoch 299/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2599 - acc: 0.9238 - val_loss: 0.2127 - val_acc: 0.9442\n",
      "Epoch 300/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2719 - acc: 0.9248 - val_loss: 0.2227 - val_acc: 0.9467\n",
      "Epoch 301/650\n",
      "3804/3804 [==============================] - 1s 146us/step - loss: 0.2519 - acc: 0.9280 - val_loss: 0.2149 - val_acc: 0.9479\n",
      "Epoch 302/650\n",
      "3804/3804 [==============================] - 0s 126us/step - loss: 0.2789 - acc: 0.9253 - val_loss: 0.2274 - val_acc: 0.9436\n",
      "Epoch 303/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2698 - acc: 0.9182 - val_loss: 0.2110 - val_acc: 0.9479\n",
      "Epoch 304/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2594 - acc: 0.9290 - val_loss: 0.2164 - val_acc: 0.9405\n",
      "Epoch 305/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2634 - acc: 0.9211 - val_loss: 0.2317 - val_acc: 0.9387\n",
      "Epoch 306/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2703 - acc: 0.9206 - val_loss: 0.2393 - val_acc: 0.9436\n",
      "Epoch 307/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2693 - acc: 0.9203 - val_loss: 0.2294 - val_acc: 0.9430\n",
      "Epoch 308/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2429 - acc: 0.9261 - val_loss: 0.2352 - val_acc: 0.9442\n",
      "Epoch 309/650\n",
      "3804/3804 [==============================] - 0s 127us/step - loss: 0.2624 - acc: 0.9251 - val_loss: 0.2187 - val_acc: 0.9479\n",
      "Epoch 310/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2614 - acc: 0.9269 - val_loss: 0.2224 - val_acc: 0.9448\n",
      "Epoch 311/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2767 - acc: 0.9225 - val_loss: 0.2181 - val_acc: 0.9473\n",
      "Epoch 312/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2245 - acc: 0.9317 - val_loss: 0.2222 - val_acc: 0.9460\n",
      "Epoch 313/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2498 - acc: 0.9282 - val_loss: 0.2143 - val_acc: 0.9491\n",
      "Epoch 314/650\n",
      "3804/3804 [==============================] - 0s 125us/step - loss: 0.2636 - acc: 0.9203 - val_loss: 0.2286 - val_acc: 0.9442\n",
      "Epoch 315/650\n",
      "3804/3804 [==============================] - 0s 126us/step - loss: 0.2334 - acc: 0.9324 - val_loss: 0.2284 - val_acc: 0.9418\n",
      "Epoch 316/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2688 - acc: 0.9177 - val_loss: 0.2216 - val_acc: 0.9393\n",
      "Epoch 317/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2341 - acc: 0.9293 - val_loss: 0.2136 - val_acc: 0.9473\n",
      "Epoch 318/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2579 - acc: 0.9290 - val_loss: 0.2185 - val_acc: 0.9454\n",
      "Epoch 319/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2489 - acc: 0.9314 - val_loss: 0.2063 - val_acc: 0.9503\n",
      "Epoch 320/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2671 - acc: 0.9232 - val_loss: 0.2115 - val_acc: 0.9467\n",
      "Epoch 321/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2567 - acc: 0.9288 - val_loss: 0.2204 - val_acc: 0.9460\n",
      "Epoch 322/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2486 - acc: 0.9338 - val_loss: 0.2335 - val_acc: 0.9350\n",
      "Epoch 323/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2694 - acc: 0.9214 - val_loss: 0.2178 - val_acc: 0.9375\n",
      "Epoch 324/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2768 - acc: 0.9227 - val_loss: 0.2184 - val_acc: 0.9405\n",
      "Epoch 325/650\n",
      "3804/3804 [==============================] - 0s 128us/step - loss: 0.2464 - acc: 0.9332 - val_loss: 0.2133 - val_acc: 0.9467\n",
      "Epoch 326/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2455 - acc: 0.9290 - val_loss: 0.2233 - val_acc: 0.9393\n",
      "Epoch 327/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2606 - acc: 0.9267 - val_loss: 0.2176 - val_acc: 0.9418\n",
      "Epoch 328/650\n",
      "3804/3804 [==============================] - 1s 143us/step - loss: 0.2527 - acc: 0.9261 - val_loss: 0.2050 - val_acc: 0.9387\n",
      "Epoch 329/650\n",
      "3804/3804 [==============================] - 1s 180us/step - loss: 0.2169 - acc: 0.9374 - val_loss: 0.2080 - val_acc: 0.9448\n",
      "Epoch 330/650\n",
      "3804/3804 [==============================] - 1s 154us/step - loss: 0.2405 - acc: 0.9340 - val_loss: 0.2120 - val_acc: 0.9424\n",
      "Epoch 331/650\n",
      "3804/3804 [==============================] - 1s 142us/step - loss: 0.2697 - acc: 0.9293 - val_loss: 0.2083 - val_acc: 0.9424\n",
      "Epoch 332/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2448 - acc: 0.9303 - val_loss: 0.2038 - val_acc: 0.9460\n",
      "Epoch 333/650\n",
      "3804/3804 [==============================] - 1s 163us/step - loss: 0.2407 - acc: 0.9317 - val_loss: 0.2017 - val_acc: 0.9479\n",
      "Epoch 334/650\n",
      "3804/3804 [==============================] - 1s 168us/step - loss: 0.2699 - acc: 0.9248 - val_loss: 0.2236 - val_acc: 0.9338\n",
      "Epoch 335/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2776 - acc: 0.9232 - val_loss: 0.2119 - val_acc: 0.9418\n",
      "Epoch 336/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2695 - acc: 0.9235 - val_loss: 0.2037 - val_acc: 0.9497\n",
      "Epoch 337/650\n",
      "3804/3804 [==============================] - 1s 146us/step - loss: 0.2500 - acc: 0.9285 - val_loss: 0.2056 - val_acc: 0.9442\n",
      "Epoch 338/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2393 - acc: 0.9330 - val_loss: 0.2026 - val_acc: 0.9430\n",
      "Epoch 339/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2437 - acc: 0.9306 - val_loss: 0.2080 - val_acc: 0.9436\n",
      "Epoch 340/650\n",
      "3804/3804 [==============================] - 1s 147us/step - loss: 0.2606 - acc: 0.9272 - val_loss: 0.2197 - val_acc: 0.9411\n",
      "Epoch 341/650\n",
      "3804/3804 [==============================] - 1s 153us/step - loss: 0.2564 - acc: 0.9288 - val_loss: 0.1991 - val_acc: 0.9442\n",
      "Epoch 342/650\n",
      "3804/3804 [==============================] - 1s 148us/step - loss: 0.2168 - acc: 0.9343 - val_loss: 0.2068 - val_acc: 0.9454\n",
      "Epoch 343/650\n",
      "3804/3804 [==============================] - 1s 149us/step - loss: 0.2427 - acc: 0.9272 - val_loss: 0.2256 - val_acc: 0.9411\n",
      "Epoch 344/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2656 - acc: 0.9261 - val_loss: 0.2239 - val_acc: 0.9405\n",
      "Epoch 345/650\n",
      "3804/3804 [==============================] - 1s 166us/step - loss: 0.2510 - acc: 0.9301 - val_loss: 0.2247 - val_acc: 0.9442\n",
      "Epoch 346/650\n",
      "3804/3804 [==============================] - 1s 181us/step - loss: 0.2575 - acc: 0.9290 - val_loss: 0.2085 - val_acc: 0.9485\n",
      "Epoch 347/650\n",
      "3804/3804 [==============================] - 1s 172us/step - loss: 0.2465 - acc: 0.9324 - val_loss: 0.2134 - val_acc: 0.9448\n",
      "Epoch 348/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2709 - acc: 0.9235 - val_loss: 0.2035 - val_acc: 0.9479\n",
      "Epoch 349/650\n",
      "3804/3804 [==============================] - 1s 143us/step - loss: 0.2464 - acc: 0.9338 - val_loss: 0.2075 - val_acc: 0.9424\n",
      "Epoch 350/650\n",
      "3804/3804 [==============================] - 1s 151us/step - loss: 0.2563 - acc: 0.9309 - val_loss: 0.2254 - val_acc: 0.9393\n",
      "Epoch 351/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2595 - acc: 0.9269 - val_loss: 0.2234 - val_acc: 0.9375\n",
      "Epoch 352/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2502 - acc: 0.9274 - val_loss: 0.2261 - val_acc: 0.9387\n",
      "Epoch 353/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2588 - acc: 0.9280 - val_loss: 0.2195 - val_acc: 0.9424\n",
      "Epoch 354/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2290 - acc: 0.9309 - val_loss: 0.2324 - val_acc: 0.9387\n",
      "Epoch 355/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2381 - acc: 0.9353 - val_loss: 0.2210 - val_acc: 0.9405\n",
      "Epoch 356/650\n",
      "3804/3804 [==============================] - 1s 151us/step - loss: 0.2704 - acc: 0.9230 - val_loss: 0.2259 - val_acc: 0.9411\n",
      "Epoch 357/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2467 - acc: 0.9309 - val_loss: 0.2199 - val_acc: 0.9454\n",
      "Epoch 358/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2541 - acc: 0.9311 - val_loss: 0.2105 - val_acc: 0.9454\n",
      "Epoch 359/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2694 - acc: 0.9290 - val_loss: 0.2137 - val_acc: 0.9467\n",
      "Epoch 360/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2615 - acc: 0.9327 - val_loss: 0.2215 - val_acc: 0.9393\n",
      "Epoch 361/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2754 - acc: 0.9222 - val_loss: 0.2128 - val_acc: 0.9430\n",
      "Epoch 362/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2485 - acc: 0.9267 - val_loss: 0.2159 - val_acc: 0.9436\n",
      "Epoch 363/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2498 - acc: 0.9295 - val_loss: 0.2169 - val_acc: 0.9399\n",
      "Epoch 364/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2679 - acc: 0.9301 - val_loss: 0.2081 - val_acc: 0.9436\n",
      "Epoch 365/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2582 - acc: 0.9277 - val_loss: 0.2179 - val_acc: 0.9436\n",
      "Epoch 366/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2414 - acc: 0.9277 - val_loss: 0.2271 - val_acc: 0.9375\n",
      "Epoch 367/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2385 - acc: 0.9324 - val_loss: 0.2192 - val_acc: 0.9399\n",
      "Epoch 368/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2144 - acc: 0.9361 - val_loss: 0.2107 - val_acc: 0.9418\n",
      "Epoch 369/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2292 - acc: 0.9338 - val_loss: 0.2153 - val_acc: 0.9473\n",
      "Epoch 370/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2306 - acc: 0.9319 - val_loss: 0.2152 - val_acc: 0.9381\n",
      "Epoch 371/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2462 - acc: 0.9253 - val_loss: 0.2217 - val_acc: 0.9411\n",
      "Epoch 372/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2170 - acc: 0.9340 - val_loss: 0.2155 - val_acc: 0.9473\n",
      "Epoch 373/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2515 - acc: 0.9293 - val_loss: 0.2147 - val_acc: 0.9430\n",
      "Epoch 374/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2360 - acc: 0.9267 - val_loss: 0.2048 - val_acc: 0.9430\n",
      "Epoch 375/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2321 - acc: 0.9348 - val_loss: 0.2138 - val_acc: 0.9442\n",
      "Epoch 376/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2610 - acc: 0.9243 - val_loss: 0.2045 - val_acc: 0.9418\n",
      "Epoch 377/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2379 - acc: 0.9345 - val_loss: 0.2118 - val_acc: 0.9411\n",
      "Epoch 378/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2435 - acc: 0.9274 - val_loss: 0.2059 - val_acc: 0.9430\n",
      "Epoch 379/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2429 - acc: 0.9311 - val_loss: 0.2048 - val_acc: 0.9387\n",
      "Epoch 380/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2376 - acc: 0.9335 - val_loss: 0.1997 - val_acc: 0.9479\n",
      "Epoch 381/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2352 - acc: 0.9330 - val_loss: 0.2092 - val_acc: 0.9411\n",
      "Epoch 382/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2622 - acc: 0.9256 - val_loss: 0.2094 - val_acc: 0.9436\n",
      "Epoch 383/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2605 - acc: 0.9295 - val_loss: 0.2336 - val_acc: 0.9356\n",
      "Epoch 384/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2686 - acc: 0.9269 - val_loss: 0.2341 - val_acc: 0.9356\n",
      "Epoch 385/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2318 - acc: 0.9369 - val_loss: 0.2313 - val_acc: 0.9368\n",
      "Epoch 386/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2324 - acc: 0.9322 - val_loss: 0.2196 - val_acc: 0.9430\n",
      "Epoch 387/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2344 - acc: 0.9309 - val_loss: 0.2208 - val_acc: 0.9405\n",
      "Epoch 388/650\n",
      "3804/3804 [==============================] - 1s 155us/step - loss: 0.2457 - acc: 0.9309 - val_loss: 0.2140 - val_acc: 0.9424\n",
      "Epoch 389/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.1929 - acc: 0.9440 - val_loss: 0.2161 - val_acc: 0.9454\n",
      "Epoch 390/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2236 - acc: 0.9353 - val_loss: 0.2370 - val_acc: 0.9405\n",
      "Epoch 391/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2743 - acc: 0.9285 - val_loss: 0.2201 - val_acc: 0.9362\n",
      "Epoch 392/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2529 - acc: 0.9303 - val_loss: 0.2247 - val_acc: 0.9405\n",
      "Epoch 393/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2693 - acc: 0.9298 - val_loss: 0.2084 - val_acc: 0.9436\n",
      "Epoch 394/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2730 - acc: 0.9253 - val_loss: 0.2282 - val_acc: 0.9430\n",
      "Epoch 395/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2278 - acc: 0.9343 - val_loss: 0.2180 - val_acc: 0.9418\n",
      "Epoch 396/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2239 - acc: 0.9374 - val_loss: 0.2513 - val_acc: 0.9326\n",
      "Epoch 397/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2890 - acc: 0.9246 - val_loss: 0.2477 - val_acc: 0.9215\n",
      "Epoch 398/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2987 - acc: 0.9290 - val_loss: 0.2453 - val_acc: 0.9381\n",
      "Epoch 399/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2391 - acc: 0.9285 - val_loss: 0.2371 - val_acc: 0.9375\n",
      "Epoch 400/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2383 - acc: 0.9327 - val_loss: 0.2170 - val_acc: 0.9418\n",
      "Epoch 401/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2390 - acc: 0.9332 - val_loss: 0.2165 - val_acc: 0.9350\n",
      "Epoch 402/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2601 - acc: 0.9259 - val_loss: 0.2187 - val_acc: 0.9393\n",
      "Epoch 403/650\n",
      "3804/3804 [==============================] - 1s 151us/step - loss: 0.2659 - acc: 0.9285 - val_loss: 0.1976 - val_acc: 0.9467\n",
      "Epoch 404/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2564 - acc: 0.9272 - val_loss: 0.2343 - val_acc: 0.9405\n",
      "Epoch 405/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2230 - acc: 0.9306 - val_loss: 0.2368 - val_acc: 0.9338\n",
      "Epoch 406/650\n",
      "3804/3804 [==============================] - 1s 144us/step - loss: 0.2193 - acc: 0.9327 - val_loss: 0.2312 - val_acc: 0.9387\n",
      "Epoch 407/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2174 - acc: 0.9338 - val_loss: 0.2338 - val_acc: 0.9381\n",
      "Epoch 408/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2241 - acc: 0.9335 - val_loss: 0.2104 - val_acc: 0.9460\n",
      "Epoch 409/650\n",
      "3804/3804 [==============================] - 0s 129us/step - loss: 0.2429 - acc: 0.9309 - val_loss: 0.2377 - val_acc: 0.9393\n",
      "Epoch 410/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2265 - acc: 0.9332 - val_loss: 0.2243 - val_acc: 0.9460\n",
      "Epoch 411/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2497 - acc: 0.9385 - val_loss: 0.2271 - val_acc: 0.9362\n",
      "Epoch 412/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2578 - acc: 0.9317 - val_loss: 0.2149 - val_acc: 0.9411\n",
      "Epoch 413/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2300 - acc: 0.9351 - val_loss: 0.2267 - val_acc: 0.9436\n",
      "Epoch 414/650\n",
      "3804/3804 [==============================] - 1s 152us/step - loss: 0.2166 - acc: 0.9393 - val_loss: 0.2219 - val_acc: 0.9411\n",
      "Epoch 415/650\n",
      "3804/3804 [==============================] - 1s 143us/step - loss: 0.2241 - acc: 0.9330 - val_loss: 0.2250 - val_acc: 0.9424\n",
      "Epoch 416/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2384 - acc: 0.9377 - val_loss: 0.2249 - val_acc: 0.9356\n",
      "Epoch 417/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2566 - acc: 0.9345 - val_loss: 0.2233 - val_acc: 0.9448\n",
      "Epoch 418/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2713 - acc: 0.9309 - val_loss: 0.2322 - val_acc: 0.9393\n",
      "Epoch 419/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2515 - acc: 0.9274 - val_loss: 0.2255 - val_acc: 0.9387\n",
      "Epoch 420/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2631 - acc: 0.9330 - val_loss: 0.2290 - val_acc: 0.9442\n",
      "Epoch 421/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2428 - acc: 0.9267 - val_loss: 0.2309 - val_acc: 0.9436\n",
      "Epoch 422/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2455 - acc: 0.9319 - val_loss: 0.2213 - val_acc: 0.9387\n",
      "Epoch 423/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2599 - acc: 0.9298 - val_loss: 0.2149 - val_acc: 0.9393\n",
      "Epoch 424/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2345 - acc: 0.9301 - val_loss: 0.2409 - val_acc: 0.9393\n",
      "Epoch 425/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2424 - acc: 0.9340 - val_loss: 0.2405 - val_acc: 0.9356\n",
      "Epoch 426/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2385 - acc: 0.9361 - val_loss: 0.2330 - val_acc: 0.9393\n",
      "Epoch 427/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2244 - acc: 0.9382 - val_loss: 0.2378 - val_acc: 0.9442\n",
      "Epoch 428/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2527 - acc: 0.9277 - val_loss: 0.2327 - val_acc: 0.9418\n",
      "Epoch 429/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2602 - acc: 0.9285 - val_loss: 0.2319 - val_acc: 0.9405\n",
      "Epoch 430/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2553 - acc: 0.9267 - val_loss: 0.2313 - val_acc: 0.9368\n",
      "Epoch 431/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2458 - acc: 0.9319 - val_loss: 0.2253 - val_acc: 0.9405\n",
      "Epoch 432/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2066 - acc: 0.9364 - val_loss: 0.2272 - val_acc: 0.9375\n",
      "Epoch 433/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2487 - acc: 0.9303 - val_loss: 0.2164 - val_acc: 0.9442\n",
      "Epoch 434/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2425 - acc: 0.9377 - val_loss: 0.2424 - val_acc: 0.9362\n",
      "Epoch 435/650\n",
      "3804/3804 [==============================] - 1s 153us/step - loss: 0.2334 - acc: 0.9332 - val_loss: 0.2224 - val_acc: 0.9399\n",
      "Epoch 436/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2284 - acc: 0.9361 - val_loss: 0.2357 - val_acc: 0.9381\n",
      "Epoch 437/650\n",
      "3804/3804 [==============================] - 1s 154us/step - loss: 0.2287 - acc: 0.9338 - val_loss: 0.2237 - val_acc: 0.9430\n",
      "Epoch 438/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2369 - acc: 0.9290 - val_loss: 0.2567 - val_acc: 0.9436\n",
      "Epoch 439/650\n",
      "3804/3804 [==============================] - 1s 149us/step - loss: 0.2511 - acc: 0.9259 - val_loss: 0.2476 - val_acc: 0.9375\n",
      "Epoch 440/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2553 - acc: 0.9259 - val_loss: 0.2110 - val_acc: 0.9436\n",
      "Epoch 441/650\n",
      "3804/3804 [==============================] - 1s 167us/step - loss: 0.2296 - acc: 0.9359 - val_loss: 0.2213 - val_acc: 0.9436\n",
      "Epoch 442/650\n",
      "3804/3804 [==============================] - 1s 165us/step - loss: 0.2317 - acc: 0.9324 - val_loss: 0.2079 - val_acc: 0.9460\n",
      "Epoch 443/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2314 - acc: 0.9314 - val_loss: 0.2083 - val_acc: 0.9467\n",
      "Epoch 444/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2155 - acc: 0.9382 - val_loss: 0.2228 - val_acc: 0.9430\n",
      "Epoch 445/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2517 - acc: 0.9253 - val_loss: 0.2312 - val_acc: 0.9387\n",
      "Epoch 446/650\n",
      "3804/3804 [==============================] - 1s 178us/step - loss: 0.2624 - acc: 0.9243 - val_loss: 0.2285 - val_acc: 0.9399\n",
      "Epoch 447/650\n",
      "3804/3804 [==============================] - 1s 183us/step - loss: 0.2382 - acc: 0.9332 - val_loss: 0.2438 - val_acc: 0.9436\n",
      "Epoch 448/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2535 - acc: 0.9340 - val_loss: 0.2244 - val_acc: 0.9405\n",
      "Epoch 449/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2106 - acc: 0.9411 - val_loss: 0.2273 - val_acc: 0.9399\n",
      "Epoch 450/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2242 - acc: 0.9264 - val_loss: 0.2142 - val_acc: 0.9436\n",
      "Epoch 451/650\n",
      "3804/3804 [==============================] - 1s 146us/step - loss: 0.2325 - acc: 0.9406 - val_loss: 0.2391 - val_acc: 0.9368\n",
      "Epoch 452/650\n",
      "3804/3804 [==============================] - 1s 150us/step - loss: 0.2519 - acc: 0.9301 - val_loss: 0.2270 - val_acc: 0.9399\n",
      "Epoch 453/650\n",
      "3804/3804 [==============================] - 1s 155us/step - loss: 0.2331 - acc: 0.9306 - val_loss: 0.2248 - val_acc: 0.9399\n",
      "Epoch 454/650\n",
      "3804/3804 [==============================] - 1s 146us/step - loss: 0.2407 - acc: 0.9343 - val_loss: 0.2311 - val_acc: 0.9387\n",
      "Epoch 455/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2534 - acc: 0.9317 - val_loss: 0.2244 - val_acc: 0.9405\n",
      "Epoch 456/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2145 - acc: 0.9340 - val_loss: 0.2219 - val_acc: 0.9424\n",
      "Epoch 457/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2588 - acc: 0.9338 - val_loss: 0.2180 - val_acc: 0.9418\n",
      "Epoch 458/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2239 - acc: 0.9338 - val_loss: 0.2316 - val_acc: 0.9375\n",
      "Epoch 459/650\n",
      "3804/3804 [==============================] - 1s 141us/step - loss: 0.2339 - acc: 0.9309 - val_loss: 0.2512 - val_acc: 0.9418\n",
      "Epoch 460/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2518 - acc: 0.9306 - val_loss: 0.2407 - val_acc: 0.9387\n",
      "Epoch 461/650\n",
      "3804/3804 [==============================] - 1s 141us/step - loss: 0.2574 - acc: 0.9267 - val_loss: 0.2391 - val_acc: 0.9338\n",
      "Epoch 462/650\n",
      "3804/3804 [==============================] - 1s 147us/step - loss: 0.2488 - acc: 0.9272 - val_loss: 0.2453 - val_acc: 0.9418\n",
      "Epoch 463/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2201 - acc: 0.9387 - val_loss: 0.2139 - val_acc: 0.9448\n",
      "Epoch 464/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2476 - acc: 0.9327 - val_loss: 0.2365 - val_acc: 0.9405\n",
      "Epoch 465/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2016 - acc: 0.9382 - val_loss: 0.2405 - val_acc: 0.9362\n",
      "Epoch 466/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2140 - acc: 0.9324 - val_loss: 0.2317 - val_acc: 0.9405\n",
      "Epoch 467/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2629 - acc: 0.9285 - val_loss: 0.2338 - val_acc: 0.9405\n",
      "Epoch 468/650\n",
      "3804/3804 [==============================] - 1s 153us/step - loss: 0.2552 - acc: 0.9267 - val_loss: 0.2392 - val_acc: 0.9350\n",
      "Epoch 469/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2587 - acc: 0.9256 - val_loss: 0.2406 - val_acc: 0.9338\n",
      "Epoch 470/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2614 - acc: 0.9280 - val_loss: 0.2430 - val_acc: 0.9393\n",
      "Epoch 471/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2370 - acc: 0.9348 - val_loss: 0.2321 - val_acc: 0.9399\n",
      "Epoch 472/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2214 - acc: 0.9380 - val_loss: 0.2270 - val_acc: 0.9442\n",
      "Epoch 473/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2332 - acc: 0.9338 - val_loss: 0.2243 - val_acc: 0.9411\n",
      "Epoch 474/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2373 - acc: 0.9343 - val_loss: 0.2266 - val_acc: 0.9375\n",
      "Epoch 475/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2570 - acc: 0.9309 - val_loss: 0.2271 - val_acc: 0.9418\n",
      "Epoch 476/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2258 - acc: 0.9338 - val_loss: 0.2158 - val_acc: 0.9491\n",
      "Epoch 477/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2492 - acc: 0.9359 - val_loss: 0.2094 - val_acc: 0.9467\n",
      "Epoch 478/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2450 - acc: 0.9351 - val_loss: 0.2041 - val_acc: 0.9430\n",
      "Epoch 479/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2688 - acc: 0.9322 - val_loss: 0.2051 - val_acc: 0.9387\n",
      "Epoch 480/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2219 - acc: 0.9377 - val_loss: 0.2157 - val_acc: 0.9430\n",
      "Epoch 481/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2248 - acc: 0.9311 - val_loss: 0.2103 - val_acc: 0.9448\n",
      "Epoch 482/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2473 - acc: 0.9332 - val_loss: 0.2175 - val_acc: 0.9411\n",
      "Epoch 483/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2250 - acc: 0.9380 - val_loss: 0.2264 - val_acc: 0.9344\n",
      "Epoch 484/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2553 - acc: 0.9309 - val_loss: 0.2326 - val_acc: 0.9387\n",
      "Epoch 485/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2109 - acc: 0.9382 - val_loss: 0.2098 - val_acc: 0.9375\n",
      "Epoch 486/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2144 - acc: 0.9406 - val_loss: 0.2259 - val_acc: 0.9405\n",
      "Epoch 487/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2723 - acc: 0.9282 - val_loss: 0.2343 - val_acc: 0.9381\n",
      "Epoch 488/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.1978 - acc: 0.9409 - val_loss: 0.2229 - val_acc: 0.9399\n",
      "Epoch 489/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2478 - acc: 0.9298 - val_loss: 0.2198 - val_acc: 0.9387\n",
      "Epoch 490/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2411 - acc: 0.9351 - val_loss: 0.2287 - val_acc: 0.9399\n",
      "Epoch 491/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2316 - acc: 0.9348 - val_loss: 0.2330 - val_acc: 0.9381\n",
      "Epoch 492/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2228 - acc: 0.9356 - val_loss: 0.2136 - val_acc: 0.9393\n",
      "Epoch 493/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2441 - acc: 0.9361 - val_loss: 0.2222 - val_acc: 0.9442\n",
      "Epoch 494/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2337 - acc: 0.9340 - val_loss: 0.2169 - val_acc: 0.9405\n",
      "Epoch 495/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2326 - acc: 0.9364 - val_loss: 0.2168 - val_acc: 0.9375\n",
      "Epoch 496/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2539 - acc: 0.9356 - val_loss: 0.2428 - val_acc: 0.9301\n",
      "Epoch 497/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2189 - acc: 0.9409 - val_loss: 0.2271 - val_acc: 0.9368\n",
      "Epoch 498/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2189 - acc: 0.9366 - val_loss: 0.2244 - val_acc: 0.9393\n",
      "Epoch 499/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2188 - acc: 0.9422 - val_loss: 0.2168 - val_acc: 0.9405\n",
      "Epoch 500/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2287 - acc: 0.9340 - val_loss: 0.2380 - val_acc: 0.9424\n",
      "Epoch 501/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2411 - acc: 0.9372 - val_loss: 0.2381 - val_acc: 0.9381\n",
      "Epoch 502/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2464 - acc: 0.9295 - val_loss: 0.2378 - val_acc: 0.9375\n",
      "Epoch 503/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2695 - acc: 0.9269 - val_loss: 0.2270 - val_acc: 0.9387\n",
      "Epoch 504/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2777 - acc: 0.9338 - val_loss: 0.2546 - val_acc: 0.9344\n",
      "Epoch 505/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2140 - acc: 0.9353 - val_loss: 0.2359 - val_acc: 0.9418\n",
      "Epoch 506/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2224 - acc: 0.9377 - val_loss: 0.2601 - val_acc: 0.9362\n",
      "Epoch 507/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2521 - acc: 0.9290 - val_loss: 0.2637 - val_acc: 0.9246\n",
      "Epoch 508/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2401 - acc: 0.9288 - val_loss: 0.2541 - val_acc: 0.9356\n",
      "Epoch 509/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2574 - acc: 0.9264 - val_loss: 0.2616 - val_acc: 0.9283\n",
      "Epoch 510/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2386 - acc: 0.9343 - val_loss: 0.2412 - val_acc: 0.9381\n",
      "Epoch 511/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2481 - acc: 0.9301 - val_loss: 0.2354 - val_acc: 0.9375\n",
      "Epoch 512/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2342 - acc: 0.9288 - val_loss: 0.2506 - val_acc: 0.9362\n",
      "Epoch 513/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2696 - acc: 0.9251 - val_loss: 0.2374 - val_acc: 0.9362\n",
      "Epoch 514/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2689 - acc: 0.9301 - val_loss: 0.2584 - val_acc: 0.9368\n",
      "Epoch 515/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2231 - acc: 0.9332 - val_loss: 0.2508 - val_acc: 0.9362\n",
      "Epoch 516/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2700 - acc: 0.9272 - val_loss: 0.2429 - val_acc: 0.9350\n",
      "Epoch 517/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2377 - acc: 0.9322 - val_loss: 0.2499 - val_acc: 0.9411\n",
      "Epoch 518/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2441 - acc: 0.9330 - val_loss: 0.2537 - val_acc: 0.9375\n",
      "Epoch 519/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2432 - acc: 0.9306 - val_loss: 0.2486 - val_acc: 0.9411\n",
      "Epoch 520/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2426 - acc: 0.9311 - val_loss: 0.2462 - val_acc: 0.9387\n",
      "Epoch 521/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2575 - acc: 0.9298 - val_loss: 0.2344 - val_acc: 0.9454\n",
      "Epoch 522/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2546 - acc: 0.9261 - val_loss: 0.2228 - val_acc: 0.9424\n",
      "Epoch 523/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2798 - acc: 0.9280 - val_loss: 0.2279 - val_acc: 0.9405\n",
      "Epoch 524/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2486 - acc: 0.9288 - val_loss: 0.2546 - val_acc: 0.9264\n",
      "Epoch 525/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2581 - acc: 0.9272 - val_loss: 0.2503 - val_acc: 0.9350\n",
      "Epoch 526/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2421 - acc: 0.9330 - val_loss: 0.2153 - val_acc: 0.9467\n",
      "Epoch 527/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2024 - acc: 0.9416 - val_loss: 0.2311 - val_acc: 0.9436\n",
      "Epoch 528/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2261 - acc: 0.9356 - val_loss: 0.2461 - val_acc: 0.9375\n",
      "Epoch 529/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2383 - acc: 0.9348 - val_loss: 0.2499 - val_acc: 0.9368\n",
      "Epoch 530/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2848 - acc: 0.9322 - val_loss: 0.2574 - val_acc: 0.9375\n",
      "Epoch 531/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2241 - acc: 0.9424 - val_loss: 0.2387 - val_acc: 0.9393\n",
      "Epoch 532/650\n",
      "3804/3804 [==============================] - 0s 130us/step - loss: 0.2257 - acc: 0.9380 - val_loss: 0.2461 - val_acc: 0.9393\n",
      "Epoch 533/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2280 - acc: 0.9369 - val_loss: 0.2750 - val_acc: 0.9332\n",
      "Epoch 534/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2238 - acc: 0.9319 - val_loss: 0.2575 - val_acc: 0.9307\n",
      "Epoch 535/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2460 - acc: 0.9327 - val_loss: 0.2444 - val_acc: 0.9418\n",
      "Epoch 536/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2238 - acc: 0.9361 - val_loss: 0.2250 - val_acc: 0.9393\n",
      "Epoch 537/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2207 - acc: 0.9393 - val_loss: 0.2476 - val_acc: 0.9387\n",
      "Epoch 538/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2402 - acc: 0.9269 - val_loss: 0.2373 - val_acc: 0.9381\n",
      "Epoch 539/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2321 - acc: 0.9377 - val_loss: 0.2461 - val_acc: 0.9313\n",
      "Epoch 540/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2403 - acc: 0.9361 - val_loss: 0.2245 - val_acc: 0.9399\n",
      "Epoch 541/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2127 - acc: 0.9385 - val_loss: 0.2324 - val_acc: 0.9387\n",
      "Epoch 542/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2489 - acc: 0.9338 - val_loss: 0.2614 - val_acc: 0.9350\n",
      "Epoch 543/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2381 - acc: 0.9261 - val_loss: 0.2363 - val_acc: 0.9375\n",
      "Epoch 544/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2717 - acc: 0.9274 - val_loss: 0.2438 - val_acc: 0.9393\n",
      "Epoch 545/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2194 - acc: 0.9356 - val_loss: 0.2305 - val_acc: 0.9375\n",
      "Epoch 546/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2344 - acc: 0.9374 - val_loss: 0.2531 - val_acc: 0.9332\n",
      "Epoch 547/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2238 - acc: 0.9290 - val_loss: 0.2539 - val_acc: 0.9375\n",
      "Epoch 548/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.1922 - acc: 0.9409 - val_loss: 0.2437 - val_acc: 0.9362\n",
      "Epoch 549/650\n",
      "3804/3804 [==============================] - 1s 142us/step - loss: 0.2091 - acc: 0.9427 - val_loss: 0.2468 - val_acc: 0.9393\n",
      "Epoch 550/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2311 - acc: 0.9348 - val_loss: 0.2322 - val_acc: 0.9430\n",
      "Epoch 551/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2147 - acc: 0.9324 - val_loss: 0.2424 - val_acc: 0.9430\n",
      "Epoch 552/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2335 - acc: 0.9303 - val_loss: 0.2653 - val_acc: 0.9405\n",
      "Epoch 553/650\n",
      "3804/3804 [==============================] - 0s 131us/step - loss: 0.2307 - acc: 0.9351 - val_loss: 0.2807 - val_acc: 0.9387\n",
      "Epoch 554/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2136 - acc: 0.9390 - val_loss: 0.2392 - val_acc: 0.9332\n",
      "Epoch 555/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2386 - acc: 0.9309 - val_loss: 0.2263 - val_acc: 0.9375\n",
      "Epoch 556/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2466 - acc: 0.9288 - val_loss: 0.2425 - val_acc: 0.9381\n",
      "Epoch 557/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2402 - acc: 0.9366 - val_loss: 0.2547 - val_acc: 0.9356\n",
      "Epoch 558/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2388 - acc: 0.9356 - val_loss: 0.2504 - val_acc: 0.9362\n",
      "Epoch 559/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2617 - acc: 0.9309 - val_loss: 0.2422 - val_acc: 0.9430\n",
      "Epoch 560/650\n",
      "3804/3804 [==============================] - 1s 149us/step - loss: 0.2467 - acc: 0.9353 - val_loss: 0.2557 - val_acc: 0.9307\n",
      "Epoch 561/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2632 - acc: 0.9319 - val_loss: 0.2531 - val_acc: 0.9393\n",
      "Epoch 562/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2104 - acc: 0.9393 - val_loss: 0.2372 - val_acc: 0.9418\n",
      "Epoch 563/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.1905 - acc: 0.9414 - val_loss: 0.2370 - val_acc: 0.9442\n",
      "Epoch 564/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.1979 - acc: 0.9432 - val_loss: 0.2463 - val_acc: 0.9393\n",
      "Epoch 565/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2531 - acc: 0.9317 - val_loss: 0.2380 - val_acc: 0.9387\n",
      "Epoch 566/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2633 - acc: 0.9309 - val_loss: 0.2265 - val_acc: 0.9405\n",
      "Epoch 567/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2246 - acc: 0.9330 - val_loss: 0.2401 - val_acc: 0.9381\n",
      "Epoch 568/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2163 - acc: 0.9409 - val_loss: 0.2337 - val_acc: 0.9381\n",
      "Epoch 569/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2117 - acc: 0.9411 - val_loss: 0.2247 - val_acc: 0.9430\n",
      "Epoch 570/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2212 - acc: 0.9382 - val_loss: 0.2247 - val_acc: 0.9356\n",
      "Epoch 571/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2165 - acc: 0.9406 - val_loss: 0.2503 - val_acc: 0.9344\n",
      "Epoch 572/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2370 - acc: 0.9327 - val_loss: 0.2533 - val_acc: 0.9362\n",
      "Epoch 573/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2248 - acc: 0.9393 - val_loss: 0.2232 - val_acc: 0.9460\n",
      "Epoch 574/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2484 - acc: 0.9282 - val_loss: 0.2563 - val_acc: 0.9399\n",
      "Epoch 575/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2349 - acc: 0.9374 - val_loss: 0.2672 - val_acc: 0.9356\n",
      "Epoch 576/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2393 - acc: 0.9374 - val_loss: 0.2596 - val_acc: 0.9368\n",
      "Epoch 577/650\n",
      "3804/3804 [==============================] - 1s 144us/step - loss: 0.2077 - acc: 0.9398 - val_loss: 0.2731 - val_acc: 0.9350\n",
      "Epoch 578/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2369 - acc: 0.9348 - val_loss: 0.2739 - val_acc: 0.9313\n",
      "Epoch 579/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2714 - acc: 0.9293 - val_loss: 0.2625 - val_acc: 0.9350\n",
      "Epoch 580/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2415 - acc: 0.9322 - val_loss: 0.2915 - val_acc: 0.9344\n",
      "Epoch 581/650\n",
      "3804/3804 [==============================] - 1s 141us/step - loss: 0.2425 - acc: 0.9295 - val_loss: 0.2664 - val_acc: 0.9326\n",
      "Epoch 582/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2389 - acc: 0.9353 - val_loss: 0.2502 - val_acc: 0.9344\n",
      "Epoch 583/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2334 - acc: 0.9414 - val_loss: 0.2627 - val_acc: 0.9418\n",
      "Epoch 584/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2320 - acc: 0.9372 - val_loss: 0.2435 - val_acc: 0.9375\n",
      "Epoch 585/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2361 - acc: 0.9411 - val_loss: 0.2442 - val_acc: 0.9332\n",
      "Epoch 586/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2155 - acc: 0.9387 - val_loss: 0.2336 - val_acc: 0.9375\n",
      "Epoch 587/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2207 - acc: 0.9332 - val_loss: 0.2519 - val_acc: 0.9338\n",
      "Epoch 588/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2274 - acc: 0.9330 - val_loss: 0.2367 - val_acc: 0.9338\n",
      "Epoch 589/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2104 - acc: 0.9369 - val_loss: 0.2393 - val_acc: 0.9393\n",
      "Epoch 590/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2406 - acc: 0.9303 - val_loss: 0.2503 - val_acc: 0.9387\n",
      "Epoch 591/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2529 - acc: 0.9338 - val_loss: 0.2629 - val_acc: 0.9356\n",
      "Epoch 592/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2323 - acc: 0.9364 - val_loss: 0.2373 - val_acc: 0.9350\n",
      "Epoch 593/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2004 - acc: 0.9380 - val_loss: 0.2489 - val_acc: 0.9356\n",
      "Epoch 594/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2155 - acc: 0.9422 - val_loss: 0.2826 - val_acc: 0.9344\n",
      "Epoch 595/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.1993 - acc: 0.9469 - val_loss: 0.2877 - val_acc: 0.9411\n",
      "Epoch 596/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2522 - acc: 0.9324 - val_loss: 0.2738 - val_acc: 0.9350\n",
      "Epoch 597/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2474 - acc: 0.9369 - val_loss: 0.2675 - val_acc: 0.9460\n",
      "Epoch 598/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.1949 - acc: 0.9419 - val_loss: 0.2687 - val_acc: 0.9393\n",
      "Epoch 599/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2255 - acc: 0.9414 - val_loss: 0.2765 - val_acc: 0.9368\n",
      "Epoch 600/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2391 - acc: 0.9348 - val_loss: 0.2890 - val_acc: 0.9295\n",
      "Epoch 601/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2413 - acc: 0.9301 - val_loss: 0.2815 - val_acc: 0.9350\n",
      "Epoch 602/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2188 - acc: 0.9390 - val_loss: 0.2787 - val_acc: 0.9375\n",
      "Epoch 603/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2202 - acc: 0.9369 - val_loss: 0.2686 - val_acc: 0.9393\n",
      "Epoch 604/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2460 - acc: 0.9351 - val_loss: 0.2948 - val_acc: 0.9326\n",
      "Epoch 605/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2090 - acc: 0.9364 - val_loss: 0.2756 - val_acc: 0.9240\n",
      "Epoch 606/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2734 - acc: 0.9251 - val_loss: 0.2385 - val_acc: 0.9411\n",
      "Epoch 607/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2161 - acc: 0.9409 - val_loss: 0.2557 - val_acc: 0.9411\n",
      "Epoch 608/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2309 - acc: 0.9356 - val_loss: 0.2713 - val_acc: 0.9338\n",
      "Epoch 609/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2327 - acc: 0.9403 - val_loss: 0.2764 - val_acc: 0.9344\n",
      "Epoch 610/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2140 - acc: 0.9406 - val_loss: 0.2608 - val_acc: 0.9338\n",
      "Epoch 611/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2388 - acc: 0.9351 - val_loss: 0.2665 - val_acc: 0.9350\n",
      "Epoch 612/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.1879 - acc: 0.9422 - val_loss: 0.2420 - val_acc: 0.9368\n",
      "Epoch 613/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2475 - acc: 0.9327 - val_loss: 0.2522 - val_acc: 0.9405\n",
      "Epoch 614/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2126 - acc: 0.9422 - val_loss: 0.2495 - val_acc: 0.9356\n",
      "Epoch 615/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2341 - acc: 0.9327 - val_loss: 0.2545 - val_acc: 0.9411\n",
      "Epoch 616/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2443 - acc: 0.9311 - val_loss: 0.2441 - val_acc: 0.9418\n",
      "Epoch 617/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2234 - acc: 0.9361 - val_loss: 0.2620 - val_acc: 0.9405\n",
      "Epoch 618/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2186 - acc: 0.9369 - val_loss: 0.2562 - val_acc: 0.9393\n",
      "Epoch 619/650\n",
      "3804/3804 [==============================] - 1s 132us/step - loss: 0.2082 - acc: 0.9437 - val_loss: 0.2409 - val_acc: 0.9479\n",
      "Epoch 620/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2414 - acc: 0.9385 - val_loss: 0.2619 - val_acc: 0.9393\n",
      "Epoch 621/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2374 - acc: 0.9401 - val_loss: 0.2481 - val_acc: 0.9411\n",
      "Epoch 622/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2475 - acc: 0.9340 - val_loss: 0.2556 - val_acc: 0.9362\n",
      "Epoch 623/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2155 - acc: 0.9330 - val_loss: 0.2312 - val_acc: 0.9387\n",
      "Epoch 624/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2698 - acc: 0.9285 - val_loss: 0.2748 - val_acc: 0.9332\n",
      "Epoch 625/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2542 - acc: 0.9356 - val_loss: 0.2454 - val_acc: 0.9344\n",
      "Epoch 626/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2186 - acc: 0.9387 - val_loss: 0.2454 - val_acc: 0.9375\n",
      "Epoch 627/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2135 - acc: 0.9416 - val_loss: 0.2366 - val_acc: 0.9399\n",
      "Epoch 628/650\n",
      "3804/3804 [==============================] - 1s 141us/step - loss: 0.2403 - acc: 0.9353 - val_loss: 0.2620 - val_acc: 0.9307\n",
      "Epoch 629/650\n",
      "3804/3804 [==============================] - 1s 137us/step - loss: 0.2409 - acc: 0.9311 - val_loss: 0.2504 - val_acc: 0.9332\n",
      "Epoch 630/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2416 - acc: 0.9301 - val_loss: 0.2492 - val_acc: 0.9326\n",
      "Epoch 631/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2192 - acc: 0.9364 - val_loss: 0.2623 - val_acc: 0.9350\n",
      "Epoch 632/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2452 - acc: 0.9359 - val_loss: 0.2380 - val_acc: 0.9338\n",
      "Epoch 633/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2194 - acc: 0.9382 - val_loss: 0.2425 - val_acc: 0.9326\n",
      "Epoch 634/650\n",
      "3804/3804 [==============================] - 1s 136us/step - loss: 0.2625 - acc: 0.9274 - val_loss: 0.2439 - val_acc: 0.9332\n",
      "Epoch 635/650\n",
      "3804/3804 [==============================] - 1s 135us/step - loss: 0.2706 - acc: 0.9293 - val_loss: 0.2465 - val_acc: 0.9405\n",
      "Epoch 636/650\n",
      "3804/3804 [==============================] - 1s 133us/step - loss: 0.2523 - acc: 0.9332 - val_loss: 0.2510 - val_acc: 0.9387\n",
      "Epoch 637/650\n",
      "3804/3804 [==============================] - 1s 141us/step - loss: 0.2334 - acc: 0.9314 - val_loss: 0.2304 - val_acc: 0.9387\n",
      "Epoch 638/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2184 - acc: 0.9430 - val_loss: 0.2279 - val_acc: 0.9399\n",
      "Epoch 639/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2084 - acc: 0.9479 - val_loss: 0.2303 - val_acc: 0.9375\n",
      "Epoch 640/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2152 - acc: 0.9401 - val_loss: 0.2386 - val_acc: 0.9362\n",
      "Epoch 641/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2093 - acc: 0.9385 - val_loss: 0.2626 - val_acc: 0.9319\n",
      "Epoch 642/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2298 - acc: 0.9353 - val_loss: 0.2661 - val_acc: 0.9362\n",
      "Epoch 643/650\n",
      "3804/3804 [==============================] - 1s 134us/step - loss: 0.2197 - acc: 0.9343 - val_loss: 0.2425 - val_acc: 0.9356\n",
      "Epoch 644/650\n",
      "3804/3804 [==============================] - 1s 138us/step - loss: 0.2189 - acc: 0.9390 - val_loss: 0.2433 - val_acc: 0.9405\n",
      "Epoch 645/650\n",
      "3804/3804 [==============================] - 1s 142us/step - loss: 0.2265 - acc: 0.9353 - val_loss: 0.2552 - val_acc: 0.9326\n",
      "Epoch 646/650\n",
      "3804/3804 [==============================] - 1s 139us/step - loss: 0.2222 - acc: 0.9369 - val_loss: 0.2544 - val_acc: 0.9375\n",
      "Epoch 647/650\n",
      "3804/3804 [==============================] - 1s 155us/step - loss: 0.2252 - acc: 0.9369 - val_loss: 0.2682 - val_acc: 0.9338\n",
      "Epoch 648/650\n",
      "3804/3804 [==============================] - 1s 140us/step - loss: 0.2487 - acc: 0.9393 - val_loss: 0.2508 - val_acc: 0.9399\n",
      "Epoch 649/650\n",
      "3804/3804 [==============================] - 1s 157us/step - loss: 0.2323 - acc: 0.9377 - val_loss: 0.2586 - val_acc: 0.9375\n",
      "Epoch 650/650\n",
      "3804/3804 [==============================] - 1s 175us/step - loss: 0.2353 - acc: 0.9351 - val_loss: 0.2469 - val_acc: 0.9368\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x7fe5be6eec88>"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# training the data\n",
    "model.fit(x_train,y_train, batch_size=32, epochs=650, validation_data=(x_test, y_test))"
   ]
  }
 ],
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