[{'role': 'system', 'content': "You are an expert in machine learning and your task is to classify code snippets into one of the following categories: ['helper_functions', 'load_data', 'data_exploration', 'data_preprocessing', 'evaluation', 'modelling', 'prediction', 'result_visualization', 'save_results', 'comment_only']."}, {'role': 'user', 'content': "Identify the single most appropriate category to which the provided code belongs. Provide your response as a single category label without any additional information, commentary, or personal opinions.\\nPython Code:def create_grayscale_10_layer_model():\noptimizer = 'adam'\nobjective = 'binary_crossentropy'\nmodel = Sequential()\nmodel.add(Convolution2D(64, 3, 3, border_mode='same', input_shape=(224, 224, 1), activation='relu'))\nmodel.add(Convolution2D(64, 3, 3, border_mode='same', activation='relu'))\nmodel.add(MaxPooling2D(pool_size=(2, 2)))\nmodel.add(Convolution2D(128, 3, 3, border_mode='same', activation='relu'))\nmodel.add(Convolution2D(128, 3, 3, border_mode='same', activation='relu'))\nmodel.add(MaxPooling2D(pool_size=(2, 2)))\nmodel.add(Convolution2D(256, 3, 3, border_mode='same', activation='relu'))\nmodel.add(Convolution2D(256, 3, 3, border_mode='same', activation='relu'))\nmodel.add(Convolution2D(256, 3, 3, border_mode='same', activation='relu'))\nmodel.add(MaxPooling2D(pool_size=(2, 2)))\nmodel.add(Flatten())\nmodel.add(Dense(256, activation='relu'))\nmodel.add(Dropout(0.5))\nmodel.add(Dense(256, activation='relu'))\nmodel.add(Dropout(0.5))\nmodel.add(Dense(1))\nmodel.add(Activation('sigmoid'))\nmodel.compile(loss=objective, optimizer=optimizer, metrics=['accuracy'])\nreturn model\nclass LossHistory(Callback):\ndef on_train_begin(self, logs={}):\nself.losses = []\nself.val_losses = []\ndef on_epoch_end(self, batch, logs={}):\nself.losses.append(logs.get('loss'))\nself.val_losses.append(logs.get('val_loss'))"}, {'role': 'assistant', 'content': 'modelling'}]