Notebook_8_Cross_Validation_Nonunique_Name_Replacement.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Notebook 2: CNN\n",
    "\n",
    "## Overview: \n",
    "\n",
    "1. Begin by importing and getting the embeddings and word to index mappings we created in [Notebook 1: Embed Words](Notebook_1_Embed_Words.ipynb)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Parameters\n",
    "# ==================================================\n",
    "\n",
    "# Model Hyperparameters\n",
    "embedding_dim = 20  #Dimensionality of character embedding (default: 128)\n",
    "filter_sizes =  \"3,4,5\" #\"Comma-separated filter sizes (default: '3,4,5')\")\n",
    "num_filters = 50  #\"Number of filters per filter size (default: 128)\")\n",
    "dropout_keep_prob = 0.5 #\"Dropout keep probability (default: 0.5)\")\n",
    "l2_reg_lambda = 3.0 #\"L2 regularizaion lambda (default: 0.0)\")\n",
    "\n",
    "# Training parameters\n",
    "batch_size = 64 # \"Batch Size (default: 64)\")\n",
    "num_epochs = 500 #\"Number of training epochs (default: 200)\")\n",
    "evaluate_every = 100  #\"Evaluate model on dev set after this many steps (default: 100)\")\n",
    "checkpoint_every = 10000 # \"Save model after this many steps (default: 100)\")\n",
    "\n",
    "# Evaluation Parameters\n",
    "num_folds = 10 # number of cross validation folds \n",
    "\n",
    "# Misc Parameters\n",
    "allow_soft_placement = True # \"Allow device soft device placement\")\n",
    "log_device_placement = False  #\"Log placement of ops on devices\")\n",
    "display_train_steps = False # toggles output of training step results\n",
    "\n",
    "run_name = \"nonunique-names\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import cPickle as pickle\n",
    "from tensorflow.models.rnn.rnn_cell import BasicLSTMCell, LSTMCell \n",
    "import itertools\n",
    "from collections import Counter\n",
    "import csv\n",
    "import re\n",
    "import numpy as np\n",
    "import string"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "embeddings = None\n",
    "mappings = None\n",
    "rows = None\n",
    "\n",
    "with open(\"word_embeddings.pkl\", \"rb\") as f:\n",
    "    embeddings = pickle.load(f)\n",
    "with open(\"word_mappings.pkl\", \"rb\") as f:\n",
    "    mappings = pickle.load(f)\n",
    "    \n",
    "\n",
    "urlFinder = re.compile('\\w+:\\/{2}[\\d\\w-]+(\\.[\\d\\w-]+)*(?:(?:\\/[^\\s/]*))*')\n",
    "atNameFinder = re.compile(r'@([A-Za-z0-9_]+)')\n",
    "atNameCounter = 0\n",
    "\n",
    "exclude_punc = set([\n",
    "        \"!\",\n",
    "        \"?\",\n",
    "        \".\",\n",
    "        \",\",\n",
    "        \":\",\n",
    "        \";\",\n",
    "        \"'\",\n",
    "        \"\\\"\",\n",
    "        \"“\",\n",
    "        \"’\",\n",
    "        \"-\"\n",
    "])\n",
    "\n",
    "sentences = []\n",
    "labels = []\n",
    "x = []\n",
    "y = []\n",
    "_y = []\n",
    "\n",
    "with open('data.csv', 'rb') as f:\n",
    "    reader = csv.reader(f, delimiter=',')   \n",
    "    \n",
    "    for row in reader:\n",
    "        words = []\n",
    "        \n",
    "        for word in row[1] \\\n",
    "            .strip() \\\n",
    "            .replace(\"&amp;\", \"\") \\\n",
    "            .replace(\"&gt;\",\"\") \\\n",
    "            .replace(\"&lt;\", \"\") \\\n",
    "            .lower().split():\n",
    "            \n",
    "            if urlFinder.match(word):\n",
    "                words.append(\"<URL/>\")\n",
    "            elif atNameFinder.search(word):\n",
    "                words.append(\"<AT_NAME_/>\")\n",
    "            else:\n",
    "                word = ''.join(ch for ch in word if ch not in exclude_punc)\n",
    "                words.append(word)\n",
    "        sentences.append(words)\n",
    "        labels.append(([0, 1] if row[0] == \"example\" else [1, 0]))\n",
    "        _y.append(1 if row[0] == \"example\" else 0)\n",
    "\n",
    "\n",
    "sequence_length = max(len(i) for i in sentences)\n",
    "padded_sentences = []\n",
    "for i in range(len(sentences)):\n",
    "    sentence = sentences[i]\n",
    "    num_padding = sequence_length - len(sentence)\n",
    "    new_sentence = sentence + [\"<PAD/>\"] * num_padding\n",
    "    padded_sentences.append(new_sentence)\n",
    "    \n",
    " \n",
    "word_counts = Counter(itertools.chain(*padded_sentences))\n",
    "\n",
    "# Mapping from index to word\n",
    "vocabulary_inv = [x[0] for x in word_counts.most_common()]\n",
    "# Mapping from word to index\n",
    "vocabulary = {x: i for i, x in enumerate(vocabulary_inv)}\n",
    "\n",
    "x = np.array([[vocabulary[word] for word in sentence] for sentence in padded_sentences])\n",
    "y = np.array(labels)\n",
    "_y = np.array(_y)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "\n",
    "\n",
    "class TextCNN(object):\n",
    "    \"\"\"\n",
    "    A CNN for text classification.\n",
    "    Uses an embedding layer, followed by a convolutional, max-pooling and softmax layer.\n",
    "    \"\"\"\n",
    "    def __init__(\n",
    "      self, sequence_length, num_classes, vocab_size,\n",
    "      embedding_size, filter_sizes, num_filters, l2_reg_lambda=0.0):\n",
    "\n",
    "        # Placeholders for input, output and dropout\n",
    "        self.input_x = tf.placeholder(tf.int32, [None, sequence_length], name=\"input_x\")\n",
    "        self.input_y = tf.placeholder(tf.float32, [None, num_classes], name=\"input_y\")\n",
    "        self.dropout_keep_prob = tf.placeholder(tf.float32, name=\"dropout_keep_prob\")\n",
    "        self.t = tf.placeholder(tf.int32, [None], name=\"t\")\n",
    "        self.f = tf.placeholder(tf.int32, [None], name=\"f\")\n",
    "\n",
    "        # Keeping track of l2 regularization loss (optional)\n",
    "        l2_loss = tf.constant(0.0)\n",
    "\n",
    "        # Embedding layer\n",
    "        with tf.device('/cpu:0'), tf.name_scope(\"embedding\"):\n",
    "            W = tf.Variable(\n",
    "                tf.random_uniform([vocab_size, embedding_size], -1.0, 1.0),\n",
    "                name=\"W\")\n",
    "            self.embedded_chars = tf.nn.embedding_lookup(W, self.input_x)\n",
    "            self.embedded_chars_expanded = tf.expand_dims(self.embedded_chars, -1)\n",
    "\n",
    "        # Create a convolution + maxpool layer for each filter size\n",
    "        pooled_outputs = []\n",
    "        for i, filter_size in enumerate(filter_sizes):\n",
    "            with tf.name_scope(\"conv-maxpool-%s\" % filter_size):\n",
    "                # Convolution Layer\n",
    "                filter_shape = [filter_size, embedding_size, 1, num_filters]\n",
    "                W = tf.Variable(tf.truncated_normal(filter_shape, stddev=0.1), name=\"W\")\n",
    "                b = tf.Variable(tf.constant(0.1, shape=[num_filters]), name=\"b\")\n",
    "                conv = tf.nn.conv2d(\n",
    "                    self.embedded_chars_expanded,\n",
    "                    W,\n",
    "                    strides=[1, 1, 1, 1],\n",
    "                    padding=\"VALID\",\n",
    "                    name=\"conv\")\n",
    "                # Apply nonlinearity\n",
    "                h = tf.nn.relu(tf.nn.bias_add(conv, b), name=\"relu\")\n",
    "                # Maxpooling over the outputs\n",
    "                pooled = tf.nn.max_pool(\n",
    "                    h,\n",
    "                    ksize=[1, sequence_length - filter_size + 1, 1, 1],\n",
    "                    strides=[1, 1, 1, 1],\n",
    "                    padding='VALID',\n",
    "                    name=\"pool\")\n",
    "                pooled_outputs.append(pooled)\n",
    "\n",
    "        # Combine all the pooled features\n",
    "        num_filters_total = num_filters * len(filter_sizes)\n",
    "        self.h_pool = tf.concat(3, pooled_outputs)\n",
    "        self.h_pool_flat = tf.reshape(self.h_pool, [-1, num_filters_total])\n",
    "\n",
    "        # Add dropout\n",
    "        with tf.name_scope(\"dropout\"):\n",
    "            self.h_drop = tf.nn.dropout(self.h_pool_flat, self.dropout_keep_prob)\n",
    "\n",
    "        # Final (unnormalized) scores and predictions\n",
    "        with tf.name_scope(\"output\"):\n",
    "            W = tf.Variable(tf.truncated_normal([num_filters_total, num_classes], stddev=0.1), name=\"W\")\n",
    "            b = tf.Variable(tf.constant(0.1, shape=[num_classes]), name=\"b\")\n",
    "            l2_loss += tf.nn.l2_loss(W)\n",
    "            l2_loss += tf.nn.l2_loss(b)\n",
    "            self.scores = tf.nn.xw_plus_b(self.h_drop, W, b, name=\"scores\")\n",
    "            self.predictions = tf.argmax(self.scores, 1, name=\"predictions\")\n",
    "\n",
    "        # CalculateMean cross-entropy loss\n",
    "        with tf.name_scope(\"loss\"):\n",
    "            losses = tf.nn.softmax_cross_entropy_with_logits(self.scores, self.input_y)\n",
    "            self.loss = tf.reduce_mean(losses) + l2_reg_lambda * l2_loss\n",
    "\n",
    "        # Accuracy\n",
    "        with tf.name_scope(\"accuracy\"):\n",
    "            correct_predictions = tf.equal(self.predictions, tf.argmax(self.input_y, 1))\n",
    "            self.accuracy = tf.reduce_mean(tf.cast(correct_predictions, \"float\"), name=\"accuracy\")\n",
    "            \n",
    "        with tf.name_scope(\"sensitivity_and_specificity\"):\n",
    "            t = tf.fill(tf.shape(self.predictions), tf.cast(1, \"int64\"))\n",
    "            f = tf.fill(tf.shape(self.predictions), tf.cast(0, \"int64\"))\n",
    "            \n",
    "            TN = tf.size( \n",
    "                tf.where(\n",
    "                    tf.logical_and(\n",
    "                        tf.equal(\n",
    "                            tf.argmax(self.input_y, 1),\n",
    "                            f,\n",
    "                            name=\"equal_a\"\n",
    "                        ),\n",
    "                        tf.equal(\n",
    "                            self.predictions,\n",
    "                            f,\n",
    "                            name=\"equal_b\"\n",
    "                        )\n",
    "                    )\n",
    "                )\n",
    "            )\n",
    "\n",
    "            FP = tf.size(\n",
    "                tf.where(\n",
    "                    tf.logical_and(\n",
    "                        tf.equal(\n",
    "                            tf.argmax(self.input_y, 1),\n",
    "                            f,\n",
    "                            name=\"equal_c\"\n",
    "                        ),\n",
    "                        tf.equal(\n",
    "                            self.predictions,\n",
    "                           t,\n",
    "                            name=\"equal_d\"\n",
    "                        )\n",
    "                    )\n",
    "                )\n",
    "            )    \n",
    "\n",
    "            FN = tf.size(\n",
    "                tf.where(\n",
    "                    tf.logical_and(\n",
    "                        tf.equal(\n",
    "                            tf.argmax(self.input_y, 1),\n",
    "                            t,\n",
    "                            name=\"equal_f\"\n",
    "                        ),\n",
    "                        tf.equal(\n",
    "                            self.predictions,\n",
    "                            f,\n",
    "                            name=\"equal_g\"\n",
    "                        )\n",
    "                    )\n",
    "                )\n",
    "            )\n",
    "\n",
    "\n",
    "            TP = tf.size(\n",
    "                tf.where(\n",
    "                    tf.logical_and(\n",
    "                        tf.equal(\n",
    "                            tf.argmax(self.input_y, 1),\n",
    "                            t,\n",
    "                            name=\"equal_h\"\n",
    "                        ),\n",
    "                        tf.equal(\n",
    "                            self.predictions,\n",
    "                            t,\n",
    "                            name=\"equal_i\"\n",
    "                        )\n",
    "                    )\n",
    "                )\n",
    "            )\n",
    "\n",
    "            self.sensitivity = tf.div(\n",
    "                tf.cast(TP, \"float64\"),\n",
    "                tf.cast(\n",
    "                    tf.add(\n",
    "                        TP,\n",
    "                        FN\n",
    "                    ),\n",
    "                    \"float64\"\n",
    "                )\n",
    "            )\n",
    "            \n",
    "            self.specificity = tf.div(\n",
    "                tf.cast(TN, \"float64\"),\n",
    "                tf.cast(\n",
    "                    tf.add(\n",
    "                        TN,\n",
    "                        FP\n",
    "                    ),\n",
    "                    \"float64\"\n",
    "                )\n",
    "            )\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def batch_iter(data, batch_size, num_epochs):\n",
    "    \"\"\"\n",
    "    Generates a batch iterator for a dataset.\n",
    "    \"\"\"\n",
    "    data = np.array(data)\n",
    "    data_size = len(data)\n",
    "    num_batches_per_epoch = int(len(data)/batch_size) + 1\n",
    "    for epoch in range(num_epochs):\n",
    "        # Shuffle the data at each epoch\n",
    "        shuffle_indices = np.random.permutation(np.arange(data_size))\n",
    "        shuffled_data = data[shuffle_indices]\n",
    "        for batch_num in range(num_batches_per_epoch):\n",
    "            start_index = batch_num * batch_size\n",
    "            end_index = min((batch_num + 1) * batch_size, data_size)\n",
    "            yield shuffled_data[start_index:end_index]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loading data...\n",
      "Writing to /notebooks/AdHClassification/Expiriment #1.3 - Non-Candidate Tweets Included/runs/1458053202\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:46:48.653407: step 100, loss 3.29157, acc 0.911704\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:46:53.580117: step 200, loss 2.77684, acc 0.911704\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:46:58.535706: step 300, loss 2.3678, acc 0.911704\n",
      "\n",
      "\n",
      "Final Evaluation for fold 0:\n",
      "2016-03-15T14:47:00.778929: step 345, loss 2.20421, acc 0.911704\n",
      "2016-03-15T14:47:00.783079: step 345, loss 2.0769, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.785509: step 345, loss 2.05508, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.787537: step 345, loss 2.19644, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.789559: step 345, loss 1.99297, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.791797: step 345, loss 2.02208, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.793751: step 345, loss 2.0169, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.795524: step 345, loss 2.06154, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.797449: step 345, loss 3.27097, acc 0\n",
      "\n",
      "2016-03-15T14:47:00.799249: step 345, loss 2.10103, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.801189: step 345, loss 1.99408, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.803056: step 345, loss 3.61384, acc 0\n",
      "\n",
      "2016-03-15T14:47:00.804803: step 345, loss 3.71928, acc 0\n",
      "\n",
      "2016-03-15T14:47:00.806613: step 345, loss 2.03935, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.808350: step 345, loss 1.98803, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.810405: step 345, loss 2.17498, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.812101: step 345, loss 2.03139, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.813639: step 345, loss 1.97669, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.815149: step 345, loss 2.14292, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.816597: step 345, loss 2.09603, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.818076: step 345, loss 2.07383, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.819615: step 345, loss 2.04293, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.821173: step 345, loss 2.08092, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.822776: step 345, loss 2.06432, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.824341: step 345, loss 2.05112, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.826139: step 345, loss 2.07072, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.827741: step 345, loss 2.06927, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.829348: step 345, loss 2.05059, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.830848: step 345, loss 2.20631, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.833177: step 345, loss 1.99248, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.834666: step 345, loss 2.11559, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.836349: step 345, loss 1.96842, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.838065: step 345, loss 2.11474, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.839490: step 345, loss 1.98936, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.840924: step 345, loss 2.00658, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.842500: step 345, loss 2.05697, acc 1\n",
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      "2016-03-15T14:47:00.845271: step 345, loss 2.03327, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.846862: step 345, loss 3.9986, acc 0\n",
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      "\n",
      "2016-03-15T14:47:00.853317: step 345, loss 2.10313, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.854935: step 345, loss 3.95926, acc 0\n",
      "\n",
      "2016-03-15T14:47:00.856532: step 345, loss 2.12997, acc 1\n",
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      "2016-03-15T14:47:00.857937: step 345, loss 2.01033, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.859580: step 345, loss 2.1218, acc 1\n",
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      "2016-03-15T14:47:00.862599: step 345, loss 2.0793, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.864052: step 345, loss 2.07586, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.865537: step 345, loss 3.39795, acc 0\n",
      "\n",
      "2016-03-15T14:47:00.866970: step 345, loss 3.49205, acc 0\n",
      "\n",
      "2016-03-15T14:47:00.868797: step 345, loss 3.57897, acc 0\n",
      "\n",
      "2016-03-15T14:47:00.870470: step 345, loss 2.02857, acc 1\n",
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      "\n",
      "2016-03-15T14:47:00.879189: step 345, loss 2.05818, acc 1\n",
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      "\n",
      "2016-03-15T14:47:00.882096: step 345, loss 2.06644, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.884272: step 345, loss 2.07139, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.885821: step 345, loss 2.04682, acc 1\n",
      "\n",
      "2016-03-15T14:47:00.887441: step 345, loss 2.06193, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:47:01.596850: step 345, loss 2.04333, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.598128: step 345, loss 1.99637, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.599952: step 345, loss 1.99091, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.601448: step 345, loss 2.09211, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.603379: step 345, loss 1.99593, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.605130: step 345, loss 2.03677, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.606728: step 345, loss 2.06892, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.608167: step 345, loss 2.0568, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.610421: step 345, loss 2.08766, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.612063: step 345, loss 2.01896, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.613591: step 345, loss 1.99065, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.615207: step 345, loss 2.04169, acc 1\n",
      "\n",
      "2016-03-15T14:47:01.616685: step 345, loss 2.05964, acc 1\n",
      "\n",
      "True Positives 0\n",
      "True Negatives 444\n",
      "False Positives 0\n",
      "False Negatives 43\n",
      "Sensitivity: 0.0\n",
      "Specificity: 1.0\n",
      "\n",
      "Writing to /notebooks/AdHClassification/Expiriment #1.3 - Non-Candidate Tweets Included/runs/1458053222\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:47:08.286830: step 100, loss 2.99698, acc 0.948665\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:47:13.251645: step 200, loss 2.53674, acc 0.948665\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:47:18.155763: step 300, loss 2.15409, acc 0.948665\n",
      "\n",
      "\n",
      "Final Evaluation for fold 1:\n",
      "2016-03-15T14:47:20.438147: step 345, loss 2.00454, acc 0.948665\n",
      "2016-03-15T14:47:20.442563: step 345, loss 1.96857, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.444898: step 345, loss 3.85767, acc 0\n",
      "\n",
      "2016-03-15T14:47:20.447458: step 345, loss 1.89752, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.449624: step 345, loss 1.87541, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.451580: step 345, loss 1.91255, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.453439: step 345, loss 1.95372, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.455187: step 345, loss 1.92086, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.457076: step 345, loss 1.88115, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.458841: step 345, loss 1.86604, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.460450: step 345, loss 1.95714, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.462292: step 345, loss 1.9017, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.463995: step 345, loss 1.90067, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.465561: step 345, loss 1.87728, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.467234: step 345, loss 1.85742, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.469140: step 345, loss 1.88592, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.470995: step 345, loss 1.86719, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.472932: step 345, loss 1.87848, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.474527: step 345, loss 1.89224, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.476106: step 345, loss 1.91922, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:47:20.479184: step 345, loss 1.90687, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.480792: step 345, loss 1.84048, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.482255: step 345, loss 1.89202, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.483939: step 345, loss 1.89174, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.485546: step 345, loss 1.90535, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.487362: step 345, loss 1.85056, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.488868: step 345, loss 1.94529, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.491493: step 345, loss 1.89571, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.493355: step 345, loss 1.9459, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.495003: step 345, loss 1.89805, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.496810: step 345, loss 1.90058, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.498458: step 345, loss 3.71067, acc 0\n",
      "\n",
      "2016-03-15T14:47:20.499976: step 345, loss 1.88114, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.501505: step 345, loss 1.91652, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.503013: step 345, loss 1.84784, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.504530: step 345, loss 1.89041, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:47:20.507855: step 345, loss 1.88264, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.509395: step 345, loss 1.8942, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.511147: step 345, loss 1.90453, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.513319: step 345, loss 1.92154, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.514999: step 345, loss 1.91303, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.517132: step 345, loss 1.86086, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.519050: step 345, loss 1.90913, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.520614: step 345, loss 1.83237, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.522189: step 345, loss 1.87835, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.523671: step 345, loss 1.85644, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.525192: step 345, loss 1.90793, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.526790: step 345, loss 1.89108, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.528315: step 345, loss 1.84163, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.529931: step 345, loss 1.91301, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.531405: step 345, loss 1.88346, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.533026: step 345, loss 1.87949, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.534733: step 345, loss 1.86622, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.536129: step 345, loss 1.89109, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.537813: step 345, loss 1.91765, acc 1\n",
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      "2016-03-15T14:47:20.539416: step 345, loss 2.04409, acc 1\n",
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      "2016-03-15T14:47:20.540891: step 345, loss 1.86852, acc 1\n",
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      "2016-03-15T14:47:20.543519: step 345, loss 1.92545, acc 1\n",
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      "2016-03-15T14:47:20.557235: step 345, loss 1.97433, acc 1\n",
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      "\n",
      "2016-03-15T14:47:20.560278: step 345, loss 1.85176, acc 1\n",
      "\n",
      "2016-03-15T14:47:20.561932: step 345, loss 1.89933, acc 1\n",
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      "2016-03-15T14:47:21.114508: step 345, loss 3.84847, acc 0\n",
      "\n",
      "2016-03-15T14:47:21.116214: step 345, loss 1.88354, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.118002: step 345, loss 1.8883, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.119944: step 345, loss 1.8986, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.121779: step 345, loss 1.88674, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.123453: step 345, loss 4.50475, acc 0\n",
      "\n",
      "2016-03-15T14:47:21.125347: step 345, loss 1.92594, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.127154: step 345, loss 1.90283, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.128846: step 345, loss 1.88626, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.130951: step 345, loss 1.95803, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.132963: step 345, loss 1.88214, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.135043: step 345, loss 1.8834, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.136934: step 345, loss 4.31259, acc 0\n",
      "\n",
      "2016-03-15T14:47:21.138630: step 345, loss 1.88233, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.140020: step 345, loss 1.88792, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.141676: step 345, loss 1.9047, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.143576: step 345, loss 1.89717, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.145253: step 345, loss 1.90108, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.147150: step 345, loss 1.89424, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.148783: step 345, loss 1.92185, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.150496: step 345, loss 1.85615, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.152263: step 345, loss 1.91588, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.153673: step 345, loss 1.8883, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.155194: step 345, loss 3.87119, acc 0\n",
      "\n",
      "2016-03-15T14:47:21.156906: step 345, loss 1.86515, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.158715: step 345, loss 1.93361, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.162190: step 345, loss 1.89218, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.164023: step 345, loss 1.96299, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.165788: step 345, loss 1.90778, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.167476: step 345, loss 1.88388, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.169340: step 345, loss 1.86322, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.170994: step 345, loss 1.92956, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.172709: step 345, loss 3.98645, acc 0\n",
      "\n",
      "2016-03-15T14:47:21.174394: step 345, loss 1.91998, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.176377: step 345, loss 1.86282, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.178255: step 345, loss 1.89002, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.179940: step 345, loss 1.88668, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.181818: step 345, loss 1.86343, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.183446: step 345, loss 1.88962, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.185210: step 345, loss 3.49578, acc 0\n",
      "\n",
      "2016-03-15T14:47:21.186977: step 345, loss 1.85257, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.188728: step 345, loss 1.88271, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.190346: step 345, loss 1.87468, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.191974: step 345, loss 1.93817, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.193329: step 345, loss 1.92828, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.194913: step 345, loss 1.85651, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.196891: step 345, loss 1.88307, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.198602: step 345, loss 1.87443, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.200380: step 345, loss 1.86676, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.202071: step 345, loss 1.9296, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.203936: step 345, loss 1.84241, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.205489: step 345, loss 1.87857, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.207247: step 345, loss 1.90142, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.209261: step 345, loss 1.86695, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.210954: step 345, loss 1.87881, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.213793: step 345, loss 1.93554, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.215583: step 345, loss 1.84563, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.217582: step 345, loss 1.85898, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.219266: step 345, loss 1.89647, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.220850: step 345, loss 1.85844, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.222540: step 345, loss 3.74441, acc 0\n",
      "\n",
      "2016-03-15T14:47:21.224365: step 345, loss 1.85017, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.226300: step 345, loss 1.88035, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.227786: step 345, loss 1.96618, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.229760: step 345, loss 1.85647, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.231394: step 345, loss 1.92779, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.233133: step 345, loss 1.98995, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.234954: step 345, loss 1.88507, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.237060: step 345, loss 1.86973, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.238839: step 345, loss 1.88315, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.240580: step 345, loss 1.88057, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.242317: step 345, loss 1.89574, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.244112: step 345, loss 1.89944, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.245836: step 345, loss 1.95608, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.247596: step 345, loss 1.93817, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.249442: step 345, loss 1.85843, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.251276: step 345, loss 1.88089, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.252735: step 345, loss 1.90187, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.254414: step 345, loss 1.90206, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.256261: step 345, loss 1.90243, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.257777: step 345, loss 1.86579, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.259335: step 345, loss 1.87101, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.261148: step 345, loss 1.91306, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.262854: step 345, loss 4.0339, acc 0\n",
      "\n",
      "2016-03-15T14:47:21.265657: step 345, loss 1.91323, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.267652: step 345, loss 4.03829, acc 0\n",
      "\n",
      "2016-03-15T14:47:21.269770: step 345, loss 3.85515, acc 0\n",
      "\n",
      "2016-03-15T14:47:21.271591: step 345, loss 1.91958, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.273424: step 345, loss 1.9509, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.275220: step 345, loss 1.93554, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.276989: step 345, loss 1.90516, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.278880: step 345, loss 1.9285, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.280620: step 345, loss 1.90489, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.282340: step 345, loss 1.89341, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.284199: step 345, loss 1.89207, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.286039: step 345, loss 1.88305, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.287832: step 345, loss 1.83606, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.289809: step 345, loss 1.92532, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.291502: step 345, loss 1.8912, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.293249: step 345, loss 1.88115, acc 1\n",
      "\n",
      "2016-03-15T14:47:21.295056: step 345, loss 1.88935, acc 1\n",
      "\n",
      "True Positives 0\n",
      "True Negatives 462\n",
      "False Positives 0\n",
      "False Negatives 25\n",
      "Sensitivity: 0.0\n",
      "Specificity: 1.0\n",
      "\n",
      "Writing to /notebooks/AdHClassification/Expiriment #1.3 - Non-Candidate Tweets Included/runs/1458053241\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:47:27.734110: step 100, loss 3.47444, acc 0.969199\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:47:32.793887: step 200, loss 2.92912, acc 0.969199\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:47:37.834826: step 300, loss 2.48658, acc 0.969199\n",
      "\n",
      "\n",
      "Final Evaluation for fold 2:\n",
      "2016-03-15T14:47:40.141344: step 345, loss 2.31329, acc 0.969199\n",
      "2016-03-15T14:47:40.144589: step 345, loss 2.16731, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.146848: step 345, loss 2.4029, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.148850: step 345, loss 2.25159, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.151938: step 345, loss 2.24934, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.154470: step 345, loss 2.26743, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.156884: step 345, loss 2.20778, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.158960: step 345, loss 2.19514, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.161134: step 345, loss 3.97665, acc 0\n",
      "\n",
      "2016-03-15T14:47:40.163088: step 345, loss 2.24964, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.164709: step 345, loss 2.21, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.166306: step 345, loss 2.25152, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.167786: step 345, loss 2.26815, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.169335: step 345, loss 2.21463, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.170939: step 345, loss 2.19529, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.172445: step 345, loss 2.23186, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.173922: step 345, loss 2.25423, acc 1\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:47:40.180256: step 345, loss 2.25075, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.181613: step 345, loss 2.26921, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.183237: step 345, loss 3.40491, acc 0\n",
      "\n",
      "2016-03-15T14:47:40.184761: step 345, loss 2.247, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:47:40.187746: step 345, loss 2.27648, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.189328: step 345, loss 4.42046, acc 0\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "2016-03-15T14:47:40.637433: step 345, loss 2.31913, acc 1\n",
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      "\n",
      "2016-03-15T14:47:40.847554: step 345, loss 3.74419, acc 0\n",
      "\n",
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      "2016-03-15T14:47:40.925148: step 345, loss 2.22461, acc 1\n",
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      "\n",
      "2016-03-15T14:47:40.930430: step 345, loss 2.18235, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:47:40.933833: step 345, loss 2.27488, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.935410: step 345, loss 2.3031, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.937249: step 345, loss 2.24248, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.938995: step 345, loss 2.27203, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.940483: step 345, loss 2.24191, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.942012: step 345, loss 2.31306, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.943651: step 345, loss 2.32556, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.945146: step 345, loss 2.36509, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.946831: step 345, loss 2.28023, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.948306: step 345, loss 2.28223, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.950491: step 345, loss 2.24001, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.952575: step 345, loss 2.29274, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.954431: step 345, loss 2.20677, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.956180: step 345, loss 2.3213, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.957961: step 345, loss 2.29869, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.959719: step 345, loss 2.30211, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.961227: step 345, loss 2.17896, acc 1\n",
      "\n",
      "2016-03-15T14:47:40.963066: step 345, loss 2.22039, acc 1\n",
      "\n",
      "True Positives 0\n",
      "True Negatives 472\n",
      "False Positives 0\n",
      "False Negatives 15\n",
      "Sensitivity: 0.0\n",
      "Specificity: 1.0\n",
      "\n",
      "Writing to /notebooks/AdHClassification/Expiriment #1.3 - Non-Candidate Tweets Included/runs/1458053261\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:47:47.466377: step 100, loss 3.00279, acc 0.887064\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:47:52.327558: step 200, loss 2.53359, acc 0.887064\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:47:57.295340: step 300, loss 2.14848, acc 0.887064\n",
      "\n",
      "\n",
      "Final Evaluation for fold 3:\n",
      "2016-03-15T14:47:59.545752: step 345, loss 1.99808, acc 0.887064\n",
      "2016-03-15T14:47:59.549680: step 345, loss 1.79828, acc 1\n",
      "\n",
      "2016-03-15T14:47:59.551900: step 345, loss 1.8451, acc 1\n",
      "\n",
      "2016-03-15T14:47:59.553841: step 345, loss 1.78117, acc 1\n",
      "\n",
      "2016-03-15T14:47:59.555708: step 345, loss 1.7593, acc 1\n",
      "\n",
      "2016-03-15T14:47:59.557169: step 345, loss 1.78552, acc 1\n",
      "\n",
      "2016-03-15T14:47:59.558692: step 345, loss 1.77449, acc 1\n",
      "\n",
      "2016-03-15T14:47:59.560300: step 345, loss 1.80068, acc 1\n",
      "\n",
      "2016-03-15T14:47:59.561698: step 345, loss 1.79268, acc 1\n",
      "\n",
      "2016-03-15T14:47:59.563743: step 345, loss 3.48512, acc 0\n",
      "\n",
      "2016-03-15T14:47:59.565327: step 345, loss 1.78196, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:48:00.274137: step 345, loss 1.8381, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.275958: step 345, loss 3.58128, acc 0\n",
      "\n",
      "2016-03-15T14:48:00.277761: step 345, loss 1.78224, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.279646: step 345, loss 1.73961, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.281258: step 345, loss 1.75775, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.282947: step 345, loss 1.7894, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.284724: step 345, loss 1.75839, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.286449: step 345, loss 1.78754, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.287926: step 345, loss 1.83089, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.289434: step 345, loss 1.84816, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.290993: step 345, loss 1.81621, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.292794: step 345, loss 1.79689, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.294672: step 345, loss 1.7817, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.296468: step 345, loss 1.81472, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.298481: step 345, loss 1.8414, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.300235: step 345, loss 1.90016, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.302274: step 345, loss 1.82547, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.304162: step 345, loss 1.77377, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.305566: step 345, loss 3.31802, acc 0\n",
      "\n",
      "2016-03-15T14:48:00.307261: step 345, loss 3.68452, acc 0\n",
      "\n",
      "2016-03-15T14:48:00.309040: step 345, loss 3.50472, acc 0\n",
      "\n",
      "2016-03-15T14:48:00.311061: step 345, loss 1.79341, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.312783: step 345, loss 1.75263, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.314519: step 345, loss 1.82074, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.316050: step 345, loss 1.79021, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.317726: step 345, loss 1.75934, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.319751: step 345, loss 1.90557, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.321610: step 345, loss 1.82616, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.323564: step 345, loss 1.77859, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.325206: step 345, loss 1.7904, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.326898: step 345, loss 1.812, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.328593: step 345, loss 1.75249, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.330507: step 345, loss 1.81048, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.332316: step 345, loss 1.80814, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.334074: step 345, loss 3.64142, acc 0\n",
      "\n",
      "2016-03-15T14:48:00.335841: step 345, loss 1.78532, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.337777: step 345, loss 1.76848, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.339651: step 345, loss 3.21649, acc 0\n",
      "\n",
      "2016-03-15T14:48:00.341474: step 345, loss 1.7534, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.343409: step 345, loss 1.79521, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.345152: step 345, loss 1.82693, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.346994: step 345, loss 1.78028, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.348364: step 345, loss 1.85065, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.350357: step 345, loss 1.82915, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.352290: step 345, loss 1.80466, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.354088: step 345, loss 1.78263, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.355904: step 345, loss 1.78122, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.357740: step 345, loss 1.8203, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.359497: step 345, loss 1.7738, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.361041: step 345, loss 1.77445, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.362565: step 345, loss 1.77366, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.364435: step 345, loss 1.75891, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.366208: step 345, loss 1.74989, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.367896: step 345, loss 1.76525, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.369923: step 345, loss 1.7898, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.371749: step 345, loss 1.7966, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.373471: step 345, loss 1.80818, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.375768: step 345, loss 1.80646, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.377625: step 345, loss 1.78506, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.379592: step 345, loss 1.80942, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.381717: step 345, loss 1.74912, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.383311: step 345, loss 1.88428, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.384862: step 345, loss 1.81726, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.386572: step 345, loss 1.83282, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.388201: step 345, loss 1.89657, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.389840: step 345, loss 1.79274, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.391529: step 345, loss 1.79459, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.393473: step 345, loss 1.75165, acc 1\n",
      "\n",
      "2016-03-15T14:48:00.395402: step 345, loss 1.77221, acc 1\n",
      "\n",
      "True Positives 0\n",
      "True Negatives 432\n",
      "False Positives 0\n",
      "False Negatives 55\n",
      "Sensitivity: 0.0\n",
      "Specificity: 1.0\n",
      "\n",
      "Writing to /notebooks/AdHClassification/Expiriment #1.3 - Non-Candidate Tweets Included/runs/1458053280\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:48:06.782598: step 100, loss 2.71795, acc 0.965092\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:48:11.739618: step 200, loss 2.28571, acc 0.965092\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:48:16.664306: step 300, loss 1.92485, acc 0.965092\n",
      "\n",
      "\n",
      "Final Evaluation for fold 4:\n",
      "2016-03-15T14:48:18.914597: step 345, loss 1.78767, acc 0.965092\n",
      "2016-03-15T14:48:18.917767: step 345, loss 1.75117, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.920747: step 345, loss 1.77482, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.922856: step 345, loss 1.70253, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.924887: step 345, loss 1.76429, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.926849: step 345, loss 1.75152, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.928555: step 345, loss 1.68605, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.930120: step 345, loss 1.7838, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.931801: step 345, loss 1.69904, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.933319: step 345, loss 1.69008, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.934773: step 345, loss 1.73946, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.936401: step 345, loss 1.823, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.938046: step 345, loss 1.79914, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.940353: step 345, loss 1.71835, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.941915: step 345, loss 1.72157, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.943478: step 345, loss 1.72792, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.945101: step 345, loss 1.82881, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.946654: step 345, loss 1.73256, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.948145: step 345, loss 1.72159, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.949796: step 345, loss 1.80716, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.951364: step 345, loss 1.76334, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.952969: step 345, loss 1.79331, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.954445: step 345, loss 1.71607, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.956052: step 345, loss 1.73454, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.957648: step 345, loss 1.79083, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.959279: step 345, loss 1.69448, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.960862: step 345, loss 1.71677, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.962474: step 345, loss 1.73543, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.964105: step 345, loss 1.72434, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.965615: step 345, loss 1.723, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.967055: step 345, loss 1.71484, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.968525: step 345, loss 1.72251, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.970800: step 345, loss 1.67398, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.972487: step 345, loss 1.66793, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.974209: step 345, loss 1.68911, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.975870: step 345, loss 1.69887, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.977382: step 345, loss 1.67359, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.978648: step 345, loss 1.65199, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.980275: step 345, loss 1.69724, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.981911: step 345, loss 1.73082, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.983490: step 345, loss 1.74788, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.984863: step 345, loss 1.76646, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.986620: step 345, loss 1.67191, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.988202: step 345, loss 1.65915, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.989782: step 345, loss 1.74041, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.991471: step 345, loss 1.70119, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.993126: step 345, loss 1.73584, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.994509: step 345, loss 1.69615, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.996080: step 345, loss 1.69265, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.998078: step 345, loss 1.75738, acc 1\n",
      "\n",
      "2016-03-15T14:48:18.999895: step 345, loss 1.72804, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.001660: step 345, loss 1.70337, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.003089: step 345, loss 1.73114, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.004471: step 345, loss 1.70871, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.006092: step 345, loss 1.71055, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.007917: step 345, loss 1.71823, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.009406: step 345, loss 1.693, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.010925: step 345, loss 1.84817, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.012537: step 345, loss 1.78696, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.014089: step 345, loss 1.68181, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.015564: step 345, loss 1.70636, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.016977: step 345, loss 1.75392, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.018476: step 345, loss 1.70886, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.020361: step 345, loss 1.75562, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.023894: step 345, loss 1.82742, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.025353: step 345, loss 1.76398, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.026990: step 345, loss 1.71495, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.028744: step 345, loss 1.75186, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.030271: step 345, loss 1.80381, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.031512: step 345, loss 1.72339, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.033033: step 345, loss 1.73905, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.034373: step 345, loss 1.80542, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.036075: step 345, loss 1.72735, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.037647: step 345, loss 1.69711, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.039045: step 345, loss 1.75335, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.041061: step 345, loss 1.86125, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.042635: step 345, loss 1.7486, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.044137: step 345, loss 1.91185, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.045528: step 345, loss 1.72223, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:48:19.048533: step 345, loss 1.70159, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.050742: step 345, loss 1.73475, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.052051: step 345, loss 1.72267, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.053743: step 345, loss 1.70114, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.055273: step 345, loss 1.73476, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.056755: step 345, loss 1.7081, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.058274: step 345, loss 1.67373, acc 1\n",
      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:48:19.062912: step 345, loss 1.73871, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.064539: step 345, loss 1.68141, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.066013: step 345, loss 1.77931, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.067491: step 345, loss 1.73063, acc 1\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:48:19.079231: step 345, loss 1.729, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.080648: step 345, loss 1.6942, acc 1\n",
      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:48:19.085362: step 345, loss 1.72581, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.087025: step 345, loss 1.68749, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.088500: step 345, loss 1.74979, acc 1\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:48:19.097669: step 345, loss 1.68619, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.099158: step 345, loss 1.67342, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.100998: step 345, loss 1.76779, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.102848: step 345, loss 1.77857, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.104819: step 345, loss 3.70021, acc 0\n",
      "\n",
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      "\n",
      "2016-03-15T14:48:19.108577: step 345, loss 3.46568, acc 0\n",
      "\n",
      "2016-03-15T14:48:19.110490: step 345, loss 3.72978, acc 0\n",
      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:48:19.124384: step 345, loss 3.42366, acc 0\n",
      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:48:19.488974: step 345, loss 1.68918, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.490725: step 345, loss 1.7387, acc 1\n",
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      "2016-03-15T14:48:19.495687: step 345, loss 1.71625, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:48:19.500690: step 345, loss 1.75577, acc 1\n",
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      "2016-03-15T14:48:19.502383: step 345, loss 1.69266, acc 1\n",
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      "2016-03-15T14:48:19.504266: step 345, loss 1.72332, acc 1\n",
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      "2016-03-15T14:48:19.506184: step 345, loss 1.70551, acc 1\n",
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      "2016-03-15T14:48:19.511696: step 345, loss 1.69993, acc 1\n",
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      "2016-03-15T14:48:19.513618: step 345, loss 1.78015, acc 1\n",
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      "2016-03-15T14:48:19.515555: step 345, loss 1.79355, acc 1\n",
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      "2016-03-15T14:48:19.519454: step 345, loss 1.81341, acc 1\n",
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      "2016-03-15T14:48:19.521392: step 345, loss 1.80663, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.523152: step 345, loss 1.71684, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.524883: step 345, loss 1.71931, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.526551: step 345, loss 1.70051, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.528364: step 345, loss 1.71838, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.530024: step 345, loss 1.72996, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.531771: step 345, loss 1.75777, acc 1\n",
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      "2016-03-15T14:48:19.533860: step 345, loss 1.67659, acc 1\n",
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      "2016-03-15T14:48:19.535574: step 345, loss 1.7426, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.537691: step 345, loss 1.71446, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.540427: step 345, loss 1.71342, acc 1\n",
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      "2016-03-15T14:48:19.541998: step 345, loss 1.72736, acc 1\n",
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      "2016-03-15T14:48:19.545892: step 345, loss 1.78406, acc 1\n",
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      "2016-03-15T14:48:19.547748: step 345, loss 1.70648, acc 1\n",
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      "\n",
      "2016-03-15T14:48:19.570452: step 345, loss 1.76283, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.572015: step 345, loss 1.73467, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:48:19.575277: step 345, loss 1.68159, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.576803: step 345, loss 1.6627, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.578359: step 345, loss 1.828, acc 1\n",
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      "2016-03-15T14:48:19.579971: step 345, loss 1.73207, acc 1\n",
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      "2016-03-15T14:48:19.581658: step 345, loss 1.66189, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.583329: step 345, loss 1.70789, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.584867: step 345, loss 1.72404, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.586341: step 345, loss 1.65753, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.587807: step 345, loss 1.65753, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.589506: step 345, loss 1.68461, acc 1\n",
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      "\n",
      "2016-03-15T14:48:19.595383: step 345, loss 1.73495, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.597010: step 345, loss 1.70837, acc 1\n",
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      "\n",
      "2016-03-15T14:48:19.600086: step 345, loss 1.71937, acc 1\n",
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      "2016-03-15T14:48:19.602834: step 345, loss 1.78596, acc 1\n",
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      "2016-03-15T14:48:19.605646: step 345, loss 1.76478, acc 1\n",
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      "2016-03-15T14:48:19.608481: step 345, loss 1.73446, acc 1\n",
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      "2016-03-15T14:48:19.630013: step 345, loss 1.72615, acc 1\n",
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      "2016-03-15T14:48:19.638608: step 345, loss 1.67967, acc 1\n",
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      "2016-03-15T14:48:19.640417: step 345, loss 1.80954, acc 1\n",
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      "2016-03-15T14:48:19.642624: step 345, loss 1.77234, acc 1\n",
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      "2016-03-15T14:48:19.646146: step 345, loss 1.71749, acc 1\n",
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      "2016-03-15T14:48:19.649754: step 345, loss 1.66137, acc 1\n",
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      "2016-03-15T14:48:19.655152: step 345, loss 1.66233, acc 1\n",
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      "2016-03-15T14:48:19.657192: step 345, loss 1.77108, acc 1\n",
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      "2016-03-15T14:48:19.658855: step 345, loss 1.70634, acc 1\n",
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      "2016-03-15T14:48:19.660612: step 345, loss 1.66447, acc 1\n",
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      "2016-03-15T14:48:19.664051: step 345, loss 1.66697, acc 1\n",
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      "2016-03-15T14:48:19.667752: step 345, loss 1.70663, acc 1\n",
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      "2016-03-15T14:48:19.669472: step 345, loss 1.71086, acc 1\n",
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      "2016-03-15T14:48:19.673263: step 345, loss 1.72982, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.675143: step 345, loss 1.75111, acc 1\n",
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      "2016-03-15T14:48:19.676976: step 345, loss 1.698, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.678679: step 345, loss 1.67626, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.680452: step 345, loss 1.78055, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.682305: step 345, loss 1.6863, acc 1\n",
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      "2016-03-15T14:48:19.683975: step 345, loss 1.75573, acc 1\n",
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      "2016-03-15T14:48:19.685737: step 345, loss 1.71106, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.687392: step 345, loss 1.67637, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.689267: step 345, loss 3.39012, acc 0\n",
      "\n",
      "2016-03-15T14:48:19.690929: step 345, loss 1.69914, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.692892: step 345, loss 1.74482, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.695369: step 345, loss 3.05233, acc 0\n",
      "\n",
      "2016-03-15T14:48:19.697133: step 345, loss 3.2957, acc 0\n",
      "\n",
      "2016-03-15T14:48:19.698903: step 345, loss 1.83641, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.700669: step 345, loss 1.706, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.702417: step 345, loss 1.78998, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.704160: step 345, loss 1.69109, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.705956: step 345, loss 1.69876, acc 1\n",
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      "2016-03-15T14:48:19.707564: step 345, loss 1.74988, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.709368: step 345, loss 1.71712, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.711179: step 345, loss 1.70083, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.712769: step 345, loss 3.21268, acc 0\n",
      "\n",
      "2016-03-15T14:48:19.714463: step 345, loss 1.71847, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.716298: step 345, loss 1.74787, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.718136: step 345, loss 1.72461, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.719981: step 345, loss 1.68715, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.721420: step 345, loss 1.77277, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.723099: step 345, loss 1.71963, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.724790: step 345, loss 1.70919, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.726533: step 345, loss 1.75017, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.728381: step 345, loss 1.69359, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.730097: step 345, loss 1.66904, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.731482: step 345, loss 1.7432, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.732946: step 345, loss 1.7532, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.734640: step 345, loss 1.71307, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.736738: step 345, loss 1.6567, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.738545: step 345, loss 1.71711, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.740246: step 345, loss 1.8087, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.741869: step 345, loss 3.32952, acc 0\n",
      "\n",
      "2016-03-15T14:48:19.743594: step 345, loss 1.73548, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.746035: step 345, loss 1.72357, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.747753: step 345, loss 1.6745, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.749967: step 345, loss 1.6564, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.751774: step 345, loss 1.70998, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.753556: step 345, loss 1.80286, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.755465: step 345, loss 1.698, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.757464: step 345, loss 1.70428, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.759489: step 345, loss 1.74614, acc 1\n",
      "\n",
      "2016-03-15T14:48:19.761456: step 345, loss 1.73823, acc 1\n",
      "\n",
      "True Positives 0\n",
      "True Negatives 470\n",
      "False Positives 0\n",
      "False Negatives 17\n",
      "Sensitivity: 0.0\n",
      "Specificity: 1.0\n",
      "\n",
      "Writing to /notebooks/AdHClassification/Expiriment #1.3 - Non-Candidate Tweets Included/runs/1458053300\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:48:26.342522: step 100, loss 3.34429, acc 0.909465\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:48:31.334203: step 200, loss 2.83871, acc 0.909465\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:48:36.472171: step 300, loss 2.41723, acc 0.909465\n",
      "\n",
      "\n",
      "Final Evaluation for fold 5:\n",
      "2016-03-15T14:48:38.715636: step 345, loss 2.24875, acc 0.909465\n",
      "2016-03-15T14:48:38.719539: step 345, loss 2.09008, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.721433: step 345, loss 2.08718, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.723103: step 345, loss 2.047, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.724755: step 345, loss 2.07473, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.726825: step 345, loss 2.03141, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.728978: step 345, loss 2.02077, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.730909: step 345, loss 2.04689, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.732960: step 345, loss 2.06342, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.735211: step 345, loss 2.06831, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.736874: step 345, loss 2.03647, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.738522: step 345, loss 2.02301, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.740214: step 345, loss 2.04228, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.741820: step 345, loss 2.10528, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.743672: step 345, loss 2.09832, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.745294: step 345, loss 2.03162, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.746809: step 345, loss 2.06776, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.748428: step 345, loss 2.07602, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.749937: step 345, loss 2.00027, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.751684: step 345, loss 2.09044, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.753408: step 345, loss 2.08517, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.754972: step 345, loss 2.05424, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.756553: step 345, loss 2.05444, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.757997: step 345, loss 2.05444, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.759587: step 345, loss 2.09803, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.761138: step 345, loss 2.0406, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.762779: step 345, loss 2.06178, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.764276: step 345, loss 2.13519, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.765689: step 345, loss 2.17863, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.767237: step 345, loss 2.02524, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.769580: step 345, loss 2.02486, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.771079: step 345, loss 2.04634, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.772712: step 345, loss 2.08642, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.774286: step 345, loss 2.07195, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.775830: step 345, loss 2.16611, acc 1\n",
      "\n",
      "2016-03-15T14:48:38.777485: step 345, loss 2.02558, acc 1\n",
      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:48:38.781948: step 345, loss 2.0563, acc 1\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:48:39.480405: step 345, loss 2.09874, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.482279: step 345, loss 2.05261, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.484025: step 345, loss 2.0668, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.485746: step 345, loss 2.35023, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.487466: step 345, loss 4.01688, acc 0\n",
      "\n",
      "2016-03-15T14:48:39.489249: step 345, loss 2.02915, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.491072: step 345, loss 2.03909, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.492821: step 345, loss 4.09634, acc 0\n",
      "\n",
      "2016-03-15T14:48:39.496231: step 345, loss 3.83717, acc 0\n",
      "\n",
      "2016-03-15T14:48:39.497870: step 345, loss 2.13937, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.499436: step 345, loss 2.05283, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.501009: step 345, loss 2.08611, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.502460: step 345, loss 2.12821, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.504067: step 345, loss 2.08798, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.505666: step 345, loss 2.10385, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.507258: step 345, loss 3.81774, acc 0\n",
      "\n",
      "2016-03-15T14:48:39.509461: step 345, loss 2.06513, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.510804: step 345, loss 2.11023, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.512525: step 345, loss 2.06266, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.514184: step 345, loss 2.12623, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.515679: step 345, loss 2.01851, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.517319: step 345, loss 2.02726, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.519016: step 345, loss 2.0751, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.520531: step 345, loss 2.02405, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.522169: step 345, loss 2.16819, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.523839: step 345, loss 2.10204, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.525305: step 345, loss 2.13783, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.526951: step 345, loss 2.09515, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.528634: step 345, loss 2.04041, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.530200: step 345, loss 3.85736, acc 0\n",
      "\n",
      "2016-03-15T14:48:39.531676: step 345, loss 2.08985, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.533073: step 345, loss 2.03905, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.534541: step 345, loss 2.04251, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.536149: step 345, loss 2.06491, acc 1\n",
      "\n",
      "2016-03-15T14:48:39.537457: step 345, loss 4.10395, acc 0\n",
      "\n",
      "True Positives 0\n",
      "True Negatives 442\n",
      "False Positives 0\n",
      "False Negatives 44\n",
      "Sensitivity: 0.0\n",
      "Specificity: 1.0\n",
      "\n",
      "Writing to /notebooks/AdHClassification/Expiriment #1.3 - Non-Candidate Tweets Included/runs/1458053320\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:48:46.081352: step 100, loss 3.80442, acc 0.760825\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:48:51.145997: step 200, loss 3.30017, acc 0.760825\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:48:56.186619: step 300, loss 2.85939, acc 0.760825\n",
      "\n",
      "\n",
      "Final Evaluation for fold 6:\n",
      "2016-03-15T14:48:58.422711: step 345, loss 2.68153, acc 0.760825\n",
      "2016-03-15T14:48:58.427098: step 345, loss 2.23421, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.429229: step 345, loss 2.22006, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.431525: step 345, loss 2.20244, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.433758: step 345, loss 2.26569, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.435822: step 345, loss 3.54069, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.437759: step 345, loss 2.23585, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.439913: step 345, loss 2.28492, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.441945: step 345, loss 2.34809, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.444361: step 345, loss 2.34728, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.446837: step 345, loss 3.88938, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.448774: step 345, loss 2.24433, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.450244: step 345, loss 2.34314, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.451724: step 345, loss 4.20751, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.453203: step 345, loss 2.33037, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.454528: step 345, loss 2.26761, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.456217: step 345, loss 2.25943, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.458131: step 345, loss 2.29535, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.460227: step 345, loss 2.3269, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.461913: step 345, loss 4.08283, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.463599: step 345, loss 2.22244, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.465283: step 345, loss 4.09219, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.466887: step 345, loss 3.52039, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.468353: step 345, loss 2.29522, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.469948: step 345, loss 2.29487, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.471674: step 345, loss 2.30721, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.473315: step 345, loss 2.28449, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.474859: step 345, loss 4.18484, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.477170: step 345, loss 3.57211, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.478658: step 345, loss 2.31875, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.480166: step 345, loss 2.2733, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.481679: step 345, loss 2.2517, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.483319: step 345, loss 2.26745, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.485034: step 345, loss 4.17493, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.486660: step 345, loss 2.21488, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.488127: step 345, loss 2.42989, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.489881: step 345, loss 2.27564, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.491489: step 345, loss 2.22826, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.493386: step 345, loss 2.29934, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.494823: step 345, loss 2.28478, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.496268: step 345, loss 2.26886, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.497682: step 345, loss 2.28136, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.499097: step 345, loss 2.24624, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.500509: step 345, loss 2.38949, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.501992: step 345, loss 3.94816, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.503484: step 345, loss 2.2236, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.504999: step 345, loss 2.27482, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.506361: step 345, loss 2.23, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.507877: step 345, loss 2.23459, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.509397: step 345, loss 2.24543, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.510805: step 345, loss 2.29186, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.512214: step 345, loss 2.24232, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.513560: step 345, loss 2.31934, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.514837: step 345, loss 2.23443, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.516195: step 345, loss 4.1901, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.517662: step 345, loss 2.27541, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.519325: step 345, loss 2.20668, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.520683: step 345, loss 2.3008, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.522386: step 345, loss 2.2686, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.523955: step 345, loss 2.33039, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.525712: step 345, loss 4.17228, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.527831: step 345, loss 2.2725, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.529474: step 345, loss 2.22749, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.531267: step 345, loss 2.40714, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.533108: step 345, loss 2.23058, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.534812: step 345, loss 2.1927, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.536177: step 345, loss 2.31735, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.537646: step 345, loss 2.32916, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.539147: step 345, loss 2.28495, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.540736: step 345, loss 4.45329, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.542235: step 345, loss 3.96758, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.543719: step 345, loss 2.21151, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.545187: step 345, loss 2.30568, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.546849: step 345, loss 2.25773, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.548254: step 345, loss 2.21049, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.549562: step 345, loss 2.2937, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.551132: step 345, loss 2.26704, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.553065: step 345, loss 4.11779, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.554998: step 345, loss 2.22225, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.556877: step 345, loss 4.13316, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.558314: step 345, loss 2.2638, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.559823: step 345, loss 2.27877, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.561389: step 345, loss 3.98872, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.562979: step 345, loss 3.81862, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.564655: step 345, loss 2.29253, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.566329: step 345, loss 3.43613, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.567710: step 345, loss 2.28447, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.569267: step 345, loss 2.30888, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.570649: step 345, loss 2.2887, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.572234: step 345, loss 2.36588, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.573639: step 345, loss 4.16116, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.575077: step 345, loss 2.28812, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.576451: step 345, loss 2.22472, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.578618: step 345, loss 4.17374, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.580101: step 345, loss 2.24713, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.581712: step 345, loss 2.32847, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:48:58.584803: step 345, loss 2.31094, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.586599: step 345, loss 2.31875, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.588083: step 345, loss 2.36908, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.589473: step 345, loss 2.31104, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.591025: step 345, loss 2.30095, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.592723: step 345, loss 2.28029, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.594475: step 345, loss 4.05335, acc 0\n",
      "\n",
      "2016-03-15T14:48:58.596119: step 345, loss 2.19978, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:48:58.599128: step 345, loss 2.27301, acc 1\n",
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      "2016-03-15T14:48:58.600778: step 345, loss 2.33092, acc 1\n",
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      "\n",
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      "2016-03-15T14:48:58.605481: step 345, loss 2.26588, acc 1\n",
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      "\n",
      "2016-03-15T14:48:58.609878: step 345, loss 2.20827, acc 1\n",
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      "2016-03-15T14:48:58.614349: step 345, loss 2.28674, acc 1\n",
      "\n",
      "2016-03-15T14:48:58.615987: step 345, loss 3.75742, acc 0\n",
      "\n",
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      "2016-03-15T14:48:59.053443: step 345, loss 2.33463, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.055393: step 345, loss 2.23868, acc 1\n",
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      "\n",
      "2016-03-15T14:48:59.060494: step 345, loss 2.34262, acc 1\n",
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      "\n",
      "2016-03-15T14:48:59.063953: step 345, loss 4.03144, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.066061: step 345, loss 2.28439, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.067727: step 345, loss 2.28951, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.069574: step 345, loss 4.39468, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.071358: step 345, loss 2.29496, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.073314: step 345, loss 4.43951, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.075194: step 345, loss 2.32525, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.076735: step 345, loss 2.38113, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.078258: step 345, loss 2.25571, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.079935: step 345, loss 2.30119, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.081594: step 345, loss 2.40107, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.083455: step 345, loss 2.25302, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.085206: step 345, loss 2.2727, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.087173: step 345, loss 2.22113, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.088955: step 345, loss 2.36984, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.090745: step 345, loss 2.32466, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.092312: step 345, loss 3.97903, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.094134: step 345, loss 2.26597, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.095958: step 345, loss 2.25748, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.097784: step 345, loss 2.29829, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.099424: step 345, loss 2.25691, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.101287: step 345, loss 3.77434, acc 0\n",
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      "2016-03-15T14:48:59.105134: step 345, loss 2.30845, acc 1\n",
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      "2016-03-15T14:48:59.106916: step 345, loss 2.33906, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.109009: step 345, loss 3.91167, acc 0\n",
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      "2016-03-15T14:48:59.110638: step 345, loss 3.44753, acc 0\n",
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      "2016-03-15T14:48:59.112773: step 345, loss 2.21156, acc 1\n",
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      "2016-03-15T14:48:59.116071: step 345, loss 2.31112, acc 1\n",
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      "2016-03-15T14:48:59.119613: step 345, loss 2.25168, acc 1\n",
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      "2016-03-15T14:48:59.121244: step 345, loss 2.26628, acc 1\n",
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      "2016-03-15T14:48:59.123104: step 345, loss 2.19324, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.125003: step 345, loss 2.31424, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.126594: step 345, loss 4.1657, acc 0\n",
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      "2016-03-15T14:48:59.128194: step 345, loss 2.19421, acc 1\n",
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      "2016-03-15T14:48:59.133011: step 345, loss 2.27985, acc 1\n",
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      "2016-03-15T14:48:59.136394: step 345, loss 2.22803, acc 1\n",
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      "\n",
      "2016-03-15T14:48:59.140880: step 345, loss 2.28835, acc 1\n",
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      "2016-03-15T14:48:59.142355: step 345, loss 2.21204, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.143745: step 345, loss 2.38153, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.144953: step 345, loss 2.33646, acc 1\n",
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      "2016-03-15T14:48:59.146900: step 345, loss 2.25951, acc 1\n",
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      "2016-03-15T14:48:59.148804: step 345, loss 2.28431, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.150755: step 345, loss 2.23294, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.152506: step 345, loss 2.32446, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.153974: step 345, loss 2.25978, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.157393: step 345, loss 2.26624, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.159142: step 345, loss 2.30712, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.160592: step 345, loss 2.24799, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.162026: step 345, loss 4.22269, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.163669: step 345, loss 2.32486, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.165243: step 345, loss 2.32624, acc 1\n",
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      "2016-03-15T14:48:59.166750: step 345, loss 2.19937, acc 1\n",
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      "2016-03-15T14:48:59.168821: step 345, loss 2.32689, acc 1\n",
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      "2016-03-15T14:48:59.170426: step 345, loss 2.2844, acc 1\n",
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      "2016-03-15T14:48:59.171826: step 345, loss 2.25708, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.173417: step 345, loss 3.95534, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.174949: step 345, loss 4.19057, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.176496: step 345, loss 4.43037, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.178054: step 345, loss 2.25447, acc 1\n",
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      "2016-03-15T14:48:59.179531: step 345, loss 2.31346, acc 1\n",
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      "2016-03-15T14:48:59.181241: step 345, loss 2.23738, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.182951: step 345, loss 2.25627, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.184707: step 345, loss 2.29874, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.186337: step 345, loss 3.61426, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.187847: step 345, loss 2.31391, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.189114: step 345, loss 3.68503, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.190792: step 345, loss 2.34733, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.192644: step 345, loss 2.27794, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.194422: step 345, loss 2.22421, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.196251: step 345, loss 2.19421, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.197833: step 345, loss 2.37974, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.199323: step 345, loss 2.24455, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.200902: step 345, loss 2.29472, acc 1\n",
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      "2016-03-15T14:48:59.202392: step 345, loss 2.30486, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.204016: step 345, loss 2.3848, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.205643: step 345, loss 2.26184, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.208085: step 345, loss 4.1263, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.209838: step 345, loss 3.98735, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.211698: step 345, loss 4.25399, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.213319: step 345, loss 2.28322, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.215039: step 345, loss 2.2568, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.216839: step 345, loss 2.24731, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.218401: step 345, loss 2.25141, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.219914: step 345, loss 2.31428, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.221326: step 345, loss 2.35897, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.222873: step 345, loss 3.79764, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.224364: step 345, loss 2.275, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.225861: step 345, loss 2.29496, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.227293: step 345, loss 2.30159, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.228723: step 345, loss 3.78424, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.230188: step 345, loss 2.29899, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.231758: step 345, loss 2.30968, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.233278: step 345, loss 3.79379, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.234692: step 345, loss 2.28298, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.236375: step 345, loss 2.27691, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.238169: step 345, loss 2.35006, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.239932: step 345, loss 3.70623, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.241631: step 345, loss 2.31731, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.243516: step 345, loss 4.25152, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.245394: step 345, loss 3.64969, acc 0\n",
      "\n",
      "2016-03-15T14:48:59.247337: step 345, loss 2.35362, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.249262: step 345, loss 2.19978, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.251042: step 345, loss 2.30625, acc 1\n",
      "\n",
      "2016-03-15T14:48:59.252928: step 345, loss 2.25647, acc 1\n",
      "\n",
      "True Positives 0\n",
      "True Negatives 369\n",
      "False Positives 0\n",
      "False Negatives 116\n",
      "Sensitivity: 0.0\n",
      "Specificity: 1.0\n",
      "\n",
      "Writing to /notebooks/AdHClassification/Expiriment #1.3 - Non-Candidate Tweets Included/runs/1458053339\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:49:05.819606: step 100, loss 3.07138, acc 0.783505\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:49:10.768983: step 200, loss 2.6113, acc 0.783505\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:49:15.813988: step 300, loss 2.22898, acc 0.783505\n",
      "\n",
      "\n",
      "Final Evaluation for fold 7:\n",
      "2016-03-15T14:49:18.067574: step 345, loss 2.07775, acc 0.783505\n",
      "2016-03-15T14:49:18.070788: step 345, loss 1.65839, acc 1\n",
      "\n",
      "2016-03-15T14:49:18.072980: step 345, loss 1.66855, acc 1\n",
      "\n",
      "2016-03-15T14:49:18.075831: step 345, loss 3.29202, acc 0\n",
      "\n",
      "2016-03-15T14:49:18.077803: step 345, loss 1.68898, acc 1\n",
      "\n",
      "2016-03-15T14:49:18.079547: step 345, loss 3.65509, acc 0\n",
      "\n",
      "2016-03-15T14:49:18.081209: step 345, loss 1.64958, acc 1\n",
      "\n",
      "2016-03-15T14:49:18.082768: step 345, loss 3.2733, acc 0\n",
      "\n",
      "2016-03-15T14:49:18.084282: step 345, loss 1.70305, acc 1\n",
      "\n",
      "2016-03-15T14:49:18.085775: step 345, loss 1.66524, acc 1\n",
      "\n",
      "2016-03-15T14:49:18.087259: step 345, loss 3.51332, acc 0\n",
      "\n",
      "2016-03-15T14:49:18.088842: step 345, loss 1.64496, acc 1\n",
      "\n",
      "2016-03-15T14:49:18.090429: step 345, loss 1.63372, acc 1\n",
      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:49:18.094853: step 345, loss 1.73136, acc 1\n",
      "\n",
      "2016-03-15T14:49:18.096579: step 345, loss 3.29565, acc 0\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:49:18.106876: step 345, loss 3.38131, acc 0\n",
      "\n",
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      "\n",
      "2016-03-15T14:49:18.111421: step 345, loss 1.73032, acc 1\n",
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      "\n",
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      "\n",
      "2016-03-15T14:49:18.117246: step 345, loss 1.74997, acc 1\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:49:18.145000: step 345, loss 1.66714, acc 1\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:49:18.153611: step 345, loss 3.07061, acc 0\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:49:18.179324: step 345, loss 1.70069, acc 1\n",
      "\n",
      "2016-03-15T14:49:18.180989: step 345, loss 1.65162, acc 1\n",
      "\n",
      "2016-03-15T14:49:18.182530: step 345, loss 1.66473, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:49:18.185326: step 345, loss 3.6546, acc 0\n",
      "\n",
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      "\n",
      "2016-03-15T14:49:18.188370: step 345, loss 1.74562, acc 1\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
      "2016-03-15T14:49:18.887123: step 345, loss 3.12057, acc 0\n",
      "\n",
      "True Positives 0\n",
      "True Negatives 380\n",
      "False Positives 0\n",
      "False Negatives 105\n",
      "Sensitivity: 0.0\n",
      "Specificity: 1.0\n",
      "\n",
      "Writing to /notebooks/AdHClassification/Expiriment #1.3 - Non-Candidate Tweets Included/runs/1458053359\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:49:25.513179: step 100, loss 3.894, acc 0.686598\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:49:30.410569: step 200, loss 3.37471, acc 0.686598\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:49:35.327711: step 300, loss 2.93109, acc 0.686598\n",
      "\n",
      "\n",
      "Final Evaluation for fold 8:\n",
      "2016-03-15T14:49:37.563042: step 345, loss 2.74803, acc 0.686598\n",
      "2016-03-15T14:49:37.567315: step 345, loss 2.0659, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.569819: step 345, loss 4.22307, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.572130: step 345, loss 2.21728, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.574475: step 345, loss 2.12596, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.576711: step 345, loss 4.29007, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.578928: step 345, loss 2.11576, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.581115: step 345, loss 3.5845, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.583181: step 345, loss 3.83098, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.585060: step 345, loss 2.26477, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.586946: step 345, loss 2.15706, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.588962: step 345, loss 2.10671, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.590978: step 345, loss 3.88126, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.593072: step 345, loss 2.08998, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.594886: step 345, loss 2.09172, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.596609: step 345, loss 2.05925, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.598234: step 345, loss 2.14424, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.599798: step 345, loss 4.7993, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.601325: step 345, loss 2.15473, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.602884: step 345, loss 4.35873, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.604334: step 345, loss 2.16141, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.605820: step 345, loss 2.20183, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.607363: step 345, loss 2.15306, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.608792: step 345, loss 2.06188, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.610158: step 345, loss 2.11437, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.611715: step 345, loss 3.56238, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.613277: step 345, loss 3.58482, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.614700: step 345, loss 3.93739, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.617305: step 345, loss 4.38983, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.619062: step 345, loss 2.1142, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.620658: step 345, loss 4.62227, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.622227: step 345, loss 4.3251, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.623909: step 345, loss 2.05969, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.625368: step 345, loss 2.17063, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.626855: step 345, loss 2.17579, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.628508: step 345, loss 2.1661, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.630118: step 345, loss 2.17393, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.631628: step 345, loss 2.15534, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.633075: step 345, loss 2.12279, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.634448: step 345, loss 2.1372, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.635808: step 345, loss 2.13012, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.637366: step 345, loss 2.11339, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.638927: step 345, loss 2.15301, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.640443: step 345, loss 2.08685, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.642328: step 345, loss 2.18107, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.643748: step 345, loss 2.16928, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.645224: step 345, loss 2.05968, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.646811: step 345, loss 2.17398, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.648358: step 345, loss 2.06044, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.649833: step 345, loss 3.805, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.651189: step 345, loss 3.48645, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.652760: step 345, loss 2.13985, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.654443: step 345, loss 2.05837, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.655804: step 345, loss 2.09101, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.657241: step 345, loss 2.14624, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.658497: step 345, loss 4.97567, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.659872: step 345, loss 2.15688, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.661485: step 345, loss 4.4248, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.662881: step 345, loss 2.08779, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.664269: step 345, loss 2.21519, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.665643: step 345, loss 2.14251, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.667799: step 345, loss 2.16485, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.669305: step 345, loss 2.17468, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.670690: step 345, loss 4.32958, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.672283: step 345, loss 3.94172, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.673770: step 345, loss 2.09041, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.675086: step 345, loss 3.96163, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.676540: step 345, loss 2.14335, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.678060: step 345, loss 4.18009, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.679591: step 345, loss 2.11413, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.681440: step 345, loss 2.20095, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.683158: step 345, loss 2.1519, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.684779: step 345, loss 2.13813, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.686484: step 345, loss 2.15759, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.688012: step 345, loss 2.16223, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.689513: step 345, loss 2.05976, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.690948: step 345, loss 2.08846, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.692509: step 345, loss 4.06657, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.693945: step 345, loss 2.1564, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.695571: step 345, loss 4.16607, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.697058: step 345, loss 2.05962, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.698528: step 345, loss 4.19059, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.700063: step 345, loss 2.10808, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.701581: step 345, loss 2.16161, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.703441: step 345, loss 2.16594, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.705094: step 345, loss 2.16042, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.706553: step 345, loss 2.10113, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.708008: step 345, loss 2.25354, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.709575: step 345, loss 2.10411, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.711009: step 345, loss 2.07877, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.712612: step 345, loss 3.79913, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.713935: step 345, loss 2.12095, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.715437: step 345, loss 4.35644, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.716921: step 345, loss 2.13786, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.719184: step 345, loss 4.73633, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.720990: step 345, loss 2.17852, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.722399: step 345, loss 2.15437, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.723753: step 345, loss 3.66926, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.725263: step 345, loss 2.16196, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.726643: step 345, loss 2.16458, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.727938: step 345, loss 2.05821, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.729836: step 345, loss 3.67458, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.731293: step 345, loss 2.19388, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.732834: step 345, loss 2.16524, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.734182: step 345, loss 2.12262, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.735541: step 345, loss 2.12952, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.736981: step 345, loss 2.15615, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.738297: step 345, loss 2.08908, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.739569: step 345, loss 2.06093, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.740829: step 345, loss 4.11813, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.742131: step 345, loss 4.38335, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.743583: step 345, loss 2.05675, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.745135: step 345, loss 2.08206, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.746901: step 345, loss 2.09519, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.748733: step 345, loss 3.78945, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.750545: step 345, loss 2.12905, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.752315: step 345, loss 2.15947, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.754000: step 345, loss 2.10476, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.755744: step 345, loss 2.22829, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.757529: step 345, loss 2.15759, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.759280: step 345, loss 3.99066, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.761042: step 345, loss 2.17388, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.762870: step 345, loss 2.15331, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.764723: step 345, loss 2.15288, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.766412: step 345, loss 2.06193, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.768144: step 345, loss 2.11884, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.770766: step 345, loss 4.07211, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.772960: step 345, loss 3.93945, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.774581: step 345, loss 2.1263, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.776635: step 345, loss 4.31427, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.778354: step 345, loss 2.24204, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.780167: step 345, loss 3.82219, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.781861: step 345, loss 2.13366, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.783579: step 345, loss 2.08276, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.785167: step 345, loss 2.06352, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.786530: step 345, loss 2.157, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.788246: step 345, loss 2.11722, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.790078: step 345, loss 2.13775, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.791857: step 345, loss 2.22745, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.793245: step 345, loss 2.12236, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.794969: step 345, loss 4.31983, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.796684: step 345, loss 2.15496, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.798125: step 345, loss 3.70864, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.799721: step 345, loss 2.08035, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.801106: step 345, loss 2.14647, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.802476: step 345, loss 3.96599, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.804259: step 345, loss 4.10348, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.805990: step 345, loss 4.05379, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.807541: step 345, loss 4.68159, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.809174: step 345, loss 2.09873, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.810745: step 345, loss 2.06307, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.812299: step 345, loss 4.12029, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.813950: step 345, loss 4.03814, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.815673: step 345, loss 2.10246, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.817487: step 345, loss 2.19145, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.819247: step 345, loss 4.48777, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.822112: step 345, loss 4.43491, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.824071: step 345, loss 2.12925, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.826093: step 345, loss 2.17464, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.828115: step 345, loss 2.13042, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.830049: step 345, loss 3.75147, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.831775: step 345, loss 2.1518, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.833613: step 345, loss 4.12867, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.835363: step 345, loss 2.07869, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.837295: step 345, loss 2.09932, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.839012: step 345, loss 2.10737, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.840737: step 345, loss 2.09444, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.842456: step 345, loss 2.25694, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.844156: step 345, loss 2.18703, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.845764: step 345, loss 2.17692, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.847587: step 345, loss 2.14538, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.849371: step 345, loss 2.0582, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.850941: step 345, loss 2.15294, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.852668: step 345, loss 2.13155, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.854362: step 345, loss 2.05723, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.856239: step 345, loss 2.10668, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.857967: step 345, loss 3.803, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.859618: step 345, loss 2.11019, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.861170: step 345, loss 2.0554, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.862646: step 345, loss 2.12888, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.864172: step 345, loss 2.20726, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.865645: step 345, loss 2.0887, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.867231: step 345, loss 2.14915, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.868978: step 345, loss 2.08547, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.870615: step 345, loss 3.85033, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.873066: step 345, loss 2.14863, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.874843: step 345, loss 2.10644, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.876548: step 345, loss 2.14234, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.878209: step 345, loss 4.05115, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.879849: step 345, loss 2.13463, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.881482: step 345, loss 4.11409, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.883183: step 345, loss 3.63331, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.884778: step 345, loss 4.25725, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.886411: step 345, loss 2.16641, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.888155: step 345, loss 2.19242, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.889817: step 345, loss 2.19937, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.891453: step 345, loss 2.08367, acc 1\n",
      "\n",
      "2016-03-15T14:49:37.893321: step 345, loss 3.81075, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.895078: step 345, loss 4.74929, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.896937: step 345, loss 4.0863, acc 0\n",
      "\n",
      "2016-03-15T14:49:37.898648: step 345, loss 4.10812, acc 0\n",
      "\n",
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      "\n",
      "2016-03-15T14:49:38.285382: step 345, loss 2.05483, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.287331: step 345, loss 2.12795, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.289252: step 345, loss 2.07479, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.291526: step 345, loss 2.11522, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.293244: step 345, loss 2.1579, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.294987: step 345, loss 2.15512, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.296753: step 345, loss 2.05855, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.298571: step 345, loss 2.22052, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.300442: step 345, loss 4.22279, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.302143: step 345, loss 4.58388, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.303944: step 345, loss 2.15678, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.305709: step 345, loss 2.13712, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.307510: step 345, loss 2.17705, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.309685: step 345, loss 2.14411, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.311920: step 345, loss 2.14825, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.313748: step 345, loss 2.23564, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.315479: step 345, loss 4.26574, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.317577: step 345, loss 4.37072, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.319273: step 345, loss 2.08866, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.320828: step 345, loss 3.90715, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.322222: step 345, loss 3.99569, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.323905: step 345, loss 2.1506, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.325270: step 345, loss 4.13755, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.326787: step 345, loss 2.16623, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.328239: step 345, loss 2.10962, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.329607: step 345, loss 2.14892, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.331096: step 345, loss 2.20326, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.332518: step 345, loss 2.19947, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.333884: step 345, loss 3.97064, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.336811: step 345, loss 2.12157, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.338549: step 345, loss 3.98551, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.340338: step 345, loss 2.08112, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.342042: step 345, loss 4.32234, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.343553: step 345, loss 2.06525, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.345305: step 345, loss 2.14638, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.347032: step 345, loss 2.05765, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.348717: step 345, loss 2.1476, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.350368: step 345, loss 2.14596, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.351887: step 345, loss 3.97365, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.353410: step 345, loss 3.75363, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.354829: step 345, loss 2.05634, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.356690: step 345, loss 2.15983, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.358326: step 345, loss 2.1414, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.360073: step 345, loss 3.43738, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.361901: step 345, loss 4.41485, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.363652: step 345, loss 2.10478, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.365372: step 345, loss 2.2455, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.367136: step 345, loss 2.06419, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.368933: step 345, loss 2.15332, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.370717: step 345, loss 2.21784, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.372421: step 345, loss 2.17503, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.374297: step 345, loss 2.05133, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.376362: step 345, loss 2.22374, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.378180: step 345, loss 4.1796, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.379947: step 345, loss 3.9446, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.381613: step 345, loss 2.23488, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.383579: step 345, loss 2.23639, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.385342: step 345, loss 2.10151, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.388064: step 345, loss 3.91527, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.390011: step 345, loss 4.25955, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.391690: step 345, loss 4.00786, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.393439: step 345, loss 2.05578, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.395290: step 345, loss 2.06108, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.397087: step 345, loss 2.10241, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.398926: step 345, loss 2.13424, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.400423: step 345, loss 2.10775, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.401979: step 345, loss 4.00296, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.403865: step 345, loss 2.16093, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.405609: step 345, loss 3.98797, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.407455: step 345, loss 2.08967, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.408976: step 345, loss 3.95887, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.410874: step 345, loss 2.16173, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.412476: step 345, loss 2.21375, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.414439: step 345, loss 2.12866, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.416203: step 345, loss 2.08542, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.418132: step 345, loss 3.57118, acc 0\n",
      "\n",
      "2016-03-15T14:49:38.419705: step 345, loss 2.15928, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.421522: step 345, loss 2.14617, acc 1\n",
      "\n",
      "2016-03-15T14:49:38.423393: step 345, loss 2.19234, acc 1\n",
      "\n",
      "True Positives 0\n",
      "True Negatives 333\n",
      "False Positives 0\n",
      "False Negatives 152\n",
      "Sensitivity: 0.0\n",
      "Specificity: 1.0\n",
      "\n",
      "Writing to /notebooks/AdHClassification/Expiriment #1.3 - Non-Candidate Tweets Included/runs/1458053378\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:49:44.890422: step 100, loss 3.45981, acc 0.723711\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:49:49.856814: step 200, loss 2.9982, acc 0.723711\n",
      "\n",
      "\n",
      "Evaluation:\n",
      "2016-03-15T14:49:54.891937: step 300, loss 2.57854, acc 0.723711\n",
      "\n",
      "\n",
      "Final Evaluation for fold 9:\n",
      "2016-03-15T14:49:57.127429: step 345, loss 2.43566, acc 0.723711\n",
      "2016-03-15T14:49:57.131413: step 345, loss 3.96804, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.133880: step 345, loss 1.83173, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.136185: step 345, loss 1.90893, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.138264: step 345, loss 3.85261, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.140484: step 345, loss 3.65107, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.142259: step 345, loss 3.76528, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.144063: step 345, loss 1.93908, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.146420: step 345, loss 2.0197, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.148196: step 345, loss 1.85657, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.150157: step 345, loss 4.07133, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.152101: step 345, loss 1.9567, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.154288: step 345, loss 1.94219, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.156100: step 345, loss 3.74952, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.157696: step 345, loss 3.31138, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.159204: step 345, loss 2.03524, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.160688: step 345, loss 3.65789, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.162252: step 345, loss 3.99019, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.163685: step 345, loss 1.98467, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.165309: step 345, loss 2.03245, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.166917: step 345, loss 1.83492, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.168519: step 345, loss 4.1986, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.170057: step 345, loss 3.75481, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.171606: step 345, loss 1.90674, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.173366: step 345, loss 1.87383, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.175114: step 345, loss 1.9127, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.176913: step 345, loss 1.95867, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.178614: step 345, loss 1.90257, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.181087: step 345, loss 1.98002, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.182598: step 345, loss 4.15679, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.184235: step 345, loss 3.61575, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.185779: step 345, loss 1.93768, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.187340: step 345, loss 3.79051, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.188823: step 345, loss 1.87693, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.190480: step 345, loss 1.88356, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.192098: step 345, loss 1.86232, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.193699: step 345, loss 3.37616, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.195234: step 345, loss 1.88705, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.196735: step 345, loss 1.98595, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.198157: step 345, loss 1.91644, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.199961: step 345, loss 4.21307, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.201469: step 345, loss 3.87707, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.203184: step 345, loss 2.00963, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.204788: step 345, loss 1.96126, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.206350: step 345, loss 1.96541, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.207937: step 345, loss 1.88505, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.209393: step 345, loss 3.41226, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.210873: step 345, loss 2.04893, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.212494: step 345, loss 1.83885, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.214179: step 345, loss 1.87827, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.216012: step 345, loss 1.97018, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.217548: step 345, loss 3.86476, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.219200: step 345, loss 3.60595, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.220911: step 345, loss 3.97124, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.222547: step 345, loss 1.99773, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.224143: step 345, loss 1.83991, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.225687: step 345, loss 1.94492, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.227274: step 345, loss 1.9574, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.228654: step 345, loss 1.94767, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.230281: step 345, loss 3.73133, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.232663: step 345, loss 1.83791, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.234129: step 345, loss 1.86331, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.235656: step 345, loss 1.86459, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.237120: step 345, loss 1.8645, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.238637: step 345, loss 1.9565, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.240233: step 345, loss 1.9339, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.241695: step 345, loss 1.94828, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.243187: step 345, loss 1.88052, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.244666: step 345, loss 1.9951, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.246387: step 345, loss 1.9419, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.247868: step 345, loss 3.65801, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.249419: step 345, loss 1.96655, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.251023: step 345, loss 3.69858, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.252385: step 345, loss 3.6147, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.253893: step 345, loss 3.72997, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.255470: step 345, loss 1.84571, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.257218: step 345, loss 3.30018, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.258848: step 345, loss 1.83571, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.260499: step 345, loss 1.97873, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.262124: step 345, loss 3.67567, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.263625: step 345, loss 1.9396, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.265199: step 345, loss 2.01685, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.266743: step 345, loss 1.84441, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.268237: step 345, loss 3.46523, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.269802: step 345, loss 3.33232, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.271338: step 345, loss 1.92771, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.272949: step 345, loss 1.94858, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:49:57.276017: step 345, loss 1.93223, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.277711: step 345, loss 1.9656, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.279269: step 345, loss 2.03043, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.281036: step 345, loss 2.00972, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.283931: step 345, loss 1.97719, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:49:57.286995: step 345, loss 1.94874, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.288647: step 345, loss 1.91455, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:49:57.291758: step 345, loss 3.88565, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.293343: step 345, loss 1.93638, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.294824: step 345, loss 1.94105, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.296509: step 345, loss 1.99603, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.298004: step 345, loss 2.03023, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.299690: step 345, loss 1.90849, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.300966: step 345, loss 1.92127, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.302277: step 345, loss 1.9423, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.303759: step 345, loss 1.88055, acc 1\n",
      "\n",
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      "\n",
      "2016-03-15T14:49:57.306505: step 345, loss 1.88334, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.308006: step 345, loss 1.83446, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.309341: step 345, loss 1.93466, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.310562: step 345, loss 1.913, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.312068: step 345, loss 2.00576, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.313384: step 345, loss 1.91201, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.314781: step 345, loss 4.06891, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.316317: step 345, loss 1.97085, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.317952: step 345, loss 1.87704, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.319454: step 345, loss 3.81317, acc 0\n",
      "\n",
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      "2016-03-15T14:49:57.667459: step 345, loss 2.00167, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.669239: step 345, loss 1.83811, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.670949: step 345, loss 3.90465, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.672795: step 345, loss 1.83633, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.674762: step 345, loss 1.84564, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.676720: step 345, loss 3.72746, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.678420: step 345, loss 1.83966, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.680401: step 345, loss 1.9882, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.682207: step 345, loss 1.88618, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.684086: step 345, loss 1.92934, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.685780: step 345, loss 3.47376, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.687500: step 345, loss 3.48373, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.689252: step 345, loss 3.56712, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.691114: step 345, loss 4.28068, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.693739: step 345, loss 1.84569, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.695642: step 345, loss 3.71417, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.697189: step 345, loss 1.96068, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.698630: step 345, loss 1.95156, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.700246: step 345, loss 1.86413, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.701852: step 345, loss 1.9884, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.703577: step 345, loss 1.93754, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.705173: step 345, loss 1.86404, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.706629: step 345, loss 1.99735, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.708135: step 345, loss 1.93407, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.709769: step 345, loss 1.93277, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.711591: step 345, loss 1.86752, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.713380: step 345, loss 1.84092, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.714981: step 345, loss 1.92578, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.716741: step 345, loss 1.93078, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.718525: step 345, loss 1.96297, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.720536: step 345, loss 1.8365, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.722253: step 345, loss 2.00313, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.724088: step 345, loss 1.90805, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.726005: step 345, loss 1.94068, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.727887: step 345, loss 1.88225, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.729633: step 345, loss 1.89722, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.731276: step 345, loss 1.98541, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.733043: step 345, loss 1.83753, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.734771: step 345, loss 1.97877, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.736705: step 345, loss 1.83579, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.738589: step 345, loss 1.83173, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.740759: step 345, loss 4.11607, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.742362: step 345, loss 1.95063, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.744962: step 345, loss 1.97677, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.746897: step 345, loss 1.83568, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.749166: step 345, loss 3.73886, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.751076: step 345, loss 1.92092, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.752917: step 345, loss 1.91594, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.755001: step 345, loss 1.97278, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.757052: step 345, loss 1.9577, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.759023: step 345, loss 1.97009, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.760840: step 345, loss 1.93396, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.762732: step 345, loss 2.02013, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.764711: step 345, loss 1.94492, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.766686: step 345, loss 3.4953, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.768442: step 345, loss 1.86711, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.770350: step 345, loss 1.95349, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.772094: step 345, loss 1.83895, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.773891: step 345, loss 1.93747, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.775757: step 345, loss 1.99263, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.777649: step 345, loss 3.58284, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.779189: step 345, loss 1.98872, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.781159: step 345, loss 1.85595, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.783189: step 345, loss 1.92904, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.785232: step 345, loss 1.92506, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.787066: step 345, loss 3.80021, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.788875: step 345, loss 3.07565, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.790649: step 345, loss 1.97857, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.792546: step 345, loss 1.84387, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.794314: step 345, loss 4.76963, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.796906: step 345, loss 1.93854, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.798783: step 345, loss 3.09654, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.800542: step 345, loss 3.84372, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.802409: step 345, loss 1.94872, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.804277: step 345, loss 1.94554, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.806089: step 345, loss 1.94595, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.807660: step 345, loss 1.92585, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.809394: step 345, loss 3.96955, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.811160: step 345, loss 3.71952, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.812721: step 345, loss 1.96903, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.814301: step 345, loss 1.83712, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.815846: step 345, loss 1.96203, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.817439: step 345, loss 1.92235, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.819115: step 345, loss 1.9154, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.820800: step 345, loss 4.10314, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.822529: step 345, loss 1.85567, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.824245: step 345, loss 1.96337, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.825810: step 345, loss 3.98971, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.827508: step 345, loss 2.07345, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.829296: step 345, loss 3.69289, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.831426: step 345, loss 2.01136, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.833134: step 345, loss 1.8423, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.834981: step 345, loss 2.01319, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.836553: step 345, loss 3.58924, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.838216: step 345, loss 1.92383, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.839960: step 345, loss 3.35333, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.841577: step 345, loss 1.93135, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.843212: step 345, loss 4.0832, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.845011: step 345, loss 1.97117, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.847625: step 345, loss 1.95888, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.849344: step 345, loss 1.90953, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.851007: step 345, loss 1.98194, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.852816: step 345, loss 2.00773, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.854711: step 345, loss 1.97275, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.856543: step 345, loss 1.90771, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.858397: step 345, loss 1.89912, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.860134: step 345, loss 2.05212, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.861937: step 345, loss 1.93323, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.863731: step 345, loss 1.96121, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.865294: step 345, loss 2.04894, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.867010: step 345, loss 1.93504, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.868993: step 345, loss 1.89974, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.870954: step 345, loss 3.80064, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.872601: step 345, loss 1.85246, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.874406: step 345, loss 1.90506, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.876244: step 345, loss 1.93971, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.878208: step 345, loss 2.04062, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.880084: step 345, loss 2.04566, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.881898: step 345, loss 1.83736, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.883705: step 345, loss 1.87584, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.885474: step 345, loss 1.94586, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.887248: step 345, loss 3.70819, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.889623: step 345, loss 2.04379, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.892271: step 345, loss 1.94572, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.894121: step 345, loss 1.94552, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.896212: step 345, loss 2.06717, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.899011: step 345, loss 1.85608, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.900853: step 345, loss 3.60421, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.902808: step 345, loss 2.06314, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.904719: step 345, loss 1.9689, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.906498: step 345, loss 2.05073, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.908617: step 345, loss 1.85649, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.910697: step 345, loss 1.89955, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.912598: step 345, loss 2.02487, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.914362: step 345, loss 2.05798, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.916410: step 345, loss 1.90312, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.918303: step 345, loss 1.96721, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.920261: step 345, loss 1.95154, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.922236: step 345, loss 2.02088, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.924065: step 345, loss 3.41419, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.925579: step 345, loss 2.00779, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.927285: step 345, loss 4.0036, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.929163: step 345, loss 1.92284, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.931036: step 345, loss 3.7008, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.932979: step 345, loss 3.89535, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.934852: step 345, loss 1.93872, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.936394: step 345, loss 2.03413, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.937942: step 345, loss 1.91927, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.940109: step 345, loss 1.98296, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.941626: step 345, loss 1.91776, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.943372: step 345, loss 3.75801, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.945079: step 345, loss 1.93943, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.946738: step 345, loss 1.96915, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.948345: step 345, loss 1.92563, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.951010: step 345, loss 3.47702, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.952553: step 345, loss 2.05983, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.954430: step 345, loss 3.81665, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.956231: step 345, loss 1.91832, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.958017: step 345, loss 1.95509, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.959770: step 345, loss 1.99294, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.961307: step 345, loss 2.00578, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.962968: step 345, loss 2.02816, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.964545: step 345, loss 3.57025, acc 0\n",
      "\n",
      "2016-03-15T14:49:57.966469: step 345, loss 1.92841, acc 1\n",
      "\n",
      "2016-03-15T14:49:57.968007: step 345, loss 2.05338, acc 1\n",
      "\n",
      "True Positives 0\n",
      "True Negatives 351\n",
      "False Positives 0\n",
      "False Negatives 134\n",
      "Sensitivity: 0.0\n",
      "Specificity: 1.0\n",
      "\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import os\n",
    "import time\n",
    "import datetime\n",
    "from sklearn.cross_validation import StratifiedKFold\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "# Data Preparatopn\n",
    "# ==================================================\n",
    "\n",
    "# Load data\n",
    "print(\"Loading data...\")\n",
    "np.random.seed(10)\n",
    "shuffle_indices = np.random.permutation(np.arange(len(y)))\n",
    "x_shuffled = x[shuffle_indices]\n",
    "y_shuffled = y[shuffle_indices]\n",
    "_y_shuffled = _y[shuffle_indices]\n",
    "\n",
    "skf = StratifiedKFold(_y_shuffled, n_folds=num_folds)\n",
    "\n",
    "fold_accuracies = []\n",
    "fold_specificities = []\n",
    "fold_sensitivities = []\n",
    "\n",
    "# Split train/test set\n",
    "# TODO: This is very crude, should use cross-validation\n",
    "#x_train, x_dev = x_shuffled[:len(x_shuffled)-1], x_shuffled[-len(x_shuffled)-1:]\n",
    "#y_train, y_dev = y_shuffled[:len(y_shuffled)-1], y_shuffled[-len(y_shuffled)-1:]\n",
    "#print(\"Vocabulary Size: {:d}\".format(len(vocabulary)))\n",
    "#print(\"Train/Dev split: {:d}/{:d}\".format(len(y_train), len(y_dev)))\n",
    "#print(\"Train Pos/Dev Pos Split {:d}/{:d}\"\n",
    "#      .format(\n",
    "#        len(\n",
    "#            [y for y in y_train if y[0] == 0 and y[1] == 1]\n",
    "#        ), len(\n",
    "#            [y for y in y_dev if y[0] == 0 and y[1] == 1]\n",
    "#        )))\n",
    "#print(\"Train Neg/Dev Neg Split {:d}/{:d}\"\n",
    "#      .format(\n",
    "#        len(\n",
    "#            [y for y in y_train if y[0] == 1 and y[1] == 0]\n",
    "#        ), len(\n",
    "#            [y for y in y_dev if y[0] == 1 and y[1] == 0]\n",
    "#        )))\n",
    "\n",
    "\n",
    "# Training\n",
    "# ==================================================\n",
    "\n",
    "for idx, fold in zip(skf, range(num_folds)):\n",
    "    x_train = x[idx[0]]\n",
    "    y_train = y[idx[0]]\n",
    "    \n",
    "    x_dev = x[idx[1]]\n",
    "    y_dev = y[idx[1]]\n",
    "    \n",
    "    \n",
    "    \n",
    "    \n",
    "    \n",
    "    with tf.Graph().as_default():\n",
    "        session_conf = tf.ConfigProto(\n",
    "          allow_soft_placement=allow_soft_placement,\n",
    "          log_device_placement=log_device_placement)\n",
    "        sess = tf.Session(config=session_conf)\n",
    "        with sess.as_default():\n",
    "            cnn = TextCNN(\n",
    "                sequence_length=x_train.shape[1],\n",
    "                num_classes=2,\n",
    "                vocab_size=len(vocabulary),\n",
    "                embedding_size=embedding_dim,\n",
    "                filter_sizes=map(int, filter_sizes.split(\",\")),\n",
    "                num_filters=num_filters,\n",
    "                l2_reg_lambda=l2_reg_lambda)\n",
    "\n",
    "            # Define Training procedure\n",
    "            global_step = tf.Variable(0, name=\"global_step\", trainable=False)\n",
    "            optimizer = tf.train.AdamOptimizer(1e-4)\n",
    "            grads_and_vars = optimizer.compute_gradients(cnn.loss)\n",
    "            train_op = optimizer.apply_gradients(grads_and_vars, global_step=global_step)\n",
    "\n",
    "            # Keep track of gradient values and sparsity (optional)\n",
    "            grad_summaries = []\n",
    "            for g, v in grads_and_vars:\n",
    "                if g is not None:\n",
    "                    grad_hist_summary = tf.histogram_summary(\"{}/grad/hist\".format(v.name), g)\n",
    "                    sparsity_summary = tf.scalar_summary(\"{}/grad/sparsity\".format(v.name), tf.nn.zero_fraction(g))\n",
    "                    grad_summaries.append(grad_hist_summary)\n",
    "                    grad_summaries.append(sparsity_summary)\n",
    "            grad_summaries_merged = tf.merge_summary(grad_summaries)\n",
    "\n",
    "            # Output directory for models and summaries\n",
    "            timestamp = str(int(time.time()))\n",
    "            out_dir = os.path.abspath(os.path.join(os.path.curdir, \"runs\", run_name, timestamp))\n",
    "            print(\"Writing to {}\\n\".format(out_dir))\n",
    "\n",
    "            # Summaries for loss and accuracy\n",
    "            loss_summary = tf.scalar_summary(\"loss\", cnn.loss)\n",
    "            acc_summary = tf.scalar_summary(\"accuracy\", cnn.accuracy)\n",
    "            \n",
    "            sens_summary = tf.scalar_summary(\"sensitivity\", cnn.sensitivity)\n",
    "            spec_summary = tf.scalar_summary(\"specificity\", cnn.specificity)\n",
    "\n",
    "            # Train Summaries\n",
    "            train_summary_op = tf.merge_summary([loss_summary, acc_summary, sens_summary, spec_summary, grad_summaries_merged])\n",
    "            train_summary_dir = os.path.join(out_dir, \"summaries\", \"train\", str(fold))\n",
    "            train_summary_writer = tf.train.SummaryWriter(train_summary_dir, sess.graph_def)\n",
    "\n",
    "            # Dev summaries\n",
    "            dev_summary_op = tf.merge_summary([loss_summary, acc_summary, sens_summary, spec_summary])\n",
    "            dev_summary_dir = os.path.join(out_dir, \"summaries\", \"dev\", str(fold))\n",
    "            dev_summary_writer = tf.train.SummaryWriter(dev_summary_dir, sess.graph_def)\n",
    "\n",
    "            # Checkpoint directory. Tensorflow assumes this directory already exists so we need to create it\n",
    "            checkpoint_dir = os.path.abspath(os.path.join(out_dir, \"checkpoints\"))\n",
    "            checkpoint_prefix = os.path.join(checkpoint_dir, \"model\")\n",
    "            if not os.path.exists(checkpoint_dir):\n",
    "                os.makedirs(checkpoint_dir)\n",
    "            saver = tf.train.Saver(tf.all_variables())\n",
    "\n",
    "            # Initialize all variables\n",
    "            sess.run(tf.initialize_all_variables())\n",
    "    \n",
    "            def train_step(x_batch, y_batch):\n",
    "                \"\"\"\n",
    "                A single training step\n",
    "                \"\"\"\n",
    "                feed_dict = {\n",
    "                  cnn.input_x: x_batch,\n",
    "                  cnn.input_y: y_batch,\n",
    "                  cnn.dropout_keep_prob: dropout_keep_prob,\n",
    "                  cnn.t: [ len(y_batch)],\n",
    "                  cnn.f: [ len(y_batch)]\n",
    "                }\n",
    "                _, step, summaries, loss, accuracy = sess.run(\n",
    "                    [train_op, global_step, train_summary_op, cnn.loss, cnn.accuracy],\n",
    "                    feed_dict)\n",
    "                time_str = datetime.datetime.now().isoformat()\n",
    "                if(display_train_steps):\n",
    "                    print(\"{}: step {}, loss {:g}, acc {:g}\".format(time_str, step, loss, accuracy))\n",
    "                train_summary_writer.add_summary(summaries, step)\n",
    "\n",
    "            def dev_step(x_batch, y_batch, writer=None):\n",
    "                \"\"\"\n",
    "                Evaluates model on a dev set\n",
    "                \"\"\"\n",
    "                feed_dict = {\n",
    "                  cnn.input_x: x_batch,\n",
    "                  cnn.input_y: y_batch,\n",
    "                  cnn.dropout_keep_prob: 1.0,\n",
    "                  cnn.t: [ len(y_batch)],\n",
    "                  cnn.f: [ len(y_batch)]\n",
    "                }\n",
    "                step, summaries, loss, accuracy, sensitivity, specificity = sess.run(\n",
    "                    [global_step, dev_summary_op, cnn.loss, cnn.accuracy, cnn.sensitivity, cnn.specificity],\n",
    "                    feed_dict)\n",
    "                time_str = datetime.datetime.now().isoformat()\n",
    "                print(\"{}: step {}, loss {:g}, acc {:g} sens {:g} spec {:g}\".format(time_str, step, loss, accuracy, sensitivity, specificity))\n",
    "                \n",
    "                if writer:\n",
    "                    writer.add_summary(summaries, step)\n",
    "                return accuracy, sensitivity, specificity\n",
    "\n",
    "            # Generate batches\n",
    "            batches = batch_iter(\n",
    "                zip(x_train, y_train), batch_size, num_epochs)\n",
    "            # Training loop. For each batch...\n",
    "            for batch in batches:\n",
    "                x_batch, y_batch = zip(*batch)\n",
    "                train_step(x_batch, y_batch)\n",
    "                current_step = tf.train.global_step(sess, global_step)\n",
    "                if current_step % checkpoint_every == 0:\n",
    "                    path = saver.save(sess, checkpoint_prefix, global_step=current_step)\n",
    "                    print(\"Saved model checkpoint to {}\\n\".format(path))\n",
    "                if current_step % evaluate_every == 0:\n",
    "                    print(\"\\nEvaluation:\")\n",
    "                    dev_step(x_dev, y_dev, writer=dev_summary_writer)\n",
    "                    print(\"\")\n",
    "            \n",
    "            print(\"\\nFinal Evaluation for fold %s:\" % fold)\n",
    "            acc, sens, spec = dev_step(x_dev, y_dev, writer=dev_summary_writer)\n",
    "            fold_accuracies.append(acc)\n",
    "            fold_sensitivities.append(sens)\n",
    "            print(\"Sensitivity: %s\" % sens)\n",
    "            fold_specificities.append(spec)\n",
    "            print(\"Specificity: %s\" % spec)\n",
    "   \n",
    "        print(\"\")\n",
    "        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false,
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "10-fold final accuracy: 0.854582905769\n",
      "10-fold final specificity: 1.0\n",
      "10-fold final sensitivity: 0.0\n"
     ]
    }
   ],
   "source": [
    "final_accuracy = sum(fold_accuracies) / float(len(fold_accuracies))\n",
    "print(\"10-fold final accuracy: %s\" % final_accuracy)\n",
    "final_specificity = sum(fold_specificities) / float(len(fold_specificities))\n",
    "print(\"10-fold final specificity: %s\" % final_specificity)\n",
    "final_sensitivities = sum(fold_sensitivities) / float(len(fold_sensitivities))\n",
    "print(\"10-fold final sensitivity: %s\" % final_sensitivities)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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