Named_Entity_Recognition_(NER).ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/PraveenLiyanage/Named-Entity-Recognition-NER/blob/main/Named_Entity_Recognition_(NER).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
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        },
        "id": "De5TyLgadGNJ",
        "outputId": "835fd607-e54c-427c-aadb-0278a39f3713"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
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            "Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit->simpletransformers) (2023.12.1)\n",
            "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit->simpletransformers) (0.32.1)\n",
            "Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit->simpletransformers) (0.17.1)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich<14,>=10.14.0->streamlit->simpletransformers) (0.1.2)\n",
            "Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /usr/local/lib/python3.10/dist-packages (from pyasn1-modules>=0.2.1->google-auth<3,>=1.6.3->tensorboard->simpletransformers) (0.5.1)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.10/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<2,>=0.5->tensorboard->simpletransformers) (3.2.2)\n",
            "Building wheels for collected packages: seqeval\n",
            "  Building wheel for seqeval (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for seqeval: filename=seqeval-1.2.2-py3-none-any.whl size=16162 sha256=ac37c1ba8caa50856d38dc961be96934310ab8d6214648aad86426e082b8ac58\n",
            "  Stored in directory: /root/.cache/pip/wheels/1a/67/4a/ad4082dd7dfc30f2abfe4d80a2ed5926a506eb8a972b4767fa\n",
            "Successfully built seqeval\n",
            "Installing collected packages: sentencepiece, watchdog, validators, tensorboardx, smmap, setproctitle, sentry-sdk, docker-pycreds, dill, pydeck, multiprocess, gitdb, seqeval, GitPython, wandb, datasets, streamlit, simpletransformers\n",
            "Successfully installed GitPython-3.1.41 datasets-2.16.1 dill-0.3.7 docker-pycreds-0.4.0 gitdb-4.0.11 multiprocess-0.70.15 pydeck-0.8.1b0 sentencepiece-0.1.99 sentry-sdk-1.39.2 seqeval-1.2.2 setproctitle-1.3.3 simpletransformers-0.64.5 smmap-5.0.1 streamlit-1.30.0 tensorboardx-2.6.2.2 validators-0.22.0 wandb-0.16.2 watchdog-3.0.0\n"
          ]
        }
      ],
      "source": [
        "!pip install simpletransformers"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "tuYruZdrdWa-"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "data = pd.read_csv(\"/content/drive/MyDrive/ner_dataset.csv\",encoding=\"latin1\" )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 979
        },
        "id": "h4bk-GLZeUB4",
        "outputId": "bbe6c032-cd90-403b-e5ed-d2a1eabe41cd"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "     Sentence #           Word  POS    Tag\n",
              "0   Sentence: 1      Thousands  NNS      O\n",
              "1           NaN             of   IN      O\n",
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              "6           NaN         London  NNP  B-geo\n",
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              "8           NaN        protest   VB      O\n",
              "9           NaN            the   DT      O\n",
              "10          NaN            war   NN      O\n",
              "11          NaN             in   IN      O\n",
              "12          NaN           Iraq  NNP  B-geo\n",
              "13          NaN            and   CC      O\n",
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              "15          NaN            the   DT      O\n",
              "16          NaN     withdrawal   NN      O\n",
              "17          NaN             of   IN      O\n",
              "18          NaN        British   JJ  B-gpe\n",
              "19          NaN         troops  NNS      O\n",
              "20          NaN           from   IN      O\n",
              "21          NaN           that   DT      O\n",
              "22          NaN        country   NN      O\n",
              "23          NaN              .    .      O\n",
              "24  Sentence: 2       Families  NNS      O\n",
              "25          NaN             of   IN      O\n",
              "26          NaN       soldiers  NNS      O\n",
              "27          NaN         killed  VBN      O\n",
              "28          NaN             in   IN      O\n",
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              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-d3efc50c-f220-42a4-9830-bfd1621613e6 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ],
      "source": [
        "data.head(30)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "55Q9YFZjeXaA"
      },
      "outputs": [],
      "source": [
        "data =data.fillna(method =\"ffill\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 979
        },
        "id": "Y6xyNOYmechn",
        "outputId": "1debeb43-70d3-4338-8789-5bd6dcd9be50"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     Sentence #           Word  POS    Tag\n",
              "0   Sentence: 1      Thousands  NNS      O\n",
              "1   Sentence: 1             of   IN      O\n",
              "2   Sentence: 1  demonstrators  NNS      O\n",
              "3   Sentence: 1           have  VBP      O\n",
              "4   Sentence: 1        marched  VBN      O\n",
              "5   Sentence: 1        through   IN      O\n",
              "6   Sentence: 1         London  NNP  B-geo\n",
              "7   Sentence: 1             to   TO      O\n",
              "8   Sentence: 1        protest   VB      O\n",
              "9   Sentence: 1            the   DT      O\n",
              "10  Sentence: 1            war   NN      O\n",
              "11  Sentence: 1             in   IN      O\n",
              "12  Sentence: 1           Iraq  NNP  B-geo\n",
              "13  Sentence: 1            and   CC      O\n",
              "14  Sentence: 1         demand   VB      O\n",
              "15  Sentence: 1            the   DT      O\n",
              "16  Sentence: 1     withdrawal   NN      O\n",
              "17  Sentence: 1             of   IN      O\n",
              "18  Sentence: 1        British   JJ  B-gpe\n",
              "19  Sentence: 1         troops  NNS      O\n",
              "20  Sentence: 1           from   IN      O\n",
              "21  Sentence: 1           that   DT      O\n",
              "22  Sentence: 1        country   NN      O\n",
              "23  Sentence: 1              .    .      O\n",
              "24  Sentence: 2       Families  NNS      O\n",
              "25  Sentence: 2             of   IN      O\n",
              "26  Sentence: 2       soldiers  NNS      O\n",
              "27  Sentence: 2         killed  VBN      O\n",
              "28  Sentence: 2             in   IN      O\n",
              "29  Sentence: 2            the   DT      O"
            ],
            "text/html": [
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              "      <th></th>\n",
              "      <th>Sentence #</th>\n",
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              "      <td>Sentence: 1</td>\n",
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              "      <td>demonstrators</td>\n",
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              "      <th>3</th>\n",
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              "      <th>7</th>\n",
              "      <td>Sentence: 1</td>\n",
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              "      <td>Sentence: 1</td>\n",
              "      <td>protest</td>\n",
              "      <td>VB</td>\n",
              "      <td>O</td>\n",
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              "      <th>9</th>\n",
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              "      <td>DT</td>\n",
              "      <td>O</td>\n",
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              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Sentence: 1</td>\n",
              "      <td>war</td>\n",
              "      <td>NN</td>\n",
              "      <td>O</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Sentence: 1</td>\n",
              "      <td>in</td>\n",
              "      <td>IN</td>\n",
              "      <td>O</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Sentence: 1</td>\n",
              "      <td>Iraq</td>\n",
              "      <td>NNP</td>\n",
              "      <td>B-geo</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Sentence: 1</td>\n",
              "      <td>and</td>\n",
              "      <td>CC</td>\n",
              "      <td>O</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Sentence: 1</td>\n",
              "      <td>demand</td>\n",
              "      <td>VB</td>\n",
              "      <td>O</td>\n",
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              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>Sentence: 1</td>\n",
              "      <td>the</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>Sentence: 1</td>\n",
              "      <td>withdrawal</td>\n",
              "      <td>NN</td>\n",
              "      <td>O</td>\n",
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              "      <th>17</th>\n",
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              "      <th>18</th>\n",
              "      <td>Sentence: 1</td>\n",
              "      <td>British</td>\n",
              "      <td>JJ</td>\n",
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              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>Sentence: 1</td>\n",
              "      <td>troops</td>\n",
              "      <td>NNS</td>\n",
              "      <td>O</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>Sentence: 1</td>\n",
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              "      <td>Sentence: 1</td>\n",
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              "      <td>O</td>\n",
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              "      <th>24</th>\n",
              "      <td>Sentence: 2</td>\n",
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              "      <th>27</th>\n",
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              "      <td>O</td>\n",
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              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
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              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "\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",
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              "\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",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      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-52d26f15-423b-4fb7-8188-f3bca7315535 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-52d26f15-423b-4fb7-8188-f3bca7315535');\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-63362bb4-02f3-41a4-8947-65e17c5f7eec\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-63362bb4-02f3-41a4-8947-65e17c5f7eec')\"\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",
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              "    </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",
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              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "    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-63362bb4-02f3-41a4-8947-65e17c5f7eec button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ],
      "source": [
        "data.head(30)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.preprocessing import LabelEncoder\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import accuracy_score"
      ],
      "metadata": {
        "id": "5thSp_mbvc2u"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BGOVB1KXeek7"
      },
      "outputs": [],
      "source": [
        "data[\"Sentence #\"] = LabelEncoder().fit_transform(data[\"Sentence #\"] )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 979
        },
        "id": "6qiTOmVAeuYZ",
        "outputId": "acf15dd1-c809-4da1-d334-24e1e1e82017"
      },
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          "data": {
            "text/plain": [
              "    Sentence #           Word  POS    Tag\n",
              "0            0      Thousands  NNS      O\n",
              "1            0             of   IN      O\n",
              "2            0  demonstrators  NNS      O\n",
              "3            0           have  VBP      O\n",
              "4            0        marched  VBN      O\n",
              "5            0        through   IN      O\n",
              "6            0         London  NNP  B-geo\n",
              "7            0             to   TO      O\n",
              "8            0        protest   VB      O\n",
              "9            0            the   DT      O\n",
              "10           0            war   NN      O\n",
              "11           0             in   IN      O\n",
              "12           0           Iraq  NNP  B-geo\n",
              "13           0            and   CC      O\n",
              "14           0         demand   VB      O\n",
              "15           0            the   DT      O\n",
              "16           0     withdrawal   NN      O\n",
              "17           0             of   IN      O\n",
              "18           0        British   JJ  B-gpe\n",
              "19           0         troops  NNS      O\n",
              "20           0           from   IN      O\n",
              "21           0           that   DT      O\n",
              "22           0        country   NN      O\n",
              "23           0              .    .      O\n",
              "24       11111       Families  NNS      O\n",
              "25       11111             of   IN      O\n",
              "26       11111       soldiers  NNS      O\n",
              "27       11111         killed  VBN      O\n",
              "28       11111             in   IN      O\n",
              "29       11111            the   DT      O"
            ],
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              "      <td>O</td>\n",
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              "      <th>20</th>\n",
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              "      <td>from</td>\n",
              "      <td>IN</td>\n",
              "      <td>O</td>\n",
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              "      <th>21</th>\n",
              "      <td>0</td>\n",
              "      <td>that</td>\n",
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              "      <td>O</td>\n",
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              "      <th>22</th>\n",
              "      <td>0</td>\n",
              "      <td>country</td>\n",
              "      <td>NN</td>\n",
              "      <td>O</td>\n",
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              "      <th>23</th>\n",
              "      <td>0</td>\n",
              "      <td>.</td>\n",
              "      <td>.</td>\n",
              "      <td>O</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>11111</td>\n",
              "      <td>Families</td>\n",
              "      <td>NNS</td>\n",
              "      <td>O</td>\n",
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              "      <th>25</th>\n",
              "      <td>11111</td>\n",
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              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
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              "\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "  @keyframes spin {\n",
              "    0% {\n",
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              "\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",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "\n",
              "    </div>\n",
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            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ],
      "source": [
        "data.head(30)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Po789ZWVexNY"
      },
      "outputs": [],
      "source": [
        "data.rename(columns={\"Sentence #\":\"sentence_id\",\"Word\":\"words\",\"Tag\":\"labels\"}, inplace =True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "eX1h3TtZe2m9"
      },
      "outputs": [],
      "source": [
        "data[\"labels\"] = data[\"labels\"].str.upper()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "cjhv72Oue6dM"
      },
      "outputs": [],
      "source": [
        "X= data[[\"sentence_id\",\"words\"]]\n",
        "Y =data[\"labels\"]"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "xl4RiiI5e85o"
      },
      "outputs": [],
      "source": [
        "x_train, x_test, y_train, y_test = train_test_split(X,Y, test_size =0.2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "T1iFWbxBe_HX"
      },
      "outputs": [],
      "source": [
        "#building up train data and test data\n",
        "train_data = pd.DataFrame({\"sentence_id\":x_train[\"sentence_id\"],\"words\":x_train[\"words\"],\"labels\":y_train})\n",
        "test_data = pd.DataFrame({\"sentence_id\":x_test[\"sentence_id\"],\"words\":x_test[\"words\"],\"labels\":y_test})"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 419
        },
        "id": "mNS6mrCOfC8Y",
        "outputId": "1ce98493-804b-4111-bcf3-027bbf2df38a"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        sentence_id    words labels\n",
              "754457        27216       in      O\n",
              "485476        13576     were      O\n",
              "744124        26697   having      O\n",
              "473887        12973   wanted      O\n",
              "813816        30222       's      O\n",
              "...             ...      ...    ...\n",
              "563696        17529    argue      O\n",
              "20456         47105  cellist      O\n",
              "519449        15286        ,      O\n",
              "746700        26822   United  B-GEO\n",
              "558346        17270      The      O\n",
              "\n",
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              "      <td>having</td>\n",
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              "      <td>O</td>\n",
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              "      <th>20456</th>\n",
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              "      <td>17270</td>\n",
              "      <td>The</td>\n",
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              "      buttonEl.style.display =\n",
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              "        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",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "\n",
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              "  @keyframes spin {\n",
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              "    60% {\n",
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              "      border-right-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "  }\n",
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              "\n",
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              "    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",
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              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
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              "        console.error('Error during call to suggestCharts:', error);\n",
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              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
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              "\n",
              "  <div id=\"id_6b4f18e8-f9e4-44b7-9461-90bd91221e46\">\n",
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              "      .colab-df-generate {\n",
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              "        fill: #1967D2;\n",
              "        height: 32px;\n",
              "        padding: 0 0 0 0;\n",
              "        width: 32px;\n",
              "      }\n",
              "\n",
              "      .colab-df-generate:hover {\n",
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              "        box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "      [theme=dark] .colab-df-generate {\n",
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              "      }\n",
              "\n",
              "      [theme=dark] .colab-df-generate:hover {\n",
              "        background-color: #434B5C;\n",
              "        box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "    </style>\n",
              "    <button class=\"colab-df-generate\" onclick=\"generateWithVariable('train_data')\"\n",
              "            title=\"Generate code using this dataframe.\"\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",
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              "        document.querySelector('#id_6b4f18e8-f9e4-44b7-9461-90bd91221e46 button.colab-df-generate');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      buttonEl.onclick = () => {\n",
              "        google.colab.notebook.generateWithVariable('train_data');\n",
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              "    </script>\n",
              "  </div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ],
      "source": [
        "train_data"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "OpCmMQlBfHGU"
      },
      "source": [
        "##**Train the model**"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jPjPpYelfE_v"
      },
      "outputs": [],
      "source": [
        "from simpletransformers.ner import NERModel,NERArgs"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "vEl-bkpVfNE4",
        "outputId": "59360994-3f29-4b0a-ec79-3d5dfd79ccbd"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['O',\n",
              " 'B-GEO',\n",
              " 'B-GPE',\n",
              " 'B-PER',\n",
              " 'I-GEO',\n",
              " 'B-ORG',\n",
              " 'I-ORG',\n",
              " 'B-TIM',\n",
              " 'B-ART',\n",
              " 'I-ART',\n",
              " 'I-PER',\n",
              " 'I-GPE',\n",
              " 'I-TIM',\n",
              " 'B-NAT',\n",
              " 'B-EVE',\n",
              " 'I-EVE',\n",
              " 'I-NAT']"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ],
      "source": [
        "label = data[\"labels\"].unique().tolist()\n",
        "label"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "o8snvgH_fShh"
      },
      "outputs": [],
      "source": [
        "args = NERArgs()\n",
        "args.num_train_epochs = 1\n",
        "args.learning_rate = 1e-4\n",
        "args.overwrite_output_dir =True\n",
        "args.train_batch_size = 32\n",
        "args.eval_batch_size = 32"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "k1c7NMBwfUz0",
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      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:88: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
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          "text": [
            "Some weights of BertForTokenClassification were not initialized from the model checkpoint at bert-base-cased and are newly initialized: ['classifier.bias', 'classifier.weight']\n",
            "You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"
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              "  0%|          | 0/3 [00:00<?, ?it/s]"
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            "/usr/local/lib/python3.10/dist-packages/torch/optim/lr_scheduler.py:136: UserWarning: Detected call of `lr_scheduler.step()` before `optimizer.step()`. In PyTorch 1.1.0 and later, you should call them in the opposite order: `optimizer.step()` before `lr_scheduler.step()`.  Failure to do this will result in PyTorch skipping the first value of the learning rate schedule. See more details at https://pytorch.org/docs/stable/optim.html#how-to-adjust-learning-rate\n",
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