Make_Model_Accuracy.ipynb

{
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  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "provenance": [],
      "gpuType": "T4"
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    },
    "accelerator": "GPU"
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oGTpVUDpYjT9",
        "outputId": "86732980-840f-435a-856d-2d246aedfc1e"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ],
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import StandardScaler, LabelEncoder\n",
        "from sklearn.metrics import accuracy_score\n",
        "from keras.models import Sequential\n",
        "from keras.layers import Dense\n",
        "from keras.utils import to_categorical\n",
        "\n",
        "# Load the dataset\n",
        "data = pd.read_excel('/content/drive/MyDrive/Lomba/DSW 2023/Telco_customer_churn_adapted_v2.xlsx')\n",
        "\n",
        "# Hapus kolom yang tidak diinginkan\n",
        "columns_to_drop = [\"Location\", \"Longitude\", \"Latitude\", \"Customer ID\"]\n",
        "data = data.drop(columns=columns_to_drop, axis=1)\n",
        "\n",
        "# Mengubah data kategorikal menjadi numerik menggunakan LabelEncoder\n",
        "le = LabelEncoder()\n",
        "data['Device Class'] = le.fit_transform(data['Device Class'])\n",
        "data['Games Product'] = le.fit_transform(data['Games Product'])\n",
        "data['Music Product'] = le.fit_transform(data['Music Product'])\n",
        "data['Education Product'] = le.fit_transform(data['Education Product'])\n",
        "data['Call Center'] = le.fit_transform(data['Call Center'])\n",
        "data['Video Product'] = le.fit_transform(data['Video Product'])\n",
        "data['Use MyApp'] = le.fit_transform(data['Use MyApp'])\n",
        "data['Payment Method'] = le.fit_transform(data['Payment Method'])\n",
        "data['Churn Label'] = le.fit_transform(data['Churn Label'])\n",
        "\n",
        "# Iterasi melalui setiap fitur\n",
        "for column in data.drop('Churn Label', axis=1).columns:\n",
        "    # Ambil satu fitur dan labelnya\n",
        "    X = data[[column]].values\n",
        "    y = data['Churn Label'].values\n",
        "\n",
        "    # Split the data into training and test sets\n",
        "    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.25, random_state=42)\n",
        "\n",
        "    # Standardisasi fitur menggunakan StandardScaler\n",
        "    scaler = StandardScaler()\n",
        "    X_train = scaler.fit_transform(X_train)\n",
        "    X_test = scaler.transform(X_test)\n",
        "\n",
        "    # Konversi label menjadi one-hot encoding\n",
        "    y_train_encoded = to_categorical(y_train)\n",
        "    y_test_encoded = to_categorical(y_test)\n",
        "\n",
        "    # Membangun model ANN\n",
        "    model = Sequential()\n",
        "    model.add(Dense(128, input_dim=X_train.shape[1], activation='relu'))\n",
        "    model.add(Dense(64, activation='relu'))\n",
        "    model.add(Dense(2, activation='softmax'))  # Jumlah neuron output sesuaikan dengan jumlah kelas (binary: 2, multi-class: sesuaikan)\n",
        "\n",
        "    # Mengompilasi model\n",
        "    model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n",
        "\n",
        "    # Melatih model\n",
        "    model.fit(X_train, y_train_encoded, epochs=50, batch_size=32, validation_data=(X_test, y_test_encoded))\n",
        "\n",
        "    # Memprediksi Churn Label menggunakan data uji\n",
        "    predictions = np.argmax(model.predict(X_test), axis=1)\n",
        "\n",
        "    # Menghitung akurasi prediksi\n",
        "    accuracy = accuracy_score(y_test, predictions)\n",
        "    print(f'Accuracy for {column}: {accuracy}')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MI8pXbyUY6j_",
        "outputId": "f7a9aa06-2c5d-44b0-a42d-78655098d80d"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/50\n",
            "166/166 [==============================] - 3s 8ms/step - loss: 0.5316 - accuracy: 0.7408 - val_loss: 0.5263 - val_accuracy: 0.7439\n",
            "Epoch 2/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5052 - accuracy: 0.7484 - val_loss: 0.5262 - val_accuracy: 0.7445\n",
            "Epoch 3/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5038 - accuracy: 0.7501 - val_loss: 0.5265 - val_accuracy: 0.7445\n",
            "Epoch 4/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5037 - accuracy: 0.7499 - val_loss: 0.5262 - val_accuracy: 0.7354\n",
            "Epoch 5/50\n",
            "166/166 [==============================] - 1s 7ms/step - loss: 0.5046 - accuracy: 0.7473 - val_loss: 0.5264 - val_accuracy: 0.7155\n",
            "Epoch 6/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5043 - accuracy: 0.7474 - val_loss: 0.5250 - val_accuracy: 0.7428\n",
            "Epoch 7/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5040 - accuracy: 0.7509 - val_loss: 0.5267 - val_accuracy: 0.7416\n",
            "Epoch 8/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5041 - accuracy: 0.7524 - val_loss: 0.5249 - val_accuracy: 0.7445\n",
            "Epoch 9/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5025 - accuracy: 0.7529 - val_loss: 0.5272 - val_accuracy: 0.7416\n",
            "Epoch 10/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5043 - accuracy: 0.7469 - val_loss: 0.5240 - val_accuracy: 0.7439\n",
            "Epoch 11/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5032 - accuracy: 0.7537 - val_loss: 0.5333 - val_accuracy: 0.7166\n",
            "Epoch 12/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5029 - accuracy: 0.7552 - val_loss: 0.5247 - val_accuracy: 0.7445\n",
            "Epoch 13/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5037 - accuracy: 0.7512 - val_loss: 0.5252 - val_accuracy: 0.7428\n",
            "Epoch 14/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5031 - accuracy: 0.7548 - val_loss: 0.5234 - val_accuracy: 0.7439\n",
            "Epoch 15/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5021 - accuracy: 0.7539 - val_loss: 0.5265 - val_accuracy: 0.7155\n",
            "Epoch 16/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5023 - accuracy: 0.7539 - val_loss: 0.5253 - val_accuracy: 0.7507\n",
            "Epoch 17/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5021 - accuracy: 0.7531 - val_loss: 0.5240 - val_accuracy: 0.7439\n",
            "Epoch 18/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5028 - accuracy: 0.7512 - val_loss: 0.5256 - val_accuracy: 0.7507\n",
            "Epoch 19/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5026 - accuracy: 0.7501 - val_loss: 0.5249 - val_accuracy: 0.7507\n",
            "Epoch 20/50\n",
            "166/166 [==============================] - 2s 10ms/step - loss: 0.5025 - accuracy: 0.7478 - val_loss: 0.5254 - val_accuracy: 0.7445\n",
            "Epoch 21/50\n",
            "166/166 [==============================] - 2s 15ms/step - loss: 0.5029 - accuracy: 0.7495 - val_loss: 0.5251 - val_accuracy: 0.7439\n",
            "Epoch 22/50\n",
            "166/166 [==============================] - 2s 12ms/step - loss: 0.5032 - accuracy: 0.7512 - val_loss: 0.5269 - val_accuracy: 0.7416\n",
            "Epoch 23/50\n",
            "166/166 [==============================] - 1s 7ms/step - loss: 0.5026 - accuracy: 0.7558 - val_loss: 0.5261 - val_accuracy: 0.7445\n",
            "Epoch 24/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5019 - accuracy: 0.7509 - val_loss: 0.5233 - val_accuracy: 0.7439\n",
            "Epoch 25/50\n",
            "166/166 [==============================] - 1s 7ms/step - loss: 0.5019 - accuracy: 0.7562 - val_loss: 0.5253 - val_accuracy: 0.7428\n",
            "Epoch 26/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5025 - accuracy: 0.7520 - val_loss: 0.5254 - val_accuracy: 0.7445\n",
            "Epoch 27/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5026 - accuracy: 0.7493 - val_loss: 0.5261 - val_accuracy: 0.7445\n",
            "Epoch 28/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5021 - accuracy: 0.7552 - val_loss: 0.5251 - val_accuracy: 0.7428\n",
            "Epoch 29/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5023 - accuracy: 0.7533 - val_loss: 0.5248 - val_accuracy: 0.7428\n",
            "Epoch 30/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5028 - accuracy: 0.7526 - val_loss: 0.5247 - val_accuracy: 0.7439\n",
            "Epoch 31/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5029 - accuracy: 0.7531 - val_loss: 0.5253 - val_accuracy: 0.7445\n",
            "Epoch 32/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5019 - accuracy: 0.7535 - val_loss: 0.5239 - val_accuracy: 0.7507\n",
            "Epoch 33/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5020 - accuracy: 0.7580 - val_loss: 0.5260 - val_accuracy: 0.7428\n",
            "Epoch 34/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5020 - accuracy: 0.7527 - val_loss: 0.5255 - val_accuracy: 0.7507\n",
            "Epoch 35/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5017 - accuracy: 0.7535 - val_loss: 0.5265 - val_accuracy: 0.7155\n",
            "Epoch 36/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5035 - accuracy: 0.7474 - val_loss: 0.5262 - val_accuracy: 0.7428\n",
            "Epoch 37/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5018 - accuracy: 0.7544 - val_loss: 0.5241 - val_accuracy: 0.7507\n",
            "Epoch 38/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5023 - accuracy: 0.7526 - val_loss: 0.5253 - val_accuracy: 0.7445\n",
            "Epoch 39/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5013 - accuracy: 0.7550 - val_loss: 0.5281 - val_accuracy: 0.7439\n",
            "Epoch 40/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5028 - accuracy: 0.7527 - val_loss: 0.5254 - val_accuracy: 0.7445\n",
            "Epoch 41/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5017 - accuracy: 0.7539 - val_loss: 0.5236 - val_accuracy: 0.7439\n",
            "Epoch 42/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5017 - accuracy: 0.7548 - val_loss: 0.5290 - val_accuracy: 0.7445\n",
            "Epoch 43/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5020 - accuracy: 0.7522 - val_loss: 0.5258 - val_accuracy: 0.7507\n",
            "Epoch 44/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5020 - accuracy: 0.7535 - val_loss: 0.5234 - val_accuracy: 0.7439\n",
            "Epoch 45/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5013 - accuracy: 0.7562 - val_loss: 0.5268 - val_accuracy: 0.7416\n",
            "Epoch 46/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5022 - accuracy: 0.7560 - val_loss: 0.5240 - val_accuracy: 0.7428\n",
            "Epoch 47/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5020 - accuracy: 0.7556 - val_loss: 0.5239 - val_accuracy: 0.7439\n",
            "Epoch 48/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5013 - accuracy: 0.7560 - val_loss: 0.5262 - val_accuracy: 0.7445\n",
            "Epoch 49/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5027 - accuracy: 0.7501 - val_loss: 0.5292 - val_accuracy: 0.7507\n",
            "Epoch 50/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5016 - accuracy: 0.7537 - val_loss: 0.5237 - val_accuracy: 0.7507\n",
            "56/56 [==============================] - 0s 1ms/step\n",
            "Accuracy for Tenure Months: 0.750709823963657\n",
            "Epoch 1/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5600 - accuracy: 0.7382 - val_loss: 0.5460 - val_accuracy: 0.7166\n",
            "Epoch 2/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5239 - accuracy: 0.7406 - val_loss: 0.5367 - val_accuracy: 0.7166\n",
            "Epoch 3/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5217 - accuracy: 0.7406 - val_loss: 0.5364 - val_accuracy: 0.7166\n",
            "Epoch 4/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5213 - accuracy: 0.7406 - val_loss: 0.5401 - val_accuracy: 0.7166\n",
            "Epoch 5/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5211 - accuracy: 0.7406 - val_loss: 0.5380 - val_accuracy: 0.7166\n",
            "Epoch 6/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5208 - accuracy: 0.7406 - val_loss: 0.5382 - val_accuracy: 0.7166\n",
            "Epoch 7/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5214 - accuracy: 0.7406 - val_loss: 0.5415 - val_accuracy: 0.7166\n",
            "Epoch 8/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5202 - accuracy: 0.7406 - val_loss: 0.5388 - val_accuracy: 0.7166\n",
            "Epoch 9/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5207 - accuracy: 0.7406 - val_loss: 0.5364 - val_accuracy: 0.7166\n",
            "Epoch 10/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5200 - accuracy: 0.7406 - val_loss: 0.5386 - val_accuracy: 0.7166\n",
            "Epoch 11/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5209 - accuracy: 0.7406 - val_loss: 0.5368 - val_accuracy: 0.7166\n",
            "Epoch 12/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5198 - accuracy: 0.7406 - val_loss: 0.5363 - val_accuracy: 0.7166\n",
            "Epoch 13/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5202 - accuracy: 0.7406 - val_loss: 0.5372 - val_accuracy: 0.7166\n",
            "Epoch 14/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5202 - accuracy: 0.7406 - val_loss: 0.5379 - val_accuracy: 0.7166\n",
            "Epoch 15/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5204 - accuracy: 0.7406 - val_loss: 0.5372 - val_accuracy: 0.7166\n",
            "Epoch 16/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5201 - accuracy: 0.7406 - val_loss: 0.5375 - val_accuracy: 0.7166\n",
            "Epoch 17/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5196 - accuracy: 0.7406 - val_loss: 0.5366 - val_accuracy: 0.7166\n",
            "Epoch 18/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5197 - accuracy: 0.7406 - val_loss: 0.5368 - val_accuracy: 0.7166\n",
            "Epoch 19/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5202 - accuracy: 0.7406 - val_loss: 0.5384 - val_accuracy: 0.7166\n",
            "Epoch 20/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5198 - accuracy: 0.7406 - val_loss: 0.5371 - val_accuracy: 0.7166\n",
            "Epoch 21/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5196 - accuracy: 0.7406 - val_loss: 0.5368 - val_accuracy: 0.7166\n",
            "Epoch 22/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5195 - accuracy: 0.7406 - val_loss: 0.5372 - val_accuracy: 0.7166\n",
            "Epoch 23/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5199 - accuracy: 0.7406 - val_loss: 0.5364 - val_accuracy: 0.7166\n",
            "Epoch 24/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5203 - accuracy: 0.7406 - val_loss: 0.5366 - val_accuracy: 0.7166\n",
            "Epoch 25/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5193 - accuracy: 0.7406 - val_loss: 0.5364 - val_accuracy: 0.7166\n",
            "Epoch 26/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5210 - accuracy: 0.7406 - val_loss: 0.5368 - val_accuracy: 0.7166\n",
            "Epoch 27/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5193 - accuracy: 0.7406 - val_loss: 0.5383 - val_accuracy: 0.7166\n",
            "Epoch 28/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5200 - accuracy: 0.7406 - val_loss: 0.5377 - val_accuracy: 0.7166\n",
            "Epoch 29/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5198 - accuracy: 0.7406 - val_loss: 0.5381 - val_accuracy: 0.7166\n",
            "Epoch 30/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5198 - accuracy: 0.7406 - val_loss: 0.5374 - val_accuracy: 0.7166\n",
            "Epoch 31/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5199 - accuracy: 0.7406 - val_loss: 0.5370 - val_accuracy: 0.7166\n",
            "Epoch 32/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5197 - accuracy: 0.7406 - val_loss: 0.5387 - val_accuracy: 0.7166\n",
            "Epoch 33/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5200 - accuracy: 0.7406 - val_loss: 0.5388 - val_accuracy: 0.7166\n",
            "Epoch 34/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5193 - accuracy: 0.7406 - val_loss: 0.5374 - val_accuracy: 0.7166\n",
            "Epoch 35/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5196 - accuracy: 0.7406 - val_loss: 0.5384 - val_accuracy: 0.7166\n",
            "Epoch 36/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5193 - accuracy: 0.7406 - val_loss: 0.5373 - val_accuracy: 0.7166\n",
            "Epoch 37/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5197 - accuracy: 0.7406 - val_loss: 0.5372 - val_accuracy: 0.7166\n",
            "Epoch 38/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5187 - accuracy: 0.7406 - val_loss: 0.5391 - val_accuracy: 0.7166\n",
            "Epoch 39/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5197 - accuracy: 0.7406 - val_loss: 0.5379 - val_accuracy: 0.7166\n",
            "Epoch 40/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5195 - accuracy: 0.7406 - val_loss: 0.5376 - val_accuracy: 0.7166\n",
            "Epoch 41/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5194 - accuracy: 0.7406 - val_loss: 0.5368 - val_accuracy: 0.7166\n",
            "Epoch 42/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5193 - accuracy: 0.7406 - val_loss: 0.5382 - val_accuracy: 0.7166\n",
            "Epoch 43/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5194 - accuracy: 0.7406 - val_loss: 0.5369 - val_accuracy: 0.7166\n",
            "Epoch 44/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5193 - accuracy: 0.7406 - val_loss: 0.5393 - val_accuracy: 0.7166\n",
            "Epoch 45/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5198 - accuracy: 0.7406 - val_loss: 0.5370 - val_accuracy: 0.7166\n",
            "Epoch 46/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5192 - accuracy: 0.7406 - val_loss: 0.5367 - val_accuracy: 0.7166\n",
            "Epoch 47/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5192 - accuracy: 0.7406 - val_loss: 0.5373 - val_accuracy: 0.7166\n",
            "Epoch 48/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5197 - accuracy: 0.7406 - val_loss: 0.5373 - val_accuracy: 0.7166\n",
            "Epoch 49/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5191 - accuracy: 0.7406 - val_loss: 0.5368 - val_accuracy: 0.7166\n",
            "Epoch 50/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5191 - accuracy: 0.7406 - val_loss: 0.5368 - val_accuracy: 0.7166\n",
            "56/56 [==============================] - 0s 2ms/step\n",
            "Accuracy for Device Class: 0.7166382737081204\n",
            "Epoch 1/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5435 - accuracy: 0.7406 - val_loss: 0.5443 - val_accuracy: 0.7166\n",
            "Epoch 2/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5145 - accuracy: 0.7406 - val_loss: 0.5347 - val_accuracy: 0.7166\n",
            "Epoch 3/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5109 - accuracy: 0.7406 - val_loss: 0.5338 - val_accuracy: 0.7166\n",
            "Epoch 4/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5112 - accuracy: 0.7406 - val_loss: 0.5328 - val_accuracy: 0.7166\n",
            "Epoch 5/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5100 - accuracy: 0.7406 - val_loss: 0.5322 - val_accuracy: 0.7166\n",
            "Epoch 6/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5097 - accuracy: 0.7406 - val_loss: 0.5317 - val_accuracy: 0.7166\n",
            "Epoch 7/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5101 - accuracy: 0.7406 - val_loss: 0.5317 - val_accuracy: 0.7166\n",
            "Epoch 8/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5109 - accuracy: 0.7370 - val_loss: 0.5329 - val_accuracy: 0.7166\n",
            "Epoch 9/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5102 - accuracy: 0.7406 - val_loss: 0.5352 - val_accuracy: 0.7166\n",
            "Epoch 10/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5096 - accuracy: 0.7406 - val_loss: 0.5372 - val_accuracy: 0.7166\n",
            "Epoch 11/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5094 - accuracy: 0.7406 - val_loss: 0.5331 - val_accuracy: 0.7166\n",
            "Epoch 12/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5096 - accuracy: 0.7406 - val_loss: 0.5317 - val_accuracy: 0.7166\n",
            "Epoch 13/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5096 - accuracy: 0.7406 - val_loss: 0.5331 - val_accuracy: 0.7166\n",
            "Epoch 14/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5093 - accuracy: 0.7406 - val_loss: 0.5324 - val_accuracy: 0.7166\n",
            "Epoch 15/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5092 - accuracy: 0.7406 - val_loss: 0.5338 - val_accuracy: 0.7166\n",
            "Epoch 16/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5096 - accuracy: 0.7406 - val_loss: 0.5323 - val_accuracy: 0.7166\n",
            "Epoch 17/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5097 - accuracy: 0.7406 - val_loss: 0.5319 - val_accuracy: 0.7166\n",
            "Epoch 18/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5094 - accuracy: 0.7406 - val_loss: 0.5343 - val_accuracy: 0.7166\n",
            "Epoch 19/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5086 - accuracy: 0.7406 - val_loss: 0.5319 - val_accuracy: 0.7166\n",
            "Epoch 20/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5091 - accuracy: 0.7406 - val_loss: 0.5329 - val_accuracy: 0.7166\n",
            "Epoch 21/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5091 - accuracy: 0.7406 - val_loss: 0.5317 - val_accuracy: 0.7166\n",
            "Epoch 22/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5095 - accuracy: 0.7406 - val_loss: 0.5314 - val_accuracy: 0.7166\n",
            "Epoch 23/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5088 - accuracy: 0.7406 - val_loss: 0.5335 - val_accuracy: 0.7166\n",
            "Epoch 24/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5096 - accuracy: 0.7406 - val_loss: 0.5331 - val_accuracy: 0.7166\n",
            "Epoch 25/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5091 - accuracy: 0.7406 - val_loss: 0.5325 - val_accuracy: 0.7166\n",
            "Epoch 26/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5092 - accuracy: 0.7406 - val_loss: 0.5319 - val_accuracy: 0.7166\n",
            "Epoch 27/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5090 - accuracy: 0.7406 - val_loss: 0.5316 - val_accuracy: 0.7166\n",
            "Epoch 28/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5091 - accuracy: 0.7406 - val_loss: 0.5330 - val_accuracy: 0.7166\n",
            "Epoch 29/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5094 - accuracy: 0.7406 - val_loss: 0.5328 - val_accuracy: 0.7166\n",
            "Epoch 30/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5100 - accuracy: 0.7406 - val_loss: 0.5315 - val_accuracy: 0.7166\n",
            "Epoch 31/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5086 - accuracy: 0.7406 - val_loss: 0.5320 - val_accuracy: 0.7166\n",
            "Epoch 32/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5098 - accuracy: 0.7406 - val_loss: 0.5315 - val_accuracy: 0.7166\n",
            "Epoch 33/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5086 - accuracy: 0.7406 - val_loss: 0.5324 - val_accuracy: 0.7166\n",
            "Epoch 34/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5091 - accuracy: 0.7406 - val_loss: 0.5332 - val_accuracy: 0.7166\n",
            "Epoch 35/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5088 - accuracy: 0.7406 - val_loss: 0.5328 - val_accuracy: 0.7166\n",
            "Epoch 36/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5096 - accuracy: 0.7406 - val_loss: 0.5312 - val_accuracy: 0.7166\n",
            "Epoch 37/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5089 - accuracy: 0.7406 - val_loss: 0.5317 - val_accuracy: 0.7166\n",
            "Epoch 38/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5087 - accuracy: 0.7406 - val_loss: 0.5363 - val_accuracy: 0.7166\n",
            "Epoch 39/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5092 - accuracy: 0.7406 - val_loss: 0.5326 - val_accuracy: 0.7166\n",
            "Epoch 40/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5087 - accuracy: 0.7406 - val_loss: 0.5336 - val_accuracy: 0.7166\n",
            "Epoch 41/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5090 - accuracy: 0.7406 - val_loss: 0.5318 - val_accuracy: 0.7166\n",
            "Epoch 42/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5095 - accuracy: 0.7406 - val_loss: 0.5328 - val_accuracy: 0.7166\n",
            "Epoch 43/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5098 - accuracy: 0.7406 - val_loss: 0.5320 - val_accuracy: 0.7166\n",
            "Epoch 44/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5085 - accuracy: 0.7406 - val_loss: 0.5359 - val_accuracy: 0.7166\n",
            "Epoch 45/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5097 - accuracy: 0.7406 - val_loss: 0.5315 - val_accuracy: 0.7166\n",
            "Epoch 46/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5099 - accuracy: 0.7406 - val_loss: 0.5316 - val_accuracy: 0.7166\n",
            "Epoch 47/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5093 - accuracy: 0.7406 - val_loss: 0.5352 - val_accuracy: 0.7166\n",
            "Epoch 48/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5091 - accuracy: 0.7406 - val_loss: 0.5321 - val_accuracy: 0.7166\n",
            "Epoch 49/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5094 - accuracy: 0.7406 - val_loss: 0.5316 - val_accuracy: 0.7166\n",
            "Epoch 50/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5086 - accuracy: 0.7406 - val_loss: 0.5322 - val_accuracy: 0.7166\n",
            "56/56 [==============================] - 0s 2ms/step\n",
            "Accuracy for Games Product: 0.7166382737081204\n",
            "Epoch 1/50\n",
            "166/166 [==============================] - 2s 5ms/step - loss: 0.5681 - accuracy: 0.7406 - val_loss: 0.5521 - val_accuracy: 0.7166\n",
            "Epoch 2/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5340 - accuracy: 0.7406 - val_loss: 0.5448 - val_accuracy: 0.7166\n",
            "Epoch 3/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5322 - accuracy: 0.7406 - val_loss: 0.5437 - val_accuracy: 0.7166\n",
            "Epoch 4/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5318 - accuracy: 0.7406 - val_loss: 0.5456 - val_accuracy: 0.7166\n",
            "Epoch 5/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5292 - accuracy: 0.7406 - val_loss: 0.5459 - val_accuracy: 0.7166\n",
            "Epoch 6/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5303 - accuracy: 0.7406 - val_loss: 0.5463 - val_accuracy: 0.7166\n",
            "Epoch 7/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5307 - accuracy: 0.7406 - val_loss: 0.5457 - val_accuracy: 0.7166\n",
            "Epoch 8/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5312 - accuracy: 0.7406 - val_loss: 0.5557 - val_accuracy: 0.7166\n",
            "Epoch 9/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5308 - accuracy: 0.7406 - val_loss: 0.5423 - val_accuracy: 0.7166\n",
            "Epoch 10/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5302 - accuracy: 0.7406 - val_loss: 0.5470 - val_accuracy: 0.7166\n",
            "Epoch 11/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5311 - accuracy: 0.7406 - val_loss: 0.5455 - val_accuracy: 0.7166\n",
            "Epoch 12/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5305 - accuracy: 0.7406 - val_loss: 0.5423 - val_accuracy: 0.7166\n",
            "Epoch 13/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5299 - accuracy: 0.7406 - val_loss: 0.5428 - val_accuracy: 0.7166\n",
            "Epoch 14/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5300 - accuracy: 0.7406 - val_loss: 0.5444 - val_accuracy: 0.7166\n",
            "Epoch 15/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5296 - accuracy: 0.7406 - val_loss: 0.5422 - val_accuracy: 0.7166\n",
            "Epoch 16/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5297 - accuracy: 0.7406 - val_loss: 0.5458 - val_accuracy: 0.7166\n",
            "Epoch 17/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5315 - accuracy: 0.7406 - val_loss: 0.5438 - val_accuracy: 0.7166\n",
            "Epoch 18/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5313 - accuracy: 0.7406 - val_loss: 0.5424 - val_accuracy: 0.7166\n",
            "Epoch 19/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5292 - accuracy: 0.7406 - val_loss: 0.5453 - val_accuracy: 0.7166\n",
            "Epoch 20/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5308 - accuracy: 0.7406 - val_loss: 0.5437 - val_accuracy: 0.7166\n",
            "Epoch 21/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5308 - accuracy: 0.7406 - val_loss: 0.5431 - val_accuracy: 0.7166\n",
            "Epoch 22/50\n",
            "166/166 [==============================] - 2s 10ms/step - loss: 0.5292 - accuracy: 0.7406 - val_loss: 0.5434 - val_accuracy: 0.7166\n",
            "Epoch 23/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5299 - accuracy: 0.7406 - val_loss: 0.5487 - val_accuracy: 0.7166\n",
            "Epoch 24/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5304 - accuracy: 0.7406 - val_loss: 0.5452 - val_accuracy: 0.7166\n",
            "Epoch 25/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5287 - accuracy: 0.7406 - val_loss: 0.5489 - val_accuracy: 0.7166\n",
            "Epoch 26/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5295 - accuracy: 0.7406 - val_loss: 0.5463 - val_accuracy: 0.7166\n",
            "Epoch 27/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5303 - accuracy: 0.7406 - val_loss: 0.5422 - val_accuracy: 0.7166\n",
            "Epoch 28/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5303 - accuracy: 0.7406 - val_loss: 0.5447 - val_accuracy: 0.7166\n",
            "Epoch 29/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5295 - accuracy: 0.7406 - val_loss: 0.5449 - val_accuracy: 0.7166\n",
            "Epoch 30/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5290 - accuracy: 0.7406 - val_loss: 0.5466 - val_accuracy: 0.7166\n",
            "Epoch 31/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5294 - accuracy: 0.7406 - val_loss: 0.5462 - val_accuracy: 0.7166\n",
            "Epoch 32/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5290 - accuracy: 0.7406 - val_loss: 0.5449 - val_accuracy: 0.7166\n",
            "Epoch 33/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5304 - accuracy: 0.7406 - val_loss: 0.5441 - val_accuracy: 0.7166\n",
            "Epoch 34/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5293 - accuracy: 0.7406 - val_loss: 0.5434 - val_accuracy: 0.7166\n",
            "Epoch 35/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5297 - accuracy: 0.7406 - val_loss: 0.5452 - val_accuracy: 0.7166\n",
            "Epoch 36/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5288 - accuracy: 0.7406 - val_loss: 0.5438 - val_accuracy: 0.7166\n",
            "Epoch 37/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5295 - accuracy: 0.7406 - val_loss: 0.5434 - val_accuracy: 0.7166\n",
            "Epoch 38/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5292 - accuracy: 0.7406 - val_loss: 0.5449 - val_accuracy: 0.7166\n",
            "Epoch 39/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5297 - accuracy: 0.7406 - val_loss: 0.5428 - val_accuracy: 0.7166\n",
            "Epoch 40/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5292 - accuracy: 0.7406 - val_loss: 0.5442 - val_accuracy: 0.7166\n",
            "Epoch 41/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5291 - accuracy: 0.7406 - val_loss: 0.5441 - val_accuracy: 0.7166\n",
            "Epoch 42/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5288 - accuracy: 0.7406 - val_loss: 0.5425 - val_accuracy: 0.7166\n",
            "Epoch 43/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5292 - accuracy: 0.7406 - val_loss: 0.5434 - val_accuracy: 0.7166\n",
            "Epoch 44/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5287 - accuracy: 0.7406 - val_loss: 0.5455 - val_accuracy: 0.7166\n",
            "Epoch 45/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5297 - accuracy: 0.7406 - val_loss: 0.5451 - val_accuracy: 0.7166\n",
            "Epoch 46/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5290 - accuracy: 0.7406 - val_loss: 0.5454 - val_accuracy: 0.7166\n",
            "Epoch 47/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5297 - accuracy: 0.7406 - val_loss: 0.5446 - val_accuracy: 0.7166\n",
            "Epoch 48/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5294 - accuracy: 0.7406 - val_loss: 0.5435 - val_accuracy: 0.7166\n",
            "Epoch 49/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5296 - accuracy: 0.7406 - val_loss: 0.5449 - val_accuracy: 0.7166\n",
            "Epoch 50/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5289 - accuracy: 0.7406 - val_loss: 0.5457 - val_accuracy: 0.7166\n",
            "56/56 [==============================] - 0s 2ms/step\n",
            "Accuracy for Music Product: 0.7166382737081204\n",
            "Epoch 1/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5710 - accuracy: 0.7406 - val_loss: 0.5648 - val_accuracy: 0.7166\n",
            "Epoch 2/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5356 - accuracy: 0.7384 - val_loss: 0.5640 - val_accuracy: 0.7166\n",
            "Epoch 3/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5340 - accuracy: 0.7406 - val_loss: 0.5486 - val_accuracy: 0.7166\n",
            "Epoch 4/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5325 - accuracy: 0.7406 - val_loss: 0.5502 - val_accuracy: 0.7166\n",
            "Epoch 5/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5325 - accuracy: 0.7406 - val_loss: 0.5492 - val_accuracy: 0.7166\n",
            "Epoch 6/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5322 - accuracy: 0.7406 - val_loss: 0.5546 - val_accuracy: 0.7166\n",
            "Epoch 7/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5320 - accuracy: 0.7406 - val_loss: 0.5519 - val_accuracy: 0.7166\n",
            "Epoch 8/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5323 - accuracy: 0.7406 - val_loss: 0.5505 - val_accuracy: 0.7166\n",
            "Epoch 9/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5329 - accuracy: 0.7406 - val_loss: 0.5485 - val_accuracy: 0.7166\n",
            "Epoch 10/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5315 - accuracy: 0.7406 - val_loss: 0.5498 - val_accuracy: 0.7166\n",
            "Epoch 11/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5312 - accuracy: 0.7406 - val_loss: 0.5511 - val_accuracy: 0.7166\n",
            "Epoch 12/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5312 - accuracy: 0.7406 - val_loss: 0.5495 - val_accuracy: 0.7166\n",
            "Epoch 13/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5325 - accuracy: 0.7406 - val_loss: 0.5492 - val_accuracy: 0.7166\n",
            "Epoch 14/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5325 - accuracy: 0.7406 - val_loss: 0.5495 - val_accuracy: 0.7166\n",
            "Epoch 15/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5331 - accuracy: 0.7406 - val_loss: 0.5490 - val_accuracy: 0.7166\n",
            "Epoch 16/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5310 - accuracy: 0.7406 - val_loss: 0.5487 - val_accuracy: 0.7166\n",
            "Epoch 17/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5321 - accuracy: 0.7406 - val_loss: 0.5524 - val_accuracy: 0.7166\n",
            "Epoch 18/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5312 - accuracy: 0.7406 - val_loss: 0.5488 - val_accuracy: 0.7166\n",
            "Epoch 19/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5314 - accuracy: 0.7406 - val_loss: 0.5499 - val_accuracy: 0.7166\n",
            "Epoch 20/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5312 - accuracy: 0.7406 - val_loss: 0.5514 - val_accuracy: 0.7166\n",
            "Epoch 21/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5315 - accuracy: 0.7406 - val_loss: 0.5494 - val_accuracy: 0.7166\n",
            "Epoch 22/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5314 - accuracy: 0.7406 - val_loss: 0.5490 - val_accuracy: 0.7166\n",
            "Epoch 23/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5313 - accuracy: 0.7406 - val_loss: 0.5505 - val_accuracy: 0.7166\n",
            "Epoch 24/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5314 - accuracy: 0.7406 - val_loss: 0.5503 - val_accuracy: 0.7166\n",
            "Epoch 25/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5312 - accuracy: 0.7406 - val_loss: 0.5492 - val_accuracy: 0.7166\n",
            "Epoch 26/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5315 - accuracy: 0.7406 - val_loss: 0.5503 - val_accuracy: 0.7166\n",
            "Epoch 27/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5316 - accuracy: 0.7406 - val_loss: 0.5506 - val_accuracy: 0.7166\n",
            "Epoch 28/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5322 - accuracy: 0.7406 - val_loss: 0.5493 - val_accuracy: 0.7166\n",
            "Epoch 29/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5305 - accuracy: 0.7406 - val_loss: 0.5514 - val_accuracy: 0.7166\n",
            "Epoch 30/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5315 - accuracy: 0.7406 - val_loss: 0.5509 - val_accuracy: 0.7166\n",
            "Epoch 31/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5317 - accuracy: 0.7406 - val_loss: 0.5504 - val_accuracy: 0.7166\n",
            "Epoch 32/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5312 - accuracy: 0.7406 - val_loss: 0.5498 - val_accuracy: 0.7166\n",
            "Epoch 33/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5316 - accuracy: 0.7406 - val_loss: 0.5490 - val_accuracy: 0.7166\n",
            "Epoch 34/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5312 - accuracy: 0.7406 - val_loss: 0.5488 - val_accuracy: 0.7166\n",
            "Epoch 35/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5312 - accuracy: 0.7406 - val_loss: 0.5490 - val_accuracy: 0.7166\n",
            "Epoch 36/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5301 - accuracy: 0.7406 - val_loss: 0.5487 - val_accuracy: 0.7166\n",
            "Epoch 37/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5311 - accuracy: 0.7406 - val_loss: 0.5513 - val_accuracy: 0.7166\n",
            "Epoch 38/50\n",
            "166/166 [==============================] - 1s 7ms/step - loss: 0.5315 - accuracy: 0.7406 - val_loss: 0.5494 - val_accuracy: 0.7166\n",
            "Epoch 39/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5310 - accuracy: 0.7406 - val_loss: 0.5487 - val_accuracy: 0.7166\n",
            "Epoch 40/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5308 - accuracy: 0.7406 - val_loss: 0.5487 - val_accuracy: 0.7166\n",
            "Epoch 41/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5317 - accuracy: 0.7406 - val_loss: 0.5493 - val_accuracy: 0.7166\n",
            "Epoch 42/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5312 - accuracy: 0.7406 - val_loss: 0.5494 - val_accuracy: 0.7166\n",
            "Epoch 43/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5314 - accuracy: 0.7406 - val_loss: 0.5484 - val_accuracy: 0.7166\n",
            "Epoch 44/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5316 - accuracy: 0.7406 - val_loss: 0.5489 - val_accuracy: 0.7166\n",
            "Epoch 45/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5309 - accuracy: 0.7406 - val_loss: 0.5505 - val_accuracy: 0.7166\n",
            "Epoch 46/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5319 - accuracy: 0.7406 - val_loss: 0.5492 - val_accuracy: 0.7166\n",
            "Epoch 47/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5308 - accuracy: 0.7406 - val_loss: 0.5494 - val_accuracy: 0.7166\n",
            "Epoch 48/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5303 - accuracy: 0.7406 - val_loss: 0.5509 - val_accuracy: 0.7166\n",
            "Epoch 49/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5307 - accuracy: 0.7406 - val_loss: 0.5491 - val_accuracy: 0.7166\n",
            "Epoch 50/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5309 - accuracy: 0.7406 - val_loss: 0.5491 - val_accuracy: 0.7166\n",
            "56/56 [==============================] - 0s 3ms/step\n",
            "Accuracy for Education Product: 0.7166382737081204\n",
            "Epoch 1/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5632 - accuracy: 0.7395 - val_loss: 0.5802 - val_accuracy: 0.7166\n",
            "Epoch 2/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5605 - accuracy: 0.7406 - val_loss: 0.5781 - val_accuracy: 0.7166\n",
            "Epoch 3/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5602 - accuracy: 0.7406 - val_loss: 0.5806 - val_accuracy: 0.7166\n",
            "Epoch 4/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5602 - accuracy: 0.7406 - val_loss: 0.5806 - val_accuracy: 0.7166\n",
            "Epoch 5/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5604 - accuracy: 0.7406 - val_loss: 0.5780 - val_accuracy: 0.7166\n",
            "Epoch 6/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5605 - accuracy: 0.7406 - val_loss: 0.5786 - val_accuracy: 0.7166\n",
            "Epoch 7/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5613 - accuracy: 0.7406 - val_loss: 0.5808 - val_accuracy: 0.7166\n",
            "Epoch 8/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5605 - accuracy: 0.7406 - val_loss: 0.5803 - val_accuracy: 0.7166\n",
            "Epoch 9/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5601 - accuracy: 0.7406 - val_loss: 0.5804 - val_accuracy: 0.7166\n",
            "Epoch 10/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5594 - accuracy: 0.7406 - val_loss: 0.5787 - val_accuracy: 0.7166\n",
            "Epoch 11/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5612 - accuracy: 0.7406 - val_loss: 0.5783 - val_accuracy: 0.7166\n",
            "Epoch 12/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5597 - accuracy: 0.7406 - val_loss: 0.5797 - val_accuracy: 0.7166\n",
            "Epoch 13/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5595 - accuracy: 0.7406 - val_loss: 0.5796 - val_accuracy: 0.7166\n",
            "Epoch 14/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5599 - accuracy: 0.7406 - val_loss: 0.5844 - val_accuracy: 0.7166\n",
            "Epoch 15/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5605 - accuracy: 0.7406 - val_loss: 0.5797 - val_accuracy: 0.7166\n",
            "Epoch 16/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5606 - accuracy: 0.7406 - val_loss: 0.5787 - val_accuracy: 0.7166\n",
            "Epoch 17/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5604 - accuracy: 0.7406 - val_loss: 0.5810 - val_accuracy: 0.7166\n",
            "Epoch 18/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5600 - accuracy: 0.7406 - val_loss: 0.5789 - val_accuracy: 0.7166\n",
            "Epoch 19/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5601 - accuracy: 0.7406 - val_loss: 0.5812 - val_accuracy: 0.7166\n",
            "Epoch 20/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5602 - accuracy: 0.7406 - val_loss: 0.5802 - val_accuracy: 0.7166\n",
            "Epoch 21/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5599 - accuracy: 0.7406 - val_loss: 0.5801 - val_accuracy: 0.7166\n",
            "Epoch 22/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5600 - accuracy: 0.7406 - val_loss: 0.5786 - val_accuracy: 0.7166\n",
            "Epoch 23/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5597 - accuracy: 0.7406 - val_loss: 0.5801 - val_accuracy: 0.7166\n",
            "Epoch 24/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5603 - accuracy: 0.7406 - val_loss: 0.5786 - val_accuracy: 0.7166\n",
            "Epoch 25/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5599 - accuracy: 0.7406 - val_loss: 0.5796 - val_accuracy: 0.7166\n",
            "Epoch 26/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5600 - accuracy: 0.7406 - val_loss: 0.5779 - val_accuracy: 0.7166\n",
            "Epoch 27/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5596 - accuracy: 0.7406 - val_loss: 0.5807 - val_accuracy: 0.7166\n",
            "Epoch 28/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5605 - accuracy: 0.7406 - val_loss: 0.5790 - val_accuracy: 0.7166\n",
            "Epoch 29/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5598 - accuracy: 0.7406 - val_loss: 0.5781 - val_accuracy: 0.7166\n",
            "Epoch 30/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5602 - accuracy: 0.7406 - val_loss: 0.5809 - val_accuracy: 0.7166\n",
            "Epoch 31/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5602 - accuracy: 0.7406 - val_loss: 0.5791 - val_accuracy: 0.7166\n",
            "Epoch 32/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5603 - accuracy: 0.7406 - val_loss: 0.5796 - val_accuracy: 0.7166\n",
            "Epoch 33/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5596 - accuracy: 0.7406 - val_loss: 0.5791 - val_accuracy: 0.7166\n",
            "Epoch 34/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5596 - accuracy: 0.7406 - val_loss: 0.5853 - val_accuracy: 0.7166\n",
            "Epoch 35/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5604 - accuracy: 0.7406 - val_loss: 0.5814 - val_accuracy: 0.7166\n",
            "Epoch 36/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5598 - accuracy: 0.7406 - val_loss: 0.5803 - val_accuracy: 0.7166\n",
            "Epoch 37/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5598 - accuracy: 0.7406 - val_loss: 0.5789 - val_accuracy: 0.7166\n",
            "Epoch 38/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5605 - accuracy: 0.7406 - val_loss: 0.5786 - val_accuracy: 0.7166\n",
            "Epoch 39/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5595 - accuracy: 0.7406 - val_loss: 0.5788 - val_accuracy: 0.7166\n",
            "Epoch 40/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5606 - accuracy: 0.7406 - val_loss: 0.5790 - val_accuracy: 0.7166\n",
            "Epoch 41/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5600 - accuracy: 0.7406 - val_loss: 0.5785 - val_accuracy: 0.7166\n",
            "Epoch 42/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5596 - accuracy: 0.7406 - val_loss: 0.5792 - val_accuracy: 0.7166\n",
            "Epoch 43/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5599 - accuracy: 0.7406 - val_loss: 0.5795 - val_accuracy: 0.7166\n",
            "Epoch 44/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5596 - accuracy: 0.7406 - val_loss: 0.5784 - val_accuracy: 0.7166\n",
            "Epoch 45/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5596 - accuracy: 0.7406 - val_loss: 0.5787 - val_accuracy: 0.7166\n",
            "Epoch 46/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5599 - accuracy: 0.7406 - val_loss: 0.5791 - val_accuracy: 0.7166\n",
            "Epoch 47/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5595 - accuracy: 0.7406 - val_loss: 0.5789 - val_accuracy: 0.7166\n",
            "Epoch 48/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5600 - accuracy: 0.7406 - val_loss: 0.5795 - val_accuracy: 0.7166\n",
            "Epoch 49/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5595 - accuracy: 0.7406 - val_loss: 0.5806 - val_accuracy: 0.7166\n",
            "Epoch 50/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5596 - accuracy: 0.7406 - val_loss: 0.5809 - val_accuracy: 0.7166\n",
            "56/56 [==============================] - 0s 3ms/step\n",
            "Accuracy for Call Center: 0.7166382737081204\n",
            "Epoch 1/50\n",
            "166/166 [==============================] - 2s 5ms/step - loss: 0.5850 - accuracy: 0.7342 - val_loss: 0.5696 - val_accuracy: 0.7166\n",
            "Epoch 2/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5453 - accuracy: 0.7406 - val_loss: 0.5655 - val_accuracy: 0.7166\n",
            "Epoch 3/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5441 - accuracy: 0.7406 - val_loss: 0.5645 - val_accuracy: 0.7166\n",
            "Epoch 4/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5440 - accuracy: 0.7406 - val_loss: 0.5668 - val_accuracy: 0.7166\n",
            "Epoch 5/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5441 - accuracy: 0.7406 - val_loss: 0.5663 - val_accuracy: 0.7166\n",
            "Epoch 6/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5429 - accuracy: 0.7406 - val_loss: 0.5661 - val_accuracy: 0.7166\n",
            "Epoch 7/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5437 - accuracy: 0.7406 - val_loss: 0.5652 - val_accuracy: 0.7166\n",
            "Epoch 8/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5426 - accuracy: 0.7406 - val_loss: 0.5693 - val_accuracy: 0.7166\n",
            "Epoch 9/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5419 - accuracy: 0.7406 - val_loss: 0.5671 - val_accuracy: 0.7166\n",
            "Epoch 10/50\n",
            "166/166 [==============================] - 0s 3ms/step - loss: 0.5422 - accuracy: 0.7406 - val_loss: 0.5650 - val_accuracy: 0.7166\n",
            "Epoch 11/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5421 - accuracy: 0.7406 - val_loss: 0.5816 - val_accuracy: 0.7166\n",
            "Epoch 12/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5444 - accuracy: 0.7406 - val_loss: 0.5651 - val_accuracy: 0.7166\n",
            "Epoch 13/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5423 - accuracy: 0.7406 - val_loss: 0.5665 - val_accuracy: 0.7166\n",
            "Epoch 14/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5427 - accuracy: 0.7406 - val_loss: 0.5651 - val_accuracy: 0.7166\n",
            "Epoch 15/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5425 - accuracy: 0.7406 - val_loss: 0.5683 - val_accuracy: 0.7166\n",
            "Epoch 16/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5422 - accuracy: 0.7406 - val_loss: 0.5647 - val_accuracy: 0.7166\n",
            "Epoch 17/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5426 - accuracy: 0.7406 - val_loss: 0.5663 - val_accuracy: 0.7166\n",
            "Epoch 18/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5429 - accuracy: 0.7406 - val_loss: 0.5655 - val_accuracy: 0.7166\n",
            "Epoch 19/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5426 - accuracy: 0.7406 - val_loss: 0.5645 - val_accuracy: 0.7166\n",
            "Epoch 20/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5639 - val_accuracy: 0.7166\n",
            "Epoch 21/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5417 - accuracy: 0.7406 - val_loss: 0.5710 - val_accuracy: 0.7166\n",
            "Epoch 22/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5437 - accuracy: 0.7406 - val_loss: 0.5650 - val_accuracy: 0.7166\n",
            "Epoch 23/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5423 - accuracy: 0.7406 - val_loss: 0.5677 - val_accuracy: 0.7166\n",
            "Epoch 24/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5422 - accuracy: 0.7406 - val_loss: 0.5644 - val_accuracy: 0.7166\n",
            "Epoch 25/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5420 - accuracy: 0.7406 - val_loss: 0.5643 - val_accuracy: 0.7166\n",
            "Epoch 26/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5423 - accuracy: 0.7406 - val_loss: 0.5641 - val_accuracy: 0.7166\n",
            "Epoch 27/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5654 - val_accuracy: 0.7166\n",
            "Epoch 28/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5421 - accuracy: 0.7406 - val_loss: 0.5647 - val_accuracy: 0.7166\n",
            "Epoch 29/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5418 - accuracy: 0.7406 - val_loss: 0.5672 - val_accuracy: 0.7166\n",
            "Epoch 30/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5417 - accuracy: 0.7406 - val_loss: 0.5648 - val_accuracy: 0.7166\n",
            "Epoch 31/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5414 - accuracy: 0.7406 - val_loss: 0.5665 - val_accuracy: 0.7166\n",
            "Epoch 32/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5417 - accuracy: 0.7406 - val_loss: 0.5649 - val_accuracy: 0.7166\n",
            "Epoch 33/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5417 - accuracy: 0.7406 - val_loss: 0.5662 - val_accuracy: 0.7166\n",
            "Epoch 34/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5643 - val_accuracy: 0.7166\n",
            "Epoch 35/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5653 - val_accuracy: 0.7166\n",
            "Epoch 36/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5418 - accuracy: 0.7406 - val_loss: 0.5672 - val_accuracy: 0.7166\n",
            "Epoch 37/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5417 - accuracy: 0.7406 - val_loss: 0.5648 - val_accuracy: 0.7166\n",
            "Epoch 38/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5420 - accuracy: 0.7406 - val_loss: 0.5653 - val_accuracy: 0.7166\n",
            "Epoch 39/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5426 - accuracy: 0.7406 - val_loss: 0.5645 - val_accuracy: 0.7166\n",
            "Epoch 40/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5414 - accuracy: 0.7406 - val_loss: 0.5649 - val_accuracy: 0.7166\n",
            "Epoch 41/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5670 - val_accuracy: 0.7166\n",
            "Epoch 42/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5415 - accuracy: 0.7406 - val_loss: 0.5641 - val_accuracy: 0.7166\n",
            "Epoch 43/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5419 - accuracy: 0.7406 - val_loss: 0.5645 - val_accuracy: 0.7166\n",
            "Epoch 44/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5414 - accuracy: 0.7406 - val_loss: 0.5661 - val_accuracy: 0.7166\n",
            "Epoch 45/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5418 - accuracy: 0.7406 - val_loss: 0.5648 - val_accuracy: 0.7166\n",
            "Epoch 46/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5420 - accuracy: 0.7406 - val_loss: 0.5647 - val_accuracy: 0.7166\n",
            "Epoch 47/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5423 - accuracy: 0.7406 - val_loss: 0.5644 - val_accuracy: 0.7166\n",
            "Epoch 48/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5419 - accuracy: 0.7406 - val_loss: 0.5645 - val_accuracy: 0.7166\n",
            "Epoch 49/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5646 - val_accuracy: 0.7166\n",
            "Epoch 50/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5423 - accuracy: 0.7406 - val_loss: 0.5649 - val_accuracy: 0.7166\n",
            "56/56 [==============================] - 0s 3ms/step\n",
            "Accuracy for Video Product: 0.7166382737081204\n",
            "Epoch 1/50\n",
            "166/166 [==============================] - 2s 5ms/step - loss: 0.5790 - accuracy: 0.7382 - val_loss: 0.5698 - val_accuracy: 0.7166\n",
            "Epoch 2/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5457 - accuracy: 0.7406 - val_loss: 0.5651 - val_accuracy: 0.7166\n",
            "Epoch 3/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5424 - accuracy: 0.7406 - val_loss: 0.5645 - val_accuracy: 0.7166\n",
            "Epoch 4/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5434 - accuracy: 0.7406 - val_loss: 0.5688 - val_accuracy: 0.7166\n",
            "Epoch 5/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5432 - accuracy: 0.7406 - val_loss: 0.5656 - val_accuracy: 0.7166\n",
            "Epoch 6/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5432 - accuracy: 0.7406 - val_loss: 0.5655 - val_accuracy: 0.7166\n",
            "Epoch 7/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5414 - accuracy: 0.7406 - val_loss: 0.5665 - val_accuracy: 0.7166\n",
            "Epoch 8/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5419 - accuracy: 0.7406 - val_loss: 0.5651 - val_accuracy: 0.7166\n",
            "Epoch 9/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5434 - accuracy: 0.7406 - val_loss: 0.5677 - val_accuracy: 0.7166\n",
            "Epoch 10/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5446 - accuracy: 0.7406 - val_loss: 0.5646 - val_accuracy: 0.7166\n",
            "Epoch 11/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5417 - accuracy: 0.7406 - val_loss: 0.5681 - val_accuracy: 0.7166\n",
            "Epoch 12/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5429 - accuracy: 0.7406 - val_loss: 0.5654 - val_accuracy: 0.7166\n",
            "Epoch 13/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5418 - accuracy: 0.7406 - val_loss: 0.5656 - val_accuracy: 0.7166\n",
            "Epoch 14/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5418 - accuracy: 0.7406 - val_loss: 0.5640 - val_accuracy: 0.7166\n",
            "Epoch 15/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5412 - accuracy: 0.7406 - val_loss: 0.5776 - val_accuracy: 0.7166\n",
            "Epoch 16/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5415 - accuracy: 0.7406 - val_loss: 0.5654 - val_accuracy: 0.7166\n",
            "Epoch 17/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5424 - accuracy: 0.7406 - val_loss: 0.5644 - val_accuracy: 0.7166\n",
            "Epoch 18/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5433 - accuracy: 0.7406 - val_loss: 0.5664 - val_accuracy: 0.7166\n",
            "Epoch 19/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5422 - accuracy: 0.7406 - val_loss: 0.5647 - val_accuracy: 0.7166\n",
            "Epoch 20/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5418 - accuracy: 0.7406 - val_loss: 0.5646 - val_accuracy: 0.7166\n",
            "Epoch 21/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5417 - accuracy: 0.7406 - val_loss: 0.5641 - val_accuracy: 0.7166\n",
            "Epoch 22/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5417 - accuracy: 0.7406 - val_loss: 0.5663 - val_accuracy: 0.7166\n",
            "Epoch 23/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5424 - accuracy: 0.7406 - val_loss: 0.5648 - val_accuracy: 0.7166\n",
            "Epoch 24/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5420 - accuracy: 0.7406 - val_loss: 0.5640 - val_accuracy: 0.7166\n",
            "Epoch 25/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5418 - accuracy: 0.7406 - val_loss: 0.5645 - val_accuracy: 0.7166\n",
            "Epoch 26/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5421 - accuracy: 0.7406 - val_loss: 0.5670 - val_accuracy: 0.7166\n",
            "Epoch 27/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5419 - accuracy: 0.7406 - val_loss: 0.5645 - val_accuracy: 0.7166\n",
            "Epoch 28/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5415 - accuracy: 0.7406 - val_loss: 0.5657 - val_accuracy: 0.7166\n",
            "Epoch 29/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5419 - accuracy: 0.7406 - val_loss: 0.5655 - val_accuracy: 0.7166\n",
            "Epoch 30/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5414 - accuracy: 0.7406 - val_loss: 0.5659 - val_accuracy: 0.7166\n",
            "Epoch 31/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5415 - accuracy: 0.7406 - val_loss: 0.5643 - val_accuracy: 0.7166\n",
            "Epoch 32/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5427 - accuracy: 0.7406 - val_loss: 0.5645 - val_accuracy: 0.7166\n",
            "Epoch 33/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5649 - val_accuracy: 0.7166\n",
            "Epoch 34/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5415 - accuracy: 0.7406 - val_loss: 0.5645 - val_accuracy: 0.7166\n",
            "Epoch 35/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5426 - accuracy: 0.7406 - val_loss: 0.5662 - val_accuracy: 0.7166\n",
            "Epoch 36/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5420 - accuracy: 0.7406 - val_loss: 0.5646 - val_accuracy: 0.7166\n",
            "Epoch 37/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5655 - val_accuracy: 0.7166\n",
            "Epoch 38/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5419 - accuracy: 0.7406 - val_loss: 0.5665 - val_accuracy: 0.7166\n",
            "Epoch 39/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5422 - accuracy: 0.7406 - val_loss: 0.5650 - val_accuracy: 0.7166\n",
            "Epoch 40/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5651 - val_accuracy: 0.7166\n",
            "Epoch 41/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5656 - val_accuracy: 0.7166\n",
            "Epoch 42/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5642 - val_accuracy: 0.7166\n",
            "Epoch 43/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5652 - val_accuracy: 0.7166\n",
            "Epoch 44/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5418 - accuracy: 0.7406 - val_loss: 0.5665 - val_accuracy: 0.7166\n",
            "Epoch 45/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5673 - val_accuracy: 0.7166\n",
            "Epoch 46/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5652 - val_accuracy: 0.7166\n",
            "Epoch 47/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5412 - accuracy: 0.7406 - val_loss: 0.5650 - val_accuracy: 0.7166\n",
            "Epoch 48/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5417 - accuracy: 0.7406 - val_loss: 0.5653 - val_accuracy: 0.7166\n",
            "Epoch 49/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5418 - accuracy: 0.7406 - val_loss: 0.5656 - val_accuracy: 0.7166\n",
            "Epoch 50/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5414 - accuracy: 0.7406 - val_loss: 0.5641 - val_accuracy: 0.7166\n",
            "56/56 [==============================] - 0s 3ms/step\n",
            "Accuracy for Use MyApp: 0.7166382737081204\n",
            "Epoch 1/50\n",
            "166/166 [==============================] - 2s 5ms/step - loss: 0.5552 - accuracy: 0.7393 - val_loss: 0.5534 - val_accuracy: 0.7166\n",
            "Epoch 2/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5314 - accuracy: 0.7384 - val_loss: 0.5531 - val_accuracy: 0.6979\n",
            "Epoch 3/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5332 - accuracy: 0.7357 - val_loss: 0.5498 - val_accuracy: 0.7166\n",
            "Epoch 4/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5308 - accuracy: 0.7368 - val_loss: 0.5543 - val_accuracy: 0.7166\n",
            "Epoch 5/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5311 - accuracy: 0.7385 - val_loss: 0.5535 - val_accuracy: 0.7166\n",
            "Epoch 6/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5313 - accuracy: 0.7370 - val_loss: 0.5497 - val_accuracy: 0.7166\n",
            "Epoch 7/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5309 - accuracy: 0.7370 - val_loss: 0.5525 - val_accuracy: 0.7166\n",
            "Epoch 8/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5304 - accuracy: 0.7412 - val_loss: 0.5535 - val_accuracy: 0.6979\n",
            "Epoch 9/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5321 - accuracy: 0.7336 - val_loss: 0.5504 - val_accuracy: 0.7166\n",
            "Epoch 10/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5304 - accuracy: 0.7372 - val_loss: 0.5520 - val_accuracy: 0.7166\n",
            "Epoch 11/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5309 - accuracy: 0.7406 - val_loss: 0.5533 - val_accuracy: 0.7166\n",
            "Epoch 12/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5307 - accuracy: 0.7406 - val_loss: 0.5517 - val_accuracy: 0.7166\n",
            "Epoch 13/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5306 - accuracy: 0.7380 - val_loss: 0.5512 - val_accuracy: 0.7166\n",
            "Epoch 14/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5311 - accuracy: 0.7406 - val_loss: 0.5561 - val_accuracy: 0.7166\n",
            "Epoch 15/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5311 - accuracy: 0.7406 - val_loss: 0.5516 - val_accuracy: 0.7166\n",
            "Epoch 16/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5306 - accuracy: 0.7406 - val_loss: 0.5518 - val_accuracy: 0.7166\n",
            "Epoch 17/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5302 - accuracy: 0.7406 - val_loss: 0.5515 - val_accuracy: 0.7166\n",
            "Epoch 18/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5302 - accuracy: 0.7393 - val_loss: 0.5501 - val_accuracy: 0.7166\n",
            "Epoch 19/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5305 - accuracy: 0.7406 - val_loss: 0.5504 - val_accuracy: 0.7166\n",
            "Epoch 20/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5302 - accuracy: 0.7406 - val_loss: 0.5496 - val_accuracy: 0.7166\n",
            "Epoch 21/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5296 - accuracy: 0.7406 - val_loss: 0.5507 - val_accuracy: 0.7166\n",
            "Epoch 22/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5299 - accuracy: 0.7406 - val_loss: 0.5496 - val_accuracy: 0.7166\n",
            "Epoch 23/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5304 - accuracy: 0.7406 - val_loss: 0.5496 - val_accuracy: 0.7166\n",
            "Epoch 24/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5300 - accuracy: 0.7382 - val_loss: 0.5509 - val_accuracy: 0.7166\n",
            "Epoch 25/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5307 - accuracy: 0.7406 - val_loss: 0.5503 - val_accuracy: 0.7166\n",
            "Epoch 26/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5309 - accuracy: 0.7406 - val_loss: 0.5499 - val_accuracy: 0.7166\n",
            "Epoch 27/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5307 - accuracy: 0.7406 - val_loss: 0.5520 - val_accuracy: 0.7166\n",
            "Epoch 28/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5302 - accuracy: 0.7406 - val_loss: 0.5502 - val_accuracy: 0.7166\n",
            "Epoch 29/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5308 - accuracy: 0.7406 - val_loss: 0.5546 - val_accuracy: 0.7166\n",
            "Epoch 30/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5305 - accuracy: 0.7406 - val_loss: 0.5493 - val_accuracy: 0.7166\n",
            "Epoch 31/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5305 - accuracy: 0.7406 - val_loss: 0.5508 - val_accuracy: 0.7166\n",
            "Epoch 32/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5304 - accuracy: 0.7406 - val_loss: 0.5520 - val_accuracy: 0.7166\n",
            "Epoch 33/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5298 - accuracy: 0.7406 - val_loss: 0.5511 - val_accuracy: 0.7166\n",
            "Epoch 34/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5301 - accuracy: 0.7406 - val_loss: 0.5496 - val_accuracy: 0.7166\n",
            "Epoch 35/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5299 - accuracy: 0.7406 - val_loss: 0.5502 - val_accuracy: 0.7166\n",
            "Epoch 36/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5296 - accuracy: 0.7406 - val_loss: 0.5521 - val_accuracy: 0.7166\n",
            "Epoch 37/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5299 - accuracy: 0.7406 - val_loss: 0.5512 - val_accuracy: 0.7166\n",
            "Epoch 38/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5301 - accuracy: 0.7406 - val_loss: 0.5500 - val_accuracy: 0.7166\n",
            "Epoch 39/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5295 - accuracy: 0.7406 - val_loss: 0.5546 - val_accuracy: 0.7166\n",
            "Epoch 40/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5301 - accuracy: 0.7406 - val_loss: 0.5496 - val_accuracy: 0.7166\n",
            "Epoch 41/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5295 - accuracy: 0.7406 - val_loss: 0.5501 - val_accuracy: 0.7166\n",
            "Epoch 42/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5295 - accuracy: 0.7406 - val_loss: 0.5498 - val_accuracy: 0.7166\n",
            "Epoch 43/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5297 - accuracy: 0.7406 - val_loss: 0.5492 - val_accuracy: 0.7166\n",
            "Epoch 44/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5297 - accuracy: 0.7406 - val_loss: 0.5505 - val_accuracy: 0.7166\n",
            "Epoch 45/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5297 - accuracy: 0.7406 - val_loss: 0.5500 - val_accuracy: 0.7166\n",
            "Epoch 46/50\n",
            "166/166 [==============================] - 2s 9ms/step - loss: 0.5295 - accuracy: 0.7406 - val_loss: 0.5507 - val_accuracy: 0.7166\n",
            "Epoch 47/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5298 - accuracy: 0.7406 - val_loss: 0.5502 - val_accuracy: 0.7166\n",
            "Epoch 48/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5296 - accuracy: 0.7406 - val_loss: 0.5512 - val_accuracy: 0.7166\n",
            "Epoch 49/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5296 - accuracy: 0.7406 - val_loss: 0.5536 - val_accuracy: 0.7166\n",
            "Epoch 50/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5301 - accuracy: 0.7406 - val_loss: 0.5511 - val_accuracy: 0.7166\n",
            "56/56 [==============================] - 0s 4ms/step\n",
            "Accuracy for Payment Method: 0.7166382737081204\n",
            "Epoch 1/50\n",
            "166/166 [==============================] - 2s 7ms/step - loss: 0.5599 - accuracy: 0.7349 - val_loss: 0.5756 - val_accuracy: 0.7166\n",
            "Epoch 2/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5466 - accuracy: 0.7406 - val_loss: 0.5720 - val_accuracy: 0.7166\n",
            "Epoch 3/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5442 - accuracy: 0.7406 - val_loss: 0.5697 - val_accuracy: 0.7166\n",
            "Epoch 4/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5435 - accuracy: 0.7406 - val_loss: 0.5706 - val_accuracy: 0.7166\n",
            "Epoch 5/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5434 - accuracy: 0.7406 - val_loss: 0.5696 - val_accuracy: 0.7166\n",
            "Epoch 6/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5431 - accuracy: 0.7406 - val_loss: 0.5700 - val_accuracy: 0.7166\n",
            "Epoch 7/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5421 - accuracy: 0.7406 - val_loss: 0.5675 - val_accuracy: 0.7166\n",
            "Epoch 8/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5416 - accuracy: 0.7406 - val_loss: 0.5695 - val_accuracy: 0.7166\n",
            "Epoch 9/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5410 - accuracy: 0.7406 - val_loss: 0.5656 - val_accuracy: 0.7166\n",
            "Epoch 10/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5399 - accuracy: 0.7406 - val_loss: 0.5634 - val_accuracy: 0.7166\n",
            "Epoch 11/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5394 - accuracy: 0.7406 - val_loss: 0.5643 - val_accuracy: 0.7166\n",
            "Epoch 12/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5391 - accuracy: 0.7406 - val_loss: 0.5666 - val_accuracy: 0.7166\n",
            "Epoch 13/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5387 - accuracy: 0.7406 - val_loss: 0.5623 - val_accuracy: 0.7166\n",
            "Epoch 14/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5385 - accuracy: 0.7406 - val_loss: 0.5625 - val_accuracy: 0.7166\n",
            "Epoch 15/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5367 - accuracy: 0.7406 - val_loss: 0.5630 - val_accuracy: 0.7166\n",
            "Epoch 16/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5376 - accuracy: 0.7406 - val_loss: 0.5597 - val_accuracy: 0.7166\n",
            "Epoch 17/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5368 - accuracy: 0.7406 - val_loss: 0.5675 - val_accuracy: 0.7166\n",
            "Epoch 18/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5361 - accuracy: 0.7406 - val_loss: 0.5599 - val_accuracy: 0.7166\n",
            "Epoch 19/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5362 - accuracy: 0.7406 - val_loss: 0.5598 - val_accuracy: 0.7166\n",
            "Epoch 20/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5362 - accuracy: 0.7406 - val_loss: 0.5587 - val_accuracy: 0.7166\n",
            "Epoch 21/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5349 - accuracy: 0.7406 - val_loss: 0.5593 - val_accuracy: 0.7166\n",
            "Epoch 22/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5366 - accuracy: 0.7406 - val_loss: 0.5594 - val_accuracy: 0.7166\n",
            "Epoch 23/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5354 - accuracy: 0.7406 - val_loss: 0.5578 - val_accuracy: 0.7166\n",
            "Epoch 24/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5346 - accuracy: 0.7406 - val_loss: 0.5581 - val_accuracy: 0.7166\n",
            "Epoch 25/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5348 - accuracy: 0.7406 - val_loss: 0.5594 - val_accuracy: 0.7166\n",
            "Epoch 26/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5364 - accuracy: 0.7406 - val_loss: 0.5623 - val_accuracy: 0.7166\n",
            "Epoch 27/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5348 - accuracy: 0.7406 - val_loss: 0.5589 - val_accuracy: 0.7166\n",
            "Epoch 28/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5343 - accuracy: 0.7406 - val_loss: 0.5560 - val_accuracy: 0.7166\n",
            "Epoch 29/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5338 - accuracy: 0.7406 - val_loss: 0.5571 - val_accuracy: 0.7166\n",
            "Epoch 30/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5334 - accuracy: 0.7406 - val_loss: 0.5590 - val_accuracy: 0.7166\n",
            "Epoch 31/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5358 - accuracy: 0.7406 - val_loss: 0.5572 - val_accuracy: 0.7166\n",
            "Epoch 32/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5345 - accuracy: 0.7406 - val_loss: 0.5561 - val_accuracy: 0.7166\n",
            "Epoch 33/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5337 - accuracy: 0.7406 - val_loss: 0.5561 - val_accuracy: 0.7166\n",
            "Epoch 34/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5336 - accuracy: 0.7406 - val_loss: 0.5556 - val_accuracy: 0.7166\n",
            "Epoch 35/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5338 - accuracy: 0.7406 - val_loss: 0.5545 - val_accuracy: 0.7166\n",
            "Epoch 36/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5333 - accuracy: 0.7406 - val_loss: 0.5552 - val_accuracy: 0.7166\n",
            "Epoch 37/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5332 - accuracy: 0.7406 - val_loss: 0.5608 - val_accuracy: 0.7166\n",
            "Epoch 38/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5338 - accuracy: 0.7406 - val_loss: 0.5562 - val_accuracy: 0.7166\n",
            "Epoch 39/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5330 - accuracy: 0.7406 - val_loss: 0.5581 - val_accuracy: 0.7166\n",
            "Epoch 40/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5330 - accuracy: 0.7406 - val_loss: 0.5586 - val_accuracy: 0.7166\n",
            "Epoch 41/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5332 - accuracy: 0.7406 - val_loss: 0.5552 - val_accuracy: 0.7166\n",
            "Epoch 42/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5334 - accuracy: 0.7406 - val_loss: 0.5568 - val_accuracy: 0.7166\n",
            "Epoch 43/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5324 - accuracy: 0.7406 - val_loss: 0.5545 - val_accuracy: 0.7166\n",
            "Epoch 44/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5337 - accuracy: 0.7406 - val_loss: 0.5558 - val_accuracy: 0.7166\n",
            "Epoch 45/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5330 - accuracy: 0.7406 - val_loss: 0.5550 - val_accuracy: 0.7166\n",
            "Epoch 46/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5331 - accuracy: 0.7406 - val_loss: 0.5580 - val_accuracy: 0.7166\n",
            "Epoch 47/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5318 - accuracy: 0.7406 - val_loss: 0.5597 - val_accuracy: 0.7166\n",
            "Epoch 48/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5326 - accuracy: 0.7406 - val_loss: 0.5545 - val_accuracy: 0.7166\n",
            "Epoch 49/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5324 - accuracy: 0.7406 - val_loss: 0.5547 - val_accuracy: 0.7166\n",
            "Epoch 50/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5352 - accuracy: 0.7406 - val_loss: 0.5545 - val_accuracy: 0.7166\n",
            "56/56 [==============================] - 0s 3ms/step\n",
            "Accuracy for Monthly Purchase (Thou. IDR): 0.7166382737081204\n",
            "Epoch 1/50\n",
            "166/166 [==============================] - 2s 6ms/step - loss: 0.5800 - accuracy: 0.7351 - val_loss: 0.5889 - val_accuracy: 0.7166\n",
            "Epoch 2/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5656 - accuracy: 0.7406 - val_loss: 0.5892 - val_accuracy: 0.7166\n",
            "Epoch 3/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5654 - accuracy: 0.7406 - val_loss: 0.5886 - val_accuracy: 0.7166\n",
            "Epoch 4/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5648 - accuracy: 0.7406 - val_loss: 0.5922 - val_accuracy: 0.7166\n",
            "Epoch 5/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5659 - accuracy: 0.7406 - val_loss: 0.5921 - val_accuracy: 0.7166\n",
            "Epoch 6/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5644 - accuracy: 0.7406 - val_loss: 0.5907 - val_accuracy: 0.7166\n",
            "Epoch 7/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5643 - accuracy: 0.7406 - val_loss: 0.5904 - val_accuracy: 0.7166\n",
            "Epoch 8/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5642 - accuracy: 0.7406 - val_loss: 0.5912 - val_accuracy: 0.7166\n",
            "Epoch 9/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5646 - accuracy: 0.7406 - val_loss: 0.5899 - val_accuracy: 0.7166\n",
            "Epoch 10/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5641 - accuracy: 0.7406 - val_loss: 0.5895 - val_accuracy: 0.7166\n",
            "Epoch 11/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5638 - accuracy: 0.7406 - val_loss: 0.5879 - val_accuracy: 0.7166\n",
            "Epoch 12/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5640 - accuracy: 0.7406 - val_loss: 0.5904 - val_accuracy: 0.7166\n",
            "Epoch 13/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5642 - accuracy: 0.7406 - val_loss: 0.5887 - val_accuracy: 0.7166\n",
            "Epoch 14/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5636 - accuracy: 0.7406 - val_loss: 0.5901 - val_accuracy: 0.7166\n",
            "Epoch 15/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5639 - accuracy: 0.7406 - val_loss: 0.5905 - val_accuracy: 0.7166\n",
            "Epoch 16/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5637 - accuracy: 0.7406 - val_loss: 0.5921 - val_accuracy: 0.7166\n",
            "Epoch 17/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5630 - accuracy: 0.7406 - val_loss: 0.5882 - val_accuracy: 0.7166\n",
            "Epoch 18/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5630 - accuracy: 0.7406 - val_loss: 0.5872 - val_accuracy: 0.7166\n",
            "Epoch 19/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5627 - accuracy: 0.7406 - val_loss: 0.5891 - val_accuracy: 0.7166\n",
            "Epoch 20/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5624 - accuracy: 0.7406 - val_loss: 0.5922 - val_accuracy: 0.7166\n",
            "Epoch 21/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5637 - accuracy: 0.7406 - val_loss: 0.5867 - val_accuracy: 0.7166\n",
            "Epoch 22/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5633 - accuracy: 0.7406 - val_loss: 0.5875 - val_accuracy: 0.7166\n",
            "Epoch 23/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5632 - accuracy: 0.7406 - val_loss: 0.5868 - val_accuracy: 0.7166\n",
            "Epoch 24/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5624 - accuracy: 0.7406 - val_loss: 0.5860 - val_accuracy: 0.7166\n",
            "Epoch 25/50\n",
            "166/166 [==============================] - 1s 7ms/step - loss: 0.5630 - accuracy: 0.7406 - val_loss: 0.5866 - val_accuracy: 0.7166\n",
            "Epoch 26/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5629 - accuracy: 0.7406 - val_loss: 0.5881 - val_accuracy: 0.7166\n",
            "Epoch 27/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5627 - accuracy: 0.7406 - val_loss: 0.5878 - val_accuracy: 0.7166\n",
            "Epoch 28/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5620 - accuracy: 0.7406 - val_loss: 0.5876 - val_accuracy: 0.7166\n",
            "Epoch 29/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5622 - accuracy: 0.7406 - val_loss: 0.5898 - val_accuracy: 0.7166\n",
            "Epoch 30/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5629 - accuracy: 0.7406 - val_loss: 0.5859 - val_accuracy: 0.7166\n",
            "Epoch 31/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5626 - accuracy: 0.7406 - val_loss: 0.5868 - val_accuracy: 0.7166\n",
            "Epoch 32/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5616 - accuracy: 0.7406 - val_loss: 0.5870 - val_accuracy: 0.7166\n",
            "Epoch 33/50\n",
            "166/166 [==============================] - 1s 6ms/step - loss: 0.5621 - accuracy: 0.7406 - val_loss: 0.5871 - val_accuracy: 0.7166\n",
            "Epoch 34/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5620 - accuracy: 0.7406 - val_loss: 0.5859 - val_accuracy: 0.7166\n",
            "Epoch 35/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5622 - accuracy: 0.7406 - val_loss: 0.5860 - val_accuracy: 0.7166\n",
            "Epoch 36/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5618 - accuracy: 0.7406 - val_loss: 0.5899 - val_accuracy: 0.7166\n",
            "Epoch 37/50\n",
            "166/166 [==============================] - 1s 5ms/step - loss: 0.5614 - accuracy: 0.7406 - val_loss: 0.5871 - val_accuracy: 0.7166\n",
            "Epoch 38/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5625 - accuracy: 0.7406 - val_loss: 0.5881 - val_accuracy: 0.7166\n",
            "Epoch 39/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5620 - accuracy: 0.7406 - val_loss: 0.5878 - val_accuracy: 0.7166\n",
            "Epoch 40/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5623 - accuracy: 0.7406 - val_loss: 0.5872 - val_accuracy: 0.7166\n",
            "Epoch 41/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5619 - accuracy: 0.7406 - val_loss: 0.5866 - val_accuracy: 0.7166\n",
            "Epoch 42/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5617 - accuracy: 0.7406 - val_loss: 0.5906 - val_accuracy: 0.7166\n",
            "Epoch 43/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5615 - accuracy: 0.7406 - val_loss: 0.5887 - val_accuracy: 0.7166\n",
            "Epoch 44/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5625 - accuracy: 0.7406 - val_loss: 0.5859 - val_accuracy: 0.7166\n",
            "Epoch 45/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5616 - accuracy: 0.7406 - val_loss: 0.5905 - val_accuracy: 0.7166\n",
            "Epoch 46/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5614 - accuracy: 0.7406 - val_loss: 0.5859 - val_accuracy: 0.7166\n",
            "Epoch 47/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5619 - accuracy: 0.7406 - val_loss: 0.5904 - val_accuracy: 0.7166\n",
            "Epoch 48/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5619 - accuracy: 0.7406 - val_loss: 0.5879 - val_accuracy: 0.7166\n",
            "Epoch 49/50\n",
            "166/166 [==============================] - 1s 3ms/step - loss: 0.5619 - accuracy: 0.7406 - val_loss: 0.5876 - val_accuracy: 0.7166\n",
            "Epoch 50/50\n",
            "166/166 [==============================] - 1s 4ms/step - loss: 0.5619 - accuracy: 0.7406 - val_loss: 0.5887 - val_accuracy: 0.7166\n",
            "56/56 [==============================] - 0s 2ms/step\n",
            "Accuracy for CLTV (Predicted Thou. IDR): 0.7166382737081204\n"
          ]
        }
      ]
    }
  ]
}