Great_Notebook.ipynb

{
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      "cell_type": "code",
      "execution_count": 1,
      "id": "976b6e34",
      "metadata": {
        "id": "976b6e34"
      },
      "outputs": [],
      "source": [
        "import pandas as pd"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "GkkuClDVeryA",
        "outputId": "cb0f0e08-368f-4346-ed25-c18138c96edb"
      },
      "id": "GkkuClDVeryA",
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "id": "0f20674e",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 289
        },
        "id": "0f20674e",
        "outputId": "97f1010a-b42b-4287-9f05-93998571c814"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "<ipython-input-3-edb31e30d49e>:1: DtypeWarning: Columns (14,22,24) have mixed types. Specify dtype option on import or set low_memory=False.\n",
            "  df = pd.read_csv(\"drive/MyDrive/Practicum/pharmacy_claims.csv.gz\")\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "(2570133, 48)\n"
          ]
        },
        {
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              "  </style>\n",
              "\n",
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              "        document.querySelector('#df-fa1be8a5-4bb6-43d1-a1b9-edb78157fa66 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
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              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-fa1be8a5-4bb6-43d1-a1b9-edb78157fa66');\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",
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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",
              "      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",
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            ]
          },
          "metadata": {},
          "execution_count": 3
        }
      ],
      "source": [
        "df = pd.read_csv(\"drive/MyDrive/Practicum/pharmacy_claims.csv.gz\")\n",
        "print(df.shape)\n",
        "df.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "id": "fa020892",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "fa020892",
        "outputId": "feb15274-765c-4ed4-e926-c6a0d4fc4666"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                       Field  \\\n",
              "0             Member Life ID   \n",
              "1               Group Number   \n",
              "2                    Section   \n",
              "3                 Department   \n",
              "4  Package Code / Class Code   \n",
              "\n",
              "                                          Definition  \n",
              "0                                  Unique Identifier  \n",
              "1  The groups are defined based on the account's ...  \n",
              "2  The groups are defined based on the account's ...  \n",
              "3  The groups are defined based on the account's ...  \n",
              "4  The groups are defined based on the account's ...  "
            ],
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              "      <th>0</th>\n",
              "      <td>Member Life ID</td>\n",
              "      <td>Unique Identifier</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Group Number</td>\n",
              "      <td>The groups are defined based on the account's ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Section</td>\n",
              "      <td>The groups are defined based on the account's ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Department</td>\n",
              "      <td>The groups are defined based on the account's ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Package Code / Class Code</td>\n",
              "      <td>The groups are defined based on the account's ...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-30fb8818-210e-4374-ae5c-08c2d1fb1030')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-30fb8818-210e-4374-ae5c-08c2d1fb1030 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-30fb8818-210e-4374-ae5c-08c2d1fb1030');\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-fad52791-7bf3-42d2-a738-1a93a155be98\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-fad52791-7bf3-42d2-a738-1a93a155be98')\"\n",
              "            title=\"Suggest charts.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-fad52791-7bf3-42d2-a738-1a93a155be98 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
        }
      ],
      "source": [
        "data_dict = pd.read_excel('drive/MyDrive/Practicum/Data Dictionary Pharmacy Claims.xlsx', skiprows=1)\n",
        "data_dict.head()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "id": "97847524",
      "metadata": {
        "id": "97847524"
      },
      "outputs": [],
      "source": [
        "col_names = data_dict['Field'].apply(lambda x: (x.lower().split(\"/\")[0].split(\"(\")[0].strip().replace(\" \", \"_\"))).tolist()\n",
        "df.columns = col_names"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "id": "d7d58ab6",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d7d58ab6",
        "outputId": "26ee7ce8-5af1-4bc6-ce3b-95b7ffd8033d"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(1512707, 48)"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "df = df[df['member_life_id']!=-1]\n",
        "df.shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "id": "b8c47ae3",
      "metadata": {
        "id": "b8c47ae3"
      },
      "outputs": [],
      "source": [
        "df = df[df[\"subgroup\"]!='001901088MD3000008K6GW']"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "id": "17d2304a",
      "metadata": {
        "id": "17d2304a"
      },
      "outputs": [],
      "source": [
        "cols_to_gen = [\n",
        "    'member_life_id', 'birth_date', 'gender_code',\n",
        "    'subscriber_zip', 'claim_number', 'prescription_number',\n",
        "    'ndc', 'drug_name', 'specialty_drug_indicator', 'generic_indicator',\n",
        "    'drug_tier', 'fill_date', 'paid_date', 'days_supply', 'quantity_dispensed',\n",
        "    'refill_number', 'number_of_refills', 'billed_amount', 'paid_amount'\n",
        "]\n",
        "df = df[cols_to_gen]"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for col in df.columns:\n",
        "  df[col] = df[col].astype(str)"
      ],
      "metadata": {
        "id": "06BzW64QvKnx"
      },
      "id": "06BzW64QvKnx",
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sample_df = df.sample(100000, random_state=10)"
      ],
      "metadata": {
        "id": "wJLF5GKVwVC6"
      },
      "id": "wJLF5GKVwVC6",
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import os\n",
        "os.environ[\"PYTORCH_CUDA_ALLOC_CONF\"] = \"max_split_size_mb:512\""
      ],
      "metadata": {
        "id": "48bpPJv3yCVr"
      },
      "id": "48bpPJv3yCVr",
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install be-great"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IZx1D4A79l_D",
        "outputId": "fa93d0af-a7a2-4eae-9724-e93d56b7a23b"
      },
      "id": "IZx1D4A79l_D",
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting be-great\n",
            "  Downloading be_great-0.0.7-py3-none-any.whl (16 kB)\n",
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            "Installing collected packages: tokenizers, safetensors, xxhash, dill, multiprocess, huggingface-hub, transformers, datasets, accelerate, be-great\n",
            "Successfully installed accelerate-0.23.0 be-great-0.0.7 datasets-2.14.5 dill-0.3.7 huggingface-hub-0.17.3 multiprocess-0.70.15 safetensors-0.3.3 tokenizers-0.13.3 transformers-4.33.3 xxhash-3.3.0\n"
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        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "You're using a GPT2TokenizerFast tokenizer. Please note that with a fast tokenizer, using the `__call__` method is faster than using a method to encode the text followed by a call to the `pad` method to get a padded encoding.\n"
          ]
        },
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              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='490' max='6250' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [ 490/6250 04:40 < 55:13, 1.74 it/s, Epoch 0.08/1]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              " <tr style=\"text-align: left;\">\n",
              "      <th>Step</th>\n",
              "      <th>Training Loss</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "  </tbody>\n",
              "</table><p>"
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      ],
      "source": [
        "from be_great import GReaT\n",
        "model = GReaT(llm='distilgpt2', batch_size=16, epochs=1, save_steps=400000)\n",
        "\n",
        "model.fit(sample_df)"
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