{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Introduction to Prof-Weight"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This method uses white-box access to the layers of a pre-trained complex neural network model, a training dataset and a training algorithm for a simple model (presumably with much smaller number of parameters compared to the complex model like Decision Tree, Neural Nets with very few layers) and produces a new model in the simple model hypothesis class. \n",
    "\n",
    "The aim is to make sure that this new simple model (trained with the help of a complex model) has a higher accuracy on the training dataset than the output of the simple model training algorithm working **only** with the training dataset. \n",
    "\n",
    "The reasons why one would prefer a simple model is because of resource constraints or because of better interpretability offered by the simple model.\n",
    "\n",
    "The main idea is the following: For every sample (x,y) in the training dataset, we would like to produce a sample weight w(x,y) which indicates how easy/hard the example is to learn. w(x,y) is higher if the example is easier to learn for the complex model. Prof-Weight obtains these weights as follows:\n",
    "\n",
    " a) Take the complex model layer L (flattened layer output). Create dataset consisting L(x),y. \n",
    " \n",
    " b) Train a logistic classifier (we call it the probe classifier) that uses the representation L(x) and predicts y using a linear model. Let the probabilistic confidences of the probe classifier model trained only on Layer L representation be p(x,y,L).\n",
    " \n",
    " c) Repeat steps a and b for the top K layers in the complex model.\n",
    " \n",
    " d) Now take every point (x,y) in the training dataset available for the simple model to train. Let w(x,y)= (\\sum_{L} p(x,y,L))/ num of layers used. These are the new sample weights.\n",
    " \n",
    " e) Use the simple model training algorithm with w(x,y) as the sample weights.\n",
    " \n",
    " Intuition: Measure of hardness or easiness of the sample may not be indicated by the final layer confidences in a highly confident complex deep neural network model in a manner that is useful for training a much simpler model. So we track how easy is a sample to predict from lower level layers's representation. So the average of the probe classifier's predictions for top K layers being high means that that sample's prediction is confident from a much lower layer indicating easiness of the sample. For a hard example, only last few layer confidences will be higher. Earlier layer representations won't have enough distinguishability.\n",
    " \n",
    "We demonstrate this method where the complex model (an 18 layer Resnet) is trained on 30000 samples of the CIFAR-10 training dataset. The simple model is a Resnet with only one Resblock. The training dataset available is the rest of the 20000 samples in the standard CIFAR-10 dataset. The test dataset is the 10000 samples as in standard CIFAR-10 dataset.\n",
    "\n",
    "Demonstrations: a) We demonstrate how to attach probes to a specific layer on a complex model stored as a tensorflow checkpoint. b) How to evaulate the flattened layer output and then use it to train a logistic probe classifier to predict y. c) Use pre-stored probe classifiers' confidences for the top K layers (we dont show probe training on all the top K layers in the notebook. However, we do demonstrate probe classifier training on one of the layers) and form sample weights d) Train the simple model using these new sample weights using the Prof-Weight Explainer Class.\n",
    "\n",
    "Complex Model is trained on train1 (30000 samples), Simple Model is alwasy trained on train2 (20000) samples. Probe Classifiers are trained on layer representations of the complex model on train1 samples. However, probe confidences are evaluated on train2 (on which the simple model is also trained) to provide sample weights.\n",
    "\n",
    " \n",
    "References for this method:\n",
    "  1. Amit Dhurandhar, Karthikeyan Shanmugam, Ronny Luss, Peder Olsen. \"Improving Simple Models with Confidence Profiles\", NeurIPS 2018.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Evaluating a Given Layer of a Tensorflow Checkpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "import sys\n",
    "sys.path.append(\"../../\")\n",
    "from aix360.algorithms.profwt import train_probes\n",
    "from aix360.algorithms.profwt import attach_probe_checkpoint\n",
    "from aix360.datasets.cifar_dataset import CIFARDataset\n",
    "import json\n",
    "import numpy as np\n",
    "import tensorflow as tf\n",
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Obtain parent directory for acccessing various data files.\n",
    "parent_dir = '../../aix360/models/profwt'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define a path for the tensorflow checkpoint of a pre-trained complex model\n",
    "\n",
    "This complex Resnet model has been trained using the model definitions obtained from: https://github.com/tensorflow/models/tree/master/research/resnet"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "checkpoint_path = os.path.join(parent_dir, \"checkpoints/train_resnetmodel_new1_799.ckpt\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the Dataset on which Layer outputs need to be evaluated. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset_obj=CIFARDataset(\"../../aix360/data/cifar_data\")\n",
    "x_train1 =dataset_obj.load_file('cifar-10-train1-image.json')\n",
    "y_train1=dataset_obj.load_file('cifar-10-train1-label.json')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define a filename where you want layer output to be saved."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "../../aix360/models/profwt/data/probe_run1.npy\n"
     ]
    }
   ],
   "source": [
    "run=1\n",
    "os.mkdir(parent_dir+'/data')\n",
    "to_save_filename=parent_dir+'/data/probe_run'+str(run)+'.npy'\n",
    "print(to_save_filename)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Print Names of all Layers from the model in the checkpoint"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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'save/RestoreV2_259' type=RestoreV2>, <tf.Operation 'save/Assign_259' type=Assign>, <tf.Operation 'save/RestoreV2_260/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_260/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_260' type=RestoreV2>, <tf.Operation 'save/Assign_260' type=Assign>, <tf.Operation 'save/RestoreV2_261/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_261/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_261' type=RestoreV2>, <tf.Operation 'save/Assign_261' type=Assign>, <tf.Operation 'save/RestoreV2_262/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_262/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_262' type=RestoreV2>, <tf.Operation 'save/Assign_262' type=Assign>, <tf.Operation 'save/RestoreV2_263/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_263/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_263' type=RestoreV2>, <tf.Operation 'save/Assign_263' type=Assign>, <tf.Operation 'save/RestoreV2_264/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_264/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_264' type=RestoreV2>, <tf.Operation 'save/Assign_264' type=Assign>, <tf.Operation 'save/RestoreV2_265/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_265/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_265' type=RestoreV2>, <tf.Operation 'save/Assign_265' type=Assign>, <tf.Operation 'save/RestoreV2_266/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_266/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_266' type=RestoreV2>, <tf.Operation 'save/Assign_266' type=Assign>, <tf.Operation 'save/RestoreV2_267/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_267/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_267' type=RestoreV2>, <tf.Operation 'save/Assign_267' type=Assign>, <tf.Operation 'save/RestoreV2_268/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_268/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_268' type=RestoreV2>, <tf.Operation 'save/Assign_268' type=Assign>, <tf.Operation 'save/RestoreV2_269/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_269/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_269' type=RestoreV2>, <tf.Operation 'save/Assign_269' type=Assign>, <tf.Operation 'save/RestoreV2_270/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_270/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_270' type=RestoreV2>, <tf.Operation 'save/Assign_270' type=Assign>, <tf.Operation 'save/RestoreV2_271/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_271/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_271' type=RestoreV2>, <tf.Operation 'save/Assign_271' type=Assign>, <tf.Operation 'save/RestoreV2_272/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_272/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_272' type=RestoreV2>, <tf.Operation 'save/Assign_272' type=Assign>, <tf.Operation 'save/RestoreV2_273/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_273/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_273' type=RestoreV2>, <tf.Operation 'save/Assign_273' type=Assign>, <tf.Operation 'save/RestoreV2_274/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_274/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_274' type=RestoreV2>, <tf.Operation 'save/Assign_274' type=Assign>, <tf.Operation 'save/RestoreV2_275/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_275/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_275' type=RestoreV2>, <tf.Operation 'save/Assign_275' type=Assign>, <tf.Operation 'save/RestoreV2_276/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_276/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_276' type=RestoreV2>, <tf.Operation 'save/Assign_276' type=Assign>, <tf.Operation 'save/RestoreV2_277/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_277/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_277' type=RestoreV2>, <tf.Operation 'save/Assign_277' type=Assign>, <tf.Operation 'save/RestoreV2_278/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_278/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_278' type=RestoreV2>, <tf.Operation 'save/Assign_278' type=Assign>, <tf.Operation 'save/RestoreV2_279/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_279/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_279' type=RestoreV2>, <tf.Operation 'save/Assign_279' type=Assign>, <tf.Operation 'save/RestoreV2_280/tensor_names' type=Const>, <tf.Operation 'save/RestoreV2_280/shape_and_slices' type=Const>, <tf.Operation 'save/RestoreV2_280' type=RestoreV2>, <tf.Operation 'save/Assign_280' type=Assign>, <tf.Operation 'save/restore_all' type=NoOp>, <tf.Operation 'init_1' type=NoOp>]\n"
     ]
    }
   ],
   "source": [
    "attach_probe_checkpoint.print_layer_labels(checkpoint_path)\n",
    "tf.reset_default_graph()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Identify tensor names corresponding to a) Layer whose output is of interest \n",
    "b) Input layer where the model takes in  image/data sample c) Layer where model takes in the labels to fit. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Fixing a specific operation_name to define the layer output\n",
    "operation_name='unit_1_1/sub_add/add:0'\n",
    "# In this case the probe is intended to be after the second Resnet Block in 18 layer Resnet for CIFAR-10\n",
    "\n",
    "input_features_name='Placeholder:0'\n",
    "label_name='Placeholder_1:0'\n",
    "#These two correspond to Placeholder tensors for Feature input and label"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tapping the Layer Output, Evaluating and Storing it in a File"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "attach_probe_eval() function loads a tensorflow checkpoint from a path, takes these inputs: a) Layer name whose output it needs to evaluate) Placeholder Tensor name corresponding to feature input x and c) Placeholder Tensor name corresponding to Label y  d) Data samples to evaulate the layer outputs on. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tensor(\"unit_1_1/sub_add/add:0\", shape=(?, 32, 32, 16), dtype=float32)\n",
      "Tensor(\"Reshape:0\", shape=(?, 16384), dtype=float32)\n",
      "INFO:tensorflow:Restoring parameters from ../../aix360/models/profwt/checkpoints/train_resnetmodel_new1_799.ckpt\n",
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      "probe shape (30000, 16384)\n"
     ]
    }
   ],
   "source": [
    "pr=attach_probe_checkpoint.attach_probe_eval(input_features_name,label_name,operation_name,x_train1,y_train1,checkpoint_path)\n",
    "np.save(to_save_filename,pr)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Training a Logistic Probe Classifier based on Layer Outputs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load the Layer Output File for which Probe Classifier needs to be trained."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "# In this script, samples for probe training and probe confidence evaluations are done \n",
    "# on the layer outputs obtained from the same dataset. Load the layer output values from the file.\n",
    "#In general, it can be made different by supplying a new y_train2 and probe_eval_input \n",
    "y_train2=y_train1\n",
    "probe_train_input=np.load(parent_dir+'/data/probe_run1.npy')\n",
    "probe_eval_input=probe_train_input"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Supply Filenames to save Probe Classifier Model, Model Confidences"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "run=1\n",
    "num_classes=10\n",
    "to_save_pred_filename=parent_dir+\"/data/probe_pred_run\"+str(run)+'.npy'\n",
    "to_save_probe_model_filename=parent_dir+\"/data/probe_model_run\"+str(run)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Train a Probe Classifier, Evaluate it on Layer Outputs from a Dataset,\n",
    "## Store the probe confidences in a File."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "WARNING:tensorflow:From ../../aix360/algorithms/profwt/train_probes.py:31: UniformUnitScaling.__init__ (from tensorflow.python.ops.init_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "Use tf.initializers.variance_scaling instead with distribution=uniform to get equivalent behavior.\n",
      "WARNING:tensorflow:From ../../aix360/algorithms/profwt/train_probes.py:70: softmax_cross_entropy_with_logits (from tensorflow.python.ops.nn_ops) is deprecated and will be removed in a future version.\n",
      "Instructions for updating:\n",
      "\n",
      "Future major versions of TensorFlow will allow gradients to flow\n",
      "into the labels input on backprop by default.\n",
      "\n",
      "See tf.nn.softmax_cross_entropy_with_logits_v2.\n",
      "\n",
      "Start Training Probe Model.....\n",
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      "Starting to Evaluate Probe Model Confidences and Saving in a File.....\n",
      "INFO:tensorflow:Restoring parameters from ../../aix360/models/profwt/data/probe_model_run1\n",
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      "(30000, 10)\n",
      "(30000, 10)\n",
      "Probe Confidences/Logits Saved...\n"
     ]
    }
   ],
   "source": [
    "(log,pred)=train_probes.probe_train_eval(probe_train_input,y_train1,num_classes,probe_eval_input,y_train2,to_save_probe_model_filename)\n",
    "np.save(to_save_pred_filename,pred)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simple Model Training - Unweighted on the Dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/Users/1j1060/tensorflow3/lib/python3.6/site-packages/h5py/__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`.\n",
      "  from ._conv import register_converters as _register_converters\n",
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "import keras\n",
    "from keras.layers import Dense, Conv2D, BatchNormalization, Activation\n",
    "from keras.layers import AveragePooling2D, Input, Flatten\n",
    "from keras.optimizers import Adam\n",
    "from keras.callbacks import ModelCheckpoint, LearningRateScheduler\n",
    "from keras.callbacks import ReduceLROnPlateau\n",
    "from keras.preprocessing.image import ImageDataGenerator\n",
    "from keras.regularizers import l2\n",
    "from keras import backend as K\n",
    "from keras.models import Model\n",
    "import os"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Import the ProfWeight Explainer Class."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "from aix360.algorithms.profwt.profwt import ProfweightExplainer\n",
    "from aix360.algorithms.profwt.resnet_keras_model import resnet_v1,lr_schedule,HParams"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Open the file constaining the training dataset for training the simple model. This file could be (In this example it is different) different from the dataset used for training the complex model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_train shape: (20000, 32, 32, 3)\n",
      "y_train shape: (20000, 10)\n"
     ]
    }
   ],
   "source": [
    "x_train2=dataset_obj.load_file('cifar-10-train2-image.json')\n",
    "y_train2=dataset_obj.load_file('cifar-10-train2-label.json')\n",
    "x_test=dataset_obj.load_file('cifar-10-test-image.json')\n",
    "y_test=dataset_obj.load_file('cifar-10-test-label.json')\n",
    "\n",
    "print('x_train shape:', x_train2.shape)\n",
    "print('y_train shape:', y_train2.shape)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Specify checkpoint to save the model after training the simple model on x_train2,y_train2 dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "save_dir = os.path.join(os.getcwd(), 'saved_models')\n",
    "model_name = 'resnet_target_model_unweighted.h5' \n",
    "if not os.path.isdir(save_dir):\n",
    "    os.makedirs(save_dir)\n",
    "filepath = os.path.join(save_dir, model_name)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Specify Learning Rate Schedule and all the hyper parameters for training. In this example, these are recommended setting from a popular Keras implementation of resnet models for CIFAR-10."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Learning rate:  0.001\n"
     ]
    }
   ],
   "source": [
    "lr_scheduler = LearningRateScheduler(lr_schedule)\n",
    "lr_reducer = ReduceLROnPlateau(factor=np.sqrt(0.1),cooldown=0,patience=5,min_lr=0.5e-6)\n",
    "hps = HParams(lr_scheduler=lr_scheduler,lr_reducer=lr_reducer,batch_size=128,epochs=200,checkpoint_path=filepath,num_classes=10,complexity_param=1,optimizer=Adam(lr=lr_schedule(0)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "ProfWeightExplainer Class has a fit function that trains a simple model using a provided keras model that is built by calling the resnet_v1 function specified in the model file resnet_keras_model.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_1 (InputLayer)            (None, 32, 32, 3)    0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_1 (Conv2D)               (None, 32, 32, 16)   448         input_1[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_1 (BatchNor (None, 32, 32, 16)   64          conv2d_1[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_1 (Activation)       (None, 32, 32, 16)   0           batch_normalization_1[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_2 (Conv2D)               (None, 32, 32, 16)   2320        activation_1[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_2 (BatchNor (None, 32, 32, 16)   64          conv2d_2[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_2 (Activation)       (None, 32, 32, 16)   0           batch_normalization_2[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_3 (Conv2D)               (None, 32, 32, 16)   2320        activation_2[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_3 (BatchNor (None, 32, 32, 16)   64          conv2d_3[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "add_1 (Add)                     (None, 32, 32, 16)   0           activation_1[0][0]               \n",
      "                                                                 batch_normalization_3[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_3 (Activation)       (None, 32, 32, 16)   0           add_1[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_4 (Conv2D)               (None, 16, 16, 32)   4640        activation_3[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_4 (BatchNor (None, 16, 16, 32)   128         conv2d_4[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_4 (Activation)       (None, 16, 16, 32)   0           batch_normalization_4[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_5 (Conv2D)               (None, 16, 16, 32)   9248        activation_4[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_6 (Conv2D)               (None, 16, 16, 32)   544         activation_3[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_5 (BatchNor (None, 16, 16, 32)   128         conv2d_5[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "add_2 (Add)                     (None, 16, 16, 32)   0           conv2d_6[0][0]                   \n",
      "                                                                 batch_normalization_5[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_5 (Activation)       (None, 16, 16, 32)   0           add_2[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_7 (Conv2D)               (None, 8, 8, 64)     18496       activation_5[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_6 (BatchNor (None, 8, 8, 64)     256         conv2d_7[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "activation_6 (Activation)       (None, 8, 8, 64)     0           batch_normalization_6[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_8 (Conv2D)               (None, 8, 8, 64)     36928       activation_6[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_9 (Conv2D)               (None, 8, 8, 64)     2112        activation_5[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_7 (BatchNor (None, 8, 8, 64)     256         conv2d_8[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "add_3 (Add)                     (None, 8, 8, 64)     0           conv2d_9[0][0]                   \n",
      "                                                                 batch_normalization_7[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "activation_7 (Activation)       (None, 8, 8, 64)     0           add_3[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_1 (AveragePoo (None, 1, 1, 64)     0           activation_7[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "flatten_1 (Flatten)             (None, 64)           0           average_pooling2d_1[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "dense_1 (Dense)                 (None, 10)           650         flatten_1[0][0]                  \n",
      "==================================================================================================\n",
      "Total params: 78,666\n",
      "Trainable params: 78,186\n",
      "Non-trainable params: 480\n",
      "__________________________________________________________________________________________________\n",
      "Train on 20000 samples, validate on 500 samples\n",
      "Learning rate:  0.001\n",
      "Epoch 1/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 1.7537 - acc: 0.3788\n",
      "Epoch 00001: val_acc improved from -inf to 0.19600, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_unweighted.h5\n",
      "20000/20000 [==============================] - 78s 4ms/step - loss: 1.7537 - acc: 0.3789 - val_loss: 2.7654 - val_acc: 0.1960\n",
      "Learning rate:  0.001\n",
      "Epoch 2/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 1.4443 - acc: 0.4983\n",
      "Epoch 00002: val_acc improved from 0.19600 to 0.37400, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_unweighted.h5\n",
      "20000/20000 [==============================] - 79s 4ms/step - loss: 1.4440 - acc: 0.4985 - val_loss: 1.7532 - val_acc: 0.3740\n",
      "Learning rate:  0.001\n",
      "Epoch 3/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 1.2890 - acc: 0.5572\n",
      "Epoch 00003: val_acc improved from 0.37400 to 0.50800, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_unweighted.h5\n",
      "20000/20000 [==============================] - 78s 4ms/step - loss: 1.2887 - acc: 0.5575 - val_loss: 1.3537 - val_acc: 0.5080\n",
      "Learning rate:  0.001\n",
      "Epoch 4/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 1.1897 - acc: 0.5937\n",
      "Epoch 00004: val_acc improved from 0.50800 to 0.57000, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_unweighted.h5\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 1.1895 - acc: 0.5938 - val_loss: 1.2342 - val_acc: 0.5700\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Learning rate:  0.001\n",
      "Epoch 5/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 1.1156 - acc: 0.6255\n",
      "Epoch 00005: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 1.1159 - acc: 0.6253 - val_loss: 1.2336 - val_acc: 0.5560\n",
      "Learning rate:  0.001\n",
      "Epoch 6/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 1.0482 - acc: 0.6499\n",
      "Epoch 00006: val_acc did not improve\n",
      "20000/20000 [==============================] - 78s 4ms/step - loss: 1.0483 - acc: 0.6499 - val_loss: 1.3257 - val_acc: 0.5380\n",
      "Learning rate:  0.001\n",
      "Epoch 7/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.9800 - acc: 0.6763\n",
      "Epoch 00007: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.9800 - acc: 0.6763 - val_loss: 1.4286 - val_acc: 0.5180\n",
      "Learning rate:  0.001\n",
      "Epoch 8/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.9250 - acc: 0.6953\n",
      "Epoch 00008: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.9251 - acc: 0.6953 - val_loss: 1.5477 - val_acc: 0.4940\n",
      "Learning rate:  0.001\n",
      "Epoch 9/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.8890 - acc: 0.7098\n",
      "Epoch 00009: val_acc improved from 0.57000 to 0.59000, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_unweighted.h5\n",
      "20000/20000 [==============================] - 93s 5ms/step - loss: 0.8891 - acc: 0.7099 - val_loss: 1.2582 - val_acc: 0.5900\n",
      "Learning rate:  0.001\n",
      "Epoch 10/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.8331 - acc: 0.7266\n",
      "Epoch 00010: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.8339 - acc: 0.7262 - val_loss: 1.3667 - val_acc: 0.5540\n",
      "Learning rate:  0.001\n",
      "Epoch 11/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.7970 - acc: 0.7408\n",
      "Epoch 00011: val_acc improved from 0.59000 to 0.61600, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_unweighted.h5\n",
      "20000/20000 [==============================] - 89s 4ms/step - loss: 0.7973 - acc: 0.7407 - val_loss: 1.1424 - val_acc: 0.6160\n",
      "Learning rate:  0.001\n",
      "Epoch 12/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.7522 - acc: 0.7549\n",
      "Epoch 00012: val_acc did not improve\n",
      "20000/20000 [==============================] - 92s 5ms/step - loss: 0.7526 - acc: 0.7548 - val_loss: 1.2989 - val_acc: 0.5720\n",
      "Learning rate:  0.001\n",
      "Epoch 13/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.7266 - acc: 0.7656\n",
      "Epoch 00013: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.7266 - acc: 0.7654 - val_loss: 1.3133 - val_acc: 0.5740\n",
      "Learning rate:  0.001\n",
      "Epoch 14/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.6790 - acc: 0.7840\n",
      "Epoch 00014: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.6790 - acc: 0.7839 - val_loss: 1.1774 - val_acc: 0.6020\n",
      "Learning rate:  0.001\n",
      "Epoch 15/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.6408 - acc: 0.7941\n",
      "Epoch 00015: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.6410 - acc: 0.7941 - val_loss: 1.6373 - val_acc: 0.4840\n",
      "Learning rate:  0.001\n",
      "Epoch 16/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.6084 - acc: 0.8099\n",
      "Epoch 00016: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.6082 - acc: 0.8100 - val_loss: 1.7080 - val_acc: 0.5360\n",
      "Learning rate:  0.001\n",
      "Epoch 17/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.5642 - acc: 0.8271\n",
      "Epoch 00017: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.5646 - acc: 0.8269 - val_loss: 1.2826 - val_acc: 0.5880\n",
      "Learning rate:  0.001\n",
      "Epoch 18/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.5350 - acc: 0.8375\n",
      "Epoch 00018: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.5351 - acc: 0.8374 - val_loss: 1.9862 - val_acc: 0.5160\n",
      "Learning rate:  0.001\n",
      "Epoch 19/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.4997 - acc: 0.8496\n",
      "Epoch 00019: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.4994 - acc: 0.8497 - val_loss: 1.8156 - val_acc: 0.5320\n",
      "Learning rate:  0.001\n",
      "Epoch 20/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.4797 - acc: 0.8594\n",
      "Epoch 00020: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.4797 - acc: 0.8594 - val_loss: 1.5741 - val_acc: 0.5660\n",
      "Learning rate:  0.001\n",
      "Epoch 21/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.4519 - acc: 0.8655\n",
      "Epoch 00021: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.4518 - acc: 0.8656 - val_loss: 2.7822 - val_acc: 0.4080\n",
      "Learning rate:  0.001\n",
      "Epoch 22/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.4252 - acc: 0.8798\n",
      "Epoch 00022: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.4252 - acc: 0.8798 - val_loss: 2.0501 - val_acc: 0.5220\n",
      "Learning rate:  0.001\n",
      "Epoch 23/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.3957 - acc: 0.8877\n",
      "Epoch 00023: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.3957 - acc: 0.8878 - val_loss: 1.8616 - val_acc: 0.5000\n",
      "Learning rate:  0.001\n",
      "Epoch 24/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.3740 - acc: 0.8965\n",
      "Epoch 00024: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.3744 - acc: 0.8964 - val_loss: 1.6495 - val_acc: 0.5780\n",
      "Learning rate:  0.001\n",
      "Epoch 25/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.3571 - acc: 0.9023\n",
      "Epoch 00025: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.3576 - acc: 0.9022 - val_loss: 1.8401 - val_acc: 0.5260\n",
      "Learning rate:  0.001\n",
      "Epoch 26/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.3336 - acc: 0.9100\n",
      "Epoch 00026: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.3342 - acc: 0.9097 - val_loss: 2.1686 - val_acc: 0.5180\n",
      "Learning rate:  0.001\n",
      "Epoch 27/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.3244 - acc: 0.9151\n",
      "Epoch 00027: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.3242 - acc: 0.9152 - val_loss: 1.9763 - val_acc: 0.5760\n",
      "Learning rate:  0.001\n",
      "Epoch 28/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2920 - acc: 0.9259\n",
      "Epoch 00028: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.2924 - acc: 0.9258 - val_loss: 2.8018 - val_acc: 0.4860\n",
      "Learning rate:  0.001\n",
      "Epoch 29/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2748 - acc: 0.9329\n",
      "Epoch 00029: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.2748 - acc: 0.9330 - val_loss: 1.8500 - val_acc: 0.5360\n",
      "Learning rate:  0.001\n",
      "Epoch 30/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2637 - acc: 0.9363\n",
      "Epoch 00030: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.2637 - acc: 0.9363 - val_loss: 1.7060 - val_acc: 0.5840\n",
      "Learning rate:  0.001\n",
      "Epoch 31/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2463 - acc: 0.9440\n",
      "Epoch 00031: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.2464 - acc: 0.9438 - val_loss: 1.8693 - val_acc: 0.5800\n",
      "Learning rate:  0.001\n",
      "Epoch 32/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2426 - acc: 0.9442\n",
      "Epoch 00032: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.2424 - acc: 0.9443 - val_loss: 1.9180 - val_acc: 0.5740\n",
      "Learning rate:  0.001\n",
      "Epoch 33/200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2293 - acc: 0.9496\n",
      "Epoch 00033: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.2294 - acc: 0.9496 - val_loss: 2.3893 - val_acc: 0.5100\n",
      "Learning rate:  0.001\n",
      "Epoch 34/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2318 - acc: 0.9478\n",
      "Epoch 00034: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.2319 - acc: 0.9478 - val_loss: 2.1293 - val_acc: 0.5540\n",
      "Learning rate:  0.001\n",
      "Epoch 35/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2225 - acc: 0.9510\n",
      "Epoch 00035: val_acc did not improve\n",
      "20000/20000 [==============================] - 98s 5ms/step - loss: 0.2235 - acc: 0.9507 - val_loss: 2.0747 - val_acc: 0.5560\n",
      "Learning rate:  0.001\n",
      "Epoch 36/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2295 - acc: 0.9485\n",
      "Epoch 00036: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.2296 - acc: 0.9484 - val_loss: 1.9203 - val_acc: 0.5820\n",
      "Learning rate:  0.001\n",
      "Epoch 37/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1914 - acc: 0.9645\n",
      "Epoch 00037: val_acc did not improve\n",
      "20000/20000 [==============================] - 93s 5ms/step - loss: 0.1916 - acc: 0.9645 - val_loss: 2.1618 - val_acc: 0.5700\n",
      "Learning rate:  0.001\n",
      "Epoch 38/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1979 - acc: 0.9586\n",
      "Epoch 00038: val_acc did not improve\n",
      "20000/20000 [==============================] - 98s 5ms/step - loss: 0.1978 - acc: 0.9587 - val_loss: 2.7718 - val_acc: 0.5240\n",
      "Learning rate:  0.001\n",
      "Epoch 39/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1896 - acc: 0.9627\n",
      "Epoch 00039: val_acc did not improve\n",
      "20000/20000 [==============================] - 89s 4ms/step - loss: 0.1896 - acc: 0.9627 - val_loss: 2.3221 - val_acc: 0.5620\n",
      "Learning rate:  0.001\n",
      "Epoch 40/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1977 - acc: 0.9584\n",
      "Epoch 00040: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.1977 - acc: 0.9583 - val_loss: 2.8365 - val_acc: 0.5180\n",
      "Learning rate:  0.001\n",
      "Epoch 41/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1861 - acc: 0.9636\n",
      "Epoch 00041: val_acc did not improve\n",
      "20000/20000 [==============================] - 99s 5ms/step - loss: 0.1864 - acc: 0.9634 - val_loss: 2.3616 - val_acc: 0.5620\n",
      "Learning rate:  0.001\n",
      "Epoch 42/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1911 - acc: 0.9603\n",
      "Epoch 00042: val_acc did not improve\n",
      "20000/20000 [==============================] - 89s 4ms/step - loss: 0.1911 - acc: 0.9603 - val_loss: 2.4828 - val_acc: 0.5220\n",
      "Learning rate:  0.001\n",
      "Epoch 43/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1840 - acc: 0.9633\n",
      "Epoch 00043: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 4ms/step - loss: 0.1849 - acc: 0.9630 - val_loss: 3.1005 - val_acc: 0.5040\n",
      "Learning rate:  0.001\n",
      "Epoch 44/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1935 - acc: 0.9606\n",
      "Epoch 00044: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.1936 - acc: 0.9605 - val_loss: 3.0432 - val_acc: 0.5220\n",
      "Learning rate:  0.001\n",
      "Epoch 45/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1810 - acc: 0.9648\n",
      "Epoch 00045: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.1810 - acc: 0.9647 - val_loss: 1.9895 - val_acc: 0.5780\n",
      "Learning rate:  0.001\n",
      "Epoch 46/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1550 - acc: 0.9742\n",
      "Epoch 00046: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.1551 - acc: 0.9741 - val_loss: 2.5270 - val_acc: 0.5460\n",
      "Learning rate:  0.001\n",
      "Epoch 47/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1533 - acc: 0.9772\n",
      "Epoch 00047: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.1535 - acc: 0.9770 - val_loss: 3.1516 - val_acc: 0.4940\n",
      "Learning rate:  0.001\n",
      "Epoch 48/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1610 - acc: 0.9728\n",
      "Epoch 00048: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.1610 - acc: 0.9728 - val_loss: 3.0021 - val_acc: 0.5100\n",
      "Learning rate:  0.001\n",
      "Epoch 49/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1375 - acc: 0.9811\n",
      "Epoch 00049: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.1375 - acc: 0.9810 - val_loss: 2.4277 - val_acc: 0.5660\n",
      "Learning rate:  0.001\n",
      "Epoch 50/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1541 - acc: 0.9740\n",
      "Epoch 00050: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.1542 - acc: 0.9739 - val_loss: 2.5801 - val_acc: 0.5660\n",
      "Learning rate:  0.001\n",
      "Epoch 51/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1927 - acc: 0.9586\n",
      "Epoch 00051: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.1927 - acc: 0.9586 - val_loss: 3.5708 - val_acc: 0.5020\n",
      "Learning rate:  0.001\n",
      "Epoch 52/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1670 - acc: 0.9703\n",
      "Epoch 00052: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.1671 - acc: 0.9701 - val_loss: 2.5823 - val_acc: 0.5500\n",
      "Learning rate:  0.001\n",
      "Epoch 53/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1715 - acc: 0.9656\n",
      "Epoch 00053: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.1713 - acc: 0.9657 - val_loss: 3.0892 - val_acc: 0.5240\n",
      "Learning rate:  0.001\n",
      "Epoch 54/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1691 - acc: 0.9690\n",
      "Epoch 00054: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.1691 - acc: 0.9689 - val_loss: 3.4058 - val_acc: 0.4600\n",
      "Learning rate:  0.001\n",
      "Epoch 55/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1751 - acc: 0.9654\n",
      "Epoch 00055: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 4ms/step - loss: 0.1760 - acc: 0.9651 - val_loss: 2.2525 - val_acc: 0.5820\n",
      "Learning rate:  0.001\n",
      "Epoch 56/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1994 - acc: 0.9570\n",
      "Epoch 00056: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 4ms/step - loss: 0.1992 - acc: 0.9570 - val_loss: 2.3523 - val_acc: 0.5820\n",
      "Learning rate:  0.001\n",
      "Epoch 57/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1409 - acc: 0.9797\n",
      "Epoch 00057: val_acc did not improve\n",
      "20000/20000 [==============================] - 89s 4ms/step - loss: 0.1411 - acc: 0.9797 - val_loss: 2.2169 - val_acc: 0.6040\n",
      "Learning rate:  0.001\n",
      "Epoch 58/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1257 - acc: 0.9863\n",
      "Epoch 00058: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 4ms/step - loss: 0.1258 - acc: 0.9863 - val_loss: 2.2568 - val_acc: 0.5820\n",
      "Learning rate:  0.001\n",
      "Epoch 59/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1108 - acc: 0.9925\n",
      "Epoch 00059: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 4ms/step - loss: 0.1108 - acc: 0.9926 - val_loss: 2.6571 - val_acc: 0.5600\n",
      "Learning rate:  0.001\n",
      "Epoch 60/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1090 - acc: 0.9919\n",
      "Epoch 00060: val_acc did not improve\n",
      "20000/20000 [==============================] - 89s 4ms/step - loss: 0.1091 - acc: 0.9919 - val_loss: 2.5297 - val_acc: 0.5540\n",
      "Learning rate:  0.001\n",
      "Epoch 61/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1234 - acc: 0.9851\n",
      "Epoch 00061: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.1234 - acc: 0.9851 - val_loss: 2.7876 - val_acc: 0.5600\n",
      "Learning rate:  0.001\n",
      "Epoch 62/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1862 - acc: 0.9607\n",
      "Epoch 00062: val_acc did not improve\n",
      "20000/20000 [==============================] - 92s 5ms/step - loss: 0.1861 - acc: 0.9607 - val_loss: 3.2215 - val_acc: 0.5500\n",
      "Learning rate:  0.001\n",
      "Epoch 63/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2270 - acc: 0.9443\n",
      "Epoch 00063: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.2272 - acc: 0.9442 - val_loss: 3.0210 - val_acc: 0.5680\n",
      "Learning rate:  0.001\n",
      "Epoch 64/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1723 - acc: 0.9677\n",
      "Epoch 00064: val_acc did not improve\n",
      "20000/20000 [==============================] - 97s 5ms/step - loss: 0.1725 - acc: 0.9676 - val_loss: 2.7429 - val_acc: 0.5700\n",
      "Learning rate:  0.001\n",
      "Epoch 65/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1528 - acc: 0.9743\n",
      "Epoch 00065: val_acc did not improve\n",
      "20000/20000 [==============================] - 103s 5ms/step - loss: 0.1528 - acc: 0.9743 - val_loss: 2.5961 - val_acc: 0.5600\n",
      "Learning rate:  0.001\n",
      "Epoch 66/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1234 - acc: 0.9873\n",
      "Epoch 00066: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.1234 - acc: 0.9873 - val_loss: 2.7328 - val_acc: 0.5500\n",
      "Learning rate:  0.001\n",
      "Epoch 67/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1089 - acc: 0.9926\n",
      "Epoch 00067: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.1089 - acc: 0.9926 - val_loss: 2.9422 - val_acc: 0.5380\n",
      "Learning rate:  0.001\n",
      "Epoch 68/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1028 - acc: 0.9938\n",
      "Epoch 00068: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.1029 - acc: 0.9937 - val_loss: 2.6488 - val_acc: 0.5720\n",
      "Learning rate:  0.001\n",
      "Epoch 69/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1310 - acc: 0.9832\n",
      "Epoch 00069: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 4ms/step - loss: 0.1318 - acc: 0.9829 - val_loss: 3.1946 - val_acc: 0.5280\n",
      "Learning rate:  0.001\n",
      "Epoch 70/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2078 - acc: 0.9527\n",
      "Epoch 00070: val_acc did not improve\n",
      "20000/20000 [==============================] - 94s 5ms/step - loss: 0.2078 - acc: 0.9528 - val_loss: 3.4378 - val_acc: 0.4840\n",
      "Learning rate:  0.001\n",
      "Epoch 71/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1849 - acc: 0.9635\n",
      "Epoch 00071: val_acc did not improve\n",
      "20000/20000 [==============================] - 89s 4ms/step - loss: 0.1850 - acc: 0.9634 - val_loss: 2.8612 - val_acc: 0.5340\n",
      "Learning rate:  0.001\n",
      "Epoch 72/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1604 - acc: 0.9710\n",
      "Epoch 00072: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.1606 - acc: 0.9709 - val_loss: 3.1511 - val_acc: 0.5300\n",
      "Learning rate:  0.001\n",
      "Epoch 73/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1516 - acc: 0.9759\n",
      "Epoch 00073: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.1518 - acc: 0.9759 - val_loss: 3.2399 - val_acc: 0.5400\n",
      "Learning rate:  0.001\n",
      "Epoch 74/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1296 - acc: 0.9845\n",
      "Epoch 00074: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.1297 - acc: 0.9845 - val_loss: 2.5100 - val_acc: 0.5960\n",
      "Learning rate:  0.001\n",
      "Epoch 75/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1159 - acc: 0.9899\n",
      "Epoch 00075: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.1160 - acc: 0.9899 - val_loss: 2.5246 - val_acc: 0.5820\n",
      "Learning rate:  0.001\n",
      "Epoch 76/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1098 - acc: 0.9916\n",
      "Epoch 00076: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.1099 - acc: 0.9915 - val_loss: 2.5748 - val_acc: 0.5700\n",
      "Learning rate:  0.001\n",
      "Epoch 77/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1372 - acc: 0.9813\n",
      "Epoch 00077: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.1373 - acc: 0.9813 - val_loss: 3.0990 - val_acc: 0.5480\n",
      "Learning rate:  0.001\n",
      "Epoch 78/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1553 - acc: 0.9718\n",
      "Epoch 00078: val_acc did not improve\n",
      "20000/20000 [==============================] - 89s 4ms/step - loss: 0.1552 - acc: 0.9718 - val_loss: 3.6318 - val_acc: 0.5080\n",
      "Learning rate:  0.001\n",
      "Epoch 79/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1658 - acc: 0.9688\n",
      "Epoch 00079: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.1660 - acc: 0.9687 - val_loss: 3.4663 - val_acc: 0.5200\n",
      "Learning rate:  0.001\n",
      "Epoch 80/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1556 - acc: 0.9742\n",
      "Epoch 00080: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.1558 - acc: 0.9741 - val_loss: 3.7072 - val_acc: 0.4900\n",
      "Learning rate:  0.001\n",
      "Epoch 81/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1420 - acc: 0.9788\n",
      "Epoch 00081: val_acc did not improve\n",
      "20000/20000 [==============================] - 89s 4ms/step - loss: 0.1420 - acc: 0.9788 - val_loss: 3.0134 - val_acc: 0.5460\n",
      "Learning rate:  0.0001\n",
      "Epoch 82/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0994 - acc: 0.9956\n",
      "Epoch 00082: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0994 - acc: 0.9956 - val_loss: 2.1839 - val_acc: 0.6140\n",
      "Learning rate:  0.0001\n",
      "Epoch 83/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0903 - acc: 0.9991\n",
      "Epoch 00083: val_acc did not improve\n",
      "20000/20000 [==============================] - 95s 5ms/step - loss: 0.0903 - acc: 0.9991 - val_loss: 2.1926 - val_acc: 0.6060\n",
      "Learning rate:  0.0001\n",
      "Epoch 84/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0879 - acc: 0.9994\n",
      "Epoch 00084: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0879 - acc: 0.9995 - val_loss: 2.1914 - val_acc: 0.6040\n",
      "Learning rate:  0.0001\n",
      "Epoch 85/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0865 - acc: 0.9996\n",
      "Epoch 00085: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0866 - acc: 0.9996 - val_loss: 2.1996 - val_acc: 0.6080\n",
      "Learning rate:  0.0001\n",
      "Epoch 86/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0852 - acc: 0.9997\n",
      "Epoch 00086: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0853 - acc: 0.9997 - val_loss: 2.2075 - val_acc: 0.6040\n",
      "Learning rate:  0.0001\n",
      "Epoch 87/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0846 - acc: 0.9998\n",
      "Epoch 00087: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0846 - acc: 0.9999 - val_loss: 2.2367 - val_acc: 0.6160\n",
      "Learning rate:  0.0001\n",
      "Epoch 88/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0838 - acc: 0.9999\n",
      "Epoch 00088: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0840 - acc: 0.9999 - val_loss: 2.2325 - val_acc: 0.6040\n",
      "Learning rate:  0.0001\n",
      "Epoch 89/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0837 - acc: 0.9998\n",
      "Epoch 00089: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0837 - acc: 0.9999 - val_loss: 2.2448 - val_acc: 0.6120\n",
      "Learning rate:  0.0001\n",
      "Epoch 90/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0824 - acc: 0.9999\n",
      "Epoch 00090: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0825 - acc: 1.0000 - val_loss: 2.2410 - val_acc: 0.6140\n",
      "Learning rate:  0.0001\n",
      "Epoch 91/200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0823 - acc: 0.9999\n",
      "Epoch 00091: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.0823 - acc: 1.0000 - val_loss: 2.2553 - val_acc: 0.6100\n",
      "Learning rate:  0.0001\n",
      "Epoch 92/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0815 - acc: 1.0000\n",
      "Epoch 00092: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.0815 - acc: 1.0000 - val_loss: 2.2517 - val_acc: 0.6160\n",
      "Learning rate:  0.0001\n",
      "Epoch 93/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0808 - acc: 1.0000\n",
      "Epoch 00093: val_acc did not improve\n",
      "20000/20000 [==============================] - 89s 4ms/step - loss: 0.0808 - acc: 1.0000 - val_loss: 2.2757 - val_acc: 0.6060\n",
      "Learning rate:  0.0001\n",
      "Epoch 94/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0806 - acc: 1.0000\n",
      "Epoch 00094: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0806 - acc: 1.0000 - val_loss: 2.2620 - val_acc: 0.6100\n",
      "Learning rate:  0.0001\n",
      "Epoch 95/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0802 - acc: 1.0000\n",
      "Epoch 00095: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0802 - acc: 1.0000 - val_loss: 2.2760 - val_acc: 0.6040\n",
      "Learning rate:  0.0001\n",
      "Epoch 96/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0799 - acc: 0.9999\n",
      "Epoch 00096: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0799 - acc: 1.0000 - val_loss: 2.2982 - val_acc: 0.6060\n",
      "Learning rate:  0.0001\n",
      "Epoch 97/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0792 - acc: 0.9999\n",
      "Epoch 00097: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0793 - acc: 1.0000 - val_loss: 2.2948 - val_acc: 0.6120\n",
      "Learning rate:  0.0001\n",
      "Epoch 98/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0790 - acc: 0.9999\n",
      "Epoch 00098: val_acc did not improve\n",
      "20000/20000 [==============================] - 79s 4ms/step - loss: 0.0790 - acc: 1.0000 - val_loss: 2.2924 - val_acc: 0.6060\n",
      "Learning rate:  0.0001\n",
      "Epoch 99/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0788 - acc: 0.9999\n",
      "Epoch 00099: val_acc did not improve\n",
      "20000/20000 [==============================] - 79s 4ms/step - loss: 0.0788 - acc: 0.9999 - val_loss: 2.3238 - val_acc: 0.6040\n",
      "Learning rate:  0.0001\n",
      "Epoch 100/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0780 - acc: 1.0000\n",
      "Epoch 00100: val_acc did not improve\n",
      "20000/20000 [==============================] - 78s 4ms/step - loss: 0.0780 - acc: 1.0000 - val_loss: 2.3238 - val_acc: 0.6120\n",
      "Learning rate:  0.0001\n",
      "Epoch 101/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0775 - acc: 1.0000\n",
      "Epoch 00101: val_acc did not improve\n",
      "20000/20000 [==============================] - 78s 4ms/step - loss: 0.0775 - acc: 1.0000 - val_loss: 2.3456 - val_acc: 0.6060\n",
      "Learning rate:  0.0001\n",
      "Epoch 102/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0773 - acc: 1.0000\n",
      "Epoch 00102: val_acc did not improve\n",
      "20000/20000 [==============================] - 78s 4ms/step - loss: 0.0773 - acc: 1.0000 - val_loss: 2.3443 - val_acc: 0.5940\n",
      "Learning rate:  0.0001\n",
      "Epoch 103/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0766 - acc: 1.0000\n",
      "Epoch 00103: val_acc did not improve\n",
      "20000/20000 [==============================] - 78s 4ms/step - loss: 0.0767 - acc: 1.0000 - val_loss: 2.3351 - val_acc: 0.6040\n",
      "Learning rate:  0.0001\n",
      "Epoch 104/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0766 - acc: 0.9999\n",
      "Epoch 00104: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0767 - acc: 0.9999 - val_loss: 2.3501 - val_acc: 0.6140\n",
      "Learning rate:  0.0001\n",
      "Epoch 105/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0760 - acc: 1.0000\n",
      "Epoch 00105: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0760 - acc: 1.0000 - val_loss: 2.3564 - val_acc: 0.5980\n",
      "Learning rate:  0.0001\n",
      "Epoch 106/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0752 - acc: 1.0000\n",
      "Epoch 00106: val_acc did not improve\n",
      "20000/20000 [==============================] - 79s 4ms/step - loss: 0.0752 - acc: 1.0000 - val_loss: 2.3593 - val_acc: 0.6080\n",
      "Learning rate:  0.0001\n",
      "Epoch 107/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0753 - acc: 0.9999\n",
      "Epoch 00107: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0754 - acc: 1.0000 - val_loss: 2.3625 - val_acc: 0.6080\n",
      "Learning rate:  0.0001\n",
      "Epoch 108/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0745 - acc: 1.0000\n",
      "Epoch 00108: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0745 - acc: 1.0000 - val_loss: 2.3905 - val_acc: 0.5920\n",
      "Learning rate:  0.0001\n",
      "Epoch 109/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0740 - acc: 1.0000\n",
      "Epoch 00109: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0740 - acc: 1.0000 - val_loss: 2.3621 - val_acc: 0.6120\n",
      "Learning rate:  0.0001\n",
      "Epoch 110/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0731 - acc: 1.0000\n",
      "Epoch 00110: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0733 - acc: 1.0000 - val_loss: 2.3654 - val_acc: 0.5920\n",
      "Learning rate:  0.0001\n",
      "Epoch 111/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0732 - acc: 1.0000\n",
      "Epoch 00111: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.0732 - acc: 1.0000 - val_loss: 2.4044 - val_acc: 0.5960\n",
      "Learning rate:  0.0001\n",
      "Epoch 112/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0723 - acc: 1.0000\n",
      "Epoch 00112: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0723 - acc: 1.0000 - val_loss: 2.3979 - val_acc: 0.6000\n",
      "Learning rate:  0.0001\n",
      "Epoch 113/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0715 - acc: 1.0000\n",
      "Epoch 00113: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0715 - acc: 1.0000 - val_loss: 2.3851 - val_acc: 0.6020\n",
      "Learning rate:  0.0001\n",
      "Epoch 114/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0711 - acc: 1.0000\n",
      "Epoch 00114: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0712 - acc: 1.0000 - val_loss: 2.4106 - val_acc: 0.6080\n",
      "Learning rate:  0.0001\n",
      "Epoch 115/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0714 - acc: 0.9998\n",
      "Epoch 00115: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0714 - acc: 0.9999 - val_loss: 2.4110 - val_acc: 0.6120\n",
      "Learning rate:  0.0001\n",
      "Epoch 116/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0702 - acc: 1.0000\n",
      "Epoch 00116: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0703 - acc: 1.0000 - val_loss: 2.4085 - val_acc: 0.6060\n",
      "Learning rate:  0.0001\n",
      "Epoch 117/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0700 - acc: 1.0000\n",
      "Epoch 00117: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0700 - acc: 1.0000 - val_loss: 2.4191 - val_acc: 0.5980\n",
      "Learning rate:  0.0001\n",
      "Epoch 118/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0693 - acc: 0.9999\n",
      "Epoch 00118: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0693 - acc: 1.0000 - val_loss: 2.4271 - val_acc: 0.6140\n",
      "Learning rate:  0.0001\n",
      "Epoch 119/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0688 - acc: 0.9999\n",
      "Epoch 00119: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0688 - acc: 0.9999 - val_loss: 2.4389 - val_acc: 0.6120\n",
      "Learning rate:  0.0001\n",
      "Epoch 120/200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0681 - acc: 1.0000\n",
      "Epoch 00120: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0681 - acc: 1.0000 - val_loss: 2.5083 - val_acc: 0.5900\n",
      "Learning rate:  0.0001\n",
      "Epoch 121/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0672 - acc: 1.0000\n",
      "Epoch 00121: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0672 - acc: 1.0000 - val_loss: 2.4561 - val_acc: 0.6000\n",
      "Learning rate:  1e-05\n",
      "Epoch 122/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0668 - acc: 1.0000\n",
      "Epoch 00122: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0668 - acc: 1.0000 - val_loss: 2.4685 - val_acc: 0.6000\n",
      "Learning rate:  1e-05\n",
      "Epoch 123/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0667 - acc: 1.0000\n",
      "Epoch 00123: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0667 - acc: 1.0000 - val_loss: 2.4675 - val_acc: 0.5960\n",
      "Learning rate:  1e-05\n",
      "Epoch 124/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0667 - acc: 1.0000\n",
      "Epoch 00124: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0667 - acc: 1.0000 - val_loss: 2.4628 - val_acc: 0.6100\n",
      "Learning rate:  1e-05\n",
      "Epoch 125/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0665 - acc: 1.0000\n",
      "Epoch 00125: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0665 - acc: 1.0000 - val_loss: 2.4635 - val_acc: 0.6100\n",
      "Learning rate:  1e-05\n",
      "Epoch 126/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0664 - acc: 0.9999\n",
      "Epoch 00126: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0664 - acc: 1.0000 - val_loss: 2.4627 - val_acc: 0.6040\n",
      "Learning rate:  1e-05\n",
      "Epoch 127/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0664 - acc: 1.0000\n",
      "Epoch 00127: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0664 - acc: 1.0000 - val_loss: 2.4656 - val_acc: 0.6080\n",
      "Learning rate:  1e-05\n",
      "Epoch 128/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0662 - acc: 1.0000\n",
      "Epoch 00128: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0663 - acc: 1.0000 - val_loss: 2.4634 - val_acc: 0.6060\n",
      "Learning rate:  1e-05\n",
      "Epoch 129/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0662 - acc: 1.0000\n",
      "Epoch 00129: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0662 - acc: 1.0000 - val_loss: 2.4599 - val_acc: 0.6080\n",
      "Learning rate:  1e-05\n",
      "Epoch 130/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0660 - acc: 1.0000\n",
      "Epoch 00130: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0660 - acc: 1.0000 - val_loss: 2.4649 - val_acc: 0.6120\n",
      "Learning rate:  1e-05\n",
      "Epoch 131/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0660 - acc: 1.0000\n",
      "Epoch 00131: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0660 - acc: 1.0000 - val_loss: 2.4654 - val_acc: 0.6100\n",
      "Learning rate:  1e-05\n",
      "Epoch 132/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0659 - acc: 1.0000\n",
      "Epoch 00132: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.0659 - acc: 1.0000 - val_loss: 2.4722 - val_acc: 0.6000\n",
      "Learning rate:  1e-05\n",
      "Epoch 133/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0659 - acc: 1.0000\n",
      "Epoch 00133: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.0659 - acc: 1.0000 - val_loss: 2.4743 - val_acc: 0.6020\n",
      "Learning rate:  1e-05\n",
      "Epoch 134/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0657 - acc: 1.0000\n",
      "Epoch 00134: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.0657 - acc: 1.0000 - val_loss: 2.4747 - val_acc: 0.6100\n",
      "Learning rate:  1e-05\n",
      "Epoch 135/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0657 - acc: 1.0000\n",
      "Epoch 00135: val_acc did not improve\n",
      "20000/20000 [==============================] - 89s 4ms/step - loss: 0.0657 - acc: 1.0000 - val_loss: 2.4735 - val_acc: 0.6040\n",
      "Learning rate:  1e-05\n",
      "Epoch 136/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0655 - acc: 1.0000\n",
      "Epoch 00136: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.0655 - acc: 1.0000 - val_loss: 2.4763 - val_acc: 0.6040\n",
      "Learning rate:  1e-05\n",
      "Epoch 137/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0654 - acc: 1.0000\n",
      "Epoch 00137: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.0654 - acc: 1.0000 - val_loss: 2.4752 - val_acc: 0.6020\n",
      "Learning rate:  1e-05\n",
      "Epoch 138/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0654 - acc: 1.0000\n",
      "Epoch 00138: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0655 - acc: 1.0000 - val_loss: 2.4690 - val_acc: 0.6040\n",
      "Learning rate:  1e-05\n",
      "Epoch 139/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0653 - acc: 1.0000\n",
      "Epoch 00139: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0653 - acc: 1.0000 - val_loss: 2.4633 - val_acc: 0.6060\n",
      "Learning rate:  1e-05\n",
      "Epoch 140/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0651 - acc: 1.0000\n",
      "Epoch 00140: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0651 - acc: 1.0000 - val_loss: 2.4702 - val_acc: 0.6060\n",
      "Learning rate:  1e-05\n",
      "Epoch 141/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0651 - acc: 1.0000\n",
      "Epoch 00141: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0652 - acc: 1.0000 - val_loss: 2.4639 - val_acc: 0.6080\n",
      "Learning rate:  1e-05\n",
      "Epoch 142/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0653 - acc: 1.0000\n",
      "Epoch 00142: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0653 - acc: 1.0000 - val_loss: 2.4688 - val_acc: 0.6120\n",
      "Learning rate:  1e-05\n",
      "Epoch 143/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0650 - acc: 1.0000\n",
      "Epoch 00143: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0650 - acc: 1.0000 - val_loss: 2.4832 - val_acc: 0.6060\n",
      "Learning rate:  1e-05\n",
      "Epoch 144/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0649 - acc: 1.0000\n",
      "Epoch 00144: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0649 - acc: 1.0000 - val_loss: 2.4797 - val_acc: 0.6040\n",
      "Learning rate:  1e-05\n",
      "Epoch 145/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0650 - acc: 1.0000\n",
      "Epoch 00145: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0650 - acc: 1.0000 - val_loss: 2.4790 - val_acc: 0.6080\n",
      "Learning rate:  1e-05\n",
      "Epoch 146/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0649 - acc: 1.0000\n",
      "Epoch 00146: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.0649 - acc: 1.0000 - val_loss: 2.4721 - val_acc: 0.6000\n",
      "Learning rate:  1e-05\n",
      "Epoch 147/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0647 - acc: 0.9999\n",
      "Epoch 00147: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.0647 - acc: 1.0000 - val_loss: 2.4751 - val_acc: 0.6000\n",
      "Learning rate:  1e-05\n",
      "Epoch 148/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0647 - acc: 0.9999\n",
      "Epoch 00148: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 4ms/step - loss: 0.0647 - acc: 1.0000 - val_loss: 2.4759 - val_acc: 0.5980\n",
      "Learning rate:  1e-05\n",
      "Epoch 149/200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0646 - acc: 1.0000\n",
      "Epoch 00149: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0646 - acc: 1.0000 - val_loss: 2.4768 - val_acc: 0.6000\n",
      "Learning rate:  1e-05\n",
      "Epoch 150/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0645 - acc: 1.0000\n",
      "Epoch 00150: val_acc did not improve\n",
      "20000/20000 [==============================] - 92s 5ms/step - loss: 0.0645 - acc: 1.0000 - val_loss: 2.4797 - val_acc: 0.6020\n",
      "Learning rate:  1e-05\n",
      "Epoch 151/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0644 - acc: 1.0000\n",
      "Epoch 00151: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0644 - acc: 1.0000 - val_loss: 2.4785 - val_acc: 0.5980\n",
      "Learning rate:  1e-05\n",
      "Epoch 152/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0643 - acc: 1.0000\n",
      "Epoch 00152: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.0643 - acc: 1.0000 - val_loss: 2.4847 - val_acc: 0.5980\n",
      "Learning rate:  1e-05\n",
      "Epoch 153/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0642 - acc: 1.0000\n",
      "Epoch 00153: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0642 - acc: 1.0000 - val_loss: 2.4887 - val_acc: 0.6020\n",
      "Learning rate:  1e-05\n",
      "Epoch 154/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0642 - acc: 1.0000\n",
      "Epoch 00154: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0642 - acc: 1.0000 - val_loss: 2.4807 - val_acc: 0.6000\n",
      "Learning rate:  1e-05\n",
      "Epoch 155/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0639 - acc: 1.0000\n",
      "Epoch 00155: val_acc did not improve\n",
      "20000/20000 [==============================] - 93s 5ms/step - loss: 0.0639 - acc: 1.0000 - val_loss: 2.4842 - val_acc: 0.6000\n",
      "Learning rate:  1e-05\n",
      "Epoch 156/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0639 - acc: 1.0000\n",
      "Epoch 00156: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 4ms/step - loss: 0.0639 - acc: 1.0000 - val_loss: 2.4750 - val_acc: 0.6040\n",
      "Learning rate:  1e-05\n",
      "Epoch 157/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0639 - acc: 1.0000\n",
      "Epoch 00157: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 4ms/step - loss: 0.0639 - acc: 1.0000 - val_loss: 2.4832 - val_acc: 0.6040\n",
      "Learning rate:  1e-05\n",
      "Epoch 158/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0638 - acc: 1.0000\n",
      "Epoch 00158: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0638 - acc: 1.0000 - val_loss: 2.4910 - val_acc: 0.6060\n",
      "Learning rate:  1e-05\n",
      "Epoch 159/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0636 - acc: 1.0000\n",
      "Epoch 00159: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0636 - acc: 1.0000 - val_loss: 2.4761 - val_acc: 0.6040\n",
      "Learning rate:  1e-05\n",
      "Epoch 160/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0636 - acc: 1.0000\n",
      "Epoch 00160: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0636 - acc: 1.0000 - val_loss: 2.4783 - val_acc: 0.6040\n",
      "Learning rate:  1e-05\n",
      "Epoch 161/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0635 - acc: 0.9999\n",
      "Epoch 00161: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0635 - acc: 1.0000 - val_loss: 2.4850 - val_acc: 0.6120\n",
      "Learning rate:  1e-06\n",
      "Epoch 162/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0634 - acc: 1.0000\n",
      "Epoch 00162: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0635 - acc: 1.0000 - val_loss: 2.4845 - val_acc: 0.6040\n",
      "Learning rate:  1e-06\n",
      "Epoch 163/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00163: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4844 - val_acc: 0.5980\n",
      "Learning rate:  1e-06\n",
      "Epoch 164/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00164: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4869 - val_acc: 0.6020\n",
      "Learning rate:  1e-06\n",
      "Epoch 165/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0634 - acc: 1.0000\n",
      "Epoch 00165: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0637 - acc: 0.9999 - val_loss: 2.4867 - val_acc: 0.6000\n",
      "Learning rate:  1e-06\n",
      "Epoch 166/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00166: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 4ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4872 - val_acc: 0.5960\n",
      "Learning rate:  1e-06\n",
      "Epoch 167/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0634 - acc: 1.0000\n",
      "Epoch 00167: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.0634 - acc: 1.0000 - val_loss: 2.4839 - val_acc: 0.5980\n",
      "Learning rate:  1e-06\n",
      "Epoch 168/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00168: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.0634 - acc: 1.0000 - val_loss: 2.4866 - val_acc: 0.6000\n",
      "Learning rate:  1e-06\n",
      "Epoch 169/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00169: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4852 - val_acc: 0.5960\n",
      "Learning rate:  1e-06\n",
      "Epoch 170/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0634 - acc: 1.0000\n",
      "Epoch 00170: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.0634 - acc: 1.0000 - val_loss: 2.4865 - val_acc: 0.5980\n",
      "Learning rate:  1e-06\n",
      "Epoch 171/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00171: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4876 - val_acc: 0.6000\n",
      "Learning rate:  1e-06\n",
      "Epoch 172/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0634 - acc: 1.0000\n",
      "Epoch 00172: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 5ms/step - loss: 0.0634 - acc: 1.0000 - val_loss: 2.4898 - val_acc: 0.6040\n",
      "Learning rate:  1e-06\n",
      "Epoch 173/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00173: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4887 - val_acc: 0.5960\n",
      "Learning rate:  1e-06\n",
      "Epoch 174/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00174: val_acc did not improve\n",
      "20000/20000 [==============================] - 92s 5ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4906 - val_acc: 0.6040\n",
      "Learning rate:  1e-06\n",
      "Epoch 175/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00175: val_acc did not improve\n",
      "20000/20000 [==============================] - 92s 5ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4880 - val_acc: 0.6020\n",
      "Learning rate:  1e-06\n",
      "Epoch 176/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00176: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4883 - val_acc: 0.6020\n",
      "Learning rate:  1e-06\n",
      "Epoch 177/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00177: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4861 - val_acc: 0.5960\n",
      "Learning rate:  1e-06\n",
      "Epoch 178/200\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00178: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4904 - val_acc: 0.6040\n",
      "Learning rate:  1e-06\n",
      "Epoch 179/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 0.9999\n",
      "Epoch 00179: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4898 - val_acc: 0.6040\n",
      "Learning rate:  1e-06\n",
      "Epoch 180/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00180: val_acc did not improve\n",
      "20000/20000 [==============================] - 91s 5ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4898 - val_acc: 0.6000\n",
      "Learning rate:  1e-06\n",
      "Epoch 181/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00181: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4890 - val_acc: 0.5960\n",
      "Learning rate:  5e-07\n",
      "Epoch 182/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00182: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4893 - val_acc: 0.5960\n",
      "Learning rate:  5e-07\n",
      "Epoch 183/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00183: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4870 - val_acc: 0.5980\n",
      "Learning rate:  5e-07\n",
      "Epoch 184/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0631 - acc: 1.0000\n",
      "Epoch 00184: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4875 - val_acc: 0.5980\n",
      "Learning rate:  5e-07\n",
      "Epoch 185/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00185: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4883 - val_acc: 0.6000\n",
      "Learning rate:  5e-07\n",
      "Epoch 186/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00186: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4885 - val_acc: 0.5980\n",
      "Learning rate:  5e-07\n",
      "Epoch 187/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00187: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0634 - acc: 1.0000 - val_loss: 2.4894 - val_acc: 0.6000\n",
      "Learning rate:  5e-07\n",
      "Epoch 188/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0631 - acc: 1.0000\n",
      "Epoch 00188: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4876 - val_acc: 0.6000\n",
      "Learning rate:  5e-07\n",
      "Epoch 189/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00189: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4879 - val_acc: 0.6000\n",
      "Learning rate:  5e-07\n",
      "Epoch 190/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00190: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4872 - val_acc: 0.5960\n",
      "Learning rate:  5e-07\n",
      "Epoch 191/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00191: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4866 - val_acc: 0.5960\n",
      "Learning rate:  5e-07\n",
      "Epoch 192/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00192: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4882 - val_acc: 0.5960\n",
      "Learning rate:  5e-07\n",
      "Epoch 193/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0631 - acc: 1.0000\n",
      "Epoch 00193: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0631 - acc: 1.0000 - val_loss: 2.4902 - val_acc: 0.6000\n",
      "Learning rate:  5e-07\n",
      "Epoch 194/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00194: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4892 - val_acc: 0.5980\n",
      "Learning rate:  5e-07\n",
      "Epoch 195/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00195: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4873 - val_acc: 0.5960\n",
      "Learning rate:  5e-07\n",
      "Epoch 196/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00196: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4908 - val_acc: 0.6000\n",
      "Learning rate:  5e-07\n",
      "Epoch 197/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 1.0000\n",
      "Epoch 00197: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4893 - val_acc: 0.6020\n",
      "Learning rate:  5e-07\n",
      "Epoch 198/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0631 - acc: 1.0000\n",
      "Epoch 00198: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4889 - val_acc: 0.5980\n",
      "Learning rate:  5e-07\n",
      "Epoch 199/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00199: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0632 - acc: 1.0000 - val_loss: 2.4904 - val_acc: 0.6020\n",
      "Learning rate:  5e-07\n",
      "Epoch 200/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0632 - acc: 1.0000\n",
      "Epoch 00200: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0633 - acc: 1.0000 - val_loss: 2.4902 - val_acc: 0.6040\n",
      "10000/10000 [==============================] - 15s 1ms/step\n",
      "Initial Simple Model Accuracy: 0.6364\n"
     ]
    }
   ],
   "source": [
    "a=ProfweightExplainer()\n",
    "m=a.fit(x_train2,y_train2,x_test,y_test,resnet_v1,hps,'neural_keras')\n",
    "print(\"Initial Simple Model Accuracy:\",m[1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Simple Model training with Prof Weight- Sample Weights Obtained from Probe Confidences of Various Layers."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "List of all filenames - each of which contains the probe confidences of a specific layer corresponding to the samples in x_train2,y_train2 dataset. This is assumed to have been obtained using functions in attach_probe_checkpoint.py and train_probes.py."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "list_probe_filenames=[parent_dir+'/probe_output/probe_2_out_pred'+str(x)+'.npy' for x in range(10,17)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Specify a new checkpoint for the simple model with Prof Weight + set identical hyper parameters for learning rate schedule and training."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Learning rate:  0.001\n"
     ]
    }
   ],
   "source": [
    "save_dir = os.path.join(os.getcwd(), 'saved_models')\n",
    "model_name = 'resnet_target_model_weighted.h5' \n",
    "if not os.path.isdir(save_dir):\n",
    "    os.makedirs(save_dir)\n",
    "filepath = os.path.join(save_dir, model_name)\n",
    "hps = HParams(lr_scheduler=lr_scheduler,lr_reducer=lr_reducer,batch_size=128,epochs=200,checkpoint_path=filepath,num_classes=10,complexity_param=1,optimizer=Adam(lr=lr_schedule(0)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Call the ProfWeight Explainer Class's explain function - This is same as the fit function but additionally specifies list of probe filenames and start and end layer whose confidences need to be averaged to be used as the sample weights. This explain function also scores the new simple model obtained after weighted training on the test data set."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_2 (InputLayer)            (None, 32, 32, 3)    0                                            \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_10 (Conv2D)              (None, 32, 32, 16)   448         input_2[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_8 (BatchNor (None, 32, 32, 16)   64          conv2d_10[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_8 (Activation)       (None, 32, 32, 16)   0           batch_normalization_8[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_11 (Conv2D)              (None, 32, 32, 16)   2320        activation_8[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_9 (BatchNor (None, 32, 32, 16)   64          conv2d_11[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_9 (Activation)       (None, 32, 32, 16)   0           batch_normalization_9[0][0]      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_12 (Conv2D)              (None, 32, 32, 16)   2320        activation_9[0][0]               \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_10 (BatchNo (None, 32, 32, 16)   64          conv2d_12[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_4 (Add)                     (None, 32, 32, 16)   0           activation_8[0][0]               \n",
      "                                                                 batch_normalization_10[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_10 (Activation)      (None, 32, 32, 16)   0           add_4[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_13 (Conv2D)              (None, 16, 16, 32)   4640        activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_11 (BatchNo (None, 16, 16, 32)   128         conv2d_13[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_11 (Activation)      (None, 16, 16, 32)   0           batch_normalization_11[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_14 (Conv2D)              (None, 16, 16, 32)   9248        activation_11[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_15 (Conv2D)              (None, 16, 16, 32)   544         activation_10[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_12 (BatchNo (None, 16, 16, 32)   128         conv2d_14[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_5 (Add)                     (None, 16, 16, 32)   0           conv2d_15[0][0]                  \n",
      "                                                                 batch_normalization_12[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_12 (Activation)      (None, 16, 16, 32)   0           add_5[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_16 (Conv2D)              (None, 8, 8, 64)     18496       activation_12[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_13 (BatchNo (None, 8, 8, 64)     256         conv2d_16[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "activation_13 (Activation)      (None, 8, 8, 64)     0           batch_normalization_13[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_17 (Conv2D)              (None, 8, 8, 64)     36928       activation_13[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "conv2d_18 (Conv2D)              (None, 8, 8, 64)     2112        activation_12[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_14 (BatchNo (None, 8, 8, 64)     256         conv2d_17[0][0]                  \n",
      "__________________________________________________________________________________________________\n",
      "add_6 (Add)                     (None, 8, 8, 64)     0           conv2d_18[0][0]                  \n",
      "                                                                 batch_normalization_14[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "activation_14 (Activation)      (None, 8, 8, 64)     0           add_6[0][0]                      \n",
      "__________________________________________________________________________________________________\n",
      "average_pooling2d_2 (AveragePoo (None, 1, 1, 64)     0           activation_14[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "flatten_2 (Flatten)             (None, 64)           0           average_pooling2d_2[0][0]        \n",
      "__________________________________________________________________________________________________\n",
      "dense_2 (Dense)                 (None, 10)           650         flatten_2[0][0]                  \n",
      "==================================================================================================\n",
      "Total params: 78,666\n",
      "Trainable params: 78,186\n",
      "Non-trainable params: 480\n",
      "__________________________________________________________________________________________________\n",
      "Train on 20000 samples, validate on 500 samples\n",
      "Learning rate:  0.001\n",
      "Epoch 1/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 1.3629 - acc: 0.3731\n",
      "Epoch 00001: val_acc improved from -inf to 0.34000, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 1.3625 - acc: 0.3733 - val_loss: 1.8125 - val_acc: 0.3400\n",
      "Learning rate:  0.001\n",
      "Epoch 2/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 1.0352 - acc: 0.5020\n",
      "Epoch 00002: val_acc improved from 0.34000 to 0.40200, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 1.0350 - acc: 0.5019 - val_loss: 1.8655 - val_acc: 0.4020\n",
      "Learning rate:  0.001\n",
      "Epoch 3/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.8876 - acc: 0.5634\n",
      "Epoch 00003: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.8878 - acc: 0.5632 - val_loss: 1.7293 - val_acc: 0.3940\n",
      "Learning rate:  0.001\n",
      "Epoch 4/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.7974 - acc: 0.5972\n",
      "Epoch 00004: val_acc improved from 0.40200 to 0.56800, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.7976 - acc: 0.5970 - val_loss: 1.2677 - val_acc: 0.5680\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Learning rate:  0.001\n",
      "Epoch 5/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.7146 - acc: 0.6343\n",
      "Epoch 00005: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.7145 - acc: 0.6344 - val_loss: 1.5109 - val_acc: 0.4760\n",
      "Learning rate:  0.001\n",
      "Epoch 6/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.6566 - acc: 0.6574\n",
      "Epoch 00006: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.6565 - acc: 0.6572 - val_loss: 1.6429 - val_acc: 0.5040\n",
      "Learning rate:  0.001\n",
      "Epoch 7/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.6042 - acc: 0.6796\n",
      "Epoch 00007: val_acc improved from 0.56800 to 0.59400, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.6045 - acc: 0.6794 - val_loss: 1.1950 - val_acc: 0.5940\n",
      "Learning rate:  0.001\n",
      "Epoch 8/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.5631 - acc: 0.6968\n",
      "Epoch 00008: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.5630 - acc: 0.6966 - val_loss: 1.5353 - val_acc: 0.4900\n",
      "Learning rate:  0.001\n",
      "Epoch 9/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.5159 - acc: 0.7171\n",
      "Epoch 00009: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.5159 - acc: 0.7171 - val_loss: 1.3132 - val_acc: 0.5880\n",
      "Learning rate:  0.001\n",
      "Epoch 10/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.4871 - acc: 0.7240\n",
      "Epoch 00010: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.4871 - acc: 0.7242 - val_loss: 1.5911 - val_acc: 0.5100\n",
      "Learning rate:  0.001\n",
      "Epoch 11/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.4496 - acc: 0.7440\n",
      "Epoch 00011: val_acc improved from 0.59400 to 0.61600, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.4497 - acc: 0.7439 - val_loss: 1.2388 - val_acc: 0.6160\n",
      "Learning rate:  0.001\n",
      "Epoch 12/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.4194 - acc: 0.7586\n",
      "Epoch 00012: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.4192 - acc: 0.7587 - val_loss: 1.3255 - val_acc: 0.6040\n",
      "Learning rate:  0.001\n",
      "Epoch 13/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.3897 - acc: 0.7711\n",
      "Epoch 00013: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.3895 - acc: 0.7711 - val_loss: 1.7558 - val_acc: 0.5180\n",
      "Learning rate:  0.001\n",
      "Epoch 14/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.3648 - acc: 0.7805\n",
      "Epoch 00014: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.3653 - acc: 0.7803 - val_loss: 1.3449 - val_acc: 0.6100\n",
      "Learning rate:  0.001\n",
      "Epoch 15/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.3428 - acc: 0.7918\n",
      "Epoch 00015: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.3428 - acc: 0.7918 - val_loss: 1.4443 - val_acc: 0.6120\n",
      "Learning rate:  0.001\n",
      "Epoch 16/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.3115 - acc: 0.8069\n",
      "Epoch 00016: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.3115 - acc: 0.8069 - val_loss: 2.1172 - val_acc: 0.4660\n",
      "Learning rate:  0.001\n",
      "Epoch 17/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2919 - acc: 0.8152\n",
      "Epoch 00017: val_acc improved from 0.61600 to 0.62000, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.2922 - acc: 0.8152 - val_loss: 1.2935 - val_acc: 0.6200\n",
      "Learning rate:  0.001\n",
      "Epoch 18/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2703 - acc: 0.8247\n",
      "Epoch 00018: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.2704 - acc: 0.8246 - val_loss: 1.5217 - val_acc: 0.5980\n",
      "Learning rate:  0.001\n",
      "Epoch 19/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2528 - acc: 0.8345\n",
      "Epoch 00019: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.2531 - acc: 0.8343 - val_loss: 1.4426 - val_acc: 0.6000\n",
      "Learning rate:  0.001\n",
      "Epoch 20/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2398 - acc: 0.8391\n",
      "Epoch 00020: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.2400 - acc: 0.8389 - val_loss: 1.8150 - val_acc: 0.5780\n",
      "Learning rate:  0.001\n",
      "Epoch 21/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2277 - acc: 0.8463\n",
      "Epoch 00021: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.2279 - acc: 0.8463 - val_loss: 1.5997 - val_acc: 0.5840\n",
      "Learning rate:  0.001\n",
      "Epoch 22/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2096 - acc: 0.8548\n",
      "Epoch 00022: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.2097 - acc: 0.8548 - val_loss: 2.4682 - val_acc: 0.5080\n",
      "Learning rate:  0.001\n",
      "Epoch 23/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1986 - acc: 0.8591\n",
      "Epoch 00023: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1986 - acc: 0.8591 - val_loss: 1.9452 - val_acc: 0.5600\n",
      "Learning rate:  0.001\n",
      "Epoch 24/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1884 - acc: 0.8646\n",
      "Epoch 00024: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1886 - acc: 0.8645 - val_loss: 2.0089 - val_acc: 0.5560\n",
      "Learning rate:  0.001\n",
      "Epoch 25/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1869 - acc: 0.8652\n",
      "Epoch 00025: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.1871 - acc: 0.8653 - val_loss: 1.9945 - val_acc: 0.5780\n",
      "Learning rate:  0.001\n",
      "Epoch 26/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1798 - acc: 0.8678\n",
      "Epoch 00026: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1797 - acc: 0.8679 - val_loss: 2.0091 - val_acc: 0.5920\n",
      "Learning rate:  0.001\n",
      "Epoch 27/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1583 - acc: 0.8800\n",
      "Epoch 00027: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1585 - acc: 0.8799 - val_loss: 1.8829 - val_acc: 0.6040\n",
      "Learning rate:  0.001\n",
      "Epoch 28/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1601 - acc: 0.8788\n",
      "Epoch 00028: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1602 - acc: 0.8787 - val_loss: 2.5501 - val_acc: 0.5540\n",
      "Learning rate:  0.001\n",
      "Epoch 29/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1521 - acc: 0.8812\n",
      "Epoch 00029: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1521 - acc: 0.8813 - val_loss: 2.4368 - val_acc: 0.5140\n",
      "Learning rate:  0.001\n",
      "Epoch 30/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1407 - acc: 0.8882\n",
      "Epoch 00030: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1407 - acc: 0.8881 - val_loss: 2.8118 - val_acc: 0.5100\n",
      "Learning rate:  0.001\n",
      "Epoch 31/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1435 - acc: 0.8867\n",
      "Epoch 00031: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1439 - acc: 0.8863 - val_loss: 2.2212 - val_acc: 0.5640\n",
      "Learning rate:  0.001\n",
      "Epoch 32/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1683 - acc: 0.8731\n",
      "Epoch 00032: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1685 - acc: 0.8731 - val_loss: 2.2477 - val_acc: 0.5720\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Learning rate:  0.001\n",
      "Epoch 33/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1378 - acc: 0.8904\n",
      "Epoch 00033: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1380 - acc: 0.8903 - val_loss: 2.2082 - val_acc: 0.5620\n",
      "Learning rate:  0.001\n",
      "Epoch 34/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1395 - acc: 0.8878\n",
      "Epoch 00034: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1395 - acc: 0.8877 - val_loss: 1.9936 - val_acc: 0.6060\n",
      "Learning rate:  0.001\n",
      "Epoch 35/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1248 - acc: 0.8975\n",
      "Epoch 00035: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1248 - acc: 0.8976 - val_loss: 2.5040 - val_acc: 0.5200\n",
      "Learning rate:  0.001\n",
      "Epoch 36/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1251 - acc: 0.8941\n",
      "Epoch 00036: val_acc improved from 0.62000 to 0.62200, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1251 - acc: 0.8943 - val_loss: 1.8172 - val_acc: 0.6220\n",
      "Learning rate:  0.001\n",
      "Epoch 37/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1217 - acc: 0.8988\n",
      "Epoch 00037: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1218 - acc: 0.8987 - val_loss: 2.2856 - val_acc: 0.6080\n",
      "Learning rate:  0.001\n",
      "Epoch 38/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1354 - acc: 0.8912\n",
      "Epoch 00038: val_acc improved from 0.62200 to 0.63200, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.1354 - acc: 0.8910 - val_loss: 1.7511 - val_acc: 0.6320\n",
      "Learning rate:  0.001\n",
      "Epoch 39/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1251 - acc: 0.8977\n",
      "Epoch 00039: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.1255 - acc: 0.8976 - val_loss: 2.2910 - val_acc: 0.5800\n",
      "Learning rate:  0.001\n",
      "Epoch 40/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1656 - acc: 0.8758\n",
      "Epoch 00040: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1660 - acc: 0.8756 - val_loss: 2.9480 - val_acc: 0.5640\n",
      "Learning rate:  0.001\n",
      "Epoch 41/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1332 - acc: 0.8918\n",
      "Epoch 00041: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1332 - acc: 0.8918 - val_loss: 2.4033 - val_acc: 0.5800\n",
      "Learning rate:  0.001\n",
      "Epoch 42/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1154 - acc: 0.9017\n",
      "Epoch 00042: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.1155 - acc: 0.9017 - val_loss: 2.0254 - val_acc: 0.6100\n",
      "Learning rate:  0.001\n",
      "Epoch 43/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1126 - acc: 0.9055\n",
      "Epoch 00043: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1126 - acc: 0.9053 - val_loss: 2.5272 - val_acc: 0.5660\n",
      "Learning rate:  0.001\n",
      "Epoch 44/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0999 - acc: 0.9103\n",
      "Epoch 00044: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0999 - acc: 0.9103 - val_loss: 1.9496 - val_acc: 0.6300\n",
      "Learning rate:  0.001\n",
      "Epoch 45/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0959 - acc: 0.9130\n",
      "Epoch 00045: val_acc improved from 0.63200 to 0.65200, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0960 - acc: 0.9130 - val_loss: 1.8603 - val_acc: 0.6520\n",
      "Learning rate:  0.001\n",
      "Epoch 46/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1202 - acc: 0.9001\n",
      "Epoch 00046: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1206 - acc: 0.9000 - val_loss: 3.4532 - val_acc: 0.5100\n",
      "Learning rate:  0.001\n",
      "Epoch 47/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1979 - acc: 0.8628\n",
      "Epoch 00047: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1978 - acc: 0.8627 - val_loss: 2.2592 - val_acc: 0.6040\n",
      "Learning rate:  0.001\n",
      "Epoch 48/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1180 - acc: 0.9032\n",
      "Epoch 00048: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1180 - acc: 0.9032 - val_loss: 3.8494 - val_acc: 0.4820\n",
      "Learning rate:  0.001\n",
      "Epoch 49/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0983 - acc: 0.9128\n",
      "Epoch 00049: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0983 - acc: 0.9129 - val_loss: 2.0801 - val_acc: 0.6300\n",
      "Learning rate:  0.001\n",
      "Epoch 50/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0838 - acc: 0.9205\n",
      "Epoch 00050: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0838 - acc: 0.9205 - val_loss: 1.8530 - val_acc: 0.6400\n",
      "Learning rate:  0.001\n",
      "Epoch 51/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0882 - acc: 0.9178\n",
      "Epoch 00051: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0882 - acc: 0.9179 - val_loss: 2.2185 - val_acc: 0.6220\n",
      "Learning rate:  0.001\n",
      "Epoch 52/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0963 - acc: 0.9150\n",
      "Epoch 00052: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0964 - acc: 0.9149 - val_loss: 2.8008 - val_acc: 0.6060\n",
      "Learning rate:  0.001\n",
      "Epoch 53/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1259 - acc: 0.8982\n",
      "Epoch 00053: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1259 - acc: 0.8982 - val_loss: 2.8354 - val_acc: 0.5540\n",
      "Learning rate:  0.001\n",
      "Epoch 54/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1369 - acc: 0.8915\n",
      "Epoch 00054: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.1370 - acc: 0.8912 - val_loss: 4.0077 - val_acc: 0.4560\n",
      "Learning rate:  0.001\n",
      "Epoch 55/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1293 - acc: 0.8973\n",
      "Epoch 00055: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1293 - acc: 0.8975 - val_loss: 2.1551 - val_acc: 0.6080\n",
      "Learning rate:  0.001\n",
      "Epoch 56/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1202 - acc: 0.8977\n",
      "Epoch 00056: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.1202 - acc: 0.8978 - val_loss: 2.1962 - val_acc: 0.6000\n",
      "Learning rate:  0.001\n",
      "Epoch 57/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0972 - acc: 0.9135\n",
      "Epoch 00057: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.0972 - acc: 0.9136 - val_loss: 2.3782 - val_acc: 0.6080\n",
      "Learning rate:  0.001\n",
      "Epoch 58/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0871 - acc: 0.9213\n",
      "Epoch 00058: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0871 - acc: 0.9213 - val_loss: 2.1894 - val_acc: 0.6380\n",
      "Learning rate:  0.001\n",
      "Epoch 59/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0789 - acc: 0.9252\n",
      "Epoch 00059: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0791 - acc: 0.9252 - val_loss: 1.9817 - val_acc: 0.6440\n",
      "Learning rate:  0.001\n",
      "Epoch 60/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1147 - acc: 0.9039\n",
      "Epoch 00060: val_acc did not improve\n",
      "20000/20000 [==============================] - 90s 4ms/step - loss: 0.1148 - acc: 0.9039 - val_loss: 2.6443 - val_acc: 0.5940\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Learning rate:  0.001\n",
      "Epoch 61/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1360 - acc: 0.8936\n",
      "Epoch 00061: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.1361 - acc: 0.8936 - val_loss: 4.9183 - val_acc: 0.3640\n",
      "Learning rate:  0.001\n",
      "Epoch 62/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1366 - acc: 0.8943\n",
      "Epoch 00062: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.1365 - acc: 0.8943 - val_loss: 3.1165 - val_acc: 0.5560\n",
      "Learning rate:  0.001\n",
      "Epoch 63/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0972 - acc: 0.9142\n",
      "Epoch 00063: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.0972 - acc: 0.9142 - val_loss: 2.2720 - val_acc: 0.5880\n",
      "Learning rate:  0.001\n",
      "Epoch 64/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0856 - acc: 0.9199\n",
      "Epoch 00064: val_acc improved from 0.65200 to 0.66400, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.0856 - acc: 0.9200 - val_loss: 1.9621 - val_acc: 0.6640\n",
      "Learning rate:  0.001\n",
      "Epoch 65/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0760 - acc: 0.9268\n",
      "Epoch 00065: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0761 - acc: 0.9268 - val_loss: 2.0084 - val_acc: 0.6640\n",
      "Learning rate:  0.001\n",
      "Epoch 66/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0849 - acc: 0.9218\n",
      "Epoch 00066: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0849 - acc: 0.9219 - val_loss: 2.7412 - val_acc: 0.6060\n",
      "Learning rate:  0.001\n",
      "Epoch 67/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0994 - acc: 0.9131\n",
      "Epoch 00067: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0994 - acc: 0.9131 - val_loss: 2.7860 - val_acc: 0.5840\n",
      "Learning rate:  0.001\n",
      "Epoch 68/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1368 - acc: 0.8916\n",
      "Epoch 00068: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1369 - acc: 0.8917 - val_loss: 3.5017 - val_acc: 0.5540\n",
      "Learning rate:  0.001\n",
      "Epoch 69/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1421 - acc: 0.8891\n",
      "Epoch 00069: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1421 - acc: 0.8891 - val_loss: 4.0718 - val_acc: 0.4700\n",
      "Learning rate:  0.001\n",
      "Epoch 70/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1074 - acc: 0.9098\n",
      "Epoch 00070: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.1074 - acc: 0.9098 - val_loss: 2.0360 - val_acc: 0.6440\n",
      "Learning rate:  0.001\n",
      "Epoch 71/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0893 - acc: 0.9198\n",
      "Epoch 00071: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0894 - acc: 0.9198 - val_loss: 3.2752 - val_acc: 0.5300\n",
      "Learning rate:  0.001\n",
      "Epoch 72/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0843 - acc: 0.9207\n",
      "Epoch 00072: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0843 - acc: 0.9207 - val_loss: 2.1851 - val_acc: 0.6360\n",
      "Learning rate:  0.001\n",
      "Epoch 73/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0754 - acc: 0.9278\n",
      "Epoch 00073: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0755 - acc: 0.9278 - val_loss: 2.1552 - val_acc: 0.6340\n",
      "Learning rate:  0.001\n",
      "Epoch 74/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0721 - acc: 0.9292\n",
      "Epoch 00074: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0721 - acc: 0.9294 - val_loss: 1.9981 - val_acc: 0.6460\n",
      "Learning rate:  0.001\n",
      "Epoch 75/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0659 - acc: 0.9331\n",
      "Epoch 00075: val_acc improved from 0.66400 to 0.67200, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0659 - acc: 0.9331 - val_loss: 1.9187 - val_acc: 0.6720\n",
      "Learning rate:  0.001\n",
      "Epoch 76/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0643 - acc: 0.9339\n",
      "Epoch 00076: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0643 - acc: 0.9338 - val_loss: 2.1630 - val_acc: 0.6620\n",
      "Learning rate:  0.001\n",
      "Epoch 77/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0628 - acc: 0.9349\n",
      "Epoch 00077: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0628 - acc: 0.9350 - val_loss: 2.0802 - val_acc: 0.6420\n",
      "Learning rate:  0.001\n",
      "Epoch 78/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.2322 - acc: 0.8555\n",
      "Epoch 00078: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.2326 - acc: 0.8553 - val_loss: 4.0073 - val_acc: 0.4900\n",
      "Learning rate:  0.001\n",
      "Epoch 79/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1854 - acc: 0.8698\n",
      "Epoch 00079: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.1853 - acc: 0.8700 - val_loss: 2.1362 - val_acc: 0.5880\n",
      "Learning rate:  0.001\n",
      "Epoch 80/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.1022 - acc: 0.9119\n",
      "Epoch 00080: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.1023 - acc: 0.9120 - val_loss: 2.4133 - val_acc: 0.6080\n",
      "Learning rate:  0.001\n",
      "Epoch 81/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0854 - acc: 0.9225\n",
      "Epoch 00081: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0854 - acc: 0.9225 - val_loss: 2.0171 - val_acc: 0.6140\n",
      "Learning rate:  0.0001\n",
      "Epoch 82/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0723 - acc: 0.9309\n",
      "Epoch 00082: val_acc improved from 0.67200 to 0.68200, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0723 - acc: 0.9308 - val_loss: 1.7146 - val_acc: 0.6820\n",
      "Learning rate:  0.0001\n",
      "Epoch 83/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0693 - acc: 0.9327\n",
      "Epoch 00083: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0694 - acc: 0.9326 - val_loss: 1.7464 - val_acc: 0.6800\n",
      "Learning rate:  0.0001\n",
      "Epoch 84/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0682 - acc: 0.9330\n",
      "Epoch 00084: val_acc improved from 0.68200 to 0.68200, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0685 - acc: 0.9330 - val_loss: 1.7338 - val_acc: 0.6820\n",
      "Learning rate:  0.0001\n",
      "Epoch 85/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0675 - acc: 0.9332\n",
      "Epoch 00085: val_acc improved from 0.68200 to 0.68600, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0675 - acc: 0.9332 - val_loss: 1.7476 - val_acc: 0.6860\n",
      "Learning rate:  0.0001\n",
      "Epoch 86/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0670 - acc: 0.9330\n",
      "Epoch 00086: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0670 - acc: 0.9330 - val_loss: 1.7452 - val_acc: 0.6840\n",
      "Learning rate:  0.0001\n",
      "Epoch 87/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0664 - acc: 0.9341\n",
      "Epoch 00087: val_acc improved from 0.68600 to 0.68600, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0664 - acc: 0.9341 - val_loss: 1.7541 - val_acc: 0.6860\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Learning rate:  0.0001\n",
      "Epoch 88/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0658 - acc: 0.9344\n",
      "Epoch 00088: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0658 - acc: 0.9344 - val_loss: 1.7468 - val_acc: 0.6780\n",
      "Learning rate:  0.0001\n",
      "Epoch 89/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0655 - acc: 0.9343\n",
      "Epoch 00089: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0656 - acc: 0.9342 - val_loss: 1.7672 - val_acc: 0.6760\n",
      "Learning rate:  0.0001\n",
      "Epoch 90/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0651 - acc: 0.9341\n",
      "Epoch 00090: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0651 - acc: 0.9342 - val_loss: 1.7668 - val_acc: 0.6820\n",
      "Learning rate:  0.0001\n",
      "Epoch 91/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0648 - acc: 0.9357\n",
      "Epoch 00091: val_acc improved from 0.68600 to 0.69000, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0648 - acc: 0.9357 - val_loss: 1.7704 - val_acc: 0.6900\n",
      "Learning rate:  0.0001\n",
      "Epoch 92/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0644 - acc: 0.9348\n",
      "Epoch 00092: val_acc did not improve\n",
      "20000/20000 [==============================] - 80s 4ms/step - loss: 0.0645 - acc: 0.9347 - val_loss: 1.7688 - val_acc: 0.6840\n",
      "Learning rate:  0.0001\n",
      "Epoch 93/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0640 - acc: 0.9358\n",
      "Epoch 00093: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0640 - acc: 0.9357 - val_loss: 1.7954 - val_acc: 0.6800\n",
      "Learning rate:  0.0001\n",
      "Epoch 94/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0637 - acc: 0.9358\n",
      "Epoch 00094: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0637 - acc: 0.9359 - val_loss: 1.7979 - val_acc: 0.6720\n",
      "Learning rate:  0.0001\n",
      "Epoch 95/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0633 - acc: 0.9366\n",
      "Epoch 00095: val_acc did not improve\n",
      "20000/20000 [==============================] - 81s 4ms/step - loss: 0.0633 - acc: 0.9366 - val_loss: 1.8099 - val_acc: 0.6820\n",
      "Learning rate:  0.0001\n",
      "Epoch 96/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0628 - acc: 0.9357\n",
      "Epoch 00096: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.0628 - acc: 0.9358 - val_loss: 1.7989 - val_acc: 0.6820\n",
      "Learning rate:  0.0001\n",
      "Epoch 97/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0625 - acc: 0.9363\n",
      "Epoch 00097: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.0625 - acc: 0.9363 - val_loss: 1.8067 - val_acc: 0.6840\n",
      "Learning rate:  0.0001\n",
      "Epoch 98/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0620 - acc: 0.9366\n",
      "Epoch 00098: val_acc did not improve\n",
      "20000/20000 [==============================] - 82s 4ms/step - loss: 0.0620 - acc: 0.9366 - val_loss: 1.8088 - val_acc: 0.6800\n",
      "Learning rate:  0.0001\n",
      "Epoch 99/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0616 - acc: 0.9361\n",
      "Epoch 00099: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0616 - acc: 0.9362 - val_loss: 1.8229 - val_acc: 0.6800\n",
      "Learning rate:  0.0001\n",
      "Epoch 100/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0614 - acc: 0.9365\n",
      "Epoch 00100: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0614 - acc: 0.9365 - val_loss: 1.8511 - val_acc: 0.6880\n",
      "Learning rate:  0.0001\n",
      "Epoch 101/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0607 - acc: 0.9364\n",
      "Epoch 00101: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0607 - acc: 0.9362 - val_loss: 1.8381 - val_acc: 0.6820\n",
      "Learning rate:  0.0001\n",
      "Epoch 102/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0601 - acc: 0.9372\n",
      "Epoch 00102: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0602 - acc: 0.9371 - val_loss: 1.8337 - val_acc: 0.6720\n",
      "Learning rate:  0.0001\n",
      "Epoch 103/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0596 - acc: 0.9372\n",
      "Epoch 00103: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0596 - acc: 0.9371 - val_loss: 1.8453 - val_acc: 0.6760\n",
      "Learning rate:  0.0001\n",
      "Epoch 104/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0592 - acc: 0.9369\n",
      "Epoch 00104: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0592 - acc: 0.9369 - val_loss: 1.8373 - val_acc: 0.6760\n",
      "Learning rate:  0.0001\n",
      "Epoch 105/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0588 - acc: 0.9381\n",
      "Epoch 00105: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0588 - acc: 0.9381 - val_loss: 1.8490 - val_acc: 0.6720\n",
      "Learning rate:  0.0001\n",
      "Epoch 106/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0581 - acc: 0.9382\n",
      "Epoch 00106: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0581 - acc: 0.9381 - val_loss: 1.8366 - val_acc: 0.6720\n",
      "Learning rate:  0.0001\n",
      "Epoch 107/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0576 - acc: 0.9381\n",
      "Epoch 00107: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0576 - acc: 0.9380 - val_loss: 1.8733 - val_acc: 0.6820\n",
      "Learning rate:  0.0001\n",
      "Epoch 108/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0571 - acc: 0.9384\n",
      "Epoch 00108: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0571 - acc: 0.9383 - val_loss: 1.8534 - val_acc: 0.6780\n",
      "Learning rate:  0.0001\n",
      "Epoch 109/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0564 - acc: 0.9381\n",
      "Epoch 00109: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0567 - acc: 0.9378 - val_loss: 1.8978 - val_acc: 0.6740\n",
      "Learning rate:  0.0001\n",
      "Epoch 110/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0583 - acc: 0.9369\n",
      "Epoch 00110: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0583 - acc: 0.9371 - val_loss: 1.8575 - val_acc: 0.6880\n",
      "Learning rate:  0.0001\n",
      "Epoch 111/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0559 - acc: 0.9388\n",
      "Epoch 00111: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0559 - acc: 0.9388 - val_loss: 1.8460 - val_acc: 0.6780\n",
      "Learning rate:  0.0001\n",
      "Epoch 112/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0555 - acc: 0.9388\n",
      "Epoch 00112: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0555 - acc: 0.9387 - val_loss: 1.8494 - val_acc: 0.6680\n",
      "Learning rate:  0.0001\n",
      "Epoch 113/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0547 - acc: 0.9387\n",
      "Epoch 00113: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0547 - acc: 0.9385 - val_loss: 1.8962 - val_acc: 0.6720\n",
      "Learning rate:  0.0001\n",
      "Epoch 114/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0546 - acc: 0.9395\n",
      "Epoch 00114: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0546 - acc: 0.9394 - val_loss: 1.9005 - val_acc: 0.6800\n",
      "Learning rate:  0.0001\n",
      "Epoch 115/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0538 - acc: 0.9389\n",
      "Epoch 00115: val_acc did not improve\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0538 - acc: 0.9388 - val_loss: 1.9350 - val_acc: 0.6760\n",
      "Learning rate:  0.0001\n",
      "Epoch 116/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0532 - acc: 0.9393\n",
      "Epoch 00116: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0532 - acc: 0.9392 - val_loss: 1.8662 - val_acc: 0.6780\n",
      "Learning rate:  0.0001\n",
      "Epoch 117/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0530 - acc: 0.9393\n",
      "Epoch 00117: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0530 - acc: 0.9393 - val_loss: 1.8919 - val_acc: 0.6820\n",
      "Learning rate:  0.0001\n",
      "Epoch 118/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0523 - acc: 0.9403\n",
      "Epoch 00118: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0524 - acc: 0.9403 - val_loss: 1.9177 - val_acc: 0.6800\n",
      "Learning rate:  0.0001\n",
      "Epoch 119/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0530 - acc: 0.9386\n",
      "Epoch 00119: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0530 - acc: 0.9386 - val_loss: 1.8767 - val_acc: 0.6800\n",
      "Learning rate:  0.0001\n",
      "Epoch 120/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0519 - acc: 0.9399\n",
      "Epoch 00120: val_acc improved from 0.69000 to 0.70200, saving model to /Users/1j1060/Research/Codes/Transfer/Runs-neurips-2019/saved_models/resnet_target_model_weighted.h5\n",
      "20000/20000 [==============================] - 83s 4ms/step - loss: 0.0519 - acc: 0.9398 - val_loss: 1.8863 - val_acc: 0.7020\n",
      "Learning rate:  0.0001\n",
      "Epoch 121/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0511 - acc: 0.9398\n",
      "Epoch 00121: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0512 - acc: 0.9398 - val_loss: 1.8754 - val_acc: 0.6840\n",
      "Learning rate:  1e-05\n",
      "Epoch 122/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0507 - acc: 0.9401\n",
      "Epoch 00122: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0507 - acc: 0.9401 - val_loss: 1.8750 - val_acc: 0.6860\n",
      "Learning rate:  1e-05\n",
      "Epoch 123/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0506 - acc: 0.9399\n",
      "Epoch 00123: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0506 - acc: 0.9400 - val_loss: 1.8796 - val_acc: 0.6820\n",
      "Learning rate:  1e-05\n",
      "Epoch 124/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0505 - acc: 0.9405\n",
      "Epoch 00124: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0505 - acc: 0.9405 - val_loss: 1.8852 - val_acc: 0.6800\n",
      "Learning rate:  1e-05\n",
      "Epoch 125/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0504 - acc: 0.9403\n",
      "Epoch 00125: val_acc did not improve\n",
      "20000/20000 [==============================] - 84s 4ms/step - loss: 0.0505 - acc: 0.9404 - val_loss: 1.8907 - val_acc: 0.6800\n",
      "Learning rate:  1e-05\n",
      "Epoch 126/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0503 - acc: 0.9402\n",
      "Epoch 00126: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0503 - acc: 0.9401 - val_loss: 1.8920 - val_acc: 0.6840\n",
      "Learning rate:  1e-05\n",
      "Epoch 127/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0503 - acc: 0.9411\n",
      "Epoch 00127: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0503 - acc: 0.9412 - val_loss: 1.8953 - val_acc: 0.6840\n",
      "Learning rate:  1e-05\n",
      "Epoch 128/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0503 - acc: 0.9401\n",
      "Epoch 00128: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0503 - acc: 0.9401 - val_loss: 1.8953 - val_acc: 0.6840\n",
      "Learning rate:  1e-05\n",
      "Epoch 129/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0502 - acc: 0.9398\n",
      "Epoch 00129: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0502 - acc: 0.9397 - val_loss: 1.8910 - val_acc: 0.6860\n",
      "Learning rate:  1e-05\n",
      "Epoch 130/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0501 - acc: 0.9398\n",
      "Epoch 00130: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0501 - acc: 0.9398 - val_loss: 1.8937 - val_acc: 0.6840\n",
      "Learning rate:  1e-05\n",
      "Epoch 131/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0501 - acc: 0.9403\n",
      "Epoch 00131: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0501 - acc: 0.9403 - val_loss: 1.8931 - val_acc: 0.6860\n",
      "Learning rate:  1e-05\n",
      "Epoch 132/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0500 - acc: 0.9399\n",
      "Epoch 00132: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0500 - acc: 0.9398 - val_loss: 1.9057 - val_acc: 0.6860\n",
      "Learning rate:  1e-05\n",
      "Epoch 133/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0500 - acc: 0.9395\n",
      "Epoch 00133: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0500 - acc: 0.9396 - val_loss: 1.9008 - val_acc: 0.6820\n",
      "Learning rate:  1e-05\n",
      "Epoch 134/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0498 - acc: 0.9404\n",
      "Epoch 00134: val_acc did not improve\n",
      "20000/20000 [==============================] - 85s 4ms/step - loss: 0.0498 - acc: 0.9404 - val_loss: 1.9022 - val_acc: 0.6800\n",
      "Learning rate:  1e-05\n",
      "Epoch 135/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0497 - acc: 0.9405\n",
      "Epoch 00135: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0497 - acc: 0.9405 - val_loss: 1.8961 - val_acc: 0.6820\n",
      "Learning rate:  1e-05\n",
      "Epoch 136/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0496 - acc: 0.9402\n",
      "Epoch 00136: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0496 - acc: 0.9402 - val_loss: 1.8998 - val_acc: 0.6820\n",
      "Learning rate:  1e-05\n",
      "Epoch 137/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0496 - acc: 0.9409\n",
      "Epoch 00137: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0496 - acc: 0.9409 - val_loss: 1.9124 - val_acc: 0.6820\n",
      "Learning rate:  1e-05\n",
      "Epoch 138/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0494 - acc: 0.9411\n",
      "Epoch 00138: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0494 - acc: 0.9410 - val_loss: 1.9086 - val_acc: 0.6840\n",
      "Learning rate:  1e-05\n",
      "Epoch 139/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0494 - acc: 0.9407\n",
      "Epoch 00139: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0494 - acc: 0.9405 - val_loss: 1.9020 - val_acc: 0.6820\n",
      "Learning rate:  1e-05\n",
      "Epoch 140/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0493 - acc: 0.9403\n",
      "Epoch 00140: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0493 - acc: 0.9403 - val_loss: 1.8963 - val_acc: 0.6780\n",
      "Learning rate:  1e-05\n",
      "Epoch 141/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0492 - acc: 0.9405\n",
      "Epoch 00141: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0492 - acc: 0.9403 - val_loss: 1.8969 - val_acc: 0.6800\n",
      "Learning rate:  1e-05\n",
      "Epoch 142/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0490 - acc: 0.9401\n",
      "Epoch 00142: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0490 - acc: 0.9400 - val_loss: 1.9065 - val_acc: 0.6820\n",
      "Learning rate:  1e-05\n",
      "Epoch 143/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0491 - acc: 0.9409\n",
      "Epoch 00143: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0491 - acc: 0.9409 - val_loss: 1.9020 - val_acc: 0.6780\n",
      "Learning rate:  1e-05\n",
      "Epoch 144/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0489 - acc: 0.9410\n",
      "Epoch 00144: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0489 - acc: 0.9410 - val_loss: 1.9113 - val_acc: 0.6800\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Learning rate:  1e-05\n",
      "Epoch 145/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0487 - acc: 0.9404\n",
      "Epoch 00145: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0487 - acc: 0.9403 - val_loss: 1.9060 - val_acc: 0.6840\n",
      "Learning rate:  1e-05\n",
      "Epoch 146/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0487 - acc: 0.9407\n",
      "Epoch 00146: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0487 - acc: 0.9407 - val_loss: 1.8993 - val_acc: 0.6780\n",
      "Learning rate:  1e-05\n",
      "Epoch 147/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0486 - acc: 0.9405\n",
      "Epoch 00147: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0486 - acc: 0.9405 - val_loss: 1.9037 - val_acc: 0.6820\n",
      "Learning rate:  1e-05\n",
      "Epoch 148/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0485 - acc: 0.9410\n",
      "Epoch 00148: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0485 - acc: 0.9411 - val_loss: 1.8996 - val_acc: 0.6760\n",
      "Learning rate:  1e-05\n",
      "Epoch 149/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0483 - acc: 0.9409\n",
      "Epoch 00149: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0483 - acc: 0.9408 - val_loss: 1.9071 - val_acc: 0.6780\n",
      "Learning rate:  1e-05\n",
      "Epoch 150/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0483 - acc: 0.9400\n",
      "Epoch 00150: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0484 - acc: 0.9401 - val_loss: 1.8995 - val_acc: 0.6800\n",
      "Learning rate:  1e-05\n",
      "Epoch 151/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0483 - acc: 0.9410\n",
      "Epoch 00151: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0483 - acc: 0.9411 - val_loss: 1.9181 - val_acc: 0.6800\n",
      "Learning rate:  1e-05\n",
      "Epoch 152/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0481 - acc: 0.9416\n",
      "Epoch 00152: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0481 - acc: 0.9416 - val_loss: 1.9218 - val_acc: 0.6840\n",
      "Learning rate:  1e-05\n",
      "Epoch 153/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0480 - acc: 0.9410\n",
      "Epoch 00153: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0480 - acc: 0.9410 - val_loss: 1.9119 - val_acc: 0.6780\n",
      "Learning rate:  1e-05\n",
      "Epoch 154/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0479 - acc: 0.9404\n",
      "Epoch 00154: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0479 - acc: 0.9405 - val_loss: 1.9089 - val_acc: 0.6840\n",
      "Learning rate:  1e-05\n",
      "Epoch 155/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0478 - acc: 0.9410\n",
      "Epoch 00155: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0478 - acc: 0.9410 - val_loss: 1.9190 - val_acc: 0.6800\n",
      "Learning rate:  1e-05\n",
      "Epoch 156/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0477 - acc: 0.9412\n",
      "Epoch 00156: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0477 - acc: 0.9412 - val_loss: 1.9179 - val_acc: 0.6820\n",
      "Learning rate:  1e-05\n",
      "Epoch 157/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0477 - acc: 0.9413\n",
      "Epoch 00157: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0477 - acc: 0.9413 - val_loss: 1.9207 - val_acc: 0.6820\n",
      "Learning rate:  1e-05\n",
      "Epoch 158/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0476 - acc: 0.9403\n",
      "Epoch 00158: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.0476 - acc: 0.9403 - val_loss: 1.9211 - val_acc: 0.6780\n",
      "Learning rate:  1e-05\n",
      "Epoch 159/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0475 - acc: 0.9403\n",
      "Epoch 00159: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0475 - acc: 0.9403 - val_loss: 1.9237 - val_acc: 0.6800\n",
      "Learning rate:  1e-05\n",
      "Epoch 160/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0474 - acc: 0.9411\n",
      "Epoch 00160: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0474 - acc: 0.9411 - val_loss: 1.9182 - val_acc: 0.6760\n",
      "Learning rate:  1e-05\n",
      "Epoch 161/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0472 - acc: 0.9414\n",
      "Epoch 00161: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0472 - acc: 0.9414 - val_loss: 1.9108 - val_acc: 0.6820\n",
      "Learning rate:  1e-06\n",
      "Epoch 162/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0473 - acc: 0.9411\n",
      "Epoch 00162: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0473 - acc: 0.9410 - val_loss: 1.9165 - val_acc: 0.6840\n",
      "Learning rate:  1e-06\n",
      "Epoch 163/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0472 - acc: 0.9403\n",
      "Epoch 00163: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0472 - acc: 0.9403 - val_loss: 1.9189 - val_acc: 0.6840\n",
      "Learning rate:  1e-06\n",
      "Epoch 164/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0472 - acc: 0.9415\n",
      "Epoch 00164: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0473 - acc: 0.9415 - val_loss: 1.9207 - val_acc: 0.6860\n",
      "Learning rate:  1e-06\n",
      "Epoch 165/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0472 - acc: 0.9401\n",
      "Epoch 00165: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0472 - acc: 0.9402 - val_loss: 1.9205 - val_acc: 0.6860\n",
      "Learning rate:  1e-06\n",
      "Epoch 166/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0473 - acc: 0.9407\n",
      "Epoch 00166: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0473 - acc: 0.9407 - val_loss: 1.9226 - val_acc: 0.6900\n",
      "Learning rate:  1e-06\n",
      "Epoch 167/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0472 - acc: 0.9415\n",
      "Epoch 00167: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0472 - acc: 0.9414 - val_loss: 1.9230 - val_acc: 0.6880\n",
      "Learning rate:  1e-06\n",
      "Epoch 168/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0472 - acc: 0.9409\n",
      "Epoch 00168: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0472 - acc: 0.9410 - val_loss: 1.9217 - val_acc: 0.6880\n",
      "Learning rate:  1e-06\n",
      "Epoch 169/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0472 - acc: 0.9411\n",
      "Epoch 00169: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0472 - acc: 0.9410 - val_loss: 1.9216 - val_acc: 0.6840\n",
      "Learning rate:  1e-06\n",
      "Epoch 170/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0472 - acc: 0.9414\n",
      "Epoch 00170: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0472 - acc: 0.9414 - val_loss: 1.9190 - val_acc: 0.6840\n",
      "Learning rate:  1e-06\n",
      "Epoch 171/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0472 - acc: 0.9417\n",
      "Epoch 00171: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0472 - acc: 0.9418 - val_loss: 1.9214 - val_acc: 0.6880\n",
      "Learning rate:  1e-06\n",
      "Epoch 172/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0471 - acc: 0.9407\n",
      "Epoch 00172: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0471 - acc: 0.9407 - val_loss: 1.9208 - val_acc: 0.6880\n",
      "Learning rate:  1e-06\n",
      "Epoch 173/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0471 - acc: 0.9414\n",
      "Epoch 00173: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0471 - acc: 0.9414 - val_loss: 1.9194 - val_acc: 0.6860\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Learning rate:  1e-06\n",
      "Epoch 174/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0472 - acc: 0.9414\n",
      "Epoch 00174: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0472 - acc: 0.9415 - val_loss: 1.9188 - val_acc: 0.6880\n",
      "Learning rate:  1e-06\n",
      "Epoch 175/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0471 - acc: 0.9411\n",
      "Epoch 00175: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0471 - acc: 0.9410 - val_loss: 1.9202 - val_acc: 0.6880\n",
      "Learning rate:  1e-06\n",
      "Epoch 176/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0471 - acc: 0.9408\n",
      "Epoch 00176: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0471 - acc: 0.9408 - val_loss: 1.9205 - val_acc: 0.6880\n",
      "Learning rate:  1e-06\n",
      "Epoch 177/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0472 - acc: 0.9418\n",
      "Epoch 00177: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0472 - acc: 0.9419 - val_loss: 1.9215 - val_acc: 0.6920\n",
      "Learning rate:  1e-06\n",
      "Epoch 178/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9408\n",
      "Epoch 00178: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9409 - val_loss: 1.9202 - val_acc: 0.6900\n",
      "Learning rate:  1e-06\n",
      "Epoch 179/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0471 - acc: 0.9412\n",
      "Epoch 00179: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0471 - acc: 0.9412 - val_loss: 1.9220 - val_acc: 0.6920\n",
      "Learning rate:  1e-06\n",
      "Epoch 180/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0471 - acc: 0.9412\n",
      "Epoch 00180: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0471 - acc: 0.9412 - val_loss: 1.9226 - val_acc: 0.6900\n",
      "Learning rate:  1e-06\n",
      "Epoch 181/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9410\n",
      "Epoch 00181: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9408 - val_loss: 1.9228 - val_acc: 0.6920\n",
      "Learning rate:  5e-07\n",
      "Epoch 182/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0471 - acc: 0.9412\n",
      "Epoch 00182: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0471 - acc: 0.9412 - val_loss: 1.9210 - val_acc: 0.6920\n",
      "Learning rate:  5e-07\n",
      "Epoch 183/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9422\n",
      "Epoch 00183: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9421 - val_loss: 1.9209 - val_acc: 0.6880\n",
      "Learning rate:  5e-07\n",
      "Epoch 184/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0471 - acc: 0.9415\n",
      "Epoch 00184: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0471 - acc: 0.9412 - val_loss: 1.9230 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 185/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9412\n",
      "Epoch 00185: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9411 - val_loss: 1.9236 - val_acc: 0.6920\n",
      "Learning rate:  5e-07\n",
      "Epoch 186/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9411\n",
      "Epoch 00186: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9411 - val_loss: 1.9233 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 187/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9410\n",
      "Epoch 00187: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0471 - acc: 0.9410 - val_loss: 1.9225 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 188/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9410\n",
      "Epoch 00188: val_acc did not improve\n",
      "20000/20000 [==============================] - 86s 4ms/step - loss: 0.0470 - acc: 0.9410 - val_loss: 1.9250 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 189/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9415\n",
      "Epoch 00189: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9415 - val_loss: 1.9258 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 190/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9410\n",
      "Epoch 00190: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9411 - val_loss: 1.9255 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 191/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9414\n",
      "Epoch 00191: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9412 - val_loss: 1.9238 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 192/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9416\n",
      "Epoch 00192: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9416 - val_loss: 1.9254 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 193/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0471 - acc: 0.9412\n",
      "Epoch 00193: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0471 - acc: 0.9412 - val_loss: 1.9238 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 194/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9418\n",
      "Epoch 00194: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9416 - val_loss: 1.9238 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 195/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9415\n",
      "Epoch 00195: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0471 - acc: 0.9416 - val_loss: 1.9239 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 196/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9415\n",
      "Epoch 00196: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9414 - val_loss: 1.9210 - val_acc: 0.6840\n",
      "Learning rate:  5e-07\n",
      "Epoch 197/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9409\n",
      "Epoch 00197: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9408 - val_loss: 1.9215 - val_acc: 0.6880\n",
      "Learning rate:  5e-07\n",
      "Epoch 198/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9402\n",
      "Epoch 00198: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0470 - acc: 0.9401 - val_loss: 1.9218 - val_acc: 0.6840\n",
      "Learning rate:  5e-07\n",
      "Epoch 199/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0469 - acc: 0.9410\n",
      "Epoch 00199: val_acc did not improve\n",
      "20000/20000 [==============================] - 87s 4ms/step - loss: 0.0469 - acc: 0.9409 - val_loss: 1.9245 - val_acc: 0.6900\n",
      "Learning rate:  5e-07\n",
      "Epoch 200/200\n",
      "19968/20000 [============================>.] - ETA: 0s - loss: 0.0470 - acc: 0.9412\n",
      "Epoch 00200: val_acc did not improve\n",
      "20000/20000 [==============================] - 88s 4ms/step - loss: 0.0470 - acc: 0.9412 - val_loss: 1.9225 - val_acc: 0.6880\n",
      "10000/10000 [==============================] - 15s 2ms/step\n",
      "Accuracy of Prof-Weighted Simple Model: 0.6563\n"
     ]
    }
   ],
   "source": [
    "a.explain(x_train2,y_train2,x_test,y_test,resnet_v1,hps,list_probe_filenames,2,6,'neural_keras')"
   ]
  }
 ],
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