17flowers.ipynb

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        "outputId": "fe25db52-2fb8-4e51-d38d-8f5631fcc85e"
      },
      "source": [
        "!pip install wandb\n",
        "import tensorflow as tf\n",
        "from tensorflow.keras.preprocessing.image import ImageDataGenerator\n",
        "import numpy as np\n",
        "from tensorflow.keras.layers import Dense,MaxPool2D,Flatten,Conv2D\n",
        "import os\n",
        "from tensorflow.keras import layers\n",
        "from wandb.keras import WandbCallback\n",
        "import wandb\n",
        "from sklearn.metrics import classification_report, confusion_matrix"
      ],
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: wandb in /usr/local/lib/python3.7/dist-packages (0.12.4)\n",
            "Requirement already satisfied: six>=1.13.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (1.15.0)\n",
            "Requirement already satisfied: psutil>=5.0.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (5.4.8)\n",
            "Requirement already satisfied: subprocess32>=3.5.3 in /usr/local/lib/python3.7/dist-packages (from wandb) (3.5.4)\n",
            "Requirement already satisfied: docker-pycreds>=0.4.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (0.4.0)\n",
            "Requirement already satisfied: yaspin>=1.0.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (2.1.0)\n",
            "Requirement already satisfied: requests<3,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (2.23.0)\n",
            "Requirement already satisfied: sentry-sdk>=1.0.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (1.4.3)\n",
            "Requirement already satisfied: pathtools in /usr/local/lib/python3.7/dist-packages (from wandb) (0.1.2)\n",
            "Requirement already satisfied: python-dateutil>=2.6.1 in /usr/local/lib/python3.7/dist-packages (from wandb) (2.8.2)\n",
            "Requirement already satisfied: shortuuid>=0.5.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (1.0.1)\n",
            "Requirement already satisfied: Click!=8.0.0,>=7.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (7.1.2)\n",
            "Requirement already satisfied: protobuf>=3.12.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (3.17.3)\n",
            "Requirement already satisfied: promise<3,>=2.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (2.3)\n",
            "Requirement already satisfied: GitPython>=1.0.0 in /usr/local/lib/python3.7/dist-packages (from wandb) (3.1.24)\n",
            "Requirement already satisfied: PyYAML in /usr/local/lib/python3.7/dist-packages (from wandb) (3.13)\n",
            "Requirement already satisfied: configparser>=3.8.1 in /usr/local/lib/python3.7/dist-packages (from wandb) (5.0.2)\n",
            "Requirement already satisfied: gitdb<5,>=4.0.1 in /usr/local/lib/python3.7/dist-packages (from GitPython>=1.0.0->wandb) (4.0.7)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.7/dist-packages (from GitPython>=1.0.0->wandb) (3.7.4.3)\n",
            "Requirement already satisfied: smmap<5,>=3.0.1 in /usr/local/lib/python3.7/dist-packages (from gitdb<5,>=4.0.1->GitPython>=1.0.0->wandb) (4.0.0)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.0.0->wandb) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.0.0->wandb) (2.10)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.0.0->wandb) (3.0.4)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests<3,>=2.0.0->wandb) (2021.5.30)\n",
            "Requirement already satisfied: termcolor<2.0.0,>=1.1.0 in /usr/local/lib/python3.7/dist-packages (from yaspin>=1.0.0->wandb) (1.1.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7myJFO0mln2f"
      },
      "source": [
        "dataset_train='/content/drive/MyDrive/Flowers/Train'\n",
        "dataset_test='/content/drive/MyDrive/Flowers/Test'\n",
        "width=height=224\n",
        "batch_size=32"
      ],
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qSy9BCymmEjb"
      },
      "source": [
        "data_generator=ImageDataGenerator(\n",
        "rescale=1./255,\n",
        "horizontal_flip=True,\n",
        "rotation_range=20,\n",
        "zoom_range=0.1,\n",
        "validation_split=0.2,\n",
        ")\n"
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "b6jLCrldtT3p"
      },
      "source": [
        ""
      ],
      "execution_count": 24,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TbG9Y2OjnhtB",
        "outputId": "ac359c3c-21a3-423a-b172-7450a92362ee"
      },
      "source": [
        "train_data=data_generator.flow_from_directory(\n",
        "    dataset_train,\n",
        "    target_size=(width,height),\n",
        "    class_mode='categorical',\n",
        "    batch_size=batch_size,\n",
        "    shuffle=True,\n",
        "    subset='training'\n",
        ")\n",
        "val_data=data_generator.flow_from_directory(\n",
        "    dataset_train,\n",
        "    target_size=(width,height),\n",
        "    class_mode='categorical',\n",
        "    batch_size=batch_size,\n",
        "    shuffle=True,\n",
        "    subset='validation'\n",
        ")\n",
        "test_data=data_generator.flow_from_directory(\n",
        "    dataset_test,\n",
        "    target_size=(width,height),\n",
        "    class_mode='categorical',\n",
        "    batch_size=batch_size,\n",
        "    shuffle=True,\n",
        "  \n",
        ")"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Found 884 images belonging to 17 classes.\n",
            "Found 204 images belonging to 17 classes.\n",
            "Found 272 images belonging to 17 classes.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JhpYCtD0mEwV"
      },
      "source": [
        "base_model = tf.keras.applications.ResNet50V2(\n",
        "    input_shape=(width, height, 3),\n",
        "    include_top = False,\n",
        "    weights = 'imagenet',\n",
        "    pooling = 'max'\n",
        "    )"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s0PHEyCSmE37",
        "outputId": "bf3bfce3-5d59-4352-8b62-9709bc07b294"
      },
      "source": [
        "base_model.summary()"
      ],
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Model: \"resnet50v2\"\n",
            "__________________________________________________________________________________________________\n",
            "Layer (type)                    Output Shape         Param #     Connected to                     \n",
            "==================================================================================================\n",
            "input_3 (InputLayer)            [(None, 224, 224, 3) 0                                            \n",
            "__________________________________________________________________________________________________\n",
            "conv1_pad (ZeroPadding2D)       (None, 230, 230, 3)  0           input_3[0][0]                    \n",
            "__________________________________________________________________________________________________\n",
            "conv1_conv (Conv2D)             (None, 112, 112, 64) 9472        conv1_pad[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "pool1_pad (ZeroPadding2D)       (None, 114, 114, 64) 0           conv1_conv[0][0]                 \n",
            "__________________________________________________________________________________________________\n",
            "pool1_pool (MaxPooling2D)       (None, 56, 56, 64)   0           pool1_pad[0][0]                  \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_preact_bn (BatchNo (None, 56, 56, 64)   256         pool1_pool[0][0]                 \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_preact_relu (Activ (None, 56, 56, 64)   0           conv2_block1_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_1_conv (Conv2D)    (None, 56, 56, 64)   4096        conv2_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_1_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block1_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_1_relu (Activation (None, 56, 56, 64)   0           conv2_block1_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_2_pad (ZeroPadding (None, 58, 58, 64)   0           conv2_block1_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_2_conv (Conv2D)    (None, 56, 56, 64)   36864       conv2_block1_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_2_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block1_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_2_relu (Activation (None, 56, 56, 64)   0           conv2_block1_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_0_conv (Conv2D)    (None, 56, 56, 256)  16640       conv2_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_3_conv (Conv2D)    (None, 56, 56, 256)  16640       conv2_block1_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block1_out (Add)          (None, 56, 56, 256)  0           conv2_block1_0_conv[0][0]        \n",
            "                                                                 conv2_block1_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_preact_bn (BatchNo (None, 56, 56, 256)  1024        conv2_block1_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_preact_relu (Activ (None, 56, 56, 256)  0           conv2_block2_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_1_conv (Conv2D)    (None, 56, 56, 64)   16384       conv2_block2_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_1_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block2_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_1_relu (Activation (None, 56, 56, 64)   0           conv2_block2_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_2_pad (ZeroPadding (None, 58, 58, 64)   0           conv2_block2_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_2_conv (Conv2D)    (None, 56, 56, 64)   36864       conv2_block2_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_2_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block2_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_2_relu (Activation (None, 56, 56, 64)   0           conv2_block2_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_3_conv (Conv2D)    (None, 56, 56, 256)  16640       conv2_block2_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block2_out (Add)          (None, 56, 56, 256)  0           conv2_block1_out[0][0]           \n",
            "                                                                 conv2_block2_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_preact_bn (BatchNo (None, 56, 56, 256)  1024        conv2_block2_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_preact_relu (Activ (None, 56, 56, 256)  0           conv2_block3_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_1_conv (Conv2D)    (None, 56, 56, 64)   16384       conv2_block3_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_1_bn (BatchNormali (None, 56, 56, 64)   256         conv2_block3_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_1_relu (Activation (None, 56, 56, 64)   0           conv2_block3_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_2_pad (ZeroPadding (None, 58, 58, 64)   0           conv2_block3_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_2_conv (Conv2D)    (None, 28, 28, 64)   36864       conv2_block3_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_2_bn (BatchNormali (None, 28, 28, 64)   256         conv2_block3_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_2_relu (Activation (None, 28, 28, 64)   0           conv2_block3_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "max_pooling2d_6 (MaxPooling2D)  (None, 28, 28, 256)  0           conv2_block2_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_3_conv (Conv2D)    (None, 28, 28, 256)  16640       conv2_block3_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv2_block3_out (Add)          (None, 28, 28, 256)  0           max_pooling2d_6[0][0]            \n",
            "                                                                 conv2_block3_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_preact_bn (BatchNo (None, 28, 28, 256)  1024        conv2_block3_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_preact_relu (Activ (None, 28, 28, 256)  0           conv3_block1_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_1_conv (Conv2D)    (None, 28, 28, 128)  32768       conv3_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block1_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_1_relu (Activation (None, 28, 28, 128)  0           conv3_block1_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block1_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block1_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block1_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_2_relu (Activation (None, 28, 28, 128)  0           conv3_block1_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_0_conv (Conv2D)    (None, 28, 28, 512)  131584      conv3_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block1_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block1_out (Add)          (None, 28, 28, 512)  0           conv3_block1_0_conv[0][0]        \n",
            "                                                                 conv3_block1_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block1_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block2_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block2_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block2_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_1_relu (Activation (None, 28, 28, 128)  0           conv3_block2_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block2_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block2_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block2_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_2_relu (Activation (None, 28, 28, 128)  0           conv3_block2_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block2_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block2_out (Add)          (None, 28, 28, 512)  0           conv3_block1_out[0][0]           \n",
            "                                                                 conv3_block2_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block2_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block3_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block3_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block3_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_1_relu (Activation (None, 28, 28, 128)  0           conv3_block3_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block3_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_2_conv (Conv2D)    (None, 28, 28, 128)  147456      conv3_block3_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_2_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block3_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_2_relu (Activation (None, 28, 28, 128)  0           conv3_block3_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_3_conv (Conv2D)    (None, 28, 28, 512)  66048       conv3_block3_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block3_out (Add)          (None, 28, 28, 512)  0           conv3_block2_out[0][0]           \n",
            "                                                                 conv3_block3_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_preact_bn (BatchNo (None, 28, 28, 512)  2048        conv3_block3_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_preact_relu (Activ (None, 28, 28, 512)  0           conv3_block4_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_1_conv (Conv2D)    (None, 28, 28, 128)  65536       conv3_block4_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_1_bn (BatchNormali (None, 28, 28, 128)  512         conv3_block4_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_1_relu (Activation (None, 28, 28, 128)  0           conv3_block4_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_2_pad (ZeroPadding (None, 30, 30, 128)  0           conv3_block4_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_2_conv (Conv2D)    (None, 14, 14, 128)  147456      conv3_block4_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_2_bn (BatchNormali (None, 14, 14, 128)  512         conv3_block4_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_2_relu (Activation (None, 14, 14, 128)  0           conv3_block4_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "max_pooling2d_7 (MaxPooling2D)  (None, 14, 14, 512)  0           conv3_block3_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_3_conv (Conv2D)    (None, 14, 14, 512)  66048       conv3_block4_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv3_block4_out (Add)          (None, 14, 14, 512)  0           max_pooling2d_7[0][0]            \n",
            "                                                                 conv3_block4_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_preact_bn (BatchNo (None, 14, 14, 512)  2048        conv3_block4_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_preact_relu (Activ (None, 14, 14, 512)  0           conv4_block1_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_1_conv (Conv2D)    (None, 14, 14, 256)  131072      conv4_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block1_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_1_relu (Activation (None, 14, 14, 256)  0           conv4_block1_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block1_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block1_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block1_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_2_relu (Activation (None, 14, 14, 256)  0           conv4_block1_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_0_conv (Conv2D)    (None, 14, 14, 1024) 525312      conv4_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block1_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block1_out (Add)          (None, 14, 14, 1024) 0           conv4_block1_0_conv[0][0]        \n",
            "                                                                 conv4_block1_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block1_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block2_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block2_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block2_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_1_relu (Activation (None, 14, 14, 256)  0           conv4_block2_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block2_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block2_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block2_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_2_relu (Activation (None, 14, 14, 256)  0           conv4_block2_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block2_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block2_out (Add)          (None, 14, 14, 1024) 0           conv4_block1_out[0][0]           \n",
            "                                                                 conv4_block2_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block2_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block3_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block3_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block3_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_1_relu (Activation (None, 14, 14, 256)  0           conv4_block3_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block3_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block3_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block3_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_2_relu (Activation (None, 14, 14, 256)  0           conv4_block3_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block3_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block3_out (Add)          (None, 14, 14, 1024) 0           conv4_block2_out[0][0]           \n",
            "                                                                 conv4_block3_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block3_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block4_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block4_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block4_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_1_relu (Activation (None, 14, 14, 256)  0           conv4_block4_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block4_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block4_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block4_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_2_relu (Activation (None, 14, 14, 256)  0           conv4_block4_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block4_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block4_out (Add)          (None, 14, 14, 1024) 0           conv4_block3_out[0][0]           \n",
            "                                                                 conv4_block4_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block4_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block5_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block5_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block5_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_1_relu (Activation (None, 14, 14, 256)  0           conv4_block5_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block5_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_2_conv (Conv2D)    (None, 14, 14, 256)  589824      conv4_block5_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_2_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block5_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_2_relu (Activation (None, 14, 14, 256)  0           conv4_block5_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_3_conv (Conv2D)    (None, 14, 14, 1024) 263168      conv4_block5_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block5_out (Add)          (None, 14, 14, 1024) 0           conv4_block4_out[0][0]           \n",
            "                                                                 conv4_block5_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_preact_bn (BatchNo (None, 14, 14, 1024) 4096        conv4_block5_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_preact_relu (Activ (None, 14, 14, 1024) 0           conv4_block6_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_1_conv (Conv2D)    (None, 14, 14, 256)  262144      conv4_block6_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_1_bn (BatchNormali (None, 14, 14, 256)  1024        conv4_block6_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_1_relu (Activation (None, 14, 14, 256)  0           conv4_block6_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_2_pad (ZeroPadding (None, 16, 16, 256)  0           conv4_block6_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_2_conv (Conv2D)    (None, 7, 7, 256)    589824      conv4_block6_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_2_bn (BatchNormali (None, 7, 7, 256)    1024        conv4_block6_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_2_relu (Activation (None, 7, 7, 256)    0           conv4_block6_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "max_pooling2d_8 (MaxPooling2D)  (None, 7, 7, 1024)   0           conv4_block5_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_3_conv (Conv2D)    (None, 7, 7, 1024)   263168      conv4_block6_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv4_block6_out (Add)          (None, 7, 7, 1024)   0           max_pooling2d_8[0][0]            \n",
            "                                                                 conv4_block6_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_preact_bn (BatchNo (None, 7, 7, 1024)   4096        conv4_block6_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_preact_relu (Activ (None, 7, 7, 1024)   0           conv5_block1_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_1_conv (Conv2D)    (None, 7, 7, 512)    524288      conv5_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_1_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block1_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_1_relu (Activation (None, 7, 7, 512)    0           conv5_block1_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_2_pad (ZeroPadding (None, 9, 9, 512)    0           conv5_block1_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_2_conv (Conv2D)    (None, 7, 7, 512)    2359296     conv5_block1_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_2_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block1_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_2_relu (Activation (None, 7, 7, 512)    0           conv5_block1_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_0_conv (Conv2D)    (None, 7, 7, 2048)   2099200     conv5_block1_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_3_conv (Conv2D)    (None, 7, 7, 2048)   1050624     conv5_block1_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block1_out (Add)          (None, 7, 7, 2048)   0           conv5_block1_0_conv[0][0]        \n",
            "                                                                 conv5_block1_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_preact_bn (BatchNo (None, 7, 7, 2048)   8192        conv5_block1_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_preact_relu (Activ (None, 7, 7, 2048)   0           conv5_block2_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_1_conv (Conv2D)    (None, 7, 7, 512)    1048576     conv5_block2_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_1_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block2_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_1_relu (Activation (None, 7, 7, 512)    0           conv5_block2_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_2_pad (ZeroPadding (None, 9, 9, 512)    0           conv5_block2_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_2_conv (Conv2D)    (None, 7, 7, 512)    2359296     conv5_block2_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_2_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block2_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_2_relu (Activation (None, 7, 7, 512)    0           conv5_block2_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_3_conv (Conv2D)    (None, 7, 7, 2048)   1050624     conv5_block2_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block2_out (Add)          (None, 7, 7, 2048)   0           conv5_block1_out[0][0]           \n",
            "                                                                 conv5_block2_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_preact_bn (BatchNo (None, 7, 7, 2048)   8192        conv5_block2_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_preact_relu (Activ (None, 7, 7, 2048)   0           conv5_block3_preact_bn[0][0]     \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_1_conv (Conv2D)    (None, 7, 7, 512)    1048576     conv5_block3_preact_relu[0][0]   \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_1_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block3_1_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_1_relu (Activation (None, 7, 7, 512)    0           conv5_block3_1_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_2_pad (ZeroPadding (None, 9, 9, 512)    0           conv5_block3_1_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_2_conv (Conv2D)    (None, 7, 7, 512)    2359296     conv5_block3_2_pad[0][0]         \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_2_bn (BatchNormali (None, 7, 7, 512)    2048        conv5_block3_2_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_2_relu (Activation (None, 7, 7, 512)    0           conv5_block3_2_bn[0][0]          \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_3_conv (Conv2D)    (None, 7, 7, 2048)   1050624     conv5_block3_2_relu[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "conv5_block3_out (Add)          (None, 7, 7, 2048)   0           conv5_block2_out[0][0]           \n",
            "                                                                 conv5_block3_3_conv[0][0]        \n",
            "__________________________________________________________________________________________________\n",
            "post_bn (BatchNormalization)    (None, 7, 7, 2048)   8192        conv5_block3_out[0][0]           \n",
            "__________________________________________________________________________________________________\n",
            "post_relu (Activation)          (None, 7, 7, 2048)   0           post_bn[0][0]                    \n",
            "__________________________________________________________________________________________________\n",
            "max_pool (GlobalMaxPooling2D)   (None, 2048)         0           post_relu[0][0]                  \n",
            "==================================================================================================\n",
            "Total params: 23,564,800\n",
            "Trainable params: 23,519,360\n",
            "Non-trainable params: 45,440\n",
            "__________________________________________________________________________________________________\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IfjiV1a5mE5W"
      },
      "source": [
        "for layer in base_model.layers[:-8]:\n",
        "  layer.trainable=False"
      ],
      "execution_count": 28,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5UmBZVBomE_j"
      },
      "source": [
        "model = tf.keras.Sequential([\n",
        "        base_model,\n",
        "        Flatten(),\n",
        "        layers.Dense(128, activation='relu'),\n",
        "        layers.Dense(32, activation='relu'),\n",
        "        layers.BatchNormalization(),\n",
        "        layers.Dense(17, activation='sigmoid'),              \n",
        "])"
      ],
      "execution_count": 29,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 199,
          "referenced_widgets": [
            "6b92ddcae10145969be510356fcf6c49",
            "0998b2212af945dfae8c23221d3a24d1",
            "70a3de6bf94941dd8ec3e84d9912de22",
            "a13923ecb9d24c95a7b281e373545941",
            "c9143a065c7f47958744fc6745ed1efa",
            "8f099047cb6345328f0ed364a40365dd",
            "030752fb9fff4b57bb8b871f19e67532",
            "16350b78844b4e7187f0fecfe92134af"
          ]
        },
        "id": "h_Bm0fVuqyB-",
        "outputId": "a0e3e0ac-8b41-4c22-c14a-c312ea5af3d0"
      },
      "source": [
        "wandb.init(project=\"17flowers\")"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Finishing last run (ID:1ikj75iy) before initializing another..."
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            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<br/>Waiting for W&B process to finish, PID 361... <strong style=\"color:green\">(success).</strong>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
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          },
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        },
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              "VBox(children=(Label(value=' 0.00MB of 0.00MB uploaded (0.00MB deduped)\\r'), FloatProgress(value=1.0, max=1.0)…"
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          },
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        {
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            "text/html": [
              "<style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
              "    .wandb-row { display: flex; flex-direction: row; flex-wrap: wrap; width: 100% }\n",
              "    .wandb-col { display: flex; flex-direction: column; flex-basis: 100%; flex: 1; padding: 10px; }\n",
              "    </style>\n",
              "<div class=\"wandb-row\"><div class=\"wandb-col\">\n",
              "</div><div class=\"wandb-col\">\n",
              "</div></div>\n",
              "Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)\n",
              "<br/>Synced <strong style=\"color:#cdcd00\">distinctive-butterfly-12</strong>: <a href=\"https://wandb.ai/zeinabmostafavi/17flowers/runs/1ikj75iy\" target=\"_blank\">https://wandb.ai/zeinabmostafavi/17flowers/runs/1ikj75iy</a><br/>\n",
              "Find logs at: <code>./wandb/run-20211019_144311-1ikj75iy/logs</code><br/>\n"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
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        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Successfully finished last run (ID:1ikj75iy). Initializing new run:<br/>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "                    Syncing run <strong><a href=\"https://wandb.ai/zeinabmostafavi/17flowers/runs/3kqbvkpu\" target=\"_blank\">lucky-monkey-13</a></strong> to <a href=\"https://wandb.ai/zeinabmostafavi/17flowers\" target=\"_blank\">Weights & Biases</a> (<a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">docs</a>).<br/>\n",
              "\n",
              "                "
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              "<IPython.core.display.HTML object>"
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        {
          "output_type": "execute_result",
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              "<wandb.sdk.wandb_run.Run at 0x7f76218cd650>"
            ],
            "text/html": [
              "<button onClick=\"this.nextSibling.style.display='block';this.style.display='none';\">Display W&B run</button><iframe src=\"https://wandb.ai/zeinabmostafavi/17flowers/runs/3kqbvkpu?jupyter=true\" style=\"border:none;width:100%;height:420px;display:none;\"></iframe>"
            ]
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "znNDtC_cljTA"
      },
      "source": [
        "config = wandb.config\n",
        "config.learning_rate = 0.001\n",
        "model.compile(\n",
        "    loss=tf.keras.losses.categorical_crossentropy,optimizer=tf.keras.optimizers.Adam(learning_rate=config.learning_rate),\n",
        "    metrics=['accuracy']\n",
        ")"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EjUJANfNrnsk",
        "outputId": "1d1a9158-9ec6-40b5-c2cd-510bab662330"
      },
      "source": [
        "model.fit(train_data,\n",
        "          steps_per_epoch = train_data.samples / batch_size,\n",
        "          validation_data = val_data,\n",
        "          validation_steps = val_data.samples / batch_size,\n",
        "          epochs = 10\n",
        ")\n",
        "\n"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Epoch 1/10\n",
            "27/27 [==============================] - 26s 803ms/step - loss: 1.4763 - accuracy: 0.6052 - val_loss: 1.7119 - val_accuracy: 0.6471\n",
            "Epoch 2/10\n",
            "27/27 [==============================] - 21s 743ms/step - loss: 0.6271 - accuracy: 0.9163 - val_loss: 0.8988 - val_accuracy: 0.7304\n",
            "Epoch 3/10\n",
            "27/27 [==============================] - 20s 733ms/step - loss: 0.3510 - accuracy: 0.9695 - val_loss: 0.4241 - val_accuracy: 0.8725\n",
            "Epoch 4/10\n",
            "27/27 [==============================] - 21s 743ms/step - loss: 0.2090 - accuracy: 0.9887 - val_loss: 0.8842 - val_accuracy: 0.7843\n",
            "Epoch 5/10\n",
            "27/27 [==============================] - 21s 743ms/step - loss: 0.1655 - accuracy: 0.9910 - val_loss: 0.3559 - val_accuracy: 0.9118\n",
            "Epoch 6/10\n",
            "27/27 [==============================] - 21s 744ms/step - loss: 0.1152 - accuracy: 0.9966 - val_loss: 0.2355 - val_accuracy: 0.9363\n",
            "Epoch 7/10\n",
            "27/27 [==============================] - 21s 752ms/step - loss: 0.0853 - accuracy: 0.9955 - val_loss: 0.2480 - val_accuracy: 0.9559\n",
            "Epoch 8/10\n",
            "27/27 [==============================] - 21s 746ms/step - loss: 0.0678 - accuracy: 0.9977 - val_loss: 0.2281 - val_accuracy: 0.9363\n",
            "Epoch 9/10\n",
            "27/27 [==============================] - 21s 745ms/step - loss: 0.0505 - accuracy: 1.0000 - val_loss: 0.2131 - val_accuracy: 0.9510\n",
            "Epoch 10/10\n",
            "27/27 [==============================] - 20s 739ms/step - loss: 0.0443 - accuracy: 0.9989 - val_loss: 0.2691 - val_accuracy: 0.9412\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<keras.callbacks.History at 0x7f75ab2c7a90>"
            ]
          },
          "metadata": {},
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BExp_y2Yrn5S",
        "outputId": "f5607cd5-183e-4484-98ea-70bcdcc4d051"
      },
      "source": [
        "model.evaluate(test_data)"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "9/9 [==============================] - 5s 563ms/step - loss: 0.5059 - accuracy: 0.8493\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.5058785676956177, 0.8492646813392639]"
            ]
          },
          "metadata": {},
          "execution_count": 33
        }
      ]
    }
  ]
}