main.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import utilys as ut\n",
    "import os\n",
    "from scipy.misc import imread,imresize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1623 total character classes\n",
      "1423 characters assigned for training, 200 characters assigned for validation\n"
     ]
    }
   ],
   "source": [
    "width = 20\n",
    "\n",
    "# gather data paths\n",
    "subfolds = ut.extend_children('data','')\n",
    "datafolds = [subfolds[0],subfolds[3]]\n",
    "alphabets = ut.extend_generation(datafolds,'')\n",
    "charpaths = ut.extend_generation(alphabets,'')\n",
    "chars_dataset = [v.split('/')[2]+'/'+v.split('/')[3] for v in charpaths]\n",
    "\n",
    "# index-value conversion dictionaries for character set\n",
    "i2v = {i:v for i, v in enumerate(chars_dataset)}\n",
    "v2i = {v:i for i, v in enumerate(chars_dataset)}\n",
    "\n",
    "# get size of dataset\n",
    "mc_dataset = len(charpaths)\n",
    "print(mc_dataset,'total character classes')\n",
    "\n",
    "# train split\n",
    "mc_train = 1423\n",
    "chars_train = chars_dataset[:mc_train]\n",
    "classes_train = [v2i[v] for v in chars_train]\n",
    "\n",
    "# validation split\n",
    "mc_val = mc_dataset-mc_train\n",
    "chars_val = chars_dataset[-mc_val:]\n",
    "classes_val = [v2i[v] for v in chars_val]\n",
    "\n",
    "print('%s characters assigned for training, %s characters assigned for validation'%(mc_train,mc_val))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0/1623 character folders loaded\n",
      "200/1623 character folders loaded\n",
      "400/1623 character folders loaded\n",
      "600/1623 character folders loaded\n",
      "800/1623 character folders loaded\n",
      "1000/1623 character folders loaded\n",
      "1200/1623 character folders loaded\n",
      "1400/1623 character folders loaded\n",
      "1600/1623 character folders loaded\n"
     ]
    }
   ],
   "source": [
    "# load images from character paths\n",
    "imgs_dataset = []\n",
    "for i, charfold in enumerate(charpaths):\n",
    "    if i%200==0:\n",
    "        print('%s/%s character folders loaded'%(i,mc_dataset))\n",
    "    imgs_dataset.append([ ut.load_image(imgpath,(width,width))/127.5-1 for imgpath in ut.extend_children(charfold,'.png') ] )\n",
    "# access imgs_dataset [ character index ] [ sample index ] [ row,col ]\n",
    "\n",
    "# split images between train and validation sets\n",
    "imgs_train = imgs_dataset[:mc_train]\n",
    "imgs_val = imgs_dataset[-mc_val:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "#classes_val, imgs_val = ut.shuffle_xy(classes_val,imgs_val,7)\n",
    "\n",
    "n_classes = 5\n",
    "memory_size = 128 # number of features per entry\n",
    "memory_dim = 40 # number of entries in memory\n",
    "learning_rate = 1e-3\n",
    "batch_size = 16\n",
    "\n",
    "n_inputs = width*width+n_classes\n",
    "n_hnodes = 200\n",
    "n_outputs = n_classes\n",
    "mem_size = memory_size\n",
    "mem_dim = memory_dim\n",
    "\n",
    "\n",
    "weights = lambda shape,name: tf.Variable(tf.truncated_normal(shape, stddev=0.1),name=name)\n",
    "biases = lambda shape,name: tf.Variable(tf.constant(0.1, shape=shape),name=name)\n",
    "conv2d = lambda x, W: tf.nn.conv2d(x, W, strides=[1, 2, 2, 1], padding='SAME')\n",
    "max_pool = lambda x: tf.nn.max_pool(x, ksize=[1, 2, 2, 1], strides=[1, 2, 2, 1], padding='SAME')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "from MANN import MANN\n",
    "\n",
    "X = tf.placeholder(tf.float32, shape=[batch_size, None, width, width])\n",
    "y = tf.placeholder(tf.float32, shape=[batch_size, None, n_classes])\n",
    "\n",
    "X_mat = tf.transpose(tf.reshape(X,[batch_size,-1,width*width]),perm=[1,0,2])\n",
    "y_tr = tf.transpose(y,perm=[1,0,2])\n",
    "y_tm1 = tf.concat([tf.zeros([1,batch_size,n_classes]),y_tr[:-1,:]],0)\n",
    "\n",
    "if False:\n",
    "    W_c1 = weights([5,5,1,2],'Conv1_Weights')\n",
    "    b_c1 = biases([2],'Conv1_Biases')\n",
    "    W_c2 = weights([5,5,2,4],'Conv2_Weights')\n",
    "    b_c2 = biases([4],'Conv2_Biases')\n",
    "\n",
    "    # 100x100x1\n",
    "    h_c1 = tf.nn.relu(conv2d(x_image,W_c1)+b_c1)\n",
    "    # 50x50x2\n",
    "    h_p1 = max_pool(h_c1)\n",
    "    # 25x25x2\n",
    "    h_c2 = tf.nn.relu(conv2d(h_p1,W_c2)+b_c2)\n",
    "    # 13x13x4\n",
    "    h_p2 = max_pool(h_c2)\n",
    "    # 7x7x4\n",
    "    h_conv = tf.reshape(h_p2,[-1,7*7*4])\n",
    "    # 196\n",
    "\n",
    "X_mann = tf.concat([X_mat,y_tm1],-1)\n",
    "\n",
    "MANN1 = MANN(n_inputs,n_hnodes,n_classes,memory_size,memory_dim,X_mann,batch_size)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n_xh = n_inputs+n_hnodes\n",
    "n_hr = n_hnodes+mem_dim\n",
    "W_init = tf.contrib.layers.xavier_initializer()\n",
    "b_init = tf.constant_initializer(0)\n",
    "#with tf.variable_scope('Weights', reuse=True):\n",
    "if False:\n",
    "    # LSTM Gate Weights\n",
    "    W_gf = tf.get_variable('W_forget_gate', shape=[n_xh,n_hnodes], initializer=W_init)\n",
    "    b_gf = tf.get_variable('b_forget_gate', shape=[n_hnodes], initializer=b_init)\n",
    "    W_gi = tf.get_variable('W_input_gate', shape=[n_xh,n_hnodes], initializer=W_init)\n",
    "    b_gi = tf.get_variable('b_input_gate', shape=[n_hnodes], initializer=b_init)\n",
    "    W_go = tf.get_variable('W_output_gate', shape=[n_xh,n_hnodes], initializer=W_init)\n",
    "    b_go = tf.get_variable('b_output_gate', shape=[n_hnodes], initializer=b_init)\n",
    "    # LSTM Tanh Weights\n",
    "    W_u = tf.get_variable('W_remember', shape=[n_xh,n_hnodes], initializer=W_init)\n",
    "    b_u = tf.get_variable('b_remember', shape=[n_hnodes], initializer=b_init)\n",
    "    # Controller Weights\n",
    "    W_kr = tf.get_variable('W_read_key', shape=[n_hnodes,mem_dim], initializer=W_init)\n",
    "    b_kr = tf.get_variable('b_read_key', shape=[mem_dim], initializer=b_init)\n",
    "    W_kw = tf.get_variable('W_write_key', shape=[n_hnodes,mem_dim], initializer=W_init)\n",
    "    b_kw = tf.get_variable('b_write_key', shape=[mem_dim], initializer=b_init)\n",
    "    alpha = tf.get_variable('sigmoid_alpha', shape=[1,1], initializer=b_init)\n",
    "    # Logit Weights\n",
    "    W_o = tf.get_variable('W_output', shape=[n_hr,n_outputs], initializer=W_init)\n",
    "    b_o = tf.get_variable('b_output', shape=[n_outputs], initializer=b_init)\n",
    "    pass\n",
    "#thetas = [W_gf,b_gf,W_gi,b_gi,W_go,b_go,W_u,b_u,W_kr,b_kr,W_kw,alpha,b_kw,W_o,b_o]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(?, 16, 405) (?, 16, 5) <unknown>\n"
     ]
    }
   ],
   "source": [
    "M, h, c, wu, wr, r, o = MANN1\n",
    "\n",
    "xentropy = tf.nn.softmax_cross_entropy_with_logits(labels=y_tr,logits=o)\n",
    "loss = tf.reduce_mean(xentropy)\n",
    "\n",
    "trainable_variables = tf.trainable_variables()\n",
    "optimizer = tf.train.AdamOptimizer(learning_rate)\n",
    "grads, _ = tf.clip_by_global_norm(tf.gradients(loss,trainable_variables),30)\n",
    "train_step = optimizer.apply_gradients(zip(grads,trainable_variables))\n",
    "\n",
    "correct_prediction = tf.equal(tf.argmax(o, -1), tf.argmax(y_tr, -1))\n",
    "accuracy = tf.reduce_mean(tf.cast(correct_prediction, tf.float32))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "sess = tf.Session()\n",
    "sess.run(tf.global_variables_initializer())\n",
    "saver = tf.train.Saver()\n",
    "savedir = './saved_models_omniglot/Mod1'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "INFO:tensorflow:Restoring parameters from ./saved_models_omniglot/Mod1\\400/Model.ckpt\n",
      "Epoch 1 starting..\n",
      "Epoch 1 / Batch (1/17) / Accuracy 0.7113 / Loss 0.671945\n",
      "Epoch 1 / Batch (2/17) / Accuracy 0.7450 / Loss 0.644811\n",
      "Epoch 1 / Batch (3/17) / Accuracy 0.7237 / Loss 0.671712\n",
      "Epoch 1 / Batch (4/17) / Accuracy 0.7106 / Loss 0.681302\n",
      "Epoch 1 / Batch (5/17) / Accuracy 0.7369 / Loss 0.638603\n",
      "Epoch 1 / Batch (6/17) / Accuracy 0.7556 / Loss 0.609996\n",
      "Epoch 1 / Batch (7/17) / Accuracy 0.7437 / Loss 0.645145\n",
      "Epoch 1 / Batch (8/17) / Accuracy 0.7294 / Loss 0.658106\n",
      "Epoch 1 / Batch (9/17) / Accuracy 0.7256 / Loss 0.660708\n",
      "Epoch 1 / Batch (10/17) / Accuracy 0.7344 / Loss 0.639564\n",
      "Epoch 1 / Batch (11/17) / Accuracy 0.7244 / Loss 0.659034\n",
      "Epoch 1 / Batch (12/17) / Accuracy 0.6950 / Loss 0.724729\n",
      "Epoch 1 / Batch (13/17) / Accuracy 0.7506 / Loss 0.624792\n",
      "Epoch 1 / Batch (14/17) / Accuracy 0.7344 / Loss 0.651112\n",
      "Epoch 1 / Batch (15/17) / Accuracy 0.7212 / Loss 0.650918\n",
      "Epoch 1 / Batch (16/17) / Accuracy 0.7656 / Loss 0.584192\n",
      "Epoch 1 / Batch (17/17) / Accuracy 0.7444 / Loss 0.633408\n",
      "Epoch 1 complete, 6.1542627811431885 seconds elapsed\n",
      "\n",
      "Epoch 2 starting..\n",
      "Epoch 2 / Batch (1/17) / Accuracy 0.6856 / Loss 0.703257\n",
      "Epoch 2 / Batch (2/17) / Accuracy 0.7356 / Loss 0.613349\n",
      "Epoch 2 / Batch (3/17) / Accuracy 0.7225 / Loss 0.655898\n",
      "Epoch 2 / Batch (4/17) / Accuracy 0.7387 / Loss 0.639761\n",
      "Epoch 2 / Batch (5/17) / Accuracy 0.7406 / Loss 0.622548\n",
      "Epoch 2 / Batch (6/17) / Accuracy 0.7381 / Loss 0.629597\n",
      "Epoch 2 / Batch (7/17) / Accuracy 0.7500 / Loss 0.606462\n",
      "Epoch 2 / Batch (8/17) / Accuracy 0.7325 / Loss 0.620954\n",
      "Epoch 2 / Batch (9/17) / Accuracy 0.7325 / Loss 0.665826\n",
      "Epoch 2 / Batch (10/17) / Accuracy 0.7594 / Loss 0.621279\n",
      "Epoch 2 / Batch (11/17) / Accuracy 0.7475 / Loss 0.625986\n",
      "Epoch 2 / Batch (12/17) / Accuracy 0.7444 / Loss 0.633516\n",
      "Epoch 2 / Batch (13/17) / Accuracy 0.7831 / Loss 0.564727\n",
      "Epoch 2 / Batch (14/17) / Accuracy 0.7144 / Loss 0.677993\n",
      "Epoch 2 / Batch (15/17) / Accuracy 0.7950 / Loss 0.560948\n",
      "Epoch 2 / Batch (16/17) / Accuracy 0.7444 / Loss 0.617777\n",
      "Epoch 2 / Batch (17/17) / Accuracy 0.7469 / Loss 0.633821\n",
      "Epoch 2 complete, 6.360037326812744 seconds elapsed\n",
      "\n",
      "Epoch 3 starting..\n",
      "Epoch 3 / Batch (1/17) / Accuracy 0.7656 / Loss 0.587297\n",
      "Epoch 3 / Batch (2/17) / Accuracy 0.7869 / Loss 0.544838\n",
      "Epoch 3 / Batch (3/17) / Accuracy 0.7456 / Loss 0.651336\n",
      "Epoch 3 / Batch (4/17) / Accuracy 0.7237 / Loss 0.656665\n",
      "Epoch 3 / Batch (5/17) / Accuracy 0.7881 / Loss 0.566876\n",
      "Epoch 3 / Batch (6/17) / Accuracy 0.7206 / Loss 0.654445\n",
      "Epoch 3 / Batch (7/17) / Accuracy 0.7588 / Loss 0.606446\n",
      "Epoch 3 / Batch (8/17) / Accuracy 0.7269 / Loss 0.658744\n",
      "Epoch 3 / Batch (9/17) / Accuracy 0.7600 / Loss 0.606615\n",
      "Epoch 3 / Batch (10/17) / Accuracy 0.7588 / Loss 0.598105\n",
      "Epoch 3 / Batch (11/17) / Accuracy 0.7287 / Loss 0.670858\n",
      "Epoch 3 / Batch (12/17) / Accuracy 0.7088 / Loss 0.649571\n",
      "Epoch 3 / Batch (13/17) / Accuracy 0.7394 / Loss 0.646979\n",
      "Epoch 3 / Batch (14/17) / Accuracy 0.7706 / Loss 0.577017\n",
      "Epoch 3 / Batch (15/17) / Accuracy 0.7763 / Loss 0.578418\n",
      "Epoch 3 / Batch (16/17) / Accuracy 0.7394 / Loss 0.622271\n",
      "Epoch 3 / Batch (17/17) / Accuracy 0.7556 / Loss 0.603637\n",
      "Epoch 3 complete, 6.405174255371094 seconds elapsed\n",
      "\n",
      "Epoch 4 starting..\n",
      "Epoch 4 / Batch (1/17) / Accuracy 0.7125 / Loss 0.686879\n",
      "Epoch 4 / Batch (2/17) / Accuracy 0.7337 / Loss 0.633556\n",
      "Epoch 4 / Batch (3/17) / Accuracy 0.7331 / Loss 0.650190\n",
      "Epoch 4 / Batch (4/17) / Accuracy 0.7350 / Loss 0.655358\n",
      "Epoch 4 / Batch (5/17) / Accuracy 0.6994 / Loss 0.691910\n",
      "Epoch 4 / Batch (6/17) / Accuracy 0.7575 / Loss 0.594300\n",
      "Epoch 4 / Batch (7/17) / Accuracy 0.7000 / Loss 0.655379\n",
      "Epoch 4 / Batch (8/17) / Accuracy 0.6806 / Loss 0.773270\n",
      "Epoch 4 / Batch (9/17) / Accuracy 0.7100 / Loss 0.695913\n",
      "Epoch 4 / Batch (10/17) / Accuracy 0.6756 / Loss 0.782160\n",
      "Epoch 4 / Batch (11/17) / Accuracy 0.7350 / Loss 0.622593\n",
      "Epoch 4 / Batch (12/17) / Accuracy 0.7256 / Loss 0.691142\n",
      "Epoch 4 / Batch (13/17) / Accuracy 0.6675 / Loss 0.804088\n",
      "Epoch 4 / Batch (14/17) / Accuracy 0.7406 / Loss 0.599814\n",
      "Epoch 4 / Batch (15/17) / Accuracy 0.7644 / Loss 0.581925\n",
      "Epoch 4 / Batch (16/17) / Accuracy 0.7200 / Loss 0.644410\n",
      "Epoch 4 / Batch (17/17) / Accuracy 0.7356 / Loss 0.648121\n",
      "Epoch 4 complete, 6.621491193771362 seconds elapsed\n",
      "\n",
      "Epoch 5 starting..\n",
      "Epoch 5 / Batch (1/17) / Accuracy 0.7644 / Loss 0.579350\n",
      "Epoch 5 / Batch (2/17) / Accuracy 0.7262 / Loss 0.658934\n",
      "Epoch 5 / Batch (3/17) / Accuracy 0.7219 / Loss 0.688552\n",
      "Epoch 5 / Batch (4/17) / Accuracy 0.7394 / Loss 0.619770\n",
      "Epoch 5 / Batch (5/17) / Accuracy 0.7619 / Loss 0.641135\n",
      "Epoch 5 / Batch (6/17) / Accuracy 0.7581 / Loss 0.634418\n",
      "Epoch 5 / Batch (7/17) / Accuracy 0.7056 / Loss 0.697733\n",
      "Epoch 5 / Batch (8/17) / Accuracy 0.7575 / Loss 0.575508\n",
      "Epoch 5 / Batch (9/17) / Accuracy 0.7525 / Loss 0.663904\n",
      "Epoch 5 / Batch (10/17) / Accuracy 0.7250 / Loss 0.687159\n",
      "Epoch 5 / Batch (11/17) / Accuracy 0.6856 / Loss 0.728146\n",
      "Epoch 5 / Batch (12/17) / Accuracy 0.7581 / Loss 0.632369\n",
      "Epoch 5 / Batch (13/17) / Accuracy 0.7131 / Loss 0.722245\n",
      "Epoch 5 / Batch (14/17) / Accuracy 0.7306 / Loss 0.650595\n",
      "Epoch 5 / Batch (15/17) / Accuracy 0.7319 / Loss 0.674172\n",
      "Epoch 5 / Batch (16/17) / Accuracy 0.6944 / Loss 0.735362\n",
      "Epoch 5 / Batch (17/17) / Accuracy 0.7150 / Loss 0.743080\n",
      "Epoch 5 complete, 6.378998517990112 seconds elapsed\n",
      "\n",
      "Epoch 6 starting..\n",
      "Epoch 6 / Batch (1/17) / Accuracy 0.7631 / Loss 0.575369\n",
      "Epoch 6 / Batch (2/17) / Accuracy 0.7400 / Loss 0.642609\n",
      "Epoch 6 / Batch (3/17) / Accuracy 0.7269 / Loss 0.634860\n",
      "Epoch 6 / Batch (4/17) / Accuracy 0.7219 / Loss 0.647871\n",
      "Epoch 6 / Batch (5/17) / Accuracy 0.7588 / Loss 0.597021\n",
      "Epoch 6 / Batch (6/17) / Accuracy 0.7331 / Loss 0.649076\n",
      "Epoch 6 / Batch (7/17) / Accuracy 0.7269 / Loss 0.657025\n",
      "Epoch 6 / Batch (8/17) / Accuracy 0.7412 / Loss 0.621193\n",
      "Epoch 6 / Batch (9/17) / Accuracy 0.7406 / Loss 0.637563\n",
      "Epoch 6 / Batch (10/17) / Accuracy 0.7312 / Loss 0.641530\n",
      "Epoch 6 / Batch (11/17) / Accuracy 0.7588 / Loss 0.601679\n",
      "Epoch 6 / Batch (12/17) / Accuracy 0.7550 / Loss 0.602411\n",
      "Epoch 6 / Batch (13/17) / Accuracy 0.7450 / Loss 0.620964\n",
      "Epoch 6 / Batch (14/17) / Accuracy 0.7494 / Loss 0.642667\n",
      "Epoch 6 / Batch (15/17) / Accuracy 0.7031 / Loss 0.679784\n",
      "Epoch 6 / Batch (16/17) / Accuracy 0.7369 / Loss 0.627797\n",
      "Epoch 6 / Batch (17/17) / Accuracy 0.7494 / Loss 0.634566\n",
      "Epoch 6 complete, 6.546600103378296 seconds elapsed\n",
      "\n",
      "Epoch 7 starting..\n",
      "Epoch 7 / Batch (1/17) / Accuracy 0.7650 / Loss 0.583488\n",
      "Epoch 7 / Batch (2/17) / Accuracy 0.6812 / Loss 0.755365\n",
      "Epoch 7 / Batch (3/17) / Accuracy 0.7125 / Loss 0.684930\n",
      "Epoch 7 / Batch (4/17) / Accuracy 0.7113 / Loss 0.707555\n",
      "Epoch 7 / Batch (5/17) / Accuracy 0.6875 / Loss 0.732237\n",
      "Epoch 7 / Batch (6/17) / Accuracy 0.7175 / Loss 0.693406\n",
      "Epoch 7 / Batch (7/17) / Accuracy 0.7119 / Loss 0.707591\n",
      "Epoch 7 / Batch (8/17) / Accuracy 0.6950 / Loss 0.692917\n",
      "Epoch 7 / Batch (9/17) / Accuracy 0.7262 / Loss 0.641773\n",
      "Epoch 7 / Batch (10/17) / Accuracy 0.7300 / Loss 0.689076\n",
      "Epoch 7 / Batch (11/17) / Accuracy 0.7381 / Loss 0.635315\n",
      "Epoch 7 / Batch (12/17) / Accuracy 0.7013 / Loss 0.730114\n",
      "Epoch 7 / Batch (13/17) / Accuracy 0.7312 / Loss 0.629034\n",
      "Epoch 7 / Batch (14/17) / Accuracy 0.7369 / Loss 0.640223\n",
      "Epoch 7 / Batch (15/17) / Accuracy 0.7681 / Loss 0.584401\n",
      "Epoch 7 / Batch (16/17) / Accuracy 0.7369 / Loss 0.623759\n",
      "Epoch 7 / Batch (17/17) / Accuracy 0.7506 / Loss 0.598163\n",
      "Epoch 7 complete, 6.644334077835083 seconds elapsed\n",
      "\n",
      "Epoch 8 starting..\n",
      "Epoch 8 / Batch (1/17) / Accuracy 0.7519 / Loss 0.606559\n",
      "Epoch 8 / Batch (2/17) / Accuracy 0.7481 / Loss 0.613750\n",
      "Epoch 8 / Batch (3/17) / Accuracy 0.7456 / Loss 0.630327\n",
      "Epoch 8 / Batch (4/17) / Accuracy 0.7675 / Loss 0.598156\n",
      "Epoch 8 / Batch (5/17) / Accuracy 0.7563 / Loss 0.604661\n",
      "Epoch 8 / Batch (6/17) / Accuracy 0.7606 / Loss 0.560584\n",
      "Epoch 8 / Batch (7/17) / Accuracy 0.7544 / Loss 0.614675\n",
      "Epoch 8 / Batch (8/17) / Accuracy 0.7506 / Loss 0.614272\n",
      "Epoch 8 / Batch (9/17) / Accuracy 0.7575 / Loss 0.621548\n",
      "Epoch 8 / Batch (10/17) / Accuracy 0.7281 / Loss 0.619514\n",
      "Epoch 8 / Batch (11/17) / Accuracy 0.7125 / Loss 0.696588\n",
      "Epoch 8 / Batch (12/17) / Accuracy 0.7425 / Loss 0.625694\n",
      "Epoch 8 / Batch (13/17) / Accuracy 0.7894 / Loss 0.550739\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 8 / Batch (14/17) / Accuracy 0.7669 / Loss 0.606161\n",
      "Epoch 8 / Batch (15/17) / Accuracy 0.7194 / Loss 0.693386\n",
      "Epoch 8 / Batch (16/17) / Accuracy 0.7381 / Loss 0.612737\n",
      "Epoch 8 / Batch (17/17) / Accuracy 0.7800 / Loss 0.574044\n",
      "Epoch 8 complete, 6.74535608291626 seconds elapsed\n",
      "\n",
      "Epoch 9 starting..\n",
      "Epoch 9 / Batch (1/17) / Accuracy 0.7531 / Loss 0.581178\n",
      "Epoch 9 / Batch (2/17) / Accuracy 0.7206 / Loss 0.648977\n",
      "Epoch 9 / Batch (3/17) / Accuracy 0.7844 / Loss 0.546066\n",
      "Epoch 9 / Batch (4/17) / Accuracy 0.7713 / Loss 0.606559\n",
      "Epoch 9 / Batch (5/17) / Accuracy 0.7656 / Loss 0.560695\n",
      "Epoch 9 / Batch (6/17) / Accuracy 0.7681 / Loss 0.547315\n",
      "Epoch 9 / Batch (7/17) / Accuracy 0.7619 / Loss 0.593824\n",
      "Epoch 9 / Batch (8/17) / Accuracy 0.7237 / Loss 0.613027\n",
      "Epoch 9 / Batch (9/17) / Accuracy 0.7431 / Loss 0.616972\n",
      "Epoch 9 / Batch (10/17) / Accuracy 0.7856 / Loss 0.563586\n",
      "Epoch 9 / Batch (11/17) / Accuracy 0.7569 / Loss 0.609299\n",
      "Epoch 9 / Batch (12/17) / Accuracy 0.7206 / Loss 0.658705\n",
      "Epoch 9 / Batch (13/17) / Accuracy 0.7475 / Loss 0.598093\n",
      "Epoch 9 / Batch (14/17) / Accuracy 0.7550 / Loss 0.600702\n",
      "Epoch 9 / Batch (15/17) / Accuracy 0.7350 / Loss 0.659240\n",
      "Epoch 9 / Batch (16/17) / Accuracy 0.7425 / Loss 0.616221\n",
      "Epoch 9 / Batch (17/17) / Accuracy 0.7669 / Loss 0.581194\n",
      "Epoch 9 complete, 6.637797117233276 seconds elapsed\n",
      "\n",
      "Epoch 10 starting..\n",
      "Epoch 10 / Batch (1/17) / Accuracy 0.7625 / Loss 0.611029\n",
      "Epoch 10 / Batch (2/17) / Accuracy 0.7281 / Loss 0.702995\n",
      "Epoch 10 / Batch (3/17) / Accuracy 0.7688 / Loss 0.586985\n",
      "Epoch 10 / Batch (4/17) / Accuracy 0.7725 / Loss 0.589979\n",
      "Epoch 10 / Batch (5/17) / Accuracy 0.7294 / Loss 0.657429\n",
      "Epoch 10 / Batch (6/17) / Accuracy 0.7694 / Loss 0.625424\n",
      "Epoch 10 / Batch (7/17) / Accuracy 0.7656 / Loss 0.580866\n",
      "Epoch 10 / Batch (8/17) / Accuracy 0.7487 / Loss 0.614819\n",
      "Epoch 10 / Batch (9/17) / Accuracy 0.7494 / Loss 0.614984\n",
      "Epoch 10 / Batch (10/17) / Accuracy 0.7763 / Loss 0.547072\n",
      "Epoch 10 / Batch (11/17) / Accuracy 0.7875 / Loss 0.547168\n",
      "Epoch 10 / Batch (12/17) / Accuracy 0.7713 / Loss 0.568332\n",
      "Epoch 10 / Batch (13/17) / Accuracy 0.7519 / Loss 0.587755\n",
      "Epoch 10 / Batch (14/17) / Accuracy 0.7669 / Loss 0.573978\n",
      "Epoch 10 / Batch (15/17) / Accuracy 0.6900 / Loss 0.721307\n",
      "Epoch 10 / Batch (16/17) / Accuracy 0.7094 / Loss 0.709192\n",
      "Epoch 10 / Batch (17/17) / Accuracy 0.7738 / Loss 0.586673\n",
      "Epoch 10 complete, 6.006861209869385 seconds elapsed\n",
      "\n",
      "Epoch 11 starting..\n",
      "Epoch 11 / Batch (1/17) / Accuracy 0.7362 / Loss 0.625752\n",
      "Epoch 11 / Batch (2/17) / Accuracy 0.7375 / Loss 0.651488\n",
      "Epoch 11 / Batch (3/17) / Accuracy 0.7469 / Loss 0.638726\n",
      "Epoch 11 / Batch (4/17) / Accuracy 0.7456 / Loss 0.622360\n",
      "Epoch 11 / Batch (5/17) / Accuracy 0.7713 / Loss 0.575627\n",
      "Epoch 11 / Batch (6/17) / Accuracy 0.7063 / Loss 0.668428\n",
      "Epoch 11 / Batch (7/17) / Accuracy 0.7400 / Loss 0.627989\n",
      "Epoch 11 / Batch (8/17) / Accuracy 0.7050 / Loss 0.684977\n",
      "Epoch 11 / Batch (9/17) / Accuracy 0.7475 / Loss 0.628187\n",
      "Epoch 11 / Batch (10/17) / Accuracy 0.7075 / Loss 0.705804\n",
      "Epoch 11 / Batch (11/17) / Accuracy 0.7738 / Loss 0.532475\n",
      "Epoch 11 / Batch (12/17) / Accuracy 0.7219 / Loss 0.623495\n",
      "Epoch 11 / Batch (13/17) / Accuracy 0.7206 / Loss 0.647457\n",
      "Epoch 11 / Batch (14/17) / Accuracy 0.7800 / Loss 0.560899\n",
      "Epoch 11 / Batch (15/17) / Accuracy 0.7819 / Loss 0.525869\n",
      "Epoch 11 / Batch (16/17) / Accuracy 0.7619 / Loss 0.581523\n",
      "Epoch 11 / Batch (17/17) / Accuracy 0.7544 / Loss 0.602214\n",
      "Epoch 11 complete, 6.223297119140625 seconds elapsed\n",
      "\n",
      "Epoch 12 starting..\n",
      "Epoch 12 / Batch (1/17) / Accuracy 0.7638 / Loss 0.593504\n",
      "Epoch 12 / Batch (2/17) / Accuracy 0.7237 / Loss 0.657334\n",
      "Epoch 12 / Batch (3/17) / Accuracy 0.7150 / Loss 0.668069\n",
      "Epoch 12 / Batch (4/17) / Accuracy 0.7575 / Loss 0.602381\n",
      "Epoch 12 / Batch (5/17) / Accuracy 0.7663 / Loss 0.575233\n",
      "Epoch 12 / Batch (6/17) / Accuracy 0.7606 / Loss 0.605847\n",
      "Epoch 12 / Batch (7/17) / Accuracy 0.7056 / Loss 0.669937\n",
      "Epoch 12 / Batch (8/17) / Accuracy 0.7538 / Loss 0.619942\n",
      "Epoch 12 / Batch (9/17) / Accuracy 0.7444 / Loss 0.665212\n",
      "Epoch 12 / Batch (10/17) / Accuracy 0.7906 / Loss 0.529444\n",
      "Epoch 12 / Batch (11/17) / Accuracy 0.7381 / Loss 0.659224\n",
      "Epoch 12 / Batch (12/17) / Accuracy 0.7444 / Loss 0.622508\n",
      "Epoch 12 / Batch (13/17) / Accuracy 0.7506 / Loss 0.606094\n",
      "Epoch 12 / Batch (14/17) / Accuracy 0.7300 / Loss 0.659103\n",
      "Epoch 12 / Batch (15/17) / Accuracy 0.7200 / Loss 0.652805\n",
      "Epoch 12 / Batch (16/17) / Accuracy 0.7625 / Loss 0.582833\n",
      "Epoch 12 / Batch (17/17) / Accuracy 0.7387 / Loss 0.624627\n",
      "Epoch 12 complete, 6.228002548217773 seconds elapsed\n",
      "\n",
      "Epoch 13 starting..\n",
      "Epoch 13 / Batch (1/17) / Accuracy 0.7688 / Loss 0.602519\n",
      "Epoch 13 / Batch (2/17) / Accuracy 0.7681 / Loss 0.563725\n",
      "Epoch 13 / Batch (3/17) / Accuracy 0.7469 / Loss 0.620954\n",
      "Epoch 13 / Batch (4/17) / Accuracy 0.7606 / Loss 0.611383\n",
      "Epoch 13 / Batch (5/17) / Accuracy 0.7381 / Loss 0.650115\n",
      "Epoch 13 / Batch (6/17) / Accuracy 0.7544 / Loss 0.615840\n",
      "Epoch 13 / Batch (7/17) / Accuracy 0.7581 / Loss 0.614772\n",
      "Epoch 13 / Batch (8/17) / Accuracy 0.7369 / Loss 0.688079\n",
      "Epoch 13 / Batch (9/17) / Accuracy 0.7806 / Loss 0.549425\n",
      "Epoch 13 / Batch (10/17) / Accuracy 0.7231 / Loss 0.686147\n",
      "Epoch 13 / Batch (11/17) / Accuracy 0.7600 / Loss 0.564579\n",
      "Epoch 13 / Batch (12/17) / Accuracy 0.7312 / Loss 0.638370\n",
      "Epoch 13 / Batch (13/17) / Accuracy 0.7725 / Loss 0.600557\n",
      "Epoch 13 / Batch (14/17) / Accuracy 0.7075 / Loss 0.681334\n",
      "Epoch 13 / Batch (15/17) / Accuracy 0.7487 / Loss 0.602703\n",
      "Epoch 13 / Batch (16/17) / Accuracy 0.7738 / Loss 0.591463\n",
      "Epoch 13 / Batch (17/17) / Accuracy 0.7375 / Loss 0.635011\n",
      "Epoch 13 complete, 6.649819612503052 seconds elapsed\n",
      "\n",
      "Epoch 14 starting..\n",
      "Epoch 14 / Batch (1/17) / Accuracy 0.7406 / Loss 0.611453\n",
      "Epoch 14 / Batch (2/17) / Accuracy 0.7525 / Loss 0.589525\n",
      "Epoch 14 / Batch (3/17) / Accuracy 0.7481 / Loss 0.611497\n",
      "Epoch 14 / Batch (4/17) / Accuracy 0.7837 / Loss 0.541429\n",
      "Epoch 14 / Batch (5/17) / Accuracy 0.7594 / Loss 0.618536\n",
      "Epoch 14 / Batch (6/17) / Accuracy 0.7506 / Loss 0.604699\n",
      "Epoch 14 / Batch (7/17) / Accuracy 0.7644 / Loss 0.592512\n",
      "Epoch 14 / Batch (8/17) / Accuracy 0.7663 / Loss 0.558713\n",
      "Epoch 14 / Batch (9/17) / Accuracy 0.7725 / Loss 0.580893\n",
      "Epoch 14 / Batch (10/17) / Accuracy 0.6919 / Loss 0.713364\n",
      "Epoch 14 / Batch (11/17) / Accuracy 0.7650 / Loss 0.573203\n",
      "Epoch 14 / Batch (12/17) / Accuracy 0.7688 / Loss 0.599767\n",
      "Epoch 14 / Batch (13/17) / Accuracy 0.7269 / Loss 0.644328\n",
      "Epoch 14 / Batch (14/17) / Accuracy 0.7575 / Loss 0.609088\n",
      "Epoch 14 / Batch (15/17) / Accuracy 0.7294 / Loss 0.622046\n",
      "Epoch 14 / Batch (16/17) / Accuracy 0.7419 / Loss 0.645369\n",
      "Epoch 14 / Batch (17/17) / Accuracy 0.7519 / Loss 0.608716\n",
      "Epoch 14 complete, 6.219892263412476 seconds elapsed\n",
      "\n",
      "Epoch 15 starting..\n",
      "Epoch 15 / Batch (1/17) / Accuracy 0.7613 / Loss 0.633273\n",
      "Epoch 15 / Batch (2/17) / Accuracy 0.7738 / Loss 0.589176\n",
      "Epoch 15 / Batch (3/17) / Accuracy 0.7450 / Loss 0.624375\n",
      "Epoch 15 / Batch (4/17) / Accuracy 0.7525 / Loss 0.582223\n",
      "Epoch 15 / Batch (5/17) / Accuracy 0.7319 / Loss 0.635225\n",
      "Epoch 15 / Batch (6/17) / Accuracy 0.7556 / Loss 0.610634\n",
      "Epoch 15 / Batch (7/17) / Accuracy 0.8194 / Loss 0.466494\n",
      "Epoch 15 / Batch (8/17) / Accuracy 0.7769 / Loss 0.529810\n",
      "Epoch 15 / Batch (9/17) / Accuracy 0.7688 / Loss 0.591726\n",
      "Epoch 15 / Batch (10/17) / Accuracy 0.7937 / Loss 0.565278\n",
      "Epoch 15 / Batch (11/17) / Accuracy 0.7956 / Loss 0.530678\n",
      "Epoch 15 / Batch (12/17) / Accuracy 0.7531 / Loss 0.622432\n",
      "Epoch 15 / Batch (13/17) / Accuracy 0.7563 / Loss 0.618291\n",
      "Epoch 15 / Batch (14/17) / Accuracy 0.7369 / Loss 0.626702\n",
      "Epoch 15 / Batch (15/17) / Accuracy 0.6963 / Loss 0.753582\n",
      "Epoch 15 / Batch (16/17) / Accuracy 0.7394 / Loss 0.651500\n",
      "Epoch 15 / Batch (17/17) / Accuracy 0.7544 / Loss 0.605542\n",
      "Epoch 15 complete, 5.7983317375183105 seconds elapsed\n",
      "\n",
      "Epoch 16 starting..\n",
      "Epoch 16 / Batch (1/17) / Accuracy 0.7563 / Loss 0.605781\n",
      "Epoch 16 / Batch (2/17) / Accuracy 0.7219 / Loss 0.636670\n",
      "Epoch 16 / Batch (3/17) / Accuracy 0.8094 / Loss 0.514629\n",
      "Epoch 16 / Batch (4/17) / Accuracy 0.7656 / Loss 0.591221\n",
      "Epoch 16 / Batch (5/17) / Accuracy 0.7663 / Loss 0.592094\n",
      "Epoch 16 / Batch (6/17) / Accuracy 0.7312 / Loss 0.648617\n",
      "Epoch 16 / Batch (7/17) / Accuracy 0.7469 / Loss 0.605961\n",
      "Epoch 16 / Batch (8/17) / Accuracy 0.7225 / Loss 0.673313\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 16 / Batch (9/17) / Accuracy 0.7937 / Loss 0.548923\n",
      "Epoch 16 / Batch (10/17) / Accuracy 0.7294 / Loss 0.633567\n",
      "Epoch 16 / Batch (11/17) / Accuracy 0.7887 / Loss 0.544576\n",
      "Epoch 16 / Batch (12/17) / Accuracy 0.7163 / Loss 0.674455\n",
      "Epoch 16 / Batch (13/17) / Accuracy 0.7550 / Loss 0.584072\n",
      "Epoch 16 / Batch (14/17) / Accuracy 0.7369 / Loss 0.641047\n",
      "Epoch 16 / Batch (15/17) / Accuracy 0.7719 / Loss 0.597684\n",
      "Epoch 16 / Batch (16/17) / Accuracy 0.7569 / Loss 0.612319\n",
      "Epoch 16 / Batch (17/17) / Accuracy 0.7450 / Loss 0.603866\n",
      "Epoch 16 complete, 6.946115970611572 seconds elapsed\n",
      "\n",
      "Epoch 17 starting..\n",
      "Epoch 17 / Batch (1/17) / Accuracy 0.7375 / Loss 0.643184\n",
      "Epoch 17 / Batch (2/17) / Accuracy 0.7306 / Loss 0.656599\n",
      "Epoch 17 / Batch (3/17) / Accuracy 0.7725 / Loss 0.595611\n",
      "Epoch 17 / Batch (4/17) / Accuracy 0.7538 / Loss 0.610237\n",
      "Epoch 17 / Batch (5/17) / Accuracy 0.7894 / Loss 0.546325\n",
      "Epoch 17 / Batch (6/17) / Accuracy 0.7656 / Loss 0.571148\n",
      "Epoch 17 / Batch (7/17) / Accuracy 0.7887 / Loss 0.559522\n",
      "Epoch 17 / Batch (8/17) / Accuracy 0.7412 / Loss 0.631466\n",
      "Epoch 17 / Batch (9/17) / Accuracy 0.7588 / Loss 0.607836\n",
      "Epoch 17 / Batch (10/17) / Accuracy 0.7431 / Loss 0.623086\n",
      "Epoch 17 / Batch (11/17) / Accuracy 0.7581 / Loss 0.587993\n",
      "Epoch 17 / Batch (12/17) / Accuracy 0.7556 / Loss 0.603015\n",
      "Epoch 17 / Batch (13/17) / Accuracy 0.7531 / Loss 0.638741\n",
      "Epoch 17 / Batch (14/17) / Accuracy 0.7650 / Loss 0.580749\n",
      "Epoch 17 / Batch (15/17) / Accuracy 0.7231 / Loss 0.644532\n",
      "Epoch 17 / Batch (16/17) / Accuracy 0.7156 / Loss 0.693999\n",
      "Epoch 17 / Batch (17/17) / Accuracy 0.7756 / Loss 0.556705\n",
      "Epoch 17 complete, 6.871932744979858 seconds elapsed\n",
      "\n",
      "Epoch 18 starting..\n",
      "Epoch 18 / Batch (1/17) / Accuracy 0.7869 / Loss 0.536011\n",
      "Epoch 18 / Batch (2/17) / Accuracy 0.7875 / Loss 0.567351\n",
      "Epoch 18 / Batch (3/17) / Accuracy 0.7775 / Loss 0.575063\n",
      "Epoch 18 / Batch (4/17) / Accuracy 0.7375 / Loss 0.616980\n",
      "Epoch 18 / Batch (5/17) / Accuracy 0.7763 / Loss 0.562488\n",
      "Epoch 18 / Batch (6/17) / Accuracy 0.7425 / Loss 0.636459\n",
      "Epoch 18 / Batch (7/17) / Accuracy 0.7756 / Loss 0.562881\n",
      "Epoch 18 / Batch (8/17) / Accuracy 0.7750 / Loss 0.570063\n",
      "Epoch 18 / Batch (9/17) / Accuracy 0.7337 / Loss 0.664482\n",
      "Epoch 18 / Batch (10/17) / Accuracy 0.7581 / Loss 0.611003\n",
      "Epoch 18 / Batch (11/17) / Accuracy 0.8006 / Loss 0.530001\n",
      "Epoch 18 / Batch (12/17) / Accuracy 0.7312 / Loss 0.638592\n",
      "Epoch 18 / Batch (13/17) / Accuracy 0.7619 / Loss 0.574682\n",
      "Epoch 18 / Batch (14/17) / Accuracy 0.7638 / Loss 0.571388\n",
      "Epoch 18 / Batch (15/17) / Accuracy 0.7544 / Loss 0.605560\n",
      "Epoch 18 / Batch (16/17) / Accuracy 0.7300 / Loss 0.646834\n",
      "Epoch 18 / Batch (17/17) / Accuracy 0.7300 / Loss 0.648227\n",
      "Epoch 18 complete, 6.261225700378418 seconds elapsed\n",
      "\n",
      "Epoch 19 starting..\n",
      "Epoch 19 / Batch (1/17) / Accuracy 0.7606 / Loss 0.577363\n",
      "Epoch 19 / Batch (2/17) / Accuracy 0.7700 / Loss 0.594913\n",
      "Epoch 19 / Batch (3/17) / Accuracy 0.7437 / Loss 0.627089\n",
      "Epoch 19 / Batch (4/17) / Accuracy 0.7431 / Loss 0.643144\n",
      "Epoch 19 / Batch (5/17) / Accuracy 0.7369 / Loss 0.635589\n",
      "Epoch 19 / Batch (6/17) / Accuracy 0.7694 / Loss 0.597653\n",
      "Epoch 19 / Batch (7/17) / Accuracy 0.7681 / Loss 0.580839\n",
      "Epoch 19 / Batch (8/17) / Accuracy 0.7212 / Loss 0.660502\n",
      "Epoch 19 / Batch (9/17) / Accuracy 0.7237 / Loss 0.673413\n",
      "Epoch 19 / Batch (10/17) / Accuracy 0.7331 / Loss 0.634178\n",
      "Epoch 19 / Batch (11/17) / Accuracy 0.7075 / Loss 0.673680\n",
      "Epoch 19 / Batch (12/17) / Accuracy 0.7525 / Loss 0.653051\n",
      "Epoch 19 / Batch (13/17) / Accuracy 0.8025 / Loss 0.514573\n",
      "Epoch 19 / Batch (14/17) / Accuracy 0.7631 / Loss 0.603345\n",
      "Epoch 19 / Batch (15/17) / Accuracy 0.7469 / Loss 0.593184\n",
      "Epoch 19 / Batch (16/17) / Accuracy 0.7725 / Loss 0.546549\n",
      "Epoch 19 / Batch (17/17) / Accuracy 0.7588 / Loss 0.590230\n",
      "Epoch 19 complete, 6.395267963409424 seconds elapsed\n",
      "\n",
      "Epoch 20 starting..\n",
      "Epoch 20 / Batch (1/17) / Accuracy 0.7775 / Loss 0.543728\n",
      "Epoch 20 / Batch (2/17) / Accuracy 0.7794 / Loss 0.559700\n",
      "Epoch 20 / Batch (3/17) / Accuracy 0.7575 / Loss 0.585725\n",
      "Epoch 20 / Batch (4/17) / Accuracy 0.7544 / Loss 0.619644\n",
      "Epoch 20 / Batch (5/17) / Accuracy 0.7806 / Loss 0.566742\n",
      "Epoch 20 / Batch (6/17) / Accuracy 0.7588 / Loss 0.596527\n",
      "Epoch 20 / Batch (7/17) / Accuracy 0.7900 / Loss 0.526598\n",
      "Epoch 20 / Batch (8/17) / Accuracy 0.7569 / Loss 0.603813\n",
      "Epoch 20 / Batch (9/17) / Accuracy 0.7506 / Loss 0.594072\n",
      "Epoch 20 / Batch (10/17) / Accuracy 0.7506 / Loss 0.581703\n",
      "Epoch 20 / Batch (11/17) / Accuracy 0.7581 / Loss 0.618349\n",
      "Epoch 20 / Batch (12/17) / Accuracy 0.7831 / Loss 0.564118\n",
      "Epoch 20 / Batch (13/17) / Accuracy 0.7812 / Loss 0.559648\n",
      "Epoch 20 / Batch (14/17) / Accuracy 0.7462 / Loss 0.596075\n",
      "Epoch 20 / Batch (15/17) / Accuracy 0.7750 / Loss 0.553733\n",
      "Epoch 20 / Batch (16/17) / Accuracy 0.7312 / Loss 0.659721\n",
      "Epoch 20 / Batch (17/17) / Accuracy 0.7325 / Loss 0.652304\n",
      "Epoch 20 complete, 5.9869983196258545 seconds elapsed\n",
      "\n",
      "Epoch 21 starting..\n",
      "Epoch 21 / Batch (1/17) / Accuracy 0.7431 / Loss 0.637800\n",
      "Epoch 21 / Batch (2/17) / Accuracy 0.7462 / Loss 0.627014\n",
      "Epoch 21 / Batch (3/17) / Accuracy 0.7675 / Loss 0.577842\n",
      "Epoch 21 / Batch (4/17) / Accuracy 0.7331 / Loss 0.639808\n",
      "Epoch 21 / Batch (5/17) / Accuracy 0.7869 / Loss 0.574643\n",
      "Epoch 21 / Batch (6/17) / Accuracy 0.7706 / Loss 0.576719\n",
      "Epoch 21 / Batch (7/17) / Accuracy 0.7750 / Loss 0.539623\n",
      "Epoch 21 / Batch (8/17) / Accuracy 0.7569 / Loss 0.561664\n",
      "Epoch 21 / Batch (9/17) / Accuracy 0.7544 / Loss 0.600875\n",
      "Epoch 21 / Batch (10/17) / Accuracy 0.7713 / Loss 0.558543\n",
      "Epoch 21 / Batch (11/17) / Accuracy 0.7619 / Loss 0.591535\n",
      "Epoch 21 / Batch (12/17) / Accuracy 0.7312 / Loss 0.647102\n",
      "Epoch 21 / Batch (13/17) / Accuracy 0.7362 / Loss 0.611567\n",
      "Epoch 21 / Batch (14/17) / Accuracy 0.7556 / Loss 0.626632\n",
      "Epoch 21 / Batch (15/17) / Accuracy 0.7588 / Loss 0.582403\n",
      "Epoch 21 / Batch (16/17) / Accuracy 0.7237 / Loss 0.650731\n",
      "Epoch 21 / Batch (17/17) / Accuracy 0.7563 / Loss 0.620554\n",
      "Epoch 21 complete, 6.37499213218689 seconds elapsed\n",
      "\n",
      "Epoch 22 starting..\n",
      "Epoch 22 / Batch (1/17) / Accuracy 0.7131 / Loss 0.709249\n",
      "Epoch 22 / Batch (2/17) / Accuracy 0.7937 / Loss 0.538643\n",
      "Epoch 22 / Batch (3/17) / Accuracy 0.7669 / Loss 0.561458\n",
      "Epoch 22 / Batch (4/17) / Accuracy 0.7531 / Loss 0.601162\n",
      "Epoch 22 / Batch (5/17) / Accuracy 0.7500 / Loss 0.612113\n",
      "Epoch 22 / Batch (6/17) / Accuracy 0.7625 / Loss 0.589258\n",
      "Epoch 22 / Batch (7/17) / Accuracy 0.7613 / Loss 0.587139\n",
      "Epoch 22 / Batch (8/17) / Accuracy 0.7500 / Loss 0.621282\n",
      "Epoch 22 / Batch (9/17) / Accuracy 0.7469 / Loss 0.627367\n",
      "Epoch 22 / Batch (10/17) / Accuracy 0.7237 / Loss 0.646954\n",
      "Epoch 22 / Batch (11/17) / Accuracy 0.7481 / Loss 0.600501\n",
      "Epoch 22 / Batch (12/17) / Accuracy 0.7369 / Loss 0.627875\n",
      "Epoch 22 / Batch (13/17) / Accuracy 0.7219 / Loss 0.663158\n",
      "Epoch 22 / Batch (14/17) / Accuracy 0.7663 / Loss 0.572704\n",
      "Epoch 22 / Batch (15/17) / Accuracy 0.7306 / Loss 0.676604\n",
      "Epoch 22 / Batch (16/17) / Accuracy 0.7381 / Loss 0.663134\n",
      "Epoch 22 / Batch (17/17) / Accuracy 0.7219 / Loss 0.656883\n",
      "Epoch 22 complete, 5.879810094833374 seconds elapsed\n",
      "\n",
      "Epoch 23 starting..\n",
      "Epoch 23 / Batch (1/17) / Accuracy 0.7656 / Loss 0.591748\n",
      "Epoch 23 / Batch (2/17) / Accuracy 0.7225 / Loss 0.667752\n",
      "Epoch 23 / Batch (3/17) / Accuracy 0.7262 / Loss 0.640855\n",
      "Epoch 23 / Batch (4/17) / Accuracy 0.7538 / Loss 0.573397\n",
      "Epoch 23 / Batch (5/17) / Accuracy 0.7556 / Loss 0.583507\n",
      "Epoch 23 / Batch (6/17) / Accuracy 0.7212 / Loss 0.643552\n",
      "Epoch 23 / Batch (7/17) / Accuracy 0.7469 / Loss 0.599589\n",
      "Epoch 23 / Batch (8/17) / Accuracy 0.7237 / Loss 0.652147\n",
      "Epoch 23 / Batch (9/17) / Accuracy 0.7650 / Loss 0.604954\n",
      "Epoch 23 / Batch (10/17) / Accuracy 0.6925 / Loss 0.725127\n",
      "Epoch 23 / Batch (11/17) / Accuracy 0.7475 / Loss 0.638317\n",
      "Epoch 23 / Batch (12/17) / Accuracy 0.7856 / Loss 0.549110\n",
      "Epoch 23 / Batch (13/17) / Accuracy 0.7469 / Loss 0.631685\n",
      "Epoch 23 / Batch (14/17) / Accuracy 0.7831 / Loss 0.550210\n",
      "Epoch 23 / Batch (15/17) / Accuracy 0.7456 / Loss 0.597369\n",
      "Epoch 23 / Batch (16/17) / Accuracy 0.7500 / Loss 0.591802\n",
      "Epoch 23 / Batch (17/17) / Accuracy 0.7900 / Loss 0.515905\n",
      "Epoch 23 complete, 6.821530342102051 seconds elapsed\n",
      "\n",
      "Epoch 24 starting..\n",
      "Epoch 24 / Batch (1/17) / Accuracy 0.7781 / Loss 0.558863\n",
      "Epoch 24 / Batch (2/17) / Accuracy 0.7437 / Loss 0.627485\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 24 / Batch (3/17) / Accuracy 0.8250 / Loss 0.466747\n",
      "Epoch 24 / Batch (4/17) / Accuracy 0.7681 / Loss 0.563182\n",
      "Epoch 24 / Batch (5/17) / Accuracy 0.7481 / Loss 0.607339\n",
      "Epoch 24 / Batch (6/17) / Accuracy 0.7544 / Loss 0.598065\n",
      "Epoch 24 / Batch (7/17) / Accuracy 0.7962 / Loss 0.522475\n",
      "Epoch 24 / Batch (8/17) / Accuracy 0.8119 / Loss 0.492900\n",
      "Epoch 24 / Batch (9/17) / Accuracy 0.7769 / Loss 0.558326\n",
      "Epoch 24 / Batch (10/17) / Accuracy 0.7600 / Loss 0.573125\n",
      "Epoch 24 / Batch (11/17) / Accuracy 0.8131 / Loss 0.498918\n",
      "Epoch 24 / Batch (12/17) / Accuracy 0.7656 / Loss 0.591792\n",
      "Epoch 24 / Batch (13/17) / Accuracy 0.7219 / Loss 0.650938\n",
      "Epoch 24 / Batch (14/17) / Accuracy 0.7656 / Loss 0.586672\n",
      "Epoch 24 / Batch (15/17) / Accuracy 0.7906 / Loss 0.553954\n",
      "Epoch 24 / Batch (16/17) / Accuracy 0.7613 / Loss 0.628721\n",
      "Epoch 24 / Batch (17/17) / Accuracy 0.7475 / Loss 0.606786\n",
      "Epoch 24 complete, 6.047562122344971 seconds elapsed\n",
      "\n",
      "Epoch 25 starting..\n",
      "Epoch 25 / Batch (1/17) / Accuracy 0.7419 / Loss 0.616831\n",
      "Epoch 25 / Batch (2/17) / Accuracy 0.7837 / Loss 0.533012\n",
      "Epoch 25 / Batch (3/17) / Accuracy 0.7344 / Loss 0.654196\n",
      "Epoch 25 / Batch (4/17) / Accuracy 0.7119 / Loss 0.673910\n",
      "Epoch 25 / Batch (5/17) / Accuracy 0.7806 / Loss 0.519512\n",
      "Epoch 25 / Batch (6/17) / Accuracy 0.7437 / Loss 0.613423\n",
      "Epoch 25 / Batch (7/17) / Accuracy 0.7825 / Loss 0.557345\n",
      "Epoch 25 / Batch (8/17) / Accuracy 0.7719 / Loss 0.584141\n",
      "Epoch 25 / Batch (9/17) / Accuracy 0.7806 / Loss 0.559402\n",
      "Epoch 25 / Batch (10/17) / Accuracy 0.7956 / Loss 0.545852\n",
      "Epoch 25 / Batch (11/17) / Accuracy 0.7494 / Loss 0.626118\n",
      "Epoch 25 / Batch (12/17) / Accuracy 0.7837 / Loss 0.548219\n",
      "Epoch 25 / Batch (13/17) / Accuracy 0.7744 / Loss 0.560759\n",
      "Epoch 25 / Batch (14/17) / Accuracy 0.7519 / Loss 0.592977\n",
      "Epoch 25 / Batch (15/17) / Accuracy 0.7575 / Loss 0.590771\n",
      "Epoch 25 / Batch (16/17) / Accuracy 0.7625 / Loss 0.594941\n",
      "Epoch 25 / Batch (17/17) / Accuracy 0.7156 / Loss 0.661473\n",
      "Epoch 25 complete, 6.051137685775757 seconds elapsed\n",
      "\n",
      "Epoch 26 starting..\n",
      "Epoch 26 / Batch (1/17) / Accuracy 0.7356 / Loss 0.622131\n",
      "Epoch 26 / Batch (2/17) / Accuracy 0.7594 / Loss 0.568092\n",
      "Epoch 26 / Batch (3/17) / Accuracy 0.7356 / Loss 0.641450\n",
      "Epoch 26 / Batch (4/17) / Accuracy 0.7600 / Loss 0.603475\n",
      "Epoch 26 / Batch (5/17) / Accuracy 0.7462 / Loss 0.596847\n",
      "Epoch 26 / Batch (6/17) / Accuracy 0.7144 / Loss 0.693469\n",
      "Epoch 26 / Batch (7/17) / Accuracy 0.7581 / Loss 0.590301\n",
      "Epoch 26 / Batch (8/17) / Accuracy 0.7450 / Loss 0.627410\n",
      "Epoch 26 / Batch (9/17) / Accuracy 0.7538 / Loss 0.572713\n",
      "Epoch 26 / Batch (10/17) / Accuracy 0.7631 / Loss 0.552346\n",
      "Epoch 26 / Batch (11/17) / Accuracy 0.7763 / Loss 0.574997\n",
      "Epoch 26 / Batch (12/17) / Accuracy 0.7731 / Loss 0.570692\n",
      "Epoch 26 / Batch (13/17) / Accuracy 0.7713 / Loss 0.547270\n",
      "Epoch 26 / Batch (14/17) / Accuracy 0.7644 / Loss 0.569576\n",
      "Epoch 26 / Batch (15/17) / Accuracy 0.7394 / Loss 0.623044\n",
      "Epoch 26 / Batch (16/17) / Accuracy 0.7462 / Loss 0.612825\n",
      "Epoch 26 / Batch (17/17) / Accuracy 0.7394 / Loss 0.634242\n",
      "Epoch 26 complete, 6.505898952484131 seconds elapsed\n",
      "\n",
      "Epoch 27 starting..\n",
      "Epoch 27 / Batch (1/17) / Accuracy 0.7650 / Loss 0.569667\n",
      "Epoch 27 / Batch (2/17) / Accuracy 0.7619 / Loss 0.564309\n",
      "Epoch 27 / Batch (3/17) / Accuracy 0.7631 / Loss 0.584719\n",
      "Epoch 27 / Batch (4/17) / Accuracy 0.7362 / Loss 0.622749\n",
      "Epoch 27 / Batch (5/17) / Accuracy 0.7606 / Loss 0.587223\n",
      "Epoch 27 / Batch (6/17) / Accuracy 0.7525 / Loss 0.615346\n",
      "Epoch 27 / Batch (7/17) / Accuracy 0.7831 / Loss 0.529422\n",
      "Epoch 27 / Batch (8/17) / Accuracy 0.8156 / Loss 0.526381\n",
      "Epoch 27 / Batch (9/17) / Accuracy 0.7769 / Loss 0.548344\n",
      "Epoch 27 / Batch (10/17) / Accuracy 0.7900 / Loss 0.567899\n",
      "Epoch 27 / Batch (11/17) / Accuracy 0.7437 / Loss 0.615028\n",
      "Epoch 27 / Batch (12/17) / Accuracy 0.7881 / Loss 0.528079\n",
      "Epoch 27 / Batch (13/17) / Accuracy 0.7644 / Loss 0.572356\n",
      "Epoch 27 / Batch (14/17) / Accuracy 0.7769 / Loss 0.576947\n",
      "Epoch 27 / Batch (15/17) / Accuracy 0.7544 / Loss 0.610260\n",
      "Epoch 27 / Batch (16/17) / Accuracy 0.7725 / Loss 0.556929\n",
      "Epoch 27 / Batch (17/17) / Accuracy 0.7756 / Loss 0.563240\n",
      "Epoch 27 complete, 6.927247047424316 seconds elapsed\n",
      "\n",
      "Epoch 28 starting..\n",
      "Epoch 28 / Batch (1/17) / Accuracy 0.7456 / Loss 0.621331\n",
      "Epoch 28 / Batch (2/17) / Accuracy 0.7525 / Loss 0.619775\n",
      "Epoch 28 / Batch (3/17) / Accuracy 0.7812 / Loss 0.551254\n",
      "Epoch 28 / Batch (4/17) / Accuracy 0.7344 / Loss 0.677591\n",
      "Epoch 28 / Batch (5/17) / Accuracy 0.7937 / Loss 0.538205\n",
      "Epoch 28 / Batch (6/17) / Accuracy 0.7694 / Loss 0.553856\n",
      "Epoch 28 / Batch (7/17) / Accuracy 0.7906 / Loss 0.535429\n",
      "Epoch 28 / Batch (8/17) / Accuracy 0.7563 / Loss 0.605089\n",
      "Epoch 28 / Batch (9/17) / Accuracy 0.7862 / Loss 0.563161\n",
      "Epoch 28 / Batch (10/17) / Accuracy 0.7663 / Loss 0.568983\n",
      "Epoch 28 / Batch (11/17) / Accuracy 0.7850 / Loss 0.559575\n",
      "Epoch 28 / Batch (12/17) / Accuracy 0.7669 / Loss 0.569438\n",
      "Epoch 28 / Batch (13/17) / Accuracy 0.7450 / Loss 0.610245\n",
      "Epoch 28 / Batch (14/17) / Accuracy 0.7206 / Loss 0.663914\n",
      "Epoch 28 / Batch (15/17) / Accuracy 0.7812 / Loss 0.538223\n",
      "Epoch 28 / Batch (16/17) / Accuracy 0.7437 / Loss 0.660728\n",
      "Epoch 28 / Batch (17/17) / Accuracy 0.7725 / Loss 0.583331\n",
      "Epoch 28 complete, 6.615246057510376 seconds elapsed\n",
      "\n",
      "Epoch 29 starting..\n",
      "Epoch 29 / Batch (1/17) / Accuracy 0.7038 / Loss 0.747330\n",
      "Epoch 29 / Batch (2/17) / Accuracy 0.7681 / Loss 0.579526\n",
      "Epoch 29 / Batch (3/17) / Accuracy 0.7613 / Loss 0.574696\n",
      "Epoch 29 / Batch (4/17) / Accuracy 0.7212 / Loss 0.665316\n",
      "Epoch 29 / Batch (5/17) / Accuracy 0.7937 / Loss 0.573028\n",
      "Epoch 29 / Batch (6/17) / Accuracy 0.7138 / Loss 0.672751\n",
      "Epoch 29 / Batch (7/17) / Accuracy 0.7469 / Loss 0.597737\n",
      "Epoch 29 / Batch (8/17) / Accuracy 0.7444 / Loss 0.619011\n",
      "Epoch 29 / Batch (9/17) / Accuracy 0.7531 / Loss 0.629317\n",
      "Epoch 29 / Batch (10/17) / Accuracy 0.7475 / Loss 0.632253\n",
      "Epoch 29 / Batch (11/17) / Accuracy 0.7744 / Loss 0.564389\n",
      "Epoch 29 / Batch (12/17) / Accuracy 0.7487 / Loss 0.610934\n",
      "Epoch 29 / Batch (13/17) / Accuracy 0.7569 / Loss 0.600054\n",
      "Epoch 29 / Batch (14/17) / Accuracy 0.7581 / Loss 0.562092\n",
      "Epoch 29 / Batch (15/17) / Accuracy 0.7588 / Loss 0.588543\n",
      "Epoch 29 / Batch (16/17) / Accuracy 0.7638 / Loss 0.611327\n",
      "Epoch 29 / Batch (17/17) / Accuracy 0.7731 / Loss 0.550244\n",
      "Epoch 29 complete, 6.369272470474243 seconds elapsed\n",
      "\n",
      "Epoch 30 starting..\n",
      "Epoch 30 / Batch (1/17) / Accuracy 0.7631 / Loss 0.575962\n",
      "Epoch 30 / Batch (2/17) / Accuracy 0.7644 / Loss 0.608285\n",
      "Epoch 30 / Batch (3/17) / Accuracy 0.7894 / Loss 0.562996\n",
      "Epoch 30 / Batch (4/17) / Accuracy 0.7519 / Loss 0.597367\n",
      "Epoch 30 / Batch (5/17) / Accuracy 0.7494 / Loss 0.594907\n",
      "Epoch 30 / Batch (6/17) / Accuracy 0.7875 / Loss 0.526161\n",
      "Epoch 30 / Batch (7/17) / Accuracy 0.7381 / Loss 0.622939\n",
      "Epoch 30 / Batch (8/17) / Accuracy 0.7437 / Loss 0.649437\n",
      "Epoch 30 / Batch (9/17) / Accuracy 0.7900 / Loss 0.521163\n",
      "Epoch 30 / Batch (10/17) / Accuracy 0.7700 / Loss 0.562660\n",
      "Epoch 30 / Batch (11/17) / Accuracy 0.7713 / Loss 0.588662\n",
      "Epoch 30 / Batch (12/17) / Accuracy 0.7431 / Loss 0.622152\n",
      "Epoch 30 / Batch (13/17) / Accuracy 0.7425 / Loss 0.642805\n",
      "Epoch 30 / Batch (14/17) / Accuracy 0.7669 / Loss 0.560019\n",
      "Epoch 30 / Batch (15/17) / Accuracy 0.7563 / Loss 0.611263\n",
      "Epoch 30 / Batch (16/17) / Accuracy 0.7519 / Loss 0.618217\n",
      "Epoch 30 / Batch (17/17) / Accuracy 0.7975 / Loss 0.549215\n",
      "Epoch 30 complete, 6.47123122215271 seconds elapsed\n",
      "\n",
      "Epoch 31 starting..\n",
      "Epoch 31 / Batch (1/17) / Accuracy 0.7956 / Loss 0.537258\n",
      "Epoch 31 / Batch (2/17) / Accuracy 0.8206 / Loss 0.493784\n",
      "Epoch 31 / Batch (3/17) / Accuracy 0.7575 / Loss 0.589215\n",
      "Epoch 31 / Batch (4/17) / Accuracy 0.7569 / Loss 0.597479\n",
      "Epoch 31 / Batch (5/17) / Accuracy 0.7775 / Loss 0.554044\n",
      "Epoch 31 / Batch (6/17) / Accuracy 0.7819 / Loss 0.552525\n",
      "Epoch 31 / Batch (7/17) / Accuracy 0.7619 / Loss 0.579732\n",
      "Epoch 31 / Batch (8/17) / Accuracy 0.7906 / Loss 0.503531\n",
      "Epoch 31 / Batch (9/17) / Accuracy 0.7588 / Loss 0.591243\n",
      "Epoch 31 / Batch (10/17) / Accuracy 0.7700 / Loss 0.564360\n",
      "Epoch 31 / Batch (11/17) / Accuracy 0.7344 / Loss 0.620950\n",
      "Epoch 31 / Batch (12/17) / Accuracy 0.7950 / Loss 0.564378\n",
      "Epoch 31 / Batch (13/17) / Accuracy 0.7194 / Loss 0.690924\n",
      "Epoch 31 / Batch (14/17) / Accuracy 0.7381 / Loss 0.639949\n",
      "Epoch 31 / Batch (15/17) / Accuracy 0.8000 / Loss 0.535222\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 31 / Batch (16/17) / Accuracy 0.7487 / Loss 0.606316\n",
      "Epoch 31 / Batch (17/17) / Accuracy 0.8025 / Loss 0.519609\n",
      "Epoch 31 complete, 6.210492372512817 seconds elapsed\n",
      "\n",
      "Epoch 32 starting..\n",
      "Epoch 32 / Batch (1/17) / Accuracy 0.7944 / Loss 0.552802\n",
      "Epoch 32 / Batch (2/17) / Accuracy 0.7962 / Loss 0.534948\n",
      "Epoch 32 / Batch (3/17) / Accuracy 0.7750 / Loss 0.557986\n",
      "Epoch 32 / Batch (4/17) / Accuracy 0.7437 / Loss 0.622557\n",
      "Epoch 32 / Batch (5/17) / Accuracy 0.7925 / Loss 0.515151\n",
      "Epoch 32 / Batch (6/17) / Accuracy 0.7206 / Loss 0.640117\n",
      "Epoch 32 / Batch (7/17) / Accuracy 0.7719 / Loss 0.607279\n",
      "Epoch 32 / Batch (8/17) / Accuracy 0.7525 / Loss 0.615771\n",
      "Epoch 32 / Batch (9/17) / Accuracy 0.8106 / Loss 0.504405\n",
      "Epoch 32 / Batch (10/17) / Accuracy 0.7663 / Loss 0.600492\n",
      "Epoch 32 / Batch (11/17) / Accuracy 0.7525 / Loss 0.631222\n",
      "Epoch 32 / Batch (12/17) / Accuracy 0.7819 / Loss 0.543282\n",
      "Epoch 32 / Batch (13/17) / Accuracy 0.7819 / Loss 0.555128\n",
      "Epoch 32 / Batch (14/17) / Accuracy 0.7931 / Loss 0.532045\n",
      "Epoch 32 / Batch (15/17) / Accuracy 0.7644 / Loss 0.592271\n",
      "Epoch 32 / Batch (16/17) / Accuracy 0.8012 / Loss 0.502213\n",
      "Epoch 32 / Batch (17/17) / Accuracy 0.8031 / Loss 0.533087\n",
      "Epoch 32 complete, 6.319188117980957 seconds elapsed\n",
      "\n",
      "Epoch 33 starting..\n",
      "Epoch 33 / Batch (1/17) / Accuracy 0.7625 / Loss 0.574686\n",
      "Epoch 33 / Batch (2/17) / Accuracy 0.7563 / Loss 0.599135\n",
      "Epoch 33 / Batch (3/17) / Accuracy 0.7556 / Loss 0.578154\n",
      "Epoch 33 / Batch (4/17) / Accuracy 0.8056 / Loss 0.519766\n",
      "Epoch 33 / Batch (5/17) / Accuracy 0.7462 / Loss 0.619441\n",
      "Epoch 33 / Batch (6/17) / Accuracy 0.7594 / Loss 0.590351\n",
      "Epoch 33 / Batch (7/17) / Accuracy 0.7694 / Loss 0.597309\n",
      "Epoch 33 / Batch (8/17) / Accuracy 0.7925 / Loss 0.549779\n",
      "Epoch 33 / Batch (9/17) / Accuracy 0.7700 / Loss 0.552988\n",
      "Epoch 33 / Batch (10/17) / Accuracy 0.7900 / Loss 0.551352\n",
      "Epoch 33 / Batch (11/17) / Accuracy 0.7906 / Loss 0.543008\n",
      "Epoch 33 / Batch (12/17) / Accuracy 0.7862 / Loss 0.545858\n",
      "Epoch 33 / Batch (13/17) / Accuracy 0.7381 / Loss 0.622057\n",
      "Epoch 33 / Batch (14/17) / Accuracy 0.7469 / Loss 0.626218\n",
      "Epoch 33 / Batch (15/17) / Accuracy 0.7688 / Loss 0.586198\n",
      "Epoch 33 / Batch (16/17) / Accuracy 0.7444 / Loss 0.610221\n",
      "Epoch 33 / Batch (17/17) / Accuracy 0.7819 / Loss 0.531595\n",
      "Epoch 33 complete, 6.977829694747925 seconds elapsed\n",
      "\n",
      "Epoch 34 starting..\n",
      "Epoch 34 / Batch (1/17) / Accuracy 0.7962 / Loss 0.529907\n",
      "Epoch 34 / Batch (2/17) / Accuracy 0.7638 / Loss 0.572537\n",
      "Epoch 34 / Batch (3/17) / Accuracy 0.7319 / Loss 0.639618\n",
      "Epoch 34 / Batch (4/17) / Accuracy 0.7694 / Loss 0.578883\n",
      "Epoch 34 / Batch (5/17) / Accuracy 0.7300 / Loss 0.632675\n",
      "Epoch 34 / Batch (6/17) / Accuracy 0.7600 / Loss 0.586439\n",
      "Epoch 34 / Batch (7/17) / Accuracy 0.7956 / Loss 0.531029\n",
      "Epoch 34 / Batch (8/17) / Accuracy 0.7663 / Loss 0.558062\n",
      "Epoch 34 / Batch (9/17) / Accuracy 0.7756 / Loss 0.549245\n",
      "Epoch 34 / Batch (10/17) / Accuracy 0.7675 / Loss 0.570950\n",
      "Epoch 34 / Batch (11/17) / Accuracy 0.7462 / Loss 0.632208\n",
      "Epoch 34 / Batch (12/17) / Accuracy 0.7812 / Loss 0.572206\n",
      "Epoch 34 / Batch (13/17) / Accuracy 0.7731 / Loss 0.562845\n",
      "Epoch 34 / Batch (14/17) / Accuracy 0.7788 / Loss 0.545754\n",
      "Epoch 34 / Batch (15/17) / Accuracy 0.7394 / Loss 0.607680\n",
      "Epoch 34 / Batch (16/17) / Accuracy 0.7544 / Loss 0.597641\n",
      "Epoch 34 / Batch (17/17) / Accuracy 0.7656 / Loss 0.554547\n",
      "Epoch 34 complete, 6.4907615184783936 seconds elapsed\n",
      "\n",
      "Epoch 35 starting..\n",
      "Epoch 35 / Batch (1/17) / Accuracy 0.7706 / Loss 0.573901\n",
      "Epoch 35 / Batch (2/17) / Accuracy 0.7650 / Loss 0.598108\n",
      "Epoch 35 / Batch (3/17) / Accuracy 0.8069 / Loss 0.502534\n",
      "Epoch 35 / Batch (4/17) / Accuracy 0.7325 / Loss 0.626418\n",
      "Epoch 35 / Batch (5/17) / Accuracy 0.7825 / Loss 0.545793\n",
      "Epoch 35 / Batch (6/17) / Accuracy 0.7919 / Loss 0.523760\n",
      "Epoch 35 / Batch (7/17) / Accuracy 0.7519 / Loss 0.582510\n",
      "Epoch 35 / Batch (8/17) / Accuracy 0.7812 / Loss 0.540392\n",
      "Epoch 35 / Batch (9/17) / Accuracy 0.8256 / Loss 0.468666\n",
      "Epoch 35 / Batch (10/17) / Accuracy 0.7975 / Loss 0.532429\n",
      "Epoch 35 / Batch (11/17) / Accuracy 0.7450 / Loss 0.639296\n",
      "Epoch 35 / Batch (12/17) / Accuracy 0.8006 / Loss 0.547990\n",
      "Epoch 35 / Batch (13/17) / Accuracy 0.7663 / Loss 0.571042\n",
      "Epoch 35 / Batch (14/17) / Accuracy 0.8019 / Loss 0.517271\n",
      "Epoch 35 / Batch (15/17) / Accuracy 0.7725 / Loss 0.581930\n",
      "Epoch 35 / Batch (16/17) / Accuracy 0.7644 / Loss 0.556135\n",
      "Epoch 35 / Batch (17/17) / Accuracy 0.7694 / Loss 0.564156\n",
      "Epoch 35 complete, 6.100672721862793 seconds elapsed\n",
      "\n",
      "Epoch 36 starting..\n",
      "Epoch 36 / Batch (1/17) / Accuracy 0.7763 / Loss 0.546840\n",
      "Epoch 36 / Batch (2/17) / Accuracy 0.8313 / Loss 0.467773\n",
      "Epoch 36 / Batch (3/17) / Accuracy 0.7713 / Loss 0.577459\n",
      "Epoch 36 / Batch (4/17) / Accuracy 0.7619 / Loss 0.581786\n",
      "Epoch 36 / Batch (5/17) / Accuracy 0.8231 / Loss 0.454451\n",
      "Epoch 36 / Batch (6/17) / Accuracy 0.7738 / Loss 0.561079\n",
      "Epoch 36 / Batch (7/17) / Accuracy 0.7750 / Loss 0.563111\n",
      "Epoch 36 / Batch (8/17) / Accuracy 0.7956 / Loss 0.523004\n",
      "Epoch 36 / Batch (9/17) / Accuracy 0.7375 / Loss 0.659600\n",
      "Epoch 36 / Batch (10/17) / Accuracy 0.7394 / Loss 0.662994\n",
      "Epoch 36 / Batch (11/17) / Accuracy 0.7431 / Loss 0.634000\n",
      "Epoch 36 / Batch (12/17) / Accuracy 0.7500 / Loss 0.636464\n",
      "Epoch 36 / Batch (13/17) / Accuracy 0.7750 / Loss 0.614652\n",
      "Epoch 36 / Batch (14/17) / Accuracy 0.7700 / Loss 0.563587\n",
      "Epoch 36 / Batch (15/17) / Accuracy 0.7837 / Loss 0.531850\n",
      "Epoch 36 / Batch (16/17) / Accuracy 0.7831 / Loss 0.557590\n",
      "Epoch 36 / Batch (17/17) / Accuracy 0.8087 / Loss 0.508867\n",
      "Epoch 36 complete, 6.266145944595337 seconds elapsed\n",
      "\n",
      "Epoch 37 starting..\n",
      "Epoch 37 / Batch (1/17) / Accuracy 0.7763 / Loss 0.545675\n",
      "Epoch 37 / Batch (2/17) / Accuracy 0.7812 / Loss 0.554077\n",
      "Epoch 37 / Batch (3/17) / Accuracy 0.7656 / Loss 0.562616\n",
      "Epoch 37 / Batch (4/17) / Accuracy 0.7713 / Loss 0.562248\n",
      "Epoch 37 / Batch (5/17) / Accuracy 0.7875 / Loss 0.518839\n",
      "Epoch 37 / Batch (6/17) / Accuracy 0.7581 / Loss 0.618655\n",
      "Epoch 37 / Batch (7/17) / Accuracy 0.7588 / Loss 0.608494\n",
      "Epoch 37 / Batch (8/17) / Accuracy 0.7700 / Loss 0.595373\n",
      "Epoch 37 / Batch (9/17) / Accuracy 0.7700 / Loss 0.603877\n",
      "Epoch 37 / Batch (10/17) / Accuracy 0.7825 / Loss 0.563298\n",
      "Epoch 37 / Batch (11/17) / Accuracy 0.7881 / Loss 0.543159\n",
      "Epoch 37 / Batch (12/17) / Accuracy 0.7431 / Loss 0.602637\n",
      "Epoch 37 / Batch (13/17) / Accuracy 0.7994 / Loss 0.559968\n",
      "Epoch 37 / Batch (14/17) / Accuracy 0.7050 / Loss 0.682819\n",
      "Epoch 37 / Batch (15/17) / Accuracy 0.7638 / Loss 0.591713\n",
      "Epoch 37 / Batch (16/17) / Accuracy 0.7588 / Loss 0.585629\n",
      "Epoch 37 / Batch (17/17) / Accuracy 0.7656 / Loss 0.577249\n",
      "Epoch 37 complete, 5.988021373748779 seconds elapsed\n",
      "\n",
      "Epoch 38 starting..\n",
      "Epoch 38 / Batch (1/17) / Accuracy 0.7412 / Loss 0.630981\n",
      "Epoch 38 / Batch (2/17) / Accuracy 0.7369 / Loss 0.610509\n",
      "Epoch 38 / Batch (3/17) / Accuracy 0.7588 / Loss 0.564610\n",
      "Epoch 38 / Batch (4/17) / Accuracy 0.7738 / Loss 0.581092\n",
      "Epoch 38 / Batch (5/17) / Accuracy 0.7775 / Loss 0.548659\n",
      "Epoch 38 / Batch (6/17) / Accuracy 0.7763 / Loss 0.555243\n",
      "Epoch 38 / Batch (7/17) / Accuracy 0.7719 / Loss 0.594011\n",
      "Epoch 38 / Batch (8/17) / Accuracy 0.7669 / Loss 0.547936\n",
      "Epoch 38 / Batch (9/17) / Accuracy 0.7494 / Loss 0.598272\n",
      "Epoch 38 / Batch (10/17) / Accuracy 0.7781 / Loss 0.585972\n",
      "Epoch 38 / Batch (11/17) / Accuracy 0.7556 / Loss 0.602429\n",
      "Epoch 38 / Batch (12/17) / Accuracy 0.7337 / Loss 0.633072\n",
      "Epoch 38 / Batch (13/17) / Accuracy 0.7475 / Loss 0.622247\n",
      "Epoch 38 / Batch (14/17) / Accuracy 0.7844 / Loss 0.554885\n",
      "Epoch 38 / Batch (15/17) / Accuracy 0.7356 / Loss 0.632867\n",
      "Epoch 38 / Batch (16/17) / Accuracy 0.7350 / Loss 0.637844\n",
      "Epoch 38 / Batch (17/17) / Accuracy 0.7856 / Loss 0.561789\n",
      "Epoch 38 complete, 6.979547500610352 seconds elapsed\n",
      "\n",
      "Epoch 39 starting..\n",
      "Epoch 39 / Batch (1/17) / Accuracy 0.7738 / Loss 0.555992\n",
      "Epoch 39 / Batch (2/17) / Accuracy 0.7819 / Loss 0.541410\n",
      "Epoch 39 / Batch (3/17) / Accuracy 0.7650 / Loss 0.554883\n",
      "Epoch 39 / Batch (4/17) / Accuracy 0.7594 / Loss 0.569560\n",
      "Epoch 39 / Batch (5/17) / Accuracy 0.7613 / Loss 0.593242\n",
      "Epoch 39 / Batch (6/17) / Accuracy 0.7906 / Loss 0.530707\n",
      "Epoch 39 / Batch (7/17) / Accuracy 0.7237 / Loss 0.634648\n",
      "Epoch 39 / Batch (8/17) / Accuracy 0.7481 / Loss 0.588975\n",
      "Epoch 39 / Batch (9/17) / Accuracy 0.7475 / Loss 0.626929\n",
      "Epoch 39 / Batch (10/17) / Accuracy 0.7437 / Loss 0.615209\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 39 / Batch (11/17) / Accuracy 0.7362 / Loss 0.655351\n",
      "Epoch 39 / Batch (12/17) / Accuracy 0.8037 / Loss 0.498866\n",
      "Epoch 39 / Batch (13/17) / Accuracy 0.8019 / Loss 0.521225\n",
      "Epoch 39 / Batch (14/17) / Accuracy 0.7700 / Loss 0.593502\n",
      "Epoch 39 / Batch (15/17) / Accuracy 0.7519 / Loss 0.582883\n",
      "Epoch 39 / Batch (16/17) / Accuracy 0.7506 / Loss 0.613481\n",
      "Epoch 39 / Batch (17/17) / Accuracy 0.8019 / Loss 0.529451\n",
      "Epoch 39 complete, 5.625711679458618 seconds elapsed\n",
      "\n",
      "Epoch 40 starting..\n",
      "Epoch 40 / Batch (1/17) / Accuracy 0.7456 / Loss 0.599496\n",
      "Epoch 40 / Batch (2/17) / Accuracy 0.7350 / Loss 0.637154\n",
      "Epoch 40 / Batch (3/17) / Accuracy 0.8425 / Loss 0.448510\n",
      "Epoch 40 / Batch (4/17) / Accuracy 0.7544 / Loss 0.621959\n",
      "Epoch 40 / Batch (5/17) / Accuracy 0.7919 / Loss 0.536937\n",
      "Epoch 40 / Batch (6/17) / Accuracy 0.7613 / Loss 0.588349\n",
      "Epoch 40 / Batch (7/17) / Accuracy 0.7219 / Loss 0.658299\n",
      "Epoch 40 / Batch (8/17) / Accuracy 0.7725 / Loss 0.590065\n",
      "Epoch 40 / Batch (9/17) / Accuracy 0.7981 / Loss 0.493282\n",
      "Epoch 40 / Batch (10/17) / Accuracy 0.7713 / Loss 0.600142\n",
      "Epoch 40 / Batch (11/17) / Accuracy 0.7556 / Loss 0.617442\n",
      "Epoch 40 / Batch (12/17) / Accuracy 0.7625 / Loss 0.578673\n",
      "Epoch 40 / Batch (13/17) / Accuracy 0.7738 / Loss 0.568608\n",
      "Epoch 40 / Batch (14/17) / Accuracy 0.7462 / Loss 0.605529\n",
      "Epoch 40 / Batch (15/17) / Accuracy 0.7944 / Loss 0.517553\n",
      "Epoch 40 / Batch (16/17) / Accuracy 0.7375 / Loss 0.626278\n",
      "Epoch 40 / Batch (17/17) / Accuracy 0.7644 / Loss 0.584937\n",
      "Epoch 40 complete, 4.990076065063477 seconds elapsed\n",
      "\n",
      "Epoch 41 starting..\n",
      "Epoch 41 / Batch (1/17) / Accuracy 0.7563 / Loss 0.595527\n",
      "Epoch 41 / Batch (2/17) / Accuracy 0.7900 / Loss 0.539135\n",
      "Epoch 41 / Batch (3/17) / Accuracy 0.7694 / Loss 0.598998\n",
      "Epoch 41 / Batch (4/17) / Accuracy 0.7531 / Loss 0.611658\n",
      "Epoch 41 / Batch (5/17) / Accuracy 0.7631 / Loss 0.604054\n",
      "Epoch 41 / Batch (6/17) / Accuracy 0.7437 / Loss 0.638227\n",
      "Epoch 41 / Batch (7/17) / Accuracy 0.8037 / Loss 0.524932\n",
      "Epoch 41 / Batch (8/17) / Accuracy 0.7894 / Loss 0.532644\n",
      "Epoch 41 / Batch (9/17) / Accuracy 0.7200 / Loss 0.687453\n",
      "Epoch 41 / Batch (10/17) / Accuracy 0.7987 / Loss 0.511435\n",
      "Epoch 41 / Batch (11/17) / Accuracy 0.7700 / Loss 0.543864\n",
      "Epoch 41 / Batch (12/17) / Accuracy 0.7506 / Loss 0.609390\n",
      "Epoch 41 / Batch (13/17) / Accuracy 0.7625 / Loss 0.575483\n",
      "Epoch 41 / Batch (14/17) / Accuracy 0.7800 / Loss 0.537605\n",
      "Epoch 41 / Batch (15/17) / Accuracy 0.7956 / Loss 0.523735\n",
      "Epoch 41 / Batch (16/17) / Accuracy 0.7681 / Loss 0.590852\n",
      "Epoch 41 / Batch (17/17) / Accuracy 0.7406 / Loss 0.632672\n",
      "Epoch 41 complete, 5.255580186843872 seconds elapsed\n",
      "\n",
      "Epoch 42 starting..\n",
      "Epoch 42 / Batch (1/17) / Accuracy 0.7412 / Loss 0.636437\n",
      "Epoch 42 / Batch (2/17) / Accuracy 0.7744 / Loss 0.526496\n",
      "Epoch 42 / Batch (3/17) / Accuracy 0.7550 / Loss 0.589946\n",
      "Epoch 42 / Batch (4/17) / Accuracy 0.7394 / Loss 0.629341\n",
      "Epoch 42 / Batch (5/17) / Accuracy 0.7481 / Loss 0.630147\n",
      "Epoch 42 / Batch (6/17) / Accuracy 0.7356 / Loss 0.618087\n",
      "Epoch 42 / Batch (7/17) / Accuracy 0.7419 / Loss 0.606879\n",
      "Epoch 42 / Batch (8/17) / Accuracy 0.7819 / Loss 0.587587\n",
      "Epoch 42 / Batch (9/17) / Accuracy 0.7569 / Loss 0.602774\n",
      "Epoch 42 / Batch (10/17) / Accuracy 0.7869 / Loss 0.529548\n",
      "Epoch 42 / Batch (11/17) / Accuracy 0.7775 / Loss 0.555378\n",
      "Epoch 42 / Batch (12/17) / Accuracy 0.7500 / Loss 0.583581\n",
      "Epoch 42 / Batch (13/17) / Accuracy 0.7769 / Loss 0.581259\n",
      "Epoch 42 / Batch (14/17) / Accuracy 0.7862 / Loss 0.513549\n",
      "Epoch 42 / Batch (15/17) / Accuracy 0.8050 / Loss 0.512273\n",
      "Epoch 42 / Batch (16/17) / Accuracy 0.7400 / Loss 0.659383\n",
      "Epoch 42 / Batch (17/17) / Accuracy 0.7919 / Loss 0.538879\n",
      "Epoch 42 complete, 5.6109938621521 seconds elapsed\n",
      "\n",
      "Epoch 43 starting..\n",
      "Epoch 43 / Batch (1/17) / Accuracy 0.7544 / Loss 0.614980\n",
      "Epoch 43 / Batch (2/17) / Accuracy 0.7481 / Loss 0.609969\n",
      "Epoch 43 / Batch (3/17) / Accuracy 0.8219 / Loss 0.461820\n",
      "Epoch 43 / Batch (4/17) / Accuracy 0.7850 / Loss 0.550144\n",
      "Epoch 43 / Batch (5/17) / Accuracy 0.7713 / Loss 0.560958\n",
      "Epoch 43 / Batch (6/17) / Accuracy 0.7962 / Loss 0.515036\n",
      "Epoch 43 / Batch (7/17) / Accuracy 0.7575 / Loss 0.600758\n",
      "Epoch 43 / Batch (8/17) / Accuracy 0.7475 / Loss 0.603335\n",
      "Epoch 43 / Batch (9/17) / Accuracy 0.7681 / Loss 0.593269\n",
      "Epoch 43 / Batch (10/17) / Accuracy 0.7825 / Loss 0.546367\n",
      "Epoch 43 / Batch (11/17) / Accuracy 0.7606 / Loss 0.581101\n",
      "Epoch 43 / Batch (12/17) / Accuracy 0.7894 / Loss 0.533847\n",
      "Epoch 43 / Batch (13/17) / Accuracy 0.7800 / Loss 0.561816\n",
      "Epoch 43 / Batch (14/17) / Accuracy 0.7694 / Loss 0.572476\n",
      "Epoch 43 / Batch (15/17) / Accuracy 0.8031 / Loss 0.483279\n",
      "Epoch 43 / Batch (16/17) / Accuracy 0.7681 / Loss 0.569914\n",
      "Epoch 43 / Batch (17/17) / Accuracy 0.7694 / Loss 0.599355\n",
      "Epoch 43 complete, 6.343657493591309 seconds elapsed\n",
      "\n",
      "Epoch 44 starting..\n",
      "Epoch 44 / Batch (1/17) / Accuracy 0.7481 / Loss 0.574275\n",
      "Epoch 44 / Batch (2/17) / Accuracy 0.7725 / Loss 0.570949\n",
      "Epoch 44 / Batch (3/17) / Accuracy 0.7575 / Loss 0.598926\n",
      "Epoch 44 / Batch (4/17) / Accuracy 0.7850 / Loss 0.571363\n",
      "Epoch 44 / Batch (5/17) / Accuracy 0.7531 / Loss 0.619048\n",
      "Epoch 44 / Batch (6/17) / Accuracy 0.7175 / Loss 0.678136\n",
      "Epoch 44 / Batch (7/17) / Accuracy 0.7656 / Loss 0.565810\n",
      "Epoch 44 / Batch (8/17) / Accuracy 0.7600 / Loss 0.560404\n",
      "Epoch 44 / Batch (9/17) / Accuracy 0.7688 / Loss 0.581799\n",
      "Epoch 44 / Batch (10/17) / Accuracy 0.7919 / Loss 0.531293\n",
      "Epoch 44 / Batch (11/17) / Accuracy 0.7675 / Loss 0.572423\n",
      "Epoch 44 / Batch (12/17) / Accuracy 0.7931 / Loss 0.517890\n",
      "Epoch 44 / Batch (13/17) / Accuracy 0.8219 / Loss 0.466844\n",
      "Epoch 44 / Batch (14/17) / Accuracy 0.7600 / Loss 0.598294\n",
      "Epoch 44 / Batch (15/17) / Accuracy 0.7788 / Loss 0.574695\n",
      "Epoch 44 / Batch (16/17) / Accuracy 0.7931 / Loss 0.514230\n",
      "Epoch 44 / Batch (17/17) / Accuracy 0.7625 / Loss 0.590919\n",
      "Epoch 44 complete, 6.0410990715026855 seconds elapsed\n",
      "\n",
      "Epoch 45 starting..\n",
      "Epoch 45 / Batch (1/17) / Accuracy 0.7875 / Loss 0.535222\n",
      "Epoch 45 / Batch (2/17) / Accuracy 0.7800 / Loss 0.542381\n",
      "Epoch 45 / Batch (3/17) / Accuracy 0.7794 / Loss 0.542736\n",
      "Epoch 45 / Batch (4/17) / Accuracy 0.7694 / Loss 0.571193\n",
      "Epoch 45 / Batch (5/17) / Accuracy 0.7706 / Loss 0.559777\n",
      "Epoch 45 / Batch (6/17) / Accuracy 0.7750 / Loss 0.539445\n",
      "Epoch 45 / Batch (7/17) / Accuracy 0.7850 / Loss 0.520907\n",
      "Epoch 45 / Batch (8/17) / Accuracy 0.8050 / Loss 0.490381\n",
      "Epoch 45 / Batch (9/17) / Accuracy 0.7663 / Loss 0.574783\n",
      "Epoch 45 / Batch (10/17) / Accuracy 0.7631 / Loss 0.581240\n",
      "Epoch 45 / Batch (11/17) / Accuracy 0.7706 / Loss 0.587659\n",
      "Epoch 45 / Batch (12/17) / Accuracy 0.7181 / Loss 0.665954\n",
      "Epoch 45 / Batch (13/17) / Accuracy 0.7588 / Loss 0.569537\n",
      "Epoch 45 / Batch (14/17) / Accuracy 0.7788 / Loss 0.557632\n",
      "Epoch 45 / Batch (15/17) / Accuracy 0.7763 / Loss 0.576938\n",
      "Epoch 45 / Batch (16/17) / Accuracy 0.8031 / Loss 0.512303\n",
      "Epoch 45 / Batch (17/17) / Accuracy 0.7638 / Loss 0.589472\n",
      "Epoch 45 complete, 6.152706861495972 seconds elapsed\n",
      "\n",
      "Epoch 46 starting..\n",
      "Epoch 46 / Batch (1/17) / Accuracy 0.8019 / Loss 0.502549\n",
      "Epoch 46 / Batch (2/17) / Accuracy 0.7550 / Loss 0.598918\n",
      "Epoch 46 / Batch (3/17) / Accuracy 0.7831 / Loss 0.528701\n",
      "Epoch 46 / Batch (4/17) / Accuracy 0.7400 / Loss 0.601796\n",
      "Epoch 46 / Batch (5/17) / Accuracy 0.7456 / Loss 0.610037\n",
      "Epoch 46 / Batch (6/17) / Accuracy 0.7975 / Loss 0.516655\n",
      "Epoch 46 / Batch (7/17) / Accuracy 0.7337 / Loss 0.624722\n",
      "Epoch 46 / Batch (8/17) / Accuracy 0.7825 / Loss 0.561968\n",
      "Epoch 46 / Batch (9/17) / Accuracy 0.7631 / Loss 0.573842\n",
      "Epoch 46 / Batch (10/17) / Accuracy 0.7494 / Loss 0.620506\n",
      "Epoch 46 / Batch (11/17) / Accuracy 0.7763 / Loss 0.563491\n",
      "Epoch 46 / Batch (12/17) / Accuracy 0.7556 / Loss 0.617774\n",
      "Epoch 46 / Batch (13/17) / Accuracy 0.7206 / Loss 0.643971\n",
      "Epoch 46 / Batch (14/17) / Accuracy 0.7750 / Loss 0.519798\n",
      "Epoch 46 / Batch (15/17) / Accuracy 0.7619 / Loss 0.569602\n",
      "Epoch 46 / Batch (16/17) / Accuracy 0.7306 / Loss 0.646497\n",
      "Epoch 46 / Batch (17/17) / Accuracy 0.7444 / Loss 0.586144\n",
      "Epoch 46 complete, 6.319077491760254 seconds elapsed\n",
      "\n",
      "Epoch 47 starting..\n",
      "Epoch 47 / Batch (1/17) / Accuracy 0.8012 / Loss 0.525017\n",
      "Epoch 47 / Batch (2/17) / Accuracy 0.8025 / Loss 0.523165\n",
      "Epoch 47 / Batch (3/17) / Accuracy 0.7625 / Loss 0.599261\n",
      "Epoch 47 / Batch (4/17) / Accuracy 0.7731 / Loss 0.525595\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 47 / Batch (5/17) / Accuracy 0.7731 / Loss 0.545043\n",
      "Epoch 47 / Batch (6/17) / Accuracy 0.8100 / Loss 0.499352\n",
      "Epoch 47 / Batch (7/17) / Accuracy 0.7819 / Loss 0.531346\n",
      "Epoch 47 / Batch (8/17) / Accuracy 0.8112 / Loss 0.488926\n",
      "Epoch 47 / Batch (9/17) / Accuracy 0.7837 / Loss 0.537739\n",
      "Epoch 47 / Batch (10/17) / Accuracy 0.7513 / Loss 0.576242\n",
      "Epoch 47 / Batch (11/17) / Accuracy 0.7713 / Loss 0.564019\n",
      "Epoch 47 / Batch (12/17) / Accuracy 0.7738 / Loss 0.562468\n",
      "Epoch 47 / Batch (13/17) / Accuracy 0.7806 / Loss 0.566431\n",
      "Epoch 47 / Batch (14/17) / Accuracy 0.7950 / Loss 0.525890\n",
      "Epoch 47 / Batch (15/17) / Accuracy 0.7894 / Loss 0.527607\n",
      "Epoch 47 / Batch (16/17) / Accuracy 0.8163 / Loss 0.474175\n",
      "Epoch 47 / Batch (17/17) / Accuracy 0.7862 / Loss 0.515862\n",
      "Epoch 47 complete, 6.85599946975708 seconds elapsed\n",
      "\n",
      "Epoch 48 starting..\n",
      "Epoch 48 / Batch (1/17) / Accuracy 0.8144 / Loss 0.484719\n",
      "Epoch 48 / Batch (2/17) / Accuracy 0.8019 / Loss 0.512832\n",
      "Epoch 48 / Batch (3/17) / Accuracy 0.7256 / Loss 0.657767\n",
      "Epoch 48 / Batch (4/17) / Accuracy 0.8125 / Loss 0.493349\n",
      "Epoch 48 / Batch (5/17) / Accuracy 0.7650 / Loss 0.576213\n",
      "Epoch 48 / Batch (6/17) / Accuracy 0.8050 / Loss 0.493016\n",
      "Epoch 48 / Batch (7/17) / Accuracy 0.7800 / Loss 0.564959\n",
      "Epoch 48 / Batch (8/17) / Accuracy 0.8025 / Loss 0.498422\n",
      "Epoch 48 / Batch (9/17) / Accuracy 0.8044 / Loss 0.502032\n",
      "Epoch 48 / Batch (10/17) / Accuracy 0.7675 / Loss 0.596514\n",
      "Epoch 48 / Batch (11/17) / Accuracy 0.7856 / Loss 0.555954\n",
      "Epoch 48 / Batch (12/17) / Accuracy 0.7825 / Loss 0.554933\n",
      "Epoch 48 / Batch (13/17) / Accuracy 0.7538 / Loss 0.587597\n",
      "Epoch 48 / Batch (14/17) / Accuracy 0.7925 / Loss 0.500089\n",
      "Epoch 48 / Batch (15/17) / Accuracy 0.7781 / Loss 0.563488\n",
      "Epoch 48 / Batch (16/17) / Accuracy 0.7937 / Loss 0.534222\n",
      "Epoch 48 / Batch (17/17) / Accuracy 0.7844 / Loss 0.570337\n",
      "Epoch 48 complete, 6.433396339416504 seconds elapsed\n",
      "\n",
      "Epoch 49 starting..\n",
      "Epoch 49 / Batch (1/17) / Accuracy 0.7775 / Loss 0.544678\n",
      "Epoch 49 / Batch (2/17) / Accuracy 0.7819 / Loss 0.547946\n",
      "Epoch 49 / Batch (3/17) / Accuracy 0.7669 / Loss 0.563329\n",
      "Epoch 49 / Batch (4/17) / Accuracy 0.7831 / Loss 0.518582\n",
      "Epoch 49 / Batch (5/17) / Accuracy 0.7694 / Loss 0.548554\n",
      "Epoch 49 / Batch (6/17) / Accuracy 0.7906 / Loss 0.553213\n",
      "Epoch 49 / Batch (7/17) / Accuracy 0.7956 / Loss 0.511577\n",
      "Epoch 49 / Batch (8/17) / Accuracy 0.7525 / Loss 0.614741\n",
      "Epoch 49 / Batch (9/17) / Accuracy 0.7869 / Loss 0.566810\n",
      "Epoch 49 / Batch (10/17) / Accuracy 0.7825 / Loss 0.535831\n",
      "Epoch 49 / Batch (11/17) / Accuracy 0.7613 / Loss 0.573087\n",
      "Epoch 49 / Batch (12/17) / Accuracy 0.7994 / Loss 0.510993\n",
      "Epoch 49 / Batch (13/17) / Accuracy 0.7681 / Loss 0.607790\n",
      "Epoch 49 / Batch (14/17) / Accuracy 0.7744 / Loss 0.579570\n",
      "Epoch 49 / Batch (15/17) / Accuracy 0.7812 / Loss 0.551010\n",
      "Epoch 49 / Batch (16/17) / Accuracy 0.7763 / Loss 0.565012\n",
      "Epoch 49 / Batch (17/17) / Accuracy 0.7969 / Loss 0.506595\n",
      "Epoch 49 complete, 6.561055898666382 seconds elapsed\n",
      "\n",
      "Epoch 50 starting..\n",
      "Epoch 50 / Batch (1/17) / Accuracy 0.8019 / Loss 0.507604\n",
      "Epoch 50 / Batch (2/17) / Accuracy 0.8056 / Loss 0.508082\n",
      "Epoch 50 / Batch (3/17) / Accuracy 0.7650 / Loss 0.569003\n",
      "Epoch 50 / Batch (4/17) / Accuracy 0.7631 / Loss 0.558102\n",
      "Epoch 50 / Batch (5/17) / Accuracy 0.8331 / Loss 0.450630\n",
      "Epoch 50 / Batch (6/17) / Accuracy 0.7894 / Loss 0.558681\n",
      "Epoch 50 / Batch (7/17) / Accuracy 0.7663 / Loss 0.610860\n",
      "Epoch 50 / Batch (8/17) / Accuracy 0.7425 / Loss 0.621898\n",
      "Epoch 50 / Batch (9/17) / Accuracy 0.7431 / Loss 0.583785\n",
      "Epoch 50 / Batch (10/17) / Accuracy 0.7563 / Loss 0.617877\n",
      "Epoch 50 / Batch (11/17) / Accuracy 0.7625 / Loss 0.582801\n",
      "Epoch 50 / Batch (12/17) / Accuracy 0.7994 / Loss 0.524788\n",
      "Epoch 50 / Batch (13/17) / Accuracy 0.7925 / Loss 0.537015\n",
      "Epoch 50 / Batch (14/17) / Accuracy 0.7894 / Loss 0.529601\n",
      "Epoch 50 / Batch (15/17) / Accuracy 0.7837 / Loss 0.524907\n",
      "Epoch 50 / Batch (16/17) / Accuracy 0.7844 / Loss 0.527439\n",
      "Epoch 50 / Batch (17/17) / Accuracy 0.7788 / Loss 0.565470\n",
      "Epoch 50 complete, 6.528847694396973 seconds elapsed\n",
      "\n",
      "Epoch 51 starting..\n",
      "Epoch 51 / Batch (1/17) / Accuracy 0.7281 / Loss 0.657621\n",
      "Epoch 51 / Batch (2/17) / Accuracy 0.7700 / Loss 0.569763\n",
      "Epoch 51 / Batch (3/17) / Accuracy 0.7819 / Loss 0.558684\n",
      "Epoch 51 / Batch (4/17) / Accuracy 0.7656 / Loss 0.568983\n",
      "Epoch 51 / Batch (5/17) / Accuracy 0.7713 / Loss 0.570421\n",
      "Epoch 51 / Batch (6/17) / Accuracy 0.8144 / Loss 0.488388\n",
      "Epoch 51 / Batch (7/17) / Accuracy 0.8294 / Loss 0.449743\n",
      "Epoch 51 / Batch (8/17) / Accuracy 0.8200 / Loss 0.439834\n",
      "Epoch 51 / Batch (9/17) / Accuracy 0.7887 / Loss 0.552084\n",
      "Epoch 51 / Batch (10/17) / Accuracy 0.7544 / Loss 0.606750\n",
      "Epoch 51 / Batch (11/17) / Accuracy 0.8050 / Loss 0.503693\n",
      "Epoch 51 / Batch (12/17) / Accuracy 0.7800 / Loss 0.524663\n",
      "Epoch 51 / Batch (13/17) / Accuracy 0.7769 / Loss 0.543281\n",
      "Epoch 51 / Batch (14/17) / Accuracy 0.7919 / Loss 0.546617\n",
      "Epoch 51 / Batch (15/17) / Accuracy 0.7387 / Loss 0.644913\n",
      "Epoch 51 / Batch (16/17) / Accuracy 0.7881 / Loss 0.519308\n",
      "Epoch 51 / Batch (17/17) / Accuracy 0.7581 / Loss 0.588061\n",
      "Epoch 51 complete, 6.237921237945557 seconds elapsed\n",
      "\n",
      "Epoch 52 starting..\n",
      "Epoch 52 / Batch (1/17) / Accuracy 0.7887 / Loss 0.510040\n",
      "Epoch 52 / Batch (2/17) / Accuracy 0.7656 / Loss 0.598279\n",
      "Epoch 52 / Batch (3/17) / Accuracy 0.7738 / Loss 0.592255\n",
      "Epoch 52 / Batch (4/17) / Accuracy 0.7781 / Loss 0.577493\n",
      "Epoch 52 / Batch (5/17) / Accuracy 0.7444 / Loss 0.611286\n",
      "Epoch 52 / Batch (6/17) / Accuracy 0.7613 / Loss 0.591593\n",
      "Epoch 52 / Batch (7/17) / Accuracy 0.7412 / Loss 0.633579\n",
      "Epoch 52 / Batch (8/17) / Accuracy 0.7663 / Loss 0.615460\n",
      "Epoch 52 / Batch (9/17) / Accuracy 0.7744 / Loss 0.550231\n",
      "Epoch 52 / Batch (10/17) / Accuracy 0.7456 / Loss 0.600747\n",
      "Epoch 52 / Batch (11/17) / Accuracy 0.7613 / Loss 0.551721\n",
      "Epoch 52 / Batch (12/17) / Accuracy 0.7763 / Loss 0.571847\n",
      "Epoch 52 / Batch (13/17) / Accuracy 0.7525 / Loss 0.615449\n",
      "Epoch 52 / Batch (14/17) / Accuracy 0.7994 / Loss 0.491441\n",
      "Epoch 52 / Batch (15/17) / Accuracy 0.7469 / Loss 0.618179\n",
      "Epoch 52 / Batch (16/17) / Accuracy 0.7788 / Loss 0.561546\n",
      "Epoch 52 / Batch (17/17) / Accuracy 0.7613 / Loss 0.617107\n",
      "Epoch 52 complete, 5.86548113822937 seconds elapsed\n",
      "\n",
      "Epoch 53 starting..\n",
      "Epoch 53 / Batch (1/17) / Accuracy 0.7469 / Loss 0.633968\n",
      "Epoch 53 / Batch (2/17) / Accuracy 0.7688 / Loss 0.545882\n",
      "Epoch 53 / Batch (3/17) / Accuracy 0.7781 / Loss 0.587466\n",
      "Epoch 53 / Batch (4/17) / Accuracy 0.7563 / Loss 0.619537\n",
      "Epoch 53 / Batch (5/17) / Accuracy 0.7738 / Loss 0.517561\n",
      "Epoch 53 / Batch (6/17) / Accuracy 0.7731 / Loss 0.580795\n",
      "Epoch 53 / Batch (7/17) / Accuracy 0.7894 / Loss 0.531238\n",
      "Epoch 53 / Batch (8/17) / Accuracy 0.6950 / Loss 0.754638\n",
      "Epoch 53 / Batch (9/17) / Accuracy 0.7731 / Loss 0.562057\n",
      "Epoch 53 / Batch (10/17) / Accuracy 0.7663 / Loss 0.568182\n",
      "Epoch 53 / Batch (11/17) / Accuracy 0.7638 / Loss 0.587008\n",
      "Epoch 53 / Batch (12/17) / Accuracy 0.7975 / Loss 0.511823\n",
      "Epoch 53 / Batch (13/17) / Accuracy 0.7631 / Loss 0.572006\n",
      "Epoch 53 / Batch (14/17) / Accuracy 0.8213 / Loss 0.468935\n",
      "Epoch 53 / Batch (15/17) / Accuracy 0.7744 / Loss 0.569610\n",
      "Epoch 53 / Batch (16/17) / Accuracy 0.7675 / Loss 0.544624\n",
      "Epoch 53 / Batch (17/17) / Accuracy 0.7875 / Loss 0.517004\n",
      "Epoch 53 complete, 6.774399518966675 seconds elapsed\n",
      "\n",
      "Epoch 54 starting..\n",
      "Epoch 54 / Batch (1/17) / Accuracy 0.7975 / Loss 0.549732\n",
      "Epoch 54 / Batch (2/17) / Accuracy 0.7912 / Loss 0.513504\n",
      "Epoch 54 / Batch (3/17) / Accuracy 0.7800 / Loss 0.549438\n",
      "Epoch 54 / Batch (4/17) / Accuracy 0.8000 / Loss 0.517690\n",
      "Epoch 54 / Batch (5/17) / Accuracy 0.7613 / Loss 0.582578\n",
      "Epoch 54 / Batch (6/17) / Accuracy 0.7875 / Loss 0.490676\n",
      "Epoch 54 / Batch (7/17) / Accuracy 0.7900 / Loss 0.516330\n",
      "Epoch 54 / Batch (8/17) / Accuracy 0.7869 / Loss 0.529207\n",
      "Epoch 54 / Batch (9/17) / Accuracy 0.8144 / Loss 0.482022\n",
      "Epoch 54 / Batch (10/17) / Accuracy 0.7544 / Loss 0.622842\n",
      "Epoch 54 / Batch (11/17) / Accuracy 0.8006 / Loss 0.524432\n",
      "Epoch 54 / Batch (12/17) / Accuracy 0.7444 / Loss 0.616671\n",
      "Epoch 54 / Batch (13/17) / Accuracy 0.7731 / Loss 0.539669\n",
      "Epoch 54 / Batch (14/17) / Accuracy 0.7837 / Loss 0.564657\n",
      "Epoch 54 / Batch (15/17) / Accuracy 0.7925 / Loss 0.508296\n",
      "Epoch 54 / Batch (16/17) / Accuracy 0.7706 / Loss 0.558902\n",
      "Epoch 54 / Batch (17/17) / Accuracy 0.7937 / Loss 0.553424\n",
      "Epoch 54 complete, 6.717164516448975 seconds elapsed\n",
      "\n",
      "Epoch 55 starting..\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 55 / Batch (1/17) / Accuracy 0.7906 / Loss 0.532653\n",
      "Epoch 55 / Batch (2/17) / Accuracy 0.7769 / Loss 0.545819\n",
      "Epoch 55 / Batch (3/17) / Accuracy 0.7556 / Loss 0.588435\n",
      "Epoch 55 / Batch (4/17) / Accuracy 0.7856 / Loss 0.544359\n",
      "Epoch 55 / Batch (5/17) / Accuracy 0.8062 / Loss 0.495049\n",
      "Epoch 55 / Batch (6/17) / Accuracy 0.7800 / Loss 0.547436\n",
      "Epoch 55 / Batch (7/17) / Accuracy 0.7850 / Loss 0.546109\n",
      "Epoch 55 / Batch (8/17) / Accuracy 0.7588 / Loss 0.583035\n",
      "Epoch 55 / Batch (9/17) / Accuracy 0.7750 / Loss 0.566512\n",
      "Epoch 55 / Batch (10/17) / Accuracy 0.7931 / Loss 0.509142\n",
      "Epoch 55 / Batch (11/17) / Accuracy 0.7969 / Loss 0.526846\n",
      "Epoch 55 / Batch (12/17) / Accuracy 0.8225 / Loss 0.472315\n",
      "Epoch 55 / Batch (13/17) / Accuracy 0.7806 / Loss 0.556919\n",
      "Epoch 55 / Batch (14/17) / Accuracy 0.7400 / Loss 0.651433\n",
      "Epoch 55 / Batch (15/17) / Accuracy 0.7919 / Loss 0.545217\n",
      "Epoch 55 / Batch (16/17) / Accuracy 0.8119 / Loss 0.499774\n",
      "Epoch 55 / Batch (17/17) / Accuracy 0.7837 / Loss 0.531871\n",
      "Epoch 55 complete, 6.88456654548645 seconds elapsed\n",
      "\n",
      "Epoch 56 starting..\n",
      "Epoch 56 / Batch (1/17) / Accuracy 0.7781 / Loss 0.535437\n",
      "Epoch 56 / Batch (2/17) / Accuracy 0.7594 / Loss 0.579506\n",
      "Epoch 56 / Batch (3/17) / Accuracy 0.7494 / Loss 0.601247\n",
      "Epoch 56 / Batch (4/17) / Accuracy 0.7594 / Loss 0.606743\n",
      "Epoch 56 / Batch (5/17) / Accuracy 0.7788 / Loss 0.547741\n",
      "Epoch 56 / Batch (6/17) / Accuracy 0.7563 / Loss 0.598853\n",
      "Epoch 56 / Batch (7/17) / Accuracy 0.7788 / Loss 0.549677\n",
      "Epoch 56 / Batch (8/17) / Accuracy 0.7750 / Loss 0.533965\n",
      "Epoch 56 / Batch (9/17) / Accuracy 0.7437 / Loss 0.584099\n",
      "Epoch 56 / Batch (10/17) / Accuracy 0.7212 / Loss 0.685255\n",
      "Epoch 56 / Batch (11/17) / Accuracy 0.7887 / Loss 0.568642\n",
      "Epoch 56 / Batch (12/17) / Accuracy 0.7744 / Loss 0.559112\n",
      "Epoch 56 / Batch (13/17) / Accuracy 0.7613 / Loss 0.601682\n",
      "Epoch 56 / Batch (14/17) / Accuracy 0.7788 / Loss 0.563280\n",
      "Epoch 56 / Batch (15/17) / Accuracy 0.7906 / Loss 0.523595\n",
      "Epoch 56 / Batch (16/17) / Accuracy 0.7856 / Loss 0.538068\n",
      "Epoch 56 / Batch (17/17) / Accuracy 0.7631 / Loss 0.566454\n",
      "Epoch 56 complete, 6.393730640411377 seconds elapsed\n",
      "\n",
      "Epoch 57 starting..\n",
      "Epoch 57 / Batch (1/17) / Accuracy 0.7681 / Loss 0.550064\n",
      "Epoch 57 / Batch (2/17) / Accuracy 0.7869 / Loss 0.545119\n",
      "Epoch 57 / Batch (3/17) / Accuracy 0.7850 / Loss 0.534845\n",
      "Epoch 57 / Batch (4/17) / Accuracy 0.7706 / Loss 0.587153\n",
      "Epoch 57 / Batch (5/17) / Accuracy 0.7531 / Loss 0.595723\n",
      "Epoch 57 / Batch (6/17) / Accuracy 0.8056 / Loss 0.487757\n",
      "Epoch 57 / Batch (7/17) / Accuracy 0.7225 / Loss 0.640372\n",
      "Epoch 57 / Batch (8/17) / Accuracy 0.7319 / Loss 0.634169\n",
      "Epoch 57 / Batch (9/17) / Accuracy 0.7394 / Loss 0.631261\n",
      "Epoch 57 / Batch (10/17) / Accuracy 0.7800 / Loss 0.545758\n",
      "Epoch 57 / Batch (11/17) / Accuracy 0.7419 / Loss 0.631411\n",
      "Epoch 57 / Batch (12/17) / Accuracy 0.7619 / Loss 0.580631\n",
      "Epoch 57 / Batch (13/17) / Accuracy 0.7619 / Loss 0.603042\n",
      "Epoch 57 / Batch (14/17) / Accuracy 0.7831 / Loss 0.543420\n",
      "Epoch 57 / Batch (15/17) / Accuracy 0.7594 / Loss 0.614233\n",
      "Epoch 57 / Batch (16/17) / Accuracy 0.7475 / Loss 0.630047\n",
      "Epoch 57 / Batch (17/17) / Accuracy 0.7544 / Loss 0.579837\n",
      "Epoch 57 complete, 6.75265097618103 seconds elapsed\n",
      "\n",
      "Epoch 58 starting..\n",
      "Epoch 58 / Batch (1/17) / Accuracy 0.7756 / Loss 0.572871\n",
      "Epoch 58 / Batch (2/17) / Accuracy 0.7931 / Loss 0.558604\n",
      "Epoch 58 / Batch (3/17) / Accuracy 0.7550 / Loss 0.578726\n",
      "Epoch 58 / Batch (4/17) / Accuracy 0.7700 / Loss 0.562815\n",
      "Epoch 58 / Batch (5/17) / Accuracy 0.7875 / Loss 0.549527\n",
      "Epoch 58 / Batch (6/17) / Accuracy 0.7763 / Loss 0.550825\n",
      "Epoch 58 / Batch (7/17) / Accuracy 0.7887 / Loss 0.527912\n",
      "Epoch 58 / Batch (8/17) / Accuracy 0.7925 / Loss 0.530904\n",
      "Epoch 58 / Batch (9/17) / Accuracy 0.7519 / Loss 0.593157\n",
      "Epoch 58 / Batch (10/17) / Accuracy 0.7775 / Loss 0.554407\n",
      "Epoch 58 / Batch (11/17) / Accuracy 0.7906 / Loss 0.524363\n",
      "Epoch 58 / Batch (12/17) / Accuracy 0.7594 / Loss 0.625589\n",
      "Epoch 58 / Batch (13/17) / Accuracy 0.7656 / Loss 0.565720\n",
      "Epoch 58 / Batch (14/17) / Accuracy 0.7769 / Loss 0.582869\n",
      "Epoch 58 / Batch (15/17) / Accuracy 0.7975 / Loss 0.499941\n",
      "Epoch 58 / Batch (16/17) / Accuracy 0.7837 / Loss 0.522462\n",
      "Epoch 58 / Batch (17/17) / Accuracy 0.7825 / Loss 0.557532\n",
      "Epoch 58 complete, 6.3768839836120605 seconds elapsed\n",
      "\n",
      "Epoch 59 starting..\n",
      "Epoch 59 / Batch (1/17) / Accuracy 0.7931 / Loss 0.497454\n",
      "Epoch 59 / Batch (2/17) / Accuracy 0.7619 / Loss 0.575499\n",
      "Epoch 59 / Batch (3/17) / Accuracy 0.7594 / Loss 0.594333\n",
      "Epoch 59 / Batch (4/17) / Accuracy 0.7563 / Loss 0.601653\n",
      "Epoch 59 / Batch (5/17) / Accuracy 0.7625 / Loss 0.606399\n",
      "Epoch 59 / Batch (6/17) / Accuracy 0.7538 / Loss 0.623464\n",
      "Epoch 59 / Batch (7/17) / Accuracy 0.7525 / Loss 0.629410\n",
      "Epoch 59 / Batch (8/17) / Accuracy 0.7613 / Loss 0.592529\n",
      "Epoch 59 / Batch (9/17) / Accuracy 0.7844 / Loss 0.552425\n",
      "Epoch 59 / Batch (10/17) / Accuracy 0.7456 / Loss 0.603313\n",
      "Epoch 59 / Batch (11/17) / Accuracy 0.7513 / Loss 0.635405\n",
      "Epoch 59 / Batch (12/17) / Accuracy 0.7200 / Loss 0.696057\n",
      "Epoch 59 / Batch (13/17) / Accuracy 0.7287 / Loss 0.644773\n",
      "Epoch 59 / Batch (14/17) / Accuracy 0.7869 / Loss 0.547416\n",
      "Epoch 59 / Batch (15/17) / Accuracy 0.7563 / Loss 0.617485\n",
      "Epoch 59 / Batch (16/17) / Accuracy 0.6913 / Loss 0.695570\n",
      "Epoch 59 / Batch (17/17) / Accuracy 0.7894 / Loss 0.529161\n",
      "Epoch 59 complete, 6.533658027648926 seconds elapsed\n",
      "\n",
      "Epoch 60 starting..\n",
      "Epoch 60 / Batch (1/17) / Accuracy 0.7431 / Loss 0.622623\n",
      "Epoch 60 / Batch (2/17) / Accuracy 0.7275 / Loss 0.666389\n",
      "Epoch 60 / Batch (3/17) / Accuracy 0.7644 / Loss 0.598264\n",
      "Epoch 60 / Batch (4/17) / Accuracy 0.7231 / Loss 0.664296\n",
      "Epoch 60 / Batch (5/17) / Accuracy 0.7350 / Loss 0.663044\n",
      "Epoch 60 / Batch (6/17) / Accuracy 0.7944 / Loss 0.513985\n",
      "Epoch 60 / Batch (7/17) / Accuracy 0.7806 / Loss 0.531367\n",
      "Epoch 60 / Batch (8/17) / Accuracy 0.7469 / Loss 0.594802\n",
      "Epoch 60 / Batch (9/17) / Accuracy 0.7619 / Loss 0.588736\n",
      "Epoch 60 / Batch (10/17) / Accuracy 0.7919 / Loss 0.529750\n",
      "Epoch 60 / Batch (11/17) / Accuracy 0.7269 / Loss 0.675876\n",
      "Epoch 60 / Batch (12/17) / Accuracy 0.7956 / Loss 0.491027\n",
      "Epoch 60 / Batch (13/17) / Accuracy 0.7875 / Loss 0.548967\n",
      "Epoch 60 / Batch (14/17) / Accuracy 0.7688 / Loss 0.582515\n",
      "Epoch 60 / Batch (15/17) / Accuracy 0.7956 / Loss 0.520095\n",
      "Epoch 60 / Batch (16/17) / Accuracy 0.8006 / Loss 0.521473\n",
      "Epoch 60 / Batch (17/17) / Accuracy 0.7462 / Loss 0.615096\n",
      "Epoch 60 complete, 6.640803813934326 seconds elapsed\n",
      "\n",
      "Epoch 61 starting..\n",
      "Epoch 61 / Batch (1/17) / Accuracy 0.8150 / Loss 0.482761\n",
      "Epoch 61 / Batch (2/17) / Accuracy 0.8056 / Loss 0.507387\n",
      "Epoch 61 / Batch (3/17) / Accuracy 0.7750 / Loss 0.568774\n",
      "Epoch 61 / Batch (4/17) / Accuracy 0.7862 / Loss 0.514517\n",
      "Epoch 61 / Batch (5/17) / Accuracy 0.7237 / Loss 0.637969\n",
      "Epoch 61 / Batch (6/17) / Accuracy 0.7831 / Loss 0.537858\n",
      "Epoch 61 / Batch (7/17) / Accuracy 0.8062 / Loss 0.501175\n",
      "Epoch 61 / Batch (8/17) / Accuracy 0.7713 / Loss 0.559815\n",
      "Epoch 61 / Batch (9/17) / Accuracy 0.8069 / Loss 0.488941\n",
      "Epoch 61 / Batch (10/17) / Accuracy 0.7694 / Loss 0.561401\n",
      "Epoch 61 / Batch (11/17) / Accuracy 0.7819 / Loss 0.536627\n",
      "Epoch 61 / Batch (12/17) / Accuracy 0.7663 / Loss 0.609915\n",
      "Epoch 61 / Batch (13/17) / Accuracy 0.8012 / Loss 0.529194\n",
      "Epoch 61 / Batch (14/17) / Accuracy 0.7719 / Loss 0.584765\n",
      "Epoch 61 / Batch (15/17) / Accuracy 0.7944 / Loss 0.519055\n",
      "Epoch 61 / Batch (16/17) / Accuracy 0.7450 / Loss 0.614608\n",
      "Epoch 61 / Batch (17/17) / Accuracy 0.7450 / Loss 0.632538\n",
      "Epoch 61 complete, 6.592204570770264 seconds elapsed\n",
      "\n",
      "Epoch 62 starting..\n",
      "Epoch 62 / Batch (1/17) / Accuracy 0.7950 / Loss 0.516474\n",
      "Epoch 62 / Batch (2/17) / Accuracy 0.7631 / Loss 0.607858\n",
      "Epoch 62 / Batch (3/17) / Accuracy 0.7469 / Loss 0.597790\n",
      "Epoch 62 / Batch (4/17) / Accuracy 0.7806 / Loss 0.588523\n",
      "Epoch 62 / Batch (5/17) / Accuracy 0.7694 / Loss 0.580075\n",
      "Epoch 62 / Batch (6/17) / Accuracy 0.7669 / Loss 0.580719\n",
      "Epoch 62 / Batch (7/17) / Accuracy 0.7644 / Loss 0.577207\n",
      "Epoch 62 / Batch (8/17) / Accuracy 0.7969 / Loss 0.508985\n",
      "Epoch 62 / Batch (9/17) / Accuracy 0.7613 / Loss 0.580250\n",
      "Epoch 62 / Batch (10/17) / Accuracy 0.7862 / Loss 0.524582\n",
      "Epoch 62 / Batch (11/17) / Accuracy 0.7769 / Loss 0.554567\n",
      "Epoch 62 / Batch (12/17) / Accuracy 0.7738 / Loss 0.578478\n",
      "Epoch 62 / Batch (13/17) / Accuracy 0.7325 / Loss 0.652235\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 62 / Batch (14/17) / Accuracy 0.7700 / Loss 0.557003\n",
      "Epoch 62 / Batch (15/17) / Accuracy 0.7588 / Loss 0.611269\n",
      "Epoch 62 / Batch (16/17) / Accuracy 0.8025 / Loss 0.484347\n",
      "Epoch 62 / Batch (17/17) / Accuracy 0.7887 / Loss 0.535912\n",
      "Epoch 62 complete, 6.5488996505737305 seconds elapsed\n",
      "\n",
      "Epoch 63 starting..\n",
      "Epoch 63 / Batch (1/17) / Accuracy 0.7837 / Loss 0.498237\n",
      "Epoch 63 / Batch (2/17) / Accuracy 0.7619 / Loss 0.577309\n",
      "Epoch 63 / Batch (3/17) / Accuracy 0.8006 / Loss 0.487259\n",
      "Epoch 63 / Batch (4/17) / Accuracy 0.7513 / Loss 0.551923\n",
      "Epoch 63 / Batch (5/17) / Accuracy 0.7862 / Loss 0.520128\n",
      "Epoch 63 / Batch (6/17) / Accuracy 0.7563 / Loss 0.594753\n",
      "Epoch 63 / Batch (7/17) / Accuracy 0.7819 / Loss 0.573788\n",
      "Epoch 63 / Batch (8/17) / Accuracy 0.7887 / Loss 0.534371\n",
      "Epoch 63 / Batch (9/17) / Accuracy 0.8062 / Loss 0.491046\n",
      "Epoch 63 / Batch (10/17) / Accuracy 0.7650 / Loss 0.570614\n",
      "Epoch 63 / Batch (11/17) / Accuracy 0.8194 / Loss 0.495364\n",
      "Epoch 63 / Batch (12/17) / Accuracy 0.7794 / Loss 0.547031\n",
      "Epoch 63 / Batch (13/17) / Accuracy 0.7450 / Loss 0.580817\n",
      "Epoch 63 / Batch (14/17) / Accuracy 0.8031 / Loss 0.502658\n",
      "Epoch 63 / Batch (15/17) / Accuracy 0.7713 / Loss 0.568410\n",
      "Epoch 63 / Batch (16/17) / Accuracy 0.7819 / Loss 0.564424\n",
      "Epoch 63 / Batch (17/17) / Accuracy 0.7856 / Loss 0.545822\n",
      "Epoch 63 complete, 6.481101751327515 seconds elapsed\n",
      "\n",
      "Epoch 64 starting..\n",
      "Epoch 64 / Batch (1/17) / Accuracy 0.7462 / Loss 0.632114\n",
      "Epoch 64 / Batch (2/17) / Accuracy 0.7469 / Loss 0.613509\n",
      "Epoch 64 / Batch (3/17) / Accuracy 0.7588 / Loss 0.550707\n",
      "Epoch 64 / Batch (4/17) / Accuracy 0.7731 / Loss 0.583767\n",
      "Epoch 64 / Batch (5/17) / Accuracy 0.7656 / Loss 0.580112\n",
      "Epoch 64 / Batch (6/17) / Accuracy 0.7700 / Loss 0.530206\n",
      "Epoch 64 / Batch (7/17) / Accuracy 0.8244 / Loss 0.467543\n",
      "Epoch 64 / Batch (8/17) / Accuracy 0.7450 / Loss 0.626944\n",
      "Epoch 64 / Batch (9/17) / Accuracy 0.7331 / Loss 0.641273\n",
      "Epoch 64 / Batch (10/17) / Accuracy 0.7725 / Loss 0.586765\n",
      "Epoch 64 / Batch (11/17) / Accuracy 0.7788 / Loss 0.540841\n",
      "Epoch 64 / Batch (12/17) / Accuracy 0.7619 / Loss 0.569802\n",
      "Epoch 64 / Batch (13/17) / Accuracy 0.8050 / Loss 0.506698\n",
      "Epoch 64 / Batch (14/17) / Accuracy 0.7450 / Loss 0.608162\n",
      "Epoch 64 / Batch (15/17) / Accuracy 0.8119 / Loss 0.466236\n",
      "Epoch 64 / Batch (16/17) / Accuracy 0.7450 / Loss 0.605247\n",
      "Epoch 64 / Batch (17/17) / Accuracy 0.7613 / Loss 0.549796\n",
      "Epoch 64 complete, 6.713230609893799 seconds elapsed\n",
      "\n",
      "Epoch 65 starting..\n",
      "Epoch 65 / Batch (1/17) / Accuracy 0.8006 / Loss 0.513247\n",
      "Epoch 65 / Batch (2/17) / Accuracy 0.7694 / Loss 0.572867\n",
      "Epoch 65 / Batch (3/17) / Accuracy 0.8037 / Loss 0.499668\n",
      "Epoch 65 / Batch (4/17) / Accuracy 0.7581 / Loss 0.578610\n",
      "Epoch 65 / Batch (5/17) / Accuracy 0.7869 / Loss 0.539684\n",
      "Epoch 65 / Batch (6/17) / Accuracy 0.8138 / Loss 0.500953\n",
      "Epoch 65 / Batch (7/17) / Accuracy 0.7594 / Loss 0.585633\n",
      "Epoch 65 / Batch (8/17) / Accuracy 0.7969 / Loss 0.504835\n",
      "Epoch 65 / Batch (9/17) / Accuracy 0.8050 / Loss 0.481069\n",
      "Epoch 65 / Batch (10/17) / Accuracy 0.7519 / Loss 0.591670\n",
      "Epoch 65 / Batch (11/17) / Accuracy 0.7912 / Loss 0.541011\n",
      "Epoch 65 / Batch (12/17) / Accuracy 0.7638 / Loss 0.593392\n",
      "Epoch 65 / Batch (13/17) / Accuracy 0.7731 / Loss 0.596562\n",
      "Epoch 65 / Batch (14/17) / Accuracy 0.7606 / Loss 0.556005\n",
      "Epoch 65 / Batch (15/17) / Accuracy 0.7875 / Loss 0.532518\n",
      "Epoch 65 / Batch (16/17) / Accuracy 0.7775 / Loss 0.560068\n",
      "Epoch 65 / Batch (17/17) / Accuracy 0.7775 / Loss 0.527797\n",
      "Epoch 65 complete, 6.563365459442139 seconds elapsed\n",
      "\n",
      "Epoch 66 starting..\n",
      "Epoch 66 / Batch (1/17) / Accuracy 0.7900 / Loss 0.517402\n",
      "Epoch 66 / Batch (2/17) / Accuracy 0.8112 / Loss 0.492099\n",
      "Epoch 66 / Batch (3/17) / Accuracy 0.7625 / Loss 0.568576\n",
      "Epoch 66 / Batch (4/17) / Accuracy 0.7613 / Loss 0.614024\n",
      "Epoch 66 / Batch (5/17) / Accuracy 0.7675 / Loss 0.571769\n",
      "Epoch 66 / Batch (6/17) / Accuracy 0.8200 / Loss 0.483826\n",
      "Epoch 66 / Batch (7/17) / Accuracy 0.7900 / Loss 0.554464\n",
      "Epoch 66 / Batch (8/17) / Accuracy 0.8094 / Loss 0.489677\n",
      "Epoch 66 / Batch (9/17) / Accuracy 0.7794 / Loss 0.548176\n",
      "Epoch 66 / Batch (10/17) / Accuracy 0.7944 / Loss 0.529256\n",
      "Epoch 66 / Batch (11/17) / Accuracy 0.7756 / Loss 0.571458\n",
      "Epoch 66 / Batch (12/17) / Accuracy 0.7887 / Loss 0.524328\n",
      "Epoch 66 / Batch (13/17) / Accuracy 0.8050 / Loss 0.512735\n",
      "Epoch 66 / Batch (14/17) / Accuracy 0.7513 / Loss 0.597581\n",
      "Epoch 66 / Batch (15/17) / Accuracy 0.7812 / Loss 0.550962\n",
      "Epoch 66 / Batch (16/17) / Accuracy 0.7887 / Loss 0.535841\n",
      "Epoch 66 / Batch (17/17) / Accuracy 0.7713 / Loss 0.548101\n",
      "Epoch 66 complete, 6.452970266342163 seconds elapsed\n",
      "\n",
      "Epoch 67 starting..\n",
      "Epoch 67 / Batch (1/17) / Accuracy 0.7937 / Loss 0.518652\n",
      "Epoch 67 / Batch (2/17) / Accuracy 0.7900 / Loss 0.512201\n",
      "Epoch 67 / Batch (3/17) / Accuracy 0.7819 / Loss 0.528048\n",
      "Epoch 67 / Batch (4/17) / Accuracy 0.7694 / Loss 0.550597\n",
      "Epoch 67 / Batch (5/17) / Accuracy 0.7738 / Loss 0.579013\n",
      "Epoch 67 / Batch (6/17) / Accuracy 0.7619 / Loss 0.581630\n",
      "Epoch 67 / Batch (7/17) / Accuracy 0.7638 / Loss 0.561463\n",
      "Epoch 67 / Batch (8/17) / Accuracy 0.7619 / Loss 0.575598\n",
      "Epoch 67 / Batch (9/17) / Accuracy 0.7956 / Loss 0.521772\n",
      "Epoch 67 / Batch (10/17) / Accuracy 0.7669 / Loss 0.579733\n",
      "Epoch 67 / Batch (11/17) / Accuracy 0.7594 / Loss 0.596375\n",
      "Epoch 67 / Batch (12/17) / Accuracy 0.7994 / Loss 0.479207\n",
      "Epoch 67 / Batch (13/17) / Accuracy 0.7588 / Loss 0.598753\n",
      "Epoch 67 / Batch (14/17) / Accuracy 0.7781 / Loss 0.544453\n",
      "Epoch 67 / Batch (15/17) / Accuracy 0.7656 / Loss 0.566242\n",
      "Epoch 67 / Batch (16/17) / Accuracy 0.7675 / Loss 0.572640\n",
      "Epoch 67 / Batch (17/17) / Accuracy 0.8150 / Loss 0.492332\n",
      "Epoch 67 complete, 6.289172172546387 seconds elapsed\n",
      "\n",
      "Epoch 68 starting..\n",
      "Epoch 68 / Batch (1/17) / Accuracy 0.7800 / Loss 0.530659\n",
      "Epoch 68 / Batch (2/17) / Accuracy 0.7925 / Loss 0.531988\n",
      "Epoch 68 / Batch (3/17) / Accuracy 0.8094 / Loss 0.512325\n",
      "Epoch 68 / Batch (4/17) / Accuracy 0.7962 / Loss 0.512179\n",
      "Epoch 68 / Batch (5/17) / Accuracy 0.7731 / Loss 0.551544\n",
      "Epoch 68 / Batch (6/17) / Accuracy 0.7719 / Loss 0.583137\n",
      "Epoch 68 / Batch (7/17) / Accuracy 0.7563 / Loss 0.613272\n",
      "Epoch 68 / Batch (8/17) / Accuracy 0.7656 / Loss 0.584083\n",
      "Epoch 68 / Batch (9/17) / Accuracy 0.7719 / Loss 0.543565\n",
      "Epoch 68 / Batch (10/17) / Accuracy 0.7981 / Loss 0.506164\n",
      "Epoch 68 / Batch (11/17) / Accuracy 0.7694 / Loss 0.553758\n",
      "Epoch 68 / Batch (12/17) / Accuracy 0.7862 / Loss 0.531579\n",
      "Epoch 68 / Batch (13/17) / Accuracy 0.7500 / Loss 0.631834\n",
      "Epoch 68 / Batch (14/17) / Accuracy 0.7925 / Loss 0.536947\n",
      "Epoch 68 / Batch (15/17) / Accuracy 0.7969 / Loss 0.519994\n",
      "Epoch 68 / Batch (16/17) / Accuracy 0.7713 / Loss 0.560881\n",
      "Epoch 68 / Batch (17/17) / Accuracy 0.7619 / Loss 0.586960\n",
      "Epoch 68 complete, 6.340097188949585 seconds elapsed\n",
      "\n",
      "Epoch 69 starting..\n",
      "Epoch 69 / Batch (1/17) / Accuracy 0.7500 / Loss 0.609274\n",
      "Epoch 69 / Batch (2/17) / Accuracy 0.8231 / Loss 0.467324\n",
      "Epoch 69 / Batch (3/17) / Accuracy 0.7788 / Loss 0.555936\n",
      "Epoch 69 / Batch (4/17) / Accuracy 0.7775 / Loss 0.542196\n",
      "Epoch 69 / Batch (5/17) / Accuracy 0.8037 / Loss 0.508924\n",
      "Epoch 69 / Batch (6/17) / Accuracy 0.7781 / Loss 0.574783\n",
      "Epoch 69 / Batch (7/17) / Accuracy 0.7806 / Loss 0.545461\n",
      "Epoch 69 / Batch (8/17) / Accuracy 0.7819 / Loss 0.520838\n",
      "Epoch 69 / Batch (9/17) / Accuracy 0.7806 / Loss 0.529425\n",
      "Epoch 69 / Batch (10/17) / Accuracy 0.7706 / Loss 0.561421\n",
      "Epoch 69 / Batch (11/17) / Accuracy 0.7887 / Loss 0.523700\n",
      "Epoch 69 / Batch (12/17) / Accuracy 0.7831 / Loss 0.559486\n",
      "Epoch 69 / Batch (13/17) / Accuracy 0.7975 / Loss 0.526888\n",
      "Epoch 69 / Batch (14/17) / Accuracy 0.8094 / Loss 0.502919\n",
      "Epoch 69 / Batch (15/17) / Accuracy 0.8094 / Loss 0.516344\n",
      "Epoch 69 / Batch (16/17) / Accuracy 0.7987 / Loss 0.553111\n",
      "Epoch 69 / Batch (17/17) / Accuracy 0.7750 / Loss 0.575792\n",
      "Epoch 69 complete, 7.1161603927612305 seconds elapsed\n",
      "\n",
      "Epoch 70 starting..\n",
      "Epoch 70 / Batch (1/17) / Accuracy 0.7675 / Loss 0.559144\n",
      "Epoch 70 / Batch (2/17) / Accuracy 0.7800 / Loss 0.534273\n",
      "Epoch 70 / Batch (3/17) / Accuracy 0.7706 / Loss 0.558907\n",
      "Epoch 70 / Batch (4/17) / Accuracy 0.7850 / Loss 0.544982\n",
      "Epoch 70 / Batch (5/17) / Accuracy 0.7725 / Loss 0.567209\n",
      "Epoch 70 / Batch (6/17) / Accuracy 0.8006 / Loss 0.500926\n",
      "Epoch 70 / Batch (7/17) / Accuracy 0.7881 / Loss 0.516630\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 70 / Batch (8/17) / Accuracy 0.7575 / Loss 0.569621\n",
      "Epoch 70 / Batch (9/17) / Accuracy 0.7781 / Loss 0.566251\n",
      "Epoch 70 / Batch (10/17) / Accuracy 0.7994 / Loss 0.493032\n",
      "Epoch 70 / Batch (11/17) / Accuracy 0.8150 / Loss 0.452360\n",
      "Epoch 70 / Batch (12/17) / Accuracy 0.7563 / Loss 0.597790\n",
      "Epoch 70 / Batch (13/17) / Accuracy 0.7962 / Loss 0.510876\n",
      "Epoch 70 / Batch (14/17) / Accuracy 0.7769 / Loss 0.571859\n",
      "Epoch 70 / Batch (15/17) / Accuracy 0.7506 / Loss 0.597261\n",
      "Epoch 70 / Batch (16/17) / Accuracy 0.7812 / Loss 0.552185\n",
      "Epoch 70 / Batch (17/17) / Accuracy 0.7819 / Loss 0.546938\n",
      "Epoch 70 complete, 6.636115312576294 seconds elapsed\n",
      "\n",
      "Epoch 71 starting..\n",
      "Epoch 71 / Batch (1/17) / Accuracy 0.7713 / Loss 0.554797\n",
      "Epoch 71 / Batch (2/17) / Accuracy 0.7656 / Loss 0.576386\n",
      "Epoch 71 / Batch (3/17) / Accuracy 0.8100 / Loss 0.492960\n",
      "Epoch 71 / Batch (4/17) / Accuracy 0.7744 / Loss 0.581403\n",
      "Epoch 71 / Batch (5/17) / Accuracy 0.8112 / Loss 0.497324\n",
      "Epoch 71 / Batch (6/17) / Accuracy 0.7487 / Loss 0.615472\n",
      "Epoch 71 / Batch (7/17) / Accuracy 0.7944 / Loss 0.530287\n",
      "Epoch 71 / Batch (8/17) / Accuracy 0.7638 / Loss 0.595742\n",
      "Epoch 71 / Batch (9/17) / Accuracy 0.7788 / Loss 0.553793\n",
      "Epoch 71 / Batch (10/17) / Accuracy 0.7681 / Loss 0.604822\n",
      "Epoch 71 / Batch (11/17) / Accuracy 0.7156 / Loss 0.691252\n",
      "Epoch 71 / Batch (12/17) / Accuracy 0.7819 / Loss 0.535620\n",
      "Epoch 71 / Batch (13/17) / Accuracy 0.7812 / Loss 0.507395\n",
      "Epoch 71 / Batch (14/17) / Accuracy 0.8037 / Loss 0.497390\n",
      "Epoch 71 / Batch (15/17) / Accuracy 0.7519 / Loss 0.609949\n",
      "Epoch 71 / Batch (16/17) / Accuracy 0.7750 / Loss 0.535908\n",
      "Epoch 71 / Batch (17/17) / Accuracy 0.7962 / Loss 0.496835\n",
      "Epoch 71 complete, 6.885906219482422 seconds elapsed\n",
      "\n",
      "Epoch 72 starting..\n",
      "Epoch 72 / Batch (1/17) / Accuracy 0.7812 / Loss 0.556357\n",
      "Epoch 72 / Batch (2/17) / Accuracy 0.7725 / Loss 0.553029\n",
      "Epoch 72 / Batch (3/17) / Accuracy 0.7656 / Loss 0.580754\n",
      "Epoch 72 / Batch (4/17) / Accuracy 0.7862 / Loss 0.538499\n",
      "Epoch 72 / Batch (5/17) / Accuracy 0.7981 / Loss 0.503403\n",
      "Epoch 72 / Batch (6/17) / Accuracy 0.7906 / Loss 0.521199\n",
      "Epoch 72 / Batch (7/17) / Accuracy 0.7375 / Loss 0.619859\n",
      "Epoch 72 / Batch (8/17) / Accuracy 0.7444 / Loss 0.641425\n",
      "Epoch 72 / Batch (9/17) / Accuracy 0.7962 / Loss 0.529421\n",
      "Epoch 72 / Batch (10/17) / Accuracy 0.7950 / Loss 0.501381\n",
      "Epoch 72 / Batch (11/17) / Accuracy 0.7481 / Loss 0.613825\n",
      "Epoch 72 / Batch (12/17) / Accuracy 0.7731 / Loss 0.550913\n",
      "Epoch 72 / Batch (13/17) / Accuracy 0.7763 / Loss 0.584842\n",
      "Epoch 72 / Batch (14/17) / Accuracy 0.8019 / Loss 0.510995\n",
      "Epoch 72 / Batch (15/17) / Accuracy 0.7663 / Loss 0.585222\n",
      "Epoch 72 / Batch (16/17) / Accuracy 0.8012 / Loss 0.516814\n",
      "Epoch 72 / Batch (17/17) / Accuracy 0.7613 / Loss 0.606926\n",
      "Epoch 72 complete, 6.400544166564941 seconds elapsed\n",
      "\n",
      "Epoch 73 starting..\n",
      "Epoch 73 / Batch (1/17) / Accuracy 0.8019 / Loss 0.506796\n",
      "Epoch 73 / Batch (2/17) / Accuracy 0.7656 / Loss 0.584323\n",
      "Epoch 73 / Batch (3/17) / Accuracy 0.7862 / Loss 0.557035\n",
      "Epoch 73 / Batch (4/17) / Accuracy 0.7875 / Loss 0.536186\n",
      "Epoch 73 / Batch (5/17) / Accuracy 0.8019 / Loss 0.491930\n",
      "Epoch 73 / Batch (6/17) / Accuracy 0.7656 / Loss 0.578890\n",
      "Epoch 73 / Batch (7/17) / Accuracy 0.7563 / Loss 0.624794\n",
      "Epoch 73 / Batch (8/17) / Accuracy 0.7681 / Loss 0.560658\n",
      "Epoch 73 / Batch (9/17) / Accuracy 0.7850 / Loss 0.536890\n",
      "Epoch 73 / Batch (10/17) / Accuracy 0.7456 / Loss 0.591396\n",
      "Epoch 73 / Batch (11/17) / Accuracy 0.8450 / Loss 0.429360\n",
      "Epoch 73 / Batch (12/17) / Accuracy 0.7756 / Loss 0.603959\n",
      "Epoch 73 / Batch (13/17) / Accuracy 0.7725 / Loss 0.553958\n",
      "Epoch 73 / Batch (14/17) / Accuracy 0.8281 / Loss 0.446615\n",
      "Epoch 73 / Batch (15/17) / Accuracy 0.8431 / Loss 0.418965\n",
      "Epoch 73 / Batch (16/17) / Accuracy 0.7731 / Loss 0.571423\n",
      "Epoch 73 / Batch (17/17) / Accuracy 0.7462 / Loss 0.591485\n",
      "Epoch 73 complete, 6.645887136459351 seconds elapsed\n",
      "\n",
      "Epoch 74 starting..\n",
      "Epoch 74 / Batch (1/17) / Accuracy 0.7987 / Loss 0.498263\n",
      "Epoch 74 / Batch (2/17) / Accuracy 0.8037 / Loss 0.487936\n",
      "Epoch 74 / Batch (3/17) / Accuracy 0.7956 / Loss 0.495874\n",
      "Epoch 74 / Batch (4/17) / Accuracy 0.7594 / Loss 0.557869\n",
      "Epoch 74 / Batch (5/17) / Accuracy 0.7663 / Loss 0.566589\n",
      "Epoch 74 / Batch (6/17) / Accuracy 0.7881 / Loss 0.534765\n",
      "Epoch 74 / Batch (7/17) / Accuracy 0.7350 / Loss 0.675157\n",
      "Epoch 74 / Batch (8/17) / Accuracy 0.8025 / Loss 0.534625\n",
      "Epoch 74 / Batch (9/17) / Accuracy 0.7931 / Loss 0.505507\n",
      "Epoch 74 / Batch (10/17) / Accuracy 0.7887 / Loss 0.565731\n",
      "Epoch 74 / Batch (11/17) / Accuracy 0.7681 / Loss 0.564044\n",
      "Epoch 74 / Batch (12/17) / Accuracy 0.7750 / Loss 0.557503\n",
      "Epoch 74 / Batch (13/17) / Accuracy 0.7875 / Loss 0.553221\n",
      "Epoch 74 / Batch (14/17) / Accuracy 0.7625 / Loss 0.570266\n",
      "Epoch 74 / Batch (15/17) / Accuracy 0.7613 / Loss 0.575091\n",
      "Epoch 74 / Batch (16/17) / Accuracy 0.8037 / Loss 0.500122\n",
      "Epoch 74 / Batch (17/17) / Accuracy 0.7862 / Loss 0.548848\n",
      "Epoch 74 complete, 6.1446332931518555 seconds elapsed\n",
      "\n",
      "Epoch 75 starting..\n",
      "Epoch 75 / Batch (1/17) / Accuracy 0.7756 / Loss 0.554023\n",
      "Epoch 75 / Batch (2/17) / Accuracy 0.7644 / Loss 0.560644\n",
      "Epoch 75 / Batch (3/17) / Accuracy 0.8106 / Loss 0.488147\n",
      "Epoch 75 / Batch (4/17) / Accuracy 0.7625 / Loss 0.565724\n",
      "Epoch 75 / Batch (5/17) / Accuracy 0.7406 / Loss 0.612910\n",
      "Epoch 75 / Batch (6/17) / Accuracy 0.7287 / Loss 0.653184\n",
      "Epoch 75 / Batch (7/17) / Accuracy 0.8106 / Loss 0.484573\n",
      "Epoch 75 / Batch (8/17) / Accuracy 0.7688 / Loss 0.571457\n",
      "Epoch 75 / Batch (9/17) / Accuracy 0.7638 / Loss 0.574842\n",
      "Epoch 75 / Batch (10/17) / Accuracy 0.7738 / Loss 0.584344\n",
      "Epoch 75 / Batch (11/17) / Accuracy 0.7706 / Loss 0.569401\n",
      "Epoch 75 / Batch (12/17) / Accuracy 0.7462 / Loss 0.605239\n",
      "Epoch 75 / Batch (13/17) / Accuracy 0.7613 / Loss 0.605647\n",
      "Epoch 75 / Batch (14/17) / Accuracy 0.7525 / Loss 0.607512\n",
      "Epoch 75 / Batch (15/17) / Accuracy 0.8169 / Loss 0.473163\n",
      "Epoch 75 / Batch (16/17) / Accuracy 0.8269 / Loss 0.465542\n",
      "Epoch 75 / Batch (17/17) / Accuracy 0.7788 / Loss 0.529662\n",
      "Epoch 75 complete, 6.499531269073486 seconds elapsed\n",
      "\n",
      "Epoch 76 starting..\n",
      "Epoch 76 / Batch (1/17) / Accuracy 0.7794 / Loss 0.564322\n",
      "Epoch 76 / Batch (2/17) / Accuracy 0.8106 / Loss 0.491915\n",
      "Epoch 76 / Batch (3/17) / Accuracy 0.7513 / Loss 0.577970\n",
      "Epoch 76 / Batch (4/17) / Accuracy 0.7912 / Loss 0.535878\n",
      "Epoch 76 / Batch (5/17) / Accuracy 0.7825 / Loss 0.535991\n",
      "Epoch 76 / Batch (6/17) / Accuracy 0.7894 / Loss 0.544240\n",
      "Epoch 76 / Batch (7/17) / Accuracy 0.7994 / Loss 0.517917\n",
      "Epoch 76 / Batch (8/17) / Accuracy 0.7706 / Loss 0.551894\n",
      "Epoch 76 / Batch (9/17) / Accuracy 0.7575 / Loss 0.588585\n",
      "Epoch 76 / Batch (10/17) / Accuracy 0.7763 / Loss 0.548080\n",
      "Epoch 76 / Batch (11/17) / Accuracy 0.7912 / Loss 0.513326\n",
      "Epoch 76 / Batch (12/17) / Accuracy 0.7650 / Loss 0.574596\n",
      "Epoch 76 / Batch (13/17) / Accuracy 0.8050 / Loss 0.490243\n",
      "Epoch 76 / Batch (14/17) / Accuracy 0.7881 / Loss 0.546759\n",
      "Epoch 76 / Batch (15/17) / Accuracy 0.7706 / Loss 0.543627\n",
      "Epoch 76 / Batch (16/17) / Accuracy 0.7763 / Loss 0.545915\n",
      "Epoch 76 / Batch (17/17) / Accuracy 0.7912 / Loss 0.522808\n",
      "Epoch 76 complete, 6.972301483154297 seconds elapsed\n",
      "\n",
      "Epoch 77 starting..\n",
      "Epoch 77 / Batch (1/17) / Accuracy 0.8056 / Loss 0.497675\n",
      "Epoch 77 / Batch (2/17) / Accuracy 0.7769 / Loss 0.544262\n",
      "Epoch 77 / Batch (3/17) / Accuracy 0.7331 / Loss 0.622642\n",
      "Epoch 77 / Batch (4/17) / Accuracy 0.7750 / Loss 0.569607\n",
      "Epoch 77 / Batch (5/17) / Accuracy 0.7850 / Loss 0.526275\n",
      "Epoch 77 / Batch (6/17) / Accuracy 0.8044 / Loss 0.512764\n",
      "Epoch 77 / Batch (7/17) / Accuracy 0.7875 / Loss 0.548564\n",
      "Epoch 77 / Batch (8/17) / Accuracy 0.8056 / Loss 0.494420\n",
      "Epoch 77 / Batch (9/17) / Accuracy 0.7881 / Loss 0.500596\n",
      "Epoch 77 / Batch (10/17) / Accuracy 0.7875 / Loss 0.540744\n",
      "Epoch 77 / Batch (11/17) / Accuracy 0.7487 / Loss 0.587950\n",
      "Epoch 77 / Batch (12/17) / Accuracy 0.7606 / Loss 0.581067\n",
      "Epoch 77 / Batch (13/17) / Accuracy 0.7600 / Loss 0.587750\n",
      "Epoch 77 / Batch (14/17) / Accuracy 0.8019 / Loss 0.506529\n",
      "Epoch 77 / Batch (15/17) / Accuracy 0.7887 / Loss 0.538109\n",
      "Epoch 77 / Batch (16/17) / Accuracy 0.7775 / Loss 0.582292\n",
      "Epoch 77 / Batch (17/17) / Accuracy 0.7881 / Loss 0.511459\n",
      "Epoch 77 complete, 6.535981893539429 seconds elapsed\n",
      "\n",
      "Epoch 78 starting..\n",
      "Epoch 78 / Batch (1/17) / Accuracy 0.7725 / Loss 0.585577\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 78 / Batch (2/17) / Accuracy 0.7975 / Loss 0.515993\n",
      "Epoch 78 / Batch (3/17) / Accuracy 0.7719 / Loss 0.556626\n",
      "Epoch 78 / Batch (4/17) / Accuracy 0.7925 / Loss 0.543091\n",
      "Epoch 78 / Batch (5/17) / Accuracy 0.7969 / Loss 0.508906\n",
      "Epoch 78 / Batch (6/17) / Accuracy 0.8219 / Loss 0.469983\n",
      "Epoch 78 / Batch (7/17) / Accuracy 0.7706 / Loss 0.567776\n",
      "Epoch 78 / Batch (8/17) / Accuracy 0.7694 / Loss 0.585221\n",
      "Epoch 78 / Batch (9/17) / Accuracy 0.8144 / Loss 0.487135\n",
      "Epoch 78 / Batch (10/17) / Accuracy 0.8025 / Loss 0.508423\n",
      "Epoch 78 / Batch (11/17) / Accuracy 0.7837 / Loss 0.541396\n",
      "Epoch 78 / Batch (12/17) / Accuracy 0.7600 / Loss 0.606124\n",
      "Epoch 78 / Batch (13/17) / Accuracy 0.7631 / Loss 0.575239\n",
      "Epoch 78 / Batch (14/17) / Accuracy 0.7931 / Loss 0.514299\n",
      "Epoch 78 / Batch (15/17) / Accuracy 0.7837 / Loss 0.569305\n",
      "Epoch 78 / Batch (16/17) / Accuracy 0.8256 / Loss 0.447468\n",
      "Epoch 78 / Batch (17/17) / Accuracy 0.7812 / Loss 0.544705\n",
      "Epoch 78 complete, 6.330784559249878 seconds elapsed\n",
      "\n",
      "Epoch 79 starting..\n",
      "Epoch 79 / Batch (1/17) / Accuracy 0.7763 / Loss 0.536603\n",
      "Epoch 79 / Batch (2/17) / Accuracy 0.7450 / Loss 0.646734\n",
      "Epoch 79 / Batch (3/17) / Accuracy 0.7444 / Loss 0.619885\n",
      "Epoch 79 / Batch (4/17) / Accuracy 0.8238 / Loss 0.459914\n",
      "Epoch 79 / Batch (5/17) / Accuracy 0.7825 / Loss 0.540719\n",
      "Epoch 79 / Batch (6/17) / Accuracy 0.7869 / Loss 0.537345\n",
      "Epoch 79 / Batch (7/17) / Accuracy 0.7806 / Loss 0.555340\n",
      "Epoch 79 / Batch (8/17) / Accuracy 0.8081 / Loss 0.500322\n",
      "Epoch 79 / Batch (9/17) / Accuracy 0.7300 / Loss 0.656809\n",
      "Epoch 79 / Batch (10/17) / Accuracy 0.7656 / Loss 0.552869\n",
      "Epoch 79 / Batch (11/17) / Accuracy 0.8188 / Loss 0.464894\n",
      "Epoch 79 / Batch (12/17) / Accuracy 0.7437 / Loss 0.603695\n",
      "Epoch 79 / Batch (13/17) / Accuracy 0.8019 / Loss 0.515118\n",
      "Epoch 79 / Batch (14/17) / Accuracy 0.8006 / Loss 0.540583\n",
      "Epoch 79 / Batch (15/17) / Accuracy 0.7906 / Loss 0.553183\n",
      "Epoch 79 / Batch (16/17) / Accuracy 0.7588 / Loss 0.586259\n",
      "Epoch 79 / Batch (17/17) / Accuracy 0.7513 / Loss 0.606792\n",
      "Epoch 79 complete, 6.379948139190674 seconds elapsed\n",
      "\n",
      "Epoch 80 starting..\n",
      "Epoch 80 / Batch (1/17) / Accuracy 0.7794 / Loss 0.539869\n",
      "Epoch 80 / Batch (2/17) / Accuracy 0.7906 / Loss 0.510269\n",
      "Epoch 80 / Batch (3/17) / Accuracy 0.7531 / Loss 0.583914\n",
      "Epoch 80 / Batch (4/17) / Accuracy 0.7719 / Loss 0.564204\n",
      "Epoch 80 / Batch (5/17) / Accuracy 0.7956 / Loss 0.526361\n",
      "Epoch 80 / Batch (6/17) / Accuracy 0.7956 / Loss 0.513747\n",
      "Epoch 80 / Batch (7/17) / Accuracy 0.8000 / Loss 0.497633\n",
      "Epoch 80 / Batch (8/17) / Accuracy 0.8106 / Loss 0.516372\n",
      "Epoch 80 / Batch (9/17) / Accuracy 0.8100 / Loss 0.484731\n",
      "Epoch 80 / Batch (10/17) / Accuracy 0.7825 / Loss 0.542116\n",
      "Epoch 80 / Batch (11/17) / Accuracy 0.7925 / Loss 0.534383\n",
      "Epoch 80 / Batch (12/17) / Accuracy 0.8069 / Loss 0.491757\n",
      "Epoch 80 / Batch (13/17) / Accuracy 0.7731 / Loss 0.573533\n",
      "Epoch 80 / Batch (14/17) / Accuracy 0.7831 / Loss 0.539567\n",
      "Epoch 80 / Batch (15/17) / Accuracy 0.7681 / Loss 0.569877\n",
      "Epoch 80 / Batch (16/17) / Accuracy 0.8131 / Loss 0.480662\n",
      "Epoch 80 / Batch (17/17) / Accuracy 0.8019 / Loss 0.515755\n",
      "Epoch 80 complete, 6.254787445068359 seconds elapsed\n",
      "\n",
      "Epoch 81 starting..\n",
      "Epoch 81 / Batch (1/17) / Accuracy 0.7837 / Loss 0.524767\n",
      "Epoch 81 / Batch (2/17) / Accuracy 0.7800 / Loss 0.541707\n",
      "Epoch 81 / Batch (3/17) / Accuracy 0.7775 / Loss 0.545759\n",
      "Epoch 81 / Batch (4/17) / Accuracy 0.7862 / Loss 0.525644\n",
      "Epoch 81 / Batch (5/17) / Accuracy 0.8056 / Loss 0.478168\n",
      "Epoch 81 / Batch (6/17) / Accuracy 0.8106 / Loss 0.484538\n",
      "Epoch 81 / Batch (7/17) / Accuracy 0.7956 / Loss 0.505867\n",
      "Epoch 81 / Batch (8/17) / Accuracy 0.7769 / Loss 0.558209\n",
      "Epoch 81 / Batch (9/17) / Accuracy 0.7875 / Loss 0.527687\n",
      "Epoch 81 / Batch (10/17) / Accuracy 0.7819 / Loss 0.525511\n",
      "Epoch 81 / Batch (11/17) / Accuracy 0.8406 / Loss 0.448387\n",
      "Epoch 81 / Batch (12/17) / Accuracy 0.7681 / Loss 0.579632\n",
      "Epoch 81 / Batch (13/17) / Accuracy 0.7619 / Loss 0.574246\n",
      "Epoch 81 / Batch (14/17) / Accuracy 0.7769 / Loss 0.561920\n",
      "Epoch 81 / Batch (15/17) / Accuracy 0.7275 / Loss 0.692677\n",
      "Epoch 81 / Batch (16/17) / Accuracy 0.7644 / Loss 0.587641\n",
      "Epoch 81 / Batch (17/17) / Accuracy 0.7594 / Loss 0.582075\n",
      "Epoch 81 complete, 6.716978549957275 seconds elapsed\n",
      "\n",
      "Epoch 82 starting..\n",
      "Epoch 82 / Batch (1/17) / Accuracy 0.7688 / Loss 0.561724\n",
      "Epoch 82 / Batch (2/17) / Accuracy 0.7644 / Loss 0.566492\n",
      "Epoch 82 / Batch (3/17) / Accuracy 0.7650 / Loss 0.570518\n",
      "Epoch 82 / Batch (4/17) / Accuracy 0.7825 / Loss 0.555639\n",
      "Epoch 82 / Batch (5/17) / Accuracy 0.8100 / Loss 0.473223\n",
      "Epoch 82 / Batch (6/17) / Accuracy 0.8131 / Loss 0.465663\n",
      "Epoch 82 / Batch (7/17) / Accuracy 0.7744 / Loss 0.562228\n",
      "Epoch 82 / Batch (8/17) / Accuracy 0.8200 / Loss 0.516276\n",
      "Epoch 82 / Batch (9/17) / Accuracy 0.7887 / Loss 0.522470\n",
      "Epoch 82 / Batch (10/17) / Accuracy 0.7763 / Loss 0.551795\n",
      "Epoch 82 / Batch (11/17) / Accuracy 0.7969 / Loss 0.504636\n",
      "Epoch 82 / Batch (12/17) / Accuracy 0.8031 / Loss 0.472588\n",
      "Epoch 82 / Batch (13/17) / Accuracy 0.8031 / Loss 0.511997\n",
      "Epoch 82 / Batch (14/17) / Accuracy 0.7869 / Loss 0.531180\n",
      "Epoch 82 / Batch (15/17) / Accuracy 0.7969 / Loss 0.534430\n",
      "Epoch 82 / Batch (16/17) / Accuracy 0.8006 / Loss 0.514454\n",
      "Epoch 82 / Batch (17/17) / Accuracy 0.8031 / Loss 0.493500\n",
      "Epoch 82 complete, 6.344147205352783 seconds elapsed\n",
      "\n",
      "Epoch 83 starting..\n",
      "Epoch 83 / Batch (1/17) / Accuracy 0.8000 / Loss 0.517792\n",
      "Epoch 83 / Batch (2/17) / Accuracy 0.7775 / Loss 0.541263\n",
      "Epoch 83 / Batch (3/17) / Accuracy 0.7669 / Loss 0.564276\n",
      "Epoch 83 / Batch (4/17) / Accuracy 0.7894 / Loss 0.525069\n",
      "Epoch 83 / Batch (5/17) / Accuracy 0.8138 / Loss 0.506209\n",
      "Epoch 83 / Batch (6/17) / Accuracy 0.7950 / Loss 0.532906\n",
      "Epoch 83 / Batch (7/17) / Accuracy 0.7962 / Loss 0.500735\n",
      "Epoch 83 / Batch (8/17) / Accuracy 0.7994 / Loss 0.513559\n",
      "Epoch 83 / Batch (9/17) / Accuracy 0.8006 / Loss 0.515096\n",
      "Epoch 83 / Batch (10/17) / Accuracy 0.7544 / Loss 0.561095\n",
      "Epoch 83 / Batch (11/17) / Accuracy 0.7944 / Loss 0.552840\n",
      "Epoch 83 / Batch (12/17) / Accuracy 0.7763 / Loss 0.553874\n",
      "Epoch 83 / Batch (13/17) / Accuracy 0.7987 / Loss 0.512374\n",
      "Epoch 83 / Batch (14/17) / Accuracy 0.8144 / Loss 0.480905\n",
      "Epoch 83 / Batch (15/17) / Accuracy 0.8200 / Loss 0.473657\n",
      "Epoch 83 / Batch (16/17) / Accuracy 0.7462 / Loss 0.622777\n",
      "Epoch 83 / Batch (17/17) / Accuracy 0.8175 / Loss 0.460310\n",
      "Epoch 83 complete, 6.668657541275024 seconds elapsed\n",
      "\n",
      "Epoch 84 starting..\n",
      "Epoch 84 / Batch (1/17) / Accuracy 0.7738 / Loss 0.549005\n",
      "Epoch 84 / Batch (2/17) / Accuracy 0.7594 / Loss 0.603343\n",
      "Epoch 84 / Batch (3/17) / Accuracy 0.7613 / Loss 0.594494\n",
      "Epoch 84 / Batch (4/17) / Accuracy 0.8169 / Loss 0.474829\n",
      "Epoch 84 / Batch (5/17) / Accuracy 0.7975 / Loss 0.515335\n",
      "Epoch 84 / Batch (6/17) / Accuracy 0.7719 / Loss 0.541789\n",
      "Epoch 84 / Batch (7/17) / Accuracy 0.7925 / Loss 0.511559\n",
      "Epoch 84 / Batch (8/17) / Accuracy 0.8012 / Loss 0.522864\n",
      "Epoch 84 / Batch (9/17) / Accuracy 0.7462 / Loss 0.640716\n",
      "Epoch 84 / Batch (10/17) / Accuracy 0.7975 / Loss 0.507877\n",
      "Epoch 84 / Batch (11/17) / Accuracy 0.7794 / Loss 0.524222\n",
      "Epoch 84 / Batch (12/17) / Accuracy 0.7681 / Loss 0.549965\n",
      "Epoch 84 / Batch (13/17) / Accuracy 0.7638 / Loss 0.610483\n",
      "Epoch 84 / Batch (14/17) / Accuracy 0.7763 / Loss 0.567412\n",
      "Epoch 84 / Batch (15/17) / Accuracy 0.7925 / Loss 0.498340\n",
      "Epoch 84 / Batch (16/17) / Accuracy 0.7563 / Loss 0.584917\n",
      "Epoch 84 / Batch (17/17) / Accuracy 0.7794 / Loss 0.574204\n",
      "Epoch 84 complete, 6.6229822635650635 seconds elapsed\n",
      "\n",
      "Epoch 85 starting..\n",
      "Epoch 85 / Batch (1/17) / Accuracy 0.8119 / Loss 0.499941\n",
      "Epoch 85 / Batch (2/17) / Accuracy 0.7731 / Loss 0.599393\n",
      "Epoch 85 / Batch (3/17) / Accuracy 0.7975 / Loss 0.497107\n",
      "Epoch 85 / Batch (4/17) / Accuracy 0.7906 / Loss 0.540806\n",
      "Epoch 85 / Batch (5/17) / Accuracy 0.7750 / Loss 0.554894\n",
      "Epoch 85 / Batch (6/17) / Accuracy 0.8037 / Loss 0.492312\n",
      "Epoch 85 / Batch (7/17) / Accuracy 0.7469 / Loss 0.580141\n",
      "Epoch 85 / Batch (8/17) / Accuracy 0.7800 / Loss 0.563496\n",
      "Epoch 85 / Batch (9/17) / Accuracy 0.7681 / Loss 0.554725\n",
      "Epoch 85 / Batch (10/17) / Accuracy 0.7638 / Loss 0.586589\n",
      "Epoch 85 / Batch (11/17) / Accuracy 0.7881 / Loss 0.549348\n",
      "Epoch 85 / Batch (12/17) / Accuracy 0.7756 / Loss 0.557648\n",
      "Epoch 85 / Batch (13/17) / Accuracy 0.7819 / Loss 0.570132\n",
      "Epoch 85 / Batch (14/17) / Accuracy 0.7713 / Loss 0.555560\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 85 / Batch (15/17) / Accuracy 0.7931 / Loss 0.529290\n",
      "Epoch 85 / Batch (16/17) / Accuracy 0.7431 / Loss 0.585664\n",
      "Epoch 85 / Batch (17/17) / Accuracy 0.7681 / Loss 0.549909\n",
      "Epoch 85 complete, 6.319923162460327 seconds elapsed\n",
      "\n",
      "Epoch 86 starting..\n",
      "Epoch 86 / Batch (1/17) / Accuracy 0.7862 / Loss 0.569600\n",
      "Epoch 86 / Batch (2/17) / Accuracy 0.7756 / Loss 0.554769\n",
      "Epoch 86 / Batch (3/17) / Accuracy 0.7706 / Loss 0.570681\n",
      "Epoch 86 / Batch (4/17) / Accuracy 0.8087 / Loss 0.495859\n",
      "Epoch 86 / Batch (5/17) / Accuracy 0.7719 / Loss 0.558798\n",
      "Epoch 86 / Batch (6/17) / Accuracy 0.7619 / Loss 0.600536\n",
      "Epoch 86 / Batch (7/17) / Accuracy 0.7744 / Loss 0.521180\n",
      "Epoch 86 / Batch (8/17) / Accuracy 0.7281 / Loss 0.633537\n",
      "Epoch 86 / Batch (9/17) / Accuracy 0.8069 / Loss 0.484119\n",
      "Epoch 86 / Batch (10/17) / Accuracy 0.8025 / Loss 0.502407\n",
      "Epoch 86 / Batch (11/17) / Accuracy 0.7525 / Loss 0.598781\n",
      "Epoch 86 / Batch (12/17) / Accuracy 0.7625 / Loss 0.583162\n",
      "Epoch 86 / Batch (13/17) / Accuracy 0.7912 / Loss 0.541676\n",
      "Epoch 86 / Batch (14/17) / Accuracy 0.7944 / Loss 0.542109\n",
      "Epoch 86 / Batch (15/17) / Accuracy 0.7775 / Loss 0.584450\n",
      "Epoch 86 / Batch (16/17) / Accuracy 0.8056 / Loss 0.515395\n",
      "Epoch 86 / Batch (17/17) / Accuracy 0.7956 / Loss 0.519310\n",
      "Epoch 86 complete, 6.32136869430542 seconds elapsed\n",
      "\n",
      "Epoch 87 starting..\n",
      "Epoch 87 / Batch (1/17) / Accuracy 0.7950 / Loss 0.523620\n",
      "Epoch 87 / Batch (2/17) / Accuracy 0.8169 / Loss 0.483503\n",
      "Epoch 87 / Batch (3/17) / Accuracy 0.7794 / Loss 0.555662\n",
      "Epoch 87 / Batch (4/17) / Accuracy 0.7962 / Loss 0.533533\n",
      "Epoch 87 / Batch (5/17) / Accuracy 0.7862 / Loss 0.524777\n",
      "Epoch 87 / Batch (6/17) / Accuracy 0.7369 / Loss 0.619977\n",
      "Epoch 87 / Batch (7/17) / Accuracy 0.7650 / Loss 0.578949\n",
      "Epoch 87 / Batch (8/17) / Accuracy 0.7844 / Loss 0.553811\n",
      "Epoch 87 / Batch (9/17) / Accuracy 0.7956 / Loss 0.501065\n",
      "Epoch 87 / Batch (10/17) / Accuracy 0.8119 / Loss 0.480739\n",
      "Epoch 87 / Batch (11/17) / Accuracy 0.7925 / Loss 0.508275\n",
      "Epoch 87 / Batch (12/17) / Accuracy 0.7869 / Loss 0.540269\n",
      "Epoch 87 / Batch (13/17) / Accuracy 0.7906 / Loss 0.538298\n",
      "Epoch 87 / Batch (14/17) / Accuracy 0.8163 / Loss 0.494130\n",
      "Epoch 87 / Batch (15/17) / Accuracy 0.7912 / Loss 0.511596\n",
      "Epoch 87 / Batch (16/17) / Accuracy 0.7856 / Loss 0.500725\n",
      "Epoch 87 / Batch (17/17) / Accuracy 0.7731 / Loss 0.590591\n",
      "Epoch 87 complete, 6.615971326828003 seconds elapsed\n",
      "\n",
      "Epoch 88 starting..\n",
      "Epoch 88 / Batch (1/17) / Accuracy 0.7856 / Loss 0.511936\n",
      "Epoch 88 / Batch (2/17) / Accuracy 0.7819 / Loss 0.536803\n",
      "Epoch 88 / Batch (3/17) / Accuracy 0.7944 / Loss 0.540036\n",
      "Epoch 88 / Batch (4/17) / Accuracy 0.7856 / Loss 0.537095\n",
      "Epoch 88 / Batch (5/17) / Accuracy 0.7506 / Loss 0.650930\n",
      "Epoch 88 / Batch (6/17) / Accuracy 0.8200 / Loss 0.500006\n",
      "Epoch 88 / Batch (7/17) / Accuracy 0.7663 / Loss 0.541827\n",
      "Epoch 88 / Batch (8/17) / Accuracy 0.7906 / Loss 0.523783\n",
      "Epoch 88 / Batch (9/17) / Accuracy 0.7563 / Loss 0.566483\n",
      "Epoch 88 / Batch (10/17) / Accuracy 0.7906 / Loss 0.528709\n",
      "Epoch 88 / Batch (11/17) / Accuracy 0.7750 / Loss 0.589926\n",
      "Epoch 88 / Batch (12/17) / Accuracy 0.7744 / Loss 0.544492\n",
      "Epoch 88 / Batch (13/17) / Accuracy 0.7850 / Loss 0.533861\n",
      "Epoch 88 / Batch (14/17) / Accuracy 0.7819 / Loss 0.569539\n",
      "Epoch 88 / Batch (15/17) / Accuracy 0.7844 / Loss 0.561312\n",
      "Epoch 88 / Batch (16/17) / Accuracy 0.8150 / Loss 0.481868\n",
      "Epoch 88 / Batch (17/17) / Accuracy 0.7788 / Loss 0.534875\n",
      "Epoch 88 complete, 6.892352104187012 seconds elapsed\n",
      "\n",
      "Epoch 89 starting..\n",
      "Epoch 89 / Batch (1/17) / Accuracy 0.7819 / Loss 0.539169\n",
      "Epoch 89 / Batch (2/17) / Accuracy 0.8138 / Loss 0.515127\n",
      "Epoch 89 / Batch (3/17) / Accuracy 0.8006 / Loss 0.510850\n",
      "Epoch 89 / Batch (4/17) / Accuracy 0.8100 / Loss 0.476036\n",
      "Epoch 89 / Batch (5/17) / Accuracy 0.8138 / Loss 0.470030\n",
      "Epoch 89 / Batch (6/17) / Accuracy 0.7625 / Loss 0.562598\n",
      "Epoch 89 / Batch (7/17) / Accuracy 0.8081 / Loss 0.494406\n",
      "Epoch 89 / Batch (8/17) / Accuracy 0.7681 / Loss 0.592066\n",
      "Epoch 89 / Batch (9/17) / Accuracy 0.8150 / Loss 0.490470\n",
      "Epoch 89 / Batch (10/17) / Accuracy 0.7788 / Loss 0.526608\n",
      "Epoch 89 / Batch (11/17) / Accuracy 0.7738 / Loss 0.543291\n",
      "Epoch 89 / Batch (12/17) / Accuracy 0.7556 / Loss 0.590591\n",
      "Epoch 89 / Batch (13/17) / Accuracy 0.8050 / Loss 0.527235\n",
      "Epoch 89 / Batch (14/17) / Accuracy 0.7669 / Loss 0.558753\n",
      "Epoch 89 / Batch (15/17) / Accuracy 0.8050 / Loss 0.516698\n",
      "Epoch 89 / Batch (16/17) / Accuracy 0.7600 / Loss 0.564347\n",
      "Epoch 89 / Batch (17/17) / Accuracy 0.7675 / Loss 0.559284\n",
      "Epoch 89 complete, 6.363542556762695 seconds elapsed\n",
      "\n",
      "Epoch 90 starting..\n",
      "Epoch 90 / Batch (1/17) / Accuracy 0.7881 / Loss 0.524083\n",
      "Epoch 90 / Batch (2/17) / Accuracy 0.7962 / Loss 0.517008\n",
      "Epoch 90 / Batch (3/17) / Accuracy 0.7794 / Loss 0.514919\n",
      "Epoch 90 / Batch (4/17) / Accuracy 0.7625 / Loss 0.579784\n",
      "Epoch 90 / Batch (5/17) / Accuracy 0.7731 / Loss 0.567816\n",
      "Epoch 90 / Batch (6/17) / Accuracy 0.7844 / Loss 0.543525\n",
      "Epoch 90 / Batch (7/17) / Accuracy 0.7619 / Loss 0.566376\n",
      "Epoch 90 / Batch (8/17) / Accuracy 0.7500 / Loss 0.589350\n",
      "Epoch 90 / Batch (9/17) / Accuracy 0.7750 / Loss 0.560275\n",
      "Epoch 90 / Batch (10/17) / Accuracy 0.7287 / Loss 0.648233\n",
      "Epoch 90 / Batch (11/17) / Accuracy 0.7894 / Loss 0.494555\n",
      "Epoch 90 / Batch (12/17) / Accuracy 0.7688 / Loss 0.586896\n",
      "Epoch 90 / Batch (13/17) / Accuracy 0.7781 / Loss 0.529292\n",
      "Epoch 90 / Batch (14/17) / Accuracy 0.7769 / Loss 0.531294\n",
      "Epoch 90 / Batch (15/17) / Accuracy 0.7719 / Loss 0.574484\n",
      "Epoch 90 / Batch (16/17) / Accuracy 0.8050 / Loss 0.489686\n",
      "Epoch 90 / Batch (17/17) / Accuracy 0.7994 / Loss 0.503398\n",
      "Epoch 90 complete, 6.682783603668213 seconds elapsed\n",
      "\n",
      "Epoch 91 starting..\n",
      "Epoch 91 / Batch (1/17) / Accuracy 0.7675 / Loss 0.572673\n",
      "Epoch 91 / Batch (2/17) / Accuracy 0.7794 / Loss 0.565862\n",
      "Epoch 91 / Batch (3/17) / Accuracy 0.7600 / Loss 0.592188\n",
      "Epoch 91 / Batch (4/17) / Accuracy 0.7744 / Loss 0.566554\n",
      "Epoch 91 / Batch (5/17) / Accuracy 0.7887 / Loss 0.550490\n",
      "Epoch 91 / Batch (6/17) / Accuracy 0.7794 / Loss 0.528939\n",
      "Epoch 91 / Batch (7/17) / Accuracy 0.7900 / Loss 0.510132\n",
      "Epoch 91 / Batch (8/17) / Accuracy 0.7700 / Loss 0.564849\n",
      "Epoch 91 / Batch (9/17) / Accuracy 0.7850 / Loss 0.539975\n",
      "Epoch 91 / Batch (10/17) / Accuracy 0.7950 / Loss 0.508319\n",
      "Epoch 91 / Batch (11/17) / Accuracy 0.7519 / Loss 0.619608\n",
      "Epoch 91 / Batch (12/17) / Accuracy 0.8156 / Loss 0.463469\n",
      "Epoch 91 / Batch (13/17) / Accuracy 0.7862 / Loss 0.570563\n",
      "Epoch 91 / Batch (14/17) / Accuracy 0.7837 / Loss 0.535713\n",
      "Epoch 91 / Batch (15/17) / Accuracy 0.8356 / Loss 0.425592\n",
      "Epoch 91 / Batch (16/17) / Accuracy 0.8281 / Loss 0.466227\n",
      "Epoch 91 / Batch (17/17) / Accuracy 0.7594 / Loss 0.593529\n",
      "Epoch 91 complete, 6.33403468132019 seconds elapsed\n",
      "\n",
      "Epoch 92 starting..\n",
      "Epoch 92 / Batch (1/17) / Accuracy 0.8475 / Loss 0.419521\n",
      "Epoch 92 / Batch (2/17) / Accuracy 0.7494 / Loss 0.610995\n",
      "Epoch 92 / Batch (3/17) / Accuracy 0.7831 / Loss 0.514984\n",
      "Epoch 92 / Batch (4/17) / Accuracy 0.7887 / Loss 0.528890\n",
      "Epoch 92 / Batch (5/17) / Accuracy 0.7812 / Loss 0.552313\n",
      "Epoch 92 / Batch (6/17) / Accuracy 0.7994 / Loss 0.493097\n",
      "Epoch 92 / Batch (7/17) / Accuracy 0.8100 / Loss 0.479185\n",
      "Epoch 92 / Batch (8/17) / Accuracy 0.7912 / Loss 0.536257\n",
      "Epoch 92 / Batch (9/17) / Accuracy 0.7837 / Loss 0.552373\n",
      "Epoch 92 / Batch (10/17) / Accuracy 0.8000 / Loss 0.488303\n",
      "Epoch 92 / Batch (11/17) / Accuracy 0.8281 / Loss 0.460485\n",
      "Epoch 92 / Batch (12/17) / Accuracy 0.8037 / Loss 0.509109\n",
      "Epoch 92 / Batch (13/17) / Accuracy 0.7975 / Loss 0.517626\n",
      "Epoch 92 / Batch (14/17) / Accuracy 0.8188 / Loss 0.464325\n",
      "Epoch 92 / Batch (15/17) / Accuracy 0.8094 / Loss 0.481056\n",
      "Epoch 92 / Batch (16/17) / Accuracy 0.7806 / Loss 0.587326\n",
      "Epoch 92 / Batch (17/17) / Accuracy 0.8019 / Loss 0.475981\n",
      "Epoch 92 complete, 6.928232669830322 seconds elapsed\n",
      "\n",
      "Epoch 93 starting..\n",
      "Epoch 93 / Batch (1/17) / Accuracy 0.7600 / Loss 0.587919\n",
      "Epoch 93 / Batch (2/17) / Accuracy 0.7738 / Loss 0.547694\n",
      "Epoch 93 / Batch (3/17) / Accuracy 0.7275 / Loss 0.614734\n",
      "Epoch 93 / Batch (4/17) / Accuracy 0.7606 / Loss 0.590391\n",
      "Epoch 93 / Batch (5/17) / Accuracy 0.7831 / Loss 0.532483\n",
      "Epoch 93 / Batch (6/17) / Accuracy 0.7806 / Loss 0.537997\n",
      "Epoch 93 / Batch (7/17) / Accuracy 0.8119 / Loss 0.464447\n",
      "Epoch 93 / Batch (8/17) / Accuracy 0.7487 / Loss 0.613715\n",
      "Epoch 93 / Batch (9/17) / Accuracy 0.7569 / Loss 0.593876\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 93 / Batch (10/17) / Accuracy 0.7825 / Loss 0.534268\n",
      "Epoch 93 / Batch (11/17) / Accuracy 0.7806 / Loss 0.559355\n",
      "Epoch 93 / Batch (12/17) / Accuracy 0.7669 / Loss 0.574533\n",
      "Epoch 93 / Batch (13/17) / Accuracy 0.7950 / Loss 0.517408\n",
      "Epoch 93 / Batch (14/17) / Accuracy 0.8006 / Loss 0.472039\n",
      "Epoch 93 / Batch (15/17) / Accuracy 0.7531 / Loss 0.597423\n",
      "Epoch 93 / Batch (16/17) / Accuracy 0.8069 / Loss 0.489957\n",
      "Epoch 93 / Batch (17/17) / Accuracy 0.7862 / Loss 0.544314\n",
      "Epoch 93 complete, 6.04791784286499 seconds elapsed\n",
      "\n",
      "Epoch 94 starting..\n",
      "Epoch 94 / Batch (1/17) / Accuracy 0.7669 / Loss 0.541298\n",
      "Epoch 94 / Batch (2/17) / Accuracy 0.7850 / Loss 0.550450\n",
      "Epoch 94 / Batch (3/17) / Accuracy 0.7975 / Loss 0.504369\n",
      "Epoch 94 / Batch (4/17) / Accuracy 0.8081 / Loss 0.488525\n",
      "Epoch 94 / Batch (5/17) / Accuracy 0.8131 / Loss 0.490535\n",
      "Epoch 94 / Batch (6/17) / Accuracy 0.8288 / Loss 0.437897\n",
      "Epoch 94 / Batch (7/17) / Accuracy 0.8037 / Loss 0.495576\n",
      "Epoch 94 / Batch (8/17) / Accuracy 0.7881 / Loss 0.552979\n",
      "Epoch 94 / Batch (9/17) / Accuracy 0.7987 / Loss 0.478527\n",
      "Epoch 94 / Batch (10/17) / Accuracy 0.7694 / Loss 0.590848\n",
      "Epoch 94 / Batch (11/17) / Accuracy 0.7713 / Loss 0.547596\n",
      "Epoch 94 / Batch (12/17) / Accuracy 0.8050 / Loss 0.485333\n",
      "Epoch 94 / Batch (13/17) / Accuracy 0.8381 / Loss 0.445209\n",
      "Epoch 94 / Batch (14/17) / Accuracy 0.7631 / Loss 0.565689\n",
      "Epoch 94 / Batch (15/17) / Accuracy 0.7881 / Loss 0.530841\n",
      "Epoch 94 / Batch (16/17) / Accuracy 0.8081 / Loss 0.511027\n",
      "Epoch 94 / Batch (17/17) / Accuracy 0.7831 / Loss 0.542917\n",
      "Epoch 94 complete, 5.7893407344818115 seconds elapsed\n",
      "\n",
      "Epoch 95 starting..\n",
      "Epoch 95 / Batch (1/17) / Accuracy 0.7800 / Loss 0.557193\n",
      "Epoch 95 / Batch (2/17) / Accuracy 0.7919 / Loss 0.530804\n",
      "Epoch 95 / Batch (3/17) / Accuracy 0.7969 / Loss 0.504054\n",
      "Epoch 95 / Batch (4/17) / Accuracy 0.8125 / Loss 0.467378\n",
      "Epoch 95 / Batch (5/17) / Accuracy 0.7675 / Loss 0.551457\n",
      "Epoch 95 / Batch (6/17) / Accuracy 0.7775 / Loss 0.554593\n",
      "Epoch 95 / Batch (7/17) / Accuracy 0.7831 / Loss 0.525845\n",
      "Epoch 95 / Batch (8/17) / Accuracy 0.8087 / Loss 0.486102\n",
      "Epoch 95 / Batch (9/17) / Accuracy 0.7563 / Loss 0.588105\n",
      "Epoch 95 / Batch (10/17) / Accuracy 0.7856 / Loss 0.547788\n",
      "Epoch 95 / Batch (11/17) / Accuracy 0.8231 / Loss 0.440125\n",
      "Epoch 95 / Batch (12/17) / Accuracy 0.7800 / Loss 0.517479\n",
      "Epoch 95 / Batch (13/17) / Accuracy 0.7700 / Loss 0.551483\n",
      "Epoch 95 / Batch (14/17) / Accuracy 0.7887 / Loss 0.539176\n",
      "Epoch 95 / Batch (15/17) / Accuracy 0.7694 / Loss 0.583654\n",
      "Epoch 95 / Batch (16/17) / Accuracy 0.8056 / Loss 0.503789\n",
      "Epoch 95 / Batch (17/17) / Accuracy 0.7837 / Loss 0.528702\n",
      "Epoch 95 complete, 6.402680397033691 seconds elapsed\n",
      "\n",
      "Epoch 96 starting..\n",
      "Epoch 96 / Batch (1/17) / Accuracy 0.7525 / Loss 0.586313\n",
      "Epoch 96 / Batch (2/17) / Accuracy 0.7669 / Loss 0.503863\n",
      "Epoch 96 / Batch (3/17) / Accuracy 0.7669 / Loss 0.548974\n",
      "Epoch 96 / Batch (4/17) / Accuracy 0.7500 / Loss 0.612417\n",
      "Epoch 96 / Batch (5/17) / Accuracy 0.7837 / Loss 0.592794\n",
      "Epoch 96 / Batch (6/17) / Accuracy 0.7862 / Loss 0.538502\n",
      "Epoch 96 / Batch (7/17) / Accuracy 0.7919 / Loss 0.522351\n",
      "Epoch 96 / Batch (8/17) / Accuracy 0.7781 / Loss 0.595997\n",
      "Epoch 96 / Batch (9/17) / Accuracy 0.7969 / Loss 0.513450\n",
      "Epoch 96 / Batch (10/17) / Accuracy 0.7925 / Loss 0.511273\n",
      "Epoch 96 / Batch (11/17) / Accuracy 0.7625 / Loss 0.587642\n",
      "Epoch 96 / Batch (12/17) / Accuracy 0.7862 / Loss 0.545838\n",
      "Epoch 96 / Batch (13/17) / Accuracy 0.8075 / Loss 0.514066\n",
      "Epoch 96 / Batch (14/17) / Accuracy 0.7906 / Loss 0.575648\n",
      "Epoch 96 / Batch (15/17) / Accuracy 0.7387 / Loss 0.632755\n",
      "Epoch 96 / Batch (16/17) / Accuracy 0.7837 / Loss 0.527269\n",
      "Epoch 96 / Batch (17/17) / Accuracy 0.7738 / Loss 0.559984\n",
      "Epoch 96 complete, 6.461624622344971 seconds elapsed\n",
      "\n",
      "Epoch 97 starting..\n",
      "Epoch 97 / Batch (1/17) / Accuracy 0.7788 / Loss 0.531282\n",
      "Epoch 97 / Batch (2/17) / Accuracy 0.7738 / Loss 0.542514\n",
      "Epoch 97 / Batch (3/17) / Accuracy 0.7769 / Loss 0.530351\n",
      "Epoch 97 / Batch (4/17) / Accuracy 0.7375 / Loss 0.614288\n",
      "Epoch 97 / Batch (5/17) / Accuracy 0.7475 / Loss 0.622515\n",
      "Epoch 97 / Batch (6/17) / Accuracy 0.7887 / Loss 0.540325\n",
      "Epoch 97 / Batch (7/17) / Accuracy 0.7806 / Loss 0.552009\n",
      "Epoch 97 / Batch (8/17) / Accuracy 0.7725 / Loss 0.562582\n",
      "Epoch 97 / Batch (9/17) / Accuracy 0.7763 / Loss 0.563019\n",
      "Epoch 97 / Batch (10/17) / Accuracy 0.8075 / Loss 0.499915\n",
      "Epoch 97 / Batch (11/17) / Accuracy 0.7644 / Loss 0.591847\n",
      "Epoch 97 / Batch (12/17) / Accuracy 0.8244 / Loss 0.471702\n",
      "Epoch 97 / Batch (13/17) / Accuracy 0.7806 / Loss 0.550833\n",
      "Epoch 97 / Batch (14/17) / Accuracy 0.7588 / Loss 0.631419\n",
      "Epoch 97 / Batch (15/17) / Accuracy 0.7806 / Loss 0.536610\n",
      "Epoch 97 / Batch (16/17) / Accuracy 0.8081 / Loss 0.482404\n",
      "Epoch 97 / Batch (17/17) / Accuracy 0.7781 / Loss 0.538963\n",
      "Epoch 97 complete, 6.669391870498657 seconds elapsed\n",
      "\n",
      "Epoch 98 starting..\n",
      "Epoch 98 / Batch (1/17) / Accuracy 0.7981 / Loss 0.525933\n",
      "Epoch 98 / Batch (2/17) / Accuracy 0.7987 / Loss 0.505190\n",
      "Epoch 98 / Batch (3/17) / Accuracy 0.7237 / Loss 0.645992\n",
      "Epoch 98 / Batch (4/17) / Accuracy 0.7850 / Loss 0.518680\n",
      "Epoch 98 / Batch (5/17) / Accuracy 0.7900 / Loss 0.527270\n",
      "Epoch 98 / Batch (6/17) / Accuracy 0.7894 / Loss 0.525959\n",
      "Epoch 98 / Batch (7/17) / Accuracy 0.7575 / Loss 0.611696\n",
      "Epoch 98 / Batch (8/17) / Accuracy 0.7550 / Loss 0.584997\n",
      "Epoch 98 / Batch (9/17) / Accuracy 0.7956 / Loss 0.511589\n",
      "Epoch 98 / Batch (10/17) / Accuracy 0.8106 / Loss 0.486147\n",
      "Epoch 98 / Batch (11/17) / Accuracy 0.7788 / Loss 0.530277\n",
      "Epoch 98 / Batch (12/17) / Accuracy 0.7981 / Loss 0.482454\n",
      "Epoch 98 / Batch (13/17) / Accuracy 0.7500 / Loss 0.598983\n",
      "Epoch 98 / Batch (14/17) / Accuracy 0.8069 / Loss 0.497126\n",
      "Epoch 98 / Batch (15/17) / Accuracy 0.7906 / Loss 0.517718\n",
      "Epoch 98 / Batch (16/17) / Accuracy 0.7969 / Loss 0.519909\n",
      "Epoch 98 / Batch (17/17) / Accuracy 0.7594 / Loss 0.601511\n",
      "Epoch 98 complete, 4.966417074203491 seconds elapsed\n",
      "\n",
      "Epoch 99 starting..\n",
      "Epoch 99 / Batch (1/17) / Accuracy 0.8281 / Loss 0.471622\n",
      "Epoch 99 / Batch (2/17) / Accuracy 0.7894 / Loss 0.551136\n",
      "Epoch 99 / Batch (3/17) / Accuracy 0.7956 / Loss 0.517622\n",
      "Epoch 99 / Batch (4/17) / Accuracy 0.7937 / Loss 0.498095\n",
      "Epoch 99 / Batch (5/17) / Accuracy 0.7937 / Loss 0.521818\n",
      "Epoch 99 / Batch (6/17) / Accuracy 0.7738 / Loss 0.545713\n",
      "Epoch 99 / Batch (7/17) / Accuracy 0.7812 / Loss 0.537283\n",
      "Epoch 99 / Batch (8/17) / Accuracy 0.7969 / Loss 0.500120\n",
      "Epoch 99 / Batch (9/17) / Accuracy 0.7869 / Loss 0.530292\n",
      "Epoch 99 / Batch (10/17) / Accuracy 0.7969 / Loss 0.523383\n",
      "Epoch 99 / Batch (11/17) / Accuracy 0.7950 / Loss 0.516579\n",
      "Epoch 99 / Batch (12/17) / Accuracy 0.8131 / Loss 0.462427\n",
      "Epoch 99 / Batch (13/17) / Accuracy 0.7887 / Loss 0.506864\n",
      "Epoch 99 / Batch (14/17) / Accuracy 0.7912 / Loss 0.515573\n",
      "Epoch 99 / Batch (15/17) / Accuracy 0.7950 / Loss 0.507773\n",
      "Epoch 99 / Batch (16/17) / Accuracy 0.7663 / Loss 0.564691\n",
      "Epoch 99 / Batch (17/17) / Accuracy 0.7675 / Loss 0.560493\n",
      "Epoch 99 complete, 5.012310266494751 seconds elapsed\n",
      "\n",
      "Epoch 100 starting..\n",
      "Epoch 100 / Batch (1/17) / Accuracy 0.8037 / Loss 0.495455\n",
      "Epoch 100 / Batch (2/17) / Accuracy 0.7969 / Loss 0.511593\n",
      "Epoch 100 / Batch (3/17) / Accuracy 0.7956 / Loss 0.506682\n",
      "Epoch 100 / Batch (4/17) / Accuracy 0.7706 / Loss 0.567864\n",
      "Epoch 100 / Batch (5/17) / Accuracy 0.7750 / Loss 0.551199\n",
      "Epoch 100 / Batch (6/17) / Accuracy 0.8037 / Loss 0.493513\n",
      "Epoch 100 / Batch (7/17) / Accuracy 0.7638 / Loss 0.591091\n",
      "Epoch 100 / Batch (8/17) / Accuracy 0.8219 / Loss 0.479076\n",
      "Epoch 100 / Batch (9/17) / Accuracy 0.7775 / Loss 0.574523\n",
      "Epoch 100 / Batch (10/17) / Accuracy 0.7719 / Loss 0.546977\n",
      "Epoch 100 / Batch (11/17) / Accuracy 0.8087 / Loss 0.520116\n",
      "Epoch 100 / Batch (12/17) / Accuracy 0.7494 / Loss 0.596802\n",
      "Epoch 100 / Batch (13/17) / Accuracy 0.7700 / Loss 0.544198\n",
      "Epoch 100 / Batch (14/17) / Accuracy 0.7631 / Loss 0.551703\n",
      "Epoch 100 / Batch (15/17) / Accuracy 0.8056 / Loss 0.494845\n",
      "Epoch 100 / Batch (16/17) / Accuracy 0.8019 / Loss 0.521609\n",
      "Epoch 100 / Batch (17/17) / Accuracy 0.7763 / Loss 0.531162\n",
      "Epoch 100 complete, 5.006041765213013 seconds elapsed\n",
      "\n",
      "Epoch 101 starting..\n",
      "Epoch 101 / Batch (1/17) / Accuracy 0.7850 / Loss 0.543877\n",
      "Epoch 101 / Batch (2/17) / Accuracy 0.8181 / Loss 0.477948\n",
      "Epoch 101 / Batch (3/17) / Accuracy 0.7713 / Loss 0.552292\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 101 / Batch (4/17) / Accuracy 0.7844 / Loss 0.528556\n",
      "Epoch 101 / Batch (5/17) / Accuracy 0.7644 / Loss 0.582842\n",
      "Epoch 101 / Batch (6/17) / Accuracy 0.7831 / Loss 0.572505\n",
      "Epoch 101 / Batch (7/17) / Accuracy 0.7819 / Loss 0.547974\n",
      "Epoch 101 / Batch (8/17) / Accuracy 0.7844 / Loss 0.529318\n",
      "Epoch 101 / Batch (9/17) / Accuracy 0.7219 / Loss 0.676967\n",
      "Epoch 101 / Batch (10/17) / Accuracy 0.7850 / Loss 0.538908\n",
      "Epoch 101 / Batch (11/17) / Accuracy 0.8175 / Loss 0.461181\n",
      "Epoch 101 / Batch (12/17) / Accuracy 0.7944 / Loss 0.518077\n",
      "Epoch 101 / Batch (13/17) / Accuracy 0.7669 / Loss 0.587566\n",
      "Epoch 101 / Batch (14/17) / Accuracy 0.7756 / Loss 0.546813\n",
      "Epoch 101 / Batch (15/17) / Accuracy 0.7944 / Loss 0.531684\n",
      "Epoch 101 / Batch (16/17) / Accuracy 0.7844 / Loss 0.541626\n",
      "Epoch 101 / Batch (17/17) / Accuracy 0.7462 / Loss 0.593296\n",
      "Epoch 101 complete, 5.145467519760132 seconds elapsed\n",
      "\n",
      "Epoch 102 starting..\n",
      "Epoch 102 / Batch (1/17) / Accuracy 0.7738 / Loss 0.556985\n",
      "Epoch 102 / Batch (2/17) / Accuracy 0.7744 / Loss 0.553951\n",
      "Epoch 102 / Batch (3/17) / Accuracy 0.7950 / Loss 0.514930\n",
      "Epoch 102 / Batch (4/17) / Accuracy 0.8012 / Loss 0.528004\n",
      "Epoch 102 / Batch (5/17) / Accuracy 0.7950 / Loss 0.520371\n",
      "Epoch 102 / Batch (6/17) / Accuracy 0.8350 / Loss 0.436478\n",
      "Epoch 102 / Batch (7/17) / Accuracy 0.7969 / Loss 0.521020\n",
      "Epoch 102 / Batch (8/17) / Accuracy 0.7937 / Loss 0.519177\n",
      "Epoch 102 / Batch (9/17) / Accuracy 0.7738 / Loss 0.563475\n",
      "Epoch 102 / Batch (10/17) / Accuracy 0.7937 / Loss 0.524552\n",
      "Epoch 102 / Batch (11/17) / Accuracy 0.7794 / Loss 0.575235\n",
      "Epoch 102 / Batch (12/17) / Accuracy 0.8019 / Loss 0.507779\n",
      "Epoch 102 / Batch (13/17) / Accuracy 0.8112 / Loss 0.467307\n",
      "Epoch 102 / Batch (14/17) / Accuracy 0.8100 / Loss 0.479147\n",
      "Epoch 102 / Batch (15/17) / Accuracy 0.7800 / Loss 0.536014\n",
      "Epoch 102 / Batch (16/17) / Accuracy 0.7819 / Loss 0.534791\n",
      "Epoch 102 / Batch (17/17) / Accuracy 0.7725 / Loss 0.543327\n",
      "Epoch 102 complete, 5.061506271362305 seconds elapsed\n",
      "\n",
      "Epoch 103 starting..\n",
      "Epoch 103 / Batch (1/17) / Accuracy 0.8050 / Loss 0.514919\n",
      "Epoch 103 / Batch (2/17) / Accuracy 0.8163 / Loss 0.513443\n",
      "Epoch 103 / Batch (3/17) / Accuracy 0.7894 / Loss 0.510456\n",
      "Epoch 103 / Batch (4/17) / Accuracy 0.8012 / Loss 0.531955\n",
      "Epoch 103 / Batch (5/17) / Accuracy 0.7850 / Loss 0.536774\n",
      "Epoch 103 / Batch (6/17) / Accuracy 0.7800 / Loss 0.574941\n",
      "Epoch 103 / Batch (7/17) / Accuracy 0.7869 / Loss 0.489302\n",
      "Epoch 103 / Batch (8/17) / Accuracy 0.7806 / Loss 0.537460\n",
      "Epoch 103 / Batch (9/17) / Accuracy 0.8344 / Loss 0.440907\n",
      "Epoch 103 / Batch (10/17) / Accuracy 0.8044 / Loss 0.489824\n",
      "Epoch 103 / Batch (11/17) / Accuracy 0.8225 / Loss 0.483520\n",
      "Epoch 103 / Batch (12/17) / Accuracy 0.7937 / Loss 0.515003\n",
      "Epoch 103 / Batch (13/17) / Accuracy 0.7856 / Loss 0.561582\n",
      "Epoch 103 / Batch (14/17) / Accuracy 0.7594 / Loss 0.604594\n",
      "Epoch 103 / Batch (15/17) / Accuracy 0.7844 / Loss 0.551751\n",
      "Epoch 103 / Batch (16/17) / Accuracy 0.8025 / Loss 0.489002\n",
      "Epoch 103 / Batch (17/17) / Accuracy 0.8106 / Loss 0.478381\n",
      "Epoch 103 complete, 5.045345306396484 seconds elapsed\n",
      "\n",
      "Epoch 104 starting..\n",
      "Epoch 104 / Batch (1/17) / Accuracy 0.7981 / Loss 0.512107\n",
      "Epoch 104 / Batch (2/17) / Accuracy 0.7750 / Loss 0.550410\n",
      "Epoch 104 / Batch (3/17) / Accuracy 0.8081 / Loss 0.488619\n",
      "Epoch 104 / Batch (4/17) / Accuracy 0.8294 / Loss 0.473849\n",
      "Epoch 104 / Batch (5/17) / Accuracy 0.7819 / Loss 0.520162\n",
      "Epoch 104 / Batch (6/17) / Accuracy 0.8000 / Loss 0.505351\n",
      "Epoch 104 / Batch (7/17) / Accuracy 0.7919 / Loss 0.518196\n",
      "Epoch 104 / Batch (8/17) / Accuracy 0.7912 / Loss 0.511093\n",
      "Epoch 104 / Batch (9/17) / Accuracy 0.8131 / Loss 0.478152\n",
      "Epoch 104 / Batch (10/17) / Accuracy 0.7731 / Loss 0.548788\n",
      "Epoch 104 / Batch (11/17) / Accuracy 0.7950 / Loss 0.534149\n",
      "Epoch 104 / Batch (12/17) / Accuracy 0.7969 / Loss 0.527864\n",
      "Epoch 104 / Batch (13/17) / Accuracy 0.7956 / Loss 0.502191\n",
      "Epoch 104 / Batch (14/17) / Accuracy 0.7919 / Loss 0.521925\n",
      "Epoch 104 / Batch (15/17) / Accuracy 0.8069 / Loss 0.500253\n",
      "Epoch 104 / Batch (16/17) / Accuracy 0.7981 / Loss 0.497739\n",
      "Epoch 104 / Batch (17/17) / Accuracy 0.7819 / Loss 0.522285\n",
      "Epoch 104 complete, 5.173871278762817 seconds elapsed\n",
      "\n",
      "Epoch 105 starting..\n",
      "Epoch 105 / Batch (1/17) / Accuracy 0.8037 / Loss 0.479608\n",
      "Epoch 105 / Batch (2/17) / Accuracy 0.8012 / Loss 0.546804\n",
      "Epoch 105 / Batch (3/17) / Accuracy 0.7800 / Loss 0.551390\n",
      "Epoch 105 / Batch (4/17) / Accuracy 0.8006 / Loss 0.506148\n",
      "Epoch 105 / Batch (5/17) / Accuracy 0.7719 / Loss 0.533985\n",
      "Epoch 105 / Batch (6/17) / Accuracy 0.7638 / Loss 0.588138\n",
      "Epoch 105 / Batch (7/17) / Accuracy 0.7588 / Loss 0.549069\n",
      "Epoch 105 / Batch (8/17) / Accuracy 0.8087 / Loss 0.500903\n",
      "Epoch 105 / Batch (9/17) / Accuracy 0.7656 / Loss 0.574890\n",
      "Epoch 105 / Batch (10/17) / Accuracy 0.7506 / Loss 0.554888\n",
      "Epoch 105 / Batch (11/17) / Accuracy 0.7444 / Loss 0.598961\n",
      "Epoch 105 / Batch (12/17) / Accuracy 0.7844 / Loss 0.546916\n",
      "Epoch 105 / Batch (13/17) / Accuracy 0.8119 / Loss 0.470874\n",
      "Epoch 105 / Batch (14/17) / Accuracy 0.7656 / Loss 0.567702\n",
      "Epoch 105 / Batch (15/17) / Accuracy 0.7700 / Loss 0.563401\n",
      "Epoch 105 / Batch (16/17) / Accuracy 0.7869 / Loss 0.529408\n",
      "Epoch 105 / Batch (17/17) / Accuracy 0.7850 / Loss 0.518493\n",
      "Epoch 105 complete, 5.093577861785889 seconds elapsed\n",
      "\n",
      "Epoch 106 starting..\n",
      "Epoch 106 / Batch (1/17) / Accuracy 0.7869 / Loss 0.543170\n",
      "Epoch 106 / Batch (2/17) / Accuracy 0.7781 / Loss 0.531953\n",
      "Epoch 106 / Batch (3/17) / Accuracy 0.7881 / Loss 0.550376\n",
      "Epoch 106 / Batch (4/17) / Accuracy 0.7869 / Loss 0.535605\n",
      "Epoch 106 / Batch (5/17) / Accuracy 0.7719 / Loss 0.559908\n",
      "Epoch 106 / Batch (6/17) / Accuracy 0.8012 / Loss 0.492277\n",
      "Epoch 106 / Batch (7/17) / Accuracy 0.7987 / Loss 0.517172\n",
      "Epoch 106 / Batch (8/17) / Accuracy 0.7750 / Loss 0.575078\n",
      "Epoch 106 / Batch (9/17) / Accuracy 0.7975 / Loss 0.495915\n",
      "Epoch 106 / Batch (10/17) / Accuracy 0.8125 / Loss 0.484773\n",
      "Epoch 106 / Batch (11/17) / Accuracy 0.7856 / Loss 0.534335\n",
      "Epoch 106 / Batch (12/17) / Accuracy 0.7831 / Loss 0.524915\n",
      "Epoch 106 / Batch (13/17) / Accuracy 0.7856 / Loss 0.522480\n",
      "Epoch 106 / Batch (14/17) / Accuracy 0.8512 / Loss 0.405868\n",
      "Epoch 106 / Batch (15/17) / Accuracy 0.7844 / Loss 0.520903\n",
      "Epoch 106 / Batch (16/17) / Accuracy 0.8037 / Loss 0.499360\n",
      "Epoch 106 / Batch (17/17) / Accuracy 0.7869 / Loss 0.520731\n",
      "Epoch 106 complete, 4.9802405834198 seconds elapsed\n",
      "\n",
      "Epoch 107 starting..\n",
      "Epoch 107 / Batch (1/17) / Accuracy 0.8100 / Loss 0.479368\n",
      "Epoch 107 / Batch (2/17) / Accuracy 0.7950 / Loss 0.507986\n",
      "Epoch 107 / Batch (3/17) / Accuracy 0.7887 / Loss 0.523203\n",
      "Epoch 107 / Batch (4/17) / Accuracy 0.8100 / Loss 0.470592\n",
      "Epoch 107 / Batch (5/17) / Accuracy 0.8319 / Loss 0.442721\n",
      "Epoch 107 / Batch (6/17) / Accuracy 0.7625 / Loss 0.571074\n",
      "Epoch 107 / Batch (7/17) / Accuracy 0.7781 / Loss 0.523028\n",
      "Epoch 107 / Batch (8/17) / Accuracy 0.7694 / Loss 0.558345\n",
      "Epoch 107 / Batch (9/17) / Accuracy 0.7931 / Loss 0.502308\n",
      "Epoch 107 / Batch (10/17) / Accuracy 0.8250 / Loss 0.425851\n",
      "Epoch 107 / Batch (11/17) / Accuracy 0.8150 / Loss 0.478671\n",
      "Epoch 107 / Batch (12/17) / Accuracy 0.8163 / Loss 0.476687\n",
      "Epoch 107 / Batch (13/17) / Accuracy 0.8188 / Loss 0.494862\n",
      "Epoch 107 / Batch (14/17) / Accuracy 0.7919 / Loss 0.516729\n",
      "Epoch 107 / Batch (15/17) / Accuracy 0.8031 / Loss 0.478381\n",
      "Epoch 107 / Batch (16/17) / Accuracy 0.7906 / Loss 0.518429\n",
      "Epoch 107 / Batch (17/17) / Accuracy 0.7950 / Loss 0.501815\n",
      "Epoch 107 complete, 5.034496545791626 seconds elapsed\n",
      "\n",
      "Epoch 108 starting..\n",
      "Epoch 108 / Batch (1/17) / Accuracy 0.7937 / Loss 0.489115\n",
      "Epoch 108 / Batch (2/17) / Accuracy 0.7825 / Loss 0.547872\n",
      "Epoch 108 / Batch (3/17) / Accuracy 0.7875 / Loss 0.489424\n",
      "Epoch 108 / Batch (4/17) / Accuracy 0.7844 / Loss 0.566472\n",
      "Epoch 108 / Batch (5/17) / Accuracy 0.7956 / Loss 0.529653\n",
      "Epoch 108 / Batch (6/17) / Accuracy 0.7731 / Loss 0.554905\n",
      "Epoch 108 / Batch (7/17) / Accuracy 0.7969 / Loss 0.517767\n",
      "Epoch 108 / Batch (8/17) / Accuracy 0.7656 / Loss 0.595925\n",
      "Epoch 108 / Batch (9/17) / Accuracy 0.7725 / Loss 0.546164\n",
      "Epoch 108 / Batch (10/17) / Accuracy 0.8156 / Loss 0.477920\n",
      "Epoch 108 / Batch (11/17) / Accuracy 0.7675 / Loss 0.530013\n",
      "Epoch 108 / Batch (12/17) / Accuracy 0.7756 / Loss 0.531837\n",
      "Epoch 108 / Batch (13/17) / Accuracy 0.8094 / Loss 0.473367\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 108 / Batch (14/17) / Accuracy 0.7819 / Loss 0.527029\n",
      "Epoch 108 / Batch (15/17) / Accuracy 0.7944 / Loss 0.521412\n",
      "Epoch 108 / Batch (16/17) / Accuracy 0.7931 / Loss 0.502957\n",
      "Epoch 108 / Batch (17/17) / Accuracy 0.8144 / Loss 0.463410\n",
      "Epoch 108 complete, 5.0660035610198975 seconds elapsed\n",
      "\n",
      "Epoch 109 starting..\n",
      "Epoch 109 / Batch (1/17) / Accuracy 0.7912 / Loss 0.499869\n",
      "Epoch 109 / Batch (2/17) / Accuracy 0.8144 / Loss 0.471399\n",
      "Epoch 109 / Batch (3/17) / Accuracy 0.8156 / Loss 0.476460\n",
      "Epoch 109 / Batch (4/17) / Accuracy 0.7931 / Loss 0.500581\n",
      "Epoch 109 / Batch (5/17) / Accuracy 0.7606 / Loss 0.579062\n",
      "Epoch 109 / Batch (6/17) / Accuracy 0.8363 / Loss 0.432849\n",
      "Epoch 109 / Batch (7/17) / Accuracy 0.7588 / Loss 0.590969\n",
      "Epoch 109 / Batch (8/17) / Accuracy 0.7987 / Loss 0.517409\n",
      "Epoch 109 / Batch (9/17) / Accuracy 0.7862 / Loss 0.538952\n",
      "Epoch 109 / Batch (10/17) / Accuracy 0.7919 / Loss 0.499315\n",
      "Epoch 109 / Batch (11/17) / Accuracy 0.8069 / Loss 0.483565\n",
      "Epoch 109 / Batch (12/17) / Accuracy 0.7912 / Loss 0.508695\n",
      "Epoch 109 / Batch (13/17) / Accuracy 0.7494 / Loss 0.623409\n",
      "Epoch 109 / Batch (14/17) / Accuracy 0.7781 / Loss 0.536438\n",
      "Epoch 109 / Batch (15/17) / Accuracy 0.7850 / Loss 0.550007\n",
      "Epoch 109 / Batch (16/17) / Accuracy 0.8006 / Loss 0.502335\n",
      "Epoch 109 / Batch (17/17) / Accuracy 0.7837 / Loss 0.520981\n",
      "Epoch 109 complete, 4.939158916473389 seconds elapsed\n",
      "\n",
      "Epoch 110 starting..\n",
      "Epoch 110 / Batch (1/17) / Accuracy 0.7831 / Loss 0.534357\n",
      "Epoch 110 / Batch (2/17) / Accuracy 0.7975 / Loss 0.507110\n",
      "Epoch 110 / Batch (3/17) / Accuracy 0.8031 / Loss 0.493801\n",
      "Epoch 110 / Batch (4/17) / Accuracy 0.7750 / Loss 0.530225\n",
      "Epoch 110 / Batch (5/17) / Accuracy 0.7919 / Loss 0.516352\n",
      "Epoch 110 / Batch (6/17) / Accuracy 0.8006 / Loss 0.481282\n",
      "Epoch 110 / Batch (7/17) / Accuracy 0.8112 / Loss 0.522866\n",
      "Epoch 110 / Batch (8/17) / Accuracy 0.7956 / Loss 0.521275\n",
      "Epoch 110 / Batch (9/17) / Accuracy 0.7856 / Loss 0.502361\n",
      "Epoch 110 / Batch (10/17) / Accuracy 0.8475 / Loss 0.422235\n",
      "Epoch 110 / Batch (11/17) / Accuracy 0.7812 / Loss 0.545323\n",
      "Epoch 110 / Batch (12/17) / Accuracy 0.7875 / Loss 0.512567\n",
      "Epoch 110 / Batch (13/17) / Accuracy 0.7962 / Loss 0.515548\n",
      "Epoch 110 / Batch (14/17) / Accuracy 0.7706 / Loss 0.540473\n",
      "Epoch 110 / Batch (15/17) / Accuracy 0.7525 / Loss 0.596005\n",
      "Epoch 110 / Batch (16/17) / Accuracy 0.8056 / Loss 0.502721\n",
      "Epoch 110 / Batch (17/17) / Accuracy 0.8138 / Loss 0.499854\n",
      "Epoch 110 complete, 4.9674177169799805 seconds elapsed\n",
      "\n",
      "Epoch 111 starting..\n",
      "Epoch 111 / Batch (1/17) / Accuracy 0.7962 / Loss 0.523869\n",
      "Epoch 111 / Batch (2/17) / Accuracy 0.7975 / Loss 0.514344\n",
      "Epoch 111 / Batch (3/17) / Accuracy 0.7450 / Loss 0.631579\n",
      "Epoch 111 / Batch (4/17) / Accuracy 0.8019 / Loss 0.490745\n",
      "Epoch 111 / Batch (5/17) / Accuracy 0.7644 / Loss 0.583848\n",
      "Epoch 111 / Batch (6/17) / Accuracy 0.8106 / Loss 0.491164\n",
      "Epoch 111 / Batch (7/17) / Accuracy 0.7575 / Loss 0.603182\n",
      "Epoch 111 / Batch (8/17) / Accuracy 0.7556 / Loss 0.557989\n",
      "Epoch 111 / Batch (9/17) / Accuracy 0.8062 / Loss 0.493533\n",
      "Epoch 111 / Batch (10/17) / Accuracy 0.7944 / Loss 0.500093\n",
      "Epoch 111 / Batch (11/17) / Accuracy 0.7769 / Loss 0.552890\n",
      "Epoch 111 / Batch (12/17) / Accuracy 0.7944 / Loss 0.523249\n",
      "Epoch 111 / Batch (13/17) / Accuracy 0.8037 / Loss 0.490729\n",
      "Epoch 111 / Batch (14/17) / Accuracy 0.7788 / Loss 0.532935\n",
      "Epoch 111 / Batch (15/17) / Accuracy 0.7500 / Loss 0.633165\n",
      "Epoch 111 / Batch (16/17) / Accuracy 0.7837 / Loss 0.531535\n",
      "Epoch 111 / Batch (17/17) / Accuracy 0.7912 / Loss 0.524705\n",
      "Epoch 111 complete, 4.977326154708862 seconds elapsed\n",
      "\n",
      "Epoch 112 starting..\n",
      "Epoch 112 / Batch (1/17) / Accuracy 0.7681 / Loss 0.559588\n",
      "Epoch 112 / Batch (2/17) / Accuracy 0.8087 / Loss 0.499578\n",
      "Epoch 112 / Batch (3/17) / Accuracy 0.8075 / Loss 0.476348\n",
      "Epoch 112 / Batch (4/17) / Accuracy 0.8194 / Loss 0.482782\n",
      "Epoch 112 / Batch (5/17) / Accuracy 0.7756 / Loss 0.548810\n",
      "Epoch 112 / Batch (6/17) / Accuracy 0.7912 / Loss 0.521296\n",
      "Epoch 112 / Batch (7/17) / Accuracy 0.8044 / Loss 0.507221\n",
      "Epoch 112 / Batch (8/17) / Accuracy 0.7987 / Loss 0.510225\n",
      "Epoch 112 / Batch (9/17) / Accuracy 0.8087 / Loss 0.481504\n",
      "Epoch 112 / Batch (10/17) / Accuracy 0.8144 / Loss 0.481422\n",
      "Epoch 112 / Batch (11/17) / Accuracy 0.8069 / Loss 0.497748\n",
      "Epoch 112 / Batch (12/17) / Accuracy 0.8250 / Loss 0.462809\n",
      "Epoch 112 / Batch (13/17) / Accuracy 0.8031 / Loss 0.467860\n",
      "Epoch 112 / Batch (14/17) / Accuracy 0.7794 / Loss 0.543395\n",
      "Epoch 112 / Batch (15/17) / Accuracy 0.7763 / Loss 0.568340\n",
      "Epoch 112 / Batch (16/17) / Accuracy 0.7994 / Loss 0.502757\n",
      "Epoch 112 / Batch (17/17) / Accuracy 0.7981 / Loss 0.522773\n",
      "Epoch 112 complete, 4.887311935424805 seconds elapsed\n",
      "\n",
      "Epoch 113 starting..\n",
      "Epoch 113 / Batch (1/17) / Accuracy 0.7831 / Loss 0.519377\n",
      "Epoch 113 / Batch (2/17) / Accuracy 0.7894 / Loss 0.503580\n",
      "Epoch 113 / Batch (3/17) / Accuracy 0.7688 / Loss 0.593533\n",
      "Epoch 113 / Batch (4/17) / Accuracy 0.7862 / Loss 0.514218\n",
      "Epoch 113 / Batch (5/17) / Accuracy 0.7794 / Loss 0.540137\n",
      "Epoch 113 / Batch (6/17) / Accuracy 0.7556 / Loss 0.606550\n",
      "Epoch 113 / Batch (7/17) / Accuracy 0.8194 / Loss 0.466088\n",
      "Epoch 113 / Batch (8/17) / Accuracy 0.7919 / Loss 0.543776\n",
      "Epoch 113 / Batch (9/17) / Accuracy 0.7831 / Loss 0.549566\n",
      "Epoch 113 / Batch (10/17) / Accuracy 0.7825 / Loss 0.586958\n",
      "Epoch 113 / Batch (11/17) / Accuracy 0.7769 / Loss 0.593462\n",
      "Epoch 113 / Batch (12/17) / Accuracy 0.7788 / Loss 0.525423\n",
      "Epoch 113 / Batch (13/17) / Accuracy 0.7731 / Loss 0.557219\n",
      "Epoch 113 / Batch (14/17) / Accuracy 0.7856 / Loss 0.544962\n",
      "Epoch 113 / Batch (15/17) / Accuracy 0.7869 / Loss 0.542757\n",
      "Epoch 113 / Batch (16/17) / Accuracy 0.7581 / Loss 0.557256\n",
      "Epoch 113 / Batch (17/17) / Accuracy 0.7869 / Loss 0.534278\n",
      "Epoch 113 complete, 4.873913526535034 seconds elapsed\n",
      "\n",
      "Epoch 114 starting..\n",
      "Epoch 114 / Batch (1/17) / Accuracy 0.7406 / Loss 0.630111\n",
      "Epoch 114 / Batch (2/17) / Accuracy 0.7788 / Loss 0.566140\n",
      "Epoch 114 / Batch (3/17) / Accuracy 0.8125 / Loss 0.502881\n",
      "Epoch 114 / Batch (4/17) / Accuracy 0.7694 / Loss 0.551616\n",
      "Epoch 114 / Batch (5/17) / Accuracy 0.8000 / Loss 0.489928\n",
      "Epoch 114 / Batch (6/17) / Accuracy 0.7794 / Loss 0.538015\n",
      "Epoch 114 / Batch (7/17) / Accuracy 0.7869 / Loss 0.522283\n",
      "Epoch 114 / Batch (8/17) / Accuracy 0.7856 / Loss 0.534631\n",
      "Epoch 114 / Batch (9/17) / Accuracy 0.7875 / Loss 0.504267\n",
      "Epoch 114 / Batch (10/17) / Accuracy 0.7969 / Loss 0.517059\n",
      "Epoch 114 / Batch (11/17) / Accuracy 0.7900 / Loss 0.555932\n",
      "Epoch 114 / Batch (12/17) / Accuracy 0.7781 / Loss 0.572404\n",
      "Epoch 114 / Batch (13/17) / Accuracy 0.7525 / Loss 0.590235\n",
      "Epoch 114 / Batch (14/17) / Accuracy 0.7869 / Loss 0.498878\n",
      "Epoch 114 / Batch (15/17) / Accuracy 0.7900 / Loss 0.532859\n",
      "Epoch 114 / Batch (16/17) / Accuracy 0.7756 / Loss 0.521310\n",
      "Epoch 114 / Batch (17/17) / Accuracy 0.7719 / Loss 0.528983\n",
      "Epoch 114 complete, 6.108101844787598 seconds elapsed\n",
      "\n",
      "Epoch 115 starting..\n",
      "Epoch 115 / Batch (1/17) / Accuracy 0.8044 / Loss 0.479814\n",
      "Epoch 115 / Batch (2/17) / Accuracy 0.7800 / Loss 0.567412\n",
      "Epoch 115 / Batch (3/17) / Accuracy 0.7975 / Loss 0.484044\n",
      "Epoch 115 / Batch (4/17) / Accuracy 0.7819 / Loss 0.500949\n",
      "Epoch 115 / Batch (5/17) / Accuracy 0.8000 / Loss 0.499755\n",
      "Epoch 115 / Batch (6/17) / Accuracy 0.7844 / Loss 0.544104\n",
      "Epoch 115 / Batch (7/17) / Accuracy 0.8069 / Loss 0.478647\n",
      "Epoch 115 / Batch (8/17) / Accuracy 0.8125 / Loss 0.467927\n",
      "Epoch 115 / Batch (9/17) / Accuracy 0.7556 / Loss 0.611655\n",
      "Epoch 115 / Batch (10/17) / Accuracy 0.8100 / Loss 0.468223\n",
      "Epoch 115 / Batch (11/17) / Accuracy 0.7775 / Loss 0.552781\n",
      "Epoch 115 / Batch (12/17) / Accuracy 0.8231 / Loss 0.466650\n",
      "Epoch 115 / Batch (13/17) / Accuracy 0.8100 / Loss 0.501116\n",
      "Epoch 115 / Batch (14/17) / Accuracy 0.7844 / Loss 0.556607\n",
      "Epoch 115 / Batch (15/17) / Accuracy 0.7613 / Loss 0.587471\n",
      "Epoch 115 / Batch (16/17) / Accuracy 0.8056 / Loss 0.488553\n",
      "Epoch 115 / Batch (17/17) / Accuracy 0.7900 / Loss 0.519686\n",
      "Epoch 115 complete, 6.613460540771484 seconds elapsed\n",
      "\n",
      "Epoch 116 starting..\n",
      "Epoch 116 / Batch (1/17) / Accuracy 0.8081 / Loss 0.501551\n",
      "Epoch 116 / Batch (2/17) / Accuracy 0.8000 / Loss 0.517204\n",
      "Epoch 116 / Batch (3/17) / Accuracy 0.8213 / Loss 0.489769\n",
      "Epoch 116 / Batch (4/17) / Accuracy 0.7981 / Loss 0.497218\n",
      "Epoch 116 / Batch (5/17) / Accuracy 0.8044 / Loss 0.527974\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 116 / Batch (6/17) / Accuracy 0.8119 / Loss 0.492014\n",
      "Epoch 116 / Batch (7/17) / Accuracy 0.7875 / Loss 0.522511\n",
      "Epoch 116 / Batch (8/17) / Accuracy 0.8019 / Loss 0.506900\n",
      "Epoch 116 / Batch (9/17) / Accuracy 0.8081 / Loss 0.529586\n",
      "Epoch 116 / Batch (10/17) / Accuracy 0.7775 / Loss 0.526774\n",
      "Epoch 116 / Batch (11/17) / Accuracy 0.8313 / Loss 0.459923\n",
      "Epoch 116 / Batch (12/17) / Accuracy 0.7769 / Loss 0.532020\n",
      "Epoch 116 / Batch (13/17) / Accuracy 0.8081 / Loss 0.489397\n",
      "Epoch 116 / Batch (14/17) / Accuracy 0.7869 / Loss 0.496603\n",
      "Epoch 116 / Batch (15/17) / Accuracy 0.7912 / Loss 0.483608\n",
      "Epoch 116 / Batch (16/17) / Accuracy 0.7900 / Loss 0.502167\n",
      "Epoch 116 / Batch (17/17) / Accuracy 0.7937 / Loss 0.520447\n",
      "Epoch 116 complete, 6.389297723770142 seconds elapsed\n",
      "\n",
      "Epoch 117 starting..\n",
      "Epoch 117 / Batch (1/17) / Accuracy 0.8094 / Loss 0.487730\n",
      "Epoch 117 / Batch (2/17) / Accuracy 0.7706 / Loss 0.558609\n",
      "Epoch 117 / Batch (3/17) / Accuracy 0.7994 / Loss 0.484278\n",
      "Epoch 117 / Batch (4/17) / Accuracy 0.8031 / Loss 0.499744\n",
      "Epoch 117 / Batch (5/17) / Accuracy 0.8306 / Loss 0.450573\n",
      "Epoch 117 / Batch (6/17) / Accuracy 0.7800 / Loss 0.555201\n",
      "Epoch 117 / Batch (7/17) / Accuracy 0.7919 / Loss 0.509683\n",
      "Epoch 117 / Batch (8/17) / Accuracy 0.7744 / Loss 0.529806\n",
      "Epoch 117 / Batch (9/17) / Accuracy 0.7950 / Loss 0.522912\n",
      "Epoch 117 / Batch (10/17) / Accuracy 0.8131 / Loss 0.456986\n",
      "Epoch 117 / Batch (11/17) / Accuracy 0.7862 / Loss 0.544869\n",
      "Epoch 117 / Batch (12/17) / Accuracy 0.7750 / Loss 0.522228\n",
      "Epoch 117 / Batch (13/17) / Accuracy 0.8256 / Loss 0.452969\n",
      "Epoch 117 / Batch (14/17) / Accuracy 0.7700 / Loss 0.573524\n",
      "Epoch 117 / Batch (15/17) / Accuracy 0.8219 / Loss 0.453435\n",
      "Epoch 117 / Batch (16/17) / Accuracy 0.7663 / Loss 0.565865\n",
      "Epoch 117 / Batch (17/17) / Accuracy 0.7956 / Loss 0.543565\n",
      "Epoch 117 complete, 6.626988172531128 seconds elapsed\n",
      "\n",
      "Epoch 118 starting..\n",
      "Epoch 118 / Batch (1/17) / Accuracy 0.8256 / Loss 0.440639\n",
      "Epoch 118 / Batch (2/17) / Accuracy 0.7556 / Loss 0.599321\n",
      "Epoch 118 / Batch (3/17) / Accuracy 0.7487 / Loss 0.587395\n",
      "Epoch 118 / Batch (4/17) / Accuracy 0.7631 / Loss 0.546192\n",
      "Epoch 118 / Batch (5/17) / Accuracy 0.8100 / Loss 0.501251\n",
      "Epoch 118 / Batch (6/17) / Accuracy 0.8031 / Loss 0.506268\n",
      "Epoch 118 / Batch (7/17) / Accuracy 0.7788 / Loss 0.536038\n",
      "Epoch 118 / Batch (8/17) / Accuracy 0.7819 / Loss 0.561708\n",
      "Epoch 118 / Batch (9/17) / Accuracy 0.8163 / Loss 0.498819\n",
      "Epoch 118 / Batch (10/17) / Accuracy 0.8138 / Loss 0.506688\n",
      "Epoch 118 / Batch (11/17) / Accuracy 0.7719 / Loss 0.534062\n",
      "Epoch 118 / Batch (12/17) / Accuracy 0.7588 / Loss 0.584446\n",
      "Epoch 118 / Batch (13/17) / Accuracy 0.7969 / Loss 0.505208\n",
      "Epoch 118 / Batch (14/17) / Accuracy 0.7788 / Loss 0.566623\n",
      "Epoch 118 / Batch (15/17) / Accuracy 0.7881 / Loss 0.528998\n",
      "Epoch 118 / Batch (16/17) / Accuracy 0.7606 / Loss 0.572148\n",
      "Epoch 118 / Batch (17/17) / Accuracy 0.7700 / Loss 0.543056\n",
      "Epoch 118 complete, 6.395957708358765 seconds elapsed\n",
      "\n",
      "Epoch 119 starting..\n",
      "Epoch 119 / Batch (1/17) / Accuracy 0.8019 / Loss 0.505332\n",
      "Epoch 119 / Batch (2/17) / Accuracy 0.7900 / Loss 0.491593\n",
      "Epoch 119 / Batch (3/17) / Accuracy 0.8094 / Loss 0.482342\n",
      "Epoch 119 / Batch (4/17) / Accuracy 0.8344 / Loss 0.426539\n",
      "Epoch 119 / Batch (5/17) / Accuracy 0.8025 / Loss 0.537387\n",
      "Epoch 119 / Batch (6/17) / Accuracy 0.7581 / Loss 0.633327\n",
      "Epoch 119 / Batch (7/17) / Accuracy 0.7800 / Loss 0.529156\n",
      "Epoch 119 / Batch (8/17) / Accuracy 0.8019 / Loss 0.525402\n",
      "Epoch 119 / Batch (9/17) / Accuracy 0.7794 / Loss 0.547529\n",
      "Epoch 119 / Batch (10/17) / Accuracy 0.7981 / Loss 0.491041\n",
      "Epoch 119 / Batch (11/17) / Accuracy 0.7862 / Loss 0.545723\n",
      "Epoch 119 / Batch (12/17) / Accuracy 0.8006 / Loss 0.505357\n",
      "Epoch 119 / Batch (13/17) / Accuracy 0.7887 / Loss 0.514735\n",
      "Epoch 119 / Batch (14/17) / Accuracy 0.7987 / Loss 0.484736\n",
      "Epoch 119 / Batch (15/17) / Accuracy 0.7538 / Loss 0.570376\n",
      "Epoch 119 / Batch (16/17) / Accuracy 0.7950 / Loss 0.507874\n",
      "Epoch 119 / Batch (17/17) / Accuracy 0.7744 / Loss 0.537574\n",
      "Epoch 119 complete, 6.336322069168091 seconds elapsed\n",
      "\n",
      "Epoch 120 starting..\n",
      "Epoch 120 / Batch (1/17) / Accuracy 0.8256 / Loss 0.467293\n",
      "Epoch 120 / Batch (2/17) / Accuracy 0.8087 / Loss 0.479071\n",
      "Epoch 120 / Batch (3/17) / Accuracy 0.8250 / Loss 0.434271\n",
      "Epoch 120 / Batch (4/17) / Accuracy 0.7750 / Loss 0.558323\n",
      "Epoch 120 / Batch (5/17) / Accuracy 0.8131 / Loss 0.481401\n",
      "Epoch 120 / Batch (6/17) / Accuracy 0.7881 / Loss 0.516058\n",
      "Epoch 120 / Batch (7/17) / Accuracy 0.7962 / Loss 0.558329\n",
      "Epoch 120 / Batch (8/17) / Accuracy 0.7856 / Loss 0.543081\n",
      "Epoch 120 / Batch (9/17) / Accuracy 0.7919 / Loss 0.512340\n",
      "Epoch 120 / Batch (10/17) / Accuracy 0.7588 / Loss 0.566127\n",
      "Epoch 120 / Batch (11/17) / Accuracy 0.7844 / Loss 0.541510\n",
      "Epoch 120 / Batch (12/17) / Accuracy 0.8025 / Loss 0.490856\n",
      "Epoch 120 / Batch (13/17) / Accuracy 0.7719 / Loss 0.578350\n",
      "Epoch 120 / Batch (14/17) / Accuracy 0.8006 / Loss 0.515766\n",
      "Epoch 120 / Batch (15/17) / Accuracy 0.7769 / Loss 0.556239\n",
      "Epoch 120 / Batch (16/17) / Accuracy 0.7725 / Loss 0.555899\n",
      "Epoch 120 / Batch (17/17) / Accuracy 0.7900 / Loss 0.562905\n",
      "Epoch 120 complete, 6.6028900146484375 seconds elapsed\n",
      "\n",
      "Epoch 121 starting..\n",
      "Epoch 121 / Batch (1/17) / Accuracy 0.8331 / Loss 0.444451\n",
      "Epoch 121 / Batch (2/17) / Accuracy 0.8100 / Loss 0.496189\n",
      "Epoch 121 / Batch (3/17) / Accuracy 0.7981 / Loss 0.501625\n",
      "Epoch 121 / Batch (4/17) / Accuracy 0.7594 / Loss 0.585219\n",
      "Epoch 121 / Batch (5/17) / Accuracy 0.8075 / Loss 0.503828\n",
      "Epoch 121 / Batch (6/17) / Accuracy 0.8519 / Loss 0.387533\n",
      "Epoch 121 / Batch (7/17) / Accuracy 0.7706 / Loss 0.563436\n",
      "Epoch 121 / Batch (8/17) / Accuracy 0.7625 / Loss 0.585030\n",
      "Epoch 121 / Batch (9/17) / Accuracy 0.8037 / Loss 0.505039\n",
      "Epoch 121 / Batch (10/17) / Accuracy 0.8225 / Loss 0.463792\n",
      "Epoch 121 / Batch (11/17) / Accuracy 0.7800 / Loss 0.555350\n",
      "Epoch 121 / Batch (12/17) / Accuracy 0.7887 / Loss 0.516629\n",
      "Epoch 121 / Batch (13/17) / Accuracy 0.7800 / Loss 0.556193\n",
      "Epoch 121 / Batch (14/17) / Accuracy 0.7744 / Loss 0.548129\n",
      "Epoch 121 / Batch (15/17) / Accuracy 0.7788 / Loss 0.532014\n",
      "Epoch 121 / Batch (16/17) / Accuracy 0.8144 / Loss 0.473407\n",
      "Epoch 121 / Batch (17/17) / Accuracy 0.7912 / Loss 0.522737\n",
      "Epoch 121 complete, 6.104544162750244 seconds elapsed\n",
      "\n",
      "Epoch 122 starting..\n",
      "Epoch 122 / Batch (1/17) / Accuracy 0.7763 / Loss 0.543739\n",
      "Epoch 122 / Batch (2/17) / Accuracy 0.7950 / Loss 0.499742\n",
      "Epoch 122 / Batch (3/17) / Accuracy 0.8369 / Loss 0.417703\n",
      "Epoch 122 / Batch (4/17) / Accuracy 0.7919 / Loss 0.539355\n",
      "Epoch 122 / Batch (5/17) / Accuracy 0.7656 / Loss 0.591741\n",
      "Epoch 122 / Batch (6/17) / Accuracy 0.7925 / Loss 0.544126\n",
      "Epoch 122 / Batch (7/17) / Accuracy 0.7694 / Loss 0.575621\n",
      "Epoch 122 / Batch (8/17) / Accuracy 0.8144 / Loss 0.471630\n",
      "Epoch 122 / Batch (9/17) / Accuracy 0.7962 / Loss 0.505958\n",
      "Epoch 122 / Batch (10/17) / Accuracy 0.8019 / Loss 0.505195\n",
      "Epoch 122 / Batch (11/17) / Accuracy 0.7912 / Loss 0.502834\n",
      "Epoch 122 / Batch (12/17) / Accuracy 0.7912 / Loss 0.525131\n",
      "Epoch 122 / Batch (13/17) / Accuracy 0.8156 / Loss 0.485053\n",
      "Epoch 122 / Batch (14/17) / Accuracy 0.7487 / Loss 0.641377\n",
      "Epoch 122 / Batch (15/17) / Accuracy 0.7919 / Loss 0.501662\n",
      "Epoch 122 / Batch (16/17) / Accuracy 0.8025 / Loss 0.496841\n",
      "Epoch 122 / Batch (17/17) / Accuracy 0.7794 / Loss 0.537856\n",
      "Epoch 122 complete, 6.74441385269165 seconds elapsed\n",
      "\n",
      "Epoch 123 starting..\n",
      "Epoch 123 / Batch (1/17) / Accuracy 0.7719 / Loss 0.530280\n",
      "Epoch 123 / Batch (2/17) / Accuracy 0.7713 / Loss 0.605554\n",
      "Epoch 123 / Batch (3/17) / Accuracy 0.7794 / Loss 0.540394\n",
      "Epoch 123 / Batch (4/17) / Accuracy 0.7706 / Loss 0.586045\n",
      "Epoch 123 / Batch (5/17) / Accuracy 0.7919 / Loss 0.505173\n",
      "Epoch 123 / Batch (6/17) / Accuracy 0.8219 / Loss 0.450113\n",
      "Epoch 123 / Batch (7/17) / Accuracy 0.8031 / Loss 0.504274\n",
      "Epoch 123 / Batch (8/17) / Accuracy 0.7806 / Loss 0.539042\n",
      "Epoch 123 / Batch (9/17) / Accuracy 0.7825 / Loss 0.540149\n",
      "Epoch 123 / Batch (10/17) / Accuracy 0.8025 / Loss 0.476846\n",
      "Epoch 123 / Batch (11/17) / Accuracy 0.8181 / Loss 0.480995\n",
      "Epoch 123 / Batch (12/17) / Accuracy 0.7881 / Loss 0.537931\n",
      "Epoch 123 / Batch (13/17) / Accuracy 0.8044 / Loss 0.526141\n",
      "Epoch 123 / Batch (14/17) / Accuracy 0.7819 / Loss 0.560749\n",
      "Epoch 123 / Batch (15/17) / Accuracy 0.7619 / Loss 0.567204\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 123 / Batch (16/17) / Accuracy 0.7719 / Loss 0.549720\n",
      "Epoch 123 / Batch (17/17) / Accuracy 0.7837 / Loss 0.535162\n",
      "Epoch 123 complete, 6.410094738006592 seconds elapsed\n",
      "\n",
      "Epoch 124 starting..\n",
      "Epoch 124 / Batch (1/17) / Accuracy 0.8306 / Loss 0.493460\n",
      "Epoch 124 / Batch (2/17) / Accuracy 0.7519 / Loss 0.606093\n",
      "Epoch 124 / Batch (3/17) / Accuracy 0.7675 / Loss 0.552478\n",
      "Epoch 124 / Batch (4/17) / Accuracy 0.7850 / Loss 0.513363\n",
      "Epoch 124 / Batch (5/17) / Accuracy 0.8112 / Loss 0.471112\n",
      "Epoch 124 / Batch (6/17) / Accuracy 0.7781 / Loss 0.567016\n",
      "Epoch 124 / Batch (7/17) / Accuracy 0.7631 / Loss 0.570803\n",
      "Epoch 124 / Batch (8/17) / Accuracy 0.7944 / Loss 0.499764\n",
      "Epoch 124 / Batch (9/17) / Accuracy 0.7456 / Loss 0.600510\n",
      "Epoch 124 / Batch (10/17) / Accuracy 0.8381 / Loss 0.419121\n",
      "Epoch 124 / Batch (11/17) / Accuracy 0.8125 / Loss 0.493329\n",
      "Epoch 124 / Batch (12/17) / Accuracy 0.8050 / Loss 0.495429\n",
      "Epoch 124 / Batch (13/17) / Accuracy 0.7956 / Loss 0.521378\n",
      "Epoch 124 / Batch (14/17) / Accuracy 0.8294 / Loss 0.426493\n",
      "Epoch 124 / Batch (15/17) / Accuracy 0.8075 / Loss 0.483067\n",
      "Epoch 124 / Batch (16/17) / Accuracy 0.7994 / Loss 0.517512\n",
      "Epoch 124 / Batch (17/17) / Accuracy 0.8194 / Loss 0.435927\n",
      "Epoch 124 complete, 6.3144214153289795 seconds elapsed\n",
      "\n",
      "Epoch 125 starting..\n",
      "Epoch 125 / Batch (1/17) / Accuracy 0.8106 / Loss 0.483304\n",
      "Epoch 125 / Batch (2/17) / Accuracy 0.8056 / Loss 0.525145\n",
      "Epoch 125 / Batch (3/17) / Accuracy 0.8006 / Loss 0.484855\n",
      "Epoch 125 / Batch (4/17) / Accuracy 0.7994 / Loss 0.483764\n",
      "Epoch 125 / Batch (5/17) / Accuracy 0.7944 / Loss 0.546390\n",
      "Epoch 125 / Batch (6/17) / Accuracy 0.7981 / Loss 0.504953\n",
      "Epoch 125 / Batch (7/17) / Accuracy 0.7769 / Loss 0.536240\n",
      "Epoch 125 / Batch (8/17) / Accuracy 0.7756 / Loss 0.577513\n",
      "Epoch 125 / Batch (9/17) / Accuracy 0.7812 / Loss 0.531174\n",
      "Epoch 125 / Batch (10/17) / Accuracy 0.7625 / Loss 0.571831\n",
      "Epoch 125 / Batch (11/17) / Accuracy 0.7656 / Loss 0.582261\n",
      "Epoch 125 / Batch (12/17) / Accuracy 0.8231 / Loss 0.467041\n",
      "Epoch 125 / Batch (13/17) / Accuracy 0.7800 / Loss 0.553442\n",
      "Epoch 125 / Batch (14/17) / Accuracy 0.8150 / Loss 0.468573\n",
      "Epoch 125 / Batch (15/17) / Accuracy 0.7856 / Loss 0.558943\n",
      "Epoch 125 / Batch (16/17) / Accuracy 0.8050 / Loss 0.465942\n",
      "Epoch 125 / Batch (17/17) / Accuracy 0.8288 / Loss 0.457730\n",
      "Epoch 125 complete, 6.956027269363403 seconds elapsed\n",
      "\n",
      "Epoch 126 starting..\n",
      "Epoch 126 / Batch (1/17) / Accuracy 0.8012 / Loss 0.486395\n",
      "Epoch 126 / Batch (2/17) / Accuracy 0.7950 / Loss 0.498132\n",
      "Epoch 126 / Batch (3/17) / Accuracy 0.8050 / Loss 0.515754\n",
      "Epoch 126 / Batch (4/17) / Accuracy 0.8256 / Loss 0.444455\n",
      "Epoch 126 / Batch (5/17) / Accuracy 0.8106 / Loss 0.483255\n",
      "Epoch 126 / Batch (6/17) / Accuracy 0.7731 / Loss 0.545923\n",
      "Epoch 126 / Batch (7/17) / Accuracy 0.7869 / Loss 0.540046\n",
      "Epoch 126 / Batch (8/17) / Accuracy 0.7931 / Loss 0.523129\n",
      "Epoch 126 / Batch (9/17) / Accuracy 0.7950 / Loss 0.502720\n",
      "Epoch 126 / Batch (10/17) / Accuracy 0.7819 / Loss 0.538767\n",
      "Epoch 126 / Batch (11/17) / Accuracy 0.8281 / Loss 0.437968\n",
      "Epoch 126 / Batch (12/17) / Accuracy 0.8012 / Loss 0.506693\n",
      "Epoch 126 / Batch (13/17) / Accuracy 0.8281 / Loss 0.447662\n",
      "Epoch 126 / Batch (14/17) / Accuracy 0.7862 / Loss 0.513649\n",
      "Epoch 126 / Batch (15/17) / Accuracy 0.8006 / Loss 0.494123\n",
      "Epoch 126 / Batch (16/17) / Accuracy 0.7937 / Loss 0.542864\n",
      "Epoch 126 / Batch (17/17) / Accuracy 0.7731 / Loss 0.571520\n",
      "Epoch 126 complete, 6.6681067943573 seconds elapsed\n",
      "\n",
      "Epoch 127 starting..\n",
      "Epoch 127 / Batch (1/17) / Accuracy 0.7894 / Loss 0.516513\n",
      "Epoch 127 / Batch (2/17) / Accuracy 0.7956 / Loss 0.513505\n",
      "Epoch 127 / Batch (3/17) / Accuracy 0.8094 / Loss 0.499633\n",
      "Epoch 127 / Batch (4/17) / Accuracy 0.7956 / Loss 0.493291\n",
      "Epoch 127 / Batch (5/17) / Accuracy 0.7825 / Loss 0.521368\n",
      "Epoch 127 / Batch (6/17) / Accuracy 0.8006 / Loss 0.490363\n",
      "Epoch 127 / Batch (7/17) / Accuracy 0.7563 / Loss 0.567401\n",
      "Epoch 127 / Batch (8/17) / Accuracy 0.8144 / Loss 0.449211\n",
      "Epoch 127 / Batch (9/17) / Accuracy 0.7806 / Loss 0.571468\n",
      "Epoch 127 / Batch (10/17) / Accuracy 0.7925 / Loss 0.496847\n",
      "Epoch 127 / Batch (11/17) / Accuracy 0.7700 / Loss 0.550846\n",
      "Epoch 127 / Batch (12/17) / Accuracy 0.8069 / Loss 0.472911\n",
      "Epoch 127 / Batch (13/17) / Accuracy 0.7775 / Loss 0.529427\n",
      "Epoch 127 / Batch (14/17) / Accuracy 0.7931 / Loss 0.520046\n",
      "Epoch 127 / Batch (15/17) / Accuracy 0.8238 / Loss 0.451575\n",
      "Epoch 127 / Batch (16/17) / Accuracy 0.8225 / Loss 0.478823\n",
      "Epoch 127 / Batch (17/17) / Accuracy 0.8050 / Loss 0.487264\n",
      "Epoch 127 complete, 6.293310642242432 seconds elapsed\n",
      "\n",
      "Epoch 128 starting..\n",
      "Epoch 128 / Batch (1/17) / Accuracy 0.8050 / Loss 0.492102\n",
      "Epoch 128 / Batch (2/17) / Accuracy 0.8069 / Loss 0.494505\n",
      "Epoch 128 / Batch (3/17) / Accuracy 0.7856 / Loss 0.562764\n",
      "Epoch 128 / Batch (4/17) / Accuracy 0.8094 / Loss 0.480690\n",
      "Epoch 128 / Batch (5/17) / Accuracy 0.8163 / Loss 0.485937\n",
      "Epoch 128 / Batch (6/17) / Accuracy 0.7706 / Loss 0.545647\n",
      "Epoch 128 / Batch (7/17) / Accuracy 0.8238 / Loss 0.459518\n",
      "Epoch 128 / Batch (8/17) / Accuracy 0.8169 / Loss 0.472427\n",
      "Epoch 128 / Batch (9/17) / Accuracy 0.7812 / Loss 0.545485\n",
      "Epoch 128 / Batch (10/17) / Accuracy 0.7856 / Loss 0.515508\n",
      "Epoch 128 / Batch (11/17) / Accuracy 0.8056 / Loss 0.495165\n",
      "Epoch 128 / Batch (12/17) / Accuracy 0.8119 / Loss 0.482510\n",
      "Epoch 128 / Batch (13/17) / Accuracy 0.8037 / Loss 0.511172\n",
      "Epoch 128 / Batch (14/17) / Accuracy 0.7875 / Loss 0.541314\n",
      "Epoch 128 / Batch (15/17) / Accuracy 0.8131 / Loss 0.506195\n",
      "Epoch 128 / Batch (16/17) / Accuracy 0.7900 / Loss 0.526217\n",
      "Epoch 128 / Batch (17/17) / Accuracy 0.7975 / Loss 0.504487\n",
      "Epoch 128 complete, 6.7486653327941895 seconds elapsed\n",
      "\n",
      "Epoch 129 starting..\n",
      "Epoch 129 / Batch (1/17) / Accuracy 0.7956 / Loss 0.502844\n",
      "Epoch 129 / Batch (2/17) / Accuracy 0.8125 / Loss 0.489732\n",
      "Epoch 129 / Batch (3/17) / Accuracy 0.8081 / Loss 0.483569\n",
      "Epoch 129 / Batch (4/17) / Accuracy 0.7837 / Loss 0.503550\n",
      "Epoch 129 / Batch (5/17) / Accuracy 0.7750 / Loss 0.546409\n",
      "Epoch 129 / Batch (6/17) / Accuracy 0.7806 / Loss 0.545663\n",
      "Epoch 129 / Batch (7/17) / Accuracy 0.8256 / Loss 0.445693\n",
      "Epoch 129 / Batch (8/17) / Accuracy 0.7937 / Loss 0.520706\n",
      "Epoch 129 / Batch (9/17) / Accuracy 0.8031 / Loss 0.506615\n",
      "Epoch 129 / Batch (10/17) / Accuracy 0.8125 / Loss 0.472677\n",
      "Epoch 129 / Batch (11/17) / Accuracy 0.7825 / Loss 0.535638\n",
      "Epoch 129 / Batch (12/17) / Accuracy 0.8206 / Loss 0.464443\n",
      "Epoch 129 / Batch (13/17) / Accuracy 0.8206 / Loss 0.464947\n",
      "Epoch 129 / Batch (14/17) / Accuracy 0.8375 / Loss 0.435974\n",
      "Epoch 129 / Batch (15/17) / Accuracy 0.7837 / Loss 0.539461\n",
      "Epoch 129 / Batch (16/17) / Accuracy 0.8325 / Loss 0.429360\n",
      "Epoch 129 / Batch (17/17) / Accuracy 0.8050 / Loss 0.503545\n",
      "Epoch 129 complete, 6.463213205337524 seconds elapsed\n",
      "\n",
      "Epoch 130 starting..\n",
      "Epoch 130 / Batch (1/17) / Accuracy 0.8081 / Loss 0.454407\n",
      "Epoch 130 / Batch (2/17) / Accuracy 0.7819 / Loss 0.506766\n",
      "Epoch 130 / Batch (3/17) / Accuracy 0.7856 / Loss 0.535250\n",
      "Epoch 130 / Batch (4/17) / Accuracy 0.7900 / Loss 0.514337\n",
      "Epoch 130 / Batch (5/17) / Accuracy 0.8012 / Loss 0.511743\n",
      "Epoch 130 / Batch (6/17) / Accuracy 0.7944 / Loss 0.492740\n",
      "Epoch 130 / Batch (7/17) / Accuracy 0.7719 / Loss 0.562572\n",
      "Epoch 130 / Batch (8/17) / Accuracy 0.7925 / Loss 0.504400\n",
      "Epoch 130 / Batch (9/17) / Accuracy 0.7969 / Loss 0.518557\n",
      "Epoch 130 / Batch (10/17) / Accuracy 0.8331 / Loss 0.438382\n",
      "Epoch 130 / Batch (11/17) / Accuracy 0.7569 / Loss 0.589909\n",
      "Epoch 130 / Batch (12/17) / Accuracy 0.7881 / Loss 0.522455\n",
      "Epoch 130 / Batch (13/17) / Accuracy 0.8075 / Loss 0.492423\n",
      "Epoch 130 / Batch (14/17) / Accuracy 0.7856 / Loss 0.521920\n",
      "Epoch 130 / Batch (15/17) / Accuracy 0.7744 / Loss 0.581491\n",
      "Epoch 130 / Batch (16/17) / Accuracy 0.7750 / Loss 0.532116\n",
      "Epoch 130 / Batch (17/17) / Accuracy 0.7869 / Loss 0.532898\n",
      "Epoch 130 complete, 6.99903416633606 seconds elapsed\n",
      "\n",
      "Epoch 131 starting..\n",
      "Epoch 131 / Batch (1/17) / Accuracy 0.7812 / Loss 0.553064\n",
      "Epoch 131 / Batch (2/17) / Accuracy 0.7875 / Loss 0.570579\n",
      "Epoch 131 / Batch (3/17) / Accuracy 0.8331 / Loss 0.413714\n",
      "Epoch 131 / Batch (4/17) / Accuracy 0.8125 / Loss 0.493068\n",
      "Epoch 131 / Batch (5/17) / Accuracy 0.8031 / Loss 0.511322\n",
      "Epoch 131 / Batch (6/17) / Accuracy 0.8256 / Loss 0.439308\n",
      "Epoch 131 / Batch (7/17) / Accuracy 0.8019 / Loss 0.495395\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 131 / Batch (8/17) / Accuracy 0.8225 / Loss 0.450537\n",
      "Epoch 131 / Batch (9/17) / Accuracy 0.8012 / Loss 0.487531\n",
      "Epoch 131 / Batch (10/17) / Accuracy 0.7681 / Loss 0.564868\n",
      "Epoch 131 / Batch (11/17) / Accuracy 0.7806 / Loss 0.522175\n",
      "Epoch 131 / Batch (12/17) / Accuracy 0.7800 / Loss 0.526355\n",
      "Epoch 131 / Batch (13/17) / Accuracy 0.8006 / Loss 0.531225\n",
      "Epoch 131 / Batch (14/17) / Accuracy 0.8006 / Loss 0.516802\n",
      "Epoch 131 / Batch (15/17) / Accuracy 0.7487 / Loss 0.615098\n",
      "Epoch 131 / Batch (16/17) / Accuracy 0.7881 / Loss 0.519479\n",
      "Epoch 131 / Batch (17/17) / Accuracy 0.7725 / Loss 0.545300\n",
      "Epoch 131 complete, 6.19576096534729 seconds elapsed\n",
      "\n",
      "Epoch 132 starting..\n",
      "Epoch 132 / Batch (1/17) / Accuracy 0.8225 / Loss 0.461291\n",
      "Epoch 132 / Batch (2/17) / Accuracy 0.7975 / Loss 0.509805\n",
      "Epoch 132 / Batch (3/17) / Accuracy 0.7925 / Loss 0.508156\n",
      "Epoch 132 / Batch (4/17) / Accuracy 0.8406 / Loss 0.430193\n",
      "Epoch 132 / Batch (5/17) / Accuracy 0.7781 / Loss 0.565208\n",
      "Epoch 132 / Batch (6/17) / Accuracy 0.7969 / Loss 0.514375\n",
      "Epoch 132 / Batch (7/17) / Accuracy 0.7556 / Loss 0.585705\n",
      "Epoch 132 / Batch (8/17) / Accuracy 0.7812 / Loss 0.567497\n",
      "Epoch 132 / Batch (9/17) / Accuracy 0.8131 / Loss 0.469331\n",
      "Epoch 132 / Batch (10/17) / Accuracy 0.8294 / Loss 0.450158\n",
      "Epoch 132 / Batch (11/17) / Accuracy 0.8263 / Loss 0.472112\n",
      "Epoch 132 / Batch (12/17) / Accuracy 0.7894 / Loss 0.519086\n",
      "Epoch 132 / Batch (13/17) / Accuracy 0.7650 / Loss 0.571689\n",
      "Epoch 132 / Batch (14/17) / Accuracy 0.8175 / Loss 0.453848\n",
      "Epoch 132 / Batch (15/17) / Accuracy 0.7756 / Loss 0.546350\n",
      "Epoch 132 / Batch (16/17) / Accuracy 0.8256 / Loss 0.471528\n",
      "Epoch 132 / Batch (17/17) / Accuracy 0.7631 / Loss 0.572250\n",
      "Epoch 132 complete, 6.505292654037476 seconds elapsed\n",
      "\n",
      "Epoch 133 starting..\n",
      "Epoch 133 / Batch (1/17) / Accuracy 0.7650 / Loss 0.593370\n",
      "Epoch 133 / Batch (2/17) / Accuracy 0.8044 / Loss 0.486161\n",
      "Epoch 133 / Batch (3/17) / Accuracy 0.7975 / Loss 0.527167\n",
      "Epoch 133 / Batch (4/17) / Accuracy 0.7781 / Loss 0.528330\n",
      "Epoch 133 / Batch (5/17) / Accuracy 0.7900 / Loss 0.527039\n",
      "Epoch 133 / Batch (6/17) / Accuracy 0.7694 / Loss 0.556913\n",
      "Epoch 133 / Batch (7/17) / Accuracy 0.8125 / Loss 0.473204\n",
      "Epoch 133 / Batch (8/17) / Accuracy 0.7812 / Loss 0.537758\n",
      "Epoch 133 / Batch (9/17) / Accuracy 0.8169 / Loss 0.483647\n",
      "Epoch 133 / Batch (10/17) / Accuracy 0.8163 / Loss 0.466782\n",
      "Epoch 133 / Batch (11/17) / Accuracy 0.7713 / Loss 0.551353\n",
      "Epoch 133 / Batch (12/17) / Accuracy 0.7825 / Loss 0.529901\n",
      "Epoch 133 / Batch (13/17) / Accuracy 0.8112 / Loss 0.508754\n",
      "Epoch 133 / Batch (14/17) / Accuracy 0.7944 / Loss 0.549968\n",
      "Epoch 133 / Batch (15/17) / Accuracy 0.7950 / Loss 0.499018\n",
      "Epoch 133 / Batch (16/17) / Accuracy 0.8056 / Loss 0.509060\n",
      "Epoch 133 / Batch (17/17) / Accuracy 0.7937 / Loss 0.523092\n",
      "Epoch 133 complete, 7.045791387557983 seconds elapsed\n",
      "\n",
      "Epoch 134 starting..\n",
      "Epoch 134 / Batch (1/17) / Accuracy 0.8044 / Loss 0.486658\n",
      "Epoch 134 / Batch (2/17) / Accuracy 0.8012 / Loss 0.511153\n",
      "Epoch 134 / Batch (3/17) / Accuracy 0.7900 / Loss 0.503636\n",
      "Epoch 134 / Batch (4/17) / Accuracy 0.7850 / Loss 0.530241\n",
      "Epoch 134 / Batch (5/17) / Accuracy 0.8275 / Loss 0.443136\n",
      "Epoch 134 / Batch (6/17) / Accuracy 0.8194 / Loss 0.465291\n",
      "Epoch 134 / Batch (7/17) / Accuracy 0.7881 / Loss 0.548179\n",
      "Epoch 134 / Batch (8/17) / Accuracy 0.7981 / Loss 0.507027\n",
      "Epoch 134 / Batch (9/17) / Accuracy 0.7744 / Loss 0.557802\n",
      "Epoch 134 / Batch (10/17) / Accuracy 0.8087 / Loss 0.499747\n",
      "Epoch 134 / Batch (11/17) / Accuracy 0.8163 / Loss 0.483593\n",
      "Epoch 134 / Batch (12/17) / Accuracy 0.7987 / Loss 0.524957\n",
      "Epoch 134 / Batch (13/17) / Accuracy 0.7931 / Loss 0.558157\n",
      "Epoch 134 / Batch (14/17) / Accuracy 0.7862 / Loss 0.519439\n",
      "Epoch 134 / Batch (15/17) / Accuracy 0.8175 / Loss 0.509022\n",
      "Epoch 134 / Batch (16/17) / Accuracy 0.7781 / Loss 0.577331\n",
      "Epoch 134 / Batch (17/17) / Accuracy 0.7919 / Loss 0.504821\n",
      "Epoch 134 complete, 6.690294504165649 seconds elapsed\n",
      "\n",
      "Epoch 135 starting..\n",
      "Epoch 135 / Batch (1/17) / Accuracy 0.7987 / Loss 0.506267\n",
      "Epoch 135 / Batch (2/17) / Accuracy 0.8138 / Loss 0.488754\n",
      "Epoch 135 / Batch (3/17) / Accuracy 0.7750 / Loss 0.534269\n",
      "Epoch 135 / Batch (4/17) / Accuracy 0.7981 / Loss 0.526050\n",
      "Epoch 135 / Batch (5/17) / Accuracy 0.7937 / Loss 0.502242\n",
      "Epoch 135 / Batch (6/17) / Accuracy 0.7912 / Loss 0.518010\n",
      "Epoch 135 / Batch (7/17) / Accuracy 0.8037 / Loss 0.503807\n",
      "Epoch 135 / Batch (8/17) / Accuracy 0.7844 / Loss 0.539677\n",
      "Epoch 135 / Batch (9/17) / Accuracy 0.7962 / Loss 0.533549\n",
      "Epoch 135 / Batch (10/17) / Accuracy 0.8331 / Loss 0.442607\n",
      "Epoch 135 / Batch (11/17) / Accuracy 0.8100 / Loss 0.488854\n",
      "Epoch 135 / Batch (12/17) / Accuracy 0.7862 / Loss 0.552876\n",
      "Epoch 135 / Batch (13/17) / Accuracy 0.7750 / Loss 0.534294\n",
      "Epoch 135 / Batch (14/17) / Accuracy 0.7975 / Loss 0.529753\n",
      "Epoch 135 / Batch (15/17) / Accuracy 0.8025 / Loss 0.506327\n",
      "Epoch 135 / Batch (16/17) / Accuracy 0.8081 / Loss 0.486211\n",
      "Epoch 135 / Batch (17/17) / Accuracy 0.8150 / Loss 0.459267\n",
      "Epoch 135 complete, 6.300860404968262 seconds elapsed\n",
      "\n",
      "Epoch 136 starting..\n",
      "Epoch 136 / Batch (1/17) / Accuracy 0.8269 / Loss 0.469499\n",
      "Epoch 136 / Batch (2/17) / Accuracy 0.8231 / Loss 0.448331\n",
      "Epoch 136 / Batch (3/17) / Accuracy 0.7987 / Loss 0.501926\n",
      "Epoch 136 / Batch (4/17) / Accuracy 0.7956 / Loss 0.499135\n",
      "Epoch 136 / Batch (5/17) / Accuracy 0.8019 / Loss 0.496878\n",
      "Epoch 136 / Batch (6/17) / Accuracy 0.8075 / Loss 0.473068\n",
      "Epoch 136 / Batch (7/17) / Accuracy 0.8469 / Loss 0.419131\n",
      "Epoch 136 / Batch (8/17) / Accuracy 0.7844 / Loss 0.532818\n",
      "Epoch 136 / Batch (9/17) / Accuracy 0.7906 / Loss 0.517966\n",
      "Epoch 136 / Batch (10/17) / Accuracy 0.7869 / Loss 0.509101\n",
      "Epoch 136 / Batch (11/17) / Accuracy 0.7925 / Loss 0.522371\n",
      "Epoch 136 / Batch (12/17) / Accuracy 0.7837 / Loss 0.543531\n",
      "Epoch 136 / Batch (13/17) / Accuracy 0.8344 / Loss 0.446214\n",
      "Epoch 136 / Batch (14/17) / Accuracy 0.8094 / Loss 0.477851\n",
      "Epoch 136 / Batch (15/17) / Accuracy 0.7925 / Loss 0.522516\n",
      "Epoch 136 / Batch (16/17) / Accuracy 0.7962 / Loss 0.496842\n",
      "Epoch 136 / Batch (17/17) / Accuracy 0.7881 / Loss 0.534429\n",
      "Epoch 136 complete, 5.9931347370147705 seconds elapsed\n",
      "\n",
      "Epoch 137 starting..\n",
      "Epoch 137 / Batch (1/17) / Accuracy 0.7962 / Loss 0.543128\n",
      "Epoch 137 / Batch (2/17) / Accuracy 0.8119 / Loss 0.462871\n",
      "Epoch 137 / Batch (3/17) / Accuracy 0.7844 / Loss 0.531063\n",
      "Epoch 137 / Batch (4/17) / Accuracy 0.7850 / Loss 0.573949\n",
      "Epoch 137 / Batch (5/17) / Accuracy 0.7906 / Loss 0.528042\n",
      "Epoch 137 / Batch (6/17) / Accuracy 0.7875 / Loss 0.528535\n",
      "Epoch 137 / Batch (7/17) / Accuracy 0.7731 / Loss 0.567277\n",
      "Epoch 137 / Batch (8/17) / Accuracy 0.8344 / Loss 0.457580\n",
      "Epoch 137 / Batch (9/17) / Accuracy 0.7375 / Loss 0.630611\n",
      "Epoch 137 / Batch (10/17) / Accuracy 0.7681 / Loss 0.550555\n",
      "Epoch 137 / Batch (11/17) / Accuracy 0.8300 / Loss 0.458446\n",
      "Epoch 137 / Batch (12/17) / Accuracy 0.7869 / Loss 0.526404\n",
      "Epoch 137 / Batch (13/17) / Accuracy 0.8206 / Loss 0.465354\n",
      "Epoch 137 / Batch (14/17) / Accuracy 0.8131 / Loss 0.458635\n",
      "Epoch 137 / Batch (15/17) / Accuracy 0.8050 / Loss 0.477324\n",
      "Epoch 137 / Batch (16/17) / Accuracy 0.8075 / Loss 0.473485\n",
      "Epoch 137 / Batch (17/17) / Accuracy 0.7881 / Loss 0.524201\n",
      "Epoch 137 complete, 6.124695777893066 seconds elapsed\n",
      "\n",
      "Epoch 138 starting..\n",
      "Epoch 138 / Batch (1/17) / Accuracy 0.7931 / Loss 0.505265\n",
      "Epoch 138 / Batch (2/17) / Accuracy 0.8031 / Loss 0.488525\n",
      "Epoch 138 / Batch (3/17) / Accuracy 0.7962 / Loss 0.489856\n",
      "Epoch 138 / Batch (4/17) / Accuracy 0.8062 / Loss 0.488825\n",
      "Epoch 138 / Batch (5/17) / Accuracy 0.7887 / Loss 0.509840\n",
      "Epoch 138 / Batch (6/17) / Accuracy 0.7725 / Loss 0.558475\n",
      "Epoch 138 / Batch (7/17) / Accuracy 0.7794 / Loss 0.522792\n",
      "Epoch 138 / Batch (8/17) / Accuracy 0.7906 / Loss 0.481951\n",
      "Epoch 138 / Batch (9/17) / Accuracy 0.8075 / Loss 0.491325\n",
      "Epoch 138 / Batch (10/17) / Accuracy 0.8219 / Loss 0.468881\n",
      "Epoch 138 / Batch (11/17) / Accuracy 0.8188 / Loss 0.455963\n",
      "Epoch 138 / Batch (12/17) / Accuracy 0.7769 / Loss 0.596940\n",
      "Epoch 138 / Batch (13/17) / Accuracy 0.8056 / Loss 0.487102\n",
      "Epoch 138 / Batch (14/17) / Accuracy 0.7969 / Loss 0.493649\n",
      "Epoch 138 / Batch (15/17) / Accuracy 0.7775 / Loss 0.530219\n",
      "Epoch 138 / Batch (16/17) / Accuracy 0.7994 / Loss 0.514297\n",
      "Epoch 138 / Batch (17/17) / Accuracy 0.8213 / Loss 0.479888\n",
      "Epoch 138 complete, 6.439574718475342 seconds elapsed\n",
      "\n",
      "Epoch 139 starting..\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 139 / Batch (1/17) / Accuracy 0.7650 / Loss 0.576198\n",
      "Epoch 139 / Batch (2/17) / Accuracy 0.8150 / Loss 0.467322\n",
      "Epoch 139 / Batch (3/17) / Accuracy 0.7825 / Loss 0.536174\n",
      "Epoch 139 / Batch (4/17) / Accuracy 0.7725 / Loss 0.544619\n",
      "Epoch 139 / Batch (5/17) / Accuracy 0.8012 / Loss 0.475433\n",
      "Epoch 139 / Batch (6/17) / Accuracy 0.7831 / Loss 0.559417\n",
      "Epoch 139 / Batch (7/17) / Accuracy 0.7588 / Loss 0.562707\n",
      "Epoch 139 / Batch (8/17) / Accuracy 0.7519 / Loss 0.583033\n",
      "Epoch 139 / Batch (9/17) / Accuracy 0.7956 / Loss 0.510746\n",
      "Epoch 139 / Batch (10/17) / Accuracy 0.8062 / Loss 0.471705\n",
      "Epoch 139 / Batch (11/17) / Accuracy 0.8112 / Loss 0.513732\n",
      "Epoch 139 / Batch (12/17) / Accuracy 0.7581 / Loss 0.579644\n",
      "Epoch 139 / Batch (13/17) / Accuracy 0.7856 / Loss 0.558516\n",
      "Epoch 139 / Batch (14/17) / Accuracy 0.7844 / Loss 0.563311\n",
      "Epoch 139 / Batch (15/17) / Accuracy 0.8081 / Loss 0.478688\n",
      "Epoch 139 / Batch (16/17) / Accuracy 0.8119 / Loss 0.467122\n",
      "Epoch 139 / Batch (17/17) / Accuracy 0.8181 / Loss 0.477404\n",
      "Epoch 139 complete, 6.52846360206604 seconds elapsed\n",
      "\n",
      "Epoch 140 starting..\n",
      "Epoch 140 / Batch (1/17) / Accuracy 0.8181 / Loss 0.476088\n",
      "Epoch 140 / Batch (2/17) / Accuracy 0.8325 / Loss 0.428901\n",
      "Epoch 140 / Batch (3/17) / Accuracy 0.8188 / Loss 0.472302\n",
      "Epoch 140 / Batch (4/17) / Accuracy 0.7769 / Loss 0.571250\n",
      "Epoch 140 / Batch (5/17) / Accuracy 0.7994 / Loss 0.494720\n",
      "Epoch 140 / Batch (6/17) / Accuracy 0.8056 / Loss 0.501705\n",
      "Epoch 140 / Batch (7/17) / Accuracy 0.7937 / Loss 0.529719\n",
      "Epoch 140 / Batch (8/17) / Accuracy 0.7925 / Loss 0.516871\n",
      "Epoch 140 / Batch (9/17) / Accuracy 0.8200 / Loss 0.469923\n",
      "Epoch 140 / Batch (10/17) / Accuracy 0.8344 / Loss 0.418553\n",
      "Epoch 140 / Batch (11/17) / Accuracy 0.7756 / Loss 0.546369\n",
      "Epoch 140 / Batch (12/17) / Accuracy 0.8044 / Loss 0.490673\n",
      "Epoch 140 / Batch (13/17) / Accuracy 0.8106 / Loss 0.484511\n",
      "Epoch 140 / Batch (14/17) / Accuracy 0.7713 / Loss 0.544512\n",
      "Epoch 140 / Batch (15/17) / Accuracy 0.7869 / Loss 0.521132\n",
      "Epoch 140 / Batch (16/17) / Accuracy 0.8037 / Loss 0.507132\n",
      "Epoch 140 / Batch (17/17) / Accuracy 0.7881 / Loss 0.540093\n",
      "Epoch 140 complete, 6.251406669616699 seconds elapsed\n",
      "\n",
      "Epoch 141 starting..\n",
      "Epoch 141 / Batch (1/17) / Accuracy 0.7837 / Loss 0.526294\n",
      "Epoch 141 / Batch (2/17) / Accuracy 0.7912 / Loss 0.506653\n",
      "Epoch 141 / Batch (3/17) / Accuracy 0.8044 / Loss 0.479962\n",
      "Epoch 141 / Batch (4/17) / Accuracy 0.7837 / Loss 0.541967\n",
      "Epoch 141 / Batch (5/17) / Accuracy 0.8025 / Loss 0.477334\n",
      "Epoch 141 / Batch (6/17) / Accuracy 0.7975 / Loss 0.498090\n",
      "Epoch 141 / Batch (7/17) / Accuracy 0.7981 / Loss 0.503251\n",
      "Epoch 141 / Batch (8/17) / Accuracy 0.8138 / Loss 0.478058\n",
      "Epoch 141 / Batch (9/17) / Accuracy 0.7619 / Loss 0.571720\n",
      "Epoch 141 / Batch (10/17) / Accuracy 0.8006 / Loss 0.506377\n",
      "Epoch 141 / Batch (11/17) / Accuracy 0.8050 / Loss 0.496786\n",
      "Epoch 141 / Batch (12/17) / Accuracy 0.8000 / Loss 0.511018\n",
      "Epoch 141 / Batch (13/17) / Accuracy 0.7850 / Loss 0.540671\n",
      "Epoch 141 / Batch (14/17) / Accuracy 0.8150 / Loss 0.491264\n",
      "Epoch 141 / Batch (15/17) / Accuracy 0.7937 / Loss 0.508591\n",
      "Epoch 141 / Batch (16/17) / Accuracy 0.7831 / Loss 0.513354\n",
      "Epoch 141 / Batch (17/17) / Accuracy 0.7844 / Loss 0.556507\n",
      "Epoch 141 complete, 6.565685510635376 seconds elapsed\n",
      "\n",
      "Epoch 142 starting..\n",
      "Epoch 142 / Batch (1/17) / Accuracy 0.7738 / Loss 0.548808\n",
      "Epoch 142 / Batch (2/17) / Accuracy 0.8119 / Loss 0.451155\n",
      "Epoch 142 / Batch (3/17) / Accuracy 0.7900 / Loss 0.520695\n",
      "Epoch 142 / Batch (4/17) / Accuracy 0.8062 / Loss 0.489107\n",
      "Epoch 142 / Batch (5/17) / Accuracy 0.7819 / Loss 0.538255\n",
      "Epoch 142 / Batch (6/17) / Accuracy 0.7725 / Loss 0.570487\n",
      "Epoch 142 / Batch (7/17) / Accuracy 0.8163 / Loss 0.481492\n",
      "Epoch 142 / Batch (8/17) / Accuracy 0.8313 / Loss 0.429351\n",
      "Epoch 142 / Batch (9/17) / Accuracy 0.8338 / Loss 0.435401\n",
      "Epoch 142 / Batch (10/17) / Accuracy 0.8062 / Loss 0.494837\n",
      "Epoch 142 / Batch (11/17) / Accuracy 0.7850 / Loss 0.531612\n",
      "Epoch 142 / Batch (12/17) / Accuracy 0.8144 / Loss 0.489250\n",
      "Epoch 142 / Batch (13/17) / Accuracy 0.7763 / Loss 0.541599\n",
      "Epoch 142 / Batch (14/17) / Accuracy 0.8313 / Loss 0.428050\n",
      "Epoch 142 / Batch (15/17) / Accuracy 0.7606 / Loss 0.579783\n",
      "Epoch 142 / Batch (16/17) / Accuracy 0.7806 / Loss 0.536123\n",
      "Epoch 142 / Batch (17/17) / Accuracy 0.8225 / Loss 0.475202\n",
      "Epoch 142 complete, 6.510633707046509 seconds elapsed\n",
      "\n",
      "Epoch 143 starting..\n",
      "Epoch 143 / Batch (1/17) / Accuracy 0.8244 / Loss 0.464342\n",
      "Epoch 143 / Batch (2/17) / Accuracy 0.8019 / Loss 0.487721\n",
      "Epoch 143 / Batch (3/17) / Accuracy 0.8000 / Loss 0.513132\n",
      "Epoch 143 / Batch (4/17) / Accuracy 0.8256 / Loss 0.456866\n",
      "Epoch 143 / Batch (5/17) / Accuracy 0.8225 / Loss 0.448793\n",
      "Epoch 143 / Batch (6/17) / Accuracy 0.7962 / Loss 0.544026\n",
      "Epoch 143 / Batch (7/17) / Accuracy 0.7987 / Loss 0.506415\n",
      "Epoch 143 / Batch (8/17) / Accuracy 0.8156 / Loss 0.467319\n",
      "Epoch 143 / Batch (9/17) / Accuracy 0.7513 / Loss 0.612606\n",
      "Epoch 143 / Batch (10/17) / Accuracy 0.8275 / Loss 0.452490\n",
      "Epoch 143 / Batch (11/17) / Accuracy 0.8313 / Loss 0.441306\n",
      "Epoch 143 / Batch (12/17) / Accuracy 0.8131 / Loss 0.495951\n",
      "Epoch 143 / Batch (13/17) / Accuracy 0.8019 / Loss 0.463534\n",
      "Epoch 143 / Batch (14/17) / Accuracy 0.7937 / Loss 0.512545\n",
      "Epoch 143 / Batch (15/17) / Accuracy 0.8194 / Loss 0.488573\n",
      "Epoch 143 / Batch (16/17) / Accuracy 0.7937 / Loss 0.528985\n",
      "Epoch 143 / Batch (17/17) / Accuracy 0.8056 / Loss 0.476293\n",
      "Epoch 143 complete, 6.086852312088013 seconds elapsed\n",
      "\n",
      "Epoch 144 starting..\n",
      "Epoch 144 / Batch (1/17) / Accuracy 0.7925 / Loss 0.519427\n",
      "Epoch 144 / Batch (2/17) / Accuracy 0.7812 / Loss 0.545565\n",
      "Epoch 144 / Batch (3/17) / Accuracy 0.7912 / Loss 0.522830\n",
      "Epoch 144 / Batch (4/17) / Accuracy 0.7906 / Loss 0.511308\n",
      "Epoch 144 / Batch (5/17) / Accuracy 0.8050 / Loss 0.478201\n",
      "Epoch 144 / Batch (6/17) / Accuracy 0.8037 / Loss 0.500932\n",
      "Epoch 144 / Batch (7/17) / Accuracy 0.8175 / Loss 0.459710\n",
      "Epoch 144 / Batch (8/17) / Accuracy 0.7987 / Loss 0.496138\n",
      "Epoch 144 / Batch (9/17) / Accuracy 0.8056 / Loss 0.476642\n",
      "Epoch 144 / Batch (10/17) / Accuracy 0.7738 / Loss 0.561001\n",
      "Epoch 144 / Batch (11/17) / Accuracy 0.8112 / Loss 0.495380\n",
      "Epoch 144 / Batch (12/17) / Accuracy 0.7694 / Loss 0.545432\n",
      "Epoch 144 / Batch (13/17) / Accuracy 0.7700 / Loss 0.557612\n",
      "Epoch 144 / Batch (14/17) / Accuracy 0.8050 / Loss 0.480432\n",
      "Epoch 144 / Batch (15/17) / Accuracy 0.7862 / Loss 0.522167\n",
      "Epoch 144 / Batch (16/17) / Accuracy 0.7956 / Loss 0.538278\n",
      "Epoch 144 / Batch (17/17) / Accuracy 0.7781 / Loss 0.515566\n",
      "Epoch 144 complete, 6.414565801620483 seconds elapsed\n",
      "\n",
      "Epoch 145 starting..\n",
      "Epoch 145 / Batch (1/17) / Accuracy 0.7675 / Loss 0.554853\n",
      "Epoch 145 / Batch (2/17) / Accuracy 0.8150 / Loss 0.465349\n",
      "Epoch 145 / Batch (3/17) / Accuracy 0.7781 / Loss 0.520808\n",
      "Epoch 145 / Batch (4/17) / Accuracy 0.7788 / Loss 0.543764\n",
      "Epoch 145 / Batch (5/17) / Accuracy 0.8238 / Loss 0.447691\n",
      "Epoch 145 / Batch (6/17) / Accuracy 0.7962 / Loss 0.507131\n",
      "Epoch 145 / Batch (7/17) / Accuracy 0.8344 / Loss 0.447062\n",
      "Epoch 145 / Batch (8/17) / Accuracy 0.7775 / Loss 0.550367\n",
      "Epoch 145 / Batch (9/17) / Accuracy 0.8106 / Loss 0.484196\n",
      "Epoch 145 / Batch (10/17) / Accuracy 0.7744 / Loss 0.550406\n",
      "Epoch 145 / Batch (11/17) / Accuracy 0.8037 / Loss 0.462088\n",
      "Epoch 145 / Batch (12/17) / Accuracy 0.8106 / Loss 0.471082\n",
      "Epoch 145 / Batch (13/17) / Accuracy 0.8069 / Loss 0.507578\n",
      "Epoch 145 / Batch (14/17) / Accuracy 0.7781 / Loss 0.519694\n",
      "Epoch 145 / Batch (15/17) / Accuracy 0.8062 / Loss 0.479489\n",
      "Epoch 145 / Batch (16/17) / Accuracy 0.8100 / Loss 0.487754\n",
      "Epoch 145 / Batch (17/17) / Accuracy 0.7850 / Loss 0.518857\n",
      "Epoch 145 complete, 5.795433282852173 seconds elapsed\n",
      "\n",
      "Epoch 146 starting..\n",
      "Epoch 146 / Batch (1/17) / Accuracy 0.7850 / Loss 0.542686\n",
      "Epoch 146 / Batch (2/17) / Accuracy 0.7794 / Loss 0.519407\n",
      "Epoch 146 / Batch (3/17) / Accuracy 0.7894 / Loss 0.503510\n",
      "Epoch 146 / Batch (4/17) / Accuracy 0.7887 / Loss 0.548770\n",
      "Epoch 146 / Batch (5/17) / Accuracy 0.8050 / Loss 0.488782\n",
      "Epoch 146 / Batch (6/17) / Accuracy 0.8131 / Loss 0.461347\n",
      "Epoch 146 / Batch (7/17) / Accuracy 0.7613 / Loss 0.577139\n",
      "Epoch 146 / Batch (8/17) / Accuracy 0.7875 / Loss 0.522779\n",
      "Epoch 146 / Batch (9/17) / Accuracy 0.7844 / Loss 0.536302\n",
      "Epoch 146 / Batch (10/17) / Accuracy 0.7869 / Loss 0.523925\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 146 / Batch (11/17) / Accuracy 0.7875 / Loss 0.524839\n",
      "Epoch 146 / Batch (12/17) / Accuracy 0.8400 / Loss 0.426751\n",
      "Epoch 146 / Batch (13/17) / Accuracy 0.8200 / Loss 0.473565\n",
      "Epoch 146 / Batch (14/17) / Accuracy 0.8056 / Loss 0.486095\n",
      "Epoch 146 / Batch (15/17) / Accuracy 0.8175 / Loss 0.480350\n",
      "Epoch 146 / Batch (16/17) / Accuracy 0.7994 / Loss 0.493269\n",
      "Epoch 146 / Batch (17/17) / Accuracy 0.8094 / Loss 0.495138\n",
      "Epoch 146 complete, 6.507414102554321 seconds elapsed\n",
      "\n",
      "Epoch 147 starting..\n",
      "Epoch 147 / Batch (1/17) / Accuracy 0.8100 / Loss 0.489375\n",
      "Epoch 147 / Batch (2/17) / Accuracy 0.7806 / Loss 0.531279\n",
      "Epoch 147 / Batch (3/17) / Accuracy 0.8062 / Loss 0.502179\n",
      "Epoch 147 / Batch (4/17) / Accuracy 0.8056 / Loss 0.486355\n",
      "Epoch 147 / Batch (5/17) / Accuracy 0.8250 / Loss 0.446523\n",
      "Epoch 147 / Batch (6/17) / Accuracy 0.7925 / Loss 0.493846\n",
      "Epoch 147 / Batch (7/17) / Accuracy 0.7481 / Loss 0.633353\n",
      "Epoch 147 / Batch (8/17) / Accuracy 0.7975 / Loss 0.508167\n",
      "Epoch 147 / Batch (9/17) / Accuracy 0.7800 / Loss 0.557317\n",
      "Epoch 147 / Batch (10/17) / Accuracy 0.7650 / Loss 0.571309\n",
      "Epoch 147 / Batch (11/17) / Accuracy 0.7825 / Loss 0.553682\n",
      "Epoch 147 / Batch (12/17) / Accuracy 0.8131 / Loss 0.507267\n",
      "Epoch 147 / Batch (13/17) / Accuracy 0.7806 / Loss 0.551956\n",
      "Epoch 147 / Batch (14/17) / Accuracy 0.8156 / Loss 0.450273\n",
      "Epoch 147 / Batch (15/17) / Accuracy 0.7900 / Loss 0.503151\n",
      "Epoch 147 / Batch (16/17) / Accuracy 0.8119 / Loss 0.489363\n",
      "Epoch 147 / Batch (17/17) / Accuracy 0.7937 / Loss 0.546253\n",
      "Epoch 147 complete, 6.308252811431885 seconds elapsed\n",
      "\n",
      "Epoch 148 starting..\n",
      "Epoch 148 / Batch (1/17) / Accuracy 0.7975 / Loss 0.518765\n",
      "Epoch 148 / Batch (2/17) / Accuracy 0.8062 / Loss 0.474657\n",
      "Epoch 148 / Batch (3/17) / Accuracy 0.7731 / Loss 0.543430\n",
      "Epoch 148 / Batch (4/17) / Accuracy 0.8037 / Loss 0.476669\n",
      "Epoch 148 / Batch (5/17) / Accuracy 0.8000 / Loss 0.498642\n",
      "Epoch 148 / Batch (6/17) / Accuracy 0.8069 / Loss 0.468966\n",
      "Epoch 148 / Batch (7/17) / Accuracy 0.8356 / Loss 0.423916\n",
      "Epoch 148 / Batch (8/17) / Accuracy 0.7981 / Loss 0.511280\n",
      "Epoch 148 / Batch (9/17) / Accuracy 0.7812 / Loss 0.538317\n",
      "Epoch 148 / Batch (10/17) / Accuracy 0.7594 / Loss 0.571272\n",
      "Epoch 148 / Batch (11/17) / Accuracy 0.8288 / Loss 0.460189\n",
      "Epoch 148 / Batch (12/17) / Accuracy 0.7825 / Loss 0.553541\n",
      "Epoch 148 / Batch (13/17) / Accuracy 0.8313 / Loss 0.451967\n",
      "Epoch 148 / Batch (14/17) / Accuracy 0.8044 / Loss 0.515934\n",
      "Epoch 148 / Batch (15/17) / Accuracy 0.8006 / Loss 0.500206\n",
      "Epoch 148 / Batch (16/17) / Accuracy 0.7887 / Loss 0.540685\n",
      "Epoch 148 / Batch (17/17) / Accuracy 0.8044 / Loss 0.478958\n",
      "Epoch 148 complete, 6.388781785964966 seconds elapsed\n",
      "\n",
      "Epoch 149 starting..\n",
      "Epoch 149 / Batch (1/17) / Accuracy 0.7856 / Loss 0.535479\n",
      "Epoch 149 / Batch (2/17) / Accuracy 0.8044 / Loss 0.479392\n",
      "Epoch 149 / Batch (3/17) / Accuracy 0.7713 / Loss 0.582292\n",
      "Epoch 149 / Batch (4/17) / Accuracy 0.8144 / Loss 0.459127\n",
      "Epoch 149 / Batch (5/17) / Accuracy 0.7331 / Loss 0.681787\n",
      "Epoch 149 / Batch (6/17) / Accuracy 0.8194 / Loss 0.457471\n",
      "Epoch 149 / Batch (7/17) / Accuracy 0.7894 / Loss 0.522347\n",
      "Epoch 149 / Batch (8/17) / Accuracy 0.7894 / Loss 0.513629\n",
      "Epoch 149 / Batch (9/17) / Accuracy 0.8250 / Loss 0.454710\n",
      "Epoch 149 / Batch (10/17) / Accuracy 0.7850 / Loss 0.547600\n",
      "Epoch 149 / Batch (11/17) / Accuracy 0.7744 / Loss 0.538218\n",
      "Epoch 149 / Batch (12/17) / Accuracy 0.7887 / Loss 0.525698\n",
      "Epoch 149 / Batch (13/17) / Accuracy 0.7837 / Loss 0.522957\n",
      "Epoch 149 / Batch (14/17) / Accuracy 0.8044 / Loss 0.492185\n",
      "Epoch 149 / Batch (15/17) / Accuracy 0.7969 / Loss 0.513666\n",
      "Epoch 149 / Batch (16/17) / Accuracy 0.8219 / Loss 0.456916\n",
      "Epoch 149 / Batch (17/17) / Accuracy 0.7950 / Loss 0.531154\n",
      "Epoch 149 complete, 6.4897027015686035 seconds elapsed\n",
      "\n",
      "Epoch 150 starting..\n",
      "Epoch 150 / Batch (1/17) / Accuracy 0.7919 / Loss 0.480305\n",
      "Epoch 150 / Batch (2/17) / Accuracy 0.7750 / Loss 0.539182\n",
      "Epoch 150 / Batch (3/17) / Accuracy 0.7937 / Loss 0.520064\n",
      "Epoch 150 / Batch (4/17) / Accuracy 0.8056 / Loss 0.510746\n",
      "Epoch 150 / Batch (5/17) / Accuracy 0.7738 / Loss 0.531022\n",
      "Epoch 150 / Batch (6/17) / Accuracy 0.8313 / Loss 0.421547\n",
      "Epoch 150 / Batch (7/17) / Accuracy 0.8000 / Loss 0.522733\n",
      "Epoch 150 / Batch (8/17) / Accuracy 0.7481 / Loss 0.641174\n",
      "Epoch 150 / Batch (9/17) / Accuracy 0.7994 / Loss 0.480081\n",
      "Epoch 150 / Batch (10/17) / Accuracy 0.7925 / Loss 0.520118\n",
      "Epoch 150 / Batch (11/17) / Accuracy 0.8163 / Loss 0.447503\n",
      "Epoch 150 / Batch (12/17) / Accuracy 0.8106 / Loss 0.487673\n",
      "Epoch 150 / Batch (13/17) / Accuracy 0.7725 / Loss 0.516652\n",
      "Epoch 150 / Batch (14/17) / Accuracy 0.8106 / Loss 0.498276\n",
      "Epoch 150 / Batch (15/17) / Accuracy 0.8050 / Loss 0.470407\n",
      "Epoch 150 / Batch (16/17) / Accuracy 0.7887 / Loss 0.529552\n",
      "Epoch 150 / Batch (17/17) / Accuracy 0.8138 / Loss 0.469593\n",
      "Epoch 150 complete, 6.6641340255737305 seconds elapsed\n",
      "\n",
      "Epoch 151 starting..\n",
      "Epoch 151 / Batch (1/17) / Accuracy 0.8150 / Loss 0.458848\n",
      "Epoch 151 / Batch (2/17) / Accuracy 0.7887 / Loss 0.491268\n",
      "Epoch 151 / Batch (3/17) / Accuracy 0.7919 / Loss 0.520657\n",
      "Epoch 151 / Batch (4/17) / Accuracy 0.7656 / Loss 0.561157\n",
      "Epoch 151 / Batch (5/17) / Accuracy 0.8213 / Loss 0.458977\n",
      "Epoch 151 / Batch (6/17) / Accuracy 0.8213 / Loss 0.458678\n",
      "Epoch 151 / Batch (7/17) / Accuracy 0.8106 / Loss 0.479938\n",
      "Epoch 151 / Batch (8/17) / Accuracy 0.8294 / Loss 0.446952\n",
      "Epoch 151 / Batch (9/17) / Accuracy 0.7644 / Loss 0.555134\n",
      "Epoch 151 / Batch (10/17) / Accuracy 0.8413 / Loss 0.432722\n",
      "Epoch 151 / Batch (11/17) / Accuracy 0.8094 / Loss 0.455343\n",
      "Epoch 151 / Batch (12/17) / Accuracy 0.7950 / Loss 0.491251\n",
      "Epoch 151 / Batch (13/17) / Accuracy 0.8037 / Loss 0.518872\n",
      "Epoch 151 / Batch (14/17) / Accuracy 0.7706 / Loss 0.536002\n",
      "Epoch 151 / Batch (15/17) / Accuracy 0.7962 / Loss 0.504229\n",
      "Epoch 151 / Batch (16/17) / Accuracy 0.7775 / Loss 0.544183\n",
      "Epoch 151 / Batch (17/17) / Accuracy 0.7800 / Loss 0.548798\n",
      "Epoch 151 complete, 6.283928632736206 seconds elapsed\n",
      "\n",
      "Epoch 152 starting..\n",
      "Epoch 152 / Batch (1/17) / Accuracy 0.7937 / Loss 0.521341\n",
      "Epoch 152 / Batch (2/17) / Accuracy 0.7987 / Loss 0.516556\n",
      "Epoch 152 / Batch (3/17) / Accuracy 0.8106 / Loss 0.482271\n",
      "Epoch 152 / Batch (4/17) / Accuracy 0.8044 / Loss 0.515471\n",
      "Epoch 152 / Batch (5/17) / Accuracy 0.8244 / Loss 0.457528\n",
      "Epoch 152 / Batch (6/17) / Accuracy 0.7738 / Loss 0.595469\n",
      "Epoch 152 / Batch (7/17) / Accuracy 0.7825 / Loss 0.501576\n",
      "Epoch 152 / Batch (8/17) / Accuracy 0.8163 / Loss 0.465302\n",
      "Epoch 152 / Batch (9/17) / Accuracy 0.7956 / Loss 0.495766\n",
      "Epoch 152 / Batch (10/17) / Accuracy 0.7669 / Loss 0.566100\n",
      "Epoch 152 / Batch (11/17) / Accuracy 0.7869 / Loss 0.552584\n",
      "Epoch 152 / Batch (12/17) / Accuracy 0.8056 / Loss 0.518502\n",
      "Epoch 152 / Batch (13/17) / Accuracy 0.7525 / Loss 0.609071\n",
      "Epoch 152 / Batch (14/17) / Accuracy 0.7875 / Loss 0.533928\n",
      "Epoch 152 / Batch (15/17) / Accuracy 0.7881 / Loss 0.515980\n",
      "Epoch 152 / Batch (16/17) / Accuracy 0.7625 / Loss 0.564369\n",
      "Epoch 152 / Batch (17/17) / Accuracy 0.8188 / Loss 0.457864\n",
      "Epoch 152 complete, 6.2400524616241455 seconds elapsed\n",
      "\n",
      "Epoch 153 starting..\n",
      "Epoch 153 / Batch (1/17) / Accuracy 0.7887 / Loss 0.537160\n",
      "Epoch 153 / Batch (2/17) / Accuracy 0.8225 / Loss 0.451034\n",
      "Epoch 153 / Batch (3/17) / Accuracy 0.8019 / Loss 0.487315\n",
      "Epoch 153 / Batch (4/17) / Accuracy 0.8025 / Loss 0.482191\n",
      "Epoch 153 / Batch (5/17) / Accuracy 0.7781 / Loss 0.561577\n",
      "Epoch 153 / Batch (6/17) / Accuracy 0.7806 / Loss 0.555321\n",
      "Epoch 153 / Batch (7/17) / Accuracy 0.7906 / Loss 0.518497\n",
      "Epoch 153 / Batch (8/17) / Accuracy 0.8269 / Loss 0.445154\n",
      "Epoch 153 / Batch (9/17) / Accuracy 0.8219 / Loss 0.489656\n",
      "Epoch 153 / Batch (10/17) / Accuracy 0.8194 / Loss 0.469816\n",
      "Epoch 153 / Batch (11/17) / Accuracy 0.8156 / Loss 0.461920\n",
      "Epoch 153 / Batch (12/17) / Accuracy 0.7769 / Loss 0.553143\n",
      "Epoch 153 / Batch (13/17) / Accuracy 0.8006 / Loss 0.490346\n",
      "Epoch 153 / Batch (14/17) / Accuracy 0.8194 / Loss 0.479348\n",
      "Epoch 153 / Batch (15/17) / Accuracy 0.7800 / Loss 0.531036\n",
      "Epoch 153 / Batch (16/17) / Accuracy 0.8231 / Loss 0.446200\n",
      "Epoch 153 / Batch (17/17) / Accuracy 0.8213 / Loss 0.445401\n",
      "Epoch 153 complete, 6.8920509815216064 seconds elapsed\n",
      "\n",
      "Epoch 154 starting..\n",
      "Epoch 154 / Batch (1/17) / Accuracy 0.8100 / Loss 0.509466\n",
      "Epoch 154 / Batch (2/17) / Accuracy 0.8169 / Loss 0.461028\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 154 / Batch (3/17) / Accuracy 0.8044 / Loss 0.509870\n",
      "Epoch 154 / Batch (4/17) / Accuracy 0.8050 / Loss 0.506974\n",
      "Epoch 154 / Batch (5/17) / Accuracy 0.7981 / Loss 0.526750\n",
      "Epoch 154 / Batch (6/17) / Accuracy 0.8069 / Loss 0.510451\n",
      "Epoch 154 / Batch (7/17) / Accuracy 0.7906 / Loss 0.514003\n",
      "Epoch 154 / Batch (8/17) / Accuracy 0.7644 / Loss 0.590749\n",
      "Epoch 154 / Batch (9/17) / Accuracy 0.8325 / Loss 0.439403\n",
      "Epoch 154 / Batch (10/17) / Accuracy 0.8281 / Loss 0.418921\n",
      "Epoch 154 / Batch (11/17) / Accuracy 0.8256 / Loss 0.451086\n",
      "Epoch 154 / Batch (12/17) / Accuracy 0.7700 / Loss 0.556493\n",
      "Epoch 154 / Batch (13/17) / Accuracy 0.7869 / Loss 0.545409\n",
      "Epoch 154 / Batch (14/17) / Accuracy 0.7588 / Loss 0.564792\n",
      "Epoch 154 / Batch (15/17) / Accuracy 0.7475 / Loss 0.583851\n",
      "Epoch 154 / Batch (16/17) / Accuracy 0.7962 / Loss 0.509406\n",
      "Epoch 154 / Batch (17/17) / Accuracy 0.7906 / Loss 0.510690\n",
      "Epoch 154 complete, 6.176886558532715 seconds elapsed\n",
      "\n",
      "Epoch 155 starting..\n",
      "Epoch 155 / Batch (1/17) / Accuracy 0.7594 / Loss 0.572627\n",
      "Epoch 155 / Batch (2/17) / Accuracy 0.7431 / Loss 0.616226\n",
      "Epoch 155 / Batch (3/17) / Accuracy 0.7350 / Loss 0.648545\n",
      "Epoch 155 / Batch (4/17) / Accuracy 0.7619 / Loss 0.583975\n",
      "Epoch 155 / Batch (5/17) / Accuracy 0.7837 / Loss 0.548864\n",
      "Epoch 155 / Batch (6/17) / Accuracy 0.7644 / Loss 0.593968\n",
      "Epoch 155 / Batch (7/17) / Accuracy 0.8119 / Loss 0.483253\n",
      "Epoch 155 / Batch (8/17) / Accuracy 0.8006 / Loss 0.524845\n",
      "Epoch 155 / Batch (9/17) / Accuracy 0.7844 / Loss 0.517653\n",
      "Epoch 155 / Batch (10/17) / Accuracy 0.7819 / Loss 0.522390\n",
      "Epoch 155 / Batch (11/17) / Accuracy 0.7844 / Loss 0.532865\n",
      "Epoch 155 / Batch (12/17) / Accuracy 0.8025 / Loss 0.459873\n",
      "Epoch 155 / Batch (13/17) / Accuracy 0.7819 / Loss 0.519148\n",
      "Epoch 155 / Batch (14/17) / Accuracy 0.7950 / Loss 0.482057\n",
      "Epoch 155 / Batch (15/17) / Accuracy 0.7912 / Loss 0.504150\n",
      "Epoch 155 / Batch (16/17) / Accuracy 0.8169 / Loss 0.469743\n",
      "Epoch 155 / Batch (17/17) / Accuracy 0.8175 / Loss 0.479232\n",
      "Epoch 155 complete, 6.797304630279541 seconds elapsed\n",
      "\n",
      "Epoch 156 starting..\n",
      "Epoch 156 / Batch (1/17) / Accuracy 0.7919 / Loss 0.512838\n",
      "Epoch 156 / Batch (2/17) / Accuracy 0.7862 / Loss 0.542102\n",
      "Epoch 156 / Batch (3/17) / Accuracy 0.7613 / Loss 0.562329\n",
      "Epoch 156 / Batch (4/17) / Accuracy 0.7775 / Loss 0.555889\n",
      "Epoch 156 / Batch (5/17) / Accuracy 0.8275 / Loss 0.449048\n",
      "Epoch 156 / Batch (6/17) / Accuracy 0.7962 / Loss 0.511259\n",
      "Epoch 156 / Batch (7/17) / Accuracy 0.7650 / Loss 0.562764\n",
      "Epoch 156 / Batch (8/17) / Accuracy 0.8263 / Loss 0.428549\n",
      "Epoch 156 / Batch (9/17) / Accuracy 0.8056 / Loss 0.489863\n",
      "Epoch 156 / Batch (10/17) / Accuracy 0.7800 / Loss 0.520806\n",
      "Epoch 156 / Batch (11/17) / Accuracy 0.7856 / Loss 0.533794\n",
      "Epoch 156 / Batch (12/17) / Accuracy 0.8163 / Loss 0.467026\n",
      "Epoch 156 / Batch (13/17) / Accuracy 0.7937 / Loss 0.519565\n",
      "Epoch 156 / Batch (14/17) / Accuracy 0.8075 / Loss 0.487956\n",
      "Epoch 156 / Batch (15/17) / Accuracy 0.7750 / Loss 0.528446\n",
      "Epoch 156 / Batch (16/17) / Accuracy 0.8006 / Loss 0.510307\n",
      "Epoch 156 / Batch (17/17) / Accuracy 0.7994 / Loss 0.510410\n",
      "Epoch 156 complete, 6.266157627105713 seconds elapsed\n",
      "\n",
      "Epoch 157 starting..\n",
      "Epoch 157 / Batch (1/17) / Accuracy 0.8069 / Loss 0.477207\n",
      "Epoch 157 / Batch (2/17) / Accuracy 0.8031 / Loss 0.487552\n",
      "Epoch 157 / Batch (3/17) / Accuracy 0.8344 / Loss 0.434734\n",
      "Epoch 157 / Batch (4/17) / Accuracy 0.7956 / Loss 0.517975\n",
      "Epoch 157 / Batch (5/17) / Accuracy 0.8231 / Loss 0.465825\n",
      "Epoch 157 / Batch (6/17) / Accuracy 0.8338 / Loss 0.436041\n",
      "Epoch 157 / Batch (7/17) / Accuracy 0.7900 / Loss 0.508398\n",
      "Epoch 157 / Batch (8/17) / Accuracy 0.7981 / Loss 0.488214\n",
      "Epoch 157 / Batch (9/17) / Accuracy 0.8213 / Loss 0.451970\n",
      "Epoch 157 / Batch (10/17) / Accuracy 0.7869 / Loss 0.496504\n",
      "Epoch 157 / Batch (11/17) / Accuracy 0.7962 / Loss 0.490215\n",
      "Epoch 157 / Batch (12/17) / Accuracy 0.8281 / Loss 0.426412\n",
      "Epoch 157 / Batch (13/17) / Accuracy 0.7862 / Loss 0.522043\n",
      "Epoch 157 / Batch (14/17) / Accuracy 0.8025 / Loss 0.476396\n",
      "Epoch 157 / Batch (15/17) / Accuracy 0.8119 / Loss 0.487172\n",
      "Epoch 157 / Batch (16/17) / Accuracy 0.7763 / Loss 0.539683\n",
      "Epoch 157 / Batch (17/17) / Accuracy 0.8025 / Loss 0.516524\n",
      "Epoch 157 complete, 7.5006468296051025 seconds elapsed\n",
      "\n",
      "Epoch 158 starting..\n",
      "Epoch 158 / Batch (1/17) / Accuracy 0.7994 / Loss 0.496428\n",
      "Epoch 158 / Batch (2/17) / Accuracy 0.7856 / Loss 0.527363\n",
      "Epoch 158 / Batch (3/17) / Accuracy 0.8263 / Loss 0.455752\n",
      "Epoch 158 / Batch (4/17) / Accuracy 0.7713 / Loss 0.581925\n",
      "Epoch 158 / Batch (5/17) / Accuracy 0.7719 / Loss 0.565328\n",
      "Epoch 158 / Batch (6/17) / Accuracy 0.8225 / Loss 0.461061\n",
      "Epoch 158 / Batch (7/17) / Accuracy 0.8294 / Loss 0.457198\n",
      "Epoch 158 / Batch (8/17) / Accuracy 0.8031 / Loss 0.495664\n",
      "Epoch 158 / Batch (9/17) / Accuracy 0.8450 / Loss 0.420974\n",
      "Epoch 158 / Batch (10/17) / Accuracy 0.7781 / Loss 0.529367\n",
      "Epoch 158 / Batch (11/17) / Accuracy 0.7794 / Loss 0.538054\n",
      "Epoch 158 / Batch (12/17) / Accuracy 0.7962 / Loss 0.487357\n",
      "Epoch 158 / Batch (13/17) / Accuracy 0.7962 / Loss 0.480727\n",
      "Epoch 158 / Batch (14/17) / Accuracy 0.7881 / Loss 0.522147\n",
      "Epoch 158 / Batch (15/17) / Accuracy 0.7956 / Loss 0.484644\n",
      "Epoch 158 / Batch (16/17) / Accuracy 0.7731 / Loss 0.539148\n",
      "Epoch 158 / Batch (17/17) / Accuracy 0.8131 / Loss 0.472339\n",
      "Epoch 158 complete, 7.102458477020264 seconds elapsed\n",
      "\n",
      "Epoch 159 starting..\n",
      "Epoch 159 / Batch (1/17) / Accuracy 0.8231 / Loss 0.471973\n",
      "Epoch 159 / Batch (2/17) / Accuracy 0.7962 / Loss 0.516538\n",
      "Epoch 159 / Batch (3/17) / Accuracy 0.7969 / Loss 0.511179\n",
      "Epoch 159 / Batch (4/17) / Accuracy 0.8087 / Loss 0.507217\n",
      "Epoch 159 / Batch (5/17) / Accuracy 0.7962 / Loss 0.523576\n",
      "Epoch 159 / Batch (6/17) / Accuracy 0.8144 / Loss 0.456690\n",
      "Epoch 159 / Batch (7/17) / Accuracy 0.8213 / Loss 0.438724\n",
      "Epoch 159 / Batch (8/17) / Accuracy 0.7931 / Loss 0.522184\n",
      "Epoch 159 / Batch (9/17) / Accuracy 0.8037 / Loss 0.517039\n",
      "Epoch 159 / Batch (10/17) / Accuracy 0.7756 / Loss 0.579702\n",
      "Epoch 159 / Batch (11/17) / Accuracy 0.7681 / Loss 0.534944\n",
      "Epoch 159 / Batch (12/17) / Accuracy 0.8019 / Loss 0.542797\n",
      "Epoch 159 / Batch (13/17) / Accuracy 0.7994 / Loss 0.489146\n",
      "Epoch 159 / Batch (14/17) / Accuracy 0.8112 / Loss 0.472370\n",
      "Epoch 159 / Batch (15/17) / Accuracy 0.7987 / Loss 0.530687\n",
      "Epoch 159 / Batch (16/17) / Accuracy 0.8156 / Loss 0.452511\n",
      "Epoch 159 / Batch (17/17) / Accuracy 0.7475 / Loss 0.582954\n",
      "Epoch 159 complete, 6.669717073440552 seconds elapsed\n",
      "\n",
      "Epoch 160 starting..\n",
      "Epoch 160 / Batch (1/17) / Accuracy 0.7894 / Loss 0.519469\n",
      "Epoch 160 / Batch (2/17) / Accuracy 0.7675 / Loss 0.548254\n",
      "Epoch 160 / Batch (3/17) / Accuracy 0.7944 / Loss 0.517782\n",
      "Epoch 160 / Batch (4/17) / Accuracy 0.8012 / Loss 0.520536\n",
      "Epoch 160 / Batch (5/17) / Accuracy 0.8375 / Loss 0.440428\n",
      "Epoch 160 / Batch (6/17) / Accuracy 0.8000 / Loss 0.500427\n",
      "Epoch 160 / Batch (7/17) / Accuracy 0.7694 / Loss 0.531214\n",
      "Epoch 160 / Batch (8/17) / Accuracy 0.8225 / Loss 0.437716\n",
      "Epoch 160 / Batch (9/17) / Accuracy 0.8275 / Loss 0.439171\n",
      "Epoch 160 / Batch (10/17) / Accuracy 0.8050 / Loss 0.480760\n",
      "Epoch 160 / Batch (11/17) / Accuracy 0.7869 / Loss 0.552054\n",
      "Epoch 160 / Batch (12/17) / Accuracy 0.8131 / Loss 0.482283\n",
      "Epoch 160 / Batch (13/17) / Accuracy 0.8300 / Loss 0.426514\n",
      "Epoch 160 / Batch (14/17) / Accuracy 0.7869 / Loss 0.519255\n",
      "Epoch 160 / Batch (15/17) / Accuracy 0.7987 / Loss 0.512957\n",
      "Epoch 160 / Batch (16/17) / Accuracy 0.8244 / Loss 0.469327\n",
      "Epoch 160 / Batch (17/17) / Accuracy 0.7844 / Loss 0.530564\n",
      "Epoch 160 complete, 6.206495046615601 seconds elapsed\n",
      "\n",
      "Epoch 161 starting..\n",
      "Epoch 161 / Batch (1/17) / Accuracy 0.8225 / Loss 0.446212\n",
      "Epoch 161 / Batch (2/17) / Accuracy 0.8069 / Loss 0.495109\n",
      "Epoch 161 / Batch (3/17) / Accuracy 0.7975 / Loss 0.492853\n",
      "Epoch 161 / Batch (4/17) / Accuracy 0.8381 / Loss 0.430649\n",
      "Epoch 161 / Batch (5/17) / Accuracy 0.8075 / Loss 0.492954\n",
      "Epoch 161 / Batch (6/17) / Accuracy 0.8325 / Loss 0.417955\n",
      "Epoch 161 / Batch (7/17) / Accuracy 0.7669 / Loss 0.561044\n",
      "Epoch 161 / Batch (8/17) / Accuracy 0.7912 / Loss 0.507373\n",
      "Epoch 161 / Batch (9/17) / Accuracy 0.8175 / Loss 0.454657\n",
      "Epoch 161 / Batch (10/17) / Accuracy 0.8119 / Loss 0.482953\n",
      "Epoch 161 / Batch (11/17) / Accuracy 0.8031 / Loss 0.494280\n",
      "Epoch 161 / Batch (12/17) / Accuracy 0.7981 / Loss 0.481851\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 161 / Batch (13/17) / Accuracy 0.7937 / Loss 0.498249\n",
      "Epoch 161 / Batch (14/17) / Accuracy 0.7837 / Loss 0.540570\n",
      "Epoch 161 / Batch (15/17) / Accuracy 0.7950 / Loss 0.505844\n",
      "Epoch 161 / Batch (16/17) / Accuracy 0.8050 / Loss 0.477822\n",
      "Epoch 161 / Batch (17/17) / Accuracy 0.8431 / Loss 0.424857\n",
      "Epoch 161 complete, 6.563315153121948 seconds elapsed\n",
      "\n",
      "Epoch 162 starting..\n",
      "Epoch 162 / Batch (1/17) / Accuracy 0.8144 / Loss 0.463862\n",
      "Epoch 162 / Batch (2/17) / Accuracy 0.7862 / Loss 0.529594\n",
      "Epoch 162 / Batch (3/17) / Accuracy 0.8313 / Loss 0.408543\n",
      "Epoch 162 / Batch (4/17) / Accuracy 0.7862 / Loss 0.516080\n",
      "Epoch 162 / Batch (5/17) / Accuracy 0.7750 / Loss 0.540589\n",
      "Epoch 162 / Batch (6/17) / Accuracy 0.7844 / Loss 0.534978\n",
      "Epoch 162 / Batch (7/17) / Accuracy 0.8156 / Loss 0.463576\n",
      "Epoch 162 / Batch (8/17) / Accuracy 0.7925 / Loss 0.522569\n",
      "Epoch 162 / Batch (9/17) / Accuracy 0.8256 / Loss 0.444404\n",
      "Epoch 162 / Batch (10/17) / Accuracy 0.8037 / Loss 0.457596\n",
      "Epoch 162 / Batch (11/17) / Accuracy 0.8138 / Loss 0.458404\n",
      "Epoch 162 / Batch (12/17) / Accuracy 0.8112 / Loss 0.488763\n",
      "Epoch 162 / Batch (13/17) / Accuracy 0.7831 / Loss 0.537345\n",
      "Epoch 162 / Batch (14/17) / Accuracy 0.7881 / Loss 0.540460\n",
      "Epoch 162 / Batch (15/17) / Accuracy 0.7981 / Loss 0.531654\n",
      "Epoch 162 / Batch (16/17) / Accuracy 0.8119 / Loss 0.463472\n",
      "Epoch 162 / Batch (17/17) / Accuracy 0.8100 / Loss 0.478441\n",
      "Epoch 162 complete, 6.531036615371704 seconds elapsed\n",
      "\n",
      "Epoch 163 starting..\n",
      "Epoch 163 / Batch (1/17) / Accuracy 0.7950 / Loss 0.512914\n",
      "Epoch 163 / Batch (2/17) / Accuracy 0.8125 / Loss 0.458742\n",
      "Epoch 163 / Batch (3/17) / Accuracy 0.8306 / Loss 0.428518\n",
      "Epoch 163 / Batch (4/17) / Accuracy 0.8100 / Loss 0.462784\n",
      "Epoch 163 / Batch (5/17) / Accuracy 0.8175 / Loss 0.478312\n",
      "Epoch 163 / Batch (6/17) / Accuracy 0.8031 / Loss 0.487434\n",
      "Epoch 163 / Batch (7/17) / Accuracy 0.8119 / Loss 0.487879\n",
      "Epoch 163 / Batch (8/17) / Accuracy 0.7862 / Loss 0.522463\n",
      "Epoch 163 / Batch (9/17) / Accuracy 0.8000 / Loss 0.491273\n",
      "Epoch 163 / Batch (10/17) / Accuracy 0.8000 / Loss 0.489774\n",
      "Epoch 163 / Batch (11/17) / Accuracy 0.8213 / Loss 0.472226\n",
      "Epoch 163 / Batch (12/17) / Accuracy 0.8062 / Loss 0.513865\n",
      "Epoch 163 / Batch (13/17) / Accuracy 0.8169 / Loss 0.456015\n",
      "Epoch 163 / Batch (14/17) / Accuracy 0.7869 / Loss 0.526061\n",
      "Epoch 163 / Batch (15/17) / Accuracy 0.8269 / Loss 0.426571\n",
      "Epoch 163 / Batch (16/17) / Accuracy 0.8331 / Loss 0.451910\n",
      "Epoch 163 / Batch (17/17) / Accuracy 0.8369 / Loss 0.437085\n",
      "Epoch 163 complete, 5.9725120067596436 seconds elapsed\n",
      "\n",
      "Epoch 164 starting..\n",
      "Epoch 164 / Batch (1/17) / Accuracy 0.8275 / Loss 0.418247\n",
      "Epoch 164 / Batch (2/17) / Accuracy 0.7881 / Loss 0.555264\n",
      "Epoch 164 / Batch (3/17) / Accuracy 0.8263 / Loss 0.440090\n",
      "Epoch 164 / Batch (4/17) / Accuracy 0.8388 / Loss 0.420463\n",
      "Epoch 164 / Batch (5/17) / Accuracy 0.8150 / Loss 0.487434\n",
      "Epoch 164 / Batch (6/17) / Accuracy 0.8275 / Loss 0.464291\n",
      "Epoch 164 / Batch (7/17) / Accuracy 0.8256 / Loss 0.443987\n",
      "Epoch 164 / Batch (8/17) / Accuracy 0.8344 / Loss 0.412360\n",
      "Epoch 164 / Batch (9/17) / Accuracy 0.7675 / Loss 0.567856\n",
      "Epoch 164 / Batch (10/17) / Accuracy 0.7919 / Loss 0.537398\n",
      "Epoch 164 / Batch (11/17) / Accuracy 0.7738 / Loss 0.561908\n",
      "Epoch 164 / Batch (12/17) / Accuracy 0.7819 / Loss 0.516358\n",
      "Epoch 164 / Batch (13/17) / Accuracy 0.8056 / Loss 0.520082\n",
      "Epoch 164 / Batch (14/17) / Accuracy 0.8025 / Loss 0.501532\n",
      "Epoch 164 / Batch (15/17) / Accuracy 0.8169 / Loss 0.497410\n",
      "Epoch 164 / Batch (16/17) / Accuracy 0.8112 / Loss 0.467918\n",
      "Epoch 164 / Batch (17/17) / Accuracy 0.8456 / Loss 0.400608\n",
      "Epoch 164 complete, 6.5467071533203125 seconds elapsed\n",
      "\n",
      "Epoch 165 starting..\n",
      "Epoch 165 / Batch (1/17) / Accuracy 0.7850 / Loss 0.557695\n",
      "Epoch 165 / Batch (2/17) / Accuracy 0.7812 / Loss 0.557788\n",
      "Epoch 165 / Batch (3/17) / Accuracy 0.8106 / Loss 0.469139\n",
      "Epoch 165 / Batch (4/17) / Accuracy 0.8194 / Loss 0.457995\n",
      "Epoch 165 / Batch (5/17) / Accuracy 0.7781 / Loss 0.542182\n",
      "Epoch 165 / Batch (6/17) / Accuracy 0.7769 / Loss 0.537772\n",
      "Epoch 165 / Batch (7/17) / Accuracy 0.7875 / Loss 0.512636\n",
      "Epoch 165 / Batch (8/17) / Accuracy 0.8481 / Loss 0.385961\n",
      "Epoch 165 / Batch (9/17) / Accuracy 0.8075 / Loss 0.492191\n",
      "Epoch 165 / Batch (10/17) / Accuracy 0.8087 / Loss 0.480022\n",
      "Epoch 165 / Batch (11/17) / Accuracy 0.8219 / Loss 0.448530\n",
      "Epoch 165 / Batch (12/17) / Accuracy 0.8338 / Loss 0.448544\n",
      "Epoch 165 / Batch (13/17) / Accuracy 0.8075 / Loss 0.512508\n",
      "Epoch 165 / Batch (14/17) / Accuracy 0.8181 / Loss 0.496653\n",
      "Epoch 165 / Batch (15/17) / Accuracy 0.8012 / Loss 0.503682\n",
      "Epoch 165 / Batch (16/17) / Accuracy 0.8163 / Loss 0.475257\n",
      "Epoch 165 / Batch (17/17) / Accuracy 0.8306 / Loss 0.459740\n",
      "Epoch 165 complete, 6.696371078491211 seconds elapsed\n",
      "\n",
      "Epoch 166 starting..\n",
      "Epoch 166 / Batch (1/17) / Accuracy 0.8000 / Loss 0.487802\n",
      "Epoch 166 / Batch (2/17) / Accuracy 0.8263 / Loss 0.443501\n",
      "Epoch 166 / Batch (3/17) / Accuracy 0.7744 / Loss 0.541024\n",
      "Epoch 166 / Batch (4/17) / Accuracy 0.8294 / Loss 0.439789\n",
      "Epoch 166 / Batch (5/17) / Accuracy 0.8150 / Loss 0.476141\n",
      "Epoch 166 / Batch (6/17) / Accuracy 0.8306 / Loss 0.436010\n",
      "Epoch 166 / Batch (7/17) / Accuracy 0.8069 / Loss 0.477248\n",
      "Epoch 166 / Batch (8/17) / Accuracy 0.7944 / Loss 0.507029\n",
      "Epoch 166 / Batch (9/17) / Accuracy 0.7969 / Loss 0.511953\n",
      "Epoch 166 / Batch (10/17) / Accuracy 0.7856 / Loss 0.554614\n",
      "Epoch 166 / Batch (11/17) / Accuracy 0.7975 / Loss 0.524861\n",
      "Epoch 166 / Batch (12/17) / Accuracy 0.7906 / Loss 0.518584\n",
      "Epoch 166 / Batch (13/17) / Accuracy 0.7906 / Loss 0.517944\n",
      "Epoch 166 / Batch (14/17) / Accuracy 0.7944 / Loss 0.524150\n",
      "Epoch 166 / Batch (15/17) / Accuracy 0.8156 / Loss 0.493734\n",
      "Epoch 166 / Batch (16/17) / Accuracy 0.8181 / Loss 0.429516\n",
      "Epoch 166 / Batch (17/17) / Accuracy 0.8062 / Loss 0.500407\n",
      "Epoch 166 complete, 6.3634819984436035 seconds elapsed\n",
      "\n",
      "Epoch 167 starting..\n",
      "Epoch 167 / Batch (1/17) / Accuracy 0.7912 / Loss 0.513032\n",
      "Epoch 167 / Batch (2/17) / Accuracy 0.7975 / Loss 0.490399\n",
      "Epoch 167 / Batch (3/17) / Accuracy 0.7844 / Loss 0.506375\n",
      "Epoch 167 / Batch (4/17) / Accuracy 0.8269 / Loss 0.441789\n",
      "Epoch 167 / Batch (5/17) / Accuracy 0.7819 / Loss 0.536576\n",
      "Epoch 167 / Batch (6/17) / Accuracy 0.8231 / Loss 0.491967\n",
      "Epoch 167 / Batch (7/17) / Accuracy 0.8100 / Loss 0.482673\n",
      "Epoch 167 / Batch (8/17) / Accuracy 0.7950 / Loss 0.509003\n",
      "Epoch 167 / Batch (9/17) / Accuracy 0.8169 / Loss 0.465118\n",
      "Epoch 167 / Batch (10/17) / Accuracy 0.7713 / Loss 0.548293\n",
      "Epoch 167 / Batch (11/17) / Accuracy 0.7937 / Loss 0.531331\n",
      "Epoch 167 / Batch (12/17) / Accuracy 0.7844 / Loss 0.536318\n",
      "Epoch 167 / Batch (13/17) / Accuracy 0.8494 / Loss 0.422406\n",
      "Epoch 167 / Batch (14/17) / Accuracy 0.8169 / Loss 0.450524\n",
      "Epoch 167 / Batch (15/17) / Accuracy 0.8019 / Loss 0.470360\n",
      "Epoch 167 / Batch (16/17) / Accuracy 0.7806 / Loss 0.547801\n",
      "Epoch 167 / Batch (17/17) / Accuracy 0.7956 / Loss 0.547337\n",
      "Epoch 167 complete, 6.607323169708252 seconds elapsed\n",
      "\n",
      "Epoch 168 starting..\n",
      "Epoch 168 / Batch (1/17) / Accuracy 0.7663 / Loss 0.524466\n",
      "Epoch 168 / Batch (2/17) / Accuracy 0.8294 / Loss 0.429944\n",
      "Epoch 168 / Batch (3/17) / Accuracy 0.8006 / Loss 0.496304\n",
      "Epoch 168 / Batch (4/17) / Accuracy 0.7650 / Loss 0.573203\n",
      "Epoch 168 / Batch (5/17) / Accuracy 0.7969 / Loss 0.522245\n",
      "Epoch 168 / Batch (6/17) / Accuracy 0.7844 / Loss 0.515923\n",
      "Epoch 168 / Batch (7/17) / Accuracy 0.7750 / Loss 0.553080\n",
      "Epoch 168 / Batch (8/17) / Accuracy 0.8156 / Loss 0.453844\n",
      "Epoch 168 / Batch (9/17) / Accuracy 0.8075 / Loss 0.474919\n",
      "Epoch 168 / Batch (10/17) / Accuracy 0.8031 / Loss 0.493723\n",
      "Epoch 168 / Batch (11/17) / Accuracy 0.7994 / Loss 0.503826\n",
      "Epoch 168 / Batch (12/17) / Accuracy 0.8150 / Loss 0.458192\n",
      "Epoch 168 / Batch (13/17) / Accuracy 0.7950 / Loss 0.574206\n",
      "Epoch 168 / Batch (14/17) / Accuracy 0.7569 / Loss 0.564559\n",
      "Epoch 168 / Batch (15/17) / Accuracy 0.8238 / Loss 0.454343\n",
      "Epoch 168 / Batch (16/17) / Accuracy 0.7850 / Loss 0.501761\n",
      "Epoch 168 / Batch (17/17) / Accuracy 0.8112 / Loss 0.475494\n",
      "Epoch 168 complete, 6.5595314502716064 seconds elapsed\n",
      "\n",
      "Epoch 169 starting..\n",
      "Epoch 169 / Batch (1/17) / Accuracy 0.8056 / Loss 0.479181\n",
      "Epoch 169 / Batch (2/17) / Accuracy 0.8200 / Loss 0.439172\n",
      "Epoch 169 / Batch (3/17) / Accuracy 0.7738 / Loss 0.588381\n",
      "Epoch 169 / Batch (4/17) / Accuracy 0.7869 / Loss 0.553507\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 169 / Batch (5/17) / Accuracy 0.8256 / Loss 0.465348\n",
      "Epoch 169 / Batch (6/17) / Accuracy 0.8069 / Loss 0.456705\n",
      "Epoch 169 / Batch (7/17) / Accuracy 0.7794 / Loss 0.533488\n",
      "Epoch 169 / Batch (8/17) / Accuracy 0.8050 / Loss 0.483992\n",
      "Epoch 169 / Batch (9/17) / Accuracy 0.8094 / Loss 0.497730\n",
      "Epoch 169 / Batch (10/17) / Accuracy 0.7519 / Loss 0.575957\n",
      "Epoch 169 / Batch (11/17) / Accuracy 0.7688 / Loss 0.546000\n",
      "Epoch 169 / Batch (12/17) / Accuracy 0.7862 / Loss 0.530445\n",
      "Epoch 169 / Batch (13/17) / Accuracy 0.8094 / Loss 0.477400\n",
      "Epoch 169 / Batch (14/17) / Accuracy 0.7850 / Loss 0.506109\n",
      "Epoch 169 / Batch (15/17) / Accuracy 0.8163 / Loss 0.459782\n",
      "Epoch 169 / Batch (16/17) / Accuracy 0.8281 / Loss 0.449057\n",
      "Epoch 169 / Batch (17/17) / Accuracy 0.7881 / Loss 0.539169\n",
      "Epoch 169 complete, 6.770236253738403 seconds elapsed\n",
      "\n",
      "Epoch 170 starting..\n",
      "Epoch 170 / Batch (1/17) / Accuracy 0.8294 / Loss 0.435838\n",
      "Epoch 170 / Batch (2/17) / Accuracy 0.8175 / Loss 0.474735\n",
      "Epoch 170 / Batch (3/17) / Accuracy 0.8294 / Loss 0.419960\n",
      "Epoch 170 / Batch (4/17) / Accuracy 0.8475 / Loss 0.431153\n",
      "Epoch 170 / Batch (5/17) / Accuracy 0.8075 / Loss 0.482701\n",
      "Epoch 170 / Batch (6/17) / Accuracy 0.7969 / Loss 0.495703\n",
      "Epoch 170 / Batch (7/17) / Accuracy 0.7794 / Loss 0.527246\n",
      "Epoch 170 / Batch (8/17) / Accuracy 0.8425 / Loss 0.414995\n",
      "Epoch 170 / Batch (9/17) / Accuracy 0.7931 / Loss 0.533537\n",
      "Epoch 170 / Batch (10/17) / Accuracy 0.8219 / Loss 0.465849\n",
      "Epoch 170 / Batch (11/17) / Accuracy 0.7925 / Loss 0.551077\n",
      "Epoch 170 / Batch (12/17) / Accuracy 0.8150 / Loss 0.493240\n",
      "Epoch 170 / Batch (13/17) / Accuracy 0.8112 / Loss 0.463638\n",
      "Epoch 170 / Batch (14/17) / Accuracy 0.8131 / Loss 0.450424\n",
      "Epoch 170 / Batch (15/17) / Accuracy 0.8044 / Loss 0.485184\n",
      "Epoch 170 / Batch (16/17) / Accuracy 0.7706 / Loss 0.538114\n",
      "Epoch 170 / Batch (17/17) / Accuracy 0.7969 / Loss 0.485277\n",
      "Epoch 170 complete, 6.203261613845825 seconds elapsed\n",
      "\n",
      "Epoch 171 starting..\n",
      "Epoch 171 / Batch (1/17) / Accuracy 0.8206 / Loss 0.433621\n",
      "Epoch 171 / Batch (2/17) / Accuracy 0.8244 / Loss 0.456301\n",
      "Epoch 171 / Batch (3/17) / Accuracy 0.7994 / Loss 0.541102\n",
      "Epoch 171 / Batch (4/17) / Accuracy 0.7887 / Loss 0.512286\n",
      "Epoch 171 / Batch (5/17) / Accuracy 0.8131 / Loss 0.471785\n",
      "Epoch 171 / Batch (6/17) / Accuracy 0.8019 / Loss 0.521825\n",
      "Epoch 171 / Batch (7/17) / Accuracy 0.8069 / Loss 0.480378\n",
      "Epoch 171 / Batch (8/17) / Accuracy 0.7956 / Loss 0.502866\n",
      "Epoch 171 / Batch (9/17) / Accuracy 0.7912 / Loss 0.522621\n",
      "Epoch 171 / Batch (10/17) / Accuracy 0.8031 / Loss 0.521260\n",
      "Epoch 171 / Batch (11/17) / Accuracy 0.7881 / Loss 0.523962\n",
      "Epoch 171 / Batch (12/17) / Accuracy 0.8131 / Loss 0.485085\n",
      "Epoch 171 / Batch (13/17) / Accuracy 0.8062 / Loss 0.497309\n",
      "Epoch 171 / Batch (14/17) / Accuracy 0.8144 / Loss 0.477714\n",
      "Epoch 171 / Batch (15/17) / Accuracy 0.8338 / Loss 0.437587\n",
      "Epoch 171 / Batch (16/17) / Accuracy 0.7894 / Loss 0.516178\n",
      "Epoch 171 / Batch (17/17) / Accuracy 0.7669 / Loss 0.577045\n",
      "Epoch 171 complete, 6.606121301651001 seconds elapsed\n",
      "\n",
      "Epoch 172 starting..\n",
      "Epoch 172 / Batch (1/17) / Accuracy 0.7987 / Loss 0.496662\n",
      "Epoch 172 / Batch (2/17) / Accuracy 0.8200 / Loss 0.442134\n",
      "Epoch 172 / Batch (3/17) / Accuracy 0.7981 / Loss 0.524496\n",
      "Epoch 172 / Batch (4/17) / Accuracy 0.8119 / Loss 0.454869\n",
      "Epoch 172 / Batch (5/17) / Accuracy 0.8263 / Loss 0.432856\n",
      "Epoch 172 / Batch (6/17) / Accuracy 0.8037 / Loss 0.523048\n",
      "Epoch 172 / Batch (7/17) / Accuracy 0.7763 / Loss 0.563750\n",
      "Epoch 172 / Batch (8/17) / Accuracy 0.8106 / Loss 0.489317\n",
      "Epoch 172 / Batch (9/17) / Accuracy 0.8000 / Loss 0.514646\n",
      "Epoch 172 / Batch (10/17) / Accuracy 0.8119 / Loss 0.452935\n",
      "Epoch 172 / Batch (11/17) / Accuracy 0.8269 / Loss 0.450556\n",
      "Epoch 172 / Batch (12/17) / Accuracy 0.8319 / Loss 0.439552\n",
      "Epoch 172 / Batch (13/17) / Accuracy 0.7569 / Loss 0.575663\n",
      "Epoch 172 / Batch (14/17) / Accuracy 0.8512 / Loss 0.407905\n",
      "Epoch 172 / Batch (15/17) / Accuracy 0.7969 / Loss 0.506043\n",
      "Epoch 172 / Batch (16/17) / Accuracy 0.8087 / Loss 0.515781\n",
      "Epoch 172 / Batch (17/17) / Accuracy 0.8512 / Loss 0.395768\n",
      "Epoch 172 complete, 6.940701007843018 seconds elapsed\n",
      "\n",
      "Epoch 173 starting..\n",
      "Epoch 173 / Batch (1/17) / Accuracy 0.7681 / Loss 0.561431\n",
      "Epoch 173 / Batch (2/17) / Accuracy 0.8087 / Loss 0.513209\n",
      "Epoch 173 / Batch (3/17) / Accuracy 0.7912 / Loss 0.529413\n",
      "Epoch 173 / Batch (4/17) / Accuracy 0.8019 / Loss 0.485379\n",
      "Epoch 173 / Batch (5/17) / Accuracy 0.8050 / Loss 0.489451\n",
      "Epoch 173 / Batch (6/17) / Accuracy 0.8062 / Loss 0.468992\n",
      "Epoch 173 / Batch (7/17) / Accuracy 0.8250 / Loss 0.445369\n",
      "Epoch 173 / Batch (8/17) / Accuracy 0.8225 / Loss 0.463135\n",
      "Epoch 173 / Batch (9/17) / Accuracy 0.7919 / Loss 0.542304\n",
      "Epoch 173 / Batch (10/17) / Accuracy 0.8319 / Loss 0.436885\n",
      "Epoch 173 / Batch (11/17) / Accuracy 0.7725 / Loss 0.532067\n",
      "Epoch 173 / Batch (12/17) / Accuracy 0.8231 / Loss 0.459924\n",
      "Epoch 173 / Batch (13/17) / Accuracy 0.7894 / Loss 0.521282\n",
      "Epoch 173 / Batch (14/17) / Accuracy 0.7837 / Loss 0.503888\n",
      "Epoch 173 / Batch (15/17) / Accuracy 0.8238 / Loss 0.469239\n",
      "Epoch 173 / Batch (16/17) / Accuracy 0.7875 / Loss 0.514420\n",
      "Epoch 173 / Batch (17/17) / Accuracy 0.7956 / Loss 0.508669\n",
      "Epoch 173 complete, 6.645620584487915 seconds elapsed\n",
      "\n",
      "Epoch 174 starting..\n",
      "Epoch 174 / Batch (1/17) / Accuracy 0.7794 / Loss 0.541625\n",
      "Epoch 174 / Batch (2/17) / Accuracy 0.8344 / Loss 0.436496\n",
      "Epoch 174 / Batch (3/17) / Accuracy 0.8100 / Loss 0.495221\n",
      "Epoch 174 / Batch (4/17) / Accuracy 0.8125 / Loss 0.468915\n",
      "Epoch 174 / Batch (5/17) / Accuracy 0.7906 / Loss 0.516298\n",
      "Epoch 174 / Batch (6/17) / Accuracy 0.7700 / Loss 0.579477\n",
      "Epoch 174 / Batch (7/17) / Accuracy 0.8081 / Loss 0.491750\n",
      "Epoch 174 / Batch (8/17) / Accuracy 0.7613 / Loss 0.564617\n",
      "Epoch 174 / Batch (9/17) / Accuracy 0.7912 / Loss 0.525219\n",
      "Epoch 174 / Batch (10/17) / Accuracy 0.8269 / Loss 0.470113\n",
      "Epoch 174 / Batch (11/17) / Accuracy 0.7906 / Loss 0.518411\n",
      "Epoch 174 / Batch (12/17) / Accuracy 0.7631 / Loss 0.562537\n",
      "Epoch 174 / Batch (13/17) / Accuracy 0.8281 / Loss 0.467533\n",
      "Epoch 174 / Batch (14/17) / Accuracy 0.7563 / Loss 0.568573\n",
      "Epoch 174 / Batch (15/17) / Accuracy 0.7675 / Loss 0.532526\n",
      "Epoch 174 / Batch (16/17) / Accuracy 0.8087 / Loss 0.489478\n",
      "Epoch 174 / Batch (17/17) / Accuracy 0.8025 / Loss 0.486794\n",
      "Epoch 174 complete, 6.453308582305908 seconds elapsed\n",
      "\n",
      "Epoch 175 starting..\n",
      "Epoch 175 / Batch (1/17) / Accuracy 0.7394 / Loss 0.569456\n",
      "Epoch 175 / Batch (2/17) / Accuracy 0.8050 / Loss 0.506756\n",
      "Epoch 175 / Batch (3/17) / Accuracy 0.8037 / Loss 0.505585\n",
      "Epoch 175 / Batch (4/17) / Accuracy 0.7825 / Loss 0.552820\n",
      "Epoch 175 / Batch (5/17) / Accuracy 0.8000 / Loss 0.495630\n",
      "Epoch 175 / Batch (6/17) / Accuracy 0.7850 / Loss 0.510292\n",
      "Epoch 175 / Batch (7/17) / Accuracy 0.7906 / Loss 0.504191\n",
      "Epoch 175 / Batch (8/17) / Accuracy 0.7812 / Loss 0.541168\n",
      "Epoch 175 / Batch (9/17) / Accuracy 0.7969 / Loss 0.495100\n",
      "Epoch 175 / Batch (10/17) / Accuracy 0.8050 / Loss 0.473960\n",
      "Epoch 175 / Batch (11/17) / Accuracy 0.7931 / Loss 0.504039\n",
      "Epoch 175 / Batch (12/17) / Accuracy 0.7837 / Loss 0.552496\n",
      "Epoch 175 / Batch (13/17) / Accuracy 0.8006 / Loss 0.485273\n",
      "Epoch 175 / Batch (14/17) / Accuracy 0.8075 / Loss 0.493388\n",
      "Epoch 175 / Batch (15/17) / Accuracy 0.7969 / Loss 0.485671\n",
      "Epoch 175 / Batch (16/17) / Accuracy 0.7881 / Loss 0.544283\n",
      "Epoch 175 / Batch (17/17) / Accuracy 0.7844 / Loss 0.536951\n",
      "Epoch 175 complete, 6.303019762039185 seconds elapsed\n",
      "\n",
      "Epoch 176 starting..\n",
      "Epoch 176 / Batch (1/17) / Accuracy 0.7981 / Loss 0.467001\n",
      "Epoch 176 / Batch (2/17) / Accuracy 0.8475 / Loss 0.417581\n",
      "Epoch 176 / Batch (3/17) / Accuracy 0.7969 / Loss 0.526816\n",
      "Epoch 176 / Batch (4/17) / Accuracy 0.7981 / Loss 0.526634\n",
      "Epoch 176 / Batch (5/17) / Accuracy 0.8112 / Loss 0.499721\n",
      "Epoch 176 / Batch (6/17) / Accuracy 0.7800 / Loss 0.555229\n",
      "Epoch 176 / Batch (7/17) / Accuracy 0.7800 / Loss 0.508764\n",
      "Epoch 176 / Batch (8/17) / Accuracy 0.8213 / Loss 0.459866\n",
      "Epoch 176 / Batch (9/17) / Accuracy 0.7919 / Loss 0.493677\n",
      "Epoch 176 / Batch (10/17) / Accuracy 0.7487 / Loss 0.585527\n",
      "Epoch 176 / Batch (11/17) / Accuracy 0.8481 / Loss 0.408061\n",
      "Epoch 176 / Batch (12/17) / Accuracy 0.7775 / Loss 0.538202\n",
      "Epoch 176 / Batch (13/17) / Accuracy 0.7969 / Loss 0.527952\n",
      "Epoch 176 / Batch (14/17) / Accuracy 0.7806 / Loss 0.540371\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 176 / Batch (15/17) / Accuracy 0.7844 / Loss 0.570433\n",
      "Epoch 176 / Batch (16/17) / Accuracy 0.7887 / Loss 0.511538\n",
      "Epoch 176 / Batch (17/17) / Accuracy 0.8225 / Loss 0.465704\n",
      "Epoch 176 complete, 7.120281934738159 seconds elapsed\n",
      "\n",
      "Epoch 177 starting..\n",
      "Epoch 177 / Batch (1/17) / Accuracy 0.7856 / Loss 0.552337\n",
      "Epoch 177 / Batch (2/17) / Accuracy 0.7881 / Loss 0.533566\n",
      "Epoch 177 / Batch (3/17) / Accuracy 0.8225 / Loss 0.446175\n",
      "Epoch 177 / Batch (4/17) / Accuracy 0.7850 / Loss 0.542271\n",
      "Epoch 177 / Batch (5/17) / Accuracy 0.7906 / Loss 0.511026\n",
      "Epoch 177 / Batch (6/17) / Accuracy 0.7738 / Loss 0.550798\n",
      "Epoch 177 / Batch (7/17) / Accuracy 0.7906 / Loss 0.529022\n",
      "Epoch 177 / Batch (8/17) / Accuracy 0.7919 / Loss 0.495930\n",
      "Epoch 177 / Batch (9/17) / Accuracy 0.8169 / Loss 0.464101\n",
      "Epoch 177 / Batch (10/17) / Accuracy 0.7975 / Loss 0.479578\n",
      "Epoch 177 / Batch (11/17) / Accuracy 0.7919 / Loss 0.509442\n",
      "Epoch 177 / Batch (12/17) / Accuracy 0.7812 / Loss 0.525829\n",
      "Epoch 177 / Batch (13/17) / Accuracy 0.7756 / Loss 0.545603\n",
      "Epoch 177 / Batch (14/17) / Accuracy 0.7794 / Loss 0.570173\n",
      "Epoch 177 / Batch (15/17) / Accuracy 0.8031 / Loss 0.494730\n",
      "Epoch 177 / Batch (16/17) / Accuracy 0.8100 / Loss 0.487633\n",
      "Epoch 177 / Batch (17/17) / Accuracy 0.7987 / Loss 0.501410\n",
      "Epoch 177 complete, 6.7427356243133545 seconds elapsed\n",
      "\n",
      "Epoch 178 starting..\n",
      "Epoch 178 / Batch (1/17) / Accuracy 0.7606 / Loss 0.571840\n",
      "Epoch 178 / Batch (2/17) / Accuracy 0.7494 / Loss 0.648056\n",
      "Epoch 178 / Batch (3/17) / Accuracy 0.7800 / Loss 0.526199\n",
      "Epoch 178 / Batch (4/17) / Accuracy 0.8037 / Loss 0.490704\n",
      "Epoch 178 / Batch (5/17) / Accuracy 0.7850 / Loss 0.523645\n",
      "Epoch 178 / Batch (6/17) / Accuracy 0.8000 / Loss 0.482034\n",
      "Epoch 178 / Batch (7/17) / Accuracy 0.7975 / Loss 0.492479\n",
      "Epoch 178 / Batch (8/17) / Accuracy 0.8012 / Loss 0.496752\n",
      "Epoch 178 / Batch (9/17) / Accuracy 0.8250 / Loss 0.440512\n",
      "Epoch 178 / Batch (10/17) / Accuracy 0.8000 / Loss 0.524774\n",
      "Epoch 178 / Batch (11/17) / Accuracy 0.8306 / Loss 0.445003\n",
      "Epoch 178 / Batch (12/17) / Accuracy 0.8144 / Loss 0.482917\n",
      "Epoch 178 / Batch (13/17) / Accuracy 0.8169 / Loss 0.474976\n",
      "Epoch 178 / Batch (14/17) / Accuracy 0.8156 / Loss 0.468646\n",
      "Epoch 178 / Batch (15/17) / Accuracy 0.7756 / Loss 0.536603\n",
      "Epoch 178 / Batch (16/17) / Accuracy 0.7881 / Loss 0.495081\n",
      "Epoch 178 / Batch (17/17) / Accuracy 0.8188 / Loss 0.466345\n",
      "Epoch 178 complete, 6.584666728973389 seconds elapsed\n",
      "\n",
      "Epoch 179 starting..\n",
      "Epoch 179 / Batch (1/17) / Accuracy 0.7744 / Loss 0.551243\n",
      "Epoch 179 / Batch (2/17) / Accuracy 0.7994 / Loss 0.470121\n",
      "Epoch 179 / Batch (3/17) / Accuracy 0.7613 / Loss 0.580882\n",
      "Epoch 179 / Batch (4/17) / Accuracy 0.7800 / Loss 0.522911\n",
      "Epoch 179 / Batch (5/17) / Accuracy 0.7594 / Loss 0.605864\n",
      "Epoch 179 / Batch (6/17) / Accuracy 0.7956 / Loss 0.489771\n",
      "Epoch 179 / Batch (7/17) / Accuracy 0.8075 / Loss 0.479609\n",
      "Epoch 179 / Batch (8/17) / Accuracy 0.8144 / Loss 0.477536\n",
      "Epoch 179 / Batch (9/17) / Accuracy 0.7981 / Loss 0.542301\n",
      "Epoch 179 / Batch (10/17) / Accuracy 0.8100 / Loss 0.493873\n",
      "Epoch 179 / Batch (11/17) / Accuracy 0.7644 / Loss 0.556975\n",
      "Epoch 179 / Batch (12/17) / Accuracy 0.8112 / Loss 0.464261\n",
      "Epoch 179 / Batch (13/17) / Accuracy 0.7894 / Loss 0.509903\n",
      "Epoch 179 / Batch (14/17) / Accuracy 0.7794 / Loss 0.536053\n",
      "Epoch 179 / Batch (15/17) / Accuracy 0.8037 / Loss 0.505323\n",
      "Epoch 179 / Batch (16/17) / Accuracy 0.7894 / Loss 0.513231\n",
      "Epoch 179 / Batch (17/17) / Accuracy 0.8238 / Loss 0.455615\n",
      "Epoch 179 complete, 6.706385850906372 seconds elapsed\n",
      "\n",
      "Epoch 180 starting..\n",
      "Epoch 180 / Batch (1/17) / Accuracy 0.8388 / Loss 0.449521\n",
      "Epoch 180 / Batch (2/17) / Accuracy 0.8250 / Loss 0.413428\n",
      "Epoch 180 / Batch (3/17) / Accuracy 0.7912 / Loss 0.528074\n",
      "Epoch 180 / Batch (4/17) / Accuracy 0.7969 / Loss 0.502794\n",
      "Epoch 180 / Batch (5/17) / Accuracy 0.7912 / Loss 0.502315\n",
      "Epoch 180 / Batch (6/17) / Accuracy 0.8263 / Loss 0.414332\n",
      "Epoch 180 / Batch (7/17) / Accuracy 0.8062 / Loss 0.491597\n",
      "Epoch 180 / Batch (8/17) / Accuracy 0.8081 / Loss 0.469487\n",
      "Epoch 180 / Batch (9/17) / Accuracy 0.7750 / Loss 0.531919\n",
      "Epoch 180 / Batch (10/17) / Accuracy 0.7931 / Loss 0.529443\n",
      "Epoch 180 / Batch (11/17) / Accuracy 0.7944 / Loss 0.507360\n",
      "Epoch 180 / Batch (12/17) / Accuracy 0.8375 / Loss 0.446504\n",
      "Epoch 180 / Batch (13/17) / Accuracy 0.8188 / Loss 0.468572\n",
      "Epoch 180 / Batch (14/17) / Accuracy 0.8369 / Loss 0.445435\n",
      "Epoch 180 / Batch (15/17) / Accuracy 0.7950 / Loss 0.514309\n",
      "Epoch 180 / Batch (16/17) / Accuracy 0.8181 / Loss 0.454278\n",
      "Epoch 180 / Batch (17/17) / Accuracy 0.8206 / Loss 0.458784\n",
      "Epoch 180 complete, 6.36681604385376 seconds elapsed\n",
      "\n",
      "Epoch 181 starting..\n",
      "Epoch 181 / Batch (1/17) / Accuracy 0.8019 / Loss 0.511093\n",
      "Epoch 181 / Batch (2/17) / Accuracy 0.8138 / Loss 0.480881\n",
      "Epoch 181 / Batch (3/17) / Accuracy 0.7869 / Loss 0.533635\n",
      "Epoch 181 / Batch (4/17) / Accuracy 0.7650 / Loss 0.573395\n",
      "Epoch 181 / Batch (5/17) / Accuracy 0.8012 / Loss 0.501282\n",
      "Epoch 181 / Batch (6/17) / Accuracy 0.8106 / Loss 0.476599\n",
      "Epoch 181 / Batch (7/17) / Accuracy 0.7906 / Loss 0.518735\n",
      "Epoch 181 / Batch (8/17) / Accuracy 0.8188 / Loss 0.454667\n",
      "Epoch 181 / Batch (9/17) / Accuracy 0.8575 / Loss 0.420321\n",
      "Epoch 181 / Batch (10/17) / Accuracy 0.7800 / Loss 0.553396\n",
      "Epoch 181 / Batch (11/17) / Accuracy 0.8181 / Loss 0.455291\n",
      "Epoch 181 / Batch (12/17) / Accuracy 0.8056 / Loss 0.477840\n",
      "Epoch 181 / Batch (13/17) / Accuracy 0.7788 / Loss 0.529288\n",
      "Epoch 181 / Batch (14/17) / Accuracy 0.7850 / Loss 0.534346\n",
      "Epoch 181 / Batch (15/17) / Accuracy 0.8131 / Loss 0.488846\n",
      "Epoch 181 / Batch (16/17) / Accuracy 0.8506 / Loss 0.402750\n",
      "Epoch 181 / Batch (17/17) / Accuracy 0.8050 / Loss 0.477969\n",
      "Epoch 181 complete, 6.196645975112915 seconds elapsed\n",
      "\n",
      "Epoch 182 starting..\n",
      "Epoch 182 / Batch (1/17) / Accuracy 0.8219 / Loss 0.458177\n",
      "Epoch 182 / Batch (2/17) / Accuracy 0.7900 / Loss 0.521283\n",
      "Epoch 182 / Batch (3/17) / Accuracy 0.8125 / Loss 0.487382\n",
      "Epoch 182 / Batch (4/17) / Accuracy 0.7956 / Loss 0.501358\n",
      "Epoch 182 / Batch (5/17) / Accuracy 0.8112 / Loss 0.481893\n",
      "Epoch 182 / Batch (6/17) / Accuracy 0.7856 / Loss 0.506471\n",
      "Epoch 182 / Batch (7/17) / Accuracy 0.8400 / Loss 0.424315\n",
      "Epoch 182 / Batch (8/17) / Accuracy 0.7800 / Loss 0.555876\n",
      "Epoch 182 / Batch (9/17) / Accuracy 0.8231 / Loss 0.450714\n",
      "Epoch 182 / Batch (10/17) / Accuracy 0.8256 / Loss 0.462685\n",
      "Epoch 182 / Batch (11/17) / Accuracy 0.7738 / Loss 0.562779\n",
      "Epoch 182 / Batch (12/17) / Accuracy 0.8200 / Loss 0.476551\n",
      "Epoch 182 / Batch (13/17) / Accuracy 0.8131 / Loss 0.468128\n",
      "Epoch 182 / Batch (14/17) / Accuracy 0.8269 / Loss 0.446704\n",
      "Epoch 182 / Batch (15/17) / Accuracy 0.8087 / Loss 0.457458\n",
      "Epoch 182 / Batch (16/17) / Accuracy 0.8075 / Loss 0.505333\n",
      "Epoch 182 / Batch (17/17) / Accuracy 0.7950 / Loss 0.508939\n",
      "Epoch 182 complete, 6.901476144790649 seconds elapsed\n",
      "\n",
      "Epoch 183 starting..\n",
      "Epoch 183 / Batch (1/17) / Accuracy 0.8169 / Loss 0.469437\n",
      "Epoch 183 / Batch (2/17) / Accuracy 0.7769 / Loss 0.537661\n",
      "Epoch 183 / Batch (3/17) / Accuracy 0.8369 / Loss 0.448520\n",
      "Epoch 183 / Batch (4/17) / Accuracy 0.8119 / Loss 0.470462\n",
      "Epoch 183 / Batch (5/17) / Accuracy 0.8163 / Loss 0.445042\n",
      "Epoch 183 / Batch (6/17) / Accuracy 0.8100 / Loss 0.478169\n",
      "Epoch 183 / Batch (7/17) / Accuracy 0.8438 / Loss 0.433217\n",
      "Epoch 183 / Batch (8/17) / Accuracy 0.8175 / Loss 0.460375\n",
      "Epoch 183 / Batch (9/17) / Accuracy 0.7500 / Loss 0.578435\n",
      "Epoch 183 / Batch (10/17) / Accuracy 0.8256 / Loss 0.446063\n",
      "Epoch 183 / Batch (11/17) / Accuracy 0.8231 / Loss 0.454752\n",
      "Epoch 183 / Batch (12/17) / Accuracy 0.8188 / Loss 0.474868\n",
      "Epoch 183 / Batch (13/17) / Accuracy 0.8181 / Loss 0.446568\n",
      "Epoch 183 / Batch (14/17) / Accuracy 0.8444 / Loss 0.413579\n",
      "Epoch 183 / Batch (15/17) / Accuracy 0.8163 / Loss 0.454926\n",
      "Epoch 183 / Batch (16/17) / Accuracy 0.8188 / Loss 0.476382\n",
      "Epoch 183 / Batch (17/17) / Accuracy 0.8419 / Loss 0.415203\n",
      "Epoch 183 complete, 6.6304261684417725 seconds elapsed\n",
      "\n",
      "Epoch 184 starting..\n",
      "Epoch 184 / Batch (1/17) / Accuracy 0.8406 / Loss 0.442846\n",
      "Epoch 184 / Batch (2/17) / Accuracy 0.8150 / Loss 0.478938\n",
      "Epoch 184 / Batch (3/17) / Accuracy 0.7819 / Loss 0.514559\n",
      "Epoch 184 / Batch (4/17) / Accuracy 0.7638 / Loss 0.587690\n",
      "Epoch 184 / Batch (5/17) / Accuracy 0.7713 / Loss 0.560513\n",
      "Epoch 184 / Batch (6/17) / Accuracy 0.8144 / Loss 0.481207\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 184 / Batch (7/17) / Accuracy 0.8194 / Loss 0.474690\n",
      "Epoch 184 / Batch (8/17) / Accuracy 0.8056 / Loss 0.488374\n",
      "Epoch 184 / Batch (9/17) / Accuracy 0.8125 / Loss 0.454453\n",
      "Epoch 184 / Batch (10/17) / Accuracy 0.8100 / Loss 0.457538\n",
      "Epoch 184 / Batch (11/17) / Accuracy 0.7969 / Loss 0.493138\n",
      "Epoch 184 / Batch (12/17) / Accuracy 0.8056 / Loss 0.485785\n",
      "Epoch 184 / Batch (13/17) / Accuracy 0.8106 / Loss 0.471089\n",
      "Epoch 184 / Batch (14/17) / Accuracy 0.7881 / Loss 0.520379\n",
      "Epoch 184 / Batch (15/17) / Accuracy 0.8512 / Loss 0.408183\n",
      "Epoch 184 / Batch (16/17) / Accuracy 0.8231 / Loss 0.434666\n",
      "Epoch 184 / Batch (17/17) / Accuracy 0.7925 / Loss 0.512472\n",
      "Epoch 184 complete, 6.627939462661743 seconds elapsed\n",
      "\n",
      "Epoch 185 starting..\n",
      "Epoch 185 / Batch (1/17) / Accuracy 0.8400 / Loss 0.392662\n",
      "Epoch 185 / Batch (2/17) / Accuracy 0.8000 / Loss 0.510011\n",
      "Epoch 185 / Batch (3/17) / Accuracy 0.8175 / Loss 0.468123\n",
      "Epoch 185 / Batch (4/17) / Accuracy 0.8369 / Loss 0.421872\n",
      "Epoch 185 / Batch (5/17) / Accuracy 0.7900 / Loss 0.496094\n",
      "Epoch 185 / Batch (6/17) / Accuracy 0.7894 / Loss 0.486152\n",
      "Epoch 185 / Batch (7/17) / Accuracy 0.8419 / Loss 0.405369\n",
      "Epoch 185 / Batch (8/17) / Accuracy 0.8344 / Loss 0.440071\n",
      "Epoch 185 / Batch (9/17) / Accuracy 0.8481 / Loss 0.421782\n",
      "Epoch 185 / Batch (10/17) / Accuracy 0.7781 / Loss 0.519018\n",
      "Epoch 185 / Batch (11/17) / Accuracy 0.7912 / Loss 0.526555\n",
      "Epoch 185 / Batch (12/17) / Accuracy 0.8231 / Loss 0.468194\n",
      "Epoch 185 / Batch (13/17) / Accuracy 0.8119 / Loss 0.466495\n",
      "Epoch 185 / Batch (14/17) / Accuracy 0.7812 / Loss 0.511740\n",
      "Epoch 185 / Batch (15/17) / Accuracy 0.7969 / Loss 0.514130\n",
      "Epoch 185 / Batch (16/17) / Accuracy 0.8306 / Loss 0.440683\n",
      "Epoch 185 / Batch (17/17) / Accuracy 0.8381 / Loss 0.422413\n",
      "Epoch 185 complete, 6.428187847137451 seconds elapsed\n",
      "\n",
      "Epoch 186 starting..\n",
      "Epoch 186 / Batch (1/17) / Accuracy 0.8438 / Loss 0.426635\n",
      "Epoch 186 / Batch (2/17) / Accuracy 0.8119 / Loss 0.475331\n",
      "Epoch 186 / Batch (3/17) / Accuracy 0.7969 / Loss 0.500834\n",
      "Epoch 186 / Batch (4/17) / Accuracy 0.7663 / Loss 0.557587\n",
      "Epoch 186 / Batch (5/17) / Accuracy 0.8050 / Loss 0.504727\n",
      "Epoch 186 / Batch (6/17) / Accuracy 0.8263 / Loss 0.480692\n",
      "Epoch 186 / Batch (7/17) / Accuracy 0.8044 / Loss 0.478001\n",
      "Epoch 186 / Batch (8/17) / Accuracy 0.7900 / Loss 0.509984\n",
      "Epoch 186 / Batch (9/17) / Accuracy 0.8200 / Loss 0.465380\n",
      "Epoch 186 / Batch (10/17) / Accuracy 0.7731 / Loss 0.543943\n",
      "Epoch 186 / Batch (11/17) / Accuracy 0.8100 / Loss 0.478337\n",
      "Epoch 186 / Batch (12/17) / Accuracy 0.7900 / Loss 0.518610\n",
      "Epoch 186 / Batch (13/17) / Accuracy 0.7806 / Loss 0.533716\n",
      "Epoch 186 / Batch (14/17) / Accuracy 0.8006 / Loss 0.509482\n",
      "Epoch 186 / Batch (15/17) / Accuracy 0.7825 / Loss 0.540969\n",
      "Epoch 186 / Batch (16/17) / Accuracy 0.7919 / Loss 0.498494\n",
      "Epoch 186 / Batch (17/17) / Accuracy 0.7906 / Loss 0.514054\n",
      "Epoch 186 complete, 6.261555433273315 seconds elapsed\n",
      "\n",
      "Epoch 187 starting..\n",
      "Epoch 187 / Batch (1/17) / Accuracy 0.8037 / Loss 0.490885\n",
      "Epoch 187 / Batch (2/17) / Accuracy 0.8062 / Loss 0.494676\n",
      "Epoch 187 / Batch (3/17) / Accuracy 0.8163 / Loss 0.489449\n",
      "Epoch 187 / Batch (4/17) / Accuracy 0.7706 / Loss 0.579044\n",
      "Epoch 187 / Batch (5/17) / Accuracy 0.7825 / Loss 0.521601\n",
      "Epoch 187 / Batch (6/17) / Accuracy 0.7856 / Loss 0.524334\n",
      "Epoch 187 / Batch (7/17) / Accuracy 0.8325 / Loss 0.440508\n",
      "Epoch 187 / Batch (8/17) / Accuracy 0.7800 / Loss 0.540852\n",
      "Epoch 187 / Batch (9/17) / Accuracy 0.8125 / Loss 0.490771\n",
      "Epoch 187 / Batch (10/17) / Accuracy 0.8181 / Loss 0.465055\n",
      "Epoch 187 / Batch (11/17) / Accuracy 0.8294 / Loss 0.429712\n",
      "Epoch 187 / Batch (12/17) / Accuracy 0.8056 / Loss 0.483610\n",
      "Epoch 187 / Batch (13/17) / Accuracy 0.8144 / Loss 0.483703\n",
      "Epoch 187 / Batch (14/17) / Accuracy 0.7931 / Loss 0.504360\n",
      "Epoch 187 / Batch (15/17) / Accuracy 0.8200 / Loss 0.466527\n",
      "Epoch 187 / Batch (16/17) / Accuracy 0.8106 / Loss 0.482077\n",
      "Epoch 187 / Batch (17/17) / Accuracy 0.8044 / Loss 0.501069\n",
      "Epoch 187 complete, 7.133212327957153 seconds elapsed\n",
      "\n",
      "Epoch 188 starting..\n",
      "Epoch 188 / Batch (1/17) / Accuracy 0.8056 / Loss 0.480373\n",
      "Epoch 188 / Batch (2/17) / Accuracy 0.8194 / Loss 0.445586\n",
      "Epoch 188 / Batch (3/17) / Accuracy 0.8294 / Loss 0.431109\n",
      "Epoch 188 / Batch (4/17) / Accuracy 0.7981 / Loss 0.519296\n",
      "Epoch 188 / Batch (5/17) / Accuracy 0.7694 / Loss 0.577732\n",
      "Epoch 188 / Batch (6/17) / Accuracy 0.8062 / Loss 0.462507\n",
      "Epoch 188 / Batch (7/17) / Accuracy 0.8425 / Loss 0.438004\n",
      "Epoch 188 / Batch (8/17) / Accuracy 0.7613 / Loss 0.548696\n",
      "Epoch 188 / Batch (9/17) / Accuracy 0.8012 / Loss 0.494179\n",
      "Epoch 188 / Batch (10/17) / Accuracy 0.8031 / Loss 0.498082\n",
      "Epoch 188 / Batch (11/17) / Accuracy 0.8138 / Loss 0.472209\n",
      "Epoch 188 / Batch (12/17) / Accuracy 0.8069 / Loss 0.482723\n",
      "Epoch 188 / Batch (13/17) / Accuracy 0.7800 / Loss 0.515758\n",
      "Epoch 188 / Batch (14/17) / Accuracy 0.7844 / Loss 0.553770\n",
      "Epoch 188 / Batch (15/17) / Accuracy 0.8000 / Loss 0.497661\n",
      "Epoch 188 / Batch (16/17) / Accuracy 0.8075 / Loss 0.470289\n",
      "Epoch 188 / Batch (17/17) / Accuracy 0.8406 / Loss 0.431696\n",
      "Epoch 188 complete, 6.592840909957886 seconds elapsed\n",
      "\n",
      "Epoch 189 starting..\n",
      "Epoch 189 / Batch (1/17) / Accuracy 0.7925 / Loss 0.524463\n",
      "Epoch 189 / Batch (2/17) / Accuracy 0.8019 / Loss 0.489393\n",
      "Epoch 189 / Batch (3/17) / Accuracy 0.8350 / Loss 0.424160\n",
      "Epoch 189 / Batch (4/17) / Accuracy 0.8056 / Loss 0.481744\n",
      "Epoch 189 / Batch (5/17) / Accuracy 0.8200 / Loss 0.469358\n",
      "Epoch 189 / Batch (6/17) / Accuracy 0.8256 / Loss 0.472119\n",
      "Epoch 189 / Batch (7/17) / Accuracy 0.8006 / Loss 0.485321\n",
      "Epoch 189 / Batch (8/17) / Accuracy 0.8350 / Loss 0.435833\n",
      "Epoch 189 / Batch (9/17) / Accuracy 0.7919 / Loss 0.557944\n",
      "Epoch 189 / Batch (10/17) / Accuracy 0.7812 / Loss 0.553906\n",
      "Epoch 189 / Batch (11/17) / Accuracy 0.7925 / Loss 0.523632\n",
      "Epoch 189 / Batch (12/17) / Accuracy 0.8175 / Loss 0.474492\n",
      "Epoch 189 / Batch (13/17) / Accuracy 0.7844 / Loss 0.535989\n",
      "Epoch 189 / Batch (14/17) / Accuracy 0.8231 / Loss 0.457999\n",
      "Epoch 189 / Batch (15/17) / Accuracy 0.7713 / Loss 0.537085\n",
      "Epoch 189 / Batch (16/17) / Accuracy 0.8031 / Loss 0.473589\n",
      "Epoch 189 / Batch (17/17) / Accuracy 0.7894 / Loss 0.519224\n",
      "Epoch 189 complete, 6.074152946472168 seconds elapsed\n",
      "\n",
      "Epoch 190 starting..\n",
      "Epoch 190 / Batch (1/17) / Accuracy 0.8356 / Loss 0.431289\n",
      "Epoch 190 / Batch (2/17) / Accuracy 0.8075 / Loss 0.494970\n",
      "Epoch 190 / Batch (3/17) / Accuracy 0.7650 / Loss 0.564519\n",
      "Epoch 190 / Batch (4/17) / Accuracy 0.7794 / Loss 0.565141\n",
      "Epoch 190 / Batch (5/17) / Accuracy 0.8069 / Loss 0.502715\n",
      "Epoch 190 / Batch (6/17) / Accuracy 0.8194 / Loss 0.442117\n",
      "Epoch 190 / Batch (7/17) / Accuracy 0.7912 / Loss 0.501054\n",
      "Epoch 190 / Batch (8/17) / Accuracy 0.7925 / Loss 0.510736\n",
      "Epoch 190 / Batch (9/17) / Accuracy 0.7831 / Loss 0.533943\n",
      "Epoch 190 / Batch (10/17) / Accuracy 0.7875 / Loss 0.525811\n",
      "Epoch 190 / Batch (11/17) / Accuracy 0.8012 / Loss 0.488200\n",
      "Epoch 190 / Batch (12/17) / Accuracy 0.7763 / Loss 0.529947\n",
      "Epoch 190 / Batch (13/17) / Accuracy 0.8238 / Loss 0.455078\n",
      "Epoch 190 / Batch (14/17) / Accuracy 0.8188 / Loss 0.448629\n",
      "Epoch 190 / Batch (15/17) / Accuracy 0.7781 / Loss 0.530812\n",
      "Epoch 190 / Batch (16/17) / Accuracy 0.7975 / Loss 0.504770\n",
      "Epoch 190 / Batch (17/17) / Accuracy 0.7794 / Loss 0.551076\n",
      "Epoch 190 complete, 5.90680456161499 seconds elapsed\n",
      "\n",
      "Epoch 191 starting..\n",
      "Epoch 191 / Batch (1/17) / Accuracy 0.7844 / Loss 0.535291\n",
      "Epoch 191 / Batch (2/17) / Accuracy 0.7675 / Loss 0.562763\n",
      "Epoch 191 / Batch (3/17) / Accuracy 0.7875 / Loss 0.534232\n",
      "Epoch 191 / Batch (4/17) / Accuracy 0.7812 / Loss 0.533096\n",
      "Epoch 191 / Batch (5/17) / Accuracy 0.7619 / Loss 0.550764\n",
      "Epoch 191 / Batch (6/17) / Accuracy 0.7756 / Loss 0.564709\n",
      "Epoch 191 / Batch (7/17) / Accuracy 0.7837 / Loss 0.531884\n",
      "Epoch 191 / Batch (8/17) / Accuracy 0.7944 / Loss 0.513561\n",
      "Epoch 191 / Batch (9/17) / Accuracy 0.7688 / Loss 0.547320\n",
      "Epoch 191 / Batch (10/17) / Accuracy 0.8256 / Loss 0.435236\n",
      "Epoch 191 / Batch (11/17) / Accuracy 0.7975 / Loss 0.505770\n",
      "Epoch 191 / Batch (12/17) / Accuracy 0.8100 / Loss 0.502062\n",
      "Epoch 191 / Batch (13/17) / Accuracy 0.8006 / Loss 0.512336\n",
      "Epoch 191 / Batch (14/17) / Accuracy 0.8056 / Loss 0.498718\n",
      "Epoch 191 / Batch (15/17) / Accuracy 0.8250 / Loss 0.455536\n",
      "Epoch 191 / Batch (16/17) / Accuracy 0.8138 / Loss 0.500991\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 191 / Batch (17/17) / Accuracy 0.7987 / Loss 0.493966\n",
      "Epoch 191 complete, 7.096114158630371 seconds elapsed\n",
      "\n",
      "Epoch 192 starting..\n",
      "Epoch 192 / Batch (1/17) / Accuracy 0.8144 / Loss 0.479891\n",
      "Epoch 192 / Batch (2/17) / Accuracy 0.8031 / Loss 0.479412\n",
      "Epoch 192 / Batch (3/17) / Accuracy 0.7713 / Loss 0.554034\n",
      "Epoch 192 / Batch (4/17) / Accuracy 0.7769 / Loss 0.563025\n",
      "Epoch 192 / Batch (5/17) / Accuracy 0.8163 / Loss 0.454329\n",
      "Epoch 192 / Batch (6/17) / Accuracy 0.8069 / Loss 0.487645\n",
      "Epoch 192 / Batch (7/17) / Accuracy 0.7881 / Loss 0.524198\n",
      "Epoch 192 / Batch (8/17) / Accuracy 0.7794 / Loss 0.504621\n",
      "Epoch 192 / Batch (9/17) / Accuracy 0.7663 / Loss 0.584415\n",
      "Epoch 192 / Batch (10/17) / Accuracy 0.8150 / Loss 0.470765\n",
      "Epoch 192 / Batch (11/17) / Accuracy 0.8031 / Loss 0.482722\n",
      "Epoch 192 / Batch (12/17) / Accuracy 0.8012 / Loss 0.521274\n",
      "Epoch 192 / Batch (13/17) / Accuracy 0.7556 / Loss 0.594620\n",
      "Epoch 192 / Batch (14/17) / Accuracy 0.7619 / Loss 0.545932\n",
      "Epoch 192 / Batch (15/17) / Accuracy 0.8075 / Loss 0.479730\n",
      "Epoch 192 / Batch (16/17) / Accuracy 0.8156 / Loss 0.489431\n",
      "Epoch 192 / Batch (17/17) / Accuracy 0.7975 / Loss 0.487286\n",
      "Epoch 192 complete, 6.90314245223999 seconds elapsed\n",
      "\n",
      "Epoch 193 starting..\n",
      "Epoch 193 / Batch (1/17) / Accuracy 0.8238 / Loss 0.434770\n",
      "Epoch 193 / Batch (2/17) / Accuracy 0.8200 / Loss 0.447917\n",
      "Epoch 193 / Batch (3/17) / Accuracy 0.7850 / Loss 0.513263\n",
      "Epoch 193 / Batch (4/17) / Accuracy 0.7994 / Loss 0.496538\n",
      "Epoch 193 / Batch (5/17) / Accuracy 0.7606 / Loss 0.574643\n",
      "Epoch 193 / Batch (6/17) / Accuracy 0.8438 / Loss 0.449096\n",
      "Epoch 193 / Batch (7/17) / Accuracy 0.7981 / Loss 0.503699\n",
      "Epoch 193 / Batch (8/17) / Accuracy 0.8156 / Loss 0.466735\n",
      "Epoch 193 / Batch (9/17) / Accuracy 0.8294 / Loss 0.431383\n",
      "Epoch 193 / Batch (10/17) / Accuracy 0.8019 / Loss 0.500780\n",
      "Epoch 193 / Batch (11/17) / Accuracy 0.8338 / Loss 0.452787\n",
      "Epoch 193 / Batch (12/17) / Accuracy 0.8050 / Loss 0.487534\n",
      "Epoch 193 / Batch (13/17) / Accuracy 0.8000 / Loss 0.494302\n",
      "Epoch 193 / Batch (14/17) / Accuracy 0.8069 / Loss 0.472373\n",
      "Epoch 193 / Batch (15/17) / Accuracy 0.8138 / Loss 0.478328\n",
      "Epoch 193 / Batch (16/17) / Accuracy 0.8269 / Loss 0.444545\n",
      "Epoch 193 / Batch (17/17) / Accuracy 0.7756 / Loss 0.553252\n",
      "Epoch 193 complete, 6.472051382064819 seconds elapsed\n",
      "\n",
      "Epoch 194 starting..\n",
      "Epoch 194 / Batch (1/17) / Accuracy 0.8050 / Loss 0.491946\n",
      "Epoch 194 / Batch (2/17) / Accuracy 0.8081 / Loss 0.462905\n",
      "Epoch 194 / Batch (3/17) / Accuracy 0.7987 / Loss 0.511203\n",
      "Epoch 194 / Batch (4/17) / Accuracy 0.8175 / Loss 0.455485\n",
      "Epoch 194 / Batch (5/17) / Accuracy 0.8250 / Loss 0.455901\n",
      "Epoch 194 / Batch (6/17) / Accuracy 0.8031 / Loss 0.523126\n",
      "Epoch 194 / Batch (7/17) / Accuracy 0.8238 / Loss 0.494965\n",
      "Epoch 194 / Batch (8/17) / Accuracy 0.7994 / Loss 0.525421\n",
      "Epoch 194 / Batch (9/17) / Accuracy 0.8131 / Loss 0.455224\n",
      "Epoch 194 / Batch (10/17) / Accuracy 0.8169 / Loss 0.488734\n",
      "Epoch 194 / Batch (11/17) / Accuracy 0.8044 / Loss 0.506291\n",
      "Epoch 194 / Batch (12/17) / Accuracy 0.8037 / Loss 0.480057\n",
      "Epoch 194 / Batch (13/17) / Accuracy 0.7844 / Loss 0.557624\n",
      "Epoch 194 / Batch (14/17) / Accuracy 0.8356 / Loss 0.404982\n",
      "Epoch 194 / Batch (15/17) / Accuracy 0.8131 / Loss 0.485357\n",
      "Epoch 194 / Batch (16/17) / Accuracy 0.8025 / Loss 0.494094\n",
      "Epoch 194 / Batch (17/17) / Accuracy 0.8300 / Loss 0.443445\n",
      "Epoch 194 complete, 6.573849439620972 seconds elapsed\n",
      "\n",
      "Epoch 195 starting..\n",
      "Epoch 195 / Batch (1/17) / Accuracy 0.7812 / Loss 0.520964\n",
      "Epoch 195 / Batch (2/17) / Accuracy 0.8250 / Loss 0.448125\n",
      "Epoch 195 / Batch (3/17) / Accuracy 0.7600 / Loss 0.588926\n",
      "Epoch 195 / Batch (4/17) / Accuracy 0.8125 / Loss 0.469825\n",
      "Epoch 195 / Batch (5/17) / Accuracy 0.7962 / Loss 0.490111\n",
      "Epoch 195 / Batch (6/17) / Accuracy 0.8131 / Loss 0.488588\n",
      "Epoch 195 / Batch (7/17) / Accuracy 0.7831 / Loss 0.540794\n",
      "Epoch 195 / Batch (8/17) / Accuracy 0.8363 / Loss 0.421391\n",
      "Epoch 195 / Batch (9/17) / Accuracy 0.7987 / Loss 0.500139\n",
      "Epoch 195 / Batch (10/17) / Accuracy 0.7881 / Loss 0.560825\n",
      "Epoch 195 / Batch (11/17) / Accuracy 0.8169 / Loss 0.464586\n",
      "Epoch 195 / Batch (12/17) / Accuracy 0.7750 / Loss 0.575148\n",
      "Epoch 195 / Batch (13/17) / Accuracy 0.7731 / Loss 0.531643\n",
      "Epoch 195 / Batch (14/17) / Accuracy 0.8250 / Loss 0.445220\n",
      "Epoch 195 / Batch (15/17) / Accuracy 0.8219 / Loss 0.448977\n",
      "Epoch 195 / Batch (16/17) / Accuracy 0.7931 / Loss 0.510307\n",
      "Epoch 195 / Batch (17/17) / Accuracy 0.8381 / Loss 0.416842\n",
      "Epoch 195 complete, 6.6465163230896 seconds elapsed\n",
      "\n",
      "Epoch 196 starting..\n",
      "Epoch 196 / Batch (1/17) / Accuracy 0.7844 / Loss 0.531740\n",
      "Epoch 196 / Batch (2/17) / Accuracy 0.7788 / Loss 0.514010\n",
      "Epoch 196 / Batch (3/17) / Accuracy 0.8206 / Loss 0.436059\n",
      "Epoch 196 / Batch (4/17) / Accuracy 0.7994 / Loss 0.505424\n",
      "Epoch 196 / Batch (5/17) / Accuracy 0.7738 / Loss 0.548014\n",
      "Epoch 196 / Batch (6/17) / Accuracy 0.8313 / Loss 0.423438\n",
      "Epoch 196 / Batch (7/17) / Accuracy 0.7931 / Loss 0.500940\n",
      "Epoch 196 / Batch (8/17) / Accuracy 0.8006 / Loss 0.489546\n",
      "Epoch 196 / Batch (9/17) / Accuracy 0.8037 / Loss 0.504831\n",
      "Epoch 196 / Batch (10/17) / Accuracy 0.7987 / Loss 0.486402\n",
      "Epoch 196 / Batch (11/17) / Accuracy 0.7850 / Loss 0.506298\n",
      "Epoch 196 / Batch (12/17) / Accuracy 0.8206 / Loss 0.454200\n",
      "Epoch 196 / Batch (13/17) / Accuracy 0.8169 / Loss 0.470200\n",
      "Epoch 196 / Batch (14/17) / Accuracy 0.7887 / Loss 0.516794\n",
      "Epoch 196 / Batch (15/17) / Accuracy 0.7925 / Loss 0.517345\n",
      "Epoch 196 / Batch (16/17) / Accuracy 0.8094 / Loss 0.469370\n",
      "Epoch 196 / Batch (17/17) / Accuracy 0.7950 / Loss 0.531609\n",
      "Epoch 196 complete, 6.336901664733887 seconds elapsed\n",
      "\n",
      "Epoch 197 starting..\n",
      "Epoch 197 / Batch (1/17) / Accuracy 0.8587 / Loss 0.393109\n",
      "Epoch 197 / Batch (2/17) / Accuracy 0.8425 / Loss 0.434019\n",
      "Epoch 197 / Batch (3/17) / Accuracy 0.8300 / Loss 0.445617\n",
      "Epoch 197 / Batch (4/17) / Accuracy 0.8150 / Loss 0.480588\n",
      "Epoch 197 / Batch (5/17) / Accuracy 0.8294 / Loss 0.428967\n",
      "Epoch 197 / Batch (6/17) / Accuracy 0.8037 / Loss 0.534936\n",
      "Epoch 197 / Batch (7/17) / Accuracy 0.7819 / Loss 0.587020\n",
      "Epoch 197 / Batch (8/17) / Accuracy 0.8006 / Loss 0.481409\n",
      "Epoch 197 / Batch (9/17) / Accuracy 0.7850 / Loss 0.557878\n",
      "Epoch 197 / Batch (10/17) / Accuracy 0.7869 / Loss 0.540639\n",
      "Epoch 197 / Batch (11/17) / Accuracy 0.7994 / Loss 0.466509\n",
      "Epoch 197 / Batch (12/17) / Accuracy 0.7981 / Loss 0.500492\n",
      "Epoch 197 / Batch (13/17) / Accuracy 0.8062 / Loss 0.485734\n",
      "Epoch 197 / Batch (14/17) / Accuracy 0.7869 / Loss 0.511118\n",
      "Epoch 197 / Batch (15/17) / Accuracy 0.7894 / Loss 0.503635\n",
      "Epoch 197 / Batch (16/17) / Accuracy 0.7906 / Loss 0.533461\n",
      "Epoch 197 / Batch (17/17) / Accuracy 0.8056 / Loss 0.473666\n",
      "Epoch 197 complete, 6.7172839641571045 seconds elapsed\n",
      "\n",
      "Epoch 198 starting..\n",
      "Epoch 198 / Batch (1/17) / Accuracy 0.8025 / Loss 0.478409\n",
      "Epoch 198 / Batch (2/17) / Accuracy 0.8050 / Loss 0.468268\n",
      "Epoch 198 / Batch (3/17) / Accuracy 0.8075 / Loss 0.488806\n",
      "Epoch 198 / Batch (4/17) / Accuracy 0.8269 / Loss 0.420101\n",
      "Epoch 198 / Batch (5/17) / Accuracy 0.8100 / Loss 0.476064\n",
      "Epoch 198 / Batch (6/17) / Accuracy 0.8087 / Loss 0.469462\n",
      "Epoch 198 / Batch (7/17) / Accuracy 0.8112 / Loss 0.461083\n",
      "Epoch 198 / Batch (8/17) / Accuracy 0.8169 / Loss 0.490181\n",
      "Epoch 198 / Batch (9/17) / Accuracy 0.8213 / Loss 0.452465\n",
      "Epoch 198 / Batch (10/17) / Accuracy 0.8456 / Loss 0.431695\n",
      "Epoch 198 / Batch (11/17) / Accuracy 0.8188 / Loss 0.462953\n",
      "Epoch 198 / Batch (12/17) / Accuracy 0.8263 / Loss 0.440750\n",
      "Epoch 198 / Batch (13/17) / Accuracy 0.7875 / Loss 0.522192\n",
      "Epoch 198 / Batch (14/17) / Accuracy 0.7969 / Loss 0.492160\n",
      "Epoch 198 / Batch (15/17) / Accuracy 0.8275 / Loss 0.436849\n",
      "Epoch 198 / Batch (16/17) / Accuracy 0.7944 / Loss 0.540714\n",
      "Epoch 198 / Batch (17/17) / Accuracy 0.8163 / Loss 0.463074\n",
      "Epoch 198 complete, 6.598716735839844 seconds elapsed\n",
      "\n",
      "Epoch 199 starting..\n",
      "Epoch 199 / Batch (1/17) / Accuracy 0.7987 / Loss 0.496181\n",
      "Epoch 199 / Batch (2/17) / Accuracy 0.8194 / Loss 0.460659\n",
      "Epoch 199 / Batch (3/17) / Accuracy 0.8519 / Loss 0.412244\n",
      "Epoch 199 / Batch (4/17) / Accuracy 0.8350 / Loss 0.424823\n",
      "Epoch 199 / Batch (5/17) / Accuracy 0.7837 / Loss 0.571973\n",
      "Epoch 199 / Batch (6/17) / Accuracy 0.7925 / Loss 0.533682\n",
      "Epoch 199 / Batch (7/17) / Accuracy 0.8175 / Loss 0.462450\n",
      "Epoch 199 / Batch (8/17) / Accuracy 0.8238 / Loss 0.459862\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 199 / Batch (9/17) / Accuracy 0.8219 / Loss 0.448000\n",
      "Epoch 199 / Batch (10/17) / Accuracy 0.8419 / Loss 0.416292\n",
      "Epoch 199 / Batch (11/17) / Accuracy 0.8025 / Loss 0.483695\n",
      "Epoch 199 / Batch (12/17) / Accuracy 0.8000 / Loss 0.512354\n",
      "Epoch 199 / Batch (13/17) / Accuracy 0.7862 / Loss 0.530842\n",
      "Epoch 199 / Batch (14/17) / Accuracy 0.8213 / Loss 0.470594\n",
      "Epoch 199 / Batch (15/17) / Accuracy 0.8131 / Loss 0.465403\n",
      "Epoch 199 / Batch (16/17) / Accuracy 0.7781 / Loss 0.570146\n",
      "Epoch 199 / Batch (17/17) / Accuracy 0.7987 / Loss 0.503926\n",
      "Epoch 199 complete, 6.553985834121704 seconds elapsed\n",
      "\n",
      "Epoch 200 starting..\n",
      "Epoch 200 / Batch (1/17) / Accuracy 0.8219 / Loss 0.451674\n",
      "Epoch 200 / Batch (2/17) / Accuracy 0.7906 / Loss 0.528641\n",
      "Epoch 200 / Batch (3/17) / Accuracy 0.7825 / Loss 0.543741\n",
      "Epoch 200 / Batch (4/17) / Accuracy 0.8206 / Loss 0.472859\n",
      "Epoch 200 / Batch (5/17) / Accuracy 0.8056 / Loss 0.504474\n",
      "Epoch 200 / Batch (6/17) / Accuracy 0.7731 / Loss 0.564456\n",
      "Epoch 200 / Batch (7/17) / Accuracy 0.8169 / Loss 0.449125\n",
      "Epoch 200 / Batch (8/17) / Accuracy 0.7987 / Loss 0.486309\n",
      "Epoch 200 / Batch (9/17) / Accuracy 0.8081 / Loss 0.486626\n",
      "Epoch 200 / Batch (10/17) / Accuracy 0.7713 / Loss 0.552147\n",
      "Epoch 200 / Batch (11/17) / Accuracy 0.7769 / Loss 0.561458\n",
      "Epoch 200 / Batch (12/17) / Accuracy 0.7600 / Loss 0.574824\n",
      "Epoch 200 / Batch (13/17) / Accuracy 0.8406 / Loss 0.419334\n",
      "Epoch 200 / Batch (14/17) / Accuracy 0.8175 / Loss 0.459170\n",
      "Epoch 200 / Batch (15/17) / Accuracy 0.8244 / Loss 0.425752\n",
      "Epoch 200 / Batch (16/17) / Accuracy 0.7869 / Loss 0.512794\n",
      "Epoch 200 / Batch (17/17) / Accuracy 0.7969 / Loss 0.488152\n",
      "Epoch 200 complete, 6.335416793823242 seconds elapsed\n",
      "\n",
      "Epoch 201 starting..\n",
      "Epoch 201 / Batch (1/17) / Accuracy 0.8106 / Loss 0.458782\n",
      "Epoch 201 / Batch (2/17) / Accuracy 0.7919 / Loss 0.514382\n",
      "Epoch 201 / Batch (3/17) / Accuracy 0.8006 / Loss 0.508248\n",
      "Epoch 201 / Batch (4/17) / Accuracy 0.7881 / Loss 0.482265\n",
      "Epoch 201 / Batch (5/17) / Accuracy 0.8363 / Loss 0.430419\n",
      "Epoch 201 / Batch (6/17) / Accuracy 0.7900 / Loss 0.530037\n",
      "Epoch 201 / Batch (7/17) / Accuracy 0.8256 / Loss 0.448876\n",
      "Epoch 201 / Batch (8/17) / Accuracy 0.7900 / Loss 0.536379\n",
      "Epoch 201 / Batch (9/17) / Accuracy 0.8338 / Loss 0.426523\n",
      "Epoch 201 / Batch (10/17) / Accuracy 0.7850 / Loss 0.551493\n",
      "Epoch 201 / Batch (11/17) / Accuracy 0.7812 / Loss 0.537643\n",
      "Epoch 201 / Batch (12/17) / Accuracy 0.7775 / Loss 0.556448\n",
      "Epoch 201 / Batch (13/17) / Accuracy 0.8094 / Loss 0.467211\n",
      "Epoch 201 / Batch (14/17) / Accuracy 0.7588 / Loss 0.575933\n",
      "Epoch 201 / Batch (15/17) / Accuracy 0.8194 / Loss 0.481268\n",
      "Epoch 201 / Batch (16/17) / Accuracy 0.8294 / Loss 0.437347\n",
      "Epoch 201 / Batch (17/17) / Accuracy 0.8044 / Loss 0.487029\n",
      "Epoch 201 complete, 6.620690822601318 seconds elapsed\n",
      "\n",
      "Epoch 202 starting..\n",
      "Epoch 202 / Batch (1/17) / Accuracy 0.7875 / Loss 0.533790\n",
      "Epoch 202 / Batch (2/17) / Accuracy 0.8112 / Loss 0.488324\n",
      "Epoch 202 / Batch (3/17) / Accuracy 0.8306 / Loss 0.424508\n",
      "Epoch 202 / Batch (4/17) / Accuracy 0.8156 / Loss 0.485854\n",
      "Epoch 202 / Batch (5/17) / Accuracy 0.8087 / Loss 0.519002\n",
      "Epoch 202 / Batch (6/17) / Accuracy 0.7825 / Loss 0.520968\n",
      "Epoch 202 / Batch (7/17) / Accuracy 0.7694 / Loss 0.554010\n",
      "Epoch 202 / Batch (8/17) / Accuracy 0.7731 / Loss 0.524987\n",
      "Epoch 202 / Batch (9/17) / Accuracy 0.8144 / Loss 0.483100\n",
      "Epoch 202 / Batch (10/17) / Accuracy 0.7987 / Loss 0.496588\n",
      "Epoch 202 / Batch (11/17) / Accuracy 0.7931 / Loss 0.545472\n",
      "Epoch 202 / Batch (12/17) / Accuracy 0.8050 / Loss 0.503528\n",
      "Epoch 202 / Batch (13/17) / Accuracy 0.8181 / Loss 0.476830\n",
      "Epoch 202 / Batch (14/17) / Accuracy 0.7588 / Loss 0.591412\n",
      "Epoch 202 / Batch (15/17) / Accuracy 0.8000 / Loss 0.481620\n",
      "Epoch 202 / Batch (16/17) / Accuracy 0.8106 / Loss 0.484435\n",
      "Epoch 202 / Batch (17/17) / Accuracy 0.8025 / Loss 0.471538\n",
      "Epoch 202 complete, 6.415594577789307 seconds elapsed\n",
      "\n",
      "Epoch 203 starting..\n",
      "Epoch 203 / Batch (1/17) / Accuracy 0.8106 / Loss 0.474513\n",
      "Epoch 203 / Batch (2/17) / Accuracy 0.7969 / Loss 0.509893\n",
      "Epoch 203 / Batch (3/17) / Accuracy 0.8119 / Loss 0.485891\n",
      "Epoch 203 / Batch (4/17) / Accuracy 0.7862 / Loss 0.524681\n",
      "Epoch 203 / Batch (5/17) / Accuracy 0.7550 / Loss 0.579489\n",
      "Epoch 203 / Batch (6/17) / Accuracy 0.8181 / Loss 0.466498\n",
      "Epoch 203 / Batch (7/17) / Accuracy 0.8250 / Loss 0.427151\n",
      "Epoch 203 / Batch (8/17) / Accuracy 0.8100 / Loss 0.463173\n",
      "Epoch 203 / Batch (9/17) / Accuracy 0.8206 / Loss 0.477104\n",
      "Epoch 203 / Batch (10/17) / Accuracy 0.8062 / Loss 0.489898\n",
      "Epoch 203 / Batch (11/17) / Accuracy 0.8000 / Loss 0.490321\n",
      "Epoch 203 / Batch (12/17) / Accuracy 0.7769 / Loss 0.512106\n",
      "Epoch 203 / Batch (13/17) / Accuracy 0.8281 / Loss 0.441412\n",
      "Epoch 203 / Batch (14/17) / Accuracy 0.8081 / Loss 0.490654\n",
      "Epoch 203 / Batch (15/17) / Accuracy 0.7806 / Loss 0.527225\n",
      "Epoch 203 / Batch (16/17) / Accuracy 0.8331 / Loss 0.429713\n",
      "Epoch 203 / Batch (17/17) / Accuracy 0.8050 / Loss 0.485504\n",
      "Epoch 203 complete, 6.895278453826904 seconds elapsed\n",
      "\n",
      "Epoch 204 starting..\n",
      "Epoch 204 / Batch (1/17) / Accuracy 0.8087 / Loss 0.463990\n",
      "Epoch 204 / Batch (2/17) / Accuracy 0.8025 / Loss 0.491005\n",
      "Epoch 204 / Batch (3/17) / Accuracy 0.8075 / Loss 0.491436\n",
      "Epoch 204 / Batch (4/17) / Accuracy 0.8206 / Loss 0.439406\n",
      "Epoch 204 / Batch (5/17) / Accuracy 0.8138 / Loss 0.459076\n",
      "Epoch 204 / Batch (6/17) / Accuracy 0.7994 / Loss 0.513466\n",
      "Epoch 204 / Batch (7/17) / Accuracy 0.8281 / Loss 0.465968\n",
      "Epoch 204 / Batch (8/17) / Accuracy 0.7912 / Loss 0.510537\n",
      "Epoch 204 / Batch (9/17) / Accuracy 0.8106 / Loss 0.474854\n",
      "Epoch 204 / Batch (10/17) / Accuracy 0.8294 / Loss 0.441396\n",
      "Epoch 204 / Batch (11/17) / Accuracy 0.7788 / Loss 0.568406\n",
      "Epoch 204 / Batch (12/17) / Accuracy 0.7912 / Loss 0.522076\n",
      "Epoch 204 / Batch (13/17) / Accuracy 0.7763 / Loss 0.547373\n",
      "Epoch 204 / Batch (14/17) / Accuracy 0.8144 / Loss 0.445897\n",
      "Epoch 204 / Batch (15/17) / Accuracy 0.8225 / Loss 0.450906\n",
      "Epoch 204 / Batch (16/17) / Accuracy 0.8106 / Loss 0.473883\n",
      "Epoch 204 / Batch (17/17) / Accuracy 0.8225 / Loss 0.456856\n",
      "Epoch 204 complete, 6.53618597984314 seconds elapsed\n",
      "\n",
      "Epoch 205 starting..\n",
      "Epoch 205 / Batch (1/17) / Accuracy 0.8075 / Loss 0.483614\n",
      "Epoch 205 / Batch (2/17) / Accuracy 0.8338 / Loss 0.449496\n",
      "Epoch 205 / Batch (3/17) / Accuracy 0.8012 / Loss 0.464199\n",
      "Epoch 205 / Batch (4/17) / Accuracy 0.8156 / Loss 0.469069\n",
      "Epoch 205 / Batch (5/17) / Accuracy 0.8169 / Loss 0.450322\n",
      "Epoch 205 / Batch (6/17) / Accuracy 0.7862 / Loss 0.492037\n",
      "Epoch 205 / Batch (7/17) / Accuracy 0.7937 / Loss 0.513605\n",
      "Epoch 205 / Batch (8/17) / Accuracy 0.8244 / Loss 0.430816\n",
      "Epoch 205 / Batch (9/17) / Accuracy 0.8006 / Loss 0.495251\n",
      "Epoch 205 / Batch (10/17) / Accuracy 0.8281 / Loss 0.464199\n",
      "Epoch 205 / Batch (11/17) / Accuracy 0.8363 / Loss 0.437090\n",
      "Epoch 205 / Batch (12/17) / Accuracy 0.8269 / Loss 0.429808\n",
      "Epoch 205 / Batch (13/17) / Accuracy 0.8000 / Loss 0.506332\n",
      "Epoch 205 / Batch (14/17) / Accuracy 0.7975 / Loss 0.520931\n",
      "Epoch 205 / Batch (15/17) / Accuracy 0.7800 / Loss 0.526563\n",
      "Epoch 205 / Batch (16/17) / Accuracy 0.8175 / Loss 0.484794\n",
      "Epoch 205 / Batch (17/17) / Accuracy 0.8219 / Loss 0.446999\n",
      "Epoch 205 complete, 5.944817543029785 seconds elapsed\n",
      "\n",
      "Epoch 206 starting..\n",
      "Epoch 206 / Batch (1/17) / Accuracy 0.8025 / Loss 0.497737\n",
      "Epoch 206 / Batch (2/17) / Accuracy 0.8281 / Loss 0.419513\n",
      "Epoch 206 / Batch (3/17) / Accuracy 0.8213 / Loss 0.444809\n",
      "Epoch 206 / Batch (4/17) / Accuracy 0.7788 / Loss 0.566415\n",
      "Epoch 206 / Batch (5/17) / Accuracy 0.8331 / Loss 0.426062\n",
      "Epoch 206 / Batch (6/17) / Accuracy 0.8213 / Loss 0.445624\n",
      "Epoch 206 / Batch (7/17) / Accuracy 0.8244 / Loss 0.425893\n",
      "Epoch 206 / Batch (8/17) / Accuracy 0.8525 / Loss 0.416838\n",
      "Epoch 206 / Batch (9/17) / Accuracy 0.8225 / Loss 0.460987\n",
      "Epoch 206 / Batch (10/17) / Accuracy 0.8219 / Loss 0.450030\n",
      "Epoch 206 / Batch (11/17) / Accuracy 0.8188 / Loss 0.443522\n",
      "Epoch 206 / Batch (12/17) / Accuracy 0.8100 / Loss 0.489334\n",
      "Epoch 206 / Batch (13/17) / Accuracy 0.8106 / Loss 0.487678\n",
      "Epoch 206 / Batch (14/17) / Accuracy 0.7850 / Loss 0.522185\n",
      "Epoch 206 / Batch (15/17) / Accuracy 0.8119 / Loss 0.483783\n",
      "Epoch 206 / Batch (16/17) / Accuracy 0.8094 / Loss 0.477584\n",
      "Epoch 206 / Batch (17/17) / Accuracy 0.8181 / Loss 0.457228\n",
      "Epoch 206 complete, 6.3587963581085205 seconds elapsed\n",
      "\n",
      "Epoch 207 starting..\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 207 / Batch (1/17) / Accuracy 0.8169 / Loss 0.461575\n",
      "Epoch 207 / Batch (2/17) / Accuracy 0.8188 / Loss 0.468706\n",
      "Epoch 207 / Batch (3/17) / Accuracy 0.8006 / Loss 0.494443\n",
      "Epoch 207 / Batch (4/17) / Accuracy 0.8381 / Loss 0.421549\n",
      "Epoch 207 / Batch (5/17) / Accuracy 0.7900 / Loss 0.524547\n",
      "Epoch 207 / Batch (6/17) / Accuracy 0.8331 / Loss 0.422096\n",
      "Epoch 207 / Batch (7/17) / Accuracy 0.8119 / Loss 0.477846\n",
      "Epoch 207 / Batch (8/17) / Accuracy 0.8306 / Loss 0.451224\n",
      "Epoch 207 / Batch (9/17) / Accuracy 0.8238 / Loss 0.446365\n",
      "Epoch 207 / Batch (10/17) / Accuracy 0.8406 / Loss 0.423202\n",
      "Epoch 207 / Batch (11/17) / Accuracy 0.8050 / Loss 0.487152\n",
      "Epoch 207 / Batch (12/17) / Accuracy 0.8087 / Loss 0.465671\n",
      "Epoch 207 / Batch (13/17) / Accuracy 0.8050 / Loss 0.478793\n",
      "Epoch 207 / Batch (14/17) / Accuracy 0.7862 / Loss 0.505297\n",
      "Epoch 207 / Batch (15/17) / Accuracy 0.8094 / Loss 0.461280\n",
      "Epoch 207 / Batch (16/17) / Accuracy 0.8125 / Loss 0.460548\n",
      "Epoch 207 / Batch (17/17) / Accuracy 0.8081 / Loss 0.479556\n",
      "Epoch 207 complete, 6.610924243927002 seconds elapsed\n",
      "\n",
      "Epoch 208 starting..\n",
      "Epoch 208 / Batch (1/17) / Accuracy 0.8075 / Loss 0.472062\n",
      "Epoch 208 / Batch (2/17) / Accuracy 0.8119 / Loss 0.464234\n",
      "Epoch 208 / Batch (3/17) / Accuracy 0.8269 / Loss 0.445345\n",
      "Epoch 208 / Batch (4/17) / Accuracy 0.8044 / Loss 0.491629\n",
      "Epoch 208 / Batch (5/17) / Accuracy 0.7850 / Loss 0.559737\n",
      "Epoch 208 / Batch (6/17) / Accuracy 0.7856 / Loss 0.503186\n",
      "Epoch 208 / Batch (7/17) / Accuracy 0.8094 / Loss 0.467056\n",
      "Epoch 208 / Batch (8/17) / Accuracy 0.8150 / Loss 0.471808\n",
      "Epoch 208 / Batch (9/17) / Accuracy 0.8156 / Loss 0.501669\n",
      "Epoch 208 / Batch (10/17) / Accuracy 0.8206 / Loss 0.463531\n",
      "Epoch 208 / Batch (11/17) / Accuracy 0.7819 / Loss 0.540766\n",
      "Epoch 208 / Batch (12/17) / Accuracy 0.7744 / Loss 0.551056\n",
      "Epoch 208 / Batch (13/17) / Accuracy 0.8100 / Loss 0.478641\n",
      "Epoch 208 / Batch (14/17) / Accuracy 0.7775 / Loss 0.514435\n",
      "Epoch 208 / Batch (15/17) / Accuracy 0.7931 / Loss 0.481554\n",
      "Epoch 208 / Batch (16/17) / Accuracy 0.8044 / Loss 0.475495\n",
      "Epoch 208 / Batch (17/17) / Accuracy 0.7981 / Loss 0.486968\n",
      "Epoch 208 complete, 5.742303371429443 seconds elapsed\n",
      "\n",
      "Epoch 209 starting..\n",
      "Epoch 209 / Batch (1/17) / Accuracy 0.7887 / Loss 0.490509\n",
      "Epoch 209 / Batch (2/17) / Accuracy 0.7744 / Loss 0.556258\n",
      "Epoch 209 / Batch (3/17) / Accuracy 0.8213 / Loss 0.451442\n",
      "Epoch 209 / Batch (4/17) / Accuracy 0.8256 / Loss 0.444420\n",
      "Epoch 209 / Batch (5/17) / Accuracy 0.8306 / Loss 0.433516\n",
      "Epoch 209 / Batch (6/17) / Accuracy 0.8175 / Loss 0.456071\n",
      "Epoch 209 / Batch (7/17) / Accuracy 0.7850 / Loss 0.511231\n",
      "Epoch 209 / Batch (8/17) / Accuracy 0.8094 / Loss 0.491940\n",
      "Epoch 209 / Batch (9/17) / Accuracy 0.8200 / Loss 0.488253\n",
      "Epoch 209 / Batch (10/17) / Accuracy 0.8050 / Loss 0.504344\n",
      "Epoch 209 / Batch (11/17) / Accuracy 0.8100 / Loss 0.496911\n",
      "Epoch 209 / Batch (12/17) / Accuracy 0.8175 / Loss 0.471938\n",
      "Epoch 209 / Batch (13/17) / Accuracy 0.8106 / Loss 0.520780\n",
      "Epoch 209 / Batch (14/17) / Accuracy 0.8044 / Loss 0.491026\n",
      "Epoch 209 / Batch (15/17) / Accuracy 0.8169 / Loss 0.467452\n",
      "Epoch 209 / Batch (16/17) / Accuracy 0.8394 / Loss 0.443928\n",
      "Epoch 209 / Batch (17/17) / Accuracy 0.8100 / Loss 0.466971\n",
      "Epoch 209 complete, 6.308520078659058 seconds elapsed\n",
      "\n",
      "Epoch 210 starting..\n",
      "Epoch 210 / Batch (1/17) / Accuracy 0.8163 / Loss 0.462691\n",
      "Epoch 210 / Batch (2/17) / Accuracy 0.8087 / Loss 0.475677\n",
      "Epoch 210 / Batch (3/17) / Accuracy 0.7969 / Loss 0.487050\n",
      "Epoch 210 / Batch (4/17) / Accuracy 0.8194 / Loss 0.455329\n",
      "Epoch 210 / Batch (5/17) / Accuracy 0.8131 / Loss 0.471208\n",
      "Epoch 210 / Batch (6/17) / Accuracy 0.8431 / Loss 0.405895\n",
      "Epoch 210 / Batch (7/17) / Accuracy 0.8131 / Loss 0.447047\n",
      "Epoch 210 / Batch (8/17) / Accuracy 0.8231 / Loss 0.446852\n",
      "Epoch 210 / Batch (9/17) / Accuracy 0.8444 / Loss 0.401232\n",
      "Epoch 210 / Batch (10/17) / Accuracy 0.8044 / Loss 0.498960\n",
      "Epoch 210 / Batch (11/17) / Accuracy 0.8150 / Loss 0.465537\n",
      "Epoch 210 / Batch (12/17) / Accuracy 0.8044 / Loss 0.490078\n",
      "Epoch 210 / Batch (13/17) / Accuracy 0.7962 / Loss 0.525114\n",
      "Epoch 210 / Batch (14/17) / Accuracy 0.8106 / Loss 0.466724\n",
      "Epoch 210 / Batch (15/17) / Accuracy 0.8044 / Loss 0.481391\n",
      "Epoch 210 / Batch (16/17) / Accuracy 0.8087 / Loss 0.481511\n",
      "Epoch 210 / Batch (17/17) / Accuracy 0.8106 / Loss 0.476124\n",
      "Epoch 210 complete, 6.709208965301514 seconds elapsed\n",
      "\n",
      "Epoch 211 starting..\n",
      "Epoch 211 / Batch (1/17) / Accuracy 0.8313 / Loss 0.414514\n",
      "Epoch 211 / Batch (2/17) / Accuracy 0.8006 / Loss 0.472003\n",
      "Epoch 211 / Batch (3/17) / Accuracy 0.8206 / Loss 0.452389\n",
      "Epoch 211 / Batch (4/17) / Accuracy 0.7962 / Loss 0.490435\n",
      "Epoch 211 / Batch (5/17) / Accuracy 0.8100 / Loss 0.471848\n",
      "Epoch 211 / Batch (6/17) / Accuracy 0.8225 / Loss 0.440282\n",
      "Epoch 211 / Batch (7/17) / Accuracy 0.8350 / Loss 0.431993\n",
      "Epoch 211 / Batch (8/17) / Accuracy 0.8481 / Loss 0.410008\n",
      "Epoch 211 / Batch (9/17) / Accuracy 0.8306 / Loss 0.429042\n",
      "Epoch 211 / Batch (10/17) / Accuracy 0.7981 / Loss 0.487493\n",
      "Epoch 211 / Batch (11/17) / Accuracy 0.8456 / Loss 0.390785\n",
      "Epoch 211 / Batch (12/17) / Accuracy 0.8056 / Loss 0.484090\n",
      "Epoch 211 / Batch (13/17) / Accuracy 0.7981 / Loss 0.481362\n",
      "Epoch 211 / Batch (14/17) / Accuracy 0.8138 / Loss 0.474424\n",
      "Epoch 211 / Batch (15/17) / Accuracy 0.8206 / Loss 0.465820\n",
      "Epoch 211 / Batch (16/17) / Accuracy 0.7987 / Loss 0.497698\n",
      "Epoch 211 / Batch (17/17) / Accuracy 0.8425 / Loss 0.412163\n",
      "Epoch 211 complete, 6.771120548248291 seconds elapsed\n",
      "\n",
      "Epoch 212 starting..\n",
      "Epoch 212 / Batch (1/17) / Accuracy 0.7912 / Loss 0.515275\n",
      "Epoch 212 / Batch (2/17) / Accuracy 0.8344 / Loss 0.415666\n",
      "Epoch 212 / Batch (3/17) / Accuracy 0.7969 / Loss 0.495161\n",
      "Epoch 212 / Batch (4/17) / Accuracy 0.8344 / Loss 0.438726\n",
      "Epoch 212 / Batch (5/17) / Accuracy 0.7619 / Loss 0.551235\n",
      "Epoch 212 / Batch (6/17) / Accuracy 0.7956 / Loss 0.502151\n",
      "Epoch 212 / Batch (7/17) / Accuracy 0.8375 / Loss 0.428591\n",
      "Epoch 212 / Batch (8/17) / Accuracy 0.8250 / Loss 0.448309\n",
      "Epoch 212 / Batch (9/17) / Accuracy 0.8394 / Loss 0.426848\n",
      "Epoch 212 / Batch (10/17) / Accuracy 0.7844 / Loss 0.527317\n",
      "Epoch 212 / Batch (11/17) / Accuracy 0.7950 / Loss 0.529434\n",
      "Epoch 212 / Batch (12/17) / Accuracy 0.8275 / Loss 0.443250\n",
      "Epoch 212 / Batch (13/17) / Accuracy 0.8069 / Loss 0.506162\n",
      "Epoch 212 / Batch (14/17) / Accuracy 0.7862 / Loss 0.526126\n",
      "Epoch 212 / Batch (15/17) / Accuracy 0.7981 / Loss 0.490623\n",
      "Epoch 212 / Batch (16/17) / Accuracy 0.8019 / Loss 0.467309\n",
      "Epoch 212 / Batch (17/17) / Accuracy 0.8081 / Loss 0.474927\n",
      "Epoch 212 complete, 6.239960432052612 seconds elapsed\n",
      "\n",
      "Epoch 213 starting..\n",
      "Epoch 213 / Batch (1/17) / Accuracy 0.8106 / Loss 0.487485\n",
      "Epoch 213 / Batch (2/17) / Accuracy 0.7894 / Loss 0.529194\n",
      "Epoch 213 / Batch (3/17) / Accuracy 0.8025 / Loss 0.493015\n",
      "Epoch 213 / Batch (4/17) / Accuracy 0.7794 / Loss 0.526409\n",
      "Epoch 213 / Batch (5/17) / Accuracy 0.7919 / Loss 0.570898\n",
      "Epoch 213 / Batch (6/17) / Accuracy 0.8163 / Loss 0.500817\n",
      "Epoch 213 / Batch (7/17) / Accuracy 0.8062 / Loss 0.489756\n",
      "Epoch 213 / Batch (8/17) / Accuracy 0.7900 / Loss 0.529882\n",
      "Epoch 213 / Batch (9/17) / Accuracy 0.8062 / Loss 0.473880\n",
      "Epoch 213 / Batch (10/17) / Accuracy 0.8087 / Loss 0.467123\n",
      "Epoch 213 / Batch (11/17) / Accuracy 0.8112 / Loss 0.490209\n",
      "Epoch 213 / Batch (12/17) / Accuracy 0.8025 / Loss 0.505488\n",
      "Epoch 213 / Batch (13/17) / Accuracy 0.8544 / Loss 0.414489\n",
      "Epoch 213 / Batch (14/17) / Accuracy 0.7794 / Loss 0.571112\n",
      "Epoch 213 / Batch (15/17) / Accuracy 0.8238 / Loss 0.463882\n",
      "Epoch 213 / Batch (16/17) / Accuracy 0.7950 / Loss 0.513587\n",
      "Epoch 213 / Batch (17/17) / Accuracy 0.8194 / Loss 0.451368\n",
      "Epoch 213 complete, 6.558390855789185 seconds elapsed\n",
      "\n",
      "Epoch 214 starting..\n",
      "Epoch 214 / Batch (1/17) / Accuracy 0.8012 / Loss 0.533255\n",
      "Epoch 214 / Batch (2/17) / Accuracy 0.8044 / Loss 0.496585\n",
      "Epoch 214 / Batch (3/17) / Accuracy 0.8081 / Loss 0.497442\n",
      "Epoch 214 / Batch (4/17) / Accuracy 0.8112 / Loss 0.476634\n",
      "Epoch 214 / Batch (5/17) / Accuracy 0.8019 / Loss 0.473669\n",
      "Epoch 214 / Batch (6/17) / Accuracy 0.8431 / Loss 0.427016\n",
      "Epoch 214 / Batch (7/17) / Accuracy 0.8062 / Loss 0.522458\n",
      "Epoch 214 / Batch (8/17) / Accuracy 0.7994 / Loss 0.485491\n",
      "Epoch 214 / Batch (9/17) / Accuracy 0.7731 / Loss 0.555225\n",
      "Epoch 214 / Batch (10/17) / Accuracy 0.8562 / Loss 0.382449\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 214 / Batch (11/17) / Accuracy 0.8056 / Loss 0.469657\n",
      "Epoch 214 / Batch (12/17) / Accuracy 0.7969 / Loss 0.486111\n",
      "Epoch 214 / Batch (13/17) / Accuracy 0.8319 / Loss 0.421217\n",
      "Epoch 214 / Batch (14/17) / Accuracy 0.8119 / Loss 0.474195\n",
      "Epoch 214 / Batch (15/17) / Accuracy 0.8037 / Loss 0.470743\n",
      "Epoch 214 / Batch (16/17) / Accuracy 0.7925 / Loss 0.522423\n",
      "Epoch 214 / Batch (17/17) / Accuracy 0.8406 / Loss 0.414722\n",
      "Epoch 214 complete, 6.6569859981536865 seconds elapsed\n",
      "\n",
      "Epoch 215 starting..\n",
      "Epoch 215 / Batch (1/17) / Accuracy 0.8238 / Loss 0.440256\n",
      "Epoch 215 / Batch (2/17) / Accuracy 0.8044 / Loss 0.472309\n",
      "Epoch 215 / Batch (3/17) / Accuracy 0.7850 / Loss 0.546666\n",
      "Epoch 215 / Batch (4/17) / Accuracy 0.8031 / Loss 0.469056\n",
      "Epoch 215 / Batch (5/17) / Accuracy 0.7894 / Loss 0.488983\n",
      "Epoch 215 / Batch (6/17) / Accuracy 0.8100 / Loss 0.487711\n",
      "Epoch 215 / Batch (7/17) / Accuracy 0.8044 / Loss 0.447336\n",
      "Epoch 215 / Batch (8/17) / Accuracy 0.8031 / Loss 0.488987\n",
      "Epoch 215 / Batch (9/17) / Accuracy 0.8050 / Loss 0.480324\n",
      "Epoch 215 / Batch (10/17) / Accuracy 0.8075 / Loss 0.481909\n",
      "Epoch 215 / Batch (11/17) / Accuracy 0.8331 / Loss 0.433326\n",
      "Epoch 215 / Batch (12/17) / Accuracy 0.8269 / Loss 0.441760\n",
      "Epoch 215 / Batch (13/17) / Accuracy 0.8200 / Loss 0.462332\n",
      "Epoch 215 / Batch (14/17) / Accuracy 0.8131 / Loss 0.479362\n",
      "Epoch 215 / Batch (15/17) / Accuracy 0.7900 / Loss 0.528137\n",
      "Epoch 215 / Batch (16/17) / Accuracy 0.8169 / Loss 0.469235\n",
      "Epoch 215 / Batch (17/17) / Accuracy 0.8125 / Loss 0.480192\n",
      "Epoch 215 complete, 6.3490846157073975 seconds elapsed\n",
      "\n",
      "Epoch 216 starting..\n",
      "Epoch 216 / Batch (1/17) / Accuracy 0.7525 / Loss 0.575059\n",
      "Epoch 216 / Batch (2/17) / Accuracy 0.8163 / Loss 0.438779\n",
      "Epoch 216 / Batch (3/17) / Accuracy 0.8125 / Loss 0.469809\n",
      "Epoch 216 / Batch (4/17) / Accuracy 0.8350 / Loss 0.432166\n",
      "Epoch 216 / Batch (5/17) / Accuracy 0.8019 / Loss 0.469497\n",
      "Epoch 216 / Batch (6/17) / Accuracy 0.7969 / Loss 0.483852\n",
      "Epoch 216 / Batch (7/17) / Accuracy 0.8163 / Loss 0.424471\n",
      "Epoch 216 / Batch (8/17) / Accuracy 0.8175 / Loss 0.452061\n",
      "Epoch 216 / Batch (9/17) / Accuracy 0.8175 / Loss 0.455813\n",
      "Epoch 216 / Batch (10/17) / Accuracy 0.8231 / Loss 0.446188\n",
      "Epoch 216 / Batch (11/17) / Accuracy 0.8231 / Loss 0.449963\n",
      "Epoch 216 / Batch (12/17) / Accuracy 0.8150 / Loss 0.470329\n",
      "Epoch 216 / Batch (13/17) / Accuracy 0.8481 / Loss 0.407513\n",
      "Epoch 216 / Batch (14/17) / Accuracy 0.8081 / Loss 0.479729\n",
      "Epoch 216 / Batch (15/17) / Accuracy 0.8138 / Loss 0.452716\n",
      "Epoch 216 / Batch (16/17) / Accuracy 0.8225 / Loss 0.434583\n",
      "Epoch 216 / Batch (17/17) / Accuracy 0.8219 / Loss 0.470781\n",
      "Epoch 216 complete, 6.719647645950317 seconds elapsed\n",
      "\n",
      "Epoch 217 starting..\n",
      "Epoch 217 / Batch (1/17) / Accuracy 0.8244 / Loss 0.466585\n",
      "Epoch 217 / Batch (2/17) / Accuracy 0.8188 / Loss 0.442710\n",
      "Epoch 217 / Batch (3/17) / Accuracy 0.7869 / Loss 0.494878\n",
      "Epoch 217 / Batch (4/17) / Accuracy 0.7925 / Loss 0.516711\n",
      "Epoch 217 / Batch (5/17) / Accuracy 0.8094 / Loss 0.466107\n",
      "Epoch 217 / Batch (6/17) / Accuracy 0.8263 / Loss 0.438040\n",
      "Epoch 217 / Batch (7/17) / Accuracy 0.8087 / Loss 0.502397\n",
      "Epoch 217 / Batch (8/17) / Accuracy 0.8219 / Loss 0.474263\n",
      "Epoch 217 / Batch (9/17) / Accuracy 0.8238 / Loss 0.441776\n",
      "Epoch 217 / Batch (10/17) / Accuracy 0.7581 / Loss 0.562914\n",
      "Epoch 217 / Batch (11/17) / Accuracy 0.7819 / Loss 0.550508\n",
      "Epoch 217 / Batch (12/17) / Accuracy 0.8131 / Loss 0.478176\n",
      "Epoch 217 / Batch (13/17) / Accuracy 0.8338 / Loss 0.447025\n",
      "Epoch 217 / Batch (14/17) / Accuracy 0.8081 / Loss 0.505460\n",
      "Epoch 217 / Batch (15/17) / Accuracy 0.8419 / Loss 0.423115\n",
      "Epoch 217 / Batch (16/17) / Accuracy 0.7856 / Loss 0.522413\n",
      "Epoch 217 / Batch (17/17) / Accuracy 0.7825 / Loss 0.509044\n",
      "Epoch 217 complete, 6.33081579208374 seconds elapsed\n",
      "\n",
      "Epoch 218 starting..\n",
      "Epoch 218 / Batch (1/17) / Accuracy 0.8238 / Loss 0.438714\n",
      "Epoch 218 / Batch (2/17) / Accuracy 0.8263 / Loss 0.431288\n",
      "Epoch 218 / Batch (3/17) / Accuracy 0.8031 / Loss 0.491026\n",
      "Epoch 218 / Batch (4/17) / Accuracy 0.8025 / Loss 0.480312\n",
      "Epoch 218 / Batch (5/17) / Accuracy 0.8056 / Loss 0.480467\n",
      "Epoch 218 / Batch (6/17) / Accuracy 0.8406 / Loss 0.413440\n",
      "Epoch 218 / Batch (7/17) / Accuracy 0.7725 / Loss 0.545320\n",
      "Epoch 218 / Batch (8/17) / Accuracy 0.8131 / Loss 0.493561\n",
      "Epoch 218 / Batch (9/17) / Accuracy 0.8288 / Loss 0.431672\n",
      "Epoch 218 / Batch (10/17) / Accuracy 0.7806 / Loss 0.528227\n",
      "Epoch 218 / Batch (11/17) / Accuracy 0.7837 / Loss 0.506681\n",
      "Epoch 218 / Batch (12/17) / Accuracy 0.8169 / Loss 0.459841\n",
      "Epoch 218 / Batch (13/17) / Accuracy 0.7763 / Loss 0.547237\n",
      "Epoch 218 / Batch (14/17) / Accuracy 0.8400 / Loss 0.411079\n",
      "Epoch 218 / Batch (15/17) / Accuracy 0.8388 / Loss 0.421136\n",
      "Epoch 218 / Batch (16/17) / Accuracy 0.8112 / Loss 0.458845\n",
      "Epoch 218 / Batch (17/17) / Accuracy 0.7944 / Loss 0.538142\n",
      "Epoch 218 complete, 6.1666693687438965 seconds elapsed\n",
      "\n",
      "Epoch 219 starting..\n",
      "Epoch 219 / Batch (1/17) / Accuracy 0.8062 / Loss 0.482076\n",
      "Epoch 219 / Batch (2/17) / Accuracy 0.8106 / Loss 0.456735\n",
      "Epoch 219 / Batch (3/17) / Accuracy 0.7763 / Loss 0.545491\n",
      "Epoch 219 / Batch (4/17) / Accuracy 0.7788 / Loss 0.535005\n",
      "Epoch 219 / Batch (5/17) / Accuracy 0.8056 / Loss 0.501410\n",
      "Epoch 219 / Batch (6/17) / Accuracy 0.8006 / Loss 0.486904\n",
      "Epoch 219 / Batch (7/17) / Accuracy 0.8325 / Loss 0.411890\n",
      "Epoch 219 / Batch (8/17) / Accuracy 0.7738 / Loss 0.563857\n",
      "Epoch 219 / Batch (9/17) / Accuracy 0.8219 / Loss 0.446303\n",
      "Epoch 219 / Batch (10/17) / Accuracy 0.7862 / Loss 0.518667\n",
      "Epoch 219 / Batch (11/17) / Accuracy 0.7969 / Loss 0.500941\n",
      "Epoch 219 / Batch (12/17) / Accuracy 0.7931 / Loss 0.511550\n",
      "Epoch 219 / Batch (13/17) / Accuracy 0.7962 / Loss 0.475228\n",
      "Epoch 219 / Batch (14/17) / Accuracy 0.7781 / Loss 0.549323\n",
      "Epoch 219 / Batch (15/17) / Accuracy 0.8219 / Loss 0.435141\n",
      "Epoch 219 / Batch (16/17) / Accuracy 0.7925 / Loss 0.518766\n",
      "Epoch 219 / Batch (17/17) / Accuracy 0.8231 / Loss 0.444814\n",
      "Epoch 219 complete, 6.560866117477417 seconds elapsed\n",
      "\n",
      "Epoch 220 starting..\n",
      "Epoch 220 / Batch (1/17) / Accuracy 0.7981 / Loss 0.496623\n",
      "Epoch 220 / Batch (2/17) / Accuracy 0.8050 / Loss 0.490922\n",
      "Epoch 220 / Batch (3/17) / Accuracy 0.8125 / Loss 0.466720\n",
      "Epoch 220 / Batch (4/17) / Accuracy 0.7825 / Loss 0.534819\n",
      "Epoch 220 / Batch (5/17) / Accuracy 0.8125 / Loss 0.485838\n",
      "Epoch 220 / Batch (6/17) / Accuracy 0.8169 / Loss 0.434727\n",
      "Epoch 220 / Batch (7/17) / Accuracy 0.7769 / Loss 0.557059\n",
      "Epoch 220 / Batch (8/17) / Accuracy 0.8213 / Loss 0.450861\n",
      "Epoch 220 / Batch (9/17) / Accuracy 0.8050 / Loss 0.487240\n",
      "Epoch 220 / Batch (10/17) / Accuracy 0.8106 / Loss 0.489578\n",
      "Epoch 220 / Batch (11/17) / Accuracy 0.7850 / Loss 0.512719\n",
      "Epoch 220 / Batch (12/17) / Accuracy 0.8413 / Loss 0.438835\n",
      "Epoch 220 / Batch (13/17) / Accuracy 0.8175 / Loss 0.461663\n",
      "Epoch 220 / Batch (14/17) / Accuracy 0.8150 / Loss 0.460376\n",
      "Epoch 220 / Batch (15/17) / Accuracy 0.7919 / Loss 0.519490\n",
      "Epoch 220 / Batch (16/17) / Accuracy 0.7800 / Loss 0.559150\n",
      "Epoch 220 / Batch (17/17) / Accuracy 0.7594 / Loss 0.536158\n",
      "Epoch 220 complete, 6.3213114738464355 seconds elapsed\n",
      "\n",
      "Epoch 221 starting..\n",
      "Epoch 221 / Batch (1/17) / Accuracy 0.7669 / Loss 0.551136\n",
      "Epoch 221 / Batch (2/17) / Accuracy 0.7887 / Loss 0.521508\n",
      "Epoch 221 / Batch (3/17) / Accuracy 0.8244 / Loss 0.432954\n",
      "Epoch 221 / Batch (4/17) / Accuracy 0.8250 / Loss 0.466414\n",
      "Epoch 221 / Batch (5/17) / Accuracy 0.8050 / Loss 0.463981\n",
      "Epoch 221 / Batch (6/17) / Accuracy 0.7862 / Loss 0.527231\n",
      "Epoch 221 / Batch (7/17) / Accuracy 0.7937 / Loss 0.497204\n",
      "Epoch 221 / Batch (8/17) / Accuracy 0.8169 / Loss 0.452481\n",
      "Epoch 221 / Batch (9/17) / Accuracy 0.8350 / Loss 0.400928\n",
      "Epoch 221 / Batch (10/17) / Accuracy 0.8138 / Loss 0.441620\n",
      "Epoch 221 / Batch (11/17) / Accuracy 0.8150 / Loss 0.475174\n",
      "Epoch 221 / Batch (12/17) / Accuracy 0.7925 / Loss 0.505763\n",
      "Epoch 221 / Batch (13/17) / Accuracy 0.8225 / Loss 0.460934\n",
      "Epoch 221 / Batch (14/17) / Accuracy 0.8363 / Loss 0.410933\n",
      "Epoch 221 / Batch (15/17) / Accuracy 0.8131 / Loss 0.469991\n",
      "Epoch 221 / Batch (16/17) / Accuracy 0.7894 / Loss 0.509195\n",
      "Epoch 221 / Batch (17/17) / Accuracy 0.8213 / Loss 0.474253\n",
      "Epoch 221 complete, 7.020813465118408 seconds elapsed\n",
      "\n",
      "Epoch 222 starting..\n",
      "Epoch 222 / Batch (1/17) / Accuracy 0.8000 / Loss 0.465692\n",
      "Epoch 222 / Batch (2/17) / Accuracy 0.7875 / Loss 0.520700\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 222 / Batch (3/17) / Accuracy 0.8375 / Loss 0.428790\n",
      "Epoch 222 / Batch (4/17) / Accuracy 0.7994 / Loss 0.488963\n",
      "Epoch 222 / Batch (5/17) / Accuracy 0.7769 / Loss 0.545941\n",
      "Epoch 222 / Batch (6/17) / Accuracy 0.8281 / Loss 0.439765\n",
      "Epoch 222 / Batch (7/17) / Accuracy 0.7925 / Loss 0.509055\n",
      "Epoch 222 / Batch (8/17) / Accuracy 0.8269 / Loss 0.453157\n",
      "Epoch 222 / Batch (9/17) / Accuracy 0.8256 / Loss 0.438113\n",
      "Epoch 222 / Batch (10/17) / Accuracy 0.8119 / Loss 0.481502\n",
      "Epoch 222 / Batch (11/17) / Accuracy 0.8419 / Loss 0.409285\n",
      "Epoch 222 / Batch (12/17) / Accuracy 0.8062 / Loss 0.483656\n",
      "Epoch 222 / Batch (13/17) / Accuracy 0.7962 / Loss 0.526736\n",
      "Epoch 222 / Batch (14/17) / Accuracy 0.7650 / Loss 0.591865\n",
      "Epoch 222 / Batch (15/17) / Accuracy 0.8181 / Loss 0.487924\n",
      "Epoch 222 / Batch (16/17) / Accuracy 0.7900 / Loss 0.527742\n",
      "Epoch 222 / Batch (17/17) / Accuracy 0.8112 / Loss 0.443790\n",
      "Epoch 222 complete, 6.878716230392456 seconds elapsed\n",
      "\n",
      "Epoch 223 starting..\n",
      "Epoch 223 / Batch (1/17) / Accuracy 0.8150 / Loss 0.468188\n",
      "Epoch 223 / Batch (2/17) / Accuracy 0.7675 / Loss 0.567061\n",
      "Epoch 223 / Batch (3/17) / Accuracy 0.7862 / Loss 0.538446\n",
      "Epoch 223 / Batch (4/17) / Accuracy 0.8350 / Loss 0.430434\n",
      "Epoch 223 / Batch (5/17) / Accuracy 0.7769 / Loss 0.544490\n",
      "Epoch 223 / Batch (6/17) / Accuracy 0.8469 / Loss 0.423147\n",
      "Epoch 223 / Batch (7/17) / Accuracy 0.7869 / Loss 0.544276\n",
      "Epoch 223 / Batch (8/17) / Accuracy 0.7881 / Loss 0.513768\n",
      "Epoch 223 / Batch (9/17) / Accuracy 0.8319 / Loss 0.444807\n",
      "Epoch 223 / Batch (10/17) / Accuracy 0.8100 / Loss 0.452322\n",
      "Epoch 223 / Batch (11/17) / Accuracy 0.8250 / Loss 0.465005\n",
      "Epoch 223 / Batch (12/17) / Accuracy 0.8238 / Loss 0.454719\n",
      "Epoch 223 / Batch (13/17) / Accuracy 0.8062 / Loss 0.476718\n",
      "Epoch 223 / Batch (14/17) / Accuracy 0.7919 / Loss 0.522053\n",
      "Epoch 223 / Batch (15/17) / Accuracy 0.8431 / Loss 0.408107\n",
      "Epoch 223 / Batch (16/17) / Accuracy 0.7937 / Loss 0.538811\n",
      "Epoch 223 / Batch (17/17) / Accuracy 0.8506 / Loss 0.389074\n",
      "Epoch 223 complete, 6.7810986042022705 seconds elapsed\n",
      "\n",
      "Epoch 224 starting..\n",
      "Epoch 224 / Batch (1/17) / Accuracy 0.8087 / Loss 0.483882\n",
      "Epoch 224 / Batch (2/17) / Accuracy 0.7706 / Loss 0.559874\n",
      "Epoch 224 / Batch (3/17) / Accuracy 0.8244 / Loss 0.435700\n",
      "Epoch 224 / Batch (4/17) / Accuracy 0.8375 / Loss 0.425225\n",
      "Epoch 224 / Batch (5/17) / Accuracy 0.8181 / Loss 0.460421\n",
      "Epoch 224 / Batch (6/17) / Accuracy 0.8325 / Loss 0.414195\n",
      "Epoch 224 / Batch (7/17) / Accuracy 0.7969 / Loss 0.467439\n",
      "Epoch 224 / Batch (8/17) / Accuracy 0.7881 / Loss 0.525638\n",
      "Epoch 224 / Batch (9/17) / Accuracy 0.8069 / Loss 0.474533\n",
      "Epoch 224 / Batch (10/17) / Accuracy 0.8131 / Loss 0.471111\n",
      "Epoch 224 / Batch (11/17) / Accuracy 0.8000 / Loss 0.487718\n",
      "Epoch 224 / Batch (12/17) / Accuracy 0.8194 / Loss 0.471698\n",
      "Epoch 224 / Batch (13/17) / Accuracy 0.7806 / Loss 0.545249\n",
      "Epoch 224 / Batch (14/17) / Accuracy 0.8331 / Loss 0.445098\n",
      "Epoch 224 / Batch (15/17) / Accuracy 0.8325 / Loss 0.442884\n",
      "Epoch 224 / Batch (16/17) / Accuracy 0.8131 / Loss 0.462252\n",
      "Epoch 224 / Batch (17/17) / Accuracy 0.7906 / Loss 0.475070\n",
      "Epoch 224 complete, 6.597101211547852 seconds elapsed\n",
      "\n",
      "Epoch 225 starting..\n",
      "Epoch 225 / Batch (1/17) / Accuracy 0.8263 / Loss 0.436871\n",
      "Epoch 225 / Batch (2/17) / Accuracy 0.8256 / Loss 0.430586\n",
      "Epoch 225 / Batch (3/17) / Accuracy 0.8138 / Loss 0.490660\n",
      "Epoch 225 / Batch (4/17) / Accuracy 0.7869 / Loss 0.518635\n",
      "Epoch 225 / Batch (5/17) / Accuracy 0.8219 / Loss 0.446474\n",
      "Epoch 225 / Batch (6/17) / Accuracy 0.7856 / Loss 0.542041\n",
      "Epoch 225 / Batch (7/17) / Accuracy 0.8119 / Loss 0.455767\n",
      "Epoch 225 / Batch (8/17) / Accuracy 0.8244 / Loss 0.463009\n",
      "Epoch 225 / Batch (9/17) / Accuracy 0.8181 / Loss 0.444580\n",
      "Epoch 225 / Batch (10/17) / Accuracy 0.8194 / Loss 0.442909\n",
      "Epoch 225 / Batch (11/17) / Accuracy 0.8213 / Loss 0.442503\n",
      "Epoch 225 / Batch (12/17) / Accuracy 0.8269 / Loss 0.435877\n",
      "Epoch 225 / Batch (13/17) / Accuracy 0.8200 / Loss 0.440631\n",
      "Epoch 225 / Batch (14/17) / Accuracy 0.8150 / Loss 0.482398\n",
      "Epoch 225 / Batch (15/17) / Accuracy 0.8188 / Loss 0.460915\n",
      "Epoch 225 / Batch (16/17) / Accuracy 0.8331 / Loss 0.431934\n",
      "Epoch 225 / Batch (17/17) / Accuracy 0.8062 / Loss 0.499054\n",
      "Epoch 225 complete, 6.755804061889648 seconds elapsed\n",
      "\n",
      "Epoch 226 starting..\n",
      "Epoch 226 / Batch (1/17) / Accuracy 0.7981 / Loss 0.484818\n",
      "Epoch 226 / Batch (2/17) / Accuracy 0.8138 / Loss 0.469673\n",
      "Epoch 226 / Batch (3/17) / Accuracy 0.8119 / Loss 0.484526\n",
      "Epoch 226 / Batch (4/17) / Accuracy 0.8075 / Loss 0.505347\n",
      "Epoch 226 / Batch (5/17) / Accuracy 0.8219 / Loss 0.473169\n",
      "Epoch 226 / Batch (6/17) / Accuracy 0.7975 / Loss 0.495311\n",
      "Epoch 226 / Batch (7/17) / Accuracy 0.8100 / Loss 0.493295\n",
      "Epoch 226 / Batch (8/17) / Accuracy 0.7919 / Loss 0.530520\n",
      "Epoch 226 / Batch (9/17) / Accuracy 0.8163 / Loss 0.457536\n",
      "Epoch 226 / Batch (10/17) / Accuracy 0.8288 / Loss 0.444657\n",
      "Epoch 226 / Batch (11/17) / Accuracy 0.8181 / Loss 0.458406\n",
      "Epoch 226 / Batch (12/17) / Accuracy 0.7862 / Loss 0.527653\n",
      "Epoch 226 / Batch (13/17) / Accuracy 0.8138 / Loss 0.467647\n",
      "Epoch 226 / Batch (14/17) / Accuracy 0.7769 / Loss 0.542244\n",
      "Epoch 226 / Batch (15/17) / Accuracy 0.7837 / Loss 0.547886\n",
      "Epoch 226 / Batch (16/17) / Accuracy 0.8394 / Loss 0.425569\n",
      "Epoch 226 / Batch (17/17) / Accuracy 0.7781 / Loss 0.544464\n",
      "Epoch 226 complete, 6.71436619758606 seconds elapsed\n",
      "\n",
      "Epoch 227 starting..\n",
      "Epoch 227 / Batch (1/17) / Accuracy 0.7856 / Loss 0.546749\n",
      "Epoch 227 / Batch (2/17) / Accuracy 0.8044 / Loss 0.490040\n",
      "Epoch 227 / Batch (3/17) / Accuracy 0.8263 / Loss 0.438253\n",
      "Epoch 227 / Batch (4/17) / Accuracy 0.8106 / Loss 0.481699\n",
      "Epoch 227 / Batch (5/17) / Accuracy 0.8069 / Loss 0.467770\n",
      "Epoch 227 / Batch (6/17) / Accuracy 0.8375 / Loss 0.404620\n",
      "Epoch 227 / Batch (7/17) / Accuracy 0.8200 / Loss 0.465550\n",
      "Epoch 227 / Batch (8/17) / Accuracy 0.8112 / Loss 0.473227\n",
      "Epoch 227 / Batch (9/17) / Accuracy 0.8369 / Loss 0.439579\n",
      "Epoch 227 / Batch (10/17) / Accuracy 0.8150 / Loss 0.475204\n",
      "Epoch 227 / Batch (11/17) / Accuracy 0.8338 / Loss 0.425623\n",
      "Epoch 227 / Batch (12/17) / Accuracy 0.7756 / Loss 0.542348\n",
      "Epoch 227 / Batch (13/17) / Accuracy 0.8369 / Loss 0.435618\n",
      "Epoch 227 / Batch (14/17) / Accuracy 0.8081 / Loss 0.473483\n",
      "Epoch 227 / Batch (15/17) / Accuracy 0.7881 / Loss 0.536655\n",
      "Epoch 227 / Batch (16/17) / Accuracy 0.8213 / Loss 0.455233\n",
      "Epoch 227 / Batch (17/17) / Accuracy 0.8288 / Loss 0.435083\n",
      "Epoch 227 complete, 6.107863187789917 seconds elapsed\n",
      "\n",
      "Epoch 228 starting..\n",
      "Epoch 228 / Batch (1/17) / Accuracy 0.8263 / Loss 0.439202\n",
      "Epoch 228 / Batch (2/17) / Accuracy 0.7713 / Loss 0.533954\n",
      "Epoch 228 / Batch (3/17) / Accuracy 0.7794 / Loss 0.550532\n",
      "Epoch 228 / Batch (4/17) / Accuracy 0.8338 / Loss 0.434332\n",
      "Epoch 228 / Batch (5/17) / Accuracy 0.8175 / Loss 0.469410\n",
      "Epoch 228 / Batch (6/17) / Accuracy 0.8081 / Loss 0.487888\n",
      "Epoch 228 / Batch (7/17) / Accuracy 0.7769 / Loss 0.534383\n",
      "Epoch 228 / Batch (8/17) / Accuracy 0.8175 / Loss 0.453424\n",
      "Epoch 228 / Batch (9/17) / Accuracy 0.8112 / Loss 0.468361\n",
      "Epoch 228 / Batch (10/17) / Accuracy 0.8181 / Loss 0.471645\n",
      "Epoch 228 / Batch (11/17) / Accuracy 0.8006 / Loss 0.518676\n",
      "Epoch 228 / Batch (12/17) / Accuracy 0.8244 / Loss 0.468591\n",
      "Epoch 228 / Batch (13/17) / Accuracy 0.7925 / Loss 0.502488\n",
      "Epoch 228 / Batch (14/17) / Accuracy 0.7912 / Loss 0.519108\n",
      "Epoch 228 / Batch (15/17) / Accuracy 0.7962 / Loss 0.520312\n",
      "Epoch 228 / Batch (16/17) / Accuracy 0.8144 / Loss 0.472985\n",
      "Epoch 228 / Batch (17/17) / Accuracy 0.8056 / Loss 0.475036\n",
      "Epoch 228 complete, 6.7652106285095215 seconds elapsed\n",
      "\n",
      "Epoch 229 starting..\n",
      "Epoch 229 / Batch (1/17) / Accuracy 0.8231 / Loss 0.459831\n",
      "Epoch 229 / Batch (2/17) / Accuracy 0.7875 / Loss 0.545296\n",
      "Epoch 229 / Batch (3/17) / Accuracy 0.8069 / Loss 0.461729\n",
      "Epoch 229 / Batch (4/17) / Accuracy 0.8131 / Loss 0.481604\n",
      "Epoch 229 / Batch (5/17) / Accuracy 0.8306 / Loss 0.428949\n",
      "Epoch 229 / Batch (6/17) / Accuracy 0.7975 / Loss 0.515088\n",
      "Epoch 229 / Batch (7/17) / Accuracy 0.8363 / Loss 0.430727\n",
      "Epoch 229 / Batch (8/17) / Accuracy 0.8400 / Loss 0.417586\n",
      "Epoch 229 / Batch (9/17) / Accuracy 0.8037 / Loss 0.497483\n",
      "Epoch 229 / Batch (10/17) / Accuracy 0.8131 / Loss 0.469524\n",
      "Epoch 229 / Batch (11/17) / Accuracy 0.8069 / Loss 0.511543\n",
      "Epoch 229 / Batch (12/17) / Accuracy 0.8288 / Loss 0.437536\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 229 / Batch (13/17) / Accuracy 0.8275 / Loss 0.441622\n",
      "Epoch 229 / Batch (14/17) / Accuracy 0.7744 / Loss 0.573014\n",
      "Epoch 229 / Batch (15/17) / Accuracy 0.7912 / Loss 0.520694\n",
      "Epoch 229 / Batch (16/17) / Accuracy 0.7850 / Loss 0.554527\n",
      "Epoch 229 / Batch (17/17) / Accuracy 0.7738 / Loss 0.539211\n",
      "Epoch 229 complete, 6.58453106880188 seconds elapsed\n",
      "\n",
      "Epoch 230 starting..\n",
      "Epoch 230 / Batch (1/17) / Accuracy 0.7544 / Loss 0.562306\n",
      "Epoch 230 / Batch (2/17) / Accuracy 0.7713 / Loss 0.538525\n",
      "Epoch 230 / Batch (3/17) / Accuracy 0.8112 / Loss 0.466689\n",
      "Epoch 230 / Batch (4/17) / Accuracy 0.8031 / Loss 0.476568\n",
      "Epoch 230 / Batch (5/17) / Accuracy 0.8250 / Loss 0.462378\n",
      "Epoch 230 / Batch (6/17) / Accuracy 0.7462 / Loss 0.587054\n",
      "Epoch 230 / Batch (7/17) / Accuracy 0.8244 / Loss 0.447410\n",
      "Epoch 230 / Batch (8/17) / Accuracy 0.7919 / Loss 0.517804\n",
      "Epoch 230 / Batch (9/17) / Accuracy 0.7912 / Loss 0.505611\n",
      "Epoch 230 / Batch (10/17) / Accuracy 0.8294 / Loss 0.450815\n",
      "Epoch 230 / Batch (11/17) / Accuracy 0.8269 / Loss 0.432414\n",
      "Epoch 230 / Batch (12/17) / Accuracy 0.8106 / Loss 0.472214\n",
      "Epoch 230 / Batch (13/17) / Accuracy 0.7769 / Loss 0.525850\n",
      "Epoch 230 / Batch (14/17) / Accuracy 0.7781 / Loss 0.513795\n",
      "Epoch 230 / Batch (15/17) / Accuracy 0.8156 / Loss 0.450655\n",
      "Epoch 230 / Batch (16/17) / Accuracy 0.7962 / Loss 0.488695\n",
      "Epoch 230 / Batch (17/17) / Accuracy 0.8163 / Loss 0.453072\n",
      "Epoch 230 complete, 6.278934955596924 seconds elapsed\n",
      "\n",
      "Epoch 231 starting..\n",
      "Epoch 231 / Batch (1/17) / Accuracy 0.8163 / Loss 0.484624\n",
      "Epoch 231 / Batch (2/17) / Accuracy 0.8356 / Loss 0.446041\n",
      "Epoch 231 / Batch (3/17) / Accuracy 0.8081 / Loss 0.505583\n",
      "Epoch 231 / Batch (4/17) / Accuracy 0.7744 / Loss 0.550041\n",
      "Epoch 231 / Batch (5/17) / Accuracy 0.8556 / Loss 0.412299\n",
      "Epoch 231 / Batch (6/17) / Accuracy 0.8150 / Loss 0.453110\n",
      "Epoch 231 / Batch (7/17) / Accuracy 0.7937 / Loss 0.498568\n",
      "Epoch 231 / Batch (8/17) / Accuracy 0.8175 / Loss 0.491394\n",
      "Epoch 231 / Batch (9/17) / Accuracy 0.8200 / Loss 0.480719\n",
      "Epoch 231 / Batch (10/17) / Accuracy 0.8138 / Loss 0.474460\n",
      "Epoch 231 / Batch (11/17) / Accuracy 0.7850 / Loss 0.522906\n",
      "Epoch 231 / Batch (12/17) / Accuracy 0.8144 / Loss 0.466201\n",
      "Epoch 231 / Batch (13/17) / Accuracy 0.7950 / Loss 0.536365\n",
      "Epoch 231 / Batch (14/17) / Accuracy 0.7894 / Loss 0.512671\n",
      "Epoch 231 / Batch (15/17) / Accuracy 0.8206 / Loss 0.452238\n",
      "Epoch 231 / Batch (16/17) / Accuracy 0.8169 / Loss 0.440838\n",
      "Epoch 231 / Batch (17/17) / Accuracy 0.8281 / Loss 0.469143\n",
      "Epoch 231 complete, 6.648499250411987 seconds elapsed\n",
      "\n",
      "Epoch 232 starting..\n",
      "Epoch 232 / Batch (1/17) / Accuracy 0.8131 / Loss 0.458497\n",
      "Epoch 232 / Batch (2/17) / Accuracy 0.7919 / Loss 0.482370\n",
      "Epoch 232 / Batch (3/17) / Accuracy 0.8106 / Loss 0.468823\n",
      "Epoch 232 / Batch (4/17) / Accuracy 0.7806 / Loss 0.523086\n",
      "Epoch 232 / Batch (5/17) / Accuracy 0.8281 / Loss 0.420804\n",
      "Epoch 232 / Batch (6/17) / Accuracy 0.8106 / Loss 0.463564\n",
      "Epoch 232 / Batch (7/17) / Accuracy 0.8131 / Loss 0.489753\n",
      "Epoch 232 / Batch (8/17) / Accuracy 0.8163 / Loss 0.514850\n",
      "Epoch 232 / Batch (9/17) / Accuracy 0.8438 / Loss 0.400025\n",
      "Epoch 232 / Batch (10/17) / Accuracy 0.8462 / Loss 0.401689\n",
      "Epoch 232 / Batch (11/17) / Accuracy 0.8462 / Loss 0.413439\n",
      "Epoch 232 / Batch (12/17) / Accuracy 0.8062 / Loss 0.473554\n",
      "Epoch 232 / Batch (13/17) / Accuracy 0.8450 / Loss 0.394711\n",
      "Epoch 232 / Batch (14/17) / Accuracy 0.7812 / Loss 0.529745\n",
      "Epoch 232 / Batch (15/17) / Accuracy 0.8019 / Loss 0.482643\n",
      "Epoch 232 / Batch (16/17) / Accuracy 0.8231 / Loss 0.457410\n",
      "Epoch 232 / Batch (17/17) / Accuracy 0.8163 / Loss 0.484159\n",
      "Epoch 232 complete, 6.749385118484497 seconds elapsed\n",
      "\n",
      "Epoch 233 starting..\n",
      "Epoch 233 / Batch (1/17) / Accuracy 0.8256 / Loss 0.443678\n",
      "Epoch 233 / Batch (2/17) / Accuracy 0.8119 / Loss 0.488051\n",
      "Epoch 233 / Batch (3/17) / Accuracy 0.8188 / Loss 0.454245\n",
      "Epoch 233 / Batch (4/17) / Accuracy 0.8069 / Loss 0.462865\n",
      "Epoch 233 / Batch (5/17) / Accuracy 0.8294 / Loss 0.467354\n",
      "Epoch 233 / Batch (6/17) / Accuracy 0.8019 / Loss 0.506836\n",
      "Epoch 233 / Batch (7/17) / Accuracy 0.8219 / Loss 0.472823\n",
      "Epoch 233 / Batch (8/17) / Accuracy 0.8288 / Loss 0.459751\n",
      "Epoch 233 / Batch (9/17) / Accuracy 0.7950 / Loss 0.493765\n",
      "Epoch 233 / Batch (10/17) / Accuracy 0.8325 / Loss 0.426486\n",
      "Epoch 233 / Batch (11/17) / Accuracy 0.8288 / Loss 0.442526\n",
      "Epoch 233 / Batch (12/17) / Accuracy 0.8119 / Loss 0.455503\n",
      "Epoch 233 / Batch (13/17) / Accuracy 0.7906 / Loss 0.512292\n",
      "Epoch 233 / Batch (14/17) / Accuracy 0.8188 / Loss 0.484652\n",
      "Epoch 233 / Batch (15/17) / Accuracy 0.8156 / Loss 0.491440\n",
      "Epoch 233 / Batch (16/17) / Accuracy 0.8325 / Loss 0.431556\n",
      "Epoch 233 / Batch (17/17) / Accuracy 0.8275 / Loss 0.428149\n",
      "Epoch 233 complete, 6.826503753662109 seconds elapsed\n",
      "\n",
      "Epoch 234 starting..\n",
      "Epoch 234 / Batch (1/17) / Accuracy 0.8138 / Loss 0.493507\n",
      "Epoch 234 / Batch (2/17) / Accuracy 0.8375 / Loss 0.413483\n",
      "Epoch 234 / Batch (3/17) / Accuracy 0.8450 / Loss 0.420924\n",
      "Epoch 234 / Batch (4/17) / Accuracy 0.8331 / Loss 0.419497\n",
      "Epoch 234 / Batch (5/17) / Accuracy 0.7763 / Loss 0.576173\n",
      "Epoch 234 / Batch (6/17) / Accuracy 0.8106 / Loss 0.463829\n",
      "Epoch 234 / Batch (7/17) / Accuracy 0.8363 / Loss 0.423570\n",
      "Epoch 234 / Batch (8/17) / Accuracy 0.8150 / Loss 0.450541\n",
      "Epoch 234 / Batch (9/17) / Accuracy 0.8025 / Loss 0.475560\n",
      "Epoch 234 / Batch (10/17) / Accuracy 0.8069 / Loss 0.514817\n",
      "Epoch 234 / Batch (11/17) / Accuracy 0.7894 / Loss 0.539132\n",
      "Epoch 234 / Batch (12/17) / Accuracy 0.7856 / Loss 0.512567\n",
      "Epoch 234 / Batch (13/17) / Accuracy 0.8081 / Loss 0.473025\n",
      "Epoch 234 / Batch (14/17) / Accuracy 0.8112 / Loss 0.447845\n",
      "Epoch 234 / Batch (15/17) / Accuracy 0.8394 / Loss 0.412842\n",
      "Epoch 234 / Batch (16/17) / Accuracy 0.7706 / Loss 0.512498\n",
      "Epoch 234 / Batch (17/17) / Accuracy 0.8219 / Loss 0.460667\n",
      "Epoch 234 complete, 7.154684782028198 seconds elapsed\n",
      "\n",
      "Epoch 235 starting..\n",
      "Epoch 235 / Batch (1/17) / Accuracy 0.8544 / Loss 0.398711\n",
      "Epoch 235 / Batch (2/17) / Accuracy 0.8338 / Loss 0.430383\n",
      "Epoch 235 / Batch (3/17) / Accuracy 0.8031 / Loss 0.490655\n",
      "Epoch 235 / Batch (4/17) / Accuracy 0.8131 / Loss 0.479844\n",
      "Epoch 235 / Batch (5/17) / Accuracy 0.8069 / Loss 0.486141\n",
      "Epoch 235 / Batch (6/17) / Accuracy 0.8144 / Loss 0.484549\n",
      "Epoch 235 / Batch (7/17) / Accuracy 0.8331 / Loss 0.445457\n",
      "Epoch 235 / Batch (8/17) / Accuracy 0.8300 / Loss 0.433447\n",
      "Epoch 235 / Batch (9/17) / Accuracy 0.8163 / Loss 0.460251\n",
      "Epoch 235 / Batch (10/17) / Accuracy 0.8181 / Loss 0.498191\n",
      "Epoch 235 / Batch (11/17) / Accuracy 0.8225 / Loss 0.465591\n",
      "Epoch 235 / Batch (12/17) / Accuracy 0.8587 / Loss 0.382181\n",
      "Epoch 235 / Batch (13/17) / Accuracy 0.8044 / Loss 0.490796\n",
      "Epoch 235 / Batch (14/17) / Accuracy 0.8012 / Loss 0.503814\n",
      "Epoch 235 / Batch (15/17) / Accuracy 0.8125 / Loss 0.461145\n",
      "Epoch 235 / Batch (16/17) / Accuracy 0.7756 / Loss 0.537898\n",
      "Epoch 235 / Batch (17/17) / Accuracy 0.8388 / Loss 0.424266\n",
      "Epoch 235 complete, 6.4012980461120605 seconds elapsed\n",
      "\n",
      "Epoch 236 starting..\n",
      "Epoch 236 / Batch (1/17) / Accuracy 0.7850 / Loss 0.518388\n",
      "Epoch 236 / Batch (2/17) / Accuracy 0.7825 / Loss 0.546102\n",
      "Epoch 236 / Batch (3/17) / Accuracy 0.8069 / Loss 0.495268\n",
      "Epoch 236 / Batch (4/17) / Accuracy 0.8512 / Loss 0.404233\n",
      "Epoch 236 / Batch (5/17) / Accuracy 0.7919 / Loss 0.521024\n",
      "Epoch 236 / Batch (6/17) / Accuracy 0.7937 / Loss 0.517877\n",
      "Epoch 236 / Batch (7/17) / Accuracy 0.8150 / Loss 0.484019\n",
      "Epoch 236 / Batch (8/17) / Accuracy 0.8006 / Loss 0.470551\n",
      "Epoch 236 / Batch (9/17) / Accuracy 0.8169 / Loss 0.465415\n",
      "Epoch 236 / Batch (10/17) / Accuracy 0.8163 / Loss 0.456450\n",
      "Epoch 236 / Batch (11/17) / Accuracy 0.8550 / Loss 0.397024\n",
      "Epoch 236 / Batch (12/17) / Accuracy 0.8369 / Loss 0.433511\n",
      "Epoch 236 / Batch (13/17) / Accuracy 0.7950 / Loss 0.527874\n",
      "Epoch 236 / Batch (14/17) / Accuracy 0.8050 / Loss 0.495624\n",
      "Epoch 236 / Batch (15/17) / Accuracy 0.7831 / Loss 0.528583\n",
      "Epoch 236 / Batch (16/17) / Accuracy 0.7962 / Loss 0.546154\n",
      "Epoch 236 / Batch (17/17) / Accuracy 0.7831 / Loss 0.507901\n",
      "Epoch 236 complete, 6.593378305435181 seconds elapsed\n",
      "\n",
      "Epoch 237 starting..\n",
      "Epoch 237 / Batch (1/17) / Accuracy 0.8188 / Loss 0.450254\n",
      "Epoch 237 / Batch (2/17) / Accuracy 0.8125 / Loss 0.465237\n",
      "Epoch 237 / Batch (3/17) / Accuracy 0.8138 / Loss 0.478081\n",
      "Epoch 237 / Batch (4/17) / Accuracy 0.7944 / Loss 0.496361\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 237 / Batch (5/17) / Accuracy 0.8369 / Loss 0.415593\n",
      "Epoch 237 / Batch (6/17) / Accuracy 0.8087 / Loss 0.463537\n",
      "Epoch 237 / Batch (7/17) / Accuracy 0.8675 / Loss 0.381626\n",
      "Epoch 237 / Batch (8/17) / Accuracy 0.7763 / Loss 0.513750\n",
      "Epoch 237 / Batch (9/17) / Accuracy 0.8000 / Loss 0.479450\n",
      "Epoch 237 / Batch (10/17) / Accuracy 0.8238 / Loss 0.440078\n",
      "Epoch 237 / Batch (11/17) / Accuracy 0.8644 / Loss 0.375679\n",
      "Epoch 237 / Batch (12/17) / Accuracy 0.8056 / Loss 0.491243\n",
      "Epoch 237 / Batch (13/17) / Accuracy 0.8494 / Loss 0.413689\n",
      "Epoch 237 / Batch (14/17) / Accuracy 0.8194 / Loss 0.482061\n",
      "Epoch 237 / Batch (15/17) / Accuracy 0.8025 / Loss 0.496030\n",
      "Epoch 237 / Batch (16/17) / Accuracy 0.7981 / Loss 0.514981\n",
      "Epoch 237 / Batch (17/17) / Accuracy 0.8150 / Loss 0.468816\n",
      "Epoch 237 complete, 6.182999610900879 seconds elapsed\n",
      "\n",
      "Epoch 238 starting..\n",
      "Epoch 238 / Batch (1/17) / Accuracy 0.8131 / Loss 0.468761\n",
      "Epoch 238 / Batch (2/17) / Accuracy 0.8288 / Loss 0.425298\n",
      "Epoch 238 / Batch (3/17) / Accuracy 0.8219 / Loss 0.453188\n",
      "Epoch 238 / Batch (4/17) / Accuracy 0.7931 / Loss 0.521605\n",
      "Epoch 238 / Batch (5/17) / Accuracy 0.8344 / Loss 0.413980\n",
      "Epoch 238 / Batch (6/17) / Accuracy 0.8263 / Loss 0.465810\n",
      "Epoch 238 / Batch (7/17) / Accuracy 0.8275 / Loss 0.428963\n",
      "Epoch 238 / Batch (8/17) / Accuracy 0.7887 / Loss 0.509819\n",
      "Epoch 238 / Batch (9/17) / Accuracy 0.7900 / Loss 0.514504\n",
      "Epoch 238 / Batch (10/17) / Accuracy 0.8056 / Loss 0.474642\n",
      "Epoch 238 / Batch (11/17) / Accuracy 0.7975 / Loss 0.505191\n",
      "Epoch 238 / Batch (12/17) / Accuracy 0.8206 / Loss 0.447250\n",
      "Epoch 238 / Batch (13/17) / Accuracy 0.7650 / Loss 0.578776\n",
      "Epoch 238 / Batch (14/17) / Accuracy 0.7900 / Loss 0.531496\n",
      "Epoch 238 / Batch (15/17) / Accuracy 0.8081 / Loss 0.447360\n",
      "Epoch 238 / Batch (16/17) / Accuracy 0.7750 / Loss 0.522009\n",
      "Epoch 238 / Batch (17/17) / Accuracy 0.8025 / Loss 0.503764\n",
      "Epoch 238 complete, 6.597192764282227 seconds elapsed\n",
      "\n",
      "Epoch 239 starting..\n",
      "Epoch 239 / Batch (1/17) / Accuracy 0.8025 / Loss 0.494992\n",
      "Epoch 239 / Batch (2/17) / Accuracy 0.8175 / Loss 0.487960\n",
      "Epoch 239 / Batch (3/17) / Accuracy 0.8131 / Loss 0.442905\n",
      "Epoch 239 / Batch (4/17) / Accuracy 0.7894 / Loss 0.519830\n",
      "Epoch 239 / Batch (5/17) / Accuracy 0.8413 / Loss 0.408986\n",
      "Epoch 239 / Batch (6/17) / Accuracy 0.7919 / Loss 0.503347\n",
      "Epoch 239 / Batch (7/17) / Accuracy 0.7631 / Loss 0.560249\n",
      "Epoch 239 / Batch (8/17) / Accuracy 0.8081 / Loss 0.534084\n",
      "Epoch 239 / Batch (9/17) / Accuracy 0.8206 / Loss 0.479005\n",
      "Epoch 239 / Batch (10/17) / Accuracy 0.8037 / Loss 0.494050\n",
      "Epoch 239 / Batch (11/17) / Accuracy 0.8600 / Loss 0.368551\n",
      "Epoch 239 / Batch (12/17) / Accuracy 0.8119 / Loss 0.458114\n",
      "Epoch 239 / Batch (13/17) / Accuracy 0.7856 / Loss 0.539461\n",
      "Epoch 239 / Batch (14/17) / Accuracy 0.8100 / Loss 0.490496\n",
      "Epoch 239 / Batch (15/17) / Accuracy 0.8125 / Loss 0.472839\n",
      "Epoch 239 / Batch (16/17) / Accuracy 0.8231 / Loss 0.479016\n",
      "Epoch 239 / Batch (17/17) / Accuracy 0.8313 / Loss 0.436572\n",
      "Epoch 239 complete, 6.3443896770477295 seconds elapsed\n",
      "\n",
      "Epoch 240 starting..\n",
      "Epoch 240 / Batch (1/17) / Accuracy 0.8406 / Loss 0.422714\n",
      "Epoch 240 / Batch (2/17) / Accuracy 0.8194 / Loss 0.473840\n",
      "Epoch 240 / Batch (3/17) / Accuracy 0.8200 / Loss 0.433733\n",
      "Epoch 240 / Batch (4/17) / Accuracy 0.8400 / Loss 0.435281\n",
      "Epoch 240 / Batch (5/17) / Accuracy 0.8087 / Loss 0.484969\n",
      "Epoch 240 / Batch (6/17) / Accuracy 0.8144 / Loss 0.469043\n",
      "Epoch 240 / Batch (7/17) / Accuracy 0.8356 / Loss 0.434383\n",
      "Epoch 240 / Batch (8/17) / Accuracy 0.8181 / Loss 0.462768\n",
      "Epoch 240 / Batch (9/17) / Accuracy 0.8200 / Loss 0.457402\n",
      "Epoch 240 / Batch (10/17) / Accuracy 0.7800 / Loss 0.546681\n",
      "Epoch 240 / Batch (11/17) / Accuracy 0.8356 / Loss 0.435894\n",
      "Epoch 240 / Batch (12/17) / Accuracy 0.8069 / Loss 0.482637\n",
      "Epoch 240 / Batch (13/17) / Accuracy 0.8306 / Loss 0.422364\n",
      "Epoch 240 / Batch (14/17) / Accuracy 0.7862 / Loss 0.529769\n",
      "Epoch 240 / Batch (15/17) / Accuracy 0.8219 / Loss 0.448139\n",
      "Epoch 240 / Batch (16/17) / Accuracy 0.7894 / Loss 0.529143\n",
      "Epoch 240 / Batch (17/17) / Accuracy 0.8069 / Loss 0.476748\n",
      "Epoch 240 complete, 6.341634511947632 seconds elapsed\n",
      "\n",
      "Epoch 241 starting..\n",
      "Epoch 241 / Batch (1/17) / Accuracy 0.7994 / Loss 0.505878\n",
      "Epoch 241 / Batch (2/17) / Accuracy 0.7969 / Loss 0.498960\n",
      "Epoch 241 / Batch (3/17) / Accuracy 0.8456 / Loss 0.425814\n",
      "Epoch 241 / Batch (4/17) / Accuracy 0.8062 / Loss 0.442666\n",
      "Epoch 241 / Batch (5/17) / Accuracy 0.8037 / Loss 0.463126\n",
      "Epoch 241 / Batch (6/17) / Accuracy 0.8019 / Loss 0.492009\n",
      "Epoch 241 / Batch (7/17) / Accuracy 0.7937 / Loss 0.517648\n",
      "Epoch 241 / Batch (8/17) / Accuracy 0.7619 / Loss 0.559660\n",
      "Epoch 241 / Batch (9/17) / Accuracy 0.8100 / Loss 0.452284\n",
      "Epoch 241 / Batch (10/17) / Accuracy 0.7987 / Loss 0.465170\n",
      "Epoch 241 / Batch (11/17) / Accuracy 0.8056 / Loss 0.532062\n",
      "Epoch 241 / Batch (12/17) / Accuracy 0.8344 / Loss 0.447488\n",
      "Epoch 241 / Batch (13/17) / Accuracy 0.8313 / Loss 0.434906\n",
      "Epoch 241 / Batch (14/17) / Accuracy 0.8081 / Loss 0.469815\n",
      "Epoch 241 / Batch (15/17) / Accuracy 0.8044 / Loss 0.464827\n",
      "Epoch 241 / Batch (16/17) / Accuracy 0.8325 / Loss 0.456794\n",
      "Epoch 241 / Batch (17/17) / Accuracy 0.8125 / Loss 0.469329\n",
      "Epoch 241 complete, 6.56286883354187 seconds elapsed\n",
      "\n",
      "Epoch 242 starting..\n",
      "Epoch 242 / Batch (1/17) / Accuracy 0.8225 / Loss 0.473223\n",
      "Epoch 242 / Batch (2/17) / Accuracy 0.8244 / Loss 0.439445\n",
      "Epoch 242 / Batch (3/17) / Accuracy 0.8413 / Loss 0.413094\n",
      "Epoch 242 / Batch (4/17) / Accuracy 0.7731 / Loss 0.541605\n",
      "Epoch 242 / Batch (5/17) / Accuracy 0.7763 / Loss 0.523722\n",
      "Epoch 242 / Batch (6/17) / Accuracy 0.8281 / Loss 0.474846\n",
      "Epoch 242 / Batch (7/17) / Accuracy 0.7950 / Loss 0.485550\n",
      "Epoch 242 / Batch (8/17) / Accuracy 0.8000 / Loss 0.489151\n",
      "Epoch 242 / Batch (9/17) / Accuracy 0.8206 / Loss 0.473570\n",
      "Epoch 242 / Batch (10/17) / Accuracy 0.8194 / Loss 0.462654\n",
      "Epoch 242 / Batch (11/17) / Accuracy 0.8175 / Loss 0.452212\n",
      "Epoch 242 / Batch (12/17) / Accuracy 0.7912 / Loss 0.513801\n",
      "Epoch 242 / Batch (13/17) / Accuracy 0.7912 / Loss 0.527890\n",
      "Epoch 242 / Batch (14/17) / Accuracy 0.7869 / Loss 0.539575\n",
      "Epoch 242 / Batch (15/17) / Accuracy 0.8225 / Loss 0.451453\n",
      "Epoch 242 / Batch (16/17) / Accuracy 0.7919 / Loss 0.523231\n",
      "Epoch 242 / Batch (17/17) / Accuracy 0.8062 / Loss 0.503455\n",
      "Epoch 242 complete, 6.724134683609009 seconds elapsed\n",
      "\n",
      "Epoch 243 starting..\n",
      "Epoch 243 / Batch (1/17) / Accuracy 0.8256 / Loss 0.434490\n",
      "Epoch 243 / Batch (2/17) / Accuracy 0.8356 / Loss 0.423253\n",
      "Epoch 243 / Batch (3/17) / Accuracy 0.8181 / Loss 0.481039\n",
      "Epoch 243 / Batch (4/17) / Accuracy 0.8181 / Loss 0.473388\n",
      "Epoch 243 / Batch (5/17) / Accuracy 0.8094 / Loss 0.446048\n",
      "Epoch 243 / Batch (6/17) / Accuracy 0.8194 / Loss 0.443058\n",
      "Epoch 243 / Batch (7/17) / Accuracy 0.8200 / Loss 0.458527\n",
      "Epoch 243 / Batch (8/17) / Accuracy 0.8194 / Loss 0.476950\n",
      "Epoch 243 / Batch (9/17) / Accuracy 0.8269 / Loss 0.462953\n",
      "Epoch 243 / Batch (10/17) / Accuracy 0.8500 / Loss 0.382317\n",
      "Epoch 243 / Batch (11/17) / Accuracy 0.8150 / Loss 0.456207\n",
      "Epoch 243 / Batch (12/17) / Accuracy 0.7900 / Loss 0.538018\n",
      "Epoch 243 / Batch (13/17) / Accuracy 0.7831 / Loss 0.524336\n",
      "Epoch 243 / Batch (14/17) / Accuracy 0.8037 / Loss 0.478998\n",
      "Epoch 243 / Batch (15/17) / Accuracy 0.8531 / Loss 0.392135\n",
      "Epoch 243 / Batch (16/17) / Accuracy 0.7969 / Loss 0.467692\n",
      "Epoch 243 / Batch (17/17) / Accuracy 0.8200 / Loss 0.464130\n",
      "Epoch 243 complete, 6.208540201187134 seconds elapsed\n",
      "\n",
      "Epoch 244 starting..\n",
      "Epoch 244 / Batch (1/17) / Accuracy 0.7781 / Loss 0.510530\n",
      "Epoch 244 / Batch (2/17) / Accuracy 0.8325 / Loss 0.428798\n",
      "Epoch 244 / Batch (3/17) / Accuracy 0.8100 / Loss 0.459945\n",
      "Epoch 244 / Batch (4/17) / Accuracy 0.8256 / Loss 0.441613\n",
      "Epoch 244 / Batch (5/17) / Accuracy 0.8281 / Loss 0.443603\n",
      "Epoch 244 / Batch (6/17) / Accuracy 0.8244 / Loss 0.453957\n",
      "Epoch 244 / Batch (7/17) / Accuracy 0.7869 / Loss 0.519325\n",
      "Epoch 244 / Batch (8/17) / Accuracy 0.8181 / Loss 0.463605\n",
      "Epoch 244 / Batch (9/17) / Accuracy 0.8288 / Loss 0.456419\n",
      "Epoch 244 / Batch (10/17) / Accuracy 0.7794 / Loss 0.542550\n",
      "Epoch 244 / Batch (11/17) / Accuracy 0.8138 / Loss 0.472061\n",
      "Epoch 244 / Batch (12/17) / Accuracy 0.8300 / Loss 0.439146\n",
      "Epoch 244 / Batch (13/17) / Accuracy 0.8119 / Loss 0.477704\n",
      "Epoch 244 / Batch (14/17) / Accuracy 0.8138 / Loss 0.462426\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 244 / Batch (15/17) / Accuracy 0.8350 / Loss 0.425595\n",
      "Epoch 244 / Batch (16/17) / Accuracy 0.8012 / Loss 0.501647\n",
      "Epoch 244 / Batch (17/17) / Accuracy 0.8037 / Loss 0.507027\n",
      "Epoch 244 complete, 6.171422481536865 seconds elapsed\n",
      "\n",
      "Epoch 245 starting..\n",
      "Epoch 245 / Batch (1/17) / Accuracy 0.8200 / Loss 0.458002\n",
      "Epoch 245 / Batch (2/17) / Accuracy 0.8156 / Loss 0.469583\n",
      "Epoch 245 / Batch (3/17) / Accuracy 0.8156 / Loss 0.469401\n",
      "Epoch 245 / Batch (4/17) / Accuracy 0.8125 / Loss 0.471134\n",
      "Epoch 245 / Batch (5/17) / Accuracy 0.8238 / Loss 0.424251\n",
      "Epoch 245 / Batch (6/17) / Accuracy 0.8288 / Loss 0.434093\n",
      "Epoch 245 / Batch (7/17) / Accuracy 0.8194 / Loss 0.479518\n",
      "Epoch 245 / Batch (8/17) / Accuracy 0.7931 / Loss 0.504012\n",
      "Epoch 245 / Batch (9/17) / Accuracy 0.7663 / Loss 0.560952\n",
      "Epoch 245 / Batch (10/17) / Accuracy 0.8338 / Loss 0.433432\n",
      "Epoch 245 / Batch (11/17) / Accuracy 0.8288 / Loss 0.411528\n",
      "Epoch 245 / Batch (12/17) / Accuracy 0.7906 / Loss 0.493410\n",
      "Epoch 245 / Batch (13/17) / Accuracy 0.8344 / Loss 0.438468\n",
      "Epoch 245 / Batch (14/17) / Accuracy 0.8087 / Loss 0.464302\n",
      "Epoch 245 / Batch (15/17) / Accuracy 0.8075 / Loss 0.519684\n",
      "Epoch 245 / Batch (16/17) / Accuracy 0.8106 / Loss 0.487725\n",
      "Epoch 245 / Batch (17/17) / Accuracy 0.8525 / Loss 0.385780\n",
      "Epoch 245 complete, 7.215457439422607 seconds elapsed\n",
      "\n",
      "Epoch 246 starting..\n",
      "Epoch 246 / Batch (1/17) / Accuracy 0.8181 / Loss 0.456977\n",
      "Epoch 246 / Batch (2/17) / Accuracy 0.7994 / Loss 0.475884\n",
      "Epoch 246 / Batch (3/17) / Accuracy 0.8338 / Loss 0.430365\n",
      "Epoch 246 / Batch (4/17) / Accuracy 0.8631 / Loss 0.362489\n",
      "Epoch 246 / Batch (5/17) / Accuracy 0.7613 / Loss 0.595364\n",
      "Epoch 246 / Batch (6/17) / Accuracy 0.8206 / Loss 0.445486\n",
      "Epoch 246 / Batch (7/17) / Accuracy 0.8206 / Loss 0.457495\n",
      "Epoch 246 / Batch (8/17) / Accuracy 0.7987 / Loss 0.500003\n",
      "Epoch 246 / Batch (9/17) / Accuracy 0.8481 / Loss 0.421869\n",
      "Epoch 246 / Batch (10/17) / Accuracy 0.8019 / Loss 0.491775\n",
      "Epoch 246 / Batch (11/17) / Accuracy 0.7956 / Loss 0.522136\n",
      "Epoch 246 / Batch (12/17) / Accuracy 0.8087 / Loss 0.496303\n",
      "Epoch 246 / Batch (13/17) / Accuracy 0.8000 / Loss 0.494663\n",
      "Epoch 246 / Batch (14/17) / Accuracy 0.8037 / Loss 0.484878\n",
      "Epoch 246 / Batch (15/17) / Accuracy 0.8294 / Loss 0.441127\n",
      "Epoch 246 / Batch (16/17) / Accuracy 0.8181 / Loss 0.462608\n",
      "Epoch 246 / Batch (17/17) / Accuracy 0.8313 / Loss 0.441107\n",
      "Epoch 246 complete, 6.690464973449707 seconds elapsed\n",
      "\n",
      "Epoch 247 starting..\n",
      "Epoch 247 / Batch (1/17) / Accuracy 0.8531 / Loss 0.419630\n",
      "Epoch 247 / Batch (2/17) / Accuracy 0.8037 / Loss 0.491228\n",
      "Epoch 247 / Batch (3/17) / Accuracy 0.8244 / Loss 0.432591\n",
      "Epoch 247 / Batch (4/17) / Accuracy 0.7794 / Loss 0.525934\n",
      "Epoch 247 / Batch (5/17) / Accuracy 0.8062 / Loss 0.462608\n",
      "Epoch 247 / Batch (6/17) / Accuracy 0.8281 / Loss 0.447241\n",
      "Epoch 247 / Batch (7/17) / Accuracy 0.8269 / Loss 0.431670\n",
      "Epoch 247 / Batch (8/17) / Accuracy 0.8119 / Loss 0.466695\n",
      "Epoch 247 / Batch (9/17) / Accuracy 0.8306 / Loss 0.428291\n",
      "Epoch 247 / Batch (10/17) / Accuracy 0.8363 / Loss 0.399217\n",
      "Epoch 247 / Batch (11/17) / Accuracy 0.8200 / Loss 0.447214\n",
      "Epoch 247 / Batch (12/17) / Accuracy 0.8213 / Loss 0.441949\n",
      "Epoch 247 / Batch (13/17) / Accuracy 0.8394 / Loss 0.422199\n",
      "Epoch 247 / Batch (14/17) / Accuracy 0.8163 / Loss 0.474571\n",
      "Epoch 247 / Batch (15/17) / Accuracy 0.7937 / Loss 0.511698\n",
      "Epoch 247 / Batch (16/17) / Accuracy 0.8306 / Loss 0.431300\n",
      "Epoch 247 / Batch (17/17) / Accuracy 0.8075 / Loss 0.461416\n",
      "Epoch 247 complete, 6.2842347621917725 seconds elapsed\n",
      "\n",
      "Epoch 248 starting..\n",
      "Epoch 248 / Batch (1/17) / Accuracy 0.8075 / Loss 0.486505\n",
      "Epoch 248 / Batch (2/17) / Accuracy 0.8075 / Loss 0.479956\n",
      "Epoch 248 / Batch (3/17) / Accuracy 0.7800 / Loss 0.543980\n",
      "Epoch 248 / Batch (4/17) / Accuracy 0.8156 / Loss 0.447357\n",
      "Epoch 248 / Batch (5/17) / Accuracy 0.7862 / Loss 0.508047\n",
      "Epoch 248 / Batch (6/17) / Accuracy 0.8094 / Loss 0.456243\n",
      "Epoch 248 / Batch (7/17) / Accuracy 0.8050 / Loss 0.509496\n",
      "Epoch 248 / Batch (8/17) / Accuracy 0.7994 / Loss 0.505289\n",
      "Epoch 248 / Batch (9/17) / Accuracy 0.8325 / Loss 0.433437\n",
      "Epoch 248 / Batch (10/17) / Accuracy 0.8100 / Loss 0.481447\n",
      "Epoch 248 / Batch (11/17) / Accuracy 0.8119 / Loss 0.462810\n",
      "Epoch 248 / Batch (12/17) / Accuracy 0.8075 / Loss 0.480042\n",
      "Epoch 248 / Batch (13/17) / Accuracy 0.7962 / Loss 0.515709\n",
      "Epoch 248 / Batch (14/17) / Accuracy 0.8156 / Loss 0.450361\n",
      "Epoch 248 / Batch (15/17) / Accuracy 0.8200 / Loss 0.440170\n",
      "Epoch 248 / Batch (16/17) / Accuracy 0.8150 / Loss 0.450738\n",
      "Epoch 248 / Batch (17/17) / Accuracy 0.8056 / Loss 0.495945\n",
      "Epoch 248 complete, 6.726760149002075 seconds elapsed\n",
      "\n",
      "Epoch 249 starting..\n",
      "Epoch 249 / Batch (1/17) / Accuracy 0.7856 / Loss 0.531708\n",
      "Epoch 249 / Batch (2/17) / Accuracy 0.7950 / Loss 0.492893\n",
      "Epoch 249 / Batch (3/17) / Accuracy 0.8313 / Loss 0.423509\n",
      "Epoch 249 / Batch (4/17) / Accuracy 0.8281 / Loss 0.430193\n",
      "Epoch 249 / Batch (5/17) / Accuracy 0.8169 / Loss 0.439192\n",
      "Epoch 249 / Batch (6/17) / Accuracy 0.8069 / Loss 0.493846\n",
      "Epoch 249 / Batch (7/17) / Accuracy 0.8188 / Loss 0.491118\n",
      "Epoch 249 / Batch (8/17) / Accuracy 0.7981 / Loss 0.500052\n",
      "Epoch 249 / Batch (9/17) / Accuracy 0.8562 / Loss 0.380334\n",
      "Epoch 249 / Batch (10/17) / Accuracy 0.8156 / Loss 0.462890\n",
      "Epoch 249 / Batch (11/17) / Accuracy 0.8112 / Loss 0.503806\n",
      "Epoch 249 / Batch (12/17) / Accuracy 0.8369 / Loss 0.407909\n",
      "Epoch 249 / Batch (13/17) / Accuracy 0.8525 / Loss 0.393582\n",
      "Epoch 249 / Batch (14/17) / Accuracy 0.8244 / Loss 0.426811\n",
      "Epoch 249 / Batch (15/17) / Accuracy 0.8438 / Loss 0.393855\n",
      "Epoch 249 / Batch (16/17) / Accuracy 0.8381 / Loss 0.431502\n",
      "Epoch 249 / Batch (17/17) / Accuracy 0.8163 / Loss 0.410987\n",
      "Epoch 249 complete, 6.584498882293701 seconds elapsed\n",
      "\n",
      "Epoch 250 starting..\n",
      "Epoch 250 / Batch (1/17) / Accuracy 0.8350 / Loss 0.417174\n",
      "Epoch 250 / Batch (2/17) / Accuracy 0.8138 / Loss 0.481389\n",
      "Epoch 250 / Batch (3/17) / Accuracy 0.8138 / Loss 0.478083\n",
      "Epoch 250 / Batch (4/17) / Accuracy 0.7912 / Loss 0.511886\n",
      "Epoch 250 / Batch (5/17) / Accuracy 0.7981 / Loss 0.493098\n",
      "Epoch 250 / Batch (6/17) / Accuracy 0.8056 / Loss 0.444306\n",
      "Epoch 250 / Batch (7/17) / Accuracy 0.8250 / Loss 0.434455\n",
      "Epoch 250 / Batch (8/17) / Accuracy 0.8406 / Loss 0.429858\n",
      "Epoch 250 / Batch (9/17) / Accuracy 0.8138 / Loss 0.464875\n",
      "Epoch 250 / Batch (10/17) / Accuracy 0.8344 / Loss 0.428351\n",
      "Epoch 250 / Batch (11/17) / Accuracy 0.8263 / Loss 0.401235\n",
      "Epoch 250 / Batch (12/17) / Accuracy 0.8125 / Loss 0.449764\n",
      "Epoch 250 / Batch (13/17) / Accuracy 0.8062 / Loss 0.473504\n",
      "Epoch 250 / Batch (14/17) / Accuracy 0.8069 / Loss 0.472867\n",
      "Epoch 250 / Batch (15/17) / Accuracy 0.8275 / Loss 0.430877\n",
      "Epoch 250 / Batch (16/17) / Accuracy 0.8406 / Loss 0.411695\n",
      "Epoch 250 / Batch (17/17) / Accuracy 0.8031 / Loss 0.502042\n",
      "Epoch 250 complete, 6.319491863250732 seconds elapsed\n",
      "\n",
      "Epoch 251 starting..\n",
      "Epoch 251 / Batch (1/17) / Accuracy 0.8156 / Loss 0.454759\n",
      "Epoch 251 / Batch (2/17) / Accuracy 0.8363 / Loss 0.417094\n",
      "Epoch 251 / Batch (3/17) / Accuracy 0.8487 / Loss 0.377158\n",
      "Epoch 251 / Batch (4/17) / Accuracy 0.8244 / Loss 0.456845\n",
      "Epoch 251 / Batch (5/17) / Accuracy 0.8175 / Loss 0.471835\n",
      "Epoch 251 / Batch (6/17) / Accuracy 0.8256 / Loss 0.451448\n",
      "Epoch 251 / Batch (7/17) / Accuracy 0.8194 / Loss 0.443529\n",
      "Epoch 251 / Batch (8/17) / Accuracy 0.7837 / Loss 0.528022\n",
      "Epoch 251 / Batch (9/17) / Accuracy 0.8256 / Loss 0.418491\n",
      "Epoch 251 / Batch (10/17) / Accuracy 0.7931 / Loss 0.525135\n",
      "Epoch 251 / Batch (11/17) / Accuracy 0.8125 / Loss 0.482166\n",
      "Epoch 251 / Batch (12/17) / Accuracy 0.7912 / Loss 0.501373\n",
      "Epoch 251 / Batch (13/17) / Accuracy 0.8169 / Loss 0.464112\n",
      "Epoch 251 / Batch (14/17) / Accuracy 0.8019 / Loss 0.486917\n",
      "Epoch 251 / Batch (15/17) / Accuracy 0.8281 / Loss 0.436201\n",
      "Epoch 251 / Batch (16/17) / Accuracy 0.8037 / Loss 0.489412\n",
      "Epoch 251 / Batch (17/17) / Accuracy 0.8231 / Loss 0.442830\n",
      "Epoch 251 complete, 6.660051107406616 seconds elapsed\n",
      "\n",
      "Epoch 252 starting..\n",
      "Epoch 252 / Batch (1/17) / Accuracy 0.8081 / Loss 0.444790\n",
      "Epoch 252 / Batch (2/17) / Accuracy 0.7925 / Loss 0.466670\n",
      "Epoch 252 / Batch (3/17) / Accuracy 0.8112 / Loss 0.482147\n",
      "Epoch 252 / Batch (4/17) / Accuracy 0.7962 / Loss 0.497433\n",
      "Epoch 252 / Batch (5/17) / Accuracy 0.8169 / Loss 0.434772\n",
      "Epoch 252 / Batch (6/17) / Accuracy 0.7981 / Loss 0.499138\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 252 / Batch (7/17) / Accuracy 0.8144 / Loss 0.452480\n",
      "Epoch 252 / Batch (8/17) / Accuracy 0.8050 / Loss 0.486024\n",
      "Epoch 252 / Batch (9/17) / Accuracy 0.8006 / Loss 0.518948\n",
      "Epoch 252 / Batch (10/17) / Accuracy 0.8012 / Loss 0.513248\n",
      "Epoch 252 / Batch (11/17) / Accuracy 0.8012 / Loss 0.490161\n",
      "Epoch 252 / Batch (12/17) / Accuracy 0.8012 / Loss 0.516548\n",
      "Epoch 252 / Batch (13/17) / Accuracy 0.7875 / Loss 0.515889\n",
      "Epoch 252 / Batch (14/17) / Accuracy 0.8394 / Loss 0.427003\n",
      "Epoch 252 / Batch (15/17) / Accuracy 0.8131 / Loss 0.471850\n",
      "Epoch 252 / Batch (16/17) / Accuracy 0.7900 / Loss 0.515547\n",
      "Epoch 252 / Batch (17/17) / Accuracy 0.8400 / Loss 0.400700\n",
      "Epoch 252 complete, 6.9282331466674805 seconds elapsed\n",
      "\n",
      "Epoch 253 starting..\n",
      "Epoch 253 / Batch (1/17) / Accuracy 0.8163 / Loss 0.473930\n",
      "Epoch 253 / Batch (2/17) / Accuracy 0.8031 / Loss 0.478209\n",
      "Epoch 253 / Batch (3/17) / Accuracy 0.8075 / Loss 0.466460\n",
      "Epoch 253 / Batch (4/17) / Accuracy 0.7981 / Loss 0.495639\n",
      "Epoch 253 / Batch (5/17) / Accuracy 0.8075 / Loss 0.504220\n",
      "Epoch 253 / Batch (6/17) / Accuracy 0.7962 / Loss 0.500627\n",
      "Epoch 253 / Batch (7/17) / Accuracy 0.8206 / Loss 0.455395\n",
      "Epoch 253 / Batch (8/17) / Accuracy 0.7513 / Loss 0.592547\n",
      "Epoch 253 / Batch (9/17) / Accuracy 0.7644 / Loss 0.588632\n",
      "Epoch 253 / Batch (10/17) / Accuracy 0.7638 / Loss 0.585843\n",
      "Epoch 253 / Batch (11/17) / Accuracy 0.8281 / Loss 0.427417\n",
      "Epoch 253 / Batch (12/17) / Accuracy 0.7588 / Loss 0.585987\n",
      "Epoch 253 / Batch (13/17) / Accuracy 0.8206 / Loss 0.436063\n",
      "Epoch 253 / Batch (14/17) / Accuracy 0.8138 / Loss 0.476318\n",
      "Epoch 253 / Batch (15/17) / Accuracy 0.8238 / Loss 0.459224\n",
      "Epoch 253 / Batch (16/17) / Accuracy 0.8344 / Loss 0.462682\n",
      "Epoch 253 / Batch (17/17) / Accuracy 0.8300 / Loss 0.450609\n",
      "Epoch 253 complete, 6.429004669189453 seconds elapsed\n",
      "\n",
      "Epoch 254 starting..\n",
      "Epoch 254 / Batch (1/17) / Accuracy 0.8181 / Loss 0.443999\n",
      "Epoch 254 / Batch (2/17) / Accuracy 0.8144 / Loss 0.466517\n",
      "Epoch 254 / Batch (3/17) / Accuracy 0.7856 / Loss 0.520004\n",
      "Epoch 254 / Batch (4/17) / Accuracy 0.7800 / Loss 0.529171\n",
      "Epoch 254 / Batch (5/17) / Accuracy 0.8375 / Loss 0.398332\n",
      "Epoch 254 / Batch (6/17) / Accuracy 0.8119 / Loss 0.463495\n",
      "Epoch 254 / Batch (7/17) / Accuracy 0.8156 / Loss 0.477693\n",
      "Epoch 254 / Batch (8/17) / Accuracy 0.8425 / Loss 0.400419\n",
      "Epoch 254 / Batch (9/17) / Accuracy 0.7900 / Loss 0.515712\n",
      "Epoch 254 / Batch (10/17) / Accuracy 0.8100 / Loss 0.488923\n",
      "Epoch 254 / Batch (11/17) / Accuracy 0.8131 / Loss 0.453716\n",
      "Epoch 254 / Batch (12/17) / Accuracy 0.8231 / Loss 0.441725\n",
      "Epoch 254 / Batch (13/17) / Accuracy 0.8163 / Loss 0.471537\n",
      "Epoch 254 / Batch (14/17) / Accuracy 0.8244 / Loss 0.464631\n",
      "Epoch 254 / Batch (15/17) / Accuracy 0.8050 / Loss 0.448973\n",
      "Epoch 254 / Batch (16/17) / Accuracy 0.8056 / Loss 0.481754\n",
      "Epoch 254 / Batch (17/17) / Accuracy 0.8037 / Loss 0.455963\n",
      "Epoch 254 complete, 6.21151328086853 seconds elapsed\n",
      "\n",
      "Epoch 255 starting..\n",
      "Epoch 255 / Batch (1/17) / Accuracy 0.8175 / Loss 0.447381\n",
      "Epoch 255 / Batch (2/17) / Accuracy 0.8000 / Loss 0.500540\n",
      "Epoch 255 / Batch (3/17) / Accuracy 0.8419 / Loss 0.426233\n",
      "Epoch 255 / Batch (4/17) / Accuracy 0.8144 / Loss 0.462280\n",
      "Epoch 255 / Batch (5/17) / Accuracy 0.8319 / Loss 0.420043\n",
      "Epoch 255 / Batch (6/17) / Accuracy 0.8231 / Loss 0.432058\n",
      "Epoch 255 / Batch (7/17) / Accuracy 0.8244 / Loss 0.440071\n",
      "Epoch 255 / Batch (8/17) / Accuracy 0.8231 / Loss 0.450431\n",
      "Epoch 255 / Batch (9/17) / Accuracy 0.8000 / Loss 0.509670\n",
      "Epoch 255 / Batch (10/17) / Accuracy 0.8112 / Loss 0.476153\n",
      "Epoch 255 / Batch (11/17) / Accuracy 0.8175 / Loss 0.449694\n",
      "Epoch 255 / Batch (12/17) / Accuracy 0.7906 / Loss 0.533061\n",
      "Epoch 255 / Batch (13/17) / Accuracy 0.7937 / Loss 0.497450\n",
      "Epoch 255 / Batch (14/17) / Accuracy 0.8281 / Loss 0.437411\n",
      "Epoch 255 / Batch (15/17) / Accuracy 0.8431 / Loss 0.398899\n",
      "Epoch 255 / Batch (16/17) / Accuracy 0.8431 / Loss 0.419114\n",
      "Epoch 255 / Batch (17/17) / Accuracy 0.7806 / Loss 0.569483\n",
      "Epoch 255 complete, 6.635671854019165 seconds elapsed\n",
      "\n",
      "Epoch 256 starting..\n",
      "Epoch 256 / Batch (1/17) / Accuracy 0.8288 / Loss 0.447098\n",
      "Epoch 256 / Batch (2/17) / Accuracy 0.8475 / Loss 0.406239\n",
      "Epoch 256 / Batch (3/17) / Accuracy 0.8331 / Loss 0.426683\n",
      "Epoch 256 / Batch (4/17) / Accuracy 0.8119 / Loss 0.446267\n",
      "Epoch 256 / Batch (5/17) / Accuracy 0.8062 / Loss 0.484882\n",
      "Epoch 256 / Batch (6/17) / Accuracy 0.8112 / Loss 0.474093\n",
      "Epoch 256 / Batch (7/17) / Accuracy 0.8456 / Loss 0.411995\n",
      "Epoch 256 / Batch (8/17) / Accuracy 0.8344 / Loss 0.439887\n",
      "Epoch 256 / Batch (9/17) / Accuracy 0.8175 / Loss 0.481245\n",
      "Epoch 256 / Batch (10/17) / Accuracy 0.8037 / Loss 0.486406\n",
      "Epoch 256 / Batch (11/17) / Accuracy 0.8431 / Loss 0.416938\n",
      "Epoch 256 / Batch (12/17) / Accuracy 0.8219 / Loss 0.472046\n",
      "Epoch 256 / Batch (13/17) / Accuracy 0.8050 / Loss 0.468539\n",
      "Epoch 256 / Batch (14/17) / Accuracy 0.8344 / Loss 0.422813\n",
      "Epoch 256 / Batch (15/17) / Accuracy 0.8238 / Loss 0.428341\n",
      "Epoch 256 / Batch (16/17) / Accuracy 0.8206 / Loss 0.483704\n",
      "Epoch 256 / Batch (17/17) / Accuracy 0.7944 / Loss 0.496124\n",
      "Epoch 256 complete, 6.331457614898682 seconds elapsed\n",
      "\n",
      "Epoch 257 starting..\n",
      "Epoch 257 / Batch (1/17) / Accuracy 0.7981 / Loss 0.495269\n",
      "Epoch 257 / Batch (2/17) / Accuracy 0.8288 / Loss 0.444124\n",
      "Epoch 257 / Batch (3/17) / Accuracy 0.8381 / Loss 0.404281\n",
      "Epoch 257 / Batch (4/17) / Accuracy 0.8400 / Loss 0.407541\n",
      "Epoch 257 / Batch (5/17) / Accuracy 0.8069 / Loss 0.469726\n",
      "Epoch 257 / Batch (6/17) / Accuracy 0.8075 / Loss 0.483929\n",
      "Epoch 257 / Batch (7/17) / Accuracy 0.7812 / Loss 0.525133\n",
      "Epoch 257 / Batch (8/17) / Accuracy 0.8281 / Loss 0.415692\n",
      "Epoch 257 / Batch (9/17) / Accuracy 0.8169 / Loss 0.460579\n",
      "Epoch 257 / Batch (10/17) / Accuracy 0.7887 / Loss 0.480716\n",
      "Epoch 257 / Batch (11/17) / Accuracy 0.8131 / Loss 0.460347\n",
      "Epoch 257 / Batch (12/17) / Accuracy 0.8169 / Loss 0.437308\n",
      "Epoch 257 / Batch (13/17) / Accuracy 0.8256 / Loss 0.427462\n",
      "Epoch 257 / Batch (14/17) / Accuracy 0.8338 / Loss 0.449242\n",
      "Epoch 257 / Batch (15/17) / Accuracy 0.8419 / Loss 0.423558\n",
      "Epoch 257 / Batch (16/17) / Accuracy 0.8131 / Loss 0.482206\n",
      "Epoch 257 / Batch (17/17) / Accuracy 0.8075 / Loss 0.462710\n",
      "Epoch 257 complete, 6.429772138595581 seconds elapsed\n",
      "\n",
      "Epoch 258 starting..\n",
      "Epoch 258 / Batch (1/17) / Accuracy 0.8238 / Loss 0.453130\n",
      "Epoch 258 / Batch (2/17) / Accuracy 0.8138 / Loss 0.481954\n",
      "Epoch 258 / Batch (3/17) / Accuracy 0.8356 / Loss 0.412350\n",
      "Epoch 258 / Batch (4/17) / Accuracy 0.8181 / Loss 0.453822\n",
      "Epoch 258 / Batch (5/17) / Accuracy 0.8188 / Loss 0.457434\n",
      "Epoch 258 / Batch (6/17) / Accuracy 0.8369 / Loss 0.439962\n",
      "Epoch 258 / Batch (7/17) / Accuracy 0.8087 / Loss 0.465767\n",
      "Epoch 258 / Batch (8/17) / Accuracy 0.8050 / Loss 0.506210\n",
      "Epoch 258 / Batch (9/17) / Accuracy 0.8125 / Loss 0.429543\n",
      "Epoch 258 / Batch (10/17) / Accuracy 0.7950 / Loss 0.523056\n",
      "Epoch 258 / Batch (11/17) / Accuracy 0.8313 / Loss 0.443753\n",
      "Epoch 258 / Batch (12/17) / Accuracy 0.7950 / Loss 0.492416\n",
      "Epoch 258 / Batch (13/17) / Accuracy 0.8175 / Loss 0.442917\n",
      "Epoch 258 / Batch (14/17) / Accuracy 0.8238 / Loss 0.441940\n",
      "Epoch 258 / Batch (15/17) / Accuracy 0.8194 / Loss 0.447915\n",
      "Epoch 258 / Batch (16/17) / Accuracy 0.8194 / Loss 0.478917\n",
      "Epoch 258 / Batch (17/17) / Accuracy 0.8394 / Loss 0.398281\n",
      "Epoch 258 complete, 6.533998489379883 seconds elapsed\n",
      "\n",
      "Epoch 259 starting..\n",
      "Epoch 259 / Batch (1/17) / Accuracy 0.8075 / Loss 0.460335\n",
      "Epoch 259 / Batch (2/17) / Accuracy 0.8075 / Loss 0.454435\n",
      "Epoch 259 / Batch (3/17) / Accuracy 0.8175 / Loss 0.430328\n",
      "Epoch 259 / Batch (4/17) / Accuracy 0.8025 / Loss 0.473634\n",
      "Epoch 259 / Batch (5/17) / Accuracy 0.8144 / Loss 0.475575\n",
      "Epoch 259 / Batch (6/17) / Accuracy 0.7925 / Loss 0.485933\n",
      "Epoch 259 / Batch (7/17) / Accuracy 0.8188 / Loss 0.446306\n",
      "Epoch 259 / Batch (8/17) / Accuracy 0.8250 / Loss 0.443662\n",
      "Epoch 259 / Batch (9/17) / Accuracy 0.8431 / Loss 0.433202\n",
      "Epoch 259 / Batch (10/17) / Accuracy 0.8281 / Loss 0.428832\n",
      "Epoch 259 / Batch (11/17) / Accuracy 0.8112 / Loss 0.466816\n",
      "Epoch 259 / Batch (12/17) / Accuracy 0.7987 / Loss 0.477600\n",
      "Epoch 259 / Batch (13/17) / Accuracy 0.8275 / Loss 0.461703\n",
      "Epoch 259 / Batch (14/17) / Accuracy 0.8213 / Loss 0.472935\n",
      "Epoch 259 / Batch (15/17) / Accuracy 0.8112 / Loss 0.472786\n",
      "Epoch 259 / Batch (16/17) / Accuracy 0.7894 / Loss 0.506290\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 259 / Batch (17/17) / Accuracy 0.8087 / Loss 0.487746\n",
      "Epoch 259 complete, 6.33124852180481 seconds elapsed\n",
      "\n",
      "Epoch 260 starting..\n",
      "Epoch 260 / Batch (1/17) / Accuracy 0.8094 / Loss 0.501205\n",
      "Epoch 260 / Batch (2/17) / Accuracy 0.8225 / Loss 0.429133\n",
      "Epoch 260 / Batch (3/17) / Accuracy 0.8219 / Loss 0.450728\n",
      "Epoch 260 / Batch (4/17) / Accuracy 0.8044 / Loss 0.463615\n",
      "Epoch 260 / Batch (5/17) / Accuracy 0.8238 / Loss 0.460790\n",
      "Epoch 260 / Batch (6/17) / Accuracy 0.8500 / Loss 0.408053\n",
      "Epoch 260 / Batch (7/17) / Accuracy 0.8456 / Loss 0.404992\n",
      "Epoch 260 / Batch (8/17) / Accuracy 0.8537 / Loss 0.409962\n",
      "Epoch 260 / Batch (9/17) / Accuracy 0.8238 / Loss 0.469151\n",
      "Epoch 260 / Batch (10/17) / Accuracy 0.8250 / Loss 0.456856\n",
      "Epoch 260 / Batch (11/17) / Accuracy 0.8288 / Loss 0.444780\n",
      "Epoch 260 / Batch (12/17) / Accuracy 0.8400 / Loss 0.404509\n",
      "Epoch 260 / Batch (13/17) / Accuracy 0.8194 / Loss 0.453056\n",
      "Epoch 260 / Batch (14/17) / Accuracy 0.8263 / Loss 0.460748\n",
      "Epoch 260 / Batch (15/17) / Accuracy 0.8625 / Loss 0.386429\n",
      "Epoch 260 / Batch (16/17) / Accuracy 0.8119 / Loss 0.470352\n",
      "Epoch 260 / Batch (17/17) / Accuracy 0.8456 / Loss 0.404317\n",
      "Epoch 260 complete, 6.251288652420044 seconds elapsed\n",
      "\n",
      "Epoch 261 starting..\n",
      "Epoch 261 / Batch (1/17) / Accuracy 0.8275 / Loss 0.425861\n",
      "Epoch 261 / Batch (2/17) / Accuracy 0.8263 / Loss 0.451579\n",
      "Epoch 261 / Batch (3/17) / Accuracy 0.7975 / Loss 0.498391\n",
      "Epoch 261 / Batch (4/17) / Accuracy 0.8019 / Loss 0.504175\n",
      "Epoch 261 / Batch (5/17) / Accuracy 0.8062 / Loss 0.481757\n",
      "Epoch 261 / Batch (6/17) / Accuracy 0.8025 / Loss 0.512445\n",
      "Epoch 261 / Batch (7/17) / Accuracy 0.8163 / Loss 0.462787\n",
      "Epoch 261 / Batch (8/17) / Accuracy 0.8156 / Loss 0.453817\n",
      "Epoch 261 / Batch (9/17) / Accuracy 0.8087 / Loss 0.497343\n",
      "Epoch 261 / Batch (10/17) / Accuracy 0.8044 / Loss 0.463358\n",
      "Epoch 261 / Batch (11/17) / Accuracy 0.8256 / Loss 0.459993\n",
      "Epoch 261 / Batch (12/17) / Accuracy 0.8269 / Loss 0.440294\n",
      "Epoch 261 / Batch (13/17) / Accuracy 0.7975 / Loss 0.488267\n",
      "Epoch 261 / Batch (14/17) / Accuracy 0.8000 / Loss 0.491151\n",
      "Epoch 261 / Batch (15/17) / Accuracy 0.8263 / Loss 0.443147\n",
      "Epoch 261 / Batch (16/17) / Accuracy 0.7975 / Loss 0.482464\n",
      "Epoch 261 / Batch (17/17) / Accuracy 0.7944 / Loss 0.477487\n",
      "Epoch 261 complete, 7.191911458969116 seconds elapsed\n",
      "\n",
      "Epoch 262 starting..\n",
      "Epoch 262 / Batch (1/17) / Accuracy 0.7987 / Loss 0.465285\n",
      "Epoch 262 / Batch (2/17) / Accuracy 0.8225 / Loss 0.476251\n",
      "Epoch 262 / Batch (3/17) / Accuracy 0.8400 / Loss 0.434378\n",
      "Epoch 262 / Batch (4/17) / Accuracy 0.8219 / Loss 0.471011\n",
      "Epoch 262 / Batch (5/17) / Accuracy 0.8425 / Loss 0.424065\n",
      "Epoch 262 / Batch (6/17) / Accuracy 0.7956 / Loss 0.520171\n",
      "Epoch 262 / Batch (7/17) / Accuracy 0.8138 / Loss 0.475403\n",
      "Epoch 262 / Batch (8/17) / Accuracy 0.7969 / Loss 0.519007\n",
      "Epoch 262 / Batch (9/17) / Accuracy 0.8319 / Loss 0.435251\n",
      "Epoch 262 / Batch (10/17) / Accuracy 0.8369 / Loss 0.403865\n",
      "Epoch 262 / Batch (11/17) / Accuracy 0.8156 / Loss 0.456421\n",
      "Epoch 262 / Batch (12/17) / Accuracy 0.8131 / Loss 0.474082\n",
      "Epoch 262 / Batch (13/17) / Accuracy 0.8419 / Loss 0.387181\n",
      "Epoch 262 / Batch (14/17) / Accuracy 0.8363 / Loss 0.434005\n",
      "Epoch 262 / Batch (15/17) / Accuracy 0.8144 / Loss 0.453269\n",
      "Epoch 262 / Batch (16/17) / Accuracy 0.8219 / Loss 0.431337\n",
      "Epoch 262 / Batch (17/17) / Accuracy 0.8556 / Loss 0.382289\n",
      "Epoch 262 complete, 6.689856052398682 seconds elapsed\n",
      "\n",
      "Epoch 263 starting..\n",
      "Epoch 263 / Batch (1/17) / Accuracy 0.7994 / Loss 0.485951\n",
      "Epoch 263 / Batch (2/17) / Accuracy 0.8250 / Loss 0.444814\n",
      "Epoch 263 / Batch (3/17) / Accuracy 0.7581 / Loss 0.593032\n",
      "Epoch 263 / Batch (4/17) / Accuracy 0.8425 / Loss 0.380361\n",
      "Epoch 263 / Batch (5/17) / Accuracy 0.8263 / Loss 0.434835\n",
      "Epoch 263 / Batch (6/17) / Accuracy 0.8006 / Loss 0.478158\n",
      "Epoch 263 / Batch (7/17) / Accuracy 0.7912 / Loss 0.501560\n",
      "Epoch 263 / Batch (8/17) / Accuracy 0.8744 / Loss 0.350083\n",
      "Epoch 263 / Batch (9/17) / Accuracy 0.8406 / Loss 0.408410\n",
      "Epoch 263 / Batch (10/17) / Accuracy 0.8519 / Loss 0.379494\n",
      "Epoch 263 / Batch (11/17) / Accuracy 0.8306 / Loss 0.436130\n",
      "Epoch 263 / Batch (12/17) / Accuracy 0.8150 / Loss 0.457924\n",
      "Epoch 263 / Batch (13/17) / Accuracy 0.8475 / Loss 0.405551\n",
      "Epoch 263 / Batch (14/17) / Accuracy 0.8288 / Loss 0.438568\n",
      "Epoch 263 / Batch (15/17) / Accuracy 0.8188 / Loss 0.450405\n",
      "Epoch 263 / Batch (16/17) / Accuracy 0.7925 / Loss 0.512837\n",
      "Epoch 263 / Batch (17/17) / Accuracy 0.8037 / Loss 0.476010\n",
      "Epoch 263 complete, 6.335044622421265 seconds elapsed\n",
      "\n",
      "Epoch 264 starting..\n",
      "Epoch 264 / Batch (1/17) / Accuracy 0.8219 / Loss 0.446855\n",
      "Epoch 264 / Batch (2/17) / Accuracy 0.8313 / Loss 0.460137\n",
      "Epoch 264 / Batch (3/17) / Accuracy 0.8069 / Loss 0.458116\n",
      "Epoch 264 / Batch (4/17) / Accuracy 0.8325 / Loss 0.455653\n",
      "Epoch 264 / Batch (5/17) / Accuracy 0.7881 / Loss 0.493751\n",
      "Epoch 264 / Batch (6/17) / Accuracy 0.8425 / Loss 0.418518\n",
      "Epoch 264 / Batch (7/17) / Accuracy 0.8094 / Loss 0.489608\n",
      "Epoch 264 / Batch (8/17) / Accuracy 0.6881 / Loss 0.981699\n",
      "Epoch 264 / Batch (9/17) / Accuracy 0.7775 / Loss 0.517603\n",
      "Epoch 264 / Batch (10/17) / Accuracy 0.7538 / Loss 0.642911\n",
      "Epoch 264 / Batch (11/17) / Accuracy 0.7356 / Loss 0.616832\n",
      "Epoch 264 / Batch (12/17) / Accuracy 0.7219 / Loss 0.656324\n",
      "Epoch 264 / Batch (13/17) / Accuracy 0.7138 / Loss 0.705218\n",
      "Epoch 264 / Batch (14/17) / Accuracy 0.7731 / Loss 0.532549\n",
      "Epoch 264 / Batch (15/17) / Accuracy 0.7444 / Loss 0.615517\n",
      "Epoch 264 / Batch (16/17) / Accuracy 0.7150 / Loss 0.717624\n",
      "Epoch 264 / Batch (17/17) / Accuracy 0.7406 / Loss 0.593285\n",
      "Epoch 264 complete, 6.549839496612549 seconds elapsed\n",
      "\n",
      "Epoch 265 starting..\n",
      "Epoch 265 / Batch (1/17) / Accuracy 0.7219 / Loss 0.679897\n",
      "Epoch 265 / Batch (2/17) / Accuracy 0.7694 / Loss 0.547911\n",
      "Epoch 265 / Batch (3/17) / Accuracy 0.8200 / Loss 0.459653\n",
      "Epoch 265 / Batch (4/17) / Accuracy 0.7525 / Loss 0.607299\n",
      "Epoch 265 / Batch (5/17) / Accuracy 0.8050 / Loss 0.499394\n",
      "Epoch 265 / Batch (6/17) / Accuracy 0.7837 / Loss 0.543729\n",
      "Epoch 265 / Batch (7/17) / Accuracy 0.7950 / Loss 0.504504\n",
      "Epoch 265 / Batch (8/17) / Accuracy 0.7781 / Loss 0.535729\n",
      "Epoch 265 / Batch (9/17) / Accuracy 0.7900 / Loss 0.525699\n",
      "Epoch 265 / Batch (10/17) / Accuracy 0.7956 / Loss 0.512825\n",
      "Epoch 265 / Batch (11/17) / Accuracy 0.7850 / Loss 0.513493\n",
      "Epoch 265 / Batch (12/17) / Accuracy 0.7869 / Loss 0.507610\n",
      "Epoch 265 / Batch (13/17) / Accuracy 0.7550 / Loss 0.560638\n",
      "Epoch 265 / Batch (14/17) / Accuracy 0.8569 / Loss 0.378152\n",
      "Epoch 265 / Batch (15/17) / Accuracy 0.8031 / Loss 0.497418\n",
      "Epoch 265 / Batch (16/17) / Accuracy 0.7644 / Loss 0.533710\n",
      "Epoch 265 / Batch (17/17) / Accuracy 0.7731 / Loss 0.529483\n",
      "Epoch 265 complete, 5.964729309082031 seconds elapsed\n",
      "\n",
      "Epoch 266 starting..\n",
      "Epoch 266 / Batch (1/17) / Accuracy 0.7750 / Loss 0.525889\n",
      "Epoch 266 / Batch (2/17) / Accuracy 0.8100 / Loss 0.501291\n",
      "Epoch 266 / Batch (3/17) / Accuracy 0.8462 / Loss 0.388182\n",
      "Epoch 266 / Batch (4/17) / Accuracy 0.7744 / Loss 0.537044\n",
      "Epoch 266 / Batch (5/17) / Accuracy 0.8106 / Loss 0.456423\n",
      "Epoch 266 / Batch (6/17) / Accuracy 0.8400 / Loss 0.419185\n",
      "Epoch 266 / Batch (7/17) / Accuracy 0.8037 / Loss 0.485765\n",
      "Epoch 266 / Batch (8/17) / Accuracy 0.8181 / Loss 0.448137\n",
      "Epoch 266 / Batch (9/17) / Accuracy 0.7837 / Loss 0.524433\n",
      "Epoch 266 / Batch (10/17) / Accuracy 0.8112 / Loss 0.451885\n",
      "Epoch 266 / Batch (11/17) / Accuracy 0.7725 / Loss 0.551137\n",
      "Epoch 266 / Batch (12/17) / Accuracy 0.8000 / Loss 0.501995\n",
      "Epoch 266 / Batch (13/17) / Accuracy 0.8144 / Loss 0.466536\n",
      "Epoch 266 / Batch (14/17) / Accuracy 0.7937 / Loss 0.539279\n",
      "Epoch 266 / Batch (15/17) / Accuracy 0.8037 / Loss 0.488046\n",
      "Epoch 266 / Batch (16/17) / Accuracy 0.7925 / Loss 0.484397\n",
      "Epoch 266 / Batch (17/17) / Accuracy 0.8112 / Loss 0.452356\n",
      "Epoch 266 complete, 6.659926652908325 seconds elapsed\n",
      "\n",
      "Epoch 267 starting..\n",
      "Epoch 267 / Batch (1/17) / Accuracy 0.8037 / Loss 0.464198\n",
      "Epoch 267 / Batch (2/17) / Accuracy 0.7844 / Loss 0.535299\n",
      "Epoch 267 / Batch (3/17) / Accuracy 0.8075 / Loss 0.497626\n",
      "Epoch 267 / Batch (4/17) / Accuracy 0.7981 / Loss 0.479925\n",
      "Epoch 267 / Batch (5/17) / Accuracy 0.8163 / Loss 0.468945\n",
      "Epoch 267 / Batch (6/17) / Accuracy 0.7912 / Loss 0.532327\n",
      "Epoch 267 / Batch (7/17) / Accuracy 0.8006 / Loss 0.489738\n",
      "Epoch 267 / Batch (8/17) / Accuracy 0.7544 / Loss 0.615810\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 267 / Batch (9/17) / Accuracy 0.8062 / Loss 0.506407\n",
      "Epoch 267 / Batch (10/17) / Accuracy 0.8213 / Loss 0.449382\n",
      "Epoch 267 / Batch (11/17) / Accuracy 0.7850 / Loss 0.528667\n",
      "Epoch 267 / Batch (12/17) / Accuracy 0.7856 / Loss 0.528171\n",
      "Epoch 267 / Batch (13/17) / Accuracy 0.8138 / Loss 0.451431\n",
      "Epoch 267 / Batch (14/17) / Accuracy 0.7706 / Loss 0.574469\n",
      "Epoch 267 / Batch (15/17) / Accuracy 0.8225 / Loss 0.459369\n",
      "Epoch 267 / Batch (16/17) / Accuracy 0.8319 / Loss 0.450075\n",
      "Epoch 267 / Batch (17/17) / Accuracy 0.8000 / Loss 0.493603\n",
      "Epoch 267 complete, 6.345165729522705 seconds elapsed\n",
      "\n",
      "Epoch 268 starting..\n",
      "Epoch 268 / Batch (1/17) / Accuracy 0.8025 / Loss 0.498305\n",
      "Epoch 268 / Batch (2/17) / Accuracy 0.7912 / Loss 0.541902\n",
      "Epoch 268 / Batch (3/17) / Accuracy 0.8288 / Loss 0.423757\n",
      "Epoch 268 / Batch (4/17) / Accuracy 0.8037 / Loss 0.468891\n",
      "Epoch 268 / Batch (5/17) / Accuracy 0.8100 / Loss 0.476744\n",
      "Epoch 268 / Batch (6/17) / Accuracy 0.8006 / Loss 0.482845\n",
      "Epoch 268 / Batch (7/17) / Accuracy 0.8000 / Loss 0.480560\n",
      "Epoch 268 / Batch (8/17) / Accuracy 0.7925 / Loss 0.525349\n",
      "Epoch 268 / Batch (9/17) / Accuracy 0.8175 / Loss 0.438303\n",
      "Epoch 268 / Batch (10/17) / Accuracy 0.8169 / Loss 0.442869\n",
      "Epoch 268 / Batch (11/17) / Accuracy 0.8375 / Loss 0.410980\n",
      "Epoch 268 / Batch (12/17) / Accuracy 0.8481 / Loss 0.415958\n",
      "Epoch 268 / Batch (13/17) / Accuracy 0.8112 / Loss 0.458285\n",
      "Epoch 268 / Batch (14/17) / Accuracy 0.8037 / Loss 0.511259\n",
      "Epoch 268 / Batch (15/17) / Accuracy 0.8100 / Loss 0.457637\n",
      "Epoch 268 / Batch (16/17) / Accuracy 0.7800 / Loss 0.521449\n",
      "Epoch 268 / Batch (17/17) / Accuracy 0.8000 / Loss 0.475655\n",
      "Epoch 268 complete, 6.7586140632629395 seconds elapsed\n",
      "\n",
      "Epoch 269 starting..\n",
      "Epoch 269 / Batch (1/17) / Accuracy 0.8344 / Loss 0.431849\n",
      "Epoch 269 / Batch (2/17) / Accuracy 0.8138 / Loss 0.468718\n",
      "Epoch 269 / Batch (3/17) / Accuracy 0.8069 / Loss 0.473993\n",
      "Epoch 269 / Batch (4/17) / Accuracy 0.8006 / Loss 0.494526\n",
      "Epoch 269 / Batch (5/17) / Accuracy 0.7981 / Loss 0.516585\n",
      "Epoch 269 / Batch (6/17) / Accuracy 0.8112 / Loss 0.454806\n",
      "Epoch 269 / Batch (7/17) / Accuracy 0.8150 / Loss 0.472606\n",
      "Epoch 269 / Batch (8/17) / Accuracy 0.7862 / Loss 0.510547\n",
      "Epoch 269 / Batch (9/17) / Accuracy 0.8050 / Loss 0.484434\n",
      "Epoch 269 / Batch (10/17) / Accuracy 0.8087 / Loss 0.468642\n",
      "Epoch 269 / Batch (11/17) / Accuracy 0.7806 / Loss 0.524390\n",
      "Epoch 269 / Batch (12/17) / Accuracy 0.7969 / Loss 0.499326\n",
      "Epoch 269 / Batch (13/17) / Accuracy 0.8106 / Loss 0.505482\n",
      "Epoch 269 / Batch (14/17) / Accuracy 0.8219 / Loss 0.426700\n",
      "Epoch 269 / Batch (15/17) / Accuracy 0.8112 / Loss 0.454533\n",
      "Epoch 269 / Batch (16/17) / Accuracy 0.7731 / Loss 0.568826\n",
      "Epoch 269 / Batch (17/17) / Accuracy 0.8031 / Loss 0.473001\n",
      "Epoch 269 complete, 6.740052223205566 seconds elapsed\n",
      "\n",
      "Epoch 270 starting..\n",
      "Epoch 270 / Batch (1/17) / Accuracy 0.7506 / Loss 0.610759\n",
      "Epoch 270 / Batch (2/17) / Accuracy 0.8087 / Loss 0.490201\n",
      "Epoch 270 / Batch (3/17) / Accuracy 0.8425 / Loss 0.412438\n",
      "Epoch 270 / Batch (4/17) / Accuracy 0.8112 / Loss 0.487680\n",
      "Epoch 270 / Batch (5/17) / Accuracy 0.8194 / Loss 0.444321\n",
      "Epoch 270 / Batch (6/17) / Accuracy 0.8125 / Loss 0.473692\n",
      "Epoch 270 / Batch (7/17) / Accuracy 0.8119 / Loss 0.459623\n",
      "Epoch 270 / Batch (8/17) / Accuracy 0.7681 / Loss 0.551122\n",
      "Epoch 270 / Batch (9/17) / Accuracy 0.7638 / Loss 0.597965\n",
      "Epoch 270 / Batch (10/17) / Accuracy 0.7869 / Loss 0.514710\n",
      "Epoch 270 / Batch (11/17) / Accuracy 0.7594 / Loss 0.589660\n",
      "Epoch 270 / Batch (12/17) / Accuracy 0.7894 / Loss 0.512499\n",
      "Epoch 270 / Batch (13/17) / Accuracy 0.8394 / Loss 0.430594\n",
      "Epoch 270 / Batch (14/17) / Accuracy 0.8388 / Loss 0.390083\n",
      "Epoch 270 / Batch (15/17) / Accuracy 0.7506 / Loss 0.581829\n",
      "Epoch 270 / Batch (16/17) / Accuracy 0.7856 / Loss 0.529571\n",
      "Epoch 270 / Batch (17/17) / Accuracy 0.8075 / Loss 0.470546\n",
      "Epoch 270 complete, 5.832481622695923 seconds elapsed\n",
      "\n",
      "Epoch 271 starting..\n",
      "Epoch 271 / Batch (1/17) / Accuracy 0.8062 / Loss 0.500415\n",
      "Epoch 271 / Batch (2/17) / Accuracy 0.7631 / Loss 0.579295\n",
      "Epoch 271 / Batch (3/17) / Accuracy 0.7669 / Loss 0.544912\n",
      "Epoch 271 / Batch (4/17) / Accuracy 0.7887 / Loss 0.485737\n",
      "Epoch 271 / Batch (5/17) / Accuracy 0.8213 / Loss 0.470402\n",
      "Epoch 271 / Batch (6/17) / Accuracy 0.7800 / Loss 0.539243\n",
      "Epoch 271 / Batch (7/17) / Accuracy 0.8106 / Loss 0.481951\n",
      "Epoch 271 / Batch (8/17) / Accuracy 0.7638 / Loss 0.582895\n",
      "Epoch 271 / Batch (9/17) / Accuracy 0.8050 / Loss 0.505412\n",
      "Epoch 271 / Batch (10/17) / Accuracy 0.7688 / Loss 0.559164\n",
      "Epoch 271 / Batch (11/17) / Accuracy 0.7869 / Loss 0.527124\n",
      "Epoch 271 / Batch (12/17) / Accuracy 0.7531 / Loss 0.578994\n",
      "Epoch 271 / Batch (13/17) / Accuracy 0.8050 / Loss 0.502480\n",
      "Epoch 271 / Batch (14/17) / Accuracy 0.7887 / Loss 0.532365\n",
      "Epoch 271 / Batch (15/17) / Accuracy 0.8031 / Loss 0.479014\n",
      "Epoch 271 / Batch (16/17) / Accuracy 0.8012 / Loss 0.479059\n",
      "Epoch 271 / Batch (17/17) / Accuracy 0.8225 / Loss 0.464963\n",
      "Epoch 271 complete, 6.452930450439453 seconds elapsed\n",
      "\n",
      "Epoch 272 starting..\n",
      "Epoch 272 / Batch (1/17) / Accuracy 0.7825 / Loss 0.537972\n",
      "Epoch 272 / Batch (2/17) / Accuracy 0.8075 / Loss 0.485462\n",
      "Epoch 272 / Batch (3/17) / Accuracy 0.8175 / Loss 0.476254\n",
      "Epoch 272 / Batch (4/17) / Accuracy 0.8200 / Loss 0.484826\n",
      "Epoch 272 / Batch (5/17) / Accuracy 0.8281 / Loss 0.460755\n",
      "Epoch 272 / Batch (6/17) / Accuracy 0.8325 / Loss 0.431322\n",
      "Epoch 272 / Batch (7/17) / Accuracy 0.7600 / Loss 0.591610\n",
      "Epoch 272 / Batch (8/17) / Accuracy 0.7950 / Loss 0.490199\n",
      "Epoch 272 / Batch (9/17) / Accuracy 0.8025 / Loss 0.476378\n",
      "Epoch 272 / Batch (10/17) / Accuracy 0.8050 / Loss 0.485970\n",
      "Epoch 272 / Batch (11/17) / Accuracy 0.8400 / Loss 0.403529\n",
      "Epoch 272 / Batch (12/17) / Accuracy 0.8062 / Loss 0.481306\n",
      "Epoch 272 / Batch (13/17) / Accuracy 0.7925 / Loss 0.490959\n",
      "Epoch 272 / Batch (14/17) / Accuracy 0.8094 / Loss 0.466905\n",
      "Epoch 272 / Batch (15/17) / Accuracy 0.8419 / Loss 0.420731\n",
      "Epoch 272 / Batch (16/17) / Accuracy 0.7744 / Loss 0.547877\n",
      "Epoch 272 / Batch (17/17) / Accuracy 0.8138 / Loss 0.460759\n",
      "Epoch 272 complete, 6.364553213119507 seconds elapsed\n",
      "\n",
      "Epoch 273 starting..\n",
      "Epoch 273 / Batch (1/17) / Accuracy 0.7931 / Loss 0.494481\n",
      "Epoch 273 / Batch (2/17) / Accuracy 0.7944 / Loss 0.509720\n",
      "Epoch 273 / Batch (3/17) / Accuracy 0.8462 / Loss 0.392092\n",
      "Epoch 273 / Batch (4/17) / Accuracy 0.8138 / Loss 0.480175\n",
      "Epoch 273 / Batch (5/17) / Accuracy 0.8313 / Loss 0.450565\n",
      "Epoch 273 / Batch (6/17) / Accuracy 0.8175 / Loss 0.480659\n",
      "Epoch 273 / Batch (7/17) / Accuracy 0.8031 / Loss 0.501131\n",
      "Epoch 273 / Batch (8/17) / Accuracy 0.7956 / Loss 0.510776\n",
      "Epoch 273 / Batch (9/17) / Accuracy 0.8288 / Loss 0.436079\n",
      "Epoch 273 / Batch (10/17) / Accuracy 0.8006 / Loss 0.503314\n",
      "Epoch 273 / Batch (11/17) / Accuracy 0.8206 / Loss 0.455331\n",
      "Epoch 273 / Batch (12/17) / Accuracy 0.8194 / Loss 0.473227\n",
      "Epoch 273 / Batch (13/17) / Accuracy 0.7819 / Loss 0.506296\n",
      "Epoch 273 / Batch (14/17) / Accuracy 0.7856 / Loss 0.523641\n",
      "Epoch 273 / Batch (15/17) / Accuracy 0.8213 / Loss 0.448625\n",
      "Epoch 273 / Batch (16/17) / Accuracy 0.8288 / Loss 0.444405\n",
      "Epoch 273 / Batch (17/17) / Accuracy 0.8281 / Loss 0.432692\n",
      "Epoch 273 complete, 6.295180559158325 seconds elapsed\n",
      "\n",
      "Epoch 274 starting..\n",
      "Epoch 274 / Batch (1/17) / Accuracy 0.8231 / Loss 0.452481\n",
      "Epoch 274 / Batch (2/17) / Accuracy 0.7844 / Loss 0.516122\n",
      "Epoch 274 / Batch (3/17) / Accuracy 0.8431 / Loss 0.426396\n",
      "Epoch 274 / Batch (4/17) / Accuracy 0.7831 / Loss 0.506237\n",
      "Epoch 274 / Batch (5/17) / Accuracy 0.8281 / Loss 0.437399\n",
      "Epoch 274 / Batch (6/17) / Accuracy 0.8062 / Loss 0.490349\n",
      "Epoch 274 / Batch (7/17) / Accuracy 0.8294 / Loss 0.450206\n",
      "Epoch 274 / Batch (8/17) / Accuracy 0.8062 / Loss 0.501491\n",
      "Epoch 274 / Batch (9/17) / Accuracy 0.8156 / Loss 0.465884\n",
      "Epoch 274 / Batch (10/17) / Accuracy 0.7487 / Loss 0.562455\n",
      "Epoch 274 / Batch (11/17) / Accuracy 0.8356 / Loss 0.403934\n",
      "Epoch 274 / Batch (12/17) / Accuracy 0.8125 / Loss 0.446646\n",
      "Epoch 274 / Batch (13/17) / Accuracy 0.7513 / Loss 0.600234\n",
      "Epoch 274 / Batch (14/17) / Accuracy 0.8031 / Loss 0.474444\n",
      "Epoch 274 / Batch (15/17) / Accuracy 0.8019 / Loss 0.510737\n",
      "Epoch 274 / Batch (16/17) / Accuracy 0.8300 / Loss 0.440910\n",
      "Epoch 274 / Batch (17/17) / Accuracy 0.8444 / Loss 0.415679\n",
      "Epoch 274 complete, 6.062812328338623 seconds elapsed\n",
      "\n",
      "Epoch 275 starting..\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 275 / Batch (1/17) / Accuracy 0.8200 / Loss 0.488447\n",
      "Epoch 275 / Batch (2/17) / Accuracy 0.7881 / Loss 0.510160\n",
      "Epoch 275 / Batch (3/17) / Accuracy 0.8138 / Loss 0.483985\n",
      "Epoch 275 / Batch (4/17) / Accuracy 0.8356 / Loss 0.402410\n",
      "Epoch 275 / Batch (5/17) / Accuracy 0.8100 / Loss 0.443030\n",
      "Epoch 275 / Batch (6/17) / Accuracy 0.8369 / Loss 0.435752\n",
      "Epoch 275 / Batch (7/17) / Accuracy 0.7731 / Loss 0.543910\n",
      "Epoch 275 / Batch (8/17) / Accuracy 0.8144 / Loss 0.458960\n",
      "Epoch 275 / Batch (9/17) / Accuracy 0.8250 / Loss 0.467961\n",
      "Epoch 275 / Batch (10/17) / Accuracy 0.8125 / Loss 0.477647\n",
      "Epoch 275 / Batch (11/17) / Accuracy 0.8175 / Loss 0.473645\n",
      "Epoch 275 / Batch (12/17) / Accuracy 0.8156 / Loss 0.456379\n",
      "Epoch 275 / Batch (13/17) / Accuracy 0.8081 / Loss 0.493442\n",
      "Epoch 275 / Batch (14/17) / Accuracy 0.7856 / Loss 0.530086\n",
      "Epoch 275 / Batch (15/17) / Accuracy 0.8019 / Loss 0.469501\n",
      "Epoch 275 / Batch (16/17) / Accuracy 0.8200 / Loss 0.459676\n",
      "Epoch 275 / Batch (17/17) / Accuracy 0.7619 / Loss 0.534665\n",
      "Epoch 275 complete, 6.0681164264678955 seconds elapsed\n",
      "\n",
      "Epoch 276 starting..\n",
      "Epoch 276 / Batch (1/17) / Accuracy 0.8169 / Loss 0.481344\n",
      "Epoch 276 / Batch (2/17) / Accuracy 0.8119 / Loss 0.449367\n",
      "Epoch 276 / Batch (3/17) / Accuracy 0.7956 / Loss 0.490157\n",
      "Epoch 276 / Batch (4/17) / Accuracy 0.8244 / Loss 0.422278\n",
      "Epoch 276 / Batch (5/17) / Accuracy 0.8188 / Loss 0.462307\n",
      "Epoch 276 / Batch (6/17) / Accuracy 0.8031 / Loss 0.492848\n",
      "Epoch 276 / Batch (7/17) / Accuracy 0.7956 / Loss 0.513609\n",
      "Epoch 276 / Batch (8/17) / Accuracy 0.8150 / Loss 0.460550\n",
      "Epoch 276 / Batch (9/17) / Accuracy 0.8200 / Loss 0.450678\n",
      "Epoch 276 / Batch (10/17) / Accuracy 0.8125 / Loss 0.453525\n",
      "Epoch 276 / Batch (11/17) / Accuracy 0.8319 / Loss 0.450251\n",
      "Epoch 276 / Batch (12/17) / Accuracy 0.8106 / Loss 0.481901\n",
      "Epoch 276 / Batch (13/17) / Accuracy 0.7738 / Loss 0.580461\n",
      "Epoch 276 / Batch (14/17) / Accuracy 0.8425 / Loss 0.408040\n",
      "Epoch 276 / Batch (15/17) / Accuracy 0.8062 / Loss 0.478147\n",
      "Epoch 276 / Batch (16/17) / Accuracy 0.8462 / Loss 0.408192\n",
      "Epoch 276 / Batch (17/17) / Accuracy 0.8131 / Loss 0.453195\n",
      "Epoch 276 complete, 5.955042839050293 seconds elapsed\n",
      "\n",
      "Epoch 277 starting..\n",
      "Epoch 277 / Batch (1/17) / Accuracy 0.8087 / Loss 0.471990\n",
      "Epoch 277 / Batch (2/17) / Accuracy 0.8438 / Loss 0.412939\n",
      "Epoch 277 / Batch (3/17) / Accuracy 0.7994 / Loss 0.517430\n",
      "Epoch 277 / Batch (4/17) / Accuracy 0.8244 / Loss 0.447194\n",
      "Epoch 277 / Batch (5/17) / Accuracy 0.7744 / Loss 0.568427\n",
      "Epoch 277 / Batch (6/17) / Accuracy 0.8106 / Loss 0.445816\n",
      "Epoch 277 / Batch (7/17) / Accuracy 0.7775 / Loss 0.503801\n",
      "Epoch 277 / Batch (8/17) / Accuracy 0.8150 / Loss 0.490066\n",
      "Epoch 277 / Batch (9/17) / Accuracy 0.7744 / Loss 0.546829\n",
      "Epoch 277 / Batch (10/17) / Accuracy 0.8481 / Loss 0.381263\n",
      "Epoch 277 / Batch (11/17) / Accuracy 0.8206 / Loss 0.450017\n",
      "Epoch 277 / Batch (12/17) / Accuracy 0.8406 / Loss 0.421265\n",
      "Epoch 277 / Batch (13/17) / Accuracy 0.7987 / Loss 0.510688\n",
      "Epoch 277 / Batch (14/17) / Accuracy 0.8119 / Loss 0.456494\n",
      "Epoch 277 / Batch (15/17) / Accuracy 0.8469 / Loss 0.395631\n",
      "Epoch 277 / Batch (16/17) / Accuracy 0.8288 / Loss 0.443488\n",
      "Epoch 277 / Batch (17/17) / Accuracy 0.8188 / Loss 0.439626\n",
      "Epoch 277 complete, 5.875812530517578 seconds elapsed\n",
      "\n",
      "Epoch 278 starting..\n",
      "Epoch 278 / Batch (1/17) / Accuracy 0.8281 / Loss 0.403690\n",
      "Epoch 278 / Batch (2/17) / Accuracy 0.8306 / Loss 0.431420\n",
      "Epoch 278 / Batch (3/17) / Accuracy 0.8519 / Loss 0.378120\n",
      "Epoch 278 / Batch (4/17) / Accuracy 0.8019 / Loss 0.479723\n",
      "Epoch 278 / Batch (5/17) / Accuracy 0.8031 / Loss 0.477605\n",
      "Epoch 278 / Batch (6/17) / Accuracy 0.8375 / Loss 0.418182\n",
      "Epoch 278 / Batch (7/17) / Accuracy 0.8138 / Loss 0.445758\n",
      "Epoch 278 / Batch (8/17) / Accuracy 0.8319 / Loss 0.428160\n",
      "Epoch 278 / Batch (9/17) / Accuracy 0.8144 / Loss 0.470783\n",
      "Epoch 278 / Batch (10/17) / Accuracy 0.8112 / Loss 0.467649\n",
      "Epoch 278 / Batch (11/17) / Accuracy 0.8019 / Loss 0.518156\n",
      "Epoch 278 / Batch (12/17) / Accuracy 0.7987 / Loss 0.494381\n",
      "Epoch 278 / Batch (13/17) / Accuracy 0.8244 / Loss 0.438782\n",
      "Epoch 278 / Batch (14/17) / Accuracy 0.7881 / Loss 0.531357\n",
      "Epoch 278 / Batch (15/17) / Accuracy 0.7862 / Loss 0.526936\n",
      "Epoch 278 / Batch (16/17) / Accuracy 0.7781 / Loss 0.532960\n",
      "Epoch 278 / Batch (17/17) / Accuracy 0.8175 / Loss 0.442585\n",
      "Epoch 278 complete, 6.4245219230651855 seconds elapsed\n",
      "\n",
      "Epoch 279 starting..\n",
      "Epoch 279 / Batch (1/17) / Accuracy 0.7994 / Loss 0.500272\n",
      "Epoch 279 / Batch (2/17) / Accuracy 0.8131 / Loss 0.466912\n",
      "Epoch 279 / Batch (3/17) / Accuracy 0.8106 / Loss 0.468533\n",
      "Epoch 279 / Batch (4/17) / Accuracy 0.8081 / Loss 0.479548\n",
      "Epoch 279 / Batch (5/17) / Accuracy 0.8556 / Loss 0.383112\n",
      "Epoch 279 / Batch (6/17) / Accuracy 0.8094 / Loss 0.460667\n",
      "Epoch 279 / Batch (7/17) / Accuracy 0.7900 / Loss 0.499880\n",
      "Epoch 279 / Batch (8/17) / Accuracy 0.8031 / Loss 0.495539\n",
      "Epoch 279 / Batch (9/17) / Accuracy 0.8062 / Loss 0.497614\n",
      "Epoch 279 / Batch (10/17) / Accuracy 0.8319 / Loss 0.431204\n",
      "Epoch 279 / Batch (11/17) / Accuracy 0.8144 / Loss 0.474382\n",
      "Epoch 279 / Batch (12/17) / Accuracy 0.8281 / Loss 0.420103\n",
      "Epoch 279 / Batch (13/17) / Accuracy 0.8450 / Loss 0.401278\n",
      "Epoch 279 / Batch (14/17) / Accuracy 0.8000 / Loss 0.493619\n",
      "Epoch 279 / Batch (15/17) / Accuracy 0.8256 / Loss 0.439916\n",
      "Epoch 279 / Batch (16/17) / Accuracy 0.8006 / Loss 0.494821\n",
      "Epoch 279 / Batch (17/17) / Accuracy 0.8475 / Loss 0.410368\n",
      "Epoch 279 complete, 5.70371413230896 seconds elapsed\n",
      "\n",
      "Epoch 280 starting..\n",
      "Epoch 280 / Batch (1/17) / Accuracy 0.8188 / Loss 0.447841\n",
      "Epoch 280 / Batch (2/17) / Accuracy 0.7800 / Loss 0.532086\n",
      "Epoch 280 / Batch (3/17) / Accuracy 0.8400 / Loss 0.394497\n",
      "Epoch 280 / Batch (4/17) / Accuracy 0.7981 / Loss 0.502425\n",
      "Epoch 280 / Batch (5/17) / Accuracy 0.8363 / Loss 0.419547\n",
      "Epoch 280 / Batch (6/17) / Accuracy 0.8125 / Loss 0.450453\n",
      "Epoch 280 / Batch (7/17) / Accuracy 0.8163 / Loss 0.465225\n",
      "Epoch 280 / Batch (8/17) / Accuracy 0.8344 / Loss 0.423439\n",
      "Epoch 280 / Batch (9/17) / Accuracy 0.8288 / Loss 0.442197\n",
      "Epoch 280 / Batch (10/17) / Accuracy 0.8687 / Loss 0.361816\n",
      "Epoch 280 / Batch (11/17) / Accuracy 0.7919 / Loss 0.484572\n",
      "Epoch 280 / Batch (12/17) / Accuracy 0.8188 / Loss 0.459179\n",
      "Epoch 280 / Batch (13/17) / Accuracy 0.8156 / Loss 0.469495\n",
      "Epoch 280 / Batch (14/17) / Accuracy 0.8462 / Loss 0.442390\n",
      "Epoch 280 / Batch (15/17) / Accuracy 0.8181 / Loss 0.467150\n",
      "Epoch 280 / Batch (16/17) / Accuracy 0.8406 / Loss 0.423403\n",
      "Epoch 280 / Batch (17/17) / Accuracy 0.8375 / Loss 0.395240\n",
      "Epoch 280 complete, 5.89605712890625 seconds elapsed\n",
      "\n",
      "Epoch 281 starting..\n",
      "Epoch 281 / Batch (1/17) / Accuracy 0.8188 / Loss 0.451707\n",
      "Epoch 281 / Batch (2/17) / Accuracy 0.8213 / Loss 0.431978\n",
      "Epoch 281 / Batch (3/17) / Accuracy 0.7437 / Loss 0.591249\n",
      "Epoch 281 / Batch (4/17) / Accuracy 0.8100 / Loss 0.472640\n",
      "Epoch 281 / Batch (5/17) / Accuracy 0.8456 / Loss 0.403926\n",
      "Epoch 281 / Batch (6/17) / Accuracy 0.8456 / Loss 0.418231\n",
      "Epoch 281 / Batch (7/17) / Accuracy 0.7706 / Loss 0.549249\n",
      "Epoch 281 / Batch (8/17) / Accuracy 0.8062 / Loss 0.498079\n",
      "Epoch 281 / Batch (9/17) / Accuracy 0.8238 / Loss 0.442294\n",
      "Epoch 281 / Batch (10/17) / Accuracy 0.7987 / Loss 0.462718\n",
      "Epoch 281 / Batch (11/17) / Accuracy 0.8163 / Loss 0.478992\n",
      "Epoch 281 / Batch (12/17) / Accuracy 0.8331 / Loss 0.417909\n",
      "Epoch 281 / Batch (13/17) / Accuracy 0.7862 / Loss 0.517754\n",
      "Epoch 281 / Batch (14/17) / Accuracy 0.8331 / Loss 0.433255\n",
      "Epoch 281 / Batch (15/17) / Accuracy 0.8156 / Loss 0.456103\n",
      "Epoch 281 / Batch (16/17) / Accuracy 0.8037 / Loss 0.472587\n",
      "Epoch 281 / Batch (17/17) / Accuracy 0.8350 / Loss 0.413600\n",
      "Epoch 281 complete, 5.696703910827637 seconds elapsed\n",
      "\n",
      "Epoch 282 starting..\n",
      "Epoch 282 / Batch (1/17) / Accuracy 0.8519 / Loss 0.412668\n",
      "Epoch 282 / Batch (2/17) / Accuracy 0.8150 / Loss 0.485653\n",
      "Epoch 282 / Batch (3/17) / Accuracy 0.8050 / Loss 0.471725\n",
      "Epoch 282 / Batch (4/17) / Accuracy 0.8037 / Loss 0.461337\n",
      "Epoch 282 / Batch (5/17) / Accuracy 0.8100 / Loss 0.474841\n",
      "Epoch 282 / Batch (6/17) / Accuracy 0.8569 / Loss 0.384210\n",
      "Epoch 282 / Batch (7/17) / Accuracy 0.8637 / Loss 0.367605\n",
      "Epoch 282 / Batch (8/17) / Accuracy 0.7719 / Loss 0.541044\n",
      "Epoch 282 / Batch (9/17) / Accuracy 0.8537 / Loss 0.395521\n",
      "Epoch 282 / Batch (10/17) / Accuracy 0.8037 / Loss 0.486424\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 282 / Batch (11/17) / Accuracy 0.8194 / Loss 0.455784\n",
      "Epoch 282 / Batch (12/17) / Accuracy 0.8394 / Loss 0.425780\n",
      "Epoch 282 / Batch (13/17) / Accuracy 0.8288 / Loss 0.452382\n",
      "Epoch 282 / Batch (14/17) / Accuracy 0.7856 / Loss 0.504065\n",
      "Epoch 282 / Batch (15/17) / Accuracy 0.8206 / Loss 0.477182\n",
      "Epoch 282 / Batch (16/17) / Accuracy 0.8313 / Loss 0.448391\n",
      "Epoch 282 / Batch (17/17) / Accuracy 0.8325 / Loss 0.435069\n",
      "Epoch 282 complete, 5.559034824371338 seconds elapsed\n",
      "\n",
      "Epoch 283 starting..\n",
      "Epoch 283 / Batch (1/17) / Accuracy 0.7994 / Loss 0.500007\n",
      "Epoch 283 / Batch (2/17) / Accuracy 0.8256 / Loss 0.448884\n",
      "Epoch 283 / Batch (3/17) / Accuracy 0.8188 / Loss 0.445747\n",
      "Epoch 283 / Batch (4/17) / Accuracy 0.8219 / Loss 0.462280\n",
      "Epoch 283 / Batch (5/17) / Accuracy 0.8150 / Loss 0.468585\n",
      "Epoch 283 / Batch (6/17) / Accuracy 0.8150 / Loss 0.466631\n",
      "Epoch 283 / Batch (7/17) / Accuracy 0.8356 / Loss 0.437286\n",
      "Epoch 283 / Batch (8/17) / Accuracy 0.8125 / Loss 0.474973\n",
      "Epoch 283 / Batch (9/17) / Accuracy 0.8281 / Loss 0.444602\n",
      "Epoch 283 / Batch (10/17) / Accuracy 0.7981 / Loss 0.491652\n",
      "Epoch 283 / Batch (11/17) / Accuracy 0.7875 / Loss 0.554445\n",
      "Epoch 283 / Batch (12/17) / Accuracy 0.8356 / Loss 0.423228\n",
      "Epoch 283 / Batch (13/17) / Accuracy 0.7875 / Loss 0.531662\n",
      "Epoch 283 / Batch (14/17) / Accuracy 0.8181 / Loss 0.467347\n",
      "Epoch 283 / Batch (15/17) / Accuracy 0.8238 / Loss 0.463790\n",
      "Epoch 283 / Batch (16/17) / Accuracy 0.8131 / Loss 0.468870\n",
      "Epoch 283 / Batch (17/17) / Accuracy 0.8325 / Loss 0.430050\n",
      "Epoch 283 complete, 5.949430227279663 seconds elapsed\n",
      "\n",
      "Epoch 284 starting..\n",
      "Epoch 284 / Batch (1/17) / Accuracy 0.8075 / Loss 0.461494\n",
      "Epoch 284 / Batch (2/17) / Accuracy 0.8206 / Loss 0.436500\n",
      "Epoch 284 / Batch (3/17) / Accuracy 0.8238 / Loss 0.451963\n",
      "Epoch 284 / Batch (4/17) / Accuracy 0.8475 / Loss 0.408958\n",
      "Epoch 284 / Batch (5/17) / Accuracy 0.8213 / Loss 0.463101\n",
      "Epoch 284 / Batch (6/17) / Accuracy 0.8194 / Loss 0.489873\n",
      "Epoch 284 / Batch (7/17) / Accuracy 0.8288 / Loss 0.414189\n",
      "Epoch 284 / Batch (8/17) / Accuracy 0.8794 / Loss 0.338038\n",
      "Epoch 284 / Batch (9/17) / Accuracy 0.8269 / Loss 0.466072\n",
      "Epoch 284 / Batch (10/17) / Accuracy 0.8100 / Loss 0.450672\n",
      "Epoch 284 / Batch (11/17) / Accuracy 0.8075 / Loss 0.486013\n",
      "Epoch 284 / Batch (12/17) / Accuracy 0.8275 / Loss 0.425403\n",
      "Epoch 284 / Batch (13/17) / Accuracy 0.8313 / Loss 0.418959\n",
      "Epoch 284 / Batch (14/17) / Accuracy 0.8163 / Loss 0.464463\n",
      "Epoch 284 / Batch (15/17) / Accuracy 0.8450 / Loss 0.417678\n",
      "Epoch 284 / Batch (16/17) / Accuracy 0.8106 / Loss 0.480934\n",
      "Epoch 284 / Batch (17/17) / Accuracy 0.7894 / Loss 0.499575\n",
      "Epoch 284 complete, 5.577677965164185 seconds elapsed\n",
      "\n",
      "Epoch 285 starting..\n",
      "Epoch 285 / Batch (1/17) / Accuracy 0.7850 / Loss 0.515885\n",
      "Epoch 285 / Batch (2/17) / Accuracy 0.8469 / Loss 0.388869\n",
      "Epoch 285 / Batch (3/17) / Accuracy 0.8256 / Loss 0.436173\n",
      "Epoch 285 / Batch (4/17) / Accuracy 0.8138 / Loss 0.460638\n",
      "Epoch 285 / Batch (5/17) / Accuracy 0.7825 / Loss 0.514425\n",
      "Epoch 285 / Batch (6/17) / Accuracy 0.8037 / Loss 0.478084\n",
      "Epoch 285 / Batch (7/17) / Accuracy 0.8150 / Loss 0.441333\n",
      "Epoch 285 / Batch (8/17) / Accuracy 0.7900 / Loss 0.503148\n",
      "Epoch 285 / Batch (9/17) / Accuracy 0.8062 / Loss 0.477187\n",
      "Epoch 285 / Batch (10/17) / Accuracy 0.8300 / Loss 0.443945\n",
      "Epoch 285 / Batch (11/17) / Accuracy 0.8238 / Loss 0.462425\n",
      "Epoch 285 / Batch (12/17) / Accuracy 0.8131 / Loss 0.454160\n",
      "Epoch 285 / Batch (13/17) / Accuracy 0.8075 / Loss 0.485338\n",
      "Epoch 285 / Batch (14/17) / Accuracy 0.8012 / Loss 0.469464\n",
      "Epoch 285 / Batch (15/17) / Accuracy 0.8081 / Loss 0.468580\n",
      "Epoch 285 / Batch (16/17) / Accuracy 0.7713 / Loss 0.546878\n",
      "Epoch 285 / Batch (17/17) / Accuracy 0.8425 / Loss 0.380011\n",
      "Epoch 285 complete, 5.859332323074341 seconds elapsed\n",
      "\n",
      "Epoch 286 starting..\n",
      "Epoch 286 / Batch (1/17) / Accuracy 0.8044 / Loss 0.494554\n",
      "Epoch 286 / Batch (2/17) / Accuracy 0.7556 / Loss 0.569236\n",
      "Epoch 286 / Batch (3/17) / Accuracy 0.8413 / Loss 0.418770\n",
      "Epoch 286 / Batch (4/17) / Accuracy 0.8181 / Loss 0.452741\n",
      "Epoch 286 / Batch (5/17) / Accuracy 0.7812 / Loss 0.539077\n",
      "Epoch 286 / Batch (6/17) / Accuracy 0.8244 / Loss 0.444500\n",
      "Epoch 286 / Batch (7/17) / Accuracy 0.8313 / Loss 0.438802\n",
      "Epoch 286 / Batch (8/17) / Accuracy 0.8294 / Loss 0.436483\n",
      "Epoch 286 / Batch (9/17) / Accuracy 0.8487 / Loss 0.386973\n",
      "Epoch 286 / Batch (10/17) / Accuracy 0.8244 / Loss 0.475388\n",
      "Epoch 286 / Batch (11/17) / Accuracy 0.7894 / Loss 0.506999\n",
      "Epoch 286 / Batch (12/17) / Accuracy 0.8012 / Loss 0.493935\n",
      "Epoch 286 / Batch (13/17) / Accuracy 0.7831 / Loss 0.510514\n",
      "Epoch 286 / Batch (14/17) / Accuracy 0.8144 / Loss 0.454938\n",
      "Epoch 286 / Batch (15/17) / Accuracy 0.8106 / Loss 0.485302\n",
      "Epoch 286 / Batch (16/17) / Accuracy 0.8150 / Loss 0.452389\n",
      "Epoch 286 / Batch (17/17) / Accuracy 0.8181 / Loss 0.446390\n",
      "Epoch 286 complete, 6.059345722198486 seconds elapsed\n",
      "\n",
      "Epoch 287 starting..\n",
      "Epoch 287 / Batch (1/17) / Accuracy 0.8006 / Loss 0.454563\n",
      "Epoch 287 / Batch (2/17) / Accuracy 0.8044 / Loss 0.453454\n",
      "Epoch 287 / Batch (3/17) / Accuracy 0.8250 / Loss 0.425552\n",
      "Epoch 287 / Batch (4/17) / Accuracy 0.8169 / Loss 0.466047\n",
      "Epoch 287 / Batch (5/17) / Accuracy 0.8044 / Loss 0.503141\n",
      "Epoch 287 / Batch (6/17) / Accuracy 0.8100 / Loss 0.504188\n",
      "Epoch 287 / Batch (7/17) / Accuracy 0.8506 / Loss 0.382114\n",
      "Epoch 287 / Batch (8/17) / Accuracy 0.8250 / Loss 0.461911\n",
      "Epoch 287 / Batch (9/17) / Accuracy 0.8087 / Loss 0.467609\n",
      "Epoch 287 / Batch (10/17) / Accuracy 0.8106 / Loss 0.487010\n",
      "Epoch 287 / Batch (11/17) / Accuracy 0.8238 / Loss 0.455768\n",
      "Epoch 287 / Batch (12/17) / Accuracy 0.8200 / Loss 0.465636\n",
      "Epoch 287 / Batch (13/17) / Accuracy 0.8175 / Loss 0.476330\n",
      "Epoch 287 / Batch (14/17) / Accuracy 0.8094 / Loss 0.455988\n",
      "Epoch 287 / Batch (15/17) / Accuracy 0.8025 / Loss 0.498420\n",
      "Epoch 287 / Batch (16/17) / Accuracy 0.8456 / Loss 0.416331\n",
      "Epoch 287 / Batch (17/17) / Accuracy 0.7962 / Loss 0.488729\n",
      "Epoch 287 complete, 5.466048717498779 seconds elapsed\n",
      "\n",
      "Epoch 288 starting..\n",
      "Epoch 288 / Batch (1/17) / Accuracy 0.7812 / Loss 0.529532\n",
      "Epoch 288 / Batch (2/17) / Accuracy 0.8000 / Loss 0.479239\n",
      "Epoch 288 / Batch (3/17) / Accuracy 0.8012 / Loss 0.463083\n",
      "Epoch 288 / Batch (4/17) / Accuracy 0.7962 / Loss 0.546910\n",
      "Epoch 288 / Batch (5/17) / Accuracy 0.8169 / Loss 0.445858\n",
      "Epoch 288 / Batch (6/17) / Accuracy 0.7575 / Loss 0.591768\n",
      "Epoch 288 / Batch (7/17) / Accuracy 0.8188 / Loss 0.463683\n",
      "Epoch 288 / Batch (8/17) / Accuracy 0.7581 / Loss 0.606723\n",
      "Epoch 288 / Batch (9/17) / Accuracy 0.8056 / Loss 0.474619\n",
      "Epoch 288 / Batch (10/17) / Accuracy 0.8375 / Loss 0.425394\n",
      "Epoch 288 / Batch (11/17) / Accuracy 0.8313 / Loss 0.461498\n",
      "Epoch 288 / Batch (12/17) / Accuracy 0.8469 / Loss 0.403414\n",
      "Epoch 288 / Batch (13/17) / Accuracy 0.8144 / Loss 0.449410\n",
      "Epoch 288 / Batch (14/17) / Accuracy 0.8350 / Loss 0.422484\n",
      "Epoch 288 / Batch (15/17) / Accuracy 0.8356 / Loss 0.422163\n",
      "Epoch 288 / Batch (16/17) / Accuracy 0.8319 / Loss 0.421706\n",
      "Epoch 288 / Batch (17/17) / Accuracy 0.7769 / Loss 0.547725\n",
      "Epoch 288 complete, 5.495165586471558 seconds elapsed\n",
      "\n",
      "Epoch 289 starting..\n",
      "Epoch 289 / Batch (1/17) / Accuracy 0.7900 / Loss 0.540005\n",
      "Epoch 289 / Batch (2/17) / Accuracy 0.8131 / Loss 0.474975\n",
      "Epoch 289 / Batch (3/17) / Accuracy 0.8300 / Loss 0.415872\n",
      "Epoch 289 / Batch (4/17) / Accuracy 0.8131 / Loss 0.444573\n",
      "Epoch 289 / Batch (5/17) / Accuracy 0.8163 / Loss 0.455550\n",
      "Epoch 289 / Batch (6/17) / Accuracy 0.8181 / Loss 0.445157\n",
      "Epoch 289 / Batch (7/17) / Accuracy 0.8006 / Loss 0.506712\n",
      "Epoch 289 / Batch (8/17) / Accuracy 0.8169 / Loss 0.472009\n",
      "Epoch 289 / Batch (9/17) / Accuracy 0.7975 / Loss 0.496861\n",
      "Epoch 289 / Batch (10/17) / Accuracy 0.8250 / Loss 0.430500\n",
      "Epoch 289 / Batch (11/17) / Accuracy 0.8444 / Loss 0.409501\n",
      "Epoch 289 / Batch (12/17) / Accuracy 0.8012 / Loss 0.504168\n",
      "Epoch 289 / Batch (13/17) / Accuracy 0.7969 / Loss 0.514017\n",
      "Epoch 289 / Batch (14/17) / Accuracy 0.7756 / Loss 0.567792\n",
      "Epoch 289 / Batch (15/17) / Accuracy 0.7937 / Loss 0.508325\n",
      "Epoch 289 / Batch (16/17) / Accuracy 0.7775 / Loss 0.557006\n",
      "Epoch 289 / Batch (17/17) / Accuracy 0.8375 / Loss 0.442621\n",
      "Epoch 289 complete, 5.742351531982422 seconds elapsed\n",
      "\n",
      "Epoch 290 starting..\n",
      "Epoch 290 / Batch (1/17) / Accuracy 0.7981 / Loss 0.493363\n",
      "Epoch 290 / Batch (2/17) / Accuracy 0.7819 / Loss 0.519837\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 290 / Batch (3/17) / Accuracy 0.8219 / Loss 0.430371\n",
      "Epoch 290 / Batch (4/17) / Accuracy 0.8106 / Loss 0.487210\n",
      "Epoch 290 / Batch (5/17) / Accuracy 0.8150 / Loss 0.470605\n",
      "Epoch 290 / Batch (6/17) / Accuracy 0.8112 / Loss 0.498537\n",
      "Epoch 290 / Batch (7/17) / Accuracy 0.8275 / Loss 0.461549\n",
      "Epoch 290 / Batch (8/17) / Accuracy 0.8400 / Loss 0.410112\n",
      "Epoch 290 / Batch (9/17) / Accuracy 0.8288 / Loss 0.474041\n",
      "Epoch 290 / Batch (10/17) / Accuracy 0.8112 / Loss 0.451521\n",
      "Epoch 290 / Batch (11/17) / Accuracy 0.8175 / Loss 0.476594\n",
      "Epoch 290 / Batch (12/17) / Accuracy 0.8306 / Loss 0.429783\n",
      "Epoch 290 / Batch (13/17) / Accuracy 0.7975 / Loss 0.493039\n",
      "Epoch 290 / Batch (14/17) / Accuracy 0.8487 / Loss 0.407023\n",
      "Epoch 290 / Batch (15/17) / Accuracy 0.8006 / Loss 0.529298\n",
      "Epoch 290 / Batch (16/17) / Accuracy 0.8244 / Loss 0.435627\n",
      "Epoch 290 / Batch (17/17) / Accuracy 0.8550 / Loss 0.379092\n",
      "Epoch 290 complete, 6.081199407577515 seconds elapsed\n",
      "\n",
      "Epoch 291 starting..\n",
      "Epoch 291 / Batch (1/17) / Accuracy 0.8056 / Loss 0.482055\n",
      "Epoch 291 / Batch (2/17) / Accuracy 0.8288 / Loss 0.422665\n",
      "Epoch 291 / Batch (3/17) / Accuracy 0.8219 / Loss 0.465484\n",
      "Epoch 291 / Batch (4/17) / Accuracy 0.8169 / Loss 0.457168\n",
      "Epoch 291 / Batch (5/17) / Accuracy 0.8506 / Loss 0.394166\n",
      "Epoch 291 / Batch (6/17) / Accuracy 0.7875 / Loss 0.512520\n",
      "Epoch 291 / Batch (7/17) / Accuracy 0.8375 / Loss 0.445755\n",
      "Epoch 291 / Batch (8/17) / Accuracy 0.8406 / Loss 0.408872\n",
      "Epoch 291 / Batch (9/17) / Accuracy 0.8344 / Loss 0.437233\n",
      "Epoch 291 / Batch (10/17) / Accuracy 0.8319 / Loss 0.403594\n",
      "Epoch 291 / Batch (11/17) / Accuracy 0.8200 / Loss 0.465451\n",
      "Epoch 291 / Batch (12/17) / Accuracy 0.7825 / Loss 0.511793\n",
      "Epoch 291 / Batch (13/17) / Accuracy 0.8025 / Loss 0.495816\n",
      "Epoch 291 / Batch (14/17) / Accuracy 0.8012 / Loss 0.498689\n",
      "Epoch 291 / Batch (15/17) / Accuracy 0.8494 / Loss 0.404954\n",
      "Epoch 291 / Batch (16/17) / Accuracy 0.7831 / Loss 0.524389\n",
      "Epoch 291 / Batch (17/17) / Accuracy 0.7862 / Loss 0.539735\n",
      "Epoch 291 complete, 5.260707855224609 seconds elapsed\n",
      "\n",
      "Epoch 292 starting..\n",
      "Epoch 292 / Batch (1/17) / Accuracy 0.8269 / Loss 0.426497\n",
      "Epoch 292 / Batch (2/17) / Accuracy 0.8213 / Loss 0.469953\n",
      "Epoch 292 / Batch (3/17) / Accuracy 0.8131 / Loss 0.462102\n",
      "Epoch 292 / Batch (4/17) / Accuracy 0.8244 / Loss 0.446321\n",
      "Epoch 292 / Batch (5/17) / Accuracy 0.8169 / Loss 0.452535\n",
      "Epoch 292 / Batch (6/17) / Accuracy 0.8150 / Loss 0.476482\n",
      "Epoch 292 / Batch (7/17) / Accuracy 0.8494 / Loss 0.417938\n",
      "Epoch 292 / Batch (8/17) / Accuracy 0.7794 / Loss 0.508627\n",
      "Epoch 292 / Batch (9/17) / Accuracy 0.7619 / Loss 0.566992\n",
      "Epoch 292 / Batch (10/17) / Accuracy 0.8512 / Loss 0.392942\n",
      "Epoch 292 / Batch (11/17) / Accuracy 0.8012 / Loss 0.467501\n",
      "Epoch 292 / Batch (12/17) / Accuracy 0.8288 / Loss 0.438733\n",
      "Epoch 292 / Batch (13/17) / Accuracy 0.8188 / Loss 0.443200\n",
      "Epoch 292 / Batch (14/17) / Accuracy 0.7575 / Loss 0.537773\n",
      "Epoch 292 / Batch (15/17) / Accuracy 0.8363 / Loss 0.430290\n",
      "Epoch 292 / Batch (16/17) / Accuracy 0.8519 / Loss 0.393381\n",
      "Epoch 292 / Batch (17/17) / Accuracy 0.8356 / Loss 0.433176\n",
      "Epoch 292 complete, 5.335008382797241 seconds elapsed\n",
      "\n",
      "Epoch 293 starting..\n",
      "Epoch 293 / Batch (1/17) / Accuracy 0.7937 / Loss 0.497488\n",
      "Epoch 293 / Batch (2/17) / Accuracy 0.8562 / Loss 0.394026\n",
      "Epoch 293 / Batch (3/17) / Accuracy 0.8194 / Loss 0.447075\n",
      "Epoch 293 / Batch (4/17) / Accuracy 0.8119 / Loss 0.462293\n",
      "Epoch 293 / Batch (5/17) / Accuracy 0.7800 / Loss 0.518123\n",
      "Epoch 293 / Batch (6/17) / Accuracy 0.8581 / Loss 0.387593\n",
      "Epoch 293 / Batch (7/17) / Accuracy 0.7669 / Loss 0.576271\n",
      "Epoch 293 / Batch (8/17) / Accuracy 0.8138 / Loss 0.437355\n",
      "Epoch 293 / Batch (9/17) / Accuracy 0.8256 / Loss 0.458311\n",
      "Epoch 293 / Batch (10/17) / Accuracy 0.8238 / Loss 0.445578\n",
      "Epoch 293 / Batch (11/17) / Accuracy 0.7906 / Loss 0.523173\n",
      "Epoch 293 / Batch (12/17) / Accuracy 0.8188 / Loss 0.440755\n",
      "Epoch 293 / Batch (13/17) / Accuracy 0.8012 / Loss 0.485398\n",
      "Epoch 293 / Batch (14/17) / Accuracy 0.8288 / Loss 0.423982\n",
      "Epoch 293 / Batch (15/17) / Accuracy 0.7987 / Loss 0.473322\n",
      "Epoch 293 / Batch (16/17) / Accuracy 0.8288 / Loss 0.445122\n",
      "Epoch 293 / Batch (17/17) / Accuracy 0.8325 / Loss 0.415009\n",
      "Epoch 293 complete, 5.646803140640259 seconds elapsed\n",
      "\n",
      "Epoch 294 starting..\n",
      "Epoch 294 / Batch (1/17) / Accuracy 0.7706 / Loss 0.557210\n",
      "Epoch 294 / Batch (2/17) / Accuracy 0.8050 / Loss 0.466851\n",
      "Epoch 294 / Batch (3/17) / Accuracy 0.7875 / Loss 0.511968\n",
      "Epoch 294 / Batch (4/17) / Accuracy 0.8381 / Loss 0.405188\n",
      "Epoch 294 / Batch (5/17) / Accuracy 0.8256 / Loss 0.421269\n",
      "Epoch 294 / Batch (6/17) / Accuracy 0.8069 / Loss 0.469609\n",
      "Epoch 294 / Batch (7/17) / Accuracy 0.8163 / Loss 0.442012\n",
      "Epoch 294 / Batch (8/17) / Accuracy 0.8363 / Loss 0.412192\n",
      "Epoch 294 / Batch (9/17) / Accuracy 0.8194 / Loss 0.438213\n",
      "Epoch 294 / Batch (10/17) / Accuracy 0.8119 / Loss 0.473126\n",
      "Epoch 294 / Batch (11/17) / Accuracy 0.7981 / Loss 0.499652\n",
      "Epoch 294 / Batch (12/17) / Accuracy 0.8181 / Loss 0.477044\n",
      "Epoch 294 / Batch (13/17) / Accuracy 0.7900 / Loss 0.500620\n",
      "Epoch 294 / Batch (14/17) / Accuracy 0.8144 / Loss 0.478468\n",
      "Epoch 294 / Batch (15/17) / Accuracy 0.8050 / Loss 0.499750\n",
      "Epoch 294 / Batch (16/17) / Accuracy 0.8462 / Loss 0.412864\n",
      "Epoch 294 / Batch (17/17) / Accuracy 0.8219 / Loss 0.407906\n",
      "Epoch 294 complete, 5.618942975997925 seconds elapsed\n",
      "\n",
      "Epoch 295 starting..\n",
      "Epoch 295 / Batch (1/17) / Accuracy 0.7794 / Loss 0.514189\n",
      "Epoch 295 / Batch (2/17) / Accuracy 0.8219 / Loss 0.434982\n",
      "Epoch 295 / Batch (3/17) / Accuracy 0.8294 / Loss 0.440931\n",
      "Epoch 295 / Batch (4/17) / Accuracy 0.7681 / Loss 0.539878\n",
      "Epoch 295 / Batch (5/17) / Accuracy 0.8350 / Loss 0.432121\n",
      "Epoch 295 / Batch (6/17) / Accuracy 0.8294 / Loss 0.442061\n",
      "Epoch 295 / Batch (7/17) / Accuracy 0.8306 / Loss 0.435228\n",
      "Epoch 295 / Batch (8/17) / Accuracy 0.7887 / Loss 0.514240\n",
      "Epoch 295 / Batch (9/17) / Accuracy 0.8400 / Loss 0.424585\n",
      "Epoch 295 / Batch (10/17) / Accuracy 0.8062 / Loss 0.481435\n",
      "Epoch 295 / Batch (11/17) / Accuracy 0.8194 / Loss 0.440687\n",
      "Epoch 295 / Batch (12/17) / Accuracy 0.8238 / Loss 0.429340\n",
      "Epoch 295 / Batch (13/17) / Accuracy 0.8044 / Loss 0.476377\n",
      "Epoch 295 / Batch (14/17) / Accuracy 0.8019 / Loss 0.491560\n",
      "Epoch 295 / Batch (15/17) / Accuracy 0.8169 / Loss 0.453285\n",
      "Epoch 295 / Batch (16/17) / Accuracy 0.8331 / Loss 0.421668\n",
      "Epoch 295 / Batch (17/17) / Accuracy 0.8331 / Loss 0.430366\n",
      "Epoch 295 complete, 5.6827826499938965 seconds elapsed\n",
      "\n",
      "Epoch 296 starting..\n",
      "Epoch 296 / Batch (1/17) / Accuracy 0.8462 / Loss 0.412718\n",
      "Epoch 296 / Batch (2/17) / Accuracy 0.8156 / Loss 0.438190\n",
      "Epoch 296 / Batch (3/17) / Accuracy 0.8487 / Loss 0.400279\n",
      "Epoch 296 / Batch (4/17) / Accuracy 0.8263 / Loss 0.431442\n",
      "Epoch 296 / Batch (5/17) / Accuracy 0.8419 / Loss 0.418308\n",
      "Epoch 296 / Batch (6/17) / Accuracy 0.8169 / Loss 0.468516\n",
      "Epoch 296 / Batch (7/17) / Accuracy 0.8238 / Loss 0.449606\n",
      "Epoch 296 / Batch (8/17) / Accuracy 0.8269 / Loss 0.428280\n",
      "Epoch 296 / Batch (9/17) / Accuracy 0.8438 / Loss 0.397994\n",
      "Epoch 296 / Batch (10/17) / Accuracy 0.8500 / Loss 0.389247\n",
      "Epoch 296 / Batch (11/17) / Accuracy 0.8081 / Loss 0.464459\n",
      "Epoch 296 / Batch (12/17) / Accuracy 0.7931 / Loss 0.507505\n",
      "Epoch 296 / Batch (13/17) / Accuracy 0.8200 / Loss 0.446630\n",
      "Epoch 296 / Batch (14/17) / Accuracy 0.8450 / Loss 0.394508\n",
      "Epoch 296 / Batch (15/17) / Accuracy 0.8044 / Loss 0.489964\n",
      "Epoch 296 / Batch (16/17) / Accuracy 0.8256 / Loss 0.445936\n",
      "Epoch 296 / Batch (17/17) / Accuracy 0.8244 / Loss 0.447368\n",
      "Epoch 296 complete, 5.615494012832642 seconds elapsed\n",
      "\n",
      "Epoch 297 starting..\n",
      "Epoch 297 / Batch (1/17) / Accuracy 0.8456 / Loss 0.381521\n",
      "Epoch 297 / Batch (2/17) / Accuracy 0.8138 / Loss 0.476113\n",
      "Epoch 297 / Batch (3/17) / Accuracy 0.8394 / Loss 0.416285\n",
      "Epoch 297 / Batch (4/17) / Accuracy 0.8169 / Loss 0.453460\n",
      "Epoch 297 / Batch (5/17) / Accuracy 0.8306 / Loss 0.426325\n",
      "Epoch 297 / Batch (6/17) / Accuracy 0.8612 / Loss 0.389957\n",
      "Epoch 297 / Batch (7/17) / Accuracy 0.8062 / Loss 0.468370\n",
      "Epoch 297 / Batch (8/17) / Accuracy 0.8200 / Loss 0.451889\n",
      "Epoch 297 / Batch (9/17) / Accuracy 0.8025 / Loss 0.468534\n",
      "Epoch 297 / Batch (10/17) / Accuracy 0.8150 / Loss 0.428383\n",
      "Epoch 297 / Batch (11/17) / Accuracy 0.7969 / Loss 0.494556\n",
      "Epoch 297 / Batch (12/17) / Accuracy 0.8181 / Loss 0.457716\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 297 / Batch (13/17) / Accuracy 0.8194 / Loss 0.453274\n",
      "Epoch 297 / Batch (14/17) / Accuracy 0.8275 / Loss 0.437758\n",
      "Epoch 297 / Batch (15/17) / Accuracy 0.8487 / Loss 0.415197\n",
      "Epoch 297 / Batch (16/17) / Accuracy 0.7900 / Loss 0.525422\n",
      "Epoch 297 / Batch (17/17) / Accuracy 0.8081 / Loss 0.445249\n",
      "Epoch 297 complete, 6.12343168258667 seconds elapsed\n",
      "\n",
      "Epoch 298 starting..\n",
      "Epoch 298 / Batch (1/17) / Accuracy 0.8269 / Loss 0.413630\n",
      "Epoch 298 / Batch (2/17) / Accuracy 0.8125 / Loss 0.450087\n",
      "Epoch 298 / Batch (3/17) / Accuracy 0.7931 / Loss 0.505145\n",
      "Epoch 298 / Batch (4/17) / Accuracy 0.8581 / Loss 0.384580\n",
      "Epoch 298 / Batch (5/17) / Accuracy 0.7625 / Loss 0.575347\n",
      "Epoch 298 / Batch (6/17) / Accuracy 0.8419 / Loss 0.386529\n",
      "Epoch 298 / Batch (7/17) / Accuracy 0.8175 / Loss 0.438428\n",
      "Epoch 298 / Batch (8/17) / Accuracy 0.8306 / Loss 0.444675\n",
      "Epoch 298 / Batch (9/17) / Accuracy 0.8325 / Loss 0.434040\n",
      "Epoch 298 / Batch (10/17) / Accuracy 0.8144 / Loss 0.457286\n",
      "Epoch 298 / Batch (11/17) / Accuracy 0.8344 / Loss 0.426906\n",
      "Epoch 298 / Batch (12/17) / Accuracy 0.7681 / Loss 0.508263\n",
      "Epoch 298 / Batch (13/17) / Accuracy 0.8344 / Loss 0.404251\n",
      "Epoch 298 / Batch (14/17) / Accuracy 0.7669 / Loss 0.538514\n",
      "Epoch 298 / Batch (15/17) / Accuracy 0.8006 / Loss 0.488355\n",
      "Epoch 298 / Batch (16/17) / Accuracy 0.8469 / Loss 0.394064\n",
      "Epoch 298 / Batch (17/17) / Accuracy 0.8356 / Loss 0.427857\n",
      "Epoch 298 complete, 6.242105007171631 seconds elapsed\n",
      "\n",
      "Epoch 299 starting..\n",
      "Epoch 299 / Batch (1/17) / Accuracy 0.8213 / Loss 0.444727\n",
      "Epoch 299 / Batch (2/17) / Accuracy 0.8069 / Loss 0.501548\n",
      "Epoch 299 / Batch (3/17) / Accuracy 0.8406 / Loss 0.402624\n",
      "Epoch 299 / Batch (4/17) / Accuracy 0.8069 / Loss 0.454598\n",
      "Epoch 299 / Batch (5/17) / Accuracy 0.8087 / Loss 0.503132\n",
      "Epoch 299 / Batch (6/17) / Accuracy 0.8469 / Loss 0.393610\n",
      "Epoch 299 / Batch (7/17) / Accuracy 0.8012 / Loss 0.498429\n",
      "Epoch 299 / Batch (8/17) / Accuracy 0.8294 / Loss 0.440461\n",
      "Epoch 299 / Batch (9/17) / Accuracy 0.8338 / Loss 0.431529\n",
      "Epoch 299 / Batch (10/17) / Accuracy 0.8175 / Loss 0.453413\n",
      "Epoch 299 / Batch (11/17) / Accuracy 0.8238 / Loss 0.431672\n",
      "Epoch 299 / Batch (12/17) / Accuracy 0.8306 / Loss 0.426181\n",
      "Epoch 299 / Batch (13/17) / Accuracy 0.8712 / Loss 0.345827\n",
      "Epoch 299 / Batch (14/17) / Accuracy 0.8306 / Loss 0.448155\n",
      "Epoch 299 / Batch (15/17) / Accuracy 0.8481 / Loss 0.386861\n",
      "Epoch 299 / Batch (16/17) / Accuracy 0.8394 / Loss 0.403179\n",
      "Epoch 299 / Batch (17/17) / Accuracy 0.8250 / Loss 0.451717\n",
      "Epoch 299 complete, 5.993581295013428 seconds elapsed\n",
      "\n",
      "Epoch 300 starting..\n",
      "Epoch 300 / Batch (1/17) / Accuracy 0.8019 / Loss 0.474292\n",
      "Epoch 300 / Batch (2/17) / Accuracy 0.8506 / Loss 0.376123\n",
      "Epoch 300 / Batch (3/17) / Accuracy 0.8250 / Loss 0.438371\n",
      "Epoch 300 / Batch (4/17) / Accuracy 0.7756 / Loss 0.530347\n",
      "Epoch 300 / Batch (5/17) / Accuracy 0.8087 / Loss 0.485958\n",
      "Epoch 300 / Batch (6/17) / Accuracy 0.7931 / Loss 0.519368\n",
      "Epoch 300 / Batch (7/17) / Accuracy 0.8338 / Loss 0.410744\n",
      "Epoch 300 / Batch (8/17) / Accuracy 0.7837 / Loss 0.507108\n",
      "Epoch 300 / Batch (9/17) / Accuracy 0.8213 / Loss 0.469898\n",
      "Epoch 300 / Batch (10/17) / Accuracy 0.8475 / Loss 0.383452\n",
      "Epoch 300 / Batch (11/17) / Accuracy 0.7744 / Loss 0.534835\n",
      "Epoch 300 / Batch (12/17) / Accuracy 0.8356 / Loss 0.425507\n",
      "Epoch 300 / Batch (13/17) / Accuracy 0.8175 / Loss 0.428417\n",
      "Epoch 300 / Batch (14/17) / Accuracy 0.8331 / Loss 0.413894\n",
      "Epoch 300 / Batch (15/17) / Accuracy 0.8606 / Loss 0.382821\n",
      "Epoch 300 / Batch (16/17) / Accuracy 0.8288 / Loss 0.438939\n",
      "Epoch 300 / Batch (17/17) / Accuracy 0.8606 / Loss 0.372635\n",
      "Epoch 300 complete, 6.119603633880615 seconds elapsed\n",
      "\n",
      "Epoch 301 starting..\n",
      "Epoch 301 / Batch (1/17) / Accuracy 0.8138 / Loss 0.478871\n",
      "Epoch 301 / Batch (2/17) / Accuracy 0.7931 / Loss 0.527982\n",
      "Epoch 301 / Batch (3/17) / Accuracy 0.8556 / Loss 0.379952\n",
      "Epoch 301 / Batch (4/17) / Accuracy 0.8281 / Loss 0.433870\n",
      "Epoch 301 / Batch (5/17) / Accuracy 0.7788 / Loss 0.535381\n",
      "Epoch 301 / Batch (6/17) / Accuracy 0.8200 / Loss 0.476586\n",
      "Epoch 301 / Batch (7/17) / Accuracy 0.8094 / Loss 0.443918\n",
      "Epoch 301 / Batch (8/17) / Accuracy 0.8263 / Loss 0.442530\n",
      "Epoch 301 / Batch (9/17) / Accuracy 0.8194 / Loss 0.432636\n",
      "Epoch 301 / Batch (10/17) / Accuracy 0.8269 / Loss 0.443176\n",
      "Epoch 301 / Batch (11/17) / Accuracy 0.8081 / Loss 0.453947\n",
      "Epoch 301 / Batch (12/17) / Accuracy 0.8206 / Loss 0.477394\n",
      "Epoch 301 / Batch (13/17) / Accuracy 0.8019 / Loss 0.508466\n",
      "Epoch 301 / Batch (14/17) / Accuracy 0.8375 / Loss 0.411424\n",
      "Epoch 301 / Batch (15/17) / Accuracy 0.8375 / Loss 0.408824\n",
      "Epoch 301 / Batch (16/17) / Accuracy 0.8400 / Loss 0.422107\n",
      "Epoch 301 / Batch (17/17) / Accuracy 0.8438 / Loss 0.426588\n",
      "Epoch 301 complete, 5.859649896621704 seconds elapsed\n",
      "\n",
      "Epoch 302 starting..\n",
      "Epoch 302 / Batch (1/17) / Accuracy 0.8256 / Loss 0.415673\n",
      "Epoch 302 / Batch (2/17) / Accuracy 0.8363 / Loss 0.413241\n",
      "Epoch 302 / Batch (3/17) / Accuracy 0.8300 / Loss 0.441237\n",
      "Epoch 302 / Batch (4/17) / Accuracy 0.8356 / Loss 0.417310\n",
      "Epoch 302 / Batch (5/17) / Accuracy 0.8594 / Loss 0.360062\n",
      "Epoch 302 / Batch (6/17) / Accuracy 0.8131 / Loss 0.467967\n",
      "Epoch 302 / Batch (7/17) / Accuracy 0.8344 / Loss 0.426862\n",
      "Epoch 302 / Batch (8/17) / Accuracy 0.8206 / Loss 0.457616\n",
      "Epoch 302 / Batch (9/17) / Accuracy 0.8294 / Loss 0.428991\n",
      "Epoch 302 / Batch (10/17) / Accuracy 0.7819 / Loss 0.509686\n",
      "Epoch 302 / Batch (11/17) / Accuracy 0.7994 / Loss 0.495610\n",
      "Epoch 302 / Batch (12/17) / Accuracy 0.8225 / Loss 0.434243\n",
      "Epoch 302 / Batch (13/17) / Accuracy 0.8031 / Loss 0.491665\n",
      "Epoch 302 / Batch (14/17) / Accuracy 0.8069 / Loss 0.475047\n",
      "Epoch 302 / Batch (15/17) / Accuracy 0.8019 / Loss 0.481356\n",
      "Epoch 302 / Batch (16/17) / Accuracy 0.8419 / Loss 0.424595\n",
      "Epoch 302 / Batch (17/17) / Accuracy 0.8194 / Loss 0.447427\n",
      "Epoch 302 complete, 6.316688299179077 seconds elapsed\n",
      "\n",
      "Epoch 303 starting..\n",
      "Epoch 303 / Batch (1/17) / Accuracy 0.8450 / Loss 0.404164\n",
      "Epoch 303 / Batch (2/17) / Accuracy 0.8375 / Loss 0.425398\n",
      "Epoch 303 / Batch (3/17) / Accuracy 0.8213 / Loss 0.439280\n",
      "Epoch 303 / Batch (4/17) / Accuracy 0.8075 / Loss 0.475231\n",
      "Epoch 303 / Batch (5/17) / Accuracy 0.8225 / Loss 0.471012\n",
      "Epoch 303 / Batch (6/17) / Accuracy 0.8163 / Loss 0.463032\n",
      "Epoch 303 / Batch (7/17) / Accuracy 0.8344 / Loss 0.441727\n",
      "Epoch 303 / Batch (8/17) / Accuracy 0.8363 / Loss 0.408538\n",
      "Epoch 303 / Batch (9/17) / Accuracy 0.8263 / Loss 0.471349\n",
      "Epoch 303 / Batch (10/17) / Accuracy 0.7850 / Loss 0.507001\n",
      "Epoch 303 / Batch (11/17) / Accuracy 0.8231 / Loss 0.430945\n",
      "Epoch 303 / Batch (12/17) / Accuracy 0.8244 / Loss 0.425050\n",
      "Epoch 303 / Batch (13/17) / Accuracy 0.8069 / Loss 0.515609\n",
      "Epoch 303 / Batch (14/17) / Accuracy 0.8431 / Loss 0.409299\n",
      "Epoch 303 / Batch (15/17) / Accuracy 0.8025 / Loss 0.509969\n",
      "Epoch 303 / Batch (16/17) / Accuracy 0.8200 / Loss 0.448032\n",
      "Epoch 303 / Batch (17/17) / Accuracy 0.8263 / Loss 0.455977\n",
      "Epoch 303 complete, 5.5981385707855225 seconds elapsed\n",
      "\n",
      "Epoch 304 starting..\n",
      "Epoch 304 / Batch (1/17) / Accuracy 0.8244 / Loss 0.447062\n",
      "Epoch 304 / Batch (2/17) / Accuracy 0.7906 / Loss 0.522568\n",
      "Epoch 304 / Batch (3/17) / Accuracy 0.8194 / Loss 0.435322\n",
      "Epoch 304 / Batch (4/17) / Accuracy 0.8044 / Loss 0.461817\n",
      "Epoch 304 / Batch (5/17) / Accuracy 0.8175 / Loss 0.458035\n",
      "Epoch 304 / Batch (6/17) / Accuracy 0.8169 / Loss 0.448137\n",
      "Epoch 304 / Batch (7/17) / Accuracy 0.8175 / Loss 0.476016\n",
      "Epoch 304 / Batch (8/17) / Accuracy 0.8419 / Loss 0.394246\n",
      "Epoch 304 / Batch (9/17) / Accuracy 0.7956 / Loss 0.507720\n",
      "Epoch 304 / Batch (10/17) / Accuracy 0.8194 / Loss 0.485721\n",
      "Epoch 304 / Batch (11/17) / Accuracy 0.8294 / Loss 0.442964\n",
      "Epoch 304 / Batch (12/17) / Accuracy 0.8050 / Loss 0.483063\n",
      "Epoch 304 / Batch (13/17) / Accuracy 0.8375 / Loss 0.417416\n",
      "Epoch 304 / Batch (14/17) / Accuracy 0.8419 / Loss 0.410266\n",
      "Epoch 304 / Batch (15/17) / Accuracy 0.8019 / Loss 0.501440\n",
      "Epoch 304 / Batch (16/17) / Accuracy 0.8050 / Loss 0.489308\n",
      "Epoch 304 / Batch (17/17) / Accuracy 0.8375 / Loss 0.426898\n",
      "Epoch 304 complete, 5.668283224105835 seconds elapsed\n",
      "\n",
      "Epoch 305 starting..\n",
      "Epoch 305 / Batch (1/17) / Accuracy 0.8263 / Loss 0.429316\n",
      "Epoch 305 / Batch (2/17) / Accuracy 0.8288 / Loss 0.415609\n",
      "Epoch 305 / Batch (3/17) / Accuracy 0.8569 / Loss 0.368049\n",
      "Epoch 305 / Batch (4/17) / Accuracy 0.8438 / Loss 0.398344\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 305 / Batch (5/17) / Accuracy 0.8175 / Loss 0.443229\n",
      "Epoch 305 / Batch (6/17) / Accuracy 0.8044 / Loss 0.499914\n",
      "Epoch 305 / Batch (7/17) / Accuracy 0.8125 / Loss 0.434082\n",
      "Epoch 305 / Batch (8/17) / Accuracy 0.8031 / Loss 0.517825\n",
      "Epoch 305 / Batch (9/17) / Accuracy 0.8238 / Loss 0.436861\n",
      "Epoch 305 / Batch (10/17) / Accuracy 0.7875 / Loss 0.491925\n",
      "Epoch 305 / Batch (11/17) / Accuracy 0.8037 / Loss 0.479484\n",
      "Epoch 305 / Batch (12/17) / Accuracy 0.8094 / Loss 0.462124\n",
      "Epoch 305 / Batch (13/17) / Accuracy 0.8188 / Loss 0.459355\n",
      "Epoch 305 / Batch (14/17) / Accuracy 0.7819 / Loss 0.520497\n",
      "Epoch 305 / Batch (15/17) / Accuracy 0.8200 / Loss 0.463758\n",
      "Epoch 305 / Batch (16/17) / Accuracy 0.8350 / Loss 0.426681\n",
      "Epoch 305 / Batch (17/17) / Accuracy 0.8281 / Loss 0.425473\n",
      "Epoch 305 complete, 5.649144172668457 seconds elapsed\n",
      "\n",
      "Epoch 306 starting..\n",
      "Epoch 306 / Batch (1/17) / Accuracy 0.7831 / Loss 0.542304\n",
      "Epoch 306 / Batch (2/17) / Accuracy 0.8031 / Loss 0.495055\n",
      "Epoch 306 / Batch (3/17) / Accuracy 0.8106 / Loss 0.473358\n",
      "Epoch 306 / Batch (4/17) / Accuracy 0.8350 / Loss 0.415851\n",
      "Epoch 306 / Batch (5/17) / Accuracy 0.8313 / Loss 0.450689\n",
      "Epoch 306 / Batch (6/17) / Accuracy 0.8425 / Loss 0.406623\n",
      "Epoch 306 / Batch (7/17) / Accuracy 0.8288 / Loss 0.442053\n",
      "Epoch 306 / Batch (8/17) / Accuracy 0.8388 / Loss 0.427095\n",
      "Epoch 306 / Batch (9/17) / Accuracy 0.8163 / Loss 0.437476\n",
      "Epoch 306 / Batch (10/17) / Accuracy 0.8200 / Loss 0.421628\n",
      "Epoch 306 / Batch (11/17) / Accuracy 0.8056 / Loss 0.497130\n",
      "Epoch 306 / Batch (12/17) / Accuracy 0.8087 / Loss 0.459977\n",
      "Epoch 306 / Batch (13/17) / Accuracy 0.8350 / Loss 0.418097\n",
      "Epoch 306 / Batch (14/17) / Accuracy 0.8206 / Loss 0.464757\n",
      "Epoch 306 / Batch (15/17) / Accuracy 0.8356 / Loss 0.422426\n",
      "Epoch 306 / Batch (16/17) / Accuracy 0.8181 / Loss 0.474097\n",
      "Epoch 306 / Batch (17/17) / Accuracy 0.8462 / Loss 0.401015\n",
      "Epoch 306 complete, 6.037366151809692 seconds elapsed\n",
      "\n",
      "Epoch 307 starting..\n",
      "Epoch 307 / Batch (1/17) / Accuracy 0.8231 / Loss 0.420368\n",
      "Epoch 307 / Batch (2/17) / Accuracy 0.8419 / Loss 0.425637\n",
      "Epoch 307 / Batch (3/17) / Accuracy 0.8694 / Loss 0.348918\n",
      "Epoch 307 / Batch (4/17) / Accuracy 0.8119 / Loss 0.450867\n",
      "Epoch 307 / Batch (5/17) / Accuracy 0.8106 / Loss 0.466493\n",
      "Epoch 307 / Batch (6/17) / Accuracy 0.8356 / Loss 0.395156\n",
      "Epoch 307 / Batch (7/17) / Accuracy 0.8163 / Loss 0.459121\n",
      "Epoch 307 / Batch (8/17) / Accuracy 0.8188 / Loss 0.462108\n",
      "Epoch 307 / Batch (9/17) / Accuracy 0.8131 / Loss 0.480738\n",
      "Epoch 307 / Batch (10/17) / Accuracy 0.7987 / Loss 0.512250\n",
      "Epoch 307 / Batch (11/17) / Accuracy 0.8000 / Loss 0.520666\n",
      "Epoch 307 / Batch (12/17) / Accuracy 0.8319 / Loss 0.424286\n",
      "Epoch 307 / Batch (13/17) / Accuracy 0.8350 / Loss 0.416763\n",
      "Epoch 307 / Batch (14/17) / Accuracy 0.8275 / Loss 0.423848\n",
      "Epoch 307 / Batch (15/17) / Accuracy 0.8450 / Loss 0.415567\n",
      "Epoch 307 / Batch (16/17) / Accuracy 0.8650 / Loss 0.382980\n",
      "Epoch 307 / Batch (17/17) / Accuracy 0.8425 / Loss 0.437230\n",
      "Epoch 307 complete, 5.480876922607422 seconds elapsed\n",
      "\n",
      "Epoch 308 starting..\n",
      "Epoch 308 / Batch (1/17) / Accuracy 0.7525 / Loss 0.591447\n",
      "Epoch 308 / Batch (2/17) / Accuracy 0.8306 / Loss 0.443432\n",
      "Epoch 308 / Batch (3/17) / Accuracy 0.8581 / Loss 0.374336\n",
      "Epoch 308 / Batch (4/17) / Accuracy 0.8062 / Loss 0.461322\n",
      "Epoch 308 / Batch (5/17) / Accuracy 0.8225 / Loss 0.459716\n",
      "Epoch 308 / Batch (6/17) / Accuracy 0.8781 / Loss 0.338307\n",
      "Epoch 308 / Batch (7/17) / Accuracy 0.8188 / Loss 0.498308\n",
      "Epoch 308 / Batch (8/17) / Accuracy 0.8438 / Loss 0.391764\n",
      "Epoch 308 / Batch (9/17) / Accuracy 0.7956 / Loss 0.501178\n",
      "Epoch 308 / Batch (10/17) / Accuracy 0.8244 / Loss 0.450728\n",
      "Epoch 308 / Batch (11/17) / Accuracy 0.8575 / Loss 0.363924\n",
      "Epoch 308 / Batch (12/17) / Accuracy 0.7987 / Loss 0.507061\n",
      "Epoch 308 / Batch (13/17) / Accuracy 0.7944 / Loss 0.522767\n",
      "Epoch 308 / Batch (14/17) / Accuracy 0.8325 / Loss 0.426120\n",
      "Epoch 308 / Batch (15/17) / Accuracy 0.7937 / Loss 0.518958\n",
      "Epoch 308 / Batch (16/17) / Accuracy 0.8356 / Loss 0.437651\n",
      "Epoch 308 / Batch (17/17) / Accuracy 0.8256 / Loss 0.441762\n",
      "Epoch 308 complete, 6.224117279052734 seconds elapsed\n",
      "\n",
      "Epoch 309 starting..\n",
      "Epoch 309 / Batch (1/17) / Accuracy 0.8550 / Loss 0.378668\n",
      "Epoch 309 / Batch (2/17) / Accuracy 0.8263 / Loss 0.466227\n",
      "Epoch 309 / Batch (3/17) / Accuracy 0.8112 / Loss 0.467103\n",
      "Epoch 309 / Batch (4/17) / Accuracy 0.8363 / Loss 0.457640\n",
      "Epoch 309 / Batch (5/17) / Accuracy 0.7763 / Loss 0.501550\n",
      "Epoch 309 / Batch (6/17) / Accuracy 0.7763 / Loss 0.550597\n",
      "Epoch 309 / Batch (7/17) / Accuracy 0.8256 / Loss 0.438392\n",
      "Epoch 309 / Batch (8/17) / Accuracy 0.8275 / Loss 0.423728\n",
      "Epoch 309 / Batch (9/17) / Accuracy 0.7937 / Loss 0.498474\n",
      "Epoch 309 / Batch (10/17) / Accuracy 0.8081 / Loss 0.466310\n",
      "Epoch 309 / Batch (11/17) / Accuracy 0.8131 / Loss 0.463623\n",
      "Epoch 309 / Batch (12/17) / Accuracy 0.8388 / Loss 0.406092\n",
      "Epoch 309 / Batch (13/17) / Accuracy 0.8250 / Loss 0.420473\n",
      "Epoch 309 / Batch (14/17) / Accuracy 0.8025 / Loss 0.506069\n",
      "Epoch 309 / Batch (15/17) / Accuracy 0.7912 / Loss 0.516912\n",
      "Epoch 309 / Batch (16/17) / Accuracy 0.8200 / Loss 0.442750\n",
      "Epoch 309 / Batch (17/17) / Accuracy 0.7906 / Loss 0.535444\n",
      "Epoch 309 complete, 6.531177282333374 seconds elapsed\n",
      "\n",
      "Epoch 310 starting..\n",
      "Epoch 310 / Batch (1/17) / Accuracy 0.8081 / Loss 0.499998\n",
      "Epoch 310 / Batch (2/17) / Accuracy 0.8112 / Loss 0.449696\n",
      "Epoch 310 / Batch (3/17) / Accuracy 0.7981 / Loss 0.480271\n",
      "Epoch 310 / Batch (4/17) / Accuracy 0.8006 / Loss 0.483521\n",
      "Epoch 310 / Batch (5/17) / Accuracy 0.8294 / Loss 0.443192\n",
      "Epoch 310 / Batch (6/17) / Accuracy 0.8125 / Loss 0.487696\n",
      "Epoch 310 / Batch (7/17) / Accuracy 0.8169 / Loss 0.441701\n",
      "Epoch 310 / Batch (8/17) / Accuracy 0.8037 / Loss 0.486057\n",
      "Epoch 310 / Batch (9/17) / Accuracy 0.8056 / Loss 0.486524\n",
      "Epoch 310 / Batch (10/17) / Accuracy 0.8025 / Loss 0.495008\n",
      "Epoch 310 / Batch (11/17) / Accuracy 0.8444 / Loss 0.436006\n",
      "Epoch 310 / Batch (12/17) / Accuracy 0.8356 / Loss 0.421483\n",
      "Epoch 310 / Batch (13/17) / Accuracy 0.8031 / Loss 0.492457\n",
      "Epoch 310 / Batch (14/17) / Accuracy 0.8306 / Loss 0.397439\n",
      "Epoch 310 / Batch (15/17) / Accuracy 0.7900 / Loss 0.523208\n",
      "Epoch 310 / Batch (16/17) / Accuracy 0.7869 / Loss 0.569936\n",
      "Epoch 310 / Batch (17/17) / Accuracy 0.8500 / Loss 0.400177\n",
      "Epoch 310 complete, 6.246476411819458 seconds elapsed\n",
      "\n",
      "Epoch 311 starting..\n",
      "Epoch 311 / Batch (1/17) / Accuracy 0.8219 / Loss 0.428548\n",
      "Epoch 311 / Batch (2/17) / Accuracy 0.8119 / Loss 0.475529\n",
      "Epoch 311 / Batch (3/17) / Accuracy 0.8019 / Loss 0.517044\n",
      "Epoch 311 / Batch (4/17) / Accuracy 0.8469 / Loss 0.368785\n",
      "Epoch 311 / Batch (5/17) / Accuracy 0.8138 / Loss 0.446599\n",
      "Epoch 311 / Batch (6/17) / Accuracy 0.8506 / Loss 0.379678\n",
      "Epoch 311 / Batch (7/17) / Accuracy 0.8331 / Loss 0.414362\n",
      "Epoch 311 / Batch (8/17) / Accuracy 0.8062 / Loss 0.474909\n",
      "Epoch 311 / Batch (9/17) / Accuracy 0.8081 / Loss 0.491518\n",
      "Epoch 311 / Batch (10/17) / Accuracy 0.8125 / Loss 0.486260\n",
      "Epoch 311 / Batch (11/17) / Accuracy 0.8256 / Loss 0.472691\n",
      "Epoch 311 / Batch (12/17) / Accuracy 0.8263 / Loss 0.438172\n",
      "Epoch 311 / Batch (13/17) / Accuracy 0.8325 / Loss 0.449729\n",
      "Epoch 311 / Batch (14/17) / Accuracy 0.8194 / Loss 0.463654\n",
      "Epoch 311 / Batch (15/17) / Accuracy 0.8056 / Loss 0.465525\n",
      "Epoch 311 / Batch (16/17) / Accuracy 0.7925 / Loss 0.492629\n",
      "Epoch 311 / Batch (17/17) / Accuracy 0.8394 / Loss 0.403162\n",
      "Epoch 311 complete, 6.759880304336548 seconds elapsed\n",
      "\n",
      "Epoch 312 starting..\n",
      "Epoch 312 / Batch (1/17) / Accuracy 0.8144 / Loss 0.453852\n",
      "Epoch 312 / Batch (2/17) / Accuracy 0.8087 / Loss 0.496268\n",
      "Epoch 312 / Batch (3/17) / Accuracy 0.8581 / Loss 0.382060\n",
      "Epoch 312 / Batch (4/17) / Accuracy 0.7975 / Loss 0.506966\n",
      "Epoch 312 / Batch (5/17) / Accuracy 0.8481 / Loss 0.381828\n",
      "Epoch 312 / Batch (6/17) / Accuracy 0.8375 / Loss 0.404289\n",
      "Epoch 312 / Batch (7/17) / Accuracy 0.8175 / Loss 0.470250\n",
      "Epoch 312 / Batch (8/17) / Accuracy 0.8100 / Loss 0.473360\n",
      "Epoch 312 / Batch (9/17) / Accuracy 0.8431 / Loss 0.406633\n",
      "Epoch 312 / Batch (10/17) / Accuracy 0.8300 / Loss 0.430034\n",
      "Epoch 312 / Batch (11/17) / Accuracy 0.8375 / Loss 0.418167\n",
      "Epoch 312 / Batch (12/17) / Accuracy 0.8313 / Loss 0.445364\n",
      "Epoch 312 / Batch (13/17) / Accuracy 0.7788 / Loss 0.501388\n",
      "Epoch 312 / Batch (14/17) / Accuracy 0.8275 / Loss 0.427674\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 312 / Batch (15/17) / Accuracy 0.8275 / Loss 0.423506\n",
      "Epoch 312 / Batch (16/17) / Accuracy 0.8181 / Loss 0.434698\n",
      "Epoch 312 / Batch (17/17) / Accuracy 0.8219 / Loss 0.435984\n",
      "Epoch 312 complete, 6.335596799850464 seconds elapsed\n",
      "\n",
      "Epoch 313 starting..\n",
      "Epoch 313 / Batch (1/17) / Accuracy 0.8331 / Loss 0.430604\n",
      "Epoch 313 / Batch (2/17) / Accuracy 0.8188 / Loss 0.439817\n",
      "Epoch 313 / Batch (3/17) / Accuracy 0.7931 / Loss 0.502491\n",
      "Epoch 313 / Batch (4/17) / Accuracy 0.8169 / Loss 0.436991\n",
      "Epoch 313 / Batch (5/17) / Accuracy 0.7987 / Loss 0.512178\n",
      "Epoch 313 / Batch (6/17) / Accuracy 0.8169 / Loss 0.442716\n",
      "Epoch 313 / Batch (7/17) / Accuracy 0.8281 / Loss 0.442001\n",
      "Epoch 313 / Batch (8/17) / Accuracy 0.8125 / Loss 0.462877\n",
      "Epoch 313 / Batch (9/17) / Accuracy 0.8512 / Loss 0.415020\n",
      "Epoch 313 / Batch (10/17) / Accuracy 0.7981 / Loss 0.507355\n",
      "Epoch 313 / Batch (11/17) / Accuracy 0.8031 / Loss 0.487828\n",
      "Epoch 313 / Batch (12/17) / Accuracy 0.8181 / Loss 0.463708\n",
      "Epoch 313 / Batch (13/17) / Accuracy 0.8344 / Loss 0.423577\n",
      "Epoch 313 / Batch (14/17) / Accuracy 0.8481 / Loss 0.397069\n",
      "Epoch 313 / Batch (15/17) / Accuracy 0.7956 / Loss 0.527636\n",
      "Epoch 313 / Batch (16/17) / Accuracy 0.8056 / Loss 0.493764\n",
      "Epoch 313 / Batch (17/17) / Accuracy 0.8012 / Loss 0.496075\n",
      "Epoch 313 complete, 6.4322755336761475 seconds elapsed\n",
      "\n",
      "Epoch 314 starting..\n",
      "Epoch 314 / Batch (1/17) / Accuracy 0.8175 / Loss 0.451292\n",
      "Epoch 314 / Batch (2/17) / Accuracy 0.8469 / Loss 0.394756\n",
      "Epoch 314 / Batch (3/17) / Accuracy 0.8331 / Loss 0.437228\n",
      "Epoch 314 / Batch (4/17) / Accuracy 0.8138 / Loss 0.453246\n",
      "Epoch 314 / Batch (5/17) / Accuracy 0.8175 / Loss 0.455136\n",
      "Epoch 314 / Batch (6/17) / Accuracy 0.8119 / Loss 0.444130\n",
      "Epoch 314 / Batch (7/17) / Accuracy 0.8056 / Loss 0.514304\n",
      "Epoch 314 / Batch (8/17) / Accuracy 0.8263 / Loss 0.424754\n",
      "Epoch 314 / Batch (9/17) / Accuracy 0.8475 / Loss 0.421142\n",
      "Epoch 314 / Batch (10/17) / Accuracy 0.8344 / Loss 0.428583\n",
      "Epoch 314 / Batch (11/17) / Accuracy 0.8325 / Loss 0.456076\n",
      "Epoch 314 / Batch (12/17) / Accuracy 0.8200 / Loss 0.449079\n",
      "Epoch 314 / Batch (13/17) / Accuracy 0.7919 / Loss 0.502666\n",
      "Epoch 314 / Batch (14/17) / Accuracy 0.8331 / Loss 0.402854\n",
      "Epoch 314 / Batch (15/17) / Accuracy 0.8156 / Loss 0.472093\n",
      "Epoch 314 / Batch (16/17) / Accuracy 0.8600 / Loss 0.366122\n",
      "Epoch 314 / Batch (17/17) / Accuracy 0.8019 / Loss 0.509720\n",
      "Epoch 314 complete, 6.685384511947632 seconds elapsed\n",
      "\n",
      "Epoch 315 starting..\n",
      "Epoch 315 / Batch (1/17) / Accuracy 0.8238 / Loss 0.433567\n",
      "Epoch 315 / Batch (2/17) / Accuracy 0.8175 / Loss 0.456872\n",
      "Epoch 315 / Batch (3/17) / Accuracy 0.7887 / Loss 0.524480\n",
      "Epoch 315 / Batch (4/17) / Accuracy 0.8144 / Loss 0.474808\n",
      "Epoch 315 / Batch (5/17) / Accuracy 0.7769 / Loss 0.531822\n",
      "Epoch 315 / Batch (6/17) / Accuracy 0.8150 / Loss 0.478263\n",
      "Epoch 315 / Batch (7/17) / Accuracy 0.8294 / Loss 0.428549\n",
      "Epoch 315 / Batch (8/17) / Accuracy 0.8175 / Loss 0.443608\n",
      "Epoch 315 / Batch (9/17) / Accuracy 0.8288 / Loss 0.453327\n",
      "Epoch 315 / Batch (10/17) / Accuracy 0.7962 / Loss 0.503419\n",
      "Epoch 315 / Batch (11/17) / Accuracy 0.8375 / Loss 0.397566\n",
      "Epoch 315 / Batch (12/17) / Accuracy 0.8163 / Loss 0.466305\n",
      "Epoch 315 / Batch (13/17) / Accuracy 0.8288 / Loss 0.410674\n",
      "Epoch 315 / Batch (14/17) / Accuracy 0.8100 / Loss 0.492544\n",
      "Epoch 315 / Batch (15/17) / Accuracy 0.7925 / Loss 0.502314\n",
      "Epoch 315 / Batch (16/17) / Accuracy 0.7975 / Loss 0.519638\n",
      "Epoch 315 / Batch (17/17) / Accuracy 0.8075 / Loss 0.444393\n",
      "Epoch 315 complete, 6.737215042114258 seconds elapsed\n",
      "\n",
      "Epoch 316 starting..\n",
      "Epoch 316 / Batch (1/17) / Accuracy 0.8094 / Loss 0.459484\n",
      "Epoch 316 / Batch (2/17) / Accuracy 0.8125 / Loss 0.502549\n",
      "Epoch 316 / Batch (3/17) / Accuracy 0.8125 / Loss 0.476759\n",
      "Epoch 316 / Batch (4/17) / Accuracy 0.8375 / Loss 0.422598\n",
      "Epoch 316 / Batch (5/17) / Accuracy 0.8138 / Loss 0.456677\n",
      "Epoch 316 / Batch (6/17) / Accuracy 0.8319 / Loss 0.416314\n",
      "Epoch 316 / Batch (7/17) / Accuracy 0.8281 / Loss 0.438277\n",
      "Epoch 316 / Batch (8/17) / Accuracy 0.8150 / Loss 0.468940\n",
      "Epoch 316 / Batch (9/17) / Accuracy 0.8438 / Loss 0.408303\n",
      "Epoch 316 / Batch (10/17) / Accuracy 0.8906 / Loss 0.339319\n",
      "Epoch 316 / Batch (11/17) / Accuracy 0.8431 / Loss 0.430890\n",
      "Epoch 316 / Batch (12/17) / Accuracy 0.8119 / Loss 0.451495\n",
      "Epoch 316 / Batch (13/17) / Accuracy 0.8400 / Loss 0.406011\n",
      "Epoch 316 / Batch (14/17) / Accuracy 0.8000 / Loss 0.475345\n",
      "Epoch 316 / Batch (15/17) / Accuracy 0.7881 / Loss 0.515864\n",
      "Epoch 316 / Batch (16/17) / Accuracy 0.8256 / Loss 0.435044\n",
      "Epoch 316 / Batch (17/17) / Accuracy 0.8175 / Loss 0.450062\n",
      "Epoch 316 complete, 6.654351234436035 seconds elapsed\n",
      "\n",
      "Epoch 317 starting..\n",
      "Epoch 317 / Batch (1/17) / Accuracy 0.7975 / Loss 0.530377\n",
      "Epoch 317 / Batch (2/17) / Accuracy 0.8300 / Loss 0.435692\n",
      "Epoch 317 / Batch (3/17) / Accuracy 0.8444 / Loss 0.405379\n",
      "Epoch 317 / Batch (4/17) / Accuracy 0.8344 / Loss 0.429333\n",
      "Epoch 317 / Batch (5/17) / Accuracy 0.8344 / Loss 0.397071\n",
      "Epoch 317 / Batch (6/17) / Accuracy 0.8081 / Loss 0.470525\n",
      "Epoch 317 / Batch (7/17) / Accuracy 0.7962 / Loss 0.499961\n",
      "Epoch 317 / Batch (8/17) / Accuracy 0.8431 / Loss 0.436522\n",
      "Epoch 317 / Batch (9/17) / Accuracy 0.8350 / Loss 0.459431\n",
      "Epoch 317 / Batch (10/17) / Accuracy 0.8544 / Loss 0.403147\n",
      "Epoch 317 / Batch (11/17) / Accuracy 0.8300 / Loss 0.413704\n",
      "Epoch 317 / Batch (12/17) / Accuracy 0.8044 / Loss 0.493305\n",
      "Epoch 317 / Batch (13/17) / Accuracy 0.8112 / Loss 0.470961\n",
      "Epoch 317 / Batch (14/17) / Accuracy 0.8081 / Loss 0.464352\n",
      "Epoch 317 / Batch (15/17) / Accuracy 0.7919 / Loss 0.479659\n",
      "Epoch 317 / Batch (16/17) / Accuracy 0.8081 / Loss 0.457592\n",
      "Epoch 317 / Batch (17/17) / Accuracy 0.8294 / Loss 0.418214\n",
      "Epoch 317 complete, 7.169095516204834 seconds elapsed\n",
      "\n",
      "Epoch 318 starting..\n",
      "Epoch 318 / Batch (1/17) / Accuracy 0.8275 / Loss 0.454414\n",
      "Epoch 318 / Batch (2/17) / Accuracy 0.7919 / Loss 0.500213\n",
      "Epoch 318 / Batch (3/17) / Accuracy 0.8256 / Loss 0.440435\n",
      "Epoch 318 / Batch (4/17) / Accuracy 0.8050 / Loss 0.498110\n",
      "Epoch 318 / Batch (5/17) / Accuracy 0.8300 / Loss 0.413974\n",
      "Epoch 318 / Batch (6/17) / Accuracy 0.8294 / Loss 0.446896\n",
      "Epoch 318 / Batch (7/17) / Accuracy 0.8244 / Loss 0.424557\n",
      "Epoch 318 / Batch (8/17) / Accuracy 0.8144 / Loss 0.472729\n",
      "Epoch 318 / Batch (9/17) / Accuracy 0.8169 / Loss 0.451240\n",
      "Epoch 318 / Batch (10/17) / Accuracy 0.8669 / Loss 0.360204\n",
      "Epoch 318 / Batch (11/17) / Accuracy 0.7962 / Loss 0.484228\n",
      "Epoch 318 / Batch (12/17) / Accuracy 0.8181 / Loss 0.469342\n",
      "Epoch 318 / Batch (13/17) / Accuracy 0.7900 / Loss 0.534073\n",
      "Epoch 318 / Batch (14/17) / Accuracy 0.8300 / Loss 0.461581\n",
      "Epoch 318 / Batch (15/17) / Accuracy 0.8356 / Loss 0.418203\n",
      "Epoch 318 / Batch (16/17) / Accuracy 0.8675 / Loss 0.341632\n",
      "Epoch 318 / Batch (17/17) / Accuracy 0.8156 / Loss 0.459064\n",
      "Epoch 318 complete, 6.859575033187866 seconds elapsed\n",
      "\n",
      "Epoch 319 starting..\n",
      "Epoch 319 / Batch (1/17) / Accuracy 0.8006 / Loss 0.490712\n",
      "Epoch 319 / Batch (2/17) / Accuracy 0.8087 / Loss 0.467807\n",
      "Epoch 319 / Batch (3/17) / Accuracy 0.8169 / Loss 0.442455\n",
      "Epoch 319 / Batch (4/17) / Accuracy 0.8281 / Loss 0.441505\n",
      "Epoch 319 / Batch (5/17) / Accuracy 0.8188 / Loss 0.472700\n",
      "Epoch 319 / Batch (6/17) / Accuracy 0.8056 / Loss 0.473419\n",
      "Epoch 319 / Batch (7/17) / Accuracy 0.8269 / Loss 0.412939\n",
      "Epoch 319 / Batch (8/17) / Accuracy 0.8400 / Loss 0.409989\n",
      "Epoch 319 / Batch (9/17) / Accuracy 0.8094 / Loss 0.481751\n",
      "Epoch 319 / Batch (10/17) / Accuracy 0.8062 / Loss 0.492678\n",
      "Epoch 319 / Batch (11/17) / Accuracy 0.8094 / Loss 0.484005\n",
      "Epoch 319 / Batch (12/17) / Accuracy 0.8294 / Loss 0.442980\n",
      "Epoch 319 / Batch (13/17) / Accuracy 0.8388 / Loss 0.434295\n",
      "Epoch 319 / Batch (14/17) / Accuracy 0.8225 / Loss 0.430662\n",
      "Epoch 319 / Batch (15/17) / Accuracy 0.8125 / Loss 0.446362\n",
      "Epoch 319 / Batch (16/17) / Accuracy 0.8406 / Loss 0.424236\n",
      "Epoch 319 / Batch (17/17) / Accuracy 0.8331 / Loss 0.432657\n",
      "Epoch 319 complete, 6.991730213165283 seconds elapsed\n",
      "\n",
      "Epoch 320 starting..\n",
      "Epoch 320 / Batch (1/17) / Accuracy 0.8594 / Loss 0.373240\n",
      "Epoch 320 / Batch (2/17) / Accuracy 0.8081 / Loss 0.477001\n",
      "Epoch 320 / Batch (3/17) / Accuracy 0.8344 / Loss 0.447856\n",
      "Epoch 320 / Batch (4/17) / Accuracy 0.8469 / Loss 0.406662\n",
      "Epoch 320 / Batch (5/17) / Accuracy 0.8244 / Loss 0.429301\n",
      "Epoch 320 / Batch (6/17) / Accuracy 0.8075 / Loss 0.459060\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 320 / Batch (7/17) / Accuracy 0.8431 / Loss 0.387353\n",
      "Epoch 320 / Batch (8/17) / Accuracy 0.8406 / Loss 0.389368\n",
      "Epoch 320 / Batch (9/17) / Accuracy 0.8419 / Loss 0.396569\n",
      "Epoch 320 / Batch (10/17) / Accuracy 0.8194 / Loss 0.449811\n",
      "Epoch 320 / Batch (11/17) / Accuracy 0.8338 / Loss 0.432695\n",
      "Epoch 320 / Batch (12/17) / Accuracy 0.8350 / Loss 0.425321\n",
      "Epoch 320 / Batch (13/17) / Accuracy 0.8263 / Loss 0.427584\n",
      "Epoch 320 / Batch (14/17) / Accuracy 0.8194 / Loss 0.455506\n",
      "Epoch 320 / Batch (15/17) / Accuracy 0.8388 / Loss 0.417866\n",
      "Epoch 320 / Batch (16/17) / Accuracy 0.8319 / Loss 0.425989\n",
      "Epoch 320 / Batch (17/17) / Accuracy 0.8494 / Loss 0.397959\n",
      "Epoch 320 complete, 6.591274976730347 seconds elapsed\n",
      "\n",
      "Epoch 321 starting..\n",
      "Epoch 321 / Batch (1/17) / Accuracy 0.8200 / Loss 0.456065\n",
      "Epoch 321 / Batch (2/17) / Accuracy 0.8294 / Loss 0.405846\n",
      "Epoch 321 / Batch (3/17) / Accuracy 0.7931 / Loss 0.499967\n",
      "Epoch 321 / Batch (4/17) / Accuracy 0.8369 / Loss 0.421862\n",
      "Epoch 321 / Batch (5/17) / Accuracy 0.8244 / Loss 0.432158\n",
      "Epoch 321 / Batch (6/17) / Accuracy 0.8156 / Loss 0.471408\n",
      "Epoch 321 / Batch (7/17) / Accuracy 0.7919 / Loss 0.509689\n",
      "Epoch 321 / Batch (8/17) / Accuracy 0.8456 / Loss 0.395680\n",
      "Epoch 321 / Batch (9/17) / Accuracy 0.8494 / Loss 0.398068\n",
      "Epoch 321 / Batch (10/17) / Accuracy 0.7975 / Loss 0.508503\n",
      "Epoch 321 / Batch (11/17) / Accuracy 0.8469 / Loss 0.397148\n",
      "Epoch 321 / Batch (12/17) / Accuracy 0.8163 / Loss 0.442205\n",
      "Epoch 321 / Batch (13/17) / Accuracy 0.7894 / Loss 0.506230\n",
      "Epoch 321 / Batch (14/17) / Accuracy 0.8062 / Loss 0.459570\n",
      "Epoch 321 / Batch (15/17) / Accuracy 0.8112 / Loss 0.489293\n",
      "Epoch 321 / Batch (16/17) / Accuracy 0.8056 / Loss 0.492946\n",
      "Epoch 321 / Batch (17/17) / Accuracy 0.8188 / Loss 0.464863\n",
      "Epoch 321 complete, 6.637463808059692 seconds elapsed\n",
      "\n",
      "Epoch 322 starting..\n",
      "Epoch 322 / Batch (1/17) / Accuracy 0.7994 / Loss 0.488496\n",
      "Epoch 322 / Batch (2/17) / Accuracy 0.8131 / Loss 0.449456\n",
      "Epoch 322 / Batch (3/17) / Accuracy 0.8081 / Loss 0.491159\n",
      "Epoch 322 / Batch (4/17) / Accuracy 0.8206 / Loss 0.442512\n",
      "Epoch 322 / Batch (5/17) / Accuracy 0.8294 / Loss 0.425500\n",
      "Epoch 322 / Batch (6/17) / Accuracy 0.8338 / Loss 0.442463\n",
      "Epoch 322 / Batch (7/17) / Accuracy 0.7994 / Loss 0.484961\n",
      "Epoch 322 / Batch (8/17) / Accuracy 0.8125 / Loss 0.449120\n",
      "Epoch 322 / Batch (9/17) / Accuracy 0.8206 / Loss 0.458422\n",
      "Epoch 322 / Batch (10/17) / Accuracy 0.8456 / Loss 0.408757\n",
      "Epoch 322 / Batch (11/17) / Accuracy 0.8544 / Loss 0.370538\n",
      "Epoch 322 / Batch (12/17) / Accuracy 0.8544 / Loss 0.396104\n",
      "Epoch 322 / Batch (13/17) / Accuracy 0.8519 / Loss 0.412156\n",
      "Epoch 322 / Batch (14/17) / Accuracy 0.8481 / Loss 0.387646\n",
      "Epoch 322 / Batch (15/17) / Accuracy 0.8138 / Loss 0.474152\n",
      "Epoch 322 / Batch (16/17) / Accuracy 0.8606 / Loss 0.384556\n",
      "Epoch 322 / Batch (17/17) / Accuracy 0.8388 / Loss 0.441353\n",
      "Epoch 322 complete, 6.558314323425293 seconds elapsed\n",
      "\n",
      "Epoch 323 starting..\n",
      "Epoch 323 / Batch (1/17) / Accuracy 0.8325 / Loss 0.439968\n",
      "Epoch 323 / Batch (2/17) / Accuracy 0.8631 / Loss 0.381142\n",
      "Epoch 323 / Batch (3/17) / Accuracy 0.8319 / Loss 0.437142\n",
      "Epoch 323 / Batch (4/17) / Accuracy 0.8138 / Loss 0.472678\n",
      "Epoch 323 / Batch (5/17) / Accuracy 0.8244 / Loss 0.449324\n",
      "Epoch 323 / Batch (6/17) / Accuracy 0.7925 / Loss 0.494520\n",
      "Epoch 323 / Batch (7/17) / Accuracy 0.8019 / Loss 0.478793\n",
      "Epoch 323 / Batch (8/17) / Accuracy 0.8188 / Loss 0.460721\n",
      "Epoch 323 / Batch (9/17) / Accuracy 0.8456 / Loss 0.386938\n",
      "Epoch 323 / Batch (10/17) / Accuracy 0.8306 / Loss 0.424180\n",
      "Epoch 323 / Batch (11/17) / Accuracy 0.8150 / Loss 0.470279\n",
      "Epoch 323 / Batch (12/17) / Accuracy 0.8138 / Loss 0.490120\n",
      "Epoch 323 / Batch (13/17) / Accuracy 0.8131 / Loss 0.447835\n",
      "Epoch 323 / Batch (14/17) / Accuracy 0.8156 / Loss 0.448189\n",
      "Epoch 323 / Batch (15/17) / Accuracy 0.8525 / Loss 0.377363\n",
      "Epoch 323 / Batch (16/17) / Accuracy 0.8125 / Loss 0.444993\n",
      "Epoch 323 / Batch (17/17) / Accuracy 0.8644 / Loss 0.367097\n",
      "Epoch 323 complete, 6.486186265945435 seconds elapsed\n",
      "\n",
      "Epoch 324 starting..\n",
      "Epoch 324 / Batch (1/17) / Accuracy 0.8506 / Loss 0.408542\n",
      "Epoch 324 / Batch (2/17) / Accuracy 0.8231 / Loss 0.457453\n",
      "Epoch 324 / Batch (3/17) / Accuracy 0.8394 / Loss 0.435255\n",
      "Epoch 324 / Batch (4/17) / Accuracy 0.8238 / Loss 0.439676\n",
      "Epoch 324 / Batch (5/17) / Accuracy 0.8325 / Loss 0.445649\n",
      "Epoch 324 / Batch (6/17) / Accuracy 0.8394 / Loss 0.395951\n",
      "Epoch 324 / Batch (7/17) / Accuracy 0.8487 / Loss 0.389706\n",
      "Epoch 324 / Batch (8/17) / Accuracy 0.8731 / Loss 0.350314\n",
      "Epoch 324 / Batch (9/17) / Accuracy 0.8575 / Loss 0.385044\n",
      "Epoch 324 / Batch (10/17) / Accuracy 0.7906 / Loss 0.498053\n",
      "Epoch 324 / Batch (11/17) / Accuracy 0.8413 / Loss 0.395860\n",
      "Epoch 324 / Batch (12/17) / Accuracy 0.8413 / Loss 0.411197\n",
      "Epoch 324 / Batch (13/17) / Accuracy 0.8181 / Loss 0.457380\n",
      "Epoch 324 / Batch (14/17) / Accuracy 0.8487 / Loss 0.423201\n",
      "Epoch 324 / Batch (15/17) / Accuracy 0.8369 / Loss 0.422815\n",
      "Epoch 324 / Batch (16/17) / Accuracy 0.7650 / Loss 0.561702\n",
      "Epoch 324 / Batch (17/17) / Accuracy 0.8281 / Loss 0.408150\n",
      "Epoch 324 complete, 6.8184592723846436 seconds elapsed\n",
      "\n",
      "Epoch 325 starting..\n",
      "Epoch 325 / Batch (1/17) / Accuracy 0.8350 / Loss 0.407825\n",
      "Epoch 325 / Batch (2/17) / Accuracy 0.8612 / Loss 0.390126\n",
      "Epoch 325 / Batch (3/17) / Accuracy 0.8100 / Loss 0.478023\n",
      "Epoch 325 / Batch (4/17) / Accuracy 0.8037 / Loss 0.532882\n",
      "Epoch 325 / Batch (5/17) / Accuracy 0.8294 / Loss 0.419283\n",
      "Epoch 325 / Batch (6/17) / Accuracy 0.8281 / Loss 0.426453\n",
      "Epoch 325 / Batch (7/17) / Accuracy 0.8131 / Loss 0.469420\n",
      "Epoch 325 / Batch (8/17) / Accuracy 0.8350 / Loss 0.423211\n",
      "Epoch 325 / Batch (9/17) / Accuracy 0.8112 / Loss 0.461861\n",
      "Epoch 325 / Batch (10/17) / Accuracy 0.8556 / Loss 0.379714\n",
      "Epoch 325 / Batch (11/17) / Accuracy 0.7987 / Loss 0.515950\n",
      "Epoch 325 / Batch (12/17) / Accuracy 0.8094 / Loss 0.443348\n",
      "Epoch 325 / Batch (13/17) / Accuracy 0.8081 / Loss 0.477216\n",
      "Epoch 325 / Batch (14/17) / Accuracy 0.8369 / Loss 0.426656\n",
      "Epoch 325 / Batch (15/17) / Accuracy 0.8331 / Loss 0.423058\n",
      "Epoch 325 / Batch (16/17) / Accuracy 0.8263 / Loss 0.444649\n",
      "Epoch 325 / Batch (17/17) / Accuracy 0.8369 / Loss 0.400182\n",
      "Epoch 325 complete, 5.897363901138306 seconds elapsed\n",
      "\n",
      "Epoch 326 starting..\n",
      "Epoch 326 / Batch (1/17) / Accuracy 0.8181 / Loss 0.469410\n",
      "Epoch 326 / Batch (2/17) / Accuracy 0.7962 / Loss 0.498605\n",
      "Epoch 326 / Batch (3/17) / Accuracy 0.8338 / Loss 0.422102\n",
      "Epoch 326 / Batch (4/17) / Accuracy 0.8319 / Loss 0.426472\n",
      "Epoch 326 / Batch (5/17) / Accuracy 0.8400 / Loss 0.415775\n",
      "Epoch 326 / Batch (6/17) / Accuracy 0.8206 / Loss 0.435799\n",
      "Epoch 326 / Batch (7/17) / Accuracy 0.8381 / Loss 0.428730\n",
      "Epoch 326 / Batch (8/17) / Accuracy 0.7975 / Loss 0.516768\n",
      "Epoch 326 / Batch (9/17) / Accuracy 0.8244 / Loss 0.433456\n",
      "Epoch 326 / Batch (10/17) / Accuracy 0.8106 / Loss 0.487016\n",
      "Epoch 326 / Batch (11/17) / Accuracy 0.7987 / Loss 0.470033\n",
      "Epoch 326 / Batch (12/17) / Accuracy 0.8369 / Loss 0.447753\n",
      "Epoch 326 / Batch (13/17) / Accuracy 0.8062 / Loss 0.442311\n",
      "Epoch 326 / Batch (14/17) / Accuracy 0.8194 / Loss 0.454248\n",
      "Epoch 326 / Batch (15/17) / Accuracy 0.8112 / Loss 0.451321\n",
      "Epoch 326 / Batch (16/17) / Accuracy 0.8094 / Loss 0.459109\n",
      "Epoch 326 / Batch (17/17) / Accuracy 0.7931 / Loss 0.511942\n",
      "Epoch 326 complete, 5.982445001602173 seconds elapsed\n",
      "\n",
      "Epoch 327 starting..\n",
      "Epoch 327 / Batch (1/17) / Accuracy 0.7812 / Loss 0.503579\n",
      "Epoch 327 / Batch (2/17) / Accuracy 0.8431 / Loss 0.396596\n",
      "Epoch 327 / Batch (3/17) / Accuracy 0.8200 / Loss 0.442399\n",
      "Epoch 327 / Batch (4/17) / Accuracy 0.8506 / Loss 0.396535\n",
      "Epoch 327 / Batch (5/17) / Accuracy 0.8106 / Loss 0.472311\n",
      "Epoch 327 / Batch (6/17) / Accuracy 0.8694 / Loss 0.370415\n",
      "Epoch 327 / Batch (7/17) / Accuracy 0.8381 / Loss 0.424897\n",
      "Epoch 327 / Batch (8/17) / Accuracy 0.8263 / Loss 0.445003\n",
      "Epoch 327 / Batch (9/17) / Accuracy 0.8425 / Loss 0.409799\n",
      "Epoch 327 / Batch (10/17) / Accuracy 0.8062 / Loss 0.496387\n",
      "Epoch 327 / Batch (11/17) / Accuracy 0.8625 / Loss 0.354036\n",
      "Epoch 327 / Batch (12/17) / Accuracy 0.8419 / Loss 0.416762\n",
      "Epoch 327 / Batch (13/17) / Accuracy 0.8288 / Loss 0.437877\n",
      "Epoch 327 / Batch (14/17) / Accuracy 0.8425 / Loss 0.414556\n",
      "Epoch 327 / Batch (15/17) / Accuracy 0.8363 / Loss 0.423239\n",
      "Epoch 327 / Batch (16/17) / Accuracy 0.8213 / Loss 0.478166\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 327 / Batch (17/17) / Accuracy 0.8313 / Loss 0.431261\n",
      "Epoch 327 complete, 6.288687467575073 seconds elapsed\n",
      "\n",
      "Epoch 328 starting..\n",
      "Epoch 328 / Batch (1/17) / Accuracy 0.8481 / Loss 0.401882\n",
      "Epoch 328 / Batch (2/17) / Accuracy 0.8156 / Loss 0.456273\n",
      "Epoch 328 / Batch (3/17) / Accuracy 0.8138 / Loss 0.458856\n",
      "Epoch 328 / Batch (4/17) / Accuracy 0.7831 / Loss 0.530740\n",
      "Epoch 328 / Batch (5/17) / Accuracy 0.8219 / Loss 0.430928\n",
      "Epoch 328 / Batch (6/17) / Accuracy 0.8256 / Loss 0.427297\n",
      "Epoch 328 / Batch (7/17) / Accuracy 0.8163 / Loss 0.462129\n",
      "Epoch 328 / Batch (8/17) / Accuracy 0.7881 / Loss 0.518670\n",
      "Epoch 328 / Batch (9/17) / Accuracy 0.8250 / Loss 0.443523\n",
      "Epoch 328 / Batch (10/17) / Accuracy 0.8131 / Loss 0.453939\n",
      "Epoch 328 / Batch (11/17) / Accuracy 0.8288 / Loss 0.436099\n",
      "Epoch 328 / Batch (12/17) / Accuracy 0.8406 / Loss 0.405073\n",
      "Epoch 328 / Batch (13/17) / Accuracy 0.8206 / Loss 0.460903\n",
      "Epoch 328 / Batch (14/17) / Accuracy 0.8363 / Loss 0.406031\n",
      "Epoch 328 / Batch (15/17) / Accuracy 0.8369 / Loss 0.418486\n",
      "Epoch 328 / Batch (16/17) / Accuracy 0.8169 / Loss 0.472312\n",
      "Epoch 328 / Batch (17/17) / Accuracy 0.8144 / Loss 0.475335\n",
      "Epoch 328 complete, 6.408348798751831 seconds elapsed\n",
      "\n",
      "Epoch 329 starting..\n",
      "Epoch 329 / Batch (1/17) / Accuracy 0.8275 / Loss 0.446969\n",
      "Epoch 329 / Batch (2/17) / Accuracy 0.7887 / Loss 0.491747\n",
      "Epoch 329 / Batch (3/17) / Accuracy 0.8012 / Loss 0.491402\n",
      "Epoch 329 / Batch (4/17) / Accuracy 0.8419 / Loss 0.413732\n",
      "Epoch 329 / Batch (5/17) / Accuracy 0.8375 / Loss 0.415580\n",
      "Epoch 329 / Batch (6/17) / Accuracy 0.8313 / Loss 0.431053\n",
      "Epoch 329 / Batch (7/17) / Accuracy 0.8487 / Loss 0.394830\n",
      "Epoch 329 / Batch (8/17) / Accuracy 0.8600 / Loss 0.376175\n",
      "Epoch 329 / Batch (9/17) / Accuracy 0.8200 / Loss 0.440074\n",
      "Epoch 329 / Batch (10/17) / Accuracy 0.8150 / Loss 0.454001\n",
      "Epoch 329 / Batch (11/17) / Accuracy 0.8612 / Loss 0.393263\n",
      "Epoch 329 / Batch (12/17) / Accuracy 0.8338 / Loss 0.411645\n",
      "Epoch 329 / Batch (13/17) / Accuracy 0.8363 / Loss 0.420112\n",
      "Epoch 329 / Batch (14/17) / Accuracy 0.8438 / Loss 0.412584\n",
      "Epoch 329 / Batch (15/17) / Accuracy 0.8225 / Loss 0.446068\n",
      "Epoch 329 / Batch (16/17) / Accuracy 0.8306 / Loss 0.418571\n",
      "Epoch 329 / Batch (17/17) / Accuracy 0.7950 / Loss 0.518633\n",
      "Epoch 329 complete, 6.858739614486694 seconds elapsed\n",
      "\n",
      "Epoch 330 starting..\n",
      "Epoch 330 / Batch (1/17) / Accuracy 0.7856 / Loss 0.529426\n",
      "Epoch 330 / Batch (2/17) / Accuracy 0.8219 / Loss 0.469836\n",
      "Epoch 330 / Batch (3/17) / Accuracy 0.8331 / Loss 0.423607\n",
      "Epoch 330 / Batch (4/17) / Accuracy 0.8238 / Loss 0.422527\n",
      "Epoch 330 / Batch (5/17) / Accuracy 0.8363 / Loss 0.423880\n",
      "Epoch 330 / Batch (6/17) / Accuracy 0.8325 / Loss 0.406068\n",
      "Epoch 330 / Batch (7/17) / Accuracy 0.8144 / Loss 0.473248\n",
      "Epoch 330 / Batch (8/17) / Accuracy 0.7912 / Loss 0.494591\n",
      "Epoch 330 / Batch (9/17) / Accuracy 0.8062 / Loss 0.495099\n",
      "Epoch 330 / Batch (10/17) / Accuracy 0.8544 / Loss 0.374734\n",
      "Epoch 330 / Batch (11/17) / Accuracy 0.8269 / Loss 0.443720\n",
      "Epoch 330 / Batch (12/17) / Accuracy 0.8375 / Loss 0.407043\n",
      "Epoch 330 / Batch (13/17) / Accuracy 0.8450 / Loss 0.419719\n",
      "Epoch 330 / Batch (14/17) / Accuracy 0.8094 / Loss 0.479614\n",
      "Epoch 330 / Batch (15/17) / Accuracy 0.8394 / Loss 0.406751\n",
      "Epoch 330 / Batch (16/17) / Accuracy 0.8156 / Loss 0.458301\n",
      "Epoch 330 / Batch (17/17) / Accuracy 0.8200 / Loss 0.446356\n",
      "Epoch 330 complete, 6.347645282745361 seconds elapsed\n",
      "\n",
      "Epoch 331 starting..\n",
      "Epoch 331 / Batch (1/17) / Accuracy 0.8225 / Loss 0.453450\n",
      "Epoch 331 / Batch (2/17) / Accuracy 0.8325 / Loss 0.414392\n",
      "Epoch 331 / Batch (3/17) / Accuracy 0.8544 / Loss 0.393567\n",
      "Epoch 331 / Batch (4/17) / Accuracy 0.8656 / Loss 0.377728\n",
      "Epoch 331 / Batch (5/17) / Accuracy 0.8537 / Loss 0.374105\n",
      "Epoch 331 / Batch (6/17) / Accuracy 0.8256 / Loss 0.458161\n",
      "Epoch 331 / Batch (7/17) / Accuracy 0.8150 / Loss 0.476010\n",
      "Epoch 331 / Batch (8/17) / Accuracy 0.8238 / Loss 0.458704\n",
      "Epoch 331 / Batch (9/17) / Accuracy 0.8112 / Loss 0.476719\n",
      "Epoch 331 / Batch (10/17) / Accuracy 0.8331 / Loss 0.415706\n",
      "Epoch 331 / Batch (11/17) / Accuracy 0.8369 / Loss 0.412250\n",
      "Epoch 331 / Batch (12/17) / Accuracy 0.8388 / Loss 0.415219\n",
      "Epoch 331 / Batch (13/17) / Accuracy 0.8737 / Loss 0.363123\n",
      "Epoch 331 / Batch (14/17) / Accuracy 0.8125 / Loss 0.462875\n",
      "Epoch 331 / Batch (15/17) / Accuracy 0.8269 / Loss 0.445189\n",
      "Epoch 331 / Batch (16/17) / Accuracy 0.8244 / Loss 0.456280\n",
      "Epoch 331 / Batch (17/17) / Accuracy 0.8219 / Loss 0.445515\n",
      "Epoch 331 complete, 6.173985719680786 seconds elapsed\n",
      "\n",
      "Epoch 332 starting..\n",
      "Epoch 332 / Batch (1/17) / Accuracy 0.8156 / Loss 0.452241\n",
      "Epoch 332 / Batch (2/17) / Accuracy 0.8562 / Loss 0.409823\n",
      "Epoch 332 / Batch (3/17) / Accuracy 0.8369 / Loss 0.405989\n",
      "Epoch 332 / Batch (4/17) / Accuracy 0.8544 / Loss 0.402421\n",
      "Epoch 332 / Batch (5/17) / Accuracy 0.8000 / Loss 0.484205\n",
      "Epoch 332 / Batch (6/17) / Accuracy 0.8131 / Loss 0.477995\n",
      "Epoch 332 / Batch (7/17) / Accuracy 0.8256 / Loss 0.415900\n",
      "Epoch 332 / Batch (8/17) / Accuracy 0.8313 / Loss 0.430569\n",
      "Epoch 332 / Batch (9/17) / Accuracy 0.8375 / Loss 0.416667\n",
      "Epoch 332 / Batch (10/17) / Accuracy 0.8206 / Loss 0.445769\n",
      "Epoch 332 / Batch (11/17) / Accuracy 0.8444 / Loss 0.382044\n",
      "Epoch 332 / Batch (12/17) / Accuracy 0.8050 / Loss 0.459975\n",
      "Epoch 332 / Batch (13/17) / Accuracy 0.8531 / Loss 0.389929\n",
      "Epoch 332 / Batch (14/17) / Accuracy 0.7956 / Loss 0.486276\n",
      "Epoch 332 / Batch (15/17) / Accuracy 0.8288 / Loss 0.461087\n",
      "Epoch 332 / Batch (16/17) / Accuracy 0.8238 / Loss 0.457465\n",
      "Epoch 332 / Batch (17/17) / Accuracy 0.8594 / Loss 0.361609\n",
      "Epoch 332 complete, 6.090198755264282 seconds elapsed\n",
      "\n",
      "Epoch 333 starting..\n",
      "Epoch 333 / Batch (1/17) / Accuracy 0.8338 / Loss 0.433606\n",
      "Epoch 333 / Batch (2/17) / Accuracy 0.8581 / Loss 0.355244\n",
      "Epoch 333 / Batch (3/17) / Accuracy 0.8300 / Loss 0.430836\n",
      "Epoch 333 / Batch (4/17) / Accuracy 0.8106 / Loss 0.494562\n",
      "Epoch 333 / Batch (5/17) / Accuracy 0.7994 / Loss 0.515431\n",
      "Epoch 333 / Batch (6/17) / Accuracy 0.8119 / Loss 0.465239\n",
      "Epoch 333 / Batch (7/17) / Accuracy 0.8562 / Loss 0.367910\n",
      "Epoch 333 / Batch (8/17) / Accuracy 0.7881 / Loss 0.505458\n",
      "Epoch 333 / Batch (9/17) / Accuracy 0.8419 / Loss 0.387881\n",
      "Epoch 333 / Batch (10/17) / Accuracy 0.8369 / Loss 0.416463\n",
      "Epoch 333 / Batch (11/17) / Accuracy 0.8300 / Loss 0.431684\n",
      "Epoch 333 / Batch (12/17) / Accuracy 0.8444 / Loss 0.388776\n",
      "Epoch 333 / Batch (13/17) / Accuracy 0.8012 / Loss 0.493740\n",
      "Epoch 333 / Batch (14/17) / Accuracy 0.8438 / Loss 0.415785\n",
      "Epoch 333 / Batch (15/17) / Accuracy 0.8037 / Loss 0.489388\n",
      "Epoch 333 / Batch (16/17) / Accuracy 0.8450 / Loss 0.402679\n",
      "Epoch 333 / Batch (17/17) / Accuracy 0.8144 / Loss 0.460247\n",
      "Epoch 333 complete, 6.7837629318237305 seconds elapsed\n",
      "\n",
      "Epoch 334 starting..\n",
      "Epoch 334 / Batch (1/17) / Accuracy 0.8331 / Loss 0.401410\n",
      "Epoch 334 / Batch (2/17) / Accuracy 0.8263 / Loss 0.441520\n",
      "Epoch 334 / Batch (3/17) / Accuracy 0.8363 / Loss 0.410055\n",
      "Epoch 334 / Batch (4/17) / Accuracy 0.8288 / Loss 0.456322\n",
      "Epoch 334 / Batch (5/17) / Accuracy 0.8512 / Loss 0.405461\n",
      "Epoch 334 / Batch (6/17) / Accuracy 0.8300 / Loss 0.423773\n",
      "Epoch 334 / Batch (7/17) / Accuracy 0.8163 / Loss 0.458944\n",
      "Epoch 334 / Batch (8/17) / Accuracy 0.8331 / Loss 0.421564\n",
      "Epoch 334 / Batch (9/17) / Accuracy 0.8381 / Loss 0.424396\n",
      "Epoch 334 / Batch (10/17) / Accuracy 0.8269 / Loss 0.438616\n",
      "Epoch 334 / Batch (11/17) / Accuracy 0.8012 / Loss 0.479635\n",
      "Epoch 334 / Batch (12/17) / Accuracy 0.8075 / Loss 0.474070\n",
      "Epoch 334 / Batch (13/17) / Accuracy 0.8363 / Loss 0.419569\n",
      "Epoch 334 / Batch (14/17) / Accuracy 0.8744 / Loss 0.344846\n",
      "Epoch 334 / Batch (15/17) / Accuracy 0.8119 / Loss 0.474256\n",
      "Epoch 334 / Batch (16/17) / Accuracy 0.8413 / Loss 0.388145\n",
      "Epoch 334 / Batch (17/17) / Accuracy 0.8125 / Loss 0.459054\n",
      "Epoch 334 complete, 5.622295379638672 seconds elapsed\n",
      "\n",
      "Epoch 335 starting..\n",
      "Epoch 335 / Batch (1/17) / Accuracy 0.8244 / Loss 0.418283\n",
      "Epoch 335 / Batch (2/17) / Accuracy 0.8144 / Loss 0.440084\n",
      "Epoch 335 / Batch (3/17) / Accuracy 0.8081 / Loss 0.454807\n",
      "Epoch 335 / Batch (4/17) / Accuracy 0.8313 / Loss 0.396079\n",
      "Epoch 335 / Batch (5/17) / Accuracy 0.7981 / Loss 0.490666\n",
      "Epoch 335 / Batch (6/17) / Accuracy 0.8313 / Loss 0.436851\n",
      "Epoch 335 / Batch (7/17) / Accuracy 0.8219 / Loss 0.479014\n",
      "Epoch 335 / Batch (8/17) / Accuracy 0.8438 / Loss 0.404706\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 335 / Batch (9/17) / Accuracy 0.8531 / Loss 0.397351\n",
      "Epoch 335 / Batch (10/17) / Accuracy 0.8106 / Loss 0.468602\n",
      "Epoch 335 / Batch (11/17) / Accuracy 0.8325 / Loss 0.429531\n",
      "Epoch 335 / Batch (12/17) / Accuracy 0.8606 / Loss 0.357045\n",
      "Epoch 335 / Batch (13/17) / Accuracy 0.7981 / Loss 0.511363\n",
      "Epoch 335 / Batch (14/17) / Accuracy 0.8238 / Loss 0.435840\n",
      "Epoch 335 / Batch (15/17) / Accuracy 0.8112 / Loss 0.466668\n",
      "Epoch 335 / Batch (16/17) / Accuracy 0.7969 / Loss 0.497217\n",
      "Epoch 335 / Batch (17/17) / Accuracy 0.8250 / Loss 0.457381\n",
      "Epoch 335 complete, 5.1435933113098145 seconds elapsed\n",
      "\n",
      "Epoch 336 starting..\n",
      "Epoch 336 / Batch (1/17) / Accuracy 0.7962 / Loss 0.504640\n",
      "Epoch 336 / Batch (2/17) / Accuracy 0.8138 / Loss 0.475016\n",
      "Epoch 336 / Batch (3/17) / Accuracy 0.8350 / Loss 0.418170\n",
      "Epoch 336 / Batch (4/17) / Accuracy 0.8238 / Loss 0.420504\n",
      "Epoch 336 / Batch (5/17) / Accuracy 0.7781 / Loss 0.524089\n",
      "Epoch 336 / Batch (6/17) / Accuracy 0.8400 / Loss 0.417370\n",
      "Epoch 336 / Batch (7/17) / Accuracy 0.8144 / Loss 0.457929\n",
      "Epoch 336 / Batch (8/17) / Accuracy 0.8319 / Loss 0.433268\n",
      "Epoch 336 / Batch (9/17) / Accuracy 0.7981 / Loss 0.499457\n",
      "Epoch 336 / Batch (10/17) / Accuracy 0.8238 / Loss 0.463840\n",
      "Epoch 336 / Batch (11/17) / Accuracy 0.7856 / Loss 0.545745\n",
      "Epoch 336 / Batch (12/17) / Accuracy 0.8469 / Loss 0.384848\n",
      "Epoch 336 / Batch (13/17) / Accuracy 0.8356 / Loss 0.410423\n",
      "Epoch 336 / Batch (14/17) / Accuracy 0.8450 / Loss 0.417097\n",
      "Epoch 336 / Batch (15/17) / Accuracy 0.8506 / Loss 0.400474\n",
      "Epoch 336 / Batch (16/17) / Accuracy 0.7969 / Loss 0.489314\n",
      "Epoch 336 / Batch (17/17) / Accuracy 0.8194 / Loss 0.450432\n",
      "Epoch 336 complete, 6.045563459396362 seconds elapsed\n",
      "\n",
      "Epoch 337 starting..\n",
      "Epoch 337 / Batch (1/17) / Accuracy 0.8131 / Loss 0.496981\n",
      "Epoch 337 / Batch (2/17) / Accuracy 0.8225 / Loss 0.425215\n",
      "Epoch 337 / Batch (3/17) / Accuracy 0.8238 / Loss 0.442548\n",
      "Epoch 337 / Batch (4/17) / Accuracy 0.8269 / Loss 0.449755\n",
      "Epoch 337 / Batch (5/17) / Accuracy 0.8331 / Loss 0.434400\n",
      "Epoch 337 / Batch (6/17) / Accuracy 0.7763 / Loss 0.541816\n",
      "Epoch 337 / Batch (7/17) / Accuracy 0.8444 / Loss 0.398825\n",
      "Epoch 337 / Batch (8/17) / Accuracy 0.8288 / Loss 0.429314\n",
      "Epoch 337 / Batch (9/17) / Accuracy 0.8662 / Loss 0.363841\n",
      "Epoch 337 / Batch (10/17) / Accuracy 0.8131 / Loss 0.445798\n",
      "Epoch 337 / Batch (11/17) / Accuracy 0.8037 / Loss 0.475789\n",
      "Epoch 337 / Batch (12/17) / Accuracy 0.8731 / Loss 0.339521\n",
      "Epoch 337 / Batch (13/17) / Accuracy 0.8188 / Loss 0.465412\n",
      "Epoch 337 / Batch (14/17) / Accuracy 0.8244 / Loss 0.434237\n",
      "Epoch 337 / Batch (15/17) / Accuracy 0.8594 / Loss 0.367008\n",
      "Epoch 337 / Batch (16/17) / Accuracy 0.7881 / Loss 0.503849\n",
      "Epoch 337 / Batch (17/17) / Accuracy 0.8469 / Loss 0.382452\n",
      "Epoch 337 complete, 5.880067586898804 seconds elapsed\n",
      "\n",
      "Epoch 338 starting..\n",
      "Epoch 338 / Batch (1/17) / Accuracy 0.8219 / Loss 0.473034\n",
      "Epoch 338 / Batch (2/17) / Accuracy 0.8694 / Loss 0.356285\n",
      "Epoch 338 / Batch (3/17) / Accuracy 0.8450 / Loss 0.394286\n",
      "Epoch 338 / Batch (4/17) / Accuracy 0.7950 / Loss 0.519707\n",
      "Epoch 338 / Batch (5/17) / Accuracy 0.8512 / Loss 0.378251\n",
      "Epoch 338 / Batch (6/17) / Accuracy 0.8000 / Loss 0.489587\n",
      "Epoch 338 / Batch (7/17) / Accuracy 0.8619 / Loss 0.371742\n",
      "Epoch 338 / Batch (8/17) / Accuracy 0.8169 / Loss 0.444063\n",
      "Epoch 338 / Batch (9/17) / Accuracy 0.8331 / Loss 0.396654\n",
      "Epoch 338 / Batch (10/17) / Accuracy 0.8325 / Loss 0.424458\n",
      "Epoch 338 / Batch (11/17) / Accuracy 0.8319 / Loss 0.398576\n",
      "Epoch 338 / Batch (12/17) / Accuracy 0.8525 / Loss 0.387513\n",
      "Epoch 338 / Batch (13/17) / Accuracy 0.8525 / Loss 0.382128\n",
      "Epoch 338 / Batch (14/17) / Accuracy 0.8231 / Loss 0.430215\n",
      "Epoch 338 / Batch (15/17) / Accuracy 0.8131 / Loss 0.450761\n",
      "Epoch 338 / Batch (16/17) / Accuracy 0.8138 / Loss 0.445185\n",
      "Epoch 338 / Batch (17/17) / Accuracy 0.8319 / Loss 0.438483\n",
      "Epoch 338 complete, 5.500314950942993 seconds elapsed\n",
      "\n",
      "Epoch 339 starting..\n",
      "Epoch 339 / Batch (1/17) / Accuracy 0.8256 / Loss 0.473373\n",
      "Epoch 339 / Batch (2/17) / Accuracy 0.8206 / Loss 0.467188\n",
      "Epoch 339 / Batch (3/17) / Accuracy 0.8069 / Loss 0.489812\n",
      "Epoch 339 / Batch (4/17) / Accuracy 0.8231 / Loss 0.455160\n",
      "Epoch 339 / Batch (5/17) / Accuracy 0.8056 / Loss 0.471021\n",
      "Epoch 339 / Batch (6/17) / Accuracy 0.8363 / Loss 0.417542\n",
      "Epoch 339 / Batch (7/17) / Accuracy 0.8456 / Loss 0.412362\n",
      "Epoch 339 / Batch (8/17) / Accuracy 0.8400 / Loss 0.408487\n",
      "Epoch 339 / Batch (9/17) / Accuracy 0.8263 / Loss 0.426085\n",
      "Epoch 339 / Batch (10/17) / Accuracy 0.7925 / Loss 0.482258\n",
      "Epoch 339 / Batch (11/17) / Accuracy 0.8344 / Loss 0.460539\n",
      "Epoch 339 / Batch (12/17) / Accuracy 0.8419 / Loss 0.404453\n",
      "Epoch 339 / Batch (13/17) / Accuracy 0.8181 / Loss 0.476830\n",
      "Epoch 339 / Batch (14/17) / Accuracy 0.8381 / Loss 0.416071\n",
      "Epoch 339 / Batch (15/17) / Accuracy 0.8344 / Loss 0.414889\n",
      "Epoch 339 / Batch (16/17) / Accuracy 0.8213 / Loss 0.451239\n",
      "Epoch 339 / Batch (17/17) / Accuracy 0.8288 / Loss 0.423191\n",
      "Epoch 339 complete, 5.114433288574219 seconds elapsed\n",
      "\n",
      "Epoch 340 starting..\n",
      "Epoch 340 / Batch (1/17) / Accuracy 0.8469 / Loss 0.401875\n",
      "Epoch 340 / Batch (2/17) / Accuracy 0.8619 / Loss 0.379719\n",
      "Epoch 340 / Batch (3/17) / Accuracy 0.8206 / Loss 0.463906\n",
      "Epoch 340 / Batch (4/17) / Accuracy 0.8344 / Loss 0.407870\n",
      "Epoch 340 / Batch (5/17) / Accuracy 0.8156 / Loss 0.460790\n",
      "Epoch 340 / Batch (6/17) / Accuracy 0.8338 / Loss 0.414985\n",
      "Epoch 340 / Batch (7/17) / Accuracy 0.8100 / Loss 0.490424\n",
      "Epoch 340 / Batch (8/17) / Accuracy 0.8213 / Loss 0.421995\n",
      "Epoch 340 / Batch (9/17) / Accuracy 0.8288 / Loss 0.447232\n",
      "Epoch 340 / Batch (10/17) / Accuracy 0.7962 / Loss 0.481207\n",
      "Epoch 340 / Batch (11/17) / Accuracy 0.8050 / Loss 0.452980\n",
      "Epoch 340 / Batch (12/17) / Accuracy 0.8381 / Loss 0.419097\n",
      "Epoch 340 / Batch (13/17) / Accuracy 0.8175 / Loss 0.455981\n",
      "Epoch 340 / Batch (14/17) / Accuracy 0.8325 / Loss 0.420108\n",
      "Epoch 340 / Batch (15/17) / Accuracy 0.8331 / Loss 0.448590\n",
      "Epoch 340 / Batch (16/17) / Accuracy 0.7956 / Loss 0.525639\n",
      "Epoch 340 / Batch (17/17) / Accuracy 0.8094 / Loss 0.484032\n",
      "Epoch 340 complete, 5.680801630020142 seconds elapsed\n",
      "\n",
      "Epoch 341 starting..\n",
      "Epoch 341 / Batch (1/17) / Accuracy 0.8375 / Loss 0.412962\n",
      "Epoch 341 / Batch (2/17) / Accuracy 0.8006 / Loss 0.492579\n",
      "Epoch 341 / Batch (3/17) / Accuracy 0.8156 / Loss 0.459409\n",
      "Epoch 341 / Batch (4/17) / Accuracy 0.8250 / Loss 0.433388\n",
      "Epoch 341 / Batch (5/17) / Accuracy 0.8263 / Loss 0.416195\n",
      "Epoch 341 / Batch (6/17) / Accuracy 0.8181 / Loss 0.444014\n",
      "Epoch 341 / Batch (7/17) / Accuracy 0.8331 / Loss 0.403466\n",
      "Epoch 341 / Batch (8/17) / Accuracy 0.8156 / Loss 0.476196\n",
      "Epoch 341 / Batch (9/17) / Accuracy 0.7812 / Loss 0.562647\n",
      "Epoch 341 / Batch (10/17) / Accuracy 0.8500 / Loss 0.366543\n",
      "Epoch 341 / Batch (11/17) / Accuracy 0.7919 / Loss 0.514700\n",
      "Epoch 341 / Batch (12/17) / Accuracy 0.7869 / Loss 0.488715\n",
      "Epoch 341 / Batch (13/17) / Accuracy 0.8650 / Loss 0.351364\n",
      "Epoch 341 / Batch (14/17) / Accuracy 0.8462 / Loss 0.433046\n",
      "Epoch 341 / Batch (15/17) / Accuracy 0.7763 / Loss 0.515867\n",
      "Epoch 341 / Batch (16/17) / Accuracy 0.8431 / Loss 0.409765\n",
      "Epoch 341 / Batch (17/17) / Accuracy 0.8581 / Loss 0.360636\n",
      "Epoch 341 complete, 5.273617267608643 seconds elapsed\n",
      "\n",
      "Epoch 342 starting..\n",
      "Epoch 342 / Batch (1/17) / Accuracy 0.8631 / Loss 0.375517\n",
      "Epoch 342 / Batch (2/17) / Accuracy 0.8306 / Loss 0.427938\n",
      "Epoch 342 / Batch (3/17) / Accuracy 0.8231 / Loss 0.436615\n",
      "Epoch 342 / Batch (4/17) / Accuracy 0.8219 / Loss 0.443649\n",
      "Epoch 342 / Batch (5/17) / Accuracy 0.8231 / Loss 0.454479\n",
      "Epoch 342 / Batch (6/17) / Accuracy 0.8363 / Loss 0.409764\n",
      "Epoch 342 / Batch (7/17) / Accuracy 0.8338 / Loss 0.424656\n",
      "Epoch 342 / Batch (8/17) / Accuracy 0.8112 / Loss 0.477335\n",
      "Epoch 342 / Batch (9/17) / Accuracy 0.8281 / Loss 0.407720\n",
      "Epoch 342 / Batch (10/17) / Accuracy 0.8281 / Loss 0.421518\n",
      "Epoch 342 / Batch (11/17) / Accuracy 0.7994 / Loss 0.492667\n",
      "Epoch 342 / Batch (12/17) / Accuracy 0.8056 / Loss 0.453392\n",
      "Epoch 342 / Batch (13/17) / Accuracy 0.8512 / Loss 0.388122\n",
      "Epoch 342 / Batch (14/17) / Accuracy 0.8181 / Loss 0.438002\n",
      "Epoch 342 / Batch (15/17) / Accuracy 0.8000 / Loss 0.486779\n",
      "Epoch 342 / Batch (16/17) / Accuracy 0.8394 / Loss 0.403677\n",
      "Epoch 342 / Batch (17/17) / Accuracy 0.8025 / Loss 0.471567\n",
      "Epoch 342 complete, 5.224481105804443 seconds elapsed\n",
      "\n",
      "Epoch 343 starting..\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 343 / Batch (1/17) / Accuracy 0.8238 / Loss 0.441266\n",
      "Epoch 343 / Batch (2/17) / Accuracy 0.8194 / Loss 0.454753\n",
      "Epoch 343 / Batch (3/17) / Accuracy 0.8394 / Loss 0.434562\n",
      "Epoch 343 / Batch (4/17) / Accuracy 0.8350 / Loss 0.408326\n",
      "Epoch 343 / Batch (5/17) / Accuracy 0.8581 / Loss 0.366780\n",
      "Epoch 343 / Batch (6/17) / Accuracy 0.7638 / Loss 0.539399\n",
      "Epoch 343 / Batch (7/17) / Accuracy 0.8119 / Loss 0.439364\n",
      "Epoch 343 / Batch (8/17) / Accuracy 0.8388 / Loss 0.408817\n",
      "Epoch 343 / Batch (9/17) / Accuracy 0.8244 / Loss 0.426116\n",
      "Epoch 343 / Batch (10/17) / Accuracy 0.8169 / Loss 0.476298\n",
      "Epoch 343 / Batch (11/17) / Accuracy 0.8394 / Loss 0.403807\n",
      "Epoch 343 / Batch (12/17) / Accuracy 0.8256 / Loss 0.462036\n",
      "Epoch 343 / Batch (13/17) / Accuracy 0.8575 / Loss 0.377092\n",
      "Epoch 343 / Batch (14/17) / Accuracy 0.7881 / Loss 0.534295\n",
      "Epoch 343 / Batch (15/17) / Accuracy 0.8325 / Loss 0.438799\n",
      "Epoch 343 / Batch (16/17) / Accuracy 0.8675 / Loss 0.358873\n",
      "Epoch 343 / Batch (17/17) / Accuracy 0.8313 / Loss 0.425564\n",
      "Epoch 343 complete, 5.395812034606934 seconds elapsed\n",
      "\n",
      "Epoch 344 starting..\n",
      "Epoch 344 / Batch (1/17) / Accuracy 0.8419 / Loss 0.413541\n",
      "Epoch 344 / Batch (2/17) / Accuracy 0.8256 / Loss 0.421587\n",
      "Epoch 344 / Batch (3/17) / Accuracy 0.8025 / Loss 0.472362\n",
      "Epoch 344 / Batch (4/17) / Accuracy 0.8500 / Loss 0.381797\n",
      "Epoch 344 / Batch (5/17) / Accuracy 0.8413 / Loss 0.410447\n",
      "Epoch 344 / Batch (6/17) / Accuracy 0.8175 / Loss 0.485586\n",
      "Epoch 344 / Batch (7/17) / Accuracy 0.8444 / Loss 0.373272\n",
      "Epoch 344 / Batch (8/17) / Accuracy 0.8413 / Loss 0.433677\n",
      "Epoch 344 / Batch (9/17) / Accuracy 0.8394 / Loss 0.414758\n",
      "Epoch 344 / Batch (10/17) / Accuracy 0.8256 / Loss 0.436224\n",
      "Epoch 344 / Batch (11/17) / Accuracy 0.8200 / Loss 0.457306\n",
      "Epoch 344 / Batch (12/17) / Accuracy 0.8044 / Loss 0.475642\n",
      "Epoch 344 / Batch (13/17) / Accuracy 0.8050 / Loss 0.473417\n",
      "Epoch 344 / Batch (14/17) / Accuracy 0.8369 / Loss 0.428915\n",
      "Epoch 344 / Batch (15/17) / Accuracy 0.8231 / Loss 0.450355\n",
      "Epoch 344 / Batch (16/17) / Accuracy 0.8256 / Loss 0.404142\n",
      "Epoch 344 / Batch (17/17) / Accuracy 0.7975 / Loss 0.493666\n",
      "Epoch 344 complete, 5.633554458618164 seconds elapsed\n",
      "\n",
      "Epoch 345 starting..\n",
      "Epoch 345 / Batch (1/17) / Accuracy 0.8400 / Loss 0.412242\n",
      "Epoch 345 / Batch (2/17) / Accuracy 0.8231 / Loss 0.441447\n",
      "Epoch 345 / Batch (3/17) / Accuracy 0.8188 / Loss 0.459960\n",
      "Epoch 345 / Batch (4/17) / Accuracy 0.8275 / Loss 0.430744\n",
      "Epoch 345 / Batch (5/17) / Accuracy 0.8081 / Loss 0.474750\n",
      "Epoch 345 / Batch (6/17) / Accuracy 0.8100 / Loss 0.458363\n",
      "Epoch 345 / Batch (7/17) / Accuracy 0.8350 / Loss 0.429288\n",
      "Epoch 345 / Batch (8/17) / Accuracy 0.8300 / Loss 0.433618\n",
      "Epoch 345 / Batch (9/17) / Accuracy 0.8275 / Loss 0.458853\n",
      "Epoch 345 / Batch (10/17) / Accuracy 0.8356 / Loss 0.397779\n",
      "Epoch 345 / Batch (11/17) / Accuracy 0.8325 / Loss 0.464515\n",
      "Epoch 345 / Batch (12/17) / Accuracy 0.8056 / Loss 0.494562\n",
      "Epoch 345 / Batch (13/17) / Accuracy 0.8219 / Loss 0.470978\n",
      "Epoch 345 / Batch (14/17) / Accuracy 0.8331 / Loss 0.421171\n",
      "Epoch 345 / Batch (15/17) / Accuracy 0.8219 / Loss 0.456064\n",
      "Epoch 345 / Batch (16/17) / Accuracy 0.7981 / Loss 0.511507\n",
      "Epoch 345 / Batch (17/17) / Accuracy 0.8394 / Loss 0.399473\n",
      "Epoch 345 complete, 5.252022981643677 seconds elapsed\n",
      "\n",
      "Epoch 346 starting..\n",
      "Epoch 346 / Batch (1/17) / Accuracy 0.7894 / Loss 0.528276\n",
      "Epoch 346 / Batch (2/17) / Accuracy 0.8025 / Loss 0.478278\n",
      "Epoch 346 / Batch (3/17) / Accuracy 0.8037 / Loss 0.474822\n",
      "Epoch 346 / Batch (4/17) / Accuracy 0.7812 / Loss 0.553016\n",
      "Epoch 346 / Batch (5/17) / Accuracy 0.7969 / Loss 0.480840\n",
      "Epoch 346 / Batch (6/17) / Accuracy 0.8219 / Loss 0.454809\n",
      "Epoch 346 / Batch (7/17) / Accuracy 0.8156 / Loss 0.464445\n",
      "Epoch 346 / Batch (8/17) / Accuracy 0.8575 / Loss 0.386154\n",
      "Epoch 346 / Batch (9/17) / Accuracy 0.8338 / Loss 0.425272\n",
      "Epoch 346 / Batch (10/17) / Accuracy 0.8156 / Loss 0.460573\n",
      "Epoch 346 / Batch (11/17) / Accuracy 0.8100 / Loss 0.460434\n",
      "Epoch 346 / Batch (12/17) / Accuracy 0.8050 / Loss 0.492628\n",
      "Epoch 346 / Batch (13/17) / Accuracy 0.8081 / Loss 0.471131\n",
      "Epoch 346 / Batch (14/17) / Accuracy 0.8044 / Loss 0.462018\n",
      "Epoch 346 / Batch (15/17) / Accuracy 0.8375 / Loss 0.434089\n",
      "Epoch 346 / Batch (16/17) / Accuracy 0.8106 / Loss 0.472492\n",
      "Epoch 346 / Batch (17/17) / Accuracy 0.8263 / Loss 0.437804\n",
      "Epoch 346 complete, 6.1121985912323 seconds elapsed\n",
      "\n",
      "Epoch 347 starting..\n",
      "Epoch 347 / Batch (1/17) / Accuracy 0.8587 / Loss 0.384762\n",
      "Epoch 347 / Batch (2/17) / Accuracy 0.8200 / Loss 0.450712\n",
      "Epoch 347 / Batch (3/17) / Accuracy 0.8356 / Loss 0.424659\n",
      "Epoch 347 / Batch (4/17) / Accuracy 0.8206 / Loss 0.447356\n",
      "Epoch 347 / Batch (5/17) / Accuracy 0.8350 / Loss 0.403948\n",
      "Epoch 347 / Batch (6/17) / Accuracy 0.8350 / Loss 0.413011\n",
      "Epoch 347 / Batch (7/17) / Accuracy 0.8119 / Loss 0.465126\n",
      "Epoch 347 / Batch (8/17) / Accuracy 0.8581 / Loss 0.364039\n",
      "Epoch 347 / Batch (9/17) / Accuracy 0.8356 / Loss 0.434165\n",
      "Epoch 347 / Batch (10/17) / Accuracy 0.8313 / Loss 0.415191\n",
      "Epoch 347 / Batch (11/17) / Accuracy 0.8475 / Loss 0.410171\n",
      "Epoch 347 / Batch (12/17) / Accuracy 0.8306 / Loss 0.421694\n",
      "Epoch 347 / Batch (13/17) / Accuracy 0.8531 / Loss 0.375694\n",
      "Epoch 347 / Batch (14/17) / Accuracy 0.8263 / Loss 0.450138\n",
      "Epoch 347 / Batch (15/17) / Accuracy 0.8294 / Loss 0.429324\n",
      "Epoch 347 / Batch (16/17) / Accuracy 0.8363 / Loss 0.429250\n",
      "Epoch 347 / Batch (17/17) / Accuracy 0.8519 / Loss 0.397925\n",
      "Epoch 347 complete, 5.6052000522613525 seconds elapsed\n",
      "\n",
      "Epoch 348 starting..\n",
      "Epoch 348 / Batch (1/17) / Accuracy 0.8300 / Loss 0.433898\n",
      "Epoch 348 / Batch (2/17) / Accuracy 0.8400 / Loss 0.424031\n",
      "Epoch 348 / Batch (3/17) / Accuracy 0.8294 / Loss 0.430807\n",
      "Epoch 348 / Batch (4/17) / Accuracy 0.8612 / Loss 0.367326\n",
      "Epoch 348 / Batch (5/17) / Accuracy 0.8144 / Loss 0.465461\n",
      "Epoch 348 / Batch (6/17) / Accuracy 0.8275 / Loss 0.450511\n",
      "Epoch 348 / Batch (7/17) / Accuracy 0.8512 / Loss 0.390226\n",
      "Epoch 348 / Batch (8/17) / Accuracy 0.8069 / Loss 0.470197\n",
      "Epoch 348 / Batch (9/17) / Accuracy 0.8350 / Loss 0.405766\n",
      "Epoch 348 / Batch (10/17) / Accuracy 0.8631 / Loss 0.377945\n",
      "Epoch 348 / Batch (11/17) / Accuracy 0.8444 / Loss 0.399493\n",
      "Epoch 348 / Batch (12/17) / Accuracy 0.8400 / Loss 0.424150\n",
      "Epoch 348 / Batch (13/17) / Accuracy 0.8525 / Loss 0.384458\n",
      "Epoch 348 / Batch (14/17) / Accuracy 0.8325 / Loss 0.394135\n",
      "Epoch 348 / Batch (15/17) / Accuracy 0.8375 / Loss 0.404852\n",
      "Epoch 348 / Batch (16/17) / Accuracy 0.7881 / Loss 0.497196\n",
      "Epoch 348 / Batch (17/17) / Accuracy 0.8413 / Loss 0.392024\n",
      "Epoch 348 complete, 6.15363883972168 seconds elapsed\n",
      "\n",
      "Epoch 349 starting..\n",
      "Epoch 349 / Batch (1/17) / Accuracy 0.8144 / Loss 0.473020\n",
      "Epoch 349 / Batch (2/17) / Accuracy 0.8306 / Loss 0.425538\n",
      "Epoch 349 / Batch (3/17) / Accuracy 0.8350 / Loss 0.437114\n",
      "Epoch 349 / Batch (4/17) / Accuracy 0.8475 / Loss 0.393904\n",
      "Epoch 349 / Batch (5/17) / Accuracy 0.8300 / Loss 0.456124\n",
      "Epoch 349 / Batch (6/17) / Accuracy 0.8725 / Loss 0.328844\n",
      "Epoch 349 / Batch (7/17) / Accuracy 0.8188 / Loss 0.413020\n",
      "Epoch 349 / Batch (8/17) / Accuracy 0.8031 / Loss 0.467964\n",
      "Epoch 349 / Batch (9/17) / Accuracy 0.8350 / Loss 0.412153\n",
      "Epoch 349 / Batch (10/17) / Accuracy 0.8256 / Loss 0.439020\n",
      "Epoch 349 / Batch (11/17) / Accuracy 0.8394 / Loss 0.421160\n",
      "Epoch 349 / Batch (12/17) / Accuracy 0.8269 / Loss 0.443474\n",
      "Epoch 349 / Batch (13/17) / Accuracy 0.8200 / Loss 0.443377\n",
      "Epoch 349 / Batch (14/17) / Accuracy 0.7931 / Loss 0.493510\n",
      "Epoch 349 / Batch (15/17) / Accuracy 0.8306 / Loss 0.436429\n",
      "Epoch 349 / Batch (16/17) / Accuracy 0.8519 / Loss 0.412471\n",
      "Epoch 349 / Batch (17/17) / Accuracy 0.8325 / Loss 0.420352\n",
      "Epoch 349 complete, 6.115908622741699 seconds elapsed\n",
      "\n",
      "Epoch 350 starting..\n",
      "Epoch 350 / Batch (1/17) / Accuracy 0.8263 / Loss 0.457105\n",
      "Epoch 350 / Batch (2/17) / Accuracy 0.8400 / Loss 0.401373\n",
      "Epoch 350 / Batch (3/17) / Accuracy 0.8281 / Loss 0.443592\n",
      "Epoch 350 / Batch (4/17) / Accuracy 0.8325 / Loss 0.423386\n",
      "Epoch 350 / Batch (5/17) / Accuracy 0.8106 / Loss 0.463936\n",
      "Epoch 350 / Batch (6/17) / Accuracy 0.8081 / Loss 0.472755\n",
      "Epoch 350 / Batch (7/17) / Accuracy 0.8413 / Loss 0.407197\n",
      "Epoch 350 / Batch (8/17) / Accuracy 0.8462 / Loss 0.373133\n",
      "Epoch 350 / Batch (9/17) / Accuracy 0.8338 / Loss 0.423142\n",
      "Epoch 350 / Batch (10/17) / Accuracy 0.8600 / Loss 0.359050\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 350 / Batch (11/17) / Accuracy 0.8225 / Loss 0.424137\n",
      "Epoch 350 / Batch (12/17) / Accuracy 0.8250 / Loss 0.427007\n",
      "Epoch 350 / Batch (13/17) / Accuracy 0.8294 / Loss 0.432676\n",
      "Epoch 350 / Batch (14/17) / Accuracy 0.8438 / Loss 0.413920\n",
      "Epoch 350 / Batch (15/17) / Accuracy 0.8181 / Loss 0.460675\n",
      "Epoch 350 / Batch (16/17) / Accuracy 0.7825 / Loss 0.543244\n",
      "Epoch 350 / Batch (17/17) / Accuracy 0.8294 / Loss 0.429511\n",
      "Epoch 350 complete, 5.844927549362183 seconds elapsed\n",
      "\n",
      "Epoch 351 starting..\n",
      "Epoch 351 / Batch (1/17) / Accuracy 0.8306 / Loss 0.441681\n",
      "Epoch 351 / Batch (2/17) / Accuracy 0.8344 / Loss 0.442370\n",
      "Epoch 351 / Batch (3/17) / Accuracy 0.8363 / Loss 0.421513\n",
      "Epoch 351 / Batch (4/17) / Accuracy 0.8537 / Loss 0.377533\n",
      "Epoch 351 / Batch (5/17) / Accuracy 0.8419 / Loss 0.410515\n",
      "Epoch 351 / Batch (6/17) / Accuracy 0.8131 / Loss 0.460378\n",
      "Epoch 351 / Batch (7/17) / Accuracy 0.8562 / Loss 0.382347\n",
      "Epoch 351 / Batch (8/17) / Accuracy 0.8313 / Loss 0.429727\n",
      "Epoch 351 / Batch (9/17) / Accuracy 0.8306 / Loss 0.427094\n",
      "Epoch 351 / Batch (10/17) / Accuracy 0.8263 / Loss 0.436772\n",
      "Epoch 351 / Batch (11/17) / Accuracy 0.8181 / Loss 0.443982\n",
      "Epoch 351 / Batch (12/17) / Accuracy 0.8350 / Loss 0.407660\n",
      "Epoch 351 / Batch (13/17) / Accuracy 0.8306 / Loss 0.411826\n",
      "Epoch 351 / Batch (14/17) / Accuracy 0.8500 / Loss 0.405460\n",
      "Epoch 351 / Batch (15/17) / Accuracy 0.7950 / Loss 0.503054\n",
      "Epoch 351 / Batch (16/17) / Accuracy 0.8406 / Loss 0.402493\n",
      "Epoch 351 / Batch (17/17) / Accuracy 0.8525 / Loss 0.378429\n",
      "Epoch 351 complete, 5.528733968734741 seconds elapsed\n",
      "\n",
      "Epoch 352 starting..\n",
      "Epoch 352 / Batch (1/17) / Accuracy 0.8531 / Loss 0.364728\n",
      "Epoch 352 / Batch (2/17) / Accuracy 0.8306 / Loss 0.405858\n",
      "Epoch 352 / Batch (3/17) / Accuracy 0.8419 / Loss 0.420251\n",
      "Epoch 352 / Batch (4/17) / Accuracy 0.8438 / Loss 0.392229\n",
      "Epoch 352 / Batch (5/17) / Accuracy 0.8413 / Loss 0.414855\n",
      "Epoch 352 / Batch (6/17) / Accuracy 0.8294 / Loss 0.444004\n",
      "Epoch 352 / Batch (7/17) / Accuracy 0.8344 / Loss 0.407404\n",
      "Epoch 352 / Batch (8/17) / Accuracy 0.8069 / Loss 0.460521\n",
      "Epoch 352 / Batch (9/17) / Accuracy 0.8381 / Loss 0.415886\n",
      "Epoch 352 / Batch (10/17) / Accuracy 0.8425 / Loss 0.403181\n",
      "Epoch 352 / Batch (11/17) / Accuracy 0.8400 / Loss 0.396046\n",
      "Epoch 352 / Batch (12/17) / Accuracy 0.8294 / Loss 0.422734\n",
      "Epoch 352 / Batch (13/17) / Accuracy 0.8394 / Loss 0.411007\n",
      "Epoch 352 / Batch (14/17) / Accuracy 0.8025 / Loss 0.498411\n",
      "Epoch 352 / Batch (15/17) / Accuracy 0.8444 / Loss 0.417683\n",
      "Epoch 352 / Batch (16/17) / Accuracy 0.8200 / Loss 0.459062\n",
      "Epoch 352 / Batch (17/17) / Accuracy 0.8363 / Loss 0.394844\n",
      "Epoch 352 complete, 5.514338254928589 seconds elapsed\n",
      "\n",
      "Epoch 353 starting..\n",
      "Epoch 353 / Batch (1/17) / Accuracy 0.8169 / Loss 0.474453\n",
      "Epoch 353 / Batch (2/17) / Accuracy 0.8356 / Loss 0.419946\n",
      "Epoch 353 / Batch (3/17) / Accuracy 0.8694 / Loss 0.341025\n",
      "Epoch 353 / Batch (4/17) / Accuracy 0.8281 / Loss 0.428453\n",
      "Epoch 353 / Batch (5/17) / Accuracy 0.8194 / Loss 0.443256\n",
      "Epoch 353 / Batch (6/17) / Accuracy 0.8150 / Loss 0.479255\n",
      "Epoch 353 / Batch (7/17) / Accuracy 0.8087 / Loss 0.447791\n",
      "Epoch 353 / Batch (8/17) / Accuracy 0.8487 / Loss 0.405655\n",
      "Epoch 353 / Batch (9/17) / Accuracy 0.8138 / Loss 0.432419\n",
      "Epoch 353 / Batch (10/17) / Accuracy 0.8506 / Loss 0.407777\n",
      "Epoch 353 / Batch (11/17) / Accuracy 0.8450 / Loss 0.418450\n",
      "Epoch 353 / Batch (12/17) / Accuracy 0.7688 / Loss 0.583056\n",
      "Epoch 353 / Batch (13/17) / Accuracy 0.8256 / Loss 0.450977\n",
      "Epoch 353 / Batch (14/17) / Accuracy 0.8056 / Loss 0.461614\n",
      "Epoch 353 / Batch (15/17) / Accuracy 0.8244 / Loss 0.440751\n",
      "Epoch 353 / Batch (16/17) / Accuracy 0.7925 / Loss 0.540123\n",
      "Epoch 353 / Batch (17/17) / Accuracy 0.8244 / Loss 0.453999\n",
      "Epoch 353 complete, 5.911649942398071 seconds elapsed\n",
      "\n",
      "Epoch 354 starting..\n",
      "Epoch 354 / Batch (1/17) / Accuracy 0.8131 / Loss 0.455834\n",
      "Epoch 354 / Batch (2/17) / Accuracy 0.8313 / Loss 0.424938\n",
      "Epoch 354 / Batch (3/17) / Accuracy 0.8025 / Loss 0.491966\n",
      "Epoch 354 / Batch (4/17) / Accuracy 0.8294 / Loss 0.411245\n",
      "Epoch 354 / Batch (5/17) / Accuracy 0.8144 / Loss 0.467651\n",
      "Epoch 354 / Batch (6/17) / Accuracy 0.8062 / Loss 0.469030\n",
      "Epoch 354 / Batch (7/17) / Accuracy 0.8050 / Loss 0.488142\n",
      "Epoch 354 / Batch (8/17) / Accuracy 0.8519 / Loss 0.408452\n",
      "Epoch 354 / Batch (9/17) / Accuracy 0.8000 / Loss 0.480252\n",
      "Epoch 354 / Batch (10/17) / Accuracy 0.8388 / Loss 0.406001\n",
      "Epoch 354 / Batch (11/17) / Accuracy 0.8531 / Loss 0.400362\n",
      "Epoch 354 / Batch (12/17) / Accuracy 0.8031 / Loss 0.479829\n",
      "Epoch 354 / Batch (13/17) / Accuracy 0.8231 / Loss 0.440318\n",
      "Epoch 354 / Batch (14/17) / Accuracy 0.8044 / Loss 0.473082\n",
      "Epoch 354 / Batch (15/17) / Accuracy 0.8275 / Loss 0.470007\n",
      "Epoch 354 / Batch (16/17) / Accuracy 0.8606 / Loss 0.380471\n",
      "Epoch 354 / Batch (17/17) / Accuracy 0.8494 / Loss 0.392117\n",
      "Epoch 354 complete, 5.699113130569458 seconds elapsed\n",
      "\n",
      "Epoch 355 starting..\n",
      "Epoch 355 / Batch (1/17) / Accuracy 0.8225 / Loss 0.432012\n",
      "Epoch 355 / Batch (2/17) / Accuracy 0.8256 / Loss 0.444150\n",
      "Epoch 355 / Batch (3/17) / Accuracy 0.8119 / Loss 0.457604\n",
      "Epoch 355 / Batch (4/17) / Accuracy 0.8300 / Loss 0.436587\n",
      "Epoch 355 / Batch (5/17) / Accuracy 0.8244 / Loss 0.434079\n",
      "Epoch 355 / Batch (6/17) / Accuracy 0.8250 / Loss 0.428734\n",
      "Epoch 355 / Batch (7/17) / Accuracy 0.8288 / Loss 0.429741\n",
      "Epoch 355 / Batch (8/17) / Accuracy 0.8181 / Loss 0.452163\n",
      "Epoch 355 / Batch (9/17) / Accuracy 0.8106 / Loss 0.476164\n",
      "Epoch 355 / Batch (10/17) / Accuracy 0.8156 / Loss 0.473194\n",
      "Epoch 355 / Batch (11/17) / Accuracy 0.7944 / Loss 0.485254\n",
      "Epoch 355 / Batch (12/17) / Accuracy 0.8537 / Loss 0.379593\n",
      "Epoch 355 / Batch (13/17) / Accuracy 0.8369 / Loss 0.404391\n",
      "Epoch 355 / Batch (14/17) / Accuracy 0.8094 / Loss 0.487480\n",
      "Epoch 355 / Batch (15/17) / Accuracy 0.8606 / Loss 0.358993\n",
      "Epoch 355 / Batch (16/17) / Accuracy 0.8288 / Loss 0.433309\n",
      "Epoch 355 / Batch (17/17) / Accuracy 0.8225 / Loss 0.455791\n",
      "Epoch 355 complete, 5.7924275398254395 seconds elapsed\n",
      "\n",
      "Epoch 356 starting..\n",
      "Epoch 356 / Batch (1/17) / Accuracy 0.8231 / Loss 0.452396\n",
      "Epoch 356 / Batch (2/17) / Accuracy 0.8338 / Loss 0.441105\n",
      "Epoch 356 / Batch (3/17) / Accuracy 0.8537 / Loss 0.396450\n",
      "Epoch 356 / Batch (4/17) / Accuracy 0.7937 / Loss 0.510576\n",
      "Epoch 356 / Batch (5/17) / Accuracy 0.8294 / Loss 0.431737\n",
      "Epoch 356 / Batch (6/17) / Accuracy 0.8231 / Loss 0.449649\n",
      "Epoch 356 / Batch (7/17) / Accuracy 0.8481 / Loss 0.384634\n",
      "Epoch 356 / Batch (8/17) / Accuracy 0.8375 / Loss 0.418550\n",
      "Epoch 356 / Batch (9/17) / Accuracy 0.8012 / Loss 0.477771\n",
      "Epoch 356 / Batch (10/17) / Accuracy 0.8188 / Loss 0.462683\n",
      "Epoch 356 / Batch (11/17) / Accuracy 0.8125 / Loss 0.458357\n",
      "Epoch 356 / Batch (12/17) / Accuracy 0.7812 / Loss 0.520666\n",
      "Epoch 356 / Batch (13/17) / Accuracy 0.8825 / Loss 0.323104\n",
      "Epoch 356 / Batch (14/17) / Accuracy 0.8119 / Loss 0.506313\n",
      "Epoch 356 / Batch (15/17) / Accuracy 0.8300 / Loss 0.442995\n",
      "Epoch 356 / Batch (16/17) / Accuracy 0.8475 / Loss 0.394510\n",
      "Epoch 356 / Batch (17/17) / Accuracy 0.8306 / Loss 0.412322\n",
      "Epoch 356 complete, 5.520658493041992 seconds elapsed\n",
      "\n",
      "Epoch 357 starting..\n",
      "Epoch 357 / Batch (1/17) / Accuracy 0.8225 / Loss 0.446936\n",
      "Epoch 357 / Batch (2/17) / Accuracy 0.8388 / Loss 0.383200\n",
      "Epoch 357 / Batch (3/17) / Accuracy 0.8444 / Loss 0.416629\n",
      "Epoch 357 / Batch (4/17) / Accuracy 0.8194 / Loss 0.461974\n",
      "Epoch 357 / Batch (5/17) / Accuracy 0.8213 / Loss 0.460716\n",
      "Epoch 357 / Batch (6/17) / Accuracy 0.8481 / Loss 0.386609\n",
      "Epoch 357 / Batch (7/17) / Accuracy 0.8719 / Loss 0.370759\n",
      "Epoch 357 / Batch (8/17) / Accuracy 0.8344 / Loss 0.411121\n",
      "Epoch 357 / Batch (9/17) / Accuracy 0.8669 / Loss 0.337110\n",
      "Epoch 357 / Batch (10/17) / Accuracy 0.8344 / Loss 0.430768\n",
      "Epoch 357 / Batch (11/17) / Accuracy 0.8231 / Loss 0.446750\n",
      "Epoch 357 / Batch (12/17) / Accuracy 0.8181 / Loss 0.493204\n",
      "Epoch 357 / Batch (13/17) / Accuracy 0.8469 / Loss 0.414026\n",
      "Epoch 357 / Batch (14/17) / Accuracy 0.8369 / Loss 0.405577\n",
      "Epoch 357 / Batch (15/17) / Accuracy 0.8238 / Loss 0.431118\n",
      "Epoch 357 / Batch (16/17) / Accuracy 0.8356 / Loss 0.401578\n",
      "Epoch 357 / Batch (17/17) / Accuracy 0.8106 / Loss 0.460616\n",
      "Epoch 357 complete, 6.600205898284912 seconds elapsed\n",
      "\n",
      "Epoch 358 starting..\n",
      "Epoch 358 / Batch (1/17) / Accuracy 0.8369 / Loss 0.396467\n",
      "Epoch 358 / Batch (2/17) / Accuracy 0.8350 / Loss 0.408853\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 358 / Batch (3/17) / Accuracy 0.8456 / Loss 0.389558\n",
      "Epoch 358 / Batch (4/17) / Accuracy 0.8275 / Loss 0.425684\n",
      "Epoch 358 / Batch (5/17) / Accuracy 0.8413 / Loss 0.414639\n",
      "Epoch 358 / Batch (6/17) / Accuracy 0.8569 / Loss 0.395705\n",
      "Epoch 358 / Batch (7/17) / Accuracy 0.8269 / Loss 0.440666\n",
      "Epoch 358 / Batch (8/17) / Accuracy 0.8156 / Loss 0.467872\n",
      "Epoch 358 / Batch (9/17) / Accuracy 0.8288 / Loss 0.422825\n",
      "Epoch 358 / Batch (10/17) / Accuracy 0.8112 / Loss 0.437791\n",
      "Epoch 358 / Batch (11/17) / Accuracy 0.8256 / Loss 0.443390\n",
      "Epoch 358 / Batch (12/17) / Accuracy 0.8350 / Loss 0.470909\n",
      "Epoch 358 / Batch (13/17) / Accuracy 0.8081 / Loss 0.505016\n",
      "Epoch 358 / Batch (14/17) / Accuracy 0.8050 / Loss 0.490642\n",
      "Epoch 358 / Batch (15/17) / Accuracy 0.8131 / Loss 0.464117\n",
      "Epoch 358 / Batch (16/17) / Accuracy 0.8450 / Loss 0.423087\n",
      "Epoch 358 / Batch (17/17) / Accuracy 0.8019 / Loss 0.455770\n",
      "Epoch 358 complete, 5.819776773452759 seconds elapsed\n",
      "\n",
      "Epoch 359 starting..\n",
      "Epoch 359 / Batch (1/17) / Accuracy 0.8269 / Loss 0.426355\n",
      "Epoch 359 / Batch (2/17) / Accuracy 0.8200 / Loss 0.471464\n",
      "Epoch 359 / Batch (3/17) / Accuracy 0.8294 / Loss 0.423603\n",
      "Epoch 359 / Batch (4/17) / Accuracy 0.8031 / Loss 0.517584\n",
      "Epoch 359 / Batch (5/17) / Accuracy 0.8225 / Loss 0.432349\n",
      "Epoch 359 / Batch (6/17) / Accuracy 0.8625 / Loss 0.352210\n",
      "Epoch 359 / Batch (7/17) / Accuracy 0.7981 / Loss 0.487714\n",
      "Epoch 359 / Batch (8/17) / Accuracy 0.8425 / Loss 0.404324\n",
      "Epoch 359 / Batch (9/17) / Accuracy 0.8238 / Loss 0.417660\n",
      "Epoch 359 / Batch (10/17) / Accuracy 0.8331 / Loss 0.426004\n",
      "Epoch 359 / Batch (11/17) / Accuracy 0.8375 / Loss 0.406425\n",
      "Epoch 359 / Batch (12/17) / Accuracy 0.8550 / Loss 0.382350\n",
      "Epoch 359 / Batch (13/17) / Accuracy 0.8194 / Loss 0.431765\n",
      "Epoch 359 / Batch (14/17) / Accuracy 0.8044 / Loss 0.473786\n",
      "Epoch 359 / Batch (15/17) / Accuracy 0.8319 / Loss 0.444305\n",
      "Epoch 359 / Batch (16/17) / Accuracy 0.8169 / Loss 0.455255\n",
      "Epoch 359 / Batch (17/17) / Accuracy 0.8325 / Loss 0.418228\n",
      "Epoch 359 complete, 5.703131437301636 seconds elapsed\n",
      "\n",
      "Epoch 360 starting..\n",
      "Epoch 360 / Batch (1/17) / Accuracy 0.8406 / Loss 0.400427\n",
      "Epoch 360 / Batch (2/17) / Accuracy 0.8231 / Loss 0.443827\n",
      "Epoch 360 / Batch (3/17) / Accuracy 0.8413 / Loss 0.416979\n",
      "Epoch 360 / Batch (4/17) / Accuracy 0.8325 / Loss 0.430770\n",
      "Epoch 360 / Batch (5/17) / Accuracy 0.8244 / Loss 0.447787\n",
      "Epoch 360 / Batch (6/17) / Accuracy 0.8487 / Loss 0.414378\n",
      "Epoch 360 / Batch (7/17) / Accuracy 0.8788 / Loss 0.348374\n",
      "Epoch 360 / Batch (8/17) / Accuracy 0.8431 / Loss 0.388128\n",
      "Epoch 360 / Batch (9/17) / Accuracy 0.8350 / Loss 0.403465\n",
      "Epoch 360 / Batch (10/17) / Accuracy 0.8475 / Loss 0.388854\n",
      "Epoch 360 / Batch (11/17) / Accuracy 0.8112 / Loss 0.456879\n",
      "Epoch 360 / Batch (12/17) / Accuracy 0.8100 / Loss 0.480935\n",
      "Epoch 360 / Batch (13/17) / Accuracy 0.8725 / Loss 0.350914\n",
      "Epoch 360 / Batch (14/17) / Accuracy 0.8269 / Loss 0.422665\n",
      "Epoch 360 / Batch (15/17) / Accuracy 0.8313 / Loss 0.415028\n",
      "Epoch 360 / Batch (16/17) / Accuracy 0.8325 / Loss 0.434749\n",
      "Epoch 360 / Batch (17/17) / Accuracy 0.8456 / Loss 0.391188\n",
      "Epoch 360 complete, 6.330853223800659 seconds elapsed\n",
      "\n",
      "Epoch 361 starting..\n",
      "Epoch 361 / Batch (1/17) / Accuracy 0.8356 / Loss 0.407456\n",
      "Epoch 361 / Batch (2/17) / Accuracy 0.8225 / Loss 0.453485\n",
      "Epoch 361 / Batch (3/17) / Accuracy 0.8350 / Loss 0.408027\n",
      "Epoch 361 / Batch (4/17) / Accuracy 0.8456 / Loss 0.416611\n",
      "Epoch 361 / Batch (5/17) / Accuracy 0.8406 / Loss 0.391554\n",
      "Epoch 361 / Batch (6/17) / Accuracy 0.8306 / Loss 0.421404\n",
      "Epoch 361 / Batch (7/17) / Accuracy 0.8281 / Loss 0.427193\n",
      "Epoch 361 / Batch (8/17) / Accuracy 0.8000 / Loss 0.489901\n",
      "Epoch 361 / Batch (9/17) / Accuracy 0.8487 / Loss 0.399267\n",
      "Epoch 361 / Batch (10/17) / Accuracy 0.8475 / Loss 0.408105\n",
      "Epoch 361 / Batch (11/17) / Accuracy 0.8294 / Loss 0.441970\n",
      "Epoch 361 / Batch (12/17) / Accuracy 0.8269 / Loss 0.435201\n",
      "Epoch 361 / Batch (13/17) / Accuracy 0.8106 / Loss 0.449667\n",
      "Epoch 361 / Batch (14/17) / Accuracy 0.8438 / Loss 0.394182\n",
      "Epoch 361 / Batch (15/17) / Accuracy 0.8456 / Loss 0.394551\n",
      "Epoch 361 / Batch (16/17) / Accuracy 0.8444 / Loss 0.431057\n",
      "Epoch 361 / Batch (17/17) / Accuracy 0.8381 / Loss 0.395773\n",
      "Epoch 361 complete, 5.358161211013794 seconds elapsed\n",
      "\n",
      "Epoch 362 starting..\n",
      "Epoch 362 / Batch (1/17) / Accuracy 0.8469 / Loss 0.406465\n",
      "Epoch 362 / Batch (2/17) / Accuracy 0.8250 / Loss 0.443989\n",
      "Epoch 362 / Batch (3/17) / Accuracy 0.8263 / Loss 0.414546\n",
      "Epoch 362 / Batch (4/17) / Accuracy 0.8381 / Loss 0.406204\n",
      "Epoch 362 / Batch (5/17) / Accuracy 0.8238 / Loss 0.445295\n",
      "Epoch 362 / Batch (6/17) / Accuracy 0.7969 / Loss 0.524794\n",
      "Epoch 362 / Batch (7/17) / Accuracy 0.8050 / Loss 0.471045\n",
      "Epoch 362 / Batch (8/17) / Accuracy 0.8575 / Loss 0.362598\n",
      "Epoch 362 / Batch (9/17) / Accuracy 0.7862 / Loss 0.509632\n",
      "Epoch 362 / Batch (10/17) / Accuracy 0.8275 / Loss 0.425478\n",
      "Epoch 362 / Batch (11/17) / Accuracy 0.8256 / Loss 0.438111\n",
      "Epoch 362 / Batch (12/17) / Accuracy 0.7819 / Loss 0.543803\n",
      "Epoch 362 / Batch (13/17) / Accuracy 0.8394 / Loss 0.405823\n",
      "Epoch 362 / Batch (14/17) / Accuracy 0.8612 / Loss 0.363652\n",
      "Epoch 362 / Batch (15/17) / Accuracy 0.8794 / Loss 0.343060\n",
      "Epoch 362 / Batch (16/17) / Accuracy 0.8481 / Loss 0.395947\n",
      "Epoch 362 / Batch (17/17) / Accuracy 0.8250 / Loss 0.450264\n",
      "Epoch 362 complete, 5.523921012878418 seconds elapsed\n",
      "\n",
      "Epoch 363 starting..\n",
      "Epoch 363 / Batch (1/17) / Accuracy 0.8712 / Loss 0.349766\n",
      "Epoch 363 / Batch (2/17) / Accuracy 0.8388 / Loss 0.425146\n",
      "Epoch 363 / Batch (3/17) / Accuracy 0.8363 / Loss 0.398333\n",
      "Epoch 363 / Batch (4/17) / Accuracy 0.8125 / Loss 0.466258\n",
      "Epoch 363 / Batch (5/17) / Accuracy 0.8269 / Loss 0.445163\n",
      "Epoch 363 / Batch (6/17) / Accuracy 0.8019 / Loss 0.490751\n",
      "Epoch 363 / Batch (7/17) / Accuracy 0.8119 / Loss 0.451096\n",
      "Epoch 363 / Batch (8/17) / Accuracy 0.8112 / Loss 0.484298\n",
      "Epoch 363 / Batch (9/17) / Accuracy 0.8350 / Loss 0.429287\n",
      "Epoch 363 / Batch (10/17) / Accuracy 0.8294 / Loss 0.425162\n",
      "Epoch 363 / Batch (11/17) / Accuracy 0.8238 / Loss 0.419963\n",
      "Epoch 363 / Batch (12/17) / Accuracy 0.8256 / Loss 0.438271\n",
      "Epoch 363 / Batch (13/17) / Accuracy 0.8456 / Loss 0.383695\n",
      "Epoch 363 / Batch (14/17) / Accuracy 0.8238 / Loss 0.462893\n",
      "Epoch 363 / Batch (15/17) / Accuracy 0.8625 / Loss 0.368691\n",
      "Epoch 363 / Batch (16/17) / Accuracy 0.8087 / Loss 0.477051\n",
      "Epoch 363 / Batch (17/17) / Accuracy 0.8188 / Loss 0.469592\n",
      "Epoch 363 complete, 5.993659019470215 seconds elapsed\n",
      "\n",
      "Epoch 364 starting..\n",
      "Epoch 364 / Batch (1/17) / Accuracy 0.8069 / Loss 0.481455\n",
      "Epoch 364 / Batch (2/17) / Accuracy 0.8169 / Loss 0.457608\n",
      "Epoch 364 / Batch (3/17) / Accuracy 0.8150 / Loss 0.444758\n",
      "Epoch 364 / Batch (4/17) / Accuracy 0.8225 / Loss 0.437651\n",
      "Epoch 364 / Batch (5/17) / Accuracy 0.8263 / Loss 0.464763\n",
      "Epoch 364 / Batch (6/17) / Accuracy 0.8325 / Loss 0.420635\n",
      "Epoch 364 / Batch (7/17) / Accuracy 0.8288 / Loss 0.423813\n",
      "Epoch 364 / Batch (8/17) / Accuracy 0.8356 / Loss 0.412040\n",
      "Epoch 364 / Batch (9/17) / Accuracy 0.8669 / Loss 0.363910\n",
      "Epoch 364 / Batch (10/17) / Accuracy 0.8375 / Loss 0.433232\n",
      "Epoch 364 / Batch (11/17) / Accuracy 0.8575 / Loss 0.386952\n",
      "Epoch 364 / Batch (12/17) / Accuracy 0.8175 / Loss 0.466363\n",
      "Epoch 364 / Batch (13/17) / Accuracy 0.8413 / Loss 0.403975\n",
      "Epoch 364 / Batch (14/17) / Accuracy 0.8487 / Loss 0.362258\n",
      "Epoch 364 / Batch (15/17) / Accuracy 0.7900 / Loss 0.517800\n",
      "Epoch 364 / Batch (16/17) / Accuracy 0.8238 / Loss 0.432927\n",
      "Epoch 364 / Batch (17/17) / Accuracy 0.8138 / Loss 0.448250\n",
      "Epoch 364 complete, 5.4246625900268555 seconds elapsed\n",
      "\n",
      "Epoch 365 starting..\n",
      "Epoch 365 / Batch (1/17) / Accuracy 0.8300 / Loss 0.432484\n",
      "Epoch 365 / Batch (2/17) / Accuracy 0.8325 / Loss 0.420185\n",
      "Epoch 365 / Batch (3/17) / Accuracy 0.8394 / Loss 0.391429\n",
      "Epoch 365 / Batch (4/17) / Accuracy 0.8044 / Loss 0.482932\n",
      "Epoch 365 / Batch (5/17) / Accuracy 0.8462 / Loss 0.391004\n",
      "Epoch 365 / Batch (6/17) / Accuracy 0.7919 / Loss 0.473124\n",
      "Epoch 365 / Batch (7/17) / Accuracy 0.8319 / Loss 0.430060\n",
      "Epoch 365 / Batch (8/17) / Accuracy 0.8369 / Loss 0.395256\n",
      "Epoch 365 / Batch (9/17) / Accuracy 0.8188 / Loss 0.476428\n",
      "Epoch 365 / Batch (10/17) / Accuracy 0.8006 / Loss 0.494553\n",
      "Epoch 365 / Batch (11/17) / Accuracy 0.8456 / Loss 0.401136\n",
      "Epoch 365 / Batch (12/17) / Accuracy 0.8062 / Loss 0.489221\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 365 / Batch (13/17) / Accuracy 0.8425 / Loss 0.404223\n",
      "Epoch 365 / Batch (14/17) / Accuracy 0.8144 / Loss 0.458892\n",
      "Epoch 365 / Batch (15/17) / Accuracy 0.8131 / Loss 0.451438\n",
      "Epoch 365 / Batch (16/17) / Accuracy 0.8500 / Loss 0.378467\n",
      "Epoch 365 / Batch (17/17) / Accuracy 0.8331 / Loss 0.450083\n",
      "Epoch 365 complete, 5.170769453048706 seconds elapsed\n",
      "\n",
      "Epoch 366 starting..\n",
      "Epoch 366 / Batch (1/17) / Accuracy 0.8425 / Loss 0.396252\n",
      "Epoch 366 / Batch (2/17) / Accuracy 0.8087 / Loss 0.491229\n",
      "Epoch 366 / Batch (3/17) / Accuracy 0.8200 / Loss 0.446925\n",
      "Epoch 366 / Batch (4/17) / Accuracy 0.8112 / Loss 0.479899\n",
      "Epoch 366 / Batch (5/17) / Accuracy 0.8519 / Loss 0.371181\n",
      "Epoch 366 / Batch (6/17) / Accuracy 0.8275 / Loss 0.412489\n",
      "Epoch 366 / Batch (7/17) / Accuracy 0.8375 / Loss 0.393839\n",
      "Epoch 366 / Batch (8/17) / Accuracy 0.8175 / Loss 0.449383\n",
      "Epoch 366 / Batch (9/17) / Accuracy 0.8356 / Loss 0.419550\n",
      "Epoch 366 / Batch (10/17) / Accuracy 0.8125 / Loss 0.456242\n",
      "Epoch 366 / Batch (11/17) / Accuracy 0.8319 / Loss 0.417197\n",
      "Epoch 366 / Batch (12/17) / Accuracy 0.8031 / Loss 0.485567\n",
      "Epoch 366 / Batch (13/17) / Accuracy 0.8331 / Loss 0.426540\n",
      "Epoch 366 / Batch (14/17) / Accuracy 0.8119 / Loss 0.443805\n",
      "Epoch 366 / Batch (15/17) / Accuracy 0.8106 / Loss 0.472070\n",
      "Epoch 366 / Batch (16/17) / Accuracy 0.8325 / Loss 0.425336\n",
      "Epoch 366 / Batch (17/17) / Accuracy 0.8344 / Loss 0.426817\n",
      "Epoch 366 complete, 5.393331050872803 seconds elapsed\n",
      "\n",
      "Epoch 367 starting..\n",
      "Epoch 367 / Batch (1/17) / Accuracy 0.8281 / Loss 0.450565\n",
      "Epoch 367 / Batch (2/17) / Accuracy 0.8469 / Loss 0.384393\n",
      "Epoch 367 / Batch (3/17) / Accuracy 0.8313 / Loss 0.436899\n",
      "Epoch 367 / Batch (4/17) / Accuracy 0.8444 / Loss 0.409081\n",
      "Epoch 367 / Batch (5/17) / Accuracy 0.8213 / Loss 0.465457\n",
      "Epoch 367 / Batch (6/17) / Accuracy 0.8200 / Loss 0.445836\n",
      "Epoch 367 / Batch (7/17) / Accuracy 0.8106 / Loss 0.435722\n",
      "Epoch 367 / Batch (8/17) / Accuracy 0.8081 / Loss 0.495424\n",
      "Epoch 367 / Batch (9/17) / Accuracy 0.8194 / Loss 0.454891\n",
      "Epoch 367 / Batch (10/17) / Accuracy 0.8456 / Loss 0.383496\n",
      "Epoch 367 / Batch (11/17) / Accuracy 0.8256 / Loss 0.414291\n",
      "Epoch 367 / Batch (12/17) / Accuracy 0.8469 / Loss 0.371083\n",
      "Epoch 367 / Batch (13/17) / Accuracy 0.8556 / Loss 0.371643\n",
      "Epoch 367 / Batch (14/17) / Accuracy 0.8138 / Loss 0.475009\n",
      "Epoch 367 / Batch (15/17) / Accuracy 0.8456 / Loss 0.405600\n",
      "Epoch 367 / Batch (16/17) / Accuracy 0.8662 / Loss 0.385097\n",
      "Epoch 367 / Batch (17/17) / Accuracy 0.8356 / Loss 0.418116\n",
      "Epoch 367 complete, 5.456892967224121 seconds elapsed\n",
      "\n",
      "Epoch 368 starting..\n",
      "Epoch 368 / Batch (1/17) / Accuracy 0.8438 / Loss 0.418411\n",
      "Epoch 368 / Batch (2/17) / Accuracy 0.8556 / Loss 0.367821\n",
      "Epoch 368 / Batch (3/17) / Accuracy 0.7975 / Loss 0.486447\n",
      "Epoch 368 / Batch (4/17) / Accuracy 0.8319 / Loss 0.416403\n",
      "Epoch 368 / Batch (5/17) / Accuracy 0.8800 / Loss 0.369194\n",
      "Epoch 368 / Batch (6/17) / Accuracy 0.8525 / Loss 0.389828\n",
      "Epoch 368 / Batch (7/17) / Accuracy 0.8213 / Loss 0.452929\n",
      "Epoch 368 / Batch (8/17) / Accuracy 0.8319 / Loss 0.437990\n",
      "Epoch 368 / Batch (9/17) / Accuracy 0.8325 / Loss 0.422252\n",
      "Epoch 368 / Batch (10/17) / Accuracy 0.8494 / Loss 0.398197\n",
      "Epoch 368 / Batch (11/17) / Accuracy 0.8219 / Loss 0.439617\n",
      "Epoch 368 / Batch (12/17) / Accuracy 0.8169 / Loss 0.451850\n",
      "Epoch 368 / Batch (13/17) / Accuracy 0.8419 / Loss 0.418383\n",
      "Epoch 368 / Batch (14/17) / Accuracy 0.8075 / Loss 0.476156\n",
      "Epoch 368 / Batch (15/17) / Accuracy 0.8600 / Loss 0.360643\n",
      "Epoch 368 / Batch (16/17) / Accuracy 0.8300 / Loss 0.442207\n",
      "Epoch 368 / Batch (17/17) / Accuracy 0.8494 / Loss 0.391468\n",
      "Epoch 368 complete, 5.664873123168945 seconds elapsed\n",
      "\n",
      "Epoch 369 starting..\n",
      "Epoch 369 / Batch (1/17) / Accuracy 0.8381 / Loss 0.413281\n",
      "Epoch 369 / Batch (2/17) / Accuracy 0.8481 / Loss 0.388563\n",
      "Epoch 369 / Batch (3/17) / Accuracy 0.8525 / Loss 0.414841\n",
      "Epoch 369 / Batch (4/17) / Accuracy 0.8537 / Loss 0.373725\n",
      "Epoch 369 / Batch (5/17) / Accuracy 0.8281 / Loss 0.436844\n",
      "Epoch 369 / Batch (6/17) / Accuracy 0.8344 / Loss 0.428596\n",
      "Epoch 369 / Batch (7/17) / Accuracy 0.8225 / Loss 0.441228\n",
      "Epoch 369 / Batch (8/17) / Accuracy 0.8431 / Loss 0.400824\n",
      "Epoch 369 / Batch (9/17) / Accuracy 0.8487 / Loss 0.392396\n",
      "Epoch 369 / Batch (10/17) / Accuracy 0.8219 / Loss 0.444055\n",
      "Epoch 369 / Batch (11/17) / Accuracy 0.8531 / Loss 0.387922\n",
      "Epoch 369 / Batch (12/17) / Accuracy 0.8356 / Loss 0.411344\n",
      "Epoch 369 / Batch (13/17) / Accuracy 0.8300 / Loss 0.428393\n",
      "Epoch 369 / Batch (14/17) / Accuracy 0.8537 / Loss 0.396427\n",
      "Epoch 369 / Batch (15/17) / Accuracy 0.8462 / Loss 0.391026\n",
      "Epoch 369 / Batch (16/17) / Accuracy 0.8462 / Loss 0.404327\n",
      "Epoch 369 / Batch (17/17) / Accuracy 0.8650 / Loss 0.357898\n",
      "Epoch 369 complete, 5.3147642612457275 seconds elapsed\n",
      "\n",
      "Epoch 370 starting..\n",
      "Epoch 370 / Batch (1/17) / Accuracy 0.8388 / Loss 0.393984\n",
      "Epoch 370 / Batch (2/17) / Accuracy 0.8500 / Loss 0.375467\n",
      "Epoch 370 / Batch (3/17) / Accuracy 0.8512 / Loss 0.402807\n",
      "Epoch 370 / Batch (4/17) / Accuracy 0.8537 / Loss 0.390078\n",
      "Epoch 370 / Batch (5/17) / Accuracy 0.8487 / Loss 0.398445\n",
      "Epoch 370 / Batch (6/17) / Accuracy 0.8325 / Loss 0.460275\n",
      "Epoch 370 / Batch (7/17) / Accuracy 0.8537 / Loss 0.385614\n",
      "Epoch 370 / Batch (8/17) / Accuracy 0.8712 / Loss 0.333088\n",
      "Epoch 370 / Batch (9/17) / Accuracy 0.7844 / Loss 0.540559\n",
      "Epoch 370 / Batch (10/17) / Accuracy 0.8369 / Loss 0.411831\n",
      "Epoch 370 / Batch (11/17) / Accuracy 0.8100 / Loss 0.466472\n",
      "Epoch 370 / Batch (12/17) / Accuracy 0.8300 / Loss 0.428271\n",
      "Epoch 370 / Batch (13/17) / Accuracy 0.8369 / Loss 0.401583\n",
      "Epoch 370 / Batch (14/17) / Accuracy 0.8169 / Loss 0.453028\n",
      "Epoch 370 / Batch (15/17) / Accuracy 0.8556 / Loss 0.374081\n",
      "Epoch 370 / Batch (16/17) / Accuracy 0.8425 / Loss 0.384971\n",
      "Epoch 370 / Batch (17/17) / Accuracy 0.8512 / Loss 0.380208\n",
      "Epoch 370 complete, 5.580310821533203 seconds elapsed\n",
      "\n",
      "Epoch 371 starting..\n",
      "Epoch 371 / Batch (1/17) / Accuracy 0.8581 / Loss 0.394981\n",
      "Epoch 371 / Batch (2/17) / Accuracy 0.8419 / Loss 0.390596\n",
      "Epoch 371 / Batch (3/17) / Accuracy 0.8575 / Loss 0.366499\n",
      "Epoch 371 / Batch (4/17) / Accuracy 0.8550 / Loss 0.347667\n",
      "Epoch 371 / Batch (5/17) / Accuracy 0.8450 / Loss 0.371143\n",
      "Epoch 371 / Batch (6/17) / Accuracy 0.8431 / Loss 0.384510\n",
      "Epoch 371 / Batch (7/17) / Accuracy 0.8231 / Loss 0.407956\n",
      "Epoch 371 / Batch (8/17) / Accuracy 0.8388 / Loss 0.398645\n",
      "Epoch 371 / Batch (9/17) / Accuracy 0.8537 / Loss 0.389746\n",
      "Epoch 371 / Batch (10/17) / Accuracy 0.8556 / Loss 0.407089\n",
      "Epoch 371 / Batch (11/17) / Accuracy 0.8288 / Loss 0.418242\n",
      "Epoch 371 / Batch (12/17) / Accuracy 0.8469 / Loss 0.376989\n",
      "Epoch 371 / Batch (13/17) / Accuracy 0.8700 / Loss 0.345919\n",
      "Epoch 371 / Batch (14/17) / Accuracy 0.8081 / Loss 0.479829\n",
      "Epoch 371 / Batch (15/17) / Accuracy 0.8519 / Loss 0.392082\n",
      "Epoch 371 / Batch (16/17) / Accuracy 0.8431 / Loss 0.405635\n",
      "Epoch 371 / Batch (17/17) / Accuracy 0.8394 / Loss 0.394951\n",
      "Epoch 371 complete, 5.681556463241577 seconds elapsed\n",
      "\n",
      "Epoch 372 starting..\n",
      "Epoch 372 / Batch (1/17) / Accuracy 0.8306 / Loss 0.418561\n",
      "Epoch 372 / Batch (2/17) / Accuracy 0.8381 / Loss 0.406072\n",
      "Epoch 372 / Batch (3/17) / Accuracy 0.8350 / Loss 0.428956\n",
      "Epoch 372 / Batch (4/17) / Accuracy 0.8000 / Loss 0.517115\n",
      "Epoch 372 / Batch (5/17) / Accuracy 0.8481 / Loss 0.383859\n",
      "Epoch 372 / Batch (6/17) / Accuracy 0.8381 / Loss 0.400468\n",
      "Epoch 372 / Batch (7/17) / Accuracy 0.8363 / Loss 0.404538\n",
      "Epoch 372 / Batch (8/17) / Accuracy 0.8669 / Loss 0.340742\n",
      "Epoch 372 / Batch (9/17) / Accuracy 0.8156 / Loss 0.466322\n",
      "Epoch 372 / Batch (10/17) / Accuracy 0.8263 / Loss 0.438809\n",
      "Epoch 372 / Batch (11/17) / Accuracy 0.8144 / Loss 0.475997\n",
      "Epoch 372 / Batch (12/17) / Accuracy 0.8450 / Loss 0.375102\n",
      "Epoch 372 / Batch (13/17) / Accuracy 0.8188 / Loss 0.431580\n",
      "Epoch 372 / Batch (14/17) / Accuracy 0.8581 / Loss 0.356901\n",
      "Epoch 372 / Batch (15/17) / Accuracy 0.8138 / Loss 0.482676\n",
      "Epoch 372 / Batch (16/17) / Accuracy 0.8188 / Loss 0.453953\n",
      "Epoch 372 / Batch (17/17) / Accuracy 0.8344 / Loss 0.419508\n",
      "Epoch 372 complete, 5.280302047729492 seconds elapsed\n",
      "\n",
      "Epoch 373 starting..\n",
      "Epoch 373 / Batch (1/17) / Accuracy 0.8512 / Loss 0.394185\n",
      "Epoch 373 / Batch (2/17) / Accuracy 0.8462 / Loss 0.398723\n",
      "Epoch 373 / Batch (3/17) / Accuracy 0.8194 / Loss 0.453743\n",
      "Epoch 373 / Batch (4/17) / Accuracy 0.8119 / Loss 0.455805\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 373 / Batch (5/17) / Accuracy 0.8175 / Loss 0.491845\n",
      "Epoch 373 / Batch (6/17) / Accuracy 0.8450 / Loss 0.415164\n",
      "Epoch 373 / Batch (7/17) / Accuracy 0.8450 / Loss 0.407657\n",
      "Epoch 373 / Batch (8/17) / Accuracy 0.8725 / Loss 0.335671\n",
      "Epoch 373 / Batch (9/17) / Accuracy 0.8569 / Loss 0.384409\n",
      "Epoch 373 / Batch (10/17) / Accuracy 0.8456 / Loss 0.407235\n",
      "Epoch 373 / Batch (11/17) / Accuracy 0.8119 / Loss 0.464250\n",
      "Epoch 373 / Batch (12/17) / Accuracy 0.8213 / Loss 0.464025\n",
      "Epoch 373 / Batch (13/17) / Accuracy 0.8081 / Loss 0.502483\n",
      "Epoch 373 / Batch (14/17) / Accuracy 0.8556 / Loss 0.363706\n",
      "Epoch 373 / Batch (15/17) / Accuracy 0.8813 / Loss 0.339943\n",
      "Epoch 373 / Batch (16/17) / Accuracy 0.8188 / Loss 0.452389\n",
      "Epoch 373 / Batch (17/17) / Accuracy 0.8350 / Loss 0.430583\n",
      "Epoch 373 complete, 5.484385967254639 seconds elapsed\n",
      "\n",
      "Epoch 374 starting..\n",
      "Epoch 374 / Batch (1/17) / Accuracy 0.8313 / Loss 0.421024\n",
      "Epoch 374 / Batch (2/17) / Accuracy 0.8081 / Loss 0.475794\n",
      "Epoch 374 / Batch (3/17) / Accuracy 0.8006 / Loss 0.491636\n",
      "Epoch 374 / Batch (4/17) / Accuracy 0.8556 / Loss 0.360088\n",
      "Epoch 374 / Batch (5/17) / Accuracy 0.8219 / Loss 0.444950\n",
      "Epoch 374 / Batch (6/17) / Accuracy 0.8231 / Loss 0.433583\n",
      "Epoch 374 / Batch (7/17) / Accuracy 0.8388 / Loss 0.421535\n",
      "Epoch 374 / Batch (8/17) / Accuracy 0.8544 / Loss 0.385062\n",
      "Epoch 374 / Batch (9/17) / Accuracy 0.8456 / Loss 0.401006\n",
      "Epoch 374 / Batch (10/17) / Accuracy 0.8100 / Loss 0.477322\n",
      "Epoch 374 / Batch (11/17) / Accuracy 0.8206 / Loss 0.411857\n",
      "Epoch 374 / Batch (12/17) / Accuracy 0.8531 / Loss 0.379622\n",
      "Epoch 374 / Batch (13/17) / Accuracy 0.8250 / Loss 0.441004\n",
      "Epoch 374 / Batch (14/17) / Accuracy 0.8250 / Loss 0.446612\n",
      "Epoch 374 / Batch (15/17) / Accuracy 0.8231 / Loss 0.422044\n",
      "Epoch 374 / Batch (16/17) / Accuracy 0.8438 / Loss 0.394591\n",
      "Epoch 374 / Batch (17/17) / Accuracy 0.8487 / Loss 0.412514\n",
      "Epoch 374 complete, 6.2964558601379395 seconds elapsed\n",
      "\n",
      "Epoch 375 starting..\n",
      "Epoch 375 / Batch (1/17) / Accuracy 0.8594 / Loss 0.387301\n",
      "Epoch 375 / Batch (2/17) / Accuracy 0.8469 / Loss 0.422183\n",
      "Epoch 375 / Batch (3/17) / Accuracy 0.8475 / Loss 0.406271\n",
      "Epoch 375 / Batch (4/17) / Accuracy 0.8325 / Loss 0.418744\n",
      "Epoch 375 / Batch (5/17) / Accuracy 0.8169 / Loss 0.454209\n",
      "Epoch 375 / Batch (6/17) / Accuracy 0.8156 / Loss 0.463783\n",
      "Epoch 375 / Batch (7/17) / Accuracy 0.8481 / Loss 0.384739\n",
      "Epoch 375 / Batch (8/17) / Accuracy 0.8031 / Loss 0.490776\n",
      "Epoch 375 / Batch (9/17) / Accuracy 0.8200 / Loss 0.441871\n",
      "Epoch 375 / Batch (10/17) / Accuracy 0.7994 / Loss 0.456125\n",
      "Epoch 375 / Batch (11/17) / Accuracy 0.8100 / Loss 0.473914\n",
      "Epoch 375 / Batch (12/17) / Accuracy 0.8450 / Loss 0.425565\n",
      "Epoch 375 / Batch (13/17) / Accuracy 0.8175 / Loss 0.466610\n",
      "Epoch 375 / Batch (14/17) / Accuracy 0.8375 / Loss 0.409500\n",
      "Epoch 375 / Batch (15/17) / Accuracy 0.8281 / Loss 0.439443\n",
      "Epoch 375 / Batch (16/17) / Accuracy 0.8181 / Loss 0.453916\n",
      "Epoch 375 / Batch (17/17) / Accuracy 0.7912 / Loss 0.521540\n",
      "Epoch 375 complete, 5.528954744338989 seconds elapsed\n",
      "\n",
      "Epoch 376 starting..\n",
      "Epoch 376 / Batch (1/17) / Accuracy 0.8350 / Loss 0.423429\n",
      "Epoch 376 / Batch (2/17) / Accuracy 0.8369 / Loss 0.422244\n",
      "Epoch 376 / Batch (3/17) / Accuracy 0.8175 / Loss 0.466591\n",
      "Epoch 376 / Batch (4/17) / Accuracy 0.8400 / Loss 0.400012\n",
      "Epoch 376 / Batch (5/17) / Accuracy 0.8062 / Loss 0.477259\n",
      "Epoch 376 / Batch (6/17) / Accuracy 0.8012 / Loss 0.471421\n",
      "Epoch 376 / Batch (7/17) / Accuracy 0.8269 / Loss 0.450880\n",
      "Epoch 376 / Batch (8/17) / Accuracy 0.8169 / Loss 0.426606\n",
      "Epoch 376 / Batch (9/17) / Accuracy 0.8481 / Loss 0.407983\n",
      "Epoch 376 / Batch (10/17) / Accuracy 0.8263 / Loss 0.447341\n",
      "Epoch 376 / Batch (11/17) / Accuracy 0.8231 / Loss 0.457505\n",
      "Epoch 376 / Batch (12/17) / Accuracy 0.7900 / Loss 0.503912\n",
      "Epoch 376 / Batch (13/17) / Accuracy 0.8087 / Loss 0.491725\n",
      "Epoch 376 / Batch (14/17) / Accuracy 0.8469 / Loss 0.358841\n",
      "Epoch 376 / Batch (15/17) / Accuracy 0.8181 / Loss 0.435901\n",
      "Epoch 376 / Batch (16/17) / Accuracy 0.8275 / Loss 0.435454\n",
      "Epoch 376 / Batch (17/17) / Accuracy 0.8406 / Loss 0.401128\n",
      "Epoch 376 complete, 5.526331186294556 seconds elapsed\n",
      "\n",
      "Epoch 377 starting..\n",
      "Epoch 377 / Batch (1/17) / Accuracy 0.7875 / Loss 0.551517\n",
      "Epoch 377 / Batch (2/17) / Accuracy 0.8275 / Loss 0.435064\n",
      "Epoch 377 / Batch (3/17) / Accuracy 0.8425 / Loss 0.381849\n",
      "Epoch 377 / Batch (4/17) / Accuracy 0.8269 / Loss 0.407508\n",
      "Epoch 377 / Batch (5/17) / Accuracy 0.8487 / Loss 0.405341\n",
      "Epoch 377 / Batch (6/17) / Accuracy 0.8194 / Loss 0.436472\n",
      "Epoch 377 / Batch (7/17) / Accuracy 0.8294 / Loss 0.436508\n",
      "Epoch 377 / Batch (8/17) / Accuracy 0.8369 / Loss 0.419205\n",
      "Epoch 377 / Batch (9/17) / Accuracy 0.8481 / Loss 0.404100\n",
      "Epoch 377 / Batch (10/17) / Accuracy 0.8381 / Loss 0.410570\n",
      "Epoch 377 / Batch (11/17) / Accuracy 0.8450 / Loss 0.383936\n",
      "Epoch 377 / Batch (12/17) / Accuracy 0.7981 / Loss 0.501799\n",
      "Epoch 377 / Batch (13/17) / Accuracy 0.7931 / Loss 0.535234\n",
      "Epoch 377 / Batch (14/17) / Accuracy 0.8675 / Loss 0.356633\n",
      "Epoch 377 / Batch (15/17) / Accuracy 0.7812 / Loss 0.512348\n",
      "Epoch 377 / Batch (16/17) / Accuracy 0.8194 / Loss 0.435013\n",
      "Epoch 377 / Batch (17/17) / Accuracy 0.8500 / Loss 0.409194\n",
      "Epoch 377 complete, 5.261831045150757 seconds elapsed\n",
      "\n",
      "Epoch 378 starting..\n",
      "Epoch 378 / Batch (1/17) / Accuracy 0.8331 / Loss 0.456806\n",
      "Epoch 378 / Batch (2/17) / Accuracy 0.8188 / Loss 0.460554\n",
      "Epoch 378 / Batch (3/17) / Accuracy 0.8225 / Loss 0.453050\n",
      "Epoch 378 / Batch (4/17) / Accuracy 0.8012 / Loss 0.465033\n",
      "Epoch 378 / Batch (5/17) / Accuracy 0.8487 / Loss 0.369695\n",
      "Epoch 378 / Batch (6/17) / Accuracy 0.8306 / Loss 0.421955\n",
      "Epoch 378 / Batch (7/17) / Accuracy 0.8044 / Loss 0.511189\n",
      "Epoch 378 / Batch (8/17) / Accuracy 0.8388 / Loss 0.403148\n",
      "Epoch 378 / Batch (9/17) / Accuracy 0.8356 / Loss 0.414723\n",
      "Epoch 378 / Batch (10/17) / Accuracy 0.8487 / Loss 0.392709\n",
      "Epoch 378 / Batch (11/17) / Accuracy 0.8344 / Loss 0.400309\n",
      "Epoch 378 / Batch (12/17) / Accuracy 0.8225 / Loss 0.420673\n",
      "Epoch 378 / Batch (13/17) / Accuracy 0.8288 / Loss 0.448642\n",
      "Epoch 378 / Batch (14/17) / Accuracy 0.8269 / Loss 0.423821\n",
      "Epoch 378 / Batch (15/17) / Accuracy 0.8181 / Loss 0.452012\n",
      "Epoch 378 / Batch (16/17) / Accuracy 0.8687 / Loss 0.336319\n",
      "Epoch 378 / Batch (17/17) / Accuracy 0.8475 / Loss 0.393060\n",
      "Epoch 378 complete, 5.737119197845459 seconds elapsed\n",
      "\n",
      "Epoch 379 starting..\n",
      "Epoch 379 / Batch (1/17) / Accuracy 0.8375 / Loss 0.406712\n",
      "Epoch 379 / Batch (2/17) / Accuracy 0.8338 / Loss 0.424991\n",
      "Epoch 379 / Batch (3/17) / Accuracy 0.8394 / Loss 0.417876\n",
      "Epoch 379 / Batch (4/17) / Accuracy 0.8506 / Loss 0.402388\n",
      "Epoch 379 / Batch (5/17) / Accuracy 0.7994 / Loss 0.496889\n",
      "Epoch 379 / Batch (6/17) / Accuracy 0.8125 / Loss 0.473263\n",
      "Epoch 379 / Batch (7/17) / Accuracy 0.8606 / Loss 0.374924\n",
      "Epoch 379 / Batch (8/17) / Accuracy 0.8144 / Loss 0.479373\n",
      "Epoch 379 / Batch (9/17) / Accuracy 0.8175 / Loss 0.446068\n",
      "Epoch 379 / Batch (10/17) / Accuracy 0.8225 / Loss 0.444414\n",
      "Epoch 379 / Batch (11/17) / Accuracy 0.8175 / Loss 0.426581\n",
      "Epoch 379 / Batch (12/17) / Accuracy 0.8169 / Loss 0.454857\n",
      "Epoch 379 / Batch (13/17) / Accuracy 0.8169 / Loss 0.441304\n",
      "Epoch 379 / Batch (14/17) / Accuracy 0.8075 / Loss 0.454548\n",
      "Epoch 379 / Batch (15/17) / Accuracy 0.8756 / Loss 0.352319\n",
      "Epoch 379 / Batch (16/17) / Accuracy 0.8356 / Loss 0.414056\n",
      "Epoch 379 / Batch (17/17) / Accuracy 0.8325 / Loss 0.398407\n",
      "Epoch 379 complete, 5.854687690734863 seconds elapsed\n",
      "\n",
      "Epoch 380 starting..\n",
      "Epoch 380 / Batch (1/17) / Accuracy 0.8600 / Loss 0.365246\n",
      "Epoch 380 / Batch (2/17) / Accuracy 0.8519 / Loss 0.395990\n",
      "Epoch 380 / Batch (3/17) / Accuracy 0.8150 / Loss 0.487253\n",
      "Epoch 380 / Batch (4/17) / Accuracy 0.8406 / Loss 0.426616\n",
      "Epoch 380 / Batch (5/17) / Accuracy 0.8112 / Loss 0.455799\n",
      "Epoch 380 / Batch (6/17) / Accuracy 0.8519 / Loss 0.392008\n",
      "Epoch 380 / Batch (7/17) / Accuracy 0.8244 / Loss 0.465941\n",
      "Epoch 380 / Batch (8/17) / Accuracy 0.8394 / Loss 0.407027\n",
      "Epoch 380 / Batch (9/17) / Accuracy 0.8125 / Loss 0.453709\n",
      "Epoch 380 / Batch (10/17) / Accuracy 0.8419 / Loss 0.408354\n",
      "Epoch 380 / Batch (11/17) / Accuracy 0.8644 / Loss 0.351674\n",
      "Epoch 380 / Batch (12/17) / Accuracy 0.8144 / Loss 0.449461\n",
      "Epoch 380 / Batch (13/17) / Accuracy 0.8338 / Loss 0.431707\n",
      "Epoch 380 / Batch (14/17) / Accuracy 0.8650 / Loss 0.353269\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 380 / Batch (15/17) / Accuracy 0.8562 / Loss 0.376095\n",
      "Epoch 380 / Batch (16/17) / Accuracy 0.8106 / Loss 0.487519\n",
      "Epoch 380 / Batch (17/17) / Accuracy 0.8163 / Loss 0.461185\n",
      "Epoch 380 complete, 5.770671606063843 seconds elapsed\n",
      "\n",
      "Epoch 381 starting..\n",
      "Epoch 381 / Batch (1/17) / Accuracy 0.8338 / Loss 0.432692\n",
      "Epoch 381 / Batch (2/17) / Accuracy 0.8338 / Loss 0.406721\n",
      "Epoch 381 / Batch (3/17) / Accuracy 0.8450 / Loss 0.406309\n",
      "Epoch 381 / Batch (4/17) / Accuracy 0.8269 / Loss 0.440055\n",
      "Epoch 381 / Batch (5/17) / Accuracy 0.8150 / Loss 0.454356\n",
      "Epoch 381 / Batch (6/17) / Accuracy 0.8537 / Loss 0.368425\n",
      "Epoch 381 / Batch (7/17) / Accuracy 0.8381 / Loss 0.404754\n",
      "Epoch 381 / Batch (8/17) / Accuracy 0.8406 / Loss 0.404923\n",
      "Epoch 381 / Batch (9/17) / Accuracy 0.8494 / Loss 0.359417\n",
      "Epoch 381 / Batch (10/17) / Accuracy 0.8487 / Loss 0.424374\n",
      "Epoch 381 / Batch (11/17) / Accuracy 0.8400 / Loss 0.401527\n",
      "Epoch 381 / Batch (12/17) / Accuracy 0.8238 / Loss 0.440315\n",
      "Epoch 381 / Batch (13/17) / Accuracy 0.8438 / Loss 0.387840\n",
      "Epoch 381 / Batch (14/17) / Accuracy 0.8469 / Loss 0.393084\n",
      "Epoch 381 / Batch (15/17) / Accuracy 0.8675 / Loss 0.359199\n",
      "Epoch 381 / Batch (16/17) / Accuracy 0.8450 / Loss 0.390352\n",
      "Epoch 381 / Batch (17/17) / Accuracy 0.8075 / Loss 0.464974\n",
      "Epoch 381 complete, 5.891263484954834 seconds elapsed\n",
      "\n",
      "Epoch 382 starting..\n",
      "Epoch 382 / Batch (1/17) / Accuracy 0.8512 / Loss 0.399683\n",
      "Epoch 382 / Batch (2/17) / Accuracy 0.7994 / Loss 0.468143\n",
      "Epoch 382 / Batch (3/17) / Accuracy 0.8706 / Loss 0.344445\n",
      "Epoch 382 / Batch (4/17) / Accuracy 0.8475 / Loss 0.408399\n",
      "Epoch 382 / Batch (5/17) / Accuracy 0.8181 / Loss 0.482274\n",
      "Epoch 382 / Batch (6/17) / Accuracy 0.8363 / Loss 0.410950\n",
      "Epoch 382 / Batch (7/17) / Accuracy 0.8288 / Loss 0.440851\n",
      "Epoch 382 / Batch (8/17) / Accuracy 0.8369 / Loss 0.393329\n",
      "Epoch 382 / Batch (9/17) / Accuracy 0.8256 / Loss 0.456845\n",
      "Epoch 382 / Batch (10/17) / Accuracy 0.7600 / Loss 0.551929\n",
      "Epoch 382 / Batch (11/17) / Accuracy 0.8363 / Loss 0.428014\n",
      "Epoch 382 / Batch (12/17) / Accuracy 0.8250 / Loss 0.438350\n",
      "Epoch 382 / Batch (13/17) / Accuracy 0.8244 / Loss 0.443786\n",
      "Epoch 382 / Batch (14/17) / Accuracy 0.8331 / Loss 0.414386\n",
      "Epoch 382 / Batch (15/17) / Accuracy 0.8356 / Loss 0.449105\n",
      "Epoch 382 / Batch (16/17) / Accuracy 0.8238 / Loss 0.455128\n",
      "Epoch 382 / Batch (17/17) / Accuracy 0.8231 / Loss 0.446212\n",
      "Epoch 382 complete, 6.162833213806152 seconds elapsed\n",
      "\n",
      "Epoch 383 starting..\n",
      "Epoch 383 / Batch (1/17) / Accuracy 0.8344 / Loss 0.420015\n",
      "Epoch 383 / Batch (2/17) / Accuracy 0.8419 / Loss 0.406576\n",
      "Epoch 383 / Batch (3/17) / Accuracy 0.8188 / Loss 0.436509\n",
      "Epoch 383 / Batch (4/17) / Accuracy 0.8425 / Loss 0.396015\n",
      "Epoch 383 / Batch (5/17) / Accuracy 0.8206 / Loss 0.415713\n",
      "Epoch 383 / Batch (6/17) / Accuracy 0.8325 / Loss 0.413475\n",
      "Epoch 383 / Batch (7/17) / Accuracy 0.8400 / Loss 0.412892\n",
      "Epoch 383 / Batch (8/17) / Accuracy 0.8369 / Loss 0.415216\n",
      "Epoch 383 / Batch (9/17) / Accuracy 0.8369 / Loss 0.419894\n",
      "Epoch 383 / Batch (10/17) / Accuracy 0.8319 / Loss 0.417094\n",
      "Epoch 383 / Batch (11/17) / Accuracy 0.8325 / Loss 0.427230\n",
      "Epoch 383 / Batch (12/17) / Accuracy 0.8200 / Loss 0.444990\n",
      "Epoch 383 / Batch (13/17) / Accuracy 0.8587 / Loss 0.372555\n",
      "Epoch 383 / Batch (14/17) / Accuracy 0.8394 / Loss 0.428115\n",
      "Epoch 383 / Batch (15/17) / Accuracy 0.8325 / Loss 0.422126\n",
      "Epoch 383 / Batch (16/17) / Accuracy 0.8250 / Loss 0.452579\n",
      "Epoch 383 / Batch (17/17) / Accuracy 0.8413 / Loss 0.419106\n",
      "Epoch 383 complete, 5.144294738769531 seconds elapsed\n",
      "\n",
      "Epoch 384 starting..\n",
      "Epoch 384 / Batch (1/17) / Accuracy 0.8231 / Loss 0.424711\n",
      "Epoch 384 / Batch (2/17) / Accuracy 0.8250 / Loss 0.439747\n",
      "Epoch 384 / Batch (3/17) / Accuracy 0.8288 / Loss 0.414753\n",
      "Epoch 384 / Batch (4/17) / Accuracy 0.8425 / Loss 0.410566\n",
      "Epoch 384 / Batch (5/17) / Accuracy 0.8288 / Loss 0.448159\n",
      "Epoch 384 / Batch (6/17) / Accuracy 0.8213 / Loss 0.416837\n",
      "Epoch 384 / Batch (7/17) / Accuracy 0.8381 / Loss 0.446207\n",
      "Epoch 384 / Batch (8/17) / Accuracy 0.8694 / Loss 0.359387\n",
      "Epoch 384 / Batch (9/17) / Accuracy 0.8338 / Loss 0.434916\n",
      "Epoch 384 / Batch (10/17) / Accuracy 0.8256 / Loss 0.444933\n",
      "Epoch 384 / Batch (11/17) / Accuracy 0.8706 / Loss 0.338976\n",
      "Epoch 384 / Batch (12/17) / Accuracy 0.8263 / Loss 0.430278\n",
      "Epoch 384 / Batch (13/17) / Accuracy 0.8313 / Loss 0.409706\n",
      "Epoch 384 / Batch (14/17) / Accuracy 0.8112 / Loss 0.478052\n",
      "Epoch 384 / Batch (15/17) / Accuracy 0.8481 / Loss 0.384477\n",
      "Epoch 384 / Batch (16/17) / Accuracy 0.8475 / Loss 0.405554\n",
      "Epoch 384 / Batch (17/17) / Accuracy 0.8475 / Loss 0.411963\n",
      "Epoch 384 complete, 5.157340049743652 seconds elapsed\n",
      "\n",
      "Epoch 385 starting..\n",
      "Epoch 385 / Batch (1/17) / Accuracy 0.8331 / Loss 0.411354\n",
      "Epoch 385 / Batch (2/17) / Accuracy 0.8587 / Loss 0.363396\n",
      "Epoch 385 / Batch (3/17) / Accuracy 0.8181 / Loss 0.429118\n",
      "Epoch 385 / Batch (4/17) / Accuracy 0.8344 / Loss 0.425289\n",
      "Epoch 385 / Batch (5/17) / Accuracy 0.8125 / Loss 0.472899\n",
      "Epoch 385 / Batch (6/17) / Accuracy 0.8637 / Loss 0.363354\n",
      "Epoch 385 / Batch (7/17) / Accuracy 0.8369 / Loss 0.425586\n",
      "Epoch 385 / Batch (8/17) / Accuracy 0.8163 / Loss 0.465680\n",
      "Epoch 385 / Batch (9/17) / Accuracy 0.8456 / Loss 0.426620\n",
      "Epoch 385 / Batch (10/17) / Accuracy 0.8512 / Loss 0.409703\n",
      "Epoch 385 / Batch (11/17) / Accuracy 0.8188 / Loss 0.455008\n",
      "Epoch 385 / Batch (12/17) / Accuracy 0.8500 / Loss 0.397038\n",
      "Epoch 385 / Batch (13/17) / Accuracy 0.8319 / Loss 0.444443\n",
      "Epoch 385 / Batch (14/17) / Accuracy 0.8112 / Loss 0.502884\n",
      "Epoch 385 / Batch (15/17) / Accuracy 0.8344 / Loss 0.400692\n",
      "Epoch 385 / Batch (16/17) / Accuracy 0.8288 / Loss 0.443694\n",
      "Epoch 385 / Batch (17/17) / Accuracy 0.8263 / Loss 0.437214\n",
      "Epoch 385 complete, 5.572034597396851 seconds elapsed\n",
      "\n",
      "Epoch 386 starting..\n",
      "Epoch 386 / Batch (1/17) / Accuracy 0.8506 / Loss 0.400091\n",
      "Epoch 386 / Batch (2/17) / Accuracy 0.8344 / Loss 0.440791\n",
      "Epoch 386 / Batch (3/17) / Accuracy 0.8537 / Loss 0.391238\n",
      "Epoch 386 / Batch (4/17) / Accuracy 0.8263 / Loss 0.430417\n",
      "Epoch 386 / Batch (5/17) / Accuracy 0.8587 / Loss 0.364461\n",
      "Epoch 386 / Batch (6/17) / Accuracy 0.8444 / Loss 0.374896\n",
      "Epoch 386 / Batch (7/17) / Accuracy 0.8375 / Loss 0.435090\n",
      "Epoch 386 / Batch (8/17) / Accuracy 0.8200 / Loss 0.444837\n",
      "Epoch 386 / Batch (9/17) / Accuracy 0.8525 / Loss 0.392679\n",
      "Epoch 386 / Batch (10/17) / Accuracy 0.8562 / Loss 0.367690\n",
      "Epoch 386 / Batch (11/17) / Accuracy 0.8350 / Loss 0.411241\n",
      "Epoch 386 / Batch (12/17) / Accuracy 0.8469 / Loss 0.371026\n",
      "Epoch 386 / Batch (13/17) / Accuracy 0.8375 / Loss 0.415377\n",
      "Epoch 386 / Batch (14/17) / Accuracy 0.8269 / Loss 0.417527\n",
      "Epoch 386 / Batch (15/17) / Accuracy 0.8544 / Loss 0.369031\n",
      "Epoch 386 / Batch (16/17) / Accuracy 0.8163 / Loss 0.456731\n",
      "Epoch 386 / Batch (17/17) / Accuracy 0.8188 / Loss 0.442138\n",
      "Epoch 386 complete, 5.816632509231567 seconds elapsed\n",
      "\n",
      "Epoch 387 starting..\n",
      "Epoch 387 / Batch (1/17) / Accuracy 0.8238 / Loss 0.441819\n",
      "Epoch 387 / Batch (2/17) / Accuracy 0.8087 / Loss 0.459354\n",
      "Epoch 387 / Batch (3/17) / Accuracy 0.8462 / Loss 0.415206\n",
      "Epoch 387 / Batch (4/17) / Accuracy 0.8406 / Loss 0.407100\n",
      "Epoch 387 / Batch (5/17) / Accuracy 0.8388 / Loss 0.401964\n",
      "Epoch 387 / Batch (6/17) / Accuracy 0.8131 / Loss 0.451967\n",
      "Epoch 387 / Batch (7/17) / Accuracy 0.8487 / Loss 0.370747\n",
      "Epoch 387 / Batch (8/17) / Accuracy 0.8338 / Loss 0.405239\n",
      "Epoch 387 / Batch (9/17) / Accuracy 0.7987 / Loss 0.495736\n",
      "Epoch 387 / Batch (10/17) / Accuracy 0.8131 / Loss 0.464904\n",
      "Epoch 387 / Batch (11/17) / Accuracy 0.8350 / Loss 0.385817\n",
      "Epoch 387 / Batch (12/17) / Accuracy 0.8431 / Loss 0.402380\n",
      "Epoch 387 / Batch (13/17) / Accuracy 0.8244 / Loss 0.439282\n",
      "Epoch 387 / Batch (14/17) / Accuracy 0.8225 / Loss 0.452002\n",
      "Epoch 387 / Batch (15/17) / Accuracy 0.8381 / Loss 0.417776\n",
      "Epoch 387 / Batch (16/17) / Accuracy 0.8006 / Loss 0.468441\n",
      "Epoch 387 / Batch (17/17) / Accuracy 0.8163 / Loss 0.466842\n",
      "Epoch 387 complete, 5.8359456062316895 seconds elapsed\n",
      "\n",
      "Epoch 388 starting..\n",
      "Epoch 388 / Batch (1/17) / Accuracy 0.8581 / Loss 0.378420\n",
      "Epoch 388 / Batch (2/17) / Accuracy 0.8306 / Loss 0.469420\n",
      "Epoch 388 / Batch (3/17) / Accuracy 0.8263 / Loss 0.449312\n",
      "Epoch 388 / Batch (4/17) / Accuracy 0.8281 / Loss 0.440660\n",
      "Epoch 388 / Batch (5/17) / Accuracy 0.8188 / Loss 0.462891\n",
      "Epoch 388 / Batch (6/17) / Accuracy 0.8288 / Loss 0.432904\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 388 / Batch (7/17) / Accuracy 0.8375 / Loss 0.402202\n",
      "Epoch 388 / Batch (8/17) / Accuracy 0.8194 / Loss 0.434908\n",
      "Epoch 388 / Batch (9/17) / Accuracy 0.8575 / Loss 0.384884\n",
      "Epoch 388 / Batch (10/17) / Accuracy 0.8100 / Loss 0.479487\n",
      "Epoch 388 / Batch (11/17) / Accuracy 0.8531 / Loss 0.396593\n",
      "Epoch 388 / Batch (12/17) / Accuracy 0.8419 / Loss 0.413618\n",
      "Epoch 388 / Batch (13/17) / Accuracy 0.8400 / Loss 0.415553\n",
      "Epoch 388 / Batch (14/17) / Accuracy 0.8219 / Loss 0.432781\n",
      "Epoch 388 / Batch (15/17) / Accuracy 0.8462 / Loss 0.403051\n",
      "Epoch 388 / Batch (16/17) / Accuracy 0.8288 / Loss 0.431000\n",
      "Epoch 388 / Batch (17/17) / Accuracy 0.8319 / Loss 0.424539\n",
      "Epoch 388 complete, 5.829784870147705 seconds elapsed\n",
      "\n",
      "Epoch 389 starting..\n",
      "Epoch 389 / Batch (1/17) / Accuracy 0.8288 / Loss 0.411104\n",
      "Epoch 389 / Batch (2/17) / Accuracy 0.8081 / Loss 0.456704\n",
      "Epoch 389 / Batch (3/17) / Accuracy 0.8338 / Loss 0.412193\n",
      "Epoch 389 / Batch (4/17) / Accuracy 0.8225 / Loss 0.437441\n",
      "Epoch 389 / Batch (5/17) / Accuracy 0.8350 / Loss 0.402764\n",
      "Epoch 389 / Batch (6/17) / Accuracy 0.8263 / Loss 0.432294\n",
      "Epoch 389 / Batch (7/17) / Accuracy 0.8519 / Loss 0.386332\n",
      "Epoch 389 / Batch (8/17) / Accuracy 0.8475 / Loss 0.387770\n",
      "Epoch 389 / Batch (9/17) / Accuracy 0.8450 / Loss 0.391575\n",
      "Epoch 389 / Batch (10/17) / Accuracy 0.8612 / Loss 0.373671\n",
      "Epoch 389 / Batch (11/17) / Accuracy 0.8506 / Loss 0.379894\n",
      "Epoch 389 / Batch (12/17) / Accuracy 0.8144 / Loss 0.470424\n",
      "Epoch 389 / Batch (13/17) / Accuracy 0.8562 / Loss 0.371799\n",
      "Epoch 389 / Batch (14/17) / Accuracy 0.8562 / Loss 0.368774\n",
      "Epoch 389 / Batch (15/17) / Accuracy 0.8344 / Loss 0.431135\n",
      "Epoch 389 / Batch (16/17) / Accuracy 0.8475 / Loss 0.368361\n",
      "Epoch 389 / Batch (17/17) / Accuracy 0.8637 / Loss 0.369333\n",
      "Epoch 389 complete, 5.849165201187134 seconds elapsed\n",
      "\n",
      "Epoch 390 starting..\n",
      "Epoch 390 / Batch (1/17) / Accuracy 0.8537 / Loss 0.339481\n",
      "Epoch 390 / Batch (2/17) / Accuracy 0.8400 / Loss 0.391408\n",
      "Epoch 390 / Batch (3/17) / Accuracy 0.8394 / Loss 0.399780\n",
      "Epoch 390 / Batch (4/17) / Accuracy 0.8388 / Loss 0.417500\n",
      "Epoch 390 / Batch (5/17) / Accuracy 0.8612 / Loss 0.373916\n",
      "Epoch 390 / Batch (6/17) / Accuracy 0.8550 / Loss 0.380370\n",
      "Epoch 390 / Batch (7/17) / Accuracy 0.8188 / Loss 0.490785\n",
      "Epoch 390 / Batch (8/17) / Accuracy 0.8469 / Loss 0.400001\n",
      "Epoch 390 / Batch (9/17) / Accuracy 0.8637 / Loss 0.379183\n",
      "Epoch 390 / Batch (10/17) / Accuracy 0.8537 / Loss 0.380730\n",
      "Epoch 390 / Batch (11/17) / Accuracy 0.8406 / Loss 0.400770\n",
      "Epoch 390 / Batch (12/17) / Accuracy 0.8288 / Loss 0.441232\n",
      "Epoch 390 / Batch (13/17) / Accuracy 0.8631 / Loss 0.358468\n",
      "Epoch 390 / Batch (14/17) / Accuracy 0.8138 / Loss 0.472682\n",
      "Epoch 390 / Batch (15/17) / Accuracy 0.8506 / Loss 0.446969\n",
      "Epoch 390 / Batch (16/17) / Accuracy 0.8506 / Loss 0.381728\n",
      "Epoch 390 / Batch (17/17) / Accuracy 0.8219 / Loss 0.437801\n",
      "Epoch 390 complete, 6.051468849182129 seconds elapsed\n",
      "\n",
      "Epoch 391 starting..\n",
      "Epoch 391 / Batch (1/17) / Accuracy 0.8537 / Loss 0.357798\n",
      "Epoch 391 / Batch (2/17) / Accuracy 0.8438 / Loss 0.382052\n",
      "Epoch 391 / Batch (3/17) / Accuracy 0.8506 / Loss 0.392670\n",
      "Epoch 391 / Batch (4/17) / Accuracy 0.8637 / Loss 0.373946\n",
      "Epoch 391 / Batch (5/17) / Accuracy 0.8450 / Loss 0.414341\n",
      "Epoch 391 / Batch (6/17) / Accuracy 0.8112 / Loss 0.465151\n",
      "Epoch 391 / Batch (7/17) / Accuracy 0.8669 / Loss 0.343521\n",
      "Epoch 391 / Batch (8/17) / Accuracy 0.8363 / Loss 0.426482\n",
      "Epoch 391 / Batch (9/17) / Accuracy 0.8294 / Loss 0.427787\n",
      "Epoch 391 / Batch (10/17) / Accuracy 0.8294 / Loss 0.422797\n",
      "Epoch 391 / Batch (11/17) / Accuracy 0.8338 / Loss 0.408099\n",
      "Epoch 391 / Batch (12/17) / Accuracy 0.8300 / Loss 0.433780\n",
      "Epoch 391 / Batch (13/17) / Accuracy 0.8512 / Loss 0.396008\n",
      "Epoch 391 / Batch (14/17) / Accuracy 0.8431 / Loss 0.399918\n",
      "Epoch 391 / Batch (15/17) / Accuracy 0.8438 / Loss 0.374334\n",
      "Epoch 391 / Batch (16/17) / Accuracy 0.8687 / Loss 0.331507\n",
      "Epoch 391 / Batch (17/17) / Accuracy 0.8600 / Loss 0.362970\n",
      "Epoch 391 complete, 6.305238246917725 seconds elapsed\n",
      "\n",
      "Epoch 392 starting..\n",
      "Epoch 392 / Batch (1/17) / Accuracy 0.8275 / Loss 0.449348\n",
      "Epoch 392 / Batch (2/17) / Accuracy 0.8075 / Loss 0.466664\n",
      "Epoch 392 / Batch (3/17) / Accuracy 0.8181 / Loss 0.437624\n",
      "Epoch 392 / Batch (4/17) / Accuracy 0.8888 / Loss 0.337632\n",
      "Epoch 392 / Batch (5/17) / Accuracy 0.7994 / Loss 0.500833\n",
      "Epoch 392 / Batch (6/17) / Accuracy 0.8731 / Loss 0.339483\n",
      "Epoch 392 / Batch (7/17) / Accuracy 0.8444 / Loss 0.386501\n",
      "Epoch 392 / Batch (8/17) / Accuracy 0.8413 / Loss 0.402899\n",
      "Epoch 392 / Batch (9/17) / Accuracy 0.8544 / Loss 0.368652\n",
      "Epoch 392 / Batch (10/17) / Accuracy 0.8431 / Loss 0.385260\n",
      "Epoch 392 / Batch (11/17) / Accuracy 0.8175 / Loss 0.447906\n",
      "Epoch 392 / Batch (12/17) / Accuracy 0.8487 / Loss 0.379690\n",
      "Epoch 392 / Batch (13/17) / Accuracy 0.8413 / Loss 0.423133\n",
      "Epoch 392 / Batch (14/17) / Accuracy 0.8256 / Loss 0.432178\n",
      "Epoch 392 / Batch (15/17) / Accuracy 0.8419 / Loss 0.389853\n",
      "Epoch 392 / Batch (16/17) / Accuracy 0.8356 / Loss 0.416794\n",
      "Epoch 392 / Batch (17/17) / Accuracy 0.8169 / Loss 0.442089\n",
      "Epoch 392 complete, 5.561652898788452 seconds elapsed\n",
      "\n",
      "Epoch 393 starting..\n",
      "Epoch 393 / Batch (1/17) / Accuracy 0.8250 / Loss 0.423236\n",
      "Epoch 393 / Batch (2/17) / Accuracy 0.8450 / Loss 0.408445\n",
      "Epoch 393 / Batch (3/17) / Accuracy 0.8444 / Loss 0.432823\n",
      "Epoch 393 / Batch (4/17) / Accuracy 0.8338 / Loss 0.436550\n",
      "Epoch 393 / Batch (5/17) / Accuracy 0.8300 / Loss 0.421642\n",
      "Epoch 393 / Batch (6/17) / Accuracy 0.8381 / Loss 0.431001\n",
      "Epoch 393 / Batch (7/17) / Accuracy 0.8163 / Loss 0.451464\n",
      "Epoch 393 / Batch (8/17) / Accuracy 0.8425 / Loss 0.418493\n",
      "Epoch 393 / Batch (9/17) / Accuracy 0.8181 / Loss 0.427158\n",
      "Epoch 393 / Batch (10/17) / Accuracy 0.8406 / Loss 0.439751\n",
      "Epoch 393 / Batch (11/17) / Accuracy 0.8313 / Loss 0.443780\n",
      "Epoch 393 / Batch (12/17) / Accuracy 0.8856 / Loss 0.309016\n",
      "Epoch 393 / Batch (13/17) / Accuracy 0.8125 / Loss 0.469476\n",
      "Epoch 393 / Batch (14/17) / Accuracy 0.8544 / Loss 0.386625\n",
      "Epoch 393 / Batch (15/17) / Accuracy 0.8388 / Loss 0.395462\n",
      "Epoch 393 / Batch (16/17) / Accuracy 0.8375 / Loss 0.404436\n",
      "Epoch 393 / Batch (17/17) / Accuracy 0.8425 / Loss 0.381680\n",
      "Epoch 393 complete, 6.046098947525024 seconds elapsed\n",
      "\n",
      "Epoch 394 starting..\n",
      "Epoch 394 / Batch (1/17) / Accuracy 0.8413 / Loss 0.407896\n",
      "Epoch 394 / Batch (2/17) / Accuracy 0.8587 / Loss 0.359221\n",
      "Epoch 394 / Batch (3/17) / Accuracy 0.8419 / Loss 0.396629\n",
      "Epoch 394 / Batch (4/17) / Accuracy 0.8169 / Loss 0.447214\n",
      "Epoch 394 / Batch (5/17) / Accuracy 0.8656 / Loss 0.387408\n",
      "Epoch 394 / Batch (6/17) / Accuracy 0.8300 / Loss 0.437341\n",
      "Epoch 394 / Batch (7/17) / Accuracy 0.8238 / Loss 0.439299\n",
      "Epoch 394 / Batch (8/17) / Accuracy 0.8338 / Loss 0.412626\n",
      "Epoch 394 / Batch (9/17) / Accuracy 0.8581 / Loss 0.373939\n",
      "Epoch 394 / Batch (10/17) / Accuracy 0.8338 / Loss 0.425259\n",
      "Epoch 394 / Batch (11/17) / Accuracy 0.8469 / Loss 0.396291\n",
      "Epoch 394 / Batch (12/17) / Accuracy 0.8319 / Loss 0.401013\n",
      "Epoch 394 / Batch (13/17) / Accuracy 0.8188 / Loss 0.443355\n",
      "Epoch 394 / Batch (14/17) / Accuracy 0.8163 / Loss 0.460740\n",
      "Epoch 394 / Batch (15/17) / Accuracy 0.8594 / Loss 0.375861\n",
      "Epoch 394 / Batch (16/17) / Accuracy 0.8537 / Loss 0.372069\n",
      "Epoch 394 / Batch (17/17) / Accuracy 0.8031 / Loss 0.494885\n",
      "Epoch 394 complete, 6.076816558837891 seconds elapsed\n",
      "\n",
      "Epoch 395 starting..\n",
      "Epoch 395 / Batch (1/17) / Accuracy 0.8438 / Loss 0.401709\n",
      "Epoch 395 / Batch (2/17) / Accuracy 0.8213 / Loss 0.437447\n",
      "Epoch 395 / Batch (3/17) / Accuracy 0.8394 / Loss 0.402148\n",
      "Epoch 395 / Batch (4/17) / Accuracy 0.8400 / Loss 0.403198\n",
      "Epoch 395 / Batch (5/17) / Accuracy 0.8456 / Loss 0.418644\n",
      "Epoch 395 / Batch (6/17) / Accuracy 0.8462 / Loss 0.408755\n",
      "Epoch 395 / Batch (7/17) / Accuracy 0.8156 / Loss 0.458748\n",
      "Epoch 395 / Batch (8/17) / Accuracy 0.8275 / Loss 0.453668\n",
      "Epoch 395 / Batch (9/17) / Accuracy 0.8369 / Loss 0.432727\n",
      "Epoch 395 / Batch (10/17) / Accuracy 0.8619 / Loss 0.370769\n",
      "Epoch 395 / Batch (11/17) / Accuracy 0.8537 / Loss 0.371677\n",
      "Epoch 395 / Batch (12/17) / Accuracy 0.8400 / Loss 0.418748\n",
      "Epoch 395 / Batch (13/17) / Accuracy 0.8288 / Loss 0.430544\n",
      "Epoch 395 / Batch (14/17) / Accuracy 0.8637 / Loss 0.363569\n",
      "Epoch 395 / Batch (15/17) / Accuracy 0.8206 / Loss 0.476075\n",
      "Epoch 395 / Batch (16/17) / Accuracy 0.7844 / Loss 0.534925\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 395 / Batch (17/17) / Accuracy 0.8381 / Loss 0.426970\n",
      "Epoch 395 complete, 6.016657829284668 seconds elapsed\n",
      "\n",
      "Epoch 396 starting..\n",
      "Epoch 396 / Batch (1/17) / Accuracy 0.8462 / Loss 0.394463\n",
      "Epoch 396 / Batch (2/17) / Accuracy 0.8625 / Loss 0.362781\n",
      "Epoch 396 / Batch (3/17) / Accuracy 0.8288 / Loss 0.430087\n",
      "Epoch 396 / Batch (4/17) / Accuracy 0.8369 / Loss 0.404840\n",
      "Epoch 396 / Batch (5/17) / Accuracy 0.8169 / Loss 0.480826\n",
      "Epoch 396 / Batch (6/17) / Accuracy 0.8512 / Loss 0.385863\n",
      "Epoch 396 / Batch (7/17) / Accuracy 0.8712 / Loss 0.330523\n",
      "Epoch 396 / Batch (8/17) / Accuracy 0.8506 / Loss 0.376084\n",
      "Epoch 396 / Batch (9/17) / Accuracy 0.8294 / Loss 0.439016\n",
      "Epoch 396 / Batch (10/17) / Accuracy 0.8188 / Loss 0.446438\n",
      "Epoch 396 / Batch (11/17) / Accuracy 0.8431 / Loss 0.409443\n",
      "Epoch 396 / Batch (12/17) / Accuracy 0.8819 / Loss 0.343340\n",
      "Epoch 396 / Batch (13/17) / Accuracy 0.8481 / Loss 0.376595\n",
      "Epoch 396 / Batch (14/17) / Accuracy 0.8487 / Loss 0.404466\n",
      "Epoch 396 / Batch (15/17) / Accuracy 0.8462 / Loss 0.396648\n",
      "Epoch 396 / Batch (16/17) / Accuracy 0.8881 / Loss 0.311473\n",
      "Epoch 396 / Batch (17/17) / Accuracy 0.8338 / Loss 0.454352\n",
      "Epoch 396 complete, 5.87550687789917 seconds elapsed\n",
      "\n",
      "Epoch 397 starting..\n",
      "Epoch 397 / Batch (1/17) / Accuracy 0.8506 / Loss 0.369105\n",
      "Epoch 397 / Batch (2/17) / Accuracy 0.8569 / Loss 0.372418\n",
      "Epoch 397 / Batch (3/17) / Accuracy 0.8631 / Loss 0.339735\n",
      "Epoch 397 / Batch (4/17) / Accuracy 0.8481 / Loss 0.375327\n",
      "Epoch 397 / Batch (5/17) / Accuracy 0.8169 / Loss 0.472237\n",
      "Epoch 397 / Batch (6/17) / Accuracy 0.8481 / Loss 0.390252\n",
      "Epoch 397 / Batch (7/17) / Accuracy 0.8331 / Loss 0.430970\n",
      "Epoch 397 / Batch (8/17) / Accuracy 0.8544 / Loss 0.371979\n",
      "Epoch 397 / Batch (9/17) / Accuracy 0.8250 / Loss 0.439929\n",
      "Epoch 397 / Batch (10/17) / Accuracy 0.8206 / Loss 0.442795\n",
      "Epoch 397 / Batch (11/17) / Accuracy 0.8469 / Loss 0.382599\n",
      "Epoch 397 / Batch (12/17) / Accuracy 0.8562 / Loss 0.373465\n",
      "Epoch 397 / Batch (13/17) / Accuracy 0.8350 / Loss 0.394653\n",
      "Epoch 397 / Batch (14/17) / Accuracy 0.8119 / Loss 0.462239\n",
      "Epoch 397 / Batch (15/17) / Accuracy 0.8381 / Loss 0.413212\n",
      "Epoch 397 / Batch (16/17) / Accuracy 0.8413 / Loss 0.398720\n",
      "Epoch 397 / Batch (17/17) / Accuracy 0.7975 / Loss 0.503879\n",
      "Epoch 397 complete, 5.6456732749938965 seconds elapsed\n",
      "\n",
      "Epoch 398 starting..\n",
      "Epoch 398 / Batch (1/17) / Accuracy 0.8581 / Loss 0.372432\n",
      "Epoch 398 / Batch (2/17) / Accuracy 0.8456 / Loss 0.398548\n",
      "Epoch 398 / Batch (3/17) / Accuracy 0.8231 / Loss 0.467135\n",
      "Epoch 398 / Batch (4/17) / Accuracy 0.8319 / Loss 0.413741\n",
      "Epoch 398 / Batch (5/17) / Accuracy 0.8419 / Loss 0.424675\n",
      "Epoch 398 / Batch (6/17) / Accuracy 0.8313 / Loss 0.443308\n",
      "Epoch 398 / Batch (7/17) / Accuracy 0.8719 / Loss 0.370015\n",
      "Epoch 398 / Batch (8/17) / Accuracy 0.8562 / Loss 0.382126\n",
      "Epoch 398 / Batch (9/17) / Accuracy 0.8662 / Loss 0.371871\n",
      "Epoch 398 / Batch (10/17) / Accuracy 0.8500 / Loss 0.405864\n",
      "Epoch 398 / Batch (11/17) / Accuracy 0.8544 / Loss 0.396935\n",
      "Epoch 398 / Batch (12/17) / Accuracy 0.8319 / Loss 0.431596\n",
      "Epoch 398 / Batch (13/17) / Accuracy 0.8338 / Loss 0.426968\n",
      "Epoch 398 / Batch (14/17) / Accuracy 0.8344 / Loss 0.448678\n",
      "Epoch 398 / Batch (15/17) / Accuracy 0.8400 / Loss 0.400932\n",
      "Epoch 398 / Batch (16/17) / Accuracy 0.8225 / Loss 0.481087\n",
      "Epoch 398 / Batch (17/17) / Accuracy 0.8138 / Loss 0.472335\n",
      "Epoch 398 complete, 6.225250720977783 seconds elapsed\n",
      "\n",
      "Epoch 399 starting..\n",
      "Epoch 399 / Batch (1/17) / Accuracy 0.8338 / Loss 0.411706\n",
      "Epoch 399 / Batch (2/17) / Accuracy 0.8369 / Loss 0.388115\n",
      "Epoch 399 / Batch (3/17) / Accuracy 0.8281 / Loss 0.430154\n",
      "Epoch 399 / Batch (4/17) / Accuracy 0.8394 / Loss 0.406793\n",
      "Epoch 399 / Batch (5/17) / Accuracy 0.8450 / Loss 0.401587\n",
      "Epoch 399 / Batch (6/17) / Accuracy 0.8231 / Loss 0.432155\n",
      "Epoch 399 / Batch (7/17) / Accuracy 0.8225 / Loss 0.432128\n",
      "Epoch 399 / Batch (8/17) / Accuracy 0.8219 / Loss 0.453647\n",
      "Epoch 399 / Batch (9/17) / Accuracy 0.8519 / Loss 0.397509\n",
      "Epoch 399 / Batch (10/17) / Accuracy 0.8575 / Loss 0.368078\n",
      "Epoch 399 / Batch (11/17) / Accuracy 0.8019 / Loss 0.482443\n",
      "Epoch 399 / Batch (12/17) / Accuracy 0.8119 / Loss 0.450639\n",
      "Epoch 399 / Batch (13/17) / Accuracy 0.8456 / Loss 0.421582\n",
      "Epoch 399 / Batch (14/17) / Accuracy 0.8725 / Loss 0.340866\n",
      "Epoch 399 / Batch (15/17) / Accuracy 0.8438 / Loss 0.402704\n",
      "Epoch 399 / Batch (16/17) / Accuracy 0.8144 / Loss 0.436052\n",
      "Epoch 399 / Batch (17/17) / Accuracy 0.8556 / Loss 0.379782\n",
      "Epoch 399 complete, 5.922934532165527 seconds elapsed\n",
      "\n",
      "Epoch 400 starting..\n",
      "Epoch 400 / Batch (1/17) / Accuracy 0.8375 / Loss 0.411767\n",
      "Epoch 400 / Batch (2/17) / Accuracy 0.8500 / Loss 0.406628\n",
      "Epoch 400 / Batch (3/17) / Accuracy 0.8263 / Loss 0.465390\n",
      "Epoch 400 / Batch (4/17) / Accuracy 0.8669 / Loss 0.350850\n",
      "Epoch 400 / Batch (5/17) / Accuracy 0.8363 / Loss 0.406008\n",
      "Epoch 400 / Batch (6/17) / Accuracy 0.8150 / Loss 0.416147\n",
      "Epoch 400 / Batch (7/17) / Accuracy 0.8469 / Loss 0.393906\n",
      "Epoch 400 / Batch (8/17) / Accuracy 0.8562 / Loss 0.372276\n",
      "Epoch 400 / Batch (9/17) / Accuracy 0.8356 / Loss 0.389323\n",
      "Epoch 400 / Batch (10/17) / Accuracy 0.8356 / Loss 0.427260\n",
      "Epoch 400 / Batch (11/17) / Accuracy 0.8500 / Loss 0.390301\n",
      "Epoch 400 / Batch (12/17) / Accuracy 0.8694 / Loss 0.340578\n",
      "Epoch 400 / Batch (13/17) / Accuracy 0.8275 / Loss 0.408289\n",
      "Epoch 400 / Batch (14/17) / Accuracy 0.8381 / Loss 0.395614\n",
      "Epoch 400 / Batch (15/17) / Accuracy 0.8163 / Loss 0.457696\n",
      "Epoch 400 / Batch (16/17) / Accuracy 0.8363 / Loss 0.446754\n",
      "Epoch 400 / Batch (17/17) / Accuracy 0.8381 / Loss 0.407218\n",
      "Epoch 400 complete, 5.5612828731536865 seconds elapsed\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import time\n",
    "import os\n",
    "\n",
    "n_epochs = 400\n",
    "\n",
    "if True:\n",
    "    saver.restore(sess, os.path.join(savedir,'400/Model.ckpt'))\n",
    "\n",
    "with sess.as_default():\n",
    "    for epoch in range(n_epochs):\n",
    "        print('Epoch {} starting..'.format(epoch+1))\n",
    "        epoch_start = time.time()\n",
    "        classes_epoch, imgs_epoch = ut.shuffle_xy(classes_train,imgs_train)\n",
    "        \n",
    "        n_batches = len(classes_epoch)//(n_classes*batch_size)\n",
    "        for batch in range(n_batches):\n",
    "            classes_batch = classes_epoch[batch*n_classes*batch_size:(batch+1)*n_classes*batch_size]\n",
    "            imgs_batch = imgs_epoch[batch*n_classes*batch_size:(batch+1)*n_classes*batch_size]\n",
    "            \n",
    "            Xl_batch, yl_batch = [], []\n",
    "            for episode in range(batch_size):\n",
    "                imgs_ep = imgs_batch[episode*n_classes:(episode+1)*n_classes]\n",
    "                Xl_ep, yl_ep = [], []\n",
    "                for ind, cat in enumerate(imgs_ep):\n",
    "                    for arr in cat:\n",
    "                        Xl_ep.append(arr)\n",
    "                        yl_ep.append(ut.one_hot(ind,n_classes))\n",
    "                Xl_shuff, yl_shuff = ut.shuffle_xy(Xl_ep,yl_ep)\n",
    "                X_arr, y_arr = np.asarray(Xl_shuff), np.asarray(yl_shuff)\n",
    "                Xl_batch.append(X_arr)\n",
    "                yl_batch.append(y_arr)\n",
    "            X_train, y_train = np.asarray(Xl_batch), np.asarray(yl_batch)\n",
    "            \n",
    "            _, loss_train, accuracy_train = sess.run((train_step,loss,accuracy),feed_dict={X:X_train,y:y_train})\n",
    "            print('Epoch %d'%(epoch+1),'/ Batch (%d/%d)'%(batch+1,n_batches),'/ Accuracy %.4f / Loss %f'%(accuracy_train,loss_train))\n",
    "            \n",
    "        epoch_end = time.time()\n",
    "        time_elapsed = epoch_end-epoch_start\n",
    "        print('Epoch {} complete,'.format(epoch+1),time_elapsed,'seconds elapsed')\n",
    "        if (epoch+1)%40 == 0:\n",
    "            iterdir = os.path.join(savedir,str(epoch+1))\n",
    "            if not os.path.exists(iterdir):\n",
    "                os.makedirs(iterdir)\n",
    "            saver.save(sess,'{}/Model.ckpt'.format(iterdir))\n",
    "        print()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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