code_15_stability_of_decision_tree.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n",
      "/home/huz/miniconda3/envs/CyTOF_DL/lib/python3.7/site-packages/sklearn/externals/six.py:31: FutureWarning: The module is deprecated in version 0.21 and will be removed in version 0.23 since we've dropped support for Python 2.7. Please rely on the official version of six (https://pypi.org/project/six/).\n",
      "  \"(https://pypi.org/project/six/).\", FutureWarning)\n"
     ]
    }
   ],
   "source": [
    "from __future__ import print_function\n",
    "import os; os.environ['KERAS_BACKEND'] = 'tensorflow'\n",
    "import keras\n",
    "from keras.datasets import mnist\n",
    "from keras.models import Sequential\n",
    "from keras.layers import Dense, Dropout, Flatten, BatchNormalization, Activation, Concatenate\n",
    "from keras.layers import Conv2D, MaxPooling2D, AveragePooling2D, Input\n",
    "from keras import backend as K\n",
    "from keras.models import load_model\n",
    "import pickle\n",
    "import pandas as pd\n",
    "import re\n",
    "import numpy as np\n",
    "import random\n",
    "from keras.utils.vis_utils import plot_model\n",
    "import keras.callbacks\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.manifold import TSNE\n",
    "from sklearn import datasets, linear_model\n",
    "import seaborn as sns\n",
    "import pydotplus\n",
    "#from numpy.random import seed; seed(123)\n",
    "#import tensorflow as tf; tf.random.set_seed(123)\n",
    "from sklearn.metrics import roc_auc_score\n",
    "from statsmodels.formula.api import ols\n",
    "from statsmodels.stats.anova import anova_lm\n",
    "from scipy.stats import kruskal\n",
    "from scipy.stats import ttest_ind\n",
    "from sklearn.tree import DecisionTreeRegressor\n",
    "from sklearn.model_selection import cross_validate\n",
    "from sklearn.externals.six import StringIO  \n",
    "from sklearn.tree import export_graphviz, DecisionTreeRegressor\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(532, 10000, 27, 1)\n"
     ]
    }
   ],
   "source": [
    "##### load data #####\n",
    "processed_data = pickle.load( open( \"result_04_processed_data_no_scale_Final.obj\", \"rb\" ) )\n",
    "cytof_files = processed_data[\"cytof_files\"]\n",
    "cytof_files.to_csv(\"result_05_cytof_files.csv\")\n",
    "expr_list = processed_data[\"expr_list\"]\n",
    "markerNames = processed_data[\"marker_names\"]\n",
    "\n",
    "r1 = [t1==t1 for t1 in cytof_files.CMV_Ab] \n",
    "cytof_files = cytof_files.loc[r1,:]\n",
    "expr_list = expr_list[r1]\n",
    "print(expr_list.shape)\n",
    "\n",
    "y = cytof_files.CMV_Ab.values> 2\n",
    "x = expr_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "##### split train, validation and test######\n",
    "\n",
    "train_id = [i for i in range(len(x)) if cytof_files.study_accession.iloc[i] not in [\"SDY515\",\"SDY519\"]]\n",
    "valid_id = [i for i in range(len(x)) if cytof_files.study_accession.iloc[i]==\"SDY515\"]\n",
    "test_id = [i for i in range(len(x)) if cytof_files.study_accession.iloc[i]==\"SDY519\"]\n",
    "\n",
    "x_train = x[train_id]\n",
    "x_valid = x[valid_id]\n",
    "x_test = x[test_id]\n",
    "\n",
    "y_train = y[train_id]\n",
    "y_valid = y[valid_id]\n",
    "y_test = y[test_id]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "##### define model #####\n",
    "model_input = Input(shape=x_train[0].shape)\n",
    "model_output = Conv2D(3, kernel_size=(1, x_train.shape[2]),\n",
    "                 activation=None)(model_input)\n",
    "model_output = BatchNormalization()(model_output)\n",
    "model_output = Activation(\"relu\")(model_output)\n",
    "#model_output = Dropout(0.3)(model_output)\n",
    "\n",
    "model_output = Conv2D(3, (1, 1), activation=None)(model_output)\n",
    "model_output = BatchNormalization()(model_output)\n",
    "model_output = Activation(\"relu\")(model_output)\n",
    "\n",
    "model_output = AveragePooling2D(pool_size=(10000, 1))(model_output)\n",
    "model_output = Flatten()(model_output)\n",
    "\n",
    "model_output = Dense(3, activation=None)(model_output)\n",
    "model_output = BatchNormalization()(model_output)\n",
    "model_output = Activation(\"relu\")(model_output)\n",
    "model_output = Dense(1, activation=None)(model_output)\n",
    "model_output = BatchNormalization()(model_output)\n",
    "model_output = Activation(\"sigmoid\")(model_output)\n",
    "\n",
    "\n",
    "earlyStop = keras.callbacks.EarlyStopping(monitor='loss', min_delta=0.0001, patience=100, \n",
    "                                          verbose=0, mode='auto', baseline=None, restore_best_weights=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 341 samples, validate on 71 samples\n",
      "Epoch 1/10000\n",
      "341/341 [==============================] - 3s 7ms/step - loss: 0.8242 - accuracy: 0.4751 - val_loss: 0.7725 - val_accuracy: 0.4648\n",
      "Epoch 2/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8223 - accuracy: 0.4751 - val_loss: 0.7607 - val_accuracy: 0.4648\n",
      "Epoch 3/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8205 - accuracy: 0.4428 - val_loss: 0.7496 - val_accuracy: 0.4648\n",
      "Epoch 4/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8205 - accuracy: 0.4575 - val_loss: 0.7389 - val_accuracy: 0.4648\n",
      "Epoch 5/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8345 - accuracy: 0.4633 - val_loss: 0.7290 - val_accuracy: 0.4648\n",
      "Epoch 6/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8292 - accuracy: 0.4457 - val_loss: 0.7198 - val_accuracy: 0.4648\n",
      "Epoch 7/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8094 - accuracy: 0.5015 - val_loss: 0.7114 - val_accuracy: 0.4648\n",
      "Epoch 8/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8142 - accuracy: 0.4868 - val_loss: 0.7038 - val_accuracy: 0.4648\n",
      "Epoch 9/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8085 - accuracy: 0.5015 - val_loss: 0.6969 - val_accuracy: 0.4648\n",
      "Epoch 10/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8189 - accuracy: 0.4985 - val_loss: 0.6906 - val_accuracy: 0.4789\n",
      "Epoch 11/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8202 - accuracy: 0.4839 - val_loss: 0.6852 - val_accuracy: 0.5070\n",
      "Epoch 12/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8176 - accuracy: 0.4897 - val_loss: 0.6803 - val_accuracy: 0.5634\n",
      "Epoch 13/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8108 - accuracy: 0.5044 - val_loss: 0.6759 - val_accuracy: 0.6197\n",
      "Epoch 14/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.8113 - accuracy: 0.4868 - val_loss: 0.6722 - val_accuracy: 0.5915\n",
      "Epoch 15/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.8069 - accuracy: 0.4839 - val_loss: 0.6690 - val_accuracy: 0.5915\n",
      "Epoch 16/10000\n",
      "341/341 [==============================] - 2s 5ms/step - loss: 0.8027 - accuracy: 0.4809 - val_loss: 0.6664 - val_accuracy: 0.6338\n",
      "Epoch 17/10000\n",
      "341/341 [==============================] - 2s 5ms/step - loss: 0.8111 - accuracy: 0.4839 - val_loss: 0.6643 - val_accuracy: 0.6197\n",
      "Epoch 18/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.8031 - accuracy: 0.5015 - val_loss: 0.6627 - val_accuracy: 0.6479\n",
      "Epoch 19/10000\n",
      "341/341 [==============================] - 2s 5ms/step - loss: 0.8049 - accuracy: 0.4839 - val_loss: 0.6618 - val_accuracy: 0.6479\n",
      "Epoch 20/10000\n",
      "341/341 [==============================] - 2s 5ms/step - loss: 0.8098 - accuracy: 0.4985 - val_loss: 0.6618 - val_accuracy: 0.6197\n",
      "Epoch 21/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7995 - accuracy: 0.4897 - val_loss: 0.6630 - val_accuracy: 0.5915\n",
      "Epoch 22/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8129 - accuracy: 0.4751 - val_loss: 0.6643 - val_accuracy: 0.5915\n",
      "Epoch 23/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7979 - accuracy: 0.4927 - val_loss: 0.6658 - val_accuracy: 0.6056\n",
      "Epoch 24/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8126 - accuracy: 0.4985 - val_loss: 0.6678 - val_accuracy: 0.5775\n",
      "Epoch 25/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8155 - accuracy: 0.4809 - val_loss: 0.6705 - val_accuracy: 0.5634\n",
      "Epoch 26/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8100 - accuracy: 0.4809 - val_loss: 0.6743 - val_accuracy: 0.5634\n",
      "Epoch 27/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7926 - accuracy: 0.5132 - val_loss: 0.6788 - val_accuracy: 0.5634\n",
      "Epoch 28/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.7898 - accuracy: 0.5044 - val_loss: 0.6836 - val_accuracy: 0.5493\n",
      "Epoch 29/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7892 - accuracy: 0.5015 - val_loss: 0.6890 - val_accuracy: 0.5352\n",
      "Epoch 30/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8058 - accuracy: 0.4839 - val_loss: 0.6940 - val_accuracy: 0.5352\n",
      "Epoch 31/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8129 - accuracy: 0.4751 - val_loss: 0.6988 - val_accuracy: 0.5070\n",
      "Epoch 32/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7936 - accuracy: 0.4927 - val_loss: 0.7035 - val_accuracy: 0.5070\n",
      "Epoch 33/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7953 - accuracy: 0.4897 - val_loss: 0.7082 - val_accuracy: 0.5070\n",
      "Epoch 34/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7963 - accuracy: 0.5337 - val_loss: 0.7128 - val_accuracy: 0.5211\n",
      "Epoch 35/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7916 - accuracy: 0.4927 - val_loss: 0.7169 - val_accuracy: 0.5211\n",
      "Epoch 36/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8001 - accuracy: 0.4897 - val_loss: 0.7206 - val_accuracy: 0.5352\n",
      "Epoch 37/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8048 - accuracy: 0.4897 - val_loss: 0.7250 - val_accuracy: 0.5211\n",
      "Epoch 38/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7865 - accuracy: 0.4927 - val_loss: 0.7297 - val_accuracy: 0.4930\n",
      "Epoch 39/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.8111 - accuracy: 0.4868 - val_loss: 0.7343 - val_accuracy: 0.4930\n",
      "Epoch 40/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7972 - accuracy: 0.4927 - val_loss: 0.7391 - val_accuracy: 0.4789\n",
      "Epoch 41/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7979 - accuracy: 0.5044 - val_loss: 0.7440 - val_accuracy: 0.4648\n",
      "Epoch 42/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7981 - accuracy: 0.4927 - val_loss: 0.7482 - val_accuracy: 0.4789\n",
      "Epoch 43/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7856 - accuracy: 0.5015 - val_loss: 0.7521 - val_accuracy: 0.4507\n",
      "Epoch 44/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7968 - accuracy: 0.5132 - val_loss: 0.7565 - val_accuracy: 0.4366\n",
      "Epoch 45/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7987 - accuracy: 0.4985 - val_loss: 0.7607 - val_accuracy: 0.4366\n",
      "Epoch 46/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7979 - accuracy: 0.4956 - val_loss: 0.7645 - val_accuracy: 0.4225\n",
      "Epoch 47/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7967 - accuracy: 0.5044 - val_loss: 0.7688 - val_accuracy: 0.3944\n",
      "Epoch 48/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7923 - accuracy: 0.5015 - val_loss: 0.7735 - val_accuracy: 0.3803\n",
      "Epoch 49/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7918 - accuracy: 0.5308 - val_loss: 0.7784 - val_accuracy: 0.4085\n",
      "Epoch 50/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7954 - accuracy: 0.4985 - val_loss: 0.7838 - val_accuracy: 0.4085\n",
      "Epoch 51/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7825 - accuracy: 0.5132 - val_loss: 0.7896 - val_accuracy: 0.4085\n",
      "Epoch 52/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7831 - accuracy: 0.5161 - val_loss: 0.7951 - val_accuracy: 0.4085\n",
      "Epoch 53/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7783 - accuracy: 0.5220 - val_loss: 0.8014 - val_accuracy: 0.3944\n",
      "Epoch 54/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7933 - accuracy: 0.5073 - val_loss: 0.8078 - val_accuracy: 0.3944\n",
      "Epoch 55/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7857 - accuracy: 0.5073 - val_loss: 0.8142 - val_accuracy: 0.4225\n",
      "Epoch 56/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7897 - accuracy: 0.5103 - val_loss: 0.8209 - val_accuracy: 0.4225\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 57/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7702 - accuracy: 0.5308 - val_loss: 0.8277 - val_accuracy: 0.4366\n",
      "Epoch 58/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7759 - accuracy: 0.5308 - val_loss: 0.8349 - val_accuracy: 0.4366\n",
      "Epoch 59/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7789 - accuracy: 0.4985 - val_loss: 0.8421 - val_accuracy: 0.4085\n",
      "Epoch 60/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7848 - accuracy: 0.5220 - val_loss: 0.8494 - val_accuracy: 0.4225\n",
      "Epoch 61/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7714 - accuracy: 0.5308 - val_loss: 0.8569 - val_accuracy: 0.4366\n",
      "Epoch 62/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7840 - accuracy: 0.5220 - val_loss: 0.8642 - val_accuracy: 0.4366\n",
      "Epoch 63/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7821 - accuracy: 0.5308 - val_loss: 0.8718 - val_accuracy: 0.4366\n",
      "Epoch 64/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7756 - accuracy: 0.5103 - val_loss: 0.8795 - val_accuracy: 0.4366\n",
      "Epoch 65/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7773 - accuracy: 0.5073 - val_loss: 0.8871 - val_accuracy: 0.4507\n",
      "Epoch 66/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7833 - accuracy: 0.5220 - val_loss: 0.8934 - val_accuracy: 0.4507\n",
      "Epoch 67/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7767 - accuracy: 0.5161 - val_loss: 0.9006 - val_accuracy: 0.4507\n",
      "Epoch 68/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7710 - accuracy: 0.5103 - val_loss: 0.9083 - val_accuracy: 0.4507\n",
      "Epoch 69/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7746 - accuracy: 0.4868 - val_loss: 0.9146 - val_accuracy: 0.4648\n",
      "Epoch 70/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7832 - accuracy: 0.4985 - val_loss: 0.9214 - val_accuracy: 0.4366\n",
      "Epoch 71/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7810 - accuracy: 0.5132 - val_loss: 0.9284 - val_accuracy: 0.4366\n",
      "Epoch 72/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7903 - accuracy: 0.5161 - val_loss: 0.9349 - val_accuracy: 0.4507\n",
      "Epoch 73/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7687 - accuracy: 0.5425 - val_loss: 0.9421 - val_accuracy: 0.4507\n",
      "Epoch 74/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7790 - accuracy: 0.5161 - val_loss: 0.9482 - val_accuracy: 0.4507\n",
      "Epoch 75/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7719 - accuracy: 0.5367 - val_loss: 0.9552 - val_accuracy: 0.4507\n",
      "Epoch 76/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7655 - accuracy: 0.5220 - val_loss: 0.9617 - val_accuracy: 0.4648\n",
      "Epoch 77/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7742 - accuracy: 0.5044 - val_loss: 0.9674 - val_accuracy: 0.4648\n",
      "Epoch 78/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7732 - accuracy: 0.5220 - val_loss: 0.9735 - val_accuracy: 0.4648\n",
      "Epoch 79/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7794 - accuracy: 0.5132 - val_loss: 0.9787 - val_accuracy: 0.4789\n",
      "Epoch 80/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7819 - accuracy: 0.5132 - val_loss: 0.9828 - val_accuracy: 0.4789\n",
      "Epoch 81/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7748 - accuracy: 0.5396 - val_loss: 0.9878 - val_accuracy: 0.4789\n",
      "Epoch 82/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7626 - accuracy: 0.5337 - val_loss: 0.9925 - val_accuracy: 0.4789\n",
      "Epoch 83/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7663 - accuracy: 0.5132 - val_loss: 0.9976 - val_accuracy: 0.4930\n",
      "Epoch 84/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7677 - accuracy: 0.5337 - val_loss: 1.0017 - val_accuracy: 0.4930\n",
      "Epoch 85/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7773 - accuracy: 0.5191 - val_loss: 1.0055 - val_accuracy: 0.4930\n",
      "Epoch 86/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7634 - accuracy: 0.5279 - val_loss: 1.0103 - val_accuracy: 0.4930\n",
      "Epoch 87/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7721 - accuracy: 0.5279 - val_loss: 1.0151 - val_accuracy: 0.4930\n",
      "Epoch 88/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7678 - accuracy: 0.5249 - val_loss: 1.0200 - val_accuracy: 0.4789\n",
      "Epoch 89/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7697 - accuracy: 0.5396 - val_loss: 1.0241 - val_accuracy: 0.4930\n",
      "Epoch 90/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7686 - accuracy: 0.5132 - val_loss: 1.0271 - val_accuracy: 0.4930\n",
      "Epoch 91/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7690 - accuracy: 0.5249 - val_loss: 1.0314 - val_accuracy: 0.4930\n",
      "Epoch 92/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7647 - accuracy: 0.5279 - val_loss: 1.0340 - val_accuracy: 0.4930\n",
      "Epoch 93/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7530 - accuracy: 0.5484 - val_loss: 1.0375 - val_accuracy: 0.4930\n",
      "Epoch 94/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7635 - accuracy: 0.5220 - val_loss: 1.0411 - val_accuracy: 0.4930\n",
      "Epoch 95/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7611 - accuracy: 0.5279 - val_loss: 1.0443 - val_accuracy: 0.4930\n",
      "Epoch 96/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7678 - accuracy: 0.5367 - val_loss: 1.0489 - val_accuracy: 0.4930\n",
      "Epoch 97/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7673 - accuracy: 0.5220 - val_loss: 1.0528 - val_accuracy: 0.4930\n",
      "Epoch 98/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7625 - accuracy: 0.5337 - val_loss: 1.0573 - val_accuracy: 0.4930\n",
      "Epoch 99/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.7630 - accuracy: 0.5455 - val_loss: 1.0609 - val_accuracy: 0.4930\n",
      "Epoch 100/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7483 - accuracy: 0.5161 - val_loss: 1.0626 - val_accuracy: 0.4930\n",
      "Epoch 101/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7546 - accuracy: 0.5367 - val_loss: 1.0647 - val_accuracy: 0.4930\n",
      "Epoch 102/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7559 - accuracy: 0.5337 - val_loss: 1.0677 - val_accuracy: 0.4930\n",
      "Epoch 103/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7501 - accuracy: 0.5367 - val_loss: 1.0701 - val_accuracy: 0.4789\n",
      "Epoch 104/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7605 - accuracy: 0.5337 - val_loss: 1.0728 - val_accuracy: 0.4789\n",
      "Epoch 105/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7519 - accuracy: 0.5396 - val_loss: 1.0745 - val_accuracy: 0.4789\n",
      "Epoch 106/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7533 - accuracy: 0.5337 - val_loss: 1.0768 - val_accuracy: 0.4789\n",
      "Epoch 107/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7432 - accuracy: 0.5337 - val_loss: 1.0766 - val_accuracy: 0.4789\n",
      "Epoch 108/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7452 - accuracy: 0.5337 - val_loss: 1.0798 - val_accuracy: 0.4789\n",
      "Epoch 109/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7492 - accuracy: 0.5425 - val_loss: 1.0834 - val_accuracy: 0.4930\n",
      "Epoch 110/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7484 - accuracy: 0.5425 - val_loss: 1.0845 - val_accuracy: 0.4930\n",
      "Epoch 111/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7575 - accuracy: 0.5396 - val_loss: 1.0854 - val_accuracy: 0.4930\n",
      "Epoch 112/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7563 - accuracy: 0.5337 - val_loss: 1.0858 - val_accuracy: 0.4930\n",
      "Epoch 113/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7477 - accuracy: 0.5308 - val_loss: 1.0856 - val_accuracy: 0.4930\n",
      "Epoch 114/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7507 - accuracy: 0.5308 - val_loss: 1.0865 - val_accuracy: 0.4930\n",
      "Epoch 115/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7488 - accuracy: 0.5396 - val_loss: 1.0873 - val_accuracy: 0.4930\n",
      "Epoch 116/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7412 - accuracy: 0.5572 - val_loss: 1.0892 - val_accuracy: 0.4930\n",
      "Epoch 117/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7540 - accuracy: 0.5543 - val_loss: 1.0897 - val_accuracy: 0.5070\n",
      "Epoch 118/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7386 - accuracy: 0.5689 - val_loss: 1.0919 - val_accuracy: 0.5070\n",
      "Epoch 119/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7468 - accuracy: 0.5484 - val_loss: 1.0933 - val_accuracy: 0.5070\n",
      "Epoch 120/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7499 - accuracy: 0.5279 - val_loss: 1.0964 - val_accuracy: 0.5070\n",
      "Epoch 121/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7386 - accuracy: 0.5337 - val_loss: 1.0998 - val_accuracy: 0.4930\n",
      "Epoch 122/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7558 - accuracy: 0.5455 - val_loss: 1.1025 - val_accuracy: 0.4930\n",
      "Epoch 123/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7377 - accuracy: 0.5455 - val_loss: 1.1044 - val_accuracy: 0.5070\n",
      "Epoch 124/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7385 - accuracy: 0.5484 - val_loss: 1.1052 - val_accuracy: 0.5070\n",
      "Epoch 125/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7335 - accuracy: 0.5455 - val_loss: 1.1059 - val_accuracy: 0.5070\n",
      "Epoch 126/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7381 - accuracy: 0.5367 - val_loss: 1.1071 - val_accuracy: 0.5070\n",
      "Epoch 127/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7386 - accuracy: 0.5367 - val_loss: 1.1075 - val_accuracy: 0.5070\n",
      "Epoch 128/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7301 - accuracy: 0.5601 - val_loss: 1.1081 - val_accuracy: 0.5070\n",
      "Epoch 129/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7441 - accuracy: 0.5367 - val_loss: 1.1089 - val_accuracy: 0.5070\n",
      "Epoch 130/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7455 - accuracy: 0.5367 - val_loss: 1.1104 - val_accuracy: 0.5070\n",
      "Epoch 131/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7463 - accuracy: 0.5630 - val_loss: 1.1112 - val_accuracy: 0.5070\n",
      "Epoch 132/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7417 - accuracy: 0.5572 - val_loss: 1.1131 - val_accuracy: 0.5070\n",
      "Epoch 133/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7376 - accuracy: 0.5425 - val_loss: 1.1144 - val_accuracy: 0.5070\n",
      "Epoch 134/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7426 - accuracy: 0.5601 - val_loss: 1.1154 - val_accuracy: 0.5070\n",
      "Epoch 135/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7313 - accuracy: 0.5572 - val_loss: 1.1155 - val_accuracy: 0.5070\n",
      "Epoch 136/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7352 - accuracy: 0.5425 - val_loss: 1.1173 - val_accuracy: 0.5070\n",
      "Epoch 137/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7379 - accuracy: 0.5425 - val_loss: 1.1199 - val_accuracy: 0.5070\n",
      "Epoch 138/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7410 - accuracy: 0.5455 - val_loss: 1.1216 - val_accuracy: 0.5070\n",
      "Epoch 139/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7340 - accuracy: 0.5660 - val_loss: 1.1243 - val_accuracy: 0.5070\n",
      "Epoch 140/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7314 - accuracy: 0.5777 - val_loss: 1.1268 - val_accuracy: 0.5070\n",
      "Epoch 141/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7274 - accuracy: 0.5572 - val_loss: 1.1290 - val_accuracy: 0.5070\n",
      "Epoch 142/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7292 - accuracy: 0.5689 - val_loss: 1.1302 - val_accuracy: 0.5070\n",
      "Epoch 143/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7270 - accuracy: 0.5748 - val_loss: 1.1315 - val_accuracy: 0.5070\n",
      "Epoch 144/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7284 - accuracy: 0.5718 - val_loss: 1.1334 - val_accuracy: 0.5070\n",
      "Epoch 145/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7386 - accuracy: 0.5572 - val_loss: 1.1354 - val_accuracy: 0.4930\n",
      "Epoch 146/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7386 - accuracy: 0.5572 - val_loss: 1.1363 - val_accuracy: 0.4930\n",
      "Epoch 147/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7205 - accuracy: 0.5689 - val_loss: 1.1372 - val_accuracy: 0.4930\n",
      "Epoch 148/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7282 - accuracy: 0.5396 - val_loss: 1.1387 - val_accuracy: 0.4930\n",
      "Epoch 149/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7197 - accuracy: 0.5601 - val_loss: 1.1401 - val_accuracy: 0.4930\n",
      "Epoch 150/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7258 - accuracy: 0.5513 - val_loss: 1.1405 - val_accuracy: 0.4930\n",
      "Epoch 151/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7322 - accuracy: 0.5367 - val_loss: 1.1389 - val_accuracy: 0.4930\n",
      "Epoch 152/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7216 - accuracy: 0.5601 - val_loss: 1.1376 - val_accuracy: 0.4930\n",
      "Epoch 153/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7230 - accuracy: 0.5689 - val_loss: 1.1389 - val_accuracy: 0.4930\n",
      "Epoch 154/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7257 - accuracy: 0.5455 - val_loss: 1.1387 - val_accuracy: 0.4930\n",
      "Epoch 155/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7194 - accuracy: 0.5689 - val_loss: 1.1386 - val_accuracy: 0.4930\n",
      "Epoch 156/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7279 - accuracy: 0.5718 - val_loss: 1.1374 - val_accuracy: 0.4930\n",
      "Epoch 157/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7220 - accuracy: 0.5836 - val_loss: 1.1373 - val_accuracy: 0.4930\n",
      "Epoch 158/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7242 - accuracy: 0.5777 - val_loss: 1.1363 - val_accuracy: 0.4930\n",
      "Epoch 159/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7251 - accuracy: 0.5777 - val_loss: 1.1355 - val_accuracy: 0.4930\n",
      "Epoch 160/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7186 - accuracy: 0.5660 - val_loss: 1.1343 - val_accuracy: 0.4930\n",
      "Epoch 161/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7150 - accuracy: 0.5836 - val_loss: 1.1358 - val_accuracy: 0.4789\n",
      "Epoch 162/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7187 - accuracy: 0.5865 - val_loss: 1.1357 - val_accuracy: 0.4789\n",
      "Epoch 163/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7205 - accuracy: 0.5894 - val_loss: 1.1346 - val_accuracy: 0.4789\n",
      "Epoch 164/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7203 - accuracy: 0.5748 - val_loss: 1.1345 - val_accuracy: 0.4789\n",
      "Epoch 165/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7283 - accuracy: 0.5718 - val_loss: 1.1345 - val_accuracy: 0.4789\n",
      "Epoch 166/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7194 - accuracy: 0.5689 - val_loss: 1.1356 - val_accuracy: 0.4789\n",
      "Epoch 167/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7185 - accuracy: 0.5543 - val_loss: 1.1362 - val_accuracy: 0.4789\n",
      "Epoch 168/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7167 - accuracy: 0.5660 - val_loss: 1.1353 - val_accuracy: 0.4789\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 169/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7191 - accuracy: 0.5953 - val_loss: 1.1344 - val_accuracy: 0.4789\n",
      "Epoch 170/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7282 - accuracy: 0.5630 - val_loss: 1.1342 - val_accuracy: 0.4789\n",
      "Epoch 171/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7137 - accuracy: 0.5689 - val_loss: 1.1334 - val_accuracy: 0.4789\n",
      "Epoch 172/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7145 - accuracy: 0.5894 - val_loss: 1.1358 - val_accuracy: 0.4789\n",
      "Epoch 173/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7074 - accuracy: 0.5806 - val_loss: 1.1366 - val_accuracy: 0.4789\n",
      "Epoch 174/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7134 - accuracy: 0.6070 - val_loss: 1.1398 - val_accuracy: 0.4789\n",
      "Epoch 175/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7189 - accuracy: 0.5630 - val_loss: 1.1414 - val_accuracy: 0.4789\n",
      "Epoch 176/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7183 - accuracy: 0.5718 - val_loss: 1.1444 - val_accuracy: 0.4789\n",
      "Epoch 177/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7054 - accuracy: 0.5689 - val_loss: 1.1454 - val_accuracy: 0.4789\n",
      "Epoch 178/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7059 - accuracy: 0.5982 - val_loss: 1.1449 - val_accuracy: 0.4789\n",
      "Epoch 179/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7129 - accuracy: 0.5689 - val_loss: 1.1435 - val_accuracy: 0.4789\n",
      "Epoch 180/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7181 - accuracy: 0.5748 - val_loss: 1.1445 - val_accuracy: 0.4789\n",
      "Epoch 181/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7090 - accuracy: 0.5718 - val_loss: 1.1464 - val_accuracy: 0.4789\n",
      "Epoch 182/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7099 - accuracy: 0.5806 - val_loss: 1.1462 - val_accuracy: 0.4789\n",
      "Epoch 183/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7019 - accuracy: 0.5924 - val_loss: 1.1468 - val_accuracy: 0.4789\n",
      "Epoch 184/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7034 - accuracy: 0.5806 - val_loss: 1.1483 - val_accuracy: 0.4789\n",
      "Epoch 185/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7055 - accuracy: 0.5748 - val_loss: 1.1495 - val_accuracy: 0.4789\n",
      "Epoch 186/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7075 - accuracy: 0.5660 - val_loss: 1.1505 - val_accuracy: 0.4789\n",
      "Epoch 187/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7188 - accuracy: 0.5777 - val_loss: 1.1517 - val_accuracy: 0.4789\n",
      "Epoch 188/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7086 - accuracy: 0.5777 - val_loss: 1.1539 - val_accuracy: 0.4789\n",
      "Epoch 189/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6953 - accuracy: 0.5924 - val_loss: 1.1555 - val_accuracy: 0.4789\n",
      "Epoch 190/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7009 - accuracy: 0.5894 - val_loss: 1.1566 - val_accuracy: 0.4789\n",
      "Epoch 191/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7050 - accuracy: 0.5924 - val_loss: 1.1577 - val_accuracy: 0.4789\n",
      "Epoch 192/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7042 - accuracy: 0.5806 - val_loss: 1.1567 - val_accuracy: 0.4789\n",
      "Epoch 193/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7043 - accuracy: 0.5894 - val_loss: 1.1572 - val_accuracy: 0.4789\n",
      "Epoch 194/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6980 - accuracy: 0.6012 - val_loss: 1.1584 - val_accuracy: 0.4789\n",
      "Epoch 195/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7040 - accuracy: 0.5865 - val_loss: 1.1599 - val_accuracy: 0.4789\n",
      "Epoch 196/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6915 - accuracy: 0.5924 - val_loss: 1.1616 - val_accuracy: 0.4789\n",
      "Epoch 197/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6905 - accuracy: 0.5953 - val_loss: 1.1623 - val_accuracy: 0.4789\n",
      "Epoch 198/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6984 - accuracy: 0.5924 - val_loss: 1.1612 - val_accuracy: 0.4789\n",
      "Epoch 199/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.7022 - accuracy: 0.5982 - val_loss: 1.1612 - val_accuracy: 0.4789\n",
      "Epoch 200/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6941 - accuracy: 0.6041 - val_loss: 1.1617 - val_accuracy: 0.4789\n",
      "Epoch 201/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6962 - accuracy: 0.6012 - val_loss: 1.1625 - val_accuracy: 0.4789\n",
      "Epoch 202/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.7058 - accuracy: 0.5924 - val_loss: 1.1618 - val_accuracy: 0.4789\n",
      "Epoch 203/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6907 - accuracy: 0.5894 - val_loss: 1.1620 - val_accuracy: 0.4789\n",
      "Epoch 204/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6874 - accuracy: 0.6188 - val_loss: 1.1616 - val_accuracy: 0.4789\n",
      "Epoch 205/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6925 - accuracy: 0.5953 - val_loss: 1.1622 - val_accuracy: 0.4789\n",
      "Epoch 206/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6846 - accuracy: 0.6041 - val_loss: 1.1654 - val_accuracy: 0.4789\n",
      "Epoch 207/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6952 - accuracy: 0.5953 - val_loss: 1.1672 - val_accuracy: 0.4789\n",
      "Epoch 208/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6895 - accuracy: 0.5894 - val_loss: 1.1677 - val_accuracy: 0.4789\n",
      "Epoch 209/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6889 - accuracy: 0.6129 - val_loss: 1.1681 - val_accuracy: 0.4789\n",
      "Epoch 210/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6900 - accuracy: 0.5982 - val_loss: 1.1707 - val_accuracy: 0.4789\n",
      "Epoch 211/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6980 - accuracy: 0.5894 - val_loss: 1.1717 - val_accuracy: 0.4789\n",
      "Epoch 212/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6900 - accuracy: 0.6100 - val_loss: 1.1740 - val_accuracy: 0.4789\n",
      "Epoch 213/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6874 - accuracy: 0.6246 - val_loss: 1.1755 - val_accuracy: 0.4789\n",
      "Epoch 214/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6808 - accuracy: 0.6158 - val_loss: 1.1757 - val_accuracy: 0.4789\n",
      "Epoch 215/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6914 - accuracy: 0.6012 - val_loss: 1.1749 - val_accuracy: 0.4789\n",
      "Epoch 216/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6840 - accuracy: 0.6012 - val_loss: 1.1754 - val_accuracy: 0.4789\n",
      "Epoch 217/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6869 - accuracy: 0.5865 - val_loss: 1.1754 - val_accuracy: 0.4789\n",
      "Epoch 218/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6782 - accuracy: 0.6070 - val_loss: 1.1757 - val_accuracy: 0.4789\n",
      "Epoch 219/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6856 - accuracy: 0.6100 - val_loss: 1.1762 - val_accuracy: 0.4789\n",
      "Epoch 220/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6866 - accuracy: 0.6129 - val_loss: 1.1770 - val_accuracy: 0.4789\n",
      "Epoch 221/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6746 - accuracy: 0.6041 - val_loss: 1.1781 - val_accuracy: 0.4789\n",
      "Epoch 222/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6853 - accuracy: 0.5924 - val_loss: 1.1797 - val_accuracy: 0.4648\n",
      "Epoch 223/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6801 - accuracy: 0.6100 - val_loss: 1.1798 - val_accuracy: 0.4648\n",
      "Epoch 224/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6858 - accuracy: 0.6100 - val_loss: 1.1798 - val_accuracy: 0.4648\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 225/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6813 - accuracy: 0.6129 - val_loss: 1.1826 - val_accuracy: 0.4648\n",
      "Epoch 226/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6842 - accuracy: 0.6100 - val_loss: 1.1867 - val_accuracy: 0.4648\n",
      "Epoch 227/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6845 - accuracy: 0.5982 - val_loss: 1.1919 - val_accuracy: 0.4648\n",
      "Epoch 228/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6780 - accuracy: 0.6041 - val_loss: 1.1931 - val_accuracy: 0.4648\n",
      "Epoch 229/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6732 - accuracy: 0.6158 - val_loss: 1.1957 - val_accuracy: 0.4648\n",
      "Epoch 230/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6810 - accuracy: 0.6100 - val_loss: 1.1994 - val_accuracy: 0.4789\n",
      "Epoch 231/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6831 - accuracy: 0.5953 - val_loss: 1.2013 - val_accuracy: 0.4789\n",
      "Epoch 232/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6742 - accuracy: 0.6070 - val_loss: 1.2035 - val_accuracy: 0.4789\n",
      "Epoch 233/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6700 - accuracy: 0.6129 - val_loss: 1.2044 - val_accuracy: 0.4789\n",
      "Epoch 234/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6728 - accuracy: 0.6158 - val_loss: 1.2061 - val_accuracy: 0.4789\n",
      "Epoch 235/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6757 - accuracy: 0.6188 - val_loss: 1.2078 - val_accuracy: 0.4789\n",
      "Epoch 236/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6764 - accuracy: 0.6070 - val_loss: 1.2070 - val_accuracy: 0.4789\n",
      "Epoch 237/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6688 - accuracy: 0.6276 - val_loss: 1.2090 - val_accuracy: 0.4789\n",
      "Epoch 238/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6688 - accuracy: 0.6100 - val_loss: 1.2100 - val_accuracy: 0.4789\n",
      "Epoch 239/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6640 - accuracy: 0.5924 - val_loss: 1.2163 - val_accuracy: 0.4789\n",
      "Epoch 240/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6741 - accuracy: 0.6305 - val_loss: 1.2189 - val_accuracy: 0.4789\n",
      "Epoch 241/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6709 - accuracy: 0.6217 - val_loss: 1.2201 - val_accuracy: 0.4789\n",
      "Epoch 242/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6639 - accuracy: 0.6100 - val_loss: 1.2217 - val_accuracy: 0.4789\n",
      "Epoch 243/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6650 - accuracy: 0.6217 - val_loss: 1.2240 - val_accuracy: 0.4789\n",
      "Epoch 244/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6537 - accuracy: 0.6276 - val_loss: 1.2281 - val_accuracy: 0.4789\n",
      "Epoch 245/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6578 - accuracy: 0.6422 - val_loss: 1.2331 - val_accuracy: 0.4789\n",
      "Epoch 246/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6693 - accuracy: 0.6305 - val_loss: 1.2375 - val_accuracy: 0.4789\n",
      "Epoch 247/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6564 - accuracy: 0.6129 - val_loss: 1.2411 - val_accuracy: 0.4789\n",
      "Epoch 248/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6580 - accuracy: 0.6158 - val_loss: 1.2454 - val_accuracy: 0.4789\n",
      "Epoch 249/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6694 - accuracy: 0.6188 - val_loss: 1.2503 - val_accuracy: 0.4648\n",
      "Epoch 250/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6633 - accuracy: 0.6276 - val_loss: 1.2529 - val_accuracy: 0.4648\n",
      "Epoch 251/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6484 - accuracy: 0.6364 - val_loss: 1.2560 - val_accuracy: 0.4648\n",
      "Epoch 252/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6526 - accuracy: 0.6276 - val_loss: 1.2592 - val_accuracy: 0.4648\n",
      "Epoch 253/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6624 - accuracy: 0.6246 - val_loss: 1.2586 - val_accuracy: 0.4648\n",
      "Epoch 254/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6529 - accuracy: 0.6188 - val_loss: 1.2622 - val_accuracy: 0.4648\n",
      "Epoch 255/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6452 - accuracy: 0.6246 - val_loss: 1.2661 - val_accuracy: 0.4648\n",
      "Epoch 256/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6567 - accuracy: 0.6364 - val_loss: 1.2713 - val_accuracy: 0.4648\n",
      "Epoch 257/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6588 - accuracy: 0.6188 - val_loss: 1.2726 - val_accuracy: 0.4648\n",
      "Epoch 258/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6684 - accuracy: 0.6129 - val_loss: 1.2765 - val_accuracy: 0.4648\n",
      "Epoch 259/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6614 - accuracy: 0.6158 - val_loss: 1.2781 - val_accuracy: 0.4648\n",
      "Epoch 260/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6594 - accuracy: 0.6305 - val_loss: 1.2811 - val_accuracy: 0.4648\n",
      "Epoch 261/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6541 - accuracy: 0.6364 - val_loss: 1.2805 - val_accuracy: 0.4648\n",
      "Epoch 262/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6510 - accuracy: 0.6364 - val_loss: 1.2818 - val_accuracy: 0.4648\n",
      "Epoch 263/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6508 - accuracy: 0.6305 - val_loss: 1.2815 - val_accuracy: 0.4648\n",
      "Epoch 264/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6548 - accuracy: 0.6276 - val_loss: 1.2834 - val_accuracy: 0.4648\n",
      "Epoch 265/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6559 - accuracy: 0.6188 - val_loss: 1.2865 - val_accuracy: 0.4648\n",
      "Epoch 266/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6551 - accuracy: 0.6217 - val_loss: 1.2945 - val_accuracy: 0.4648\n",
      "Epoch 267/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6451 - accuracy: 0.6217 - val_loss: 1.3014 - val_accuracy: 0.4648\n",
      "Epoch 268/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6474 - accuracy: 0.6364 - val_loss: 1.3051 - val_accuracy: 0.4648\n",
      "Epoch 269/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6495 - accuracy: 0.6246 - val_loss: 1.3114 - val_accuracy: 0.4648\n",
      "Epoch 270/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6459 - accuracy: 0.6481 - val_loss: 1.3158 - val_accuracy: 0.4648\n",
      "Epoch 271/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6463 - accuracy: 0.6481 - val_loss: 1.3204 - val_accuracy: 0.4648\n",
      "Epoch 272/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6518 - accuracy: 0.6158 - val_loss: 1.3262 - val_accuracy: 0.4648\n",
      "Epoch 273/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6476 - accuracy: 0.6364 - val_loss: 1.3341 - val_accuracy: 0.4648\n",
      "Epoch 274/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6431 - accuracy: 0.6364 - val_loss: 1.3395 - val_accuracy: 0.4648\n",
      "Epoch 275/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6428 - accuracy: 0.6422 - val_loss: 1.3437 - val_accuracy: 0.4648\n",
      "Epoch 276/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6418 - accuracy: 0.6305 - val_loss: 1.3496 - val_accuracy: 0.4648\n",
      "Epoch 277/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6405 - accuracy: 0.6364 - val_loss: 1.3565 - val_accuracy: 0.4648\n",
      "Epoch 278/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6421 - accuracy: 0.6188 - val_loss: 1.3649 - val_accuracy: 0.4648\n",
      "Epoch 279/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6296 - accuracy: 0.6481 - val_loss: 1.3673 - val_accuracy: 0.4648\n",
      "Epoch 280/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6263 - accuracy: 0.6305 - val_loss: 1.3743 - val_accuracy: 0.4648\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 281/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6340 - accuracy: 0.6246 - val_loss: 1.3812 - val_accuracy: 0.4648\n",
      "Epoch 282/10000\n",
      "341/341 [==============================] - 2s 5ms/step - loss: 0.6391 - accuracy: 0.6276 - val_loss: 1.3891 - val_accuracy: 0.4648\n",
      "Epoch 283/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6304 - accuracy: 0.6569 - val_loss: 1.3933 - val_accuracy: 0.4648\n",
      "Epoch 284/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6315 - accuracy: 0.6422 - val_loss: 1.3971 - val_accuracy: 0.4648\n",
      "Epoch 285/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6291 - accuracy: 0.6510 - val_loss: 1.3986 - val_accuracy: 0.4648\n",
      "Epoch 286/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6370 - accuracy: 0.6334 - val_loss: 1.4035 - val_accuracy: 0.4648\n",
      "Epoch 287/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6266 - accuracy: 0.6452 - val_loss: 1.4077 - val_accuracy: 0.4648\n",
      "Epoch 288/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.6327 - accuracy: 0.6334 - val_loss: 1.4145 - val_accuracy: 0.4648\n",
      "Epoch 289/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6252 - accuracy: 0.6598 - val_loss: 1.4207 - val_accuracy: 0.4648\n",
      "Epoch 290/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6285 - accuracy: 0.6452 - val_loss: 1.4223 - val_accuracy: 0.4648\n",
      "Epoch 291/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6298 - accuracy: 0.6628 - val_loss: 1.4286 - val_accuracy: 0.4648\n",
      "Epoch 292/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6217 - accuracy: 0.6481 - val_loss: 1.4319 - val_accuracy: 0.4648\n",
      "Epoch 293/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6257 - accuracy: 0.6510 - val_loss: 1.4376 - val_accuracy: 0.4648\n",
      "Epoch 294/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6269 - accuracy: 0.6422 - val_loss: 1.4435 - val_accuracy: 0.4648\n",
      "Epoch 295/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6210 - accuracy: 0.6305 - val_loss: 1.4455 - val_accuracy: 0.4648\n",
      "Epoch 296/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6223 - accuracy: 0.6628 - val_loss: 1.4496 - val_accuracy: 0.4648\n",
      "Epoch 297/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6253 - accuracy: 0.6422 - val_loss: 1.4529 - val_accuracy: 0.4648\n",
      "Epoch 298/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6193 - accuracy: 0.6628 - val_loss: 1.4581 - val_accuracy: 0.4648\n",
      "Epoch 299/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6249 - accuracy: 0.6422 - val_loss: 1.4591 - val_accuracy: 0.4648\n",
      "Epoch 300/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6238 - accuracy: 0.6569 - val_loss: 1.4623 - val_accuracy: 0.4648\n",
      "Epoch 301/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6210 - accuracy: 0.6422 - val_loss: 1.4606 - val_accuracy: 0.4648\n",
      "Epoch 302/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6215 - accuracy: 0.6393 - val_loss: 1.4659 - val_accuracy: 0.4648\n",
      "Epoch 303/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6257 - accuracy: 0.6481 - val_loss: 1.4690 - val_accuracy: 0.4648\n",
      "Epoch 304/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6184 - accuracy: 0.6452 - val_loss: 1.4657 - val_accuracy: 0.4648\n",
      "Epoch 305/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6252 - accuracy: 0.6217 - val_loss: 1.4668 - val_accuracy: 0.4648\n",
      "Epoch 306/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6107 - accuracy: 0.6657 - val_loss: 1.4633 - val_accuracy: 0.4648\n",
      "Epoch 307/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6115 - accuracy: 0.6833 - val_loss: 1.4675 - val_accuracy: 0.4648\n",
      "Epoch 308/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6111 - accuracy: 0.6628 - val_loss: 1.4711 - val_accuracy: 0.4648\n",
      "Epoch 309/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6139 - accuracy: 0.6540 - val_loss: 1.4651 - val_accuracy: 0.4648\n",
      "Epoch 310/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6150 - accuracy: 0.6657 - val_loss: 1.4628 - val_accuracy: 0.4648\n",
      "Epoch 311/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6189 - accuracy: 0.6745 - val_loss: 1.4612 - val_accuracy: 0.4648\n",
      "Epoch 312/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6101 - accuracy: 0.6481 - val_loss: 1.4584 - val_accuracy: 0.4648\n",
      "Epoch 313/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6130 - accuracy: 0.6598 - val_loss: 1.4572 - val_accuracy: 0.4648\n",
      "Epoch 314/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6106 - accuracy: 0.6510 - val_loss: 1.4644 - val_accuracy: 0.4648\n",
      "Epoch 315/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6093 - accuracy: 0.6657 - val_loss: 1.4620 - val_accuracy: 0.4648\n",
      "Epoch 316/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6149 - accuracy: 0.6569 - val_loss: 1.4583 - val_accuracy: 0.4648\n",
      "Epoch 317/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6108 - accuracy: 0.6745 - val_loss: 1.4561 - val_accuracy: 0.4648\n",
      "Epoch 318/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6083 - accuracy: 0.6598 - val_loss: 1.4551 - val_accuracy: 0.4648\n",
      "Epoch 319/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6025 - accuracy: 0.6745 - val_loss: 1.4584 - val_accuracy: 0.4648\n",
      "Epoch 320/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6072 - accuracy: 0.6686 - val_loss: 1.4593 - val_accuracy: 0.4648\n",
      "Epoch 321/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6026 - accuracy: 0.6745 - val_loss: 1.4571 - val_accuracy: 0.4648\n",
      "Epoch 322/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6058 - accuracy: 0.6862 - val_loss: 1.4580 - val_accuracy: 0.4648\n",
      "Epoch 323/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6052 - accuracy: 0.6569 - val_loss: 1.4558 - val_accuracy: 0.4648\n",
      "Epoch 324/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6024 - accuracy: 0.6804 - val_loss: 1.4568 - val_accuracy: 0.4648\n",
      "Epoch 325/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6027 - accuracy: 0.6979 - val_loss: 1.4456 - val_accuracy: 0.4648\n",
      "Epoch 326/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6100 - accuracy: 0.6686 - val_loss: 1.4358 - val_accuracy: 0.4648\n",
      "Epoch 327/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6045 - accuracy: 0.6774 - val_loss: 1.4314 - val_accuracy: 0.4789\n",
      "Epoch 328/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5981 - accuracy: 0.6950 - val_loss: 1.4291 - val_accuracy: 0.4789\n",
      "Epoch 329/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6023 - accuracy: 0.6716 - val_loss: 1.4287 - val_accuracy: 0.4789\n",
      "Epoch 330/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6062 - accuracy: 0.6716 - val_loss: 1.4165 - val_accuracy: 0.4789\n",
      "Epoch 331/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6027 - accuracy: 0.6921 - val_loss: 1.4163 - val_accuracy: 0.4789\n",
      "Epoch 332/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5921 - accuracy: 0.6979 - val_loss: 1.4092 - val_accuracy: 0.4789\n",
      "Epoch 333/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5916 - accuracy: 0.6862 - val_loss: 1.4026 - val_accuracy: 0.4789\n",
      "Epoch 334/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5956 - accuracy: 0.6891 - val_loss: 1.3996 - val_accuracy: 0.4930\n",
      "Epoch 335/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5964 - accuracy: 0.6891 - val_loss: 1.3909 - val_accuracy: 0.4930\n",
      "Epoch 336/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6036 - accuracy: 0.6862 - val_loss: 1.3882 - val_accuracy: 0.4930\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 337/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6015 - accuracy: 0.6921 - val_loss: 1.3912 - val_accuracy: 0.4930\n",
      "Epoch 338/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5991 - accuracy: 0.6862 - val_loss: 1.3875 - val_accuracy: 0.4930\n",
      "Epoch 339/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5979 - accuracy: 0.6804 - val_loss: 1.3859 - val_accuracy: 0.4930\n",
      "Epoch 340/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.6004 - accuracy: 0.7009 - val_loss: 1.3805 - val_accuracy: 0.4930\n",
      "Epoch 341/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5999 - accuracy: 0.6921 - val_loss: 1.3738 - val_accuracy: 0.4930\n",
      "Epoch 342/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.5913 - accuracy: 0.7155 - val_loss: 1.3703 - val_accuracy: 0.4930\n",
      "Epoch 343/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5904 - accuracy: 0.7009 - val_loss: 1.3668 - val_accuracy: 0.4930\n",
      "Epoch 344/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5898 - accuracy: 0.7155 - val_loss: 1.3600 - val_accuracy: 0.4930\n",
      "Epoch 345/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5902 - accuracy: 0.6862 - val_loss: 1.3428 - val_accuracy: 0.4930\n",
      "Epoch 346/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5965 - accuracy: 0.7009 - val_loss: 1.3317 - val_accuracy: 0.4930\n",
      "Epoch 347/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5857 - accuracy: 0.7038 - val_loss: 1.3174 - val_accuracy: 0.4789\n",
      "Epoch 348/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5908 - accuracy: 0.7067 - val_loss: 1.3052 - val_accuracy: 0.4789\n",
      "Epoch 349/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5878 - accuracy: 0.7126 - val_loss: 1.2995 - val_accuracy: 0.4789\n",
      "Epoch 350/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5909 - accuracy: 0.7009 - val_loss: 1.2951 - val_accuracy: 0.4789\n",
      "Epoch 351/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5854 - accuracy: 0.6921 - val_loss: 1.2893 - val_accuracy: 0.4789\n",
      "Epoch 352/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5821 - accuracy: 0.7126 - val_loss: 1.2858 - val_accuracy: 0.4789\n",
      "Epoch 353/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5923 - accuracy: 0.7067 - val_loss: 1.2773 - val_accuracy: 0.4930\n",
      "Epoch 354/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5915 - accuracy: 0.6833 - val_loss: 1.2794 - val_accuracy: 0.4930\n",
      "Epoch 355/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5854 - accuracy: 0.7009 - val_loss: 1.2786 - val_accuracy: 0.4930\n",
      "Epoch 356/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5870 - accuracy: 0.6921 - val_loss: 1.2754 - val_accuracy: 0.4930\n",
      "Epoch 357/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5789 - accuracy: 0.7097 - val_loss: 1.2774 - val_accuracy: 0.4930\n",
      "Epoch 358/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5795 - accuracy: 0.6950 - val_loss: 1.2699 - val_accuracy: 0.4930\n",
      "Epoch 359/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5828 - accuracy: 0.7155 - val_loss: 1.2610 - val_accuracy: 0.5070\n",
      "Epoch 360/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.5901 - accuracy: 0.6862 - val_loss: 1.2676 - val_accuracy: 0.5070\n",
      "Epoch 361/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5829 - accuracy: 0.6891 - val_loss: 1.2666 - val_accuracy: 0.5070\n",
      "Epoch 362/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5859 - accuracy: 0.6891 - val_loss: 1.2596 - val_accuracy: 0.5070\n",
      "Epoch 363/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5881 - accuracy: 0.7009 - val_loss: 1.2613 - val_accuracy: 0.5070\n",
      "Epoch 364/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5872 - accuracy: 0.6862 - val_loss: 1.2498 - val_accuracy: 0.5070\n",
      "Epoch 365/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5836 - accuracy: 0.7038 - val_loss: 1.2400 - val_accuracy: 0.5070\n",
      "Epoch 366/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5723 - accuracy: 0.7009 - val_loss: 1.2457 - val_accuracy: 0.5070\n",
      "Epoch 367/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5808 - accuracy: 0.6950 - val_loss: 1.2394 - val_accuracy: 0.5070\n",
      "Epoch 368/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5820 - accuracy: 0.7097 - val_loss: 1.2349 - val_accuracy: 0.4930\n",
      "Epoch 369/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5784 - accuracy: 0.7097 - val_loss: 1.2312 - val_accuracy: 0.4930\n",
      "Epoch 370/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5704 - accuracy: 0.7302 - val_loss: 1.2325 - val_accuracy: 0.4930\n",
      "Epoch 371/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5839 - accuracy: 0.7067 - val_loss: 1.2288 - val_accuracy: 0.4930\n",
      "Epoch 372/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5726 - accuracy: 0.7243 - val_loss: 1.2285 - val_accuracy: 0.4930\n",
      "Epoch 373/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5788 - accuracy: 0.7126 - val_loss: 1.2214 - val_accuracy: 0.4930\n",
      "Epoch 374/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5701 - accuracy: 0.7067 - val_loss: 1.2136 - val_accuracy: 0.4930\n",
      "Epoch 375/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5767 - accuracy: 0.7155 - val_loss: 1.2069 - val_accuracy: 0.5070\n",
      "Epoch 376/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5763 - accuracy: 0.7185 - val_loss: 1.1928 - val_accuracy: 0.5070\n",
      "Epoch 377/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5668 - accuracy: 0.7331 - val_loss: 1.1893 - val_accuracy: 0.5070\n",
      "Epoch 378/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5758 - accuracy: 0.6979 - val_loss: 1.1842 - val_accuracy: 0.5070\n",
      "Epoch 379/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5806 - accuracy: 0.7038 - val_loss: 1.1780 - val_accuracy: 0.5070\n",
      "Epoch 380/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5685 - accuracy: 0.7185 - val_loss: 1.1670 - val_accuracy: 0.5070\n",
      "Epoch 381/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5704 - accuracy: 0.7067 - val_loss: 1.1626 - val_accuracy: 0.5070\n",
      "Epoch 382/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5668 - accuracy: 0.7067 - val_loss: 1.1532 - val_accuracy: 0.5070\n",
      "Epoch 383/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5697 - accuracy: 0.6950 - val_loss: 1.1521 - val_accuracy: 0.5070\n",
      "Epoch 384/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5653 - accuracy: 0.7214 - val_loss: 1.1530 - val_accuracy: 0.5070\n",
      "Epoch 385/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5660 - accuracy: 0.7273 - val_loss: 1.1571 - val_accuracy: 0.5070\n",
      "Epoch 386/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5720 - accuracy: 0.7155 - val_loss: 1.1534 - val_accuracy: 0.5070\n",
      "Epoch 387/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5750 - accuracy: 0.7185 - val_loss: 1.1510 - val_accuracy: 0.5070\n",
      "Epoch 388/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5710 - accuracy: 0.7126 - val_loss: 1.1490 - val_accuracy: 0.5070\n",
      "Epoch 389/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5774 - accuracy: 0.7097 - val_loss: 1.1435 - val_accuracy: 0.5070\n",
      "Epoch 390/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5650 - accuracy: 0.7038 - val_loss: 1.1402 - val_accuracy: 0.5070\n",
      "Epoch 391/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5716 - accuracy: 0.7185 - val_loss: 1.1376 - val_accuracy: 0.5070\n",
      "Epoch 392/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5660 - accuracy: 0.6979 - val_loss: 1.1377 - val_accuracy: 0.5070\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 393/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5656 - accuracy: 0.7185 - val_loss: 1.1313 - val_accuracy: 0.5211\n",
      "Epoch 394/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5754 - accuracy: 0.7126 - val_loss: 1.1244 - val_accuracy: 0.5211\n",
      "Epoch 395/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5639 - accuracy: 0.7273 - val_loss: 1.1193 - val_accuracy: 0.5211\n",
      "Epoch 396/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5666 - accuracy: 0.7331 - val_loss: 1.1142 - val_accuracy: 0.5211\n",
      "Epoch 397/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5640 - accuracy: 0.7273 - val_loss: 1.1167 - val_accuracy: 0.5211\n",
      "Epoch 398/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5646 - accuracy: 0.7214 - val_loss: 1.1136 - val_accuracy: 0.5211\n",
      "Epoch 399/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5649 - accuracy: 0.7243 - val_loss: 1.1168 - val_accuracy: 0.5211\n",
      "Epoch 400/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5604 - accuracy: 0.7361 - val_loss: 1.1090 - val_accuracy: 0.5352\n",
      "Epoch 401/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5632 - accuracy: 0.7155 - val_loss: 1.1045 - val_accuracy: 0.5352\n",
      "Epoch 402/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5593 - accuracy: 0.7302 - val_loss: 1.0977 - val_accuracy: 0.5493\n",
      "Epoch 403/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5634 - accuracy: 0.7097 - val_loss: 1.0915 - val_accuracy: 0.5493\n",
      "Epoch 404/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5598 - accuracy: 0.7361 - val_loss: 1.0853 - val_accuracy: 0.5352\n",
      "Epoch 405/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5646 - accuracy: 0.6979 - val_loss: 1.0810 - val_accuracy: 0.5352\n",
      "Epoch 406/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5693 - accuracy: 0.7097 - val_loss: 1.0843 - val_accuracy: 0.5352\n",
      "Epoch 407/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5546 - accuracy: 0.7361 - val_loss: 1.0839 - val_accuracy: 0.5352\n",
      "Epoch 408/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5672 - accuracy: 0.7155 - val_loss: 1.0855 - val_accuracy: 0.5352\n",
      "Epoch 409/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5595 - accuracy: 0.7273 - val_loss: 1.0871 - val_accuracy: 0.5352\n",
      "Epoch 410/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5562 - accuracy: 0.7214 - val_loss: 1.0877 - val_accuracy: 0.5352\n",
      "Epoch 411/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5581 - accuracy: 0.7419 - val_loss: 1.0872 - val_accuracy: 0.5352\n",
      "Epoch 412/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5572 - accuracy: 0.7361 - val_loss: 1.0891 - val_accuracy: 0.5352\n",
      "Epoch 413/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5571 - accuracy: 0.7214 - val_loss: 1.0835 - val_accuracy: 0.5352\n",
      "Epoch 414/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5601 - accuracy: 0.7243 - val_loss: 1.0782 - val_accuracy: 0.5352\n",
      "Epoch 415/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5629 - accuracy: 0.7097 - val_loss: 1.0793 - val_accuracy: 0.5352\n",
      "Epoch 416/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5578 - accuracy: 0.7449 - val_loss: 1.0789 - val_accuracy: 0.5352\n",
      "Epoch 417/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5621 - accuracy: 0.7009 - val_loss: 1.0801 - val_accuracy: 0.5352\n",
      "Epoch 418/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5594 - accuracy: 0.7155 - val_loss: 1.0734 - val_accuracy: 0.5352\n",
      "Epoch 419/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5545 - accuracy: 0.7243 - val_loss: 1.0759 - val_accuracy: 0.5352\n",
      "Epoch 420/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5581 - accuracy: 0.7331 - val_loss: 1.0732 - val_accuracy: 0.5352\n",
      "Epoch 421/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5581 - accuracy: 0.7243 - val_loss: 1.0697 - val_accuracy: 0.5352\n",
      "Epoch 422/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5532 - accuracy: 0.7243 - val_loss: 1.0636 - val_accuracy: 0.5352\n",
      "Epoch 423/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5549 - accuracy: 0.7331 - val_loss: 1.0639 - val_accuracy: 0.5352\n",
      "Epoch 424/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5474 - accuracy: 0.7185 - val_loss: 1.0580 - val_accuracy: 0.5352\n",
      "Epoch 425/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5513 - accuracy: 0.7390 - val_loss: 1.0615 - val_accuracy: 0.5352\n",
      "Epoch 426/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5514 - accuracy: 0.7419 - val_loss: 1.0694 - val_accuracy: 0.5352\n",
      "Epoch 427/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5487 - accuracy: 0.7273 - val_loss: 1.0707 - val_accuracy: 0.5352\n",
      "Epoch 428/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5504 - accuracy: 0.7390 - val_loss: 1.0681 - val_accuracy: 0.5352\n",
      "Epoch 429/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5467 - accuracy: 0.7361 - val_loss: 1.0656 - val_accuracy: 0.5352\n",
      "Epoch 430/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.5583 - accuracy: 0.7273 - val_loss: 1.0669 - val_accuracy: 0.5352\n",
      "Epoch 431/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5642 - accuracy: 0.7126 - val_loss: 1.0676 - val_accuracy: 0.5352\n",
      "Epoch 432/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5485 - accuracy: 0.7537 - val_loss: 1.0691 - val_accuracy: 0.5352\n",
      "Epoch 433/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5484 - accuracy: 0.7302 - val_loss: 1.0693 - val_accuracy: 0.5352\n",
      "Epoch 434/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5500 - accuracy: 0.7243 - val_loss: 1.0681 - val_accuracy: 0.5352\n",
      "Epoch 435/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5538 - accuracy: 0.7185 - val_loss: 1.0687 - val_accuracy: 0.5352\n",
      "Epoch 436/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5481 - accuracy: 0.7390 - val_loss: 1.0767 - val_accuracy: 0.5352\n",
      "Epoch 437/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5458 - accuracy: 0.7419 - val_loss: 1.0709 - val_accuracy: 0.5352\n",
      "Epoch 438/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5548 - accuracy: 0.7390 - val_loss: 1.0796 - val_accuracy: 0.5352\n",
      "Epoch 439/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5515 - accuracy: 0.7419 - val_loss: 1.0816 - val_accuracy: 0.5352\n",
      "Epoch 440/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5493 - accuracy: 0.7302 - val_loss: 1.0815 - val_accuracy: 0.5352\n",
      "Epoch 441/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5494 - accuracy: 0.7419 - val_loss: 1.0845 - val_accuracy: 0.5352\n",
      "Epoch 442/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5425 - accuracy: 0.7419 - val_loss: 1.0942 - val_accuracy: 0.5352\n",
      "Epoch 443/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5555 - accuracy: 0.7361 - val_loss: 1.1010 - val_accuracy: 0.5493\n",
      "Epoch 444/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5479 - accuracy: 0.7449 - val_loss: 1.1030 - val_accuracy: 0.5493\n",
      "Epoch 445/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5461 - accuracy: 0.7390 - val_loss: 1.1067 - val_accuracy: 0.5493\n",
      "Epoch 446/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5497 - accuracy: 0.7243 - val_loss: 1.1009 - val_accuracy: 0.5493\n",
      "Epoch 447/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5499 - accuracy: 0.7302 - val_loss: 1.1023 - val_accuracy: 0.5352\n",
      "Epoch 448/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5533 - accuracy: 0.7419 - val_loss: 1.1035 - val_accuracy: 0.5352\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 449/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5428 - accuracy: 0.7449 - val_loss: 1.0993 - val_accuracy: 0.5211\n",
      "Epoch 450/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5429 - accuracy: 0.7390 - val_loss: 1.0959 - val_accuracy: 0.5211\n",
      "Epoch 451/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5464 - accuracy: 0.7566 - val_loss: 1.0918 - val_accuracy: 0.5211\n",
      "Epoch 452/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5547 - accuracy: 0.7273 - val_loss: 1.0898 - val_accuracy: 0.5211\n",
      "Epoch 453/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5425 - accuracy: 0.7478 - val_loss: 1.0829 - val_accuracy: 0.5211\n",
      "Epoch 454/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5469 - accuracy: 0.7449 - val_loss: 1.0820 - val_accuracy: 0.5211\n",
      "Epoch 455/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5409 - accuracy: 0.7478 - val_loss: 1.0842 - val_accuracy: 0.5211\n",
      "Epoch 456/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5453 - accuracy: 0.7331 - val_loss: 1.0812 - val_accuracy: 0.5211\n",
      "Epoch 457/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5490 - accuracy: 0.7595 - val_loss: 1.0780 - val_accuracy: 0.5211\n",
      "Epoch 458/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5412 - accuracy: 0.7507 - val_loss: 1.0807 - val_accuracy: 0.5211\n",
      "Epoch 459/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5400 - accuracy: 0.7625 - val_loss: 1.0686 - val_accuracy: 0.5352\n",
      "Epoch 460/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5338 - accuracy: 0.7478 - val_loss: 1.0698 - val_accuracy: 0.5352\n",
      "Epoch 461/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5475 - accuracy: 0.7302 - val_loss: 1.0756 - val_accuracy: 0.5352\n",
      "Epoch 462/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5439 - accuracy: 0.7478 - val_loss: 1.0764 - val_accuracy: 0.5352\n",
      "Epoch 463/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5395 - accuracy: 0.7361 - val_loss: 1.0802 - val_accuracy: 0.5352\n",
      "Epoch 464/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5413 - accuracy: 0.7507 - val_loss: 1.0811 - val_accuracy: 0.5352\n",
      "Epoch 465/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5304 - accuracy: 0.7654 - val_loss: 1.0803 - val_accuracy: 0.5352\n",
      "Epoch 466/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5332 - accuracy: 0.7683 - val_loss: 1.0785 - val_accuracy: 0.5352\n",
      "Epoch 467/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5387 - accuracy: 0.7273 - val_loss: 1.0809 - val_accuracy: 0.5352\n",
      "Epoch 468/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5412 - accuracy: 0.7361 - val_loss: 1.0832 - val_accuracy: 0.5352\n",
      "Epoch 469/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5385 - accuracy: 0.7155 - val_loss: 1.0749 - val_accuracy: 0.5352\n",
      "Epoch 470/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5347 - accuracy: 0.7566 - val_loss: 1.0784 - val_accuracy: 0.5352\n",
      "Epoch 471/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5277 - accuracy: 0.7302 - val_loss: 1.0816 - val_accuracy: 0.5352\n",
      "Epoch 472/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5397 - accuracy: 0.7419 - val_loss: 1.0716 - val_accuracy: 0.5352\n",
      "Epoch 473/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5395 - accuracy: 0.7507 - val_loss: 1.0665 - val_accuracy: 0.5352\n",
      "Epoch 474/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5345 - accuracy: 0.7478 - val_loss: 1.0649 - val_accuracy: 0.5352\n",
      "Epoch 475/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5333 - accuracy: 0.7478 - val_loss: 1.0670 - val_accuracy: 0.5352\n",
      "Epoch 476/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5347 - accuracy: 0.7537 - val_loss: 1.0618 - val_accuracy: 0.5493\n",
      "Epoch 477/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5361 - accuracy: 0.7742 - val_loss: 1.0632 - val_accuracy: 0.5493\n",
      "Epoch 478/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5341 - accuracy: 0.7625 - val_loss: 1.0614 - val_accuracy: 0.5493\n",
      "Epoch 479/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5315 - accuracy: 0.7507 - val_loss: 1.0634 - val_accuracy: 0.5352\n",
      "Epoch 480/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5379 - accuracy: 0.7390 - val_loss: 1.0597 - val_accuracy: 0.5352\n",
      "Epoch 481/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5311 - accuracy: 0.7537 - val_loss: 1.0583 - val_accuracy: 0.5493\n",
      "Epoch 482/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5360 - accuracy: 0.7595 - val_loss: 1.0688 - val_accuracy: 0.5352\n",
      "Epoch 483/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5360 - accuracy: 0.7331 - val_loss: 1.0769 - val_accuracy: 0.5211\n",
      "Epoch 484/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5308 - accuracy: 0.7478 - val_loss: 1.0787 - val_accuracy: 0.5211\n",
      "Epoch 485/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5296 - accuracy: 0.7625 - val_loss: 1.0809 - val_accuracy: 0.5211\n",
      "Epoch 486/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5255 - accuracy: 0.7625 - val_loss: 1.0821 - val_accuracy: 0.5211\n",
      "Epoch 487/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5252 - accuracy: 0.7625 - val_loss: 1.0722 - val_accuracy: 0.5352\n",
      "Epoch 488/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5271 - accuracy: 0.7566 - val_loss: 1.0660 - val_accuracy: 0.5493\n",
      "Epoch 489/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5285 - accuracy: 0.7654 - val_loss: 1.0612 - val_accuracy: 0.5493\n",
      "Epoch 490/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5262 - accuracy: 0.7595 - val_loss: 1.0583 - val_accuracy: 0.5493\n",
      "Epoch 491/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5199 - accuracy: 0.7595 - val_loss: 1.0589 - val_accuracy: 0.5493\n",
      "Epoch 492/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5157 - accuracy: 0.7771 - val_loss: 1.0588 - val_accuracy: 0.5493\n",
      "Epoch 493/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5253 - accuracy: 0.7742 - val_loss: 1.0620 - val_accuracy: 0.5493\n",
      "Epoch 494/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5245 - accuracy: 0.7566 - val_loss: 1.0592 - val_accuracy: 0.5493\n",
      "Epoch 495/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5275 - accuracy: 0.7625 - val_loss: 1.0588 - val_accuracy: 0.5493\n",
      "Epoch 496/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5326 - accuracy: 0.7478 - val_loss: 1.0532 - val_accuracy: 0.5493\n",
      "Epoch 497/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5271 - accuracy: 0.7537 - val_loss: 1.0536 - val_accuracy: 0.5493\n",
      "Epoch 498/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5377 - accuracy: 0.7478 - val_loss: 1.0612 - val_accuracy: 0.5493\n",
      "Epoch 499/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5266 - accuracy: 0.7683 - val_loss: 1.0641 - val_accuracy: 0.5493\n",
      "Epoch 500/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5208 - accuracy: 0.7595 - val_loss: 1.0766 - val_accuracy: 0.5493\n",
      "Epoch 501/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5182 - accuracy: 0.7537 - val_loss: 1.0859 - val_accuracy: 0.5352\n",
      "Epoch 502/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5287 - accuracy: 0.7566 - val_loss: 1.0912 - val_accuracy: 0.5352\n",
      "Epoch 503/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5201 - accuracy: 0.7830 - val_loss: 1.1001 - val_accuracy: 0.5211\n",
      "Epoch 504/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5264 - accuracy: 0.7683 - val_loss: 1.1013 - val_accuracy: 0.5211\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 505/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5229 - accuracy: 0.7742 - val_loss: 1.1076 - val_accuracy: 0.5211\n",
      "Epoch 506/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5250 - accuracy: 0.7566 - val_loss: 1.1126 - val_accuracy: 0.5352\n",
      "Epoch 507/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5324 - accuracy: 0.7654 - val_loss: 1.1079 - val_accuracy: 0.5211\n",
      "Epoch 508/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5137 - accuracy: 0.7771 - val_loss: 1.1074 - val_accuracy: 0.5352\n",
      "Epoch 509/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5218 - accuracy: 0.7625 - val_loss: 1.0938 - val_accuracy: 0.5352\n",
      "Epoch 510/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5282 - accuracy: 0.7507 - val_loss: 1.0925 - val_accuracy: 0.5352\n",
      "Epoch 511/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5149 - accuracy: 0.7742 - val_loss: 1.0827 - val_accuracy: 0.5493\n",
      "Epoch 512/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5133 - accuracy: 0.7771 - val_loss: 1.0837 - val_accuracy: 0.5352\n",
      "Epoch 513/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5254 - accuracy: 0.7683 - val_loss: 1.0796 - val_accuracy: 0.5493\n",
      "Epoch 514/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5168 - accuracy: 0.7742 - val_loss: 1.0694 - val_accuracy: 0.5493\n",
      "Epoch 515/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5253 - accuracy: 0.7537 - val_loss: 1.0725 - val_accuracy: 0.5493\n",
      "Epoch 516/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5111 - accuracy: 0.7595 - val_loss: 1.0810 - val_accuracy: 0.5493\n",
      "Epoch 517/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5156 - accuracy: 0.7742 - val_loss: 1.0844 - val_accuracy: 0.5493\n",
      "Epoch 518/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5174 - accuracy: 0.7595 - val_loss: 1.0900 - val_accuracy: 0.5352\n",
      "Epoch 519/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5216 - accuracy: 0.7625 - val_loss: 1.0983 - val_accuracy: 0.5352\n",
      "Epoch 520/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5211 - accuracy: 0.7566 - val_loss: 1.1006 - val_accuracy: 0.5352\n",
      "Epoch 521/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5125 - accuracy: 0.7742 - val_loss: 1.1070 - val_accuracy: 0.5352\n",
      "Epoch 522/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5130 - accuracy: 0.7713 - val_loss: 1.1137 - val_accuracy: 0.5493\n",
      "Epoch 523/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5129 - accuracy: 0.7361 - val_loss: 1.1069 - val_accuracy: 0.5352\n",
      "Epoch 524/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5135 - accuracy: 0.7654 - val_loss: 1.0978 - val_accuracy: 0.5352\n",
      "Epoch 525/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5140 - accuracy: 0.7713 - val_loss: 1.0891 - val_accuracy: 0.5352\n",
      "Epoch 526/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5078 - accuracy: 0.7742 - val_loss: 1.0860 - val_accuracy: 0.5493\n",
      "Epoch 527/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5132 - accuracy: 0.7683 - val_loss: 1.0862 - val_accuracy: 0.5493\n",
      "Epoch 528/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5120 - accuracy: 0.7771 - val_loss: 1.0930 - val_accuracy: 0.5352\n",
      "Epoch 529/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5147 - accuracy: 0.7713 - val_loss: 1.0889 - val_accuracy: 0.5352\n",
      "Epoch 530/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5137 - accuracy: 0.7771 - val_loss: 1.0938 - val_accuracy: 0.5352\n",
      "Epoch 531/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5076 - accuracy: 0.7830 - val_loss: 1.0978 - val_accuracy: 0.5352\n",
      "Epoch 532/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5216 - accuracy: 0.7566 - val_loss: 1.0946 - val_accuracy: 0.5352\n",
      "Epoch 533/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5139 - accuracy: 0.7771 - val_loss: 1.1086 - val_accuracy: 0.5493\n",
      "Epoch 534/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5127 - accuracy: 0.7830 - val_loss: 1.1221 - val_accuracy: 0.5493\n",
      "Epoch 535/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5054 - accuracy: 0.7771 - val_loss: 1.1207 - val_accuracy: 0.5493\n",
      "Epoch 536/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5068 - accuracy: 0.7742 - val_loss: 1.1137 - val_accuracy: 0.5493\n",
      "Epoch 537/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5129 - accuracy: 0.7713 - val_loss: 1.1048 - val_accuracy: 0.5493\n",
      "Epoch 538/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5110 - accuracy: 0.7654 - val_loss: 1.1109 - val_accuracy: 0.5493\n",
      "Epoch 539/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5028 - accuracy: 0.7859 - val_loss: 1.1058 - val_accuracy: 0.5493\n",
      "Epoch 540/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5048 - accuracy: 0.7889 - val_loss: 1.1092 - val_accuracy: 0.5493\n",
      "Epoch 541/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5051 - accuracy: 0.7830 - val_loss: 1.1161 - val_accuracy: 0.5493\n",
      "Epoch 542/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5070 - accuracy: 0.7918 - val_loss: 1.1104 - val_accuracy: 0.5493\n",
      "Epoch 543/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5041 - accuracy: 0.7771 - val_loss: 1.1172 - val_accuracy: 0.5493\n",
      "Epoch 544/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5029 - accuracy: 0.7918 - val_loss: 1.1234 - val_accuracy: 0.5493\n",
      "Epoch 545/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5058 - accuracy: 0.7742 - val_loss: 1.1202 - val_accuracy: 0.5493\n",
      "Epoch 546/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5032 - accuracy: 0.7977 - val_loss: 1.1249 - val_accuracy: 0.5493\n",
      "Epoch 547/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5084 - accuracy: 0.7654 - val_loss: 1.1292 - val_accuracy: 0.5493\n",
      "Epoch 548/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5053 - accuracy: 0.7771 - val_loss: 1.1247 - val_accuracy: 0.5493\n",
      "Epoch 549/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4976 - accuracy: 0.7801 - val_loss: 1.1170 - val_accuracy: 0.5493\n",
      "Epoch 550/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5118 - accuracy: 0.7683 - val_loss: 1.1155 - val_accuracy: 0.5493\n",
      "Epoch 551/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5017 - accuracy: 0.7859 - val_loss: 1.0994 - val_accuracy: 0.5634\n",
      "Epoch 552/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5012 - accuracy: 0.7830 - val_loss: 1.0901 - val_accuracy: 0.5493\n",
      "Epoch 553/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5018 - accuracy: 0.7742 - val_loss: 1.0958 - val_accuracy: 0.5634\n",
      "Epoch 554/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5031 - accuracy: 0.7771 - val_loss: 1.1066 - val_accuracy: 0.5493\n",
      "Epoch 555/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5088 - accuracy: 0.7654 - val_loss: 1.1190 - val_accuracy: 0.5493\n",
      "Epoch 556/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4969 - accuracy: 0.7859 - val_loss: 1.1258 - val_accuracy: 0.5493\n",
      "Epoch 557/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5056 - accuracy: 0.7771 - val_loss: 1.1265 - val_accuracy: 0.5493\n",
      "Epoch 558/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5005 - accuracy: 0.7889 - val_loss: 1.1357 - val_accuracy: 0.5493\n",
      "Epoch 559/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5025 - accuracy: 0.7566 - val_loss: 1.1388 - val_accuracy: 0.5493\n",
      "Epoch 560/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4977 - accuracy: 0.7947 - val_loss: 1.1452 - val_accuracy: 0.5493\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 561/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4997 - accuracy: 0.7859 - val_loss: 1.1536 - val_accuracy: 0.5493\n",
      "Epoch 562/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4944 - accuracy: 0.7889 - val_loss: 1.1473 - val_accuracy: 0.5493\n",
      "Epoch 563/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4962 - accuracy: 0.7801 - val_loss: 1.1693 - val_accuracy: 0.5352\n",
      "Epoch 564/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4951 - accuracy: 0.7801 - val_loss: 1.1685 - val_accuracy: 0.5352\n",
      "Epoch 565/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4994 - accuracy: 0.7830 - val_loss: 1.1500 - val_accuracy: 0.5493\n",
      "Epoch 566/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5007 - accuracy: 0.7918 - val_loss: 1.1500 - val_accuracy: 0.5493\n",
      "Epoch 567/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4896 - accuracy: 0.8094 - val_loss: 1.1513 - val_accuracy: 0.5493\n",
      "Epoch 568/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4950 - accuracy: 0.7889 - val_loss: 1.1447 - val_accuracy: 0.5493\n",
      "Epoch 569/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5032 - accuracy: 0.7625 - val_loss: 1.1324 - val_accuracy: 0.5493\n",
      "Epoch 570/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4953 - accuracy: 0.7947 - val_loss: 1.1285 - val_accuracy: 0.5493\n",
      "Epoch 571/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4908 - accuracy: 0.7918 - val_loss: 1.1202 - val_accuracy: 0.5493\n",
      "Epoch 572/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4953 - accuracy: 0.7742 - val_loss: 1.1239 - val_accuracy: 0.5493\n",
      "Epoch 573/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4966 - accuracy: 0.7830 - val_loss: 1.1221 - val_accuracy: 0.5493\n",
      "Epoch 574/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4963 - accuracy: 0.7830 - val_loss: 1.1169 - val_accuracy: 0.5493\n",
      "Epoch 575/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4970 - accuracy: 0.7947 - val_loss: 1.1205 - val_accuracy: 0.5493\n",
      "Epoch 576/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4937 - accuracy: 0.7889 - val_loss: 1.1283 - val_accuracy: 0.5493\n",
      "Epoch 577/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4876 - accuracy: 0.7889 - val_loss: 1.1267 - val_accuracy: 0.5493\n",
      "Epoch 578/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4903 - accuracy: 0.7859 - val_loss: 1.1453 - val_accuracy: 0.5493\n",
      "Epoch 579/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4865 - accuracy: 0.7918 - val_loss: 1.1537 - val_accuracy: 0.5352\n",
      "Epoch 580/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.4957 - accuracy: 0.7801 - val_loss: 1.1561 - val_accuracy: 0.5352\n",
      "Epoch 581/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4892 - accuracy: 0.7889 - val_loss: 1.1558 - val_accuracy: 0.5352\n",
      "Epoch 582/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4853 - accuracy: 0.7918 - val_loss: 1.1528 - val_accuracy: 0.5352\n",
      "Epoch 583/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4974 - accuracy: 0.8006 - val_loss: 1.1413 - val_accuracy: 0.5493\n",
      "Epoch 584/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4903 - accuracy: 0.7801 - val_loss: 1.1357 - val_accuracy: 0.5493\n",
      "Epoch 585/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.5026 - accuracy: 0.7918 - val_loss: 1.1336 - val_accuracy: 0.5493\n",
      "Epoch 586/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4858 - accuracy: 0.8152 - val_loss: 1.1268 - val_accuracy: 0.5493\n",
      "Epoch 587/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4929 - accuracy: 0.7977 - val_loss: 1.1267 - val_accuracy: 0.5493\n",
      "Epoch 588/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4879 - accuracy: 0.8035 - val_loss: 1.1262 - val_accuracy: 0.5493\n",
      "Epoch 589/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4978 - accuracy: 0.7713 - val_loss: 1.1238 - val_accuracy: 0.5493\n",
      "Epoch 590/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4924 - accuracy: 0.7859 - val_loss: 1.1089 - val_accuracy: 0.5493\n",
      "Epoch 591/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4852 - accuracy: 0.8035 - val_loss: 1.1110 - val_accuracy: 0.5493\n",
      "Epoch 592/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4879 - accuracy: 0.7977 - val_loss: 1.1114 - val_accuracy: 0.5493\n",
      "Epoch 593/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4909 - accuracy: 0.7830 - val_loss: 1.1246 - val_accuracy: 0.5493\n",
      "Epoch 594/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4846 - accuracy: 0.8065 - val_loss: 1.1332 - val_accuracy: 0.5493\n",
      "Epoch 595/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4824 - accuracy: 0.8152 - val_loss: 1.1407 - val_accuracy: 0.5493\n",
      "Epoch 596/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4892 - accuracy: 0.7801 - val_loss: 1.1410 - val_accuracy: 0.5493\n",
      "Epoch 597/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4898 - accuracy: 0.8123 - val_loss: 1.1373 - val_accuracy: 0.5493\n",
      "Epoch 598/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4825 - accuracy: 0.8094 - val_loss: 1.1319 - val_accuracy: 0.5493\n",
      "Epoch 599/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4843 - accuracy: 0.8094 - val_loss: 1.1245 - val_accuracy: 0.5493\n",
      "Epoch 600/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4843 - accuracy: 0.8006 - val_loss: 1.1091 - val_accuracy: 0.5493\n",
      "Epoch 601/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4833 - accuracy: 0.8035 - val_loss: 1.1124 - val_accuracy: 0.5493\n",
      "Epoch 602/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4983 - accuracy: 0.7947 - val_loss: 1.1183 - val_accuracy: 0.5493\n",
      "Epoch 603/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4787 - accuracy: 0.8211 - val_loss: 1.1216 - val_accuracy: 0.5493\n",
      "Epoch 604/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4832 - accuracy: 0.7889 - val_loss: 1.1149 - val_accuracy: 0.5493\n",
      "Epoch 605/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4790 - accuracy: 0.8006 - val_loss: 1.1199 - val_accuracy: 0.5493\n",
      "Epoch 606/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4794 - accuracy: 0.7889 - val_loss: 1.1345 - val_accuracy: 0.5493\n",
      "Epoch 607/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4767 - accuracy: 0.8065 - val_loss: 1.1397 - val_accuracy: 0.5493\n",
      "Epoch 608/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4817 - accuracy: 0.8065 - val_loss: 1.1365 - val_accuracy: 0.5493\n",
      "Epoch 609/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4807 - accuracy: 0.7918 - val_loss: 1.1237 - val_accuracy: 0.5493\n",
      "Epoch 610/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4795 - accuracy: 0.8094 - val_loss: 1.1360 - val_accuracy: 0.5352\n",
      "Epoch 611/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4833 - accuracy: 0.8035 - val_loss: 1.1421 - val_accuracy: 0.5352\n",
      "Epoch 612/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4802 - accuracy: 0.8035 - val_loss: 1.1434 - val_accuracy: 0.5493\n",
      "Epoch 613/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4793 - accuracy: 0.8006 - val_loss: 1.1496 - val_accuracy: 0.5493\n",
      "Epoch 614/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4817 - accuracy: 0.7918 - val_loss: 1.1548 - val_accuracy: 0.5493\n",
      "Epoch 615/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4802 - accuracy: 0.7889 - val_loss: 1.1645 - val_accuracy: 0.5634\n",
      "Epoch 616/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4860 - accuracy: 0.7918 - val_loss: 1.1649 - val_accuracy: 0.5634\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 617/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4778 - accuracy: 0.8065 - val_loss: 1.1635 - val_accuracy: 0.5634\n",
      "Epoch 618/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4739 - accuracy: 0.7947 - val_loss: 1.1441 - val_accuracy: 0.5493\n",
      "Epoch 619/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4755 - accuracy: 0.7947 - val_loss: 1.1394 - val_accuracy: 0.5493\n",
      "Epoch 620/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4790 - accuracy: 0.8094 - val_loss: 1.1183 - val_accuracy: 0.5634\n",
      "Epoch 621/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4836 - accuracy: 0.7977 - val_loss: 1.0903 - val_accuracy: 0.5775\n",
      "Epoch 622/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4931 - accuracy: 0.7889 - val_loss: 1.0638 - val_accuracy: 0.5634\n",
      "Epoch 623/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4762 - accuracy: 0.8006 - val_loss: 1.0561 - val_accuracy: 0.5775\n",
      "Epoch 624/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4713 - accuracy: 0.8065 - val_loss: 1.0411 - val_accuracy: 0.5775\n",
      "Epoch 625/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4811 - accuracy: 0.8065 - val_loss: 1.0594 - val_accuracy: 0.5634\n",
      "Epoch 626/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4700 - accuracy: 0.7977 - val_loss: 1.0746 - val_accuracy: 0.5634\n",
      "Epoch 627/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4696 - accuracy: 0.8182 - val_loss: 1.0759 - val_accuracy: 0.5634\n",
      "Epoch 628/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4702 - accuracy: 0.8211 - val_loss: 1.0637 - val_accuracy: 0.5634\n",
      "Epoch 629/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4771 - accuracy: 0.8035 - val_loss: 1.0582 - val_accuracy: 0.5775\n",
      "Epoch 630/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4798 - accuracy: 0.8065 - val_loss: 1.0556 - val_accuracy: 0.5775\n",
      "Epoch 631/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4774 - accuracy: 0.8094 - val_loss: 1.0439 - val_accuracy: 0.5775\n",
      "Epoch 632/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4741 - accuracy: 0.8123 - val_loss: 1.0408 - val_accuracy: 0.5775\n",
      "Epoch 633/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4818 - accuracy: 0.7977 - val_loss: 1.0392 - val_accuracy: 0.5775\n",
      "Epoch 634/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4775 - accuracy: 0.8123 - val_loss: 1.0398 - val_accuracy: 0.5775\n",
      "Epoch 635/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4790 - accuracy: 0.7977 - val_loss: 1.0358 - val_accuracy: 0.5915\n",
      "Epoch 636/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4730 - accuracy: 0.8065 - val_loss: 1.0228 - val_accuracy: 0.5915\n",
      "Epoch 637/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4729 - accuracy: 0.8065 - val_loss: 1.0210 - val_accuracy: 0.5915\n",
      "Epoch 638/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4725 - accuracy: 0.7947 - val_loss: 1.0362 - val_accuracy: 0.5915\n",
      "Epoch 639/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4695 - accuracy: 0.8240 - val_loss: 1.0559 - val_accuracy: 0.5915\n",
      "Epoch 640/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4687 - accuracy: 0.7889 - val_loss: 1.0617 - val_accuracy: 0.5775\n",
      "Epoch 641/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4852 - accuracy: 0.8065 - val_loss: 1.0626 - val_accuracy: 0.5775\n",
      "Epoch 642/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4781 - accuracy: 0.8006 - val_loss: 1.0724 - val_accuracy: 0.5775\n",
      "Epoch 643/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4648 - accuracy: 0.8035 - val_loss: 1.0810 - val_accuracy: 0.5775\n",
      "Epoch 644/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4740 - accuracy: 0.8094 - val_loss: 1.0858 - val_accuracy: 0.5775\n",
      "Epoch 645/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.4634 - accuracy: 0.8240 - val_loss: 1.0873 - val_accuracy: 0.5775\n",
      "Epoch 646/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4677 - accuracy: 0.8182 - val_loss: 1.0824 - val_accuracy: 0.5775\n",
      "Epoch 647/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4705 - accuracy: 0.7977 - val_loss: 1.0798 - val_accuracy: 0.5775\n",
      "Epoch 648/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4720 - accuracy: 0.8152 - val_loss: 1.0846 - val_accuracy: 0.5775\n",
      "Epoch 649/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4825 - accuracy: 0.8094 - val_loss: 1.0799 - val_accuracy: 0.5634\n",
      "Epoch 650/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4683 - accuracy: 0.8211 - val_loss: 1.0775 - val_accuracy: 0.5634\n",
      "Epoch 651/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4611 - accuracy: 0.8182 - val_loss: 1.0803 - val_accuracy: 0.5634\n",
      "Epoch 652/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4713 - accuracy: 0.8035 - val_loss: 1.0779 - val_accuracy: 0.5634\n",
      "Epoch 653/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.4651 - accuracy: 0.8065 - val_loss: 1.0859 - val_accuracy: 0.5634\n",
      "Epoch 654/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4630 - accuracy: 0.8182 - val_loss: 1.0766 - val_accuracy: 0.5634\n",
      "Epoch 655/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4709 - accuracy: 0.7947 - val_loss: 1.0830 - val_accuracy: 0.5634\n",
      "Epoch 656/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4704 - accuracy: 0.8270 - val_loss: 1.1000 - val_accuracy: 0.5775\n",
      "Epoch 657/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4620 - accuracy: 0.8123 - val_loss: 1.0981 - val_accuracy: 0.5634\n",
      "Epoch 658/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4636 - accuracy: 0.8065 - val_loss: 1.1023 - val_accuracy: 0.5634\n",
      "Epoch 659/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4621 - accuracy: 0.8152 - val_loss: 1.1020 - val_accuracy: 0.5634\n",
      "Epoch 660/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4626 - accuracy: 0.8211 - val_loss: 1.0949 - val_accuracy: 0.5634\n",
      "Epoch 661/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4746 - accuracy: 0.8006 - val_loss: 1.0898 - val_accuracy: 0.5634\n",
      "Epoch 662/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4702 - accuracy: 0.7889 - val_loss: 1.0884 - val_accuracy: 0.5634\n",
      "Epoch 663/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4730 - accuracy: 0.8123 - val_loss: 1.0862 - val_accuracy: 0.5634\n",
      "Epoch 664/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4699 - accuracy: 0.8035 - val_loss: 1.0829 - val_accuracy: 0.5634\n",
      "Epoch 665/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4662 - accuracy: 0.8270 - val_loss: 1.0813 - val_accuracy: 0.5634\n",
      "Epoch 666/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4658 - accuracy: 0.8182 - val_loss: 1.0928 - val_accuracy: 0.5634\n",
      "Epoch 667/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4596 - accuracy: 0.8358 - val_loss: 1.0993 - val_accuracy: 0.5634\n",
      "Epoch 668/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4700 - accuracy: 0.8152 - val_loss: 1.0968 - val_accuracy: 0.5634\n",
      "Epoch 669/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4602 - accuracy: 0.8299 - val_loss: 1.1004 - val_accuracy: 0.5775\n",
      "Epoch 670/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4636 - accuracy: 0.8270 - val_loss: 1.1065 - val_accuracy: 0.5634\n",
      "Epoch 671/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4651 - accuracy: 0.8240 - val_loss: 1.1167 - val_accuracy: 0.5634\n",
      "Epoch 672/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4682 - accuracy: 0.8211 - val_loss: 1.0924 - val_accuracy: 0.5775\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 673/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4624 - accuracy: 0.8270 - val_loss: 1.0653 - val_accuracy: 0.5775\n",
      "Epoch 674/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4588 - accuracy: 0.8211 - val_loss: 1.0610 - val_accuracy: 0.5775\n",
      "Epoch 675/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4610 - accuracy: 0.8240 - val_loss: 1.0593 - val_accuracy: 0.5775\n",
      "Epoch 676/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4571 - accuracy: 0.8152 - val_loss: 1.0499 - val_accuracy: 0.5775\n",
      "Epoch 677/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4669 - accuracy: 0.8152 - val_loss: 1.0535 - val_accuracy: 0.5775\n",
      "Epoch 678/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4582 - accuracy: 0.8299 - val_loss: 1.0646 - val_accuracy: 0.5775\n",
      "Epoch 679/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4611 - accuracy: 0.8240 - val_loss: 1.0655 - val_accuracy: 0.5775\n",
      "Epoch 680/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4580 - accuracy: 0.8240 - val_loss: 1.0627 - val_accuracy: 0.5775\n",
      "Epoch 681/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4704 - accuracy: 0.8211 - val_loss: 1.0663 - val_accuracy: 0.5775\n",
      "Epoch 682/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4556 - accuracy: 0.8446 - val_loss: 1.0729 - val_accuracy: 0.5775\n",
      "Epoch 683/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4524 - accuracy: 0.8416 - val_loss: 1.0752 - val_accuracy: 0.5775\n",
      "Epoch 684/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4512 - accuracy: 0.8358 - val_loss: 1.0742 - val_accuracy: 0.5775\n",
      "Epoch 685/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4574 - accuracy: 0.8211 - val_loss: 1.0826 - val_accuracy: 0.5634\n",
      "Epoch 686/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4601 - accuracy: 0.8299 - val_loss: 1.0890 - val_accuracy: 0.5493\n",
      "Epoch 687/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4555 - accuracy: 0.8152 - val_loss: 1.0945 - val_accuracy: 0.5493\n",
      "Epoch 688/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4672 - accuracy: 0.8240 - val_loss: 1.0837 - val_accuracy: 0.5634\n",
      "Epoch 689/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4571 - accuracy: 0.8387 - val_loss: 1.0800 - val_accuracy: 0.5634\n",
      "Epoch 690/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4616 - accuracy: 0.8328 - val_loss: 1.0906 - val_accuracy: 0.5493\n",
      "Epoch 691/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4508 - accuracy: 0.8416 - val_loss: 1.0988 - val_accuracy: 0.5634\n",
      "Epoch 692/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4725 - accuracy: 0.8270 - val_loss: 1.0907 - val_accuracy: 0.5634\n",
      "Epoch 693/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4534 - accuracy: 0.8270 - val_loss: 1.1011 - val_accuracy: 0.5634\n",
      "Epoch 694/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4562 - accuracy: 0.8240 - val_loss: 1.1001 - val_accuracy: 0.5634\n",
      "Epoch 695/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4586 - accuracy: 0.8211 - val_loss: 1.0907 - val_accuracy: 0.5634\n",
      "Epoch 696/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4605 - accuracy: 0.8328 - val_loss: 1.0801 - val_accuracy: 0.5634\n",
      "Epoch 697/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4593 - accuracy: 0.8182 - val_loss: 1.0736 - val_accuracy: 0.5634\n",
      "Epoch 698/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4625 - accuracy: 0.8270 - val_loss: 1.0778 - val_accuracy: 0.5634\n",
      "Epoch 699/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4542 - accuracy: 0.8387 - val_loss: 1.0805 - val_accuracy: 0.5634\n",
      "Epoch 700/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4704 - accuracy: 0.8035 - val_loss: 1.0793 - val_accuracy: 0.5634\n",
      "Epoch 701/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4612 - accuracy: 0.8182 - val_loss: 1.0965 - val_accuracy: 0.5634\n",
      "Epoch 702/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4680 - accuracy: 0.8094 - val_loss: 1.0982 - val_accuracy: 0.5634\n",
      "Epoch 703/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4536 - accuracy: 0.8299 - val_loss: 1.0911 - val_accuracy: 0.5775\n",
      "Epoch 704/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4529 - accuracy: 0.8358 - val_loss: 1.0930 - val_accuracy: 0.5775\n",
      "Epoch 705/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4603 - accuracy: 0.8182 - val_loss: 1.0916 - val_accuracy: 0.5634\n",
      "Epoch 706/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4556 - accuracy: 0.8240 - val_loss: 1.0761 - val_accuracy: 0.5634\n",
      "Epoch 707/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4608 - accuracy: 0.8358 - val_loss: 1.0755 - val_accuracy: 0.5634\n",
      "Epoch 708/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4495 - accuracy: 0.8416 - val_loss: 1.0739 - val_accuracy: 0.5634\n",
      "Epoch 709/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4601 - accuracy: 0.8123 - val_loss: 1.0810 - val_accuracy: 0.5634\n",
      "Epoch 710/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4651 - accuracy: 0.8182 - val_loss: 1.0766 - val_accuracy: 0.5634\n",
      "Epoch 711/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4500 - accuracy: 0.8240 - val_loss: 1.0794 - val_accuracy: 0.5634\n",
      "Epoch 712/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4495 - accuracy: 0.8387 - val_loss: 1.0758 - val_accuracy: 0.5775\n",
      "Epoch 713/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4490 - accuracy: 0.8211 - val_loss: 1.0772 - val_accuracy: 0.5775\n",
      "Epoch 714/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4499 - accuracy: 0.8240 - val_loss: 1.0764 - val_accuracy: 0.5775\n",
      "Epoch 715/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4492 - accuracy: 0.8416 - val_loss: 1.0739 - val_accuracy: 0.5775\n",
      "Epoch 716/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4500 - accuracy: 0.8387 - val_loss: 1.0736 - val_accuracy: 0.5775\n",
      "Epoch 717/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4569 - accuracy: 0.7977 - val_loss: 1.0719 - val_accuracy: 0.5775\n",
      "Epoch 718/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4523 - accuracy: 0.8299 - val_loss: 1.0681 - val_accuracy: 0.5775\n",
      "Epoch 719/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4508 - accuracy: 0.8328 - val_loss: 1.0804 - val_accuracy: 0.5634\n",
      "Epoch 720/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4556 - accuracy: 0.8387 - val_loss: 1.0697 - val_accuracy: 0.5775\n",
      "Epoch 721/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4451 - accuracy: 0.8328 - val_loss: 1.0623 - val_accuracy: 0.5775\n",
      "Epoch 722/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4552 - accuracy: 0.8211 - val_loss: 1.0597 - val_accuracy: 0.5775\n",
      "Epoch 723/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4422 - accuracy: 0.8270 - val_loss: 1.0588 - val_accuracy: 0.5775\n",
      "Epoch 724/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4510 - accuracy: 0.8328 - val_loss: 1.0539 - val_accuracy: 0.5775\n",
      "Epoch 725/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4501 - accuracy: 0.8270 - val_loss: 1.0550 - val_accuracy: 0.5775\n",
      "Epoch 726/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4441 - accuracy: 0.8475 - val_loss: 1.0572 - val_accuracy: 0.5775\n",
      "Epoch 727/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4536 - accuracy: 0.8299 - val_loss: 1.0707 - val_accuracy: 0.5775\n",
      "Epoch 728/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4400 - accuracy: 0.8534 - val_loss: 1.0829 - val_accuracy: 0.5634\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 729/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4555 - accuracy: 0.8152 - val_loss: 1.0841 - val_accuracy: 0.5634\n",
      "Epoch 730/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4555 - accuracy: 0.8182 - val_loss: 1.0793 - val_accuracy: 0.5634\n",
      "Epoch 731/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4501 - accuracy: 0.8446 - val_loss: 1.0780 - val_accuracy: 0.5634\n",
      "Epoch 732/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4623 - accuracy: 0.8006 - val_loss: 1.0982 - val_accuracy: 0.5634\n",
      "Epoch 733/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4465 - accuracy: 0.8270 - val_loss: 1.0973 - val_accuracy: 0.5634\n",
      "Epoch 734/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4518 - accuracy: 0.8299 - val_loss: 1.0832 - val_accuracy: 0.5634\n",
      "Epoch 735/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4505 - accuracy: 0.8240 - val_loss: 1.0592 - val_accuracy: 0.5915\n",
      "Epoch 736/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4496 - accuracy: 0.8152 - val_loss: 1.0586 - val_accuracy: 0.5775\n",
      "Epoch 737/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4446 - accuracy: 0.8328 - val_loss: 1.0500 - val_accuracy: 0.5775\n",
      "Epoch 738/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4490 - accuracy: 0.8152 - val_loss: 1.0373 - val_accuracy: 0.5775\n",
      "Epoch 739/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4487 - accuracy: 0.8123 - val_loss: 1.0332 - val_accuracy: 0.5775\n",
      "Epoch 740/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4475 - accuracy: 0.8270 - val_loss: 1.0279 - val_accuracy: 0.5775\n",
      "Epoch 741/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4457 - accuracy: 0.8182 - val_loss: 1.0472 - val_accuracy: 0.5775\n",
      "Epoch 742/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4453 - accuracy: 0.8446 - val_loss: 1.0540 - val_accuracy: 0.5775\n",
      "Epoch 743/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4474 - accuracy: 0.8299 - val_loss: 1.0455 - val_accuracy: 0.5775\n",
      "Epoch 744/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4456 - accuracy: 0.8299 - val_loss: 1.0527 - val_accuracy: 0.5775\n",
      "Epoch 745/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4559 - accuracy: 0.8211 - val_loss: 1.0300 - val_accuracy: 0.5775\n",
      "Epoch 746/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4535 - accuracy: 0.8387 - val_loss: 1.0254 - val_accuracy: 0.5775\n",
      "Epoch 747/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4456 - accuracy: 0.8446 - val_loss: 1.0218 - val_accuracy: 0.5775\n",
      "Epoch 748/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4344 - accuracy: 0.8475 - val_loss: 1.0260 - val_accuracy: 0.5775\n",
      "Epoch 749/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4462 - accuracy: 0.8358 - val_loss: 1.0243 - val_accuracy: 0.5775\n",
      "Epoch 750/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4484 - accuracy: 0.8387 - val_loss: 1.0422 - val_accuracy: 0.5775\n",
      "Epoch 751/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4553 - accuracy: 0.8328 - val_loss: 1.0425 - val_accuracy: 0.5775\n",
      "Epoch 752/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4476 - accuracy: 0.8240 - val_loss: 1.0408 - val_accuracy: 0.5775\n",
      "Epoch 753/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4410 - accuracy: 0.8446 - val_loss: 1.0415 - val_accuracy: 0.5775\n",
      "Epoch 754/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4412 - accuracy: 0.8358 - val_loss: 1.0517 - val_accuracy: 0.5775\n",
      "Epoch 755/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4407 - accuracy: 0.8446 - val_loss: 1.0546 - val_accuracy: 0.5915\n",
      "Epoch 756/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4408 - accuracy: 0.8475 - val_loss: 1.0555 - val_accuracy: 0.5775\n",
      "Epoch 757/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4432 - accuracy: 0.8416 - val_loss: 1.0567 - val_accuracy: 0.5775\n",
      "Epoch 758/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4446 - accuracy: 0.8270 - val_loss: 1.0640 - val_accuracy: 0.5915\n",
      "Epoch 759/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4478 - accuracy: 0.8123 - val_loss: 1.0748 - val_accuracy: 0.5775\n",
      "Epoch 760/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4417 - accuracy: 0.8416 - val_loss: 1.0650 - val_accuracy: 0.5915\n",
      "Epoch 761/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4446 - accuracy: 0.8299 - val_loss: 1.0594 - val_accuracy: 0.5775\n",
      "Epoch 762/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4486 - accuracy: 0.8534 - val_loss: 1.0435 - val_accuracy: 0.5775\n",
      "Epoch 763/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4446 - accuracy: 0.8240 - val_loss: 1.0490 - val_accuracy: 0.5775\n",
      "Epoch 764/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4361 - accuracy: 0.8622 - val_loss: 1.0446 - val_accuracy: 0.5775\n",
      "Epoch 765/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4385 - accuracy: 0.8504 - val_loss: 1.0292 - val_accuracy: 0.5775\n",
      "Epoch 766/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4449 - accuracy: 0.8358 - val_loss: 1.0274 - val_accuracy: 0.5775\n",
      "Epoch 767/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4386 - accuracy: 0.8240 - val_loss: 1.0244 - val_accuracy: 0.5775\n",
      "Epoch 768/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4489 - accuracy: 0.8299 - val_loss: 1.0301 - val_accuracy: 0.5775\n",
      "Epoch 769/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4444 - accuracy: 0.8504 - val_loss: 1.0472 - val_accuracy: 0.5775\n",
      "Epoch 770/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4444 - accuracy: 0.8328 - val_loss: 1.0598 - val_accuracy: 0.5915\n",
      "Epoch 771/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4501 - accuracy: 0.8270 - val_loss: 1.0546 - val_accuracy: 0.5775\n",
      "Epoch 772/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4396 - accuracy: 0.8328 - val_loss: 1.0497 - val_accuracy: 0.5775\n",
      "Epoch 773/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4423 - accuracy: 0.8328 - val_loss: 1.0482 - val_accuracy: 0.5775\n",
      "Epoch 774/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4507 - accuracy: 0.8182 - val_loss: 1.0501 - val_accuracy: 0.5775\n",
      "Epoch 775/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4417 - accuracy: 0.8152 - val_loss: 1.0516 - val_accuracy: 0.5775\n",
      "Epoch 776/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4408 - accuracy: 0.8328 - val_loss: 1.0648 - val_accuracy: 0.5915\n",
      "Epoch 777/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.4364 - accuracy: 0.8475 - val_loss: 1.0671 - val_accuracy: 0.5915\n",
      "Epoch 778/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4445 - accuracy: 0.8123 - val_loss: 1.0703 - val_accuracy: 0.5915\n",
      "Epoch 779/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4424 - accuracy: 0.8504 - val_loss: 1.0766 - val_accuracy: 0.5775\n",
      "Epoch 780/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4413 - accuracy: 0.8416 - val_loss: 1.0875 - val_accuracy: 0.5775\n",
      "Epoch 781/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4340 - accuracy: 0.8328 - val_loss: 1.0967 - val_accuracy: 0.5493\n",
      "Epoch 782/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4405 - accuracy: 0.8387 - val_loss: 1.1098 - val_accuracy: 0.5493\n",
      "Epoch 783/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4344 - accuracy: 0.8387 - val_loss: 1.1105 - val_accuracy: 0.5493\n",
      "Epoch 784/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4354 - accuracy: 0.8416 - val_loss: 1.1125 - val_accuracy: 0.5493\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 785/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4327 - accuracy: 0.8387 - val_loss: 1.1098 - val_accuracy: 0.5493\n",
      "Epoch 786/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4431 - accuracy: 0.8270 - val_loss: 1.1075 - val_accuracy: 0.5493\n",
      "Epoch 787/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4366 - accuracy: 0.8299 - val_loss: 1.1187 - val_accuracy: 0.5493\n",
      "Epoch 788/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4450 - accuracy: 0.8211 - val_loss: 1.1150 - val_accuracy: 0.5493\n",
      "Epoch 789/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4380 - accuracy: 0.8446 - val_loss: 1.1087 - val_accuracy: 0.5493\n",
      "Epoch 790/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4357 - accuracy: 0.8328 - val_loss: 1.1044 - val_accuracy: 0.5493\n",
      "Epoch 791/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4474 - accuracy: 0.8387 - val_loss: 1.0958 - val_accuracy: 0.5493\n",
      "Epoch 792/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4342 - accuracy: 0.8475 - val_loss: 1.0890 - val_accuracy: 0.5493\n",
      "Epoch 793/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4359 - accuracy: 0.8328 - val_loss: 1.0793 - val_accuracy: 0.5634\n",
      "Epoch 794/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4336 - accuracy: 0.8475 - val_loss: 1.0809 - val_accuracy: 0.5634\n",
      "Epoch 795/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4342 - accuracy: 0.8534 - val_loss: 1.0804 - val_accuracy: 0.5634\n",
      "Epoch 796/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4328 - accuracy: 0.8534 - val_loss: 1.0764 - val_accuracy: 0.5775\n",
      "Epoch 797/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4408 - accuracy: 0.8299 - val_loss: 1.0740 - val_accuracy: 0.5915\n",
      "Epoch 798/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4341 - accuracy: 0.8475 - val_loss: 1.0655 - val_accuracy: 0.5915\n",
      "Epoch 799/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4435 - accuracy: 0.8299 - val_loss: 1.0695 - val_accuracy: 0.5915\n",
      "Epoch 800/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4344 - accuracy: 0.8534 - val_loss: 1.0739 - val_accuracy: 0.5915\n",
      "Epoch 801/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4375 - accuracy: 0.8504 - val_loss: 1.0815 - val_accuracy: 0.5634\n",
      "Epoch 802/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4446 - accuracy: 0.8328 - val_loss: 1.0643 - val_accuracy: 0.5915\n",
      "Epoch 803/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4336 - accuracy: 0.8416 - val_loss: 1.0619 - val_accuracy: 0.5915\n",
      "Epoch 804/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4374 - accuracy: 0.8299 - val_loss: 1.0634 - val_accuracy: 0.5915\n",
      "Epoch 805/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4342 - accuracy: 0.8475 - val_loss: 1.0582 - val_accuracy: 0.5915\n",
      "Epoch 806/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4390 - accuracy: 0.8358 - val_loss: 1.0696 - val_accuracy: 0.5775\n",
      "Epoch 807/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4386 - accuracy: 0.8446 - val_loss: 1.0580 - val_accuracy: 0.5915\n",
      "Epoch 808/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4370 - accuracy: 0.8358 - val_loss: 1.0512 - val_accuracy: 0.5915\n",
      "Epoch 809/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4320 - accuracy: 0.8270 - val_loss: 1.0566 - val_accuracy: 0.5915\n",
      "Epoch 810/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4328 - accuracy: 0.8358 - val_loss: 1.0669 - val_accuracy: 0.5775\n",
      "Epoch 811/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4335 - accuracy: 0.8446 - val_loss: 1.0621 - val_accuracy: 0.5915\n",
      "Epoch 812/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4300 - accuracy: 0.8328 - val_loss: 1.0538 - val_accuracy: 0.5915\n",
      "Epoch 813/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4424 - accuracy: 0.8240 - val_loss: 1.0626 - val_accuracy: 0.5915\n",
      "Epoch 814/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4343 - accuracy: 0.8446 - val_loss: 1.0756 - val_accuracy: 0.5775\n",
      "Epoch 815/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4384 - accuracy: 0.8358 - val_loss: 1.0763 - val_accuracy: 0.5775\n",
      "Epoch 816/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4339 - accuracy: 0.8563 - val_loss: 1.0777 - val_accuracy: 0.5775\n",
      "Epoch 817/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4348 - accuracy: 0.8299 - val_loss: 1.0811 - val_accuracy: 0.5634\n",
      "Epoch 818/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4491 - accuracy: 0.8240 - val_loss: 1.0851 - val_accuracy: 0.5634\n",
      "Epoch 819/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4316 - accuracy: 0.8387 - val_loss: 1.0829 - val_accuracy: 0.5634\n",
      "Epoch 820/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4277 - accuracy: 0.8387 - val_loss: 1.0729 - val_accuracy: 0.5775\n",
      "Epoch 821/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4374 - accuracy: 0.8563 - val_loss: 1.0638 - val_accuracy: 0.5915\n",
      "Epoch 822/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4341 - accuracy: 0.8446 - val_loss: 1.0429 - val_accuracy: 0.5915\n",
      "Epoch 823/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4379 - accuracy: 0.8416 - val_loss: 1.0442 - val_accuracy: 0.5915\n",
      "Epoch 824/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4397 - accuracy: 0.8416 - val_loss: 1.0427 - val_accuracy: 0.5915\n",
      "Epoch 825/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4392 - accuracy: 0.8358 - val_loss: 1.0335 - val_accuracy: 0.5775\n",
      "Epoch 826/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4330 - accuracy: 0.8416 - val_loss: 1.0401 - val_accuracy: 0.5775\n",
      "Epoch 827/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4396 - accuracy: 0.8504 - val_loss: 1.0442 - val_accuracy: 0.5915\n",
      "Epoch 828/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4329 - accuracy: 0.8534 - val_loss: 1.0509 - val_accuracy: 0.5915\n",
      "Epoch 829/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4372 - accuracy: 0.8534 - val_loss: 1.0670 - val_accuracy: 0.5915\n",
      "Epoch 830/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4334 - accuracy: 0.8504 - val_loss: 1.0875 - val_accuracy: 0.5634\n",
      "Epoch 831/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4292 - accuracy: 0.8504 - val_loss: 1.1050 - val_accuracy: 0.5493\n",
      "Epoch 832/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4340 - accuracy: 0.8504 - val_loss: 1.1019 - val_accuracy: 0.5493\n",
      "Epoch 833/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4324 - accuracy: 0.8475 - val_loss: 1.1021 - val_accuracy: 0.5493\n",
      "Epoch 834/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4302 - accuracy: 0.8328 - val_loss: 1.1001 - val_accuracy: 0.5634\n",
      "Epoch 835/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4436 - accuracy: 0.8328 - val_loss: 1.1074 - val_accuracy: 0.5493\n",
      "Epoch 836/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4361 - accuracy: 0.8299 - val_loss: 1.1106 - val_accuracy: 0.5493\n",
      "Epoch 837/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4412 - accuracy: 0.8182 - val_loss: 1.1123 - val_accuracy: 0.5493\n",
      "Epoch 838/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4304 - accuracy: 0.8387 - val_loss: 1.1053 - val_accuracy: 0.5634\n",
      "Epoch 839/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4275 - accuracy: 0.8504 - val_loss: 1.1038 - val_accuracy: 0.5634\n",
      "Epoch 840/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4419 - accuracy: 0.8358 - val_loss: 1.1030 - val_accuracy: 0.5634\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 841/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4472 - accuracy: 0.8328 - val_loss: 1.1100 - val_accuracy: 0.5634\n",
      "Epoch 842/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4329 - accuracy: 0.8534 - val_loss: 1.1166 - val_accuracy: 0.5493\n",
      "Epoch 843/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4347 - accuracy: 0.8299 - val_loss: 1.1241 - val_accuracy: 0.5493\n",
      "Epoch 844/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4270 - accuracy: 0.8475 - val_loss: 1.1279 - val_accuracy: 0.5493\n",
      "Epoch 845/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4227 - accuracy: 0.8680 - val_loss: 1.1176 - val_accuracy: 0.5634\n",
      "Epoch 846/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4303 - accuracy: 0.8504 - val_loss: 1.1009 - val_accuracy: 0.5634\n",
      "Epoch 847/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4404 - accuracy: 0.8416 - val_loss: 1.0853 - val_accuracy: 0.5634\n",
      "Epoch 848/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4359 - accuracy: 0.8387 - val_loss: 1.0802 - val_accuracy: 0.5634\n",
      "Epoch 849/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4258 - accuracy: 0.8563 - val_loss: 1.0741 - val_accuracy: 0.5775\n",
      "Epoch 850/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4305 - accuracy: 0.8475 - val_loss: 1.0787 - val_accuracy: 0.5775\n",
      "Epoch 851/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4318 - accuracy: 0.8446 - val_loss: 1.0862 - val_accuracy: 0.5634\n",
      "Epoch 852/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4313 - accuracy: 0.8504 - val_loss: 1.0954 - val_accuracy: 0.5634\n",
      "Epoch 853/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4414 - accuracy: 0.8152 - val_loss: 1.1017 - val_accuracy: 0.5634\n",
      "Epoch 854/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4415 - accuracy: 0.8123 - val_loss: 1.1134 - val_accuracy: 0.5634\n",
      "Epoch 855/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4306 - accuracy: 0.8446 - val_loss: 1.1175 - val_accuracy: 0.5493\n",
      "Epoch 856/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4400 - accuracy: 0.8299 - val_loss: 1.1016 - val_accuracy: 0.5634\n",
      "Epoch 857/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4352 - accuracy: 0.8270 - val_loss: 1.1073 - val_accuracy: 0.5634\n",
      "Epoch 858/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4272 - accuracy: 0.8416 - val_loss: 1.0960 - val_accuracy: 0.5634\n",
      "Epoch 859/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4267 - accuracy: 0.8475 - val_loss: 1.0764 - val_accuracy: 0.5775\n",
      "Epoch 860/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4284 - accuracy: 0.8387 - val_loss: 1.0723 - val_accuracy: 0.5775\n",
      "Epoch 861/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4339 - accuracy: 0.8358 - val_loss: 1.0696 - val_accuracy: 0.5775\n",
      "Epoch 862/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4346 - accuracy: 0.8416 - val_loss: 1.0765 - val_accuracy: 0.5775\n",
      "Epoch 863/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4243 - accuracy: 0.8504 - val_loss: 1.0777 - val_accuracy: 0.5775\n",
      "Epoch 864/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4274 - accuracy: 0.8563 - val_loss: 1.0797 - val_accuracy: 0.5634\n",
      "Epoch 865/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4292 - accuracy: 0.8592 - val_loss: 1.0842 - val_accuracy: 0.5634\n",
      "Epoch 866/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4289 - accuracy: 0.8534 - val_loss: 1.0980 - val_accuracy: 0.5634\n",
      "Epoch 867/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4258 - accuracy: 0.8563 - val_loss: 1.1028 - val_accuracy: 0.5634\n",
      "Epoch 868/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4221 - accuracy: 0.8534 - val_loss: 1.1009 - val_accuracy: 0.5634\n",
      "Epoch 869/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4348 - accuracy: 0.8240 - val_loss: 1.1096 - val_accuracy: 0.5634\n",
      "Epoch 870/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4275 - accuracy: 0.8504 - val_loss: 1.1125 - val_accuracy: 0.5634\n",
      "Epoch 871/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4287 - accuracy: 0.8358 - val_loss: 1.1183 - val_accuracy: 0.5634\n",
      "Epoch 872/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4242 - accuracy: 0.8475 - val_loss: 1.1276 - val_accuracy: 0.5634\n",
      "Epoch 873/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4317 - accuracy: 0.8387 - val_loss: 1.1184 - val_accuracy: 0.5634\n",
      "Epoch 874/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4247 - accuracy: 0.8416 - val_loss: 1.1130 - val_accuracy: 0.5634\n",
      "Epoch 875/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4305 - accuracy: 0.8446 - val_loss: 1.1123 - val_accuracy: 0.5634\n",
      "Epoch 876/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4296 - accuracy: 0.8387 - val_loss: 1.1080 - val_accuracy: 0.5634\n",
      "Epoch 877/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4213 - accuracy: 0.8534 - val_loss: 1.0978 - val_accuracy: 0.5634\n",
      "Epoch 878/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4198 - accuracy: 0.8534 - val_loss: 1.0803 - val_accuracy: 0.5634\n",
      "Epoch 879/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4243 - accuracy: 0.8504 - val_loss: 1.0751 - val_accuracy: 0.5775\n",
      "Epoch 880/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4251 - accuracy: 0.8534 - val_loss: 1.0727 - val_accuracy: 0.5775\n",
      "Epoch 881/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4251 - accuracy: 0.8504 - val_loss: 1.0700 - val_accuracy: 0.5775\n",
      "Epoch 882/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4204 - accuracy: 0.8504 - val_loss: 1.0689 - val_accuracy: 0.5775\n",
      "Epoch 883/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4276 - accuracy: 0.8387 - val_loss: 1.0577 - val_accuracy: 0.5915\n",
      "Epoch 884/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4213 - accuracy: 0.8534 - val_loss: 1.0638 - val_accuracy: 0.5915\n",
      "Epoch 885/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4248 - accuracy: 0.8299 - val_loss: 1.0684 - val_accuracy: 0.5915\n",
      "Epoch 886/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4249 - accuracy: 0.8416 - val_loss: 1.0755 - val_accuracy: 0.5775\n",
      "Epoch 887/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.4187 - accuracy: 0.8651 - val_loss: 1.0690 - val_accuracy: 0.5915\n",
      "Epoch 888/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4211 - accuracy: 0.8563 - val_loss: 1.0720 - val_accuracy: 0.5775\n",
      "Epoch 889/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4267 - accuracy: 0.8387 - val_loss: 1.0727 - val_accuracy: 0.5775\n",
      "Epoch 890/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4219 - accuracy: 0.8504 - val_loss: 1.0873 - val_accuracy: 0.5634\n",
      "Epoch 891/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4264 - accuracy: 0.8504 - val_loss: 1.0971 - val_accuracy: 0.5634\n",
      "Epoch 892/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4238 - accuracy: 0.8446 - val_loss: 1.1235 - val_accuracy: 0.5775\n",
      "Epoch 893/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.4268 - accuracy: 0.8387 - val_loss: 1.1417 - val_accuracy: 0.5634\n",
      "Epoch 894/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4182 - accuracy: 0.8563 - val_loss: 1.1465 - val_accuracy: 0.5634\n",
      "Epoch 895/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4182 - accuracy: 0.8504 - val_loss: 1.1359 - val_accuracy: 0.5634\n",
      "Epoch 896/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4261 - accuracy: 0.8270 - val_loss: 1.1316 - val_accuracy: 0.5634\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 897/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4189 - accuracy: 0.8446 - val_loss: 1.1297 - val_accuracy: 0.5634\n",
      "Epoch 898/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4264 - accuracy: 0.8504 - val_loss: 1.1385 - val_accuracy: 0.5634\n",
      "Epoch 899/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4275 - accuracy: 0.8299 - val_loss: 1.1379 - val_accuracy: 0.5634\n",
      "Epoch 900/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4212 - accuracy: 0.8504 - val_loss: 1.1261 - val_accuracy: 0.5775\n",
      "Epoch 901/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4212 - accuracy: 0.8504 - val_loss: 1.1145 - val_accuracy: 0.5775\n",
      "Epoch 902/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4231 - accuracy: 0.8563 - val_loss: 1.1119 - val_accuracy: 0.5775\n",
      "Epoch 903/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4191 - accuracy: 0.8416 - val_loss: 1.1121 - val_accuracy: 0.5775\n",
      "Epoch 904/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4219 - accuracy: 0.8446 - val_loss: 1.1048 - val_accuracy: 0.5775\n",
      "Epoch 905/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4269 - accuracy: 0.8475 - val_loss: 1.1126 - val_accuracy: 0.5775\n",
      "Epoch 906/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4287 - accuracy: 0.8270 - val_loss: 1.1179 - val_accuracy: 0.5775\n",
      "Epoch 907/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4176 - accuracy: 0.8534 - val_loss: 1.1144 - val_accuracy: 0.5775\n",
      "Epoch 908/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4203 - accuracy: 0.8475 - val_loss: 1.1118 - val_accuracy: 0.5775\n",
      "Epoch 909/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4241 - accuracy: 0.8328 - val_loss: 1.1163 - val_accuracy: 0.5775\n",
      "Epoch 910/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4136 - accuracy: 0.8680 - val_loss: 1.1225 - val_accuracy: 0.5775\n",
      "Epoch 911/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4250 - accuracy: 0.8358 - val_loss: 1.1184 - val_accuracy: 0.5775\n",
      "Epoch 912/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4208 - accuracy: 0.8563 - val_loss: 1.1196 - val_accuracy: 0.5775\n",
      "Epoch 913/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4124 - accuracy: 0.8504 - val_loss: 1.1199 - val_accuracy: 0.5775\n",
      "Epoch 914/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4202 - accuracy: 0.8504 - val_loss: 1.1165 - val_accuracy: 0.5775\n",
      "Epoch 915/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4261 - accuracy: 0.8563 - val_loss: 1.1124 - val_accuracy: 0.5775\n",
      "Epoch 916/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4146 - accuracy: 0.8592 - val_loss: 1.1112 - val_accuracy: 0.5775\n",
      "Epoch 917/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4232 - accuracy: 0.8475 - val_loss: 1.0902 - val_accuracy: 0.5775\n",
      "Epoch 918/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4133 - accuracy: 0.8504 - val_loss: 1.0784 - val_accuracy: 0.5915\n",
      "Epoch 919/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4293 - accuracy: 0.8416 - val_loss: 1.0914 - val_accuracy: 0.5775\n",
      "Epoch 920/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4332 - accuracy: 0.8094 - val_loss: 1.0969 - val_accuracy: 0.5775\n",
      "Epoch 921/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4154 - accuracy: 0.8592 - val_loss: 1.0988 - val_accuracy: 0.5775\n",
      "Epoch 922/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4188 - accuracy: 0.8416 - val_loss: 1.1017 - val_accuracy: 0.5775\n",
      "Epoch 923/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4176 - accuracy: 0.8534 - val_loss: 1.1319 - val_accuracy: 0.5775\n",
      "Epoch 924/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4204 - accuracy: 0.8475 - val_loss: 1.1520 - val_accuracy: 0.5634\n",
      "Epoch 925/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4218 - accuracy: 0.8534 - val_loss: 1.1559 - val_accuracy: 0.5634\n",
      "Epoch 926/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4222 - accuracy: 0.8504 - val_loss: 1.1581 - val_accuracy: 0.5634\n",
      "Epoch 927/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4139 - accuracy: 0.8592 - val_loss: 1.1570 - val_accuracy: 0.5634\n",
      "Epoch 928/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4163 - accuracy: 0.8651 - val_loss: 1.1540 - val_accuracy: 0.5634\n",
      "Epoch 929/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4203 - accuracy: 0.8387 - val_loss: 1.1565 - val_accuracy: 0.5634\n",
      "Epoch 930/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4184 - accuracy: 0.8534 - val_loss: 1.1562 - val_accuracy: 0.5634\n",
      "Epoch 931/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4099 - accuracy: 0.8680 - val_loss: 1.1556 - val_accuracy: 0.5634\n",
      "Epoch 932/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4122 - accuracy: 0.8534 - val_loss: 1.1532 - val_accuracy: 0.5775\n",
      "Epoch 933/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4213 - accuracy: 0.8504 - val_loss: 1.1481 - val_accuracy: 0.5775\n",
      "Epoch 934/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4111 - accuracy: 0.8622 - val_loss: 1.1390 - val_accuracy: 0.5775\n",
      "Epoch 935/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4202 - accuracy: 0.8475 - val_loss: 1.1352 - val_accuracy: 0.5775\n",
      "Epoch 936/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4124 - accuracy: 0.8651 - val_loss: 1.1275 - val_accuracy: 0.5775\n",
      "Epoch 937/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4221 - accuracy: 0.8416 - val_loss: 1.1187 - val_accuracy: 0.5775\n",
      "Epoch 938/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4172 - accuracy: 0.8534 - val_loss: 1.1120 - val_accuracy: 0.5775\n",
      "Epoch 939/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4132 - accuracy: 0.8592 - val_loss: 1.1047 - val_accuracy: 0.5775\n",
      "Epoch 940/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4162 - accuracy: 0.8622 - val_loss: 1.1014 - val_accuracy: 0.5775\n",
      "Epoch 941/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4127 - accuracy: 0.8680 - val_loss: 1.1045 - val_accuracy: 0.5775\n",
      "Epoch 942/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4154 - accuracy: 0.8534 - val_loss: 1.0969 - val_accuracy: 0.5775\n",
      "Epoch 943/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4231 - accuracy: 0.8622 - val_loss: 1.0893 - val_accuracy: 0.5775\n",
      "Epoch 944/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4159 - accuracy: 0.8592 - val_loss: 1.0768 - val_accuracy: 0.5775\n",
      "Epoch 945/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4144 - accuracy: 0.8504 - val_loss: 1.0738 - val_accuracy: 0.5775\n",
      "Epoch 946/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4139 - accuracy: 0.8504 - val_loss: 1.0851 - val_accuracy: 0.5775\n",
      "Epoch 947/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4129 - accuracy: 0.8680 - val_loss: 1.0939 - val_accuracy: 0.5634\n",
      "Epoch 948/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4178 - accuracy: 0.8534 - val_loss: 1.0885 - val_accuracy: 0.5775\n",
      "Epoch 949/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4145 - accuracy: 0.8504 - val_loss: 1.0871 - val_accuracy: 0.5775\n",
      "Epoch 950/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4165 - accuracy: 0.8563 - val_loss: 1.0960 - val_accuracy: 0.5915\n",
      "Epoch 951/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4159 - accuracy: 0.8446 - val_loss: 1.1101 - val_accuracy: 0.5775\n",
      "Epoch 952/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4152 - accuracy: 0.8504 - val_loss: 1.1105 - val_accuracy: 0.5775\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 953/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4146 - accuracy: 0.8534 - val_loss: 1.0998 - val_accuracy: 0.5775\n",
      "Epoch 954/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4133 - accuracy: 0.8563 - val_loss: 1.1040 - val_accuracy: 0.5775\n",
      "Epoch 955/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4112 - accuracy: 0.8563 - val_loss: 1.1032 - val_accuracy: 0.5915\n",
      "Epoch 956/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4160 - accuracy: 0.8563 - val_loss: 1.1101 - val_accuracy: 0.5775\n",
      "Epoch 957/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4109 - accuracy: 0.8563 - val_loss: 1.1246 - val_accuracy: 0.5775\n",
      "Epoch 958/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4286 - accuracy: 0.8328 - val_loss: 1.1224 - val_accuracy: 0.5775\n",
      "Epoch 959/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4105 - accuracy: 0.8622 - val_loss: 1.1033 - val_accuracy: 0.5915\n",
      "Epoch 960/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4194 - accuracy: 0.8504 - val_loss: 1.1061 - val_accuracy: 0.5915\n",
      "Epoch 961/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4144 - accuracy: 0.8504 - val_loss: 1.1171 - val_accuracy: 0.5775\n",
      "Epoch 962/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4173 - accuracy: 0.8416 - val_loss: 1.1360 - val_accuracy: 0.5775\n",
      "Epoch 963/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4184 - accuracy: 0.8475 - val_loss: 1.1444 - val_accuracy: 0.5775\n",
      "Epoch 964/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4165 - accuracy: 0.8446 - val_loss: 1.1417 - val_accuracy: 0.5775\n",
      "Epoch 965/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.4128 - accuracy: 0.8534 - val_loss: 1.1468 - val_accuracy: 0.5775\n",
      "Epoch 966/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4181 - accuracy: 0.8475 - val_loss: 1.1571 - val_accuracy: 0.5775\n",
      "Epoch 967/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4141 - accuracy: 0.8475 - val_loss: 1.1553 - val_accuracy: 0.5775\n",
      "Epoch 968/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4133 - accuracy: 0.8622 - val_loss: 1.1567 - val_accuracy: 0.5775\n",
      "Epoch 969/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4098 - accuracy: 0.8387 - val_loss: 1.1568 - val_accuracy: 0.5775\n",
      "Epoch 970/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4195 - accuracy: 0.8328 - val_loss: 1.1444 - val_accuracy: 0.5775\n",
      "Epoch 971/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4092 - accuracy: 0.8475 - val_loss: 1.1365 - val_accuracy: 0.5775\n",
      "Epoch 972/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4142 - accuracy: 0.8622 - val_loss: 1.1430 - val_accuracy: 0.5775\n",
      "Epoch 973/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4095 - accuracy: 0.8563 - val_loss: 1.1414 - val_accuracy: 0.5775\n",
      "Epoch 974/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4158 - accuracy: 0.8446 - val_loss: 1.1286 - val_accuracy: 0.5775\n",
      "Epoch 975/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4167 - accuracy: 0.8651 - val_loss: 1.1233 - val_accuracy: 0.5915\n",
      "Epoch 976/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4068 - accuracy: 0.8563 - val_loss: 1.1272 - val_accuracy: 0.5775\n",
      "Epoch 977/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4089 - accuracy: 0.8651 - val_loss: 1.1193 - val_accuracy: 0.5915\n",
      "Epoch 978/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4147 - accuracy: 0.8416 - val_loss: 1.1292 - val_accuracy: 0.5775\n",
      "Epoch 979/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4175 - accuracy: 0.8446 - val_loss: 1.1302 - val_accuracy: 0.5915\n",
      "Epoch 980/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4109 - accuracy: 0.8446 - val_loss: 1.1218 - val_accuracy: 0.5915\n",
      "Epoch 981/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4083 - accuracy: 0.8622 - val_loss: 1.1159 - val_accuracy: 0.5915\n",
      "Epoch 982/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4137 - accuracy: 0.8592 - val_loss: 1.1121 - val_accuracy: 0.5915\n",
      "Epoch 983/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4073 - accuracy: 0.8563 - val_loss: 1.1114 - val_accuracy: 0.5915\n",
      "Epoch 984/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4092 - accuracy: 0.8622 - val_loss: 1.1099 - val_accuracy: 0.5915\n",
      "Epoch 985/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4011 - accuracy: 0.8651 - val_loss: 1.1080 - val_accuracy: 0.5915\n",
      "Epoch 986/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4081 - accuracy: 0.8651 - val_loss: 1.1084 - val_accuracy: 0.5915\n",
      "Epoch 987/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4170 - accuracy: 0.8416 - val_loss: 1.1125 - val_accuracy: 0.5915\n",
      "Epoch 988/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4158 - accuracy: 0.8534 - val_loss: 1.1026 - val_accuracy: 0.5915\n",
      "Epoch 989/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4066 - accuracy: 0.8534 - val_loss: 1.1123 - val_accuracy: 0.5915\n",
      "Epoch 990/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4157 - accuracy: 0.8563 - val_loss: 1.1268 - val_accuracy: 0.5915\n",
      "Epoch 991/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4138 - accuracy: 0.8622 - val_loss: 1.1384 - val_accuracy: 0.5915\n",
      "Epoch 992/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4156 - accuracy: 0.8622 - val_loss: 1.1434 - val_accuracy: 0.5915\n",
      "Epoch 993/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4036 - accuracy: 0.8651 - val_loss: 1.1562 - val_accuracy: 0.5775\n",
      "Epoch 994/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4121 - accuracy: 0.8416 - val_loss: 1.1670 - val_accuracy: 0.5775\n",
      "Epoch 995/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4089 - accuracy: 0.8622 - val_loss: 1.1545 - val_accuracy: 0.5775\n",
      "Epoch 996/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4158 - accuracy: 0.8534 - val_loss: 1.1508 - val_accuracy: 0.5775\n",
      "Epoch 997/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4243 - accuracy: 0.8563 - val_loss: 1.1616 - val_accuracy: 0.5775\n",
      "Epoch 998/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4177 - accuracy: 0.8358 - val_loss: 1.1510 - val_accuracy: 0.5775\n",
      "Epoch 999/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4079 - accuracy: 0.8651 - val_loss: 1.1363 - val_accuracy: 0.5915\n",
      "Epoch 1000/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4078 - accuracy: 0.8563 - val_loss: 1.1292 - val_accuracy: 0.5915\n",
      "Epoch 1001/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4159 - accuracy: 0.8387 - val_loss: 1.1285 - val_accuracy: 0.5915\n",
      "Epoch 1002/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4097 - accuracy: 0.8680 - val_loss: 1.1363 - val_accuracy: 0.5915\n",
      "Epoch 1003/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4073 - accuracy: 0.8592 - val_loss: 1.1431 - val_accuracy: 0.5915\n",
      "Epoch 1004/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4069 - accuracy: 0.8592 - val_loss: 1.1419 - val_accuracy: 0.5915\n",
      "Epoch 1005/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4042 - accuracy: 0.8622 - val_loss: 1.1441 - val_accuracy: 0.5915\n",
      "Epoch 1006/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4184 - accuracy: 0.8358 - val_loss: 1.1326 - val_accuracy: 0.5915\n",
      "Epoch 1007/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4181 - accuracy: 0.8504 - val_loss: 1.1262 - val_accuracy: 0.5915\n",
      "Epoch 1008/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4146 - accuracy: 0.8328 - val_loss: 1.1164 - val_accuracy: 0.5915\n",
      "Epoch 1009/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.4045 - accuracy: 0.8651 - val_loss: 1.1166 - val_accuracy: 0.5915\n",
      "Epoch 1010/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4047 - accuracy: 0.8534 - val_loss: 1.1224 - val_accuracy: 0.5915\n",
      "Epoch 1011/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4080 - accuracy: 0.8563 - val_loss: 1.1294 - val_accuracy: 0.5915\n",
      "Epoch 1012/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4094 - accuracy: 0.8710 - val_loss: 1.1400 - val_accuracy: 0.5915\n",
      "Epoch 1013/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4040 - accuracy: 0.8622 - val_loss: 1.1388 - val_accuracy: 0.5915\n",
      "Epoch 1014/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4039 - accuracy: 0.8563 - val_loss: 1.1360 - val_accuracy: 0.5915\n",
      "Epoch 1015/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4142 - accuracy: 0.8387 - val_loss: 1.1378 - val_accuracy: 0.5915\n",
      "Epoch 1016/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4059 - accuracy: 0.8592 - val_loss: 1.1283 - val_accuracy: 0.5915\n",
      "Epoch 1017/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4084 - accuracy: 0.8504 - val_loss: 1.1279 - val_accuracy: 0.5915\n",
      "Epoch 1018/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4038 - accuracy: 0.8563 - val_loss: 1.1345 - val_accuracy: 0.5915\n",
      "Epoch 1019/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4116 - accuracy: 0.8358 - val_loss: 1.1418 - val_accuracy: 0.5915\n",
      "Epoch 1020/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4068 - accuracy: 0.8504 - val_loss: 1.1559 - val_accuracy: 0.5915\n",
      "Epoch 1021/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4167 - accuracy: 0.8563 - val_loss: 1.1493 - val_accuracy: 0.5915\n",
      "Epoch 1022/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4048 - accuracy: 0.8651 - val_loss: 1.1444 - val_accuracy: 0.5915\n",
      "Epoch 1023/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4080 - accuracy: 0.8739 - val_loss: 1.1506 - val_accuracy: 0.5915\n",
      "Epoch 1024/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4069 - accuracy: 0.8534 - val_loss: 1.1682 - val_accuracy: 0.5915\n",
      "Epoch 1025/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4028 - accuracy: 0.8622 - val_loss: 1.1745 - val_accuracy: 0.5775\n",
      "Epoch 1026/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4115 - accuracy: 0.8416 - val_loss: 1.1791 - val_accuracy: 0.5775\n",
      "Epoch 1027/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4186 - accuracy: 0.8387 - val_loss: 1.1879 - val_accuracy: 0.5775\n",
      "Epoch 1028/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3998 - accuracy: 0.8739 - val_loss: 1.1903 - val_accuracy: 0.5775\n",
      "Epoch 1029/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3989 - accuracy: 0.8592 - val_loss: 1.1893 - val_accuracy: 0.5775\n",
      "Epoch 1030/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4018 - accuracy: 0.8651 - val_loss: 1.1866 - val_accuracy: 0.5775\n",
      "Epoch 1031/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4032 - accuracy: 0.8592 - val_loss: 1.1932 - val_accuracy: 0.5775\n",
      "Epoch 1032/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4051 - accuracy: 0.8475 - val_loss: 1.1992 - val_accuracy: 0.5634\n",
      "Epoch 1033/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3969 - accuracy: 0.8651 - val_loss: 1.1887 - val_accuracy: 0.5775\n",
      "Epoch 1034/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4052 - accuracy: 0.8622 - val_loss: 1.1926 - val_accuracy: 0.5775\n",
      "Epoch 1035/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4115 - accuracy: 0.8534 - val_loss: 1.1853 - val_accuracy: 0.5915\n",
      "Epoch 1036/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4053 - accuracy: 0.8680 - val_loss: 1.1869 - val_accuracy: 0.5915\n",
      "Epoch 1037/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4026 - accuracy: 0.8622 - val_loss: 1.1763 - val_accuracy: 0.5915\n",
      "Epoch 1038/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4023 - accuracy: 0.8563 - val_loss: 1.1591 - val_accuracy: 0.5915\n",
      "Epoch 1039/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4061 - accuracy: 0.8622 - val_loss: 1.1481 - val_accuracy: 0.5915\n",
      "Epoch 1040/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4051 - accuracy: 0.8680 - val_loss: 1.1496 - val_accuracy: 0.5915\n",
      "Epoch 1041/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3987 - accuracy: 0.8622 - val_loss: 1.1458 - val_accuracy: 0.5915\n",
      "Epoch 1042/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4048 - accuracy: 0.8504 - val_loss: 1.1511 - val_accuracy: 0.5915\n",
      "Epoch 1043/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3969 - accuracy: 0.8739 - val_loss: 1.1573 - val_accuracy: 0.5915\n",
      "Epoch 1044/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4021 - accuracy: 0.8680 - val_loss: 1.1622 - val_accuracy: 0.5915\n",
      "Epoch 1045/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4048 - accuracy: 0.8534 - val_loss: 1.1551 - val_accuracy: 0.5915\n",
      "Epoch 1046/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4023 - accuracy: 0.8651 - val_loss: 1.1504 - val_accuracy: 0.5915\n",
      "Epoch 1047/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4026 - accuracy: 0.8475 - val_loss: 1.1419 - val_accuracy: 0.5915\n",
      "Epoch 1048/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3986 - accuracy: 0.8856 - val_loss: 1.1450 - val_accuracy: 0.5915\n",
      "Epoch 1049/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4085 - accuracy: 0.8504 - val_loss: 1.1457 - val_accuracy: 0.5915\n",
      "Epoch 1050/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3980 - accuracy: 0.8856 - val_loss: 1.1414 - val_accuracy: 0.5915\n",
      "Epoch 1051/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4026 - accuracy: 0.8680 - val_loss: 1.1549 - val_accuracy: 0.5915\n",
      "Epoch 1052/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4053 - accuracy: 0.8651 - val_loss: 1.1614 - val_accuracy: 0.5915\n",
      "Epoch 1053/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3962 - accuracy: 0.8710 - val_loss: 1.1601 - val_accuracy: 0.5915\n",
      "Epoch 1054/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4019 - accuracy: 0.8651 - val_loss: 1.1618 - val_accuracy: 0.5915\n",
      "Epoch 1055/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4054 - accuracy: 0.8680 - val_loss: 1.1585 - val_accuracy: 0.5915\n",
      "Epoch 1056/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4004 - accuracy: 0.8710 - val_loss: 1.1544 - val_accuracy: 0.5915\n",
      "Epoch 1057/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3973 - accuracy: 0.8622 - val_loss: 1.1579 - val_accuracy: 0.5915\n",
      "Epoch 1058/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4165 - accuracy: 0.8328 - val_loss: 1.1700 - val_accuracy: 0.5915\n",
      "Epoch 1059/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3998 - accuracy: 0.8651 - val_loss: 1.1884 - val_accuracy: 0.5915\n",
      "Epoch 1060/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3978 - accuracy: 0.8680 - val_loss: 1.1911 - val_accuracy: 0.5915\n",
      "Epoch 1061/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4016 - accuracy: 0.8504 - val_loss: 1.1979 - val_accuracy: 0.5915\n",
      "Epoch 1062/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4004 - accuracy: 0.8446 - val_loss: 1.1983 - val_accuracy: 0.5915\n",
      "Epoch 1063/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3980 - accuracy: 0.8739 - val_loss: 1.1800 - val_accuracy: 0.5915\n",
      "Epoch 1064/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4065 - accuracy: 0.8475 - val_loss: 1.1707 - val_accuracy: 0.5915\n",
      "Epoch 1065/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4023 - accuracy: 0.8592 - val_loss: 1.1718 - val_accuracy: 0.5915\n",
      "Epoch 1066/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4052 - accuracy: 0.8651 - val_loss: 1.1726 - val_accuracy: 0.5915\n",
      "Epoch 1067/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3969 - accuracy: 0.8680 - val_loss: 1.1826 - val_accuracy: 0.5915\n",
      "Epoch 1068/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4018 - accuracy: 0.8592 - val_loss: 1.1755 - val_accuracy: 0.5915\n",
      "Epoch 1069/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4050 - accuracy: 0.8651 - val_loss: 1.1574 - val_accuracy: 0.5915\n",
      "Epoch 1070/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4009 - accuracy: 0.8504 - val_loss: 1.1487 - val_accuracy: 0.5915\n",
      "Epoch 1071/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3924 - accuracy: 0.8680 - val_loss: 1.1568 - val_accuracy: 0.5915\n",
      "Epoch 1072/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4068 - accuracy: 0.8534 - val_loss: 1.1589 - val_accuracy: 0.5915\n",
      "Epoch 1073/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4057 - accuracy: 0.8475 - val_loss: 1.1668 - val_accuracy: 0.5915\n",
      "Epoch 1074/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4019 - accuracy: 0.8651 - val_loss: 1.1816 - val_accuracy: 0.5915\n",
      "Epoch 1075/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4124 - accuracy: 0.8475 - val_loss: 1.1777 - val_accuracy: 0.5915\n",
      "Epoch 1076/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4007 - accuracy: 0.8299 - val_loss: 1.1690 - val_accuracy: 0.5915\n",
      "Epoch 1077/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3926 - accuracy: 0.8622 - val_loss: 1.1825 - val_accuracy: 0.5915\n",
      "Epoch 1078/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4017 - accuracy: 0.8446 - val_loss: 1.2024 - val_accuracy: 0.5915\n",
      "Epoch 1079/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3941 - accuracy: 0.8534 - val_loss: 1.2107 - val_accuracy: 0.5915\n",
      "Epoch 1080/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4006 - accuracy: 0.8622 - val_loss: 1.2203 - val_accuracy: 0.5915\n",
      "Epoch 1081/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4016 - accuracy: 0.8534 - val_loss: 1.2116 - val_accuracy: 0.5915\n",
      "Epoch 1082/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3909 - accuracy: 0.8534 - val_loss: 1.2053 - val_accuracy: 0.5915\n",
      "Epoch 1083/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3985 - accuracy: 0.8622 - val_loss: 1.2107 - val_accuracy: 0.5915\n",
      "Epoch 1084/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3910 - accuracy: 0.8680 - val_loss: 1.2094 - val_accuracy: 0.5915\n",
      "Epoch 1085/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3966 - accuracy: 0.8739 - val_loss: 1.2025 - val_accuracy: 0.5915\n",
      "Epoch 1086/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4032 - accuracy: 0.8592 - val_loss: 1.1910 - val_accuracy: 0.5915\n",
      "Epoch 1087/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4025 - accuracy: 0.8504 - val_loss: 1.1982 - val_accuracy: 0.5915\n",
      "Epoch 1088/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3935 - accuracy: 0.8622 - val_loss: 1.2003 - val_accuracy: 0.5915\n",
      "Epoch 1089/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4003 - accuracy: 0.8651 - val_loss: 1.1942 - val_accuracy: 0.5915\n",
      "Epoch 1090/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3993 - accuracy: 0.8622 - val_loss: 1.2027 - val_accuracy: 0.5915\n",
      "Epoch 1091/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3918 - accuracy: 0.8622 - val_loss: 1.1999 - val_accuracy: 0.5915\n",
      "Epoch 1092/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3964 - accuracy: 0.8563 - val_loss: 1.2002 - val_accuracy: 0.5915\n",
      "Epoch 1093/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4044 - accuracy: 0.8534 - val_loss: 1.1999 - val_accuracy: 0.5915\n",
      "Epoch 1094/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3947 - accuracy: 0.8592 - val_loss: 1.2001 - val_accuracy: 0.5915\n",
      "Epoch 1095/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3910 - accuracy: 0.8592 - val_loss: 1.1895 - val_accuracy: 0.5915\n",
      "Epoch 1096/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3922 - accuracy: 0.8592 - val_loss: 1.1948 - val_accuracy: 0.5915\n",
      "Epoch 1097/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4056 - accuracy: 0.8416 - val_loss: 1.2059 - val_accuracy: 0.5915\n",
      "Epoch 1098/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3945 - accuracy: 0.8680 - val_loss: 1.2112 - val_accuracy: 0.5915\n",
      "Epoch 1099/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3965 - accuracy: 0.8651 - val_loss: 1.2020 - val_accuracy: 0.5915\n",
      "Epoch 1100/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4014 - accuracy: 0.8592 - val_loss: 1.2037 - val_accuracy: 0.5915\n",
      "Epoch 1101/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3984 - accuracy: 0.8651 - val_loss: 1.1990 - val_accuracy: 0.5915\n",
      "Epoch 1102/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3978 - accuracy: 0.8710 - val_loss: 1.2043 - val_accuracy: 0.5915\n",
      "Epoch 1103/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3934 - accuracy: 0.8622 - val_loss: 1.2053 - val_accuracy: 0.5915\n",
      "Epoch 1104/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4137 - accuracy: 0.8446 - val_loss: 1.2164 - val_accuracy: 0.5915\n",
      "Epoch 1105/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4039 - accuracy: 0.8328 - val_loss: 1.2315 - val_accuracy: 0.5915\n",
      "Epoch 1106/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3944 - accuracy: 0.8592 - val_loss: 1.2312 - val_accuracy: 0.5915\n",
      "Epoch 1107/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3892 - accuracy: 0.8622 - val_loss: 1.2420 - val_accuracy: 0.5775\n",
      "Epoch 1108/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3909 - accuracy: 0.8739 - val_loss: 1.2370 - val_accuracy: 0.5915\n",
      "Epoch 1109/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3899 - accuracy: 0.8651 - val_loss: 1.2289 - val_accuracy: 0.5915\n",
      "Epoch 1110/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3955 - accuracy: 0.8651 - val_loss: 1.2269 - val_accuracy: 0.5915\n",
      "Epoch 1111/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3932 - accuracy: 0.8680 - val_loss: 1.2235 - val_accuracy: 0.5915\n",
      "Epoch 1112/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3911 - accuracy: 0.8680 - val_loss: 1.2187 - val_accuracy: 0.5915\n",
      "Epoch 1113/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4155 - accuracy: 0.8475 - val_loss: 1.2108 - val_accuracy: 0.5915\n",
      "Epoch 1114/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3934 - accuracy: 0.8534 - val_loss: 1.2048 - val_accuracy: 0.5915\n",
      "Epoch 1115/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3965 - accuracy: 0.8592 - val_loss: 1.1982 - val_accuracy: 0.5915\n",
      "Epoch 1116/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3961 - accuracy: 0.8534 - val_loss: 1.2045 - val_accuracy: 0.5915\n",
      "Epoch 1117/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3885 - accuracy: 0.8651 - val_loss: 1.2176 - val_accuracy: 0.5915\n",
      "Epoch 1118/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3908 - accuracy: 0.8563 - val_loss: 1.2252 - val_accuracy: 0.5915\n",
      "Epoch 1119/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3927 - accuracy: 0.8504 - val_loss: 1.2399 - val_accuracy: 0.5775\n",
      "Epoch 1120/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3936 - accuracy: 0.8768 - val_loss: 1.2336 - val_accuracy: 0.5915\n",
      "Epoch 1121/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3922 - accuracy: 0.8651 - val_loss: 1.2221 - val_accuracy: 0.5915\n",
      "Epoch 1122/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3926 - accuracy: 0.8622 - val_loss: 1.2316 - val_accuracy: 0.5915\n",
      "Epoch 1123/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3983 - accuracy: 0.8651 - val_loss: 1.2329 - val_accuracy: 0.5915\n",
      "Epoch 1124/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3904 - accuracy: 0.8651 - val_loss: 1.2337 - val_accuracy: 0.5915\n",
      "Epoch 1125/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3920 - accuracy: 0.8651 - val_loss: 1.2380 - val_accuracy: 0.5915\n",
      "Epoch 1126/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3927 - accuracy: 0.8387 - val_loss: 1.2392 - val_accuracy: 0.5915\n",
      "Epoch 1127/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3906 - accuracy: 0.8622 - val_loss: 1.2392 - val_accuracy: 0.5915\n",
      "Epoch 1128/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3912 - accuracy: 0.8651 - val_loss: 1.2335 - val_accuracy: 0.5915\n",
      "Epoch 1129/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3907 - accuracy: 0.8739 - val_loss: 1.2304 - val_accuracy: 0.5915\n",
      "Epoch 1130/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4056 - accuracy: 0.8504 - val_loss: 1.2205 - val_accuracy: 0.5915\n",
      "Epoch 1131/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3868 - accuracy: 0.8768 - val_loss: 1.2208 - val_accuracy: 0.5915\n",
      "Epoch 1132/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4008 - accuracy: 0.8622 - val_loss: 1.2258 - val_accuracy: 0.5915\n",
      "Epoch 1133/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3914 - accuracy: 0.8710 - val_loss: 1.2264 - val_accuracy: 0.5915\n",
      "Epoch 1134/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3870 - accuracy: 0.8768 - val_loss: 1.2146 - val_accuracy: 0.5915\n",
      "Epoch 1135/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3957 - accuracy: 0.8651 - val_loss: 1.2131 - val_accuracy: 0.5915\n",
      "Epoch 1136/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3863 - accuracy: 0.8680 - val_loss: 1.2204 - val_accuracy: 0.5915\n",
      "Epoch 1137/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3863 - accuracy: 0.8739 - val_loss: 1.2028 - val_accuracy: 0.5915\n",
      "Epoch 1138/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4013 - accuracy: 0.8563 - val_loss: 1.2039 - val_accuracy: 0.5915\n",
      "Epoch 1139/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3895 - accuracy: 0.8592 - val_loss: 1.2079 - val_accuracy: 0.5915\n",
      "Epoch 1140/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3946 - accuracy: 0.8592 - val_loss: 1.2071 - val_accuracy: 0.5915\n",
      "Epoch 1141/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3926 - accuracy: 0.8768 - val_loss: 1.2171 - val_accuracy: 0.5915\n",
      "Epoch 1142/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3896 - accuracy: 0.8739 - val_loss: 1.2085 - val_accuracy: 0.5915\n",
      "Epoch 1143/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3977 - accuracy: 0.8563 - val_loss: 1.2070 - val_accuracy: 0.5915\n",
      "Epoch 1144/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3872 - accuracy: 0.8710 - val_loss: 1.2047 - val_accuracy: 0.5915\n",
      "Epoch 1145/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3904 - accuracy: 0.8622 - val_loss: 1.2131 - val_accuracy: 0.5915\n",
      "Epoch 1146/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3992 - accuracy: 0.8592 - val_loss: 1.2174 - val_accuracy: 0.5915\n",
      "Epoch 1147/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3954 - accuracy: 0.8592 - val_loss: 1.2061 - val_accuracy: 0.5915\n",
      "Epoch 1148/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3961 - accuracy: 0.8563 - val_loss: 1.2183 - val_accuracy: 0.5915\n",
      "Epoch 1149/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3896 - accuracy: 0.8504 - val_loss: 1.2151 - val_accuracy: 0.5915\n",
      "Epoch 1150/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4032 - accuracy: 0.8504 - val_loss: 1.2334 - val_accuracy: 0.5915\n",
      "Epoch 1151/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3991 - accuracy: 0.8592 - val_loss: 1.2317 - val_accuracy: 0.5915\n",
      "Epoch 1152/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3939 - accuracy: 0.8622 - val_loss: 1.2395 - val_accuracy: 0.5915\n",
      "Epoch 1153/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3960 - accuracy: 0.8563 - val_loss: 1.2312 - val_accuracy: 0.5915\n",
      "Epoch 1154/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3841 - accuracy: 0.8651 - val_loss: 1.2493 - val_accuracy: 0.5915\n",
      "Epoch 1155/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3967 - accuracy: 0.8563 - val_loss: 1.2727 - val_accuracy: 0.5775\n",
      "Epoch 1156/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3849 - accuracy: 0.8710 - val_loss: 1.2977 - val_accuracy: 0.5775\n",
      "Epoch 1157/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3942 - accuracy: 0.8563 - val_loss: 1.3036 - val_accuracy: 0.5775\n",
      "Epoch 1158/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3952 - accuracy: 0.8592 - val_loss: 1.3062 - val_accuracy: 0.5775\n",
      "Epoch 1159/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3992 - accuracy: 0.8446 - val_loss: 1.3066 - val_accuracy: 0.5775\n",
      "Epoch 1160/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3861 - accuracy: 0.8592 - val_loss: 1.3024 - val_accuracy: 0.5775\n",
      "Epoch 1161/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3896 - accuracy: 0.8563 - val_loss: 1.2953 - val_accuracy: 0.5775\n",
      "Epoch 1162/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3931 - accuracy: 0.8592 - val_loss: 1.2779 - val_accuracy: 0.5775\n",
      "Epoch 1163/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3871 - accuracy: 0.8680 - val_loss: 1.2533 - val_accuracy: 0.5915\n",
      "Epoch 1164/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3845 - accuracy: 0.8651 - val_loss: 1.2497 - val_accuracy: 0.5915\n",
      "Epoch 1165/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3997 - accuracy: 0.8328 - val_loss: 1.2560 - val_accuracy: 0.5915\n",
      "Epoch 1166/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3885 - accuracy: 0.8622 - val_loss: 1.2651 - val_accuracy: 0.5915\n",
      "Epoch 1167/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3874 - accuracy: 0.8680 - val_loss: 1.2867 - val_accuracy: 0.5775\n",
      "Epoch 1168/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3864 - accuracy: 0.8710 - val_loss: 1.2926 - val_accuracy: 0.5775\n",
      "Epoch 1169/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3867 - accuracy: 0.8651 - val_loss: 1.2907 - val_accuracy: 0.5775\n",
      "Epoch 1170/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3883 - accuracy: 0.8710 - val_loss: 1.2995 - val_accuracy: 0.5775\n",
      "Epoch 1171/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4043 - accuracy: 0.8622 - val_loss: 1.2839 - val_accuracy: 0.5775\n",
      "Epoch 1172/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3861 - accuracy: 0.8592 - val_loss: 1.2836 - val_accuracy: 0.5775\n",
      "Epoch 1173/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3842 - accuracy: 0.8651 - val_loss: 1.2746 - val_accuracy: 0.5915\n",
      "Epoch 1174/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3843 - accuracy: 0.8739 - val_loss: 1.2705 - val_accuracy: 0.5915\n",
      "Epoch 1175/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3893 - accuracy: 0.8680 - val_loss: 1.2649 - val_accuracy: 0.5915\n",
      "Epoch 1176/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3878 - accuracy: 0.8680 - val_loss: 1.2648 - val_accuracy: 0.5915\n",
      "Epoch 1177/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3888 - accuracy: 0.8504 - val_loss: 1.2821 - val_accuracy: 0.5775\n",
      "Epoch 1178/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3746 - accuracy: 0.8592 - val_loss: 1.2829 - val_accuracy: 0.5775\n",
      "Epoch 1179/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3892 - accuracy: 0.8710 - val_loss: 1.2763 - val_accuracy: 0.5775\n",
      "Epoch 1180/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3892 - accuracy: 0.8768 - val_loss: 1.2595 - val_accuracy: 0.5915\n",
      "Epoch 1181/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3946 - accuracy: 0.8446 - val_loss: 1.2644 - val_accuracy: 0.5915\n",
      "Epoch 1182/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3839 - accuracy: 0.8710 - val_loss: 1.2724 - val_accuracy: 0.5915\n",
      "Epoch 1183/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3953 - accuracy: 0.8534 - val_loss: 1.2738 - val_accuracy: 0.5915\n",
      "Epoch 1184/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3850 - accuracy: 0.8739 - val_loss: 1.2655 - val_accuracy: 0.5915\n",
      "Epoch 1185/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3845 - accuracy: 0.8798 - val_loss: 1.2516 - val_accuracy: 0.5915\n",
      "Epoch 1186/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3829 - accuracy: 0.8680 - val_loss: 1.2516 - val_accuracy: 0.5915\n",
      "Epoch 1187/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4003 - accuracy: 0.8504 - val_loss: 1.2546 - val_accuracy: 0.5915\n",
      "Epoch 1188/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3880 - accuracy: 0.8680 - val_loss: 1.2705 - val_accuracy: 0.5915\n",
      "Epoch 1189/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4009 - accuracy: 0.8387 - val_loss: 1.2850 - val_accuracy: 0.5775\n",
      "Epoch 1190/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3859 - accuracy: 0.8592 - val_loss: 1.2648 - val_accuracy: 0.5915\n",
      "Epoch 1191/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3797 - accuracy: 0.8651 - val_loss: 1.2485 - val_accuracy: 0.5915\n",
      "Epoch 1192/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3806 - accuracy: 0.8475 - val_loss: 1.2372 - val_accuracy: 0.5915\n",
      "Epoch 1193/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3894 - accuracy: 0.8622 - val_loss: 1.2280 - val_accuracy: 0.5915\n",
      "Epoch 1194/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3860 - accuracy: 0.8651 - val_loss: 1.2364 - val_accuracy: 0.5915\n",
      "Epoch 1195/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3956 - accuracy: 0.8592 - val_loss: 1.2542 - val_accuracy: 0.5915\n",
      "Epoch 1196/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3872 - accuracy: 0.8798 - val_loss: 1.2678 - val_accuracy: 0.5915\n",
      "Epoch 1197/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3873 - accuracy: 0.8592 - val_loss: 1.2694 - val_accuracy: 0.5915\n",
      "Epoch 1198/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3866 - accuracy: 0.8534 - val_loss: 1.2695 - val_accuracy: 0.5915\n",
      "Epoch 1199/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3860 - accuracy: 0.8739 - val_loss: 1.2677 - val_accuracy: 0.5915\n",
      "Epoch 1200/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3801 - accuracy: 0.8739 - val_loss: 1.2729 - val_accuracy: 0.5915\n",
      "Epoch 1201/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3946 - accuracy: 0.8534 - val_loss: 1.2871 - val_accuracy: 0.5915\n",
      "Epoch 1202/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3943 - accuracy: 0.8710 - val_loss: 1.2780 - val_accuracy: 0.5915\n",
      "Epoch 1203/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3865 - accuracy: 0.8680 - val_loss: 1.2838 - val_accuracy: 0.5915\n",
      "Epoch 1204/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3990 - accuracy: 0.8592 - val_loss: 1.2817 - val_accuracy: 0.5915\n",
      "Epoch 1205/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3792 - accuracy: 0.8651 - val_loss: 1.2762 - val_accuracy: 0.5915\n",
      "Epoch 1206/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3950 - accuracy: 0.8592 - val_loss: 1.2735 - val_accuracy: 0.5915\n",
      "Epoch 1207/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3824 - accuracy: 0.8739 - val_loss: 1.2683 - val_accuracy: 0.5915\n",
      "Epoch 1208/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3800 - accuracy: 0.8680 - val_loss: 1.2604 - val_accuracy: 0.5915\n",
      "Epoch 1209/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3834 - accuracy: 0.8651 - val_loss: 1.2421 - val_accuracy: 0.5915\n",
      "Epoch 1210/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3807 - accuracy: 0.8915 - val_loss: 1.2452 - val_accuracy: 0.5915\n",
      "Epoch 1211/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3816 - accuracy: 0.8680 - val_loss: 1.2527 - val_accuracy: 0.5915\n",
      "Epoch 1212/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3773 - accuracy: 0.8710 - val_loss: 1.2454 - val_accuracy: 0.5915\n",
      "Epoch 1213/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3815 - accuracy: 0.8680 - val_loss: 1.2710 - val_accuracy: 0.5915\n",
      "Epoch 1214/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3967 - accuracy: 0.8651 - val_loss: 1.2863 - val_accuracy: 0.5915\n",
      "Epoch 1215/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3815 - accuracy: 0.8534 - val_loss: 1.2775 - val_accuracy: 0.5915\n",
      "Epoch 1216/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3863 - accuracy: 0.8592 - val_loss: 1.2673 - val_accuracy: 0.5915\n",
      "Epoch 1217/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3963 - accuracy: 0.8680 - val_loss: 1.2580 - val_accuracy: 0.5915\n",
      "Epoch 1218/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3792 - accuracy: 0.8592 - val_loss: 1.2654 - val_accuracy: 0.5915\n",
      "Epoch 1219/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3876 - accuracy: 0.8534 - val_loss: 1.2794 - val_accuracy: 0.5915\n",
      "Epoch 1220/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3859 - accuracy: 0.8592 - val_loss: 1.2961 - val_accuracy: 0.5915\n",
      "Epoch 1221/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3892 - accuracy: 0.8563 - val_loss: 1.2922 - val_accuracy: 0.5915\n",
      "Epoch 1222/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3871 - accuracy: 0.8680 - val_loss: 1.2826 - val_accuracy: 0.5915\n",
      "Epoch 1223/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3878 - accuracy: 0.8563 - val_loss: 1.2781 - val_accuracy: 0.5915\n",
      "Epoch 1224/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3913 - accuracy: 0.8534 - val_loss: 1.2765 - val_accuracy: 0.5915\n",
      "Epoch 1225/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3802 - accuracy: 0.8622 - val_loss: 1.2732 - val_accuracy: 0.5915\n",
      "Epoch 1226/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3790 - accuracy: 0.8680 - val_loss: 1.2674 - val_accuracy: 0.5915\n",
      "Epoch 1227/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.4055 - accuracy: 0.8651 - val_loss: 1.2746 - val_accuracy: 0.5915\n",
      "Epoch 1228/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3867 - accuracy: 0.8680 - val_loss: 1.2717 - val_accuracy: 0.5915\n",
      "Epoch 1229/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3955 - accuracy: 0.8592 - val_loss: 1.2703 - val_accuracy: 0.5915\n",
      "Epoch 1230/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3873 - accuracy: 0.8534 - val_loss: 1.2717 - val_accuracy: 0.5915\n",
      "Epoch 1231/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3971 - accuracy: 0.8446 - val_loss: 1.2688 - val_accuracy: 0.5915\n",
      "Epoch 1232/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3777 - accuracy: 0.8798 - val_loss: 1.2765 - val_accuracy: 0.5915\n",
      "Epoch 1233/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3807 - accuracy: 0.8739 - val_loss: 1.2822 - val_accuracy: 0.5915\n",
      "Epoch 1234/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3957 - accuracy: 0.8416 - val_loss: 1.2936 - val_accuracy: 0.5915\n",
      "Epoch 1235/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3876 - accuracy: 0.8710 - val_loss: 1.3010 - val_accuracy: 0.5915\n",
      "Epoch 1236/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3904 - accuracy: 0.8534 - val_loss: 1.2875 - val_accuracy: 0.5915\n",
      "Epoch 1237/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3817 - accuracy: 0.8710 - val_loss: 1.2827 - val_accuracy: 0.5915\n",
      "Epoch 1238/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3768 - accuracy: 0.8504 - val_loss: 1.2732 - val_accuracy: 0.5915\n",
      "Epoch 1239/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3740 - accuracy: 0.8827 - val_loss: 1.2712 - val_accuracy: 0.5915\n",
      "Epoch 1240/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3934 - accuracy: 0.8475 - val_loss: 1.2721 - val_accuracy: 0.5915\n",
      "Epoch 1241/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3838 - accuracy: 0.8680 - val_loss: 1.2778 - val_accuracy: 0.5915\n",
      "Epoch 1242/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3806 - accuracy: 0.8680 - val_loss: 1.2794 - val_accuracy: 0.5915\n",
      "Epoch 1243/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3777 - accuracy: 0.8768 - val_loss: 1.2808 - val_accuracy: 0.5915\n",
      "Epoch 1244/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3759 - accuracy: 0.8739 - val_loss: 1.2870 - val_accuracy: 0.5915\n",
      "Epoch 1245/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3758 - accuracy: 0.8710 - val_loss: 1.3034 - val_accuracy: 0.5915\n",
      "Epoch 1246/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3735 - accuracy: 0.8739 - val_loss: 1.3056 - val_accuracy: 0.5915\n",
      "Epoch 1247/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3688 - accuracy: 0.8739 - val_loss: 1.3062 - val_accuracy: 0.5775\n",
      "Epoch 1248/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3865 - accuracy: 0.8534 - val_loss: 1.3162 - val_accuracy: 0.5775\n",
      "Epoch 1249/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3777 - accuracy: 0.8827 - val_loss: 1.2930 - val_accuracy: 0.5915\n",
      "Epoch 1250/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3794 - accuracy: 0.8622 - val_loss: 1.2808 - val_accuracy: 0.5915\n",
      "Epoch 1251/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3730 - accuracy: 0.8739 - val_loss: 1.2818 - val_accuracy: 0.5915\n",
      "Epoch 1252/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.3752 - accuracy: 0.8798 - val_loss: 1.2816 - val_accuracy: 0.5915\n",
      "Epoch 1253/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3853 - accuracy: 0.8504 - val_loss: 1.2769 - val_accuracy: 0.5915\n",
      "Epoch 1254/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3784 - accuracy: 0.8563 - val_loss: 1.2830 - val_accuracy: 0.5915\n",
      "Epoch 1255/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3797 - accuracy: 0.8563 - val_loss: 1.2856 - val_accuracy: 0.5915\n",
      "Epoch 1256/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3719 - accuracy: 0.8974 - val_loss: 1.2997 - val_accuracy: 0.5915\n",
      "Epoch 1257/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3796 - accuracy: 0.8622 - val_loss: 1.2977 - val_accuracy: 0.5915\n",
      "Epoch 1258/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3796 - accuracy: 0.8768 - val_loss: 1.2897 - val_accuracy: 0.5915\n",
      "Epoch 1259/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3791 - accuracy: 0.8622 - val_loss: 1.2843 - val_accuracy: 0.5915\n",
      "Epoch 1260/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3765 - accuracy: 0.8710 - val_loss: 1.2804 - val_accuracy: 0.5915\n",
      "Epoch 1261/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3772 - accuracy: 0.8739 - val_loss: 1.2828 - val_accuracy: 0.5915\n",
      "Epoch 1262/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3691 - accuracy: 0.8827 - val_loss: 1.2891 - val_accuracy: 0.5915\n",
      "Epoch 1263/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3754 - accuracy: 0.8798 - val_loss: 1.2779 - val_accuracy: 0.5915\n",
      "Epoch 1264/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3774 - accuracy: 0.8710 - val_loss: 1.2849 - val_accuracy: 0.5915\n",
      "Epoch 1265/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3695 - accuracy: 0.8798 - val_loss: 1.2776 - val_accuracy: 0.5915\n",
      "Epoch 1266/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3857 - accuracy: 0.8563 - val_loss: 1.2810 - val_accuracy: 0.5915\n",
      "Epoch 1267/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3692 - accuracy: 0.8710 - val_loss: 1.2841 - val_accuracy: 0.5915\n",
      "Epoch 1268/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3751 - accuracy: 0.8768 - val_loss: 1.2663 - val_accuracy: 0.5915\n",
      "Epoch 1269/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3809 - accuracy: 0.8651 - val_loss: 1.2514 - val_accuracy: 0.5915\n",
      "Epoch 1270/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3800 - accuracy: 0.8651 - val_loss: 1.2470 - val_accuracy: 0.5915\n",
      "Epoch 1271/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3826 - accuracy: 0.8768 - val_loss: 1.2475 - val_accuracy: 0.5915\n",
      "Epoch 1272/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3804 - accuracy: 0.8592 - val_loss: 1.2690 - val_accuracy: 0.5915\n",
      "Epoch 1273/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3756 - accuracy: 0.8680 - val_loss: 1.2730 - val_accuracy: 0.5915\n",
      "Epoch 1274/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3762 - accuracy: 0.8710 - val_loss: 1.2900 - val_accuracy: 0.5915\n",
      "Epoch 1275/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3798 - accuracy: 0.8592 - val_loss: 1.3073 - val_accuracy: 0.5915\n",
      "Epoch 1276/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3804 - accuracy: 0.8710 - val_loss: 1.3069 - val_accuracy: 0.5915\n",
      "Epoch 1277/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3867 - accuracy: 0.8651 - val_loss: 1.3108 - val_accuracy: 0.5915\n",
      "Epoch 1278/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3699 - accuracy: 0.8768 - val_loss: 1.3072 - val_accuracy: 0.5915\n",
      "Epoch 1279/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3758 - accuracy: 0.8680 - val_loss: 1.3034 - val_accuracy: 0.5915\n",
      "Epoch 1280/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3807 - accuracy: 0.8622 - val_loss: 1.3049 - val_accuracy: 0.5915\n",
      "Epoch 1281/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3771 - accuracy: 0.8651 - val_loss: 1.2920 - val_accuracy: 0.5915\n",
      "Epoch 1282/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3824 - accuracy: 0.8622 - val_loss: 1.2870 - val_accuracy: 0.5915\n",
      "Epoch 1283/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3734 - accuracy: 0.8768 - val_loss: 1.2745 - val_accuracy: 0.5915\n",
      "Epoch 1284/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3851 - accuracy: 0.8622 - val_loss: 1.2779 - val_accuracy: 0.5915\n",
      "Epoch 1285/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3907 - accuracy: 0.8446 - val_loss: 1.2888 - val_accuracy: 0.5915\n",
      "Epoch 1286/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3730 - accuracy: 0.8739 - val_loss: 1.3008 - val_accuracy: 0.5915\n",
      "Epoch 1287/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3766 - accuracy: 0.8651 - val_loss: 1.3085 - val_accuracy: 0.5915\n",
      "Epoch 1288/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3765 - accuracy: 0.8680 - val_loss: 1.3038 - val_accuracy: 0.5915\n",
      "Epoch 1289/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3825 - accuracy: 0.8710 - val_loss: 1.2900 - val_accuracy: 0.5915\n",
      "Epoch 1290/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3732 - accuracy: 0.8739 - val_loss: 1.2861 - val_accuracy: 0.5915\n",
      "Epoch 1291/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3723 - accuracy: 0.8768 - val_loss: 1.3049 - val_accuracy: 0.5915\n",
      "Epoch 1292/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3747 - accuracy: 0.8680 - val_loss: 1.3113 - val_accuracy: 0.5915\n",
      "Epoch 1293/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3864 - accuracy: 0.8680 - val_loss: 1.2904 - val_accuracy: 0.5915\n",
      "Epoch 1294/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3768 - accuracy: 0.8680 - val_loss: 1.2938 - val_accuracy: 0.5915\n",
      "Epoch 1295/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3770 - accuracy: 0.8710 - val_loss: 1.2844 - val_accuracy: 0.5915\n",
      "Epoch 1296/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3783 - accuracy: 0.8827 - val_loss: 1.2789 - val_accuracy: 0.5915\n",
      "Epoch 1297/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3780 - accuracy: 0.8680 - val_loss: 1.2629 - val_accuracy: 0.5915\n",
      "Epoch 1298/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3798 - accuracy: 0.8534 - val_loss: 1.2695 - val_accuracy: 0.5915\n",
      "Epoch 1299/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3702 - accuracy: 0.8827 - val_loss: 1.2889 - val_accuracy: 0.5915\n",
      "Epoch 1300/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3760 - accuracy: 0.8651 - val_loss: 1.3058 - val_accuracy: 0.5915\n",
      "Epoch 1301/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.3756 - accuracy: 0.8710 - val_loss: 1.3031 - val_accuracy: 0.5915\n",
      "Epoch 1302/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3756 - accuracy: 0.8739 - val_loss: 1.3113 - val_accuracy: 0.5915\n",
      "Epoch 1303/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3728 - accuracy: 0.8710 - val_loss: 1.3178 - val_accuracy: 0.5915\n",
      "Epoch 1304/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.3844 - accuracy: 0.8504 - val_loss: 1.3093 - val_accuracy: 0.5915\n",
      "Epoch 1305/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3787 - accuracy: 0.8622 - val_loss: 1.3281 - val_accuracy: 0.5915\n",
      "Epoch 1306/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3755 - accuracy: 0.8651 - val_loss: 1.3374 - val_accuracy: 0.5915\n",
      "Epoch 1307/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3773 - accuracy: 0.8651 - val_loss: 1.3392 - val_accuracy: 0.5915\n",
      "Epoch 1308/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3816 - accuracy: 0.8534 - val_loss: 1.3444 - val_accuracy: 0.5915\n",
      "Epoch 1309/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3826 - accuracy: 0.8680 - val_loss: 1.3519 - val_accuracy: 0.5915\n",
      "Epoch 1310/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3779 - accuracy: 0.8710 - val_loss: 1.3504 - val_accuracy: 0.5915\n",
      "Epoch 1311/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3845 - accuracy: 0.8475 - val_loss: 1.3444 - val_accuracy: 0.5915\n",
      "Epoch 1312/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.3801 - accuracy: 0.8504 - val_loss: 1.3527 - val_accuracy: 0.5775\n",
      "Epoch 1313/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3740 - accuracy: 0.8592 - val_loss: 1.3508 - val_accuracy: 0.5775\n",
      "Epoch 1314/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3761 - accuracy: 0.8739 - val_loss: 1.3573 - val_accuracy: 0.5775\n",
      "Epoch 1315/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3791 - accuracy: 0.8827 - val_loss: 1.3642 - val_accuracy: 0.5775\n",
      "Epoch 1316/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3644 - accuracy: 0.8768 - val_loss: 1.3663 - val_accuracy: 0.5634\n",
      "Epoch 1317/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3740 - accuracy: 0.8768 - val_loss: 1.3776 - val_accuracy: 0.5634\n",
      "Epoch 1318/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3737 - accuracy: 0.8622 - val_loss: 1.3653 - val_accuracy: 0.5775\n",
      "Epoch 1319/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3768 - accuracy: 0.8680 - val_loss: 1.3622 - val_accuracy: 0.5775\n",
      "Epoch 1320/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3728 - accuracy: 0.8680 - val_loss: 1.3702 - val_accuracy: 0.5775\n",
      "Epoch 1321/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3686 - accuracy: 0.8798 - val_loss: 1.3451 - val_accuracy: 0.5915\n",
      "Epoch 1322/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3695 - accuracy: 0.8798 - val_loss: 1.3323 - val_accuracy: 0.5915\n",
      "Epoch 1323/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3772 - accuracy: 0.8446 - val_loss: 1.3181 - val_accuracy: 0.5915\n",
      "Epoch 1324/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3707 - accuracy: 0.8622 - val_loss: 1.3370 - val_accuracy: 0.5915\n",
      "Epoch 1325/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3705 - accuracy: 0.8680 - val_loss: 1.3343 - val_accuracy: 0.5915\n",
      "Epoch 1326/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3690 - accuracy: 0.8710 - val_loss: 1.3438 - val_accuracy: 0.5915\n",
      "Epoch 1327/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3686 - accuracy: 0.8768 - val_loss: 1.3498 - val_accuracy: 0.5915\n",
      "Epoch 1328/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3733 - accuracy: 0.8622 - val_loss: 1.3466 - val_accuracy: 0.5915\n",
      "Epoch 1329/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3767 - accuracy: 0.8504 - val_loss: 1.3459 - val_accuracy: 0.5915\n",
      "Epoch 1330/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3658 - accuracy: 0.8827 - val_loss: 1.3411 - val_accuracy: 0.5915\n",
      "Epoch 1331/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3755 - accuracy: 0.8651 - val_loss: 1.3521 - val_accuracy: 0.5775\n",
      "Epoch 1332/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3709 - accuracy: 0.8768 - val_loss: 1.3572 - val_accuracy: 0.5775\n",
      "Epoch 1333/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3818 - accuracy: 0.8563 - val_loss: 1.3522 - val_accuracy: 0.5915\n",
      "Epoch 1334/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3726 - accuracy: 0.8798 - val_loss: 1.3465 - val_accuracy: 0.5915\n",
      "Epoch 1335/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3662 - accuracy: 0.8739 - val_loss: 1.3258 - val_accuracy: 0.5915\n",
      "Epoch 1336/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3820 - accuracy: 0.8622 - val_loss: 1.3293 - val_accuracy: 0.5915\n",
      "Epoch 1337/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3685 - accuracy: 0.8710 - val_loss: 1.3300 - val_accuracy: 0.5915\n",
      "Epoch 1338/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3617 - accuracy: 0.8710 - val_loss: 1.3237 - val_accuracy: 0.5915\n",
      "Epoch 1339/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3663 - accuracy: 0.8710 - val_loss: 1.3216 - val_accuracy: 0.5915\n",
      "Epoch 1340/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3679 - accuracy: 0.8768 - val_loss: 1.3197 - val_accuracy: 0.5915\n",
      "Epoch 1341/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3668 - accuracy: 0.8622 - val_loss: 1.3358 - val_accuracy: 0.5915\n",
      "Epoch 1342/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3708 - accuracy: 0.8739 - val_loss: 1.3344 - val_accuracy: 0.5915\n",
      "Epoch 1343/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3640 - accuracy: 0.8680 - val_loss: 1.3364 - val_accuracy: 0.5915\n",
      "Epoch 1344/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3654 - accuracy: 0.8710 - val_loss: 1.3397 - val_accuracy: 0.5915\n",
      "Epoch 1345/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3685 - accuracy: 0.8710 - val_loss: 1.3468 - val_accuracy: 0.5915\n",
      "Epoch 1346/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3676 - accuracy: 0.8710 - val_loss: 1.3527 - val_accuracy: 0.5915\n",
      "Epoch 1347/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3695 - accuracy: 0.8827 - val_loss: 1.3368 - val_accuracy: 0.5915\n",
      "Epoch 1348/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3730 - accuracy: 0.8739 - val_loss: 1.3493 - val_accuracy: 0.5915\n",
      "Epoch 1349/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3776 - accuracy: 0.8622 - val_loss: 1.3603 - val_accuracy: 0.5915\n",
      "Epoch 1350/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3665 - accuracy: 0.8651 - val_loss: 1.3568 - val_accuracy: 0.5915\n",
      "Epoch 1351/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3674 - accuracy: 0.8622 - val_loss: 1.3623 - val_accuracy: 0.5915\n",
      "Epoch 1352/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3604 - accuracy: 0.8827 - val_loss: 1.3731 - val_accuracy: 0.5775\n",
      "Epoch 1353/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3652 - accuracy: 0.8622 - val_loss: 1.3777 - val_accuracy: 0.5775\n",
      "Epoch 1354/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3710 - accuracy: 0.8680 - val_loss: 1.3910 - val_accuracy: 0.5634\n",
      "Epoch 1355/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3914 - accuracy: 0.8446 - val_loss: 1.3862 - val_accuracy: 0.5775\n",
      "Epoch 1356/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3653 - accuracy: 0.8680 - val_loss: 1.3747 - val_accuracy: 0.5775\n",
      "Epoch 1357/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3663 - accuracy: 0.8651 - val_loss: 1.3539 - val_accuracy: 0.5915\n",
      "Epoch 1358/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3630 - accuracy: 0.8768 - val_loss: 1.3433 - val_accuracy: 0.5915\n",
      "Epoch 1359/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3698 - accuracy: 0.8622 - val_loss: 1.3322 - val_accuracy: 0.5915\n",
      "Epoch 1360/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3782 - accuracy: 0.8563 - val_loss: 1.3524 - val_accuracy: 0.5915\n",
      "Epoch 1361/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3732 - accuracy: 0.8680 - val_loss: 1.3644 - val_accuracy: 0.5915\n",
      "Epoch 1362/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3771 - accuracy: 0.8710 - val_loss: 1.3616 - val_accuracy: 0.5915\n",
      "Epoch 1363/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3723 - accuracy: 0.8534 - val_loss: 1.3531 - val_accuracy: 0.5915\n",
      "Epoch 1364/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3667 - accuracy: 0.8710 - val_loss: 1.3470 - val_accuracy: 0.5915\n",
      "Epoch 1365/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3703 - accuracy: 0.8622 - val_loss: 1.3551 - val_accuracy: 0.5915\n",
      "Epoch 1366/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3736 - accuracy: 0.8504 - val_loss: 1.3573 - val_accuracy: 0.5915\n",
      "Epoch 1367/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3646 - accuracy: 0.8592 - val_loss: 1.3466 - val_accuracy: 0.5915\n",
      "Epoch 1368/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3719 - accuracy: 0.8710 - val_loss: 1.3499 - val_accuracy: 0.5915\n",
      "Epoch 1369/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3789 - accuracy: 0.8592 - val_loss: 1.3622 - val_accuracy: 0.5915\n",
      "Epoch 1370/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3722 - accuracy: 0.8592 - val_loss: 1.3683 - val_accuracy: 0.5915\n",
      "Epoch 1371/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3634 - accuracy: 0.8739 - val_loss: 1.3669 - val_accuracy: 0.5915\n",
      "Epoch 1372/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3742 - accuracy: 0.8622 - val_loss: 1.3530 - val_accuracy: 0.5915\n",
      "Epoch 1373/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3774 - accuracy: 0.8563 - val_loss: 1.3604 - val_accuracy: 0.5915\n",
      "Epoch 1374/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3692 - accuracy: 0.8768 - val_loss: 1.3578 - val_accuracy: 0.5915\n",
      "Epoch 1375/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3674 - accuracy: 0.8856 - val_loss: 1.3558 - val_accuracy: 0.5915\n",
      "Epoch 1376/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3622 - accuracy: 0.8680 - val_loss: 1.3651 - val_accuracy: 0.5915\n",
      "Epoch 1377/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3837 - accuracy: 0.8680 - val_loss: 1.3603 - val_accuracy: 0.5915\n",
      "Epoch 1378/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3774 - accuracy: 0.8710 - val_loss: 1.3717 - val_accuracy: 0.5915\n",
      "Epoch 1379/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3645 - accuracy: 0.8710 - val_loss: 1.3716 - val_accuracy: 0.5915\n",
      "Epoch 1380/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3695 - accuracy: 0.8622 - val_loss: 1.3652 - val_accuracy: 0.5915\n",
      "Epoch 1381/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3645 - accuracy: 0.8651 - val_loss: 1.3689 - val_accuracy: 0.5915\n",
      "Epoch 1382/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3650 - accuracy: 0.8798 - val_loss: 1.3749 - val_accuracy: 0.5915\n",
      "Epoch 1383/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3782 - accuracy: 0.8563 - val_loss: 1.3934 - val_accuracy: 0.5775\n",
      "Epoch 1384/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3635 - accuracy: 0.8622 - val_loss: 1.3881 - val_accuracy: 0.5775\n",
      "Epoch 1385/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3646 - accuracy: 0.8827 - val_loss: 1.3881 - val_accuracy: 0.5775\n",
      "Epoch 1386/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3687 - accuracy: 0.8739 - val_loss: 1.3919 - val_accuracy: 0.5775\n",
      "Epoch 1387/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3703 - accuracy: 0.8622 - val_loss: 1.4029 - val_accuracy: 0.5634\n",
      "Epoch 1388/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3572 - accuracy: 0.8768 - val_loss: 1.4192 - val_accuracy: 0.5634\n",
      "Epoch 1389/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3610 - accuracy: 0.8710 - val_loss: 1.4096 - val_accuracy: 0.5634\n",
      "Epoch 1390/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3702 - accuracy: 0.8651 - val_loss: 1.3993 - val_accuracy: 0.5775\n",
      "Epoch 1391/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3643 - accuracy: 0.8592 - val_loss: 1.3869 - val_accuracy: 0.5775\n",
      "Epoch 1392/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3676 - accuracy: 0.8710 - val_loss: 1.3917 - val_accuracy: 0.5775\n",
      "Epoch 1393/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3632 - accuracy: 0.8827 - val_loss: 1.4102 - val_accuracy: 0.5634\n",
      "Epoch 1394/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3692 - accuracy: 0.8739 - val_loss: 1.4152 - val_accuracy: 0.5634\n",
      "Epoch 1395/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3624 - accuracy: 0.8622 - val_loss: 1.4077 - val_accuracy: 0.5775\n",
      "Epoch 1396/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3730 - accuracy: 0.8680 - val_loss: 1.4055 - val_accuracy: 0.5775\n",
      "Epoch 1397/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3664 - accuracy: 0.8827 - val_loss: 1.4163 - val_accuracy: 0.5634\n",
      "Epoch 1398/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3618 - accuracy: 0.8710 - val_loss: 1.4164 - val_accuracy: 0.5634\n",
      "Epoch 1399/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3625 - accuracy: 0.8739 - val_loss: 1.4156 - val_accuracy: 0.5775\n",
      "Epoch 1400/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3618 - accuracy: 0.8680 - val_loss: 1.4096 - val_accuracy: 0.5775\n",
      "Epoch 1401/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3596 - accuracy: 0.8710 - val_loss: 1.4082 - val_accuracy: 0.5775\n",
      "Epoch 1402/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3704 - accuracy: 0.8563 - val_loss: 1.4186 - val_accuracy: 0.5775\n",
      "Epoch 1403/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3627 - accuracy: 0.8680 - val_loss: 1.4059 - val_accuracy: 0.5775\n",
      "Epoch 1404/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3611 - accuracy: 0.8768 - val_loss: 1.4092 - val_accuracy: 0.5775\n",
      "Epoch 1405/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3582 - accuracy: 0.8798 - val_loss: 1.4082 - val_accuracy: 0.5775\n",
      "Epoch 1406/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3634 - accuracy: 0.8798 - val_loss: 1.3998 - val_accuracy: 0.5775\n",
      "Epoch 1407/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3804 - accuracy: 0.8446 - val_loss: 1.3844 - val_accuracy: 0.5775\n",
      "Epoch 1408/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3585 - accuracy: 0.8768 - val_loss: 1.3958 - val_accuracy: 0.5775\n",
      "Epoch 1409/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3585 - accuracy: 0.8798 - val_loss: 1.4006 - val_accuracy: 0.5775\n",
      "Epoch 1410/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3671 - accuracy: 0.8710 - val_loss: 1.4078 - val_accuracy: 0.5775\n",
      "Epoch 1411/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3589 - accuracy: 0.8856 - val_loss: 1.4052 - val_accuracy: 0.5775\n",
      "Epoch 1412/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3645 - accuracy: 0.8651 - val_loss: 1.4056 - val_accuracy: 0.5775\n",
      "Epoch 1413/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3676 - accuracy: 0.8622 - val_loss: 1.3894 - val_accuracy: 0.5775\n",
      "Epoch 1414/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3558 - accuracy: 0.8798 - val_loss: 1.3883 - val_accuracy: 0.5775\n",
      "Epoch 1415/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3705 - accuracy: 0.8592 - val_loss: 1.3944 - val_accuracy: 0.5775\n",
      "Epoch 1416/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3581 - accuracy: 0.8739 - val_loss: 1.3817 - val_accuracy: 0.5915\n",
      "Epoch 1417/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3694 - accuracy: 0.8710 - val_loss: 1.3843 - val_accuracy: 0.5915\n",
      "Epoch 1418/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3637 - accuracy: 0.8739 - val_loss: 1.4001 - val_accuracy: 0.5775\n",
      "Epoch 1419/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3611 - accuracy: 0.8680 - val_loss: 1.4086 - val_accuracy: 0.5775\n",
      "Epoch 1420/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3678 - accuracy: 0.8563 - val_loss: 1.3962 - val_accuracy: 0.5775\n",
      "Epoch 1421/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3659 - accuracy: 0.8592 - val_loss: 1.3898 - val_accuracy: 0.5775\n",
      "Epoch 1422/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3735 - accuracy: 0.8680 - val_loss: 1.3836 - val_accuracy: 0.5915\n",
      "Epoch 1423/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3690 - accuracy: 0.8768 - val_loss: 1.3894 - val_accuracy: 0.5775\n",
      "Epoch 1424/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3577 - accuracy: 0.8651 - val_loss: 1.3941 - val_accuracy: 0.5775\n",
      "Epoch 1425/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3703 - accuracy: 0.8622 - val_loss: 1.4180 - val_accuracy: 0.5775\n",
      "Epoch 1426/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3660 - accuracy: 0.8710 - val_loss: 1.4082 - val_accuracy: 0.5775\n",
      "Epoch 1427/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3548 - accuracy: 0.8739 - val_loss: 1.4042 - val_accuracy: 0.5775\n",
      "Epoch 1428/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3671 - accuracy: 0.8710 - val_loss: 1.3945 - val_accuracy: 0.5775\n",
      "Epoch 1429/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3685 - accuracy: 0.8475 - val_loss: 1.3858 - val_accuracy: 0.5775\n",
      "Epoch 1430/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3646 - accuracy: 0.8592 - val_loss: 1.3902 - val_accuracy: 0.5775\n",
      "Epoch 1431/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3573 - accuracy: 0.8739 - val_loss: 1.4087 - val_accuracy: 0.5775\n",
      "Epoch 1432/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3592 - accuracy: 0.8622 - val_loss: 1.4259 - val_accuracy: 0.5775\n",
      "Epoch 1433/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3665 - accuracy: 0.8651 - val_loss: 1.4358 - val_accuracy: 0.5634\n",
      "Epoch 1434/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3562 - accuracy: 0.8680 - val_loss: 1.4538 - val_accuracy: 0.5634\n",
      "Epoch 1435/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3606 - accuracy: 0.8768 - val_loss: 1.4296 - val_accuracy: 0.5775\n",
      "Epoch 1436/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3576 - accuracy: 0.8592 - val_loss: 1.4348 - val_accuracy: 0.5775\n",
      "Epoch 1437/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3559 - accuracy: 0.8592 - val_loss: 1.4396 - val_accuracy: 0.5634\n",
      "Epoch 1438/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3578 - accuracy: 0.8856 - val_loss: 1.4415 - val_accuracy: 0.5634\n",
      "Epoch 1439/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3659 - accuracy: 0.8651 - val_loss: 1.4587 - val_accuracy: 0.5634\n",
      "Epoch 1440/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3731 - accuracy: 0.8622 - val_loss: 1.4634 - val_accuracy: 0.5634\n",
      "Epoch 1441/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3615 - accuracy: 0.8651 - val_loss: 1.4660 - val_accuracy: 0.5634\n",
      "Epoch 1442/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3547 - accuracy: 0.8798 - val_loss: 1.4626 - val_accuracy: 0.5634\n",
      "Epoch 1443/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3553 - accuracy: 0.8768 - val_loss: 1.4639 - val_accuracy: 0.5634\n",
      "Epoch 1444/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3578 - accuracy: 0.8680 - val_loss: 1.4682 - val_accuracy: 0.5634\n",
      "Epoch 1445/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3587 - accuracy: 0.8739 - val_loss: 1.4563 - val_accuracy: 0.5634\n",
      "Epoch 1446/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3565 - accuracy: 0.8710 - val_loss: 1.4473 - val_accuracy: 0.5634\n",
      "Epoch 1447/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.3690 - accuracy: 0.8710 - val_loss: 1.4515 - val_accuracy: 0.5634\n",
      "Epoch 1448/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3565 - accuracy: 0.8680 - val_loss: 1.4619 - val_accuracy: 0.5634\n",
      "Epoch 1449/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3595 - accuracy: 0.8739 - val_loss: 1.4279 - val_accuracy: 0.5775\n",
      "Epoch 1450/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3636 - accuracy: 0.8680 - val_loss: 1.4202 - val_accuracy: 0.5775\n",
      "Epoch 1451/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3657 - accuracy: 0.8504 - val_loss: 1.4323 - val_accuracy: 0.5775\n",
      "Epoch 1452/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3541 - accuracy: 0.8886 - val_loss: 1.4314 - val_accuracy: 0.5775\n",
      "Epoch 1453/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3585 - accuracy: 0.8798 - val_loss: 1.4398 - val_accuracy: 0.5775\n",
      "Epoch 1454/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3510 - accuracy: 0.8739 - val_loss: 1.4515 - val_accuracy: 0.5775\n",
      "Epoch 1455/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3621 - accuracy: 0.8680 - val_loss: 1.4628 - val_accuracy: 0.5634\n",
      "Epoch 1456/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3676 - accuracy: 0.8622 - val_loss: 1.4561 - val_accuracy: 0.5634\n",
      "Epoch 1457/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3690 - accuracy: 0.8622 - val_loss: 1.4424 - val_accuracy: 0.5775\n",
      "Epoch 1458/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3545 - accuracy: 0.8827 - val_loss: 1.4253 - val_accuracy: 0.5775\n",
      "Epoch 1459/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3509 - accuracy: 0.8886 - val_loss: 1.4332 - val_accuracy: 0.5775\n",
      "Epoch 1460/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3541 - accuracy: 0.8651 - val_loss: 1.4455 - val_accuracy: 0.5775\n",
      "Epoch 1461/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3501 - accuracy: 0.8710 - val_loss: 1.4514 - val_accuracy: 0.5634\n",
      "Epoch 1462/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3529 - accuracy: 0.8827 - val_loss: 1.4593 - val_accuracy: 0.5634\n",
      "Epoch 1463/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3667 - accuracy: 0.8680 - val_loss: 1.4689 - val_accuracy: 0.5634\n",
      "Epoch 1464/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3541 - accuracy: 0.8680 - val_loss: 1.4720 - val_accuracy: 0.5634\n",
      "Epoch 1465/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3702 - accuracy: 0.8651 - val_loss: 1.4696 - val_accuracy: 0.5634\n",
      "Epoch 1466/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3699 - accuracy: 0.8768 - val_loss: 1.4638 - val_accuracy: 0.5634\n",
      "Epoch 1467/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3591 - accuracy: 0.8710 - val_loss: 1.4832 - val_accuracy: 0.5634\n",
      "Epoch 1468/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3516 - accuracy: 0.8739 - val_loss: 1.4963 - val_accuracy: 0.5634\n",
      "Epoch 1469/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3584 - accuracy: 0.8739 - val_loss: 1.4913 - val_accuracy: 0.5634\n",
      "Epoch 1470/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3595 - accuracy: 0.8622 - val_loss: 1.4705 - val_accuracy: 0.5634\n",
      "Epoch 1471/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3648 - accuracy: 0.8856 - val_loss: 1.4735 - val_accuracy: 0.5634\n",
      "Epoch 1472/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3537 - accuracy: 0.8827 - val_loss: 1.4738 - val_accuracy: 0.5634\n",
      "Epoch 1473/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3543 - accuracy: 0.8768 - val_loss: 1.4594 - val_accuracy: 0.5775\n",
      "Epoch 1474/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3624 - accuracy: 0.8622 - val_loss: 1.4558 - val_accuracy: 0.5775\n",
      "Epoch 1475/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3572 - accuracy: 0.8651 - val_loss: 1.4721 - val_accuracy: 0.5634\n",
      "Epoch 1476/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3584 - accuracy: 0.8768 - val_loss: 1.4693 - val_accuracy: 0.5634\n",
      "Epoch 1477/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3537 - accuracy: 0.8798 - val_loss: 1.4794 - val_accuracy: 0.5634\n",
      "Epoch 1478/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3544 - accuracy: 0.8651 - val_loss: 1.4782 - val_accuracy: 0.5634\n",
      "Epoch 1479/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3730 - accuracy: 0.8622 - val_loss: 1.4716 - val_accuracy: 0.5634\n",
      "Epoch 1480/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3549 - accuracy: 0.8739 - val_loss: 1.4637 - val_accuracy: 0.5634\n",
      "Epoch 1481/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3519 - accuracy: 0.8710 - val_loss: 1.4719 - val_accuracy: 0.5634\n",
      "Epoch 1482/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3598 - accuracy: 0.8827 - val_loss: 1.4659 - val_accuracy: 0.5634\n",
      "Epoch 1483/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3661 - accuracy: 0.8651 - val_loss: 1.4747 - val_accuracy: 0.5634\n",
      "Epoch 1484/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3543 - accuracy: 0.8886 - val_loss: 1.4658 - val_accuracy: 0.5634\n",
      "Epoch 1485/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3640 - accuracy: 0.8651 - val_loss: 1.4401 - val_accuracy: 0.5775\n",
      "Epoch 1486/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3617 - accuracy: 0.8651 - val_loss: 1.4451 - val_accuracy: 0.5775\n",
      "Epoch 1487/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3594 - accuracy: 0.8739 - val_loss: 1.4351 - val_accuracy: 0.5775\n",
      "Epoch 1488/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3490 - accuracy: 0.8768 - val_loss: 1.4192 - val_accuracy: 0.5775\n",
      "Epoch 1489/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3595 - accuracy: 0.8680 - val_loss: 1.4013 - val_accuracy: 0.5775\n",
      "Epoch 1490/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3658 - accuracy: 0.8768 - val_loss: 1.4193 - val_accuracy: 0.5775\n",
      "Epoch 1491/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3530 - accuracy: 0.8592 - val_loss: 1.4625 - val_accuracy: 0.5775\n",
      "Epoch 1492/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3623 - accuracy: 0.8710 - val_loss: 1.4749 - val_accuracy: 0.5634\n",
      "Epoch 1493/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3490 - accuracy: 0.9032 - val_loss: 1.4677 - val_accuracy: 0.5775\n",
      "Epoch 1494/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3561 - accuracy: 0.8739 - val_loss: 1.4728 - val_accuracy: 0.5634\n",
      "Epoch 1495/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3493 - accuracy: 0.8827 - val_loss: 1.4619 - val_accuracy: 0.5775\n",
      "Epoch 1496/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3607 - accuracy: 0.8768 - val_loss: 1.4766 - val_accuracy: 0.5634\n",
      "Epoch 1497/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3488 - accuracy: 0.8944 - val_loss: 1.4760 - val_accuracy: 0.5634\n",
      "Epoch 1498/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3578 - accuracy: 0.8680 - val_loss: 1.4535 - val_accuracy: 0.5775\n",
      "Epoch 1499/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3477 - accuracy: 0.8651 - val_loss: 1.4568 - val_accuracy: 0.5775\n",
      "Epoch 1500/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3663 - accuracy: 0.8768 - val_loss: 1.4463 - val_accuracy: 0.5775\n",
      "Epoch 1501/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3745 - accuracy: 0.8358 - val_loss: 1.4515 - val_accuracy: 0.5775\n",
      "Epoch 1502/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3553 - accuracy: 0.8710 - val_loss: 1.4470 - val_accuracy: 0.5775\n",
      "Epoch 1503/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3530 - accuracy: 0.8856 - val_loss: 1.4465 - val_accuracy: 0.5775\n",
      "Epoch 1504/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3558 - accuracy: 0.8856 - val_loss: 1.4439 - val_accuracy: 0.5775\n",
      "Epoch 1505/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3555 - accuracy: 0.8592 - val_loss: 1.4511 - val_accuracy: 0.5775\n",
      "Epoch 1506/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3525 - accuracy: 0.8798 - val_loss: 1.4645 - val_accuracy: 0.5775\n",
      "Epoch 1507/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3579 - accuracy: 0.8680 - val_loss: 1.4901 - val_accuracy: 0.5634\n",
      "Epoch 1508/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3495 - accuracy: 0.8856 - val_loss: 1.5152 - val_accuracy: 0.5634\n",
      "Epoch 1509/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3561 - accuracy: 0.8622 - val_loss: 1.5119 - val_accuracy: 0.5634\n",
      "Epoch 1510/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3502 - accuracy: 0.8856 - val_loss: 1.5102 - val_accuracy: 0.5634\n",
      "Epoch 1511/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3476 - accuracy: 0.8710 - val_loss: 1.4923 - val_accuracy: 0.5775\n",
      "Epoch 1512/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3531 - accuracy: 0.8710 - val_loss: 1.4765 - val_accuracy: 0.5775\n",
      "Epoch 1513/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3551 - accuracy: 0.8768 - val_loss: 1.4737 - val_accuracy: 0.5775\n",
      "Epoch 1514/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3572 - accuracy: 0.8768 - val_loss: 1.4606 - val_accuracy: 0.5775\n",
      "Epoch 1515/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3610 - accuracy: 0.8739 - val_loss: 1.4549 - val_accuracy: 0.5775\n",
      "Epoch 1516/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3564 - accuracy: 0.8592 - val_loss: 1.4607 - val_accuracy: 0.5775\n",
      "Epoch 1517/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3642 - accuracy: 0.8592 - val_loss: 1.4621 - val_accuracy: 0.5775\n",
      "Epoch 1518/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3474 - accuracy: 0.8798 - val_loss: 1.4582 - val_accuracy: 0.5775\n",
      "Epoch 1519/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3650 - accuracy: 0.8768 - val_loss: 1.4503 - val_accuracy: 0.5775\n",
      "Epoch 1520/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3630 - accuracy: 0.8915 - val_loss: 1.4824 - val_accuracy: 0.5775\n",
      "Epoch 1521/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3458 - accuracy: 0.8798 - val_loss: 1.4959 - val_accuracy: 0.5775\n",
      "Epoch 1522/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3566 - accuracy: 0.8739 - val_loss: 1.5052 - val_accuracy: 0.5634\n",
      "Epoch 1523/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3506 - accuracy: 0.9032 - val_loss: 1.5148 - val_accuracy: 0.5634\n",
      "Epoch 1524/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3804 - accuracy: 0.8534 - val_loss: 1.5209 - val_accuracy: 0.5493\n",
      "Epoch 1525/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3738 - accuracy: 0.8622 - val_loss: 1.5107 - val_accuracy: 0.5634\n",
      "Epoch 1526/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3680 - accuracy: 0.8768 - val_loss: 1.5352 - val_accuracy: 0.5493\n",
      "Epoch 1527/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3487 - accuracy: 0.8856 - val_loss: 1.5087 - val_accuracy: 0.5634\n",
      "Epoch 1528/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3545 - accuracy: 0.8592 - val_loss: 1.4990 - val_accuracy: 0.5634\n",
      "Epoch 1529/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3462 - accuracy: 0.8798 - val_loss: 1.5019 - val_accuracy: 0.5634\n",
      "Epoch 1530/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3493 - accuracy: 0.8680 - val_loss: 1.4985 - val_accuracy: 0.5775\n",
      "Epoch 1531/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3535 - accuracy: 0.8886 - val_loss: 1.4794 - val_accuracy: 0.5775\n",
      "Epoch 1532/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3516 - accuracy: 0.8798 - val_loss: 1.4817 - val_accuracy: 0.5775\n",
      "Epoch 1533/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3628 - accuracy: 0.8504 - val_loss: 1.4920 - val_accuracy: 0.5775\n",
      "Epoch 1534/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3563 - accuracy: 0.8827 - val_loss: 1.4774 - val_accuracy: 0.5775\n",
      "Epoch 1535/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3499 - accuracy: 0.8798 - val_loss: 1.4827 - val_accuracy: 0.5775\n",
      "Epoch 1536/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3491 - accuracy: 0.8856 - val_loss: 1.4905 - val_accuracy: 0.5775\n",
      "Epoch 1537/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3568 - accuracy: 0.8827 - val_loss: 1.4784 - val_accuracy: 0.5775\n",
      "Epoch 1538/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3507 - accuracy: 0.8710 - val_loss: 1.4519 - val_accuracy: 0.5775\n",
      "Epoch 1539/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3655 - accuracy: 0.8886 - val_loss: 1.4406 - val_accuracy: 0.5775\n",
      "Epoch 1540/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3584 - accuracy: 0.8768 - val_loss: 1.4324 - val_accuracy: 0.5775\n",
      "Epoch 1541/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3498 - accuracy: 0.8886 - val_loss: 1.4376 - val_accuracy: 0.5775\n",
      "Epoch 1542/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3628 - accuracy: 0.8739 - val_loss: 1.4518 - val_accuracy: 0.5775\n",
      "Epoch 1543/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3526 - accuracy: 0.8651 - val_loss: 1.4857 - val_accuracy: 0.5775\n",
      "Epoch 1544/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3491 - accuracy: 0.8798 - val_loss: 1.5023 - val_accuracy: 0.5775\n",
      "Epoch 1545/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3502 - accuracy: 0.8710 - val_loss: 1.5044 - val_accuracy: 0.5775\n",
      "Epoch 1546/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3626 - accuracy: 0.8680 - val_loss: 1.5185 - val_accuracy: 0.5634\n",
      "Epoch 1547/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3602 - accuracy: 0.8739 - val_loss: 1.5150 - val_accuracy: 0.5634\n",
      "Epoch 1548/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3472 - accuracy: 0.8798 - val_loss: 1.5241 - val_accuracy: 0.5634\n",
      "Epoch 1549/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3495 - accuracy: 0.8739 - val_loss: 1.5198 - val_accuracy: 0.5634\n",
      "Epoch 1550/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3501 - accuracy: 0.8798 - val_loss: 1.5120 - val_accuracy: 0.5634\n",
      "Epoch 1551/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3568 - accuracy: 0.8739 - val_loss: 1.5259 - val_accuracy: 0.5634\n",
      "Epoch 1552/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3712 - accuracy: 0.8534 - val_loss: 1.5309 - val_accuracy: 0.5493\n",
      "Epoch 1553/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3562 - accuracy: 0.8768 - val_loss: 1.5598 - val_accuracy: 0.5352\n",
      "Epoch 1554/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3587 - accuracy: 0.8651 - val_loss: 1.5837 - val_accuracy: 0.5352\n",
      "Epoch 1555/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3470 - accuracy: 0.8856 - val_loss: 1.5680 - val_accuracy: 0.5352\n",
      "Epoch 1556/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3617 - accuracy: 0.8710 - val_loss: 1.5761 - val_accuracy: 0.5352\n",
      "Epoch 1557/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3681 - accuracy: 0.8387 - val_loss: 1.5899 - val_accuracy: 0.5211\n",
      "Epoch 1558/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3397 - accuracy: 0.8739 - val_loss: 1.6139 - val_accuracy: 0.5211\n",
      "Epoch 1559/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3504 - accuracy: 0.8680 - val_loss: 1.6173 - val_accuracy: 0.5211\n",
      "Epoch 1560/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3533 - accuracy: 0.8827 - val_loss: 1.6144 - val_accuracy: 0.5211\n",
      "Epoch 1561/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3484 - accuracy: 0.8710 - val_loss: 1.5987 - val_accuracy: 0.5211\n",
      "Epoch 1562/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3475 - accuracy: 0.8856 - val_loss: 1.5693 - val_accuracy: 0.5352\n",
      "Epoch 1563/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3553 - accuracy: 0.8651 - val_loss: 1.5476 - val_accuracy: 0.5493\n",
      "Epoch 1564/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3568 - accuracy: 0.8680 - val_loss: 1.5125 - val_accuracy: 0.5775\n",
      "Epoch 1565/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3563 - accuracy: 0.8680 - val_loss: 1.5068 - val_accuracy: 0.5775\n",
      "Epoch 1566/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3404 - accuracy: 0.8798 - val_loss: 1.5105 - val_accuracy: 0.5775\n",
      "Epoch 1567/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3563 - accuracy: 0.8739 - val_loss: 1.5144 - val_accuracy: 0.5775\n",
      "Epoch 1568/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3451 - accuracy: 0.8680 - val_loss: 1.5073 - val_accuracy: 0.5775\n",
      "Epoch 1569/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3497 - accuracy: 0.8651 - val_loss: 1.4925 - val_accuracy: 0.5775\n",
      "Epoch 1570/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3453 - accuracy: 0.8827 - val_loss: 1.5044 - val_accuracy: 0.5775\n",
      "Epoch 1571/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3478 - accuracy: 0.8739 - val_loss: 1.4984 - val_accuracy: 0.5775\n",
      "Epoch 1572/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3420 - accuracy: 0.8739 - val_loss: 1.4921 - val_accuracy: 0.5775\n",
      "Epoch 1573/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3561 - accuracy: 0.8798 - val_loss: 1.5129 - val_accuracy: 0.5775\n",
      "Epoch 1574/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3489 - accuracy: 0.8739 - val_loss: 1.5258 - val_accuracy: 0.5634\n",
      "Epoch 1575/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3475 - accuracy: 0.8739 - val_loss: 1.5304 - val_accuracy: 0.5634\n",
      "Epoch 1576/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3444 - accuracy: 0.8798 - val_loss: 1.5219 - val_accuracy: 0.5634\n",
      "Epoch 1577/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3602 - accuracy: 0.8710 - val_loss: 1.5320 - val_accuracy: 0.5634\n",
      "Epoch 1578/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3519 - accuracy: 0.8739 - val_loss: 1.5199 - val_accuracy: 0.5775\n",
      "Epoch 1579/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3596 - accuracy: 0.8768 - val_loss: 1.5261 - val_accuracy: 0.5634\n",
      "Epoch 1580/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3555 - accuracy: 0.8622 - val_loss: 1.5003 - val_accuracy: 0.5775\n",
      "Epoch 1581/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3509 - accuracy: 0.8886 - val_loss: 1.4820 - val_accuracy: 0.5775\n",
      "Epoch 1582/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3598 - accuracy: 0.8563 - val_loss: 1.4934 - val_accuracy: 0.5775\n",
      "Epoch 1583/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3537 - accuracy: 0.8710 - val_loss: 1.5119 - val_accuracy: 0.5775\n",
      "Epoch 1584/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3437 - accuracy: 0.8768 - val_loss: 1.5216 - val_accuracy: 0.5775\n",
      "Epoch 1585/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3458 - accuracy: 0.8798 - val_loss: 1.5195 - val_accuracy: 0.5775\n",
      "Epoch 1586/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3605 - accuracy: 0.8651 - val_loss: 1.5350 - val_accuracy: 0.5775\n",
      "Epoch 1587/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3453 - accuracy: 0.8856 - val_loss: 1.5359 - val_accuracy: 0.5775\n",
      "Epoch 1588/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3484 - accuracy: 0.8680 - val_loss: 1.5557 - val_accuracy: 0.5493\n",
      "Epoch 1589/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3496 - accuracy: 0.8739 - val_loss: 1.5567 - val_accuracy: 0.5493\n",
      "Epoch 1590/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3444 - accuracy: 0.8886 - val_loss: 1.5440 - val_accuracy: 0.5775\n",
      "Epoch 1591/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3530 - accuracy: 0.8710 - val_loss: 1.5512 - val_accuracy: 0.5634\n",
      "Epoch 1592/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3382 - accuracy: 0.8827 - val_loss: 1.5611 - val_accuracy: 0.5493\n",
      "Epoch 1593/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3718 - accuracy: 0.8504 - val_loss: 1.5750 - val_accuracy: 0.5493\n",
      "Epoch 1594/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3482 - accuracy: 0.8856 - val_loss: 1.5823 - val_accuracy: 0.5493\n",
      "Epoch 1595/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3440 - accuracy: 0.8739 - val_loss: 1.5648 - val_accuracy: 0.5493\n",
      "Epoch 1596/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3585 - accuracy: 0.8651 - val_loss: 1.5778 - val_accuracy: 0.5493\n",
      "Epoch 1597/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3481 - accuracy: 0.8710 - val_loss: 1.5828 - val_accuracy: 0.5493\n",
      "Epoch 1598/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3467 - accuracy: 0.8768 - val_loss: 1.5832 - val_accuracy: 0.5493\n",
      "Epoch 1599/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3518 - accuracy: 0.8534 - val_loss: 1.5765 - val_accuracy: 0.5493\n",
      "Epoch 1600/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3424 - accuracy: 0.8856 - val_loss: 1.5783 - val_accuracy: 0.5493\n",
      "Epoch 1601/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3819 - accuracy: 0.8387 - val_loss: 1.5718 - val_accuracy: 0.5493\n",
      "Epoch 1602/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3474 - accuracy: 0.8768 - val_loss: 1.5690 - val_accuracy: 0.5493\n",
      "Epoch 1603/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3486 - accuracy: 0.8856 - val_loss: 1.5595 - val_accuracy: 0.5493\n",
      "Epoch 1604/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3621 - accuracy: 0.8622 - val_loss: 1.5701 - val_accuracy: 0.5493\n",
      "Epoch 1605/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3507 - accuracy: 0.8768 - val_loss: 1.5740 - val_accuracy: 0.5493\n",
      "Epoch 1606/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3516 - accuracy: 0.8680 - val_loss: 1.5810 - val_accuracy: 0.5493\n",
      "Epoch 1607/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3443 - accuracy: 0.8798 - val_loss: 1.5894 - val_accuracy: 0.5352\n",
      "Epoch 1608/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3382 - accuracy: 0.8886 - val_loss: 1.6135 - val_accuracy: 0.5352\n",
      "Epoch 1609/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3458 - accuracy: 0.8651 - val_loss: 1.6067 - val_accuracy: 0.5352\n",
      "Epoch 1610/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3454 - accuracy: 0.8856 - val_loss: 1.6082 - val_accuracy: 0.5352\n",
      "Epoch 1611/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3410 - accuracy: 0.8768 - val_loss: 1.6105 - val_accuracy: 0.5352\n",
      "Epoch 1612/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3463 - accuracy: 0.8915 - val_loss: 1.6008 - val_accuracy: 0.5352\n",
      "Epoch 1613/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3437 - accuracy: 0.8651 - val_loss: 1.5876 - val_accuracy: 0.5493\n",
      "Epoch 1614/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3454 - accuracy: 0.8856 - val_loss: 1.5758 - val_accuracy: 0.5493\n",
      "Epoch 1615/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3440 - accuracy: 0.8944 - val_loss: 1.5753 - val_accuracy: 0.5493\n",
      "Epoch 1616/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3514 - accuracy: 0.8680 - val_loss: 1.5804 - val_accuracy: 0.5493\n",
      "Epoch 1617/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3455 - accuracy: 0.8915 - val_loss: 1.5720 - val_accuracy: 0.5493\n",
      "Epoch 1618/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3471 - accuracy: 0.8710 - val_loss: 1.5700 - val_accuracy: 0.5493\n",
      "Epoch 1619/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3460 - accuracy: 0.8856 - val_loss: 1.5586 - val_accuracy: 0.5493\n",
      "Epoch 1620/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3574 - accuracy: 0.8622 - val_loss: 1.5885 - val_accuracy: 0.5352\n",
      "Epoch 1621/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3522 - accuracy: 0.8798 - val_loss: 1.5770 - val_accuracy: 0.5493\n",
      "Epoch 1622/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3530 - accuracy: 0.8768 - val_loss: 1.5815 - val_accuracy: 0.5493\n",
      "Epoch 1623/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3399 - accuracy: 0.8827 - val_loss: 1.6028 - val_accuracy: 0.5352\n",
      "Epoch 1624/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3580 - accuracy: 0.8710 - val_loss: 1.6383 - val_accuracy: 0.5352\n",
      "Epoch 1625/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3458 - accuracy: 0.8651 - val_loss: 1.6553 - val_accuracy: 0.5352\n",
      "Epoch 1626/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3509 - accuracy: 0.8739 - val_loss: 1.6487 - val_accuracy: 0.5352\n",
      "Epoch 1627/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3338 - accuracy: 0.8856 - val_loss: 1.6540 - val_accuracy: 0.5352\n",
      "Epoch 1628/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3392 - accuracy: 0.8827 - val_loss: 1.6236 - val_accuracy: 0.5352\n",
      "Epoch 1629/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3475 - accuracy: 0.8592 - val_loss: 1.6046 - val_accuracy: 0.5352\n",
      "Epoch 1630/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3463 - accuracy: 0.8739 - val_loss: 1.5918 - val_accuracy: 0.5493\n",
      "Epoch 1631/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3420 - accuracy: 0.8827 - val_loss: 1.5782 - val_accuracy: 0.5493\n",
      "Epoch 1632/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3454 - accuracy: 0.8739 - val_loss: 1.5812 - val_accuracy: 0.5493\n",
      "Epoch 1633/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3463 - accuracy: 0.8827 - val_loss: 1.5639 - val_accuracy: 0.5493\n",
      "Epoch 1634/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3346 - accuracy: 0.8827 - val_loss: 1.5701 - val_accuracy: 0.5493\n",
      "Epoch 1635/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3483 - accuracy: 0.8974 - val_loss: 1.5975 - val_accuracy: 0.5352\n",
      "Epoch 1636/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3439 - accuracy: 0.8827 - val_loss: 1.6034 - val_accuracy: 0.5352\n",
      "Epoch 1637/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3482 - accuracy: 0.8827 - val_loss: 1.6019 - val_accuracy: 0.5352\n",
      "Epoch 1638/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3318 - accuracy: 0.9003 - val_loss: 1.6007 - val_accuracy: 0.5352\n",
      "Epoch 1639/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3482 - accuracy: 0.8680 - val_loss: 1.6259 - val_accuracy: 0.5352\n",
      "Epoch 1640/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3439 - accuracy: 0.8798 - val_loss: 1.6452 - val_accuracy: 0.5352\n",
      "Epoch 1641/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3468 - accuracy: 0.8768 - val_loss: 1.6678 - val_accuracy: 0.5352\n",
      "Epoch 1642/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3579 - accuracy: 0.8886 - val_loss: 1.6512 - val_accuracy: 0.5352\n",
      "Epoch 1643/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3489 - accuracy: 0.8710 - val_loss: 1.6316 - val_accuracy: 0.5352\n",
      "Epoch 1644/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3451 - accuracy: 0.8827 - val_loss: 1.6514 - val_accuracy: 0.5352\n",
      "Epoch 1645/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3483 - accuracy: 0.8768 - val_loss: 1.6405 - val_accuracy: 0.5352\n",
      "Epoch 1646/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3503 - accuracy: 0.8680 - val_loss: 1.6354 - val_accuracy: 0.5352\n",
      "Epoch 1647/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3435 - accuracy: 0.8768 - val_loss: 1.6065 - val_accuracy: 0.5352\n",
      "Epoch 1648/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3482 - accuracy: 0.8680 - val_loss: 1.5907 - val_accuracy: 0.5493\n",
      "Epoch 1649/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3396 - accuracy: 0.8798 - val_loss: 1.6155 - val_accuracy: 0.5352\n",
      "Epoch 1650/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3463 - accuracy: 0.8886 - val_loss: 1.6280 - val_accuracy: 0.5352\n",
      "Epoch 1651/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3543 - accuracy: 0.8768 - val_loss: 1.6124 - val_accuracy: 0.5352\n",
      "Epoch 1652/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3574 - accuracy: 0.8592 - val_loss: 1.6201 - val_accuracy: 0.5352\n",
      "Epoch 1653/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3497 - accuracy: 0.8827 - val_loss: 1.6177 - val_accuracy: 0.5352\n",
      "Epoch 1654/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3448 - accuracy: 0.8651 - val_loss: 1.6009 - val_accuracy: 0.5493\n",
      "Epoch 1655/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3297 - accuracy: 0.8915 - val_loss: 1.6069 - val_accuracy: 0.5493\n",
      "Epoch 1656/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3431 - accuracy: 0.8856 - val_loss: 1.6426 - val_accuracy: 0.5352\n",
      "Epoch 1657/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3453 - accuracy: 0.8856 - val_loss: 1.6523 - val_accuracy: 0.5352\n",
      "Epoch 1658/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3390 - accuracy: 0.8915 - val_loss: 1.6377 - val_accuracy: 0.5352\n",
      "Epoch 1659/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3485 - accuracy: 0.8710 - val_loss: 1.6298 - val_accuracy: 0.5352\n",
      "Epoch 1660/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3520 - accuracy: 0.8710 - val_loss: 1.6291 - val_accuracy: 0.5352\n",
      "Epoch 1661/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3347 - accuracy: 0.8680 - val_loss: 1.6316 - val_accuracy: 0.5352\n",
      "Epoch 1662/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3399 - accuracy: 0.8856 - val_loss: 1.6343 - val_accuracy: 0.5352\n",
      "Epoch 1663/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3456 - accuracy: 0.8710 - val_loss: 1.6452 - val_accuracy: 0.5352\n",
      "Epoch 1664/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.3385 - accuracy: 0.8886 - val_loss: 1.6363 - val_accuracy: 0.5352\n",
      "Epoch 1665/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3376 - accuracy: 0.8856 - val_loss: 1.6583 - val_accuracy: 0.5352\n",
      "Epoch 1666/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3333 - accuracy: 0.8710 - val_loss: 1.6600 - val_accuracy: 0.5352\n",
      "Epoch 1667/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3432 - accuracy: 0.8651 - val_loss: 1.6634 - val_accuracy: 0.5352\n",
      "Epoch 1668/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3371 - accuracy: 0.8768 - val_loss: 1.6453 - val_accuracy: 0.5352\n",
      "Epoch 1669/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3337 - accuracy: 0.8739 - val_loss: 1.6338 - val_accuracy: 0.5352\n",
      "Epoch 1670/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3306 - accuracy: 0.8798 - val_loss: 1.6229 - val_accuracy: 0.5352\n",
      "Epoch 1671/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3391 - accuracy: 0.8768 - val_loss: 1.6157 - val_accuracy: 0.5352\n",
      "Epoch 1672/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3466 - accuracy: 0.8827 - val_loss: 1.6183 - val_accuracy: 0.5352\n",
      "Epoch 1673/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3379 - accuracy: 0.8915 - val_loss: 1.6390 - val_accuracy: 0.5352\n",
      "Epoch 1674/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3314 - accuracy: 0.8856 - val_loss: 1.6385 - val_accuracy: 0.5352\n",
      "Epoch 1675/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3557 - accuracy: 0.8827 - val_loss: 1.6448 - val_accuracy: 0.5352\n",
      "Epoch 1676/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3378 - accuracy: 0.9062 - val_loss: 1.6665 - val_accuracy: 0.5352\n",
      "Epoch 1677/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3485 - accuracy: 0.8768 - val_loss: 1.6684 - val_accuracy: 0.5352\n",
      "Epoch 1678/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3367 - accuracy: 0.8856 - val_loss: 1.6618 - val_accuracy: 0.5352\n",
      "Epoch 1679/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3374 - accuracy: 0.8739 - val_loss: 1.6604 - val_accuracy: 0.5352\n",
      "Epoch 1680/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3336 - accuracy: 0.8886 - val_loss: 1.6339 - val_accuracy: 0.5352\n",
      "Epoch 1681/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3769 - accuracy: 0.8534 - val_loss: 1.6430 - val_accuracy: 0.5352\n",
      "Epoch 1682/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3436 - accuracy: 0.8827 - val_loss: 1.6461 - val_accuracy: 0.5352\n",
      "Epoch 1683/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3279 - accuracy: 0.8915 - val_loss: 1.6568 - val_accuracy: 0.5352\n",
      "Epoch 1684/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3485 - accuracy: 0.8680 - val_loss: 1.6463 - val_accuracy: 0.5352\n",
      "Epoch 1685/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3397 - accuracy: 0.8798 - val_loss: 1.6474 - val_accuracy: 0.5352\n",
      "Epoch 1686/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3405 - accuracy: 0.8798 - val_loss: 1.6362 - val_accuracy: 0.5493\n",
      "Epoch 1687/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3362 - accuracy: 0.8915 - val_loss: 1.6407 - val_accuracy: 0.5352\n",
      "Epoch 1688/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3426 - accuracy: 0.8768 - val_loss: 1.6355 - val_accuracy: 0.5493\n",
      "Epoch 1689/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3293 - accuracy: 0.8915 - val_loss: 1.6134 - val_accuracy: 0.5634\n",
      "Epoch 1690/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3382 - accuracy: 0.8651 - val_loss: 1.6091 - val_accuracy: 0.5634\n",
      "Epoch 1691/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3397 - accuracy: 0.8827 - val_loss: 1.6240 - val_accuracy: 0.5493\n",
      "Epoch 1692/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3477 - accuracy: 0.8680 - val_loss: 1.6271 - val_accuracy: 0.5352\n",
      "Epoch 1693/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3445 - accuracy: 0.8739 - val_loss: 1.6400 - val_accuracy: 0.5352\n",
      "Epoch 1694/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3622 - accuracy: 0.8592 - val_loss: 1.6631 - val_accuracy: 0.5352\n",
      "Epoch 1695/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3532 - accuracy: 0.8563 - val_loss: 1.6858 - val_accuracy: 0.5352\n",
      "Epoch 1696/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3345 - accuracy: 0.8886 - val_loss: 1.7074 - val_accuracy: 0.5352\n",
      "Epoch 1697/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3468 - accuracy: 0.8768 - val_loss: 1.7028 - val_accuracy: 0.5352\n",
      "Epoch 1698/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3486 - accuracy: 0.8710 - val_loss: 1.6766 - val_accuracy: 0.5352\n",
      "Epoch 1699/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3397 - accuracy: 0.8856 - val_loss: 1.6722 - val_accuracy: 0.5352\n",
      "Epoch 1700/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3360 - accuracy: 0.8944 - val_loss: 1.6618 - val_accuracy: 0.5352\n",
      "Epoch 1701/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3375 - accuracy: 0.8827 - val_loss: 1.6533 - val_accuracy: 0.5352\n",
      "Epoch 1702/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3438 - accuracy: 0.8856 - val_loss: 1.6527 - val_accuracy: 0.5352\n",
      "Epoch 1703/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3452 - accuracy: 0.8768 - val_loss: 1.6553 - val_accuracy: 0.5352\n",
      "Epoch 1704/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3334 - accuracy: 0.8944 - val_loss: 1.6521 - val_accuracy: 0.5352\n",
      "Epoch 1705/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3359 - accuracy: 0.8768 - val_loss: 1.6264 - val_accuracy: 0.5493\n",
      "Epoch 1706/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3529 - accuracy: 0.8739 - val_loss: 1.5879 - val_accuracy: 0.5634\n",
      "Epoch 1707/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3470 - accuracy: 0.8856 - val_loss: 1.5906 - val_accuracy: 0.5634\n",
      "Epoch 1708/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3484 - accuracy: 0.8768 - val_loss: 1.5874 - val_accuracy: 0.5634\n",
      "Epoch 1709/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3230 - accuracy: 0.9091 - val_loss: 1.5829 - val_accuracy: 0.5634\n",
      "Epoch 1710/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3454 - accuracy: 0.8710 - val_loss: 1.5786 - val_accuracy: 0.5634\n",
      "Epoch 1711/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3383 - accuracy: 0.8856 - val_loss: 1.6012 - val_accuracy: 0.5634\n",
      "Epoch 1712/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3401 - accuracy: 0.8680 - val_loss: 1.6074 - val_accuracy: 0.5634\n",
      "Epoch 1713/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3270 - accuracy: 0.8768 - val_loss: 1.6256 - val_accuracy: 0.5352\n",
      "Epoch 1714/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3388 - accuracy: 0.8768 - val_loss: 1.6469 - val_accuracy: 0.5352\n",
      "Epoch 1715/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3395 - accuracy: 0.8622 - val_loss: 1.6692 - val_accuracy: 0.5352\n",
      "Epoch 1716/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3356 - accuracy: 0.8886 - val_loss: 1.6693 - val_accuracy: 0.5352\n",
      "Epoch 1717/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3434 - accuracy: 0.8739 - val_loss: 1.6736 - val_accuracy: 0.5352\n",
      "Epoch 1718/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3391 - accuracy: 0.8768 - val_loss: 1.6711 - val_accuracy: 0.5352\n",
      "Epoch 1719/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3399 - accuracy: 0.8768 - val_loss: 1.6553 - val_accuracy: 0.5352\n",
      "Epoch 1720/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3335 - accuracy: 0.8798 - val_loss: 1.6221 - val_accuracy: 0.5634\n",
      "Epoch 1721/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3498 - accuracy: 0.8739 - val_loss: 1.5985 - val_accuracy: 0.5634\n",
      "Epoch 1722/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3329 - accuracy: 0.8856 - val_loss: 1.5915 - val_accuracy: 0.5634\n",
      "Epoch 1723/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3342 - accuracy: 0.8768 - val_loss: 1.6011 - val_accuracy: 0.5634\n",
      "Epoch 1724/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3324 - accuracy: 0.8798 - val_loss: 1.6000 - val_accuracy: 0.5634\n",
      "Epoch 1725/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3335 - accuracy: 0.8886 - val_loss: 1.6045 - val_accuracy: 0.5634\n",
      "Epoch 1726/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3300 - accuracy: 0.8886 - val_loss: 1.6211 - val_accuracy: 0.5634\n",
      "Epoch 1727/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3383 - accuracy: 0.8856 - val_loss: 1.6653 - val_accuracy: 0.5352\n",
      "Epoch 1728/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3254 - accuracy: 0.8974 - val_loss: 1.6811 - val_accuracy: 0.5352\n",
      "Epoch 1729/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3334 - accuracy: 0.8798 - val_loss: 1.6761 - val_accuracy: 0.5352\n",
      "Epoch 1730/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3259 - accuracy: 0.8944 - val_loss: 1.6788 - val_accuracy: 0.5352\n",
      "Epoch 1731/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3471 - accuracy: 0.8768 - val_loss: 1.7028 - val_accuracy: 0.5352\n",
      "Epoch 1732/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3438 - accuracy: 0.8710 - val_loss: 1.7137 - val_accuracy: 0.5352\n",
      "Epoch 1733/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3404 - accuracy: 0.8798 - val_loss: 1.7241 - val_accuracy: 0.5352\n",
      "Epoch 1734/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3308 - accuracy: 0.8798 - val_loss: 1.7273 - val_accuracy: 0.5352\n",
      "Epoch 1735/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3313 - accuracy: 0.8768 - val_loss: 1.7224 - val_accuracy: 0.5352\n",
      "Epoch 1736/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3398 - accuracy: 0.8768 - val_loss: 1.7171 - val_accuracy: 0.5352\n",
      "Epoch 1737/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3353 - accuracy: 0.8798 - val_loss: 1.7236 - val_accuracy: 0.5352\n",
      "Epoch 1738/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3275 - accuracy: 0.8798 - val_loss: 1.7298 - val_accuracy: 0.5352\n",
      "Epoch 1739/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3498 - accuracy: 0.8710 - val_loss: 1.7520 - val_accuracy: 0.5211\n",
      "Epoch 1740/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3336 - accuracy: 0.8827 - val_loss: 1.7540 - val_accuracy: 0.5211\n",
      "Epoch 1741/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3245 - accuracy: 0.8886 - val_loss: 1.7521 - val_accuracy: 0.5211\n",
      "Epoch 1742/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3332 - accuracy: 0.8798 - val_loss: 1.7327 - val_accuracy: 0.5352\n",
      "Epoch 1743/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3286 - accuracy: 0.8827 - val_loss: 1.7224 - val_accuracy: 0.5352\n",
      "Epoch 1744/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3354 - accuracy: 0.8886 - val_loss: 1.6869 - val_accuracy: 0.5352\n",
      "Epoch 1745/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3314 - accuracy: 0.8856 - val_loss: 1.6758 - val_accuracy: 0.5352\n",
      "Epoch 1746/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3361 - accuracy: 0.8915 - val_loss: 1.6745 - val_accuracy: 0.5352\n",
      "Epoch 1747/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3352 - accuracy: 0.8856 - val_loss: 1.6594 - val_accuracy: 0.5352\n",
      "Epoch 1748/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3366 - accuracy: 0.8798 - val_loss: 1.6561 - val_accuracy: 0.5352\n",
      "Epoch 1749/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3287 - accuracy: 0.8915 - val_loss: 1.6706 - val_accuracy: 0.5352\n",
      "Epoch 1750/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3321 - accuracy: 0.8768 - val_loss: 1.6544 - val_accuracy: 0.5352\n",
      "Epoch 1751/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3279 - accuracy: 0.8915 - val_loss: 1.6599 - val_accuracy: 0.5352\n",
      "Epoch 1752/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3383 - accuracy: 0.8915 - val_loss: 1.6779 - val_accuracy: 0.5352\n",
      "Epoch 1753/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3334 - accuracy: 0.8915 - val_loss: 1.6917 - val_accuracy: 0.5352\n",
      "Epoch 1754/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3480 - accuracy: 0.8680 - val_loss: 1.6635 - val_accuracy: 0.5352\n",
      "Epoch 1755/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3427 - accuracy: 0.8739 - val_loss: 1.6738 - val_accuracy: 0.5352\n",
      "Epoch 1756/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3238 - accuracy: 0.8944 - val_loss: 1.6863 - val_accuracy: 0.5352\n",
      "Epoch 1757/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3280 - accuracy: 0.8827 - val_loss: 1.6828 - val_accuracy: 0.5352\n",
      "Epoch 1758/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3321 - accuracy: 0.8886 - val_loss: 1.6752 - val_accuracy: 0.5352\n",
      "Epoch 1759/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3413 - accuracy: 0.8798 - val_loss: 1.6896 - val_accuracy: 0.5352\n",
      "Epoch 1760/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3323 - accuracy: 0.8886 - val_loss: 1.7116 - val_accuracy: 0.5352\n",
      "Epoch 1761/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3375 - accuracy: 0.8651 - val_loss: 1.7189 - val_accuracy: 0.5352\n",
      "Epoch 1762/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3398 - accuracy: 0.8710 - val_loss: 1.7189 - val_accuracy: 0.5352\n",
      "Epoch 1763/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3287 - accuracy: 0.8886 - val_loss: 1.7355 - val_accuracy: 0.5352\n",
      "Epoch 1764/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3241 - accuracy: 0.8915 - val_loss: 1.7212 - val_accuracy: 0.5352\n",
      "Epoch 1765/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3320 - accuracy: 0.8886 - val_loss: 1.7294 - val_accuracy: 0.5352\n",
      "Epoch 1766/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3446 - accuracy: 0.8856 - val_loss: 1.7056 - val_accuracy: 0.5352\n",
      "Epoch 1767/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3302 - accuracy: 0.8827 - val_loss: 1.6890 - val_accuracy: 0.5352\n",
      "Epoch 1768/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3256 - accuracy: 0.8768 - val_loss: 1.6778 - val_accuracy: 0.5352\n",
      "Epoch 1769/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3336 - accuracy: 0.8798 - val_loss: 1.6604 - val_accuracy: 0.5352\n",
      "Epoch 1770/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3341 - accuracy: 0.8886 - val_loss: 1.6929 - val_accuracy: 0.5352\n",
      "Epoch 1771/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3267 - accuracy: 0.8944 - val_loss: 1.7257 - val_accuracy: 0.5352\n",
      "Epoch 1772/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3406 - accuracy: 0.8827 - val_loss: 1.7380 - val_accuracy: 0.5352\n",
      "Epoch 1773/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3315 - accuracy: 0.8798 - val_loss: 1.7272 - val_accuracy: 0.5352\n",
      "Epoch 1774/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3317 - accuracy: 0.8768 - val_loss: 1.7123 - val_accuracy: 0.5352\n",
      "Epoch 1775/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3184 - accuracy: 0.9032 - val_loss: 1.7163 - val_accuracy: 0.5352\n",
      "Epoch 1776/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3367 - accuracy: 0.8886 - val_loss: 1.7178 - val_accuracy: 0.5352\n",
      "Epoch 1777/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3359 - accuracy: 0.8622 - val_loss: 1.7122 - val_accuracy: 0.5352\n",
      "Epoch 1778/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3363 - accuracy: 0.8886 - val_loss: 1.7166 - val_accuracy: 0.5352\n",
      "Epoch 1779/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3487 - accuracy: 0.8710 - val_loss: 1.7329 - val_accuracy: 0.5352\n",
      "Epoch 1780/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3326 - accuracy: 0.8768 - val_loss: 1.7518 - val_accuracy: 0.5352\n",
      "Epoch 1781/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3288 - accuracy: 0.8856 - val_loss: 1.7780 - val_accuracy: 0.5211\n",
      "Epoch 1782/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3357 - accuracy: 0.8768 - val_loss: 1.7771 - val_accuracy: 0.5211\n",
      "Epoch 1783/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3274 - accuracy: 0.8915 - val_loss: 1.7763 - val_accuracy: 0.5211\n",
      "Epoch 1784/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3303 - accuracy: 0.8798 - val_loss: 1.7750 - val_accuracy: 0.5211\n",
      "Epoch 1785/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3296 - accuracy: 0.8886 - val_loss: 1.7662 - val_accuracy: 0.5211\n",
      "Epoch 1786/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3332 - accuracy: 0.8856 - val_loss: 1.7456 - val_accuracy: 0.5352\n",
      "Epoch 1787/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3308 - accuracy: 0.8915 - val_loss: 1.7303 - val_accuracy: 0.5352\n",
      "Epoch 1788/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3519 - accuracy: 0.8710 - val_loss: 1.7310 - val_accuracy: 0.5352\n",
      "Epoch 1789/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3246 - accuracy: 0.8944 - val_loss: 1.7430 - val_accuracy: 0.5352\n",
      "Epoch 1790/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3343 - accuracy: 0.8827 - val_loss: 1.7387 - val_accuracy: 0.5352\n",
      "Epoch 1791/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3435 - accuracy: 0.8739 - val_loss: 1.7203 - val_accuracy: 0.5352\n",
      "Epoch 1792/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3351 - accuracy: 0.8768 - val_loss: 1.7197 - val_accuracy: 0.5352\n",
      "Epoch 1793/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3288 - accuracy: 0.9003 - val_loss: 1.7127 - val_accuracy: 0.5352\n",
      "Epoch 1794/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3306 - accuracy: 0.8798 - val_loss: 1.7234 - val_accuracy: 0.5352\n",
      "Epoch 1795/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3279 - accuracy: 0.8827 - val_loss: 1.7555 - val_accuracy: 0.5352\n",
      "Epoch 1796/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3298 - accuracy: 0.8827 - val_loss: 1.7478 - val_accuracy: 0.5352\n",
      "Epoch 1797/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3300 - accuracy: 0.8798 - val_loss: 1.7348 - val_accuracy: 0.5352\n",
      "Epoch 1798/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3363 - accuracy: 0.8680 - val_loss: 1.7355 - val_accuracy: 0.5352\n",
      "Epoch 1799/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3321 - accuracy: 0.8798 - val_loss: 1.7140 - val_accuracy: 0.5352\n",
      "Epoch 1800/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3436 - accuracy: 0.8710 - val_loss: 1.7108 - val_accuracy: 0.5352\n",
      "Epoch 1801/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3418 - accuracy: 0.8739 - val_loss: 1.7033 - val_accuracy: 0.5352\n",
      "Epoch 1802/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3232 - accuracy: 0.8915 - val_loss: 1.7186 - val_accuracy: 0.5352\n",
      "Epoch 1803/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3290 - accuracy: 0.8915 - val_loss: 1.7209 - val_accuracy: 0.5352\n",
      "Epoch 1804/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3278 - accuracy: 0.8798 - val_loss: 1.7196 - val_accuracy: 0.5352\n",
      "Epoch 1805/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3344 - accuracy: 0.8886 - val_loss: 1.7396 - val_accuracy: 0.5352\n",
      "Epoch 1806/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3322 - accuracy: 0.8768 - val_loss: 1.7470 - val_accuracy: 0.5352\n",
      "Epoch 1807/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3392 - accuracy: 0.8768 - val_loss: 1.7443 - val_accuracy: 0.5352\n",
      "Epoch 1808/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3270 - accuracy: 0.8915 - val_loss: 1.7140 - val_accuracy: 0.5352\n",
      "Epoch 1809/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3233 - accuracy: 0.8827 - val_loss: 1.7097 - val_accuracy: 0.5352\n",
      "Epoch 1810/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3271 - accuracy: 0.8944 - val_loss: 1.7076 - val_accuracy: 0.5352\n",
      "Epoch 1811/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3289 - accuracy: 0.8798 - val_loss: 1.7253 - val_accuracy: 0.5352\n",
      "Epoch 1812/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3399 - accuracy: 0.8856 - val_loss: 1.7263 - val_accuracy: 0.5352\n",
      "Epoch 1813/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3272 - accuracy: 0.8886 - val_loss: 1.7430 - val_accuracy: 0.5352\n",
      "Epoch 1814/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3228 - accuracy: 0.8768 - val_loss: 1.7349 - val_accuracy: 0.5352\n",
      "Epoch 1815/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3314 - accuracy: 0.8798 - val_loss: 1.7166 - val_accuracy: 0.5352\n",
      "Epoch 1816/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3220 - accuracy: 0.8974 - val_loss: 1.7102 - val_accuracy: 0.5352\n",
      "Epoch 1817/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3309 - accuracy: 0.8856 - val_loss: 1.7256 - val_accuracy: 0.5352\n",
      "Epoch 1818/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3232 - accuracy: 0.8886 - val_loss: 1.7415 - val_accuracy: 0.5352\n",
      "Epoch 1819/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3247 - accuracy: 0.8798 - val_loss: 1.7515 - val_accuracy: 0.5352\n",
      "Epoch 1820/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3386 - accuracy: 0.8974 - val_loss: 1.7434 - val_accuracy: 0.5352\n",
      "Epoch 1821/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3152 - accuracy: 0.8944 - val_loss: 1.7462 - val_accuracy: 0.5352\n",
      "Epoch 1822/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3207 - accuracy: 0.8886 - val_loss: 1.7325 - val_accuracy: 0.5352\n",
      "Epoch 1823/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3367 - accuracy: 0.8710 - val_loss: 1.7431 - val_accuracy: 0.5352\n",
      "Epoch 1824/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3361 - accuracy: 0.8915 - val_loss: 1.7415 - val_accuracy: 0.5352\n",
      "Epoch 1825/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3305 - accuracy: 0.8798 - val_loss: 1.7606 - val_accuracy: 0.5352\n",
      "Epoch 1826/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3227 - accuracy: 0.8915 - val_loss: 1.7963 - val_accuracy: 0.5211\n",
      "Epoch 1827/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3258 - accuracy: 0.8768 - val_loss: 1.8303 - val_accuracy: 0.5211\n",
      "Epoch 1828/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3221 - accuracy: 0.8974 - val_loss: 1.8100 - val_accuracy: 0.5211\n",
      "Epoch 1829/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3238 - accuracy: 0.8856 - val_loss: 1.7776 - val_accuracy: 0.5211\n",
      "Epoch 1830/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3266 - accuracy: 0.8886 - val_loss: 1.7615 - val_accuracy: 0.5211\n",
      "Epoch 1831/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3544 - accuracy: 0.8563 - val_loss: 1.7381 - val_accuracy: 0.5352\n",
      "Epoch 1832/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3313 - accuracy: 0.8798 - val_loss: 1.7420 - val_accuracy: 0.5352\n",
      "Epoch 1833/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3279 - accuracy: 0.8944 - val_loss: 1.7462 - val_accuracy: 0.5352\n",
      "Epoch 1834/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3341 - accuracy: 0.8827 - val_loss: 1.7753 - val_accuracy: 0.5211\n",
      "Epoch 1835/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3179 - accuracy: 0.8798 - val_loss: 1.7889 - val_accuracy: 0.5211\n",
      "Epoch 1836/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3229 - accuracy: 0.8944 - val_loss: 1.7726 - val_accuracy: 0.5352\n",
      "Epoch 1837/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3356 - accuracy: 0.8768 - val_loss: 1.7888 - val_accuracy: 0.5211\n",
      "Epoch 1838/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3446 - accuracy: 0.8710 - val_loss: 1.7987 - val_accuracy: 0.5211\n",
      "Epoch 1839/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3249 - accuracy: 0.8827 - val_loss: 1.8036 - val_accuracy: 0.5211\n",
      "Epoch 1840/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3274 - accuracy: 0.8886 - val_loss: 1.8112 - val_accuracy: 0.5211\n",
      "Epoch 1841/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.3254 - accuracy: 0.8915 - val_loss: 1.8239 - val_accuracy: 0.5211\n",
      "Epoch 1842/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3337 - accuracy: 0.8886 - val_loss: 1.8356 - val_accuracy: 0.5211\n",
      "Epoch 1843/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3227 - accuracy: 0.8915 - val_loss: 1.8220 - val_accuracy: 0.5211\n",
      "Epoch 1844/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3355 - accuracy: 0.8739 - val_loss: 1.8027 - val_accuracy: 0.5211\n",
      "Epoch 1845/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3284 - accuracy: 0.9003 - val_loss: 1.7760 - val_accuracy: 0.5352\n",
      "Epoch 1846/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3214 - accuracy: 0.9003 - val_loss: 1.7677 - val_accuracy: 0.5352\n",
      "Epoch 1847/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3348 - accuracy: 0.8739 - val_loss: 1.7535 - val_accuracy: 0.5352\n",
      "Epoch 1848/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3298 - accuracy: 0.8622 - val_loss: 1.7312 - val_accuracy: 0.5352\n",
      "Epoch 1849/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3203 - accuracy: 0.8886 - val_loss: 1.7142 - val_accuracy: 0.5493\n",
      "Epoch 1850/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3248 - accuracy: 0.8827 - val_loss: 1.7454 - val_accuracy: 0.5352\n",
      "Epoch 1851/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3354 - accuracy: 0.8798 - val_loss: 1.7853 - val_accuracy: 0.5352\n",
      "Epoch 1852/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3340 - accuracy: 0.8798 - val_loss: 1.7796 - val_accuracy: 0.5352\n",
      "Epoch 1853/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3294 - accuracy: 0.8974 - val_loss: 1.7609 - val_accuracy: 0.5352\n",
      "Epoch 1854/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3537 - accuracy: 0.8622 - val_loss: 1.7558 - val_accuracy: 0.5352\n",
      "Epoch 1855/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3220 - accuracy: 0.8974 - val_loss: 1.7373 - val_accuracy: 0.5493\n",
      "Epoch 1856/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3175 - accuracy: 0.8915 - val_loss: 1.7641 - val_accuracy: 0.5352\n",
      "Epoch 1857/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3257 - accuracy: 0.8974 - val_loss: 1.7513 - val_accuracy: 0.5352\n",
      "Epoch 1858/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3340 - accuracy: 0.8651 - val_loss: 1.7692 - val_accuracy: 0.5352\n",
      "Epoch 1859/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3197 - accuracy: 0.8944 - val_loss: 1.7686 - val_accuracy: 0.5352\n",
      "Epoch 1860/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3218 - accuracy: 0.8856 - val_loss: 1.7691 - val_accuracy: 0.5352\n",
      "Epoch 1861/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3336 - accuracy: 0.8886 - val_loss: 1.7653 - val_accuracy: 0.5352\n",
      "Epoch 1862/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3422 - accuracy: 0.8739 - val_loss: 1.7581 - val_accuracy: 0.5352\n",
      "Epoch 1863/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3183 - accuracy: 0.8856 - val_loss: 1.7763 - val_accuracy: 0.5352\n",
      "Epoch 1864/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3185 - accuracy: 0.8944 - val_loss: 1.7761 - val_accuracy: 0.5352\n",
      "Epoch 1865/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3218 - accuracy: 0.8886 - val_loss: 1.7822 - val_accuracy: 0.5352\n",
      "Epoch 1866/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3319 - accuracy: 0.8739 - val_loss: 1.8028 - val_accuracy: 0.5352\n",
      "Epoch 1867/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3151 - accuracy: 0.8974 - val_loss: 1.8217 - val_accuracy: 0.5211\n",
      "Epoch 1868/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3280 - accuracy: 0.8768 - val_loss: 1.8411 - val_accuracy: 0.5211\n",
      "Epoch 1869/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3260 - accuracy: 0.8827 - val_loss: 1.8260 - val_accuracy: 0.5211\n",
      "Epoch 1870/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3217 - accuracy: 0.8886 - val_loss: 1.8443 - val_accuracy: 0.5211\n",
      "Epoch 1871/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3288 - accuracy: 0.8768 - val_loss: 1.8475 - val_accuracy: 0.5211\n",
      "Epoch 1872/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3294 - accuracy: 0.8944 - val_loss: 1.8538 - val_accuracy: 0.5211\n",
      "Epoch 1873/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3303 - accuracy: 0.8768 - val_loss: 1.8321 - val_accuracy: 0.5211\n",
      "Epoch 1874/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3407 - accuracy: 0.8710 - val_loss: 1.8024 - val_accuracy: 0.5352\n",
      "Epoch 1875/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3345 - accuracy: 0.8798 - val_loss: 1.7799 - val_accuracy: 0.5352\n",
      "Epoch 1876/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3343 - accuracy: 0.8827 - val_loss: 1.7667 - val_accuracy: 0.5352\n",
      "Epoch 1877/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3222 - accuracy: 0.8739 - val_loss: 1.7646 - val_accuracy: 0.5352\n",
      "Epoch 1878/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3209 - accuracy: 0.8915 - val_loss: 1.7401 - val_accuracy: 0.5493\n",
      "Epoch 1879/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3181 - accuracy: 0.8886 - val_loss: 1.7670 - val_accuracy: 0.5352\n",
      "Epoch 1880/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3244 - accuracy: 0.9003 - val_loss: 1.7994 - val_accuracy: 0.5352\n",
      "Epoch 1881/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3239 - accuracy: 0.8710 - val_loss: 1.8047 - val_accuracy: 0.5352\n",
      "Epoch 1882/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3210 - accuracy: 0.8944 - val_loss: 1.8006 - val_accuracy: 0.5352\n",
      "Epoch 1883/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3265 - accuracy: 0.8856 - val_loss: 1.8234 - val_accuracy: 0.5352\n",
      "Epoch 1884/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3266 - accuracy: 0.8915 - val_loss: 1.8374 - val_accuracy: 0.5211\n",
      "Epoch 1885/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3355 - accuracy: 0.8680 - val_loss: 1.8309 - val_accuracy: 0.5352\n",
      "Epoch 1886/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3154 - accuracy: 0.8974 - val_loss: 1.8308 - val_accuracy: 0.5352\n",
      "Epoch 1887/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3399 - accuracy: 0.8886 - val_loss: 1.8400 - val_accuracy: 0.5211\n",
      "Epoch 1888/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3220 - accuracy: 0.8798 - val_loss: 1.8334 - val_accuracy: 0.5352\n",
      "Epoch 1889/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3190 - accuracy: 0.8886 - val_loss: 1.8232 - val_accuracy: 0.5352\n",
      "Epoch 1890/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3267 - accuracy: 0.8798 - val_loss: 1.8256 - val_accuracy: 0.5352\n",
      "Epoch 1891/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3382 - accuracy: 0.8798 - val_loss: 1.8205 - val_accuracy: 0.5352\n",
      "Epoch 1892/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3159 - accuracy: 0.8827 - val_loss: 1.8076 - val_accuracy: 0.5352\n",
      "Epoch 1893/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3147 - accuracy: 0.8915 - val_loss: 1.8076 - val_accuracy: 0.5352\n",
      "Epoch 1894/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3271 - accuracy: 0.8974 - val_loss: 1.8050 - val_accuracy: 0.5352\n",
      "Epoch 1895/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3278 - accuracy: 0.8710 - val_loss: 1.7971 - val_accuracy: 0.5352\n",
      "Epoch 1896/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3214 - accuracy: 0.8886 - val_loss: 1.7765 - val_accuracy: 0.5352\n",
      "Epoch 1897/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3203 - accuracy: 0.8739 - val_loss: 1.7617 - val_accuracy: 0.5352\n",
      "Epoch 1898/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3357 - accuracy: 0.8680 - val_loss: 1.8147 - val_accuracy: 0.5352\n",
      "Epoch 1899/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3268 - accuracy: 0.8944 - val_loss: 1.8238 - val_accuracy: 0.5352\n",
      "Epoch 1900/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3222 - accuracy: 0.8798 - val_loss: 1.8003 - val_accuracy: 0.5352\n",
      "Epoch 1901/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3238 - accuracy: 0.8974 - val_loss: 1.7919 - val_accuracy: 0.5352\n",
      "Epoch 1902/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3190 - accuracy: 0.8915 - val_loss: 1.8013 - val_accuracy: 0.5352\n",
      "Epoch 1903/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3529 - accuracy: 0.8328 - val_loss: 1.7824 - val_accuracy: 0.5352\n",
      "Epoch 1904/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3254 - accuracy: 0.8944 - val_loss: 1.7712 - val_accuracy: 0.5352\n",
      "Epoch 1905/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3350 - accuracy: 0.8739 - val_loss: 1.7826 - val_accuracy: 0.5352\n",
      "Epoch 1906/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3130 - accuracy: 0.8944 - val_loss: 1.7912 - val_accuracy: 0.5352\n",
      "Epoch 1907/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3295 - accuracy: 0.8768 - val_loss: 1.8057 - val_accuracy: 0.5352\n",
      "Epoch 1908/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3167 - accuracy: 0.8798 - val_loss: 1.8018 - val_accuracy: 0.5352\n",
      "Epoch 1909/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3178 - accuracy: 0.9032 - val_loss: 1.7978 - val_accuracy: 0.5352\n",
      "Epoch 1910/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3212 - accuracy: 0.8856 - val_loss: 1.7990 - val_accuracy: 0.5352\n",
      "Epoch 1911/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3243 - accuracy: 0.8827 - val_loss: 1.8120 - val_accuracy: 0.5352\n",
      "Epoch 1912/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3141 - accuracy: 0.9003 - val_loss: 1.8215 - val_accuracy: 0.5352\n",
      "Epoch 1913/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3245 - accuracy: 0.8710 - val_loss: 1.8407 - val_accuracy: 0.5352\n",
      "Epoch 1914/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3137 - accuracy: 0.8915 - val_loss: 1.8554 - val_accuracy: 0.5352\n",
      "Epoch 1915/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3144 - accuracy: 0.8974 - val_loss: 1.8599 - val_accuracy: 0.5211\n",
      "Epoch 1916/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.3371 - accuracy: 0.8651 - val_loss: 1.8829 - val_accuracy: 0.5211\n",
      "Epoch 1917/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3175 - accuracy: 0.8944 - val_loss: 1.8871 - val_accuracy: 0.5211\n",
      "Epoch 1918/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3139 - accuracy: 0.8915 - val_loss: 1.8957 - val_accuracy: 0.5211\n",
      "Epoch 1919/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3203 - accuracy: 0.8739 - val_loss: 1.8821 - val_accuracy: 0.5211\n",
      "Epoch 1920/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3191 - accuracy: 0.8798 - val_loss: 1.8632 - val_accuracy: 0.5211\n",
      "Epoch 1921/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3351 - accuracy: 0.8886 - val_loss: 1.8402 - val_accuracy: 0.5352\n",
      "Epoch 1922/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3237 - accuracy: 0.8856 - val_loss: 1.8282 - val_accuracy: 0.5352\n",
      "Epoch 1923/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3264 - accuracy: 0.8886 - val_loss: 1.8346 - val_accuracy: 0.5352\n",
      "Epoch 1924/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3175 - accuracy: 0.8856 - val_loss: 1.8223 - val_accuracy: 0.5352\n",
      "Epoch 1925/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3259 - accuracy: 0.8827 - val_loss: 1.8195 - val_accuracy: 0.5352\n",
      "Epoch 1926/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3097 - accuracy: 0.9003 - val_loss: 1.8224 - val_accuracy: 0.5352\n",
      "Epoch 1927/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3175 - accuracy: 0.8915 - val_loss: 1.8170 - val_accuracy: 0.5352\n",
      "Epoch 1928/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3334 - accuracy: 0.8798 - val_loss: 1.8516 - val_accuracy: 0.5352\n",
      "Epoch 1929/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3175 - accuracy: 0.8915 - val_loss: 1.8618 - val_accuracy: 0.5211\n",
      "Epoch 1930/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3336 - accuracy: 0.8798 - val_loss: 1.8587 - val_accuracy: 0.5352\n",
      "Epoch 1931/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3189 - accuracy: 0.9003 - val_loss: 1.8778 - val_accuracy: 0.5211\n",
      "Epoch 1932/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3118 - accuracy: 0.8974 - val_loss: 1.8926 - val_accuracy: 0.5211\n",
      "Epoch 1933/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3174 - accuracy: 0.9003 - val_loss: 1.9267 - val_accuracy: 0.5211\n",
      "Epoch 1934/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3253 - accuracy: 0.8886 - val_loss: 1.9132 - val_accuracy: 0.5211\n",
      "Epoch 1935/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3163 - accuracy: 0.8944 - val_loss: 1.8906 - val_accuracy: 0.5211\n",
      "Epoch 1936/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3227 - accuracy: 0.8944 - val_loss: 1.8941 - val_accuracy: 0.5211\n",
      "Epoch 1937/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3220 - accuracy: 0.8915 - val_loss: 1.9045 - val_accuracy: 0.5211\n",
      "Epoch 1938/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3284 - accuracy: 0.8827 - val_loss: 1.9294 - val_accuracy: 0.5211\n",
      "Epoch 1939/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3363 - accuracy: 0.8651 - val_loss: 1.9362 - val_accuracy: 0.5211\n",
      "Epoch 1940/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3161 - accuracy: 0.8827 - val_loss: 1.9026 - val_accuracy: 0.5211\n",
      "Epoch 1941/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3178 - accuracy: 0.8768 - val_loss: 1.8748 - val_accuracy: 0.5352\n",
      "Epoch 1942/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3280 - accuracy: 0.8827 - val_loss: 1.8885 - val_accuracy: 0.5352\n",
      "Epoch 1943/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3187 - accuracy: 0.8944 - val_loss: 1.8918 - val_accuracy: 0.5352\n",
      "Epoch 1944/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3300 - accuracy: 0.8886 - val_loss: 1.8884 - val_accuracy: 0.5352\n",
      "Epoch 1945/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3167 - accuracy: 0.8974 - val_loss: 1.8822 - val_accuracy: 0.5352\n",
      "Epoch 1946/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3329 - accuracy: 0.8827 - val_loss: 1.8686 - val_accuracy: 0.5352\n",
      "Epoch 1947/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3127 - accuracy: 0.9032 - val_loss: 1.8473 - val_accuracy: 0.5352\n",
      "Epoch 1948/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3201 - accuracy: 0.8768 - val_loss: 1.8313 - val_accuracy: 0.5352\n",
      "Epoch 1949/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3187 - accuracy: 0.8915 - val_loss: 1.8677 - val_accuracy: 0.5352\n",
      "Epoch 1950/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3284 - accuracy: 0.8768 - val_loss: 1.8981 - val_accuracy: 0.5211\n",
      "Epoch 1951/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3160 - accuracy: 0.8944 - val_loss: 1.8915 - val_accuracy: 0.5352\n",
      "Epoch 1952/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3164 - accuracy: 0.9003 - val_loss: 1.8978 - val_accuracy: 0.5352\n",
      "Epoch 1953/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3190 - accuracy: 0.9062 - val_loss: 1.9078 - val_accuracy: 0.5211\n",
      "Epoch 1954/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3064 - accuracy: 0.9091 - val_loss: 1.8924 - val_accuracy: 0.5352\n",
      "Epoch 1955/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3248 - accuracy: 0.8944 - val_loss: 1.8845 - val_accuracy: 0.5352\n",
      "Epoch 1956/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3256 - accuracy: 0.8680 - val_loss: 1.9020 - val_accuracy: 0.5211\n",
      "Epoch 1957/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3280 - accuracy: 0.8827 - val_loss: 1.9208 - val_accuracy: 0.5211\n",
      "Epoch 1958/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3231 - accuracy: 0.8827 - val_loss: 1.9124 - val_accuracy: 0.5211\n",
      "Epoch 1959/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3098 - accuracy: 0.9032 - val_loss: 1.9004 - val_accuracy: 0.5211\n",
      "Epoch 1960/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3210 - accuracy: 0.8886 - val_loss: 1.8870 - val_accuracy: 0.5352\n",
      "Epoch 1961/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3097 - accuracy: 0.9003 - val_loss: 1.8762 - val_accuracy: 0.5352\n",
      "Epoch 1962/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3338 - accuracy: 0.8651 - val_loss: 1.8586 - val_accuracy: 0.5352\n",
      "Epoch 1963/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3218 - accuracy: 0.8915 - val_loss: 1.8452 - val_accuracy: 0.5352\n",
      "Epoch 1964/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3181 - accuracy: 0.8886 - val_loss: 1.8361 - val_accuracy: 0.5352\n",
      "Epoch 1965/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3284 - accuracy: 0.8856 - val_loss: 1.8350 - val_accuracy: 0.5352\n",
      "Epoch 1966/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3215 - accuracy: 0.8974 - val_loss: 1.8536 - val_accuracy: 0.5352\n",
      "Epoch 1967/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3193 - accuracy: 0.8798 - val_loss: 1.8664 - val_accuracy: 0.5352\n",
      "Epoch 1968/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3350 - accuracy: 0.8534 - val_loss: 1.8849 - val_accuracy: 0.5352\n",
      "Epoch 1969/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3230 - accuracy: 0.8827 - val_loss: 1.8612 - val_accuracy: 0.5352\n",
      "Epoch 1970/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3098 - accuracy: 0.8944 - val_loss: 1.8711 - val_accuracy: 0.5352\n",
      "Epoch 1971/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3209 - accuracy: 0.8974 - val_loss: 1.8858 - val_accuracy: 0.5352\n",
      "Epoch 1972/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3143 - accuracy: 0.8886 - val_loss: 1.8781 - val_accuracy: 0.5352\n",
      "Epoch 1973/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3213 - accuracy: 0.8798 - val_loss: 1.8787 - val_accuracy: 0.5352\n",
      "Epoch 1974/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3068 - accuracy: 0.8974 - val_loss: 1.8563 - val_accuracy: 0.5352\n",
      "Epoch 1975/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3178 - accuracy: 0.8886 - val_loss: 1.8448 - val_accuracy: 0.5352\n",
      "Epoch 1976/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3231 - accuracy: 0.8886 - val_loss: 1.8456 - val_accuracy: 0.5352\n",
      "Epoch 1977/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3257 - accuracy: 0.8856 - val_loss: 1.8568 - val_accuracy: 0.5352\n",
      "Epoch 1978/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3127 - accuracy: 0.8798 - val_loss: 1.8629 - val_accuracy: 0.5352\n",
      "Epoch 1979/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3328 - accuracy: 0.8768 - val_loss: 1.8841 - val_accuracy: 0.5352\n",
      "Epoch 1980/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3246 - accuracy: 0.8944 - val_loss: 1.8980 - val_accuracy: 0.5352\n",
      "Epoch 1981/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3192 - accuracy: 0.8915 - val_loss: 1.9001 - val_accuracy: 0.5211\n",
      "Epoch 1982/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3149 - accuracy: 0.8915 - val_loss: 1.9057 - val_accuracy: 0.5211\n",
      "Epoch 1983/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3214 - accuracy: 0.9003 - val_loss: 1.9105 - val_accuracy: 0.5211\n",
      "Epoch 1984/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3120 - accuracy: 0.8944 - val_loss: 1.9008 - val_accuracy: 0.5211\n",
      "Epoch 1985/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3141 - accuracy: 0.8974 - val_loss: 1.9055 - val_accuracy: 0.5211\n",
      "Epoch 1986/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3099 - accuracy: 0.8915 - val_loss: 1.8718 - val_accuracy: 0.5352\n",
      "Epoch 1987/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3266 - accuracy: 0.8739 - val_loss: 1.8632 - val_accuracy: 0.5352\n",
      "Epoch 1988/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3113 - accuracy: 0.8886 - val_loss: 1.8571 - val_accuracy: 0.5352\n",
      "Epoch 1989/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3274 - accuracy: 0.8768 - val_loss: 1.8701 - val_accuracy: 0.5352\n",
      "Epoch 1990/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3224 - accuracy: 0.8886 - val_loss: 1.8876 - val_accuracy: 0.5352\n",
      "Epoch 1991/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3162 - accuracy: 0.8915 - val_loss: 1.8738 - val_accuracy: 0.5352\n",
      "Epoch 1992/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3068 - accuracy: 0.8915 - val_loss: 1.8641 - val_accuracy: 0.5352\n",
      "Epoch 1993/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3069 - accuracy: 0.9003 - val_loss: 1.8619 - val_accuracy: 0.5352\n",
      "Epoch 1994/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3246 - accuracy: 0.8651 - val_loss: 1.8668 - val_accuracy: 0.5352\n",
      "Epoch 1995/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3083 - accuracy: 0.8944 - val_loss: 1.8849 - val_accuracy: 0.5352\n",
      "Epoch 1996/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3117 - accuracy: 0.9003 - val_loss: 1.9096 - val_accuracy: 0.5211\n",
      "Epoch 1997/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3157 - accuracy: 0.8739 - val_loss: 1.9321 - val_accuracy: 0.5211\n",
      "Epoch 1998/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3149 - accuracy: 0.8798 - val_loss: 1.9298 - val_accuracy: 0.5211\n",
      "Epoch 1999/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3401 - accuracy: 0.8768 - val_loss: 1.9403 - val_accuracy: 0.5211\n",
      "Epoch 2000/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3099 - accuracy: 0.8974 - val_loss: 1.9324 - val_accuracy: 0.5211\n",
      "Epoch 2001/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3075 - accuracy: 0.8974 - val_loss: 1.9381 - val_accuracy: 0.5211\n",
      "Epoch 2002/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3232 - accuracy: 0.8974 - val_loss: 1.9271 - val_accuracy: 0.5211\n",
      "Epoch 2003/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3211 - accuracy: 0.8974 - val_loss: 1.9485 - val_accuracy: 0.5211\n",
      "Epoch 2004/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3458 - accuracy: 0.8504 - val_loss: 1.9327 - val_accuracy: 0.5211\n",
      "Epoch 2005/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3073 - accuracy: 0.9003 - val_loss: 1.9122 - val_accuracy: 0.5352\n",
      "Epoch 2006/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3271 - accuracy: 0.8710 - val_loss: 1.9201 - val_accuracy: 0.5352\n",
      "Epoch 2007/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3418 - accuracy: 0.8680 - val_loss: 1.8750 - val_accuracy: 0.5352\n",
      "Epoch 2008/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3180 - accuracy: 0.8798 - val_loss: 1.8601 - val_accuracy: 0.5352\n",
      "Epoch 2009/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3151 - accuracy: 0.8768 - val_loss: 1.8472 - val_accuracy: 0.5352\n",
      "Epoch 2010/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3196 - accuracy: 0.8856 - val_loss: 1.8439 - val_accuracy: 0.5352\n",
      "Epoch 2011/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3231 - accuracy: 0.8798 - val_loss: 1.8664 - val_accuracy: 0.5352\n",
      "Epoch 2012/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3144 - accuracy: 0.8856 - val_loss: 1.8646 - val_accuracy: 0.5352\n",
      "Epoch 2013/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3259 - accuracy: 0.8768 - val_loss: 1.8689 - val_accuracy: 0.5352\n",
      "Epoch 2014/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3185 - accuracy: 0.8768 - val_loss: 1.8802 - val_accuracy: 0.5352\n",
      "Epoch 2015/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3046 - accuracy: 0.8915 - val_loss: 1.8952 - val_accuracy: 0.5352\n",
      "Epoch 2016/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3268 - accuracy: 0.8886 - val_loss: 1.9091 - val_accuracy: 0.5352\n",
      "Epoch 2017/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3268 - accuracy: 0.8710 - val_loss: 1.9037 - val_accuracy: 0.5352\n",
      "Epoch 2018/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3166 - accuracy: 0.8944 - val_loss: 1.9146 - val_accuracy: 0.5352\n",
      "Epoch 2019/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3074 - accuracy: 0.8886 - val_loss: 1.8733 - val_accuracy: 0.5352\n",
      "Epoch 2020/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3150 - accuracy: 0.9003 - val_loss: 1.8567 - val_accuracy: 0.5352\n",
      "Epoch 2021/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3126 - accuracy: 0.8915 - val_loss: 1.8609 - val_accuracy: 0.5352\n",
      "Epoch 2022/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3234 - accuracy: 0.8798 - val_loss: 1.8819 - val_accuracy: 0.5352\n",
      "Epoch 2023/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3320 - accuracy: 0.8768 - val_loss: 1.9138 - val_accuracy: 0.5352\n",
      "Epoch 2024/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3229 - accuracy: 0.8827 - val_loss: 1.9701 - val_accuracy: 0.5211\n",
      "Epoch 2025/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3104 - accuracy: 0.8856 - val_loss: 2.0249 - val_accuracy: 0.5211\n",
      "Epoch 2026/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3192 - accuracy: 0.8798 - val_loss: 2.0595 - val_accuracy: 0.4930\n",
      "Epoch 2027/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3234 - accuracy: 0.8827 - val_loss: 2.0589 - val_accuracy: 0.4930\n",
      "Epoch 2028/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3131 - accuracy: 0.8974 - val_loss: 2.0268 - val_accuracy: 0.5211\n",
      "Epoch 2029/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3199 - accuracy: 0.8798 - val_loss: 1.9895 - val_accuracy: 0.5211\n",
      "Epoch 2030/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3051 - accuracy: 0.8974 - val_loss: 1.9446 - val_accuracy: 0.5352\n",
      "Epoch 2031/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3032 - accuracy: 0.9062 - val_loss: 1.9432 - val_accuracy: 0.5352\n",
      "Epoch 2032/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3148 - accuracy: 0.9003 - val_loss: 1.9411 - val_accuracy: 0.5352\n",
      "Epoch 2033/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3101 - accuracy: 0.8915 - val_loss: 1.9459 - val_accuracy: 0.5352\n",
      "Epoch 2034/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3145 - accuracy: 0.8798 - val_loss: 1.9446 - val_accuracy: 0.5352\n",
      "Epoch 2035/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3138 - accuracy: 0.8944 - val_loss: 1.9518 - val_accuracy: 0.5352\n",
      "Epoch 2036/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3245 - accuracy: 0.8827 - val_loss: 1.9926 - val_accuracy: 0.5211\n",
      "Epoch 2037/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3404 - accuracy: 0.8739 - val_loss: 2.0262 - val_accuracy: 0.5211\n",
      "Epoch 2038/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3082 - accuracy: 0.8974 - val_loss: 2.0539 - val_accuracy: 0.5070\n",
      "Epoch 2039/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3064 - accuracy: 0.8974 - val_loss: 2.0280 - val_accuracy: 0.5070\n",
      "Epoch 2040/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3431 - accuracy: 0.8622 - val_loss: 2.0117 - val_accuracy: 0.5211\n",
      "Epoch 2041/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3107 - accuracy: 0.8944 - val_loss: 1.9956 - val_accuracy: 0.5211\n",
      "Epoch 2042/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2993 - accuracy: 0.9150 - val_loss: 1.9492 - val_accuracy: 0.5352\n",
      "Epoch 2043/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3205 - accuracy: 0.8886 - val_loss: 1.9144 - val_accuracy: 0.5352\n",
      "Epoch 2044/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3022 - accuracy: 0.9179 - val_loss: 1.9116 - val_accuracy: 0.5352\n",
      "Epoch 2045/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3119 - accuracy: 0.9091 - val_loss: 1.9203 - val_accuracy: 0.5352\n",
      "Epoch 2046/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3149 - accuracy: 0.9062 - val_loss: 1.9413 - val_accuracy: 0.5352\n",
      "Epoch 2047/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3165 - accuracy: 0.8856 - val_loss: 1.9453 - val_accuracy: 0.5352\n",
      "Epoch 2048/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3300 - accuracy: 0.8710 - val_loss: 1.9474 - val_accuracy: 0.5352\n",
      "Epoch 2049/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3128 - accuracy: 0.8915 - val_loss: 1.9489 - val_accuracy: 0.5352\n",
      "Epoch 2050/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3244 - accuracy: 0.8974 - val_loss: 1.9137 - val_accuracy: 0.5352\n",
      "Epoch 2051/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3059 - accuracy: 0.8915 - val_loss: 1.9075 - val_accuracy: 0.5352\n",
      "Epoch 2052/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3154 - accuracy: 0.8827 - val_loss: 1.8981 - val_accuracy: 0.5352\n",
      "Epoch 2053/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3097 - accuracy: 0.8974 - val_loss: 1.9197 - val_accuracy: 0.5352\n",
      "Epoch 2054/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3247 - accuracy: 0.8768 - val_loss: 1.9233 - val_accuracy: 0.5352\n",
      "Epoch 2055/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3356 - accuracy: 0.8739 - val_loss: 1.9450 - val_accuracy: 0.5352\n",
      "Epoch 2056/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3184 - accuracy: 0.8856 - val_loss: 1.9675 - val_accuracy: 0.5352\n",
      "Epoch 2057/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3048 - accuracy: 0.8915 - val_loss: 1.9877 - val_accuracy: 0.5211\n",
      "Epoch 2058/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3065 - accuracy: 0.8944 - val_loss: 1.9989 - val_accuracy: 0.5211\n",
      "Epoch 2059/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3185 - accuracy: 0.8798 - val_loss: 1.9978 - val_accuracy: 0.5211\n",
      "Epoch 2060/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3062 - accuracy: 0.9091 - val_loss: 1.9762 - val_accuracy: 0.5352\n",
      "Epoch 2061/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3054 - accuracy: 0.9032 - val_loss: 1.9674 - val_accuracy: 0.5352\n",
      "Epoch 2062/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3102 - accuracy: 0.8886 - val_loss: 1.9881 - val_accuracy: 0.5211\n",
      "Epoch 2063/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3013 - accuracy: 0.9062 - val_loss: 1.9983 - val_accuracy: 0.5211\n",
      "Epoch 2064/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3080 - accuracy: 0.8944 - val_loss: 2.0149 - val_accuracy: 0.5211\n",
      "Epoch 2065/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3061 - accuracy: 0.8739 - val_loss: 2.0197 - val_accuracy: 0.5211\n",
      "Epoch 2066/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3188 - accuracy: 0.8915 - val_loss: 2.0015 - val_accuracy: 0.5211\n",
      "Epoch 2067/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3156 - accuracy: 0.8798 - val_loss: 1.9820 - val_accuracy: 0.5352\n",
      "Epoch 2068/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3230 - accuracy: 0.9032 - val_loss: 1.9702 - val_accuracy: 0.5352\n",
      "Epoch 2069/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3031 - accuracy: 0.8974 - val_loss: 1.9681 - val_accuracy: 0.5352\n",
      "Epoch 2070/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3022 - accuracy: 0.9003 - val_loss: 1.9832 - val_accuracy: 0.5352\n",
      "Epoch 2071/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3195 - accuracy: 0.8827 - val_loss: 2.0103 - val_accuracy: 0.5211\n",
      "Epoch 2072/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3193 - accuracy: 0.8827 - val_loss: 2.0100 - val_accuracy: 0.5211\n",
      "Epoch 2073/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3098 - accuracy: 0.8886 - val_loss: 2.0165 - val_accuracy: 0.5211\n",
      "Epoch 2074/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3074 - accuracy: 0.8944 - val_loss: 2.0294 - val_accuracy: 0.5211\n",
      "Epoch 2075/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3188 - accuracy: 0.8856 - val_loss: 2.0405 - val_accuracy: 0.5211\n",
      "Epoch 2076/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3112 - accuracy: 0.8915 - val_loss: 2.0746 - val_accuracy: 0.4930\n",
      "Epoch 2077/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3193 - accuracy: 0.8886 - val_loss: 2.0767 - val_accuracy: 0.4930\n",
      "Epoch 2078/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3020 - accuracy: 0.9062 - val_loss: 2.0603 - val_accuracy: 0.5070\n",
      "Epoch 2079/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3183 - accuracy: 0.8651 - val_loss: 2.0457 - val_accuracy: 0.5070\n",
      "Epoch 2080/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3083 - accuracy: 0.8944 - val_loss: 2.0082 - val_accuracy: 0.5211\n",
      "Epoch 2081/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3076 - accuracy: 0.8974 - val_loss: 1.9985 - val_accuracy: 0.5352\n",
      "Epoch 2082/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3018 - accuracy: 0.8944 - val_loss: 1.9823 - val_accuracy: 0.5352\n",
      "Epoch 2083/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3031 - accuracy: 0.9062 - val_loss: 1.9730 - val_accuracy: 0.5352\n",
      "Epoch 2084/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3405 - accuracy: 0.8680 - val_loss: 2.0101 - val_accuracy: 0.5211\n",
      "Epoch 2085/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3074 - accuracy: 0.9091 - val_loss: 2.0206 - val_accuracy: 0.5211\n",
      "Epoch 2086/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3130 - accuracy: 0.8856 - val_loss: 2.0568 - val_accuracy: 0.5070\n",
      "Epoch 2087/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3025 - accuracy: 0.9032 - val_loss: 2.0681 - val_accuracy: 0.5070\n",
      "Epoch 2088/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3121 - accuracy: 0.8944 - val_loss: 2.0603 - val_accuracy: 0.5070\n",
      "Epoch 2089/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3180 - accuracy: 0.8827 - val_loss: 2.0349 - val_accuracy: 0.5211\n",
      "Epoch 2090/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.3011 - accuracy: 0.8944 - val_loss: 2.0150 - val_accuracy: 0.5211\n",
      "Epoch 2091/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3055 - accuracy: 0.9091 - val_loss: 1.9816 - val_accuracy: 0.5352\n",
      "Epoch 2092/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3083 - accuracy: 0.8974 - val_loss: 1.9592 - val_accuracy: 0.5352\n",
      "Epoch 2093/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3113 - accuracy: 0.8798 - val_loss: 1.9384 - val_accuracy: 0.5352\n",
      "Epoch 2094/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3019 - accuracy: 0.9003 - val_loss: 1.9285 - val_accuracy: 0.5352\n",
      "Epoch 2095/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3133 - accuracy: 0.8886 - val_loss: 1.9056 - val_accuracy: 0.5352\n",
      "Epoch 2096/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3095 - accuracy: 0.8827 - val_loss: 1.9150 - val_accuracy: 0.5352\n",
      "Epoch 2097/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3391 - accuracy: 0.8798 - val_loss: 1.9082 - val_accuracy: 0.5352\n",
      "Epoch 2098/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3126 - accuracy: 0.9003 - val_loss: 1.9060 - val_accuracy: 0.5352\n",
      "Epoch 2099/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3053 - accuracy: 0.8944 - val_loss: 1.9439 - val_accuracy: 0.5352\n",
      "Epoch 2100/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3175 - accuracy: 0.8886 - val_loss: 1.9748 - val_accuracy: 0.5352\n",
      "Epoch 2101/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3160 - accuracy: 0.8886 - val_loss: 1.9868 - val_accuracy: 0.5352\n",
      "Epoch 2102/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2990 - accuracy: 0.9091 - val_loss: 1.9889 - val_accuracy: 0.5352\n",
      "Epoch 2103/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3047 - accuracy: 0.9091 - val_loss: 1.9681 - val_accuracy: 0.5352\n",
      "Epoch 2104/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2986 - accuracy: 0.9003 - val_loss: 1.9854 - val_accuracy: 0.5352\n",
      "Epoch 2105/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3076 - accuracy: 0.8944 - val_loss: 1.9524 - val_accuracy: 0.5352\n",
      "Epoch 2106/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3153 - accuracy: 0.8886 - val_loss: 1.9584 - val_accuracy: 0.5352\n",
      "Epoch 2107/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3217 - accuracy: 0.8798 - val_loss: 1.9618 - val_accuracy: 0.5352\n",
      "Epoch 2108/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3120 - accuracy: 0.8856 - val_loss: 1.9653 - val_accuracy: 0.5352\n",
      "Epoch 2109/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3169 - accuracy: 0.8886 - val_loss: 1.9687 - val_accuracy: 0.5352\n",
      "Epoch 2110/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3050 - accuracy: 0.9032 - val_loss: 1.9627 - val_accuracy: 0.5352\n",
      "Epoch 2111/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3050 - accuracy: 0.9062 - val_loss: 1.9776 - val_accuracy: 0.5352\n",
      "Epoch 2112/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3016 - accuracy: 0.9003 - val_loss: 1.9572 - val_accuracy: 0.5352\n",
      "Epoch 2113/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3051 - accuracy: 0.9003 - val_loss: 1.9725 - val_accuracy: 0.5352\n",
      "Epoch 2114/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3267 - accuracy: 0.8915 - val_loss: 1.9931 - val_accuracy: 0.5352\n",
      "Epoch 2115/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3158 - accuracy: 0.9003 - val_loss: 1.9835 - val_accuracy: 0.5352\n",
      "Epoch 2116/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3140 - accuracy: 0.9003 - val_loss: 1.9905 - val_accuracy: 0.5352\n",
      "Epoch 2117/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3124 - accuracy: 0.8856 - val_loss: 1.9986 - val_accuracy: 0.5352\n",
      "Epoch 2118/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3132 - accuracy: 0.8974 - val_loss: 2.0045 - val_accuracy: 0.5211\n",
      "Epoch 2119/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3367 - accuracy: 0.8651 - val_loss: 2.0169 - val_accuracy: 0.5211\n",
      "Epoch 2120/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3150 - accuracy: 0.8886 - val_loss: 2.0015 - val_accuracy: 0.5352\n",
      "Epoch 2121/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3235 - accuracy: 0.8827 - val_loss: 1.9927 - val_accuracy: 0.5352\n",
      "Epoch 2122/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3071 - accuracy: 0.8944 - val_loss: 2.0145 - val_accuracy: 0.5211\n",
      "Epoch 2123/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3165 - accuracy: 0.8798 - val_loss: 2.0310 - val_accuracy: 0.5211\n",
      "Epoch 2124/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3145 - accuracy: 0.8915 - val_loss: 2.0462 - val_accuracy: 0.5211\n",
      "Epoch 2125/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3037 - accuracy: 0.9032 - val_loss: 2.0441 - val_accuracy: 0.5211\n",
      "Epoch 2126/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3146 - accuracy: 0.8944 - val_loss: 2.0635 - val_accuracy: 0.5070\n",
      "Epoch 2127/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3112 - accuracy: 0.8915 - val_loss: 2.0462 - val_accuracy: 0.5211\n",
      "Epoch 2128/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3013 - accuracy: 0.9091 - val_loss: 2.0033 - val_accuracy: 0.5352\n",
      "Epoch 2129/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3206 - accuracy: 0.8856 - val_loss: 1.9725 - val_accuracy: 0.5352\n",
      "Epoch 2130/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3250 - accuracy: 0.8856 - val_loss: 1.9817 - val_accuracy: 0.5352\n",
      "Epoch 2131/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3164 - accuracy: 0.8768 - val_loss: 1.9918 - val_accuracy: 0.5352\n",
      "Epoch 2132/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3113 - accuracy: 0.8827 - val_loss: 1.9924 - val_accuracy: 0.5352\n",
      "Epoch 2133/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3126 - accuracy: 0.8886 - val_loss: 2.0269 - val_accuracy: 0.5352\n",
      "Epoch 2134/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3139 - accuracy: 0.8856 - val_loss: 2.0293 - val_accuracy: 0.5352\n",
      "Epoch 2135/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3212 - accuracy: 0.8856 - val_loss: 2.0361 - val_accuracy: 0.5352\n",
      "Epoch 2136/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3112 - accuracy: 0.8768 - val_loss: 2.0497 - val_accuracy: 0.5211\n",
      "Epoch 2137/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3117 - accuracy: 0.8886 - val_loss: 2.0910 - val_accuracy: 0.5211\n",
      "Epoch 2138/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3189 - accuracy: 0.8739 - val_loss: 2.0626 - val_accuracy: 0.5211\n",
      "Epoch 2139/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3094 - accuracy: 0.8856 - val_loss: 2.0061 - val_accuracy: 0.5352\n",
      "Epoch 2140/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3070 - accuracy: 0.8915 - val_loss: 1.9895 - val_accuracy: 0.5352\n",
      "Epoch 2141/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3145 - accuracy: 0.8798 - val_loss: 1.9644 - val_accuracy: 0.5352\n",
      "Epoch 2142/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3076 - accuracy: 0.8974 - val_loss: 1.9546 - val_accuracy: 0.5352\n",
      "Epoch 2143/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3175 - accuracy: 0.8827 - val_loss: 1.9610 - val_accuracy: 0.5352\n",
      "Epoch 2144/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3035 - accuracy: 0.8827 - val_loss: 1.9556 - val_accuracy: 0.5352\n",
      "Epoch 2145/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2963 - accuracy: 0.9032 - val_loss: 1.9860 - val_accuracy: 0.5352\n",
      "Epoch 2146/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3124 - accuracy: 0.8798 - val_loss: 2.0292 - val_accuracy: 0.5352\n",
      "Epoch 2147/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3105 - accuracy: 0.8915 - val_loss: 2.0813 - val_accuracy: 0.5211\n",
      "Epoch 2148/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3129 - accuracy: 0.8974 - val_loss: 2.0954 - val_accuracy: 0.5211\n",
      "Epoch 2149/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3026 - accuracy: 0.8827 - val_loss: 2.0733 - val_accuracy: 0.5211\n",
      "Epoch 2150/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3055 - accuracy: 0.8886 - val_loss: 2.0481 - val_accuracy: 0.5352\n",
      "Epoch 2151/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3148 - accuracy: 0.8944 - val_loss: 2.0571 - val_accuracy: 0.5211\n",
      "Epoch 2152/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3200 - accuracy: 0.8651 - val_loss: 2.0735 - val_accuracy: 0.5211\n",
      "Epoch 2153/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3001 - accuracy: 0.9003 - val_loss: 2.0545 - val_accuracy: 0.5211\n",
      "Epoch 2154/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3202 - accuracy: 0.8768 - val_loss: 2.0524 - val_accuracy: 0.5211\n",
      "Epoch 2155/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2988 - accuracy: 0.8915 - val_loss: 2.0479 - val_accuracy: 0.5352\n",
      "Epoch 2156/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3136 - accuracy: 0.8768 - val_loss: 2.0227 - val_accuracy: 0.5352\n",
      "Epoch 2157/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3118 - accuracy: 0.8886 - val_loss: 2.0131 - val_accuracy: 0.5352\n",
      "Epoch 2158/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2996 - accuracy: 0.8944 - val_loss: 2.0166 - val_accuracy: 0.5352\n",
      "Epoch 2159/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3096 - accuracy: 0.8856 - val_loss: 2.0527 - val_accuracy: 0.5352\n",
      "Epoch 2160/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3134 - accuracy: 0.8798 - val_loss: 2.0981 - val_accuracy: 0.5211\n",
      "Epoch 2161/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3195 - accuracy: 0.8680 - val_loss: 2.1189 - val_accuracy: 0.5070\n",
      "Epoch 2162/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2998 - accuracy: 0.8915 - val_loss: 2.1405 - val_accuracy: 0.4930\n",
      "Epoch 2163/10000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3191 - accuracy: 0.8798 - val_loss: 2.1680 - val_accuracy: 0.4930\n",
      "Epoch 2164/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3066 - accuracy: 0.8915 - val_loss: 2.1668 - val_accuracy: 0.4930\n",
      "Epoch 2165/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3129 - accuracy: 0.8886 - val_loss: 2.1642 - val_accuracy: 0.4930\n",
      "Epoch 2166/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3053 - accuracy: 0.8886 - val_loss: 2.1393 - val_accuracy: 0.4930\n",
      "Epoch 2167/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3126 - accuracy: 0.8915 - val_loss: 2.1113 - val_accuracy: 0.5211\n",
      "Epoch 2168/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3073 - accuracy: 0.8915 - val_loss: 2.0626 - val_accuracy: 0.5352\n",
      "Epoch 2169/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3076 - accuracy: 0.8974 - val_loss: 2.0601 - val_accuracy: 0.5352\n",
      "Epoch 2170/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3208 - accuracy: 0.8592 - val_loss: 2.0383 - val_accuracy: 0.5352\n",
      "Epoch 2171/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3047 - accuracy: 0.8974 - val_loss: 2.0051 - val_accuracy: 0.5352\n",
      "Epoch 2172/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3047 - accuracy: 0.8827 - val_loss: 1.9854 - val_accuracy: 0.5352\n",
      "Epoch 2173/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3145 - accuracy: 0.8680 - val_loss: 2.0426 - val_accuracy: 0.5352\n",
      "Epoch 2174/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3054 - accuracy: 0.8974 - val_loss: 2.0713 - val_accuracy: 0.5352\n",
      "Epoch 2175/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3229 - accuracy: 0.8710 - val_loss: 2.0762 - val_accuracy: 0.5352\n",
      "Epoch 2176/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3014 - accuracy: 0.8944 - val_loss: 2.1037 - val_accuracy: 0.5211\n",
      "Epoch 2177/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3077 - accuracy: 0.8827 - val_loss: 2.0832 - val_accuracy: 0.5211\n",
      "Epoch 2178/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2962 - accuracy: 0.9032 - val_loss: 2.0883 - val_accuracy: 0.5211\n",
      "Epoch 2179/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3032 - accuracy: 0.8827 - val_loss: 2.0921 - val_accuracy: 0.5211\n",
      "Epoch 2180/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3127 - accuracy: 0.8827 - val_loss: 2.1000 - val_accuracy: 0.5211\n",
      "Epoch 2181/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3046 - accuracy: 0.8886 - val_loss: 2.1184 - val_accuracy: 0.5211\n",
      "Epoch 2182/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3088 - accuracy: 0.8915 - val_loss: 2.1377 - val_accuracy: 0.5211\n",
      "Epoch 2183/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3085 - accuracy: 0.9003 - val_loss: 2.1722 - val_accuracy: 0.4930\n",
      "Epoch 2184/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3113 - accuracy: 0.8827 - val_loss: 2.1542 - val_accuracy: 0.5070\n",
      "Epoch 2185/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3038 - accuracy: 0.9062 - val_loss: 2.1548 - val_accuracy: 0.5070\n",
      "Epoch 2186/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2978 - accuracy: 0.9003 - val_loss: 2.1637 - val_accuracy: 0.4930\n",
      "Epoch 2187/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3046 - accuracy: 0.9003 - val_loss: 2.1702 - val_accuracy: 0.4930\n",
      "Epoch 2188/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3049 - accuracy: 0.8974 - val_loss: 2.1466 - val_accuracy: 0.5211\n",
      "Epoch 2189/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3036 - accuracy: 0.8915 - val_loss: 2.1005 - val_accuracy: 0.5211\n",
      "Epoch 2190/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3050 - accuracy: 0.8798 - val_loss: 2.0757 - val_accuracy: 0.5352\n",
      "Epoch 2191/10000\n",
      "341/341 [==============================] - 2s 4ms/step - loss: 0.3067 - accuracy: 0.9003 - val_loss: 2.0936 - val_accuracy: 0.5211\n",
      "Epoch 2192/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3066 - accuracy: 0.8915 - val_loss: 2.1122 - val_accuracy: 0.5211\n",
      "Epoch 2193/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3088 - accuracy: 0.8944 - val_loss: 2.1039 - val_accuracy: 0.5211\n",
      "Epoch 2194/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3171 - accuracy: 0.8886 - val_loss: 2.1304 - val_accuracy: 0.5211\n",
      "Epoch 2195/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3029 - accuracy: 0.8915 - val_loss: 2.1587 - val_accuracy: 0.5070\n",
      "Epoch 2196/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3133 - accuracy: 0.8798 - val_loss: 2.1590 - val_accuracy: 0.5070\n",
      "Epoch 2197/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3162 - accuracy: 0.8710 - val_loss: 2.1430 - val_accuracy: 0.5211\n",
      "Epoch 2198/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3143 - accuracy: 0.8739 - val_loss: 2.1421 - val_accuracy: 0.5211\n",
      "Epoch 2199/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2930 - accuracy: 0.8974 - val_loss: 2.1367 - val_accuracy: 0.5211\n",
      "Epoch 2200/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3100 - accuracy: 0.8827 - val_loss: 2.1256 - val_accuracy: 0.5211\n",
      "Epoch 2201/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3128 - accuracy: 0.8768 - val_loss: 2.0913 - val_accuracy: 0.5352\n",
      "Epoch 2202/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2943 - accuracy: 0.8944 - val_loss: 2.0665 - val_accuracy: 0.5352\n",
      "Epoch 2203/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3079 - accuracy: 0.8798 - val_loss: 2.0615 - val_accuracy: 0.5352\n",
      "Epoch 2204/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2982 - accuracy: 0.8974 - val_loss: 2.0624 - val_accuracy: 0.5352\n",
      "Epoch 2205/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3099 - accuracy: 0.8886 - val_loss: 2.0501 - val_accuracy: 0.5352\n",
      "Epoch 2206/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3065 - accuracy: 0.8886 - val_loss: 2.0491 - val_accuracy: 0.5352\n",
      "Epoch 2207/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2914 - accuracy: 0.9091 - val_loss: 2.0566 - val_accuracy: 0.5352\n",
      "Epoch 2208/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3024 - accuracy: 0.9032 - val_loss: 2.0565 - val_accuracy: 0.5352\n",
      "Epoch 2209/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3027 - accuracy: 0.8886 - val_loss: 2.0753 - val_accuracy: 0.5352\n",
      "Epoch 2210/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3211 - accuracy: 0.8886 - val_loss: 2.0901 - val_accuracy: 0.5352\n",
      "Epoch 2211/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2998 - accuracy: 0.9003 - val_loss: 2.1053 - val_accuracy: 0.5211\n",
      "Epoch 2212/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2917 - accuracy: 0.9062 - val_loss: 2.1208 - val_accuracy: 0.5211\n",
      "Epoch 2213/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3259 - accuracy: 0.8739 - val_loss: 2.1069 - val_accuracy: 0.5211\n",
      "Epoch 2214/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3057 - accuracy: 0.8886 - val_loss: 2.0989 - val_accuracy: 0.5211\n",
      "Epoch 2215/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3113 - accuracy: 0.8827 - val_loss: 2.1064 - val_accuracy: 0.5211\n",
      "Epoch 2216/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3080 - accuracy: 0.8974 - val_loss: 2.0924 - val_accuracy: 0.5211\n",
      "Epoch 2217/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2978 - accuracy: 0.9003 - val_loss: 2.1132 - val_accuracy: 0.5211\n",
      "Epoch 2218/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3259 - accuracy: 0.8651 - val_loss: 2.1380 - val_accuracy: 0.5070\n",
      "Epoch 2219/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3008 - accuracy: 0.8827 - val_loss: 2.1531 - val_accuracy: 0.5070\n",
      "Epoch 2220/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2959 - accuracy: 0.8944 - val_loss: 2.1365 - val_accuracy: 0.5211\n",
      "Epoch 2221/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3049 - accuracy: 0.9062 - val_loss: 2.1063 - val_accuracy: 0.5211\n",
      "Epoch 2222/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2987 - accuracy: 0.9032 - val_loss: 2.0849 - val_accuracy: 0.5352\n",
      "Epoch 2223/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2965 - accuracy: 0.9062 - val_loss: 2.0826 - val_accuracy: 0.5352\n",
      "Epoch 2224/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2908 - accuracy: 0.9003 - val_loss: 2.1010 - val_accuracy: 0.5211\n",
      "Epoch 2225/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3068 - accuracy: 0.8856 - val_loss: 2.1393 - val_accuracy: 0.5211\n",
      "Epoch 2226/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3111 - accuracy: 0.8886 - val_loss: 2.1648 - val_accuracy: 0.5070\n",
      "Epoch 2227/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2982 - accuracy: 0.9120 - val_loss: 2.2192 - val_accuracy: 0.4930\n",
      "Epoch 2228/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3016 - accuracy: 0.8944 - val_loss: 2.2137 - val_accuracy: 0.4930\n",
      "Epoch 2229/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2999 - accuracy: 0.9003 - val_loss: 2.1912 - val_accuracy: 0.4930\n",
      "Epoch 2230/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3097 - accuracy: 0.9003 - val_loss: 2.2016 - val_accuracy: 0.4930\n",
      "Epoch 2231/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3006 - accuracy: 0.9032 - val_loss: 2.1660 - val_accuracy: 0.5070\n",
      "Epoch 2232/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3008 - accuracy: 0.9032 - val_loss: 2.1484 - val_accuracy: 0.5211\n",
      "Epoch 2233/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.2977 - accuracy: 0.8944 - val_loss: 2.1404 - val_accuracy: 0.5211\n",
      "Epoch 2234/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3151 - accuracy: 0.8739 - val_loss: 2.1578 - val_accuracy: 0.5211\n",
      "Epoch 2235/10000\n",
      "341/341 [==============================] - 1s 4ms/step - loss: 0.3199 - accuracy: 0.8739 - val_loss: 2.1804 - val_accuracy: 0.5070\n",
      "Epoch 2236/10000\n",
      "120/341 [=========>....................] - ETA: 0s - loss: 0.3211 - accuracy: 0.8917"
     ]
    }
   ],
   "source": [
    "##### 10 fold test######\n",
    "valid_sdy = cytof_files.study_accession.unique()\n",
    "result = pd.DataFrame(columns=['valid', 'test', 'auc'])\n",
    "\n",
    "for i in range(10):\n",
    "    sdy = np.random.choice(valid_sdy, size=2, replace=False)\n",
    "    train_id = [i for i in range(len(x)) if cytof_files.study_accession.iloc[i] not in sdy]\n",
    "    valid_id = [i for i in range(len(x)) if cytof_files.study_accession.iloc[i]==sdy[0]]\n",
    "    test_id = [i for i in range(len(x)) if cytof_files.study_accession.iloc[i]==sdy[1]]\n",
    "\n",
    "    x_train = x[train_id]\n",
    "    x_valid = x[valid_id]\n",
    "    x_test = x[test_id]\n",
    "\n",
    "    y_train = y[train_id]\n",
    "    y_valid = y[valid_id]\n",
    "    y_test = y[test_id]\n",
    "    \n",
    "    checkpointer = keras.callbacks.ModelCheckpoint(filepath=('result_15/'+'weights'+str(i)+'.hdf5'), \n",
    "                                                   monitor='val_loss', verbose=0, save_best_only=True)\n",
    "    \n",
    "    model = keras.models.Model(inputs=[model_input],\n",
    "                           outputs=model_output)\n",
    "    \n",
    "    model.compile(loss='binary_crossentropy',\n",
    "              optimizer=keras.optimizers.Adam(lr=0.0001),\n",
    "              metrics=['accuracy'])\n",
    "\n",
    "    model.fit([x_train], y_train,\n",
    "          batch_size=60,\n",
    "          epochs=10000,\n",
    "          verbose=1,\n",
    "          callbacks=[checkpointer,earlyStop],\n",
    "          validation_data=([x_valid], y_valid))\n",
    "\n",
    "    best_model = load_model('result_15/'+'weights'+str(i)+'.hdf5')\n",
    "\n",
    "    y_true = y_test\n",
    "    y_scores = best_model.predict([x_test])\n",
    "    result = result.append({'valid':sdy[0] , 'test': sdy[1], 'auc': roc_auc_score(y_true, y_scores)}, \n",
    "                           ignore_index=True)\n",
    "    \n",
    "    result.to_csv(\"result_15_10fold_test.csv\",index=False)\n",
    "    \n",
    "    # interpret\n",
    "    dY = np.zeros([x_test.shape[0],x_test.shape[1]])\n",
    "    s1 = np.random.randint(0,(x_test.shape[1]-1),int(x_test.shape[1]*0.05))\n",
    "\n",
    "    for i2 in range(x_test.shape[0]):\n",
    "        pred_i2 = best_model.predict([x_test[[i2],:,:,:]])\n",
    "        for j in range(x_test.shape[1]):\n",
    "            t1 = x_test[[i2],:,:,:].copy()\n",
    "            t1[:,s1,:,:] = t1[:,j,:,:]\n",
    "            pred_j = best_model.predict([t1])\n",
    "            dY[i2,j] = pred_j-pred_i2\n",
    "\n",
    "    # reformat dY\n",
    "    x_test2 = x_test.reshape((x_test.shape[0]*x_test.shape[1],27))\n",
    "    dY = dY.reshape([x_test.shape[0]*x_test.shape[1]])\n",
    "\n",
    "    # Build decision tree to identify cell subset with high dY\n",
    "    regr_1 = DecisionTreeRegressor(max_depth=4)\n",
    "    regr_1.fit(x_test2, dY)\n",
    "\n",
    "    # Plot the decision tree\n",
    "    dot_data = StringIO()\n",
    "    export_graphviz(regr_1, out_file=dot_data, \n",
    "                    feature_names= markerNames,\n",
    "                    filled=True, rounded=True,\n",
    "                    special_characters=True)\n",
    "    graph = pydotplus.graph_from_dot_data(dot_data.getvalue())  \n",
    "    graph.write_pdf(('result_15/'+'tree'+str(i)+'.pdf')) "
   ]
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    "\n",
    "\n"
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