5 Model_training_per_recipe.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training prediction models (per recipe)\n",
    "\n",
    "Use pre-trained DenseNet121 model as backbone model.\n",
    "\n",
    "Add Imagenet preprocessing to the first layer\n",
    "\n",
    "Five models: calorie, calorie+ingredient, calorie+category, calorie+nutrient, calorie+3 vectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ast\n",
    "import pickle\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from tensorflow import config\n",
    "\n",
    "gpu_devices = config.experimental.list_physical_devices('GPU')\n",
    "\n",
    "for device in gpu_devices: config.experimental.set_memory_growth(device, True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "os.environ[\"CUDA_DEVICE_ORDER\"]=\"PCI_BUS_ID\"\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"]=\"0 2\""
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load preprocessed csv file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5422\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>title</th>\n",
       "      <th>image</th>\n",
       "      <th>ingredients</th>\n",
       "      <th>nutrients</th>\n",
       "      <th>file_name</th>\n",
       "      <th>category</th>\n",
       "      <th>serving</th>\n",
       "      <th>url</th>\n",
       "      <th>source</th>\n",
       "      <th>calorie</th>\n",
       "      <th>calorie_per_recipe</th>\n",
       "      <th>category_vector</th>\n",
       "      <th>parsed_ingredients</th>\n",
       "      <th>ingredient_vector</th>\n",
       "      <th>nutrient_vector</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Easy bread rolls</td>\n",
       "      <td>https://images.immediate.co.uk/production/vola...</td>\n",
       "      <td>['500g strong white bread flour , plus extra f...</td>\n",
       "      <td>{'calories': '246 calories', 'fatContent': '2 ...</td>\n",
       "      <td>bread0.jpg</td>\n",
       "      <td>bread</td>\n",
       "      <td>8.0</td>\n",
       "      <td>https://www.bbcgoodfood.com/recipes/Easy-bread...</td>\n",
       "      <td>bbc</td>\n",
       "      <td>246</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>[1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]</td>\n",
       "      <td>['bread flour', 'action yeast', 'caster sugar'...</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>[16.0, 384.0, 64.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Vegan banana bread</td>\n",
       "      <td>https://images.immediate.co.uk/production/vola...</td>\n",
       "      <td>['3 large black bananas', '75ml vegetable oil ...</td>\n",
       "      <td>{'calories': '218 calories', 'fatContent': '8 ...</td>\n",
       "      <td>bread1.jpg</td>\n",
       "      <td>bread</td>\n",
       "      <td>10.0</td>\n",
       "      <td>https://www.bbcgoodfood.com/recipes/Vegan-bana...</td>\n",
       "      <td>bbc</td>\n",
       "      <td>218</td>\n",
       "      <td>2180.0</td>\n",
       "      <td>[1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]</td>\n",
       "      <td>['black banana', 'sunflower oil', 'brown sugar...</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>[80.0, 330.0, 30.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Meatball &amp; garlic bread traybake</td>\n",
       "      <td>https://images.immediate.co.uk/production/vola...</td>\n",
       "      <td>['350g turkey thigh mince', '1 tsp dried orega...</td>\n",
       "      <td>{'calories': '565 calories', 'fatContent': '28...</td>\n",
       "      <td>bread2.jpg</td>\n",
       "      <td>bread</td>\n",
       "      <td>3.0</td>\n",
       "      <td>https://www.bbcgoodfood.com/recipes/Meatball-&amp;...</td>\n",
       "      <td>bbc</td>\n",
       "      <td>565</td>\n",
       "      <td>1695.0</td>\n",
       "      <td>[1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]</td>\n",
       "      <td>['thigh mince', 'tsp oregano', 'fennel seed', ...</td>\n",
       "      <td>[1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>[84.0, 102.0, 126.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Naan bread</td>\n",
       "      <td>https://images.immediate.co.uk/production/vola...</td>\n",
       "      <td>['1x 7g sachet dried yeast', '2 tsp golden cas...</td>\n",
       "      <td>{'calories': '224 calories', 'fatContent': '8 ...</td>\n",
       "      <td>bread3.jpg</td>\n",
       "      <td>bread</td>\n",
       "      <td>8.0</td>\n",
       "      <td>https://www.bbcgoodfood.com/recipes/Naan-bread</td>\n",
       "      <td>bbc</td>\n",
       "      <td>224</td>\n",
       "      <td>1792.0</td>\n",
       "      <td>[1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]</td>\n",
       "      <td>['sachet yeast', 'caster sugar', 'bread flour'...</td>\n",
       "      <td>[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>[64.0, 248.0, 48.0]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Pitta bread</td>\n",
       "      <td>https://images.immediate.co.uk/production/vola...</td>\n",
       "      <td>['2 tsp fast-action dried yeast', '500g strong...</td>\n",
       "      <td>{'calories': '246 calories', 'fatContent': '2 ...</td>\n",
       "      <td>bread4.jpg</td>\n",
       "      <td>bread</td>\n",
       "      <td>8.0</td>\n",
       "      <td>https://www.bbcgoodfood.com/recipes/Pitta-bread</td>\n",
       "      <td>bbc</td>\n",
       "      <td>246</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>[1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]</td>\n",
       "      <td>['fastaction yeast', 'bread flour', 'tsp salt'...</td>\n",
       "      <td>[1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...</td>\n",
       "      <td>[16.0, 376.0, 64.0]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                              title  \\\n",
       "0                  Easy bread rolls   \n",
       "1                Vegan banana bread   \n",
       "2  Meatball & garlic bread traybake   \n",
       "3                        Naan bread   \n",
       "4                       Pitta bread   \n",
       "\n",
       "                                               image  \\\n",
       "0  https://images.immediate.co.uk/production/vola...   \n",
       "1  https://images.immediate.co.uk/production/vola...   \n",
       "2  https://images.immediate.co.uk/production/vola...   \n",
       "3  https://images.immediate.co.uk/production/vola...   \n",
       "4  https://images.immediate.co.uk/production/vola...   \n",
       "\n",
       "                                         ingredients  \\\n",
       "0  ['500g strong white bread flour , plus extra f...   \n",
       "1  ['3 large black bananas', '75ml vegetable oil ...   \n",
       "2  ['350g turkey thigh mince', '1 tsp dried orega...   \n",
       "3  ['1x 7g sachet dried yeast', '2 tsp golden cas...   \n",
       "4  ['2 tsp fast-action dried yeast', '500g strong...   \n",
       "\n",
       "                                           nutrients   file_name category  \\\n",
       "0  {'calories': '246 calories', 'fatContent': '2 ...  bread0.jpg    bread   \n",
       "1  {'calories': '218 calories', 'fatContent': '8 ...  bread1.jpg    bread   \n",
       "2  {'calories': '565 calories', 'fatContent': '28...  bread2.jpg    bread   \n",
       "3  {'calories': '224 calories', 'fatContent': '8 ...  bread3.jpg    bread   \n",
       "4  {'calories': '246 calories', 'fatContent': '2 ...  bread4.jpg    bread   \n",
       "\n",
       "   serving                                                url source  calorie  \\\n",
       "0      8.0  https://www.bbcgoodfood.com/recipes/Easy-bread...    bbc      246   \n",
       "1     10.0  https://www.bbcgoodfood.com/recipes/Vegan-bana...    bbc      218   \n",
       "2      3.0  https://www.bbcgoodfood.com/recipes/Meatball-&...    bbc      565   \n",
       "3      8.0     https://www.bbcgoodfood.com/recipes/Naan-bread    bbc      224   \n",
       "4      8.0    https://www.bbcgoodfood.com/recipes/Pitta-bread    bbc      246   \n",
       "\n",
       "   calorie_per_recipe                       category_vector  \\\n",
       "0              1968.0  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]   \n",
       "1              2180.0  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]   \n",
       "2              1695.0  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]   \n",
       "3              1792.0  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]   \n",
       "4              1968.0  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]   \n",
       "\n",
       "                                  parsed_ingredients  \\\n",
       "0  ['bread flour', 'action yeast', 'caster sugar'...   \n",
       "1  ['black banana', 'sunflower oil', 'brown sugar...   \n",
       "2  ['thigh mince', 'tsp oregano', 'fennel seed', ...   \n",
       "3  ['sachet yeast', 'caster sugar', 'bread flour'...   \n",
       "4  ['fastaction yeast', 'bread flour', 'tsp salt'...   \n",
       "\n",
       "                                   ingredient_vector       nutrient_vector  \n",
       "0  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   [16.0, 384.0, 64.0]  \n",
       "1  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   [80.0, 330.0, 30.0]  \n",
       "2  [1, 1, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...  [84.0, 102.0, 126.0]  \n",
       "3  [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   [64.0, 248.0, 48.0]  \n",
       "4  [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ...   [16.0, 376.0, 64.0]  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "train_data = pd.read_csv('./data/train_per_recipe_complete.csv')\n",
    "\n",
    "# transform format from string to list \n",
    "train_data['category_vector'] = train_data['category_vector'].apply(ast.literal_eval)\n",
    "train_data['nutrient_vector'] = train_data['nutrient_vector'].apply(ast.literal_eval)\n",
    "train_data['ingredient_vector'] = train_data['ingredient_vector'].apply(ast.literal_eval)\n",
    "\n",
    "print(len(train_data))\n",
    "train_data.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Build network\n",
    "\n",
    "Add imagenet preprocessing as the first layer.\n",
    "\n",
    "use Densenet121 as the backbone model.\n",
    "\n",
    "define multi-outputs with corresponding activation functions to help improve the accurcy of calorie(y)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"model\"\n",
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            [(None, 256, 256, 3) 0                                            \n",
      "__________________________________________________________________________________________________\n",
      "tf_op_layer_Cast (TensorFlowOpL [(None, 256, 256, 3) 0           input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "tf_op_layer_truediv (TensorFlow [(None, 256, 256, 3) 0           tf_op_layer_Cast[0][0]           \n",
      "__________________________________________________________________________________________________\n",
      "tf_op_layer_BiasAdd (TensorFlow [(None, 256, 256, 3) 0           tf_op_layer_truediv[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "tf_op_layer_truediv_1 (TensorFl [(None, 256, 256, 3) 0           tf_op_layer_BiasAdd[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "densenet121 (Model)             multiple             7037504     tf_op_layer_truediv_1[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "global_average_pooling2d (Globa (None, 1024)         0           densenet121[1][0]                \n",
      "__________________________________________________________________________________________________\n",
      "dense (Dense)                   (None, 256)          262400      global_average_pooling2d[0][0]   \n",
      "__________________________________________________________________________________________________\n",
      "dropout (Dropout)               (None, 256)          0           dense[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "calorie (Dense)                 (None, 1)            257         dropout[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "category_vector (Dense)         (None, 12)           3084        dropout[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "nutrient_vector (Dense)         (None, 3)            771         dropout[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "ingredient_vector (Dense)       (None, 100)          25700       dropout[0][0]                    \n",
      "==================================================================================================\n",
      "Total params: 7,329,716\n",
      "Trainable params: 292,212\n",
      "Non-trainable params: 7,037,504\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "# do not mix tensorflow and keras...\n",
    "# https://stackoverflow.com/questions/51821537/attributeerror-node-object-has-no-attribute-output-masks\n",
    "\n",
    "\n",
    "import tensorflow as tf\n",
    "\n",
    "i = tf.keras.layers.Input([256, 256, 3], dtype = tf.uint8)\n",
    "x = tf.cast(i, tf.float32)\n",
    "x = tf.keras.applications.densenet.preprocess_input(x)\n",
    "core = tf.keras.applications.densenet.DenseNet121(weights='imagenet', include_top=False)\n",
    "\n",
    "x = core(x)\n",
    "x = tf.keras.layers.GlobalAveragePooling2D()(x)\n",
    "x = tf.keras.layers.Dense(256, activation='relu')(x)\n",
    "x = tf.keras.layers.Dropout(0.2)(x)\n",
    "y = tf.keras.layers.Dense(1, activation = \"relu\", name='calorie')(x)\n",
    "y1 = tf.keras.layers.Dense(12, activation = \"softmax\", name='category_vector')(x)\n",
    "y2 = tf.keras.layers.Dense(3, activation = \"relu\", name='nutrient_vector')(x)\n",
    "y3 = tf.keras.layers.Dense(100, activation = \"sigmoid\", name='ingredient_vector')(x)\n",
    "\n",
    "model = tf.keras.models.Model(inputs=[i], outputs=[y, y1, y2, y3])\n",
    "\n",
    "for l in model.layers:\n",
    "    l.trainable = False\n",
    "for l in model.layers[-7:]:\n",
    "    l.trainable = True\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "# calorie part model\n",
    "# cannot load_model... be careful with Lambda layer\n",
    "\n",
    "from keras.models import Model\n",
    "from keras.layers import Lambda, Dense, Input, Flatten, concatenate, GlobalAveragePooling2D\n",
    "from keras.applications.densenet import DenseNet121, preprocess_input\n",
    "\n",
    "inputs = Input(shape=(256, 256, 3))\n",
    "preprocess = Lambda(preprocess_input)(inputs)\n",
    "#preprocess = preprocess_input(inputs)\n",
    "\n",
    "base_model = DenseNet121(weights='imagenet', include_top=False, input_shape=(256, 256, 3))\n",
    "base_model = base_model(preprocess)\n",
    "#base_model.trainable = False\n",
    "\n",
    "x = GlobalAveragePooling2D()(base_model)\n",
    "x = Dense(128, activation='relu')(x)\n",
    "\n",
    "# use relu as activation to produce non-negative result\n",
    "nutrient_pred = Dense(1, activation = \"relu\", name='nutrients')(x)\n",
    "\n",
    "#out = concatenate([branchA, branchB])\n",
    "\n",
    "model = Model(inputs=inputs, outputs=nutrient_pred)\n",
    "\n",
    "for l in model.layers:\n",
    "    l.trainable = False\n",
    "for l in model.layers[-3:]:\n",
    "    l.trainable = True\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train multi-task models (per recipe)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 5. output: calorie + three vectors"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 4333 validated image filenames.\n",
      "Found 1083 validated image filenames.\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "\n",
    "datagen=ImageDataGenerator(\n",
    "    #rescale=1/255, \n",
    "    validation_split=0.2, \n",
    "    rotation_range=20,\n",
    "    width_shift_range=0.2,\n",
    "    height_shift_range=0.2,\n",
    "    horizontal_flip=True,\n",
    "    )\n",
    "\n",
    "train_generator = datagen.flow_from_dataframe(\n",
    "    dataframe=train_data,\n",
    "    directory='./data/train/',\n",
    "    target_size = (256,256),\n",
    "    x_col='file_name',\n",
    "    y_col= ['calorie_per_recipe', 'category_vector', 'nutrient_vector', 'ingredient_vector'],\n",
    "    batch_size=128,\n",
    "    shuffle=True,\n",
    "    subset='training',\n",
    "    class_mode='multi_output')\n",
    "\n",
    "valid_generator = datagen.flow_from_dataframe(\n",
    "    dataframe=train_data,\n",
    "    directory='./data/train/',\n",
    "    target_size = (256,256),\n",
    "    x_col='file_name',\n",
    "    y_col= ['calorie_per_recipe', 'category_vector', 'nutrient_vector', 'ingredient_vector'],\n",
    "    batch_size=128,\n",
    "    shuffle=True,\n",
    "    subset='validation',\n",
    "    class_mode='multi_output')\n",
    "    #validate_filenames=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-6-3612ca4b023f>:19: Model.fit_generator (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use Model.fit, which supports generators.\n",
      "Train for 34 steps, validate for 8 steps\n",
      "Epoch 1/100\n",
      "22/34 [==================>...........] - ETA: 31s - loss: 2372024.2784 - calorie_loss: 2359787.7500 - category_vector_loss: 4.8052 - nutrient_vector_loss: 12230.8447 - ingredient_vector_loss: 0.5777 - calorie_mse: 2358423.5000 - category_vector_mse: 0.1019 - nutrient_vector_mse: 12216.0215 - ingredient_vector_mse: 0.1403"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/uceezku/project/lib64/python3.6/site-packages/PIL/Image.py:963: UserWarning: Palette images with Transparency expressed in bytes should be converted to RGBA images\n",
      "  \"Palette images with Transparency expressed in bytes should be \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33/34 [============================>.] - ETA: 2s - loss: 2284408.3295 - calorie_loss: 2268710.2500 - category_vector_loss: 6.2619 - nutrient_vector_loss: 15690.9697 - ingredient_vector_loss: 0.5952 - calorie_mse: 2267391.2500 - category_vector_mse: 0.1094 - nutrient_vector_mse: 15696.7441 - ingredient_vector_mse: 0.1171\n",
      "Epoch 00001: val_calorie_loss improved from inf to 2528235.25000, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 104s 3s/step - loss: 2268644.2318 - calorie_loss: 2253274.0000 - category_vector_loss: 6.4079 - nutrient_vector_loss: 15401.6191 - ingredient_vector_loss: 0.5989 - calorie_mse: 2251926.0000 - category_vector_mse: 0.1099 - nutrient_vector_mse: 15405.9541 - ingredient_vector_mse: 0.1160 - val_loss: 2536606.8750 - val_calorie_loss: 2528235.2500 - val_category_vector_loss: 10.8528 - val_nutrient_vector_loss: 8360.1836 - val_ingredient_vector_loss: 0.4049 - val_calorie_mse: 2528235.2500 - val_category_vector_mse: 0.1302 - val_nutrient_vector_mse: 8360.1836 - val_ingredient_vector_mse: 0.0410\n",
      "Epoch 2/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 1507389.6402 - calorie_loss: 1496406.6250 - category_vector_loss: 16.4931 - nutrient_vector_loss: 10965.7207 - ingredient_vector_loss: 1.0103 - calorie_mse: 1495144.8750 - category_vector_mse: 0.1308 - nutrient_vector_mse: 10991.3877 - ingredient_vector_mse: 0.0815\n",
      "Epoch 00002: val_calorie_loss improved from 2528235.25000 to 1608023.62500, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 98s 3s/step - loss: 1497084.8853 - calorie_loss: 1486272.2500 - category_vector_loss: 16.6543 - nutrient_vector_loss: 10830.7930 - ingredient_vector_loss: 1.0181 - calorie_mse: 1485003.2500 - category_vector_mse: 0.1310 - nutrient_vector_mse: 10855.1104 - ingredient_vector_mse: 0.0814 - val_loss: 1614609.1250 - val_calorie_loss: 1608023.6250 - val_category_vector_loss: 18.2135 - val_nutrient_vector_loss: 6566.6250 - val_ingredient_vector_loss: 0.7329 - val_calorie_mse: 1608023.6250 - val_category_vector_mse: 0.1602 - val_nutrient_vector_mse: 6566.6250 - val_ingredient_vector_mse: 0.0411\n",
      "Epoch 3/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 779985.0246 - calorie_loss: 769362.5625 - category_vector_loss: 24.2235 - nutrient_vector_loss: 10596.8145 - ingredient_vector_loss: 1.5069 - calorie_mse: 770286.3750 - category_vector_mse: 0.1338 - nutrient_vector_mse: 10621.2842 - ingredient_vector_mse: 0.0857\n",
      "Epoch 00003: val_calorie_loss improved from 1608023.62500 to 925573.25000, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 98s 3s/step - loss: 780058.2334 - calorie_loss: 769527.0625 - category_vector_loss: 24.2693 - nutrient_vector_loss: 10479.1357 - ingredient_vector_loss: 1.5136 - calorie_mse: 770424.3125 - category_vector_mse: 0.1340 - nutrient_vector_mse: 10502.3682 - ingredient_vector_mse: 0.0857 - val_loss: 932285.7109 - val_calorie_loss: 925573.2500 - val_category_vector_loss: 22.5011 - val_nutrient_vector_loss: 6689.0991 - val_ingredient_vector_loss: 0.9177 - val_calorie_mse: 925573.2500 - val_category_vector_mse: 0.1198 - val_nutrient_vector_mse: 6689.0991 - val_ingredient_vector_mse: 0.0416\n",
      "Epoch 4/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 564569.4744 - calorie_loss: 553870.1250 - category_vector_loss: 27.2169 - nutrient_vector_loss: 10670.3887 - ingredient_vector_loss: 1.6953 - calorie_mse: 554054.0625 - category_vector_mse: 0.1358 - nutrient_vector_mse: 10693.3945 - ingredient_vector_mse: 0.0861\n",
      "Epoch 00004: val_calorie_loss improved from 925573.25000 to 727975.75000, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 97s 3s/step - loss: 564323.1116 - calorie_loss: 553764.6250 - category_vector_loss: 27.1862 - nutrient_vector_loss: 10523.8438 - ingredient_vector_loss: 1.6950 - calorie_mse: 553942.6875 - category_vector_mse: 0.1359 - nutrient_vector_mse: 10545.5273 - ingredient_vector_mse: 0.0861 - val_loss: 734607.4062 - val_calorie_loss: 727975.7500 - val_category_vector_loss: 25.5345 - val_nutrient_vector_loss: 6605.2407 - val_ingredient_vector_loss: 0.9432 - val_calorie_mse: 727975.7500 - val_category_vector_mse: 0.1608 - val_nutrient_vector_mse: 6605.2407 - val_ingredient_vector_mse: 0.0405\n",
      "Epoch 5/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 555278.0095 - calorie_loss: 544473.7500 - category_vector_loss: 25.8293 - nutrient_vector_loss: 10776.7930 - ingredient_vector_loss: 1.6104 - calorie_mse: 544897.3125 - category_vector_mse: 0.1358 - nutrient_vector_mse: 10802.1318 - ingredient_vector_mse: 0.0858\n",
      "Epoch 00005: val_calorie_loss did not improve from 727975.75000\n",
      "34/34 [==============================] - 99s 3s/step - loss: 554777.9794 - calorie_loss: 544117.5000 - category_vector_loss: 25.8292 - nutrient_vector_loss: 10620.6260 - ingredient_vector_loss: 1.6053 - calorie_mse: 544527.0000 - category_vector_mse: 0.1358 - nutrient_vector_mse: 10644.5312 - ingredient_vector_mse: 0.0857 - val_loss: 739010.8203 - val_calorie_loss: 731942.2500 - val_category_vector_loss: 22.3490 - val_nutrient_vector_loss: 7045.3384 - val_ingredient_vector_loss: 0.8845 - val_calorie_mse: 731942.2500 - val_category_vector_mse: 0.1665 - val_nutrient_vector_mse: 7045.3384 - val_ingredient_vector_mse: 0.0417\n",
      "Epoch 6/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 552035.5445 - calorie_loss: 541339.5625 - category_vector_loss: 22.9962 - nutrient_vector_loss: 10671.5781 - ingredient_vector_loss: 1.4505 - calorie_mse: 541760.5625 - category_vector_mse: 0.1339 - nutrient_vector_mse: 10694.2227 - ingredient_vector_mse: 0.0848\n",
      "Epoch 00006: val_calorie_loss improved from 727975.75000 to 727681.50000, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 99s 3s/step - loss: 548940.3844 - calorie_loss: 538398.3125 - category_vector_loss: 22.9851 - nutrient_vector_loss: 10505.8076 - ingredient_vector_loss: 1.4500 - calorie_mse: 538793.9375 - category_vector_mse: 0.1338 - nutrient_vector_mse: 10527.0576 - ingredient_vector_mse: 0.0848 - val_loss: 734676.7031 - val_calorie_loss: 727681.5000 - val_category_vector_loss: 26.8567 - val_nutrient_vector_loss: 6967.5356 - val_ingredient_vector_loss: 0.7999 - val_calorie_mse: 727681.5000 - val_category_vector_mse: 0.1665 - val_nutrient_vector_mse: 6967.5356 - val_ingredient_vector_mse: 0.0404\n",
      "Epoch 7/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 543137.7273 - calorie_loss: 532572.5000 - category_vector_loss: 20.7182 - nutrient_vector_loss: 10543.2451 - ingredient_vector_loss: 1.2896 - calorie_mse: 532940.7500 - category_vector_mse: 0.1340 - nutrient_vector_mse: 10567.5039 - ingredient_vector_mse: 0.0837\n",
      "Epoch 00007: val_calorie_loss did not improve from 727681.50000\n",
      "34/34 [==============================] - 99s 3s/step - loss: 544902.8572 - calorie_loss: 534459.8125 - category_vector_loss: 20.6099 - nutrient_vector_loss: 10410.0361 - ingredient_vector_loss: 1.2875 - calorie_mse: 534825.5000 - category_vector_mse: 0.1340 - nutrient_vector_mse: 10432.9932 - ingredient_vector_mse: 0.0837 - val_loss: 740865.5938 - val_calorie_loss: 733678.3750 - val_category_vector_loss: 22.1468 - val_nutrient_vector_loss: 7164.3564 - val_ingredient_vector_loss: 0.7399 - val_calorie_mse: 733678.3750 - val_category_vector_mse: 0.1563 - val_nutrient_vector_mse: 7164.3564 - val_ingredient_vector_mse: 0.0405\n",
      "Epoch 8/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 549096.6714 - calorie_loss: 538540.1875 - category_vector_loss: 19.0899 - nutrient_vector_loss: 10536.2012 - ingredient_vector_loss: 1.1770 - calorie_mse: 538931.0000 - category_vector_mse: 0.1327 - nutrient_vector_mse: 10560.5146 - ingredient_vector_mse: 0.0835\n",
      "Epoch 00008: val_calorie_loss improved from 727681.50000 to 714919.87500, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 99s 3s/step - loss: 547277.1919 - calorie_loss: 536859.7500 - category_vector_loss: 19.0567 - nutrient_vector_loss: 10385.8896 - ingredient_vector_loss: 1.1732 - calorie_mse: 537231.6875 - category_vector_mse: 0.1327 - nutrient_vector_mse: 10408.8262 - ingredient_vector_mse: 0.0834 - val_loss: 721613.1641 - val_calorie_loss: 714919.8750 - val_category_vector_loss: 23.2529 - val_nutrient_vector_loss: 6669.4126 - val_ingredient_vector_loss: 0.6591 - val_calorie_mse: 714919.8750 - val_category_vector_mse: 0.1663 - val_nutrient_vector_mse: 6669.4126 - val_ingredient_vector_mse: 0.0408\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 9/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 548451.4157 - calorie_loss: 538012.0000 - category_vector_loss: 16.9036 - nutrient_vector_loss: 10421.4395 - ingredient_vector_loss: 1.0486 - calorie_mse: 538393.2500 - category_vector_mse: 0.1302 - nutrient_vector_mse: 10443.6113 - ingredient_vector_mse: 0.0819\n",
      "Epoch 00009: val_calorie_loss improved from 714919.87500 to 708325.37500, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 97s 3s/step - loss: 548903.8713 - calorie_loss: 538607.1875 - category_vector_loss: 16.8865 - nutrient_vector_loss: 10267.5117 - ingredient_vector_loss: 1.0474 - calorie_mse: 538979.8125 - category_vector_mse: 0.1301 - nutrient_vector_mse: 10288.3535 - ingredient_vector_mse: 0.0819 - val_loss: 714981.4297 - val_calorie_loss: 708325.3750 - val_category_vector_loss: 24.2329 - val_nutrient_vector_loss: 6631.2622 - val_ingredient_vector_loss: 0.6254 - val_calorie_mse: 708325.3750 - val_category_vector_mse: 0.1420 - val_nutrient_vector_mse: 6631.2622 - val_ingredient_vector_mse: 0.0405\n",
      "Epoch 10/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 543604.5019 - calorie_loss: 533192.1250 - category_vector_loss: 14.9425 - nutrient_vector_loss: 10396.4531 - ingredient_vector_loss: 0.9292 - calorie_mse: 533609.6250 - category_vector_mse: 0.1269 - nutrient_vector_mse: 10420.9336 - ingredient_vector_mse: 0.0796\n",
      "Epoch 00010: val_calorie_loss improved from 708325.37500 to 702655.43750, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 542010.9750 - calorie_loss: 531727.1875 - category_vector_loss: 14.9343 - nutrient_vector_loss: 10255.8066 - ingredient_vector_loss: 0.9264 - calorie_mse: 532125.9375 - category_vector_mse: 0.1272 - nutrient_vector_mse: 10278.9463 - ingredient_vector_mse: 0.0796 - val_loss: 709439.3594 - val_calorie_loss: 702655.4375 - val_category_vector_loss: 23.0727 - val_nutrient_vector_loss: 6760.2598 - val_ingredient_vector_loss: 0.5605 - val_calorie_mse: 702655.4375 - val_category_vector_mse: 0.1399 - val_nutrient_vector_mse: 6760.2598 - val_ingredient_vector_mse: 0.0406\n",
      "Epoch 11/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 549051.2566 - calorie_loss: 538625.3125 - category_vector_loss: 12.9329 - nutrient_vector_loss: 10412.2012 - ingredient_vector_loss: 0.8110 - calorie_mse: 539047.7500 - category_vector_mse: 0.1255 - nutrient_vector_mse: 10437.3916 - ingredient_vector_mse: 0.0771\n",
      "Epoch 00011: val_calorie_loss improved from 702655.43750 to 699000.50000, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 547611.0791 - calorie_loss: 537340.5625 - category_vector_loss: 12.9540 - nutrient_vector_loss: 10244.4893 - ingredient_vector_loss: 0.8102 - calorie_mse: 537744.8750 - category_vector_mse: 0.1258 - nutrient_vector_mse: 10268.2002 - ingredient_vector_mse: 0.0772 - val_loss: 705772.3438 - val_calorie_loss: 699000.5000 - val_category_vector_loss: 18.3554 - val_nutrient_vector_loss: 6752.9980 - val_ingredient_vector_loss: 0.4889 - val_calorie_mse: 699000.5000 - val_category_vector_mse: 0.1305 - val_nutrient_vector_mse: 6752.9980 - val_ingredient_vector_mse: 0.0396\n",
      "Epoch 12/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 538307.3873 - calorie_loss: 527993.6875 - category_vector_loss: 11.3423 - nutrient_vector_loss: 10301.5879 - ingredient_vector_loss: 0.7190 - calorie_mse: 528395.3125 - category_vector_mse: 0.1242 - nutrient_vector_mse: 10325.5273 - ingredient_vector_mse: 0.0746\n",
      "Epoch 00012: val_calorie_loss improved from 699000.50000 to 690163.37500, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 538356.5316 - calorie_loss: 528181.3125 - category_vector_loss: 11.3024 - nutrient_vector_loss: 10151.3926 - ingredient_vector_loss: 0.7197 - calorie_mse: 528571.8750 - category_vector_mse: 0.1240 - nutrient_vector_mse: 10173.9658 - ingredient_vector_mse: 0.0746 - val_loss: 697055.1953 - val_calorie_loss: 690163.3750 - val_category_vector_loss: 22.2712 - val_nutrient_vector_loss: 6869.1099 - val_ingredient_vector_loss: 0.4578 - val_calorie_mse: 690163.3750 - val_category_vector_mse: 0.1364 - val_nutrient_vector_mse: 6869.1099 - val_ingredient_vector_mse: 0.0411\n",
      "Epoch 13/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 543508.9025 - calorie_loss: 533111.0000 - category_vector_loss: 9.8523 - nutrient_vector_loss: 10387.4355 - ingredient_vector_loss: 0.6236 - calorie_mse: 533540.5625 - category_vector_mse: 0.1183 - nutrient_vector_mse: 10411.9268 - ingredient_vector_mse: 0.0718\n",
      "Epoch 00013: val_calorie_loss improved from 690163.37500 to 678392.81250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 543658.1275 - calorie_loss: 533405.2500 - category_vector_loss: 9.7957 - nutrient_vector_loss: 10229.8672 - ingredient_vector_loss: 0.6230 - calorie_mse: 533823.4375 - category_vector_mse: 0.1184 - nutrient_vector_mse: 10252.9443 - ingredient_vector_mse: 0.0717 - val_loss: 684912.9062 - val_calorie_loss: 678392.8125 - val_category_vector_loss: 18.9271 - val_nutrient_vector_loss: 6500.7471 - val_ingredient_vector_loss: 0.4131 - val_calorie_mse: 678392.8125 - val_category_vector_mse: 0.1016 - val_nutrient_vector_mse: 6500.7471 - val_ingredient_vector_mse: 0.0432\n",
      "Epoch 14/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 536908.8646 - calorie_loss: 526649.9375 - category_vector_loss: 8.5847 - nutrient_vector_loss: 10249.7783 - ingredient_vector_loss: 0.5456 - calorie_mse: 527105.6250 - category_vector_mse: 0.1147 - nutrient_vector_mse: 10273.7695 - ingredient_vector_mse: 0.0685\n",
      "Epoch 00014: val_calorie_loss improved from 678392.81250 to 669882.12500, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 536290.6127 - calorie_loss: 526160.8750 - category_vector_loss: 8.5864 - nutrient_vector_loss: 10107.3877 - ingredient_vector_loss: 0.5453 - calorie_mse: 526601.0000 - category_vector_mse: 0.1147 - nutrient_vector_mse: 10130.0459 - ingredient_vector_mse: 0.0687 - val_loss: 676453.9844 - val_calorie_loss: 669882.1250 - val_category_vector_loss: 17.1576 - val_nutrient_vector_loss: 6554.2871 - val_ingredient_vector_loss: 0.3708 - val_calorie_mse: 669882.1250 - val_category_vector_mse: 0.1189 - val_nutrient_vector_mse: 6554.2871 - val_ingredient_vector_mse: 0.0442\n",
      "Epoch 15/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 535018.1127 - calorie_loss: 524700.8125 - category_vector_loss: 7.1174 - nutrient_vector_loss: 10309.6914 - ingredient_vector_loss: 0.4780 - calorie_mse: 525075.9375 - category_vector_mse: 0.1075 - nutrient_vector_mse: 10333.4150 - ingredient_vector_mse: 0.0652\n",
      "Epoch 00015: val_calorie_loss improved from 669882.12500 to 666762.87500, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 533564.4702 - calorie_loss: 523411.6562 - category_vector_loss: 7.0947 - nutrient_vector_loss: 10134.3594 - ingredient_vector_loss: 0.4774 - calorie_mse: 523770.0938 - category_vector_mse: 0.1076 - nutrient_vector_mse: 10156.6143 - ingredient_vector_mse: 0.0652 - val_loss: 673208.6953 - val_calorie_loss: 666762.8750 - val_category_vector_loss: 17.9693 - val_nutrient_vector_loss: 6427.5303 - val_ingredient_vector_loss: 0.3285 - val_calorie_mse: 666762.8750 - val_category_vector_mse: 0.1130 - val_nutrient_vector_mse: 6427.5303 - val_ingredient_vector_mse: 0.0411\n",
      "Epoch 16/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 533036.8220 - calorie_loss: 522770.8438 - category_vector_loss: 6.1919 - nutrient_vector_loss: 10259.3994 - ingredient_vector_loss: 0.4198 - calorie_mse: 523155.6875 - category_vector_mse: 0.1022 - nutrient_vector_mse: 10283.3379 - ingredient_vector_mse: 0.0624\n",
      "Epoch 00016: val_calorie_loss did not improve from 666762.87500\n",
      "34/34 [==============================] - 90s 3s/step - loss: 534653.4794 - calorie_loss: 524524.4375 - category_vector_loss: 6.2082 - nutrient_vector_loss: 10110.9199 - ingredient_vector_loss: 0.4185 - calorie_mse: 524905.5625 - category_vector_mse: 0.1021 - nutrient_vector_mse: 10133.5000 - ingredient_vector_mse: 0.0623 - val_loss: 676563.6172 - val_calorie_loss: 670286.6250 - val_category_vector_loss: 15.8350 - val_nutrient_vector_loss: 6260.8545 - val_ingredient_vector_loss: 0.3075 - val_calorie_mse: 670286.6250 - val_category_vector_mse: 0.0975 - val_nutrient_vector_mse: 6260.8545 - val_ingredient_vector_mse: 0.0428\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 17/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 534622.2027 - calorie_loss: 524435.0000 - category_vector_loss: 5.4188 - nutrient_vector_loss: 10181.3740 - ingredient_vector_loss: 0.3677 - calorie_mse: 524789.6250 - category_vector_mse: 0.0975 - nutrient_vector_mse: 10205.6758 - ingredient_vector_mse: 0.0595\n",
      "Epoch 00017: val_calorie_loss improved from 666762.87500 to 653464.62500, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 535751.8141 - calorie_loss: 525694.2500 - category_vector_loss: 5.4030 - nutrient_vector_loss: 10041.1299 - ingredient_vector_loss: 0.3671 - calorie_mse: 526043.8750 - category_vector_mse: 0.0974 - nutrient_vector_mse: 10064.0986 - ingredient_vector_mse: 0.0595 - val_loss: 659583.8516 - val_calorie_loss: 653464.6250 - val_category_vector_loss: 15.1773 - val_nutrient_vector_loss: 6103.8203 - val_ingredient_vector_loss: 0.2839 - val_calorie_mse: 653464.6250 - val_category_vector_mse: 0.0965 - val_nutrient_vector_mse: 6103.8203 - val_ingredient_vector_mse: 0.0425\n",
      "Epoch 18/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 529250.5028 - calorie_loss: 519088.0000 - category_vector_loss: 4.6742 - nutrient_vector_loss: 10157.4961 - ingredient_vector_loss: 0.3348 - calorie_mse: 519579.3750 - category_vector_mse: 0.0927 - nutrient_vector_mse: 10182.0596 - ingredient_vector_mse: 0.0579\n",
      "Epoch 00018: val_calorie_loss improved from 653464.62500 to 651522.06250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 530829.1427 - calorie_loss: 520798.4688 - category_vector_loss: 4.6835 - nutrient_vector_loss: 10011.1670 - ingredient_vector_loss: 0.3336 - calorie_mse: 521282.8125 - category_vector_mse: 0.0925 - nutrient_vector_mse: 10034.3633 - ingredient_vector_mse: 0.0578 - val_loss: 657643.7266 - val_calorie_loss: 651522.0625 - val_category_vector_loss: 14.4440 - val_nutrient_vector_loss: 6107.0098 - val_ingredient_vector_loss: 0.2584 - val_calorie_mse: 651522.0625 - val_category_vector_mse: 0.1033 - val_nutrient_vector_mse: 6107.0098 - val_ingredient_vector_mse: 0.0415\n",
      "Epoch 19/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 527237.6335 - calorie_loss: 517136.7188 - category_vector_loss: 4.2785 - nutrient_vector_loss: 10096.2871 - ingredient_vector_loss: 0.3069 - calorie_mse: 517520.7812 - category_vector_mse: 0.0891 - nutrient_vector_mse: 10120.2607 - ingredient_vector_mse: 0.0559\n",
      "Epoch 00019: val_calorie_loss improved from 651522.06250 to 646425.43750, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 526562.9609 - calorie_loss: 516607.7188 - category_vector_loss: 4.2720 - nutrient_vector_loss: 9939.4268 - ingredient_vector_loss: 0.3064 - calorie_mse: 516978.0938 - category_vector_mse: 0.0890 - nutrient_vector_mse: 9962.0039 - ingredient_vector_mse: 0.0559 - val_loss: 652629.2031 - val_calorie_loss: 646425.4375 - val_category_vector_loss: 12.8877 - val_nutrient_vector_loss: 6190.6416 - val_ingredient_vector_loss: 0.2479 - val_calorie_mse: 646425.4375 - val_category_vector_mse: 0.1057 - val_nutrient_vector_mse: 6190.6416 - val_ingredient_vector_mse: 0.0457\n",
      "Epoch 20/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 525876.3958 - calorie_loss: 515759.3438 - category_vector_loss: 3.8981 - nutrient_vector_loss: 10112.9521 - ingredient_vector_loss: 0.2772 - calorie_mse: 516146.6562 - category_vector_mse: 0.0879 - nutrient_vector_mse: 10138.2646 - ingredient_vector_mse: 0.0541\n",
      "Epoch 00020: val_calorie_loss improved from 646425.43750 to 631560.06250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 526229.6101 - calorie_loss: 516228.1875 - category_vector_loss: 3.8939 - nutrient_vector_loss: 9985.8369 - ingredient_vector_loss: 0.2772 - calorie_mse: 516606.1250 - category_vector_mse: 0.0877 - nutrient_vector_mse: 10009.8457 - ingredient_vector_mse: 0.0541 - val_loss: 637689.0625 - val_calorie_loss: 631560.0625 - val_category_vector_loss: 11.0617 - val_nutrient_vector_loss: 6117.7080 - val_ingredient_vector_loss: 0.2203 - val_calorie_mse: 631560.0625 - val_category_vector_mse: 0.0832 - val_nutrient_vector_mse: 6117.7080 - val_ingredient_vector_mse: 0.0392\n",
      "Epoch 21/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 526235.2396 - calorie_loss: 516184.7188 - category_vector_loss: 3.5623 - nutrient_vector_loss: 10046.6348 - ingredient_vector_loss: 0.2557 - calorie_mse: 516621.2188 - category_vector_mse: 0.0855 - nutrient_vector_mse: 10071.5078 - ingredient_vector_mse: 0.0523\n",
      "Epoch 00021: val_calorie_loss improved from 631560.06250 to 628219.81250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 525254.1406 - calorie_loss: 515338.9375 - category_vector_loss: 3.5705 - nutrient_vector_loss: 9898.6484 - ingredient_vector_loss: 0.2556 - calorie_mse: 515758.8125 - category_vector_mse: 0.0854 - nutrient_vector_mse: 9922.1387 - ingredient_vector_mse: 0.0523 - val_loss: 634192.7734 - val_calorie_loss: 628219.8125 - val_category_vector_loss: 11.1922 - val_nutrient_vector_loss: 5961.5244 - val_ingredient_vector_loss: 0.2166 - val_calorie_mse: 628219.8125 - val_category_vector_mse: 0.0908 - val_nutrient_vector_mse: 5961.5244 - val_ingredient_vector_mse: 0.0417\n",
      "Epoch 22/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 521989.8400 - calorie_loss: 511848.3750 - category_vector_loss: 3.2604 - nutrient_vector_loss: 10137.9492 - ingredient_vector_loss: 0.2405 - calorie_mse: 512228.9062 - category_vector_mse: 0.0815 - nutrient_vector_mse: 10162.7188 - ingredient_vector_mse: 0.0513\n",
      "Epoch 00022: val_calorie_loss did not improve from 628219.81250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 522858.4901 - calorie_loss: 512854.0625 - category_vector_loss: 3.2542 - nutrient_vector_loss: 9989.5889 - ingredient_vector_loss: 0.2402 - calorie_mse: 513227.7812 - category_vector_mse: 0.0814 - nutrient_vector_mse: 10012.9766 - ingredient_vector_mse: 0.0513 - val_loss: 634333.5000 - val_calorie_loss: 628349.5000 - val_category_vector_loss: 10.0899 - val_nutrient_vector_loss: 5973.7637 - val_ingredient_vector_loss: 0.2146 - val_calorie_mse: 628349.5000 - val_category_vector_mse: 0.0872 - val_nutrient_vector_mse: 5973.7637 - val_ingredient_vector_mse: 0.0421\n",
      "Epoch 23/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 519852.3059 - calorie_loss: 509862.0625 - category_vector_loss: 3.0292 - nutrient_vector_loss: 9986.9834 - ingredient_vector_loss: 0.2299 - calorie_mse: 510320.5625 - category_vector_mse: 0.0795 - nutrient_vector_mse: 10011.4355 - ingredient_vector_mse: 0.0505 \n",
      "Epoch 00023: val_calorie_loss improved from 628219.81250 to 614392.56250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 519550.1788 - calorie_loss: 509648.8750 - category_vector_loss: 3.0577 - nutrient_vector_loss: 9884.6289 - ingredient_vector_loss: 0.2299 - calorie_mse: 510092.9062 - category_vector_mse: 0.0796 - nutrient_vector_mse: 9907.9102 - ingredient_vector_mse: 0.0505 - val_loss: 620423.4648 - val_calorie_loss: 614392.5625 - val_category_vector_loss: 10.1801 - val_nutrient_vector_loss: 6020.5674 - val_ingredient_vector_loss: 0.1950 - val_calorie_mse: 614392.5625 - val_category_vector_mse: 0.0955 - val_nutrient_vector_mse: 6020.5674 - val_ingredient_vector_mse: 0.0413\n",
      "Epoch 24/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 523483.4498 - calorie_loss: 513355.8750 - category_vector_loss: 2.9712 - nutrient_vector_loss: 10124.4316 - ingredient_vector_loss: 0.2222 - calorie_mse: 513744.6250 - category_vector_mse: 0.0790 - nutrient_vector_mse: 10149.7363 - ingredient_vector_mse: 0.0498\n",
      "Epoch 00024: val_calorie_loss did not improve from 614392.56250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 521217.1039 - calorie_loss: 511245.2812 - category_vector_loss: 2.9769 - nutrient_vector_loss: 9957.4688 - ingredient_vector_loss: 0.2221 - calorie_mse: 511613.3125 - category_vector_mse: 0.0790 - nutrient_vector_mse: 9981.2930 - ingredient_vector_mse: 0.0497 - val_loss: 622504.8906 - val_calorie_loss: 616434.4375 - val_category_vector_loss: 9.7186 - val_nutrient_vector_loss: 6060.5312 - val_ingredient_vector_loss: 0.1923 - val_calorie_mse: 616434.4375 - val_category_vector_mse: 0.0851 - val_nutrient_vector_mse: 6060.5312 - val_ingredient_vector_mse: 0.0402\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 25/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 520521.2689 - calorie_loss: 510511.5625 - category_vector_loss: 2.7581 - nutrient_vector_loss: 10006.7627 - ingredient_vector_loss: 0.2166 - calorie_mse: 510966.8750 - category_vector_mse: 0.0767 - nutrient_vector_mse: 10030.7520 - ingredient_vector_mse: 0.0491\n",
      "Epoch 00025: val_calorie_loss improved from 614392.56250 to 607373.25000, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 520375.9261 - calorie_loss: 510494.8750 - category_vector_loss: 2.7658 - nutrient_vector_loss: 9864.8164 - ingredient_vector_loss: 0.2167 - calorie_mse: 510936.6562 - category_vector_mse: 0.0767 - nutrient_vector_mse: 9887.4746 - ingredient_vector_mse: 0.0491 - val_loss: 613568.0078 - val_calorie_loss: 607373.2500 - val_category_vector_loss: 10.8307 - val_nutrient_vector_loss: 6183.7637 - val_ingredient_vector_loss: 0.1955 - val_calorie_mse: 607373.2500 - val_category_vector_mse: 0.0892 - val_nutrient_vector_mse: 6183.7637 - val_ingredient_vector_mse: 0.0431\n",
      "Epoch 26/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 517030.3106 - calorie_loss: 507089.7188 - category_vector_loss: 2.7029 - nutrient_vector_loss: 9937.6895 - ingredient_vector_loss: 0.2136 - calorie_mse: 507544.5938 - category_vector_mse: 0.0756 - nutrient_vector_mse: 9962.2773 - ingredient_vector_mse: 0.0488  \n",
      "Epoch 00026: val_calorie_loss improved from 607373.25000 to 597183.37500, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 517284.6797 - calorie_loss: 507441.3438 - category_vector_loss: 2.6905 - nutrient_vector_loss: 9827.1357 - ingredient_vector_loss: 0.2134 - calorie_mse: 507884.3125 - category_vector_mse: 0.0755 - nutrient_vector_mse: 9850.5127 - ingredient_vector_mse: 0.0488 - val_loss: 603358.5352 - val_calorie_loss: 597183.3750 - val_category_vector_loss: 10.0025 - val_nutrient_vector_loss: 6164.9756 - val_ingredient_vector_loss: 0.1944 - val_calorie_mse: 597183.3750 - val_category_vector_mse: 0.0833 - val_nutrient_vector_mse: 6164.9756 - val_ingredient_vector_mse: 0.0433\n",
      "Epoch 27/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 516993.3267 - calorie_loss: 507046.4688 - category_vector_loss: 2.7380 - nutrient_vector_loss: 9943.9463 - ingredient_vector_loss: 0.2073 - calorie_mse: 507536.4375 - category_vector_mse: 0.0785 - nutrient_vector_mse: 9968.7217 - ingredient_vector_mse: 0.0480  \n",
      "Epoch 00027: val_calorie_loss improved from 597183.37500 to 592245.06250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 518007.7546 - calorie_loss: 508149.0625 - category_vector_loss: 2.7299 - nutrient_vector_loss: 9841.3730 - ingredient_vector_loss: 0.2074 - calorie_mse: 508629.4062 - category_vector_mse: 0.0785 - nutrient_vector_mse: 9864.9678 - ingredient_vector_mse: 0.0480 - val_loss: 598243.8281 - val_calorie_loss: 592245.0625 - val_category_vector_loss: 8.9785 - val_nutrient_vector_loss: 5989.6113 - val_ingredient_vector_loss: 0.1968 - val_calorie_mse: 592245.0625 - val_category_vector_mse: 0.0774 - val_nutrient_vector_mse: 5989.6113 - val_ingredient_vector_mse: 0.0433\n",
      "Epoch 28/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 517371.3939 - calorie_loss: 507341.3438 - category_vector_loss: 2.6518 - nutrient_vector_loss: 10027.1768 - ingredient_vector_loss: 0.2077 - calorie_mse: 507872.8438 - category_vector_mse: 0.0767 - nutrient_vector_mse: 10052.2109 - ingredient_vector_mse: 0.0483\n",
      "Epoch 00028: val_calorie_loss improved from 592245.06250 to 578552.31250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 517922.6535 - calorie_loss: 508008.4062 - category_vector_loss: 2.6598 - nutrient_vector_loss: 9895.8809 - ingredient_vector_loss: 0.2077 - calorie_mse: 508527.1250 - category_vector_mse: 0.0767 - nutrient_vector_mse: 9919.5996 - ingredient_vector_mse: 0.0483 - val_loss: 584613.6562 - val_calorie_loss: 578552.3125 - val_category_vector_loss: 8.9072 - val_nutrient_vector_loss: 6052.2588 - val_ingredient_vector_loss: 0.1899 - val_calorie_mse: 578552.3125 - val_category_vector_mse: 0.0988 - val_nutrient_vector_mse: 6052.2588 - val_ingredient_vector_mse: 0.0428\n",
      "Epoch 29/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 512921.4375 - calorie_loss: 502913.8125 - category_vector_loss: 2.5944 - nutrient_vector_loss: 10004.8252 - ingredient_vector_loss: 0.2069 - calorie_mse: 503455.7500 - category_vector_mse: 0.0764 - nutrient_vector_mse: 10029.8535 - ingredient_vector_mse: 0.0479\n",
      "Epoch 00029: val_calorie_loss did not improve from 578552.31250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 510931.8314 - calorie_loss: 501061.0000 - category_vector_loss: 2.5921 - nutrient_vector_loss: 9852.5986 - ingredient_vector_loss: 0.2066 - calorie_mse: 501578.8125 - category_vector_mse: 0.0764 - nutrient_vector_mse: 9876.2207 - ingredient_vector_mse: 0.0479 - val_loss: 588590.2852 - val_calorie_loss: 582596.1875 - val_category_vector_loss: 8.7902 - val_nutrient_vector_loss: 5985.0488 - val_ingredient_vector_loss: 0.1993 - val_calorie_mse: 582596.1875 - val_category_vector_mse: 0.0922 - val_nutrient_vector_mse: 5985.0488 - val_ingredient_vector_mse: 0.0445\n",
      "Epoch 30/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 517266.3712 - calorie_loss: 507249.8125 - category_vector_loss: 2.5506 - nutrient_vector_loss: 10013.8281 - ingredient_vector_loss: 0.2033 - calorie_mse: 507249.8125 - category_vector_mse: 0.0751 - nutrient_vector_mse: 10013.8281 - ingredient_vector_mse: 0.0476\n",
      "Epoch 00030: val_calorie_loss improved from 578552.31250 to 569395.43750, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 513913.6012 - calorie_loss: 504049.1250 - category_vector_loss: 2.5430 - nutrient_vector_loss: 9847.8545 - ingredient_vector_loss: 0.2035 - calorie_mse: 504512.2500 - category_vector_mse: 0.0750 - nutrient_vector_mse: 9871.8721 - ingredient_vector_mse: 0.0476 - val_loss: 575237.9883 - val_calorie_loss: 569395.4375 - val_category_vector_loss: 8.8427 - val_nutrient_vector_loss: 5833.5518 - val_ingredient_vector_loss: 0.1860 - val_calorie_mse: 569395.4375 - val_category_vector_mse: 0.0910 - val_nutrient_vector_mse: 5833.5518 - val_ingredient_vector_mse: 0.0421\n",
      "Epoch 31/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 510321.6676 - calorie_loss: 500385.7812 - category_vector_loss: 2.6318 - nutrient_vector_loss: 9933.0947 - ingredient_vector_loss: 0.2031 - calorie_mse: 500809.1250 - category_vector_mse: 0.0763 - nutrient_vector_mse: 9958.1572 - ingredient_vector_mse: 0.0477  \n",
      "Epoch 00031: val_calorie_loss improved from 569395.43750 to 566171.43750, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 511772.3690 - calorie_loss: 501941.1875 - category_vector_loss: 2.6306 - nutrient_vector_loss: 9815.7754 - ingredient_vector_loss: 0.2029 - calorie_mse: 502358.8438 - category_vector_mse: 0.0762 - nutrient_vector_mse: 9839.5840 - ingredient_vector_mse: 0.0477 - val_loss: 571998.3320 - val_calorie_loss: 566171.4375 - val_category_vector_loss: 8.9359 - val_nutrient_vector_loss: 5817.8232 - val_ingredient_vector_loss: 0.1908 - val_calorie_mse: 566171.4375 - val_category_vector_mse: 0.0957 - val_nutrient_vector_mse: 5817.8232 - val_ingredient_vector_mse: 0.0415\n",
      "Epoch 32/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 512906.4015 - calorie_loss: 502917.0000 - category_vector_loss: 2.4802 - nutrient_vector_loss: 9986.7881 - ingredient_vector_loss: 0.2057 - calorie_mse: 503478.1875 - category_vector_mse: 0.0747 - nutrient_vector_mse: 10011.6182 - ingredient_vector_mse: 0.0480 \n",
      "Epoch 00032: val_calorie_loss improved from 566171.43750 to 562161.37500, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 510862.3105 - calorie_loss: 501007.3438 - category_vector_loss: 2.4801 - nutrient_vector_loss: 9836.3594 - ingredient_vector_loss: 0.2054 - calorie_mse: 501543.5938 - category_vector_mse: 0.0747 - nutrient_vector_mse: 9859.7969 - ingredient_vector_mse: 0.0479 - val_loss: 568099.1250 - val_calorie_loss: 562161.3750 - val_category_vector_loss: 7.7316 - val_nutrient_vector_loss: 5929.8013 - val_ingredient_vector_loss: 0.1956 - val_calorie_mse: 562161.3750 - val_category_vector_mse: 0.0926 - val_nutrient_vector_mse: 5929.8013 - val_ingredient_vector_mse: 0.0399\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 33/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 501311.5994 - calorie_loss: 491392.4688 - category_vector_loss: 2.5120 - nutrient_vector_loss: 9916.3877 - ingredient_vector_loss: 0.2045 - calorie_mse: 491782.1250 - category_vector_mse: 0.0755 - nutrient_vector_mse: 9940.7891 - ingredient_vector_mse: 0.0476  \n",
      "Epoch 00033: val_calorie_loss improved from 562161.37500 to 559593.43750, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 500961.8985 - calorie_loss: 491191.9688 - category_vector_loss: 2.5112 - nutrient_vector_loss: 9755.7451 - ingredient_vector_loss: 0.2049 - calorie_mse: 491569.2500 - category_vector_mse: 0.0755 - nutrient_vector_mse: 9778.7227 - ingredient_vector_mse: 0.0478 - val_loss: 565484.5547 - val_calorie_loss: 559593.4375 - val_category_vector_loss: 5.1134 - val_nutrient_vector_loss: 5885.7871 - val_ingredient_vector_loss: 0.1967 - val_calorie_mse: 559593.4375 - val_category_vector_mse: 0.0822 - val_nutrient_vector_mse: 5885.7871 - val_ingredient_vector_mse: 0.0459\n",
      "Epoch 34/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 509907.1392 - calorie_loss: 499911.5000 - category_vector_loss: 2.5026 - nutrient_vector_loss: 9992.9834 - ingredient_vector_loss: 0.2044 - calorie_mse: 500397.7500 - category_vector_mse: 0.0760 - nutrient_vector_mse: 10018.8154 - ingredient_vector_mse: 0.0479 \n",
      "Epoch 00034: val_calorie_loss improved from 559593.43750 to 555615.81250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 507810.2816 - calorie_loss: 497984.9375 - category_vector_loss: 2.5002 - nutrient_vector_loss: 9808.7393 - ingredient_vector_loss: 0.2046 - calorie_mse: 498448.3750 - category_vector_mse: 0.0761 - nutrient_vector_mse: 9833.0010 - ingredient_vector_mse: 0.0479 - val_loss: 561445.7031 - val_calorie_loss: 555615.8125 - val_category_vector_loss: 7.1153 - val_nutrient_vector_loss: 5822.6030 - val_ingredient_vector_loss: 0.1936 - val_calorie_mse: 555615.8125 - val_category_vector_mse: 0.0910 - val_nutrient_vector_mse: 5822.6030 - val_ingredient_vector_mse: 0.0434\n",
      "Epoch 35/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 502399.8769 - calorie_loss: 492488.2812 - category_vector_loss: 2.4710 - nutrient_vector_loss: 9908.9053 - ingredient_vector_loss: 0.2039 - calorie_mse: 492871.0312 - category_vector_mse: 0.0746 - nutrient_vector_mse: 9934.4385 - ingredient_vector_mse: 0.0477  \n",
      "Epoch 00035: val_calorie_loss improved from 555615.81250 to 546984.43750, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 500858.0342 - calorie_loss: 491066.0312 - category_vector_loss: 2.4741 - nutrient_vector_loss: 9778.1660 - ingredient_vector_loss: 0.2036 - calorie_mse: 491431.2188 - category_vector_mse: 0.0747 - nutrient_vector_mse: 9802.3711 - ingredient_vector_mse: 0.0476 - val_loss: 552773.3555 - val_calorie_loss: 546984.4375 - val_category_vector_loss: 8.7144 - val_nutrient_vector_loss: 5780.0171 - val_ingredient_vector_loss: 0.1870 - val_calorie_mse: 546984.4375 - val_category_vector_mse: 0.0933 - val_nutrient_vector_mse: 5780.0171 - val_ingredient_vector_mse: 0.0409\n",
      "Epoch 36/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 503581.3134 - calorie_loss: 493631.3438 - category_vector_loss: 2.6162 - nutrient_vector_loss: 9947.2012 - ingredient_vector_loss: 0.2019 - calorie_mse: 494129.8750 - category_vector_mse: 0.0770 - nutrient_vector_mse: 9973.0830 - ingredient_vector_mse: 0.0476  \n",
      "Epoch 00036: val_calorie_loss improved from 546984.43750 to 539949.31250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 503099.7826 - calorie_loss: 493302.0312 - category_vector_loss: 2.6119 - nutrient_vector_loss: 9780.4854 - ingredient_vector_loss: 0.2020 - calorie_mse: 493784.3750 - category_vector_mse: 0.0771 - nutrient_vector_mse: 9804.8711 - ingredient_vector_mse: 0.0476 - val_loss: 545871.5820 - val_calorie_loss: 539949.3125 - val_category_vector_loss: 5.6469 - val_nutrient_vector_loss: 5916.4492 - val_ingredient_vector_loss: 0.1850 - val_calorie_mse: 539949.3125 - val_category_vector_mse: 0.0940 - val_nutrient_vector_mse: 5916.4492 - val_ingredient_vector_mse: 0.0418\n",
      "Epoch 37/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 501747.5000 - calorie_loss: 491830.5312 - category_vector_loss: 2.3242 - nutrient_vector_loss: 9914.4004 - ingredient_vector_loss: 0.2027 - calorie_mse: 492343.8125 - category_vector_mse: 0.0733 - nutrient_vector_mse: 9939.4561 - ingredient_vector_mse: 0.0476  \n",
      "Epoch 00037: val_calorie_loss improved from 539949.31250 to 537018.87500, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 502055.6545 - calorie_loss: 492261.8125 - category_vector_loss: 2.3329 - nutrient_vector_loss: 9776.3037 - ingredient_vector_loss: 0.2026 - calorie_mse: 492761.8438 - category_vector_mse: 0.0733 - nutrient_vector_mse: 9800.0127 - ingredient_vector_mse: 0.0476 - val_loss: 542901.8633 - val_calorie_loss: 537018.8750 - val_category_vector_loss: 4.9916 - val_nutrient_vector_loss: 5877.7871 - val_ingredient_vector_loss: 0.1919 - val_calorie_mse: 537018.8750 - val_category_vector_mse: 0.0852 - val_nutrient_vector_mse: 5877.7871 - val_ingredient_vector_mse: 0.0431\n",
      "Epoch 38/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 505442.0521 - calorie_loss: 495458.2188 - category_vector_loss: 2.3994 - nutrient_vector_loss: 9981.2119 - ingredient_vector_loss: 0.2034 - calorie_mse: 496006.0000 - category_vector_mse: 0.0743 - nutrient_vector_mse: 10006.9365 - ingredient_vector_mse: 0.0478 \n",
      "Epoch 00038: val_calorie_loss did not improve from 537018.87500\n",
      "34/34 [==============================] - 91s 3s/step - loss: 503922.1469 - calorie_loss: 494106.0625 - category_vector_loss: 2.4006 - nutrient_vector_loss: 9797.7627 - ingredient_vector_loss: 0.2034 - calorie_mse: 494631.7188 - category_vector_mse: 0.0743 - nutrient_vector_mse: 9821.9229 - ingredient_vector_mse: 0.0478 - val_loss: 546655.3711 - val_calorie_loss: 540779.8125 - val_category_vector_loss: 5.4921 - val_nutrient_vector_loss: 5869.8506 - val_ingredient_vector_loss: 0.1850 - val_calorie_mse: 540779.8125 - val_category_vector_mse: 0.0988 - val_nutrient_vector_mse: 5869.8506 - val_ingredient_vector_mse: 0.0411\n",
      "Epoch 39/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 503620.5237 - calorie_loss: 493645.5000 - category_vector_loss: 2.3803 - nutrient_vector_loss: 9972.4170 - ingredient_vector_loss: 0.2015 - calorie_mse: 493645.5000 - category_vector_mse: 0.0737 - nutrient_vector_mse: 9972.4170 - ingredient_vector_mse: 0.0476  \n",
      "Epoch 00039: val_calorie_loss improved from 537018.87500 to 531118.12500, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 500055.4989 - calorie_loss: 490233.4062 - category_vector_loss: 2.3750 - nutrient_vector_loss: 9804.7041 - ingredient_vector_loss: 0.2015 - calorie_mse: 490727.1562 - category_vector_mse: 0.0737 - nutrient_vector_mse: 9828.9717 - ingredient_vector_mse: 0.0476 - val_loss: 536926.6680 - val_calorie_loss: 531118.1250 - val_category_vector_loss: 6.9172 - val_nutrient_vector_loss: 5801.4253 - val_ingredient_vector_loss: 0.1822 - val_calorie_mse: 531118.1250 - val_category_vector_mse: 0.0934 - val_nutrient_vector_mse: 5801.4253 - val_ingredient_vector_mse: 0.0414\n",
      "Epoch 40/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 502977.9489 - calorie_loss: 493128.0938 - category_vector_loss: 2.3263 - nutrient_vector_loss: 9847.3096 - ingredient_vector_loss: 0.2014 - calorie_mse: 493628.5938 - category_vector_mse: 0.0734 - nutrient_vector_mse: 9873.4219 - ingredient_vector_mse: 0.0475  \n",
      "Epoch 00040: val_calorie_loss did not improve from 531118.12500\n",
      "34/34 [==============================] - 89s 3s/step - loss: 504290.9713 - calorie_loss: 494550.8125 - category_vector_loss: 2.3227 - nutrient_vector_loss: 9722.8467 - ingredient_vector_loss: 0.2016 - calorie_mse: 495042.7812 - category_vector_mse: 0.0734 - nutrient_vector_mse: 9747.6416 - ingredient_vector_mse: 0.0476 - val_loss: 544792.9766 - val_calorie_loss: 538956.1875 - val_category_vector_loss: 5.1924 - val_nutrient_vector_loss: 5831.4399 - val_ingredient_vector_loss: 0.1915 - val_calorie_mse: 538956.1875 - val_category_vector_mse: 0.0916 - val_nutrient_vector_mse: 5831.4399 - val_ingredient_vector_mse: 0.0424\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 41/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 497685.0142 - calorie_loss: 487849.6875 - category_vector_loss: 2.3282 - nutrient_vector_loss: 9832.7471 - ingredient_vector_loss: 0.2008 - calorie_mse: 488403.8125 - category_vector_mse: 0.0738 - nutrient_vector_mse: 9858.0596 - ingredient_vector_mse: 0.0475  \n",
      "Epoch 00041: val_calorie_loss did not improve from 531118.12500\n",
      "34/34 [==============================] - 90s 3s/step - loss: 497576.4083 - calorie_loss: 487881.3750 - category_vector_loss: 2.3272 - nutrient_vector_loss: 9676.4209 - ingredient_vector_loss: 0.2010 - calorie_mse: 488419.2500 - category_vector_mse: 0.0738 - nutrient_vector_mse: 9700.2998 - ingredient_vector_mse: 0.0475 - val_loss: 538736.6758 - val_calorie_loss: 532944.7500 - val_category_vector_loss: 4.7831 - val_nutrient_vector_loss: 5786.9189 - val_ingredient_vector_loss: 0.1846 - val_calorie_mse: 532944.7500 - val_category_vector_mse: 0.0929 - val_nutrient_vector_mse: 5786.9189 - val_ingredient_vector_mse: 0.0413\n",
      "Epoch 42/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 497733.4006 - calorie_loss: 487873.3438 - category_vector_loss: 2.3705 - nutrient_vector_loss: 9857.4766 - ingredient_vector_loss: 0.2014 - calorie_mse: 488368.5000 - category_vector_mse: 0.0743 - nutrient_vector_mse: 9882.0400 - ingredient_vector_mse: 0.0474\n",
      "Epoch 00042: val_calorie_loss did not improve from 531118.12500\n",
      "34/34 [==============================] - 89s 3s/step - loss: 495847.2864 - calorie_loss: 486114.1250 - category_vector_loss: 2.3673 - nutrient_vector_loss: 9716.4062 - ingredient_vector_loss: 0.2013 - calorie_mse: 486586.9375 - category_vector_mse: 0.0742 - nutrient_vector_mse: 9739.6260 - ingredient_vector_mse: 0.0474 - val_loss: 540584.1250 - val_calorie_loss: 534705.3750 - val_category_vector_loss: 4.6932 - val_nutrient_vector_loss: 5873.8086 - val_ingredient_vector_loss: 0.1875 - val_calorie_mse: 534705.3750 - val_category_vector_mse: 0.0870 - val_nutrient_vector_mse: 5873.8086 - val_ingredient_vector_mse: 0.0434\n",
      "Epoch 43/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 496759.1733 - calorie_loss: 486925.7188 - category_vector_loss: 2.2721 - nutrient_vector_loss: 9830.9648 - ingredient_vector_loss: 0.1997 - calorie_mse: 487486.8125 - category_vector_mse: 0.0732 - nutrient_vector_mse: 9856.1689 - ingredient_vector_mse: 0.0473 \n",
      "Epoch 00043: val_calorie_loss improved from 531118.12500 to 519520.81250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 496593.0334 - calorie_loss: 486888.3125 - category_vector_loss: 2.2730 - nutrient_vector_loss: 9685.9863 - ingredient_vector_loss: 0.1997 - calorie_mse: 487432.6562 - category_vector_mse: 0.0732 - nutrient_vector_mse: 9709.8105 - ingredient_vector_mse: 0.0473 - val_loss: 525298.4023 - val_calorie_loss: 519520.8125 - val_category_vector_loss: 5.2267 - val_nutrient_vector_loss: 5772.1689 - val_ingredient_vector_loss: 0.1890 - val_calorie_mse: 519520.8125 - val_category_vector_mse: 0.0878 - val_nutrient_vector_mse: 5772.1689 - val_ingredient_vector_mse: 0.0425\n",
      "Epoch 44/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 490904.8930 - calorie_loss: 481074.5000 - category_vector_loss: 2.2875 - nutrient_vector_loss: 9827.9424 - ingredient_vector_loss: 0.1981 - calorie_mse: 481522.8750 - category_vector_mse: 0.0731 - nutrient_vector_mse: 9852.9434 - ingredient_vector_mse: 0.0471 \n",
      "Epoch 00044: val_calorie_loss did not improve from 519520.81250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 493317.2642 - calorie_loss: 483606.3438 - category_vector_loss: 2.2860 - nutrient_vector_loss: 9695.0234 - ingredient_vector_loss: 0.1984 - calorie_mse: 484052.5938 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9718.7041 - ingredient_vector_mse: 0.0472 - val_loss: 528375.5703 - val_calorie_loss: 522573.4062 - val_category_vector_loss: 4.8579 - val_nutrient_vector_loss: 5797.1157 - val_ingredient_vector_loss: 0.1854 - val_calorie_mse: 522573.4062 - val_category_vector_mse: 0.0850 - val_nutrient_vector_mse: 5797.1157 - val_ingredient_vector_mse: 0.0421\n",
      "Epoch 45/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 497318.6619 - calorie_loss: 487431.4375 - category_vector_loss: 2.3211 - nutrient_vector_loss: 9884.7334 - ingredient_vector_loss: 0.2004 - calorie_mse: 488001.4062 - category_vector_mse: 0.0738 - nutrient_vector_mse: 9910.9541 - ingredient_vector_mse: 0.0476\n",
      "Epoch 00045: val_calorie_loss did not improve from 519520.81250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 495676.4282 - calorie_loss: 485925.6562 - category_vector_loss: 2.3176 - nutrient_vector_loss: 9731.9648 - ingredient_vector_loss: 0.2001 - calorie_mse: 486472.1875 - category_vector_mse: 0.0737 - nutrient_vector_mse: 9756.7412 - ingredient_vector_mse: 0.0475 - val_loss: 529916.5039 - val_calorie_loss: 524062.9062 - val_category_vector_loss: 3.9315 - val_nutrient_vector_loss: 5849.4224 - val_ingredient_vector_loss: 0.1851 - val_calorie_mse: 524062.9062 - val_category_vector_mse: 0.0801 - val_nutrient_vector_mse: 5849.4224 - val_ingredient_vector_mse: 0.0406\n",
      "Epoch 46/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 495664.8684 - calorie_loss: 485762.7188 - category_vector_loss: 2.3013 - nutrient_vector_loss: 9899.6680 - ingredient_vector_loss: 0.1994 - calorie_mse: 486283.5625 - category_vector_mse: 0.0735 - nutrient_vector_mse: 9925.1201 - ingredient_vector_mse: 0.0474  \n",
      "Epoch 00046: val_calorie_loss did not improve from 519520.81250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 495264.9590 - calorie_loss: 485502.2500 - category_vector_loss: 2.3011 - nutrient_vector_loss: 9745.1660 - ingredient_vector_loss: 0.1992 - calorie_mse: 486006.5625 - category_vector_mse: 0.0735 - nutrient_vector_mse: 9769.1895 - ingredient_vector_mse: 0.0473 - val_loss: 528710.8164 - val_calorie_loss: 522896.5000 - val_category_vector_loss: 3.8266 - val_nutrient_vector_loss: 5810.2637 - val_ingredient_vector_loss: 0.1759 - val_calorie_mse: 522896.5000 - val_category_vector_mse: 0.0859 - val_nutrient_vector_mse: 5810.2637 - val_ingredient_vector_mse: 0.0401\n",
      "Epoch 47/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 495057.9953 - calorie_loss: 485185.1562 - category_vector_loss: 2.2969 - nutrient_vector_loss: 9870.3584 - ingredient_vector_loss: 0.1999 - calorie_mse: 485578.6562 - category_vector_mse: 0.0733 - nutrient_vector_mse: 9894.9707 - ingredient_vector_mse: 0.0474  \n",
      "Epoch 00047: val_calorie_loss improved from 519520.81250 to 515486.31250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 493945.3937 - calorie_loss: 484222.6250 - category_vector_loss: 2.2953 - nutrient_vector_loss: 9708.8340 - ingredient_vector_loss: 0.1996 - calorie_mse: 484600.2812 - category_vector_mse: 0.0732 - nutrient_vector_mse: 9732.0107 - ingredient_vector_mse: 0.0473 - val_loss: 521274.9609 - val_calorie_loss: 515486.3125 - val_category_vector_loss: 4.6939 - val_nutrient_vector_loss: 5783.7603 - val_ingredient_vector_loss: 0.1836 - val_calorie_mse: 515486.3125 - val_category_vector_mse: 0.0898 - val_nutrient_vector_mse: 5783.7603 - val_ingredient_vector_mse: 0.0412\n",
      "Epoch 48/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 492842.9602 - calorie_loss: 483016.7188 - category_vector_loss: 2.2640 - nutrient_vector_loss: 9823.8369 - ingredient_vector_loss: 0.1990 - calorie_mse: 483538.4688 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9848.8818 - ingredient_vector_mse: 0.0472 \n",
      "Epoch 00048: val_calorie_loss did not improve from 515486.31250\n",
      "34/34 [==============================] - 91s 3s/step - loss: 491382.1844 - calorie_loss: 481702.5312 - category_vector_loss: 2.2654 - nutrient_vector_loss: 9662.2725 - ingredient_vector_loss: 0.1990 - calorie_mse: 482203.0938 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9685.8682 - ingredient_vector_mse: 0.0472 - val_loss: 522573.0273 - val_calorie_loss: 516805.7812 - val_category_vector_loss: 4.7030 - val_nutrient_vector_loss: 5762.3452 - val_ingredient_vector_loss: 0.1927 - val_calorie_mse: 516805.7812 - val_category_vector_mse: 0.0908 - val_nutrient_vector_mse: 5762.3452 - val_ingredient_vector_mse: 0.0452\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 49/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 493371.3920 - calorie_loss: 483500.1562 - category_vector_loss: 2.3290 - nutrient_vector_loss: 9868.8008 - ingredient_vector_loss: 0.2011 - calorie_mse: 483983.3750 - category_vector_mse: 0.0734 - nutrient_vector_mse: 9894.3281 - ingredient_vector_mse: 0.0475  \n",
      "Epoch 00049: val_calorie_loss improved from 515486.31250 to 512990.75000, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 491292.8567 - calorie_loss: 481591.2500 - category_vector_loss: 2.3285 - nutrient_vector_loss: 9685.3506 - ingredient_vector_loss: 0.2012 - calorie_mse: 482051.7812 - category_vector_mse: 0.0734 - nutrient_vector_mse: 9709.3184 - ingredient_vector_mse: 0.0475 - val_loss: 518774.0742 - val_calorie_loss: 512990.7500 - val_category_vector_loss: 4.1781 - val_nutrient_vector_loss: 5778.9199 - val_ingredient_vector_loss: 0.1904 - val_calorie_mse: 512990.7500 - val_category_vector_mse: 0.0825 - val_nutrient_vector_mse: 5778.9199 - val_ingredient_vector_mse: 0.0418\n",
      "Epoch 50/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 489728.8902 - calorie_loss: 479885.9375 - category_vector_loss: 2.2715 - nutrient_vector_loss: 9840.5391 - ingredient_vector_loss: 0.2018 - calorie_mse: 480371.1250 - category_vector_mse: 0.0727 - nutrient_vector_mse: 9866.1982 - ingredient_vector_mse: 0.0476  \n",
      "Epoch 00050: val_calorie_loss did not improve from 512990.75000\n",
      "34/34 [==============================] - 89s 3s/step - loss: 488096.1631 - calorie_loss: 478385.7812 - category_vector_loss: 2.2746 - nutrient_vector_loss: 9694.0029 - ingredient_vector_loss: 0.2017 - calorie_mse: 478850.0625 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9718.2617 - ingredient_vector_mse: 0.0476 - val_loss: 522053.8164 - val_calorie_loss: 516311.2188 - val_category_vector_loss: 4.2967 - val_nutrient_vector_loss: 5738.1265 - val_ingredient_vector_loss: 0.1835 - val_calorie_mse: 516311.2188 - val_category_vector_mse: 0.0786 - val_nutrient_vector_mse: 5738.1265 - val_ingredient_vector_mse: 0.0412\n",
      "Epoch 51/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 488276.0123 - calorie_loss: 478464.1250 - category_vector_loss: 2.3334 - nutrient_vector_loss: 9809.3516 - ingredient_vector_loss: 0.1989 - calorie_mse: 479000.7812 - category_vector_mse: 0.0740 - nutrient_vector_mse: 9835.1260 - ingredient_vector_mse: 0.0472 \n",
      "Epoch 00051: val_calorie_loss did not improve from 512990.75000\n",
      "34/34 [==============================] - 89s 3s/step - loss: 489301.0479 - calorie_loss: 479574.7188 - category_vector_loss: 2.3328 - nutrient_vector_loss: 9708.0850 - ingredient_vector_loss: 0.1992 - calorie_mse: 480100.3750 - category_vector_mse: 0.0740 - nutrient_vector_mse: 9732.6533 - ingredient_vector_mse: 0.0473 - val_loss: 520534.0117 - val_calorie_loss: 514787.3125 - val_category_vector_loss: 4.1852 - val_nutrient_vector_loss: 5742.3711 - val_ingredient_vector_loss: 0.1844 - val_calorie_mse: 514787.3125 - val_category_vector_mse: 0.0926 - val_nutrient_vector_mse: 5742.3711 - val_ingredient_vector_mse: 0.0412\n",
      "Epoch 52/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 490685.0871 - calorie_loss: 480845.5312 - category_vector_loss: 2.3696 - nutrient_vector_loss: 9836.9414 - ingredient_vector_loss: 0.1986 - calorie_mse: 481220.8750 - category_vector_mse: 0.0746 - nutrient_vector_mse: 9862.3096 - ingredient_vector_mse: 0.0472 \n",
      "Epoch 00052: val_calorie_loss did not improve from 512990.75000\n",
      "34/34 [==============================] - 91s 3s/step - loss: 491047.3902 - calorie_loss: 481353.8438 - category_vector_loss: 2.3711 - nutrient_vector_loss: 9679.7793 - ingredient_vector_loss: 0.1988 - calorie_mse: 481720.3438 - category_vector_mse: 0.0746 - nutrient_vector_mse: 9703.7090 - ingredient_vector_mse: 0.0472 - val_loss: 519244.2930 - val_calorie_loss: 513495.5625 - val_category_vector_loss: 4.8708 - val_nutrient_vector_loss: 5743.6621 - val_ingredient_vector_loss: 0.1854 - val_calorie_mse: 513495.5625 - val_category_vector_mse: 0.0879 - val_nutrient_vector_mse: 5743.6621 - val_ingredient_vector_mse: 0.0412\n",
      "Epoch 53/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 486334.3125 - calorie_loss: 476539.1250 - category_vector_loss: 2.2919 - nutrient_vector_loss: 9792.7432 - ingredient_vector_loss: 0.1999 - calorie_mse: 477006.1875 - category_vector_mse: 0.0731 - nutrient_vector_mse: 9818.0801 - ingredient_vector_mse: 0.0473\n",
      "Epoch 00053: val_calorie_loss did not improve from 512990.75000\n",
      "34/34 [==============================] - 90s 3s/step - loss: 487498.9653 - calorie_loss: 477807.6250 - category_vector_loss: 2.2909 - nutrient_vector_loss: 9675.0879 - ingredient_vector_loss: 0.1997 - calorie_mse: 478266.4688 - category_vector_mse: 0.0731 - nutrient_vector_mse: 9699.1611 - ingredient_vector_mse: 0.0472 - val_loss: 520272.7500 - val_calorie_loss: 514478.0938 - val_category_vector_loss: 4.4819 - val_nutrient_vector_loss: 5789.9692 - val_ingredient_vector_loss: 0.1773 - val_calorie_mse: 514478.0938 - val_category_vector_mse: 0.0989 - val_nutrient_vector_mse: 5789.9692 - val_ingredient_vector_mse: 0.0395\n",
      "Epoch 54/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 487137.6013 - calorie_loss: 477366.7500 - category_vector_loss: 2.3196 - nutrient_vector_loss: 9768.3809 - ingredient_vector_loss: 0.1990 - calorie_mse: 477902.9062 - category_vector_mse: 0.0738 - nutrient_vector_mse: 9793.7598 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00054: val_calorie_loss did not improve from 512990.75000\n",
      "34/34 [==============================] - 90s 3s/step - loss: 487120.8071 - calorie_loss: 477444.2500 - category_vector_loss: 2.3158 - nutrient_vector_loss: 9658.5078 - ingredient_vector_loss: 0.1990 - calorie_mse: 477964.9062 - category_vector_mse: 0.0737 - nutrient_vector_mse: 9682.6562 - ingredient_vector_mse: 0.0472 - val_loss: 521019.2734 - val_calorie_loss: 515267.4375 - val_category_vector_loss: 3.6720 - val_nutrient_vector_loss: 5748.0190 - val_ingredient_vector_loss: 0.1863 - val_calorie_mse: 515267.4375 - val_category_vector_mse: 0.0920 - val_nutrient_vector_mse: 5748.0190 - val_ingredient_vector_mse: 0.0409\n",
      "Epoch 55/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 489867.1136 - calorie_loss: 480016.5312 - category_vector_loss: 2.2473 - nutrient_vector_loss: 9848.1436 - ingredient_vector_loss: 0.1990 - calorie_mse: 480593.0625 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9874.8252 - ingredient_vector_mse: 0.0473 \n",
      "Epoch 00055: val_calorie_loss did not improve from 512990.75000\n",
      "34/34 [==============================] - 89s 3s/step - loss: 486751.8669 - calorie_loss: 477056.7812 - category_vector_loss: 2.2484 - nutrient_vector_loss: 9676.3027 - ingredient_vector_loss: 0.1993 - calorie_mse: 477603.3125 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9701.4424 - ingredient_vector_mse: 0.0473 - val_loss: 519307.1875 - val_calorie_loss: 513559.8125 - val_category_vector_loss: 4.3547 - val_nutrient_vector_loss: 5742.8599 - val_ingredient_vector_loss: 0.1845 - val_calorie_mse: 513559.8125 - val_category_vector_mse: 0.0939 - val_nutrient_vector_mse: 5742.8599 - val_ingredient_vector_mse: 0.0396\n",
      "Epoch 56/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 482152.8580 - calorie_loss: 472437.0625 - category_vector_loss: 2.2555 - nutrient_vector_loss: 9713.3252 - ingredient_vector_loss: 0.1990 - calorie_mse: 472855.5938 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9738.0996 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00056: val_calorie_loss improved from 512990.75000 to 509497.43750, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 483571.4959 - calorie_loss: 473968.8125 - category_vector_loss: 2.2554 - nutrient_vector_loss: 9587.7373 - ingredient_vector_loss: 0.1991 - calorie_mse: 474381.7188 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9611.2295 - ingredient_vector_mse: 0.0472 - val_loss: 515293.4805 - val_calorie_loss: 509497.4375 - val_category_vector_loss: 3.2696 - val_nutrient_vector_loss: 5792.5903 - val_ingredient_vector_loss: 0.1844 - val_calorie_mse: 509497.4375 - val_category_vector_mse: 0.0805 - val_nutrient_vector_mse: 5792.5903 - val_ingredient_vector_mse: 0.0407\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 57/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 483985.7386 - calorie_loss: 474245.4688 - category_vector_loss: 2.3242 - nutrient_vector_loss: 9737.7363 - ingredient_vector_loss: 0.1981 - calorie_mse: 474695.7188 - category_vector_mse: 0.0742 - nutrient_vector_mse: 9763.3555 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00057: val_calorie_loss did not improve from 509497.43750\n",
      "34/34 [==============================] - 90s 3s/step - loss: 484707.8709 - calorie_loss: 475060.0312 - category_vector_loss: 2.3269 - nutrient_vector_loss: 9632.0107 - ingredient_vector_loss: 0.1983 - calorie_mse: 475500.5625 - category_vector_mse: 0.0742 - nutrient_vector_mse: 9656.4092 - ingredient_vector_mse: 0.0471 - val_loss: 518342.6250 - val_calorie_loss: 512579.5000 - val_category_vector_loss: 3.8303 - val_nutrient_vector_loss: 5759.1318 - val_ingredient_vector_loss: 0.1873 - val_calorie_mse: 512579.5000 - val_category_vector_mse: 0.0863 - val_nutrient_vector_mse: 5759.1318 - val_ingredient_vector_mse: 0.0416\n",
      "Epoch 58/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 481508.2225 - calorie_loss: 471683.0625 - category_vector_loss: 2.3008 - nutrient_vector_loss: 9822.7334 - ingredient_vector_loss: 0.1983 - calorie_mse: 472105.2812 - category_vector_mse: 0.0739 - nutrient_vector_mse: 9848.3535 - ingredient_vector_mse: 0.0471 \n",
      "Epoch 00058: val_calorie_loss did not improve from 509497.43750\n",
      "34/34 [==============================] - 90s 3s/step - loss: 485173.9610 - calorie_loss: 475468.1562 - category_vector_loss: 2.3027 - nutrient_vector_loss: 9690.5127 - ingredient_vector_loss: 0.1986 - calorie_mse: 475894.5000 - category_vector_mse: 0.0740 - nutrient_vector_mse: 9714.7969 - ingredient_vector_mse: 0.0472 - val_loss: 519512.6914 - val_calorie_loss: 513671.0625 - val_category_vector_loss: 3.4682 - val_nutrient_vector_loss: 5838.0288 - val_ingredient_vector_loss: 0.1810 - val_calorie_mse: 513671.0625 - val_category_vector_mse: 0.0869 - val_nutrient_vector_mse: 5838.0288 - val_ingredient_vector_mse: 0.0412\n",
      "Epoch 59/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 487043.1705 - calorie_loss: 477262.3438 - category_vector_loss: 2.2896 - nutrient_vector_loss: 9778.3887 - ingredient_vector_loss: 0.1978 - calorie_mse: 477714.8125 - category_vector_mse: 0.0735 - nutrient_vector_mse: 9803.2646 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00059: val_calorie_loss improved from 509497.43750 to 508135.06250, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 484497.7904 - calorie_loss: 474859.2812 - category_vector_loss: 2.2967 - nutrient_vector_loss: 9623.1328 - ingredient_vector_loss: 0.1980 - calorie_mse: 475287.8750 - category_vector_mse: 0.0736 - nutrient_vector_mse: 9646.5938 - ingredient_vector_mse: 0.0471 - val_loss: 513862.0273 - val_calorie_loss: 508135.0625 - val_category_vector_loss: 3.8662 - val_nutrient_vector_loss: 5722.8994 - val_ingredient_vector_loss: 0.1787 - val_calorie_mse: 508135.0625 - val_category_vector_mse: 0.0801 - val_nutrient_vector_mse: 5722.8994 - val_ingredient_vector_mse: 0.0400\n",
      "Epoch 60/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 486054.8958 - calorie_loss: 476266.4375 - category_vector_loss: 2.2601 - nutrient_vector_loss: 9786.0693 - ingredient_vector_loss: 0.1981 - calorie_mse: 476822.5312 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9811.6309 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00060: val_calorie_loss did not improve from 508135.06250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 484189.8349 - calorie_loss: 474536.4062 - category_vector_loss: 2.2575 - nutrient_vector_loss: 9635.1416 - ingredient_vector_loss: 0.1978 - calorie_mse: 475068.5000 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9659.2861 - ingredient_vector_mse: 0.0471 - val_loss: 516084.3242 - val_calorie_loss: 510310.5625 - val_category_vector_loss: 3.9709 - val_nutrient_vector_loss: 5769.6060 - val_ingredient_vector_loss: 0.1751 - val_calorie_mse: 510310.5625 - val_category_vector_mse: 0.0954 - val_nutrient_vector_mse: 5769.6060 - val_ingredient_vector_mse: 0.0389\n",
      "Epoch 61/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 487731.7794 - calorie_loss: 477901.0625 - category_vector_loss: 2.2511 - nutrient_vector_loss: 9828.2764 - ingredient_vector_loss: 0.1974 - calorie_mse: 477901.0625 - category_vector_mse: 0.0727 - nutrient_vector_mse: 9828.2764 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00061: val_calorie_loss did not improve from 508135.06250\n",
      "34/34 [==============================] - 89s 3s/step - loss: 484674.5251 - calorie_loss: 474993.5938 - category_vector_loss: 2.2503 - nutrient_vector_loss: 9665.7969 - ingredient_vector_loss: 0.1974 - calorie_mse: 475414.3125 - category_vector_mse: 0.0727 - nutrient_vector_mse: 9689.3076 - ingredient_vector_mse: 0.0472 - val_loss: 520291.7539 - val_calorie_loss: 514493.1875 - val_category_vector_loss: 4.1552 - val_nutrient_vector_loss: 5794.2568 - val_ingredient_vector_loss: 0.1773 - val_calorie_mse: 514493.1875 - val_category_vector_mse: 0.0816 - val_nutrient_vector_mse: 5794.2568 - val_ingredient_vector_mse: 0.0403\n",
      "Epoch 62/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 480399.0360 - calorie_loss: 470682.9688 - category_vector_loss: 2.2893 - nutrient_vector_loss: 9713.5615 - ingredient_vector_loss: 0.1971 - calorie_mse: 471152.8438 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9738.8418 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00062: val_calorie_loss did not improve from 508135.06250\n",
      "34/34 [==============================] - 89s 3s/step - loss: 481262.5815 - calorie_loss: 471632.6562 - category_vector_loss: 2.2959 - nutrient_vector_loss: 9613.5791 - ingredient_vector_loss: 0.1973 - calorie_mse: 472092.8125 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9637.6738 - ingredient_vector_mse: 0.0471 - val_loss: 517111.0625 - val_calorie_loss: 511360.3438 - val_category_vector_loss: 4.1966 - val_nutrient_vector_loss: 5746.3535 - val_ingredient_vector_loss: 0.1780 - val_calorie_mse: 511360.3438 - val_category_vector_mse: 0.0899 - val_nutrient_vector_mse: 5746.3535 - val_ingredient_vector_mse: 0.0396\n",
      "Epoch 63/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 476117.1288 - calorie_loss: 466382.6875 - category_vector_loss: 2.3005 - nutrient_vector_loss: 9731.9707 - ingredient_vector_loss: 0.1983 - calorie_mse: 466847.1875 - category_vector_mse: 0.0735 - nutrient_vector_mse: 9757.2285 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00063: val_calorie_loss did not improve from 508135.06250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 478936.7605 - calorie_loss: 469315.5312 - category_vector_loss: 2.3025 - nutrient_vector_loss: 9604.8301 - ingredient_vector_loss: 0.1983 - calorie_mse: 469779.1875 - category_vector_mse: 0.0735 - nutrient_vector_mse: 9628.7842 - ingredient_vector_mse: 0.0470 - val_loss: 514410.0820 - val_calorie_loss: 508647.0625 - val_category_vector_loss: 4.8721 - val_nutrient_vector_loss: 5757.9497 - val_ingredient_vector_loss: 0.1858 - val_calorie_mse: 508647.0625 - val_category_vector_mse: 0.1009 - val_nutrient_vector_mse: 5757.9497 - val_ingredient_vector_mse: 0.0420\n",
      "Epoch 64/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 480550.3939 - calorie_loss: 470781.5625 - category_vector_loss: 2.2890 - nutrient_vector_loss: 9766.2266 - ingredient_vector_loss: 0.2001 - calorie_mse: 471239.5625 - category_vector_mse: 0.0734 - nutrient_vector_mse: 9791.5479 - ingredient_vector_mse: 0.0474\n",
      "Epoch 00064: val_calorie_loss improved from 508135.06250 to 507471.25000, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 478537.5508 - calorie_loss: 468908.8125 - category_vector_loss: 2.2831 - nutrient_vector_loss: 9613.0039 - ingredient_vector_loss: 0.1995 - calorie_mse: 469345.0625 - category_vector_mse: 0.0732 - nutrient_vector_mse: 9636.9053 - ingredient_vector_mse: 0.0472 - val_loss: 513228.7148 - val_calorie_loss: 507471.2500 - val_category_vector_loss: 4.2459 - val_nutrient_vector_loss: 5752.9995 - val_ingredient_vector_loss: 0.1893 - val_calorie_mse: 507471.2500 - val_category_vector_mse: 0.0922 - val_nutrient_vector_mse: 5752.9995 - val_ingredient_vector_mse: 0.0416\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 65/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 479588.0407 - calorie_loss: 469816.1875 - category_vector_loss: 2.2538 - nutrient_vector_loss: 9769.4883 - ingredient_vector_loss: 0.1976 - calorie_mse: 470357.5312 - category_vector_mse: 0.0729 - nutrient_vector_mse: 9795.6934 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00065: val_calorie_loss did not improve from 507471.25000\n",
      "34/34 [==============================] - 90s 3s/step - loss: 479746.2305 - calorie_loss: 470108.2188 - category_vector_loss: 2.2525 - nutrient_vector_loss: 9619.8848 - ingredient_vector_loss: 0.1977 - calorie_mse: 470634.8438 - category_vector_mse: 0.0729 - nutrient_vector_mse: 9644.6602 - ingredient_vector_mse: 0.0471 - val_loss: 516009.2969 - val_calorie_loss: 510228.5625 - val_category_vector_loss: 3.3046 - val_nutrient_vector_loss: 5777.1763 - val_ingredient_vector_loss: 0.1845 - val_calorie_mse: 510228.5625 - val_category_vector_mse: 0.0823 - val_nutrient_vector_mse: 5777.1763 - val_ingredient_vector_mse: 0.0415\n",
      "Epoch 66/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 481378.8523 - calorie_loss: 471648.9062 - category_vector_loss: 2.2548 - nutrient_vector_loss: 9727.4629 - ingredient_vector_loss: 0.1990 - calorie_mse: 472163.7812 - category_vector_mse: 0.0731 - nutrient_vector_mse: 9752.7363 - ingredient_vector_mse: 0.0473\n",
      "Epoch 00066: val_calorie_loss improved from 507471.25000 to 498569.59375, saving model to ./multi-output/recipe_three_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 482143.5181 - calorie_loss: 472501.5312 - category_vector_loss: 2.2563 - nutrient_vector_loss: 9624.4297 - ingredient_vector_loss: 0.1990 - calorie_mse: 473004.9375 - category_vector_mse: 0.0731 - nutrient_vector_mse: 9648.5049 - ingredient_vector_mse: 0.0473 - val_loss: 504280.0586 - val_calorie_loss: 498569.5938 - val_category_vector_loss: 3.7885 - val_nutrient_vector_loss: 5706.4473 - val_ingredient_vector_loss: 0.1800 - val_calorie_mse: 498569.5938 - val_category_vector_mse: 0.0948 - val_nutrient_vector_mse: 5706.4473 - val_ingredient_vector_mse: 0.0392\n",
      "Epoch 67/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 481805.7509 - calorie_loss: 472035.4062 - category_vector_loss: 2.2541 - nutrient_vector_loss: 9767.9316 - ingredient_vector_loss: 0.1971 - calorie_mse: 472488.8125 - category_vector_mse: 0.0726 - nutrient_vector_mse: 9793.4023 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00067: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 479682.9745 - calorie_loss: 470045.6875 - category_vector_loss: 2.2564 - nutrient_vector_loss: 9621.8525 - ingredient_vector_loss: 0.1970 - calorie_mse: 470476.9688 - category_vector_mse: 0.0727 - nutrient_vector_mse: 9645.9307 - ingredient_vector_mse: 0.0470 - val_loss: 515357.2305 - val_calorie_loss: 509613.1875 - val_category_vector_loss: 5.0177 - val_nutrient_vector_loss: 5738.8159 - val_ingredient_vector_loss: 0.1883 - val_calorie_mse: 509613.1875 - val_category_vector_mse: 0.0899 - val_nutrient_vector_mse: 5738.8159 - val_ingredient_vector_mse: 0.0445\n",
      "Epoch 68/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 476160.0066 - calorie_loss: 466389.7500 - category_vector_loss: 2.2529 - nutrient_vector_loss: 9767.7939 - ingredient_vector_loss: 0.1975 - calorie_mse: 466898.4688 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9793.4326 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00068: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 476384.0258 - calorie_loss: 466745.7812 - category_vector_loss: 2.2567 - nutrient_vector_loss: 9620.9365 - ingredient_vector_loss: 0.1975 - calorie_mse: 467241.0312 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9645.1738 - ingredient_vector_mse: 0.0471 - val_loss: 511320.7656 - val_calorie_loss: 505556.0000 - val_category_vector_loss: 3.5231 - val_nutrient_vector_loss: 5761.0098 - val_ingredient_vector_loss: 0.1815 - val_calorie_mse: 505556.0000 - val_category_vector_mse: 0.0872 - val_nutrient_vector_mse: 5761.0098 - val_ingredient_vector_mse: 0.0404\n",
      "Epoch 69/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 481861.7140 - calorie_loss: 472088.1875 - category_vector_loss: 2.2102 - nutrient_vector_loss: 9771.1064 - ingredient_vector_loss: 0.1977 - calorie_mse: 472088.1875 - category_vector_mse: 0.0721 - nutrient_vector_mse: 9771.1064 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00069: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 478677.4119 - calorie_loss: 469052.5312 - category_vector_loss: 2.2100 - nutrient_vector_loss: 9609.2266 - ingredient_vector_loss: 0.1978 - calorie_mse: 469491.8125 - category_vector_mse: 0.0721 - nutrient_vector_mse: 9632.6514 - ingredient_vector_mse: 0.0471 - val_loss: 511048.7852 - val_calorie_loss: 505323.0625 - val_category_vector_loss: 4.2505 - val_nutrient_vector_loss: 5721.2847 - val_ingredient_vector_loss: 0.1894 - val_calorie_mse: 505323.0625 - val_category_vector_mse: 0.0912 - val_nutrient_vector_mse: 5721.2847 - val_ingredient_vector_mse: 0.0419\n",
      "Epoch 70/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 478001.6468 - calorie_loss: 468239.6875 - category_vector_loss: 2.2523 - nutrient_vector_loss: 9759.4707 - ingredient_vector_loss: 0.1981 - calorie_mse: 468662.8750 - category_vector_mse: 0.0725 - nutrient_vector_mse: 9784.2217 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00070: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 480761.5574 - calorie_loss: 471118.5312 - category_vector_loss: 2.2514 - nutrient_vector_loss: 9627.7852 - ingredient_vector_loss: 0.1981 - calorie_mse: 471541.8438 - category_vector_mse: 0.0725 - nutrient_vector_mse: 9651.2275 - ingredient_vector_mse: 0.0471 - val_loss: 510410.6992 - val_calorie_loss: 504522.1250 - val_category_vector_loss: 3.9242 - val_nutrient_vector_loss: 5884.4546 - val_ingredient_vector_loss: 0.1879 - val_calorie_mse: 504522.1250 - val_category_vector_mse: 0.0863 - val_nutrient_vector_mse: 5884.4546 - val_ingredient_vector_mse: 0.0426\n",
      "Epoch 71/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 474525.3419 - calorie_loss: 464819.5625 - category_vector_loss: 2.2860 - nutrient_vector_loss: 9703.3057 - ingredient_vector_loss: 0.1966 - calorie_mse: 465355.3438 - category_vector_mse: 0.0734 - nutrient_vector_mse: 9728.4785 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00071: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 91s 3s/step - loss: 475745.2336 - calorie_loss: 466154.3125 - category_vector_loss: 2.2836 - nutrient_vector_loss: 9572.7617 - ingredient_vector_loss: 0.1966 - calorie_mse: 466680.1250 - category_vector_mse: 0.0733 - nutrient_vector_mse: 9596.6182 - ingredient_vector_mse: 0.0469 - val_loss: 511485.0625 - val_calorie_loss: 505747.0625 - val_category_vector_loss: 3.8692 - val_nutrient_vector_loss: 5733.9551 - val_ingredient_vector_loss: 0.1784 - val_calorie_mse: 505747.0625 - val_category_vector_mse: 0.0823 - val_nutrient_vector_mse: 5733.9551 - val_ingredient_vector_mse: 0.0403\n",
      "Epoch 72/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 477368.8267 - calorie_loss: 467587.1875 - category_vector_loss: 2.2361 - nutrient_vector_loss: 9779.1924 - ingredient_vector_loss: 0.1976 - calorie_mse: 468051.2500 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9804.9746 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00072: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 477998.1469 - calorie_loss: 468366.8750 - category_vector_loss: 2.2354 - nutrient_vector_loss: 9615.1582 - ingredient_vector_loss: 0.1976 - calorie_mse: 468820.6562 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9639.4600 - ingredient_vector_mse: 0.0470 - val_loss: 514690.8555 - val_calorie_loss: 508935.1250 - val_category_vector_loss: 4.6420 - val_nutrient_vector_loss: 5750.9170 - val_ingredient_vector_loss: 0.1803 - val_calorie_mse: 508935.1250 - val_category_vector_mse: 0.0933 - val_nutrient_vector_mse: 5750.9170 - val_ingredient_vector_mse: 0.0400\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 73/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 473843.3239 - calorie_loss: 464104.0625 - category_vector_loss: 2.2578 - nutrient_vector_loss: 9736.7705 - ingredient_vector_loss: 0.1967 - calorie_mse: 464610.3438 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9762.2461 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00073: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 475447.9845 - calorie_loss: 465839.9375 - category_vector_loss: 2.2588 - nutrient_vector_loss: 9590.5957 - ingredient_vector_loss: 0.1965 - calorie_mse: 466338.8750 - category_vector_mse: 0.0729 - nutrient_vector_mse: 9614.6768 - ingredient_vector_mse: 0.0471 - val_loss: 510384.6719 - val_calorie_loss: 504659.6875 - val_category_vector_loss: 3.4036 - val_nutrient_vector_loss: 5721.3901 - val_ingredient_vector_loss: 0.1801 - val_calorie_mse: 504659.6875 - val_category_vector_mse: 0.0833 - val_nutrient_vector_mse: 5721.3901 - val_ingredient_vector_mse: 0.0410\n",
      "Epoch 74/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 484859.5871 - calorie_loss: 475046.5625 - category_vector_loss: 2.2490 - nutrient_vector_loss: 9810.5908 - ingredient_vector_loss: 0.1976 - calorie_mse: 475531.4062 - category_vector_mse: 0.0729 - nutrient_vector_mse: 9836.1826 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00074: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 483427.1195 - calorie_loss: 473749.9688 - category_vector_loss: 2.2457 - nutrient_vector_loss: 9660.7656 - ingredient_vector_loss: 0.1977 - calorie_mse: 474214.8125 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9684.9443 - ingredient_vector_mse: 0.0472 - val_loss: 513065.2031 - val_calorie_loss: 507280.7812 - val_category_vector_loss: 3.4782 - val_nutrient_vector_loss: 5780.7524 - val_ingredient_vector_loss: 0.1873 - val_calorie_mse: 507280.7812 - val_category_vector_mse: 0.0899 - val_nutrient_vector_mse: 5780.7524 - val_ingredient_vector_mse: 0.0413\n",
      "Epoch 75/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 477628.8191 - calorie_loss: 467885.3750 - category_vector_loss: 2.2559 - nutrient_vector_loss: 9741.0234 - ingredient_vector_loss: 0.1983 - calorie_mse: 468409.9688 - category_vector_mse: 0.0726 - nutrient_vector_mse: 9766.1904 - ingredient_vector_mse: 0.0473\n",
      "Epoch 00075: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 476175.3112 - calorie_loss: 466576.9062 - category_vector_loss: 2.2556 - nutrient_vector_loss: 9580.8965 - ingredient_vector_loss: 0.1984 - calorie_mse: 467080.2812 - category_vector_mse: 0.0725 - nutrient_vector_mse: 9604.6172 - ingredient_vector_mse: 0.0473 - val_loss: 518020.0312 - val_calorie_loss: 512228.9062 - val_category_vector_loss: 4.5639 - val_nutrient_vector_loss: 5786.3999 - val_ingredient_vector_loss: 0.1850 - val_calorie_mse: 512228.9062 - val_category_vector_mse: 0.1008 - val_nutrient_vector_mse: 5786.3999 - val_ingredient_vector_mse: 0.0409\n",
      "Epoch 76/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 474161.6619 - calorie_loss: 464449.5312 - category_vector_loss: 2.2736 - nutrient_vector_loss: 9709.6709 - ingredient_vector_loss: 0.1978 - calorie_mse: 464974.7812 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9735.1084 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00076: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 473238.2752 - calorie_loss: 463662.7500 - category_vector_loss: 2.2719 - nutrient_vector_loss: 9557.9443 - ingredient_vector_loss: 0.1977 - calorie_mse: 464169.0000 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9581.9658 - ingredient_vector_mse: 0.0471 - val_loss: 519098.9805 - val_calorie_loss: 513256.2188 - val_category_vector_loss: 4.2548 - val_nutrient_vector_loss: 5838.3413 - val_ingredient_vector_loss: 0.1819 - val_calorie_mse: 513256.2188 - val_category_vector_mse: 0.0884 - val_nutrient_vector_mse: 5838.3413 - val_ingredient_vector_mse: 0.0402\n",
      "Epoch 77/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 479529.0634 - calorie_loss: 469744.8125 - category_vector_loss: 2.2544 - nutrient_vector_loss: 9781.8281 - ingredient_vector_loss: 0.1965 - calorie_mse: 470287.2812 - category_vector_mse: 0.0726 - nutrient_vector_mse: 9807.8311 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00077: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 478763.5245 - calorie_loss: 469116.5000 - category_vector_loss: 2.2487 - nutrient_vector_loss: 9628.9482 - ingredient_vector_loss: 0.1967 - calorie_mse: 469640.1875 - category_vector_mse: 0.0725 - nutrient_vector_mse: 9653.5117 - ingredient_vector_mse: 0.0469 - val_loss: 518718.0117 - val_calorie_loss: 512780.2188 - val_category_vector_loss: 4.7437 - val_nutrient_vector_loss: 5932.8906 - val_ingredient_vector_loss: 0.1798 - val_calorie_mse: 512780.2188 - val_category_vector_mse: 0.0945 - val_nutrient_vector_mse: 5932.8906 - val_ingredient_vector_mse: 0.0400\n",
      "Epoch 78/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 474439.2964 - calorie_loss: 464660.3750 - category_vector_loss: 2.3392 - nutrient_vector_loss: 9776.4355 - ingredient_vector_loss: 0.1974 - calorie_mse: 465187.8750 - category_vector_mse: 0.0743 - nutrient_vector_mse: 9802.5186 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00078: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 475288.5341 - calorie_loss: 465645.6875 - category_vector_loss: 2.3344 - nutrient_vector_loss: 9624.9033 - ingredient_vector_loss: 0.1972 - calorie_mse: 466161.9375 - category_vector_mse: 0.0742 - nutrient_vector_mse: 9649.5518 - ingredient_vector_mse: 0.0470 - val_loss: 508362.7930 - val_calorie_loss: 502612.4062 - val_category_vector_loss: 3.7490 - val_nutrient_vector_loss: 5746.4604 - val_ingredient_vector_loss: 0.1859 - val_calorie_mse: 502612.4062 - val_category_vector_mse: 0.0853 - val_nutrient_vector_mse: 5746.4604 - val_ingredient_vector_mse: 0.0412\n",
      "Epoch 79/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 471114.3116 - calorie_loss: 461443.3125 - category_vector_loss: 2.2612 - nutrient_vector_loss: 9668.4971 - ingredient_vector_loss: 0.1956 - calorie_mse: 462014.2812 - category_vector_mse: 0.0731 - nutrient_vector_mse: 9693.3799 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00079: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 472461.0635 - calorie_loss: 462893.2500 - category_vector_loss: 2.2568 - nutrient_vector_loss: 9548.6426 - ingredient_vector_loss: 0.1952 - calorie_mse: 463453.7188 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9572.2646 - ingredient_vector_mse: 0.0468 - val_loss: 508750.0078 - val_calorie_loss: 502926.3438 - val_category_vector_loss: 4.6271 - val_nutrient_vector_loss: 5818.8330 - val_ingredient_vector_loss: 0.1875 - val_calorie_mse: 502926.3438 - val_category_vector_mse: 0.0942 - val_nutrient_vector_mse: 5818.8330 - val_ingredient_vector_mse: 0.0415\n",
      "Epoch 80/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 471928.2945 - calorie_loss: 462206.5938 - category_vector_loss: 2.2851 - nutrient_vector_loss: 9719.2324 - ingredient_vector_loss: 0.1968 - calorie_mse: 462803.8125 - category_vector_mse: 0.0737 - nutrient_vector_mse: 9745.5303 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00080: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 473090.2202 - calorie_loss: 463483.1250 - category_vector_loss: 2.2859 - nutrient_vector_loss: 9587.2129 - ingredient_vector_loss: 0.1967 - calorie_mse: 464068.2812 - category_vector_mse: 0.0737 - nutrient_vector_mse: 9612.1562 - ingredient_vector_mse: 0.0470 - val_loss: 517188.9453 - val_calorie_loss: 511400.6875 - val_category_vector_loss: 3.2475 - val_nutrient_vector_loss: 5784.8516 - val_ingredient_vector_loss: 0.1899 - val_calorie_mse: 511400.6875 - val_category_vector_mse: 0.0855 - val_nutrient_vector_mse: 5784.8516 - val_ingredient_vector_mse: 0.0434\n",
      "Epoch 81/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 471797.8684 - calorie_loss: 462064.8438 - category_vector_loss: 2.2347 - nutrient_vector_loss: 9730.6055 - ingredient_vector_loss: 0.1975 - calorie_mse: 462629.6875 - category_vector_mse: 0.0723 - nutrient_vector_mse: 9756.1963 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00081: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 473482.5016 - calorie_loss: 463868.4062 - category_vector_loss: 2.2349 - nutrient_vector_loss: 9595.0908 - ingredient_vector_loss: 0.1978 - calorie_mse: 464424.4688 - category_vector_mse: 0.0723 - nutrient_vector_mse: 9619.3320 - ingredient_vector_mse: 0.0471 - val_loss: 517127.5312 - val_calorie_loss: 511358.6562 - val_category_vector_loss: 3.6064 - val_nutrient_vector_loss: 5765.0815 - val_ingredient_vector_loss: 0.1959 - val_calorie_mse: 511358.6562 - val_category_vector_mse: 0.0870 - val_nutrient_vector_mse: 5765.0815 - val_ingredient_vector_mse: 0.0433\n",
      "Epoch 82/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469223.0123 - calorie_loss: 459514.0000 - category_vector_loss: 2.2353 - nutrient_vector_loss: 9706.6123 - ingredient_vector_loss: 0.1972 - calorie_mse: 460159.0000 - category_vector_mse: 0.0726 - nutrient_vector_mse: 9733.2588 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00082: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 469923.8341 - calorie_loss: 460359.8438 - category_vector_loss: 2.2349 - nutrient_vector_loss: 9542.8730 - ingredient_vector_loss: 0.1971 - calorie_mse: 460989.5000 - category_vector_mse: 0.0726 - nutrient_vector_mse: 9568.0137 - ingredient_vector_mse: 0.0471 - val_loss: 512852.9219 - val_calorie_loss: 507098.5000 - val_category_vector_loss: 4.7183 - val_nutrient_vector_loss: 5749.5244 - val_ingredient_vector_loss: 0.1803 - val_calorie_mse: 507098.5000 - val_category_vector_mse: 0.0881 - val_nutrient_vector_mse: 5749.5244 - val_ingredient_vector_mse: 0.0416\n",
      "Epoch 83/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 470382.8674 - calorie_loss: 460666.5312 - category_vector_loss: 2.2668 - nutrient_vector_loss: 9713.8701 - ingredient_vector_loss: 0.1978 - calorie_mse: 461189.9062 - category_vector_mse: 0.0729 - nutrient_vector_mse: 9739.4258 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00083: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 472305.9412 - calorie_loss: 462697.8125 - category_vector_loss: 2.2662 - nutrient_vector_loss: 9590.1973 - ingredient_vector_loss: 0.1980 - calorie_mse: 463214.6250 - category_vector_mse: 0.0729 - nutrient_vector_mse: 9614.4561 - ingredient_vector_mse: 0.0472 - val_loss: 510064.2422 - val_calorie_loss: 504363.7188 - val_category_vector_loss: 3.8825 - val_nutrient_vector_loss: 5696.4170 - val_ingredient_vector_loss: 0.1933 - val_calorie_mse: 504363.7188 - val_category_vector_mse: 0.0852 - val_nutrient_vector_mse: 5696.4170 - val_ingredient_vector_mse: 0.0466\n",
      "Epoch 84/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469437.9242 - calorie_loss: 459732.5312 - category_vector_loss: 2.2217 - nutrient_vector_loss: 9702.9346 - ingredient_vector_loss: 0.1981 - calorie_mse: 460248.1250 - category_vector_mse: 0.0721 - nutrient_vector_mse: 9728.6641 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00084: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 469999.1216 - calorie_loss: 460419.4688 - category_vector_loss: 2.2235 - nutrient_vector_loss: 9562.1230 - ingredient_vector_loss: 0.1980 - calorie_mse: 460922.8438 - category_vector_mse: 0.0722 - nutrient_vector_mse: 9586.4746 - ingredient_vector_mse: 0.0472 - val_loss: 517083.8438 - val_calorie_loss: 511311.5000 - val_category_vector_loss: 3.1905 - val_nutrient_vector_loss: 5768.9316 - val_ingredient_vector_loss: 0.1837 - val_calorie_mse: 511311.5000 - val_category_vector_mse: 0.0790 - val_nutrient_vector_mse: 5768.9316 - val_ingredient_vector_mse: 0.0429\n",
      "Epoch 85/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 470301.6013 - calorie_loss: 460618.1250 - category_vector_loss: 2.2547 - nutrient_vector_loss: 9681.0723 - ingredient_vector_loss: 0.1944 - calorie_mse: 461200.6250 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9706.6377 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00085: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 471134.9646 - calorie_loss: 461535.3750 - category_vector_loss: 2.2563 - nutrient_vector_loss: 9580.2217 - ingredient_vector_loss: 0.1946 - calorie_mse: 462104.6875 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9604.5898 - ingredient_vector_mse: 0.0468 - val_loss: 511612.1953 - val_calorie_loss: 505764.4375 - val_category_vector_loss: 5.2909 - val_nutrient_vector_loss: 5842.2979 - val_ingredient_vector_loss: 0.1773 - val_calorie_mse: 505764.4375 - val_category_vector_mse: 0.0890 - val_nutrient_vector_mse: 5842.2979 - val_ingredient_vector_mse: 0.0393\n",
      "Epoch 86/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 470877.4489 - calorie_loss: 461123.5938 - category_vector_loss: 2.2583 - nutrient_vector_loss: 9751.3418 - ingredient_vector_loss: 0.1968 - calorie_mse: 461672.9375 - category_vector_mse: 0.0725 - nutrient_vector_mse: 9777.7832 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00086: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 91s 3s/step - loss: 469962.2903 - calorie_loss: 460359.0000 - category_vector_loss: 2.2551 - nutrient_vector_loss: 9584.9414 - ingredient_vector_loss: 0.1970 - calorie_mse: 460888.7500 - category_vector_mse: 0.0725 - nutrient_vector_mse: 9609.8721 - ingredient_vector_mse: 0.0470 - val_loss: 509314.2383 - val_calorie_loss: 503567.2500 - val_category_vector_loss: 3.8139 - val_nutrient_vector_loss: 5742.9482 - val_ingredient_vector_loss: 0.1848 - val_calorie_mse: 503567.2500 - val_category_vector_mse: 0.0859 - val_nutrient_vector_mse: 5742.9482 - val_ingredient_vector_mse: 0.0417\n",
      "Epoch 87/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 468606.8920 - calorie_loss: 458929.7188 - category_vector_loss: 2.2276 - nutrient_vector_loss: 9674.7402 - ingredient_vector_loss: 0.1967 - calorie_mse: 459428.4688 - category_vector_mse: 0.0722 - nutrient_vector_mse: 9699.4434 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00087: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 91s 3s/step - loss: 470511.8135 - calorie_loss: 460945.9375 - category_vector_loss: 2.2292 - nutrient_vector_loss: 9548.6943 - ingredient_vector_loss: 0.1967 - calorie_mse: 461438.7812 - category_vector_mse: 0.0722 - nutrient_vector_mse: 9572.1143 - ingredient_vector_mse: 0.0469 - val_loss: 514561.2930 - val_calorie_loss: 508749.4688 - val_category_vector_loss: 3.1106 - val_nutrient_vector_loss: 5808.5356 - val_ingredient_vector_loss: 0.1839 - val_calorie_mse: 508749.4688 - val_category_vector_mse: 0.0800 - val_nutrient_vector_mse: 5808.5356 - val_ingredient_vector_mse: 0.0414\n",
      "Epoch 88/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 470657.7538 - calorie_loss: 460929.5000 - category_vector_loss: 2.2194 - nutrient_vector_loss: 9725.8770 - ingredient_vector_loss: 0.1976 - calorie_mse: 461371.3125 - category_vector_mse: 0.0722 - nutrient_vector_mse: 9751.0117 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00088: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 472340.0026 - calorie_loss: 462737.3750 - category_vector_loss: 2.2194 - nutrient_vector_loss: 9587.0605 - ingredient_vector_loss: 0.1976 - calorie_mse: 463174.0938 - category_vector_mse: 0.0722 - nutrient_vector_mse: 9610.8438 - ingredient_vector_mse: 0.0471 - val_loss: 516372.2344 - val_calorie_loss: 510609.0000 - val_category_vector_loss: 3.1547 - val_nutrient_vector_loss: 5759.9189 - val_ingredient_vector_loss: 0.1863 - val_calorie_mse: 510609.0000 - val_category_vector_mse: 0.0812 - val_nutrient_vector_mse: 5759.9189 - val_ingredient_vector_mse: 0.0427\n",
      "Epoch 89/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33/34 [============================>.] - ETA: 2s - loss: 470636.3731 - calorie_loss: 460911.2812 - category_vector_loss: 2.2607 - nutrient_vector_loss: 9722.6250 - ingredient_vector_loss: 0.1973 - calorie_mse: 461427.5312 - category_vector_mse: 0.0729 - nutrient_vector_mse: 9747.7559 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00089: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 471691.0632 - calorie_loss: 462100.3125 - category_vector_loss: 2.2605 - nutrient_vector_loss: 9573.1152 - ingredient_vector_loss: 0.1970 - calorie_mse: 462606.5312 - category_vector_mse: 0.0729 - nutrient_vector_mse: 9596.8477 - ingredient_vector_mse: 0.0471 - val_loss: 514320.7070 - val_calorie_loss: 508535.3750 - val_category_vector_loss: 3.5461 - val_nutrient_vector_loss: 5781.6147 - val_ingredient_vector_loss: 0.1851 - val_calorie_mse: 508535.3750 - val_category_vector_mse: 0.0854 - val_nutrient_vector_mse: 5781.6147 - val_ingredient_vector_mse: 0.0413\n",
      "Epoch 90/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 474073.1297 - calorie_loss: 464321.7500 - category_vector_loss: 2.2698 - nutrient_vector_loss: 9748.8896 - ingredient_vector_loss: 0.1970 - calorie_mse: 464321.7500 - category_vector_mse: 0.0726 - nutrient_vector_mse: 9748.8896 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00090: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 470192.4610 - calorie_loss: 460595.0000 - category_vector_loss: 2.2694 - nutrient_vector_loss: 9578.8750 - ingredient_vector_loss: 0.1973 - calorie_mse: 461134.2812 - category_vector_mse: 0.0726 - nutrient_vector_mse: 9603.4766 - ingredient_vector_mse: 0.0470 - val_loss: 516383.5000 - val_calorie_loss: 510590.9688 - val_category_vector_loss: 3.5891 - val_nutrient_vector_loss: 5788.7734 - val_ingredient_vector_loss: 0.1843 - val_calorie_mse: 510590.9688 - val_category_vector_mse: 0.0853 - val_nutrient_vector_mse: 5788.7734 - val_ingredient_vector_mse: 0.0413\n",
      "Epoch 91/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 468024.1610 - calorie_loss: 458311.3438 - category_vector_loss: 2.2124 - nutrient_vector_loss: 9710.3672 - ingredient_vector_loss: 0.1970 - calorie_mse: 458915.8125 - category_vector_mse: 0.0719 - nutrient_vector_mse: 9736.6318 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00091: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 467904.3082 - calorie_loss: 458333.5938 - category_vector_loss: 2.2155 - nutrient_vector_loss: 9550.7842 - ingredient_vector_loss: 0.1973 - calorie_mse: 458920.3125 - category_vector_mse: 0.0719 - nutrient_vector_mse: 9575.5723 - ingredient_vector_mse: 0.0470 - val_loss: 508001.1719 - val_calorie_loss: 502242.4062 - val_category_vector_loss: 3.5902 - val_nutrient_vector_loss: 5754.9756 - val_ingredient_vector_loss: 0.1910 - val_calorie_mse: 502242.4062 - val_category_vector_mse: 0.0800 - val_nutrient_vector_mse: 5754.9756 - val_ingredient_vector_mse: 0.0436\n",
      "Epoch 92/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 471728.9839 - calorie_loss: 461999.0000 - category_vector_loss: 2.2303 - nutrient_vector_loss: 9727.5527 - ingredient_vector_loss: 0.1967 - calorie_mse: 462550.7188 - category_vector_mse: 0.0722 - nutrient_vector_mse: 9753.6689 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00092: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 469896.6613 - calorie_loss: 460301.2500 - category_vector_loss: 2.2275 - nutrient_vector_loss: 9577.1934 - ingredient_vector_loss: 0.1963 - calorie_mse: 460829.2500 - category_vector_mse: 0.0722 - nutrient_vector_mse: 9601.8779 - ingredient_vector_mse: 0.0470 - val_loss: 513849.7227 - val_calorie_loss: 508079.7188 - val_category_vector_loss: 3.8837 - val_nutrient_vector_loss: 5765.9160 - val_ingredient_vector_loss: 0.1927 - val_calorie_mse: 508079.7188 - val_category_vector_mse: 0.0878 - val_nutrient_vector_mse: 5765.9160 - val_ingredient_vector_mse: 0.0438\n",
      "Epoch 93/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 466265.8646 - calorie_loss: 456557.0625 - category_vector_loss: 2.2423 - nutrient_vector_loss: 9706.3975 - ingredient_vector_loss: 0.1967 - calorie_mse: 457066.5000 - category_vector_mse: 0.0723 - nutrient_vector_mse: 9732.1123 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00093: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 467697.5396 - calorie_loss: 458104.7500 - category_vector_loss: 2.2396 - nutrient_vector_loss: 9575.3525 - ingredient_vector_loss: 0.1967 - calorie_mse: 458605.9375 - category_vector_mse: 0.0723 - nutrient_vector_mse: 9599.7334 - ingredient_vector_mse: 0.0470 - val_loss: 515105.4609 - val_calorie_loss: 509345.1875 - val_category_vector_loss: 4.0273 - val_nutrient_vector_loss: 5756.0366 - val_ingredient_vector_loss: 0.1826 - val_calorie_mse: 509345.1875 - val_category_vector_mse: 0.0900 - val_nutrient_vector_mse: 5756.0366 - val_ingredient_vector_mse: 0.0407\n",
      "Epoch 94/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 473243.6335 - calorie_loss: 463537.9375 - category_vector_loss: 2.2451 - nutrient_vector_loss: 9703.2949 - ingredient_vector_loss: 0.1958 - calorie_mse: 464190.7812 - category_vector_mse: 0.0724 - nutrient_vector_mse: 9728.4727 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00094: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 91s 3s/step - loss: 473004.4552 - calorie_loss: 463405.5625 - category_vector_loss: 2.2483 - nutrient_vector_loss: 9577.7314 - ingredient_vector_loss: 0.1956 - calorie_mse: 464038.5312 - category_vector_mse: 0.0725 - nutrient_vector_mse: 9601.6152 - ingredient_vector_mse: 0.0469 - val_loss: 520237.4805 - val_calorie_loss: 514472.6875 - val_category_vector_loss: 3.4653 - val_nutrient_vector_loss: 5761.1333 - val_ingredient_vector_loss: 0.1747 - val_calorie_mse: 514472.6875 - val_category_vector_mse: 0.0805 - val_nutrient_vector_mse: 5761.1333 - val_ingredient_vector_mse: 0.0388\n",
      "Epoch 95/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 468269.3977 - calorie_loss: 458568.3125 - category_vector_loss: 2.2534 - nutrient_vector_loss: 9698.6250 - ingredient_vector_loss: 0.1958 - calorie_mse: 459140.0312 - category_vector_mse: 0.0731 - nutrient_vector_mse: 9724.4336 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00095: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 91s 3s/step - loss: 465960.1812 - calorie_loss: 456393.6875 - category_vector_loss: 2.2509 - nutrient_vector_loss: 9547.7568 - ingredient_vector_loss: 0.1954 - calorie_mse: 456938.9688 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9572.1416 - ingredient_vector_mse: 0.0468 - val_loss: 518112.8398 - val_calorie_loss: 512347.1562 - val_category_vector_loss: 4.0701 - val_nutrient_vector_loss: 5761.4067 - val_ingredient_vector_loss: 0.1832 - val_calorie_mse: 512347.1562 - val_category_vector_mse: 0.0909 - val_nutrient_vector_mse: 5761.4067 - val_ingredient_vector_mse: 0.0403\n",
      "Epoch 96/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 466500.4905 - calorie_loss: 456787.8438 - category_vector_loss: 2.2390 - nutrient_vector_loss: 9710.2031 - ingredient_vector_loss: 0.1966 - calorie_mse: 457300.4062 - category_vector_mse: 0.0725 - nutrient_vector_mse: 9735.9814 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00096: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 464876.2326 - calorie_loss: 455310.8125 - category_vector_loss: 2.2429 - nutrient_vector_loss: 9548.2529 - ingredient_vector_loss: 0.1964 - calorie_mse: 455801.7812 - category_vector_mse: 0.0726 - nutrient_vector_mse: 9572.5596 - ingredient_vector_mse: 0.0470 - val_loss: 509728.1602 - val_calorie_loss: 503971.4062 - val_category_vector_loss: 4.0350 - val_nutrient_vector_loss: 5752.5532 - val_ingredient_vector_loss: 0.1742 - val_calorie_mse: 503971.4062 - val_category_vector_mse: 0.0891 - val_nutrient_vector_mse: 5752.5532 - val_ingredient_vector_mse: 0.0390\n",
      "Epoch 97/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 470221.4119 - calorie_loss: 460484.1875 - category_vector_loss: 2.2138 - nutrient_vector_loss: 9734.8555 - ingredient_vector_loss: 0.1952 - calorie_mse: 461080.9688 - category_vector_mse: 0.0720 - nutrient_vector_mse: 9760.6943 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00097: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 470503.0410 - calorie_loss: 460889.0625 - category_vector_loss: 2.2157 - nutrient_vector_loss: 9594.3008 - ingredient_vector_loss: 0.1952 - calorie_mse: 461469.9688 - category_vector_mse: 0.0720 - nutrient_vector_mse: 9618.7598 - ingredient_vector_mse: 0.0468 - val_loss: 506190.4492 - val_calorie_loss: 500457.6875 - val_category_vector_loss: 3.6930 - val_nutrient_vector_loss: 5728.8691 - val_ingredient_vector_loss: 0.1842 - val_calorie_mse: 500457.6875 - val_category_vector_mse: 0.0844 - val_nutrient_vector_mse: 5728.8691 - val_ingredient_vector_mse: 0.0415\n",
      "Epoch 98/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 462785.0739 - calorie_loss: 453086.5938 - category_vector_loss: 2.2060 - nutrient_vector_loss: 9696.1250 - ingredient_vector_loss: 0.1959 - calorie_mse: 453674.0312 - category_vector_mse: 0.0719 - nutrient_vector_mse: 9722.4385 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00098: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 90s 3s/step - loss: 462065.6344 - calorie_loss: 452514.8438 - category_vector_loss: 2.2023 - nutrient_vector_loss: 9531.5186 - ingredient_vector_loss: 0.1959 - calorie_mse: 453082.4375 - category_vector_mse: 0.0718 - nutrient_vector_mse: 9556.3320 - ingredient_vector_mse: 0.0469 - val_loss: 510813.1484 - val_calorie_loss: 505064.3125 - val_category_vector_loss: 4.4352 - val_nutrient_vector_loss: 5744.2051 - val_ingredient_vector_loss: 0.1880 - val_calorie_mse: 505064.3125 - val_category_vector_mse: 0.0897 - val_nutrient_vector_mse: 5744.2051 - val_ingredient_vector_mse: 0.0418\n",
      "Epoch 99/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469468.3987 - calorie_loss: 459760.1875 - category_vector_loss: 2.2700 - nutrient_vector_loss: 9705.7637 - ingredient_vector_loss: 0.1966 - calorie_mse: 460261.4062 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9731.4189 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00099: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 466535.6783 - calorie_loss: 456964.1562 - category_vector_loss: 2.2685 - nutrient_vector_loss: 9554.8418 - ingredient_vector_loss: 0.1961 - calorie_mse: 457438.2812 - category_vector_mse: 0.0730 - nutrient_vector_mse: 9579.0781 - ingredient_vector_mse: 0.0470 - val_loss: 511790.4531 - val_calorie_loss: 506046.7500 - val_category_vector_loss: 5.4348 - val_nutrient_vector_loss: 5738.0972 - val_ingredient_vector_loss: 0.1826 - val_calorie_mse: 506046.7500 - val_category_vector_mse: 0.0971 - val_nutrient_vector_mse: 5738.0972 - val_ingredient_vector_mse: 0.0418\n",
      "Epoch 100/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 467867.9110 - calorie_loss: 458146.8125 - category_vector_loss: 2.2424 - nutrient_vector_loss: 9718.5654 - ingredient_vector_loss: 0.1962 - calorie_mse: 458585.8750 - category_vector_mse: 0.0728 - nutrient_vector_mse: 9743.3223 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00100: val_calorie_loss did not improve from 498569.59375\n",
      "34/34 [==============================] - 92s 3s/step - loss: 469186.1842 - calorie_loss: 459577.2500 - category_vector_loss: 2.2398 - nutrient_vector_loss: 9593.3721 - ingredient_vector_loss: 0.1963 - calorie_mse: 460009.6250 - category_vector_mse: 0.0727 - nutrient_vector_mse: 9616.8496 - ingredient_vector_mse: 0.0469 - val_loss: 511372.5859 - val_calorie_loss: 505602.0000 - val_category_vector_loss: 4.4984 - val_nutrient_vector_loss: 5765.8921 - val_ingredient_vector_loss: 0.1904 - val_calorie_mse: 505602.0000 - val_category_vector_mse: 0.0938 - val_nutrient_vector_mse: 5765.8921 - val_ingredient_vector_mse: 0.0423\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.optimizers import Adam\n",
    "from tensorflow.keras.callbacks import ModelCheckpoint\n",
    "from tensorflow.keras import metrics\n",
    "\n",
    "model.compile(optimizer=Adam(lr=1e-3), loss={'calorie':'mse', 'ingredient_vector':'binary_crossentropy', \n",
    "                                             'category_vector':'categorical_crossentropy', 'nutrient_vector':'mse'}\n",
    "                                              , metrics=['mse'])\n",
    "\n",
    " \n",
    "checkpointer = ModelCheckpoint(filepath='./multi-output/recipe_three_vector_100epoch.h5', verbose=1, \n",
    "                               monitor='val_calorie_loss', mode='auto', save_best_only=True)\n",
    "\n",
    "history = model.fit_generator(generator=train_generator, \n",
    "                    steps_per_epoch=round(train_generator.n/train_generator.batch_size),\n",
    "                    epochs=100,\n",
    "                    validation_data=valid_generator,\n",
    "                    validation_steps=round(valid_generator.n/valid_generator.batch_size),\n",
    "                    callbacks=[checkpointer]\n",
    "                   ) \n",
    "\n",
    "\n",
    "with open('./multi-output/recipe_three_vector_100epoch.pkl','wb') as f:\n",
    "    pickle.dump(history.history, f) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 4. output: calorie+ingredient vector "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 4381 validated image filenames.\n",
      "Found 1095 validated image filenames.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/uceezku/project/lib64/python3.6/site-packages/keras_preprocessing/image/dataframe_iterator.py:282: UserWarning: Found 6 invalid image filename(s) in x_col=\"file_name\". These filename(s) will be ignored.\n",
      "  .format(n_invalid, x_col)\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "\n",
    "datagen=ImageDataGenerator(\n",
    "    #rescale=1/255, \n",
    "    validation_split=0.2, \n",
    "    rotation_range=20,\n",
    "    width_shift_range=0.2,\n",
    "    height_shift_range=0.2,\n",
    "    horizontal_flip=True,\n",
    "    )\n",
    "\n",
    "train_generator = datagen.flow_from_dataframe(\n",
    "    dataframe=train_data,\n",
    "    directory='./data/train/',\n",
    "    target_size = (256,256),\n",
    "    x_col='file_name',\n",
    "    y_col= ['calorie_per_recipe', 'ingredient_vector'],\n",
    "    batch_size=128,\n",
    "    shuffle=True,\n",
    "    subset='training',\n",
    "    class_mode='multi_output')\n",
    "\n",
    "\n",
    "valid_generator = datagen.flow_from_dataframe(\n",
    "    dataframe=train_data,\n",
    "    directory='./data/train/',\n",
    "    target_size = (256,256),\n",
    "    x_col='file_name',\n",
    "    y_col= ['calorie_per_recipe', 'ingredient_vector'],\n",
    "    batch_size=128,\n",
    "    shuffle=True,\n",
    "    subset='validation',\n",
    "    class_mode='multi_output')\n",
    "    #validate_filenames=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-6-4ffc0ab60faf>:18: Model.fit_generator (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use Model.fit, which supports generators.\n",
      "Train for 34 steps, validate for 9 steps\n",
      "Epoch 1/100\n",
      "17/34 [==============>...............] - ETA: 43s - loss: 2392970.4926 - calorie_loss: 2392970.0000 - ingredient_vector_loss: 0.5621 - calorie_mse: 2392970.0000 - ingredient_vector_mse: 0.1614"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/uceezku/project/lib64/python3.6/site-packages/PIL/Image.py:963: UserWarning: Palette images with Transparency expressed in bytes should be converted to RGBA images\n",
      "  \"Palette images with Transparency expressed in bytes should be \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33/34 [============================>.] - ETA: 2s - loss: 2275248.8295 - calorie_loss: 2275248.0000 - ingredient_vector_loss: 0.5605 - calorie_mse: 2287610.0000 - ingredient_vector_mse: 0.1169\n",
      "Epoch 00001: val_calorie_loss improved from inf to 2528830.25000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 99s 3s/step - loss: 2261403.2980 - calorie_loss: 2261069.5000 - ingredient_vector_loss: 0.5630 - calorie_mse: 2272729.2500 - ingredient_vector_mse: 0.1155 - val_loss: 2528830.8056 - val_calorie_loss: 2528830.2500 - val_ingredient_vector_loss: 0.3921 - val_calorie_mse: 2530111.5000 - val_ingredient_vector_mse: 0.0404\n",
      "Epoch 2/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 1554385.1250 - calorie_loss: 1554384.2500 - ingredient_vector_loss: 0.9349 - calorie_mse: 1560814.0000 - ingredient_vector_mse: 0.0804\n",
      "Epoch 00002: val_calorie_loss improved from 2528830.25000 to 1672365.37500, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 1540206.6292 - calorie_loss: 1540037.0000 - ingredient_vector_loss: 0.9423 - calorie_mse: 1545939.2500 - ingredient_vector_mse: 0.0806 - val_loss: 1672365.8472 - val_calorie_loss: 1672365.3750 - val_ingredient_vector_loss: 0.6731 - val_calorie_mse: 1673536.5000 - val_ingredient_vector_mse: 0.0403\n",
      "Epoch 3/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 839364.5473 - calorie_loss: 839363.1250 - ingredient_vector_loss: 1.4108 - calorie_mse: 848515.5625 - ingredient_vector_mse: 0.0843\n",
      "Epoch 00003: val_calorie_loss improved from 1672365.37500 to 979005.12500, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 834578.8445 - calorie_loss: 834327.1875 - ingredient_vector_loss: 1.4147 - calorie_mse: 843086.9375 - ingredient_vector_mse: 0.0843 - val_loss: 979005.9236 - val_calorie_loss: 979005.1250 - val_ingredient_vector_loss: 0.8924 - val_calorie_mse: 979162.4375 - val_ingredient_vector_mse: 0.0417\n",
      "Epoch 4/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 559624.1913 - calorie_loss: 559622.5625 - ingredient_vector_loss: 1.6318 - calorie_mse: 565346.3125 - ingredient_vector_mse: 0.0857\n",
      "Epoch 00004: val_calorie_loss improved from 979005.12500 to 746082.75000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 558926.9034 - calorie_loss: 558767.2500 - ingredient_vector_loss: 1.6323 - calorie_mse: 564298.8125 - ingredient_vector_mse: 0.0857 - val_loss: 746083.6111 - val_calorie_loss: 746082.7500 - val_ingredient_vector_loss: 0.9223 - val_calorie_mse: 746400.8750 - val_ingredient_vector_mse: 0.0415\n",
      "Epoch 5/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 545406.1752 - calorie_loss: 545404.6875 - ingredient_vector_loss: 1.5483 - calorie_mse: 551924.7500 - ingredient_vector_mse: 0.0850\n",
      "Epoch 00005: val_calorie_loss improved from 746082.75000 to 726866.18750, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 544807.3910 - calorie_loss: 544625.6875 - ingredient_vector_loss: 1.5469 - calorie_mse: 550931.4375 - ingredient_vector_mse: 0.0849 - val_loss: 726866.9653 - val_calorie_loss: 726866.1875 - val_ingredient_vector_loss: 0.8540 - val_calorie_mse: 726619.0625 - val_ingredient_vector_mse: 0.0414\n",
      "Epoch 6/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 537385.0530 - calorie_loss: 537383.6250 - ingredient_vector_loss: 1.3874 - calorie_mse: 543526.1875 - ingredient_vector_mse: 0.0843\n",
      "Epoch 00006: val_calorie_loss did not improve from 726866.18750\n",
      "34/34 [==============================] - 91s 3s/step - loss: 539778.0692 - calorie_loss: 539604.9375 - ingredient_vector_loss: 1.3852 - calorie_mse: 545614.3125 - ingredient_vector_mse: 0.0842 - val_loss: 728297.5417 - val_calorie_loss: 728296.7500 - val_ingredient_vector_loss: 0.7981 - val_calorie_mse: 728928.6875 - val_ingredient_vector_mse: 0.0404\n",
      "Epoch 7/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 536747.0483 - calorie_loss: 536745.6875 - ingredient_vector_loss: 1.2598 - calorie_mse: 543159.3750 - ingredient_vector_mse: 0.0834\n",
      "Epoch 00007: val_calorie_loss improved from 726866.18750 to 721286.87500, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 539576.1503 - calorie_loss: 539395.3125 - ingredient_vector_loss: 1.2570 - calorie_mse: 545677.6250 - ingredient_vector_mse: 0.0833 - val_loss: 721287.6250 - val_calorie_loss: 721286.8750 - val_ingredient_vector_loss: 0.7298 - val_calorie_mse: 722704.3750 - val_ingredient_vector_mse: 0.0411\n",
      "Epoch 8/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 539087.1695 - calorie_loss: 539086.0625 - ingredient_vector_loss: 1.1184 - calorie_mse: 544202.6250 - ingredient_vector_mse: 0.0823\n",
      "Epoch 00008: val_calorie_loss improved from 721286.87500 to 714441.81250, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 538403.4038 - calorie_loss: 538261.0625 - ingredient_vector_loss: 1.1140 - calorie_mse: 543204.4375 - ingredient_vector_mse: 0.0821 - val_loss: 714442.4653 - val_calorie_loss: 714441.8125 - val_ingredient_vector_loss: 0.6513 - val_calorie_mse: 715166.7500 - val_ingredient_vector_mse: 0.0405\n",
      "Epoch 9/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 537321.6562 - calorie_loss: 537320.6875 - ingredient_vector_loss: 0.9862 - calorie_mse: 543189.4375 - ingredient_vector_mse: 0.0810\n",
      "Epoch 00009: val_calorie_loss improved from 714441.81250 to 706887.68750, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 539920.3097 - calorie_loss: 539755.0625 - ingredient_vector_loss: 0.9849 - calorie_mse: 545503.8750 - ingredient_vector_mse: 0.0810 - val_loss: 706888.2153 - val_calorie_loss: 706887.6875 - val_ingredient_vector_loss: 0.5852 - val_calorie_mse: 706884.8125 - val_ingredient_vector_mse: 0.0405\n",
      "Epoch 10/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 531910.5540 - calorie_loss: 531909.6875 - ingredient_vector_loss: 0.8692 - calorie_mse: 537647.3125 - ingredient_vector_mse: 0.0783\n",
      "Epoch 00010: val_calorie_loss improved from 706887.68750 to 706692.75000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 533786.4513 - calorie_loss: 533625.5000 - ingredient_vector_loss: 0.8672 - calorie_mse: 539230.3125 - ingredient_vector_mse: 0.0782 - val_loss: 706693.2431 - val_calorie_loss: 706692.7500 - val_ingredient_vector_loss: 0.5453 - val_calorie_mse: 706676.1875 - val_ingredient_vector_mse: 0.0401\n",
      "Epoch 11/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 523815.4332 - calorie_loss: 523814.6562 - ingredient_vector_loss: 0.7733 - calorie_mse: 530945.7500 - ingredient_vector_mse: 0.0764\n",
      "Epoch 00011: val_calorie_loss improved from 706692.75000 to 697146.75000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 525515.9165 - calorie_loss: 525316.5000 - ingredient_vector_loss: 0.7706 - calorie_mse: 532267.9375 - ingredient_vector_mse: 0.0765 - val_loss: 697147.2292 - val_calorie_loss: 697146.7500 - val_ingredient_vector_loss: 0.4666 - val_calorie_mse: 696470.0625 - val_ingredient_vector_mse: 0.0424\n",
      "Epoch 12/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 535151.7978 - calorie_loss: 535151.1250 - ingredient_vector_loss: 0.6731 - calorie_mse: 542076.4375 - ingredient_vector_mse: 0.0739\n",
      "Epoch 00012: val_calorie_loss did not improve from 697146.75000\n",
      "34/34 [==============================] - 91s 3s/step - loss: 535608.3843 - calorie_loss: 535415.6250 - ingredient_vector_loss: 0.6703 - calorie_mse: 542138.6875 - ingredient_vector_mse: 0.0737 - val_loss: 697697.4583 - val_calorie_loss: 697697.0000 - val_ingredient_vector_loss: 0.4297 - val_calorie_mse: 697779.1250 - val_ingredient_vector_mse: 0.0451\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 526592.9309 - calorie_loss: 526592.3125 - ingredient_vector_loss: 0.5859 - calorie_mse: 532538.8750 - ingredient_vector_mse: 0.0701\n",
      "Epoch 00013: val_calorie_loss improved from 697146.75000 to 679527.50000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 530161.1823 - calorie_loss: 529993.5000 - ingredient_vector_loss: 0.5835 - calorie_mse: 535840.3125 - ingredient_vector_mse: 0.0699 - val_loss: 679527.8750 - val_calorie_loss: 679527.5000 - val_ingredient_vector_loss: 0.4116 - val_calorie_mse: 679274.0625 - val_ingredient_vector_mse: 0.0463\n",
      "Epoch 14/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 528896.6212 - calorie_loss: 528896.1250 - ingredient_vector_loss: 0.5123 - calorie_mse: 535280.3125 - ingredient_vector_mse: 0.0668\n",
      "Epoch 00014: val_calorie_loss improved from 679527.50000 to 677007.31250, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 529878.4470 - calorie_loss: 529700.5000 - ingredient_vector_loss: 0.5110 - calorie_mse: 535911.2500 - ingredient_vector_mse: 0.0668 - val_loss: 677007.7222 - val_calorie_loss: 677007.3125 - val_ingredient_vector_loss: 0.3525 - val_calorie_mse: 677596.9375 - val_ingredient_vector_mse: 0.0419\n",
      "Epoch 15/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 522424.2045 - calorie_loss: 522423.6875 - ingredient_vector_loss: 0.4502 - calorie_mse: 528225.8750 - ingredient_vector_mse: 0.0640\n",
      "Epoch 00015: val_calorie_loss improved from 677007.31250 to 664919.00000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 522767.2382 - calorie_loss: 522605.8125 - ingredient_vector_loss: 0.4491 - calorie_mse: 528237.6250 - ingredient_vector_mse: 0.0639 - val_loss: 664919.2917 - val_calorie_loss: 664919.0000 - val_ingredient_vector_loss: 0.3335 - val_calorie_mse: 664152.0000 - val_ingredient_vector_mse: 0.0440\n",
      "Epoch 16/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 526472.0407 - calorie_loss: 526471.6875 - ingredient_vector_loss: 0.4008 - calorie_mse: 532840.3125 - ingredient_vector_mse: 0.0612\n",
      "Epoch 00016: val_calorie_loss improved from 664919.00000 to 663778.50000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 526311.4174 - calorie_loss: 526134.8125 - ingredient_vector_loss: 0.4004 - calorie_mse: 532303.9375 - ingredient_vector_mse: 0.0611 - val_loss: 663778.7569 - val_calorie_loss: 663778.5000 - val_ingredient_vector_loss: 0.2886 - val_calorie_mse: 664214.6250 - val_ingredient_vector_mse: 0.0402\n",
      "Epoch 17/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 524661.1127 - calorie_loss: 524660.7500 - ingredient_vector_loss: 0.3543 - calorie_mse: 531804.7500 - ingredient_vector_mse: 0.0590\n",
      "Epoch 00017: val_calorie_loss improved from 663778.50000 to 657801.18750, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 521568.6688 - calorie_loss: 521372.4688 - ingredient_vector_loss: 0.3536 - calorie_mse: 528225.0000 - ingredient_vector_mse: 0.0589 - val_loss: 657801.3854 - val_calorie_loss: 657801.1875 - val_ingredient_vector_loss: 0.2726 - val_calorie_mse: 657583.0000 - val_ingredient_vector_mse: 0.0409\n",
      "Epoch 18/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 521477.7685 - calorie_loss: 521477.4062 - ingredient_vector_loss: 0.3192 - calorie_mse: 527740.0000 - ingredient_vector_mse: 0.0568\n",
      "Epoch 00018: val_calorie_loss improved from 657801.18750 to 653946.25000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 521499.6479 - calorie_loss: 521325.8125 - ingredient_vector_loss: 0.3189 - calorie_mse: 527396.4375 - ingredient_vector_mse: 0.0567 - val_loss: 653946.4410 - val_calorie_loss: 653946.2500 - val_ingredient_vector_loss: 0.2473 - val_calorie_mse: 652811.5000 - val_ingredient_vector_mse: 0.0414\n",
      "Epoch 19/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 530450.7718 - calorie_loss: 530450.4375 - ingredient_vector_loss: 0.2867 - calorie_mse: 530450.4375 - ingredient_vector_mse: 0.0545\n",
      "Epoch 00019: val_calorie_loss improved from 653946.25000 to 650031.75000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 529608.2233 - calorie_loss: 529607.8750 - ingredient_vector_loss: 0.2863 - calorie_mse: 529607.8750 - ingredient_vector_mse: 0.0544 - val_loss: 650032.0417 - val_calorie_loss: 650031.7500 - val_ingredient_vector_loss: 0.2391 - val_calorie_mse: 649574.3750 - val_ingredient_vector_mse: 0.0417\n",
      "Epoch 20/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 521978.3030 - calorie_loss: 521978.0000 - ingredient_vector_loss: 0.2620 - calorie_mse: 528104.8750 - ingredient_vector_mse: 0.0525\n",
      "Epoch 00020: val_calorie_loss improved from 650031.75000 to 635918.75000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 88s 3s/step - loss: 518733.5825 - calorie_loss: 518565.7500 - ingredient_vector_loss: 0.2615 - calorie_mse: 524428.8125 - ingredient_vector_mse: 0.0525 - val_loss: 635918.9896 - val_calorie_loss: 635918.7500 - val_ingredient_vector_loss: 0.2309 - val_calorie_mse: 634528.9375 - val_ingredient_vector_mse: 0.0441\n",
      "Epoch 21/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 510954.6884 - calorie_loss: 510954.5000 - ingredient_vector_loss: 0.2460 - calorie_mse: 516813.9062 - ingredient_vector_mse: 0.0516\n",
      "Epoch 00021: val_calorie_loss improved from 635918.75000 to 632099.56250, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 88s 3s/step - loss: 511743.7279 - calorie_loss: 511580.7188 - ingredient_vector_loss: 0.2456 - calorie_mse: 517278.3750 - ingredient_vector_mse: 0.0515 - val_loss: 632099.7812 - val_calorie_loss: 632099.5625 - val_ingredient_vector_loss: 0.2133 - val_calorie_mse: 632022.3750 - val_ingredient_vector_mse: 0.0411\n",
      "Epoch 22/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 510751.5966 - calorie_loss: 510751.4062 - ingredient_vector_loss: 0.2332 - calorie_mse: 516761.9688 - ingredient_vector_mse: 0.0506\n",
      "Epoch 00022: val_calorie_loss improved from 632099.56250 to 617316.00000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 88s 3s/step - loss: 513598.1548 - calorie_loss: 513429.5938 - ingredient_vector_loss: 0.2328 - calorie_mse: 519321.6250 - ingredient_vector_mse: 0.0506 - val_loss: 617316.2014 - val_calorie_loss: 617316.0000 - val_ingredient_vector_loss: 0.2092 - val_calorie_mse: 616873.1250 - val_ingredient_vector_mse: 0.0410\n",
      "Epoch 23/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 511557.8409 - calorie_loss: 511557.5625 - ingredient_vector_loss: 0.2243 - calorie_mse: 517125.6875 - ingredient_vector_mse: 0.0495\n",
      "Epoch 00023: val_calorie_loss did not improve from 617316.00000\n",
      "34/34 [==============================] - 88s 3s/step - loss: 514322.5992 - calorie_loss: 514166.2812 - ingredient_vector_loss: 0.2240 - calorie_mse: 519627.5625 - ingredient_vector_mse: 0.0494 - val_loss: 622635.2153 - val_calorie_loss: 622635.0625 - val_ingredient_vector_loss: 0.2126 - val_calorie_mse: 622217.0625 - val_ingredient_vector_mse: 0.0440\n",
      "Epoch 24/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 514130.8793 - calorie_loss: 514130.5938 - ingredient_vector_loss: 0.2181 - calorie_mse: 520310.7500 - ingredient_vector_mse: 0.0487\n",
      "Epoch 00024: val_calorie_loss improved from 617316.00000 to 610053.62500, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 88s 3s/step - loss: 513474.8082 - calorie_loss: 513303.8125 - ingredient_vector_loss: 0.2179 - calorie_mse: 519278.7500 - ingredient_vector_mse: 0.0487 - val_loss: 610053.7986 - val_calorie_loss: 610053.6250 - val_ingredient_vector_loss: 0.1901 - val_calorie_mse: 609204.7500 - val_ingredient_vector_mse: 0.0408\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 25/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 506488.8134 - calorie_loss: 506488.5625 - ingredient_vector_loss: 0.2141 - calorie_mse: 512168.6875 - ingredient_vector_mse: 0.0484\n",
      "Epoch 00025: val_calorie_loss improved from 610053.62500 to 599199.81250, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 88s 3s/step - loss: 510770.7531 - calorie_loss: 510610.3438 - ingredient_vector_loss: 0.2140 - calorie_mse: 516215.4688 - ingredient_vector_mse: 0.0484 - val_loss: 599200.0069 - val_calorie_loss: 599199.8125 - val_ingredient_vector_loss: 0.1901 - val_calorie_mse: 598938.5625 - val_ingredient_vector_mse: 0.0407\n",
      "Epoch 26/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 505353.1117 - calorie_loss: 505352.9375 - ingredient_vector_loss: 0.2094 - calorie_mse: 511495.9688 - ingredient_vector_mse: 0.0481\n",
      "Epoch 00026: val_calorie_loss improved from 599199.81250 to 598838.00000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 88s 3s/step - loss: 506980.2965 - calorie_loss: 506808.9375 - ingredient_vector_loss: 0.2094 - calorie_mse: 512801.0000 - ingredient_vector_mse: 0.0481 - val_loss: 598838.1354 - val_calorie_loss: 598838.0000 - val_ingredient_vector_loss: 0.1959 - val_calorie_mse: 597452.5625 - val_ingredient_vector_mse: 0.0432\n",
      "Epoch 27/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 500254.9564 - calorie_loss: 500254.7500 - ingredient_vector_loss: 0.2077 - calorie_mse: 506052.0312 - ingredient_vector_mse: 0.0478\n",
      "Epoch 00027: val_calorie_loss improved from 598838.00000 to 597772.31250, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 88s 3s/step - loss: 502341.4240 - calorie_loss: 502179.2812 - ingredient_vector_loss: 0.2077 - calorie_mse: 507846.8750 - ingredient_vector_mse: 0.0479 - val_loss: 597772.5451 - val_calorie_loss: 597772.3125 - val_ingredient_vector_loss: 0.2095 - val_calorie_mse: 596446.8750 - val_ingredient_vector_mse: 0.0455\n",
      "Epoch 28/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 496467.1667 - calorie_loss: 496466.9688 - ingredient_vector_loss: 0.2096 - calorie_mse: 501279.1562 - ingredient_vector_mse: 0.0480\n",
      "Epoch 00028: val_calorie_loss improved from 597772.31250 to 587814.62500, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 499618.4645 - calorie_loss: 499482.8750 - ingredient_vector_loss: 0.2096 - calorie_mse: 504220.4688 - ingredient_vector_mse: 0.0481 - val_loss: 587814.8333 - val_calorie_loss: 587814.6250 - val_ingredient_vector_loss: 0.1984 - val_calorie_mse: 587404.7500 - val_ingredient_vector_mse: 0.0465\n",
      "Epoch 29/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 494173.3295 - calorie_loss: 494173.1562 - ingredient_vector_loss: 0.2069 - calorie_mse: 499498.1250 - ingredient_vector_mse: 0.0481\n",
      "Epoch 00029: val_calorie_loss improved from 587814.62500 to 573704.56250, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 88s 3s/step - loss: 498115.0850 - calorie_loss: 497964.8125 - ingredient_vector_loss: 0.2069 - calorie_mse: 503217.8125 - ingredient_vector_mse: 0.0481 - val_loss: 573704.7951 - val_calorie_loss: 573704.5625 - val_ingredient_vector_loss: 0.1789 - val_calorie_mse: 573465.6875 - val_ingredient_vector_mse: 0.0402\n",
      "Epoch 30/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 497430.4034 - calorie_loss: 497430.1875 - ingredient_vector_loss: 0.2021 - calorie_mse: 503610.7812 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00030: val_calorie_loss did not improve from 573704.56250\n",
      "34/34 [==============================] - 88s 3s/step - loss: 497924.2548 - calorie_loss: 497752.5312 - ingredient_vector_loss: 0.2022 - calorie_mse: 503754.6250 - ingredient_vector_mse: 0.0472 - val_loss: 583231.1736 - val_calorie_loss: 583231.0000 - val_ingredient_vector_loss: 0.1912 - val_calorie_mse: 581191.3750 - val_ingredient_vector_mse: 0.0432\n",
      "Epoch 31/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 500130.0455 - calorie_loss: 500129.8750 - ingredient_vector_loss: 0.2037 - calorie_mse: 504616.6562 - ingredient_vector_mse: 0.0477\n",
      "Epoch 00031: val_calorie_loss improved from 573704.56250 to 569725.56250, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 88s 3s/step - loss: 501188.1197 - calorie_loss: 501063.0000 - ingredient_vector_loss: 0.2036 - calorie_mse: 505436.4688 - ingredient_vector_mse: 0.0477 - val_loss: 569725.7257 - val_calorie_loss: 569725.5625 - val_ingredient_vector_loss: 0.1907 - val_calorie_mse: 569019.9375 - val_ingredient_vector_mse: 0.0433\n",
      "Epoch 32/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 500262.3258 - calorie_loss: 500262.1562 - ingredient_vector_loss: 0.2041 - calorie_mse: 504709.0938 - ingredient_vector_mse: 0.0474\n",
      "Epoch 00032: val_calorie_loss improved from 569725.56250 to 560132.37500, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 499572.5449 - calorie_loss: 499449.7188 - ingredient_vector_loss: 0.2044 - calorie_mse: 503743.8750 - ingredient_vector_mse: 0.0475 - val_loss: 560132.5660 - val_calorie_loss: 560132.3750 - val_ingredient_vector_loss: 0.1923 - val_calorie_mse: 558843.0625 - val_ingredient_vector_mse: 0.0437\n",
      "Epoch 33/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 492961.1619 - calorie_loss: 492960.9375 - ingredient_vector_loss: 0.2012 - calorie_mse: 498459.5938 - ingredient_vector_mse: 0.0475\n",
      "Epoch 00033: val_calorie_loss did not improve from 560132.37500\n",
      "34/34 [==============================] - 89s 3s/step - loss: 495468.9951 - calorie_loss: 495314.8125 - ingredient_vector_loss: 0.2012 - calorie_mse: 500702.7812 - ingredient_vector_mse: 0.0475 - val_loss: 562732.1285 - val_calorie_loss: 562731.9375 - val_ingredient_vector_loss: 0.1844 - val_calorie_mse: 561389.5625 - val_ingredient_vector_mse: 0.0431\n",
      "Epoch 34/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 496458.8153 - calorie_loss: 496458.6250 - ingredient_vector_loss: 0.2014 - calorie_mse: 501325.0000 - ingredient_vector_mse: 0.0473\n",
      "Epoch 00034: val_calorie_loss improved from 560132.37500 to 554284.25000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 498683.1888 - calorie_loss: 498546.7500 - ingredient_vector_loss: 0.2015 - calorie_mse: 503315.2500 - ingredient_vector_mse: 0.0473 - val_loss: 554284.4583 - val_calorie_loss: 554284.2500 - val_ingredient_vector_loss: 0.1942 - val_calorie_mse: 553510.1875 - val_ingredient_vector_mse: 0.0428\n",
      "Epoch 35/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 489096.1681 - calorie_loss: 489096.0000 - ingredient_vector_loss: 0.2015 - calorie_mse: 494563.6250 - ingredient_vector_mse: 0.0473\n",
      "Epoch 00035: val_calorie_loss improved from 554284.25000 to 544416.81250, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 491446.3107 - calorie_loss: 491293.1875 - ingredient_vector_loss: 0.2015 - calorie_mse: 496647.4062 - ingredient_vector_mse: 0.0473 - val_loss: 544417.0486 - val_calorie_loss: 544416.8125 - val_ingredient_vector_loss: 0.2051 - val_calorie_mse: 543909.8750 - val_ingredient_vector_mse: 0.0451\n",
      "Epoch 36/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 485020.9044 - calorie_loss: 485020.7188 - ingredient_vector_loss: 0.2020 - calorie_mse: 491272.9688 - ingredient_vector_mse: 0.0473\n",
      "Epoch 00036: val_calorie_loss did not improve from 544416.81250\n",
      "34/34 [==============================] - 89s 3s/step - loss: 487381.0275 - calorie_loss: 487206.1562 - ingredient_vector_loss: 0.2020 - calorie_mse: 493321.0938 - ingredient_vector_mse: 0.0473 - val_loss: 555515.4757 - val_calorie_loss: 555515.2500 - val_ingredient_vector_loss: 0.1852 - val_calorie_mse: 553723.0625 - val_ingredient_vector_mse: 0.0407\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 37/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 493060.9214 - calorie_loss: 493060.7188 - ingredient_vector_loss: 0.2019 - calorie_mse: 497850.3750 - ingredient_vector_mse: 0.0474\n",
      "Epoch 00037: val_calorie_loss improved from 544416.81250 to 543395.18750, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 492976.1908 - calorie_loss: 492843.4062 - ingredient_vector_loss: 0.2020 - calorie_mse: 497483.8438 - ingredient_vector_mse: 0.0474 - val_loss: 543395.3681 - val_calorie_loss: 543395.1875 - val_ingredient_vector_loss: 0.1900 - val_calorie_mse: 543163.6875 - val_ingredient_vector_mse: 0.0424\n",
      "Epoch 38/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 494589.2547 - calorie_loss: 494589.0312 - ingredient_vector_loss: 0.2012 - calorie_mse: 499337.5938 - ingredient_vector_mse: 0.0473\n",
      "Epoch 00038: val_calorie_loss improved from 543395.18750 to 537223.75000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 494350.9415 - calorie_loss: 494219.3438 - ingredient_vector_loss: 0.2012 - calorie_mse: 498816.4062 - ingredient_vector_mse: 0.0473 - val_loss: 537224.0590 - val_calorie_loss: 537223.7500 - val_ingredient_vector_loss: 0.1902 - val_calorie_mse: 535789.5625 - val_ingredient_vector_mse: 0.0419\n",
      "Epoch 39/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 488835.1255 - calorie_loss: 488834.9375 - ingredient_vector_loss: 0.2037 - calorie_mse: 494763.3125 - ingredient_vector_mse: 0.0476\n",
      "Epoch 00039: val_calorie_loss did not improve from 537223.75000\n",
      "34/34 [==============================] - 92s 3s/step - loss: 487047.2453 - calorie_loss: 486884.0625 - ingredient_vector_loss: 0.2037 - calorie_mse: 492588.5938 - ingredient_vector_mse: 0.0476 - val_loss: 546289.2604 - val_calorie_loss: 546289.1250 - val_ingredient_vector_loss: 0.1802 - val_calorie_mse: 543926.5625 - val_ingredient_vector_mse: 0.0405\n",
      "Epoch 40/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 486982.8722 - calorie_loss: 486982.5938 - ingredient_vector_loss: 0.2014 - calorie_mse: 492105.5938 - ingredient_vector_mse: 0.0474\n",
      "Epoch 00040: val_calorie_loss did not improve from 537223.75000\n",
      "34/34 [==============================] - 97s 3s/step - loss: 487310.1827 - calorie_loss: 487167.8125 - ingredient_vector_loss: 0.2014 - calorie_mse: 492140.9375 - ingredient_vector_mse: 0.0474 - val_loss: 541732.7674 - val_calorie_loss: 541732.6250 - val_ingredient_vector_loss: 0.1817 - val_calorie_mse: 540521.8125 - val_ingredient_vector_mse: 0.0412\n",
      "Epoch 41/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 490772.5062 - calorie_loss: 490772.3750 - ingredient_vector_loss: 0.2005 - calorie_mse: 496593.5938 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00041: val_calorie_loss improved from 537223.75000 to 532385.56250, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 98s 3s/step - loss: 490773.8532 - calorie_loss: 490612.5000 - ingredient_vector_loss: 0.2007 - calorie_mse: 496254.7812 - ingredient_vector_mse: 0.0472 - val_loss: 532385.7396 - val_calorie_loss: 532385.5625 - val_ingredient_vector_loss: 0.1907 - val_calorie_mse: 530720.5000 - val_ingredient_vector_mse: 0.0421\n",
      "Epoch 42/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 487926.0578 - calorie_loss: 487925.9062 - ingredient_vector_loss: 0.2008 - calorie_mse: 493058.9062 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00042: val_calorie_loss improved from 532385.56250 to 527931.43750, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 98s 3s/step - loss: 488796.0301 - calorie_loss: 488653.1562 - ingredient_vector_loss: 0.2007 - calorie_mse: 493648.5938 - ingredient_vector_mse: 0.0472 - val_loss: 527931.6389 - val_calorie_loss: 527931.4375 - val_ingredient_vector_loss: 0.1884 - val_calorie_mse: 527428.4375 - val_ingredient_vector_mse: 0.0414\n",
      "Epoch 43/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 487221.4460 - calorie_loss: 487221.2812 - ingredient_vector_loss: 0.1993 - calorie_mse: 492318.8438 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00043: val_calorie_loss did not improve from 527931.43750\n",
      "34/34 [==============================] - 96s 3s/step - loss: 484683.8018 - calorie_loss: 484544.1562 - ingredient_vector_loss: 0.1994 - calorie_mse: 489425.9688 - ingredient_vector_mse: 0.0470 - val_loss: 529022.6389 - val_calorie_loss: 529022.5000 - val_ingredient_vector_loss: 0.1838 - val_calorie_mse: 527782.5625 - val_ingredient_vector_mse: 0.0404\n",
      "Epoch 44/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 478845.8371 - calorie_loss: 478845.6250 - ingredient_vector_loss: 0.1997 - calorie_mse: 484238.5938 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00044: val_calorie_loss improved from 527931.43750 to 527355.43750, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 477581.0348 - calorie_loss: 477432.3125 - ingredient_vector_loss: 0.1996 - calorie_mse: 482630.0625 - ingredient_vector_mse: 0.0472 - val_loss: 527355.5868 - val_calorie_loss: 527355.4375 - val_ingredient_vector_loss: 0.1925 - val_calorie_mse: 526255.3125 - val_ingredient_vector_mse: 0.0439\n",
      "Epoch 45/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 485288.7036 - calorie_loss: 485288.5000 - ingredient_vector_loss: 0.2004 - calorie_mse: 490461.4062 - ingredient_vector_mse: 0.0473\n",
      "Epoch 00045: val_calorie_loss improved from 527355.43750 to 523559.93750, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 97s 3s/step - loss: 484727.3554 - calorie_loss: 484584.2812 - ingredient_vector_loss: 0.2002 - calorie_mse: 489585.0938 - ingredient_vector_mse: 0.0473 - val_loss: 523560.1146 - val_calorie_loss: 523559.9375 - val_ingredient_vector_loss: 0.1867 - val_calorie_mse: 521744.3750 - val_ingredient_vector_mse: 0.0415\n",
      "Epoch 46/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 473707.3542 - calorie_loss: 473707.1875 - ingredient_vector_loss: 0.1986 - calorie_mse: 478855.0938 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00046: val_calorie_loss did not improve from 523559.93750\n",
      "34/34 [==============================] - 97s 3s/step - loss: 476235.2182 - calorie_loss: 476090.7812 - ingredient_vector_loss: 0.1986 - calorie_mse: 481139.2812 - ingredient_vector_mse: 0.0471 - val_loss: 528299.4062 - val_calorie_loss: 528299.1875 - val_ingredient_vector_loss: 0.1855 - val_calorie_mse: 526736.1250 - val_ingredient_vector_mse: 0.0423\n",
      "Epoch 47/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 484070.6629 - calorie_loss: 484070.5000 - ingredient_vector_loss: 0.2001 - calorie_mse: 489311.6250 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00047: val_calorie_loss improved from 523559.93750 to 522376.34375, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 97s 3s/step - loss: 485050.9894 - calorie_loss: 484905.0000 - ingredient_vector_loss: 0.2002 - calorie_mse: 490007.8438 - ingredient_vector_mse: 0.0472 - val_loss: 522376.4965 - val_calorie_loss: 522376.3438 - val_ingredient_vector_loss: 0.1862 - val_calorie_mse: 520862.0312 - val_ingredient_vector_mse: 0.0407\n",
      "Epoch 48/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 477098.9328 - calorie_loss: 477098.7188 - ingredient_vector_loss: 0.2004 - calorie_mse: 482120.3125 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00048: val_calorie_loss improved from 522376.34375 to 518992.84375, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 97s 3s/step - loss: 477182.8256 - calorie_loss: 477043.5000 - ingredient_vector_loss: 0.2003 - calorie_mse: 481912.6562 - ingredient_vector_mse: 0.0471 - val_loss: 518993.0382 - val_calorie_loss: 518992.8438 - val_ingredient_vector_loss: 0.1975 - val_calorie_mse: 517818.2188 - val_ingredient_vector_mse: 0.0454\n",
      "Epoch 49/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 481120.3963 - calorie_loss: 481120.1562 - ingredient_vector_loss: 0.2008 - calorie_mse: 486465.9375 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00049: val_calorie_loss did not improve from 518992.84375\n",
      "34/34 [==============================] - 96s 3s/step - loss: 479243.4212 - calorie_loss: 479096.3750 - ingredient_vector_loss: 0.2008 - calorie_mse: 484234.1875 - ingredient_vector_mse: 0.0472 - val_loss: 525193.2500 - val_calorie_loss: 525193.0625 - val_ingredient_vector_loss: 0.2047 - val_calorie_mse: 523085.6250 - val_ingredient_vector_mse: 0.0451\n",
      "Epoch 50/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 478809.2008 - calorie_loss: 478808.9375 - ingredient_vector_loss: 0.1991 - calorie_mse: 484443.0000 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00050: val_calorie_loss did not improve from 518992.84375\n",
      "34/34 [==============================] - 96s 3s/step - loss: 480039.7113 - calorie_loss: 479882.6250 - ingredient_vector_loss: 0.1991 - calorie_mse: 485372.1250 - ingredient_vector_mse: 0.0472 - val_loss: 522218.1632 - val_calorie_loss: 522217.9375 - val_ingredient_vector_loss: 0.1851 - val_calorie_mse: 519841.7188 - val_ingredient_vector_mse: 0.0416\n",
      "Epoch 51/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 477777.2652 - calorie_loss: 477777.0938 - ingredient_vector_loss: 0.1984 - calorie_mse: 482793.4375 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00051: val_calorie_loss did not improve from 518992.84375\n",
      "34/34 [==============================] - 96s 3s/step - loss: 475951.3228 - calorie_loss: 475813.4375 - ingredient_vector_loss: 0.1987 - calorie_mse: 480633.0938 - ingredient_vector_mse: 0.0471 - val_loss: 522747.7882 - val_calorie_loss: 522747.6250 - val_ingredient_vector_loss: 0.1931 - val_calorie_mse: 521027.5625 - val_ingredient_vector_mse: 0.0438\n",
      "Epoch 52/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 473645.1468 - calorie_loss: 473644.9688 - ingredient_vector_loss: 0.1989 - calorie_mse: 479061.8750 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00052: val_calorie_loss did not improve from 518992.84375\n",
      "34/34 [==============================] - 96s 3s/step - loss: 473712.0702 - calorie_loss: 473561.8125 - ingredient_vector_loss: 0.1988 - calorie_mse: 478813.7500 - ingredient_vector_mse: 0.0470 - val_loss: 519948.9271 - val_calorie_loss: 519948.7188 - val_ingredient_vector_loss: 0.1812 - val_calorie_mse: 518461.8438 - val_ingredient_vector_mse: 0.0407\n",
      "Epoch 53/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 472761.6283 - calorie_loss: 472761.4062 - ingredient_vector_loss: 0.1994 - calorie_mse: 478093.1250 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00053: val_calorie_loss improved from 518992.84375 to 516340.00000, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 97s 3s/step - loss: 473386.5247 - calorie_loss: 473238.2500 - ingredient_vector_loss: 0.1994 - calorie_mse: 478420.5938 - ingredient_vector_mse: 0.0471 - val_loss: 516340.2188 - val_calorie_loss: 516340.0000 - val_ingredient_vector_loss: 0.1780 - val_calorie_mse: 514588.8750 - val_ingredient_vector_mse: 0.0403\n",
      "Epoch 54/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 475167.0672 - calorie_loss: 475166.8438 - ingredient_vector_loss: 0.1978 - calorie_mse: 480625.1875 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00054: val_calorie_loss did not improve from 516340.00000\n",
      "34/34 [==============================] - 96s 3s/step - loss: 476523.3520 - calorie_loss: 476371.0625 - ingredient_vector_loss: 0.1980 - calorie_mse: 481693.1562 - ingredient_vector_mse: 0.0469 - val_loss: 520009.9306 - val_calorie_loss: 520009.7188 - val_ingredient_vector_loss: 0.1932 - val_calorie_mse: 517604.8750 - val_ingredient_vector_mse: 0.0411\n",
      "Epoch 55/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 472606.6757 - calorie_loss: 472606.5000 - ingredient_vector_loss: 0.1987 - calorie_mse: 478381.1250 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00055: val_calorie_loss improved from 516340.00000 to 514846.21875, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 97s 3s/step - loss: 473490.5321 - calorie_loss: 473329.8438 - ingredient_vector_loss: 0.1986 - calorie_mse: 478947.5000 - ingredient_vector_mse: 0.0468 - val_loss: 514846.4514 - val_calorie_loss: 514846.2188 - val_ingredient_vector_loss: 0.1850 - val_calorie_mse: 513385.7812 - val_ingredient_vector_mse: 0.0420\n",
      "Epoch 56/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 471952.5000 - calorie_loss: 471952.3750 - ingredient_vector_loss: 0.1986 - calorie_mse: 477082.3438 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00056: val_calorie_loss did not improve from 514846.21875\n",
      "34/34 [==============================] - 96s 3s/step - loss: 473014.3235 - calorie_loss: 472871.4062 - ingredient_vector_loss: 0.1988 - calorie_mse: 477868.4062 - ingredient_vector_mse: 0.0470 - val_loss: 517098.4306 - val_calorie_loss: 517098.2812 - val_ingredient_vector_loss: 0.1922 - val_calorie_mse: 515496.4375 - val_ingredient_vector_mse: 0.0423\n",
      "Epoch 57/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 474699.3049 - calorie_loss: 474699.0938 - ingredient_vector_loss: 0.1993 - calorie_mse: 479465.5312 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00057: val_calorie_loss did not improve from 514846.21875\n",
      "34/34 [==============================] - 96s 3s/step - loss: 474493.4742 - calorie_loss: 474361.4062 - ingredient_vector_loss: 0.1990 - calorie_mse: 478976.5312 - ingredient_vector_mse: 0.0469 - val_loss: 519934.0347 - val_calorie_loss: 519933.8438 - val_ingredient_vector_loss: 0.1724 - val_calorie_mse: 518827.4375 - val_ingredient_vector_mse: 0.0392\n",
      "Epoch 58/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 467522.0559 - calorie_loss: 467521.8750 - ingredient_vector_loss: 0.1993 - calorie_mse: 472300.2500 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00058: val_calorie_loss did not improve from 514846.21875\n",
      "34/34 [==============================] - 97s 3s/step - loss: 467788.2755 - calorie_loss: 467655.5938 - ingredient_vector_loss: 0.1992 - calorie_mse: 472293.2812 - ingredient_vector_mse: 0.0469 - val_loss: 523898.0868 - val_calorie_loss: 523897.8750 - val_ingredient_vector_loss: 0.1863 - val_calorie_mse: 521168.7188 - val_ingredient_vector_mse: 0.0408\n",
      "Epoch 59/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 471167.2008 - calorie_loss: 471166.9688 - ingredient_vector_loss: 0.1961 - calorie_mse: 476890.6562 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00059: val_calorie_loss did not improve from 514846.21875\n",
      "34/34 [==============================] - 90s 3s/step - loss: 471499.6822 - calorie_loss: 471340.7500 - ingredient_vector_loss: 0.1963 - calorie_mse: 476896.2188 - ingredient_vector_mse: 0.0467 - val_loss: 516386.2257 - val_calorie_loss: 516386.0625 - val_ingredient_vector_loss: 0.1850 - val_calorie_mse: 513993.1875 - val_ingredient_vector_mse: 0.0417\n",
      "Epoch 60/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 468515.8191 - calorie_loss: 468515.6250 - ingredient_vector_loss: 0.1966 - calorie_mse: 473702.9688 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00060: val_calorie_loss did not improve from 514846.21875\n",
      "34/34 [==============================] - 88s 3s/step - loss: 469602.3421 - calorie_loss: 469457.7812 - ingredient_vector_loss: 0.1968 - calorie_mse: 474510.9375 - ingredient_vector_mse: 0.0468 - val_loss: 518140.6181 - val_calorie_loss: 518140.4375 - val_ingredient_vector_loss: 0.1891 - val_calorie_mse: 516131.5312 - val_ingredient_vector_mse: 0.0427\n",
      "Epoch 61/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 470275.2467 - calorie_loss: 470275.0938 - ingredient_vector_loss: 0.1998 - calorie_mse: 475470.5000 - ingredient_vector_mse: 0.0472\n",
      "Epoch 00061: val_calorie_loss improved from 514846.21875 to 514129.78125, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 471746.1134 - calorie_loss: 471601.1250 - ingredient_vector_loss: 0.1995 - calorie_mse: 476671.0312 - ingredient_vector_mse: 0.0472 - val_loss: 514129.9479 - val_calorie_loss: 514129.7812 - val_ingredient_vector_loss: 0.1861 - val_calorie_mse: 512363.1250 - val_ingredient_vector_mse: 0.0411\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 62/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469098.9062 - calorie_loss: 469098.7188 - ingredient_vector_loss: 0.1973 - calorie_mse: 474021.5312 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00062: val_calorie_loss did not improve from 514129.78125\n",
      "34/34 [==============================] - 88s 3s/step - loss: 470187.3382 - calorie_loss: 470050.1250 - ingredient_vector_loss: 0.1976 - calorie_mse: 474846.9062 - ingredient_vector_mse: 0.0469 - val_loss: 519711.7986 - val_calorie_loss: 519711.6250 - val_ingredient_vector_loss: 0.1845 - val_calorie_mse: 516831.6250 - val_ingredient_vector_mse: 0.0422\n",
      "Epoch 63/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 471467.3925 - calorie_loss: 471467.2188 - ingredient_vector_loss: 0.1990 - calorie_mse: 477030.0312 - ingredient_vector_mse: 0.0471\n",
      "Epoch 00063: val_calorie_loss did not improve from 514129.78125\n",
      "34/34 [==============================] - 88s 3s/step - loss: 469711.4486 - calorie_loss: 469558.3750 - ingredient_vector_loss: 0.1987 - calorie_mse: 474909.3438 - ingredient_vector_mse: 0.0471 - val_loss: 519008.0799 - val_calorie_loss: 519007.8750 - val_ingredient_vector_loss: 0.1906 - val_calorie_mse: 516672.2812 - val_ingredient_vector_mse: 0.0414\n",
      "Epoch 64/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 467778.3622 - calorie_loss: 467778.1562 - ingredient_vector_loss: 0.1976 - calorie_mse: 473040.8750 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00064: val_calorie_loss did not improve from 514129.78125\n",
      "34/34 [==============================] - 88s 3s/step - loss: 468309.7150 - calorie_loss: 468163.4062 - ingredient_vector_loss: 0.1977 - calorie_mse: 473276.7188 - ingredient_vector_mse: 0.0468 - val_loss: 517710.7674 - val_calorie_loss: 517710.6250 - val_ingredient_vector_loss: 0.1852 - val_calorie_mse: 515165.6250 - val_ingredient_vector_mse: 0.0419\n",
      "Epoch 65/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 464599.8362 - calorie_loss: 464599.5938 - ingredient_vector_loss: 0.1965 - calorie_mse: 469304.4688 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00065: val_calorie_loss improved from 514129.78125 to 513437.34375, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 464870.8503 - calorie_loss: 464740.1562 - ingredient_vector_loss: 0.1962 - calorie_mse: 469306.6875 - ingredient_vector_mse: 0.0468 - val_loss: 513437.5799 - val_calorie_loss: 513437.3438 - val_ingredient_vector_loss: 0.1763 - val_calorie_mse: 512415.4375 - val_ingredient_vector_mse: 0.0398\n",
      "Epoch 66/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 476478.6222 - calorie_loss: 476478.4375 - ingredient_vector_loss: 0.1961 - calorie_mse: 476478.4375 - ingredient_vector_mse: 0.0466\n",
      "Epoch 00066: val_calorie_loss did not improve from 513437.34375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 470834.2356 - calorie_loss: 470707.3750 - ingredient_vector_loss: 0.1966 - calorie_mse: 475140.4688 - ingredient_vector_mse: 0.0466 - val_loss: 519405.4028 - val_calorie_loss: 519405.2188 - val_ingredient_vector_loss: 0.1765 - val_calorie_mse: 516748.4062 - val_ingredient_vector_mse: 0.0397\n",
      "Epoch 67/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 464347.5705 - calorie_loss: 464347.4375 - ingredient_vector_loss: 0.1984 - calorie_mse: 469256.9375 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00067: val_calorie_loss did not improve from 513437.34375\n",
      "34/34 [==============================] - 89s 3s/step - loss: 464124.7405 - calorie_loss: 463988.7812 - ingredient_vector_loss: 0.1981 - calorie_mse: 468742.1875 - ingredient_vector_mse: 0.0469 - val_loss: 517025.3819 - val_calorie_loss: 517025.2188 - val_ingredient_vector_loss: 0.1815 - val_calorie_mse: 513970.6250 - val_ingredient_vector_mse: 0.0396\n",
      "Epoch 68/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 466443.9498 - calorie_loss: 466443.7188 - ingredient_vector_loss: 0.1981 - calorie_mse: 471940.0938 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00068: val_calorie_loss did not improve from 513437.34375\n",
      "34/34 [==============================] - 88s 3s/step - loss: 464975.2353 - calorie_loss: 464823.7500 - ingredient_vector_loss: 0.1980 - calorie_mse: 470117.0000 - ingredient_vector_mse: 0.0469 - val_loss: 518677.2465 - val_calorie_loss: 518677.0625 - val_ingredient_vector_loss: 0.1876 - val_calorie_mse: 516050.7500 - val_ingredient_vector_mse: 0.0422\n",
      "Epoch 69/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 467242.3935 - calorie_loss: 467242.2500 - ingredient_vector_loss: 0.1969 - calorie_mse: 473162.3438 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00069: val_calorie_loss did not improve from 513437.34375\n",
      "34/34 [==============================] - 88s 3s/step - loss: 466219.4905 - calorie_loss: 466056.0625 - ingredient_vector_loss: 0.1970 - calorie_mse: 471770.3750 - ingredient_vector_mse: 0.0469 - val_loss: 523736.3785 - val_calorie_loss: 523736.1562 - val_ingredient_vector_loss: 0.1835 - val_calorie_mse: 521185.5938 - val_ingredient_vector_mse: 0.0412\n",
      "Epoch 70/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 476050.8314 - calorie_loss: 476050.6562 - ingredient_vector_loss: 0.1954 - calorie_mse: 476050.6562 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00070: val_calorie_loss did not improve from 513437.34375\n",
      "34/34 [==============================] - 88s 3s/step - loss: 468752.1517 - calorie_loss: 468588.2188 - ingredient_vector_loss: 0.1958 - calorie_mse: 474320.5938 - ingredient_vector_mse: 0.0468 - val_loss: 520502.4757 - val_calorie_loss: 520502.2812 - val_ingredient_vector_loss: 0.1777 - val_calorie_mse: 518169.3125 - val_ingredient_vector_mse: 0.0401\n",
      "Epoch 71/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 464939.8106 - calorie_loss: 464939.6250 - ingredient_vector_loss: 0.1975 - calorie_mse: 469730.0938 - ingredient_vector_mse: 0.0470\n",
      "Epoch 00071: val_calorie_loss improved from 513437.34375 to 508627.12500, saving model to ./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 465337.5858 - calorie_loss: 465204.4688 - ingredient_vector_loss: 0.1977 - calorie_mse: 469856.9062 - ingredient_vector_mse: 0.0470 - val_loss: 508627.3333 - val_calorie_loss: 508627.1250 - val_ingredient_vector_loss: 0.1917 - val_calorie_mse: 507404.4375 - val_ingredient_vector_mse: 0.0436\n",
      "Epoch 72/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 464741.9957 - calorie_loss: 464741.6875 - ingredient_vector_loss: 0.1960 - calorie_mse: 470610.6562 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00072: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 88s 3s/step - loss: 464822.8986 - calorie_loss: 464660.0312 - ingredient_vector_loss: 0.1962 - calorie_mse: 470350.4688 - ingredient_vector_mse: 0.0468 - val_loss: 516037.6667 - val_calorie_loss: 516037.4375 - val_ingredient_vector_loss: 0.1855 - val_calorie_mse: 513459.3750 - val_ingredient_vector_mse: 0.0414\n",
      "Epoch 73/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 465187.9877 - calorie_loss: 465187.8125 - ingredient_vector_loss: 0.1974 - calorie_mse: 470035.5625 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00073: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 88s 3s/step - loss: 464344.1933 - calorie_loss: 464210.3125 - ingredient_vector_loss: 0.1976 - calorie_mse: 468889.4062 - ingredient_vector_mse: 0.0470 - val_loss: 515019.0903 - val_calorie_loss: 515018.8750 - val_ingredient_vector_loss: 0.1827 - val_calorie_mse: 512522.6250 - val_ingredient_vector_mse: 0.0402\n",
      "Epoch 74/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 460369.8854 - calorie_loss: 460369.6562 - ingredient_vector_loss: 0.1966 - calorie_mse: 464875.1250 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00074: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 89s 3s/step - loss: 461018.0712 - calorie_loss: 460892.6562 - ingredient_vector_loss: 0.1962 - calorie_mse: 465274.6875 - ingredient_vector_mse: 0.0467 - val_loss: 524600.3542 - val_calorie_loss: 524600.1875 - val_ingredient_vector_loss: 0.1839 - val_calorie_mse: 523069.9688 - val_ingredient_vector_mse: 0.0412\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 75/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 464550.3973 - calorie_loss: 464550.1875 - ingredient_vector_loss: 0.1961 - calorie_mse: 470022.9375 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00075: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 88s 3s/step - loss: 465592.9664 - calorie_loss: 465440.5000 - ingredient_vector_loss: 0.1963 - calorie_mse: 470769.2812 - ingredient_vector_mse: 0.0467 - val_loss: 517829.4861 - val_calorie_loss: 517829.3438 - val_ingredient_vector_loss: 0.1807 - val_calorie_mse: 515577.5625 - val_ingredient_vector_mse: 0.0401\n",
      "Epoch 76/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 462953.7827 - calorie_loss: 462953.5312 - ingredient_vector_loss: 0.1951 - calorie_mse: 467914.9688 - ingredient_vector_mse: 0.0465\n",
      "Epoch 00076: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 88s 3s/step - loss: 463281.5552 - calorie_loss: 463143.7188 - ingredient_vector_loss: 0.1952 - calorie_mse: 467960.2500 - ingredient_vector_mse: 0.0466 - val_loss: 527278.4965 - val_calorie_loss: 527278.2500 - val_ingredient_vector_loss: 0.1863 - val_calorie_mse: 524158.0625 - val_ingredient_vector_mse: 0.0424\n",
      "Epoch 77/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 460708.3343 - calorie_loss: 460708.2188 - ingredient_vector_loss: 0.1959 - calorie_mse: 465642.5312 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00077: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 461362.9577 - calorie_loss: 461225.7500 - ingredient_vector_loss: 0.1960 - calorie_mse: 466023.6250 - ingredient_vector_mse: 0.0467 - val_loss: 525081.7361 - val_calorie_loss: 525081.5625 - val_ingredient_vector_loss: 0.1886 - val_calorie_mse: 523041.4375 - val_ingredient_vector_mse: 0.0426\n",
      "Epoch 78/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 473571.0540 - calorie_loss: 473570.8750 - ingredient_vector_loss: 0.1959 - calorie_mse: 473570.8750 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00078: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 97s 3s/step - loss: 471254.7776 - calorie_loss: 471254.5938 - ingredient_vector_loss: 0.1958 - calorie_mse: 471254.5938 - ingredient_vector_mse: 0.0467 - val_loss: 514883.3056 - val_calorie_loss: 514883.1250 - val_ingredient_vector_loss: 0.1813 - val_calorie_mse: 512722.3438 - val_ingredient_vector_mse: 0.0401\n",
      "Epoch 79/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 463142.8499 - calorie_loss: 463142.6250 - ingredient_vector_loss: 0.1954 - calorie_mse: 468168.0938 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00079: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 464067.2201 - calorie_loss: 463927.2500 - ingredient_vector_loss: 0.1957 - calorie_mse: 468819.6875 - ingredient_vector_mse: 0.0468 - val_loss: 520825.4722 - val_calorie_loss: 520825.2812 - val_ingredient_vector_loss: 0.1813 - val_calorie_mse: 518256.8125 - val_ingredient_vector_mse: 0.0405\n",
      "Epoch 80/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 461933.0431 - calorie_loss: 461932.8125 - ingredient_vector_loss: 0.1953 - calorie_mse: 467281.0312 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00080: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 461340.2295 - calorie_loss: 461192.2812 - ingredient_vector_loss: 0.1956 - calorie_mse: 466362.2812 - ingredient_vector_mse: 0.0468 - val_loss: 523095.5938 - val_calorie_loss: 523095.3750 - val_ingredient_vector_loss: 0.1812 - val_calorie_mse: 520176.6250 - val_ingredient_vector_mse: 0.0409\n",
      "Epoch 81/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 457516.7940 - calorie_loss: 457516.5938 - ingredient_vector_loss: 0.1951 - calorie_mse: 463243.4062 - ingredient_vector_mse: 0.0466\n",
      "Epoch 00081: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 460069.3623 - calorie_loss: 459908.8750 - ingredient_vector_loss: 0.1951 - calorie_mse: 465519.0312 - ingredient_vector_mse: 0.0466 - val_loss: 518793.0486 - val_calorie_loss: 518792.8750 - val_ingredient_vector_loss: 0.1838 - val_calorie_mse: 515437.2500 - val_ingredient_vector_mse: 0.0429\n",
      "Epoch 82/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 465766.8262 - calorie_loss: 465766.5625 - ingredient_vector_loss: 0.1944 - calorie_mse: 470821.1875 - ingredient_vector_mse: 0.0466\n",
      "Epoch 00082: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 465388.0795 - calorie_loss: 465248.1250 - ingredient_vector_loss: 0.1948 - calorie_mse: 470138.5312 - ingredient_vector_mse: 0.0467 - val_loss: 517048.1424 - val_calorie_loss: 517047.9375 - val_ingredient_vector_loss: 0.1845 - val_calorie_mse: 514608.0938 - val_ingredient_vector_mse: 0.0412\n",
      "Epoch 83/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 459474.9110 - calorie_loss: 459474.7188 - ingredient_vector_loss: 0.1962 - calorie_mse: 464181.0000 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00083: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 458910.4505 - calorie_loss: 458780.3125 - ingredient_vector_loss: 0.1964 - calorie_mse: 463328.7812 - ingredient_vector_mse: 0.0470 - val_loss: 515254.5486 - val_calorie_loss: 515254.3438 - val_ingredient_vector_loss: 0.1845 - val_calorie_mse: 513325.0625 - val_ingredient_vector_mse: 0.0419\n",
      "Epoch 84/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 460392.0284 - calorie_loss: 460391.8750 - ingredient_vector_loss: 0.1957 - calorie_mse: 465693.4688 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00084: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 458898.9966 - calorie_loss: 458753.0312 - ingredient_vector_loss: 0.1957 - calorie_mse: 463856.9062 - ingredient_vector_mse: 0.0467 - val_loss: 515202.9722 - val_calorie_loss: 515202.8438 - val_ingredient_vector_loss: 0.1773 - val_calorie_mse: 511426.1562 - val_ingredient_vector_mse: 0.0405\n",
      "Epoch 85/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 454820.9564 - calorie_loss: 454820.7500 - ingredient_vector_loss: 0.1954 - calorie_mse: 460352.8125 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00085: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 456290.2211 - calorie_loss: 456135.8438 - ingredient_vector_loss: 0.1954 - calorie_mse: 461532.0312 - ingredient_vector_mse: 0.0467 - val_loss: 516232.2153 - val_calorie_loss: 516232.0000 - val_ingredient_vector_loss: 0.1919 - val_calorie_mse: 513037.9688 - val_ingredient_vector_mse: 0.0418\n",
      "Epoch 86/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 458556.0890 - calorie_loss: 458555.9062 - ingredient_vector_loss: 0.1959 - calorie_mse: 462964.3125 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00086: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 458002.9499 - calorie_loss: 457881.0625 - ingredient_vector_loss: 0.1959 - calorie_mse: 462141.0625 - ingredient_vector_mse: 0.0467 - val_loss: 510876.6806 - val_calorie_loss: 510876.5000 - val_ingredient_vector_loss: 0.1902 - val_calorie_mse: 507500.7812 - val_ingredient_vector_mse: 0.0418\n",
      "Epoch 87/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 455461.9053 - calorie_loss: 455461.7812 - ingredient_vector_loss: 0.1962 - calorie_mse: 460741.0312 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00087: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 454057.8464 - calorie_loss: 453912.4688 - ingredient_vector_loss: 0.1961 - calorie_mse: 458996.7812 - ingredient_vector_mse: 0.0468 - val_loss: 517224.4167 - val_calorie_loss: 517224.2188 - val_ingredient_vector_loss: 0.1855 - val_calorie_mse: 513818.3750 - val_ingredient_vector_mse: 0.0399\n",
      "Epoch 88/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 457216.9134 - calorie_loss: 457216.7188 - ingredient_vector_loss: 0.1963 - calorie_mse: 462746.3438 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00088: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 457555.1528 - calorie_loss: 457401.6250 - ingredient_vector_loss: 0.1964 - calorie_mse: 462769.1250 - ingredient_vector_mse: 0.0468 - val_loss: 513472.1424 - val_calorie_loss: 513471.9375 - val_ingredient_vector_loss: 0.1795 - val_calorie_mse: 512011.8125 - val_ingredient_vector_mse: 0.0396\n",
      "Epoch 89/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 460294.6676 - calorie_loss: 460294.4375 - ingredient_vector_loss: 0.1964 - calorie_mse: 464975.2500 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00089: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 458529.7990 - calorie_loss: 458401.1250 - ingredient_vector_loss: 0.1962 - calorie_mse: 462897.0000 - ingredient_vector_mse: 0.0468 - val_loss: 517119.4340 - val_calorie_loss: 517119.2188 - val_ingredient_vector_loss: 0.1853 - val_calorie_mse: 514515.9375 - val_ingredient_vector_mse: 0.0426\n",
      "Epoch 90/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 458444.2760 - calorie_loss: 458444.0625 - ingredient_vector_loss: 0.1958 - calorie_mse: 464243.1250 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00090: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 456341.4825 - calorie_loss: 456182.0625 - ingredient_vector_loss: 0.1958 - calorie_mse: 461753.9375 - ingredient_vector_mse: 0.0467 - val_loss: 518189.6424 - val_calorie_loss: 518189.4375 - val_ingredient_vector_loss: 0.1832 - val_calorie_mse: 515618.7812 - val_ingredient_vector_mse: 0.0409\n",
      "Epoch 91/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 458559.6468 - calorie_loss: 458559.5000 - ingredient_vector_loss: 0.1974 - calorie_mse: 464086.5312 - ingredient_vector_mse: 0.0468\n",
      "Epoch 00091: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 95s 3s/step - loss: 460769.4893 - calorie_loss: 460614.7812 - ingredient_vector_loss: 0.1975 - calorie_mse: 466023.3438 - ingredient_vector_mse: 0.0468 - val_loss: 509649.1875 - val_calorie_loss: 509649.0000 - val_ingredient_vector_loss: 0.1900 - val_calorie_mse: 507475.4062 - val_ingredient_vector_mse: 0.0432\n",
      "Epoch 92/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 451714.4152 - calorie_loss: 451714.2812 - ingredient_vector_loss: 0.1967 - calorie_mse: 457827.0625 - ingredient_vector_mse: 0.0469\n",
      "Epoch 00092: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 95s 3s/step - loss: 453162.8378 - calorie_loss: 452992.4375 - ingredient_vector_loss: 0.1963 - calorie_mse: 458951.0000 - ingredient_vector_mse: 0.0467 - val_loss: 518644.4931 - val_calorie_loss: 518644.2812 - val_ingredient_vector_loss: 0.1858 - val_calorie_mse: 515210.5938 - val_ingredient_vector_mse: 0.0424\n",
      "Epoch 93/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 450444.7060 - calorie_loss: 450444.5000 - ingredient_vector_loss: 0.1948 - calorie_mse: 455887.9688 - ingredient_vector_mse: 0.0465\n",
      "Epoch 00093: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 95s 3s/step - loss: 451881.9304 - calorie_loss: 451730.0000 - ingredient_vector_loss: 0.1949 - calorie_mse: 457039.5625 - ingredient_vector_mse: 0.0466 - val_loss: 516063.7847 - val_calorie_loss: 516063.6250 - val_ingredient_vector_loss: 0.1903 - val_calorie_mse: 512913.4062 - val_ingredient_vector_mse: 0.0442\n",
      "Epoch 94/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 459245.1993 - calorie_loss: 459245.0938 - ingredient_vector_loss: 0.1947 - calorie_mse: 464584.6250 - ingredient_vector_mse: 0.0465\n",
      "Epoch 00094: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 95s 3s/step - loss: 459493.7256 - calorie_loss: 459345.5938 - ingredient_vector_loss: 0.1950 - calorie_mse: 464526.7500 - ingredient_vector_mse: 0.0466 - val_loss: 510627.7743 - val_calorie_loss: 510627.5625 - val_ingredient_vector_loss: 0.1889 - val_calorie_mse: 508566.7812 - val_ingredient_vector_mse: 0.0427\n",
      "Epoch 95/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 451829.5346 - calorie_loss: 451829.4375 - ingredient_vector_loss: 0.1949 - calorie_mse: 458006.1875 - ingredient_vector_mse: 0.0466\n",
      "Epoch 00095: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 95s 3s/step - loss: 454291.7953 - calorie_loss: 454119.0000 - ingredient_vector_loss: 0.1948 - calorie_mse: 460163.1562 - ingredient_vector_mse: 0.0466 - val_loss: 519896.0694 - val_calorie_loss: 519895.8750 - val_ingredient_vector_loss: 0.1835 - val_calorie_mse: 516393.1562 - val_ingredient_vector_mse: 0.0419\n",
      "Epoch 96/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 456170.0341 - calorie_loss: 456169.8438 - ingredient_vector_loss: 0.1940 - calorie_mse: 461252.2812 - ingredient_vector_mse: 0.0465\n",
      "Epoch 00096: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 458577.6916 - calorie_loss: 458435.1562 - ingredient_vector_loss: 0.1942 - calorie_mse: 463417.3438 - ingredient_vector_mse: 0.0465 - val_loss: 519146.4757 - val_calorie_loss: 519146.2812 - val_ingredient_vector_loss: 0.1847 - val_calorie_mse: 516029.9688 - val_ingredient_vector_mse: 0.0413\n",
      "Epoch 97/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 458920.7917 - calorie_loss: 458920.5625 - ingredient_vector_loss: 0.1957 - calorie_mse: 464249.2188 - ingredient_vector_mse: 0.0466\n",
      "Epoch 00097: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 95s 3s/step - loss: 459776.8250 - calorie_loss: 459628.4688 - ingredient_vector_loss: 0.1957 - calorie_mse: 464813.2188 - ingredient_vector_mse: 0.0466 - val_loss: 522818.4236 - val_calorie_loss: 522818.2188 - val_ingredient_vector_loss: 0.1810 - val_calorie_mse: 519907.6562 - val_ingredient_vector_mse: 0.0404\n",
      "Epoch 98/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 454240.6037 - calorie_loss: 454240.4375 - ingredient_vector_loss: 0.1958 - calorie_mse: 459327.1250 - ingredient_vector_mse: 0.0467\n",
      "Epoch 00098: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 95s 3s/step - loss: 455859.0184 - calorie_loss: 455716.8750 - ingredient_vector_loss: 0.1958 - calorie_mse: 460684.8438 - ingredient_vector_mse: 0.0467 - val_loss: 518240.6840 - val_calorie_loss: 518240.5000 - val_ingredient_vector_loss: 0.1859 - val_calorie_mse: 516229.8438 - val_ingredient_vector_mse: 0.0428\n",
      "Epoch 99/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 453503.0246 - calorie_loss: 453502.8125 - ingredient_vector_loss: 0.1942 - calorie_mse: 459419.7500 - ingredient_vector_mse: 0.0466\n",
      "Epoch 00099: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 95s 3s/step - loss: 454673.1265 - calorie_loss: 454508.2812 - ingredient_vector_loss: 0.1943 - calorie_mse: 460270.5312 - ingredient_vector_mse: 0.0466 - val_loss: 517856.3542 - val_calorie_loss: 517856.1562 - val_ingredient_vector_loss: 0.1766 - val_calorie_mse: 513782.8750 - val_ingredient_vector_mse: 0.0396\n",
      "Epoch 100/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 460333.4522 - calorie_loss: 460333.3438 - ingredient_vector_loss: 0.1936 - calorie_mse: 465398.6875 - ingredient_vector_mse: 0.0465\n",
      "Epoch 00100: val_calorie_loss did not improve from 508627.12500\n",
      "34/34 [==============================] - 95s 3s/step - loss: 461079.9182 - calorie_loss: 460939.0312 - ingredient_vector_loss: 0.1938 - calorie_mse: 465866.0312 - ingredient_vector_mse: 0.0465 - val_loss: 521591.8194 - val_calorie_loss: 521591.6562 - val_ingredient_vector_loss: 0.1863 - val_calorie_mse: 519409.2188 - val_ingredient_vector_mse: 0.0422\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.optimizers import Adam\n",
    "from tensorflow.keras.callbacks import ModelCheckpoint\n",
    "from tensorflow.keras import metrics\n",
    "\n",
    "model.compile(optimizer=Adam(lr=1e-3), loss={'calorie':'mse', 'ingredient_vector':'binary_crossentropy'}\n",
    "              , metrics=['mse'])\n",
    "\n",
    "checkpointer = ModelCheckpoint(filepath='./multi-output/ingredients/recipe_ingredient_vector_100epoch.h5', verbose=1, \n",
    "                               monitor='val_calorie_loss', mode='auto', save_best_only=True)\n",
    "\n",
    "history = model.fit_generator(generator=train_generator, \n",
    "                    steps_per_epoch=round(train_generator.n/train_generator.batch_size),\n",
    "                    epochs=100,\n",
    "                    validation_data=valid_generator,\n",
    "                    validation_steps=round(valid_generator.n/valid_generator.batch_size),\n",
    "                    callbacks=[checkpointer]\n",
    "                   )\n",
    "\n",
    "\n",
    "with open('./multi-output/ingredients/recipe_ingredient_vector_100epoch.pkl','wb') as f:\n",
    "    pickle.dump(history.history, f) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3. output: calorie+nutrient vecotr (fat, carbs, protein)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 4333 validated image filenames.\n",
      "Found 1083 validated image filenames.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/uceezku/project/lib64/python3.6/site-packages/keras_preprocessing/image/dataframe_iterator.py:282: UserWarning: Found 6 invalid image filename(s) in x_col=\"file_name\". These filename(s) will be ignored.\n",
      "  .format(n_invalid, x_col)\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "\n",
    "datagen=ImageDataGenerator(\n",
    "    #rescale=1/255, \n",
    "    validation_split=0.2, \n",
    "    rotation_range=20,\n",
    "    width_shift_range=0.2,\n",
    "    height_shift_range=0.2,\n",
    "    horizontal_flip=True,\n",
    "    )\n",
    "\n",
    "train_generator = datagen.flow_from_dataframe(\n",
    "    dataframe=train_data,\n",
    "    directory='./data/train/',\n",
    "    target_size = (256,256),\n",
    "    x_col='file_name',\n",
    "    y_col= ['calorie_per_recipe', 'nutrient_vector'],\n",
    "    batch_size=128,\n",
    "    shuffle=True,\n",
    "    subset='training',\n",
    "    class_mode='multi_output')\n",
    "\n",
    "\n",
    "valid_generator = datagen.flow_from_dataframe(\n",
    "    dataframe=train_data,\n",
    "    directory='./data/train/',\n",
    "    target_size = (256,256),\n",
    "    x_col='file_name',\n",
    "    y_col= ['calorie_per_recipe', 'nutrient_vector'],\n",
    "    batch_size=128,\n",
    "    shuffle=True,\n",
    "    subset='validation',\n",
    "    class_mode='multi_output')\n",
    "    #validate_filenames=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-5-82ba74ecadda>:18: Model.fit_generator (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use Model.fit, which supports generators.\n",
      "Train for 34 steps, validate for 8 steps\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/uceezku/project/lib64/python3.6/site-packages/PIL/Image.py:963: UserWarning: Palette images with Transparency expressed in bytes should be converted to RGBA images\n",
      "  \"Palette images with Transparency expressed in bytes should be \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33/34 [============================>.] - ETA: 2s - loss: 2323837.6970 - calorie_loss: 2307693.5000 - nutrient_vector_loss: 16144.3652 - calorie_mse: 2307168.0000 - nutrient_vector_mse: 16155.1885\n",
      "Epoch 00001: val_calorie_loss improved from inf to 2585427.75000, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 2304571.9711 - calorie_loss: 2288765.2500 - nutrient_vector_loss: 15823.7061 - calorie_mse: 2288172.0000 - nutrient_vector_mse: 15832.8027 - val_loss: 2594349.6250 - val_calorie_loss: 2585427.7500 - val_nutrient_vector_loss: 8921.9316 - val_calorie_mse: 2585427.7500 - val_nutrient_vector_mse: 8921.9316\n",
      "Epoch 2/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 1600368.4091 - calorie_loss: 1589396.5000 - nutrient_vector_loss: 10972.1016 - calorie_mse: 1589396.5000 - nutrient_vector_mse: 10972.1016\n",
      "Epoch 00002: val_calorie_loss improved from 2585427.75000 to 1719161.87500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 1586952.3115 - calorie_loss: 1576071.0000 - nutrient_vector_loss: 10825.7148 - calorie_mse: 1577999.3750 - nutrient_vector_mse: 10846.8975 - val_loss: 1725369.4844 - val_calorie_loss: 1719161.8750 - val_nutrient_vector_loss: 6207.6982 - val_calorie_mse: 1719161.8750 - val_nutrient_vector_mse: 6207.6982\n",
      "Epoch 3/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 878112.4205 - calorie_loss: 867353.6250 - nutrient_vector_loss: 10758.7344 - calorie_mse: 868288.1875 - nutrient_vector_mse: 10780.8398\n",
      "Epoch 00003: val_calorie_loss improved from 1719161.87500 to 998859.62500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 870095.9330 - calorie_loss: 859456.5000 - nutrient_vector_loss: 10613.9219 - calorie_mse: 860328.8125 - nutrient_vector_mse: 10634.7393 - val_loss: 1005682.5000 - val_calorie_loss: 998859.6250 - val_nutrient_vector_loss: 6822.9043 - val_calorie_mse: 998859.6250 - val_nutrient_vector_mse: 6822.9043\n",
      "Epoch 4/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 580244.2860 - calorie_loss: 569458.3750 - nutrient_vector_loss: 10785.9717 - calorie_mse: 569302.9375 - nutrient_vector_mse: 10809.4229\n",
      "Epoch 00004: val_calorie_loss improved from 998859.62500 to 751579.00000, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 577086.0837 - calorie_loss: 566490.6250 - nutrient_vector_loss: 10599.5400 - calorie_mse: 566326.8125 - nutrient_vector_mse: 10621.4814 - val_loss: 758157.0469 - val_calorie_loss: 751579.0000 - val_nutrient_vector_loss: 6578.0674 - val_calorie_mse: 751579.0000 - val_nutrient_vector_mse: 6578.0674\n",
      "Epoch 5/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 556366.4034 - calorie_loss: 545472.4375 - nutrient_vector_loss: 10894.0732 - calorie_mse: 545103.6250 - nutrient_vector_mse: 10916.0938\n",
      "Epoch 00005: val_calorie_loss improved from 751579.00000 to 712367.25000, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 556626.1313 - calorie_loss: 545916.3125 - nutrient_vector_loss: 10719.5059 - calorie_mse: 545560.3125 - nutrient_vector_mse: 10740.1104 - val_loss: 719150.1875 - val_calorie_loss: 712367.2500 - val_nutrient_vector_loss: 6782.9673 - val_calorie_mse: 712367.2500 - val_nutrient_vector_mse: 6782.9673\n",
      "Epoch 6/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 554647.5038 - calorie_loss: 543897.2500 - nutrient_vector_loss: 10750.2344 - calorie_mse: 543767.5625 - nutrient_vector_mse: 10772.4844\n",
      "Epoch 00006: val_calorie_loss did not improve from 712367.25000\n",
      "34/34 [==============================] - 90s 3s/step - loss: 555027.4918 - calorie_loss: 544444.0000 - nutrient_vector_loss: 10586.4053 - calorie_mse: 544320.5000 - nutrient_vector_mse: 10607.2803 - val_loss: 725720.5078 - val_calorie_loss: 719148.1875 - val_nutrient_vector_loss: 6572.2954 - val_calorie_mse: 719148.1875 - val_nutrient_vector_mse: 6572.2954\n",
      "Epoch 7/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 554726.3731 - calorie_loss: 544041.1875 - nutrient_vector_loss: 10685.1562 - calorie_mse: 543875.8750 - nutrient_vector_mse: 10707.8213\n",
      "Epoch 00007: val_calorie_loss did not improve from 712367.25000\n",
      "34/34 [==============================] - 91s 3s/step - loss: 554239.9800 - calorie_loss: 543712.5000 - nutrient_vector_loss: 10531.5498 - calorie_mse: 543550.5625 - nutrient_vector_mse: 10552.8711 - val_loss: 726220.1094 - val_calorie_loss: 719315.1875 - val_nutrient_vector_loss: 6904.9150 - val_calorie_mse: 719315.1875 - val_nutrient_vector_mse: 6904.9150\n",
      "Epoch 8/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 553735.5502 - calorie_loss: 543135.4375 - nutrient_vector_loss: 10600.0811 - calorie_mse: 543008.1250 - nutrient_vector_mse: 10622.4746\n",
      "Epoch 00008: val_calorie_loss improved from 712367.25000 to 710795.25000, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 553721.2875 - calorie_loss: 543262.7500 - nutrient_vector_loss: 10461.4385 - calorie_mse: 543139.7500 - nutrient_vector_mse: 10482.5615 - val_loss: 717180.0938 - val_calorie_loss: 710795.2500 - val_nutrient_vector_loss: 6384.8389 - val_calorie_mse: 710795.2500 - val_nutrient_vector_mse: 6384.8389\n",
      "Epoch 9/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 548394.0009 - calorie_loss: 537873.3125 - nutrient_vector_loss: 10520.6094 - calorie_mse: 537747.0625 - nutrient_vector_mse: 10543.4766\n",
      "Epoch 00009: val_calorie_loss improved from 710795.25000 to 706389.06250, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 551874.3529 - calorie_loss: 541478.1875 - nutrient_vector_loss: 10398.5615 - calorie_mse: 541371.4375 - nutrient_vector_mse: 10420.2178 - val_loss: 713050.9141 - val_calorie_loss: 706389.0625 - val_nutrient_vector_loss: 6661.8257 - val_calorie_mse: 706389.0625 - val_nutrient_vector_mse: 6661.8257\n",
      "Epoch 10/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 551591.6108 - calorie_loss: 541069.7500 - nutrient_vector_loss: 10521.8389 - calorie_mse: 540887.0000 - nutrient_vector_mse: 10543.5674\n",
      "Epoch 00010: val_calorie_loss improved from 706389.06250 to 706219.87500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 551580.6245 - calorie_loss: 541214.5000 - nutrient_vector_loss: 10370.5811 - calorie_mse: 541037.7500 - nutrient_vector_mse: 10391.0039 - val_loss: 712793.8438 - val_calorie_loss: 706219.8750 - val_nutrient_vector_loss: 6573.9443 - val_calorie_mse: 706219.8750 - val_nutrient_vector_mse: 6573.9443\n",
      "Epoch 11/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 548627.7405 - calorie_loss: 538160.5625 - nutrient_vector_loss: 10467.1719 - calorie_mse: 538070.8750 - nutrient_vector_mse: 10490.0713\n",
      "Epoch 00011: val_calorie_loss improved from 706219.87500 to 692955.37500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 548876.9051 - calorie_loss: 538577.3750 - nutrient_vector_loss: 10301.3672 - calorie_mse: 538492.1875 - nutrient_vector_mse: 10322.8633 - val_loss: 699566.6094 - val_calorie_loss: 692955.3750 - val_nutrient_vector_loss: 6611.1855 - val_calorie_mse: 692955.3750 - val_nutrient_vector_mse: 6611.1855\n",
      "Epoch 12/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 538045.8665 - calorie_loss: 532595.1875 - nutrient_vector_loss: 5450.6582 - calorie_mse: 532540.5625 - nutrient_vector_mse: 5450.5825\n",
      "Epoch 00012: val_calorie_loss improved from 692955.37500 to 688841.75000, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 542467.4666 - calorie_loss: 532177.2500 - nutrient_vector_loss: 10291.1748 - calorie_mse: 532122.3750 - nutrient_vector_mse: 10312.3271 - val_loss: 695435.1953 - val_calorie_loss: 688841.7500 - val_nutrient_vector_loss: 6593.4233 - val_calorie_mse: 688841.7500 - val_nutrient_vector_mse: 6593.4233\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 538678.7121 - calorie_loss: 533243.5000 - nutrient_vector_loss: 5435.2192 - calorie_mse: 533187.3125 - nutrient_vector_mse: 5435.2666\n",
      "Epoch 00013: val_calorie_loss improved from 688841.75000 to 677861.75000, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 543601.8866 - calorie_loss: 533324.3750 - nutrient_vector_loss: 10278.5059 - calorie_mse: 533270.1250 - nutrient_vector_mse: 10299.7891 - val_loss: 684405.3750 - val_calorie_loss: 677861.7500 - val_nutrient_vector_loss: 6543.5859 - val_calorie_mse: 677861.7500 - val_nutrient_vector_mse: 6543.5859\n",
      "Epoch 14/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 544505.5805 - calorie_loss: 534093.7500 - nutrient_vector_loss: 10411.8877 - calorie_mse: 534029.2500 - nutrient_vector_mse: 10434.0127\n",
      "Epoch 00014: val_calorie_loss improved from 677861.75000 to 675227.87500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 543588.7004 - calorie_loss: 533310.5000 - nutrient_vector_loss: 10279.5098 - calorie_mse: 533244.5000 - nutrient_vector_mse: 10300.4014 - val_loss: 681844.0703 - val_calorie_loss: 675227.8750 - val_nutrient_vector_loss: 6616.2305 - val_calorie_mse: 675227.8750 - val_nutrient_vector_mse: 6616.2305\n",
      "Epoch 15/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 539665.3191 - calorie_loss: 529353.2500 - nutrient_vector_loss: 10312.0293 - calorie_mse: 529188.7500 - nutrient_vector_mse: 10334.2812\n",
      "Epoch 00015: val_calorie_loss improved from 675227.87500 to 673857.68750, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 540930.7209 - calorie_loss: 530767.4375 - nutrient_vector_loss: 10167.0547 - calorie_mse: 530614.0000 - nutrient_vector_mse: 10188.0127 - val_loss: 680376.9219 - val_calorie_loss: 673857.6875 - val_nutrient_vector_loss: 6519.2300 - val_calorie_mse: 673857.6875 - val_nutrient_vector_mse: 6519.2300\n",
      "Epoch 16/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 538290.9053 - calorie_loss: 528014.1875 - nutrient_vector_loss: 10276.7012 - calorie_mse: 527923.1875 - nutrient_vector_mse: 10300.5029\n",
      "Epoch 00016: val_calorie_loss improved from 673857.68750 to 660358.68750, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 535662.2737 - calorie_loss: 525557.3125 - nutrient_vector_loss: 10107.1543 - calorie_mse: 525458.2500 - nutrient_vector_mse: 10129.5107 - val_loss: 666818.4375 - val_calorie_loss: 660358.6875 - val_nutrient_vector_loss: 6459.8110 - val_calorie_mse: 660358.6875 - val_nutrient_vector_mse: 6459.8110\n",
      "Epoch 17/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 533711.6212 - calorie_loss: 523480.0000 - nutrient_vector_loss: 10231.6426 - calorie_mse: 523530.2812 - nutrient_vector_mse: 10253.8691\n",
      "Epoch 00017: val_calorie_loss improved from 660358.68750 to 657099.81250, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 535185.7627 - calorie_loss: 525100.5000 - nutrient_vector_loss: 10083.1338 - calorie_mse: 525156.3750 - nutrient_vector_mse: 10104.0527 - val_loss: 663758.8906 - val_calorie_loss: 657099.8125 - val_nutrient_vector_loss: 6659.0820 - val_calorie_mse: 657099.8125 - val_nutrient_vector_mse: 6659.0820\n",
      "Epoch 18/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 539457.0966 - calorie_loss: 529239.5625 - nutrient_vector_loss: 10217.4541 - calorie_mse: 529214.1875 - nutrient_vector_mse: 10240.2852\n",
      "Epoch 00018: val_calorie_loss improved from 657099.81250 to 654715.87500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 536554.4018 - calorie_loss: 526495.8125 - nutrient_vector_loss: 10058.9307 - calorie_mse: 526459.1250 - nutrient_vector_mse: 10080.3926 - val_loss: 661489.9375 - val_calorie_loss: 654715.8750 - val_nutrient_vector_loss: 6774.0737 - val_calorie_mse: 654715.8750 - val_nutrient_vector_mse: 6774.0737\n",
      "Epoch 19/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 531581.0417 - calorie_loss: 521342.9688 - nutrient_vector_loss: 10238.0635 - calorie_mse: 521198.9688 - nutrient_vector_mse: 10259.9072\n",
      "Epoch 00019: val_calorie_loss improved from 654715.87500 to 635173.56250, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 533196.5639 - calorie_loss: 523107.4062 - nutrient_vector_loss: 10092.3379 - calorie_mse: 522975.3750 - nutrient_vector_mse: 10112.8975 - val_loss: 641674.6172 - val_calorie_loss: 635173.5625 - val_nutrient_vector_loss: 6501.0908 - val_calorie_mse: 635173.5625 - val_nutrient_vector_mse: 6501.0908\n",
      "Epoch 20/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 533202.3551 - calorie_loss: 523024.6562 - nutrient_vector_loss: 10177.7002 - calorie_mse: 523033.5625 - nutrient_vector_mse: 10200.5635\n",
      "Epoch 00020: val_calorie_loss did not improve from 635173.56250\n",
      "34/34 [==============================] - 89s 3s/step - loss: 537037.9277 - calorie_loss: 526972.1250 - nutrient_vector_loss: 10064.4775 - calorie_mse: 526998.0625 - nutrient_vector_mse: 10086.1689 - val_loss: 651836.5000 - val_calorie_loss: 645450.1875 - val_nutrient_vector_loss: 6386.3330 - val_calorie_mse: 645450.1875 - val_nutrient_vector_mse: 6386.3330\n",
      "Epoch 21/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 532097.2992 - calorie_loss: 521929.0312 - nutrient_vector_loss: 10168.1963 - calorie_mse: 521906.8125 - nutrient_vector_mse: 10191.3906\n",
      "Epoch 00021: val_calorie_loss improved from 635173.56250 to 626361.87500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 530860.1945 - calorie_loss: 520849.9375 - nutrient_vector_loss: 10010.2979 - calorie_mse: 520823.6250 - nutrient_vector_mse: 10032.1143 - val_loss: 632482.1172 - val_calorie_loss: 626361.8750 - val_nutrient_vector_loss: 6120.2920 - val_calorie_mse: 626361.8750 - val_nutrient_vector_mse: 6120.2920\n",
      "Epoch 22/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 527831.8049 - calorie_loss: 517656.3750 - nutrient_vector_loss: 10175.4004 - calorie_mse: 517511.5938 - nutrient_vector_mse: 10197.8887\n",
      "Epoch 00022: val_calorie_loss improved from 626361.87500 to 620979.81250, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 528864.7029 - calorie_loss: 518853.4688 - nutrient_vector_loss: 10014.4346 - calorie_mse: 518718.2188 - nutrient_vector_mse: 10035.5527 - val_loss: 627064.2266 - val_calorie_loss: 620979.8125 - val_nutrient_vector_loss: 6084.4546 - val_calorie_mse: 620979.8125 - val_nutrient_vector_mse: 6084.4546\n",
      "Epoch 23/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 530699.2888 - calorie_loss: 520525.5625 - nutrient_vector_loss: 10173.6689 - calorie_mse: 520385.3438 - nutrient_vector_mse: 10195.9092\n",
      "Epoch 00023: val_calorie_loss improved from 620979.81250 to 612308.12500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 529075.8286 - calorie_loss: 519059.8125 - nutrient_vector_loss: 10019.4609 - calorie_mse: 518917.3125 - nutrient_vector_mse: 10040.3691 - val_loss: 618481.9219 - val_calorie_loss: 612308.1250 - val_nutrient_vector_loss: 6173.7271 - val_calorie_mse: 612308.1250 - val_nutrient_vector_mse: 6173.7271\n",
      "Epoch 24/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 523185.4072 - calorie_loss: 513033.5000 - nutrient_vector_loss: 10151.9922 - calorie_mse: 512889.2188 - nutrient_vector_mse: 10174.8428\n",
      "Epoch 00024: val_calorie_loss did not improve from 612308.12500\n",
      "34/34 [==============================] - 91s 3s/step - loss: 524975.4405 - calorie_loss: 514969.0000 - nutrient_vector_loss: 10009.6953 - calorie_mse: 514837.4375 - nutrient_vector_mse: 10031.2471 - val_loss: 623212.2734 - val_calorie_loss: 617106.7500 - val_nutrient_vector_loss: 6105.5430 - val_calorie_mse: 617106.7500 - val_nutrient_vector_mse: 6105.5430\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 25/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 525598.1297 - calorie_loss: 515486.8438 - nutrient_vector_loss: 10111.2549 - calorie_mse: 515392.0938 - nutrient_vector_mse: 10134.5840\n",
      "Epoch 00025: val_calorie_loss improved from 612308.12500 to 611306.43750, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 524003.6468 - calorie_loss: 514059.0000 - nutrient_vector_loss: 9946.7803 - calorie_mse: 513960.7812 - nutrient_vector_mse: 9968.6992 - val_loss: 617516.9375 - val_calorie_loss: 611306.4375 - val_nutrient_vector_loss: 6210.5371 - val_calorie_mse: 611306.4375 - val_nutrient_vector_mse: 6210.5371\n",
      "Epoch 26/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 526698.2547 - calorie_loss: 516582.6562 - nutrient_vector_loss: 10115.5283 - calorie_mse: 516535.9688 - nutrient_vector_mse: 10138.4121\n",
      "Epoch 00026: val_calorie_loss improved from 611306.43750 to 603347.00000, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 525523.5585 - calorie_loss: 515563.5312 - nutrient_vector_loss: 9960.7666 - calorie_mse: 515513.7500 - nutrient_vector_mse: 9982.2959 - val_loss: 609739.3516 - val_calorie_loss: 603347.0000 - val_nutrient_vector_loss: 6392.3462 - val_calorie_mse: 603347.0000 - val_nutrient_vector_mse: 6392.3462\n",
      "Epoch 27/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 519727.5369 - calorie_loss: 509652.5000 - nutrient_vector_loss: 10075.1289 - calorie_mse: 509604.1875 - nutrient_vector_mse: 10098.2617\n",
      "Epoch 00027: val_calorie_loss improved from 603347.00000 to 592693.93750, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 519300.8480 - calorie_loss: 509363.9375 - nutrient_vector_loss: 9937.7217 - calorie_mse: 509315.8125 - nutrient_vector_mse: 9959.5693 - val_loss: 598718.4609 - val_calorie_loss: 592693.9375 - val_nutrient_vector_loss: 6024.4883 - val_calorie_mse: 592693.9375 - val_nutrient_vector_mse: 6024.4883\n",
      "Epoch 28/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 525040.1326 - calorie_loss: 514913.6250 - nutrient_vector_loss: 10126.5146 - calorie_mse: 514826.9062 - nutrient_vector_mse: 10149.4844\n",
      "Epoch 00028: val_calorie_loss did not improve from 592693.93750\n",
      "34/34 [==============================] - 92s 3s/step - loss: 523867.3077 - calorie_loss: 513894.5938 - nutrient_vector_loss: 9974.6807 - calorie_mse: 513805.9375 - nutrient_vector_mse: 9996.3066 - val_loss: 599205.2109 - val_calorie_loss: 593251.8125 - val_nutrient_vector_loss: 5953.4414 - val_calorie_mse: 593251.8125 - val_nutrient_vector_mse: 5953.4414\n",
      "Epoch 29/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 520180.3561 - calorie_loss: 510097.7500 - nutrient_vector_loss: 10082.4619 - calorie_mse: 510048.8750 - nutrient_vector_mse: 10105.5146\n",
      "Epoch 00029: val_calorie_loss improved from 592693.93750 to 580430.87500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 518512.7086 - calorie_loss: 508586.2812 - nutrient_vector_loss: 9927.1797 - calorie_mse: 508532.2812 - nutrient_vector_mse: 9948.8691 - val_loss: 586395.6562 - val_calorie_loss: 580430.8750 - val_nutrient_vector_loss: 5964.7988 - val_calorie_mse: 580430.8750 - val_nutrient_vector_mse: 5964.7988\n",
      "Epoch 30/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 517608.8409 - calorie_loss: 507565.6562 - nutrient_vector_loss: 10043.1719 - calorie_mse: 507544.3125 - nutrient_vector_mse: 10065.9648\n",
      "Epoch 00030: val_calorie_loss improved from 580430.87500 to 571835.25000, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 516605.0186 - calorie_loss: 506714.4062 - nutrient_vector_loss: 9890.6846 - calorie_mse: 506690.0000 - nutrient_vector_mse: 9912.1357 - val_loss: 577822.9375 - val_calorie_loss: 571835.2500 - val_nutrient_vector_loss: 5987.6953 - val_calorie_mse: 571835.2500 - val_nutrient_vector_mse: 5987.6953\n",
      "Epoch 31/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 517119.4091 - calorie_loss: 507036.6875 - nutrient_vector_loss: 10082.7773 - calorie_mse: 506889.3438 - nutrient_vector_mse: 10105.9512\n",
      "Epoch 00031: val_calorie_loss did not improve from 571835.25000\n",
      "34/34 [==============================] - 91s 3s/step - loss: 514457.5674 - calorie_loss: 504555.0625 - nutrient_vector_loss: 9906.3359 - calorie_mse: 504401.1875 - nutrient_vector_mse: 9928.0518 - val_loss: 578639.6953 - val_calorie_loss: 572742.4375 - val_nutrient_vector_loss: 5897.2266 - val_calorie_mse: 572742.4375 - val_nutrient_vector_mse: 5897.2266\n",
      "Epoch 32/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 512279.1847 - calorie_loss: 502243.4375 - nutrient_vector_loss: 10035.7363 - calorie_mse: 502079.0312 - nutrient_vector_mse: 10058.4463\n",
      "Epoch 00032: val_calorie_loss improved from 571835.25000 to 570565.68750, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 512044.3371 - calorie_loss: 502182.2500 - nutrient_vector_loss: 9866.0488 - calorie_mse: 502022.4375 - nutrient_vector_mse: 9887.3438 - val_loss: 576699.2188 - val_calorie_loss: 570565.6875 - val_nutrient_vector_loss: 6133.5195 - val_calorie_mse: 570565.6875 - val_nutrient_vector_mse: 6133.5195\n",
      "Epoch 33/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 516440.9801 - calorie_loss: 506450.8125 - nutrient_vector_loss: 9990.2344 - calorie_mse: 506438.2812 - nutrient_vector_mse: 10013.7432 \n",
      "Epoch 00033: val_calorie_loss improved from 570565.68750 to 550394.62500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 91s 3s/step - loss: 513324.0095 - calorie_loss: 503494.2812 - nutrient_vector_loss: 9829.8740 - calorie_mse: 503469.1562 - nutrient_vector_mse: 9851.9854 - val_loss: 556132.5273 - val_calorie_loss: 550394.6250 - val_nutrient_vector_loss: 5737.8887 - val_calorie_mse: 550394.6250 - val_nutrient_vector_mse: 5737.8887\n",
      "Epoch 34/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 511237.3968 - calorie_loss: 501281.0938 - nutrient_vector_loss: 9956.3242 - calorie_mse: 501312.4688 - nutrient_vector_mse: 9979.7744  \n",
      "Epoch 00034: val_calorie_loss did not improve from 550394.62500\n",
      "34/34 [==============================] - 93s 3s/step - loss: 511527.0899 - calorie_loss: 501684.8750 - nutrient_vector_loss: 9840.6572 - calorie_mse: 501717.0938 - nutrient_vector_mse: 9862.9082 - val_loss: 557075.0586 - val_calorie_loss: 551190.1875 - val_nutrient_vector_loss: 5884.8345 - val_calorie_mse: 551190.1875 - val_nutrient_vector_mse: 5884.8345\n",
      "Epoch 35/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 506842.8258 - calorie_loss: 496844.2188 - nutrient_vector_loss: 9998.6875 - calorie_mse: 496879.9062 - nutrient_vector_mse: 10022.2393 \n",
      "Epoch 00035: val_calorie_loss did not improve from 550394.62500\n",
      "34/34 [==============================] - 91s 3s/step - loss: 508339.8411 - calorie_loss: 498486.2500 - nutrient_vector_loss: 9851.8555 - calorie_mse: 498528.0625 - nutrient_vector_mse: 9874.0674 - val_loss: 563144.6484 - val_calorie_loss: 557001.8125 - val_nutrient_vector_loss: 6142.8320 - val_calorie_mse: 557001.8125 - val_nutrient_vector_mse: 6142.8320\n",
      "Epoch 36/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 506957.5331 - calorie_loss: 496991.0312 - nutrient_vector_loss: 9966.4658 - calorie_mse: 496980.4062 - nutrient_vector_mse: 9989.4580  \n",
      "Epoch 00036: val_calorie_loss improved from 550394.62500 to 545561.37500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 508102.5055 - calorie_loss: 498284.1875 - nutrient_vector_loss: 9817.8223 - calorie_mse: 498279.5000 - nutrient_vector_mse: 9839.4844 - val_loss: 551465.3516 - val_calorie_loss: 545561.3750 - val_nutrient_vector_loss: 5903.9194 - val_calorie_mse: 545561.3750 - val_nutrient_vector_mse: 5903.9194\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 37/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 504194.0142 - calorie_loss: 494243.0000 - nutrient_vector_loss: 9951.0254 - calorie_mse: 494243.0000 - nutrient_vector_mse: 9951.0254  \n",
      "Epoch 00037: val_calorie_loss improved from 545561.37500 to 536950.50000, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 504091.8012 - calorie_loss: 494290.8750 - nutrient_vector_loss: 9800.4932 - calorie_mse: 494283.9375 - nutrient_vector_mse: 9822.2754 - val_loss: 542706.0039 - val_calorie_loss: 536950.5000 - val_nutrient_vector_loss: 5755.4932 - val_calorie_mse: 536950.5000 - val_nutrient_vector_mse: 5755.4932\n",
      "Epoch 38/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 506300.2472 - calorie_loss: 496407.0625 - nutrient_vector_loss: 9893.2227 - calorie_mse: 496457.2188 - nutrient_vector_mse: 9916.5635  \n",
      "Epoch 00038: val_calorie_loss did not improve from 536950.50000\n",
      "34/34 [==============================] - 92s 3s/step - loss: 507626.9534 - calorie_loss: 497838.4062 - nutrient_vector_loss: 9786.3760 - calorie_mse: 497893.3438 - nutrient_vector_mse: 9808.5586 - val_loss: 546954.1953 - val_calorie_loss: 541168.6250 - val_nutrient_vector_loss: 5785.5332 - val_calorie_mse: 541168.6250 - val_nutrient_vector_mse: 5785.5332\n",
      "Epoch 39/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 509227.1449 - calorie_loss: 499211.6250 - nutrient_vector_loss: 10015.4824 - calorie_mse: 499213.9062 - nutrient_vector_mse: 10038.9170\n",
      "Epoch 00039: val_calorie_loss improved from 536950.50000 to 529333.50000, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 507886.2542 - calorie_loss: 498033.3438 - nutrient_vector_loss: 9852.3242 - calorie_mse: 498030.4375 - nutrient_vector_mse: 9874.3516 - val_loss: 535258.4844 - val_calorie_loss: 529333.5000 - val_nutrient_vector_loss: 5925.0415 - val_calorie_mse: 529333.5000 - val_nutrient_vector_mse: 5925.0415\n",
      "Epoch 40/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 497036.6439 - calorie_loss: 492063.2812 - nutrient_vector_loss: 4973.3940 - calorie_mse: 492094.4062 - nutrient_vector_mse: 4973.7847\n",
      "Epoch 00040: val_calorie_loss improved from 529333.50000 to 525279.62500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 90s 3s/step - loss: 502162.1897 - calorie_loss: 492356.1562 - nutrient_vector_loss: 9804.5518 - calorie_mse: 492387.6562 - nutrient_vector_mse: 9826.1143 - val_loss: 531067.4727 - val_calorie_loss: 525279.6250 - val_nutrient_vector_loss: 5787.8071 - val_calorie_mse: 525279.6250 - val_nutrient_vector_mse: 5787.8071\n",
      "Epoch 41/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 500901.6960 - calorie_loss: 490929.4688 - nutrient_vector_loss: 9972.1992 - calorie_mse: 490885.7500 - nutrient_vector_mse: 9995.3389  \n",
      "Epoch 00041: val_calorie_loss did not improve from 525279.62500\n",
      "34/34 [==============================] - 90s 3s/step - loss: 500211.9252 - calorie_loss: 490412.7500 - nutrient_vector_loss: 9799.7812 - calorie_mse: 490368.0938 - nutrient_vector_mse: 9821.4814 - val_loss: 538673.7422 - val_calorie_loss: 532814.9375 - val_nutrient_vector_loss: 5858.7695 - val_calorie_mse: 532814.9375 - val_nutrient_vector_mse: 5858.7695\n",
      "Epoch 42/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 498538.0265 - calorie_loss: 488620.5938 - nutrient_vector_loss: 9917.4443 - calorie_mse: 488737.6562 - nutrient_vector_mse: 9940.8604  \n",
      "Epoch 00042: val_calorie_loss improved from 525279.62500 to 520189.37500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 499618.1255 - calorie_loss: 489845.1250 - nutrient_vector_loss: 9768.9971 - calorie_mse: 489964.0938 - nutrient_vector_mse: 9791.0703 - val_loss: 525985.2812 - val_calorie_loss: 520189.3750 - val_nutrient_vector_loss: 5795.9561 - val_calorie_mse: 520189.3750 - val_nutrient_vector_mse: 5795.9561\n",
      "Epoch 43/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 501697.0085 - calorie_loss: 491823.8750 - nutrient_vector_loss: 9873.2275 - calorie_mse: 491792.2500 - nutrient_vector_mse: 9895.9395 \n",
      "Epoch 00043: val_calorie_loss did not improve from 520189.37500\n",
      "34/34 [==============================] - 91s 3s/step - loss: 502604.4341 - calorie_loss: 492845.8438 - nutrient_vector_loss: 9758.8096 - calorie_mse: 492819.6562 - nutrient_vector_mse: 9780.3486 - val_loss: 529142.5234 - val_calorie_loss: 523475.9375 - val_nutrient_vector_loss: 5666.5918 - val_calorie_mse: 523475.9375 - val_nutrient_vector_mse: 5666.5918\n",
      "Epoch 44/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 496563.5473 - calorie_loss: 486646.9062 - nutrient_vector_loss: 9916.6279 - calorie_mse: 486674.6875 - nutrient_vector_mse: 9939.9590  \n",
      "Epoch 00044: val_calorie_loss improved from 520189.37500 to 516427.56250, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 497815.0652 - calorie_loss: 488061.4062 - nutrient_vector_loss: 9752.0771 - calorie_mse: 488094.5625 - nutrient_vector_mse: 9773.9980 - val_loss: 522131.4453 - val_calorie_loss: 516427.5625 - val_nutrient_vector_loss: 5703.8838 - val_calorie_mse: 516427.5625 - val_nutrient_vector_mse: 5703.8838\n",
      "Epoch 45/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 494170.0066 - calorie_loss: 484320.3750 - nutrient_vector_loss: 9849.7002 - calorie_mse: 484414.1250 - nutrient_vector_mse: 9873.6514  \n",
      "Epoch 00045: val_calorie_loss improved from 516427.56250 to 510995.56250, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 494789.2108 - calorie_loss: 485057.3438 - nutrient_vector_loss: 9728.5771 - calorie_mse: 485151.5938 - nutrient_vector_mse: 9751.2900 - val_loss: 516780.6523 - val_calorie_loss: 510995.5625 - val_nutrient_vector_loss: 5785.0381 - val_calorie_mse: 510995.5625 - val_nutrient_vector_mse: 5785.0381\n",
      "Epoch 46/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 493548.2576 - calorie_loss: 483659.5625 - nutrient_vector_loss: 9888.6826 - calorie_mse: 483669.9688 - nutrient_vector_mse: 9912.0938  \n",
      "Epoch 00046: val_calorie_loss did not improve from 510995.56250\n",
      "34/34 [==============================] - 91s 3s/step - loss: 495022.2214 - calorie_loss: 485274.6875 - nutrient_vector_loss: 9746.4355 - calorie_mse: 485291.8438 - nutrient_vector_mse: 9768.5312 - val_loss: 522112.8398 - val_calorie_loss: 516336.9062 - val_nutrient_vector_loss: 5775.9385 - val_calorie_mse: 516336.9062 - val_nutrient_vector_mse: 5775.9385\n",
      "Epoch 47/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 499716.8068 - calorie_loss: 489817.7188 - nutrient_vector_loss: 9899.0811 - calorie_mse: 489829.6562 - nutrient_vector_mse: 9922.5098  \n",
      "Epoch 00047: val_calorie_loss did not improve from 510995.56250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 497706.2618 - calorie_loss: 487963.4375 - nutrient_vector_loss: 9742.1064 - calorie_mse: 487966.9062 - nutrient_vector_mse: 9764.1543 - val_loss: 520672.4648 - val_calorie_loss: 514971.3750 - val_nutrient_vector_loss: 5701.0933 - val_calorie_mse: 514971.3750 - val_nutrient_vector_mse: 5701.0933\n",
      "Epoch 48/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 496127.1051 - calorie_loss: 486261.9375 - nutrient_vector_loss: 9865.1006 - calorie_mse: 486297.5312 - nutrient_vector_mse: 9888.7285  \n",
      "Epoch 00048: val_calorie_loss improved from 510995.56250 to 510979.37500, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 494766.4345 - calorie_loss: 485040.6250 - nutrient_vector_loss: 9724.2900 - calorie_mse: 485069.8125 - nutrient_vector_mse: 9746.6035 - val_loss: 516635.4727 - val_calorie_loss: 510979.3750 - val_nutrient_vector_loss: 5656.0537 - val_calorie_mse: 510979.3750 - val_nutrient_vector_mse: 5656.0537\n",
      "Epoch 49/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 492559.0000 - calorie_loss: 482751.8125 - nutrient_vector_loss: 9807.0957 - calorie_mse: 482832.4062 - nutrient_vector_mse: 9830.7402\n",
      "Epoch 00049: val_calorie_loss improved from 510979.37500 to 502113.06250, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 92s 3s/step - loss: 494750.1472 - calorie_loss: 485064.2812 - nutrient_vector_loss: 9682.6025 - calorie_mse: 485152.6562 - nutrient_vector_mse: 9705.0029 - val_loss: 507747.1094 - val_calorie_loss: 502113.0625 - val_nutrient_vector_loss: 5634.0044 - val_calorie_mse: 502113.0625 - val_nutrient_vector_mse: 5634.0044\n",
      "Epoch 50/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 491454.6430 - calorie_loss: 481605.2500 - nutrient_vector_loss: 9849.4258 - calorie_mse: 481707.7812 - nutrient_vector_mse: 9873.2070  \n",
      "Epoch 00050: val_calorie_loss did not improve from 502113.06250\n",
      "34/34 [==============================] - 91s 3s/step - loss: 492355.1860 - calorie_loss: 482646.7188 - nutrient_vector_loss: 9704.8828 - calorie_mse: 482750.7812 - nutrient_vector_mse: 9727.3281 - val_loss: 514588.9648 - val_calorie_loss: 508915.5000 - val_nutrient_vector_loss: 5673.4570 - val_calorie_mse: 508915.5000 - val_nutrient_vector_mse: 5673.4570\n",
      "Epoch 51/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 487970.6752 - calorie_loss: 478175.5000 - nutrient_vector_loss: 9795.1719 - calorie_mse: 478198.6875 - nutrient_vector_mse: 9818.8818\n",
      "Epoch 00051: val_calorie_loss did not improve from 502113.06250\n",
      "34/34 [==============================] - 89s 3s/step - loss: 489354.4318 - calorie_loss: 479667.8125 - nutrient_vector_loss: 9685.1328 - calorie_mse: 479696.8438 - nutrient_vector_mse: 9707.6592 - val_loss: 508654.9922 - val_calorie_loss: 502996.9688 - val_nutrient_vector_loss: 5657.9941 - val_calorie_mse: 502996.9688 - val_nutrient_vector_mse: 5657.9941\n",
      "Epoch 52/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 488402.5966 - calorie_loss: 478618.9688 - nutrient_vector_loss: 9783.6211 - calorie_mse: 478645.3750 - nutrient_vector_mse: 9806.6719\n",
      "Epoch 00052: val_calorie_loss did not improve from 502113.06250\n",
      "34/34 [==============================] - 91s 3s/step - loss: 488658.1480 - calorie_loss: 478994.0000 - nutrient_vector_loss: 9662.7266 - calorie_mse: 479021.2500 - nutrient_vector_mse: 9684.5664 - val_loss: 511460.1172 - val_calorie_loss: 505819.7500 - val_nutrient_vector_loss: 5640.3477 - val_calorie_mse: 505819.7500 - val_nutrient_vector_mse: 5640.3477\n",
      "Epoch 53/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 491162.8816 - calorie_loss: 481315.9688 - nutrient_vector_loss: 9846.9238 - calorie_mse: 481423.6562 - nutrient_vector_mse: 9870.9229  \n",
      "Epoch 00053: val_calorie_loss improved from 502113.06250 to 499430.56250, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 490584.4244 - calorie_loss: 480888.4062 - nutrient_vector_loss: 9692.4404 - calorie_mse: 480991.0312 - nutrient_vector_mse: 9715.0527 - val_loss: 505098.6523 - val_calorie_loss: 499430.5625 - val_nutrient_vector_loss: 5668.0918 - val_calorie_mse: 499430.5625 - val_nutrient_vector_mse: 5668.0918\n",
      "Epoch 54/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 489437.0587 - calorie_loss: 479606.5312 - nutrient_vector_loss: 9830.5156 - calorie_mse: 479697.4375 - nutrient_vector_mse: 9853.9854\n",
      "Epoch 00054: val_calorie_loss did not improve from 499430.56250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 490317.3408 - calorie_loss: 480634.2500 - nutrient_vector_loss: 9679.8105 - calorie_mse: 480726.9688 - nutrient_vector_mse: 9701.9268 - val_loss: 513558.2266 - val_calorie_loss: 507911.6875 - val_nutrient_vector_loss: 5646.5298 - val_calorie_mse: 507911.6875 - val_nutrient_vector_mse: 5646.5298\n",
      "Epoch 55/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 483936.5407 - calorie_loss: 474120.1250 - nutrient_vector_loss: 9816.4463 - calorie_mse: 474186.1875 - nutrient_vector_mse: 9840.0713\n",
      "Epoch 00055: val_calorie_loss did not improve from 499430.56250\n",
      "34/34 [==============================] - 93s 3s/step - loss: 486297.9068 - calorie_loss: 476620.5000 - nutrient_vector_loss: 9674.6396 - calorie_mse: 476695.5625 - nutrient_vector_mse: 9696.9453 - val_loss: 508302.5117 - val_calorie_loss: 502663.0000 - val_nutrient_vector_loss: 5639.5176 - val_calorie_mse: 502663.0000 - val_nutrient_vector_mse: 5639.5176\n",
      "Epoch 56/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 485722.0284 - calorie_loss: 475914.7812 - nutrient_vector_loss: 9807.2969 - calorie_mse: 475914.7812 - nutrient_vector_mse: 9807.2969\n",
      "Epoch 00056: val_calorie_loss did not improve from 499430.56250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 485978.6424 - calorie_loss: 476321.2500 - nutrient_vector_loss: 9658.5137 - calorie_mse: 476262.4375 - nutrient_vector_mse: 9680.0430 - val_loss: 512175.8398 - val_calorie_loss: 506555.4375 - val_nutrient_vector_loss: 5620.4102 - val_calorie_mse: 506555.4375 - val_nutrient_vector_mse: 5620.4102\n",
      "Epoch 57/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 493363.7112 - calorie_loss: 483502.8125 - nutrient_vector_loss: 9860.9297 - calorie_mse: 483591.2188 - nutrient_vector_mse: 9885.1709  \n",
      "Epoch 00057: val_calorie_loss did not improve from 499430.56250\n",
      "34/34 [==============================] - 90s 3s/step - loss: 490132.5288 - calorie_loss: 480444.5625 - nutrient_vector_loss: 9685.2979 - calorie_mse: 480516.9375 - nutrient_vector_mse: 9708.0527 - val_loss: 516725.0664 - val_calorie_loss: 511081.3438 - val_nutrient_vector_loss: 5643.7280 - val_calorie_mse: 511081.3438 - val_nutrient_vector_mse: 5643.7280\n",
      "Epoch 58/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 489130.7595 - calorie_loss: 479336.1562 - nutrient_vector_loss: 9794.6211 - calorie_mse: 479454.0938 - nutrient_vector_mse: 9818.3496\n",
      "Epoch 00058: val_calorie_loss did not improve from 499430.56250\n",
      "34/34 [==============================] - 88s 3s/step - loss: 487171.8765 - calorie_loss: 477509.8750 - nutrient_vector_loss: 9658.3252 - calorie_mse: 477616.3438 - nutrient_vector_mse: 9680.7549 - val_loss: 509026.8398 - val_calorie_loss: 503403.0000 - val_nutrient_vector_loss: 5623.8311 - val_calorie_mse: 503403.0000 - val_nutrient_vector_mse: 5623.8311\n",
      "Epoch 59/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 483365.9470 - calorie_loss: 473594.4688 - nutrient_vector_loss: 9771.5029 - calorie_mse: 473677.4062 - nutrient_vector_mse: 9794.9863\n",
      "Epoch 00059: val_calorie_loss did not improve from 499430.56250\n",
      "34/34 [==============================] - 88s 3s/step - loss: 483826.5203 - calorie_loss: 474165.6250 - nutrient_vector_loss: 9657.8916 - calorie_mse: 474248.6250 - nutrient_vector_mse: 9680.1826 - val_loss: 508213.5508 - val_calorie_loss: 502565.6875 - val_nutrient_vector_loss: 5647.8936 - val_calorie_mse: 502565.6875 - val_nutrient_vector_mse: 5647.8936\n",
      "Epoch 60/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 487583.1581 - calorie_loss: 477797.5312 - nutrient_vector_loss: 9785.6748 - calorie_mse: 477977.5312 - nutrient_vector_mse: 9809.3242\n",
      "Epoch 00060: val_calorie_loss improved from 499430.56250 to 499401.09375, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 487015.9888 - calorie_loss: 477345.4688 - nutrient_vector_loss: 9665.0146 - calorie_mse: 477518.1562 - nutrient_vector_mse: 9687.4355 - val_loss: 504995.9883 - val_calorie_loss: 499401.0938 - val_nutrient_vector_loss: 5594.8857 - val_calorie_mse: 499401.0938 - val_nutrient_vector_mse: 5594.8857\n",
      "Epoch 61/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 482147.9252 - calorie_loss: 472324.1875 - nutrient_vector_loss: 9823.7832 - calorie_mse: 472442.5000 - nutrient_vector_mse: 9847.9004\n",
      "Epoch 00061: val_calorie_loss improved from 499401.09375 to 498758.68750, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 482454.2946 - calorie_loss: 472795.3750 - nutrient_vector_loss: 9654.9639 - calorie_mse: 472912.2500 - nutrient_vector_mse: 9677.6289 - val_loss: 504350.5781 - val_calorie_loss: 498758.6875 - val_nutrient_vector_loss: 5591.9268 - val_calorie_mse: 498758.6875 - val_nutrient_vector_mse: 5591.9268\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 62/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 488356.9280 - calorie_loss: 478563.1875 - nutrient_vector_loss: 9793.7598 - calorie_mse: 478675.5938 - nutrient_vector_mse: 9817.9014\n",
      "Epoch 00062: val_calorie_loss did not improve from 498758.68750\n",
      "34/34 [==============================] - 90s 3s/step - loss: 486878.1263 - calorie_loss: 477238.9688 - nutrient_vector_loss: 9635.5723 - calorie_mse: 477342.2500 - nutrient_vector_mse: 9658.3076 - val_loss: 506673.7734 - val_calorie_loss: 501046.6875 - val_nutrient_vector_loss: 5627.0923 - val_calorie_mse: 501046.6875 - val_nutrient_vector_mse: 5627.0923\n",
      "Epoch 63/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 485657.6506 - calorie_loss: 475843.0312 - nutrient_vector_loss: 9814.5947 - calorie_mse: 475945.8125 - nutrient_vector_mse: 9838.4834\n",
      "Epoch 00063: val_calorie_loss did not improve from 498758.68750\n",
      "34/34 [==============================] - 89s 3s/step - loss: 483319.1564 - calorie_loss: 473661.7188 - nutrient_vector_loss: 9654.1943 - calorie_mse: 473751.9062 - nutrient_vector_mse: 9676.6738 - val_loss: 506192.6133 - val_calorie_loss: 500580.5938 - val_nutrient_vector_loss: 5612.0498 - val_calorie_mse: 500580.5938 - val_nutrient_vector_mse: 5612.0498\n",
      "Epoch 64/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 480158.4451 - calorie_loss: 470386.5000 - nutrient_vector_loss: 9771.9424 - calorie_mse: 470461.9688 - nutrient_vector_mse: 9795.6797\n",
      "Epoch 00064: val_calorie_loss did not improve from 498758.68750\n",
      "34/34 [==============================] - 89s 3s/step - loss: 482023.7981 - calorie_loss: 472391.2812 - nutrient_vector_loss: 9629.5400 - calorie_mse: 472473.3125 - nutrient_vector_mse: 9651.9521 - val_loss: 510269.9219 - val_calorie_loss: 504645.2500 - val_nutrient_vector_loss: 5624.6484 - val_calorie_mse: 504645.2500 - val_nutrient_vector_mse: 5624.6484\n",
      "Epoch 65/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 483893.6591 - calorie_loss: 474117.7812 - nutrient_vector_loss: 9775.8594 - calorie_mse: 474107.9375 - nutrient_vector_mse: 9799.2715\n",
      "Epoch 00065: val_calorie_loss improved from 498758.68750 to 496642.90625, saving model to ./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5\n",
      "34/34 [==============================] - 89s 3s/step - loss: 482732.3255 - calorie_loss: 473108.5000 - nutrient_vector_loss: 9623.5928 - calorie_mse: 473094.5312 - nutrient_vector_mse: 9645.6455 - val_loss: 502279.6406 - val_calorie_loss: 496642.9062 - val_nutrient_vector_loss: 5636.7305 - val_calorie_mse: 496642.9062 - val_nutrient_vector_mse: 5636.7305\n",
      "Epoch 66/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 483055.9830 - calorie_loss: 473252.6250 - nutrient_vector_loss: 9803.3281 - calorie_mse: 473343.8438 - nutrient_vector_mse: 9827.3584\n",
      "Epoch 00066: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 482282.2053 - calorie_loss: 472627.3438 - nutrient_vector_loss: 9651.7461 - calorie_mse: 472713.1250 - nutrient_vector_mse: 9674.4033 - val_loss: 507779.9883 - val_calorie_loss: 502152.9062 - val_nutrient_vector_loss: 5627.0845 - val_calorie_mse: 502152.9062 - val_nutrient_vector_mse: 5627.0845\n",
      "Epoch 67/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 482252.5133 - calorie_loss: 472468.3125 - nutrient_vector_loss: 9784.2656 - calorie_mse: 472515.2500 - nutrient_vector_mse: 9807.9033\n",
      "Epoch 00067: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 479576.9511 - calorie_loss: 469945.1875 - nutrient_vector_loss: 9630.1943 - calorie_mse: 469979.6562 - nutrient_vector_mse: 9652.4570 - val_loss: 512489.6758 - val_calorie_loss: 506888.3750 - val_nutrient_vector_loss: 5601.3369 - val_calorie_mse: 506888.3750 - val_nutrient_vector_mse: 5601.3369\n",
      "Epoch 68/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 481295.7992 - calorie_loss: 471515.7500 - nutrient_vector_loss: 9780.0420 - calorie_mse: 471719.7812 - nutrient_vector_mse: 9804.8379\n",
      "Epoch 00068: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 89s 3s/step - loss: 479095.4168 - calorie_loss: 469481.4062 - nutrient_vector_loss: 9607.9453 - calorie_mse: 469670.5000 - nutrient_vector_mse: 9631.2549 - val_loss: 513986.5195 - val_calorie_loss: 508336.4062 - val_nutrient_vector_loss: 5650.1274 - val_calorie_mse: 508336.4062 - val_nutrient_vector_mse: 5650.1274\n",
      "Epoch 69/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 481900.9820 - calorie_loss: 472151.0625 - nutrient_vector_loss: 9749.9092 - calorie_mse: 472238.1562 - nutrient_vector_mse: 9773.6748\n",
      "Epoch 00069: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 481208.6132 - calorie_loss: 471591.5000 - nutrient_vector_loss: 9614.1123 - calorie_mse: 471673.5625 - nutrient_vector_mse: 9636.5811 - val_loss: 511964.5156 - val_calorie_loss: 506204.0000 - val_nutrient_vector_loss: 5760.5063 - val_calorie_mse: 506204.0000 - val_nutrient_vector_mse: 5760.5063\n",
      "Epoch 70/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 479096.8722 - calorie_loss: 469338.0938 - nutrient_vector_loss: 9758.7979 - calorie_mse: 469489.3125 - nutrient_vector_mse: 9783.3213\n",
      "Epoch 00070: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 478705.8412 - calorie_loss: 469099.8750 - nutrient_vector_loss: 9601.1611 - calorie_mse: 469245.5938 - nutrient_vector_mse: 9624.2686 - val_loss: 512127.0742 - val_calorie_loss: 506376.9375 - val_nutrient_vector_loss: 5750.1802 - val_calorie_mse: 506376.9375 - val_nutrient_vector_mse: 5750.1802\n",
      "Epoch 71/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 479776.9081 - calorie_loss: 470056.0625 - nutrient_vector_loss: 9720.8691 - calorie_mse: 470244.0625 - nutrient_vector_mse: 9745.0225\n",
      "Epoch 00071: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 479147.9571 - calorie_loss: 469547.5625 - nutrient_vector_loss: 9594.6133 - calorie_mse: 469727.7812 - nutrient_vector_mse: 9617.4990 - val_loss: 510453.3984 - val_calorie_loss: 504781.5625 - val_nutrient_vector_loss: 5671.8086 - val_calorie_mse: 504781.5625 - val_nutrient_vector_mse: 5671.8086\n",
      "Epoch 72/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 470139.6828 - calorie_loss: 465332.5000 - nutrient_vector_loss: 4807.1631 - calorie_mse: 465545.5312 - nutrient_vector_mse: 4809.1577\n",
      "Epoch 00072: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 474020.6721 - calorie_loss: 464384.1250 - nutrient_vector_loss: 9630.0908 - calorie_mse: 464586.6875 - nutrient_vector_mse: 9653.1748 - val_loss: 511221.9609 - val_calorie_loss: 505518.9688 - val_nutrient_vector_loss: 5703.0098 - val_calorie_mse: 505518.9688 - val_nutrient_vector_mse: 5703.0098\n",
      "Epoch 73/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 477665.2500 - calorie_loss: 467930.7812 - nutrient_vector_loss: 9734.5273 - calorie_mse: 468003.8438 - nutrient_vector_mse: 9757.9619\n",
      "Epoch 00073: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 476688.0813 - calorie_loss: 467086.4062 - nutrient_vector_loss: 9599.1865 - calorie_mse: 467153.6250 - nutrient_vector_mse: 9621.3350 - val_loss: 507582.6055 - val_calorie_loss: 501932.1250 - val_nutrient_vector_loss: 5650.4766 - val_calorie_mse: 501932.1250 - val_nutrient_vector_mse: 5650.4766\n",
      "Epoch 74/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469079.6373 - calorie_loss: 464286.1875 - nutrient_vector_loss: 4793.4229 - calorie_mse: 464489.1562 - nutrient_vector_mse: 4795.5664\n",
      "Epoch 00074: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 89s 3s/step - loss: 473030.4342 - calorie_loss: 463433.5625 - nutrient_vector_loss: 9590.6670 - calorie_mse: 463626.8125 - nutrient_vector_mse: 9613.7822 - val_loss: 514238.7383 - val_calorie_loss: 508610.3438 - val_nutrient_vector_loss: 5628.3965 - val_calorie_mse: 508610.3438 - val_nutrient_vector_mse: 5628.3965\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 75/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 482456.0739 - calorie_loss: 472678.4375 - nutrient_vector_loss: 9777.6094 - calorie_mse: 472813.8125 - nutrient_vector_mse: 9801.5635\n",
      "Epoch 00075: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 89s 3s/step - loss: 479461.4914 - calorie_loss: 469835.9688 - nutrient_vector_loss: 9621.4287 - calorie_mse: 469954.9062 - nutrient_vector_mse: 9643.9902 - val_loss: 514037.1484 - val_calorie_loss: 508370.6562 - val_nutrient_vector_loss: 5666.5000 - val_calorie_mse: 508370.6562 - val_nutrient_vector_mse: 5666.5000\n",
      "Epoch 76/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 475482.9972 - calorie_loss: 465754.4062 - nutrient_vector_loss: 9728.5527 - calorie_mse: 465831.8750 - nutrient_vector_mse: 9752.7891\n",
      "Epoch 00076: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 89s 3s/step - loss: 477006.0731 - calorie_loss: 467393.8125 - nutrient_vector_loss: 9609.1953 - calorie_mse: 467476.2188 - nutrient_vector_mse: 9632.1914 - val_loss: 505325.6719 - val_calorie_loss: 499681.0000 - val_nutrient_vector_loss: 5644.6948 - val_calorie_mse: 499681.0000 - val_nutrient_vector_mse: 5644.6948\n",
      "Epoch 77/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 475658.0180 - calorie_loss: 470862.5000 - nutrient_vector_loss: 4795.5244 - calorie_mse: 470921.7812 - nutrient_vector_mse: 4796.7324\n",
      "Epoch 00077: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 89s 3s/step - loss: 479719.3361 - calorie_loss: 470116.5312 - nutrient_vector_loss: 9600.6250 - calorie_mse: 470170.7812 - nutrient_vector_mse: 9622.8662 - val_loss: 513280.9414 - val_calorie_loss: 507604.6250 - val_nutrient_vector_loss: 5676.3555 - val_calorie_mse: 507604.6250 - val_nutrient_vector_mse: 5676.3555\n",
      "Epoch 78/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 475600.0455 - calorie_loss: 465851.1562 - nutrient_vector_loss: 9748.8662 - calorie_mse: 465881.2188 - nutrient_vector_mse: 9772.3301\n",
      "Epoch 00078: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 474988.3072 - calorie_loss: 465390.3750 - nutrient_vector_loss: 9596.4873 - calorie_mse: 465417.5312 - nutrient_vector_mse: 9618.5898 - val_loss: 513000.6914 - val_calorie_loss: 507222.3438 - val_nutrient_vector_loss: 5778.3110 - val_calorie_mse: 507222.3438 - val_nutrient_vector_mse: 5778.3110\n",
      "Epoch 79/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 477496.8134 - calorie_loss: 467777.9062 - nutrient_vector_loss: 9718.9092 - calorie_mse: 467962.8750 - nutrient_vector_mse: 9743.4561\n",
      "Epoch 00079: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 475839.6876 - calorie_loss: 466248.5000 - nutrient_vector_loss: 9585.5840 - calorie_mse: 466421.3125 - nutrient_vector_mse: 9608.8203 - val_loss: 509916.5938 - val_calorie_loss: 504233.6562 - val_nutrient_vector_loss: 5682.9824 - val_calorie_mse: 504233.6562 - val_nutrient_vector_mse: 5682.9824\n",
      "Epoch 80/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 474887.6023 - calorie_loss: 465148.9688 - nutrient_vector_loss: 9738.6211 - calorie_mse: 465342.1250 - nutrient_vector_mse: 9762.7910\n",
      "Epoch 00080: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 473907.1826 - calorie_loss: 464314.9375 - nutrient_vector_loss: 9586.3174 - calorie_mse: 464498.7500 - nutrient_vector_mse: 9609.1055 - val_loss: 509234.9453 - val_calorie_loss: 503588.3438 - val_nutrient_vector_loss: 5646.6191 - val_calorie_mse: 503588.3438 - val_nutrient_vector_mse: 5646.6191\n",
      "Epoch 81/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 474667.0644 - calorie_loss: 464911.5625 - nutrient_vector_loss: 9755.5117 - calorie_mse: 465053.6875 - nutrient_vector_mse: 9779.3193\n",
      "Epoch 00081: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 474230.5037 - calorie_loss: 464623.6875 - nutrient_vector_loss: 9602.3105 - calorie_mse: 464760.3125 - nutrient_vector_mse: 9624.7432 - val_loss: 512304.6953 - val_calorie_loss: 506586.4375 - val_nutrient_vector_loss: 5718.2603 - val_calorie_mse: 506586.4375 - val_nutrient_vector_mse: 5718.2603\n",
      "Epoch 82/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 473375.6875 - calorie_loss: 463632.4688 - nutrient_vector_loss: 9743.2646 - calorie_mse: 463694.3125 - nutrient_vector_mse: 9766.8906\n",
      "Epoch 00082: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 473684.6672 - calorie_loss: 464103.8125 - nutrient_vector_loss: 9578.4678 - calorie_mse: 464165.9375 - nutrient_vector_mse: 9600.6738 - val_loss: 510159.4297 - val_calorie_loss: 504513.3125 - val_nutrient_vector_loss: 5646.1050 - val_calorie_mse: 504513.3125 - val_nutrient_vector_mse: 5646.1050\n",
      "Epoch 83/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 476632.6250 - calorie_loss: 466875.5312 - nutrient_vector_loss: 9757.0879 - calorie_mse: 466890.8750 - nutrient_vector_mse: 9780.7930\n",
      "Epoch 00083: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 475755.7437 - calorie_loss: 466155.0938 - nutrient_vector_loss: 9599.6797 - calorie_mse: 466166.8125 - nutrient_vector_mse: 9621.9941 - val_loss: 518970.8359 - val_calorie_loss: 513275.7500 - val_nutrient_vector_loss: 5695.0410 - val_calorie_mse: 513275.7500 - val_nutrient_vector_mse: 5695.0410\n",
      "Epoch 84/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 472293.1193 - calorie_loss: 462540.5312 - nutrient_vector_loss: 9752.5332 - calorie_mse: 462623.3750 - nutrient_vector_mse: 9776.6328\n",
      "Epoch 00084: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 473315.9352 - calorie_loss: 463724.6250 - nutrient_vector_loss: 9588.1982 - calorie_mse: 463810.1875 - nutrient_vector_mse: 9610.8652 - val_loss: 506990.8125 - val_calorie_loss: 501385.9375 - val_nutrient_vector_loss: 5604.8677 - val_calorie_mse: 501385.9375 - val_nutrient_vector_mse: 5604.8677\n",
      "Epoch 85/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 472771.3741 - calorie_loss: 463009.5000 - nutrient_vector_loss: 9761.8389 - calorie_mse: 463181.6250 - nutrient_vector_mse: 9785.8691\n",
      "Epoch 00085: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 472324.4994 - calorie_loss: 462713.6875 - nutrient_vector_loss: 9605.4307 - calorie_mse: 462879.4062 - nutrient_vector_mse: 9628.0654 - val_loss: 508349.5664 - val_calorie_loss: 502733.7812 - val_nutrient_vector_loss: 5615.7954 - val_calorie_mse: 502733.7812 - val_nutrient_vector_mse: 5615.7954\n",
      "Epoch 86/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 475509.9176 - calorie_loss: 465763.9375 - nutrient_vector_loss: 9745.8730 - calorie_mse: 465985.3438 - nutrient_vector_mse: 9770.3701\n",
      "Epoch 00086: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 475616.1752 - calorie_loss: 465981.9375 - nutrient_vector_loss: 9627.2891 - calorie_mse: 466197.7812 - nutrient_vector_mse: 9650.5420 - val_loss: 511078.0742 - val_calorie_loss: 505436.5000 - val_nutrient_vector_loss: 5641.5835 - val_calorie_mse: 505436.5000 - val_nutrient_vector_mse: 5641.5835\n",
      "Epoch 87/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 468411.8902 - calorie_loss: 458657.7500 - nutrient_vector_loss: 9754.2139 - calorie_mse: 458834.5938 - nutrient_vector_mse: 9779.0918\n",
      "Epoch 00087: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 470598.5354 - calorie_loss: 460989.9375 - nutrient_vector_loss: 9602.8047 - calorie_mse: 461171.7812 - nutrient_vector_mse: 9626.2832 - val_loss: 514016.0469 - val_calorie_loss: 508380.6875 - val_nutrient_vector_loss: 5635.3765 - val_calorie_mse: 508380.6875 - val_nutrient_vector_mse: 5635.3765\n",
      "Epoch 88/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 470513.4460 - calorie_loss: 460793.1250 - nutrient_vector_loss: 9720.3438 - calorie_mse: 460991.1875 - nutrient_vector_mse: 9744.6182\n",
      "Epoch 00088: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 470303.1658 - calorie_loss: 460711.0625 - nutrient_vector_loss: 9585.9844 - calorie_mse: 460902.9062 - nutrient_vector_mse: 9608.9531 - val_loss: 509661.1562 - val_calorie_loss: 503964.6875 - val_nutrient_vector_loss: 5696.5078 - val_calorie_mse: 503964.6875 - val_nutrient_vector_mse: 5696.5078\n",
      "Epoch 89/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 475462.5559 - calorie_loss: 465735.5312 - nutrient_vector_loss: 9727.0479 - calorie_mse: 465846.7812 - nutrient_vector_mse: 9751.0684\n",
      "Epoch 00089: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 473207.0892 - calorie_loss: 463624.6562 - nutrient_vector_loss: 9579.0020 - calorie_mse: 463723.3438 - nutrient_vector_mse: 9601.6631 - val_loss: 515692.1836 - val_calorie_loss: 509919.5312 - val_nutrient_vector_loss: 5772.6543 - val_calorie_mse: 509919.5312 - val_nutrient_vector_mse: 5772.6543\n",
      "Epoch 90/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469007.5729 - calorie_loss: 459280.7812 - nutrient_vector_loss: 9726.7236 - calorie_mse: 459374.4062 - nutrient_vector_mse: 9750.2930\n",
      "Epoch 00090: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 87s 3s/step - loss: 468612.3459 - calorie_loss: 459025.0000 - nutrient_vector_loss: 9584.0713 - calorie_mse: 459114.7500 - nutrient_vector_mse: 9606.3193 - val_loss: 519111.0273 - val_calorie_loss: 513322.4375 - val_nutrient_vector_loss: 5788.5986 - val_calorie_mse: 513322.4375 - val_nutrient_vector_mse: 5788.5986\n",
      "Epoch 91/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469787.2367 - calorie_loss: 460022.3750 - nutrient_vector_loss: 9764.8604 - calorie_mse: 460227.0312 - nutrient_vector_mse: 9789.5352\n",
      "Epoch 00091: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 468366.8893 - calorie_loss: 458767.7500 - nutrient_vector_loss: 9592.9414 - calorie_mse: 458960.8750 - nutrient_vector_mse: 9616.1328 - val_loss: 511096.1875 - val_calorie_loss: 505398.7812 - val_nutrient_vector_loss: 5697.4204 - val_calorie_mse: 505398.7812 - val_nutrient_vector_mse: 5697.4204\n",
      "Epoch 92/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469151.3939 - calorie_loss: 459436.5312 - nutrient_vector_loss: 9714.8203 - calorie_mse: 459665.6875 - nutrient_vector_mse: 9739.2266\n",
      "Epoch 00092: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 87s 3s/step - loss: 467518.7623 - calorie_loss: 457940.1250 - nutrient_vector_loss: 9571.7832 - calorie_mse: 458155.9375 - nutrient_vector_mse: 9594.8418 - val_loss: 527016.1133 - val_calorie_loss: 521370.8438 - val_nutrient_vector_loss: 5645.2544 - val_calorie_mse: 521370.8438 - val_nutrient_vector_mse: 5645.2544\n",
      "Epoch 93/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 466249.2992 - calorie_loss: 456555.9688 - nutrient_vector_loss: 9693.2969 - calorie_mse: 456717.5312 - nutrient_vector_mse: 9717.7021\n",
      "Epoch 00093: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 468409.4978 - calorie_loss: 458842.9375 - nutrient_vector_loss: 9561.1025 - calorie_mse: 459009.7812 - nutrient_vector_mse: 9584.2080 - val_loss: 519316.0352 - val_calorie_loss: 513652.9375 - val_nutrient_vector_loss: 5663.1162 - val_calorie_mse: 513652.9375 - val_nutrient_vector_mse: 5663.1162\n",
      "Epoch 94/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 472663.2216 - calorie_loss: 462918.0938 - nutrient_vector_loss: 9745.1406 - calorie_mse: 463062.8438 - nutrient_vector_mse: 9769.2949\n",
      "Epoch 00094: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 471122.2588 - calorie_loss: 461541.7500 - nutrient_vector_loss: 9576.0215 - calorie_mse: 461676.2188 - nutrient_vector_mse: 9598.7197 - val_loss: 513453.1562 - val_calorie_loss: 507810.5000 - val_nutrient_vector_loss: 5642.6562 - val_calorie_mse: 507810.5000 - val_nutrient_vector_mse: 5642.6562\n",
      "Epoch 95/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 462199.0634 - calorie_loss: 457449.0938 - nutrient_vector_loss: 4749.9590 - calorie_mse: 457491.6562 - nutrient_vector_mse: 4750.7852\n",
      "Epoch 00095: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 466260.6192 - calorie_loss: 456680.8438 - nutrient_vector_loss: 9578.0459 - calorie_mse: 456718.8125 - nutrient_vector_mse: 9600.0186 - val_loss: 516680.1484 - val_calorie_loss: 511017.6875 - val_nutrient_vector_loss: 5662.4673 - val_calorie_mse: 511017.6875 - val_nutrient_vector_mse: 5662.4673\n",
      "Epoch 96/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 470479.0616 - calorie_loss: 460746.1250 - nutrient_vector_loss: 9732.9873 - calorie_mse: 460883.0312 - nutrient_vector_mse: 9757.1523\n",
      "Epoch 00096: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 469670.7962 - calorie_loss: 460090.9062 - nutrient_vector_loss: 9575.5664 - calorie_mse: 460220.9062 - nutrient_vector_mse: 9598.3262 - val_loss: 510437.4805 - val_calorie_loss: 504767.7500 - val_nutrient_vector_loss: 5669.7148 - val_calorie_mse: 504767.7500 - val_nutrient_vector_mse: 5669.7148\n",
      "Epoch 97/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 467530.3759 - calorie_loss: 457839.4688 - nutrient_vector_loss: 9690.9697 - calorie_mse: 457956.0625 - nutrient_vector_mse: 9714.8975\n",
      "Epoch 00097: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 468178.2780 - calorie_loss: 458600.5625 - nutrient_vector_loss: 9573.8027 - calorie_mse: 458717.0625 - nutrient_vector_mse: 9596.5098 - val_loss: 508799.3672 - val_calorie_loss: 503143.9062 - val_nutrient_vector_loss: 5655.4521 - val_calorie_mse: 503143.9062 - val_nutrient_vector_mse: 5655.4521\n",
      "Epoch 98/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469265.9318 - calorie_loss: 459568.8438 - nutrient_vector_loss: 9697.0596 - calorie_mse: 459753.1562 - nutrient_vector_mse: 9721.1904\n",
      "Epoch 00098: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 89s 3s/step - loss: 469466.5205 - calorie_loss: 459915.7500 - nutrient_vector_loss: 9544.9277 - calorie_mse: 460096.1562 - nutrient_vector_mse: 9567.6777 - val_loss: 506205.7500 - val_calorie_loss: 500605.3125 - val_nutrient_vector_loss: 5600.4561 - val_calorie_mse: 500605.3125 - val_nutrient_vector_mse: 5600.4561\n",
      "Epoch 99/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 468609.1468 - calorie_loss: 458871.8438 - nutrient_vector_loss: 9737.2920 - calorie_mse: 458959.5938 - nutrient_vector_mse: 9761.1924\n",
      "Epoch 00099: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 88s 3s/step - loss: 469731.5436 - calorie_loss: 460150.4688 - nutrient_vector_loss: 9577.8389 - calorie_mse: 460241.2500 - nutrient_vector_mse: 9600.3340 - val_loss: 516755.5820 - val_calorie_loss: 511041.1875 - val_nutrient_vector_loss: 5714.3843 - val_calorie_mse: 511041.1875 - val_nutrient_vector_mse: 5714.3843\n",
      "Epoch 100/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 468451.4517 - calorie_loss: 458703.6875 - nutrient_vector_loss: 9747.7441 - calorie_mse: 458845.1562 - nutrient_vector_mse: 9771.5293\n",
      "Epoch 00100: val_calorie_loss did not improve from 496642.90625\n",
      "34/34 [==============================] - 89s 3s/step - loss: 469782.8818 - calorie_loss: 460181.6875 - nutrient_vector_loss: 9596.4473 - calorie_mse: 460325.4375 - nutrient_vector_mse: 9618.8662 - val_loss: 519986.4297 - val_calorie_loss: 514255.9688 - val_nutrient_vector_loss: 5730.4600 - val_calorie_mse: 514255.9688 - val_nutrient_vector_mse: 5730.4600\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.optimizers import Adam\n",
    "from tensorflow.keras.callbacks import ModelCheckpoint\n",
    "from tensorflow.keras import metrics\n",
    "\n",
    "model.compile(optimizer=Adam(lr=1e-3), loss={'calorie':'mse', 'nutrient_vector':'mse'}\n",
    "              , metrics=['mse'])\n",
    "\n",
    "checkpointer = ModelCheckpoint(filepath='./multi-output/nutrients/recipe_nutrient_vector_100epoch.h5', verbose=1, \n",
    "                               monitor='val_calorie_loss', mode='auto', save_best_only=True)\n",
    "\n",
    "history = model.fit_generator(generator=train_generator, \n",
    "                    steps_per_epoch=round(train_generator.n/train_generator.batch_size),\n",
    "                    epochs=100,\n",
    "                    validation_data=valid_generator,\n",
    "                    validation_steps=round(valid_generator.n/valid_generator.batch_size),\n",
    "                    callbacks=[checkpointer]\n",
    "                   )\n",
    "\n",
    "\n",
    "# save model and history\n",
    "with open('./multi-output/nutrients/recipe_nutrient_vector_100epoch.pkl','wb') as f:\n",
    "    pickle.dump(history.history, f) \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2. output: calorie+category vector"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 4381 validated image filenames.\n",
      "Found 1095 validated image filenames.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/uceezku/project/lib64/python3.6/site-packages/keras_preprocessing/image/dataframe_iterator.py:282: UserWarning: Found 6 invalid image filename(s) in x_col=\"file_name\". These filename(s) will be ignored.\n",
      "  .format(n_invalid, x_col)\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "\n",
    "datagen=ImageDataGenerator(\n",
    "    #rescale=1/255, \n",
    "    validation_split=0.2, \n",
    "    rotation_range=20,\n",
    "    width_shift_range=0.2,\n",
    "    height_shift_range=0.2,\n",
    "    horizontal_flip=True,\n",
    "    )\n",
    "\n",
    "train_generator = datagen.flow_from_dataframe(\n",
    "    dataframe=train_data,\n",
    "    directory='./data/train/',\n",
    "    target_size = (256,256),\n",
    "    x_col='file_name',\n",
    "    y_col= ['calorie_per_recipe', 'category_vector'],\n",
    "    batch_size=128,\n",
    "    shuffle=True,\n",
    "    subset='training',\n",
    "    class_mode='multi_output')\n",
    "\n",
    "\n",
    "valid_generator = datagen.flow_from_dataframe(\n",
    "    dataframe=train_data,\n",
    "    directory='./data/train/',\n",
    "    target_size = (256,256),\n",
    "    x_col='file_name',\n",
    "    y_col= ['calorie_per_recipe', 'category_vector'],\n",
    "    batch_size=128,\n",
    "    shuffle=True,\n",
    "    subset='validation',\n",
    "    class_mode='multi_output')\n",
    "    #validate_filenames=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-5-a742a0748662>:19: Model.fit_generator (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use Model.fit, which supports generators.\n",
      "Train for 34 steps, validate for 9 steps\n",
      "Epoch 1/100\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/uceezku/project/lib64/python3.6/site-packages/PIL/Image.py:963: UserWarning: Palette images with Transparency expressed in bytes should be converted to RGBA images\n",
      "  \"Palette images with Transparency expressed in bytes should be \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33/34 [============================>.] - ETA: 3s - loss: 2256159.2235 - calorie_loss: 2256152.7500 - category_vector_loss: 6.3916 - calorie_mse: 2268023.5000 - category_vector_mse: 0.1098\n",
      "Epoch 00001: val_calorie_loss improved from inf to 2518097.00000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 170s 5s/step - loss: 2248534.5279 - calorie_loss: 2248204.2500 - category_vector_loss: 6.5264 - calorie_mse: 2259532.7500 - category_vector_mse: 0.1101 - val_loss: 2518104.7222 - val_calorie_loss: 2518097.0000 - val_category_vector_loss: 7.9451 - val_calorie_mse: 2502326.0000 - val_category_vector_mse: 0.1114\n",
      "Epoch 2/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 1531658.2386 - calorie_loss: 1531641.7500 - category_vector_loss: 16.5356 - calorie_mse: 1530106.0000 - category_vector_mse: 0.1310\n",
      "Epoch 00002: val_calorie_loss improved from 2518097.00000 to 1646814.25000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 97s 3s/step - loss: 1518572.0821 - calorie_loss: 1518606.6250 - category_vector_loss: 16.7069 - calorie_mse: 1516813.6250 - category_vector_mse: 0.1314 - val_loss: 1646828.2639 - val_calorie_loss: 1646814.2500 - val_category_vector_loss: 14.1644 - val_calorie_mse: 1637158.8750 - val_category_vector_mse: 0.1123\n",
      "Epoch 3/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 812255.4593 - calorie_loss: 812230.6875 - category_vector_loss: 24.8342 - calorie_mse: 819927.4375 - category_vector_mse: 0.1339\n",
      "Epoch 00003: val_calorie_loss improved from 1646814.25000 to 966306.12500, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 811162.4775 - calorie_loss: 810925.1250 - category_vector_loss: 24.9748 - calorie_mse: 818359.8125 - category_vector_mse: 0.1339 - val_loss: 966329.6458 - val_calorie_loss: 966306.1250 - val_category_vector_loss: 23.4581 - val_calorie_mse: 964045.0625 - val_category_vector_mse: 0.1664\n",
      "Epoch 4/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 563683.4953 - calorie_loss: 563655.2500 - category_vector_loss: 28.2362 - calorie_mse: 567964.6250 - category_vector_mse: 0.1376\n",
      "Epoch 00004: val_calorie_loss improved from 966306.12500 to 741646.12500, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 562424.3830 - calorie_loss: 562277.6875 - category_vector_loss: 28.1933 - calorie_mse: 566425.3125 - category_vector_mse: 0.1375 - val_loss: 741671.0694 - val_calorie_loss: 741646.1250 - val_category_vector_loss: 25.0184 - val_calorie_mse: 742283.1250 - val_category_vector_mse: 0.1667\n",
      "Epoch 5/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 542606.3722 - calorie_loss: 542579.4375 - category_vector_loss: 26.8128 - calorie_mse: 546030.2500 - category_vector_mse: 0.1357\n",
      "Epoch 00005: val_calorie_loss improved from 741646.12500 to 728243.50000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 543094.5888 - calorie_loss: 542971.6875 - category_vector_loss: 26.8906 - calorie_mse: 546327.7500 - category_vector_mse: 0.1361 - val_loss: 728259.6736 - val_calorie_loss: 728243.5000 - val_category_vector_loss: 16.1928 - val_calorie_mse: 729049.7500 - val_category_vector_mse: 0.1419\n",
      "Epoch 6/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 538994.9290 - calorie_loss: 538970.8750 - category_vector_loss: 24.1179 - calorie_mse: 541787.8125 - category_vector_mse: 0.1361\n",
      "Epoch 00006: val_calorie_loss did not improve from 728243.50000\n",
      "34/34 [==============================] - 95s 3s/step - loss: 539349.1574 - calorie_loss: 539246.8750 - category_vector_loss: 24.0658 - calorie_mse: 541985.4375 - category_vector_mse: 0.1360 - val_loss: 728909.6875 - val_calorie_loss: 728888.0000 - val_category_vector_loss: 21.6966 - val_calorie_mse: 728343.0625 - val_category_vector_mse: 0.1606\n",
      "Epoch 7/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 539844.5303 - calorie_loss: 539823.0625 - category_vector_loss: 21.5209 - calorie_mse: 542609.5000 - category_vector_mse: 0.1336\n",
      "Epoch 00007: val_calorie_loss improved from 728243.50000 to 716892.50000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 97s 3s/step - loss: 540345.3373 - calorie_loss: 540246.4375 - category_vector_loss: 21.5035 - calorie_mse: 542958.8125 - category_vector_mse: 0.1337 - val_loss: 716910.6111 - val_calorie_loss: 716892.5000 - val_category_vector_loss: 18.0552 - val_calorie_mse: 717213.4375 - val_category_vector_mse: 0.1387\n",
      "Epoch 8/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 541331.1458 - calorie_loss: 541311.9375 - category_vector_loss: 19.2394 - calorie_mse: 544882.5000 - category_vector_mse: 0.1322\n",
      "Epoch 00008: val_calorie_loss improved from 716892.50000 to 713356.75000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 95s 3s/step - loss: 540680.9807 - calorie_loss: 540563.3125 - category_vector_loss: 19.2761 - calorie_mse: 544008.9375 - category_vector_mse: 0.1324 - val_loss: 713376.4097 - val_calorie_loss: 713356.7500 - val_category_vector_loss: 19.6043 - val_calorie_mse: 714029.5000 - val_category_vector_mse: 0.1115\n",
      "Epoch 9/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 539161.3456 - calorie_loss: 539144.3125 - category_vector_loss: 17.0223 - calorie_mse: 541559.1875 - category_vector_mse: 0.1313\n",
      "Epoch 00009: val_calorie_loss improved from 713356.75000 to 713092.37500, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 537723.8344 - calorie_loss: 537640.8125 - category_vector_loss: 17.0596 - calorie_mse: 539948.0000 - category_vector_mse: 0.1312 - val_loss: 713117.5625 - val_calorie_loss: 713092.3750 - val_category_vector_loss: 25.1498 - val_calorie_mse: 712988.4375 - val_category_vector_mse: 0.1651\n",
      "Epoch 10/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 537692.0417 - calorie_loss: 537676.7500 - category_vector_loss: 15.3428 - calorie_mse: 541978.3750 - category_vector_mse: 0.1282\n",
      "Epoch 00010: val_calorie_loss improved from 713092.37500 to 707687.50000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 538519.6045 - calorie_loss: 538384.6250 - category_vector_loss: 15.3103 - calorie_mse: 542573.3125 - category_vector_mse: 0.1280 - val_loss: 707709.4167 - val_calorie_loss: 707687.5000 - val_category_vector_loss: 21.8963 - val_calorie_mse: 708273.1875 - val_category_vector_mse: 0.1526\n",
      "Epoch 11/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 539264.4839 - calorie_loss: 539251.1875 - category_vector_loss: 13.2540 - calorie_mse: 541336.2500 - category_vector_mse: 0.1254\n",
      "Epoch 00011: val_calorie_loss improved from 707687.50000 to 699554.93750, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 97s 3s/step - loss: 536972.9256 - calorie_loss: 536903.5000 - category_vector_loss: 13.2091 - calorie_mse: 538871.0625 - category_vector_mse: 0.1254 - val_loss: 699575.2361 - val_calorie_loss: 699554.9375 - val_category_vector_loss: 20.3150 - val_calorie_mse: 700093.1250 - val_category_vector_mse: 0.1025\n",
      "Epoch 12/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 538233.4432 - calorie_loss: 538221.8750 - category_vector_loss: 11.5808 - calorie_mse: 538221.8750 - category_vector_mse: 0.1245\n",
      "Epoch 00012: val_calorie_loss improved from 699554.93750 to 693036.50000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 98s 3s/step - loss: 533915.7405 - calorie_loss: 533807.3750 - category_vector_loss: 11.5283 - calorie_mse: 537198.4375 - category_vector_mse: 0.1245 - val_loss: 693053.4444 - val_calorie_loss: 693036.5000 - val_category_vector_loss: 16.9552 - val_calorie_mse: 694042.7500 - val_category_vector_mse: 0.1342\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 13/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 537569.5199 - calorie_loss: 537559.2500 - category_vector_loss: 10.2230 - calorie_mse: 539892.9375 - category_vector_mse: 0.1199\n",
      "Epoch 00013: val_calorie_loss did not improve from 693036.50000\n",
      "34/34 [==============================] - 96s 3s/step - loss: 537077.5095 - calorie_loss: 537003.0000 - category_vector_loss: 10.2103 - calorie_mse: 539253.5000 - category_vector_mse: 0.1198 - val_loss: 694515.5833 - val_calorie_loss: 694497.9375 - val_category_vector_loss: 17.6555 - val_calorie_mse: 695405.0625 - val_category_vector_mse: 0.1106\n",
      "Epoch 14/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 534473.4640 - calorie_loss: 534464.5625 - category_vector_loss: 8.9097 - calorie_mse: 537013.0000 - category_vector_mse: 0.1160\n",
      "Epoch 00014: val_calorie_loss improved from 693036.50000 to 680451.31250, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 532968.9659 - calorie_loss: 532890.5000 - category_vector_loss: 8.8840 - calorie_mse: 535325.6250 - category_vector_mse: 0.1159 - val_loss: 680469.9306 - val_calorie_loss: 680451.3125 - val_category_vector_loss: 18.5906 - val_calorie_mse: 681849.1250 - val_category_vector_mse: 0.1393\n",
      "Epoch 15/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 535419.9366 - calorie_loss: 535412.6875 - category_vector_loss: 7.2611 - calorie_mse: 535412.6875 - category_vector_mse: 0.1093\n",
      "Epoch 00015: val_calorie_loss improved from 680451.31250 to 666886.56250, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 99s 3s/step - loss: 535047.3493 - calorie_loss: 535040.1250 - category_vector_loss: 7.2307 - calorie_mse: 535040.1250 - category_vector_mse: 0.1091 - val_loss: 666904.6736 - val_calorie_loss: 666886.5625 - val_category_vector_loss: 18.0837 - val_calorie_mse: 669230.3125 - val_category_vector_mse: 0.1210\n",
      "Epoch 16/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 532063.6326 - calorie_loss: 532057.1875 - category_vector_loss: 6.3666 - calorie_mse: 532057.1875 - category_vector_mse: 0.1057\n",
      "Epoch 00016: val_calorie_loss improved from 666886.56250 to 665814.50000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 99s 3s/step - loss: 532394.2978 - calorie_loss: 532387.9375 - category_vector_loss: 6.3316 - calorie_mse: 532387.9375 - category_vector_mse: 0.1055 - val_loss: 665830.5208 - val_calorie_loss: 665814.5000 - val_category_vector_loss: 15.9945 - val_calorie_mse: 666832.5625 - val_category_vector_mse: 0.0941\n",
      "Epoch 17/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 527521.7850 - calorie_loss: 527516.2500 - category_vector_loss: 5.5788 - calorie_mse: 530410.5000 - category_vector_mse: 0.0979\n",
      "Epoch 00017: val_calorie_loss improved from 665814.50000 to 665522.06250, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 527004.5363 - calorie_loss: 526919.2500 - category_vector_loss: 5.5498 - calorie_mse: 529712.5000 - category_vector_mse: 0.0977 - val_loss: 665537.0000 - val_calorie_loss: 665522.0625 - val_category_vector_loss: 14.9039 - val_calorie_mse: 666113.9375 - val_category_vector_mse: 0.1081\n",
      "Epoch 18/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 520956.4830 - calorie_loss: 520951.5000 - category_vector_loss: 4.9042 - calorie_mse: 523636.6875 - category_vector_mse: 0.0940\n",
      "Epoch 00018: val_calorie_loss improved from 665522.06250 to 650363.06250, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 521719.9307 - calorie_loss: 521640.0625 - category_vector_loss: 4.9196 - calorie_mse: 524260.4375 - category_vector_mse: 0.0941 - val_loss: 650377.0556 - val_calorie_loss: 650363.0625 - val_category_vector_loss: 14.0344 - val_calorie_mse: 651301.8750 - val_category_vector_mse: 0.1295\n",
      "Epoch 19/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 525168.6439 - calorie_loss: 525164.0625 - category_vector_loss: 4.5349 - calorie_mse: 528611.1875 - category_vector_mse: 0.0914\n",
      "Epoch 00019: val_calorie_loss did not improve from 650363.06250\n",
      "34/34 [==============================] - 97s 3s/step - loss: 526654.7612 - calorie_loss: 526553.7500 - category_vector_loss: 4.5148 - calorie_mse: 529929.5000 - category_vector_mse: 0.0913 - val_loss: 652838.1250 - val_calorie_loss: 652825.7500 - val_category_vector_loss: 12.4227 - val_calorie_mse: 654698.6250 - val_category_vector_mse: 0.1015\n",
      "Epoch 20/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 526966.8977 - calorie_loss: 526963.1250 - category_vector_loss: 3.8426 - calorie_mse: 526963.1250 - category_vector_mse: 0.0862\n",
      "Epoch 00020: val_calorie_loss improved from 650363.06250 to 637092.25000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 98s 3s/step - loss: 527483.2316 - calorie_loss: 527479.5000 - category_vector_loss: 3.8283 - calorie_mse: 527479.5000 - category_vector_mse: 0.0863 - val_loss: 637103.9236 - val_calorie_loss: 637092.2500 - val_category_vector_loss: 11.7280 - val_calorie_mse: 638275.4375 - val_category_vector_mse: 0.0998\n",
      "Epoch 21/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 529099.1553 - calorie_loss: 529095.6250 - category_vector_loss: 3.5654 - calorie_mse: 531120.1875 - category_vector_mse: 0.0858\n",
      "Epoch 00021: val_calorie_loss did not improve from 637092.25000\n",
      "34/34 [==============================] - 96s 3s/step - loss: 526304.1068 - calorie_loss: 526246.3750 - category_vector_loss: 3.5855 - calorie_mse: 528143.6250 - category_vector_mse: 0.0856 - val_loss: 641608.9861 - val_calorie_loss: 641597.2500 - val_category_vector_loss: 11.6860 - val_calorie_mse: 642101.8125 - val_category_vector_mse: 0.1172\n",
      "Epoch 22/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 525057.0597 - calorie_loss: 525053.7500 - category_vector_loss: 3.3107 - calorie_mse: 528431.3125 - category_vector_mse: 0.0831\n",
      "Epoch 00022: val_calorie_loss improved from 637092.25000 to 618926.37500, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 95s 3s/step - loss: 524345.1414 - calorie_loss: 524248.7500 - category_vector_loss: 3.3004 - calorie_mse: 527505.9375 - category_vector_mse: 0.0831 - val_loss: 618935.6111 - val_calorie_loss: 618926.3750 - val_category_vector_loss: 9.2218 - val_calorie_mse: 620954.0625 - val_category_vector_mse: 0.0912\n",
      "Epoch 23/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 522729.1146 - calorie_loss: 522726.0625 - category_vector_loss: 2.9942 - calorie_mse: 526725.5000 - category_vector_mse: 0.0795\n",
      "Epoch 00023: val_calorie_loss did not improve from 618926.37500\n",
      "34/34 [==============================] - 96s 3s/step - loss: 520342.8702 - calorie_loss: 520230.6562 - category_vector_loss: 2.9866 - calorie_mse: 524051.6250 - category_vector_mse: 0.0795 - val_loss: 620130.4028 - val_calorie_loss: 620123.0000 - val_category_vector_loss: 7.3666 - val_calorie_mse: 621315.5000 - val_category_vector_mse: 0.0856\n",
      "Epoch 24/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 514755.6487 - calorie_loss: 514752.6562 - category_vector_loss: 2.9754 - calorie_mse: 516875.4062 - category_vector_mse: 0.0801\n",
      "Epoch 00024: val_calorie_loss improved from 618926.37500 to 615065.50000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 515739.9924 - calorie_loss: 515677.5938 - category_vector_loss: 2.9743 - calorie_mse: 517757.9688 - category_vector_mse: 0.0800 - val_loss: 615076.3611 - val_calorie_loss: 615065.5000 - val_category_vector_loss: 10.8145 - val_calorie_mse: 616835.1250 - val_category_vector_mse: 0.0958\n",
      "Epoch 25/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 515101.6591 - calorie_loss: 515098.8438 - category_vector_loss: 2.8281 - calorie_mse: 515098.8438 - category_vector_mse: 0.0798\n",
      "Epoch 00025: val_calorie_loss improved from 615065.50000 to 614418.50000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 97s 3s/step - loss: 515735.5129 - calorie_loss: 515732.7188 - category_vector_loss: 2.8233 - calorie_mse: 515732.7188 - category_vector_mse: 0.0797 - val_loss: 614426.1250 - val_calorie_loss: 614418.5000 - val_category_vector_loss: 7.6526 - val_calorie_mse: 614635.0000 - val_category_vector_mse: 0.0864\n",
      "Epoch 26/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 510138.5199 - calorie_loss: 510135.8125 - category_vector_loss: 2.6952 - calorie_mse: 512880.9062 - category_vector_mse: 0.0777\n",
      "Epoch 00026: val_calorie_loss improved from 614418.50000 to 597294.81250, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 95s 3s/step - loss: 509019.2905 - calorie_loss: 508941.2812 - category_vector_loss: 2.6978 - calorie_mse: 511576.0000 - category_vector_mse: 0.0778 - val_loss: 597302.9549 - val_calorie_loss: 597294.8125 - val_category_vector_loss: 8.1505 - val_calorie_mse: 598823.8125 - val_category_vector_mse: 0.0868\n",
      "Epoch 27/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 506644.6591 - calorie_loss: 506641.9688 - category_vector_loss: 2.5771 - calorie_mse: 509876.0938 - category_vector_mse: 0.0769\n",
      "Epoch 00027: val_calorie_loss improved from 597294.81250 to 589789.75000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 508887.7930 - calorie_loss: 508794.0625 - category_vector_loss: 2.5732 - calorie_mse: 511980.9062 - category_vector_mse: 0.0769 - val_loss: 589799.1146 - val_calorie_loss: 589789.7500 - val_category_vector_loss: 9.3747 - val_calorie_mse: 590858.7500 - val_category_vector_mse: 0.0908\n",
      "Epoch 28/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 507822.6449 - calorie_loss: 507820.1250 - category_vector_loss: 2.5444 - calorie_mse: 510333.0000 - category_vector_mse: 0.0748\n",
      "Epoch 00028: val_calorie_loss did not improve from 589789.75000\n",
      "34/34 [==============================] - 96s 3s/step - loss: 508687.0237 - calorie_loss: 508614.3438 - category_vector_loss: 2.5334 - calorie_mse: 511070.0938 - category_vector_mse: 0.0747 - val_loss: 596462.9792 - val_calorie_loss: 596455.2500 - val_category_vector_loss: 7.7025 - val_calorie_mse: 598130.6250 - val_category_vector_mse: 0.0886\n",
      "Epoch 29/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 504333.3769 - calorie_loss: 504330.7812 - category_vector_loss: 2.5618 - calorie_mse: 507109.5312 - category_vector_mse: 0.0758\n",
      "Epoch 00029: val_calorie_loss did not improve from 589789.75000\n",
      "34/34 [==============================] - 96s 3s/step - loss: 506867.5055 - calorie_loss: 506786.2812 - category_vector_loss: 2.5621 - calorie_mse: 509538.5312 - category_vector_mse: 0.0758 - val_loss: 590749.9167 - val_calorie_loss: 590741.5000 - val_category_vector_loss: 8.3871 - val_calorie_mse: 591667.6250 - val_category_vector_mse: 0.0927\n",
      "Epoch 30/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 505789.7386 - calorie_loss: 505787.3125 - category_vector_loss: 2.4830 - calorie_mse: 507863.8438 - category_vector_mse: 0.0746\n",
      "Epoch 00030: val_calorie_loss improved from 589789.75000 to 576628.81250, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 507592.1025 - calorie_loss: 507530.9375 - category_vector_loss: 2.4844 - calorie_mse: 509585.5938 - category_vector_mse: 0.0746 - val_loss: 576636.9201 - val_calorie_loss: 576628.8125 - val_category_vector_loss: 8.1007 - val_calorie_mse: 578400.5000 - val_category_vector_mse: 0.0886\n",
      "Epoch 31/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 503193.1989 - calorie_loss: 503190.5625 - category_vector_loss: 2.5827 - calorie_mse: 505583.2812 - category_vector_mse: 0.0760\n",
      "Epoch 00031: val_calorie_loss improved from 576628.81250 to 572289.56250, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 503010.6543 - calorie_loss: 502941.8750 - category_vector_loss: 2.5847 - calorie_mse: 505256.7812 - category_vector_mse: 0.0760 - val_loss: 572294.8611 - val_calorie_loss: 572289.5625 - val_category_vector_loss: 5.3222 - val_calorie_mse: 573728.9375 - val_category_vector_mse: 0.0843\n",
      "Epoch 32/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 505150.7595 - calorie_loss: 505148.3438 - category_vector_loss: 2.4037 - calorie_mse: 505148.3438 - category_vector_mse: 0.0746\n",
      "Epoch 00032: val_calorie_loss improved from 572289.56250 to 559408.68750, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 501483.2018 - calorie_loss: 501398.4688 - category_vector_loss: 2.4065 - calorie_mse: 504278.9688 - category_vector_mse: 0.0746 - val_loss: 559414.3368 - val_calorie_loss: 559408.6875 - val_category_vector_loss: 5.6729 - val_calorie_mse: 562389.4375 - val_category_vector_mse: 0.0870\n",
      "Epoch 33/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 503381.1903 - calorie_loss: 503378.6562 - category_vector_loss: 2.5775 - calorie_mse: 506359.9375 - category_vector_mse: 0.0764\n",
      "Epoch 00033: val_calorie_loss did not improve from 559408.68750\n",
      "34/34 [==============================] - 95s 3s/step - loss: 503202.7813 - calorie_loss: 503117.8125 - category_vector_loss: 2.5804 - calorie_mse: 506003.2812 - category_vector_mse: 0.0763 - val_loss: 560968.5625 - val_calorie_loss: 560962.0000 - val_category_vector_loss: 6.5365 - val_calorie_mse: 563046.8750 - val_category_vector_mse: 0.0911\n",
      "Epoch 34/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 506704.8835 - calorie_loss: 506702.3750 - category_vector_loss: 2.4952 - calorie_mse: 509080.4688 - category_vector_mse: 0.0759\n",
      "Epoch 00034: val_calorie_loss improved from 559408.68750 to 554216.62500, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 504628.5666 - calorie_loss: 504561.5938 - category_vector_loss: 2.4954 - calorie_mse: 506818.3125 - category_vector_mse: 0.0759 - val_loss: 554222.0694 - val_calorie_loss: 554216.6250 - val_category_vector_loss: 5.4613 - val_calorie_mse: 556294.6875 - val_category_vector_mse: 0.0877\n",
      "Epoch 35/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 503456.5180 - calorie_loss: 503454.1562 - category_vector_loss: 2.4269 - calorie_mse: 505725.6562 - category_vector_mse: 0.0748\n",
      "Epoch 00035: val_calorie_loss improved from 554216.62500 to 549685.62500, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 501369.9365 - calorie_loss: 501306.0625 - category_vector_loss: 2.4226 - calorie_mse: 503459.1875 - category_vector_mse: 0.0748 - val_loss: 549691.5174 - val_calorie_loss: 549685.6250 - val_category_vector_loss: 5.9005 - val_calorie_mse: 552117.2500 - val_category_vector_mse: 0.0872\n",
      "Epoch 36/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 499152.6487 - calorie_loss: 499150.2500 - category_vector_loss: 2.4353 - calorie_mse: 501524.4062 - category_vector_mse: 0.0753\n",
      "Epoch 00036: val_calorie_loss did not improve from 549685.62500\n",
      "34/34 [==============================] - 95s 3s/step - loss: 500389.6172 - calorie_loss: 500320.6562 - category_vector_loss: 2.4352 - calorie_mse: 502650.6250 - category_vector_mse: 0.0753 - val_loss: 560810.6424 - val_calorie_loss: 560805.1875 - val_category_vector_loss: 5.4517 - val_calorie_mse: 562212.7500 - val_category_vector_mse: 0.0900\n",
      "Epoch 37/100\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33/34 [============================>.] - ETA: 2s - loss: 493286.8134 - calorie_loss: 493284.4062 - category_vector_loss: 2.4037 - calorie_mse: 495922.5000 - category_vector_mse: 0.0754\n",
      "Epoch 00037: val_calorie_loss improved from 549685.62500 to 545685.50000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 495499.2194 - calorie_loss: 495422.2812 - category_vector_loss: 2.3952 - calorie_mse: 498030.7500 - category_vector_mse: 0.0753 - val_loss: 545691.4236 - val_calorie_loss: 545685.5000 - val_category_vector_loss: 5.9407 - val_calorie_mse: 547951.9375 - val_category_vector_mse: 0.0902\n",
      "Epoch 38/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 498795.9034 - calorie_loss: 498793.5000 - category_vector_loss: 2.4183 - calorie_mse: 500605.3438 - category_vector_mse: 0.0741\n",
      "Epoch 00038: val_calorie_loss improved from 545685.50000 to 540783.31250, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 495837.3675 - calorie_loss: 495786.7500 - category_vector_loss: 2.4199 - calorie_mse: 497474.0625 - category_vector_mse: 0.0741 - val_loss: 540789.4965 - val_calorie_loss: 540783.3125 - val_category_vector_loss: 6.1700 - val_calorie_mse: 543131.2500 - val_category_vector_mse: 0.0915\n",
      "Epoch 39/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 490932.2680 - calorie_loss: 490929.8125 - category_vector_loss: 2.4019 - calorie_mse: 493563.7812 - category_vector_mse: 0.0741\n",
      "Epoch 00039: val_calorie_loss improved from 540783.31250 to 535324.25000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 492428.0375 - calorie_loss: 492351.6562 - category_vector_loss: 2.3964 - calorie_mse: 494939.4375 - category_vector_mse: 0.0741 - val_loss: 535330.0174 - val_calorie_loss: 535324.2500 - val_category_vector_loss: 5.6799 - val_calorie_mse: 538153.8125 - val_category_vector_mse: 0.0831\n",
      "Epoch 40/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 496267.3920 - calorie_loss: 496265.0938 - category_vector_loss: 2.3356 - calorie_mse: 498340.9688 - category_vector_mse: 0.0739\n",
      "Epoch 00040: val_calorie_loss did not improve from 535324.25000\n",
      "34/34 [==============================] - 95s 3s/step - loss: 494918.6857 - calorie_loss: 494859.7500 - category_vector_loss: 2.3414 - calorie_mse: 496840.4688 - category_vector_mse: 0.0740 - val_loss: 537537.8333 - val_calorie_loss: 537533.0625 - val_category_vector_loss: 4.7805 - val_calorie_mse: 540054.9375 - val_category_vector_mse: 0.0913\n",
      "Epoch 41/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 489723.7964 - calorie_loss: 489721.4375 - category_vector_loss: 2.3908 - calorie_mse: 491198.5000 - category_vector_mse: 0.0750\n",
      "Epoch 00041: val_calorie_loss improved from 535324.25000 to 531718.00000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 96s 3s/step - loss: 492563.2745 - calorie_loss: 492518.1250 - category_vector_loss: 2.3859 - calorie_mse: 494015.8438 - category_vector_mse: 0.0749 - val_loss: 531722.6007 - val_calorie_loss: 531718.0000 - val_category_vector_loss: 4.6075 - val_calorie_mse: 533819.1875 - val_category_vector_mse: 0.0927\n",
      "Epoch 42/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 496419.7509 - calorie_loss: 496417.4375 - category_vector_loss: 2.3749 - calorie_mse: 497500.3125 - category_vector_mse: 0.0753\n",
      "Epoch 00042: val_calorie_loss improved from 531718.00000 to 531366.87500, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 98s 3s/step - loss: 495985.1466 - calorie_loss: 495953.1250 - category_vector_loss: 2.3724 - calorie_mse: 496992.6250 - category_vector_mse: 0.0752 - val_loss: 531371.6875 - val_calorie_loss: 531366.8750 - val_category_vector_loss: 4.8322 - val_calorie_mse: 532762.6250 - val_category_vector_mse: 0.0962\n",
      "Epoch 43/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 487627.1619 - calorie_loss: 487624.7812 - category_vector_loss: 2.3459 - calorie_mse: 489607.3438 - category_vector_mse: 0.0738\n",
      "Epoch 00043: val_calorie_loss improved from 531366.87500 to 529304.87500, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 94s 3s/step - loss: 486816.6943 - calorie_loss: 486759.9688 - category_vector_loss: 2.3438 - calorie_mse: 488662.7500 - category_vector_mse: 0.0738 - val_loss: 529309.7569 - val_calorie_loss: 529304.8750 - val_category_vector_loss: 4.8893 - val_calorie_mse: 532122.0000 - val_category_vector_mse: 0.1021\n",
      "Epoch 44/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 485727.4508 - calorie_loss: 485725.1250 - category_vector_loss: 2.3225 - calorie_mse: 489191.3438 - category_vector_mse: 0.0736\n",
      "Epoch 00044: val_calorie_loss improved from 529304.87500 to 517661.37500, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 94s 3s/step - loss: 488821.0723 - calorie_loss: 488720.7188 - category_vector_loss: 2.3266 - calorie_mse: 492152.3125 - category_vector_mse: 0.0736 - val_loss: 517665.0590 - val_calorie_loss: 517661.3750 - val_category_vector_loss: 3.6670 - val_calorie_mse: 521112.7812 - val_category_vector_mse: 0.0872\n",
      "Epoch 45/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 484903.7121 - calorie_loss: 484901.2500 - category_vector_loss: 2.3718 - calorie_mse: 487415.2188 - category_vector_mse: 0.0739\n",
      "Epoch 00045: val_calorie_loss did not improve from 517661.37500\n",
      "34/34 [==============================] - 93s 3s/step - loss: 487284.2051 - calorie_loss: 487210.5312 - category_vector_loss: 2.3746 - calorie_mse: 489702.5938 - category_vector_mse: 0.0739 - val_loss: 520061.7361 - val_calorie_loss: 520057.6562 - val_category_vector_loss: 4.0273 - val_calorie_mse: 522811.7188 - val_category_vector_mse: 0.0907\n",
      "Epoch 46/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 487474.0653 - calorie_loss: 487471.6562 - category_vector_loss: 2.4003 - calorie_mse: 490381.7188 - category_vector_mse: 0.0747\n",
      "Epoch 00046: val_calorie_loss did not improve from 517661.37500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 487342.0304 - calorie_loss: 487259.1250 - category_vector_loss: 2.4006 - calorie_mse: 490076.6250 - category_vector_mse: 0.0748 - val_loss: 522596.3472 - val_calorie_loss: 522592.8750 - val_category_vector_loss: 3.4768 - val_calorie_mse: 525007.3125 - val_category_vector_mse: 0.0838\n",
      "Epoch 47/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 482246.3485 - calorie_loss: 482243.9688 - category_vector_loss: 2.3463 - calorie_mse: 484609.3750 - category_vector_mse: 0.0741\n",
      "Epoch 00047: val_calorie_loss did not improve from 517661.37500\n",
      "34/34 [==============================] - 94s 3s/step - loss: 484087.8262 - calorie_loss: 484018.7500 - category_vector_loss: 2.3426 - calorie_mse: 486354.2500 - category_vector_mse: 0.0740 - val_loss: 519168.0694 - val_calorie_loss: 519164.3750 - val_category_vector_loss: 3.6650 - val_calorie_mse: 521340.7188 - val_category_vector_mse: 0.0883\n",
      "Epoch 48/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 479802.9555 - calorie_loss: 479800.5312 - category_vector_loss: 2.3797 - calorie_mse: 482820.6562 - category_vector_mse: 0.0752\n",
      "Epoch 00048: val_calorie_loss did not improve from 517661.37500\n",
      "34/34 [==============================] - 93s 3s/step - loss: 480118.7807 - calorie_loss: 480032.5312 - category_vector_loss: 2.3806 - calorie_mse: 482967.1562 - category_vector_mse: 0.0752 - val_loss: 521076.2431 - val_calorie_loss: 521071.7188 - val_category_vector_loss: 4.5533 - val_calorie_mse: 523612.3438 - val_category_vector_mse: 0.0857\n",
      "Epoch 49/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 486975.8722 - calorie_loss: 486973.5625 - category_vector_loss: 2.3593 - calorie_mse: 490061.1562 - category_vector_mse: 0.0743\n",
      "Epoch 00049: val_calorie_loss improved from 517661.37500 to 515702.50000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "34/34 [==============================] - 95s 3s/step - loss: 485424.5111 - calorie_loss: 485337.7500 - category_vector_loss: 2.3614 - calorie_mse: 488294.3125 - category_vector_mse: 0.0744 - val_loss: 515706.6076 - val_calorie_loss: 515702.5000 - val_category_vector_loss: 4.0453 - val_calorie_mse: 518319.5625 - val_category_vector_mse: 0.0911\n",
      "Epoch 50/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 479904.0975 - calorie_loss: 479901.6875 - category_vector_loss: 2.3923 - calorie_mse: 482738.5625 - category_vector_mse: 0.0748\n",
      "Epoch 00050: val_calorie_loss did not improve from 515702.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 479551.4766 - calorie_loss: 479470.7500 - category_vector_loss: 2.3917 - calorie_mse: 482212.2188 - category_vector_mse: 0.0748 - val_loss: 519608.7986 - val_calorie_loss: 519603.7812 - val_category_vector_loss: 5.0189 - val_calorie_mse: 521916.3750 - val_category_vector_mse: 0.0966\n",
      "Epoch 51/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 485404.8542 - calorie_loss: 485402.5000 - category_vector_loss: 2.3577 - calorie_mse: 487767.8125 - category_vector_mse: 0.0744\n",
      "Epoch 00051: val_calorie_loss did not improve from 515702.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 484561.4622 - calorie_loss: 484494.1562 - category_vector_loss: 2.3607 - calorie_mse: 486767.1562 - category_vector_mse: 0.0744 - val_loss: 517455.4167 - val_calorie_loss: 517451.2188 - val_category_vector_loss: 4.1738 - val_calorie_mse: 520388.2188 - val_category_vector_mse: 0.0844\n",
      "Epoch 52/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 480124.5634 - calorie_loss: 480122.2812 - category_vector_loss: 2.2825 - calorie_mse: 482533.2188 - category_vector_mse: 0.0726\n",
      "Epoch 00052: val_calorie_loss did not improve from 515702.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 480046.2830 - calorie_loss: 479977.2500 - category_vector_loss: 2.2840 - calorie_mse: 482312.2812 - category_vector_mse: 0.0726 - val_loss: 518710.5833 - val_calorie_loss: 518707.0000 - val_category_vector_loss: 3.5669 - val_calorie_mse: 520681.6250 - val_category_vector_mse: 0.0823\n",
      "Epoch 53/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 480787.6278 - calorie_loss: 480785.2812 - category_vector_loss: 2.3609 - calorie_mse: 484074.3438 - category_vector_mse: 0.0747\n",
      "Epoch 00053: val_calorie_loss improved from 515702.50000 to 507314.21875, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 94s 3s/step - loss: 481058.7890 - calorie_loss: 480965.1875 - category_vector_loss: 2.3576 - calorie_mse: 484159.4375 - category_vector_mse: 0.0747 - val_loss: 507318.1146 - val_calorie_loss: 507314.2188 - val_category_vector_loss: 3.9195 - val_calorie_mse: 510884.5938 - val_category_vector_mse: 0.0922\n",
      "Epoch 54/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 482488.6354 - calorie_loss: 482486.2500 - category_vector_loss: 2.3100 - calorie_mse: 484471.7812 - category_vector_mse: 0.0739\n",
      "Epoch 00054: val_calorie_loss did not improve from 507314.21875\n",
      "34/34 [==============================] - 94s 3s/step - loss: 481212.7034 - calorie_loss: 481156.1875 - category_vector_loss: 2.3040 - calorie_mse: 483051.0000 - category_vector_mse: 0.0737 - val_loss: 512912.4097 - val_calorie_loss: 512907.2812 - val_category_vector_loss: 5.1077 - val_calorie_mse: 514939.2188 - val_category_vector_mse: 0.0912\n",
      "Epoch 55/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 484500.8475 - calorie_loss: 484498.5000 - category_vector_loss: 2.2766 - calorie_mse: 487782.8750 - category_vector_mse: 0.0731\n",
      "Epoch 00055: val_calorie_loss did not improve from 507314.21875\n",
      "34/34 [==============================] - 93s 3s/step - loss: 483146.1938 - calorie_loss: 483053.7812 - category_vector_loss: 2.2792 - calorie_mse: 486205.6562 - category_vector_mse: 0.0731 - val_loss: 509667.1771 - val_calorie_loss: 509664.0625 - val_category_vector_loss: 3.1190 - val_calorie_mse: 512255.7188 - val_category_vector_mse: 0.0865\n",
      "Epoch 56/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 483363.2926 - calorie_loss: 483360.9688 - category_vector_loss: 2.3055 - calorie_mse: 485616.9688 - category_vector_mse: 0.0734\n",
      "Epoch 00056: val_calorie_loss did not improve from 507314.21875\n",
      "34/34 [==============================] - 94s 3s/step - loss: 482646.3262 - calorie_loss: 482582.0000 - category_vector_loss: 2.3137 - calorie_mse: 484751.9688 - category_vector_mse: 0.0735 - val_loss: 514136.3993 - val_calorie_loss: 514132.0000 - val_category_vector_loss: 4.4235 - val_calorie_mse: 516669.0312 - val_category_vector_mse: 0.0957\n",
      "Epoch 57/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 483404.1913 - calorie_loss: 483401.8438 - category_vector_loss: 2.3410 - calorie_mse: 486028.4688 - category_vector_mse: 0.0739\n",
      "Epoch 00057: val_calorie_loss improved from 507314.21875 to 505533.50000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 94s 3s/step - loss: 483038.2205 - calorie_loss: 482963.3750 - category_vector_loss: 2.3384 - calorie_mse: 485500.7500 - category_vector_mse: 0.0738 - val_loss: 505537.7812 - val_calorie_loss: 505533.5000 - val_category_vector_loss: 4.2480 - val_calorie_mse: 508448.2500 - val_category_vector_mse: 0.1058\n",
      "Epoch 58/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 479021.7992 - calorie_loss: 479019.4688 - category_vector_loss: 2.3079 - calorie_mse: 482606.6875 - category_vector_mse: 0.0738\n",
      "Epoch 00058: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 478826.5353 - calorie_loss: 478724.9688 - category_vector_loss: 2.3084 - calorie_mse: 482197.4062 - category_vector_mse: 0.0739 - val_loss: 512540.8576 - val_calorie_loss: 512537.2188 - val_category_vector_loss: 3.6663 - val_calorie_mse: 515217.8125 - val_category_vector_mse: 0.0901\n",
      "Epoch 59/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 475588.5720 - calorie_loss: 475586.3750 - category_vector_loss: 2.2588 - calorie_mse: 478183.7812 - category_vector_mse: 0.0730\n",
      "Epoch 00059: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 475887.6498 - calorie_loss: 475813.3125 - category_vector_loss: 2.2587 - calorie_mse: 478337.8750 - category_vector_mse: 0.0730 - val_loss: 514000.4653 - val_calorie_loss: 513995.7812 - val_category_vector_loss: 4.6582 - val_calorie_mse: 517394.2500 - val_category_vector_mse: 0.0943\n",
      "Epoch 60/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 477638.9555 - calorie_loss: 477636.6250 - category_vector_loss: 2.3359 - calorie_mse: 480730.4688 - category_vector_mse: 0.0736\n",
      "Epoch 00060: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 477908.5164 - calorie_loss: 477820.3438 - category_vector_loss: 2.3319 - calorie_mse: 480825.3750 - category_vector_mse: 0.0737 - val_loss: 511692.0799 - val_calorie_loss: 511687.7812 - val_category_vector_loss: 4.2808 - val_calorie_mse: 515538.2812 - val_category_vector_mse: 0.0943\n",
      "Epoch 61/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 477191.1951 - calorie_loss: 477188.9375 - category_vector_loss: 2.2971 - calorie_mse: 479872.1875 - category_vector_mse: 0.0732\n",
      "Epoch 00061: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 479242.3359 - calorie_loss: 479164.4062 - category_vector_loss: 2.2979 - calorie_mse: 481812.8750 - category_vector_mse: 0.0732 - val_loss: 507728.7326 - val_calorie_loss: 507725.2188 - val_category_vector_loss: 3.5350 - val_calorie_mse: 510373.0000 - val_category_vector_mse: 0.0884\n",
      "Epoch 62/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 479404.3769 - calorie_loss: 479402.0312 - category_vector_loss: 2.3558 - calorie_mse: 482440.3750 - category_vector_mse: 0.0739\n",
      "Epoch 00062: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 479799.5887 - calorie_loss: 479712.8125 - category_vector_loss: 2.3587 - calorie_mse: 482666.9688 - category_vector_mse: 0.0739 - val_loss: 512877.9549 - val_calorie_loss: 512873.0625 - val_category_vector_loss: 4.8986 - val_calorie_mse: 516017.3438 - val_category_vector_mse: 0.0979\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 63/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 477803.1307 - calorie_loss: 477800.8750 - category_vector_loss: 2.2753 - calorie_mse: 479947.3438 - category_vector_mse: 0.0730\n",
      "Epoch 00063: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 477335.1828 - calorie_loss: 477273.7812 - category_vector_loss: 2.2771 - calorie_mse: 479343.3750 - category_vector_mse: 0.0730 - val_loss: 510315.5521 - val_calorie_loss: 510311.4375 - val_category_vector_loss: 4.0618 - val_calorie_mse: 514174.6562 - val_category_vector_mse: 0.0884\n",
      "Epoch 64/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 472270.7955 - calorie_loss: 472268.4375 - category_vector_loss: 2.3433 - calorie_mse: 474424.4688 - category_vector_mse: 0.0743\n",
      "Epoch 00064: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 472237.8550 - calorie_loss: 472175.7812 - category_vector_loss: 2.3435 - calorie_mse: 474264.8125 - category_vector_mse: 0.0743 - val_loss: 509212.1840 - val_calorie_loss: 509207.1562 - val_category_vector_loss: 5.0406 - val_calorie_mse: 511986.2188 - val_category_vector_mse: 0.0889\n",
      "Epoch 65/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 472589.9782 - calorie_loss: 472587.6562 - category_vector_loss: 2.2882 - calorie_mse: 474270.5000 - category_vector_mse: 0.0734\n",
      "Epoch 00065: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 472472.0251 - calorie_loss: 472423.2188 - category_vector_loss: 2.2850 - calorie_mse: 474051.5625 - category_vector_mse: 0.0734 - val_loss: 514772.7361 - val_calorie_loss: 514768.7188 - val_category_vector_loss: 3.9871 - val_calorie_mse: 518529.8750 - val_category_vector_mse: 0.0849\n",
      "Epoch 66/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 474400.4299 - calorie_loss: 474398.1875 - category_vector_loss: 2.2643 - calorie_mse: 477304.5312 - category_vector_mse: 0.0733\n",
      "Epoch 00066: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 472551.0075 - calorie_loss: 472469.5000 - category_vector_loss: 2.2700 - calorie_mse: 475243.4688 - category_vector_mse: 0.0733 - val_loss: 510107.4826 - val_calorie_loss: 510103.0625 - val_category_vector_loss: 4.4316 - val_calorie_mse: 513469.5312 - val_category_vector_mse: 0.0923\n",
      "Epoch 67/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 476628.8428 - calorie_loss: 476626.4375 - category_vector_loss: 2.3355 - calorie_mse: 478778.1875 - category_vector_mse: 0.0740\n",
      "Epoch 00067: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 474653.4687 - calorie_loss: 474592.7812 - category_vector_loss: 2.3313 - calorie_mse: 476632.4688 - category_vector_mse: 0.0739 - val_loss: 508530.0312 - val_calorie_loss: 508525.3438 - val_category_vector_loss: 4.6997 - val_calorie_mse: 511604.0625 - val_category_vector_mse: 0.0953\n",
      "Epoch 68/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 471719.8523 - calorie_loss: 471717.5000 - category_vector_loss: 2.3311 - calorie_mse: 475013.1250 - category_vector_mse: 0.0739\n",
      "Epoch 00068: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 470246.1148 - calorie_loss: 470153.4688 - category_vector_loss: 2.3445 - calorie_mse: 473313.4688 - category_vector_mse: 0.0741 - val_loss: 512996.2535 - val_calorie_loss: 512991.6562 - val_category_vector_loss: 4.5531 - val_calorie_mse: 515889.8438 - val_category_vector_mse: 0.0913\n",
      "Epoch 69/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 472608.4612 - calorie_loss: 472606.0938 - category_vector_loss: 2.3174 - calorie_mse: 475052.1250 - category_vector_mse: 0.0737\n",
      "Epoch 00069: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 472707.5598 - calorie_loss: 472637.3750 - category_vector_loss: 2.3199 - calorie_mse: 475010.5312 - category_vector_mse: 0.0737 - val_loss: 513151.1736 - val_calorie_loss: 513147.0000 - val_category_vector_loss: 4.1862 - val_calorie_mse: 516789.8750 - val_category_vector_mse: 0.0858\n",
      "Epoch 70/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469103.2263 - calorie_loss: 469101.0000 - category_vector_loss: 2.2865 - calorie_mse: 471284.1250 - category_vector_mse: 0.0730\n",
      "Epoch 00070: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 468577.1582 - calorie_loss: 468514.8125 - category_vector_loss: 2.2812 - calorie_mse: 470618.5938 - category_vector_mse: 0.0729 - val_loss: 507060.5278 - val_calorie_loss: 507056.1562 - val_category_vector_loss: 4.3830 - val_calorie_mse: 509765.7188 - val_category_vector_mse: 0.0883\n",
      "Epoch 71/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 464831.7083 - calorie_loss: 464829.4375 - category_vector_loss: 2.2894 - calorie_mse: 467337.1250 - category_vector_mse: 0.0736\n",
      "Epoch 00071: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 95s 3s/step - loss: 466189.8238 - calorie_loss: 466117.2188 - category_vector_loss: 2.2833 - calorie_mse: 468579.4062 - category_vector_mse: 0.0735 - val_loss: 505901.0833 - val_calorie_loss: 505897.2812 - val_category_vector_loss: 3.8042 - val_calorie_mse: 509072.4375 - val_category_vector_mse: 0.0854\n",
      "Epoch 72/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 473563.9394 - calorie_loss: 473561.5938 - category_vector_loss: 2.3048 - calorie_mse: 473561.5938 - category_vector_mse: 0.0738\n",
      "Epoch 00072: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 95s 3s/step - loss: 470759.2094 - calorie_loss: 470693.9375 - category_vector_loss: 2.3053 - calorie_mse: 472896.7812 - category_vector_mse: 0.0738 - val_loss: 506639.7465 - val_calorie_loss: 506635.2188 - val_category_vector_loss: 4.5840 - val_calorie_mse: 510645.8438 - val_category_vector_mse: 0.0986\n",
      "Epoch 73/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469468.2869 - calorie_loss: 469466.0000 - category_vector_loss: 2.2863 - calorie_mse: 472538.8125 - category_vector_mse: 0.0728\n",
      "Epoch 00073: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 96s 3s/step - loss: 469049.2110 - calorie_loss: 468962.1250 - category_vector_loss: 2.2801 - calorie_mse: 471930.7188 - category_vector_mse: 0.0727 - val_loss: 515157.2326 - val_calorie_loss: 515152.8750 - val_category_vector_loss: 4.3776 - val_calorie_mse: 517952.5938 - val_category_vector_mse: 0.0854\n",
      "Epoch 74/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 473423.5066 - calorie_loss: 473421.1562 - category_vector_loss: 2.2957 - calorie_mse: 475820.8125 - category_vector_mse: 0.0739\n",
      "Epoch 00074: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 475125.0391 - calorie_loss: 475055.1250 - category_vector_loss: 2.2947 - calorie_mse: 477420.5625 - category_vector_mse: 0.0739 - val_loss: 511351.4965 - val_calorie_loss: 511348.0625 - val_category_vector_loss: 3.4149 - val_calorie_mse: 514668.8438 - val_category_vector_mse: 0.0931\n",
      "Epoch 75/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 471176.1496 - calorie_loss: 471173.8438 - category_vector_loss: 2.2998 - calorie_mse: 471173.8438 - category_vector_mse: 0.0738\n",
      "Epoch 00075: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 95s 3s/step - loss: 472846.7335 - calorie_loss: 472844.4375 - category_vector_loss: 2.3030 - calorie_mse: 472844.4375 - category_vector_mse: 0.0739 - val_loss: 512355.1111 - val_calorie_loss: 512350.5625 - val_category_vector_loss: 4.5080 - val_calorie_mse: 515041.5625 - val_category_vector_mse: 0.0931\n",
      "Epoch 76/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 473128.0455 - calorie_loss: 473125.7812 - category_vector_loss: 2.2856 - calorie_mse: 475964.4375 - category_vector_mse: 0.0732\n",
      "Epoch 00076: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 472419.9441 - calorie_loss: 472339.5625 - category_vector_loss: 2.2851 - calorie_mse: 475074.4688 - category_vector_mse: 0.0731 - val_loss: 506362.3403 - val_calorie_loss: 506357.0625 - val_category_vector_loss: 5.2895 - val_calorie_mse: 508612.3125 - val_category_vector_mse: 0.0868\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 77/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 469585.5426 - calorie_loss: 469583.2500 - category_vector_loss: 2.2740 - calorie_mse: 471811.7500 - category_vector_mse: 0.0727\n",
      "Epoch 00077: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 467453.8063 - calorie_loss: 467391.2188 - category_vector_loss: 2.2725 - calorie_mse: 469501.6250 - category_vector_mse: 0.0727 - val_loss: 510189.2951 - val_calorie_loss: 510184.8750 - val_category_vector_loss: 4.3901 - val_calorie_mse: 512794.5312 - val_category_vector_mse: 0.1040\n",
      "Epoch 78/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 463931.5455 - calorie_loss: 463929.2500 - category_vector_loss: 2.2670 - calorie_mse: 465772.3438 - category_vector_mse: 0.0735\n",
      "Epoch 00078: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 464998.2023 - calorie_loss: 464944.1562 - category_vector_loss: 2.2744 - calorie_mse: 466755.4062 - category_vector_mse: 0.0737 - val_loss: 506555.6944 - val_calorie_loss: 506551.0625 - val_category_vector_loss: 4.6468 - val_calorie_mse: 509710.4375 - val_category_vector_mse: 0.0802\n",
      "Epoch 79/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 467326.2320 - calorie_loss: 467323.9375 - category_vector_loss: 2.2718 - calorie_mse: 469161.1562 - category_vector_mse: 0.0731\n",
      "Epoch 00079: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 470530.8263 - calorie_loss: 470475.5312 - category_vector_loss: 2.2725 - calorie_mse: 472330.8125 - category_vector_mse: 0.0731 - val_loss: 524185.8576 - val_calorie_loss: 524182.2812 - val_category_vector_loss: 3.5564 - val_calorie_mse: 527161.0625 - val_category_vector_mse: 0.0862\n",
      "Epoch 80/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 472921.5663 - calorie_loss: 472919.2812 - category_vector_loss: 2.2703 - calorie_mse: 475734.2500 - category_vector_mse: 0.0730\n",
      "Epoch 00080: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 472483.1789 - calorie_loss: 472403.2500 - category_vector_loss: 2.2677 - calorie_mse: 475121.5000 - category_vector_mse: 0.0730 - val_loss: 512431.6250 - val_calorie_loss: 512427.6562 - val_category_vector_loss: 4.0080 - val_calorie_mse: 515495.5625 - val_category_vector_mse: 0.0866\n",
      "Epoch 81/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 465385.6089 - calorie_loss: 465383.3750 - category_vector_loss: 2.2515 - calorie_mse: 468366.7188 - category_vector_mse: 0.0726\n",
      "Epoch 00081: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 463070.0881 - calorie_loss: 462986.7500 - category_vector_loss: 2.2527 - calorie_mse: 465824.5312 - category_vector_mse: 0.0726 - val_loss: 515593.3576 - val_calorie_loss: 515589.0625 - val_category_vector_loss: 4.3429 - val_calorie_mse: 518755.7812 - val_category_vector_mse: 0.0929\n",
      "Epoch 82/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 466913.0672 - calorie_loss: 466910.7188 - category_vector_loss: 2.2775 - calorie_mse: 469906.9688 - category_vector_mse: 0.0731\n",
      "Epoch 00082: val_calorie_loss did not improve from 505533.50000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 465235.8970 - calorie_loss: 465151.7188 - category_vector_loss: 2.2767 - calorie_mse: 468016.8125 - category_vector_mse: 0.0731 - val_loss: 513870.9062 - val_calorie_loss: 513866.6562 - val_category_vector_loss: 4.1967 - val_calorie_mse: 517128.0625 - val_category_vector_mse: 0.0935\n",
      "Epoch 83/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 462837.1354 - calorie_loss: 462834.9062 - category_vector_loss: 2.2507 - calorie_mse: 465749.6562 - category_vector_mse: 0.0728\n",
      "Epoch 00083: val_calorie_loss improved from 505533.50000 to 502429.00000, saving model to ./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5\n",
      "34/34 [==============================] - 93s 3s/step - loss: 460450.4014 - calorie_loss: 460369.0625 - category_vector_loss: 2.2488 - calorie_mse: 463138.6562 - category_vector_mse: 0.0728 - val_loss: 502434.3507 - val_calorie_loss: 502429.0000 - val_category_vector_loss: 5.2945 - val_calorie_mse: 506396.5312 - val_category_vector_mse: 0.0956\n",
      "Epoch 84/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 467080.5057 - calorie_loss: 467078.3438 - category_vector_loss: 2.2564 - calorie_mse: 470586.2188 - category_vector_mse: 0.0729\n",
      "Epoch 00084: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 468211.3261 - calorie_loss: 468111.2500 - category_vector_loss: 2.2563 - calorie_mse: 471537.6250 - category_vector_mse: 0.0729 - val_loss: 510339.9965 - val_calorie_loss: 510335.1250 - val_category_vector_loss: 4.9210 - val_calorie_mse: 513160.1250 - val_category_vector_mse: 0.0894\n",
      "Epoch 85/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 468663.7955 - calorie_loss: 468661.5000 - category_vector_loss: 2.2780 - calorie_mse: 472155.9688 - category_vector_mse: 0.0729\n",
      "Epoch 00085: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 466428.8513 - calorie_loss: 466331.2500 - category_vector_loss: 2.2827 - calorie_mse: 469666.3438 - category_vector_mse: 0.0729 - val_loss: 504396.6910 - val_calorie_loss: 504393.7812 - val_category_vector_loss: 2.9660 - val_calorie_mse: 506756.4375 - val_category_vector_mse: 0.0798\n",
      "Epoch 86/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 463575.7973 - calorie_loss: 463573.5000 - category_vector_loss: 2.2922 - calorie_mse: 466123.3438 - category_vector_mse: 0.0734\n",
      "Epoch 00086: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 463559.4876 - calorie_loss: 463486.5625 - category_vector_loss: 2.2926 - calorie_mse: 465957.6562 - category_vector_mse: 0.0734 - val_loss: 520386.9549 - val_calorie_loss: 520383.4375 - val_category_vector_loss: 3.5335 - val_calorie_mse: 522906.2500 - val_category_vector_mse: 0.0837\n",
      "Epoch 87/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 462164.6572 - calorie_loss: 462162.4375 - category_vector_loss: 2.2946 - calorie_mse: 465447.9062 - category_vector_mse: 0.0731\n",
      "Epoch 00087: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 96s 3s/step - loss: 464331.2751 - calorie_loss: 464236.6250 - category_vector_loss: 2.2947 - calorie_mse: 467471.5000 - category_vector_mse: 0.0732 - val_loss: 515597.8750 - val_calorie_loss: 515594.3438 - val_category_vector_loss: 3.5839 - val_calorie_mse: 518290.0625 - val_category_vector_mse: 0.0843\n",
      "Epoch 88/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 466931.9205 - calorie_loss: 466929.6875 - category_vector_loss: 2.2227 - calorie_mse: 470026.8438 - category_vector_mse: 0.0723\n",
      "Epoch 00088: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 466232.4747 - calorie_loss: 466144.9375 - category_vector_loss: 2.2237 - calorie_mse: 469130.5938 - category_vector_mse: 0.0723 - val_loss: 510213.8090 - val_calorie_loss: 510210.2188 - val_category_vector_loss: 3.6183 - val_calorie_mse: 514182.9688 - val_category_vector_mse: 0.0831\n",
      "Epoch 89/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 466517.1146 - calorie_loss: 466514.8125 - category_vector_loss: 2.3042 - calorie_mse: 468638.5938 - category_vector_mse: 0.0739\n",
      "Epoch 00089: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 467389.2404 - calorie_loss: 467327.5625 - category_vector_loss: 2.3019 - calorie_mse: 469406.3438 - category_vector_mse: 0.0739 - val_loss: 515321.4479 - val_calorie_loss: 515317.9375 - val_category_vector_loss: 3.5319 - val_calorie_mse: 518054.8750 - val_category_vector_mse: 0.0826\n",
      "Epoch 90/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 465031.1648 - calorie_loss: 465028.8438 - category_vector_loss: 2.3141 - calorie_mse: 466909.4062 - category_vector_mse: 0.0735\n",
      "Epoch 00090: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 466428.7048 - calorie_loss: 466373.3750 - category_vector_loss: 2.3142 - calorie_mse: 468228.6250 - category_vector_mse: 0.0734 - val_loss: 508967.2778 - val_calorie_loss: 508962.7188 - val_category_vector_loss: 4.6073 - val_calorie_mse: 511457.5938 - val_category_vector_mse: 0.0980\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 91/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 457220.1004 - calorie_loss: 457217.7812 - category_vector_loss: 2.3007 - calorie_mse: 460222.3750 - category_vector_mse: 0.0732\n",
      "Epoch 00091: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 460477.4940 - calorie_loss: 460389.7812 - category_vector_loss: 2.3055 - calorie_mse: 463377.7812 - category_vector_mse: 0.0733 - val_loss: 506016.5312 - val_calorie_loss: 506012.8438 - val_category_vector_loss: 3.7168 - val_calorie_mse: 508280.1562 - val_category_vector_mse: 0.0902\n",
      "Epoch 92/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 462510.0852 - calorie_loss: 462507.7500 - category_vector_loss: 2.2752 - calorie_mse: 464979.9688 - category_vector_mse: 0.0732\n",
      "Epoch 00092: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 462999.9432 - calorie_loss: 462928.8125 - category_vector_loss: 2.2735 - calorie_mse: 465336.4375 - category_vector_mse: 0.0732 - val_loss: 514670.9167 - val_calorie_loss: 514667.1250 - val_category_vector_loss: 3.8002 - val_calorie_mse: 518307.1875 - val_category_vector_mse: 0.0962\n",
      "Epoch 93/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 466594.5881 - calorie_loss: 466592.3125 - category_vector_loss: 2.2735 - calorie_mse: 469762.1250 - category_vector_mse: 0.0728\n",
      "Epoch 00093: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 464742.9585 - calorie_loss: 464654.1250 - category_vector_loss: 2.2733 - calorie_mse: 467683.4062 - category_vector_mse: 0.0728 - val_loss: 506751.2500 - val_calorie_loss: 506748.0000 - val_category_vector_loss: 3.2291 - val_calorie_mse: 509106.6250 - val_category_vector_mse: 0.0865\n",
      "Epoch 94/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 471017.8655 - calorie_loss: 471015.6250 - category_vector_loss: 2.2587 - calorie_mse: 474306.5312 - category_vector_mse: 0.0731\n",
      "Epoch 00094: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 469077.6684 - calorie_loss: 468985.5938 - category_vector_loss: 2.2579 - calorie_mse: 472130.1875 - category_vector_mse: 0.0730 - val_loss: 511111.4757 - val_calorie_loss: 511108.1562 - val_category_vector_loss: 3.3177 - val_calorie_mse: 513584.6875 - val_category_vector_mse: 0.0957\n",
      "Epoch 95/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 463079.5663 - calorie_loss: 463077.2812 - category_vector_loss: 2.2437 - calorie_mse: 466356.6562 - category_vector_mse: 0.0729\n",
      "Epoch 00095: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 94s 3s/step - loss: 460875.3596 - calorie_loss: 460783.7188 - category_vector_loss: 2.2444 - calorie_mse: 463911.0000 - category_vector_mse: 0.0728 - val_loss: 509423.4826 - val_calorie_loss: 509419.7812 - val_category_vector_loss: 3.7100 - val_calorie_mse: 512345.7188 - val_category_vector_mse: 0.0894\n",
      "Epoch 96/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 460020.1686 - calorie_loss: 460017.8125 - category_vector_loss: 2.2886 - calorie_mse: 462798.4062 - category_vector_mse: 0.0740\n",
      "Epoch 00096: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 462430.7707 - calorie_loss: 462349.8125 - category_vector_loss: 2.2895 - calorie_mse: 465101.0312 - category_vector_mse: 0.0740 - val_loss: 515079.8333 - val_calorie_loss: 515076.6250 - val_category_vector_loss: 3.2122 - val_calorie_mse: 517234.9062 - val_category_vector_mse: 0.0811\n",
      "Epoch 97/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 463906.9915 - calorie_loss: 463904.6875 - category_vector_loss: 2.2861 - calorie_mse: 466772.3125 - category_vector_mse: 0.0735\n",
      "Epoch 00097: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 461199.5122 - calorie_loss: 461119.6250 - category_vector_loss: 2.2840 - calorie_mse: 463836.0938 - category_vector_mse: 0.0735 - val_loss: 508662.4028 - val_calorie_loss: 508658.6250 - val_category_vector_loss: 3.8158 - val_calorie_mse: 511692.9688 - val_category_vector_mse: 0.0976\n",
      "Epoch 98/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 459889.8987 - calorie_loss: 459887.6250 - category_vector_loss: 2.2731 - calorie_mse: 462484.3750 - category_vector_mse: 0.0728\n",
      "Epoch 00098: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 462133.1663 - calorie_loss: 462057.5000 - category_vector_loss: 2.2775 - calorie_mse: 464626.5938 - category_vector_mse: 0.0729 - val_loss: 507941.1181 - val_calorie_loss: 507937.5625 - val_category_vector_loss: 3.5671 - val_calorie_mse: 510885.7500 - val_category_vector_mse: 0.0830\n",
      "Epoch 99/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 455732.2926 - calorie_loss: 455730.0312 - category_vector_loss: 2.2690 - calorie_mse: 459222.4375 - category_vector_mse: 0.0731\n",
      "Epoch 00099: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 93s 3s/step - loss: 454950.1219 - calorie_loss: 454851.6875 - category_vector_loss: 2.2665 - calorie_mse: 458218.5312 - category_vector_mse: 0.0731 - val_loss: 514513.3090 - val_calorie_loss: 514509.2188 - val_category_vector_loss: 4.0708 - val_calorie_mse: 517080.1250 - val_category_vector_mse: 0.0818\n",
      "Epoch 100/100\n",
      "33/34 [============================>.] - ETA: 2s - loss: 463563.3191 - calorie_loss: 463561.0938 - category_vector_loss: 2.2465 - calorie_mse: 463561.0938 - category_vector_mse: 0.0728\n",
      "Epoch 00100: val_calorie_loss did not improve from 502429.00000\n",
      "34/34 [==============================] - 96s 3s/step - loss: 465332.7941 - calorie_loss: 465330.5625 - category_vector_loss: 2.2512 - calorie_mse: 465330.5625 - category_vector_mse: 0.0729 - val_loss: 506576.2396 - val_calorie_loss: 506571.2812 - val_category_vector_loss: 4.9221 - val_calorie_mse: 509273.4375 - val_category_vector_mse: 0.0944\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.optimizers import Adam\n",
    "from tensorflow.keras.callbacks import ModelCheckpoint\n",
    "from tensorflow.keras import metrics\n",
    "\n",
    "model.compile(optimizer=Adam(lr=1e-3), loss={'calorie':'mse', 'category_vector':'categorical_crossentropy'}\n",
    "              , metrics=['mse'])\n",
    "\n",
    "\n",
    "checkpointer = ModelCheckpoint(filepath='./multi-output/category/recipe_256_128_1e_3_categorical_vector.h5', verbose=1, \n",
    "                               monitor='val_calorie_loss', mode='auto', save_best_only=True)\n",
    "\n",
    "history = model.fit_generator(generator=train_generator, \n",
    "                    steps_per_epoch=round(train_generator.n/train_generator.batch_size),\n",
    "                    epochs=100,\n",
    "                    validation_data=valid_generator,\n",
    "                    validation_steps=round(valid_generator.n/valid_generator.batch_size),  \n",
    "                    callbacks=[checkpointer]\n",
    "                   )\n",
    "\n",
    "\n",
    "with open('./multi-output/category/recipe_256_128_1e_3_categorical_vector.pkl','wb') as f:\n",
    "    pickle.dump(history.history, f)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1. output: calorie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found 4381 validated image filenames.\n",
      "Found 1095 validated image filenames.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/uceezku/project/lib64/python3.6/site-packages/keras_preprocessing/image/dataframe_iterator.py:282: UserWarning: Found 6 invalid image filename(s) in x_col=\"file_name\". These filename(s) will be ignored.\n",
      "  .format(n_invalid, x_col)\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
    "\n",
    "datagen=ImageDataGenerator(\n",
    "    #rescale=1/255, \n",
    "    validation_split=0.2, \n",
    "    rotation_range=20,\n",
    "    width_shift_range=0.2,\n",
    "    height_shift_range=0.2,\n",
    "    horizontal_flip=True,\n",
    "    )\n",
    "\n",
    "train_generator = datagen.flow_from_dataframe(\n",
    "    dataframe=train_data,\n",
    "    directory='./data/train/',\n",
    "    target_size = (256,256),\n",
    "    x_col='file_name',\n",
    "    y_col='calorie_per_recipe',\n",
    "    batch_size=128,\n",
    "    shuffle=True,\n",
    "    subset='training',\n",
    "    class_mode='raw')\n",
    "\n",
    "valid_generator = datagen.flow_from_dataframe(\n",
    "    dataframe=train_data,\n",
    "    directory='./data/train/',\n",
    "    target_size = (256,256),\n",
    "    x_col='file_name',\n",
    "    y_col='calorie_per_recipe', \n",
    "    batch_size=128,\n",
    "    shuffle=True,\n",
    "    subset='validation',\n",
    "    class_mode='raw')\n",
    "    #validate_filenames=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From <ipython-input-4-eb95347980fb>:17: Model.fit_generator (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Please use Model.fit, which supports generators.\n",
      "WARNING:tensorflow:sample_weight modes were coerced from\n",
      "  ...\n",
      "    to  \n",
      "  ['...']\n",
      "WARNING:tensorflow:sample_weight modes were coerced from\n",
      "  ...\n",
      "    to  \n",
      "  ['...']\n",
      "Train for 34 steps, validate for 9 steps\n",
      "Epoch 1/50\n",
      " 1/34 [..............................] - ETA: 3:49 - loss: 3258967.0000 - mse: 3258967.0000"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/uceezku/project/lib64/python3.6/site-packages/PIL/Image.py:963: UserWarning: Palette images with Transparency expressed in bytes should be converted to RGBA images\n",
      "  \"Palette images with Transparency expressed in bytes should be \"\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "33/34 [============================>.] - ETA: 5s - loss: 2366922.5644 - mse: 2345513.7500 \n",
      "Epoch 00001: val_loss improved from inf to 2721431.63889, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 212s 6s/step - loss: 2363292.9282 - mse: 2343053.0000 - val_loss: 2721431.6389 - val_mse: 2709933.5000\n",
      "Epoch 2/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 1882804.1515 - mse: 1867199.6250\n",
      "Epoch 00002: val_loss improved from 2721431.63889 to 2127970.29167, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 203s 6s/step - loss: 1865049.1330 - mse: 1849955.2500 - val_loss: 2127970.2917 - val_mse: 2118688.0000\n",
      "Epoch 3/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 1252759.9337 - mse: 1248806.1250\n",
      "Epoch 00003: val_loss improved from 2127970.29167 to 1467133.86111, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 204s 6s/step - loss: 1246431.9661 - mse: 1242566.2500 - val_loss: 1467133.8611 - val_mse: 1461273.6250\n",
      "Epoch 4/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 787568.3239 - mse: 776919.8125\n",
      "Epoch 00004: val_loss improved from 1467133.86111 to 991303.95833, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 205s 6s/step - loss: 783221.2908 - mse: 773096.7500 - val_loss: 991303.9583 - val_mse: 987761.1250\n",
      "Epoch 5/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 591619.0019 - mse: 588262.8750\n",
      "Epoch 00005: val_loss improved from 991303.95833 to 788832.95833, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 205s 6s/step - loss: 588938.2287 - mse: 585717.6250 - val_loss: 788832.9583 - val_mse: 786597.0000\n",
      "Epoch 6/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 558698.8636 - mse: 557486.4375\n",
      "Epoch 00006: val_loss improved from 788832.95833 to 742536.54861, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 204s 6s/step - loss: 558286.4172 - mse: 557135.5000 - val_loss: 742536.5486 - val_mse: 741561.5000\n",
      "Epoch 7/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 552737.4972 - mse: 552008.7500\n",
      "Epoch 00007: val_loss improved from 742536.54861 to 727426.78472, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 203s 6s/step - loss: 549912.2613 - mse: 549162.2500 - val_loss: 727426.7847 - val_mse: 725775.5625\n",
      "Epoch 8/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 548570.7008 - mse: 545443.8125\n",
      "Epoch 00008: val_loss did not improve from 727426.78472\n",
      "34/34 [==============================] - 205s 6s/step - loss: 547397.6505 - mse: 544427.0000 - val_loss: 729579.1736 - val_mse: 727653.6875\n",
      "Epoch 9/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 549098.3911 - mse: 549098.4375 \n",
      "Epoch 00009: val_loss improved from 727426.78472 to 724785.55556, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 204s 6s/step - loss: 550734.4962 - mse: 549486.2500 - val_loss: 724785.5556 - val_mse: 723460.9375\n",
      "Epoch 10/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 544886.3201 - mse: 543822.1875\n",
      "Epoch 00010: val_loss improved from 724785.55556 to 718466.87500, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 205s 6s/step - loss: 543410.5359 - mse: 542375.1875 - val_loss: 718466.8750 - val_mse: 716317.6875\n",
      "Epoch 11/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 543152.1884 - mse: 543152.1875 \n",
      "Epoch 00011: val_loss did not improve from 718466.87500\n",
      "34/34 [==============================] - 205s 6s/step - loss: 545531.2975 - mse: 543716.1250 - val_loss: 718709.0278 - val_mse: 716547.2500\n",
      "Epoch 12/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 547423.0483 - mse: 546463.0000 \n",
      "Epoch 00012: val_loss improved from 718466.87500 to 708653.55556, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 207s 6s/step - loss: 546157.5023 - mse: 545225.0000 - val_loss: 708653.5556 - val_mse: 706747.7500\n",
      "Epoch 13/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 547888.0464 - mse: 545299.2500\n",
      "Epoch 00013: val_loss did not improve from 708653.55556\n",
      "34/34 [==============================] - 203s 6s/step - loss: 549342.9600 - mse: 546938.3125 - val_loss: 712310.4306 - val_mse: 710592.6250\n",
      "Epoch 14/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 544832.9195 - mse: 543113.2500 \n",
      "Epoch 00014: val_loss improved from 708653.55556 to 704227.17361, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 205s 6s/step - loss: 547935.7847 - mse: 546386.7500 - val_loss: 704227.1736 - val_mse: 702328.8750\n",
      "Epoch 15/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 546542.5369 - mse: 545024.0625\n",
      "Epoch 00015: val_loss improved from 704227.17361 to 699410.99306, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 204s 6s/step - loss: 547442.8625 - mse: 546033.5000 - val_loss: 699410.9931 - val_mse: 698549.1250\n",
      "Epoch 16/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 544896.7680 - mse: 541638.3125\n",
      "Epoch 00016: val_loss improved from 699410.99306 to 691271.09722, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 205s 6s/step - loss: 546927.9433 - mse: 543905.7500 - val_loss: 691271.0972 - val_mse: 689544.5625\n",
      "Epoch 17/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 538637.2386 - mse: 537077.6875\n",
      "Epoch 00017: val_loss did not improve from 691271.09722\n",
      "34/34 [==============================] - 204s 6s/step - loss: 539921.2987 - mse: 538481.8750 - val_loss: 695305.6597 - val_mse: 693206.5000\n",
      "Epoch 18/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 540868.5483 - mse: 538162.7500\n",
      "Epoch 00018: val_loss improved from 691271.09722 to 689556.43056, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 205s 6s/step - loss: 540858.6583 - mse: 538310.7500 - val_loss: 689556.4306 - val_mse: 688340.8750\n",
      "Epoch 19/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 541291.2500 - mse: 539749.9375\n",
      "Epoch 00019: val_loss improved from 689556.43056 to 683597.62500, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 205s 6s/step - loss: 538633.4276 - mse: 537122.1250 - val_loss: 683597.6250 - val_mse: 683488.8750\n",
      "Epoch 20/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 539890.9991 - mse: 538527.9375\n",
      "Epoch 00020: val_loss improved from 683597.62500 to 682566.13889, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 206s 6s/step - loss: 537592.3843 - mse: 536257.0625 - val_loss: 682566.1389 - val_mse: 679823.9375\n",
      "Epoch 21/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 539055.1752 - mse: 537007.3125\n",
      "Epoch 00021: val_loss improved from 682566.13889 to 675516.45139, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 203s 6s/step - loss: 536665.5816 - mse: 534683.4375 - val_loss: 675516.4514 - val_mse: 674066.2500\n",
      "Epoch 22/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 540760.0795 - mse: 538191.3125\n",
      "Epoch 00022: val_loss improved from 675516.45139 to 672878.82639, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 205s 6s/step - loss: 542938.6517 - mse: 540569.1875 - val_loss: 672878.8264 - val_mse: 670275.9375\n",
      "Epoch 23/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 531787.9375 - mse: 529866.5000\n",
      "Epoch 00023: val_loss improved from 672878.82639 to 661338.31250, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 205s 6s/step - loss: 531415.2055 - mse: 529597.6250 - val_loss: 661338.3125 - val_mse: 659959.8750\n",
      "Epoch 24/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 530691.5530 - mse: 528727.8750 \n",
      "Epoch 00024: val_loss did not improve from 661338.31250\n",
      "34/34 [==============================] - 205s 6s/step - loss: 532696.6904 - mse: 530893.0625 - val_loss: 663228.7604 - val_mse: 661645.7500\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 25/50\n",
      "33/34 [============================>.] - ETA: 4s - loss: 532254.7727 - mse: 529508.4375\n",
      "Epoch 00025: val_loss improved from 661338.31250 to 656689.13194, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 205s 6s/step - loss: 533683.4187 - mse: 531129.8125 - val_loss: 656689.1319 - val_mse: 655548.0625\n",
      "Epoch 26/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 532668.1212 - mse: 531168.0000 \n",
      "Epoch 00026: val_loss improved from 656689.13194 to 644554.62153, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 205s 6s/step - loss: 530561.3760 - mse: 529101.2500 - val_loss: 644554.6215 - val_mse: 642673.0625\n",
      "Epoch 27/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 529327.3447 - mse: 526392.8125 \n",
      "Epoch 00027: val_loss improved from 644554.62153 to 642749.46181, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 206s 6s/step - loss: 529571.1451 - mse: 526813.5625 - val_loss: 642749.4618 - val_mse: 642165.5000\n",
      "Epoch 28/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 531254.6884 - mse: 529534.0625 \n",
      "Epoch 00028: val_loss improved from 642749.46181 to 640391.71181, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 228s 7s/step - loss: 529271.1821 - mse: 527606.2500 - val_loss: 640391.7118 - val_mse: 639784.0625\n",
      "Epoch 29/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 529546.0152 - mse: 528689.5625 \n",
      "Epoch 00029: val_loss improved from 640391.71181 to 635560.20139, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 243s 7s/step - loss: 525391.9022 - mse: 524491.6250 - val_loss: 635560.2014 - val_mse: 634737.1250\n",
      "Epoch 30/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 526622.2358 - mse: 523677.9375 \n",
      "Epoch 00030: val_loss improved from 635560.20139 to 630881.79861, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 239s 7s/step - loss: 525147.1544 - mse: 522341.5938 - val_loss: 630881.7986 - val_mse: 629257.8750\n",
      "Epoch 31/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 524132.6562 - mse: 522609.1250 \n",
      "Epoch 00031: val_loss improved from 630881.79861 to 624474.58333, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 243s 7s/step - loss: 523431.4379 - mse: 521981.1250 - val_loss: 624474.5833 - val_mse: 623372.9375\n",
      "Epoch 32/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 528561.7945 - mse: 527091.1875 \n",
      "Epoch 00032: val_loss improved from 624474.58333 to 612639.17014, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 244s 7s/step - loss: 529715.5541 - mse: 528357.0000 - val_loss: 612639.1701 - val_mse: 611600.9375\n",
      "Epoch 33/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 523293.1970 - mse: 521941.2500 \n",
      "Epoch 00033: val_loss did not improve from 612639.17014\n",
      "34/34 [==============================] - 242s 7s/step - loss: 524619.6232 - mse: 523376.6250 - val_loss: 617575.4931 - val_mse: 617705.5000\n",
      "Epoch 34/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 516154.8068 - mse: 515684.1875 \n",
      "Epoch 00034: val_loss improved from 612639.17014 to 610972.17361, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 240s 7s/step - loss: 517006.0099 - mse: 516582.1250 - val_loss: 610972.1736 - val_mse: 610796.2500\n",
      "Epoch 35/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 512653.1155 - mse: 511217.4688 \n",
      "Epoch 00035: val_loss improved from 610972.17361 to 607567.94097, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 240s 7s/step - loss: 512495.4923 - mse: 511140.2188 - val_loss: 607567.9410 - val_mse: 607373.0000\n",
      "Epoch 36/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 517031.2169 - mse: 516710.2188 \n",
      "Epoch 00036: val_loss improved from 607567.94097 to 599788.04167, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 241s 7s/step - loss: 517895.6751 - mse: 517612.9688 - val_loss: 599788.0417 - val_mse: 599638.6250\n",
      "Epoch 37/50\n",
      "33/34 [============================>.] - ETA: 6s - loss: 512549.3438 - mse: 512549.4062 \n",
      "Epoch 00037: val_loss did not improve from 599788.04167\n",
      "34/34 [==============================] - 242s 7s/step - loss: 512460.6790 - mse: 512528.3750 - val_loss: 603051.8542 - val_mse: 602578.5000\n",
      "Epoch 38/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 506709.0833 - mse: 506709.0312 \n",
      "Epoch 00038: val_loss improved from 599788.04167 to 598533.52778, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 241s 7s/step - loss: 508298.6931 - mse: 507085.8750 - val_loss: 598533.5278 - val_mse: 598496.1250\n",
      "Epoch 39/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 516236.6667 - mse: 516083.4375 \n",
      "Epoch 00039: val_loss improved from 598533.52778 to 590749.56250, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 243s 7s/step - loss: 512274.6656 - mse: 512040.8750 - val_loss: 590749.5625 - val_mse: 590684.1250\n",
      "Epoch 40/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 512577.8873 - mse: 511382.0625 \n",
      "Epoch 00040: val_loss improved from 590749.56250 to 585087.34375, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 241s 7s/step - loss: 515002.3271 - mse: 513931.1562 - val_loss: 585087.3438 - val_mse: 584286.6875\n",
      "Epoch 41/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 514080.2680 - mse: 512819.3125 \n",
      "Epoch 00041: val_loss improved from 585087.34375 to 581399.22222, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 246s 7s/step - loss: 515973.3072 - mse: 514828.8125 - val_loss: 581399.2222 - val_mse: 582050.4375\n",
      "Epoch 42/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 506824.0275 - mse: 505956.0312 \n",
      "Epoch 00042: val_loss improved from 581399.22222 to 580218.11806, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 247s 7s/step - loss: 505363.9673 - mse: 504513.6875 - val_loss: 580218.1181 - val_mse: 580505.6250\n",
      "Epoch 43/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 509711.4214 - mse: 509992.6250 \n",
      "Epoch 00043: val_loss improved from 580218.11806 to 577074.95833, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 247s 7s/step - loss: 511694.7768 - mse: 512004.3438 - val_loss: 577074.9583 - val_mse: 577449.6250\n",
      "Epoch 44/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 508037.5208 - mse: 506815.8750 \n",
      "Epoch 00044: val_loss improved from 577074.95833 to 567948.70139, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 246s 7s/step - loss: 507957.2810 - mse: 506805.1875 - val_loss: 567948.7014 - val_mse: 567603.1875\n",
      "Epoch 45/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 510183.5303 - mse: 509144.3438 \n",
      "Epoch 00045: val_loss improved from 567948.70139 to 559740.86806, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 245s 7s/step - loss: 510780.9922 - mse: 509816.0312 - val_loss: 559740.8681 - val_mse: 560750.9375\n",
      "Epoch 46/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 503197.2585 - mse: 502204.5312 \n",
      "Epoch 00046: val_loss improved from 559740.86806 to 557780.06250, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 246s 7s/step - loss: 501542.1086 - mse: 500570.0000 - val_loss: 557780.0625 - val_mse: 558038.5625\n",
      "Epoch 47/50\n",
      "33/34 [============================>.] - ETA: 6s - loss: 508840.4820 - mse: 507559.2812 \n",
      "Epoch 00047: val_loss improved from 557780.06250 to 555471.30556, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 247s 7s/step - loss: 505982.6566 - mse: 504711.7500 - val_loss: 555471.3056 - val_mse: 555880.1875\n",
      "Epoch 48/50\n",
      "33/34 [============================>.] - ETA: 6s - loss: 502838.6922 - mse: 503445.1875 \n",
      "Epoch 00048: val_loss did not improve from 555471.30556\n",
      "34/34 [==============================] - 246s 7s/step - loss: 504378.8956 - mse: 504984.7812 - val_loss: 555657.3021 - val_mse: 555865.8750\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 49/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 506130.2633 - mse: 506309.5000 \n",
      "Epoch 00049: val_loss did not improve from 555471.30556\n",
      "34/34 [==============================] - 245s 7s/step - loss: 504593.2354 - mse: 504727.2500 - val_loss: 555537.6319 - val_mse: 555977.8125\n",
      "Epoch 50/50\n",
      "33/34 [============================>.] - ETA: 5s - loss: 496317.6477 - mse: 495853.5625 \n",
      "Epoch 00050: val_loss improved from 555471.30556 to 550740.50347, saving model to ./complex_model/128_per_recipe.h5\n",
      "34/34 [==============================] - 247s 7s/step - loss: 497892.6490 - mse: 497491.2812 - val_loss: 550740.5035 - val_mse: 551527.0625\n"
     ]
    }
   ],
   "source": [
    "from tensorflow.keras.optimizers import Adam\n",
    "from tensorflow.keras.callbacks import ModelCheckpoint\n",
    "from tensorflow.keras import metrics\n",
    "\n",
    "model.compile(optimizer=Adam(lr=1e-3), loss='mse', metrics=['mse'])\n",
    "\n",
    "checkpointer = ModelCheckpoint(filepath='./complex_model/128_per_recipe.h5', verbose=1, \n",
    "                               monitor='val_loss', mode='auto', save_best_only=True)\n",
    "\n",
    "history = model.fit_generator(generator=train_generator,\n",
    "                    steps_per_epoch=round(train_generator.n/train_generator.batch_size),\n",
    "                    epochs=50,\n",
    "                    validation_data=valid_generator,\n",
    "                    validation_steps=round(valid_generator.n/valid_generator.batch_size),\n",
    "                    callbacks=[checkpointer]\n",
    "                   ) \n",
    "\n",
    "\n",
    "with open('./complex_model/128_per_recipe.pkl','wb') as f:\n",
    "    pickle.dump(history.history, f)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f7b66d5fa20>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 864x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# imagenet preprocessing\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "history = history.history\n",
    "\n",
    "plt.figure(figsize=(12,6))\n",
    "plt.plot(history['loss'], label='train_loss')\n",
    "plt.plot(history['val_loss'], label='val_loss')\n",
    "\n",
    "plt.title(\"Loss on training and validation set\")\n",
    "plt.xlabel('Epoch')\n",
    "plt.ylabel('MSE Loss (kcal)')\n",
    "plt.legend()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}