Assignment_2.ipynb

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      "source": [
        "# Assinment House loan data analysis using nueral net - Ankesh"
      ],
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        "id": "rO-2GUePEi4j"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "from sklearn.preprocessing import LabelEncoder, OneHotEncoder\n",
        "import seaborn as sns\n",
        "from sklearn.model_selection import train_test_split"
      ],
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        "id": "X8Hg6qbpUirf"
      },
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      "outputs": []
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      "execution_count": 2,
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        "id": "CtfJoNx8T6p4"
      },
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      "source": [
        "import keras\n",
        "import tensorflow as tf\n",
        "\n",
        "from sklearn.linear_model import LogisticRegression\n",
        "from keras.models import Sequential\n",
        "from keras.layers import Dense, Dropout\n",
        "from keras.optimizers import RMSprop\n",
        "from matplotlib import pyplot"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data = pd.read_csv(\"/content/drive/MyDrive/AEKA_TECH/loan_data.csv\")"
      ],
      "metadata": {
        "id": "s3TLFq9gUBke"
      },
      "execution_count": 3,
      "outputs": []
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            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 307511 entries, 0 to 307510\n",
            "Columns: 122 entries, SK_ID_CURR to AMT_REQ_CREDIT_BUREAU_YEAR\n",
            "dtypes: float64(65), int64(41), object(16)\n",
            "memory usage: 286.2+ MB\n"
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              "   SK_ID_CURR  TARGET NAME_CONTRACT_TYPE CODE_GENDER FLAG_OWN_CAR  \\\n",
              "0      100002       1         Cash loans           M            N   \n",
              "1      100003       0         Cash loans           F            N   \n",
              "2      100004       0    Revolving loans           M            Y   \n",
              "3      100006       0         Cash loans           F            N   \n",
              "4      100007       0         Cash loans           M            N   \n",
              "\n",
              "  FLAG_OWN_REALTY  CNT_CHILDREN  AMT_INCOME_TOTAL  AMT_CREDIT  AMT_ANNUITY  \\\n",
              "0               Y             0          202500.0    406597.5      24700.5   \n",
              "1               N             0          270000.0   1293502.5      35698.5   \n",
              "2               Y             0           67500.0    135000.0       6750.0   \n",
              "3               Y             0          135000.0    312682.5      29686.5   \n",
              "4               Y             0          121500.0    513000.0      21865.5   \n",
              "\n",
              "   ...  FLAG_DOCUMENT_18 FLAG_DOCUMENT_19 FLAG_DOCUMENT_20 FLAG_DOCUMENT_21  \\\n",
              "0  ...                 0                0                0                0   \n",
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              "4  ...                 0                0                0                0   \n",
              "\n",
              "  AMT_REQ_CREDIT_BUREAU_HOUR AMT_REQ_CREDIT_BUREAU_DAY  \\\n",
              "0                        0.0                       0.0   \n",
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              "2                        0.0                       0.0   \n",
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              "\n",
              "   AMT_REQ_CREDIT_BUREAU_WEEK  AMT_REQ_CREDIT_BUREAU_MON  \\\n",
              "0                         0.0                        0.0   \n",
              "1                         0.0                        0.0   \n",
              "2                         0.0                        0.0   \n",
              "3                         NaN                        NaN   \n",
              "4                         0.0                        0.0   \n",
              "\n",
              "   AMT_REQ_CREDIT_BUREAU_QRT  AMT_REQ_CREDIT_BUREAU_YEAR  \n",
              "0                        0.0                         1.0  \n",
              "1                        0.0                         0.0  \n",
              "2                        0.0                         0.0  \n",
              "3                        NaN                         NaN  \n",
              "4                        0.0                         0.0  \n",
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              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-25f246ab-becf-4d37-ab87-518948b29627 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": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "WqEFC2UFW3zg"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Null Values"
      ],
      "metadata": {
        "id": "VdZ7kOYoW2Wv"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "total = (data.isnull().sum()/data.shape[0])*100\n"
      ],
      "metadata": {
        "id": "KXy7z91MUstl"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "with pd.option_context('display.max_rows', None, 'display.max_columns', None):  # more options can be specified also\n",
        "    print(total.sort_values(ascending=False))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QURQkC5XU-5r",
        "outputId": "5d03ed07-7708-438a-f4e3-b9963ea6c633"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "COMMONAREA_MEDI                 69.872297\n",
            "COMMONAREA_AVG                  69.872297\n",
            "COMMONAREA_MODE                 69.872297\n",
            "NONLIVINGAPARTMENTS_MODE        69.432963\n",
            "NONLIVINGAPARTMENTS_AVG         69.432963\n",
            "NONLIVINGAPARTMENTS_MEDI        69.432963\n",
            "FONDKAPREMONT_MODE              68.386172\n",
            "LIVINGAPARTMENTS_MODE           68.354953\n",
            "LIVINGAPARTMENTS_AVG            68.354953\n",
            "LIVINGAPARTMENTS_MEDI           68.354953\n",
            "FLOORSMIN_AVG                   67.848630\n",
            "FLOORSMIN_MODE                  67.848630\n",
            "FLOORSMIN_MEDI                  67.848630\n",
            "YEARS_BUILD_MEDI                66.497784\n",
            "YEARS_BUILD_MODE                66.497784\n",
            "YEARS_BUILD_AVG                 66.497784\n",
            "OWN_CAR_AGE                     65.990810\n",
            "LANDAREA_MEDI                   59.376738\n",
            "LANDAREA_MODE                   59.376738\n",
            "LANDAREA_AVG                    59.376738\n",
            "BASEMENTAREA_MEDI               58.515956\n",
            "BASEMENTAREA_AVG                58.515956\n",
            "BASEMENTAREA_MODE               58.515956\n",
            "EXT_SOURCE_1                    56.381073\n",
            "NONLIVINGAREA_MODE              55.179164\n",
            "NONLIVINGAREA_AVG               55.179164\n",
            "NONLIVINGAREA_MEDI              55.179164\n",
            "ELEVATORS_MEDI                  53.295980\n",
            "ELEVATORS_AVG                   53.295980\n",
            "ELEVATORS_MODE                  53.295980\n",
            "WALLSMATERIAL_MODE              50.840783\n",
            "APARTMENTS_MEDI                 50.749729\n",
            "APARTMENTS_AVG                  50.749729\n",
            "APARTMENTS_MODE                 50.749729\n",
            "ENTRANCES_MEDI                  50.348768\n",
            "ENTRANCES_AVG                   50.348768\n",
            "ENTRANCES_MODE                  50.348768\n",
            "LIVINGAREA_AVG                  50.193326\n",
            "LIVINGAREA_MODE                 50.193326\n",
            "LIVINGAREA_MEDI                 50.193326\n",
            "HOUSETYPE_MODE                  50.176091\n",
            "FLOORSMAX_MODE                  49.760822\n",
            "FLOORSMAX_MEDI                  49.760822\n",
            "FLOORSMAX_AVG                   49.760822\n",
            "YEARS_BEGINEXPLUATATION_MODE    48.781019\n",
            "YEARS_BEGINEXPLUATATION_MEDI    48.781019\n",
            "YEARS_BEGINEXPLUATATION_AVG     48.781019\n",
            "TOTALAREA_MODE                  48.268517\n",
            "EMERGENCYSTATE_MODE             47.398304\n",
            "OCCUPATION_TYPE                 31.345545\n",
            "EXT_SOURCE_3                    19.825307\n",
            "AMT_REQ_CREDIT_BUREAU_HOUR      13.501631\n",
            "AMT_REQ_CREDIT_BUREAU_DAY       13.501631\n",
            "AMT_REQ_CREDIT_BUREAU_WEEK      13.501631\n",
            "AMT_REQ_CREDIT_BUREAU_MON       13.501631\n",
            "AMT_REQ_CREDIT_BUREAU_QRT       13.501631\n",
            "AMT_REQ_CREDIT_BUREAU_YEAR      13.501631\n",
            "NAME_TYPE_SUITE                  0.420148\n",
            "OBS_30_CNT_SOCIAL_CIRCLE         0.332021\n",
            "DEF_30_CNT_SOCIAL_CIRCLE         0.332021\n",
            "OBS_60_CNT_SOCIAL_CIRCLE         0.332021\n",
            "DEF_60_CNT_SOCIAL_CIRCLE         0.332021\n",
            "EXT_SOURCE_2                     0.214626\n",
            "AMT_GOODS_PRICE                  0.090403\n",
            "AMT_ANNUITY                      0.003902\n",
            "CNT_FAM_MEMBERS                  0.000650\n",
            "DAYS_LAST_PHONE_CHANGE           0.000325\n",
            "CNT_CHILDREN                     0.000000\n",
            "FLAG_DOCUMENT_8                  0.000000\n",
            "NAME_CONTRACT_TYPE               0.000000\n",
            "CODE_GENDER                      0.000000\n",
            "FLAG_OWN_CAR                     0.000000\n",
            "FLAG_DOCUMENT_2                  0.000000\n",
            "FLAG_DOCUMENT_3                  0.000000\n",
            "FLAG_DOCUMENT_4                  0.000000\n",
            "FLAG_DOCUMENT_5                  0.000000\n",
            "FLAG_DOCUMENT_6                  0.000000\n",
            "FLAG_DOCUMENT_7                  0.000000\n",
            "FLAG_DOCUMENT_9                  0.000000\n",
            "FLAG_DOCUMENT_21                 0.000000\n",
            "FLAG_DOCUMENT_10                 0.000000\n",
            "FLAG_DOCUMENT_11                 0.000000\n",
            "FLAG_OWN_REALTY                  0.000000\n",
            "FLAG_DOCUMENT_13                 0.000000\n",
            "FLAG_DOCUMENT_14                 0.000000\n",
            "FLAG_DOCUMENT_15                 0.000000\n",
            "FLAG_DOCUMENT_16                 0.000000\n",
            "FLAG_DOCUMENT_17                 0.000000\n",
            "FLAG_DOCUMENT_18                 0.000000\n",
            "FLAG_DOCUMENT_19                 0.000000\n",
            "FLAG_DOCUMENT_20                 0.000000\n",
            "FLAG_DOCUMENT_12                 0.000000\n",
            "AMT_CREDIT                       0.000000\n",
            "AMT_INCOME_TOTAL                 0.000000\n",
            "FLAG_PHONE                       0.000000\n",
            "LIVE_CITY_NOT_WORK_CITY          0.000000\n",
            "REG_CITY_NOT_WORK_CITY           0.000000\n",
            "TARGET                           0.000000\n",
            "REG_CITY_NOT_LIVE_CITY           0.000000\n",
            "LIVE_REGION_NOT_WORK_REGION      0.000000\n",
            "REG_REGION_NOT_WORK_REGION       0.000000\n",
            "REG_REGION_NOT_LIVE_REGION       0.000000\n",
            "HOUR_APPR_PROCESS_START          0.000000\n",
            "WEEKDAY_APPR_PROCESS_START       0.000000\n",
            "REGION_RATING_CLIENT_W_CITY      0.000000\n",
            "REGION_RATING_CLIENT             0.000000\n",
            "FLAG_EMAIL                       0.000000\n",
            "FLAG_CONT_MOBILE                 0.000000\n",
            "ORGANIZATION_TYPE                0.000000\n",
            "FLAG_WORK_PHONE                  0.000000\n",
            "FLAG_EMP_PHONE                   0.000000\n",
            "FLAG_MOBIL                       0.000000\n",
            "DAYS_ID_PUBLISH                  0.000000\n",
            "DAYS_REGISTRATION                0.000000\n",
            "DAYS_EMPLOYED                    0.000000\n",
            "DAYS_BIRTH                       0.000000\n",
            "REGION_POPULATION_RELATIVE       0.000000\n",
            "NAME_HOUSING_TYPE                0.000000\n",
            "NAME_FAMILY_STATUS               0.000000\n",
            "NAME_EDUCATION_TYPE              0.000000\n",
            "NAME_INCOME_TYPE                 0.000000\n",
            "SK_ID_CURR                       0.000000\n",
            "dtype: float64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Data Imbalance count"
      ],
      "metadata": {
        "id": "bNIzAnKvYDcO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "(data.TARGET.value_counts()/data.shape[0]) *100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fWznpK0mVYTW",
        "outputId": "1b66b36f-fa64-46db-815c-34f5e87be5bc"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    91.927118\n",
              "1     8.072882\n",
              "Name: TARGET, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I6Ug2ZkDXd67",
        "outputId": "02b4819e-1b34-49a8-91a8-645600e745f9"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "307511"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Null value check and processing"
      ],
      "metadata": {
        "id": "B1qAHQmt4qw9"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# total = pd.DataFrame(total,columns=[\"col_name\",\"percentage\"], index=False)\n",
        "total  = total.to_frame().reset_index()\n",
        "total.rename(columns={\"index\":\"col_name\",0:\"percentage\"},inplace=True)"
      ],
      "metadata": {
        "id": "lPq7yg5NYdZ5"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "total"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "id": "p-GY7Y_NZxYj",
        "outputId": "19107e13-175d-443a-f065-b63f59634cd0"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                       col_name  percentage\n",
              "0                    SK_ID_CURR    0.000000\n",
              "1                        TARGET    0.000000\n",
              "2            NAME_CONTRACT_TYPE    0.000000\n",
              "3                   CODE_GENDER    0.000000\n",
              "4                  FLAG_OWN_CAR    0.000000\n",
              "..                          ...         ...\n",
              "117   AMT_REQ_CREDIT_BUREAU_DAY   13.501631\n",
              "118  AMT_REQ_CREDIT_BUREAU_WEEK   13.501631\n",
              "119   AMT_REQ_CREDIT_BUREAU_MON   13.501631\n",
              "120   AMT_REQ_CREDIT_BUREAU_QRT   13.501631\n",
              "121  AMT_REQ_CREDIT_BUREAU_YEAR   13.501631\n",
              "\n",
              "[122 rows x 2 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a068d28d-f381-4168-a0bd-b053d33731c3\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>col_name</th>\n",
              "      <th>percentage</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>SK_ID_CURR</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>TARGET</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>NAME_CONTRACT_TYPE</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CODE_GENDER</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>FLAG_OWN_CAR</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>117</th>\n",
              "      <td>AMT_REQ_CREDIT_BUREAU_DAY</td>\n",
              "      <td>13.501631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>118</th>\n",
              "      <td>AMT_REQ_CREDIT_BUREAU_WEEK</td>\n",
              "      <td>13.501631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119</th>\n",
              "      <td>AMT_REQ_CREDIT_BUREAU_MON</td>\n",
              "      <td>13.501631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>120</th>\n",
              "      <td>AMT_REQ_CREDIT_BUREAU_QRT</td>\n",
              "      <td>13.501631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121</th>\n",
              "      <td>AMT_REQ_CREDIT_BUREAU_YEAR</td>\n",
              "      <td>13.501631</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>122 rows × 2 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a068d28d-f381-4168-a0bd-b053d33731c3')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
              "    <path d=\"M120-120v-720h720v720H120Zm60-500h600v-160H180v160Zm220 220h160v-160H400v160Zm0 220h160v-160H400v160ZM180-400h160v-160H180v160Zm440 0h160v-160H620v160ZM180-180h160v-160H180v160Zm440 0h160v-160H620v160Z\"/>\n",
              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-a068d28d-f381-4168-a0bd-b053d33731c3 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-a068d28d-f381-4168-a0bd-b053d33731c3');\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-75cf0dc5-d611-46ea-938c-cb8ff9bff39d\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-75cf0dc5-d611-46ea-938c-cb8ff9bff39d')\"\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",
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              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
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              "    80% {\n",
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              "      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-75cf0dc5-d611-46ea-938c-cb8ff9bff39d 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": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "to_remove =list( total[total.percentage > 33].col_name )\n",
        "to_remove"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rUDYlmd7Z8rh",
        "outputId": "9975f8e7-216e-45b8-8f0c-670c257b04e3"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['OWN_CAR_AGE',\n",
              " 'EXT_SOURCE_1',\n",
              " 'APARTMENTS_AVG',\n",
              " 'BASEMENTAREA_AVG',\n",
              " 'YEARS_BEGINEXPLUATATION_AVG',\n",
              " 'YEARS_BUILD_AVG',\n",
              " 'COMMONAREA_AVG',\n",
              " 'ELEVATORS_AVG',\n",
              " 'ENTRANCES_AVG',\n",
              " 'FLOORSMAX_AVG',\n",
              " 'FLOORSMIN_AVG',\n",
              " 'LANDAREA_AVG',\n",
              " 'LIVINGAPARTMENTS_AVG',\n",
              " 'LIVINGAREA_AVG',\n",
              " 'NONLIVINGAPARTMENTS_AVG',\n",
              " 'NONLIVINGAREA_AVG',\n",
              " 'APARTMENTS_MODE',\n",
              " 'BASEMENTAREA_MODE',\n",
              " 'YEARS_BEGINEXPLUATATION_MODE',\n",
              " 'YEARS_BUILD_MODE',\n",
              " 'COMMONAREA_MODE',\n",
              " 'ELEVATORS_MODE',\n",
              " 'ENTRANCES_MODE',\n",
              " 'FLOORSMAX_MODE',\n",
              " 'FLOORSMIN_MODE',\n",
              " 'LANDAREA_MODE',\n",
              " 'LIVINGAPARTMENTS_MODE',\n",
              " 'LIVINGAREA_MODE',\n",
              " 'NONLIVINGAPARTMENTS_MODE',\n",
              " 'NONLIVINGAREA_MODE',\n",
              " 'APARTMENTS_MEDI',\n",
              " 'BASEMENTAREA_MEDI',\n",
              " 'YEARS_BEGINEXPLUATATION_MEDI',\n",
              " 'YEARS_BUILD_MEDI',\n",
              " 'COMMONAREA_MEDI',\n",
              " 'ELEVATORS_MEDI',\n",
              " 'ENTRANCES_MEDI',\n",
              " 'FLOORSMAX_MEDI',\n",
              " 'FLOORSMIN_MEDI',\n",
              " 'LANDAREA_MEDI',\n",
              " 'LIVINGAPARTMENTS_MEDI',\n",
              " 'LIVINGAREA_MEDI',\n",
              " 'NONLIVINGAPARTMENTS_MEDI',\n",
              " 'NONLIVINGAREA_MEDI',\n",
              " 'FONDKAPREMONT_MODE',\n",
              " 'HOUSETYPE_MODE',\n",
              " 'TOTALAREA_MODE',\n",
              " 'WALLSMATERIAL_MODE',\n",
              " 'EMERGENCYSTATE_MODE']"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "BBHPO20JcPHW"
      },
      "execution_count": 12,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "#rmove the columns to drop from data frame and null percentage df\n",
        "df_clean = data.drop(to_remove, axis='columns')\n",
        "\n",
        "for col_name in to_remove:\n",
        "  total.drop( total[total[\"col_name\"] == col_name].index, axis='rows',inplace=True)\n",
        "total"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 444
        },
        "id": "2Q2kECkXaFTr",
        "outputId": "bb0c1ce3-61cf-4256-deae-5d97f978d452"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                       col_name  percentage\n",
              "0                    SK_ID_CURR    0.000000\n",
              "1                        TARGET    0.000000\n",
              "2            NAME_CONTRACT_TYPE    0.000000\n",
              "3                   CODE_GENDER    0.000000\n",
              "4                  FLAG_OWN_CAR    0.000000\n",
              "..                          ...         ...\n",
              "117   AMT_REQ_CREDIT_BUREAU_DAY   13.501631\n",
              "118  AMT_REQ_CREDIT_BUREAU_WEEK   13.501631\n",
              "119   AMT_REQ_CREDIT_BUREAU_MON   13.501631\n",
              "120   AMT_REQ_CREDIT_BUREAU_QRT   13.501631\n",
              "121  AMT_REQ_CREDIT_BUREAU_YEAR   13.501631\n",
              "\n",
              "[73 rows x 2 columns]"
            ],
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              "      <th>0</th>\n",
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              "      <th>1</th>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>NAME_CONTRACT_TYPE</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>CODE_GENDER</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>FLAG_OWN_CAR</td>\n",
              "      <td>0.000000</td>\n",
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              "      <td>13.501631</td>\n",
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              "      <th>118</th>\n",
              "      <td>AMT_REQ_CREDIT_BUREAU_WEEK</td>\n",
              "      <td>13.501631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>119</th>\n",
              "      <td>AMT_REQ_CREDIT_BUREAU_MON</td>\n",
              "      <td>13.501631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>120</th>\n",
              "      <td>AMT_REQ_CREDIT_BUREAU_QRT</td>\n",
              "      <td>13.501631</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>121</th>\n",
              "      <td>AMT_REQ_CREDIT_BUREAU_YEAR</td>\n",
              "      <td>13.501631</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>73 rows × 2 columns</p>\n",
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              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-56f7b605-5f30-4236-941d-8e0f6e8cea35 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-56f7b605-5f30-4236-941d-8e0f6e8cea35');\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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              "    height: 32px;\n",
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              "    width: 32px;\n",
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              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
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              "  @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-right-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-3c9faa86-808c-43c0-a69e-890c245dd80b 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": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_clean.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 256
        },
        "id": "GHiKrfCkcQCT",
        "outputId": "42689706-2f77-485f-f295-92ca051d8f4c"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "   SK_ID_CURR  TARGET NAME_CONTRACT_TYPE CODE_GENDER FLAG_OWN_CAR  \\\n",
              "0      100002       1         Cash loans           M            N   \n",
              "1      100003       0         Cash loans           F            N   \n",
              "2      100004       0    Revolving loans           M            Y   \n",
              "3      100006       0         Cash loans           F            N   \n",
              "4      100007       0         Cash loans           M            N   \n",
              "\n",
              "  FLAG_OWN_REALTY  CNT_CHILDREN  AMT_INCOME_TOTAL  AMT_CREDIT  AMT_ANNUITY  \\\n",
              "0               Y             0          202500.0    406597.5      24700.5   \n",
              "1               N             0          270000.0   1293502.5      35698.5   \n",
              "2               Y             0           67500.0    135000.0       6750.0   \n",
              "3               Y             0          135000.0    312682.5      29686.5   \n",
              "4               Y             0          121500.0    513000.0      21865.5   \n",
              "\n",
              "   ...  FLAG_DOCUMENT_18 FLAG_DOCUMENT_19 FLAG_DOCUMENT_20 FLAG_DOCUMENT_21  \\\n",
              "0  ...                 0                0                0                0   \n",
              "1  ...                 0                0                0                0   \n",
              "2  ...                 0                0                0                0   \n",
              "3  ...                 0                0                0                0   \n",
              "4  ...                 0                0                0                0   \n",
              "\n",
              "  AMT_REQ_CREDIT_BUREAU_HOUR AMT_REQ_CREDIT_BUREAU_DAY  \\\n",
              "0                        0.0                       0.0   \n",
              "1                        0.0                       0.0   \n",
              "2                        0.0                       0.0   \n",
              "3                        NaN                       NaN   \n",
              "4                        0.0                       0.0   \n",
              "\n",
              "   AMT_REQ_CREDIT_BUREAU_WEEK  AMT_REQ_CREDIT_BUREAU_MON  \\\n",
              "0                         0.0                        0.0   \n",
              "1                         0.0                        0.0   \n",
              "2                         0.0                        0.0   \n",
              "3                         NaN                        NaN   \n",
              "4                         0.0                        0.0   \n",
              "\n",
              "   AMT_REQ_CREDIT_BUREAU_QRT  AMT_REQ_CREDIT_BUREAU_YEAR  \n",
              "0                        0.0                         1.0  \n",
              "1                        0.0                         0.0  \n",
              "2                        0.0                         0.0  \n",
              "3                        NaN                         NaN  \n",
              "4                        0.0                         0.0  \n",
              "\n",
              "[5 rows x 73 columns]"
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              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
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              "        text-align: right;\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SK_ID_CURR</th>\n",
              "      <th>TARGET</th>\n",
              "      <th>NAME_CONTRACT_TYPE</th>\n",
              "      <th>CODE_GENDER</th>\n",
              "      <th>FLAG_OWN_CAR</th>\n",
              "      <th>FLAG_OWN_REALTY</th>\n",
              "      <th>CNT_CHILDREN</th>\n",
              "      <th>AMT_INCOME_TOTAL</th>\n",
              "      <th>AMT_CREDIT</th>\n",
              "      <th>AMT_ANNUITY</th>\n",
              "      <th>...</th>\n",
              "      <th>FLAG_DOCUMENT_18</th>\n",
              "      <th>FLAG_DOCUMENT_19</th>\n",
              "      <th>FLAG_DOCUMENT_20</th>\n",
              "      <th>FLAG_DOCUMENT_21</th>\n",
              "      <th>AMT_REQ_CREDIT_BUREAU_HOUR</th>\n",
              "      <th>AMT_REQ_CREDIT_BUREAU_DAY</th>\n",
              "      <th>AMT_REQ_CREDIT_BUREAU_WEEK</th>\n",
              "      <th>AMT_REQ_CREDIT_BUREAU_MON</th>\n",
              "      <th>AMT_REQ_CREDIT_BUREAU_QRT</th>\n",
              "      <th>AMT_REQ_CREDIT_BUREAU_YEAR</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>100002</td>\n",
              "      <td>1</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>M</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>202500.0</td>\n",
              "      <td>406597.5</td>\n",
              "      <td>24700.5</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>100003</td>\n",
              "      <td>0</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>F</td>\n",
              "      <td>N</td>\n",
              "      <td>N</td>\n",
              "      <td>0</td>\n",
              "      <td>270000.0</td>\n",
              "      <td>1293502.5</td>\n",
              "      <td>35698.5</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>100004</td>\n",
              "      <td>0</td>\n",
              "      <td>Revolving loans</td>\n",
              "      <td>M</td>\n",
              "      <td>Y</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>67500.0</td>\n",
              "      <td>135000.0</td>\n",
              "      <td>6750.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>100006</td>\n",
              "      <td>0</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>F</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>135000.0</td>\n",
              "      <td>312682.5</td>\n",
              "      <td>29686.5</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>100007</td>\n",
              "      <td>0</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>M</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>121500.0</td>\n",
              "      <td>513000.0</td>\n",
              "      <td>21865.5</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 73 columns</p>\n",
              "</div>\n",
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              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-43b38494-8549-48d8-8a9e-0b4b405af1d0');\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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              "        docLink.innerHTML = docLinkHtml;\n",
              "        element.appendChild(docLink);\n",
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              "  [theme=dark] .colab-df-quickchart {\n",
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              "\n",
              "  .colab-df-quickchart {\n",
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              "    width: 32px;\n",
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              "  .colab-df-quickchart:hover {\n",
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              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
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              "    box-shadow: none;\n",
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              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
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              "    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-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
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              "      border-bottom-color: var(--fill-color);\n",
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              "  }\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-0e7816a0-c0c3-44c4-a614-3429e9c4d629 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": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "with pd.option_context('display.max_rows', None, 'display.max_columns', None):  # more options can be specified also\n",
        "    df_clean.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "69dhcO_LciSu",
        "outputId": "6b9f0649-1313-4973-8eed-baf94755334a"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 307511 entries, 0 to 307510\n",
            "Data columns (total 73 columns):\n",
            " #   Column                       Non-Null Count   Dtype  \n",
            "---  ------                       --------------   -----  \n",
            " 0   SK_ID_CURR                   307511 non-null  int64  \n",
            " 1   TARGET                       307511 non-null  int64  \n",
            " 2   NAME_CONTRACT_TYPE           307511 non-null  object \n",
            " 3   CODE_GENDER                  307511 non-null  object \n",
            " 4   FLAG_OWN_CAR                 307511 non-null  object \n",
            " 5   FLAG_OWN_REALTY              307511 non-null  object \n",
            " 6   CNT_CHILDREN                 307511 non-null  int64  \n",
            " 7   AMT_INCOME_TOTAL             307511 non-null  float64\n",
            " 8   AMT_CREDIT                   307511 non-null  float64\n",
            " 9   AMT_ANNUITY                  307499 non-null  float64\n",
            " 10  AMT_GOODS_PRICE              307233 non-null  float64\n",
            " 11  NAME_TYPE_SUITE              306219 non-null  object \n",
            " 12  NAME_INCOME_TYPE             307511 non-null  object \n",
            " 13  NAME_EDUCATION_TYPE          307511 non-null  object \n",
            " 14  NAME_FAMILY_STATUS           307511 non-null  object \n",
            " 15  NAME_HOUSING_TYPE            307511 non-null  object \n",
            " 16  REGION_POPULATION_RELATIVE   307511 non-null  float64\n",
            " 17  DAYS_BIRTH                   307511 non-null  int64  \n",
            " 18  DAYS_EMPLOYED                307511 non-null  int64  \n",
            " 19  DAYS_REGISTRATION            307511 non-null  float64\n",
            " 20  DAYS_ID_PUBLISH              307511 non-null  int64  \n",
            " 21  FLAG_MOBIL                   307511 non-null  int64  \n",
            " 22  FLAG_EMP_PHONE               307511 non-null  int64  \n",
            " 23  FLAG_WORK_PHONE              307511 non-null  int64  \n",
            " 24  FLAG_CONT_MOBILE             307511 non-null  int64  \n",
            " 25  FLAG_PHONE                   307511 non-null  int64  \n",
            " 26  FLAG_EMAIL                   307511 non-null  int64  \n",
            " 27  OCCUPATION_TYPE              211120 non-null  object \n",
            " 28  CNT_FAM_MEMBERS              307509 non-null  float64\n",
            " 29  REGION_RATING_CLIENT         307511 non-null  int64  \n",
            " 30  REGION_RATING_CLIENT_W_CITY  307511 non-null  int64  \n",
            " 31  WEEKDAY_APPR_PROCESS_START   307511 non-null  object \n",
            " 32  HOUR_APPR_PROCESS_START      307511 non-null  int64  \n",
            " 33  REG_REGION_NOT_LIVE_REGION   307511 non-null  int64  \n",
            " 34  REG_REGION_NOT_WORK_REGION   307511 non-null  int64  \n",
            " 35  LIVE_REGION_NOT_WORK_REGION  307511 non-null  int64  \n",
            " 36  REG_CITY_NOT_LIVE_CITY       307511 non-null  int64  \n",
            " 37  REG_CITY_NOT_WORK_CITY       307511 non-null  int64  \n",
            " 38  LIVE_CITY_NOT_WORK_CITY      307511 non-null  int64  \n",
            " 39  ORGANIZATION_TYPE            307511 non-null  object \n",
            " 40  EXT_SOURCE_2                 306851 non-null  float64\n",
            " 41  EXT_SOURCE_3                 246546 non-null  float64\n",
            " 42  OBS_30_CNT_SOCIAL_CIRCLE     306490 non-null  float64\n",
            " 43  DEF_30_CNT_SOCIAL_CIRCLE     306490 non-null  float64\n",
            " 44  OBS_60_CNT_SOCIAL_CIRCLE     306490 non-null  float64\n",
            " 45  DEF_60_CNT_SOCIAL_CIRCLE     306490 non-null  float64\n",
            " 46  DAYS_LAST_PHONE_CHANGE       307510 non-null  float64\n",
            " 47  FLAG_DOCUMENT_2              307511 non-null  int64  \n",
            " 48  FLAG_DOCUMENT_3              307511 non-null  int64  \n",
            " 49  FLAG_DOCUMENT_4              307511 non-null  int64  \n",
            " 50  FLAG_DOCUMENT_5              307511 non-null  int64  \n",
            " 51  FLAG_DOCUMENT_6              307511 non-null  int64  \n",
            " 52  FLAG_DOCUMENT_7              307511 non-null  int64  \n",
            " 53  FLAG_DOCUMENT_8              307511 non-null  int64  \n",
            " 54  FLAG_DOCUMENT_9              307511 non-null  int64  \n",
            " 55  FLAG_DOCUMENT_10             307511 non-null  int64  \n",
            " 56  FLAG_DOCUMENT_11             307511 non-null  int64  \n",
            " 57  FLAG_DOCUMENT_12             307511 non-null  int64  \n",
            " 58  FLAG_DOCUMENT_13             307511 non-null  int64  \n",
            " 59  FLAG_DOCUMENT_14             307511 non-null  int64  \n",
            " 60  FLAG_DOCUMENT_15             307511 non-null  int64  \n",
            " 61  FLAG_DOCUMENT_16             307511 non-null  int64  \n",
            " 62  FLAG_DOCUMENT_17             307511 non-null  int64  \n",
            " 63  FLAG_DOCUMENT_18             307511 non-null  int64  \n",
            " 64  FLAG_DOCUMENT_19             307511 non-null  int64  \n",
            " 65  FLAG_DOCUMENT_20             307511 non-null  int64  \n",
            " 66  FLAG_DOCUMENT_21             307511 non-null  int64  \n",
            " 67  AMT_REQ_CREDIT_BUREAU_HOUR   265992 non-null  float64\n",
            " 68  AMT_REQ_CREDIT_BUREAU_DAY    265992 non-null  float64\n",
            " 69  AMT_REQ_CREDIT_BUREAU_WEEK   265992 non-null  float64\n",
            " 70  AMT_REQ_CREDIT_BUREAU_MON    265992 non-null  float64\n",
            " 71  AMT_REQ_CREDIT_BUREAU_QRT    265992 non-null  float64\n",
            " 72  AMT_REQ_CREDIT_BUREAU_YEAR   265992 non-null  float64\n",
            "dtypes: float64(20), int64(41), object(12)\n",
            "memory usage: 171.3+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "data.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Z3w7HwYlcw8C",
        "outputId": "f3349b52-e1a5-4bb2-8d67-7ba240273a3a"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(307511, 122)"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "r8mHhE1uc-iE"
      },
      "execution_count": 16,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## OCCUPATION_TYPE\n",
        "\n",
        "`df_clean[df_clean[\"TARGET\"] == 1].OCCUPATION_TYPE.value_counts()` : defaulting by category\n",
        "\n",
        "`df_clean.OCCUPATION_TYPE.value_counts()` : total count\n",
        "\n",
        "Even though OCCUPATION_TYPE has high null count 33 % but including this as this seems like a pretty relevant field as per domain logic.\n",
        "As can be seen below low skill occupation type have a higher defaulting percentage"
      ],
      "metadata": {
        "id": "Yf9w_MBFe18Z"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "(df_clean[df_clean[\"TARGET\"] == 1].OCCUPATION_TYPE.value_counts()/df_clean.OCCUPATION_TYPE.value_counts() *100).sort_values()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7JyqV7wkdM3j",
        "outputId": "aa7d597a-25bb-4ad3-eab1-ea1955730e31"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Accountants               4.830327\n",
              "High skill tech staff     6.159930\n",
              "Managers                  6.214028\n",
              "Core staff                6.303954\n",
              "HR staff                  6.394316\n",
              "IT staff                  6.463878\n",
              "Private service staff     6.598793\n",
              "Medicine staff            6.700246\n",
              "Secretaries               7.049808\n",
              "Realty agents             7.856192\n",
              "Cleaning staff            9.606705\n",
              "Sales staff               9.631799\n",
              "Cooking staff            10.443996\n",
              "Laborers                 10.578770\n",
              "Security staff           10.742449\n",
              "Waiters/barmen staff     11.275964\n",
              "Drivers                  11.326130\n",
              "Low-skill Laborers       17.152413\n",
              "Name: OCCUPATION_TYPE, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n",
        "  print(df_clean.nunique().sort_values())"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0-C7xaxFeCV0",
        "outputId": "feb09f85-de3e-48c1-93d9-162eb93b9b97"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "REG_CITY_NOT_LIVE_CITY              2\n",
            "FLAG_EMAIL                          2\n",
            "FLAG_DOCUMENT_9                     2\n",
            "REG_REGION_NOT_LIVE_REGION          2\n",
            "REG_REGION_NOT_WORK_REGION          2\n",
            "LIVE_REGION_NOT_WORK_REGION         2\n",
            "REG_CITY_NOT_WORK_CITY              2\n",
            "LIVE_CITY_NOT_WORK_CITY             2\n",
            "FLAG_DOCUMENT_16                    2\n",
            "FLAG_DOCUMENT_15                    2\n",
            "FLAG_PHONE                          2\n",
            "FLAG_DOCUMENT_14                    2\n",
            "FLAG_DOCUMENT_12                    2\n",
            "FLAG_DOCUMENT_11                    2\n",
            "FLAG_DOCUMENT_2                     2\n",
            "FLAG_DOCUMENT_3                     2\n",
            "FLAG_DOCUMENT_4                     2\n",
            "FLAG_DOCUMENT_5                     2\n",
            "FLAG_DOCUMENT_6                     2\n",
            "FLAG_DOCUMENT_7                     2\n",
            "FLAG_DOCUMENT_8                     2\n",
            "FLAG_DOCUMENT_13                    2\n",
            "FLAG_CONT_MOBILE                    2\n",
            "FLAG_DOCUMENT_10                    2\n",
            "FLAG_EMP_PHONE                      2\n",
            "FLAG_MOBIL                          2\n",
            "FLAG_DOCUMENT_17                    2\n",
            "FLAG_DOCUMENT_18                    2\n",
            "TARGET                              2\n",
            "NAME_CONTRACT_TYPE                  2\n",
            "FLAG_DOCUMENT_19                    2\n",
            "FLAG_DOCUMENT_20                    2\n",
            "FLAG_DOCUMENT_21                    2\n",
            "FLAG_OWN_CAR                        2\n",
            "FLAG_OWN_REALTY                     2\n",
            "FLAG_WORK_PHONE                     2\n",
            "REGION_RATING_CLIENT                3\n",
            "REGION_RATING_CLIENT_W_CITY         3\n",
            "CODE_GENDER                         3\n",
            "AMT_REQ_CREDIT_BUREAU_HOUR          5\n",
            "NAME_EDUCATION_TYPE                 5\n",
            "NAME_FAMILY_STATUS                  6\n",
            "NAME_HOUSING_TYPE                   6\n",
            "NAME_TYPE_SUITE                     7\n",
            "WEEKDAY_APPR_PROCESS_START          7\n",
            "NAME_INCOME_TYPE                    8\n",
            "AMT_REQ_CREDIT_BUREAU_DAY           9\n",
            "DEF_60_CNT_SOCIAL_CIRCLE            9\n",
            "AMT_REQ_CREDIT_BUREAU_WEEK          9\n",
            "DEF_30_CNT_SOCIAL_CIRCLE           10\n",
            "AMT_REQ_CREDIT_BUREAU_QRT          11\n",
            "CNT_CHILDREN                       15\n",
            "CNT_FAM_MEMBERS                    17\n",
            "OCCUPATION_TYPE                    18\n",
            "AMT_REQ_CREDIT_BUREAU_MON          24\n",
            "HOUR_APPR_PROCESS_START            24\n",
            "AMT_REQ_CREDIT_BUREAU_YEAR         25\n",
            "OBS_60_CNT_SOCIAL_CIRCLE           33\n",
            "OBS_30_CNT_SOCIAL_CIRCLE           33\n",
            "ORGANIZATION_TYPE                  58\n",
            "REGION_POPULATION_RELATIVE         81\n",
            "EXT_SOURCE_3                      814\n",
            "AMT_GOODS_PRICE                  1002\n",
            "AMT_INCOME_TOTAL                 2548\n",
            "DAYS_LAST_PHONE_CHANGE           3773\n",
            "AMT_CREDIT                       5603\n",
            "DAYS_ID_PUBLISH                  6168\n",
            "DAYS_EMPLOYED                   12574\n",
            "AMT_ANNUITY                     13672\n",
            "DAYS_REGISTRATION               15688\n",
            "DAYS_BIRTH                      17460\n",
            "EXT_SOURCE_2                   119831\n",
            "SK_ID_CURR                     307511\n",
            "dtype: int64\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Process columns that have Nan"
      ],
      "metadata": {
        "id": "Rui85u7UgU3t"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "with pd.option_context('display.max_rows', None, 'display.max_columns', None):  # more options can be specified also\n",
        "    print(total.sort_values('percentage'))"
      ],
      "metadata": {
        "id": "aHTK_R8EeCT9",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "500e80fe-29dd-4819-fa3d-46fcafec0379"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "                        col_name  percentage\n",
            "0                     SK_ID_CURR    0.000000\n",
            "33       HOUR_APPR_PROCESS_START    0.000000\n",
            "34    REG_REGION_NOT_LIVE_REGION    0.000000\n",
            "35    REG_REGION_NOT_WORK_REGION    0.000000\n",
            "36   LIVE_REGION_NOT_WORK_REGION    0.000000\n",
            "38        REG_CITY_NOT_WORK_CITY    0.000000\n",
            "39       LIVE_CITY_NOT_WORK_CITY    0.000000\n",
            "40             ORGANIZATION_TYPE    0.000000\n",
            "96               FLAG_DOCUMENT_2    0.000000\n",
            "97               FLAG_DOCUMENT_3    0.000000\n",
            "98               FLAG_DOCUMENT_4    0.000000\n",
            "99               FLAG_DOCUMENT_5    0.000000\n",
            "100              FLAG_DOCUMENT_6    0.000000\n",
            "101              FLAG_DOCUMENT_7    0.000000\n",
            "102              FLAG_DOCUMENT_8    0.000000\n",
            "103              FLAG_DOCUMENT_9    0.000000\n",
            "104             FLAG_DOCUMENT_10    0.000000\n",
            "105             FLAG_DOCUMENT_11    0.000000\n",
            "106             FLAG_DOCUMENT_12    0.000000\n",
            "107             FLAG_DOCUMENT_13    0.000000\n",
            "108             FLAG_DOCUMENT_14    0.000000\n",
            "109             FLAG_DOCUMENT_15    0.000000\n",
            "110             FLAG_DOCUMENT_16    0.000000\n",
            "111             FLAG_DOCUMENT_17    0.000000\n",
            "112             FLAG_DOCUMENT_18    0.000000\n",
            "113             FLAG_DOCUMENT_19    0.000000\n",
            "114             FLAG_DOCUMENT_20    0.000000\n",
            "115             FLAG_DOCUMENT_21    0.000000\n",
            "32    WEEKDAY_APPR_PROCESS_START    0.000000\n",
            "31   REGION_RATING_CLIENT_W_CITY    0.000000\n",
            "37        REG_CITY_NOT_LIVE_CITY    0.000000\n",
            "16    REGION_POPULATION_RELATIVE    0.000000\n",
            "14            NAME_FAMILY_STATUS    0.000000\n",
            "15             NAME_HOUSING_TYPE    0.000000\n",
            "30          REGION_RATING_CLIENT    0.000000\n",
            "17                    DAYS_BIRTH    0.000000\n",
            "18                 DAYS_EMPLOYED    0.000000\n",
            "19             DAYS_REGISTRATION    0.000000\n",
            "20               DAYS_ID_PUBLISH    0.000000\n",
            "8                     AMT_CREDIT    0.000000\n",
            "7               AMT_INCOME_TOTAL    0.000000\n",
            "13           NAME_EDUCATION_TYPE    0.000000\n",
            "6                   CNT_CHILDREN    0.000000\n",
            "4                   FLAG_OWN_CAR    0.000000\n",
            "3                    CODE_GENDER    0.000000\n",
            "22                    FLAG_MOBIL    0.000000\n",
            "23                FLAG_EMP_PHONE    0.000000\n",
            "24               FLAG_WORK_PHONE    0.000000\n",
            "2             NAME_CONTRACT_TYPE    0.000000\n",
            "25              FLAG_CONT_MOBILE    0.000000\n",
            "26                    FLAG_PHONE    0.000000\n",
            "27                    FLAG_EMAIL    0.000000\n",
            "1                         TARGET    0.000000\n",
            "5                FLAG_OWN_REALTY    0.000000\n",
            "12              NAME_INCOME_TYPE    0.000000\n",
            "95        DAYS_LAST_PHONE_CHANGE    0.000325\n",
            "29               CNT_FAM_MEMBERS    0.000650\n",
            "9                    AMT_ANNUITY    0.003902\n",
            "10               AMT_GOODS_PRICE    0.090403\n",
            "42                  EXT_SOURCE_2    0.214626\n",
            "94      DEF_60_CNT_SOCIAL_CIRCLE    0.332021\n",
            "93      OBS_60_CNT_SOCIAL_CIRCLE    0.332021\n",
            "92      DEF_30_CNT_SOCIAL_CIRCLE    0.332021\n",
            "91      OBS_30_CNT_SOCIAL_CIRCLE    0.332021\n",
            "11               NAME_TYPE_SUITE    0.420148\n",
            "120    AMT_REQ_CREDIT_BUREAU_QRT   13.501631\n",
            "116   AMT_REQ_CREDIT_BUREAU_HOUR   13.501631\n",
            "117    AMT_REQ_CREDIT_BUREAU_DAY   13.501631\n",
            "118   AMT_REQ_CREDIT_BUREAU_WEEK   13.501631\n",
            "119    AMT_REQ_CREDIT_BUREAU_MON   13.501631\n",
            "121   AMT_REQ_CREDIT_BUREAU_YEAR   13.501631\n",
            "43                  EXT_SOURCE_3   19.825307\n",
            "28               OCCUPATION_TYPE   31.345545\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "with pd.option_context('display.max_rows', None, 'display.max_columns', None):\n",
        "  df_clean.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CcS0hb8IhcTX",
        "outputId": "650295d2-7b1f-46cb-e079-dc1bf6e76300"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 307511 entries, 0 to 307510\n",
            "Data columns (total 73 columns):\n",
            " #   Column                       Non-Null Count   Dtype  \n",
            "---  ------                       --------------   -----  \n",
            " 0   SK_ID_CURR                   307511 non-null  int64  \n",
            " 1   TARGET                       307511 non-null  int64  \n",
            " 2   NAME_CONTRACT_TYPE           307511 non-null  object \n",
            " 3   CODE_GENDER                  307511 non-null  object \n",
            " 4   FLAG_OWN_CAR                 307511 non-null  object \n",
            " 5   FLAG_OWN_REALTY              307511 non-null  object \n",
            " 6   CNT_CHILDREN                 307511 non-null  int64  \n",
            " 7   AMT_INCOME_TOTAL             307511 non-null  float64\n",
            " 8   AMT_CREDIT                   307511 non-null  float64\n",
            " 9   AMT_ANNUITY                  307499 non-null  float64\n",
            " 10  AMT_GOODS_PRICE              307233 non-null  float64\n",
            " 11  NAME_TYPE_SUITE              306219 non-null  object \n",
            " 12  NAME_INCOME_TYPE             307511 non-null  object \n",
            " 13  NAME_EDUCATION_TYPE          307511 non-null  object \n",
            " 14  NAME_FAMILY_STATUS           307511 non-null  object \n",
            " 15  NAME_HOUSING_TYPE            307511 non-null  object \n",
            " 16  REGION_POPULATION_RELATIVE   307511 non-null  float64\n",
            " 17  DAYS_BIRTH                   307511 non-null  int64  \n",
            " 18  DAYS_EMPLOYED                307511 non-null  int64  \n",
            " 19  DAYS_REGISTRATION            307511 non-null  float64\n",
            " 20  DAYS_ID_PUBLISH              307511 non-null  int64  \n",
            " 21  FLAG_MOBIL                   307511 non-null  int64  \n",
            " 22  FLAG_EMP_PHONE               307511 non-null  int64  \n",
            " 23  FLAG_WORK_PHONE              307511 non-null  int64  \n",
            " 24  FLAG_CONT_MOBILE             307511 non-null  int64  \n",
            " 25  FLAG_PHONE                   307511 non-null  int64  \n",
            " 26  FLAG_EMAIL                   307511 non-null  int64  \n",
            " 27  OCCUPATION_TYPE              211120 non-null  object \n",
            " 28  CNT_FAM_MEMBERS              307509 non-null  float64\n",
            " 29  REGION_RATING_CLIENT         307511 non-null  int64  \n",
            " 30  REGION_RATING_CLIENT_W_CITY  307511 non-null  int64  \n",
            " 31  WEEKDAY_APPR_PROCESS_START   307511 non-null  object \n",
            " 32  HOUR_APPR_PROCESS_START      307511 non-null  int64  \n",
            " 33  REG_REGION_NOT_LIVE_REGION   307511 non-null  int64  \n",
            " 34  REG_REGION_NOT_WORK_REGION   307511 non-null  int64  \n",
            " 35  LIVE_REGION_NOT_WORK_REGION  307511 non-null  int64  \n",
            " 36  REG_CITY_NOT_LIVE_CITY       307511 non-null  int64  \n",
            " 37  REG_CITY_NOT_WORK_CITY       307511 non-null  int64  \n",
            " 38  LIVE_CITY_NOT_WORK_CITY      307511 non-null  int64  \n",
            " 39  ORGANIZATION_TYPE            307511 non-null  object \n",
            " 40  EXT_SOURCE_2                 306851 non-null  float64\n",
            " 41  EXT_SOURCE_3                 246546 non-null  float64\n",
            " 42  OBS_30_CNT_SOCIAL_CIRCLE     306490 non-null  float64\n",
            " 43  DEF_30_CNT_SOCIAL_CIRCLE     306490 non-null  float64\n",
            " 44  OBS_60_CNT_SOCIAL_CIRCLE     306490 non-null  float64\n",
            " 45  DEF_60_CNT_SOCIAL_CIRCLE     306490 non-null  float64\n",
            " 46  DAYS_LAST_PHONE_CHANGE       307510 non-null  float64\n",
            " 47  FLAG_DOCUMENT_2              307511 non-null  int64  \n",
            " 48  FLAG_DOCUMENT_3              307511 non-null  int64  \n",
            " 49  FLAG_DOCUMENT_4              307511 non-null  int64  \n",
            " 50  FLAG_DOCUMENT_5              307511 non-null  int64  \n",
            " 51  FLAG_DOCUMENT_6              307511 non-null  int64  \n",
            " 52  FLAG_DOCUMENT_7              307511 non-null  int64  \n",
            " 53  FLAG_DOCUMENT_8              307511 non-null  int64  \n",
            " 54  FLAG_DOCUMENT_9              307511 non-null  int64  \n",
            " 55  FLAG_DOCUMENT_10             307511 non-null  int64  \n",
            " 56  FLAG_DOCUMENT_11             307511 non-null  int64  \n",
            " 57  FLAG_DOCUMENT_12             307511 non-null  int64  \n",
            " 58  FLAG_DOCUMENT_13             307511 non-null  int64  \n",
            " 59  FLAG_DOCUMENT_14             307511 non-null  int64  \n",
            " 60  FLAG_DOCUMENT_15             307511 non-null  int64  \n",
            " 61  FLAG_DOCUMENT_16             307511 non-null  int64  \n",
            " 62  FLAG_DOCUMENT_17             307511 non-null  int64  \n",
            " 63  FLAG_DOCUMENT_18             307511 non-null  int64  \n",
            " 64  FLAG_DOCUMENT_19             307511 non-null  int64  \n",
            " 65  FLAG_DOCUMENT_20             307511 non-null  int64  \n",
            " 66  FLAG_DOCUMENT_21             307511 non-null  int64  \n",
            " 67  AMT_REQ_CREDIT_BUREAU_HOUR   265992 non-null  float64\n",
            " 68  AMT_REQ_CREDIT_BUREAU_DAY    265992 non-null  float64\n",
            " 69  AMT_REQ_CREDIT_BUREAU_WEEK   265992 non-null  float64\n",
            " 70  AMT_REQ_CREDIT_BUREAU_MON    265992 non-null  float64\n",
            " 71  AMT_REQ_CREDIT_BUREAU_QRT    265992 non-null  float64\n",
            " 72  AMT_REQ_CREDIT_BUREAU_YEAR   265992 non-null  float64\n",
            "dtypes: float64(20), int64(41), object(12)\n",
            "memory usage: 171.3+ MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# from imblearn.over_sampling import SMOTE\n",
        "# sm = SMOTE(random_state=42)\n",
        "#  = sm.fit_resample(x,y)"
      ],
      "metadata": {
        "id": "pxxCghfOeCR8"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# cols for encoding\n",
        "sel_cols = list(df_clean.select_dtypes(include='object'))\n",
        "sel_cols\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "X_ycsCgkeCNH",
        "outputId": "785deb02-6afb-4439-dd06-6e8239fe45b3"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['NAME_CONTRACT_TYPE',\n",
              " 'CODE_GENDER',\n",
              " 'FLAG_OWN_CAR',\n",
              " 'FLAG_OWN_REALTY',\n",
              " 'NAME_TYPE_SUITE',\n",
              " 'NAME_INCOME_TYPE',\n",
              " 'NAME_EDUCATION_TYPE',\n",
              " 'NAME_FAMILY_STATUS',\n",
              " 'NAME_HOUSING_TYPE',\n",
              " 'OCCUPATION_TYPE',\n",
              " 'WEEKDAY_APPR_PROCESS_START',\n",
              " 'ORGANIZATION_TYPE']"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Find and fill Nan"
      ],
      "metadata": {
        "id": "0CsCE8GQ5emI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "# find the col that have non zero null values and require necoding\n",
        "# foor the reaminaing cols having non zero percentage we set na to 0\n",
        "\n",
        "checklist = list(total[total['percentage'] > 0].col_name )\n",
        "\n",
        "for sel_col in sel_cols:\n",
        "  print(f\"{sel_col =}\")\n",
        "  if sel_col in checklist:\n",
        "    print(f\"obj type col {sel_col =} removing from checklist\")\n",
        "    checklist.remove(sel_col)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Dd17lUEJeCKm",
        "outputId": "2ab1bd71-ad15-44c1-ed8c-7feb87202c78"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "sel_col ='NAME_CONTRACT_TYPE'\n",
            "sel_col ='CODE_GENDER'\n",
            "sel_col ='FLAG_OWN_CAR'\n",
            "sel_col ='FLAG_OWN_REALTY'\n",
            "sel_col ='NAME_TYPE_SUITE'\n",
            "obj type col sel_col ='NAME_TYPE_SUITE' removing from checklist\n",
            "sel_col ='NAME_INCOME_TYPE'\n",
            "sel_col ='NAME_EDUCATION_TYPE'\n",
            "sel_col ='NAME_FAMILY_STATUS'\n",
            "sel_col ='NAME_HOUSING_TYPE'\n",
            "sel_col ='OCCUPATION_TYPE'\n",
            "obj type col sel_col ='OCCUPATION_TYPE' removing from checklist\n",
            "sel_col ='WEEKDAY_APPR_PROCESS_START'\n",
            "sel_col ='ORGANIZATION_TYPE'\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df_clean.NAME_TYPE_SUITE.value_counts()"
      ],
      "metadata": {
        "id": "i5fKUMGweCHR",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "24f2a3f2-b4f2-4f18-8308-48d0366c725e"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Unaccompanied      248526\n",
              "Family              40149\n",
              "Spouse, partner     11370\n",
              "Children             3267\n",
              "Other_B              1770\n",
              "Other_A               866\n",
              "Group of people       271\n",
              "Name: NAME_TYPE_SUITE, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "checklist"
      ],
      "metadata": {
        "id": "g3epJ68DeCCe",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6b2d8286-a459-4a5e-93e8-e1f5b7ecefcf"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['AMT_ANNUITY',\n",
              " 'AMT_GOODS_PRICE',\n",
              " 'CNT_FAM_MEMBERS',\n",
              " 'EXT_SOURCE_2',\n",
              " 'EXT_SOURCE_3',\n",
              " 'OBS_30_CNT_SOCIAL_CIRCLE',\n",
              " 'DEF_30_CNT_SOCIAL_CIRCLE',\n",
              " 'OBS_60_CNT_SOCIAL_CIRCLE',\n",
              " 'DEF_60_CNT_SOCIAL_CIRCLE',\n",
              " 'DAYS_LAST_PHONE_CHANGE',\n",
              " 'AMT_REQ_CREDIT_BUREAU_HOUR',\n",
              " 'AMT_REQ_CREDIT_BUREAU_DAY',\n",
              " 'AMT_REQ_CREDIT_BUREAU_WEEK',\n",
              " 'AMT_REQ_CREDIT_BUREAU_MON',\n",
              " 'AMT_REQ_CREDIT_BUREAU_QRT',\n",
              " 'AMT_REQ_CREDIT_BUREAU_YEAR']"
            ]
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "proc_df =df_clean.copy()\n",
        "\n",
        "for col_name in checklist:\n",
        "  print(f\" processing { col_name = }\")\n",
        "  proc_df[col_name].fillna(0,inplace=True)\n",
        "\n",
        "sanity = (proc_df.isnull().sum()/proc_df.shape[0])*100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wygmMCPX6rzy",
        "outputId": "b8297d60-eda8-4820-f1c1-df5788ba50f6"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " processing  col_name = 'AMT_ANNUITY'\n",
            " processing  col_name = 'AMT_GOODS_PRICE'\n",
            " processing  col_name = 'CNT_FAM_MEMBERS'\n",
            " processing  col_name = 'EXT_SOURCE_2'\n",
            " processing  col_name = 'EXT_SOURCE_3'\n",
            " processing  col_name = 'OBS_30_CNT_SOCIAL_CIRCLE'\n",
            " processing  col_name = 'DEF_30_CNT_SOCIAL_CIRCLE'\n",
            " processing  col_name = 'OBS_60_CNT_SOCIAL_CIRCLE'\n",
            " processing  col_name = 'DEF_60_CNT_SOCIAL_CIRCLE'\n",
            " processing  col_name = 'DAYS_LAST_PHONE_CHANGE'\n",
            " processing  col_name = 'AMT_REQ_CREDIT_BUREAU_HOUR'\n",
            " processing  col_name = 'AMT_REQ_CREDIT_BUREAU_DAY'\n",
            " processing  col_name = 'AMT_REQ_CREDIT_BUREAU_WEEK'\n",
            " processing  col_name = 'AMT_REQ_CREDIT_BUREAU_MON'\n",
            " processing  col_name = 'AMT_REQ_CREDIT_BUREAU_QRT'\n",
            " processing  col_name = 'AMT_REQ_CREDIT_BUREAU_YEAR'\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "sanity"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fNefBZlp7kA8",
        "outputId": "c91953c6-1198-4549-db0e-a283e14ca01e"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "SK_ID_CURR                    0.0\n",
              "TARGET                        0.0\n",
              "NAME_CONTRACT_TYPE            0.0\n",
              "CODE_GENDER                   0.0\n",
              "FLAG_OWN_CAR                  0.0\n",
              "                             ... \n",
              "AMT_REQ_CREDIT_BUREAU_DAY     0.0\n",
              "AMT_REQ_CREDIT_BUREAU_WEEK    0.0\n",
              "AMT_REQ_CREDIT_BUREAU_MON     0.0\n",
              "AMT_REQ_CREDIT_BUREAU_QRT     0.0\n",
              "AMT_REQ_CREDIT_BUREAU_YEAR    0.0\n",
              "Length: 73, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# adding dummies\n",
        "cols_1 = pd.get_dummies(proc_df.NAME_TYPE_SUITE, prefix = \"NAME_TYPE_SUITE\")\n",
        "cols_2 = pd.get_dummies(proc_df.OCCUPATION_TYPE, prefix = \"OCCUPATION_TYPE\")"
      ],
      "metadata": {
        "id": "K01wO1cN76ui"
      },
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "proc_df = pd.concat([proc_df,cols_1,cols_2],axis = 1)"
      ],
      "metadata": {
        "id": "BD8dXtpe_Crs"
      },
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "proc_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "FwV3PbFUos9O",
        "outputId": "427ece1a-f6bf-470f-a726-bfe6c6262545"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        SK_ID_CURR  TARGET NAME_CONTRACT_TYPE CODE_GENDER FLAG_OWN_CAR  \\\n",
              "0           100002       1         Cash loans           M            N   \n",
              "1           100003       0         Cash loans           F            N   \n",
              "2           100004       0    Revolving loans           M            Y   \n",
              "3           100006       0         Cash loans           F            N   \n",
              "4           100007       0         Cash loans           M            N   \n",
              "...            ...     ...                ...         ...          ...   \n",
              "307506      456251       0         Cash loans           M            N   \n",
              "307507      456252       0         Cash loans           F            N   \n",
              "307508      456253       0         Cash loans           F            N   \n",
              "307509      456254       1         Cash loans           F            N   \n",
              "307510      456255       0         Cash loans           F            N   \n",
              "\n",
              "       FLAG_OWN_REALTY  CNT_CHILDREN  AMT_INCOME_TOTAL  AMT_CREDIT  \\\n",
              "0                    Y             0          202500.0    406597.5   \n",
              "1                    N             0          270000.0   1293502.5   \n",
              "2                    Y             0           67500.0    135000.0   \n",
              "3                    Y             0          135000.0    312682.5   \n",
              "4                    Y             0          121500.0    513000.0   \n",
              "...                ...           ...               ...         ...   \n",
              "307506               N             0          157500.0    254700.0   \n",
              "307507               Y             0           72000.0    269550.0   \n",
              "307508               Y             0          153000.0    677664.0   \n",
              "307509               Y             0          171000.0    370107.0   \n",
              "307510               N             0          157500.0    675000.0   \n",
              "\n",
              "        AMT_ANNUITY  ...  OCCUPATION_TYPE_Laborers  \\\n",
              "0           24700.5  ...                         1   \n",
              "1           35698.5  ...                         0   \n",
              "2            6750.0  ...                         1   \n",
              "3           29686.5  ...                         1   \n",
              "4           21865.5  ...                         0   \n",
              "...             ...  ...                       ...   \n",
              "307506      27558.0  ...                         0   \n",
              "307507      12001.5  ...                         0   \n",
              "307508      29979.0  ...                         0   \n",
              "307509      20205.0  ...                         1   \n",
              "307510      49117.5  ...                         1   \n",
              "\n",
              "       OCCUPATION_TYPE_Low-skill Laborers OCCUPATION_TYPE_Managers  \\\n",
              "0                                       0                        0   \n",
              "1                                       0                        0   \n",
              "2                                       0                        0   \n",
              "3                                       0                        0   \n",
              "4                                       0                        0   \n",
              "...                                   ...                      ...   \n",
              "307506                                  0                        0   \n",
              "307507                                  0                        0   \n",
              "307508                                  0                        1   \n",
              "307509                                  0                        0   \n",
              "307510                                  0                        0   \n",
              "\n",
              "       OCCUPATION_TYPE_Medicine staff OCCUPATION_TYPE_Private service staff  \\\n",
              "0                                   0                                     0   \n",
              "1                                   0                                     0   \n",
              "2                                   0                                     0   \n",
              "3                                   0                                     0   \n",
              "4                                   0                                     0   \n",
              "...                               ...                                   ...   \n",
              "307506                              0                                     0   \n",
              "307507                              0                                     0   \n",
              "307508                              0                                     0   \n",
              "307509                              0                                     0   \n",
              "307510                              0                                     0   \n",
              "\n",
              "       OCCUPATION_TYPE_Realty agents  OCCUPATION_TYPE_Sales staff  \\\n",
              "0                                  0                            0   \n",
              "1                                  0                            0   \n",
              "2                                  0                            0   \n",
              "3                                  0                            0   \n",
              "4                                  0                            0   \n",
              "...                              ...                          ...   \n",
              "307506                             0                            1   \n",
              "307507                             0                            0   \n",
              "307508                             0                            0   \n",
              "307509                             0                            0   \n",
              "307510                             0                            0   \n",
              "\n",
              "        OCCUPATION_TYPE_Secretaries  OCCUPATION_TYPE_Security staff  \\\n",
              "0                                 0                               0   \n",
              "1                                 0                               0   \n",
              "2                                 0                               0   \n",
              "3                                 0                               0   \n",
              "4                                 0                               0   \n",
              "...                             ...                             ...   \n",
              "307506                            0                               0   \n",
              "307507                            0                               0   \n",
              "307508                            0                               0   \n",
              "307509                            0                               0   \n",
              "307510                            0                               0   \n",
              "\n",
              "        OCCUPATION_TYPE_Waiters/barmen staff  \n",
              "0                                          0  \n",
              "1                                          0  \n",
              "2                                          0  \n",
              "3                                          0  \n",
              "4                                          0  \n",
              "...                                      ...  \n",
              "307506                                     0  \n",
              "307507                                     0  \n",
              "307508                                     0  \n",
              "307509                                     0  \n",
              "307510                                     0  \n",
              "\n",
              "[307511 rows x 98 columns]"
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-09a2dd84-45aa-47b0-9f0b-ebac7f30a937\" class=\"colab-df-container\">\n",
              "    <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SK_ID_CURR</th>\n",
              "      <th>TARGET</th>\n",
              "      <th>NAME_CONTRACT_TYPE</th>\n",
              "      <th>CODE_GENDER</th>\n",
              "      <th>FLAG_OWN_CAR</th>\n",
              "      <th>FLAG_OWN_REALTY</th>\n",
              "      <th>CNT_CHILDREN</th>\n",
              "      <th>AMT_INCOME_TOTAL</th>\n",
              "      <th>AMT_CREDIT</th>\n",
              "      <th>AMT_ANNUITY</th>\n",
              "      <th>...</th>\n",
              "      <th>OCCUPATION_TYPE_Laborers</th>\n",
              "      <th>OCCUPATION_TYPE_Low-skill Laborers</th>\n",
              "      <th>OCCUPATION_TYPE_Managers</th>\n",
              "      <th>OCCUPATION_TYPE_Medicine staff</th>\n",
              "      <th>OCCUPATION_TYPE_Private service staff</th>\n",
              "      <th>OCCUPATION_TYPE_Realty agents</th>\n",
              "      <th>OCCUPATION_TYPE_Sales staff</th>\n",
              "      <th>OCCUPATION_TYPE_Secretaries</th>\n",
              "      <th>OCCUPATION_TYPE_Security staff</th>\n",
              "      <th>OCCUPATION_TYPE_Waiters/barmen staff</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>100002</td>\n",
              "      <td>1</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>M</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>202500.0</td>\n",
              "      <td>406597.5</td>\n",
              "      <td>24700.5</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>100003</td>\n",
              "      <td>0</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>F</td>\n",
              "      <td>N</td>\n",
              "      <td>N</td>\n",
              "      <td>0</td>\n",
              "      <td>270000.0</td>\n",
              "      <td>1293502.5</td>\n",
              "      <td>35698.5</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>100004</td>\n",
              "      <td>0</td>\n",
              "      <td>Revolving loans</td>\n",
              "      <td>M</td>\n",
              "      <td>Y</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>67500.0</td>\n",
              "      <td>135000.0</td>\n",
              "      <td>6750.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>100006</td>\n",
              "      <td>0</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>F</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>135000.0</td>\n",
              "      <td>312682.5</td>\n",
              "      <td>29686.5</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>100007</td>\n",
              "      <td>0</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>M</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>121500.0</td>\n",
              "      <td>513000.0</td>\n",
              "      <td>21865.5</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>307506</th>\n",
              "      <td>456251</td>\n",
              "      <td>0</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>M</td>\n",
              "      <td>N</td>\n",
              "      <td>N</td>\n",
              "      <td>0</td>\n",
              "      <td>157500.0</td>\n",
              "      <td>254700.0</td>\n",
              "      <td>27558.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>307507</th>\n",
              "      <td>456252</td>\n",
              "      <td>0</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>F</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>72000.0</td>\n",
              "      <td>269550.0</td>\n",
              "      <td>12001.5</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>307508</th>\n",
              "      <td>456253</td>\n",
              "      <td>0</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>F</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>153000.0</td>\n",
              "      <td>677664.0</td>\n",
              "      <td>29979.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>307509</th>\n",
              "      <td>456254</td>\n",
              "      <td>1</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>F</td>\n",
              "      <td>N</td>\n",
              "      <td>Y</td>\n",
              "      <td>0</td>\n",
              "      <td>171000.0</td>\n",
              "      <td>370107.0</td>\n",
              "      <td>20205.0</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>307510</th>\n",
              "      <td>456255</td>\n",
              "      <td>0</td>\n",
              "      <td>Cash loans</td>\n",
              "      <td>F</td>\n",
              "      <td>N</td>\n",
              "      <td>N</td>\n",
              "      <td>0</td>\n",
              "      <td>157500.0</td>\n",
              "      <td>675000.0</td>\n",
              "      <td>49117.5</td>\n",
              "      <td>...</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>307511 rows × 98 columns</p>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
              "\n",
              "  <div class=\"colab-df-container\">\n",
              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-09a2dd84-45aa-47b0-9f0b-ebac7f30a937')\"\n",
              "            title=\"Convert this dataframe to an interactive table.\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\" viewBox=\"0 -960 960 960\">\n",
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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-09a2dd84-45aa-47b0-9f0b-ebac7f30a937 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-09a2dd84-45aa-47b0-9f0b-ebac7f30a937');\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-91b576b9-76f3-4bc8-94a0-f0fb3c7c8941\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-91b576b9-76f3-4bc8-94a0-f0fb3c7c8941')\"\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-91b576b9-76f3-4bc8-94a0-f0fb3c7c8941 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": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "proc_df = proc_df.drop(['OCCUPATION_TYPE','NAME_TYPE_SUITE'], axis = 'columns')"
      ],
      "metadata": {
        "id": "-a_QOva__aKa"
      },
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Find all object dtype cols"
      ],
      "metadata": {
        "id": "TxlGwm1I5RCT"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "sel_cols = list(proc_df.select_dtypes(include='object'))\n",
        "sel_cols"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "i46J2yDopIVa",
        "outputId": "65ecb067-2d9c-4a3b-8466-0c303d35f79e"
      },
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['NAME_CONTRACT_TYPE',\n",
              " 'CODE_GENDER',\n",
              " 'FLAG_OWN_CAR',\n",
              " 'FLAG_OWN_REALTY',\n",
              " 'NAME_INCOME_TYPE',\n",
              " 'NAME_EDUCATION_TYPE',\n",
              " 'NAME_FAMILY_STATUS',\n",
              " 'NAME_HOUSING_TYPE',\n",
              " 'WEEKDAY_APPR_PROCESS_START',\n",
              " 'ORGANIZATION_TYPE']"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "for sel_col in sel_cols:\n",
        "  print(f\" {sel_col = }  \")\n",
        "  print(f\"{ proc_df[sel_col].value_counts() }\\n\")\n",
        "  print(f\"{'--' * 20}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wGxWIwVxqxi2",
        "outputId": "50007ffa-a5f5-4db1-f624-583adc9219ff"
      },
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " sel_col = 'NAME_CONTRACT_TYPE'  \n",
            "Cash loans         278232\n",
            "Revolving loans     29279\n",
            "Name: NAME_CONTRACT_TYPE, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'CODE_GENDER'  \n",
            "F      202448\n",
            "M      105059\n",
            "XNA         4\n",
            "Name: CODE_GENDER, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'FLAG_OWN_CAR'  \n",
            "N    202924\n",
            "Y    104587\n",
            "Name: FLAG_OWN_CAR, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'FLAG_OWN_REALTY'  \n",
            "Y    213312\n",
            "N     94199\n",
            "Name: FLAG_OWN_REALTY, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'NAME_INCOME_TYPE'  \n",
            "Working                 158774\n",
            "Commercial associate     71617\n",
            "Pensioner                55362\n",
            "State servant            21703\n",
            "Unemployed                  22\n",
            "Student                     18\n",
            "Businessman                 10\n",
            "Maternity leave              5\n",
            "Name: NAME_INCOME_TYPE, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'NAME_EDUCATION_TYPE'  \n",
            "Secondary / secondary special    218391\n",
            "Higher education                  74863\n",
            "Incomplete higher                 10277\n",
            "Lower secondary                    3816\n",
            "Academic degree                     164\n",
            "Name: NAME_EDUCATION_TYPE, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'NAME_FAMILY_STATUS'  \n",
            "Married                 196432\n",
            "Single / not married     45444\n",
            "Civil marriage           29775\n",
            "Separated                19770\n",
            "Widow                    16088\n",
            "Unknown                      2\n",
            "Name: NAME_FAMILY_STATUS, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'NAME_HOUSING_TYPE'  \n",
            "House / apartment      272868\n",
            "With parents            14840\n",
            "Municipal apartment     11183\n",
            "Rented apartment         4881\n",
            "Office apartment         2617\n",
            "Co-op apartment          1122\n",
            "Name: NAME_HOUSING_TYPE, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'WEEKDAY_APPR_PROCESS_START'  \n",
            "TUESDAY      53901\n",
            "WEDNESDAY    51934\n",
            "MONDAY       50714\n",
            "THURSDAY     50591\n",
            "FRIDAY       50338\n",
            "SATURDAY     33852\n",
            "SUNDAY       16181\n",
            "Name: WEEKDAY_APPR_PROCESS_START, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'ORGANIZATION_TYPE'  \n",
            "Business Entity Type 3    67992\n",
            "XNA                       55374\n",
            "Self-employed             38412\n",
            "Other                     16683\n",
            "Medicine                  11193\n",
            "Business Entity Type 2    10553\n",
            "Government                10404\n",
            "School                     8893\n",
            "Trade: type 7              7831\n",
            "Kindergarten               6880\n",
            "Construction               6721\n",
            "Business Entity Type 1     5984\n",
            "Transport: type 4          5398\n",
            "Trade: type 3              3492\n",
            "Industry: type 9           3368\n",
            "Industry: type 3           3278\n",
            "Security                   3247\n",
            "Housing                    2958\n",
            "Industry: type 11          2704\n",
            "Military                   2634\n",
            "Bank                       2507\n",
            "Agriculture                2454\n",
            "Police                     2341\n",
            "Transport: type 2          2204\n",
            "Postal                     2157\n",
            "Security Ministries        1974\n",
            "Trade: type 2              1900\n",
            "Restaurant                 1811\n",
            "Services                   1575\n",
            "University                 1327\n",
            "Industry: type 7           1307\n",
            "Transport: type 3          1187\n",
            "Industry: type 1           1039\n",
            "Hotel                       966\n",
            "Electricity                 950\n",
            "Industry: type 4            877\n",
            "Trade: type 6               631\n",
            "Industry: type 5            599\n",
            "Insurance                   597\n",
            "Telecom                     577\n",
            "Emergency                   560\n",
            "Industry: type 2            458\n",
            "Advertising                 429\n",
            "Realtor                     396\n",
            "Culture                     379\n",
            "Industry: type 12           369\n",
            "Trade: type 1               348\n",
            "Mobile                      317\n",
            "Legal Services              305\n",
            "Cleaning                    260\n",
            "Transport: type 1           201\n",
            "Industry: type 6            112\n",
            "Industry: type 10           109\n",
            "Religion                     85\n",
            "Industry: type 13            67\n",
            "Trade: type 4                64\n",
            "Trade: type 5                49\n",
            "Industry: type 8             24\n",
            "Name: ORGANIZATION_TYPE, dtype: int64\n",
            "\n",
            "----------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "proc_df[['oc_1','oc_2']] = proc_df.ORGANIZATION_TYPE.str.split(\":\",expand = True)"
      ],
      "metadata": {
        "id": "kMSR58O5q0k_"
      },
      "execution_count": 34,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "proc_df['ORGANIZATION_TYPE'] = proc_df['oc_1']"
      ],
      "metadata": {
        "id": "6IWRG1s0q4PN"
      },
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "proc_df = proc_df.drop(['oc_2'],axis = 'columns')\n",
        "proc_df = proc_df.drop(['oc_1'], axis = 1)"
      ],
      "metadata": {
        "id": "Maixj_nd2TES"
      },
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Encoding all object dtype cols"
      ],
      "metadata": {
        "id": "VpwN9iuD5CoS"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "for sel_col in sel_cols:\n",
        "  print(f\" {sel_col = }  \")\n",
        "  print(f\"{ proc_df[sel_col].value_counts() }\\n\")\n",
        "  print(f\"{'--' * 20}\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bMZprZF02S8U",
        "outputId": "24c67a20-579e-4fbc-cf33-c4d9ba2d54b8"
      },
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            " sel_col = 'NAME_CONTRACT_TYPE'  \n",
            "Cash loans         278232\n",
            "Revolving loans     29279\n",
            "Name: NAME_CONTRACT_TYPE, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'CODE_GENDER'  \n",
            "F      202448\n",
            "M      105059\n",
            "XNA         4\n",
            "Name: CODE_GENDER, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'FLAG_OWN_CAR'  \n",
            "N    202924\n",
            "Y    104587\n",
            "Name: FLAG_OWN_CAR, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'FLAG_OWN_REALTY'  \n",
            "Y    213312\n",
            "N     94199\n",
            "Name: FLAG_OWN_REALTY, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'NAME_INCOME_TYPE'  \n",
            "Working                 158774\n",
            "Commercial associate     71617\n",
            "Pensioner                55362\n",
            "State servant            21703\n",
            "Unemployed                  22\n",
            "Student                     18\n",
            "Businessman                 10\n",
            "Maternity leave              5\n",
            "Name: NAME_INCOME_TYPE, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'NAME_EDUCATION_TYPE'  \n",
            "Secondary / secondary special    218391\n",
            "Higher education                  74863\n",
            "Incomplete higher                 10277\n",
            "Lower secondary                    3816\n",
            "Academic degree                     164\n",
            "Name: NAME_EDUCATION_TYPE, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'NAME_FAMILY_STATUS'  \n",
            "Married                 196432\n",
            "Single / not married     45444\n",
            "Civil marriage           29775\n",
            "Separated                19770\n",
            "Widow                    16088\n",
            "Unknown                      2\n",
            "Name: NAME_FAMILY_STATUS, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'NAME_HOUSING_TYPE'  \n",
            "House / apartment      272868\n",
            "With parents            14840\n",
            "Municipal apartment     11183\n",
            "Rented apartment         4881\n",
            "Office apartment         2617\n",
            "Co-op apartment          1122\n",
            "Name: NAME_HOUSING_TYPE, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'WEEKDAY_APPR_PROCESS_START'  \n",
            "TUESDAY      53901\n",
            "WEDNESDAY    51934\n",
            "MONDAY       50714\n",
            "THURSDAY     50591\n",
            "FRIDAY       50338\n",
            "SATURDAY     33852\n",
            "SUNDAY       16181\n",
            "Name: WEEKDAY_APPR_PROCESS_START, dtype: int64\n",
            "\n",
            "----------------------------------------\n",
            " sel_col = 'ORGANIZATION_TYPE'  \n",
            "Business Entity Type 3    67992\n",
            "XNA                       55374\n",
            "Self-employed             38412\n",
            "Other                     16683\n",
            "Trade                     14315\n",
            "Industry                  14311\n",
            "Medicine                  11193\n",
            "Business Entity Type 2    10553\n",
            "Government                10404\n",
            "Transport                  8990\n",
            "School                     8893\n",
            "Kindergarten               6880\n",
            "Construction               6721\n",
            "Business Entity Type 1     5984\n",
            "Security                   3247\n",
            "Housing                    2958\n",
            "Military                   2634\n",
            "Bank                       2507\n",
            "Agriculture                2454\n",
            "Police                     2341\n",
            "Postal                     2157\n",
            "Security Ministries        1974\n",
            "Restaurant                 1811\n",
            "Services                   1575\n",
            "University                 1327\n",
            "Hotel                       966\n",
            "Electricity                 950\n",
            "Insurance                   597\n",
            "Telecom                     577\n",
            "Emergency                   560\n",
            "Advertising                 429\n",
            "Realtor                     396\n",
            "Culture                     379\n",
            "Mobile                      317\n",
            "Legal Services              305\n",
            "Cleaning                    260\n",
            "Religion                     85\n",
            "Name: ORGANIZATION_TYPE, dtype: int64\n",
            "\n",
            "----------------------------------------\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "fin_proc_df = proc_df.copy()\n",
        "agg_list = [fin_proc_df]\n",
        "for sel_col in sel_cols:\n",
        "  to_add = pd.get_dummies(fin_proc_df[sel_col],prefix=sel_col)\n",
        "  agg_list.append(to_add)\n",
        "\n",
        "agg_list\n",
        "fin_proc_df = pd.concat(agg_list, axis =1)\n",
        "\n",
        "fin_proc_df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "LVaOavDJ2S5_",
        "outputId": "b3e6095d-7671-4017-bb76-aa4534ef4d79"
      },
      "execution_count": 38,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "        SK_ID_CURR  TARGET NAME_CONTRACT_TYPE CODE_GENDER FLAG_OWN_CAR  \\\n",
              "0           100002       1         Cash loans           M            N   \n",
              "1           100003       0         Cash loans           F            N   \n",
              "2           100004       0    Revolving loans           M            Y   \n",
              "3           100006       0         Cash loans           F            N   \n",
              "4           100007       0         Cash loans           M            N   \n",
              "...            ...     ...                ...         ...          ...   \n",
              "307506      456251       0         Cash loans           M            N   \n",
              "307507      456252       0         Cash loans           F            N   \n",
              "307508      456253       0         Cash loans           F            N   \n",
              "307509      456254       1         Cash loans           F            N   \n",
              "307510      456255       0         Cash loans           F            N   \n",
              "\n",
              "       FLAG_OWN_REALTY  CNT_CHILDREN  AMT_INCOME_TOTAL  AMT_CREDIT  \\\n",
              "0                    Y             0          202500.0    406597.5   \n",
              "1                    N             0          270000.0   1293502.5   \n",
              "2                    Y             0           67500.0    135000.0   \n",
              "3                    Y             0          135000.0    312682.5   \n",
              "4                    Y             0          121500.0    513000.0   \n",
              "...                ...           ...               ...         ...   \n",
              "307506               N             0          157500.0    254700.0   \n",
              "307507               Y             0           72000.0    269550.0   \n",
              "307508               Y             0          153000.0    677664.0   \n",
              "307509               Y             0          171000.0    370107.0   \n",
              "307510               N             0          157500.0    675000.0   \n",
              "\n",
              "        AMT_ANNUITY  ...  ORGANIZATION_TYPE_School ORGANIZATION_TYPE_Security  \\\n",
              "0           24700.5  ...                         0                          0   \n",
              "1           35698.5  ...                         1                          0   \n",
              "2            6750.0  ...                         0                          0   \n",
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              "307509      20205.0  ...                         0                          0   \n",
              "307510      49117.5  ...                         0                          0   \n",
              "\n",
              "       ORGANIZATION_TYPE_Security Ministries ORGANIZATION_TYPE_Self-employed  \\\n",
              "0                                          0                               0   \n",
              "1                                          0                               0   \n",
              "2                                          0                               0   \n",
              "3                                          0                               0   \n",
              "4                                          0                               0   \n",
              "...                                      ...                             ...   \n",
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              "307508                                     0                               0   \n",
              "307509                                     0                               0   \n",
              "307510                                     0                               0   \n",
              "\n",
              "       ORGANIZATION_TYPE_Services  ORGANIZATION_TYPE_Telecom  \\\n",
              "0                               0                          0   \n",
              "1                               0                          0   \n",
              "2                               0                          0   \n",
              "3                               0                          0   \n",
              "4                               0                          0   \n",
              "...                           ...                        ...   \n",
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              "307510                          0                          0   \n",
              "\n",
              "        ORGANIZATION_TYPE_Trade  ORGANIZATION_TYPE_Transport  \\\n",
              "0                             0                            0   \n",
              "1                             0                            0   \n",
              "2                             0                            0   \n",
              "3                             0                            0   \n",
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              "...                         ...                          ...   \n",
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              "0                                  0                      0  \n",
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              "[307511 rows x 174 columns]"
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              "      <th>SK_ID_CURR</th>\n",
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              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-b90e306c-25d7-4493-b667-bbf9e5b1cdb8');\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-af75c230-d60c-4c97-b731-974ac68445c9\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-af75c230-d60c-4c97-b731-974ac68445c9')\"\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-af75c230-d60c-4c97-b731-974ac68445c9 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": 38
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "fin_proc_df = fin_proc_df.drop(sel_cols, axis =1)"
      ],
      "metadata": {
        "id": "9BC8Mnyb4Lgk"
      },
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Imbalance check"
      ],
      "metadata": {
        "id": "djNvCi9P5rEU"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "(fin_proc_df.TARGET.value_counts()/fin_proc_df.shape[0]) *100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "RfkcGGA94LWv",
        "outputId": "3af75cd7-8bf6-4c29-d1a3-f15c8925dc67"
      },
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    91.927118\n",
              "1     8.072882\n",
              "Name: TARGET, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## SMOTE\n",
        "\n"
      ],
      "metadata": {
        "id": "rR0khdZ0q2Ox"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x = fin_proc_df.drop(columns=['TARGET'],axis=\"column\")\n",
        "y = fin_proc_df['TARGET']"
      ],
      "metadata": {
        "id": "497aQUG1q5Sx"
      },
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "x.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "WAl7yDvb6sR4",
        "outputId": "138c0d76-f4ef-42c2-d18c-7a457e05cff7"
      },
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.frame.DataFrame'>\n",
            "RangeIndex: 307511 entries, 0 to 307510\n",
            "Columns: 163 entries, SK_ID_CURR to ORGANIZATION_TYPE_XNA\n",
            "dtypes: float64(20), int64(40), uint8(103)\n",
            "memory usage: 171.0 MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "y.info()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LLMSDYGC6sPg",
        "outputId": "a4de11ca-8cbd-444f-ce18-e93f78711d3d"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "<class 'pandas.core.series.Series'>\n",
            "RangeIndex: 307511 entries, 0 to 307510\n",
            "Series name: TARGET\n",
            "Non-Null Count   Dtype\n",
            "--------------   -----\n",
            "307511 non-null  int64\n",
            "dtypes: int64(1)\n",
            "memory usage: 2.3 MB\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from imblearn.over_sampling import SMOTE\n",
        "sm = SMOTE(random_state=42)\n",
        "X_RES,Y_RES = sm.fit_resample(x,y)\n"
      ],
      "metadata": {
        "id": "wbuZbju56sM7"
      },
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "(Y_RES.value_counts()/X_RES.shape[0]) *100"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "d1aHTBMC8WFx",
        "outputId": "ae6b2495-62c2-4e40-a30c-8621d2bc6954"
      },
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1    50.0\n",
              "0    50.0\n",
              "Name: TARGET, dtype: float64"
            ]
          },
          "metadata": {},
          "execution_count": 45
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Train test split"
      ],
      "metadata": {
        "id": "EaILv0038FKI"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "x_train, x_test, y_train, y_test = train_test_split(X_RES, Y_RES, test_size=0.33)"
      ],
      "metadata": {
        "id": "9cBT4_Fz67FY"
      },
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y_test.value_counts()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "rZ516JlwLMmU",
        "outputId": "edf08962-26f6-4810-beea-83e4bd980e9b"
      },
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0    93318\n",
              "1    93255\n",
              "Name: TARGET, dtype: int64"
            ]
          },
          "metadata": {},
          "execution_count": 47
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "x_train.shape"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_E61Cl0v8Pqw",
        "outputId": "da1733be-e0ce-4fca-975f-e802ec5e37b7"
      },
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(378799, 163)"
            ]
          },
          "metadata": {},
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "348wizFo_wsn"
      },
      "execution_count": 48,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Nueral Net"
      ],
      "metadata": {
        "id": "K3jdpzKI8SKK"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "\n",
        "print(\"Num GPUs Available: \", len(tf.config.list_physical_devices('GPU')))\n",
        "gpus = tf.config.list_logical_devices('GPU')\n",
        "strategy = tf.distribute.MirroredStrategy(gpus)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8a8wdU8x_0_4",
        "outputId": "2ae6574f-350f-4cbe-fcfa-3f5a364a32c7"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Num GPUs Available:  1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "with strategy.scope():\n",
        "  model = Sequential(name=\"defaulter_nn\",)\n",
        "  # l1\n",
        "  model.add(Dense( 1024, activation='relu', input_shape=(x_train.shape[1],)))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "  # l2\n",
        "  model.add(Dense( 1024, activation='relu', input_shape=(x_train.shape[1],)))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "  # l3\n",
        "  model.add(Dense( 1024, activation='relu', input_shape=(x_train.shape[1],)))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "  # l4\n",
        "  model.add(Dense(512, activation='relu'))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "  # l5\n",
        "  model.add(Dense(512, activation='relu'))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "  # l6\n",
        "  model.add(Dense(128, activation='relu'))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "  # l7\n",
        "  model.add(Dense(128, activation='relu'))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "  # l8\n",
        "  model.add(Dense(128, activation='relu'))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "  # l9\n",
        "  model.add(Dense(64, activation='relu'))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "  # l10\n",
        "  model.add(Dense(64, activation='relu'))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "  # l11\n",
        "  model.add(Dense(64, activation='relu'))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "\n",
        "  # l12\n",
        "  model.add(Dense(32, activation='relu'))\n",
        "  model.add(Dropout(0.2))\n",
        "  model.add(tf.keras.layers.BatchNormalization(synchronized=True))\n",
        "\n",
        "  # out has 1 nueron because output is 0 or 1\n",
        "  model.add(Dense(1, activation='sigmoid'))\n",
        "  model.summary()\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "sdpNbIV48KgA",
        "outputId": "87febe87-1730-4dc9-8563-632a0dcc6e13"
      },
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"defaulter_nn\"\n",
            "_________________________________________________________________\n",
            " Layer (type)                Output Shape              Param #   \n",
            "=================================================================\n",
            " dense (Dense)               (None, 1024)              167936    \n",
            "                                                                 \n",
            " dropout (Dropout)           (None, 1024)              0         \n",
            "                                                                 \n",
            " batch_normalization (Batch  (None, 1024)              4096      \n",
            " Normalization)                                                  \n",
            "                                                                 \n",
            " dense_1 (Dense)             (None, 1024)              1049600   \n",
            "                                                                 \n",
            " dropout_1 (Dropout)         (None, 1024)              0         \n",
            "                                                                 \n",
            " batch_normalization_1 (Bat  (None, 1024)              4096      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dense_2 (Dense)             (None, 1024)              1049600   \n",
            "                                                                 \n",
            " dropout_2 (Dropout)         (None, 1024)              0         \n",
            "                                                                 \n",
            " batch_normalization_2 (Bat  (None, 1024)              4096      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dense_3 (Dense)             (None, 512)               524800    \n",
            "                                                                 \n",
            " dropout_3 (Dropout)         (None, 512)               0         \n",
            "                                                                 \n",
            " batch_normalization_3 (Bat  (None, 512)               2048      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dense_4 (Dense)             (None, 512)               262656    \n",
            "                                                                 \n",
            " dropout_4 (Dropout)         (None, 512)               0         \n",
            "                                                                 \n",
            " batch_normalization_4 (Bat  (None, 512)               2048      \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dense_5 (Dense)             (None, 128)               65664     \n",
            "                                                                 \n",
            " dropout_5 (Dropout)         (None, 128)               0         \n",
            "                                                                 \n",
            " batch_normalization_5 (Bat  (None, 128)               512       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dense_6 (Dense)             (None, 128)               16512     \n",
            "                                                                 \n",
            " dropout_6 (Dropout)         (None, 128)               0         \n",
            "                                                                 \n",
            " batch_normalization_6 (Bat  (None, 128)               512       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dense_7 (Dense)             (None, 128)               16512     \n",
            "                                                                 \n",
            " dropout_7 (Dropout)         (None, 128)               0         \n",
            "                                                                 \n",
            " batch_normalization_7 (Bat  (None, 128)               512       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dense_8 (Dense)             (None, 64)                8256      \n",
            "                                                                 \n",
            " dropout_8 (Dropout)         (None, 64)                0         \n",
            "                                                                 \n",
            " batch_normalization_8 (Bat  (None, 64)                256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dense_9 (Dense)             (None, 64)                4160      \n",
            "                                                                 \n",
            " dropout_9 (Dropout)         (None, 64)                0         \n",
            "                                                                 \n",
            " batch_normalization_9 (Bat  (None, 64)                256       \n",
            " chNormalization)                                                \n",
            "                                                                 \n",
            " dense_10 (Dense)            (None, 64)                4160      \n",
            "                                                                 \n",
            " dropout_10 (Dropout)        (None, 64)                0         \n",
            "                                                                 \n",
            " batch_normalization_10 (Ba  (None, 64)                256       \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " dense_11 (Dense)            (None, 32)                2080      \n",
            "                                                                 \n",
            " dropout_11 (Dropout)        (None, 32)                0         \n",
            "                                                                 \n",
            " batch_normalization_11 (Ba  (None, 32)                128       \n",
            " tchNormalization)                                               \n",
            "                                                                 \n",
            " dense_12 (Dense)            (None, 1)                 33        \n",
            "                                                                 \n",
            "=================================================================\n",
            "Total params: 3190785 (12.17 MB)\n",
            "Trainable params: 3181377 (12.14 MB)\n",
            "Non-trainable params: 9408 (36.75 KB)\n",
            "_________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from keras.optimizers import Adam, Nadam\n",
        "\n",
        "model.compile(loss='binary_crossentropy',\n",
        "              optimizer=Nadam(lr=0.05),\n",
        "              metrics=['accuracy','Precision','Recall','AUC'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CdA2rlqB8Kd8",
        "outputId": "13926db4-351b-4249-fe21-2aa5faea9d0f"
      },
      "execution_count": 54,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "WARNING:absl:`lr` is deprecated in Keras optimizer, please use `learning_rate` or use the legacy optimizer, e.g.,tf.keras.optimizers.legacy.Nadam.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "batch_size = 40000\n",
        "epochs = 2000\n",
        "with strategy.scope():\n",
        "  history = model.fit(x_train, y_train,\n",
        "                      batch_size=batch_size,\n",
        "                      epochs=epochs,\n",
        "                      validation_data=(x_test, y_test))\n",
        "# Model Eval\n",
        "score = model.evaluate(x_test, y_test, verbose=0)\n",
        "for i in range(len(score)):\n",
        "    print(f'{model.metrics_names[i]} — -> {score[i]}')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dDRXbj0h8Kbu",
        "outputId": "a9a80f85-0b62-428d-8eee-0a30ffe5d120"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/2000\n",
            "10/10 [==============================] - 21s 461ms/step - loss: 0.3078 - accuracy: 0.8727 - precision: 0.8593 - recall: 0.8913 - auc: 0.9426 - val_loss: 0.4896 - val_accuracy: 0.7910 - val_precision: 0.7110 - val_recall: 0.9804 - val_auc: 0.9062\n",
            "Epoch 2/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.2532 - accuracy: 0.8947 - precision: 0.8828 - recall: 0.9103 - auc: 0.9602 - val_loss: 0.5323 - val_accuracy: 0.7752 - val_precision: 0.6939 - val_recall: 0.9848 - val_auc: 0.8996\n",
            "Epoch 3/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2507 - accuracy: 0.8961 - precision: 0.8840 - recall: 0.9118 - auc: 0.9609 - val_loss: 0.4870 - val_accuracy: 0.7929 - val_precision: 0.7125 - val_recall: 0.9817 - val_auc: 0.9080\n",
            "Epoch 4/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2508 - accuracy: 0.8950 - precision: 0.8823 - recall: 0.9117 - auc: 0.9609 - val_loss: 0.5048 - val_accuracy: 0.7926 - val_precision: 0.7124 - val_recall: 0.9810 - val_auc: 0.9023\n",
            "Epoch 5/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2481 - accuracy: 0.8970 - precision: 0.8841 - recall: 0.9139 - auc: 0.9617 - val_loss: 0.4847 - val_accuracy: 0.8043 - val_precision: 0.7261 - val_recall: 0.9768 - val_auc: 0.9050\n",
            "Epoch 6/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2505 - accuracy: 0.8954 - precision: 0.8834 - recall: 0.9111 - auc: 0.9609 - val_loss: 0.4864 - val_accuracy: 0.8045 - val_precision: 0.7269 - val_recall: 0.9753 - val_auc: 0.9019\n",
            "Epoch 7/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.2457 - accuracy: 0.8982 - precision: 0.8860 - recall: 0.9140 - auc: 0.9625 - val_loss: 0.4786 - val_accuracy: 0.8116 - val_precision: 0.7382 - val_recall: 0.9652 - val_auc: 0.8948\n",
            "Epoch 8/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2437 - accuracy: 0.8989 - precision: 0.8886 - recall: 0.9121 - auc: 0.9631 - val_loss: 0.5139 - val_accuracy: 0.8021 - val_precision: 0.7258 - val_recall: 0.9709 - val_auc: 0.8862\n",
            "Epoch 9/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.2448 - accuracy: 0.8978 - precision: 0.8861 - recall: 0.9131 - auc: 0.9628 - val_loss: 0.5060 - val_accuracy: 0.8080 - val_precision: 0.7323 - val_recall: 0.9707 - val_auc: 0.8922\n",
            "Epoch 10/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2455 - accuracy: 0.8973 - precision: 0.8849 - recall: 0.9135 - auc: 0.9626 - val_loss: 0.4985 - val_accuracy: 0.8125 - val_precision: 0.7382 - val_recall: 0.9682 - val_auc: 0.8917\n",
            "Epoch 11/2000\n",
            "10/10 [==============================] - 5s 480ms/step - loss: 0.2478 - accuracy: 0.8972 - precision: 0.8877 - recall: 0.9095 - auc: 0.9618 - val_loss: 0.5020 - val_accuracy: 0.8056 - val_precision: 0.7287 - val_recall: 0.9734 - val_auc: 0.8958\n",
            "Epoch 12/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.2442 - accuracy: 0.8986 - precision: 0.8873 - recall: 0.9132 - auc: 0.9630 - val_loss: 0.5041 - val_accuracy: 0.8086 - val_precision: 0.7332 - val_recall: 0.9701 - val_auc: 0.8916\n",
            "Epoch 13/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2431 - accuracy: 0.8990 - precision: 0.8884 - recall: 0.9127 - auc: 0.9633 - val_loss: 0.5088 - val_accuracy: 0.8063 - val_precision: 0.7303 - val_recall: 0.9710 - val_auc: 0.8907\n",
            "Epoch 14/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.2442 - accuracy: 0.8985 - precision: 0.8878 - recall: 0.9123 - auc: 0.9629 - val_loss: 0.4889 - val_accuracy: 0.8156 - val_precision: 0.7432 - val_recall: 0.9643 - val_auc: 0.8938\n",
            "Epoch 15/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.2449 - accuracy: 0.8980 - precision: 0.8861 - recall: 0.9133 - auc: 0.9628 - val_loss: 0.5217 - val_accuracy: 0.8054 - val_precision: 0.7293 - val_recall: 0.9713 - val_auc: 0.8876\n",
            "Epoch 16/2000\n",
            "10/10 [==============================] - 4s 421ms/step - loss: 0.2487 - accuracy: 0.8961 - precision: 0.8838 - recall: 0.9123 - auc: 0.9616 - val_loss: 0.4662 - val_accuracy: 0.8194 - val_precision: 0.7467 - val_recall: 0.9664 - val_auc: 0.9028\n",
            "Epoch 17/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.2450 - accuracy: 0.8978 - precision: 0.8867 - recall: 0.9121 - auc: 0.9627 - val_loss: 0.5024 - val_accuracy: 0.8075 - val_precision: 0.7312 - val_recall: 0.9723 - val_auc: 0.8951\n",
            "Epoch 18/2000\n",
            "10/10 [==============================] - 4s 384ms/step - loss: 0.2470 - accuracy: 0.8968 - precision: 0.8855 - recall: 0.9115 - auc: 0.9621 - val_loss: 0.5127 - val_accuracy: 0.8009 - val_precision: 0.7224 - val_recall: 0.9771 - val_auc: 0.8913\n",
            "Epoch 19/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.2507 - accuracy: 0.8948 - precision: 0.8825 - recall: 0.9110 - auc: 0.9610 - val_loss: 0.4842 - val_accuracy: 0.8019 - val_precision: 0.7231 - val_recall: 0.9783 - val_auc: 0.9048\n",
            "Epoch 20/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2459 - accuracy: 0.8974 - precision: 0.8832 - recall: 0.9159 - auc: 0.9624 - val_loss: 0.5069 - val_accuracy: 0.8003 - val_precision: 0.7210 - val_recall: 0.9793 - val_auc: 0.9002\n",
            "Epoch 21/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.2455 - accuracy: 0.8974 - precision: 0.8871 - recall: 0.9108 - auc: 0.9626 - val_loss: 0.4966 - val_accuracy: 0.8070 - val_precision: 0.7323 - val_recall: 0.9675 - val_auc: 0.8899\n",
            "Epoch 22/2000\n",
            "10/10 [==============================] - 4s 385ms/step - loss: 0.2434 - accuracy: 0.8987 - precision: 0.8858 - recall: 0.9155 - auc: 0.9632 - val_loss: 0.5140 - val_accuracy: 0.8015 - val_precision: 0.7242 - val_recall: 0.9738 - val_auc: 0.8914\n",
            "Epoch 23/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2436 - accuracy: 0.8990 - precision: 0.8885 - recall: 0.9126 - auc: 0.9632 - val_loss: 0.4867 - val_accuracy: 0.8113 - val_precision: 0.7365 - val_recall: 0.9693 - val_auc: 0.8955\n",
            "Epoch 24/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2444 - accuracy: 0.8984 - precision: 0.8869 - recall: 0.9134 - auc: 0.9629 - val_loss: 0.4705 - val_accuracy: 0.8220 - val_precision: 0.7529 - val_recall: 0.9585 - val_auc: 0.8951\n",
            "Epoch 25/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2443 - accuracy: 0.8987 - precision: 0.8872 - recall: 0.9136 - auc: 0.9629 - val_loss: 0.5055 - val_accuracy: 0.8073 - val_precision: 0.7307 - val_recall: 0.9730 - val_auc: 0.8928\n",
            "Epoch 26/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.2446 - accuracy: 0.8982 - precision: 0.8881 - recall: 0.9112 - auc: 0.9629 - val_loss: 0.5024 - val_accuracy: 0.8101 - val_precision: 0.7347 - val_recall: 0.9707 - val_auc: 0.8926\n",
            "Epoch 27/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.2435 - accuracy: 0.8989 - precision: 0.8860 - recall: 0.9157 - auc: 0.9633 - val_loss: 0.4966 - val_accuracy: 0.8129 - val_precision: 0.7376 - val_recall: 0.9711 - val_auc: 0.8973\n",
            "Epoch 28/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2442 - accuracy: 0.8985 - precision: 0.8878 - recall: 0.9122 - auc: 0.9630 - val_loss: 0.5176 - val_accuracy: 0.8035 - val_precision: 0.7257 - val_recall: 0.9755 - val_auc: 0.8914\n",
            "Epoch 29/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2505 - accuracy: 0.8958 - precision: 0.8848 - recall: 0.9102 - auc: 0.9611 - val_loss: 0.4815 - val_accuracy: 0.8050 - val_precision: 0.7270 - val_recall: 0.9764 - val_auc: 0.9065\n",
            "Epoch 30/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.2456 - accuracy: 0.8978 - precision: 0.8852 - recall: 0.9141 - auc: 0.9625 - val_loss: 0.5055 - val_accuracy: 0.7953 - val_precision: 0.7159 - val_recall: 0.9792 - val_auc: 0.8981\n",
            "Epoch 31/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2428 - accuracy: 0.8989 - precision: 0.8856 - recall: 0.9162 - auc: 0.9634 - val_loss: 0.5151 - val_accuracy: 0.8046 - val_precision: 0.7275 - val_recall: 0.9737 - val_auc: 0.8933\n",
            "Epoch 32/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2432 - accuracy: 0.8988 - precision: 0.8885 - recall: 0.9120 - auc: 0.9633 - val_loss: 0.4845 - val_accuracy: 0.8176 - val_precision: 0.7472 - val_recall: 0.9598 - val_auc: 0.8924\n",
            "Epoch 33/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.2445 - accuracy: 0.8983 - precision: 0.8863 - recall: 0.9138 - auc: 0.9629 - val_loss: 0.5062 - val_accuracy: 0.8052 - val_precision: 0.7295 - val_recall: 0.9701 - val_auc: 0.8898\n",
            "Epoch 34/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2433 - accuracy: 0.8991 - precision: 0.8867 - recall: 0.9152 - auc: 0.9633 - val_loss: 0.5455 - val_accuracy: 0.7933 - val_precision: 0.7141 - val_recall: 0.9782 - val_auc: 0.8875\n",
            "Epoch 35/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2465 - accuracy: 0.8976 - precision: 0.8854 - recall: 0.9135 - auc: 0.9623 - val_loss: 0.5064 - val_accuracy: 0.8013 - val_precision: 0.7228 - val_recall: 0.9773 - val_auc: 0.8990\n",
            "Epoch 36/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2404 - accuracy: 0.9006 - precision: 0.8901 - recall: 0.9140 - auc: 0.9641 - val_loss: 0.5362 - val_accuracy: 0.7909 - val_precision: 0.7109 - val_recall: 0.9803 - val_auc: 0.8890\n",
            "Epoch 37/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.2439 - accuracy: 0.8986 - precision: 0.8862 - recall: 0.9148 - auc: 0.9631 - val_loss: 0.5199 - val_accuracy: 0.7955 - val_precision: 0.7164 - val_recall: 0.9783 - val_auc: 0.8926\n",
            "Epoch 38/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2427 - accuracy: 0.9001 - precision: 0.8889 - recall: 0.9146 - auc: 0.9634 - val_loss: 0.5192 - val_accuracy: 0.8027 - val_precision: 0.7239 - val_recall: 0.9786 - val_auc: 0.8967\n",
            "Epoch 39/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2435 - accuracy: 0.8989 - precision: 0.8874 - recall: 0.9137 - auc: 0.9632 - val_loss: 0.5303 - val_accuracy: 0.7918 - val_precision: 0.7116 - val_recall: 0.9811 - val_auc: 0.8963\n",
            "Epoch 40/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2414 - accuracy: 0.8994 - precision: 0.8870 - recall: 0.9153 - auc: 0.9638 - val_loss: 0.5281 - val_accuracy: 0.7983 - val_precision: 0.7193 - val_recall: 0.9780 - val_auc: 0.8915\n",
            "Epoch 41/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.2392 - accuracy: 0.9010 - precision: 0.8884 - recall: 0.9172 - auc: 0.9644 - val_loss: 0.5058 - val_accuracy: 0.8086 - val_precision: 0.7321 - val_recall: 0.9732 - val_auc: 0.8945\n",
            "Epoch 42/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2428 - accuracy: 0.8992 - precision: 0.8890 - recall: 0.9125 - auc: 0.9634 - val_loss: 0.5066 - val_accuracy: 0.8035 - val_precision: 0.7254 - val_recall: 0.9764 - val_auc: 0.8965\n",
            "Epoch 43/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2392 - accuracy: 0.9010 - precision: 0.8908 - recall: 0.9141 - auc: 0.9645 - val_loss: 0.5075 - val_accuracy: 0.8064 - val_precision: 0.7284 - val_recall: 0.9770 - val_auc: 0.8974\n",
            "Epoch 44/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.2418 - accuracy: 0.8994 - precision: 0.8887 - recall: 0.9133 - auc: 0.9637 - val_loss: 0.5226 - val_accuracy: 0.8003 - val_precision: 0.7217 - val_recall: 0.9774 - val_auc: 0.8935\n",
            "Epoch 45/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.2397 - accuracy: 0.9010 - precision: 0.8907 - recall: 0.9141 - auc: 0.9644 - val_loss: 0.4887 - val_accuracy: 0.8157 - val_precision: 0.7416 - val_recall: 0.9689 - val_auc: 0.8975\n",
            "Epoch 46/2000\n",
            "10/10 [==============================] - 4s 385ms/step - loss: 0.2403 - accuracy: 0.9003 - precision: 0.8888 - recall: 0.9152 - auc: 0.9641 - val_loss: 0.4890 - val_accuracy: 0.8114 - val_precision: 0.7339 - val_recall: 0.9770 - val_auc: 0.9061\n",
            "Epoch 47/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2414 - accuracy: 0.8999 - precision: 0.8891 - recall: 0.9140 - auc: 0.9638 - val_loss: 0.4965 - val_accuracy: 0.8087 - val_precision: 0.7310 - val_recall: 0.9768 - val_auc: 0.8999\n",
            "Epoch 48/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.2383 - accuracy: 0.9015 - precision: 0.8896 - recall: 0.9168 - auc: 0.9648 - val_loss: 0.5155 - val_accuracy: 0.8057 - val_precision: 0.7284 - val_recall: 0.9748 - val_auc: 0.8903\n",
            "Epoch 49/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2379 - accuracy: 0.9018 - precision: 0.8897 - recall: 0.9173 - auc: 0.9649 - val_loss: 0.5209 - val_accuracy: 0.8033 - val_precision: 0.7245 - val_recall: 0.9784 - val_auc: 0.9008\n",
            "Epoch 50/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2421 - accuracy: 0.9000 - precision: 0.8912 - recall: 0.9114 - auc: 0.9637 - val_loss: 0.4553 - val_accuracy: 0.8216 - val_precision: 0.7496 - val_recall: 0.9656 - val_auc: 0.9056\n",
            "Epoch 51/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2399 - accuracy: 0.9008 - precision: 0.8897 - recall: 0.9150 - auc: 0.9643 - val_loss: 0.5266 - val_accuracy: 0.8019 - val_precision: 0.7232 - val_recall: 0.9780 - val_auc: 0.8970\n",
            "Epoch 52/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2379 - accuracy: 0.9010 - precision: 0.8906 - recall: 0.9143 - auc: 0.9649 - val_loss: 0.5031 - val_accuracy: 0.8106 - val_precision: 0.7348 - val_recall: 0.9718 - val_auc: 0.8971\n",
            "Epoch 53/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2488 - accuracy: 0.8966 - precision: 0.8834 - recall: 0.9138 - auc: 0.9616 - val_loss: 0.4510 - val_accuracy: 0.8138 - val_precision: 0.7375 - val_recall: 0.9740 - val_auc: 0.9172\n",
            "Epoch 54/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2461 - accuracy: 0.8979 - precision: 0.8857 - recall: 0.9137 - auc: 0.9625 - val_loss: 0.4346 - val_accuracy: 0.8151 - val_precision: 0.7388 - val_recall: 0.9748 - val_auc: 0.9191\n",
            "Epoch 55/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.2384 - accuracy: 0.9007 - precision: 0.8894 - recall: 0.9153 - auc: 0.9647 - val_loss: 0.4842 - val_accuracy: 0.8033 - val_precision: 0.7248 - val_recall: 0.9779 - val_auc: 0.9053\n",
            "Epoch 56/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.2386 - accuracy: 0.9010 - precision: 0.8914 - recall: 0.9134 - auc: 0.9647 - val_loss: 0.5329 - val_accuracy: 0.7893 - val_precision: 0.7091 - val_recall: 0.9808 - val_auc: 0.8916\n",
            "Epoch 57/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2397 - accuracy: 0.9007 - precision: 0.8890 - recall: 0.9158 - auc: 0.9645 - val_loss: 0.5000 - val_accuracy: 0.8094 - val_precision: 0.7331 - val_recall: 0.9728 - val_auc: 0.8977\n",
            "Epoch 58/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2381 - accuracy: 0.9011 - precision: 0.8906 - recall: 0.9145 - auc: 0.9648 - val_loss: 0.5186 - val_accuracy: 0.8060 - val_precision: 0.7286 - val_recall: 0.9751 - val_auc: 0.8933\n",
            "Epoch 59/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2377 - accuracy: 0.9014 - precision: 0.8905 - recall: 0.9153 - auc: 0.9649 - val_loss: 0.5165 - val_accuracy: 0.8069 - val_precision: 0.7315 - val_recall: 0.9694 - val_auc: 0.8913\n",
            "Epoch 60/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2385 - accuracy: 0.9015 - precision: 0.8900 - recall: 0.9164 - auc: 0.9647 - val_loss: 0.5337 - val_accuracy: 0.7993 - val_precision: 0.7207 - val_recall: 0.9771 - val_auc: 0.8942\n",
            "Epoch 61/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2377 - accuracy: 0.9015 - precision: 0.8908 - recall: 0.9152 - auc: 0.9650 - val_loss: 0.4854 - val_accuracy: 0.8195 - val_precision: 0.7496 - val_recall: 0.9592 - val_auc: 0.8961\n",
            "Epoch 62/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2490 - accuracy: 0.8966 - precision: 0.8857 - recall: 0.9108 - auc: 0.9616 - val_loss: 0.4615 - val_accuracy: 0.8113 - val_precision: 0.7357 - val_recall: 0.9715 - val_auc: 0.9110\n",
            "Epoch 63/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2440 - accuracy: 0.8985 - precision: 0.8855 - recall: 0.9153 - auc: 0.9630 - val_loss: 0.4462 - val_accuracy: 0.8243 - val_precision: 0.7513 - val_recall: 0.9694 - val_auc: 0.9143\n",
            "Epoch 64/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2376 - accuracy: 0.9017 - precision: 0.8916 - recall: 0.9146 - auc: 0.9650 - val_loss: 0.5126 - val_accuracy: 0.8075 - val_precision: 0.7298 - val_recall: 0.9763 - val_auc: 0.8992\n",
            "Epoch 65/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.2364 - accuracy: 0.9017 - precision: 0.8905 - recall: 0.9160 - auc: 0.9653 - val_loss: 0.5020 - val_accuracy: 0.8108 - val_precision: 0.7347 - val_recall: 0.9730 - val_auc: 0.8998\n",
            "Epoch 66/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2389 - accuracy: 0.9009 - precision: 0.8902 - recall: 0.9146 - auc: 0.9645 - val_loss: 0.4641 - val_accuracy: 0.7848 - val_precision: 0.7946 - val_recall: 0.7680 - val_auc: 0.8715\n",
            "Epoch 67/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2373 - accuracy: 0.9016 - precision: 0.8903 - recall: 0.9162 - auc: 0.9651 - val_loss: 0.4434 - val_accuracy: 0.8246 - val_precision: 0.7785 - val_recall: 0.9071 - val_auc: 0.8908\n",
            "Epoch 68/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2368 - accuracy: 0.9019 - precision: 0.8935 - recall: 0.9126 - auc: 0.9652 - val_loss: 0.4974 - val_accuracy: 0.8145 - val_precision: 0.7422 - val_recall: 0.9634 - val_auc: 0.8939\n",
            "Epoch 69/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.2378 - accuracy: 0.9011 - precision: 0.8902 - recall: 0.9152 - auc: 0.9649 - val_loss: 0.4548 - val_accuracy: 0.8270 - val_precision: 0.7591 - val_recall: 0.9579 - val_auc: 0.9028\n",
            "Epoch 70/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2386 - accuracy: 0.9012 - precision: 0.8893 - recall: 0.9166 - auc: 0.9647 - val_loss: 0.4750 - val_accuracy: 0.8228 - val_precision: 0.7530 - val_recall: 0.9607 - val_auc: 0.8986\n",
            "Epoch 71/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2390 - accuracy: 0.9010 - precision: 0.8902 - recall: 0.9149 - auc: 0.9647 - val_loss: 0.4782 - val_accuracy: 0.8221 - val_precision: 0.7506 - val_recall: 0.9645 - val_auc: 0.9001\n",
            "Epoch 72/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.2372 - accuracy: 0.9022 - precision: 0.8939 - recall: 0.9127 - auc: 0.9650 - val_loss: 0.5465 - val_accuracy: 0.7924 - val_precision: 0.7122 - val_recall: 0.9814 - val_auc: 0.8937\n",
            "Epoch 73/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2354 - accuracy: 0.9026 - precision: 0.8908 - recall: 0.9178 - auc: 0.9656 - val_loss: 0.5021 - val_accuracy: 0.8143 - val_precision: 0.7397 - val_recall: 0.9698 - val_auc: 0.8959\n",
            "Epoch 74/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2365 - accuracy: 0.9020 - precision: 0.8903 - recall: 0.9171 - auc: 0.9652 - val_loss: 0.4962 - val_accuracy: 0.8171 - val_precision: 0.7432 - val_recall: 0.9690 - val_auc: 0.8997\n",
            "Epoch 75/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2372 - accuracy: 0.9019 - precision: 0.8908 - recall: 0.9162 - auc: 0.9651 - val_loss: 0.4726 - val_accuracy: 0.8244 - val_precision: 0.7523 - val_recall: 0.9671 - val_auc: 0.9042\n",
            "Epoch 76/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.2350 - accuracy: 0.9030 - precision: 0.8939 - recall: 0.9145 - auc: 0.9658 - val_loss: 0.4835 - val_accuracy: 0.8192 - val_precision: 0.7466 - val_recall: 0.9661 - val_auc: 0.8976\n",
            "Epoch 77/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2384 - accuracy: 0.9022 - precision: 0.8909 - recall: 0.9166 - auc: 0.9647 - val_loss: 0.4270 - val_accuracy: 0.8328 - val_precision: 0.7624 - val_recall: 0.9667 - val_auc: 0.9178\n",
            "Epoch 78/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2371 - accuracy: 0.9019 - precision: 0.8900 - recall: 0.9171 - auc: 0.9651 - val_loss: 0.5068 - val_accuracy: 0.8085 - val_precision: 0.7326 - val_recall: 0.9714 - val_auc: 0.8950\n",
            "Epoch 79/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.2359 - accuracy: 0.9026 - precision: 0.8918 - recall: 0.9163 - auc: 0.9655 - val_loss: 0.5200 - val_accuracy: 0.7957 - val_precision: 0.7160 - val_recall: 0.9799 - val_auc: 0.8994\n",
            "Epoch 80/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.2327 - accuracy: 0.9041 - precision: 0.8935 - recall: 0.9176 - auc: 0.9663 - val_loss: 0.5076 - val_accuracy: 0.8060 - val_precision: 0.7289 - val_recall: 0.9742 - val_auc: 0.8952\n",
            "Epoch 81/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.2336 - accuracy: 0.9038 - precision: 0.8921 - recall: 0.9186 - auc: 0.9661 - val_loss: 0.5245 - val_accuracy: 0.8066 - val_precision: 0.7297 - val_recall: 0.9740 - val_auc: 0.8947\n",
            "Epoch 82/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2406 - accuracy: 0.9007 - precision: 0.8898 - recall: 0.9148 - auc: 0.9641 - val_loss: 0.4805 - val_accuracy: 0.8141 - val_precision: 0.7384 - val_recall: 0.9728 - val_auc: 0.9067\n",
            "Epoch 83/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2337 - accuracy: 0.9037 - precision: 0.8920 - recall: 0.9186 - auc: 0.9661 - val_loss: 0.4997 - val_accuracy: 0.8149 - val_precision: 0.7397 - val_recall: 0.9714 - val_auc: 0.9015\n",
            "Epoch 84/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2334 - accuracy: 0.9032 - precision: 0.8923 - recall: 0.9170 - auc: 0.9662 - val_loss: 0.5273 - val_accuracy: 0.7956 - val_precision: 0.7160 - val_recall: 0.9798 - val_auc: 0.8977\n",
            "Epoch 85/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.2374 - accuracy: 0.9016 - precision: 0.8906 - recall: 0.9157 - auc: 0.9650 - val_loss: 0.4677 - val_accuracy: 0.8153 - val_precision: 0.7410 - val_recall: 0.9693 - val_auc: 0.9065\n",
            "Epoch 86/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2356 - accuracy: 0.9018 - precision: 0.8895 - recall: 0.9175 - auc: 0.9656 - val_loss: 0.4953 - val_accuracy: 0.8081 - val_precision: 0.7316 - val_recall: 0.9732 - val_auc: 0.8983\n",
            "Epoch 87/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.2341 - accuracy: 0.9030 - precision: 0.8932 - recall: 0.9155 - auc: 0.9661 - val_loss: 0.5088 - val_accuracy: 0.8049 - val_precision: 0.7270 - val_recall: 0.9764 - val_auc: 0.8986\n",
            "Epoch 88/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.2332 - accuracy: 0.9037 - precision: 0.8931 - recall: 0.9172 - auc: 0.9662 - val_loss: 0.5262 - val_accuracy: 0.7973 - val_precision: 0.7186 - val_recall: 0.9772 - val_auc: 0.8917\n",
            "Epoch 89/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2368 - accuracy: 0.9025 - precision: 0.8890 - recall: 0.9201 - auc: 0.9652 - val_loss: 0.4897 - val_accuracy: 0.8046 - val_precision: 0.7259 - val_recall: 0.9786 - val_auc: 0.9082\n",
            "Epoch 90/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.2352 - accuracy: 0.9030 - precision: 0.8916 - recall: 0.9176 - auc: 0.9657 - val_loss: 0.5417 - val_accuracy: 0.7678 - val_precision: 0.7599 - val_recall: 0.7829 - val_auc: 0.8464\n",
            "Epoch 91/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2381 - accuracy: 0.9018 - precision: 0.8911 - recall: 0.9154 - auc: 0.9648 - val_loss: 0.4788 - val_accuracy: 0.7975 - val_precision: 0.7430 - val_recall: 0.9092 - val_auc: 0.8752\n",
            "Epoch 92/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2393 - accuracy: 0.9004 - precision: 0.8882 - recall: 0.9161 - auc: 0.9645 - val_loss: 0.5037 - val_accuracy: 0.7988 - val_precision: 0.7246 - val_recall: 0.9638 - val_auc: 0.8870\n",
            "Epoch 93/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2380 - accuracy: 0.9010 - precision: 0.8901 - recall: 0.9151 - auc: 0.9649 - val_loss: 0.5126 - val_accuracy: 0.8053 - val_precision: 0.7276 - val_recall: 0.9760 - val_auc: 0.9003\n",
            "Epoch 94/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2359 - accuracy: 0.9025 - precision: 0.8921 - recall: 0.9157 - auc: 0.9655 - val_loss: 0.5417 - val_accuracy: 0.7983 - val_precision: 0.7187 - val_recall: 0.9799 - val_auc: 0.8951\n",
            "Epoch 95/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2373 - accuracy: 0.9021 - precision: 0.8905 - recall: 0.9171 - auc: 0.9651 - val_loss: 0.4849 - val_accuracy: 0.8156 - val_precision: 0.7399 - val_recall: 0.9733 - val_auc: 0.9061\n",
            "Epoch 96/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2362 - accuracy: 0.9020 - precision: 0.8909 - recall: 0.9163 - auc: 0.9654 - val_loss: 0.5259 - val_accuracy: 0.8021 - val_precision: 0.7236 - val_recall: 0.9774 - val_auc: 0.8966\n",
            "Epoch 97/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2341 - accuracy: 0.9035 - precision: 0.8936 - recall: 0.9160 - auc: 0.9660 - val_loss: 0.4991 - val_accuracy: 0.8129 - val_precision: 0.7369 - val_recall: 0.9732 - val_auc: 0.9026\n",
            "Epoch 98/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.2358 - accuracy: 0.9019 - precision: 0.8901 - recall: 0.9171 - auc: 0.9656 - val_loss: 0.4611 - val_accuracy: 0.8183 - val_precision: 0.7431 - val_recall: 0.9726 - val_auc: 0.9109\n",
            "Epoch 99/2000\n",
            "10/10 [==============================] - 4s 385ms/step - loss: 0.2342 - accuracy: 0.9031 - precision: 0.8906 - recall: 0.9190 - auc: 0.9660 - val_loss: 0.5107 - val_accuracy: 0.8064 - val_precision: 0.7287 - val_recall: 0.9762 - val_auc: 0.8987\n",
            "Epoch 100/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2323 - accuracy: 0.9036 - precision: 0.8914 - recall: 0.9193 - auc: 0.9665 - val_loss: 0.5400 - val_accuracy: 0.7994 - val_precision: 0.7205 - val_recall: 0.9783 - val_auc: 0.8942\n",
            "Epoch 101/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.2361 - accuracy: 0.9027 - precision: 0.8920 - recall: 0.9163 - auc: 0.9654 - val_loss: 0.5559 - val_accuracy: 0.7871 - val_precision: 0.7063 - val_recall: 0.9826 - val_auc: 0.8957\n",
            "Epoch 102/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2346 - accuracy: 0.9025 - precision: 0.8914 - recall: 0.9167 - auc: 0.9659 - val_loss: 0.4921 - val_accuracy: 0.8146 - val_precision: 0.7395 - val_recall: 0.9712 - val_auc: 0.9020\n",
            "Epoch 103/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2346 - accuracy: 0.9027 - precision: 0.8923 - recall: 0.9159 - auc: 0.9659 - val_loss: 0.5416 - val_accuracy: 0.7893 - val_precision: 0.7085 - val_recall: 0.9829 - val_auc: 0.9017\n",
            "Epoch 104/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.2364 - accuracy: 0.9024 - precision: 0.8928 - recall: 0.9145 - auc: 0.9654 - val_loss: 0.5157 - val_accuracy: 0.8006 - val_precision: 0.7215 - val_recall: 0.9790 - val_auc: 0.9043\n",
            "Epoch 105/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2325 - accuracy: 0.9035 - precision: 0.8913 - recall: 0.9190 - auc: 0.9665 - val_loss: 0.4956 - val_accuracy: 0.8096 - val_precision: 0.7324 - val_recall: 0.9756 - val_auc: 0.9062\n",
            "Epoch 106/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2302 - accuracy: 0.9048 - precision: 0.8928 - recall: 0.9201 - auc: 0.9671 - val_loss: 0.5267 - val_accuracy: 0.8037 - val_precision: 0.7268 - val_recall: 0.9730 - val_auc: 0.8916\n",
            "Epoch 107/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.2306 - accuracy: 0.9048 - precision: 0.8936 - recall: 0.9191 - auc: 0.9669 - val_loss: 0.5025 - val_accuracy: 0.8131 - val_precision: 0.7369 - val_recall: 0.9739 - val_auc: 0.9000\n",
            "Epoch 108/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2421 - accuracy: 0.8999 - precision: 0.8897 - recall: 0.9129 - auc: 0.9637 - val_loss: 0.4737 - val_accuracy: 0.8100 - val_precision: 0.7327 - val_recall: 0.9758 - val_auc: 0.9129\n",
            "Epoch 109/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.2341 - accuracy: 0.9031 - precision: 0.8898 - recall: 0.9203 - auc: 0.9660 - val_loss: 0.4659 - val_accuracy: 0.8171 - val_precision: 0.7422 - val_recall: 0.9716 - val_auc: 0.9076\n",
            "Epoch 110/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2314 - accuracy: 0.9046 - precision: 0.8934 - recall: 0.9188 - auc: 0.9668 - val_loss: 0.5142 - val_accuracy: 0.8070 - val_precision: 0.7298 - val_recall: 0.9749 - val_auc: 0.8998\n",
            "Epoch 111/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.2304 - accuracy: 0.9048 - precision: 0.8945 - recall: 0.9180 - auc: 0.9671 - val_loss: 0.5481 - val_accuracy: 0.7958 - val_precision: 0.7162 - val_recall: 0.9795 - val_auc: 0.8942\n",
            "Epoch 112/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2304 - accuracy: 0.9048 - precision: 0.8947 - recall: 0.9177 - auc: 0.9671 - val_loss: 0.4917 - val_accuracy: 0.8114 - val_precision: 0.7431 - val_recall: 0.9516 - val_auc: 0.8889\n",
            "Epoch 113/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2359 - accuracy: 0.9026 - precision: 0.8932 - recall: 0.9147 - auc: 0.9655 - val_loss: 0.4561 - val_accuracy: 0.8170 - val_precision: 0.7443 - val_recall: 0.9656 - val_auc: 0.9033\n",
            "Epoch 114/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2322 - accuracy: 0.9041 - precision: 0.8911 - recall: 0.9207 - auc: 0.9666 - val_loss: 0.4842 - val_accuracy: 0.8185 - val_precision: 0.7437 - val_recall: 0.9718 - val_auc: 0.9030\n",
            "Epoch 115/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.2318 - accuracy: 0.9037 - precision: 0.8923 - recall: 0.9183 - auc: 0.9666 - val_loss: 0.4892 - val_accuracy: 0.8164 - val_precision: 0.7430 - val_recall: 0.9672 - val_auc: 0.8962\n",
            "Epoch 116/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2348 - accuracy: 0.9033 - precision: 0.8924 - recall: 0.9171 - auc: 0.9657 - val_loss: 0.4890 - val_accuracy: 0.8096 - val_precision: 0.7326 - val_recall: 0.9748 - val_auc: 0.9041\n",
            "Epoch 117/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2302 - accuracy: 0.9055 - precision: 0.8950 - recall: 0.9189 - auc: 0.9671 - val_loss: 0.5097 - val_accuracy: 0.8023 - val_precision: 0.7229 - val_recall: 0.9802 - val_auc: 0.9041\n",
            "Epoch 118/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.2309 - accuracy: 0.9049 - precision: 0.8950 - recall: 0.9175 - auc: 0.9670 - val_loss: 0.5218 - val_accuracy: 0.8032 - val_precision: 0.7252 - val_recall: 0.9761 - val_auc: 0.8974\n",
            "Epoch 119/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2323 - accuracy: 0.9041 - precision: 0.8959 - recall: 0.9144 - auc: 0.9665 - val_loss: 0.5122 - val_accuracy: 0.8012 - val_precision: 0.7228 - val_recall: 0.9768 - val_auc: 0.8992\n",
            "Epoch 120/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2301 - accuracy: 0.9052 - precision: 0.8955 - recall: 0.9174 - auc: 0.9671 - val_loss: 0.4614 - val_accuracy: 0.8212 - val_precision: 0.7467 - val_recall: 0.9719 - val_auc: 0.9119\n",
            "Epoch 121/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2293 - accuracy: 0.9055 - precision: 0.8928 - recall: 0.9218 - auc: 0.9674 - val_loss: 0.4790 - val_accuracy: 0.8229 - val_precision: 0.7501 - val_recall: 0.9681 - val_auc: 0.9059\n",
            "Epoch 122/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.2296 - accuracy: 0.9057 - precision: 0.8971 - recall: 0.9166 - auc: 0.9673 - val_loss: 0.5332 - val_accuracy: 0.8048 - val_precision: 0.7275 - val_recall: 0.9745 - val_auc: 0.8933\n",
            "Epoch 123/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2306 - accuracy: 0.9051 - precision: 0.8949 - recall: 0.9180 - auc: 0.9670 - val_loss: 0.4956 - val_accuracy: 0.8121 - val_precision: 0.7374 - val_recall: 0.9692 - val_auc: 0.8995\n",
            "Epoch 124/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2284 - accuracy: 0.9067 - precision: 0.8950 - recall: 0.9216 - auc: 0.9677 - val_loss: 0.4951 - val_accuracy: 0.8157 - val_precision: 0.7407 - val_recall: 0.9715 - val_auc: 0.9040\n",
            "Epoch 125/2000\n",
            "10/10 [==============================] - 4s 419ms/step - loss: 0.2311 - accuracy: 0.9051 - precision: 0.8937 - recall: 0.9195 - auc: 0.9669 - val_loss: 0.5233 - val_accuracy: 0.8034 - val_precision: 0.7252 - val_recall: 0.9767 - val_auc: 0.8971\n",
            "Epoch 126/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.2283 - accuracy: 0.9056 - precision: 0.8957 - recall: 0.9181 - auc: 0.9677 - val_loss: 0.5011 - val_accuracy: 0.8141 - val_precision: 0.7390 - val_recall: 0.9710 - val_auc: 0.8980\n",
            "Epoch 127/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.2277 - accuracy: 0.9062 - precision: 0.8953 - recall: 0.9201 - auc: 0.9678 - val_loss: 0.5308 - val_accuracy: 0.8027 - val_precision: 0.7244 - val_recall: 0.9770 - val_auc: 0.8957\n",
            "Epoch 128/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2266 - accuracy: 0.9067 - precision: 0.8985 - recall: 0.9169 - auc: 0.9682 - val_loss: 0.5034 - val_accuracy: 0.8125 - val_precision: 0.7363 - val_recall: 0.9734 - val_auc: 0.9009\n",
            "Epoch 129/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2287 - accuracy: 0.9057 - precision: 0.8957 - recall: 0.9185 - auc: 0.9676 - val_loss: 0.5286 - val_accuracy: 0.8015 - val_precision: 0.7232 - val_recall: 0.9768 - val_auc: 0.8971\n",
            "Epoch 130/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.2283 - accuracy: 0.9054 - precision: 0.8945 - recall: 0.9192 - auc: 0.9677 - val_loss: 0.5017 - val_accuracy: 0.8144 - val_precision: 0.7387 - val_recall: 0.9729 - val_auc: 0.9033\n",
            "Epoch 131/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2311 - accuracy: 0.9044 - precision: 0.8952 - recall: 0.9160 - auc: 0.9669 - val_loss: 0.5277 - val_accuracy: 0.8019 - val_precision: 0.7227 - val_recall: 0.9797 - val_auc: 0.9017\n",
            "Epoch 132/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2262 - accuracy: 0.9070 - precision: 0.8955 - recall: 0.9216 - auc: 0.9682 - val_loss: 0.5265 - val_accuracy: 0.8053 - val_precision: 0.7284 - val_recall: 0.9735 - val_auc: 0.8934\n",
            "Epoch 133/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.2301 - accuracy: 0.9054 - precision: 0.8928 - recall: 0.9215 - auc: 0.9671 - val_loss: 0.4362 - val_accuracy: 0.8303 - val_precision: 0.7599 - val_recall: 0.9655 - val_auc: 0.9166\n",
            "Epoch 134/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2306 - accuracy: 0.9046 - precision: 0.8927 - recall: 0.9198 - auc: 0.9670 - val_loss: 0.5090 - val_accuracy: 0.8088 - val_precision: 0.7317 - val_recall: 0.9750 - val_auc: 0.8983\n",
            "Epoch 135/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2305 - accuracy: 0.9052 - precision: 0.8936 - recall: 0.9199 - auc: 0.9671 - val_loss: 0.4891 - val_accuracy: 0.8172 - val_precision: 0.7430 - val_recall: 0.9696 - val_auc: 0.9024\n",
            "Epoch 136/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2309 - accuracy: 0.9051 - precision: 0.8953 - recall: 0.9174 - auc: 0.9669 - val_loss: 0.4730 - val_accuracy: 0.8247 - val_precision: 0.7538 - val_recall: 0.9643 - val_auc: 0.9087\n",
            "Epoch 137/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2312 - accuracy: 0.9053 - precision: 0.8937 - recall: 0.9201 - auc: 0.9669 - val_loss: 0.4766 - val_accuracy: 0.8234 - val_precision: 0.7516 - val_recall: 0.9658 - val_auc: 0.9037\n",
            "Epoch 138/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2271 - accuracy: 0.9063 - precision: 0.8958 - recall: 0.9196 - auc: 0.9680 - val_loss: 0.5398 - val_accuracy: 0.7985 - val_precision: 0.7191 - val_recall: 0.9795 - val_auc: 0.8994\n",
            "Epoch 139/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.2252 - accuracy: 0.9076 - precision: 0.8996 - recall: 0.9178 - auc: 0.9686 - val_loss: 0.5204 - val_accuracy: 0.7968 - val_precision: 0.7164 - val_recall: 0.9823 - val_auc: 0.9026\n",
            "Epoch 140/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2272 - accuracy: 0.9069 - precision: 0.8956 - recall: 0.9212 - auc: 0.9680 - val_loss: 0.4876 - val_accuracy: 0.8148 - val_precision: 0.7405 - val_recall: 0.9690 - val_auc: 0.9007\n",
            "Epoch 141/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2276 - accuracy: 0.9061 - precision: 0.8963 - recall: 0.9185 - auc: 0.9679 - val_loss: 0.5204 - val_accuracy: 0.8015 - val_precision: 0.7226 - val_recall: 0.9787 - val_auc: 0.8995\n",
            "Epoch 142/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2285 - accuracy: 0.9063 - precision: 0.8960 - recall: 0.9194 - auc: 0.9676 - val_loss: 0.5187 - val_accuracy: 0.8007 - val_precision: 0.7219 - val_recall: 0.9779 - val_auc: 0.8963\n",
            "Epoch 143/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.2288 - accuracy: 0.9055 - precision: 0.8967 - recall: 0.9167 - auc: 0.9675 - val_loss: 0.4883 - val_accuracy: 0.8155 - val_precision: 0.7399 - val_recall: 0.9730 - val_auc: 0.9030\n",
            "Epoch 144/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2278 - accuracy: 0.9063 - precision: 0.8958 - recall: 0.9196 - auc: 0.9678 - val_loss: 0.5214 - val_accuracy: 0.7932 - val_precision: 0.7135 - val_recall: 0.9794 - val_auc: 0.8962\n",
            "Epoch 145/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2307 - accuracy: 0.9052 - precision: 0.8937 - recall: 0.9197 - auc: 0.9670 - val_loss: 0.4905 - val_accuracy: 0.8084 - val_precision: 0.7313 - val_recall: 0.9751 - val_auc: 0.9053\n",
            "Epoch 146/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.2232 - accuracy: 0.9085 - precision: 0.8979 - recall: 0.9219 - auc: 0.9690 - val_loss: 0.5457 - val_accuracy: 0.7906 - val_precision: 0.7100 - val_recall: 0.9821 - val_auc: 0.8985\n",
            "Epoch 147/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2238 - accuracy: 0.9077 - precision: 0.8969 - recall: 0.9215 - auc: 0.9689 - val_loss: 0.4416 - val_accuracy: 0.8213 - val_precision: 0.7448 - val_recall: 0.9773 - val_auc: 0.9253\n",
            "Epoch 148/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2254 - accuracy: 0.9076 - precision: 0.8946 - recall: 0.9240 - auc: 0.9685 - val_loss: 0.4839 - val_accuracy: 0.8147 - val_precision: 0.7383 - val_recall: 0.9746 - val_auc: 0.9104\n",
            "Epoch 149/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.2258 - accuracy: 0.9073 - precision: 0.8983 - recall: 0.9188 - auc: 0.9684 - val_loss: 0.5224 - val_accuracy: 0.8057 - val_precision: 0.7280 - val_recall: 0.9757 - val_auc: 0.9000\n",
            "Epoch 150/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.2245 - accuracy: 0.9076 - precision: 0.8964 - recall: 0.9219 - auc: 0.9687 - val_loss: 0.5063 - val_accuracy: 0.8075 - val_precision: 0.7311 - val_recall: 0.9727 - val_auc: 0.9032\n",
            "Epoch 151/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2281 - accuracy: 0.9059 - precision: 0.8972 - recall: 0.9169 - auc: 0.9678 - val_loss: 0.4951 - val_accuracy: 0.8117 - val_precision: 0.7373 - val_recall: 0.9682 - val_auc: 0.8993\n",
            "Epoch 152/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2266 - accuracy: 0.9064 - precision: 0.8969 - recall: 0.9184 - auc: 0.9682 - val_loss: 0.5558 - val_accuracy: 0.7884 - val_precision: 0.7076 - val_recall: 0.9825 - val_auc: 0.8958\n",
            "Epoch 153/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2241 - accuracy: 0.9079 - precision: 0.8991 - recall: 0.9190 - auc: 0.9689 - val_loss: 0.5415 - val_accuracy: 0.7922 - val_precision: 0.7118 - val_recall: 0.9818 - val_auc: 0.9005\n",
            "Epoch 154/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.2251 - accuracy: 0.9073 - precision: 0.8996 - recall: 0.9168 - auc: 0.9686 - val_loss: 0.5303 - val_accuracy: 0.7975 - val_precision: 0.7181 - val_recall: 0.9794 - val_auc: 0.8979\n",
            "Epoch 155/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.2245 - accuracy: 0.9081 - precision: 0.8985 - recall: 0.9201 - auc: 0.9688 - val_loss: 0.5252 - val_accuracy: 0.7980 - val_precision: 0.7184 - val_recall: 0.9801 - val_auc: 0.9019\n",
            "Epoch 156/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2219 - accuracy: 0.9092 - precision: 0.8976 - recall: 0.9238 - auc: 0.9695 - val_loss: 0.5490 - val_accuracy: 0.7972 - val_precision: 0.7175 - val_recall: 0.9802 - val_auc: 0.8975\n",
            "Epoch 157/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2245 - accuracy: 0.9077 - precision: 0.9004 - recall: 0.9168 - auc: 0.9687 - val_loss: 0.4931 - val_accuracy: 0.8124 - val_precision: 0.7355 - val_recall: 0.9754 - val_auc: 0.9079\n",
            "Epoch 158/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2219 - accuracy: 0.9087 - precision: 0.8982 - recall: 0.9219 - auc: 0.9695 - val_loss: 0.5035 - val_accuracy: 0.8109 - val_precision: 0.7342 - val_recall: 0.9745 - val_auc: 0.9045\n",
            "Epoch 159/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2210 - accuracy: 0.9091 - precision: 0.8982 - recall: 0.9227 - auc: 0.9697 - val_loss: 0.5373 - val_accuracy: 0.8060 - val_precision: 0.7301 - val_recall: 0.9707 - val_auc: 0.8875\n",
            "Epoch 160/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.2297 - accuracy: 0.9054 - precision: 0.8953 - recall: 0.9184 - auc: 0.9672 - val_loss: 0.4726 - val_accuracy: 0.8121 - val_precision: 0.7339 - val_recall: 0.9790 - val_auc: 0.9149\n",
            "Epoch 161/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.2227 - accuracy: 0.9084 - precision: 0.8969 - recall: 0.9230 - auc: 0.9692 - val_loss: 0.4762 - val_accuracy: 0.8070 - val_precision: 0.7285 - val_recall: 0.9787 - val_auc: 0.9127\n",
            "Epoch 162/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2225 - accuracy: 0.9083 - precision: 0.8982 - recall: 0.9211 - auc: 0.9693 - val_loss: 0.5162 - val_accuracy: 0.8001 - val_precision: 0.7206 - val_recall: 0.9799 - val_auc: 0.9021\n",
            "Epoch 163/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2218 - accuracy: 0.9082 - precision: 0.8981 - recall: 0.9209 - auc: 0.9695 - val_loss: 0.4616 - val_accuracy: 0.8276 - val_precision: 0.7565 - val_recall: 0.9662 - val_auc: 0.9083\n",
            "Epoch 164/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.2233 - accuracy: 0.9079 - precision: 0.8983 - recall: 0.9201 - auc: 0.9691 - val_loss: 0.4929 - val_accuracy: 0.8137 - val_precision: 0.7370 - val_recall: 0.9751 - val_auc: 0.9080\n",
            "Epoch 165/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.2212 - accuracy: 0.9093 - precision: 0.8994 - recall: 0.9218 - auc: 0.9696 - val_loss: 0.5195 - val_accuracy: 0.8088 - val_precision: 0.7317 - val_recall: 0.9750 - val_auc: 0.8982\n",
            "Epoch 166/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2219 - accuracy: 0.9087 - precision: 0.8989 - recall: 0.9210 - auc: 0.9694 - val_loss: 0.5062 - val_accuracy: 0.8120 - val_precision: 0.7358 - val_recall: 0.9734 - val_auc: 0.9034\n",
            "Epoch 167/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.2236 - accuracy: 0.9081 - precision: 0.8995 - recall: 0.9189 - auc: 0.9689 - val_loss: 0.5245 - val_accuracy: 0.8031 - val_precision: 0.7240 - val_recall: 0.9795 - val_auc: 0.9021\n",
            "Epoch 168/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2200 - accuracy: 0.9097 - precision: 0.8986 - recall: 0.9237 - auc: 0.9700 - val_loss: 0.5220 - val_accuracy: 0.8089 - val_precision: 0.7323 - val_recall: 0.9737 - val_auc: 0.8988\n",
            "Epoch 169/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2271 - accuracy: 0.9054 - precision: 0.8946 - recall: 0.9191 - auc: 0.9681 - val_loss: 0.4988 - val_accuracy: 0.8089 - val_precision: 0.7331 - val_recall: 0.9714 - val_auc: 0.9041\n",
            "Epoch 170/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2240 - accuracy: 0.9083 - precision: 0.8966 - recall: 0.9232 - auc: 0.9688 - val_loss: 0.4678 - val_accuracy: 0.8203 - val_precision: 0.7477 - val_recall: 0.9667 - val_auc: 0.9078\n",
            "Epoch 171/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.2237 - accuracy: 0.9084 - precision: 0.8976 - recall: 0.9219 - auc: 0.9689 - val_loss: 0.5028 - val_accuracy: 0.8142 - val_precision: 0.7394 - val_recall: 0.9703 - val_auc: 0.9033\n",
            "Epoch 172/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.2212 - accuracy: 0.9094 - precision: 0.8977 - recall: 0.9242 - auc: 0.9696 - val_loss: 0.5031 - val_accuracy: 0.8138 - val_precision: 0.7397 - val_recall: 0.9680 - val_auc: 0.8990\n",
            "Epoch 173/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2245 - accuracy: 0.9078 - precision: 0.8979 - recall: 0.9203 - auc: 0.9687 - val_loss: 0.5242 - val_accuracy: 0.8077 - val_precision: 0.7305 - val_recall: 0.9747 - val_auc: 0.8965\n",
            "Epoch 174/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2245 - accuracy: 0.9080 - precision: 0.8992 - recall: 0.9191 - auc: 0.9688 - val_loss: 0.5271 - val_accuracy: 0.8031 - val_precision: 0.7247 - val_recall: 0.9772 - val_auc: 0.8987\n",
            "Epoch 175/2000\n",
            "10/10 [==============================] - 5s 482ms/step - loss: 0.2228 - accuracy: 0.9086 - precision: 0.8975 - recall: 0.9225 - auc: 0.9692 - val_loss: 0.5415 - val_accuracy: 0.7965 - val_precision: 0.7166 - val_recall: 0.9804 - val_auc: 0.8985\n",
            "Epoch 176/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2206 - accuracy: 0.9100 - precision: 0.9014 - recall: 0.9208 - auc: 0.9698 - val_loss: 0.5203 - val_accuracy: 0.8046 - val_precision: 0.7268 - val_recall: 0.9760 - val_auc: 0.8982\n",
            "Epoch 177/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2223 - accuracy: 0.9091 - precision: 0.8997 - recall: 0.9209 - auc: 0.9693 - val_loss: 0.4795 - val_accuracy: 0.8195 - val_precision: 0.7467 - val_recall: 0.9667 - val_auc: 0.8998\n",
            "Epoch 178/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2246 - accuracy: 0.9075 - precision: 0.8996 - recall: 0.9173 - auc: 0.9687 - val_loss: 0.4656 - val_accuracy: 0.8239 - val_precision: 0.7534 - val_recall: 0.9628 - val_auc: 0.9054\n",
            "Epoch 179/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2227 - accuracy: 0.9085 - precision: 0.8969 - recall: 0.9232 - auc: 0.9692 - val_loss: 0.5092 - val_accuracy: 0.8121 - val_precision: 0.7362 - val_recall: 0.9725 - val_auc: 0.9015\n",
            "Epoch 180/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2236 - accuracy: 0.9077 - precision: 0.8966 - recall: 0.9217 - auc: 0.9690 - val_loss: 0.4421 - val_accuracy: 0.8327 - val_precision: 0.7631 - val_recall: 0.9646 - val_auc: 0.9165\n",
            "Epoch 181/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2271 - accuracy: 0.9062 - precision: 0.8969 - recall: 0.9180 - auc: 0.9681 - val_loss: 0.5066 - val_accuracy: 0.8069 - val_precision: 0.7285 - val_recall: 0.9782 - val_auc: 0.9086\n",
            "Epoch 182/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.2207 - accuracy: 0.9094 - precision: 0.8985 - recall: 0.9231 - auc: 0.9698 - val_loss: 0.4832 - val_accuracy: 0.8171 - val_precision: 0.7411 - val_recall: 0.9747 - val_auc: 0.9120\n",
            "Epoch 183/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2217 - accuracy: 0.9086 - precision: 0.9004 - recall: 0.9188 - auc: 0.9695 - val_loss: 0.5060 - val_accuracy: 0.8112 - val_precision: 0.7341 - val_recall: 0.9757 - val_auc: 0.9076\n",
            "Epoch 184/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2198 - accuracy: 0.9105 - precision: 0.9007 - recall: 0.9228 - auc: 0.9700 - val_loss: 0.5225 - val_accuracy: 0.8093 - val_precision: 0.7338 - val_recall: 0.9706 - val_auc: 0.8974\n",
            "Epoch 185/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2200 - accuracy: 0.9095 - precision: 0.8998 - recall: 0.9217 - auc: 0.9700 - val_loss: 0.4768 - val_accuracy: 0.8243 - val_precision: 0.7515 - val_recall: 0.9689 - val_auc: 0.9129\n",
            "Epoch 186/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.2226 - accuracy: 0.9089 - precision: 0.8979 - recall: 0.9227 - auc: 0.9693 - val_loss: 0.5297 - val_accuracy: 0.8099 - val_precision: 0.7335 - val_recall: 0.9735 - val_auc: 0.9069\n",
            "Epoch 187/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2219 - accuracy: 0.9093 - precision: 0.9000 - recall: 0.9209 - auc: 0.9694 - val_loss: 0.5494 - val_accuracy: 0.8033 - val_precision: 0.7260 - val_recall: 0.9740 - val_auc: 0.8965\n",
            "Epoch 188/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2175 - accuracy: 0.9110 - precision: 0.9015 - recall: 0.9228 - auc: 0.9706 - val_loss: 0.5012 - val_accuracy: 0.8158 - val_precision: 0.7418 - val_recall: 0.9685 - val_auc: 0.9000\n",
            "Epoch 189/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.2207 - accuracy: 0.9091 - precision: 0.9001 - recall: 0.9203 - auc: 0.9698 - val_loss: 0.5225 - val_accuracy: 0.8045 - val_precision: 0.7264 - val_recall: 0.9769 - val_auc: 0.9031\n",
            "Epoch 190/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2190 - accuracy: 0.9100 - precision: 0.9004 - recall: 0.9220 - auc: 0.9703 - val_loss: 0.5130 - val_accuracy: 0.8061 - val_precision: 0.7277 - val_recall: 0.9779 - val_auc: 0.9058\n",
            "Epoch 191/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2197 - accuracy: 0.9099 - precision: 0.9007 - recall: 0.9215 - auc: 0.9700 - val_loss: 0.4921 - val_accuracy: 0.8162 - val_precision: 0.7398 - val_recall: 0.9753 - val_auc: 0.9100\n",
            "Epoch 192/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.2205 - accuracy: 0.9096 - precision: 0.9006 - recall: 0.9208 - auc: 0.9698 - val_loss: 0.4653 - val_accuracy: 0.8235 - val_precision: 0.7517 - val_recall: 0.9660 - val_auc: 0.9111\n",
            "Epoch 193/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2204 - accuracy: 0.9096 - precision: 0.9014 - recall: 0.9200 - auc: 0.9698 - val_loss: 0.5243 - val_accuracy: 0.7896 - val_precision: 0.7087 - val_recall: 0.9834 - val_auc: 0.9054\n",
            "Epoch 194/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2204 - accuracy: 0.9094 - precision: 0.8985 - recall: 0.9231 - auc: 0.9699 - val_loss: 0.4952 - val_accuracy: 0.8095 - val_precision: 0.7316 - val_recall: 0.9772 - val_auc: 0.9104\n",
            "Epoch 195/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2222 - accuracy: 0.9085 - precision: 0.8992 - recall: 0.9203 - auc: 0.9694 - val_loss: 0.5353 - val_accuracy: 0.8012 - val_precision: 0.7221 - val_recall: 0.9791 - val_auc: 0.9015\n",
            "Epoch 196/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.2215 - accuracy: 0.9095 - precision: 0.9006 - recall: 0.9207 - auc: 0.9695 - val_loss: 0.5134 - val_accuracy: 0.8028 - val_precision: 0.7240 - val_recall: 0.9786 - val_auc: 0.9036\n",
            "Epoch 197/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2195 - accuracy: 0.9101 - precision: 0.9010 - recall: 0.9216 - auc: 0.9701 - val_loss: 0.5474 - val_accuracy: 0.7992 - val_precision: 0.7202 - val_recall: 0.9785 - val_auc: 0.8972\n",
            "Epoch 198/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2197 - accuracy: 0.9104 - precision: 0.9015 - recall: 0.9215 - auc: 0.9701 - val_loss: 0.4977 - val_accuracy: 0.8184 - val_precision: 0.7436 - val_recall: 0.9716 - val_auc: 0.9045\n",
            "Epoch 199/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2186 - accuracy: 0.9103 - precision: 0.8987 - recall: 0.9249 - auc: 0.9704 - val_loss: 0.4459 - val_accuracy: 0.8301 - val_precision: 0.7573 - val_recall: 0.9714 - val_auc: 0.9205\n",
            "Epoch 200/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2177 - accuracy: 0.9109 - precision: 0.9012 - recall: 0.9230 - auc: 0.9706 - val_loss: 0.4936 - val_accuracy: 0.8159 - val_precision: 0.7405 - val_recall: 0.9726 - val_auc: 0.9054\n",
            "Epoch 201/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2175 - accuracy: 0.9107 - precision: 0.9027 - recall: 0.9206 - auc: 0.9707 - val_loss: 0.5252 - val_accuracy: 0.8041 - val_precision: 0.7252 - val_recall: 0.9791 - val_auc: 0.9026\n",
            "Epoch 202/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.2166 - accuracy: 0.9114 - precision: 0.9009 - recall: 0.9246 - auc: 0.9709 - val_loss: 0.5020 - val_accuracy: 0.8183 - val_precision: 0.7459 - val_recall: 0.9653 - val_auc: 0.9001\n",
            "Epoch 203/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.2181 - accuracy: 0.9105 - precision: 0.9005 - recall: 0.9231 - auc: 0.9705 - val_loss: 0.4680 - val_accuracy: 0.8279 - val_precision: 0.7588 - val_recall: 0.9613 - val_auc: 0.9094\n",
            "Epoch 204/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2183 - accuracy: 0.9108 - precision: 0.9012 - recall: 0.9228 - auc: 0.9704 - val_loss: 0.4840 - val_accuracy: 0.8167 - val_precision: 0.7533 - val_recall: 0.9418 - val_auc: 0.8960\n",
            "Epoch 205/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2195 - accuracy: 0.9102 - precision: 0.8996 - recall: 0.9234 - auc: 0.9700 - val_loss: 0.4874 - val_accuracy: 0.8230 - val_precision: 0.7519 - val_recall: 0.9640 - val_auc: 0.9044\n",
            "Epoch 206/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.2251 - accuracy: 0.9073 - precision: 0.9011 - recall: 0.9152 - auc: 0.9686 - val_loss: 0.4784 - val_accuracy: 0.8216 - val_precision: 0.7477 - val_recall: 0.9707 - val_auc: 0.9122\n",
            "Epoch 207/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2210 - accuracy: 0.9088 - precision: 0.9008 - recall: 0.9187 - auc: 0.9698 - val_loss: 0.4813 - val_accuracy: 0.8193 - val_precision: 0.7434 - val_recall: 0.9751 - val_auc: 0.9141\n",
            "Epoch 208/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2185 - accuracy: 0.9110 - precision: 0.9018 - recall: 0.9224 - auc: 0.9704 - val_loss: 0.5272 - val_accuracy: 0.8047 - val_precision: 0.7265 - val_recall: 0.9772 - val_auc: 0.9018\n",
            "Epoch 209/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2196 - accuracy: 0.9099 - precision: 0.9007 - recall: 0.9215 - auc: 0.9701 - val_loss: 0.4874 - val_accuracy: 0.8167 - val_precision: 0.7413 - val_recall: 0.9727 - val_auc: 0.9092\n",
            "Epoch 210/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.2178 - accuracy: 0.9106 - precision: 0.9018 - recall: 0.9217 - auc: 0.9705 - val_loss: 0.5248 - val_accuracy: 0.8041 - val_precision: 0.7263 - val_recall: 0.9757 - val_auc: 0.8993\n",
            "Epoch 211/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2253 - accuracy: 0.9076 - precision: 0.8975 - recall: 0.9202 - auc: 0.9685 - val_loss: 0.4823 - val_accuracy: 0.8097 - val_precision: 0.7315 - val_recall: 0.9784 - val_auc: 0.9194\n",
            "Epoch 212/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2177 - accuracy: 0.9106 - precision: 0.9008 - recall: 0.9228 - auc: 0.9706 - val_loss: 0.5333 - val_accuracy: 0.8012 - val_precision: 0.7222 - val_recall: 0.9788 - val_auc: 0.9066\n",
            "Epoch 213/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.2197 - accuracy: 0.9095 - precision: 0.8997 - recall: 0.9219 - auc: 0.9700 - val_loss: 0.5278 - val_accuracy: 0.8075 - val_precision: 0.7300 - val_recall: 0.9759 - val_auc: 0.9031\n",
            "Epoch 214/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.2195 - accuracy: 0.9104 - precision: 0.9022 - recall: 0.9207 - auc: 0.9701 - val_loss: 0.5024 - val_accuracy: 0.8160 - val_precision: 0.7405 - val_recall: 0.9729 - val_auc: 0.9062\n",
            "Epoch 215/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2162 - accuracy: 0.9118 - precision: 0.9027 - recall: 0.9231 - auc: 0.9710 - val_loss: 0.4995 - val_accuracy: 0.8195 - val_precision: 0.7452 - val_recall: 0.9709 - val_auc: 0.9061\n",
            "Epoch 216/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2165 - accuracy: 0.9115 - precision: 0.9021 - recall: 0.9233 - auc: 0.9709 - val_loss: 0.5767 - val_accuracy: 0.7929 - val_precision: 0.7130 - val_recall: 0.9804 - val_auc: 0.8965\n",
            "Epoch 217/2000\n",
            "10/10 [==============================] - 4s 457ms/step - loss: 0.2218 - accuracy: 0.9092 - precision: 0.9000 - recall: 0.9208 - auc: 0.9695 - val_loss: 0.5291 - val_accuracy: 0.8038 - val_precision: 0.7246 - val_recall: 0.9797 - val_auc: 0.9076\n",
            "Epoch 218/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2164 - accuracy: 0.9116 - precision: 0.9028 - recall: 0.9227 - auc: 0.9710 - val_loss: 0.4992 - val_accuracy: 0.8149 - val_precision: 0.7389 - val_recall: 0.9738 - val_auc: 0.9114\n",
            "Epoch 219/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2128 - accuracy: 0.9128 - precision: 0.9051 - recall: 0.9223 - auc: 0.9719 - val_loss: 0.5083 - val_accuracy: 0.8144 - val_precision: 0.7381 - val_recall: 0.9742 - val_auc: 0.9074\n",
            "Epoch 220/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2175 - accuracy: 0.9110 - precision: 0.9030 - recall: 0.9209 - auc: 0.9707 - val_loss: 0.4938 - val_accuracy: 0.8198 - val_precision: 0.7454 - val_recall: 0.9714 - val_auc: 0.9095\n",
            "Epoch 221/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.2149 - accuracy: 0.9119 - precision: 0.9022 - recall: 0.9241 - auc: 0.9714 - val_loss: 0.5093 - val_accuracy: 0.8142 - val_precision: 0.7379 - val_recall: 0.9743 - val_auc: 0.9076\n",
            "Epoch 222/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2165 - accuracy: 0.9113 - precision: 0.9018 - recall: 0.9230 - auc: 0.9709 - val_loss: 0.5079 - val_accuracy: 0.8143 - val_precision: 0.7379 - val_recall: 0.9745 - val_auc: 0.9055\n",
            "Epoch 223/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2172 - accuracy: 0.9111 - precision: 0.9011 - recall: 0.9236 - auc: 0.9708 - val_loss: 0.5384 - val_accuracy: 0.7980 - val_precision: 0.7181 - val_recall: 0.9809 - val_auc: 0.9068\n",
            "Epoch 224/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.2191 - accuracy: 0.9103 - precision: 0.9003 - recall: 0.9229 - auc: 0.9703 - val_loss: 0.4999 - val_accuracy: 0.8168 - val_precision: 0.7403 - val_recall: 0.9759 - val_auc: 0.9135\n",
            "Epoch 225/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2180 - accuracy: 0.9110 - precision: 0.9028 - recall: 0.9211 - auc: 0.9705 - val_loss: 0.5214 - val_accuracy: 0.8051 - val_precision: 0.7259 - val_recall: 0.9803 - val_auc: 0.9122\n",
            "Epoch 226/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2204 - accuracy: 0.9096 - precision: 0.9010 - recall: 0.9203 - auc: 0.9699 - val_loss: 0.4768 - val_accuracy: 0.8122 - val_precision: 0.7338 - val_recall: 0.9796 - val_auc: 0.9238\n",
            "Epoch 227/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.2190 - accuracy: 0.9101 - precision: 0.9000 - recall: 0.9228 - auc: 0.9703 - val_loss: 0.4836 - val_accuracy: 0.8199 - val_precision: 0.7460 - val_recall: 0.9701 - val_auc: 0.9109\n",
            "Epoch 228/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.2157 - accuracy: 0.9114 - precision: 0.9011 - recall: 0.9242 - auc: 0.9711 - val_loss: 0.5422 - val_accuracy: 0.8018 - val_precision: 0.7235 - val_recall: 0.9767 - val_auc: 0.9024\n",
            "Epoch 229/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2170 - accuracy: 0.9116 - precision: 0.9030 - recall: 0.9223 - auc: 0.9708 - val_loss: 0.5128 - val_accuracy: 0.8138 - val_precision: 0.7384 - val_recall: 0.9718 - val_auc: 0.9041\n",
            "Epoch 230/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2147 - accuracy: 0.9125 - precision: 0.9024 - recall: 0.9251 - auc: 0.9714 - val_loss: 0.4893 - val_accuracy: 0.8155 - val_precision: 0.7382 - val_recall: 0.9776 - val_auc: 0.9161\n",
            "Epoch 231/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.2141 - accuracy: 0.9124 - precision: 0.9018 - recall: 0.9257 - auc: 0.9715 - val_loss: 0.5256 - val_accuracy: 0.8033 - val_precision: 0.7237 - val_recall: 0.9811 - val_auc: 0.9095\n",
            "Epoch 232/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2296 - accuracy: 0.9057 - precision: 0.8959 - recall: 0.9180 - auc: 0.9674 - val_loss: 0.4201 - val_accuracy: 0.8296 - val_precision: 0.7557 - val_recall: 0.9740 - val_auc: 0.9310\n",
            "Epoch 233/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2205 - accuracy: 0.9094 - precision: 0.8990 - recall: 0.9226 - auc: 0.9699 - val_loss: 0.4456 - val_accuracy: 0.8249 - val_precision: 0.7508 - val_recall: 0.9725 - val_auc: 0.9211\n",
            "Epoch 234/2000\n",
            "10/10 [==============================] - 5s 481ms/step - loss: 0.2179 - accuracy: 0.9110 - precision: 0.9013 - recall: 0.9231 - auc: 0.9706 - val_loss: 0.4951 - val_accuracy: 0.8128 - val_precision: 0.7355 - val_recall: 0.9766 - val_auc: 0.9099\n",
            "Epoch 235/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2158 - accuracy: 0.9117 - precision: 0.9006 - recall: 0.9256 - auc: 0.9711 - val_loss: 0.5610 - val_accuracy: 0.7907 - val_precision: 0.7096 - val_recall: 0.9838 - val_auc: 0.9003\n",
            "Epoch 236/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2164 - accuracy: 0.9113 - precision: 0.9022 - recall: 0.9227 - auc: 0.9710 - val_loss: 0.5193 - val_accuracy: 0.8102 - val_precision: 0.7320 - val_recall: 0.9784 - val_auc: 0.9056\n",
            "Epoch 237/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.2145 - accuracy: 0.9128 - precision: 0.9039 - recall: 0.9238 - auc: 0.9714 - val_loss: 0.5010 - val_accuracy: 0.8211 - val_precision: 0.7475 - val_recall: 0.9695 - val_auc: 0.9058\n",
            "Epoch 238/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.2132 - accuracy: 0.9129 - precision: 0.9052 - recall: 0.9223 - auc: 0.9718 - val_loss: 0.5173 - val_accuracy: 0.8143 - val_precision: 0.7383 - val_recall: 0.9735 - val_auc: 0.9041\n",
            "Epoch 239/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2144 - accuracy: 0.9122 - precision: 0.9035 - recall: 0.9230 - auc: 0.9715 - val_loss: 0.5347 - val_accuracy: 0.8074 - val_precision: 0.7319 - val_recall: 0.9697 - val_auc: 0.8920\n",
            "Epoch 240/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2155 - accuracy: 0.9118 - precision: 0.9032 - recall: 0.9225 - auc: 0.9712 - val_loss: 0.4747 - val_accuracy: 0.8242 - val_precision: 0.7510 - val_recall: 0.9697 - val_auc: 0.9107\n",
            "Epoch 241/2000\n",
            "10/10 [==============================] - 4s 426ms/step - loss: 0.2130 - accuracy: 0.9133 - precision: 0.9041 - recall: 0.9247 - auc: 0.9718 - val_loss: 0.4794 - val_accuracy: 0.8239 - val_precision: 0.7507 - val_recall: 0.9698 - val_auc: 0.9108\n",
            "Epoch 242/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.2159 - accuracy: 0.9117 - precision: 0.9036 - recall: 0.9217 - auc: 0.9711 - val_loss: 0.5018 - val_accuracy: 0.8080 - val_precision: 0.7300 - val_recall: 0.9774 - val_auc: 0.9060\n",
            "Epoch 243/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2215 - accuracy: 0.9094 - precision: 0.8978 - recall: 0.9239 - auc: 0.9696 - val_loss: 0.4404 - val_accuracy: 0.8291 - val_precision: 0.7576 - val_recall: 0.9677 - val_auc: 0.9213\n",
            "Epoch 244/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2143 - accuracy: 0.9122 - precision: 0.9037 - recall: 0.9228 - auc: 0.9715 - val_loss: 0.4824 - val_accuracy: 0.8233 - val_precision: 0.7491 - val_recall: 0.9722 - val_auc: 0.9149\n",
            "Epoch 245/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.2130 - accuracy: 0.9129 - precision: 0.9036 - recall: 0.9244 - auc: 0.9718 - val_loss: 0.4922 - val_accuracy: 0.8209 - val_precision: 0.7471 - val_recall: 0.9701 - val_auc: 0.9081\n",
            "Epoch 246/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2167 - accuracy: 0.9113 - precision: 0.9026 - recall: 0.9220 - auc: 0.9709 - val_loss: 0.5023 - val_accuracy: 0.8113 - val_precision: 0.7337 - val_recall: 0.9772 - val_auc: 0.9102\n",
            "Epoch 247/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2154 - accuracy: 0.9115 - precision: 0.8989 - recall: 0.9274 - auc: 0.9712 - val_loss: 0.4698 - val_accuracy: 0.8250 - val_precision: 0.7530 - val_recall: 0.9671 - val_auc: 0.9112\n",
            "Epoch 248/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.2143 - accuracy: 0.9129 - precision: 0.9063 - recall: 0.9212 - auc: 0.9715 - val_loss: 0.4976 - val_accuracy: 0.8139 - val_precision: 0.7367 - val_recall: 0.9766 - val_auc: 0.9124\n",
            "Epoch 249/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2166 - accuracy: 0.9115 - precision: 0.8999 - recall: 0.9261 - auc: 0.9709 - val_loss: 0.4857 - val_accuracy: 0.8192 - val_precision: 0.7443 - val_recall: 0.9724 - val_auc: 0.9137\n",
            "Epoch 250/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2164 - accuracy: 0.9114 - precision: 0.9047 - recall: 0.9198 - auc: 0.9710 - val_loss: 0.4738 - val_accuracy: 0.8229 - val_precision: 0.7502 - val_recall: 0.9680 - val_auc: 0.9101\n",
            "Epoch 251/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2149 - accuracy: 0.9122 - precision: 0.9032 - recall: 0.9234 - auc: 0.9713 - val_loss: 0.4951 - val_accuracy: 0.8206 - val_precision: 0.7487 - val_recall: 0.9651 - val_auc: 0.9033\n",
            "Epoch 252/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2174 - accuracy: 0.9108 - precision: 0.9016 - recall: 0.9224 - auc: 0.9707 - val_loss: 0.5099 - val_accuracy: 0.8041 - val_precision: 0.7242 - val_recall: 0.9821 - val_auc: 0.9158\n",
            "Epoch 253/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.2120 - accuracy: 0.9136 - precision: 0.9020 - recall: 0.9281 - auc: 0.9721 - val_loss: 0.4596 - val_accuracy: 0.8282 - val_precision: 0.7557 - val_recall: 0.9698 - val_auc: 0.9184\n",
            "Epoch 254/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2132 - accuracy: 0.9132 - precision: 0.9048 - recall: 0.9234 - auc: 0.9718 - val_loss: 0.4786 - val_accuracy: 0.8202 - val_precision: 0.7456 - val_recall: 0.9720 - val_auc: 0.9095\n",
            "Epoch 255/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.2186 - accuracy: 0.9108 - precision: 0.8995 - recall: 0.9250 - auc: 0.9703 - val_loss: 0.4594 - val_accuracy: 0.8223 - val_precision: 0.7479 - val_recall: 0.9721 - val_auc: 0.9157\n",
            "Epoch 256/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.2164 - accuracy: 0.9115 - precision: 0.9022 - recall: 0.9230 - auc: 0.9710 - val_loss: 0.4890 - val_accuracy: 0.8195 - val_precision: 0.7485 - val_recall: 0.9622 - val_auc: 0.9015\n",
            "Epoch 257/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2142 - accuracy: 0.9129 - precision: 0.9041 - recall: 0.9237 - auc: 0.9716 - val_loss: 0.5034 - val_accuracy: 0.8131 - val_precision: 0.7367 - val_recall: 0.9742 - val_auc: 0.9054\n",
            "Epoch 258/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2156 - accuracy: 0.9120 - precision: 0.9032 - recall: 0.9230 - auc: 0.9712 - val_loss: 0.4883 - val_accuracy: 0.8162 - val_precision: 0.7406 - val_recall: 0.9729 - val_auc: 0.9106\n",
            "Epoch 259/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.2130 - accuracy: 0.9130 - precision: 0.9025 - recall: 0.9260 - auc: 0.9719 - val_loss: 0.5191 - val_accuracy: 0.8069 - val_precision: 0.7285 - val_recall: 0.9782 - val_auc: 0.9060\n",
            "Epoch 260/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2152 - accuracy: 0.9122 - precision: 0.9033 - recall: 0.9234 - auc: 0.9712 - val_loss: 0.5404 - val_accuracy: 0.8020 - val_precision: 0.7233 - val_recall: 0.9781 - val_auc: 0.8999\n",
            "Epoch 261/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2163 - accuracy: 0.9114 - precision: 0.9034 - recall: 0.9213 - auc: 0.9710 - val_loss: 0.5340 - val_accuracy: 0.8058 - val_precision: 0.7276 - val_recall: 0.9774 - val_auc: 0.9001\n",
            "Epoch 262/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2131 - accuracy: 0.9133 - precision: 0.9045 - recall: 0.9242 - auc: 0.9718 - val_loss: 0.5337 - val_accuracy: 0.8050 - val_precision: 0.7264 - val_recall: 0.9784 - val_auc: 0.9069\n",
            "Epoch 263/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2144 - accuracy: 0.9130 - precision: 0.9039 - recall: 0.9242 - auc: 0.9715 - val_loss: 0.4882 - val_accuracy: 0.8188 - val_precision: 0.7432 - val_recall: 0.9741 - val_auc: 0.9135\n",
            "Epoch 264/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2111 - accuracy: 0.9137 - precision: 0.9049 - recall: 0.9247 - auc: 0.9724 - val_loss: 0.5402 - val_accuracy: 0.8050 - val_precision: 0.7277 - val_recall: 0.9746 - val_auc: 0.8959\n",
            "Epoch 265/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2131 - accuracy: 0.9126 - precision: 0.9027 - recall: 0.9248 - auc: 0.9718 - val_loss: 0.5120 - val_accuracy: 0.8083 - val_precision: 0.7299 - val_recall: 0.9785 - val_auc: 0.9074\n",
            "Epoch 266/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.2147 - accuracy: 0.9125 - precision: 0.9020 - recall: 0.9256 - auc: 0.9714 - val_loss: 0.4710 - val_accuracy: 0.8173 - val_precision: 0.7408 - val_recall: 0.9758 - val_auc: 0.9179\n",
            "Epoch 267/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2116 - accuracy: 0.9136 - precision: 0.9045 - recall: 0.9249 - auc: 0.9722 - val_loss: 0.5411 - val_accuracy: 0.8033 - val_precision: 0.7249 - val_recall: 0.9773 - val_auc: 0.9043\n",
            "Epoch 268/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2157 - accuracy: 0.9120 - precision: 0.9034 - recall: 0.9228 - auc: 0.9711 - val_loss: 0.5305 - val_accuracy: 0.8105 - val_precision: 0.7333 - val_recall: 0.9757 - val_auc: 0.9037\n",
            "Epoch 269/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.2109 - accuracy: 0.9144 - precision: 0.9052 - recall: 0.9258 - auc: 0.9724 - val_loss: 0.5371 - val_accuracy: 0.8034 - val_precision: 0.7241 - val_recall: 0.9800 - val_auc: 0.9066\n",
            "Epoch 270/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.2103 - accuracy: 0.9147 - precision: 0.9061 - recall: 0.9253 - auc: 0.9725 - val_loss: 0.5240 - val_accuracy: 0.8100 - val_precision: 0.7325 - val_recall: 0.9765 - val_auc: 0.9051\n",
            "Epoch 271/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.2087 - accuracy: 0.9150 - precision: 0.9082 - recall: 0.9233 - auc: 0.9730 - val_loss: 0.5265 - val_accuracy: 0.8103 - val_precision: 0.7328 - val_recall: 0.9767 - val_auc: 0.9034\n",
            "Epoch 272/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.2115 - accuracy: 0.9137 - precision: 0.9048 - recall: 0.9246 - auc: 0.9722 - val_loss: 0.5128 - val_accuracy: 0.8094 - val_precision: 0.7316 - val_recall: 0.9770 - val_auc: 0.9067\n",
            "Epoch 273/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2131 - accuracy: 0.9138 - precision: 0.9044 - recall: 0.9255 - auc: 0.9718 - val_loss: 0.4910 - val_accuracy: 0.8154 - val_precision: 0.7380 - val_recall: 0.9776 - val_auc: 0.9118\n",
            "Epoch 274/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2104 - accuracy: 0.9147 - precision: 0.9051 - recall: 0.9266 - auc: 0.9725 - val_loss: 0.4946 - val_accuracy: 0.8205 - val_precision: 0.7464 - val_recall: 0.9706 - val_auc: 0.9050\n",
            "Epoch 275/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2111 - accuracy: 0.9138 - precision: 0.9062 - recall: 0.9233 - auc: 0.9724 - val_loss: 0.5074 - val_accuracy: 0.8125 - val_precision: 0.7372 - val_recall: 0.9710 - val_auc: 0.8972\n",
            "Epoch 276/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2149 - accuracy: 0.9121 - precision: 0.9039 - recall: 0.9223 - auc: 0.9714 - val_loss: 0.4428 - val_accuracy: 0.8293 - val_precision: 0.7586 - val_recall: 0.9657 - val_auc: 0.9157\n",
            "Epoch 277/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2119 - accuracy: 0.9131 - precision: 0.9049 - recall: 0.9232 - auc: 0.9722 - val_loss: 0.5142 - val_accuracy: 0.8082 - val_precision: 0.7298 - val_recall: 0.9785 - val_auc: 0.9113\n",
            "Epoch 278/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2089 - accuracy: 0.9154 - precision: 0.9062 - recall: 0.9267 - auc: 0.9730 - val_loss: 0.5173 - val_accuracy: 0.8075 - val_precision: 0.7287 - val_recall: 0.9793 - val_auc: 0.9086\n",
            "Epoch 279/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.2102 - accuracy: 0.9144 - precision: 0.9048 - recall: 0.9263 - auc: 0.9725 - val_loss: 0.4799 - val_accuracy: 0.8172 - val_precision: 0.7406 - val_recall: 0.9762 - val_auc: 0.9165\n",
            "Epoch 280/2000\n",
            "10/10 [==============================] - 5s 478ms/step - loss: 0.2101 - accuracy: 0.9140 - precision: 0.9051 - recall: 0.9251 - auc: 0.9726 - val_loss: 0.5160 - val_accuracy: 0.8124 - val_precision: 0.7362 - val_recall: 0.9734 - val_auc: 0.9070\n",
            "Epoch 281/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2103 - accuracy: 0.9144 - precision: 0.9061 - recall: 0.9248 - auc: 0.9725 - val_loss: 0.4899 - val_accuracy: 0.8179 - val_precision: 0.7420 - val_recall: 0.9746 - val_auc: 0.9162\n",
            "Epoch 282/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2075 - accuracy: 0.9159 - precision: 0.9065 - recall: 0.9274 - auc: 0.9733 - val_loss: 0.4745 - val_accuracy: 0.8211 - val_precision: 0.7445 - val_recall: 0.9777 - val_auc: 0.9241\n",
            "Epoch 283/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2106 - accuracy: 0.9143 - precision: 0.9051 - recall: 0.9258 - auc: 0.9725 - val_loss: 0.5225 - val_accuracy: 0.8076 - val_precision: 0.7287 - val_recall: 0.9801 - val_auc: 0.9139\n",
            "Epoch 284/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.2135 - accuracy: 0.9130 - precision: 0.9028 - recall: 0.9256 - auc: 0.9717 - val_loss: 0.5638 - val_accuracy: 0.7935 - val_precision: 0.7128 - val_recall: 0.9831 - val_auc: 0.9094\n",
            "Epoch 285/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2102 - accuracy: 0.9148 - precision: 0.9060 - recall: 0.9257 - auc: 0.9725 - val_loss: 0.5234 - val_accuracy: 0.8063 - val_precision: 0.7273 - val_recall: 0.9799 - val_auc: 0.9105\n",
            "Epoch 286/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2118 - accuracy: 0.9137 - precision: 0.9046 - recall: 0.9250 - auc: 0.9721 - val_loss: 0.4851 - val_accuracy: 0.8126 - val_precision: 0.7338 - val_recall: 0.9808 - val_auc: 0.9253\n",
            "Epoch 287/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2096 - accuracy: 0.9146 - precision: 0.9065 - recall: 0.9245 - auc: 0.9728 - val_loss: 0.4808 - val_accuracy: 0.8182 - val_precision: 0.7410 - val_recall: 0.9783 - val_auc: 0.9214\n",
            "Epoch 288/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2092 - accuracy: 0.9150 - precision: 0.9057 - recall: 0.9265 - auc: 0.9728 - val_loss: 0.5098 - val_accuracy: 0.8102 - val_precision: 0.7327 - val_recall: 0.9765 - val_auc: 0.9067\n",
            "Epoch 289/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2095 - accuracy: 0.9147 - precision: 0.9061 - recall: 0.9254 - auc: 0.9728 - val_loss: 0.5333 - val_accuracy: 0.8085 - val_precision: 0.7324 - val_recall: 0.9720 - val_auc: 0.9013\n",
            "Epoch 290/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.2130 - accuracy: 0.9131 - precision: 0.9060 - recall: 0.9220 - auc: 0.9718 - val_loss: 0.5601 - val_accuracy: 0.7952 - val_precision: 0.7147 - val_recall: 0.9825 - val_auc: 0.9058\n",
            "Epoch 291/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2116 - accuracy: 0.9136 - precision: 0.9042 - recall: 0.9251 - auc: 0.9722 - val_loss: 0.4819 - val_accuracy: 0.8220 - val_precision: 0.7472 - val_recall: 0.9731 - val_auc: 0.9144\n",
            "Epoch 292/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2091 - accuracy: 0.9145 - precision: 0.9052 - recall: 0.9261 - auc: 0.9728 - val_loss: 0.5207 - val_accuracy: 0.8067 - val_precision: 0.7276 - val_recall: 0.9802 - val_auc: 0.9136\n",
            "Epoch 293/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2077 - accuracy: 0.9157 - precision: 0.9077 - recall: 0.9256 - auc: 0.9733 - val_loss: 0.5263 - val_accuracy: 0.8054 - val_precision: 0.7259 - val_recall: 0.9812 - val_auc: 0.9125\n",
            "Epoch 294/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.2132 - accuracy: 0.9127 - precision: 0.9023 - recall: 0.9256 - auc: 0.9718 - val_loss: 0.4982 - val_accuracy: 0.8167 - val_precision: 0.7399 - val_recall: 0.9767 - val_auc: 0.9165\n",
            "Epoch 295/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2072 - accuracy: 0.9159 - precision: 0.9082 - recall: 0.9255 - auc: 0.9733 - val_loss: 0.5425 - val_accuracy: 0.8020 - val_precision: 0.7220 - val_recall: 0.9820 - val_auc: 0.9084\n",
            "Epoch 296/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2105 - accuracy: 0.9149 - precision: 0.9052 - recall: 0.9268 - auc: 0.9725 - val_loss: 0.5518 - val_accuracy: 0.7941 - val_precision: 0.7127 - val_recall: 0.9853 - val_auc: 0.9114\n",
            "Epoch 297/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.2071 - accuracy: 0.9158 - precision: 0.9062 - recall: 0.9276 - auc: 0.9734 - val_loss: 0.5247 - val_accuracy: 0.8081 - val_precision: 0.7288 - val_recall: 0.9812 - val_auc: 0.9141\n",
            "Epoch 298/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.2082 - accuracy: 0.9153 - precision: 0.9073 - recall: 0.9252 - auc: 0.9731 - val_loss: 0.4806 - val_accuracy: 0.8229 - val_precision: 0.7470 - val_recall: 0.9764 - val_auc: 0.9188\n",
            "Epoch 299/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.2073 - accuracy: 0.9153 - precision: 0.9079 - recall: 0.9245 - auc: 0.9733 - val_loss: 0.5675 - val_accuracy: 0.7975 - val_precision: 0.7173 - val_recall: 0.9820 - val_auc: 0.9051\n",
            "Epoch 300/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2094 - accuracy: 0.9150 - precision: 0.9068 - recall: 0.9251 - auc: 0.9728 - val_loss: 0.5265 - val_accuracy: 0.8069 - val_precision: 0.7281 - val_recall: 0.9793 - val_auc: 0.9084\n",
            "Epoch 301/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.2083 - accuracy: 0.9157 - precision: 0.9055 - recall: 0.9284 - auc: 0.9730 - val_loss: 0.5412 - val_accuracy: 0.8044 - val_precision: 0.7253 - val_recall: 0.9797 - val_auc: 0.9089\n",
            "Epoch 302/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2099 - accuracy: 0.9147 - precision: 0.9058 - recall: 0.9257 - auc: 0.9727 - val_loss: 0.4609 - val_accuracy: 0.8285 - val_precision: 0.7547 - val_recall: 0.9731 - val_auc: 0.9250\n",
            "Epoch 303/2000\n",
            "10/10 [==============================] - 4s 385ms/step - loss: 0.2074 - accuracy: 0.9157 - precision: 0.9062 - recall: 0.9276 - auc: 0.9733 - val_loss: 0.4838 - val_accuracy: 0.8219 - val_precision: 0.7468 - val_recall: 0.9736 - val_auc: 0.9168\n",
            "Epoch 304/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2072 - accuracy: 0.9157 - precision: 0.9083 - recall: 0.9249 - auc: 0.9733 - val_loss: 0.5288 - val_accuracy: 0.8045 - val_precision: 0.7253 - val_recall: 0.9800 - val_auc: 0.9108\n",
            "Epoch 305/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.2069 - accuracy: 0.9162 - precision: 0.9077 - recall: 0.9266 - auc: 0.9734 - val_loss: 0.5384 - val_accuracy: 0.8013 - val_precision: 0.7215 - val_recall: 0.9811 - val_auc: 0.9100\n",
            "Epoch 306/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.2093 - accuracy: 0.9147 - precision: 0.9042 - recall: 0.9277 - auc: 0.9728 - val_loss: 0.5389 - val_accuracy: 0.7989 - val_precision: 0.7186 - val_recall: 0.9823 - val_auc: 0.9110\n",
            "Epoch 307/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2063 - accuracy: 0.9160 - precision: 0.9083 - recall: 0.9253 - auc: 0.9736 - val_loss: 0.4510 - val_accuracy: 0.8322 - val_precision: 0.7631 - val_recall: 0.9633 - val_auc: 0.9183\n",
            "Epoch 308/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.2101 - accuracy: 0.9144 - precision: 0.9051 - recall: 0.9259 - auc: 0.9726 - val_loss: 0.5098 - val_accuracy: 0.8098 - val_precision: 0.7314 - val_recall: 0.9790 - val_auc: 0.9180\n",
            "Epoch 309/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2067 - accuracy: 0.9157 - precision: 0.9063 - recall: 0.9274 - auc: 0.9735 - val_loss: 0.4975 - val_accuracy: 0.8119 - val_precision: 0.7346 - val_recall: 0.9764 - val_auc: 0.9127\n",
            "Epoch 310/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2065 - accuracy: 0.9165 - precision: 0.9075 - recall: 0.9275 - auc: 0.9735 - val_loss: 0.5225 - val_accuracy: 0.8051 - val_precision: 0.7262 - val_recall: 0.9793 - val_auc: 0.9087\n",
            "Epoch 311/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2060 - accuracy: 0.9163 - precision: 0.9081 - recall: 0.9263 - auc: 0.9736 - val_loss: 0.5040 - val_accuracy: 0.8124 - val_precision: 0.7345 - val_recall: 0.9782 - val_auc: 0.9106\n",
            "Epoch 312/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.2057 - accuracy: 0.9166 - precision: 0.9073 - recall: 0.9280 - auc: 0.9737 - val_loss: 0.5062 - val_accuracy: 0.8141 - val_precision: 0.7362 - val_recall: 0.9788 - val_auc: 0.9169\n",
            "Epoch 313/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.2109 - accuracy: 0.9144 - precision: 0.9059 - recall: 0.9248 - auc: 0.9724 - val_loss: 0.4585 - val_accuracy: 0.8269 - val_precision: 0.7525 - val_recall: 0.9740 - val_auc: 0.9263\n",
            "Epoch 314/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2062 - accuracy: 0.9162 - precision: 0.9067 - recall: 0.9278 - auc: 0.9736 - val_loss: 0.4593 - val_accuracy: 0.8262 - val_precision: 0.7522 - val_recall: 0.9728 - val_auc: 0.9199\n",
            "Epoch 315/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.2098 - accuracy: 0.9146 - precision: 0.9064 - recall: 0.9247 - auc: 0.9726 - val_loss: 0.4958 - val_accuracy: 0.8091 - val_precision: 0.7331 - val_recall: 0.9719 - val_auc: 0.9070\n",
            "Epoch 316/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2060 - accuracy: 0.9161 - precision: 0.9051 - recall: 0.9296 - auc: 0.9736 - val_loss: 0.4969 - val_accuracy: 0.8116 - val_precision: 0.7349 - val_recall: 0.9745 - val_auc: 0.9095\n",
            "Epoch 317/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2064 - accuracy: 0.9161 - precision: 0.9065 - recall: 0.9278 - auc: 0.9736 - val_loss: 0.5124 - val_accuracy: 0.8125 - val_precision: 0.7377 - val_recall: 0.9698 - val_auc: 0.9043\n",
            "Epoch 318/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.2094 - accuracy: 0.9148 - precision: 0.9070 - recall: 0.9244 - auc: 0.9728 - val_loss: 0.4418 - val_accuracy: 0.8354 - val_precision: 0.7705 - val_recall: 0.9551 - val_auc: 0.9129\n",
            "Epoch 319/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.2074 - accuracy: 0.9156 - precision: 0.9066 - recall: 0.9266 - auc: 0.9733 - val_loss: 0.4598 - val_accuracy: 0.8323 - val_precision: 0.7666 - val_recall: 0.9553 - val_auc: 0.9127\n",
            "Epoch 320/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2077 - accuracy: 0.9157 - precision: 0.9069 - recall: 0.9266 - auc: 0.9732 - val_loss: 0.4815 - val_accuracy: 0.8215 - val_precision: 0.7458 - val_recall: 0.9753 - val_auc: 0.9144\n",
            "Epoch 321/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2091 - accuracy: 0.9154 - precision: 0.9054 - recall: 0.9277 - auc: 0.9729 - val_loss: 0.4809 - val_accuracy: 0.8205 - val_precision: 0.7449 - val_recall: 0.9747 - val_auc: 0.9169\n",
            "Epoch 322/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2059 - accuracy: 0.9167 - precision: 0.9098 - recall: 0.9251 - auc: 0.9736 - val_loss: 0.5200 - val_accuracy: 0.8022 - val_precision: 0.7227 - val_recall: 0.9806 - val_auc: 0.9096\n",
            "Epoch 323/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2152 - accuracy: 0.9122 - precision: 0.9042 - recall: 0.9221 - auc: 0.9713 - val_loss: 0.4608 - val_accuracy: 0.8188 - val_precision: 0.7420 - val_recall: 0.9771 - val_auc: 0.9272\n",
            "Epoch 324/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.2069 - accuracy: 0.9162 - precision: 0.9071 - recall: 0.9275 - auc: 0.9734 - val_loss: 0.4540 - val_accuracy: 0.8235 - val_precision: 0.7487 - val_recall: 0.9738 - val_auc: 0.9256\n",
            "Epoch 325/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2049 - accuracy: 0.9166 - precision: 0.9092 - recall: 0.9256 - auc: 0.9739 - val_loss: 0.4726 - val_accuracy: 0.8228 - val_precision: 0.7490 - val_recall: 0.9708 - val_auc: 0.9168\n",
            "Epoch 326/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.2051 - accuracy: 0.9165 - precision: 0.9073 - recall: 0.9279 - auc: 0.9739 - val_loss: 0.4656 - val_accuracy: 0.8244 - val_precision: 0.7501 - val_recall: 0.9728 - val_auc: 0.9171\n",
            "Epoch 327/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2121 - accuracy: 0.9138 - precision: 0.9044 - recall: 0.9254 - auc: 0.9720 - val_loss: 0.4192 - val_accuracy: 0.8426 - val_precision: 0.7777 - val_recall: 0.9592 - val_auc: 0.9229\n",
            "Epoch 328/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2086 - accuracy: 0.9155 - precision: 0.9080 - recall: 0.9246 - auc: 0.9730 - val_loss: 0.4553 - val_accuracy: 0.8313 - val_precision: 0.7595 - val_recall: 0.9696 - val_auc: 0.9193\n",
            "Epoch 329/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.2052 - accuracy: 0.9172 - precision: 0.9077 - recall: 0.9289 - auc: 0.9739 - val_loss: 0.4571 - val_accuracy: 0.8303 - val_precision: 0.7610 - val_recall: 0.9631 - val_auc: 0.9137\n",
            "Epoch 330/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2032 - accuracy: 0.9176 - precision: 0.9070 - recall: 0.9306 - auc: 0.9744 - val_loss: 0.5359 - val_accuracy: 0.8063 - val_precision: 0.7275 - val_recall: 0.9791 - val_auc: 0.9100\n",
            "Epoch 331/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2054 - accuracy: 0.9167 - precision: 0.9070 - recall: 0.9286 - auc: 0.9738 - val_loss: 0.4840 - val_accuracy: 0.8280 - val_precision: 0.7554 - val_recall: 0.9702 - val_auc: 0.9140\n",
            "Epoch 332/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.2064 - accuracy: 0.9165 - precision: 0.9061 - recall: 0.9293 - auc: 0.9735 - val_loss: 0.4575 - val_accuracy: 0.8328 - val_precision: 0.7596 - val_recall: 0.9734 - val_auc: 0.9259\n",
            "Epoch 333/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.2074 - accuracy: 0.9159 - precision: 0.9073 - recall: 0.9266 - auc: 0.9733 - val_loss: 0.4917 - val_accuracy: 0.8204 - val_precision: 0.7453 - val_recall: 0.9735 - val_auc: 0.9152\n",
            "Epoch 334/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2037 - accuracy: 0.9173 - precision: 0.9111 - recall: 0.9250 - auc: 0.9743 - val_loss: 0.4944 - val_accuracy: 0.8227 - val_precision: 0.7488 - val_recall: 0.9709 - val_auc: 0.9133\n",
            "Epoch 335/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2034 - accuracy: 0.9174 - precision: 0.9082 - recall: 0.9287 - auc: 0.9743 - val_loss: 0.4649 - val_accuracy: 0.8285 - val_precision: 0.7543 - val_recall: 0.9741 - val_auc: 0.9211\n",
            "Epoch 336/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.2045 - accuracy: 0.9173 - precision: 0.9081 - recall: 0.9286 - auc: 0.9741 - val_loss: 0.5077 - val_accuracy: 0.8088 - val_precision: 0.7309 - val_recall: 0.9773 - val_auc: 0.9111\n",
            "Epoch 337/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2036 - accuracy: 0.9175 - precision: 0.9103 - recall: 0.9262 - auc: 0.9743 - val_loss: 0.5205 - val_accuracy: 0.8065 - val_precision: 0.7279 - val_recall: 0.9789 - val_auc: 0.9125\n",
            "Epoch 338/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.2040 - accuracy: 0.9169 - precision: 0.9091 - recall: 0.9265 - auc: 0.9742 - val_loss: 0.5142 - val_accuracy: 0.8147 - val_precision: 0.7381 - val_recall: 0.9752 - val_auc: 0.9123\n",
            "Epoch 339/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2042 - accuracy: 0.9172 - precision: 0.9091 - recall: 0.9270 - auc: 0.9741 - val_loss: 0.5127 - val_accuracy: 0.8119 - val_precision: 0.7340 - val_recall: 0.9781 - val_auc: 0.9137\n",
            "Epoch 340/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.2064 - accuracy: 0.9165 - precision: 0.9075 - recall: 0.9276 - auc: 0.9736 - val_loss: 0.5337 - val_accuracy: 0.8050 - val_precision: 0.7261 - val_recall: 0.9793 - val_auc: 0.9113\n",
            "Epoch 341/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2044 - accuracy: 0.9166 - precision: 0.9090 - recall: 0.9258 - auc: 0.9741 - val_loss: 0.4806 - val_accuracy: 0.8242 - val_precision: 0.7495 - val_recall: 0.9737 - val_auc: 0.9185\n",
            "Epoch 342/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2044 - accuracy: 0.9168 - precision: 0.9077 - recall: 0.9279 - auc: 0.9741 - val_loss: 0.5079 - val_accuracy: 0.8162 - val_precision: 0.7399 - val_recall: 0.9750 - val_auc: 0.9119\n",
            "Epoch 343/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.2032 - accuracy: 0.9179 - precision: 0.9096 - recall: 0.9281 - auc: 0.9744 - val_loss: 0.4312 - val_accuracy: 0.8379 - val_precision: 0.7694 - val_recall: 0.9650 - val_auc: 0.9248\n",
            "Epoch 344/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2025 - accuracy: 0.9179 - precision: 0.9093 - recall: 0.9285 - auc: 0.9745 - val_loss: 0.4523 - val_accuracy: 0.8343 - val_precision: 0.7619 - val_recall: 0.9724 - val_auc: 0.9227\n",
            "Epoch 345/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2034 - accuracy: 0.9174 - precision: 0.9084 - recall: 0.9284 - auc: 0.9743 - val_loss: 0.4638 - val_accuracy: 0.8264 - val_precision: 0.7517 - val_recall: 0.9746 - val_auc: 0.9221\n",
            "Epoch 346/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2080 - accuracy: 0.9154 - precision: 0.9082 - recall: 0.9243 - auc: 0.9732 - val_loss: 0.5064 - val_accuracy: 0.8119 - val_precision: 0.7339 - val_recall: 0.9785 - val_auc: 0.9173\n",
            "Epoch 347/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.2026 - accuracy: 0.9180 - precision: 0.9081 - recall: 0.9302 - auc: 0.9745 - val_loss: 0.5400 - val_accuracy: 0.7987 - val_precision: 0.7183 - val_recall: 0.9827 - val_auc: 0.9138\n",
            "Epoch 348/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2024 - accuracy: 0.9174 - precision: 0.9093 - recall: 0.9274 - auc: 0.9745 - val_loss: 0.5099 - val_accuracy: 0.8103 - val_precision: 0.7315 - val_recall: 0.9800 - val_auc: 0.9155\n",
            "Epoch 349/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2033 - accuracy: 0.9176 - precision: 0.9101 - recall: 0.9268 - auc: 0.9744 - val_loss: 0.4709 - val_accuracy: 0.8238 - val_precision: 0.7489 - val_recall: 0.9742 - val_auc: 0.9193\n",
            "Epoch 350/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.2054 - accuracy: 0.9169 - precision: 0.9102 - recall: 0.9251 - auc: 0.9738 - val_loss: 0.5431 - val_accuracy: 0.8004 - val_precision: 0.7204 - val_recall: 0.9816 - val_auc: 0.9111\n",
            "Epoch 351/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2016 - accuracy: 0.9183 - precision: 0.9103 - recall: 0.9282 - auc: 0.9747 - val_loss: 0.5264 - val_accuracy: 0.7976 - val_precision: 0.7166 - val_recall: 0.9845 - val_auc: 0.9184\n",
            "Epoch 352/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2025 - accuracy: 0.9186 - precision: 0.9106 - recall: 0.9283 - auc: 0.9745 - val_loss: 0.4880 - val_accuracy: 0.8157 - val_precision: 0.7383 - val_recall: 0.9780 - val_auc: 0.9189\n",
            "Epoch 353/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2024 - accuracy: 0.9176 - precision: 0.9081 - recall: 0.9292 - auc: 0.9745 - val_loss: 0.5208 - val_accuracy: 0.8061 - val_precision: 0.7268 - val_recall: 0.9808 - val_auc: 0.9101\n",
            "Epoch 354/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.2019 - accuracy: 0.9180 - precision: 0.9098 - recall: 0.9279 - auc: 0.9747 - val_loss: 0.5082 - val_accuracy: 0.8114 - val_precision: 0.7333 - val_recall: 0.9784 - val_auc: 0.9131\n",
            "Epoch 355/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.2033 - accuracy: 0.9178 - precision: 0.9082 - recall: 0.9296 - auc: 0.9743 - val_loss: 0.5109 - val_accuracy: 0.8149 - val_precision: 0.7368 - val_recall: 0.9795 - val_auc: 0.9156\n",
            "Epoch 356/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.2046 - accuracy: 0.9175 - precision: 0.9116 - recall: 0.9247 - auc: 0.9740 - val_loss: 0.5192 - val_accuracy: 0.8081 - val_precision: 0.7290 - val_recall: 0.9807 - val_auc: 0.9167\n",
            "Epoch 357/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2005 - accuracy: 0.9185 - precision: 0.9121 - recall: 0.9264 - auc: 0.9751 - val_loss: 0.5206 - val_accuracy: 0.8076 - val_precision: 0.7286 - val_recall: 0.9801 - val_auc: 0.9147\n",
            "Epoch 358/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.2018 - accuracy: 0.9182 - precision: 0.9108 - recall: 0.9271 - auc: 0.9747 - val_loss: 0.5361 - val_accuracy: 0.7962 - val_precision: 0.7153 - val_recall: 0.9841 - val_auc: 0.9150\n",
            "Epoch 359/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.2010 - accuracy: 0.9185 - precision: 0.9105 - recall: 0.9283 - auc: 0.9749 - val_loss: 0.5032 - val_accuracy: 0.8101 - val_precision: 0.7315 - val_recall: 0.9798 - val_auc: 0.9159\n",
            "Epoch 360/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2016 - accuracy: 0.9191 - precision: 0.9115 - recall: 0.9284 - auc: 0.9747 - val_loss: 0.4598 - val_accuracy: 0.8256 - val_precision: 0.7548 - val_recall: 0.9644 - val_auc: 0.9120\n",
            "Epoch 361/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.2282 - accuracy: 0.9069 - precision: 0.8977 - recall: 0.9184 - auc: 0.9679 - val_loss: 0.4114 - val_accuracy: 0.8374 - val_precision: 0.7640 - val_recall: 0.9762 - val_auc: 0.9424\n",
            "Epoch 362/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.2147 - accuracy: 0.9129 - precision: 0.9043 - recall: 0.9237 - auc: 0.9714 - val_loss: 0.4184 - val_accuracy: 0.8306 - val_precision: 0.7569 - val_recall: 0.9738 - val_auc: 0.9363\n",
            "Epoch 363/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2061 - accuracy: 0.9163 - precision: 0.9088 - recall: 0.9255 - auc: 0.9736 - val_loss: 0.4153 - val_accuracy: 0.8377 - val_precision: 0.7660 - val_recall: 0.9724 - val_auc: 0.9355\n",
            "Epoch 364/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2022 - accuracy: 0.9188 - precision: 0.9105 - recall: 0.9288 - auc: 0.9746 - val_loss: 0.4951 - val_accuracy: 0.8094 - val_precision: 0.7301 - val_recall: 0.9814 - val_auc: 0.9257\n",
            "Epoch 365/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.2044 - accuracy: 0.9168 - precision: 0.9092 - recall: 0.9260 - auc: 0.9741 - val_loss: 0.4692 - val_accuracy: 0.8302 - val_precision: 0.7564 - val_recall: 0.9739 - val_auc: 0.9233\n",
            "Epoch 366/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1994 - accuracy: 0.9192 - precision: 0.9112 - recall: 0.9290 - auc: 0.9753 - val_loss: 0.5260 - val_accuracy: 0.8089 - val_precision: 0.7300 - val_recall: 0.9803 - val_auc: 0.9165\n",
            "Epoch 367/2000\n",
            "10/10 [==============================] - 4s 385ms/step - loss: 0.1986 - accuracy: 0.9198 - precision: 0.9116 - recall: 0.9298 - auc: 0.9755 - val_loss: 0.5466 - val_accuracy: 0.8041 - val_precision: 0.7244 - val_recall: 0.9815 - val_auc: 0.9152\n",
            "Epoch 368/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1984 - accuracy: 0.9198 - precision: 0.9128 - recall: 0.9282 - auc: 0.9755 - val_loss: 0.5462 - val_accuracy: 0.8023 - val_precision: 0.7223 - val_recall: 0.9821 - val_auc: 0.9136\n",
            "Epoch 369/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.2025 - accuracy: 0.9181 - precision: 0.9098 - recall: 0.9284 - auc: 0.9746 - val_loss: 0.5206 - val_accuracy: 0.8175 - val_precision: 0.7410 - val_recall: 0.9759 - val_auc: 0.9110\n",
            "Epoch 370/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2028 - accuracy: 0.9178 - precision: 0.9094 - recall: 0.9281 - auc: 0.9744 - val_loss: 0.4457 - val_accuracy: 0.8430 - val_precision: 0.7805 - val_recall: 0.9544 - val_auc: 0.9169\n",
            "Epoch 371/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.2004 - accuracy: 0.9189 - precision: 0.9085 - recall: 0.9317 - auc: 0.9751 - val_loss: 0.4777 - val_accuracy: 0.8360 - val_precision: 0.7675 - val_recall: 0.9638 - val_auc: 0.9175\n",
            "Epoch 372/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.2037 - accuracy: 0.9174 - precision: 0.9118 - recall: 0.9243 - auc: 0.9743 - val_loss: 0.5281 - val_accuracy: 0.8153 - val_precision: 0.7373 - val_recall: 0.9794 - val_auc: 0.9178\n",
            "Epoch 373/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.2007 - accuracy: 0.9186 - precision: 0.9122 - recall: 0.9265 - auc: 0.9750 - val_loss: 0.5307 - val_accuracy: 0.8077 - val_precision: 0.7290 - val_recall: 0.9793 - val_auc: 0.9111\n",
            "Epoch 374/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1987 - accuracy: 0.9193 - precision: 0.9121 - recall: 0.9281 - auc: 0.9755 - val_loss: 0.4670 - val_accuracy: 0.8276 - val_precision: 0.7578 - val_recall: 0.9629 - val_auc: 0.9121\n",
            "Epoch 375/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.2041 - accuracy: 0.9174 - precision: 0.9088 - recall: 0.9280 - auc: 0.9742 - val_loss: 0.5225 - val_accuracy: 0.8056 - val_precision: 0.7255 - val_recall: 0.9831 - val_auc: 0.9202\n",
            "Epoch 376/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1984 - accuracy: 0.9197 - precision: 0.9126 - recall: 0.9284 - auc: 0.9755 - val_loss: 0.5522 - val_accuracy: 0.7937 - val_precision: 0.7126 - val_recall: 0.9842 - val_auc: 0.9146\n",
            "Epoch 377/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1995 - accuracy: 0.9197 - precision: 0.9105 - recall: 0.9310 - auc: 0.9753 - val_loss: 0.5478 - val_accuracy: 0.7946 - val_precision: 0.7130 - val_recall: 0.9857 - val_auc: 0.9178\n",
            "Epoch 378/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1989 - accuracy: 0.9196 - precision: 0.9134 - recall: 0.9271 - auc: 0.9754 - val_loss: 0.5079 - val_accuracy: 0.8154 - val_precision: 0.7385 - val_recall: 0.9765 - val_auc: 0.9153\n",
            "Epoch 379/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1987 - accuracy: 0.9193 - precision: 0.9118 - recall: 0.9285 - auc: 0.9755 - val_loss: 0.5059 - val_accuracy: 0.8129 - val_precision: 0.7341 - val_recall: 0.9808 - val_auc: 0.9179\n",
            "Epoch 380/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1975 - accuracy: 0.9203 - precision: 0.9125 - recall: 0.9298 - auc: 0.9758 - val_loss: 0.5082 - val_accuracy: 0.8103 - val_precision: 0.7310 - val_recall: 0.9818 - val_auc: 0.9167\n",
            "Epoch 381/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1955 - accuracy: 0.9212 - precision: 0.9123 - recall: 0.9321 - auc: 0.9762 - val_loss: 0.4960 - val_accuracy: 0.8175 - val_precision: 0.7401 - val_recall: 0.9785 - val_auc: 0.9157\n",
            "Epoch 382/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.2003 - accuracy: 0.9189 - precision: 0.9111 - recall: 0.9285 - auc: 0.9751 - val_loss: 0.5788 - val_accuracy: 0.7818 - val_precision: 0.6997 - val_recall: 0.9870 - val_auc: 0.9102\n",
            "Epoch 383/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1988 - accuracy: 0.9197 - precision: 0.9108 - recall: 0.9306 - auc: 0.9755 - val_loss: 0.4185 - val_accuracy: 0.8395 - val_precision: 0.7671 - val_recall: 0.9748 - val_auc: 0.9344\n",
            "Epoch 384/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1995 - accuracy: 0.9188 - precision: 0.9107 - recall: 0.9288 - auc: 0.9753 - val_loss: 0.4796 - val_accuracy: 0.8189 - val_precision: 0.7418 - val_recall: 0.9779 - val_auc: 0.9218\n",
            "Epoch 385/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1962 - accuracy: 0.9209 - precision: 0.9145 - recall: 0.9287 - auc: 0.9761 - val_loss: 0.4505 - val_accuracy: 0.8300 - val_precision: 0.7578 - val_recall: 0.9700 - val_auc: 0.9201\n",
            "Epoch 386/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1956 - accuracy: 0.9211 - precision: 0.9117 - recall: 0.9326 - auc: 0.9763 - val_loss: 0.4915 - val_accuracy: 0.8200 - val_precision: 0.7436 - val_recall: 0.9766 - val_auc: 0.9148\n",
            "Epoch 387/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1999 - accuracy: 0.9192 - precision: 0.9118 - recall: 0.9283 - auc: 0.9752 - val_loss: 0.4427 - val_accuracy: 0.8358 - val_precision: 0.7641 - val_recall: 0.9712 - val_auc: 0.9258\n",
            "Epoch 388/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1988 - accuracy: 0.9198 - precision: 0.9103 - recall: 0.9313 - auc: 0.9755 - val_loss: 0.5234 - val_accuracy: 0.8072 - val_precision: 0.7283 - val_recall: 0.9799 - val_auc: 0.9125\n",
            "Epoch 389/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1968 - accuracy: 0.9208 - precision: 0.9138 - recall: 0.9293 - auc: 0.9759 - val_loss: 0.4938 - val_accuracy: 0.8231 - val_precision: 0.7479 - val_recall: 0.9745 - val_auc: 0.9168\n",
            "Epoch 390/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.2009 - accuracy: 0.9184 - precision: 0.9123 - recall: 0.9258 - auc: 0.9750 - val_loss: 0.4522 - val_accuracy: 0.8340 - val_precision: 0.7623 - val_recall: 0.9706 - val_auc: 0.9235\n",
            "Epoch 391/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1993 - accuracy: 0.9195 - precision: 0.9129 - recall: 0.9275 - auc: 0.9754 - val_loss: 0.4241 - val_accuracy: 0.8407 - val_precision: 0.7761 - val_recall: 0.9575 - val_auc: 0.9237\n",
            "Epoch 392/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2068 - accuracy: 0.9162 - precision: 0.9079 - recall: 0.9264 - auc: 0.9735 - val_loss: 0.5351 - val_accuracy: 0.8099 - val_precision: 0.7317 - val_recall: 0.9784 - val_auc: 0.9160\n",
            "Epoch 393/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1968 - accuracy: 0.9206 - precision: 0.9138 - recall: 0.9288 - auc: 0.9759 - val_loss: 0.4262 - val_accuracy: 0.8457 - val_precision: 0.7819 - val_recall: 0.9587 - val_auc: 0.9244\n",
            "Epoch 394/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.2004 - accuracy: 0.9187 - precision: 0.9117 - recall: 0.9273 - auc: 0.9751 - val_loss: 0.4342 - val_accuracy: 0.8376 - val_precision: 0.7658 - val_recall: 0.9724 - val_auc: 0.9330\n",
            "Epoch 395/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1952 - accuracy: 0.9214 - precision: 0.9137 - recall: 0.9308 - auc: 0.9763 - val_loss: 0.5560 - val_accuracy: 0.7966 - val_precision: 0.7159 - val_recall: 0.9834 - val_auc: 0.9155\n",
            "Epoch 396/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1967 - accuracy: 0.9205 - precision: 0.9150 - recall: 0.9272 - auc: 0.9760 - val_loss: 0.5603 - val_accuracy: 0.7926 - val_precision: 0.7114 - val_recall: 0.9845 - val_auc: 0.9139\n",
            "Epoch 397/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.2016 - accuracy: 0.9190 - precision: 0.9109 - recall: 0.9288 - auc: 0.9748 - val_loss: 0.4420 - val_accuracy: 0.8386 - val_precision: 0.7729 - val_recall: 0.9587 - val_auc: 0.9187\n",
            "Epoch 398/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1989 - accuracy: 0.9198 - precision: 0.9134 - recall: 0.9276 - auc: 0.9754 - val_loss: 0.4044 - val_accuracy: 0.8482 - val_precision: 0.7822 - val_recall: 0.9649 - val_auc: 0.9331\n",
            "Epoch 399/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1971 - accuracy: 0.9208 - precision: 0.9114 - recall: 0.9321 - auc: 0.9758 - val_loss: 0.5059 - val_accuracy: 0.8134 - val_precision: 0.7352 - val_recall: 0.9795 - val_auc: 0.9210\n",
            "Epoch 400/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1959 - accuracy: 0.9211 - precision: 0.9133 - recall: 0.9307 - auc: 0.9762 - val_loss: 0.5424 - val_accuracy: 0.8012 - val_precision: 0.7210 - val_recall: 0.9827 - val_auc: 0.9173\n",
            "Epoch 401/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1984 - accuracy: 0.9200 - precision: 0.9122 - recall: 0.9294 - auc: 0.9755 - val_loss: 0.5407 - val_accuracy: 0.8039 - val_precision: 0.7240 - val_recall: 0.9819 - val_auc: 0.9139\n",
            "Epoch 402/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1982 - accuracy: 0.9196 - precision: 0.9115 - recall: 0.9295 - auc: 0.9756 - val_loss: 0.5289 - val_accuracy: 0.8076 - val_precision: 0.7287 - val_recall: 0.9800 - val_auc: 0.9168\n",
            "Epoch 403/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1965 - accuracy: 0.9207 - precision: 0.9133 - recall: 0.9297 - auc: 0.9760 - val_loss: 0.4957 - val_accuracy: 0.8215 - val_precision: 0.7465 - val_recall: 0.9734 - val_auc: 0.9153\n",
            "Epoch 404/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1949 - accuracy: 0.9213 - precision: 0.9150 - recall: 0.9288 - auc: 0.9764 - val_loss: 0.5136 - val_accuracy: 0.8120 - val_precision: 0.7337 - val_recall: 0.9793 - val_auc: 0.9158\n",
            "Epoch 405/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1927 - accuracy: 0.9221 - precision: 0.9154 - recall: 0.9302 - auc: 0.9769 - val_loss: 0.5388 - val_accuracy: 0.8079 - val_precision: 0.7293 - val_recall: 0.9793 - val_auc: 0.9117\n",
            "Epoch 406/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1958 - accuracy: 0.9209 - precision: 0.9137 - recall: 0.9295 - auc: 0.9762 - val_loss: 0.5575 - val_accuracy: 0.7998 - val_precision: 0.7195 - val_recall: 0.9825 - val_auc: 0.9107\n",
            "Epoch 407/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1997 - accuracy: 0.9191 - precision: 0.9099 - recall: 0.9303 - auc: 0.9753 - val_loss: 0.4731 - val_accuracy: 0.8196 - val_precision: 0.7433 - val_recall: 0.9763 - val_auc: 0.9252\n",
            "Epoch 408/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1947 - accuracy: 0.9215 - precision: 0.9151 - recall: 0.9293 - auc: 0.9764 - val_loss: 0.5049 - val_accuracy: 0.8103 - val_precision: 0.7313 - val_recall: 0.9810 - val_auc: 0.9219\n",
            "Epoch 409/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1993 - accuracy: 0.9191 - precision: 0.9120 - recall: 0.9278 - auc: 0.9754 - val_loss: 0.5155 - val_accuracy: 0.8015 - val_precision: 0.7208 - val_recall: 0.9838 - val_auc: 0.9191\n",
            "Epoch 410/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.1963 - accuracy: 0.9210 - precision: 0.9139 - recall: 0.9297 - auc: 0.9761 - val_loss: 0.5252 - val_accuracy: 0.7987 - val_precision: 0.7177 - val_recall: 0.9845 - val_auc: 0.9197\n",
            "Epoch 411/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1999 - accuracy: 0.9190 - precision: 0.9126 - recall: 0.9269 - auc: 0.9751 - val_loss: 0.4934 - val_accuracy: 0.8142 - val_precision: 0.7371 - val_recall: 0.9765 - val_auc: 0.9176\n",
            "Epoch 412/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1946 - accuracy: 0.9218 - precision: 0.9150 - recall: 0.9301 - auc: 0.9764 - val_loss: 0.5101 - val_accuracy: 0.8115 - val_precision: 0.7332 - val_recall: 0.9790 - val_auc: 0.9169\n",
            "Epoch 413/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1942 - accuracy: 0.9221 - precision: 0.9146 - recall: 0.9311 - auc: 0.9766 - val_loss: 0.5436 - val_accuracy: 0.8034 - val_precision: 0.7233 - val_recall: 0.9824 - val_auc: 0.9150\n",
            "Epoch 414/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1957 - accuracy: 0.9211 - precision: 0.9131 - recall: 0.9309 - auc: 0.9762 - val_loss: 0.4908 - val_accuracy: 0.8227 - val_precision: 0.7479 - val_recall: 0.9733 - val_auc: 0.9149\n",
            "Epoch 415/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1923 - accuracy: 0.9227 - precision: 0.9156 - recall: 0.9312 - auc: 0.9770 - val_loss: 0.5083 - val_accuracy: 0.8167 - val_precision: 0.7403 - val_recall: 0.9755 - val_auc: 0.9121\n",
            "Epoch 416/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1942 - accuracy: 0.9218 - precision: 0.9143 - recall: 0.9308 - auc: 0.9766 - val_loss: 0.5291 - val_accuracy: 0.8129 - val_precision: 0.7348 - val_recall: 0.9791 - val_auc: 0.9163\n",
            "Epoch 417/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1907 - accuracy: 0.9240 - precision: 0.9160 - recall: 0.9337 - auc: 0.9773 - val_loss: 0.4864 - val_accuracy: 0.8268 - val_precision: 0.7520 - val_recall: 0.9750 - val_auc: 0.9215\n",
            "Epoch 418/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1956 - accuracy: 0.9209 - precision: 0.9117 - recall: 0.9321 - auc: 0.9763 - val_loss: 0.4945 - val_accuracy: 0.8214 - val_precision: 0.7467 - val_recall: 0.9726 - val_auc: 0.9146\n",
            "Epoch 419/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1923 - accuracy: 0.9220 - precision: 0.9153 - recall: 0.9302 - auc: 0.9771 - val_loss: 0.5366 - val_accuracy: 0.8058 - val_precision: 0.7266 - val_recall: 0.9803 - val_auc: 0.9137\n",
            "Epoch 420/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1950 - accuracy: 0.9214 - precision: 0.9148 - recall: 0.9294 - auc: 0.9764 - val_loss: 0.5129 - val_accuracy: 0.8127 - val_precision: 0.7349 - val_recall: 0.9782 - val_auc: 0.9139\n",
            "Epoch 421/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1980 - accuracy: 0.9202 - precision: 0.9125 - recall: 0.9294 - auc: 0.9757 - val_loss: 0.4439 - val_accuracy: 0.8323 - val_precision: 0.7592 - val_recall: 0.9731 - val_auc: 0.9280\n",
            "Epoch 422/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1922 - accuracy: 0.9229 - precision: 0.9154 - recall: 0.9321 - auc: 0.9770 - val_loss: 0.5111 - val_accuracy: 0.8046 - val_precision: 0.7242 - val_recall: 0.9836 - val_auc: 0.9213\n",
            "Epoch 423/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1947 - accuracy: 0.9218 - precision: 0.9140 - recall: 0.9313 - auc: 0.9765 - val_loss: 0.5080 - val_accuracy: 0.8142 - val_precision: 0.7362 - val_recall: 0.9789 - val_auc: 0.9155\n",
            "Epoch 424/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1920 - accuracy: 0.9226 - precision: 0.9146 - recall: 0.9323 - auc: 0.9771 - val_loss: 0.4822 - val_accuracy: 0.8233 - val_precision: 0.7468 - val_recall: 0.9782 - val_auc: 0.9219\n",
            "Epoch 425/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1924 - accuracy: 0.9231 - precision: 0.9161 - recall: 0.9315 - auc: 0.9770 - val_loss: 0.4891 - val_accuracy: 0.8200 - val_precision: 0.7421 - val_recall: 0.9807 - val_auc: 0.9249\n",
            "Epoch 426/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1932 - accuracy: 0.9229 - precision: 0.9142 - recall: 0.9335 - auc: 0.9768 - val_loss: 0.5877 - val_accuracy: 0.7931 - val_precision: 0.7124 - val_recall: 0.9830 - val_auc: 0.9074\n",
            "Epoch 427/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1941 - accuracy: 0.9218 - precision: 0.9149 - recall: 0.9302 - auc: 0.9767 - val_loss: 0.4834 - val_accuracy: 0.8254 - val_precision: 0.7486 - val_recall: 0.9797 - val_auc: 0.9278\n",
            "Epoch 428/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1892 - accuracy: 0.9241 - precision: 0.9171 - recall: 0.9326 - auc: 0.9778 - val_loss: 0.5605 - val_accuracy: 0.7928 - val_precision: 0.7113 - val_recall: 0.9854 - val_auc: 0.9141\n",
            "Epoch 429/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1962 - accuracy: 0.9210 - precision: 0.9122 - recall: 0.9316 - auc: 0.9761 - val_loss: 0.3878 - val_accuracy: 0.8526 - val_precision: 0.7981 - val_recall: 0.9439 - val_auc: 0.9267\n",
            "Epoch 430/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1951 - accuracy: 0.9208 - precision: 0.9136 - recall: 0.9296 - auc: 0.9764 - val_loss: 0.4401 - val_accuracy: 0.8340 - val_precision: 0.7614 - val_recall: 0.9726 - val_auc: 0.9311\n",
            "Epoch 431/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1905 - accuracy: 0.9237 - precision: 0.9177 - recall: 0.9310 - auc: 0.9774 - val_loss: 0.4528 - val_accuracy: 0.8320 - val_precision: 0.7658 - val_recall: 0.9563 - val_auc: 0.9133\n",
            "Epoch 432/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1920 - accuracy: 0.9230 - precision: 0.9157 - recall: 0.9317 - auc: 0.9771 - val_loss: 0.5369 - val_accuracy: 0.7993 - val_precision: 0.7187 - val_recall: 0.9833 - val_auc: 0.9168\n",
            "Epoch 433/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1901 - accuracy: 0.9234 - precision: 0.9165 - recall: 0.9318 - auc: 0.9775 - val_loss: 0.5118 - val_accuracy: 0.8090 - val_precision: 0.7296 - val_recall: 0.9814 - val_auc: 0.9178\n",
            "Epoch 434/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1938 - accuracy: 0.9224 - precision: 0.9159 - recall: 0.9303 - auc: 0.9767 - val_loss: 0.5190 - val_accuracy: 0.8101 - val_precision: 0.7308 - val_recall: 0.9819 - val_auc: 0.9195\n",
            "Epoch 435/2000\n",
            "10/10 [==============================] - 4s 421ms/step - loss: 0.1903 - accuracy: 0.9242 - precision: 0.9160 - recall: 0.9340 - auc: 0.9774 - val_loss: 0.5050 - val_accuracy: 0.8148 - val_precision: 0.7372 - val_recall: 0.9782 - val_auc: 0.9163\n",
            "Epoch 436/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1923 - accuracy: 0.9226 - precision: 0.9150 - recall: 0.9317 - auc: 0.9770 - val_loss: 0.5159 - val_accuracy: 0.8127 - val_precision: 0.7341 - val_recall: 0.9804 - val_auc: 0.9202\n",
            "Epoch 437/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1893 - accuracy: 0.9237 - precision: 0.9169 - recall: 0.9318 - auc: 0.9777 - val_loss: 0.4990 - val_accuracy: 0.8192 - val_precision: 0.7427 - val_recall: 0.9765 - val_auc: 0.9217\n",
            "Epoch 438/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1953 - accuracy: 0.9214 - precision: 0.9152 - recall: 0.9290 - auc: 0.9763 - val_loss: 0.4379 - val_accuracy: 0.8397 - val_precision: 0.7744 - val_recall: 0.9585 - val_auc: 0.9213\n",
            "Epoch 439/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1922 - accuracy: 0.9226 - precision: 0.9145 - recall: 0.9323 - auc: 0.9770 - val_loss: 0.5150 - val_accuracy: 0.8126 - val_precision: 0.7342 - val_recall: 0.9799 - val_auc: 0.9205\n",
            "Epoch 440/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1911 - accuracy: 0.9238 - precision: 0.9175 - recall: 0.9313 - auc: 0.9773 - val_loss: 0.4912 - val_accuracy: 0.8130 - val_precision: 0.7340 - val_recall: 0.9814 - val_auc: 0.9253\n",
            "Epoch 441/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.1909 - accuracy: 0.9239 - precision: 0.9145 - recall: 0.9353 - auc: 0.9773 - val_loss: 0.5658 - val_accuracy: 0.7860 - val_precision: 0.7044 - val_recall: 0.9852 - val_auc: 0.9119\n",
            "Epoch 442/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1910 - accuracy: 0.9233 - precision: 0.9166 - recall: 0.9314 - auc: 0.9773 - val_loss: 0.4708 - val_accuracy: 0.8268 - val_precision: 0.7532 - val_recall: 0.9720 - val_auc: 0.9212\n",
            "Epoch 443/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1917 - accuracy: 0.9231 - precision: 0.9155 - recall: 0.9323 - auc: 0.9771 - val_loss: 0.4881 - val_accuracy: 0.8210 - val_precision: 0.7453 - val_recall: 0.9754 - val_auc: 0.9201\n",
            "Epoch 444/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1895 - accuracy: 0.9234 - precision: 0.9161 - recall: 0.9322 - auc: 0.9777 - val_loss: 0.4962 - val_accuracy: 0.8159 - val_precision: 0.7386 - val_recall: 0.9779 - val_auc: 0.9176\n",
            "Epoch 445/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1944 - accuracy: 0.9215 - precision: 0.9146 - recall: 0.9298 - auc: 0.9765 - val_loss: 0.5261 - val_accuracy: 0.8006 - val_precision: 0.7199 - val_recall: 0.9840 - val_auc: 0.9179\n",
            "Epoch 446/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1959 - accuracy: 0.9211 - precision: 0.9143 - recall: 0.9293 - auc: 0.9762 - val_loss: 0.5094 - val_accuracy: 0.7983 - val_precision: 0.7172 - val_recall: 0.9850 - val_auc: 0.9243\n",
            "Epoch 447/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1915 - accuracy: 0.9229 - precision: 0.9140 - recall: 0.9338 - auc: 0.9772 - val_loss: 0.4489 - val_accuracy: 0.8289 - val_precision: 0.7551 - val_recall: 0.9735 - val_auc: 0.9257\n",
            "Epoch 448/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1898 - accuracy: 0.9243 - precision: 0.9180 - recall: 0.9318 - auc: 0.9776 - val_loss: 0.5172 - val_accuracy: 0.8085 - val_precision: 0.7291 - val_recall: 0.9817 - val_auc: 0.9219\n",
            "Epoch 449/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1879 - accuracy: 0.9247 - precision: 0.9194 - recall: 0.9311 - auc: 0.9780 - val_loss: 0.5274 - val_accuracy: 0.8040 - val_precision: 0.7244 - val_recall: 0.9813 - val_auc: 0.9165\n",
            "Epoch 450/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1927 - accuracy: 0.9229 - precision: 0.9153 - recall: 0.9320 - auc: 0.9769 - val_loss: 0.4919 - val_accuracy: 0.8181 - val_precision: 0.7419 - val_recall: 0.9754 - val_auc: 0.9165\n",
            "Epoch 451/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1898 - accuracy: 0.9244 - precision: 0.9186 - recall: 0.9314 - auc: 0.9776 - val_loss: 0.5216 - val_accuracy: 0.8101 - val_precision: 0.7311 - val_recall: 0.9809 - val_auc: 0.9187\n",
            "Epoch 452/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1919 - accuracy: 0.9230 - precision: 0.9167 - recall: 0.9306 - auc: 0.9771 - val_loss: 0.3706 - val_accuracy: 0.8588 - val_precision: 0.7988 - val_recall: 0.9593 - val_auc: 0.9408\n",
            "Epoch 453/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1897 - accuracy: 0.9239 - precision: 0.9166 - recall: 0.9328 - auc: 0.9776 - val_loss: 0.4606 - val_accuracy: 0.8348 - val_precision: 0.7620 - val_recall: 0.9734 - val_auc: 0.9294\n",
            "Epoch 454/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1931 - accuracy: 0.9227 - precision: 0.9162 - recall: 0.9306 - auc: 0.9768 - val_loss: 0.4643 - val_accuracy: 0.8290 - val_precision: 0.7599 - val_recall: 0.9618 - val_auc: 0.9154\n",
            "Epoch 455/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1961 - accuracy: 0.9206 - precision: 0.9121 - recall: 0.9309 - auc: 0.9761 - val_loss: 0.5340 - val_accuracy: 0.8115 - val_precision: 0.7338 - val_recall: 0.9774 - val_auc: 0.9120\n",
            "Epoch 456/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1928 - accuracy: 0.9223 - precision: 0.9145 - recall: 0.9317 - auc: 0.9769 - val_loss: 0.4985 - val_accuracy: 0.8207 - val_precision: 0.7442 - val_recall: 0.9772 - val_auc: 0.9191\n",
            "Epoch 457/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1913 - accuracy: 0.9232 - precision: 0.9143 - recall: 0.9340 - auc: 0.9772 - val_loss: 0.4453 - val_accuracy: 0.8350 - val_precision: 0.7616 - val_recall: 0.9751 - val_auc: 0.9295\n",
            "Epoch 458/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1879 - accuracy: 0.9247 - precision: 0.9171 - recall: 0.9339 - auc: 0.9781 - val_loss: 0.5051 - val_accuracy: 0.8158 - val_precision: 0.7389 - val_recall: 0.9766 - val_auc: 0.9207\n",
            "Epoch 459/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1953 - accuracy: 0.9217 - precision: 0.9156 - recall: 0.9291 - auc: 0.9763 - val_loss: 0.3576 - val_accuracy: 0.8480 - val_precision: 0.8466 - val_recall: 0.8497 - val_auc: 0.9243\n",
            "Epoch 460/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1881 - accuracy: 0.9246 - precision: 0.9175 - recall: 0.9331 - auc: 0.9781 - val_loss: 0.4987 - val_accuracy: 0.8185 - val_precision: 0.7416 - val_recall: 0.9774 - val_auc: 0.9240\n",
            "Epoch 461/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1888 - accuracy: 0.9245 - precision: 0.9167 - recall: 0.9338 - auc: 0.9779 - val_loss: 0.3913 - val_accuracy: 0.8518 - val_precision: 0.7867 - val_recall: 0.9652 - val_auc: 0.9372\n",
            "Epoch 462/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1852 - accuracy: 0.9256 - precision: 0.9182 - recall: 0.9345 - auc: 0.9786 - val_loss: 0.3564 - val_accuracy: 0.8500 - val_precision: 0.8460 - val_recall: 0.8557 - val_auc: 0.9250\n",
            "Epoch 463/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.1926 - accuracy: 0.9226 - precision: 0.9161 - recall: 0.9305 - auc: 0.9769 - val_loss: 0.4853 - val_accuracy: 0.8187 - val_precision: 0.7410 - val_recall: 0.9799 - val_auc: 0.9263\n",
            "Epoch 464/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1848 - accuracy: 0.9263 - precision: 0.9194 - recall: 0.9347 - auc: 0.9787 - val_loss: 0.3537 - val_accuracy: 0.8631 - val_precision: 0.8064 - val_recall: 0.9553 - val_auc: 0.9410\n",
            "Epoch 465/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1871 - accuracy: 0.9252 - precision: 0.9187 - recall: 0.9329 - auc: 0.9782 - val_loss: 0.5309 - val_accuracy: 0.8069 - val_precision: 0.7276 - val_recall: 0.9810 - val_auc: 0.9141\n",
            "Epoch 466/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1849 - accuracy: 0.9259 - precision: 0.9188 - recall: 0.9346 - auc: 0.9787 - val_loss: 0.4362 - val_accuracy: 0.8433 - val_precision: 0.7755 - val_recall: 0.9660 - val_auc: 0.9305\n",
            "Epoch 467/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1883 - accuracy: 0.9255 - precision: 0.9183 - recall: 0.9341 - auc: 0.9780 - val_loss: 0.4888 - val_accuracy: 0.8266 - val_precision: 0.7519 - val_recall: 0.9746 - val_auc: 0.9207\n",
            "Epoch 468/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1866 - accuracy: 0.9257 - precision: 0.9184 - recall: 0.9344 - auc: 0.9783 - val_loss: 0.3754 - val_accuracy: 0.8583 - val_precision: 0.8011 - val_recall: 0.9532 - val_auc: 0.9359\n",
            "Epoch 469/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.1859 - accuracy: 0.9259 - precision: 0.9208 - recall: 0.9321 - auc: 0.9785 - val_loss: 0.4167 - val_accuracy: 0.8435 - val_precision: 0.7734 - val_recall: 0.9716 - val_auc: 0.9348\n",
            "Epoch 470/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1853 - accuracy: 0.9260 - precision: 0.9198 - recall: 0.9333 - auc: 0.9786 - val_loss: 0.4533 - val_accuracy: 0.8364 - val_precision: 0.7671 - val_recall: 0.9660 - val_auc: 0.9206\n",
            "Epoch 471/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1853 - accuracy: 0.9258 - precision: 0.9192 - recall: 0.9338 - auc: 0.9786 - val_loss: 0.5136 - val_accuracy: 0.8191 - val_precision: 0.7432 - val_recall: 0.9749 - val_auc: 0.9142\n",
            "Epoch 472/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1889 - accuracy: 0.9245 - precision: 0.9187 - recall: 0.9314 - auc: 0.9778 - val_loss: 0.5214 - val_accuracy: 0.8161 - val_precision: 0.7379 - val_recall: 0.9802 - val_auc: 0.9194\n",
            "Epoch 473/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1831 - accuracy: 0.9267 - precision: 0.9210 - recall: 0.9335 - auc: 0.9792 - val_loss: 0.3964 - val_accuracy: 0.8538 - val_precision: 0.7897 - val_recall: 0.9644 - val_auc: 0.9373\n",
            "Epoch 474/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1877 - accuracy: 0.9248 - precision: 0.9195 - recall: 0.9311 - auc: 0.9781 - val_loss: 0.5167 - val_accuracy: 0.8147 - val_precision: 0.7361 - val_recall: 0.9810 - val_auc: 0.9236\n",
            "Epoch 475/2000\n",
            "10/10 [==============================] - 5s 481ms/step - loss: 0.1793 - accuracy: 0.9284 - precision: 0.9228 - recall: 0.9351 - auc: 0.9799 - val_loss: 0.5464 - val_accuracy: 0.7969 - val_precision: 0.7156 - val_recall: 0.9855 - val_auc: 0.9215\n",
            "Epoch 476/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1824 - accuracy: 0.9272 - precision: 0.9206 - recall: 0.9350 - auc: 0.9793 - val_loss: 0.3815 - val_accuracy: 0.8326 - val_precision: 0.8448 - val_recall: 0.8149 - val_auc: 0.9174\n",
            "Epoch 477/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1842 - accuracy: 0.9268 - precision: 0.9214 - recall: 0.9333 - auc: 0.9789 - val_loss: 0.5120 - val_accuracy: 0.8072 - val_precision: 0.7277 - val_recall: 0.9815 - val_auc: 0.9218\n",
            "Epoch 478/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1830 - accuracy: 0.9276 - precision: 0.9219 - recall: 0.9345 - auc: 0.9792 - val_loss: 0.5369 - val_accuracy: 0.8004 - val_precision: 0.7198 - val_recall: 0.9835 - val_auc: 0.9191\n",
            "Epoch 479/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1820 - accuracy: 0.9274 - precision: 0.9227 - recall: 0.9330 - auc: 0.9794 - val_loss: 0.5872 - val_accuracy: 0.7810 - val_precision: 0.6987 - val_recall: 0.9877 - val_auc: 0.9137\n",
            "Epoch 480/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1822 - accuracy: 0.9276 - precision: 0.9222 - recall: 0.9341 - auc: 0.9793 - val_loss: 0.5137 - val_accuracy: 0.8068 - val_precision: 0.7278 - val_recall: 0.9799 - val_auc: 0.9192\n",
            "Epoch 481/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1864 - accuracy: 0.9257 - precision: 0.9182 - recall: 0.9347 - auc: 0.9784 - val_loss: 0.5656 - val_accuracy: 0.7957 - val_precision: 0.7145 - val_recall: 0.9845 - val_auc: 0.9144\n",
            "Epoch 482/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1829 - accuracy: 0.9275 - precision: 0.9216 - recall: 0.9347 - auc: 0.9792 - val_loss: 0.3929 - val_accuracy: 0.8221 - val_precision: 0.8534 - val_recall: 0.7777 - val_auc: 0.9134\n",
            "Epoch 483/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1774 - accuracy: 0.9297 - precision: 0.9232 - recall: 0.9373 - auc: 0.9804 - val_loss: 0.4966 - val_accuracy: 0.8215 - val_precision: 0.7469 - val_recall: 0.9725 - val_auc: 0.9182\n",
            "Epoch 484/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1809 - accuracy: 0.9281 - precision: 0.9225 - recall: 0.9347 - auc: 0.9796 - val_loss: 0.5232 - val_accuracy: 0.8126 - val_precision: 0.7337 - val_recall: 0.9809 - val_auc: 0.9214\n",
            "Epoch 485/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1792 - accuracy: 0.9286 - precision: 0.9230 - recall: 0.9353 - auc: 0.9800 - val_loss: 0.5269 - val_accuracy: 0.8146 - val_precision: 0.7373 - val_recall: 0.9773 - val_auc: 0.9170\n",
            "Epoch 486/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1821 - accuracy: 0.9279 - precision: 0.9234 - recall: 0.9334 - auc: 0.9793 - val_loss: 0.5377 - val_accuracy: 0.8045 - val_precision: 0.7249 - val_recall: 0.9814 - val_auc: 0.9187\n",
            "Epoch 487/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1837 - accuracy: 0.9266 - precision: 0.9205 - recall: 0.9338 - auc: 0.9790 - val_loss: 0.3236 - val_accuracy: 0.8674 - val_precision: 0.8301 - val_recall: 0.9239 - val_auc: 0.9419\n",
            "Epoch 488/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1763 - accuracy: 0.9298 - precision: 0.9240 - recall: 0.9366 - auc: 0.9806 - val_loss: 0.5503 - val_accuracy: 0.8048 - val_precision: 0.7248 - val_recall: 0.9824 - val_auc: 0.9158\n",
            "Epoch 489/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1828 - accuracy: 0.9277 - precision: 0.9227 - recall: 0.9335 - auc: 0.9792 - val_loss: 0.6597 - val_accuracy: 0.7199 - val_precision: 0.8783 - val_recall: 0.5102 - val_auc: 0.8647\n",
            "Epoch 490/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1918 - accuracy: 0.9235 - precision: 0.9178 - recall: 0.9302 - auc: 0.9771 - val_loss: 0.4648 - val_accuracy: 0.8183 - val_precision: 0.7414 - val_recall: 0.9774 - val_auc: 0.9270\n",
            "Epoch 491/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2006 - accuracy: 0.9186 - precision: 0.9099 - recall: 0.9292 - auc: 0.9751 - val_loss: 0.4811 - val_accuracy: 0.8220 - val_precision: 0.7470 - val_recall: 0.9737 - val_auc: 0.9211\n",
            "Epoch 492/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1966 - accuracy: 0.9205 - precision: 0.9135 - recall: 0.9289 - auc: 0.9760 - val_loss: 0.4786 - val_accuracy: 0.8227 - val_precision: 0.7477 - val_recall: 0.9740 - val_auc: 0.9178\n",
            "Epoch 493/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1962 - accuracy: 0.9208 - precision: 0.9138 - recall: 0.9293 - auc: 0.9761 - val_loss: 0.4875 - val_accuracy: 0.8213 - val_precision: 0.7448 - val_recall: 0.9774 - val_auc: 0.9219\n",
            "Epoch 494/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1959 - accuracy: 0.9216 - precision: 0.9134 - recall: 0.9315 - auc: 0.9761 - val_loss: 0.4689 - val_accuracy: 0.8286 - val_precision: 0.7593 - val_recall: 0.9619 - val_auc: 0.9129\n",
            "Epoch 495/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.2030 - accuracy: 0.9179 - precision: 0.9103 - recall: 0.9273 - auc: 0.9744 - val_loss: 0.4284 - val_accuracy: 0.8291 - val_precision: 0.7539 - val_recall: 0.9771 - val_auc: 0.9368\n",
            "Epoch 496/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1948 - accuracy: 0.9213 - precision: 0.9126 - recall: 0.9320 - auc: 0.9764 - val_loss: 0.4385 - val_accuracy: 0.8327 - val_precision: 0.7595 - val_recall: 0.9736 - val_auc: 0.9313\n",
            "Epoch 497/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1904 - accuracy: 0.9236 - precision: 0.9159 - recall: 0.9328 - auc: 0.9774 - val_loss: 0.4748 - val_accuracy: 0.8199 - val_precision: 0.7422 - val_recall: 0.9800 - val_auc: 0.9282\n",
            "Epoch 498/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1963 - accuracy: 0.9208 - precision: 0.9130 - recall: 0.9302 - auc: 0.9760 - val_loss: 0.4218 - val_accuracy: 0.8345 - val_precision: 0.7685 - val_recall: 0.9573 - val_auc: 0.9215\n",
            "Epoch 499/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1943 - accuracy: 0.9220 - precision: 0.9141 - recall: 0.9317 - auc: 0.9765 - val_loss: 0.4682 - val_accuracy: 0.8248 - val_precision: 0.7499 - val_recall: 0.9745 - val_auc: 0.9219\n",
            "Epoch 500/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1939 - accuracy: 0.9221 - precision: 0.9138 - recall: 0.9322 - auc: 0.9766 - val_loss: 0.4599 - val_accuracy: 0.8308 - val_precision: 0.7580 - val_recall: 0.9718 - val_auc: 0.9238\n",
            "Epoch 501/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1970 - accuracy: 0.9201 - precision: 0.9115 - recall: 0.9307 - auc: 0.9758 - val_loss: 0.4689 - val_accuracy: 0.8250 - val_precision: 0.7505 - val_recall: 0.9736 - val_auc: 0.9222\n",
            "Epoch 502/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1911 - accuracy: 0.9233 - precision: 0.9149 - recall: 0.9334 - auc: 0.9773 - val_loss: 0.4597 - val_accuracy: 0.8301 - val_precision: 0.7577 - val_recall: 0.9703 - val_auc: 0.9222\n",
            "Epoch 503/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1918 - accuracy: 0.9226 - precision: 0.9155 - recall: 0.9311 - auc: 0.9771 - val_loss: 0.5119 - val_accuracy: 0.8092 - val_precision: 0.7303 - val_recall: 0.9802 - val_auc: 0.9172\n",
            "Epoch 504/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1921 - accuracy: 0.9230 - precision: 0.9142 - recall: 0.9336 - auc: 0.9770 - val_loss: 0.5281 - val_accuracy: 0.8009 - val_precision: 0.7208 - val_recall: 0.9822 - val_auc: 0.9137\n",
            "Epoch 505/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1921 - accuracy: 0.9230 - precision: 0.9150 - recall: 0.9327 - auc: 0.9770 - val_loss: 0.4959 - val_accuracy: 0.8124 - val_precision: 0.7341 - val_recall: 0.9794 - val_auc: 0.9191\n",
            "Epoch 506/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1926 - accuracy: 0.9228 - precision: 0.9148 - recall: 0.9324 - auc: 0.9769 - val_loss: 0.4611 - val_accuracy: 0.8218 - val_precision: 0.7457 - val_recall: 0.9765 - val_auc: 0.9244\n",
            "Epoch 507/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1998 - accuracy: 0.9196 - precision: 0.9109 - recall: 0.9301 - auc: 0.9753 - val_loss: 0.4788 - val_accuracy: 0.8076 - val_precision: 0.7283 - val_recall: 0.9811 - val_auc: 0.9258\n",
            "Epoch 508/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1926 - accuracy: 0.9226 - precision: 0.9138 - recall: 0.9332 - auc: 0.9769 - val_loss: 0.4724 - val_accuracy: 0.8179 - val_precision: 0.7404 - val_recall: 0.9789 - val_auc: 0.9270\n",
            "Epoch 509/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1935 - accuracy: 0.9218 - precision: 0.9146 - recall: 0.9305 - auc: 0.9767 - val_loss: 0.5053 - val_accuracy: 0.8120 - val_precision: 0.7337 - val_recall: 0.9792 - val_auc: 0.9193\n",
            "Epoch 510/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1931 - accuracy: 0.9222 - precision: 0.9125 - recall: 0.9339 - auc: 0.9768 - val_loss: 0.5263 - val_accuracy: 0.8105 - val_precision: 0.7330 - val_recall: 0.9766 - val_auc: 0.9113\n",
            "Epoch 511/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1954 - accuracy: 0.9215 - precision: 0.9144 - recall: 0.9300 - auc: 0.9762 - val_loss: 0.4906 - val_accuracy: 0.8164 - val_precision: 0.7389 - val_recall: 0.9783 - val_auc: 0.9226\n",
            "Epoch 512/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1902 - accuracy: 0.9234 - precision: 0.9169 - recall: 0.9311 - auc: 0.9774 - val_loss: 0.4493 - val_accuracy: 0.8325 - val_precision: 0.7604 - val_recall: 0.9706 - val_auc: 0.9251\n",
            "Epoch 513/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1918 - accuracy: 0.9228 - precision: 0.9154 - recall: 0.9317 - auc: 0.9771 - val_loss: 0.4809 - val_accuracy: 0.8221 - val_precision: 0.7463 - val_recall: 0.9760 - val_auc: 0.9209\n",
            "Epoch 514/2000\n",
            "10/10 [==============================] - 4s 423ms/step - loss: 0.1918 - accuracy: 0.9227 - precision: 0.9136 - recall: 0.9338 - auc: 0.9771 - val_loss: 0.4879 - val_accuracy: 0.8193 - val_precision: 0.7428 - val_recall: 0.9764 - val_auc: 0.9234\n",
            "Epoch 515/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.1897 - accuracy: 0.9234 - precision: 0.9169 - recall: 0.9314 - auc: 0.9777 - val_loss: 0.5124 - val_accuracy: 0.8130 - val_precision: 0.7355 - val_recall: 0.9772 - val_auc: 0.9187\n",
            "Epoch 516/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1925 - accuracy: 0.9223 - precision: 0.9150 - recall: 0.9311 - auc: 0.9769 - val_loss: 0.4960 - val_accuracy: 0.8156 - val_precision: 0.7385 - val_recall: 0.9771 - val_auc: 0.9201\n",
            "Epoch 517/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1908 - accuracy: 0.9229 - precision: 0.9132 - recall: 0.9346 - auc: 0.9773 - val_loss: 0.4616 - val_accuracy: 0.8270 - val_precision: 0.7528 - val_recall: 0.9734 - val_auc: 0.9245\n",
            "Epoch 518/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1955 - accuracy: 0.9208 - precision: 0.9134 - recall: 0.9299 - auc: 0.9762 - val_loss: 0.5053 - val_accuracy: 0.8159 - val_precision: 0.7390 - val_recall: 0.9767 - val_auc: 0.9175\n",
            "Epoch 519/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1938 - accuracy: 0.9214 - precision: 0.9132 - recall: 0.9314 - auc: 0.9766 - val_loss: 0.4767 - val_accuracy: 0.8203 - val_precision: 0.7434 - val_recall: 0.9782 - val_auc: 0.9284\n",
            "Epoch 520/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1909 - accuracy: 0.9230 - precision: 0.9157 - recall: 0.9318 - auc: 0.9773 - val_loss: 0.5018 - val_accuracy: 0.8139 - val_precision: 0.7359 - val_recall: 0.9792 - val_auc: 0.9224\n",
            "Epoch 521/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1896 - accuracy: 0.9236 - precision: 0.9154 - recall: 0.9336 - auc: 0.9776 - val_loss: 0.4719 - val_accuracy: 0.8254 - val_precision: 0.7523 - val_recall: 0.9703 - val_auc: 0.9203\n",
            "Epoch 522/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1908 - accuracy: 0.9231 - precision: 0.9167 - recall: 0.9309 - auc: 0.9774 - val_loss: 0.4882 - val_accuracy: 0.8179 - val_precision: 0.7404 - val_recall: 0.9788 - val_auc: 0.9226\n",
            "Epoch 523/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1929 - accuracy: 0.9222 - precision: 0.9137 - recall: 0.9324 - auc: 0.9768 - val_loss: 0.5336 - val_accuracy: 0.8018 - val_precision: 0.7216 - val_recall: 0.9826 - val_auc: 0.9179\n",
            "Epoch 524/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1921 - accuracy: 0.9226 - precision: 0.9150 - recall: 0.9319 - auc: 0.9770 - val_loss: 0.5007 - val_accuracy: 0.8158 - val_precision: 0.7386 - val_recall: 0.9775 - val_auc: 0.9209\n",
            "Epoch 525/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1881 - accuracy: 0.9249 - precision: 0.9168 - recall: 0.9347 - auc: 0.9780 - val_loss: 0.5339 - val_accuracy: 0.8028 - val_precision: 0.7225 - val_recall: 0.9829 - val_auc: 0.9219\n",
            "Epoch 526/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1904 - accuracy: 0.9235 - precision: 0.9171 - recall: 0.9312 - auc: 0.9774 - val_loss: 0.4847 - val_accuracy: 0.8217 - val_precision: 0.7458 - val_recall: 0.9760 - val_auc: 0.9238\n",
            "Epoch 527/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1925 - accuracy: 0.9223 - precision: 0.9151 - recall: 0.9309 - auc: 0.9769 - val_loss: 0.4770 - val_accuracy: 0.8190 - val_precision: 0.7423 - val_recall: 0.9772 - val_auc: 0.9227\n",
            "Epoch 528/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1933 - accuracy: 0.9222 - precision: 0.9143 - recall: 0.9318 - auc: 0.9768 - val_loss: 0.5147 - val_accuracy: 0.8046 - val_precision: 0.7246 - val_recall: 0.9825 - val_auc: 0.9266\n",
            "Epoch 529/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1931 - accuracy: 0.9227 - precision: 0.9147 - recall: 0.9323 - auc: 0.9768 - val_loss: 0.4927 - val_accuracy: 0.8219 - val_precision: 0.7458 - val_recall: 0.9764 - val_auc: 0.9233\n",
            "Epoch 530/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1917 - accuracy: 0.9231 - precision: 0.9156 - recall: 0.9320 - auc: 0.9771 - val_loss: 0.4809 - val_accuracy: 0.8274 - val_precision: 0.7532 - val_recall: 0.9737 - val_auc: 0.9245\n",
            "Epoch 531/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1881 - accuracy: 0.9245 - precision: 0.9180 - recall: 0.9323 - auc: 0.9780 - val_loss: 0.5170 - val_accuracy: 0.8120 - val_precision: 0.7332 - val_recall: 0.9807 - val_auc: 0.9206\n",
            "Epoch 532/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1955 - accuracy: 0.9210 - precision: 0.9129 - recall: 0.9307 - auc: 0.9763 - val_loss: 0.4722 - val_accuracy: 0.8252 - val_precision: 0.7501 - val_recall: 0.9751 - val_auc: 0.9275\n",
            "Epoch 533/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1896 - accuracy: 0.9238 - precision: 0.9163 - recall: 0.9328 - auc: 0.9776 - val_loss: 0.4861 - val_accuracy: 0.8195 - val_precision: 0.7428 - val_recall: 0.9774 - val_auc: 0.9264\n",
            "Epoch 534/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1929 - accuracy: 0.9224 - precision: 0.9142 - recall: 0.9324 - auc: 0.9769 - val_loss: 0.5073 - val_accuracy: 0.8112 - val_precision: 0.7324 - val_recall: 0.9807 - val_auc: 0.9219\n",
            "Epoch 535/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1912 - accuracy: 0.9227 - precision: 0.9149 - recall: 0.9322 - auc: 0.9773 - val_loss: 0.5016 - val_accuracy: 0.8088 - val_precision: 0.7297 - val_recall: 0.9807 - val_auc: 0.9216\n",
            "Epoch 536/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1885 - accuracy: 0.9243 - precision: 0.9170 - recall: 0.9332 - auc: 0.9778 - val_loss: 0.5057 - val_accuracy: 0.8092 - val_precision: 0.7299 - val_recall: 0.9814 - val_auc: 0.9221\n",
            "Epoch 537/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1875 - accuracy: 0.9250 - precision: 0.9172 - recall: 0.9345 - auc: 0.9781 - val_loss: 0.4766 - val_accuracy: 0.8232 - val_precision: 0.7488 - val_recall: 0.9725 - val_auc: 0.9193\n",
            "Epoch 538/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1915 - accuracy: 0.9226 - precision: 0.9154 - recall: 0.9312 - auc: 0.9772 - val_loss: 0.4774 - val_accuracy: 0.8171 - val_precision: 0.7396 - val_recall: 0.9785 - val_auc: 0.9243\n",
            "Epoch 539/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1931 - accuracy: 0.9218 - precision: 0.9123 - recall: 0.9335 - auc: 0.9768 - val_loss: 0.5017 - val_accuracy: 0.8110 - val_precision: 0.7331 - val_recall: 0.9779 - val_auc: 0.9166\n",
            "Epoch 540/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1900 - accuracy: 0.9235 - precision: 0.9162 - recall: 0.9323 - auc: 0.9775 - val_loss: 0.5209 - val_accuracy: 0.8059 - val_precision: 0.7260 - val_recall: 0.9825 - val_auc: 0.9197\n",
            "Epoch 541/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1918 - accuracy: 0.9229 - precision: 0.9152 - recall: 0.9322 - auc: 0.9771 - val_loss: 0.4953 - val_accuracy: 0.8091 - val_precision: 0.7299 - val_recall: 0.9811 - val_auc: 0.9263\n",
            "Epoch 542/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1902 - accuracy: 0.9232 - precision: 0.9149 - recall: 0.9331 - auc: 0.9774 - val_loss: 0.5014 - val_accuracy: 0.8173 - val_precision: 0.7397 - val_recall: 0.9790 - val_auc: 0.9239\n",
            "Epoch 543/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1909 - accuracy: 0.9236 - precision: 0.9159 - recall: 0.9328 - auc: 0.9773 - val_loss: 0.4928 - val_accuracy: 0.8136 - val_precision: 0.7350 - val_recall: 0.9809 - val_auc: 0.9264\n",
            "Epoch 544/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1900 - accuracy: 0.9238 - precision: 0.9179 - recall: 0.9307 - auc: 0.9775 - val_loss: 0.5091 - val_accuracy: 0.8102 - val_precision: 0.7320 - val_recall: 0.9784 - val_auc: 0.9193\n",
            "Epoch 545/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.2010 - accuracy: 0.9196 - precision: 0.9109 - recall: 0.9303 - auc: 0.9749 - val_loss: 0.4373 - val_accuracy: 0.8305 - val_precision: 0.7554 - val_recall: 0.9774 - val_auc: 0.9400\n",
            "Epoch 546/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1900 - accuracy: 0.9238 - precision: 0.9168 - recall: 0.9323 - auc: 0.9775 - val_loss: 0.4020 - val_accuracy: 0.8432 - val_precision: 0.7844 - val_recall: 0.9464 - val_auc: 0.9267\n",
            "Epoch 547/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1945 - accuracy: 0.9215 - precision: 0.9145 - recall: 0.9300 - auc: 0.9765 - val_loss: 0.4620 - val_accuracy: 0.8252 - val_precision: 0.7503 - val_recall: 0.9747 - val_auc: 0.9263\n",
            "Epoch 548/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1876 - accuracy: 0.9248 - precision: 0.9184 - recall: 0.9326 - auc: 0.9781 - val_loss: 0.5310 - val_accuracy: 0.8003 - val_precision: 0.7197 - val_recall: 0.9835 - val_auc: 0.9198\n",
            "Epoch 549/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1882 - accuracy: 0.9244 - precision: 0.9156 - recall: 0.9350 - auc: 0.9779 - val_loss: 0.5000 - val_accuracy: 0.8128 - val_precision: 0.7345 - val_recall: 0.9796 - val_auc: 0.9212\n",
            "Epoch 550/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1909 - accuracy: 0.9230 - precision: 0.9166 - recall: 0.9306 - auc: 0.9773 - val_loss: 0.4458 - val_accuracy: 0.8285 - val_precision: 0.7536 - val_recall: 0.9762 - val_auc: 0.9318\n",
            "Epoch 551/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1897 - accuracy: 0.9237 - precision: 0.9166 - recall: 0.9322 - auc: 0.9776 - val_loss: 0.4959 - val_accuracy: 0.8200 - val_precision: 0.7433 - val_recall: 0.9774 - val_auc: 0.9235\n",
            "Epoch 552/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1901 - accuracy: 0.9238 - precision: 0.9185 - recall: 0.9302 - auc: 0.9775 - val_loss: 0.5332 - val_accuracy: 0.8028 - val_precision: 0.7224 - val_recall: 0.9832 - val_auc: 0.9199\n",
            "Epoch 553/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1860 - accuracy: 0.9251 - precision: 0.9160 - recall: 0.9361 - auc: 0.9785 - val_loss: 0.5421 - val_accuracy: 0.8019 - val_precision: 0.7221 - val_recall: 0.9815 - val_auc: 0.9206\n",
            "Epoch 554/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1884 - accuracy: 0.9241 - precision: 0.9193 - recall: 0.9300 - auc: 0.9779 - val_loss: 0.5298 - val_accuracy: 0.8039 - val_precision: 0.7240 - val_recall: 0.9822 - val_auc: 0.9226\n",
            "Epoch 555/2000\n",
            "10/10 [==============================] - 4s 385ms/step - loss: 0.1938 - accuracy: 0.9217 - precision: 0.9139 - recall: 0.9310 - auc: 0.9766 - val_loss: 0.4343 - val_accuracy: 0.8352 - val_precision: 0.7633 - val_recall: 0.9715 - val_auc: 0.9341\n",
            "Epoch 556/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1882 - accuracy: 0.9246 - precision: 0.9187 - recall: 0.9317 - auc: 0.9780 - val_loss: 0.4282 - val_accuracy: 0.8378 - val_precision: 0.7673 - val_recall: 0.9694 - val_auc: 0.9311\n",
            "Epoch 557/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1869 - accuracy: 0.9249 - precision: 0.9187 - recall: 0.9323 - auc: 0.9783 - val_loss: 0.4495 - val_accuracy: 0.8319 - val_precision: 0.7591 - val_recall: 0.9723 - val_auc: 0.9271\n",
            "Epoch 558/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1889 - accuracy: 0.9243 - precision: 0.9154 - recall: 0.9350 - auc: 0.9778 - val_loss: 0.4893 - val_accuracy: 0.8147 - val_precision: 0.7369 - val_recall: 0.9787 - val_auc: 0.9244\n",
            "Epoch 559/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1863 - accuracy: 0.9250 - precision: 0.9162 - recall: 0.9356 - auc: 0.9784 - val_loss: 0.4697 - val_accuracy: 0.8260 - val_precision: 0.7508 - val_recall: 0.9757 - val_auc: 0.9283\n",
            "Epoch 560/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1863 - accuracy: 0.9251 - precision: 0.9167 - recall: 0.9353 - auc: 0.9783 - val_loss: 0.4495 - val_accuracy: 0.8343 - val_precision: 0.7668 - val_recall: 0.9608 - val_auc: 0.9198\n",
            "Epoch 561/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1907 - accuracy: 0.9233 - precision: 0.9175 - recall: 0.9303 - auc: 0.9774 - val_loss: 0.5412 - val_accuracy: 0.8021 - val_precision: 0.7214 - val_recall: 0.9840 - val_auc: 0.9215\n",
            "Epoch 562/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1922 - accuracy: 0.9224 - precision: 0.9141 - recall: 0.9324 - auc: 0.9771 - val_loss: 0.4625 - val_accuracy: 0.8275 - val_precision: 0.7557 - val_recall: 0.9677 - val_auc: 0.9246\n",
            "Epoch 563/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1862 - accuracy: 0.9250 - precision: 0.9183 - recall: 0.9331 - auc: 0.9784 - val_loss: 0.5098 - val_accuracy: 0.8138 - val_precision: 0.7353 - val_recall: 0.9803 - val_auc: 0.9245\n",
            "Epoch 564/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1884 - accuracy: 0.9246 - precision: 0.9175 - recall: 0.9331 - auc: 0.9779 - val_loss: 0.4786 - val_accuracy: 0.8260 - val_precision: 0.7505 - val_recall: 0.9763 - val_auc: 0.9278\n",
            "Epoch 565/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1873 - accuracy: 0.9251 - precision: 0.9192 - recall: 0.9320 - auc: 0.9782 - val_loss: 0.4855 - val_accuracy: 0.8230 - val_precision: 0.7480 - val_recall: 0.9739 - val_auc: 0.9228\n",
            "Epoch 566/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1877 - accuracy: 0.9242 - precision: 0.9165 - recall: 0.9335 - auc: 0.9781 - val_loss: 0.5355 - val_accuracy: 0.8117 - val_precision: 0.7330 - val_recall: 0.9805 - val_auc: 0.9186\n",
            "Epoch 567/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1875 - accuracy: 0.9250 - precision: 0.9175 - recall: 0.9340 - auc: 0.9781 - val_loss: 0.5387 - val_accuracy: 0.8100 - val_precision: 0.7313 - val_recall: 0.9801 - val_auc: 0.9179\n",
            "Epoch 568/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1888 - accuracy: 0.9239 - precision: 0.9164 - recall: 0.9330 - auc: 0.9778 - val_loss: 0.4865 - val_accuracy: 0.8255 - val_precision: 0.7502 - val_recall: 0.9759 - val_auc: 0.9236\n",
            "Epoch 569/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1846 - accuracy: 0.9263 - precision: 0.9190 - recall: 0.9350 - auc: 0.9787 - val_loss: 0.5392 - val_accuracy: 0.8029 - val_precision: 0.7232 - val_recall: 0.9814 - val_auc: 0.9179\n",
            "Epoch 570/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1862 - accuracy: 0.9254 - precision: 0.9187 - recall: 0.9335 - auc: 0.9784 - val_loss: 0.4959 - val_accuracy: 0.8046 - val_precision: 0.7789 - val_recall: 0.8506 - val_auc: 0.8834\n",
            "Epoch 571/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1889 - accuracy: 0.9242 - precision: 0.9176 - recall: 0.9321 - auc: 0.9778 - val_loss: 0.3934 - val_accuracy: 0.8513 - val_precision: 0.7918 - val_recall: 0.9532 - val_auc: 0.9299\n",
            "Epoch 572/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1876 - accuracy: 0.9246 - precision: 0.9168 - recall: 0.9339 - auc: 0.9781 - val_loss: 0.4760 - val_accuracy: 0.8223 - val_precision: 0.7459 - val_recall: 0.9776 - val_auc: 0.9251\n",
            "Epoch 573/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1872 - accuracy: 0.9245 - precision: 0.9175 - recall: 0.9329 - auc: 0.9782 - val_loss: 0.4744 - val_accuracy: 0.8297 - val_precision: 0.7566 - val_recall: 0.9720 - val_auc: 0.9240\n",
            "Epoch 574/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1876 - accuracy: 0.9249 - precision: 0.9184 - recall: 0.9328 - auc: 0.9781 - val_loss: 0.5077 - val_accuracy: 0.8181 - val_precision: 0.7417 - val_recall: 0.9759 - val_auc: 0.9203\n",
            "Epoch 575/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1872 - accuracy: 0.9251 - precision: 0.9194 - recall: 0.9319 - auc: 0.9782 - val_loss: 0.5176 - val_accuracy: 0.8107 - val_precision: 0.7315 - val_recall: 0.9814 - val_auc: 0.9244\n",
            "Epoch 576/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1873 - accuracy: 0.9252 - precision: 0.9182 - recall: 0.9336 - auc: 0.9781 - val_loss: 0.5112 - val_accuracy: 0.8145 - val_precision: 0.7368 - val_recall: 0.9785 - val_auc: 0.9228\n",
            "Epoch 577/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1857 - accuracy: 0.9261 - precision: 0.9209 - recall: 0.9323 - auc: 0.9785 - val_loss: 0.4883 - val_accuracy: 0.8203 - val_precision: 0.7439 - val_recall: 0.9769 - val_auc: 0.9238\n",
            "Epoch 578/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1891 - accuracy: 0.9244 - precision: 0.9185 - recall: 0.9314 - auc: 0.9777 - val_loss: 0.4705 - val_accuracy: 0.8239 - val_precision: 0.7473 - val_recall: 0.9784 - val_auc: 0.9300\n",
            "Epoch 579/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1857 - accuracy: 0.9251 - precision: 0.9167 - recall: 0.9352 - auc: 0.9785 - val_loss: 0.4731 - val_accuracy: 0.8254 - val_precision: 0.7502 - val_recall: 0.9756 - val_auc: 0.9270\n",
            "Epoch 580/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1879 - accuracy: 0.9244 - precision: 0.9171 - recall: 0.9332 - auc: 0.9780 - val_loss: 0.4735 - val_accuracy: 0.8268 - val_precision: 0.7522 - val_recall: 0.9745 - val_auc: 0.9255\n",
            "Epoch 581/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1902 - accuracy: 0.9240 - precision: 0.9179 - recall: 0.9313 - auc: 0.9775 - val_loss: 0.4784 - val_accuracy: 0.8246 - val_precision: 0.7506 - val_recall: 0.9723 - val_auc: 0.9198\n",
            "Epoch 582/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1883 - accuracy: 0.9242 - precision: 0.9175 - recall: 0.9322 - auc: 0.9779 - val_loss: 0.5008 - val_accuracy: 0.8184 - val_precision: 0.7426 - val_recall: 0.9743 - val_auc: 0.9175\n",
            "Epoch 583/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1865 - accuracy: 0.9252 - precision: 0.9187 - recall: 0.9330 - auc: 0.9784 - val_loss: 0.5076 - val_accuracy: 0.8156 - val_precision: 0.7376 - val_recall: 0.9794 - val_auc: 0.9236\n",
            "Epoch 584/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1919 - accuracy: 0.9228 - precision: 0.9165 - recall: 0.9304 - auc: 0.9772 - val_loss: 0.5103 - val_accuracy: 0.7785 - val_precision: 0.8203 - val_recall: 0.7129 - val_auc: 0.8722\n",
            "Epoch 585/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1932 - accuracy: 0.9218 - precision: 0.9154 - recall: 0.9297 - auc: 0.9769 - val_loss: 0.4361 - val_accuracy: 0.8349 - val_precision: 0.7711 - val_recall: 0.9525 - val_auc: 0.9190\n",
            "Epoch 586/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1886 - accuracy: 0.9246 - precision: 0.9170 - recall: 0.9338 - auc: 0.9778 - val_loss: 0.4701 - val_accuracy: 0.8276 - val_precision: 0.7542 - val_recall: 0.9721 - val_auc: 0.9241\n",
            "Epoch 587/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1903 - accuracy: 0.9237 - precision: 0.9173 - recall: 0.9314 - auc: 0.9775 - val_loss: 0.4593 - val_accuracy: 0.8235 - val_precision: 0.7474 - val_recall: 0.9770 - val_auc: 0.9273\n",
            "Epoch 588/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1890 - accuracy: 0.9241 - precision: 0.9159 - recall: 0.9340 - auc: 0.9778 - val_loss: 0.5199 - val_accuracy: 0.8117 - val_precision: 0.7329 - val_recall: 0.9806 - val_auc: 0.9233\n",
            "Epoch 589/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1881 - accuracy: 0.9247 - precision: 0.9163 - recall: 0.9348 - auc: 0.9779 - val_loss: 0.5179 - val_accuracy: 0.8122 - val_precision: 0.7330 - val_recall: 0.9819 - val_auc: 0.9233\n",
            "Epoch 590/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1864 - accuracy: 0.9253 - precision: 0.9175 - recall: 0.9348 - auc: 0.9784 - val_loss: 0.4845 - val_accuracy: 0.8253 - val_precision: 0.7499 - val_recall: 0.9759 - val_auc: 0.9232\n",
            "Epoch 591/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1885 - accuracy: 0.9245 - precision: 0.9172 - recall: 0.9334 - auc: 0.9779 - val_loss: 0.4992 - val_accuracy: 0.8186 - val_precision: 0.7416 - val_recall: 0.9777 - val_auc: 0.9230\n",
            "Epoch 592/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1908 - accuracy: 0.9228 - precision: 0.9165 - recall: 0.9304 - auc: 0.9774 - val_loss: 0.4768 - val_accuracy: 0.8184 - val_precision: 0.7422 - val_recall: 0.9756 - val_auc: 0.9229\n",
            "Epoch 593/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1855 - accuracy: 0.9256 - precision: 0.9181 - recall: 0.9347 - auc: 0.9786 - val_loss: 0.5049 - val_accuracy: 0.8165 - val_precision: 0.7385 - val_recall: 0.9796 - val_auc: 0.9215\n",
            "Epoch 594/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1895 - accuracy: 0.9234 - precision: 0.9164 - recall: 0.9318 - auc: 0.9777 - val_loss: 0.4742 - val_accuracy: 0.8320 - val_precision: 0.7595 - val_recall: 0.9716 - val_auc: 0.9214\n",
            "Epoch 595/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1884 - accuracy: 0.9242 - precision: 0.9178 - recall: 0.9317 - auc: 0.9779 - val_loss: 0.4928 - val_accuracy: 0.8170 - val_precision: 0.7389 - val_recall: 0.9800 - val_auc: 0.9255\n",
            "Epoch 596/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1879 - accuracy: 0.9249 - precision: 0.9163 - recall: 0.9353 - auc: 0.9780 - val_loss: 0.5006 - val_accuracy: 0.8198 - val_precision: 0.7440 - val_recall: 0.9751 - val_auc: 0.9215\n",
            "Epoch 597/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1882 - accuracy: 0.9250 - precision: 0.9183 - recall: 0.9330 - auc: 0.9780 - val_loss: 0.4544 - val_accuracy: 0.8346 - val_precision: 0.7640 - val_recall: 0.9683 - val_auc: 0.9271\n",
            "Epoch 598/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1876 - accuracy: 0.9245 - precision: 0.9177 - recall: 0.9325 - auc: 0.9781 - val_loss: 0.4509 - val_accuracy: 0.8258 - val_precision: 0.7650 - val_recall: 0.9402 - val_auc: 0.9122\n",
            "Epoch 599/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1903 - accuracy: 0.9234 - precision: 0.9149 - recall: 0.9336 - auc: 0.9775 - val_loss: 0.5095 - val_accuracy: 0.8101 - val_precision: 0.7307 - val_recall: 0.9820 - val_auc: 0.9299\n",
            "Epoch 600/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1895 - accuracy: 0.9236 - precision: 0.9167 - recall: 0.9320 - auc: 0.9776 - val_loss: 0.4837 - val_accuracy: 0.8237 - val_precision: 0.7486 - val_recall: 0.9747 - val_auc: 0.9241\n",
            "Epoch 601/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1922 - accuracy: 0.9222 - precision: 0.9150 - recall: 0.9309 - auc: 0.9771 - val_loss: 0.5104 - val_accuracy: 0.7797 - val_precision: 0.7969 - val_recall: 0.7506 - val_auc: 0.8675\n",
            "Epoch 602/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1916 - accuracy: 0.9233 - precision: 0.9146 - recall: 0.9338 - auc: 0.9771 - val_loss: 0.4910 - val_accuracy: 0.8237 - val_precision: 0.7498 - val_recall: 0.9713 - val_auc: 0.9178\n",
            "Epoch 603/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1886 - accuracy: 0.9245 - precision: 0.9176 - recall: 0.9327 - auc: 0.9779 - val_loss: 0.5327 - val_accuracy: 0.8115 - val_precision: 0.7325 - val_recall: 0.9812 - val_auc: 0.9214\n",
            "Epoch 604/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1886 - accuracy: 0.9239 - precision: 0.9170 - recall: 0.9321 - auc: 0.9779 - val_loss: 0.5362 - val_accuracy: 0.8115 - val_precision: 0.7331 - val_recall: 0.9796 - val_auc: 0.9170\n",
            "Epoch 605/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1861 - accuracy: 0.9253 - precision: 0.9185 - recall: 0.9335 - auc: 0.9785 - val_loss: 0.5561 - val_accuracy: 0.8086 - val_precision: 0.7298 - val_recall: 0.9800 - val_auc: 0.9158\n",
            "Epoch 606/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1869 - accuracy: 0.9246 - precision: 0.9171 - recall: 0.9336 - auc: 0.9783 - val_loss: 0.5197 - val_accuracy: 0.8147 - val_precision: 0.7368 - val_recall: 0.9791 - val_auc: 0.9200\n",
            "Epoch 607/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1890 - accuracy: 0.9240 - precision: 0.9186 - recall: 0.9305 - auc: 0.9778 - val_loss: 0.5358 - val_accuracy: 0.8046 - val_precision: 0.7243 - val_recall: 0.9834 - val_auc: 0.9242\n",
            "Epoch 608/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1875 - accuracy: 0.9250 - precision: 0.9169 - recall: 0.9348 - auc: 0.9781 - val_loss: 0.4799 - val_accuracy: 0.8240 - val_precision: 0.7494 - val_recall: 0.9733 - val_auc: 0.9232\n",
            "Epoch 609/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1874 - accuracy: 0.9246 - precision: 0.9187 - recall: 0.9316 - auc: 0.9781 - val_loss: 0.5109 - val_accuracy: 0.8150 - val_precision: 0.7364 - val_recall: 0.9811 - val_auc: 0.9257\n",
            "Epoch 610/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1920 - accuracy: 0.9228 - precision: 0.9156 - recall: 0.9315 - auc: 0.9771 - val_loss: 0.4813 - val_accuracy: 0.8194 - val_precision: 0.7478 - val_recall: 0.9635 - val_auc: 0.9143\n",
            "Epoch 611/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1880 - accuracy: 0.9247 - precision: 0.9182 - recall: 0.9326 - auc: 0.9780 - val_loss: 0.4787 - val_accuracy: 0.8222 - val_precision: 0.7457 - val_recall: 0.9777 - val_auc: 0.9244\n",
            "Epoch 612/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.1875 - accuracy: 0.9242 - precision: 0.9168 - recall: 0.9332 - auc: 0.9782 - val_loss: 0.5090 - val_accuracy: 0.8158 - val_precision: 0.7376 - val_recall: 0.9801 - val_auc: 0.9227\n",
            "Epoch 613/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1888 - accuracy: 0.9242 - precision: 0.9172 - recall: 0.9327 - auc: 0.9778 - val_loss: 0.4100 - val_accuracy: 0.8365 - val_precision: 0.7703 - val_recall: 0.9588 - val_auc: 0.9271\n",
            "Epoch 614/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1929 - accuracy: 0.9229 - precision: 0.9138 - recall: 0.9338 - auc: 0.9768 - val_loss: 0.4265 - val_accuracy: 0.8319 - val_precision: 0.7737 - val_recall: 0.9380 - val_auc: 0.9141\n",
            "Epoch 615/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1923 - accuracy: 0.9229 - precision: 0.9155 - recall: 0.9319 - auc: 0.9770 - val_loss: 0.4793 - val_accuracy: 0.8216 - val_precision: 0.7456 - val_recall: 0.9760 - val_auc: 0.9260\n",
            "Epoch 616/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1892 - accuracy: 0.9242 - precision: 0.9165 - recall: 0.9335 - auc: 0.9777 - val_loss: 0.5400 - val_accuracy: 0.7989 - val_precision: 0.7182 - val_recall: 0.9837 - val_auc: 0.9208\n",
            "Epoch 617/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1860 - accuracy: 0.9253 - precision: 0.9176 - recall: 0.9345 - auc: 0.9785 - val_loss: 0.5040 - val_accuracy: 0.8200 - val_precision: 0.7430 - val_recall: 0.9783 - val_auc: 0.9231\n",
            "Epoch 618/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1845 - accuracy: 0.9265 - precision: 0.9187 - recall: 0.9359 - auc: 0.9788 - val_loss: 0.5318 - val_accuracy: 0.8102 - val_precision: 0.7313 - val_recall: 0.9805 - val_auc: 0.9217\n",
            "Epoch 619/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1828 - accuracy: 0.9271 - precision: 0.9237 - recall: 0.9310 - auc: 0.9792 - val_loss: 0.5154 - val_accuracy: 0.8129 - val_precision: 0.7343 - val_recall: 0.9806 - val_auc: 0.9225\n",
            "Epoch 620/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1874 - accuracy: 0.9253 - precision: 0.9181 - recall: 0.9339 - auc: 0.9781 - val_loss: 0.5564 - val_accuracy: 0.7971 - val_precision: 0.7162 - val_recall: 0.9838 - val_auc: 0.9171\n",
            "Epoch 621/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1844 - accuracy: 0.9261 - precision: 0.9193 - recall: 0.9343 - auc: 0.9788 - val_loss: 0.5191 - val_accuracy: 0.8078 - val_precision: 0.7290 - val_recall: 0.9795 - val_auc: 0.9174\n",
            "Epoch 622/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1839 - accuracy: 0.9265 - precision: 0.9196 - recall: 0.9349 - auc: 0.9789 - val_loss: 0.5100 - val_accuracy: 0.8085 - val_precision: 0.7296 - val_recall: 0.9802 - val_auc: 0.9221\n",
            "Epoch 623/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1861 - accuracy: 0.9254 - precision: 0.9185 - recall: 0.9337 - auc: 0.9784 - val_loss: 0.5182 - val_accuracy: 0.8060 - val_precision: 0.7260 - val_recall: 0.9828 - val_auc: 0.9244\n",
            "Epoch 624/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1848 - accuracy: 0.9256 - precision: 0.9194 - recall: 0.9331 - auc: 0.9788 - val_loss: 0.4925 - val_accuracy: 0.8133 - val_precision: 0.7346 - val_recall: 0.9809 - val_auc: 0.9267\n",
            "Epoch 625/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1866 - accuracy: 0.9257 - precision: 0.9190 - recall: 0.9337 - auc: 0.9783 - val_loss: 0.4215 - val_accuracy: 0.8348 - val_precision: 0.7670 - val_recall: 0.9618 - val_auc: 0.9252\n",
            "Epoch 626/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1839 - accuracy: 0.9266 - precision: 0.9199 - recall: 0.9345 - auc: 0.9790 - val_loss: 0.4402 - val_accuracy: 0.8271 - val_precision: 0.7673 - val_recall: 0.9389 - val_auc: 0.9103\n",
            "Epoch 627/2000\n",
            "10/10 [==============================] - 5s 480ms/step - loss: 0.1857 - accuracy: 0.9256 - precision: 0.9177 - recall: 0.9350 - auc: 0.9785 - val_loss: 0.4335 - val_accuracy: 0.8350 - val_precision: 0.7681 - val_recall: 0.9596 - val_auc: 0.9210\n",
            "Epoch 628/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1877 - accuracy: 0.9244 - precision: 0.9167 - recall: 0.9336 - auc: 0.9781 - val_loss: 0.5651 - val_accuracy: 0.7934 - val_precision: 0.7120 - val_recall: 0.9854 - val_auc: 0.9196\n",
            "Epoch 629/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1857 - accuracy: 0.9261 - precision: 0.9194 - recall: 0.9341 - auc: 0.9784 - val_loss: 0.5129 - val_accuracy: 0.8095 - val_precision: 0.7303 - val_recall: 0.9812 - val_auc: 0.9252\n",
            "Epoch 630/2000\n",
            "10/10 [==============================] - 5s 476ms/step - loss: 0.1818 - accuracy: 0.9276 - precision: 0.9230 - recall: 0.9330 - auc: 0.9794 - val_loss: 0.5430 - val_accuracy: 0.7995 - val_precision: 0.7188 - val_recall: 0.9838 - val_auc: 0.9230\n",
            "Epoch 631/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1868 - accuracy: 0.9250 - precision: 0.9186 - recall: 0.9327 - auc: 0.9783 - val_loss: 0.5020 - val_accuracy: 0.8182 - val_precision: 0.7406 - val_recall: 0.9793 - val_auc: 0.9255\n",
            "Epoch 632/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1808 - accuracy: 0.9276 - precision: 0.9209 - recall: 0.9356 - auc: 0.9796 - val_loss: 0.5182 - val_accuracy: 0.8131 - val_precision: 0.7348 - val_recall: 0.9798 - val_auc: 0.9212\n",
            "Epoch 633/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1844 - accuracy: 0.9265 - precision: 0.9196 - recall: 0.9347 - auc: 0.9788 - val_loss: 0.4334 - val_accuracy: 0.8317 - val_precision: 0.7639 - val_recall: 0.9600 - val_auc: 0.9220\n",
            "Epoch 634/2000\n",
            "10/10 [==============================] - 4s 420ms/step - loss: 0.1886 - accuracy: 0.9242 - precision: 0.9168 - recall: 0.9330 - auc: 0.9779 - val_loss: 0.4127 - val_accuracy: 0.8245 - val_precision: 0.7969 - val_recall: 0.8707 - val_auc: 0.9061\n",
            "Epoch 635/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1864 - accuracy: 0.9256 - precision: 0.9184 - recall: 0.9343 - auc: 0.9784 - val_loss: 0.4482 - val_accuracy: 0.8263 - val_precision: 0.7572 - val_recall: 0.9604 - val_auc: 0.9181\n",
            "Epoch 636/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1898 - accuracy: 0.9233 - precision: 0.9166 - recall: 0.9314 - auc: 0.9776 - val_loss: 0.4689 - val_accuracy: 0.8210 - val_precision: 0.7441 - val_recall: 0.9784 - val_auc: 0.9311\n",
            "Epoch 637/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1850 - accuracy: 0.9257 - precision: 0.9181 - recall: 0.9349 - auc: 0.9787 - val_loss: 0.4773 - val_accuracy: 0.8277 - val_precision: 0.7527 - val_recall: 0.9760 - val_auc: 0.9291\n",
            "Epoch 638/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1849 - accuracy: 0.9261 - precision: 0.9210 - recall: 0.9323 - auc: 0.9787 - val_loss: 0.5257 - val_accuracy: 0.8095 - val_precision: 0.7298 - val_recall: 0.9827 - val_auc: 0.9267\n",
            "Epoch 639/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.2065 - accuracy: 0.9170 - precision: 0.9080 - recall: 0.9280 - auc: 0.9736 - val_loss: 0.4411 - val_accuracy: 0.8247 - val_precision: 0.7470 - val_recall: 0.9818 - val_auc: 0.9458\n",
            "Epoch 640/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1923 - accuracy: 0.9226 - precision: 0.9154 - recall: 0.9313 - auc: 0.9770 - val_loss: 0.3861 - val_accuracy: 0.8426 - val_precision: 0.7717 - val_recall: 0.9730 - val_auc: 0.9453\n",
            "Epoch 641/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1875 - accuracy: 0.9250 - precision: 0.9188 - recall: 0.9326 - auc: 0.9781 - val_loss: 0.4677 - val_accuracy: 0.8228 - val_precision: 0.7464 - val_recall: 0.9777 - val_auc: 0.9337\n",
            "Epoch 642/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1867 - accuracy: 0.9250 - precision: 0.9181 - recall: 0.9334 - auc: 0.9783 - val_loss: 0.4504 - val_accuracy: 0.8295 - val_precision: 0.7570 - val_recall: 0.9706 - val_auc: 0.9266\n",
            "Epoch 643/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1845 - accuracy: 0.9263 - precision: 0.9186 - recall: 0.9356 - auc: 0.9788 - val_loss: 0.5167 - val_accuracy: 0.8096 - val_precision: 0.7301 - val_recall: 0.9822 - val_auc: 0.9236\n",
            "Epoch 644/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1850 - accuracy: 0.9257 - precision: 0.9179 - recall: 0.9351 - auc: 0.9787 - val_loss: 0.5148 - val_accuracy: 0.8118 - val_precision: 0.7330 - val_recall: 0.9809 - val_auc: 0.9265\n",
            "Epoch 645/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1840 - accuracy: 0.9260 - precision: 0.9183 - recall: 0.9354 - auc: 0.9789 - val_loss: 0.4906 - val_accuracy: 0.8210 - val_precision: 0.7454 - val_recall: 0.9749 - val_auc: 0.9200\n",
            "Epoch 646/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1847 - accuracy: 0.9261 - precision: 0.9203 - recall: 0.9331 - auc: 0.9788 - val_loss: 0.5223 - val_accuracy: 0.8087 - val_precision: 0.7300 - val_recall: 0.9798 - val_auc: 0.9171\n",
            "Epoch 647/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1825 - accuracy: 0.9272 - precision: 0.9213 - recall: 0.9342 - auc: 0.9793 - val_loss: 0.4900 - val_accuracy: 0.8172 - val_precision: 0.7408 - val_recall: 0.9757 - val_auc: 0.9201\n",
            "Epoch 648/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1844 - accuracy: 0.9263 - precision: 0.9179 - recall: 0.9364 - auc: 0.9788 - val_loss: 0.5029 - val_accuracy: 0.8144 - val_precision: 0.7362 - val_recall: 0.9795 - val_auc: 0.9219\n",
            "Epoch 649/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1857 - accuracy: 0.9255 - precision: 0.9186 - recall: 0.9337 - auc: 0.9786 - val_loss: 0.4871 - val_accuracy: 0.8165 - val_precision: 0.7386 - val_recall: 0.9795 - val_auc: 0.9294\n",
            "Epoch 650/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1868 - accuracy: 0.9249 - precision: 0.9177 - recall: 0.9335 - auc: 0.9783 - val_loss: 0.4860 - val_accuracy: 0.8136 - val_precision: 0.7346 - val_recall: 0.9817 - val_auc: 0.9293\n",
            "Epoch 651/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1846 - accuracy: 0.9259 - precision: 0.9184 - recall: 0.9348 - auc: 0.9787 - val_loss: 0.4767 - val_accuracy: 0.8226 - val_precision: 0.7461 - val_recall: 0.9777 - val_auc: 0.9278\n",
            "Epoch 652/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1855 - accuracy: 0.9256 - precision: 0.9205 - recall: 0.9317 - auc: 0.9786 - val_loss: 0.4978 - val_accuracy: 0.8063 - val_precision: 0.7266 - val_recall: 0.9820 - val_auc: 0.9262\n",
            "Epoch 653/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1876 - accuracy: 0.9249 - precision: 0.9178 - recall: 0.9333 - auc: 0.9780 - val_loss: 0.4832 - val_accuracy: 0.8146 - val_precision: 0.7359 - val_recall: 0.9813 - val_auc: 0.9281\n",
            "Epoch 654/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1850 - accuracy: 0.9256 - precision: 0.9185 - recall: 0.9342 - auc: 0.9787 - val_loss: 0.4565 - val_accuracy: 0.8263 - val_precision: 0.7519 - val_recall: 0.9739 - val_auc: 0.9267\n",
            "Epoch 655/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1877 - accuracy: 0.9248 - precision: 0.9170 - recall: 0.9342 - auc: 0.9780 - val_loss: 0.4515 - val_accuracy: 0.8302 - val_precision: 0.7554 - val_recall: 0.9763 - val_auc: 0.9327\n",
            "Epoch 656/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1853 - accuracy: 0.9255 - precision: 0.9192 - recall: 0.9330 - auc: 0.9786 - val_loss: 0.5022 - val_accuracy: 0.8144 - val_precision: 0.7358 - val_recall: 0.9808 - val_auc: 0.9270\n",
            "Epoch 657/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1849 - accuracy: 0.9257 - precision: 0.9187 - recall: 0.9341 - auc: 0.9787 - val_loss: 0.4866 - val_accuracy: 0.8224 - val_precision: 0.7460 - val_recall: 0.9775 - val_auc: 0.9253\n",
            "Epoch 658/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1844 - accuracy: 0.9257 - precision: 0.9182 - recall: 0.9347 - auc: 0.9788 - val_loss: 0.5194 - val_accuracy: 0.8090 - val_precision: 0.7298 - val_recall: 0.9812 - val_auc: 0.9214\n",
            "Epoch 659/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1851 - accuracy: 0.9258 - precision: 0.9186 - recall: 0.9345 - auc: 0.9787 - val_loss: 0.5043 - val_accuracy: 0.8146 - val_precision: 0.7357 - val_recall: 0.9818 - val_auc: 0.9281\n",
            "Epoch 660/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1828 - accuracy: 0.9263 - precision: 0.9202 - recall: 0.9336 - auc: 0.9792 - val_loss: 0.4796 - val_accuracy: 0.8278 - val_precision: 0.7543 - val_recall: 0.9719 - val_auc: 0.9219\n",
            "Epoch 661/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1828 - accuracy: 0.9273 - precision: 0.9224 - recall: 0.9332 - auc: 0.9792 - val_loss: 0.4694 - val_accuracy: 0.8303 - val_precision: 0.7565 - val_recall: 0.9740 - val_auc: 0.9263\n",
            "Epoch 662/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1854 - accuracy: 0.9253 - precision: 0.9178 - recall: 0.9344 - auc: 0.9786 - val_loss: 0.5030 - val_accuracy: 0.8221 - val_precision: 0.7450 - val_recall: 0.9793 - val_auc: 0.9282\n",
            "Epoch 663/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.1858 - accuracy: 0.9259 - precision: 0.9179 - recall: 0.9356 - auc: 0.9785 - val_loss: 0.4967 - val_accuracy: 0.8136 - val_precision: 0.7349 - val_recall: 0.9810 - val_auc: 0.9319\n",
            "Epoch 664/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1850 - accuracy: 0.9257 - precision: 0.9195 - recall: 0.9330 - auc: 0.9787 - val_loss: 0.5016 - val_accuracy: 0.8128 - val_precision: 0.7333 - val_recall: 0.9828 - val_auc: 0.9318\n",
            "Epoch 665/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1820 - accuracy: 0.9273 - precision: 0.9196 - recall: 0.9364 - auc: 0.9794 - val_loss: 0.5134 - val_accuracy: 0.8087 - val_precision: 0.7290 - val_recall: 0.9825 - val_auc: 0.9275\n",
            "Epoch 666/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1860 - accuracy: 0.9254 - precision: 0.9171 - recall: 0.9354 - auc: 0.9784 - val_loss: 0.4990 - val_accuracy: 0.8170 - val_precision: 0.7392 - val_recall: 0.9793 - val_auc: 0.9245\n",
            "Epoch 667/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1830 - accuracy: 0.9267 - precision: 0.9199 - recall: 0.9349 - auc: 0.9791 - val_loss: 0.5189 - val_accuracy: 0.8127 - val_precision: 0.7343 - val_recall: 0.9797 - val_auc: 0.9222\n",
            "Epoch 668/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1831 - accuracy: 0.9272 - precision: 0.9204 - recall: 0.9352 - auc: 0.9791 - val_loss: 0.5379 - val_accuracy: 0.8084 - val_precision: 0.7289 - val_recall: 0.9817 - val_auc: 0.9210\n",
            "Epoch 669/2000\n",
            "10/10 [==============================] - 4s 420ms/step - loss: 0.1819 - accuracy: 0.9272 - precision: 0.9192 - recall: 0.9368 - auc: 0.9794 - val_loss: 0.4831 - val_accuracy: 0.8269 - val_precision: 0.7520 - val_recall: 0.9751 - val_auc: 0.9254\n",
            "Epoch 670/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1860 - accuracy: 0.9257 - precision: 0.9188 - recall: 0.9340 - auc: 0.9784 - val_loss: 0.4673 - val_accuracy: 0.8310 - val_precision: 0.7588 - val_recall: 0.9705 - val_auc: 0.9254\n",
            "Epoch 671/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1836 - accuracy: 0.9268 - precision: 0.9201 - recall: 0.9348 - auc: 0.9790 - val_loss: 0.4469 - val_accuracy: 0.8386 - val_precision: 0.7684 - val_recall: 0.9692 - val_auc: 0.9303\n",
            "Epoch 672/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1834 - accuracy: 0.9263 - precision: 0.9207 - recall: 0.9331 - auc: 0.9791 - val_loss: 0.4954 - val_accuracy: 0.8167 - val_precision: 0.7385 - val_recall: 0.9805 - val_auc: 0.9285\n",
            "Epoch 673/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1846 - accuracy: 0.9261 - precision: 0.9194 - recall: 0.9341 - auc: 0.9788 - val_loss: 0.4781 - val_accuracy: 0.8229 - val_precision: 0.7463 - val_recall: 0.9781 - val_auc: 0.9317\n",
            "Epoch 674/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1845 - accuracy: 0.9261 - precision: 0.9174 - recall: 0.9364 - auc: 0.9788 - val_loss: 0.5026 - val_accuracy: 0.8069 - val_precision: 0.7281 - val_recall: 0.9796 - val_auc: 0.9231\n",
            "Epoch 675/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1895 - accuracy: 0.9233 - precision: 0.9177 - recall: 0.9301 - auc: 0.9777 - val_loss: 0.4560 - val_accuracy: 0.8272 - val_precision: 0.7529 - val_recall: 0.9737 - val_auc: 0.9298\n",
            "Epoch 676/2000\n",
            "10/10 [==============================] - 5s 487ms/step - loss: 0.1829 - accuracy: 0.9269 - precision: 0.9207 - recall: 0.9343 - auc: 0.9792 - val_loss: 0.4789 - val_accuracy: 0.8198 - val_precision: 0.7430 - val_recall: 0.9777 - val_auc: 0.9268\n",
            "Epoch 677/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1840 - accuracy: 0.9265 - precision: 0.9177 - recall: 0.9372 - auc: 0.9789 - val_loss: 0.5157 - val_accuracy: 0.8123 - val_precision: 0.7335 - val_recall: 0.9808 - val_auc: 0.9227\n",
            "Epoch 678/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1828 - accuracy: 0.9270 - precision: 0.9212 - recall: 0.9338 - auc: 0.9792 - val_loss: 0.5050 - val_accuracy: 0.8145 - val_precision: 0.7362 - val_recall: 0.9802 - val_auc: 0.9252\n",
            "Epoch 679/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1824 - accuracy: 0.9266 - precision: 0.9177 - recall: 0.9373 - auc: 0.9793 - val_loss: 0.4919 - val_accuracy: 0.8222 - val_precision: 0.7457 - val_recall: 0.9776 - val_auc: 0.9263\n",
            "Epoch 680/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1855 - accuracy: 0.9260 - precision: 0.9200 - recall: 0.9331 - auc: 0.9786 - val_loss: 0.4654 - val_accuracy: 0.8322 - val_precision: 0.7586 - val_recall: 0.9743 - val_auc: 0.9287\n",
            "Epoch 681/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1815 - accuracy: 0.9270 - precision: 0.9200 - recall: 0.9354 - auc: 0.9795 - val_loss: 0.4794 - val_accuracy: 0.8300 - val_precision: 0.7554 - val_recall: 0.9758 - val_auc: 0.9285\n",
            "Epoch 682/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1809 - accuracy: 0.9276 - precision: 0.9208 - recall: 0.9358 - auc: 0.9796 - val_loss: 0.4700 - val_accuracy: 0.8344 - val_precision: 0.7616 - val_recall: 0.9735 - val_auc: 0.9282\n",
            "Epoch 683/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1835 - accuracy: 0.9264 - precision: 0.9184 - recall: 0.9361 - auc: 0.9790 - val_loss: 0.4792 - val_accuracy: 0.8307 - val_precision: 0.7580 - val_recall: 0.9713 - val_auc: 0.9218\n",
            "Epoch 684/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1913 - accuracy: 0.9236 - precision: 0.9156 - recall: 0.9332 - auc: 0.9773 - val_loss: 0.4309 - val_accuracy: 0.8377 - val_precision: 0.7658 - val_recall: 0.9729 - val_auc: 0.9361\n",
            "Epoch 685/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1868 - accuracy: 0.9248 - precision: 0.9182 - recall: 0.9328 - auc: 0.9783 - val_loss: 0.3944 - val_accuracy: 0.8441 - val_precision: 0.7754 - val_recall: 0.9688 - val_auc: 0.9406\n",
            "Epoch 686/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1828 - accuracy: 0.9274 - precision: 0.9219 - recall: 0.9341 - auc: 0.9791 - val_loss: 0.4518 - val_accuracy: 0.8282 - val_precision: 0.7530 - val_recall: 0.9767 - val_auc: 0.9345\n",
            "Epoch 687/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1855 - accuracy: 0.9256 - precision: 0.9192 - recall: 0.9333 - auc: 0.9785 - val_loss: 0.5143 - val_accuracy: 0.8096 - val_precision: 0.7306 - val_recall: 0.9806 - val_auc: 0.9275\n",
            "Epoch 688/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1829 - accuracy: 0.9270 - precision: 0.9222 - recall: 0.9327 - auc: 0.9791 - val_loss: 0.4938 - val_accuracy: 0.8180 - val_precision: 0.7402 - val_recall: 0.9799 - val_auc: 0.9286\n",
            "Epoch 689/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1831 - accuracy: 0.9262 - precision: 0.9181 - recall: 0.9358 - auc: 0.9792 - val_loss: 0.4117 - val_accuracy: 0.8427 - val_precision: 0.7978 - val_recall: 0.9178 - val_auc: 0.9153\n",
            "Epoch 690/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1877 - accuracy: 0.9252 - precision: 0.9202 - recall: 0.9310 - auc: 0.9780 - val_loss: 0.4451 - val_accuracy: 0.8348 - val_precision: 0.7629 - val_recall: 0.9713 - val_auc: 0.9271\n",
            "Epoch 691/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1866 - accuracy: 0.9252 - precision: 0.9185 - recall: 0.9332 - auc: 0.9784 - val_loss: 0.4450 - val_accuracy: 0.8312 - val_precision: 0.7579 - val_recall: 0.9733 - val_auc: 0.9304\n",
            "Epoch 692/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1834 - accuracy: 0.9268 - precision: 0.9209 - recall: 0.9338 - auc: 0.9790 - val_loss: 0.4046 - val_accuracy: 0.8455 - val_precision: 0.7798 - val_recall: 0.9627 - val_auc: 0.9308\n",
            "Epoch 693/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1869 - accuracy: 0.9250 - precision: 0.9184 - recall: 0.9330 - auc: 0.9783 - val_loss: 0.4426 - val_accuracy: 0.8391 - val_precision: 0.7692 - val_recall: 0.9686 - val_auc: 0.9280\n",
            "Epoch 694/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1846 - accuracy: 0.9265 - precision: 0.9204 - recall: 0.9337 - auc: 0.9788 - val_loss: 0.4692 - val_accuracy: 0.8283 - val_precision: 0.7532 - val_recall: 0.9765 - val_auc: 0.9303\n",
            "Epoch 695/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1844 - accuracy: 0.9266 - precision: 0.9204 - recall: 0.9339 - auc: 0.9788 - val_loss: 0.5088 - val_accuracy: 0.8143 - val_precision: 0.7358 - val_recall: 0.9807 - val_auc: 0.9261\n",
            "Epoch 696/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1816 - accuracy: 0.9271 - precision: 0.9203 - recall: 0.9352 - auc: 0.9794 - val_loss: 0.4553 - val_accuracy: 0.8345 - val_precision: 0.7642 - val_recall: 0.9672 - val_auc: 0.9233\n",
            "Epoch 697/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1846 - accuracy: 0.9262 - precision: 0.9210 - recall: 0.9324 - auc: 0.9788 - val_loss: 0.4600 - val_accuracy: 0.8292 - val_precision: 0.7579 - val_recall: 0.9675 - val_auc: 0.9194\n",
            "Epoch 698/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1849 - accuracy: 0.9255 - precision: 0.9185 - recall: 0.9338 - auc: 0.9787 - val_loss: 0.4839 - val_accuracy: 0.8198 - val_precision: 0.7428 - val_recall: 0.9783 - val_auc: 0.9252\n",
            "Epoch 699/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1819 - accuracy: 0.9273 - precision: 0.9194 - recall: 0.9367 - auc: 0.9794 - val_loss: 0.4656 - val_accuracy: 0.8271 - val_precision: 0.7518 - val_recall: 0.9762 - val_auc: 0.9300\n",
            "Epoch 700/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1841 - accuracy: 0.9267 - precision: 0.9216 - recall: 0.9327 - auc: 0.9789 - val_loss: 0.4839 - val_accuracy: 0.8206 - val_precision: 0.7428 - val_recall: 0.9807 - val_auc: 0.9324\n",
            "Epoch 701/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1813 - accuracy: 0.9277 - precision: 0.9204 - recall: 0.9363 - auc: 0.9795 - val_loss: 0.4669 - val_accuracy: 0.8304 - val_precision: 0.7570 - val_recall: 0.9732 - val_auc: 0.9280\n",
            "Epoch 702/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1818 - accuracy: 0.9274 - precision: 0.9202 - recall: 0.9360 - auc: 0.9794 - val_loss: 0.4989 - val_accuracy: 0.8207 - val_precision: 0.7437 - val_recall: 0.9786 - val_auc: 0.9260\n",
            "Epoch 703/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1859 - accuracy: 0.9260 - precision: 0.9197 - recall: 0.9336 - auc: 0.9785 - val_loss: 0.4246 - val_accuracy: 0.8421 - val_precision: 0.7766 - val_recall: 0.9602 - val_auc: 0.9285\n",
            "Epoch 704/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1844 - accuracy: 0.9263 - precision: 0.9191 - recall: 0.9349 - auc: 0.9788 - val_loss: 0.4730 - val_accuracy: 0.8290 - val_precision: 0.7556 - val_recall: 0.9725 - val_auc: 0.9270\n",
            "Epoch 705/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1807 - accuracy: 0.9280 - precision: 0.9232 - recall: 0.9336 - auc: 0.9796 - val_loss: 0.5196 - val_accuracy: 0.8094 - val_precision: 0.7300 - val_recall: 0.9817 - val_auc: 0.9240\n",
            "Epoch 706/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1831 - accuracy: 0.9273 - precision: 0.9203 - recall: 0.9357 - auc: 0.9791 - val_loss: 0.5231 - val_accuracy: 0.8072 - val_precision: 0.7272 - val_recall: 0.9830 - val_auc: 0.9248\n",
            "Epoch 707/2000\n",
            "10/10 [==============================] - 4s 417ms/step - loss: 0.1823 - accuracy: 0.9271 - precision: 0.9195 - recall: 0.9362 - auc: 0.9793 - val_loss: 0.4756 - val_accuracy: 0.8250 - val_precision: 0.7485 - val_recall: 0.9787 - val_auc: 0.9311\n",
            "Epoch 708/2000\n",
            "10/10 [==============================] - 5s 489ms/step - loss: 0.1818 - accuracy: 0.9270 - precision: 0.9221 - recall: 0.9327 - auc: 0.9794 - val_loss: 0.5063 - val_accuracy: 0.8160 - val_precision: 0.7381 - val_recall: 0.9793 - val_auc: 0.9235\n",
            "Epoch 709/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1932 - accuracy: 0.9231 - precision: 0.9167 - recall: 0.9308 - auc: 0.9768 - val_loss: 0.4106 - val_accuracy: 0.8380 - val_precision: 0.7638 - val_recall: 0.9784 - val_auc: 0.9471\n",
            "Epoch 710/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1900 - accuracy: 0.9240 - precision: 0.9178 - recall: 0.9314 - auc: 0.9776 - val_loss: 0.3803 - val_accuracy: 0.8514 - val_precision: 0.7829 - val_recall: 0.9722 - val_auc: 0.9501\n",
            "Epoch 711/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1829 - accuracy: 0.9266 - precision: 0.9193 - recall: 0.9354 - auc: 0.9792 - val_loss: 0.4086 - val_accuracy: 0.8436 - val_precision: 0.7732 - val_recall: 0.9724 - val_auc: 0.9434\n",
            "Epoch 712/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1832 - accuracy: 0.9268 - precision: 0.9227 - recall: 0.9316 - auc: 0.9791 - val_loss: 0.4852 - val_accuracy: 0.8182 - val_precision: 0.7402 - val_recall: 0.9803 - val_auc: 0.9328\n",
            "Epoch 713/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1816 - accuracy: 0.9279 - precision: 0.9197 - recall: 0.9378 - auc: 0.9794 - val_loss: 0.4716 - val_accuracy: 0.8279 - val_precision: 0.7528 - val_recall: 0.9762 - val_auc: 0.9320\n",
            "Epoch 714/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1834 - accuracy: 0.9272 - precision: 0.9215 - recall: 0.9340 - auc: 0.9790 - val_loss: 0.4766 - val_accuracy: 0.8291 - val_precision: 0.7541 - val_recall: 0.9766 - val_auc: 0.9338\n",
            "Epoch 715/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1810 - accuracy: 0.9279 - precision: 0.9228 - recall: 0.9339 - auc: 0.9795 - val_loss: 0.5344 - val_accuracy: 0.8069 - val_precision: 0.7276 - val_recall: 0.9810 - val_auc: 0.9251\n",
            "Epoch 716/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1826 - accuracy: 0.9271 - precision: 0.9206 - recall: 0.9348 - auc: 0.9792 - val_loss: 0.5243 - val_accuracy: 0.8182 - val_precision: 0.7407 - val_recall: 0.9791 - val_auc: 0.9241\n",
            "Epoch 717/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1782 - accuracy: 0.9285 - precision: 0.9228 - recall: 0.9353 - auc: 0.9802 - val_loss: 0.5395 - val_accuracy: 0.8112 - val_precision: 0.7318 - val_recall: 0.9823 - val_auc: 0.9254\n",
            "Epoch 718/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1779 - accuracy: 0.9287 - precision: 0.9231 - recall: 0.9353 - auc: 0.9803 - val_loss: 0.4921 - val_accuracy: 0.8277 - val_precision: 0.7550 - val_recall: 0.9702 - val_auc: 0.9202\n",
            "Epoch 719/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1798 - accuracy: 0.9276 - precision: 0.9216 - recall: 0.9347 - auc: 0.9799 - val_loss: 0.5153 - val_accuracy: 0.8205 - val_precision: 0.7435 - val_recall: 0.9784 - val_auc: 0.9243\n",
            "Epoch 720/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1804 - accuracy: 0.9280 - precision: 0.9204 - recall: 0.9370 - auc: 0.9797 - val_loss: 0.5383 - val_accuracy: 0.8088 - val_precision: 0.7291 - val_recall: 0.9825 - val_auc: 0.9250\n",
            "Epoch 721/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1763 - accuracy: 0.9295 - precision: 0.9245 - recall: 0.9355 - auc: 0.9806 - val_loss: 0.5460 - val_accuracy: 0.8001 - val_precision: 0.7192 - val_recall: 0.9843 - val_auc: 0.9264\n",
            "Epoch 722/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1806 - accuracy: 0.9277 - precision: 0.9219 - recall: 0.9345 - auc: 0.9796 - val_loss: 0.4947 - val_accuracy: 0.8243 - val_precision: 0.7487 - val_recall: 0.9762 - val_auc: 0.9265\n",
            "Epoch 723/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1843 - accuracy: 0.9261 - precision: 0.9193 - recall: 0.9342 - auc: 0.9788 - val_loss: 0.5314 - val_accuracy: 0.8051 - val_precision: 0.7249 - val_recall: 0.9834 - val_auc: 0.9295\n",
            "Epoch 724/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1850 - accuracy: 0.9262 - precision: 0.9216 - recall: 0.9317 - auc: 0.9787 - val_loss: 0.4466 - val_accuracy: 0.8345 - val_precision: 0.7627 - val_recall: 0.9711 - val_auc: 0.9315\n",
            "Epoch 725/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1784 - accuracy: 0.9289 - precision: 0.9218 - recall: 0.9374 - auc: 0.9801 - val_loss: 0.4772 - val_accuracy: 0.8257 - val_precision: 0.7503 - val_recall: 0.9759 - val_auc: 0.9282\n",
            "Epoch 726/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1793 - accuracy: 0.9285 - precision: 0.9214 - recall: 0.9369 - auc: 0.9800 - val_loss: 0.5246 - val_accuracy: 0.8124 - val_precision: 0.7332 - val_recall: 0.9820 - val_auc: 0.9272\n",
            "Epoch 727/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1789 - accuracy: 0.9283 - precision: 0.9205 - recall: 0.9375 - auc: 0.9800 - val_loss: 0.4784 - val_accuracy: 0.8302 - val_precision: 0.7566 - val_recall: 0.9736 - val_auc: 0.9267\n",
            "Epoch 728/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1772 - accuracy: 0.9297 - precision: 0.9232 - recall: 0.9375 - auc: 0.9805 - val_loss: 0.4767 - val_accuracy: 0.8316 - val_precision: 0.7578 - val_recall: 0.9745 - val_auc: 0.9288\n",
            "Epoch 729/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1804 - accuracy: 0.9278 - precision: 0.9206 - recall: 0.9365 - auc: 0.9798 - val_loss: 0.4885 - val_accuracy: 0.8260 - val_precision: 0.7509 - val_recall: 0.9753 - val_auc: 0.9265\n",
            "Epoch 730/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1809 - accuracy: 0.9279 - precision: 0.9197 - recall: 0.9376 - auc: 0.9796 - val_loss: 0.4809 - val_accuracy: 0.8314 - val_precision: 0.7578 - val_recall: 0.9738 - val_auc: 0.9255\n",
            "Epoch 731/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1787 - accuracy: 0.9291 - precision: 0.9220 - recall: 0.9375 - auc: 0.9800 - val_loss: 0.4534 - val_accuracy: 0.8367 - val_precision: 0.7660 - val_recall: 0.9695 - val_auc: 0.9257\n",
            "Epoch 732/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1798 - accuracy: 0.9283 - precision: 0.9220 - recall: 0.9358 - auc: 0.9798 - val_loss: 0.4686 - val_accuracy: 0.8300 - val_precision: 0.7557 - val_recall: 0.9750 - val_auc: 0.9272\n",
            "Epoch 733/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1819 - accuracy: 0.9273 - precision: 0.9193 - recall: 0.9369 - auc: 0.9793 - val_loss: 0.4786 - val_accuracy: 0.8286 - val_precision: 0.7540 - val_recall: 0.9753 - val_auc: 0.9276\n",
            "Epoch 734/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1812 - accuracy: 0.9277 - precision: 0.9208 - recall: 0.9359 - auc: 0.9796 - val_loss: 0.4953 - val_accuracy: 0.8181 - val_precision: 0.7401 - val_recall: 0.9801 - val_auc: 0.9294\n",
            "Epoch 735/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1797 - accuracy: 0.9282 - precision: 0.9203 - recall: 0.9377 - auc: 0.9798 - val_loss: 0.4895 - val_accuracy: 0.8242 - val_precision: 0.7477 - val_recall: 0.9785 - val_auc: 0.9306\n",
            "Epoch 736/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1782 - accuracy: 0.9292 - precision: 0.9249 - recall: 0.9343 - auc: 0.9802 - val_loss: 0.4961 - val_accuracy: 0.8186 - val_precision: 0.7409 - val_recall: 0.9796 - val_auc: 0.9262\n",
            "Epoch 737/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1782 - accuracy: 0.9285 - precision: 0.9218 - recall: 0.9364 - auc: 0.9802 - val_loss: 0.4900 - val_accuracy: 0.8210 - val_precision: 0.7454 - val_recall: 0.9748 - val_auc: 0.9213\n",
            "Epoch 738/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1784 - accuracy: 0.9288 - precision: 0.9236 - recall: 0.9349 - auc: 0.9802 - val_loss: 0.4634 - val_accuracy: 0.8312 - val_precision: 0.7572 - val_recall: 0.9749 - val_auc: 0.9286\n",
            "Epoch 739/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1823 - accuracy: 0.9274 - precision: 0.9207 - recall: 0.9355 - auc: 0.9793 - val_loss: 0.4667 - val_accuracy: 0.8255 - val_precision: 0.7490 - val_recall: 0.9787 - val_auc: 0.9333\n",
            "Epoch 740/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1781 - accuracy: 0.9293 - precision: 0.9230 - recall: 0.9368 - auc: 0.9802 - val_loss: 0.4265 - val_accuracy: 0.8352 - val_precision: 0.7616 - val_recall: 0.9757 - val_auc: 0.9382\n",
            "Epoch 741/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1756 - accuracy: 0.9298 - precision: 0.9237 - recall: 0.9371 - auc: 0.9808 - val_loss: 0.4749 - val_accuracy: 0.8221 - val_precision: 0.7451 - val_recall: 0.9790 - val_auc: 0.9314\n",
            "Epoch 742/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1785 - accuracy: 0.9287 - precision: 0.9233 - recall: 0.9350 - auc: 0.9801 - val_loss: 0.5043 - val_accuracy: 0.8133 - val_precision: 0.7344 - val_recall: 0.9812 - val_auc: 0.9279\n",
            "Epoch 743/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1798 - accuracy: 0.9283 - precision: 0.9194 - recall: 0.9388 - auc: 0.9798 - val_loss: 0.5434 - val_accuracy: 0.8060 - val_precision: 0.7260 - val_recall: 0.9827 - val_auc: 0.9252\n",
            "Epoch 744/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1814 - accuracy: 0.9276 - precision: 0.9225 - recall: 0.9336 - auc: 0.9795 - val_loss: 0.4436 - val_accuracy: 0.8367 - val_precision: 0.7636 - val_recall: 0.9751 - val_auc: 0.9376\n",
            "Epoch 745/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1803 - accuracy: 0.9282 - precision: 0.9213 - recall: 0.9365 - auc: 0.9797 - val_loss: 0.4487 - val_accuracy: 0.8345 - val_precision: 0.7623 - val_recall: 0.9719 - val_auc: 0.9320\n",
            "Epoch 746/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1814 - accuracy: 0.9276 - precision: 0.9208 - recall: 0.9358 - auc: 0.9795 - val_loss: 0.4814 - val_accuracy: 0.8266 - val_precision: 0.7506 - val_recall: 0.9778 - val_auc: 0.9326\n",
            "Epoch 747/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1759 - accuracy: 0.9303 - precision: 0.9249 - recall: 0.9367 - auc: 0.9807 - val_loss: 0.5000 - val_accuracy: 0.8217 - val_precision: 0.7445 - val_recall: 0.9793 - val_auc: 0.9302\n",
            "Epoch 748/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1769 - accuracy: 0.9303 - precision: 0.9234 - recall: 0.9384 - auc: 0.9804 - val_loss: 0.4493 - val_accuracy: 0.8361 - val_precision: 0.7642 - val_recall: 0.9721 - val_auc: 0.9316\n",
            "Epoch 749/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1808 - accuracy: 0.9279 - precision: 0.9215 - recall: 0.9356 - auc: 0.9796 - val_loss: 0.5223 - val_accuracy: 0.8078 - val_precision: 0.7276 - val_recall: 0.9837 - val_auc: 0.9317\n",
            "Epoch 750/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1784 - accuracy: 0.9292 - precision: 0.9236 - recall: 0.9358 - auc: 0.9801 - val_loss: 0.5239 - val_accuracy: 0.8065 - val_precision: 0.7261 - val_recall: 0.9842 - val_auc: 0.9315\n",
            "Epoch 751/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1802 - accuracy: 0.9278 - precision: 0.9207 - recall: 0.9362 - auc: 0.9797 - val_loss: 0.4798 - val_accuracy: 0.8178 - val_precision: 0.7412 - val_recall: 0.9763 - val_auc: 0.9255\n",
            "Epoch 752/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1780 - accuracy: 0.9289 - precision: 0.9228 - recall: 0.9361 - auc: 0.9803 - val_loss: 0.5370 - val_accuracy: 0.7955 - val_precision: 0.7138 - val_recall: 0.9860 - val_auc: 0.9284\n",
            "Epoch 753/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1789 - accuracy: 0.9286 - precision: 0.9197 - recall: 0.9393 - auc: 0.9800 - val_loss: 0.4493 - val_accuracy: 0.8334 - val_precision: 0.7602 - val_recall: 0.9737 - val_auc: 0.9335\n",
            "Epoch 754/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1767 - accuracy: 0.9297 - precision: 0.9232 - recall: 0.9375 - auc: 0.9805 - val_loss: 0.4777 - val_accuracy: 0.8176 - val_precision: 0.7388 - val_recall: 0.9823 - val_auc: 0.9338\n",
            "Epoch 755/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1782 - accuracy: 0.9291 - precision: 0.9229 - recall: 0.9364 - auc: 0.9802 - val_loss: 0.5051 - val_accuracy: 0.8134 - val_precision: 0.7347 - val_recall: 0.9810 - val_auc: 0.9292\n",
            "Epoch 756/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1766 - accuracy: 0.9299 - precision: 0.9235 - recall: 0.9374 - auc: 0.9805 - val_loss: 0.4563 - val_accuracy: 0.8239 - val_precision: 0.7477 - val_recall: 0.9775 - val_auc: 0.9328\n",
            "Epoch 757/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1763 - accuracy: 0.9300 - precision: 0.9243 - recall: 0.9367 - auc: 0.9806 - val_loss: 0.4449 - val_accuracy: 0.8348 - val_precision: 0.7628 - val_recall: 0.9716 - val_auc: 0.9322\n",
            "Epoch 758/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1776 - accuracy: 0.9296 - precision: 0.9240 - recall: 0.9362 - auc: 0.9803 - val_loss: 0.4772 - val_accuracy: 0.8322 - val_precision: 0.7597 - val_recall: 0.9717 - val_auc: 0.9255\n",
            "Epoch 759/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1783 - accuracy: 0.9289 - precision: 0.9256 - recall: 0.9328 - auc: 0.9802 - val_loss: 0.4744 - val_accuracy: 0.8255 - val_precision: 0.7526 - val_recall: 0.9697 - val_auc: 0.9221\n",
            "Epoch 760/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1789 - accuracy: 0.9283 - precision: 0.9205 - recall: 0.9377 - auc: 0.9801 - val_loss: 0.4654 - val_accuracy: 0.8327 - val_precision: 0.7601 - val_recall: 0.9721 - val_auc: 0.9294\n",
            "Epoch 761/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1776 - accuracy: 0.9295 - precision: 0.9227 - recall: 0.9376 - auc: 0.9803 - val_loss: 0.4295 - val_accuracy: 0.8406 - val_precision: 0.7715 - val_recall: 0.9677 - val_auc: 0.9310\n",
            "Epoch 762/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1791 - accuracy: 0.9283 - precision: 0.9233 - recall: 0.9342 - auc: 0.9801 - val_loss: 0.5150 - val_accuracy: 0.8127 - val_precision: 0.7337 - val_recall: 0.9814 - val_auc: 0.9282\n",
            "Epoch 763/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1758 - accuracy: 0.9307 - precision: 0.9237 - recall: 0.9390 - auc: 0.9807 - val_loss: 0.4248 - val_accuracy: 0.8478 - val_precision: 0.7841 - val_recall: 0.9598 - val_auc: 0.9277\n",
            "Epoch 764/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1828 - accuracy: 0.9268 - precision: 0.9201 - recall: 0.9347 - auc: 0.9792 - val_loss: 0.4328 - val_accuracy: 0.8414 - val_precision: 0.7719 - val_recall: 0.9690 - val_auc: 0.9346\n",
            "Epoch 765/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1755 - accuracy: 0.9303 - precision: 0.9235 - recall: 0.9384 - auc: 0.9808 - val_loss: 0.4359 - val_accuracy: 0.8386 - val_precision: 0.7661 - val_recall: 0.9748 - val_auc: 0.9386\n",
            "Epoch 766/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1773 - accuracy: 0.9295 - precision: 0.9249 - recall: 0.9350 - auc: 0.9804 - val_loss: 0.4455 - val_accuracy: 0.8341 - val_precision: 0.7615 - val_recall: 0.9728 - val_auc: 0.9317\n",
            "Epoch 767/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1775 - accuracy: 0.9290 - precision: 0.9215 - recall: 0.9379 - auc: 0.9804 - val_loss: 0.4369 - val_accuracy: 0.8397 - val_precision: 0.7687 - val_recall: 0.9717 - val_auc: 0.9346\n",
            "Epoch 768/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1769 - accuracy: 0.9296 - precision: 0.9248 - recall: 0.9353 - auc: 0.9805 - val_loss: 0.4774 - val_accuracy: 0.8238 - val_precision: 0.7467 - val_recall: 0.9798 - val_auc: 0.9351\n",
            "Epoch 769/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1742 - accuracy: 0.9312 - precision: 0.9257 - recall: 0.9376 - auc: 0.9810 - val_loss: 0.4667 - val_accuracy: 0.8286 - val_precision: 0.7537 - val_recall: 0.9760 - val_auc: 0.9312\n",
            "Epoch 770/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1743 - accuracy: 0.9306 - precision: 0.9268 - recall: 0.9350 - auc: 0.9811 - val_loss: 0.4327 - val_accuracy: 0.8397 - val_precision: 0.7712 - val_recall: 0.9657 - val_auc: 0.9291\n",
            "Epoch 771/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1747 - accuracy: 0.9305 - precision: 0.9247 - recall: 0.9373 - auc: 0.9809 - val_loss: 0.5247 - val_accuracy: 0.8131 - val_precision: 0.7337 - val_recall: 0.9829 - val_auc: 0.9299\n",
            "Epoch 772/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1758 - accuracy: 0.9298 - precision: 0.9242 - recall: 0.9364 - auc: 0.9807 - val_loss: 0.5376 - val_accuracy: 0.8108 - val_precision: 0.7314 - val_recall: 0.9821 - val_auc: 0.9273\n",
            "Epoch 773/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1820 - accuracy: 0.9270 - precision: 0.9227 - recall: 0.9321 - auc: 0.9794 - val_loss: 0.4855 - val_accuracy: 0.8275 - val_precision: 0.7521 - val_recall: 0.9770 - val_auc: 0.9300\n",
            "Epoch 774/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1747 - accuracy: 0.9307 - precision: 0.9257 - recall: 0.9365 - auc: 0.9810 - val_loss: 0.4810 - val_accuracy: 0.8269 - val_precision: 0.7516 - val_recall: 0.9762 - val_auc: 0.9306\n",
            "Epoch 775/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1725 - accuracy: 0.9315 - precision: 0.9268 - recall: 0.9370 - auc: 0.9814 - val_loss: 0.5220 - val_accuracy: 0.8101 - val_precision: 0.7308 - val_recall: 0.9815 - val_auc: 0.9266\n",
            "Epoch 776/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1887 - accuracy: 0.9253 - precision: 0.9202 - recall: 0.9313 - auc: 0.9778 - val_loss: 0.3686 - val_accuracy: 0.8520 - val_precision: 0.7868 - val_recall: 0.9657 - val_auc: 0.9440\n",
            "Epoch 777/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1814 - accuracy: 0.9278 - precision: 0.9209 - recall: 0.9361 - auc: 0.9794 - val_loss: 0.3874 - val_accuracy: 0.8461 - val_precision: 0.7773 - val_recall: 0.9698 - val_auc: 0.9450\n",
            "Epoch 778/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1764 - accuracy: 0.9297 - precision: 0.9245 - recall: 0.9359 - auc: 0.9806 - val_loss: 0.4216 - val_accuracy: 0.8365 - val_precision: 0.7632 - val_recall: 0.9756 - val_auc: 0.9415\n",
            "Epoch 779/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1756 - accuracy: 0.9300 - precision: 0.9230 - recall: 0.9384 - auc: 0.9808 - val_loss: 0.4545 - val_accuracy: 0.8342 - val_precision: 0.7603 - val_recall: 0.9759 - val_auc: 0.9371\n",
            "Epoch 780/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1733 - accuracy: 0.9314 - precision: 0.9248 - recall: 0.9392 - auc: 0.9812 - val_loss: 0.4844 - val_accuracy: 0.8216 - val_precision: 0.7438 - val_recall: 0.9810 - val_auc: 0.9350\n",
            "Epoch 781/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1753 - accuracy: 0.9304 - precision: 0.9257 - recall: 0.9360 - auc: 0.9808 - val_loss: 0.4773 - val_accuracy: 0.8265 - val_precision: 0.7512 - val_recall: 0.9760 - val_auc: 0.9309\n",
            "Epoch 782/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1758 - accuracy: 0.9297 - precision: 0.9231 - recall: 0.9375 - auc: 0.9807 - val_loss: 0.5130 - val_accuracy: 0.8166 - val_precision: 0.7380 - val_recall: 0.9815 - val_auc: 0.9311\n",
            "Epoch 783/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1771 - accuracy: 0.9294 - precision: 0.9246 - recall: 0.9351 - auc: 0.9804 - val_loss: 0.5420 - val_accuracy: 0.8082 - val_precision: 0.7279 - val_recall: 0.9840 - val_auc: 0.9298\n",
            "Epoch 784/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1749 - accuracy: 0.9307 - precision: 0.9259 - recall: 0.9365 - auc: 0.9809 - val_loss: 0.5425 - val_accuracy: 0.8065 - val_precision: 0.7261 - val_recall: 0.9841 - val_auc: 0.9262\n",
            "Epoch 785/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1739 - accuracy: 0.9309 - precision: 0.9254 - recall: 0.9375 - auc: 0.9811 - val_loss: 0.4818 - val_accuracy: 0.8253 - val_precision: 0.7477 - val_recall: 0.9820 - val_auc: 0.9372\n",
            "Epoch 786/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1708 - accuracy: 0.9317 - precision: 0.9287 - recall: 0.9354 - auc: 0.9817 - val_loss: 0.5307 - val_accuracy: 0.8083 - val_precision: 0.7282 - val_recall: 0.9835 - val_auc: 0.9282\n",
            "Epoch 787/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1808 - accuracy: 0.9279 - precision: 0.9212 - recall: 0.9358 - auc: 0.9796 - val_loss: 0.4553 - val_accuracy: 0.8357 - val_precision: 0.7631 - val_recall: 0.9736 - val_auc: 0.9326\n",
            "Epoch 788/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1751 - accuracy: 0.9302 - precision: 0.9238 - recall: 0.9378 - auc: 0.9809 - val_loss: 0.5302 - val_accuracy: 0.8120 - val_precision: 0.7324 - val_recall: 0.9830 - val_auc: 0.9285\n",
            "Epoch 789/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1777 - accuracy: 0.9297 - precision: 0.9243 - recall: 0.9361 - auc: 0.9803 - val_loss: 0.5098 - val_accuracy: 0.8116 - val_precision: 0.7318 - val_recall: 0.9834 - val_auc: 0.9340\n",
            "Epoch 790/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1749 - accuracy: 0.9306 - precision: 0.9246 - recall: 0.9378 - auc: 0.9809 - val_loss: 0.4277 - val_accuracy: 0.8375 - val_precision: 0.7651 - val_recall: 0.9738 - val_auc: 0.9359\n",
            "Epoch 791/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1779 - accuracy: 0.9296 - precision: 0.9229 - recall: 0.9376 - auc: 0.9803 - val_loss: 0.5251 - val_accuracy: 0.8084 - val_precision: 0.7287 - val_recall: 0.9826 - val_auc: 0.9249\n",
            "Epoch 792/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1740 - accuracy: 0.9308 - precision: 0.9246 - recall: 0.9382 - auc: 0.9811 - val_loss: 0.5153 - val_accuracy: 0.8124 - val_precision: 0.7329 - val_recall: 0.9830 - val_auc: 0.9275\n",
            "Epoch 793/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1727 - accuracy: 0.9310 - precision: 0.9264 - recall: 0.9364 - auc: 0.9814 - val_loss: 0.5001 - val_accuracy: 0.8169 - val_precision: 0.7382 - val_recall: 0.9821 - val_auc: 0.9287\n",
            "Epoch 794/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1762 - accuracy: 0.9302 - precision: 0.9237 - recall: 0.9379 - auc: 0.9806 - val_loss: 0.4862 - val_accuracy: 0.8137 - val_precision: 0.7340 - val_recall: 0.9838 - val_auc: 0.9359\n",
            "Epoch 795/2000\n",
            "10/10 [==============================] - 4s 385ms/step - loss: 0.1762 - accuracy: 0.9299 - precision: 0.9233 - recall: 0.9377 - auc: 0.9806 - val_loss: 0.4085 - val_accuracy: 0.8461 - val_precision: 0.7767 - val_recall: 0.9714 - val_auc: 0.9419\n",
            "Epoch 796/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1718 - accuracy: 0.9320 - precision: 0.9277 - recall: 0.9370 - auc: 0.9816 - val_loss: 0.4669 - val_accuracy: 0.8270 - val_precision: 0.7504 - val_recall: 0.9797 - val_auc: 0.9376\n",
            "Epoch 797/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1724 - accuracy: 0.9314 - precision: 0.9256 - recall: 0.9382 - auc: 0.9814 - val_loss: 0.4393 - val_accuracy: 0.8421 - val_precision: 0.7713 - val_recall: 0.9723 - val_auc: 0.9371\n",
            "Epoch 798/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1739 - accuracy: 0.9312 - precision: 0.9250 - recall: 0.9386 - auc: 0.9811 - val_loss: 0.4443 - val_accuracy: 0.8368 - val_precision: 0.7639 - val_recall: 0.9747 - val_auc: 0.9356\n",
            "Epoch 799/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1724 - accuracy: 0.9319 - precision: 0.9252 - recall: 0.9398 - auc: 0.9815 - val_loss: 0.5360 - val_accuracy: 0.8058 - val_precision: 0.7254 - val_recall: 0.9840 - val_auc: 0.9272\n",
            "Epoch 800/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1785 - accuracy: 0.9285 - precision: 0.9225 - recall: 0.9356 - auc: 0.9801 - val_loss: 0.4934 - val_accuracy: 0.8199 - val_precision: 0.7416 - val_recall: 0.9817 - val_auc: 0.9341\n",
            "Epoch 801/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1748 - accuracy: 0.9302 - precision: 0.9266 - recall: 0.9346 - auc: 0.9809 - val_loss: 0.5197 - val_accuracy: 0.8105 - val_precision: 0.7306 - val_recall: 0.9838 - val_auc: 0.9311\n",
            "Epoch 802/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1760 - accuracy: 0.9297 - precision: 0.9238 - recall: 0.9366 - auc: 0.9807 - val_loss: 0.4904 - val_accuracy: 0.8180 - val_precision: 0.7401 - val_recall: 0.9801 - val_auc: 0.9302\n",
            "Epoch 803/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1819 - accuracy: 0.9276 - precision: 0.9221 - recall: 0.9342 - auc: 0.9794 - val_loss: 0.3902 - val_accuracy: 0.8491 - val_precision: 0.7849 - val_recall: 0.9616 - val_auc: 0.9390\n",
            "Epoch 804/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1759 - accuracy: 0.9299 - precision: 0.9241 - recall: 0.9368 - auc: 0.9807 - val_loss: 0.4160 - val_accuracy: 0.8403 - val_precision: 0.7696 - val_recall: 0.9712 - val_auc: 0.9368\n",
            "Epoch 805/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1728 - accuracy: 0.9312 - precision: 0.9241 - recall: 0.9396 - auc: 0.9814 - val_loss: 0.4737 - val_accuracy: 0.8254 - val_precision: 0.7487 - val_recall: 0.9795 - val_auc: 0.9342\n",
            "Epoch 806/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1738 - accuracy: 0.9313 - precision: 0.9261 - recall: 0.9375 - auc: 0.9811 - val_loss: 0.4899 - val_accuracy: 0.8214 - val_precision: 0.7431 - val_recall: 0.9820 - val_auc: 0.9337\n",
            "Epoch 807/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1703 - accuracy: 0.9327 - precision: 0.9287 - recall: 0.9374 - auc: 0.9819 - val_loss: 0.4537 - val_accuracy: 0.8274 - val_precision: 0.7521 - val_recall: 0.9768 - val_auc: 0.9347\n",
            "Epoch 808/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1769 - accuracy: 0.9298 - precision: 0.9237 - recall: 0.9370 - auc: 0.9805 - val_loss: 0.5011 - val_accuracy: 0.8186 - val_precision: 0.7407 - val_recall: 0.9802 - val_auc: 0.9306\n",
            "Epoch 809/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1739 - accuracy: 0.9308 - precision: 0.9259 - recall: 0.9366 - auc: 0.9811 - val_loss: 0.4895 - val_accuracy: 0.8184 - val_precision: 0.7407 - val_recall: 0.9797 - val_auc: 0.9307\n",
            "Epoch 810/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1723 - accuracy: 0.9321 - precision: 0.9270 - recall: 0.9380 - auc: 0.9815 - val_loss: 0.5536 - val_accuracy: 0.7981 - val_precision: 0.7169 - val_recall: 0.9851 - val_auc: 0.9224\n",
            "Epoch 811/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1737 - accuracy: 0.9310 - precision: 0.9253 - recall: 0.9377 - auc: 0.9812 - val_loss: 0.4761 - val_accuracy: 0.8228 - val_precision: 0.7448 - val_recall: 0.9820 - val_auc: 0.9361\n",
            "Epoch 812/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1704 - accuracy: 0.9325 - precision: 0.9269 - recall: 0.9389 - auc: 0.9819 - val_loss: 0.5380 - val_accuracy: 0.7998 - val_precision: 0.7183 - val_recall: 0.9863 - val_auc: 0.9296\n",
            "Epoch 813/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1726 - accuracy: 0.9316 - precision: 0.9262 - recall: 0.9380 - auc: 0.9814 - val_loss: 0.5534 - val_accuracy: 0.7910 - val_precision: 0.7087 - val_recall: 0.9877 - val_auc: 0.9312\n",
            "Epoch 814/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1761 - accuracy: 0.9301 - precision: 0.9251 - recall: 0.9360 - auc: 0.9807 - val_loss: 0.3663 - val_accuracy: 0.8551 - val_precision: 0.8080 - val_recall: 0.9315 - val_auc: 0.9329\n",
            "Epoch 815/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1704 - accuracy: 0.9325 - precision: 0.9269 - recall: 0.9392 - auc: 0.9818 - val_loss: 0.4535 - val_accuracy: 0.8338 - val_precision: 0.7651 - val_recall: 0.9631 - val_auc: 0.9237\n",
            "Epoch 816/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1733 - accuracy: 0.9314 - precision: 0.9276 - recall: 0.9358 - auc: 0.9812 - val_loss: 0.5112 - val_accuracy: 0.8199 - val_precision: 0.7418 - val_recall: 0.9810 - val_auc: 0.9283\n",
            "Epoch 817/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1696 - accuracy: 0.9328 - precision: 0.9274 - recall: 0.9391 - auc: 0.9820 - val_loss: 0.5135 - val_accuracy: 0.8158 - val_precision: 0.7365 - val_recall: 0.9831 - val_auc: 0.9322\n",
            "Epoch 818/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1690 - accuracy: 0.9333 - precision: 0.9255 - recall: 0.9425 - auc: 0.9822 - val_loss: 0.3768 - val_accuracy: 0.8540 - val_precision: 0.8107 - val_recall: 0.9234 - val_auc: 0.9306\n",
            "Epoch 819/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1705 - accuracy: 0.9323 - precision: 0.9252 - recall: 0.9407 - auc: 0.9818 - val_loss: 0.5008 - val_accuracy: 0.8199 - val_precision: 0.7416 - val_recall: 0.9819 - val_auc: 0.9337\n",
            "Epoch 820/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1713 - accuracy: 0.9319 - precision: 0.9268 - recall: 0.9379 - auc: 0.9817 - val_loss: 0.5152 - val_accuracy: 0.8167 - val_precision: 0.7381 - val_recall: 0.9816 - val_auc: 0.9306\n",
            "Epoch 821/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1744 - accuracy: 0.9308 - precision: 0.9270 - recall: 0.9353 - auc: 0.9810 - val_loss: 0.4109 - val_accuracy: 0.8454 - val_precision: 0.7768 - val_recall: 0.9692 - val_auc: 0.9402\n",
            "Epoch 822/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1741 - accuracy: 0.9306 - precision: 0.9255 - recall: 0.9365 - auc: 0.9811 - val_loss: 0.4658 - val_accuracy: 0.8258 - val_precision: 0.7495 - val_recall: 0.9785 - val_auc: 0.9351\n",
            "Epoch 823/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1725 - accuracy: 0.9315 - precision: 0.9264 - recall: 0.9374 - auc: 0.9814 - val_loss: 0.4013 - val_accuracy: 0.8454 - val_precision: 0.7763 - val_recall: 0.9704 - val_auc: 0.9413\n",
            "Epoch 824/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1687 - accuracy: 0.9332 - precision: 0.9285 - recall: 0.9388 - auc: 0.9822 - val_loss: 0.3753 - val_accuracy: 0.8318 - val_precision: 0.8526 - val_recall: 0.8023 - val_auc: 0.9199\n",
            "Epoch 825/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1679 - accuracy: 0.9343 - precision: 0.9306 - recall: 0.9387 - auc: 0.9823 - val_loss: 0.3654 - val_accuracy: 0.8414 - val_precision: 0.8521 - val_recall: 0.8261 - val_auc: 0.9255\n",
            "Epoch 826/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1669 - accuracy: 0.9340 - precision: 0.9302 - recall: 0.9385 - auc: 0.9826 - val_loss: 0.4997 - val_accuracy: 0.8230 - val_precision: 0.7467 - val_recall: 0.9772 - val_auc: 0.9286\n",
            "Epoch 827/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1642 - accuracy: 0.9358 - precision: 0.9306 - recall: 0.9418 - auc: 0.9831 - val_loss: 0.5195 - val_accuracy: 0.8140 - val_precision: 0.7345 - val_recall: 0.9833 - val_auc: 0.9322\n",
            "Epoch 828/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1724 - accuracy: 0.9319 - precision: 0.9244 - recall: 0.9409 - auc: 0.9814 - val_loss: 0.5064 - val_accuracy: 0.8201 - val_precision: 0.7424 - val_recall: 0.9803 - val_auc: 0.9293\n",
            "Epoch 829/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1716 - accuracy: 0.9323 - precision: 0.9261 - recall: 0.9395 - auc: 0.9816 - val_loss: 0.3763 - val_accuracy: 0.8555 - val_precision: 0.7926 - val_recall: 0.9629 - val_auc: 0.9443\n",
            "Epoch 830/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1647 - accuracy: 0.9350 - precision: 0.9299 - recall: 0.9410 - auc: 0.9830 - val_loss: 0.4874 - val_accuracy: 0.8239 - val_precision: 0.7481 - val_recall: 0.9764 - val_auc: 0.9286\n",
            "Epoch 831/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1647 - accuracy: 0.9355 - precision: 0.9337 - recall: 0.9377 - auc: 0.9830 - val_loss: 0.3683 - val_accuracy: 0.8559 - val_precision: 0.8020 - val_recall: 0.9450 - val_auc: 0.9380\n",
            "Epoch 832/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1702 - accuracy: 0.9327 - precision: 0.9282 - recall: 0.9381 - auc: 0.9819 - val_loss: 0.3730 - val_accuracy: 0.8548 - val_precision: 0.8032 - val_recall: 0.9399 - val_auc: 0.9357\n",
            "Epoch 833/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1623 - accuracy: 0.9365 - precision: 0.9317 - recall: 0.9421 - auc: 0.9835 - val_loss: 0.4827 - val_accuracy: 0.8264 - val_precision: 0.7501 - val_recall: 0.9788 - val_auc: 0.9335\n",
            "Epoch 834/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1646 - accuracy: 0.9352 - precision: 0.9295 - recall: 0.9419 - auc: 0.9830 - val_loss: 0.7493 - val_accuracy: 0.6989 - val_precision: 0.8872 - val_recall: 0.4556 - val_auc: 0.8560\n",
            "Epoch 835/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1794 - accuracy: 0.9284 - precision: 0.9229 - recall: 0.9349 - auc: 0.9800 - val_loss: 0.7747 - val_accuracy: 0.6861 - val_precision: 0.8836 - val_recall: 0.4285 - val_auc: 0.8523\n",
            "Epoch 836/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1740 - accuracy: 0.9305 - precision: 0.9256 - recall: 0.9362 - auc: 0.9811 - val_loss: 0.4314 - val_accuracy: 0.8026 - val_precision: 0.8493 - val_recall: 0.7355 - val_auc: 0.9025\n",
            "Epoch 837/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1760 - accuracy: 0.9303 - precision: 0.9257 - recall: 0.9358 - auc: 0.9807 - val_loss: 0.4276 - val_accuracy: 0.8366 - val_precision: 0.7645 - val_recall: 0.9727 - val_auc: 0.9355\n",
            "Epoch 838/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1672 - accuracy: 0.9340 - precision: 0.9275 - recall: 0.9417 - auc: 0.9825 - val_loss: 0.4915 - val_accuracy: 0.8221 - val_precision: 0.7446 - val_recall: 0.9805 - val_auc: 0.9350\n",
            "Epoch 839/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1639 - accuracy: 0.9356 - precision: 0.9321 - recall: 0.9395 - auc: 0.9831 - val_loss: 0.5147 - val_accuracy: 0.8131 - val_precision: 0.7336 - val_recall: 0.9832 - val_auc: 0.9317\n",
            "Epoch 840/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1645 - accuracy: 0.9355 - precision: 0.9329 - recall: 0.9384 - auc: 0.9830 - val_loss: 0.5190 - val_accuracy: 0.8134 - val_precision: 0.7338 - val_recall: 0.9834 - val_auc: 0.9307\n",
            "Epoch 841/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1637 - accuracy: 0.9355 - precision: 0.9313 - recall: 0.9405 - auc: 0.9833 - val_loss: 0.5465 - val_accuracy: 0.8063 - val_precision: 0.7256 - val_recall: 0.9851 - val_auc: 0.9293\n",
            "Epoch 842/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1825 - accuracy: 0.9273 - precision: 0.9203 - recall: 0.9356 - auc: 0.9792 - val_loss: 0.3984 - val_accuracy: 0.8155 - val_precision: 0.8572 - val_recall: 0.7570 - val_auc: 0.9127\n",
            "Epoch 843/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1794 - accuracy: 0.9286 - precision: 0.9223 - recall: 0.9361 - auc: 0.9800 - val_loss: 0.3507 - val_accuracy: 0.8541 - val_precision: 0.8129 - val_recall: 0.9198 - val_auc: 0.9336\n",
            "Epoch 844/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1693 - accuracy: 0.9326 - precision: 0.9283 - recall: 0.9378 - auc: 0.9821 - val_loss: 0.4713 - val_accuracy: 0.8246 - val_precision: 0.7473 - val_recall: 0.9808 - val_auc: 0.9376\n",
            "Epoch 845/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1621 - accuracy: 0.9363 - precision: 0.9312 - recall: 0.9422 - auc: 0.9836 - val_loss: 0.4543 - val_accuracy: 0.8311 - val_precision: 0.7566 - val_recall: 0.9761 - val_auc: 0.9358\n",
            "Epoch 846/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1628 - accuracy: 0.9364 - precision: 0.9321 - recall: 0.9414 - auc: 0.9834 - val_loss: 0.5594 - val_accuracy: 0.7971 - val_precision: 0.7149 - val_recall: 0.9881 - val_auc: 0.9321\n",
            "Epoch 847/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1693 - accuracy: 0.9328 - precision: 0.9268 - recall: 0.9398 - auc: 0.9821 - val_loss: 0.4839 - val_accuracy: 0.8193 - val_precision: 0.7421 - val_recall: 0.9786 - val_auc: 0.9289\n",
            "Epoch 848/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1615 - accuracy: 0.9369 - precision: 0.9333 - recall: 0.9412 - auc: 0.9837 - val_loss: 0.5367 - val_accuracy: 0.8062 - val_precision: 0.7254 - val_recall: 0.9850 - val_auc: 0.9340\n",
            "Epoch 849/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1577 - accuracy: 0.9382 - precision: 0.9326 - recall: 0.9448 - auc: 0.9843 - val_loss: 0.5240 - val_accuracy: 0.8148 - val_precision: 0.7361 - val_recall: 0.9813 - val_auc: 0.9293\n",
            "Epoch 850/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1582 - accuracy: 0.9381 - precision: 0.9342 - recall: 0.9426 - auc: 0.9843 - val_loss: 0.5171 - val_accuracy: 0.8138 - val_precision: 0.7337 - val_recall: 0.9848 - val_auc: 0.9393\n",
            "Epoch 851/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1623 - accuracy: 0.9364 - precision: 0.9335 - recall: 0.9397 - auc: 0.9835 - val_loss: 0.5357 - val_accuracy: 0.8031 - val_precision: 0.7216 - val_recall: 0.9869 - val_auc: 0.9363\n",
            "Epoch 852/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1582 - accuracy: 0.9384 - precision: 0.9349 - recall: 0.9425 - auc: 0.9843 - val_loss: 0.5206 - val_accuracy: 0.8168 - val_precision: 0.7383 - val_recall: 0.9814 - val_auc: 0.9313\n",
            "Epoch 853/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1571 - accuracy: 0.9386 - precision: 0.9371 - recall: 0.9403 - auc: 0.9845 - val_loss: 0.5371 - val_accuracy: 0.8082 - val_precision: 0.7279 - val_recall: 0.9842 - val_auc: 0.9309\n",
            "Epoch 854/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1591 - accuracy: 0.9379 - precision: 0.9342 - recall: 0.9422 - auc: 0.9841 - val_loss: 0.5151 - val_accuracy: 0.8106 - val_precision: 0.7304 - val_recall: 0.9844 - val_auc: 0.9350\n",
            "Epoch 855/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1604 - accuracy: 0.9370 - precision: 0.9322 - recall: 0.9427 - auc: 0.9839 - val_loss: 0.5848 - val_accuracy: 0.7866 - val_precision: 0.7041 - val_recall: 0.9882 - val_auc: 0.9330\n",
            "Epoch 856/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1589 - accuracy: 0.9378 - precision: 0.9346 - recall: 0.9415 - auc: 0.9842 - val_loss: 0.5280 - val_accuracy: 0.8086 - val_precision: 0.7279 - val_recall: 0.9854 - val_auc: 0.9355\n",
            "Epoch 857/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1572 - accuracy: 0.9384 - precision: 0.9344 - recall: 0.9431 - auc: 0.9845 - val_loss: 0.6087 - val_accuracy: 0.7839 - val_precision: 0.7013 - val_recall: 0.9891 - val_auc: 0.9254\n",
            "Epoch 858/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1684 - accuracy: 0.9343 - precision: 0.9295 - recall: 0.9400 - auc: 0.9822 - val_loss: 0.5723 - val_accuracy: 0.8021 - val_precision: 0.7208 - val_recall: 0.9859 - val_auc: 0.9313\n",
            "Epoch 859/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1564 - accuracy: 0.9391 - precision: 0.9351 - recall: 0.9437 - auc: 0.9845 - val_loss: 0.5376 - val_accuracy: 0.8061 - val_precision: 0.7253 - val_recall: 0.9852 - val_auc: 0.9362\n",
            "Epoch 860/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1542 - accuracy: 0.9402 - precision: 0.9378 - recall: 0.9429 - auc: 0.9850 - val_loss: 0.5569 - val_accuracy: 0.7990 - val_precision: 0.7172 - val_recall: 0.9869 - val_auc: 0.9330\n",
            "Epoch 861/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1660 - accuracy: 0.9348 - precision: 0.9304 - recall: 0.9400 - auc: 0.9828 - val_loss: 0.8089 - val_accuracy: 0.6822 - val_precision: 0.8850 - val_recall: 0.4185 - val_auc: 0.8548\n",
            "Epoch 862/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1708 - accuracy: 0.9328 - precision: 0.9267 - recall: 0.9401 - auc: 0.9818 - val_loss: 0.3641 - val_accuracy: 0.8494 - val_precision: 0.8032 - val_recall: 0.9254 - val_auc: 0.9317\n",
            "Epoch 863/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1600 - accuracy: 0.9373 - precision: 0.9340 - recall: 0.9411 - auc: 0.9839 - val_loss: 0.5644 - val_accuracy: 0.7983 - val_precision: 0.7166 - val_recall: 0.9866 - val_auc: 0.9284\n",
            "Epoch 864/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1543 - accuracy: 0.9396 - precision: 0.9370 - recall: 0.9426 - auc: 0.9850 - val_loss: 0.5680 - val_accuracy: 0.7975 - val_precision: 0.7159 - val_recall: 0.9863 - val_auc: 0.9277\n",
            "Epoch 865/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1485 - accuracy: 0.9424 - precision: 0.9391 - recall: 0.9462 - auc: 0.9861 - val_loss: 0.5570 - val_accuracy: 0.8053 - val_precision: 0.7245 - val_recall: 0.9853 - val_auc: 0.9351\n",
            "Epoch 866/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1701 - accuracy: 0.9328 - precision: 0.9290 - recall: 0.9372 - auc: 0.9819 - val_loss: 0.3900 - val_accuracy: 0.8556 - val_precision: 0.7901 - val_recall: 0.9685 - val_auc: 0.9445\n",
            "Epoch 867/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1609 - accuracy: 0.9372 - precision: 0.9327 - recall: 0.9423 - auc: 0.9837 - val_loss: 0.5706 - val_accuracy: 0.7951 - val_precision: 0.7130 - val_recall: 0.9877 - val_auc: 0.9287\n",
            "Epoch 868/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1539 - accuracy: 0.9400 - precision: 0.9356 - recall: 0.9449 - auc: 0.9851 - val_loss: 0.5095 - val_accuracy: 0.8226 - val_precision: 0.7449 - val_recall: 0.9810 - val_auc: 0.9351\n",
            "Epoch 869/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1608 - accuracy: 0.9367 - precision: 0.9322 - recall: 0.9419 - auc: 0.9838 - val_loss: 0.8347 - val_accuracy: 0.6683 - val_precision: 0.8991 - val_recall: 0.3788 - val_auc: 0.8505\n",
            "Epoch 870/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1757 - accuracy: 0.9303 - precision: 0.9250 - recall: 0.9366 - auc: 0.9808 - val_loss: 0.8000 - val_accuracy: 0.6657 - val_precision: 0.8912 - val_recall: 0.3771 - val_auc: 0.8553\n",
            "Epoch 871/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.1739 - accuracy: 0.9306 - precision: 0.9242 - recall: 0.9381 - auc: 0.9811 - val_loss: 0.5558 - val_accuracy: 0.7371 - val_precision: 0.8899 - val_recall: 0.5410 - val_auc: 0.8936\n",
            "Epoch 872/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1732 - accuracy: 0.9318 - precision: 0.9259 - recall: 0.9386 - auc: 0.9812 - val_loss: 0.3888 - val_accuracy: 0.8183 - val_precision: 0.8598 - val_recall: 0.7603 - val_auc: 0.9161\n",
            "Epoch 873/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1742 - accuracy: 0.9304 - precision: 0.9262 - recall: 0.9353 - auc: 0.9811 - val_loss: 0.3368 - val_accuracy: 0.8557 - val_precision: 0.8380 - val_recall: 0.8819 - val_auc: 0.9329\n",
            "Epoch 874/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1739 - accuracy: 0.9307 - precision: 0.9264 - recall: 0.9357 - auc: 0.9811 - val_loss: 0.3702 - val_accuracy: 0.8554 - val_precision: 0.8051 - val_recall: 0.9377 - val_auc: 0.9346\n",
            "Epoch 875/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1698 - accuracy: 0.9329 - precision: 0.9278 - recall: 0.9389 - auc: 0.9820 - val_loss: 0.5110 - val_accuracy: 0.8125 - val_precision: 0.7337 - val_recall: 0.9809 - val_auc: 0.9280\n",
            "Epoch 876/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1740 - accuracy: 0.9310 - precision: 0.9259 - recall: 0.9370 - auc: 0.9811 - val_loss: 0.4681 - val_accuracy: 0.8295 - val_precision: 0.7531 - val_recall: 0.9802 - val_auc: 0.9380\n",
            "Epoch 877/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1701 - accuracy: 0.9323 - precision: 0.9266 - recall: 0.9390 - auc: 0.9820 - val_loss: 0.4660 - val_accuracy: 0.8283 - val_precision: 0.7525 - val_recall: 0.9783 - val_auc: 0.9389\n",
            "Epoch 878/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1530 - accuracy: 0.9405 - precision: 0.9376 - recall: 0.9439 - auc: 0.9853 - val_loss: 0.5331 - val_accuracy: 0.8059 - val_precision: 0.7246 - val_recall: 0.9867 - val_auc: 0.9396\n",
            "Epoch 879/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1484 - accuracy: 0.9427 - precision: 0.9393 - recall: 0.9465 - auc: 0.9861 - val_loss: 0.5281 - val_accuracy: 0.8102 - val_precision: 0.7301 - val_recall: 0.9841 - val_auc: 0.9359\n",
            "Epoch 880/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1763 - accuracy: 0.9300 - precision: 0.9236 - recall: 0.9376 - auc: 0.9806 - val_loss: 0.3660 - val_accuracy: 0.8349 - val_precision: 0.8556 - val_recall: 0.8056 - val_auc: 0.9229\n",
            "Epoch 881/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1759 - accuracy: 0.9302 - precision: 0.9268 - recall: 0.9342 - auc: 0.9807 - val_loss: 0.4235 - val_accuracy: 0.7960 - val_precision: 0.8842 - val_recall: 0.6811 - val_auc: 0.9138\n",
            "Epoch 882/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1741 - accuracy: 0.9305 - precision: 0.9245 - recall: 0.9375 - auc: 0.9811 - val_loss: 0.3452 - val_accuracy: 0.8470 - val_precision: 0.8470 - val_recall: 0.8469 - val_auc: 0.9287\n",
            "Epoch 883/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1756 - accuracy: 0.9299 - precision: 0.9239 - recall: 0.9371 - auc: 0.9808 - val_loss: 0.3183 - val_accuracy: 0.8649 - val_precision: 0.8537 - val_recall: 0.8807 - val_auc: 0.9388\n",
            "Epoch 884/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1746 - accuracy: 0.9304 - precision: 0.9254 - recall: 0.9364 - auc: 0.9810 - val_loss: 0.3329 - val_accuracy: 0.8652 - val_precision: 0.8222 - val_recall: 0.9318 - val_auc: 0.9412\n",
            "Epoch 885/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1727 - accuracy: 0.9311 - precision: 0.9249 - recall: 0.9385 - auc: 0.9814 - val_loss: 0.3840 - val_accuracy: 0.8490 - val_precision: 0.7849 - val_recall: 0.9614 - val_auc: 0.9392\n",
            "Epoch 886/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1743 - accuracy: 0.9305 - precision: 0.9234 - recall: 0.9388 - auc: 0.9810 - val_loss: 0.4342 - val_accuracy: 0.8352 - val_precision: 0.7635 - val_recall: 0.9713 - val_auc: 0.9386\n",
            "Epoch 887/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1711 - accuracy: 0.9321 - precision: 0.9261 - recall: 0.9393 - auc: 0.9817 - val_loss: 0.3696 - val_accuracy: 0.8587 - val_precision: 0.7964 - val_recall: 0.9636 - val_auc: 0.9447\n",
            "Epoch 888/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1750 - accuracy: 0.9301 - precision: 0.9252 - recall: 0.9359 - auc: 0.9809 - val_loss: 0.5574 - val_accuracy: 0.7947 - val_precision: 0.7132 - val_recall: 0.9855 - val_auc: 0.9315\n",
            "Epoch 889/2000\n",
            "10/10 [==============================] - 4s 417ms/step - loss: 0.1720 - accuracy: 0.9316 - precision: 0.9264 - recall: 0.9377 - auc: 0.9815 - val_loss: 0.4681 - val_accuracy: 0.8290 - val_precision: 0.7566 - val_recall: 0.9701 - val_auc: 0.9237\n",
            "Epoch 890/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1760 - accuracy: 0.9300 - precision: 0.9228 - recall: 0.9386 - auc: 0.9807 - val_loss: 0.4179 - val_accuracy: 0.8435 - val_precision: 0.7765 - val_recall: 0.9644 - val_auc: 0.9346\n",
            "Epoch 891/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1708 - accuracy: 0.9323 - precision: 0.9279 - recall: 0.9375 - auc: 0.9818 - val_loss: 0.4744 - val_accuracy: 0.8254 - val_precision: 0.7489 - val_recall: 0.9789 - val_auc: 0.9354\n",
            "Epoch 892/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1674 - accuracy: 0.9336 - precision: 0.9287 - recall: 0.9394 - auc: 0.9825 - val_loss: 0.5134 - val_accuracy: 0.8107 - val_precision: 0.7308 - val_recall: 0.9835 - val_auc: 0.9309\n",
            "Epoch 893/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1624 - accuracy: 0.9361 - precision: 0.9308 - recall: 0.9423 - auc: 0.9835 - val_loss: 0.4761 - val_accuracy: 0.8296 - val_precision: 0.7540 - val_recall: 0.9781 - val_auc: 0.9360\n",
            "Epoch 894/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1527 - accuracy: 0.9404 - precision: 0.9373 - recall: 0.9440 - auc: 0.9854 - val_loss: 0.5422 - val_accuracy: 0.8120 - val_precision: 0.7323 - val_recall: 0.9833 - val_auc: 0.9332\n",
            "Epoch 895/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1517 - accuracy: 0.9408 - precision: 0.9385 - recall: 0.9434 - auc: 0.9856 - val_loss: 0.5502 - val_accuracy: 0.8135 - val_precision: 0.7340 - val_recall: 0.9832 - val_auc: 0.9315\n",
            "Epoch 896/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1666 - accuracy: 0.9341 - precision: 0.9300 - recall: 0.9388 - auc: 0.9827 - val_loss: 0.5867 - val_accuracy: 0.8009 - val_precision: 0.7195 - val_recall: 0.9861 - val_auc: 0.9242\n",
            "Epoch 897/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1578 - accuracy: 0.9380 - precision: 0.9341 - recall: 0.9426 - auc: 0.9843 - val_loss: 0.4969 - val_accuracy: 0.8243 - val_precision: 0.7470 - val_recall: 0.9806 - val_auc: 0.9356\n",
            "Epoch 898/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1498 - accuracy: 0.9417 - precision: 0.9392 - recall: 0.9445 - auc: 0.9859 - val_loss: 0.5743 - val_accuracy: 0.8035 - val_precision: 0.7222 - val_recall: 0.9862 - val_auc: 0.9308\n",
            "Epoch 899/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1488 - accuracy: 0.9423 - precision: 0.9385 - recall: 0.9467 - auc: 0.9860 - val_loss: 0.6031 - val_accuracy: 0.7970 - val_precision: 0.7151 - val_recall: 0.9871 - val_auc: 0.9276\n",
            "Epoch 900/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1528 - accuracy: 0.9409 - precision: 0.9379 - recall: 0.9443 - auc: 0.9853 - val_loss: 0.5850 - val_accuracy: 0.7931 - val_precision: 0.7109 - val_recall: 0.9879 - val_auc: 0.9331\n",
            "Epoch 901/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1759 - accuracy: 0.9303 - precision: 0.9245 - recall: 0.9370 - auc: 0.9807 - val_loss: 0.4692 - val_accuracy: 0.7668 - val_precision: 0.8770 - val_recall: 0.6204 - val_auc: 0.9009\n",
            "Epoch 902/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1841 - accuracy: 0.9261 - precision: 0.9207 - recall: 0.9325 - auc: 0.9789 - val_loss: 0.4660 - val_accuracy: 0.7745 - val_precision: 0.8929 - val_recall: 0.6238 - val_auc: 0.9099\n",
            "Epoch 903/2000\n",
            "10/10 [==============================] - 5s 487ms/step - loss: 0.1719 - accuracy: 0.9318 - precision: 0.9266 - recall: 0.9379 - auc: 0.9815 - val_loss: 0.3701 - val_accuracy: 0.8307 - val_precision: 0.8726 - val_recall: 0.7743 - val_auc: 0.9251\n",
            "Epoch 904/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1709 - accuracy: 0.9322 - precision: 0.9267 - recall: 0.9387 - auc: 0.9818 - val_loss: 0.3444 - val_accuracy: 0.8494 - val_precision: 0.8538 - val_recall: 0.8430 - val_auc: 0.9293\n",
            "Epoch 905/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1755 - accuracy: 0.9299 - precision: 0.9239 - recall: 0.9371 - auc: 0.9808 - val_loss: 0.3518 - val_accuracy: 0.8583 - val_precision: 0.8139 - val_recall: 0.9288 - val_auc: 0.9359\n",
            "Epoch 906/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1747 - accuracy: 0.9302 - precision: 0.9249 - recall: 0.9365 - auc: 0.9810 - val_loss: 0.3684 - val_accuracy: 0.8556 - val_precision: 0.7941 - val_recall: 0.9601 - val_auc: 0.9448\n",
            "Epoch 907/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1691 - accuracy: 0.9329 - precision: 0.9257 - recall: 0.9414 - auc: 0.9821 - val_loss: 0.3950 - val_accuracy: 0.8520 - val_precision: 0.7884 - val_recall: 0.9622 - val_auc: 0.9404\n",
            "Epoch 908/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1704 - accuracy: 0.9320 - precision: 0.9256 - recall: 0.9396 - auc: 0.9819 - val_loss: 0.4205 - val_accuracy: 0.8439 - val_precision: 0.7742 - val_recall: 0.9709 - val_auc: 0.9403\n",
            "Epoch 909/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1696 - accuracy: 0.9322 - precision: 0.9282 - recall: 0.9369 - auc: 0.9821 - val_loss: 0.4610 - val_accuracy: 0.8311 - val_precision: 0.7565 - val_recall: 0.9764 - val_auc: 0.9332\n",
            "Epoch 910/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1719 - accuracy: 0.9319 - precision: 0.9274 - recall: 0.9372 - auc: 0.9815 - val_loss: 0.4657 - val_accuracy: 0.8292 - val_precision: 0.7540 - val_recall: 0.9770 - val_auc: 0.9320\n",
            "Epoch 911/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1699 - accuracy: 0.9324 - precision: 0.9247 - recall: 0.9415 - auc: 0.9820 - val_loss: 0.4432 - val_accuracy: 0.8328 - val_precision: 0.7578 - val_recall: 0.9780 - val_auc: 0.9406\n",
            "Epoch 912/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1709 - accuracy: 0.9319 - precision: 0.9248 - recall: 0.9402 - auc: 0.9817 - val_loss: 0.3860 - val_accuracy: 0.8578 - val_precision: 0.8006 - val_recall: 0.9528 - val_auc: 0.9370\n",
            "Epoch 913/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1752 - accuracy: 0.9306 - precision: 0.9270 - recall: 0.9349 - auc: 0.9809 - val_loss: 0.4992 - val_accuracy: 0.8245 - val_precision: 0.7482 - val_recall: 0.9781 - val_auc: 0.9304\n",
            "Epoch 914/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1725 - accuracy: 0.9310 - precision: 0.9258 - recall: 0.9372 - auc: 0.9814 - val_loss: 0.4804 - val_accuracy: 0.8266 - val_precision: 0.7505 - val_recall: 0.9782 - val_auc: 0.9363\n",
            "Epoch 915/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1699 - accuracy: 0.9325 - precision: 0.9255 - recall: 0.9408 - auc: 0.9820 - val_loss: 0.4743 - val_accuracy: 0.8259 - val_precision: 0.7490 - val_recall: 0.9801 - val_auc: 0.9369\n",
            "Epoch 916/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1712 - accuracy: 0.9320 - precision: 0.9268 - recall: 0.9381 - auc: 0.9817 - val_loss: 0.4653 - val_accuracy: 0.8305 - val_precision: 0.7558 - val_recall: 0.9763 - val_auc: 0.9334\n",
            "Epoch 917/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1732 - accuracy: 0.9315 - precision: 0.9255 - recall: 0.9385 - auc: 0.9812 - val_loss: 0.5336 - val_accuracy: 0.8047 - val_precision: 0.7242 - val_recall: 0.9840 - val_auc: 0.9324\n",
            "Epoch 918/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1709 - accuracy: 0.9321 - precision: 0.9264 - recall: 0.9389 - auc: 0.9818 - val_loss: 0.4822 - val_accuracy: 0.8269 - val_precision: 0.7506 - val_recall: 0.9790 - val_auc: 0.9327\n",
            "Epoch 919/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1685 - accuracy: 0.9333 - precision: 0.9278 - recall: 0.9398 - auc: 0.9822 - val_loss: 0.4680 - val_accuracy: 0.8292 - val_precision: 0.7544 - val_recall: 0.9762 - val_auc: 0.9327\n",
            "Epoch 920/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1690 - accuracy: 0.9330 - precision: 0.9269 - recall: 0.9402 - auc: 0.9821 - val_loss: 0.4724 - val_accuracy: 0.8283 - val_precision: 0.7524 - val_recall: 0.9784 - val_auc: 0.9344\n",
            "Epoch 921/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1668 - accuracy: 0.9342 - precision: 0.9302 - recall: 0.9388 - auc: 0.9826 - val_loss: 0.5526 - val_accuracy: 0.8005 - val_precision: 0.7192 - val_recall: 0.9855 - val_auc: 0.9288\n",
            "Epoch 922/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.2023 - accuracy: 0.9198 - precision: 0.9152 - recall: 0.9254 - auc: 0.9747 - val_loss: 0.3891 - val_accuracy: 0.8448 - val_precision: 0.7718 - val_recall: 0.9788 - val_auc: 0.9541\n",
            "Epoch 923/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1853 - accuracy: 0.9259 - precision: 0.9196 - recall: 0.9335 - auc: 0.9787 - val_loss: 0.3622 - val_accuracy: 0.8521 - val_precision: 0.7850 - val_recall: 0.9696 - val_auc: 0.9497\n",
            "Epoch 924/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1744 - accuracy: 0.9306 - precision: 0.9256 - recall: 0.9366 - auc: 0.9810 - val_loss: 0.3678 - val_accuracy: 0.8524 - val_precision: 0.7845 - val_recall: 0.9716 - val_auc: 0.9507\n",
            "Epoch 925/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1708 - accuracy: 0.9324 - precision: 0.9289 - recall: 0.9366 - auc: 0.9818 - val_loss: 0.4305 - val_accuracy: 0.8322 - val_precision: 0.7570 - val_recall: 0.9784 - val_auc: 0.9455\n",
            "Epoch 926/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1689 - accuracy: 0.9332 - precision: 0.9269 - recall: 0.9407 - auc: 0.9822 - val_loss: 0.4244 - val_accuracy: 0.8371 - val_precision: 0.7651 - val_recall: 0.9728 - val_auc: 0.9399\n",
            "Epoch 927/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1694 - accuracy: 0.9332 - precision: 0.9270 - recall: 0.9404 - auc: 0.9820 - val_loss: 0.4590 - val_accuracy: 0.8280 - val_precision: 0.7526 - val_recall: 0.9773 - val_auc: 0.9372\n",
            "Epoch 928/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1681 - accuracy: 0.9336 - precision: 0.9289 - recall: 0.9391 - auc: 0.9824 - val_loss: 0.4753 - val_accuracy: 0.8266 - val_precision: 0.7508 - val_recall: 0.9775 - val_auc: 0.9339\n",
            "Epoch 929/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1659 - accuracy: 0.9344 - precision: 0.9286 - recall: 0.9411 - auc: 0.9828 - val_loss: 0.5033 - val_accuracy: 0.8216 - val_precision: 0.7438 - val_recall: 0.9811 - val_auc: 0.9327\n",
            "Epoch 930/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1613 - accuracy: 0.9369 - precision: 0.9331 - recall: 0.9414 - auc: 0.9837 - val_loss: 0.4674 - val_accuracy: 0.8318 - val_precision: 0.7590 - val_recall: 0.9722 - val_auc: 0.9319\n",
            "Epoch 931/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1527 - accuracy: 0.9407 - precision: 0.9380 - recall: 0.9439 - auc: 0.9853 - val_loss: 0.5129 - val_accuracy: 0.8161 - val_precision: 0.7372 - val_recall: 0.9824 - val_auc: 0.9356\n",
            "Epoch 932/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1529 - accuracy: 0.9403 - precision: 0.9353 - recall: 0.9461 - auc: 0.9852 - val_loss: 0.5050 - val_accuracy: 0.8182 - val_precision: 0.7405 - val_recall: 0.9796 - val_auc: 0.9319\n",
            "Epoch 933/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1514 - accuracy: 0.9412 - precision: 0.9392 - recall: 0.9434 - auc: 0.9855 - val_loss: 0.4869 - val_accuracy: 0.8253 - val_precision: 0.7483 - val_recall: 0.9800 - val_auc: 0.9358\n",
            "Epoch 934/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1482 - accuracy: 0.9419 - precision: 0.9396 - recall: 0.9445 - auc: 0.9862 - val_loss: 0.4781 - val_accuracy: 0.8270 - val_precision: 0.7513 - val_recall: 0.9776 - val_auc: 0.9359\n",
            "Epoch 935/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1484 - accuracy: 0.9426 - precision: 0.9394 - recall: 0.9463 - auc: 0.9861 - val_loss: 0.5252 - val_accuracy: 0.8157 - val_precision: 0.7369 - val_recall: 0.9818 - val_auc: 0.9343\n",
            "Epoch 936/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1543 - accuracy: 0.9399 - precision: 0.9365 - recall: 0.9439 - auc: 0.9850 - val_loss: 0.4964 - val_accuracy: 0.8262 - val_precision: 0.7500 - val_recall: 0.9783 - val_auc: 0.9332\n",
            "Epoch 937/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1448 - accuracy: 0.9437 - precision: 0.9402 - recall: 0.9477 - auc: 0.9867 - val_loss: 0.5842 - val_accuracy: 0.7993 - val_precision: 0.7174 - val_recall: 0.9872 - val_auc: 0.9332\n",
            "Epoch 938/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1624 - accuracy: 0.9366 - precision: 0.9331 - recall: 0.9407 - auc: 0.9835 - val_loss: 0.4234 - val_accuracy: 0.8352 - val_precision: 0.7628 - val_recall: 0.9729 - val_auc: 0.9392\n",
            "Epoch 939/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1721 - accuracy: 0.9318 - precision: 0.9255 - recall: 0.9393 - auc: 0.9815 - val_loss: 0.3674 - val_accuracy: 0.8350 - val_precision: 0.8552 - val_recall: 0.8065 - val_auc: 0.9231\n",
            "Epoch 940/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1709 - accuracy: 0.9322 - precision: 0.9275 - recall: 0.9377 - auc: 0.9818 - val_loss: 0.3640 - val_accuracy: 0.8394 - val_precision: 0.8411 - val_recall: 0.8367 - val_auc: 0.9231\n",
            "Epoch 941/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1703 - accuracy: 0.9319 - precision: 0.9266 - recall: 0.9381 - auc: 0.9819 - val_loss: 0.3581 - val_accuracy: 0.8499 - val_precision: 0.8200 - val_recall: 0.8965 - val_auc: 0.9293\n",
            "Epoch 942/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1691 - accuracy: 0.9328 - precision: 0.9259 - recall: 0.9409 - auc: 0.9821 - val_loss: 0.3666 - val_accuracy: 0.8577 - val_precision: 0.8128 - val_recall: 0.9293 - val_auc: 0.9356\n",
            "Epoch 943/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1670 - accuracy: 0.9341 - precision: 0.9298 - recall: 0.9391 - auc: 0.9825 - val_loss: 0.3872 - val_accuracy: 0.8513 - val_precision: 0.7901 - val_recall: 0.9567 - val_auc: 0.9382\n",
            "Epoch 944/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1692 - accuracy: 0.9332 - precision: 0.9279 - recall: 0.9394 - auc: 0.9821 - val_loss: 0.3743 - val_accuracy: 0.8541 - val_precision: 0.7992 - val_recall: 0.9457 - val_auc: 0.9356\n",
            "Epoch 945/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1696 - accuracy: 0.9327 - precision: 0.9267 - recall: 0.9397 - auc: 0.9820 - val_loss: 0.4340 - val_accuracy: 0.8382 - val_precision: 0.7653 - val_recall: 0.9753 - val_auc: 0.9424\n",
            "Epoch 946/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1671 - accuracy: 0.9343 - precision: 0.9296 - recall: 0.9397 - auc: 0.9825 - val_loss: 0.4667 - val_accuracy: 0.8277 - val_precision: 0.7519 - val_recall: 0.9779 - val_auc: 0.9386\n",
            "Epoch 947/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1699 - accuracy: 0.9324 - precision: 0.9279 - recall: 0.9376 - auc: 0.9819 - val_loss: 0.4512 - val_accuracy: 0.8323 - val_precision: 0.7571 - val_recall: 0.9785 - val_auc: 0.9411\n",
            "Epoch 948/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1695 - accuracy: 0.9328 - precision: 0.9264 - recall: 0.9403 - auc: 0.9820 - val_loss: 0.4379 - val_accuracy: 0.8369 - val_precision: 0.7642 - val_recall: 0.9742 - val_auc: 0.9382\n",
            "Epoch 949/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1660 - accuracy: 0.9348 - precision: 0.9301 - recall: 0.9403 - auc: 0.9828 - val_loss: 0.4647 - val_accuracy: 0.8328 - val_precision: 0.7580 - val_recall: 0.9775 - val_auc: 0.9372\n",
            "Epoch 950/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1653 - accuracy: 0.9349 - precision: 0.9289 - recall: 0.9419 - auc: 0.9829 - val_loss: 0.5353 - val_accuracy: 0.8072 - val_precision: 0.7268 - val_recall: 0.9843 - val_auc: 0.9325\n",
            "Epoch 951/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1668 - accuracy: 0.9342 - precision: 0.9293 - recall: 0.9399 - auc: 0.9826 - val_loss: 0.4360 - val_accuracy: 0.8349 - val_precision: 0.7636 - val_recall: 0.9700 - val_auc: 0.9311\n",
            "Epoch 952/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1705 - accuracy: 0.9324 - precision: 0.9267 - recall: 0.9391 - auc: 0.9819 - val_loss: 0.3978 - val_accuracy: 0.8524 - val_precision: 0.7898 - val_recall: 0.9603 - val_auc: 0.9364\n",
            "Epoch 953/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1685 - accuracy: 0.9330 - precision: 0.9274 - recall: 0.9396 - auc: 0.9823 - val_loss: 0.4541 - val_accuracy: 0.8304 - val_precision: 0.7548 - val_recall: 0.9785 - val_auc: 0.9375\n",
            "Epoch 954/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1664 - accuracy: 0.9337 - precision: 0.9273 - recall: 0.9413 - auc: 0.9827 - val_loss: 0.4926 - val_accuracy: 0.8170 - val_precision: 0.7374 - val_recall: 0.9846 - val_auc: 0.9378\n",
            "Epoch 955/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1667 - accuracy: 0.9335 - precision: 0.9279 - recall: 0.9400 - auc: 0.9826 - val_loss: 0.4283 - val_accuracy: 0.8403 - val_precision: 0.7698 - val_recall: 0.9709 - val_auc: 0.9373\n",
            "Epoch 956/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1683 - accuracy: 0.9335 - precision: 0.9297 - recall: 0.9379 - auc: 0.9823 - val_loss: 0.4958 - val_accuracy: 0.8156 - val_precision: 0.7363 - val_recall: 0.9832 - val_auc: 0.9372\n",
            "Epoch 957/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1650 - accuracy: 0.9349 - precision: 0.9306 - recall: 0.9399 - auc: 0.9829 - val_loss: 0.4531 - val_accuracy: 0.8333 - val_precision: 0.7603 - val_recall: 0.9733 - val_auc: 0.9316\n",
            "Epoch 958/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1663 - accuracy: 0.9341 - precision: 0.9291 - recall: 0.9399 - auc: 0.9827 - val_loss: 0.4856 - val_accuracy: 0.8193 - val_precision: 0.7403 - val_recall: 0.9834 - val_auc: 0.9380\n",
            "Epoch 959/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1638 - accuracy: 0.9354 - precision: 0.9319 - recall: 0.9395 - auc: 0.9832 - val_loss: 0.4759 - val_accuracy: 0.8223 - val_precision: 0.7445 - val_recall: 0.9814 - val_auc: 0.9369\n",
            "Epoch 960/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1658 - accuracy: 0.9347 - precision: 0.9296 - recall: 0.9408 - auc: 0.9827 - val_loss: 0.5780 - val_accuracy: 0.7898 - val_precision: 0.7072 - val_recall: 0.9887 - val_auc: 0.9315\n",
            "Epoch 961/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1638 - accuracy: 0.9354 - precision: 0.9305 - recall: 0.9413 - auc: 0.9832 - val_loss: 0.5046 - val_accuracy: 0.8170 - val_precision: 0.7376 - val_recall: 0.9838 - val_auc: 0.9378\n",
            "Epoch 962/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1598 - accuracy: 0.9370 - precision: 0.9344 - recall: 0.9400 - auc: 0.9840 - val_loss: 0.4874 - val_accuracy: 0.8234 - val_precision: 0.7456 - val_recall: 0.9814 - val_auc: 0.9378\n",
            "Epoch 963/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1503 - accuracy: 0.9412 - precision: 0.9369 - recall: 0.9462 - auc: 0.9858 - val_loss: 0.5099 - val_accuracy: 0.8209 - val_precision: 0.7428 - val_recall: 0.9816 - val_auc: 0.9393\n",
            "Epoch 964/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1500 - accuracy: 0.9414 - precision: 0.9386 - recall: 0.9447 - auc: 0.9858 - val_loss: 0.5034 - val_accuracy: 0.8168 - val_precision: 0.7387 - val_recall: 0.9802 - val_auc: 0.9367\n",
            "Epoch 965/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1507 - accuracy: 0.9417 - precision: 0.9385 - recall: 0.9454 - auc: 0.9857 - val_loss: 0.4845 - val_accuracy: 0.8296 - val_precision: 0.7540 - val_recall: 0.9781 - val_auc: 0.9388\n",
            "Epoch 966/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1481 - accuracy: 0.9426 - precision: 0.9403 - recall: 0.9452 - auc: 0.9862 - val_loss: 0.5189 - val_accuracy: 0.8188 - val_precision: 0.7397 - val_recall: 0.9837 - val_auc: 0.9414\n",
            "Epoch 967/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1457 - accuracy: 0.9436 - precision: 0.9421 - recall: 0.9453 - auc: 0.9866 - val_loss: 0.5419 - val_accuracy: 0.8090 - val_precision: 0.7289 - val_recall: 0.9839 - val_auc: 0.9347\n",
            "Epoch 968/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1450 - accuracy: 0.9436 - precision: 0.9413 - recall: 0.9463 - auc: 0.9867 - val_loss: 0.5975 - val_accuracy: 0.7901 - val_precision: 0.7075 - val_recall: 0.9890 - val_auc: 0.9368\n",
            "Epoch 969/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1613 - accuracy: 0.9365 - precision: 0.9318 - recall: 0.9419 - auc: 0.9837 - val_loss: 0.5215 - val_accuracy: 0.8049 - val_precision: 0.7237 - val_recall: 0.9861 - val_auc: 0.9362\n",
            "Epoch 970/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1662 - accuracy: 0.9345 - precision: 0.9274 - recall: 0.9428 - auc: 0.9828 - val_loss: 0.5089 - val_accuracy: 0.8119 - val_precision: 0.7325 - val_recall: 0.9824 - val_auc: 0.9317\n",
            "Epoch 971/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1578 - accuracy: 0.9385 - precision: 0.9342 - recall: 0.9434 - auc: 0.9844 - val_loss: 0.5221 - val_accuracy: 0.8084 - val_precision: 0.7282 - val_recall: 0.9836 - val_auc: 0.9308\n",
            "Epoch 972/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1572 - accuracy: 0.9386 - precision: 0.9352 - recall: 0.9426 - auc: 0.9845 - val_loss: 0.4715 - val_accuracy: 0.8213 - val_precision: 0.7442 - val_recall: 0.9789 - val_auc: 0.9401\n",
            "Epoch 973/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1484 - accuracy: 0.9422 - precision: 0.9393 - recall: 0.9455 - auc: 0.9861 - val_loss: 0.4641 - val_accuracy: 0.8281 - val_precision: 0.7531 - val_recall: 0.9760 - val_auc: 0.9401\n",
            "Epoch 974/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1429 - accuracy: 0.9451 - precision: 0.9429 - recall: 0.9476 - auc: 0.9871 - val_loss: 0.5651 - val_accuracy: 0.7994 - val_precision: 0.7172 - val_recall: 0.9883 - val_auc: 0.9408\n",
            "Epoch 975/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1454 - accuracy: 0.9436 - precision: 0.9407 - recall: 0.9470 - auc: 0.9867 - val_loss: 0.5010 - val_accuracy: 0.8213 - val_precision: 0.7458 - val_recall: 0.9746 - val_auc: 0.9304\n",
            "Epoch 976/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1515 - accuracy: 0.9413 - precision: 0.9388 - recall: 0.9441 - auc: 0.9855 - val_loss: 0.5578 - val_accuracy: 0.8048 - val_precision: 0.7237 - val_recall: 0.9861 - val_auc: 0.9352\n",
            "Epoch 977/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1401 - accuracy: 0.9456 - precision: 0.9437 - recall: 0.9478 - auc: 0.9876 - val_loss: 0.5717 - val_accuracy: 0.8022 - val_precision: 0.7206 - val_recall: 0.9869 - val_auc: 0.9367\n",
            "Epoch 978/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1473 - accuracy: 0.9428 - precision: 0.9399 - recall: 0.9460 - auc: 0.9863 - val_loss: 0.5790 - val_accuracy: 0.7989 - val_precision: 0.7167 - val_recall: 0.9884 - val_auc: 0.9357\n",
            "Epoch 979/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1519 - accuracy: 0.9405 - precision: 0.9380 - recall: 0.9433 - auc: 0.9855 - val_loss: 0.5255 - val_accuracy: 0.8138 - val_precision: 0.7339 - val_recall: 0.9843 - val_auc: 0.9375\n",
            "Epoch 980/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1398 - accuracy: 0.9456 - precision: 0.9415 - recall: 0.9503 - auc: 0.9876 - val_loss: 0.5232 - val_accuracy: 0.8150 - val_precision: 0.7365 - val_recall: 0.9807 - val_auc: 0.9353\n",
            "Epoch 981/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1456 - accuracy: 0.9437 - precision: 0.9430 - recall: 0.9445 - auc: 0.9866 - val_loss: 0.5276 - val_accuracy: 0.8085 - val_precision: 0.7276 - val_recall: 0.9860 - val_auc: 0.9425\n",
            "Epoch 982/2000\n",
            "10/10 [==============================] - 5s 491ms/step - loss: 0.1495 - accuracy: 0.9420 - precision: 0.9366 - recall: 0.9482 - auc: 0.9859 - val_loss: 0.5399 - val_accuracy: 0.8059 - val_precision: 0.7245 - val_recall: 0.9870 - val_auc: 0.9379\n",
            "Epoch 983/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1389 - accuracy: 0.9461 - precision: 0.9431 - recall: 0.9494 - auc: 0.9878 - val_loss: 0.6072 - val_accuracy: 0.7885 - val_precision: 0.7057 - val_recall: 0.9894 - val_auc: 0.9349\n",
            "Epoch 984/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1430 - accuracy: 0.9445 - precision: 0.9431 - recall: 0.9461 - auc: 0.9870 - val_loss: 0.4969 - val_accuracy: 0.8281 - val_precision: 0.7508 - val_recall: 0.9819 - val_auc: 0.9440\n",
            "Epoch 985/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1454 - accuracy: 0.9437 - precision: 0.9421 - recall: 0.9455 - auc: 0.9867 - val_loss: 0.6175 - val_accuracy: 0.7988 - val_precision: 0.7167 - val_recall: 0.9879 - val_auc: 0.9316\n",
            "Epoch 986/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1422 - accuracy: 0.9453 - precision: 0.9438 - recall: 0.9471 - auc: 0.9872 - val_loss: 0.5852 - val_accuracy: 0.8029 - val_precision: 0.7212 - val_recall: 0.9872 - val_auc: 0.9356\n",
            "Epoch 987/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1422 - accuracy: 0.9448 - precision: 0.9407 - recall: 0.9496 - auc: 0.9872 - val_loss: 0.5771 - val_accuracy: 0.8018 - val_precision: 0.7199 - val_recall: 0.9876 - val_auc: 0.9388\n",
            "Epoch 988/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1452 - accuracy: 0.9436 - precision: 0.9439 - recall: 0.9434 - auc: 0.9867 - val_loss: 0.3851 - val_accuracy: 0.8479 - val_precision: 0.7777 - val_recall: 0.9742 - val_auc: 0.9519\n",
            "Epoch 989/2000\n",
            "10/10 [==============================] - 4s 417ms/step - loss: 0.1566 - accuracy: 0.9383 - precision: 0.9362 - recall: 0.9407 - auc: 0.9847 - val_loss: 0.5359 - val_accuracy: 0.8107 - val_precision: 0.7306 - val_recall: 0.9843 - val_auc: 0.9340\n",
            "Epoch 990/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1405 - accuracy: 0.9458 - precision: 0.9444 - recall: 0.9474 - auc: 0.9875 - val_loss: 0.5720 - val_accuracy: 0.7984 - val_precision: 0.7162 - val_recall: 0.9883 - val_auc: 0.9376\n",
            "Epoch 991/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1420 - accuracy: 0.9446 - precision: 0.9426 - recall: 0.9469 - auc: 0.9872 - val_loss: 0.5565 - val_accuracy: 0.8031 - val_precision: 0.7215 - val_recall: 0.9870 - val_auc: 0.9352\n",
            "Epoch 992/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1450 - accuracy: 0.9439 - precision: 0.9410 - recall: 0.9472 - auc: 0.9868 - val_loss: 0.5540 - val_accuracy: 0.8084 - val_precision: 0.7273 - val_recall: 0.9865 - val_auc: 0.9378\n",
            "Epoch 993/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1353 - accuracy: 0.9478 - precision: 0.9464 - recall: 0.9493 - auc: 0.9884 - val_loss: 0.6015 - val_accuracy: 0.7992 - val_precision: 0.7168 - val_recall: 0.9890 - val_auc: 0.9388\n",
            "Epoch 994/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1401 - accuracy: 0.9459 - precision: 0.9442 - recall: 0.9479 - auc: 0.9876 - val_loss: 0.5429 - val_accuracy: 0.8163 - val_precision: 0.7364 - val_recall: 0.9851 - val_auc: 0.9398\n",
            "Epoch 995/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1371 - accuracy: 0.9472 - precision: 0.9455 - recall: 0.9491 - auc: 0.9881 - val_loss: 0.6040 - val_accuracy: 0.7939 - val_precision: 0.7114 - val_recall: 0.9888 - val_auc: 0.9356\n",
            "Epoch 996/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1363 - accuracy: 0.9473 - precision: 0.9449 - recall: 0.9501 - auc: 0.9882 - val_loss: 0.6028 - val_accuracy: 0.7948 - val_precision: 0.7123 - val_recall: 0.9890 - val_auc: 0.9354\n",
            "Epoch 997/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1398 - accuracy: 0.9455 - precision: 0.9436 - recall: 0.9478 - auc: 0.9876 - val_loss: 0.5709 - val_accuracy: 0.8044 - val_precision: 0.7233 - val_recall: 0.9857 - val_auc: 0.9341\n",
            "Epoch 998/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1359 - accuracy: 0.9473 - precision: 0.9456 - recall: 0.9492 - auc: 0.9883 - val_loss: 0.3838 - val_accuracy: 0.8560 - val_precision: 0.7896 - val_recall: 0.9705 - val_auc: 0.9518\n",
            "Epoch 999/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1410 - accuracy: 0.9452 - precision: 0.9439 - recall: 0.9466 - auc: 0.9874 - val_loss: 0.6196 - val_accuracy: 0.7859 - val_precision: 0.7030 - val_recall: 0.9898 - val_auc: 0.9353\n",
            "Epoch 1000/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1373 - accuracy: 0.9472 - precision: 0.9465 - recall: 0.9479 - auc: 0.9880 - val_loss: 0.6864 - val_accuracy: 0.7679 - val_precision: 0.6846 - val_recall: 0.9932 - val_auc: 0.9384\n",
            "Epoch 1001/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1408 - accuracy: 0.9455 - precision: 0.9421 - recall: 0.9493 - auc: 0.9874 - val_loss: 0.6135 - val_accuracy: 0.7835 - val_precision: 0.7005 - val_recall: 0.9903 - val_auc: 0.9311\n",
            "Epoch 1002/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1302 - accuracy: 0.9496 - precision: 0.9496 - recall: 0.9495 - auc: 0.9892 - val_loss: 0.6602 - val_accuracy: 0.7697 - val_precision: 0.6864 - val_recall: 0.9929 - val_auc: 0.9339\n",
            "Epoch 1003/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1519 - accuracy: 0.9407 - precision: 0.9380 - recall: 0.9438 - auc: 0.9855 - val_loss: 0.6012 - val_accuracy: 0.7926 - val_precision: 0.7100 - val_recall: 0.9888 - val_auc: 0.9311\n",
            "Epoch 1004/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1524 - accuracy: 0.9406 - precision: 0.9361 - recall: 0.9457 - auc: 0.9854 - val_loss: 0.6806 - val_accuracy: 0.7697 - val_precision: 0.6863 - val_recall: 0.9930 - val_auc: 0.9343\n",
            "Epoch 1005/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1314 - accuracy: 0.9498 - precision: 0.9473 - recall: 0.9525 - auc: 0.9889 - val_loss: 0.6110 - val_accuracy: 0.7956 - val_precision: 0.7126 - val_recall: 0.9906 - val_auc: 0.9430\n",
            "Epoch 1006/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1383 - accuracy: 0.9465 - precision: 0.9457 - recall: 0.9474 - auc: 0.9879 - val_loss: 0.6984 - val_accuracy: 0.7731 - val_precision: 0.6896 - val_recall: 0.9931 - val_auc: 0.9384\n",
            "Epoch 1007/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1373 - accuracy: 0.9472 - precision: 0.9470 - recall: 0.9475 - auc: 0.9880 - val_loss: 0.5889 - val_accuracy: 0.8038 - val_precision: 0.7222 - val_recall: 0.9874 - val_auc: 0.9371\n",
            "Epoch 1008/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1354 - accuracy: 0.9474 - precision: 0.9469 - recall: 0.9479 - auc: 0.9884 - val_loss: 0.6237 - val_accuracy: 0.7948 - val_precision: 0.7121 - val_recall: 0.9893 - val_auc: 0.9346\n",
            "Epoch 1009/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1480 - accuracy: 0.9422 - precision: 0.9411 - recall: 0.9434 - auc: 0.9862 - val_loss: 0.8677 - val_accuracy: 0.5878 - val_precision: 0.8358 - val_recall: 0.2181 - val_auc: 0.8060\n",
            "Epoch 1010/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1720 - accuracy: 0.9317 - precision: 0.9245 - recall: 0.9403 - auc: 0.9816 - val_loss: 0.8084 - val_accuracy: 0.5948 - val_precision: 0.8902 - val_recall: 0.2159 - val_auc: 0.8407\n",
            "Epoch 1011/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1690 - accuracy: 0.9329 - precision: 0.9276 - recall: 0.9391 - auc: 0.9821 - val_loss: 0.6659 - val_accuracy: 0.6545 - val_precision: 0.9085 - val_recall: 0.3432 - val_auc: 0.8820\n",
            "Epoch 1012/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1681 - accuracy: 0.9337 - precision: 0.9291 - recall: 0.9390 - auc: 0.9824 - val_loss: 0.4878 - val_accuracy: 0.7338 - val_precision: 0.9009 - val_recall: 0.5252 - val_auc: 0.9078\n",
            "Epoch 1013/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1700 - accuracy: 0.9325 - precision: 0.9279 - recall: 0.9379 - auc: 0.9820 - val_loss: 0.3987 - val_accuracy: 0.7944 - val_precision: 0.8913 - val_recall: 0.6703 - val_auc: 0.9208\n",
            "Epoch 1014/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1676 - accuracy: 0.9338 - precision: 0.9270 - recall: 0.9417 - auc: 0.9824 - val_loss: 0.3475 - val_accuracy: 0.8376 - val_precision: 0.8787 - val_recall: 0.7832 - val_auc: 0.9301\n",
            "Epoch 1015/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1689 - accuracy: 0.9332 - precision: 0.9286 - recall: 0.9386 - auc: 0.9822 - val_loss: 0.3005 - val_accuracy: 0.8775 - val_precision: 0.8519 - val_recall: 0.9137 - val_auc: 0.9467\n",
            "Epoch 1016/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1662 - accuracy: 0.9339 - precision: 0.9286 - recall: 0.9401 - auc: 0.9828 - val_loss: 0.3881 - val_accuracy: 0.8516 - val_precision: 0.7841 - val_recall: 0.9700 - val_auc: 0.9457\n",
            "Epoch 1017/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1668 - accuracy: 0.9342 - precision: 0.9286 - recall: 0.9407 - auc: 0.9826 - val_loss: 0.3390 - val_accuracy: 0.8648 - val_precision: 0.8141 - val_recall: 0.9453 - val_auc: 0.9435\n",
            "Epoch 1018/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1700 - accuracy: 0.9324 - precision: 0.9260 - recall: 0.9400 - auc: 0.9819 - val_loss: 0.3647 - val_accuracy: 0.8585 - val_precision: 0.8010 - val_recall: 0.9538 - val_auc: 0.9385\n",
            "Epoch 1019/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1682 - accuracy: 0.9339 - precision: 0.9311 - recall: 0.9372 - auc: 0.9823 - val_loss: 0.4507 - val_accuracy: 0.8251 - val_precision: 0.7488 - val_recall: 0.9780 - val_auc: 0.9351\n",
            "Epoch 1020/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1633 - accuracy: 0.9357 - precision: 0.9318 - recall: 0.9401 - auc: 0.9833 - val_loss: 0.4479 - val_accuracy: 0.8297 - val_precision: 0.7553 - val_recall: 0.9752 - val_auc: 0.9324\n",
            "Epoch 1021/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1633 - accuracy: 0.9352 - precision: 0.9298 - recall: 0.9417 - auc: 0.9833 - val_loss: 0.4509 - val_accuracy: 0.8327 - val_precision: 0.7592 - val_recall: 0.9745 - val_auc: 0.9333\n",
            "Epoch 1022/2000\n",
            "10/10 [==============================] - 4s 425ms/step - loss: 0.1673 - accuracy: 0.9344 - precision: 0.9305 - recall: 0.9390 - auc: 0.9824 - val_loss: 0.3632 - val_accuracy: 0.8586 - val_precision: 0.7994 - val_recall: 0.9572 - val_auc: 0.9422\n",
            "Epoch 1023/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1622 - accuracy: 0.9361 - precision: 0.9324 - recall: 0.9404 - auc: 0.9835 - val_loss: 0.3934 - val_accuracy: 0.8471 - val_precision: 0.7762 - val_recall: 0.9753 - val_auc: 0.9467\n",
            "Epoch 1024/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1624 - accuracy: 0.9359 - precision: 0.9308 - recall: 0.9419 - auc: 0.9835 - val_loss: 0.4883 - val_accuracy: 0.8188 - val_precision: 0.7404 - val_recall: 0.9815 - val_auc: 0.9342\n",
            "Epoch 1025/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1645 - accuracy: 0.9350 - precision: 0.9304 - recall: 0.9404 - auc: 0.9831 - val_loss: 0.5080 - val_accuracy: 0.8117 - val_precision: 0.7312 - val_recall: 0.9857 - val_auc: 0.9374\n",
            "Epoch 1026/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1598 - accuracy: 0.9369 - precision: 0.9318 - recall: 0.9429 - auc: 0.9840 - val_loss: 0.4724 - val_accuracy: 0.8247 - val_precision: 0.7485 - val_recall: 0.9780 - val_auc: 0.9326\n",
            "Epoch 1027/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1551 - accuracy: 0.9391 - precision: 0.9338 - recall: 0.9453 - auc: 0.9849 - val_loss: 0.5151 - val_accuracy: 0.8158 - val_precision: 0.7356 - val_recall: 0.9860 - val_auc: 0.9448\n",
            "Epoch 1028/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1523 - accuracy: 0.9402 - precision: 0.9372 - recall: 0.9438 - auc: 0.9854 - val_loss: 0.4326 - val_accuracy: 0.8425 - val_precision: 0.7723 - val_recall: 0.9713 - val_auc: 0.9393\n",
            "Epoch 1029/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1463 - accuracy: 0.9432 - precision: 0.9403 - recall: 0.9464 - auc: 0.9865 - val_loss: 0.5125 - val_accuracy: 0.8152 - val_precision: 0.7362 - val_recall: 0.9820 - val_auc: 0.9330\n",
            "Epoch 1030/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1365 - accuracy: 0.9475 - precision: 0.9445 - recall: 0.9510 - auc: 0.9881 - val_loss: 0.5091 - val_accuracy: 0.8187 - val_precision: 0.7387 - val_recall: 0.9860 - val_auc: 0.9475\n",
            "Epoch 1031/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1378 - accuracy: 0.9467 - precision: 0.9453 - recall: 0.9482 - auc: 0.9880 - val_loss: 0.5497 - val_accuracy: 0.8084 - val_precision: 0.7287 - val_recall: 0.9825 - val_auc: 0.9327\n",
            "Epoch 1032/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1323 - accuracy: 0.9491 - precision: 0.9501 - recall: 0.9480 - auc: 0.9889 - val_loss: 0.5656 - val_accuracy: 0.8065 - val_precision: 0.7248 - val_recall: 0.9881 - val_auc: 0.9440\n",
            "Epoch 1033/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1296 - accuracy: 0.9502 - precision: 0.9476 - recall: 0.9530 - auc: 0.9893 - val_loss: 0.5961 - val_accuracy: 0.7995 - val_precision: 0.7175 - val_recall: 0.9878 - val_auc: 0.9373\n",
            "Epoch 1034/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1295 - accuracy: 0.9506 - precision: 0.9503 - recall: 0.9509 - auc: 0.9893 - val_loss: 0.6144 - val_accuracy: 0.7946 - val_precision: 0.7119 - val_recall: 0.9895 - val_auc: 0.9389\n",
            "Epoch 1035/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1348 - accuracy: 0.9482 - precision: 0.9469 - recall: 0.9496 - auc: 0.9884 - val_loss: 0.7015 - val_accuracy: 0.7585 - val_precision: 0.6762 - val_recall: 0.9919 - val_auc: 0.9256\n",
            "Epoch 1036/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1607 - accuracy: 0.9372 - precision: 0.9328 - recall: 0.9423 - auc: 0.9838 - val_loss: 0.5046 - val_accuracy: 0.8220 - val_precision: 0.7455 - val_recall: 0.9777 - val_auc: 0.9287\n",
            "Epoch 1037/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1491 - accuracy: 0.9419 - precision: 0.9372 - recall: 0.9473 - auc: 0.9860 - val_loss: 0.4775 - val_accuracy: 0.8279 - val_precision: 0.7523 - val_recall: 0.9776 - val_auc: 0.9338\n",
            "Epoch 1038/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1446 - accuracy: 0.9437 - precision: 0.9415 - recall: 0.9462 - auc: 0.9868 - val_loss: 0.5913 - val_accuracy: 0.7927 - val_precision: 0.7094 - val_recall: 0.9913 - val_auc: 0.9454\n",
            "Epoch 1039/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1332 - accuracy: 0.9487 - precision: 0.9476 - recall: 0.9499 - auc: 0.9888 - val_loss: 0.5756 - val_accuracy: 0.8003 - val_precision: 0.7173 - val_recall: 0.9908 - val_auc: 0.9514\n",
            "Epoch 1040/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1383 - accuracy: 0.9466 - precision: 0.9461 - recall: 0.9472 - auc: 0.9878 - val_loss: 0.6588 - val_accuracy: 0.7739 - val_precision: 0.6905 - val_recall: 0.9923 - val_auc: 0.9399\n",
            "Epoch 1041/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1344 - accuracy: 0.9477 - precision: 0.9474 - recall: 0.9479 - auc: 0.9886 - val_loss: 0.6258 - val_accuracy: 0.7866 - val_precision: 0.7034 - val_recall: 0.9906 - val_auc: 0.9348\n",
            "Epoch 1042/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1297 - accuracy: 0.9500 - precision: 0.9482 - recall: 0.9520 - auc: 0.9893 - val_loss: 0.5588 - val_accuracy: 0.8054 - val_precision: 0.7238 - val_recall: 0.9875 - val_auc: 0.9419\n",
            "Epoch 1043/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1740 - accuracy: 0.9316 - precision: 0.9248 - recall: 0.9396 - auc: 0.9811 - val_loss: 0.3524 - val_accuracy: 0.8438 - val_precision: 0.8510 - val_recall: 0.8334 - val_auc: 0.9254\n",
            "Epoch 1044/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1691 - accuracy: 0.9326 - precision: 0.9276 - recall: 0.9385 - auc: 0.9822 - val_loss: 0.4071 - val_accuracy: 0.7969 - val_precision: 0.8853 - val_recall: 0.6821 - val_auc: 0.9185\n",
            "Epoch 1045/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1596 - accuracy: 0.9370 - precision: 0.9335 - recall: 0.9411 - auc: 0.9841 - val_loss: 0.3393 - val_accuracy: 0.8486 - val_precision: 0.8601 - val_recall: 0.8326 - val_auc: 0.9302\n",
            "Epoch 1046/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1662 - accuracy: 0.9345 - precision: 0.9300 - recall: 0.9398 - auc: 0.9827 - val_loss: 0.3274 - val_accuracy: 0.8633 - val_precision: 0.8298 - val_recall: 0.9138 - val_auc: 0.9378\n",
            "Epoch 1047/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1715 - accuracy: 0.9317 - precision: 0.9278 - recall: 0.9364 - auc: 0.9817 - val_loss: 0.3340 - val_accuracy: 0.8671 - val_precision: 0.8193 - val_recall: 0.9417 - val_auc: 0.9451\n",
            "Epoch 1048/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1574 - accuracy: 0.9382 - precision: 0.9338 - recall: 0.9434 - auc: 0.9845 - val_loss: 0.5132 - val_accuracy: 0.8094 - val_precision: 0.7276 - val_recall: 0.9888 - val_auc: 0.9501\n",
            "Epoch 1049/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1551 - accuracy: 0.9393 - precision: 0.9360 - recall: 0.9432 - auc: 0.9849 - val_loss: 0.4983 - val_accuracy: 0.8196 - val_precision: 0.7422 - val_recall: 0.9793 - val_auc: 0.9310\n",
            "Epoch 1050/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1657 - accuracy: 0.9351 - precision: 0.9321 - recall: 0.9386 - auc: 0.9829 - val_loss: 0.4606 - val_accuracy: 0.8260 - val_precision: 0.7488 - val_recall: 0.9811 - val_auc: 0.9440\n",
            "Epoch 1051/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1378 - accuracy: 0.9469 - precision: 0.9461 - recall: 0.9478 - auc: 0.9880 - val_loss: 0.5689 - val_accuracy: 0.7856 - val_precision: 0.7019 - val_recall: 0.9925 - val_auc: 0.9508\n",
            "Epoch 1052/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1317 - accuracy: 0.9493 - precision: 0.9476 - recall: 0.9511 - auc: 0.9890 - val_loss: 0.4798 - val_accuracy: 0.8297 - val_precision: 0.7538 - val_recall: 0.9792 - val_auc: 0.9397\n",
            "Epoch 1053/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1338 - accuracy: 0.9484 - precision: 0.9491 - recall: 0.9476 - auc: 0.9886 - val_loss: 0.5486 - val_accuracy: 0.8061 - val_precision: 0.7248 - val_recall: 0.9867 - val_auc: 0.9362\n",
            "Epoch 1054/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1220 - accuracy: 0.9528 - precision: 0.9530 - recall: 0.9526 - auc: 0.9905 - val_loss: 0.7077 - val_accuracy: 0.7641 - val_precision: 0.6808 - val_recall: 0.9940 - val_auc: 0.9415\n",
            "Epoch 1055/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1298 - accuracy: 0.9501 - precision: 0.9483 - recall: 0.9520 - auc: 0.9892 - val_loss: 0.6423 - val_accuracy: 0.7842 - val_precision: 0.7010 - val_recall: 0.9912 - val_auc: 0.9397\n",
            "Epoch 1056/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1324 - accuracy: 0.9491 - precision: 0.9494 - recall: 0.9488 - auc: 0.9888 - val_loss: 0.7097 - val_accuracy: 0.7630 - val_precision: 0.6797 - val_recall: 0.9944 - val_auc: 0.9420\n",
            "Epoch 1057/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1245 - accuracy: 0.9518 - precision: 0.9519 - recall: 0.9516 - auc: 0.9901 - val_loss: 0.6473 - val_accuracy: 0.7826 - val_precision: 0.6993 - val_recall: 0.9914 - val_auc: 0.9363\n",
            "Epoch 1058/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1346 - accuracy: 0.9481 - precision: 0.9461 - recall: 0.9505 - auc: 0.9885 - val_loss: 0.6475 - val_accuracy: 0.7821 - val_precision: 0.6985 - val_recall: 0.9923 - val_auc: 0.9399\n",
            "Epoch 1059/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1271 - accuracy: 0.9514 - precision: 0.9513 - recall: 0.9514 - auc: 0.9897 - val_loss: 0.6126 - val_accuracy: 0.7938 - val_precision: 0.7113 - val_recall: 0.9889 - val_auc: 0.9337\n",
            "Epoch 1060/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1387 - accuracy: 0.9467 - precision: 0.9462 - recall: 0.9472 - auc: 0.9878 - val_loss: 0.6034 - val_accuracy: 0.7853 - val_precision: 0.7018 - val_recall: 0.9919 - val_auc: 0.9478\n",
            "Epoch 1061/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1287 - accuracy: 0.9505 - precision: 0.9477 - recall: 0.9536 - auc: 0.9894 - val_loss: 0.5057 - val_accuracy: 0.8239 - val_precision: 0.7469 - val_recall: 0.9795 - val_auc: 0.9385\n",
            "Epoch 1062/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1238 - accuracy: 0.9530 - precision: 0.9544 - recall: 0.9514 - auc: 0.9902 - val_loss: 0.6070 - val_accuracy: 0.7961 - val_precision: 0.7139 - val_recall: 0.9880 - val_auc: 0.9355\n",
            "Epoch 1063/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1384 - accuracy: 0.9468 - precision: 0.9469 - recall: 0.9467 - auc: 0.9879 - val_loss: 0.6745 - val_accuracy: 0.7759 - val_precision: 0.6926 - val_recall: 0.9919 - val_auc: 0.9334\n",
            "Epoch 1064/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1364 - accuracy: 0.9474 - precision: 0.9454 - recall: 0.9497 - auc: 0.9882 - val_loss: 0.6252 - val_accuracy: 0.7947 - val_precision: 0.7123 - val_recall: 0.9884 - val_auc: 0.9282\n",
            "Epoch 1065/2000\n",
            "10/10 [==============================] - 4s 417ms/step - loss: 0.1387 - accuracy: 0.9462 - precision: 0.9439 - recall: 0.9487 - auc: 0.9878 - val_loss: 1.4611 - val_accuracy: 0.6615 - val_precision: 0.5966 - val_recall: 0.9968 - val_auc: 0.8266\n",
            "Epoch 1066/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1446 - accuracy: 0.9440 - precision: 0.9411 - recall: 0.9472 - auc: 0.9869 - val_loss: 0.5949 - val_accuracy: 0.8003 - val_precision: 0.7181 - val_recall: 0.9884 - val_auc: 0.9303\n",
            "Epoch 1067/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1281 - accuracy: 0.9505 - precision: 0.9505 - recall: 0.9506 - auc: 0.9896 - val_loss: 0.5515 - val_accuracy: 0.8146 - val_precision: 0.7342 - val_recall: 0.9860 - val_auc: 0.9396\n",
            "Epoch 1068/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1228 - accuracy: 0.9529 - precision: 0.9528 - recall: 0.9530 - auc: 0.9904 - val_loss: 0.6106 - val_accuracy: 0.7952 - val_precision: 0.7126 - val_recall: 0.9893 - val_auc: 0.9361\n",
            "Epoch 1069/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1212 - accuracy: 0.9534 - precision: 0.9522 - recall: 0.9547 - auc: 0.9906 - val_loss: 0.6840 - val_accuracy: 0.7750 - val_precision: 0.6916 - val_recall: 0.9921 - val_auc: 0.9366\n",
            "Epoch 1070/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1222 - accuracy: 0.9530 - precision: 0.9521 - recall: 0.9540 - auc: 0.9904 - val_loss: 0.6255 - val_accuracy: 0.7922 - val_precision: 0.7093 - val_recall: 0.9899 - val_auc: 0.9359\n",
            "Epoch 1071/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1292 - accuracy: 0.9501 - precision: 0.9505 - recall: 0.9498 - auc: 0.9893 - val_loss: 0.6562 - val_accuracy: 0.7706 - val_precision: 0.6872 - val_recall: 0.9929 - val_auc: 0.9350\n",
            "Epoch 1072/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1439 - accuracy: 0.9439 - precision: 0.9396 - recall: 0.9489 - auc: 0.9870 - val_loss: 0.6390 - val_accuracy: 0.7859 - val_precision: 0.7027 - val_recall: 0.9908 - val_auc: 0.9309\n",
            "Epoch 1073/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1255 - accuracy: 0.9519 - precision: 0.9510 - recall: 0.9529 - auc: 0.9899 - val_loss: 0.6845 - val_accuracy: 0.7726 - val_precision: 0.6891 - val_recall: 0.9928 - val_auc: 0.9398\n",
            "Epoch 1074/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1272 - accuracy: 0.9508 - precision: 0.9506 - recall: 0.9511 - auc: 0.9897 - val_loss: 0.6000 - val_accuracy: 0.8012 - val_precision: 0.7192 - val_recall: 0.9883 - val_auc: 0.9365\n",
            "Epoch 1075/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1217 - accuracy: 0.9532 - precision: 0.9526 - recall: 0.9539 - auc: 0.9905 - val_loss: 0.4709 - val_accuracy: 0.8295 - val_precision: 0.7512 - val_recall: 0.9852 - val_auc: 0.9551\n",
            "Epoch 1076/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1385 - accuracy: 0.9464 - precision: 0.9443 - recall: 0.9488 - auc: 0.9878 - val_loss: 2.2707 - val_accuracy: 0.5793 - val_precision: 0.5430 - val_recall: 0.9986 - val_auc: 0.7120\n",
            "Epoch 1077/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1341 - accuracy: 0.9486 - precision: 0.9477 - recall: 0.9496 - auc: 0.9886 - val_loss: 1.6399 - val_accuracy: 0.6280 - val_precision: 0.5735 - val_recall: 0.9976 - val_auc: 0.8117\n",
            "Epoch 1078/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1316 - accuracy: 0.9497 - precision: 0.9495 - recall: 0.9500 - auc: 0.9889 - val_loss: 0.8253 - val_accuracy: 0.7373 - val_precision: 0.6570 - val_recall: 0.9926 - val_auc: 0.9102\n",
            "Epoch 1079/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1309 - accuracy: 0.9497 - precision: 0.9481 - recall: 0.9516 - auc: 0.9892 - val_loss: 0.8468 - val_accuracy: 0.7356 - val_precision: 0.6551 - val_recall: 0.9948 - val_auc: 0.9275\n",
            "Epoch 1080/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1310 - accuracy: 0.9496 - precision: 0.9489 - recall: 0.9504 - auc: 0.9891 - val_loss: 0.8204 - val_accuracy: 0.7376 - val_precision: 0.6568 - val_recall: 0.9949 - val_auc: 0.9290\n",
            "Epoch 1081/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1281 - accuracy: 0.9504 - precision: 0.9497 - recall: 0.9511 - auc: 0.9895 - val_loss: 0.6111 - val_accuracy: 0.7929 - val_precision: 0.7099 - val_recall: 0.9905 - val_auc: 0.9392\n",
            "Epoch 1082/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1265 - accuracy: 0.9512 - precision: 0.9506 - recall: 0.9519 - auc: 0.9898 - val_loss: 0.6145 - val_accuracy: 0.7933 - val_precision: 0.7101 - val_recall: 0.9910 - val_auc: 0.9425\n",
            "Epoch 1083/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1230 - accuracy: 0.9527 - precision: 0.9529 - recall: 0.9525 - auc: 0.9903 - val_loss: 0.5953 - val_accuracy: 0.7967 - val_precision: 0.7137 - val_recall: 0.9907 - val_auc: 0.9432\n",
            "Epoch 1084/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1442 - accuracy: 0.9442 - precision: 0.9417 - recall: 0.9471 - auc: 0.9868 - val_loss: 0.6053 - val_accuracy: 0.7946 - val_precision: 0.7121 - val_recall: 0.9888 - val_auc: 0.9295\n",
            "Epoch 1085/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1275 - accuracy: 0.9517 - precision: 0.9495 - recall: 0.9541 - auc: 0.9896 - val_loss: 0.6174 - val_accuracy: 0.7925 - val_precision: 0.7100 - val_recall: 0.9888 - val_auc: 0.9297\n",
            "Epoch 1086/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1307 - accuracy: 0.9495 - precision: 0.9487 - recall: 0.9504 - auc: 0.9891 - val_loss: 0.6045 - val_accuracy: 0.8005 - val_precision: 0.7182 - val_recall: 0.9890 - val_auc: 0.9359\n",
            "Epoch 1087/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1302 - accuracy: 0.9502 - precision: 0.9491 - recall: 0.9513 - auc: 0.9891 - val_loss: 0.6008 - val_accuracy: 0.7985 - val_precision: 0.7171 - val_recall: 0.9858 - val_auc: 0.9261\n",
            "Epoch 1088/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1276 - accuracy: 0.9512 - precision: 0.9510 - recall: 0.9513 - auc: 0.9896 - val_loss: 0.6512 - val_accuracy: 0.7818 - val_precision: 0.6986 - val_recall: 0.9910 - val_auc: 0.9287\n",
            "Epoch 1089/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1179 - accuracy: 0.9550 - precision: 0.9557 - recall: 0.9542 - auc: 0.9911 - val_loss: 0.7052 - val_accuracy: 0.7702 - val_precision: 0.6870 - val_recall: 0.9925 - val_auc: 0.9292\n",
            "Epoch 1090/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1220 - accuracy: 0.9534 - precision: 0.9539 - recall: 0.9529 - auc: 0.9904 - val_loss: 0.6642 - val_accuracy: 0.7774 - val_precision: 0.6940 - val_recall: 0.9921 - val_auc: 0.9307\n",
            "Epoch 1091/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1224 - accuracy: 0.9534 - precision: 0.9531 - recall: 0.9538 - auc: 0.9904 - val_loss: 0.7022 - val_accuracy: 0.7685 - val_precision: 0.6852 - val_recall: 0.9929 - val_auc: 0.9298\n",
            "Epoch 1092/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1224 - accuracy: 0.9531 - precision: 0.9532 - recall: 0.9530 - auc: 0.9904 - val_loss: 0.6706 - val_accuracy: 0.7784 - val_precision: 0.6951 - val_recall: 0.9916 - val_auc: 0.9327\n",
            "Epoch 1093/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1237 - accuracy: 0.9525 - precision: 0.9523 - recall: 0.9527 - auc: 0.9902 - val_loss: 0.6238 - val_accuracy: 0.7918 - val_precision: 0.7098 - val_recall: 0.9871 - val_auc: 0.9290\n",
            "Epoch 1094/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1160 - accuracy: 0.9559 - precision: 0.9553 - recall: 0.9565 - auc: 0.9913 - val_loss: 0.7263 - val_accuracy: 0.7643 - val_precision: 0.6812 - val_recall: 0.9932 - val_auc: 0.9297\n",
            "Epoch 1095/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1140 - accuracy: 0.9563 - precision: 0.9572 - recall: 0.9552 - auc: 0.9916 - val_loss: 0.7411 - val_accuracy: 0.7698 - val_precision: 0.6864 - val_recall: 0.9931 - val_auc: 0.9320\n",
            "Epoch 1096/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1294 - accuracy: 0.9502 - precision: 0.9487 - recall: 0.9519 - auc: 0.9893 - val_loss: 0.7293 - val_accuracy: 0.7697 - val_precision: 0.6866 - val_recall: 0.9922 - val_auc: 0.9265\n",
            "Epoch 1097/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1222 - accuracy: 0.9529 - precision: 0.9523 - recall: 0.9536 - auc: 0.9904 - val_loss: 0.7450 - val_accuracy: 0.7639 - val_precision: 0.6808 - val_recall: 0.9933 - val_auc: 0.9267\n",
            "Epoch 1098/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.1266 - accuracy: 0.9513 - precision: 0.9519 - recall: 0.9507 - auc: 0.9898 - val_loss: 0.6716 - val_accuracy: 0.7753 - val_precision: 0.6918 - val_recall: 0.9927 - val_auc: 0.9371\n",
            "Epoch 1099/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1190 - accuracy: 0.9541 - precision: 0.9541 - recall: 0.9541 - auc: 0.9909 - val_loss: 0.4794 - val_accuracy: 0.8109 - val_precision: 0.7821 - val_recall: 0.8618 - val_auc: 0.8980\n",
            "Epoch 1100/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1131 - accuracy: 0.9566 - precision: 0.9578 - recall: 0.9553 - auc: 0.9917 - val_loss: 0.6651 - val_accuracy: 0.7776 - val_precision: 0.6938 - val_recall: 0.9935 - val_auc: 0.9481\n",
            "Epoch 1101/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1150 - accuracy: 0.9561 - precision: 0.9568 - recall: 0.9553 - auc: 0.9915 - val_loss: 0.3195 - val_accuracy: 0.8790 - val_precision: 0.8147 - val_recall: 0.9811 - val_auc: 0.9747\n",
            "Epoch 1102/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1189 - accuracy: 0.9545 - precision: 0.9538 - recall: 0.9554 - auc: 0.9909 - val_loss: 0.6725 - val_accuracy: 0.7748 - val_precision: 0.6912 - val_recall: 0.9933 - val_auc: 0.9380\n",
            "Epoch 1103/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1261 - accuracy: 0.9518 - precision: 0.9517 - recall: 0.9519 - auc: 0.9898 - val_loss: 0.7069 - val_accuracy: 0.7606 - val_precision: 0.6780 - val_recall: 0.9922 - val_auc: 0.9316\n",
            "Epoch 1104/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1408 - accuracy: 0.9454 - precision: 0.9430 - recall: 0.9482 - auc: 0.9875 - val_loss: 0.3838 - val_accuracy: 0.8263 - val_precision: 0.8879 - val_recall: 0.7467 - val_auc: 0.9268\n",
            "Epoch 1105/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1237 - accuracy: 0.9525 - precision: 0.9519 - recall: 0.9532 - auc: 0.9902 - val_loss: 0.6024 - val_accuracy: 0.7982 - val_precision: 0.7155 - val_recall: 0.9898 - val_auc: 0.9416\n",
            "Epoch 1106/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1096 - accuracy: 0.9579 - precision: 0.9593 - recall: 0.9565 - auc: 0.9922 - val_loss: 0.6016 - val_accuracy: 0.7971 - val_precision: 0.7142 - val_recall: 0.9905 - val_auc: 0.9466\n",
            "Epoch 1107/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1180 - accuracy: 0.9545 - precision: 0.9559 - recall: 0.9529 - auc: 0.9911 - val_loss: 0.7275 - val_accuracy: 0.7652 - val_precision: 0.6821 - val_recall: 0.9933 - val_auc: 0.9333\n",
            "Epoch 1108/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1126 - accuracy: 0.9567 - precision: 0.9582 - recall: 0.9552 - auc: 0.9918 - val_loss: 0.6814 - val_accuracy: 0.7688 - val_precision: 0.6866 - val_recall: 0.9887 - val_auc: 0.9134\n",
            "Epoch 1109/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1876 - accuracy: 0.9264 - precision: 0.9166 - recall: 0.9381 - auc: 0.9783 - val_loss: 0.8047 - val_accuracy: 0.5718 - val_precision: 0.8569 - val_recall: 0.1720 - val_auc: 0.7995\n",
            "Epoch 1110/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1773 - accuracy: 0.9293 - precision: 0.9239 - recall: 0.9357 - auc: 0.9805 - val_loss: 0.6606 - val_accuracy: 0.6514 - val_precision: 0.8765 - val_recall: 0.3522 - val_auc: 0.8496\n",
            "Epoch 1111/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1766 - accuracy: 0.9300 - precision: 0.9236 - recall: 0.9375 - auc: 0.9806 - val_loss: 0.6096 - val_accuracy: 0.6859 - val_precision: 0.8907 - val_recall: 0.4236 - val_auc: 0.8766\n",
            "Epoch 1112/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1701 - accuracy: 0.9323 - precision: 0.9273 - recall: 0.9382 - auc: 0.9819 - val_loss: 0.4229 - val_accuracy: 0.7709 - val_precision: 0.8959 - val_recall: 0.6129 - val_auc: 0.9169\n",
            "Epoch 1113/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1711 - accuracy: 0.9322 - precision: 0.9263 - recall: 0.9391 - auc: 0.9817 - val_loss: 0.3606 - val_accuracy: 0.8205 - val_precision: 0.8881 - val_recall: 0.7332 - val_auc: 0.9281\n",
            "Epoch 1114/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1707 - accuracy: 0.9329 - precision: 0.9266 - recall: 0.9403 - auc: 0.9818 - val_loss: 0.3294 - val_accuracy: 0.8477 - val_precision: 0.8892 - val_recall: 0.7943 - val_auc: 0.9376\n",
            "Epoch 1115/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1682 - accuracy: 0.9337 - precision: 0.9279 - recall: 0.9406 - auc: 0.9823 - val_loss: 0.3121 - val_accuracy: 0.8701 - val_precision: 0.8434 - val_recall: 0.9089 - val_auc: 0.9406\n",
            "Epoch 1116/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1682 - accuracy: 0.9333 - precision: 0.9283 - recall: 0.9392 - auc: 0.9823 - val_loss: 0.3336 - val_accuracy: 0.8582 - val_precision: 0.8378 - val_recall: 0.8882 - val_auc: 0.9321\n",
            "Epoch 1117/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1705 - accuracy: 0.9325 - precision: 0.9275 - recall: 0.9384 - auc: 0.9818 - val_loss: 0.6600 - val_accuracy: 0.6898 - val_precision: 0.9038 - val_recall: 0.4245 - val_auc: 0.8720\n",
            "Epoch 1118/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1714 - accuracy: 0.9320 - precision: 0.9271 - recall: 0.9378 - auc: 0.9817 - val_loss: 0.3051 - val_accuracy: 0.8701 - val_precision: 0.8691 - val_recall: 0.8714 - val_auc: 0.9420\n",
            "Epoch 1119/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1705 - accuracy: 0.9332 - precision: 0.9284 - recall: 0.9387 - auc: 0.9818 - val_loss: 0.3523 - val_accuracy: 0.8603 - val_precision: 0.8078 - val_recall: 0.9455 - val_auc: 0.9379\n",
            "Epoch 1120/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1719 - accuracy: 0.9319 - precision: 0.9270 - recall: 0.9376 - auc: 0.9816 - val_loss: 0.3627 - val_accuracy: 0.8576 - val_precision: 0.7952 - val_recall: 0.9630 - val_auc: 0.9436\n",
            "Epoch 1121/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1686 - accuracy: 0.9332 - precision: 0.9271 - recall: 0.9404 - auc: 0.9822 - val_loss: 0.4817 - val_accuracy: 0.7720 - val_precision: 0.8824 - val_recall: 0.6275 - val_auc: 0.8983\n",
            "Epoch 1122/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1695 - accuracy: 0.9331 - precision: 0.9278 - recall: 0.9393 - auc: 0.9820 - val_loss: 0.4015 - val_accuracy: 0.8141 - val_precision: 0.8597 - val_recall: 0.7505 - val_auc: 0.9104\n",
            "Epoch 1123/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1692 - accuracy: 0.9329 - precision: 0.9273 - recall: 0.9395 - auc: 0.9821 - val_loss: 0.3706 - val_accuracy: 0.8504 - val_precision: 0.8073 - val_recall: 0.9204 - val_auc: 0.9250\n",
            "Epoch 1124/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1707 - accuracy: 0.9319 - precision: 0.9278 - recall: 0.9368 - auc: 0.9818 - val_loss: 0.3921 - val_accuracy: 0.8506 - val_precision: 0.7919 - val_recall: 0.9510 - val_auc: 0.9271\n",
            "Epoch 1125/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1689 - accuracy: 0.9329 - precision: 0.9266 - recall: 0.9404 - auc: 0.9822 - val_loss: 0.4249 - val_accuracy: 0.8406 - val_precision: 0.7734 - val_recall: 0.9631 - val_auc: 0.9272\n",
            "Epoch 1126/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1644 - accuracy: 0.9350 - precision: 0.9299 - recall: 0.9409 - auc: 0.9831 - val_loss: 0.4247 - val_accuracy: 0.8388 - val_precision: 0.7759 - val_recall: 0.9526 - val_auc: 0.9204\n",
            "Epoch 1127/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1660 - accuracy: 0.9343 - precision: 0.9297 - recall: 0.9396 - auc: 0.9828 - val_loss: 0.4131 - val_accuracy: 0.8458 - val_precision: 0.7810 - val_recall: 0.9608 - val_auc: 0.9288\n",
            "Epoch 1128/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1656 - accuracy: 0.9341 - precision: 0.9296 - recall: 0.9392 - auc: 0.9829 - val_loss: 0.4364 - val_accuracy: 0.8379 - val_precision: 0.7689 - val_recall: 0.9660 - val_auc: 0.9261\n",
            "Epoch 1129/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1599 - accuracy: 0.9370 - precision: 0.9322 - recall: 0.9425 - auc: 0.9840 - val_loss: 0.4311 - val_accuracy: 0.8415 - val_precision: 0.7735 - val_recall: 0.9658 - val_auc: 0.9286\n",
            "Epoch 1130/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1541 - accuracy: 0.9396 - precision: 0.9367 - recall: 0.9430 - auc: 0.9851 - val_loss: 0.4912 - val_accuracy: 0.8195 - val_precision: 0.7405 - val_recall: 0.9837 - val_auc: 0.9359\n",
            "Epoch 1131/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1322 - accuracy: 0.9488 - precision: 0.9495 - recall: 0.9480 - auc: 0.9890 - val_loss: 0.5608 - val_accuracy: 0.8032 - val_precision: 0.7221 - val_recall: 0.9855 - val_auc: 0.9309\n",
            "Epoch 1132/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1400 - accuracy: 0.9459 - precision: 0.9442 - recall: 0.9479 - auc: 0.9876 - val_loss: 0.6884 - val_accuracy: 0.7591 - val_precision: 0.6762 - val_recall: 0.9941 - val_auc: 0.9282\n",
            "Epoch 1133/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1568 - accuracy: 0.9388 - precision: 0.9347 - recall: 0.9435 - auc: 0.9846 - val_loss: 0.6007 - val_accuracy: 0.7882 - val_precision: 0.7056 - val_recall: 0.9892 - val_auc: 0.9276\n",
            "Epoch 1134/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1388 - accuracy: 0.9463 - precision: 0.9440 - recall: 0.9489 - auc: 0.9879 - val_loss: 0.4883 - val_accuracy: 0.8244 - val_precision: 0.7534 - val_recall: 0.9644 - val_auc: 0.9245\n",
            "Epoch 1135/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1287 - accuracy: 0.9504 - precision: 0.9484 - recall: 0.9526 - auc: 0.9894 - val_loss: 0.5635 - val_accuracy: 0.8085 - val_precision: 0.7284 - val_recall: 0.9839 - val_auc: 0.9305\n",
            "Epoch 1136/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1340 - accuracy: 0.9486 - precision: 0.9484 - recall: 0.9487 - auc: 0.9886 - val_loss: 0.6308 - val_accuracy: 0.7886 - val_precision: 0.7057 - val_recall: 0.9900 - val_auc: 0.9303\n",
            "Epoch 1137/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1305 - accuracy: 0.9499 - precision: 0.9480 - recall: 0.9521 - auc: 0.9891 - val_loss: 0.6243 - val_accuracy: 0.7866 - val_precision: 0.7033 - val_recall: 0.9912 - val_auc: 0.9407\n",
            "Epoch 1138/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1225 - accuracy: 0.9529 - precision: 0.9535 - recall: 0.9523 - auc: 0.9904 - val_loss: 0.6509 - val_accuracy: 0.7866 - val_precision: 0.7037 - val_recall: 0.9900 - val_auc: 0.9387\n",
            "Epoch 1139/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1196 - accuracy: 0.9544 - precision: 0.9561 - recall: 0.9526 - auc: 0.9908 - val_loss: 0.7407 - val_accuracy: 0.7581 - val_precision: 0.6752 - val_recall: 0.9943 - val_auc: 0.9361\n",
            "Epoch 1140/2000\n",
            "10/10 [==============================] - 4s 423ms/step - loss: 0.1371 - accuracy: 0.9473 - precision: 0.9460 - recall: 0.9487 - auc: 0.9881 - val_loss: 0.5319 - val_accuracy: 0.8155 - val_precision: 0.7376 - val_recall: 0.9793 - val_auc: 0.9319\n",
            "Epoch 1141/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1252 - accuracy: 0.9517 - precision: 0.9514 - recall: 0.9520 - auc: 0.9900 - val_loss: 0.6300 - val_accuracy: 0.7886 - val_precision: 0.7058 - val_recall: 0.9896 - val_auc: 0.9357\n",
            "Epoch 1142/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1279 - accuracy: 0.9508 - precision: 0.9505 - recall: 0.9510 - auc: 0.9896 - val_loss: 0.6652 - val_accuracy: 0.7736 - val_precision: 0.6902 - val_recall: 0.9926 - val_auc: 0.9376\n",
            "Epoch 1143/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1260 - accuracy: 0.9512 - precision: 0.9508 - recall: 0.9517 - auc: 0.9899 - val_loss: 0.7673 - val_accuracy: 0.7524 - val_precision: 0.6700 - val_recall: 0.9944 - val_auc: 0.9321\n",
            "Epoch 1144/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1392 - accuracy: 0.9466 - precision: 0.9433 - recall: 0.9503 - auc: 0.9877 - val_loss: 0.7428 - val_accuracy: 0.7468 - val_precision: 0.6649 - val_recall: 0.9948 - val_auc: 0.9316\n",
            "Epoch 1145/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1217 - accuracy: 0.9541 - precision: 0.9547 - recall: 0.9534 - auc: 0.9905 - val_loss: 0.7010 - val_accuracy: 0.7747 - val_precision: 0.6917 - val_recall: 0.9909 - val_auc: 0.9305\n",
            "Epoch 1146/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.1198 - accuracy: 0.9543 - precision: 0.9544 - recall: 0.9542 - auc: 0.9908 - val_loss: 0.8281 - val_accuracy: 0.7447 - val_precision: 0.6630 - val_recall: 0.9951 - val_auc: 0.9333\n",
            "Epoch 1147/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1256 - accuracy: 0.9516 - precision: 0.9512 - recall: 0.9519 - auc: 0.9899 - val_loss: 0.7114 - val_accuracy: 0.7770 - val_precision: 0.6939 - val_recall: 0.9910 - val_auc: 0.9302\n",
            "Epoch 1148/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1167 - accuracy: 0.9553 - precision: 0.9549 - recall: 0.9558 - auc: 0.9912 - val_loss: 0.8048 - val_accuracy: 0.7505 - val_precision: 0.6683 - val_recall: 0.9945 - val_auc: 0.9304\n",
            "Epoch 1149/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1196 - accuracy: 0.9545 - precision: 0.9555 - recall: 0.9534 - auc: 0.9907 - val_loss: 0.9738 - val_accuracy: 0.7054 - val_precision: 0.6297 - val_recall: 0.9970 - val_auc: 0.9209\n",
            "Epoch 1150/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1209 - accuracy: 0.9534 - precision: 0.9525 - recall: 0.9544 - auc: 0.9907 - val_loss: 0.7650 - val_accuracy: 0.7568 - val_precision: 0.6740 - val_recall: 0.9945 - val_auc: 0.9307\n",
            "Epoch 1151/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1846 - accuracy: 0.9281 - precision: 0.9219 - recall: 0.9356 - auc: 0.9789 - val_loss: 0.3192 - val_accuracy: 0.8672 - val_precision: 0.8601 - val_recall: 0.8771 - val_auc: 0.9390\n",
            "Epoch 1152/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1646 - accuracy: 0.9349 - precision: 0.9323 - recall: 0.9379 - auc: 0.9831 - val_loss: 0.4130 - val_accuracy: 0.8381 - val_precision: 0.7641 - val_recall: 0.9781 - val_auc: 0.9454\n",
            "Epoch 1153/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1450 - accuracy: 0.9433 - precision: 0.9393 - recall: 0.9479 - auc: 0.9868 - val_loss: 0.5627 - val_accuracy: 0.8102 - val_precision: 0.7306 - val_recall: 0.9828 - val_auc: 0.9295\n",
            "Epoch 1154/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1513 - accuracy: 0.9407 - precision: 0.9387 - recall: 0.9430 - auc: 0.9856 - val_loss: 0.6272 - val_accuracy: 0.7892 - val_precision: 0.7064 - val_recall: 0.9895 - val_auc: 0.9262\n",
            "Epoch 1155/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1268 - accuracy: 0.9514 - precision: 0.9507 - recall: 0.9522 - auc: 0.9898 - val_loss: 0.6600 - val_accuracy: 0.7857 - val_precision: 0.7030 - val_recall: 0.9889 - val_auc: 0.9310\n",
            "Epoch 1156/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1193 - accuracy: 0.9544 - precision: 0.9534 - recall: 0.9555 - auc: 0.9909 - val_loss: 0.8029 - val_accuracy: 0.7546 - val_precision: 0.6720 - val_recall: 0.9943 - val_auc: 0.9318\n",
            "Epoch 1157/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1321 - accuracy: 0.9493 - precision: 0.9498 - recall: 0.9488 - auc: 0.9889 - val_loss: 0.7561 - val_accuracy: 0.7640 - val_precision: 0.6811 - val_recall: 0.9924 - val_auc: 0.9251\n",
            "Epoch 1158/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1194 - accuracy: 0.9544 - precision: 0.9546 - recall: 0.9542 - auc: 0.9908 - val_loss: 0.7191 - val_accuracy: 0.7739 - val_precision: 0.6908 - val_recall: 0.9913 - val_auc: 0.9282\n",
            "Epoch 1159/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1260 - accuracy: 0.9516 - precision: 0.9504 - recall: 0.9530 - auc: 0.9899 - val_loss: 0.7847 - val_accuracy: 0.7572 - val_precision: 0.6747 - val_recall: 0.9932 - val_auc: 0.9312\n",
            "Epoch 1160/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1145 - accuracy: 0.9562 - precision: 0.9561 - recall: 0.9563 - auc: 0.9915 - val_loss: 0.7775 - val_accuracy: 0.7562 - val_precision: 0.6736 - val_recall: 0.9936 - val_auc: 0.9266\n",
            "Epoch 1161/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1214 - accuracy: 0.9532 - precision: 0.9527 - recall: 0.9537 - auc: 0.9906 - val_loss: 0.7576 - val_accuracy: 0.7632 - val_precision: 0.6803 - val_recall: 0.9927 - val_auc: 0.9274\n",
            "Epoch 1162/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1295 - accuracy: 0.9507 - precision: 0.9491 - recall: 0.9524 - auc: 0.9892 - val_loss: 0.7160 - val_accuracy: 0.7697 - val_precision: 0.6864 - val_recall: 0.9926 - val_auc: 0.9306\n",
            "Epoch 1163/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1205 - accuracy: 0.9538 - precision: 0.9527 - recall: 0.9550 - auc: 0.9907 - val_loss: 0.7173 - val_accuracy: 0.7704 - val_precision: 0.6872 - val_recall: 0.9924 - val_auc: 0.9276\n",
            "Epoch 1164/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1127 - accuracy: 0.9568 - precision: 0.9572 - recall: 0.9564 - auc: 0.9918 - val_loss: 0.7953 - val_accuracy: 0.7560 - val_precision: 0.6733 - val_recall: 0.9943 - val_auc: 0.9289\n",
            "Epoch 1165/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1159 - accuracy: 0.9554 - precision: 0.9549 - recall: 0.9560 - auc: 0.9913 - val_loss: 0.8371 - val_accuracy: 0.7455 - val_precision: 0.6638 - val_recall: 0.9947 - val_auc: 0.9289\n",
            "Epoch 1166/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1455 - accuracy: 0.9440 - precision: 0.9424 - recall: 0.9458 - auc: 0.9866 - val_loss: 0.5826 - val_accuracy: 0.7938 - val_precision: 0.7107 - val_recall: 0.9910 - val_auc: 0.9481\n",
            "Epoch 1167/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1498 - accuracy: 0.9423 - precision: 0.9383 - recall: 0.9469 - auc: 0.9859 - val_loss: 0.3955 - val_accuracy: 0.8045 - val_precision: 0.8900 - val_recall: 0.6948 - val_auc: 0.9212\n",
            "Epoch 1168/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1644 - accuracy: 0.9354 - precision: 0.9349 - recall: 0.9361 - auc: 0.9833 - val_loss: 0.4304 - val_accuracy: 0.8393 - val_precision: 0.7645 - val_recall: 0.9803 - val_auc: 0.9492\n",
            "Epoch 1169/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1261 - accuracy: 0.9518 - precision: 0.9511 - recall: 0.9526 - auc: 0.9899 - val_loss: 0.5868 - val_accuracy: 0.8021 - val_precision: 0.7199 - val_recall: 0.9887 - val_auc: 0.9427\n",
            "Epoch 1170/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1257 - accuracy: 0.9517 - precision: 0.9523 - recall: 0.9509 - auc: 0.9899 - val_loss: 0.7176 - val_accuracy: 0.7681 - val_precision: 0.6847 - val_recall: 0.9936 - val_auc: 0.9411\n",
            "Epoch 1171/2000\n",
            "10/10 [==============================] - 4s 385ms/step - loss: 0.1678 - accuracy: 0.9352 - precision: 0.9289 - recall: 0.9425 - auc: 0.9824 - val_loss: 0.5047 - val_accuracy: 0.8140 - val_precision: 0.7332 - val_recall: 0.9869 - val_auc: 0.9457\n",
            "Epoch 1172/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1459 - accuracy: 0.9436 - precision: 0.9405 - recall: 0.9472 - auc: 0.9866 - val_loss: 0.5836 - val_accuracy: 0.8040 - val_precision: 0.7229 - val_recall: 0.9858 - val_auc: 0.9301\n",
            "Epoch 1173/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1508 - accuracy: 0.9414 - precision: 0.9364 - recall: 0.9472 - auc: 0.9856 - val_loss: 0.3636 - val_accuracy: 0.8480 - val_precision: 0.7768 - val_recall: 0.9764 - val_auc: 0.9527\n",
            "Epoch 1174/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1363 - accuracy: 0.9474 - precision: 0.9458 - recall: 0.9491 - auc: 0.9883 - val_loss: 0.6112 - val_accuracy: 0.7946 - val_precision: 0.7119 - val_recall: 0.9895 - val_auc: 0.9335\n",
            "Epoch 1175/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.1182 - accuracy: 0.9542 - precision: 0.9537 - recall: 0.9548 - auc: 0.9910 - val_loss: 0.7007 - val_accuracy: 0.7725 - val_precision: 0.6890 - val_recall: 0.9932 - val_auc: 0.9317\n",
            "Epoch 1176/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1209 - accuracy: 0.9536 - precision: 0.9528 - recall: 0.9546 - auc: 0.9906 - val_loss: 0.7595 - val_accuracy: 0.7546 - val_precision: 0.6721 - val_recall: 0.9942 - val_auc: 0.9260\n",
            "Epoch 1177/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1190 - accuracy: 0.9544 - precision: 0.9540 - recall: 0.9547 - auc: 0.9909 - val_loss: 0.2962 - val_accuracy: 0.8810 - val_precision: 0.8377 - val_recall: 0.9450 - val_auc: 0.9541\n",
            "Epoch 1178/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1277 - accuracy: 0.9512 - precision: 0.9511 - recall: 0.9512 - auc: 0.9897 - val_loss: 0.6995 - val_accuracy: 0.7726 - val_precision: 0.6893 - val_recall: 0.9923 - val_auc: 0.9296\n",
            "Epoch 1179/2000\n",
            "10/10 [==============================] - 5s 489ms/step - loss: 0.1226 - accuracy: 0.9529 - precision: 0.9524 - recall: 0.9534 - auc: 0.9904 - val_loss: 0.7704 - val_accuracy: 0.7518 - val_precision: 0.6694 - val_recall: 0.9945 - val_auc: 0.9288\n",
            "Epoch 1180/2000\n",
            "10/10 [==============================] - 4s 419ms/step - loss: 0.1230 - accuracy: 0.9531 - precision: 0.9512 - recall: 0.9552 - auc: 0.9903 - val_loss: 0.8330 - val_accuracy: 0.7319 - val_precision: 0.6517 - val_recall: 0.9958 - val_auc: 0.9232\n",
            "Epoch 1181/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1159 - accuracy: 0.9558 - precision: 0.9560 - recall: 0.9555 - auc: 0.9914 - val_loss: 0.7308 - val_accuracy: 0.7607 - val_precision: 0.6777 - val_recall: 0.9940 - val_auc: 0.9341\n",
            "Epoch 1182/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1149 - accuracy: 0.9559 - precision: 0.9557 - recall: 0.9562 - auc: 0.9915 - val_loss: 0.7345 - val_accuracy: 0.7677 - val_precision: 0.6843 - val_recall: 0.9937 - val_auc: 0.9344\n",
            "Epoch 1183/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1143 - accuracy: 0.9561 - precision: 0.9568 - recall: 0.9552 - auc: 0.9916 - val_loss: 0.8597 - val_accuracy: 0.7310 - val_precision: 0.6509 - val_recall: 0.9959 - val_auc: 0.9284\n",
            "Epoch 1184/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1108 - accuracy: 0.9571 - precision: 0.9573 - recall: 0.9570 - auc: 0.9921 - val_loss: 0.7480 - val_accuracy: 0.7609 - val_precision: 0.6778 - val_recall: 0.9945 - val_auc: 0.9374\n",
            "Epoch 1185/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1379 - accuracy: 0.9469 - precision: 0.9441 - recall: 0.9501 - auc: 0.9879 - val_loss: 0.6321 - val_accuracy: 0.7890 - val_precision: 0.7063 - val_recall: 0.9892 - val_auc: 0.9291\n",
            "Epoch 1186/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1251 - accuracy: 0.9522 - precision: 0.9521 - recall: 0.9523 - auc: 0.9900 - val_loss: 0.6770 - val_accuracy: 0.7803 - val_precision: 0.6969 - val_recall: 0.9917 - val_auc: 0.9311\n",
            "Epoch 1187/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1135 - accuracy: 0.9563 - precision: 0.9572 - recall: 0.9553 - auc: 0.9917 - val_loss: 0.8318 - val_accuracy: 0.7483 - val_precision: 0.6663 - val_recall: 0.9944 - val_auc: 0.9284\n",
            "Epoch 1188/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1312 - accuracy: 0.9492 - precision: 0.9491 - recall: 0.9493 - auc: 0.9890 - val_loss: 0.3268 - val_accuracy: 0.8530 - val_precision: 0.8930 - val_recall: 0.8019 - val_auc: 0.9388\n",
            "Epoch 1189/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1276 - accuracy: 0.9511 - precision: 0.9506 - recall: 0.9517 - auc: 0.9897 - val_loss: 0.7071 - val_accuracy: 0.7772 - val_precision: 0.6944 - val_recall: 0.9898 - val_auc: 0.9205\n",
            "Epoch 1190/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1164 - accuracy: 0.9550 - precision: 0.9553 - recall: 0.9548 - auc: 0.9913 - val_loss: 0.7041 - val_accuracy: 0.7798 - val_precision: 0.6966 - val_recall: 0.9911 - val_auc: 0.9307\n",
            "Epoch 1191/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1240 - accuracy: 0.9525 - precision: 0.9517 - recall: 0.9533 - auc: 0.9901 - val_loss: 0.4334 - val_accuracy: 0.8016 - val_precision: 0.9096 - val_recall: 0.6696 - val_auc: 0.9278\n",
            "Epoch 1192/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1275 - accuracy: 0.9508 - precision: 0.9495 - recall: 0.9523 - auc: 0.9897 - val_loss: 0.7288 - val_accuracy: 0.7717 - val_precision: 0.6886 - val_recall: 0.9918 - val_auc: 0.9273\n",
            "Epoch 1193/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1124 - accuracy: 0.9568 - precision: 0.9567 - recall: 0.9570 - auc: 0.9919 - val_loss: 0.4595 - val_accuracy: 0.8374 - val_precision: 0.7616 - val_recall: 0.9820 - val_auc: 0.9546\n",
            "Epoch 1194/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1241 - accuracy: 0.9523 - precision: 0.9504 - recall: 0.9544 - auc: 0.9902 - val_loss: 0.5650 - val_accuracy: 0.8114 - val_precision: 0.7302 - val_recall: 0.9874 - val_auc: 0.9458\n",
            "Epoch 1195/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1220 - accuracy: 0.9533 - precision: 0.9532 - recall: 0.9533 - auc: 0.9904 - val_loss: 0.7098 - val_accuracy: 0.7718 - val_precision: 0.6896 - val_recall: 0.9885 - val_auc: 0.9189\n",
            "Epoch 1196/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1095 - accuracy: 0.9580 - precision: 0.9584 - recall: 0.9576 - auc: 0.9922 - val_loss: 0.8193 - val_accuracy: 0.7480 - val_precision: 0.6660 - val_recall: 0.9943 - val_auc: 0.9257\n",
            "Epoch 1197/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.1238 - accuracy: 0.9527 - precision: 0.9511 - recall: 0.9546 - auc: 0.9902 - val_loss: 0.7355 - val_accuracy: 0.7667 - val_precision: 0.6835 - val_recall: 0.9930 - val_auc: 0.9301\n",
            "Epoch 1198/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1205 - accuracy: 0.9540 - precision: 0.9537 - recall: 0.9544 - auc: 0.9906 - val_loss: 0.3018 - val_accuracy: 0.8693 - val_precision: 0.8924 - val_recall: 0.8398 - val_auc: 0.9470\n",
            "Epoch 1199/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1241 - accuracy: 0.9522 - precision: 0.9523 - recall: 0.9522 - auc: 0.9904 - val_loss: 0.6939 - val_accuracy: 0.7787 - val_precision: 0.6958 - val_recall: 0.9900 - val_auc: 0.9262\n",
            "Epoch 1200/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1343 - accuracy: 0.9493 - precision: 0.9476 - recall: 0.9513 - auc: 0.9884 - val_loss: 0.6795 - val_accuracy: 0.7701 - val_precision: 0.6873 - val_recall: 0.9909 - val_auc: 0.9229\n",
            "Epoch 1201/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1158 - accuracy: 0.9554 - precision: 0.9561 - recall: 0.9547 - auc: 0.9914 - val_loss: 0.7910 - val_accuracy: 0.7458 - val_precision: 0.6641 - val_recall: 0.9942 - val_auc: 0.9260\n",
            "Epoch 1202/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1335 - accuracy: 0.9490 - precision: 0.9480 - recall: 0.9501 - auc: 0.9886 - val_loss: 0.6361 - val_accuracy: 0.7875 - val_precision: 0.7042 - val_recall: 0.9913 - val_auc: 0.9359\n",
            "Epoch 1203/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1131 - accuracy: 0.9566 - precision: 0.9585 - recall: 0.9545 - auc: 0.9918 - val_loss: 0.3737 - val_accuracy: 0.8363 - val_precision: 0.9061 - val_recall: 0.7502 - val_auc: 0.9374\n",
            "Epoch 1204/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1286 - accuracy: 0.9510 - precision: 0.9476 - recall: 0.9548 - auc: 0.9894 - val_loss: 0.7104 - val_accuracy: 0.7696 - val_precision: 0.6864 - val_recall: 0.9928 - val_auc: 0.9332\n",
            "Epoch 1205/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1173 - accuracy: 0.9548 - precision: 0.9539 - recall: 0.9558 - auc: 0.9911 - val_loss: 0.7778 - val_accuracy: 0.7521 - val_precision: 0.6698 - val_recall: 0.9943 - val_auc: 0.9328\n",
            "Epoch 1206/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1081 - accuracy: 0.9586 - precision: 0.9598 - recall: 0.9574 - auc: 0.9925 - val_loss: 0.8474 - val_accuracy: 0.7412 - val_precision: 0.6600 - val_recall: 0.9949 - val_auc: 0.9261\n",
            "Epoch 1207/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1684 - accuracy: 0.9345 - precision: 0.9311 - recall: 0.9385 - auc: 0.9823 - val_loss: 0.4404 - val_accuracy: 0.7831 - val_precision: 0.8798 - val_recall: 0.6557 - val_auc: 0.9082\n",
            "Epoch 1208/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1456 - accuracy: 0.9439 - precision: 0.9414 - recall: 0.9467 - auc: 0.9866 - val_loss: 0.6719 - val_accuracy: 0.7755 - val_precision: 0.6927 - val_recall: 0.9900 - val_auc: 0.9190\n",
            "Epoch 1209/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1295 - accuracy: 0.9500 - precision: 0.9496 - recall: 0.9505 - auc: 0.9894 - val_loss: 0.7334 - val_accuracy: 0.7576 - val_precision: 0.6748 - val_recall: 0.9941 - val_auc: 0.9259\n",
            "Epoch 1210/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1098 - accuracy: 0.9582 - precision: 0.9586 - recall: 0.9578 - auc: 0.9922 - val_loss: 0.6003 - val_accuracy: 0.7939 - val_precision: 0.7106 - val_recall: 0.9917 - val_auc: 0.9475\n",
            "Epoch 1211/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1188 - accuracy: 0.9545 - precision: 0.9542 - recall: 0.9548 - auc: 0.9909 - val_loss: 0.8140 - val_accuracy: 0.7441 - val_precision: 0.6627 - val_recall: 0.9937 - val_auc: 0.9220\n",
            "Epoch 1212/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1105 - accuracy: 0.9574 - precision: 0.9577 - recall: 0.9571 - auc: 0.9921 - val_loss: 0.8656 - val_accuracy: 0.7322 - val_precision: 0.6521 - val_recall: 0.9950 - val_auc: 0.9218\n",
            "Epoch 1213/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1136 - accuracy: 0.9563 - precision: 0.9548 - recall: 0.9580 - auc: 0.9917 - val_loss: 0.7781 - val_accuracy: 0.7538 - val_precision: 0.6713 - val_recall: 0.9941 - val_auc: 0.9323\n",
            "Epoch 1214/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1194 - accuracy: 0.9542 - precision: 0.9541 - recall: 0.9543 - auc: 0.9908 - val_loss: 0.2523 - val_accuracy: 0.9018 - val_precision: 0.8682 - val_recall: 0.9473 - val_auc: 0.9674\n",
            "Epoch 1215/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1151 - accuracy: 0.9564 - precision: 0.9570 - recall: 0.9557 - auc: 0.9915 - val_loss: 0.7563 - val_accuracy: 0.7571 - val_precision: 0.6744 - val_recall: 0.9940 - val_auc: 0.9319\n",
            "Epoch 1216/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1195 - accuracy: 0.9543 - precision: 0.9532 - recall: 0.9555 - auc: 0.9907 - val_loss: 0.4449 - val_accuracy: 0.8305 - val_precision: 0.7502 - val_recall: 0.9908 - val_auc: 0.9685\n",
            "Epoch 1217/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1178 - accuracy: 0.9552 - precision: 0.9551 - recall: 0.9554 - auc: 0.9912 - val_loss: 0.3847 - val_accuracy: 0.8507 - val_precision: 0.7753 - val_recall: 0.9873 - val_auc: 0.9717\n",
            "Epoch 1218/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1157 - accuracy: 0.9558 - precision: 0.9563 - recall: 0.9552 - auc: 0.9914 - val_loss: 0.7611 - val_accuracy: 0.7532 - val_precision: 0.6709 - val_recall: 0.9938 - val_auc: 0.9277\n",
            "Epoch 1219/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1091 - accuracy: 0.9583 - precision: 0.9573 - recall: 0.9593 - auc: 0.9922 - val_loss: 0.6912 - val_accuracy: 0.7715 - val_precision: 0.6876 - val_recall: 0.9950 - val_auc: 0.9520\n",
            "Epoch 1220/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1333 - accuracy: 0.9477 - precision: 0.9460 - recall: 0.9496 - auc: 0.9887 - val_loss: 0.3902 - val_accuracy: 0.8492 - val_precision: 0.7733 - val_recall: 0.9878 - val_auc: 0.9710\n",
            "Epoch 1221/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1109 - accuracy: 0.9578 - precision: 0.9580 - recall: 0.9574 - auc: 0.9921 - val_loss: 0.7867 - val_accuracy: 0.7469 - val_precision: 0.6652 - val_recall: 0.9938 - val_auc: 0.9335\n",
            "Epoch 1222/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1170 - accuracy: 0.9552 - precision: 0.9553 - recall: 0.9551 - auc: 0.9912 - val_loss: 0.7017 - val_accuracy: 0.7685 - val_precision: 0.6850 - val_recall: 0.9938 - val_auc: 0.9438\n",
            "Epoch 1223/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1343 - accuracy: 0.9492 - precision: 0.9467 - recall: 0.9519 - auc: 0.9885 - val_loss: 0.3058 - val_accuracy: 0.8682 - val_precision: 0.8698 - val_recall: 0.8659 - val_auc: 0.9427\n",
            "Epoch 1224/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1285 - accuracy: 0.9515 - precision: 0.9522 - recall: 0.9507 - auc: 0.9896 - val_loss: 0.2686 - val_accuracy: 0.8969 - val_precision: 0.8448 - val_recall: 0.9722 - val_auc: 0.9759\n",
            "Epoch 1225/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1179 - accuracy: 0.9547 - precision: 0.9560 - recall: 0.9533 - auc: 0.9912 - val_loss: 0.8473 - val_accuracy: 0.7358 - val_precision: 0.6552 - val_recall: 0.9951 - val_auc: 0.9238\n",
            "Epoch 1226/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1156 - accuracy: 0.9555 - precision: 0.9546 - recall: 0.9566 - auc: 0.9914 - val_loss: 0.9374 - val_accuracy: 0.7164 - val_precision: 0.6387 - val_recall: 0.9961 - val_auc: 0.9200\n",
            "Epoch 1227/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1073 - accuracy: 0.9591 - precision: 0.9591 - recall: 0.9591 - auc: 0.9925 - val_loss: 0.3780 - val_accuracy: 0.8578 - val_precision: 0.7831 - val_recall: 0.9896 - val_auc: 0.9800\n",
            "Epoch 1228/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1225 - accuracy: 0.9527 - precision: 0.9517 - recall: 0.9538 - auc: 0.9903 - val_loss: 0.9020 - val_accuracy: 0.7161 - val_precision: 0.6383 - val_recall: 0.9966 - val_auc: 0.9245\n",
            "Epoch 1229/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1059 - accuracy: 0.9599 - precision: 0.9613 - recall: 0.9584 - auc: 0.9927 - val_loss: 0.5047 - val_accuracy: 0.8170 - val_precision: 0.7345 - val_recall: 0.9929 - val_auc: 0.9712\n",
            "Epoch 1230/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1761 - accuracy: 0.9315 - precision: 0.9234 - recall: 0.9412 - auc: 0.9807 - val_loss: 0.7323 - val_accuracy: 0.6164 - val_precision: 0.8626 - val_recall: 0.2766 - val_auc: 0.8212\n",
            "Epoch 1231/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1765 - accuracy: 0.9301 - precision: 0.9253 - recall: 0.9356 - auc: 0.9806 - val_loss: 0.5398 - val_accuracy: 0.7153 - val_precision: 0.8772 - val_recall: 0.5006 - val_auc: 0.8831\n",
            "Epoch 1232/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1872 - accuracy: 0.9259 - precision: 0.9225 - recall: 0.9298 - auc: 0.9783 - val_loss: 0.4074 - val_accuracy: 0.8015 - val_precision: 0.8968 - val_recall: 0.6811 - val_auc: 0.9237\n",
            "Epoch 1233/2000\n",
            "10/10 [==============================] - 4s 420ms/step - loss: 0.1681 - accuracy: 0.9337 - precision: 0.9275 - recall: 0.9409 - auc: 0.9823 - val_loss: 0.3174 - val_accuracy: 0.8601 - val_precision: 0.8759 - val_recall: 0.8390 - val_auc: 0.9384\n",
            "Epoch 1234/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1585 - accuracy: 0.9380 - precision: 0.9349 - recall: 0.9416 - auc: 0.9843 - val_loss: 0.4585 - val_accuracy: 0.8276 - val_precision: 0.7518 - val_recall: 0.9781 - val_auc: 0.9326\n",
            "Epoch 1235/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1355 - accuracy: 0.9478 - precision: 0.9491 - recall: 0.9463 - auc: 0.9884 - val_loss: 0.5507 - val_accuracy: 0.8070 - val_precision: 0.7269 - val_recall: 0.9832 - val_auc: 0.9249\n",
            "Epoch 1236/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1132 - accuracy: 0.9569 - precision: 0.9573 - recall: 0.9566 - auc: 0.9917 - val_loss: 0.7886 - val_accuracy: 0.7456 - val_precision: 0.6641 - val_recall: 0.9937 - val_auc: 0.9164\n",
            "Epoch 1237/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1091 - accuracy: 0.9582 - precision: 0.9582 - recall: 0.9582 - auc: 0.9923 - val_loss: 0.9060 - val_accuracy: 0.7219 - val_precision: 0.6435 - val_recall: 0.9950 - val_auc: 0.9066\n",
            "Epoch 1238/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1330 - accuracy: 0.9490 - precision: 0.9476 - recall: 0.9505 - auc: 0.9887 - val_loss: 0.9251 - val_accuracy: 0.7002 - val_precision: 0.6255 - val_recall: 0.9970 - val_auc: 0.9120\n",
            "Epoch 1239/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1222 - accuracy: 0.9537 - precision: 0.9533 - recall: 0.9541 - auc: 0.9906 - val_loss: 0.8918 - val_accuracy: 0.7246 - val_precision: 0.6456 - val_recall: 0.9954 - val_auc: 0.9189\n",
            "Epoch 1240/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1103 - accuracy: 0.9580 - precision: 0.9595 - recall: 0.9564 - auc: 0.9921 - val_loss: 0.8509 - val_accuracy: 0.7361 - val_precision: 0.6557 - val_recall: 0.9940 - val_auc: 0.9174\n",
            "Epoch 1241/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1159 - accuracy: 0.9554 - precision: 0.9546 - recall: 0.9562 - auc: 0.9913 - val_loss: 0.9017 - val_accuracy: 0.7207 - val_precision: 0.6423 - val_recall: 0.9959 - val_auc: 0.9219\n",
            "Epoch 1242/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1057 - accuracy: 0.9594 - precision: 0.9608 - recall: 0.9579 - auc: 0.9928 - val_loss: 0.9300 - val_accuracy: 0.7219 - val_precision: 0.6433 - val_recall: 0.9957 - val_auc: 0.9212\n",
            "Epoch 1243/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1335 - accuracy: 0.9487 - precision: 0.9456 - recall: 0.9523 - auc: 0.9886 - val_loss: 0.7471 - val_accuracy: 0.7460 - val_precision: 0.6643 - val_recall: 0.9942 - val_auc: 0.9232\n",
            "Epoch 1244/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1184 - accuracy: 0.9546 - precision: 0.9554 - recall: 0.9537 - auc: 0.9911 - val_loss: 0.8340 - val_accuracy: 0.7369 - val_precision: 0.6562 - val_recall: 0.9949 - val_auc: 0.9255\n",
            "Epoch 1245/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1176 - accuracy: 0.9549 - precision: 0.9537 - recall: 0.9563 - auc: 0.9911 - val_loss: 0.8362 - val_accuracy: 0.7345 - val_precision: 0.6542 - val_recall: 0.9948 - val_auc: 0.9223\n",
            "Epoch 1246/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1095 - accuracy: 0.9580 - precision: 0.9586 - recall: 0.9574 - auc: 0.9923 - val_loss: 0.8716 - val_accuracy: 0.7325 - val_precision: 0.6526 - val_recall: 0.9938 - val_auc: 0.9199\n",
            "Epoch 1247/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1104 - accuracy: 0.9577 - precision: 0.9592 - recall: 0.9562 - auc: 0.9921 - val_loss: 1.0290 - val_accuracy: 0.7031 - val_precision: 0.6285 - val_recall: 0.9928 - val_auc: 0.8969\n",
            "Epoch 1248/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1929 - accuracy: 0.9258 - precision: 0.9181 - recall: 0.9351 - auc: 0.9771 - val_loss: 0.3504 - val_accuracy: 0.8569 - val_precision: 0.7895 - val_recall: 0.9730 - val_auc: 0.9537\n",
            "Epoch 1249/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1624 - accuracy: 0.9361 - precision: 0.9309 - recall: 0.9422 - auc: 0.9835 - val_loss: 0.5214 - val_accuracy: 0.8213 - val_precision: 0.7428 - val_recall: 0.9826 - val_auc: 0.9351\n",
            "Epoch 1250/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1467 - accuracy: 0.9423 - precision: 0.9388 - recall: 0.9464 - auc: 0.9864 - val_loss: 0.6316 - val_accuracy: 0.7951 - val_precision: 0.7126 - val_recall: 0.9886 - val_auc: 0.9308\n",
            "Epoch 1251/2000\n",
            "10/10 [==============================] - 5s 484ms/step - loss: 0.1378 - accuracy: 0.9469 - precision: 0.9453 - recall: 0.9487 - auc: 0.9879 - val_loss: 0.6029 - val_accuracy: 0.7877 - val_precision: 0.7047 - val_recall: 0.9901 - val_auc: 0.9365\n",
            "Epoch 1252/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1186 - accuracy: 0.9547 - precision: 0.9561 - recall: 0.9532 - auc: 0.9910 - val_loss: 0.7159 - val_accuracy: 0.7627 - val_precision: 0.6799 - val_recall: 0.9928 - val_auc: 0.9305\n",
            "Epoch 1253/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1230 - accuracy: 0.9528 - precision: 0.9520 - recall: 0.9537 - auc: 0.9903 - val_loss: 0.7671 - val_accuracy: 0.7472 - val_precision: 0.6653 - val_recall: 0.9947 - val_auc: 0.9294\n",
            "Epoch 1254/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1214 - accuracy: 0.9536 - precision: 0.9498 - recall: 0.9579 - auc: 0.9905 - val_loss: 0.7452 - val_accuracy: 0.7631 - val_precision: 0.6801 - val_recall: 0.9932 - val_auc: 0.9303\n",
            "Epoch 1255/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1177 - accuracy: 0.9551 - precision: 0.9577 - recall: 0.9523 - auc: 0.9910 - val_loss: 0.8147 - val_accuracy: 0.7399 - val_precision: 0.6588 - val_recall: 0.9950 - val_auc: 0.9286\n",
            "Epoch 1256/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1085 - accuracy: 0.9581 - precision: 0.9583 - recall: 0.9579 - auc: 0.9925 - val_loss: 0.8266 - val_accuracy: 0.7423 - val_precision: 0.6610 - val_recall: 0.9945 - val_auc: 0.9292\n",
            "Epoch 1257/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1148 - accuracy: 0.9561 - precision: 0.9547 - recall: 0.9576 - auc: 0.9915 - val_loss: 0.8391 - val_accuracy: 0.7367 - val_precision: 0.6559 - val_recall: 0.9952 - val_auc: 0.9286\n",
            "Epoch 1258/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1086 - accuracy: 0.9584 - precision: 0.9591 - recall: 0.9576 - auc: 0.9924 - val_loss: 0.9174 - val_accuracy: 0.7263 - val_precision: 0.6469 - val_recall: 0.9959 - val_auc: 0.9256\n",
            "Epoch 1259/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1139 - accuracy: 0.9566 - precision: 0.9568 - recall: 0.9564 - auc: 0.9916 - val_loss: 0.8590 - val_accuracy: 0.7361 - val_precision: 0.6554 - val_recall: 0.9953 - val_auc: 0.9266\n",
            "Epoch 1260/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1118 - accuracy: 0.9570 - precision: 0.9583 - recall: 0.9555 - auc: 0.9920 - val_loss: 0.8200 - val_accuracy: 0.7453 - val_precision: 0.6635 - val_recall: 0.9950 - val_auc: 0.9300\n",
            "Epoch 1261/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1051 - accuracy: 0.9596 - precision: 0.9601 - recall: 0.9591 - auc: 0.9928 - val_loss: 0.8646 - val_accuracy: 0.7370 - val_precision: 0.6562 - val_recall: 0.9954 - val_auc: 0.9295\n",
            "Epoch 1262/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1131 - accuracy: 0.9566 - precision: 0.9561 - recall: 0.9572 - auc: 0.9917 - val_loss: 0.7110 - val_accuracy: 0.7657 - val_precision: 0.6823 - val_recall: 0.9942 - val_auc: 0.9397\n",
            "Epoch 1263/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1063 - accuracy: 0.9592 - precision: 0.9597 - recall: 0.9587 - auc: 0.9927 - val_loss: 1.0413 - val_accuracy: 0.6937 - val_precision: 0.6205 - val_recall: 0.9967 - val_auc: 0.9147\n",
            "Epoch 1264/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1027 - accuracy: 0.9605 - precision: 0.9614 - recall: 0.9595 - auc: 0.9932 - val_loss: 0.9016 - val_accuracy: 0.7237 - val_precision: 0.6449 - val_recall: 0.9952 - val_auc: 0.9217\n",
            "Epoch 1265/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1236 - accuracy: 0.9525 - precision: 0.9504 - recall: 0.9549 - auc: 0.9901 - val_loss: 0.7622 - val_accuracy: 0.7444 - val_precision: 0.6628 - val_recall: 0.9947 - val_auc: 0.9295\n",
            "Epoch 1266/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1098 - accuracy: 0.9580 - precision: 0.9587 - recall: 0.9573 - auc: 0.9923 - val_loss: 0.8293 - val_accuracy: 0.7358 - val_precision: 0.6551 - val_recall: 0.9957 - val_auc: 0.9290\n",
            "Epoch 1267/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1134 - accuracy: 0.9565 - precision: 0.9559 - recall: 0.9572 - auc: 0.9917 - val_loss: 0.7637 - val_accuracy: 0.7507 - val_precision: 0.6684 - val_recall: 0.9949 - val_auc: 0.9346\n",
            "Epoch 1268/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1019 - accuracy: 0.9612 - precision: 0.9617 - recall: 0.9606 - auc: 0.9932 - val_loss: 0.9016 - val_accuracy: 0.7262 - val_precision: 0.6468 - val_recall: 0.9959 - val_auc: 0.9276\n",
            "Epoch 1269/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1112 - accuracy: 0.9575 - precision: 0.9590 - recall: 0.9560 - auc: 0.9919 - val_loss: 0.7457 - val_accuracy: 0.7434 - val_precision: 0.6617 - val_recall: 0.9954 - val_auc: 0.9470\n",
            "Epoch 1270/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1237 - accuracy: 0.9526 - precision: 0.9506 - recall: 0.9549 - auc: 0.9903 - val_loss: 0.7549 - val_accuracy: 0.7543 - val_precision: 0.6719 - val_recall: 0.9936 - val_auc: 0.9249\n",
            "Epoch 1271/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1049 - accuracy: 0.9597 - precision: 0.9595 - recall: 0.9600 - auc: 0.9929 - val_loss: 0.8215 - val_accuracy: 0.7406 - val_precision: 0.6596 - val_recall: 0.9942 - val_auc: 0.9219\n",
            "Epoch 1272/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1023 - accuracy: 0.9611 - precision: 0.9627 - recall: 0.9595 - auc: 0.9932 - val_loss: 0.9661 - val_accuracy: 0.7093 - val_precision: 0.6329 - val_recall: 0.9962 - val_auc: 0.9175\n",
            "Epoch 1273/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1220 - accuracy: 0.9540 - precision: 0.9521 - recall: 0.9561 - auc: 0.9904 - val_loss: 0.5989 - val_accuracy: 0.7936 - val_precision: 0.7104 - val_recall: 0.9911 - val_auc: 0.9445\n",
            "Epoch 1274/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1058 - accuracy: 0.9597 - precision: 0.9619 - recall: 0.9573 - auc: 0.9927 - val_loss: 0.7659 - val_accuracy: 0.7552 - val_precision: 0.6726 - val_recall: 0.9943 - val_auc: 0.9354\n",
            "Epoch 1275/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1119 - accuracy: 0.9573 - precision: 0.9570 - recall: 0.9576 - auc: 0.9918 - val_loss: 0.5074 - val_accuracy: 0.7722 - val_precision: 0.8656 - val_recall: 0.6444 - val_auc: 0.8909\n",
            "Epoch 1276/2000\n",
            "10/10 [==============================] - 4s 421ms/step - loss: 0.1316 - accuracy: 0.9500 - precision: 0.9481 - recall: 0.9522 - auc: 0.9891 - val_loss: 0.4029 - val_accuracy: 0.8549 - val_precision: 0.7838 - val_recall: 0.9800 - val_auc: 0.9596\n",
            "Epoch 1277/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1578 - accuracy: 0.9395 - precision: 0.9333 - recall: 0.9468 - auc: 0.9845 - val_loss: 0.5489 - val_accuracy: 0.6893 - val_precision: 0.9022 - val_recall: 0.4245 - val_auc: 0.8881\n",
            "Epoch 1278/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1549 - accuracy: 0.9394 - precision: 0.9372 - recall: 0.9419 - auc: 0.9853 - val_loss: 0.5751 - val_accuracy: 0.7969 - val_precision: 0.7152 - val_recall: 0.9866 - val_auc: 0.9263\n",
            "Epoch 1279/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1110 - accuracy: 0.9580 - precision: 0.9595 - recall: 0.9564 - auc: 0.9921 - val_loss: 0.8724 - val_accuracy: 0.7318 - val_precision: 0.6517 - val_recall: 0.9954 - val_auc: 0.9252\n",
            "Epoch 1280/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1161 - accuracy: 0.9554 - precision: 0.9563 - recall: 0.9544 - auc: 0.9913 - val_loss: 0.8176 - val_accuracy: 0.7407 - val_precision: 0.6595 - val_recall: 0.9952 - val_auc: 0.9277\n",
            "Epoch 1281/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1047 - accuracy: 0.9599 - precision: 0.9613 - recall: 0.9585 - auc: 0.9929 - val_loss: 0.9169 - val_accuracy: 0.7232 - val_precision: 0.6443 - val_recall: 0.9959 - val_auc: 0.9251\n",
            "Epoch 1282/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1046 - accuracy: 0.9600 - precision: 0.9618 - recall: 0.9581 - auc: 0.9929 - val_loss: 0.9408 - val_accuracy: 0.7191 - val_precision: 0.6409 - val_recall: 0.9960 - val_auc: 0.9250\n",
            "Epoch 1283/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1211 - accuracy: 0.9539 - precision: 0.9534 - recall: 0.9544 - auc: 0.9905 - val_loss: 0.8783 - val_accuracy: 0.7163 - val_precision: 0.6387 - val_recall: 0.9958 - val_auc: 0.9246\n",
            "Epoch 1284/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1130 - accuracy: 0.9571 - precision: 0.9567 - recall: 0.9575 - auc: 0.9918 - val_loss: 0.8368 - val_accuracy: 0.7331 - val_precision: 0.6529 - val_recall: 0.9952 - val_auc: 0.9343\n",
            "Epoch 1285/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1081 - accuracy: 0.9585 - precision: 0.9587 - recall: 0.9583 - auc: 0.9925 - val_loss: 0.8047 - val_accuracy: 0.7459 - val_precision: 0.6642 - val_recall: 0.9946 - val_auc: 0.9330\n",
            "Epoch 1286/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1059 - accuracy: 0.9594 - precision: 0.9618 - recall: 0.9568 - auc: 0.9927 - val_loss: 0.9523 - val_accuracy: 0.7080 - val_precision: 0.6318 - val_recall: 0.9967 - val_auc: 0.9261\n",
            "Epoch 1287/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1092 - accuracy: 0.9579 - precision: 0.9574 - recall: 0.9584 - auc: 0.9923 - val_loss: 1.0029 - val_accuracy: 0.7020 - val_precision: 0.6270 - val_recall: 0.9968 - val_auc: 0.9236\n",
            "Epoch 1288/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1015 - accuracy: 0.9610 - precision: 0.9609 - recall: 0.9612 - auc: 0.9933 - val_loss: 0.9232 - val_accuracy: 0.7184 - val_precision: 0.6404 - val_recall: 0.9956 - val_auc: 0.9232\n",
            "Epoch 1289/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1026 - accuracy: 0.9606 - precision: 0.9613 - recall: 0.9599 - auc: 0.9932 - val_loss: 1.0294 - val_accuracy: 0.7041 - val_precision: 0.6287 - val_recall: 0.9965 - val_auc: 0.9224\n",
            "Epoch 1290/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1452 - accuracy: 0.9449 - precision: 0.9437 - recall: 0.9463 - auc: 0.9867 - val_loss: 0.3226 - val_accuracy: 0.8546 - val_precision: 0.8801 - val_recall: 0.8210 - val_auc: 0.9375\n",
            "Epoch 1291/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1519 - accuracy: 0.9429 - precision: 0.9411 - recall: 0.9450 - auc: 0.9854 - val_loss: 0.7144 - val_accuracy: 0.6652 - val_precision: 0.8167 - val_recall: 0.4257 - val_auc: 0.8161\n",
            "Epoch 1292/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1816 - accuracy: 0.9278 - precision: 0.9222 - recall: 0.9343 - auc: 0.9796 - val_loss: 0.5545 - val_accuracy: 0.7112 - val_precision: 0.8756 - val_recall: 0.4920 - val_auc: 0.8779\n",
            "Epoch 1293/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1746 - accuracy: 0.9309 - precision: 0.9260 - recall: 0.9367 - auc: 0.9810 - val_loss: 0.4107 - val_accuracy: 0.7943 - val_precision: 0.9005 - val_recall: 0.6616 - val_auc: 0.9243\n",
            "Epoch 1294/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1607 - accuracy: 0.9365 - precision: 0.9327 - recall: 0.9410 - auc: 0.9839 - val_loss: 0.2965 - val_accuracy: 0.8771 - val_precision: 0.8598 - val_recall: 0.9011 - val_auc: 0.9459\n",
            "Epoch 1295/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1420 - accuracy: 0.9450 - precision: 0.9424 - recall: 0.9480 - auc: 0.9873 - val_loss: 0.5714 - val_accuracy: 0.7959 - val_precision: 0.7142 - val_recall: 0.9864 - val_auc: 0.9276\n",
            "Epoch 1296/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1121 - accuracy: 0.9573 - precision: 0.9577 - recall: 0.9568 - auc: 0.9919 - val_loss: 0.8019 - val_accuracy: 0.7457 - val_precision: 0.6641 - val_recall: 0.9938 - val_auc: 0.9202\n",
            "Epoch 1297/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1042 - accuracy: 0.9599 - precision: 0.9612 - recall: 0.9585 - auc: 0.9930 - val_loss: 0.9644 - val_accuracy: 0.7130 - val_precision: 0.6359 - val_recall: 0.9962 - val_auc: 0.9180\n",
            "Epoch 1298/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1027 - accuracy: 0.9607 - precision: 0.9635 - recall: 0.9577 - auc: 0.9931 - val_loss: 1.1174 - val_accuracy: 0.6827 - val_precision: 0.6121 - val_recall: 0.9971 - val_auc: 0.9123\n",
            "Epoch 1299/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1281 - accuracy: 0.9512 - precision: 0.9497 - recall: 0.9528 - auc: 0.9895 - val_loss: 0.7765 - val_accuracy: 0.7464 - val_precision: 0.6647 - val_recall: 0.9943 - val_auc: 0.9248\n",
            "Epoch 1300/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1081 - accuracy: 0.9593 - precision: 0.9597 - recall: 0.9589 - auc: 0.9925 - val_loss: 0.8480 - val_accuracy: 0.7452 - val_precision: 0.6639 - val_recall: 0.9928 - val_auc: 0.9171\n",
            "Epoch 1301/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1740 - accuracy: 0.9326 - precision: 0.9242 - recall: 0.9425 - auc: 0.9813 - val_loss: 0.4817 - val_accuracy: 0.7269 - val_precision: 0.8933 - val_recall: 0.5153 - val_auc: 0.8988\n",
            "Epoch 1302/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1753 - accuracy: 0.9304 - precision: 0.9235 - recall: 0.9386 - auc: 0.9810 - val_loss: 0.4937 - val_accuracy: 0.7567 - val_precision: 0.9087 - val_recall: 0.5705 - val_auc: 0.9173\n",
            "Epoch 1303/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1711 - accuracy: 0.9323 - precision: 0.9277 - recall: 0.9377 - auc: 0.9818 - val_loss: 0.3784 - val_accuracy: 0.8156 - val_precision: 0.9074 - val_recall: 0.7028 - val_auc: 0.9336\n",
            "Epoch 1304/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1627 - accuracy: 0.9355 - precision: 0.9326 - recall: 0.9390 - auc: 0.9834 - val_loss: 0.2916 - val_accuracy: 0.8785 - val_precision: 0.8671 - val_recall: 0.8939 - val_auc: 0.9470\n",
            "Epoch 1305/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1593 - accuracy: 0.9372 - precision: 0.9327 - recall: 0.9424 - auc: 0.9841 - val_loss: 0.3629 - val_accuracy: 0.8558 - val_precision: 0.7920 - val_recall: 0.9650 - val_auc: 0.9426\n",
            "Epoch 1306/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1560 - accuracy: 0.9389 - precision: 0.9359 - recall: 0.9423 - auc: 0.9848 - val_loss: 0.4830 - val_accuracy: 0.8170 - val_precision: 0.7379 - val_recall: 0.9828 - val_auc: 0.9349\n",
            "Epoch 1307/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1223 - accuracy: 0.9533 - precision: 0.9530 - recall: 0.9537 - auc: 0.9905 - val_loss: 0.5753 - val_accuracy: 0.7996 - val_precision: 0.7183 - val_recall: 0.9856 - val_auc: 0.9341\n",
            "Epoch 1308/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1062 - accuracy: 0.9594 - precision: 0.9599 - recall: 0.9589 - auc: 0.9927 - val_loss: 0.7416 - val_accuracy: 0.7553 - val_precision: 0.6732 - val_recall: 0.9919 - val_auc: 0.9206\n",
            "Epoch 1309/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1017 - accuracy: 0.9613 - precision: 0.9624 - recall: 0.9602 - auc: 0.9933 - val_loss: 0.9315 - val_accuracy: 0.7158 - val_precision: 0.6382 - val_recall: 0.9960 - val_auc: 0.9259\n",
            "Epoch 1310/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1222 - accuracy: 0.9536 - precision: 0.9521 - recall: 0.9552 - auc: 0.9903 - val_loss: 0.9148 - val_accuracy: 0.7064 - val_precision: 0.6305 - val_recall: 0.9964 - val_auc: 0.9208\n",
            "Epoch 1311/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1080 - accuracy: 0.9591 - precision: 0.9607 - recall: 0.9574 - auc: 0.9926 - val_loss: 0.8778 - val_accuracy: 0.7316 - val_precision: 0.6517 - val_recall: 0.9946 - val_auc: 0.9224\n",
            "Epoch 1312/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1016 - accuracy: 0.9612 - precision: 0.9617 - recall: 0.9606 - auc: 0.9932 - val_loss: 0.9580 - val_accuracy: 0.7131 - val_precision: 0.6360 - val_recall: 0.9960 - val_auc: 0.9234\n",
            "Epoch 1313/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1043 - accuracy: 0.9603 - precision: 0.9612 - recall: 0.9593 - auc: 0.9929 - val_loss: 0.8995 - val_accuracy: 0.7275 - val_precision: 0.6481 - val_recall: 0.9951 - val_auc: 0.9231\n",
            "Epoch 1314/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1231 - accuracy: 0.9532 - precision: 0.9520 - recall: 0.9546 - auc: 0.9902 - val_loss: 0.8022 - val_accuracy: 0.7476 - val_precision: 0.6658 - val_recall: 0.9940 - val_auc: 0.9245\n",
            "Epoch 1315/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1008 - accuracy: 0.9618 - precision: 0.9628 - recall: 0.9608 - auc: 0.9934 - val_loss: 0.8243 - val_accuracy: 0.7554 - val_precision: 0.6736 - val_recall: 0.9908 - val_auc: 0.9231\n",
            "Epoch 1316/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1122 - accuracy: 0.9572 - precision: 0.9560 - recall: 0.9586 - auc: 0.9918 - val_loss: 0.8574 - val_accuracy: 0.7393 - val_precision: 0.6582 - val_recall: 0.9950 - val_auc: 0.9293\n",
            "Epoch 1317/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1004 - accuracy: 0.9621 - precision: 0.9634 - recall: 0.9607 - auc: 0.9934 - val_loss: 1.1651 - val_accuracy: 0.6888 - val_precision: 0.6169 - val_recall: 0.9962 - val_auc: 0.9044\n",
            "Epoch 1318/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1006 - accuracy: 0.9616 - precision: 0.9643 - recall: 0.9586 - auc: 0.9934 - val_loss: 0.9128 - val_accuracy: 0.7312 - val_precision: 0.6514 - val_recall: 0.9940 - val_auc: 0.9214\n",
            "Epoch 1319/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1192 - accuracy: 0.9543 - precision: 0.9539 - recall: 0.9548 - auc: 0.9908 - val_loss: 0.7687 - val_accuracy: 0.7575 - val_precision: 0.6749 - val_recall: 0.9931 - val_auc: 0.9272\n",
            "Epoch 1320/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1050 - accuracy: 0.9596 - precision: 0.9598 - recall: 0.9594 - auc: 0.9929 - val_loss: 0.8902 - val_accuracy: 0.7359 - val_precision: 0.6553 - val_recall: 0.9952 - val_auc: 0.9249\n",
            "Epoch 1321/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0981 - accuracy: 0.9623 - precision: 0.9631 - recall: 0.9615 - auc: 0.9937 - val_loss: 0.9762 - val_accuracy: 0.7160 - val_precision: 0.6384 - val_recall: 0.9960 - val_auc: 0.9197\n",
            "Epoch 1322/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1042 - accuracy: 0.9604 - precision: 0.9608 - recall: 0.9600 - auc: 0.9929 - val_loss: 0.9218 - val_accuracy: 0.7254 - val_precision: 0.6463 - val_recall: 0.9951 - val_auc: 0.9221\n",
            "Epoch 1323/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1162 - accuracy: 0.9556 - precision: 0.9536 - recall: 0.9579 - auc: 0.9912 - val_loss: 0.7924 - val_accuracy: 0.7445 - val_precision: 0.6631 - val_recall: 0.9938 - val_auc: 0.9244\n",
            "Epoch 1324/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.0997 - accuracy: 0.9622 - precision: 0.9632 - recall: 0.9612 - auc: 0.9936 - val_loss: 0.8820 - val_accuracy: 0.7318 - val_precision: 0.6517 - val_recall: 0.9955 - val_auc: 0.9290\n",
            "Epoch 1325/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1066 - accuracy: 0.9594 - precision: 0.9590 - recall: 0.9598 - auc: 0.9925 - val_loss: 1.2878 - val_accuracy: 0.6644 - val_precision: 0.5986 - val_recall: 0.9972 - val_auc: 0.8821\n",
            "Epoch 1326/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1080 - accuracy: 0.9588 - precision: 0.9603 - recall: 0.9572 - auc: 0.9925 - val_loss: 0.8959 - val_accuracy: 0.7247 - val_precision: 0.6456 - val_recall: 0.9961 - val_auc: 0.9286\n",
            "Epoch 1327/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0980 - accuracy: 0.9629 - precision: 0.9635 - recall: 0.9622 - auc: 0.9937 - val_loss: 1.0001 - val_accuracy: 0.7022 - val_precision: 0.6271 - val_recall: 0.9969 - val_auc: 0.9239\n",
            "Epoch 1328/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1403 - accuracy: 0.9468 - precision: 0.9421 - recall: 0.9520 - auc: 0.9875 - val_loss: 0.7770 - val_accuracy: 0.7409 - val_precision: 0.6598 - val_recall: 0.9943 - val_auc: 0.9330\n",
            "Epoch 1329/2000\n",
            "10/10 [==============================] - 4s 417ms/step - loss: 0.1281 - accuracy: 0.9515 - precision: 0.9497 - recall: 0.9535 - auc: 0.9894 - val_loss: 0.7231 - val_accuracy: 0.7468 - val_precision: 0.6648 - val_recall: 0.9953 - val_auc: 0.9423\n",
            "Epoch 1330/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1045 - accuracy: 0.9599 - precision: 0.9622 - recall: 0.9574 - auc: 0.9931 - val_loss: 0.7969 - val_accuracy: 0.7411 - val_precision: 0.6597 - val_recall: 0.9954 - val_auc: 0.9402\n",
            "Epoch 1331/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1014 - accuracy: 0.9614 - precision: 0.9624 - recall: 0.9603 - auc: 0.9932 - val_loss: 0.9145 - val_accuracy: 0.7195 - val_precision: 0.6412 - val_recall: 0.9964 - val_auc: 0.9340\n",
            "Epoch 1332/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1049 - accuracy: 0.9599 - precision: 0.9610 - recall: 0.9587 - auc: 0.9928 - val_loss: 0.9150 - val_accuracy: 0.7169 - val_precision: 0.6391 - val_recall: 0.9963 - val_auc: 0.9290\n",
            "Epoch 1333/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.0980 - accuracy: 0.9628 - precision: 0.9643 - recall: 0.9612 - auc: 0.9937 - val_loss: 1.0624 - val_accuracy: 0.6912 - val_precision: 0.6185 - val_recall: 0.9973 - val_auc: 0.9222\n",
            "Epoch 1334/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1076 - accuracy: 0.9592 - precision: 0.9605 - recall: 0.9578 - auc: 0.9924 - val_loss: 0.8850 - val_accuracy: 0.7302 - val_precision: 0.6502 - val_recall: 0.9960 - val_auc: 0.9324\n",
            "Epoch 1335/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1130 - accuracy: 0.9576 - precision: 0.9571 - recall: 0.9581 - auc: 0.9916 - val_loss: 0.9405 - val_accuracy: 0.7147 - val_precision: 0.6373 - val_recall: 0.9961 - val_auc: 0.9273\n",
            "Epoch 1336/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.0979 - accuracy: 0.9630 - precision: 0.9649 - recall: 0.9611 - auc: 0.9938 - val_loss: 0.3147 - val_accuracy: 0.8769 - val_precision: 0.8680 - val_recall: 0.8890 - val_auc: 0.9473\n",
            "Epoch 1337/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1330 - accuracy: 0.9492 - precision: 0.9477 - recall: 0.9508 - auc: 0.9887 - val_loss: 0.8512 - val_accuracy: 0.7385 - val_precision: 0.6576 - val_recall: 0.9949 - val_auc: 0.9196\n",
            "Epoch 1338/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1107 - accuracy: 0.9579 - precision: 0.9586 - recall: 0.9571 - auc: 0.9921 - val_loss: 0.9634 - val_accuracy: 0.7131 - val_precision: 0.6360 - val_recall: 0.9963 - val_auc: 0.9254\n",
            "Epoch 1339/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1006 - accuracy: 0.9616 - precision: 0.9629 - recall: 0.9603 - auc: 0.9934 - val_loss: 0.8686 - val_accuracy: 0.7322 - val_precision: 0.6519 - val_recall: 0.9960 - val_auc: 0.9311\n",
            "Epoch 1340/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.0991 - accuracy: 0.9618 - precision: 0.9627 - recall: 0.9609 - auc: 0.9936 - val_loss: 0.9162 - val_accuracy: 0.7193 - val_precision: 0.6409 - val_recall: 0.9966 - val_auc: 0.9327\n",
            "Epoch 1341/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1148 - accuracy: 0.9560 - precision: 0.9543 - recall: 0.9579 - auc: 0.9915 - val_loss: 0.6841 - val_accuracy: 0.7757 - val_precision: 0.6923 - val_recall: 0.9925 - val_auc: 0.9387\n",
            "Epoch 1342/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0977 - accuracy: 0.9627 - precision: 0.9642 - recall: 0.9610 - auc: 0.9937 - val_loss: 0.8921 - val_accuracy: 0.7265 - val_precision: 0.6471 - val_recall: 0.9963 - val_auc: 0.9316\n",
            "Epoch 1343/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1041 - accuracy: 0.9604 - precision: 0.9613 - recall: 0.9594 - auc: 0.9929 - val_loss: 0.8802 - val_accuracy: 0.7309 - val_precision: 0.6508 - val_recall: 0.9959 - val_auc: 0.9310\n",
            "Epoch 1344/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.0959 - accuracy: 0.9635 - precision: 0.9659 - recall: 0.9609 - auc: 0.9939 - val_loss: 0.9544 - val_accuracy: 0.7208 - val_precision: 0.6422 - val_recall: 0.9967 - val_auc: 0.9313\n",
            "Epoch 1345/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1070 - accuracy: 0.9591 - precision: 0.9588 - recall: 0.9593 - auc: 0.9925 - val_loss: 0.9164 - val_accuracy: 0.7210 - val_precision: 0.6425 - val_recall: 0.9960 - val_auc: 0.9317\n",
            "Epoch 1346/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0984 - accuracy: 0.9625 - precision: 0.9645 - recall: 0.9603 - auc: 0.9936 - val_loss: 1.1748 - val_accuracy: 0.6816 - val_precision: 0.6112 - val_recall: 0.9971 - val_auc: 0.9065\n",
            "Epoch 1347/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1231 - accuracy: 0.9530 - precision: 0.9518 - recall: 0.9544 - auc: 0.9902 - val_loss: 0.2528 - val_accuracy: 0.8975 - val_precision: 0.8501 - val_recall: 0.9652 - val_auc: 0.9709\n",
            "Epoch 1348/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1024 - accuracy: 0.9611 - precision: 0.9619 - recall: 0.9603 - auc: 0.9932 - val_loss: 0.6607 - val_accuracy: 0.7929 - val_precision: 0.7095 - val_recall: 0.9919 - val_auc: 0.9493\n",
            "Epoch 1349/2000\n",
            "10/10 [==============================] - 4s 435ms/step - loss: 0.1109 - accuracy: 0.9582 - precision: 0.9586 - recall: 0.9579 - auc: 0.9920 - val_loss: 0.8281 - val_accuracy: 0.7433 - val_precision: 0.6617 - val_recall: 0.9949 - val_auc: 0.9278\n",
            "Epoch 1350/2000\n",
            "10/10 [==============================] - 5s 486ms/step - loss: 0.0975 - accuracy: 0.9631 - precision: 0.9658 - recall: 0.9602 - auc: 0.9938 - val_loss: 0.8487 - val_accuracy: 0.7419 - val_precision: 0.6604 - val_recall: 0.9955 - val_auc: 0.9346\n",
            "Epoch 1351/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1225 - accuracy: 0.9533 - precision: 0.9525 - recall: 0.9541 - auc: 0.9903 - val_loss: 0.6834 - val_accuracy: 0.7782 - val_precision: 0.6946 - val_recall: 0.9929 - val_auc: 0.9385\n",
            "Epoch 1352/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1072 - accuracy: 0.9591 - precision: 0.9604 - recall: 0.9577 - auc: 0.9925 - val_loss: 0.8787 - val_accuracy: 0.7335 - val_precision: 0.6533 - val_recall: 0.9945 - val_auc: 0.9173\n",
            "Epoch 1353/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1082 - accuracy: 0.9587 - precision: 0.9589 - recall: 0.9585 - auc: 0.9924 - val_loss: 0.7121 - val_accuracy: 0.7655 - val_precision: 0.6821 - val_recall: 0.9940 - val_auc: 0.9428\n",
            "Epoch 1354/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1113 - accuracy: 0.9577 - precision: 0.9573 - recall: 0.9582 - auc: 0.9918 - val_loss: 0.6060 - val_accuracy: 0.7460 - val_precision: 0.8244 - val_recall: 0.6250 - val_auc: 0.8509\n",
            "Epoch 1355/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1957 - accuracy: 0.9256 - precision: 0.9195 - recall: 0.9329 - auc: 0.9769 - val_loss: 0.8993 - val_accuracy: 0.7776 - val_precision: 0.6965 - val_recall: 0.9835 - val_auc: 0.9017\n",
            "Epoch 1356/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1562 - accuracy: 0.9421 - precision: 0.9401 - recall: 0.9443 - auc: 0.9847 - val_loss: 0.6814 - val_accuracy: 0.6918 - val_precision: 0.8218 - val_recall: 0.4895 - val_auc: 0.8339\n",
            "Epoch 1357/2000\n",
            "10/10 [==============================] - 5s 493ms/step - loss: 0.1786 - accuracy: 0.9298 - precision: 0.9255 - recall: 0.9349 - auc: 0.9805 - val_loss: 0.3454 - val_accuracy: 0.8602 - val_precision: 0.8573 - val_recall: 0.8642 - val_auc: 0.9343\n",
            "Epoch 1358/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1325 - accuracy: 0.9489 - precision: 0.9467 - recall: 0.9513 - auc: 0.9889 - val_loss: 0.6691 - val_accuracy: 0.7550 - val_precision: 0.6726 - val_recall: 0.9933 - val_auc: 0.9324\n",
            "Epoch 1359/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1061 - accuracy: 0.9595 - precision: 0.9614 - recall: 0.9576 - auc: 0.9927 - val_loss: 0.9402 - val_accuracy: 0.7140 - val_precision: 0.6368 - val_recall: 0.9958 - val_auc: 0.9241\n",
            "Epoch 1360/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1037 - accuracy: 0.9605 - precision: 0.9629 - recall: 0.9579 - auc: 0.9929 - val_loss: 1.0650 - val_accuracy: 0.6986 - val_precision: 0.6243 - val_recall: 0.9969 - val_auc: 0.9175\n",
            "Epoch 1361/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.0961 - accuracy: 0.9637 - precision: 0.9671 - recall: 0.9601 - auc: 0.9939 - val_loss: 1.1443 - val_accuracy: 0.6880 - val_precision: 0.6161 - val_recall: 0.9970 - val_auc: 0.9133\n",
            "Epoch 1362/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0963 - accuracy: 0.9636 - precision: 0.9657 - recall: 0.9615 - auc: 0.9939 - val_loss: 1.2366 - val_accuracy: 0.6776 - val_precision: 0.6082 - val_recall: 0.9976 - val_auc: 0.9058\n",
            "Epoch 1363/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.2208 - accuracy: 0.9143 - precision: 0.8972 - recall: 0.9358 - auc: 0.9709 - val_loss: 0.3657 - val_accuracy: 0.8041 - val_precision: 0.9101 - val_recall: 0.6747 - val_auc: 0.9301\n",
            "Epoch 1364/2000\n",
            "10/10 [==============================] - 4s 419ms/step - loss: 0.1847 - accuracy: 0.9275 - precision: 0.9231 - recall: 0.9327 - auc: 0.9789 - val_loss: 0.3335 - val_accuracy: 0.8419 - val_precision: 0.9168 - val_recall: 0.7521 - val_auc: 0.9422\n",
            "Epoch 1365/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1639 - accuracy: 0.9358 - precision: 0.9304 - recall: 0.9420 - auc: 0.9832 - val_loss: 0.3036 - val_accuracy: 0.8929 - val_precision: 0.8565 - val_recall: 0.9439 - val_auc: 0.9584\n",
            "Epoch 1366/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1324 - accuracy: 0.9493 - precision: 0.9481 - recall: 0.9506 - auc: 0.9889 - val_loss: 0.3802 - val_accuracy: 0.8678 - val_precision: 0.8175 - val_recall: 0.9468 - val_auc: 0.9430\n",
            "Epoch 1367/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1213 - accuracy: 0.9534 - precision: 0.9548 - recall: 0.9520 - auc: 0.9906 - val_loss: 0.3931 - val_accuracy: 0.8732 - val_precision: 0.8165 - val_recall: 0.9626 - val_auc: 0.9552\n",
            "Epoch 1368/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1134 - accuracy: 0.9563 - precision: 0.9576 - recall: 0.9549 - auc: 0.9918 - val_loss: 0.7082 - val_accuracy: 0.7954 - val_precision: 0.7137 - val_recall: 0.9863 - val_auc: 0.9286\n",
            "Epoch 1369/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1181 - accuracy: 0.9547 - precision: 0.9543 - recall: 0.9551 - auc: 0.9910 - val_loss: 0.4765 - val_accuracy: 0.8431 - val_precision: 0.7861 - val_recall: 0.9426 - val_auc: 0.9310\n",
            "Epoch 1370/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1255 - accuracy: 0.9527 - precision: 0.9512 - recall: 0.9543 - auc: 0.9900 - val_loss: 0.7123 - val_accuracy: 0.7842 - val_precision: 0.7017 - val_recall: 0.9887 - val_auc: 0.9354\n",
            "Epoch 1371/2000\n",
            "10/10 [==============================] - 4s 419ms/step - loss: 0.1042 - accuracy: 0.9606 - precision: 0.9602 - recall: 0.9611 - auc: 0.9929 - val_loss: 0.8472 - val_accuracy: 0.7623 - val_precision: 0.6796 - val_recall: 0.9923 - val_auc: 0.9310\n",
            "Epoch 1372/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1030 - accuracy: 0.9604 - precision: 0.9616 - recall: 0.9591 - auc: 0.9931 - val_loss: 0.9101 - val_accuracy: 0.7523 - val_precision: 0.6699 - val_recall: 0.9941 - val_auc: 0.9282\n",
            "Epoch 1373/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1271 - accuracy: 0.9516 - precision: 0.9505 - recall: 0.9528 - auc: 0.9895 - val_loss: 0.6439 - val_accuracy: 0.7948 - val_precision: 0.7131 - val_recall: 0.9866 - val_auc: 0.9391\n",
            "Epoch 1374/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1055 - accuracy: 0.9596 - precision: 0.9598 - recall: 0.9594 - auc: 0.9928 - val_loss: 0.5978 - val_accuracy: 0.8184 - val_precision: 0.7388 - val_recall: 0.9848 - val_auc: 0.9451\n",
            "Epoch 1375/2000\n",
            "10/10 [==============================] - 4s 420ms/step - loss: 0.1074 - accuracy: 0.9593 - precision: 0.9589 - recall: 0.9598 - auc: 0.9925 - val_loss: 0.9181 - val_accuracy: 0.7362 - val_precision: 0.6555 - val_recall: 0.9952 - val_auc: 0.9301\n",
            "Epoch 1376/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1063 - accuracy: 0.9596 - precision: 0.9601 - recall: 0.9590 - auc: 0.9926 - val_loss: 0.9726 - val_accuracy: 0.7253 - val_precision: 0.6461 - val_recall: 0.9956 - val_auc: 0.9265\n",
            "Epoch 1377/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1001 - accuracy: 0.9619 - precision: 0.9631 - recall: 0.9607 - auc: 0.9935 - val_loss: 0.8618 - val_accuracy: 0.7543 - val_precision: 0.6727 - val_recall: 0.9904 - val_auc: 0.9239\n",
            "Epoch 1378/2000\n",
            "10/10 [==============================] - 4s 417ms/step - loss: 0.1037 - accuracy: 0.9605 - precision: 0.9614 - recall: 0.9595 - auc: 0.9930 - val_loss: 0.9011 - val_accuracy: 0.7424 - val_precision: 0.6613 - val_recall: 0.9935 - val_auc: 0.9265\n",
            "Epoch 1379/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1000 - accuracy: 0.9619 - precision: 0.9624 - recall: 0.9613 - auc: 0.9934 - val_loss: 0.3079 - val_accuracy: 0.8852 - val_precision: 0.8218 - val_recall: 0.9836 - val_auc: 0.9813\n",
            "Epoch 1380/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1080 - accuracy: 0.9588 - precision: 0.9593 - recall: 0.9582 - auc: 0.9925 - val_loss: 0.8504 - val_accuracy: 0.7485 - val_precision: 0.6666 - val_recall: 0.9941 - val_auc: 0.9341\n",
            "Epoch 1381/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0991 - accuracy: 0.9625 - precision: 0.9630 - recall: 0.9620 - auc: 0.9935 - val_loss: 0.3117 - val_accuracy: 0.8833 - val_precision: 0.8165 - val_recall: 0.9889 - val_auc: 0.9856\n",
            "Epoch 1382/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1348 - accuracy: 0.9485 - precision: 0.9460 - recall: 0.9514 - auc: 0.9884 - val_loss: 0.7523 - val_accuracy: 0.7373 - val_precision: 0.6566 - val_recall: 0.9944 - val_auc: 0.9302\n",
            "Epoch 1383/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1707 - accuracy: 0.9333 - precision: 0.9249 - recall: 0.9433 - auc: 0.9821 - val_loss: 0.3328 - val_accuracy: 0.8519 - val_precision: 0.8981 - val_recall: 0.7938 - val_auc: 0.9405\n",
            "Epoch 1384/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1464 - accuracy: 0.9430 - precision: 0.9417 - recall: 0.9446 - auc: 0.9865 - val_loss: 0.5207 - val_accuracy: 0.8106 - val_precision: 0.7293 - val_recall: 0.9876 - val_auc: 0.9387\n",
            "Epoch 1385/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1399 - accuracy: 0.9467 - precision: 0.9451 - recall: 0.9485 - auc: 0.9875 - val_loss: 0.4456 - val_accuracy: 0.8380 - val_precision: 0.7646 - val_recall: 0.9767 - val_auc: 0.9410\n",
            "Epoch 1386/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1083 - accuracy: 0.9583 - precision: 0.9609 - recall: 0.9555 - auc: 0.9926 - val_loss: 0.6252 - val_accuracy: 0.7929 - val_precision: 0.7096 - val_recall: 0.9914 - val_auc: 0.9450\n",
            "Epoch 1387/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1027 - accuracy: 0.9609 - precision: 0.9630 - recall: 0.9586 - auc: 0.9931 - val_loss: 0.2720 - val_accuracy: 0.8941 - val_precision: 0.8902 - val_recall: 0.8990 - val_auc: 0.9605\n",
            "Epoch 1388/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1187 - accuracy: 0.9550 - precision: 0.9550 - recall: 0.9551 - auc: 0.9909 - val_loss: 0.7146 - val_accuracy: 0.7719 - val_precision: 0.6888 - val_recall: 0.9920 - val_auc: 0.9370\n",
            "Epoch 1389/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1012 - accuracy: 0.9614 - precision: 0.9626 - recall: 0.9600 - auc: 0.9934 - val_loss: 0.9063 - val_accuracy: 0.7332 - val_precision: 0.6529 - val_recall: 0.9954 - val_auc: 0.9295\n",
            "Epoch 1390/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1264 - accuracy: 0.9520 - precision: 0.9503 - recall: 0.9540 - auc: 0.9898 - val_loss: 0.2851 - val_accuracy: 0.8808 - val_precision: 0.8748 - val_recall: 0.8886 - val_auc: 0.9505\n",
            "Epoch 1391/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1197 - accuracy: 0.9546 - precision: 0.9540 - recall: 0.9552 - auc: 0.9912 - val_loss: 0.2511 - val_accuracy: 0.9025 - val_precision: 0.8884 - val_recall: 0.9207 - val_auc: 0.9645\n",
            "Epoch 1392/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1204 - accuracy: 0.9540 - precision: 0.9515 - recall: 0.9567 - auc: 0.9907 - val_loss: 0.4226 - val_accuracy: 0.8556 - val_precision: 0.7844 - val_recall: 0.9806 - val_auc: 0.9622\n",
            "Epoch 1393/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1024 - accuracy: 0.9606 - precision: 0.9629 - recall: 0.9582 - auc: 0.9933 - val_loss: 0.8368 - val_accuracy: 0.7476 - val_precision: 0.6659 - val_recall: 0.9933 - val_auc: 0.9290\n",
            "Epoch 1394/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1011 - accuracy: 0.9614 - precision: 0.9620 - recall: 0.9608 - auc: 0.9933 - val_loss: 0.9461 - val_accuracy: 0.7223 - val_precision: 0.6436 - val_recall: 0.9961 - val_auc: 0.9306\n",
            "Epoch 1395/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1037 - accuracy: 0.9602 - precision: 0.9611 - recall: 0.9593 - auc: 0.9930 - val_loss: 0.5322 - val_accuracy: 0.8225 - val_precision: 0.7436 - val_recall: 0.9840 - val_auc: 0.9522\n",
            "Epoch 1396/2000\n",
            "10/10 [==============================] - 4s 417ms/step - loss: 0.1131 - accuracy: 0.9568 - precision: 0.9569 - recall: 0.9566 - auc: 0.9918 - val_loss: 0.8396 - val_accuracy: 0.7380 - val_precision: 0.6571 - val_recall: 0.9953 - val_auc: 0.9359\n",
            "Epoch 1397/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1031 - accuracy: 0.9608 - precision: 0.9605 - recall: 0.9611 - auc: 0.9931 - val_loss: 0.6131 - val_accuracy: 0.8013 - val_precision: 0.7189 - val_recall: 0.9893 - val_auc: 0.9516\n",
            "Epoch 1398/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.0978 - accuracy: 0.9630 - precision: 0.9642 - recall: 0.9617 - auc: 0.9937 - val_loss: 0.8301 - val_accuracy: 0.7463 - val_precision: 0.6643 - val_recall: 0.9951 - val_auc: 0.9413\n",
            "Epoch 1399/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1142 - accuracy: 0.9567 - precision: 0.9544 - recall: 0.9592 - auc: 0.9915 - val_loss: 0.8616 - val_accuracy: 0.7331 - val_precision: 0.6528 - val_recall: 0.9957 - val_auc: 0.9286\n",
            "Epoch 1400/2000\n",
            "10/10 [==============================] - 5s 485ms/step - loss: 0.1059 - accuracy: 0.9593 - precision: 0.9607 - recall: 0.9577 - auc: 0.9928 - val_loss: 0.8396 - val_accuracy: 0.7436 - val_precision: 0.6622 - val_recall: 0.9942 - val_auc: 0.9294\n",
            "Epoch 1401/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1187 - accuracy: 0.9549 - precision: 0.9538 - recall: 0.9562 - auc: 0.9909 - val_loss: 0.8064 - val_accuracy: 0.7456 - val_precision: 0.6637 - val_recall: 0.9953 - val_auc: 0.9379\n",
            "Epoch 1402/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.0991 - accuracy: 0.9623 - precision: 0.9623 - recall: 0.9623 - auc: 0.9936 - val_loss: 0.9638 - val_accuracy: 0.7196 - val_precision: 0.6414 - val_recall: 0.9959 - val_auc: 0.9282\n",
            "Epoch 1403/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.0985 - accuracy: 0.9624 - precision: 0.9644 - recall: 0.9604 - auc: 0.9936 - val_loss: 0.9658 - val_accuracy: 0.7167 - val_precision: 0.6389 - val_recall: 0.9965 - val_auc: 0.9305\n",
            "Epoch 1404/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1013 - accuracy: 0.9611 - precision: 0.9620 - recall: 0.9600 - auc: 0.9933 - val_loss: 0.7100 - val_accuracy: 0.7780 - val_precision: 0.6944 - val_recall: 0.9925 - val_auc: 0.9461\n",
            "Epoch 1405/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1122 - accuracy: 0.9568 - precision: 0.9561 - recall: 0.9576 - auc: 0.9919 - val_loss: 0.8013 - val_accuracy: 0.7422 - val_precision: 0.6610 - val_recall: 0.9942 - val_auc: 0.9364\n",
            "Epoch 1406/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.0981 - accuracy: 0.9626 - precision: 0.9632 - recall: 0.9620 - auc: 0.9937 - val_loss: 0.5821 - val_accuracy: 0.8093 - val_precision: 0.7276 - val_recall: 0.9887 - val_auc: 0.9552\n",
            "Epoch 1407/2000\n",
            "10/10 [==============================] - 4s 421ms/step - loss: 0.1625 - accuracy: 0.9374 - precision: 0.9333 - recall: 0.9422 - auc: 0.9837 - val_loss: 0.7287 - val_accuracy: 0.5980 - val_precision: 0.8718 - val_recall: 0.2294 - val_auc: 0.8144\n",
            "Epoch 1408/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1810 - accuracy: 0.9283 - precision: 0.9243 - recall: 0.9330 - auc: 0.9800 - val_loss: 0.5985 - val_accuracy: 0.6740 - val_precision: 0.9007 - val_recall: 0.3909 - val_auc: 0.8831\n",
            "Epoch 1409/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1715 - accuracy: 0.9319 - precision: 0.9269 - recall: 0.9379 - auc: 0.9817 - val_loss: 0.4640 - val_accuracy: 0.7355 - val_precision: 0.9244 - val_recall: 0.5128 - val_auc: 0.9208\n",
            "Epoch 1410/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1828 - accuracy: 0.9279 - precision: 0.9229 - recall: 0.9339 - auc: 0.9793 - val_loss: 0.3561 - val_accuracy: 0.8144 - val_precision: 0.9217 - val_recall: 0.6870 - val_auc: 0.9390\n",
            "Epoch 1411/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1750 - accuracy: 0.9305 - precision: 0.9259 - recall: 0.9361 - auc: 0.9810 - val_loss: 0.3017 - val_accuracy: 0.8641 - val_precision: 0.9085 - val_recall: 0.8095 - val_auc: 0.9483\n",
            "Epoch 1412/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1626 - accuracy: 0.9363 - precision: 0.9313 - recall: 0.9422 - auc: 0.9834 - val_loss: 0.3493 - val_accuracy: 0.8627 - val_precision: 0.8008 - val_recall: 0.9655 - val_auc: 0.9497\n",
            "Epoch 1413/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1392 - accuracy: 0.9460 - precision: 0.9436 - recall: 0.9488 - auc: 0.9878 - val_loss: 0.4605 - val_accuracy: 0.8288 - val_precision: 0.7522 - val_recall: 0.9803 - val_auc: 0.9425\n",
            "Epoch 1414/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1205 - accuracy: 0.9539 - precision: 0.9537 - recall: 0.9542 - auc: 0.9907 - val_loss: 0.6113 - val_accuracy: 0.7945 - val_precision: 0.7118 - val_recall: 0.9893 - val_auc: 0.9407\n",
            "Epoch 1415/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1040 - accuracy: 0.9604 - precision: 0.9619 - recall: 0.9588 - auc: 0.9931 - val_loss: 0.7282 - val_accuracy: 0.7672 - val_precision: 0.6843 - val_recall: 0.9919 - val_auc: 0.9341\n",
            "Epoch 1416/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.0992 - accuracy: 0.9623 - precision: 0.9622 - recall: 0.9625 - auc: 0.9936 - val_loss: 0.8590 - val_accuracy: 0.7392 - val_precision: 0.6582 - val_recall: 0.9949 - val_auc: 0.9358\n",
            "Epoch 1417/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1003 - accuracy: 0.9616 - precision: 0.9633 - recall: 0.9599 - auc: 0.9934 - val_loss: 0.9915 - val_accuracy: 0.7064 - val_precision: 0.6304 - val_recall: 0.9970 - val_auc: 0.9326\n",
            "Epoch 1418/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1014 - accuracy: 0.9616 - precision: 0.9626 - recall: 0.9604 - auc: 0.9932 - val_loss: 0.7831 - val_accuracy: 0.7579 - val_precision: 0.6762 - val_recall: 0.9893 - val_auc: 0.9287\n",
            "Epoch 1419/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1873 - accuracy: 0.9273 - precision: 0.9196 - recall: 0.9365 - auc: 0.9784 - val_loss: 0.4006 - val_accuracy: 0.8441 - val_precision: 0.7732 - val_recall: 0.9737 - val_auc: 0.9427\n",
            "Epoch 1420/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1579 - accuracy: 0.9391 - precision: 0.9357 - recall: 0.9429 - auc: 0.9845 - val_loss: 0.4092 - val_accuracy: 0.8460 - val_precision: 0.7828 - val_recall: 0.9576 - val_auc: 0.9319\n",
            "Epoch 1421/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1533 - accuracy: 0.9400 - precision: 0.9361 - recall: 0.9445 - auc: 0.9852 - val_loss: 0.4237 - val_accuracy: 0.8406 - val_precision: 0.7695 - val_recall: 0.9723 - val_auc: 0.9378\n",
            "Epoch 1422/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1188 - accuracy: 0.9550 - precision: 0.9550 - recall: 0.9551 - auc: 0.9910 - val_loss: 0.6026 - val_accuracy: 0.7893 - val_precision: 0.7064 - val_recall: 0.9901 - val_auc: 0.9402\n",
            "Epoch 1423/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1264 - accuracy: 0.9520 - precision: 0.9514 - recall: 0.9526 - auc: 0.9898 - val_loss: 0.5830 - val_accuracy: 0.7911 - val_precision: 0.7083 - val_recall: 0.9895 - val_auc: 0.9424\n",
            "Epoch 1424/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1023 - accuracy: 0.9615 - precision: 0.9632 - recall: 0.9598 - auc: 0.9932 - val_loss: 0.8354 - val_accuracy: 0.7335 - val_precision: 0.6532 - val_recall: 0.9954 - val_auc: 0.9383\n",
            "Epoch 1425/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1172 - accuracy: 0.9555 - precision: 0.9532 - recall: 0.9580 - auc: 0.9911 - val_loss: 0.7743 - val_accuracy: 0.7477 - val_precision: 0.6657 - val_recall: 0.9951 - val_auc: 0.9383\n",
            "Epoch 1426/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1004 - accuracy: 0.9619 - precision: 0.9631 - recall: 0.9605 - auc: 0.9935 - val_loss: 0.7957 - val_accuracy: 0.7543 - val_precision: 0.6719 - val_recall: 0.9939 - val_auc: 0.9388\n",
            "Epoch 1427/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1033 - accuracy: 0.9608 - precision: 0.9614 - recall: 0.9601 - auc: 0.9930 - val_loss: 0.8689 - val_accuracy: 0.7388 - val_precision: 0.6578 - val_recall: 0.9951 - val_auc: 0.9353\n",
            "Epoch 1428/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.0969 - accuracy: 0.9630 - precision: 0.9637 - recall: 0.9623 - auc: 0.9939 - val_loss: 0.9129 - val_accuracy: 0.7319 - val_precision: 0.6518 - val_recall: 0.9957 - val_auc: 0.9353\n",
            "Epoch 1429/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1009 - accuracy: 0.9618 - precision: 0.9629 - recall: 0.9606 - auc: 0.9933 - val_loss: 0.9123 - val_accuracy: 0.7245 - val_precision: 0.6455 - val_recall: 0.9956 - val_auc: 0.9286\n",
            "Epoch 1430/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1103 - accuracy: 0.9579 - precision: 0.9578 - recall: 0.9581 - auc: 0.9922 - val_loss: 0.7301 - val_accuracy: 0.7643 - val_precision: 0.6815 - val_recall: 0.9921 - val_auc: 0.9382\n",
            "Epoch 1431/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1021 - accuracy: 0.9611 - precision: 0.9626 - recall: 0.9595 - auc: 0.9932 - val_loss: 0.8755 - val_accuracy: 0.7336 - val_precision: 0.6532 - val_recall: 0.9953 - val_auc: 0.9373\n",
            "Epoch 1432/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.0966 - accuracy: 0.9625 - precision: 0.9631 - recall: 0.9620 - auc: 0.9939 - val_loss: 0.8193 - val_accuracy: 0.7519 - val_precision: 0.6695 - val_recall: 0.9943 - val_auc: 0.9404\n",
            "Epoch 1433/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1019 - accuracy: 0.9610 - precision: 0.9630 - recall: 0.9589 - auc: 0.9932 - val_loss: 0.8777 - val_accuracy: 0.7330 - val_precision: 0.6527 - val_recall: 0.9959 - val_auc: 0.9405\n",
            "Epoch 1434/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1062 - accuracy: 0.9594 - precision: 0.9589 - recall: 0.9600 - auc: 0.9926 - val_loss: 0.8173 - val_accuracy: 0.7498 - val_precision: 0.6676 - val_recall: 0.9949 - val_auc: 0.9397\n",
            "Epoch 1435/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.0953 - accuracy: 0.9637 - precision: 0.9651 - recall: 0.9622 - auc: 0.9940 - val_loss: 0.9606 - val_accuracy: 0.7225 - val_precision: 0.6437 - val_recall: 0.9962 - val_auc: 0.9325\n",
            "Epoch 1436/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1180 - accuracy: 0.9552 - precision: 0.9558 - recall: 0.9545 - auc: 0.9909 - val_loss: 0.6715 - val_accuracy: 0.7743 - val_precision: 0.6913 - val_recall: 0.9912 - val_auc: 0.9345\n",
            "Epoch 1437/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1040 - accuracy: 0.9605 - precision: 0.9622 - recall: 0.9587 - auc: 0.9932 - val_loss: 0.7096 - val_accuracy: 0.7749 - val_precision: 0.6915 - val_recall: 0.9923 - val_auc: 0.9417\n",
            "Epoch 1438/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1201 - accuracy: 0.9544 - precision: 0.9517 - recall: 0.9575 - auc: 0.9907 - val_loss: 0.7859 - val_accuracy: 0.7414 - val_precision: 0.6600 - val_recall: 0.9954 - val_auc: 0.9371\n",
            "Epoch 1439/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1078 - accuracy: 0.9594 - precision: 0.9583 - recall: 0.9607 - auc: 0.9927 - val_loss: 0.8545 - val_accuracy: 0.7398 - val_precision: 0.6586 - val_recall: 0.9951 - val_auc: 0.9340\n",
            "Epoch 1440/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1171 - accuracy: 0.9557 - precision: 0.9552 - recall: 0.9562 - auc: 0.9912 - val_loss: 0.5702 - val_accuracy: 0.7464 - val_precision: 0.8664 - val_recall: 0.5825 - val_auc: 0.8847\n",
            "Epoch 1441/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1590 - accuracy: 0.9383 - precision: 0.9335 - recall: 0.9439 - auc: 0.9843 - val_loss: 0.3869 - val_accuracy: 0.8167 - val_precision: 0.9143 - val_recall: 0.6988 - val_auc: 0.9352\n",
            "Epoch 1442/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1313 - accuracy: 0.9494 - precision: 0.9478 - recall: 0.9513 - auc: 0.9892 - val_loss: 0.6402 - val_accuracy: 0.7910 - val_precision: 0.7084 - val_recall: 0.9890 - val_auc: 0.9357\n",
            "Epoch 1443/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1172 - accuracy: 0.9550 - precision: 0.9560 - recall: 0.9540 - auc: 0.9912 - val_loss: 0.7622 - val_accuracy: 0.7566 - val_precision: 0.6739 - val_recall: 0.9942 - val_auc: 0.9373\n",
            "Epoch 1444/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0991 - accuracy: 0.9622 - precision: 0.9639 - recall: 0.9603 - auc: 0.9936 - val_loss: 0.9466 - val_accuracy: 0.7177 - val_precision: 0.6397 - val_recall: 0.9965 - val_auc: 0.9329\n",
            "Epoch 1445/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1025 - accuracy: 0.9610 - precision: 0.9621 - recall: 0.9597 - auc: 0.9932 - val_loss: 0.8091 - val_accuracy: 0.7441 - val_precision: 0.6626 - val_recall: 0.9947 - val_auc: 0.9343\n",
            "Epoch 1446/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1066 - accuracy: 0.9599 - precision: 0.9614 - recall: 0.9582 - auc: 0.9927 - val_loss: 0.9274 - val_accuracy: 0.7171 - val_precision: 0.6391 - val_recall: 0.9968 - val_auc: 0.9362\n",
            "Epoch 1447/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.0973 - accuracy: 0.9627 - precision: 0.9628 - recall: 0.9626 - auc: 0.9938 - val_loss: 0.8207 - val_accuracy: 0.7516 - val_precision: 0.6692 - val_recall: 0.9947 - val_auc: 0.9424\n",
            "Epoch 1448/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0973 - accuracy: 0.9628 - precision: 0.9659 - recall: 0.9596 - auc: 0.9937 - val_loss: 1.0723 - val_accuracy: 0.6920 - val_precision: 0.6191 - val_recall: 0.9974 - val_auc: 0.9276\n",
            "Epoch 1449/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.0977 - accuracy: 0.9627 - precision: 0.9649 - recall: 0.9603 - auc: 0.9938 - val_loss: 0.9394 - val_accuracy: 0.7208 - val_precision: 0.6422 - val_recall: 0.9968 - val_auc: 0.9398\n",
            "Epoch 1450/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.0992 - accuracy: 0.9621 - precision: 0.9637 - recall: 0.9603 - auc: 0.9935 - val_loss: 0.4197 - val_accuracy: 0.8467 - val_precision: 0.7940 - val_recall: 0.9361 - val_auc: 0.9298\n",
            "Epoch 1451/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1289 - accuracy: 0.9518 - precision: 0.9509 - recall: 0.9527 - auc: 0.9893 - val_loss: 0.8223 - val_accuracy: 0.7260 - val_precision: 0.6467 - val_recall: 0.9958 - val_auc: 0.9356\n",
            "Epoch 1452/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.0986 - accuracy: 0.9624 - precision: 0.9635 - recall: 0.9612 - auc: 0.9937 - val_loss: 0.4046 - val_accuracy: 0.8517 - val_precision: 0.7748 - val_recall: 0.9916 - val_auc: 0.9826\n",
            "Epoch 1453/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1050 - accuracy: 0.9599 - precision: 0.9587 - recall: 0.9612 - auc: 0.9928 - val_loss: 0.8875 - val_accuracy: 0.7259 - val_precision: 0.6466 - val_recall: 0.9958 - val_auc: 0.9356\n",
            "Epoch 1454/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0964 - accuracy: 0.9630 - precision: 0.9644 - recall: 0.9615 - auc: 0.9939 - val_loss: 1.0697 - val_accuracy: 0.6907 - val_precision: 0.6181 - val_recall: 0.9974 - val_auc: 0.9258\n",
            "Epoch 1455/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1085 - accuracy: 0.9587 - precision: 0.9595 - recall: 0.9579 - auc: 0.9923 - val_loss: 0.8333 - val_accuracy: 0.7336 - val_precision: 0.6531 - val_recall: 0.9959 - val_auc: 0.9378\n",
            "Epoch 1456/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.0948 - accuracy: 0.9641 - precision: 0.9660 - recall: 0.9621 - auc: 0.9940 - val_loss: 0.9546 - val_accuracy: 0.7092 - val_precision: 0.6327 - val_recall: 0.9972 - val_auc: 0.9382\n",
            "Epoch 1457/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1024 - accuracy: 0.9607 - precision: 0.9603 - recall: 0.9612 - auc: 0.9932 - val_loss: 0.9575 - val_accuracy: 0.7096 - val_precision: 0.6330 - val_recall: 0.9970 - val_auc: 0.9316\n",
            "Epoch 1458/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0945 - accuracy: 0.9639 - precision: 0.9659 - recall: 0.9618 - auc: 0.9942 - val_loss: 0.9112 - val_accuracy: 0.7251 - val_precision: 0.6459 - val_recall: 0.9965 - val_auc: 0.9376\n",
            "Epoch 1459/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1393 - accuracy: 0.9477 - precision: 0.9449 - recall: 0.9509 - auc: 0.9876 - val_loss: 0.6457 - val_accuracy: 0.7798 - val_precision: 0.6971 - val_recall: 0.9895 - val_auc: 0.9330\n",
            "Epoch 1460/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1182 - accuracy: 0.9549 - precision: 0.9575 - recall: 0.9522 - auc: 0.9912 - val_loss: 0.8026 - val_accuracy: 0.7554 - val_precision: 0.6731 - val_recall: 0.9929 - val_auc: 0.9229\n",
            "Epoch 1461/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1473 - accuracy: 0.9444 - precision: 0.9413 - recall: 0.9480 - auc: 0.9863 - val_loss: 0.6139 - val_accuracy: 0.7890 - val_precision: 0.7063 - val_recall: 0.9894 - val_auc: 0.9327\n",
            "Epoch 1462/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1062 - accuracy: 0.9602 - precision: 0.9607 - recall: 0.9596 - auc: 0.9930 - val_loss: 0.8370 - val_accuracy: 0.7340 - val_precision: 0.6537 - val_recall: 0.9951 - val_auc: 0.9325\n",
            "Epoch 1463/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1004 - accuracy: 0.9617 - precision: 0.9631 - recall: 0.9602 - auc: 0.9934 - val_loss: 0.9966 - val_accuracy: 0.7052 - val_precision: 0.6296 - val_recall: 0.9968 - val_auc: 0.9278\n",
            "Epoch 1464/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1229 - accuracy: 0.9530 - precision: 0.9513 - recall: 0.9549 - auc: 0.9903 - val_loss: 0.8272 - val_accuracy: 0.7398 - val_precision: 0.6586 - val_recall: 0.9953 - val_auc: 0.9340\n",
            "Epoch 1465/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1057 - accuracy: 0.9595 - precision: 0.9598 - recall: 0.9592 - auc: 0.9928 - val_loss: 0.9267 - val_accuracy: 0.7260 - val_precision: 0.6468 - val_recall: 0.9952 - val_auc: 0.9295\n",
            "Epoch 1466/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0975 - accuracy: 0.9625 - precision: 0.9632 - recall: 0.9618 - auc: 0.9938 - val_loss: 0.8715 - val_accuracy: 0.7433 - val_precision: 0.6618 - val_recall: 0.9947 - val_auc: 0.9363\n",
            "Epoch 1467/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.0951 - accuracy: 0.9638 - precision: 0.9641 - recall: 0.9634 - auc: 0.9940 - val_loss: 1.1899 - val_accuracy: 0.6722 - val_precision: 0.6042 - val_recall: 0.9974 - val_auc: 0.9145\n",
            "Epoch 1468/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1065 - accuracy: 0.9593 - precision: 0.9608 - recall: 0.9578 - auc: 0.9926 - val_loss: 0.9930 - val_accuracy: 0.7066 - val_precision: 0.6306 - val_recall: 0.9967 - val_auc: 0.9241\n",
            "Epoch 1469/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0941 - accuracy: 0.9641 - precision: 0.9664 - recall: 0.9617 - auc: 0.9942 - val_loss: 1.0000 - val_accuracy: 0.7074 - val_precision: 0.6313 - val_recall: 0.9971 - val_auc: 0.9304\n",
            "Epoch 1470/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1180 - accuracy: 0.9556 - precision: 0.9537 - recall: 0.9576 - auc: 0.9909 - val_loss: 0.8524 - val_accuracy: 0.7254 - val_precision: 0.6462 - val_recall: 0.9956 - val_auc: 0.9284\n",
            "Epoch 1471/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.0979 - accuracy: 0.9626 - precision: 0.9651 - recall: 0.9600 - auc: 0.9938 - val_loss: 1.0157 - val_accuracy: 0.6983 - val_precision: 0.6241 - val_recall: 0.9966 - val_auc: 0.9221\n",
            "Epoch 1472/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0968 - accuracy: 0.9628 - precision: 0.9652 - recall: 0.9602 - auc: 0.9938 - val_loss: 0.9000 - val_accuracy: 0.7253 - val_precision: 0.6462 - val_recall: 0.9952 - val_auc: 0.9317\n",
            "Epoch 1473/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1250 - accuracy: 0.9523 - precision: 0.9513 - recall: 0.9534 - auc: 0.9900 - val_loss: 0.2153 - val_accuracy: 0.9131 - val_precision: 0.8809 - val_recall: 0.9553 - val_auc: 0.9754\n",
            "Epoch 1474/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1333 - accuracy: 0.9482 - precision: 0.9466 - recall: 0.9501 - auc: 0.9888 - val_loss: 0.3487 - val_accuracy: 0.8423 - val_precision: 0.9153 - val_recall: 0.7542 - val_auc: 0.9433\n",
            "Epoch 1475/2000\n",
            "10/10 [==============================] - 4s 420ms/step - loss: 0.1164 - accuracy: 0.9555 - precision: 0.9552 - recall: 0.9558 - auc: 0.9913 - val_loss: 0.2258 - val_accuracy: 0.9126 - val_precision: 0.8941 - val_recall: 0.9361 - val_auc: 0.9712\n",
            "Epoch 1476/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1048 - accuracy: 0.9598 - precision: 0.9616 - recall: 0.9579 - auc: 0.9929 - val_loss: 0.7824 - val_accuracy: 0.7494 - val_precision: 0.6676 - val_recall: 0.9931 - val_auc: 0.9327\n",
            "Epoch 1477/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0972 - accuracy: 0.9630 - precision: 0.9636 - recall: 0.9623 - auc: 0.9938 - val_loss: 0.9532 - val_accuracy: 0.7120 - val_precision: 0.6351 - val_recall: 0.9963 - val_auc: 0.9295\n",
            "Epoch 1478/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.0956 - accuracy: 0.9637 - precision: 0.9651 - recall: 0.9621 - auc: 0.9940 - val_loss: 0.9907 - val_accuracy: 0.7052 - val_precision: 0.6296 - val_recall: 0.9963 - val_auc: 0.9253\n",
            "Epoch 1479/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1001 - accuracy: 0.9621 - precision: 0.9631 - recall: 0.9609 - auc: 0.9934 - val_loss: 0.8688 - val_accuracy: 0.7294 - val_precision: 0.6497 - val_recall: 0.9949 - val_auc: 0.9311\n",
            "Epoch 1480/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1896 - accuracy: 0.9268 - precision: 0.9176 - recall: 0.9378 - auc: 0.9780 - val_loss: 0.7635 - val_accuracy: 0.5787 - val_precision: 0.8505 - val_recall: 0.1907 - val_auc: 0.7924\n",
            "Epoch 1481/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1875 - accuracy: 0.9254 - precision: 0.9199 - recall: 0.9320 - auc: 0.9784 - val_loss: 0.5632 - val_accuracy: 0.6815 - val_precision: 0.8997 - val_recall: 0.4084 - val_auc: 0.8811\n",
            "Epoch 1482/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1814 - accuracy: 0.9277 - precision: 0.9189 - recall: 0.9383 - auc: 0.9796 - val_loss: 0.4317 - val_accuracy: 0.7910 - val_precision: 0.8960 - val_recall: 0.6583 - val_auc: 0.9194\n",
            "Epoch 1483/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1787 - accuracy: 0.9289 - precision: 0.9236 - recall: 0.9351 - auc: 0.9801 - val_loss: 0.3656 - val_accuracy: 0.8233 - val_precision: 0.9149 - val_recall: 0.7128 - val_auc: 0.9385\n",
            "Epoch 1484/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1731 - accuracy: 0.9314 - precision: 0.9264 - recall: 0.9373 - auc: 0.9813 - val_loss: 0.3296 - val_accuracy: 0.8453 - val_precision: 0.9020 - val_recall: 0.7747 - val_auc: 0.9405\n",
            "Epoch 1485/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1731 - accuracy: 0.9310 - precision: 0.9240 - recall: 0.9393 - auc: 0.9813 - val_loss: 0.3304 - val_accuracy: 0.8410 - val_precision: 0.9101 - val_recall: 0.7565 - val_auc: 0.9415\n",
            "Epoch 1486/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1737 - accuracy: 0.9308 - precision: 0.9252 - recall: 0.9375 - auc: 0.9812 - val_loss: 0.3155 - val_accuracy: 0.8554 - val_precision: 0.8997 - val_recall: 0.7998 - val_auc: 0.9436\n",
            "Epoch 1487/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1730 - accuracy: 0.9309 - precision: 0.9242 - recall: 0.9388 - auc: 0.9814 - val_loss: 0.3183 - val_accuracy: 0.8564 - val_precision: 0.8810 - val_recall: 0.8241 - val_auc: 0.9383\n",
            "Epoch 1488/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1726 - accuracy: 0.9316 - precision: 0.9245 - recall: 0.9400 - auc: 0.9814 - val_loss: 0.2938 - val_accuracy: 0.8771 - val_precision: 0.8698 - val_recall: 0.8869 - val_auc: 0.9463\n",
            "Epoch 1489/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1716 - accuracy: 0.9320 - precision: 0.9259 - recall: 0.9390 - auc: 0.9816 - val_loss: 0.3095 - val_accuracy: 0.8726 - val_precision: 0.8483 - val_recall: 0.9072 - val_auc: 0.9417\n",
            "Epoch 1490/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1711 - accuracy: 0.9317 - precision: 0.9241 - recall: 0.9407 - auc: 0.9817 - val_loss: 0.3024 - val_accuracy: 0.8741 - val_precision: 0.8674 - val_recall: 0.8831 - val_auc: 0.9434\n",
            "Epoch 1491/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1711 - accuracy: 0.9316 - precision: 0.9257 - recall: 0.9387 - auc: 0.9817 - val_loss: 0.3078 - val_accuracy: 0.8684 - val_precision: 0.8830 - val_recall: 0.8492 - val_auc: 0.9428\n",
            "Epoch 1492/2000\n",
            "10/10 [==============================] - 5s 483ms/step - loss: 0.1735 - accuracy: 0.9308 - precision: 0.9254 - recall: 0.9372 - auc: 0.9812 - val_loss: 0.3121 - val_accuracy: 0.8752 - val_precision: 0.8320 - val_recall: 0.9403 - val_auc: 0.9470\n",
            "Epoch 1493/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1736 - accuracy: 0.9312 - precision: 0.9258 - recall: 0.9376 - auc: 0.9812 - val_loss: 0.3072 - val_accuracy: 0.8765 - val_precision: 0.8438 - val_recall: 0.9240 - val_auc: 0.9454\n",
            "Epoch 1494/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1721 - accuracy: 0.9316 - precision: 0.9276 - recall: 0.9363 - auc: 0.9815 - val_loss: 0.3394 - val_accuracy: 0.8671 - val_precision: 0.8137 - val_recall: 0.9522 - val_auc: 0.9436\n",
            "Epoch 1495/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1757 - accuracy: 0.9303 - precision: 0.9242 - recall: 0.9376 - auc: 0.9807 - val_loss: 0.3442 - val_accuracy: 0.8628 - val_precision: 0.8032 - val_recall: 0.9610 - val_auc: 0.9471\n",
            "Epoch 1496/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1667 - accuracy: 0.9343 - precision: 0.9289 - recall: 0.9406 - auc: 0.9826 - val_loss: 0.3695 - val_accuracy: 0.8538 - val_precision: 0.7897 - val_recall: 0.9644 - val_auc: 0.9425\n",
            "Epoch 1497/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1683 - accuracy: 0.9333 - precision: 0.9278 - recall: 0.9398 - auc: 0.9823 - val_loss: 0.3957 - val_accuracy: 0.8429 - val_precision: 0.7726 - val_recall: 0.9719 - val_auc: 0.9412\n",
            "Epoch 1498/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1669 - accuracy: 0.9344 - precision: 0.9289 - recall: 0.9408 - auc: 0.9825 - val_loss: 0.4297 - val_accuracy: 0.8341 - val_precision: 0.7605 - val_recall: 0.9752 - val_auc: 0.9367\n",
            "Epoch 1499/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1649 - accuracy: 0.9346 - precision: 0.9312 - recall: 0.9386 - auc: 0.9830 - val_loss: 0.3718 - val_accuracy: 0.8577 - val_precision: 0.7959 - val_recall: 0.9620 - val_auc: 0.9415\n",
            "Epoch 1500/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1717 - accuracy: 0.9323 - precision: 0.9272 - recall: 0.9382 - auc: 0.9816 - val_loss: 0.3780 - val_accuracy: 0.8494 - val_precision: 0.7813 - val_recall: 0.9703 - val_auc: 0.9447\n",
            "Epoch 1501/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1650 - accuracy: 0.9350 - precision: 0.9293 - recall: 0.9416 - auc: 0.9830 - val_loss: 0.3749 - val_accuracy: 0.8550 - val_precision: 0.7887 - val_recall: 0.9697 - val_auc: 0.9468\n",
            "Epoch 1502/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1665 - accuracy: 0.9343 - precision: 0.9285 - recall: 0.9412 - auc: 0.9826 - val_loss: 0.3413 - val_accuracy: 0.8683 - val_precision: 0.8229 - val_recall: 0.9385 - val_auc: 0.9408\n",
            "Epoch 1503/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1671 - accuracy: 0.9334 - precision: 0.9305 - recall: 0.9368 - auc: 0.9827 - val_loss: 0.3947 - val_accuracy: 0.8530 - val_precision: 0.7907 - val_recall: 0.9600 - val_auc: 0.9374\n",
            "Epoch 1504/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1626 - accuracy: 0.9357 - precision: 0.9320 - recall: 0.9400 - auc: 0.9834 - val_loss: 0.4485 - val_accuracy: 0.8345 - val_precision: 0.7601 - val_recall: 0.9772 - val_auc: 0.9364\n",
            "Epoch 1505/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1663 - accuracy: 0.9347 - precision: 0.9298 - recall: 0.9404 - auc: 0.9827 - val_loss: 0.4100 - val_accuracy: 0.8451 - val_precision: 0.7792 - val_recall: 0.9630 - val_auc: 0.9359\n",
            "Epoch 1506/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1596 - accuracy: 0.9372 - precision: 0.9330 - recall: 0.9420 - auc: 0.9840 - val_loss: 0.3912 - val_accuracy: 0.8531 - val_precision: 0.7898 - val_recall: 0.9623 - val_auc: 0.9408\n",
            "Epoch 1507/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1586 - accuracy: 0.9373 - precision: 0.9323 - recall: 0.9430 - auc: 0.9842 - val_loss: 0.4455 - val_accuracy: 0.8350 - val_precision: 0.7603 - val_recall: 0.9784 - val_auc: 0.9418\n",
            "Epoch 1508/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1577 - accuracy: 0.9382 - precision: 0.9353 - recall: 0.9415 - auc: 0.9844 - val_loss: 0.4078 - val_accuracy: 0.8409 - val_precision: 0.7679 - val_recall: 0.9771 - val_auc: 0.9481\n",
            "Epoch 1509/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1612 - accuracy: 0.9363 - precision: 0.9341 - recall: 0.9389 - auc: 0.9838 - val_loss: 0.3938 - val_accuracy: 0.8453 - val_precision: 0.7729 - val_recall: 0.9778 - val_auc: 0.9538\n",
            "Epoch 1510/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1355 - accuracy: 0.9485 - precision: 0.9464 - recall: 0.9508 - auc: 0.9884 - val_loss: 0.4957 - val_accuracy: 0.8138 - val_precision: 0.7344 - val_recall: 0.9832 - val_auc: 0.9436\n",
            "Epoch 1511/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1313 - accuracy: 0.9495 - precision: 0.9479 - recall: 0.9514 - auc: 0.9891 - val_loss: 0.4321 - val_accuracy: 0.8443 - val_precision: 0.7724 - val_recall: 0.9761 - val_auc: 0.9505\n",
            "Epoch 1512/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1088 - accuracy: 0.9590 - precision: 0.9596 - recall: 0.9583 - auc: 0.9923 - val_loss: 0.5043 - val_accuracy: 0.8295 - val_precision: 0.7527 - val_recall: 0.9813 - val_auc: 0.9472\n",
            "Epoch 1513/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1123 - accuracy: 0.9570 - precision: 0.9585 - recall: 0.9553 - auc: 0.9918 - val_loss: 0.5031 - val_accuracy: 0.8277 - val_precision: 0.7512 - val_recall: 0.9797 - val_auc: 0.9432\n",
            "Epoch 1514/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1040 - accuracy: 0.9605 - precision: 0.9600 - recall: 0.9610 - auc: 0.9930 - val_loss: 0.6190 - val_accuracy: 0.8026 - val_precision: 0.7207 - val_recall: 0.9879 - val_auc: 0.9412\n",
            "Epoch 1515/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1226 - accuracy: 0.9530 - precision: 0.9526 - recall: 0.9535 - auc: 0.9903 - val_loss: 0.5114 - val_accuracy: 0.8241 - val_precision: 0.7467 - val_recall: 0.9809 - val_auc: 0.9406\n",
            "Epoch 1516/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1021 - accuracy: 0.9612 - precision: 0.9635 - recall: 0.9588 - auc: 0.9933 - val_loss: 0.6719 - val_accuracy: 0.7884 - val_precision: 0.7054 - val_recall: 0.9901 - val_auc: 0.9411\n",
            "Epoch 1517/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.0993 - accuracy: 0.9625 - precision: 0.9627 - recall: 0.9624 - auc: 0.9935 - val_loss: 0.6995 - val_accuracy: 0.7835 - val_precision: 0.7007 - val_recall: 0.9894 - val_auc: 0.9361\n",
            "Epoch 1518/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1031 - accuracy: 0.9604 - precision: 0.9610 - recall: 0.9598 - auc: 0.9931 - val_loss: 0.7355 - val_accuracy: 0.7738 - val_precision: 0.6905 - val_recall: 0.9921 - val_auc: 0.9398\n",
            "Epoch 1519/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0953 - accuracy: 0.9637 - precision: 0.9649 - recall: 0.9624 - auc: 0.9940 - val_loss: 0.8590 - val_accuracy: 0.7426 - val_precision: 0.6612 - val_recall: 0.9948 - val_auc: 0.9364\n",
            "Epoch 1520/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.0965 - accuracy: 0.9634 - precision: 0.9639 - recall: 0.9630 - auc: 0.9938 - val_loss: 0.9278 - val_accuracy: 0.7279 - val_precision: 0.6483 - val_recall: 0.9962 - val_auc: 0.9362\n",
            "Epoch 1521/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1180 - accuracy: 0.9554 - precision: 0.9566 - recall: 0.9542 - auc: 0.9909 - val_loss: 0.8081 - val_accuracy: 0.7430 - val_precision: 0.6616 - val_recall: 0.9946 - val_auc: 0.9353\n",
            "Epoch 1522/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.0973 - accuracy: 0.9630 - precision: 0.9646 - recall: 0.9612 - auc: 0.9939 - val_loss: 0.8738 - val_accuracy: 0.7394 - val_precision: 0.6584 - val_recall: 0.9946 - val_auc: 0.9329\n",
            "Epoch 1523/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1175 - accuracy: 0.9551 - precision: 0.9553 - recall: 0.9549 - auc: 0.9911 - val_loss: 0.7214 - val_accuracy: 0.7488 - val_precision: 0.6668 - val_recall: 0.9943 - val_auc: 0.9410\n",
            "Epoch 1524/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1549 - accuracy: 0.9403 - precision: 0.9339 - recall: 0.9476 - auc: 0.9851 - val_loss: 0.6356 - val_accuracy: 0.7917 - val_precision: 0.7089 - val_recall: 0.9897 - val_auc: 0.9365\n",
            "Epoch 1525/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1209 - accuracy: 0.9540 - precision: 0.9552 - recall: 0.9528 - auc: 0.9906 - val_loss: 0.6673 - val_accuracy: 0.7955 - val_precision: 0.7132 - val_recall: 0.9883 - val_auc: 0.9366\n",
            "Epoch 1526/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1026 - accuracy: 0.9604 - precision: 0.9607 - recall: 0.9602 - auc: 0.9933 - val_loss: 0.8129 - val_accuracy: 0.7622 - val_precision: 0.6794 - val_recall: 0.9929 - val_auc: 0.9337\n",
            "Epoch 1527/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1032 - accuracy: 0.9606 - precision: 0.9612 - recall: 0.9599 - auc: 0.9931 - val_loss: 1.0065 - val_accuracy: 0.7118 - val_precision: 0.6348 - val_recall: 0.9965 - val_auc: 0.9299\n",
            "Epoch 1528/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1155 - accuracy: 0.9560 - precision: 0.9554 - recall: 0.9567 - auc: 0.9914 - val_loss: 0.7970 - val_accuracy: 0.7443 - val_precision: 0.6627 - val_recall: 0.9946 - val_auc: 0.9366\n",
            "Epoch 1529/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0996 - accuracy: 0.9626 - precision: 0.9650 - recall: 0.9600 - auc: 0.9936 - val_loss: 1.0177 - val_accuracy: 0.7013 - val_precision: 0.6264 - val_recall: 0.9969 - val_auc: 0.9325\n",
            "Epoch 1530/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1014 - accuracy: 0.9613 - precision: 0.9623 - recall: 0.9601 - auc: 0.9933 - val_loss: 0.9848 - val_accuracy: 0.7090 - val_precision: 0.6326 - val_recall: 0.9964 - val_auc: 0.9334\n",
            "Epoch 1531/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0954 - accuracy: 0.9639 - precision: 0.9663 - recall: 0.9613 - auc: 0.9940 - val_loss: 1.1463 - val_accuracy: 0.6756 - val_precision: 0.6067 - val_recall: 0.9979 - val_auc: 0.9254\n",
            "Epoch 1532/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.0984 - accuracy: 0.9623 - precision: 0.9642 - recall: 0.9602 - auc: 0.9937 - val_loss: 1.0584 - val_accuracy: 0.6921 - val_precision: 0.6193 - val_recall: 0.9969 - val_auc: 0.9246\n",
            "Epoch 1533/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1233 - accuracy: 0.9536 - precision: 0.9526 - recall: 0.9547 - auc: 0.9902 - val_loss: 0.8437 - val_accuracy: 0.7264 - val_precision: 0.6471 - val_recall: 0.9956 - val_auc: 0.9328\n",
            "Epoch 1534/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.0971 - accuracy: 0.9629 - precision: 0.9636 - recall: 0.9621 - auc: 0.9939 - val_loss: 1.0295 - val_accuracy: 0.6974 - val_precision: 0.6234 - val_recall: 0.9969 - val_auc: 0.9307\n",
            "Epoch 1535/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.0964 - accuracy: 0.9630 - precision: 0.9646 - recall: 0.9613 - auc: 0.9939 - val_loss: 0.9742 - val_accuracy: 0.7089 - val_precision: 0.6326 - val_recall: 0.9958 - val_auc: 0.9274\n",
            "Epoch 1536/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1507 - accuracy: 0.9426 - precision: 0.9384 - recall: 0.9475 - auc: 0.9856 - val_loss: 0.7080 - val_accuracy: 0.7607 - val_precision: 0.6780 - val_recall: 0.9928 - val_auc: 0.9293\n",
            "Epoch 1537/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1069 - accuracy: 0.9594 - precision: 0.9600 - recall: 0.9587 - auc: 0.9927 - val_loss: 0.8687 - val_accuracy: 0.7427 - val_precision: 0.6613 - val_recall: 0.9949 - val_auc: 0.9311\n",
            "Epoch 1538/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0975 - accuracy: 0.9630 - precision: 0.9640 - recall: 0.9620 - auc: 0.9937 - val_loss: 0.9383 - val_accuracy: 0.7297 - val_precision: 0.6499 - val_recall: 0.9952 - val_auc: 0.9267\n",
            "Epoch 1539/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1022 - accuracy: 0.9608 - precision: 0.9626 - recall: 0.9589 - auc: 0.9932 - val_loss: 1.0298 - val_accuracy: 0.7023 - val_precision: 0.6272 - val_recall: 0.9970 - val_auc: 0.9280\n",
            "Epoch 1540/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.0930 - accuracy: 0.9647 - precision: 0.9668 - recall: 0.9625 - auc: 0.9943 - val_loss: 1.1212 - val_accuracy: 0.6867 - val_precision: 0.6150 - val_recall: 0.9977 - val_auc: 0.9254\n",
            "Epoch 1541/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1135 - accuracy: 0.9570 - precision: 0.9562 - recall: 0.9578 - auc: 0.9916 - val_loss: 0.9613 - val_accuracy: 0.7008 - val_precision: 0.6260 - val_recall: 0.9970 - val_auc: 0.9320\n",
            "Epoch 1542/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.0988 - accuracy: 0.9624 - precision: 0.9633 - recall: 0.9616 - auc: 0.9937 - val_loss: 0.9404 - val_accuracy: 0.7145 - val_precision: 0.6370 - val_recall: 0.9966 - val_auc: 0.9351\n",
            "Epoch 1543/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1056 - accuracy: 0.9597 - precision: 0.9580 - recall: 0.9615 - auc: 0.9927 - val_loss: 0.8091 - val_accuracy: 0.7454 - val_precision: 0.6639 - val_recall: 0.9938 - val_auc: 0.9307\n",
            "Epoch 1544/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0950 - accuracy: 0.9636 - precision: 0.9655 - recall: 0.9617 - auc: 0.9941 - val_loss: 0.9489 - val_accuracy: 0.7155 - val_precision: 0.6379 - val_recall: 0.9965 - val_auc: 0.9304\n",
            "Epoch 1545/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0934 - accuracy: 0.9640 - precision: 0.9656 - recall: 0.9624 - auc: 0.9943 - val_loss: 1.0361 - val_accuracy: 0.7008 - val_precision: 0.6260 - val_recall: 0.9973 - val_auc: 0.9299\n",
            "Epoch 1546/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.0965 - accuracy: 0.9632 - precision: 0.9645 - recall: 0.9618 - auc: 0.9938 - val_loss: 1.0048 - val_accuracy: 0.7032 - val_precision: 0.6279 - val_recall: 0.9972 - val_auc: 0.9350\n",
            "Epoch 1547/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1096 - accuracy: 0.9587 - precision: 0.9591 - recall: 0.9583 - auc: 0.9922 - val_loss: 0.9623 - val_accuracy: 0.7072 - val_precision: 0.6311 - val_recall: 0.9969 - val_auc: 0.9281\n",
            "Epoch 1548/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0938 - accuracy: 0.9645 - precision: 0.9654 - recall: 0.9635 - auc: 0.9942 - val_loss: 1.0769 - val_accuracy: 0.6900 - val_precision: 0.6176 - val_recall: 0.9974 - val_auc: 0.9237\n",
            "Epoch 1549/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0922 - accuracy: 0.9647 - precision: 0.9670 - recall: 0.9623 - auc: 0.9944 - val_loss: 1.0451 - val_accuracy: 0.6970 - val_precision: 0.6230 - val_recall: 0.9972 - val_auc: 0.9260\n",
            "Epoch 1550/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1033 - accuracy: 0.9610 - precision: 0.9621 - recall: 0.9597 - auc: 0.9930 - val_loss: 0.2937 - val_accuracy: 0.8826 - val_precision: 0.8213 - val_recall: 0.9779 - val_auc: 0.9745\n",
            "Epoch 1551/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1104 - accuracy: 0.9579 - precision: 0.9585 - recall: 0.9573 - auc: 0.9922 - val_loss: 0.8203 - val_accuracy: 0.7395 - val_precision: 0.6586 - val_recall: 0.9944 - val_auc: 0.9292\n",
            "Epoch 1552/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1106 - accuracy: 0.9584 - precision: 0.9566 - recall: 0.9604 - auc: 0.9920 - val_loss: 0.3246 - val_accuracy: 0.8589 - val_precision: 0.8926 - val_recall: 0.8160 - val_auc: 0.9413\n",
            "Epoch 1553/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1099 - accuracy: 0.9580 - precision: 0.9576 - recall: 0.9584 - auc: 0.9924 - val_loss: 0.8204 - val_accuracy: 0.7349 - val_precision: 0.6542 - val_recall: 0.9961 - val_auc: 0.9359\n",
            "Epoch 1554/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0958 - accuracy: 0.9638 - precision: 0.9644 - recall: 0.9630 - auc: 0.9940 - val_loss: 0.4354 - val_accuracy: 0.8216 - val_precision: 0.8902 - val_recall: 0.7335 - val_auc: 0.9239\n",
            "Epoch 1555/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1767 - accuracy: 0.9339 - precision: 0.9299 - recall: 0.9385 - auc: 0.9808 - val_loss: 0.6359 - val_accuracy: 0.7571 - val_precision: 0.6742 - val_recall: 0.9950 - val_auc: 0.9477\n",
            "Epoch 1556/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1215 - accuracy: 0.9542 - precision: 0.9561 - recall: 0.9522 - auc: 0.9906 - val_loss: 0.4466 - val_accuracy: 0.8348 - val_precision: 0.7550 - val_recall: 0.9912 - val_auc: 0.9721\n",
            "Epoch 1557/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1285 - accuracy: 0.9507 - precision: 0.9510 - recall: 0.9504 - auc: 0.9895 - val_loss: 0.6726 - val_accuracy: 0.7741 - val_precision: 0.6905 - val_recall: 0.9933 - val_auc: 0.9525\n",
            "Epoch 1558/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1074 - accuracy: 0.9588 - precision: 0.9622 - recall: 0.9552 - auc: 0.9926 - val_loss: 0.6901 - val_accuracy: 0.7861 - val_precision: 0.7021 - val_recall: 0.9937 - val_auc: 0.9553\n",
            "Epoch 1559/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1240 - accuracy: 0.9523 - precision: 0.9535 - recall: 0.9510 - auc: 0.9901 - val_loss: 0.7954 - val_accuracy: 0.7508 - val_precision: 0.6684 - val_recall: 0.9948 - val_auc: 0.9463\n",
            "Epoch 1560/2000\n",
            "10/10 [==============================] - 4s 403ms/step - loss: 0.1046 - accuracy: 0.9599 - precision: 0.9620 - recall: 0.9576 - auc: 0.9930 - val_loss: 0.9264 - val_accuracy: 0.7324 - val_precision: 0.6522 - val_recall: 0.9952 - val_auc: 0.9421\n",
            "Epoch 1561/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1365 - accuracy: 0.9492 - precision: 0.9492 - recall: 0.9492 - auc: 0.9882 - val_loss: 0.6396 - val_accuracy: 0.7684 - val_precision: 0.7323 - val_recall: 0.8458 - val_auc: 0.8695\n",
            "Epoch 1562/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.2304 - accuracy: 0.9101 - precision: 0.9031 - recall: 0.9188 - auc: 0.9686 - val_loss: 0.4083 - val_accuracy: 0.8115 - val_precision: 0.8293 - val_recall: 0.7842 - val_auc: 0.9055\n",
            "Epoch 1563/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1965 - accuracy: 0.9216 - precision: 0.9151 - recall: 0.9295 - auc: 0.9762 - val_loss: 0.3674 - val_accuracy: 0.8417 - val_precision: 0.8669 - val_recall: 0.8072 - val_auc: 0.9291\n",
            "Epoch 1564/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.1866 - accuracy: 0.9257 - precision: 0.9216 - recall: 0.9305 - auc: 0.9784 - val_loss: 0.3252 - val_accuracy: 0.8657 - val_precision: 0.8776 - val_recall: 0.8497 - val_auc: 0.9433\n",
            "Epoch 1565/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1815 - accuracy: 0.9276 - precision: 0.9233 - recall: 0.9327 - auc: 0.9795 - val_loss: 0.2988 - val_accuracy: 0.8779 - val_precision: 0.8826 - val_recall: 0.8717 - val_auc: 0.9504\n",
            "Epoch 1566/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1797 - accuracy: 0.9280 - precision: 0.9215 - recall: 0.9358 - auc: 0.9799 - val_loss: 0.3007 - val_accuracy: 0.8755 - val_precision: 0.8978 - val_recall: 0.8474 - val_auc: 0.9504\n",
            "Epoch 1567/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1773 - accuracy: 0.9296 - precision: 0.9242 - recall: 0.9359 - auc: 0.9805 - val_loss: 0.2773 - val_accuracy: 0.8842 - val_precision: 0.8929 - val_recall: 0.8730 - val_auc: 0.9544\n",
            "Epoch 1568/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1750 - accuracy: 0.9309 - precision: 0.9242 - recall: 0.9390 - auc: 0.9809 - val_loss: 0.2679 - val_accuracy: 0.8858 - val_precision: 0.9109 - val_recall: 0.8552 - val_auc: 0.9577\n",
            "Epoch 1569/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1764 - accuracy: 0.9301 - precision: 0.9243 - recall: 0.9369 - auc: 0.9806 - val_loss: 0.2369 - val_accuracy: 0.9067 - val_precision: 0.8850 - val_recall: 0.9349 - val_auc: 0.9660\n",
            "Epoch 1570/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1723 - accuracy: 0.9319 - precision: 0.9269 - recall: 0.9379 - auc: 0.9815 - val_loss: 0.2569 - val_accuracy: 0.8992 - val_precision: 0.8598 - val_recall: 0.9540 - val_auc: 0.9650\n",
            "Epoch 1571/2000\n",
            "10/10 [==============================] - 5s 496ms/step - loss: 0.1674 - accuracy: 0.9343 - precision: 0.9299 - recall: 0.9394 - auc: 0.9825 - val_loss: 0.3098 - val_accuracy: 0.8771 - val_precision: 0.8174 - val_recall: 0.9709 - val_auc: 0.9613\n",
            "Epoch 1572/2000\n",
            "10/10 [==============================] - 4s 423ms/step - loss: 0.1655 - accuracy: 0.9349 - precision: 0.9307 - recall: 0.9399 - auc: 0.9829 - val_loss: 0.2922 - val_accuracy: 0.8862 - val_precision: 0.8335 - val_recall: 0.9649 - val_auc: 0.9630\n",
            "Epoch 1573/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1543 - accuracy: 0.9398 - precision: 0.9362 - recall: 0.9440 - auc: 0.9850 - val_loss: 0.3452 - val_accuracy: 0.8667 - val_precision: 0.8008 - val_recall: 0.9761 - val_auc: 0.9610\n",
            "Epoch 1574/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1414 - accuracy: 0.9452 - precision: 0.9427 - recall: 0.9481 - auc: 0.9874 - val_loss: 0.4036 - val_accuracy: 0.8514 - val_precision: 0.7783 - val_recall: 0.9825 - val_auc: 0.9584\n",
            "Epoch 1575/2000\n",
            "10/10 [==============================] - 5s 482ms/step - loss: 0.1540 - accuracy: 0.9412 - precision: 0.9378 - recall: 0.9451 - auc: 0.9851 - val_loss: 0.3022 - val_accuracy: 0.8690 - val_precision: 0.8842 - val_recall: 0.8491 - val_auc: 0.9449\n",
            "Epoch 1576/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1944 - accuracy: 0.9228 - precision: 0.9161 - recall: 0.9308 - auc: 0.9769 - val_loss: 0.4109 - val_accuracy: 0.7962 - val_precision: 0.9234 - val_recall: 0.6459 - val_auc: 0.9365\n",
            "Epoch 1577/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1772 - accuracy: 0.9303 - precision: 0.9252 - recall: 0.9363 - auc: 0.9804 - val_loss: 0.3427 - val_accuracy: 0.8489 - val_precision: 0.8976 - val_recall: 0.7876 - val_auc: 0.9403\n",
            "Epoch 1578/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1749 - accuracy: 0.9306 - precision: 0.9263 - recall: 0.9356 - auc: 0.9809 - val_loss: 0.2531 - val_accuracy: 0.8978 - val_precision: 0.8969 - val_recall: 0.8990 - val_auc: 0.9604\n",
            "Epoch 1579/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1636 - accuracy: 0.9359 - precision: 0.9326 - recall: 0.9398 - auc: 0.9832 - val_loss: 0.2793 - val_accuracy: 0.8879 - val_precision: 0.8330 - val_recall: 0.9703 - val_auc: 0.9668\n",
            "Epoch 1580/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1471 - accuracy: 0.9431 - precision: 0.9406 - recall: 0.9459 - auc: 0.9864 - val_loss: 0.3017 - val_accuracy: 0.8822 - val_precision: 0.8247 - val_recall: 0.9705 - val_auc: 0.9640\n",
            "Epoch 1581/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1179 - accuracy: 0.9553 - precision: 0.9547 - recall: 0.9559 - auc: 0.9911 - val_loss: 0.3875 - val_accuracy: 0.8565 - val_precision: 0.7855 - val_recall: 0.9808 - val_auc: 0.9612\n",
            "Epoch 1582/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1232 - accuracy: 0.9529 - precision: 0.9530 - recall: 0.9528 - auc: 0.9902 - val_loss: 0.4873 - val_accuracy: 0.8192 - val_precision: 0.7376 - val_recall: 0.9907 - val_auc: 0.9602\n",
            "Epoch 1583/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1116 - accuracy: 0.9575 - precision: 0.9578 - recall: 0.9571 - auc: 0.9920 - val_loss: 0.7334 - val_accuracy: 0.7526 - val_precision: 0.6700 - val_recall: 0.9949 - val_auc: 0.9465\n",
            "Epoch 1584/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1107 - accuracy: 0.9576 - precision: 0.9577 - recall: 0.9575 - auc: 0.9922 - val_loss: 0.6427 - val_accuracy: 0.7818 - val_precision: 0.6979 - val_recall: 0.9935 - val_auc: 0.9555\n",
            "Epoch 1585/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1013 - accuracy: 0.9613 - precision: 0.9623 - recall: 0.9602 - auc: 0.9933 - val_loss: 0.7082 - val_accuracy: 0.7692 - val_precision: 0.6855 - val_recall: 0.9943 - val_auc: 0.9535\n",
            "Epoch 1586/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1339 - accuracy: 0.9491 - precision: 0.9460 - recall: 0.9526 - auc: 0.9885 - val_loss: 0.5890 - val_accuracy: 0.7931 - val_precision: 0.7093 - val_recall: 0.9929 - val_auc: 0.9575\n",
            "Epoch 1587/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1047 - accuracy: 0.9602 - precision: 0.9629 - recall: 0.9572 - auc: 0.9930 - val_loss: 0.6308 - val_accuracy: 0.7970 - val_precision: 0.7136 - val_recall: 0.9919 - val_auc: 0.9561\n",
            "Epoch 1588/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1220 - accuracy: 0.9536 - precision: 0.9530 - recall: 0.9543 - auc: 0.9904 - val_loss: 0.5940 - val_accuracy: 0.7975 - val_precision: 0.7138 - val_recall: 0.9932 - val_auc: 0.9616\n",
            "Epoch 1589/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1169 - accuracy: 0.9556 - precision: 0.9567 - recall: 0.9543 - auc: 0.9914 - val_loss: 0.5653 - val_accuracy: 0.8129 - val_precision: 0.7310 - val_recall: 0.9900 - val_auc: 0.9584\n",
            "Epoch 1590/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1001 - accuracy: 0.9620 - precision: 0.9626 - recall: 0.9613 - auc: 0.9935 - val_loss: 0.8008 - val_accuracy: 0.7596 - val_precision: 0.6764 - val_recall: 0.9951 - val_auc: 0.9533\n",
            "Epoch 1591/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1113 - accuracy: 0.9574 - precision: 0.9577 - recall: 0.9570 - auc: 0.9920 - val_loss: 0.7753 - val_accuracy: 0.7563 - val_precision: 0.6733 - val_recall: 0.9952 - val_auc: 0.9521\n",
            "Epoch 1592/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1013 - accuracy: 0.9613 - precision: 0.9637 - recall: 0.9587 - auc: 0.9934 - val_loss: 0.7881 - val_accuracy: 0.7558 - val_precision: 0.6729 - val_recall: 0.9949 - val_auc: 0.9540\n",
            "Epoch 1593/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.0980 - accuracy: 0.9626 - precision: 0.9636 - recall: 0.9616 - auc: 0.9937 - val_loss: 0.9261 - val_accuracy: 0.7284 - val_precision: 0.6486 - val_recall: 0.9966 - val_auc: 0.9491\n",
            "Epoch 1594/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1090 - accuracy: 0.9582 - precision: 0.9584 - recall: 0.9581 - auc: 0.9923 - val_loss: 0.7871 - val_accuracy: 0.7529 - val_precision: 0.6704 - val_recall: 0.9948 - val_auc: 0.9542\n",
            "Epoch 1595/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1051 - accuracy: 0.9601 - precision: 0.9616 - recall: 0.9586 - auc: 0.9929 - val_loss: 0.7939 - val_accuracy: 0.7561 - val_precision: 0.6732 - val_recall: 0.9952 - val_auc: 0.9536\n",
            "Epoch 1596/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0985 - accuracy: 0.9623 - precision: 0.9640 - recall: 0.9605 - auc: 0.9937 - val_loss: 0.9311 - val_accuracy: 0.7256 - val_precision: 0.6462 - val_recall: 0.9968 - val_auc: 0.9485\n",
            "Epoch 1597/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.0968 - accuracy: 0.9629 - precision: 0.9636 - recall: 0.9622 - auc: 0.9939 - val_loss: 1.0405 - val_accuracy: 0.7023 - val_precision: 0.6271 - val_recall: 0.9976 - val_auc: 0.9409\n",
            "Epoch 1598/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1675 - accuracy: 0.9356 - precision: 0.9306 - recall: 0.9414 - auc: 0.9826 - val_loss: 0.3767 - val_accuracy: 0.8605 - val_precision: 0.7912 - val_recall: 0.9793 - val_auc: 0.9617\n",
            "Epoch 1599/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1212 - accuracy: 0.9539 - precision: 0.9550 - recall: 0.9527 - auc: 0.9909 - val_loss: 0.5413 - val_accuracy: 0.8248 - val_precision: 0.7452 - val_recall: 0.9869 - val_auc: 0.9572\n",
            "Epoch 1600/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1341 - accuracy: 0.9497 - precision: 0.9464 - recall: 0.9534 - auc: 0.9886 - val_loss: 0.5615 - val_accuracy: 0.8071 - val_precision: 0.7248 - val_recall: 0.9900 - val_auc: 0.9579\n",
            "Epoch 1601/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1142 - accuracy: 0.9565 - precision: 0.9587 - recall: 0.9542 - auc: 0.9919 - val_loss: 0.6367 - val_accuracy: 0.7873 - val_precision: 0.7033 - val_recall: 0.9937 - val_auc: 0.9602\n",
            "Epoch 1602/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0994 - accuracy: 0.9624 - precision: 0.9632 - recall: 0.9616 - auc: 0.9935 - val_loss: 0.9726 - val_accuracy: 0.7189 - val_precision: 0.6406 - val_recall: 0.9970 - val_auc: 0.9475\n",
            "Epoch 1603/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1088 - accuracy: 0.9583 - precision: 0.9596 - recall: 0.9569 - auc: 0.9923 - val_loss: 0.8809 - val_accuracy: 0.7353 - val_precision: 0.6545 - val_recall: 0.9964 - val_auc: 0.9511\n",
            "Epoch 1604/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.0971 - accuracy: 0.9632 - precision: 0.9648 - recall: 0.9615 - auc: 0.9938 - val_loss: 0.9701 - val_accuracy: 0.7255 - val_precision: 0.6461 - val_recall: 0.9966 - val_auc: 0.9463\n",
            "Epoch 1605/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1066 - accuracy: 0.9593 - precision: 0.9597 - recall: 0.9589 - auc: 0.9925 - val_loss: 0.8949 - val_accuracy: 0.7296 - val_precision: 0.6495 - val_recall: 0.9970 - val_auc: 0.9502\n",
            "Epoch 1606/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.0967 - accuracy: 0.9630 - precision: 0.9644 - recall: 0.9615 - auc: 0.9940 - val_loss: 0.8813 - val_accuracy: 0.7327 - val_precision: 0.6522 - val_recall: 0.9970 - val_auc: 0.9536\n",
            "Epoch 1607/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1165 - accuracy: 0.9555 - precision: 0.9542 - recall: 0.9568 - auc: 0.9912 - val_loss: 0.2756 - val_accuracy: 0.8869 - val_precision: 0.8925 - val_recall: 0.8797 - val_auc: 0.9547\n",
            "Epoch 1608/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1228 - accuracy: 0.9530 - precision: 0.9547 - recall: 0.9512 - auc: 0.9904 - val_loss: 0.6946 - val_accuracy: 0.7637 - val_precision: 0.6803 - val_recall: 0.9949 - val_auc: 0.9563\n",
            "Epoch 1609/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1155 - accuracy: 0.9554 - precision: 0.9541 - recall: 0.9569 - auc: 0.9914 - val_loss: 0.7623 - val_accuracy: 0.7545 - val_precision: 0.6718 - val_recall: 0.9950 - val_auc: 0.9538\n",
            "Epoch 1610/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.0983 - accuracy: 0.9625 - precision: 0.9641 - recall: 0.9607 - auc: 0.9937 - val_loss: 0.8428 - val_accuracy: 0.7361 - val_precision: 0.6552 - val_recall: 0.9964 - val_auc: 0.9534\n",
            "Epoch 1611/2000\n",
            "10/10 [==============================] - 4s 421ms/step - loss: 0.1038 - accuracy: 0.9605 - precision: 0.9605 - recall: 0.9605 - auc: 0.9929 - val_loss: 0.8925 - val_accuracy: 0.7242 - val_precision: 0.6450 - val_recall: 0.9968 - val_auc: 0.9490\n",
            "Epoch 1612/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.0961 - accuracy: 0.9633 - precision: 0.9665 - recall: 0.9598 - auc: 0.9940 - val_loss: 0.8603 - val_accuracy: 0.7328 - val_precision: 0.6524 - val_recall: 0.9964 - val_auc: 0.9540\n",
            "Epoch 1613/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.0944 - accuracy: 0.9639 - precision: 0.9659 - recall: 0.9619 - auc: 0.9942 - val_loss: 0.7908 - val_accuracy: 0.7553 - val_precision: 0.6724 - val_recall: 0.9955 - val_auc: 0.9567\n",
            "Epoch 1614/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1135 - accuracy: 0.9567 - precision: 0.9573 - recall: 0.9561 - auc: 0.9916 - val_loss: 0.5494 - val_accuracy: 0.8134 - val_precision: 0.7324 - val_recall: 0.9875 - val_auc: 0.9550\n",
            "Epoch 1615/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1098 - accuracy: 0.9582 - precision: 0.9583 - recall: 0.9582 - auc: 0.9923 - val_loss: 0.7033 - val_accuracy: 0.7667 - val_precision: 0.6829 - val_recall: 0.9954 - val_auc: 0.9601\n",
            "Epoch 1616/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0955 - accuracy: 0.9635 - precision: 0.9646 - recall: 0.9623 - auc: 0.9940 - val_loss: 0.8579 - val_accuracy: 0.7322 - val_precision: 0.6518 - val_recall: 0.9967 - val_auc: 0.9539\n",
            "Epoch 1617/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0958 - accuracy: 0.9634 - precision: 0.9646 - recall: 0.9621 - auc: 0.9940 - val_loss: 0.9868 - val_accuracy: 0.7026 - val_precision: 0.6274 - val_recall: 0.9974 - val_auc: 0.9447\n",
            "Epoch 1618/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.0957 - accuracy: 0.9632 - precision: 0.9640 - recall: 0.9624 - auc: 0.9939 - val_loss: 1.0947 - val_accuracy: 0.6813 - val_precision: 0.6109 - val_recall: 0.9977 - val_auc: 0.9339\n",
            "Epoch 1619/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0994 - accuracy: 0.9615 - precision: 0.9629 - recall: 0.9600 - auc: 0.9936 - val_loss: 0.7120 - val_accuracy: 0.7677 - val_precision: 0.6842 - val_recall: 0.9943 - val_auc: 0.9575\n",
            "Epoch 1620/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1006 - accuracy: 0.9614 - precision: 0.9613 - recall: 0.9615 - auc: 0.9934 - val_loss: 0.6832 - val_accuracy: 0.7748 - val_precision: 0.6908 - val_recall: 0.9948 - val_auc: 0.9619\n",
            "Epoch 1621/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1426 - accuracy: 0.9453 - precision: 0.9409 - recall: 0.9502 - auc: 0.9871 - val_loss: 0.2055 - val_accuracy: 0.9204 - val_precision: 0.9170 - val_recall: 0.9244 - val_auc: 0.9746\n",
            "Epoch 1622/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1149 - accuracy: 0.9564 - precision: 0.9573 - recall: 0.9554 - auc: 0.9917 - val_loss: 0.6784 - val_accuracy: 0.7770 - val_precision: 0.6932 - val_recall: 0.9938 - val_auc: 0.9572\n",
            "Epoch 1623/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1228 - accuracy: 0.9537 - precision: 0.9532 - recall: 0.9543 - auc: 0.9903 - val_loss: 0.5383 - val_accuracy: 0.8078 - val_precision: 0.7249 - val_recall: 0.9920 - val_auc: 0.9636\n",
            "Epoch 1624/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0987 - accuracy: 0.9625 - precision: 0.9661 - recall: 0.9587 - auc: 0.9937 - val_loss: 0.6800 - val_accuracy: 0.7706 - val_precision: 0.6869 - val_recall: 0.9943 - val_auc: 0.9590\n",
            "Epoch 1625/2000\n",
            "10/10 [==============================] - 5s 491ms/step - loss: 0.0948 - accuracy: 0.9639 - precision: 0.9642 - recall: 0.9637 - auc: 0.9941 - val_loss: 0.2987 - val_accuracy: 0.8815 - val_precision: 0.9064 - val_recall: 0.8509 - val_auc: 0.9551\n",
            "Epoch 1626/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1235 - accuracy: 0.9524 - precision: 0.9522 - recall: 0.9526 - auc: 0.9902 - val_loss: 0.6432 - val_accuracy: 0.7677 - val_precision: 0.6842 - val_recall: 0.9943 - val_auc: 0.9583\n",
            "Epoch 1627/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1009 - accuracy: 0.9616 - precision: 0.9630 - recall: 0.9600 - auc: 0.9935 - val_loss: 0.6626 - val_accuracy: 0.7835 - val_precision: 0.6995 - val_recall: 0.9936 - val_auc: 0.9598\n",
            "Epoch 1628/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1257 - accuracy: 0.9520 - precision: 0.9500 - recall: 0.9543 - auc: 0.9899 - val_loss: 0.4142 - val_accuracy: 0.8456 - val_precision: 0.7678 - val_recall: 0.9908 - val_auc: 0.9746\n",
            "Epoch 1629/2000\n",
            "10/10 [==============================] - 4s 421ms/step - loss: 0.1006 - accuracy: 0.9618 - precision: 0.9652 - recall: 0.9581 - auc: 0.9936 - val_loss: 0.8802 - val_accuracy: 0.7258 - val_precision: 0.6465 - val_recall: 0.9957 - val_auc: 0.9502\n",
            "Epoch 1630/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.2296 - accuracy: 0.9229 - precision: 0.9123 - recall: 0.9357 - auc: 0.9731 - val_loss: 1.1081 - val_accuracy: 0.6375 - val_precision: 0.7992 - val_recall: 0.3668 - val_auc: 0.7718\n",
            "Epoch 1631/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.2600 - accuracy: 0.8981 - precision: 0.8971 - recall: 0.8995 - auc: 0.9624 - val_loss: 0.6056 - val_accuracy: 0.7669 - val_precision: 0.7902 - val_recall: 0.7264 - val_auc: 0.8494\n",
            "Epoch 1632/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.2109 - accuracy: 0.9159 - precision: 0.9099 - recall: 0.9233 - auc: 0.9727 - val_loss: 0.5453 - val_accuracy: 0.7893 - val_precision: 0.8614 - val_recall: 0.6894 - val_auc: 0.8979\n",
            "Epoch 1633/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1939 - accuracy: 0.9226 - precision: 0.9148 - recall: 0.9320 - auc: 0.9766 - val_loss: 0.4287 - val_accuracy: 0.8346 - val_precision: 0.8729 - val_recall: 0.7832 - val_auc: 0.9243\n",
            "Epoch 1634/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1847 - accuracy: 0.9271 - precision: 0.9241 - recall: 0.9305 - auc: 0.9788 - val_loss: 0.4146 - val_accuracy: 0.8292 - val_precision: 0.8907 - val_recall: 0.7504 - val_auc: 0.9284\n",
            "Epoch 1635/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1793 - accuracy: 0.9291 - precision: 0.9247 - recall: 0.9344 - auc: 0.9799 - val_loss: 0.3549 - val_accuracy: 0.8526 - val_precision: 0.9032 - val_recall: 0.7898 - val_auc: 0.9424\n",
            "Epoch 1636/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1796 - accuracy: 0.9291 - precision: 0.9243 - recall: 0.9348 - auc: 0.9799 - val_loss: 0.3081 - val_accuracy: 0.8716 - val_precision: 0.9109 - val_recall: 0.8236 - val_auc: 0.9520\n",
            "Epoch 1637/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1812 - accuracy: 0.9280 - precision: 0.9229 - recall: 0.9341 - auc: 0.9795 - val_loss: 0.2912 - val_accuracy: 0.8798 - val_precision: 0.9057 - val_recall: 0.8478 - val_auc: 0.9537\n",
            "Epoch 1638/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1777 - accuracy: 0.9300 - precision: 0.9233 - recall: 0.9380 - auc: 0.9802 - val_loss: 0.2594 - val_accuracy: 0.8956 - val_precision: 0.9012 - val_recall: 0.8885 - val_auc: 0.9595\n",
            "Epoch 1639/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1744 - accuracy: 0.9309 - precision: 0.9258 - recall: 0.9369 - auc: 0.9810 - val_loss: 0.2546 - val_accuracy: 0.8992 - val_precision: 0.8936 - val_recall: 0.9062 - val_auc: 0.9606\n",
            "Epoch 1640/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1754 - accuracy: 0.9304 - precision: 0.9254 - recall: 0.9363 - auc: 0.9808 - val_loss: 0.2598 - val_accuracy: 0.8985 - val_precision: 0.8755 - val_recall: 0.9290 - val_auc: 0.9605\n",
            "Epoch 1641/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1778 - accuracy: 0.9292 - precision: 0.9235 - recall: 0.9359 - auc: 0.9803 - val_loss: 0.2479 - val_accuracy: 0.9032 - val_precision: 0.8838 - val_recall: 0.9283 - val_auc: 0.9633\n",
            "Epoch 1642/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1742 - accuracy: 0.9311 - precision: 0.9258 - recall: 0.9372 - auc: 0.9810 - val_loss: 0.2492 - val_accuracy: 0.9034 - val_precision: 0.8708 - val_recall: 0.9473 - val_auc: 0.9656\n",
            "Epoch 1643/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1749 - accuracy: 0.9306 - precision: 0.9264 - recall: 0.9355 - auc: 0.9809 - val_loss: 0.2489 - val_accuracy: 0.9037 - val_precision: 0.8686 - val_recall: 0.9513 - val_auc: 0.9663\n",
            "Epoch 1644/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1699 - accuracy: 0.9326 - precision: 0.9285 - recall: 0.9375 - auc: 0.9819 - val_loss: 0.2624 - val_accuracy: 0.8962 - val_precision: 0.8479 - val_recall: 0.9656 - val_auc: 0.9673\n",
            "Epoch 1645/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1702 - accuracy: 0.9326 - precision: 0.9272 - recall: 0.9389 - auc: 0.9819 - val_loss: 0.2671 - val_accuracy: 0.8966 - val_precision: 0.8522 - val_recall: 0.9596 - val_auc: 0.9654\n",
            "Epoch 1646/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1770 - accuracy: 0.9299 - precision: 0.9248 - recall: 0.9361 - auc: 0.9804 - val_loss: 0.3091 - val_accuracy: 0.8802 - val_precision: 0.8251 - val_recall: 0.9649 - val_auc: 0.9593\n",
            "Epoch 1647/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1763 - accuracy: 0.9300 - precision: 0.9246 - recall: 0.9364 - auc: 0.9806 - val_loss: 0.2898 - val_accuracy: 0.8864 - val_precision: 0.8441 - val_recall: 0.9479 - val_auc: 0.9570\n",
            "Epoch 1648/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1714 - accuracy: 0.9318 - precision: 0.9264 - recall: 0.9382 - auc: 0.9817 - val_loss: 0.2674 - val_accuracy: 0.8949 - val_precision: 0.8623 - val_recall: 0.9397 - val_auc: 0.9611\n",
            "Epoch 1649/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1711 - accuracy: 0.9320 - precision: 0.9269 - recall: 0.9380 - auc: 0.9817 - val_loss: 0.2902 - val_accuracy: 0.8861 - val_precision: 0.8275 - val_recall: 0.9755 - val_auc: 0.9691\n",
            "Epoch 1650/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1654 - accuracy: 0.9354 - precision: 0.9296 - recall: 0.9421 - auc: 0.9829 - val_loss: 0.3439 - val_accuracy: 0.8686 - val_precision: 0.8010 - val_recall: 0.9808 - val_auc: 0.9651\n",
            "Epoch 1651/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1714 - accuracy: 0.9323 - precision: 0.9282 - recall: 0.9371 - auc: 0.9816 - val_loss: 0.2863 - val_accuracy: 0.8885 - val_precision: 0.8405 - val_recall: 0.9589 - val_auc: 0.9623\n",
            "Epoch 1652/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1694 - accuracy: 0.9333 - precision: 0.9281 - recall: 0.9393 - auc: 0.9821 - val_loss: 0.2525 - val_accuracy: 0.9017 - val_precision: 0.8688 - val_recall: 0.9462 - val_auc: 0.9656\n",
            "Epoch 1653/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1696 - accuracy: 0.9330 - precision: 0.9288 - recall: 0.9379 - auc: 0.9820 - val_loss: 0.3041 - val_accuracy: 0.8785 - val_precision: 0.8172 - val_recall: 0.9751 - val_auc: 0.9662\n",
            "Epoch 1654/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1667 - accuracy: 0.9340 - precision: 0.9280 - recall: 0.9409 - auc: 0.9826 - val_loss: 0.2500 - val_accuracy: 0.9030 - val_precision: 0.8691 - val_recall: 0.9489 - val_auc: 0.9667\n",
            "Epoch 1655/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1653 - accuracy: 0.9349 - precision: 0.9303 - recall: 0.9403 - auc: 0.9829 - val_loss: 0.3506 - val_accuracy: 0.8662 - val_precision: 0.7994 - val_recall: 0.9775 - val_auc: 0.9625\n",
            "Epoch 1656/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1667 - accuracy: 0.9345 - precision: 0.9298 - recall: 0.9399 - auc: 0.9826 - val_loss: 0.2600 - val_accuracy: 0.8981 - val_precision: 0.8658 - val_recall: 0.9420 - val_auc: 0.9632\n",
            "Epoch 1657/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1650 - accuracy: 0.9355 - precision: 0.9308 - recall: 0.9409 - auc: 0.9829 - val_loss: 0.3105 - val_accuracy: 0.8785 - val_precision: 0.8187 - val_recall: 0.9722 - val_auc: 0.9648\n",
            "Epoch 1658/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1675 - accuracy: 0.9339 - precision: 0.9281 - recall: 0.9407 - auc: 0.9824 - val_loss: 0.2810 - val_accuracy: 0.8914 - val_precision: 0.8394 - val_recall: 0.9680 - val_auc: 0.9675\n",
            "Epoch 1659/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1695 - accuracy: 0.9332 - precision: 0.9301 - recall: 0.9367 - auc: 0.9820 - val_loss: 0.3597 - val_accuracy: 0.8571 - val_precision: 0.7872 - val_recall: 0.9787 - val_auc: 0.9597\n",
            "Epoch 1660/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1659 - accuracy: 0.9348 - precision: 0.9306 - recall: 0.9397 - auc: 0.9828 - val_loss: 0.2549 - val_accuracy: 0.8995 - val_precision: 0.8687 - val_recall: 0.9411 - val_auc: 0.9642\n",
            "Epoch 1661/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1671 - accuracy: 0.9338 - precision: 0.9301 - recall: 0.9381 - auc: 0.9825 - val_loss: 0.3115 - val_accuracy: 0.8777 - val_precision: 0.8151 - val_recall: 0.9770 - val_auc: 0.9672\n",
            "Epoch 1662/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1615 - accuracy: 0.9364 - precision: 0.9312 - recall: 0.9424 - auc: 0.9837 - val_loss: 0.2958 - val_accuracy: 0.8847 - val_precision: 0.8272 - val_recall: 0.9724 - val_auc: 0.9669\n",
            "Epoch 1663/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1686 - accuracy: 0.9336 - precision: 0.9277 - recall: 0.9406 - auc: 0.9822 - val_loss: 0.3314 - val_accuracy: 0.8680 - val_precision: 0.7998 - val_recall: 0.9816 - val_auc: 0.9680\n",
            "Epoch 1664/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1637 - accuracy: 0.9352 - precision: 0.9313 - recall: 0.9397 - auc: 0.9833 - val_loss: 0.3661 - val_accuracy: 0.8580 - val_precision: 0.7854 - val_recall: 0.9850 - val_auc: 0.9674\n",
            "Epoch 1665/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1677 - accuracy: 0.9343 - precision: 0.9298 - recall: 0.9395 - auc: 0.9824 - val_loss: 0.3169 - val_accuracy: 0.8754 - val_precision: 0.8106 - val_recall: 0.9794 - val_auc: 0.9689\n",
            "Epoch 1666/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1624 - accuracy: 0.9363 - precision: 0.9323 - recall: 0.9409 - auc: 0.9835 - val_loss: 0.3308 - val_accuracy: 0.8716 - val_precision: 0.8050 - val_recall: 0.9807 - val_auc: 0.9671\n",
            "Epoch 1667/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1616 - accuracy: 0.9362 - precision: 0.9308 - recall: 0.9425 - auc: 0.9836 - val_loss: 0.3226 - val_accuracy: 0.8752 - val_precision: 0.8110 - val_recall: 0.9782 - val_auc: 0.9674\n",
            "Epoch 1668/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1612 - accuracy: 0.9369 - precision: 0.9317 - recall: 0.9428 - auc: 0.9837 - val_loss: 0.3524 - val_accuracy: 0.8650 - val_precision: 0.7947 - val_recall: 0.9841 - val_auc: 0.9692\n",
            "Epoch 1669/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1655 - accuracy: 0.9349 - precision: 0.9315 - recall: 0.9389 - auc: 0.9829 - val_loss: 0.3163 - val_accuracy: 0.8778 - val_precision: 0.8154 - val_recall: 0.9767 - val_auc: 0.9670\n",
            "Epoch 1670/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1612 - accuracy: 0.9366 - precision: 0.9341 - recall: 0.9395 - auc: 0.9837 - val_loss: 0.3475 - val_accuracy: 0.8667 - val_precision: 0.7976 - val_recall: 0.9827 - val_auc: 0.9678\n",
            "Epoch 1671/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1638 - accuracy: 0.9358 - precision: 0.9306 - recall: 0.9419 - auc: 0.9831 - val_loss: 0.2673 - val_accuracy: 0.8973 - val_precision: 0.8484 - val_recall: 0.9673 - val_auc: 0.9706\n",
            "Epoch 1672/2000\n",
            "10/10 [==============================] - 4s 420ms/step - loss: 0.1614 - accuracy: 0.9367 - precision: 0.9321 - recall: 0.9419 - auc: 0.9837 - val_loss: 0.2738 - val_accuracy: 0.8940 - val_precision: 0.8435 - val_recall: 0.9674 - val_auc: 0.9686\n",
            "Epoch 1673/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1618 - accuracy: 0.9366 - precision: 0.9319 - recall: 0.9420 - auc: 0.9835 - val_loss: 0.3286 - val_accuracy: 0.8723 - val_precision: 0.8092 - val_recall: 0.9743 - val_auc: 0.9634\n",
            "Epoch 1674/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1595 - accuracy: 0.9370 - precision: 0.9344 - recall: 0.9401 - auc: 0.9841 - val_loss: 0.3257 - val_accuracy: 0.8743 - val_precision: 0.8121 - val_recall: 0.9737 - val_auc: 0.9639\n",
            "Epoch 1675/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1658 - accuracy: 0.9349 - precision: 0.9313 - recall: 0.9390 - auc: 0.9828 - val_loss: 0.3289 - val_accuracy: 0.8718 - val_precision: 0.8052 - val_recall: 0.9808 - val_auc: 0.9686\n",
            "Epoch 1676/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1641 - accuracy: 0.9352 - precision: 0.9295 - recall: 0.9418 - auc: 0.9832 - val_loss: 0.3474 - val_accuracy: 0.8657 - val_precision: 0.7956 - val_recall: 0.9842 - val_auc: 0.9695\n",
            "Epoch 1677/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1607 - accuracy: 0.9367 - precision: 0.9319 - recall: 0.9422 - auc: 0.9838 - val_loss: 0.3346 - val_accuracy: 0.8705 - val_precision: 0.8047 - val_recall: 0.9782 - val_auc: 0.9655\n",
            "Epoch 1678/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1628 - accuracy: 0.9360 - precision: 0.9323 - recall: 0.9402 - auc: 0.9833 - val_loss: 0.3527 - val_accuracy: 0.8609 - val_precision: 0.7905 - val_recall: 0.9820 - val_auc: 0.9656\n",
            "Epoch 1679/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1605 - accuracy: 0.9369 - precision: 0.9317 - recall: 0.9430 - auc: 0.9838 - val_loss: 0.3193 - val_accuracy: 0.8758 - val_precision: 0.8135 - val_recall: 0.9751 - val_auc: 0.9656\n",
            "Epoch 1680/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1579 - accuracy: 0.9381 - precision: 0.9342 - recall: 0.9427 - auc: 0.9843 - val_loss: 0.3424 - val_accuracy: 0.8662 - val_precision: 0.7979 - val_recall: 0.9807 - val_auc: 0.9669\n",
            "Epoch 1681/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1588 - accuracy: 0.9376 - precision: 0.9325 - recall: 0.9435 - auc: 0.9842 - val_loss: 0.3804 - val_accuracy: 0.8552 - val_precision: 0.7820 - val_recall: 0.9848 - val_auc: 0.9661\n",
            "Epoch 1682/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1511 - accuracy: 0.9409 - precision: 0.9378 - recall: 0.9445 - auc: 0.9857 - val_loss: 0.4766 - val_accuracy: 0.8243 - val_precision: 0.7435 - val_recall: 0.9901 - val_auc: 0.9632\n",
            "Epoch 1683/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1405 - accuracy: 0.9451 - precision: 0.9437 - recall: 0.9467 - auc: 0.9875 - val_loss: 0.4016 - val_accuracy: 0.8517 - val_precision: 0.7778 - val_recall: 0.9846 - val_auc: 0.9634\n",
            "Epoch 1684/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1298 - accuracy: 0.9506 - precision: 0.9490 - recall: 0.9523 - auc: 0.9892 - val_loss: 0.5884 - val_accuracy: 0.8019 - val_precision: 0.7187 - val_recall: 0.9917 - val_auc: 0.9578\n",
            "Epoch 1685/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1780 - accuracy: 0.9299 - precision: 0.9228 - recall: 0.9383 - auc: 0.9803 - val_loss: 0.3771 - val_accuracy: 0.8568 - val_precision: 0.7834 - val_recall: 0.9861 - val_auc: 0.9678\n",
            "Epoch 1686/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1648 - accuracy: 0.9346 - precision: 0.9319 - recall: 0.9378 - auc: 0.9831 - val_loss: 0.3436 - val_accuracy: 0.8701 - val_precision: 0.8040 - val_recall: 0.9786 - val_auc: 0.9654\n",
            "Epoch 1687/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1590 - accuracy: 0.9374 - precision: 0.9315 - recall: 0.9444 - auc: 0.9841 - val_loss: 0.3232 - val_accuracy: 0.8789 - val_precision: 0.8186 - val_recall: 0.9735 - val_auc: 0.9652\n",
            "Epoch 1688/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1492 - accuracy: 0.9417 - precision: 0.9386 - recall: 0.9452 - auc: 0.9860 - val_loss: 0.4034 - val_accuracy: 0.8519 - val_precision: 0.7772 - val_recall: 0.9864 - val_auc: 0.9671\n",
            "Epoch 1689/2000\n",
            "10/10 [==============================] - 5s 485ms/step - loss: 0.1206 - accuracy: 0.9539 - precision: 0.9549 - recall: 0.9529 - auc: 0.9908 - val_loss: 0.3752 - val_accuracy: 0.8716 - val_precision: 0.8057 - val_recall: 0.9791 - val_auc: 0.9668\n",
            "Epoch 1690/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1033 - accuracy: 0.9605 - precision: 0.9626 - recall: 0.9583 - auc: 0.9931 - val_loss: 0.4583 - val_accuracy: 0.8491 - val_precision: 0.7740 - val_recall: 0.9858 - val_auc: 0.9654\n",
            "Epoch 1691/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1089 - accuracy: 0.9587 - precision: 0.9587 - recall: 0.9586 - auc: 0.9923 - val_loss: 0.5423 - val_accuracy: 0.8206 - val_precision: 0.7387 - val_recall: 0.9920 - val_auc: 0.9657\n",
            "Epoch 1692/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1164 - accuracy: 0.9558 - precision: 0.9566 - recall: 0.9549 - auc: 0.9913 - val_loss: 0.5268 - val_accuracy: 0.8206 - val_precision: 0.7391 - val_recall: 0.9908 - val_auc: 0.9639\n",
            "Epoch 1693/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1135 - accuracy: 0.9573 - precision: 0.9572 - recall: 0.9574 - auc: 0.9917 - val_loss: 0.5395 - val_accuracy: 0.8192 - val_precision: 0.7376 - val_recall: 0.9907 - val_auc: 0.9633\n",
            "Epoch 1694/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.0981 - accuracy: 0.9631 - precision: 0.9645 - recall: 0.9615 - auc: 0.9937 - val_loss: 0.6485 - val_accuracy: 0.7898 - val_precision: 0.7057 - val_recall: 0.9939 - val_auc: 0.9621\n",
            "Epoch 1695/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1062 - accuracy: 0.9598 - precision: 0.9598 - recall: 0.9598 - auc: 0.9926 - val_loss: 0.8320 - val_accuracy: 0.7287 - val_precision: 0.6488 - val_recall: 0.9968 - val_auc: 0.9541\n",
            "Epoch 1696/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1307 - accuracy: 0.9498 - precision: 0.9474 - recall: 0.9524 - auc: 0.9892 - val_loss: 0.5565 - val_accuracy: 0.8004 - val_precision: 0.7169 - val_recall: 0.9928 - val_auc: 0.9637\n",
            "Epoch 1697/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1074 - accuracy: 0.9597 - precision: 0.9615 - recall: 0.9578 - auc: 0.9926 - val_loss: 0.6627 - val_accuracy: 0.7865 - val_precision: 0.7025 - val_recall: 0.9936 - val_auc: 0.9605\n",
            "Epoch 1698/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1122 - accuracy: 0.9574 - precision: 0.9592 - recall: 0.9554 - auc: 0.9918 - val_loss: 0.7389 - val_accuracy: 0.7527 - val_precision: 0.6700 - val_recall: 0.9959 - val_auc: 0.9599\n",
            "Epoch 1699/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1050 - accuracy: 0.9600 - precision: 0.9603 - recall: 0.9597 - auc: 0.9929 - val_loss: 0.7401 - val_accuracy: 0.7595 - val_precision: 0.6762 - val_recall: 0.9954 - val_auc: 0.9592\n",
            "Epoch 1700/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.0983 - accuracy: 0.9628 - precision: 0.9630 - recall: 0.9626 - auc: 0.9936 - val_loss: 0.8208 - val_accuracy: 0.7447 - val_precision: 0.6628 - val_recall: 0.9958 - val_auc: 0.9552\n",
            "Epoch 1701/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0972 - accuracy: 0.9629 - precision: 0.9663 - recall: 0.9593 - auc: 0.9938 - val_loss: 0.8863 - val_accuracy: 0.7316 - val_precision: 0.6513 - val_recall: 0.9969 - val_auc: 0.9550\n",
            "Epoch 1702/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.0941 - accuracy: 0.9641 - precision: 0.9671 - recall: 0.9609 - auc: 0.9942 - val_loss: 0.8910 - val_accuracy: 0.7316 - val_precision: 0.6513 - val_recall: 0.9967 - val_auc: 0.9535\n",
            "Epoch 1703/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0940 - accuracy: 0.9640 - precision: 0.9664 - recall: 0.9614 - auc: 0.9942 - val_loss: 0.9435 - val_accuracy: 0.7158 - val_precision: 0.6380 - val_recall: 0.9972 - val_auc: 0.9509\n",
            "Epoch 1704/2000\n",
            "10/10 [==============================] - 4s 417ms/step - loss: 0.1200 - accuracy: 0.9544 - precision: 0.9516 - recall: 0.9576 - auc: 0.9907 - val_loss: 0.7271 - val_accuracy: 0.7529 - val_precision: 0.6702 - val_recall: 0.9953 - val_auc: 0.9562\n",
            "Epoch 1705/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.0987 - accuracy: 0.9627 - precision: 0.9657 - recall: 0.9594 - auc: 0.9937 - val_loss: 0.8213 - val_accuracy: 0.7414 - val_precision: 0.6599 - val_recall: 0.9961 - val_auc: 0.9565\n",
            "Epoch 1706/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1329 - accuracy: 0.9498 - precision: 0.9466 - recall: 0.9533 - auc: 0.9888 - val_loss: 0.6856 - val_accuracy: 0.7409 - val_precision: 0.6595 - val_recall: 0.9957 - val_auc: 0.9511\n",
            "Epoch 1707/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1661 - accuracy: 0.9354 - precision: 0.9311 - recall: 0.9404 - auc: 0.9829 - val_loss: 0.3299 - val_accuracy: 0.8641 - val_precision: 0.7950 - val_recall: 0.9809 - val_auc: 0.9657\n",
            "Epoch 1708/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1428 - accuracy: 0.9448 - precision: 0.9414 - recall: 0.9486 - auc: 0.9872 - val_loss: 0.3807 - val_accuracy: 0.8549 - val_precision: 0.7861 - val_recall: 0.9751 - val_auc: 0.9566\n",
            "Epoch 1709/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1332 - accuracy: 0.9495 - precision: 0.9497 - recall: 0.9493 - auc: 0.9887 - val_loss: 0.6018 - val_accuracy: 0.7504 - val_precision: 0.9161 - val_recall: 0.5512 - val_auc: 0.9103\n",
            "Epoch 1710/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1847 - accuracy: 0.9271 - precision: 0.9184 - recall: 0.9377 - auc: 0.9790 - val_loss: 0.7818 - val_accuracy: 0.6618 - val_precision: 0.9036 - val_recall: 0.3619 - val_auc: 0.8603\n",
            "Epoch 1711/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1721 - accuracy: 0.9316 - precision: 0.9272 - recall: 0.9369 - auc: 0.9816 - val_loss: 0.6099 - val_accuracy: 0.7292 - val_precision: 0.9147 - val_recall: 0.5053 - val_auc: 0.9043\n",
            "Epoch 1712/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1696 - accuracy: 0.9330 - precision: 0.9287 - recall: 0.9380 - auc: 0.9820 - val_loss: 0.4759 - val_accuracy: 0.7891 - val_precision: 0.9274 - val_recall: 0.6271 - val_auc: 0.9329\n",
            "Epoch 1713/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1664 - accuracy: 0.9342 - precision: 0.9303 - recall: 0.9388 - auc: 0.9827 - val_loss: 0.3864 - val_accuracy: 0.8266 - val_precision: 0.9160 - val_recall: 0.7191 - val_auc: 0.9393\n",
            "Epoch 1714/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1643 - accuracy: 0.9355 - precision: 0.9325 - recall: 0.9390 - auc: 0.9831 - val_loss: 0.3401 - val_accuracy: 0.8505 - val_precision: 0.9116 - val_recall: 0.7762 - val_auc: 0.9459\n",
            "Epoch 1715/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.1683 - accuracy: 0.9336 - precision: 0.9292 - recall: 0.9388 - auc: 0.9823 - val_loss: 0.3292 - val_accuracy: 0.8569 - val_precision: 0.9234 - val_recall: 0.7783 - val_auc: 0.9515\n",
            "Epoch 1716/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1647 - accuracy: 0.9351 - precision: 0.9309 - recall: 0.9399 - auc: 0.9831 - val_loss: 0.2548 - val_accuracy: 0.8967 - val_precision: 0.9137 - val_recall: 0.8762 - val_auc: 0.9627\n",
            "Epoch 1717/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1664 - accuracy: 0.9343 - precision: 0.9282 - recall: 0.9414 - auc: 0.9826 - val_loss: 0.2616 - val_accuracy: 0.8923 - val_precision: 0.9032 - val_recall: 0.8788 - val_auc: 0.9591\n",
            "Epoch 1718/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1680 - accuracy: 0.9337 - precision: 0.9285 - recall: 0.9397 - auc: 0.9824 - val_loss: 0.2436 - val_accuracy: 0.9031 - val_precision: 0.8813 - val_recall: 0.9315 - val_auc: 0.9640\n",
            "Epoch 1719/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1656 - accuracy: 0.9350 - precision: 0.9310 - recall: 0.9397 - auc: 0.9828 - val_loss: 0.2462 - val_accuracy: 0.9019 - val_precision: 0.8691 - val_recall: 0.9463 - val_auc: 0.9652\n",
            "Epoch 1720/2000\n",
            "10/10 [==============================] - 4s 386ms/step - loss: 0.1637 - accuracy: 0.9345 - precision: 0.9289 - recall: 0.9412 - auc: 0.9833 - val_loss: 0.2465 - val_accuracy: 0.9013 - val_precision: 0.8908 - val_recall: 0.9148 - val_auc: 0.9628\n",
            "Epoch 1721/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1646 - accuracy: 0.9346 - precision: 0.9294 - recall: 0.9408 - auc: 0.9831 - val_loss: 0.2533 - val_accuracy: 0.8995 - val_precision: 0.8548 - val_recall: 0.9625 - val_auc: 0.9676\n",
            "Epoch 1722/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1597 - accuracy: 0.9366 - precision: 0.9323 - recall: 0.9416 - auc: 0.9840 - val_loss: 0.3437 - val_accuracy: 0.8667 - val_precision: 0.7974 - val_recall: 0.9833 - val_auc: 0.9668\n",
            "Epoch 1723/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1612 - accuracy: 0.9360 - precision: 0.9326 - recall: 0.9399 - auc: 0.9838 - val_loss: 0.2462 - val_accuracy: 0.9044 - val_precision: 0.8628 - val_recall: 0.9617 - val_auc: 0.9697\n",
            "Epoch 1724/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1641 - accuracy: 0.9353 - precision: 0.9316 - recall: 0.9395 - auc: 0.9831 - val_loss: 0.2543 - val_accuracy: 0.8994 - val_precision: 0.8579 - val_recall: 0.9573 - val_auc: 0.9670\n",
            "Epoch 1725/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1599 - accuracy: 0.9372 - precision: 0.9327 - recall: 0.9424 - auc: 0.9840 - val_loss: 0.3128 - val_accuracy: 0.8754 - val_precision: 0.8092 - val_recall: 0.9823 - val_auc: 0.9706\n",
            "Epoch 1726/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1604 - accuracy: 0.9368 - precision: 0.9348 - recall: 0.9391 - auc: 0.9839 - val_loss: 0.2867 - val_accuracy: 0.8869 - val_precision: 0.8320 - val_recall: 0.9693 - val_auc: 0.9664\n",
            "Epoch 1727/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1618 - accuracy: 0.9360 - precision: 0.9315 - recall: 0.9413 - auc: 0.9837 - val_loss: 0.3973 - val_accuracy: 0.8439 - val_precision: 0.7676 - val_recall: 0.9865 - val_auc: 0.9629\n",
            "Epoch 1728/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1630 - accuracy: 0.9358 - precision: 0.9299 - recall: 0.9428 - auc: 0.9834 - val_loss: 0.2650 - val_accuracy: 0.8954 - val_precision: 0.8524 - val_recall: 0.9562 - val_auc: 0.9651\n",
            "Epoch 1729/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1627 - accuracy: 0.9362 - precision: 0.9318 - recall: 0.9412 - auc: 0.9834 - val_loss: 0.2788 - val_accuracy: 0.8876 - val_precision: 0.8348 - val_recall: 0.9663 - val_auc: 0.9664\n",
            "Epoch 1730/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1640 - accuracy: 0.9353 - precision: 0.9303 - recall: 0.9412 - auc: 0.9832 - val_loss: 0.2610 - val_accuracy: 0.8956 - val_precision: 0.8617 - val_recall: 0.9424 - val_auc: 0.9625\n",
            "Epoch 1731/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1595 - accuracy: 0.9370 - precision: 0.9314 - recall: 0.9435 - auc: 0.9840 - val_loss: 0.3121 - val_accuracy: 0.8746 - val_precision: 0.8093 - val_recall: 0.9799 - val_auc: 0.9683\n",
            "Epoch 1732/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1582 - accuracy: 0.9378 - precision: 0.9331 - recall: 0.9433 - auc: 0.9844 - val_loss: 0.2924 - val_accuracy: 0.8837 - val_precision: 0.8298 - val_recall: 0.9654 - val_auc: 0.9642\n",
            "Epoch 1733/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1611 - accuracy: 0.9366 - precision: 0.9340 - recall: 0.9397 - auc: 0.9838 - val_loss: 0.2975 - val_accuracy: 0.8822 - val_precision: 0.8207 - val_recall: 0.9779 - val_auc: 0.9695\n",
            "Epoch 1734/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1554 - accuracy: 0.9388 - precision: 0.9358 - recall: 0.9421 - auc: 0.9849 - val_loss: 0.2777 - val_accuracy: 0.8900 - val_precision: 0.8388 - val_recall: 0.9654 - val_auc: 0.9665\n",
            "Epoch 1735/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1617 - accuracy: 0.9361 - precision: 0.9310 - recall: 0.9421 - auc: 0.9837 - val_loss: 0.2896 - val_accuracy: 0.8864 - val_precision: 0.8311 - val_recall: 0.9699 - val_auc: 0.9671\n",
            "Epoch 1736/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1550 - accuracy: 0.9388 - precision: 0.9358 - recall: 0.9422 - auc: 0.9849 - val_loss: 0.4205 - val_accuracy: 0.8438 - val_precision: 0.7668 - val_recall: 0.9879 - val_auc: 0.9652\n",
            "Epoch 1737/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1597 - accuracy: 0.9373 - precision: 0.9335 - recall: 0.9418 - auc: 0.9840 - val_loss: 0.2973 - val_accuracy: 0.8840 - val_precision: 0.8280 - val_recall: 0.9694 - val_auc: 0.9657\n",
            "Epoch 1738/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1570 - accuracy: 0.9380 - precision: 0.9326 - recall: 0.9442 - auc: 0.9845 - val_loss: 0.3238 - val_accuracy: 0.8730 - val_precision: 0.8082 - val_recall: 0.9779 - val_auc: 0.9664\n",
            "Epoch 1739/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1522 - accuracy: 0.9405 - precision: 0.9380 - recall: 0.9433 - auc: 0.9854 - val_loss: 0.3691 - val_accuracy: 0.8586 - val_precision: 0.7852 - val_recall: 0.9871 - val_auc: 0.9717\n",
            "Epoch 1740/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.1556 - accuracy: 0.9387 - precision: 0.9357 - recall: 0.9421 - auc: 0.9848 - val_loss: 0.2822 - val_accuracy: 0.8883 - val_precision: 0.8356 - val_recall: 0.9668 - val_auc: 0.9671\n",
            "Epoch 1741/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1538 - accuracy: 0.9398 - precision: 0.9353 - recall: 0.9450 - auc: 0.9852 - val_loss: 0.2801 - val_accuracy: 0.8896 - val_precision: 0.8367 - val_recall: 0.9679 - val_auc: 0.9676\n",
            "Epoch 1742/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1526 - accuracy: 0.9403 - precision: 0.9368 - recall: 0.9443 - auc: 0.9854 - val_loss: 0.3164 - val_accuracy: 0.8739 - val_precision: 0.8136 - val_recall: 0.9698 - val_auc: 0.9627\n",
            "Epoch 1743/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.1502 - accuracy: 0.9413 - precision: 0.9363 - recall: 0.9472 - auc: 0.9858 - val_loss: 0.4401 - val_accuracy: 0.8322 - val_precision: 0.7527 - val_recall: 0.9894 - val_auc: 0.9639\n",
            "Epoch 1744/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1547 - accuracy: 0.9392 - precision: 0.9346 - recall: 0.9445 - auc: 0.9850 - val_loss: 0.3140 - val_accuracy: 0.8731 - val_precision: 0.8103 - val_recall: 0.9742 - val_auc: 0.9654\n",
            "Epoch 1745/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1562 - accuracy: 0.9386 - precision: 0.9364 - recall: 0.9411 - auc: 0.9847 - val_loss: 0.4099 - val_accuracy: 0.8463 - val_precision: 0.7709 - val_recall: 0.9853 - val_auc: 0.9619\n",
            "Epoch 1746/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1615 - accuracy: 0.9367 - precision: 0.9338 - recall: 0.9401 - auc: 0.9837 - val_loss: 0.2961 - val_accuracy: 0.8802 - val_precision: 0.8176 - val_recall: 0.9786 - val_auc: 0.9708\n",
            "Epoch 1747/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1535 - accuracy: 0.9396 - precision: 0.9345 - recall: 0.9456 - auc: 0.9852 - val_loss: 0.3200 - val_accuracy: 0.8740 - val_precision: 0.8077 - val_recall: 0.9815 - val_auc: 0.9722\n",
            "Epoch 1748/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1491 - accuracy: 0.9418 - precision: 0.9380 - recall: 0.9463 - auc: 0.9861 - val_loss: 0.3096 - val_accuracy: 0.8809 - val_precision: 0.8198 - val_recall: 0.9762 - val_auc: 0.9688\n",
            "Epoch 1749/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1480 - accuracy: 0.9419 - precision: 0.9392 - recall: 0.9450 - auc: 0.9863 - val_loss: 0.3308 - val_accuracy: 0.8726 - val_precision: 0.8084 - val_recall: 0.9766 - val_auc: 0.9653\n",
            "Epoch 1750/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1493 - accuracy: 0.9418 - precision: 0.9394 - recall: 0.9445 - auc: 0.9860 - val_loss: 0.3255 - val_accuracy: 0.8751 - val_precision: 0.8089 - val_recall: 0.9822 - val_auc: 0.9718\n",
            "Epoch 1751/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1352 - accuracy: 0.9474 - precision: 0.9468 - recall: 0.9481 - auc: 0.9885 - val_loss: 0.2934 - val_accuracy: 0.8893 - val_precision: 0.8409 - val_recall: 0.9601 - val_auc: 0.9635\n",
            "Epoch 1752/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1388 - accuracy: 0.9462 - precision: 0.9440 - recall: 0.9487 - auc: 0.9878 - val_loss: 0.3186 - val_accuracy: 0.8767 - val_precision: 0.8217 - val_recall: 0.9622 - val_auc: 0.9594\n",
            "Epoch 1753/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1167 - accuracy: 0.9554 - precision: 0.9575 - recall: 0.9531 - auc: 0.9914 - val_loss: 0.3492 - val_accuracy: 0.8766 - val_precision: 0.8138 - val_recall: 0.9766 - val_auc: 0.9671\n",
            "Epoch 1754/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1222 - accuracy: 0.9533 - precision: 0.9544 - recall: 0.9521 - auc: 0.9904 - val_loss: 0.3531 - val_accuracy: 0.8676 - val_precision: 0.8070 - val_recall: 0.9661 - val_auc: 0.9588\n",
            "Epoch 1755/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1043 - accuracy: 0.9602 - precision: 0.9628 - recall: 0.9575 - auc: 0.9931 - val_loss: 0.4378 - val_accuracy: 0.8530 - val_precision: 0.7808 - val_recall: 0.9813 - val_auc: 0.9615\n",
            "Epoch 1756/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1113 - accuracy: 0.9577 - precision: 0.9591 - recall: 0.9563 - auc: 0.9920 - val_loss: 0.4495 - val_accuracy: 0.8475 - val_precision: 0.7720 - val_recall: 0.9862 - val_auc: 0.9651\n",
            "Epoch 1757/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.0970 - accuracy: 0.9634 - precision: 0.9652 - recall: 0.9615 - auc: 0.9938 - val_loss: 0.5439 - val_accuracy: 0.8207 - val_precision: 0.7412 - val_recall: 0.9854 - val_auc: 0.9560\n",
            "Epoch 1758/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1311 - accuracy: 0.9502 - precision: 0.9483 - recall: 0.9523 - auc: 0.9890 - val_loss: 0.4428 - val_accuracy: 0.8358 - val_precision: 0.7579 - val_recall: 0.9868 - val_auc: 0.9636\n",
            "Epoch 1759/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1114 - accuracy: 0.9579 - precision: 0.9590 - recall: 0.9566 - auc: 0.9920 - val_loss: 0.5194 - val_accuracy: 0.8244 - val_precision: 0.7443 - val_recall: 0.9882 - val_auc: 0.9600\n",
            "Epoch 1760/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0969 - accuracy: 0.9629 - precision: 0.9643 - recall: 0.9614 - auc: 0.9939 - val_loss: 0.6189 - val_accuracy: 0.8026 - val_precision: 0.7192 - val_recall: 0.9925 - val_auc: 0.9617\n",
            "Epoch 1761/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.0971 - accuracy: 0.9629 - precision: 0.9659 - recall: 0.9597 - auc: 0.9938 - val_loss: 0.8086 - val_accuracy: 0.7458 - val_precision: 0.6637 - val_recall: 0.9965 - val_auc: 0.9587\n",
            "Epoch 1762/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1315 - accuracy: 0.9497 - precision: 0.9474 - recall: 0.9523 - auc: 0.9890 - val_loss: 0.6350 - val_accuracy: 0.7726 - val_precision: 0.6887 - val_recall: 0.9948 - val_auc: 0.9596\n",
            "Epoch 1763/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1165 - accuracy: 0.9552 - precision: 0.9566 - recall: 0.9538 - auc: 0.9914 - val_loss: 0.4542 - val_accuracy: 0.8349 - val_precision: 0.7574 - val_recall: 0.9851 - val_auc: 0.9590\n",
            "Epoch 1764/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1224 - accuracy: 0.9529 - precision: 0.9513 - recall: 0.9548 - auc: 0.9904 - val_loss: 0.5088 - val_accuracy: 0.8115 - val_precision: 0.7293 - val_recall: 0.9904 - val_auc: 0.9617\n",
            "Epoch 1765/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1050 - accuracy: 0.9601 - precision: 0.9623 - recall: 0.9577 - auc: 0.9928 - val_loss: 0.6223 - val_accuracy: 0.7839 - val_precision: 0.7002 - val_recall: 0.9928 - val_auc: 0.9590\n",
            "Epoch 1766/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0977 - accuracy: 0.9631 - precision: 0.9638 - recall: 0.9623 - auc: 0.9938 - val_loss: 0.6755 - val_accuracy: 0.7720 - val_precision: 0.6887 - val_recall: 0.9923 - val_auc: 0.9550\n",
            "Epoch 1767/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1394 - accuracy: 0.9472 - precision: 0.9443 - recall: 0.9505 - auc: 0.9876 - val_loss: 0.5307 - val_accuracy: 0.8013 - val_precision: 0.7182 - val_recall: 0.9915 - val_auc: 0.9583\n",
            "Epoch 1768/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1063 - accuracy: 0.9597 - precision: 0.9626 - recall: 0.9566 - auc: 0.9927 - val_loss: 0.7358 - val_accuracy: 0.7628 - val_precision: 0.6795 - val_recall: 0.9944 - val_auc: 0.9588\n",
            "Epoch 1769/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1057 - accuracy: 0.9596 - precision: 0.9579 - recall: 0.9615 - auc: 0.9928 - val_loss: 0.7695 - val_accuracy: 0.7476 - val_precision: 0.6654 - val_recall: 0.9958 - val_auc: 0.9588\n",
            "Epoch 1770/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0985 - accuracy: 0.9625 - precision: 0.9632 - recall: 0.9617 - auc: 0.9936 - val_loss: 0.8737 - val_accuracy: 0.7241 - val_precision: 0.6449 - val_recall: 0.9971 - val_auc: 0.9576\n",
            "Epoch 1771/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0938 - accuracy: 0.9643 - precision: 0.9657 - recall: 0.9629 - auc: 0.9942 - val_loss: 0.9053 - val_accuracy: 0.7194 - val_precision: 0.6410 - val_recall: 0.9969 - val_auc: 0.9552\n",
            "Epoch 1772/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.0922 - accuracy: 0.9651 - precision: 0.9676 - recall: 0.9625 - auc: 0.9944 - val_loss: 1.0489 - val_accuracy: 0.6879 - val_precision: 0.6159 - val_recall: 0.9979 - val_auc: 0.9467\n",
            "Epoch 1773/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1655 - accuracy: 0.9369 - precision: 0.9315 - recall: 0.9432 - auc: 0.9829 - val_loss: 0.2442 - val_accuracy: 0.9017 - val_precision: 0.8694 - val_recall: 0.9454 - val_auc: 0.9651\n",
            "Epoch 1774/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1567 - accuracy: 0.9388 - precision: 0.9373 - recall: 0.9406 - auc: 0.9847 - val_loss: 0.2218 - val_accuracy: 0.9141 - val_precision: 0.8784 - val_recall: 0.9612 - val_auc: 0.9746\n",
            "Epoch 1775/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1436 - accuracy: 0.9439 - precision: 0.9419 - recall: 0.9463 - auc: 0.9871 - val_loss: 0.3426 - val_accuracy: 0.8693 - val_precision: 0.8031 - val_recall: 0.9784 - val_auc: 0.9649\n",
            "Epoch 1776/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1219 - accuracy: 0.9532 - precision: 0.9513 - recall: 0.9554 - auc: 0.9905 - val_loss: 0.6383 - val_accuracy: 0.7945 - val_precision: 0.7107 - val_recall: 0.9930 - val_auc: 0.9550\n",
            "Epoch 1777/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1170 - accuracy: 0.9554 - precision: 0.9539 - recall: 0.9570 - auc: 0.9912 - val_loss: 0.5313 - val_accuracy: 0.8080 - val_precision: 0.7251 - val_recall: 0.9920 - val_auc: 0.9625\n",
            "Epoch 1778/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1006 - accuracy: 0.9619 - precision: 0.9653 - recall: 0.9582 - auc: 0.9935 - val_loss: 0.6216 - val_accuracy: 0.7908 - val_precision: 0.7071 - val_recall: 0.9927 - val_auc: 0.9603\n",
            "Epoch 1779/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1429 - accuracy: 0.9459 - precision: 0.9433 - recall: 0.9489 - auc: 0.9870 - val_loss: 0.4500 - val_accuracy: 0.8198 - val_precision: 0.7379 - val_recall: 0.9917 - val_auc: 0.9670\n",
            "Epoch 1780/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1063 - accuracy: 0.9600 - precision: 0.9611 - recall: 0.9587 - auc: 0.9928 - val_loss: 0.5648 - val_accuracy: 0.8024 - val_precision: 0.7189 - val_recall: 0.9929 - val_auc: 0.9645\n",
            "Epoch 1781/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1046 - accuracy: 0.9608 - precision: 0.9625 - recall: 0.9588 - auc: 0.9928 - val_loss: 0.6536 - val_accuracy: 0.7763 - val_precision: 0.6923 - val_recall: 0.9944 - val_auc: 0.9611\n",
            "Epoch 1782/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.0950 - accuracy: 0.9637 - precision: 0.9666 - recall: 0.9607 - auc: 0.9942 - val_loss: 0.9220 - val_accuracy: 0.7181 - val_precision: 0.6400 - val_recall: 0.9968 - val_auc: 0.9525\n",
            "Epoch 1783/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1284 - accuracy: 0.9518 - precision: 0.9492 - recall: 0.9548 - auc: 0.9894 - val_loss: 0.7193 - val_accuracy: 0.7354 - val_precision: 0.6546 - val_recall: 0.9964 - val_auc: 0.9532\n",
            "Epoch 1784/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1096 - accuracy: 0.9589 - precision: 0.9591 - recall: 0.9586 - auc: 0.9926 - val_loss: 0.5998 - val_accuracy: 0.7981 - val_precision: 0.7149 - val_recall: 0.9914 - val_auc: 0.9589\n",
            "Epoch 1785/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1016 - accuracy: 0.9617 - precision: 0.9631 - recall: 0.9602 - auc: 0.9933 - val_loss: 0.7441 - val_accuracy: 0.7629 - val_precision: 0.6795 - val_recall: 0.9947 - val_auc: 0.9555\n",
            "Epoch 1786/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.0979 - accuracy: 0.9625 - precision: 0.9638 - recall: 0.9612 - auc: 0.9937 - val_loss: 0.7907 - val_accuracy: 0.7522 - val_precision: 0.6697 - val_recall: 0.9949 - val_auc: 0.9526\n",
            "Epoch 1787/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0983 - accuracy: 0.9624 - precision: 0.9621 - recall: 0.9626 - auc: 0.9937 - val_loss: 0.7046 - val_accuracy: 0.7828 - val_precision: 0.6999 - val_recall: 0.9899 - val_auc: 0.9474\n",
            "Epoch 1788/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1116 - accuracy: 0.9576 - precision: 0.9581 - recall: 0.9569 - auc: 0.9919 - val_loss: 0.5949 - val_accuracy: 0.7954 - val_precision: 0.7123 - val_recall: 0.9907 - val_auc: 0.9546\n",
            "Epoch 1789/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0996 - accuracy: 0.9618 - precision: 0.9640 - recall: 0.9595 - auc: 0.9936 - val_loss: 0.6971 - val_accuracy: 0.7764 - val_precision: 0.6930 - val_recall: 0.9925 - val_auc: 0.9546\n",
            "Epoch 1790/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.0934 - accuracy: 0.9644 - precision: 0.9667 - recall: 0.9620 - auc: 0.9942 - val_loss: 0.8168 - val_accuracy: 0.7436 - val_precision: 0.6618 - val_recall: 0.9960 - val_auc: 0.9561\n",
            "Epoch 1791/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1082 - accuracy: 0.9587 - precision: 0.9578 - recall: 0.9595 - auc: 0.9924 - val_loss: 0.7410 - val_accuracy: 0.7553 - val_precision: 0.6727 - val_recall: 0.9939 - val_auc: 0.9516\n",
            "Epoch 1792/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1037 - accuracy: 0.9602 - precision: 0.9616 - recall: 0.9587 - auc: 0.9931 - val_loss: 0.6844 - val_accuracy: 0.7728 - val_precision: 0.6892 - val_recall: 0.9932 - val_auc: 0.9571\n",
            "Epoch 1793/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.0990 - accuracy: 0.9620 - precision: 0.9632 - recall: 0.9608 - auc: 0.9936 - val_loss: 0.7591 - val_accuracy: 0.7556 - val_precision: 0.6726 - val_recall: 0.9954 - val_auc: 0.9563\n",
            "Epoch 1794/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0964 - accuracy: 0.9630 - precision: 0.9642 - recall: 0.9617 - auc: 0.9938 - val_loss: 1.3382 - val_accuracy: 0.6662 - val_precision: 0.6000 - val_recall: 0.9968 - val_auc: 0.8404\n",
            "Epoch 1795/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1026 - accuracy: 0.9606 - precision: 0.9622 - recall: 0.9589 - auc: 0.9932 - val_loss: 1.0684 - val_accuracy: 0.6960 - val_precision: 0.6223 - val_recall: 0.9970 - val_auc: 0.9149\n",
            "Epoch 1796/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0980 - accuracy: 0.9627 - precision: 0.9637 - recall: 0.9617 - auc: 0.9937 - val_loss: 0.9867 - val_accuracy: 0.7065 - val_precision: 0.6306 - val_recall: 0.9966 - val_auc: 0.9401\n",
            "Epoch 1797/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1467 - accuracy: 0.9442 - precision: 0.9397 - recall: 0.9494 - auc: 0.9866 - val_loss: 0.4033 - val_accuracy: 0.8058 - val_precision: 0.9118 - val_recall: 0.6769 - val_auc: 0.9294\n",
            "Epoch 1798/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1646 - accuracy: 0.9360 - precision: 0.9324 - recall: 0.9402 - auc: 0.9835 - val_loss: 0.2816 - val_accuracy: 0.8886 - val_precision: 0.8327 - val_recall: 0.9725 - val_auc: 0.9679\n",
            "Epoch 1799/2000\n",
            "10/10 [==============================] - 4s 385ms/step - loss: 0.1125 - accuracy: 0.9574 - precision: 0.9564 - recall: 0.9584 - auc: 0.9920 - val_loss: 0.4488 - val_accuracy: 0.8398 - val_precision: 0.7625 - val_recall: 0.9869 - val_auc: 0.9640\n",
            "Epoch 1800/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1071 - accuracy: 0.9591 - precision: 0.9586 - recall: 0.9597 - auc: 0.9925 - val_loss: 0.5835 - val_accuracy: 0.8087 - val_precision: 0.7269 - val_recall: 0.9887 - val_auc: 0.9564\n",
            "Epoch 1801/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1106 - accuracy: 0.9573 - precision: 0.9597 - recall: 0.9547 - auc: 0.9921 - val_loss: 0.6261 - val_accuracy: 0.7887 - val_precision: 0.7053 - val_recall: 0.9916 - val_auc: 0.9566\n",
            "Epoch 1802/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1117 - accuracy: 0.9573 - precision: 0.9573 - recall: 0.9574 - auc: 0.9919 - val_loss: 0.4793 - val_accuracy: 0.8316 - val_precision: 0.7515 - val_recall: 0.9906 - val_auc: 0.9694\n",
            "Epoch 1803/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1043 - accuracy: 0.9602 - precision: 0.9621 - recall: 0.9582 - auc: 0.9929 - val_loss: 0.6775 - val_accuracy: 0.7740 - val_precision: 0.6901 - val_recall: 0.9941 - val_auc: 0.9599\n",
            "Epoch 1804/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.0941 - accuracy: 0.9640 - precision: 0.9658 - recall: 0.9619 - auc: 0.9942 - val_loss: 0.6572 - val_accuracy: 0.7851 - val_precision: 0.7011 - val_recall: 0.9935 - val_auc: 0.9614\n",
            "Epoch 1805/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0899 - accuracy: 0.9658 - precision: 0.9676 - recall: 0.9639 - auc: 0.9947 - val_loss: 0.8051 - val_accuracy: 0.7468 - val_precision: 0.6646 - val_recall: 0.9958 - val_auc: 0.9568\n",
            "Epoch 1806/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1008 - accuracy: 0.9617 - precision: 0.9626 - recall: 0.9608 - auc: 0.9933 - val_loss: 0.6334 - val_accuracy: 0.7876 - val_precision: 0.7038 - val_recall: 0.9929 - val_auc: 0.9579\n",
            "Epoch 1807/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.0985 - accuracy: 0.9628 - precision: 0.9644 - recall: 0.9610 - auc: 0.9937 - val_loss: 0.7953 - val_accuracy: 0.7407 - val_precision: 0.6592 - val_recall: 0.9959 - val_auc: 0.9552\n",
            "Epoch 1808/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1114 - accuracy: 0.9576 - precision: 0.9571 - recall: 0.9581 - auc: 0.9919 - val_loss: 0.5512 - val_accuracy: 0.8122 - val_precision: 0.7293 - val_recall: 0.9926 - val_auc: 0.9668\n",
            "Epoch 1809/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.0938 - accuracy: 0.9639 - precision: 0.9660 - recall: 0.9617 - auc: 0.9942 - val_loss: 0.8395 - val_accuracy: 0.7365 - val_precision: 0.6556 - val_recall: 0.9960 - val_auc: 0.9535\n",
            "Epoch 1810/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1092 - accuracy: 0.9584 - precision: 0.9582 - recall: 0.9587 - auc: 0.9922 - val_loss: 0.5303 - val_accuracy: 0.8050 - val_precision: 0.7213 - val_recall: 0.9938 - val_auc: 0.9693\n",
            "Epoch 1811/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1311 - accuracy: 0.9502 - precision: 0.9477 - recall: 0.9531 - auc: 0.9891 - val_loss: 0.2413 - val_accuracy: 0.9019 - val_precision: 0.9101 - val_recall: 0.8918 - val_auc: 0.9648\n",
            "Epoch 1812/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1091 - accuracy: 0.9580 - precision: 0.9593 - recall: 0.9566 - auc: 0.9925 - val_loss: 0.7418 - val_accuracy: 0.7613 - val_precision: 0.6780 - val_recall: 0.9948 - val_auc: 0.9541\n",
            "Epoch 1813/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0950 - accuracy: 0.9635 - precision: 0.9654 - recall: 0.9616 - auc: 0.9941 - val_loss: 0.8237 - val_accuracy: 0.7460 - val_precision: 0.6640 - val_recall: 0.9956 - val_auc: 0.9529\n",
            "Epoch 1814/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.0971 - accuracy: 0.9626 - precision: 0.9636 - recall: 0.9615 - auc: 0.9938 - val_loss: 0.5781 - val_accuracy: 0.7873 - val_precision: 0.8737 - val_recall: 0.6716 - val_auc: 0.8944\n",
            "Epoch 1815/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.2050 - accuracy: 0.9223 - precision: 0.9133 - recall: 0.9332 - auc: 0.9747 - val_loss: 0.5638 - val_accuracy: 0.7587 - val_precision: 0.8736 - val_recall: 0.6048 - val_auc: 0.8795\n",
            "Epoch 1816/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1720 - accuracy: 0.9327 - precision: 0.9267 - recall: 0.9397 - auc: 0.9817 - val_loss: 0.4970 - val_accuracy: 0.7768 - val_precision: 0.9028 - val_recall: 0.6202 - val_auc: 0.9106\n",
            "Epoch 1817/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1656 - accuracy: 0.9346 - precision: 0.9298 - recall: 0.9402 - auc: 0.9829 - val_loss: 0.3584 - val_accuracy: 0.8472 - val_precision: 0.9093 - val_recall: 0.7712 - val_auc: 0.9428\n",
            "Epoch 1818/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1576 - accuracy: 0.9383 - precision: 0.9326 - recall: 0.9449 - auc: 0.9844 - val_loss: 0.2395 - val_accuracy: 0.9043 - val_precision: 0.8989 - val_recall: 0.9110 - val_auc: 0.9643\n",
            "Epoch 1819/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1471 - accuracy: 0.9431 - precision: 0.9405 - recall: 0.9461 - auc: 0.9863 - val_loss: 0.3233 - val_accuracy: 0.8710 - val_precision: 0.8059 - val_recall: 0.9773 - val_auc: 0.9643\n",
            "Epoch 1820/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1221 - accuracy: 0.9533 - precision: 0.9530 - recall: 0.9537 - auc: 0.9905 - val_loss: 0.3705 - val_accuracy: 0.8618 - val_precision: 0.7937 - val_recall: 0.9775 - val_auc: 0.9587\n",
            "Epoch 1821/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1315 - accuracy: 0.9497 - precision: 0.9483 - recall: 0.9513 - auc: 0.9890 - val_loss: 0.4460 - val_accuracy: 0.8305 - val_precision: 0.7510 - val_recall: 0.9886 - val_auc: 0.9607\n",
            "Epoch 1822/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1015 - accuracy: 0.9615 - precision: 0.9643 - recall: 0.9585 - auc: 0.9935 - val_loss: 0.6110 - val_accuracy: 0.7893 - val_precision: 0.7053 - val_recall: 0.9934 - val_auc: 0.9572\n",
            "Epoch 1823/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0985 - accuracy: 0.9623 - precision: 0.9616 - recall: 0.9631 - auc: 0.9937 - val_loss: 0.7442 - val_accuracy: 0.7571 - val_precision: 0.6741 - val_recall: 0.9950 - val_auc: 0.9549\n",
            "Epoch 1824/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1473 - accuracy: 0.9445 - precision: 0.9416 - recall: 0.9478 - auc: 0.9865 - val_loss: 0.5500 - val_accuracy: 0.7823 - val_precision: 0.8868 - val_recall: 0.6471 - val_auc: 0.9075\n",
            "Epoch 1825/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1757 - accuracy: 0.9303 - precision: 0.9261 - recall: 0.9353 - auc: 0.9810 - val_loss: 0.5308 - val_accuracy: 0.7270 - val_precision: 0.9213 - val_recall: 0.4961 - val_auc: 0.9129\n",
            "Epoch 1826/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1690 - accuracy: 0.9331 - precision: 0.9304 - recall: 0.9362 - auc: 0.9823 - val_loss: 0.4027 - val_accuracy: 0.7982 - val_precision: 0.9221 - val_recall: 0.6513 - val_auc: 0.9330\n",
            "Epoch 1827/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1619 - accuracy: 0.9366 - precision: 0.9345 - recall: 0.9391 - auc: 0.9836 - val_loss: 0.3565 - val_accuracy: 0.8346 - val_precision: 0.9187 - val_recall: 0.7340 - val_auc: 0.9437\n",
            "Epoch 1828/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1649 - accuracy: 0.9349 - precision: 0.9294 - recall: 0.9413 - auc: 0.9830 - val_loss: 0.2618 - val_accuracy: 0.8945 - val_precision: 0.8871 - val_recall: 0.9038 - val_auc: 0.9577\n",
            "Epoch 1829/2000\n",
            "10/10 [==============================] - 4s 404ms/step - loss: 0.1586 - accuracy: 0.9378 - precision: 0.9346 - recall: 0.9416 - auc: 0.9842 - val_loss: 0.2902 - val_accuracy: 0.8866 - val_precision: 0.8309 - val_recall: 0.9707 - val_auc: 0.9673\n",
            "Epoch 1830/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1495 - accuracy: 0.9418 - precision: 0.9385 - recall: 0.9456 - auc: 0.9859 - val_loss: 0.3723 - val_accuracy: 0.8587 - val_precision: 0.7867 - val_recall: 0.9842 - val_auc: 0.9670\n",
            "Epoch 1831/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1295 - accuracy: 0.9501 - precision: 0.9487 - recall: 0.9518 - auc: 0.9894 - val_loss: 0.2978 - val_accuracy: 0.8882 - val_precision: 0.8381 - val_recall: 0.9621 - val_auc: 0.9627\n",
            "Epoch 1832/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1128 - accuracy: 0.9571 - precision: 0.9572 - recall: 0.9571 - auc: 0.9918 - val_loss: 0.3738 - val_accuracy: 0.8679 - val_precision: 0.8048 - val_recall: 0.9713 - val_auc: 0.9582\n",
            "Epoch 1833/2000\n",
            "10/10 [==============================] - 4s 417ms/step - loss: 0.1009 - accuracy: 0.9617 - precision: 0.9629 - recall: 0.9603 - auc: 0.9934 - val_loss: 0.5425 - val_accuracy: 0.8229 - val_precision: 0.7421 - val_recall: 0.9895 - val_auc: 0.9604\n",
            "Epoch 1834/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1068 - accuracy: 0.9593 - precision: 0.9594 - recall: 0.9591 - auc: 0.9925 - val_loss: 0.6875 - val_accuracy: 0.7722 - val_precision: 0.6884 - val_recall: 0.9942 - val_auc: 0.9581\n",
            "Epoch 1835/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1023 - accuracy: 0.9609 - precision: 0.9630 - recall: 0.9586 - auc: 0.9933 - val_loss: 0.6542 - val_accuracy: 0.7903 - val_precision: 0.7063 - val_recall: 0.9936 - val_auc: 0.9610\n",
            "Epoch 1836/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1016 - accuracy: 0.9613 - precision: 0.9602 - recall: 0.9624 - auc: 0.9932 - val_loss: 0.7135 - val_accuracy: 0.7721 - val_precision: 0.6883 - val_recall: 0.9944 - val_auc: 0.9588\n",
            "Epoch 1837/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.0935 - accuracy: 0.9647 - precision: 0.9674 - recall: 0.9618 - auc: 0.9943 - val_loss: 0.8753 - val_accuracy: 0.7358 - val_precision: 0.6549 - val_recall: 0.9965 - val_auc: 0.9538\n",
            "Epoch 1838/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0916 - accuracy: 0.9653 - precision: 0.9663 - recall: 0.9642 - auc: 0.9944 - val_loss: 0.9199 - val_accuracy: 0.7290 - val_precision: 0.6491 - val_recall: 0.9965 - val_auc: 0.9527\n",
            "Epoch 1839/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0904 - accuracy: 0.9656 - precision: 0.9685 - recall: 0.9625 - auc: 0.9946 - val_loss: 0.9311 - val_accuracy: 0.7225 - val_precision: 0.6436 - val_recall: 0.9970 - val_auc: 0.9518\n",
            "Epoch 1840/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.0970 - accuracy: 0.9635 - precision: 0.9648 - recall: 0.9622 - auc: 0.9937 - val_loss: 1.0502 - val_accuracy: 0.6879 - val_precision: 0.6159 - val_recall: 0.9980 - val_auc: 0.9382\n",
            "Epoch 1841/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1594 - accuracy: 0.9380 - precision: 0.9307 - recall: 0.9465 - auc: 0.9841 - val_loss: 0.3892 - val_accuracy: 0.8117 - val_precision: 0.9102 - val_recall: 0.6915 - val_auc: 0.9331\n",
            "Epoch 1842/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1666 - accuracy: 0.9345 - precision: 0.9302 - recall: 0.9395 - auc: 0.9829 - val_loss: 0.3915 - val_accuracy: 0.8177 - val_precision: 0.9224 - val_recall: 0.6937 - val_auc: 0.9400\n",
            "Epoch 1843/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1564 - accuracy: 0.9387 - precision: 0.9367 - recall: 0.9410 - auc: 0.9847 - val_loss: 0.2492 - val_accuracy: 0.8999 - val_precision: 0.8996 - val_recall: 0.9002 - val_auc: 0.9621\n",
            "Epoch 1844/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1460 - accuracy: 0.9437 - precision: 0.9418 - recall: 0.9458 - auc: 0.9866 - val_loss: 0.3568 - val_accuracy: 0.8557 - val_precision: 0.7824 - val_recall: 0.9854 - val_auc: 0.9680\n",
            "Epoch 1845/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1163 - accuracy: 0.9556 - precision: 0.9574 - recall: 0.9538 - auc: 0.9914 - val_loss: 0.4427 - val_accuracy: 0.8361 - val_precision: 0.7582 - val_recall: 0.9868 - val_auc: 0.9625\n",
            "Epoch 1846/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1062 - accuracy: 0.9593 - precision: 0.9593 - recall: 0.9594 - auc: 0.9927 - val_loss: 0.5514 - val_accuracy: 0.8076 - val_precision: 0.7250 - val_recall: 0.9908 - val_auc: 0.9612\n",
            "Epoch 1847/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.0940 - accuracy: 0.9642 - precision: 0.9668 - recall: 0.9614 - auc: 0.9942 - val_loss: 0.6941 - val_accuracy: 0.7685 - val_precision: 0.6850 - val_recall: 0.9940 - val_auc: 0.9553\n",
            "Epoch 1848/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.0921 - accuracy: 0.9645 - precision: 0.9655 - recall: 0.9634 - auc: 0.9944 - val_loss: 0.8174 - val_accuracy: 0.7389 - val_precision: 0.6578 - val_recall: 0.9958 - val_auc: 0.9518\n",
            "Epoch 1849/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1438 - accuracy: 0.9448 - precision: 0.9393 - recall: 0.9510 - auc: 0.9870 - val_loss: 0.4105 - val_accuracy: 0.8387 - val_precision: 0.7610 - val_recall: 0.9875 - val_auc: 0.9661\n",
            "Epoch 1850/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1203 - accuracy: 0.9542 - precision: 0.9546 - recall: 0.9537 - auc: 0.9910 - val_loss: 0.3544 - val_accuracy: 0.8687 - val_precision: 0.8143 - val_recall: 0.9550 - val_auc: 0.9530\n",
            "Epoch 1851/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1625 - accuracy: 0.9381 - precision: 0.9341 - recall: 0.9429 - auc: 0.9835 - val_loss: 0.3465 - val_accuracy: 0.8637 - val_precision: 0.7958 - val_recall: 0.9783 - val_auc: 0.9637\n",
            "Epoch 1852/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1076 - accuracy: 0.9600 - precision: 0.9628 - recall: 0.9569 - auc: 0.9927 - val_loss: 0.5404 - val_accuracy: 0.8098 - val_precision: 0.7276 - val_recall: 0.9900 - val_auc: 0.9592\n",
            "Epoch 1853/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.0957 - accuracy: 0.9639 - precision: 0.9640 - recall: 0.9638 - auc: 0.9940 - val_loss: 0.7349 - val_accuracy: 0.7589 - val_precision: 0.6757 - val_recall: 0.9951 - val_auc: 0.9589\n",
            "Epoch 1854/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.0933 - accuracy: 0.9643 - precision: 0.9654 - recall: 0.9630 - auc: 0.9943 - val_loss: 0.8915 - val_accuracy: 0.7242 - val_precision: 0.6451 - val_recall: 0.9965 - val_auc: 0.9528\n",
            "Epoch 1855/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1147 - accuracy: 0.9565 - precision: 0.9554 - recall: 0.9578 - auc: 0.9914 - val_loss: 0.6973 - val_accuracy: 0.7574 - val_precision: 0.6744 - val_recall: 0.9951 - val_auc: 0.9595\n",
            "Epoch 1856/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0980 - accuracy: 0.9630 - precision: 0.9667 - recall: 0.9590 - auc: 0.9938 - val_loss: 0.6958 - val_accuracy: 0.7709 - val_precision: 0.6871 - val_recall: 0.9948 - val_auc: 0.9611\n",
            "Epoch 1857/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0911 - accuracy: 0.9655 - precision: 0.9675 - recall: 0.9634 - auc: 0.9945 - val_loss: 0.8111 - val_accuracy: 0.7476 - val_precision: 0.6655 - val_recall: 0.9953 - val_auc: 0.9537\n",
            "Epoch 1858/2000\n",
            "10/10 [==============================] - 4s 402ms/step - loss: 0.1074 - accuracy: 0.9594 - precision: 0.9605 - recall: 0.9581 - auc: 0.9924 - val_loss: 0.7641 - val_accuracy: 0.7513 - val_precision: 0.6689 - val_recall: 0.9947 - val_auc: 0.9529\n",
            "Epoch 1859/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0924 - accuracy: 0.9648 - precision: 0.9670 - recall: 0.9624 - auc: 0.9945 - val_loss: 0.9263 - val_accuracy: 0.7205 - val_precision: 0.6420 - val_recall: 0.9967 - val_auc: 0.9526\n",
            "Epoch 1860/2000\n",
            "10/10 [==============================] - 4s 387ms/step - loss: 0.1251 - accuracy: 0.9536 - precision: 0.9516 - recall: 0.9559 - auc: 0.9900 - val_loss: 1.1388 - val_accuracy: 0.6744 - val_precision: 0.6060 - val_recall: 0.9968 - val_auc: 0.8990\n",
            "Epoch 1861/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1842 - accuracy: 0.9283 - precision: 0.9221 - recall: 0.9358 - auc: 0.9792 - val_loss: 0.2642 - val_accuracy: 0.8920 - val_precision: 0.8972 - val_recall: 0.8854 - val_auc: 0.9590\n",
            "Epoch 1862/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1662 - accuracy: 0.9346 - precision: 0.9310 - recall: 0.9389 - auc: 0.9828 - val_loss: 0.2774 - val_accuracy: 0.8761 - val_precision: 0.9142 - val_recall: 0.8299 - val_auc: 0.9553\n",
            "Epoch 1863/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1552 - accuracy: 0.9393 - precision: 0.9360 - recall: 0.9431 - auc: 0.9850 - val_loss: 0.2478 - val_accuracy: 0.8967 - val_precision: 0.9121 - val_recall: 0.8778 - val_auc: 0.9626\n",
            "Epoch 1864/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1446 - accuracy: 0.9433 - precision: 0.9395 - recall: 0.9477 - auc: 0.9869 - val_loss: 0.3754 - val_accuracy: 0.8620 - val_precision: 0.7907 - val_recall: 0.9844 - val_auc: 0.9678\n",
            "Epoch 1865/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1254 - accuracy: 0.9517 - precision: 0.9512 - recall: 0.9523 - auc: 0.9900 - val_loss: 0.4186 - val_accuracy: 0.8527 - val_precision: 0.7793 - val_recall: 0.9839 - val_auc: 0.9616\n",
            "Epoch 1866/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1767 - accuracy: 0.9312 - precision: 0.9225 - recall: 0.9414 - auc: 0.9808 - val_loss: 0.9557 - val_accuracy: 0.6424 - val_precision: 0.9017 - val_recall: 0.3193 - val_auc: 0.8400\n",
            "Epoch 1867/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1740 - accuracy: 0.9309 - precision: 0.9277 - recall: 0.9347 - auc: 0.9814 - val_loss: 0.8269 - val_accuracy: 0.6764 - val_precision: 0.9227 - val_recall: 0.3848 - val_auc: 0.8796\n",
            "Epoch 1868/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1761 - accuracy: 0.9301 - precision: 0.9258 - recall: 0.9353 - auc: 0.9807 - val_loss: 0.4874 - val_accuracy: 0.7875 - val_precision: 0.9091 - val_recall: 0.6387 - val_auc: 0.9181\n",
            "Epoch 1869/2000\n",
            "10/10 [==============================] - 4s 421ms/step - loss: 0.1701 - accuracy: 0.9331 - precision: 0.9298 - recall: 0.9368 - auc: 0.9820 - val_loss: 0.3982 - val_accuracy: 0.8209 - val_precision: 0.9114 - val_recall: 0.7109 - val_auc: 0.9342\n",
            "Epoch 1870/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1671 - accuracy: 0.9340 - precision: 0.9306 - recall: 0.9380 - auc: 0.9826 - val_loss: 0.2939 - val_accuracy: 0.8736 - val_precision: 0.8944 - val_recall: 0.8473 - val_auc: 0.9490\n",
            "Epoch 1871/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1654 - accuracy: 0.9347 - precision: 0.9310 - recall: 0.9389 - auc: 0.9829 - val_loss: 0.3072 - val_accuracy: 0.8652 - val_precision: 0.9049 - val_recall: 0.8159 - val_auc: 0.9492\n",
            "Epoch 1872/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1657 - accuracy: 0.9341 - precision: 0.9299 - recall: 0.9391 - auc: 0.9829 - val_loss: 0.2740 - val_accuracy: 0.8839 - val_precision: 0.9046 - val_recall: 0.8582 - val_auc: 0.9559\n",
            "Epoch 1873/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1616 - accuracy: 0.9362 - precision: 0.9337 - recall: 0.9390 - auc: 0.9837 - val_loss: 0.2608 - val_accuracy: 0.8935 - val_precision: 0.8869 - val_recall: 0.9021 - val_auc: 0.9579\n",
            "Epoch 1874/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1613 - accuracy: 0.9362 - precision: 0.9321 - recall: 0.9411 - auc: 0.9837 - val_loss: 0.2475 - val_accuracy: 0.9004 - val_precision: 0.8877 - val_recall: 0.9166 - val_auc: 0.9621\n",
            "Epoch 1875/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1564 - accuracy: 0.9384 - precision: 0.9359 - recall: 0.9412 - auc: 0.9847 - val_loss: 0.2485 - val_accuracy: 0.9017 - val_precision: 0.8550 - val_recall: 0.9675 - val_auc: 0.9716\n",
            "Epoch 1876/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1622 - accuracy: 0.9358 - precision: 0.9325 - recall: 0.9397 - auc: 0.9836 - val_loss: 0.2467 - val_accuracy: 0.9025 - val_precision: 0.8719 - val_recall: 0.9435 - val_auc: 0.9649\n",
            "Epoch 1877/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1589 - accuracy: 0.9369 - precision: 0.9332 - recall: 0.9412 - auc: 0.9843 - val_loss: 0.2880 - val_accuracy: 0.8849 - val_precision: 0.8247 - val_recall: 0.9774 - val_auc: 0.9704\n",
            "Epoch 1878/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1607 - accuracy: 0.9363 - precision: 0.9321 - recall: 0.9411 - auc: 0.9839 - val_loss: 0.2513 - val_accuracy: 0.9007 - val_precision: 0.8626 - val_recall: 0.9530 - val_auc: 0.9660\n",
            "Epoch 1879/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1514 - accuracy: 0.9406 - precision: 0.9369 - recall: 0.9449 - auc: 0.9856 - val_loss: 0.2625 - val_accuracy: 0.8970 - val_precision: 0.8520 - val_recall: 0.9609 - val_auc: 0.9662\n",
            "Epoch 1880/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1625 - accuracy: 0.9358 - precision: 0.9310 - recall: 0.9414 - auc: 0.9835 - val_loss: 0.2425 - val_accuracy: 0.9050 - val_precision: 0.8695 - val_recall: 0.9529 - val_auc: 0.9682\n",
            "Epoch 1881/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1577 - accuracy: 0.9376 - precision: 0.9354 - recall: 0.9401 - auc: 0.9845 - val_loss: 0.2627 - val_accuracy: 0.8965 - val_precision: 0.8532 - val_recall: 0.9577 - val_auc: 0.9650\n",
            "Epoch 1882/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1542 - accuracy: 0.9397 - precision: 0.9353 - recall: 0.9448 - auc: 0.9851 - val_loss: 0.2965 - val_accuracy: 0.8843 - val_precision: 0.8287 - val_recall: 0.9689 - val_auc: 0.9645\n",
            "Epoch 1883/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1594 - accuracy: 0.9373 - precision: 0.9352 - recall: 0.9398 - auc: 0.9841 - val_loss: 0.3567 - val_accuracy: 0.8606 - val_precision: 0.7874 - val_recall: 0.9879 - val_auc: 0.9732\n",
            "Epoch 1884/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1508 - accuracy: 0.9410 - precision: 0.9389 - recall: 0.9434 - auc: 0.9857 - val_loss: 0.3018 - val_accuracy: 0.8812 - val_precision: 0.8223 - val_recall: 0.9725 - val_auc: 0.9647\n",
            "Epoch 1885/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1571 - accuracy: 0.9378 - precision: 0.9325 - recall: 0.9440 - auc: 0.9846 - val_loss: 0.2877 - val_accuracy: 0.8847 - val_precision: 0.8281 - val_recall: 0.9709 - val_auc: 0.9658\n",
            "Epoch 1886/2000\n",
            "10/10 [==============================] - 4s 415ms/step - loss: 0.1496 - accuracy: 0.9415 - precision: 0.9385 - recall: 0.9450 - auc: 0.9860 - val_loss: 0.2684 - val_accuracy: 0.8954 - val_precision: 0.8479 - val_recall: 0.9636 - val_auc: 0.9672\n",
            "Epoch 1887/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1581 - accuracy: 0.9374 - precision: 0.9326 - recall: 0.9431 - auc: 0.9844 - val_loss: 0.2963 - val_accuracy: 0.8842 - val_precision: 0.8272 - val_recall: 0.9712 - val_auc: 0.9661\n",
            "Epoch 1888/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1473 - accuracy: 0.9422 - precision: 0.9403 - recall: 0.9444 - auc: 0.9864 - val_loss: 1.2454 - val_accuracy: 0.6786 - val_precision: 0.6090 - val_recall: 0.9967 - val_auc: 0.8711\n",
            "Epoch 1889/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1687 - accuracy: 0.9331 - precision: 0.9282 - recall: 0.9389 - auc: 0.9822 - val_loss: 0.3008 - val_accuracy: 0.8800 - val_precision: 0.8222 - val_recall: 0.9696 - val_auc: 0.9638\n",
            "Epoch 1890/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1483 - accuracy: 0.9422 - precision: 0.9400 - recall: 0.9447 - auc: 0.9863 - val_loss: 1.3896 - val_accuracy: 0.6572 - val_precision: 0.5936 - val_recall: 0.9968 - val_auc: 0.8484\n",
            "Epoch 1891/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1736 - accuracy: 0.9315 - precision: 0.9241 - recall: 0.9402 - auc: 0.9812 - val_loss: 1.4993 - val_accuracy: 0.6398 - val_precision: 0.5814 - val_recall: 0.9975 - val_auc: 0.8359\n",
            "Epoch 1892/2000\n",
            "10/10 [==============================] - 4s 389ms/step - loss: 0.1698 - accuracy: 0.9327 - precision: 0.9279 - recall: 0.9384 - auc: 0.9820 - val_loss: 0.5816 - val_accuracy: 0.7937 - val_precision: 0.7101 - val_recall: 0.9922 - val_auc: 0.9512\n",
            "Epoch 1893/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1618 - accuracy: 0.9360 - precision: 0.9316 - recall: 0.9412 - auc: 0.9837 - val_loss: 0.2881 - val_accuracy: 0.8865 - val_precision: 0.8353 - val_recall: 0.9627 - val_auc: 0.9631\n",
            "Epoch 1894/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1525 - accuracy: 0.9400 - precision: 0.9360 - recall: 0.9447 - auc: 0.9854 - val_loss: 0.3223 - val_accuracy: 0.8738 - val_precision: 0.8111 - val_recall: 0.9744 - val_auc: 0.9638\n",
            "Epoch 1895/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1469 - accuracy: 0.9422 - precision: 0.9395 - recall: 0.9452 - auc: 0.9865 - val_loss: 0.3106 - val_accuracy: 0.8801 - val_precision: 0.8188 - val_recall: 0.9761 - val_auc: 0.9672\n",
            "Epoch 1896/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1469 - accuracy: 0.9424 - precision: 0.9392 - recall: 0.9462 - auc: 0.9865 - val_loss: 0.3052 - val_accuracy: 0.8842 - val_precision: 0.8258 - val_recall: 0.9738 - val_auc: 0.9674\n",
            "Epoch 1897/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1434 - accuracy: 0.9433 - precision: 0.9424 - recall: 0.9444 - auc: 0.9871 - val_loss: 0.3077 - val_accuracy: 0.8816 - val_precision: 0.8228 - val_recall: 0.9727 - val_auc: 0.9662\n",
            "Epoch 1898/2000\n",
            "10/10 [==============================] - 4s 407ms/step - loss: 0.1423 - accuracy: 0.9440 - precision: 0.9413 - recall: 0.9472 - auc: 0.9873 - val_loss: 0.3169 - val_accuracy: 0.8807 - val_precision: 0.8202 - val_recall: 0.9749 - val_auc: 0.9673\n",
            "Epoch 1899/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1425 - accuracy: 0.9444 - precision: 0.9416 - recall: 0.9476 - auc: 0.9872 - val_loss: 0.3385 - val_accuracy: 0.8729 - val_precision: 0.8081 - val_recall: 0.9780 - val_auc: 0.9667\n",
            "Epoch 1900/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1579 - accuracy: 0.9374 - precision: 0.9358 - recall: 0.9392 - auc: 0.9844 - val_loss: 0.3086 - val_accuracy: 0.8811 - val_precision: 0.8235 - val_recall: 0.9701 - val_auc: 0.9648\n",
            "Epoch 1901/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1466 - accuracy: 0.9428 - precision: 0.9415 - recall: 0.9442 - auc: 0.9866 - val_loss: 0.3180 - val_accuracy: 0.8795 - val_precision: 0.8192 - val_recall: 0.9738 - val_auc: 0.9661\n",
            "Epoch 1902/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1505 - accuracy: 0.9405 - precision: 0.9371 - recall: 0.9443 - auc: 0.9858 - val_loss: 0.5034 - val_accuracy: 0.8184 - val_precision: 0.7361 - val_recall: 0.9924 - val_auc: 0.9680\n",
            "Epoch 1903/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1421 - accuracy: 0.9444 - precision: 0.9426 - recall: 0.9465 - auc: 0.9874 - val_loss: 0.3072 - val_accuracy: 0.8821 - val_precision: 0.8235 - val_recall: 0.9725 - val_auc: 0.9657\n",
            "Epoch 1904/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1455 - accuracy: 0.9429 - precision: 0.9387 - recall: 0.9477 - auc: 0.9867 - val_loss: 0.3354 - val_accuracy: 0.8697 - val_precision: 0.8034 - val_recall: 0.9789 - val_auc: 0.9660\n",
            "Epoch 1905/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1373 - accuracy: 0.9459 - precision: 0.9438 - recall: 0.9482 - auc: 0.9882 - val_loss: 0.3410 - val_accuracy: 0.8711 - val_precision: 0.8056 - val_recall: 0.9781 - val_auc: 0.9659\n",
            "Epoch 1906/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1385 - accuracy: 0.9460 - precision: 0.9452 - recall: 0.9469 - auc: 0.9879 - val_loss: 0.3615 - val_accuracy: 0.8641 - val_precision: 0.7947 - val_recall: 0.9818 - val_auc: 0.9667\n",
            "Epoch 1907/2000\n",
            "10/10 [==============================] - 4s 388ms/step - loss: 0.1380 - accuracy: 0.9462 - precision: 0.9442 - recall: 0.9486 - auc: 0.9880 - val_loss: 0.3368 - val_accuracy: 0.8744 - val_precision: 0.8099 - val_recall: 0.9782 - val_auc: 0.9668\n",
            "Epoch 1908/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.1538 - accuracy: 0.9400 - precision: 0.9365 - recall: 0.9440 - auc: 0.9851 - val_loss: 2.1809 - val_accuracy: 0.5471 - val_precision: 0.5246 - val_recall: 0.9995 - val_auc: 0.7178\n",
            "Epoch 1909/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1680 - accuracy: 0.9340 - precision: 0.9296 - recall: 0.9392 - auc: 0.9824 - val_loss: 1.8196 - val_accuracy: 0.5784 - val_precision: 0.5425 - val_recall: 0.9989 - val_auc: 0.7730\n",
            "Epoch 1910/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1665 - accuracy: 0.9345 - precision: 0.9287 - recall: 0.9412 - auc: 0.9826 - val_loss: 1.3280 - val_accuracy: 0.6372 - val_precision: 0.5797 - val_recall: 0.9974 - val_auc: 0.8634\n",
            "Epoch 1911/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1635 - accuracy: 0.9358 - precision: 0.9321 - recall: 0.9401 - auc: 0.9832 - val_loss: 0.9339 - val_accuracy: 0.6988 - val_precision: 0.6245 - val_recall: 0.9963 - val_auc: 0.9203\n",
            "Epoch 1912/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1634 - accuracy: 0.9359 - precision: 0.9322 - recall: 0.9403 - auc: 0.9833 - val_loss: 0.6508 - val_accuracy: 0.7677 - val_precision: 0.6843 - val_recall: 0.9939 - val_auc: 0.9478\n",
            "Epoch 1913/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1601 - accuracy: 0.9369 - precision: 0.9321 - recall: 0.9424 - auc: 0.9839 - val_loss: 0.4962 - val_accuracy: 0.8164 - val_precision: 0.7346 - val_recall: 0.9907 - val_auc: 0.9605\n",
            "Epoch 1914/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1568 - accuracy: 0.9388 - precision: 0.9353 - recall: 0.9429 - auc: 0.9845 - val_loss: 0.4019 - val_accuracy: 0.8458 - val_precision: 0.7698 - val_recall: 0.9865 - val_auc: 0.9658\n",
            "Epoch 1915/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1541 - accuracy: 0.9396 - precision: 0.9336 - recall: 0.9466 - auc: 0.9851 - val_loss: 0.3457 - val_accuracy: 0.8644 - val_precision: 0.7946 - val_recall: 0.9827 - val_auc: 0.9676\n",
            "Epoch 1916/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1516 - accuracy: 0.9409 - precision: 0.9356 - recall: 0.9469 - auc: 0.9855 - val_loss: 0.3065 - val_accuracy: 0.8779 - val_precision: 0.8162 - val_recall: 0.9753 - val_auc: 0.9667\n",
            "Epoch 1917/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1454 - accuracy: 0.9431 - precision: 0.9395 - recall: 0.9473 - auc: 0.9867 - val_loss: 0.2936 - val_accuracy: 0.8878 - val_precision: 0.8356 - val_recall: 0.9655 - val_auc: 0.9647\n",
            "Epoch 1918/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1343 - accuracy: 0.9481 - precision: 0.9467 - recall: 0.9498 - auc: 0.9886 - val_loss: 0.2988 - val_accuracy: 0.8858 - val_precision: 0.8341 - val_recall: 0.9631 - val_auc: 0.9635\n",
            "Epoch 1919/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1430 - accuracy: 0.9453 - precision: 0.9414 - recall: 0.9498 - auc: 0.9870 - val_loss: 0.3577 - val_accuracy: 0.8560 - val_precision: 0.7851 - val_recall: 0.9801 - val_auc: 0.9618\n",
            "Epoch 1920/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1700 - accuracy: 0.9327 - precision: 0.9252 - recall: 0.9415 - auc: 0.9821 - val_loss: 0.2663 - val_accuracy: 0.8958 - val_precision: 0.8677 - val_recall: 0.9339 - val_auc: 0.9603\n",
            "Epoch 1921/2000\n",
            "10/10 [==============================] - 4s 440ms/step - loss: 0.1585 - accuracy: 0.9376 - precision: 0.9345 - recall: 0.9411 - auc: 0.9843 - val_loss: 0.2639 - val_accuracy: 0.8977 - val_precision: 0.8646 - val_recall: 0.9431 - val_auc: 0.9621\n",
            "Epoch 1922/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.1527 - accuracy: 0.9399 - precision: 0.9372 - recall: 0.9430 - auc: 0.9854 - val_loss: 0.2814 - val_accuracy: 0.8907 - val_precision: 0.8467 - val_recall: 0.9542 - val_auc: 0.9619\n",
            "Epoch 1923/2000\n",
            "10/10 [==============================] - 4s 406ms/step - loss: 0.1472 - accuracy: 0.9423 - precision: 0.9396 - recall: 0.9454 - auc: 0.9864 - val_loss: 0.2690 - val_accuracy: 0.8973 - val_precision: 0.8602 - val_recall: 0.9489 - val_auc: 0.9638\n",
            "Epoch 1924/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1476 - accuracy: 0.9418 - precision: 0.9393 - recall: 0.9447 - auc: 0.9864 - val_loss: 0.3009 - val_accuracy: 0.8874 - val_precision: 0.8313 - val_recall: 0.9719 - val_auc: 0.9671\n",
            "Epoch 1925/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1386 - accuracy: 0.9461 - precision: 0.9445 - recall: 0.9479 - auc: 0.9879 - val_loss: 0.3472 - val_accuracy: 0.8695 - val_precision: 0.8033 - val_recall: 0.9785 - val_auc: 0.9652\n",
            "Epoch 1926/2000\n",
            "10/10 [==============================] - 4s 411ms/step - loss: 0.1396 - accuracy: 0.9456 - precision: 0.9433 - recall: 0.9483 - auc: 0.9877 - val_loss: 0.3430 - val_accuracy: 0.8719 - val_precision: 0.8066 - val_recall: 0.9783 - val_auc: 0.9658\n",
            "Epoch 1927/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1347 - accuracy: 0.9475 - precision: 0.9462 - recall: 0.9490 - auc: 0.9885 - val_loss: 0.3496 - val_accuracy: 0.8707 - val_precision: 0.8047 - val_recall: 0.9790 - val_auc: 0.9660\n",
            "Epoch 1928/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1487 - accuracy: 0.9420 - precision: 0.9376 - recall: 0.9472 - auc: 0.9861 - val_loss: 0.3541 - val_accuracy: 0.8609 - val_precision: 0.7912 - val_recall: 0.9805 - val_auc: 0.9640\n",
            "Epoch 1929/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1556 - accuracy: 0.9389 - precision: 0.9370 - recall: 0.9411 - auc: 0.9849 - val_loss: 0.3322 - val_accuracy: 0.8707 - val_precision: 0.8061 - val_recall: 0.9761 - val_auc: 0.9634\n",
            "Epoch 1930/2000\n",
            "10/10 [==============================] - 4s 418ms/step - loss: 0.1420 - accuracy: 0.9443 - precision: 0.9406 - recall: 0.9485 - auc: 0.9873 - val_loss: 0.3301 - val_accuracy: 0.8732 - val_precision: 0.8104 - val_recall: 0.9743 - val_auc: 0.9640\n",
            "Epoch 1931/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1388 - accuracy: 0.9455 - precision: 0.9423 - recall: 0.9491 - auc: 0.9878 - val_loss: 0.3340 - val_accuracy: 0.8747 - val_precision: 0.8119 - val_recall: 0.9752 - val_auc: 0.9649\n",
            "Epoch 1932/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1322 - accuracy: 0.9483 - precision: 0.9477 - recall: 0.9491 - auc: 0.9890 - val_loss: 0.3482 - val_accuracy: 0.8715 - val_precision: 0.8083 - val_recall: 0.9739 - val_auc: 0.9630\n",
            "Epoch 1933/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1285 - accuracy: 0.9501 - precision: 0.9496 - recall: 0.9507 - auc: 0.9895 - val_loss: 0.3657 - val_accuracy: 0.8651 - val_precision: 0.7970 - val_recall: 0.9796 - val_auc: 0.9651\n",
            "Epoch 1934/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1259 - accuracy: 0.9506 - precision: 0.9493 - recall: 0.9521 - auc: 0.9900 - val_loss: 0.4093 - val_accuracy: 0.8542 - val_precision: 0.7815 - val_recall: 0.9833 - val_auc: 0.9641\n",
            "Epoch 1935/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1185 - accuracy: 0.9544 - precision: 0.9544 - recall: 0.9544 - auc: 0.9910 - val_loss: 0.3817 - val_accuracy: 0.8637 - val_precision: 0.7957 - val_recall: 0.9784 - val_auc: 0.9625\n",
            "Epoch 1936/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.1081 - accuracy: 0.9587 - precision: 0.9603 - recall: 0.9569 - auc: 0.9924 - val_loss: 0.3905 - val_accuracy: 0.8641 - val_precision: 0.7975 - val_recall: 0.9759 - val_auc: 0.9598\n",
            "Epoch 1937/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.0965 - accuracy: 0.9634 - precision: 0.9651 - recall: 0.9616 - auc: 0.9939 - val_loss: 0.4500 - val_accuracy: 0.8472 - val_precision: 0.7728 - val_recall: 0.9833 - val_auc: 0.9594\n",
            "Epoch 1938/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0909 - accuracy: 0.9654 - precision: 0.9671 - recall: 0.9636 - auc: 0.9945 - val_loss: 0.4966 - val_accuracy: 0.8356 - val_precision: 0.7575 - val_recall: 0.9870 - val_auc: 0.9592\n",
            "Epoch 1939/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1200 - accuracy: 0.9551 - precision: 0.9551 - recall: 0.9552 - auc: 0.9906 - val_loss: 0.5273 - val_accuracy: 0.8007 - val_precision: 0.7176 - val_recall: 0.9916 - val_auc: 0.9591\n",
            "Epoch 1940/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1162 - accuracy: 0.9560 - precision: 0.9561 - recall: 0.9558 - auc: 0.9915 - val_loss: 0.4043 - val_accuracy: 0.8477 - val_precision: 0.7812 - val_recall: 0.9658 - val_auc: 0.9503\n",
            "Epoch 1941/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1082 - accuracy: 0.9585 - precision: 0.9578 - recall: 0.9594 - auc: 0.9925 - val_loss: 0.4131 - val_accuracy: 0.8510 - val_precision: 0.7776 - val_recall: 0.9832 - val_auc: 0.9623\n",
            "Epoch 1942/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1021 - accuracy: 0.9613 - precision: 0.9626 - recall: 0.9598 - auc: 0.9932 - val_loss: 0.7140 - val_accuracy: 0.7636 - val_precision: 0.6804 - val_recall: 0.9938 - val_auc: 0.9507\n",
            "Epoch 1943/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1077 - accuracy: 0.9588 - precision: 0.9613 - recall: 0.9562 - auc: 0.9926 - val_loss: 0.5590 - val_accuracy: 0.8026 - val_precision: 0.7199 - val_recall: 0.9904 - val_auc: 0.9542\n",
            "Epoch 1944/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.0983 - accuracy: 0.9624 - precision: 0.9637 - recall: 0.9610 - auc: 0.9937 - val_loss: 0.6292 - val_accuracy: 0.7899 - val_precision: 0.7067 - val_recall: 0.9908 - val_auc: 0.9507\n",
            "Epoch 1945/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.0983 - accuracy: 0.9623 - precision: 0.9624 - recall: 0.9622 - auc: 0.9937 - val_loss: 0.7831 - val_accuracy: 0.7473 - val_precision: 0.6654 - val_recall: 0.9945 - val_auc: 0.9475\n",
            "Epoch 1946/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1015 - accuracy: 0.9610 - precision: 0.9611 - recall: 0.9610 - auc: 0.9933 - val_loss: 0.7379 - val_accuracy: 0.7626 - val_precision: 0.6794 - val_recall: 0.9942 - val_auc: 0.9520\n",
            "Epoch 1947/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.0878 - accuracy: 0.9666 - precision: 0.9683 - recall: 0.9648 - auc: 0.9949 - val_loss: 0.8477 - val_accuracy: 0.7436 - val_precision: 0.6620 - val_recall: 0.9954 - val_auc: 0.9470\n",
            "Epoch 1948/2000\n",
            "10/10 [==============================] - 4s 401ms/step - loss: 0.0872 - accuracy: 0.9670 - precision: 0.9699 - recall: 0.9638 - auc: 0.9949 - val_loss: 0.9141 - val_accuracy: 0.7271 - val_precision: 0.6475 - val_recall: 0.9965 - val_auc: 0.9458\n",
            "Epoch 1949/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.0846 - accuracy: 0.9681 - precision: 0.9713 - recall: 0.9646 - auc: 0.9952 - val_loss: 1.0032 - val_accuracy: 0.7067 - val_precision: 0.6307 - val_recall: 0.9974 - val_auc: 0.9428\n",
            "Epoch 1950/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1060 - accuracy: 0.9599 - precision: 0.9602 - recall: 0.9597 - auc: 0.9926 - val_loss: 1.4877 - val_accuracy: 0.6220 - val_precision: 0.5695 - val_recall: 0.9988 - val_auc: 0.8859\n",
            "Epoch 1951/2000\n",
            "10/10 [==============================] - 4s 420ms/step - loss: 0.0975 - accuracy: 0.9630 - precision: 0.9649 - recall: 0.9609 - auc: 0.9939 - val_loss: 1.4939 - val_accuracy: 0.6273 - val_precision: 0.5729 - val_recall: 0.9988 - val_auc: 0.8884\n",
            "Epoch 1952/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.0951 - accuracy: 0.9636 - precision: 0.9654 - recall: 0.9615 - auc: 0.9940 - val_loss: 0.8645 - val_accuracy: 0.7360 - val_precision: 0.6553 - val_recall: 0.9955 - val_auc: 0.9477\n",
            "Epoch 1953/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1119 - accuracy: 0.9574 - precision: 0.9578 - recall: 0.9570 - auc: 0.9919 - val_loss: 0.6769 - val_accuracy: 0.7698 - val_precision: 0.6861 - val_recall: 0.9943 - val_auc: 0.9531\n",
            "Epoch 1954/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0877 - accuracy: 0.9668 - precision: 0.9692 - recall: 0.9642 - auc: 0.9949 - val_loss: 0.8813 - val_accuracy: 0.7336 - val_precision: 0.6531 - val_recall: 0.9962 - val_auc: 0.9481\n",
            "Epoch 1955/2000\n",
            "10/10 [==============================] - 4s 412ms/step - loss: 0.0908 - accuracy: 0.9655 - precision: 0.9672 - recall: 0.9637 - auc: 0.9945 - val_loss: 0.8972 - val_accuracy: 0.7283 - val_precision: 0.6485 - val_recall: 0.9965 - val_auc: 0.9486\n",
            "Epoch 1956/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0839 - accuracy: 0.9678 - precision: 0.9702 - recall: 0.9652 - auc: 0.9953 - val_loss: 1.0142 - val_accuracy: 0.7040 - val_precision: 0.6284 - val_recall: 0.9977 - val_auc: 0.9446\n",
            "Epoch 1957/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0827 - accuracy: 0.9684 - precision: 0.9699 - recall: 0.9669 - auc: 0.9953 - val_loss: 1.0468 - val_accuracy: 0.6968 - val_precision: 0.6228 - val_recall: 0.9978 - val_auc: 0.9439\n",
            "Epoch 1958/2000\n",
            "10/10 [==============================] - 4s 419ms/step - loss: 0.1064 - accuracy: 0.9597 - precision: 0.9596 - recall: 0.9598 - auc: 0.9925 - val_loss: 0.6604 - val_accuracy: 0.7614 - val_precision: 0.6780 - val_recall: 0.9955 - val_auc: 0.9591\n",
            "Epoch 1959/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.0945 - accuracy: 0.9644 - precision: 0.9655 - recall: 0.9633 - auc: 0.9942 - val_loss: 0.6370 - val_accuracy: 0.7845 - val_precision: 0.7003 - val_recall: 0.9944 - val_auc: 0.9616\n",
            "Epoch 1960/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.0845 - accuracy: 0.9681 - precision: 0.9701 - recall: 0.9661 - auc: 0.9952 - val_loss: 0.8296 - val_accuracy: 0.7463 - val_precision: 0.6642 - val_recall: 0.9959 - val_auc: 0.9528\n",
            "Epoch 1961/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0849 - accuracy: 0.9679 - precision: 0.9720 - recall: 0.9636 - auc: 0.9951 - val_loss: 0.8935 - val_accuracy: 0.7216 - val_precision: 0.6428 - val_recall: 0.9971 - val_auc: 0.9507\n",
            "Epoch 1962/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1334 - accuracy: 0.9496 - precision: 0.9482 - recall: 0.9513 - auc: 0.9885 - val_loss: 0.5065 - val_accuracy: 0.7957 - val_precision: 0.7121 - val_recall: 0.9925 - val_auc: 0.9610\n",
            "Epoch 1963/2000\n",
            "10/10 [==============================] - 4s 397ms/step - loss: 0.0977 - accuracy: 0.9632 - precision: 0.9637 - recall: 0.9626 - auc: 0.9939 - val_loss: 0.6522 - val_accuracy: 0.7834 - val_precision: 0.6995 - val_recall: 0.9936 - val_auc: 0.9598\n",
            "Epoch 1964/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.0872 - accuracy: 0.9670 - precision: 0.9702 - recall: 0.9637 - auc: 0.9949 - val_loss: 0.8246 - val_accuracy: 0.7438 - val_precision: 0.6619 - val_recall: 0.9964 - val_auc: 0.9559\n",
            "Epoch 1965/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.0855 - accuracy: 0.9675 - precision: 0.9691 - recall: 0.9658 - auc: 0.9951 - val_loss: 0.9089 - val_accuracy: 0.7288 - val_precision: 0.6489 - val_recall: 0.9966 - val_auc: 0.9502\n",
            "Epoch 1966/2000\n",
            "10/10 [==============================] - 4s 413ms/step - loss: 0.0837 - accuracy: 0.9685 - precision: 0.9718 - recall: 0.9650 - auc: 0.9952 - val_loss: 0.9719 - val_accuracy: 0.7108 - val_precision: 0.6339 - val_recall: 0.9975 - val_auc: 0.9491\n",
            "Epoch 1967/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0846 - accuracy: 0.9680 - precision: 0.9699 - recall: 0.9660 - auc: 0.9951 - val_loss: 0.8949 - val_accuracy: 0.7273 - val_precision: 0.6476 - val_recall: 0.9970 - val_auc: 0.9527\n",
            "Epoch 1968/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.0818 - accuracy: 0.9690 - precision: 0.9722 - recall: 0.9657 - auc: 0.9955 - val_loss: 0.8622 - val_accuracy: 0.7375 - val_precision: 0.6563 - val_recall: 0.9966 - val_auc: 0.9529\n",
            "Epoch 1969/2000\n",
            "10/10 [==============================] - 4s 408ms/step - loss: 0.0806 - accuracy: 0.9696 - precision: 0.9733 - recall: 0.9656 - auc: 0.9956 - val_loss: 0.9600 - val_accuracy: 0.7107 - val_precision: 0.6338 - val_recall: 0.9974 - val_auc: 0.9510\n",
            "Epoch 1970/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.0815 - accuracy: 0.9691 - precision: 0.9711 - recall: 0.9670 - auc: 0.9955 - val_loss: 0.9511 - val_accuracy: 0.7142 - val_precision: 0.6367 - val_recall: 0.9973 - val_auc: 0.9480\n",
            "Epoch 1971/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1039 - accuracy: 0.9616 - precision: 0.9626 - recall: 0.9605 - auc: 0.9928 - val_loss: 1.0592 - val_accuracy: 0.6793 - val_precision: 0.6095 - val_recall: 0.9975 - val_auc: 0.9061\n",
            "Epoch 1972/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1695 - accuracy: 0.9346 - precision: 0.9275 - recall: 0.9428 - auc: 0.9822 - val_loss: 0.3951 - val_accuracy: 0.8490 - val_precision: 0.7922 - val_recall: 0.9459 - val_auc: 0.9320\n",
            "Epoch 1973/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1414 - accuracy: 0.9455 - precision: 0.9445 - recall: 0.9467 - auc: 0.9874 - val_loss: 0.7167 - val_accuracy: 0.7758 - val_precision: 0.6957 - val_recall: 0.9805 - val_auc: 0.8890\n",
            "Epoch 1974/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1868 - accuracy: 0.9285 - precision: 0.9176 - recall: 0.9417 - auc: 0.9789 - val_loss: 0.3959 - val_accuracy: 0.7563 - val_precision: 0.6736 - val_recall: 0.9940 - val_auc: 0.9446\n",
            "Epoch 1975/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1987 - accuracy: 0.9197 - precision: 0.9261 - recall: 0.9122 - auc: 0.9762 - val_loss: 0.3080 - val_accuracy: 0.8432 - val_precision: 0.7669 - val_recall: 0.9860 - val_auc: 0.9616\n",
            "Epoch 1976/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1863 - accuracy: 0.9264 - precision: 0.9183 - recall: 0.9361 - auc: 0.9784 - val_loss: 0.2607 - val_accuracy: 0.8848 - val_precision: 0.8323 - val_recall: 0.9638 - val_auc: 0.9629\n",
            "Epoch 1977/2000\n",
            "10/10 [==============================] - 4s 399ms/step - loss: 0.1806 - accuracy: 0.9287 - precision: 0.9238 - recall: 0.9344 - auc: 0.9797 - val_loss: 0.2606 - val_accuracy: 0.8899 - val_precision: 0.8421 - val_recall: 0.9597 - val_auc: 0.9626\n",
            "Epoch 1978/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1760 - accuracy: 0.9307 - precision: 0.9249 - recall: 0.9374 - auc: 0.9806 - val_loss: 0.2734 - val_accuracy: 0.8854 - val_precision: 0.8393 - val_recall: 0.9533 - val_auc: 0.9572\n",
            "Epoch 1979/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1752 - accuracy: 0.9305 - precision: 0.9244 - recall: 0.9376 - auc: 0.9808 - val_loss: 0.2449 - val_accuracy: 0.9019 - val_precision: 0.8735 - val_recall: 0.9398 - val_auc: 0.9638\n",
            "Epoch 1980/2000\n",
            "10/10 [==============================] - 4s 414ms/step - loss: 0.1729 - accuracy: 0.9314 - precision: 0.9261 - recall: 0.9378 - auc: 0.9813 - val_loss: 0.2465 - val_accuracy: 0.9010 - val_precision: 0.8672 - val_recall: 0.9469 - val_auc: 0.9645\n",
            "Epoch 1981/2000\n",
            "10/10 [==============================] - 4s 396ms/step - loss: 0.1724 - accuracy: 0.9318 - precision: 0.9258 - recall: 0.9389 - auc: 0.9814 - val_loss: 0.2570 - val_accuracy: 0.8954 - val_precision: 0.8597 - val_recall: 0.9451 - val_auc: 0.9609\n",
            "Epoch 1982/2000\n",
            "10/10 [==============================] - 4s 390ms/step - loss: 0.1707 - accuracy: 0.9326 - precision: 0.9260 - recall: 0.9404 - auc: 0.9818 - val_loss: 0.2434 - val_accuracy: 0.9023 - val_precision: 0.8753 - val_recall: 0.9383 - val_auc: 0.9640\n",
            "Epoch 1983/2000\n",
            "10/10 [==============================] - 4s 410ms/step - loss: 0.1693 - accuracy: 0.9328 - precision: 0.9278 - recall: 0.9387 - auc: 0.9821 - val_loss: 0.2467 - val_accuracy: 0.8997 - val_precision: 0.8663 - val_recall: 0.9451 - val_auc: 0.9639\n",
            "Epoch 1984/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1688 - accuracy: 0.9332 - precision: 0.9261 - recall: 0.9416 - auc: 0.9822 - val_loss: 0.2497 - val_accuracy: 0.8996 - val_precision: 0.8650 - val_recall: 0.9471 - val_auc: 0.9635\n",
            "Epoch 1985/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1664 - accuracy: 0.9341 - precision: 0.9280 - recall: 0.9413 - auc: 0.9827 - val_loss: 0.2427 - val_accuracy: 0.9035 - val_precision: 0.8795 - val_recall: 0.9350 - val_auc: 0.9642\n",
            "Epoch 1986/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1681 - accuracy: 0.9334 - precision: 0.9282 - recall: 0.9396 - auc: 0.9823 - val_loss: 0.2426 - val_accuracy: 0.9034 - val_precision: 0.8853 - val_recall: 0.9268 - val_auc: 0.9638\n",
            "Epoch 1987/2000\n",
            "10/10 [==============================] - 4s 419ms/step - loss: 0.1680 - accuracy: 0.9336 - precision: 0.9276 - recall: 0.9405 - auc: 0.9824 - val_loss: 0.2398 - val_accuracy: 0.9049 - val_precision: 0.8823 - val_recall: 0.9343 - val_auc: 0.9650\n",
            "Epoch 1988/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1649 - accuracy: 0.9345 - precision: 0.9295 - recall: 0.9403 - auc: 0.9830 - val_loss: 0.2542 - val_accuracy: 0.8994 - val_precision: 0.8641 - val_recall: 0.9478 - val_auc: 0.9639\n",
            "Epoch 1989/2000\n",
            "10/10 [==============================] - 4s 391ms/step - loss: 0.1668 - accuracy: 0.9343 - precision: 0.9286 - recall: 0.9410 - auc: 0.9826 - val_loss: 0.2440 - val_accuracy: 0.9037 - val_precision: 0.8771 - val_recall: 0.9390 - val_auc: 0.9650\n",
            "Epoch 1990/2000\n",
            "10/10 [==============================] - 4s 393ms/step - loss: 0.1643 - accuracy: 0.9352 - precision: 0.9298 - recall: 0.9415 - auc: 0.9831 - val_loss: 0.2605 - val_accuracy: 0.8985 - val_precision: 0.8602 - val_recall: 0.9515 - val_auc: 0.9639\n",
            "Epoch 1991/2000\n",
            "10/10 [==============================] - 4s 405ms/step - loss: 0.1618 - accuracy: 0.9363 - precision: 0.9315 - recall: 0.9420 - auc: 0.9837 - val_loss: 0.2502 - val_accuracy: 0.9013 - val_precision: 0.8697 - val_recall: 0.9440 - val_auc: 0.9645\n",
            "Epoch 1992/2000\n",
            "10/10 [==============================] - 4s 400ms/step - loss: 0.1629 - accuracy: 0.9354 - precision: 0.9306 - recall: 0.9410 - auc: 0.9834 - val_loss: 0.2767 - val_accuracy: 0.8912 - val_precision: 0.8471 - val_recall: 0.9547 - val_auc: 0.9619\n",
            "Epoch 1993/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1598 - accuracy: 0.9371 - precision: 0.9334 - recall: 0.9414 - auc: 0.9840 - val_loss: 0.2714 - val_accuracy: 0.8938 - val_precision: 0.8478 - val_recall: 0.9600 - val_auc: 0.9645\n",
            "Epoch 1994/2000\n",
            "10/10 [==============================] - 4s 409ms/step - loss: 0.1557 - accuracy: 0.9387 - precision: 0.9341 - recall: 0.9439 - auc: 0.9849 - val_loss: 0.2690 - val_accuracy: 0.8957 - val_precision: 0.8516 - val_recall: 0.9583 - val_auc: 0.9651\n",
            "Epoch 1995/2000\n",
            "10/10 [==============================] - 4s 398ms/step - loss: 0.1519 - accuracy: 0.9401 - precision: 0.9368 - recall: 0.9438 - auc: 0.9855 - val_loss: 0.2804 - val_accuracy: 0.8915 - val_precision: 0.8433 - val_recall: 0.9617 - val_auc: 0.9646\n",
            "Epoch 1996/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1560 - accuracy: 0.9387 - precision: 0.9336 - recall: 0.9446 - auc: 0.9848 - val_loss: 0.2697 - val_accuracy: 0.8962 - val_precision: 0.8504 - val_recall: 0.9615 - val_auc: 0.9669\n",
            "Epoch 1997/2000\n",
            "10/10 [==============================] - 4s 395ms/step - loss: 0.1497 - accuracy: 0.9416 - precision: 0.9373 - recall: 0.9465 - auc: 0.9860 - val_loss: 0.2998 - val_accuracy: 0.8862 - val_precision: 0.8311 - val_recall: 0.9695 - val_auc: 0.9660\n",
            "Epoch 1998/2000\n",
            "10/10 [==============================] - 4s 416ms/step - loss: 0.1519 - accuracy: 0.9403 - precision: 0.9375 - recall: 0.9436 - auc: 0.9855 - val_loss: 0.2870 - val_accuracy: 0.8915 - val_precision: 0.8418 - val_recall: 0.9642 - val_auc: 0.9649\n",
            "Epoch 1999/2000\n",
            "10/10 [==============================] - 4s 394ms/step - loss: 0.1429 - accuracy: 0.9437 - precision: 0.9404 - recall: 0.9475 - auc: 0.9872 - val_loss: 0.3087 - val_accuracy: 0.8845 - val_precision: 0.8277 - val_recall: 0.9711 - val_auc: 0.9656\n",
            "Epoch 2000/2000\n",
            "10/10 [==============================] - 4s 392ms/step - loss: 0.1424 - accuracy: 0.9441 - precision: 0.9427 - recall: 0.9457 - auc: 0.9872 - val_loss: 0.3016 - val_accuracy: 0.8862 - val_precision: 0.8331 - val_recall: 0.9656 - val_auc: 0.9631\n",
            "loss — -> 0.30158066749572754\n",
            "accuracy — -> 0.8861571550369263\n",
            "precision — -> 0.8331467509269714\n",
            "recall — -> 0.9656211733818054\n",
            "auc — -> 0.9630800485610962\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "Final Values\n",
        "*  accuracy — -> 0.8861571550369263\n",
        "*  precision — -> 0.8331467509269714\n",
        "*  recall — -> 0.9656211733818054\n",
        "*  auc — -> 0.9630800485610962\n",
        "\n"
      ],
      "metadata": {
        "id": "0KX8MK-uvS0d"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "import matplotlib.pyplot as plt\n",
        "epochs = 2000\n",
        "acc = history.history['accuracy']\n",
        "val_acc = history.history['val_accuracy']\n",
        "\n",
        "loss = history.history['loss']\n",
        "val_loss = history.history['val_loss']\n",
        "\n",
        "epochs_range = range(epochs)\n",
        "\n",
        "plt.figure(figsize=(8, 8))\n",
        "plt.subplot(1, 2, 1)\n",
        "plt.plot(epochs_range, acc, label='Training Accuracy')\n",
        "plt.plot(epochs_range, val_acc, label='Validation Accuracy')\n",
        "plt.legend(loc='lower right')\n",
        "plt.title('Training and Validation Accuracy')\n",
        "\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "YfRGQ7XbEbZg",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 699
        },
        "outputId": "e236ac26-a05e-4e8d-e921-e8bc4ad6c40d"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 800x800 with 1 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "1ZO_qEdPUbTl"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [],
      "metadata": {
        "id": "uBsPOzmPUbLe"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}