Facial_Expression_Recognizer.ipynb

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  "metadata": {
    "colab": {
      "name": "Facial Expression Recognizer",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w7wKofsgo7wO"
      },
      "source": [
        "## 1. Import Libraries"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UaaYsigSKDss"
      },
      "source": [
        "# Code to read csv file into Colaboratory:\n",
        "!pip install -U -q PyDrive\n",
        "from pydrive.auth import GoogleAuth\n",
        "from pydrive.drive import GoogleDrive\n",
        "from google.colab import auth\n",
        "from oauth2client.client import GoogleCredentials"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0zELce_FfXvX"
      },
      "source": [
        "from datetime import datetime\n",
        "import sys, os\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "O1bsxujiR24S"
      },
      "source": [
        "import tensorflow as tf"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "UFwV8vn8pADn"
      },
      "source": [
        "## 2. Download Dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_W_sJZWpKIS0"
      },
      "source": [
        "auth.authenticate_user()\n",
        "gauth = GoogleAuth()\n",
        "gauth.credentials = GoogleCredentials.get_application_default()\n",
        "drive = GoogleDrive(gauth)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n_ZOds8eKUZL"
      },
      "source": [
        "link = '11QbnYVRWzDIN_VIdFUhcH9u6Oex40__T' # get the fer2013.csv Google Drive id"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "XNg8AfOeKxfP"
      },
      "source": [
        "downloaded = drive.CreateFile({'id':link}) \n",
        "downloaded.GetContentFile('fer2013.csv')  \n",
        "dataset = pd.read_csv('fer2013.csv')"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nc_a3z0ML3pI",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 347
        },
        "outputId": "bf9ed88a-a58a-47ce-f464-0286eb3db0c9"
      },
      "source": [
        "dataset.head(10)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>emotion</th>\n",
              "      <th>pixels</th>\n",
              "      <th>Usage</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>70 80 82 72 58 58 60 63 54 58 60 48 89 115 121...</td>\n",
              "      <td>Training</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>151 150 147 155 148 133 111 140 170 174 182 15...</td>\n",
              "      <td>Training</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>231 212 156 164 174 138 161 173 182 200 106 38...</td>\n",
              "      <td>Training</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>24 32 36 30 32 23 19 20 30 41 21 22 32 34 21 1...</td>\n",
              "      <td>Training</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>6</td>\n",
              "      <td>4 0 0 0 0 0 0 0 0 0 0 0 3 15 23 28 48 50 58 84...</td>\n",
              "      <td>Training</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2</td>\n",
              "      <td>55 55 55 55 55 54 60 68 54 85 151 163 170 179 ...</td>\n",
              "      <td>Training</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>4</td>\n",
              "      <td>20 17 19 21 25 38 42 42 46 54 56 62 63 66 82 1...</td>\n",
              "      <td>Training</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>3</td>\n",
              "      <td>77 78 79 79 78 75 60 55 47 48 58 73 77 79 57 5...</td>\n",
              "      <td>Training</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>3</td>\n",
              "      <td>85 84 90 121 101 102 133 153 153 169 177 189 1...</td>\n",
              "      <td>Training</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2</td>\n",
              "      <td>255 254 255 254 254 179 122 107 95 124 149 150...</td>\n",
              "      <td>Training</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
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            ],
            "text/plain": [
              "   emotion                                             pixels     Usage\n",
              "0        0  70 80 82 72 58 58 60 63 54 58 60 48 89 115 121...  Training\n",
              "1        0  151 150 147 155 148 133 111 140 170 174 182 15...  Training\n",
              "2        2  231 212 156 164 174 138 161 173 182 200 106 38...  Training\n",
              "3        4  24 32 36 30 32 23 19 20 30 41 21 22 32 34 21 1...  Training\n",
              "4        6  4 0 0 0 0 0 0 0 0 0 0 0 3 15 23 28 48 50 58 84...  Training\n",
              "5        2  55 55 55 55 55 54 60 68 54 85 151 163 170 179 ...  Training\n",
              "6        4  20 17 19 21 25 38 42 42 46 54 56 62 63 66 82 1...  Training\n",
              "7        3  77 78 79 79 78 75 60 55 47 48 58 73 77 79 57 5...  Training\n",
              "8        3  85 84 90 121 101 102 133 153 153 169 177 189 1...  Training\n",
              "9        2  255 254 255 254 254 179 122 107 95 124 149 150...  Training"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 118
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gnmcpzhX7XJg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 83
        },
        "outputId": "84fc443a-518d-4642-c4a3-397079afe3ec"
      },
      "source": [
        "dataset[\"Usage\"].value_counts()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Training       28709\n",
              "PublicTest      3589\n",
              "PrivateTest     3589\n",
              "Name: Usage, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 119
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t4rPz7QSpHvR"
      },
      "source": [
        "## 3. Formatting & Converting Dataset\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SWXnO11C5DNC"
      },
      "source": [
        " # image parameters\n",
        "width, height = 48, 48\n",
        "# dropout_rate = 0.3"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CaqBEOvNNqws"
      },
      "source": [
        "dataset['pixels'] = dataset['pixels'].apply(lambda pixel_sequence: [int(pixel) for pixel in pixel_sequence.split()])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ylQ3olInObKk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 257
        },
        "outputId": "39894c9e-d2e6-48c5-a72b-7c0437de227f"
      },
      "source": [
        "emotion_map = {0:'Angry', 1:'Disgust', 2:'Fear', 3:'Happy', 4:'Sad', 5:'Surprise', 6:'Neutral'}\n",
        "emotion_counts = dataset['emotion'].value_counts().reset_index()\n",
        "emotion_counts.columns = ['emotion', 'number']\n",
        "emotion_counts['emotion'] = emotion_counts['emotion'].map(emotion_map)\n",
        "emotion_counts"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe thead th {\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>emotion</th>\n",
              "      <th>number</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Happy</td>\n",
              "      <td>8989</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Neutral</td>\n",
              "      <td>6198</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Sad</td>\n",
              "      <td>6077</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Fear</td>\n",
              "      <td>5121</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Angry</td>\n",
              "      <td>4953</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Surprise</td>\n",
              "      <td>4002</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Disgust</td>\n",
              "      <td>547</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    emotion  number\n",
              "0     Happy    8989\n",
              "1   Neutral    6198\n",
              "2       Sad    6077\n",
              "3      Fear    5121\n",
              "4     Angry    4953\n",
              "5  Surprise    4002\n",
              "6   Disgust     547"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 122
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Sdg8aFKcNz0H",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 591
        },
        "outputId": "144f246e-e96b-47b2-dcb4-58d4c15a66c6"
      },
      "source": [
        "random_seed = 8\n",
        "# randomly select 16 images\n",
        "image_sample = dataset.sample(16, random_state=random_seed)\n",
        "\n",
        "# Create subplots for images\n",
        "_, axs = plt.subplots(4, 4, figsize=(10,10))\n",
        "axs = axs.ravel()\n",
        "i = 0\n",
        "for _, row in image_sample.iterrows():\n",
        "    one_image = np.array(row['pixels']).reshape(width,height)\n",
        "    axs[i].imshow(one_image, cmap='gray')\n",
        "    axs[i].set_title(emotion_map[row['emotion']])\n",
        "    axs[i].axis('off')\n",
        "    i += 1"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 16 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LQiUR_YaQCxi",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 217
        },
        "outputId": "a23aa9cc-481f-404d-fc75-03ce24374dbb"
      },
      "source": [
        "dataset[\"emotion\"]"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0        0\n",
              "1        0\n",
              "2        2\n",
              "3        4\n",
              "4        6\n",
              "        ..\n",
              "35882    6\n",
              "35883    3\n",
              "35884    0\n",
              "35885    3\n",
              "35886    2\n",
              "Name: emotion, Length: 35887, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 124
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VB83x6lTPYA1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "62f27f84-ad74-46e7-b7da-a6761d3a7e96"
      },
      "source": [
        "# training data\n",
        "data_train = dataset[dataset['Usage']=='Training']\n",
        "# reshape image data (num of images, width, height, num of channels)\n",
        "x_train = np.array(data_train['pixels'].tolist(), dtype='float32').reshape(-1,width,height,1)/255.\n",
        "# get labels\n",
        "y_train = data_train['emotion'].to_numpy()\n",
        "\n",
        "# validation data\n",
        "data_val = dataset[dataset['Usage']!='Training']\n",
        "# reshape image data (num of images, width, height, num of channels)\n",
        "x_val = np.array(data_val['pixels'].tolist(), dtype='float32').reshape(-1,width,height,1)/255.\n",
        "# get labels\n",
        "y_val = data_val['emotion'].to_numpy()\n",
        "\n",
        "x_train.shape, y_train.shape, x_val.shape, y_val.shape"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "((28709, 48, 48, 1), (28709,), (7178, 48, 48, 1), (7178,))"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 125
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ce2hQST4pOgq"
      },
      "source": [
        "## 4. Model Training\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9Rh_F6wORH2N",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 33
        },
        "outputId": "8d5b0249-ad48-4297-998e-0b05dfd00f32"
      },
      "source": [
        "# set training parameters\n",
        "num_train_examples = x_train.shape[0]\n",
        "\n",
        "#if varying num_epochs\n",
        "num_epochs = 450\n",
        "batch_size = 230\n",
        "#batch_size = int(num_train_examples/num_epochs)\n",
        "\n",
        "#if varying batch_size\n",
        "#batch_size = 50\n",
        "#num_epochs = int(num_train_examples/batch_size)\n",
        "\n",
        "# convert numpy arrays to tf tensors\n",
        "training_tf = tf.data.Dataset.from_tensor_slices((x_train, y_train[:,None])).batch(batch_size)\n",
        "val_tf = tf.data.Dataset.from_tensor_slices((x_val, y_val[:,None])).batch(batch_size)\n",
        "\n",
        "num_train_examples, num_epochs, batch_size"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(28709, 450, 230)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 131
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "td1q97sXVuFB"
      },
      "source": [
        "nn = tf.keras.layers # neural network layer\n",
        "\n",
        "# just if you're wondering about the layer \n",
        "# --> https://www.tensorflow.org/api_docs/python/tf/keras/layers\n",
        "# --> https://www.tensorflow.org/api_docs/python/tf/keras/layers/Conv2D"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CFCWOXBZRYMs"
      },
      "source": [
        "# just a typical CNN, not gonna do a VGG16.\n",
        "model = tf.keras.Sequential([\n",
        "    nn.Conv2D(16, kernel_size=(3, 3), padding=\"same\", activation=\"relu\", input_shape=(width, height, 1),  data_format='channels_last'), #Layer 1\n",
        "    nn.Conv2D(16, kernel_size=(3, 3), padding=\"same\", activation=\"relu\"), #Layer 2\n",
        "    nn.BatchNormalization(), #Layer 3\n",
        "    nn.MaxPooling2D(pool_size=(2,2), strides=(2,2)), #Layer 3\n",
        "    nn.Dropout(0.5), #Layer 4 (dropout layer)\n",
        "\n",
        "    nn.Conv2D(32, kernel_size=(3, 3), padding=\"same\", activation=\"relu\"), #Layer 5\n",
        "    nn.BatchNormalization(), #Layer 5\n",
        "    nn.Conv2D(32, kernel_size=(3, 3), padding=\"same\", activation=\"relu\"), #layer 6\n",
        "    nn.BatchNormalization(), #Layer 6\n",
        "    nn.MaxPooling2D(pool_size=(2,2), strides=(2,2)), #Layer 7\n",
        "    nn.Dropout(0.5), #Layer 8\n",
        "\n",
        "    nn.Conv2D(64, kernel_size=(3, 3), padding=\"same\", activation=\"relu\"), #Layer 9\n",
        "    nn.BatchNormalization(), #Layer 9\n",
        "    nn.Conv2D(64, kernel_size=(3, 3), padding=\"same\", activation=\"relu\"), #Layer 10\n",
        "    nn.BatchNormalization(), #Layer 10\n",
        "    nn.MaxPooling2D(pool_size=(2,2), strides=(2,2)), #Layer 11\n",
        "    nn.Dropout(0.5), #Layer 12\n",
        "\n",
        "    nn.Conv2D(128, kernel_size=(3, 3), padding=\"same\", activation=\"relu\"), #Layer 13\n",
        "    nn.BatchNormalization(), #Layer 13\n",
        "    nn.Conv2D(128, kernel_size=(3, 3), padding=\"same\", activation=\"relu\"), #Layer 14\n",
        "    nn.BatchNormalization(), #Layer 14\n",
        "    nn.MaxPooling2D(pool_size=(2,2), strides=(2,2)), #Layer 15\n",
        "    nn.Dropout(0.5), #Layer 16\n",
        "\n",
        "    nn.Flatten(),\n",
        "\n",
        "    nn.Dense(128, activation=\"relu\"), #Layer 16\n",
        "    nn.Dropout(0.4), #Layer 17\n",
        "    nn.Dense(64, activation=\"relu\"), #Layer 18\n",
        "    nn.Dropout(0.4), #Layer 19\n",
        "    nn.Dense(32, activation=\"relu\"), #Layer 20\n",
        "    nn.Dropout(0.5), #Layer 21\n",
        "\n",
        "    nn.Dense(7, activation='softmax'), #Layer 22\n",
        "])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gONSCrqFUIW4"
      },
      "source": [
        "model.compile(optimizer='adam',\n",
        "              loss='sparse_categorical_crossentropy', # I'm not entirely sure what this does, its from the tensorflow documentation for image type of data\n",
        "              metrics=['accuracy'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FtIb7lftVOnb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "d7c5d9d0-305c-4dea-fb7f-bec2cf432fd2"
      },
      "source": [
        "facial_expression = model.fit(training_tf, \n",
        "                              validation_data=val_tf, \n",
        "                              epochs=num_epochs, \n",
        "                              verbose=2,\n",
        "                              use_multiprocessing=True)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/450\n",
            "125/125 - 9s - loss: 2.0084 - accuracy: 0.2073 - val_loss: 1.8320 - val_accuracy: 0.2471\n",
            "Epoch 2/450\n",
            "125/125 - 9s - loss: 1.8468 - accuracy: 0.2430 - val_loss: 1.8248 - val_accuracy: 0.2471\n",
            "Epoch 3/450\n",
            "125/125 - 9s - loss: 1.8270 - accuracy: 0.2477 - val_loss: 1.8148 - val_accuracy: 0.2471\n",
            "Epoch 4/450\n",
            "125/125 - 9s - loss: 1.8199 - accuracy: 0.2507 - val_loss: 1.8169 - val_accuracy: 0.2471\n",
            "Epoch 5/450\n",
            "125/125 - 9s - loss: 1.8191 - accuracy: 0.2503 - val_loss: 1.8119 - val_accuracy: 0.2471\n",
            "Epoch 6/450\n",
            "125/125 - 9s - loss: 1.8171 - accuracy: 0.2506 - val_loss: 1.8037 - val_accuracy: 0.2471\n",
            "Epoch 7/450\n",
            "125/125 - 9s - loss: 1.8145 - accuracy: 0.2506 - val_loss: 1.8016 - val_accuracy: 0.2471\n",
            "Epoch 8/450\n",
            "125/125 - 9s - loss: 1.8118 - accuracy: 0.2502 - val_loss: 1.8060 - val_accuracy: 0.2471\n",
            "Epoch 9/450\n",
            "125/125 - 9s - loss: 1.8090 - accuracy: 0.2514 - val_loss: 1.8360 - val_accuracy: 0.2471\n",
            "Epoch 10/450\n",
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            "Epoch 17/450\n",
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            "Epoch 18/450\n",
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            "Epoch 19/450\n",
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            "Epoch 20/450\n",
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            "Epoch 21/450\n",
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            "Epoch 22/450\n",
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            "Epoch 23/450\n",
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            "Epoch 24/450\n",
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            "Epoch 25/450\n",
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            "Epoch 26/450\n",
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            "Epoch 27/450\n",
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            "Epoch 28/450\n",
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            "Epoch 29/450\n",
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            "Epoch 30/450\n",
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            "Epoch 31/450\n",
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            "Epoch 32/450\n",
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            "Epoch 33/450\n",
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            "Epoch 34/450\n",
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            "Epoch 35/450\n",
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            "Epoch 36/450\n",
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            "Epoch 37/450\n",
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            "Epoch 38/450\n",
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            "Epoch 39/450\n",
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            "Epoch 40/450\n",
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            "Epoch 41/450\n",
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            "Epoch 42/450\n",
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            "Epoch 43/450\n",
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            "Epoch 44/450\n",
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            "Epoch 45/450\n",
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            "Epoch 46/450\n",
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            "Epoch 47/450\n",
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            "Epoch 48/450\n",
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            "Epoch 49/450\n",
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            "Epoch 50/450\n",
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            "Epoch 51/450\n",
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            "Epoch 52/450\n",
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            "Epoch 53/450\n",
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            "Epoch 54/450\n",
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            "Epoch 55/450\n",
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            "Epoch 56/450\n",
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            "Epoch 57/450\n",
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            "Epoch 58/450\n",
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            "Epoch 59/450\n",
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            "Epoch 60/450\n",
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            "Epoch 61/450\n",
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            "Epoch 62/450\n",
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            "Epoch 63/450\n",
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            "Epoch 64/450\n",
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            "Epoch 65/450\n",
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            "Epoch 66/450\n",
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            "Epoch 67/450\n",
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            "Epoch 68/450\n",
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            "Epoch 69/450\n",
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            "Epoch 70/450\n",
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            "Epoch 71/450\n",
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            "Epoch 72/450\n",
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            "Epoch 73/450\n",
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            "Epoch 74/450\n",
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            "Epoch 75/450\n",
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            "Epoch 76/450\n",
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            "Epoch 77/450\n",
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            "Epoch 78/450\n",
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            "Epoch 79/450\n",
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            "Epoch 80/450\n",
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            "Epoch 81/450\n",
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            "Epoch 82/450\n",
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            "Epoch 83/450\n",
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            "Epoch 84/450\n",
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            "Epoch 85/450\n",
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            "Epoch 86/450\n",
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            "Epoch 87/450\n",
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            "Epoch 88/450\n",
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            "Epoch 89/450\n",
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            "Epoch 90/450\n",
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            "Epoch 91/450\n",
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            "Epoch 93/450\n",
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            "Epoch 94/450\n",
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            "Epoch 95/450\n",
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            "Epoch 96/450\n",
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            "Epoch 97/450\n",
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            "Epoch 98/450\n",
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            "Epoch 99/450\n",
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            "Epoch 100/450\n",
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            "Epoch 101/450\n",
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            "Epoch 102/450\n",
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            "Epoch 103/450\n",
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            "Epoch 104/450\n",
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            "Epoch 107/450\n",
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            "Epoch 110/450\n",
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            "Epoch 111/450\n",
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            "Epoch 112/450\n",
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            "Epoch 113/450\n",
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            "Epoch 115/450\n",
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            "Epoch 120/450\n",
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            "Epoch 128/450\n",
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            "Epoch 129/450\n",
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            "Epoch 139/450\n",
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            "Epoch 140/450\n",
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            "Epoch 141/450\n",
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            "Epoch 142/450\n",
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            "Epoch 143/450\n",
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            "Epoch 144/450\n",
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            "Epoch 145/450\n",
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            "Epoch 146/450\n",
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            "Epoch 147/450\n",
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            "Epoch 148/450\n",
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            "Epoch 149/450\n",
            "125/125 - 9s - loss: 1.1181 - accuracy: 0.5972 - val_loss: 1.1020 - val_accuracy: 0.6000\n",
            "Epoch 150/450\n",
            "125/125 - 9s - loss: 1.1140 - accuracy: 0.5977 - val_loss: 1.0995 - val_accuracy: 0.5979\n",
            "Epoch 151/450\n",
            "125/125 - 9s - loss: 1.1192 - accuracy: 0.5980 - val_loss: 1.0781 - val_accuracy: 0.5975\n",
            "Epoch 152/450\n",
            "125/125 - 9s - loss: 1.1082 - accuracy: 0.5990 - val_loss: 1.0828 - val_accuracy: 0.6024\n",
            "Epoch 153/450\n",
            "125/125 - 9s - loss: 1.1130 - accuracy: 0.5975 - val_loss: 1.0935 - val_accuracy: 0.6071\n",
            "Epoch 154/450\n",
            "125/125 - 9s - loss: 1.1043 - accuracy: 0.5977 - val_loss: 1.1088 - val_accuracy: 0.5979\n",
            "Epoch 155/450\n",
            "125/125 - 9s - loss: 1.1083 - accuracy: 0.6023 - val_loss: 1.0892 - val_accuracy: 0.6011\n",
            "Epoch 156/450\n",
            "125/125 - 9s - loss: 1.0989 - accuracy: 0.6018 - val_loss: 1.0929 - val_accuracy: 0.5995\n",
            "Epoch 157/450\n",
            "125/125 - 9s - loss: 1.1042 - accuracy: 0.6003 - val_loss: 1.1063 - val_accuracy: 0.5936\n",
            "Epoch 158/450\n",
            "125/125 - 9s - loss: 1.1036 - accuracy: 0.6002 - val_loss: 1.1000 - val_accuracy: 0.5932\n",
            "Epoch 159/450\n",
            "125/125 - 9s - loss: 1.1002 - accuracy: 0.6025 - val_loss: 1.0943 - val_accuracy: 0.5968\n",
            "Epoch 160/450\n",
            "125/125 - 9s - loss: 1.0982 - accuracy: 0.6032 - val_loss: 1.0888 - val_accuracy: 0.6016\n",
            "Epoch 161/450\n",
            "125/125 - 9s - loss: 1.0985 - accuracy: 0.6052 - val_loss: 1.0874 - val_accuracy: 0.5992\n",
            "Epoch 162/450\n",
            "125/125 - 9s - loss: 1.1043 - accuracy: 0.6039 - val_loss: 1.1068 - val_accuracy: 0.5882\n",
            "Epoch 163/450\n",
            "125/125 - 9s - loss: 1.0975 - accuracy: 0.6031 - val_loss: 1.0899 - val_accuracy: 0.6064\n",
            "Epoch 164/450\n",
            "125/125 - 9s - loss: 1.0956 - accuracy: 0.6070 - val_loss: 1.1223 - val_accuracy: 0.5915\n",
            "Epoch 165/450\n",
            "125/125 - 9s - loss: 1.1014 - accuracy: 0.6025 - val_loss: 1.0797 - val_accuracy: 0.6052\n",
            "Epoch 166/450\n",
            "125/125 - 9s - loss: 1.0892 - accuracy: 0.6083 - val_loss: 1.0998 - val_accuracy: 0.5979\n",
            "Epoch 167/450\n",
            "125/125 - 9s - loss: 1.0914 - accuracy: 0.6023 - val_loss: 1.0813 - val_accuracy: 0.6101\n",
            "Epoch 168/450\n",
            "125/125 - 9s - loss: 1.0842 - accuracy: 0.6087 - val_loss: 1.0856 - val_accuracy: 0.6041\n",
            "Epoch 169/450\n",
            "125/125 - 9s - loss: 1.0882 - accuracy: 0.6089 - val_loss: 1.0935 - val_accuracy: 0.5958\n",
            "Epoch 170/450\n",
            "125/125 - 9s - loss: 1.0906 - accuracy: 0.6045 - val_loss: 1.0760 - val_accuracy: 0.6078\n",
            "Epoch 171/450\n",
            "125/125 - 9s - loss: 1.0949 - accuracy: 0.6034 - val_loss: 1.0655 - val_accuracy: 0.6074\n",
            "Epoch 172/450\n",
            "125/125 - 9s - loss: 1.0854 - accuracy: 0.6078 - val_loss: 1.0763 - val_accuracy: 0.6043\n",
            "Epoch 173/450\n",
            "125/125 - 9s - loss: 1.0903 - accuracy: 0.6073 - val_loss: 1.0734 - val_accuracy: 0.6134\n",
            "Epoch 174/450\n",
            "125/125 - 9s - loss: 1.0731 - accuracy: 0.6096 - val_loss: 1.0749 - val_accuracy: 0.6113\n",
            "Epoch 175/450\n",
            "125/125 - 9s - loss: 1.0746 - accuracy: 0.6133 - val_loss: 1.0774 - val_accuracy: 0.6134\n",
            "Epoch 176/450\n",
            "125/125 - 9s - loss: 1.0845 - accuracy: 0.6081 - val_loss: 1.0935 - val_accuracy: 0.6002\n",
            "Epoch 177/450\n",
            "125/125 - 9s - loss: 1.0796 - accuracy: 0.6118 - val_loss: 1.0918 - val_accuracy: 0.6024\n",
            "Epoch 178/450\n",
            "125/125 - 9s - loss: 1.0780 - accuracy: 0.6113 - val_loss: 1.0873 - val_accuracy: 0.6039\n",
            "Epoch 179/450\n",
            "125/125 - 9s - loss: 1.0804 - accuracy: 0.6101 - val_loss: 1.0866 - val_accuracy: 0.6057\n",
            "Epoch 180/450\n",
            "125/125 - 9s - loss: 1.0799 - accuracy: 0.6088 - val_loss: 1.0799 - val_accuracy: 0.6067\n",
            "Epoch 181/450\n",
            "125/125 - 9s - loss: 1.0782 - accuracy: 0.6119 - val_loss: 1.0910 - val_accuracy: 0.5967\n",
            "Epoch 182/450\n",
            "125/125 - 9s - loss: 1.0723 - accuracy: 0.6153 - val_loss: 1.0877 - val_accuracy: 0.6066\n",
            "Epoch 183/450\n",
            "125/125 - 9s - loss: 1.0637 - accuracy: 0.6124 - val_loss: 1.0619 - val_accuracy: 0.6101\n",
            "Epoch 184/450\n",
            "125/125 - 9s - loss: 1.0710 - accuracy: 0.6141 - val_loss: 1.0812 - val_accuracy: 0.6084\n",
            "Epoch 185/450\n",
            "125/125 - 9s - loss: 1.0657 - accuracy: 0.6144 - val_loss: 1.0657 - val_accuracy: 0.6082\n",
            "Epoch 186/450\n",
            "125/125 - 9s - loss: 1.0661 - accuracy: 0.6157 - val_loss: 1.0745 - val_accuracy: 0.6071\n",
            "Epoch 187/450\n",
            "125/125 - 9s - loss: 1.0630 - accuracy: 0.6193 - val_loss: 1.0670 - val_accuracy: 0.6078\n",
            "Epoch 188/450\n",
            "125/125 - 9s - loss: 1.0622 - accuracy: 0.6166 - val_loss: 1.0791 - val_accuracy: 0.6092\n",
            "Epoch 189/450\n",
            "125/125 - 9s - loss: 1.0654 - accuracy: 0.6178 - val_loss: 1.0810 - val_accuracy: 0.6042\n",
            "Epoch 190/450\n",
            "125/125 - 9s - loss: 1.0574 - accuracy: 0.6218 - val_loss: 1.0705 - val_accuracy: 0.6085\n",
            "Epoch 191/450\n",
            "125/125 - 9s - loss: 1.0586 - accuracy: 0.6187 - val_loss: 1.0784 - val_accuracy: 0.6110\n",
            "Epoch 192/450\n",
            "125/125 - 9s - loss: 1.0548 - accuracy: 0.6218 - val_loss: 1.0977 - val_accuracy: 0.6067\n",
            "Epoch 193/450\n",
            "125/125 - 9s - loss: 1.0561 - accuracy: 0.6188 - val_loss: 1.0765 - val_accuracy: 0.6078\n",
            "Epoch 194/450\n",
            "125/125 - 9s - loss: 1.0513 - accuracy: 0.6226 - val_loss: 1.0770 - val_accuracy: 0.6116\n",
            "Epoch 195/450\n",
            "125/125 - 9s - loss: 1.0496 - accuracy: 0.6233 - val_loss: 1.0803 - val_accuracy: 0.6057\n",
            "Epoch 196/450\n",
            "125/125 - 9s - loss: 1.0562 - accuracy: 0.6194 - val_loss: 1.0934 - val_accuracy: 0.6000\n",
            "Epoch 197/450\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4gho8IFUpVOH"
      },
      "source": [
        "## 5. Model Testing & Evaluation"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N7buv2GTtXPh"
      },
      "source": [
        "# MY CREATION SHALL PREDICT Validation Dataset\n",
        "test_scores = model.evaluate(x_train, y_train, batch_size=batch_size, verbose=0)\n",
        "print(\"Model Score\\n===============================\\n\")\n",
        "print(\"Loss:      \" + str(test_scores[0]))\n",
        "print(\"Accuracy:  \" + str(test_scores[1]) + \"\\n\")\n",
        "# model.predict(val_tf, use_multiprocessing=True, verbose=1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "us6s2OA5Kyzd"
      },
      "source": [
        "# Training Dataset\n",
        "train_accuracy = facial_expression.history['accuracy']\n",
        "train_loss = facial_expression.history['loss']\n",
        "val_accuracy = facial_expression.history['val_accuracy']\n",
        "val_loss = facial_expression.history['val_loss']"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yKhPVHyE50iA"
      },
      "source": [
        "#Plot accuracy against epochs\n",
        "x_axis = list(range(1, num_epochs+1))\n",
        "plt.plot(x_axis,train_accuracy, label=\"Train\")\n",
        "plt.plot(x_axis,val_accuracy, label=\"Validation\")\n",
        "plt.ylabel('Accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.legend()\n",
        "plt.title(\"Accuracy against Epochs\")\n",
        "plt.show()\n"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n9M-ZiBu9NL-"
      },
      "source": [
        "#Plot loss against epochs\n",
        "x_axis = list(range(1, num_epochs+1))\n",
        "plt.plot(x_axis,train_loss, label=\"Train\")\n",
        "plt.plot(x_axis,val_loss, label=\"Validation\")\n",
        "plt.ylabel('Loss')\n",
        "plt.xlabel('Epoch')\n",
        "plt.legend()\n",
        "plt.title(\"Loss against Epochs\")\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "z-ftZpdx7Jpd"
      },
      "source": [
        "import statistics\n",
        "\n",
        "final_train_acc = train_accuracy[len(train_accuracy)-1]\n",
        "final_train_loss = train_loss[len(train_loss)-1]\n",
        "final_val_acc = val_accuracy[len(val_accuracy)-1]\n",
        "final_val_loss = val_loss[len(val_loss)-1]\n",
        "\n",
        "var_acc = statistics.variance(train_accuracy)\n",
        "var_loss = statistics.variance(train_loss)\n",
        "\n",
        "final_train_acc, final_val_acc, final_train_loss, final_val_loss, var_acc, var_loss"
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}