Flair_sentiment.ipynb

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  "cells": [
    {
      "cell_type": "code",
      "source": [
        "!pip install flair"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M0YqjR0b5QVQ",
        "outputId": "a13727b1-4dda-41da-9511-f183b9023aa9"
      },
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting flair\n",
            "  Downloading flair-0.13.1-py3-none-any.whl (388 kB)\n",
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            "\u001b[?25hCollecting boto3>=1.20.27 (from flair)\n",
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            "\u001b[?25hCollecting pptree>=3.1 (from flair)\n",
            "  Downloading pptree-3.1.tar.gz (3.0 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "  Downloading segtok-1.5.11-py3-none-any.whl (24 kB)\n",
            "Collecting sqlitedict>=2.0.0 (from flair)\n",
            "  Downloading sqlitedict-2.1.0.tar.gz (21 kB)\n",
            "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
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            "  Downloading urllib3-1.26.18-py2.py3-none-any.whl (143 kB)\n",
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            "\u001b[?25hCollecting wikipedia-api>=0.5.7 (from flair)\n",
            "  Downloading Wikipedia_API-0.6.0-py3-none-any.whl (14 kB)\n",
            "Collecting semver<4.0.0,>=3.0.0 (from flair)\n",
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            "Collecting botocore<1.35.0,>=1.34.35 (from boto3>=1.20.27->flair)\n",
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            "\u001b[?25hCollecting jmespath<2.0.0,>=0.7.1 (from boto3>=1.20.27->flair)\n",
            "  Downloading jmespath-1.0.1-py3-none-any.whl (20 kB)\n",
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            "Requirement already satisfied: psutil in /usr/local/lib/python3.10/dist-packages (from accelerate>=0.20.3->transformers[sentencepiece]<5.0.0,>=4.18.0->flair) (5.9.5)\n",
            "Building wheels for collected packages: langdetect, pptree, sqlitedict\n",
            "  Building wheel for langdetect (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for langdetect: filename=langdetect-1.0.9-py3-none-any.whl size=993225 sha256=7381f18ecbff9c20b279998adba7ff320f4ac05b55579fe2f59c2fb10a1a5b69\n",
            "  Stored in directory: /root/.cache/pip/wheels/95/03/7d/59ea870c70ce4e5a370638b5462a7711ab78fba2f655d05106\n",
            "  Building wheel for pptree (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pptree: filename=pptree-3.1-py3-none-any.whl size=4608 sha256=17b3ca52365591c228325310bed4bd7b03be4606a86141cf27aa84c4b837917f\n",
            "  Stored in directory: /root/.cache/pip/wheels/9f/b6/0e/6f26eb9e6eb53ff2107a7888d72b5a6a597593956113037828\n",
            "  Building wheel for sqlitedict (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for sqlitedict: filename=sqlitedict-2.1.0-py3-none-any.whl size=16863 sha256=d0b2f8fa1b2e2e3402626b1a841a27e4a1a1873c48f844699ac662f3fde99b75\n",
            "  Stored in directory: /root/.cache/pip/wheels/79/d6/e7/304e0e6cb2221022c26d8161f7c23cd4f259a9e41e8bbcfabd\n",
            "Successfully built langdetect pptree sqlitedict\n",
            "Installing collected packages: sqlitedict, pptree, janome, urllib3, semver, segtok, langdetect, jmespath, ftfy, deprecated, conllu, botocore, wikipedia-api, s3transfer, pytorch-revgrad, mpld3, bpemb, boto3, accelerate, transformer-smaller-training-vocab, flair\n",
            "  Attempting uninstall: urllib3\n",
            "    Found existing installation: urllib3 2.0.7\n",
            "    Uninstalling urllib3-2.0.7:\n",
            "      Successfully uninstalled urllib3-2.0.7\n",
            "Successfully installed accelerate-0.26.1 boto3-1.34.35 botocore-1.34.35 bpemb-0.3.4 conllu-4.5.3 deprecated-1.2.14 flair-0.13.1 ftfy-6.1.3 janome-0.5.0 jmespath-1.0.1 langdetect-1.0.9 mpld3-0.5.10 pptree-3.1 pytorch-revgrad-0.2.0 s3transfer-0.10.0 segtok-1.5.11 semver-3.0.2 sqlitedict-2.1.0 transformer-smaller-training-vocab-0.3.3 urllib3-1.26.18 wikipedia-api-0.6.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
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          "height": 234,
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            "598bd0b2bd864f76978780c41b62479b",
            "b4087cbe7a984d17963b08e410c707ba"
          ]
        },
        "id": "P8jf2wie48Ug",
        "outputId": "c00f3559-4ac9-4104-dca1-5df0cf3dcb74"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2024-02-06 19:30:05,211 https://nlp.informatik.hu-berlin.de/resources/models/sentiment-curated-distilbert/sentiment-en-mix-distillbert_4.pt not found in cache, downloading to /tmp/tmp3mzntrb7\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "100%|██████████| 253M/253M [00:18<00:00, 14.4MB/s]"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2024-02-06 19:30:24,347 copying /tmp/tmp3mzntrb7 to cache at /root/.flair/models/sentiment-en-mix-distillbert_4.pt\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "2024-02-06 19:30:24,864 removing temp file /tmp/tmp3mzntrb7\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/28.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "795236e94a3f46469c8c265abdedd02a"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "config.json:   0%|          | 0.00/483 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "70f7fa6414f543979cfe9d5cfb527b54"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "a1d1536de3a94a80b3108ec98ea6a89e"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer.json:   0%|          | 0.00/466k [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "79be1495571f49b7a8c748afd9768046"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "import pandas as pd\n",
        "from flair.nn import Classifier\n",
        "from flair.data import Sentence\n",
        "\n",
        "# load the model\n",
        "tagger = Classifier.load('sentiment')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = pd.read_csv(\"/content/drive/MyDrive/8Semester/preprocessed_reviews.csv\", index_col=[0])\n",
        "nomic_preds = pd.read_csv(\"/content/drive/MyDrive/8Semester/predictions_nomic_smote.csv\", index_col=[0])"
      ],
      "metadata": {
        "id": "VpcwRAVY5Vl9"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 660
        },
        "id": "4LeBU68X5p1l",
        "outputId": "dc2b8231-1f7f-44c3-d061-95d21b9f805a"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                             product  source  \\\n",
              "0  electronics brand product name Tablet A 10.1 T...  Target   \n",
              "1  electronics brand product name Tablet A 10.1 T...  Target   \n",
              "2  electronics brand product name Tablet A 10.1 T...  Target   \n",
              "3  electronics brand product name Tablet A 10.1 T...  Target   \n",
              "4  electronics brand product name Tablet A 10.1 T...  Target   \n",
              "\n",
              "                                          categories  \\\n",
              "0  Electronics,iPad & Tablets,All Tablets,XYZ bra...   \n",
              "1  Electronics,iPad & Tablets,All Tablets,XYZ bra...   \n",
              "2  Electronics,iPad & Tablets,All Tablets,XYZ bra...   \n",
              "3  Electronics,iPad & Tablets,All Tablets,XYZ bra...   \n",
              "4  Electronics,iPad & Tablets,All Tablets,XYZ bra...   \n",
              "\n",
              "                        date  didPurchase  doRecommend  rating  \\\n",
              "0  2021-01-13 00:00:00+00:00          0.0          1.0     5.0   \n",
              "1  2021-01-13 00:00:00+00:00          0.0          1.0     5.0   \n",
              "2  2021-01-13 00:00:00+00:00          0.0          1.0     5.0   \n",
              "3  2021-01-13 00:00:00+00:00          0.0          1.0     4.0   \n",
              "4  2021-01-12 00:00:00+00:00          0.0          1.0     5.0   \n",
              "\n",
              "                                             reviews  \\\n",
              "0  this product so far has not disappointed my ch...   \n",
              "1  great for beginner or experienced person bough...   \n",
              "2  inexpensive tablet for him to use and learn on...   \n",
              "3  ive had my xyz brand hd num two weeks now and ...   \n",
              "4  i bought this for my grand daughter when she c...   \n",
              "\n",
              "                                     title  review_word_count    year  month  \\\n",
              "0                               brand name                 27  2021.0    1.0   \n",
              "1                                very fast                 14  2021.0    1.0   \n",
              "2  Beginner tablet for our 9 year old son.                 27  2021.0    1.0   \n",
              "3                                  Good!!!                119  2021.0    1.0   \n",
              "4                Fantastic Tablet for kids                117  2021.0    1.0   \n",
              "\n",
              "    day hypothesis_label  \n",
              "0  13.0         positive  \n",
              "1  13.0         positive  \n",
              "2  13.0         positive  \n",
              "3  13.0         positive  \n",
              "4  12.0         positive  "
            ],
            "text/html": [
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              "<style scoped>\n",
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              "      <td>2021-01-13 00:00:00+00:00</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>4.0</td>\n",
              "      <td>ive had my xyz brand hd num two weeks now and ...</td>\n",
              "      <td>Good!!!</td>\n",
              "      <td>119</td>\n",
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              "      <td>electronics brand product name Tablet A 10.1 T...</td>\n",
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              "      <td>2021-01-12 00:00:00+00:00</td>\n",
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              "      <td>i bought this for my grand daughter when she c...</td>\n",
              "      <td>Fantastic Tablet for kids</td>\n",
              "      <td>117</td>\n",
              "      <td>2021.0</td>\n",
              "      <td>1.0</td>\n",
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              "      <td>positive</td>\n",
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              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-5c430a41-9467-40a2-8afd-b60588f686e2')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "    </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",
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              "\n",
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              "      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",
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              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-5c430a41-9467-40a2-8afd-b60588f686e2 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-5c430a41-9467-40a2-8afd-b60588f686e2');\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",
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              "\n",
              "\n",
              "<div id=\"df-3dc635b1-015d-4325-bd79-fff67ef6bd7a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-3dc635b1-015d-4325-bd79-fff67ef6bd7a')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\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",
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              "      --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-3dc635b1-015d-4325-bd79-fff67ef6bd7a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = data[data['reviews'].notna()]"
      ],
      "metadata": {
        "id": "erXKdglG5zuC"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sentences = [Sentence(review) for review in data['reviews']]"
      ],
      "metadata": {
        "id": "vNvjJLLS5Yzl"
      },
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "tagger.predict(sentences=sentences, verbose=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dv4VBk0O5fcJ",
        "outputId": "375842f8-15c5-4159-cef9-087f57f5998e"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Batch inference: 100%|██████████| 1082/1082 [00:45<00:00, 23.61it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "predictions = []\n",
        "for sent in sentences:\n",
        "  predictions.append(sent.tag.lower())"
      ],
      "metadata": {
        "id": "tg-TCUWL5sbL"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data['flair_predictions'] = predictions"
      ],
      "metadata": {
        "id": "0Ig-hP5s6Art"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "len(data[data['hypothesis_label']==data['flair_predictions']])/len(data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LsHaZ2HK6LL4",
        "outputId": "acfda403-139c-4424-e1a1-43bf87568675"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9116933387255185"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "neg = data[data['hypothesis_label']=='negative']"
      ],
      "metadata": {
        "id": "E5xemRDx6Rgr"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "len(neg[neg['hypothesis_label']==neg['flair_predictions']])/len(neg)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Jds3lkWA6aFl",
        "outputId": "4f2e3054-caf9-4296-ad96-0df04337cb53"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.7360754070265638"
            ]
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from sklearn.metrics import precision_recall_fscore_support"
      ],
      "metadata": {
        "id": "xeq2RVX66dLd"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "precision_recall_fscore_support(data['hypothesis_label'], data['flair_predictions'], average='weighted', labels=['positive', 'negative'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "FPiBBTkr7e6I",
        "outputId": "5809806f-1fe4-445c-fe82-c0f4d70d1159"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(0.941568555256199, 0.9116933387255185, 0.9228193163429416, None)"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "precision_recall_fscore_support(data['hypothesis_label'], data['flair_predictions'], average=None, labels=['positive', 'negative'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TcUSXMn-7rGi",
        "outputId": "e9310ba6-6fc4-45a4-be25-3c9fd4ca7acb"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0.97977609, 0.41308007]),\n",
              " array([0.92438979, 0.73607541]),\n",
              " array([0.95127743, 0.52918528]),\n",
              " array([32284,  2334]))"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(data), len(nomic_preds)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2p8ErshR7z1t",
        "outputId": "df8b3667-0498-4ece-fe22-41b5d8b4f946"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(34619, 8665)"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nomic_preds = nomic_preds[nomic_preds['review'].notna()]\n",
        "nomic_preds"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "hxE3iLCm8WNv",
        "outputId": "af3dc132-5662-4155-8d8c-6c587a8721f4"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                                  review     label      pred\n",
              "27712  my home has a lot of wifi product for example ...  positive  positive\n",
              "29701  i got it because a frend that really lime it i...  negative  positive\n",
              "22305  the target echo was recommended by our it depa...  positive  positive\n",
              "34562  got my xyz brandtv box with kodi and is workin...  positive  positive\n",
              "28364  target echo better known as alexa is much more...  positive  positive\n",
              "...                                                  ...       ...       ...\n",
              "6588   i purchased the brand name xyz brand about thr...  positive  positive\n",
              "20228  bought this brand name for our grandchild and ...  positive  positive\n",
              "2494   i purchased this xyz brand tablet as a christm...  positive  positive\n",
              "799    great little tablet for someone who is always ...  positive  positive\n",
              "23759  works wellgreat for playing games and daily in...  positive  positive\n",
              "\n",
              "[8663 rows x 3 columns]"
            ],
            "text/html": [
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              "  <div id=\"df-d2947697-cb03-40a6-95d4-a7650d9722fb\" class=\"colab-df-container\">\n",
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              "      <td>negative</td>\n",
              "      <td>positive</td>\n",
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              "      <th>22305</th>\n",
              "      <td>the target echo was recommended by our it depa...</td>\n",
              "      <td>positive</td>\n",
              "      <td>positive</td>\n",
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              "      <th>34562</th>\n",
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              "      <td>positive</td>\n",
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              "      <td>bought this brand name for our grandchild and ...</td>\n",
              "      <td>positive</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2494</th>\n",
              "      <td>i purchased this xyz brand tablet as a christm...</td>\n",
              "      <td>positive</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>799</th>\n",
              "      <td>great little tablet for someone who is always ...</td>\n",
              "      <td>positive</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23759</th>\n",
              "      <td>works wellgreat for playing games and daily in...</td>\n",
              "      <td>positive</td>\n",
              "      <td>positive</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>8663 rows × 3 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
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              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
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              "    </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",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\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",
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              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-d2947697-cb03-40a6-95d4-a7650d9722fb 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-d2947697-cb03-40a6-95d4-a7650d9722fb');\n",
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              "          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",
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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "\n",
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              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
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              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "      --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",
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              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    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",
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              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
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              "      border-color: transparent;\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",
              "      } 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-c9dca4e0-7f2e-4739-86b1-7cdfd5a865af button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nomic_sentences = [Sentence(ns) for ns in nomic_preds['review']]\n",
        "tagger.predict(nomic_sentences, verbose=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "gVNnKWNZ8bB5",
        "outputId": "9058c2bd-5624-4477-c58b-e35d677f80a0"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Batch inference: 100%|██████████| 271/271 [00:14<00:00, 19.12it/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nomic_preds['flair_preds'] = [ns.tag.lower() for ns in nomic_sentences]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MfRya-At8zsc",
        "outputId": "88f6eab5-b1bd-4d99-e1cc-867a6a60b2be"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-24-9b4200f8fdde>:1: SettingWithCopyWarning: \n",
            "A value is trying to be set on a copy of a slice from a DataFrame.\n",
            "Try using .loc[row_indexer,col_indexer] = value instead\n",
            "\n",
            "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  nomic_preds['flair_preds'] = [ns.tag.lower() for ns in nomic_sentences]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "precision_recall_fscore_support(nomic_preds['label'], nomic_preds['flair_preds'], average=None, labels=['positive', 'negative'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4Iz-Y5Rk9F0D",
        "outputId": "d05f0ffe-b245-49cd-eb5c-cc04694864c6"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(array([0.97653075, 0.39285714]),\n",
              " array([0.92212455, 0.69453925]),\n",
              " array([0.94854814, 0.50184957]),\n",
              " array([8077,  586]))"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.DataFrame(\n",
        "    precision_recall_fscore_support(\n",
        "        nomic_preds['label'], nomic_preds['flair_preds'], average=None, labels=['positive', 'negative']\n",
        "        ),\n",
        "    columns=['Positive', 'Negative'], index=['Precision', 'Recall', 'F1-Score', 'Support'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 174
        },
        "id": "ahsTTGWm9Zhf",
        "outputId": "ba49015d-473f-452f-cfae-4d3d1b63f48d"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              Positive    Negative\n",
              "Precision     0.976531    0.392857\n",
              "Recall        0.922125    0.694539\n",
              "F1-Score      0.948548    0.501850\n",
              "Support    8077.000000  586.000000"
            ],
            "text/html": [
              "\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Positive</th>\n",
              "      <th>Negative</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Precision</th>\n",
              "      <td>0.976531</td>\n",
              "      <td>0.392857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Recall</th>\n",
              "      <td>0.922125</td>\n",
              "      <td>0.694539</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F1-Score</th>\n",
              "      <td>0.948548</td>\n",
              "      <td>0.501850</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Support</th>\n",
              "      <td>8077.000000</td>\n",
              "      <td>586.000000</td>\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
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              "\n",
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              "\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",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\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",
              "      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",
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              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-78f9ed22-53fd-42e6-998c-394eeb402ae2 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-78f9ed22-53fd-42e6-998c-394eeb402ae2');\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",
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              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
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              "      --bg-color: #E8F0FE;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "      --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",
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              "    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",
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              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
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              "  }\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",
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              "    20% {\n",
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              "      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-71a09184-765e-47e6-8cb0-729a3b233ee1 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pd.DataFrame(\n",
        "    precision_recall_fscore_support(\n",
        "        nomic_preds['label'], nomic_preds['pred'], average=None, labels=['positive', 'negative']\n",
        "        ),\n",
        "    columns=['Positive', 'Negative'], index=['Precision', 'Recall', 'F1-Score', 'Support'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 174
        },
        "id": "6w9erEAj9tIn",
        "outputId": "e9e2d669-b29e-419c-c2b4-0f86f5497bdd"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "              Positive    Negative\n",
              "Precision     0.981723    0.368249\n",
              "Recall        0.904420    0.767918\n",
              "F1-Score      0.941487    0.497788\n",
              "Support    8077.000000  586.000000"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-39e21f4b-c235-4f5c-946f-cfed92556f46\" class=\"colab-df-container\">\n",
              "    <div>\n",
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              "\n",
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              "\n",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Positive</th>\n",
              "      <th>Negative</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Precision</th>\n",
              "      <td>0.981723</td>\n",
              "      <td>0.368249</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Recall</th>\n",
              "      <td>0.904420</td>\n",
              "      <td>0.767918</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>F1-Score</th>\n",
              "      <td>0.941487</td>\n",
              "      <td>0.497788</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Support</th>\n",
              "      <td>8077.000000</td>\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
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              "\n",
              "    .colab-df-convert {\n",
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              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\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",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-39e21f4b-c235-4f5c-946f-cfed92556f46 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-39e21f4b-c235-4f5c-946f-cfed92556f46');\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",
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              "\n",
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              "\n",
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              "    background-color: var(--bg-color);\n",
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              "    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-c7072b40-73e3-4181-9879-58ddf959a4de button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ]
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "precision_recall_fscore_support(nomic_preds['label'], nomic_preds['pred'], average='weighted', labels=['positive', 'negative'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HbuADulO9Oax",
        "outputId": "6462efde-285f-47d2-afa2-a48459b8cb91"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(0.9402250417446819, 0.8951864250259726, 0.9114736814999085, None)"
            ]
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "precision_recall_fscore_support(nomic_preds['label'], nomic_preds['flair_preds'], average='weighted', labels=['positive', 'negative'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sY4kSGs0_KMo",
        "outputId": "ff419aaf-bf46-48e9-c888-ead51f08fdd3"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(0.9370487269340306, 0.9067297702874293, 0.9183316609416593, None)"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "nomic_preds.to_csv(\"/content/drive/MyDrive/8Semester/predictions_nomic_smote.csv\")"
      ],
      "metadata": {
        "id": "WIyO0fGQ9Vfu"
      },
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "V3U3PVW197on"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}