MNIST Dataset 2.ipynb

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    "import tensorflow as tf\n",
    "\n",
    "# Instantiate the dataset API\n",
    "fmnist = tf.keras.datasets.fashion_mnist\n",
    "\n",
    "# Load the dataset\n",
    "(x_train, y_train),(x_test, y_test) = fmnist.load_data()\n",
    "\n",
    "# Normalize the pixel values\n",
    "x_train, x_test = x_train / 255.0, x_test / 255.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b90b3849",
   "metadata": {},
   "outputs": [],
   "source": [
    "class myCallback(tf.keras.callbacks.Callback):\n",
    "  def on_epoch_end(self, epoch, logs={}):\n",
    "    '''\n",
    "    Halts the training after reaching 60 percent accuracy\n",
    "\n",
    "    Args:\n",
    "      epoch (integer) - index of epoch (required but unused in the function definition below)\n",
    "      logs (dict) - metric results from the training epoch\n",
    "    '''\n",
    "\n",
    "    # Check accuracy\n",
    "    if(logs.get('loss') < 0.4):\n",
    "\n",
    "      # Stop if threshold is met\n",
    "      print(\"\\nLoss is lower than 0.4 so cancelling training!\")\n",
    "      self.model.stop_training = True\n",
    "\n",
    "# Instantiate class\n",
    "callbacks = myCallback()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "67291219",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define the model\n",
    "model = tf.keras.models.Sequential([\n",
    "  tf.keras.layers.Flatten(input_shape=(28, 28)),\n",
    "  tf.keras.layers.Dense(512, activation=tf.nn.relu),\n",
    "  tf.keras.layers.Dense(10, activation=tf.nn.softmax)\n",
    "])\n",
    "\n",
    "# Compile the model\n",
    "model.compile(optimizer=tf.optimizers.Adam(),\n",
    "              loss='sparse_categorical_crossentropy',\n",
    "              metrics=['accuracy'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "9850c03c",
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "1875/1875 [==============================] - 7s 3ms/step - loss: 0.4723 - accuracy: 0.8303\n",
      "Epoch 2/10\n",
      "1874/1875 [============================>.] - ETA: 0s - loss: 0.3604 - accuracy: 0.8682\n",
      "Loss is lower than 0.4 so cancelling training!\n",
      "1875/1875 [==============================] - 6s 3ms/step - loss: 0.3603 - accuracy: 0.8682\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<keras.callbacks.History at 0x18d60ec3c10>"
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     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Train the model with a callback\n",
    "model.fit(x_train, y_train, epochs=10, callbacks=[callbacks])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "abcf0193",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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