{"metadata":{"kernelspec":{"language":"python","display_name":"Python 3","name":"python3"},"language_info":{"name":"python","version":"3.10.12","mimetype":"text/x-python","codemirror_mode":{"name":"ipython","version":3},"pygments_lexer":"ipython3","nbconvert_exporter":"python","file_extension":".py"},"kaggle":{"accelerator":"nvidiaTeslaT4","dataSources":[{"sourceId":14774,"databundleVersionId":875431,"sourceType":"competition"}],"dockerImageVersionId":30628,"isInternetEnabled":true,"language":"python","sourceType":"notebook","isGpuEnabled":true}},"nbformat_minor":4,"nbformat":4,"cells":[{"cell_type":"code","source":"import pandas as pd\nimport numpy as np\nimport os\nfrom prettytable import PrettyTable\nimport pickle\nimport multiprocessing\nfrom multiprocessing.pool import ThreadPool\nprint(multiprocessing.cpu_count(),\" CPU cores\")\n\nimport seaborn as sns\n%matplotlib inline\nimport matplotlib.pyplot as plt\nplt.rcParams[\"axes.grid\"] = False\n\nfrom sklearn.metrics import confusion_matrix, cohen_kappa_score,accuracy_score\n\nfrom PIL import Image\nimport cv2\n\nimport keras\nfrom keras import applications\nfrom keras.preprocessing.image import ImageDataGenerator\nfrom keras import optimizers,Model,Sequential\nfrom keras.layers import Input,GlobalAveragePooling2D,Dropout,Dense,Activation\nfrom keras.callbacks import EarlyStopping,ReduceLROnPlateau","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:00.809283Z","iopub.execute_input":"2023-12-15T18:54:00.810194Z","iopub.status.idle":"2023-12-15T18:54:00.820284Z","shell.execute_reply.started":"2023-12-15T18:54:00.81016Z","shell.execute_reply":"2023-12-15T18:54:00.81932Z"},"trusted":true},"execution_count":3,"outputs":[{"name":"stdout","text":"4 CPU cores\n","output_type":"stream"}]},{"cell_type":"code","source":"def load_data():\n train = pd.read_csv('/kaggle/input/aptos2019-blindness-detection/train.csv')\n test = pd.read_csv('/kaggle/input/aptos2019-blindness-detection/test.csv')\n\n train_dir = '/kaggle/input/aptos2019-blindness-detection/train_images'\n test_dir = '/kaggle/input/aptos2019-blindness-detection/test_images'\n\n train['file_path'] = train['id_code'].map(lambda x: os.path.join(train_dir,'{}.png'.format(x)))\n test['file_path'] = test['id_code'].map(lambda x: os.path.join(test_dir,'{}.png'.format(x)))\n\n train['file_name'] = train[\"id_code\"].apply(lambda x: x + \".png\")\n test['file_name'] = test[\"id_code\"].apply(lambda x: x + \".png\")\n\n train['diagnosis'] = train['diagnosis'].astype(str)\n\n return train,test","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:03.045368Z","iopub.execute_input":"2023-12-15T18:54:03.046239Z","iopub.status.idle":"2023-12-15T18:54:03.053353Z","shell.execute_reply.started":"2023-12-15T18:54:03.046197Z","shell.execute_reply":"2023-12-15T18:54:03.052286Z"},"trusted":true},"execution_count":4,"outputs":[]},{"cell_type":"code","source":"df_train,df_test = load_data()\nprint(df_train.shape,df_test.shape,'\\n')\ndf_train.head(6)","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:04.082294Z","iopub.execute_input":"2023-12-15T18:54:04.082695Z","iopub.status.idle":"2023-12-15T18:54:04.145548Z","shell.execute_reply.started":"2023-12-15T18:54:04.082665Z","shell.execute_reply":"2023-12-15T18:54:04.144575Z"},"trusted":true},"execution_count":5,"outputs":[{"name":"stdout","text":"(3662, 4) (1928, 3) \n\n","output_type":"stream"},{"execution_count":5,"output_type":"execute_result","data":{"text/plain":" id_code diagnosis file_path \\\n0 000c1434d8d7 2 /kaggle/input/aptos2019-blindness-detection/tr... \n1 001639a390f0 4 /kaggle/input/aptos2019-blindness-detection/tr... \n2 0024cdab0c1e 1 /kaggle/input/aptos2019-blindness-detection/tr... \n3 002c21358ce6 0 /kaggle/input/aptos2019-blindness-detection/tr... \n4 005b95c28852 0 /kaggle/input/aptos2019-blindness-detection/tr... \n5 0083ee8054ee 4 /kaggle/input/aptos2019-blindness-detection/tr... \n\n file_name \n0 000c1434d8d7.png \n1 001639a390f0.png \n2 0024cdab0c1e.png \n3 002c21358ce6.png \n4 005b95c28852.png \n5 0083ee8054ee.png ","text/html":"
\n\n\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n
id_codediagnosisfile_pathfile_name
0000c1434d8d72/kaggle/input/aptos2019-blindness-detection/tr...000c1434d8d7.png
1001639a390f04/kaggle/input/aptos2019-blindness-detection/tr...001639a390f0.png
20024cdab0c1e1/kaggle/input/aptos2019-blindness-detection/tr...0024cdab0c1e.png
3002c21358ce60/kaggle/input/aptos2019-blindness-detection/tr...002c21358ce6.png
4005b95c288520/kaggle/input/aptos2019-blindness-detection/tr...005b95c28852.png
50083ee8054ee4/kaggle/input/aptos2019-blindness-detection/tr...0083ee8054ee.png
\n
"},"metadata":{}}]},{"cell_type":"code","source":"def load_data():\n file = open('df_train_train', 'rb')\n df_train_train = pickle.load(file)\n file.close()\n\n file = open('df_train_test', 'rb')\n df_train_test = pickle.load(file)\n file.close()\n\n return df_train_train,df_train_test","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:04.710945Z","iopub.execute_input":"2023-12-15T18:54:04.711275Z","iopub.status.idle":"2023-12-15T18:54:04.717073Z","shell.execute_reply.started":"2023-12-15T18:54:04.711243Z","shell.execute_reply":"2023-12-15T18:54:04.715882Z"},"trusted":true},"execution_count":6,"outputs":[]},{"cell_type":"code","source":"from sklearn.model_selection import train_test_split\ndf_train_train,df_train_test = train_test_split(df_train,test_size = 0.2)\nprint(df_train_train.shape,df_train_test.shape)\n\n","metadata":{"_uuid":"8f2839f25d086af736a60e9eeb907d3b93b6e0e5","_cell_guid":"b1076dfc-b9ad-4769-8c92-a6c4dae69d19","execution":{"iopub.status.busy":"2023-12-15T18:54:05.296123Z","iopub.execute_input":"2023-12-15T18:54:05.296498Z","iopub.status.idle":"2023-12-15T18:54:05.321268Z","shell.execute_reply.started":"2023-12-15T18:54:05.296468Z","shell.execute_reply":"2023-12-15T18:54:05.320353Z"},"trusted":true},"execution_count":7,"outputs":[{"name":"stdout","text":"(2929, 4) (733, 4)\n","output_type":"stream"}]},{"cell_type":"code","source":"df_train_train['diagnosis']=df_train_train['diagnosis'].astype(str)\ndf_train_test['diagnosis']=df_train_test['diagnosis'].astype(str)","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:05.848535Z","iopub.execute_input":"2023-12-15T18:54:05.848882Z","iopub.status.idle":"2023-12-15T18:54:05.854362Z","shell.execute_reply.started":"2023-12-15T18:54:05.848856Z","shell.execute_reply":"2023-12-15T18:54:05.85341Z"},"trusted":true},"execution_count":8,"outputs":[]},{"cell_type":"code","source":"IMG_SIZE = 512\n","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:06.47389Z","iopub.execute_input":"2023-12-15T18:54:06.474268Z","iopub.status.idle":"2023-12-15T18:54:06.478389Z","shell.execute_reply.started":"2023-12-15T18:54:06.474237Z","shell.execute_reply":"2023-12-15T18:54:06.477424Z"},"trusted":true},"execution_count":9,"outputs":[]},{"cell_type":"code","source":"!mkdir train_images_resized\n!mkdir test_images_resized","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:06.809702Z","iopub.execute_input":"2023-12-15T18:54:06.810035Z","iopub.status.idle":"2023-12-15T18:54:08.725324Z","shell.execute_reply.started":"2023-12-15T18:54:06.810007Z","shell.execute_reply":"2023-12-15T18:54:08.724079Z"},"trusted":true},"execution_count":10,"outputs":[]},{"cell_type":"code","source":"! mkdir data","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:08.728071Z","iopub.execute_input":"2023-12-15T18:54:08.728974Z","iopub.status.idle":"2023-12-15T18:54:09.708476Z","shell.execute_reply.started":"2023-12-15T18:54:08.728932Z","shell.execute_reply":"2023-12-15T18:54:09.707186Z"},"trusted":true},"execution_count":11,"outputs":[]},{"cell_type":"code","source":"def image_resize_save(file):\n input_filepath = os.path.join('/kaggle/input/aptos2019-blindness-detection','train_images','{}.png'.format(file))\n #print(input_filepath)\n output_filepath = os.path.join('./','train_images_resized','{}.png'.format(file))\n img = cv2.imread(input_filepath)\n cv2.imwrite(output_filepath, cv2.resize(img, (IMG_SIZE,IMG_SIZE)))\n","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:09.710202Z","iopub.execute_input":"2023-12-15T18:54:09.710581Z","iopub.status.idle":"2023-12-15T18:54:09.717123Z","shell.execute_reply.started":"2023-12-15T18:54:09.710535Z","shell.execute_reply":"2023-12-15T18:54:09.716197Z"},"trusted":true},"execution_count":12,"outputs":[]},{"cell_type":"code","source":"def image_resize_save1(file):\n input_filepath = os.path.join('/kaggle/input/aptos2019-blindness-detection','train_images','{}.png'.format(file))\n #print(input_filepath)\n output_filepath = os.path.join('./','test_images_resized','{}.png'.format(file))\n img = cv2.imread(input_filepath)\n cv2.imwrite(output_filepath, cv2.resize(img, (IMG_SIZE,IMG_SIZE)))","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:09.71898Z","iopub.execute_input":"2023-12-15T18:54:09.71925Z","iopub.status.idle":"2023-12-15T18:54:09.72747Z","shell.execute_reply.started":"2023-12-15T18:54:09.719216Z","shell.execute_reply":"2023-12-15T18:54:09.726629Z"},"trusted":true},"execution_count":13,"outputs":[]},{"cell_type":"code","source":"def multiprocess_image_downloader(process:int, imgs:list):\n \"\"\"\n Inputs:\n process: (int) number of process to run\n imgs:(list) list of images\n \"\"\"\n print(f'MESSAGE: Running {process} process')\n results = ThreadPool(process).map(image_resize_save, imgs)\n return results","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:09.728684Z","iopub.execute_input":"2023-12-15T18:54:09.728936Z","iopub.status.idle":"2023-12-15T18:54:09.741526Z","shell.execute_reply.started":"2023-12-15T18:54:09.728913Z","shell.execute_reply":"2023-12-15T18:54:09.740759Z"},"trusted":true},"execution_count":14,"outputs":[]},{"cell_type":"code","source":"def multiprocess_image_downloader1(process:int, imgs:list):\n \"\"\"\n Inputs:\n process: (int) number of process to run\n imgs:(list) list of images\n \"\"\"\n print(f'MESSAGE: Running {process} process')\n results = ThreadPool(process).map(image_resize_save1, imgs)\n return results","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:09.742583Z","iopub.execute_input":"2023-12-15T18:54:09.744795Z","iopub.status.idle":"2023-12-15T18:54:09.751833Z","shell.execute_reply.started":"2023-12-15T18:54:09.74477Z","shell.execute_reply":"2023-12-15T18:54:09.751031Z"},"trusted":true},"execution_count":15,"outputs":[]},{"cell_type":"code","source":"multiprocess_image_downloader(6, list(df_train_train.id_code.values))","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:54:10.140618Z","iopub.execute_input":"2023-12-15T18:54:10.140936Z","iopub.status.idle":"2023-12-15T18:56:22.751293Z","shell.execute_reply.started":"2023-12-15T18:54:10.14091Z","shell.execute_reply":"2023-12-15T18:56:22.749727Z"},"trusted":true},"execution_count":16,"outputs":[{"name":"stdout","text":"MESSAGE: Running 6 process\n","output_type":"stream"},{"execution_count":16,"output_type":"execute_result","data":{"text/plain":"[None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n ...]"},"metadata":{}}]},{"cell_type":"code","source":"multiprocess_image_downloader1(6, list(df_train_test.id_code.values))","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:56:22.752962Z","iopub.execute_input":"2023-12-15T18:56:22.753245Z","iopub.status.idle":"2023-12-15T18:56:54.579202Z","shell.execute_reply.started":"2023-12-15T18:56:22.753219Z","shell.execute_reply":"2023-12-15T18:56:54.578273Z"},"trusted":true},"execution_count":17,"outputs":[{"name":"stdout","text":"MESSAGE: Running 6 process\n","output_type":"stream"},{"execution_count":17,"output_type":"execute_result","data":{"text/plain":"[None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None]"},"metadata":{}}]},{"cell_type":"code","source":"def crop_image_from_gray(img,tol=7):\n if img.ndim ==2:\n mask = img>tol\n return img[np.ix_(mask.any(1),mask.any(0))]\n elif img.ndim==3:\n gray_img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)\n mask = gray_img>tol\n\n check_shape = img[:,:,0][np.ix_(mask.any(1),mask.any(0))].shape[0]\n if (check_shape == 0): # image is too dark so that we crop out everything,\n return img # return original image\n else:\n img1=img[:,:,0][np.ix_(mask.any(1),mask.any(0))]\n img2=img[:,:,1][np.ix_(mask.any(1),mask.any(0))]\n img3=img[:,:,2][np.ix_(mask.any(1),mask.any(0))]\n # print(img1.shape,img2.shape,img3.shape)\n img = np.stack([img1,img2,img3],axis=-1)\n # print(img.shape)\n return img\n\ndef circle_crop(img, sigmaX = 30):\n \"\"\"\n Create circular crop around image centre\n \"\"\"\n img = crop_image_from_gray(img)\n img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n\n height, width, depth = img.shape\n\n x = int(width/2)\n y = int(height/2)\n r = np.amin((x,y))\n\n circle_img = np.zeros((height, width), np.uint8)\n cv2.circle(circle_img, (x,y), int(r), 1, thickness=-1)\n img = cv2.bitwise_and(img, img, mask=circle_img)\n img = crop_image_from_gray(img)\n img=cv2.addWeighted(img,4, cv2.GaussianBlur( img , (0,0) , sigmaX) ,-4 ,128)\n return img\n\ndef preprocess_image(file):\n input_filepath = os.path.join('./','/kaggle/working/train_images_resized','{}.png'.format(file))\n output_filepath = os.path.join('./','train_images_resized_preprocessed','{}.png'.format(file))\n #print(input_filepath)\n img = cv2.imread(input_filepath)\n img = circle_crop(img)\n cv2.imwrite(output_filepath, cv2.resize(img, (IMG_SIZE,IMG_SIZE)))","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:56:54.580515Z","iopub.execute_input":"2023-12-15T18:56:54.580839Z","iopub.status.idle":"2023-12-15T18:56:54.597759Z","shell.execute_reply.started":"2023-12-15T18:56:54.580812Z","shell.execute_reply":"2023-12-15T18:56:54.596734Z"},"trusted":true},"execution_count":18,"outputs":[]},{"cell_type":"code","source":"def preprocess_image1(file):\n input_filepath = os.path.join('./','test_images_resized','{}.png'.format(file))\n output_filepath = os.path.join('./','test_images_resized_preprocessed','{}.png'.format(file))\n #print(input_filepath)\n img = cv2.imread(input_filepath)\n img = circle_crop(img)\n cv2.imwrite(output_filepath, cv2.resize(img, (IMG_SIZE,IMG_SIZE)))","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:56:54.60076Z","iopub.execute_input":"2023-12-15T18:56:54.601685Z","iopub.status.idle":"2023-12-15T18:56:54.612984Z","shell.execute_reply.started":"2023-12-15T18:56:54.601648Z","shell.execute_reply":"2023-12-15T18:56:54.612088Z"},"trusted":true},"execution_count":19,"outputs":[]},{"cell_type":"code","source":"!mkdir './test_images_resized_preprocessed'\n!mkdir './train_images_resized_preprocessed'","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:56:54.614312Z","iopub.execute_input":"2023-12-15T18:56:54.614678Z","iopub.status.idle":"2023-12-15T18:56:56.615028Z","shell.execute_reply.started":"2023-12-15T18:56:54.614644Z","shell.execute_reply":"2023-12-15T18:56:56.613907Z"},"trusted":true},"execution_count":20,"outputs":[]},{"cell_type":"code","source":"'''This Function uses Multi processing for faster saving of images into folder'''\n\ndef multiprocess_image_processor(process:int, imgs:list):\n \"\"\"\n Inputs:\n process: (int) number of process to run\n imgs:(list) list of images\n \"\"\"\n print(f'MESSAGE: Running {process} process')\n results = ThreadPool(process).map(preprocess_image, imgs)\n return results","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:56:56.616706Z","iopub.execute_input":"2023-12-15T18:56:56.617627Z","iopub.status.idle":"2023-12-15T18:56:56.623941Z","shell.execute_reply.started":"2023-12-15T18:56:56.617566Z","shell.execute_reply":"2023-12-15T18:56:56.622942Z"},"trusted":true},"execution_count":21,"outputs":[]},{"cell_type":"code","source":"def multiprocess_image_processor1(process:int, imgs:list):\n \"\"\"\n Inputs:\n process: (int) number of process to run\n imgs:(list) list of images\n \"\"\"\n print(f'MESSAGE: Running {process} process')\n results = ThreadPool(process).map(preprocess_image1, imgs)\n return results","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:56:56.62521Z","iopub.execute_input":"2023-12-15T18:56:56.625517Z","iopub.status.idle":"2023-12-15T18:56:56.638092Z","shell.execute_reply.started":"2023-12-15T18:56:56.625491Z","shell.execute_reply":"2023-12-15T18:56:56.637299Z"},"trusted":true},"execution_count":22,"outputs":[]},{"cell_type":"code","source":"multiprocess_image_processor1(2, list(df_train_test.id_code.values))","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:56:56.639343Z","iopub.execute_input":"2023-12-15T18:56:56.639774Z","iopub.status.idle":"2023-12-15T18:58:16.907683Z","shell.execute_reply.started":"2023-12-15T18:56:56.639742Z","shell.execute_reply":"2023-12-15T18:58:16.906809Z"},"trusted":true},"execution_count":23,"outputs":[{"name":"stdout","text":"MESSAGE: Running 2 process\n","output_type":"stream"},{"execution_count":23,"output_type":"execute_result","data":{"text/plain":"[None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None]"},"metadata":{}}]},{"cell_type":"code","source":"# Use 2 cores (colab)\n# ref - https://stackoverflow.com/questions/1006289/how-to-find-out-the-number-of-cpus-using-python\n\nmultiprocess_image_processor(2, list(df_train_train.id_code.values))","metadata":{"execution":{"iopub.status.busy":"2023-12-15T18:58:16.908953Z","iopub.execute_input":"2023-12-15T18:58:16.909319Z","iopub.status.idle":"2023-12-15T19:03:36.655161Z","shell.execute_reply.started":"2023-12-15T18:58:16.909285Z","shell.execute_reply":"2023-12-15T19:03:36.654227Z"},"trusted":true},"execution_count":24,"outputs":[{"name":"stdout","text":"MESSAGE: Running 2 process\n","output_type":"stream"},{"execution_count":24,"output_type":"execute_result","data":{"text/plain":"[None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n 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None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n None,\n ...]"},"metadata":{}}]},{"cell_type":"code","source":"# Model parameters\nBATCH_SIZE = 8\nEPOCHS = 40\nWARMUP_EPOCHS = 2\nLEARNING_RATE = 1e-4\nWARMUP_LEARNING_RATE = 1e-3\nHEIGHT = 320\nWIDTH = 320\nCANAL = 3\nN_CLASSES = 5\nES_PATIENCE = 5\nRLROP_PATIENCE = 3\nDECAY_DROP = 0.5","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:36.658976Z","iopub.execute_input":"2023-12-15T19:03:36.659332Z","iopub.status.idle":"2023-12-15T19:03:36.664411Z","shell.execute_reply.started":"2023-12-15T19:03:36.659306Z","shell.execute_reply":"2023-12-15T19:03:36.663488Z"},"trusted":true},"execution_count":25,"outputs":[]},{"cell_type":"code","source":"def img_generator(train,test):\n train_datagen=ImageDataGenerator(rescale=1./255, validation_split=0.2,horizontal_flip=True)\n\n train_generator=train_datagen.flow_from_dataframe(dataframe=df_train_train,\n directory=\"./train_images_resized_preprocessed/\",\n x_col=\"file_name\",\n y_col=\"diagnosis\",\n batch_size=BATCH_SIZE,\n class_mode=\"categorical\",\n target_size=(HEIGHT, WIDTH),\n subset='training')\n\n valid_generator=train_datagen.flow_from_dataframe(dataframe=df_train_train,\n directory=\"./train_images_resized_preprocessed/\",\n x_col=\"file_name\",\n y_col=\"diagnosis\",\n batch_size=BATCH_SIZE,\n class_mode=\"categorical\",\n target_size=(HEIGHT, WIDTH),\n subset='validation')\n\n test_datagen = ImageDataGenerator(rescale=1./255)\n test_generator = test_datagen.flow_from_dataframe(dataframe=df_train_test,\n directory = \"./test_images_resized_preprocessed/\",\n x_col=\"file_name\",\n target_size=(HEIGHT, WIDTH),\n batch_size=1,\n shuffle=False,\n class_mode=None)\n\n return train_generator,valid_generator,test_generator","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:36.665606Z","iopub.execute_input":"2023-12-15T19:03:36.665889Z","iopub.status.idle":"2023-12-15T19:03:36.679404Z","shell.execute_reply.started":"2023-12-15T19:03:36.665865Z","shell.execute_reply":"2023-12-15T19:03:36.678604Z"},"trusted":true},"execution_count":26,"outputs":[]},{"cell_type":"code","source":"train_generator,valid_generator,test_generator = img_generator(df_train_train,df_train_test)","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:36.680445Z","iopub.execute_input":"2023-12-15T19:03:36.680777Z","iopub.status.idle":"2023-12-15T19:03:36.790331Z","shell.execute_reply.started":"2023-12-15T19:03:36.680745Z","shell.execute_reply":"2023-12-15T19:03:36.789451Z"},"trusted":true},"execution_count":27,"outputs":[{"name":"stdout","text":"Found 2344 validated image filenames belonging to 5 classes.\nFound 585 validated image filenames belonging to 5 classes.\nFound 733 validated image filenames.\n","output_type":"stream"}]},{"cell_type":"code","source":"def create_model(input_shape, n_out):\n input_tensor = Input(shape=input_shape)\n base_model = applications.VGG16(weights='imagenet', include_top=False,input_tensor=input_tensor)\n # base_model.load_weights('resnet50_weights_tf_dim_ordering_tf_kernels_notop.h5')\n\n x = GlobalAveragePooling2D()(base_model.output)\n x = Dropout(0.5)(x)\n x = Dense(2048, activation='relu')(x)\n x = Dropout(0.5)(x)\n final_output = Dense(n_out, activation='softmax', name='final_output')(x)\n model = Model(input_tensor, final_output)\n return model","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:36.79154Z","iopub.execute_input":"2023-12-15T19:03:36.791881Z","iopub.status.idle":"2023-12-15T19:03:36.798817Z","shell.execute_reply.started":"2023-12-15T19:03:36.79185Z","shell.execute_reply":"2023-12-15T19:03:36.797948Z"},"trusted":true},"execution_count":28,"outputs":[]},{"cell_type":"code","source":"model = create_model(input_shape=(HEIGHT, WIDTH, CANAL), n_out=N_CLASSES)\n\nfor layer in model.layers:\n layer.trainable = False\n\nfor i in range(-5, 0):\n model.layers[i].trainable = True\nmodel.summary()","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:36.800142Z","iopub.execute_input":"2023-12-15T19:03:36.801056Z","iopub.status.idle":"2023-12-15T19:03:42.012954Z","shell.execute_reply.started":"2023-12-15T19:03:36.801022Z","shell.execute_reply":"2023-12-15T19:03:42.011703Z"},"trusted":true},"execution_count":29,"outputs":[{"name":"stdout","text":"Downloading data from https://storage.googleapis.com/tensorflow/keras-applications/vgg16/vgg16_weights_tf_dim_ordering_tf_kernels_notop.h5\n58889256/58889256 [==============================] - 0s 0us/step\nModel: \"model\"\n_________________________________________________________________\n Layer (type) Output Shape Param # \n=================================================================\n input_1 (InputLayer) [(None, 320, 320, 3)] 0 \n \n block1_conv1 (Conv2D) (None, 320, 320, 64) 1792 \n \n block1_conv2 (Conv2D) (None, 320, 320, 64) 36928 \n \n block1_pool (MaxPooling2D) (None, 160, 160, 64) 0 \n \n block2_conv1 (Conv2D) (None, 160, 160, 128) 73856 \n \n block2_conv2 (Conv2D) (None, 160, 160, 128) 147584 \n \n block2_pool (MaxPooling2D) (None, 80, 80, 128) 0 \n \n block3_conv1 (Conv2D) (None, 80, 80, 256) 295168 \n \n block3_conv2 (Conv2D) (None, 80, 80, 256) 590080 \n \n block3_conv3 (Conv2D) (None, 80, 80, 256) 590080 \n \n block3_pool (MaxPooling2D) (None, 40, 40, 256) 0 \n \n block4_conv1 (Conv2D) (None, 40, 40, 512) 1180160 \n \n block4_conv2 (Conv2D) (None, 40, 40, 512) 2359808 \n \n block4_conv3 (Conv2D) (None, 40, 40, 512) 2359808 \n \n block4_pool (MaxPooling2D) (None, 20, 20, 512) 0 \n \n block5_conv1 (Conv2D) (None, 20, 20, 512) 2359808 \n \n block5_conv2 (Conv2D) (None, 20, 20, 512) 2359808 \n \n block5_conv3 (Conv2D) (None, 20, 20, 512) 2359808 \n \n block5_pool (MaxPooling2D) (None, 10, 10, 512) 0 \n \n global_average_pooling2d ( (None, 512) 0 \n GlobalAveragePooling2D) \n \n dropout (Dropout) (None, 512) 0 \n \n dense (Dense) (None, 2048) 1050624 \n \n dropout_1 (Dropout) (None, 2048) 0 \n \n final_output (Dense) (None, 5) 10245 \n \n=================================================================\nTotal params: 15775557 (60.18 MB)\nTrainable params: 1060869 (4.05 MB)\nNon-trainable params: 14714688 (56.13 MB)\n_________________________________________________________________\n","output_type":"stream"}]},{"cell_type":"code","source":"STEP_SIZE_TRAIN = train_generator.n//train_generator.batch_size\nSTEP_SIZE_VALID = valid_generator.n//valid_generator.batch_size\nprint(STEP_SIZE_TRAIN,STEP_SIZE_VALID)","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:42.014083Z","iopub.execute_input":"2023-12-15T19:03:42.014359Z","iopub.status.idle":"2023-12-15T19:03:42.020946Z","shell.execute_reply.started":"2023-12-15T19:03:42.014334Z","shell.execute_reply":"2023-12-15T19:03:42.019847Z"},"trusted":true},"execution_count":30,"outputs":[{"name":"stdout","text":"293 73\n","output_type":"stream"}]},{"cell_type":"code","source":"for layer in model.layers:\n layer.trainable = True\n\nes = EarlyStopping(monitor='val_loss', mode='min', patience=ES_PATIENCE, restore_best_weights=True, verbose=1)\nrlrop = ReduceLROnPlateau(monitor='val_loss', mode='min', patience=RLROP_PATIENCE, factor=DECAY_DROP, min_lr=1e-6, verbose=1)\n\ncallback_list = [ rlrop]\noptimizer = optimizers.Adam(lr=LEARNING_RATE)\nmodel.compile(optimizer=optimizer, loss=\"categorical_crossentropy\", metrics=['accuracy'])\nmodel.summary()","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:42.022137Z","iopub.execute_input":"2023-12-15T19:03:42.02248Z","iopub.status.idle":"2023-12-15T19:03:42.121282Z","shell.execute_reply.started":"2023-12-15T19:03:42.022447Z","shell.execute_reply":"2023-12-15T19:03:42.120446Z"},"trusted":true},"execution_count":31,"outputs":[{"name":"stdout","text":"Model: \"model\"\n_________________________________________________________________\n Layer (type) Output Shape Param # \n=================================================================\n input_1 (InputLayer) [(None, 320, 320, 3)] 0 \n \n block1_conv1 (Conv2D) (None, 320, 320, 64) 1792 \n \n block1_conv2 (Conv2D) (None, 320, 320, 64) 36928 \n \n block1_pool (MaxPooling2D) (None, 160, 160, 64) 0 \n \n block2_conv1 (Conv2D) (None, 160, 160, 128) 73856 \n \n block2_conv2 (Conv2D) (None, 160, 160, 128) 147584 \n \n block2_pool (MaxPooling2D) (None, 80, 80, 128) 0 \n \n block3_conv1 (Conv2D) (None, 80, 80, 256) 295168 \n \n block3_conv2 (Conv2D) (None, 80, 80, 256) 590080 \n \n block3_conv3 (Conv2D) (None, 80, 80, 256) 590080 \n \n block3_pool (MaxPooling2D) (None, 40, 40, 256) 0 \n \n block4_conv1 (Conv2D) (None, 40, 40, 512) 1180160 \n \n block4_conv2 (Conv2D) (None, 40, 40, 512) 2359808 \n \n block4_conv3 (Conv2D) (None, 40, 40, 512) 2359808 \n \n block4_pool (MaxPooling2D) (None, 20, 20, 512) 0 \n \n block5_conv1 (Conv2D) (None, 20, 20, 512) 2359808 \n \n block5_conv2 (Conv2D) (None, 20, 20, 512) 2359808 \n \n block5_conv3 (Conv2D) (None, 20, 20, 512) 2359808 \n \n block5_pool (MaxPooling2D) (None, 10, 10, 512) 0 \n \n global_average_pooling2d ( (None, 512) 0 \n GlobalAveragePooling2D) \n \n dropout (Dropout) (None, 512) 0 \n \n dense (Dense) (None, 2048) 1050624 \n \n dropout_1 (Dropout) (None, 2048) 0 \n \n final_output (Dense) (None, 5) 10245 \n \n=================================================================\nTotal params: 15775557 (60.18 MB)\nTrainable params: 15775557 (60.18 MB)\nNon-trainable params: 0 (0.00 Byte)\n_________________________________________________________________\n","output_type":"stream"}]},{"cell_type":"code","source":"class MyCallback(keras.callbacks.Callback):\n def __init__(self, model, patience, stop_patience, threshold, factor, batches, epochs, ask_epoch):\n super(MyCallback, self).__init__()\n self.model = model\n self.patience = patience # specifies how many epochs without improvement before learning rate is adjusted\n self.stop_patience = stop_patience # specifies how many times to adjust lr without improvement to stop training\n self.threshold = threshold # specifies training accuracy threshold when lr will be adjusted based on validation loss\n self.factor = factor # factor by which to reduce the learning rate\n self.batches = batches # number of training batch to run per epoch\n self.epochs = epochs\n self.ask_epoch = ask_epoch\n self.ask_epoch_initial = ask_epoch # save this value to restore if restarting training\n\n # callback variables\n self.count = 0 # how many times lr has been reduced without improvement\n self.stop_count = 0\n self.best_epoch = 1 # epoch with the lowest loss\n self.initial_lr = float(tf.keras.backend.get_value(model.optimizer.lr)) # get the initial learning rate and save it\n self.highest_tracc = 0.0 # set highest training accuracy to 0 initially\n self.lowest_vloss = np.inf # set lowest validation loss to infinity initially\n self.best_weights = self.model.get_weights() # set best weights to model's initial weights\n self.initial_weights = self.model.get_weights() # save initial weights if they have to get restored\n\n # Define a function that will run when train begins\n def on_train_begin(self, logs= None):\n msg = 'Do you want model asks you to halt the training [y/n] ?'\n print(msg)\n ans = input('')\n if ans in ['Y', 'y']:\n self.ask_permission = 1\n elif ans in ['N', 'n']:\n self.ask_permission = 0\n\n msg = '{0:^8s}{1:^10s}{2:^9s}{3:^9s}{4:^9s}{5:^9s}{6:^9s}{7:^10s}{8:10s}{9:^8s}'.format('Epoch', 'Loss', 'Accuracy', 'V_loss', 'V_acc', 'LR', 'Next LR', 'Monitor','% Improv', 'Duration')\n print(msg)\n self.start_time = time.time()\n\n\n def on_train_end(self, logs= None):\n stop_time = time.time()\n tr_duration = stop_time - self.start_time\n hours = tr_duration // 3600\n minutes = (tr_duration - (hours * 3600)) // 60\n seconds = tr_duration - ((hours * 3600) + (minutes * 60))\n\n msg = f'training elapsed time was {str(hours)} hours, {minutes:4.1f} minutes, {seconds:4.2f} seconds)'\n print(msg)\n\n # set the weights of the model to the best weights\n self.model.set_weights(self.best_weights)\n\n\n def on_train_batch_end(self, batch, logs= None):\n # get batch accuracy and loss\n acc = logs.get('accuracy') * 100\n loss = logs.get('loss')\n\n # prints over on the same line to show running batch count\n msg = '{0:20s}processing batch {1:} of {2:5s}- accuracy= {3:5.3f} - loss: {4:8.5f}'.format(' ', str(batch), str(self.batches), acc, loss)\n print(msg, '\\r', end= '')\n\n\n def on_epoch_begin(self, epoch, logs= None):\n self.ep_start = time.time()\n\n\n # Define method runs on the end of each epoch\n def on_epoch_end(self, epoch, logs= None):\n ep_end = time.time()\n duration = ep_end - self.ep_start\n\n lr = float(tf.keras.backend.get_value(self.model.optimizer.lr)) # get the current learning rate\n current_lr = lr\n acc = logs.get('accuracy') # get training accuracy\n v_acc = logs.get('val_accuracy') # get validation accuracy\n loss = logs.get('loss') # get training loss for this epoch\n v_loss = logs.get('val_loss') # get the validation loss for this epoch\n\n if acc < self.threshold: # if training accuracy is below threshold adjust lr based on training accuracy\n monitor = 'accuracy'\n if epoch == 0:\n pimprov = 0.0\n else:\n pimprov = (acc - self.highest_tracc ) * 100 / self.highest_tracc # define improvement of model progres\n\n if acc > self.highest_tracc: # training accuracy improved in the epoch\n self.highest_tracc = acc # set new highest training accuracy\n self.best_weights = self.model.get_weights() # training accuracy improved so save the weights\n self.count = 0 # set count to 0 since training accuracy improved\n self.stop_count = 0 # set stop counter to 0\n if v_loss < self.lowest_vloss:\n self.lowest_vloss = v_loss\n self.best_epoch = epoch + 1 # set the value of best epoch for this epoch\n\n else:\n # training accuracy did not improve check if this has happened for patience number of epochs\n # if so adjust learning rate\n if self.count >= self.patience - 1: # lr should be adjusted\n lr = lr * self.factor # adjust the learning by factor\n tf.keras.backend.set_value(self.model.optimizer.lr, lr) # set the learning rate in the optimizer\n self.count = 0 # reset the count to 0\n self.stop_count = self.stop_count + 1 # count the number of consecutive lr adjustments\n self.count = 0 # reset counter\n if v_loss < self.lowest_vloss:\n self.lowest_vloss = v_loss\n else:\n self.count = self.count + 1 # increment patience counter\n\n else: # training accuracy is above threshold so adjust learning rate based on validation loss\n monitor = 'val_loss'\n if epoch == 0:\n pimprov = 0.0\n\n else:\n pimprov = (self.lowest_vloss - v_loss ) * 100 / self.lowest_vloss\n\n if v_loss < self.lowest_vloss: # check if the validation loss improved\n self.lowest_vloss = v_loss # replace lowest validation loss with new validation loss\n self.best_weights = self.model.get_weights() # validation loss improved so save the weights\n self.count = 0 # reset count since validation loss improved\n self.stop_count = 0\n self.best_epoch = epoch + 1 # set the value of the best epoch to this epoch\n\n else: # validation loss did not improve\n if self.count >= self.patience - 1: # need to adjust lr\n lr = lr * self.factor # adjust the learning rate\n self.stop_count = self.stop_count + 1 # increment stop counter because lr was adjusted\n self.count = 0 # reset counter\n tf.keras.backend.set_value(self.model.optimizer.lr, lr) # set the learning rate in the optimizer\n\n else:\n self.count = self.count + 1 # increment the patience counter\n\n if acc > self.highest_tracc:\n self.highest_tracc = acc\n\n msg = f'{str(epoch + 1):^3s}/{str(self.epochs):4s} {loss:^9.3f}{acc * 100:^9.3f}{v_loss:^9.5f}{v_acc * 100:^9.3f}{current_lr:^9.5f}{lr:^9.5f}{monitor:^11s}{pimprov:^10.2f}{duration:^8.2f}'\n print(msg)\n\n if self.stop_count > self.stop_patience - 1: # check if learning rate has been adjusted stop_count times with no improvement\n msg = f' training has been halted at epoch {epoch + 1} after {self.stop_patience} adjustments of learning rate with no improvement'\n print(msg)\n self.model.stop_training = True # stop training\n\n else:\n if self.ask_epoch != None and self.ask_permission != 0:\n if epoch + 1 >= self.ask_epoch:\n msg = 'enter H to halt training or an integer for number of epochs to run then ask again'\n print(msg)\n\n ans = input('')\n if ans == 'H' or ans == 'h':\n msg = f'training has been halted at epoch {epoch + 1} due to user input'\n print(msg)\n self.model.stop_training = True # stop training\n\n else:\n try:\n ans = int(ans)\n self.ask_epoch += ans\n msg = f' training will continue until epoch {str(self.ask_epoch)}'\n print(msg)\n msg = '{0:^8s}{1:^10s}{2:^9s}{3:^9s}{4:^9s}{5:^9s}{6:^9s}{7:^10s}{8:10s}{9:^8s}'.format('Epoch', 'Loss', 'Accuracy', 'V_loss', 'V_acc', 'LR', 'Next LR', 'Monitor', '% Improv', 'Duration')\n print(msg)\n\n except Exception:\n print('Invalid')","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:42.122484Z","iopub.execute_input":"2023-12-15T19:03:42.122783Z","iopub.status.idle":"2023-12-15T19:03:42.157555Z","shell.execute_reply.started":"2023-12-15T19:03:42.122758Z","shell.execute_reply":"2023-12-15T19:03:42.156445Z"},"trusted":true},"execution_count":32,"outputs":[]},{"cell_type":"code","source":"from tensorflow.keras import regularizers\nfrom tensorflow.keras.layers import Conv2D, MaxPooling2D, Flatten, Dense, Activation, Dropout, BatchNormalization\nimport tensorflow as tf\nfrom tensorflow.keras.optimizers import Adam, Adamax\nimport time","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:42.158791Z","iopub.execute_input":"2023-12-15T19:03:42.159048Z","iopub.status.idle":"2023-12-15T19:03:42.292959Z","shell.execute_reply.started":"2023-12-15T19:03:42.159025Z","shell.execute_reply":"2023-12-15T19:03:42.292265Z"},"trusted":true},"execution_count":33,"outputs":[]},{"cell_type":"code","source":"# Create Model Structure\nimg_size = (224, 224)\nchannels = 3\nimg_shape = (224, 224, channels)\nclass_count = len(list(train_generator.class_indices.keys())) # to define number of classes in dense layer\n\n# create pre-trained model (you can built on pretrained model such as : efficientnet, VGG , Resnet )\n# we will use efficientnetb3 from EfficientNet family.\nbase_model = tf.keras.applications.efficientnet.EfficientNetB3(include_top= False, weights= \"imagenet\", input_shape= img_shape, pooling= 'max')\n\nmodel = Sequential([\n base_model,\n BatchNormalization(axis= -1, momentum= 0.99, epsilon= 0.001),\n Dense(256, kernel_regularizer= regularizers.l2(l= 0.016), activity_regularizer= regularizers.l1(0.006),\n bias_regularizer= regularizers.l1(0.006), activation= 'relu'),\n Dropout(rate= 0.45, seed= 123),\n Dense(class_count, activation= 'softmax')\n])\n\nmodel.compile(Adamax(learning_rate= 0.001), loss= 'categorical_crossentropy', metrics= ['accuracy'])\n\nmodel.summary()","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:42.294289Z","iopub.execute_input":"2023-12-15T19:03:42.294655Z","iopub.status.idle":"2023-12-15T19:03:48.172291Z","shell.execute_reply.started":"2023-12-15T19:03:42.294622Z","shell.execute_reply":"2023-12-15T19:03:48.171401Z"},"trusted":true},"execution_count":34,"outputs":[{"name":"stdout","text":"Downloading data from https://storage.googleapis.com/keras-applications/efficientnetb3_notop.h5\n43941136/43941136 [==============================] - 0s 0us/step\nModel: \"sequential\"\n_________________________________________________________________\n Layer (type) Output Shape Param # \n=================================================================\n efficientnetb3 (Functional (None, 1536) 10783535 \n ) \n \n batch_normalization (Batch (None, 1536) 6144 \n Normalization) \n \n dense_1 (Dense) (None, 256) 393472 \n \n dropout_2 (Dropout) (None, 256) 0 \n \n dense_2 (Dense) (None, 5) 1285 \n \n=================================================================\nTotal params: 11184436 (42.67 MB)\nTrainable params: 11094061 (42.32 MB)\nNon-trainable params: 90375 (353.03 KB)\n_________________________________________________________________\n","output_type":"stream"}]},{"cell_type":"code","source":"batch_size = 8 # set batch size for training\nepochs = 40 # number of all epochs in training\npatience = 1 #number of epochs to wait to adjust lr if monitored value does not improve\nstop_patience = 3 # number of epochs to wait before stopping training if monitored value does not improve\nthreshold = 0.9 # if train accuracy is < threshold adjust monitor accuracy, else monitor validation loss\nfactor = 0.5 # factor to reduce lr by\nask_epoch = 5 # number of epochs to run before asking if you want to halt training\nbatches = int(np.ceil(len(train_generator.labels) / batch_size)) # number of training batch to run per epoch\n\ncallbacks = [MyCallback(model= model, patience= patience, stop_patience= stop_patience, threshold= threshold,\n factor= factor, batches= batches, epochs= epochs, ask_epoch= ask_epoch )]","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:48.173674Z","iopub.execute_input":"2023-12-15T19:03:48.174322Z","iopub.status.idle":"2023-12-15T19:03:48.577076Z","shell.execute_reply.started":"2023-12-15T19:03:48.174284Z","shell.execute_reply":"2023-12-15T19:03:48.575973Z"},"trusted":true},"execution_count":35,"outputs":[]},{"cell_type":"code","source":"history = model.fit(x= train_generator, epochs= epochs, verbose= 1, callbacks= callbacks,\n validation_data= valid_generator, validation_steps= None, shuffle= False)","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:03:48.578526Z","iopub.execute_input":"2023-12-15T19:03:48.578911Z","iopub.status.idle":"2023-12-15T19:25:47.424276Z","shell.execute_reply.started":"2023-12-15T19:03:48.578876Z","shell.execute_reply":"2023-12-15T19:25:47.423225Z"},"trusted":true},"execution_count":36,"outputs":[{"name":"stdout","text":"Do you want model asks you to halt the training [y/n] ?\n","output_type":"stream"},{"output_type":"stream","name":"stdin","text":" y\n"},{"name":"stdout","text":" Epoch Loss Accuracy V_loss V_acc LR Next LR Monitor % Improv Duration\nEpoch 1/40\n","output_type":"stream"},{"name":"stderr","text":"2023-12-15 19:04:18.841641: E tensorflow/core/grappler/optimizers/meta_optimizer.cc:954] layout failed: INVALID_ARGUMENT: Size of values 0 does not match size of permutation 4 @ fanin shape insequential/efficientnetb3/block1b_drop/dropout/SelectV2-2-TransposeNHWCToNCHW-LayoutOptimizer\n","output_type":"stream"},{"name":"stdout","text":"293/293 [==============================] - ETA: 0s - loss: 7.9438 - accuracy: 0.6216 processing batch 1 of 293 - accuracy= 25.000 - loss: 9.85443 processing batch 2 of 293 - accuracy= 25.000 - loss: 10.00042 processing batch 3 of 293 - accuracy= 31.250 - loss: 9.86526 processing batch 4 of 293 - accuracy= 32.500 - loss: 10.04022 processing batch 5 of 293 - accuracy= 33.333 - loss: 10.04839 processing batch 6 of 293 - accuracy= 33.929 - loss: 9.93666 processing batch 7 of 293 - accuracy= 32.812 - loss: 10.03543 processing batch 8 of 293 - accuracy= 33.333 - loss: 9.88348 processing batch 9 of 293 - accuracy= 35.000 - loss: 9.88608 processing batch 10 of 293 - accuracy= 38.636 - loss: 9.76792 processing batch 11 of 293 - accuracy= 40.625 - loss: 9.67693 processing batch 12 of 293 - accuracy= 39.423 - loss: 9.69036 processing batch 13 of 293 - accuracy= 40.179 - loss: 9.68470 processing batch 14 of 293 - accuracy= 39.167 - loss: 9.69864 processing batch 15 of 293 - accuracy= 39.062 - loss: 9.68244 processing batch 16 of 293 - accuracy= 40.441 - loss: 9.64503 processing batch 17 of 293 - accuracy= 43.056 - loss: 9.56402 processing batch 18 of 293 - accuracy= 44.079 - loss: 9.55101 processing batch 19 of 293 - accuracy= 44.375 - loss: 9.54468 processing batch 20 of 293 - accuracy= 45.238 - loss: 9.50856 processing batch 21 of 293 - accuracy= 45.455 - loss: 9.48154 processing batch 22 of 293 - accuracy= 45.109 - loss: 9.51383 processing batch 23 of 293 - accuracy= 45.833 - loss: 9.53927 processing batch 24 of 293 - accuracy= 46.000 - loss: 9.50877 processing batch 25 of 293 - accuracy= 47.115 - loss: 9.47603 processing batch 26 of 293 - accuracy= 47.685 - loss: 9.47841 processing batch 27 of 293 - accuracy= 49.107 - loss: 9.45151 processing batch 28 of 293 - accuracy= 49.138 - loss: 9.46308 processing batch 29 of 293 - accuracy= 49.583 - loss: 9.45532 processing batch 30 of 293 - accuracy= 48.387 - loss: 9.51719 processing batch 31 of 293 - accuracy= 48.828 - loss: 9.49041 processing batch 32 of 293 - accuracy= 49.621 - loss: 9.45157 processing batch 33 of 293 - accuracy= 49.632 - loss: 9.43497 processing batch 34 of 293 - accuracy= 50.714 - loss: 9.41992 processing batch 35 of 293 - accuracy= 50.000 - loss: 9.42696 processing batch 36 of 293 - accuracy= 50.676 - loss: 9.40212 processing batch 37 of 293 - accuracy= 50.987 - loss: 9.39831 processing batch 38 of 293 - accuracy= 51.282 - loss: 9.39649 processing batch 39 of 293 - accuracy= 51.250 - loss: 9.38839 processing batch 40 of 293 - accuracy= 51.524 - loss: 9.37482 processing batch 41 of 293 - accuracy= 51.488 - loss: 9.37095 processing batch 42 of 293 - accuracy= 52.326 - loss: 9.34128 processing batch 43 of 293 - accuracy= 52.841 - loss: 9.33100 processing batch 44 of 293 - accuracy= 53.056 - loss: 9.32090 processing batch 45 of 293 - accuracy= 52.717 - loss: 9.32131 processing batch 46 of 293 - accuracy= 52.660 - loss: 9.31383 processing batch 47 of 293 - accuracy= 52.604 - loss: 9.30408 processing batch 48 of 293 - accuracy= 52.806 - loss: 9.28744 processing batch 49 of 293 - accuracy= 52.500 - loss: 9.30224 processing batch 50 of 293 - accuracy= 52.451 - loss: 9.29040 processing batch 51 of 293 - accuracy= 52.885 - loss: 9.26920 processing batch 52 of 293 - accuracy= 52.830 - loss: 9.26333 processing batch 53 of 293 - accuracy= 53.241 - loss: 9.24899 processing batch 54 of 293 - accuracy= 53.409 - loss: 9.22800 processing batch 55 of 293 - accuracy= 53.348 - loss: 9.23940 processing batch 56 of 293 - accuracy= 53.289 - loss: 9.23702 processing batch 57 of 293 - accuracy= 53.664 - loss: 9.21659 processing batch 58 of 293 - accuracy= 53.814 - loss: 9.20226 processing batch 59 of 293 - accuracy= 53.958 - loss: 9.18695 processing batch 60 of 293 - accuracy= 53.893 - loss: 9.17329 processing batch 61 of 293 - accuracy= 54.032 - loss: 9.16993 processing batch 62 of 293 - accuracy= 53.770 - loss: 9.16770 processing batch 63 of 293 - accuracy= 53.906 - loss: 9.16046 processing batch 64 of 293 - accuracy= 53.462 - loss: 9.18062 processing batch 65 of 293 - accuracy= 53.598 - loss: 9.16652 processing batch 66 of 293 - accuracy= 53.358 - loss: 9.16639 processing batch 67 of 293 - accuracy= 53.676 - loss: 9.14772 processing batch 68 of 293 - accuracy= 53.804 - loss: 9.13180 processing batch 69 of 293 - accuracy= 53.929 - loss: 9.12298 processing batch 70 of 293 - accuracy= 54.225 - loss: 9.11247 processing batch 71 of 293 - accuracy= 54.340 - loss: 9.11283 processing batch 72 of 293 - accuracy= 53.938 - loss: 9.12304 processing batch 73 of 293 - accuracy= 53.885 - loss: 9.12016 processing batch 74 of 293 - accuracy= 54.000 - loss: 9.11378 processing batch 75 of 293 - accuracy= 54.276 - loss: 9.09480 processing batch 76 of 293 - accuracy= 54.383 - loss: 9.08543 processing batch 77 of 293 - accuracy= 54.647 - loss: 9.07750 processing batch 78 of 293 - accuracy= 54.747 - loss: 9.07066 processing batch 79 of 293 - accuracy= 54.844 - loss: 9.06056 processing batch 80 of 293 - accuracy= 54.938 - loss: 9.05124 processing batch 81 of 293 - accuracy= 55.183 - loss: 9.03850 processing batch 82 of 293 - accuracy= 55.271 - loss: 9.03047 processing batch 83 of 293 - accuracy= 55.060 - loss: 9.02321 processing batch 84 of 293 - accuracy= 55.294 - loss: 9.01994 processing batch 85 of 293 - accuracy= 55.378 - loss: 9.01324 processing batch 86 of 293 - accuracy= 55.460 - loss: 9.01258 processing batch 87 of 293 - accuracy= 55.398 - loss: 9.00478 processing batch 88 of 293 - accuracy= 55.197 - loss: 9.00837 processing batch 89 of 293 - accuracy= 55.139 - loss: 9.01707 processing batch 90 of 293 - accuracy= 55.082 - loss: 9.01623 processing batch 91 of 293 - accuracy= 55.163 - loss: 9.00487 processing batch 92 of 293 - accuracy= 55.242 - loss: 8.99759 processing batch 93 of 293 - accuracy= 55.319 - loss: 8.98819 processing batch 94 of 293 - accuracy= 55.263 - loss: 8.99025 processing batch 95 of 293 - accuracy= 55.469 - loss: 8.97663 processing batch 96 of 293 - accuracy= 55.670 - loss: 8.96637 processing batch 97 of 293 - accuracy= 55.612 - loss: 8.96282 processing batch 98 of 293 - accuracy= 55.682 - loss: 8.95645 processing batch 99 of 293 - accuracy= 55.625 - loss: 8.94941 processing batch 100 of 293 - accuracy= 55.693 - loss: 8.94577 processing batch 101 of 293 - accuracy= 55.637 - loss: 8.93888 processing batch 102 of 293 - accuracy= 55.704 - loss: 8.92824 processing batch 103 of 293 - accuracy= 55.649 - loss: 8.92540 processing batch 104 of 293 - accuracy= 55.714 - loss: 8.91603 processing batch 105 of 293 - accuracy= 55.660 - loss: 8.91700 processing batch 106 of 293 - accuracy= 55.724 - loss: 8.90591 processing batch 107 of 293 - accuracy= 55.787 - loss: 8.89838 processing batch 108 of 293 - accuracy= 55.849 - loss: 8.89513 processing batch 109 of 293 - accuracy= 55.909 - loss: 8.88606 processing batch 110 of 293 - accuracy= 55.856 - loss: 8.88022 processing batch 111 of 293 - accuracy= 56.027 - loss: 8.87007 processing batch 112 of 293 - accuracy= 56.195 - loss: 8.85754 processing batch 113 of 293 - accuracy= 56.250 - loss: 8.84758 processing batch 114 of 293 - accuracy= 56.304 - loss: 8.83774 processing batch 115 of 293 - accuracy= 56.466 - loss: 8.82660 processing batch 116 of 293 - accuracy= 56.731 - loss: 8.81505 processing batch 117 of 293 - accuracy= 56.886 - loss: 8.80511 processing batch 118 of 293 - accuracy= 56.828 - loss: 8.80592 processing batch 119 of 293 - accuracy= 56.979 - loss: 8.79897 processing batch 120 of 293 - accuracy= 56.921 - loss: 8.80308 processing batch 121 of 293 - accuracy= 56.865 - loss: 8.80721 processing batch 122 of 293 - accuracy= 56.809 - loss: 8.79981 processing batch 123 of 293 - accuracy= 56.956 - loss: 8.78906 processing batch 124 of 293 - accuracy= 57.000 - loss: 8.78307 processing batch 125 of 293 - accuracy= 57.044 - loss: 8.77454 processing batch 126 of 293 - accuracy= 57.087 - loss: 8.76414 processing batch 127 of 293 - accuracy= 56.934 - loss: 8.75937 processing batch 128 of 293 - accuracy= 57.267 - loss: 8.74696 processing batch 129 of 293 - accuracy= 57.308 - loss: 8.74932 processing batch 130 of 293 - accuracy= 57.347 - loss: 8.74023 processing batch 131 of 293 - accuracy= 57.481 - loss: 8.73021 processing batch 132 of 293 - accuracy= 57.425 - loss: 8.73155 processing batch 133 of 293 - accuracy= 57.463 - loss: 8.72803 processing batch 134 of 293 - accuracy= 57.500 - loss: 8.72199 processing batch 135 of 293 - accuracy= 57.629 - loss: 8.71047 processing batch 136 of 293 - accuracy= 57.573 - loss: 8.71098 processing batch 137 of 293 - accuracy= 57.699 - loss: 8.70145 processing batch 138 of 293 - accuracy= 57.824 - loss: 8.69205 processing batch 139 of 293 - accuracy= 57.946 - loss: 8.68265 processing batch 140 of 293 - accuracy= 58.156 - loss: 8.67531 processing batch 141 of 293 - accuracy= 58.275 - loss: 8.66782 processing batch 142 of 293 - accuracy= 58.304 - loss: 8.66106 processing batch 143 of 293 - accuracy= 58.333 - loss: 8.65326 processing batch 144 of 293 - accuracy= 58.362 - loss: 8.64722 processing batch 145 of 293 - accuracy= 58.390 - loss: 8.63860 processing batch 146 of 293 - accuracy= 58.503 - loss: 8.63105 processing batch 147 of 293 - accuracy= 58.530 - loss: 8.62246 processing batch 148 of 293 - accuracy= 58.725 - loss: 8.61166 processing batch 149 of 293 - accuracy= 58.833 - loss: 8.60619 processing batch 150 of 293 - accuracy= 58.940 - loss: 8.59958 processing batch 151 of 293 - accuracy= 58.964 - loss: 8.59462 processing batch 152 of 293 - accuracy= 58.905 - loss: 8.59093 processing batch 153 of 293 - accuracy= 59.010 - loss: 8.58114 processing batch 154 of 293 - accuracy= 58.790 - loss: 8.58293 processing batch 155 of 293 - accuracy= 58.974 - loss: 8.57460 processing batch 156 of 293 - accuracy= 59.156 - loss: 8.56557 processing batch 157 of 293 - accuracy= 59.256 - loss: 8.55906 processing batch 158 of 293 - accuracy= 59.119 - loss: 8.55729 processing batch 159 of 293 - accuracy= 59.219 - loss: 8.55113 processing batch 160 of 293 - accuracy= 59.161 - loss: 8.55043 processing batch 161 of 293 - accuracy= 59.105 - loss: 8.54808 processing batch 162 of 293 - accuracy= 59.126 - loss: 8.54650 processing batch 163 of 293 - accuracy= 59.375 - loss: 8.53651 processing batch 164 of 293 - accuracy= 59.318 - loss: 8.53302 processing batch 165 of 293 - accuracy= 59.337 - loss: 8.52944 processing batch 166 of 293 - accuracy= 59.207 - loss: 8.52604 processing batch 167 of 293 - accuracy= 59.077 - loss: 8.52422 processing batch 168 of 293 - accuracy= 59.024 - loss: 8.52075 processing batch 169 of 293 - accuracy= 59.044 - loss: 8.51560 processing batch 170 of 293 - accuracy= 58.845 - loss: 8.51457 processing batch 171 of 293 - accuracy= 58.939 - loss: 8.50811 processing batch 172 of 293 - accuracy= 58.960 - loss: 8.50252 processing batch 173 of 293 - accuracy= 58.980 - loss: 8.49671 processing batch 174 of 293 - accuracy= 59.000 - loss: 8.49008 processing batch 175 of 293 - accuracy= 59.020 - loss: 8.48341 processing batch 176 of 293 - accuracy= 58.969 - loss: 8.48172 processing batch 177 of 293 - accuracy= 59.059 - loss: 8.47390 processing batch 178 of 293 - accuracy= 59.008 - loss: 8.47103 processing batch 179 of 293 - accuracy= 59.167 - loss: 8.46324 processing batch 180 of 293 - accuracy= 59.116 - loss: 8.45765 processing batch 181 of 293 - accuracy= 59.135 - loss: 8.45057 processing batch 182 of 293 - accuracy= 59.290 - loss: 8.44134 processing batch 183 of 293 - accuracy= 59.375 - loss: 8.43454 processing batch 184 of 293 - accuracy= 59.257 - loss: 8.43309 processing batch 185 of 293 - accuracy= 59.409 - loss: 8.42556 processing batch 186 of 293 - accuracy= 59.492 - loss: 8.41901 processing batch 187 of 293 - accuracy= 59.508 - loss: 8.41498 processing batch 188 of 293 - accuracy= 59.590 - loss: 8.40927 processing batch 189 of 293 - accuracy= 59.605 - loss: 8.40536 processing batch 190 of 293 - accuracy= 59.686 - loss: 8.39883 processing batch 191 of 293 - accuracy= 59.766 - loss: 8.39263 processing batch 192 of 293 - accuracy= 59.845 - loss: 8.38661 processing batch 193 of 293 - accuracy= 59.923 - loss: 8.37895 processing batch 194 of 293 - accuracy= 60.000 - loss: 8.37227 processing batch 195 of 293 - accuracy= 60.140 - loss: 8.36342 processing batch 196 of 293 - accuracy= 60.152 - loss: 8.35882 processing batch 197 of 293 - accuracy= 60.290 - loss: 8.35182 processing batch 198 of 293 - accuracy= 60.364 - loss: 8.34505 processing batch 199 of 293 - accuracy= 60.375 - loss: 8.33964 processing batch 200 of 293 - accuracy= 60.386 - loss: 8.33511 processing batch 201 of 293 - accuracy= 60.458 - loss: 8.32839 processing batch 202 of 293 - accuracy= 60.468 - loss: 8.32251 processing batch 203 of 293 - accuracy= 60.600 - loss: 8.31536 processing batch 204 of 293 - accuracy= 60.732 - loss: 8.30867 processing batch 205 of 293 - accuracy= 60.801 - loss: 8.30419 processing batch 206 of 293 - accuracy= 60.870 - loss: 8.29694 processing batch 207 of 293 - accuracy= 60.877 - loss: 8.29374 processing batch 208 of 293 - accuracy= 60.945 - loss: 8.28759 processing batch 209 of 293 - accuracy= 61.131 - loss: 8.27944 processing batch 210 of 293 - accuracy= 61.256 - loss: 8.27212 processing batch 211 of 293 - accuracy= 61.203 - loss: 8.27060 processing batch 212 of 293 - accuracy= 61.326 - loss: 8.26330 processing batch 213 of 293 - accuracy= 61.273 - loss: 8.26004 processing batch 214 of 293 - accuracy= 61.221 - loss: 8.26092 processing batch 215 of 293 - accuracy= 61.169 - loss: 8.25982 processing batch 216 of 293 - accuracy= 61.233 - loss: 8.25406 processing batch 217 of 293 - accuracy= 61.239 - loss: 8.24950 processing batch 218 of 293 - accuracy= 61.301 - loss: 8.24481 processing batch 219 of 293 - accuracy= 61.307 - loss: 8.23889 processing batch 220 of 293 - accuracy= 61.369 - loss: 8.23263 processing batch 221 of 293 - accuracy= 61.486 - loss: 8.22592 processing batch 222 of 293 - accuracy= 61.603 - loss: 8.21955 processing batch 223 of 293 - accuracy= 61.719 - loss: 8.21313 processing batch 224 of 293 - accuracy= 61.722 - loss: 8.20773 processing batch 225 of 293 - accuracy= 61.726 - loss: 8.20524 processing batch 226 of 293 - accuracy= 61.784 - loss: 8.20192 processing batch 227 of 293 - accuracy= 61.897 - loss: 8.19534 processing batch 228 of 293 - accuracy= 62.009 - loss: 8.18782 processing batch 229 of 293 - accuracy= 62.011 - loss: 8.18762 processing batch 230 of 293 - accuracy= 62.013 - loss: 8.18433 processing batch 231 of 293 - accuracy= 62.069 - loss: 8.17965 processing batch 232 of 293 - accuracy= 62.178 - loss: 8.17303 processing batch 233 of 293 - accuracy= 62.233 - loss: 8.16809 processing batch 234 of 293 - accuracy= 62.128 - loss: 8.16732 processing batch 235 of 293 - accuracy= 62.235 - loss: 8.16012 processing batch 236 of 293 - accuracy= 62.289 - loss: 8.15426 processing batch 237 of 293 - accuracy= 62.132 - loss: 8.16019 processing batch 238 of 293 - accuracy= 62.134 - loss: 8.15565 processing batch 239 of 293 - accuracy= 62.187 - loss: 8.14974 processing batch 240 of 293 - accuracy= 62.189 - loss: 8.14588 processing batch 241 of 293 - accuracy= 62.293 - loss: 8.13927 processing batch 242 of 293 - accuracy= 62.294 - loss: 8.14052 processing batch 243 of 293 - accuracy= 62.244 - loss: 8.13599 processing batch 244 of 293 - accuracy= 62.245 - loss: 8.13301 processing batch 245 of 293 - accuracy= 62.246 - loss: 8.12869 processing batch 246 of 293 - accuracy= 62.146 - loss: 8.12509 processing batch 247 of 293 - accuracy= 62.198 - loss: 8.11955 processing batch 248 of 293 - accuracy= 62.199 - loss: 8.11526 processing batch 249 of 293 - accuracy= 62.250 - loss: 8.10999 processing batch 250 of 293 - accuracy= 62.251 - loss: 8.10477 processing batch 251 of 293 - accuracy= 62.302 - loss: 8.09964 processing batch 252 of 293 - accuracy= 62.302 - loss: 8.09549 processing batch 253 of 293 - accuracy= 62.156 - loss: 8.09499 processing batch 254 of 293 - accuracy= 62.108 - loss: 8.09128 processing batch 255 of 293 - accuracy= 62.012 - loss: 8.08720 processing batch 256 of 293 - accuracy= 62.014 - loss: 8.08160 processing batch 257 of 293 - accuracy= 62.112 - loss: 8.07600 processing batch 258 of 293 - accuracy= 62.114 - loss: 8.07491 processing batch 259 of 293 - accuracy= 62.067 - loss: 8.07184 processing batch 260 of 293 - accuracy= 62.069 - loss: 8.06656 processing batch 261 of 293 - accuracy= 62.071 - loss: 8.06326 processing batch 262 of 293 - accuracy= 62.120 - loss: 8.05919 processing batch 263 of 293 - accuracy= 62.216 - loss: 8.05240 processing batch 264 of 293 - accuracy= 62.264 - loss: 8.04687 processing batch 265 of 293 - accuracy= 62.312 - loss: 8.04241 processing batch 266 of 293 - accuracy= 62.453 - loss: 8.03609 processing batch 267 of 293 - accuracy= 62.407 - loss: 8.03296 processing batch 268 of 293 - accuracy= 62.454 - loss: 8.02765 processing batch 269 of 293 - accuracy= 62.361 - loss: 8.02624 processing batch 270 of 293 - accuracy= 62.269 - loss: 8.02286 processing batch 271 of 293 - accuracy= 62.270 - loss: 8.01789 processing batch 272 of 293 - accuracy= 62.225 - loss: 8.01660 processing batch 273 of 293 - accuracy= 62.272 - loss: 8.01120 processing batch 274 of 293 - accuracy= 62.227 - loss: 8.00838 processing batch 275 of 293 - accuracy= 62.228 - loss: 8.00736 processing batch 276 of 293 - accuracy= 62.139 - loss: 8.00536 processing batch 277 of 293 - accuracy= 62.095 - loss: 8.00272 processing batch 278 of 293 - accuracy= 62.097 - loss: 8.00024 processing batch 279 of 293 - accuracy= 62.098 - loss: 7.99495 processing batch 280 of 293 - accuracy= 62.144 - loss: 7.98947 processing batch 281 of 293 - accuracy= 62.101 - loss: 7.98610 processing batch 282 of 293 - accuracy= 62.014 - loss: 7.98850 processing batch 283 of 293 - accuracy= 62.016 - loss: 7.98378 processing batch 284 of 293 - accuracy= 61.930 - loss: 7.98264 processing batch 285 of 293 - accuracy= 61.888 - loss: 7.97831 processing batch 286 of 293 - accuracy= 61.934 - loss: 7.97333 processing batch 287 of 293 - accuracy= 61.936 - loss: 7.96967 processing batch 288 of 293 - accuracy= 62.024 - loss: 7.96328 processing batch 289 of 293 - accuracy= 62.112 - loss: 7.95734 processing batch 290 of 293 - accuracy= 62.156 - loss: 7.95248 processing batch 291 of 293 - accuracy= 62.115 - loss: 7.94983 processing batch 292 of 293 - accuracy= 62.159 - loss: 7.94384 1 /40 7.944 62.159 8.64027 48.376 0.00100 0.00100 accuracy 0.00 151.16 \n293/293 [==============================] - 151s 288ms/step - loss: 7.9438 - accuracy: 0.6216 - val_loss: 8.6403 - val_accuracy: 0.4838\nEpoch 2/40\n293/293 [==============================] - ETA: 0s - loss: 5.7542 - accuracy: 0.7180 669 processing batch 1 of 293 - accuracy= 62.500 - loss: 6.67405 processing batch 2 of 293 - accuracy= 66.667 - loss: 6.58188 processing batch 3 of 293 - accuracy= 65.625 - loss: 6.65114 processing batch 4 of 293 - accuracy= 67.500 - loss: 6.57799 processing batch 5 of 293 - accuracy= 64.583 - loss: 6.60540 processing batch 6 of 293 - accuracy= 66.071 - loss: 6.63774 processing batch 7 of 293 - accuracy= 64.062 - loss: 6.64904 processing batch 8 of 293 - accuracy= 63.889 - loss: 6.66553 processing batch 9 of 293 - accuracy= 61.250 - loss: 6.70221 processing batch 10 of 293 - accuracy= 63.636 - loss: 6.65601 processing batch 11 of 293 - accuracy= 65.625 - loss: 6.64950 processing batch 12 of 293 - accuracy= 65.385 - loss: 6.62826 processing batch 13 of 293 - accuracy= 66.071 - loss: 6.61725 processing batch 14 of 293 - accuracy= 66.667 - loss: 6.61349 processing batch 15 of 293 - accuracy= 67.969 - loss: 6.57269 processing batch 16 of 293 - accuracy= 66.912 - loss: 6.58754 processing batch 17 of 293 - accuracy= 67.361 - loss: 6.58124 processing batch 18 of 293 - accuracy= 67.105 - loss: 6.59409 processing batch 19 of 293 - accuracy= 66.875 - loss: 6.60034 processing batch 20 of 293 - accuracy= 66.667 - loss: 6.59797 processing batch 21 of 293 - accuracy= 66.477 - loss: 6.58316 processing batch 22 of 293 - accuracy= 66.848 - loss: 6.57108 processing batch 23 of 293 - accuracy= 66.667 - loss: 6.57289 processing batch 24 of 293 - accuracy= 67.000 - loss: 6.56072 processing batch 25 of 293 - accuracy= 67.788 - loss: 6.54857 processing batch 26 of 293 - accuracy= 67.593 - loss: 6.55402 processing batch 27 of 293 - accuracy= 67.411 - loss: 6.55991 processing batch 28 of 293 - accuracy= 68.103 - loss: 6.55522 processing batch 29 of 293 - accuracy= 67.917 - loss: 6.55930 processing batch 30 of 293 - accuracy= 68.548 - loss: 6.54506 processing batch 31 of 293 - accuracy= 67.969 - loss: 6.54439 processing batch 32 of 293 - accuracy= 67.803 - loss: 6.53653 processing batch 33 of 293 - accuracy= 68.382 - loss: 6.52798 processing batch 34 of 293 - accuracy= 68.571 - loss: 6.51912 processing batch 35 of 293 - accuracy= 68.056 - loss: 6.52529 processing batch 36 of 293 - accuracy= 68.581 - loss: 6.51745 processing batch 37 of 293 - accuracy= 68.421 - loss: 6.51953 processing batch 38 of 293 - accuracy= 68.269 - loss: 6.51910 processing batch 39 of 293 - accuracy= 68.750 - loss: 6.50327 processing batch 40 of 293 - accuracy= 69.207 - loss: 6.48799 processing batch 41 of 293 - accuracy= 69.345 - loss: 6.47584 processing batch 42 of 293 - accuracy= 68.605 - loss: 6.48211 processing batch 43 of 293 - accuracy= 68.182 - loss: 6.49535 processing batch 44 of 293 - accuracy= 68.889 - loss: 6.47956 processing batch 45 of 293 - accuracy= 68.750 - loss: 6.48172 processing batch 46 of 293 - accuracy= 68.617 - loss: 6.48271 processing batch 47 of 293 - accuracy= 69.010 - loss: 6.47566 processing batch 48 of 293 - accuracy= 69.643 - loss: 6.46603 processing batch 49 of 293 - accuracy= 70.000 - loss: 6.45494 processing batch 50 of 293 - accuracy= 69.853 - loss: 6.45885 processing batch 51 of 293 - accuracy= 69.712 - loss: 6.45890 processing batch 52 of 293 - accuracy= 69.104 - loss: 6.46463 processing batch 53 of 293 - accuracy= 69.676 - loss: 6.45108 processing batch 54 of 293 - accuracy= 69.545 - loss: 6.45385 processing batch 55 of 293 - accuracy= 69.643 - loss: 6.44479 processing batch 56 of 293 - accuracy= 69.518 - loss: 6.44237 processing batch 57 of 293 - accuracy= 69.612 - loss: 6.43454 processing batch 58 of 293 - accuracy= 69.703 - loss: 6.43077 processing batch 59 of 293 - accuracy= 70.000 - loss: 6.42023 processing batch 60 of 293 - accuracy= 70.082 - loss: 6.41352 processing batch 61 of 293 - accuracy= 69.960 - loss: 6.40664 processing batch 62 of 293 - accuracy= 70.040 - loss: 6.39993 processing batch 63 of 293 - accuracy= 70.117 - loss: 6.39185 processing batch 64 of 293 - accuracy= 70.577 - loss: 6.37997 processing batch 65 of 293 - accuracy= 70.833 - loss: 6.37028 processing batch 66 of 293 - accuracy= 70.896 - loss: 6.36432 processing batch 67 of 293 - accuracy= 70.772 - loss: 6.36154 processing batch 68 of 293 - accuracy= 70.471 - loss: 6.37232 processing batch 69 of 293 - accuracy= 70.714 - loss: 6.36639 processing batch 70 of 293 - accuracy= 70.599 - loss: 6.37229 processing batch 71 of 293 - accuracy= 70.833 - loss: 6.36461 processing batch 72 of 293 - accuracy= 70.890 - loss: 6.36170 processing batch 73 of 293 - accuracy= 70.946 - loss: 6.35518 processing batch 74 of 293 - accuracy= 71.000 - loss: 6.35264 processing batch 75 of 293 - accuracy= 71.053 - loss: 6.36866 processing batch 76 of 293 - accuracy= 71.104 - loss: 6.36101 processing batch 77 of 293 - accuracy= 70.994 - loss: 6.35887 processing batch 78 of 293 - accuracy= 70.886 - loss: 6.35677 processing batch 79 of 293 - accuracy= 70.938 - loss: 6.35403 processing batch 80 of 293 - accuracy= 70.679 - loss: 6.35965 processing batch 81 of 293 - accuracy= 70.427 - loss: 6.36066 processing batch 82 of 293 - accuracy= 70.482 - loss: 6.35863 processing batch 83 of 293 - accuracy= 70.387 - loss: 6.35672 processing batch 84 of 293 - accuracy= 70.441 - loss: 6.35078 processing batch 85 of 293 - accuracy= 70.349 - loss: 6.34692 processing batch 86 of 293 - accuracy= 70.259 - loss: 6.34669 processing batch 87 of 293 - accuracy= 70.028 - loss: 6.34433 processing batch 88 of 293 - accuracy= 70.225 - loss: 6.33643 processing batch 89 of 293 - accuracy= 70.278 - loss: 6.33007 processing batch 90 of 293 - accuracy= 70.192 - loss: 6.32790 processing batch 91 of 293 - accuracy= 70.245 - loss: 6.32423 processing batch 92 of 293 - accuracy= 70.296 - loss: 6.32291 processing batch 93 of 293 - accuracy= 70.346 - loss: 6.31660 processing batch 94 of 293 - accuracy= 70.395 - loss: 6.31381 processing batch 95 of 293 - accuracy= 70.052 - loss: 6.32606 processing batch 96 of 293 - accuracy= 69.974 - loss: 6.32170 processing batch 97 of 293 - accuracy= 70.026 - loss: 6.31717 processing batch 98 of 293 - accuracy= 70.076 - loss: 6.31914 processing batch 99 of 293 - accuracy= 70.000 - loss: 6.31700 processing batch 100 of 293 - accuracy= 69.926 - loss: 6.31136 processing batch 101 of 293 - accuracy= 69.730 - loss: 6.31290 processing batch 102 of 293 - accuracy= 69.660 - loss: 6.31391 processing batch 103 of 293 - accuracy= 69.832 - loss: 6.30744 processing batch 104 of 293 - accuracy= 69.762 - loss: 6.30608 processing batch 105 of 293 - accuracy= 69.693 - loss: 6.30365 processing batch 106 of 293 - accuracy= 69.977 - loss: 6.29571 processing batch 107 of 293 - accuracy= 70.023 - loss: 6.29433 processing batch 108 of 293 - accuracy= 70.069 - loss: 6.28786 processing batch 109 of 293 - accuracy= 70.227 - loss: 6.28332 processing batch 110 of 293 - accuracy= 70.158 - loss: 6.28169 processing batch 111 of 293 - accuracy= 70.312 - loss: 6.27512 processing batch 112 of 293 - accuracy= 70.575 - loss: 6.26750 processing batch 113 of 293 - accuracy= 70.614 - loss: 6.26385 processing batch 114 of 293 - accuracy= 70.652 - loss: 6.26034 processing batch 115 of 293 - accuracy= 70.474 - loss: 6.26169 processing batch 116 of 293 - accuracy= 70.726 - loss: 6.25398 processing batch 117 of 293 - accuracy= 70.869 - loss: 6.25099 processing batch 118 of 293 - accuracy= 70.903 - loss: 6.24711 processing batch 119 of 293 - accuracy= 70.938 - loss: 6.24616 processing batch 120 of 293 - accuracy= 70.868 - loss: 6.24561 processing batch 121 of 293 - accuracy= 70.594 - loss: 6.24742 processing batch 122 of 293 - accuracy= 70.630 - loss: 6.24165 processing batch 123 of 293 - accuracy= 70.766 - loss: 6.23575 processing batch 124 of 293 - accuracy= 70.400 - loss: 6.24426 processing batch 125 of 293 - accuracy= 70.437 - loss: 6.24097 processing batch 126 of 293 - accuracy= 70.571 - loss: 6.23562 processing batch 127 of 293 - accuracy= 70.312 - loss: 6.24272 processing batch 128 of 293 - accuracy= 70.349 - loss: 6.23880 processing batch 129 of 293 - accuracy= 70.577 - loss: 6.23220 processing batch 130 of 293 - accuracy= 70.515 - loss: 6.22941 processing batch 131 of 293 - accuracy= 70.549 - loss: 6.22601 processing batch 132 of 293 - accuracy= 70.677 - loss: 6.22338 processing batch 133 of 293 - accuracy= 70.709 - loss: 6.21943 processing batch 134 of 293 - accuracy= 70.741 - loss: 6.21475 processing batch 135 of 293 - accuracy= 70.588 - loss: 6.21162 processing batch 136 of 293 - accuracy= 70.712 - loss: 6.20792 processing batch 137 of 293 - accuracy= 70.743 - loss: 6.20460 processing batch 138 of 293 - accuracy= 70.773 - loss: 6.20276 processing batch 139 of 293 - accuracy= 70.625 - loss: 6.20054 processing batch 140 of 293 - accuracy= 70.745 - loss: 6.19534 processing batch 141 of 293 - accuracy= 70.863 - loss: 6.18969 processing batch 142 of 293 - accuracy= 70.804 - loss: 6.18693 processing batch 143 of 293 - accuracy= 70.747 - loss: 6.18305 processing batch 144 of 293 - accuracy= 70.776 - loss: 6.17874 processing batch 145 of 293 - accuracy= 70.805 - loss: 6.17413 processing batch 146 of 293 - accuracy= 70.833 - loss: 6.16929 processing batch 147 of 293 - accuracy= 70.861 - loss: 6.16540 processing batch 148 of 293 - accuracy= 70.889 - loss: 6.16095 processing batch 149 of 293 - accuracy= 70.833 - loss: 6.15837 processing batch 150 of 293 - accuracy= 70.861 - loss: 6.15571 processing batch 151 of 293 - accuracy= 70.888 - loss: 6.15226 processing batch 152 of 293 - accuracy= 70.833 - loss: 6.15478 processing batch 153 of 293 - accuracy= 70.860 - loss: 6.15155 processing batch 154 of 293 - accuracy= 70.887 - loss: 6.14858 processing batch 155 of 293 - accuracy= 70.913 - loss: 6.14524 processing batch 156 of 293 - accuracy= 70.860 - loss: 6.14383 processing batch 157 of 293 - accuracy= 70.965 - loss: 6.13821 processing batch 158 of 293 - accuracy= 70.991 - loss: 6.13831 processing batch 159 of 293 - accuracy= 71.094 - loss: 6.13423 processing batch 160 of 293 - accuracy= 71.273 - loss: 6.12768 processing batch 161 of 293 - accuracy= 71.065 - loss: 6.12959 processing batch 162 of 293 - accuracy= 71.089 - loss: 6.12780 processing batch 163 of 293 - accuracy= 71.113 - loss: 6.12525 processing batch 164 of 293 - accuracy= 71.288 - loss: 6.11882 processing batch 165 of 293 - accuracy= 71.461 - loss: 6.11301 processing batch 166 of 293 - accuracy= 71.632 - loss: 6.10674 processing batch 167 of 293 - accuracy= 71.503 - loss: 6.10745 processing batch 168 of 293 - accuracy= 71.598 - loss: 6.10354 processing batch 169 of 293 - accuracy= 71.618 - loss: 6.10025 processing batch 170 of 293 - accuracy= 71.564 - loss: 6.09694 processing batch 171 of 293 - accuracy= 71.584 - loss: 6.09348 processing batch 172 of 293 - accuracy= 71.676 - loss: 6.08943 processing batch 173 of 293 - accuracy= 71.767 - loss: 6.08655 processing batch 174 of 293 - accuracy= 71.714 - loss: 6.08556 processing batch 175 of 293 - accuracy= 71.591 - loss: 6.08379 processing batch 176 of 293 - accuracy= 71.681 - loss: 6.07852 processing batch 177 of 293 - accuracy= 71.629 - loss: 6.07654 processing batch 178 of 293 - accuracy= 71.648 - loss: 6.07463 processing batch 179 of 293 - accuracy= 71.736 - loss: 6.07094 processing batch 180 of 293 - accuracy= 71.685 - loss: 6.06755 processing batch 181 of 293 - accuracy= 71.635 - loss: 6.06415 processing batch 182 of 293 - accuracy= 71.585 - loss: 6.06236 processing batch 183 of 293 - accuracy= 71.603 - loss: 6.06054 processing batch 184 of 293 - accuracy= 71.486 - loss: 6.05964 processing batch 185 of 293 - accuracy= 71.573 - loss: 6.05518 processing batch 186 of 293 - accuracy= 71.658 - loss: 6.05228 processing batch 187 of 293 - accuracy= 71.543 - loss: 6.05069 processing batch 188 of 293 - accuracy= 71.561 - loss: 6.04691 processing batch 189 of 293 - accuracy= 71.579 - loss: 6.04365 processing batch 190 of 293 - accuracy= 71.597 - loss: 6.04087 processing batch 191 of 293 - accuracy= 71.615 - loss: 6.03655 processing batch 192 of 293 - accuracy= 71.373 - loss: 6.03766 processing batch 193 of 293 - accuracy= 71.392 - loss: 6.03691 processing batch 194 of 293 - accuracy= 71.346 - loss: 6.03413 processing batch 195 of 293 - accuracy= 71.365 - loss: 6.03161 processing batch 196 of 293 - accuracy= 71.510 - loss: 6.02603 processing batch 197 of 293 - accuracy= 71.654 - loss: 6.02036 processing batch 198 of 293 - accuracy= 71.734 - loss: 6.01690 processing batch 199 of 293 - accuracy= 71.625 - loss: 6.01624 processing batch 200 of 293 - accuracy= 71.704 - loss: 6.01165 processing batch 201 of 293 - accuracy= 71.597 - loss: 6.01258 processing batch 202 of 293 - accuracy= 71.613 - loss: 6.00857 processing batch 203 of 293 - accuracy= 71.691 - loss: 6.00520 processing batch 204 of 293 - accuracy= 71.768 - loss: 6.00064 processing batch 205 of 293 - accuracy= 71.845 - loss: 5.99666 processing batch 206 of 293 - accuracy= 71.920 - loss: 5.99161 processing batch 207 of 293 - accuracy= 71.995 - loss: 5.98662 processing batch 208 of 293 - accuracy= 72.069 - loss: 5.98214 processing batch 209 of 293 - accuracy= 72.024 - loss: 5.97917 processing batch 210 of 293 - accuracy= 72.038 - loss: 5.97538 processing batch 211 of 293 - accuracy= 72.111 - loss: 5.97089 processing batch 212 of 293 - accuracy= 72.007 - loss: 5.97146 processing batch 213 of 293 - accuracy= 71.963 - loss: 5.96799 processing batch 214 of 293 - accuracy= 71.919 - loss: 5.96822 processing batch 215 of 293 - accuracy= 71.933 - loss: 5.96356 processing batch 216 of 293 - accuracy= 71.947 - loss: 5.96132 processing batch 217 of 293 - accuracy= 72.018 - loss: 5.95656 processing batch 218 of 293 - accuracy= 72.032 - loss: 5.95212 processing batch 219 of 293 - accuracy= 71.932 - loss: 5.95313 processing batch 220 of 293 - accuracy= 71.889 - loss: 5.95206 processing batch 221 of 293 - accuracy= 71.903 - loss: 5.94971 processing batch 222 of 293 - accuracy= 71.861 - loss: 5.94681 processing batch 223 of 293 - accuracy= 71.931 - loss: 5.94326 processing batch 224 of 293 - accuracy= 71.889 - loss: 5.94036 processing batch 225 of 293 - accuracy= 71.847 - loss: 5.93890 processing batch 226 of 293 - accuracy= 71.861 - loss: 5.93492 processing batch 227 of 293 - accuracy= 71.711 - loss: 5.93437 processing batch 228 of 293 - accuracy= 71.670 - loss: 5.93132 processing batch 229 of 293 - accuracy= 71.793 - loss: 5.92657 processing batch 230 of 293 - accuracy= 71.807 - loss: 5.92298 processing batch 231 of 293 - accuracy= 71.767 - loss: 5.92146 processing batch 232 of 293 - accuracy= 71.674 - loss: 5.92042 processing batch 233 of 293 - accuracy= 71.741 - loss: 5.91685 processing batch 234 of 293 - accuracy= 71.702 - loss: 5.91435 processing batch 235 of 293 - accuracy= 71.769 - loss: 5.91050 processing batch 236 of 293 - accuracy= 71.783 - loss: 5.90622 processing batch 237 of 293 - accuracy= 71.849 - loss: 5.90230 processing batch 238 of 293 - accuracy= 71.862 - loss: 5.89986 processing batch 239 of 293 - accuracy= 71.927 - loss: 5.89656 processing batch 240 of 293 - accuracy= 71.940 - loss: 5.89320 processing batch 241 of 293 - accuracy= 71.952 - loss: 5.88978 processing batch 242 of 293 - accuracy= 71.862 - loss: 5.88895 processing batch 243 of 293 - accuracy= 71.926 - loss: 5.88512 processing batch 244 of 293 - accuracy= 71.888 - loss: 5.88459 processing batch 245 of 293 - accuracy= 71.900 - loss: 5.88383 processing batch 246 of 293 - accuracy= 71.964 - loss: 5.87966 processing batch 247 of 293 - accuracy= 72.026 - loss: 5.87565 processing batch 248 of 293 - accuracy= 71.988 - loss: 5.87281 processing batch 249 of 293 - accuracy= 71.850 - loss: 5.87119 processing batch 250 of 293 - accuracy= 71.763 - loss: 5.87095 processing batch 251 of 293 - accuracy= 71.726 - loss: 5.86760 processing batch 252 of 293 - accuracy= 71.789 - loss: 5.86409 processing batch 253 of 293 - accuracy= 71.703 - loss: 5.86283 processing batch 254 of 293 - accuracy= 71.716 - loss: 5.85944 processing batch 255 of 293 - accuracy= 71.680 - loss: 5.85611 processing batch 256 of 293 - accuracy= 71.693 - loss: 5.85334 processing batch 257 of 293 - accuracy= 71.802 - loss: 5.84890 processing batch 258 of 293 - accuracy= 71.863 - loss: 5.84504 processing batch 259 of 293 - accuracy= 71.827 - loss: 5.84233 processing batch 260 of 293 - accuracy= 71.791 - loss: 5.84070 processing batch 261 of 293 - accuracy= 71.851 - loss: 5.83656 processing batch 262 of 293 - accuracy= 71.911 - loss: 5.83292 processing batch 263 of 293 - accuracy= 71.875 - loss: 5.82915 processing batch 264 of 293 - accuracy= 71.792 - loss: 5.82780 processing batch 265 of 293 - accuracy= 71.758 - loss: 5.82704 processing batch 266 of 293 - accuracy= 71.629 - loss: 5.82600 processing batch 267 of 293 - accuracy= 71.735 - loss: 5.82100 processing batch 268 of 293 - accuracy= 71.747 - loss: 5.81935 processing batch 269 of 293 - accuracy= 71.759 - loss: 5.81570 processing batch 270 of 293 - accuracy= 71.771 - loss: 5.81320 processing batch 271 of 293 - accuracy= 71.737 - loss: 5.81170 processing batch 272 of 293 - accuracy= 71.749 - loss: 5.80952 processing batch 273 of 293 - accuracy= 71.852 - loss: 5.80471 processing batch 274 of 293 - accuracy= 71.818 - loss: 5.80193 processing batch 275 of 293 - accuracy= 71.875 - loss: 5.79776 processing batch 276 of 293 - accuracy= 71.931 - loss: 5.79406 processing batch 277 of 293 - accuracy= 71.897 - loss: 5.79239 processing batch 278 of 293 - accuracy= 71.909 - loss: 5.78929 processing batch 279 of 293 - accuracy= 71.964 - loss: 5.78550 processing batch 280 of 293 - accuracy= 71.886 - loss: 5.78376 processing batch 281 of 293 - accuracy= 71.941 - loss: 5.78066 processing batch 282 of 293 - accuracy= 71.908 - loss: 5.77817 processing batch 283 of 293 - accuracy= 72.007 - loss: 5.77415 processing batch 284 of 293 - accuracy= 71.974 - loss: 5.77186 processing batch 285 of 293 - accuracy= 71.941 - loss: 5.77014 processing batch 286 of 293 - accuracy= 71.908 - loss: 5.76677 processing batch 287 of 293 - accuracy= 71.962 - loss: 5.76291 processing batch 288 of 293 - accuracy= 71.886 - loss: 5.76386 processing batch 289 of 293 - accuracy= 71.853 - loss: 5.76158 processing batch 290 of 293 - accuracy= 71.864 - loss: 5.75940 processing batch 291 of 293 - accuracy= 71.832 - loss: 5.75675 processing batch 292 of 293 - accuracy= 71.800 - loss: 5.75415 2 /40 5.754 71.800 5.51278 61.368 0.00100 0.00100 accuracy 15.51 81.11 \n293/293 [==============================] - 81s 277ms/step - loss: 5.7542 - accuracy: 0.7180 - val_loss: 5.5128 - val_accuracy: 0.6137\nEpoch 3/40\n293/293 [==============================] - ETA: 0s - loss: 4.2519 - accuracy: 0.7598 687 processing batch 1 of 293 - accuracy= 68.750 - loss: 4.81295 processing batch 2 of 293 - accuracy= 79.167 - loss: 4.69871 processing batch 3 of 293 - accuracy= 81.250 - loss: 4.67993 processing batch 4 of 293 - accuracy= 82.500 - loss: 4.68361 processing batch 5 of 293 - accuracy= 75.000 - loss: 4.82565 processing batch 6 of 293 - accuracy= 76.786 - loss: 4.78623 processing batch 7 of 293 - accuracy= 78.125 - loss: 4.76267 processing batch 8 of 293 - accuracy= 77.778 - loss: 4.75653 processing batch 9 of 293 - accuracy= 77.500 - loss: 4.75791 processing batch 10 of 293 - accuracy= 76.136 - loss: 4.76962 processing batch 11 of 293 - accuracy= 78.125 - loss: 4.74212 processing batch 12 of 293 - accuracy= 79.808 - loss: 4.71832 processing batch 13 of 293 - accuracy= 80.357 - loss: 4.71101 processing batch 14 of 293 - accuracy= 80.833 - loss: 4.71116 processing batch 15 of 293 - accuracy= 82.031 - loss: 4.69688 processing batch 16 of 293 - accuracy= 80.882 - loss: 4.71962 processing batch 17 of 293 - accuracy= 80.556 - loss: 4.71924 processing batch 18 of 293 - accuracy= 79.605 - loss: 4.73790 processing batch 19 of 293 - accuracy= 80.000 - loss: 4.72611 processing batch 20 of 293 - accuracy= 79.167 - loss: 4.74650 processing batch 21 of 293 - accuracy= 78.409 - loss: 4.76855 processing batch 22 of 293 - accuracy= 78.261 - loss: 4.77309 processing batch 23 of 293 - accuracy= 78.646 - loss: 4.75391 processing batch 24 of 293 - accuracy= 79.500 - loss: 4.73318 processing batch 25 of 293 - accuracy= 77.885 - loss: 4.77999 processing batch 26 of 293 - accuracy= 78.704 - loss: 4.76769 processing batch 27 of 293 - accuracy= 77.679 - loss: 4.77164 processing batch 28 of 293 - accuracy= 77.586 - loss: 4.76632 processing batch 29 of 293 - accuracy= 77.083 - loss: 4.76659 processing batch 30 of 293 - accuracy= 76.613 - loss: 4.78321 processing batch 31 of 293 - accuracy= 76.953 - loss: 4.77579 processing batch 32 of 293 - accuracy= 77.652 - loss: 4.76370 processing batch 33 of 293 - accuracy= 76.838 - loss: 4.76626 processing batch 34 of 293 - accuracy= 76.429 - loss: 4.76927 processing batch 35 of 293 - accuracy= 75.694 - loss: 4.77475 processing batch 36 of 293 - accuracy= 76.014 - loss: 4.77843 processing batch 37 of 293 - accuracy= 76.645 - loss: 4.76716 processing batch 38 of 293 - accuracy= 76.603 - loss: 4.76568 processing batch 39 of 293 - accuracy= 76.875 - loss: 4.75795 processing batch 40 of 293 - accuracy= 76.829 - loss: 4.75527 processing batch 41 of 293 - accuracy= 76.190 - loss: 4.75893 processing batch 42 of 293 - accuracy= 75.581 - loss: 4.76237 processing batch 43 of 293 - accuracy= 75.284 - loss: 4.75876 processing batch 44 of 293 - accuracy= 74.722 - loss: 4.75838 processing batch 45 of 293 - accuracy= 74.457 - loss: 4.75758 processing batch 46 of 293 - accuracy= 74.734 - loss: 4.74826 processing batch 47 of 293 - accuracy= 74.479 - loss: 4.74443 processing batch 48 of 293 - accuracy= 74.490 - loss: 4.73738 processing batch 49 of 293 - accuracy= 74.500 - loss: 4.73917 processing batch 50 of 293 - accuracy= 75.000 - loss: 4.73281 processing batch 51 of 293 - accuracy= 75.240 - loss: 4.72903 processing batch 52 of 293 - accuracy= 75.000 - loss: 4.72988 processing batch 53 of 293 - accuracy= 75.231 - loss: 4.72468 processing batch 54 of 293 - accuracy= 75.455 - loss: 4.71784 processing batch 55 of 293 - accuracy= 75.000 - loss: 4.73802 processing batch 56 of 293 - accuracy= 75.000 - loss: 4.73918 processing batch 57 of 293 - accuracy= 75.431 - loss: 4.73035 processing batch 58 of 293 - accuracy= 75.636 - loss: 4.72917 processing batch 59 of 293 - accuracy= 76.042 - loss: 4.71982 processing batch 60 of 293 - accuracy= 76.230 - loss: 4.71276 processing batch 61 of 293 - accuracy= 76.411 - loss: 4.70750 processing batch 62 of 293 - accuracy= 76.587 - loss: 4.70947 processing batch 63 of 293 - accuracy= 76.758 - loss: 4.70279 processing batch 64 of 293 - accuracy= 76.923 - loss: 4.69846 processing batch 65 of 293 - accuracy= 77.083 - loss: 4.69318 processing batch 66 of 293 - accuracy= 76.866 - loss: 4.69668 processing batch 67 of 293 - accuracy= 77.022 - loss: 4.69433 processing batch 68 of 293 - accuracy= 77.174 - loss: 4.69236 processing batch 69 of 293 - accuracy= 77.321 - loss: 4.68625 processing batch 70 of 293 - accuracy= 77.465 - loss: 4.68587 processing batch 71 of 293 - accuracy= 77.604 - loss: 4.67955 processing batch 72 of 293 - accuracy= 77.568 - loss: 4.67807 processing batch 73 of 293 - accuracy= 77.703 - loss: 4.67387 processing batch 74 of 293 - accuracy= 77.667 - loss: 4.67395 processing batch 75 of 293 - accuracy= 77.796 - loss: 4.67143 processing batch 76 of 293 - accuracy= 77.922 - loss: 4.67121 processing batch 77 of 293 - accuracy= 77.404 - loss: 4.67649 processing batch 78 of 293 - accuracy= 77.373 - loss: 4.67365 processing batch 79 of 293 - accuracy= 77.344 - loss: 4.67161 processing batch 80 of 293 - accuracy= 77.006 - loss: 4.67306 processing batch 81 of 293 - accuracy= 77.287 - loss: 4.66822 processing batch 82 of 293 - accuracy= 77.410 - loss: 4.66426 processing batch 83 of 293 - accuracy= 77.381 - loss: 4.66138 processing batch 84 of 293 - accuracy= 77.059 - loss: 4.66615 processing batch 85 of 293 - accuracy= 77.035 - loss: 4.66525 processing batch 86 of 293 - accuracy= 77.011 - loss: 4.66460 processing batch 87 of 293 - accuracy= 77.273 - loss: 4.65973 processing batch 88 of 293 - accuracy= 77.388 - loss: 4.65481 processing batch 89 of 293 - accuracy= 77.222 - loss: 4.66207 processing batch 90 of 293 - accuracy= 77.198 - loss: 4.65915 processing batch 91 of 293 - accuracy= 77.038 - loss: 4.65729 processing batch 92 of 293 - accuracy= 77.151 - loss: 4.65303 processing batch 93 of 293 - accuracy= 76.862 - loss: 4.65658 processing batch 94 of 293 - accuracy= 76.842 - loss: 4.65319 processing batch 95 of 293 - accuracy= 76.823 - loss: 4.65230 processing batch 96 of 293 - accuracy= 76.804 - loss: 4.64939 processing batch 97 of 293 - accuracy= 76.913 - loss: 4.64529 processing batch 98 of 293 - accuracy= 77.020 - loss: 4.64382 processing batch 99 of 293 - accuracy= 77.125 - loss: 4.64071 processing batch 100 of 293 - accuracy= 77.228 - loss: 4.63454 processing batch 101 of 293 - accuracy= 77.083 - loss: 4.63645 processing batch 102 of 293 - accuracy= 77.184 - loss: 4.63055 processing batch 103 of 293 - accuracy= 77.043 - loss: 4.63075 processing batch 104 of 293 - accuracy= 77.024 - loss: 4.63043 processing batch 105 of 293 - accuracy= 77.005 - loss: 4.62899 processing batch 106 of 293 - accuracy= 76.986 - loss: 4.62867 processing batch 107 of 293 - accuracy= 76.968 - loss: 4.62768 processing batch 108 of 293 - accuracy= 77.064 - loss: 4.62537 processing batch 109 of 293 - accuracy= 77.159 - loss: 4.62051 processing batch 110 of 293 - accuracy= 77.252 - loss: 4.61759 processing batch 111 of 293 - accuracy= 77.344 - loss: 4.61282 processing batch 112 of 293 - accuracy= 77.212 - loss: 4.61175 processing batch 113 of 293 - accuracy= 77.412 - loss: 4.60600 processing batch 114 of 293 - accuracy= 77.391 - loss: 4.60805 processing batch 115 of 293 - accuracy= 77.263 - loss: 4.61011 processing batch 116 of 293 - accuracy= 77.244 - loss: 4.60568 processing batch 117 of 293 - accuracy= 77.436 - loss: 4.60046 processing batch 118 of 293 - accuracy= 77.416 - loss: 4.60244 processing batch 119 of 293 - accuracy= 77.500 - loss: 4.59917 processing batch 120 of 293 - accuracy= 77.273 - loss: 4.60077 processing batch 121 of 293 - accuracy= 77.152 - loss: 4.60175 processing batch 122 of 293 - accuracy= 77.134 - loss: 4.59957 processing batch 123 of 293 - accuracy= 77.319 - loss: 4.59394 processing batch 124 of 293 - accuracy= 77.400 - loss: 4.59246 processing batch 125 of 293 - accuracy= 77.381 - loss: 4.58929 processing batch 126 of 293 - accuracy= 77.264 - loss: 4.58809 processing batch 127 of 293 - accuracy= 77.246 - loss: 4.58456 processing batch 128 of 293 - accuracy= 77.132 - loss: 4.58445 processing batch 129 of 293 - accuracy= 77.115 - loss: 4.58321 processing batch 130 of 293 - accuracy= 77.195 - loss: 4.57975 processing batch 131 of 293 - accuracy= 77.273 - loss: 4.57557 processing batch 132 of 293 - accuracy= 77.350 - loss: 4.57192 processing batch 133 of 293 - accuracy= 77.332 - loss: 4.56947 processing batch 134 of 293 - accuracy= 77.500 - loss: 4.56526 processing batch 135 of 293 - accuracy= 77.482 - loss: 4.56286 processing batch 136 of 293 - accuracy= 77.372 - loss: 4.56110 processing batch 137 of 293 - accuracy= 77.446 - loss: 4.55680 processing batch 138 of 293 - accuracy= 77.428 - loss: 4.55397 processing batch 139 of 293 - accuracy= 77.411 - loss: 4.55188 processing batch 140 of 293 - accuracy= 77.305 - loss: 4.55220 processing batch 141 of 293 - accuracy= 77.377 - loss: 4.54711 processing batch 142 of 293 - accuracy= 77.448 - loss: 4.54357 processing batch 143 of 293 - accuracy= 77.517 - loss: 4.53926 processing batch 144 of 293 - accuracy= 77.586 - loss: 4.53520 processing batch 145 of 293 - accuracy= 77.654 - loss: 4.53290 processing batch 146 of 293 - accuracy= 77.721 - loss: 4.52952 processing batch 147 of 293 - accuracy= 77.872 - loss: 4.52470 processing batch 148 of 293 - accuracy= 77.936 - loss: 4.52005 processing batch 149 of 293 - accuracy= 78.083 - loss: 4.51635 processing batch 150 of 293 - accuracy= 78.063 - loss: 4.51425 processing batch 151 of 293 - accuracy= 77.961 - loss: 4.51317 processing batch 152 of 293 - accuracy= 77.941 - loss: 4.51301 processing batch 153 of 293 - accuracy= 77.760 - loss: 4.51339 processing batch 154 of 293 - accuracy= 77.823 - loss: 4.50897 processing batch 155 of 293 - accuracy= 77.724 - loss: 4.51017 processing batch 156 of 293 - accuracy= 77.787 - loss: 4.50577 processing batch 157 of 293 - accuracy= 77.848 - loss: 4.50274 processing batch 158 of 293 - accuracy= 77.909 - loss: 4.49854 processing batch 159 of 293 - accuracy= 77.734 - loss: 4.49827 processing batch 160 of 293 - accuracy= 77.717 - loss: 4.49532 processing batch 161 of 293 - accuracy= 77.623 - loss: 4.49336 processing batch 162 of 293 - accuracy= 77.454 - loss: 4.49250 processing batch 163 of 293 - accuracy= 77.287 - loss: 4.49063 processing batch 164 of 293 - accuracy= 77.273 - loss: 4.48925 processing batch 165 of 293 - accuracy= 77.334 - loss: 4.48611 processing batch 166 of 293 - accuracy= 77.395 - loss: 4.48322 processing batch 167 of 293 - accuracy= 77.381 - loss: 4.48288 processing batch 168 of 293 - accuracy= 77.145 - loss: 4.48435 processing batch 169 of 293 - accuracy= 77.059 - loss: 4.48373 processing batch 170 of 293 - accuracy= 76.974 - loss: 4.48161 processing batch 171 of 293 - accuracy= 76.962 - loss: 4.47882 processing batch 172 of 293 - accuracy= 77.023 - loss: 4.47667 processing batch 173 of 293 - accuracy= 77.155 - loss: 4.47252 processing batch 174 of 293 - accuracy= 77.214 - loss: 4.46904 processing batch 175 of 293 - accuracy= 77.273 - loss: 4.46675 processing batch 176 of 293 - accuracy= 77.260 - loss: 4.46353 processing batch 177 of 293 - accuracy= 77.317 - loss: 4.46013 processing batch 178 of 293 - accuracy= 77.235 - loss: 4.45795 processing batch 179 of 293 - accuracy= 77.222 - loss: 4.45565 processing batch 180 of 293 - accuracy= 77.279 - loss: 4.45147 processing batch 181 of 293 - accuracy= 77.198 - loss: 4.45257 processing batch 182 of 293 - accuracy= 77.322 - loss: 4.44910 processing batch 183 of 293 - accuracy= 77.310 - loss: 4.44794 processing batch 184 of 293 - accuracy= 77.297 - loss: 4.44642 processing batch 185 of 293 - accuracy= 77.151 - loss: 4.44732 processing batch 186 of 293 - accuracy= 77.139 - loss: 4.44523 processing batch 187 of 293 - accuracy= 77.061 - loss: 4.44473 processing batch 188 of 293 - accuracy= 76.984 - loss: 4.44286 processing batch 189 of 293 - accuracy= 77.039 - loss: 4.43935 processing batch 190 of 293 - accuracy= 77.029 - loss: 4.43908 processing batch 191 of 293 - accuracy= 77.083 - loss: 4.43632 processing batch 192 of 293 - accuracy= 77.137 - loss: 4.43230 processing batch 193 of 293 - accuracy= 77.255 - loss: 4.42773 processing batch 194 of 293 - accuracy= 77.308 - loss: 4.42495 processing batch 195 of 293 - accuracy= 77.360 - loss: 4.42232 processing batch 196 of 293 - accuracy= 77.348 - loss: 4.42035 processing batch 197 of 293 - accuracy= 77.273 - loss: 4.42262 processing batch 198 of 293 - accuracy= 77.324 - loss: 4.41840 processing batch 199 of 293 - accuracy= 77.250 - loss: 4.41892 processing batch 200 of 293 - accuracy= 77.301 - loss: 4.41598 processing batch 201 of 293 - accuracy= 77.166 - loss: 4.41462 processing batch 202 of 293 - accuracy= 77.032 - loss: 4.41427 processing batch 203 of 293 - accuracy= 77.022 - loss: 4.41182 processing batch 204 of 293 - accuracy= 77.073 - loss: 4.40841 processing batch 205 of 293 - accuracy= 76.942 - loss: 4.40943 processing batch 206 of 293 - accuracy= 77.053 - loss: 4.40577 processing batch 207 of 293 - accuracy= 76.983 - loss: 4.40385 processing batch 208 of 293 - accuracy= 76.854 - loss: 4.40358 processing batch 209 of 293 - accuracy= 76.845 - loss: 4.40153 processing batch 210 of 293 - accuracy= 76.896 - loss: 4.39863 processing batch 211 of 293 - accuracy= 76.828 - loss: 4.39760 processing batch 212 of 293 - accuracy= 76.526 - loss: 4.39981 processing batch 213 of 293 - accuracy= 76.577 - loss: 4.39684 processing batch 214 of 293 - accuracy= 76.512 - loss: 4.39542 processing batch 215 of 293 - accuracy= 76.562 - loss: 4.39214 processing batch 216 of 293 - accuracy= 76.555 - loss: 4.38931 processing batch 217 of 293 - accuracy= 76.663 - loss: 4.38537 processing batch 218 of 293 - accuracy= 76.712 - loss: 4.38282 processing batch 219 of 293 - accuracy= 76.761 - loss: 4.37931 processing batch 220 of 293 - accuracy= 76.753 - loss: 4.37661 processing batch 221 of 293 - accuracy= 76.577 - loss: 4.37829 processing batch 222 of 293 - accuracy= 76.570 - loss: 4.37604 processing batch 223 of 293 - accuracy= 76.618 - loss: 4.37373 processing batch 224 of 293 - accuracy= 76.556 - loss: 4.37179 processing batch 225 of 293 - accuracy= 76.493 - loss: 4.37174 processing batch 226 of 293 - accuracy= 76.432 - loss: 4.37181 processing batch 227 of 293 - accuracy= 76.371 - loss: 4.37094 processing batch 228 of 293 - accuracy= 76.310 - loss: 4.36837 processing batch 229 of 293 - accuracy= 76.196 - loss: 4.37188 processing batch 230 of 293 - accuracy= 76.136 - loss: 4.36887 processing batch 231 of 293 - accuracy= 76.185 - loss: 4.36674 processing batch 232 of 293 - accuracy= 76.180 - loss: 4.36586 processing batch 233 of 293 - accuracy= 76.068 - loss: 4.36609 processing batch 234 of 293 - accuracy= 76.117 - loss: 4.36347 processing batch 235 of 293 - accuracy= 76.165 - loss: 4.36047 processing batch 236 of 293 - accuracy= 76.266 - loss: 4.35691 processing batch 237 of 293 - accuracy= 76.261 - loss: 4.35470 processing batch 238 of 293 - accuracy= 76.255 - loss: 4.35337 processing batch 239 of 293 - accuracy= 76.354 - loss: 4.35067 processing batch 240 of 293 - accuracy= 76.245 - loss: 4.35177 processing batch 241 of 293 - accuracy= 76.291 - loss: 4.34961 processing batch 242 of 293 - accuracy= 76.286 - loss: 4.34758 processing batch 243 of 293 - accuracy= 76.281 - loss: 4.34535 processing batch 244 of 293 - accuracy= 76.276 - loss: 4.34332 processing batch 245 of 293 - accuracy= 76.270 - loss: 4.34087 processing batch 246 of 293 - accuracy= 76.265 - loss: 4.33924 processing batch 247 of 293 - accuracy= 76.210 - loss: 4.33757 processing batch 248 of 293 - accuracy= 76.255 - loss: 4.33524 processing batch 249 of 293 - accuracy= 76.300 - loss: 4.33323 processing batch 250 of 293 - accuracy= 76.345 - loss: 4.33026 processing batch 251 of 293 - accuracy= 76.240 - loss: 4.32902 processing batch 252 of 293 - accuracy= 76.186 - loss: 4.32764 processing batch 253 of 293 - accuracy= 76.181 - loss: 4.32529 processing batch 254 of 293 - accuracy= 76.127 - loss: 4.32548 processing batch 255 of 293 - accuracy= 76.172 - loss: 4.32209 processing batch 256 of 293 - accuracy= 76.070 - loss: 4.32255 processing batch 257 of 293 - accuracy= 76.114 - loss: 4.31957 processing batch 258 of 293 - accuracy= 76.207 - loss: 4.31628 processing batch 259 of 293 - accuracy= 76.202 - loss: 4.31395 processing batch 260 of 293 - accuracy= 76.197 - loss: 4.31267 processing batch 261 of 293 - accuracy= 76.097 - loss: 4.31280 processing batch 262 of 293 - accuracy= 76.093 - loss: 4.31104 processing batch 263 of 293 - accuracy= 76.089 - loss: 4.30847 processing batch 264 of 293 - accuracy= 76.132 - loss: 4.30584 processing batch 265 of 293 - accuracy= 76.081 - loss: 4.30463 processing batch 266 of 293 - accuracy= 76.077 - loss: 4.30267 processing batch 267 of 293 - accuracy= 76.026 - loss: 4.30066 processing batch 268 of 293 - accuracy= 76.069 - loss: 4.29785 processing batch 269 of 293 - accuracy= 75.926 - loss: 4.29771 processing batch 270 of 293 - accuracy= 76.015 - loss: 4.29427 processing batch 271 of 293 - accuracy= 76.057 - loss: 4.29111 processing batch 272 of 293 - accuracy= 75.916 - loss: 4.29273 processing batch 273 of 293 - accuracy= 75.958 - loss: 4.29018 processing batch 274 of 293 - accuracy= 75.909 - loss: 4.28908 processing batch 275 of 293 - accuracy= 75.906 - loss: 4.28645 processing batch 276 of 293 - accuracy= 75.903 - loss: 4.28497 processing batch 277 of 293 - accuracy= 75.899 - loss: 4.28352 processing batch 278 of 293 - accuracy= 75.896 - loss: 4.28109 processing batch 279 of 293 - accuracy= 75.937 - loss: 4.27784 processing batch 280 of 293 - accuracy= 75.934 - loss: 4.27572 processing batch 281 of 293 - accuracy= 75.931 - loss: 4.27407 processing batch 282 of 293 - accuracy= 75.972 - loss: 4.27138 processing batch 283 of 293 - accuracy= 76.012 - loss: 4.26944 processing batch 284 of 293 - accuracy= 76.053 - loss: 4.26660 processing batch 285 of 293 - accuracy= 76.049 - loss: 4.26440 processing batch 286 of 293 - accuracy= 75.958 - loss: 4.26393 processing batch 287 of 293 - accuracy= 75.955 - loss: 4.26357 processing batch 288 of 293 - accuracy= 76.038 - loss: 4.26037 processing batch 289 of 293 - accuracy= 76.034 - loss: 4.25851 processing batch 290 of 293 - accuracy= 76.074 - loss: 4.25558 processing batch 291 of 293 - accuracy= 76.027 - loss: 4.25343 processing batch 292 of 293 - accuracy= 75.981 - loss: 4.25193 3 /40 4.252 75.981 3.73261 71.453 0.00100 0.00100 accuracy 5.82 81.81 \n293/293 [==============================] - 82s 280ms/step - loss: 4.2519 - accuracy: 0.7598 - val_loss: 3.7326 - val_accuracy: 0.7145\nEpoch 4/40\n293/293 [==============================] - ETA: 0s - loss: 3.1417 - accuracy: 0.7752 127 processing batch 1 of 293 - accuracy= 68.750 - loss: 3.77278 processing batch 2 of 293 - accuracy= 66.667 - loss: 3.79425 processing batch 3 of 293 - accuracy= 65.625 - loss: 3.79574 processing batch 4 of 293 - accuracy= 70.000 - loss: 3.76434 processing batch 5 of 293 - accuracy= 70.833 - loss: 3.72209 processing batch 6 of 293 - accuracy= 73.214 - loss: 3.67502 processing batch 7 of 293 - accuracy= 76.562 - loss: 3.61446 processing batch 8 of 293 - accuracy= 79.167 - loss: 3.56483 processing batch 9 of 293 - accuracy= 80.000 - loss: 3.53695 processing batch 10 of 293 - accuracy= 79.545 - loss: 3.57127 processing batch 11 of 293 - accuracy= 81.250 - loss: 3.54257 processing batch 12 of 293 - accuracy= 80.769 - loss: 3.53982 processing batch 13 of 293 - accuracy= 79.464 - loss: 3.55064 processing batch 14 of 293 - accuracy= 80.000 - loss: 3.53609 processing batch 15 of 293 - accuracy= 78.906 - loss: 3.53722 processing batch 16 of 293 - accuracy= 77.941 - loss: 3.55936 processing batch 17 of 293 - accuracy= 77.778 - loss: 3.55324 processing batch 18 of 293 - accuracy= 78.289 - loss: 3.53871 processing batch 19 of 293 - accuracy= 79.375 - loss: 3.52905 processing batch 20 of 293 - accuracy= 79.167 - loss: 3.55336 processing batch 21 of 293 - accuracy= 79.545 - loss: 3.54434 processing batch 22 of 293 - accuracy= 80.435 - loss: 3.52975 processing batch 23 of 293 - accuracy= 80.208 - loss: 3.52632 processing batch 24 of 293 - accuracy= 79.500 - loss: 3.52918 processing batch 25 of 293 - accuracy= 79.327 - loss: 3.52960 processing batch 26 of 293 - accuracy= 80.093 - loss: 3.51498 processing batch 27 of 293 - accuracy= 80.357 - loss: 3.50359 processing batch 28 of 293 - accuracy= 79.741 - loss: 3.52174 processing batch 29 of 293 - accuracy= 79.167 - loss: 3.53537 processing batch 30 of 293 - accuracy= 79.435 - loss: 3.53387 processing batch 31 of 293 - accuracy= 79.688 - loss: 3.52899 processing batch 32 of 293 - accuracy= 79.924 - loss: 3.51780 processing batch 33 of 293 - accuracy= 79.779 - loss: 3.50897 processing batch 34 of 293 - accuracy= 79.643 - loss: 3.51083 processing batch 35 of 293 - accuracy= 80.208 - loss: 3.49932 processing batch 36 of 293 - accuracy= 80.743 - loss: 3.49046 processing batch 37 of 293 - accuracy= 79.934 - loss: 3.50058 processing batch 38 of 293 - accuracy= 79.167 - loss: 3.51044 processing batch 39 of 293 - accuracy= 79.375 - loss: 3.50378 processing batch 40 of 293 - accuracy= 79.878 - loss: 3.49353 processing batch 41 of 293 - accuracy= 79.762 - loss: 3.49231 processing batch 42 of 293 - accuracy= 79.651 - loss: 3.49354 processing batch 43 of 293 - accuracy= 79.830 - loss: 3.48866 processing batch 44 of 293 - accuracy= 79.444 - loss: 3.48768 processing batch 45 of 293 - accuracy= 79.891 - loss: 3.48170 processing batch 46 of 293 - accuracy= 79.787 - loss: 3.48732 processing batch 47 of 293 - accuracy= 80.208 - loss: 3.48127 processing batch 48 of 293 - accuracy= 80.102 - loss: 3.48035 processing batch 49 of 293 - accuracy= 80.000 - loss: 3.48954 processing batch 50 of 293 - accuracy= 79.412 - loss: 3.49659 processing batch 51 of 293 - accuracy= 79.087 - loss: 3.50262 processing batch 52 of 293 - accuracy= 79.245 - loss: 3.49688 processing batch 53 of 293 - accuracy= 79.167 - loss: 3.49941 processing batch 54 of 293 - accuracy= 79.545 - loss: 3.49231 processing batch 55 of 293 - accuracy= 79.241 - loss: 3.49623 processing batch 56 of 293 - accuracy= 79.167 - loss: 3.49700 processing batch 57 of 293 - accuracy= 79.310 - loss: 3.49253 processing batch 58 of 293 - accuracy= 79.237 - loss: 3.49207 processing batch 59 of 293 - accuracy= 79.583 - loss: 3.48637 processing batch 60 of 293 - accuracy= 79.713 - loss: 3.48105 processing batch 61 of 293 - accuracy= 79.435 - loss: 3.48523 processing batch 62 of 293 - accuracy= 79.167 - loss: 3.48207 processing batch 63 of 293 - accuracy= 79.297 - loss: 3.47818 processing batch 64 of 293 - accuracy= 79.231 - loss: 3.47738 processing batch 65 of 293 - accuracy= 78.977 - loss: 3.47673 processing batch 66 of 293 - accuracy= 79.104 - loss: 3.47404 processing batch 67 of 293 - accuracy= 79.044 - loss: 3.47183 processing batch 68 of 293 - accuracy= 79.348 - loss: 3.46485 processing batch 69 of 293 - accuracy= 79.286 - loss: 3.46548 processing batch 70 of 293 - accuracy= 79.401 - loss: 3.46098 processing batch 71 of 293 - accuracy= 79.514 - loss: 3.45794 processing batch 72 of 293 - accuracy= 79.110 - loss: 3.46022 processing batch 73 of 293 - accuracy= 79.223 - loss: 3.45427 processing batch 74 of 293 - accuracy= 79.167 - loss: 3.45589 processing batch 75 of 293 - accuracy= 78.947 - loss: 3.45864 processing batch 76 of 293 - accuracy= 78.896 - loss: 3.45693 processing batch 77 of 293 - accuracy= 79.006 - loss: 3.45337 processing batch 78 of 293 - accuracy= 79.114 - loss: 3.45225 processing batch 79 of 293 - accuracy= 79.062 - loss: 3.45029 processing batch 80 of 293 - accuracy= 79.012 - loss: 3.44848 processing batch 81 of 293 - accuracy= 78.963 - loss: 3.44655 processing batch 82 of 293 - accuracy= 79.217 - loss: 3.44223 processing batch 83 of 293 - accuracy= 79.018 - loss: 3.43965 processing batch 84 of 293 - accuracy= 79.118 - loss: 3.43753 processing batch 85 of 293 - accuracy= 79.070 - loss: 3.44559 processing batch 86 of 293 - accuracy= 79.023 - loss: 3.44118 processing batch 87 of 293 - accuracy= 79.119 - loss: 3.43681 processing batch 88 of 293 - accuracy= 79.354 - loss: 3.43120 processing batch 89 of 293 - accuracy= 79.306 - loss: 3.43215 processing batch 90 of 293 - accuracy= 79.396 - loss: 3.42882 processing batch 91 of 293 - accuracy= 79.348 - loss: 3.42789 processing batch 92 of 293 - accuracy= 79.301 - loss: 3.42710 processing batch 93 of 293 - accuracy= 79.521 - loss: 3.42222 processing batch 94 of 293 - accuracy= 79.605 - loss: 3.41725 processing batch 95 of 293 - accuracy= 79.427 - loss: 3.41671 processing batch 96 of 293 - accuracy= 79.381 - loss: 3.41438 processing batch 97 of 293 - accuracy= 79.337 - loss: 3.41195 processing batch 98 of 293 - accuracy= 79.293 - loss: 3.41071 processing batch 99 of 293 - accuracy= 79.000 - loss: 3.41054 processing batch 100 of 293 - accuracy= 79.208 - loss: 3.40630 processing batch 101 of 293 - accuracy= 79.044 - loss: 3.40690 processing batch 102 of 293 - accuracy= 79.126 - loss: 3.40466 processing batch 103 of 293 - accuracy= 78.966 - loss: 3.40438 processing batch 104 of 293 - accuracy= 79.048 - loss: 3.40205 processing batch 105 of 293 - accuracy= 79.009 - loss: 3.39983 processing batch 106 of 293 - accuracy= 79.089 - loss: 3.39947 processing batch 107 of 293 - accuracy= 79.051 - loss: 3.39914 processing batch 108 of 293 - accuracy= 79.014 - loss: 3.39808 processing batch 109 of 293 - accuracy= 78.750 - loss: 3.39926 processing batch 110 of 293 - accuracy= 78.716 - loss: 3.39752 processing batch 111 of 293 - accuracy= 78.683 - loss: 3.39839 processing batch 112 of 293 - accuracy= 78.650 - loss: 3.40067 processing batch 113 of 293 - accuracy= 78.399 - loss: 3.40559 processing batch 114 of 293 - accuracy= 78.370 - loss: 3.40235 processing batch 115 of 293 - accuracy= 78.233 - loss: 3.40094 processing batch 116 of 293 - accuracy= 78.205 - loss: 3.39808 processing batch 117 of 293 - accuracy= 78.284 - loss: 3.39528 processing batch 118 of 293 - accuracy= 78.361 - loss: 3.39183 processing batch 119 of 293 - accuracy= 78.438 - loss: 3.38868 processing batch 120 of 293 - accuracy= 78.409 - loss: 3.38694 processing batch 121 of 293 - accuracy= 78.484 - loss: 3.38451 processing batch 122 of 293 - accuracy= 78.557 - loss: 3.38175 processing batch 123 of 293 - accuracy= 78.528 - loss: 3.37991 processing batch 124 of 293 - accuracy= 78.400 - loss: 3.38084 processing batch 125 of 293 - accuracy= 78.274 - loss: 3.38172 processing batch 126 of 293 - accuracy= 78.150 - loss: 3.38134 processing batch 127 of 293 - accuracy= 78.125 - loss: 3.37901 processing batch 128 of 293 - accuracy= 78.295 - loss: 3.37531 processing batch 129 of 293 - accuracy= 78.462 - loss: 3.37184 processing batch 130 of 293 - accuracy= 78.531 - loss: 3.36987 processing batch 131 of 293 - accuracy= 78.504 - loss: 3.36854 processing batch 132 of 293 - accuracy= 78.477 - loss: 3.36881 processing batch 133 of 293 - accuracy= 78.358 - loss: 3.36958 processing batch 134 of 293 - accuracy= 78.333 - loss: 3.36801 processing batch 135 of 293 - accuracy= 78.309 - loss: 3.36697 processing batch 136 of 293 - accuracy= 78.285 - loss: 3.36583 processing batch 137 of 293 - accuracy= 78.351 - loss: 3.36325 processing batch 138 of 293 - accuracy= 78.417 - loss: 3.35950 processing batch 139 of 293 - accuracy= 78.393 - loss: 3.35745 processing batch 140 of 293 - accuracy= 78.546 - loss: 3.35280 processing batch 141 of 293 - accuracy= 78.345 - loss: 3.35327 processing batch 142 of 293 - accuracy= 78.322 - loss: 3.35244 processing batch 143 of 293 - accuracy= 78.299 - loss: 3.35199 processing batch 144 of 293 - accuracy= 78.276 - loss: 3.35121 processing batch 145 of 293 - accuracy= 77.911 - loss: 3.35765 processing batch 146 of 293 - accuracy= 78.061 - loss: 3.35397 processing batch 147 of 293 - accuracy= 78.041 - loss: 3.35345 processing batch 148 of 293 - accuracy= 78.104 - loss: 3.34978 processing batch 149 of 293 - accuracy= 78.083 - loss: 3.34729 processing batch 150 of 293 - accuracy= 78.146 - loss: 3.34526 processing batch 151 of 293 - accuracy= 78.043 - loss: 3.34433 processing batch 152 of 293 - accuracy= 77.778 - loss: 3.34855 processing batch 153 of 293 - accuracy= 77.760 - loss: 3.34686 processing batch 154 of 293 - accuracy= 77.742 - loss: 3.34386 processing batch 155 of 293 - accuracy= 77.644 - loss: 3.34343 processing batch 156 of 293 - accuracy= 77.627 - loss: 3.34227 processing batch 157 of 293 - accuracy= 77.532 - loss: 3.34162 processing batch 158 of 293 - accuracy= 77.594 - loss: 3.33909 processing batch 159 of 293 - accuracy= 77.578 - loss: 3.33709 processing batch 160 of 293 - accuracy= 77.562 - loss: 3.33597 processing batch 161 of 293 - accuracy= 77.546 - loss: 3.33434 processing batch 162 of 293 - accuracy= 77.607 - loss: 3.33270 processing batch 163 of 293 - accuracy= 77.439 - loss: 3.33350 processing batch 164 of 293 - accuracy= 77.348 - loss: 3.33247 processing batch 165 of 293 - accuracy= 77.410 - loss: 3.32962 processing batch 166 of 293 - accuracy= 77.470 - loss: 3.32647 processing batch 167 of 293 - accuracy= 77.381 - loss: 3.32443 processing batch 168 of 293 - accuracy= 77.293 - loss: 3.32459 processing batch 169 of 293 - accuracy= 77.353 - loss: 3.32115 processing batch 170 of 293 - accuracy= 77.339 - loss: 3.31920 processing batch 171 of 293 - accuracy= 77.398 - loss: 3.31696 processing batch 172 of 293 - accuracy= 77.384 - loss: 3.31514 processing batch 173 of 293 - accuracy= 77.443 - loss: 3.31478 processing batch 174 of 293 - accuracy= 77.429 - loss: 3.31347 processing batch 175 of 293 - accuracy= 77.486 - loss: 3.31038 processing batch 176 of 293 - accuracy= 77.472 - loss: 3.30853 processing batch 177 of 293 - accuracy= 77.528 - loss: 3.30594 processing batch 178 of 293 - accuracy= 77.514 - loss: 3.30495 processing batch 179 of 293 - accuracy= 77.500 - loss: 3.30257 processing batch 180 of 293 - accuracy= 77.417 - loss: 3.30234 processing batch 181 of 293 - accuracy= 77.541 - loss: 3.29829 processing batch 182 of 293 - accuracy= 77.664 - loss: 3.29395 processing batch 183 of 293 - accuracy= 77.649 - loss: 3.29350 processing batch 184 of 293 - accuracy= 77.703 - loss: 3.29050 processing batch 185 of 293 - accuracy= 77.621 - loss: 3.29158 processing batch 186 of 293 - accuracy= 77.607 - loss: 3.28996 processing batch 187 of 293 - accuracy= 77.726 - loss: 3.28676 processing batch 188 of 293 - accuracy= 77.778 - loss: 3.28404 processing batch 189 of 293 - accuracy= 77.763 - loss: 3.28267 processing batch 190 of 293 - accuracy= 77.880 - loss: 3.27910 processing batch 191 of 293 - accuracy= 77.930 - loss: 3.27562 processing batch 192 of 293 - accuracy= 77.979 - loss: 3.27296 processing batch 193 of 293 - accuracy= 77.964 - loss: 3.27237 processing batch 194 of 293 - accuracy= 77.949 - loss: 3.27090 processing batch 195 of 293 - accuracy= 77.870 - loss: 3.27072 processing batch 196 of 293 - accuracy= 77.982 - loss: 3.26741 processing batch 197 of 293 - accuracy= 77.967 - loss: 3.26516 processing batch 198 of 293 - accuracy= 78.078 - loss: 3.26218 processing batch 199 of 293 - accuracy= 78.125 - loss: 3.25968 processing batch 200 of 293 - accuracy= 78.172 - loss: 3.25819 processing batch 201 of 293 - accuracy= 78.094 - loss: 3.25756 processing batch 202 of 293 - accuracy= 78.140 - loss: 3.25483 processing batch 203 of 293 - accuracy= 78.186 - loss: 3.25272 processing batch 204 of 293 - accuracy= 78.232 - loss: 3.25332 processing batch 205 of 293 - accuracy= 78.337 - loss: 3.25060 processing batch 206 of 293 - accuracy= 78.140 - loss: 3.25250 processing batch 207 of 293 - accuracy= 78.065 - loss: 3.25141 processing batch 208 of 293 - accuracy= 78.170 - loss: 3.24835 processing batch 209 of 293 - accuracy= 78.036 - loss: 3.25115 processing batch 210 of 293 - accuracy= 77.962 - loss: 3.25333 processing batch 211 of 293 - accuracy= 77.771 - loss: 3.25521 processing batch 212 of 293 - accuracy= 77.876 - loss: 3.25176 processing batch 213 of 293 - accuracy= 77.921 - loss: 3.24870 processing batch 214 of 293 - accuracy= 77.965 - loss: 3.24719 processing batch 215 of 293 - accuracy= 77.951 - loss: 3.24562 processing batch 216 of 293 - accuracy= 77.938 - loss: 3.24429 processing batch 217 of 293 - accuracy= 77.924 - loss: 3.24268 processing batch 218 of 293 - accuracy= 77.854 - loss: 3.24126 processing batch 219 of 293 - accuracy= 77.841 - loss: 3.23908 processing batch 220 of 293 - accuracy= 77.828 - loss: 3.23732 processing batch 221 of 293 - accuracy= 77.759 - loss: 3.23697 processing batch 222 of 293 - accuracy= 77.578 - loss: 3.24126 processing batch 223 of 293 - accuracy= 77.455 - loss: 3.24069 processing batch 224 of 293 - accuracy= 77.444 - loss: 3.23839 processing batch 225 of 293 - accuracy= 77.434 - loss: 3.23675 processing batch 226 of 293 - accuracy= 77.423 - loss: 3.23491 processing batch 227 of 293 - accuracy= 77.467 - loss: 3.23269 processing batch 228 of 293 - accuracy= 77.511 - loss: 3.23124 processing batch 229 of 293 - accuracy= 77.500 - loss: 3.23000 processing batch 230 of 293 - accuracy= 77.543 - loss: 3.22788 processing batch 231 of 293 - accuracy= 77.532 - loss: 3.22808 processing batch 232 of 293 - accuracy= 77.575 - loss: 3.22648 processing batch 233 of 293 - accuracy= 77.457 - loss: 3.22699 processing batch 234 of 293 - accuracy= 77.500 - loss: 3.22531 processing batch 235 of 293 - accuracy= 77.489 - loss: 3.22505 processing batch 236 of 293 - accuracy= 77.479 - loss: 3.22435 processing batch 237 of 293 - accuracy= 77.574 - loss: 3.22122 processing batch 238 of 293 - accuracy= 77.615 - loss: 3.21847 processing batch 239 of 293 - accuracy= 77.500 - loss: 3.21901 processing batch 240 of 293 - accuracy= 77.593 - loss: 3.21665 processing batch 241 of 293 - accuracy= 77.686 - loss: 3.21367 processing batch 242 of 293 - accuracy= 77.726 - loss: 3.21090 processing batch 243 of 293 - accuracy= 77.715 - loss: 3.20933 processing batch 244 of 293 - accuracy= 77.653 - loss: 3.20796 processing batch 245 of 293 - accuracy= 77.693 - loss: 3.20587 processing batch 246 of 293 - accuracy= 77.682 - loss: 3.20458 processing batch 247 of 293 - accuracy= 77.722 - loss: 3.20186 processing batch 248 of 293 - accuracy= 77.661 - loss: 3.20213 processing batch 249 of 293 - accuracy= 77.650 - loss: 3.20112 processing batch 250 of 293 - accuracy= 77.689 - loss: 3.19871 processing batch 251 of 293 - accuracy= 77.679 - loss: 3.19693 processing batch 252 of 293 - accuracy= 77.767 - loss: 3.19419 processing batch 253 of 293 - accuracy= 77.805 - loss: 3.19314 processing batch 254 of 293 - accuracy= 77.696 - loss: 3.19426 processing batch 255 of 293 - accuracy= 77.588 - loss: 3.19464 processing batch 256 of 293 - accuracy= 77.675 - loss: 3.19173 processing batch 257 of 293 - accuracy= 77.762 - loss: 3.18891 processing batch 258 of 293 - accuracy= 77.751 - loss: 3.18731 processing batch 259 of 293 - accuracy= 77.644 - loss: 3.18792 processing batch 260 of 293 - accuracy= 77.682 - loss: 3.18523 processing batch 261 of 293 - accuracy= 77.624 - loss: 3.18393 processing batch 262 of 293 - accuracy= 77.614 - loss: 3.18249 processing batch 263 of 293 - accuracy= 77.604 - loss: 3.18128 processing batch 264 of 293 - accuracy= 77.642 - loss: 3.17988 processing batch 265 of 293 - accuracy= 77.585 - loss: 3.17956 processing batch 266 of 293 - accuracy= 77.622 - loss: 3.17739 processing batch 267 of 293 - accuracy= 77.659 - loss: 3.17483 processing batch 268 of 293 - accuracy= 77.556 - loss: 3.17438 processing batch 269 of 293 - accuracy= 77.639 - loss: 3.17192 processing batch 270 of 293 - accuracy= 77.675 - loss: 3.16947 processing batch 271 of 293 - accuracy= 77.665 - loss: 3.16781 processing batch 272 of 293 - accuracy= 77.518 - loss: 3.16769 processing batch 273 of 293 - accuracy= 77.509 - loss: 3.16613 processing batch 274 of 293 - accuracy= 77.500 - loss: 3.16472 processing batch 275 of 293 - accuracy= 77.582 - loss: 3.16165 processing batch 276 of 293 - accuracy= 77.617 - loss: 3.16025 processing batch 277 of 293 - accuracy= 77.653 - loss: 3.15807 processing batch 278 of 293 - accuracy= 77.688 - loss: 3.15577 processing batch 279 of 293 - accuracy= 77.589 - loss: 3.15586 processing batch 280 of 293 - accuracy= 77.625 - loss: 3.15363 processing batch 281 of 293 - accuracy= 77.660 - loss: 3.15204 processing batch 282 of 293 - accuracy= 77.694 - loss: 3.15025 processing batch 283 of 293 - accuracy= 77.729 - loss: 3.14794 processing batch 284 of 293 - accuracy= 77.675 - loss: 3.14777 processing batch 285 of 293 - accuracy= 77.710 - loss: 3.14534 processing batch 286 of 293 - accuracy= 77.570 - loss: 3.14815 processing batch 287 of 293 - accuracy= 77.517 - loss: 3.14759 processing batch 288 of 293 - accuracy= 77.509 - loss: 3.14631 processing batch 289 of 293 - accuracy= 77.457 - loss: 3.14610 processing batch 290 of 293 - accuracy= 77.491 - loss: 3.14464 processing batch 291 of 293 - accuracy= 77.440 - loss: 3.14436 processing batch 292 of 293 - accuracy= 77.517 - loss: 3.14167 4 /40 3.142 77.517 2.80779 75.556 0.00100 0.00100 accuracy 2.02 82.35 \n293/293 [==============================] - 83s 281ms/step - loss: 3.1417 - accuracy: 0.7752 - val_loss: 2.8078 - val_accuracy: 0.7556\nEpoch 5/40\n293/293 [==============================] - ETA: 0s - loss: 2.3527 - accuracy: 0.8042 393 processing batch 1 of 293 - accuracy= 75.000 - loss: 2.76184 processing batch 2 of 293 - accuracy= 79.167 - loss: 2.70414 processing batch 3 of 293 - accuracy= 78.125 - loss: 2.66199 processing batch 4 of 293 - accuracy= 80.000 - loss: 2.61728 processing batch 5 of 293 - accuracy= 83.333 - loss: 2.59444 processing batch 6 of 293 - accuracy= 83.929 - loss: 2.58798 processing batch 7 of 293 - accuracy= 85.938 - loss: 2.55471 processing batch 8 of 293 - accuracy= 83.333 - loss: 2.61054 processing batch 9 of 293 - accuracy= 82.500 - loss: 2.61950 processing batch 10 of 293 - accuracy= 84.091 - loss: 2.59842 processing batch 11 of 293 - accuracy= 85.417 - loss: 2.58561 processing batch 12 of 293 - accuracy= 83.654 - loss: 2.68808 processing batch 13 of 293 - accuracy= 81.250 - loss: 2.74647 processing batch 14 of 293 - accuracy= 82.500 - loss: 2.72077 processing batch 15 of 293 - accuracy= 81.250 - loss: 2.73022 processing batch 16 of 293 - accuracy= 80.882 - loss: 2.71629 processing batch 17 of 293 - accuracy= 81.250 - loss: 2.70510 processing batch 18 of 293 - accuracy= 81.579 - loss: 2.69011 processing batch 19 of 293 - accuracy= 81.875 - loss: 2.68014 processing batch 20 of 293 - accuracy= 82.143 - loss: 2.67827 processing batch 21 of 293 - accuracy= 82.955 - loss: 2.66037 processing batch 22 of 293 - accuracy= 82.609 - loss: 2.65628 processing batch 23 of 293 - accuracy= 83.333 - loss: 2.63781 processing batch 24 of 293 - accuracy= 83.500 - loss: 2.63462 processing batch 25 of 293 - accuracy= 83.173 - loss: 2.64355 processing batch 26 of 293 - accuracy= 83.796 - loss: 2.62744 processing batch 27 of 293 - accuracy= 83.482 - loss: 2.63162 processing batch 28 of 293 - accuracy= 83.190 - loss: 2.62528 processing batch 29 of 293 - accuracy= 83.750 - loss: 2.61286 processing batch 30 of 293 - accuracy= 83.871 - loss: 2.60640 processing batch 31 of 293 - accuracy= 83.594 - loss: 2.60251 processing batch 32 of 293 - accuracy= 83.333 - loss: 2.60369 processing batch 33 of 293 - accuracy= 82.721 - loss: 2.60551 processing batch 34 of 293 - accuracy= 82.857 - loss: 2.60290 processing batch 35 of 293 - accuracy= 82.639 - loss: 2.60907 processing batch 36 of 293 - accuracy= 82.770 - loss: 2.60644 processing batch 37 of 293 - accuracy= 82.566 - loss: 2.60946 processing batch 38 of 293 - accuracy= 82.372 - loss: 2.60642 processing batch 39 of 293 - accuracy= 82.812 - loss: 2.59562 processing batch 40 of 293 - accuracy= 83.232 - loss: 2.58884 processing batch 41 of 293 - accuracy= 83.036 - loss: 2.59594 processing batch 42 of 293 - accuracy= 82.849 - loss: 2.60679 processing batch 43 of 293 - accuracy= 82.955 - loss: 2.60624 processing batch 44 of 293 - accuracy= 83.056 - loss: 2.60224 processing batch 45 of 293 - accuracy= 83.424 - loss: 2.59388 processing batch 46 of 293 - accuracy= 83.245 - loss: 2.59083 processing batch 47 of 293 - accuracy= 83.333 - loss: 2.58913 processing batch 48 of 293 - accuracy= 82.908 - loss: 2.59184 processing batch 49 of 293 - accuracy= 83.250 - loss: 2.58382 processing batch 50 of 293 - accuracy= 83.333 - loss: 2.57853 processing batch 51 of 293 - accuracy= 82.933 - loss: 2.57801 processing batch 52 of 293 - accuracy= 83.019 - loss: 2.57523 processing batch 53 of 293 - accuracy= 83.102 - loss: 2.57245 processing batch 54 of 293 - accuracy= 82.955 - loss: 2.57268 processing batch 55 of 293 - accuracy= 83.036 - loss: 2.57311 processing batch 56 of 293 - accuracy= 82.675 - loss: 2.58626 processing batch 57 of 293 - accuracy= 82.328 - loss: 2.58789 processing batch 58 of 293 - accuracy= 82.203 - loss: 2.58807 processing batch 59 of 293 - accuracy= 82.083 - loss: 2.58840 processing batch 60 of 293 - accuracy= 81.967 - loss: 2.58831 processing batch 61 of 293 - accuracy= 81.855 - loss: 2.58869 processing batch 62 of 293 - accuracy= 81.746 - loss: 2.59079 processing batch 63 of 293 - accuracy= 81.250 - loss: 2.59672 processing batch 64 of 293 - accuracy= 81.154 - loss: 2.60226 processing batch 65 of 293 - accuracy= 81.439 - loss: 2.59785 processing batch 66 of 293 - accuracy= 81.157 - loss: 2.59855 processing batch 67 of 293 - accuracy= 81.250 - loss: 2.59655 processing batch 68 of 293 - accuracy= 80.978 - loss: 2.59796 processing batch 69 of 293 - accuracy= 80.357 - loss: 2.60250 processing batch 70 of 293 - accuracy= 80.282 - loss: 2.59985 processing batch 71 of 293 - accuracy= 80.382 - loss: 2.59673 processing batch 72 of 293 - accuracy= 80.651 - loss: 2.59145 processing batch 73 of 293 - accuracy= 80.912 - loss: 2.58955 processing batch 74 of 293 - accuracy= 80.833 - loss: 2.59919 processing batch 75 of 293 - accuracy= 80.921 - loss: 2.59735 processing batch 76 of 293 - accuracy= 80.844 - loss: 2.59551 processing batch 77 of 293 - accuracy= 80.929 - loss: 2.59519 processing batch 78 of 293 - accuracy= 81.013 - loss: 2.59214 processing batch 79 of 293 - accuracy= 81.094 - loss: 2.58716 processing batch 80 of 293 - accuracy= 81.173 - loss: 2.58453 processing batch 81 of 293 - accuracy= 81.098 - loss: 2.58372 processing batch 82 of 293 - accuracy= 81.325 - loss: 2.57944 processing batch 83 of 293 - accuracy= 81.399 - loss: 2.57548 processing batch 84 of 293 - accuracy= 81.618 - loss: 2.57145 processing batch 85 of 293 - accuracy= 81.541 - loss: 2.57135 processing batch 86 of 293 - accuracy= 81.609 - loss: 2.56956 processing batch 87 of 293 - accuracy= 81.818 - loss: 2.56392 processing batch 88 of 293 - accuracy= 81.742 - loss: 2.56482 processing batch 89 of 293 - accuracy= 81.944 - loss: 2.55999 processing batch 90 of 293 - accuracy= 82.005 - loss: 2.55713 processing batch 91 of 293 - accuracy= 81.929 - loss: 2.55873 processing batch 92 of 293 - accuracy= 81.989 - loss: 2.55572 processing batch 93 of 293 - accuracy= 81.649 - loss: 2.55650 processing batch 94 of 293 - accuracy= 81.579 - loss: 2.55520 processing batch 95 of 293 - accuracy= 81.510 - loss: 2.55490 processing batch 96 of 293 - accuracy= 81.314 - loss: 2.55873 processing batch 97 of 293 - accuracy= 81.505 - loss: 2.55396 processing batch 98 of 293 - accuracy= 81.313 - loss: 2.55359 processing batch 99 of 293 - accuracy= 81.500 - loss: 2.54985 processing batch 100 of 293 - accuracy= 81.559 - loss: 2.54750 processing batch 101 of 293 - accuracy= 81.618 - loss: 2.54322 processing batch 102 of 293 - accuracy= 81.432 - loss: 2.54256 processing batch 103 of 293 - accuracy= 81.490 - loss: 2.53932 processing batch 104 of 293 - accuracy= 81.429 - loss: 2.54103 processing batch 105 of 293 - accuracy= 81.486 - loss: 2.54088 processing batch 106 of 293 - accuracy= 81.542 - loss: 2.53954 processing batch 107 of 293 - accuracy= 81.597 - loss: 2.53697 processing batch 108 of 293 - accuracy= 81.307 - loss: 2.54051 processing batch 109 of 293 - accuracy= 81.250 - loss: 2.53860 processing batch 110 of 293 - accuracy= 81.194 - loss: 2.53960 processing batch 111 of 293 - accuracy= 81.138 - loss: 2.54288 processing batch 112 of 293 - accuracy= 80.973 - loss: 2.54591 processing batch 113 of 293 - accuracy= 81.031 - loss: 2.54361 processing batch 114 of 293 - accuracy= 80.978 - loss: 2.54237 processing batch 115 of 293 - accuracy= 81.142 - loss: 2.54087 processing batch 116 of 293 - accuracy= 81.090 - loss: 2.54205 processing batch 117 of 293 - accuracy= 81.144 - loss: 2.53988 processing batch 118 of 293 - accuracy= 80.987 - loss: 2.53911 processing batch 119 of 293 - accuracy= 80.937 - loss: 2.53857 processing batch 120 of 293 - accuracy= 80.888 - loss: 2.53691 processing batch 121 of 293 - accuracy= 81.045 - loss: 2.53518 processing batch 122 of 293 - accuracy= 80.894 - loss: 2.53677 processing batch 123 of 293 - accuracy= 80.847 - loss: 2.53490 processing batch 124 of 293 - accuracy= 80.700 - loss: 2.53773 processing batch 125 of 293 - accuracy= 80.754 - loss: 2.53742 processing batch 126 of 293 - accuracy= 80.807 - loss: 2.53539 processing batch 127 of 293 - accuracy= 80.859 - loss: 2.53536 processing batch 128 of 293 - accuracy= 81.008 - loss: 2.53212 processing batch 129 of 293 - accuracy= 81.058 - loss: 2.52974 processing batch 130 of 293 - accuracy= 81.107 - loss: 2.52753 processing batch 131 of 293 - accuracy= 80.966 - loss: 2.52963 processing batch 132 of 293 - accuracy= 81.109 - loss: 2.52650 processing batch 133 of 293 - accuracy= 81.250 - loss: 2.52290 processing batch 134 of 293 - accuracy= 81.296 - loss: 2.52109 processing batch 135 of 293 - accuracy= 81.250 - loss: 2.51951 processing batch 136 of 293 - accuracy= 81.296 - loss: 2.51787 processing batch 137 of 293 - accuracy= 81.159 - loss: 2.51827 processing batch 138 of 293 - accuracy= 81.295 - loss: 2.51445 processing batch 139 of 293 - accuracy= 81.339 - loss: 2.51221 processing batch 140 of 293 - accuracy= 81.472 - loss: 2.50915 processing batch 141 of 293 - accuracy= 81.426 - loss: 2.50845 processing batch 142 of 293 - accuracy= 81.206 - loss: 2.51420 processing batch 143 of 293 - accuracy= 81.163 - loss: 2.51391 processing batch 144 of 293 - accuracy= 81.121 - loss: 2.51241 processing batch 145 of 293 - accuracy= 81.079 - loss: 2.51063 processing batch 146 of 293 - accuracy= 81.122 - loss: 2.50948 processing batch 147 of 293 - accuracy= 81.081 - loss: 2.50930 processing batch 148 of 293 - accuracy= 80.956 - loss: 2.51180 processing batch 149 of 293 - accuracy= 81.000 - loss: 2.50877 processing batch 150 of 293 - accuracy= 81.043 - loss: 2.50681 processing batch 151 of 293 - accuracy= 81.086 - loss: 2.50365 processing batch 152 of 293 - accuracy= 81.046 - loss: 2.50294 processing batch 153 of 293 - accuracy= 81.088 - loss: 2.50205 processing batch 154 of 293 - accuracy= 81.048 - loss: 2.50208 processing batch 155 of 293 - accuracy= 81.090 - loss: 2.50028 processing batch 156 of 293 - accuracy= 81.051 - loss: 2.49860 processing batch 157 of 293 - accuracy= 81.013 - loss: 2.49727 processing batch 158 of 293 - accuracy= 80.975 - loss: 2.49587 processing batch 159 of 293 - accuracy= 81.094 - loss: 2.49302 processing batch 160 of 293 - accuracy= 81.134 - loss: 2.49024 processing batch 161 of 293 - accuracy= 81.096 - loss: 2.48896 processing batch 162 of 293 - accuracy= 81.135 - loss: 2.48761 processing batch 163 of 293 - accuracy= 81.021 - loss: 2.48579 processing batch 164 of 293 - accuracy= 81.061 - loss: 2.48363 processing batch 165 of 293 - accuracy= 80.949 - loss: 2.48535 processing batch 166 of 293 - accuracy= 80.913 - loss: 2.48428 processing batch 167 of 293 - accuracy= 80.952 - loss: 2.48190 processing batch 168 of 293 - accuracy= 80.991 - loss: 2.48012 processing batch 169 of 293 - accuracy= 81.029 - loss: 2.47945 processing batch 170 of 293 - accuracy= 81.140 - loss: 2.47661 processing batch 171 of 293 - accuracy= 80.959 - loss: 2.47851 processing batch 172 of 293 - accuracy= 80.853 - loss: 2.47914 processing batch 173 of 293 - accuracy= 80.819 - loss: 2.47784 processing batch 174 of 293 - accuracy= 80.786 - loss: 2.47549 processing batch 175 of 293 - accuracy= 80.824 - loss: 2.47358 processing batch 176 of 293 - accuracy= 80.862 - loss: 2.47137 processing batch 177 of 293 - accuracy= 80.829 - loss: 2.47043 processing batch 178 of 293 - accuracy= 80.866 - loss: 2.46877 processing batch 179 of 293 - accuracy= 80.903 - loss: 2.46656 processing batch 180 of 293 - accuracy= 80.801 - loss: 2.46543 processing batch 181 of 293 - accuracy= 80.632 - loss: 2.46648 processing batch 182 of 293 - accuracy= 80.669 - loss: 2.46465 processing batch 183 of 293 - accuracy= 80.774 - loss: 2.46196 processing batch 184 of 293 - accuracy= 80.743 - loss: 2.45988 processing batch 185 of 293 - accuracy= 80.847 - loss: 2.45671 processing batch 186 of 293 - accuracy= 80.749 - loss: 2.45653 processing batch 187 of 293 - accuracy= 80.851 - loss: 2.45351 processing batch 188 of 293 - accuracy= 80.820 - loss: 2.45300 processing batch 189 of 293 - accuracy= 80.789 - loss: 2.45191 processing batch 190 of 293 - accuracy= 80.759 - loss: 2.45080 processing batch 191 of 293 - accuracy= 80.859 - loss: 2.44851 processing batch 192 of 293 - accuracy= 80.829 - loss: 2.44757 processing batch 193 of 293 - accuracy= 80.863 - loss: 2.44592 processing batch 194 of 293 - accuracy= 80.769 - loss: 2.44521 processing batch 195 of 293 - accuracy= 80.804 - loss: 2.44288 processing batch 196 of 293 - accuracy= 80.711 - loss: 2.44922 processing batch 197 of 293 - accuracy= 80.682 - loss: 2.44908 processing batch 198 of 293 - accuracy= 80.590 - loss: 2.44741 processing batch 199 of 293 - accuracy= 80.687 - loss: 2.44461 processing batch 200 of 293 - accuracy= 80.659 - loss: 2.44375 processing batch 201 of 293 - accuracy= 80.755 - loss: 2.44109 processing batch 202 of 293 - accuracy= 80.727 - loss: 2.43985 processing batch 203 of 293 - accuracy= 80.637 - loss: 2.43964 processing batch 204 of 293 - accuracy= 80.610 - loss: 2.43963 processing batch 205 of 293 - accuracy= 80.583 - loss: 2.43975 processing batch 206 of 293 - accuracy= 80.556 - loss: 2.43845 processing batch 207 of 293 - accuracy= 80.469 - loss: 2.43884 processing batch 208 of 293 - accuracy= 80.323 - loss: 2.43994 processing batch 209 of 293 - accuracy= 80.298 - loss: 2.43827 processing batch 210 of 293 - accuracy= 80.213 - loss: 2.43835 processing batch 211 of 293 - accuracy= 80.248 - loss: 2.43567 processing batch 212 of 293 - accuracy= 80.223 - loss: 2.43507 processing batch 213 of 293 - accuracy= 80.257 - loss: 2.43371 processing batch 214 of 293 - accuracy= 80.233 - loss: 2.43277 processing batch 215 of 293 - accuracy= 80.150 - loss: 2.43391 processing batch 216 of 293 - accuracy= 80.127 - loss: 2.43273 processing batch 217 of 293 - accuracy= 80.218 - loss: 2.43055 processing batch 218 of 293 - accuracy= 80.080 - loss: 2.43044 processing batch 219 of 293 - accuracy= 80.114 - loss: 2.42839 processing batch 220 of 293 - accuracy= 80.034 - loss: 2.42788 processing batch 221 of 293 - accuracy= 80.068 - loss: 2.42739 processing batch 222 of 293 - accuracy= 80.157 - loss: 2.42536 processing batch 223 of 293 - accuracy= 80.190 - loss: 2.42346 processing batch 224 of 293 - accuracy= 80.222 - loss: 2.42265 processing batch 225 of 293 - accuracy= 80.199 - loss: 2.42163 processing batch 226 of 293 - accuracy= 80.286 - loss: 2.41957 processing batch 227 of 293 - accuracy= 80.373 - loss: 2.41734 processing batch 228 of 293 - accuracy= 80.404 - loss: 2.41525 processing batch 229 of 293 - accuracy= 80.380 - loss: 2.41494 processing batch 230 of 293 - accuracy= 80.357 - loss: 2.41365 processing batch 231 of 293 - accuracy= 80.334 - loss: 2.41257 processing batch 232 of 293 - accuracy= 80.365 - loss: 2.41317 processing batch 233 of 293 - accuracy= 80.395 - loss: 2.41131 processing batch 234 of 293 - accuracy= 80.426 - loss: 2.40899 processing batch 235 of 293 - accuracy= 80.456 - loss: 2.40714 processing batch 236 of 293 - accuracy= 80.432 - loss: 2.40553 processing batch 237 of 293 - accuracy= 80.515 - loss: 2.40309 processing batch 238 of 293 - accuracy= 80.492 - loss: 2.40154 processing batch 239 of 293 - accuracy= 80.521 - loss: 2.40042 processing batch 240 of 293 - accuracy= 80.394 - loss: 2.40109 processing batch 241 of 293 - accuracy= 80.475 - loss: 2.39870 processing batch 242 of 293 - accuracy= 80.401 - loss: 2.39880 processing batch 243 of 293 - accuracy= 80.482 - loss: 2.39694 processing batch 244 of 293 - accuracy= 80.510 - loss: 2.39664 processing batch 245 of 293 - accuracy= 80.488 - loss: 2.39678 processing batch 246 of 293 - accuracy= 80.415 - loss: 2.39704 processing batch 247 of 293 - accuracy= 80.444 - loss: 2.39506 processing batch 248 of 293 - accuracy= 80.271 - loss: 2.39601 processing batch 249 of 293 - accuracy= 80.350 - loss: 2.39385 processing batch 250 of 293 - accuracy= 80.378 - loss: 2.39236 processing batch 251 of 293 - accuracy= 80.407 - loss: 2.39134 processing batch 252 of 293 - accuracy= 80.336 - loss: 2.39066 processing batch 253 of 293 - accuracy= 80.217 - loss: 2.39015 processing batch 254 of 293 - accuracy= 80.147 - loss: 2.39026 processing batch 255 of 293 - accuracy= 80.127 - loss: 2.38984 processing batch 256 of 293 - accuracy= 80.010 - loss: 2.39207 processing batch 257 of 293 - accuracy= 80.087 - loss: 2.39050 processing batch 258 of 293 - accuracy= 80.019 - loss: 2.38955 processing batch 259 of 293 - accuracy= 80.048 - loss: 2.38871 processing batch 260 of 293 - accuracy= 80.029 - loss: 2.38707 processing batch 261 of 293 - accuracy= 80.010 - loss: 2.38651 processing batch 262 of 293 - accuracy= 80.038 - loss: 2.38555 processing batch 263 of 293 - accuracy= 80.019 - loss: 2.38466 processing batch 264 of 293 - accuracy= 80.094 - loss: 2.38248 processing batch 265 of 293 - accuracy= 80.169 - loss: 2.38066 processing batch 266 of 293 - accuracy= 80.197 - loss: 2.37932 processing batch 267 of 293 - accuracy= 80.224 - loss: 2.37816 processing batch 268 of 293 - accuracy= 80.204 - loss: 2.37944 processing batch 269 of 293 - accuracy= 80.185 - loss: 2.37861 processing batch 270 of 293 - accuracy= 80.212 - loss: 2.37679 processing batch 271 of 293 - accuracy= 80.193 - loss: 2.37699 processing batch 272 of 293 - accuracy= 80.174 - loss: 2.37659 processing batch 273 of 293 - accuracy= 80.155 - loss: 2.37525 processing batch 274 of 293 - accuracy= 80.227 - loss: 2.37322 processing batch 275 of 293 - accuracy= 80.208 - loss: 2.37338 processing batch 276 of 293 - accuracy= 80.280 - loss: 2.37148 processing batch 277 of 293 - accuracy= 80.306 - loss: 2.36992 processing batch 278 of 293 - accuracy= 80.287 - loss: 2.36927 processing batch 279 of 293 - accuracy= 80.268 - loss: 2.36821 processing batch 280 of 293 - accuracy= 80.338 - loss: 2.36587 processing batch 281 of 293 - accuracy= 80.319 - loss: 2.36446 processing batch 282 of 293 - accuracy= 80.345 - loss: 2.36386 processing batch 283 of 293 - accuracy= 80.282 - loss: 2.36392 processing batch 284 of 293 - accuracy= 80.263 - loss: 2.36333 processing batch 285 of 293 - accuracy= 80.288 - loss: 2.36207 processing batch 286 of 293 - accuracy= 80.357 - loss: 2.35982 processing batch 287 of 293 - accuracy= 80.339 - loss: 2.35832 processing batch 288 of 293 - accuracy= 80.320 - loss: 2.35745 processing batch 289 of 293 - accuracy= 80.302 - loss: 2.35760 processing batch 290 of 293 - accuracy= 80.369 - loss: 2.35617 processing batch 291 of 293 - accuracy= 80.394 - loss: 2.35452 processing batch 292 of 293 - accuracy= 80.418 - loss: 2.35272 5 /40 2.353 80.418 2.28494 73.333 0.00100 0.00100 accuracy 3.74 82.64 \nenter H to halt training or an integer for number of epochs to run then ask again\n","output_type":"stream"},{"output_type":"stream","name":"stdin","text":" 10\n"},{"name":"stdout","text":" training will continue until epoch 15\n Epoch Loss Accuracy V_loss V_acc LR Next LR Monitor % Improv Duration\n293/293 [==============================] - 90s 308ms/step - loss: 2.3527 - accuracy: 0.8042 - val_loss: 2.2849 - val_accuracy: 0.7333\nEpoch 6/40\n293/293 [==============================] - ETA: 0s - loss: 1.7787 - accuracy: 0.8208 209 processing batch 1 of 293 - accuracy= 75.000 - loss: 2.05381 processing batch 2 of 293 - accuracy= 83.333 - loss: 1.93159 processing batch 3 of 293 - accuracy= 84.375 - loss: 2.03453 processing batch 4 of 293 - accuracy= 82.500 - loss: 2.01291 processing batch 5 of 293 - accuracy= 85.417 - loss: 1.96827 processing batch 6 of 293 - accuracy= 87.500 - loss: 1.92975 processing batch 7 of 293 - accuracy= 87.500 - loss: 1.92697 processing batch 8 of 293 - accuracy= 84.722 - loss: 2.00772 processing batch 9 of 293 - accuracy= 83.750 - loss: 2.01237 processing batch 10 of 293 - accuracy= 84.091 - loss: 2.00460 processing batch 11 of 293 - accuracy= 82.292 - loss: 2.03042 processing batch 12 of 293 - accuracy= 83.654 - loss: 2.00618 processing batch 13 of 293 - accuracy= 83.036 - loss: 2.01025 processing batch 14 of 293 - accuracy= 83.333 - loss: 1.99453 processing batch 15 of 293 - accuracy= 83.594 - loss: 1.98716 processing batch 16 of 293 - accuracy= 83.824 - loss: 1.97529 processing batch 17 of 293 - accuracy= 83.333 - loss: 1.97449 processing batch 18 of 293 - accuracy= 82.237 - loss: 1.99584 processing batch 19 of 293 - accuracy= 83.125 - loss: 1.98309 processing batch 20 of 293 - accuracy= 83.929 - loss: 1.96393 processing batch 21 of 293 - accuracy= 84.091 - loss: 1.96867 processing batch 22 of 293 - accuracy= 83.696 - loss: 1.97175 processing batch 23 of 293 - accuracy= 83.854 - loss: 1.96120 processing batch 24 of 293 - accuracy= 84.500 - loss: 1.95333 processing batch 25 of 293 - accuracy= 83.654 - loss: 1.96719 processing batch 26 of 293 - accuracy= 83.333 - loss: 1.96568 processing batch 27 of 293 - accuracy= 83.036 - loss: 1.96645 processing batch 28 of 293 - accuracy= 82.759 - loss: 1.97016 processing batch 29 of 293 - accuracy= 81.667 - loss: 1.98004 processing batch 30 of 293 - accuracy= 81.855 - loss: 1.97737 processing batch 31 of 293 - accuracy= 82.422 - loss: 1.96645 processing batch 32 of 293 - accuracy= 81.818 - loss: 1.97310 processing batch 33 of 293 - accuracy= 82.353 - loss: 1.96022 processing batch 34 of 293 - accuracy= 82.500 - loss: 1.95949 processing batch 35 of 293 - accuracy= 82.639 - loss: 1.95191 processing batch 36 of 293 - accuracy= 82.770 - loss: 1.94482 processing batch 37 of 293 - accuracy= 83.224 - loss: 1.94035 processing batch 38 of 293 - accuracy= 83.333 - loss: 1.93680 processing batch 39 of 293 - accuracy= 83.750 - loss: 1.92860 processing batch 40 of 293 - accuracy= 83.537 - loss: 1.92930 processing batch 41 of 293 - accuracy= 83.631 - loss: 1.92719 processing batch 42 of 293 - accuracy= 83.721 - loss: 1.92252 processing batch 43 of 293 - accuracy= 83.523 - loss: 1.92342 processing batch 44 of 293 - accuracy= 83.333 - loss: 1.92427 processing batch 45 of 293 - accuracy= 83.424 - loss: 1.92035 processing batch 46 of 293 - accuracy= 83.511 - loss: 1.92002 processing batch 47 of 293 - accuracy= 83.333 - loss: 1.92825 processing batch 48 of 293 - accuracy= 83.418 - loss: 1.92638 processing batch 49 of 293 - accuracy= 83.250 - loss: 1.93184 processing batch 50 of 293 - accuracy= 83.088 - loss: 1.93008 processing batch 51 of 293 - accuracy= 83.173 - loss: 1.92798 processing batch 52 of 293 - accuracy= 83.491 - loss: 1.92278 processing batch 53 of 293 - accuracy= 83.333 - loss: 1.92556 processing batch 54 of 293 - accuracy= 83.636 - loss: 1.92080 processing batch 55 of 293 - accuracy= 83.705 - loss: 1.91901 processing batch 56 of 293 - accuracy= 83.991 - loss: 1.91235 processing batch 57 of 293 - accuracy= 84.052 - loss: 1.90701 processing batch 58 of 293 - accuracy= 83.898 - loss: 1.90772 processing batch 59 of 293 - accuracy= 83.958 - loss: 1.90794 processing batch 60 of 293 - accuracy= 83.402 - loss: 1.91561 processing batch 61 of 293 - accuracy= 83.468 - loss: 1.91822 processing batch 62 of 293 - accuracy= 83.135 - loss: 1.93100 processing batch 63 of 293 - accuracy= 83.203 - loss: 1.93033 processing batch 64 of 293 - accuracy= 83.462 - loss: 1.92728 processing batch 65 of 293 - accuracy= 83.712 - loss: 1.92134 processing batch 66 of 293 - accuracy= 83.955 - loss: 1.91742 processing batch 67 of 293 - accuracy= 83.824 - loss: 1.92184 processing batch 68 of 293 - accuracy= 83.877 - loss: 1.92333 processing batch 69 of 293 - accuracy= 83.929 - loss: 1.92346 processing batch 70 of 293 - accuracy= 83.803 - loss: 1.92545 processing batch 71 of 293 - accuracy= 83.507 - loss: 1.92888 processing batch 72 of 293 - accuracy= 83.390 - loss: 1.93050 processing batch 73 of 293 - accuracy= 82.939 - loss: 1.93891 processing batch 74 of 293 - accuracy= 83.000 - loss: 1.93482 processing batch 75 of 293 - accuracy= 82.895 - loss: 1.93465 processing batch 76 of 293 - accuracy= 82.792 - loss: 1.93472 processing batch 77 of 293 - accuracy= 82.532 - loss: 1.93470 processing batch 78 of 293 - accuracy= 82.595 - loss: 1.93112 processing batch 79 of 293 - accuracy= 82.812 - loss: 1.92834 processing batch 80 of 293 - accuracy= 83.025 - loss: 1.92385 processing batch 81 of 293 - accuracy= 83.079 - loss: 1.92354 processing batch 82 of 293 - accuracy= 83.283 - loss: 1.91929 processing batch 83 of 293 - accuracy= 83.185 - loss: 1.92132 processing batch 84 of 293 - accuracy= 83.088 - loss: 1.92136 processing batch 85 of 293 - accuracy= 82.994 - loss: 1.92532 processing batch 86 of 293 - accuracy= 82.902 - loss: 1.92627 processing batch 87 of 293 - accuracy= 82.528 - loss: 1.93397 processing batch 88 of 293 - accuracy= 82.584 - loss: 1.93305 processing batch 89 of 293 - accuracy= 82.639 - loss: 1.93203 processing batch 90 of 293 - accuracy= 82.692 - loss: 1.92884 processing batch 91 of 293 - accuracy= 82.609 - loss: 1.92683 processing batch 92 of 293 - accuracy= 82.796 - loss: 1.92354 processing batch 93 of 293 - accuracy= 82.846 - loss: 1.92121 processing batch 94 of 293 - accuracy= 82.632 - loss: 1.92319 processing batch 95 of 293 - accuracy= 82.552 - loss: 1.92155 processing batch 96 of 293 - accuracy= 82.603 - loss: 1.91972 processing batch 97 of 293 - accuracy= 82.781 - loss: 1.91754 processing batch 98 of 293 - accuracy= 82.702 - loss: 1.91716 processing batch 99 of 293 - accuracy= 82.750 - loss: 1.91565 processing batch 100 of 293 - accuracy= 82.673 - loss: 1.91407 processing batch 101 of 293 - accuracy= 82.598 - loss: 1.91198 processing batch 102 of 293 - accuracy= 82.524 - loss: 1.91226 processing batch 103 of 293 - accuracy= 82.572 - loss: 1.91088 processing batch 104 of 293 - accuracy= 82.738 - loss: 1.90784 processing batch 105 of 293 - accuracy= 82.783 - loss: 1.90616 processing batch 106 of 293 - accuracy= 82.710 - loss: 1.90516 processing batch 107 of 293 - accuracy= 82.639 - loss: 1.90583 processing batch 108 of 293 - accuracy= 82.798 - loss: 1.90156 processing batch 109 of 293 - accuracy= 82.955 - loss: 1.89785 processing batch 110 of 293 - accuracy= 82.770 - loss: 1.89897 processing batch 111 of 293 - accuracy= 82.812 - loss: 1.89563 processing batch 112 of 293 - accuracy= 82.965 - loss: 1.89358 processing batch 113 of 293 - accuracy= 83.004 - loss: 1.89081 processing batch 114 of 293 - accuracy= 83.152 - loss: 1.88975 processing batch 115 of 293 - accuracy= 83.082 - loss: 1.88909 processing batch 116 of 293 - accuracy= 83.013 - loss: 1.88741 processing batch 117 of 293 - accuracy= 83.157 - loss: 1.88336 processing batch 118 of 293 - accuracy= 83.298 - loss: 1.87987 processing batch 119 of 293 - accuracy= 83.229 - loss: 1.88380 processing batch 120 of 293 - accuracy= 83.161 - loss: 1.88206 processing batch 121 of 293 - accuracy= 83.299 - loss: 1.87929 processing batch 122 of 293 - accuracy= 83.333 - loss: 1.87707 processing batch 123 of 293 - accuracy= 83.367 - loss: 1.87549 processing batch 124 of 293 - accuracy= 83.500 - loss: 1.87333 processing batch 125 of 293 - accuracy= 83.433 - loss: 1.87313 processing batch 126 of 293 - accuracy= 83.465 - loss: 1.87210 processing batch 127 of 293 - accuracy= 83.398 - loss: 1.87164 processing batch 128 of 293 - accuracy= 83.430 - loss: 1.86963 processing batch 129 of 293 - accuracy= 83.462 - loss: 1.87162 processing batch 130 of 293 - accuracy= 83.397 - loss: 1.87117 processing batch 131 of 293 - accuracy= 83.523 - loss: 1.86868 processing batch 132 of 293 - accuracy= 83.459 - loss: 1.86785 processing batch 133 of 293 - accuracy= 83.489 - loss: 1.86576 processing batch 134 of 293 - accuracy= 83.519 - loss: 1.86582 processing batch 135 of 293 - accuracy= 83.640 - loss: 1.86376 processing batch 136 of 293 - accuracy= 83.668 - loss: 1.86260 processing batch 137 of 293 - accuracy= 83.605 - loss: 1.86218 processing batch 138 of 293 - accuracy= 83.543 - loss: 1.86084 processing batch 139 of 293 - accuracy= 83.661 - loss: 1.85748 processing batch 140 of 293 - accuracy= 83.599 - loss: 1.85543 processing batch 141 of 293 - accuracy= 83.627 - loss: 1.85479 processing batch 142 of 293 - accuracy= 83.654 - loss: 1.85466 processing batch 143 of 293 - accuracy= 83.767 - loss: 1.85256 processing batch 144 of 293 - accuracy= 83.879 - loss: 1.84989 processing batch 145 of 293 - accuracy= 83.818 - loss: 1.85047 processing batch 146 of 293 - accuracy= 83.673 - loss: 1.85318 processing batch 147 of 293 - accuracy= 83.361 - loss: 1.86018 processing batch 148 of 293 - accuracy= 83.389 - loss: 1.85783 processing batch 149 of 293 - accuracy= 83.500 - loss: 1.85528 processing batch 150 of 293 - accuracy= 83.609 - loss: 1.85221 processing batch 151 of 293 - accuracy= 83.553 - loss: 1.85116 processing batch 152 of 293 - accuracy= 83.578 - loss: 1.84907 processing batch 153 of 293 - accuracy= 83.523 - loss: 1.84722 processing batch 154 of 293 - accuracy= 83.468 - loss: 1.84721 processing batch 155 of 293 - accuracy= 83.494 - loss: 1.84538 processing batch 156 of 293 - accuracy= 83.439 - loss: 1.84469 processing batch 157 of 293 - accuracy= 83.386 - loss: 1.84318 processing batch 158 of 293 - accuracy= 83.333 - loss: 1.84255 processing batch 159 of 293 - accuracy= 83.359 - loss: 1.84117 processing batch 160 of 293 - accuracy= 83.230 - loss: 1.84134 processing batch 161 of 293 - accuracy= 83.179 - loss: 1.84050 processing batch 162 of 293 - accuracy= 83.206 - loss: 1.83986 processing batch 163 of 293 - accuracy= 83.308 - loss: 1.83849 processing batch 164 of 293 - accuracy= 83.333 - loss: 1.83732 processing batch 165 of 293 - accuracy= 83.283 - loss: 1.83622 processing batch 166 of 293 - accuracy= 83.308 - loss: 1.83418 processing batch 167 of 293 - accuracy= 83.408 - loss: 1.83237 processing batch 168 of 293 - accuracy= 83.506 - loss: 1.82954 processing batch 169 of 293 - accuracy= 83.603 - loss: 1.82749 processing batch 170 of 293 - accuracy= 83.626 - loss: 1.82562 processing batch 171 of 293 - accuracy= 83.721 - loss: 1.82301 processing batch 172 of 293 - accuracy= 83.743 - loss: 1.82233 processing batch 173 of 293 - accuracy= 83.764 - loss: 1.82063 processing batch 174 of 293 - accuracy= 83.714 - loss: 1.81970 processing batch 175 of 293 - accuracy= 83.736 - loss: 1.81876 processing batch 176 of 293 - accuracy= 83.757 - loss: 1.81879 processing batch 177 of 293 - accuracy= 83.708 - loss: 1.81740 processing batch 178 of 293 - accuracy= 83.520 - loss: 1.81868 processing batch 179 of 293 - accuracy= 83.472 - loss: 1.81799 processing batch 180 of 293 - accuracy= 83.425 - loss: 1.81751 processing batch 181 of 293 - accuracy= 83.516 - loss: 1.81522 processing batch 182 of 293 - accuracy= 83.402 - loss: 1.81611 processing batch 183 of 293 - accuracy= 83.356 - loss: 1.81549 processing batch 184 of 293 - accuracy= 83.311 - loss: 1.81539 processing batch 185 of 293 - accuracy= 83.132 - loss: 1.81624 processing batch 186 of 293 - accuracy= 83.155 - loss: 1.81436 processing batch 187 of 293 - accuracy= 83.245 - loss: 1.81265 processing batch 188 of 293 - accuracy= 83.267 - loss: 1.81137 processing batch 189 of 293 - accuracy= 83.092 - loss: 1.81344 processing batch 190 of 293 - accuracy= 83.181 - loss: 1.81142 processing batch 191 of 293 - accuracy= 83.203 - loss: 1.81107 processing batch 192 of 293 - accuracy= 83.161 - loss: 1.81052 processing batch 193 of 293 - accuracy= 82.925 - loss: 1.81440 processing batch 194 of 293 - accuracy= 82.949 - loss: 1.81490 processing batch 195 of 293 - accuracy= 82.717 - loss: 1.81732 processing batch 196 of 293 - accuracy= 82.614 - loss: 1.81999 processing batch 197 of 293 - accuracy= 82.576 - loss: 1.82139 processing batch 198 of 293 - accuracy= 82.538 - loss: 1.82034 processing batch 199 of 293 - accuracy= 82.375 - loss: 1.82098 processing batch 200 of 293 - accuracy= 82.338 - loss: 1.82033 processing batch 201 of 293 - accuracy= 82.364 - loss: 1.81914 processing batch 202 of 293 - accuracy= 82.204 - loss: 1.82351 processing batch 203 of 293 - accuracy= 82.292 - loss: 1.82145 processing batch 204 of 293 - accuracy= 82.256 - loss: 1.82102 processing batch 205 of 293 - accuracy= 82.282 - loss: 1.82025 processing batch 206 of 293 - accuracy= 82.246 - loss: 1.81972 processing batch 207 of 293 - accuracy= 82.212 - loss: 1.81892 processing batch 208 of 293 - accuracy= 82.117 - loss: 1.81909 processing batch 209 of 293 - accuracy= 82.143 - loss: 1.81823 processing batch 210 of 293 - accuracy= 82.227 - loss: 1.81670 processing batch 211 of 293 - accuracy= 82.311 - loss: 1.81510 processing batch 212 of 293 - accuracy= 82.394 - loss: 1.81385 processing batch 213 of 293 - accuracy= 82.418 - loss: 1.81386 processing batch 214 of 293 - accuracy= 82.384 - loss: 1.81641 processing batch 215 of 293 - accuracy= 82.407 - loss: 1.81539 processing batch 216 of 293 - accuracy= 82.373 - loss: 1.81447 processing batch 217 of 293 - accuracy= 82.454 - loss: 1.81285 processing batch 218 of 293 - accuracy= 82.420 - loss: 1.81272 processing batch 219 of 293 - accuracy= 82.443 - loss: 1.81219 processing batch 220 of 293 - accuracy= 82.523 - loss: 1.81061 processing batch 221 of 293 - accuracy= 82.601 - loss: 1.80884 processing batch 222 of 293 - accuracy= 82.679 - loss: 1.80707 processing batch 223 of 293 - accuracy= 82.701 - loss: 1.80595 processing batch 224 of 293 - accuracy= 82.611 - loss: 1.80766 processing batch 225 of 293 - accuracy= 82.522 - loss: 1.80733 processing batch 226 of 293 - accuracy= 82.544 - loss: 1.80580 processing batch 227 of 293 - accuracy= 82.511 - loss: 1.80503 processing batch 228 of 293 - accuracy= 82.369 - loss: 1.80777 processing batch 229 of 293 - accuracy= 82.283 - loss: 1.80752 processing batch 230 of 293 - accuracy= 82.251 - loss: 1.80747 processing batch 231 of 293 - accuracy= 82.274 - loss: 1.80586 processing batch 232 of 293 - accuracy= 82.350 - loss: 1.80369 processing batch 233 of 293 - accuracy= 82.318 - loss: 1.80437 processing batch 234 of 293 - accuracy= 82.394 - loss: 1.80322 processing batch 235 of 293 - accuracy= 82.415 - loss: 1.80213 processing batch 236 of 293 - accuracy= 82.384 - loss: 1.80319 processing batch 237 of 293 - accuracy= 82.458 - loss: 1.80143 processing batch 238 of 293 - accuracy= 82.531 - loss: 1.79963 processing batch 239 of 293 - accuracy= 82.552 - loss: 1.79976 processing batch 240 of 293 - accuracy= 82.573 - loss: 1.79868 processing batch 241 of 293 - accuracy= 82.593 - loss: 1.79751 processing batch 242 of 293 - accuracy= 82.562 - loss: 1.79719 processing batch 243 of 293 - accuracy= 82.531 - loss: 1.80005 processing batch 244 of 293 - accuracy= 82.500 - loss: 1.80038 processing batch 245 of 293 - accuracy= 82.520 - loss: 1.79879 processing batch 246 of 293 - accuracy= 82.540 - loss: 1.79972 processing batch 247 of 293 - accuracy= 82.560 - loss: 1.79887 processing batch 248 of 293 - accuracy= 82.530 - loss: 1.79799 processing batch 249 of 293 - accuracy= 82.550 - loss: 1.79636 processing batch 250 of 293 - accuracy= 82.620 - loss: 1.79480 processing batch 251 of 293 - accuracy= 82.589 - loss: 1.79419 processing batch 252 of 293 - accuracy= 82.510 - loss: 1.79444 processing batch 253 of 293 - accuracy= 82.431 - loss: 1.79495 processing batch 254 of 293 - accuracy= 82.353 - loss: 1.79489 processing batch 255 of 293 - accuracy= 82.275 - loss: 1.79457 processing batch 256 of 293 - accuracy= 82.150 - loss: 1.79920 processing batch 257 of 293 - accuracy= 82.171 - loss: 1.79778 processing batch 258 of 293 - accuracy= 82.239 - loss: 1.79558 processing batch 259 of 293 - accuracy= 82.212 - loss: 1.79463 processing batch 260 of 293 - accuracy= 82.280 - loss: 1.79319 processing batch 261 of 293 - accuracy= 82.252 - loss: 1.79330 processing batch 262 of 293 - accuracy= 82.272 - loss: 1.79335 processing batch 263 of 293 - accuracy= 82.197 - loss: 1.79305 processing batch 264 of 293 - accuracy= 82.217 - loss: 1.79208 processing batch 265 of 293 - accuracy= 82.284 - loss: 1.79025 processing batch 266 of 293 - accuracy= 82.210 - loss: 1.79105 processing batch 267 of 293 - accuracy= 82.183 - loss: 1.79099 processing batch 268 of 293 - accuracy= 82.249 - loss: 1.78900 processing batch 269 of 293 - accuracy= 82.315 - loss: 1.78688 processing batch 270 of 293 - accuracy= 82.288 - loss: 1.78624 processing batch 271 of 293 - accuracy= 82.123 - loss: 1.78901 processing batch 272 of 293 - accuracy= 82.097 - loss: 1.78857 processing batch 273 of 293 - accuracy= 82.117 - loss: 1.78769 processing batch 274 of 293 - accuracy= 82.136 - loss: 1.78604 processing batch 275 of 293 - accuracy= 82.156 - loss: 1.78543 processing batch 276 of 293 - accuracy= 82.130 - loss: 1.78486 processing batch 277 of 293 - accuracy= 81.969 - loss: 1.78672 processing batch 278 of 293 - accuracy= 81.989 - loss: 1.78560 processing batch 279 of 293 - accuracy= 82.009 - loss: 1.78548 processing batch 280 of 293 - accuracy= 82.028 - loss: 1.78460 processing batch 281 of 293 - accuracy= 82.092 - loss: 1.78281 processing batch 282 of 293 - accuracy= 82.111 - loss: 1.78184 processing batch 283 of 293 - accuracy= 82.086 - loss: 1.78173 processing batch 284 of 293 - accuracy= 81.974 - loss: 1.78556 processing batch 285 of 293 - accuracy= 81.949 - loss: 1.78515 processing batch 286 of 293 - accuracy= 81.969 - loss: 1.78411 processing batch 287 of 293 - accuracy= 81.944 - loss: 1.78476 processing batch 288 of 293 - accuracy= 81.964 - loss: 1.78327 processing batch 289 of 293 - accuracy= 81.983 - loss: 1.78236 processing batch 290 of 293 - accuracy= 82.002 - loss: 1.78111 processing batch 291 of 293 - accuracy= 82.021 - loss: 1.78020 processing batch 292 of 293 - accuracy= 82.082 - loss: 1.77871 6 /40 1.779 82.082 2.12740 57.436 0.00100 0.00100 accuracy 2.07 82.37 \n293/293 [==============================] - 83s 281ms/step - loss: 1.7787 - accuracy: 0.8208 - val_loss: 2.1274 - val_accuracy: 0.5744\nEpoch 7/40\n293/293 [==============================] - ETA: 0s - loss: 1.3926 - accuracy: 0.8375 2651 processing batch 1 of 293 - accuracy= 87.500 - loss: 1.35405 processing batch 2 of 293 - accuracy= 87.500 - loss: 1.34039 processing batch 3 of 293 - accuracy= 87.500 - loss: 1.39617 processing batch 4 of 293 - accuracy= 80.000 - loss: 1.55151 processing batch 5 of 293 - accuracy= 83.333 - loss: 1.52167 processing batch 6 of 293 - accuracy= 83.929 - loss: 1.49433 processing batch 7 of 293 - accuracy= 82.812 - loss: 1.50781 processing batch 8 of 293 - accuracy= 81.944 - loss: 1.54520 processing batch 9 of 293 - accuracy= 81.250 - loss: 1.53532 processing batch 10 of 293 - accuracy= 81.818 - loss: 1.53885 processing batch 11 of 293 - accuracy= 83.333 - loss: 1.51325 processing batch 12 of 293 - accuracy= 82.692 - loss: 1.51232 processing batch 13 of 293 - accuracy= 83.036 - loss: 1.49585 processing batch 14 of 293 - accuracy= 81.667 - loss: 1.50009 processing batch 15 of 293 - accuracy= 82.812 - loss: 1.49644 processing batch 16 of 293 - accuracy= 82.353 - loss: 1.50234 processing batch 17 of 293 - accuracy= 83.333 - loss: 1.48885 processing batch 18 of 293 - accuracy= 82.895 - loss: 1.48296 processing batch 19 of 293 - accuracy= 82.500 - loss: 1.48812 processing batch 20 of 293 - accuracy= 82.738 - loss: 1.48689 processing batch 21 of 293 - accuracy= 81.818 - loss: 1.49522 processing batch 22 of 293 - accuracy= 82.065 - loss: 1.49311 processing batch 23 of 293 - accuracy= 82.292 - loss: 1.49779 processing batch 24 of 293 - accuracy= 83.000 - loss: 1.48546 processing batch 25 of 293 - accuracy= 83.173 - loss: 1.48336 processing batch 26 of 293 - accuracy= 83.796 - loss: 1.47464 processing batch 27 of 293 - accuracy= 83.929 - loss: 1.47134 processing batch 28 of 293 - accuracy= 84.052 - loss: 1.47457 processing batch 29 of 293 - accuracy= 82.917 - loss: 1.49741 processing batch 30 of 293 - accuracy= 82.661 - loss: 1.49622 processing batch 31 of 293 - accuracy= 83.203 - loss: 1.48930 processing batch 32 of 293 - accuracy= 83.712 - loss: 1.48159 processing batch 33 of 293 - accuracy= 83.456 - loss: 1.48695 processing batch 34 of 293 - accuracy= 83.214 - loss: 1.49099 processing batch 35 of 293 - accuracy= 83.333 - loss: 1.48803 processing batch 36 of 293 - accuracy= 82.770 - loss: 1.49407 processing batch 37 of 293 - accuracy= 82.895 - loss: 1.49598 processing batch 38 of 293 - accuracy= 83.013 - loss: 1.49254 processing batch 39 of 293 - accuracy= 82.812 - loss: 1.49876 processing batch 40 of 293 - accuracy= 83.232 - loss: 1.49031 processing batch 41 of 293 - accuracy= 83.631 - loss: 1.48360 processing batch 42 of 293 - accuracy= 83.721 - loss: 1.47797 processing batch 43 of 293 - accuracy= 83.807 - loss: 1.47829 processing batch 44 of 293 - accuracy= 83.889 - loss: 1.47510 processing batch 45 of 293 - accuracy= 83.967 - loss: 1.47764 processing batch 46 of 293 - accuracy= 83.511 - loss: 1.48418 processing batch 47 of 293 - accuracy= 83.854 - loss: 1.47852 processing batch 48 of 293 - accuracy= 83.929 - loss: 1.48266 processing batch 49 of 293 - accuracy= 84.250 - loss: 1.47674 processing batch 50 of 293 - accuracy= 84.314 - loss: 1.47886 processing batch 51 of 293 - accuracy= 83.894 - loss: 1.48729 processing batch 52 of 293 - accuracy= 83.726 - loss: 1.48597 processing batch 53 of 293 - accuracy= 83.333 - loss: 1.48977 processing batch 54 of 293 - accuracy= 83.636 - loss: 1.48449 processing batch 55 of 293 - accuracy= 83.482 - loss: 1.48365 processing batch 56 of 293 - accuracy= 83.114 - loss: 1.48523 processing batch 57 of 293 - accuracy= 82.974 - loss: 1.48528 processing batch 58 of 293 - accuracy= 82.839 - loss: 1.48509 processing batch 59 of 293 - accuracy= 82.708 - loss: 1.48513 processing batch 60 of 293 - accuracy= 82.787 - loss: 1.48760 processing batch 61 of 293 - accuracy= 82.863 - loss: 1.48457 processing batch 62 of 293 - accuracy= 82.937 - loss: 1.48142 processing batch 63 of 293 - accuracy= 83.008 - loss: 1.47823 processing batch 64 of 293 - accuracy= 82.885 - loss: 1.48152 processing batch 65 of 293 - accuracy= 82.765 - loss: 1.48114 processing batch 66 of 293 - accuracy= 82.649 - loss: 1.48271 processing batch 67 of 293 - accuracy= 82.904 - loss: 1.47957 processing batch 68 of 293 - accuracy= 82.790 - loss: 1.48391 processing batch 69 of 293 - accuracy= 82.321 - loss: 1.48945 processing batch 70 of 293 - accuracy= 82.394 - loss: 1.48756 processing batch 71 of 293 - accuracy= 82.465 - loss: 1.48760 processing batch 72 of 293 - accuracy= 82.534 - loss: 1.48749 processing batch 73 of 293 - accuracy= 82.770 - loss: 1.48468 processing batch 74 of 293 - accuracy= 82.833 - loss: 1.48578 processing batch 75 of 293 - accuracy= 82.895 - loss: 1.48299 processing batch 76 of 293 - accuracy= 82.955 - loss: 1.48392 processing batch 77 of 293 - accuracy= 83.013 - loss: 1.48404 processing batch 78 of 293 - accuracy= 82.911 - loss: 1.48891 processing batch 79 of 293 - accuracy= 82.656 - loss: 1.49345 processing batch 80 of 293 - accuracy= 82.716 - loss: 1.49054 processing batch 81 of 293 - accuracy= 82.317 - loss: 1.50007 processing batch 82 of 293 - accuracy= 82.229 - loss: 1.50195 processing batch 83 of 293 - accuracy= 82.440 - loss: 1.49864 processing batch 84 of 293 - accuracy= 82.206 - loss: 1.50027 processing batch 85 of 293 - accuracy= 82.122 - loss: 1.50356 processing batch 86 of 293 - accuracy= 82.328 - loss: 1.49945 processing batch 87 of 293 - accuracy= 82.386 - loss: 1.49747 processing batch 88 of 293 - accuracy= 82.303 - loss: 1.49724 processing batch 89 of 293 - accuracy= 82.361 - loss: 1.49532 processing batch 90 of 293 - accuracy= 82.280 - loss: 1.49722 processing batch 91 of 293 - accuracy= 82.201 - loss: 1.49668 processing batch 92 of 293 - accuracy= 82.258 - loss: 1.49563 processing batch 93 of 293 - accuracy= 82.048 - loss: 1.50044 processing batch 94 of 293 - accuracy= 82.237 - loss: 1.49838 processing batch 95 of 293 - accuracy= 82.292 - loss: 1.49601 processing batch 96 of 293 - accuracy= 82.216 - loss: 1.49649 processing batch 97 of 293 - accuracy= 82.143 - loss: 1.49655 processing batch 98 of 293 - accuracy= 82.323 - loss: 1.49468 processing batch 99 of 293 - accuracy= 82.375 - loss: 1.49243 processing batch 100 of 293 - accuracy= 82.550 - loss: 1.48927 processing batch 101 of 293 - accuracy= 82.353 - loss: 1.49457 processing batch 102 of 293 - accuracy= 82.160 - loss: 1.49717 processing batch 103 of 293 - accuracy= 82.091 - loss: 1.49757 processing batch 104 of 293 - accuracy= 82.143 - loss: 1.49519 processing batch 105 of 293 - accuracy= 82.075 - loss: 1.49628 processing batch 106 of 293 - accuracy= 82.243 - loss: 1.49355 processing batch 107 of 293 - accuracy= 82.176 - loss: 1.49735 processing batch 108 of 293 - accuracy= 81.995 - loss: 1.49699 processing batch 109 of 293 - accuracy= 81.932 - loss: 1.49807 processing batch 110 of 293 - accuracy= 81.869 - loss: 1.49874 processing batch 111 of 293 - accuracy= 81.920 - loss: 1.49688 processing batch 112 of 293 - accuracy= 81.969 - loss: 1.49490 processing batch 113 of 293 - accuracy= 82.018 - loss: 1.49267 processing batch 114 of 293 - accuracy= 82.065 - loss: 1.49126 processing batch 115 of 293 - accuracy= 82.112 - loss: 1.48861 processing batch 116 of 293 - accuracy= 82.158 - loss: 1.48662 processing batch 117 of 293 - accuracy= 82.203 - loss: 1.48544 processing batch 118 of 293 - accuracy= 82.143 - loss: 1.48455 processing batch 119 of 293 - accuracy= 82.292 - loss: 1.48161 processing batch 120 of 293 - accuracy= 82.335 - loss: 1.48170 processing batch 121 of 293 - accuracy= 82.377 - loss: 1.48154 processing batch 122 of 293 - accuracy= 82.419 - loss: 1.48084 processing batch 123 of 293 - accuracy= 82.359 - loss: 1.48104 processing batch 124 of 293 - accuracy= 82.400 - loss: 1.48141 processing batch 125 of 293 - accuracy= 82.341 - loss: 1.48122 processing batch 126 of 293 - accuracy= 82.382 - loss: 1.48053 processing batch 127 of 293 - accuracy= 82.422 - loss: 1.48026 processing batch 128 of 293 - accuracy= 82.364 - loss: 1.48105 processing batch 129 of 293 - accuracy= 82.404 - loss: 1.47908 processing batch 130 of 293 - accuracy= 82.538 - loss: 1.47616 processing batch 131 of 293 - accuracy= 82.481 - loss: 1.47514 processing batch 132 of 293 - accuracy= 82.331 - loss: 1.48092 processing batch 133 of 293 - accuracy= 82.276 - loss: 1.48004 processing batch 134 of 293 - accuracy= 82.407 - loss: 1.47678 processing batch 135 of 293 - accuracy= 82.261 - loss: 1.47888 processing batch 136 of 293 - accuracy= 82.299 - loss: 1.47685 processing batch 137 of 293 - accuracy= 82.246 - loss: 1.47697 processing batch 138 of 293 - accuracy= 82.374 - loss: 1.47402 processing batch 139 of 293 - accuracy= 82.500 - loss: 1.47186 processing batch 140 of 293 - accuracy= 82.535 - loss: 1.47117 processing batch 141 of 293 - accuracy= 82.658 - loss: 1.46883 processing batch 142 of 293 - accuracy= 82.517 - loss: 1.46921 processing batch 143 of 293 - accuracy= 82.639 - loss: 1.46850 processing batch 144 of 293 - accuracy= 82.759 - loss: 1.46578 processing batch 145 of 293 - accuracy= 82.705 - loss: 1.46517 processing batch 146 of 293 - accuracy= 82.653 - loss: 1.46528 processing batch 147 of 293 - accuracy= 82.601 - loss: 1.46545 processing batch 148 of 293 - accuracy= 82.466 - loss: 1.46826 processing batch 149 of 293 - accuracy= 82.583 - loss: 1.46578 processing batch 150 of 293 - accuracy= 82.699 - loss: 1.46408 processing batch 151 of 293 - accuracy= 82.812 - loss: 1.46253 processing batch 152 of 293 - accuracy= 82.843 - loss: 1.46105 processing batch 153 of 293 - accuracy= 82.792 - loss: 1.46036 processing batch 154 of 293 - accuracy= 82.742 - loss: 1.45900 processing batch 155 of 293 - accuracy= 82.772 - loss: 1.45934 processing batch 156 of 293 - accuracy= 82.803 - loss: 1.45765 processing batch 157 of 293 - accuracy= 82.753 - loss: 1.45830 processing batch 158 of 293 - accuracy= 82.862 - loss: 1.45582 processing batch 159 of 293 - accuracy= 82.969 - loss: 1.45327 processing batch 160 of 293 - accuracy= 82.919 - loss: 1.45338 processing batch 161 of 293 - accuracy= 82.948 - loss: 1.45135 processing batch 162 of 293 - accuracy= 83.052 - loss: 1.44960 processing batch 163 of 293 - accuracy= 82.927 - loss: 1.45086 processing batch 164 of 293 - accuracy= 82.879 - loss: 1.45154 processing batch 165 of 293 - accuracy= 82.831 - loss: 1.45218 processing batch 166 of 293 - accuracy= 82.784 - loss: 1.45209 processing batch 167 of 293 - accuracy= 82.812 - loss: 1.45209 processing batch 168 of 293 - accuracy= 82.840 - loss: 1.45179 processing batch 169 of 293 - accuracy= 82.868 - loss: 1.45008 processing batch 170 of 293 - accuracy= 82.968 - loss: 1.44843 processing batch 171 of 293 - accuracy= 82.922 - loss: 1.44785 processing batch 172 of 293 - accuracy= 82.803 - loss: 1.44857 processing batch 173 of 293 - accuracy= 82.902 - loss: 1.44703 processing batch 174 of 293 - accuracy= 82.929 - loss: 1.44524 processing batch 175 of 293 - accuracy= 83.026 - loss: 1.44426 processing batch 176 of 293 - accuracy= 83.051 - loss: 1.44367 processing batch 177 of 293 - accuracy= 83.076 - loss: 1.44306 processing batch 178 of 293 - accuracy= 83.031 - loss: 1.44497 processing batch 179 of 293 - accuracy= 83.056 - loss: 1.44451 processing batch 180 of 293 - accuracy= 83.011 - loss: 1.44511 processing batch 181 of 293 - accuracy= 83.036 - loss: 1.44472 processing batch 182 of 293 - accuracy= 83.128 - loss: 1.44329 processing batch 183 of 293 - accuracy= 83.152 - loss: 1.44204 processing batch 184 of 293 - accuracy= 83.176 - loss: 1.44094 processing batch 185 of 293 - accuracy= 83.199 - loss: 1.44041 processing batch 186 of 293 - accuracy= 83.155 - loss: 1.44006 processing batch 187 of 293 - accuracy= 83.112 - loss: 1.44151 processing batch 188 of 293 - accuracy= 83.069 - loss: 1.44070 processing batch 189 of 293 - accuracy= 83.092 - loss: 1.43892 processing batch 190 of 293 - accuracy= 83.115 - loss: 1.43805 processing batch 191 of 293 - accuracy= 83.073 - loss: 1.43816 processing batch 192 of 293 - accuracy= 83.096 - loss: 1.43687 processing batch 193 of 293 - accuracy= 83.119 - loss: 1.43522 processing batch 194 of 293 - accuracy= 83.205 - loss: 1.43321 processing batch 195 of 293 - accuracy= 83.291 - loss: 1.43144 processing batch 196 of 293 - accuracy= 83.249 - loss: 1.43106 processing batch 197 of 293 - accuracy= 83.270 - loss: 1.42971 processing batch 198 of 293 - accuracy= 83.291 - loss: 1.42925 processing batch 199 of 293 - accuracy= 83.375 - loss: 1.42740 processing batch 200 of 293 - accuracy= 83.458 - loss: 1.42537 processing batch 201 of 293 - accuracy= 83.540 - loss: 1.42383 processing batch 202 of 293 - accuracy= 83.621 - loss: 1.42215 processing batch 203 of 293 - accuracy= 83.578 - loss: 1.42225 processing batch 204 of 293 - accuracy= 83.537 - loss: 1.42360 processing batch 205 of 293 - accuracy= 83.556 - loss: 1.42281 processing batch 206 of 293 - accuracy= 83.635 - loss: 1.42069 processing batch 207 of 293 - accuracy= 83.594 - loss: 1.42063 processing batch 208 of 293 - accuracy= 83.612 - loss: 1.42034 processing batch 209 of 293 - accuracy= 83.631 - loss: 1.42008 processing batch 210 of 293 - accuracy= 83.649 - loss: 1.41892 processing batch 211 of 293 - accuracy= 83.726 - loss: 1.41680 processing batch 212 of 293 - accuracy= 83.803 - loss: 1.41525 processing batch 213 of 293 - accuracy= 83.703 - loss: 1.41719 processing batch 214 of 293 - accuracy= 83.721 - loss: 1.41657 processing batch 215 of 293 - accuracy= 83.796 - loss: 1.41520 processing batch 216 of 293 - accuracy= 83.871 - loss: 1.41356 processing batch 217 of 293 - accuracy= 83.830 - loss: 1.41442 processing batch 218 of 293 - accuracy= 83.790 - loss: 1.41411 processing batch 219 of 293 - accuracy= 83.807 - loss: 1.41339 processing batch 220 of 293 - accuracy= 83.880 - loss: 1.41154 processing batch 221 of 293 - accuracy= 83.896 - loss: 1.41051 processing batch 222 of 293 - accuracy= 83.969 - loss: 1.40850 processing batch 223 of 293 - accuracy= 83.929 - loss: 1.40927 processing batch 224 of 293 - accuracy= 83.833 - loss: 1.41125 processing batch 225 of 293 - accuracy= 83.850 - loss: 1.41137 processing batch 226 of 293 - accuracy= 83.811 - loss: 1.41193 processing batch 227 of 293 - accuracy= 83.772 - loss: 1.41199 processing batch 228 of 293 - accuracy= 83.734 - loss: 1.41249 processing batch 229 of 293 - accuracy= 83.750 - loss: 1.41139 processing batch 230 of 293 - accuracy= 83.766 - loss: 1.41259 processing batch 231 of 293 - accuracy= 83.728 - loss: 1.41269 processing batch 232 of 293 - accuracy= 83.691 - loss: 1.41383 processing batch 233 of 293 - accuracy= 83.707 - loss: 1.41304 processing batch 234 of 293 - accuracy= 83.777 - loss: 1.41245 processing batch 235 of 293 - accuracy= 83.792 - loss: 1.41186 processing batch 236 of 293 - accuracy= 83.808 - loss: 1.41141 processing batch 237 of 293 - accuracy= 83.824 - loss: 1.41117 processing batch 238 of 293 - accuracy= 83.787 - loss: 1.41178 processing batch 239 of 293 - accuracy= 83.854 - loss: 1.41061 processing batch 240 of 293 - accuracy= 83.921 - loss: 1.40895 processing batch 241 of 293 - accuracy= 83.884 - loss: 1.40842 processing batch 242 of 293 - accuracy= 83.796 - loss: 1.40930 processing batch 243 of 293 - accuracy= 83.760 - loss: 1.40821 processing batch 244 of 293 - accuracy= 83.827 - loss: 1.40712 processing batch 245 of 293 - accuracy= 83.841 - loss: 1.40650 processing batch 246 of 293 - accuracy= 83.907 - loss: 1.40544 processing batch 247 of 293 - accuracy= 83.770 - loss: 1.40792 processing batch 248 of 293 - accuracy= 83.685 - loss: 1.40861 processing batch 249 of 293 - accuracy= 83.750 - loss: 1.40697 processing batch 250 of 293 - accuracy= 83.765 - loss: 1.40666 processing batch 251 of 293 - accuracy= 83.730 - loss: 1.40689 processing batch 252 of 293 - accuracy= 83.794 - loss: 1.40539 processing batch 253 of 293 - accuracy= 83.809 - loss: 1.40443 processing batch 254 of 293 - accuracy= 83.873 - loss: 1.40279 processing batch 255 of 293 - accuracy= 83.936 - loss: 1.40165 processing batch 256 of 293 - accuracy= 83.949 - loss: 1.40107 processing batch 257 of 293 - accuracy= 83.963 - loss: 1.40025 processing batch 258 of 293 - accuracy= 83.977 - loss: 1.40011 processing batch 259 of 293 - accuracy= 83.942 - loss: 1.40024 processing batch 260 of 293 - accuracy= 83.908 - loss: 1.39962 processing batch 261 of 293 - accuracy= 83.922 - loss: 1.39916 processing batch 262 of 293 - accuracy= 83.888 - loss: 1.39926 processing batch 263 of 293 - accuracy= 83.807 - loss: 1.40630 processing batch 264 of 293 - accuracy= 83.774 - loss: 1.40701 processing batch 265 of 293 - accuracy= 83.835 - loss: 1.40597 processing batch 266 of 293 - accuracy= 83.755 - loss: 1.40603 processing batch 267 of 293 - accuracy= 83.675 - loss: 1.40697 processing batch 268 of 293 - accuracy= 83.690 - loss: 1.40583 processing batch 269 of 293 - accuracy= 83.611 - loss: 1.40719 processing batch 270 of 293 - accuracy= 83.625 - loss: 1.40605 processing batch 271 of 293 - accuracy= 83.686 - loss: 1.40464 processing batch 272 of 293 - accuracy= 83.654 - loss: 1.40417 processing batch 273 of 293 - accuracy= 83.622 - loss: 1.40389 processing batch 274 of 293 - accuracy= 83.636 - loss: 1.40395 processing batch 275 of 293 - accuracy= 83.650 - loss: 1.40345 processing batch 276 of 293 - accuracy= 83.709 - loss: 1.40189 processing batch 277 of 293 - accuracy= 83.678 - loss: 1.40104 processing batch 278 of 293 - accuracy= 83.647 - loss: 1.40077 processing batch 279 of 293 - accuracy= 83.571 - loss: 1.40204 processing batch 280 of 293 - accuracy= 83.585 - loss: 1.40121 processing batch 281 of 293 - accuracy= 83.599 - loss: 1.40038 processing batch 282 of 293 - accuracy= 83.613 - loss: 1.39981 processing batch 283 of 293 - accuracy= 83.627 - loss: 1.39908 processing batch 284 of 293 - accuracy= 83.640 - loss: 1.39895 processing batch 285 of 293 - accuracy= 83.566 - loss: 1.39889 processing batch 286 of 293 - accuracy= 83.493 - loss: 1.39959 processing batch 287 of 293 - accuracy= 83.550 - loss: 1.39820 processing batch 288 of 293 - accuracy= 83.607 - loss: 1.39685 processing batch 289 of 293 - accuracy= 83.664 - loss: 1.39594 processing batch 290 of 293 - accuracy= 83.677 - loss: 1.39509 processing batch 291 of 293 - accuracy= 83.733 - loss: 1.39345 processing batch 292 of 293 - accuracy= 83.746 - loss: 1.39259 7 /40 1.393 83.746 3.58922 48.376 0.00100 0.00100 accuracy 2.03 82.57 \n293/293 [==============================] - 83s 282ms/step - loss: 1.3926 - accuracy: 0.8375 - val_loss: 3.5892 - val_accuracy: 0.4838\nEpoch 8/40\n293/293 [==============================] - ETA: 0s - loss: 1.1097 - accuracy: 0.8648 7276 processing batch 1 of 293 - accuracy= 93.750 - loss: 1.03975 processing batch 2 of 293 - accuracy= 91.667 - loss: 1.06267 processing batch 3 of 293 - accuracy= 90.625 - loss: 1.08596 processing batch 4 of 293 - accuracy= 92.500 - loss: 1.06867 processing batch 5 of 293 - accuracy= 91.667 - loss: 1.10292 processing batch 6 of 293 - accuracy= 89.286 - loss: 1.12490 processing batch 7 of 293 - accuracy= 89.062 - loss: 1.12153 processing batch 8 of 293 - accuracy= 90.278 - loss: 1.11852 processing batch 9 of 293 - accuracy= 90.000 - loss: 1.11294 processing batch 10 of 293 - accuracy= 89.773 - loss: 1.10498 processing batch 11 of 293 - accuracy= 88.542 - loss: 1.11795 processing batch 12 of 293 - accuracy= 88.462 - loss: 1.12792 processing batch 13 of 293 - accuracy= 89.286 - loss: 1.11447 processing batch 14 of 293 - accuracy= 90.000 - loss: 1.10106 processing batch 15 of 293 - accuracy= 90.625 - loss: 1.09040 processing batch 16 of 293 - accuracy= 90.441 - loss: 1.09857 processing batch 17 of 293 - accuracy= 87.500 - loss: 1.13584 processing batch 18 of 293 - accuracy= 87.500 - loss: 1.12931 processing batch 19 of 293 - accuracy= 84.375 - loss: 1.20279 processing batch 20 of 293 - accuracy= 83.929 - loss: 1.20448 processing batch 21 of 293 - accuracy= 84.659 - loss: 1.19572 processing batch 22 of 293 - accuracy= 85.326 - loss: 1.18428 processing batch 23 of 293 - accuracy= 84.896 - loss: 1.18373 processing batch 24 of 293 - accuracy= 84.500 - loss: 1.18655 processing batch 25 of 293 - accuracy= 85.096 - loss: 1.17832 processing batch 26 of 293 - accuracy= 84.722 - loss: 1.18235 processing batch 27 of 293 - accuracy= 84.821 - loss: 1.18356 processing batch 28 of 293 - accuracy= 84.483 - loss: 1.18898 processing batch 29 of 293 - accuracy= 84.167 - loss: 1.19216 processing batch 30 of 293 - accuracy= 84.677 - loss: 1.18342 processing batch 31 of 293 - accuracy= 84.766 - loss: 1.18500 processing batch 32 of 293 - accuracy= 84.848 - loss: 1.18405 processing batch 33 of 293 - accuracy= 84.559 - loss: 1.19402 processing batch 34 of 293 - accuracy= 84.643 - loss: 1.19475 processing batch 35 of 293 - accuracy= 84.722 - loss: 1.20107 processing batch 36 of 293 - accuracy= 84.459 - loss: 1.21581 processing batch 37 of 293 - accuracy= 84.868 - loss: 1.21079 processing batch 38 of 293 - accuracy= 84.936 - loss: 1.20880 processing batch 39 of 293 - accuracy= 85.312 - loss: 1.20347 processing batch 40 of 293 - accuracy= 85.671 - loss: 1.20263 processing batch 41 of 293 - accuracy= 85.714 - loss: 1.19844 processing batch 42 of 293 - accuracy= 85.465 - loss: 1.20033 processing batch 43 of 293 - accuracy= 85.511 - loss: 1.20172 processing batch 44 of 293 - accuracy= 85.556 - loss: 1.19954 processing batch 45 of 293 - accuracy= 85.598 - loss: 1.19778 processing batch 46 of 293 - accuracy= 85.904 - loss: 1.19409 processing batch 47 of 293 - accuracy= 85.417 - loss: 1.19732 processing batch 48 of 293 - accuracy= 85.204 - loss: 1.19840 processing batch 49 of 293 - accuracy= 85.250 - loss: 1.19765 processing batch 50 of 293 - accuracy= 85.294 - loss: 1.20038 processing batch 51 of 293 - accuracy= 85.096 - loss: 1.20156 processing batch 52 of 293 - accuracy= 84.670 - loss: 1.21033 processing batch 53 of 293 - accuracy= 84.954 - loss: 1.20406 processing batch 54 of 293 - accuracy= 85.227 - loss: 1.20080 processing batch 55 of 293 - accuracy= 85.491 - loss: 1.19740 processing batch 56 of 293 - accuracy= 85.526 - loss: 1.19343 processing batch 57 of 293 - accuracy= 85.776 - loss: 1.18931 processing batch 58 of 293 - accuracy= 85.593 - loss: 1.18853 processing batch 59 of 293 - accuracy= 85.625 - loss: 1.18638 processing batch 60 of 293 - accuracy= 85.861 - loss: 1.18059 processing batch 61 of 293 - accuracy= 85.887 - loss: 1.17751 processing batch 62 of 293 - accuracy= 85.913 - loss: 1.17616 processing batch 63 of 293 - accuracy= 85.547 - loss: 1.17980 processing batch 64 of 293 - accuracy= 85.577 - loss: 1.17626 processing batch 65 of 293 - accuracy= 85.795 - loss: 1.17257 processing batch 66 of 293 - accuracy= 86.007 - loss: 1.16849 processing batch 67 of 293 - accuracy= 85.846 - loss: 1.16785 processing batch 68 of 293 - accuracy= 86.051 - loss: 1.16515 processing batch 69 of 293 - accuracy= 86.071 - loss: 1.16485 processing batch 70 of 293 - accuracy= 85.915 - loss: 1.17201 processing batch 71 of 293 - accuracy= 85.938 - loss: 1.17365 processing batch 72 of 293 - accuracy= 86.130 - loss: 1.17004 processing batch 73 of 293 - accuracy= 86.318 - loss: 1.16918 processing batch 74 of 293 - accuracy= 86.333 - loss: 1.16810 processing batch 75 of 293 - accuracy= 86.020 - loss: 1.17515 processing batch 76 of 293 - accuracy= 85.714 - loss: 1.18177 processing batch 77 of 293 - accuracy= 85.737 - loss: 1.18145 processing batch 78 of 293 - accuracy= 85.918 - loss: 1.17972 processing batch 79 of 293 - accuracy= 85.938 - loss: 1.17920 processing batch 80 of 293 - accuracy= 86.111 - loss: 1.17451 processing batch 81 of 293 - accuracy= 86.128 - loss: 1.17746 processing batch 82 of 293 - accuracy= 86.295 - loss: 1.17470 processing batch 83 of 293 - accuracy= 86.310 - loss: 1.17503 processing batch 84 of 293 - accuracy= 86.029 - loss: 1.18389 processing batch 85 of 293 - accuracy= 85.901 - loss: 1.18326 processing batch 86 of 293 - accuracy= 86.063 - loss: 1.17971 processing batch 87 of 293 - accuracy= 85.938 - loss: 1.18015 processing batch 88 of 293 - accuracy= 85.534 - loss: 1.18583 processing batch 89 of 293 - accuracy= 85.694 - loss: 1.18301 processing batch 90 of 293 - accuracy= 85.852 - loss: 1.18155 processing batch 91 of 293 - accuracy= 86.005 - loss: 1.17999 processing batch 92 of 293 - accuracy= 86.156 - loss: 1.17631 processing batch 93 of 293 - accuracy= 86.303 - loss: 1.17349 processing batch 94 of 293 - accuracy= 86.184 - loss: 1.17472 processing batch 95 of 293 - accuracy= 86.198 - loss: 1.17335 processing batch 96 of 293 - accuracy= 86.211 - loss: 1.17241 processing batch 97 of 293 - accuracy= 86.352 - loss: 1.17020 processing batch 98 of 293 - accuracy= 86.364 - loss: 1.16946 processing batch 99 of 293 - accuracy= 86.250 - loss: 1.17168 processing batch 100 of 293 - accuracy= 86.139 - loss: 1.17595 processing batch 101 of 293 - accuracy= 86.152 - loss: 1.17501 processing batch 102 of 293 - accuracy= 86.286 - loss: 1.17201 processing batch 103 of 293 - accuracy= 86.418 - loss: 1.16894 processing batch 104 of 293 - accuracy= 86.548 - loss: 1.16725 processing batch 105 of 293 - accuracy= 86.675 - loss: 1.16462 processing batch 106 of 293 - accuracy= 86.799 - loss: 1.16243 processing batch 107 of 293 - accuracy= 86.806 - loss: 1.16179 processing batch 108 of 293 - accuracy= 86.812 - loss: 1.15929 processing batch 109 of 293 - accuracy= 86.818 - loss: 1.15878 processing batch 110 of 293 - accuracy= 86.599 - loss: 1.16400 processing batch 111 of 293 - accuracy= 86.719 - loss: 1.16246 processing batch 112 of 293 - accuracy= 86.726 - loss: 1.16154 processing batch 113 of 293 - accuracy= 86.732 - loss: 1.16077 processing batch 114 of 293 - accuracy= 86.739 - loss: 1.15953 processing batch 115 of 293 - accuracy= 86.746 - loss: 1.15939 processing batch 116 of 293 - accuracy= 86.859 - loss: 1.15693 processing batch 117 of 293 - accuracy= 86.970 - loss: 1.15418 processing batch 118 of 293 - accuracy= 87.080 - loss: 1.15305 processing batch 119 of 293 - accuracy= 87.083 - loss: 1.15171 processing batch 120 of 293 - accuracy= 87.190 - loss: 1.14962 processing batch 121 of 293 - accuracy= 87.193 - loss: 1.14854 processing batch 122 of 293 - accuracy= 87.093 - loss: 1.14888 processing batch 123 of 293 - accuracy= 87.097 - loss: 1.14717 processing batch 124 of 293 - accuracy= 87.100 - loss: 1.14782 processing batch 125 of 293 - accuracy= 87.202 - loss: 1.14540 processing batch 126 of 293 - accuracy= 87.205 - loss: 1.14408 processing batch 127 of 293 - accuracy= 87.305 - loss: 1.14239 processing batch 128 of 293 - accuracy= 87.306 - loss: 1.14060 processing batch 129 of 293 - accuracy= 87.019 - loss: 1.14412 processing batch 130 of 293 - accuracy= 87.023 - loss: 1.14280 processing batch 131 of 293 - accuracy= 87.027 - loss: 1.14281 processing batch 132 of 293 - accuracy= 86.842 - loss: 1.14420 processing batch 133 of 293 - accuracy= 86.847 - loss: 1.14316 processing batch 134 of 293 - accuracy= 86.944 - loss: 1.14165 processing batch 135 of 293 - accuracy= 87.040 - loss: 1.13968 processing batch 136 of 293 - accuracy= 87.135 - loss: 1.13735 processing batch 137 of 293 - accuracy= 87.138 - loss: 1.13624 processing batch 138 of 293 - accuracy= 87.140 - loss: 1.13496 processing batch 139 of 293 - accuracy= 87.232 - loss: 1.13376 processing batch 140 of 293 - accuracy= 87.234 - loss: 1.13318 processing batch 141 of 293 - accuracy= 87.236 - loss: 1.13213 processing batch 142 of 293 - accuracy= 87.150 - loss: 1.13170 processing batch 143 of 293 - accuracy= 87.066 - loss: 1.13293 processing batch 144 of 293 - accuracy= 87.069 - loss: 1.13288 processing batch 145 of 293 - accuracy= 87.072 - loss: 1.13209 processing batch 146 of 293 - accuracy= 87.160 - loss: 1.13032 processing batch 147 of 293 - accuracy= 86.993 - loss: 1.13289 processing batch 148 of 293 - accuracy= 86.913 - loss: 1.13213 processing batch 149 of 293 - accuracy= 86.750 - loss: 1.13571 processing batch 150 of 293 - accuracy= 86.838 - loss: 1.13390 processing batch 151 of 293 - accuracy= 86.760 - loss: 1.13424 processing batch 152 of 293 - accuracy= 86.683 - loss: 1.13552 processing batch 153 of 293 - accuracy= 86.688 - loss: 1.13653 processing batch 154 of 293 - accuracy= 86.774 - loss: 1.13654 processing batch 155 of 293 - accuracy= 86.699 - loss: 1.13857 processing batch 156 of 293 - accuracy= 86.624 - loss: 1.13879 processing batch 157 of 293 - accuracy= 86.472 - loss: 1.14081 processing batch 158 of 293 - accuracy= 86.557 - loss: 1.14000 processing batch 159 of 293 - accuracy= 86.563 - loss: 1.14026 processing batch 160 of 293 - accuracy= 86.568 - loss: 1.13944 processing batch 161 of 293 - accuracy= 86.497 - loss: 1.14056 processing batch 162 of 293 - accuracy= 86.350 - loss: 1.14400 processing batch 163 of 293 - accuracy= 86.357 - loss: 1.14393 processing batch 164 of 293 - accuracy= 86.364 - loss: 1.14477 processing batch 165 of 293 - accuracy= 86.446 - loss: 1.14324 processing batch 166 of 293 - accuracy= 86.452 - loss: 1.14311 processing batch 167 of 293 - accuracy= 86.458 - loss: 1.14288 processing batch 168 of 293 - accuracy= 86.464 - loss: 1.14273 processing batch 169 of 293 - accuracy= 86.544 - loss: 1.14082 processing batch 170 of 293 - accuracy= 86.550 - loss: 1.14152 processing batch 171 of 293 - accuracy= 86.555 - loss: 1.14193 processing batch 172 of 293 - accuracy= 86.488 - loss: 1.14175 processing batch 173 of 293 - accuracy= 86.422 - loss: 1.14389 processing batch 174 of 293 - accuracy= 86.286 - loss: 1.14514 processing batch 175 of 293 - accuracy= 86.293 - loss: 1.14475 processing batch 176 of 293 - accuracy= 86.370 - loss: 1.14370 processing batch 177 of 293 - accuracy= 86.376 - loss: 1.14309 processing batch 178 of 293 - accuracy= 86.383 - loss: 1.14426 processing batch 179 of 293 - accuracy= 86.458 - loss: 1.14298 processing batch 180 of 293 - accuracy= 86.326 - loss: 1.14433 processing batch 181 of 293 - accuracy= 86.401 - loss: 1.14353 processing batch 182 of 293 - accuracy= 86.475 - loss: 1.14224 processing batch 183 of 293 - accuracy= 86.481 - loss: 1.14241 processing batch 184 of 293 - accuracy= 86.554 - loss: 1.14080 processing batch 185 of 293 - accuracy= 86.559 - loss: 1.14094 processing batch 186 of 293 - accuracy= 86.564 - loss: 1.14019 processing batch 187 of 293 - accuracy= 86.503 - loss: 1.14016 processing batch 188 of 293 - accuracy= 86.574 - loss: 1.13907 processing batch 189 of 293 - accuracy= 86.513 - loss: 1.13948 processing batch 190 of 293 - accuracy= 86.453 - loss: 1.13929 processing batch 191 of 293 - accuracy= 86.458 - loss: 1.13844 processing batch 192 of 293 - accuracy= 86.399 - loss: 1.13989 processing batch 193 of 293 - accuracy= 86.469 - loss: 1.13877 processing batch 194 of 293 - accuracy= 86.410 - loss: 1.14045 processing batch 195 of 293 - accuracy= 86.288 - loss: 1.14019 processing batch 196 of 293 - accuracy= 86.294 - loss: 1.13970 processing batch 197 of 293 - accuracy= 86.301 - loss: 1.13914 processing batch 198 of 293 - accuracy= 86.181 - loss: 1.14090 processing batch 199 of 293 - accuracy= 86.250 - loss: 1.13983 processing batch 200 of 293 - accuracy= 86.318 - loss: 1.13883 processing batch 201 of 293 - accuracy= 86.386 - loss: 1.13721 processing batch 202 of 293 - accuracy= 86.330 - loss: 1.13714 processing batch 203 of 293 - accuracy= 86.397 - loss: 1.13570 processing batch 204 of 293 - accuracy= 86.463 - loss: 1.13469 processing batch 205 of 293 - accuracy= 86.347 - loss: 1.13562 processing batch 206 of 293 - accuracy= 86.413 - loss: 1.13476 processing batch 207 of 293 - accuracy= 86.418 - loss: 1.13371 processing batch 208 of 293 - accuracy= 86.304 - loss: 1.13582 processing batch 209 of 293 - accuracy= 86.250 - loss: 1.13557 processing batch 210 of 293 - accuracy= 86.256 - loss: 1.13480 processing batch 211 of 293 - accuracy= 86.262 - loss: 1.13422 processing batch 212 of 293 - accuracy= 86.268 - loss: 1.13355 processing batch 213 of 293 - accuracy= 86.157 - loss: 1.13463 processing batch 214 of 293 - accuracy= 86.163 - loss: 1.13429 processing batch 215 of 293 - accuracy= 86.111 - loss: 1.13495 processing batch 216 of 293 - accuracy= 86.175 - loss: 1.13327 processing batch 217 of 293 - accuracy= 86.124 - loss: 1.13290 processing batch 218 of 293 - accuracy= 86.130 - loss: 1.13210 processing batch 219 of 293 - accuracy= 86.080 - loss: 1.13185 processing batch 220 of 293 - accuracy= 86.143 - loss: 1.13037 processing batch 221 of 293 - accuracy= 86.092 - loss: 1.13212 processing batch 222 of 293 - accuracy= 86.099 - loss: 1.13128 processing batch 223 of 293 - accuracy= 86.161 - loss: 1.12973 processing batch 224 of 293 - accuracy= 86.222 - loss: 1.12863 processing batch 225 of 293 - accuracy= 86.283 - loss: 1.12743 processing batch 226 of 293 - accuracy= 86.344 - loss: 1.12637 processing batch 227 of 293 - accuracy= 86.294 - loss: 1.12709 processing batch 228 of 293 - accuracy= 86.245 - loss: 1.12781 processing batch 229 of 293 - accuracy= 86.304 - loss: 1.12678 processing batch 230 of 293 - accuracy= 86.364 - loss: 1.12547 processing batch 231 of 293 - accuracy= 86.369 - loss: 1.12485 processing batch 232 of 293 - accuracy= 86.373 - loss: 1.12625 processing batch 233 of 293 - accuracy= 86.432 - loss: 1.12478 processing batch 234 of 293 - accuracy= 86.489 - loss: 1.12410 processing batch 235 of 293 - accuracy= 86.494 - loss: 1.12354 processing batch 236 of 293 - accuracy= 86.551 - loss: 1.12202 processing batch 237 of 293 - accuracy= 86.555 - loss: 1.12183 processing batch 238 of 293 - accuracy= 86.559 - loss: 1.12138 processing batch 239 of 293 - accuracy= 86.458 - loss: 1.12426 processing batch 240 of 293 - accuracy= 86.463 - loss: 1.12395 processing batch 241 of 293 - accuracy= 86.415 - loss: 1.12386 processing batch 242 of 293 - accuracy= 86.471 - loss: 1.12213 processing batch 243 of 293 - accuracy= 86.527 - loss: 1.12056 processing batch 244 of 293 - accuracy= 86.582 - loss: 1.11918 processing batch 245 of 293 - accuracy= 86.585 - loss: 1.11995 processing batch 246 of 293 - accuracy= 86.640 - loss: 1.11835 processing batch 247 of 293 - accuracy= 86.643 - loss: 1.11786 processing batch 248 of 293 - accuracy= 86.647 - loss: 1.11720 processing batch 249 of 293 - accuracy= 86.700 - loss: 1.11563 processing batch 250 of 293 - accuracy= 86.753 - loss: 1.11413 processing batch 251 of 293 - accuracy= 86.806 - loss: 1.11347 processing batch 252 of 293 - accuracy= 86.759 - loss: 1.11415 processing batch 253 of 293 - accuracy= 86.762 - loss: 1.11433 processing batch 254 of 293 - accuracy= 86.814 - loss: 1.11355 processing batch 255 of 293 - accuracy= 86.816 - loss: 1.11302 processing batch 256 of 293 - accuracy= 86.819 - loss: 1.11206 processing batch 257 of 293 - accuracy= 86.822 - loss: 1.11156 processing batch 258 of 293 - accuracy= 86.824 - loss: 1.11174 processing batch 259 of 293 - accuracy= 86.875 - loss: 1.11031 processing batch 260 of 293 - accuracy= 86.734 - loss: 1.11240 processing batch 261 of 293 - accuracy= 86.737 - loss: 1.11194 processing batch 262 of 293 - accuracy= 86.740 - loss: 1.11147 processing batch 263 of 293 - accuracy= 86.790 - loss: 1.11049 processing batch 264 of 293 - accuracy= 86.745 - loss: 1.11236 processing batch 265 of 293 - accuracy= 86.748 - loss: 1.11167 processing batch 266 of 293 - accuracy= 86.751 - loss: 1.11143 processing batch 267 of 293 - accuracy= 86.707 - loss: 1.11181 processing batch 268 of 293 - accuracy= 86.664 - loss: 1.11216 processing batch 269 of 293 - accuracy= 86.667 - loss: 1.11135 processing batch 270 of 293 - accuracy= 86.624 - loss: 1.11173 processing batch 271 of 293 - accuracy= 86.581 - loss: 1.11241 processing batch 272 of 293 - accuracy= 86.584 - loss: 1.11171 processing batch 273 of 293 - accuracy= 86.588 - loss: 1.11150 processing batch 274 of 293 - accuracy= 86.545 - loss: 1.11269 processing batch 275 of 293 - accuracy= 86.504 - loss: 1.11402 processing batch 276 of 293 - accuracy= 86.507 - loss: 1.11360 processing batch 277 of 293 - accuracy= 86.511 - loss: 1.11339 processing batch 278 of 293 - accuracy= 86.514 - loss: 1.11284 processing batch 279 of 293 - accuracy= 86.473 - loss: 1.11278 processing batch 280 of 293 - accuracy= 86.477 - loss: 1.11221 processing batch 281 of 293 - accuracy= 86.480 - loss: 1.11204 processing batch 282 of 293 - accuracy= 86.484 - loss: 1.11222 processing batch 283 of 293 - accuracy= 86.488 - loss: 1.11170 processing batch 284 of 293 - accuracy= 86.491 - loss: 1.11105 processing batch 285 of 293 - accuracy= 86.451 - loss: 1.11069 processing batch 286 of 293 - accuracy= 86.498 - loss: 1.10995 processing batch 287 of 293 - accuracy= 86.458 - loss: 1.11176 processing batch 288 of 293 - accuracy= 86.462 - loss: 1.11154 processing batch 289 of 293 - accuracy= 86.422 - loss: 1.11158 processing batch 290 of 293 - accuracy= 86.426 - loss: 1.11156 processing batch 291 of 293 - accuracy= 86.430 - loss: 1.11077 processing batch 292 of 293 - accuracy= 86.476 - loss: 1.10970 8 /40 1.110 86.476 1.67355 69.231 0.00100 0.00100 accuracy 3.26 82.31 \n293/293 [==============================] - 82s 281ms/step - loss: 1.1097 - accuracy: 0.8648 - val_loss: 1.6736 - val_accuracy: 0.6923\nEpoch 9/40\n293/293 [==============================] - ETA: 0s - loss: 0.8750 - accuracy: 0.8972 3590 processing batch 1 of 293 - accuracy= 93.750 - loss: 0.93038 processing batch 2 of 293 - accuracy= 95.833 - loss: 0.89931 processing batch 3 of 293 - accuracy= 93.750 - loss: 0.97185 processing batch 4 of 293 - accuracy= 92.500 - loss: 0.95970 processing batch 5 of 293 - accuracy= 91.667 - loss: 0.94438 processing batch 6 of 293 - accuracy= 92.857 - loss: 0.91096 processing batch 7 of 293 - accuracy= 92.188 - loss: 0.96550 processing batch 8 of 293 - accuracy= 90.278 - loss: 0.96584 processing batch 9 of 293 - accuracy= 91.250 - loss: 0.94071 processing batch 10 of 293 - accuracy= 90.909 - loss: 0.94911 processing batch 11 of 293 - accuracy= 89.583 - loss: 0.95892 processing batch 12 of 293 - accuracy= 90.385 - loss: 0.94628 processing batch 13 of 293 - accuracy= 88.393 - loss: 0.96829 processing batch 14 of 293 - accuracy= 88.333 - loss: 0.96139 processing batch 15 of 293 - accuracy= 89.062 - loss: 0.94850 processing batch 16 of 293 - accuracy= 89.706 - loss: 0.94033 processing batch 17 of 293 - accuracy= 90.278 - loss: 0.93703 processing batch 18 of 293 - accuracy= 90.789 - loss: 0.92511 processing batch 19 of 293 - accuracy= 90.625 - loss: 0.92961 processing batch 20 of 293 - accuracy= 91.071 - loss: 0.92499 processing batch 21 of 293 - accuracy= 91.477 - loss: 0.91862 processing batch 22 of 293 - accuracy= 90.761 - loss: 0.93587 processing batch 23 of 293 - accuracy= 91.146 - loss: 0.92492 processing batch 24 of 293 - accuracy= 91.500 - loss: 0.92038 processing batch 25 of 293 - accuracy= 91.827 - loss: 0.91448 processing batch 26 of 293 - accuracy= 91.667 - loss: 0.91501 processing batch 27 of 293 - accuracy= 91.964 - loss: 0.90942 processing batch 28 of 293 - accuracy= 92.241 - loss: 0.90280 processing batch 29 of 293 - accuracy= 92.083 - loss: 0.90557 processing batch 30 of 293 - accuracy= 91.935 - loss: 0.90503 processing batch 31 of 293 - accuracy= 91.797 - loss: 0.90832 processing batch 32 of 293 - accuracy= 91.667 - loss: 0.91765 processing batch 33 of 293 - accuracy= 91.912 - loss: 0.91575 processing batch 34 of 293 - accuracy= 92.143 - loss: 0.90874 processing batch 35 of 293 - accuracy= 92.014 - loss: 0.90687 processing batch 36 of 293 - accuracy= 91.892 - loss: 0.90868 processing batch 37 of 293 - accuracy= 91.447 - loss: 0.91265 processing batch 38 of 293 - accuracy= 91.346 - loss: 0.91586 processing batch 39 of 293 - accuracy= 91.250 - loss: 0.91781 processing batch 40 of 293 - accuracy= 91.463 - loss: 0.91391 processing batch 41 of 293 - accuracy= 91.369 - loss: 0.91417 processing batch 42 of 293 - accuracy= 90.988 - loss: 0.91679 processing batch 43 of 293 - accuracy= 90.909 - loss: 0.91730 processing batch 44 of 293 - accuracy= 90.833 - loss: 0.91343 processing batch 45 of 293 - accuracy= 91.033 - loss: 0.91111 processing batch 46 of 293 - accuracy= 91.223 - loss: 0.90781 processing batch 47 of 293 - accuracy= 91.406 - loss: 0.90458 processing batch 48 of 293 - accuracy= 91.582 - loss: 0.90113 processing batch 49 of 293 - accuracy= 91.250 - loss: 0.90273 processing batch 50 of 293 - accuracy= 91.422 - loss: 0.89897 processing batch 51 of 293 - accuracy= 91.346 - loss: 0.90418 processing batch 52 of 293 - accuracy= 91.509 - loss: 0.89956 processing batch 53 of 293 - accuracy= 91.667 - loss: 0.89488 processing batch 54 of 293 - accuracy= 91.591 - loss: 0.89481 processing batch 55 of 293 - accuracy= 91.518 - loss: 0.89672 processing batch 56 of 293 - accuracy= 91.667 - loss: 0.89243 processing batch 57 of 293 - accuracy= 91.595 - loss: 0.89248 processing batch 58 of 293 - accuracy= 91.314 - loss: 0.89216 processing batch 59 of 293 - accuracy= 91.042 - loss: 0.89451 processing batch 60 of 293 - accuracy= 91.189 - loss: 0.89314 processing batch 61 of 293 - accuracy= 91.129 - loss: 0.89347 processing batch 62 of 293 - accuracy= 91.270 - loss: 0.89207 processing batch 63 of 293 - accuracy= 91.406 - loss: 0.89093 processing batch 64 of 293 - accuracy= 91.346 - loss: 0.88994 processing batch 65 of 293 - accuracy= 91.288 - loss: 0.88927 processing batch 66 of 293 - accuracy= 91.231 - loss: 0.89192 processing batch 67 of 293 - accuracy= 90.993 - loss: 0.89864 processing batch 68 of 293 - accuracy= 90.942 - loss: 0.90172 processing batch 69 of 293 - accuracy= 90.893 - loss: 0.90256 processing batch 70 of 293 - accuracy= 91.021 - loss: 0.90040 processing batch 71 of 293 - accuracy= 91.146 - loss: 0.89789 processing batch 72 of 293 - accuracy= 91.267 - loss: 0.89525 processing batch 73 of 293 - accuracy= 91.047 - loss: 0.89805 processing batch 74 of 293 - accuracy= 91.167 - loss: 0.89652 processing batch 75 of 293 - accuracy= 91.283 - loss: 0.89415 processing batch 76 of 293 - accuracy= 91.396 - loss: 0.89166 processing batch 77 of 293 - accuracy= 91.346 - loss: 0.89182 processing batch 78 of 293 - accuracy= 91.456 - loss: 0.88916 processing batch 79 of 293 - accuracy= 91.562 - loss: 0.88725 processing batch 80 of 293 - accuracy= 91.358 - loss: 0.88890 processing batch 81 of 293 - accuracy= 91.463 - loss: 0.88596 processing batch 82 of 293 - accuracy= 91.416 - loss: 0.88773 processing batch 83 of 293 - accuracy= 91.518 - loss: 0.88577 processing batch 84 of 293 - accuracy= 91.471 - loss: 0.88991 processing batch 85 of 293 - accuracy= 91.424 - loss: 0.89187 processing batch 86 of 293 - accuracy= 91.379 - loss: 0.89091 processing batch 87 of 293 - accuracy= 91.477 - loss: 0.88933 processing batch 88 of 293 - accuracy= 91.573 - loss: 0.88705 processing batch 89 of 293 - accuracy= 91.528 - loss: 0.88778 processing batch 90 of 293 - accuracy= 91.346 - loss: 0.88910 processing batch 91 of 293 - accuracy= 91.304 - loss: 0.88921 processing batch 92 of 293 - accuracy= 91.129 - loss: 0.88953 processing batch 93 of 293 - accuracy= 91.090 - loss: 0.89178 processing batch 94 of 293 - accuracy= 91.184 - loss: 0.89010 processing batch 95 of 293 - accuracy= 91.276 - loss: 0.88873 processing batch 96 of 293 - accuracy= 91.366 - loss: 0.88637 processing batch 97 of 293 - accuracy= 91.454 - loss: 0.88486 processing batch 98 of 293 - accuracy= 91.540 - loss: 0.88253 processing batch 99 of 293 - accuracy= 91.625 - loss: 0.88265 processing batch 100 of 293 - accuracy= 91.337 - loss: 0.88870 processing batch 101 of 293 - accuracy= 91.422 - loss: 0.88730 processing batch 102 of 293 - accuracy= 91.383 - loss: 0.88770 processing batch 103 of 293 - accuracy= 91.346 - loss: 0.88915 processing batch 104 of 293 - accuracy= 91.429 - loss: 0.88764 processing batch 105 of 293 - accuracy= 91.509 - loss: 0.88508 processing batch 106 of 293 - accuracy= 91.472 - loss: 0.88511 processing batch 107 of 293 - accuracy= 91.551 - loss: 0.88279 processing batch 108 of 293 - accuracy= 91.399 - loss: 0.88385 processing batch 109 of 293 - accuracy= 91.364 - loss: 0.88384 processing batch 110 of 293 - accuracy= 91.329 - loss: 0.88479 processing batch 111 of 293 - accuracy= 91.406 - loss: 0.88362 processing batch 112 of 293 - accuracy= 91.482 - loss: 0.88227 processing batch 113 of 293 - accuracy= 91.557 - loss: 0.88108 processing batch 114 of 293 - accuracy= 91.522 - loss: 0.88072 processing batch 115 of 293 - accuracy= 91.379 - loss: 0.88177 processing batch 116 of 293 - accuracy= 91.346 - loss: 0.88270 processing batch 117 of 293 - accuracy= 91.208 - loss: 0.88397 processing batch 118 of 293 - accuracy= 91.071 - loss: 0.88436 processing batch 119 of 293 - accuracy= 91.146 - loss: 0.88334 processing batch 120 of 293 - accuracy= 91.219 - loss: 0.88131 processing batch 121 of 293 - accuracy= 91.086 - loss: 0.88267 processing batch 122 of 293 - accuracy= 90.955 - loss: 0.88345 processing batch 123 of 293 - accuracy= 91.028 - loss: 0.88173 processing batch 124 of 293 - accuracy= 90.900 - loss: 0.88342 processing batch 125 of 293 - accuracy= 90.873 - loss: 0.88357 processing batch 126 of 293 - accuracy= 90.650 - loss: 0.88712 processing batch 127 of 293 - accuracy= 90.723 - loss: 0.88569 processing batch 128 of 293 - accuracy= 90.601 - loss: 0.88718 processing batch 129 of 293 - accuracy= 90.577 - loss: 0.88755 processing batch 130 of 293 - accuracy= 90.553 - loss: 0.88752 processing batch 131 of 293 - accuracy= 90.530 - loss: 0.88759 processing batch 132 of 293 - accuracy= 90.508 - loss: 0.88817 processing batch 133 of 293 - accuracy= 90.485 - loss: 0.88900 processing batch 134 of 293 - accuracy= 90.556 - loss: 0.88763 processing batch 135 of 293 - accuracy= 90.625 - loss: 0.88652 processing batch 136 of 293 - accuracy= 90.693 - loss: 0.88488 processing batch 137 of 293 - accuracy= 90.670 - loss: 0.88447 processing batch 138 of 293 - accuracy= 90.558 - loss: 0.88774 processing batch 139 of 293 - accuracy= 90.536 - loss: 0.88698 processing batch 140 of 293 - accuracy= 90.603 - loss: 0.88518 processing batch 141 of 293 - accuracy= 90.493 - loss: 0.88747 processing batch 142 of 293 - accuracy= 90.472 - loss: 0.88671 processing batch 143 of 293 - accuracy= 90.538 - loss: 0.88512 processing batch 144 of 293 - accuracy= 90.603 - loss: 0.88329 processing batch 145 of 293 - accuracy= 90.582 - loss: 0.88315 processing batch 146 of 293 - accuracy= 90.646 - loss: 0.88158 processing batch 147 of 293 - accuracy= 90.625 - loss: 0.88086 processing batch 148 of 293 - accuracy= 90.520 - loss: 0.88211 processing batch 149 of 293 - accuracy= 90.583 - loss: 0.88098 processing batch 150 of 293 - accuracy= 90.646 - loss: 0.88004 processing batch 151 of 293 - accuracy= 90.625 - loss: 0.88049 processing batch 152 of 293 - accuracy= 90.686 - loss: 0.87894 processing batch 153 of 293 - accuracy= 90.666 - loss: 0.87975 processing batch 154 of 293 - accuracy= 90.645 - loss: 0.88059 processing batch 155 of 293 - accuracy= 90.625 - loss: 0.88050 processing batch 156 of 293 - accuracy= 90.685 - loss: 0.87967 processing batch 157 of 293 - accuracy= 90.744 - loss: 0.87838 processing batch 158 of 293 - accuracy= 90.566 - loss: 0.88009 processing batch 159 of 293 - accuracy= 90.156 - loss: 0.89154 processing batch 160 of 293 - accuracy= 90.062 - loss: 0.89580 processing batch 161 of 293 - accuracy= 90.123 - loss: 0.89458 processing batch 162 of 293 - accuracy= 90.031 - loss: 0.89514 processing batch 163 of 293 - accuracy= 90.091 - loss: 0.89357 processing batch 164 of 293 - accuracy= 90.152 - loss: 0.89250 processing batch 165 of 293 - accuracy= 90.211 - loss: 0.89139 processing batch 166 of 293 - accuracy= 90.195 - loss: 0.89160 processing batch 167 of 293 - accuracy= 90.104 - loss: 0.89202 processing batch 168 of 293 - accuracy= 90.089 - loss: 0.89191 processing batch 169 of 293 - accuracy= 90.147 - loss: 0.89144 processing batch 170 of 293 - accuracy= 90.205 - loss: 0.88992 processing batch 171 of 293 - accuracy= 90.189 - loss: 0.88994 processing batch 172 of 293 - accuracy= 90.173 - loss: 0.89051 processing batch 173 of 293 - accuracy= 90.086 - loss: 0.89263 processing batch 174 of 293 - accuracy= 90.071 - loss: 0.89438 processing batch 175 of 293 - accuracy= 90.128 - loss: 0.89341 processing batch 176 of 293 - accuracy= 90.184 - loss: 0.89187 processing batch 177 of 293 - accuracy= 90.169 - loss: 0.89154 processing batch 178 of 293 - accuracy= 90.223 - loss: 0.89063 processing batch 179 of 293 - accuracy= 90.278 - loss: 0.88942 processing batch 180 of 293 - accuracy= 90.331 - loss: 0.88883 processing batch 181 of 293 - accuracy= 90.316 - loss: 0.88826 processing batch 182 of 293 - accuracy= 90.301 - loss: 0.88826 processing batch 183 of 293 - accuracy= 90.285 - loss: 0.88820 processing batch 184 of 293 - accuracy= 90.270 - loss: 0.88822 processing batch 185 of 293 - accuracy= 90.255 - loss: 0.88801 processing batch 186 of 293 - accuracy= 90.174 - loss: 0.88874 processing batch 187 of 293 - accuracy= 90.160 - loss: 0.88814 processing batch 188 of 293 - accuracy= 90.146 - loss: 0.88739 processing batch 189 of 293 - accuracy= 90.197 - loss: 0.88673 processing batch 190 of 293 - accuracy= 90.183 - loss: 0.88707 processing batch 191 of 293 - accuracy= 90.169 - loss: 0.88692 processing batch 192 of 293 - accuracy= 90.091 - loss: 0.88663 processing batch 193 of 293 - accuracy= 90.077 - loss: 0.88699 processing batch 194 of 293 - accuracy= 90.064 - loss: 0.88746 processing batch 195 of 293 - accuracy= 90.115 - loss: 0.88633 processing batch 196 of 293 - accuracy= 90.102 - loss: 0.88641 processing batch 197 of 293 - accuracy= 89.962 - loss: 0.88766 processing batch 198 of 293 - accuracy= 89.950 - loss: 0.88871 processing batch 199 of 293 - accuracy= 90.000 - loss: 0.88780 processing batch 200 of 293 - accuracy= 90.050 - loss: 0.88680 processing batch 201 of 293 - accuracy= 89.975 - loss: 0.88765 processing batch 202 of 293 - accuracy= 90.025 - loss: 0.88673 processing batch 203 of 293 - accuracy= 90.012 - loss: 0.88637 processing batch 204 of 293 - accuracy= 89.878 - loss: 0.88788 processing batch 205 of 293 - accuracy= 89.867 - loss: 0.88813 processing batch 206 of 293 - accuracy= 89.855 - loss: 0.88829 processing batch 207 of 293 - accuracy= 89.904 - loss: 0.88691 processing batch 208 of 293 - accuracy= 89.952 - loss: 0.88634 processing batch 209 of 293 - accuracy= 89.940 - loss: 0.88624 processing batch 210 of 293 - accuracy= 89.988 - loss: 0.88486 processing batch 211 of 293 - accuracy= 89.917 - loss: 0.88581 processing batch 212 of 293 - accuracy= 89.789 - loss: 0.88709 processing batch 213 of 293 - accuracy= 89.836 - loss: 0.88558 processing batch 214 of 293 - accuracy= 89.884 - loss: 0.88442 processing batch 215 of 293 - accuracy= 89.931 - loss: 0.88346 processing batch 216 of 293 - accuracy= 89.919 - loss: 0.88373 processing batch 217 of 293 - accuracy= 89.966 - loss: 0.88303 processing batch 218 of 293 - accuracy= 90.011 - loss: 0.88195 processing batch 219 of 293 - accuracy= 89.943 - loss: 0.88285 processing batch 220 of 293 - accuracy= 89.989 - loss: 0.88181 processing batch 221 of 293 - accuracy= 89.977 - loss: 0.88138 processing batch 222 of 293 - accuracy= 90.022 - loss: 0.88046 processing batch 223 of 293 - accuracy= 90.011 - loss: 0.88020 processing batch 224 of 293 - accuracy= 89.889 - loss: 0.88121 processing batch 225 of 293 - accuracy= 89.934 - loss: 0.88092 processing batch 226 of 293 - accuracy= 89.978 - loss: 0.88039 processing batch 227 of 293 - accuracy= 89.912 - loss: 0.88153 processing batch 228 of 293 - accuracy= 89.956 - loss: 0.88033 processing batch 229 of 293 - accuracy= 90.000 - loss: 0.87933 processing batch 230 of 293 - accuracy= 90.043 - loss: 0.87855 processing batch 231 of 293 - accuracy= 90.086 - loss: 0.87759 processing batch 232 of 293 - accuracy= 90.021 - loss: 0.87949 processing batch 233 of 293 - accuracy= 89.957 - loss: 0.88081 processing batch 234 of 293 - accuracy= 90.000 - loss: 0.87949 processing batch 235 of 293 - accuracy= 89.989 - loss: 0.87881 processing batch 236 of 293 - accuracy= 90.032 - loss: 0.87790 processing batch 237 of 293 - accuracy= 90.074 - loss: 0.87689 processing batch 238 of 293 - accuracy= 90.010 - loss: 0.87799 processing batch 239 of 293 - accuracy= 90.000 - loss: 0.87907 processing batch 240 of 293 - accuracy= 90.041 - loss: 0.87796 processing batch 241 of 293 - accuracy= 89.928 - loss: 0.88041 processing batch 242 of 293 - accuracy= 89.866 - loss: 0.88050 processing batch 243 of 293 - accuracy= 89.857 - loss: 0.88021 processing batch 244 of 293 - accuracy= 89.847 - loss: 0.88029 processing batch 245 of 293 - accuracy= 89.787 - loss: 0.88003 processing batch 246 of 293 - accuracy= 89.828 - loss: 0.87914 processing batch 247 of 293 - accuracy= 89.869 - loss: 0.87790 processing batch 248 of 293 - accuracy= 89.859 - loss: 0.87756 processing batch 249 of 293 - accuracy= 89.900 - loss: 0.87633 processing batch 250 of 293 - accuracy= 89.890 - loss: 0.87673 processing batch 251 of 293 - accuracy= 89.931 - loss: 0.87593 processing batch 252 of 293 - accuracy= 89.921 - loss: 0.87551 processing batch 253 of 293 - accuracy= 89.911 - loss: 0.87473 processing batch 254 of 293 - accuracy= 89.853 - loss: 0.87514 processing batch 255 of 293 - accuracy= 89.844 - loss: 0.87504 processing batch 256 of 293 - accuracy= 89.737 - loss: 0.87676 processing batch 257 of 293 - accuracy= 89.777 - loss: 0.87554 processing batch 258 of 293 - accuracy= 89.817 - loss: 0.87548 processing batch 259 of 293 - accuracy= 89.856 - loss: 0.87478 processing batch 260 of 293 - accuracy= 89.799 - loss: 0.87474 processing batch 261 of 293 - accuracy= 89.790 - loss: 0.87423 processing batch 262 of 293 - accuracy= 89.781 - loss: 0.87392 processing batch 263 of 293 - accuracy= 89.773 - loss: 0.87357 processing batch 264 of 293 - accuracy= 89.670 - loss: 0.87546 processing batch 265 of 293 - accuracy= 89.662 - loss: 0.87525 processing batch 266 of 293 - accuracy= 89.700 - loss: 0.87408 processing batch 267 of 293 - accuracy= 89.692 - loss: 0.87391 processing batch 268 of 293 - accuracy= 89.730 - loss: 0.87351 processing batch 269 of 293 - accuracy= 89.769 - loss: 0.87265 processing batch 270 of 293 - accuracy= 89.760 - loss: 0.87362 processing batch 271 of 293 - accuracy= 89.798 - loss: 0.87246 processing batch 272 of 293 - accuracy= 89.789 - loss: 0.87314 processing batch 273 of 293 - accuracy= 89.827 - loss: 0.87220 processing batch 274 of 293 - accuracy= 89.818 - loss: 0.87198 processing batch 275 of 293 - accuracy= 89.855 - loss: 0.87139 processing batch 276 of 293 - accuracy= 89.847 - loss: 0.87119 processing batch 277 of 293 - accuracy= 89.883 - loss: 0.87100 processing batch 278 of 293 - accuracy= 89.875 - loss: 0.87068 processing batch 279 of 293 - accuracy= 89.866 - loss: 0.87091 processing batch 280 of 293 - accuracy= 89.902 - loss: 0.87013 processing batch 281 of 293 - accuracy= 89.805 - loss: 0.87316 processing batch 282 of 293 - accuracy= 89.841 - loss: 0.87243 processing batch 283 of 293 - accuracy= 89.745 - loss: 0.87456 processing batch 284 of 293 - accuracy= 89.649 - loss: 0.87705 processing batch 285 of 293 - accuracy= 89.685 - loss: 0.87621 processing batch 286 of 293 - accuracy= 89.721 - loss: 0.87540 processing batch 287 of 293 - accuracy= 89.757 - loss: 0.87507 processing batch 288 of 293 - accuracy= 89.749 - loss: 0.87499 processing batch 289 of 293 - accuracy= 89.784 - loss: 0.87435 processing batch 290 of 293 - accuracy= 89.820 - loss: 0.87324 processing batch 291 of 293 - accuracy= 89.769 - loss: 0.87463 processing batch 292 of 293 - accuracy= 89.718 - loss: 0.87499 9 /40 0.875 89.718 2.63353 49.573 0.00100 0.00100 accuracy 3.75 82.61 \n293/293 [==============================] - 83s 282ms/step - loss: 0.8750 - accuracy: 0.8972 - val_loss: 2.6335 - val_accuracy: 0.4957\nEpoch 10/40\n293/293 [==============================] - ETA: 0s - loss: 0.7325 - accuracy: 0.9134 7651 processing batch 1 of 293 - accuracy= 100.000 - loss: 0.65265 processing batch 2 of 293 - accuracy= 91.667 - loss: 0.99198 processing batch 3 of 293 - accuracy= 90.625 - loss: 0.93954 processing batch 4 of 293 - accuracy= 90.000 - loss: 0.91255 processing batch 5 of 293 - accuracy= 89.583 - loss: 0.89871 processing batch 6 of 293 - accuracy= 87.500 - loss: 0.89136 processing batch 7 of 293 - accuracy= 87.500 - loss: 0.89504 processing batch 8 of 293 - accuracy= 88.889 - loss: 0.87664 processing batch 9 of 293 - accuracy= 90.000 - loss: 0.85603 processing batch 10 of 293 - accuracy= 89.773 - loss: 0.85260 processing batch 11 of 293 - accuracy= 90.625 - loss: 0.82957 processing batch 12 of 293 - accuracy= 90.385 - loss: 0.82932 processing batch 13 of 293 - accuracy= 91.071 - loss: 0.81584 processing batch 14 of 293 - accuracy= 90.833 - loss: 0.81079 processing batch 15 of 293 - accuracy= 89.844 - loss: 0.81796 processing batch 16 of 293 - accuracy= 89.706 - loss: 0.82232 processing batch 17 of 293 - accuracy= 90.278 - loss: 0.81525 processing batch 18 of 293 - accuracy= 89.474 - loss: 0.81611 processing batch 19 of 293 - accuracy= 89.375 - loss: 0.81781 processing batch 20 of 293 - accuracy= 89.286 - loss: 0.82271 processing batch 21 of 293 - accuracy= 89.773 - loss: 0.81351 processing batch 22 of 293 - accuracy= 89.674 - loss: 0.82301 processing batch 23 of 293 - accuracy= 90.104 - loss: 0.81145 processing batch 24 of 293 - accuracy= 90.500 - loss: 0.80854 processing batch 25 of 293 - accuracy= 90.385 - loss: 0.81668 processing batch 26 of 293 - accuracy= 90.278 - loss: 0.81433 processing batch 27 of 293 - accuracy= 90.179 - loss: 0.80977 processing batch 28 of 293 - accuracy= 90.086 - loss: 0.80370 processing batch 29 of 293 - accuracy= 89.583 - loss: 0.80328 processing batch 30 of 293 - accuracy= 89.919 - loss: 0.79605 processing batch 31 of 293 - accuracy= 90.234 - loss: 0.79311 processing batch 32 of 293 - accuracy= 90.530 - loss: 0.78756 processing batch 33 of 293 - accuracy= 90.809 - loss: 0.78518 processing batch 34 of 293 - accuracy= 90.714 - loss: 0.79540 processing batch 35 of 293 - accuracy= 90.972 - loss: 0.78898 processing batch 36 of 293 - accuracy= 91.216 - loss: 0.78388 processing batch 37 of 293 - accuracy= 91.118 - loss: 0.78118 processing batch 38 of 293 - accuracy= 90.705 - loss: 0.78785 processing batch 39 of 293 - accuracy= 90.625 - loss: 0.78859 processing batch 40 of 293 - accuracy= 90.549 - loss: 0.79100 processing batch 41 of 293 - accuracy= 90.774 - loss: 0.78682 processing batch 42 of 293 - accuracy= 90.988 - loss: 0.78574 processing batch 43 of 293 - accuracy= 90.057 - loss: 0.80580 processing batch 44 of 293 - accuracy= 90.278 - loss: 0.80116 processing batch 45 of 293 - accuracy= 89.946 - loss: 0.81706 processing batch 46 of 293 - accuracy= 90.160 - loss: 0.81173 processing batch 47 of 293 - accuracy= 90.104 - loss: 0.80812 processing batch 48 of 293 - accuracy= 89.796 - loss: 0.81064 processing batch 49 of 293 - accuracy= 90.000 - loss: 0.81048 processing batch 50 of 293 - accuracy= 90.196 - loss: 0.80661 processing batch 51 of 293 - accuracy= 90.385 - loss: 0.80310 processing batch 52 of 293 - accuracy= 90.094 - loss: 0.80499 processing batch 53 of 293 - accuracy= 90.046 - loss: 0.80321 processing batch 54 of 293 - accuracy= 89.773 - loss: 0.80916 processing batch 55 of 293 - accuracy= 89.732 - loss: 0.80836 processing batch 56 of 293 - accuracy= 89.912 - loss: 0.80547 processing batch 57 of 293 - accuracy= 89.871 - loss: 0.80387 processing batch 58 of 293 - accuracy= 90.042 - loss: 0.80257 processing batch 59 of 293 - accuracy= 89.792 - loss: 0.80711 processing batch 60 of 293 - accuracy= 89.549 - loss: 0.81689 processing batch 61 of 293 - accuracy= 89.516 - loss: 0.82305 processing batch 62 of 293 - accuracy= 89.484 - loss: 0.82267 processing batch 63 of 293 - accuracy= 89.453 - loss: 0.82205 processing batch 64 of 293 - accuracy= 89.423 - loss: 0.82222 processing batch 65 of 293 - accuracy= 89.394 - loss: 0.81970 processing batch 66 of 293 - accuracy= 89.552 - loss: 0.81564 processing batch 67 of 293 - accuracy= 89.706 - loss: 0.81243 processing batch 68 of 293 - accuracy= 89.674 - loss: 0.81334 processing batch 69 of 293 - accuracy= 89.643 - loss: 0.81248 processing batch 70 of 293 - accuracy= 89.789 - loss: 0.81504 processing batch 71 of 293 - accuracy= 89.931 - loss: 0.81169 processing batch 72 of 293 - accuracy= 89.897 - loss: 0.81141 processing batch 73 of 293 - accuracy= 90.034 - loss: 0.80968 processing batch 74 of 293 - accuracy= 90.167 - loss: 0.80693 processing batch 75 of 293 - accuracy= 90.132 - loss: 0.80940 processing batch 76 of 293 - accuracy= 90.260 - loss: 0.80782 processing batch 77 of 293 - accuracy= 90.385 - loss: 0.80535 processing batch 78 of 293 - accuracy= 90.506 - loss: 0.80220 processing batch 79 of 293 - accuracy= 90.469 - loss: 0.80342 processing batch 80 of 293 - accuracy= 90.586 - loss: 0.80103 processing batch 81 of 293 - accuracy= 90.701 - loss: 0.79923 processing batch 82 of 293 - accuracy= 90.813 - loss: 0.79699 processing batch 83 of 293 - accuracy= 90.774 - loss: 0.79799 processing batch 84 of 293 - accuracy= 90.882 - loss: 0.79489 processing batch 85 of 293 - accuracy= 90.843 - loss: 0.79415 processing batch 86 of 293 - accuracy= 90.517 - loss: 0.79940 processing batch 87 of 293 - accuracy= 90.341 - loss: 0.80301 processing batch 88 of 293 - accuracy= 90.449 - loss: 0.80079 processing batch 89 of 293 - accuracy= 90.417 - loss: 0.79902 processing batch 90 of 293 - accuracy= 90.522 - loss: 0.79671 processing batch 91 of 293 - accuracy= 90.625 - loss: 0.79529 processing batch 92 of 293 - accuracy= 90.188 - loss: 0.79878 processing batch 93 of 293 - accuracy= 90.293 - loss: 0.79587 processing batch 94 of 293 - accuracy= 90.263 - loss: 0.79465 processing batch 95 of 293 - accuracy= 90.104 - loss: 0.79532 processing batch 96 of 293 - accuracy= 90.206 - loss: 0.79463 processing batch 97 of 293 - accuracy= 90.306 - loss: 0.79259 processing batch 98 of 293 - accuracy= 90.278 - loss: 0.79374 processing batch 99 of 293 - accuracy= 90.250 - loss: 0.79340 processing batch 100 of 293 - accuracy= 90.347 - loss: 0.79375 processing batch 101 of 293 - accuracy= 90.441 - loss: 0.79162 processing batch 102 of 293 - accuracy= 90.413 - loss: 0.79159 processing batch 103 of 293 - accuracy= 90.144 - loss: 0.79693 processing batch 104 of 293 - accuracy= 90.238 - loss: 0.79527 processing batch 105 of 293 - accuracy= 90.330 - loss: 0.79354 processing batch 106 of 293 - accuracy= 90.304 - loss: 0.79335 processing batch 107 of 293 - accuracy= 90.394 - loss: 0.79263 processing batch 108 of 293 - accuracy= 90.482 - loss: 0.79115 processing batch 109 of 293 - accuracy= 90.568 - loss: 0.78927 processing batch 110 of 293 - accuracy= 90.541 - loss: 0.79091 processing batch 111 of 293 - accuracy= 90.625 - loss: 0.78938 processing batch 112 of 293 - accuracy= 90.708 - loss: 0.78738 processing batch 113 of 293 - accuracy= 90.789 - loss: 0.78508 processing batch 114 of 293 - accuracy= 90.870 - loss: 0.78281 processing batch 115 of 293 - accuracy= 90.409 - loss: 0.79055 processing batch 116 of 293 - accuracy= 90.385 - loss: 0.79331 processing batch 117 of 293 - accuracy= 90.466 - loss: 0.79162 processing batch 118 of 293 - accuracy= 90.546 - loss: 0.78946 processing batch 119 of 293 - accuracy= 90.417 - loss: 0.79393 processing batch 120 of 293 - accuracy= 90.496 - loss: 0.79205 processing batch 121 of 293 - accuracy= 90.471 - loss: 0.79449 processing batch 122 of 293 - accuracy= 90.549 - loss: 0.79293 processing batch 123 of 293 - accuracy= 90.423 - loss: 0.79447 processing batch 124 of 293 - accuracy= 90.500 - loss: 0.79380 processing batch 125 of 293 - accuracy= 90.575 - loss: 0.79162 processing batch 126 of 293 - accuracy= 90.650 - loss: 0.78946 processing batch 127 of 293 - accuracy= 90.625 - loss: 0.78902 processing batch 128 of 293 - accuracy= 90.698 - loss: 0.78740 processing batch 129 of 293 - accuracy= 90.577 - loss: 0.78743 processing batch 130 of 293 - accuracy= 90.458 - loss: 0.79014 processing batch 131 of 293 - accuracy= 90.341 - loss: 0.79090 processing batch 132 of 293 - accuracy= 90.320 - loss: 0.79145 processing batch 133 of 293 - accuracy= 90.392 - loss: 0.79020 processing batch 134 of 293 - accuracy= 90.463 - loss: 0.78810 processing batch 135 of 293 - accuracy= 90.349 - loss: 0.78909 processing batch 136 of 293 - accuracy= 90.420 - loss: 0.78760 processing batch 137 of 293 - accuracy= 90.489 - loss: 0.78565 processing batch 138 of 293 - accuracy= 90.558 - loss: 0.78431 processing batch 139 of 293 - accuracy= 90.625 - loss: 0.78267 processing batch 140 of 293 - accuracy= 90.691 - loss: 0.78143 processing batch 141 of 293 - accuracy= 90.581 - loss: 0.78248 processing batch 142 of 293 - accuracy= 90.559 - loss: 0.78229 processing batch 143 of 293 - accuracy= 90.625 - loss: 0.78175 processing batch 144 of 293 - accuracy= 90.603 - loss: 0.78173 processing batch 145 of 293 - accuracy= 90.668 - loss: 0.78071 processing batch 146 of 293 - accuracy= 90.561 - loss: 0.78120 processing batch 147 of 293 - accuracy= 90.541 - loss: 0.78183 processing batch 148 of 293 - accuracy= 90.604 - loss: 0.78026 processing batch 149 of 293 - accuracy= 90.583 - loss: 0.78039 processing batch 150 of 293 - accuracy= 90.646 - loss: 0.77878 processing batch 151 of 293 - accuracy= 90.625 - loss: 0.77853 processing batch 152 of 293 - accuracy= 90.686 - loss: 0.77703 processing batch 153 of 293 - accuracy= 90.747 - loss: 0.77614 processing batch 154 of 293 - accuracy= 90.726 - loss: 0.77645 processing batch 155 of 293 - accuracy= 90.785 - loss: 0.77476 processing batch 156 of 293 - accuracy= 90.844 - loss: 0.77347 processing batch 157 of 293 - accuracy= 90.902 - loss: 0.77241 processing batch 158 of 293 - accuracy= 90.881 - loss: 0.77252 processing batch 159 of 293 - accuracy= 90.859 - loss: 0.77370 processing batch 160 of 293 - accuracy= 90.916 - loss: 0.77204 processing batch 161 of 293 - accuracy= 90.972 - loss: 0.77093 processing batch 162 of 293 - accuracy= 90.951 - loss: 0.77073 processing batch 163 of 293 - accuracy= 91.006 - loss: 0.76957 processing batch 164 of 293 - accuracy= 91.061 - loss: 0.76807 processing batch 165 of 293 - accuracy= 91.039 - loss: 0.76896 processing batch 166 of 293 - accuracy= 90.943 - loss: 0.77188 processing batch 167 of 293 - accuracy= 90.923 - loss: 0.77299 processing batch 168 of 293 - accuracy= 90.976 - loss: 0.77167 processing batch 169 of 293 - accuracy= 91.029 - loss: 0.77024 processing batch 170 of 293 - accuracy= 91.009 - loss: 0.76983 processing batch 171 of 293 - accuracy= 90.916 - loss: 0.77283 processing batch 172 of 293 - accuracy= 90.896 - loss: 0.77311 processing batch 173 of 293 - accuracy= 90.805 - loss: 0.77405 processing batch 174 of 293 - accuracy= 90.786 - loss: 0.77342 processing batch 175 of 293 - accuracy= 90.767 - loss: 0.77374 processing batch 176 of 293 - accuracy= 90.819 - loss: 0.77315 processing batch 177 of 293 - accuracy= 90.871 - loss: 0.77198 processing batch 178 of 293 - accuracy= 90.922 - loss: 0.77082 processing batch 179 of 293 - accuracy= 90.903 - loss: 0.77067 processing batch 180 of 293 - accuracy= 90.953 - loss: 0.77001 processing batch 181 of 293 - accuracy= 90.865 - loss: 0.77056 processing batch 182 of 293 - accuracy= 90.847 - loss: 0.77136 processing batch 183 of 293 - accuracy= 90.897 - loss: 0.77100 processing batch 184 of 293 - accuracy= 90.946 - loss: 0.76989 processing batch 185 of 293 - accuracy= 90.927 - loss: 0.76987 processing batch 186 of 293 - accuracy= 90.976 - loss: 0.76878 processing batch 187 of 293 - accuracy= 90.891 - loss: 0.76876 processing batch 188 of 293 - accuracy= 90.873 - loss: 0.76837 processing batch 189 of 293 - accuracy= 90.921 - loss: 0.76735 processing batch 190 of 293 - accuracy= 90.838 - loss: 0.76751 processing batch 191 of 293 - accuracy= 90.820 - loss: 0.76693 processing batch 192 of 293 - accuracy= 90.868 - loss: 0.76565 processing batch 193 of 293 - accuracy= 90.851 - loss: 0.76560 processing batch 194 of 293 - accuracy= 90.897 - loss: 0.76515 processing batch 195 of 293 - accuracy= 90.816 - loss: 0.76719 processing batch 196 of 293 - accuracy= 90.863 - loss: 0.76672 processing batch 197 of 293 - accuracy= 90.909 - loss: 0.76542 processing batch 198 of 293 - accuracy= 90.892 - loss: 0.76516 processing batch 199 of 293 - accuracy= 90.938 - loss: 0.76408 processing batch 200 of 293 - accuracy= 90.983 - loss: 0.76271 processing batch 201 of 293 - accuracy= 91.027 - loss: 0.76165 processing batch 202 of 293 - accuracy= 90.948 - loss: 0.76291 processing batch 203 of 293 - accuracy= 90.993 - loss: 0.76178 processing batch 204 of 293 - accuracy= 90.854 - loss: 0.76316 processing batch 205 of 293 - accuracy= 90.837 - loss: 0.76479 processing batch 206 of 293 - accuracy= 90.821 - loss: 0.76427 processing batch 207 of 293 - accuracy= 90.865 - loss: 0.76287 processing batch 208 of 293 - accuracy= 90.909 - loss: 0.76193 processing batch 209 of 293 - accuracy= 90.952 - loss: 0.76095 processing batch 210 of 293 - accuracy= 90.995 - loss: 0.75973 processing batch 211 of 293 - accuracy= 90.979 - loss: 0.75923 processing batch 212 of 293 - accuracy= 91.021 - loss: 0.75805 processing batch 213 of 293 - accuracy= 91.005 - loss: 0.75713 processing batch 214 of 293 - accuracy= 90.988 - loss: 0.75679 processing batch 215 of 293 - accuracy= 91.030 - loss: 0.75574 processing batch 216 of 293 - accuracy= 91.014 - loss: 0.75535 processing batch 217 of 293 - accuracy= 91.055 - loss: 0.75427 processing batch 218 of 293 - accuracy= 91.096 - loss: 0.75312 processing batch 219 of 293 - accuracy= 91.080 - loss: 0.75388 processing batch 220 of 293 - accuracy= 91.063 - loss: 0.75438 processing batch 221 of 293 - accuracy= 91.047 - loss: 0.75370 processing batch 222 of 293 - accuracy= 91.031 - loss: 0.75432 processing batch 223 of 293 - accuracy= 91.071 - loss: 0.75329 processing batch 224 of 293 - accuracy= 91.000 - loss: 0.75498 processing batch 225 of 293 - accuracy= 91.040 - loss: 0.75442 processing batch 226 of 293 - accuracy= 91.079 - loss: 0.75323 processing batch 227 of 293 - accuracy= 91.118 - loss: 0.75250 processing batch 228 of 293 - accuracy= 91.157 - loss: 0.75143 processing batch 229 of 293 - accuracy= 91.196 - loss: 0.75060 processing batch 230 of 293 - accuracy= 91.126 - loss: 0.75110 processing batch 231 of 293 - accuracy= 91.110 - loss: 0.75129 processing batch 232 of 293 - accuracy= 91.148 - loss: 0.75051 processing batch 233 of 293 - accuracy= 91.186 - loss: 0.74932 processing batch 234 of 293 - accuracy= 91.223 - loss: 0.74860 processing batch 235 of 293 - accuracy= 91.208 - loss: 0.74842 processing batch 236 of 293 - accuracy= 91.245 - loss: 0.74751 processing batch 237 of 293 - accuracy= 91.282 - loss: 0.74676 processing batch 238 of 293 - accuracy= 91.266 - loss: 0.74646 processing batch 239 of 293 - accuracy= 91.250 - loss: 0.74665 processing batch 240 of 293 - accuracy= 91.234 - loss: 0.74596 processing batch 241 of 293 - accuracy= 91.271 - loss: 0.74530 processing batch 242 of 293 - accuracy= 91.152 - loss: 0.74620 processing batch 243 of 293 - accuracy= 91.189 - loss: 0.74578 processing batch 244 of 293 - accuracy= 91.122 - loss: 0.74612 processing batch 245 of 293 - accuracy= 91.159 - loss: 0.74523 processing batch 246 of 293 - accuracy= 91.194 - loss: 0.74436 processing batch 247 of 293 - accuracy= 91.179 - loss: 0.74411 processing batch 248 of 293 - accuracy= 91.064 - loss: 0.74675 processing batch 249 of 293 - accuracy= 91.050 - loss: 0.74742 processing batch 250 of 293 - accuracy= 91.086 - loss: 0.74658 processing batch 251 of 293 - accuracy= 91.022 - loss: 0.74794 processing batch 252 of 293 - accuracy= 91.057 - loss: 0.74714 processing batch 253 of 293 - accuracy= 91.043 - loss: 0.74727 processing batch 254 of 293 - accuracy= 91.029 - loss: 0.74759 processing batch 255 of 293 - accuracy= 91.016 - loss: 0.74682 processing batch 256 of 293 - accuracy= 91.051 - loss: 0.74642 processing batch 257 of 293 - accuracy= 91.037 - loss: 0.74613 processing batch 258 of 293 - accuracy= 91.071 - loss: 0.74517 processing batch 259 of 293 - accuracy= 91.106 - loss: 0.74428 processing batch 260 of 293 - accuracy= 91.140 - loss: 0.74317 processing batch 261 of 293 - accuracy= 91.174 - loss: 0.74207 processing batch 262 of 293 - accuracy= 91.207 - loss: 0.74115 processing batch 263 of 293 - accuracy= 91.146 - loss: 0.74292 processing batch 264 of 293 - accuracy= 91.179 - loss: 0.74190 processing batch 265 of 293 - accuracy= 91.165 - loss: 0.74159 processing batch 266 of 293 - accuracy= 91.199 - loss: 0.74088 processing batch 267 of 293 - accuracy= 91.231 - loss: 0.73985 processing batch 268 of 293 - accuracy= 91.264 - loss: 0.73892 processing batch 269 of 293 - accuracy= 91.296 - loss: 0.73819 processing batch 270 of 293 - accuracy= 91.328 - loss: 0.73727 processing batch 271 of 293 - accuracy= 91.314 - loss: 0.73710 processing batch 272 of 293 - accuracy= 91.346 - loss: 0.73656 processing batch 273 of 293 - accuracy= 91.332 - loss: 0.73652 processing batch 274 of 293 - accuracy= 91.318 - loss: 0.73633 processing batch 275 of 293 - accuracy= 91.259 - loss: 0.73801 processing batch 276 of 293 - accuracy= 91.291 - loss: 0.73735 processing batch 277 of 293 - accuracy= 91.322 - loss: 0.73641 processing batch 278 of 293 - accuracy= 91.353 - loss: 0.73548 processing batch 279 of 293 - accuracy= 91.339 - loss: 0.73542 processing batch 280 of 293 - accuracy= 91.326 - loss: 0.73512 processing batch 281 of 293 - accuracy= 91.312 - loss: 0.73457 processing batch 282 of 293 - accuracy= 91.299 - loss: 0.73492 processing batch 283 of 293 - accuracy= 91.329 - loss: 0.73401 processing batch 284 of 293 - accuracy= 91.316 - loss: 0.73390 processing batch 285 of 293 - accuracy= 91.302 - loss: 0.73468 processing batch 286 of 293 - accuracy= 91.333 - loss: 0.73396 processing batch 287 of 293 - accuracy= 91.319 - loss: 0.73347 processing batch 288 of 293 - accuracy= 91.349 - loss: 0.73266 processing batch 289 of 293 - accuracy= 91.379 - loss: 0.73243 processing batch 290 of 293 - accuracy= 91.366 - loss: 0.73294 processing batch 291 of 293 - accuracy= 91.310 - loss: 0.73302 processing batch 292 of 293 - accuracy= 91.340 - loss: 0.7324510 /40 0.732 91.340 2.50176 49.402 0.00100 0.00050 val_loss -49.49 82.68 \n293/293 [==============================] - 83s 282ms/step - loss: 0.7325 - accuracy: 0.9134 - val_loss: 2.5018 - val_accuracy: 0.4940\nEpoch 11/40\n293/293 [==============================] - ETA: 0s - loss: 0.5784 - accuracy: 0.9509 032 processing batch 1 of 293 - accuracy= 87.500 - loss: 0.82988 processing batch 2 of 293 - accuracy= 91.667 - loss: 0.71432 processing batch 3 of 293 - accuracy= 90.625 - loss: 0.70474 processing batch 4 of 293 - accuracy= 90.000 - loss: 0.68888 processing batch 5 of 293 - accuracy= 89.583 - loss: 0.72761 processing batch 6 of 293 - accuracy= 89.286 - loss: 0.72227 processing batch 7 of 293 - accuracy= 89.062 - loss: 0.71576 processing batch 8 of 293 - accuracy= 88.889 - loss: 0.73830 processing batch 9 of 293 - accuracy= 87.500 - loss: 0.77031 processing batch 10 of 293 - accuracy= 88.636 - loss: 0.75862 processing batch 11 of 293 - accuracy= 89.583 - loss: 0.73685 processing batch 12 of 293 - accuracy= 90.385 - loss: 0.73105 processing batch 13 of 293 - accuracy= 90.179 - loss: 0.73615 processing batch 14 of 293 - accuracy= 90.833 - loss: 0.71746 processing batch 15 of 293 - accuracy= 91.406 - loss: 0.70135 processing batch 16 of 293 - accuracy= 90.441 - loss: 0.72166 processing batch 17 of 293 - accuracy= 90.278 - loss: 0.71325 processing batch 18 of 293 - accuracy= 90.789 - loss: 0.70509 processing batch 19 of 293 - accuracy= 91.250 - loss: 0.70048 processing batch 20 of 293 - accuracy= 91.667 - loss: 0.69182 processing batch 21 of 293 - accuracy= 91.477 - loss: 0.68996 processing batch 22 of 293 - accuracy= 91.848 - loss: 0.68205 processing batch 23 of 293 - accuracy= 92.188 - loss: 0.67201 processing batch 24 of 293 - accuracy= 92.500 - loss: 0.66810 processing batch 25 of 293 - accuracy= 92.308 - loss: 0.66771 processing batch 26 of 293 - accuracy= 92.593 - loss: 0.66351 processing batch 27 of 293 - accuracy= 91.964 - loss: 0.70030 processing batch 28 of 293 - accuracy= 92.241 - loss: 0.69503 processing batch 29 of 293 - accuracy= 92.500 - loss: 0.68915 processing batch 30 of 293 - accuracy= 92.742 - loss: 0.68580 processing batch 31 of 293 - accuracy= 92.969 - loss: 0.67767 processing batch 32 of 293 - accuracy= 92.803 - loss: 0.67824 processing batch 33 of 293 - accuracy= 93.015 - loss: 0.67194 processing batch 34 of 293 - accuracy= 93.214 - loss: 0.66750 processing batch 35 of 293 - accuracy= 93.403 - loss: 0.66277 processing batch 36 of 293 - accuracy= 93.581 - loss: 0.65876 processing batch 37 of 293 - accuracy= 93.750 - loss: 0.65410 processing batch 38 of 293 - accuracy= 93.910 - loss: 0.65001 processing batch 39 of 293 - accuracy= 93.750 - loss: 0.65252 processing batch 40 of 293 - accuracy= 93.902 - loss: 0.64848 processing batch 41 of 293 - accuracy= 94.048 - loss: 0.64382 processing batch 42 of 293 - accuracy= 93.895 - loss: 0.64303 processing batch 43 of 293 - accuracy= 94.034 - loss: 0.63888 processing batch 44 of 293 - accuracy= 94.167 - loss: 0.63572 processing batch 45 of 293 - accuracy= 94.293 - loss: 0.63607 processing batch 46 of 293 - accuracy= 94.415 - loss: 0.63478 processing batch 47 of 293 - accuracy= 94.531 - loss: 0.63107 processing batch 48 of 293 - accuracy= 94.643 - loss: 0.62729 processing batch 49 of 293 - accuracy= 94.500 - loss: 0.62828 processing batch 50 of 293 - accuracy= 94.608 - loss: 0.62566 processing batch 51 of 293 - accuracy= 94.712 - loss: 0.62330 processing batch 52 of 293 - accuracy= 94.811 - loss: 0.62316 processing batch 53 of 293 - accuracy= 94.907 - loss: 0.61945 processing batch 54 of 293 - accuracy= 95.000 - loss: 0.61904 processing batch 55 of 293 - accuracy= 95.089 - loss: 0.61657 processing batch 56 of 293 - accuracy= 95.175 - loss: 0.61342 processing batch 57 of 293 - accuracy= 95.259 - loss: 0.61067 processing batch 58 of 293 - accuracy= 95.339 - loss: 0.60926 processing batch 59 of 293 - accuracy= 95.208 - loss: 0.60892 processing batch 60 of 293 - accuracy= 95.287 - loss: 0.60691 processing batch 61 of 293 - accuracy= 95.363 - loss: 0.60575 processing batch 62 of 293 - accuracy= 95.437 - loss: 0.60375 processing batch 63 of 293 - accuracy= 95.312 - loss: 0.60446 processing batch 64 of 293 - accuracy= 95.385 - loss: 0.60162 processing batch 65 of 293 - accuracy= 95.265 - loss: 0.60249 processing batch 66 of 293 - accuracy= 95.336 - loss: 0.60012 processing batch 67 of 293 - accuracy= 95.404 - loss: 0.59911 processing batch 68 of 293 - accuracy= 95.471 - loss: 0.59841 processing batch 69 of 293 - accuracy= 95.536 - loss: 0.59585 processing batch 70 of 293 - accuracy= 95.599 - loss: 0.59399 processing batch 71 of 293 - accuracy= 95.660 - loss: 0.59219 processing batch 72 of 293 - accuracy= 95.719 - loss: 0.59050 processing batch 73 of 293 - accuracy= 95.777 - loss: 0.58908 processing batch 74 of 293 - accuracy= 95.667 - loss: 0.58930 processing batch 75 of 293 - accuracy= 95.724 - loss: 0.58891 processing batch 76 of 293 - accuracy= 95.617 - loss: 0.58913 processing batch 77 of 293 - accuracy= 95.673 - loss: 0.58740 processing batch 78 of 293 - accuracy= 95.728 - loss: 0.58593 processing batch 79 of 293 - accuracy= 95.781 - loss: 0.58421 processing batch 80 of 293 - accuracy= 95.833 - loss: 0.58224 processing batch 81 of 293 - accuracy= 95.884 - loss: 0.58096 processing batch 82 of 293 - accuracy= 95.633 - loss: 0.58529 processing batch 83 of 293 - accuracy= 95.685 - loss: 0.58475 processing batch 84 of 293 - accuracy= 95.588 - loss: 0.58631 processing batch 85 of 293 - accuracy= 95.494 - loss: 0.58816 processing batch 86 of 293 - accuracy= 95.546 - loss: 0.58723 processing batch 87 of 293 - accuracy= 95.455 - loss: 0.58846 processing batch 88 of 293 - accuracy= 95.225 - loss: 0.59670 processing batch 89 of 293 - accuracy= 95.278 - loss: 0.59540 processing batch 90 of 293 - accuracy= 95.192 - loss: 0.59764 processing batch 91 of 293 - accuracy= 95.245 - loss: 0.59627 processing batch 92 of 293 - accuracy= 95.296 - loss: 0.59498 processing batch 93 of 293 - accuracy= 95.346 - loss: 0.59493 processing batch 94 of 293 - accuracy= 95.395 - loss: 0.59414 processing batch 95 of 293 - accuracy= 95.443 - loss: 0.59558 processing batch 96 of 293 - accuracy= 95.490 - loss: 0.59546 processing batch 97 of 293 - accuracy= 95.536 - loss: 0.59497 processing batch 98 of 293 - accuracy= 95.581 - loss: 0.59395 processing batch 99 of 293 - accuracy= 95.500 - loss: 0.59721 processing batch 100 of 293 - accuracy= 95.421 - loss: 0.59801 processing batch 101 of 293 - accuracy= 95.466 - loss: 0.59716 processing batch 102 of 293 - accuracy= 95.267 - loss: 0.59950 processing batch 103 of 293 - accuracy= 95.312 - loss: 0.59808 processing batch 104 of 293 - accuracy= 95.357 - loss: 0.59749 processing batch 105 of 293 - accuracy= 95.165 - loss: 0.59972 processing batch 106 of 293 - accuracy= 95.093 - loss: 0.60058 processing batch 107 of 293 - accuracy= 95.023 - loss: 0.60190 processing batch 108 of 293 - accuracy= 95.069 - loss: 0.60127 processing batch 109 of 293 - accuracy= 95.000 - loss: 0.60181 processing batch 110 of 293 - accuracy= 94.932 - loss: 0.60225 processing batch 111 of 293 - accuracy= 94.866 - loss: 0.60248 processing batch 112 of 293 - accuracy= 94.912 - loss: 0.60130 processing batch 113 of 293 - accuracy= 94.846 - loss: 0.60416 processing batch 114 of 293 - accuracy= 94.891 - loss: 0.60320 processing batch 115 of 293 - accuracy= 94.828 - loss: 0.60358 processing batch 116 of 293 - accuracy= 94.872 - loss: 0.60364 processing batch 117 of 293 - accuracy= 94.915 - loss: 0.60267 processing batch 118 of 293 - accuracy= 94.958 - loss: 0.60130 processing batch 119 of 293 - accuracy= 95.000 - loss: 0.60123 processing batch 120 of 293 - accuracy= 94.938 - loss: 0.60105 processing batch 121 of 293 - accuracy= 94.980 - loss: 0.60016 processing batch 122 of 293 - accuracy= 95.020 - loss: 0.59942 processing batch 123 of 293 - accuracy= 95.060 - loss: 0.59847 processing batch 124 of 293 - accuracy= 95.100 - loss: 0.59791 processing batch 125 of 293 - accuracy= 95.040 - loss: 0.59880 processing batch 126 of 293 - accuracy= 94.980 - loss: 0.59929 processing batch 127 of 293 - accuracy= 94.824 - loss: 0.60192 processing batch 128 of 293 - accuracy= 94.864 - loss: 0.60080 processing batch 129 of 293 - accuracy= 94.808 - loss: 0.60201 processing batch 130 of 293 - accuracy= 94.847 - loss: 0.60141 processing batch 131 of 293 - accuracy= 94.886 - loss: 0.60015 processing batch 132 of 293 - accuracy= 94.925 - loss: 0.59877 processing batch 133 of 293 - accuracy= 94.963 - loss: 0.59789 processing batch 134 of 293 - accuracy= 95.000 - loss: 0.59765 processing batch 135 of 293 - accuracy= 94.945 - loss: 0.59857 processing batch 136 of 293 - accuracy= 94.982 - loss: 0.59740 processing batch 137 of 293 - accuracy= 95.018 - loss: 0.59636 processing batch 138 of 293 - accuracy= 95.054 - loss: 0.59520 processing batch 139 of 293 - accuracy= 95.000 - loss: 0.59574 processing batch 140 of 293 - accuracy= 95.035 - loss: 0.59472 processing batch 141 of 293 - accuracy= 94.806 - loss: 0.59820 processing batch 142 of 293 - accuracy= 94.755 - loss: 0.59853 processing batch 143 of 293 - accuracy= 94.792 - loss: 0.59736 processing batch 144 of 293 - accuracy= 94.828 - loss: 0.59641 processing batch 145 of 293 - accuracy= 94.863 - loss: 0.59660 processing batch 146 of 293 - accuracy= 94.898 - loss: 0.59571 processing batch 147 of 293 - accuracy= 94.932 - loss: 0.59450 processing batch 148 of 293 - accuracy= 94.966 - loss: 0.59338 processing batch 149 of 293 - accuracy= 95.000 - loss: 0.59244 processing batch 150 of 293 - accuracy= 94.785 - loss: 0.59613 processing batch 151 of 293 - accuracy= 94.819 - loss: 0.59543 processing batch 152 of 293 - accuracy= 94.853 - loss: 0.59505 processing batch 153 of 293 - accuracy= 94.886 - loss: 0.59387 processing batch 154 of 293 - accuracy= 94.919 - loss: 0.59373 processing batch 155 of 293 - accuracy= 94.952 - loss: 0.59381 processing batch 156 of 293 - accuracy= 94.904 - loss: 0.59350 processing batch 157 of 293 - accuracy= 94.778 - loss: 0.59480 processing batch 158 of 293 - accuracy= 94.811 - loss: 0.59463 processing batch 159 of 293 - accuracy= 94.844 - loss: 0.59350 processing batch 160 of 293 - accuracy= 94.876 - loss: 0.59267 processing batch 161 of 293 - accuracy= 94.907 - loss: 0.59247 processing batch 162 of 293 - accuracy= 94.862 - loss: 0.59329 processing batch 163 of 293 - accuracy= 94.817 - loss: 0.59360 processing batch 164 of 293 - accuracy= 94.848 - loss: 0.59308 processing batch 165 of 293 - accuracy= 94.880 - loss: 0.59258 processing batch 166 of 293 - accuracy= 94.910 - loss: 0.59139 processing batch 167 of 293 - accuracy= 94.940 - loss: 0.59110 processing batch 168 of 293 - accuracy= 94.896 - loss: 0.59175 processing batch 169 of 293 - accuracy= 94.926 - loss: 0.59084 processing batch 170 of 293 - accuracy= 94.956 - loss: 0.59053 processing batch 171 of 293 - accuracy= 94.985 - loss: 0.59017 processing batch 172 of 293 - accuracy= 94.942 - loss: 0.59390 processing batch 173 of 293 - accuracy= 94.971 - loss: 0.59305 processing batch 174 of 293 - accuracy= 94.929 - loss: 0.59310 processing batch 175 of 293 - accuracy= 94.957 - loss: 0.59295 processing batch 176 of 293 - accuracy= 94.915 - loss: 0.59339 processing batch 177 of 293 - accuracy= 94.944 - loss: 0.59343 processing batch 178 of 293 - accuracy= 94.972 - loss: 0.59297 processing batch 179 of 293 - accuracy= 95.000 - loss: 0.59223 processing batch 180 of 293 - accuracy= 95.028 - loss: 0.59164 processing batch 181 of 293 - accuracy= 95.055 - loss: 0.59138 processing batch 182 of 293 - accuracy= 95.014 - loss: 0.59159 processing batch 183 of 293 - accuracy= 95.041 - loss: 0.59125 processing batch 184 of 293 - accuracy= 95.068 - loss: 0.59071 processing batch 185 of 293 - accuracy= 95.094 - loss: 0.59014 processing batch 186 of 293 - accuracy= 95.120 - loss: 0.58953 processing batch 187 of 293 - accuracy= 95.146 - loss: 0.58887 processing batch 188 of 293 - accuracy= 94.974 - loss: 0.59419 processing batch 189 of 293 - accuracy= 94.868 - loss: 0.59541 processing batch 190 of 293 - accuracy= 94.830 - loss: 0.59720 processing batch 191 of 293 - accuracy= 94.857 - loss: 0.59643 processing batch 192 of 293 - accuracy= 94.883 - loss: 0.59591 processing batch 193 of 293 - accuracy= 94.910 - loss: 0.59497 processing batch 194 of 293 - accuracy= 94.936 - loss: 0.59454 processing batch 195 of 293 - accuracy= 94.962 - loss: 0.59400 processing batch 196 of 293 - accuracy= 94.987 - loss: 0.59335 processing batch 197 of 293 - accuracy= 95.013 - loss: 0.59237 processing batch 198 of 293 - accuracy= 95.038 - loss: 0.59181 processing batch 199 of 293 - accuracy= 95.063 - loss: 0.59093 processing batch 200 of 293 - accuracy= 95.087 - loss: 0.59057 processing batch 201 of 293 - accuracy= 95.111 - loss: 0.58993 processing batch 202 of 293 - accuracy= 95.074 - loss: 0.59009 processing batch 203 of 293 - accuracy= 94.975 - loss: 0.59181 processing batch 204 of 293 - accuracy= 95.000 - loss: 0.59101 processing batch 205 of 293 - accuracy= 95.024 - loss: 0.59016 processing batch 206 of 293 - accuracy= 94.988 - loss: 0.59003 processing batch 207 of 293 - accuracy= 94.952 - loss: 0.59150 processing batch 208 of 293 - accuracy= 94.856 - loss: 0.59272 processing batch 209 of 293 - accuracy= 94.821 - loss: 0.59304 processing batch 210 of 293 - accuracy= 94.846 - loss: 0.59240 processing batch 211 of 293 - accuracy= 94.870 - loss: 0.59240 processing batch 212 of 293 - accuracy= 94.894 - loss: 0.59163 processing batch 213 of 293 - accuracy= 94.918 - loss: 0.59134 processing batch 214 of 293 - accuracy= 94.942 - loss: 0.59075 processing batch 215 of 293 - accuracy= 94.907 - loss: 0.59103 processing batch 216 of 293 - accuracy= 94.873 - loss: 0.59132 processing batch 217 of 293 - accuracy= 94.897 - loss: 0.59040 processing batch 218 of 293 - accuracy= 94.920 - loss: 0.58964 processing batch 219 of 293 - accuracy= 94.886 - loss: 0.58999 processing batch 220 of 293 - accuracy= 94.910 - loss: 0.58978 processing batch 221 of 293 - accuracy= 94.932 - loss: 0.58896 processing batch 222 of 293 - accuracy= 94.955 - loss: 0.58830 processing batch 223 of 293 - accuracy= 94.922 - loss: 0.58913 processing batch 224 of 293 - accuracy= 94.944 - loss: 0.58837 processing batch 225 of 293 - accuracy= 94.967 - loss: 0.58793 processing batch 226 of 293 - accuracy= 94.989 - loss: 0.58781 processing batch 227 of 293 - accuracy= 94.956 - loss: 0.58803 processing batch 228 of 293 - accuracy= 94.978 - loss: 0.58727 processing batch 229 of 293 - accuracy= 95.000 - loss: 0.58659 processing batch 230 of 293 - accuracy= 95.022 - loss: 0.58622 processing batch 231 of 293 - accuracy= 94.989 - loss: 0.58616 processing batch 232 of 293 - accuracy= 94.957 - loss: 0.58621 processing batch 233 of 293 - accuracy= 94.872 - loss: 0.58687 processing batch 234 of 293 - accuracy= 94.894 - loss: 0.58664 processing batch 235 of 293 - accuracy= 94.915 - loss: 0.58665 processing batch 236 of 293 - accuracy= 94.937 - loss: 0.58603 processing batch 237 of 293 - accuracy= 94.958 - loss: 0.58547 processing batch 238 of 293 - accuracy= 94.979 - loss: 0.58505 processing batch 239 of 293 - accuracy= 95.000 - loss: 0.58447 processing batch 240 of 293 - accuracy= 95.021 - loss: 0.58408 processing batch 241 of 293 - accuracy= 95.041 - loss: 0.58369 processing batch 242 of 293 - accuracy= 95.062 - loss: 0.58302 processing batch 243 of 293 - accuracy= 95.082 - loss: 0.58261 processing batch 244 of 293 - accuracy= 95.102 - loss: 0.58198 processing batch 245 of 293 - accuracy= 95.122 - loss: 0.58185 processing batch 246 of 293 - accuracy= 95.142 - loss: 0.58130 processing batch 247 of 293 - accuracy= 95.161 - loss: 0.58088 processing batch 248 of 293 - accuracy= 95.181 - loss: 0.58035 processing batch 249 of 293 - accuracy= 95.100 - loss: 0.58189 processing batch 250 of 293 - accuracy= 95.020 - loss: 0.58280 processing batch 251 of 293 - accuracy= 94.990 - loss: 0.58409 processing batch 252 of 293 - accuracy= 95.010 - loss: 0.58376 processing batch 253 of 293 - accuracy= 95.030 - loss: 0.58337 processing batch 254 of 293 - accuracy= 95.000 - loss: 0.58420 processing batch 255 of 293 - accuracy= 95.020 - loss: 0.58379 processing batch 256 of 293 - accuracy= 94.990 - loss: 0.58347 processing batch 257 of 293 - accuracy= 95.010 - loss: 0.58321 processing batch 258 of 293 - accuracy= 94.981 - loss: 0.58337 processing batch 259 of 293 - accuracy= 95.000 - loss: 0.58302 processing batch 260 of 293 - accuracy= 94.875 - loss: 0.58478 processing batch 261 of 293 - accuracy= 94.895 - loss: 0.58407 processing batch 262 of 293 - accuracy= 94.914 - loss: 0.58349 processing batch 263 of 293 - accuracy= 94.934 - loss: 0.58311 processing batch 264 of 293 - accuracy= 94.953 - loss: 0.58273 processing batch 265 of 293 - accuracy= 94.925 - loss: 0.58297 processing batch 266 of 293 - accuracy= 94.944 - loss: 0.58270 processing batch 267 of 293 - accuracy= 94.916 - loss: 0.58255 processing batch 268 of 293 - accuracy= 94.935 - loss: 0.58225 processing batch 269 of 293 - accuracy= 94.907 - loss: 0.58409 processing batch 270 of 293 - accuracy= 94.880 - loss: 0.58405 processing batch 271 of 293 - accuracy= 94.853 - loss: 0.58492 processing batch 272 of 293 - accuracy= 94.872 - loss: 0.58431 processing batch 273 of 293 - accuracy= 94.891 - loss: 0.58381 processing batch 274 of 293 - accuracy= 94.909 - loss: 0.58324 processing batch 275 of 293 - accuracy= 94.882 - loss: 0.58361 processing batch 276 of 293 - accuracy= 94.901 - loss: 0.58337 processing batch 277 of 293 - accuracy= 94.919 - loss: 0.58326 processing batch 278 of 293 - accuracy= 94.892 - loss: 0.58443 processing batch 279 of 293 - accuracy= 94.911 - loss: 0.58385 processing batch 280 of 293 - accuracy= 94.929 - loss: 0.58336 processing batch 281 of 293 - accuracy= 94.947 - loss: 0.58280 processing batch 282 of 293 - accuracy= 94.965 - loss: 0.58221 processing batch 283 of 293 - accuracy= 94.982 - loss: 0.58198 processing batch 284 of 293 - accuracy= 95.000 - loss: 0.58142 processing batch 285 of 293 - accuracy= 95.017 - loss: 0.58108 processing batch 286 of 293 - accuracy= 94.991 - loss: 0.58078 processing batch 287 of 293 - accuracy= 95.009 - loss: 0.58084 processing batch 288 of 293 - accuracy= 95.026 - loss: 0.58055 processing batch 289 of 293 - accuracy= 95.043 - loss: 0.57994 processing batch 290 of 293 - accuracy= 95.060 - loss: 0.57946 processing batch 291 of 293 - accuracy= 95.077 - loss: 0.57898 processing batch 292 of 293 - accuracy= 95.094 - loss: 0.5783511 /40 0.578 95.094 1.01735 79.145 0.00050 0.00050 val_loss 39.21 82.46 \n293/293 [==============================] - 83s 282ms/step - loss: 0.5784 - accuracy: 0.9509 - val_loss: 1.0174 - val_accuracy: 0.7915\nEpoch 12/40\n293/293 [==============================] - ETA: 0s - loss: 0.5311 - accuracy: 0.9522 6497 processing batch 1 of 293 - accuracy= 100.000 - loss: 0.43309 processing batch 2 of 293 - accuracy= 100.000 - loss: 0.43035 processing batch 3 of 293 - accuracy= 100.000 - loss: 0.42992 processing batch 4 of 293 - accuracy= 100.000 - loss: 0.44087 processing batch 5 of 293 - accuracy= 100.000 - loss: 0.43170 processing batch 6 of 293 - accuracy= 100.000 - loss: 0.44184 processing batch 7 of 293 - accuracy= 95.312 - loss: 0.49904 processing batch 8 of 293 - accuracy= 95.833 - loss: 0.50313 processing batch 9 of 293 - accuracy= 96.250 - loss: 0.49644 processing batch 10 of 293 - accuracy= 96.591 - loss: 0.49688 processing batch 11 of 293 - accuracy= 95.833 - loss: 0.51526 processing batch 12 of 293 - accuracy= 93.269 - loss: 0.56685 processing batch 13 of 293 - accuracy= 93.750 - loss: 0.57112 processing batch 14 of 293 - accuracy= 94.167 - loss: 0.56290 processing batch 15 of 293 - accuracy= 92.969 - loss: 0.57754 processing batch 16 of 293 - accuracy= 92.647 - loss: 0.58364 processing batch 17 of 293 - accuracy= 93.056 - loss: 0.58320 processing batch 18 of 293 - accuracy= 93.421 - loss: 0.57444 processing batch 19 of 293 - accuracy= 93.750 - loss: 0.56521 processing batch 20 of 293 - accuracy= 94.048 - loss: 0.56529 processing batch 21 of 293 - accuracy= 93.750 - loss: 0.57219 processing batch 22 of 293 - accuracy= 94.022 - loss: 0.57047 processing batch 23 of 293 - accuracy= 93.750 - loss: 0.57240 processing batch 24 of 293 - accuracy= 94.000 - loss: 0.56612 processing batch 25 of 293 - accuracy= 94.231 - loss: 0.56264 processing batch 26 of 293 - accuracy= 93.519 - loss: 0.57838 processing batch 27 of 293 - accuracy= 93.750 - loss: 0.57313 processing batch 28 of 293 - accuracy= 93.534 - loss: 0.57696 processing batch 29 of 293 - accuracy= 93.750 - loss: 0.57089 processing batch 30 of 293 - accuracy= 93.548 - loss: 0.57077 processing batch 31 of 293 - accuracy= 93.750 - loss: 0.56646 processing batch 32 of 293 - accuracy= 93.939 - loss: 0.56047 processing batch 33 of 293 - accuracy= 94.118 - loss: 0.55708 processing batch 34 of 293 - accuracy= 94.286 - loss: 0.55398 processing batch 35 of 293 - accuracy= 94.097 - loss: 0.55476 processing batch 36 of 293 - accuracy= 93.243 - loss: 0.56513 processing batch 37 of 293 - accuracy= 93.421 - loss: 0.56065 processing batch 38 of 293 - accuracy= 93.269 - loss: 0.57289 processing batch 39 of 293 - accuracy= 93.437 - loss: 0.56954 processing batch 40 of 293 - accuracy= 93.598 - loss: 0.56819 processing batch 41 of 293 - accuracy= 93.452 - loss: 0.56947 processing batch 42 of 293 - accuracy= 93.605 - loss: 0.56703 processing batch 43 of 293 - accuracy= 93.750 - loss: 0.56352 processing batch 44 of 293 - accuracy= 93.611 - loss: 0.56750 processing batch 45 of 293 - accuracy= 93.750 - loss: 0.56380 processing batch 46 of 293 - accuracy= 93.883 - loss: 0.56113 processing batch 47 of 293 - accuracy= 93.750 - loss: 0.56324 processing batch 48 of 293 - accuracy= 93.878 - loss: 0.56054 processing batch 49 of 293 - accuracy= 93.750 - loss: 0.56097 processing batch 50 of 293 - accuracy= 93.873 - loss: 0.55933 processing batch 51 of 293 - accuracy= 93.750 - loss: 0.55999 processing batch 52 of 293 - accuracy= 93.868 - loss: 0.55739 processing batch 53 of 293 - accuracy= 93.750 - loss: 0.55722 processing batch 54 of 293 - accuracy= 93.864 - loss: 0.55823 processing batch 55 of 293 - accuracy= 93.973 - loss: 0.55832 processing batch 56 of 293 - accuracy= 94.079 - loss: 0.55617 processing batch 57 of 293 - accuracy= 94.181 - loss: 0.55379 processing batch 58 of 293 - accuracy= 94.068 - loss: 0.55278 processing batch 59 of 293 - accuracy= 94.167 - loss: 0.55000 processing batch 60 of 293 - accuracy= 94.262 - loss: 0.54851 processing batch 61 of 293 - accuracy= 94.153 - loss: 0.54810 processing batch 62 of 293 - accuracy= 94.246 - loss: 0.54624 processing batch 63 of 293 - accuracy= 94.336 - loss: 0.54426 processing batch 64 of 293 - accuracy= 94.423 - loss: 0.54279 processing batch 65 of 293 - accuracy= 94.129 - loss: 0.54950 processing batch 66 of 293 - accuracy= 94.216 - loss: 0.54722 processing batch 67 of 293 - accuracy= 94.301 - loss: 0.54549 processing batch 68 of 293 - accuracy= 94.203 - loss: 0.54672 processing batch 69 of 293 - accuracy= 94.286 - loss: 0.54527 processing batch 70 of 293 - accuracy= 94.366 - loss: 0.54474 processing batch 71 of 293 - accuracy= 94.097 - loss: 0.55107 processing batch 72 of 293 - accuracy= 94.178 - loss: 0.55150 processing batch 73 of 293 - accuracy= 94.257 - loss: 0.55108 processing batch 74 of 293 - accuracy= 94.333 - loss: 0.54873 processing batch 75 of 293 - accuracy= 94.243 - loss: 0.55113 processing batch 76 of 293 - accuracy= 94.318 - loss: 0.54957 processing batch 77 of 293 - accuracy= 94.391 - loss: 0.54756 processing batch 78 of 293 - accuracy= 94.462 - loss: 0.54582 processing batch 79 of 293 - accuracy= 94.531 - loss: 0.54396 processing batch 80 of 293 - accuracy= 94.599 - loss: 0.54243 processing batch 81 of 293 - accuracy= 94.665 - loss: 0.54156 processing batch 82 of 293 - accuracy= 94.729 - loss: 0.54135 processing batch 83 of 293 - accuracy= 94.792 - loss: 0.54071 processing batch 84 of 293 - accuracy= 94.559 - loss: 0.55026 processing batch 85 of 293 - accuracy= 94.477 - loss: 0.55097 processing batch 86 of 293 - accuracy= 94.540 - loss: 0.54969 processing batch 87 of 293 - accuracy= 94.176 - loss: 0.55584 processing batch 88 of 293 - accuracy= 94.242 - loss: 0.55460 processing batch 89 of 293 - accuracy= 94.306 - loss: 0.55316 processing batch 90 of 293 - accuracy= 94.368 - loss: 0.55128 processing batch 91 of 293 - accuracy= 94.293 - loss: 0.55591 processing batch 92 of 293 - accuracy= 94.355 - loss: 0.55434 processing batch 93 of 293 - accuracy= 94.415 - loss: 0.55350 processing batch 94 of 293 - accuracy= 94.342 - loss: 0.55409 processing batch 95 of 293 - accuracy= 94.401 - loss: 0.55253 processing batch 96 of 293 - accuracy= 94.459 - loss: 0.55127 processing batch 97 of 293 - accuracy= 94.515 - loss: 0.55009 processing batch 98 of 293 - accuracy= 94.571 - loss: 0.54876 processing batch 99 of 293 - accuracy= 94.625 - loss: 0.54807 processing batch 100 of 293 - accuracy= 94.431 - loss: 0.55242 processing batch 101 of 293 - accuracy= 94.485 - loss: 0.55068 processing batch 102 of 293 - accuracy= 94.539 - loss: 0.54942 processing batch 103 of 293 - accuracy= 94.591 - loss: 0.54815 processing batch 104 of 293 - accuracy= 94.524 - loss: 0.55026 processing batch 105 of 293 - accuracy= 94.575 - loss: 0.54888 processing batch 106 of 293 - accuracy= 94.626 - loss: 0.54765 processing batch 107 of 293 - accuracy= 94.560 - loss: 0.54765 processing batch 108 of 293 - accuracy= 94.610 - loss: 0.54686 processing batch 109 of 293 - accuracy= 94.659 - loss: 0.54572 processing batch 110 of 293 - accuracy= 94.707 - loss: 0.54599 processing batch 111 of 293 - accuracy= 94.754 - loss: 0.54468 processing batch 112 of 293 - accuracy= 94.801 - loss: 0.54382 processing batch 113 of 293 - accuracy= 94.737 - loss: 0.54543 processing batch 114 of 293 - accuracy= 94.783 - loss: 0.54493 processing batch 115 of 293 - accuracy= 94.720 - loss: 0.54510 processing batch 116 of 293 - accuracy= 94.765 - loss: 0.54399 processing batch 117 of 293 - accuracy= 94.703 - loss: 0.54516 processing batch 118 of 293 - accuracy= 94.748 - loss: 0.54487 processing batch 119 of 293 - accuracy= 94.687 - loss: 0.54417 processing batch 120 of 293 - accuracy= 94.731 - loss: 0.54327 processing batch 121 of 293 - accuracy= 94.775 - loss: 0.54189 processing batch 122 of 293 - accuracy= 94.817 - loss: 0.54045 processing batch 123 of 293 - accuracy= 94.859 - loss: 0.53977 processing batch 124 of 293 - accuracy= 94.900 - loss: 0.53887 processing batch 125 of 293 - accuracy= 94.940 - loss: 0.53810 processing batch 126 of 293 - accuracy= 94.882 - loss: 0.53826 processing batch 127 of 293 - accuracy= 94.922 - loss: 0.53719 processing batch 128 of 293 - accuracy= 94.864 - loss: 0.53810 processing batch 129 of 293 - accuracy= 94.808 - loss: 0.53917 processing batch 130 of 293 - accuracy= 94.656 - loss: 0.54660 processing batch 131 of 293 - accuracy= 94.697 - loss: 0.54571 processing batch 132 of 293 - accuracy= 94.737 - loss: 0.54484 processing batch 133 of 293 - accuracy= 94.776 - loss: 0.54357 processing batch 134 of 293 - accuracy= 94.815 - loss: 0.54269 processing batch 135 of 293 - accuracy= 94.669 - loss: 0.54430 processing batch 136 of 293 - accuracy= 94.708 - loss: 0.54318 processing batch 137 of 293 - accuracy= 94.656 - loss: 0.54331 processing batch 138 of 293 - accuracy= 94.694 - loss: 0.54213 processing batch 139 of 293 - accuracy= 94.732 - loss: 0.54267 processing batch 140 of 293 - accuracy= 94.681 - loss: 0.54237 processing batch 141 of 293 - accuracy= 94.718 - loss: 0.54236 processing batch 142 of 293 - accuracy= 94.668 - loss: 0.54300 processing batch 143 of 293 - accuracy= 94.705 - loss: 0.54282 processing batch 144 of 293 - accuracy= 94.741 - loss: 0.54189 processing batch 145 of 293 - accuracy= 94.777 - loss: 0.54103 processing batch 146 of 293 - accuracy= 94.643 - loss: 0.54566 processing batch 147 of 293 - accuracy= 94.595 - loss: 0.54608 processing batch 148 of 293 - accuracy= 94.631 - loss: 0.54584 processing batch 149 of 293 - accuracy= 94.667 - loss: 0.54555 processing batch 150 of 293 - accuracy= 94.702 - loss: 0.54533 processing batch 151 of 293 - accuracy= 94.655 - loss: 0.54618 processing batch 152 of 293 - accuracy= 94.690 - loss: 0.54591 processing batch 153 of 293 - accuracy= 94.724 - loss: 0.54518 processing batch 154 of 293 - accuracy= 94.758 - loss: 0.54497 processing batch 155 of 293 - accuracy= 94.792 - loss: 0.54404 processing batch 156 of 293 - accuracy= 94.825 - loss: 0.54367 processing batch 157 of 293 - accuracy= 94.858 - loss: 0.54285 processing batch 158 of 293 - accuracy= 94.890 - loss: 0.54210 processing batch 159 of 293 - accuracy= 94.844 - loss: 0.54233 processing batch 160 of 293 - accuracy= 94.720 - loss: 0.54407 processing batch 161 of 293 - accuracy= 94.753 - loss: 0.54314 processing batch 162 of 293 - accuracy= 94.709 - loss: 0.54450 processing batch 163 of 293 - accuracy= 94.741 - loss: 0.54402 processing batch 164 of 293 - accuracy= 94.773 - loss: 0.54409 processing batch 165 of 293 - accuracy= 94.804 - loss: 0.54318 processing batch 166 of 293 - accuracy= 94.835 - loss: 0.54248 processing batch 167 of 293 - accuracy= 94.866 - loss: 0.54169 processing batch 168 of 293 - accuracy= 94.896 - loss: 0.54130 processing batch 169 of 293 - accuracy= 94.926 - loss: 0.54068 processing batch 170 of 293 - accuracy= 94.883 - loss: 0.54040 processing batch 171 of 293 - accuracy= 94.840 - loss: 0.54118 processing batch 172 of 293 - accuracy= 94.870 - loss: 0.54036 processing batch 173 of 293 - accuracy= 94.828 - loss: 0.54065 processing batch 174 of 293 - accuracy= 94.857 - loss: 0.54030 processing batch 175 of 293 - accuracy= 94.815 - loss: 0.54085 processing batch 176 of 293 - accuracy= 94.774 - loss: 0.54113 processing batch 177 of 293 - accuracy= 94.803 - loss: 0.54068 processing batch 178 of 293 - accuracy= 94.763 - loss: 0.54080 processing batch 179 of 293 - accuracy= 94.792 - loss: 0.54014 processing batch 180 of 293 - accuracy= 94.751 - loss: 0.54023 processing batch 181 of 293 - accuracy= 94.780 - loss: 0.53974 processing batch 182 of 293 - accuracy= 94.809 - loss: 0.53917 processing batch 183 of 293 - accuracy= 94.837 - loss: 0.53842 processing batch 184 of 293 - accuracy= 94.865 - loss: 0.53752 processing batch 185 of 293 - accuracy= 94.892 - loss: 0.53680 processing batch 186 of 293 - accuracy= 94.920 - loss: 0.53601 processing batch 187 of 293 - accuracy= 94.947 - loss: 0.53544 processing batch 188 of 293 - accuracy= 94.974 - loss: 0.53481 processing batch 189 of 293 - accuracy= 95.000 - loss: 0.53457 processing batch 190 of 293 - accuracy= 95.026 - loss: 0.53402 processing batch 191 of 293 - accuracy= 95.052 - loss: 0.53316 processing batch 192 of 293 - accuracy= 95.013 - loss: 0.53324 processing batch 193 of 293 - accuracy= 94.910 - loss: 0.53509 processing batch 194 of 293 - accuracy= 94.936 - loss: 0.53477 processing batch 195 of 293 - accuracy= 94.962 - loss: 0.53435 processing batch 196 of 293 - accuracy= 94.924 - loss: 0.53610 processing batch 197 of 293 - accuracy= 94.949 - loss: 0.53584 processing batch 198 of 293 - accuracy= 94.975 - loss: 0.53528 processing batch 199 of 293 - accuracy= 94.875 - loss: 0.53704 processing batch 200 of 293 - accuracy= 94.900 - loss: 0.53626 processing batch 201 of 293 - accuracy= 94.926 - loss: 0.53547 processing batch 202 of 293 - accuracy= 94.889 - loss: 0.53542 processing batch 203 of 293 - accuracy= 94.853 - loss: 0.53586 processing batch 204 of 293 - accuracy= 94.817 - loss: 0.53767 processing batch 205 of 293 - accuracy= 94.842 - loss: 0.53743 processing batch 206 of 293 - accuracy= 94.867 - loss: 0.53673 processing batch 207 of 293 - accuracy= 94.892 - loss: 0.53603 processing batch 208 of 293 - accuracy= 94.856 - loss: 0.53794 processing batch 209 of 293 - accuracy= 94.881 - loss: 0.53791 processing batch 210 of 293 - accuracy= 94.846 - loss: 0.53921 processing batch 211 of 293 - accuracy= 94.870 - loss: 0.53908 processing batch 212 of 293 - accuracy= 94.836 - loss: 0.54069 processing batch 213 of 293 - accuracy= 94.801 - loss: 0.54154 processing batch 214 of 293 - accuracy= 94.826 - loss: 0.54081 processing batch 215 of 293 - accuracy= 94.850 - loss: 0.54033 processing batch 216 of 293 - accuracy= 94.873 - loss: 0.53979 processing batch 217 of 293 - accuracy= 94.897 - loss: 0.53904 processing batch 218 of 293 - accuracy= 94.920 - loss: 0.53904 processing batch 219 of 293 - accuracy= 94.943 - loss: 0.53861 processing batch 220 of 293 - accuracy= 94.966 - loss: 0.53807 processing batch 221 of 293 - accuracy= 94.989 - loss: 0.53734 processing batch 222 of 293 - accuracy= 95.011 - loss: 0.53690 processing batch 223 of 293 - accuracy= 94.978 - loss: 0.53805 processing batch 224 of 293 - accuracy= 94.944 - loss: 0.53831 processing batch 225 of 293 - accuracy= 94.967 - loss: 0.53805 processing batch 226 of 293 - accuracy= 94.989 - loss: 0.53736 processing batch 227 of 293 - accuracy= 95.011 - loss: 0.53690 processing batch 228 of 293 - accuracy= 94.978 - loss: 0.53828 processing batch 229 of 293 - accuracy= 94.891 - loss: 0.53916 processing batch 230 of 293 - accuracy= 94.913 - loss: 0.53895 processing batch 231 of 293 - accuracy= 94.935 - loss: 0.53831 processing batch 232 of 293 - accuracy= 94.957 - loss: 0.53795 processing batch 233 of 293 - accuracy= 94.979 - loss: 0.53746 processing batch 234 of 293 - accuracy= 95.000 - loss: 0.53735 processing batch 235 of 293 - accuracy= 95.021 - loss: 0.53666 processing batch 236 of 293 - accuracy= 95.042 - loss: 0.53596 processing batch 237 of 293 - accuracy= 95.063 - loss: 0.53561 processing batch 238 of 293 - accuracy= 95.031 - loss: 0.53648 processing batch 239 of 293 - accuracy= 95.052 - loss: 0.53612 processing batch 240 of 293 - accuracy= 95.073 - loss: 0.53567 processing batch 241 of 293 - accuracy= 95.093 - loss: 0.53495 processing batch 242 of 293 - accuracy= 95.062 - loss: 0.53566 processing batch 243 of 293 - accuracy= 94.980 - loss: 0.53706 processing batch 244 of 293 - accuracy= 94.949 - loss: 0.53723 processing batch 245 of 293 - accuracy= 94.970 - loss: 0.53696 processing batch 246 of 293 - accuracy= 94.939 - loss: 0.53744 processing batch 247 of 293 - accuracy= 94.960 - loss: 0.53717 processing batch 248 of 293 - accuracy= 94.980 - loss: 0.53712 processing batch 249 of 293 - accuracy= 95.000 - loss: 0.53654 processing batch 250 of 293 - accuracy= 95.020 - loss: 0.53600 processing batch 251 of 293 - accuracy= 94.990 - loss: 0.53665 processing batch 252 of 293 - accuracy= 95.010 - loss: 0.53610 processing batch 253 of 293 - accuracy= 95.030 - loss: 0.53542 processing batch 254 of 293 - accuracy= 95.049 - loss: 0.53476 processing batch 255 of 293 - accuracy= 95.068 - loss: 0.53432 processing batch 256 of 293 - accuracy= 95.039 - loss: 0.53555 processing batch 257 of 293 - accuracy= 95.058 - loss: 0.53511 processing batch 258 of 293 - accuracy= 95.077 - loss: 0.53472 processing batch 259 of 293 - accuracy= 95.096 - loss: 0.53484 processing batch 260 of 293 - accuracy= 95.115 - loss: 0.53435 processing batch 261 of 293 - accuracy= 95.086 - loss: 0.53558 processing batch 262 of 293 - accuracy= 95.105 - loss: 0.53496 processing batch 263 of 293 - accuracy= 95.123 - loss: 0.53484 processing batch 264 of 293 - accuracy= 95.142 - loss: 0.53434 processing batch 265 of 293 - accuracy= 95.113 - loss: 0.53506 processing batch 266 of 293 - accuracy= 95.131 - loss: 0.53476 processing batch 267 of 293 - accuracy= 95.103 - loss: 0.53558 processing batch 268 of 293 - accuracy= 95.121 - loss: 0.53504 processing batch 269 of 293 - accuracy= 95.093 - loss: 0.53528 processing batch 270 of 293 - accuracy= 95.111 - loss: 0.53481 processing batch 271 of 293 - accuracy= 95.129 - loss: 0.53442 processing batch 272 of 293 - accuracy= 95.101 - loss: 0.53508 processing batch 273 of 293 - accuracy= 95.119 - loss: 0.53467 processing batch 274 of 293 - accuracy= 95.136 - loss: 0.53403 processing batch 275 of 293 - accuracy= 95.109 - loss: 0.53458 processing batch 276 of 293 - accuracy= 95.081 - loss: 0.53447 processing batch 277 of 293 - accuracy= 95.099 - loss: 0.53521 processing batch 278 of 293 - accuracy= 95.116 - loss: 0.53505 processing batch 279 of 293 - accuracy= 95.134 - loss: 0.53444 processing batch 280 of 293 - accuracy= 95.151 - loss: 0.53398 processing batch 281 of 293 - accuracy= 95.168 - loss: 0.53354 processing batch 282 of 293 - accuracy= 95.186 - loss: 0.53306 processing batch 283 of 293 - accuracy= 95.202 - loss: 0.53287 processing batch 284 of 293 - accuracy= 95.219 - loss: 0.53243 processing batch 285 of 293 - accuracy= 95.236 - loss: 0.53210 processing batch 286 of 293 - accuracy= 95.209 - loss: 0.53298 processing batch 287 of 293 - accuracy= 95.226 - loss: 0.53250 processing batch 288 of 293 - accuracy= 95.199 - loss: 0.53247 processing batch 289 of 293 - accuracy= 95.216 - loss: 0.53217 processing batch 290 of 293 - accuracy= 95.189 - loss: 0.53219 processing batch 291 of 293 - accuracy= 95.205 - loss: 0.53167 processing batch 292 of 293 - accuracy= 95.222 - loss: 0.5311112 /40 0.531 95.222 0.88016 80.000 0.00050 0.00050 val_loss 13.49 82.23 \n293/293 [==============================] - 82s 281ms/step - loss: 0.5311 - accuracy: 0.9522 - val_loss: 0.8802 - val_accuracy: 0.8000\nEpoch 13/40\n293/293 [==============================] - ETA: 0s - loss: 0.4600 - accuracy: 0.9663 3459 processing batch 1 of 293 - accuracy= 100.000 - loss: 0.44013 processing batch 2 of 293 - accuracy= 100.000 - loss: 0.43897 processing batch 3 of 293 - accuracy= 100.000 - loss: 0.45016 processing batch 4 of 293 - accuracy= 100.000 - loss: 0.43141 processing batch 5 of 293 - accuracy= 97.917 - loss: 0.44060 processing batch 6 of 293 - accuracy= 98.214 - loss: 0.45287 processing batch 7 of 293 - accuracy= 98.438 - loss: 0.44652 processing batch 8 of 293 - accuracy= 98.611 - loss: 0.43790 processing batch 9 of 293 - accuracy= 98.750 - loss: 0.45577 processing batch 10 of 293 - accuracy= 98.864 - loss: 0.44690 processing batch 11 of 293 - accuracy= 98.958 - loss: 0.44370 processing batch 12 of 293 - accuracy= 99.038 - loss: 0.44563 processing batch 13 of 293 - accuracy= 99.107 - loss: 0.44239 processing batch 14 of 293 - accuracy= 98.333 - loss: 0.45872 processing batch 15 of 293 - accuracy= 98.438 - loss: 0.46001 processing batch 16 of 293 - accuracy= 98.529 - loss: 0.45417 processing batch 17 of 293 - accuracy= 98.611 - loss: 0.45085 processing batch 18 of 293 - accuracy= 98.026 - loss: 0.46576 processing batch 19 of 293 - accuracy= 98.125 - loss: 0.46050 processing batch 20 of 293 - accuracy= 97.024 - loss: 0.49834 processing batch 21 of 293 - accuracy= 96.591 - loss: 0.50130 processing batch 22 of 293 - accuracy= 96.196 - loss: 0.51233 processing batch 23 of 293 - accuracy= 96.354 - loss: 0.51115 processing batch 24 of 293 - accuracy= 96.500 - loss: 0.50728 processing batch 25 of 293 - accuracy= 96.635 - loss: 0.50464 processing batch 26 of 293 - accuracy= 96.759 - loss: 0.50489 processing batch 27 of 293 - accuracy= 96.875 - loss: 0.50243 processing batch 28 of 293 - accuracy= 96.983 - loss: 0.49786 processing batch 29 of 293 - accuracy= 97.083 - loss: 0.49549 processing batch 30 of 293 - accuracy= 97.177 - loss: 0.49071 processing batch 31 of 293 - accuracy= 97.266 - loss: 0.48647 processing batch 32 of 293 - accuracy= 97.348 - loss: 0.48696 processing batch 33 of 293 - accuracy= 97.426 - loss: 0.48571 processing batch 34 of 293 - accuracy= 97.500 - loss: 0.48192 processing batch 35 of 293 - accuracy= 97.569 - loss: 0.48291 processing batch 36 of 293 - accuracy= 97.635 - loss: 0.48133 processing batch 37 of 293 - accuracy= 97.697 - loss: 0.47854 processing batch 38 of 293 - accuracy= 97.756 - loss: 0.47647 processing batch 39 of 293 - accuracy= 97.812 - loss: 0.47354 processing batch 40 of 293 - accuracy= 97.866 - loss: 0.47147 processing batch 41 of 293 - accuracy= 97.917 - loss: 0.46987 processing batch 42 of 293 - accuracy= 97.384 - loss: 0.48240 processing batch 43 of 293 - accuracy= 97.443 - loss: 0.48125 processing batch 44 of 293 - accuracy= 97.500 - loss: 0.48049 processing batch 45 of 293 - accuracy= 97.554 - loss: 0.47986 processing batch 46 of 293 - accuracy= 97.606 - loss: 0.47756 processing batch 47 of 293 - accuracy= 97.656 - loss: 0.47575 processing batch 48 of 293 - accuracy= 97.704 - loss: 0.47505 processing batch 49 of 293 - accuracy= 97.500 - loss: 0.47697 processing batch 50 of 293 - accuracy= 97.549 - loss: 0.47569 processing batch 51 of 293 - accuracy= 97.596 - loss: 0.47424 processing batch 52 of 293 - accuracy= 97.642 - loss: 0.47362 processing batch 53 of 293 - accuracy= 97.685 - loss: 0.47154 processing batch 54 of 293 - accuracy= 97.500 - loss: 0.47688 processing batch 55 of 293 - accuracy= 97.321 - loss: 0.47979 processing batch 56 of 293 - accuracy= 97.368 - loss: 0.48016 processing batch 57 of 293 - accuracy= 97.414 - loss: 0.47837 processing batch 58 of 293 - accuracy= 97.034 - loss: 0.48010 processing batch 59 of 293 - accuracy= 97.083 - loss: 0.47833 processing batch 60 of 293 - accuracy= 96.721 - loss: 0.48239 processing batch 61 of 293 - accuracy= 96.774 - loss: 0.48076 processing batch 62 of 293 - accuracy= 96.627 - loss: 0.48245 processing batch 63 of 293 - accuracy= 96.094 - loss: 0.49976 processing batch 64 of 293 - accuracy= 95.962 - loss: 0.50112 processing batch 65 of 293 - accuracy= 96.023 - loss: 0.49971 processing batch 66 of 293 - accuracy= 96.082 - loss: 0.49821 processing batch 67 of 293 - accuracy= 96.140 - loss: 0.49748 processing batch 68 of 293 - accuracy= 96.196 - loss: 0.49562 processing batch 69 of 293 - accuracy= 96.250 - loss: 0.49462 processing batch 70 of 293 - accuracy= 96.303 - loss: 0.49404 processing batch 71 of 293 - accuracy= 96.181 - loss: 0.49591 processing batch 72 of 293 - accuracy= 96.233 - loss: 0.49527 processing batch 73 of 293 - accuracy= 96.284 - loss: 0.49396 processing batch 74 of 293 - accuracy= 96.333 - loss: 0.49278 processing batch 75 of 293 - accuracy= 96.217 - loss: 0.49362 processing batch 76 of 293 - accuracy= 96.266 - loss: 0.49240 processing batch 77 of 293 - accuracy= 96.314 - loss: 0.49284 processing batch 78 of 293 - accuracy= 96.361 - loss: 0.49148 processing batch 79 of 293 - accuracy= 96.406 - loss: 0.49020 processing batch 80 of 293 - accuracy= 96.451 - loss: 0.48856 processing batch 81 of 293 - accuracy= 96.494 - loss: 0.48748 processing batch 82 of 293 - accuracy= 96.536 - loss: 0.48671 processing batch 83 of 293 - accuracy= 96.280 - loss: 0.49044 processing batch 84 of 293 - accuracy= 96.324 - loss: 0.48941 processing batch 85 of 293 - accuracy= 96.366 - loss: 0.48848 processing batch 86 of 293 - accuracy= 96.408 - loss: 0.48705 processing batch 87 of 293 - accuracy= 96.449 - loss: 0.48569 processing batch 88 of 293 - accuracy= 96.489 - loss: 0.48433 processing batch 89 of 293 - accuracy= 96.528 - loss: 0.48471 processing batch 90 of 293 - accuracy= 96.154 - loss: 0.48966 processing batch 91 of 293 - accuracy= 96.196 - loss: 0.48925 processing batch 92 of 293 - accuracy= 96.237 - loss: 0.48847 processing batch 93 of 293 - accuracy= 96.144 - loss: 0.48871 processing batch 94 of 293 - accuracy= 95.921 - loss: 0.49098 processing batch 95 of 293 - accuracy= 95.833 - loss: 0.49196 processing batch 96 of 293 - accuracy= 95.747 - loss: 0.49464 processing batch 97 of 293 - accuracy= 95.791 - loss: 0.49392 processing batch 98 of 293 - accuracy= 95.833 - loss: 0.49256 processing batch 99 of 293 - accuracy= 95.875 - loss: 0.49141 processing batch 100 of 293 - accuracy= 95.916 - loss: 0.49138 processing batch 101 of 293 - accuracy= 95.956 - loss: 0.49194 processing batch 102 of 293 - accuracy= 95.995 - loss: 0.49132 processing batch 103 of 293 - accuracy= 96.034 - loss: 0.49160 processing batch 104 of 293 - accuracy= 96.071 - loss: 0.49046 processing batch 105 of 293 - accuracy= 96.108 - loss: 0.48910 processing batch 106 of 293 - accuracy= 96.028 - loss: 0.49031 processing batch 107 of 293 - accuracy= 95.833 - loss: 0.49307 processing batch 108 of 293 - accuracy= 95.872 - loss: 0.49170 processing batch 109 of 293 - accuracy= 95.909 - loss: 0.49068 processing batch 110 of 293 - accuracy= 95.946 - loss: 0.48967 processing batch 111 of 293 - accuracy= 95.759 - loss: 0.49163 processing batch 112 of 293 - accuracy= 95.686 - loss: 0.49312 processing batch 113 of 293 - accuracy= 95.724 - loss: 0.49181 processing batch 114 of 293 - accuracy= 95.761 - loss: 0.49053 processing batch 115 of 293 - accuracy= 95.797 - loss: 0.48954 processing batch 116 of 293 - accuracy= 95.726 - loss: 0.48995 processing batch 117 of 293 - accuracy= 95.763 - loss: 0.48907 processing batch 118 of 293 - accuracy= 95.693 - loss: 0.48961 processing batch 119 of 293 - accuracy= 95.729 - loss: 0.48853 processing batch 120 of 293 - accuracy= 95.764 - loss: 0.48738 processing batch 121 of 293 - accuracy= 95.799 - loss: 0.48636 processing batch 122 of 293 - accuracy= 95.833 - loss: 0.48521 processing batch 123 of 293 - accuracy= 95.867 - loss: 0.48422 processing batch 124 of 293 - accuracy= 95.900 - loss: 0.48403 processing batch 125 of 293 - accuracy= 95.933 - loss: 0.48417 processing batch 126 of 293 - accuracy= 95.866 - loss: 0.48455 processing batch 127 of 293 - accuracy= 95.898 - loss: 0.48425 processing batch 128 of 293 - accuracy= 95.930 - loss: 0.48388 processing batch 129 of 293 - accuracy= 95.962 - loss: 0.48282 processing batch 130 of 293 - accuracy= 95.992 - loss: 0.48175 processing batch 131 of 293 - accuracy= 96.023 - loss: 0.48065 processing batch 132 of 293 - accuracy= 96.053 - loss: 0.48021 processing batch 133 of 293 - accuracy= 96.082 - loss: 0.47967 processing batch 134 of 293 - accuracy= 96.111 - loss: 0.47844 processing batch 135 of 293 - accuracy= 95.956 - loss: 0.48006 processing batch 136 of 293 - accuracy= 95.985 - loss: 0.47955 processing batch 137 of 293 - accuracy= 96.014 - loss: 0.48032 processing batch 138 of 293 - accuracy= 96.043 - loss: 0.47937 processing batch 139 of 293 - accuracy= 96.071 - loss: 0.47868 processing batch 140 of 293 - accuracy= 96.099 - loss: 0.47769 processing batch 141 of 293 - accuracy= 96.127 - loss: 0.47697 processing batch 142 of 293 - accuracy= 96.154 - loss: 0.47658 processing batch 143 of 293 - accuracy= 96.181 - loss: 0.47576 processing batch 144 of 293 - accuracy= 96.207 - loss: 0.47528 processing batch 145 of 293 - accuracy= 96.233 - loss: 0.47455 processing batch 146 of 293 - accuracy= 96.259 - loss: 0.47407 processing batch 147 of 293 - accuracy= 96.199 - loss: 0.47418 processing batch 148 of 293 - accuracy= 96.225 - loss: 0.47391 processing batch 149 of 293 - accuracy= 96.250 - loss: 0.47323 processing batch 150 of 293 - accuracy= 96.275 - loss: 0.47312 processing batch 151 of 293 - accuracy= 96.299 - loss: 0.47236 processing batch 152 of 293 - accuracy= 96.242 - loss: 0.47264 processing batch 153 of 293 - accuracy= 96.266 - loss: 0.47215 processing batch 154 of 293 - accuracy= 96.290 - loss: 0.47155 processing batch 155 of 293 - accuracy= 96.314 - loss: 0.47077 processing batch 156 of 293 - accuracy= 96.178 - loss: 0.47244 processing batch 157 of 293 - accuracy= 96.123 - loss: 0.47425 processing batch 158 of 293 - accuracy= 96.148 - loss: 0.47379 processing batch 159 of 293 - accuracy= 96.172 - loss: 0.47297 processing batch 160 of 293 - accuracy= 96.196 - loss: 0.47239 processing batch 161 of 293 - accuracy= 96.219 - loss: 0.47186 processing batch 162 of 293 - accuracy= 96.242 - loss: 0.47168 processing batch 163 of 293 - accuracy= 96.265 - loss: 0.47140 processing batch 164 of 293 - accuracy= 96.288 - loss: 0.47111 processing batch 165 of 293 - accuracy= 96.310 - loss: 0.47053 processing batch 166 of 293 - accuracy= 96.183 - loss: 0.47398 processing batch 167 of 293 - accuracy= 96.205 - loss: 0.47363 processing batch 168 of 293 - accuracy= 96.228 - loss: 0.47330 processing batch 169 of 293 - accuracy= 96.250 - loss: 0.47272 processing batch 170 of 293 - accuracy= 96.272 - loss: 0.47190 processing batch 171 of 293 - accuracy= 96.294 - loss: 0.47114 processing batch 172 of 293 - accuracy= 96.315 - loss: 0.47057 processing batch 173 of 293 - accuracy= 96.264 - loss: 0.47089 processing batch 174 of 293 - accuracy= 96.286 - loss: 0.47068 processing batch 175 of 293 - accuracy= 96.307 - loss: 0.47010 processing batch 176 of 293 - accuracy= 96.328 - loss: 0.47041 processing batch 177 of 293 - accuracy= 96.278 - loss: 0.47070 processing batch 178 of 293 - accuracy= 96.299 - loss: 0.47024 processing batch 179 of 293 - accuracy= 96.250 - loss: 0.47147 processing batch 180 of 293 - accuracy= 96.271 - loss: 0.47073 processing batch 181 of 293 - accuracy= 96.291 - loss: 0.47019 processing batch 182 of 293 - accuracy= 96.311 - loss: 0.46970 processing batch 183 of 293 - accuracy= 96.332 - loss: 0.46910 processing batch 184 of 293 - accuracy= 96.351 - loss: 0.46838 processing batch 185 of 293 - accuracy= 96.371 - loss: 0.46777 processing batch 186 of 293 - accuracy= 96.390 - loss: 0.46749 processing batch 187 of 293 - accuracy= 96.410 - loss: 0.46679 processing batch 188 of 293 - accuracy= 96.429 - loss: 0.46611 processing batch 189 of 293 - accuracy= 96.382 - loss: 0.46669 processing batch 190 of 293 - accuracy= 96.401 - loss: 0.46617 processing batch 191 of 293 - accuracy= 96.419 - loss: 0.46565 processing batch 192 of 293 - accuracy= 96.438 - loss: 0.46510 processing batch 193 of 293 - accuracy= 96.456 - loss: 0.46559 processing batch 194 of 293 - accuracy= 96.410 - loss: 0.46625 processing batch 195 of 293 - accuracy= 96.429 - loss: 0.46573 processing batch 196 of 293 - accuracy= 96.447 - loss: 0.46550 processing batch 197 of 293 - accuracy= 96.465 - loss: 0.46598 processing batch 198 of 293 - accuracy= 96.482 - loss: 0.46550 processing batch 199 of 293 - accuracy= 96.438 - loss: 0.46702 processing batch 200 of 293 - accuracy= 96.455 - loss: 0.46653 processing batch 201 of 293 - accuracy= 96.473 - loss: 0.46714 processing batch 202 of 293 - accuracy= 96.429 - loss: 0.46805 processing batch 203 of 293 - accuracy= 96.446 - loss: 0.46736 processing batch 204 of 293 - accuracy= 96.463 - loss: 0.46691 processing batch 205 of 293 - accuracy= 96.481 - loss: 0.46646 processing batch 206 of 293 - accuracy= 96.498 - loss: 0.46638 processing batch 207 of 293 - accuracy= 96.514 - loss: 0.46593 processing batch 208 of 293 - accuracy= 96.531 - loss: 0.46565 processing batch 209 of 293 - accuracy= 96.548 - loss: 0.46540 processing batch 210 of 293 - accuracy= 96.564 - loss: 0.46487 processing batch 211 of 293 - accuracy= 96.521 - loss: 0.46578 processing batch 212 of 293 - accuracy= 96.538 - loss: 0.46525 processing batch 213 of 293 - accuracy= 96.554 - loss: 0.46504 processing batch 214 of 293 - accuracy= 96.512 - loss: 0.46525 processing batch 215 of 293 - accuracy= 96.528 - loss: 0.46489 processing batch 216 of 293 - accuracy= 96.544 - loss: 0.46435 processing batch 217 of 293 - accuracy= 96.560 - loss: 0.46492 processing batch 218 of 293 - accuracy= 96.575 - loss: 0.46454 processing batch 219 of 293 - accuracy= 96.534 - loss: 0.46611 processing batch 220 of 293 - accuracy= 96.493 - loss: 0.46632 processing batch 221 of 293 - accuracy= 96.509 - loss: 0.46625 processing batch 222 of 293 - accuracy= 96.525 - loss: 0.46606 processing batch 223 of 293 - accuracy= 96.540 - loss: 0.46560 processing batch 224 of 293 - accuracy= 96.556 - loss: 0.46544 processing batch 225 of 293 - accuracy= 96.515 - loss: 0.46539 processing batch 226 of 293 - accuracy= 96.476 - loss: 0.46574 processing batch 227 of 293 - accuracy= 96.491 - loss: 0.46520 processing batch 228 of 293 - accuracy= 96.507 - loss: 0.46510 processing batch 229 of 293 - accuracy= 96.522 - loss: 0.46499 processing batch 230 of 293 - accuracy= 96.537 - loss: 0.46465 processing batch 231 of 293 - accuracy= 96.552 - loss: 0.46420 processing batch 232 of 293 - accuracy= 96.567 - loss: 0.46366 processing batch 233 of 293 - accuracy= 96.528 - loss: 0.46462 processing batch 234 of 293 - accuracy= 96.543 - loss: 0.46404 processing batch 235 of 293 - accuracy= 96.557 - loss: 0.46408 processing batch 236 of 293 - accuracy= 96.519 - loss: 0.46432 processing batch 237 of 293 - accuracy= 96.534 - loss: 0.46438 processing batch 238 of 293 - accuracy= 96.548 - loss: 0.46444 processing batch 239 of 293 - accuracy= 96.562 - loss: 0.46395 processing batch 240 of 293 - accuracy= 96.577 - loss: 0.46353 processing batch 241 of 293 - accuracy= 96.591 - loss: 0.46302 processing batch 242 of 293 - accuracy= 96.605 - loss: 0.46258 processing batch 243 of 293 - accuracy= 96.619 - loss: 0.46218 processing batch 244 of 293 - accuracy= 96.633 - loss: 0.46179 processing batch 245 of 293 - accuracy= 96.596 - loss: 0.46249 processing batch 246 of 293 - accuracy= 96.609 - loss: 0.46216 processing batch 247 of 293 - accuracy= 96.573 - loss: 0.46303 processing batch 248 of 293 - accuracy= 96.536 - loss: 0.46336 processing batch 249 of 293 - accuracy= 96.500 - loss: 0.46426 processing batch 250 of 293 - accuracy= 96.514 - loss: 0.46419 processing batch 251 of 293 - accuracy= 96.528 - loss: 0.46392 processing batch 252 of 293 - accuracy= 96.542 - loss: 0.46344 processing batch 253 of 293 - accuracy= 96.555 - loss: 0.46312 processing batch 254 of 293 - accuracy= 96.569 - loss: 0.46274 processing batch 255 of 293 - accuracy= 96.582 - loss: 0.46231 processing batch 256 of 293 - accuracy= 96.595 - loss: 0.46198 processing batch 257 of 293 - accuracy= 96.609 - loss: 0.46153 processing batch 258 of 293 - accuracy= 96.622 - loss: 0.46105 processing batch 259 of 293 - accuracy= 96.635 - loss: 0.46076 processing batch 260 of 293 - accuracy= 96.648 - loss: 0.46040 processing batch 261 of 293 - accuracy= 96.660 - loss: 0.45996 processing batch 262 of 293 - accuracy= 96.673 - loss: 0.45945 processing batch 263 of 293 - accuracy= 96.686 - loss: 0.45911 processing batch 264 of 293 - accuracy= 96.698 - loss: 0.45880 processing batch 265 of 293 - accuracy= 96.664 - loss: 0.45917 processing batch 266 of 293 - accuracy= 96.629 - loss: 0.45949 processing batch 267 of 293 - accuracy= 96.642 - loss: 0.45908 processing batch 268 of 293 - accuracy= 96.654 - loss: 0.45873 processing batch 269 of 293 - accuracy= 96.620 - loss: 0.46111 processing batch 270 of 293 - accuracy= 96.633 - loss: 0.46086 processing batch 271 of 293 - accuracy= 96.645 - loss: 0.46043 processing batch 272 of 293 - accuracy= 96.658 - loss: 0.46010 processing batch 273 of 293 - accuracy= 96.624 - loss: 0.46072 processing batch 274 of 293 - accuracy= 96.636 - loss: 0.46028 processing batch 275 of 293 - accuracy= 96.649 - loss: 0.45977 processing batch 276 of 293 - accuracy= 96.661 - loss: 0.46009 processing batch 277 of 293 - accuracy= 96.673 - loss: 0.45970 processing batch 278 of 293 - accuracy= 96.685 - loss: 0.45955 processing batch 279 of 293 - accuracy= 96.696 - loss: 0.45926 processing batch 280 of 293 - accuracy= 96.664 - loss: 0.45978 processing batch 281 of 293 - accuracy= 96.631 - loss: 0.46001 processing batch 282 of 293 - accuracy= 96.643 - loss: 0.45993 processing batch 283 of 293 - accuracy= 96.655 - loss: 0.45952 processing batch 284 of 293 - accuracy= 96.667 - loss: 0.45928 processing batch 285 of 293 - accuracy= 96.635 - loss: 0.45984 processing batch 286 of 293 - accuracy= 96.646 - loss: 0.45964 processing batch 287 of 293 - accuracy= 96.658 - loss: 0.45978 processing batch 288 of 293 - accuracy= 96.670 - loss: 0.45955 processing batch 289 of 293 - accuracy= 96.638 - loss: 0.45975 processing batch 290 of 293 - accuracy= 96.607 - loss: 0.46035 processing batch 291 of 293 - accuracy= 96.618 - loss: 0.46011 processing batch 292 of 293 - accuracy= 96.630 - loss: 0.4600313 /40 0.460 96.630 1.58290 57.778 0.00050 0.00025 val_loss -79.84 82.62 \n293/293 [==============================] - 83s 282ms/step - loss: 0.4600 - accuracy: 0.9663 - val_loss: 1.5829 - val_accuracy: 0.5778\nEpoch 14/40\n293/293 [==============================] - ETA: 0s - loss: 0.4088 - accuracy: 0.9744 763 processing batch 1 of 293 - accuracy= 93.750 - loss: 0.46114 processing batch 2 of 293 - accuracy= 95.833 - loss: 0.42454 processing batch 3 of 293 - accuracy= 93.750 - loss: 0.48873 processing batch 4 of 293 - accuracy= 92.500 - loss: 0.48940 processing batch 5 of 293 - accuracy= 91.667 - loss: 0.50625 processing batch 6 of 293 - accuracy= 92.857 - loss: 0.50332 processing batch 7 of 293 - accuracy= 93.750 - loss: 0.49548 processing batch 8 of 293 - accuracy= 94.444 - loss: 0.47971 processing batch 9 of 293 - accuracy= 95.000 - loss: 0.46868 processing batch 10 of 293 - accuracy= 95.455 - loss: 0.47022 processing batch 11 of 293 - accuracy= 94.792 - loss: 0.46872 processing batch 12 of 293 - accuracy= 95.192 - loss: 0.46514 processing batch 13 of 293 - accuracy= 95.536 - loss: 0.46069 processing batch 14 of 293 - accuracy= 95.833 - loss: 0.45450 processing batch 15 of 293 - accuracy= 96.094 - loss: 0.45128 processing batch 16 of 293 - accuracy= 96.324 - loss: 0.44512 processing batch 17 of 293 - accuracy= 96.528 - loss: 0.44201 processing batch 18 of 293 - accuracy= 96.711 - loss: 0.44018 processing batch 19 of 293 - accuracy= 96.875 - loss: 0.43784 processing batch 20 of 293 - accuracy= 96.429 - loss: 0.44181 processing batch 21 of 293 - accuracy= 96.591 - loss: 0.44084 processing batch 22 of 293 - accuracy= 96.739 - loss: 0.44161 processing batch 23 of 293 - accuracy= 96.875 - loss: 0.43851 processing batch 24 of 293 - accuracy= 97.000 - loss: 0.43779 processing batch 25 of 293 - accuracy= 97.115 - loss: 0.43346 processing batch 26 of 293 - accuracy= 97.222 - loss: 0.43018 processing batch 27 of 293 - accuracy= 97.321 - loss: 0.42852 processing batch 28 of 293 - accuracy= 96.983 - loss: 0.43542 processing batch 29 of 293 - accuracy= 97.083 - loss: 0.43129 processing batch 30 of 293 - accuracy= 97.177 - loss: 0.43091 processing batch 31 of 293 - accuracy= 97.266 - loss: 0.43094 processing batch 32 of 293 - accuracy= 97.348 - loss: 0.43029 processing batch 33 of 293 - accuracy= 96.691 - loss: 0.44843 processing batch 34 of 293 - accuracy= 96.786 - loss: 0.44611 processing batch 35 of 293 - accuracy= 96.875 - loss: 0.44397 processing batch 36 of 293 - accuracy= 96.622 - loss: 0.44849 processing batch 37 of 293 - accuracy= 96.711 - loss: 0.44582 processing batch 38 of 293 - accuracy= 96.795 - loss: 0.44319 processing batch 39 of 293 - accuracy= 96.875 - loss: 0.44389 processing batch 40 of 293 - accuracy= 96.951 - loss: 0.44131 processing batch 41 of 293 - accuracy= 97.024 - loss: 0.44057 processing batch 42 of 293 - accuracy= 97.093 - loss: 0.43952 processing batch 43 of 293 - accuracy= 97.159 - loss: 0.43751 processing batch 44 of 293 - accuracy= 97.222 - loss: 0.43549 processing batch 45 of 293 - accuracy= 97.011 - loss: 0.44356 processing batch 46 of 293 - accuracy= 97.074 - loss: 0.44259 processing batch 47 of 293 - accuracy= 97.135 - loss: 0.44044 processing batch 48 of 293 - accuracy= 96.939 - loss: 0.44418 processing batch 49 of 293 - accuracy= 96.750 - loss: 0.44650 processing batch 50 of 293 - accuracy= 96.814 - loss: 0.44493 processing batch 51 of 293 - accuracy= 96.875 - loss: 0.44293 processing batch 52 of 293 - accuracy= 96.934 - loss: 0.44066 processing batch 53 of 293 - accuracy= 96.991 - loss: 0.43934 processing batch 54 of 293 - accuracy= 96.818 - loss: 0.44174 processing batch 55 of 293 - accuracy= 96.875 - loss: 0.44141 processing batch 56 of 293 - accuracy= 96.930 - loss: 0.44409 processing batch 57 of 293 - accuracy= 96.983 - loss: 0.44185 processing batch 58 of 293 - accuracy= 97.034 - loss: 0.44239 processing batch 59 of 293 - accuracy= 97.083 - loss: 0.44061 processing batch 60 of 293 - accuracy= 97.131 - loss: 0.43913 processing batch 61 of 293 - accuracy= 97.177 - loss: 0.43724 processing batch 62 of 293 - accuracy= 97.222 - loss: 0.43512 processing batch 63 of 293 - accuracy= 97.070 - loss: 0.44003 processing batch 64 of 293 - accuracy= 97.115 - loss: 0.43899 processing batch 65 of 293 - accuracy= 97.159 - loss: 0.43770 processing batch 66 of 293 - accuracy= 97.201 - loss: 0.43625 processing batch 67 of 293 - accuracy= 97.243 - loss: 0.43634 processing batch 68 of 293 - accuracy= 97.283 - loss: 0.43591 processing batch 69 of 293 - accuracy= 97.143 - loss: 0.43757 processing batch 70 of 293 - accuracy= 97.183 - loss: 0.43830 processing batch 71 of 293 - accuracy= 97.222 - loss: 0.43752 processing batch 72 of 293 - accuracy= 97.260 - loss: 0.43646 processing batch 73 of 293 - accuracy= 97.297 - loss: 0.43563 processing batch 74 of 293 - accuracy= 97.167 - loss: 0.43683 processing batch 75 of 293 - accuracy= 97.204 - loss: 0.43589 processing batch 76 of 293 - accuracy= 97.078 - loss: 0.43636 processing batch 77 of 293 - accuracy= 97.115 - loss: 0.43551 processing batch 78 of 293 - accuracy= 97.152 - loss: 0.43445 processing batch 79 of 293 - accuracy= 97.188 - loss: 0.43386 processing batch 80 of 293 - accuracy= 97.068 - loss: 0.43405 processing batch 81 of 293 - accuracy= 97.104 - loss: 0.43289 processing batch 82 of 293 - accuracy= 97.139 - loss: 0.43259 processing batch 83 of 293 - accuracy= 97.173 - loss: 0.43270 processing batch 84 of 293 - accuracy= 97.206 - loss: 0.43168 processing batch 85 of 293 - accuracy= 97.238 - loss: 0.43178 processing batch 86 of 293 - accuracy= 97.270 - loss: 0.43038 processing batch 87 of 293 - accuracy= 97.301 - loss: 0.42941 processing batch 88 of 293 - accuracy= 97.331 - loss: 0.42877 processing batch 89 of 293 - accuracy= 97.361 - loss: 0.42836 processing batch 90 of 293 - accuracy= 97.390 - loss: 0.42726 processing batch 91 of 293 - accuracy= 97.283 - loss: 0.42859 processing batch 92 of 293 - accuracy= 97.312 - loss: 0.42765 processing batch 93 of 293 - accuracy= 97.207 - loss: 0.42882 processing batch 94 of 293 - accuracy= 97.237 - loss: 0.42836 processing batch 95 of 293 - accuracy= 97.266 - loss: 0.42721 processing batch 96 of 293 - accuracy= 97.165 - loss: 0.43062 processing batch 97 of 293 - accuracy= 97.194 - loss: 0.42963 processing batch 98 of 293 - accuracy= 97.096 - loss: 0.43077 processing batch 99 of 293 - accuracy= 97.125 - loss: 0.42982 processing batch 100 of 293 - accuracy= 97.153 - loss: 0.42925 processing batch 101 of 293 - accuracy= 97.181 - loss: 0.42921 processing batch 102 of 293 - accuracy= 97.209 - loss: 0.42997 processing batch 103 of 293 - accuracy= 97.115 - loss: 0.42971 processing batch 104 of 293 - accuracy= 97.143 - loss: 0.42896 processing batch 105 of 293 - accuracy= 97.170 - loss: 0.42823 processing batch 106 of 293 - accuracy= 97.196 - loss: 0.42794 processing batch 107 of 293 - accuracy= 97.222 - loss: 0.42720 processing batch 108 of 293 - accuracy= 97.248 - loss: 0.42708 processing batch 109 of 293 - accuracy= 97.273 - loss: 0.42633 processing batch 110 of 293 - accuracy= 97.185 - loss: 0.42620 processing batch 111 of 293 - accuracy= 97.098 - loss: 0.42693 processing batch 112 of 293 - accuracy= 97.124 - loss: 0.42599 processing batch 113 of 293 - accuracy= 97.149 - loss: 0.42548 processing batch 114 of 293 - accuracy= 97.174 - loss: 0.42442 processing batch 115 of 293 - accuracy= 97.198 - loss: 0.42396 processing batch 116 of 293 - accuracy= 97.222 - loss: 0.42304 processing batch 117 of 293 - accuracy= 97.246 - loss: 0.42289 processing batch 118 of 293 - accuracy= 97.269 - loss: 0.42206 processing batch 119 of 293 - accuracy= 97.292 - loss: 0.42142 processing batch 120 of 293 - accuracy= 97.314 - loss: 0.42090 processing batch 121 of 293 - accuracy= 97.336 - loss: 0.42052 processing batch 122 of 293 - accuracy= 97.256 - loss: 0.42161 processing batch 123 of 293 - accuracy= 97.278 - loss: 0.42112 processing batch 124 of 293 - accuracy= 97.300 - loss: 0.42041 processing batch 125 of 293 - accuracy= 97.321 - loss: 0.41980 processing batch 126 of 293 - accuracy= 97.343 - loss: 0.41913 processing batch 127 of 293 - accuracy= 97.363 - loss: 0.41843 processing batch 128 of 293 - accuracy= 97.384 - loss: 0.41760 processing batch 129 of 293 - accuracy= 97.404 - loss: 0.41749 processing batch 130 of 293 - accuracy= 97.328 - loss: 0.41786 processing batch 131 of 293 - accuracy= 97.348 - loss: 0.41762 processing batch 132 of 293 - accuracy= 97.368 - loss: 0.41715 processing batch 133 of 293 - accuracy= 97.388 - loss: 0.41657 processing batch 134 of 293 - accuracy= 97.407 - loss: 0.41630 processing batch 135 of 293 - accuracy= 97.426 - loss: 0.41560 processing batch 136 of 293 - accuracy= 97.445 - loss: 0.41551 processing batch 137 of 293 - accuracy= 97.464 - loss: 0.41573 processing batch 138 of 293 - accuracy= 97.482 - loss: 0.41530 processing batch 139 of 293 - accuracy= 97.411 - loss: 0.41630 processing batch 140 of 293 - accuracy= 97.340 - loss: 0.41659 processing batch 141 of 293 - accuracy= 97.271 - loss: 0.41695 processing batch 142 of 293 - accuracy= 97.290 - loss: 0.41652 processing batch 143 of 293 - accuracy= 97.222 - loss: 0.41683 processing batch 144 of 293 - accuracy= 97.241 - loss: 0.41678 processing batch 145 of 293 - accuracy= 97.175 - loss: 0.41754 processing batch 146 of 293 - accuracy= 97.024 - loss: 0.42018 processing batch 147 of 293 - accuracy= 97.044 - loss: 0.41983 processing batch 148 of 293 - accuracy= 97.064 - loss: 0.41923 processing batch 149 of 293 - accuracy= 97.083 - loss: 0.41889 processing batch 150 of 293 - accuracy= 97.103 - loss: 0.41927 processing batch 151 of 293 - accuracy= 97.039 - loss: 0.42065 processing batch 152 of 293 - accuracy= 96.977 - loss: 0.42199 processing batch 153 of 293 - accuracy= 96.916 - loss: 0.42263 processing batch 154 of 293 - accuracy= 96.935 - loss: 0.42217 processing batch 155 of 293 - accuracy= 96.875 - loss: 0.42454 processing batch 156 of 293 - accuracy= 96.895 - loss: 0.42465 processing batch 157 of 293 - accuracy= 96.915 - loss: 0.42463 processing batch 158 of 293 - accuracy= 96.934 - loss: 0.42461 processing batch 159 of 293 - accuracy= 96.953 - loss: 0.42401 processing batch 160 of 293 - accuracy= 96.972 - loss: 0.42378 processing batch 161 of 293 - accuracy= 96.991 - loss: 0.42384 processing batch 162 of 293 - accuracy= 97.009 - loss: 0.42366 processing batch 163 of 293 - accuracy= 97.027 - loss: 0.42303 processing batch 164 of 293 - accuracy= 97.045 - loss: 0.42227 processing batch 165 of 293 - accuracy= 96.988 - loss: 0.42260 processing batch 166 of 293 - accuracy= 97.006 - loss: 0.42235 processing batch 167 of 293 - accuracy= 97.024 - loss: 0.42186 processing batch 168 of 293 - accuracy= 97.041 - loss: 0.42148 processing batch 169 of 293 - accuracy= 97.059 - loss: 0.42110 processing batch 170 of 293 - accuracy= 97.076 - loss: 0.42075 processing batch 171 of 293 - accuracy= 97.093 - loss: 0.42029 processing batch 172 of 293 - accuracy= 97.110 - loss: 0.41964 processing batch 173 of 293 - accuracy= 97.126 - loss: 0.41914 processing batch 174 of 293 - accuracy= 97.143 - loss: 0.41894 processing batch 175 of 293 - accuracy= 97.159 - loss: 0.41864 processing batch 176 of 293 - accuracy= 97.175 - loss: 0.41800 processing batch 177 of 293 - accuracy= 97.191 - loss: 0.41755 processing batch 178 of 293 - accuracy= 97.207 - loss: 0.41758 processing batch 179 of 293 - accuracy= 97.153 - loss: 0.41942 processing batch 180 of 293 - accuracy= 97.169 - loss: 0.41917 processing batch 181 of 293 - accuracy= 97.184 - loss: 0.41878 processing batch 182 of 293 - accuracy= 97.199 - loss: 0.41872 processing batch 183 of 293 - accuracy= 97.215 - loss: 0.41836 processing batch 184 of 293 - accuracy= 97.230 - loss: 0.41791 processing batch 185 of 293 - accuracy= 97.245 - loss: 0.41777 processing batch 186 of 293 - accuracy= 97.126 - loss: 0.42047 processing batch 187 of 293 - accuracy= 97.141 - loss: 0.42008 processing batch 188 of 293 - accuracy= 97.156 - loss: 0.41989 processing batch 189 of 293 - accuracy= 97.171 - loss: 0.41922 processing batch 190 of 293 - accuracy= 97.186 - loss: 0.41888 processing batch 191 of 293 - accuracy= 97.201 - loss: 0.41857 processing batch 192 of 293 - accuracy= 97.215 - loss: 0.41838 processing batch 193 of 293 - accuracy= 97.229 - loss: 0.41806 processing batch 194 of 293 - accuracy= 97.179 - loss: 0.41931 processing batch 195 of 293 - accuracy= 97.194 - loss: 0.41892 processing batch 196 of 293 - accuracy= 97.208 - loss: 0.41823 processing batch 197 of 293 - accuracy= 97.222 - loss: 0.41795 processing batch 198 of 293 - accuracy= 97.236 - loss: 0.41766 processing batch 199 of 293 - accuracy= 97.250 - loss: 0.41736 processing batch 200 of 293 - accuracy= 97.264 - loss: 0.41696 processing batch 201 of 293 - accuracy= 97.277 - loss: 0.41658 processing batch 202 of 293 - accuracy= 97.291 - loss: 0.41673 processing batch 203 of 293 - accuracy= 97.304 - loss: 0.41624 processing batch 204 of 293 - accuracy= 97.256 - loss: 0.41718 processing batch 205 of 293 - accuracy= 97.269 - loss: 0.41819 processing batch 206 of 293 - accuracy= 97.283 - loss: 0.41776 processing batch 207 of 293 - accuracy= 97.296 - loss: 0.41781 processing batch 208 of 293 - accuracy= 97.309 - loss: 0.41775 processing batch 209 of 293 - accuracy= 97.321 - loss: 0.41775 processing batch 210 of 293 - accuracy= 97.334 - loss: 0.41725 processing batch 211 of 293 - accuracy= 97.347 - loss: 0.41666 processing batch 212 of 293 - accuracy= 97.359 - loss: 0.41645 processing batch 213 of 293 - accuracy= 97.313 - loss: 0.41674 processing batch 214 of 293 - accuracy= 97.326 - loss: 0.41649 processing batch 215 of 293 - accuracy= 97.338 - loss: 0.41628 processing batch 216 of 293 - accuracy= 97.350 - loss: 0.41603 processing batch 217 of 293 - accuracy= 97.362 - loss: 0.41583 processing batch 218 of 293 - accuracy= 97.374 - loss: 0.41570 processing batch 219 of 293 - accuracy= 97.386 - loss: 0.41578 processing batch 220 of 293 - accuracy= 97.342 - loss: 0.41595 processing batch 221 of 293 - accuracy= 97.297 - loss: 0.41642 processing batch 222 of 293 - accuracy= 97.309 - loss: 0.41612 processing batch 223 of 293 - accuracy= 97.321 - loss: 0.41587 processing batch 224 of 293 - accuracy= 97.333 - loss: 0.41544 processing batch 225 of 293 - accuracy= 97.290 - loss: 0.41594 processing batch 226 of 293 - accuracy= 97.247 - loss: 0.41661 processing batch 227 of 293 - accuracy= 97.259 - loss: 0.41619 processing batch 228 of 293 - accuracy= 97.271 - loss: 0.41618 processing batch 229 of 293 - accuracy= 97.283 - loss: 0.41562 processing batch 230 of 293 - accuracy= 97.294 - loss: 0.41526 processing batch 231 of 293 - accuracy= 97.306 - loss: 0.41500 processing batch 232 of 293 - accuracy= 97.264 - loss: 0.41526 processing batch 233 of 293 - accuracy= 97.276 - loss: 0.41482 processing batch 234 of 293 - accuracy= 97.287 - loss: 0.41447 processing batch 235 of 293 - accuracy= 97.246 - loss: 0.41471 processing batch 236 of 293 - accuracy= 97.257 - loss: 0.41439 processing batch 237 of 293 - accuracy= 97.269 - loss: 0.41397 processing batch 238 of 293 - accuracy= 97.280 - loss: 0.41366 processing batch 239 of 293 - accuracy= 97.292 - loss: 0.41391 processing batch 240 of 293 - accuracy= 97.303 - loss: 0.41356 processing batch 241 of 293 - accuracy= 97.314 - loss: 0.41317 processing batch 242 of 293 - accuracy= 97.325 - loss: 0.41266 processing batch 243 of 293 - accuracy= 97.234 - loss: 0.41413 processing batch 244 of 293 - accuracy= 97.245 - loss: 0.41412 processing batch 245 of 293 - accuracy= 97.256 - loss: 0.41367 processing batch 246 of 293 - accuracy= 97.267 - loss: 0.41325 processing batch 247 of 293 - accuracy= 97.278 - loss: 0.41318 processing batch 248 of 293 - accuracy= 97.289 - loss: 0.41311 processing batch 249 of 293 - accuracy= 97.300 - loss: 0.41285 processing batch 250 of 293 - accuracy= 97.311 - loss: 0.41266 processing batch 251 of 293 - accuracy= 97.321 - loss: 0.41225 processing batch 252 of 293 - accuracy= 97.332 - loss: 0.41218 processing batch 253 of 293 - accuracy= 97.343 - loss: 0.41179 processing batch 254 of 293 - accuracy= 97.353 - loss: 0.41170 processing batch 255 of 293 - accuracy= 97.363 - loss: 0.41159 processing batch 256 of 293 - accuracy= 97.325 - loss: 0.41178 processing batch 257 of 293 - accuracy= 97.335 - loss: 0.41162 processing batch 258 of 293 - accuracy= 97.346 - loss: 0.41125 processing batch 259 of 293 - accuracy= 97.356 - loss: 0.41098 processing batch 260 of 293 - accuracy= 97.366 - loss: 0.41057 processing batch 261 of 293 - accuracy= 97.376 - loss: 0.41047 processing batch 262 of 293 - accuracy= 97.338 - loss: 0.41142 processing batch 263 of 293 - accuracy= 97.348 - loss: 0.41112 processing batch 264 of 293 - accuracy= 97.358 - loss: 0.41096 processing batch 265 of 293 - accuracy= 97.368 - loss: 0.41056 processing batch 266 of 293 - accuracy= 97.331 - loss: 0.41102 processing batch 267 of 293 - accuracy= 97.341 - loss: 0.41071 processing batch 268 of 293 - accuracy= 97.351 - loss: 0.41042 processing batch 269 of 293 - accuracy= 97.361 - loss: 0.41014 processing batch 270 of 293 - accuracy= 97.371 - loss: 0.41000 processing batch 271 of 293 - accuracy= 97.381 - loss: 0.40986 processing batch 272 of 293 - accuracy= 97.390 - loss: 0.41001 processing batch 273 of 293 - accuracy= 97.400 - loss: 0.41002 processing batch 274 of 293 - accuracy= 97.409 - loss: 0.40992 processing batch 275 of 293 - accuracy= 97.418 - loss: 0.40969 processing batch 276 of 293 - accuracy= 97.428 - loss: 0.40924 processing batch 277 of 293 - accuracy= 97.437 - loss: 0.40911 processing batch 278 of 293 - accuracy= 97.446 - loss: 0.40879 processing batch 279 of 293 - accuracy= 97.455 - loss: 0.40857 processing batch 280 of 293 - accuracy= 97.464 - loss: 0.40844 processing batch 281 of 293 - accuracy= 97.429 - loss: 0.40872 processing batch 282 of 293 - accuracy= 97.438 - loss: 0.40870 processing batch 283 of 293 - accuracy= 97.447 - loss: 0.40835 processing batch 284 of 293 - accuracy= 97.456 - loss: 0.40849 processing batch 285 of 293 - accuracy= 97.465 - loss: 0.40845 processing batch 286 of 293 - accuracy= 97.474 - loss: 0.40847 processing batch 287 of 293 - accuracy= 97.483 - loss: 0.40819 processing batch 288 of 293 - accuracy= 97.491 - loss: 0.40789 processing batch 289 of 293 - accuracy= 97.500 - loss: 0.40769 processing batch 290 of 293 - accuracy= 97.509 - loss: 0.40749 processing batch 291 of 293 - accuracy= 97.474 - loss: 0.40839 processing batch 292 of 293 - accuracy= 97.440 - loss: 0.4087514 /40 0.409 97.440 0.89696 80.342 0.00025 0.00013 val_loss -1.91 82.40 \n293/293 [==============================] - 82s 281ms/step - loss: 0.4088 - accuracy: 0.9744 - val_loss: 0.8970 - val_accuracy: 0.8034\nEpoch 15/40\n293/293 [==============================] - ETA: 0s - loss: 0.3706 - accuracy: 0.9872 2751 processing batch 1 of 293 - accuracy= 100.000 - loss: 0.33117 processing batch 2 of 293 - accuracy= 100.000 - loss: 0.33435 processing batch 3 of 293 - accuracy= 100.000 - loss: 0.33269 processing batch 4 of 293 - accuracy= 100.000 - loss: 0.34308 processing batch 5 of 293 - accuracy= 100.000 - loss: 0.33925 processing batch 6 of 293 - accuracy= 100.000 - loss: 0.34356 processing batch 7 of 293 - accuracy= 100.000 - loss: 0.34184 processing batch 8 of 293 - accuracy= 100.000 - loss: 0.35135 processing batch 9 of 293 - accuracy= 100.000 - loss: 0.35844 processing batch 10 of 293 - accuracy= 100.000 - loss: 0.35379 processing batch 11 of 293 - accuracy= 98.958 - loss: 0.37200 processing batch 12 of 293 - accuracy= 99.038 - loss: 0.37532 processing batch 13 of 293 - accuracy= 98.214 - loss: 0.37726 processing batch 14 of 293 - accuracy= 97.500 - loss: 0.37997 processing batch 15 of 293 - accuracy= 97.656 - loss: 0.37879 processing batch 16 of 293 - accuracy= 97.794 - loss: 0.37733 processing batch 17 of 293 - accuracy= 97.917 - loss: 0.37977 processing batch 18 of 293 - accuracy= 97.368 - loss: 0.39101 processing batch 19 of 293 - accuracy= 97.500 - loss: 0.39361 processing batch 20 of 293 - accuracy= 97.619 - loss: 0.39014 processing batch 21 of 293 - accuracy= 97.727 - loss: 0.38739 processing batch 22 of 293 - accuracy= 97.826 - loss: 0.38399 processing batch 23 of 293 - accuracy= 97.917 - loss: 0.38353 processing batch 24 of 293 - accuracy= 98.000 - loss: 0.38234 processing batch 25 of 293 - accuracy= 98.077 - loss: 0.38115 processing batch 26 of 293 - accuracy= 98.148 - loss: 0.37894 processing batch 27 of 293 - accuracy= 98.214 - loss: 0.38100 processing batch 28 of 293 - accuracy= 98.276 - loss: 0.37964 processing batch 29 of 293 - accuracy= 98.333 - loss: 0.37868 processing batch 30 of 293 - accuracy= 97.984 - loss: 0.38335 processing batch 31 of 293 - accuracy= 98.047 - loss: 0.38286 processing batch 32 of 293 - accuracy= 98.106 - loss: 0.38242 processing batch 33 of 293 - accuracy= 98.162 - loss: 0.38152 processing batch 34 of 293 - accuracy= 98.214 - loss: 0.37962 processing batch 35 of 293 - accuracy= 98.264 - loss: 0.37917 processing batch 36 of 293 - accuracy= 98.311 - loss: 0.37768 processing batch 37 of 293 - accuracy= 98.355 - loss: 0.37778 processing batch 38 of 293 - accuracy= 98.077 - loss: 0.39390 processing batch 39 of 293 - accuracy= 98.125 - loss: 0.39293 processing batch 40 of 293 - accuracy= 98.171 - loss: 0.39164 processing batch 41 of 293 - accuracy= 98.214 - loss: 0.38980 processing batch 42 of 293 - accuracy= 98.256 - loss: 0.38819 processing batch 43 of 293 - accuracy= 98.011 - loss: 0.39078 processing batch 44 of 293 - accuracy= 98.056 - loss: 0.39002 processing batch 45 of 293 - accuracy= 98.098 - loss: 0.38909 processing batch 46 of 293 - accuracy= 98.138 - loss: 0.38803 processing batch 47 of 293 - accuracy= 98.177 - loss: 0.38997 processing batch 48 of 293 - accuracy= 98.214 - loss: 0.39071 processing batch 49 of 293 - accuracy= 98.250 - loss: 0.38916 processing batch 50 of 293 - accuracy= 98.284 - loss: 0.38831 processing batch 51 of 293 - accuracy= 98.317 - loss: 0.38764 processing batch 52 of 293 - accuracy= 98.349 - loss: 0.38659 processing batch 53 of 293 - accuracy= 98.148 - loss: 0.39138 processing batch 54 of 293 - accuracy= 98.182 - loss: 0.39165 processing batch 55 of 293 - accuracy= 98.214 - loss: 0.39045 processing batch 56 of 293 - accuracy= 98.246 - loss: 0.39250 processing batch 57 of 293 - accuracy= 98.276 - loss: 0.39205 processing batch 58 of 293 - accuracy= 98.305 - loss: 0.39152 processing batch 59 of 293 - accuracy= 98.333 - loss: 0.39094 processing batch 60 of 293 - accuracy= 98.156 - loss: 0.39806 processing batch 61 of 293 - accuracy= 98.185 - loss: 0.39781 processing batch 62 of 293 - accuracy= 98.214 - loss: 0.40169 processing batch 63 of 293 - accuracy= 98.242 - loss: 0.40037 processing batch 64 of 293 - accuracy= 98.269 - loss: 0.39936 processing batch 65 of 293 - accuracy= 98.295 - loss: 0.39869 processing batch 66 of 293 - accuracy= 98.321 - loss: 0.39776 processing batch 67 of 293 - accuracy= 98.346 - loss: 0.39672 processing batch 68 of 293 - accuracy= 98.188 - loss: 0.39840 processing batch 69 of 293 - accuracy= 98.214 - loss: 0.39773 processing batch 70 of 293 - accuracy= 98.239 - loss: 0.39678 processing batch 71 of 293 - accuracy= 98.264 - loss: 0.39544 processing batch 72 of 293 - accuracy= 98.116 - loss: 0.39679 processing batch 73 of 293 - accuracy= 98.142 - loss: 0.39670 processing batch 74 of 293 - accuracy= 98.167 - loss: 0.39625 processing batch 75 of 293 - accuracy= 98.191 - loss: 0.39495 processing batch 76 of 293 - accuracy= 98.214 - loss: 0.39428 processing batch 77 of 293 - accuracy= 98.237 - loss: 0.39399 processing batch 78 of 293 - accuracy= 98.259 - loss: 0.39397 processing batch 79 of 293 - accuracy= 98.281 - loss: 0.39299 processing batch 80 of 293 - accuracy= 98.302 - loss: 0.39194 processing batch 81 of 293 - accuracy= 98.323 - loss: 0.39179 processing batch 82 of 293 - accuracy= 98.343 - loss: 0.39108 processing batch 83 of 293 - accuracy= 98.363 - loss: 0.39006 processing batch 84 of 293 - accuracy= 98.382 - loss: 0.38900 processing batch 85 of 293 - accuracy= 98.401 - loss: 0.38865 processing batch 86 of 293 - accuracy= 98.420 - loss: 0.38776 processing batch 87 of 293 - accuracy= 98.438 - loss: 0.38859 processing batch 88 of 293 - accuracy= 98.455 - loss: 0.38840 processing batch 89 of 293 - accuracy= 98.472 - loss: 0.38760 processing batch 90 of 293 - accuracy= 98.489 - loss: 0.38661 processing batch 91 of 293 - accuracy= 98.505 - loss: 0.38603 processing batch 92 of 293 - accuracy= 98.522 - loss: 0.38550 processing batch 93 of 293 - accuracy= 98.537 - loss: 0.38475 processing batch 94 of 293 - accuracy= 98.553 - loss: 0.38415 processing batch 95 of 293 - accuracy= 98.438 - loss: 0.38438 processing batch 96 of 293 - accuracy= 98.454 - loss: 0.38372 processing batch 97 of 293 - accuracy= 98.469 - loss: 0.38322 processing batch 98 of 293 - accuracy= 98.359 - loss: 0.38574 processing batch 99 of 293 - accuracy= 98.375 - loss: 0.38651 processing batch 100 of 293 - accuracy= 98.391 - loss: 0.38541 processing batch 101 of 293 - accuracy= 98.407 - loss: 0.38548 processing batch 102 of 293 - accuracy= 98.422 - loss: 0.38490 processing batch 103 of 293 - accuracy= 98.438 - loss: 0.38531 processing batch 104 of 293 - accuracy= 98.452 - loss: 0.38563 processing batch 105 of 293 - accuracy= 98.467 - loss: 0.38486 processing batch 106 of 293 - accuracy= 98.481 - loss: 0.38430 processing batch 107 of 293 - accuracy= 98.495 - loss: 0.38355 processing batch 108 of 293 - accuracy= 98.509 - loss: 0.38312 processing batch 109 of 293 - accuracy= 98.523 - loss: 0.38328 processing batch 110 of 293 - accuracy= 98.423 - loss: 0.38416 processing batch 111 of 293 - accuracy= 98.438 - loss: 0.38336 processing batch 112 of 293 - accuracy= 98.451 - loss: 0.38286 processing batch 113 of 293 - accuracy= 98.465 - loss: 0.38234 processing batch 114 of 293 - accuracy= 98.478 - loss: 0.38181 processing batch 115 of 293 - accuracy= 98.491 - loss: 0.38155 processing batch 116 of 293 - accuracy= 98.504 - loss: 0.38100 processing batch 117 of 293 - accuracy= 98.517 - loss: 0.38054 processing batch 118 of 293 - accuracy= 98.529 - loss: 0.37990 processing batch 119 of 293 - accuracy= 98.542 - loss: 0.37919 processing batch 120 of 293 - accuracy= 98.554 - loss: 0.37847 processing batch 121 of 293 - accuracy= 98.566 - loss: 0.37799 processing batch 122 of 293 - accuracy= 98.577 - loss: 0.37863 processing batch 123 of 293 - accuracy= 98.589 - loss: 0.37822 processing batch 124 of 293 - accuracy= 98.600 - loss: 0.37862 processing batch 125 of 293 - accuracy= 98.611 - loss: 0.37836 processing batch 126 of 293 - accuracy= 98.622 - loss: 0.37845 processing batch 127 of 293 - accuracy= 98.633 - loss: 0.37813 processing batch 128 of 293 - accuracy= 98.643 - loss: 0.37772 processing batch 129 of 293 - accuracy= 98.654 - loss: 0.37749 processing batch 130 of 293 - accuracy= 98.664 - loss: 0.37709 processing batch 131 of 293 - accuracy= 98.674 - loss: 0.37680 processing batch 132 of 293 - accuracy= 98.684 - loss: 0.37607 processing batch 133 of 293 - accuracy= 98.694 - loss: 0.37652 processing batch 134 of 293 - accuracy= 98.704 - loss: 0.37629 processing batch 135 of 293 - accuracy= 98.713 - loss: 0.37611 processing batch 136 of 293 - accuracy= 98.723 - loss: 0.37559 processing batch 137 of 293 - accuracy= 98.732 - loss: 0.37516 processing batch 138 of 293 - accuracy= 98.741 - loss: 0.37517 processing batch 139 of 293 - accuracy= 98.661 - loss: 0.37625 processing batch 140 of 293 - accuracy= 98.670 - loss: 0.37584 processing batch 141 of 293 - accuracy= 98.680 - loss: 0.37530 processing batch 142 of 293 - accuracy= 98.689 - loss: 0.37493 processing batch 143 of 293 - accuracy= 98.698 - loss: 0.37474 processing batch 144 of 293 - accuracy= 98.707 - loss: 0.37464 processing batch 145 of 293 - accuracy= 98.716 - loss: 0.37432 processing batch 146 of 293 - accuracy= 98.724 - loss: 0.37427 processing batch 147 of 293 - accuracy= 98.733 - loss: 0.37390 processing batch 148 of 293 - accuracy= 98.742 - loss: 0.37363 processing batch 149 of 293 - accuracy= 98.750 - loss: 0.37416 processing batch 150 of 293 - accuracy= 98.675 - loss: 0.37526 processing batch 151 of 293 - accuracy= 98.602 - loss: 0.37538 processing batch 152 of 293 - accuracy= 98.611 - loss: 0.37504 processing batch 153 of 293 - accuracy= 98.539 - loss: 0.37651 processing batch 154 of 293 - accuracy= 98.548 - loss: 0.37616 processing batch 155 of 293 - accuracy= 98.558 - loss: 0.37594 processing batch 156 of 293 - accuracy= 98.567 - loss: 0.37524 processing batch 157 of 293 - accuracy= 98.576 - loss: 0.37524 processing batch 158 of 293 - accuracy= 98.585 - loss: 0.37553 processing batch 159 of 293 - accuracy= 98.594 - loss: 0.37525 processing batch 160 of 293 - accuracy= 98.602 - loss: 0.37509 processing batch 161 of 293 - accuracy= 98.611 - loss: 0.37496 processing batch 162 of 293 - accuracy= 98.620 - loss: 0.37435 processing batch 163 of 293 - accuracy= 98.628 - loss: 0.37428 processing batch 164 of 293 - accuracy= 98.636 - loss: 0.37369 processing batch 165 of 293 - accuracy= 98.645 - loss: 0.37346 processing batch 166 of 293 - accuracy= 98.653 - loss: 0.37352 processing batch 167 of 293 - accuracy= 98.661 - loss: 0.37313 processing batch 168 of 293 - accuracy= 98.669 - loss: 0.37287 processing batch 169 of 293 - accuracy= 98.676 - loss: 0.37233 processing batch 170 of 293 - accuracy= 98.684 - loss: 0.37205 processing batch 171 of 293 - accuracy= 98.692 - loss: 0.37166 processing batch 172 of 293 - accuracy= 98.699 - loss: 0.37145 processing batch 173 of 293 - accuracy= 98.563 - loss: 0.37220 processing batch 174 of 293 - accuracy= 98.571 - loss: 0.37238 processing batch 175 of 293 - accuracy= 98.580 - loss: 0.37257 processing batch 176 of 293 - accuracy= 98.588 - loss: 0.37228 processing batch 177 of 293 - accuracy= 98.596 - loss: 0.37199 processing batch 178 of 293 - accuracy= 98.603 - loss: 0.37187 processing batch 179 of 293 - accuracy= 98.611 - loss: 0.37189 processing batch 180 of 293 - accuracy= 98.550 - loss: 0.37351 processing batch 181 of 293 - accuracy= 98.558 - loss: 0.37367 processing batch 182 of 293 - accuracy= 98.566 - loss: 0.37347 processing batch 183 of 293 - accuracy= 98.573 - loss: 0.37355 processing batch 184 of 293 - accuracy= 98.581 - loss: 0.37352 processing batch 185 of 293 - accuracy= 98.589 - loss: 0.37315 processing batch 186 of 293 - accuracy= 98.596 - loss: 0.37300 processing batch 187 of 293 - accuracy= 98.604 - loss: 0.37250 processing batch 188 of 293 - accuracy= 98.611 - loss: 0.37237 processing batch 189 of 293 - accuracy= 98.618 - loss: 0.37222 processing batch 190 of 293 - accuracy= 98.626 - loss: 0.37189 processing batch 191 of 293 - accuracy= 98.633 - loss: 0.37162 processing batch 192 of 293 - accuracy= 98.640 - loss: 0.37174 processing batch 193 of 293 - accuracy= 98.647 - loss: 0.37220 processing batch 194 of 293 - accuracy= 98.654 - loss: 0.37252 processing batch 195 of 293 - accuracy= 98.661 - loss: 0.37234 processing batch 196 of 293 - accuracy= 98.668 - loss: 0.37209 processing batch 197 of 293 - accuracy= 98.674 - loss: 0.37185 processing batch 198 of 293 - accuracy= 98.681 - loss: 0.37188 processing batch 199 of 293 - accuracy= 98.625 - loss: 0.37314 processing batch 200 of 293 - accuracy= 98.632 - loss: 0.37290 processing batch 201 of 293 - accuracy= 98.639 - loss: 0.37268 processing batch 202 of 293 - accuracy= 98.645 - loss: 0.37221 processing batch 203 of 293 - accuracy= 98.652 - loss: 0.37193 processing batch 204 of 293 - accuracy= 98.659 - loss: 0.37161 processing batch 205 of 293 - accuracy= 98.604 - loss: 0.37246 processing batch 206 of 293 - accuracy= 98.611 - loss: 0.37219 processing batch 207 of 293 - accuracy= 98.618 - loss: 0.37217 processing batch 208 of 293 - accuracy= 98.624 - loss: 0.37194 processing batch 209 of 293 - accuracy= 98.631 - loss: 0.37168 processing batch 210 of 293 - accuracy= 98.637 - loss: 0.37139 processing batch 211 of 293 - accuracy= 98.644 - loss: 0.37122 processing batch 212 of 293 - accuracy= 98.650 - loss: 0.37099 processing batch 213 of 293 - accuracy= 98.657 - loss: 0.37081 processing batch 214 of 293 - accuracy= 98.663 - loss: 0.37053 processing batch 215 of 293 - accuracy= 98.669 - loss: 0.37023 processing batch 216 of 293 - accuracy= 98.675 - loss: 0.37001 processing batch 217 of 293 - accuracy= 98.681 - loss: 0.36965 processing batch 218 of 293 - accuracy= 98.630 - loss: 0.37013 processing batch 219 of 293 - accuracy= 98.636 - loss: 0.36988 processing batch 220 of 293 - accuracy= 98.586 - loss: 0.37072 processing batch 221 of 293 - accuracy= 98.592 - loss: 0.37044 processing batch 222 of 293 - accuracy= 98.599 - loss: 0.37027 processing batch 223 of 293 - accuracy= 98.605 - loss: 0.37015 processing batch 224 of 293 - accuracy= 98.611 - loss: 0.37010 processing batch 225 of 293 - accuracy= 98.617 - loss: 0.36992 processing batch 226 of 293 - accuracy= 98.623 - loss: 0.36977 processing batch 227 of 293 - accuracy= 98.629 - loss: 0.36961 processing batch 228 of 293 - accuracy= 98.635 - loss: 0.36964 processing batch 229 of 293 - accuracy= 98.533 - loss: 0.37235 processing batch 230 of 293 - accuracy= 98.539 - loss: 0.37218 processing batch 231 of 293 - accuracy= 98.545 - loss: 0.37187 processing batch 232 of 293 - accuracy= 98.551 - loss: 0.37153 processing batch 233 of 293 - accuracy= 98.558 - loss: 0.37135 processing batch 234 of 293 - accuracy= 98.564 - loss: 0.37126 processing batch 235 of 293 - accuracy= 98.570 - loss: 0.37096 processing batch 236 of 293 - accuracy= 98.576 - loss: 0.37103 processing batch 237 of 293 - accuracy= 98.582 - loss: 0.37101 processing batch 238 of 293 - accuracy= 98.588 - loss: 0.37095 processing batch 239 of 293 - accuracy= 98.594 - loss: 0.37057 processing batch 240 of 293 - accuracy= 98.600 - loss: 0.37083 processing batch 241 of 293 - accuracy= 98.605 - loss: 0.37102 processing batch 242 of 293 - accuracy= 98.611 - loss: 0.37091 processing batch 243 of 293 - accuracy= 98.617 - loss: 0.37127 processing batch 244 of 293 - accuracy= 98.571 - loss: 0.37220 processing batch 245 of 293 - accuracy= 98.577 - loss: 0.37201 processing batch 246 of 293 - accuracy= 98.583 - loss: 0.37180 processing batch 247 of 293 - accuracy= 98.589 - loss: 0.37177 processing batch 248 of 293 - accuracy= 98.594 - loss: 0.37154 processing batch 249 of 293 - accuracy= 98.600 - loss: 0.37148 processing batch 250 of 293 - accuracy= 98.606 - loss: 0.37139 processing batch 251 of 293 - accuracy= 98.611 - loss: 0.37116 processing batch 252 of 293 - accuracy= 98.617 - loss: 0.37111 processing batch 253 of 293 - accuracy= 98.622 - loss: 0.37128 processing batch 254 of 293 - accuracy= 98.627 - loss: 0.37146 processing batch 255 of 293 - accuracy= 98.633 - loss: 0.37169 processing batch 256 of 293 - accuracy= 98.638 - loss: 0.37182 processing batch 257 of 293 - accuracy= 98.643 - loss: 0.37243 processing batch 258 of 293 - accuracy= 98.649 - loss: 0.37225 processing batch 259 of 293 - accuracy= 98.654 - loss: 0.37208 processing batch 260 of 293 - accuracy= 98.659 - loss: 0.37190 processing batch 261 of 293 - accuracy= 98.664 - loss: 0.37170 processing batch 262 of 293 - accuracy= 98.669 - loss: 0.37157 processing batch 263 of 293 - accuracy= 98.674 - loss: 0.37131 processing batch 264 of 293 - accuracy= 98.679 - loss: 0.37112 processing batch 265 of 293 - accuracy= 98.684 - loss: 0.37101 processing batch 266 of 293 - accuracy= 98.689 - loss: 0.37084 processing batch 267 of 293 - accuracy= 98.694 - loss: 0.37088 processing batch 268 of 293 - accuracy= 98.699 - loss: 0.37090 processing batch 269 of 293 - accuracy= 98.704 - loss: 0.37061 processing batch 270 of 293 - accuracy= 98.662 - loss: 0.37107 processing batch 271 of 293 - accuracy= 98.667 - loss: 0.37128 processing batch 272 of 293 - accuracy= 98.672 - loss: 0.37104 processing batch 273 of 293 - accuracy= 98.677 - loss: 0.37126 processing batch 274 of 293 - accuracy= 98.682 - loss: 0.37114 processing batch 275 of 293 - accuracy= 98.687 - loss: 0.37092 processing batch 276 of 293 - accuracy= 98.691 - loss: 0.37074 processing batch 277 of 293 - accuracy= 98.696 - loss: 0.37053 processing batch 278 of 293 - accuracy= 98.701 - loss: 0.37025 processing batch 279 of 293 - accuracy= 98.705 - loss: 0.37003 processing batch 280 of 293 - accuracy= 98.710 - loss: 0.36996 processing batch 281 of 293 - accuracy= 98.715 - loss: 0.36972 processing batch 282 of 293 - accuracy= 98.719 - loss: 0.36990 processing batch 283 of 293 - accuracy= 98.724 - loss: 0.37002 processing batch 284 of 293 - accuracy= 98.684 - loss: 0.37119 processing batch 285 of 293 - accuracy= 98.689 - loss: 0.37095 processing batch 286 of 293 - accuracy= 98.693 - loss: 0.37119 processing batch 287 of 293 - accuracy= 98.698 - loss: 0.37139 processing batch 288 of 293 - accuracy= 98.702 - loss: 0.37134 processing batch 289 of 293 - accuracy= 98.707 - loss: 0.37117 processing batch 290 of 293 - accuracy= 98.711 - loss: 0.37091 processing batch 291 of 293 - accuracy= 98.716 - loss: 0.37084 processing batch 292 of 293 - accuracy= 98.720 - loss: 0.3706215 /40 0.371 98.720 0.89820 81.709 0.00013 0.00006 val_loss -2.05 82.33 \n training has been halted at epoch 15 after 3 adjustments of learning rate with no improvement\n293/293 [==============================] - 82s 281ms/step - loss: 0.3706 - accuracy: 0.9872 - val_loss: 0.8982 - val_accuracy: 0.8171\ntraining elapsed time was 0.0 hours, 21.0 minutes, 53.11 seconds)\n","output_type":"stream"}]},{"cell_type":"code","source":"complete_datagen = ImageDataGenerator(rescale=1./255)\ncomplete_generator = complete_datagen.flow_from_dataframe(dataframe=df_train_train,\n directory = \"./train_images_resized_preprocessed/\",\n x_col=\"file_name\",\n target_size=(HEIGHT, WIDTH),\n batch_size=1,\n shuffle=False,\n class_mode=None)\n\nSTEP_SIZE_COMPLETE = complete_generator.n//complete_generator.batch_size\ntrain_preds = model.predict_generator(complete_generator, steps=STEP_SIZE_COMPLETE,verbose = 1)\ntrain_preds = [np.argmax(pred) for pred in train_preds]","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:25:47.425883Z","iopub.execute_input":"2023-12-15T19:25:47.426238Z","iopub.status.idle":"2023-12-15T19:26:31.782375Z","shell.execute_reply.started":"2023-12-15T19:25:47.426208Z","shell.execute_reply":"2023-12-15T19:26:31.781502Z"},"trusted":true},"execution_count":37,"outputs":[{"name":"stdout","text":"Found 2929 validated image filenames.\n","output_type":"stream"},{"name":"stderr","text":"/tmp/ipykernel_42/1199064684.py:11: UserWarning: `Model.predict_generator` is deprecated and will be removed in a future version. Please use `Model.predict`, which supports generators.\n train_preds = model.predict_generator(complete_generator, steps=STEP_SIZE_COMPLETE,verbose = 1)\n","output_type":"stream"},{"name":"stdout","text":"2929/2929 [==============================] - 43s 14ms/step\n","output_type":"stream"}]},{"cell_type":"code","source":"print(\"Train Cohen Kappa score: %.3f\" % cohen_kappa_score(train_preds, df_train_train['diagnosis'].astype('int'), weights='quadratic'))\nprint(\"Train Accuracy score : %.3f\" % accuracy_score(df_train_train['diagnosis'].astype('int'),train_preds))","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:26:31.784028Z","iopub.execute_input":"2023-12-15T19:26:31.784515Z","iopub.status.idle":"2023-12-15T19:26:31.799539Z","shell.execute_reply.started":"2023-12-15T19:26:31.784467Z","shell.execute_reply":"2023-12-15T19:26:31.79872Z"},"trusted":true},"execution_count":38,"outputs":[{"name":"stdout","text":"Train Cohen Kappa score: 0.941\nTrain Accuracy score : 0.913\n","output_type":"stream"}]},{"cell_type":"code","source":"test_generator.reset()\nSTEP_SIZE_TEST = test_generator.n//test_generator.batch_size\ntest_preds = model.predict_generator(test_generator, steps=STEP_SIZE_TEST,verbose = 1)\ntest_labels = [np.argmax(pred) for pred in test_preds]","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:26:31.800722Z","iopub.execute_input":"2023-12-15T19:26:31.801029Z","iopub.status.idle":"2023-12-15T19:26:42.460188Z","shell.execute_reply.started":"2023-12-15T19:26:31.801002Z","shell.execute_reply":"2023-12-15T19:26:42.459325Z"},"trusted":true},"execution_count":39,"outputs":[{"name":"stdout","text":" 4/733 [..............................] - ETA: 13s","output_type":"stream"},{"name":"stderr","text":"/tmp/ipykernel_42/2753895509.py:3: UserWarning: `Model.predict_generator` is deprecated and will be removed in a future version. Please use `Model.predict`, which supports generators.\n test_preds = model.predict_generator(test_generator, steps=STEP_SIZE_TEST,verbose = 1)\n","output_type":"stream"},{"name":"stdout","text":"733/733 [==============================] - 10s 14ms/step\n","output_type":"stream"}]},{"cell_type":"code","source":"def plot_conf_matrix(true,pred,classes):\n cf = confusion_matrix(true, pred)\n\n df_cm = pd.DataFrame(cf, range(len(classes)), range(len(classes)))\n plt.figure(figsize=(8,5.5))\n sns.set(font_scale=1.4)\n sns.heatmap(df_cm, annot=True, annot_kws={\"size\": 16},xticklabels = classes ,yticklabels = classes,fmt='g')\n #sns.heatmap(df_cm, annot=True, annot_kws={\"size\": 16})\n plt.show()","metadata":{"execution":{"iopub.status.busy":"2023-12-17T18:39:57.566056Z","iopub.execute_input":"2023-12-17T18:39:57.566383Z","iopub.status.idle":"2023-12-17T18:39:57.572727Z","shell.execute_reply.started":"2023-12-17T18:39:57.566357Z","shell.execute_reply":"2023-12-17T18:39:57.571808Z"},"trusted":true},"execution_count":4,"outputs":[]},{"cell_type":"code","source":"print(\"Test Cohen Kappa score: %.3f\" % cohen_kappa_score(test_labels, df_train_test['diagnosis'].astype('int'), weights='quadratic'))\n","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:26:42.472317Z","iopub.execute_input":"2023-12-15T19:26:42.472627Z","iopub.status.idle":"2023-12-15T19:26:42.484477Z","shell.execute_reply.started":"2023-12-15T19:26:42.472591Z","shell.execute_reply":"2023-12-15T19:26:42.483437Z"},"trusted":true},"execution_count":41,"outputs":[{"name":"stdout","text":"Test Cohen Kappa score: 0.847\n","output_type":"stream"}]},{"cell_type":"code","source":"model.save('vgg16.h5')","metadata":{"execution":{"iopub.status.busy":"2023-12-15T19:26:42.48572Z","iopub.execute_input":"2023-12-15T19:26:42.486014Z","iopub.status.idle":"2023-12-15T19:26:43.654835Z","shell.execute_reply.started":"2023-12-15T19:26:42.48599Z","shell.execute_reply":"2023-12-15T19:26:43.65399Z"},"trusted":true},"execution_count":42,"outputs":[{"name":"stderr","text":"/opt/conda/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n saving_api.save_model(\n","output_type":"stream"}]},{"cell_type":"code","source":"","metadata":{},"execution_count":null,"outputs":[]}]}