KerasModel.ipynb

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      "source": [
        "# Importing libraries and modules\n",
        "import tensorflow as tf\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import matplotlib.pyplot as plt"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Read data in data frame\n",
        "df = pd.read_csv(\"sample_data/tweet_emotions.csv\")"
      ],
      "metadata": {
        "id": "nDv3rK-LodX_"
      },
      "execution_count": 9,
      "outputs": []
    },
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      "source": [
        "# Print data frame\n",
        "df.head(10)"
      ],
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              "     tweet_id   sentiment                                            content\n",
              "0  1956967341       empty  @tiffanylue i know  i was listenin to bad habi...\n",
              "1  1956967666     sadness  Layin n bed with a headache  ughhhh...waitin o...\n",
              "2  1956967696     sadness                Funeral ceremony...gloomy friday...\n",
              "3  1956967789  enthusiasm               wants to hang out with friends SOON!\n",
              "4  1956968416     neutral  @dannycastillo We want to trade with someone w...\n",
              "5  1956968477       worry  Re-pinging @ghostridah14: why didn't you go to...\n",
              "6  1956968487     sadness  I should be sleep, but im not! thinking about ...\n",
              "7  1956968636       worry               Hmmm. http://www.djhero.com/ is down\n",
              "8  1956969035     sadness            @charviray Charlene my love. I miss you\n",
              "9  1956969172     sadness         @kelcouch I'm sorry  at least it's Friday?"
            ],
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              "      <th>8</th>\n",
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              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 40000,\n  \"fields\": [\n    {\n      \"column\": \"tweet_id\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 118857896,\n        \"min\": 1693956175,\n        \"max\": 1966441171,\n        \"num_unique_values\": 40000,\n        \"samples\": [\n          1752414968,\n          1965295852,\n          1696219218\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"sentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 13,\n        \"samples\": [\n          \"relief\",\n          \"happiness\",\n          \"empty\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"content\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 39827,\n        \"samples\": [\n          \"the sun is shinning! im off out!!\",\n          \"wow i must have been tired. i fell asleep @ exactly the start of the 10pm news &amp; now up as if its 8am.\",\n          \"@knobzie their loss\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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          "metadata": {},
          "execution_count": 10
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      "source": [
        "df.drop('tweet_id', axis=1, inplace=True)\n",
        "df.head(10)"
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      "execution_count": 11,
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            "text/plain": [
              "    sentiment                                            content\n",
              "0       empty  @tiffanylue i know  i was listenin to bad habi...\n",
              "1     sadness  Layin n bed with a headache  ughhhh...waitin o...\n",
              "2     sadness                Funeral ceremony...gloomy friday...\n",
              "3  enthusiasm               wants to hang out with friends SOON!\n",
              "4     neutral  @dannycastillo We want to trade with someone w...\n",
              "5       worry  Re-pinging @ghostridah14: why didn't you go to...\n",
              "6     sadness  I should be sleep, but im not! thinking about ...\n",
              "7       worry               Hmmm. http://www.djhero.com/ is down\n",
              "8     sadness            @charviray Charlene my love. I miss you\n",
              "9     sadness         @kelcouch I'm sorry  at least it's Friday?"
            ],
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              "      <td>@charviray Charlene my love. I miss you</td>\n",
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              "      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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-0c671715-c891-446c-a8f7-abfdd8fd253b 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-0c671715-c891-446c-a8f7-abfdd8fd253b');\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",
              "\n",
              "\n",
              "<div id=\"df-cb436e06-c991-4dd0-b2d8-7f6322af86b8\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-cb436e06-c991-4dd0-b2d8-7f6322af86b8')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-cb436e06-c991-4dd0-b2d8-7f6322af86b8 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 40000,\n  \"fields\": [\n    {\n      \"column\": \"sentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 13,\n        \"samples\": [\n          \"relief\",\n          \"happiness\",\n          \"empty\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"content\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 39827,\n        \"samples\": [\n          \"the sun is shinning! im off out!!\",\n          \"wow i must have been tired. i fell asleep @ exactly the start of the 10pm news &amp; now up as if its 8am.\",\n          \"@knobzie their loss\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import re\n",
        "\n",
        "def text_cleaning(text):\n",
        "  text = re.sub(r'@[A-Za-z0-9]+', '', text)\n",
        "  text = re.sub(r'@[A-Za-zA-Z0-9]+', '', text)\n",
        "  text = re.sub(r'@[A-Za-z]+', '', text)\n",
        "  text = re.sub(r'@[-)]+', '', text)\n",
        "  text = re.sub(r'RT[\\s]+', '', text)\n",
        "  text = re.sub(r'https?\\/\\/\\S+', '', text)\n",
        "  text = re.sub(r'http?\\/\\/\\S+', '', text)\n",
        "  text = re.sub(r'&[a-z;]+', '', text)\n",
        "\n",
        "  return text"
      ],
      "metadata": {
        "id": "e9zpAAoDpPpB"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df['content'] = df['content'].apply(text_cleaning)\n",
        "df.head(10)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "id": "0tmts1MkrF_9",
        "outputId": "623d747c-3ebf-41dc-8cca-15b387818839"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "    sentiment                                            content\n",
              "0       empty   i know  i was listenin to bad habit earlier a...\n",
              "1     sadness  Layin n bed with a headache  ughhhh...waitin o...\n",
              "2     sadness                Funeral ceremony...gloomy friday...\n",
              "3  enthusiasm               wants to hang out with friends SOON!\n",
              "4     neutral   We want to trade with someone who has Houston...\n",
              "5       worry  Re-pinging : why didn't you go to prom? BC my ...\n",
              "6     sadness  I should be sleep, but im not! thinking about ...\n",
              "7       worry               Hmmm. http://www.djhero.com/ is down\n",
              "8     sadness                       Charlene my love. I miss you\n",
              "9     sadness                   I'm sorry  at least it's Friday?"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-d883873a-3c4f-4e9f-9c89-7b39dcdbf5b0\" 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>sentiment</th>\n",
              "      <th>content</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>empty</td>\n",
              "      <td>i know  i was listenin to bad habit earlier a...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>sadness</td>\n",
              "      <td>Layin n bed with a headache  ughhhh...waitin o...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>sadness</td>\n",
              "      <td>Funeral ceremony...gloomy friday...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>enthusiasm</td>\n",
              "      <td>wants to hang out with friends SOON!</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>neutral</td>\n",
              "      <td>We want to trade with someone who has Houston...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>worry</td>\n",
              "      <td>Re-pinging : why didn't you go to prom? BC my ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>sadness</td>\n",
              "      <td>I should be sleep, but im not! thinking about ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>worry</td>\n",
              "      <td>Hmmm. http://www.djhero.com/ is down</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>sadness</td>\n",
              "      <td>Charlene my love. I miss you</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>sadness</td>\n",
              "      <td>I'm sorry  at least it's Friday?</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-d883873a-3c4f-4e9f-9c89-7b39dcdbf5b0')\"\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 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\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",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\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-d883873a-3c4f-4e9f-9c89-7b39dcdbf5b0 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-d883873a-3c4f-4e9f-9c89-7b39dcdbf5b0');\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",
              "\n",
              "\n",
              "<div id=\"df-2b78f246-852c-4c4e-b70e-385969943f9b\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-2b78f246-852c-4c4e-b70e-385969943f9b')\"\n",
              "            title=\"Suggest charts\"\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",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-2b78f246-852c-4c4e-b70e-385969943f9b button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "df",
              "summary": "{\n  \"name\": \"df\",\n  \"rows\": 40000,\n  \"fields\": [\n    {\n      \"column\": \"sentiment\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 13,\n        \"samples\": [\n          \"relief\",\n          \"happiness\",\n          \"empty\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"content\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 39559,\n        \"samples\": [\n          \" road trip ftw  am playing with trains today so it's all good here\",\n          \"a band from Hawaii with a Sublime sound, so all you sublime haters can just move along  ? http://blip.fm/~5yy4n\",\n          \"Version 2 of our live, interactive Trans-Siberian ticket planner is launched: http://tinyurl.com/c5ljwm - its very cool\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.model_selection import train_test_split\n",
        "\n",
        "x_train, x_test, y_train, y_test = train_test_split(df['content'].values, df['sentiment'].values, test_size=0.30)"
      ],
      "metadata": {
        "id": "jXVSW5_C5mlq"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print('sentiment text: ', x_train[0])\n",
        "print('sentiment: ', y_train[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sfLTlqh65-_u",
        "outputId": "591d9a2a-8526-40c0-9687-d51aa48658df"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sentiment text:  My new design portfolio is finally online: http://www.designia.nl - Still needs some tweaking on the details but it's ok for now,\n",
            "sentiment:  relief\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from tensorflow.keras.preprocessing.text import Tokenizer\n",
        "from tensorflow.keras.preprocessing.sequence import pad_sequences\n",
        "\n",
        "max_vocab = 20000000\n",
        "tokenizer = Tokenizer(num_words=max_vocab)\n",
        "tokenizer.fit_on_texts(x_train)"
      ],
      "metadata": {
        "id": "Ore1wweNWNTK"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "wordidx = tokenizer.word_index\n",
        "V = len(wordidx)\n",
        "print('The size of datatset vocab is: ', V)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cGz-QciTYZbz",
        "outputId": "b23d8a23-713f-4085-f3d0-45b782e31753"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The size of datatset vocab is:  27373\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_seq = tokenizer.texts_to_sequences(x_train)\n",
        "test_seq = tokenizer.texts_to_sequences(x_test)\n",
        "print('Training sequence: ', train_seq[0])\n",
        "print('Testing sequence: ', test_seq[0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uB0oGzzjYwU3",
        "outputId": "19149011-44e7-4b66-d619-fc74cddead4b"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Training sequence:  [5, 72, 1081, 2355, 9, 237, 491, 36, 372, 7294, 1789, 82, 604, 70, 7295, 14, 3, 1790, 18, 40, 173, 11, 27]\n",
            "Testing sequence:  [205, 1, 254, 29, 3, 1038, 10366, 3267, 337, 21, 238, 1716, 2, 3, 389, 533, 18, 380, 37, 60, 2258, 160, 11, 13]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pad_train = pad_sequences(train_seq)\n",
        "T = pad_train.shape[1]\n",
        "print('The length of training sequence is: ', T)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4mAhEwpoZUZd",
        "outputId": "beece617-646b-4215-90e5-ffea1a073154"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The length of training sequence is:  33\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pad_test = pad_sequences(test_seq, maxlen=T)\n",
        "print('The length of testing sequence is: ', pad_test.shape[1])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WTVT6p74Zl3W",
        "outputId": "e7987cf3-df5b-447b-8bef-6702cee349aa"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The length of testing sequence is:  33\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from tensorflow.keras.layers import Input, Dense, Embedding, LSTM, GlobalMaxPooling1D\n",
        "from tensorflow.keras.models import Model\n",
        "\n",
        "D = 20\n",
        "M = 15\n",
        "\n",
        "i = Input (shape=(T, ))\n",
        "x = Embedding(V+1, D)(i)    # V+1 because the indexing of the words in vocab (V) start from 1 not 0\n",
        "x = LSTM(M, return_sequences=True)(x)\n",
        "x = GlobalMaxPooling1D()(x)\n",
        "x = Dense(32, activation='relu')(x)\n",
        "x = Dense(1, activation='sigmoid')(x)\n",
        "\n",
        "model = Model(i,x)\n",
        "\n",
        "# compiling the model\n",
        "model.compile(optimizer='adam',\n",
        "              loss='binary_crossentropy',\n",
        "              metrics=['accuracy'])"
      ],
      "metadata": {
        "id": "_d_AueJo7ftY"
      },
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# training the model\n",
        "r = model.fit(pad_train, y_train, validation_data=(pad_test, y_test), epochs=2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "1TpGlGp0WQF2",
        "outputId": "b217eb89-a83f-4c51-c8e7-2c7dc974c0a4"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/2\n"
          ]
        },
        {
          "output_type": "error",
          "ename": "UnimplementedError",
          "evalue": "Graph execution error:\n\nDetected at node binary_crossentropy/Cast defined at (most recent call last):\n  File \"/usr/lib/python3.10/runpy.py\", line 196, in _run_module_as_main\n\n  File \"/usr/lib/python3.10/runpy.py\", line 86, in _run_code\n\n  File \"/usr/local/lib/python3.10/dist-packages/colab_kernel_launcher.py\", line 37, in <module>\n\n  File \"/usr/local/lib/python3.10/dist-packages/traitlets/config/application.py\", line 992, in launch_instance\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/kernelapp.py\", line 619, in start\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/platform/asyncio.py\", line 195, in start\n\n  File \"/usr/lib/python3.10/asyncio/base_events.py\", line 603, in run_forever\n\n  File \"/usr/lib/python3.10/asyncio/base_events.py\", line 1909, in _run_once\n\n  File \"/usr/lib/python3.10/asyncio/events.py\", line 80, in _run\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/ioloop.py\", line 685, in <lambda>\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/ioloop.py\", line 738, in _run_callback\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/gen.py\", line 825, in inner\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/gen.py\", line 786, in run\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py\", line 361, in process_one\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/gen.py\", line 234, in wrapper\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py\", line 261, in dispatch_shell\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/gen.py\", line 234, in wrapper\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py\", line 539, in execute_request\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/gen.py\", line 234, in wrapper\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py\", line 302, in do_execute\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/zmqshell.py\", line 539, in run_cell\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 2975, in run_cell\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3030, in _run_cell\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/async_helpers.py\", line 78, in _pseudo_sync_runner\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3257, in run_cell_async\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3473, in run_ast_nodes\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3553, in run_code\n\n  File \"<ipython-input-23-b0dcd839454d>\", line 2, in <cell line: 2>\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/utils/traceback_utils.py\", line 65, in error_handler\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1807, in fit\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1401, in train_function\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1384, in step_function\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1373, in run_step\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1151, in train_step\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1209, in compute_loss\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/compile_utils.py\", line 277, in __call__\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/losses.py\", line 143, in __call__\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/losses.py\", line 270, in call\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/losses.py\", line 2521, in binary_crossentropy\n\nCast string to float is not supported\n\t [[{{node binary_crossentropy/Cast}}]] [Op:__inference_train_function_3189]",
          "traceback": [
            "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
            "\u001b[0;31mUnimplementedError\u001b[0m                        Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-23-b0dcd839454d>\u001b[0m in \u001b[0;36m<cell line: 2>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m# training the model\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m \u001b[0mr\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpad_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_train\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalidation_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpad_test\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my_test\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mepochs\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/keras/src/utils/traceback_utils.py\u001b[0m in \u001b[0;36merror_handler\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     68\u001b[0m             \u001b[0;31m# To get the full stack trace, call:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     69\u001b[0m             \u001b[0;31m# `tf.debugging.disable_traceback_filtering()`\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 70\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mwith_traceback\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfiltered_tb\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mfrom\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     71\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     72\u001b[0m             \u001b[0;32mdel\u001b[0m \u001b[0mfiltered_tb\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/tensorflow/python/eager/execute.py\u001b[0m in \u001b[0;36mquick_execute\u001b[0;34m(op_name, num_outputs, inputs, attrs, ctx, name)\u001b[0m\n\u001b[1;32m     51\u001b[0m   \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     52\u001b[0m     \u001b[0mctx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mensure_initialized\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 53\u001b[0;31m     tensors = pywrap_tfe.TFE_Py_Execute(ctx._handle, device_name, op_name,\n\u001b[0m\u001b[1;32m     54\u001b[0m                                         inputs, attrs, num_outputs)\n\u001b[1;32m     55\u001b[0m   \u001b[0;32mexcept\u001b[0m \u001b[0mcore\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_NotOkStatusException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mUnimplementedError\u001b[0m: Graph execution error:\n\nDetected at node binary_crossentropy/Cast defined at (most recent call last):\n  File \"/usr/lib/python3.10/runpy.py\", line 196, in _run_module_as_main\n\n  File \"/usr/lib/python3.10/runpy.py\", line 86, in _run_code\n\n  File \"/usr/local/lib/python3.10/dist-packages/colab_kernel_launcher.py\", line 37, in <module>\n\n  File \"/usr/local/lib/python3.10/dist-packages/traitlets/config/application.py\", line 992, in launch_instance\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/kernelapp.py\", line 619, in start\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/platform/asyncio.py\", line 195, in start\n\n  File \"/usr/lib/python3.10/asyncio/base_events.py\", line 603, in run_forever\n\n  File \"/usr/lib/python3.10/asyncio/base_events.py\", line 1909, in _run_once\n\n  File \"/usr/lib/python3.10/asyncio/events.py\", line 80, in _run\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/ioloop.py\", line 685, in <lambda>\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/ioloop.py\", line 738, in _run_callback\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/gen.py\", line 825, in inner\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/gen.py\", line 786, in run\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py\", line 361, in process_one\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/gen.py\", line 234, in wrapper\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py\", line 261, in dispatch_shell\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/gen.py\", line 234, in wrapper\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/kernelbase.py\", line 539, in execute_request\n\n  File \"/usr/local/lib/python3.10/dist-packages/tornado/gen.py\", line 234, in wrapper\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/ipkernel.py\", line 302, in do_execute\n\n  File \"/usr/local/lib/python3.10/dist-packages/ipykernel/zmqshell.py\", line 539, in run_cell\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 2975, in run_cell\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3030, in _run_cell\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/async_helpers.py\", line 78, in _pseudo_sync_runner\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3257, in run_cell_async\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3473, in run_ast_nodes\n\n  File \"/usr/local/lib/python3.10/dist-packages/IPython/core/interactiveshell.py\", line 3553, in run_code\n\n  File \"<ipython-input-23-b0dcd839454d>\", line 2, in <cell line: 2>\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/utils/traceback_utils.py\", line 65, in error_handler\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1807, in fit\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1401, in train_function\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1384, in step_function\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1373, in run_step\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1151, in train_step\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/training.py\", line 1209, in compute_loss\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/engine/compile_utils.py\", line 277, in __call__\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/losses.py\", line 143, in __call__\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/losses.py\", line 270, in call\n\n  File \"/usr/local/lib/python3.10/dist-packages/keras/src/losses.py\", line 2521, in binary_crossentropy\n\nCast string to float is not supported\n\t [[{{node binary_crossentropy/Cast}}]] [Op:__inference_train_function_3189]"
          ]
        }
      ]
    }
  ]
}