Bone_Age_Resnet50.ipynb

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        "<a href=\"https://colab.research.google.com/github/Armin-Abdollahi/Bone-Age-Estimation/blob/main/Bone_Age_Resnet50.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
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        },
        "id": "MfsPKssDLofF",
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      },
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      "outputs": [
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          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
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      "execution_count": 2,
      "metadata": {
        "id": "Wd_mxl4iLN3e"
      },
      "outputs": [],
      "source": [
        "import pandas as pd\n",
        "import tensorflow as tf\n",
        "import matplotlib.pyplot as plt\n",
        "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
        "from tensorflow.keras.applications import ResNet50\n",
        "from tensorflow.keras.layers import GlobalAveragePooling2D, Dense, Dropout\n",
        "from tensorflow.keras.optimizers import Adam"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Load the labels\n",
        "labels_path = '/content/drive/MyDrive/Digital_Hand_Atlas_Dataset/Total_Images/Bordered_XRay_Images/Label.csv'\n",
        "labels = pd.read_csv(labels_path)"
      ],
      "metadata": {
        "id": "uZiWSvKTLWAH"
      },
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "labels['Case ID'] = labels['Case ID'].apply(lambda x: str(x)+'.jpg')\n",
        "\n",
        "labels.head()"
      ],
      "metadata": {
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          "height": 206
        },
        "id": "BjE-m77ALYFU",
        "outputId": "58a6d22c-d36e-4821-a3c1-52101cff1171"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "  Case ID  Bone Age   Male Location\n",
              "0   1.jpg         0  False    Asian\n",
              "1   2.jpg         0  False    Asian\n",
              "2   3.jpg         0  False    Asian\n",
              "3   4.jpg         0  False    Asian\n",
              "4   5.jpg         0  False    Asian"
            ],
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            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "labels",
              "summary": "{\n  \"name\": \"labels\",\n  \"rows\": 7393,\n  \"fields\": [\n    {\n      \"column\": \"Case ID\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 7393,\n        \"samples\": [\n          \"7270.jpg\",\n          \"6771.jpg\",\n          \"1540.jpg\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Bone Age\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 5,\n        \"min\": 0,\n        \"max\": 18,\n        \"num_unique_values\": 19,\n        \"samples\": [\n          0,\n          5,\n          11\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Male\",\n      \"properties\": {\n        \"dtype\": \"boolean\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          true,\n          false\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"Location\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 4,\n        \"samples\": [\n          \"African American\",\n          \"Hispanic American\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Ensure the 'Case ID' column is of type string\n",
        "labels['Case ID'] = labels['Case ID'].astype(str)"
      ],
      "metadata": {
        "id": "9_eayQOCLZT7"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Create the image data generator\n",
        "datagen = ImageDataGenerator(rescale=1./255, validation_split=0.2)"
      ],
      "metadata": {
        "id": "Z9TlBSNpLa3p"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Create the train and validation generators\n",
        "train_generator = datagen.flow_from_dataframe(\n",
        "    dataframe=labels,\n",
        "    directory='/content/drive/MyDrive/Digital_Hand_Atlas_Dataset/Total_Images/Bordered_XRay_Images',\n",
        "    x_col='Case ID',\n",
        "    y_col='Bone Age',\n",
        "    target_size=(256, 256),\n",
        "    color_mode='rgb',  # Change to 'rgb' for 3 channels\n",
        "    class_mode='raw',\n",
        "    batch_size=32,\n",
        "    subset='training'\n",
        ")\n",
        "\n",
        "validation_generator = datagen.flow_from_dataframe(\n",
        "    dataframe=labels,\n",
        "    directory='/content/drive/MyDrive/Digital_Hand_Atlas_Dataset/Total_Images/Bordered_XRay_Images',\n",
        "    x_col='Case ID',\n",
        "    y_col='Bone Age',\n",
        "    target_size=(256, 256),\n",
        "    color_mode='rgb',  # Change to 'rgb' for 3 channels\n",
        "    class_mode='raw',\n",
        "    batch_size=32,\n",
        "    subset='validation'\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mhOY802eLcFM",
        "outputId": "d14f9723-771a-4958-95a9-5d22d8e8d758"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Found 5915 validated image filenames.\n",
            "Found 1478 validated image filenames.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Load pre-trained ResNet-50\n",
        "base_model = ResNet50(weights='imagenet', include_top=False, input_shape=(256, 256, 3))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ELVEAORFLdcG",
        "outputId": "99ec9a19-fd8e-40ca-b0dc-be5750db1dea"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/resnet/resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5\n",
            "\u001b[1m94765736/94765736\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 0us/step\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Add custom layers for regression\n",
        "x = GlobalAveragePooling2D()(base_model.output)\n",
        "x = Dense(512, activation='relu')(x)\n",
        "x = Dropout(0.5)(x)\n",
        "output_layer = Dense(1, activation='linear')(x)"
      ],
      "metadata": {
        "id": "htZEkh63Len2"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Create the final model\n",
        "model = tf.keras.Model(inputs=base_model.input, outputs=output_layer)"
      ],
      "metadata": {
        "id": "UeqIzspSLf6j"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Compile the model\n",
        "model.compile(optimizer=Adam(), loss='mean_squared_error', metrics=['mae', 'accuracy'])"
      ],
      "metadata": {
        "id": "9quTSVN9LhIC"
      },
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Train the model (use your train_generator and validation_generator)\n",
        "history = model.fit(\n",
        "    train_generator,\n",
        "    steps_per_epoch=train_generator.samples // 32,\n",
        "    validation_data=validation_generator,\n",
        "    validation_steps=validation_generator.samples // 32,\n",
        "    epochs=10\n",
        ")"
      ],
      "metadata": {
        "id": "wZi8kpYZLif4",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "2e56a65f-f573-4c14-8b69-7a06ffacd26e"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/10\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/keras/src/trainers/data_adapters/py_dataset_adapter.py:121: UserWarning: Your `PyDataset` class should call `super().__init__(**kwargs)` in its constructor. `**kwargs` can include `workers`, `use_multiprocessing`, `max_queue_size`. Do not pass these arguments to `fit()`, as they will be ignored.\n",
            "  self._warn_if_super_not_called()\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m2489s\u001b[0m 13s/step - accuracy: 0.0539 - loss: 12.7904 - mae: 2.5045 - val_accuracy: 0.0679 - val_loss: 68.3177 - val_mae: 6.6382\n",
            "Epoch 2/10\n",
            "\u001b[1m  1/184\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m59s\u001b[0m 325ms/step - accuracy: 0.0312 - loss: 2.7102 - mae: 1.3069"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/lib/python3.10/contextlib.py:153: UserWarning: Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least `steps_per_epoch * epochs` batches. You may need to use the `.repeat()` function when building your dataset.\n",
            "  self.gen.throw(typ, value, traceback)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 21ms/step - accuracy: 0.0312 - loss: 2.7102 - mae: 1.3069 - val_accuracy: 0.0000e+00 - val_loss: 90.9200 - val_mae: 7.4820\n",
            "Epoch 3/10\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m263s\u001b[0m 1s/step - accuracy: 0.0620 - loss: 4.0693 - mae: 1.5188 - val_accuracy: 0.0469 - val_loss: 75.8499 - val_mae: 7.1104\n",
            "Epoch 4/10\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m36s\u001b[0m 197ms/step - accuracy: 0.0312 - loss: 6.2082 - mae: 1.9020 - val_accuracy: 0.0000e+00 - val_loss: 82.1226 - val_mae: 8.5275\n",
            "Epoch 5/10\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m277s\u001b[0m 1s/step - accuracy: 0.0663 - loss: 3.2788 - mae: 1.3600 - val_accuracy: 0.0571 - val_loss: 74.9331 - val_mae: 7.1206\n",
            "Epoch 6/10\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 281us/step - accuracy: 0.0938 - loss: 3.0384 - mae: 1.3430 - val_accuracy: 0.1667 - val_loss: 78.4002 - val_mae: 7.2228\n",
            "Epoch 7/10\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m244s\u001b[0m 1s/step - accuracy: 0.0665 - loss: 2.9480 - mae: 1.2846 - val_accuracy: 0.0904 - val_loss: 15.4007 - val_mae: 3.1400\n",
            "Epoch 8/10\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m37s\u001b[0m 201ms/step - accuracy: 0.0625 - loss: 3.1297 - mae: 1.3822 - val_accuracy: 0.0000e+00 - val_loss: 38.3119 - val_mae: 5.4422\n",
            "Epoch 9/10\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m241s\u001b[0m 1s/step - accuracy: 0.0794 - loss: 2.3437 - mae: 1.1460 - val_accuracy: 0.1012 - val_loss: 9.7919 - val_mae: 2.5057\n",
            "Epoch 10/10\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 281us/step - accuracy: 0.0312 - loss: 2.7700 - mae: 1.2541 - val_accuracy: 0.1667 - val_loss: 8.5988 - val_mae: 1.9604\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Plot training & validation MAE values\n",
        "plt.figure(figsize=(18, 4))\n",
        "\n",
        "plt.subplot(1, 3, 1)\n",
        "plt.plot(history.history['mae'])\n",
        "plt.plot(history.history['val_mae'])\n",
        "plt.title('Model MAE')\n",
        "plt.ylabel('MAE')\n",
        "plt.xlabel('Epoch')\n",
        "plt.legend(['Train', 'Validation'], loc='upper left')\n",
        "\n",
        "# Plot training & validation loss values\n",
        "plt.subplot(1, 3, 2)\n",
        "plt.plot(history.history['loss'])\n",
        "plt.plot(history.history['val_loss'])\n",
        "plt.title('Model Loss')\n",
        "plt.ylabel('Loss')\n",
        "plt.xlabel('Epoch')\n",
        "plt.legend(['Train', 'Validation'], loc='upper left')\n",
        "\n",
        "# Plot training & validation accuracy values\n",
        "plt.subplot(1, 3, 3)\n",
        "plt.plot(history.history['accuracy'])\n",
        "plt.plot(history.history['val_accuracy'])\n",
        "plt.title('Model Accuracy')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.legend(['Train', 'Validation'], loc='upper left')\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "_nNFq3NFLk93",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 360
        },
        "outputId": "c7ac8c6c-dba4-413b-c0af-195aa0a3c0eb"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x400 with 3 Axes>"
            ],
            "image/png": 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          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Train the model (use your train_generator and validation_generator)\n",
        "history = model.fit(\n",
        "    train_generator,\n",
        "    steps_per_epoch=train_generator.samples // 32,\n",
        "    validation_data=validation_generator,\n",
        "    validation_steps=validation_generator.samples // 32,\n",
        "    epochs=18\n",
        ")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BELg3o5VLmYc",
        "outputId": "03823b16-1798-4f3f-a31b-1a79b755b20c"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/18\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/keras/src/trainers/data_adapters/py_dataset_adapter.py:121: UserWarning: Your `PyDataset` class should call `super().__init__(**kwargs)` in its constructor. `**kwargs` can include `workers`, `use_multiprocessing`, `max_queue_size`. Do not pass these arguments to `fit()`, as they will be ignored.\n",
            "  self._warn_if_super_not_called()\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m3000s\u001b[0m 15s/step - accuracy: 0.0535 - loss: 13.8494 - mae: 2.6265 - val_accuracy: 0.0632 - val_loss: 77.2965 - val_mae: 7.2056\n",
            "Epoch 2/18\n",
            "\u001b[1m  1/184\u001b[0m \u001b[37m━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[1m1:02\u001b[0m 341ms/step - accuracy: 0.0938 - loss: 1.9068 - mae: 1.1221"
          ]
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/lib/python3.10/contextlib.py:153: UserWarning: Your input ran out of data; interrupting training. Make sure that your dataset or generator can generate at least `steps_per_epoch * epochs` batches. You may need to use the `.repeat()` function when building your dataset.\n",
            "  self.gen.throw(typ, value, traceback)\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\b\r\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m5s\u001b[0m 25ms/step - accuracy: 0.0938 - loss: 1.9068 - mae: 1.1221 - val_accuracy: 0.1667 - val_loss: 37.8134 - val_mae: 5.0612\n",
            "Epoch 3/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m260s\u001b[0m 1s/step - accuracy: 0.0546 - loss: 3.8426 - mae: 1.4674 - val_accuracy: 0.0673 - val_loss: 74.4266 - val_mae: 7.0286\n",
            "Epoch 4/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m30s\u001b[0m 163ms/step - accuracy: 0.0938 - loss: 4.4918 - mae: 1.3821 - val_accuracy: 0.1667 - val_loss: 70.1332 - val_mae: 5.9362\n",
            "Epoch 5/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m259s\u001b[0m 1s/step - accuracy: 0.0675 - loss: 2.9720 - mae: 1.2907 - val_accuracy: 0.0639 - val_loss: 76.4419 - val_mae: 7.2364\n",
            "Epoch 6/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m35s\u001b[0m 190ms/step - accuracy: 0.0625 - loss: 6.4780 - mae: 1.7003 - val_accuracy: 0.1667 - val_loss: 71.5883 - val_mae: 7.0259\n",
            "Epoch 7/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m276s\u001b[0m 1s/step - accuracy: 0.0701 - loss: 2.8270 - mae: 1.2483 - val_accuracy: 0.0747 - val_loss: 16.0074 - val_mae: 3.2214\n",
            "Epoch 8/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 326us/step - accuracy: 0.0625 - loss: 1.0972 - mae: 0.8292 - val_accuracy: 0.0000e+00 - val_loss: 16.6675 - val_mae: 3.4404\n",
            "Epoch 9/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m246s\u001b[0m 1s/step - accuracy: 0.0791 - loss: 2.6237 - mae: 1.1896 - val_accuracy: 0.0849 - val_loss: 10.8324 - val_mae: 2.7388\n",
            "Epoch 10/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m0s\u001b[0m 295us/step - accuracy: 0.0312 - loss: 2.3636 - mae: 1.2209 - val_accuracy: 0.1667 - val_loss: 6.7099 - val_mae: 2.1373\n",
            "Epoch 11/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m252s\u001b[0m 1s/step - accuracy: 0.0733 - loss: 2.4372 - mae: 1.1501 - val_accuracy: 0.0734 - val_loss: 4.8522 - val_mae: 1.6893\n",
            "Epoch 12/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m34s\u001b[0m 183ms/step - accuracy: 0.1562 - loss: 1.8780 - mae: 1.0143 - val_accuracy: 0.0000e+00 - val_loss: 5.3189 - val_mae: 1.8298\n",
            "Epoch 13/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m251s\u001b[0m 1s/step - accuracy: 0.0719 - loss: 2.2563 - mae: 1.1060 - val_accuracy: 0.0679 - val_loss: 5.0001 - val_mae: 1.7654\n",
            "Epoch 14/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m36s\u001b[0m 194ms/step - accuracy: 0.0938 - loss: 3.9199 - mae: 1.4291 - val_accuracy: 0.0000e+00 - val_loss: 3.0387 - val_mae: 1.5001\n",
            "Epoch 15/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m253s\u001b[0m 1s/step - accuracy: 0.0835 - loss: 2.3674 - mae: 1.1334 - val_accuracy: 0.0673 - val_loss: 4.0445 - val_mae: 1.6544\n",
            "Epoch 16/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m35s\u001b[0m 187ms/step - accuracy: 0.0000e+00 - loss: 1.6308 - mae: 0.9136 - val_accuracy: 0.1667 - val_loss: 3.1157 - val_mae: 1.7005\n",
            "Epoch 17/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m279s\u001b[0m 1s/step - accuracy: 0.0803 - loss: 1.9908 - mae: 1.0380 - val_accuracy: 0.0679 - val_loss: 3.1530 - val_mae: 1.4240\n",
            "Epoch 18/18\n",
            "\u001b[1m184/184\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m38s\u001b[0m 204ms/step - accuracy: 0.0938 - loss: 1.0902 - mae: 0.8084 - val_accuracy: 0.0000e+00 - val_loss: 3.5196 - val_mae: 1.2817\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# Plot training & validation MAE values\n",
        "plt.figure(figsize=(18, 4))\n",
        "\n",
        "plt.subplot(1, 3, 1)\n",
        "plt.plot(history.history['mae'])\n",
        "plt.plot(history.history['val_mae'])\n",
        "plt.title('Model MAE')\n",
        "plt.ylabel('MAE')\n",
        "plt.xlabel('Epoch')\n",
        "plt.legend(['Train', 'Validation'], loc='upper left')\n",
        "\n",
        "# Plot training & validation loss values\n",
        "plt.subplot(1, 3, 2)\n",
        "plt.plot(history.history['loss'])\n",
        "plt.plot(history.history['val_loss'])\n",
        "plt.title('Model Loss')\n",
        "plt.ylabel('Loss')\n",
        "plt.xlabel('Epoch')\n",
        "plt.legend(['Train', 'Validation'], loc='upper left')\n",
        "\n",
        "# Plot training & validation accuracy values\n",
        "plt.subplot(1, 3, 3)\n",
        "plt.plot(history.history['accuracy'])\n",
        "plt.plot(history.history['val_accuracy'])\n",
        "plt.title('Model Accuracy')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.legend(['Train', 'Validation'], loc='upper left')\n",
        "\n",
        "plt.tight_layout()\n",
        "plt.show()"
      ],
      "metadata": {
        "id": "DweN0Io7LnCV",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 361
        },
        "outputId": "be8a48b9-e707-4c8f-9c45-87dd9ab1bba9"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 1800x400 with 3 Axes>"
            ],
            "image/png": 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\n"
          },
          "metadata": {}
        }
      ]
    }
  ]
}