diff --git a/competitions/identify-age-related-conditions/train_models/training.ipynb b/competitions/identify-age-related-conditions/train_models/training.ipynb
index 0102191..67bf823 100644
--- a/competitions/identify-age-related-conditions/train_models/training.ipynb
+++ b/competitions/identify-age-related-conditions/train_models/training.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 92,
+   "execution_count": 109,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -41,7 +41,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 93,
+   "execution_count": 110,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -66,7 +66,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 94,
+   "execution_count": 111,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -85,7 +85,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": 112,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -113,7 +113,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 96,
+   "execution_count": 113,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -146,7 +146,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": 114,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -175,12 +175,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 98,
+   "execution_count": 115,
    "metadata": {},
    "outputs": [],
    "source": [
     "grid_params = {\"units1\": [8], \"units2\": [16,32], \"units3\": [64,128], \"activation1\": [\"relu\"], \"activation2\": [\"relu\"], \n",
-    "          \"activation3\": [\"relu\"], \"optimizer\": [Adam, RMSprop, SGD], \"learning_rate\": [0.001]}\n",
+    "          \"activation3\": [\"relu\"], \"optimizer\": [Adam, RMSprop, SGD], \"learning_rate\": [0.001, 0.0007]}\n",
     "\n",
     "#GridSearch\n",
     "def grid_search_tf_model(X_train: pd.DataFrame, y_train: pd.DataFrame)->Model:\n",
@@ -218,7 +218,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 99,
+   "execution_count": 116,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -255,7 +255,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 100,
+   "execution_count": 117,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -285,7 +285,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 101,
+   "execution_count": 118,
    "metadata": {},
    "outputs": [
     {
@@ -295,7 +295,7 @@
       "57\n",
       "dataset shape: (617, 57)\n",
       "X shape: (431, 56) and y shape: (431,)\n",
-      " Columns with MI equal zero: ['DH', 'CC', 'DN', 'BR', 'CL', 'EG', 'CD ', 'AZ', 'BD ', 'CB', 'GB', 'CF', 'EJ', 'CU', 'CW ', 'DE', 'DF', 'DY', 'AB'] --> total length: 19\n"
+      " Columns with MI equal zero: ['AY', 'DN', 'CC', 'DY', 'EG', 'CH', 'DF', 'CF', 'CD ', 'CU', 'AR', 'GB', 'DE', 'EJ', 'EL', 'DV', 'AZ', 'FD ', 'BN', 'CL', 'BD ', 'CB'] --> total length: 22\n"
      ]
     }
    ],
@@ -326,191 +326,691 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 102,
+   "execution_count": 119,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "38\n",
-      "dataset shape: (617, 38)\n",
-      "Number of columns: 37\n",
+      "35\n",
+      "dataset shape: (617, 35)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of columns: 34\n",
       "Epoch 1/100\n",
-      "11/11 [==============================] - 0s 16ms/step - loss: 0.6856 - accuracy: 0.5901 - val_loss: 0.6137 - val_accuracy: 0.7816\n",
+      "11/11 [==============================] - 0s 16ms/step - loss: 0.6561 - accuracy: 0.7471 - val_loss: 0.6202 - val_accuracy: 0.8391\n",
       "Epoch 2/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.5953 - accuracy: 0.8227 - val_loss: 0.5401 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5913 - accuracy: 0.8372 - val_loss: 0.5735 - val_accuracy: 0.8391\n",
       "Epoch 3/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.5448 - accuracy: 0.8372 - val_loss: 0.4961 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5461 - accuracy: 0.8372 - val_loss: 0.5388 - val_accuracy: 0.8391\n",
       "Epoch 4/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.5096 - accuracy: 0.8372 - val_loss: 0.4673 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5114 - accuracy: 0.8372 - val_loss: 0.5133 - val_accuracy: 0.8391\n",
       "Epoch 5/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4853 - accuracy: 0.8372 - val_loss: 0.4464 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4793 - accuracy: 0.8372 - val_loss: 0.4964 - val_accuracy: 0.8391\n",
       "Epoch 6/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4643 - accuracy: 0.8372 - val_loss: 0.4334 - val_accuracy: 0.8391\n",
-      "Epoch 7/100\n",
-      " 1/11 [=>............................] - ETA: 0s - loss: 0.4852 - accuracy: 0.8125Restoring model weights from the end of the best epoch: 2.\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.4456 - accuracy: 0.8372 - val_loss: 0.4228 - val_accuracy: 0.8391\n",
-      "Epoch 7: early stopping\n",
-      "Epoch 1/100\n",
-      "11/11 [==============================] - 0s 15ms/step - loss: 0.6956 - accuracy: 0.5959 - val_loss: 0.6155 - val_accuracy: 0.8391\n",
-      "Epoch 2/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.6004 - accuracy: 0.8256 - val_loss: 0.5349 - val_accuracy: 0.8391\n",
-      "Epoch 3/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.5545 - accuracy: 0.8401 - val_loss: 0.4919 - val_accuracy: 0.8391\n",
-      "Epoch 4/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.5145 - accuracy: 0.8401 - val_loss: 0.4642 - val_accuracy: 0.8391\n",
-      "Epoch 5/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4748 - accuracy: 0.8459 - val_loss: 0.4483 - val_accuracy: 0.8391\n",
-      "Epoch 6/100\n",
-      " 1/11 [=>............................] - ETA: 0s - loss: 0.4367 - accuracy: 0.8750Restoring model weights from the end of the best epoch: 1.\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.4351 - accuracy: 0.8459 - val_loss: 0.4269 - val_accuracy: 0.8391\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.3964 - accuracy: 0.8750Restoring model weights from the end of the best epoch: 1.\n",
+      "11/11 [==============================] - 0s 5ms/step - loss: 0.4505 - accuracy: 0.8372 - val_loss: 0.4834 - val_accuracy: 0.8391\n",
       "Epoch 6: early stopping\n",
       "Epoch 1/100\n",
-      "11/11 [==============================] - 0s 16ms/step - loss: 0.7086 - accuracy: 0.4419 - val_loss: 0.6189 - val_accuracy: 0.8276\n",
+      "11/11 [==============================] - 0s 15ms/step - loss: 0.6388 - accuracy: 0.8140 - val_loss: 0.5963 - val_accuracy: 0.8391\n",
       "Epoch 2/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.5895 - accuracy: 0.8459 - val_loss: 0.5260 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5696 - accuracy: 0.8372 - val_loss: 0.5499 - val_accuracy: 0.8391\n",
       "Epoch 3/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.5449 - accuracy: 0.8372 - val_loss: 0.4829 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5243 - accuracy: 0.8372 - val_loss: 0.5189 - val_accuracy: 0.8391\n",
       "Epoch 4/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.5045 - accuracy: 0.8401 - val_loss: 0.4571 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4787 - accuracy: 0.8372 - val_loss: 0.5014 - val_accuracy: 0.8391\n",
       "Epoch 5/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.4679 - accuracy: 0.8430 - val_loss: 0.4363 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4402 - accuracy: 0.8401 - val_loss: 0.4803 - val_accuracy: 0.8391\n",
       "Epoch 6/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4300 - accuracy: 0.8430 - val_loss: 0.4170 - val_accuracy: 0.8391\n",
-      "Epoch 7/100\n",
-      " 1/11 [=>............................] - ETA: 0s - loss: 0.3338 - accuracy: 0.9062Restoring model weights from the end of the best epoch: 2.\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.3985 - accuracy: 0.8605 - val_loss: 0.3954 - val_accuracy: 0.8391\n",
-      "Epoch 7: early stopping\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.2606 - accuracy: 0.9688Restoring model weights from the end of the best epoch: 1.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4061 - accuracy: 0.8517 - val_loss: 0.4681 - val_accuracy: 0.8391\n",
+      "Epoch 6: early stopping\n",
       "Epoch 1/100\n",
-      "11/11 [==============================] - 0s 16ms/step - loss: 0.6396 - accuracy: 0.8081 - val_loss: 0.5624 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 15ms/step - loss: 0.7284 - accuracy: 0.4157 - val_loss: 0.6167 - val_accuracy: 0.8161\n",
       "Epoch 2/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.5573 - accuracy: 0.8372 - val_loss: 0.5018 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5948 - accuracy: 0.8227 - val_loss: 0.5262 - val_accuracy: 0.8391\n",
       "Epoch 3/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4990 - accuracy: 0.8372 - val_loss: 0.4580 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 5ms/step - loss: 0.5261 - accuracy: 0.8372 - val_loss: 0.4787 - val_accuracy: 0.8391\n",
       "Epoch 4/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.4496 - accuracy: 0.8343 - val_loss: 0.4293 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4769 - accuracy: 0.8372 - val_loss: 0.4398 - val_accuracy: 0.8391\n",
       "Epoch 5/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4051 - accuracy: 0.8459 - val_loss: 0.4132 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4252 - accuracy: 0.8372 - val_loss: 0.4115 - val_accuracy: 0.8391\n",
       "Epoch 6/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.3665 - accuracy: 0.8634 - val_loss: 0.4049 - val_accuracy: 0.8506\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3769 - accuracy: 0.8605 - val_loss: 0.3935 - val_accuracy: 0.8621\n",
       "Epoch 7/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.3397 - accuracy: 0.8837 - val_loss: 0.3967 - val_accuracy: 0.8506\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.3334 - accuracy: 0.8808 - val_loss: 0.3759 - val_accuracy: 0.8621\n",
       "Epoch 8/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.3178 - accuracy: 0.9041 - val_loss: 0.3961 - val_accuracy: 0.8506\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3042 - accuracy: 0.8895 - val_loss: 0.3669 - val_accuracy: 0.8621\n",
       "Epoch 9/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.3018 - accuracy: 0.9099 - val_loss: 0.3948 - val_accuracy: 0.8506\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.2833 - accuracy: 0.9012 - val_loss: 0.3631 - val_accuracy: 0.8506\n",
       "Epoch 10/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.2875 - accuracy: 0.9099 - val_loss: 0.3997 - val_accuracy: 0.8506\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.2676 - accuracy: 0.8953 - val_loss: 0.3631 - val_accuracy: 0.8506\n",
       "Epoch 11/100\n",
-      " 1/11 [=>............................] - ETA: 0s - loss: 0.3437 - accuracy: 0.9062Restoring model weights from the end of the best epoch: 6.\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.2751 - accuracy: 0.9099 - val_loss: 0.4019 - val_accuracy: 0.8506\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.1730 - accuracy: 0.9375Restoring model weights from the end of the best epoch: 6.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.2570 - accuracy: 0.8983 - val_loss: 0.3609 - val_accuracy: 0.8621\n",
       "Epoch 11: early stopping\n",
       "Epoch 1/100\n",
-      "11/11 [==============================] - 0s 16ms/step - loss: 0.8969 - accuracy: 0.2297 - val_loss: 0.7597 - val_accuracy: 0.4713\n",
+      "11/11 [==============================] - 0s 16ms/step - loss: 0.6101 - accuracy: 0.8343 - val_loss: 0.5123 - val_accuracy: 0.8391\n",
       "Epoch 2/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.7185 - accuracy: 0.5436 - val_loss: 0.6301 - val_accuracy: 0.7471\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5191 - accuracy: 0.8372 - val_loss: 0.4737 - val_accuracy: 0.8391\n",
       "Epoch 3/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.6123 - accuracy: 0.7762 - val_loss: 0.5465 - val_accuracy: 0.7586\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4540 - accuracy: 0.8634 - val_loss: 0.4463 - val_accuracy: 0.8391\n",
       "Epoch 4/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.5408 - accuracy: 0.8401 - val_loss: 0.4930 - val_accuracy: 0.8276\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4052 - accuracy: 0.8924 - val_loss: 0.4325 - val_accuracy: 0.8391\n",
       "Epoch 5/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.4907 - accuracy: 0.8459 - val_loss: 0.4590 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3703 - accuracy: 0.8924 - val_loss: 0.4291 - val_accuracy: 0.8506\n",
       "Epoch 6/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4501 - accuracy: 0.8430 - val_loss: 0.4371 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3426 - accuracy: 0.8837 - val_loss: 0.4249 - val_accuracy: 0.8506\n",
       "Epoch 7/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4202 - accuracy: 0.8459 - val_loss: 0.4190 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3215 - accuracy: 0.8953 - val_loss: 0.4196 - val_accuracy: 0.8621\n",
       "Epoch 8/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.3892 - accuracy: 0.8488 - val_loss: 0.4064 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3018 - accuracy: 0.8953 - val_loss: 0.4276 - val_accuracy: 0.8621\n",
       "Epoch 9/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.3649 - accuracy: 0.8576 - val_loss: 0.3965 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.2864 - accuracy: 0.9099 - val_loss: 0.4162 - val_accuracy: 0.8621\n",
       "Epoch 10/100\n",
-      " 1/11 [=>............................] - ETA: 0s - loss: 0.2900 - accuracy: 0.9375Restoring model weights from the end of the best epoch: 5.\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.3420 - accuracy: 0.8692 - val_loss: 0.3873 - val_accuracy: 0.8391\n",
-      "Epoch 10: early stopping\n",
-      "Epoch 1/100\n",
-      "11/11 [==============================] - 0s 16ms/step - loss: 0.6335 - accuracy: 0.7849 - val_loss: 0.5528 - val_accuracy: 0.8391\n",
-      "Epoch 2/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.5477 - accuracy: 0.8372 - val_loss: 0.4920 - val_accuracy: 0.8391\n",
-      "Epoch 3/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.4883 - accuracy: 0.8401 - val_loss: 0.4514 - val_accuracy: 0.8391\n",
-      "Epoch 4/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4435 - accuracy: 0.8430 - val_loss: 0.4220 - val_accuracy: 0.8391\n",
-      "Epoch 5/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4014 - accuracy: 0.8459 - val_loss: 0.3975 - val_accuracy: 0.8391\n",
-      "Epoch 6/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.3657 - accuracy: 0.8488 - val_loss: 0.3775 - val_accuracy: 0.8506\n",
-      "Epoch 7/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.3343 - accuracy: 0.8721 - val_loss: 0.3609 - val_accuracy: 0.8506\n",
-      "Epoch 8/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.3069 - accuracy: 0.8837 - val_loss: 0.3547 - val_accuracy: 0.8506\n",
-      "Epoch 9/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.2838 - accuracy: 0.8837 - val_loss: 0.3453 - val_accuracy: 0.8506\n",
-      "Epoch 10/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.2615 - accuracy: 0.8924 - val_loss: 0.3440 - val_accuracy: 0.8621\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.2683 - accuracy: 0.9099 - val_loss: 0.4296 - val_accuracy: 0.8736\n",
       "Epoch 11/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.2444 - accuracy: 0.9070 - val_loss: 0.3438 - val_accuracy: 0.8621\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.2542 - accuracy: 0.9099 - val_loss: 0.4342 - val_accuracy: 0.8621\n",
       "Epoch 12/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.2285 - accuracy: 0.9128 - val_loss: 0.3447 - val_accuracy: 0.8621\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.2444 - accuracy: 0.9099 - val_loss: 0.4314 - val_accuracy: 0.8621\n",
       "Epoch 13/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.2165 - accuracy: 0.9186 - val_loss: 0.3427 - val_accuracy: 0.8621\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.2345 - accuracy: 0.9157 - val_loss: 0.4260 - val_accuracy: 0.8621\n",
       "Epoch 14/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.2012 - accuracy: 0.9331 - val_loss: 0.3522 - val_accuracy: 0.8621\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.2236 - accuracy: 0.9215 - val_loss: 0.4336 - val_accuracy: 0.8621\n",
       "Epoch 15/100\n",
-      " 1/11 [=>............................] - ETA: 0s - loss: 0.1392 - accuracy: 0.9688Restoring model weights from the end of the best epoch: 10.\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.1896 - accuracy: 0.9360 - val_loss: 0.3620 - val_accuracy: 0.8621\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.3471 - accuracy: 0.8750Restoring model weights from the end of the best epoch: 10.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.2151 - accuracy: 0.9186 - val_loss: 0.4454 - val_accuracy: 0.8621\n",
       "Epoch 15: early stopping\n",
       "Epoch 1/100\n",
-      "11/11 [==============================] - 0s 16ms/step - loss: 0.7918 - accuracy: 0.3140 - val_loss: 0.6742 - val_accuracy: 0.6437\n",
+      "11/11 [==============================] - 1s 15ms/step - loss: 0.5830 - accuracy: 0.8198 - val_loss: 0.5017 - val_accuracy: 0.8391\n",
       "Epoch 2/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.6316 - accuracy: 0.7297 - val_loss: 0.5706 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5194 - accuracy: 0.8372 - val_loss: 0.4658 - val_accuracy: 0.8391\n",
       "Epoch 3/100\n",
-      "11/11 [==============================] - 0s 5ms/step - loss: 0.5542 - accuracy: 0.8256 - val_loss: 0.5122 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4839 - accuracy: 0.8430 - val_loss: 0.4392 - val_accuracy: 0.8391\n",
       "Epoch 4/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4967 - accuracy: 0.8401 - val_loss: 0.4750 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4544 - accuracy: 0.8459 - val_loss: 0.4219 - val_accuracy: 0.8391\n",
       "Epoch 5/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4508 - accuracy: 0.8401 - val_loss: 0.4540 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4315 - accuracy: 0.8488 - val_loss: 0.4098 - val_accuracy: 0.8391\n",
       "Epoch 6/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4100 - accuracy: 0.8430 - val_loss: 0.4411 - val_accuracy: 0.8391\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.7116 - accuracy: 0.6875Restoring model weights from the end of the best epoch: 1.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4103 - accuracy: 0.8488 - val_loss: 0.3997 - val_accuracy: 0.8391\n",
+      "Epoch 6: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 1s 16ms/step - loss: 0.5854 - accuracy: 0.7703 - val_loss: 0.5036 - val_accuracy: 0.8391\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4693 - accuracy: 0.8372 - val_loss: 0.4403 - val_accuracy: 0.8391\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4031 - accuracy: 0.8459 - val_loss: 0.4113 - val_accuracy: 0.8276\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3571 - accuracy: 0.8663 - val_loss: 0.3857 - val_accuracy: 0.8161\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.3235 - accuracy: 0.8779 - val_loss: 0.3706 - val_accuracy: 0.8276\n",
+      "Epoch 6/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.1695 - accuracy: 0.9375Restoring model weights from the end of the best epoch: 1.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.3049 - accuracy: 0.8866 - val_loss: 0.3606 - val_accuracy: 0.8391\n",
+      "Epoch 6: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 1s 15ms/step - loss: 0.6416 - accuracy: 0.7122 - val_loss: 0.4936 - val_accuracy: 0.8391\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4911 - accuracy: 0.8372 - val_loss: 0.4214 - val_accuracy: 0.8391\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4431 - accuracy: 0.8372 - val_loss: 0.3941 - val_accuracy: 0.8391\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4136 - accuracy: 0.8372 - val_loss: 0.3820 - val_accuracy: 0.8391\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3916 - accuracy: 0.8372 - val_loss: 0.3724 - val_accuracy: 0.8391\n",
+      "Epoch 6/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.3220 - accuracy: 0.9062Restoring model weights from the end of the best epoch: 1.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.3686 - accuracy: 0.8372 - val_loss: 0.3656 - val_accuracy: 0.8391\n",
+      "Epoch 6: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 1s 16ms/step - loss: 0.5582 - accuracy: 0.8372 - val_loss: 0.5230 - val_accuracy: 0.8391\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4594 - accuracy: 0.8372 - val_loss: 0.4956 - val_accuracy: 0.8391\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.3915 - accuracy: 0.8663 - val_loss: 0.4875 - val_accuracy: 0.8391\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3471 - accuracy: 0.8866 - val_loss: 0.4820 - val_accuracy: 0.8276\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3192 - accuracy: 0.8983 - val_loss: 0.4814 - val_accuracy: 0.8276\n",
+      "Epoch 6/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.2134 - accuracy: 0.9688Restoring model weights from the end of the best epoch: 1.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.3034 - accuracy: 0.9012 - val_loss: 0.5029 - val_accuracy: 0.8391\n",
+      "Epoch 6: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 0s 15ms/step - loss: 0.6851 - accuracy: 0.5349 - val_loss: 0.6892 - val_accuracy: 0.5862\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6764 - accuracy: 0.5669 - val_loss: 0.6811 - val_accuracy: 0.5862\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6681 - accuracy: 0.6017 - val_loss: 0.6732 - val_accuracy: 0.5862\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6602 - accuracy: 0.6134 - val_loss: 0.6657 - val_accuracy: 0.6207\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6525 - accuracy: 0.6424 - val_loss: 0.6584 - val_accuracy: 0.6207\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6452 - accuracy: 0.6541 - val_loss: 0.6515 - val_accuracy: 0.6437\n",
       "Epoch 7/100\n",
-      " 1/11 [=>............................] - ETA: 0s - loss: 0.4157 - accuracy: 0.8125Restoring model weights from the end of the best epoch: 2.\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.3695 - accuracy: 0.8517 - val_loss: 0.4333 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6382 - accuracy: 0.6831 - val_loss: 0.6448 - val_accuracy: 0.6322\n",
+      "Epoch 8/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6314 - accuracy: 0.7151 - val_loss: 0.6384 - val_accuracy: 0.6667\n",
+      "Epoch 9/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6249 - accuracy: 0.7238 - val_loss: 0.6322 - val_accuracy: 0.6897\n",
+      "Epoch 10/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6187 - accuracy: 0.7413 - val_loss: 0.6263 - val_accuracy: 0.7356\n",
+      "Epoch 11/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6128 - accuracy: 0.7674 - val_loss: 0.6206 - val_accuracy: 0.7356\n",
+      "Epoch 12/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6070 - accuracy: 0.7820 - val_loss: 0.6151 - val_accuracy: 0.7356\n",
+      "Epoch 13/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6015 - accuracy: 0.7820 - val_loss: 0.6098 - val_accuracy: 0.7471\n",
+      "Epoch 14/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5962 - accuracy: 0.7907 - val_loss: 0.6047 - val_accuracy: 0.7816\n",
+      "Epoch 15/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5911 - accuracy: 0.7965 - val_loss: 0.5998 - val_accuracy: 0.7931\n",
+      "Epoch 16/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5862 - accuracy: 0.8023 - val_loss: 0.5952 - val_accuracy: 0.8046\n",
+      "Epoch 17/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5814 - accuracy: 0.7994 - val_loss: 0.5907 - val_accuracy: 0.8161\n",
+      "Epoch 18/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5769 - accuracy: 0.8052 - val_loss: 0.5863 - val_accuracy: 0.8046\n",
+      "Epoch 19/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5725 - accuracy: 0.8140 - val_loss: 0.5822 - val_accuracy: 0.8046\n",
+      "Epoch 20/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5684 - accuracy: 0.8227 - val_loss: 0.5782 - val_accuracy: 0.8161\n",
+      "Epoch 21/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5643 - accuracy: 0.8227 - val_loss: 0.5744 - val_accuracy: 0.8046\n",
+      "Epoch 22/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.5955 - accuracy: 0.8125Restoring model weights from the end of the best epoch: 17.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5605 - accuracy: 0.8256 - val_loss: 0.5707 - val_accuracy: 0.8046\n",
+      "Epoch 22: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 0s 16ms/step - loss: 0.6567 - accuracy: 0.7587 - val_loss: 0.6396 - val_accuracy: 0.7356\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6516 - accuracy: 0.7674 - val_loss: 0.6345 - val_accuracy: 0.7586\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6468 - accuracy: 0.7791 - val_loss: 0.6297 - val_accuracy: 0.7816\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6423 - accuracy: 0.7965 - val_loss: 0.6252 - val_accuracy: 0.7931\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6379 - accuracy: 0.8052 - val_loss: 0.6207 - val_accuracy: 0.8046\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6336 - accuracy: 0.8169 - val_loss: 0.6164 - val_accuracy: 0.8046\n",
+      "Epoch 7/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6295 - accuracy: 0.8198 - val_loss: 0.6123 - val_accuracy: 0.8161\n",
+      "Epoch 8/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6256 - accuracy: 0.8227 - val_loss: 0.6084 - val_accuracy: 0.8276\n",
+      "Epoch 9/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6218 - accuracy: 0.8227 - val_loss: 0.6046 - val_accuracy: 0.8276\n",
+      "Epoch 10/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6181 - accuracy: 0.8256 - val_loss: 0.6008 - val_accuracy: 0.8276\n",
+      "Epoch 11/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6145 - accuracy: 0.8314 - val_loss: 0.5973 - val_accuracy: 0.8276\n",
+      "Epoch 12/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6111 - accuracy: 0.8343 - val_loss: 0.5938 - val_accuracy: 0.8276\n",
+      "Epoch 13/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6077 - accuracy: 0.8343 - val_loss: 0.5905 - val_accuracy: 0.8391\n",
+      "Epoch 14/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6044 - accuracy: 0.8343 - val_loss: 0.5872 - val_accuracy: 0.8391\n",
+      "Epoch 15/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6013 - accuracy: 0.8343 - val_loss: 0.5840 - val_accuracy: 0.8391\n",
+      "Epoch 16/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5982 - accuracy: 0.8343 - val_loss: 0.5810 - val_accuracy: 0.8391\n",
+      "Epoch 17/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5952 - accuracy: 0.8343 - val_loss: 0.5781 - val_accuracy: 0.8391\n",
+      "Epoch 18/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.5912 - accuracy: 0.8750Restoring model weights from the end of the best epoch: 13.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5923 - accuracy: 0.8343 - val_loss: 0.5753 - val_accuracy: 0.8391\n",
+      "Epoch 18: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 0s 15ms/step - loss: 0.7429 - accuracy: 0.4099 - val_loss: 0.7250 - val_accuracy: 0.4368\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 5ms/step - loss: 0.7316 - accuracy: 0.4477 - val_loss: 0.7135 - val_accuracy: 0.4943\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.7209 - accuracy: 0.4738 - val_loss: 0.7026 - val_accuracy: 0.5402\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.7107 - accuracy: 0.5087 - val_loss: 0.6922 - val_accuracy: 0.5517\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.7011 - accuracy: 0.5552 - val_loss: 0.6823 - val_accuracy: 0.5747\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6920 - accuracy: 0.6134 - val_loss: 0.6729 - val_accuracy: 0.6092\n",
+      "Epoch 7/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6835 - accuracy: 0.6657 - val_loss: 0.6640 - val_accuracy: 0.6437\n",
+      "Epoch 8/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6753 - accuracy: 0.6802 - val_loss: 0.6555 - val_accuracy: 0.6437\n",
+      "Epoch 9/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6676 - accuracy: 0.6948 - val_loss: 0.6475 - val_accuracy: 0.6897\n",
+      "Epoch 10/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6603 - accuracy: 0.7267 - val_loss: 0.6398 - val_accuracy: 0.7356\n",
+      "Epoch 11/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6533 - accuracy: 0.7267 - val_loss: 0.6325 - val_accuracy: 0.7701\n",
+      "Epoch 12/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6468 - accuracy: 0.7413 - val_loss: 0.6256 - val_accuracy: 0.7931\n",
+      "Epoch 13/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6405 - accuracy: 0.7500 - val_loss: 0.6189 - val_accuracy: 0.7931\n",
+      "Epoch 14/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6346 - accuracy: 0.7529 - val_loss: 0.6125 - val_accuracy: 0.7931\n",
+      "Epoch 15/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6289 - accuracy: 0.7529 - val_loss: 0.6064 - val_accuracy: 0.8161\n",
+      "Epoch 16/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6235 - accuracy: 0.7703 - val_loss: 0.6006 - val_accuracy: 0.8391\n",
+      "Epoch 17/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6183 - accuracy: 0.7878 - val_loss: 0.5951 - val_accuracy: 0.8506\n",
+      "Epoch 18/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6135 - accuracy: 0.7936 - val_loss: 0.5896 - val_accuracy: 0.8391\n",
+      "Epoch 19/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6086 - accuracy: 0.8052 - val_loss: 0.5844 - val_accuracy: 0.8391\n",
+      "Epoch 20/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6041 - accuracy: 0.8052 - val_loss: 0.5795 - val_accuracy: 0.8391\n",
+      "Epoch 21/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5998 - accuracy: 0.8023 - val_loss: 0.5748 - val_accuracy: 0.8391\n",
+      "Epoch 22/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.5433 - accuracy: 0.8125Restoring model weights from the end of the best epoch: 17.\n",
+      "11/11 [==============================] - 0s 5ms/step - loss: 0.5957 - accuracy: 0.8081 - val_loss: 0.5702 - val_accuracy: 0.8276\n",
+      "Epoch 22: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 0s 16ms/step - loss: 0.7568 - accuracy: 0.2035 - val_loss: 0.7384 - val_accuracy: 0.2299\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.7452 - accuracy: 0.2733 - val_loss: 0.7282 - val_accuracy: 0.3448\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.7341 - accuracy: 0.3401 - val_loss: 0.7183 - val_accuracy: 0.4253\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.7236 - accuracy: 0.4099 - val_loss: 0.7091 - val_accuracy: 0.4828\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.7137 - accuracy: 0.4855 - val_loss: 0.7002 - val_accuracy: 0.5862\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.7044 - accuracy: 0.5203 - val_loss: 0.6918 - val_accuracy: 0.6207\n",
+      "Epoch 7/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6955 - accuracy: 0.5698 - val_loss: 0.6838 - val_accuracy: 0.6667\n",
+      "Epoch 8/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6871 - accuracy: 0.6134 - val_loss: 0.6762 - val_accuracy: 0.6782\n",
+      "Epoch 9/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6793 - accuracy: 0.6715 - val_loss: 0.6689 - val_accuracy: 0.7126\n",
+      "Epoch 10/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6717 - accuracy: 0.7035 - val_loss: 0.6620 - val_accuracy: 0.7241\n",
+      "Epoch 11/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6647 - accuracy: 0.7238 - val_loss: 0.6554 - val_accuracy: 0.7701\n",
+      "Epoch 12/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6580 - accuracy: 0.7674 - val_loss: 0.6492 - val_accuracy: 0.7816\n",
+      "Epoch 13/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6516 - accuracy: 0.7791 - val_loss: 0.6431 - val_accuracy: 0.7816\n",
+      "Epoch 14/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6456 - accuracy: 0.7965 - val_loss: 0.6373 - val_accuracy: 0.8046\n",
+      "Epoch 15/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6398 - accuracy: 0.8081 - val_loss: 0.6319 - val_accuracy: 0.8276\n",
+      "Epoch 16/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6343 - accuracy: 0.8140 - val_loss: 0.6265 - val_accuracy: 0.8391\n",
+      "Epoch 17/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6291 - accuracy: 0.8198 - val_loss: 0.6215 - val_accuracy: 0.8391\n",
+      "Epoch 18/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6242 - accuracy: 0.8227 - val_loss: 0.6167 - val_accuracy: 0.8391\n",
+      "Epoch 19/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6194 - accuracy: 0.8314 - val_loss: 0.6120 - val_accuracy: 0.8391\n",
+      "Epoch 20/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6148 - accuracy: 0.8314 - val_loss: 0.6076 - val_accuracy: 0.8391\n",
+      "Epoch 21/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.6200 - accuracy: 0.7500Restoring model weights from the end of the best epoch: 16.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6105 - accuracy: 0.8343 - val_loss: 0.6033 - val_accuracy: 0.8391\n",
+      "Epoch 21: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 0s 15ms/step - loss: 0.7095 - accuracy: 0.4564 - val_loss: 0.6819 - val_accuracy: 0.6437\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6405 - accuracy: 0.7878 - val_loss: 0.6349 - val_accuracy: 0.8046\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5892 - accuracy: 0.8285 - val_loss: 0.5962 - val_accuracy: 0.8276\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5445 - accuracy: 0.8372 - val_loss: 0.5638 - val_accuracy: 0.8391\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5027 - accuracy: 0.8372 - val_loss: 0.5384 - val_accuracy: 0.8391\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4690 - accuracy: 0.8372 - val_loss: 0.5193 - val_accuracy: 0.8391\n",
+      "Epoch 7/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4395 - accuracy: 0.8372 - val_loss: 0.5065 - val_accuracy: 0.8391\n",
+      "Epoch 8/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4162 - accuracy: 0.8401 - val_loss: 0.4990 - val_accuracy: 0.8391\n",
+      "Epoch 9/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.3528 - accuracy: 0.8750Restoring model weights from the end of the best epoch: 4.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.3988 - accuracy: 0.8430 - val_loss: 0.4951 - val_accuracy: 0.8391\n",
+      "Epoch 9: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 0s 15ms/step - loss: 0.7215 - accuracy: 0.3983 - val_loss: 0.6485 - val_accuracy: 0.8046\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6172 - accuracy: 0.8140 - val_loss: 0.5619 - val_accuracy: 0.8391\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5548 - accuracy: 0.8372 - val_loss: 0.5092 - val_accuracy: 0.8391\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5142 - accuracy: 0.8372 - val_loss: 0.4766 - val_accuracy: 0.8391\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4841 - accuracy: 0.8372 - val_loss: 0.4526 - val_accuracy: 0.8391\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4586 - accuracy: 0.8372 - val_loss: 0.4389 - val_accuracy: 0.8391\n",
+      "Epoch 7/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.3790 - accuracy: 0.8750Restoring model weights from the end of the best epoch: 2.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4360 - accuracy: 0.8372 - val_loss: 0.4309 - val_accuracy: 0.8391\n",
       "Epoch 7: early stopping\n",
       "Epoch 1/100\n",
-      "11/11 [==============================] - 0s 15ms/step - loss: 0.8143 - accuracy: 0.2994 - val_loss: 0.6333 - val_accuracy: 0.7586\n",
+      "11/11 [==============================] - 0s 16ms/step - loss: 0.7462 - accuracy: 0.3750 - val_loss: 0.6626 - val_accuracy: 0.6897\n",
       "Epoch 2/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.5870 - accuracy: 0.8227 - val_loss: 0.5004 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6276 - accuracy: 0.7733 - val_loss: 0.5712 - val_accuracy: 0.8161\n",
       "Epoch 3/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.5142 - accuracy: 0.8372 - val_loss: 0.4455 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5523 - accuracy: 0.8401 - val_loss: 0.5149 - val_accuracy: 0.8391\n",
       "Epoch 4/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4769 - accuracy: 0.8372 - val_loss: 0.4203 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5019 - accuracy: 0.8459 - val_loss: 0.4774 - val_accuracy: 0.8391\n",
       "Epoch 5/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.4411 - accuracy: 0.8372 - val_loss: 0.4046 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4635 - accuracy: 0.8459 - val_loss: 0.4510 - val_accuracy: 0.8391\n",
       "Epoch 6/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4000 - accuracy: 0.8372 - val_loss: 0.3902 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4350 - accuracy: 0.8459 - val_loss: 0.4332 - val_accuracy: 0.8391\n",
       "Epoch 7/100\n",
-      " 1/11 [=>............................] - ETA: 0s - loss: 0.2600 - accuracy: 0.9375Restoring model weights from the end of the best epoch: 2.\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.3656 - accuracy: 0.8430 - val_loss: 0.3776 - val_accuracy: 0.8391\n",
-      "Epoch 7: early stopping\n",
-      "best acc at index 5: 0.8620689511299133\n",
-      "best loss at index 5: 0.3620067536830902\n",
-      "{'units3': 64, 'units2': 16, 'units1': 16, 'optimizer': <class 'keras.optimizers.legacy.adam.Adam'>, 'learning_rate': 0.001, 'activation3': 'relu', 'activation2': 'relu', 'activation1': 'relu'}\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4125 - accuracy: 0.8488 - val_loss: 0.4226 - val_accuracy: 0.8391\n",
+      "Epoch 8/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.3229 - accuracy: 0.9062Restoring model weights from the end of the best epoch: 3.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.3944 - accuracy: 0.8488 - val_loss: 0.4144 - val_accuracy: 0.8391\n",
+      "Epoch 8: early stopping\n",
       "Epoch 1/100\n",
-      "11/11 [==============================] - 0s 15ms/step - loss: 0.6786 - accuracy: 0.6453 - val_loss: 0.5829 - val_accuracy: 0.8276\n",
+      "11/11 [==============================] - 0s 15ms/step - loss: 0.6074 - accuracy: 0.8052 - val_loss: 0.5724 - val_accuracy: 0.8391\n",
       "Epoch 2/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.5685 - accuracy: 0.8488 - val_loss: 0.5142 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5342 - accuracy: 0.8372 - val_loss: 0.5336 - val_accuracy: 0.8391\n",
       "Epoch 3/100\n",
-      "11/11 [==============================] - 0s 5ms/step - loss: 0.5102 - accuracy: 0.8372 - val_loss: 0.4789 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4959 - accuracy: 0.8372 - val_loss: 0.5233 - val_accuracy: 0.8391\n",
       "Epoch 4/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4728 - accuracy: 0.8401 - val_loss: 0.4561 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4686 - accuracy: 0.8372 - val_loss: 0.5218 - val_accuracy: 0.8391\n",
       "Epoch 5/100\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.4380 - accuracy: 0.8488 - val_loss: 0.4398 - val_accuracy: 0.8391\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4488 - accuracy: 0.8372 - val_loss: 0.5201 - val_accuracy: 0.8391\n",
       "Epoch 6/100\n",
-      "11/11 [==============================] - 0s 3ms/step - loss: 0.4107 - accuracy: 0.8547 - val_loss: 0.4282 - val_accuracy: 0.8391\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.4088 - accuracy: 0.8750Restoring model weights from the end of the best epoch: 1.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4277 - accuracy: 0.8372 - val_loss: 0.5169 - val_accuracy: 0.8391\n",
+      "Epoch 6: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 1s 16ms/step - loss: 0.6447 - accuracy: 0.8081 - val_loss: 0.5849 - val_accuracy: 0.8391\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5958 - accuracy: 0.8372 - val_loss: 0.5489 - val_accuracy: 0.8391\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 5ms/step - loss: 0.5652 - accuracy: 0.8372 - val_loss: 0.5187 - val_accuracy: 0.8391\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5387 - accuracy: 0.8372 - val_loss: 0.4960 - val_accuracy: 0.8391\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5142 - accuracy: 0.8372 - val_loss: 0.4750 - val_accuracy: 0.8391\n",
+      "Epoch 6/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.5897 - accuracy: 0.7500Restoring model weights from the end of the best epoch: 1.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4916 - accuracy: 0.8372 - val_loss: 0.4582 - val_accuracy: 0.8391\n",
+      "Epoch 6: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 1s 16ms/step - loss: 0.6374 - accuracy: 0.7703 - val_loss: 0.5730 - val_accuracy: 0.8391\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5777 - accuracy: 0.8372 - val_loss: 0.5332 - val_accuracy: 0.8391\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5458 - accuracy: 0.8372 - val_loss: 0.5065 - val_accuracy: 0.8391\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5243 - accuracy: 0.8372 - val_loss: 0.4933 - val_accuracy: 0.8391\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5040 - accuracy: 0.8372 - val_loss: 0.4807 - val_accuracy: 0.8391\n",
+      "Epoch 6/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.3613 - accuracy: 0.9375Restoring model weights from the end of the best epoch: 1.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4850 - accuracy: 0.8372 - val_loss: 0.4738 - val_accuracy: 0.8391\n",
+      "Epoch 6: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 1s 15ms/step - loss: 0.6247 - accuracy: 0.7616 - val_loss: 0.5506 - val_accuracy: 0.8391\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5528 - accuracy: 0.8372 - val_loss: 0.5061 - val_accuracy: 0.8391\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5168 - accuracy: 0.8372 - val_loss: 0.4745 - val_accuracy: 0.8391\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4883 - accuracy: 0.8372 - val_loss: 0.4520 - val_accuracy: 0.8391\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4657 - accuracy: 0.8372 - val_loss: 0.4388 - val_accuracy: 0.8391\n",
+      "Epoch 6/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.4244 - accuracy: 0.8750Restoring model weights from the end of the best epoch: 1.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4434 - accuracy: 0.8401 - val_loss: 0.4271 - val_accuracy: 0.8391\n",
+      "Epoch 6: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 1s 16ms/step - loss: 0.6038 - accuracy: 0.8169 - val_loss: 0.5589 - val_accuracy: 0.8391\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5368 - accuracy: 0.8372 - val_loss: 0.5275 - val_accuracy: 0.8391\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5016 - accuracy: 0.8372 - val_loss: 0.5100 - val_accuracy: 0.8391\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4754 - accuracy: 0.8372 - val_loss: 0.4983 - val_accuracy: 0.8391\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4499 - accuracy: 0.8401 - val_loss: 0.4864 - val_accuracy: 0.8391\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.4290 - accuracy: 0.8401 - val_loss: 0.4761 - val_accuracy: 0.8506\n",
       "Epoch 7/100\n",
-      " 1/11 [=>............................] - ETA: 0s - loss: 0.3892 - accuracy: 0.8438Restoring model weights from the end of the best epoch: 2.\n",
-      "11/11 [==============================] - 0s 4ms/step - loss: 0.3847 - accuracy: 0.8576 - val_loss: 0.4165 - val_accuracy: 0.8391\n",
-      "Epoch 7: early stopping\n"
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4088 - accuracy: 0.8372 - val_loss: 0.4675 - val_accuracy: 0.8391\n",
+      "Epoch 8/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3895 - accuracy: 0.8517 - val_loss: 0.4596 - val_accuracy: 0.8391\n",
+      "Epoch 9/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3736 - accuracy: 0.8692 - val_loss: 0.4570 - val_accuracy: 0.8391\n",
+      "Epoch 10/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3604 - accuracy: 0.8692 - val_loss: 0.4480 - val_accuracy: 0.8391\n",
+      "Epoch 11/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.4443 - accuracy: 0.8438Restoring model weights from the end of the best epoch: 6.\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3477 - accuracy: 0.8779 - val_loss: 0.4473 - val_accuracy: 0.8391\n",
+      "Epoch 11: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 1s 15ms/step - loss: 0.5843 - accuracy: 0.8227 - val_loss: 0.5854 - val_accuracy: 0.8046\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5818 - accuracy: 0.8256 - val_loss: 0.5827 - val_accuracy: 0.8161\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5792 - accuracy: 0.8256 - val_loss: 0.5800 - val_accuracy: 0.8161\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5768 - accuracy: 0.8256 - val_loss: 0.5774 - val_accuracy: 0.8161\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5744 - accuracy: 0.8285 - val_loss: 0.5749 - val_accuracy: 0.8161\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5721 - accuracy: 0.8285 - val_loss: 0.5724 - val_accuracy: 0.8276\n",
+      "Epoch 7/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5698 - accuracy: 0.8314 - val_loss: 0.5700 - val_accuracy: 0.8276\n",
+      "Epoch 8/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5675 - accuracy: 0.8314 - val_loss: 0.5676 - val_accuracy: 0.8391\n",
+      "Epoch 9/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5653 - accuracy: 0.8285 - val_loss: 0.5652 - val_accuracy: 0.8391\n",
+      "Epoch 10/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5632 - accuracy: 0.8343 - val_loss: 0.5630 - val_accuracy: 0.8391\n",
+      "Epoch 11/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5611 - accuracy: 0.8343 - val_loss: 0.5607 - val_accuracy: 0.8391\n",
+      "Epoch 12/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5591 - accuracy: 0.8343 - val_loss: 0.5585 - val_accuracy: 0.8391\n",
+      "Epoch 13/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.5193 - accuracy: 0.8125Restoring model weights from the end of the best epoch: 8.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5570 - accuracy: 0.8343 - val_loss: 0.5563 - val_accuracy: 0.8391\n",
+      "Epoch 13: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 0s 15ms/step - loss: 0.7949 - accuracy: 0.2703 - val_loss: 0.8107 - val_accuracy: 0.2644\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.7842 - accuracy: 0.3198 - val_loss: 0.8006 - val_accuracy: 0.2989\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.7740 - accuracy: 0.3605 - val_loss: 0.7910 - val_accuracy: 0.3218\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.7642 - accuracy: 0.3721 - val_loss: 0.7816 - val_accuracy: 0.3448\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.7547 - accuracy: 0.3983 - val_loss: 0.7727 - val_accuracy: 0.3448\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.7456 - accuracy: 0.4244 - val_loss: 0.7641 - val_accuracy: 0.3793\n",
+      "Epoch 7/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.7370 - accuracy: 0.4506 - val_loss: 0.7557 - val_accuracy: 0.4253\n",
+      "Epoch 8/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.7285 - accuracy: 0.4797 - val_loss: 0.7479 - val_accuracy: 0.4483\n",
+      "Epoch 9/100\n",
+      "11/11 [==============================] - 0s 5ms/step - loss: 0.7206 - accuracy: 0.4913 - val_loss: 0.7403 - val_accuracy: 0.4828\n",
+      "Epoch 10/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.7129 - accuracy: 0.5233 - val_loss: 0.7329 - val_accuracy: 0.4828\n",
+      "Epoch 11/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.7055 - accuracy: 0.5320 - val_loss: 0.7257 - val_accuracy: 0.4828\n",
+      "Epoch 12/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6983 - accuracy: 0.5552 - val_loss: 0.7188 - val_accuracy: 0.5402\n",
+      "Epoch 13/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6914 - accuracy: 0.5959 - val_loss: 0.7122 - val_accuracy: 0.5402\n",
+      "Epoch 14/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6848 - accuracy: 0.6221 - val_loss: 0.7059 - val_accuracy: 0.5402\n",
+      "Epoch 15/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6784 - accuracy: 0.6628 - val_loss: 0.6997 - val_accuracy: 0.5402\n",
+      "Epoch 16/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6722 - accuracy: 0.6599 - val_loss: 0.6936 - val_accuracy: 0.5402\n",
+      "Epoch 17/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6662 - accuracy: 0.6715 - val_loss: 0.6879 - val_accuracy: 0.5747\n",
+      "Epoch 18/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6605 - accuracy: 0.6860 - val_loss: 0.6823 - val_accuracy: 0.5977\n",
+      "Epoch 19/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6550 - accuracy: 0.7006 - val_loss: 0.6770 - val_accuracy: 0.6092\n",
+      "Epoch 20/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6496 - accuracy: 0.7180 - val_loss: 0.6718 - val_accuracy: 0.6437\n",
+      "Epoch 21/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6445 - accuracy: 0.7384 - val_loss: 0.6668 - val_accuracy: 0.6552\n",
+      "Epoch 22/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6396 - accuracy: 0.7645 - val_loss: 0.6619 - val_accuracy: 0.6552\n",
+      "Epoch 23/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6347 - accuracy: 0.7762 - val_loss: 0.6573 - val_accuracy: 0.6552\n",
+      "Epoch 24/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6302 - accuracy: 0.7878 - val_loss: 0.6528 - val_accuracy: 0.6782\n",
+      "Epoch 25/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6257 - accuracy: 0.7994 - val_loss: 0.6484 - val_accuracy: 0.7126\n",
+      "Epoch 26/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6214 - accuracy: 0.8052 - val_loss: 0.6441 - val_accuracy: 0.7241\n",
+      "Epoch 27/100\n",
+      "11/11 [==============================] - 0s 5ms/step - loss: 0.6171 - accuracy: 0.8110 - val_loss: 0.6399 - val_accuracy: 0.7586\n",
+      "Epoch 28/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6131 - accuracy: 0.8052 - val_loss: 0.6359 - val_accuracy: 0.7701\n",
+      "Epoch 29/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6091 - accuracy: 0.8169 - val_loss: 0.6321 - val_accuracy: 0.7701\n",
+      "Epoch 30/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6054 - accuracy: 0.8256 - val_loss: 0.6283 - val_accuracy: 0.7701\n",
+      "Epoch 31/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6017 - accuracy: 0.8227 - val_loss: 0.6246 - val_accuracy: 0.7701\n",
+      "Epoch 32/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5981 - accuracy: 0.8227 - val_loss: 0.6211 - val_accuracy: 0.7816\n",
+      "Epoch 33/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5947 - accuracy: 0.8169 - val_loss: 0.6178 - val_accuracy: 0.7816\n",
+      "Epoch 34/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5914 - accuracy: 0.8285 - val_loss: 0.6144 - val_accuracy: 0.7931\n",
+      "Epoch 35/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5882 - accuracy: 0.8343 - val_loss: 0.6112 - val_accuracy: 0.7931\n",
+      "Epoch 36/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5851 - accuracy: 0.8343 - val_loss: 0.6081 - val_accuracy: 0.7931\n",
+      "Epoch 37/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5821 - accuracy: 0.8343 - val_loss: 0.6051 - val_accuracy: 0.7931\n",
+      "Epoch 38/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5791 - accuracy: 0.8343 - val_loss: 0.6021 - val_accuracy: 0.7931\n",
+      "Epoch 39/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5763 - accuracy: 0.8459 - val_loss: 0.5992 - val_accuracy: 0.8046\n",
+      "Epoch 40/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5735 - accuracy: 0.8459 - val_loss: 0.5964 - val_accuracy: 0.8046\n",
+      "Epoch 41/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5708 - accuracy: 0.8430 - val_loss: 0.5937 - val_accuracy: 0.8046\n",
+      "Epoch 42/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5681 - accuracy: 0.8459 - val_loss: 0.5911 - val_accuracy: 0.8046\n",
+      "Epoch 43/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5656 - accuracy: 0.8430 - val_loss: 0.5885 - val_accuracy: 0.8046\n",
+      "Epoch 44/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5631 - accuracy: 0.8430 - val_loss: 0.5860 - val_accuracy: 0.8161\n",
+      "Epoch 45/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5607 - accuracy: 0.8430 - val_loss: 0.5836 - val_accuracy: 0.8391\n",
+      "Epoch 46/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5584 - accuracy: 0.8430 - val_loss: 0.5813 - val_accuracy: 0.8391\n",
+      "Epoch 47/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5562 - accuracy: 0.8430 - val_loss: 0.5790 - val_accuracy: 0.8391\n",
+      "Epoch 48/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5540 - accuracy: 0.8459 - val_loss: 0.5768 - val_accuracy: 0.8391\n",
+      "Epoch 49/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.5518 - accuracy: 0.8459 - val_loss: 0.5747 - val_accuracy: 0.8391\n",
+      "Epoch 50/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.5793 - accuracy: 0.7500Restoring model weights from the end of the best epoch: 45.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5498 - accuracy: 0.8430 - val_loss: 0.5726 - val_accuracy: 0.8391\n",
+      "Epoch 50: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 0s 15ms/step - loss: 0.6551 - accuracy: 0.7180 - val_loss: 0.6410 - val_accuracy: 0.7241\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6514 - accuracy: 0.7471 - val_loss: 0.6370 - val_accuracy: 0.7586\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6479 - accuracy: 0.7616 - val_loss: 0.6330 - val_accuracy: 0.7701\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6444 - accuracy: 0.7907 - val_loss: 0.6291 - val_accuracy: 0.7816\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6410 - accuracy: 0.8023 - val_loss: 0.6253 - val_accuracy: 0.7816\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6378 - accuracy: 0.8227 - val_loss: 0.6218 - val_accuracy: 0.8161\n",
+      "Epoch 7/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6346 - accuracy: 0.8285 - val_loss: 0.6184 - val_accuracy: 0.8276\n",
+      "Epoch 8/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6315 - accuracy: 0.8372 - val_loss: 0.6149 - val_accuracy: 0.8276\n",
+      "Epoch 9/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6284 - accuracy: 0.8517 - val_loss: 0.6116 - val_accuracy: 0.8391\n",
+      "Epoch 10/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6256 - accuracy: 0.8547 - val_loss: 0.6084 - val_accuracy: 0.8391\n",
+      "Epoch 11/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6226 - accuracy: 0.8517 - val_loss: 0.6054 - val_accuracy: 0.8391\n",
+      "Epoch 12/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6198 - accuracy: 0.8547 - val_loss: 0.6024 - val_accuracy: 0.8391\n",
+      "Epoch 13/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6170 - accuracy: 0.8517 - val_loss: 0.5994 - val_accuracy: 0.8391\n",
+      "Epoch 14/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.5474 - accuracy: 0.9062Restoring model weights from the end of the best epoch: 9.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6143 - accuracy: 0.8547 - val_loss: 0.5966 - val_accuracy: 0.8391\n",
+      "Epoch 14: early stopping\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 0s 15ms/step - loss: 0.6945 - accuracy: 0.5610 - val_loss: 0.6824 - val_accuracy: 0.6552\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6874 - accuracy: 0.5959 - val_loss: 0.6757 - val_accuracy: 0.7241\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6806 - accuracy: 0.6395 - val_loss: 0.6695 - val_accuracy: 0.7356\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6742 - accuracy: 0.6744 - val_loss: 0.6634 - val_accuracy: 0.7126\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6682 - accuracy: 0.7122 - val_loss: 0.6575 - val_accuracy: 0.7241\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6624 - accuracy: 0.7267 - val_loss: 0.6520 - val_accuracy: 0.7701\n",
+      "Epoch 7/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6569 - accuracy: 0.7616 - val_loss: 0.6466 - val_accuracy: 0.7586\n",
+      "Epoch 8/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6517 - accuracy: 0.7674 - val_loss: 0.6414 - val_accuracy: 0.7586\n",
+      "Epoch 9/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6467 - accuracy: 0.7936 - val_loss: 0.6364 - val_accuracy: 0.7586\n",
+      "Epoch 10/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6420 - accuracy: 0.8052 - val_loss: 0.6316 - val_accuracy: 0.7586\n",
+      "Epoch 11/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6373 - accuracy: 0.8198 - val_loss: 0.6270 - val_accuracy: 0.8046\n",
+      "Epoch 12/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6330 - accuracy: 0.8169 - val_loss: 0.6225 - val_accuracy: 0.8046\n",
+      "Epoch 13/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6288 - accuracy: 0.8198 - val_loss: 0.6182 - val_accuracy: 0.8046\n",
+      "Epoch 14/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6248 - accuracy: 0.8256 - val_loss: 0.6140 - val_accuracy: 0.8391\n",
+      "Epoch 15/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6210 - accuracy: 0.8372 - val_loss: 0.6099 - val_accuracy: 0.8391\n",
+      "Epoch 16/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6172 - accuracy: 0.8372 - val_loss: 0.6060 - val_accuracy: 0.8391\n",
+      "Epoch 17/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.6137 - accuracy: 0.8372 - val_loss: 0.6022 - val_accuracy: 0.8391\n",
+      "Epoch 18/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6102 - accuracy: 0.8459 - val_loss: 0.5985 - val_accuracy: 0.8391\n",
+      "Epoch 19/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.5978 - accuracy: 0.8125Restoring model weights from the end of the best epoch: 14.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.6069 - accuracy: 0.8459 - val_loss: 0.5949 - val_accuracy: 0.8391\n",
+      "Epoch 19: early stopping\n",
+      "best acc at index 2: 0.8620689511299133\n",
+      "best loss at index 5: 0.36059069633483887\n",
+      "{'units3': 64, 'units2': 32, 'units1': 8, 'optimizer': <class 'keras.optimizers.legacy.adam.Adam'>, 'learning_rate': 0.001, 'activation3': 'relu', 'activation2': 'relu', 'activation1': 'relu'}\n",
+      "Epoch 1/100\n",
+      "11/11 [==============================] - 0s 15ms/step - loss: 0.6042 - accuracy: 0.8227 - val_loss: 0.5625 - val_accuracy: 0.8161\n",
+      "Epoch 2/100\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.5076 - accuracy: 0.8488 - val_loss: 0.5082 - val_accuracy: 0.8276\n",
+      "Epoch 3/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4523 - accuracy: 0.8401 - val_loss: 0.4729 - val_accuracy: 0.8391\n",
+      "Epoch 4/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.4084 - accuracy: 0.8488 - val_loss: 0.4537 - val_accuracy: 0.8391\n",
+      "Epoch 5/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3751 - accuracy: 0.8547 - val_loss: 0.4435 - val_accuracy: 0.8391\n",
+      "Epoch 6/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3506 - accuracy: 0.8605 - val_loss: 0.4383 - val_accuracy: 0.8391\n",
+      "Epoch 7/100\n",
+      "11/11 [==============================] - 0s 3ms/step - loss: 0.3295 - accuracy: 0.8779 - val_loss: 0.4319 - val_accuracy: 0.8046\n",
+      "Epoch 8/100\n",
+      " 1/11 [=>............................] - ETA: 0s - loss: 0.2080 - accuracy: 0.9062Restoring model weights from the end of the best epoch: 3.\n",
+      "11/11 [==============================] - 0s 4ms/step - loss: 0.3104 - accuracy: 0.8837 - val_loss: 0.4308 - val_accuracy: 0.8046\n",
+      "Epoch 8: early stopping\n"
      ]
     }
    ],
@@ -541,7 +1041,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 103,
+   "execution_count": 120,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -571,7 +1071,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 104,
+   "execution_count": 121,
    "metadata": {},
    "outputs": [
     {
@@ -579,8 +1079,8 @@
      "output_type": "stream",
      "text": [
       "6/6 [==============================] - 0s 1ms/step\n",
-      "0.7849462365591398\n",
-      "0.9354838709677419\n",
+      "0.8225806451612904\n",
+      "0.9247311827956989\n",
       "0.946236559139785\n"
      ]
     }
@@ -600,15 +1100,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 108,
+   "execution_count": 122,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "6/6 [==============================] - 0s 799us/step\n",
-      "0.9247311827956989\n"
+      "6/6 [==============================] - 0s 798us/step\n",
+      "0.9193548387096774\n"
      ]
     }
    ],
@@ -641,7 +1141,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 123,
    "metadata": {},
    "outputs": [
     {
@@ -650,7 +1150,7 @@
        "' submission = pd.DataFrame()\\nprediction = model.predict(x_test)\\nsubmission.insert(0, \"Id\", id_number, False)\\nsubmission.insert(1, \"class_0\", [round(1-i[0],2) for i in prediction], True)\\nsubmission.insert(2, \"class_1\", [round(i[0],2) for i in prediction], True)\\nsubmission.to_csv(\"/kaggle/working/submission.csv\",index = False) '"
       ]
      },
-     "execution_count": 71,
+     "execution_count": 123,
      "metadata": {},
      "output_type": "execute_result"
     }