sentiment_analysis_with_whole_data.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/uadR1/nlphatespeech/blob/main/sentiment_analysis_with_whole_data.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LqTSsVGODqx7",
        "outputId": "c0a7a8d6-63a1-49cc-9fcd-40ad16adbf22"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/\n",
            "Requirement already satisfied: transformers in /usr/local/lib/python3.8/dist-packages (4.25.1)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.8/dist-packages (from transformers) (3.8.0)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.8/dist-packages (from transformers) (2.23.0)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (1.21.6)\n",
            "Requirement already satisfied: huggingface-hub<1.0,>=0.10.0 in /usr/local/lib/python3.8/dist-packages (from transformers) (0.11.1)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.8/dist-packages (from transformers) (21.3)\n",
            "Requirement already satisfied: regex!=2019.12.17 in /usr/local/lib/python3.8/dist-packages (from transformers) (2022.6.2)\n",
            "Requirement already satisfied: tqdm>=4.27 in /usr/local/lib/python3.8/dist-packages (from transformers) (4.64.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.8/dist-packages (from transformers) (6.0)\n",
            "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /usr/local/lib/python3.8/dist-packages (from transformers) (0.13.2)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.8/dist-packages (from huggingface-hub<1.0,>=0.10.0->transformers) (4.4.0)\n",
            "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.8/dist-packages (from packaging>=20.0->transformers) (3.0.9)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2.10)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (1.24.3)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (3.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.8/dist-packages (from requests->transformers) (2022.9.24)\n"
          ]
        }
      ],
      "source": [
        "\n",
        "! pip install transformers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "4blMR83RCRLl"
      },
      "outputs": [],
      "source": [
        "from sklearn.feature_extraction.text import CountVectorizer,TfidfVectorizer\n",
        "from sklearn.metrics import accuracy_score \n",
        "from sklearn.base import TransformerMixin \n",
        "from sklearn.pipeline import Pipeline\n",
        "from sklearn.svm import LinearSVC\n",
        "from sklearn.model_selection import train_test_split\n",
        "from transformers import AutoModelForSequenceClassification\n",
        "from transformers import TFAutoModelForSequenceClassification\n",
        "from sklearn.metrics import classification_report\n",
        "import numpy as np\n",
        "import pandas as pd\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "BG0zqMZJGCRZ",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "3687d191-995a-405a-bdf0-1c2a1dba8efa"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount(\"/content/drive\") \n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "yMKjmFXiGfra"
      },
      "outputs": [],
      "source": [
        "path=\"/content/df_all.csv\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "NllJz39KGvR4"
      },
      "outputs": [],
      "source": [
        "df= pd.read_csv(path)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "zZ-EeWlBHqYx",
        "outputId": "b2314110-6cf6-4d90-d401-ee3fc6855db3"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Unnamed: 0                                               text  \\\n",
              "0           8   rt crooked hillary you didn't lose because yo...   \n",
              "1           9   rt estonian pm :  \" i don't want blacks in es...   \n",
              "2          34  are a bunch of religious bigots . i hope you e...   \n",
              "3          45  hamas is the only one who lies and all those l...   \n",
              "4          65  one of the questions never asked : if africans...   \n",
              "\n",
              "           class  \n",
              "0  explicit_hate  \n",
              "1  explicit_hate  \n",
              "2  explicit_hate  \n",
              "3  explicit_hate  \n",
              "4  explicit_hate  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-36bddc55-7739-45cc-9d6e-1b10c37cbb7e\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>Unnamed: 0</th>\n",
              "      <th>text</th>\n",
              "      <th>class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>8</td>\n",
              "      <td>rt crooked hillary you didn't lose because yo...</td>\n",
              "      <td>explicit_hate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>9</td>\n",
              "      <td>rt estonian pm :  \" i don't want blacks in es...</td>\n",
              "      <td>explicit_hate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>34</td>\n",
              "      <td>are a bunch of religious bigots . i hope you e...</td>\n",
              "      <td>explicit_hate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>45</td>\n",
              "      <td>hamas is the only one who lies and all those l...</td>\n",
              "      <td>explicit_hate</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>65</td>\n",
              "      <td>one of the questions never asked : if africans...</td>\n",
              "      <td>explicit_hate</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-36bddc55-7739-45cc-9d6e-1b10c37cbb7e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-36bddc55-7739-45cc-9d6e-1b10c37cbb7e button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-36bddc55-7739-45cc-9d6e-1b10c37cbb7e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "VvJnH-XTKw34"
      },
      "outputs": [],
      "source": [
        "#df2 = df.sample(frac=0.20) "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SiFGxrkmJu0U",
        "outputId": "13136c78-ede1-4881-a144-f4ad700edcd6"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(64875, 3)"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ],
      "source": [
        "df.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "b7pDnVO0CRLu",
        "outputId": "bc305dd4-4a29-4cea-9dba-c83905383d32"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Index(['not_hate', 'offensive', 'implicit_hate', 'explicit_hate'], dtype='object')"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ],
      "source": [
        "category_count = df['class'].value_counts()\n",
        "\n",
        "categories = category_count.index\n",
        "\n",
        "categories"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "gmQBFkFLCRLv"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "Zi4T7mD_CRLw"
      },
      "outputs": [],
      "source": [
        "\n",
        "import seaborn as sns"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 357
        },
        "id": "4sB6tUGQCRLx",
        "outputId": "4e03c145-5670-458c-c52f-f9e8a1a327f1"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 864x360 with 1 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "fig = plt.figure(figsize= (12, 5))\n",
        "\n",
        "ax = fig.add_subplot(111)\n",
        "\n",
        "sns.barplot(x = category_count.index, y = category_count )\n",
        "\n",
        "for a, p in enumerate(ax.patches):\n",
        "    ax.annotate(f'{categories[a]}\\n' + format(p.get_height(), '.0f'), xy = (p.get_x() + p.get_width() / 2.0, p.get_height()), xytext = (0,-25), size = 13, color = 'white' , ha = 'center', va = 'center', textcoords = 'offset points', bbox = dict(boxstyle = 'round', facecolor='none',edgecolor='white', alpha = 0.5) )\n",
        "    \n",
        "plt.xlabel('Categories', size = 12)\n",
        "\n",
        "plt.ylabel('The Number of Comments', size= 12)\n",
        "\n",
        "plt.xticks(size = 12)\n",
        "\n",
        "plt.title(\"The number of Comments by class\" , size = 14)\n",
        "\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "ceePUVQrCRLy"
      },
      "outputs": [],
      "source": [
        "#hate=1 not_hate=0"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "bDZbgJa_CRL0"
      },
      "outputs": [],
      "source": [
        "df = df.dropna()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "NdwOfrX0CRL0"
      },
      "outputs": [],
      "source": [
        "#df['text_cleaned'] = df['text'].str.replace('@[A-Za-z0-9]+\\s?','', regex=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xNOTi8DUH3j-"
      },
      "outputs": [],
      "source": [
        "#df['class_encoded'] = df['class'].astype('category').cat.codes\n",
        "#df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "fPUyD45YQ5YM",
        "outputId": "69d3bdff-e4fa-4bf5-c0c0-0756dcbacf9a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   Unnamed: 0                                               text class\n",
              "0           8   rt crooked hillary you didn't lose because yo...     1\n",
              "1           9   rt estonian pm :  \" i don't want blacks in es...     1\n",
              "2          34  are a bunch of religious bigots . i hope you e...     1\n",
              "3          45  hamas is the only one who lies and all those l...     1\n",
              "4          65  one of the questions never asked : if africans...     1"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-f7eb5afe-32d2-4f4c-955e-89f327e053a0\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>Unnamed: 0</th>\n",
              "      <th>text</th>\n",
              "      <th>class</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>8</td>\n",
              "      <td>rt crooked hillary you didn't lose because yo...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>9</td>\n",
              "      <td>rt estonian pm :  \" i don't want blacks in es...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>34</td>\n",
              "      <td>are a bunch of religious bigots . i hope you e...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>45</td>\n",
              "      <td>hamas is the only one who lies and all those l...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>65</td>\n",
              "      <td>one of the questions never asked : if africans...</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f7eb5afe-32d2-4f4c-955e-89f327e053a0')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f7eb5afe-32d2-4f4c-955e-89f327e053a0 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-f7eb5afe-32d2-4f4c-955e-89f327e053a0');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ],
      "source": [
        "\n",
        "# Replace classes \n",
        "df['class'] = np.where((df['class'] == 'not_hate'), 0, df['class'])\n",
        "df['class'] = np.where((df['class'] == 'explicit_hate'), 1, df['class'])\n",
        "df['class'] = np.where((df['class'] == 'implicit_hate'), 1, df['class'])\n",
        "df['class'] = np.where((df['class'] == 'offensive'), 1, df['class'])\n",
        "\n",
        "# show head \n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "EsvEwG98qq2b"
      },
      "outputs": [],
      "source": [
        "X=list(df['text'])\n",
        "#X=list(df['text_cleaned'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "id": "6bJRCocDrFvE"
      },
      "outputs": [],
      "source": [
        "y=list(df['class'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "aZpBn3MtssZL"
      },
      "outputs": [],
      "source": [
        "#y=list(pd.get_dummies(y,drop_first=True)['not_hate'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "dLFDWda0rIKw"
      },
      "outputs": [],
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.20, random_state = 123)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 145,
          "referenced_widgets": [
            "55ade72af027417f883124d2bd4fce1a",
            "8e930930656d4e7dbd99e9850b181bd6",
            "a839b52d44e141dbad9371c1756b2e37",
            "32679099028344c7a070bd8e48b8ea1c",
            "60dd581227224a2fb3cb4023330ea857",
            "49ee769927644a6098e3e45de6d4f5e3",
            "7216b0bbaf964b6bbf50a9ee5cf044ba",
            "42c1ea776f0c4f9f85837fe55ca60a04",
            "53ba823f487141e6843acb48acafe068",
            "cb04bb1e1456470bb70a5c78050a989c",
            "b27dfce6ee8a4ce4ac36c134498e9637",
            "ba3c9a54404c41feae4056b80e835cd0",
            "636363e42ff648a38c2ac4aff27456b8",
            "10ef9a28ea84447a9fd205b0e7aaacbf",
            "e31953345f4b46778c6f23ae462bc805",
            "64091a41997d4975af82528fe9405b04",
            "2e91f3bffd29452a91a182d5a165af7e",
            "8139cf75c78a49d2acb09261fa08d1a1",
            "a525ca370dfb4d61a52573688de3bf92",
            "c8d91a2228804f8cbcba8c51ffd8cfcc",
            "067196e0dd054eae82d22eed761e8c92",
            "c2d6ea2b31c3430392b89b6cacecda93",
            "a6e37356ebc44293acbbdc1032435e80",
            "c655d444c55c4f27abc3a196ce19c376",
            "81f3da10ab714896bdfca62d4aa87336",
            "d7434ee19cf34bc3a6ff175e331b5fa0",
            "a3bd92d925aa4ee9b4e75fd5cd0cb38f",
            "3251f731e08a4d0f9a44de53f4a8f5ef",
            "8b5bdce1bde24952af200b367aaa6c05",
            "251840ef040c467685ffc72fa620d733",
            "9d75c7c0cfc345a58e72205fc9d20d19",
            "f697f525bcff48818a2cb78d3c81fc45",
            "6d5efd5f3c2e4691bd1fda19cabd5859",
            "d7cc11f170944546bcaaf4e07e0dd6fd",
            "d14b751589a542bd86851853e9b62bd4",
            "5b0c99f747304d4696bced36e4bae9ce",
            "a361236cd00a4396bd1ddfef4832ff94",
            "65995febefe047c284c27288c7912f3b",
            "e2cc42b4aad14e53a78ddd3b0cd51280",
            "9af962cd882b4f719dd6c796d4b04935",
            "aed9071fa8b549dc9aa772cdff0316a0",
            "909da137888541a299b09f1bfffe2f5f",
            "6b4d10953a934b0990357485c1402d5b",
            "2ae0e2c7db0540589cd2ca991c4d3b8b"
          ]
        },
        "id": "bcNEJ6perOSs",
        "outputId": "c81a3ac1-8b0d-458e-c778-a1cdef1515e9"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          | 0.00/28.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "55ade72af027417f883124d2bd4fce1a"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          | 0.00/232k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "ba3c9a54404c41feae4056b80e835cd0"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          | 0.00/466k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a6e37356ebc44293acbbdc1032435e80"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          | 0.00/483 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "d7cc11f170944546bcaaf4e07e0dd6fd"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "from transformers import DistilBertTokenizerFast\n",
        "tokenizer = DistilBertTokenizerFast.from_pretrained('distilbert-base-uncased')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "-OL3fgLvrXvH"
      },
      "outputs": [],
      "source": [
        "train_encodings = tokenizer(X_train, truncation=True, padding=True)\n",
        "test_encodings = tokenizer(X_test, truncation=True, padding=True)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "id": "9B42CTCnrrEx"
      },
      "outputs": [],
      "source": [
        "#convert it in to dataset object for tensorflow\n",
        "import tensorflow as tf\n",
        "\n",
        "train_dataset = tf.data.Dataset.from_tensor_slices((\n",
        "    dict(train_encodings),\n",
        "    y_train\n",
        "))\n",
        "\n",
        "test_dataset = tf.data.Dataset.from_tensor_slices((\n",
        "    dict(test_encodings),\n",
        "    y_test\n",
        "))\n",
        "\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "id": "NH1dupK0rzfn"
      },
      "outputs": [],
      "source": [
        "from transformers import TFDistilBertForSequenceClassification, TFTrainer, TFTrainingArguments\n",
        "\n",
        "training_args = TFTrainingArguments(\n",
        "    output_dir='./results',          # output directory\n",
        "    num_train_epochs=2,              # total number of training epochs\n",
        "    per_device_train_batch_size=8,  # batch size per device during training\n",
        "    per_device_eval_batch_size=16,   # batch size for evaluation\n",
        "    warmup_steps=500,                # number of warmup steps for learning rate scheduler\n",
        "    weight_decay=0.01,               # strength of weight decay\n",
        "    logging_dir='./logs',            # directory for storing logs\n",
        "    logging_steps=10,\n",
        "    eval_steps = 10\n",
        "    )"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "u9UwPLC3N9Gs"
      },
      "source": []
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 190,
          "referenced_widgets": [
            "f134ef77361c402d9642c79c71a36412",
            "17e813b37ee04b50a2d953c0ebd6cc7d",
            "71f60a7def0e4cab8148b1afaafb7fdb",
            "01e501c4a6f242c6a6582912d47c2fbd",
            "a4b010a250dc4b56bc7ac7c85500be9c",
            "ebb189758cc14dab99b71c22e478caed",
            "08080a3d559048fca696315a37916a41",
            "ca9f5c43e4f245a5bc63548b64281187",
            "1ca6a17aa3cd4738b2344145c6250a03",
            "4e1f10b840554cc4a13ef24696a30c23",
            "e8f5cf19e520482eb3943cf4209718ba"
          ]
        },
        "id": "PZvTrEcfr7k-",
        "outputId": "514ca4ab-58e1-4fbc-a482-3dd5ee59b02e"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading:   0%|          | 0.00/363M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "f134ef77361c402d9642c79c71a36412"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Some layers from the model checkpoint at distilbert-base-uncased were not used when initializing TFDistilBertForSequenceClassification: ['vocab_projector', 'vocab_layer_norm', 'activation_13', 'vocab_transform']\n",
            "- This IS expected if you are initializing TFDistilBertForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing TFDistilBertForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n",
            "Some layers of TFDistilBertForSequenceClassification were not initialized from the model checkpoint at distilbert-base-uncased and are newly initialized: ['classifier', 'pre_classifier', 'dropout_19']\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n",
            "/usr/local/lib/python3.8/dist-packages/transformers/trainer_tf.py:115: FutureWarning: The class `TFTrainer` is deprecated and will be removed in version 5 of Transformers. We recommend using native Keras instead, by calling methods like `fit()` and `predict()` directly on the model object. Detailed examples of the Keras style can be found in our examples at https://github.com/huggingface/transformers/tree/main/examples/tensorflow\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "with training_args.strategy.scope():\n",
        "    model = TFDistilBertForSequenceClassification.from_pretrained(\"distilbert-base-uncased\")\n",
        "\n",
        "trainer = TFTrainer(\n",
        "    model=model,                         # the instantiated 🤗 Transformers model to be trained\n",
        "    args=training_args,                  # training arguments, defined above\n",
        "    train_dataset=train_dataset,         # training dataset\n",
        "    eval_dataset=test_dataset            # evaluation dataset\n",
        ")\n",
        "\n",
        "trainer.train()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "R534aDi3xD0s",
        "outputId": "399df3da-e4e2-48f7-f7d7-04320ad99810"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'eval_loss': 0.2502892011477623}"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ],
      "source": [
        "trainer.evaluate(test_dataset)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "UyBmI1WcxKjG"
      },
      "outputs": [],
      "source": [
        "#trainer.predict(test_dataset)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "id": "cetzb_u6CRL9"
      },
      "outputs": [],
      "source": [
        "output = trainer.predict(test_dataset)[0]\n",
        "output = np.argmax(output, axis = - 1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "O3XM1yfBCRL9"
      },
      "outputs": [],
      "source": [
        "output.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cfCE06jQu5cI",
        "outputId": "9d0a74e0-37f9-4f20-a319-049fbb4a8ef3"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([[6633,  554],\n",
              "       [ 731, 5040]])"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ],
      "source": [
        "from sklearn.metrics import confusion_matrix\n",
        "cm=confusion_matrix(y_test,output)\n",
        "cm"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "id": "mLDjZEijCRL_"
      },
      "outputs": [],
      "source": [
        "\n",
        "pd.DataFrame(output).to_csv('output.csv') "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "90ChCs5ZCRMA"
      },
      "outputs": [],
      "source": [
        "\n",
        "pd.DataFrame(y).to_csv('y.csv') "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "zc5xqfgRCRMA"
      },
      "outputs": [],
      "source": [
        "\n",
        "pd.DataFrame(X).to_csv('X.csv') "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "okD5we1NwhQW"
      },
      "outputs": [],
      "source": [
        "trainer.save_model('senti_model')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f9MbFGrEyNTS",
        "outputId": "c0fc09ba-b404-40ac-8da0-714dd4cffe3a"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "              precision    recall  f1-score   support\n",
            "\n",
            "           0       0.90      0.92      0.91      7187\n",
            "           1       0.90      0.87      0.89      5771\n",
            "\n",
            "    accuracy                           0.90     12958\n",
            "   macro avg       0.90      0.90      0.90     12958\n",
            "weighted avg       0.90      0.90      0.90     12958\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# model's performance\n",
        "print(classification_report(y_test, output))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "KJNGubugCRMB"
      },
      "outputs": [],
      "source": [
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 591
        },
        "id": "8p9emxu6CRMB",
        "outputId": "4b0b7d30-4192-4370-8a42-69e7c7cc0465"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<sklearn.metrics._plot.confusion_matrix.ConfusionMatrixDisplay at 0x7fe16dacbcd0>"
            ]
          },
          "metadata": {},
          "execution_count": 27
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 720x720 with 2 Axes>"
            ],
            "image/png": "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\n"
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "from sklearn import metrics\n",
        "import numpy\n",
        "plt.rcParams['figure.figsize'] = (10, 10)\n",
        "confusion_matrix = metrics.confusion_matrix(y_test, output)\n",
        "\n",
        "cm_display = metrics.ConfusionMatrixDisplay(confusion_matrix = confusion_matrix, display_labels = [\"not_hate\", \"hate\"])\n",
        "\n",
        "cm_display.plot()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jx59dV2UCRMB"
      },
      "outputs": [],
      "source": [
        "Precision = metrics.precision_score(y_test, output)\n",
        "\n",
        "print(Precision)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "F-UJYywYCRMC"
      },
      "outputs": [],
      "source": [
        "Sensitivity_recall = metrics.recall_score(y_test, output)\n",
        "print(Sensitivity_recall)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Bcon7_I5CRMC"
      },
      "outputs": [],
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt     \n",
        "\n",
        "ax= plt.subplot()\n",
        "sns.heatmap(cm, annot=True, fmt='g', ax=ax, cmap='viridis')  #annot=True to annotate cells, ftm='g' to disable scientific notation\n",
        "# labels, title and ticks\n",
        "ax.set_xlabel('Predicted labels');ax.set_ylabel('True labels'); \n",
        "ax.set_title('Confusion Matrix'); "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "hzTfcfK_CRMD"
      },
      "outputs": [],
      "source": [
        "from sklearn.metrics import roc_auc_score\n",
        "score = roc_auc_score(y_test, output)\n",
        "print(f\"ROC AUC: {score:.4f}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "OFhAD4TYCRMD"
      },
      "outputs": [],
      "source": [
        "score = roc_auc_score(y_test, output)\n",
        "print(f\"ROC AUC: {score:.4f}\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "FSgMUXn5CRME"
      },
      "outputs": [],
      "source": [
        "def get_n_roc_coordinates(y_real, y_proba, n = 50):\n",
        "    tpr_list = [0]\n",
        "    fpr_list = [0]\n",
        "    for i in range(n):\n",
        "        threshold = i/n\n",
        "\n",
        "        tpr_list.append(tpr)\n",
        "        fpr_list.append(fpr)\n",
        "    return tpr_list, fpr_list"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BFNZfYR8CRME"
      },
      "outputs": [],
      "source": [
        "import seaborn as sns\n",
        "import matplotlib.pyplot as plt\n",
        "def plot_roc_curve(tpr, fpr, scatter = True):\n",
        "    plt.figure(figsize = (5, 5))\n",
        "    if scatter:\n",
        "        sns.scatterplot(x = fpr, y = tpr)\n",
        "    sns.lineplot(x = fpr, y = tpr)\n",
        "    sns.lineplot(x = [0, 1], y = [0, 1], color = 'green')\n",
        "    plt.xlim(-0.05, 1.05)\n",
        "    plt.ylim(-0.05, 1.05)\n",
        "    plt.xlabel(\"False Positive Rate\")\n",
        "    plt.ylabel(\"True Positive Rate\")"
      ]
    }
  ],
  "metadata": {
    "accelerator": "GPU",
    "colab": {
      "machine_shape": "hm",
      "provenance": [],
      "include_colab_link": true
    },
    "gpuClass": "premium",
    "kernelspec": {
      "display_name": "Python 3.9.7 ('base')",
      "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": "3.9.7"
    },
    "vscode": {
      "interpreter": {
        "hash": "ad2bdc8ecc057115af97d19610ffacc2b4e99fae6737bb82f5d7fb13d2f2c186"
      }
    },
    "widgets": {
      "application/vnd.jupyter.widget-state+json": {
        "55ade72af027417f883124d2bd4fce1a": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_8e930930656d4e7dbd99e9850b181bd6",
              "IPY_MODEL_a839b52d44e141dbad9371c1756b2e37",
              "IPY_MODEL_32679099028344c7a070bd8e48b8ea1c"
            ],
            "layout": "IPY_MODEL_60dd581227224a2fb3cb4023330ea857"
          }
        },
        "8e930930656d4e7dbd99e9850b181bd6": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_49ee769927644a6098e3e45de6d4f5e3",
            "placeholder": "​",
            "style": "IPY_MODEL_7216b0bbaf964b6bbf50a9ee5cf044ba",
            "value": "Downloading: 100%"
          }
        },
        "a839b52d44e141dbad9371c1756b2e37": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_42c1ea776f0c4f9f85837fe55ca60a04",
            "max": 28,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_53ba823f487141e6843acb48acafe068",
            "value": 28
          }
        },
        "32679099028344c7a070bd8e48b8ea1c": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_cb04bb1e1456470bb70a5c78050a989c",
            "placeholder": "​",
            "style": "IPY_MODEL_b27dfce6ee8a4ce4ac36c134498e9637",
            "value": " 28.0/28.0 [00:00&lt;00:00, 1.09kB/s]"
          }
        },
        "60dd581227224a2fb3cb4023330ea857": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "49ee769927644a6098e3e45de6d4f5e3": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "7216b0bbaf964b6bbf50a9ee5cf044ba": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "42c1ea776f0c4f9f85837fe55ca60a04": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "53ba823f487141e6843acb48acafe068": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "cb04bb1e1456470bb70a5c78050a989c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "b27dfce6ee8a4ce4ac36c134498e9637": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "ba3c9a54404c41feae4056b80e835cd0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_636363e42ff648a38c2ac4aff27456b8",
              "IPY_MODEL_10ef9a28ea84447a9fd205b0e7aaacbf",
              "IPY_MODEL_e31953345f4b46778c6f23ae462bc805"
            ],
            "layout": "IPY_MODEL_64091a41997d4975af82528fe9405b04"
          }
        },
        "636363e42ff648a38c2ac4aff27456b8": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_2e91f3bffd29452a91a182d5a165af7e",
            "placeholder": "​",
            "style": "IPY_MODEL_8139cf75c78a49d2acb09261fa08d1a1",
            "value": "Downloading: 100%"
          }
        },
        "10ef9a28ea84447a9fd205b0e7aaacbf": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_a525ca370dfb4d61a52573688de3bf92",
            "max": 231508,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_c8d91a2228804f8cbcba8c51ffd8cfcc",
            "value": 231508
          }
        },
        "e31953345f4b46778c6f23ae462bc805": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_067196e0dd054eae82d22eed761e8c92",
            "placeholder": "​",
            "style": "IPY_MODEL_c2d6ea2b31c3430392b89b6cacecda93",
            "value": " 232k/232k [00:00&lt;00:00, 1.83MB/s]"
          }
        },
        "64091a41997d4975af82528fe9405b04": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "2e91f3bffd29452a91a182d5a165af7e": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "8139cf75c78a49d2acb09261fa08d1a1": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "a525ca370dfb4d61a52573688de3bf92": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "c8d91a2228804f8cbcba8c51ffd8cfcc": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "067196e0dd054eae82d22eed761e8c92": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "c2d6ea2b31c3430392b89b6cacecda93": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "a6e37356ebc44293acbbdc1032435e80": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_c655d444c55c4f27abc3a196ce19c376",
              "IPY_MODEL_81f3da10ab714896bdfca62d4aa87336",
              "IPY_MODEL_d7434ee19cf34bc3a6ff175e331b5fa0"
            ],
            "layout": "IPY_MODEL_a3bd92d925aa4ee9b4e75fd5cd0cb38f"
          }
        },
        "c655d444c55c4f27abc3a196ce19c376": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_3251f731e08a4d0f9a44de53f4a8f5ef",
            "placeholder": "​",
            "style": "IPY_MODEL_8b5bdce1bde24952af200b367aaa6c05",
            "value": "Downloading: 100%"
          }
        },
        "81f3da10ab714896bdfca62d4aa87336": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_251840ef040c467685ffc72fa620d733",
            "max": 466062,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_9d75c7c0cfc345a58e72205fc9d20d19",
            "value": 466062
          }
        },
        "d7434ee19cf34bc3a6ff175e331b5fa0": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_f697f525bcff48818a2cb78d3c81fc45",
            "placeholder": "​",
            "style": "IPY_MODEL_6d5efd5f3c2e4691bd1fda19cabd5859",
            "value": " 466k/466k [00:00&lt;00:00, 1.76MB/s]"
          }
        },
        "a3bd92d925aa4ee9b4e75fd5cd0cb38f": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "3251f731e08a4d0f9a44de53f4a8f5ef": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "8b5bdce1bde24952af200b367aaa6c05": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "251840ef040c467685ffc72fa620d733": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "9d75c7c0cfc345a58e72205fc9d20d19": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "f697f525bcff48818a2cb78d3c81fc45": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "6d5efd5f3c2e4691bd1fda19cabd5859": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "d7cc11f170944546bcaaf4e07e0dd6fd": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_d14b751589a542bd86851853e9b62bd4",
              "IPY_MODEL_5b0c99f747304d4696bced36e4bae9ce",
              "IPY_MODEL_a361236cd00a4396bd1ddfef4832ff94"
            ],
            "layout": "IPY_MODEL_65995febefe047c284c27288c7912f3b"
          }
        },
        "d14b751589a542bd86851853e9b62bd4": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_e2cc42b4aad14e53a78ddd3b0cd51280",
            "placeholder": "​",
            "style": "IPY_MODEL_9af962cd882b4f719dd6c796d4b04935",
            "value": "Downloading: 100%"
          }
        },
        "5b0c99f747304d4696bced36e4bae9ce": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_aed9071fa8b549dc9aa772cdff0316a0",
            "max": 483,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_909da137888541a299b09f1bfffe2f5f",
            "value": 483
          }
        },
        "a361236cd00a4396bd1ddfef4832ff94": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_6b4d10953a934b0990357485c1402d5b",
            "placeholder": "​",
            "style": "IPY_MODEL_2ae0e2c7db0540589cd2ca991c4d3b8b",
            "value": " 483/483 [00:00&lt;00:00, 19.7kB/s]"
          }
        },
        "65995febefe047c284c27288c7912f3b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "e2cc42b4aad14e53a78ddd3b0cd51280": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "9af962cd882b4f719dd6c796d4b04935": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "aed9071fa8b549dc9aa772cdff0316a0": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "909da137888541a299b09f1bfffe2f5f": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "6b4d10953a934b0990357485c1402d5b": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "2ae0e2c7db0540589cd2ca991c4d3b8b": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "f134ef77361c402d9642c79c71a36412": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HBoxModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HBoxModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HBoxView",
            "box_style": "",
            "children": [
              "IPY_MODEL_17e813b37ee04b50a2d953c0ebd6cc7d",
              "IPY_MODEL_71f60a7def0e4cab8148b1afaafb7fdb",
              "IPY_MODEL_01e501c4a6f242c6a6582912d47c2fbd"
            ],
            "layout": "IPY_MODEL_a4b010a250dc4b56bc7ac7c85500be9c"
          }
        },
        "17e813b37ee04b50a2d953c0ebd6cc7d": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_ebb189758cc14dab99b71c22e478caed",
            "placeholder": "​",
            "style": "IPY_MODEL_08080a3d559048fca696315a37916a41",
            "value": "Downloading: 100%"
          }
        },
        "71f60a7def0e4cab8148b1afaafb7fdb": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "FloatProgressModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "FloatProgressModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "ProgressView",
            "bar_style": "success",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_ca9f5c43e4f245a5bc63548b64281187",
            "max": 363423424,
            "min": 0,
            "orientation": "horizontal",
            "style": "IPY_MODEL_1ca6a17aa3cd4738b2344145c6250a03",
            "value": 363423424
          }
        },
        "01e501c4a6f242c6a6582912d47c2fbd": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "HTMLModel",
          "model_module_version": "1.5.0",
          "state": {
            "_dom_classes": [],
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "HTMLModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/controls",
            "_view_module_version": "1.5.0",
            "_view_name": "HTMLView",
            "description": "",
            "description_tooltip": null,
            "layout": "IPY_MODEL_4e1f10b840554cc4a13ef24696a30c23",
            "placeholder": "​",
            "style": "IPY_MODEL_e8f5cf19e520482eb3943cf4209718ba",
            "value": " 363M/363M [00:06&lt;00:00, 52.3MB/s]"
          }
        },
        "a4b010a250dc4b56bc7ac7c85500be9c": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "ebb189758cc14dab99b71c22e478caed": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "08080a3d559048fca696315a37916a41": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        },
        "ca9f5c43e4f245a5bc63548b64281187": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "1ca6a17aa3cd4738b2344145c6250a03": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "ProgressStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "ProgressStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "bar_color": null,
            "description_width": ""
          }
        },
        "4e1f10b840554cc4a13ef24696a30c23": {
          "model_module": "@jupyter-widgets/base",
          "model_name": "LayoutModel",
          "model_module_version": "1.2.0",
          "state": {
            "_model_module": "@jupyter-widgets/base",
            "_model_module_version": "1.2.0",
            "_model_name": "LayoutModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "LayoutView",
            "align_content": null,
            "align_items": null,
            "align_self": null,
            "border": null,
            "bottom": null,
            "display": null,
            "flex": null,
            "flex_flow": null,
            "grid_area": null,
            "grid_auto_columns": null,
            "grid_auto_flow": null,
            "grid_auto_rows": null,
            "grid_column": null,
            "grid_gap": null,
            "grid_row": null,
            "grid_template_areas": null,
            "grid_template_columns": null,
            "grid_template_rows": null,
            "height": null,
            "justify_content": null,
            "justify_items": null,
            "left": null,
            "margin": null,
            "max_height": null,
            "max_width": null,
            "min_height": null,
            "min_width": null,
            "object_fit": null,
            "object_position": null,
            "order": null,
            "overflow": null,
            "overflow_x": null,
            "overflow_y": null,
            "padding": null,
            "right": null,
            "top": null,
            "visibility": null,
            "width": null
          }
        },
        "e8f5cf19e520482eb3943cf4209718ba": {
          "model_module": "@jupyter-widgets/controls",
          "model_name": "DescriptionStyleModel",
          "model_module_version": "1.5.0",
          "state": {
            "_model_module": "@jupyter-widgets/controls",
            "_model_module_version": "1.5.0",
            "_model_name": "DescriptionStyleModel",
            "_view_count": null,
            "_view_module": "@jupyter-widgets/base",
            "_view_module_version": "1.2.0",
            "_view_name": "StyleView",
            "description_width": ""
          }
        }
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}