A2_Q3_MobileNetV2_finetuning.ipynb

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      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/mehrotrasan16/Keras-Deep-Learning/blob/02-horsesvhumans-MobileNetV2-7254-TransferLearning/A2_Q3_MobileNetV2_finetuning.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
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      "cell_type": "markdown",
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      "source": [
        "# Imports"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ePCGXBMqMQK7"
      },
      "source": [
        "import matplotlib.pyplot as plt\n",
        "import tensorflow as tf\n",
        "import tensorflow_datasets as tfds\n",
        "from tensorflow import keras"
      ],
      "execution_count": 1,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "p90uP1KLpEDZ"
      },
      "source": [
        "# Loading and Preprocessing the Data"
      ]
    },
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      },
      "source": [
        "(raw_data, raw_validation,raw_test), metadata = tfds.load(\n",
        "    'horses_or_humans',\n",
        "    split=['train[:80%]','train[80%:90%]','train[90%:]'],\n",
        "    with_info=True,\n",
        "    as_supervised=True\n",
        ")  "
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[1mDownloading and preparing dataset horses_or_humans/3.0.0 (download: 153.59 MiB, generated: Unknown size, total: 153.59 MiB) to /root/tensorflow_datasets/horses_or_humans/3.0.0...\u001b[0m\n"
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          },
          "metadata": {
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        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/urllib3/connectionpool.py:847: InsecureRequestWarning: Unverified HTTPS request is being made. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#ssl-warnings\n",
            "  InsecureRequestWarning)\n",
            "/usr/local/lib/python3.6/dist-packages/urllib3/connectionpool.py:847: InsecureRequestWarning: Unverified HTTPS request is being made. Adding certificate verification is strongly advised. See: https://urllib3.readthedocs.io/en/latest/advanced-usage.html#ssl-warnings\n",
            "  InsecureRequestWarning)\n"
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        },
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            "\n",
            "\n",
            "\n",
            "\n"
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          "name": "stdout"
        },
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        {
          "output_type": "stream",
          "text": [
            "\rShuffling and writing examples to /root/tensorflow_datasets/horses_or_humans/3.0.0.incompleteGRDC6L/horses_or_humans-train.tfrecord\n"
          ],
          "name": "stdout"
        },
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          "text": [
            "Shuffling and writing examples to /root/tensorflow_datasets/horses_or_humans/3.0.0.incompleteGRDC6L/horses_or_humans-test.tfrecord\n"
          ],
          "name": "stdout"
        },
        {
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        {
          "output_type": "stream",
          "text": [
            "\u001b[1mDataset horses_or_humans downloaded and prepared to /root/tensorflow_datasets/horses_or_humans/3.0.0. Subsequent calls will reuse this data.\u001b[0m\n"
          ],
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        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1kMwlxpKKTiO",
        "outputId": "2d25ea64-5914-48dc-b061-bf4b79a4315f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 54
        }
      },
      "source": [
        "print(raw_data,raw_validation,raw_test)"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "<DatasetV1Adapter shapes: ((300, 300, 3), ()), types: (tf.uint8, tf.int64)> <DatasetV1Adapter shapes: ((300, 300, 3), ()), types: (tf.uint8, tf.int64)> <DatasetV1Adapter shapes: ((300, 300, 3), ()), types: (tf.uint8, tf.int64)>\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "niWGT8GkLZmE"
      },
      "source": [
        "get_label_name = metadata.features['label'].int2str"
      ],
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "B28kxnT-MCra",
        "outputId": "b7569068-8940-4a82-cd74-37e323271f17",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        }
      },
      "source": [
        "for image,label in raw_data.shuffle(1024).take(2):\n",
        "    plt.figure()\n",
        "    plt.imshow(image)\n",
        "    plt.title(get_label_name(label))"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yvIAVVTCMkrs"
      },
      "source": [
        "IMG_SIZE=160\n",
        "\n",
        "def format_example(image,label):\n",
        "    image=tf.cast(image,tf.float32)\n",
        "    #normalizing the values\n",
        "    image=(image/127.5) - 1\n",
        "    #scaling the image\n",
        "    image=tf.image.resize(image,(IMG_SIZE,IMG_SIZE))\n",
        "    return image,label"
      ],
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RV2NCkyVZE8R"
      },
      "source": [
        "train = raw_data.map(format_example)\n",
        "validation=raw_validation.map(format_example)\n",
        "test=raw_test.map(format_example)"
      ],
      "execution_count": 7,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RXLYQi3FiYO4",
        "outputId": "04883448-5192-4fb9-a1b4-02f7fff0901f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "validation,test"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(<DatasetV1Adapter shapes: ((160, 160, 3), ()), types: (tf.float32, tf.int64)>,\n",
              " <DatasetV1Adapter shapes: ((160, 160, 3), ()), types: (tf.float32, tf.int64)>)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9UJOhqNKGDte"
      },
      "source": [
        "# Batching the Data\""
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Dzd-zNQGZMij",
        "outputId": "fbdba036-69d1-4a5c-8b08-807dce121563",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "BATCH_SIZE=32\n",
        "SHUFFLE_BUFFER_SIZE=1000\n",
        "\n",
        "train_batches = train.shuffle(SHUFFLE_BUFFER_SIZE).batch(BATCH_SIZE)\n",
        "validation_batches=validation.batch(BATCH_SIZE)\n",
        "test_batches=test.batch(BATCH_SIZE)\n",
        "\n",
        "for image_batch,label_batch in train_batches.take(1):\n",
        "    pass\n",
        "image_batch.shape"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "TensorShape([32, 160, 160, 3])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xwdA2iM9GINP"
      },
      "source": [
        "# Loading the MobileNetV2 Model"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kz2gjU_KbGnr",
        "outputId": "4a3ff40c-cb86-4a7a-e73b-40cc5de503f2",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 68
        }
      },
      "source": [
        "IMG_SHAPE=(IMG_SIZE,IMG_SIZE,3)\n",
        "\n",
        "base_model=tf.keras.applications.MobileNetV2(input_shape=IMG_SHAPE,include_top=False,weights='imagenet')\n",
        "feature_batch=base_model(image_batch)\n",
        "print(feature_batch.shape)"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/mobilenet_v2/mobilenet_v2_weights_tf_dim_ordering_tf_kernels_1.0_160_no_top.h5\n",
            "9412608/9406464 [==============================] - 0s 0us/step\n",
            "(32, 5, 5, 1280)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nt4ossnLGPiG"
      },
      "source": [
        "base_model.trainable=False"
      ],
      "execution_count": 11,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "P8uGCdFZb0S6",
        "outputId": "df23f225-deac-4946-f10c-ffbe0db18474",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "global_average_layer=tf.keras.layers.GlobalAveragePooling2D()\n",
        "feature_batch_average=global_average_layer(feature_batch)\n",
        "print(feature_batch_average.shape)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(32, 1280)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LlFxgPtocZ7S",
        "outputId": "5557ff87-a132-4ce1-937e-4e269377b15e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "prediction_layer = keras.layers.Dense(1)\n",
        "prediction_batch=prediction_layer(feature_batch_average)\n",
        "print(prediction_batch.shape)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(32, 1)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NFcFtoEacqKP"
      },
      "source": [
        "model=keras.Sequential([\n",
        "                        base_model,\n",
        "                        global_average_layer,\n",
        "                        prediction_layer\n",
        "])"
      ],
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pdEDO6Hqc8Sd"
      },
      "source": [
        "base_learning_rate=0.00001\n",
        "model.compile(\n",
        "    optimizer=keras.optimizers.RMSprop(lr=base_learning_rate),\n",
        "    loss=keras.losses.BinaryCrossentropy(from_logits=True),\n",
        "    metrics='accuracy'\n",
        ")"
      ],
      "execution_count": 30,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NJjNzXBzdYi2",
        "outputId": "e967bc24-7549-499e-b4d1-d1a8ad76550b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        }
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "mobilenetv2_1.00_160 (Functi (None, 5, 5, 1280)        2257984   \n",
            "_________________________________________________________________\n",
            "global_average_pooling2d (Gl (None, 1280)              0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 1)                 1281      \n",
            "=================================================================\n",
            "Total params: 2,259,265\n",
            "Trainable params: 1,281\n",
            "Non-trainable params: 2,257,984\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ebYVFlTfGUPi"
      },
      "source": [
        "## Initial Shallow Training"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QQX3DIJKekof"
      },
      "source": [
        "checkpoint_filepath='weights.{epoch:02d}-{val_loss:.2f}.hdf5'\n",
        "model_checkpoint_callback = tf.keras.callbacks.ModelCheckpoint(\n",
        "    filepath=checkpoint_filepath,\n",
        "    save_weights_only=True,\n",
        "    monitor='val_acc',\n",
        "    mode='max',\n",
        "    save_best_only=True)"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jvTLtqnSdauo",
        "outputId": "5bcd9d66-19f4-4cc3-9fbc-aa7a7b77561f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 697
        }
      },
      "source": [
        "initial_epochs=10\n",
        "history = model.fit(\n",
        "    train_batches,\n",
        "    epochs=initial_epochs,\n",
        "    validation_data=validation_batches,\n",
        "    callbacks=[model_checkpoint_callback]\n",
        ")"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/10\n",
            "     26/Unknown - 14s 557ms/step - loss: 0.6994 - accuracy: 0.5304WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "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\r26/26 [==============================] - 18s 684ms/step - loss: 0.6994 - accuracy: 0.5304 - val_loss: 0.7352 - val_accuracy: 0.6275\n",
            "Epoch 2/10\n",
            "26/26 [==============================] - ETA: 0s - loss: 0.6782 - accuracy: 0.5438WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "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\r26/26 [==============================] - 17s 660ms/step - loss: 0.6782 - accuracy: 0.5438 - val_loss: 0.7174 - val_accuracy: 0.6275\n",
            "Epoch 3/10\n",
            "26/26 [==============================] - ETA: 0s - loss: 0.6596 - accuracy: 0.5657WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "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\r26/26 [==============================] - 17s 656ms/step - loss: 0.6596 - accuracy: 0.5657 - val_loss: 0.7001 - val_accuracy: 0.6373\n",
            "Epoch 4/10\n",
            "26/26 [==============================] - ETA: 0s - loss: 0.6412 - accuracy: 0.5900WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "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\r26/26 [==============================] - 17s 655ms/step - loss: 0.6412 - accuracy: 0.5900 - val_loss: 0.6834 - val_accuracy: 0.6667\n",
            "Epoch 5/10\n",
            "26/26 [==============================] - ETA: 0s - loss: 0.6235 - accuracy: 0.6046WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "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\r26/26 [==============================] - 17s 655ms/step - loss: 0.6235 - accuracy: 0.6046 - val_loss: 0.6665 - val_accuracy: 0.6667\n",
            "Epoch 6/10\n",
            "26/26 [==============================] - ETA: 0s - loss: 0.6060 - accuracy: 0.6229WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "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\r26/26 [==============================] - 17s 657ms/step - loss: 0.6060 - accuracy: 0.6229 - val_loss: 0.6507 - val_accuracy: 0.6667\n",
            "Epoch 7/10\n",
            "26/26 [==============================] - ETA: 0s - loss: 0.5892 - accuracy: 0.6423WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "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\r26/26 [==============================] - 17s 661ms/step - loss: 0.5892 - accuracy: 0.6423 - val_loss: 0.6345 - val_accuracy: 0.6765\n",
            "Epoch 8/10\n",
            "26/26 [==============================] - ETA: 0s - loss: 0.5726 - accuracy: 0.6630WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "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\r26/26 [==============================] - 17s 657ms/step - loss: 0.5726 - accuracy: 0.6630 - val_loss: 0.6188 - val_accuracy: 0.6863\n",
            "Epoch 9/10\n",
            "26/26 [==============================] - ETA: 0s - loss: 0.5562 - accuracy: 0.6788WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "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\r26/26 [==============================] - 17s 660ms/step - loss: 0.5562 - accuracy: 0.6788 - val_loss: 0.6031 - val_accuracy: 0.6961\n",
            "Epoch 10/10\n",
            "26/26 [==============================] - ETA: 0s - loss: 0.5405 - accuracy: 0.6959WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:Can save best model only with val_acc available, skipping.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "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\r26/26 [==============================] - 17s 663ms/step - loss: 0.5405 - accuracy: 0.6959 - val_loss: 0.5878 - val_accuracy: 0.6961\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TK2s9ZBNdn-D",
        "outputId": "1b896f13-1db4-42fd-8963-13f2ad6022a6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "model.evaluate(test_batches)"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4/4 [==============================] - 1s 357ms/step - loss: 0.4952 - accuracy: 0.7670\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.4951632618904114, 0.7669903039932251]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m5jUvJEPcNqa",
        "outputId": "652e6840-4ae9-4c0b-d240-66092f7f7354",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        }
      },
      "source": [
        "#Evaluate the Model\n",
        "plt.plot(history.history['accuracy'], label='accuracy')\n",
        "plt.plot(history.history['val_accuracy'], label = 'val_accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.ylim([0.5, 1])\n",
        "plt.legend(loc='lower right')\n",
        "test_loss, test_acc = model.evaluate(validation_batches, verbose=2)\n",
        "print('\\nTest accuracy:', test_acc)"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4/4 - 1s - loss: 0.5878 - accuracy: 0.6961\n",
            "\n",
            "Test accuracy: 0.6960784196853638\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "GpnP2KrPo_l2"
      },
      "source": [
        "# Fine Tuning"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lgC9BDQdpBZY",
        "outputId": "51c08955-5551-4c79-eb2b-b4ad54f2a7ea",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "base_model.trainable=True\n",
        "\n",
        "print('Number of layers in the base model: ',len(base_model.layers))\n",
        "\n",
        "finetune_at=155"
      ],
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Number of layers in the base model:  155\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VGfQ8ps5p3wi"
      },
      "source": [
        "for layer in base_model.layers[:finetune_at]:\n",
        "    layer.trainable=False"
      ],
      "execution_count": 37,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LWgnA2iNtuHV"
      },
      "source": [
        "model.compile(loss=keras.losses.BinaryCrossentropy(from_logits=True),\n",
        "              optimizer=keras.optimizers.RMSprop(lr=base_learning_rate/10),\n",
        "              metrics=['accuracy']\n",
        "              )"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tYgwowpKuGPZ",
        "outputId": "5e274099-e5c8-4f6b-aefc-a0cdf317ce29",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 255
        }
      },
      "source": [
        "model.summary()"
      ],
      "execution_count": 39,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"sequential\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "mobilenetv2_1.00_160 (Functi (None, 5, 5, 1280)        2257984   \n",
            "_________________________________________________________________\n",
            "global_average_pooling2d (Gl (None, 1280)              0         \n",
            "_________________________________________________________________\n",
            "dense (Dense)                (None, 1)                 1281      \n",
            "=================================================================\n",
            "Total params: 2,259,265\n",
            "Trainable params: 1,281\n",
            "Non-trainable params: 2,257,984\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "tOAYxHcVuIUQ",
        "outputId": "a7af24fd-00bc-4bc8-c160-189b30b02102",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 391
        }
      },
      "source": [
        "fine_tuning_epochs=10\n",
        "total_epochs=initial_epochs+fine_tuning_epochs\n",
        "\n",
        "history_fine=model.fit(\n",
        "train_batches,\n",
        "epochs=total_epochs,\n",
        "initial_epoch=history.epoch[-1],\n",
        "validation_data=validation_batches\n",
        ")"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 10/20\n",
            "26/26 [==============================] - 19s 720ms/step - loss: 0.5310 - accuracy: 0.7068 - val_loss: 0.5859 - val_accuracy: 0.6961\n",
            "Epoch 11/20\n",
            "26/26 [==============================] - 17s 652ms/step - loss: 0.5294 - accuracy: 0.7068 - val_loss: 0.5843 - val_accuracy: 0.6961\n",
            "Epoch 12/20\n",
            "26/26 [==============================] - 17s 661ms/step - loss: 0.5278 - accuracy: 0.7092 - val_loss: 0.5828 - val_accuracy: 0.6961\n",
            "Epoch 13/20\n",
            "26/26 [==============================] - 17s 659ms/step - loss: 0.5263 - accuracy: 0.7092 - val_loss: 0.5813 - val_accuracy: 0.6961\n",
            "Epoch 14/20\n",
            "26/26 [==============================] - 17s 649ms/step - loss: 0.5247 - accuracy: 0.7129 - val_loss: 0.5798 - val_accuracy: 0.6961\n",
            "Epoch 15/20\n",
            "26/26 [==============================] - 17s 645ms/step - loss: 0.5232 - accuracy: 0.7141 - val_loss: 0.5783 - val_accuracy: 0.6961\n",
            "Epoch 16/20\n",
            "26/26 [==============================] - 17s 644ms/step - loss: 0.5216 - accuracy: 0.7153 - val_loss: 0.5768 - val_accuracy: 0.6961\n",
            "Epoch 17/20\n",
            "26/26 [==============================] - 17s 649ms/step - loss: 0.5201 - accuracy: 0.7153 - val_loss: 0.5753 - val_accuracy: 0.7059\n",
            "Epoch 18/20\n",
            "26/26 [==============================] - 17s 647ms/step - loss: 0.5186 - accuracy: 0.7153 - val_loss: 0.5738 - val_accuracy: 0.7059\n",
            "Epoch 19/20\n",
            "26/26 [==============================] - 17s 651ms/step - loss: 0.5171 - accuracy: 0.7178 - val_loss: 0.5723 - val_accuracy: 0.7255\n",
            "Epoch 20/20\n",
            "26/26 [==============================] - 17s 652ms/step - loss: 0.5155 - accuracy: 0.7190 - val_loss: 0.5708 - val_accuracy: 0.7255\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "mWhNwAPxvctH",
        "outputId": "98db7c70-052f-41a4-e269-05a0f5aa6def",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "model.evaluate(test_batches)"
      ],
      "execution_count": 41,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4/4 [==============================] - 1s 360ms/step - loss: 0.4796 - accuracy: 0.7670\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[0.4796353578567505, 0.7669903039932251]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 41
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Otsr3RCr300K",
        "outputId": "9f1adf3c-bbf4-4625-e76a-22b2964efc79",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 334
        }
      },
      "source": [
        "#Evaluate the Model\n",
        "plt.plot(history_fine.history['accuracy'], label='accuracy')\n",
        "plt.plot(history_fine.history['val_accuracy'], label = 'val_accuracy')\n",
        "plt.xlabel('Epoch')\n",
        "plt.ylabel('Accuracy')\n",
        "plt.ylim([0.5, 1.0])\n",
        "plt.legend(loc='lower right')\n",
        "test_loss, test_acc = model.evaluate(validation_batches, verbose=2)\n",
        "print('\\n Fine Tuned Test accuracy:', test_acc)"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "4/4 - 1s - loss: 0.5708 - accuracy: 0.7255\n",
            "\n",
            " Fine Tuned Test accuracy: 0.7254902124404907\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-6jkELMQFmgx"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}