additional_rnn.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "'''An implementation of sequence to sequence learning for performing addition\n",
    "        Input: \"535+61\"\n",
    "        Output: \"596\"\n",
    "\n",
    "Padding is handled by using a repeated sentinel character (space)\n",
    "Input may optionally be inverted, shown to increase performance in many tasks in:\n",
    "        \"Learning to Execute\" \n",
    "            http://arxiv.org/abs/1410.4615 and\n",
    "        \"Sequence to Sequence Learning with Neural Networks\" \n",
    "            http://papers.nips.cc/paper/5346-sequence-to-sequence-learning-with-neural-networks.pdf\n",
    "Theoretically it introduces shorter term dependencies between source and target.\n",
    "\n",
    "Two digits inverted:\n",
    "+ One layer LSTM (128 HN), 5k training examples = 99% train/test accuracy in 55 epochs\n",
    "Three digits inverted:\n",
    "+ One layer LSTM (128 HN), 50k training examples = 99% train/test accuracy in 100 epochs\n",
    "Four digits inverted:\n",
    "+ One layer LSTM (128 HN), 400k training examples = 99% train/test accuracy in 20 epochs\n",
    "Five digits inverted:\n",
    "+ One layer LSTM (128 HN), 550k training examples = 99% train/test accuracy in 30 epochs\n",
    "'''\n",
    "\n",
    "from __future__ import print_function\n",
    "from keras.models import Sequential\n",
    "from keras import layers\n",
    "import numpy as np\n",
    "from six.moves import range"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "class CharacterTable(object):\n",
    "    \"\"\"Given a set of characters:\n",
    "    + Encode them to a one hot integer representation\n",
    "    + Decode the one hot integer representation to their character output\n",
    "    + Decode a vector of probabilities to their character output\n",
    "    \"\"\"\n",
    "    def __init__(self, chars):\n",
    "        \"\"\"Initialize character table.\n",
    "        # Arguments\n",
    "            chars: Characters that can appear in the input.\n",
    "        \"\"\"\n",
    "        self.chars = sorted(set(chars))\n",
    "        self.char_indices = dict((c, i) for i, c in enumerate(self.chars))\n",
    "        self.indices_char = dict((i, c) for i, c in enumerate(self.chars))\n",
    "\n",
    "    def encode(self, C, num_rows):\n",
    "        \"\"\"One hot encode given string C.\n",
    "        # Arguments\n",
    "            num_rows: Number of rows in the returned one hot encoding. This is\n",
    "                used to keep the # of rows for each data the same.\n",
    "        \"\"\"\n",
    "        x = np.zeros((num_rows, len(self.chars)))\n",
    "        for i, c in enumerate(C):\n",
    "            x[i, self.char_indices[c]] = 1\n",
    "        return x\n",
    "\n",
    "    def decode(self, x, calc_argmax=True):\n",
    "        if calc_argmax:\n",
    "            x = x.argmax(axis=-1)\n",
    "        return ''.join(self.indices_char[x] for x in x)\n",
    "\n",
    "\n",
    "class colors:\n",
    "    ok = '\\033[92m'\n",
    "    fail = '\\033[91m'\n",
    "    close = '\\033[0m'\n",
    "\n",
    "# Parameters for the model and dataset.\n",
    "TRAINING_SIZE = 50000\n",
    "DIGITS = 3\n",
    "INVERT = True\n",
    "\n",
    "# Maximum length of input is 'int + int' (e.g., '345+678'). Maximum length of\n",
    "# int is DIGITS.\n",
    "MAXLEN = DIGITS + 1 + DIGITS\n",
    "\n",
    "# All the numbers, plus sign and space for padding.\n",
    "chars = '0123456789+ '\n",
    "ctable = CharacterTable(chars)\n",
    "\n",
    "questions = []\n",
    "expected = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Generating data...\n",
      "Total addition questions: 50000\n",
      "Vectorization...\n"
     ]
    }
   ],
   "source": [
    "seen = set()\n",
    "print('Generating data...')\n",
    "while len(questions) < TRAINING_SIZE:\n",
    "    f = lambda: int(''.join(np.random.choice(list('0123456789'))\n",
    "                    for i in range(np.random.randint(1, DIGITS + 1))))\n",
    "    a, b = f(), f()\n",
    "    \n",
    "    # Skip any addition questions we've already seen\n",
    "    # Also skip any such that x+Y == Y+x (hence the sorting).\n",
    "    key = tuple(sorted((a, b)))\n",
    "    if key in seen:\n",
    "        continue\n",
    "    \n",
    "    seen.add(key)\n",
    "    \n",
    "    # Pad the data with spaces such that it is always MAXLEN.\n",
    "    q = '{}+{}'.format(a, b)\n",
    "    query = q + ' ' * (MAXLEN - len(q))\n",
    "    ans = str(a + b)\n",
    "    \n",
    "    # Answers can be of maximum size DIGITS + 1.\n",
    "    ans += ' ' * (DIGITS + 1 - len(ans))\n",
    "    \n",
    "    if INVERT:\n",
    "        # Reverse the query, e.g., '12+345  ' becomes '  543+21'. (Note the\n",
    "        # space used for padding.)\n",
    "        query = query[::-1]\n",
    "    \n",
    "    questions.append(query)\n",
    "    expected.append(ans)\n",
    "print('Total addition questions:', len(questions))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Vectorization...\n",
      "Training Data:\n",
      "(45000, 7, 12)\n",
      "(45000, 4, 12)\n",
      "Validation Data:\n",
      "(5000, 7, 12)\n",
      "(5000, 4, 12)\n"
     ]
    }
   ],
   "source": [
    "print('Vectorization...')\n",
    "x = np.zeros((len(questions), MAXLEN, len(chars)), dtype=np.bool)\n",
    "y = np.zeros((len(questions), DIGITS + 1, len(chars)), dtype=np.bool)\n",
    "for i, sentence in enumerate(questions):\n",
    "    x[i] = ctable.encode(sentence, MAXLEN)\n",
    "for i, sentence in enumerate(expected):\n",
    "    y[i] = ctable.encode(sentence, DIGITS + 1)\n",
    "\n",
    "# Shuffle (x, y) in unison as the later parts of x will almost all be larger digits.\n",
    "indices = np.arange(len(y))\n",
    "np.random.shuffle(indices)\n",
    "x = x[indices]\n",
    "y = y[indices]\n",
    "\n",
    "# Explicitly set apart 10% for validation data that we never train over.\n",
    "split_at = len(x) - len(x) // 10\n",
    "(x_train, x_val) = x[:split_at], x[split_at:]\n",
    "(y_train, y_val) = y[:split_at], y[split_at:]\n",
    "\n",
    "print('Training Data:')\n",
    "print(x_train.shape)\n",
    "print(y_train.shape)\n",
    "\n",
    "print('Validation Data:')\n",
    "print(x_val.shape)\n",
    "print(y_val.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Build model...\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "lstm_1 (LSTM)                (None, 128)               72192     \n",
      "_________________________________________________________________\n",
      "repeat_vector_1 (RepeatVecto (None, 4, 128)            0         \n",
      "_________________________________________________________________\n",
      "lstm_2 (LSTM)                (None, 4, 128)            131584    \n",
      "_________________________________________________________________\n",
      "time_distributed_1 (TimeDist (None, 4, 12)             1548      \n",
      "_________________________________________________________________\n",
      "activation_1 (Activation)    (None, 4, 12)             0         \n",
      "=================================================================\n",
      "Total params: 205,324\n",
      "Trainable params: 205,324\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 1\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 36s - loss: 1.8867 - acc: 0.3226 - val_loss: 1.8139 - val_acc: 0.3405\n",
      "Q 560+53 \n",
      "T 613 \n",
      "\u001b[91m☒\u001b[0m 155 \n",
      "---\n",
      "Q 572+952\n",
      "T 1524\n",
      "\u001b[91m☒\u001b[0m 105 \n",
      "---\n",
      "Q 43+661 \n",
      "T 704 \n",
      "\u001b[91m☒\u001b[0m 155 \n",
      "---\n",
      "Q 607+33 \n",
      "T 640 \n",
      "\u001b[91m☒\u001b[0m 155 \n",
      "---\n",
      "Q 894+814\n",
      "T 1708\n",
      "\u001b[91m☒\u001b[0m 105 \n",
      "---\n",
      "Q 200+92 \n",
      "T 292 \n",
      "\u001b[91m☒\u001b[0m 125 \n",
      "---\n",
      "Q 93+732 \n",
      "T 825 \n",
      "\u001b[91m☒\u001b[0m 105 \n",
      "---\n",
      "Q 396+85 \n",
      "T 481 \n",
      "\u001b[91m☒\u001b[0m 105 \n",
      "---\n",
      "Q 396+865\n",
      "T 1261\n",
      "\u001b[91m☒\u001b[0m 101 \n",
      "---\n",
      "Q 13+856 \n",
      "T 869 \n",
      "\u001b[91m☒\u001b[0m 125 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 2\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 32s - loss: 1.7386 - acc: 0.3577 - val_loss: 1.6697 - val_acc: 0.3798\n",
      "Q 5+969  \n",
      "T 974 \n",
      "\u001b[91m☒\u001b[0m 104 \n",
      "---\n",
      "Q 288+86 \n",
      "T 374 \n",
      "\u001b[91m☒\u001b[0m 894 \n",
      "---\n",
      "Q 197+1  \n",
      "T 198 \n",
      "\u001b[91m☒\u001b[0m 112 \n",
      "---\n",
      "Q 975+38 \n",
      "T 1013\n",
      "\u001b[91m☒\u001b[0m 904 \n",
      "---\n",
      "Q 9+783  \n",
      "T 792 \n",
      "\u001b[91m☒\u001b[0m 904 \n",
      "---\n",
      "Q 97+80  \n",
      "T 177 \n",
      "\u001b[91m☒\u001b[0m 197 \n",
      "---\n",
      "Q 416+34 \n",
      "T 450 \n",
      "\u001b[91m☒\u001b[0m 449 \n",
      "---\n",
      "Q 385+8  \n",
      "T 393 \n",
      "\u001b[91m☒\u001b[0m 189 \n",
      "---\n",
      "Q 410+34 \n",
      "T 444 \n",
      "\u001b[91m☒\u001b[0m 449 \n",
      "---\n",
      "Q 597+364\n",
      "T 961 \n",
      "\u001b[91m☒\u001b[0m 104 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 3\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 1.5944 - acc: 0.4035 - val_loss: 1.5124 - val_acc: 0.4328\n",
      "Q 92+17  \n",
      "T 109 \n",
      "\u001b[91m☒\u001b[0m 111 \n",
      "---\n",
      "Q 63+55  \n",
      "T 118 \n",
      "\u001b[91m☒\u001b[0m 669 \n",
      "---\n",
      "Q 76+204 \n",
      "T 280 \n",
      "\u001b[91m☒\u001b[0m 371 \n",
      "---\n",
      "Q 919+78 \n",
      "T 997 \n",
      "\u001b[91m☒\u001b[0m 901 \n",
      "---\n",
      "Q 52+617 \n",
      "T 669 \n",
      "\u001b[91m☒\u001b[0m 671 \n",
      "---\n",
      "Q 806+157\n",
      "T 963 \n",
      "\u001b[91m☒\u001b[0m 101 \n",
      "---\n",
      "Q 475+5  \n",
      "T 480 \n",
      "\u001b[91m☒\u001b[0m 551 \n",
      "---\n",
      "Q 937+93 \n",
      "T 1030\n",
      "\u001b[91m☒\u001b[0m 1041\n",
      "---\n",
      "Q 118+423\n",
      "T 541 \n",
      "\u001b[91m☒\u001b[0m 796 \n",
      "---\n",
      "Q 613+47 \n",
      "T 660 \n",
      "\u001b[91m☒\u001b[0m 674 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 4\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 1.4221 - acc: 0.4697 - val_loss: 1.3347 - val_acc: 0.4982\n",
      "Q 750+47 \n",
      "T 797 \n",
      "\u001b[91m☒\u001b[0m 782 \n",
      "---\n",
      "Q 190+569\n",
      "T 759 \n",
      "\u001b[91m☒\u001b[0m 765 \n",
      "---\n",
      "Q 195+74 \n",
      "T 269 \n",
      "\u001b[91m☒\u001b[0m 255 \n",
      "---\n",
      "Q 681+860\n",
      "T 1541\n",
      "\u001b[91m☒\u001b[0m 1471\n",
      "---\n",
      "Q 675+2  \n",
      "T 677 \n",
      "\u001b[91m☒\u001b[0m 678 \n",
      "---\n",
      "Q 528+875\n",
      "T 1403\n",
      "\u001b[91m☒\u001b[0m 1311\n",
      "---\n",
      "Q 4+105  \n",
      "T 109 \n",
      "\u001b[91m☒\u001b[0m 111 \n",
      "---\n",
      "Q 60+314 \n",
      "T 374 \n",
      "\u001b[91m☒\u001b[0m 368 \n",
      "---\n",
      "Q 32+42  \n",
      "T 74  \n",
      "\u001b[91m☒\u001b[0m 37  \n",
      "---\n",
      "Q 464+7  \n",
      "T 471 \n",
      "\u001b[92m☑\u001b[0m 471 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 5\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 32s - loss: 1.2639 - acc: 0.5319 - val_loss: 1.1940 - val_acc: 0.5631\n",
      "Q 728+675\n",
      "T 1403\n",
      "\u001b[91m☒\u001b[0m 1422\n",
      "---\n",
      "Q 468+32 \n",
      "T 500 \n",
      "\u001b[91m☒\u001b[0m 499 \n",
      "---\n",
      "Q 5+718  \n",
      "T 723 \n",
      "\u001b[91m☒\u001b[0m 722 \n",
      "---\n",
      "Q 32+446 \n",
      "T 478 \n",
      "\u001b[91m☒\u001b[0m 479 \n",
      "---\n",
      "Q 0+776  \n",
      "T 776 \n",
      "\u001b[91m☒\u001b[0m 777 \n",
      "---\n",
      "Q 41+886 \n",
      "T 927 \n",
      "\u001b[91m☒\u001b[0m 999 \n",
      "---\n",
      "Q 560+39 \n",
      "T 599 \n",
      "\u001b[91m☒\u001b[0m 691 \n",
      "---\n",
      "Q 32+50  \n",
      "T 82  \n",
      "\u001b[91m☒\u001b[0m 60  \n",
      "---\n",
      "Q 595+1  \n",
      "T 596 \n",
      "\u001b[91m☒\u001b[0m 599 \n",
      "---\n",
      "Q 19+293 \n",
      "T 312 \n",
      "\u001b[91m☒\u001b[0m 219 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 6\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 32s - loss: 1.1322 - acc: 0.5852 - val_loss: 1.0745 - val_acc: 0.6079\n",
      "Q 23+800 \n",
      "T 823 \n",
      "\u001b[91m☒\u001b[0m 834 \n",
      "---\n",
      "Q 8+27   \n",
      "T 35  \n",
      "\u001b[91m☒\u001b[0m 27  \n",
      "---\n",
      "Q 894+814\n",
      "T 1708\n",
      "\u001b[91m☒\u001b[0m 1700\n",
      "---\n",
      "Q 721+88 \n",
      "T 809 \n",
      "\u001b[91m☒\u001b[0m 800 \n",
      "---\n",
      "Q 515+98 \n",
      "T 613 \n",
      "\u001b[91m☒\u001b[0m 600 \n",
      "---\n",
      "Q 314+0  \n",
      "T 314 \n",
      "\u001b[91m☒\u001b[0m 313 \n",
      "---\n",
      "Q 40+240 \n",
      "T 280 \n",
      "\u001b[91m☒\u001b[0m 362 \n",
      "---\n",
      "Q 892+396\n",
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      "\u001b[91m☒\u001b[0m 1256\n",
      "---\n",
      "Q 927+862\n",
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      "\u001b[91m☒\u001b[0m 1710\n",
      "---\n",
      "Q 119+363\n",
      "T 482 \n",
      "\u001b[91m☒\u001b[0m 502 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 7\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 1.0067 - acc: 0.6363 - val_loss: 0.9651 - val_acc: 0.6488\n",
      "Q 862+106\n",
      "T 968 \n",
      "\u001b[91m☒\u001b[0m 909 \n",
      "---\n",
      "Q 252+740\n",
      "T 992 \n",
      "\u001b[91m☒\u001b[0m 900 \n",
      "---\n",
      "Q 408+96 \n",
      "T 504 \n",
      "\u001b[91m☒\u001b[0m 596 \n",
      "---\n",
      "Q 32+19  \n",
      "T 51  \n",
      "\u001b[91m☒\u001b[0m 44  \n",
      "---\n",
      "Q 48+679 \n",
      "T 727 \n",
      "\u001b[91m☒\u001b[0m 719 \n",
      "---\n",
      "Q 5+529  \n",
      "T 534 \n",
      "\u001b[91m☒\u001b[0m 539 \n",
      "---\n",
      "Q 1+762  \n",
      "T 763 \n",
      "\u001b[91m☒\u001b[0m 764 \n",
      "---\n",
      "Q 464+5  \n",
      "T 469 \n",
      "\u001b[91m☒\u001b[0m 474 \n",
      "---\n",
      "Q 1+714  \n",
      "T 715 \n",
      "\u001b[92m☑\u001b[0m 715 \n",
      "---\n",
      "Q 178+43 \n",
      "T 221 \n",
      "\u001b[91m☒\u001b[0m 229 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 8\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 29s - loss: 0.9057 - acc: 0.6756 - val_loss: 0.8744 - val_acc: 0.6818\n",
      "Q 20+729 \n",
      "T 749 \n",
      "\u001b[91m☒\u001b[0m 759 \n",
      "---\n",
      "Q 451+37 \n",
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      "\u001b[91m☒\u001b[0m 489 \n",
      "---\n",
      "Q 48+890 \n",
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      "\u001b[91m☒\u001b[0m 939 \n",
      "---\n",
      "Q 908+456\n",
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      "\u001b[91m☒\u001b[0m 1455\n",
      "---\n",
      "Q 315+96 \n",
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      "\u001b[91m☒\u001b[0m 410 \n",
      "---\n",
      "Q 764+17 \n",
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      "\u001b[91m☒\u001b[0m 777 \n",
      "---\n",
      "Q 229+432\n",
      "T 661 \n",
      "\u001b[91m☒\u001b[0m 662 \n",
      "---\n",
      "Q 12+262 \n",
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      "\u001b[91m☒\u001b[0m 272 \n",
      "---\n",
      "Q 992+214\n",
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      "\u001b[91m☒\u001b[0m 1200\n",
      "---\n",
      "Q 38+14  \n",
      "T 52  \n",
      "\u001b[92m☑\u001b[0m 52  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 9\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 29s - loss: 0.8201 - acc: 0.7100 - val_loss: 0.8091 - val_acc: 0.7077\n",
      "Q 37+307 \n",
      "T 344 \n",
      "\u001b[91m☒\u001b[0m 341 \n",
      "---\n",
      "Q 602+12 \n",
      "T 614 \n",
      "\u001b[91m☒\u001b[0m 615 \n",
      "---\n",
      "Q 949+685\n",
      "T 1634\n",
      "\u001b[91m☒\u001b[0m 1636\n",
      "---\n",
      "Q 798+16 \n",
      "T 814 \n",
      "\u001b[91m☒\u001b[0m 810 \n",
      "---\n",
      "Q 92+901 \n",
      "T 993 \n",
      "\u001b[91m☒\u001b[0m 990 \n",
      "---\n",
      "Q 834+972\n",
      "T 1806\n",
      "\u001b[91m☒\u001b[0m 1800\n",
      "---\n",
      "Q 314+16 \n",
      "T 330 \n",
      "\u001b[92m☑\u001b[0m 330 \n",
      "---\n",
      "Q 575+22 \n",
      "T 597 \n",
      "\u001b[91m☒\u001b[0m 699 \n",
      "---\n",
      "Q 61+916 \n",
      "T 977 \n",
      "\u001b[91m☒\u001b[0m 976 \n",
      "---\n",
      "Q 289+52 \n",
      "T 341 \n",
      "\u001b[91m☒\u001b[0m 340 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 10\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.7416 - acc: 0.7404 - val_loss: 0.7110 - val_acc: 0.7510\n",
      "Q 491+1  \n",
      "T 492 \n",
      "\u001b[91m☒\u001b[0m 493 \n",
      "---\n",
      "Q 650+7  \n",
      "T 657 \n",
      "\u001b[92m☑\u001b[0m 657 \n",
      "---\n",
      "Q 505+259\n",
      "T 764 \n",
      "\u001b[91m☒\u001b[0m 756 \n",
      "---\n",
      "Q 623+296\n",
      "T 919 \n",
      "\u001b[91m☒\u001b[0m 921 \n",
      "---\n",
      "Q 602+456\n",
      "T 1058\n",
      "\u001b[91m☒\u001b[0m 1053\n",
      "---\n",
      "Q 97+954 \n",
      "T 1051\n",
      "\u001b[91m☒\u001b[0m 1046\n",
      "---\n",
      "Q 29+83  \n",
      "T 112 \n",
      "\u001b[91m☒\u001b[0m 119 \n",
      "---\n",
      "Q 667+549\n",
      "T 1216\n",
      "\u001b[91m☒\u001b[0m 1212\n",
      "---\n",
      "Q 3+752  \n",
      "T 755 \n",
      "\u001b[91m☒\u001b[0m 754 \n",
      "---\n",
      "Q 71+36  \n",
      "T 107 \n",
      "\u001b[91m☒\u001b[0m 108 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 11\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.6478 - acc: 0.7678 - val_loss: 0.5834 - val_acc: 0.7879\n",
      "Q 37+877 \n",
      "T 914 \n",
      "\u001b[91m☒\u001b[0m 918 \n",
      "---\n",
      "Q 17+767 \n",
      "T 784 \n",
      "\u001b[91m☒\u001b[0m 786 \n",
      "---\n",
      "Q 99+475 \n",
      "T 574 \n",
      "\u001b[91m☒\u001b[0m 579 \n",
      "---\n",
      "Q 51+279 \n",
      "T 330 \n",
      "\u001b[91m☒\u001b[0m 320 \n",
      "---\n",
      "Q 476+58 \n",
      "T 534 \n",
      "\u001b[92m☑\u001b[0m 534 \n",
      "---\n",
      "Q 135+53 \n",
      "T 188 \n",
      "\u001b[92m☑\u001b[0m 188 \n",
      "---\n",
      "Q 843+255\n",
      "T 1098\n",
      "\u001b[92m☑\u001b[0m 1098\n",
      "---\n",
      "Q 386+18 \n",
      "T 404 \n",
      "\u001b[92m☑\u001b[0m 404 \n",
      "---\n",
      "Q 9+120  \n",
      "T 129 \n",
      "\u001b[91m☒\u001b[0m 119 \n",
      "---\n",
      "Q 426+375\n",
      "T 801 \n",
      "\u001b[91m☒\u001b[0m 800 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 12\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 33s - loss: 0.4853 - acc: 0.8297 - val_loss: 0.4348 - val_acc: 0.8463\n",
      "Q 855+35 \n",
      "T 890 \n",
      "\u001b[92m☑\u001b[0m 890 \n",
      "---\n",
      "Q 282+4  \n",
      "T 286 \n",
      "\u001b[92m☑\u001b[0m 286 \n",
      "---\n",
      "Q 215+213\n",
      "T 428 \n",
      "\u001b[91m☒\u001b[0m 328 \n",
      "---\n",
      "Q 493+59 \n",
      "T 552 \n",
      "\u001b[91m☒\u001b[0m 551 \n",
      "---\n",
      "Q 533+543\n",
      "T 1076\n",
      "\u001b[92m☑\u001b[0m 1076\n",
      "---\n",
      "Q 589+9  \n",
      "T 598 \n",
      "\u001b[91m☒\u001b[0m 596 \n",
      "---\n",
      "Q 764+17 \n",
      "T 781 \n",
      "\u001b[91m☒\u001b[0m 782 \n",
      "---\n",
      "Q 52+44  \n",
      "T 96  \n",
      "\u001b[91m☒\u001b[0m 87  \n",
      "---\n",
      "Q 59+738 \n",
      "T 797 \n",
      "\u001b[91m☒\u001b[0m 786 \n",
      "---\n",
      "Q 927+862\n",
      "T 1789\n",
      "\u001b[91m☒\u001b[0m 1799\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 13\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 40s - loss: 0.3459 - acc: 0.8937 - val_loss: 0.3122 - val_acc: 0.9039\n",
      "Q 181+227\n",
      "T 408 \n",
      "\u001b[91m☒\u001b[0m 308 \n",
      "---\n",
      "Q 829+366\n",
      "T 1195\n",
      "\u001b[91m☒\u001b[0m 1185\n",
      "---\n",
      "Q 72+140 \n",
      "T 212 \n",
      "\u001b[92m☑\u001b[0m 212 \n",
      "---\n",
      "Q 312+211\n",
      "T 523 \n",
      "\u001b[91m☒\u001b[0m 423 \n",
      "---\n",
      "Q 3+530  \n",
      "T 533 \n",
      "\u001b[91m☒\u001b[0m 433 \n",
      "---\n",
      "Q 334+694\n",
      "T 1028\n",
      "\u001b[92m☑\u001b[0m 1028\n",
      "---\n",
      "Q 3+31   \n",
      "T 34  \n",
      "\u001b[92m☑\u001b[0m 34  \n",
      "---\n",
      "Q 64+933 \n",
      "T 997 \n",
      "\u001b[91m☒\u001b[0m 998 \n",
      "---\n",
      "Q 8+969  \n",
      "T 977 \n",
      "\u001b[92m☑\u001b[0m 977 \n",
      "---\n",
      "Q 231+244\n",
      "T 475 \n",
      "\u001b[91m☒\u001b[0m 476 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 14\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 41s - loss: 0.2491 - acc: 0.9356 - val_loss: 0.2204 - val_acc: 0.9428\n",
      "Q 237+540\n",
      "T 777 \n",
      "\u001b[91m☒\u001b[0m 776 \n",
      "---\n",
      "Q 659+513\n",
      "T 1172\n",
      "\u001b[92m☑\u001b[0m 1172\n",
      "---\n",
      "Q 16+632 \n",
      "T 648 \n",
      "\u001b[92m☑\u001b[0m 648 \n",
      "---\n",
      "Q 603+7  \n",
      "T 610 \n",
      "\u001b[91m☒\u001b[0m 600 \n",
      "---\n",
      "Q 85+582 \n",
      "T 667 \n",
      "\u001b[92m☑\u001b[0m 667 \n",
      "---\n",
      "Q 65+946 \n",
      "T 1011\n",
      "\u001b[92m☑\u001b[0m 1011\n",
      "---\n",
      "Q 359+41 \n",
      "T 400 \n",
      "\u001b[91m☒\u001b[0m 300 \n",
      "---\n",
      "Q 68+12  \n",
      "T 80  \n",
      "\u001b[91m☒\u001b[0m 70  \n",
      "---\n",
      "Q 569+48 \n",
      "T 617 \n",
      "\u001b[92m☑\u001b[0m 617 \n",
      "---\n",
      "Q 67+17  \n",
      "T 84  \n",
      "\u001b[92m☑\u001b[0m 84  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 15\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 46s - loss: 0.1786 - acc: 0.9610 - val_loss: 0.1489 - val_acc: 0.9688\n",
      "Q 221+460\n",
      "T 681 \n",
      "\u001b[92m☑\u001b[0m 681 \n",
      "---\n",
      "Q 67+50  \n",
      "T 117 \n",
      "\u001b[92m☑\u001b[0m 117 \n",
      "---\n",
      "Q 113+480\n",
      "T 593 \n",
      "\u001b[91m☒\u001b[0m 693 \n",
      "---\n",
      "Q 1+860  \n",
      "T 861 \n",
      "\u001b[92m☑\u001b[0m 861 \n",
      "---\n",
      "Q 58+733 \n",
      "T 791 \n",
      "\u001b[92m☑\u001b[0m 791 \n",
      "---\n",
      "Q 947+4  \n",
      "T 951 \n",
      "\u001b[92m☑\u001b[0m 951 \n",
      "---\n",
      "Q 525+39 \n",
      "T 564 \n",
      "\u001b[92m☑\u001b[0m 564 \n",
      "---\n",
      "Q 820+673\n",
      "T 1493\n",
      "\u001b[91m☒\u001b[0m 1593\n",
      "---\n",
      "Q 94+806 \n",
      "T 900 \n",
      "\u001b[91m☒\u001b[0m 991 \n",
      "---\n",
      "Q 14+20  \n",
      "T 34  \n",
      "\u001b[92m☑\u001b[0m 34  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 16\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 49s - loss: 0.1303 - acc: 0.9736 - val_loss: 0.1196 - val_acc: 0.9748\n",
      "Q 821+707\n",
      "T 1528\n",
      "\u001b[92m☑\u001b[0m 1528\n",
      "---\n",
      "Q 557+159\n",
      "T 716 \n",
      "\u001b[92m☑\u001b[0m 716 \n",
      "---\n",
      "Q 594+9  \n",
      "T 603 \n",
      "\u001b[92m☑\u001b[0m 603 \n",
      "---\n",
      "Q 355+13 \n",
      "T 368 \n",
      "\u001b[92m☑\u001b[0m 368 \n",
      "---\n",
      "Q 5+718  \n",
      "T 723 \n",
      "\u001b[92m☑\u001b[0m 723 \n",
      "---\n",
      "Q 539+59 \n",
      "T 598 \n",
      "\u001b[92m☑\u001b[0m 598 \n",
      "---\n",
      "Q 418+516\n",
      "T 934 \n",
      "\u001b[92m☑\u001b[0m 934 \n",
      "---\n",
      "Q 190+784\n",
      "T 974 \n",
      "\u001b[92m☑\u001b[0m 974 \n",
      "---\n",
      "Q 158+35 \n",
      "T 193 \n",
      "\u001b[92m☑\u001b[0m 193 \n",
      "---\n",
      "Q 9+52   \n",
      "T 61  \n",
      "\u001b[91m☒\u001b[0m 51  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 17\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 49s - loss: 0.0954 - acc: 0.9832 - val_loss: 0.0942 - val_acc: 0.9802\n",
      "Q 849+332\n",
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      "\u001b[92m☑\u001b[0m 1181\n",
      "---\n",
      "Q 128+554\n",
      "T 682 \n",
      "\u001b[92m☑\u001b[0m 682 \n",
      "---\n",
      "Q 163+11 \n",
      "T 174 \n",
      "\u001b[92m☑\u001b[0m 174 \n",
      "---\n",
      "Q 89+118 \n",
      "T 207 \n",
      "\u001b[92m☑\u001b[0m 207 \n",
      "---\n",
      "Q 682+392\n",
      "T 1074\n",
      "\u001b[92m☑\u001b[0m 1074\n",
      "---\n",
      "Q 56+944 \n",
      "T 1000\n",
      "\u001b[92m☑\u001b[0m 1000\n",
      "---\n",
      "Q 438+7  \n",
      "T 445 \n",
      "\u001b[92m☑\u001b[0m 445 \n",
      "---\n",
      "Q 16+997 \n",
      "T 1013\n",
      "\u001b[92m☑\u001b[0m 1013\n",
      "---\n",
      "Q 162+3  \n",
      "T 165 \n",
      "\u001b[92m☑\u001b[0m 165 \n",
      "---\n",
      "Q 74+400 \n",
      "T 474 \n",
      "\u001b[92m☑\u001b[0m 474 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 18\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 50s - loss: 0.0861 - acc: 0.9823 - val_loss: 0.0737 - val_acc: 0.9859\n",
      "Q 6+646  \n",
      "T 652 \n",
      "\u001b[92m☑\u001b[0m 652 \n",
      "---\n",
      "Q 519+73 \n",
      "T 592 \n",
      "\u001b[92m☑\u001b[0m 592 \n",
      "---\n",
      "Q 85+506 \n",
      "T 591 \n",
      "\u001b[92m☑\u001b[0m 591 \n",
      "---\n",
      "Q 67+18  \n",
      "T 85  \n",
      "\u001b[92m☑\u001b[0m 85  \n",
      "---\n",
      "Q 809+160\n",
      "T 969 \n",
      "\u001b[91m☒\u001b[0m 979 \n",
      "---\n",
      "Q 57+396 \n",
      "T 453 \n",
      "\u001b[92m☑\u001b[0m 453 \n",
      "---\n",
      "Q 797+545\n",
      "T 1342\n",
      "\u001b[92m☑\u001b[0m 1342\n",
      "---\n",
      "Q 870+741\n",
      "T 1611\n",
      "\u001b[92m☑\u001b[0m 1611\n",
      "---\n",
      "Q 673+777\n",
      "T 1450\n",
      "\u001b[92m☑\u001b[0m 1450\n",
      "---\n",
      "Q 42+292 \n",
      "T 334 \n",
      "\u001b[92m☑\u001b[0m 334 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 19\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 50s - loss: 0.0609 - acc: 0.9903 - val_loss: 0.0592 - val_acc: 0.9896\n",
      "Q 746+41 \n",
      "T 787 \n",
      "\u001b[92m☑\u001b[0m 787 \n",
      "---\n",
      "Q 140+73 \n",
      "T 213 \n",
      "\u001b[92m☑\u001b[0m 213 \n",
      "---\n",
      "Q 91+28  \n",
      "T 119 \n",
      "\u001b[92m☑\u001b[0m 119 \n",
      "---\n",
      "Q 14+20  \n",
      "T 34  \n",
      "\u001b[92m☑\u001b[0m 34  \n",
      "---\n",
      "Q 477+426\n",
      "T 903 \n",
      "\u001b[92m☑\u001b[0m 903 \n",
      "---\n",
      "Q 575+46 \n",
      "T 621 \n",
      "\u001b[92m☑\u001b[0m 621 \n",
      "---\n",
      "Q 48+34  \n",
      "T 82  \n",
      "\u001b[92m☑\u001b[0m 82  \n",
      "---\n",
      "Q 736+77 \n",
      "T 813 \n",
      "\u001b[92m☑\u001b[0m 813 \n",
      "---\n",
      "Q 283+7  \n",
      "T 290 \n",
      "\u001b[92m☑\u001b[0m 290 \n",
      "---\n",
      "Q 333+276\n",
      "T 609 \n",
      "\u001b[91m☒\u001b[0m 509 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 20\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 48s - loss: 0.0734 - acc: 0.9828 - val_loss: 0.0674 - val_acc: 0.9841\n",
      "Q 51+810 \n",
      "T 861 \n",
      "\u001b[92m☑\u001b[0m 861 \n",
      "---\n",
      "Q 207+86 \n",
      "T 293 \n",
      "\u001b[92m☑\u001b[0m 293 \n",
      "---\n",
      "Q 4+671  \n",
      "T 675 \n",
      "\u001b[92m☑\u001b[0m 675 \n",
      "---\n",
      "Q 138+939\n",
      "T 1077\n",
      "\u001b[92m☑\u001b[0m 1077\n",
      "---\n",
      "Q 797+587\n",
      "T 1384\n",
      "\u001b[92m☑\u001b[0m 1384\n",
      "---\n",
      "Q 73+967 \n",
      "T 1040\n",
      "\u001b[92m☑\u001b[0m 1040\n",
      "---\n",
      "Q 49+19  \n",
      "T 68  \n",
      "\u001b[91m☒\u001b[0m 58  \n",
      "---\n",
      "Q 135+486\n",
      "T 621 \n",
      "\u001b[92m☑\u001b[0m 621 \n",
      "---\n",
      "Q 718+623\n",
      "T 1341\n",
      "\u001b[92m☑\u001b[0m 1341\n",
      "---\n",
      "Q 12+600 \n",
      "T 612 \n",
      "\u001b[92m☑\u001b[0m 612 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 21\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 32s - loss: 0.0517 - acc: 0.9899 - val_loss: 0.0930 - val_acc: 0.9689\n",
      "Q 98+224 \n",
      "T 322 \n",
      "\u001b[92m☑\u001b[0m 322 \n",
      "---\n",
      "Q 68+29  \n",
      "T 97  \n",
      "\u001b[92m☑\u001b[0m 97  \n",
      "---\n",
      "Q 39+288 \n",
      "T 327 \n",
      "\u001b[92m☑\u001b[0m 327 \n",
      "---\n",
      "Q 3+707  \n",
      "T 710 \n",
      "\u001b[92m☑\u001b[0m 710 \n",
      "---\n",
      "Q 68+29  \n",
      "T 97  \n",
      "\u001b[92m☑\u001b[0m 97  \n",
      "---\n",
      "Q 91+633 \n",
      "T 724 \n",
      "\u001b[92m☑\u001b[0m 724 \n",
      "---\n",
      "Q 952+31 \n",
      "T 983 \n",
      "\u001b[92m☑\u001b[0m 983 \n",
      "---\n",
      "Q 162+287\n",
      "T 449 \n",
      "\u001b[92m☑\u001b[0m 449 \n",
      "---\n",
      "Q 692+796\n",
      "T 1488\n",
      "\u001b[91m☒\u001b[0m 1588\n",
      "---\n",
      "Q 3+609  \n",
      "T 612 \n",
      "\u001b[92m☑\u001b[0m 612 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 22\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 33s - loss: 0.0412 - acc: 0.9927 - val_loss: 0.0392 - val_acc: 0.9922\n",
      "Q 624+598\n",
      "T 1222\n",
      "\u001b[92m☑\u001b[0m 1222\n",
      "---\n",
      "Q 889+26 \n",
      "T 915 \n",
      "\u001b[92m☑\u001b[0m 915 \n",
      "---\n",
      "Q 10+69  \n",
      "T 79  \n",
      "\u001b[92m☑\u001b[0m 79  \n",
      "---\n",
      "Q 959+16 \n",
      "T 975 \n",
      "\u001b[92m☑\u001b[0m 975 \n",
      "---\n",
      "Q 650+7  \n",
      "T 657 \n",
      "\u001b[92m☑\u001b[0m 657 \n",
      "---\n",
      "Q 333+829\n",
      "T 1162\n",
      "\u001b[92m☑\u001b[0m 1162\n",
      "---\n",
      "Q 185+820\n",
      "T 1005\n",
      "\u001b[91m☒\u001b[0m 9005\n",
      "---\n",
      "Q 221+66 \n",
      "T 287 \n",
      "\u001b[92m☑\u001b[0m 287 \n",
      "---\n",
      "Q 317+8  \n",
      "T 325 \n",
      "\u001b[92m☑\u001b[0m 325 \n",
      "---\n",
      "Q 395+786\n",
      "T 1181\n",
      "\u001b[92m☑\u001b[0m 1181\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 23\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0310 - acc: 0.9955 - val_loss: 0.0412 - val_acc: 0.9903\n",
      "Q 7+120  \n",
      "T 127 \n",
      "\u001b[91m☒\u001b[0m 137 \n",
      "---\n",
      "Q 828+776\n",
      "T 1604\n",
      "\u001b[92m☑\u001b[0m 1604\n",
      "---\n",
      "Q 357+290\n",
      "T 647 \n",
      "\u001b[92m☑\u001b[0m 647 \n",
      "---\n",
      "Q 18+102 \n",
      "T 120 \n",
      "\u001b[92m☑\u001b[0m 120 \n",
      "---\n",
      "Q 73+796 \n",
      "T 869 \n",
      "\u001b[92m☑\u001b[0m 869 \n",
      "---\n",
      "Q 143+182\n",
      "T 325 \n",
      "\u001b[92m☑\u001b[0m 325 \n",
      "---\n",
      "Q 0+177  \n",
      "T 177 \n",
      "\u001b[92m☑\u001b[0m 177 \n",
      "---\n",
      "Q 820+36 \n",
      "T 856 \n",
      "\u001b[92m☑\u001b[0m 856 \n",
      "---\n",
      "Q 32+267 \n",
      "T 299 \n",
      "\u001b[92m☑\u001b[0m 299 \n",
      "---\n",
      "Q 309+120\n",
      "T 429 \n",
      "\u001b[92m☑\u001b[0m 429 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 24\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0406 - acc: 0.9907 - val_loss: 0.0426 - val_acc: 0.9897\n",
      "Q 28+48  \n",
      "T 76  \n",
      "\u001b[92m☑\u001b[0m 76  \n",
      "---\n",
      "Q 97+770 \n",
      "T 867 \n",
      "\u001b[92m☑\u001b[0m 867 \n",
      "---\n",
      "Q 19+881 \n",
      "T 900 \n",
      "\u001b[92m☑\u001b[0m 900 \n",
      "---\n",
      "Q 221+460\n",
      "T 681 \n",
      "\u001b[92m☑\u001b[0m 681 \n",
      "---\n",
      "Q 67+469 \n",
      "T 536 \n",
      "\u001b[92m☑\u001b[0m 536 \n",
      "---\n",
      "Q 0+871  \n",
      "T 871 \n",
      "\u001b[92m☑\u001b[0m 871 \n",
      "---\n",
      "Q 936+12 \n",
      "T 948 \n",
      "\u001b[92m☑\u001b[0m 948 \n",
      "---\n",
      "Q 74+925 \n",
      "T 999 \n",
      "\u001b[92m☑\u001b[0m 999 \n",
      "---\n",
      "Q 566+389\n",
      "T 955 \n",
      "\u001b[92m☑\u001b[0m 955 \n",
      "---\n",
      "Q 53+937 \n",
      "T 990 \n",
      "\u001b[92m☑\u001b[0m 990 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 25\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0218 - acc: 0.9972 - val_loss: 0.0228 - val_acc: 0.9969\n",
      "Q 867+803\n",
      "T 1670\n",
      "\u001b[92m☑\u001b[0m 1670\n",
      "---\n",
      "Q 40+245 \n",
      "T 285 \n",
      "\u001b[92m☑\u001b[0m 285 \n",
      "---\n",
      "Q 417+259\n",
      "T 676 \n",
      "\u001b[92m☑\u001b[0m 676 \n",
      "---\n",
      "Q 852+9  \n",
      "T 861 \n",
      "\u001b[92m☑\u001b[0m 861 \n",
      "---\n",
      "Q 663+469\n",
      "T 1132\n",
      "\u001b[92m☑\u001b[0m 1132\n",
      "---\n",
      "Q 66+58  \n",
      "T 124 \n",
      "\u001b[92m☑\u001b[0m 124 \n",
      "---\n",
      "Q 113+51 \n",
      "T 164 \n",
      "\u001b[92m☑\u001b[0m 164 \n",
      "---\n",
      "Q 967+927\n",
      "T 1894\n",
      "\u001b[92m☑\u001b[0m 1894\n",
      "---\n",
      "Q 0+602  \n",
      "T 602 \n",
      "\u001b[92m☑\u001b[0m 602 \n",
      "---\n",
      "Q 221+84 \n",
      "T 305 \n",
      "\u001b[92m☑\u001b[0m 305 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 26\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0180 - acc: 0.9979 - val_loss: 0.0231 - val_acc: 0.9949\n",
      "Q 670+88 \n",
      "T 758 \n",
      "\u001b[92m☑\u001b[0m 758 \n",
      "---\n",
      "Q 510+25 \n",
      "T 535 \n",
      "\u001b[92m☑\u001b[0m 535 \n",
      "---\n",
      "Q 622+86 \n",
      "T 708 \n",
      "\u001b[92m☑\u001b[0m 708 \n",
      "---\n",
      "Q 3+887  \n",
      "T 890 \n",
      "\u001b[92m☑\u001b[0m 890 \n",
      "---\n",
      "Q 240+11 \n",
      "T 251 \n",
      "\u001b[92m☑\u001b[0m 251 \n",
      "---\n",
      "Q 71+2   \n",
      "T 73  \n",
      "\u001b[92m☑\u001b[0m 73  \n",
      "---\n",
      "Q 371+24 \n",
      "T 395 \n",
      "\u001b[92m☑\u001b[0m 395 \n",
      "---\n",
      "Q 1+293  \n",
      "T 294 \n",
      "\u001b[92m☑\u001b[0m 294 \n",
      "---\n",
      "Q 3+908  \n",
      "T 911 \n",
      "\u001b[92m☑\u001b[0m 911 \n",
      "---\n",
      "Q 79+151 \n",
      "T 230 \n",
      "\u001b[92m☑\u001b[0m 230 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 27\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 31s - loss: 0.0489 - acc: 0.9864 - val_loss: 0.0233 - val_acc: 0.9952\n",
      "Q 661+5  \n",
      "T 666 \n",
      "\u001b[92m☑\u001b[0m 666 \n",
      "---\n",
      "Q 201+58 \n",
      "T 259 \n",
      "\u001b[92m☑\u001b[0m 259 \n",
      "---\n",
      "Q 985+905\n",
      "T 1890\n",
      "\u001b[92m☑\u001b[0m 1890\n",
      "---\n",
      "Q 94+17  \n",
      "T 111 \n",
      "\u001b[92m☑\u001b[0m 111 \n",
      "---\n",
      "Q 531+79 \n",
      "T 610 \n",
      "\u001b[92m☑\u001b[0m 610 \n",
      "---\n",
      "Q 45+759 \n",
      "T 804 \n",
      "\u001b[92m☑\u001b[0m 804 \n",
      "---\n",
      "Q 30+481 \n",
      "T 511 \n",
      "\u001b[92m☑\u001b[0m 511 \n",
      "---\n",
      "Q 895+8  \n",
      "T 903 \n",
      "\u001b[92m☑\u001b[0m 903 \n",
      "---\n",
      "Q 315+835\n",
      "T 1150\n",
      "\u001b[92m☑\u001b[0m 1150\n",
      "---\n",
      "Q 645+6  \n",
      "T 651 \n",
      "\u001b[92m☑\u001b[0m 651 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 28\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0126 - acc: 0.9990 - val_loss: 0.0179 - val_acc: 0.9968\n",
      "Q 371+24 \n",
      "T 395 \n",
      "\u001b[92m☑\u001b[0m 395 \n",
      "---\n",
      "Q 188+83 \n",
      "T 271 \n",
      "\u001b[92m☑\u001b[0m 271 \n",
      "---\n",
      "Q 61+916 \n",
      "T 977 \n",
      "\u001b[92m☑\u001b[0m 977 \n",
      "---\n",
      "Q 904+854\n",
      "T 1758\n",
      "\u001b[92m☑\u001b[0m 1758\n",
      "---\n",
      "Q 629+530\n",
      "T 1159\n",
      "\u001b[92m☑\u001b[0m 1159\n",
      "---\n",
      "Q 662+765\n",
      "T 1427\n",
      "\u001b[92m☑\u001b[0m 1427\n",
      "---\n",
      "Q 981+225\n",
      "T 1206\n",
      "\u001b[92m☑\u001b[0m 1206\n",
      "---\n",
      "Q 568+7  \n",
      "T 575 \n",
      "\u001b[92m☑\u001b[0m 575 \n",
      "---\n",
      "Q 829+68 \n",
      "T 897 \n",
      "\u001b[92m☑\u001b[0m 897 \n",
      "---\n",
      "Q 258+9  \n",
      "T 267 \n",
      "\u001b[92m☑\u001b[0m 267 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 29\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 29s - loss: 0.0187 - acc: 0.9962 - val_loss: 0.0305 - val_acc: 0.9922\n",
      "Q 143+194\n",
      "T 337 \n",
      "\u001b[92m☑\u001b[0m 337 \n",
      "---\n",
      "Q 945+1  \n",
      "T 946 \n",
      "\u001b[92m☑\u001b[0m 946 \n",
      "---\n",
      "Q 72+341 \n",
      "T 413 \n",
      "\u001b[92m☑\u001b[0m 413 \n",
      "---\n",
      "Q 655+680\n",
      "T 1335\n",
      "\u001b[92m☑\u001b[0m 1335\n",
      "---\n",
      "Q 249+2  \n",
      "T 251 \n",
      "\u001b[92m☑\u001b[0m 251 \n",
      "---\n",
      "Q 402+209\n",
      "T 611 \n",
      "\u001b[92m☑\u001b[0m 611 \n",
      "---\n",
      "Q 99+94  \n",
      "T 193 \n",
      "\u001b[92m☑\u001b[0m 193 \n",
      "---\n",
      "Q 225+99 \n",
      "T 324 \n",
      "\u001b[92m☑\u001b[0m 324 \n",
      "---\n",
      "Q 4+753  \n",
      "T 757 \n",
      "\u001b[92m☑\u001b[0m 757 \n",
      "---\n",
      "Q 25+344 \n",
      "T 369 \n",
      "\u001b[92m☑\u001b[0m 369 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 30\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0418 - acc: 0.9880 - val_loss: 0.0308 - val_acc: 0.9916\n",
      "Q 353+47 \n",
      "T 400 \n",
      "\u001b[92m☑\u001b[0m 400 \n",
      "---\n",
      "Q 50+517 \n",
      "T 567 \n",
      "\u001b[92m☑\u001b[0m 567 \n",
      "---\n",
      "Q 75+5   \n",
      "T 80  \n",
      "\u001b[92m☑\u001b[0m 80  \n",
      "---\n",
      "Q 902+6  \n",
      "T 908 \n",
      "\u001b[92m☑\u001b[0m 908 \n",
      "---\n",
      "Q 2+889  \n",
      "T 891 \n",
      "\u001b[92m☑\u001b[0m 891 \n",
      "---\n",
      "Q 799+940\n",
      "T 1739\n",
      "\u001b[91m☒\u001b[0m 1749\n",
      "---\n",
      "Q 352+802\n",
      "T 1154\n",
      "\u001b[92m☑\u001b[0m 1154\n",
      "---\n",
      "Q 57+583 \n",
      "T 640 \n",
      "\u001b[92m☑\u001b[0m 640 \n",
      "---\n",
      "Q 9+858  \n",
      "T 867 \n",
      "\u001b[92m☑\u001b[0m 867 \n",
      "---\n",
      "Q 969+262\n",
      "T 1231\n",
      "\u001b[92m☑\u001b[0m 1231\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 31\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0109 - acc: 0.9989 - val_loss: 0.0126 - val_acc: 0.9980\n",
      "Q 190+569\n",
      "T 759 \n",
      "\u001b[92m☑\u001b[0m 759 \n",
      "---\n",
      "Q 44+359 \n",
      "T 403 \n",
      "\u001b[92m☑\u001b[0m 403 \n",
      "---\n",
      "Q 845+0  \n",
      "T 845 \n",
      "\u001b[92m☑\u001b[0m 845 \n",
      "---\n",
      "Q 236+9  \n",
      "T 245 \n",
      "\u001b[92m☑\u001b[0m 245 \n",
      "---\n",
      "Q 23+249 \n",
      "T 272 \n",
      "\u001b[92m☑\u001b[0m 272 \n",
      "---\n",
      "Q 117+550\n",
      "T 667 \n",
      "\u001b[92m☑\u001b[0m 667 \n",
      "---\n",
      "Q 661+63 \n",
      "T 724 \n",
      "\u001b[92m☑\u001b[0m 724 \n",
      "---\n",
      "Q 738+465\n",
      "T 1203\n",
      "\u001b[92m☑\u001b[0m 1203\n",
      "---\n",
      "Q 92+750 \n",
      "T 842 \n",
      "\u001b[92m☑\u001b[0m 842 \n",
      "---\n",
      "Q 787+99 \n",
      "T 886 \n",
      "\u001b[92m☑\u001b[0m 886 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 32\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0084 - acc: 0.9992 - val_loss: 0.0184 - val_acc: 0.9956\n",
      "Q 79+842 \n",
      "T 921 \n",
      "\u001b[92m☑\u001b[0m 921 \n",
      "---\n",
      "Q 99+94  \n",
      "T 193 \n",
      "\u001b[92m☑\u001b[0m 193 \n",
      "---\n",
      "Q 746+41 \n",
      "T 787 \n",
      "\u001b[92m☑\u001b[0m 787 \n",
      "---\n",
      "Q 941+64 \n",
      "T 1005\n",
      "\u001b[92m☑\u001b[0m 1005\n",
      "---\n",
      "Q 1+639  \n",
      "T 640 \n",
      "\u001b[92m☑\u001b[0m 640 \n",
      "---\n",
      "Q 68+65  \n",
      "T 133 \n",
      "\u001b[92m☑\u001b[0m 133 \n",
      "---\n",
      "Q 57+390 \n",
      "T 447 \n",
      "\u001b[92m☑\u001b[0m 447 \n",
      "---\n",
      "Q 559+805\n",
      "T 1364\n",
      "\u001b[92m☑\u001b[0m 1364\n",
      "---\n",
      "Q 256+70 \n",
      "T 326 \n",
      "\u001b[92m☑\u001b[0m 326 \n",
      "---\n",
      "Q 775+975\n",
      "T 1750\n",
      "\u001b[92m☑\u001b[0m 1750\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 33\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0285 - acc: 0.9919 - val_loss: 0.1233 - val_acc: 0.9611\n",
      "Q 80+139 \n",
      "T 219 \n",
      "\u001b[92m☑\u001b[0m 219 \n",
      "---\n",
      "Q 59+738 \n",
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      "\u001b[92m☑\u001b[0m 797 \n",
      "---\n",
      "Q 62+329 \n",
      "T 391 \n",
      "\u001b[92m☑\u001b[0m 391 \n",
      "---\n",
      "Q 799+55 \n",
      "T 854 \n",
      "\u001b[91m☒\u001b[0m 844 \n",
      "---\n",
      "Q 178+851\n",
      "T 1029\n",
      "\u001b[92m☑\u001b[0m 1029\n",
      "---\n",
      "Q 15+119 \n",
      "T 134 \n",
      "\u001b[92m☑\u001b[0m 134 \n",
      "---\n",
      "Q 352+240\n",
      "T 592 \n",
      "\u001b[92m☑\u001b[0m 592 \n",
      "---\n",
      "Q 696+618\n",
      "T 1314\n",
      "\u001b[92m☑\u001b[0m 1314\n",
      "---\n",
      "Q 480+804\n",
      "T 1284\n",
      "\u001b[92m☑\u001b[0m 1284\n",
      "---\n",
      "Q 819+182\n",
      "T 1001\n",
      "\u001b[92m☑\u001b[0m 1001\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 34\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0235 - acc: 0.9939 - val_loss: 0.0112 - val_acc: 0.9979\n",
      "Q 3+970  \n",
      "T 973 \n",
      "\u001b[92m☑\u001b[0m 973 \n",
      "---\n",
      "Q 6+690  \n",
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      "\u001b[92m☑\u001b[0m 696 \n",
      "---\n",
      "Q 20+12  \n",
      "T 32  \n",
      "\u001b[92m☑\u001b[0m 32  \n",
      "---\n",
      "Q 67+333 \n",
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      "\u001b[92m☑\u001b[0m 400 \n",
      "---\n",
      "Q 630+543\n",
      "T 1173\n",
      "\u001b[92m☑\u001b[0m 1173\n",
      "---\n",
      "Q 205+2  \n",
      "T 207 \n",
      "\u001b[92m☑\u001b[0m 207 \n",
      "---\n",
      "Q 618+39 \n",
      "T 657 \n",
      "\u001b[92m☑\u001b[0m 657 \n",
      "---\n",
      "Q 184+739\n",
      "T 923 \n",
      "\u001b[92m☑\u001b[0m 923 \n",
      "---\n",
      "Q 188+832\n",
      "T 1020\n",
      "\u001b[92m☑\u001b[0m 1020\n",
      "---\n",
      "Q 12+121 \n",
      "T 133 \n",
      "\u001b[92m☑\u001b[0m 133 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 35\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0057 - acc: 0.9996 - val_loss: 0.0091 - val_acc: 0.9982\n",
      "Q 205+60 \n",
      "T 265 \n",
      "\u001b[92m☑\u001b[0m 265 \n",
      "---\n",
      "Q 589+83 \n",
      "T 672 \n",
      "\u001b[92m☑\u001b[0m 672 \n",
      "---\n",
      "Q 31+211 \n",
      "T 242 \n",
      "\u001b[92m☑\u001b[0m 242 \n",
      "---\n",
      "Q 1+274  \n",
      "T 275 \n",
      "\u001b[92m☑\u001b[0m 275 \n",
      "---\n",
      "Q 151+74 \n",
      "T 225 \n",
      "\u001b[92m☑\u001b[0m 225 \n",
      "---\n",
      "Q 48+452 \n",
      "T 500 \n",
      "\u001b[92m☑\u001b[0m 500 \n",
      "---\n",
      "Q 92+480 \n",
      "T 572 \n",
      "\u001b[92m☑\u001b[0m 572 \n",
      "---\n",
      "Q 551+55 \n",
      "T 606 \n",
      "\u001b[92m☑\u001b[0m 606 \n",
      "---\n",
      "Q 755+71 \n",
      "T 826 \n",
      "\u001b[92m☑\u001b[0m 826 \n",
      "---\n",
      "Q 207+396\n",
      "T 603 \n",
      "\u001b[92m☑\u001b[0m 603 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 36\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0048 - acc: 0.9998 - val_loss: 0.0085 - val_acc: 0.9986\n",
      "Q 237+540\n",
      "T 777 \n",
      "\u001b[92m☑\u001b[0m 777 \n",
      "---\n",
      "Q 92+878 \n",
      "T 970 \n",
      "\u001b[92m☑\u001b[0m 970 \n",
      "---\n",
      "Q 20+901 \n",
      "T 921 \n",
      "\u001b[92m☑\u001b[0m 921 \n",
      "---\n",
      "Q 3+765  \n",
      "T 768 \n",
      "\u001b[92m☑\u001b[0m 768 \n",
      "---\n",
      "Q 4+899  \n",
      "T 903 \n",
      "\u001b[92m☑\u001b[0m 903 \n",
      "---\n",
      "Q 62+248 \n",
      "T 310 \n",
      "\u001b[92m☑\u001b[0m 310 \n",
      "---\n",
      "Q 751+17 \n",
      "T 768 \n",
      "\u001b[92m☑\u001b[0m 768 \n",
      "---\n",
      "Q 19+881 \n",
      "T 900 \n",
      "\u001b[92m☑\u001b[0m 900 \n",
      "---\n",
      "Q 846+388\n",
      "T 1234\n",
      "\u001b[92m☑\u001b[0m 1234\n",
      "---\n",
      "Q 97+999 \n",
      "T 1096\n",
      "\u001b[92m☑\u001b[0m 1096\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 37\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 32s - loss: 0.0182 - acc: 0.9951 - val_loss: 0.1158 - val_acc: 0.9597\n",
      "Q 273+98 \n",
      "T 371 \n",
      "\u001b[92m☑\u001b[0m 371 \n",
      "---\n",
      "Q 787+76 \n",
      "T 863 \n",
      "\u001b[92m☑\u001b[0m 863 \n",
      "---\n",
      "Q 598+7  \n",
      "T 605 \n",
      "\u001b[92m☑\u001b[0m 605 \n",
      "---\n",
      "Q 143+1  \n",
      "T 144 \n",
      "\u001b[92m☑\u001b[0m 144 \n",
      "---\n",
      "Q 140+73 \n",
      "T 213 \n",
      "\u001b[92m☑\u001b[0m 213 \n",
      "---\n",
      "Q 94+68  \n",
      "T 162 \n",
      "\u001b[92m☑\u001b[0m 162 \n",
      "---\n",
      "Q 184+739\n",
      "T 923 \n",
      "\u001b[92m☑\u001b[0m 923 \n",
      "---\n",
      "Q 175+16 \n",
      "T 191 \n",
      "\u001b[92m☑\u001b[0m 191 \n",
      "---\n",
      "Q 21+89  \n",
      "T 110 \n",
      "\u001b[92m☑\u001b[0m 110 \n",
      "---\n",
      "Q 31+496 \n",
      "T 527 \n",
      "\u001b[92m☑\u001b[0m 527 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 38\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0273 - acc: 0.9923 - val_loss: 0.0110 - val_acc: 0.9976\n",
      "Q 5+128  \n",
      "T 133 \n",
      "\u001b[92m☑\u001b[0m 133 \n",
      "---\n",
      "Q 174+15 \n",
      "T 189 \n",
      "\u001b[92m☑\u001b[0m 189 \n",
      "---\n",
      "Q 231+51 \n",
      "T 282 \n",
      "\u001b[92m☑\u001b[0m 282 \n",
      "---\n",
      "Q 994+506\n",
      "T 1500\n",
      "\u001b[92m☑\u001b[0m 1500\n",
      "---\n",
      "Q 360+157\n",
      "T 517 \n",
      "\u001b[92m☑\u001b[0m 517 \n",
      "---\n",
      "Q 444+640\n",
      "T 1084\n",
      "\u001b[92m☑\u001b[0m 1084\n",
      "---\n",
      "Q 996+810\n",
      "T 1806\n",
      "\u001b[92m☑\u001b[0m 1806\n",
      "---\n",
      "Q 43+5   \n",
      "T 48  \n",
      "\u001b[92m☑\u001b[0m 48  \n",
      "---\n",
      "Q 28+807 \n",
      "T 835 \n",
      "\u001b[92m☑\u001b[0m 835 \n",
      "---\n",
      "Q 358+923\n",
      "T 1281\n",
      "\u001b[92m☑\u001b[0m 1281\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 39\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0043 - acc: 0.9998 - val_loss: 0.0066 - val_acc: 0.9990\n",
      "Q 205+2  \n",
      "T 207 \n",
      "\u001b[92m☑\u001b[0m 207 \n",
      "---\n",
      "Q 847+913\n",
      "T 1760\n",
      "\u001b[92m☑\u001b[0m 1760\n",
      "---\n",
      "Q 88+303 \n",
      "T 391 \n",
      "\u001b[92m☑\u001b[0m 391 \n",
      "---\n",
      "Q 34+1   \n",
      "T 35  \n",
      "\u001b[92m☑\u001b[0m 35  \n",
      "---\n",
      "Q 423+135\n",
      "T 558 \n",
      "\u001b[92m☑\u001b[0m 558 \n",
      "---\n",
      "Q 733+3  \n",
      "T 736 \n",
      "\u001b[92m☑\u001b[0m 736 \n",
      "---\n",
      "Q 65+721 \n",
      "T 786 \n",
      "\u001b[92m☑\u001b[0m 786 \n",
      "---\n",
      "Q 118+137\n",
      "T 255 \n",
      "\u001b[92m☑\u001b[0m 255 \n",
      "---\n",
      "Q 34+65  \n",
      "T 99  \n",
      "\u001b[92m☑\u001b[0m 99  \n",
      "---\n",
      "Q 845+411\n",
      "T 1256\n",
      "\u001b[92m☑\u001b[0m 1256\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 40\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0032 - acc: 0.9999 - val_loss: 0.0062 - val_acc: 0.9991\n",
      "Q 160+416\n",
      "T 576 \n",
      "\u001b[92m☑\u001b[0m 576 \n",
      "---\n",
      "Q 314+25 \n",
      "T 339 \n",
      "\u001b[92m☑\u001b[0m 339 \n",
      "---\n",
      "Q 7+970  \n",
      "T 977 \n",
      "\u001b[92m☑\u001b[0m 977 \n",
      "---\n",
      "Q 72+24  \n",
      "T 96  \n",
      "\u001b[92m☑\u001b[0m 96  \n",
      "---\n",
      "Q 86+840 \n",
      "T 926 \n",
      "\u001b[92m☑\u001b[0m 926 \n",
      "---\n",
      "Q 9+505  \n",
      "T 514 \n",
      "\u001b[92m☑\u001b[0m 514 \n",
      "---\n",
      "Q 1+891  \n",
      "T 892 \n",
      "\u001b[92m☑\u001b[0m 892 \n",
      "---\n",
      "Q 763+15 \n",
      "T 778 \n",
      "\u001b[92m☑\u001b[0m 778 \n",
      "---\n",
      "Q 61+88  \n",
      "T 149 \n",
      "\u001b[92m☑\u001b[0m 149 \n",
      "---\n",
      "Q 220+319\n",
      "T 539 \n",
      "\u001b[92m☑\u001b[0m 539 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 41\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 31s - loss: 0.0029 - acc: 0.9999 - val_loss: 0.0062 - val_acc: 0.9990\n",
      "Q 408+511\n",
      "T 919 \n",
      "\u001b[92m☑\u001b[0m 919 \n",
      "---\n",
      "Q 6+133  \n",
      "T 139 \n",
      "\u001b[92m☑\u001b[0m 139 \n",
      "---\n",
      "Q 30+204 \n",
      "T 234 \n",
      "\u001b[92m☑\u001b[0m 234 \n",
      "---\n",
      "Q 140+386\n",
      "T 526 \n",
      "\u001b[92m☑\u001b[0m 526 \n",
      "---\n",
      "Q 84+19  \n",
      "T 103 \n",
      "\u001b[92m☑\u001b[0m 103 \n",
      "---\n",
      "Q 96+595 \n",
      "T 691 \n",
      "\u001b[92m☑\u001b[0m 691 \n",
      "---\n",
      "Q 40+729 \n",
      "T 769 \n",
      "\u001b[92m☑\u001b[0m 769 \n",
      "---\n",
      "Q 40+69  \n",
      "T 109 \n",
      "\u001b[92m☑\u001b[0m 109 \n",
      "---\n",
      "Q 238+39 \n",
      "T 277 \n",
      "\u001b[92m☑\u001b[0m 277 \n",
      "---\n",
      "Q 841+225\n",
      "T 1066\n",
      "\u001b[92m☑\u001b[0m 1066\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 42\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0292 - acc: 0.9915 - val_loss: 0.1390 - val_acc: 0.9573\n",
      "Q 158+35 \n",
      "T 193 \n",
      "\u001b[92m☑\u001b[0m 193 \n",
      "---\n",
      "Q 935+12 \n",
      "T 947 \n",
      "\u001b[92m☑\u001b[0m 947 \n",
      "---\n",
      "Q 556+0  \n",
      "T 556 \n",
      "\u001b[92m☑\u001b[0m 556 \n",
      "---\n",
      "Q 590+237\n",
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      "\u001b[92m☑\u001b[0m 827 \n",
      "---\n",
      "Q 487+230\n",
      "T 717 \n",
      "\u001b[92m☑\u001b[0m 717 \n",
      "---\n",
      "Q 16+656 \n",
      "T 672 \n",
      "\u001b[92m☑\u001b[0m 672 \n",
      "---\n",
      "Q 80+64  \n",
      "T 144 \n",
      "\u001b[92m☑\u001b[0m 144 \n",
      "---\n",
      "Q 449+902\n",
      "T 1351\n",
      "\u001b[92m☑\u001b[0m 1351\n",
      "---\n",
      "Q 989+742\n",
      "T 1731\n",
      "\u001b[91m☒\u001b[0m 1721\n",
      "---\n",
      "Q 19+862 \n",
      "T 881 \n",
      "\u001b[92m☑\u001b[0m 881 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 43\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0205 - acc: 0.9941 - val_loss: 0.0164 - val_acc: 0.9954\n",
      "Q 725+789\n",
      "T 1514\n",
      "\u001b[92m☑\u001b[0m 1514\n",
      "---\n",
      "Q 563+18 \n",
      "T 581 \n",
      "\u001b[92m☑\u001b[0m 581 \n",
      "---\n",
      "Q 1+274  \n",
      "T 275 \n",
      "\u001b[92m☑\u001b[0m 275 \n",
      "---\n",
      "Q 190+138\n",
      "T 328 \n",
      "\u001b[92m☑\u001b[0m 328 \n",
      "---\n",
      "Q 2+373  \n",
      "T 375 \n",
      "\u001b[92m☑\u001b[0m 375 \n",
      "---\n",
      "Q 0+221  \n",
      "T 221 \n",
      "\u001b[92m☑\u001b[0m 221 \n",
      "---\n",
      "Q 14+20  \n",
      "T 34  \n",
      "\u001b[92m☑\u001b[0m 34  \n",
      "---\n",
      "Q 28+970 \n",
      "T 998 \n",
      "\u001b[92m☑\u001b[0m 998 \n",
      "---\n",
      "Q 37+877 \n",
      "T 914 \n",
      "\u001b[92m☑\u001b[0m 914 \n",
      "---\n",
      "Q 720+660\n",
      "T 1380\n",
      "\u001b[92m☑\u001b[0m 1380\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 44\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0049 - acc: 0.9994 - val_loss: 0.0067 - val_acc: 0.9987\n",
      "Q 672+990\n",
      "T 1662\n",
      "\u001b[92m☑\u001b[0m 1662\n",
      "---\n",
      "Q 56+18  \n",
      "T 74  \n",
      "\u001b[92m☑\u001b[0m 74  \n",
      "---\n",
      "Q 98+842 \n",
      "T 940 \n",
      "\u001b[92m☑\u001b[0m 940 \n",
      "---\n",
      "Q 65+946 \n",
      "T 1011\n",
      "\u001b[92m☑\u001b[0m 1011\n",
      "---\n",
      "Q 47+823 \n",
      "T 870 \n",
      "\u001b[92m☑\u001b[0m 870 \n",
      "---\n",
      "Q 6+819  \n",
      "T 825 \n",
      "\u001b[92m☑\u001b[0m 825 \n",
      "---\n",
      "Q 844+396\n",
      "T 1240\n",
      "\u001b[92m☑\u001b[0m 1240\n",
      "---\n",
      "Q 462+915\n",
      "T 1377\n",
      "\u001b[92m☑\u001b[0m 1377\n",
      "---\n",
      "Q 156+64 \n",
      "T 220 \n",
      "\u001b[92m☑\u001b[0m 220 \n",
      "---\n",
      "Q 774+619\n",
      "T 1393\n",
      "\u001b[92m☑\u001b[0m 1393\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 45\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0025 - acc: 0.9999 - val_loss: 0.0053 - val_acc: 0.9990\n",
      "Q 32+267 \n",
      "T 299 \n",
      "\u001b[92m☑\u001b[0m 299 \n",
      "---\n",
      "Q 983+65 \n",
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      "\u001b[92m☑\u001b[0m 1048\n",
      "---\n",
      "Q 722+49 \n",
      "T 771 \n",
      "\u001b[92m☑\u001b[0m 771 \n",
      "---\n",
      "Q 2+372  \n",
      "T 374 \n",
      "\u001b[92m☑\u001b[0m 374 \n",
      "---\n",
      "Q 420+3  \n",
      "T 423 \n",
      "\u001b[92m☑\u001b[0m 423 \n",
      "---\n",
      "Q 113+6  \n",
      "T 119 \n",
      "\u001b[92m☑\u001b[0m 119 \n",
      "---\n",
      "Q 691+490\n",
      "T 1181\n",
      "\u001b[92m☑\u001b[0m 1181\n",
      "---\n",
      "Q 3+845  \n",
      "T 848 \n",
      "\u001b[92m☑\u001b[0m 848 \n",
      "---\n",
      "Q 80+439 \n",
      "T 519 \n",
      "\u001b[92m☑\u001b[0m 519 \n",
      "---\n",
      "Q 75+5   \n",
      "T 80  \n",
      "\u001b[92m☑\u001b[0m 80  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 46\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0034 - acc: 0.9995 - val_loss: 0.0122 - val_acc: 0.9963\n",
      "Q 603+113\n",
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      "\u001b[92m☑\u001b[0m 716 \n",
      "---\n",
      "Q 57+72  \n",
      "T 129 \n",
      "\u001b[92m☑\u001b[0m 129 \n",
      "---\n",
      "Q 11+670 \n",
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      "\u001b[92m☑\u001b[0m 681 \n",
      "---\n",
      "Q 273+11 \n",
      "T 284 \n",
      "\u001b[92m☑\u001b[0m 284 \n",
      "---\n",
      "Q 706+38 \n",
      "T 744 \n",
      "\u001b[92m☑\u001b[0m 744 \n",
      "---\n",
      "Q 3+362  \n",
      "T 365 \n",
      "\u001b[91m☒\u001b[0m 366 \n",
      "---\n",
      "Q 35+127 \n",
      "T 162 \n",
      "\u001b[92m☑\u001b[0m 162 \n",
      "---\n",
      "Q 62+329 \n",
      "T 391 \n",
      "\u001b[92m☑\u001b[0m 391 \n",
      "---\n",
      "Q 28+361 \n",
      "T 389 \n",
      "\u001b[92m☑\u001b[0m 389 \n",
      "---\n",
      "Q 5+718  \n",
      "T 723 \n",
      "\u001b[92m☑\u001b[0m 723 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 47\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0588 - acc: 0.9823 - val_loss: 0.0106 - val_acc: 0.9974\n",
      "Q 622+86 \n",
      "T 708 \n",
      "\u001b[92m☑\u001b[0m 708 \n",
      "---\n",
      "Q 7+435  \n",
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      "\u001b[92m☑\u001b[0m 442 \n",
      "---\n",
      "Q 193+5  \n",
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      "\u001b[92m☑\u001b[0m 198 \n",
      "---\n",
      "Q 15+933 \n",
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      "\u001b[92m☑\u001b[0m 948 \n",
      "---\n",
      "Q 58+83  \n",
      "T 141 \n",
      "\u001b[92m☑\u001b[0m 141 \n",
      "---\n",
      "Q 511+4  \n",
      "T 515 \n",
      "\u001b[92m☑\u001b[0m 515 \n",
      "---\n",
      "Q 3+977  \n",
      "T 980 \n",
      "\u001b[92m☑\u001b[0m 980 \n",
      "---\n",
      "Q 416+34 \n",
      "T 450 \n",
      "\u001b[92m☑\u001b[0m 450 \n",
      "---\n",
      "Q 401+86 \n",
      "T 487 \n",
      "\u001b[92m☑\u001b[0m 487 \n",
      "---\n",
      "Q 83+413 \n",
      "T 496 \n",
      "\u001b[92m☑\u001b[0m 496 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 48\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0035 - acc: 0.9998 - val_loss: 0.0067 - val_acc: 0.9985\n",
      "Q 271+22 \n",
      "T 293 \n",
      "\u001b[92m☑\u001b[0m 293 \n",
      "---\n",
      "Q 556+800\n",
      "T 1356\n",
      "\u001b[92m☑\u001b[0m 1356\n",
      "---\n",
      "Q 267+0  \n",
      "T 267 \n",
      "\u001b[92m☑\u001b[0m 267 \n",
      "---\n",
      "Q 68+840 \n",
      "T 908 \n",
      "\u001b[92m☑\u001b[0m 908 \n",
      "---\n",
      "Q 75+446 \n",
      "T 521 \n",
      "\u001b[92m☑\u001b[0m 521 \n",
      "---\n",
      "Q 663+4  \n",
      "T 667 \n",
      "\u001b[92m☑\u001b[0m 667 \n",
      "---\n",
      "Q 288+107\n",
      "T 395 \n",
      "\u001b[92m☑\u001b[0m 395 \n",
      "---\n",
      "Q 943+79 \n",
      "T 1022\n",
      "\u001b[92m☑\u001b[0m 1022\n",
      "---\n",
      "Q 6+989  \n",
      "T 995 \n",
      "\u001b[92m☑\u001b[0m 995 \n",
      "---\n",
      "Q 5+310  \n",
      "T 315 \n",
      "\u001b[92m☑\u001b[0m 315 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 49\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0022 - acc: 1.0000 - val_loss: 0.0050 - val_acc: 0.9990\n",
      "Q 374+730\n",
      "T 1104\n",
      "\u001b[92m☑\u001b[0m 1104\n",
      "---\n",
      "Q 9+34   \n",
      "T 43  \n",
      "\u001b[92m☑\u001b[0m 43  \n",
      "---\n",
      "Q 8+635  \n",
      "T 643 \n",
      "\u001b[92m☑\u001b[0m 643 \n",
      "---\n",
      "Q 797+2  \n",
      "T 799 \n",
      "\u001b[92m☑\u001b[0m 799 \n",
      "---\n",
      "Q 89+198 \n",
      "T 287 \n",
      "\u001b[92m☑\u001b[0m 287 \n",
      "---\n",
      "Q 2+469  \n",
      "T 471 \n",
      "\u001b[92m☑\u001b[0m 471 \n",
      "---\n",
      "Q 325+804\n",
      "T 1129\n",
      "\u001b[92m☑\u001b[0m 1129\n",
      "---\n",
      "Q 551+55 \n",
      "T 606 \n",
      "\u001b[92m☑\u001b[0m 606 \n",
      "---\n",
      "Q 469+846\n",
      "T 1315\n",
      "\u001b[92m☑\u001b[0m 1315\n",
      "---\n",
      "Q 196+43 \n",
      "T 239 \n",
      "\u001b[92m☑\u001b[0m 239 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 50\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0019 - acc: 1.0000 - val_loss: 0.0045 - val_acc: 0.9990\n",
      "Q 25+0   \n",
      "T 25  \n",
      "\u001b[92m☑\u001b[0m 25  \n",
      "---\n",
      "Q 992+90 \n",
      "T 1082\n",
      "\u001b[92m☑\u001b[0m 1082\n",
      "---\n",
      "Q 23+984 \n",
      "T 1007\n",
      "\u001b[92m☑\u001b[0m 1007\n",
      "---\n",
      "Q 198+566\n",
      "T 764 \n",
      "\u001b[92m☑\u001b[0m 764 \n",
      "---\n",
      "Q 71+402 \n",
      "T 473 \n",
      "\u001b[92m☑\u001b[0m 473 \n",
      "---\n",
      "Q 464+5  \n",
      "T 469 \n",
      "\u001b[92m☑\u001b[0m 469 \n",
      "---\n",
      "Q 51+480 \n",
      "T 531 \n",
      "\u001b[92m☑\u001b[0m 531 \n",
      "---\n",
      "Q 257+37 \n",
      "T 294 \n",
      "\u001b[92m☑\u001b[0m 294 \n",
      "---\n",
      "Q 278+59 \n",
      "T 337 \n",
      "\u001b[92m☑\u001b[0m 337 \n",
      "---\n",
      "Q 693+811\n",
      "T 1504\n",
      "\u001b[92m☑\u001b[0m 1504\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 51\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0016 - acc: 1.0000 - val_loss: 0.0043 - val_acc: 0.9990\n",
      "Q 13+723 \n",
      "T 736 \n",
      "\u001b[92m☑\u001b[0m 736 \n",
      "---\n",
      "Q 468+32 \n",
      "T 500 \n",
      "\u001b[92m☑\u001b[0m 500 \n",
      "---\n",
      "Q 2+469  \n",
      "T 471 \n",
      "\u001b[92m☑\u001b[0m 471 \n",
      "---\n",
      "Q 88+962 \n",
      "T 1050\n",
      "\u001b[92m☑\u001b[0m 1050\n",
      "---\n",
      "Q 233+5  \n",
      "T 238 \n",
      "\u001b[92m☑\u001b[0m 238 \n",
      "---\n",
      "Q 897+78 \n",
      "T 975 \n",
      "\u001b[92m☑\u001b[0m 975 \n",
      "---\n",
      "Q 594+530\n",
      "T 1124\n",
      "\u001b[92m☑\u001b[0m 1124\n",
      "---\n",
      "Q 21+362 \n",
      "T 383 \n",
      "\u001b[92m☑\u001b[0m 383 \n",
      "---\n",
      "Q 109+375\n",
      "T 484 \n",
      "\u001b[92m☑\u001b[0m 484 \n",
      "---\n",
      "Q 37+99  \n",
      "T 136 \n",
      "\u001b[92m☑\u001b[0m 136 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 52\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0016 - acc: 1.0000 - val_loss: 0.0040 - val_acc: 0.9992\n",
      "Q 17+876 \n",
      "T 893 \n",
      "\u001b[92m☑\u001b[0m 893 \n",
      "---\n",
      "Q 257+4  \n",
      "T 261 \n",
      "\u001b[92m☑\u001b[0m 261 \n",
      "---\n",
      "Q 329+795\n",
      "T 1124\n",
      "\u001b[92m☑\u001b[0m 1124\n",
      "---\n",
      "Q 9+312  \n",
      "T 321 \n",
      "\u001b[92m☑\u001b[0m 321 \n",
      "---\n",
      "Q 172+15 \n",
      "T 187 \n",
      "\u001b[92m☑\u001b[0m 187 \n",
      "---\n",
      "Q 43+925 \n",
      "T 968 \n",
      "\u001b[92m☑\u001b[0m 968 \n",
      "---\n",
      "Q 16+760 \n",
      "T 776 \n",
      "\u001b[92m☑\u001b[0m 776 \n",
      "---\n",
      "Q 9+605  \n",
      "T 614 \n",
      "\u001b[92m☑\u001b[0m 614 \n",
      "---\n",
      "Q 567+647\n",
      "T 1214\n",
      "\u001b[92m☑\u001b[0m 1214\n",
      "---\n",
      "Q 72+171 \n",
      "T 243 \n",
      "\u001b[92m☑\u001b[0m 243 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 53\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0013 - acc: 1.0000 - val_loss: 0.0038 - val_acc: 0.9993\n",
      "Q 650+7  \n",
      "T 657 \n",
      "\u001b[92m☑\u001b[0m 657 \n",
      "---\n",
      "Q 223+145\n",
      "T 368 \n",
      "\u001b[92m☑\u001b[0m 368 \n",
      "---\n",
      "Q 489+197\n",
      "T 686 \n",
      "\u001b[92m☑\u001b[0m 686 \n",
      "---\n",
      "Q 672+8  \n",
      "T 680 \n",
      "\u001b[92m☑\u001b[0m 680 \n",
      "---\n",
      "Q 951+4  \n",
      "T 955 \n",
      "\u001b[92m☑\u001b[0m 955 \n",
      "---\n",
      "Q 28+4   \n",
      "T 32  \n",
      "\u001b[92m☑\u001b[0m 32  \n",
      "---\n",
      "Q 38+993 \n",
      "T 1031\n",
      "\u001b[92m☑\u001b[0m 1031\n",
      "---\n",
      "Q 110+0  \n",
      "T 110 \n",
      "\u001b[92m☑\u001b[0m 110 \n",
      "---\n",
      "Q 998+704\n",
      "T 1702\n",
      "\u001b[92m☑\u001b[0m 1702\n",
      "---\n",
      "Q 79+140 \n",
      "T 219 \n",
      "\u001b[92m☑\u001b[0m 219 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 54\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0319 - acc: 0.9904 - val_loss: 0.1253 - val_acc: 0.9572\n",
      "Q 382+47 \n",
      "T 429 \n",
      "\u001b[92m☑\u001b[0m 429 \n",
      "---\n",
      "Q 9+929  \n",
      "T 938 \n",
      "\u001b[92m☑\u001b[0m 938 \n",
      "---\n",
      "Q 185+820\n",
      "T 1005\n",
      "\u001b[91m☒\u001b[0m 995 \n",
      "---\n",
      "Q 396+71 \n",
      "T 467 \n",
      "\u001b[92m☑\u001b[0m 467 \n",
      "---\n",
      "Q 0+62   \n",
      "T 62  \n",
      "\u001b[92m☑\u001b[0m 62  \n",
      "---\n",
      "Q 46+821 \n",
      "T 867 \n",
      "\u001b[91m☒\u001b[0m 857 \n",
      "---\n",
      "Q 50+404 \n",
      "T 454 \n",
      "\u001b[92m☑\u001b[0m 454 \n",
      "---\n",
      "Q 8+396  \n",
      "T 404 \n",
      "\u001b[92m☑\u001b[0m 404 \n",
      "---\n",
      "Q 410+227\n",
      "T 637 \n",
      "\u001b[92m☑\u001b[0m 637 \n",
      "---\n",
      "Q 23+984 \n",
      "T 1007\n",
      "\u001b[92m☑\u001b[0m 1007\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 55\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 30s - loss: 0.0179 - acc: 0.9948 - val_loss: 0.0065 - val_acc: 0.9984\n",
      "Q 210+114\n",
      "T 324 \n",
      "\u001b[92m☑\u001b[0m 324 \n",
      "---\n",
      "Q 41+886 \n",
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      "\u001b[92m☑\u001b[0m 927 \n",
      "---\n",
      "Q 801+29 \n",
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      "\u001b[92m☑\u001b[0m 830 \n",
      "---\n",
      "Q 52+669 \n",
      "T 721 \n",
      "\u001b[92m☑\u001b[0m 721 \n",
      "---\n",
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      "T 162 \n",
      "\u001b[92m☑\u001b[0m 162 \n",
      "---\n",
      "Q 873+27 \n",
      "T 900 \n",
      "\u001b[92m☑\u001b[0m 900 \n",
      "---\n",
      "Q 718+77 \n",
      "T 795 \n",
      "\u001b[92m☑\u001b[0m 795 \n",
      "---\n",
      "Q 34+174 \n",
      "T 208 \n",
      "\u001b[92m☑\u001b[0m 208 \n",
      "---\n",
      "Q 99+298 \n",
      "T 397 \n",
      "\u001b[92m☑\u001b[0m 397 \n",
      "---\n",
      "Q 315+823\n",
      "T 1138\n",
      "\u001b[92m☑\u001b[0m 1138\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 56\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0020 - acc: 0.9999 - val_loss: 0.0049 - val_acc: 0.9990\n",
      "Q 704+14 \n",
      "T 718 \n",
      "\u001b[92m☑\u001b[0m 718 \n",
      "---\n",
      "Q 892+964\n",
      "T 1856\n",
      "\u001b[92m☑\u001b[0m 1856\n",
      "---\n",
      "Q 888+74 \n",
      "T 962 \n",
      "\u001b[92m☑\u001b[0m 962 \n",
      "---\n",
      "Q 82+211 \n",
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      "\u001b[92m☑\u001b[0m 293 \n",
      "---\n",
      "Q 67+17  \n",
      "T 84  \n",
      "\u001b[92m☑\u001b[0m 84  \n",
      "---\n",
      "Q 72+628 \n",
      "T 700 \n",
      "\u001b[92m☑\u001b[0m 700 \n",
      "---\n",
      "Q 93+786 \n",
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      "\u001b[92m☑\u001b[0m 879 \n",
      "---\n",
      "Q 8+450  \n",
      "T 458 \n",
      "\u001b[92m☑\u001b[0m 458 \n",
      "---\n",
      "Q 25+73  \n",
      "T 98  \n",
      "\u001b[92m☑\u001b[0m 98  \n",
      "---\n",
      "Q 51+630 \n",
      "T 681 \n",
      "\u001b[92m☑\u001b[0m 681 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 57\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0015 - acc: 1.0000 - val_loss: 0.0035 - val_acc: 0.9992\n",
      "Q 529+82 \n",
      "T 611 \n",
      "\u001b[92m☑\u001b[0m 611 \n",
      "---\n",
      "Q 190+12 \n",
      "T 202 \n",
      "\u001b[92m☑\u001b[0m 202 \n",
      "---\n",
      "Q 9+34   \n",
      "T 43  \n",
      "\u001b[92m☑\u001b[0m 43  \n",
      "---\n",
      "Q 93+104 \n",
      "T 197 \n",
      "\u001b[92m☑\u001b[0m 197 \n",
      "---\n",
      "Q 40+97  \n",
      "T 137 \n",
      "\u001b[92m☑\u001b[0m 137 \n",
      "---\n",
      "Q 269+731\n",
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      "\u001b[92m☑\u001b[0m 1000\n",
      "---\n",
      "Q 39+850 \n",
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      "\u001b[92m☑\u001b[0m 889 \n",
      "---\n",
      "Q 195+139\n",
      "T 334 \n",
      "\u001b[92m☑\u001b[0m 334 \n",
      "---\n",
      "Q 74+551 \n",
      "T 625 \n",
      "\u001b[92m☑\u001b[0m 625 \n",
      "---\n",
      "Q 5+529  \n",
      "T 534 \n",
      "\u001b[92m☑\u001b[0m 534 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 58\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 29s - loss: 0.0012 - acc: 1.0000 - val_loss: 0.0031 - val_acc: 0.9996\n",
      "Q 24+869 \n",
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      "\u001b[92m☑\u001b[0m 893 \n",
      "---\n",
      "Q 268+53 \n",
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      "\u001b[92m☑\u001b[0m 321 \n",
      "---\n",
      "Q 965+0  \n",
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      "\u001b[92m☑\u001b[0m 965 \n",
      "---\n",
      "Q 80+139 \n",
      "T 219 \n",
      "\u001b[92m☑\u001b[0m 219 \n",
      "---\n",
      "Q 2+819  \n",
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      "\u001b[92m☑\u001b[0m 821 \n",
      "---\n",
      "Q 181+144\n",
      "T 325 \n",
      "\u001b[92m☑\u001b[0m 325 \n",
      "---\n",
      "Q 949+567\n",
      "T 1516\n",
      "\u001b[92m☑\u001b[0m 1516\n",
      "---\n",
      "Q 318+801\n",
      "T 1119\n",
      "\u001b[92m☑\u001b[0m 1119\n",
      "---\n",
      "Q 71+212 \n",
      "T 283 \n",
      "\u001b[92m☑\u001b[0m 283 \n",
      "---\n",
      "Q 529+631\n",
      "T 1160\n",
      "\u001b[92m☑\u001b[0m 1160\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 59\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0010 - acc: 1.0000 - val_loss: 0.0033 - val_acc: 0.9994\n",
      "Q 8+650  \n",
      "T 658 \n",
      "\u001b[92m☑\u001b[0m 658 \n",
      "---\n",
      "Q 39+340 \n",
      "T 379 \n",
      "\u001b[92m☑\u001b[0m 379 \n",
      "---\n",
      "Q 0+130  \n",
      "T 130 \n",
      "\u001b[92m☑\u001b[0m 130 \n",
      "---\n",
      "Q 634+13 \n",
      "T 647 \n",
      "\u001b[92m☑\u001b[0m 647 \n",
      "---\n",
      "Q 38+133 \n",
      "T 171 \n",
      "\u001b[92m☑\u001b[0m 171 \n",
      "---\n",
      "Q 58+587 \n",
      "T 645 \n",
      "\u001b[92m☑\u001b[0m 645 \n",
      "---\n",
      "Q 86+302 \n",
      "T 388 \n",
      "\u001b[92m☑\u001b[0m 388 \n",
      "---\n",
      "Q 836+148\n",
      "T 984 \n",
      "\u001b[92m☑\u001b[0m 984 \n",
      "---\n",
      "Q 767+34 \n",
      "T 801 \n",
      "\u001b[92m☑\u001b[0m 801 \n",
      "---\n",
      "Q 73+336 \n",
      "T 409 \n",
      "\u001b[92m☑\u001b[0m 409 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 60\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0011 - acc: 1.0000 - val_loss: 0.0050 - val_acc: 0.9987\n",
      "Q 241+67 \n",
      "T 308 \n",
      "\u001b[92m☑\u001b[0m 308 \n",
      "---\n",
      "Q 807+0  \n",
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      "\u001b[92m☑\u001b[0m 807 \n",
      "---\n",
      "Q 59+282 \n",
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      "\u001b[92m☑\u001b[0m 341 \n",
      "---\n",
      "Q 966+94 \n",
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      "\u001b[92m☑\u001b[0m 1060\n",
      "---\n",
      "Q 127+646\n",
      "T 773 \n",
      "\u001b[92m☑\u001b[0m 773 \n",
      "---\n",
      "Q 35+98  \n",
      "T 133 \n",
      "\u001b[92m☑\u001b[0m 133 \n",
      "---\n",
      "Q 704+47 \n",
      "T 751 \n",
      "\u001b[92m☑\u001b[0m 751 \n",
      "---\n",
      "Q 71+661 \n",
      "T 732 \n",
      "\u001b[92m☑\u001b[0m 732 \n",
      "---\n",
      "Q 681+7  \n",
      "T 688 \n",
      "\u001b[92m☑\u001b[0m 688 \n",
      "---\n",
      "Q 5+125  \n",
      "T 130 \n",
      "\u001b[92m☑\u001b[0m 130 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 61\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0486 - acc: 0.9855 - val_loss: 0.0062 - val_acc: 0.9986\n",
      "Q 47+333 \n",
      "T 380 \n",
      "\u001b[92m☑\u001b[0m 380 \n",
      "---\n",
      "Q 822+500\n",
      "T 1322\n",
      "\u001b[92m☑\u001b[0m 1322\n",
      "---\n",
      "Q 25+17  \n",
      "T 42  \n",
      "\u001b[92m☑\u001b[0m 42  \n",
      "---\n",
      "Q 117+12 \n",
      "T 129 \n",
      "\u001b[92m☑\u001b[0m 129 \n",
      "---\n",
      "Q 366+290\n",
      "T 656 \n",
      "\u001b[92m☑\u001b[0m 656 \n",
      "---\n",
      "Q 873+924\n",
      "T 1797\n",
      "\u001b[92m☑\u001b[0m 1797\n",
      "---\n",
      "Q 14+20  \n",
      "T 34  \n",
      "\u001b[92m☑\u001b[0m 34  \n",
      "---\n",
      "Q 29+386 \n",
      "T 415 \n",
      "\u001b[92m☑\u001b[0m 415 \n",
      "---\n",
      "Q 417+3  \n",
      "T 420 \n",
      "\u001b[92m☑\u001b[0m 420 \n",
      "---\n",
      "Q 627+617\n",
      "T 1244\n",
      "\u001b[92m☑\u001b[0m 1244\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 62\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0022 - acc: 0.9999 - val_loss: 0.0041 - val_acc: 0.9992\n",
      "Q 579+72 \n",
      "T 651 \n",
      "\u001b[92m☑\u001b[0m 651 \n",
      "---\n",
      "Q 960+44 \n",
      "T 1004\n",
      "\u001b[92m☑\u001b[0m 1004\n",
      "---\n",
      "Q 529+59 \n",
      "T 588 \n",
      "\u001b[92m☑\u001b[0m 588 \n",
      "---\n",
      "Q 590+8  \n",
      "T 598 \n",
      "\u001b[92m☑\u001b[0m 598 \n",
      "---\n",
      "Q 622+4  \n",
      "T 626 \n",
      "\u001b[92m☑\u001b[0m 626 \n",
      "---\n",
      "Q 352+809\n",
      "T 1161\n",
      "\u001b[92m☑\u001b[0m 1161\n",
      "---\n",
      "Q 75+74  \n",
      "T 149 \n",
      "\u001b[92m☑\u001b[0m 149 \n",
      "---\n",
      "Q 489+90 \n",
      "T 579 \n",
      "\u001b[92m☑\u001b[0m 579 \n",
      "---\n",
      "Q 46+313 \n",
      "T 359 \n",
      "\u001b[92m☑\u001b[0m 359 \n",
      "---\n",
      "Q 138+11 \n",
      "T 149 \n",
      "\u001b[92m☑\u001b[0m 149 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 63\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0015 - acc: 0.9999 - val_loss: 0.0030 - val_acc: 0.9994\n",
      "Q 482+5  \n",
      "T 487 \n",
      "\u001b[92m☑\u001b[0m 487 \n",
      "---\n",
      "Q 47+510 \n",
      "T 557 \n",
      "\u001b[92m☑\u001b[0m 557 \n",
      "---\n",
      "Q 325+804\n",
      "T 1129\n",
      "\u001b[92m☑\u001b[0m 1129\n",
      "---\n",
      "Q 253+873\n",
      "T 1126\n",
      "\u001b[92m☑\u001b[0m 1126\n",
      "---\n",
      "Q 616+33 \n",
      "T 649 \n",
      "\u001b[92m☑\u001b[0m 649 \n",
      "---\n",
      "Q 926+310\n",
      "T 1236\n",
      "\u001b[92m☑\u001b[0m 1236\n",
      "---\n",
      "Q 5+890  \n",
      "T 895 \n",
      "\u001b[92m☑\u001b[0m 895 \n",
      "---\n",
      "Q 630+20 \n",
      "T 650 \n",
      "\u001b[92m☑\u001b[0m 650 \n",
      "---\n",
      "Q 535+37 \n",
      "T 572 \n",
      "\u001b[92m☑\u001b[0m 572 \n",
      "---\n",
      "Q 52+402 \n",
      "T 454 \n",
      "\u001b[92m☑\u001b[0m 454 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 64\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0011 - acc: 1.0000 - val_loss: 0.0028 - val_acc: 0.9994\n",
      "Q 523+376\n",
      "T 899 \n",
      "\u001b[92m☑\u001b[0m 899 \n",
      "---\n",
      "Q 64+310 \n",
      "T 374 \n",
      "\u001b[92m☑\u001b[0m 374 \n",
      "---\n",
      "Q 15+219 \n",
      "T 234 \n",
      "\u001b[92m☑\u001b[0m 234 \n",
      "---\n",
      "Q 400+37 \n",
      "T 437 \n",
      "\u001b[92m☑\u001b[0m 437 \n",
      "---\n",
      "Q 597+364\n",
      "T 961 \n",
      "\u001b[92m☑\u001b[0m 961 \n",
      "---\n",
      "Q 90+506 \n",
      "T 596 \n",
      "\u001b[92m☑\u001b[0m 596 \n",
      "---\n",
      "Q 890+600\n",
      "T 1490\n",
      "\u001b[92m☑\u001b[0m 1490\n",
      "---\n",
      "Q 155+62 \n",
      "T 217 \n",
      "\u001b[92m☑\u001b[0m 217 \n",
      "---\n",
      "Q 764+17 \n",
      "T 781 \n",
      "\u001b[92m☑\u001b[0m 781 \n",
      "---\n",
      "Q 64+933 \n",
      "T 997 \n",
      "\u001b[92m☑\u001b[0m 997 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 65\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 9.1291e-04 - acc: 1.0000 - val_loss: 0.0025 - val_acc: 0.9994\n",
      "Q 331+304\n",
      "T 635 \n",
      "\u001b[92m☑\u001b[0m 635 \n",
      "---\n",
      "Q 1+125  \n",
      "T 126 \n",
      "\u001b[92m☑\u001b[0m 126 \n",
      "---\n",
      "Q 5+128  \n",
      "T 133 \n",
      "\u001b[92m☑\u001b[0m 133 \n",
      "---\n",
      "Q 728+675\n",
      "T 1403\n",
      "\u001b[92m☑\u001b[0m 1403\n",
      "---\n",
      "Q 217+370\n",
      "T 587 \n",
      "\u001b[92m☑\u001b[0m 587 \n",
      "---\n",
      "Q 327+9  \n",
      "T 336 \n",
      "\u001b[92m☑\u001b[0m 336 \n",
      "---\n",
      "Q 46+472 \n",
      "T 518 \n",
      "\u001b[92m☑\u001b[0m 518 \n",
      "---\n",
      "Q 558+18 \n",
      "T 576 \n",
      "\u001b[92m☑\u001b[0m 576 \n",
      "---\n",
      "Q 590+115\n",
      "T 705 \n",
      "\u001b[92m☑\u001b[0m 705 \n",
      "---\n",
      "Q 72+140 \n",
      "T 212 \n",
      "\u001b[92m☑\u001b[0m 212 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 66\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0054 - acc: 0.9986 - val_loss: 0.1097 - val_acc: 0.9686\n",
      "Q 8+763  \n",
      "T 771 \n",
      "\u001b[91m☒\u001b[0m 772 \n",
      "---\n",
      "Q 81+973 \n",
      "T 1054\n",
      "\u001b[92m☑\u001b[0m 1054\n",
      "---\n",
      "Q 53+786 \n",
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      "\u001b[92m☑\u001b[0m 839 \n",
      "---\n",
      "Q 159+44 \n",
      "T 203 \n",
      "\u001b[92m☑\u001b[0m 203 \n",
      "---\n",
      "Q 147+797\n",
      "T 944 \n",
      "\u001b[91m☒\u001b[0m 933 \n",
      "---\n",
      "Q 179+0  \n",
      "T 179 \n",
      "\u001b[91m☒\u001b[0m 189 \n",
      "---\n",
      "Q 113+439\n",
      "T 552 \n",
      "\u001b[92m☑\u001b[0m 552 \n",
      "---\n",
      "Q 31+794 \n",
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      "\u001b[92m☑\u001b[0m 825 \n",
      "---\n",
      "Q 538+736\n",
      "T 1274\n",
      "\u001b[92m☑\u001b[0m 1274\n",
      "---\n",
      "Q 494+108\n",
      "T 602 \n",
      "\u001b[92m☑\u001b[0m 602 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 67\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0326 - acc: 0.9903 - val_loss: 0.0047 - val_acc: 0.9991\n",
      "Q 12+860 \n",
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      "\u001b[92m☑\u001b[0m 872 \n",
      "---\n",
      "Q 41+494 \n",
      "T 535 \n",
      "\u001b[92m☑\u001b[0m 535 \n",
      "---\n",
      "Q 508+364\n",
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      "\u001b[92m☑\u001b[0m 872 \n",
      "---\n",
      "Q 511+92 \n",
      "T 603 \n",
      "\u001b[92m☑\u001b[0m 603 \n",
      "---\n",
      "Q 85+582 \n",
      "T 667 \n",
      "\u001b[92m☑\u001b[0m 667 \n",
      "---\n",
      "Q 146+45 \n",
      "T 191 \n",
      "\u001b[92m☑\u001b[0m 191 \n",
      "---\n",
      "Q 892+942\n",
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      "\u001b[92m☑\u001b[0m 1834\n",
      "---\n",
      "Q 919+99 \n",
      "T 1018\n",
      "\u001b[92m☑\u001b[0m 1018\n",
      "---\n",
      "Q 738+85 \n",
      "T 823 \n",
      "\u001b[92m☑\u001b[0m 823 \n",
      "---\n",
      "Q 54+579 \n",
      "T 633 \n",
      "\u001b[92m☑\u001b[0m 633 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 68\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0015 - acc: 0.9999 - val_loss: 0.0032 - val_acc: 0.9994\n",
      "Q 985+26 \n",
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      "\u001b[92m☑\u001b[0m 1011\n",
      "---\n",
      "Q 974+43 \n",
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      "\u001b[92m☑\u001b[0m 1017\n",
      "---\n",
      "Q 117+2  \n",
      "T 119 \n",
      "\u001b[92m☑\u001b[0m 119 \n",
      "---\n",
      "Q 196+43 \n",
      "T 239 \n",
      "\u001b[92m☑\u001b[0m 239 \n",
      "---\n",
      "Q 738+748\n",
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      "\u001b[92m☑\u001b[0m 1486\n",
      "---\n",
      "Q 42+253 \n",
      "T 295 \n",
      "\u001b[92m☑\u001b[0m 295 \n",
      "---\n",
      "Q 515+98 \n",
      "T 613 \n",
      "\u001b[92m☑\u001b[0m 613 \n",
      "---\n",
      "Q 149+529\n",
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      "\u001b[92m☑\u001b[0m 678 \n",
      "---\n",
      "Q 5+956  \n",
      "T 961 \n",
      "\u001b[92m☑\u001b[0m 961 \n",
      "---\n",
      "Q 43+586 \n",
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      "\u001b[92m☑\u001b[0m 629 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 69\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 30s - loss: 9.6461e-04 - acc: 1.0000 - val_loss: 0.0027 - val_acc: 0.9995\n",
      "Q 24+14  \n",
      "T 38  \n",
      "\u001b[92m☑\u001b[0m 38  \n",
      "---\n",
      "Q 46+348 \n",
      "T 394 \n",
      "\u001b[92m☑\u001b[0m 394 \n",
      "---\n",
      "Q 23+978 \n",
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      "\u001b[92m☑\u001b[0m 1001\n",
      "---\n",
      "Q 1+208  \n",
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      "\u001b[92m☑\u001b[0m 209 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1151\n",
      "---\n",
      "Q 56+296 \n",
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      "\u001b[92m☑\u001b[0m 352 \n",
      "---\n",
      "Q 51+810 \n",
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      "\u001b[92m☑\u001b[0m 861 \n",
      "---\n",
      "Q 929+896\n",
      "T 1825\n",
      "\u001b[92m☑\u001b[0m 1825\n",
      "---\n",
      "Q 128+2  \n",
      "T 130 \n",
      "\u001b[92m☑\u001b[0m 130 \n",
      "---\n",
      "Q 40+14  \n",
      "T 54  \n",
      "\u001b[92m☑\u001b[0m 54  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 70\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 8.1041e-04 - acc: 1.0000 - val_loss: 0.0025 - val_acc: 0.9995\n",
      "Q 373+3  \n",
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      "\u001b[92m☑\u001b[0m 376 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 629 \n",
      "---\n",
      "Q 174+297\n",
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      "\u001b[92m☑\u001b[0m 471 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1303\n",
      "---\n",
      "Q 759+82 \n",
      "T 841 \n",
      "\u001b[92m☑\u001b[0m 841 \n",
      "---\n",
      "Q 0+842  \n",
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      "\u001b[92m☑\u001b[0m 842 \n",
      "---\n",
      "Q 41+589 \n",
      "T 630 \n",
      "\u001b[92m☑\u001b[0m 630 \n",
      "---\n",
      "Q 58+865 \n",
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      "\u001b[92m☑\u001b[0m 923 \n",
      "---\n",
      "Q 634+903\n",
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      "\u001b[92m☑\u001b[0m 1537\n",
      "---\n",
      "Q 32+477 \n",
      "T 509 \n",
      "\u001b[92m☑\u001b[0m 509 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 71\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 8.0131e-04 - acc: 1.0000 - val_loss: 0.0026 - val_acc: 0.9993\n",
      "Q 693+956\n",
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      "\u001b[92m☑\u001b[0m 1649\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 117 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 325 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 460 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1092\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 809 \n",
      "---\n",
      "Q 89+62  \n",
      "T 151 \n",
      "\u001b[92m☑\u001b[0m 151 \n",
      "---\n",
      "Q 513+34 \n",
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      "\u001b[92m☑\u001b[0m 547 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 245 \n",
      "---\n",
      "Q 277+4  \n",
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      "\u001b[92m☑\u001b[0m 281 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 72\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 7.6304e-04 - acc: 1.0000 - val_loss: 0.0024 - val_acc: 0.9997\n",
      "Q 761+979\n",
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      "\u001b[92m☑\u001b[0m 1740\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 908 \n",
      "---\n",
      "Q 357+57 \n",
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      "\u001b[92m☑\u001b[0m 414 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1894\n",
      "---\n",
      "Q 5+405  \n",
      "T 410 \n",
      "\u001b[92m☑\u001b[0m 410 \n",
      "---\n",
      "Q 774+34 \n",
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      "\u001b[92m☑\u001b[0m 808 \n",
      "---\n",
      "Q 589+10 \n",
      "T 599 \n",
      "\u001b[92m☑\u001b[0m 599 \n",
      "---\n",
      "Q 538+344\n",
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      "\u001b[92m☑\u001b[0m 882 \n",
      "---\n",
      "Q 880+63 \n",
      "T 943 \n",
      "\u001b[92m☑\u001b[0m 943 \n",
      "---\n",
      "Q 586+7  \n",
      "T 593 \n",
      "\u001b[92m☑\u001b[0m 593 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 73\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0354 - acc: 0.9901 - val_loss: 0.0561 - val_acc: 0.9803\n",
      "Q 0+700  \n",
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      "\u001b[92m☑\u001b[0m 700 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1176\n",
      "---\n",
      "Q 53+487 \n",
      "T 540 \n",
      "\u001b[92m☑\u001b[0m 540 \n",
      "---\n",
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      "\u001b[91m☒\u001b[0m 919 \n",
      "---\n",
      "Q 740+49 \n",
      "T 789 \n",
      "\u001b[92m☑\u001b[0m 789 \n",
      "---\n",
      "Q 99+861 \n",
      "T 960 \n",
      "\u001b[92m☑\u001b[0m 960 \n",
      "---\n",
      "Q 725+51 \n",
      "T 776 \n",
      "\u001b[92m☑\u001b[0m 776 \n",
      "---\n",
      "Q 71+497 \n",
      "T 568 \n",
      "\u001b[92m☑\u001b[0m 568 \n",
      "---\n",
      "Q 653+34 \n",
      "T 687 \n",
      "\u001b[92m☑\u001b[0m 687 \n",
      "---\n",
      "Q 0+353  \n",
      "T 353 \n",
      "\u001b[92m☑\u001b[0m 353 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 74\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0119 - acc: 0.9966 - val_loss: 0.0041 - val_acc: 0.9992\n",
      "Q 525+39 \n",
      "T 564 \n",
      "\u001b[92m☑\u001b[0m 564 \n",
      "---\n",
      "Q 6+214  \n",
      "T 220 \n",
      "\u001b[92m☑\u001b[0m 220 \n",
      "---\n",
      "Q 796+98 \n",
      "T 894 \n",
      "\u001b[92m☑\u001b[0m 894 \n",
      "---\n",
      "Q 257+37 \n",
      "T 294 \n",
      "\u001b[92m☑\u001b[0m 294 \n",
      "---\n",
      "Q 596+206\n",
      "T 802 \n",
      "\u001b[92m☑\u001b[0m 802 \n",
      "---\n",
      "Q 748+456\n",
      "T 1204\n",
      "\u001b[92m☑\u001b[0m 1204\n",
      "---\n",
      "Q 22+248 \n",
      "T 270 \n",
      "\u001b[92m☑\u001b[0m 270 \n",
      "---\n",
      "Q 810+318\n",
      "T 1128\n",
      "\u001b[92m☑\u001b[0m 1128\n",
      "---\n",
      "Q 780+903\n",
      "T 1683\n",
      "\u001b[92m☑\u001b[0m 1683\n",
      "---\n",
      "Q 9+193  \n",
      "T 202 \n",
      "\u001b[92m☑\u001b[0m 202 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 75\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0012 - acc: 1.0000 - val_loss: 0.0028 - val_acc: 0.9994\n",
      "Q 584+83 \n",
      "T 667 \n",
      "\u001b[92m☑\u001b[0m 667 \n",
      "---\n",
      "Q 64+353 \n",
      "T 417 \n",
      "\u001b[92m☑\u001b[0m 417 \n",
      "---\n",
      "Q 10+69  \n",
      "T 79  \n",
      "\u001b[92m☑\u001b[0m 79  \n",
      "---\n",
      "Q 52+942 \n",
      "T 994 \n",
      "\u001b[92m☑\u001b[0m 994 \n",
      "---\n",
      "Q 37+13  \n",
      "T 50  \n",
      "\u001b[92m☑\u001b[0m 50  \n",
      "---\n",
      "Q 197+4  \n",
      "T 201 \n",
      "\u001b[92m☑\u001b[0m 201 \n",
      "---\n",
      "Q 990+74 \n",
      "T 1064\n",
      "\u001b[92m☑\u001b[0m 1064\n",
      "---\n",
      "Q 253+434\n",
      "T 687 \n",
      "\u001b[92m☑\u001b[0m 687 \n",
      "---\n",
      "Q 98+431 \n",
      "T 529 \n",
      "\u001b[92m☑\u001b[0m 529 \n",
      "---\n",
      "Q 808+93 \n",
      "T 901 \n",
      "\u001b[92m☑\u001b[0m 901 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 76\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 8.3983e-04 - acc: 1.0000 - val_loss: 0.0025 - val_acc: 0.9993\n",
      "Q 401+85 \n",
      "T 486 \n",
      "\u001b[92m☑\u001b[0m 486 \n",
      "---\n",
      "Q 526+2  \n",
      "T 528 \n",
      "\u001b[92m☑\u001b[0m 528 \n",
      "---\n",
      "Q 961+11 \n",
      "T 972 \n",
      "\u001b[92m☑\u001b[0m 972 \n",
      "---\n",
      "Q 384+18 \n",
      "T 402 \n",
      "\u001b[92m☑\u001b[0m 402 \n",
      "---\n",
      "Q 55+296 \n",
      "T 351 \n",
      "\u001b[92m☑\u001b[0m 351 \n",
      "---\n",
      "Q 349+974\n",
      "T 1323\n",
      "\u001b[92m☑\u001b[0m 1323\n",
      "---\n",
      "Q 45+143 \n",
      "T 188 \n",
      "\u001b[92m☑\u001b[0m 188 \n",
      "---\n",
      "Q 18+219 \n",
      "T 237 \n",
      "\u001b[92m☑\u001b[0m 237 \n",
      "---\n",
      "Q 91+129 \n",
      "T 220 \n",
      "\u001b[92m☑\u001b[0m 220 \n",
      "---\n",
      "Q 92+878 \n",
      "T 970 \n",
      "\u001b[92m☑\u001b[0m 970 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 77\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 7.1116e-04 - acc: 1.0000 - val_loss: 0.0023 - val_acc: 0.9994\n",
      "Q 23+91  \n",
      "T 114 \n",
      "\u001b[92m☑\u001b[0m 114 \n",
      "---\n",
      "Q 616+2  \n",
      "T 618 \n",
      "\u001b[92m☑\u001b[0m 618 \n",
      "---\n",
      "Q 761+979\n",
      "T 1740\n",
      "\u001b[92m☑\u001b[0m 1740\n",
      "---\n",
      "Q 98+88  \n",
      "T 186 \n",
      "\u001b[92m☑\u001b[0m 186 \n",
      "---\n",
      "Q 91+529 \n",
      "T 620 \n",
      "\u001b[92m☑\u001b[0m 620 \n",
      "---\n",
      "Q 379+731\n",
      "T 1110\n",
      "\u001b[92m☑\u001b[0m 1110\n",
      "---\n",
      "Q 664+55 \n",
      "T 719 \n",
      "\u001b[92m☑\u001b[0m 719 \n",
      "---\n",
      "Q 129+999\n",
      "T 1128\n",
      "\u001b[92m☑\u001b[0m 1128\n",
      "---\n",
      "Q 10+381 \n",
      "T 391 \n",
      "\u001b[92m☑\u001b[0m 391 \n",
      "---\n",
      "Q 2+897  \n",
      "T 899 \n",
      "\u001b[92m☑\u001b[0m 899 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 78\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 6.1981e-04 - acc: 1.0000 - val_loss: 0.0022 - val_acc: 0.9994\n",
      "Q 933+84 \n",
      "T 1017\n",
      "\u001b[92m☑\u001b[0m 1017\n",
      "---\n",
      "Q 3+530  \n",
      "T 533 \n",
      "\u001b[92m☑\u001b[0m 533 \n",
      "---\n",
      "Q 19+293 \n",
      "T 312 \n",
      "\u001b[92m☑\u001b[0m 312 \n",
      "---\n",
      "Q 374+730\n",
      "T 1104\n",
      "\u001b[92m☑\u001b[0m 1104\n",
      "---\n",
      "Q 92+55  \n",
      "T 147 \n",
      "\u001b[92m☑\u001b[0m 147 \n",
      "---\n",
      "Q 9+343  \n",
      "T 352 \n",
      "\u001b[92m☑\u001b[0m 352 \n",
      "---\n",
      "Q 19+70  \n",
      "T 89  \n",
      "\u001b[92m☑\u001b[0m 89  \n",
      "---\n",
      "Q 34+217 \n",
      "T 251 \n",
      "\u001b[92m☑\u001b[0m 251 \n",
      "---\n",
      "Q 236+948\n",
      "T 1184\n",
      "\u001b[92m☑\u001b[0m 1184\n",
      "---\n",
      "Q 452+81 \n",
      "T 533 \n",
      "\u001b[92m☑\u001b[0m 533 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 79\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 32s - loss: 5.6210e-04 - acc: 1.0000 - val_loss: 0.0021 - val_acc: 0.9994\n",
      "Q 382+90 \n",
      "T 472 \n",
      "\u001b[92m☑\u001b[0m 472 \n",
      "---\n",
      "Q 884+80 \n",
      "T 964 \n",
      "\u001b[92m☑\u001b[0m 964 \n",
      "---\n",
      "Q 62+705 \n",
      "T 767 \n",
      "\u001b[92m☑\u001b[0m 767 \n",
      "---\n",
      "Q 71+2   \n",
      "T 73  \n",
      "\u001b[92m☑\u001b[0m 73  \n",
      "---\n",
      "Q 36+70  \n",
      "T 106 \n",
      "\u001b[92m☑\u001b[0m 106 \n",
      "---\n",
      "Q 25+44  \n",
      "T 69  \n",
      "\u001b[92m☑\u001b[0m 69  \n",
      "---\n",
      "Q 867+944\n",
      "T 1811\n",
      "\u001b[92m☑\u001b[0m 1811\n",
      "---\n",
      "Q 802+591\n",
      "T 1393\n",
      "\u001b[92m☑\u001b[0m 1393\n",
      "---\n",
      "Q 720+23 \n",
      "T 743 \n",
      "\u001b[92m☑\u001b[0m 743 \n",
      "---\n",
      "Q 907+445\n",
      "T 1352\n",
      "\u001b[92m☑\u001b[0m 1352\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 80\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 5.1905e-04 - acc: 1.0000 - val_loss: 0.0027 - val_acc: 0.9991\n",
      "Q 99+953 \n",
      "T 1052\n",
      "\u001b[92m☑\u001b[0m 1052\n",
      "---\n",
      "Q 356+88 \n",
      "T 444 \n",
      "\u001b[92m☑\u001b[0m 444 \n",
      "---\n",
      "Q 40+14  \n",
      "T 54  \n",
      "\u001b[92m☑\u001b[0m 54  \n",
      "---\n",
      "Q 816+22 \n",
      "T 838 \n",
      "\u001b[92m☑\u001b[0m 838 \n",
      "---\n",
      "Q 615+34 \n",
      "T 649 \n",
      "\u001b[92m☑\u001b[0m 649 \n",
      "---\n",
      "Q 50+30  \n",
      "T 80  \n",
      "\u001b[92m☑\u001b[0m 80  \n",
      "---\n",
      "Q 509+563\n",
      "T 1072\n",
      "\u001b[92m☑\u001b[0m 1072\n",
      "---\n",
      "Q 530+1  \n",
      "T 531 \n",
      "\u001b[92m☑\u001b[0m 531 \n",
      "---\n",
      "Q 83+767 \n",
      "T 850 \n",
      "\u001b[92m☑\u001b[0m 850 \n",
      "---\n",
      "Q 348+568\n",
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      "\u001b[92m☑\u001b[0m 916 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 81\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 4.9667e-04 - acc: 1.0000 - val_loss: 0.0025 - val_acc: 0.9994\n",
      "Q 947+227\n",
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      "\u001b[92m☑\u001b[0m 1174\n",
      "---\n",
      "Q 250+25 \n",
      "T 275 \n",
      "\u001b[92m☑\u001b[0m 275 \n",
      "---\n",
      "Q 238+475\n",
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      "\u001b[92m☑\u001b[0m 713 \n",
      "---\n",
      "Q 597+21 \n",
      "T 618 \n",
      "\u001b[92m☑\u001b[0m 618 \n",
      "---\n",
      "Q 773+8  \n",
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      "\u001b[92m☑\u001b[0m 781 \n",
      "---\n",
      "Q 36+396 \n",
      "T 432 \n",
      "\u001b[92m☑\u001b[0m 432 \n",
      "---\n",
      "Q 88+79  \n",
      "T 167 \n",
      "\u001b[92m☑\u001b[0m 167 \n",
      "---\n",
      "Q 513+34 \n",
      "T 547 \n",
      "\u001b[92m☑\u001b[0m 547 \n",
      "---\n",
      "Q 60+943 \n",
      "T 1003\n",
      "\u001b[92m☑\u001b[0m 1003\n",
      "---\n",
      "Q 42+108 \n",
      "T 150 \n",
      "\u001b[92m☑\u001b[0m 150 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 82\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0386 - acc: 0.9884 - val_loss: 0.0189 - val_acc: 0.9937\n",
      "Q 48+908 \n",
      "T 956 \n",
      "\u001b[92m☑\u001b[0m 956 \n",
      "---\n",
      "Q 808+98 \n",
      "T 906 \n",
      "\u001b[92m☑\u001b[0m 906 \n",
      "---\n",
      "Q 508+2  \n",
      "T 510 \n",
      "\u001b[92m☑\u001b[0m 510 \n",
      "---\n",
      "Q 99+48  \n",
      "T 147 \n",
      "\u001b[92m☑\u001b[0m 147 \n",
      "---\n",
      "Q 590+36 \n",
      "T 626 \n",
      "\u001b[92m☑\u001b[0m 626 \n",
      "---\n",
      "Q 359+3  \n",
      "T 362 \n",
      "\u001b[92m☑\u001b[0m 362 \n",
      "---\n",
      "Q 664+39 \n",
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      "\u001b[92m☑\u001b[0m 703 \n",
      "---\n",
      "Q 313+972\n",
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      "\u001b[92m☑\u001b[0m 1285\n",
      "---\n",
      "Q 381+53 \n",
      "T 434 \n",
      "\u001b[92m☑\u001b[0m 434 \n",
      "---\n",
      "Q 293+176\n",
      "T 469 \n",
      "\u001b[92m☑\u001b[0m 469 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 83\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 32s - loss: 0.0035 - acc: 0.9994 - val_loss: 0.0031 - val_acc: 0.9993\n",
      "Q 319+0  \n",
      "T 319 \n",
      "\u001b[92m☑\u001b[0m 319 \n",
      "---\n",
      "Q 65+721 \n",
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      "\u001b[92m☑\u001b[0m 786 \n",
      "---\n",
      "Q 310+17 \n",
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      "\u001b[92m☑\u001b[0m 327 \n",
      "---\n",
      "Q 513+805\n",
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      "\u001b[92m☑\u001b[0m 1318\n",
      "---\n",
      "Q 257+4  \n",
      "T 261 \n",
      "\u001b[92m☑\u001b[0m 261 \n",
      "---\n",
      "Q 608+234\n",
      "T 842 \n",
      "\u001b[92m☑\u001b[0m 842 \n",
      "---\n",
      "Q 208+10 \n",
      "T 218 \n",
      "\u001b[92m☑\u001b[0m 218 \n",
      "---\n",
      "Q 441+80 \n",
      "T 521 \n",
      "\u001b[92m☑\u001b[0m 521 \n",
      "---\n",
      "Q 18+43  \n",
      "T 61  \n",
      "\u001b[92m☑\u001b[0m 61  \n",
      "---\n",
      "Q 637+7  \n",
      "T 644 \n",
      "\u001b[92m☑\u001b[0m 644 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 84\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 8.9579e-04 - acc: 1.0000 - val_loss: 0.0025 - val_acc: 0.9993\n",
      "Q 908+63 \n",
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      "\u001b[92m☑\u001b[0m 971 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 642 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1002\n",
      "---\n",
      "Q 690+57 \n",
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      "\u001b[92m☑\u001b[0m 747 \n",
      "---\n",
      "Q 94+10  \n",
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      "\u001b[92m☑\u001b[0m 104 \n",
      "---\n",
      "Q 673+224\n",
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      "\u001b[92m☑\u001b[0m 897 \n",
      "---\n",
      "Q 590+993\n",
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      "\u001b[92m☑\u001b[0m 1583\n",
      "---\n",
      "Q 37+17  \n",
      "T 54  \n",
      "\u001b[92m☑\u001b[0m 54  \n",
      "---\n",
      "Q 6+614  \n",
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      "\u001b[92m☑\u001b[0m 620 \n",
      "---\n",
      "Q 502+155\n",
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      "\u001b[92m☑\u001b[0m 657 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 85\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 6.7702e-04 - acc: 1.0000 - val_loss: 0.0021 - val_acc: 0.9997\n",
      "Q 30+849 \n",
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      "\u001b[92m☑\u001b[0m 879 \n",
      "---\n",
      "Q 8+650  \n",
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      "\u001b[92m☑\u001b[0m 658 \n",
      "---\n",
      "Q 24+576 \n",
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      "\u001b[92m☑\u001b[0m 600 \n",
      "---\n",
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      "T 632 \n",
      "\u001b[92m☑\u001b[0m 632 \n",
      "---\n",
      "Q 7+986  \n",
      "T 993 \n",
      "\u001b[92m☑\u001b[0m 993 \n",
      "---\n",
      "Q 547+85 \n",
      "T 632 \n",
      "\u001b[92m☑\u001b[0m 632 \n",
      "---\n",
      "Q 968+2  \n",
      "T 970 \n",
      "\u001b[92m☑\u001b[0m 970 \n",
      "---\n",
      "Q 132+50 \n",
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      "\u001b[92m☑\u001b[0m 182 \n",
      "---\n",
      "Q 813+684\n",
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      "\u001b[92m☑\u001b[0m 1497\n",
      "---\n",
      "Q 658+706\n",
      "T 1364\n",
      "\u001b[92m☑\u001b[0m 1364\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 86\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 5.8183e-04 - acc: 1.0000 - val_loss: 0.0021 - val_acc: 0.9996\n",
      "Q 881+0  \n",
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      "\u001b[92m☑\u001b[0m 881 \n",
      "---\n",
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      "T 1686\n",
      "\u001b[92m☑\u001b[0m 1686\n",
      "---\n",
      "Q 17+767 \n",
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      "\u001b[92m☑\u001b[0m 784 \n",
      "---\n",
      "Q 372+185\n",
      "T 557 \n",
      "\u001b[92m☑\u001b[0m 557 \n",
      "---\n",
      "Q 217+338\n",
      "T 555 \n",
      "\u001b[92m☑\u001b[0m 555 \n",
      "---\n",
      "Q 129+22 \n",
      "T 151 \n",
      "\u001b[92m☑\u001b[0m 151 \n",
      "---\n",
      "Q 557+7  \n",
      "T 564 \n",
      "\u001b[92m☑\u001b[0m 564 \n",
      "---\n",
      "Q 997+885\n",
      "T 1882\n",
      "\u001b[92m☑\u001b[0m 1882\n",
      "---\n",
      "Q 880+63 \n",
      "T 943 \n",
      "\u001b[92m☑\u001b[0m 943 \n",
      "---\n",
      "Q 592+97 \n",
      "T 689 \n",
      "\u001b[92m☑\u001b[0m 689 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 87\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 32s - loss: 8.8703e-04 - acc: 0.9999 - val_loss: 0.0020 - val_acc: 0.9996\n",
      "Q 672+990\n",
      "T 1662\n",
      "\u001b[92m☑\u001b[0m 1662\n",
      "---\n",
      "Q 54+402 \n",
      "T 456 \n",
      "\u001b[92m☑\u001b[0m 456 \n",
      "---\n",
      "Q 70+201 \n",
      "T 271 \n",
      "\u001b[92m☑\u001b[0m 271 \n",
      "---\n",
      "Q 24+825 \n",
      "T 849 \n",
      "\u001b[92m☑\u001b[0m 849 \n",
      "---\n",
      "Q 93+50  \n",
      "T 143 \n",
      "\u001b[92m☑\u001b[0m 143 \n",
      "---\n",
      "Q 256+678\n",
      "T 934 \n",
      "\u001b[92m☑\u001b[0m 934 \n",
      "---\n",
      "Q 851+661\n",
      "T 1512\n",
      "\u001b[92m☑\u001b[0m 1512\n",
      "---\n",
      "Q 538+736\n",
      "T 1274\n",
      "\u001b[92m☑\u001b[0m 1274\n",
      "---\n",
      "Q 33+109 \n",
      "T 142 \n",
      "\u001b[92m☑\u001b[0m 142 \n",
      "---\n",
      "Q 329+795\n",
      "T 1124\n",
      "\u001b[92m☑\u001b[0m 1124\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 88\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 4.7175e-04 - acc: 1.0000 - val_loss: 0.0019 - val_acc: 0.9996\n",
      "Q 519+38 \n",
      "T 557 \n",
      "\u001b[92m☑\u001b[0m 557 \n",
      "---\n",
      "Q 545+95 \n",
      "T 640 \n",
      "\u001b[92m☑\u001b[0m 640 \n",
      "---\n",
      "Q 331+3  \n",
      "T 334 \n",
      "\u001b[92m☑\u001b[0m 334 \n",
      "---\n",
      "Q 753+44 \n",
      "T 797 \n",
      "\u001b[92m☑\u001b[0m 797 \n",
      "---\n",
      "Q 258+9  \n",
      "T 267 \n",
      "\u001b[92m☑\u001b[0m 267 \n",
      "---\n",
      "Q 31+385 \n",
      "T 416 \n",
      "\u001b[92m☑\u001b[0m 416 \n",
      "---\n",
      "Q 5+939  \n",
      "T 944 \n",
      "\u001b[92m☑\u001b[0m 944 \n",
      "---\n",
      "Q 793+688\n",
      "T 1481\n",
      "\u001b[92m☑\u001b[0m 1481\n",
      "---\n",
      "Q 15+267 \n",
      "T 282 \n",
      "\u001b[92m☑\u001b[0m 282 \n",
      "---\n",
      "Q 977+5  \n",
      "T 982 \n",
      "\u001b[92m☑\u001b[0m 982 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 89\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 3.9875e-04 - acc: 1.0000 - val_loss: 0.0018 - val_acc: 0.9997\n",
      "Q 179+0  \n",
      "T 179 \n",
      "\u001b[92m☑\u001b[0m 179 \n",
      "---\n",
      "Q 320+56 \n",
      "T 376 \n",
      "\u001b[92m☑\u001b[0m 376 \n",
      "---\n",
      "Q 805+29 \n",
      "T 834 \n",
      "\u001b[92m☑\u001b[0m 834 \n",
      "---\n",
      "Q 129+22 \n",
      "T 151 \n",
      "\u001b[92m☑\u001b[0m 151 \n",
      "---\n",
      "Q 27+376 \n",
      "T 403 \n",
      "\u001b[92m☑\u001b[0m 403 \n",
      "---\n",
      "Q 814+43 \n",
      "T 857 \n",
      "\u001b[92m☑\u001b[0m 857 \n",
      "---\n",
      "Q 18+885 \n",
      "T 903 \n",
      "\u001b[92m☑\u001b[0m 903 \n",
      "---\n",
      "Q 50+30  \n",
      "T 80  \n",
      "\u001b[92m☑\u001b[0m 80  \n",
      "---\n",
      "Q 61+34  \n",
      "T 95  \n",
      "\u001b[92m☑\u001b[0m 95  \n",
      "---\n",
      "Q 12+26  \n",
      "T 38  \n",
      "\u001b[92m☑\u001b[0m 38  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 90\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0367 - acc: 0.9900 - val_loss: 0.1267 - val_acc: 0.9598\n",
      "Q 510+11 \n",
      "T 521 \n",
      "\u001b[91m☒\u001b[0m 531 \n",
      "---\n",
      "Q 98+981 \n",
      "T 1079\n",
      "\u001b[92m☑\u001b[0m 1079\n",
      "---\n",
      "Q 181+834\n",
      "T 1015\n",
      "\u001b[92m☑\u001b[0m 1015\n",
      "---\n",
      "Q 51+279 \n",
      "T 330 \n",
      "\u001b[92m☑\u001b[0m 330 \n",
      "---\n",
      "Q 84+623 \n",
      "T 707 \n",
      "\u001b[91m☒\u001b[0m 717 \n",
      "---\n",
      "Q 51+420 \n",
      "T 471 \n",
      "\u001b[92m☑\u001b[0m 471 \n",
      "---\n",
      "Q 263+38 \n",
      "T 301 \n",
      "\u001b[92m☑\u001b[0m 301 \n",
      "---\n",
      "Q 131+572\n",
      "T 703 \n",
      "\u001b[92m☑\u001b[0m 703 \n",
      "---\n",
      "Q 9+605  \n",
      "T 614 \n",
      "\u001b[92m☑\u001b[0m 614 \n",
      "---\n",
      "Q 9+457  \n",
      "T 466 \n",
      "\u001b[92m☑\u001b[0m 466 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 91\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 0.0114 - acc: 0.9968 - val_loss: 0.0046 - val_acc: 0.9987\n",
      "Q 800+852\n",
      "T 1652\n",
      "\u001b[92m☑\u001b[0m 1652\n",
      "---\n",
      "Q 90+721 \n",
      "T 811 \n",
      "\u001b[92m☑\u001b[0m 811 \n",
      "---\n",
      "Q 671+862\n",
      "T 1533\n",
      "\u001b[92m☑\u001b[0m 1533\n",
      "---\n",
      "Q 8+306  \n",
      "T 314 \n",
      "\u001b[92m☑\u001b[0m 314 \n",
      "---\n",
      "Q 334+694\n",
      "T 1028\n",
      "\u001b[92m☑\u001b[0m 1028\n",
      "---\n",
      "Q 42+179 \n",
      "T 221 \n",
      "\u001b[92m☑\u001b[0m 221 \n",
      "---\n",
      "Q 74+35  \n",
      "T 109 \n",
      "\u001b[92m☑\u001b[0m 109 \n",
      "---\n",
      "Q 97+999 \n",
      "T 1096\n",
      "\u001b[92m☑\u001b[0m 1096\n",
      "---\n",
      "Q 528+5  \n",
      "T 533 \n",
      "\u001b[92m☑\u001b[0m 533 \n",
      "---\n",
      "Q 735+86 \n",
      "T 821 \n",
      "\u001b[92m☑\u001b[0m 821 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 92\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 32s - loss: 0.0010 - acc: 1.0000 - val_loss: 0.0025 - val_acc: 0.9997\n",
      "Q 95+657 \n",
      "T 752 \n",
      "\u001b[92m☑\u001b[0m 752 \n",
      "---\n",
      "Q 598+220\n",
      "T 818 \n",
      "\u001b[92m☑\u001b[0m 818 \n",
      "---\n",
      "Q 750+862\n",
      "T 1612\n",
      "\u001b[92m☑\u001b[0m 1612\n",
      "---\n",
      "Q 25+0   \n",
      "T 25  \n",
      "\u001b[92m☑\u001b[0m 25  \n",
      "---\n",
      "Q 402+93 \n",
      "T 495 \n",
      "\u001b[92m☑\u001b[0m 495 \n",
      "---\n",
      "Q 36+675 \n",
      "T 711 \n",
      "\u001b[92m☑\u001b[0m 711 \n",
      "---\n",
      "Q 634+13 \n",
      "T 647 \n",
      "\u001b[92m☑\u001b[0m 647 \n",
      "---\n",
      "Q 97+558 \n",
      "T 655 \n",
      "\u001b[92m☑\u001b[0m 655 \n",
      "---\n",
      "Q 607+1  \n",
      "T 608 \n",
      "\u001b[92m☑\u001b[0m 608 \n",
      "---\n",
      "Q 646+205\n",
      "T 851 \n",
      "\u001b[92m☑\u001b[0m 851 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 93\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 6.6099e-04 - acc: 1.0000 - val_loss: 0.0022 - val_acc: 0.9997\n",
      "Q 51+630 \n",
      "T 681 \n",
      "\u001b[92m☑\u001b[0m 681 \n",
      "---\n",
      "Q 3+461  \n",
      "T 464 \n",
      "\u001b[92m☑\u001b[0m 464 \n",
      "---\n",
      "Q 760+460\n",
      "T 1220\n",
      "\u001b[92m☑\u001b[0m 1220\n",
      "---\n",
      "Q 688+55 \n",
      "T 743 \n",
      "\u001b[92m☑\u001b[0m 743 \n",
      "---\n",
      "Q 665+59 \n",
      "T 724 \n",
      "\u001b[92m☑\u001b[0m 724 \n",
      "---\n",
      "Q 5+259  \n",
      "T 264 \n",
      "\u001b[92m☑\u001b[0m 264 \n",
      "---\n",
      "Q 115+5  \n",
      "T 120 \n",
      "\u001b[92m☑\u001b[0m 120 \n",
      "---\n",
      "Q 256+678\n",
      "T 934 \n",
      "\u001b[92m☑\u001b[0m 934 \n",
      "---\n",
      "Q 3+965  \n",
      "T 968 \n",
      "\u001b[92m☑\u001b[0m 968 \n",
      "---\n",
      "Q 325+78 \n",
      "T 403 \n",
      "\u001b[92m☑\u001b[0m 403 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 94\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 5.4595e-04 - acc: 1.0000 - val_loss: 0.0020 - val_acc: 0.9997\n",
      "Q 190+65 \n",
      "T 255 \n",
      "\u001b[92m☑\u001b[0m 255 \n",
      "---\n",
      "Q 817+986\n",
      "T 1803\n",
      "\u001b[92m☑\u001b[0m 1803\n",
      "---\n",
      "Q 346+51 \n",
      "T 397 \n",
      "\u001b[92m☑\u001b[0m 397 \n",
      "---\n",
      "Q 59+339 \n",
      "T 398 \n",
      "\u001b[92m☑\u001b[0m 398 \n",
      "---\n",
      "Q 242+31 \n",
      "T 273 \n",
      "\u001b[92m☑\u001b[0m 273 \n",
      "---\n",
      "Q 671+843\n",
      "T 1514\n",
      "\u001b[92m☑\u001b[0m 1514\n",
      "---\n",
      "Q 41+494 \n",
      "T 535 \n",
      "\u001b[92m☑\u001b[0m 535 \n",
      "---\n",
      "Q 726+332\n",
      "T 1058\n",
      "\u001b[92m☑\u001b[0m 1058\n",
      "---\n",
      "Q 355+751\n",
      "T 1106\n",
      "\u001b[92m☑\u001b[0m 1106\n",
      "---\n",
      "Q 939+937\n",
      "T 1876\n",
      "\u001b[92m☑\u001b[0m 1876\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 95\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 32s - loss: 4.7194e-04 - acc: 1.0000 - val_loss: 0.0019 - val_acc: 0.9996\n",
      "Q 935+12 \n",
      "T 947 \n",
      "\u001b[92m☑\u001b[0m 947 \n",
      "---\n",
      "Q 60+496 \n",
      "T 556 \n",
      "\u001b[92m☑\u001b[0m 556 \n",
      "---\n",
      "Q 211+0  \n",
      "T 211 \n",
      "\u001b[92m☑\u001b[0m 211 \n",
      "---\n",
      "Q 117+550\n",
      "T 667 \n",
      "\u001b[92m☑\u001b[0m 667 \n",
      "---\n",
      "Q 510+11 \n",
      "T 521 \n",
      "\u001b[92m☑\u001b[0m 521 \n",
      "---\n",
      "Q 44+954 \n",
      "T 998 \n",
      "\u001b[92m☑\u001b[0m 998 \n",
      "---\n",
      "Q 2+971  \n",
      "T 973 \n",
      "\u001b[92m☑\u001b[0m 973 \n",
      "---\n",
      "Q 0+122  \n",
      "T 122 \n",
      "\u001b[92m☑\u001b[0m 122 \n",
      "---\n",
      "Q 773+8  \n",
      "T 781 \n",
      "\u001b[92m☑\u001b[0m 781 \n",
      "---\n",
      "Q 4+397  \n",
      "T 401 \n",
      "\u001b[92m☑\u001b[0m 401 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 96\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 4.1235e-04 - acc: 1.0000 - val_loss: 0.0017 - val_acc: 0.9997\n",
      "Q 8+54   \n",
      "T 62  \n",
      "\u001b[92m☑\u001b[0m 62  \n",
      "---\n",
      "Q 750+47 \n",
      "T 797 \n",
      "\u001b[92m☑\u001b[0m 797 \n",
      "---\n",
      "Q 379+731\n",
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      "\u001b[92m☑\u001b[0m 1110\n",
      "---\n",
      "Q 449+80 \n",
      "T 529 \n",
      "\u001b[92m☑\u001b[0m 529 \n",
      "---\n",
      "Q 966+7  \n",
      "T 973 \n",
      "\u001b[92m☑\u001b[0m 973 \n",
      "---\n",
      "Q 719+8  \n",
      "T 727 \n",
      "\u001b[92m☑\u001b[0m 727 \n",
      "---\n",
      "Q 123+45 \n",
      "T 168 \n",
      "\u001b[92m☑\u001b[0m 168 \n",
      "---\n",
      "Q 73+459 \n",
      "T 532 \n",
      "\u001b[92m☑\u001b[0m 532 \n",
      "---\n",
      "Q 740+542\n",
      "T 1282\n",
      "\u001b[92m☑\u001b[0m 1282\n",
      "---\n",
      "Q 84+843 \n",
      "T 927 \n",
      "\u001b[92m☑\u001b[0m 927 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 97\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 30s - loss: 3.6908e-04 - acc: 1.0000 - val_loss: 0.0018 - val_acc: 0.9997\n",
      "Q 2+126  \n",
      "T 128 \n",
      "\u001b[92m☑\u001b[0m 128 \n",
      "---\n",
      "Q 79+842 \n",
      "T 921 \n",
      "\u001b[92m☑\u001b[0m 921 \n",
      "---\n",
      "Q 768+6  \n",
      "T 774 \n",
      "\u001b[92m☑\u001b[0m 774 \n",
      "---\n",
      "Q 937+360\n",
      "T 1297\n",
      "\u001b[92m☑\u001b[0m 1297\n",
      "---\n",
      "Q 22+1   \n",
      "T 23  \n",
      "\u001b[92m☑\u001b[0m 23  \n",
      "---\n",
      "Q 449+80 \n",
      "T 529 \n",
      "\u001b[92m☑\u001b[0m 529 \n",
      "---\n",
      "Q 590+237\n",
      "T 827 \n",
      "\u001b[92m☑\u001b[0m 827 \n",
      "---\n",
      "Q 1+258  \n",
      "T 259 \n",
      "\u001b[92m☑\u001b[0m 259 \n",
      "---\n",
      "Q 98+657 \n",
      "T 755 \n",
      "\u001b[92m☑\u001b[0m 755 \n",
      "---\n",
      "Q 426+67 \n",
      "T 493 \n",
      "\u001b[92m☑\u001b[0m 493 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 98\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 29s - loss: 3.5174e-04 - acc: 1.0000 - val_loss: 0.0017 - val_acc: 0.9997\n",
      "Q 696+25 \n",
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      "\u001b[92m☑\u001b[0m 721 \n",
      "---\n",
      "Q 90+606 \n",
      "T 696 \n",
      "\u001b[92m☑\u001b[0m 696 \n",
      "---\n",
      "Q 49+95  \n",
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      "\u001b[92m☑\u001b[0m 144 \n",
      "---\n",
      "Q 438+345\n",
      "T 783 \n",
      "\u001b[92m☑\u001b[0m 783 \n",
      "---\n",
      "Q 282+4  \n",
      "T 286 \n",
      "\u001b[92m☑\u001b[0m 286 \n",
      "---\n",
      "Q 737+303\n",
      "T 1040\n",
      "\u001b[92m☑\u001b[0m 1040\n",
      "---\n",
      "Q 511+4  \n",
      "T 515 \n",
      "\u001b[92m☑\u001b[0m 515 \n",
      "---\n",
      "Q 29+400 \n",
      "T 429 \n",
      "\u001b[92m☑\u001b[0m 429 \n",
      "---\n",
      "Q 2+372  \n",
      "T 374 \n",
      "\u001b[92m☑\u001b[0m 374 \n",
      "---\n",
      "Q 38+85  \n",
      "T 123 \n",
      "\u001b[92m☑\u001b[0m 123 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 99\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 3.2164e-04 - acc: 1.0000 - val_loss: 0.0029 - val_acc: 0.9994\n",
      "Q 5+529  \n",
      "T 534 \n",
      "\u001b[92m☑\u001b[0m 534 \n",
      "---\n",
      "Q 444+640\n",
      "T 1084\n",
      "\u001b[92m☑\u001b[0m 1084\n",
      "---\n",
      "Q 96+74  \n",
      "T 170 \n",
      "\u001b[92m☑\u001b[0m 170 \n",
      "---\n",
      "Q 93+50  \n",
      "T 143 \n",
      "\u001b[92m☑\u001b[0m 143 \n",
      "---\n",
      "Q 40+59  \n",
      "T 99  \n",
      "\u001b[92m☑\u001b[0m 99  \n",
      "---\n",
      "Q 325+257\n",
      "T 582 \n",
      "\u001b[92m☑\u001b[0m 582 \n",
      "---\n",
      "Q 8+901  \n",
      "T 909 \n",
      "\u001b[92m☑\u001b[0m 909 \n",
      "---\n",
      "Q 47+20  \n",
      "T 67  \n",
      "\u001b[92m☑\u001b[0m 67  \n",
      "---\n",
      "Q 543+21 \n",
      "T 564 \n",
      "\u001b[92m☑\u001b[0m 564 \n",
      "---\n",
      "Q 837+20 \n",
      "T 857 \n",
      "\u001b[92m☑\u001b[0m 857 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 100\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0428 - acc: 0.9881 - val_loss: 0.0072 - val_acc: 0.9980\n",
      "Q 962+624\n",
      "T 1586\n",
      "\u001b[92m☑\u001b[0m 1586\n",
      "---\n",
      "Q 132+47 \n",
      "T 179 \n",
      "\u001b[92m☑\u001b[0m 179 \n",
      "---\n",
      "Q 828+602\n",
      "T 1430\n",
      "\u001b[92m☑\u001b[0m 1430\n",
      "---\n",
      "Q 15+933 \n",
      "T 948 \n",
      "\u001b[92m☑\u001b[0m 948 \n",
      "---\n",
      "Q 319+58 \n",
      "T 377 \n",
      "\u001b[92m☑\u001b[0m 377 \n",
      "---\n",
      "Q 11+365 \n",
      "T 376 \n",
      "\u001b[92m☑\u001b[0m 376 \n",
      "---\n",
      "Q 623+19 \n",
      "T 642 \n",
      "\u001b[92m☑\u001b[0m 642 \n",
      "---\n",
      "Q 270+61 \n",
      "T 331 \n",
      "\u001b[92m☑\u001b[0m 331 \n",
      "---\n",
      "Q 60+294 \n",
      "T 354 \n",
      "\u001b[92m☑\u001b[0m 354 \n",
      "---\n",
      "Q 312+211\n",
      "T 523 \n",
      "\u001b[92m☑\u001b[0m 523 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 101\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 0.0019 - acc: 0.9998 - val_loss: 0.0026 - val_acc: 0.9994\n",
      "Q 685+394\n",
      "T 1079\n",
      "\u001b[92m☑\u001b[0m 1079\n",
      "---\n",
      "Q 1+196  \n",
      "T 197 \n",
      "\u001b[92m☑\u001b[0m 197 \n",
      "---\n",
      "Q 65+259 \n",
      "T 324 \n",
      "\u001b[92m☑\u001b[0m 324 \n",
      "---\n",
      "Q 77+139 \n",
      "T 216 \n",
      "\u001b[92m☑\u001b[0m 216 \n",
      "---\n",
      "Q 456+816\n",
      "T 1272\n",
      "\u001b[92m☑\u001b[0m 1272\n",
      "---\n",
      "Q 816+633\n",
      "T 1449\n",
      "\u001b[92m☑\u001b[0m 1449\n",
      "---\n",
      "Q 87+294 \n",
      "T 381 \n",
      "\u001b[92m☑\u001b[0m 381 \n",
      "---\n",
      "Q 9+858  \n",
      "T 867 \n",
      "\u001b[92m☑\u001b[0m 867 \n",
      "---\n",
      "Q 787+894\n",
      "T 1681\n",
      "\u001b[92m☑\u001b[0m 1681\n",
      "---\n",
      "Q 124+25 \n",
      "T 149 \n",
      "\u001b[92m☑\u001b[0m 149 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 102\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 6.6114e-04 - acc: 1.0000 - val_loss: 0.0023 - val_acc: 0.9996\n",
      "Q 949+404\n",
      "T 1353\n",
      "\u001b[92m☑\u001b[0m 1353\n",
      "---\n",
      "Q 9+593  \n",
      "T 602 \n",
      "\u001b[92m☑\u001b[0m 602 \n",
      "---\n",
      "Q 18+76  \n",
      "T 94  \n",
      "\u001b[92m☑\u001b[0m 94  \n",
      "---\n",
      "Q 913+501\n",
      "T 1414\n",
      "\u001b[92m☑\u001b[0m 1414\n",
      "---\n",
      "Q 414+256\n",
      "T 670 \n",
      "\u001b[92m☑\u001b[0m 670 \n",
      "---\n",
      "Q 6+448  \n",
      "T 454 \n",
      "\u001b[92m☑\u001b[0m 454 \n",
      "---\n",
      "Q 641+62 \n",
      "T 703 \n",
      "\u001b[92m☑\u001b[0m 703 \n",
      "---\n",
      "Q 59+761 \n",
      "T 820 \n",
      "\u001b[92m☑\u001b[0m 820 \n",
      "---\n",
      "Q 15+862 \n",
      "T 877 \n",
      "\u001b[92m☑\u001b[0m 877 \n",
      "---\n",
      "Q 210+497\n",
      "T 707 \n",
      "\u001b[92m☑\u001b[0m 707 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 103\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 30s - loss: 4.9612e-04 - acc: 1.0000 - val_loss: 0.0019 - val_acc: 0.9996\n",
      "Q 670+13 \n",
      "T 683 \n",
      "\u001b[92m☑\u001b[0m 683 \n",
      "---\n",
      "Q 1+35   \n",
      "T 36  \n",
      "\u001b[92m☑\u001b[0m 36  \n",
      "---\n",
      "Q 6+438  \n",
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      "\u001b[92m☑\u001b[0m 444 \n",
      "---\n",
      "Q 196+208\n",
      "T 404 \n",
      "\u001b[92m☑\u001b[0m 404 \n",
      "---\n",
      "Q 344+7  \n",
      "T 351 \n",
      "\u001b[92m☑\u001b[0m 351 \n",
      "---\n",
      "Q 893+506\n",
      "T 1399\n",
      "\u001b[92m☑\u001b[0m 1399\n",
      "---\n",
      "Q 729+466\n",
      "T 1195\n",
      "\u001b[92m☑\u001b[0m 1195\n",
      "---\n",
      "Q 529+59 \n",
      "T 588 \n",
      "\u001b[92m☑\u001b[0m 588 \n",
      "---\n",
      "Q 7+169  \n",
      "T 176 \n",
      "\u001b[92m☑\u001b[0m 176 \n",
      "---\n",
      "Q 135+12 \n",
      "T 147 \n",
      "\u001b[92m☑\u001b[0m 147 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 104\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 32s - loss: 4.2308e-04 - acc: 1.0000 - val_loss: 0.0018 - val_acc: 0.9996\n",
      "Q 736+17 \n",
      "T 753 \n",
      "\u001b[92m☑\u001b[0m 753 \n",
      "---\n",
      "Q 830+271\n",
      "T 1101\n",
      "\u001b[92m☑\u001b[0m 1101\n",
      "---\n",
      "Q 732+92 \n",
      "T 824 \n",
      "\u001b[92m☑\u001b[0m 824 \n",
      "---\n",
      "Q 0+31   \n",
      "T 31  \n",
      "\u001b[92m☑\u001b[0m 31  \n",
      "---\n",
      "Q 4+981  \n",
      "T 985 \n",
      "\u001b[92m☑\u001b[0m 985 \n",
      "---\n",
      "Q 1+442  \n",
      "T 443 \n",
      "\u001b[92m☑\u001b[0m 443 \n",
      "---\n",
      "Q 383+43 \n",
      "T 426 \n",
      "\u001b[92m☑\u001b[0m 426 \n",
      "---\n",
      "Q 122+7  \n",
      "T 129 \n",
      "\u001b[92m☑\u001b[0m 129 \n",
      "---\n",
      "Q 917+490\n",
      "T 1407\n",
      "\u001b[92m☑\u001b[0m 1407\n",
      "---\n",
      "Q 3+311  \n",
      "T 314 \n",
      "\u001b[92m☑\u001b[0m 314 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 105\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 31s - loss: 3.6788e-04 - acc: 1.0000 - val_loss: 0.0017 - val_acc: 0.9996\n",
      "Q 51+553 \n",
      "T 604 \n",
      "\u001b[92m☑\u001b[0m 604 \n",
      "---\n",
      "Q 23+800 \n",
      "T 823 \n",
      "\u001b[92m☑\u001b[0m 823 \n",
      "---\n",
      "Q 711+365\n",
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      "\u001b[92m☑\u001b[0m 1076\n",
      "---\n",
      "Q 12+709 \n",
      "T 721 \n",
      "\u001b[92m☑\u001b[0m 721 \n",
      "---\n",
      "Q 844+289\n",
      "T 1133\n",
      "\u001b[92m☑\u001b[0m 1133\n",
      "---\n",
      "Q 867+478\n",
      "T 1345\n",
      "\u001b[92m☑\u001b[0m 1345\n",
      "---\n",
      "Q 538+408\n",
      "T 946 \n",
      "\u001b[92m☑\u001b[0m 946 \n",
      "---\n",
      "Q 26+963 \n",
      "T 989 \n",
      "\u001b[92m☑\u001b[0m 989 \n",
      "---\n",
      "Q 834+713\n",
      "T 1547\n",
      "\u001b[92m☑\u001b[0m 1547\n",
      "---\n",
      "Q 50+75  \n",
      "T 125 \n",
      "\u001b[92m☑\u001b[0m 125 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 106\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 20s - loss: 3.3169e-04 - acc: 1.0000 - val_loss: 0.0017 - val_acc: 0.9994\n",
      "Q 33+109 \n",
      "T 142 \n",
      "\u001b[92m☑\u001b[0m 142 \n",
      "---\n",
      "Q 12+63  \n",
      "T 75  \n",
      "\u001b[92m☑\u001b[0m 75  \n",
      "---\n",
      "Q 51+630 \n",
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      "\u001b[92m☑\u001b[0m 681 \n",
      "---\n",
      "Q 325+78 \n",
      "T 403 \n",
      "\u001b[92m☑\u001b[0m 403 \n",
      "---\n",
      "Q 39+96  \n",
      "T 135 \n",
      "\u001b[92m☑\u001b[0m 135 \n",
      "---\n",
      "Q 9+783  \n",
      "T 792 \n",
      "\u001b[92m☑\u001b[0m 792 \n",
      "---\n",
      "Q 278+59 \n",
      "T 337 \n",
      "\u001b[92m☑\u001b[0m 337 \n",
      "---\n",
      "Q 603+926\n",
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      "\u001b[92m☑\u001b[0m 1529\n",
      "---\n",
      "Q 749+64 \n",
      "T 813 \n",
      "\u001b[92m☑\u001b[0m 813 \n",
      "---\n",
      "Q 28+970 \n",
      "T 998 \n",
      "\u001b[92m☑\u001b[0m 998 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 107\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 3.1954e-04 - acc: 1.0000 - val_loss: 0.0016 - val_acc: 0.9996\n",
      "Q 945+842\n",
      "T 1787\n",
      "\u001b[92m☑\u001b[0m 1787\n",
      "---\n",
      "Q 873+0  \n",
      "T 873 \n",
      "\u001b[92m☑\u001b[0m 873 \n",
      "---\n",
      "Q 819+182\n",
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      "\u001b[92m☑\u001b[0m 1001\n",
      "---\n",
      "Q 906+38 \n",
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      "\u001b[92m☑\u001b[0m 944 \n",
      "---\n",
      "Q 151+86 \n",
      "T 237 \n",
      "\u001b[92m☑\u001b[0m 237 \n",
      "---\n",
      "Q 59+226 \n",
      "T 285 \n",
      "\u001b[92m☑\u001b[0m 285 \n",
      "---\n",
      "Q 96+595 \n",
      "T 691 \n",
      "\u001b[92m☑\u001b[0m 691 \n",
      "---\n",
      "Q 353+47 \n",
      "T 400 \n",
      "\u001b[92m☑\u001b[0m 400 \n",
      "---\n",
      "Q 234+240\n",
      "T 474 \n",
      "\u001b[92m☑\u001b[0m 474 \n",
      "---\n",
      "Q 941+227\n",
      "T 1168\n",
      "\u001b[92m☑\u001b[0m 1168\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 108\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 2.6826e-04 - acc: 1.0000 - val_loss: 0.0018 - val_acc: 0.9994\n",
      "Q 2+373  \n",
      "T 375 \n",
      "\u001b[92m☑\u001b[0m 375 \n",
      "---\n",
      "Q 531+79 \n",
      "T 610 \n",
      "\u001b[92m☑\u001b[0m 610 \n",
      "---\n",
      "Q 508+2  \n",
      "T 510 \n",
      "\u001b[92m☑\u001b[0m 510 \n",
      "---\n",
      "Q 84+738 \n",
      "T 822 \n",
      "\u001b[92m☑\u001b[0m 822 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 627 \n",
      "---\n",
      "Q 592+257\n",
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      "\u001b[92m☑\u001b[0m 849 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1352\n",
      "---\n",
      "Q 41+35  \n",
      "T 76  \n",
      "\u001b[92m☑\u001b[0m 76  \n",
      "---\n",
      "Q 437+90 \n",
      "T 527 \n",
      "\u001b[92m☑\u001b[0m 527 \n",
      "---\n",
      "Q 75+26  \n",
      "T 101 \n",
      "\u001b[92m☑\u001b[0m 101 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 109\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 0.0355 - acc: 0.9900 - val_loss: 0.0243 - val_acc: 0.9917.99\n",
      "Q 40+926 \n",
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      "\u001b[92m☑\u001b[0m 966 \n",
      "---\n",
      "Q 772+545\n",
      "T 1317\n",
      "\u001b[92m☑\u001b[0m 1317\n",
      "---\n",
      "Q 880+5  \n",
      "T 885 \n",
      "\u001b[92m☑\u001b[0m 885 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 781 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1516\n",
      "---\n",
      "Q 78+202 \n",
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      "\u001b[92m☑\u001b[0m 280 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1079\n",
      "---\n",
      "Q 170+481\n",
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      "\u001b[92m☑\u001b[0m 651 \n",
      "---\n",
      "Q 652+366\n",
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      "\u001b[92m☑\u001b[0m 1018\n",
      "---\n",
      "Q 782+10 \n",
      "T 792 \n",
      "\u001b[92m☑\u001b[0m 792 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 110\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 0.0044 - acc: 0.9990 - val_loss: 0.0049 - val_acc: 0.9986\n",
      "Q 37+433 \n",
      "T 470 \n",
      "\u001b[92m☑\u001b[0m 470 \n",
      "---\n",
      "Q 32+21  \n",
      "T 53  \n",
      "\u001b[92m☑\u001b[0m 53  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1035\n",
      "---\n",
      "Q 895+8  \n",
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      "\u001b[92m☑\u001b[0m 903 \n",
      "---\n",
      "Q 300+44 \n",
      "T 344 \n",
      "\u001b[92m☑\u001b[0m 344 \n",
      "---\n",
      "Q 49+449 \n",
      "T 498 \n",
      "\u001b[92m☑\u001b[0m 498 \n",
      "---\n",
      "Q 3+549  \n",
      "T 552 \n",
      "\u001b[92m☑\u001b[0m 552 \n",
      "---\n",
      "Q 969+3  \n",
      "T 972 \n",
      "\u001b[92m☑\u001b[0m 972 \n",
      "---\n",
      "Q 555+27 \n",
      "T 582 \n",
      "\u001b[92m☑\u001b[0m 582 \n",
      "---\n",
      "Q 636+435\n",
      "T 1071\n",
      "\u001b[92m☑\u001b[0m 1071\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 111\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 18s - loss: 8.9508e-04 - acc: 1.0000 - val_loss: 0.0021 - val_acc: 0.9995\n",
      "Q 969+262\n",
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      "\u001b[92m☑\u001b[0m 1231\n",
      "---\n",
      "Q 194+64 \n",
      "T 258 \n",
      "\u001b[92m☑\u001b[0m 258 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1046\n",
      "---\n",
      "Q 56+274 \n",
      "T 330 \n",
      "\u001b[92m☑\u001b[0m 330 \n",
      "---\n",
      "Q 53+69  \n",
      "T 122 \n",
      "\u001b[92m☑\u001b[0m 122 \n",
      "---\n",
      "Q 637+7  \n",
      "T 644 \n",
      "\u001b[92m☑\u001b[0m 644 \n",
      "---\n",
      "Q 964+569\n",
      "T 1533\n",
      "\u001b[92m☑\u001b[0m 1533\n",
      "---\n",
      "Q 45+759 \n",
      "T 804 \n",
      "\u001b[92m☑\u001b[0m 804 \n",
      "---\n",
      "Q 586+7  \n",
      "T 593 \n",
      "\u001b[92m☑\u001b[0m 593 \n",
      "---\n",
      "Q 95+311 \n",
      "T 406 \n",
      "\u001b[92m☑\u001b[0m 406 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 112\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 4.9268e-04 - acc: 1.0000 - val_loss: 0.0018 - val_acc: 0.9996\n",
      "Q 703+31 \n",
      "T 734 \n",
      "\u001b[92m☑\u001b[0m 734 \n",
      "---\n",
      "Q 732+570\n",
      "T 1302\n",
      "\u001b[92m☑\u001b[0m 1302\n",
      "---\n",
      "Q 243+875\n",
      "T 1118\n",
      "\u001b[92m☑\u001b[0m 1118\n",
      "---\n",
      "Q 562+623\n",
      "T 1185\n",
      "\u001b[92m☑\u001b[0m 1185\n",
      "---\n",
      "Q 136+5  \n",
      "T 141 \n",
      "\u001b[92m☑\u001b[0m 141 \n",
      "---\n",
      "Q 7+563  \n",
      "T 570 \n",
      "\u001b[92m☑\u001b[0m 570 \n",
      "---\n",
      "Q 59+761 \n",
      "T 820 \n",
      "\u001b[92m☑\u001b[0m 820 \n",
      "---\n",
      "Q 411+17 \n",
      "T 428 \n",
      "\u001b[92m☑\u001b[0m 428 \n",
      "---\n",
      "Q 513+48 \n",
      "T 561 \n",
      "\u001b[92m☑\u001b[0m 561 \n",
      "---\n",
      "Q 93+21  \n",
      "T 114 \n",
      "\u001b[92m☑\u001b[0m 114 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 113\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 4.0623e-04 - acc: 1.0000 - val_loss: 0.0017 - val_acc: 0.9996\n",
      "Q 756+20 \n",
      "T 776 \n",
      "\u001b[92m☑\u001b[0m 776 \n",
      "---\n",
      "Q 44+29  \n",
      "T 73  \n",
      "\u001b[92m☑\u001b[0m 73  \n",
      "---\n",
      "Q 691+671\n",
      "T 1362\n",
      "\u001b[92m☑\u001b[0m 1362\n",
      "---\n",
      "Q 8+175  \n",
      "T 183 \n",
      "\u001b[92m☑\u001b[0m 183 \n",
      "---\n",
      "Q 314+25 \n",
      "T 339 \n",
      "\u001b[92m☑\u001b[0m 339 \n",
      "---\n",
      "Q 10+75  \n",
      "T 85  \n",
      "\u001b[92m☑\u001b[0m 85  \n",
      "---\n",
      "Q 81+79  \n",
      "T 160 \n",
      "\u001b[92m☑\u001b[0m 160 \n",
      "---\n",
      "Q 457+40 \n",
      "T 497 \n",
      "\u001b[92m☑\u001b[0m 497 \n",
      "---\n",
      "Q 859+865\n",
      "T 1724\n",
      "\u001b[92m☑\u001b[0m 1724\n",
      "---\n",
      "Q 82+940 \n",
      "T 1022\n",
      "\u001b[92m☑\u001b[0m 1022\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 114\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 3.4817e-04 - acc: 1.0000 - val_loss: 0.0016 - val_acc: 0.9997\n",
      "Q 501+910\n",
      "T 1411\n",
      "\u001b[92m☑\u001b[0m 1411\n",
      "---\n",
      "Q 50+502 \n",
      "T 552 \n",
      "\u001b[92m☑\u001b[0m 552 \n",
      "---\n",
      "Q 330+6  \n",
      "T 336 \n",
      "\u001b[92m☑\u001b[0m 336 \n",
      "---\n",
      "Q 966+7  \n",
      "T 973 \n",
      "\u001b[92m☑\u001b[0m 973 \n",
      "---\n",
      "Q 268+53 \n",
      "T 321 \n",
      "\u001b[92m☑\u001b[0m 321 \n",
      "---\n",
      "Q 56+41  \n",
      "T 97  \n",
      "\u001b[92m☑\u001b[0m 97  \n",
      "---\n",
      "Q 393+76 \n",
      "T 469 \n",
      "\u001b[92m☑\u001b[0m 469 \n",
      "---\n",
      "Q 2+527  \n",
      "T 529 \n",
      "\u001b[92m☑\u001b[0m 529 \n",
      "---\n",
      "Q 867+68 \n",
      "T 935 \n",
      "\u001b[92m☑\u001b[0m 935 \n",
      "---\n",
      "Q 237+17 \n",
      "T 254 \n",
      "\u001b[92m☑\u001b[0m 254 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 115\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 3.0627e-04 - acc: 1.0000 - val_loss: 0.0016 - val_acc: 0.9997\n",
      "Q 85+127 \n",
      "T 212 \n",
      "\u001b[92m☑\u001b[0m 212 \n",
      "---\n",
      "Q 0+58   \n",
      "T 58  \n",
      "\u001b[92m☑\u001b[0m 58  \n",
      "---\n",
      "Q 296+68 \n",
      "T 364 \n",
      "\u001b[92m☑\u001b[0m 364 \n",
      "---\n",
      "Q 99+475 \n",
      "T 574 \n",
      "\u001b[92m☑\u001b[0m 574 \n",
      "---\n",
      "Q 863+9  \n",
      "T 872 \n",
      "\u001b[92m☑\u001b[0m 872 \n",
      "---\n",
      "Q 274+19 \n",
      "T 293 \n",
      "\u001b[92m☑\u001b[0m 293 \n",
      "---\n",
      "Q 569+3  \n",
      "T 572 \n",
      "\u001b[92m☑\u001b[0m 572 \n",
      "---\n",
      "Q 286+42 \n",
      "T 328 \n",
      "\u001b[92m☑\u001b[0m 328 \n",
      "---\n",
      "Q 122+7  \n",
      "T 129 \n",
      "\u001b[92m☑\u001b[0m 129 \n",
      "---\n",
      "Q 108+33 \n",
      "T 141 \n",
      "\u001b[92m☑\u001b[0m 141 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 116\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.7302e-04 - acc: 1.0000 - val_loss: 0.0015 - val_acc: 0.9997\n",
      "Q 70+59  \n",
      "T 129 \n",
      "\u001b[92m☑\u001b[0m 129 \n",
      "---\n",
      "Q 3+163  \n",
      "T 166 \n",
      "\u001b[92m☑\u001b[0m 166 \n",
      "---\n",
      "Q 530+1  \n",
      "T 531 \n",
      "\u001b[92m☑\u001b[0m 531 \n",
      "---\n",
      "Q 907+264\n",
      "T 1171\n",
      "\u001b[92m☑\u001b[0m 1171\n",
      "---\n",
      "Q 669+68 \n",
      "T 737 \n",
      "\u001b[92m☑\u001b[0m 737 \n",
      "---\n",
      "Q 864+50 \n",
      "T 914 \n",
      "\u001b[92m☑\u001b[0m 914 \n",
      "---\n",
      "Q 72+271 \n",
      "T 343 \n",
      "\u001b[92m☑\u001b[0m 343 \n",
      "---\n",
      "Q 252+17 \n",
      "T 269 \n",
      "\u001b[92m☑\u001b[0m 269 \n",
      "---\n",
      "Q 55+550 \n",
      "T 605 \n",
      "\u001b[92m☑\u001b[0m 605 \n",
      "---\n",
      "Q 5+157  \n",
      "T 162 \n",
      "\u001b[92m☑\u001b[0m 162 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 117\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.4437e-04 - acc: 1.0000 - val_loss: 0.0013 - val_acc: 0.9998\n",
      "Q 722+0  \n",
      "T 722 \n",
      "\u001b[92m☑\u001b[0m 722 \n",
      "---\n",
      "Q 3+630  \n",
      "T 633 \n",
      "\u001b[92m☑\u001b[0m 633 \n",
      "---\n",
      "Q 77+35  \n",
      "T 112 \n",
      "\u001b[92m☑\u001b[0m 112 \n",
      "---\n",
      "Q 835+5  \n",
      "T 840 \n",
      "\u001b[92m☑\u001b[0m 840 \n",
      "---\n",
      "Q 62+248 \n",
      "T 310 \n",
      "\u001b[92m☑\u001b[0m 310 \n",
      "---\n",
      "Q 110+0  \n",
      "T 110 \n",
      "\u001b[92m☑\u001b[0m 110 \n",
      "---\n",
      "Q 726+700\n",
      "T 1426\n",
      "\u001b[92m☑\u001b[0m 1426\n",
      "---\n",
      "Q 97+97  \n",
      "T 194 \n",
      "\u001b[92m☑\u001b[0m 194 \n",
      "---\n",
      "Q 785+112\n",
      "T 897 \n",
      "\u001b[92m☑\u001b[0m 897 \n",
      "---\n",
      "Q 55+431 \n",
      "T 486 \n",
      "\u001b[92m☑\u001b[0m 486 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 118\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.5606e-04 - acc: 1.0000 - val_loss: 0.0019 - val_acc: 0.9996\n",
      "Q 40+729 \n",
      "T 769 \n",
      "\u001b[92m☑\u001b[0m 769 \n",
      "---\n",
      "Q 880+63 \n",
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      "\u001b[92m☑\u001b[0m 943 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 814 \n",
      "---\n",
      "Q 72+505 \n",
      "T 577 \n",
      "\u001b[92m☑\u001b[0m 577 \n",
      "---\n",
      "Q 133+112\n",
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      "\u001b[92m☑\u001b[0m 245 \n",
      "---\n",
      "Q 387+165\n",
      "T 552 \n",
      "\u001b[92m☑\u001b[0m 552 \n",
      "---\n",
      "Q 873+27 \n",
      "T 900 \n",
      "\u001b[92m☑\u001b[0m 900 \n",
      "---\n",
      "Q 351+975\n",
      "T 1326\n",
      "\u001b[92m☑\u001b[0m 1326\n",
      "---\n",
      "Q 830+597\n",
      "T 1427\n",
      "\u001b[92m☑\u001b[0m 1427\n",
      "---\n",
      "Q 113+480\n",
      "T 593 \n",
      "\u001b[92m☑\u001b[0m 593 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 119\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 0.0364 - acc: 0.9903 - val_loss: 0.0044 - val_acc: 0.9990\n",
      "Q 112+74 \n",
      "T 186 \n",
      "\u001b[92m☑\u001b[0m 186 \n",
      "---\n",
      "Q 55+619 \n",
      "T 674 \n",
      "\u001b[92m☑\u001b[0m 674 \n",
      "---\n",
      "Q 873+53 \n",
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      "\u001b[92m☑\u001b[0m 926 \n",
      "---\n",
      "Q 62+674 \n",
      "T 736 \n",
      "\u001b[92m☑\u001b[0m 736 \n",
      "---\n",
      "Q 537+0  \n",
      "T 537 \n",
      "\u001b[92m☑\u001b[0m 537 \n",
      "---\n",
      "Q 40+389 \n",
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      "\u001b[92m☑\u001b[0m 429 \n",
      "---\n",
      "Q 481+69 \n",
      "T 550 \n",
      "\u001b[92m☑\u001b[0m 550 \n",
      "---\n",
      "Q 245+83 \n",
      "T 328 \n",
      "\u001b[92m☑\u001b[0m 328 \n",
      "---\n",
      "Q 6+142  \n",
      "T 148 \n",
      "\u001b[92m☑\u001b[0m 148 \n",
      "---\n",
      "Q 873+371\n",
      "T 1244\n",
      "\u001b[92m☑\u001b[0m 1244\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 120\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 0.0028 - acc: 0.9994 - val_loss: 0.0053 - val_acc: 0.9984\n",
      "Q 23+313 \n",
      "T 336 \n",
      "\u001b[92m☑\u001b[0m 336 \n",
      "---\n",
      "Q 28+475 \n",
      "T 503 \n",
      "\u001b[92m☑\u001b[0m 503 \n",
      "---\n",
      "Q 9+502  \n",
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      "\u001b[92m☑\u001b[0m 511 \n",
      "---\n",
      "Q 455+4  \n",
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      "\u001b[92m☑\u001b[0m 459 \n",
      "---\n",
      "Q 598+90 \n",
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      "\u001b[92m☑\u001b[0m 688 \n",
      "---\n",
      "Q 789+9  \n",
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      "\u001b[92m☑\u001b[0m 798 \n",
      "---\n",
      "Q 340+4  \n",
      "T 344 \n",
      "\u001b[92m☑\u001b[0m 344 \n",
      "---\n",
      "Q 533+53 \n",
      "T 586 \n",
      "\u001b[92m☑\u001b[0m 586 \n",
      "---\n",
      "Q 639+84 \n",
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      "\u001b[92m☑\u001b[0m 723 \n",
      "---\n",
      "Q 75+648 \n",
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      "\u001b[92m☑\u001b[0m 723 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 121\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 0.0014 - acc: 0.9997 - val_loss: 0.0024 - val_acc: 0.9995\n",
      "Q 982+547\n",
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      "\u001b[92m☑\u001b[0m 1529\n",
      "---\n",
      "Q 873+836\n",
      "T 1709\n",
      "\u001b[92m☑\u001b[0m 1709\n",
      "---\n",
      "Q 66+68  \n",
      "T 134 \n",
      "\u001b[92m☑\u001b[0m 134 \n",
      "---\n",
      "Q 123+45 \n",
      "T 168 \n",
      "\u001b[92m☑\u001b[0m 168 \n",
      "---\n",
      "Q 46+472 \n",
      "T 518 \n",
      "\u001b[92m☑\u001b[0m 518 \n",
      "---\n",
      "Q 614+18 \n",
      "T 632 \n",
      "\u001b[92m☑\u001b[0m 632 \n",
      "---\n",
      "Q 897+78 \n",
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      "\u001b[92m☑\u001b[0m 975 \n",
      "---\n",
      "Q 973+554\n",
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      "\u001b[92m☑\u001b[0m 1527\n",
      "---\n",
      "Q 381+1  \n",
      "T 382 \n",
      "\u001b[92m☑\u001b[0m 382 \n",
      "---\n",
      "Q 833+902\n",
      "T 1735\n",
      "\u001b[92m☑\u001b[0m 1735\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 122\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 4.0803e-04 - acc: 1.0000 - val_loss: 0.0019 - val_acc: 0.9996\n",
      "Q 215+213\n",
      "T 428 \n",
      "\u001b[92m☑\u001b[0m 428 \n",
      "---\n",
      "Q 688+93 \n",
      "T 781 \n",
      "\u001b[92m☑\u001b[0m 781 \n",
      "---\n",
      "Q 32+561 \n",
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      "\u001b[92m☑\u001b[0m 593 \n",
      "---\n",
      "Q 1+864  \n",
      "T 865 \n",
      "\u001b[92m☑\u001b[0m 865 \n",
      "---\n",
      "Q 38+85  \n",
      "T 123 \n",
      "\u001b[92m☑\u001b[0m 123 \n",
      "---\n",
      "Q 327+42 \n",
      "T 369 \n",
      "\u001b[92m☑\u001b[0m 369 \n",
      "---\n",
      "Q 119+356\n",
      "T 475 \n",
      "\u001b[92m☑\u001b[0m 475 \n",
      "---\n",
      "Q 0+776  \n",
      "T 776 \n",
      "\u001b[92m☑\u001b[0m 776 \n",
      "---\n",
      "Q 737+80 \n",
      "T 817 \n",
      "\u001b[92m☑\u001b[0m 817 \n",
      "---\n",
      "Q 457+129\n",
      "T 586 \n",
      "\u001b[92m☑\u001b[0m 586 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 123\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 3.3046e-04 - acc: 1.0000 - val_loss: 0.0018 - val_acc: 0.9997\n",
      "Q 99+53  \n",
      "T 152 \n",
      "\u001b[92m☑\u001b[0m 152 \n",
      "---\n",
      "Q 829+42 \n",
      "T 871 \n",
      "\u001b[92m☑\u001b[0m 871 \n",
      "---\n",
      "Q 46+579 \n",
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      "\u001b[92m☑\u001b[0m 625 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1876\n",
      "---\n",
      "Q 87+531 \n",
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      "\u001b[92m☑\u001b[0m 618 \n",
      "---\n",
      "Q 34+694 \n",
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      "\u001b[92m☑\u001b[0m 728 \n",
      "---\n",
      "Q 39+305 \n",
      "T 344 \n",
      "\u001b[92m☑\u001b[0m 344 \n",
      "---\n",
      "Q 40+668 \n",
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      "\u001b[92m☑\u001b[0m 708 \n",
      "---\n",
      "Q 16+997 \n",
      "T 1013\n",
      "\u001b[92m☑\u001b[0m 1013\n",
      "---\n",
      "Q 165+945\n",
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      "\u001b[92m☑\u001b[0m 1110\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 124\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 2.8636e-04 - acc: 1.0000 - val_loss: 0.0017 - val_acc: 0.9997\n",
      "Q 685+394\n",
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      "\u001b[92m☑\u001b[0m 1079\n",
      "---\n",
      "Q 462+81 \n",
      "T 543 \n",
      "\u001b[92m☑\u001b[0m 543 \n",
      "---\n",
      "Q 270+61 \n",
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      "\u001b[92m☑\u001b[0m 331 \n",
      "---\n",
      "Q 127+646\n",
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      "\u001b[92m☑\u001b[0m 773 \n",
      "---\n",
      "Q 990+40 \n",
      "T 1030\n",
      "\u001b[92m☑\u001b[0m 1030\n",
      "---\n",
      "Q 227+29 \n",
      "T 256 \n",
      "\u001b[92m☑\u001b[0m 256 \n",
      "---\n",
      "Q 46+769 \n",
      "T 815 \n",
      "\u001b[92m☑\u001b[0m 815 \n",
      "---\n",
      "Q 129+999\n",
      "T 1128\n",
      "\u001b[92m☑\u001b[0m 1128\n",
      "---\n",
      "Q 965+0  \n",
      "T 965 \n",
      "\u001b[92m☑\u001b[0m 965 \n",
      "---\n",
      "Q 6+690  \n",
      "T 696 \n",
      "\u001b[92m☑\u001b[0m 696 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 125\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 16s - loss: 2.5346e-04 - acc: 1.0000 - val_loss: 0.0016 - val_acc: 0.9996\n",
      "Q 2+401  \n",
      "T 403 \n",
      "\u001b[92m☑\u001b[0m 403 \n",
      "---\n",
      "Q 57+396 \n",
      "T 453 \n",
      "\u001b[92m☑\u001b[0m 453 \n",
      "---\n",
      "Q 94+17  \n",
      "T 111 \n",
      "\u001b[92m☑\u001b[0m 111 \n",
      "---\n",
      "Q 116+47 \n",
      "T 163 \n",
      "\u001b[92m☑\u001b[0m 163 \n",
      "---\n",
      "Q 62+256 \n",
      "T 318 \n",
      "\u001b[92m☑\u001b[0m 318 \n",
      "---\n",
      "Q 16+797 \n",
      "T 813 \n",
      "\u001b[92m☑\u001b[0m 813 \n",
      "---\n",
      "Q 75+516 \n",
      "T 591 \n",
      "\u001b[92m☑\u001b[0m 591 \n",
      "---\n",
      "Q 93+919 \n",
      "T 1012\n",
      "\u001b[92m☑\u001b[0m 1012\n",
      "---\n",
      "Q 163+11 \n",
      "T 174 \n",
      "\u001b[92m☑\u001b[0m 174 \n",
      "---\n",
      "Q 211+121\n",
      "T 332 \n",
      "\u001b[92m☑\u001b[0m 332 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 126\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.2791e-04 - acc: 1.0000 - val_loss: 0.0015 - val_acc: 0.9996\n",
      "Q 308+7  \n",
      "T 315 \n",
      "\u001b[92m☑\u001b[0m 315 \n",
      "---\n",
      "Q 18+24  \n",
      "T 42  \n",
      "\u001b[92m☑\u001b[0m 42  \n",
      "---\n",
      "Q 68+153 \n",
      "T 221 \n",
      "\u001b[92m☑\u001b[0m 221 \n",
      "---\n",
      "Q 5+279  \n",
      "T 284 \n",
      "\u001b[92m☑\u001b[0m 284 \n",
      "---\n",
      "Q 694+2  \n",
      "T 696 \n",
      "\u001b[92m☑\u001b[0m 696 \n",
      "---\n",
      "Q 123+45 \n",
      "T 168 \n",
      "\u001b[92m☑\u001b[0m 168 \n",
      "---\n",
      "Q 367+161\n",
      "T 528 \n",
      "\u001b[92m☑\u001b[0m 528 \n",
      "---\n",
      "Q 703+33 \n",
      "T 736 \n",
      "\u001b[92m☑\u001b[0m 736 \n",
      "---\n",
      "Q 73+318 \n",
      "T 391 \n",
      "\u001b[92m☑\u001b[0m 391 \n",
      "---\n",
      "Q 597+364\n",
      "T 961 \n",
      "\u001b[92m☑\u001b[0m 961 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 127\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.0599e-04 - acc: 1.0000 - val_loss: 0.0015 - val_acc: 0.9997\n",
      "Q 666+299\n",
      "T 965 \n",
      "\u001b[92m☑\u001b[0m 965 \n",
      "---\n",
      "Q 709+393\n",
      "T 1102\n",
      "\u001b[92m☑\u001b[0m 1102\n",
      "---\n",
      "Q 89+18  \n",
      "T 107 \n",
      "\u001b[92m☑\u001b[0m 107 \n",
      "---\n",
      "Q 865+206\n",
      "T 1071\n",
      "\u001b[92m☑\u001b[0m 1071\n",
      "---\n",
      "Q 4+516  \n",
      "T 520 \n",
      "\u001b[92m☑\u001b[0m 520 \n",
      "---\n",
      "Q 42+8   \n",
      "T 50  \n",
      "\u001b[92m☑\u001b[0m 50  \n",
      "---\n",
      "Q 317+92 \n",
      "T 409 \n",
      "\u001b[92m☑\u001b[0m 409 \n",
      "---\n",
      "Q 866+41 \n",
      "T 907 \n",
      "\u001b[92m☑\u001b[0m 907 \n",
      "---\n",
      "Q 724+788\n",
      "T 1512\n",
      "\u001b[92m☑\u001b[0m 1512\n",
      "---\n",
      "Q 453+11 \n",
      "T 464 \n",
      "\u001b[92m☑\u001b[0m 464 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 128\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.0974e-04 - acc: 1.0000 - val_loss: 0.0036 - val_acc: 0.9989\n",
      "Q 140+16 \n",
      "T 156 \n",
      "\u001b[92m☑\u001b[0m 156 \n",
      "---\n",
      "Q 7+812  \n",
      "T 819 \n",
      "\u001b[92m☑\u001b[0m 819 \n",
      "---\n",
      "Q 538+521\n",
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      "\u001b[92m☑\u001b[0m 1059\n",
      "---\n",
      "Q 268+27 \n",
      "T 295 \n",
      "\u001b[92m☑\u001b[0m 295 \n",
      "---\n",
      "Q 8+256  \n",
      "T 264 \n",
      "\u001b[92m☑\u001b[0m 264 \n",
      "---\n",
      "Q 617+691\n",
      "T 1308\n",
      "\u001b[92m☑\u001b[0m 1308\n",
      "---\n",
      "Q 565+549\n",
      "T 1114\n",
      "\u001b[92m☑\u001b[0m 1114\n",
      "---\n",
      "Q 431+5  \n",
      "T 436 \n",
      "\u001b[92m☑\u001b[0m 436 \n",
      "---\n",
      "Q 700+8  \n",
      "T 708 \n",
      "\u001b[92m☑\u001b[0m 708 \n",
      "---\n",
      "Q 867+21 \n",
      "T 888 \n",
      "\u001b[92m☑\u001b[0m 888 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 129\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 0.0410 - acc: 0.9884 - val_loss: 0.0053 - val_acc: 0.9989\n",
      "Q 26+568 \n",
      "T 594 \n",
      "\u001b[92m☑\u001b[0m 594 \n",
      "---\n",
      "Q 174+15 \n",
      "T 189 \n",
      "\u001b[92m☑\u001b[0m 189 \n",
      "---\n",
      "Q 25+44  \n",
      "T 69  \n",
      "\u001b[92m☑\u001b[0m 69  \n",
      "---\n",
      "Q 645+95 \n",
      "T 740 \n",
      "\u001b[92m☑\u001b[0m 740 \n",
      "---\n",
      "Q 117+270\n",
      "T 387 \n",
      "\u001b[92m☑\u001b[0m 387 \n",
      "---\n",
      "Q 42+734 \n",
      "T 776 \n",
      "\u001b[92m☑\u001b[0m 776 \n",
      "---\n",
      "Q 471+33 \n",
      "T 504 \n",
      "\u001b[92m☑\u001b[0m 504 \n",
      "---\n",
      "Q 2+399  \n",
      "T 401 \n",
      "\u001b[92m☑\u001b[0m 401 \n",
      "---\n",
      "Q 497+28 \n",
      "T 525 \n",
      "\u001b[92m☑\u001b[0m 525 \n",
      "---\n",
      "Q 38+902 \n",
      "T 940 \n",
      "\u001b[92m☑\u001b[0m 940 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 130\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 0.0107 - acc: 0.9973 - val_loss: 0.0070 - val_acc: 0.9979\n",
      "Q 990+40 \n",
      "T 1030\n",
      "\u001b[92m☑\u001b[0m 1030\n",
      "---\n",
      "Q 253+709\n",
      "T 962 \n",
      "\u001b[92m☑\u001b[0m 962 \n",
      "---\n",
      "Q 771+867\n",
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      "\u001b[92m☑\u001b[0m 1638\n",
      "---\n",
      "Q 239+379\n",
      "T 618 \n",
      "\u001b[92m☑\u001b[0m 618 \n",
      "---\n",
      "Q 119+29 \n",
      "T 148 \n",
      "\u001b[92m☑\u001b[0m 148 \n",
      "---\n",
      "Q 201+73 \n",
      "T 274 \n",
      "\u001b[92m☑\u001b[0m 274 \n",
      "---\n",
      "Q 81+646 \n",
      "T 727 \n",
      "\u001b[92m☑\u001b[0m 727 \n",
      "---\n",
      "Q 965+0  \n",
      "T 965 \n",
      "\u001b[92m☑\u001b[0m 965 \n",
      "---\n",
      "Q 356+88 \n",
      "T 444 \n",
      "\u001b[92m☑\u001b[0m 444 \n",
      "---\n",
      "Q 794+70 \n",
      "T 864 \n",
      "\u001b[92m☑\u001b[0m 864 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 131\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 0.0013 - acc: 0.9998 - val_loss: 0.0022 - val_acc: 0.9996\n",
      "Q 70+45  \n",
      "T 115 \n",
      "\u001b[92m☑\u001b[0m 115 \n",
      "---\n",
      "Q 99+861 \n",
      "T 960 \n",
      "\u001b[92m☑\u001b[0m 960 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 724 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1027\n",
      "---\n",
      "Q 43+586 \n",
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      "\u001b[92m☑\u001b[0m 629 \n",
      "---\n",
      "Q 765+67 \n",
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      "\u001b[92m☑\u001b[0m 832 \n",
      "---\n",
      "Q 78+968 \n",
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      "\u001b[92m☑\u001b[0m 1046\n",
      "---\n",
      "Q 101+37 \n",
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      "\u001b[92m☑\u001b[0m 138 \n",
      "---\n",
      "Q 751+217\n",
      "T 968 \n",
      "\u001b[92m☑\u001b[0m 968 \n",
      "---\n",
      "Q 92+750 \n",
      "T 842 \n",
      "\u001b[92m☑\u001b[0m 842 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 132\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 4.9136e-04 - acc: 1.0000 - val_loss: 0.0018 - val_acc: 0.9997\n",
      "Q 907+445\n",
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      "\u001b[92m☑\u001b[0m 1352\n",
      "---\n",
      "Q 719+7  \n",
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      "\u001b[92m☑\u001b[0m 726 \n",
      "---\n",
      "Q 93+104 \n",
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      "\u001b[92m☑\u001b[0m 197 \n",
      "---\n",
      "Q 9+11   \n",
      "T 20  \n",
      "\u001b[91m☒\u001b[0m 10  \n",
      "---\n",
      "Q 728+6  \n",
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      "\u001b[92m☑\u001b[0m 734 \n",
      "---\n",
      "Q 28+135 \n",
      "T 163 \n",
      "\u001b[92m☑\u001b[0m 163 \n",
      "---\n",
      "Q 54+83  \n",
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      "\u001b[92m☑\u001b[0m 137 \n",
      "---\n",
      "Q 6+761  \n",
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      "\u001b[92m☑\u001b[0m 767 \n",
      "---\n",
      "Q 90+277 \n",
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      "\u001b[92m☑\u001b[0m 367 \n",
      "---\n",
      "Q 46+769 \n",
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      "\u001b[92m☑\u001b[0m 815 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 133\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 3.5864e-04 - acc: 1.0000 - val_loss: 0.0018 - val_acc: 0.9997\n",
      "Q 7+459  \n",
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      "\u001b[92m☑\u001b[0m 466 \n",
      "---\n",
      "Q 5+939  \n",
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      "\u001b[92m☑\u001b[0m 944 \n",
      "---\n",
      "Q 264+94 \n",
      "T 358 \n",
      "\u001b[92m☑\u001b[0m 358 \n",
      "---\n",
      "Q 83+178 \n",
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      "\u001b[92m☑\u001b[0m 261 \n",
      "---\n",
      "Q 208+178\n",
      "T 386 \n",
      "\u001b[92m☑\u001b[0m 386 \n",
      "---\n",
      "Q 3+483  \n",
      "T 486 \n",
      "\u001b[92m☑\u001b[0m 486 \n",
      "---\n",
      "Q 996+38 \n",
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      "\u001b[92m☑\u001b[0m 1034\n",
      "---\n",
      "Q 588+9  \n",
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      "\u001b[92m☑\u001b[0m 597 \n",
      "---\n",
      "Q 142+36 \n",
      "T 178 \n",
      "\u001b[92m☑\u001b[0m 178 \n",
      "---\n",
      "Q 755+71 \n",
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      "\u001b[92m☑\u001b[0m 826 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 134\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 3.0334e-04 - acc: 1.0000 - val_loss: 0.0016 - val_acc: 0.9997\n",
      "Q 47+602 \n",
      "T 649 \n",
      "\u001b[92m☑\u001b[0m 649 \n",
      "---\n",
      "Q 613+47 \n",
      "T 660 \n",
      "\u001b[92m☑\u001b[0m 660 \n",
      "---\n",
      "Q 754+662\n",
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      "\u001b[92m☑\u001b[0m 1416\n",
      "---\n",
      "Q 511+877\n",
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      "\u001b[92m☑\u001b[0m 1388\n",
      "---\n",
      "Q 68+258 \n",
      "T 326 \n",
      "\u001b[92m☑\u001b[0m 326 \n",
      "---\n",
      "Q 3+216  \n",
      "T 219 \n",
      "\u001b[92m☑\u001b[0m 219 \n",
      "---\n",
      "Q 36+396 \n",
      "T 432 \n",
      "\u001b[92m☑\u001b[0m 432 \n",
      "---\n",
      "Q 51+8   \n",
      "T 59  \n",
      "\u001b[92m☑\u001b[0m 59  \n",
      "---\n",
      "Q 667+603\n",
      "T 1270\n",
      "\u001b[92m☑\u001b[0m 1270\n",
      "---\n",
      "Q 5+252  \n",
      "T 257 \n",
      "\u001b[92m☑\u001b[0m 257 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 135\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 19s - loss: 2.6355e-04 - acc: 1.0000 - val_loss: 0.0016 - val_acc: 0.9997\n",
      "Q 40+134 \n",
      "T 174 \n",
      "\u001b[92m☑\u001b[0m 174 \n",
      "---\n",
      "Q 538+860\n",
      "T 1398\n",
      "\u001b[92m☑\u001b[0m 1398\n",
      "---\n",
      "Q 8+763  \n",
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      "\u001b[92m☑\u001b[0m 771 \n",
      "---\n",
      "Q 995+335\n",
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      "\u001b[92m☑\u001b[0m 1330\n",
      "---\n",
      "Q 773+8  \n",
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      "\u001b[92m☑\u001b[0m 781 \n",
      "---\n",
      "Q 962+51 \n",
      "T 1013\n",
      "\u001b[92m☑\u001b[0m 1013\n",
      "---\n",
      "Q 2+897  \n",
      "T 899 \n",
      "\u001b[92m☑\u001b[0m 899 \n",
      "---\n",
      "Q 51+810 \n",
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      "\u001b[92m☑\u001b[0m 861 \n",
      "---\n",
      "Q 3+123  \n",
      "T 126 \n",
      "\u001b[92m☑\u001b[0m 126 \n",
      "---\n",
      "Q 91+495 \n",
      "T 586 \n",
      "\u001b[92m☑\u001b[0m 586 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 136\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 2.3368e-04 - acc: 1.0000 - val_loss: 0.0016 - val_acc: 0.9997\n",
      "Q 318+541\n",
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      "\u001b[92m☑\u001b[0m 859 \n",
      "---\n",
      "Q 363+75 \n",
      "T 438 \n",
      "\u001b[92m☑\u001b[0m 438 \n",
      "---\n",
      "Q 53+567 \n",
      "T 620 \n",
      "\u001b[92m☑\u001b[0m 620 \n",
      "---\n",
      "Q 7+126  \n",
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      "\u001b[92m☑\u001b[0m 133 \n",
      "---\n",
      "Q 326+162\n",
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      "\u001b[92m☑\u001b[0m 488 \n",
      "---\n",
      "Q 121+41 \n",
      "T 162 \n",
      "\u001b[92m☑\u001b[0m 162 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1806\n",
      "---\n",
      "Q 45+762 \n",
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      "\u001b[92m☑\u001b[0m 807 \n",
      "---\n",
      "Q 69+730 \n",
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      "\u001b[92m☑\u001b[0m 799 \n",
      "---\n",
      "Q 46+736 \n",
      "T 782 \n",
      "\u001b[92m☑\u001b[0m 782 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 137\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 2.0864e-04 - acc: 1.0000 - val_loss: 0.0015 - val_acc: 0.9997\n",
      "Q 2+289  \n",
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      "\u001b[92m☑\u001b[0m 291 \n",
      "---\n",
      "Q 954+289\n",
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      "\u001b[92m☑\u001b[0m 1243\n",
      "---\n",
      "Q 724+64 \n",
      "T 788 \n",
      "\u001b[92m☑\u001b[0m 788 \n",
      "---\n",
      "Q 98+24  \n",
      "T 122 \n",
      "\u001b[92m☑\u001b[0m 122 \n",
      "---\n",
      "Q 74+382 \n",
      "T 456 \n",
      "\u001b[92m☑\u001b[0m 456 \n",
      "---\n",
      "Q 608+60 \n",
      "T 668 \n",
      "\u001b[92m☑\u001b[0m 668 \n",
      "---\n",
      "Q 61+960 \n",
      "T 1021\n",
      "\u001b[92m☑\u001b[0m 1021\n",
      "---\n",
      "Q 59+194 \n",
      "T 253 \n",
      "\u001b[92m☑\u001b[0m 253 \n",
      "---\n",
      "Q 49+218 \n",
      "T 267 \n",
      "\u001b[92m☑\u001b[0m 267 \n",
      "---\n",
      "Q 415+540\n",
      "T 955 \n",
      "\u001b[92m☑\u001b[0m 955 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 138\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.8762e-04 - acc: 1.0000 - val_loss: 0.0015 - val_acc: 0.9997\n",
      "Q 95+498 \n",
      "T 593 \n",
      "\u001b[92m☑\u001b[0m 593 \n",
      "---\n",
      "Q 708+47 \n",
      "T 755 \n",
      "\u001b[92m☑\u001b[0m 755 \n",
      "---\n",
      "Q 35+18  \n",
      "T 53  \n",
      "\u001b[92m☑\u001b[0m 53  \n",
      "---\n",
      "Q 855+48 \n",
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      "\u001b[92m☑\u001b[0m 903 \n",
      "---\n",
      "Q 767+203\n",
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      "\u001b[92m☑\u001b[0m 970 \n",
      "---\n",
      "Q 176+5  \n",
      "T 181 \n",
      "\u001b[92m☑\u001b[0m 181 \n",
      "---\n",
      "Q 57+82  \n",
      "T 139 \n",
      "\u001b[92m☑\u001b[0m 139 \n",
      "---\n",
      "Q 90+435 \n",
      "T 525 \n",
      "\u001b[92m☑\u001b[0m 525 \n",
      "---\n",
      "Q 83+273 \n",
      "T 356 \n",
      "\u001b[92m☑\u001b[0m 356 \n",
      "---\n",
      "Q 133+637\n",
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      "\u001b[92m☑\u001b[0m 770 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 139\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 17s - loss: 1.6911e-04 - acc: 1.0000 - val_loss: 0.0014 - val_acc: 0.9997\n",
      "Q 70+320 \n",
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      "\u001b[92m☑\u001b[0m 390 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 868 \n",
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      "\u001b[92m☑\u001b[0m 661 \n",
      "---\n",
      "Q 793+1  \n",
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      "\u001b[92m☑\u001b[0m 794 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 648 \n",
      "---\n",
      "Q 167+4  \n",
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      "\u001b[92m☑\u001b[0m 171 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 708 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1388\n",
      "---\n",
      "Q 24+226 \n",
      "T 250 \n",
      "\u001b[92m☑\u001b[0m 250 \n",
      "---\n",
      "Q 41+721 \n",
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      "\u001b[92m☑\u001b[0m 762 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 140\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.5227e-04 - acc: 1.0000 - val_loss: 0.0013 - val_acc: 0.9996\n",
      "Q 94+17  \n",
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      "\u001b[92m☑\u001b[0m 111 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 498 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 523 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 934 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1152\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 643 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 149 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 672 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1161\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 703 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 141\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.5119e-04 - acc: 1.0000 - val_loss: 0.0017 - val_acc: 0.9996\n",
      "Q 465+3  \n",
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      "\u001b[92m☑\u001b[0m 468 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 391 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 561 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1093\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 294 \n",
      "---\n",
      "Q 4+105  \n",
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      "\u001b[92m☑\u001b[0m 109 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1242\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 362 \n",
      "---\n",
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      "\u001b[91m☒\u001b[0m 10  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 632 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 142\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 0.0346 - acc: 0.9900 - val_loss: 0.0052 - val_acc: 0.9986\n",
      "Q 30+849 \n",
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      "\u001b[92m☑\u001b[0m 879 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1514\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 26  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 873 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 282 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 810 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 649 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 784 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 803 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 787 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 143\n",
      "Train on 45000 samples, validate on 5000 samples\n",
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      "45000/45000 [==============================] - 17s - loss: 0.0012 - acc: 0.9999 - val_loss: 0.0019 - val_acc: 0.9996\n",
      "Q 678+907\n",
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      "\u001b[92m☑\u001b[0m 1585\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1019\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 231 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 250 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 962 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 155 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 713 \n",
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      "\u001b[92m☑\u001b[0m 686 \n",
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      "\u001b[92m☑\u001b[0m 630 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 135 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 144\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 4.2291e-04 - acc: 1.0000 - val_loss: 0.0016 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 908 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 74  \n",
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      "\u001b[92m☑\u001b[0m 829 \n",
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      "\u001b[92m☑\u001b[0m 511 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1516\n",
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      "\u001b[92m☑\u001b[0m 895 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 16  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 576 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 52  \n",
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      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 145\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 3.2329e-04 - acc: 1.0000 - val_loss: 0.0015 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 203 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 215 \n",
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      "\u001b[92m☑\u001b[0m 475 \n",
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      "\u001b[92m☑\u001b[0m 338 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 563 \n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 180 \n",
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      "\u001b[92m☑\u001b[0m 700 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 481 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 118 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 146\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 2.7293e-04 - acc: 1.0000 - val_loss: 0.0014 - val_acc: 0.9998\n",
      "Q 8+52   \n",
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      "\u001b[92m☑\u001b[0m 60  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 821 \n",
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      "\u001b[92m☑\u001b[0m 487 \n",
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      "\u001b[92m☑\u001b[0m 959 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 648 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 442 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 334 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1537\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 456 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 131 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 147\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 2.3483e-04 - acc: 1.0000 - val_loss: 0.0013 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 894 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1028\n",
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      "\u001b[92m☑\u001b[0m 255 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 162 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 162 \n",
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      "\u001b[92m☑\u001b[0m 675 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 826 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 992 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 121 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 469 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 148\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 2.0585e-04 - acc: 1.0000 - val_loss: 0.0013 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 1529\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1786\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 403 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 120 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1353\n",
      "---\n",
      "Q 50+11  \n",
      "T 61  \n",
      "\u001b[92m☑\u001b[0m 61  \n",
      "---\n",
      "Q 12+334 \n",
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      "\u001b[92m☑\u001b[0m 346 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1142\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 809 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1703\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 149\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.8323e-04 - acc: 1.0000 - val_loss: 0.0012 - val_acc: 0.9997\n",
      "Q 71+242 \n",
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      "\u001b[92m☑\u001b[0m 313 \n",
      "---\n",
      "Q 4+284  \n",
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      "\u001b[92m☑\u001b[0m 288 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 486 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1135\n",
      "---\n",
      "Q 209+3  \n",
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      "\u001b[92m☑\u001b[0m 212 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 407 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 773 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 652 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 785 \n",
      "---\n",
      "Q 785+5  \n",
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      "\u001b[92m☑\u001b[0m 790 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 150\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.6286e-04 - acc: 1.0000 - val_loss: 0.0012 - val_acc: 0.9996\n",
      "Q 9+623  \n",
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      "\u001b[92m☑\u001b[0m 632 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 498 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 415 \n",
      "---\n",
      "Q 7+563  \n",
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      "\u001b[92m☑\u001b[0m 570 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 797 \n",
      "---\n",
      "Q 121+249\n",
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      "\u001b[92m☑\u001b[0m 370 \n",
      "---\n",
      "Q 5+69   \n",
      "T 74  \n",
      "\u001b[92m☑\u001b[0m 74  \n",
      "---\n",
      "Q 1+938  \n",
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      "\u001b[92m☑\u001b[0m 939 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 613 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 853 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 151\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.4827e-04 - acc: 1.0000 - val_loss: 0.0012 - val_acc: 0.9997\n",
      "Q 898+60 \n",
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      "\u001b[92m☑\u001b[0m 958 \n",
      "---\n",
      "Q 5+718  \n",
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      "\u001b[92m☑\u001b[0m 723 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 311 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1040\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 520 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 382 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 102 \n",
      "---\n",
      "Q 331+3  \n",
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      "\u001b[92m☑\u001b[0m 334 \n",
      "---\n",
      "Q 117+5  \n",
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      "\u001b[92m☑\u001b[0m 122 \n",
      "---\n",
      "Q 844+53 \n",
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      "\u001b[92m☑\u001b[0m 897 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 152\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.3295e-04 - acc: 1.0000 - val_loss: 0.0011 - val_acc: 0.9997\n",
      "Q 62+907 \n",
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      "\u001b[92m☑\u001b[0m 969 \n",
      "---\n",
      "Q 533+20 \n",
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      "\u001b[92m☑\u001b[0m 553 \n",
      "---\n",
      "Q 919+78 \n",
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      "\u001b[92m☑\u001b[0m 997 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1518\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 715 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 651 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 912 \n",
      "---\n",
      "Q 28+64  \n",
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      "\u001b[92m☑\u001b[0m 92  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 960 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1124\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 153\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 17s - loss: 1.1862e-04 - acc: 1.0000 - val_loss: 0.0011 - val_acc: 0.9997\n",
      "Q 617+695\n",
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      "\u001b[92m☑\u001b[0m 1312\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 749 \n",
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      "\u001b[92m☑\u001b[0m 835 \n",
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      "\u001b[92m☑\u001b[0m 669 \n",
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      "\u001b[92m☑\u001b[0m 76  \n",
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      "\u001b[92m☑\u001b[0m 871 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 928 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1317\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 908 \n",
      "---\n",
      "Q 31+473 \n",
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      "\u001b[92m☑\u001b[0m 504 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 154\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.1075e-04 - acc: 1.0000 - val_loss: 0.0013 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 1054\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1412\n",
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      "\u001b[92m☑\u001b[0m 914 \n",
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      "\u001b[92m☑\u001b[0m 734 \n",
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      "---\n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 1101\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 155\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 0.0375 - acc: 0.9896 - val_loss: 0.0038 - val_acc: 0.9991\n",
      "Q 8+922  \n",
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      "\u001b[92m☑\u001b[0m 930 \n",
      "---\n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 150 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 728 \n",
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      "\u001b[92m☑\u001b[0m 60  \n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 122 \n",
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      "---\n",
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      "--------------------------------------------------\n",
      "Iteration 156\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 9.2601e-04 - acc: 0.9999 - val_loss: 0.0019 - val_acc: 0.9995\n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 30  \n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 961 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 82  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 157\n",
      "Train on 45000 samples, validate on 5000 samples\n",
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      "45000/45000 [==============================] - 17s - loss: 3.7565e-04 - acc: 1.0000 - val_loss: 0.0015 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 728 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 108 \n",
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      "\u001b[92m☑\u001b[0m 77  \n",
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      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 158\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.8824e-04 - acc: 1.0000 - val_loss: 0.0013 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 679 \n",
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      "\u001b[92m☑\u001b[0m 273 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 159\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 2.4042e-04 - acc: 1.0000 - val_loss: 0.0013 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 772 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1419\n",
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      "\u001b[92m☑\u001b[0m 465 \n",
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      "\u001b[92m☑\u001b[0m 570 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 591 \n",
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      "\u001b[92m☑\u001b[0m 895 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 524 \n",
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      "\u001b[92m☑\u001b[0m 137 \n",
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      "\u001b[92m☑\u001b[0m 564 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 927 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 160\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.0695e-04 - acc: 1.0000 - val_loss: 0.0011 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 804 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1036\n",
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      "\u001b[92m☑\u001b[0m 237 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 630 \n",
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      "\u001b[92m☑\u001b[0m 313 \n",
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      "\u001b[92m☑\u001b[0m 277 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 186 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 301 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 263 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 139 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 161\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.8032e-04 - acc: 1.0000 - val_loss: 0.0010 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 996 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1331\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 543 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 187 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 869 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 961 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 578 \n",
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      "\u001b[92m☑\u001b[0m 1185\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 162\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.6039e-04 - acc: 1.0000 - val_loss: 9.9766e-04 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 256 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 958 \n",
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      "\u001b[92m☑\u001b[0m 429 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 630 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1513\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 304 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 956 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 555 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1270\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1491\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 163\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.4241e-04 - acc: 1.0000 - val_loss: 9.9952e-04 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 178 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 747 \n",
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      "\u001b[92m☑\u001b[0m 429 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 963 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1528\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 656 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1017\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 858 \n",
      "---\n",
      "Q 50+95  \n",
      "T 145 \n",
      "\u001b[92m☑\u001b[0m 145 \n",
      "---\n",
      "Q 801+97 \n",
      "T 898 \n",
      "\u001b[92m☑\u001b[0m 898 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 164\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.2725e-04 - acc: 1.0000 - val_loss: 0.0010 - val_acc: 0.9997\n",
      "Q 774+164\n",
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      "\u001b[92m☑\u001b[0m 938 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1811\n",
      "---\n",
      "Q 13+48  \n",
      "T 61  \n",
      "\u001b[92m☑\u001b[0m 61  \n",
      "---\n",
      "Q 16+62  \n",
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      "\u001b[92m☑\u001b[0m 78  \n",
      "---\n",
      "Q 674+33 \n",
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      "\u001b[92m☑\u001b[0m 707 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 438 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 314 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1002\n",
      "---\n",
      "Q 32+363 \n",
      "T 395 \n",
      "\u001b[92m☑\u001b[0m 395 \n",
      "---\n",
      "Q 93+866 \n",
      "T 959 \n",
      "\u001b[92m☑\u001b[0m 959 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 165\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.1405e-04 - acc: 1.0000 - val_loss: 9.5987e-04 - val_acc: 0.9997\n",
      "Q 40+49  \n",
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      "\u001b[92m☑\u001b[0m 89  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1005\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 814 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 902 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 894 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 242 \n",
      "---\n",
      "Q 91+64  \n",
      "T 155 \n",
      "\u001b[92m☑\u001b[0m 155 \n",
      "---\n",
      "Q 1+938  \n",
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      "\u001b[92m☑\u001b[0m 939 \n",
      "---\n",
      "Q 6+343  \n",
      "T 349 \n",
      "\u001b[92m☑\u001b[0m 349 \n",
      "---\n",
      "Q 97+85  \n",
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      "\u001b[92m☑\u001b[0m 182 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 166\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.0392e-04 - acc: 1.0000 - val_loss: 8.6710e-04 - val_acc: 0.9998\n",
      "Q 34+694 \n",
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      "\u001b[92m☑\u001b[0m 728 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1322\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 998 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 566 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 213 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 754 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 328 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 449 \n",
      "---\n",
      "Q 42+595 \n",
      "T 637 \n",
      "\u001b[92m☑\u001b[0m 637 \n",
      "---\n",
      "Q 65+73  \n",
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      "\u001b[92m☑\u001b[0m 138 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 167\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 17s - loss: 0.0105 - acc: 0.9974 - val_loss: 0.2101 - val_acc: 0.9476\n",
      "Q 90+277 \n",
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      "\u001b[92m☑\u001b[0m 367 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 340 \n",
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      "\u001b[92m☑\u001b[0m 370 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1528\n",
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      "\u001b[92m☑\u001b[0m 1042\n",
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      "\u001b[91m☒\u001b[0m 1538\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 384 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 795 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 916 \n",
      "---\n",
      "Q 80+6   \n",
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      "\u001b[92m☑\u001b[0m 86  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 168\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 0.0299 - acc: 0.9915 - val_loss: 0.0025 - val_acc: 0.9993\n",
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      "\u001b[92m☑\u001b[0m 1810\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1151\n",
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      "\u001b[92m☑\u001b[0m 78  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 528 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 458 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 825 \n",
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      "\u001b[92m☑\u001b[0m 586 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 42  \n",
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      "\u001b[92m☑\u001b[0m 296 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 146 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 169\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 6.4347e-04 - acc: 1.0000 - val_loss: 0.0016 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 208 \n",
      "---\n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 48  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 170\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 3.5476e-04 - acc: 1.0000 - val_loss: 0.0013 - val_acc: 0.9998\n",
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      "\u001b[92m☑\u001b[0m 553 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 414 \n",
      "---\n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 71  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 171\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.7804e-04 - acc: 1.0000 - val_loss: 0.0013 - val_acc: 0.9997\n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 1011\n",
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      "\u001b[92m☑\u001b[0m 656 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1420\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 172\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.3245e-04 - acc: 1.0000 - val_loss: 0.0012 - val_acc: 0.9998\n",
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      "\u001b[92m☑\u001b[0m 590 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 403 \n",
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      "\u001b[92m☑\u001b[0m 328 \n",
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      "\u001b[92m☑\u001b[0m 1404\n",
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      "\u001b[92m☑\u001b[0m 600 \n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 910 \n",
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      "\u001b[92m☑\u001b[0m 389 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 474 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 213 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 173\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.0000e-04 - acc: 1.0000 - val_loss: 0.0011 - val_acc: 0.9997\n",
      "Q 99+0   \n",
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      "\u001b[92m☑\u001b[0m 99  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 531 \n",
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      "\u001b[92m☑\u001b[0m 452 \n",
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      "\u001b[92m☑\u001b[0m 310 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 120 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 75  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 706 \n",
      "---\n",
      "Q 1+536  \n",
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      "\u001b[92m☑\u001b[0m 537 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 174\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.7453e-04 - acc: 1.0000 - val_loss: 0.0011 - val_acc: 0.9998\n",
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      "\u001b[92m☑\u001b[0m 521 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 723 \n",
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      "\u001b[92m☑\u001b[0m 833 \n",
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      "\u001b[92m☑\u001b[0m 136 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1745\n",
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      "\u001b[92m☑\u001b[0m 826 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 670 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 149 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 801 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1549\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 175\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.5390e-04 - acc: 1.0000 - val_loss: 0.0011 - val_acc: 0.9997\n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 1234\n",
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      "\u001b[92m☑\u001b[0m 436 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 125 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1020\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 942 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1022\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 124 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 667 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1055\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 176\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.3661e-04 - acc: 1.0000 - val_loss: 0.0010 - val_acc: 0.9998\n",
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      "\u001b[92m☑\u001b[0m 1518\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 129 \n",
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      "\u001b[92m☑\u001b[0m 789 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 908 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 192 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 618 \n",
      "---\n",
      "Q 85+862 \n",
      "T 947 \n",
      "\u001b[92m☑\u001b[0m 947 \n",
      "---\n",
      "Q 589+711\n",
      "T 1300\n",
      "\u001b[92m☑\u001b[0m 1300\n",
      "---\n",
      "Q 47+972 \n",
      "T 1019\n",
      "\u001b[92m☑\u001b[0m 1019\n",
      "---\n",
      "Q 403+57 \n",
      "T 460 \n",
      "\u001b[92m☑\u001b[0m 460 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 177\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.2217e-04 - acc: 1.0000 - val_loss: 9.7273e-04 - val_acc: 0.9998\n",
      "Q 19+651 \n",
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      "\u001b[92m☑\u001b[0m 670 \n",
      "---\n",
      "Q 521+425\n",
      "T 946 \n",
      "\u001b[92m☑\u001b[0m 946 \n",
      "---\n",
      "Q 799+9  \n",
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      "\u001b[92m☑\u001b[0m 808 \n",
      "---\n",
      "Q 2+610  \n",
      "T 612 \n",
      "\u001b[92m☑\u001b[0m 612 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 944 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 795 \n",
      "---\n",
      "Q 356+24 \n",
      "T 380 \n",
      "\u001b[92m☑\u001b[0m 380 \n",
      "---\n",
      "Q 183+622\n",
      "T 805 \n",
      "\u001b[92m☑\u001b[0m 805 \n",
      "---\n",
      "Q 75+756 \n",
      "T 831 \n",
      "\u001b[92m☑\u001b[0m 831 \n",
      "---\n",
      "Q 65+941 \n",
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      "\u001b[92m☑\u001b[0m 1006\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 178\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.0928e-04 - acc: 1.0000 - val_loss: 9.5509e-04 - val_acc: 0.9997\n",
      "Q 231+39 \n",
      "T 270 \n",
      "\u001b[92m☑\u001b[0m 270 \n",
      "---\n",
      "Q 5+865  \n",
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      "\u001b[92m☑\u001b[0m 870 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1044\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1356\n",
      "---\n",
      "Q 9+783  \n",
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      "\u001b[92m☑\u001b[0m 792 \n",
      "---\n",
      "Q 99+289 \n",
      "T 388 \n",
      "\u001b[92m☑\u001b[0m 388 \n",
      "---\n",
      "Q 491+84 \n",
      "T 575 \n",
      "\u001b[92m☑\u001b[0m 575 \n",
      "---\n",
      "Q 41+35  \n",
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      "\u001b[92m☑\u001b[0m 76  \n",
      "---\n",
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      "T 906 \n",
      "\u001b[92m☑\u001b[0m 906 \n",
      "---\n",
      "Q 148+83 \n",
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      "\u001b[92m☑\u001b[0m 231 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 179\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 9.8416e-05 - acc: 1.0000 - val_loss: 9.0127e-04 - val_acc: 0.9998\n",
      "Q 98+32  \n",
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      "\u001b[92m☑\u001b[0m 130 \n",
      "---\n",
      "Q 998+704\n",
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      "\u001b[92m☑\u001b[0m 1702\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1111\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1019\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1160\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 177 \n",
      "---\n",
      "Q 694+2  \n",
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      "\u001b[92m☑\u001b[0m 696 \n",
      "---\n",
      "Q 17+38  \n",
      "T 55  \n",
      "\u001b[92m☑\u001b[0m 55  \n",
      "---\n",
      "Q 766+18 \n",
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      "\u001b[92m☑\u001b[0m 784 \n",
      "---\n",
      "Q 835+5  \n",
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      "\u001b[92m☑\u001b[0m 840 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 180\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 8.9614e-05 - acc: 1.0000 - val_loss: 9.7640e-04 - val_acc: 0.9998\n",
      "Q 57+53  \n",
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      "\u001b[92m☑\u001b[0m 110 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 812 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1011\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 857 \n",
      "---\n",
      "Q 30+759 \n",
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      "\u001b[92m☑\u001b[0m 789 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 957 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 647 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 913 \n",
      "---\n",
      "Q 69+97  \n",
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      "\u001b[92m☑\u001b[0m 166 \n",
      "---\n",
      "Q 383+43 \n",
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      "\u001b[92m☑\u001b[0m 426 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 181\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 17s - loss: 0.0324 - acc: 0.9917 - val_loss: 0.0058 - val_acc: 0.9983\n",
      "Q 190+97 \n",
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      "\u001b[92m☑\u001b[0m 287 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1128\n",
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      "\u001b[92m☑\u001b[0m 1303\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 851 \n",
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      "\u001b[92m☑\u001b[0m 326 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 627 \n",
      "---\n",
      "Q 568+7  \n",
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      "\u001b[92m☑\u001b[0m 575 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 647 \n",
      "---\n",
      "Q 425+31 \n",
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      "\u001b[92m☑\u001b[0m 456 \n",
      "---\n",
      "Q 9+508  \n",
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      "\u001b[92m☑\u001b[0m 517 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 182\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 0.0013 - acc: 0.9998 - val_loss: 0.0016 - val_acc: 0.9996\n",
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      "\u001b[92m☑\u001b[0m 1327\n",
      "---\n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 732 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 107 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 340 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 850 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 395 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 287 \n",
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      "\u001b[92m☑\u001b[0m 438 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 407 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 183\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 3.6884e-04 - acc: 1.0000 - val_loss: 0.0012 - val_acc: 0.9996\n",
      "Q 9+52   \n",
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      "\u001b[92m☑\u001b[0m 61  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 599 \n",
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      "\u001b[92m☑\u001b[0m 776 \n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 977 \n",
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      "\u001b[92m☑\u001b[0m 197 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 162 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 54  \n",
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      "\u001b[92m☑\u001b[0m 221 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 184\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 2.5577e-04 - acc: 1.0000 - val_loss: 0.0011 - val_acc: 0.9996\n",
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      "---\n",
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      "\u001b[92m☑\u001b[0m 1242\n",
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      "\u001b[92m☑\u001b[0m 905 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1042\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 845 \n",
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      "\u001b[92m☑\u001b[0m 1518\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 791 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1019\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 254 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 971 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 185\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.0894e-04 - acc: 1.0000 - val_loss: 0.0011 - val_acc: 0.9997\n",
      "Q 664+55 \n",
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      "\u001b[92m☑\u001b[0m 719 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1669\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 69  \n",
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      "\u001b[92m☑\u001b[0m 273 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 632 \n",
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      "\u001b[92m☑\u001b[0m 839 \n",
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      "\u001b[92m☑\u001b[0m 326 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 226 \n",
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      "\u001b[92m☑\u001b[0m 245 \n",
      "---\n",
      "Q 18+8   \n",
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      "\u001b[92m☑\u001b[0m 26  \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 186\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.7806e-04 - acc: 1.0000 - val_loss: 0.0011 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 305 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 328 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 408 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1007\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 994 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 803 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1520\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 842 \n",
      "---\n",
      "Q 74+26  \n",
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      "\u001b[92m☑\u001b[0m 100 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1475\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 187\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.5486e-04 - acc: 1.0000 - val_loss: 9.7700e-04 - val_acc: 0.9997\n",
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      "\u001b[92m☑\u001b[0m 1302\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 240 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1296\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 95  \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 407 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 134 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1227\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 97  \n",
      "---\n",
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      "\u001b[91m☒\u001b[0m 880 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 254 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 188\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.3622e-04 - acc: 1.0000 - val_loss: 9.8483e-04 - val_acc: 0.9997\n",
      "Q 0+198  \n",
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      "\u001b[92m☑\u001b[0m 198 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 169 \n",
      "---\n",
      "Q 51+54  \n",
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      "\u001b[92m☑\u001b[0m 105 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 243 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1097\n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 1029\n",
      "---\n",
      "Q 7+333  \n",
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      "\u001b[92m☑\u001b[0m 340 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 537 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 651 \n",
      "---\n",
      "Q 815+30 \n",
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      "\u001b[92m☑\u001b[0m 845 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 189\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.2106e-04 - acc: 1.0000 - val_loss: 9.3022e-04 - val_acc: 0.9997\n",
      "Q 79+83  \n",
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      "\u001b[92m☑\u001b[0m 162 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 522 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 691 \n",
      "---\n",
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      "\u001b[92m☑\u001b[0m 377 \n",
      "---\n",
      "Q 91+432 \n",
      "T 523 \n",
      "\u001b[92m☑\u001b[0m 523 \n",
      "---\n",
      "Q 56+289 \n",
      "T 345 \n",
      "\u001b[92m☑\u001b[0m 345 \n",
      "---\n",
      "Q 369+32 \n",
      "T 401 \n",
      "\u001b[92m☑\u001b[0m 401 \n",
      "---\n",
      "Q 431+445\n",
      "T 876 \n",
      "\u001b[92m☑\u001b[0m 876 \n",
      "---\n",
      "Q 338+21 \n",
      "T 359 \n",
      "\u001b[92m☑\u001b[0m 359 \n",
      "---\n",
      "Q 434+263\n",
      "T 697 \n",
      "\u001b[92m☑\u001b[0m 697 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 190\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 1.0793e-04 - acc: 1.0000 - val_loss: 8.7021e-04 - val_acc: 0.9997\n",
      "Q 60+314 \n",
      "T 374 \n",
      "\u001b[92m☑\u001b[0m 374 \n",
      "---\n",
      "Q 2+109  \n",
      "T 111 \n",
      "\u001b[92m☑\u001b[0m 111 \n",
      "---\n",
      "Q 372+185\n",
      "T 557 \n",
      "\u001b[92m☑\u001b[0m 557 \n",
      "---\n",
      "Q 28+452 \n",
      "T 480 \n",
      "\u001b[92m☑\u001b[0m 480 \n",
      "---\n",
      "Q 49+669 \n",
      "T 718 \n",
      "\u001b[92m☑\u001b[0m 718 \n",
      "---\n",
      "Q 312+211\n",
      "T 523 \n",
      "\u001b[92m☑\u001b[0m 523 \n",
      "---\n",
      "Q 26+385 \n",
      "T 411 \n",
      "\u001b[92m☑\u001b[0m 411 \n",
      "---\n",
      "Q 529+692\n",
      "T 1221\n",
      "\u001b[92m☑\u001b[0m 1221\n",
      "---\n",
      "Q 794+41 \n",
      "T 835 \n",
      "\u001b[92m☑\u001b[0m 835 \n",
      "---\n",
      "Q 135+53 \n",
      "T 188 \n",
      "\u001b[92m☑\u001b[0m 188 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 191\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 19s - loss: 9.6888e-05 - acc: 1.0000 - val_loss: 9.1206e-04 - val_acc: 0.9997\n",
      "Q 656+663\n",
      "T 1319\n",
      "\u001b[92m☑\u001b[0m 1319\n",
      "---\n",
      "Q 55+21  \n",
      "T 76  \n",
      "\u001b[92m☑\u001b[0m 76  \n",
      "---\n",
      "Q 12+26  \n",
      "T 38  \n",
      "\u001b[92m☑\u001b[0m 38  \n",
      "---\n",
      "Q 47+233 \n",
      "T 280 \n",
      "\u001b[92m☑\u001b[0m 280 \n",
      "---\n",
      "Q 390+461\n",
      "T 851 \n",
      "\u001b[92m☑\u001b[0m 851 \n",
      "---\n",
      "Q 1+210  \n",
      "T 211 \n",
      "\u001b[92m☑\u001b[0m 211 \n",
      "---\n",
      "Q 64+268 \n",
      "T 332 \n",
      "\u001b[92m☑\u001b[0m 332 \n",
      "---\n",
      "Q 455+4  \n",
      "T 459 \n",
      "\u001b[92m☑\u001b[0m 459 \n",
      "---\n",
      "Q 994+205\n",
      "T 1199\n",
      "\u001b[92m☑\u001b[0m 1199\n",
      "---\n",
      "Q 729+466\n",
      "T 1195\n",
      "\u001b[92m☑\u001b[0m 1195\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 192\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 19s - loss: 8.7078e-05 - acc: 1.0000 - val_loss: 9.0645e-04 - val_acc: 0.9997\n",
      "Q 80+6   \n",
      "T 86  \n",
      "\u001b[92m☑\u001b[0m 86  \n",
      "---\n",
      "Q 51+480 \n",
      "T 531 \n",
      "\u001b[92m☑\u001b[0m 531 \n",
      "---\n",
      "Q 88+452 \n",
      "T 540 \n",
      "\u001b[92m☑\u001b[0m 540 \n",
      "---\n",
      "Q 975+33 \n",
      "T 1008\n",
      "\u001b[92m☑\u001b[0m 1008\n",
      "---\n",
      "Q 770+722\n",
      "T 1492\n",
      "\u001b[92m☑\u001b[0m 1492\n",
      "---\n",
      "Q 623+19 \n",
      "T 642 \n",
      "\u001b[92m☑\u001b[0m 642 \n",
      "---\n",
      "Q 199+82 \n",
      "T 281 \n",
      "\u001b[92m☑\u001b[0m 281 \n",
      "---\n",
      "Q 117+48 \n",
      "T 165 \n",
      "\u001b[92m☑\u001b[0m 165 \n",
      "---\n",
      "Q 809+744\n",
      "T 1553\n",
      "\u001b[92m☑\u001b[0m 1553\n",
      "---\n",
      "Q 953+0  \n",
      "T 953 \n",
      "\u001b[92m☑\u001b[0m 953 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 193\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 7.8512e-05 - acc: 1.0000 - val_loss: 8.3686e-04 - val_acc: 0.9997\n",
      "Q 575+46 \n",
      "T 621 \n",
      "\u001b[92m☑\u001b[0m 621 \n",
      "---\n",
      "Q 722+415\n",
      "T 1137\n",
      "\u001b[92m☑\u001b[0m 1137\n",
      "---\n",
      "Q 86+840 \n",
      "T 926 \n",
      "\u001b[92m☑\u001b[0m 926 \n",
      "---\n",
      "Q 117+550\n",
      "T 667 \n",
      "\u001b[92m☑\u001b[0m 667 \n",
      "---\n",
      "Q 538+736\n",
      "T 1274\n",
      "\u001b[92m☑\u001b[0m 1274\n",
      "---\n",
      "Q 550+806\n",
      "T 1356\n",
      "\u001b[92m☑\u001b[0m 1356\n",
      "---\n",
      "Q 28+37  \n",
      "T 65  \n",
      "\u001b[92m☑\u001b[0m 65  \n",
      "---\n",
      "Q 672+82 \n",
      "T 754 \n",
      "\u001b[92m☑\u001b[0m 754 \n",
      "---\n",
      "Q 957+310\n",
      "T 1267\n",
      "\u001b[92m☑\u001b[0m 1267\n",
      "---\n",
      "Q 178+851\n",
      "T 1029\n",
      "\u001b[92m☑\u001b[0m 1029\n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 194\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 7.4032e-05 - acc: 1.0000 - val_loss: 7.6828e-04 - val_acc: 0.9997\n",
      "Q 197+240\n",
      "T 437 \n",
      "\u001b[92m☑\u001b[0m 437 \n",
      "---\n",
      "Q 79+695 \n",
      "T 774 \n",
      "\u001b[92m☑\u001b[0m 774 \n",
      "---\n",
      "Q 138+939\n",
      "T 1077\n",
      "\u001b[92m☑\u001b[0m 1077\n",
      "---\n",
      "Q 383+43 \n",
      "T 426 \n",
      "\u001b[92m☑\u001b[0m 426 \n",
      "---\n",
      "Q 870+445\n",
      "T 1315\n",
      "\u001b[92m☑\u001b[0m 1315\n",
      "---\n",
      "Q 37+537 \n",
      "T 574 \n",
      "\u001b[92m☑\u001b[0m 574 \n",
      "---\n",
      "Q 65+888 \n",
      "T 953 \n",
      "\u001b[92m☑\u001b[0m 953 \n",
      "---\n",
      "Q 86+806 \n",
      "T 892 \n",
      "\u001b[92m☑\u001b[0m 892 \n",
      "---\n",
      "Q 49+669 \n",
      "T 718 \n",
      "\u001b[92m☑\u001b[0m 718 \n",
      "---\n",
      "Q 28+838 \n",
      "T 866 \n",
      "\u001b[92m☑\u001b[0m 866 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 195\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "45000/45000 [==============================] - 18s - loss: 0.0310 - acc: 0.9916 - val_loss: 0.0048 - val_acc: 0.9986\n",
      "Q 810+55 \n",
      "T 865 \n",
      "\u001b[92m☑\u001b[0m 865 \n",
      "---\n",
      "Q 717+747\n",
      "T 1464\n",
      "\u001b[92m☑\u001b[0m 1464\n",
      "---\n",
      "Q 37+532 \n",
      "T 569 \n",
      "\u001b[92m☑\u001b[0m 569 \n",
      "---\n",
      "Q 90+238 \n",
      "T 328 \n",
      "\u001b[92m☑\u001b[0m 328 \n",
      "---\n",
      "Q 929+424\n",
      "T 1353\n",
      "\u001b[92m☑\u001b[0m 1353\n",
      "---\n",
      "Q 54+95  \n",
      "T 149 \n",
      "\u001b[92m☑\u001b[0m 149 \n",
      "---\n",
      "Q 884+34 \n",
      "T 918 \n",
      "\u001b[92m☑\u001b[0m 918 \n",
      "---\n",
      "Q 57+72  \n",
      "T 129 \n",
      "\u001b[92m☑\u001b[0m 129 \n",
      "---\n",
      "Q 138+335\n",
      "T 473 \n",
      "\u001b[92m☑\u001b[0m 473 \n",
      "---\n",
      "Q 207+86 \n",
      "T 293 \n",
      "\u001b[92m☑\u001b[0m 293 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 196\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 0.0013 - acc: 0.9998 - val_loss: 0.0015 - val_acc: 0.9997\n",
      "Q 489+197\n",
      "T 686 \n",
      "\u001b[92m☑\u001b[0m 686 \n",
      "---\n",
      "Q 81+14  \n",
      "T 95  \n",
      "\u001b[92m☑\u001b[0m 95  \n",
      "---\n",
      "Q 94+17  \n",
      "T 111 \n",
      "\u001b[92m☑\u001b[0m 111 \n",
      "---\n",
      "Q 435+84 \n",
      "T 519 \n",
      "\u001b[92m☑\u001b[0m 519 \n",
      "---\n",
      "Q 88+292 \n",
      "T 380 \n",
      "\u001b[92m☑\u001b[0m 380 \n",
      "---\n",
      "Q 5+961  \n",
      "T 966 \n",
      "\u001b[92m☑\u001b[0m 966 \n",
      "---\n",
      "Q 43+591 \n",
      "T 634 \n",
      "\u001b[92m☑\u001b[0m 634 \n",
      "---\n",
      "Q 39+345 \n",
      "T 384 \n",
      "\u001b[92m☑\u001b[0m 384 \n",
      "---\n",
      "Q 942+112\n",
      "T 1054\n",
      "\u001b[92m☑\u001b[0m 1054\n",
      "---\n",
      "Q 90+277 \n",
      "T 367 \n",
      "\u001b[92m☑\u001b[0m 367 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 197\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 3.4687e-04 - acc: 1.0000 - val_loss: 0.0012 - val_acc: 0.9998\n",
      "Q 23+432 \n",
      "T 455 \n",
      "\u001b[92m☑\u001b[0m 455 \n",
      "---\n",
      "Q 320+649\n",
      "T 969 \n",
      "\u001b[92m☑\u001b[0m 969 \n",
      "---\n",
      "Q 67+35  \n",
      "T 102 \n",
      "\u001b[92m☑\u001b[0m 102 \n",
      "---\n",
      "Q 726+332\n",
      "T 1058\n",
      "\u001b[92m☑\u001b[0m 1058\n",
      "---\n",
      "Q 109+375\n",
      "T 484 \n",
      "\u001b[92m☑\u001b[0m 484 \n",
      "---\n",
      "Q 435+181\n",
      "T 616 \n",
      "\u001b[92m☑\u001b[0m 616 \n",
      "---\n",
      "Q 134+25 \n",
      "T 159 \n",
      "\u001b[92m☑\u001b[0m 159 \n",
      "---\n",
      "Q 673+224\n",
      "T 897 \n",
      "\u001b[92m☑\u001b[0m 897 \n",
      "---\n",
      "Q 765+213\n",
      "T 978 \n",
      "\u001b[92m☑\u001b[0m 978 \n",
      "---\n",
      "Q 446+30 \n",
      "T 476 \n",
      "\u001b[92m☑\u001b[0m 476 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 198\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 17s - loss: 2.3944e-04 - acc: 1.0000 - val_loss: 0.0011 - val_acc: 0.9998\n",
      "Q 15+400 \n",
      "T 415 \n",
      "\u001b[92m☑\u001b[0m 415 \n",
      "---\n",
      "Q 40+371 \n",
      "T 411 \n",
      "\u001b[92m☑\u001b[0m 411 \n",
      "---\n",
      "Q 70+600 \n",
      "T 670 \n",
      "\u001b[92m☑\u001b[0m 670 \n",
      "---\n",
      "Q 453+11 \n",
      "T 464 \n",
      "\u001b[92m☑\u001b[0m 464 \n",
      "---\n",
      "Q 718+83 \n",
      "T 801 \n",
      "\u001b[92m☑\u001b[0m 801 \n",
      "---\n",
      "Q 261+969\n",
      "T 1230\n",
      "\u001b[92m☑\u001b[0m 1230\n",
      "---\n",
      "Q 77+39  \n",
      "T 116 \n",
      "\u001b[92m☑\u001b[0m 116 \n",
      "---\n",
      "Q 560+53 \n",
      "T 613 \n",
      "\u001b[92m☑\u001b[0m 613 \n",
      "---\n",
      "Q 30+482 \n",
      "T 512 \n",
      "\u001b[92m☑\u001b[0m 512 \n",
      "---\n",
      "Q 195+74 \n",
      "T 269 \n",
      "\u001b[92m☑\u001b[0m 269 \n",
      "---\n",
      "\n",
      "--------------------------------------------------\n",
      "Iteration 199\n",
      "Train on 45000 samples, validate on 5000 samples\n",
      "Epoch 1/1\n",
      "45000/45000 [==============================] - 18s - loss: 1.9311e-04 - acc: 1.0000 - val_loss: 0.0010 - val_acc: 0.9998\n",
      "Q 40+265 \n",
      "T 305 \n",
      "\u001b[92m☑\u001b[0m 305 \n",
      "---\n",
      "Q 151+74 \n",
      "T 225 \n",
      "\u001b[92m☑\u001b[0m 225 \n",
      "---\n",
      "Q 52+617 \n",
      "T 669 \n",
      "\u001b[92m☑\u001b[0m 669 \n",
      "---\n",
      "Q 36+193 \n",
      "T 229 \n",
      "\u001b[92m☑\u001b[0m 229 \n",
      "---\n",
      "Q 198+566\n",
      "T 764 \n",
      "\u001b[92m☑\u001b[0m 764 \n",
      "---\n",
      "Q 722+754\n",
      "T 1476\n",
      "\u001b[92m☑\u001b[0m 1476\n",
      "---\n",
      "Q 29+597 \n",
      "T 626 \n",
      "\u001b[92m☑\u001b[0m 626 \n",
      "---\n",
      "Q 793+30 \n",
      "T 823 \n",
      "\u001b[92m☑\u001b[0m 823 \n",
      "---\n",
      "Q 720+23 \n",
      "T 743 \n",
      "\u001b[92m☑\u001b[0m 743 \n",
      "---\n",
      "Q 99+298 \n",
      "T 397 \n",
      "\u001b[92m☑\u001b[0m 397 \n",
      "---\n"
     ]
    }
   ],
   "source": [
    "# Try replacing GRU, or SimpleRNN.\n",
    "RNN = layers.LSTM\n",
    "HIDDEN_SIZE = 128\n",
    "BATCH_SIZE = 128\n",
    "LAYERS = 1\n",
    "\n",
    "print('Build model...')\n",
    "model = Sequential()\n",
    "\n",
    "# \"Encode\" the input sequence using an RNN, producing an output of HIDDEN_SIZE.\n",
    "# Note: In a situation where your input sequences have a variable length,\n",
    "# use input_shape=(None, num_feature).\n",
    "model.add(RNN(HIDDEN_SIZE, input_shape=(MAXLEN, len(chars))))\n",
    "\n",
    "# As the decoder RNN's input, repeatedly provide with the last hidden state of\n",
    "# RNN for each time step. Repeat 'DIGITS + 1' times as that's the maximum\n",
    "# length of output, e.g., when DIGITS=3, max output is 999+999=1998.\n",
    "model.add(layers.RepeatVector(DIGITS + 1))\n",
    "\n",
    "# The decoder RNN could be multiple layers stacked or a single layer.\n",
    "for _ in range(LAYERS):\n",
    "    # By setting return_sequences to True, return not only the last output but\n",
    "    # all the outputs so far in the form of (num_samples, timesteps,\n",
    "    # output_dim). This is necessary as TimeDistributed in the below expects\n",
    "    # the first dimension to be the timesteps.\n",
    "    model.add(RNN(HIDDEN_SIZE, return_sequences=True))\n",
    "\n",
    "# Apply a dense layer to the every temporal slice of an input. For each of step\n",
    "# of the output sequence, decide which character should be chosen.\n",
    "model.add(layers.TimeDistributed(layers.Dense(len(chars))))\n",
    "model.add(layers.Activation('softmax'))\n",
    "model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])\n",
    "model.summary()\n",
    "\n",
    "# Train the model each generation and show predictions against the validation\n",
    "# dataset.\n",
    "for iteration in range(1, 200):\n",
    "    print()\n",
    "    print('-' * 50)\n",
    "    print('Iteration', iteration)\n",
    "    model.fit(x_train, y_train,\n",
    "              batch_size=BATCH_SIZE,\n",
    "              epochs=1,\n",
    "              validation_data=(x_val, y_val))\n",
    "    # Select 10 samples from the validation set at random so we can visualize\n",
    "    # errors.\n",
    "    for i in range(10):\n",
    "        ind = np.random.randint(0, len(x_val))\n",
    "        rowx, rowy = x_val[np.array([ind])], y_val[np.array([ind])]\n",
    "        preds = model.predict_classes(rowx, verbose=0)\n",
    "        q = ctable.decode(rowx[0])\n",
    "        correct = ctable.decode(rowy[0])\n",
    "        guess = ctable.decode(preds[0], calc_argmax=False)\n",
    "        print('Q', q[::-1] if INVERT else q)\n",
    "        print('T', correct)\n",
    "        if correct == guess:\n",
    "            print(colors.ok + '☑' + colors.close, end=\" \")\n",
    "        else:\n",
    "            print(colors.fail + '☒' + colors.close, end=\" \")\n",
    "        print(guess)\n",
    "        print('---')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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