talk.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "from __future__ import absolute_import\n",
    "from __future__ import division\n",
    "from __future__ import print_function\n",
    "\n",
    "import collections\n",
    "import math\n",
    "import os\n",
    "import random\n",
    "import zipfile\n",
    "import emoji\n",
    "\n",
    "import numpy as np\n",
    "from six.moves import urllib\n",
    "from six.moves import xrange  # pylint: disable=redefined-builtin\n",
    "import tensorflow as tf\n",
    "import nltk\n",
    "from nltk.corpus import stopwords\n",
    "import re\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found and verified foo.zip 1633459\n",
      "Found and verified foo.zip\n"
     ]
    }
   ],
   "source": [
    "url = 'http://0.0.0.0:8000/'\n",
    "\n",
    "def maybe_download(filename, expected_bytes):\n",
    "  \"\"\"Download a file if not present, and make sure it's the right size.\"\"\"\n",
    "  if not os.path.exists(filename):\n",
    "    filename, _ = urlretrieve(url + filename, filename)\n",
    "  statinfo = os.stat(filename)\n",
    "  print('Found and verified %s' % filename, statinfo.st_size)\n",
    "  if statinfo.st_size == expected_bytes:\n",
    "    print('Found and verified %s' % filename)\n",
    "  else:\n",
    "    print(statinfo.st_size)\n",
    "    raise Exception(\n",
    "      'Failed to verify ' + filename + '. Can you get to it with a browser?')\n",
    "  return filename\n",
    "\n",
    "filename = maybe_download('foo.zip', 1633459)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Data size 627065\n"
     ]
    }
   ],
   "source": [
    "# Read the data into a list of strings.\n",
    "def read_data(filename):\n",
    "  \"\"\"Extract the first file enclosed in a zip file as a list of words\"\"\"\n",
    "  with zipfile.ZipFile(filename) as f:\n",
    "    data = tf.compat.as_str(f.read(f.namelist()[0])).split()\n",
    "#   We need stop words for capturing grammar\n",
    "#   stops = set(stopwords.words(\"english\"))\n",
    "  y = [emoji.demojize(x.translate(None, '?!,.\"').lower().decode('utf-8')).encode('ascii', 'ignore') for x in data]\n",
    "  y = [ re.sub(r'^https?:\\/\\/.*[\\r\\n]*', '', text, flags=re.MULTILINE) for text in y ]\n",
    "  y = [ re.sub(r'^\\([A-Za-z0-9]*', '', text, flags=re.MULTILINE) for text in y ]\n",
    "  y = [ re.sub(r'^@\\w+', '', text, flags=re.MULTILINE) for text in y ]\n",
    "#   y = [ x for x in y if not x in stops ]\n",
    "  return filter(None, y)\n",
    "\n",
    "words = read_data(filename)\n",
    "print('Data size', len(words))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Most common words (+UNK) [['UNK', 12732], ('the', 20439), ('to', 15162), ('i', 13551), ('a', 13551)]\n",
      "Sample data [224, 234, 424, 224, 331, 35, 2026, 13, 110, 1574] ['hey', 'tom', '^^', 'hey', 'keep', 'me', 'posted', 'on', 'any', 'contract']\n"
     ]
    }
   ],
   "source": [
    "# Step 2: Build the dictionary and replace rare words with UNK token.\n",
    "vocabulary_size = 25000 # 8-10 year old vocab\n",
    "\n",
    "def build_dataset(words):\n",
    "  count = [['UNK', -1]]\n",
    "  count.extend(collections.Counter(words).most_common(vocabulary_size - 1))\n",
    "  dictionary = dict()\n",
    "  for word, _ in count:\n",
    "    dictionary[word] = len(dictionary)\n",
    "  data = list()\n",
    "  unk_count = 0\n",
    "  for word in words:\n",
    "    if word in dictionary:\n",
    "      index = dictionary[word]\n",
    "    else:\n",
    "      index = 0  # dictionary['UNK']\n",
    "      unk_count += 1\n",
    "    data.append(index)\n",
    "  count[0][1] = unk_count\n",
    "  reverse_dictionary = dict(zip(dictionary.values(), dictionary.keys()))\n",
    "  return data, count, dictionary, reverse_dictionary\n",
    "\n",
    "data, count, dictionary, reverse_dictionary = build_dataset(words)\n",
    "del words  # Hint to reduce memory.\n",
    "print('Most common words (+UNK)', count[:5])\n",
    "print('Sample data', data[:10], [reverse_dictionary[i] for i in data[:10]])\n",
    "\n",
    "data_index = 0\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "len 25000\n",
      "234 tom -> 424 ^^\n",
      "234 tom -> 224 hey\n",
      "424 ^^ -> 234 tom\n",
      "424 ^^ -> 224 hey\n",
      "224 hey -> 331 keep\n",
      "224 hey -> 424 ^^\n",
      "331 keep -> 224 hey\n",
      "331 keep -> 35 me\n"
     ]
    }
   ],
   "source": [
    "# Step 3: Function to generate a training batch for the skip-gram model.\n",
    "def generate_batch(batch_size, num_skips, skip_window):\n",
    "  global data_index\n",
    "  assert batch_size % num_skips == 0\n",
    "  assert num_skips <= 2 * skip_window\n",
    "  batch = np.ndarray(shape=(batch_size), dtype=np.int32)\n",
    "  labels = np.ndarray(shape=(batch_size, 1), dtype=np.int32)\n",
    "  span = 2 * skip_window + 1 # [ skip_window target skip_window ]\n",
    "  buffer = collections.deque(maxlen=span)\n",
    "  for _ in range(span):\n",
    "    buffer.append(data[data_index])\n",
    "    data_index = (data_index + 1) % len(data)\n",
    "  for i in range(batch_size // num_skips):\n",
    "    target = skip_window  # target label at the center of the buffer\n",
    "    targets_to_avoid = [ skip_window ]\n",
    "    for j in range(num_skips):\n",
    "      while target in targets_to_avoid:\n",
    "        target = random.randint(0, span - 1)\n",
    "      targets_to_avoid.append(target)\n",
    "      batch[i * num_skips + j] = buffer[skip_window]\n",
    "      labels[i * num_skips + j, 0] = buffer[target]\n",
    "    buffer.append(data[data_index])\n",
    "    data_index = (data_index + 1) % len(data)\n",
    "  return batch, labels\n",
    "\n",
    "batch, labels = generate_batch(batch_size=8, num_skips=2, skip_window=1)\n",
    "print('len', len(reverse_dictionary))\n",
    "for i in range(8):\n",
    "  print(batch[i], reverse_dictionary[batch[i]],\n",
    "      '->', labels[i, 0], reverse_dictionary[labels[i, 0]])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "# Step 4: Build and train a skip-gram model.\n",
    "\n",
    "batch_size = 256\n",
    "embedding_size = 200  # Dimension of the embedding vector.\n",
    "skip_window = 1       # How many words to consider left and right.\n",
    "num_skips = 2         # How many times to reuse an input to generate a label.\n",
    "\n",
    "# We pick a random validation set to sample nearest neighbors. Here we limit the\n",
    "# validation samples to the words that have a low numeric ID, which by\n",
    "# construction are also the most frequent.\n",
    "valid_size = 16     # Random set of words to evaluate similarity on.\n",
    "valid_window = 128  # Only pick dev samples in the head of the distribution.\n",
    "valid_examples = np.random.choice(valid_window, valid_size, replace=False)\n",
    "num_sampled = 64    # Number of negative examples to sample.\n",
    "\n",
    "graph = tf.Graph()\n",
    "\n",
    "with graph.as_default():\n",
    "\n",
    "  # Input data.\n",
    "  train_inputs = tf.placeholder(tf.int32, shape=[batch_size])\n",
    "  train_labels = tf.placeholder(tf.int32, shape=[batch_size, 1])\n",
    "  valid_dataset = tf.constant(valid_examples, dtype=tf.int32)\n",
    "\n",
    "  # Ops and variables pinned to the CPU because of missing GPU implementation\n",
    "  with tf.device('/cpu:0'):\n",
    "    # Look up embeddings for inputs.\n",
    "    embeddings = tf.Variable(\n",
    "        tf.random_uniform([vocabulary_size, embedding_size], -1.0, 1.0))\n",
    "    embed = tf.nn.embedding_lookup(embeddings, train_inputs)\n",
    "\n",
    "    # Construct the variables for the NCE loss\n",
    "    nce_weights = tf.Variable(\n",
    "        tf.truncated_normal([vocabulary_size, embedding_size],\n",
    "                            stddev=1.0 / math.sqrt(embedding_size)))\n",
    "    nce_biases = tf.Variable(tf.zeros([vocabulary_size]))\n",
    "\n",
    "  # Compute the average NCE loss for the batch.\n",
    "  # tf.nce_loss automatically draws a new sample of the negative labels each\n",
    "  # time we evaluate the loss.\n",
    "  loss = tf.reduce_mean(\n",
    "      tf.nn.nce_loss(nce_weights, nce_biases, embed, train_labels,\n",
    "                     num_sampled, vocabulary_size))\n",
    "\n",
    "  optimizer = tf.train.GradientDescentOptimizer(learning_rate=0.6).minimize(loss)\n",
    "#   optimizer = tf.train.AdamOptimizer(learning_rate=0.1).minimize(loss)\n",
    "\n",
    "\n",
    "  # Compute the cosine similarity between minibatch examples and all embeddings.\n",
    "  norm = tf.sqrt(tf.reduce_sum(tf.square(embeddings), 1, keep_dims=True))\n",
    "  normalized_embeddings = embeddings / norm\n",
    "  valid_embeddings = tf.nn.embedding_lookup(\n",
    "      normalized_embeddings, valid_dataset)\n",
    "  similarity = tf.matmul(\n",
    "      valid_embeddings, normalized_embeddings, transpose_b=True)\n",
    "\n",
    "  # Add variable initializer.\n",
    "  init = tf.initialize_all_variables()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Initialized\n",
      "\n",
      "\n",
      "Average loss at step  0 :  267.384063721 \n",
      "\n",
      "\n",
      "Nearest to your: hintjens', license), #done, thermometer, ctrl-chop-head-of-chicken-and-rage-quit, unfriended, emoji), carcavelos,\n",
      "Nearest to for: replied, authorities, audit, datacentres, pushes, cloudshell, wales), atom-shell,\n",
      "Nearest to very: monolith, seat, acquisitions, connections, ambiguous, 80%+, #superexcited, #dangerous,\n",
      "Nearest to then: cyclists, pimp, burning, attacks, mat, stated, simonspringett@ntlworldcom, :cow:,\n",
      "Nearest to so: apologises, exam, sword, concur, validated, checksumming, park, maida,\n",
      "Nearest to where: fully, enable, casualty, darren, inputs, era, #no, unsafe,\n",
      "Nearest to i'll: resource, behaviour, fallen, jk, haskell, consumerism, bacalhau, artist,\n",
      "Nearest to was: pursue, rubber, go-lang, blankey, want:, 750ml, backers, presences,\n",
      "Nearest to same: codes), :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:, co-exist, irssi, pencil, spreadsheets, stirred, func1,\n",
      "Nearest to how: minerals, ththrough, comment, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, apologise, learnings, initd, airports,\n",
      "Nearest to way: make, junior, /await, gentlemen, fisherman, start, pot, l'toile,\n",
      "Nearest to would: a@tomgco, defends, drupal, clipboard, 2ms, taken, uploading, capital,\n",
      "Nearest to has: retire, agriculture, climbing, listened, 1bl, appraising, rofling, attraction,\n",
      "Nearest to guys: their, 55ish, nay, porreiro, namley, java/ruby, wins, were,\n",
      "Nearest to don't: ahahahahahahahaa, praying, strongest, documentation, slowing, table/row, 3148070-764065, homicide,\n",
      "Nearest to i'm: myemitteremit('error', jealous, autoformatter, nvidia, reason, crush, varnish, norm,\n",
      "\n",
      "\n",
      "Average loss at step  2000 :  89.2620960321 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  4000 :  32.404924258 \n",
      "\n",
      "\n",
      "Nearest to your: issues, ah, :thumbs_up_sign:, all, business, reasons, giphy, weak,\n",
      "Nearest to for: to, not, rt, and, child, feel, normal, in,\n",
      "Nearest to very: ah, connections, rt, heard, data, model, seat, want,\n",
      "Nearest to then: monday, wonderful, all, care, seem, anything, small, auto,\n",
      "Nearest to so: email, single, park, watch, based, together, concur, asking,\n",
      "Nearest to where: please, website, fully, away, can, put, development, enable,\n",
      "Nearest to i'll: source, rt, resource, behaviour, using, different, really, requires,\n",
      "Nearest to was: said, rt, whatever, take, more, welcome, isn't, transpiler,\n",
      "Nearest to same: london, leave, version, might, they're, scared, channel, case,\n",
      "Nearest to how: rt, comment, them, social, strong, drunk, except, new,\n",
      "Nearest to way: make, start, should, made, rt, phone, whatever, fine,\n",
      "Nearest to would: taken, hello, doesn't, welcome, book, docker, been, capital,\n",
      "Nearest to has: string, long, have, back, climbing, default, book, get,\n",
      "Nearest to guys: their, were, production, i've, when, though, simple, wins,\n",
      "Nearest to don't: please, problem, transpiler, ask, i've, strong, use, end,\n",
      "Nearest to i'm: reason, modules, jealous, clients, comes, to, reality, insurance,\n",
      "\n",
      "\n",
      "Average loss at step  6000 :  18.0917273995 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  8000 :  12.5298807571 \n",
      "\n",
      "\n",
      "Nearest to your: the, wanting, issues, giphy, amount, weak, reasons, themselves,\n",
      "Nearest to for: to, and, in, not, rt, with, at, of,\n",
      "Nearest to very: connections, seat, rt, ah, model, heard, wonderful, button,\n",
      "Nearest to then: monday, wonderful, mat, proposal, auto, seem, half, harp,\n",
      "Nearest to so: concur, park, single, email, UNK, watch, disappointed, sword,\n",
      "Nearest to where: fully, enable, please, website, development, darren, solved, rt,\n",
      "Nearest to i'll: resource, behaviour, rt, source, requires, artist, jk, leaves,\n",
      "Nearest to was: said, whatever, rt, take, more, transpiler, isn't, needed,\n",
      "Nearest to same: worst, leave, scared, idiot, non, version, channel, pencil,\n",
      "Nearest to how: comment, rt, social, drunk, them, except, strong, apologise,\n",
      "Nearest to way: make, start, rt, tc, made, phone, whatever, fine,\n",
      "Nearest to would: capital, taken, np, providers, hello, attempt, doesn't, can,\n",
      "Nearest to has: climbing, string, rt, default, trade, analysis, have, light,\n",
      "Nearest to guys: were, their, production, wins, i've, bigger, gifs, local,\n",
      "Nearest to don't: transpiler, documentation, please, reckon, strong, happens, ask, problem,\n",
      "Nearest to i'm: reason, jealous, modules, clients, to, insurance, comes, official,\n",
      "\n",
      "\n",
      "Average loss at step  10000 :  9.81891776896 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  12000 :  8.13396692201 \n",
      "\n",
      "\n",
      "Nearest to your: the, wanting, amount, giphy, weak, issues, themselves, reasons,\n",
      "Nearest to for: to, in, and, with, not, at, of, rt,\n",
      "Nearest to very: seat, connections, model, rt, ah, monolith, wonderful, button,\n",
      "Nearest to then: monday, wonderful, mat, proposal, auto, harp, cyclists, half,\n",
      "Nearest to so: concur, park, UNK, single, disappointed, -, sword, implemented,\n",
      "Nearest to where: fully, enable, darren, solved, development, ahahaha, please, website,\n",
      "Nearest to i'll: resource, behaviour, rt, fallen, jk, artist, source, requires,\n",
      "Nearest to was: said, whatever, is, rt, take, more, transpiler, openstack,\n",
      "Nearest to same: worst, idiot, pencil, scared, non, leave, spreadsheets, study,\n",
      "Nearest to how: comment, rt, social, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, apologise, drunk, except, harder,\n",
      "Nearest to way: make, start, tc, admit, walk, rt, fine, phone,\n",
      "Nearest to would: capital, can, np, taken, providers, rocket, doesn't, attempt,\n",
      "Nearest to has: climbing, string, retire, have, default, trade, analysis, light,\n",
      "Nearest to guys: were, their, production, wins, nay, bigger, promise, i've,\n",
      "Nearest to don't: transpiler, documentation, please, reckon, to, se, happens, rt,\n",
      "Nearest to i'm: jealous, reason, nvidia, clients, insurance, modules, is, to,\n",
      "\n",
      "\n",
      "Average loss at step  14000 :  7.35100242209 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  16000 :  6.62305992806 \n",
      "\n",
      "\n",
      "Nearest to your: the, wanting, my, amount, giphy, weak, themselves, asia,\n",
      "Nearest to for: to, in, with, and, at, not, of, splitting,\n",
      "Nearest to very: seat, connections, monolith, model, rt, courses, ah, hilarious,\n",
      "Nearest to then: mat, cyclists, wonderful, harp, monday, auto, proposal, horror,\n",
      "Nearest to so: concur, park, UNK, -, sword, disappointed, but, implemented,\n",
      "Nearest to where: fully, enable, darren, solved, ahahaha, struggle, era, development,\n",
      "Nearest to i'll: resource, behaviour, fallen, haskell, artist, jk, can, rt,\n",
      "Nearest to was: is, said, whatever, rt, pursue, openstack, take, more,\n",
      "Nearest to same: worst, idiot, pencil, spreadsheets, scared, study, non, leave,\n",
      "Nearest to how: comment, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, rt, apologise, social, drunk, initd, except,\n",
      "Nearest to way: make, start, admit, tc, walk, junior, 4g, fine,\n",
      "Nearest to would: can, capital, np, doesn't, providers, rocket, taken, attempt,\n",
      "Nearest to has: have, climbing, retire, string, default, facts, trade, plusnet,\n",
      "Nearest to guys: were, their, production, wins, nay, promise, bigger, local,\n",
      "Nearest to don't: transpiler, please, documentation, reckon, to, se, didn't, dont,\n",
      "Nearest to i'm: jealous, reason, nvidia, is, clients, insurance, norm, varnish,\n",
      "\n",
      "\n",
      "Average loss at step  18000 :  6.17707951505 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  20000 :  5.87949383163 \n",
      "\n",
      "\n",
      "Nearest to your: the, my, wanting, amount, giphy, asia, weak, themselves,\n",
      "Nearest to for: with, in, to, at, and, not, splitting, authorities,\n",
      "Nearest to very: seat, connections, monolith, model, courses, hilarious, ah, button,\n",
      "Nearest to then: cyclists, harp, mat, wonderful, auto, burning, proposal, monday,\n",
      "Nearest to so: concur, park, sword, -, but, disappointed, UNK, implemented,\n",
      "Nearest to where: enable, fully, darren, solved, ahahaha, struggle, era, unsafe,\n",
      "Nearest to i'll: resource, behaviour, fallen, can, haskell, artist, jk, scala,\n",
      "Nearest to was: is, said, whatever, pursue, openstack, isn't, rubber, take,\n",
      "Nearest to same: worst, idiot, pencil, spreadsheets, study, scared, co-exist, non,\n",
      "Nearest to how: comment, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, apologise, social, drunk, harder, except,\n",
      "Nearest to way: make, start, admit, walk, junior, tc, pot, 4g,\n",
      "Nearest to would: can, capital, doesn't, np, rocket, providers, don't, taken,\n",
      "Nearest to has: have, climbing, retire, string, facts, plusnet, is, default,\n",
      "Nearest to guys: were, their, nay, wins, production, promise, bigger, gifs,\n",
      "Nearest to don't: transpiler, please, documentation, didn't, reckon, dont, to, se,\n",
      "Nearest to i'm: jealous, nvidia, reason, norm, is, insurance, clients, varnish,\n",
      "\n",
      "\n",
      "Average loss at step  22000 :  5.61962632634 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  24000 :  5.48391075087 \n",
      "\n",
      "\n",
      "Nearest to your: the, my, wanting, asia, amount, license), andr, weak,\n",
      "Nearest to for: with, in, to, at, authorities, splitting, custard, and,\n",
      "Nearest to very: seat, monolith, connections, courses, hilarious, model, too, button,\n",
      "Nearest to then: cyclists, harp, mat, burning, auto, wonderful, horror, proposal,\n",
      "Nearest to so: concur, sword, park, -, but, disappointed, implemented, UNK,\n",
      "Nearest to where: enable, fully, darren, solved, era, struggle, ahahaha, unsafe,\n",
      "Nearest to i'll: resource, behaviour, can, fallen, haskell, scala, jk, artist,\n",
      "Nearest to was: is, said, pursue, whatever, openstack, isn't, rubber, take,\n",
      "Nearest to same: worst, idiot, pencil, spreadsheets, study, co-exist, :pp, codes),\n",
      "Nearest to how: comment, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, apologise, drunk, social, harder, airports,\n",
      "Nearest to way: make, start, admit, pot, junior, walk, tc, 4g,\n",
      "Nearest to would: can, doesn't, capital, don't, will, rocket, np, providers,\n",
      "Nearest to has: have, retire, climbing, string, facts, sr, is, plusnet,\n",
      "Nearest to guys: were, nay, their, wins, production, 100ms, promise, bigger,\n",
      "Nearest to don't: transpiler, please, didn't, dont, should, reckon, to, documentation,\n",
      "Nearest to i'm: jealous, nvidia, norm, reason, is, insurance, varnish, clients,\n",
      "\n",
      "\n",
      "Average loss at step  26000 :  5.25053980088 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  28000 :  5.16854542796 \n",
      "\n",
      "\n",
      "Nearest to your: the, my, wanting, asia, license), amount, andr, weak,\n",
      "Nearest to for: with, rt, authorities, at, in, custard, to, splitting,\n",
      "Nearest to very: seat, monolith, connections, rt, too, courses, hilarious, model,\n",
      "Nearest to then: cyclists, harp, burning, mat, auto, stated, wonderful, horror,\n",
      "Nearest to so: concur, sword, park, but, disappointed, -, implemented, journalists,\n",
      "Nearest to where: enable, fully, darren, era, solved, struggle, unsafe, ahahaha,\n",
      "Nearest to i'll: resource, can, behaviour, rt, fallen, haskell, scala, vi,\n",
      "Nearest to was: is, said, rt, pursue, openstack, isn't, whatever, rubber,\n",
      "Nearest to same: worst, idiot, pencil, spreadsheets, function(chunk, co-exist, :pp, study,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, rt, initd, apologise, drunk, airports, elections,\n",
      "Nearest to way: make, pot, junior, admit, start, walk, prank, tc,\n",
      "Nearest to would: can, doesn't, capital, will, don't, could, rocket, providers,\n",
      "Nearest to has: have, retire, climbing, string, rt, sr, facts, is,\n",
      "Nearest to guys: were, nay, their, 100ms, wins, production, permutation, promise,\n",
      "Nearest to don't: rt, dont, transpiler, didn't, please, should, reckon, slowing,\n",
      "Nearest to i'm: jealous, nvidia, norm, reason, insurance, is, varnish, clients,\n",
      "\n",
      "\n",
      "Average loss at step  30000 :  5.03011652303 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  32000 :  4.94489180966 \n",
      "\n",
      "\n",
      "Nearest to your: the, my, wanting, license), asia, andr, amount, weak,\n",
      "Nearest to for: authorities, with, rt, custard, at, splitting, teaching, to,\n",
      "Nearest to very: seat, monolith, rt, connections, too, hilarious, courses, ambiguous,\n",
      "Nearest to then: cyclists, harp, burning, mat, stated, auto, ingles, if,\n",
      "Nearest to so: concur, sword, park, disappointed, but, -, journalists, implemented,\n",
      "Nearest to where: enable, fully, darren, era, struggle, solved, unsafe, ahahaha,\n",
      "Nearest to i'll: resource, rt, can, behaviour, fallen, haskell, scala, vi,\n",
      "Nearest to was: is, said, pursue, rt, isn't, openstack, whatever, rubber,\n",
      "Nearest to same: worst, idiot, pencil, function(chunk, spreadsheets, :pp, co-exist, codes),\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, initd, rt, apologise, elections, airports, drunk,\n",
      "Nearest to way: make, pot, junior, admit, prank, start, walk, 4g,\n",
      "Nearest to would: can, doesn't, will, don't, could, capital, rocket, o'reilly,\n",
      "Nearest to has: have, retire, climbing, string, sr, rt, is, facts,\n",
      "Nearest to guys: were, nay, 100ms, their, wins, permutation, promise, production,\n",
      "Nearest to don't: rt, dont, didn't, transpiler, should, please, slowing, reckon,\n",
      "Nearest to i'm: jealous, nvidia, norm, reason, insurance, varnish, is, theory,\n",
      "\n",
      "\n",
      "Average loss at step  34000 :  4.86690038657 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  36000 :  4.79307893038 \n",
      "\n",
      "\n",
      "Nearest to your: the, my, license), wanting, asia, andr, amount, weak,\n",
      "Nearest to for: authorities, with, custard, splitting, rt, at, audit, teaching,\n",
      "Nearest to very: seat, monolith, connections, too, hilarious, rt, courses, exposure,\n",
      "Nearest to then: cyclists, harp, burning, stated, mat, ingles, refers, auto,\n",
      "Nearest to so: concur, sword, park, disappointed, but, exam, journalists, circunstances,\n",
      "Nearest to where: enable, fully, era, darren, struggle, unsafe, solved, ahahaha,\n",
      "Nearest to i'll: resource, can, rt, behaviour, haskell, fallen, scala, vi,\n",
      "Nearest to was: is, said, pursue, isn't, openstack, rubber, whatever, rightmove,\n",
      "Nearest to same: worst, idiot, pencil, function(chunk, :pp, co-exist, spreadsheets, codes),\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, initd, apologise, elections, pilau, airports, drunk,\n",
      "Nearest to way: pot, junior, admit, make, prank, walk, 4g, start,\n",
      "Nearest to would: can, doesn't, will, don't, could, capital, o'reilly, rocket,\n",
      "Nearest to has: have, retire, climbing, string, sr, facts, appraising, is,\n",
      "Nearest to guys: were, nay, 100ms, permutation, their, wins, promise, gifs,\n",
      "Nearest to don't: rt, dont, didn't, should, transpiler, please, slowing, reckon,\n",
      "Nearest to i'm: nvidia, jealous, norm, reason, theory, insurance, varnish, somebody,\n",
      "\n",
      "\n",
      "Average loss at step  38000 :  4.76155141973 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  40000 :  4.6761742596 \n",
      "\n",
      "\n",
      "Nearest to your: the, my, license), wanting, asia, andr, amount, weak,\n",
      "Nearest to for: authorities, custard, with, splitting, rt, audit, replied, teaching,\n",
      "Nearest to very: seat, monolith, too, connections, hilarious, rt, courses, exposure,\n",
      "Nearest to then: harp, cyclists, burning, stated, ingles, notifications*, mat, pimp,\n",
      "Nearest to so: concur, sword, park, disappointed, exam, but, journalists, circunstances,\n",
      "Nearest to where: enable, fully, era, darren, struggle, unsafe, solved, ahahaha,\n",
      "Nearest to i'll: resource, can, rt, haskell, fallen, behaviour, scala, vi,\n",
      "Nearest to was: is, said, pursue, isn't, openstack, rightmove, rubber, whatever,\n",
      "Nearest to same: worst, idiot, pencil, function(chunk, :pp, co-exist, codes), spreadsheets,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, comment, apologise, elections, pilau, drunk, airports,\n",
      "Nearest to way: pot, junior, prank, admit, make, walk, 4g, start,\n",
      "Nearest to would: can, doesn't, will, could, don't, capital, should, o'reilly,\n",
      "Nearest to has: have, retire, climbing, sr, string, facts, agriculture, appraising,\n",
      "Nearest to guys: were, 100ms, nay, permutation, wins, their, promise, gifs,\n",
      "Nearest to don't: rt, dont, didn't, should, transpiler, please, slowing, reckon,\n",
      "Nearest to i'm: nvidia, norm, jealous, you're, reason, theory, varnish, insurance,\n",
      "\n",
      "\n",
      "Average loss at step  42000 :  4.65699543792 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  44000 :  4.60893424511 \n",
      "\n",
      "\n",
      "Nearest to your: the, my, license), wanting, asia, andr, er;, amount,\n",
      "Nearest to for: authorities, custard, rt, splitting, audit, with, replied, teaching,\n",
      "Nearest to very: seat, monolith, too, rt, connections, hilarious, exposure, courses,\n",
      "Nearest to then: harp, cyclists, burning, stated, ingles, notifications*, refers, pimp,\n",
      "Nearest to so: concur, sword, park, disappointed, exam, maida, journalists, circunstances,\n",
      "Nearest to where: enable, fully, era, struggle, darren, unsafe, solved, ahahaha,\n",
      "Nearest to i'll: resource, rt, can, haskell, fallen, behaviour, scala, vi,\n",
      "Nearest to was: is, said, pursue, isn't, openstack, rt, rightmove, rubber,\n",
      "Nearest to same: worst, idiot, pencil, function(chunk, :pp, best, co-exist, codes),\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, comment, apologise, elections, ththrough, pilau, airports,\n",
      "Nearest to way: pot, junior, prank, admit, 4g, walk, make, start,\n",
      "Nearest to would: can, doesn't, will, could, don't, should, o'reilly, capital,\n",
      "Nearest to has: have, retire, sr, climbing, agriculture, string, facts, appraising,\n",
      "Nearest to guys: 100ms, were, nay, permutation, wins, their, gifs, picked,\n",
      "Nearest to don't: rt, dont, didn't, should, transpiler, please, slowing, reckon,\n",
      "Nearest to i'm: norm, nvidia, jealous, you're, theory, adventures, http/11, somebody,\n",
      "\n",
      "\n",
      "Average loss at step  46000 :  4.56619326016 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  48000 :  4.56361023378 \n",
      "\n",
      "\n",
      "Nearest to your: the, my, license), wanting, asia, andr, er;, amount,\n",
      "Nearest to for: authorities, custard, splitting, audit, replied, datacentres, teaching, on),\n",
      "Nearest to very: seat, monolith, too, hilarious, connections, exposure, suspicions, shortage),\n",
      "Nearest to then: cyclists, burning, harp, stated, pimp, notifications*, simonspringett@ntlworldcom, ingles,\n",
      "Nearest to so: concur, sword, park, exam, disappointed, maida, journalists, criticise,\n",
      "Nearest to where: enable, fully, era, struggle, darren, unsafe, solved, libuv,\n",
      "Nearest to i'll: can, resource, rt, haskell, fallen, behaviour, scala, vi,\n",
      "Nearest to was: is, said, pursue, isn't, openstack, rightmove, rubber, go-lang,\n",
      "Nearest to same: worst, idiot, pencil, function(chunk, :pp, best, co-exist, codes),\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, comment, apologise, elections, ththrough, pilau, airports,\n",
      "Nearest to way: pot, junior, prank, admit, 4g, walk, make, start,\n",
      "Nearest to would: can, will, doesn't, could, don't, should, o'reilly, capital,\n",
      "Nearest to has: have, sr, agriculture, retire, climbing, facts, string, queues,\n",
      "Nearest to guys: 100ms, were, nay, permutation, gifs, wins, picked, their,\n",
      "Nearest to don't: rt, dont, didn't, should, slowing, transpiler, reckon, would,\n",
      "Nearest to i'm: norm, nvidia, jealous, you're, theory, adventures, http/11, varnish,\n",
      "\n",
      "\n",
      "Average loss at step  50000 :  4.51297840351 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  52000 :  4.49727348237 \n",
      "\n",
      "\n",
      "Nearest to your: the, my, license), wanting, asia, andr, er;, #done,\n",
      "Nearest to for: authorities, custard, datacentres, audit, replied, splitting, on), teaching,\n",
      "Nearest to very: seat, monolith, too, hilarious, connections, exposure, suspicions, shortage),\n",
      "Nearest to then: burning, harp, cyclists, stated, pimp, simonspringett@ntlworldcom, ingles, notifications*,\n",
      "Nearest to so: concur, sword, park, exam, disappointed, maida, criticise, journalists,\n",
      "Nearest to where: enable, fully, era, struggle, darren, unsafe, solved, ssh+git,\n",
      "Nearest to i'll: resource, can, haskell, fallen, behaviour, scala, rt, vi,\n",
      "Nearest to was: is, said, isn't, pursue, openstack, rightmove, blankey, summarising,\n",
      "Nearest to same: worst, idiot, pencil, function(chunk, :pp, best, co-exist, codes),\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, comment, apologise, elections, ththrough, pilau, minerals,\n",
      "Nearest to way: pot, junior, prank, 4g, admit, walk, make, start,\n",
      "Nearest to would: can, will, doesn't, could, don't, should, o'reilly, rocket,\n",
      "Nearest to has: have, agriculture, sr, retire, facts, string, climbing, queues,\n",
      "Nearest to guys: 100ms, were, nay, permutation, gifs, picked, wins, their,\n",
      "Nearest to don't: dont, rt, didn't, should, slowing, reckon, would, transpiler,\n",
      "Nearest to i'm: norm, nvidia, jealous, you're, adventures, theory, http/11, uhhhh,\n",
      "\n",
      "\n",
      "Average loss at step  54000 :  4.46824384856 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  56000 :  4.45889426705 \n",
      "\n",
      "\n",
      "Nearest to your: the, my, license), wanting, andr, asia, er;, #done,\n",
      "Nearest to for: authorities, custard, datacentres, audit, replied, splitting, on), teaching,\n",
      "Nearest to very: seat, monolith, too, hilarious, exposure, suspicions, shortage), connections,\n",
      "Nearest to then: burning, stated, harp, cyclists, simonspringett@ntlworldcom, pimp, ingles, refers,\n",
      "Nearest to so: concur, sword, park, exam, maida, disappointed, criticise, simplify,\n",
      "Nearest to where: enable, fully, era, struggle, darren, unsafe, solved, permission,\n",
      "Nearest to i'll: resource, can, haskell, fallen, rt, behaviour, scala, vi,\n",
      "Nearest to was: is, said, pursue, isn't, openstack, rightmove, blankey, go-lang,\n",
      "Nearest to same: worst, idiot, pencil, function(chunk, best, :pp, codes), co-exist,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, comment, apologise, elections, ththrough, minerals, pilau,\n",
      "Nearest to way: pot, junior, prank, 4g, admit, walk, initial, start,\n",
      "Nearest to would: can, will, doesn't, could, don't, should, o'reilly, rocket,\n",
      "Nearest to has: have, agriculture, sr, facts, retire, string, 1bl, queues,\n",
      "Nearest to guys: 100ms, nay, were, permutation, gifs, picked, wins, exploiting,\n",
      "Nearest to don't: dont, rt, didn't, should, slowing, reckon, would, transpiler,\n",
      "Nearest to i'm: norm, nvidia, jealous, you're, adventures, theory, http/11, uhhhh,\n",
      "\n",
      "\n",
      "Average loss at step  58000 :  4.43940626836 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  60000 :  4.40720448767 \n",
      "\n",
      "\n",
      "Nearest to your: the, my, license), wanting, andr, asia, er;, #done,\n",
      "Nearest to for: authorities, custard, datacentres, audit, replied, on), splitting, teaching,\n",
      "Nearest to very: seat, monolith, too, hilarious, exposure, suspicions, shortage), connections,\n",
      "Nearest to then: burning, stated, harp, cyclists, simonspringett@ntlworldcom, pimp, refers, ingles,\n",
      "Nearest to so: concur, sword, park, exam, maida, simplify, disappointed, criticise,\n",
      "Nearest to where: enable, fully, era, struggle, darren, unsafe, permission, ssh+git,\n",
      "Nearest to i'll: resource, can, haskell, rt, fallen, behaviour, scala, vi,\n",
      "Nearest to was: is, said, pursue, isn't, openstack, rightmove, blankey, summarising,\n",
      "Nearest to same: worst, idiot, pencil, function(chunk, best, :pp, co-exist, codes),\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, comment, elections, apologise, ththrough, minerals, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, admit, walk, initial, favor,\n",
      "Nearest to would: can, will, doesn't, could, don't, should, o'reilly, yisssss,\n",
      "Nearest to has: have, agriculture, sr, facts, 1bl, retire, string, nintendo,\n",
      "Nearest to guys: 100ms, were, nay, permutation, gifs, picked, films, exploiting,\n",
      "Nearest to don't: dont, rt, didn't, should, slowing, reckon, would, transpiler,\n",
      "Nearest to i'm: norm, nvidia, jealous, you're, adventures, http/11, theory, uhhhh,\n",
      "\n",
      "\n",
      "Average loss at step  62000 :  4.42540799367 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  64000 :  4.37958738846 \n",
      "\n",
      "\n",
      "Nearest to your: my, the, license), wanting, andr, asia, er;, hintjens',\n",
      "Nearest to for: authorities, datacentres, custard, audit, replied, on), splitting, meantime,\n",
      "Nearest to very: seat, monolith, too, hilarious, exposure, suspicions, shortage), angularjs,\n",
      "Nearest to then: burning, stated, harp, simonspringett@ntlworldcom, cyclists, pimp, ingles, refers,\n",
      "Nearest to so: concur, sword, park, exam, maida, simplify, criticise, disappointed,\n",
      "Nearest to where: enable, fully, era, struggle, unsafe, darren, permission, ssh+git,\n",
      "Nearest to i'll: resource, can, haskell, fallen, rt, scala, behaviour, vi,\n",
      "Nearest to was: is, said, pursue, isn't, openstack, rightmove, blankey, summarising,\n",
      "Nearest to same: worst, idiot, pencil, function(chunk, best, :pp, co-exist, codes),\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, comment, elections, apologise, minerals, ththrough, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, admit, walk, favor, initial,\n",
      "Nearest to would: can, will, doesn't, could, don't, should, o'reilly, yisssss,\n",
      "Nearest to has: have, agriculture, sr, 1bl, facts, means, attraction, retire,\n",
      "Nearest to guys: 100ms, nay, were, permutation, gifs, picked, films, exploiting,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, slowing, would, transpiler,\n",
      "Nearest to i'm: norm, nvidia, jealous, you're, adventures, http/11, theory, uhhhh,\n",
      "\n",
      "\n",
      "Average loss at step  66000 :  4.38748130129 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  68000 :  4.36225596821 \n",
      "\n",
      "\n",
      "Nearest to your: my, the, license), wanting, andr, er;, asia, hintjens',\n",
      "Nearest to for: authorities, custard, datacentres, audit, on), replied, splitting, meantime,\n",
      "Nearest to very: seat, monolith, too, hilarious, exposure, suspicions, shortage), rt,\n",
      "Nearest to then: burning, stated, harp, simonspringett@ntlworldcom, cyclists, pimp, ingles, refers,\n",
      "Nearest to so: sword, concur, park, exam, maida, simplify, criticise, disappointed,\n",
      "Nearest to where: enable, fully, era, struggle, unsafe, darren, permission, def,\n",
      "Nearest to i'll: rt, resource, can, haskell, fallen, scala, behaviour, bacalhau,\n",
      "Nearest to was: is, said, isn't, pursue, openstack, rightmove, blankey, summarising,\n",
      "Nearest to same: worst, idiot, pencil, best, function(chunk, :pp, co-exist, codes),\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, elections, apologise, minerals, ththrough, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, admit, walk, favor, initial,\n",
      "Nearest to would: can, will, could, doesn't, don't, should, o'reilly, rt,\n",
      "Nearest to has: have, agriculture, sr, 1bl, facts, means, queues, attraction,\n",
      "Nearest to guys: 100ms, nay, permutation, were, gifs, picked, 2002, films,\n",
      "Nearest to don't: rt, dont, didn't, should, reckon, slowing, would, can't,\n",
      "Nearest to i'm: norm, nvidia, jealous, you're, adventures, http/11, theory, uhhhh,\n",
      "\n",
      "\n",
      "Average loss at step  70000 :  4.35204021465 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  72000 :  4.35290931118 \n",
      "\n",
      "\n",
      "Nearest to your: my, the, license), andr, wanting, er;, asia, hintjens',\n",
      "Nearest to for: authorities, datacentres, custard, replied, audit, on), pushes, meantime,\n",
      "Nearest to very: seat, monolith, too, hilarious, exposure, suspicions, shortage), pretty,\n",
      "Nearest to then: burning, stated, simonspringett@ntlworldcom, harp, pimp, cyclists, ingles, refers,\n",
      "Nearest to so: sword, concur, park, exam, maida, simplify, criticise, disappointed,\n",
      "Nearest to where: enable, fully, era, struggle, darren, unsafe, def, permission,\n",
      "Nearest to i'll: rt, resource, can, haskell, scala, fallen, behaviour, bacalhau,\n",
      "Nearest to was: is, isn't, said, pursue, openstack, rightmove, blankey, summarising,\n",
      "Nearest to same: worst, idiot, pencil, best, function(chunk, :pp, co-exist, irssi,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, elections, minerals, ththrough, apologise, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, admit, favor, walk, initial,\n",
      "Nearest to would: can, will, could, doesn't, don't, should, o'reilly, mondo,\n",
      "Nearest to has: have, agriculture, sr, 1bl, means, facts, attraction, perform,\n",
      "Nearest to guys: 100ms, nay, permutation, were, gifs, picked, 2002, 20~22,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, slowing, would, can't,\n",
      "Nearest to i'm: norm, nvidia, jealous, you're, adventures, http/11, uhhhh, theory,\n",
      "\n",
      "\n",
      "Average loss at step  74000 :  4.32194861993 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  76000 :  4.33847116601 \n",
      "\n",
      "\n",
      "Nearest to your: my, the, license), andr, er;, wanting, asia, hintjens',\n",
      "Nearest to for: authorities, datacentres, custard, audit, replied, on), pushes, cloudshell,\n",
      "Nearest to very: seat, monolith, too, hilarious, exposure, suspicions, shortage), pretty,\n",
      "Nearest to then: burning, simonspringett@ntlworldcom, stated, harp, pimp, cyclists, injury, refers,\n",
      "Nearest to so: sword, concur, park, exam, maida, simplify, criticise, disappointed,\n",
      "Nearest to where: enable, fully, era, struggle, darren, unsafe, def, permission,\n",
      "Nearest to i'll: rt, resource, haskell, can, scala, fallen, behaviour, bacalhau,\n",
      "Nearest to was: is, isn't, said, pursue, openstack, rightmove, blankey, &@dscape,\n",
      "Nearest to same: worst, idiot, pencil, best, function(chunk, :pp, irssi, co-exist,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, elections, minerals, ththrough, apologise, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, admit, initial, walk,\n",
      "Nearest to would: can, will, could, doesn't, don't, should, o'reilly, yisssss,\n",
      "Nearest to has: have, agriculture, sr, 1bl, means, facts, queues, attraction,\n",
      "Nearest to guys: 100ms, permutation, nay, were, gifs, 20~22, 2002, picked,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, slowing, would, can't,\n",
      "Nearest to i'm: norm, nvidia, you're, jealous, adventures, uhhhh, http/11, theory,\n",
      "\n",
      "\n",
      "Average loss at step  78000 :  4.29878366888 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  80000 :  4.3181094923 \n",
      "\n",
      "\n",
      "Nearest to your: my, the, license), wanting, er;, andr, asia, hintjens',\n",
      "Nearest to for: authorities, datacentres, custard, audit, on), replied, pushes, cloudshell,\n",
      "Nearest to very: seat, monolith, too, exposure, hilarious, pretty, suspicions, shortage),\n",
      "Nearest to then: burning, stated, simonspringett@ntlworldcom, pimp, harp, cyclists, injury, refers,\n",
      "Nearest to so: sword, concur, park, exam, maida, simplify, criticise, journalists,\n",
      "Nearest to where: enable, fully, era, struggle, darren, unsafe, def, permission,\n",
      "Nearest to i'll: rt, resource, haskell, can, scala, fallen, behaviour, bacalhau,\n",
      "Nearest to was: is, isn't, said, pursue, blankey, openstack, rightmove, &@dscape,\n",
      "Nearest to same: worst, idiot, pencil, best, function(chunk, :pp, irssi, co-exist,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, elections, minerals, ththrough, apologise, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, admit, initial, walk,\n",
      "Nearest to would: can, will, could, doesn't, should, don't, yisssss, o'reilly,\n",
      "Nearest to has: have, agriculture, 1bl, means, sr, facts, perform, attraction,\n",
      "Nearest to guys: 100ms, permutation, nay, were, gifs, 20~22, 2002, films,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, slowing, can't, would,\n",
      "Nearest to i'm: norm, nvidia, you're, jealous, adventures, im, uhhhh, http/11,\n",
      "\n",
      "\n",
      "Average loss at step  82000 :  4.28997674036 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  84000 :  4.28532832761 \n",
      "\n",
      "\n",
      "Nearest to your: my, the, license), andr, er;, wanting, asia, hintjens',\n",
      "Nearest to for: authorities, datacentres, custard, on), audit, replied, pushes, dialect,\n",
      "Nearest to very: seat, monolith, too, exposure, hilarious, pretty, shortage), suspicions,\n",
      "Nearest to then: burning, simonspringett@ntlworldcom, stated, pimp, harp, cyclists, injury, refers,\n",
      "Nearest to so: sword, concur, park, exam, simplify, maida, criticise, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, darren, def, unsafe, permission,\n",
      "Nearest to i'll: rt, resource, haskell, can, scala, fallen, behaviour, bacalhau,\n",
      "Nearest to was: is, pursue, isn't, said, blankey, rightmove, openstack, &@dscape,\n",
      "Nearest to same: worst, idiot, best, pencil, function(chunk, :pp, irssi, co-exist,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, elections, minerals, ththrough, apologise, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, admit, initial, walk,\n",
      "Nearest to would: can, will, could, doesn't, should, don't, yisssss, midori,\n",
      "Nearest to has: have, agriculture, 1bl, means, sr, perform, facts, attraction,\n",
      "Nearest to guys: 100ms, permutation, nay, were, gifs, 20~22, 2002, films,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, slowing, can't, would,\n",
      "Nearest to i'm: norm, nvidia, you're, jealous, adventures, im, uhhhh, http/11,\n",
      "\n",
      "\n",
      "Average loss at step  86000 :  4.29330537856 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  88000 :  4.25045283443 \n",
      "\n",
      "\n",
      "Nearest to your: my, the, license), er;, andr, wanting, asia, hintjens',\n",
      "Nearest to for: authorities, datacentres, custard, on), audit, replied, pushes, dialect,\n",
      "Nearest to very: monolith, seat, too, pretty, exposure, hilarious, suspicions, angularjs,\n",
      "Nearest to then: burning, simonspringett@ntlworldcom, pimp, stated, harp, cyclists, injury, attacks,\n",
      "Nearest to so: sword, concur, park, exam, simplify, maida, criticise, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, darren, def, unsafe, permission,\n",
      "Nearest to i'll: rt, resource, haskell, can, scala, fallen, behaviour, will,\n",
      "Nearest to was: pursue, isn't, is, said, blankey, rightmove, &@dscape, openstack,\n",
      "Nearest to same: worst, idiot, best, pencil, function(chunk, :pp, irssi, co-exist,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, elections, minerals, ththrough, apologise, robomongo,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, admit, initial, chunk,\n",
      "Nearest to would: can, will, could, doesn't, should, don't, yisssss, rt,\n",
      "Nearest to has: have, agriculture, 1bl, means, sr, perform, attraction, facts,\n",
      "Nearest to guys: 100ms, permutation, nay, were, gifs, 20~22, 2002, tottaly,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, slowing, can't, would,\n",
      "Nearest to i'm: norm, nvidia, you're, jealous, im, adventures, http/11, uhhhh,\n",
      "\n",
      "\n",
      "Average loss at step  90000 :  4.27364305063 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  92000 :  4.2447927599 \n",
      "\n",
      "\n",
      "Nearest to your: my, the, license), er;, andr, wanting, asia, hintjens',\n",
      "Nearest to for: authorities, datacentres, custard, on), replied, audit, pushes, dialect,\n",
      "Nearest to very: monolith, seat, too, pretty, exposure, hilarious, suspicions, angularjs,\n",
      "Nearest to then: burning, simonspringett@ntlworldcom, pimp, stated, harp, cyclists, injury, attacks,\n",
      "Nearest to so: sword, concur, exam, park, maida, simplify, criticise, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, unsafe, permission,\n",
      "Nearest to i'll: rt, resource, haskell, can, scala, fallen, behaviour, bacalhau,\n",
      "Nearest to was: pursue, isn't, said, is, blankey, rightmove, &@dscape, openstack,\n",
      "Nearest to same: worst, idiot, best, pencil, function(chunk, :pp, irssi, co-exist,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, minerals, elections, ththrough, apologise, robomongo,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, initial, chunk, admit,\n",
      "Nearest to would: can, will, could, doesn't, should, don't, rt, yisssss,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, sr, attraction, facts,\n",
      "Nearest to guys: 100ms, permutation, nay, were, 20~22, 2002, gifs, tottaly,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, slowing, can't, would,\n",
      "Nearest to i'm: norm, nvidia, you're, jealous, im, adventures, uhhhh, http/11,\n",
      "\n",
      "\n",
      "Average loss at step  94000 :  4.24029628638 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  96000 :  4.24158557951 \n",
      "\n",
      "\n",
      "Nearest to your: my, the, license), er;, andr, wanting, asia, hintjens',\n",
      "Nearest to for: authorities, datacentres, custard, rt, on), replied, audit, pushes,\n",
      "Nearest to very: monolith, seat, too, pretty, rt, exposure, hilarious, suspicions,\n",
      "Nearest to then: burning, pimp, simonspringett@ntlworldcom, stated, harp, injury, cyclists, attacks,\n",
      "Nearest to so: sword, concur, exam, park, simplify, maida, criticise, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, permission, unsafe,\n",
      "Nearest to i'll: rt, resource, haskell, can, scala, fallen, bacalhau, behaviour,\n",
      "Nearest to was: pursue, isn't, said, is, blankey, rightmove, &@dscape, openstack,\n",
      "Nearest to same: worst, idiot, best, pencil, function(chunk, :pp, irssi, co-exist,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, elections, minerals, ththrough, apologise, robomongo,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, initial, chunk, admit,\n",
      "Nearest to would: can, will, could, doesn't, rt, should, don't, midori,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, sr, attraction, facts,\n",
      "Nearest to guys: 100ms, permutation, nay, 20~22, 2002, gifs, were, tottaly,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, slowing, can't, would,\n",
      "Nearest to i'm: norm, nvidia, you're, im, jealous, adventures, uhhhh, http/11,\n",
      "\n",
      "\n",
      "Average loss at step  98000 :  4.20391663694 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  100000 :  4.24115013707 \n",
      "\n",
      "\n",
      "Nearest to your: my, the, license), er;, andr, wanting, asia, laugh,\n",
      "Nearest to for: authorities, datacentres, custard, on), replied, audit, pushes, dialect,\n",
      "Nearest to very: monolith, seat, pretty, too, exposure, hilarious, shortage), angularjs,\n",
      "Nearest to then: burning, simonspringett@ntlworldcom, pimp, stated, injury, harp, cyclists, attacks,\n",
      "Nearest to so: sword, concur, exam, park, simplify, criticise, maida, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, permission, unsafe,\n",
      "Nearest to i'll: rt, resource, haskell, scala, can, bacalhau, fallen, behaviour,\n",
      "Nearest to was: pursue, isn't, said, is, blankey, rightmove, &@dscape, openstack,\n",
      "Nearest to same: worst, idiot, best, pencil, function(chunk, :pp, irssi, co-exist,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, elections, minerals, ththrough, apologise, robomongo,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, initial, chunk, /await,\n",
      "Nearest to would: can, will, could, doesn't, should, don't, rt, midori,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, attraction, sr, queues,\n",
      "Nearest to guys: 100ms, permutation, nay, 20~22, 2002, gifs, were, tottaly,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, can't, slowing, he'll,\n",
      "Nearest to i'm: norm, nvidia, you're, im, jealous, adventures, uhhhh, 15tb,\n",
      "\n",
      "\n",
      "Average loss at step  102000 :  4.19484743673 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  104000 :  4.22174058686 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), the, er;, andr, wanting, laugh, asia,\n",
      "Nearest to for: authorities, datacentres, custard, on), audit, replied, pushes, dialect,\n",
      "Nearest to very: monolith, seat, pretty, too, exposure, hilarious, angularjs, shortage),\n",
      "Nearest to then: burning, pimp, simonspringett@ntlworldcom, stated, injury, cyclists, harp, addresses,\n",
      "Nearest to so: sword, concur, exam, park, simplify, maida, criticise, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, permission, unsafe,\n",
      "Nearest to i'll: rt, resource, haskell, scala, can, bacalhau, fallen, behaviour,\n",
      "Nearest to was: pursue, isn't, said, is, blankey, &@dscape, rightmove, openstack,\n",
      "Nearest to same: worst, idiot, best, pencil, irssi, :pp, function(chunk, co-exist,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, minerals, elections, ththrough, robomongo, apologise,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, initial, chunk, /await,\n",
      "Nearest to would: can, will, could, doesn't, should, don't, midori, yisssss,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, attraction, sr, facts,\n",
      "Nearest to guys: 100ms, permutation, nay, 20~22, 2002, gifs, were, tottaly,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, can't, slowing, he'll,\n",
      "Nearest to i'm: norm, nvidia, you're, im, jealous, adventures, uhhhh, http/11,\n",
      "\n",
      "\n",
      "Average loss at step  106000 :  4.20043149203 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  108000 :  4.18645685483 \n",
      "\n",
      "\n",
      "Nearest to your: my, the, license), er;, andr, wanting, laugh, asia,\n",
      "Nearest to for: authorities, datacentres, custard, on), audit, pushes, replied, dialect,\n",
      "Nearest to very: monolith, seat, pretty, too, exposure, hilarious, angularjs, shortage),\n",
      "Nearest to then: burning, simonspringett@ntlworldcom, pimp, stated, injury, harp, cyclists, addresses,\n",
      "Nearest to so: sword, concur, exam, park, simplify, maida, criticise, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, permission, unsafe,\n",
      "Nearest to i'll: rt, resource, haskell, scala, can, bacalhau, fallen, behaviour,\n",
      "Nearest to was: pursue, isn't, said, is, blankey, &@dscape, rightmove, openstack,\n",
      "Nearest to same: worst, idiot, best, pencil, irssi, :pp, function(chunk, co-exist,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, minerals, elections, ththrough, robomongo, apologise,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, initial, chunk, /await,\n",
      "Nearest to would: can, will, could, doesn't, should, don't, midori, rt,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, attraction, sr, queues,\n",
      "Nearest to guys: 100ms, permutation, nay, 20~22, 2002, gifs, were, tottaly,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, can't, slowing, he'll,\n",
      "Nearest to i'm: norm, you're, nvidia, im, jealous, adventures, uhhhh, http/11,\n",
      "\n",
      "\n",
      "Average loss at step  110000 :  4.20512461579 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  112000 :  4.16211433202 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), the, er;, andr, wanting, laugh, hintjens',\n",
      "Nearest to for: authorities, datacentres, custard, on), audit, replied, dialect, pushes,\n",
      "Nearest to very: monolith, seat, pretty, too, exposure, hilarious, angularjs, shortage),\n",
      "Nearest to then: burning, pimp, simonspringett@ntlworldcom, injury, stated, harp, cyclists, addresses,\n",
      "Nearest to so: sword, concur, exam, park, simplify, criticise, maida, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, permission, unsafe,\n",
      "Nearest to i'll: rt, haskell, resource, scala, can, bacalhau, fallen, will,\n",
      "Nearest to was: pursue, isn't, said, is, blankey, &@dscape, rightmove, openstack,\n",
      "Nearest to same: worst, idiot, best, pencil, irssi, :pp, function(chunk, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, minerals, elections, ththrough, robomongo, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, chunk, initial, /await,\n",
      "Nearest to would: can, will, could, doesn't, should, don't, midori, rt,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, attraction, sr, queues,\n",
      "Nearest to guys: 100ms, permutation, 20~22, nay, 2002, gifs, tottaly, were,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, can't, slowing, he'll,\n",
      "Nearest to i'm: norm, im, you're, nvidia, jealous, adventures, uhhhh, http/11,\n",
      "\n",
      "\n",
      "Average loss at step  114000 :  4.1773687354 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  116000 :  4.16449962419 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), the, er;, andr, wanting, laugh, hintjens',\n",
      "Nearest to for: authorities, datacentres, custard, on), audit, replied, pushes, dialect,\n",
      "Nearest to very: monolith, seat, pretty, too, exposure, hilarious, angularjs, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, stated, harp, cyclists, addresses,\n",
      "Nearest to so: sword, exam, concur, simplify, park, maida, criticise, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, permission, unsafe,\n",
      "Nearest to i'll: haskell, resource, scala, rt, can, bacalhau, fallen, will,\n",
      "Nearest to was: pursue, isn't, said, is, blankey, &@dscape, rightmove, openstack,\n",
      "Nearest to same: worst, idiot, best, pencil, irssi, :pp, function(chunk, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, minerals, elections, ththrough, robomongo, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, chunk, initial, /await,\n",
      "Nearest to would: can, will, could, doesn't, should, don't, midori, yisssss,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, attraction, sr, queues,\n",
      "Nearest to guys: 100ms, permutation, 20~22, 2002, nay, gifs, tottaly, films,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, can't, slowing, he'll,\n",
      "Nearest to i'm: norm, im, you're, nvidia, adventures, jealous, uhhhh, http/11,\n",
      "\n",
      "\n",
      "Average loss at step  118000 :  4.15544937454 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  120000 :  4.16369836211 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), the, er;, laugh, andr, wanting, lite,\n",
      "Nearest to for: authorities, datacentres, custard, on), pushes, audit, replied, dialect,\n",
      "Nearest to very: monolith, seat, pretty, exposure, too, angularjs, hilarious, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, stated, cyclists, harp, addresses,\n",
      "Nearest to so: sword, exam, concur, simplify, park, criticise, maida, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, permission, unsafe,\n",
      "Nearest to i'll: rt, haskell, resource, scala, bacalhau, can, fallen, will,\n",
      "Nearest to was: pursue, isn't, said, blankey, is, &@dscape, rightmove, openstack,\n",
      "Nearest to same: worst, idiot, best, pencil, irssi, :pp, function(chunk, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, minerals, elections, ththrough, robomongo, apologise,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, chunk, initial, /await,\n",
      "Nearest to would: can, will, could, doesn't, should, rt, don't, midori,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, attraction, sr, queues,\n",
      "Nearest to guys: 100ms, permutation, 20~22, 2002, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, can't, slowing, he'll,\n",
      "Nearest to i'm: norm, im, you're, nvidia, jealous, adventures, uhhhh, 15tb,\n",
      "\n",
      "\n",
      "Average loss at step  122000 :  4.14290672015 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  124000 :  4.16338189471 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), the, er;, laugh, andr, wanting, lite,\n",
      "Nearest to for: authorities, datacentres, custard, on), pushes, audit, replied, dialect,\n",
      "Nearest to very: monolith, pretty, seat, exposure, too, angularjs, hilarious, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, cyclists, stated, harp, addresses,\n",
      "Nearest to so: sword, exam, concur, simplify, park, maida, criticise, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, permission, unsafe,\n",
      "Nearest to i'll: rt, haskell, resource, scala, bacalhau, can, ill, fallen,\n",
      "Nearest to was: pursue, isn't, said, blankey, &@dscape, is, rightmove, anticipated,\n",
      "Nearest to same: worst, idiot, best, pencil, irssi, :pp, function(chunk, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, minerals, elections, ththrough, robomongo, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, chunk, initial, /await,\n",
      "Nearest to would: can, could, will, doesn't, should, don't, midori, won't,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, attraction, sr, queues,\n",
      "Nearest to guys: 100ms, permutation, 20~22, 2002, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, can't, slowing, he'll,\n",
      "Nearest to i'm: norm, im, you're, nvidia, jealous, adventures, uhhhh, 15tb,\n",
      "\n",
      "\n",
      "Average loss at step  126000 :  4.12142611486 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  128000 :  4.16421063312 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), the, er;, laugh, andr, wanting, lite,\n",
      "Nearest to for: authorities, datacentres, custard, on), audit, pushes, replied, dialect,\n",
      "Nearest to very: monolith, pretty, seat, exposure, too, angularjs, rt, hilarious,\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, cyclists, stated, harp, addresses,\n",
      "Nearest to so: sword, exam, concur, simplify, maida, criticise, park, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, permission, rt,\n",
      "Nearest to i'll: rt, haskell, resource, scala, bacalhau, ill, will, fallen,\n",
      "Nearest to was: pursue, isn't, said, blankey, &@dscape, is, rightmove, anticipated,\n",
      "Nearest to same: worst, idiot, best, pencil, irssi, :pp, function(chunk, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, minerals, elections, ththrough, robomongo, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, chunk, initial, /await,\n",
      "Nearest to would: can, could, will, doesn't, should, rt, don't, midori,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, attraction, sr, queues,\n",
      "Nearest to guys: 100ms, permutation, 20~22, 2002, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, didn't, reckon, should, can't, slowing, he'll,\n",
      "Nearest to i'm: norm, im, you're, nvidia, adventures, jealous, uhhhh, 15tb,\n",
      "\n",
      "\n",
      "Average loss at step  130000 :  4.12956771529 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  132000 :  4.11591145077 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), the, er;, laugh, andr, wanting, lite,\n",
      "Nearest to for: authorities, datacentres, custard, on), pushes, audit, dialect, replied,\n",
      "Nearest to very: monolith, pretty, seat, exposure, too, angularjs, hilarious, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, cyclists, stated, harp, addresses,\n",
      "Nearest to so: sword, exam, concur, simplify, criticise, maida, park, checksumming,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, permission, unsafe,\n",
      "Nearest to i'll: rt, haskell, resource, scala, bacalhau, ill, will, fallen,\n",
      "Nearest to was: pursue, isn't, said, blankey, &@dscape, rightmove, is, anticipated,\n",
      "Nearest to same: worst, idiot, best, pencil, irssi, :pp, function(chunk, pawned,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, comment, minerals, elections, ththrough, robomongo, pilau,\n",
      "Nearest to way: pot, prank, junior, 4g, favor, chunk, initial, /await,\n",
      "Nearest to would: can, will, could, doesn't, should, rt, don't, midori,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, attraction, needs, sr,\n",
      "Nearest to guys: 100ms, permutation, 20~22, 2002, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, didn't, reckon, should, can't, slowing, he'll,\n",
      "Nearest to i'm: norm, im, you're, nvidia, adventures, uhhhh, jealous, 15tb,\n",
      "\n",
      "\n",
      "Average loss at step  134000 :  4.14083850336 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  136000 :  4.09469933778 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), the, er;, laugh, andr, wanting, lite,\n",
      "Nearest to for: authorities, datacentres, custard, on), pushes, dialect, audit, replied,\n",
      "Nearest to very: monolith, pretty, seat, exposure, too, angularjs, hilarious, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, cyclists, stated, harp, addresses,\n",
      "Nearest to so: sword, exam, concur, simplify, criticise, maida, checksumming, park,\n",
      "Nearest to where: enable, fully, era, struggle, def, darren, permission, jazz,\n",
      "Nearest to i'll: rt, haskell, scala, resource, ill, bacalhau, will, fallen,\n",
      "Nearest to was: pursue, isn't, said, blankey, &@dscape, rightmove, is, anticipated,\n",
      "Nearest to same: worst, idiot, best, irssi, pencil, :pp, pawned, function(chunk,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, comment, elections, robomongo, ththrough, pilau,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, /await,\n",
      "Nearest to would: can, will, could, doesn't, should, rt, don't, midori,\n",
      "Nearest to has: have, agriculture, 1bl, means, perform, attraction, needs, sr,\n",
      "Nearest to guys: 100ms, permutation, 20~22, 2002, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, didn't, should, reckon, can't, slowing, he'll,\n",
      "Nearest to i'm: norm, im, you're, nvidia, adventures, uhhhh, jealous, 15tb,\n",
      "\n",
      "\n",
      "Average loss at step  138000 :  4.11550479762 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  140000 :  4.09991636884 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), er;, the, laugh, andr, lite, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, on), dialect, audit, pushes, replied,\n",
      "Nearest to very: monolith, pretty, seat, exposure, too, angularjs, hilarious, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, cyclists, harp, stated, addresses,\n",
      "Nearest to so: sword, exam, concur, simplify, criticise, maida, checksumming, park,\n",
      "Nearest to where: enable, fully, era, def, struggle, darren, permission, jazz,\n",
      "Nearest to i'll: rt, haskell, scala, resource, ill, bacalhau, will, fallen,\n",
      "Nearest to was: pursue, isn't, said, blankey, &@dscape, rightmove, is, anticipated,\n",
      "Nearest to same: worst, idiot, best, irssi, pencil, :pp, pawned, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, comment, elections, robomongo, ththrough, pilau,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, /await,\n",
      "Nearest to would: can, will, could, doesn't, should, don't, midori, rt,\n",
      "Nearest to has: have, 1bl, agriculture, means, perform, attraction, needs, sr,\n",
      "Nearest to guys: 100ms, permutation, 20~22, 2002, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, didn't, reckon, should, can't, he'll, slowing,\n",
      "Nearest to i'm: norm, im, you're, nvidia, adventures, uhhhh, --abbrev-commit, jealous,\n",
      "\n",
      "\n",
      "Average loss at step  142000 :  4.09755429823 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  144000 :  4.10204445565 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), er;, laugh, the, andr, lite, hintjens',\n",
      "Nearest to for: authorities, datacentres, custard, on), pushes, dialect, audit, cloudshell,\n",
      "Nearest to very: monolith, pretty, seat, exposure, too, angularjs, hilarious, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, cyclists, addresses, stated, harp,\n",
      "Nearest to so: sword, exam, concur, simplify, criticise, maida, checksumming, park,\n",
      "Nearest to where: enable, fully, era, def, struggle, darren, permission, jazz,\n",
      "Nearest to i'll: rt, haskell, scala, resource, ill, bacalhau, will, fallen,\n",
      "Nearest to was: pursue, isn't, said, blankey, &@dscape, rightmove, is, anticipated,\n",
      "Nearest to same: worst, idiot, best, irssi, pencil, :pp, pawned, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, comment, elections, robomongo, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, /await,\n",
      "Nearest to would: can, will, could, doesn't, should, don't, midori, won't,\n",
      "Nearest to has: have, agriculture, 1bl, perform, means, attraction, needs, sr,\n",
      "Nearest to guys: 100ms, 20~22, permutation, 2002, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, didn't, reckon, should, can't, he'll, slowing,\n",
      "Nearest to i'm: norm, im, you're, nvidia, adventures, uhhhh, thrown, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  146000 :  4.08336468542 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  148000 :  4.10818046379 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), er;, laugh, the, andr, lite, ctrl-chop-head-of-chicken-and-rage-quit,\n",
      "Nearest to for: authorities, datacentres, custard, on), pushes, audit, dialect, cloudshell,\n",
      "Nearest to very: monolith, pretty, seat, exposure, too, angularjs, hilarious, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, cyclists, addresses, harp, stated,\n",
      "Nearest to so: sword, exam, concur, simplify, criticise, maida, checksumming, park,\n",
      "Nearest to where: enable, fully, era, def, struggle, darren, permission, jazz,\n",
      "Nearest to i'll: haskell, scala, resource, rt, ill, bacalhau, fallen, will,\n",
      "Nearest to was: pursue, isn't, blankey, said, &@dscape, rightmove, is, anticipated,\n",
      "Nearest to same: worst, idiot, best, irssi, pencil, :pp, pawned, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, comment, elections, robomongo, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, /await,\n",
      "Nearest to would: can, could, will, doesn't, should, don't, won't, midori,\n",
      "Nearest to has: have, agriculture, 1bl, perform, means, needs, attraction, sr,\n",
      "Nearest to guys: 100ms, permutation, 20~22, 2002, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, didn't, reckon, should, can't, he'll, slowing,\n",
      "Nearest to i'm: norm, im, you're, nvidia, uhhhh, adventures, 15tb, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  150000 :  4.06595684761 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  152000 :  4.0942901523 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), er;, laugh, the, andr, lite, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, on), pushes, audit, dialect, cloudshell,\n",
      "Nearest to very: monolith, pretty, seat, exposure, too, angularjs, hilarious, rt,\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, cyclists, addresses, stated, harp,\n",
      "Nearest to so: sword, exam, simplify, concur, criticise, maida, checksumming, park,\n",
      "Nearest to where: enable, fully, def, struggle, era, darren, permission, jazz,\n",
      "Nearest to i'll: rt, haskell, scala, resource, ill, bacalhau, will, fallen,\n",
      "Nearest to was: pursue, isn't, said, blankey, &@dscape, rightmove, is, anticipated,\n",
      "Nearest to same: worst, idiot, best, irssi, pencil, pawned, :pp, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, comment, elections, robomongo, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, rt, should, don't, won't,\n",
      "Nearest to has: have, 1bl, agriculture, perform, means, needs, attraction, sr,\n",
      "Nearest to guys: 100ms, 20~22, 2002, permutation, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, didn't, reckon, should, can't, he'll, won't,\n",
      "Nearest to i'm: im, norm, you're, nvidia, uhhhh, adventures, they're, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  154000 :  4.07854570359 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  156000 :  4.05551365817 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), the, laugh, er;, lite, andr, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, on), pushes, dialect, audit, cloudshell,\n",
      "Nearest to very: monolith, pretty, seat, exposure, angularjs, too, hilarious, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, addresses, cyclists, stated, harp,\n",
      "Nearest to so: sword, exam, concur, simplify, criticise, checksumming, maida, park,\n",
      "Nearest to where: enable, fully, def, struggle, era, darren, permission, jazz,\n",
      "Nearest to i'll: rt, haskell, scala, ill, resource, bacalhau, will, -t,\n",
      "Nearest to was: pursue, isn't, blankey, said, &@dscape, rightmove, anticipated, is,\n",
      "Nearest to same: worst, idiot, best, irssi, pawned, pencil, :pp, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, comment, elections, robomongo, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, should, won't, midori, don't,\n",
      "Nearest to has: have, 1bl, agriculture, perform, means, needs, attraction, sr,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, didn't, reckon, should, can't, he'll, won't,\n",
      "Nearest to i'm: im, norm, you're, nvidia, uhhhh, adventures, they're, barbican,\n",
      "\n",
      "\n",
      "Average loss at step  158000 :  4.08832228756 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  160000 :  4.04763976103 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, andr, the, lite, ctrl-chop-head-of-chicken-and-rage-quit,\n",
      "Nearest to for: authorities, datacentres, custard, on), pushes, dialect, audit, cloudshell,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, hilarious, too, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, addresses, cyclists, stated, harp,\n",
      "Nearest to so: sword, exam, criticise, simplify, concur, checksumming, maida, stake,\n",
      "Nearest to where: enable, fully, def, era, struggle, darren, permission, jazz,\n",
      "Nearest to i'll: rt, scala, haskell, ill, resource, bacalhau, will, fallen,\n",
      "Nearest to was: pursue, isn't, blankey, &@dscape, said, rightmove, is, anticipated,\n",
      "Nearest to same: worst, idiot, best, irssi, pawned, pencil, :pp, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, elections, comment, robomongo, ththrough, pilau,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, should, won't, midori, don't,\n",
      "Nearest to has: have, 1bl, agriculture, perform, means, needs, attraction, sr,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, didn't, reckon, should, can't, he'll, won't,\n",
      "Nearest to i'm: im, norm, you're, nvidia, uhhhh, adventures, they're, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  162000 :  4.07490432837 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  164000 :  4.0455198344 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, andr, lite, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, on), dialect, audit, pushes, cloudshell,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, hilarious, too, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, cyclists, addresses, harp, stated,\n",
      "Nearest to so: sword, exam, simplify, criticise, concur, checksumming, maida, stake,\n",
      "Nearest to where: enable, fully, def, era, struggle, darren, permission, jazz,\n",
      "Nearest to i'll: rt, ill, scala, haskell, resource, bacalhau, will, fallen,\n",
      "Nearest to was: pursue, isn't, &@dscape, blankey, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, idiot, best, irssi, pawned, :pp, pencil, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, elections, comment, robomongo, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, should, won't, midori, don't,\n",
      "Nearest to has: have, 1bl, perform, agriculture, means, needs, attraction, sr,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, reckon, didn't, should, can't, he'll, won't,\n",
      "Nearest to i'm: im, norm, you're, nvidia, uhhhh, adventures, they're, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  166000 :  4.0634520525 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  168000 :  4.05563281667 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, lite, andr, ctrl-chop-head-of-chicken-and-rage-quit, the,\n",
      "Nearest to for: authorities, datacentres, custard, on), dialect, pushes, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, too, hilarious, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, addresses, cyclists, harp, discreet,\n",
      "Nearest to so: sword, exam, simplify, criticise, concur, checksumming, maida, stake,\n",
      "Nearest to where: enable, fully, def, era, struggle, darren, permission, jazz,\n",
      "Nearest to i'll: rt, ill, scala, haskell, resource, bacalhau, will, -t,\n",
      "Nearest to was: pursue, isn't, &@dscape, blankey, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, idiot, best, irssi, pawned, pencil, proj, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, comment, elections, robomongo, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, should, won't, midori, don't,\n",
      "Nearest to has: have, perform, 1bl, agriculture, means, needs, attraction, sr,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, rt, reckon, didn't, should, can't, he'll, won't,\n",
      "Nearest to i'm: im, norm, you're, nvidia, uhhhh, adventures, --abbrev-commit, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  170000 :  4.02266091678 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  172000 :  4.06502191269 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, lite, ctrl-chop-head-of-chicken-and-rage-quit, andr, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, on), dialect, pushes, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, hilarious, too, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, addresses, cyclists, discreet, harp,\n",
      "Nearest to so: sword, exam, simplify, criticise, checksumming, maida, concur, stake,\n",
      "Nearest to where: enable, fully, def, era, struggle, darren, permission, meant,\n",
      "Nearest to i'll: ill, scala, haskell, resource, bacalhau, rt, -t, will,\n",
      "Nearest to was: pursue, isn't, &@dscape, blankey, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, idiot, best, irssi, pawned, :pp, pencil, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, elections, comment, robomongo, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, could, will, doesn't, should, won't, midori, don't,\n",
      "Nearest to has: have, 1bl, perform, agriculture, needs, means, attraction, sr,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, nay, gifs, tottaly, pokemon,\n",
      "Nearest to don't: dont, reckon, didn't, should, can't, rt, won't, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, uhhhh, they're, adventures, barbican,\n",
      "\n",
      "\n",
      "Average loss at step  174000 :  4.02147361445 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  176000 :  4.0414761087 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, lite, ctrl-chop-head-of-chicken-and-rage-quit, the, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, on), pushes, dialect, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, too, hilarious, shortage),\n",
      "Nearest to then: burning, injury, pimp, simonspringett@ntlworldcom, addresses, cyclists, discreet, harp,\n",
      "Nearest to so: sword, exam, simplify, criticise, checksumming, maida, concur, stake,\n",
      "Nearest to where: enable, fully, def, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: ill, scala, haskell, resource, rt, bacalhau, will, -t,\n",
      "Nearest to was: pursue, &@dscape, isn't, blankey, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, idiot, best, pawned, irssi, :pp, proj, pencil,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, elections, robomongo, comment, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, should, won't, midori, don't,\n",
      "Nearest to has: have, perform, 1bl, agriculture, needs, means, attraction, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, nay, tottaly, gifs, pokemon,\n",
      "Nearest to don't: dont, reckon, didn't, rt, should, can't, won't, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, uhhhh, they're, adventures,\n",
      "\n",
      "\n",
      "Average loss at step  178000 :  4.03707607716 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  180000 :  4.00885062326 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, the, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, pushes, on), dialect, audit, cloudshell,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, too, hilarious, shortage),\n",
      "Nearest to then: burning, injury, addresses, pimp, simonspringett@ntlworldcom, cyclists, discreet, harp,\n",
      "Nearest to so: sword, exam, simplify, criticise, checksumming, maida, concur, stake,\n",
      "Nearest to where: enable, fully, def, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: rt, ill, scala, haskell, resource, bacalhau, will, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, idiot, best, pawned, irssi, :pp, pencil, venturebeat,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, should, won't, midori, rt,\n",
      "Nearest to has: have, perform, 1bl, needs, agriculture, means, attraction, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, nay, tottaly, gifs, descriptor,\n",
      "Nearest to don't: dont, rt, reckon, didn't, should, can't, won't, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, uhhhh, they're, barbican, adventures,\n",
      "\n",
      "\n",
      "Average loss at step  182000 :  4.0388066712 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  184000 :  4.00816494322 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig, uncap,\n",
      "Nearest to for: authorities, datacentres, custard, on), dialect, pushes, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, hilarious, too, shortage),\n",
      "Nearest to then: burning, injury, addresses, pimp, simonspringett@ntlworldcom, cyclists, harp, discreet,\n",
      "Nearest to so: sword, exam, simplify, criticise, checksumming, maida, concur, stake,\n",
      "Nearest to where: fully, enable, def, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: rt, ill, scala, haskell, resource, bacalhau, will, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, idiot, best, pawned, irssi, venturebeat, :pp, proj,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, should, won't, midori, rt,\n",
      "Nearest to has: have, needs, 1bl, perform, agriculture, means, attraction, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, rt, reckon, didn't, should, can't, won't, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, thrown, they're, uhhhh,\n",
      "\n",
      "\n",
      "Average loss at step  186000 :  4.03380116347 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  188000 :  4.00147774792 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig, uncap,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, audit, cloudshell,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, hilarious, too, shortage),\n",
      "Nearest to then: burning, injury, addresses, pimp, simonspringett@ntlworldcom, cyclists, harp, discreet,\n",
      "Nearest to so: sword, exam, simplify, checksumming, criticise, concur, maida, stake,\n",
      "Nearest to where: fully, enable, def, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: ill, rt, scala, haskell, resource, bacalhau, will, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, best, idiot, pawned, irssi, proj, venturebeat, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, should, won't, midori, *production,\n",
      "Nearest to has: have, 1bl, needs, perform, agriculture, means, attraction, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, rt, reckon, didn't, can't, should, won't, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, thrown, they're, uhhhh, barbican,\n",
      "\n",
      "\n",
      "Average loss at step  190000 :  4.037579898 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  192000 :  4.01380502242 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig, uncap,\n",
      "Nearest to for: authorities, datacentres, custard, on), dialect, pushes, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, hilarious, too, shortage),\n",
      "Nearest to then: burning, injury, addresses, pimp, cyclists, simonspringett@ntlworldcom, discreet, harp,\n",
      "Nearest to so: exam, sword, simplify, checksumming, criticise, maida, concur, stake,\n",
      "Nearest to where: enable, fully, def, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: ill, rt, scala, haskell, resource, bacalhau, will, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, best, pawned, idiot, irssi, proj, venturebeat, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, should, won't, midori, rt,\n",
      "Nearest to has: have, needs, 1bl, perform, agriculture, means, attraction, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, rt, reckon, didn't, can't, should, won't, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, they're, thrown, barbican, uhhhh,\n",
      "\n",
      "\n",
      "Average loss at step  194000 :  3.99349004284 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  196000 :  4.02674635327 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig, uncap,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, hilarious, too, shortage),\n",
      "Nearest to then: burning, injury, addresses, cyclists, pimp, simonspringett@ntlworldcom, discreet, harp,\n",
      "Nearest to so: exam, sword, simplify, checksumming, criticise, maida, concur, stake,\n",
      "Nearest to where: enable, fully, def, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: ill, rt, scala, haskell, resource, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, pawned, best, idiot, irssi, proj, venturebeat, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, ththrough, learnings,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, should, won't, midori, rt,\n",
      "Nearest to has: have, 1bl, needs, perform, agriculture, means, attraction, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, rt, reckon, didn't, can't, should, won't, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, thrown, they're, uhhhh,\n",
      "\n",
      "\n",
      "Average loss at step  198000 :  3.98262732375 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  200000 :  4.01359693896 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig, uncap,\n",
      "Nearest to for: authorities, datacentres, custard, on), dialect, pushes, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, hilarious, shortage), too,\n",
      "Nearest to then: burning, injury, addresses, pimp, cyclists, simonspringett@ntlworldcom, discreet, harp,\n",
      "Nearest to so: exam, sword, simplify, checksumming, criticise, maida, concur, stake,\n",
      "Nearest to where: enable, fully, def, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: ill, scala, rt, haskell, resource, bacalhau, will, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, pawned, best, idiot, irssi, proj, venturebeat, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, learnings, ththrough,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, won't, should, midori, *production,\n",
      "Nearest to has: have, 1bl, needs, perform, agriculture, means, attraction, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, reckon, rt, didn't, can't, won't, should, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, --abbrev-commit, thrown, they're,\n",
      "\n",
      "\n",
      "Average loss at step  202000 :  4.00390048444 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  204000 :  3.98202494822 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig, uncap,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, shortage), hilarious, too,\n",
      "Nearest to then: burning, injury, addresses, pimp, discreet, cyclists, simonspringett@ntlworldcom, harp,\n",
      "Nearest to so: exam, sword, simplify, criticise, checksumming, maida, concur, stake,\n",
      "Nearest to where: fully, enable, def, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: ill, scala, rt, haskell, resource, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, pawned, idiot, best, irssi, venturebeat, proj, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, learnings, ththrough,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, won't, should, midori, *production,\n",
      "Nearest to has: have, needs, 1bl, perform, agriculture, means, attraction, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, gifs, nay, descriptor,\n",
      "Nearest to don't: dont, reckon, didn't, rt, can't, won't, should, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, uhhhh, --abbrev-commit, they're,\n",
      "\n",
      "\n",
      "Average loss at step  206000 :  4.00263146716 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  208000 :  3.95605438574 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig, uncap,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, hilarious, shortage), too,\n",
      "Nearest to then: burning, injury, addresses, discreet, simonspringett@ntlworldcom, cyclists, pimp, harp,\n",
      "Nearest to so: exam, sword, simplify, criticise, checksumming, maida, concur, stake,\n",
      "Nearest to where: fully, enable, def, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: ill, scala, haskell, resource, rt, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, said, rightmove, anticipated, is,\n",
      "Nearest to same: worst, pawned, idiot, best, irssi, venturebeat, proj, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, learnings, ththrough,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, initial, saftey,\n",
      "Nearest to would: can, will, could, doesn't, won't, should, midori, *production,\n",
      "Nearest to has: have, needs, 1bl, perform, agriculture, means, attraction, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, reckon, didn't, can't, won't, should, rt, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, they're, thrown, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  210000 :  4.00468558872 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  212000 :  3.96869027877 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig, uncap,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, audit, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, seat, angularjs, hilarious, shortage), too,\n",
      "Nearest to then: burning, injury, addresses, discreet, pimp, cyclists, simonspringett@ntlworldcom, harp,\n",
      "Nearest to so: exam, sword, simplify, checksumming, criticise, maida, concur, stake,\n",
      "Nearest to where: fully, def, enable, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: ill, scala, haskell, resource, rt, bacalhau, will, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, anticipated, said, rightmove, is,\n",
      "Nearest to same: worst, pawned, best, idiot, irssi, venturebeat, proj, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, learnings, ththrough,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, saftey, initial,\n",
      "Nearest to would: can, will, could, doesn't, won't, should, midori, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, means, donutsthey'll, attraction,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, reckon, didn't, can't, won't, rt, should, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, thrown, --abbrev-commit, they're,\n",
      "\n",
      "\n",
      "Average loss at step  214000 :  4.00488539848 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  216000 :  3.97913061666 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, doppelganger, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, rt, angularjs, seat, hilarious, shortage),\n",
      "Nearest to then: burning, injury, addresses, discreet, cyclists, pimp, simonspringett@ntlworldcom, harp,\n",
      "Nearest to so: exam, sword, simplify, criticise, checksumming, maida, concur, stake,\n",
      "Nearest to where: fully, def, enable, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: ill, rt, scala, haskell, resource, bacalhau, will, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, said, anticipated, rightmove, is,\n",
      "Nearest to same: worst, pawned, best, idiot, irssi, venturebeat, proj, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, learnings, ththrough,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, saftey, initial,\n",
      "Nearest to would: can, will, could, rt, doesn't, won't, should, midori,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, means, attraction, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, rt, reckon, didn't, can't, won't, should, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, thrown, they're, barbican, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  218000 :  3.96054249631 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  220000 :  3.99495011532 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, doppelganger, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, pushes, on), cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, angularjs, seat, hilarious, rt, shortage),\n",
      "Nearest to then: burning, injury, addresses, discreet, cyclists, pimp, simonspringett@ntlworldcom, harp,\n",
      "Nearest to so: exam, sword, simplify, checksumming, criticise, maida, stake, concur,\n",
      "Nearest to where: fully, def, enable, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: ill, rt, scala, haskell, resource, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, anticipated, said, rightmove, is,\n",
      "Nearest to same: worst, pawned, idiot, best, irssi, venturebeat, proj, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, learnings, ththrough,\n",
      "Nearest to way: pot, prank, junior, favor, 4g, chunk, saftey, initial,\n",
      "Nearest to would: can, will, could, won't, doesn't, should, rt, midori,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, means, attraction, wants,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, rt, reckon, didn't, can't, won't, should, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, thrown, they're, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  222000 :  3.95109628654 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  224000 :  3.9816205535 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, angularjs, seat, hilarious, vba, shortage),\n",
      "Nearest to then: burning, injury, addresses, discreet, cyclists, pimp, simonspringett@ntlworldcom, right-to-left,\n",
      "Nearest to so: exam, sword, simplify, checksumming, criticise, maida, concur, stake,\n",
      "Nearest to where: def, fully, enable, struggle, era, darren, permission, meant,\n",
      "Nearest to i'll: ill, rt, scala, haskell, resource, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, isn't, anticipated, rightmove, said, is,\n",
      "Nearest to same: worst, pawned, best, idiot, irssi, venturebeat, proj, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, learnings, ththrough,\n",
      "Nearest to way: pot, junior, favor, prank, 4g, chunk, saftey, initial,\n",
      "Nearest to would: can, will, could, won't, doesn't, should, midori, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, means, donutsthey'll, wants,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, rt, reckon, didn't, can't, won't, should, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, --abbrev-commit, thrown, they're,\n",
      "\n",
      "\n",
      "Average loss at step  226000 :  3.96694529897 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  228000 :  3.94796040808 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, lite, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, angularjs, seat, hilarious, shortage), vba,\n",
      "Nearest to then: burning, injury, addresses, discreet, cyclists, pimp, simonspringett@ntlworldcom, right-to-left,\n",
      "Nearest to so: exam, sword, simplify, criticise, checksumming, maida, concur, stake,\n",
      "Nearest to where: def, fully, enable, struggle, era, darren, meant, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, resource, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, isn't, said, rightmove, is,\n",
      "Nearest to same: worst, pawned, best, idiot, irssi, venturebeat, proj, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, comment, learnings, ththrough,\n",
      "Nearest to way: pot, junior, prank, favor, 4g, chunk, saftey, initial,\n",
      "Nearest to would: can, will, could, won't, doesn't, should, midori, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, wants, means, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, reckon, rt, didn't, can't, won't, should, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, they're, thrown, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  230000 :  3.9731054188 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  232000 :  3.94116405214 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, angularjs, seat, hilarious, vba, shortage),\n",
      "Nearest to then: burning, injury, addresses, discreet, cyclists, simonspringett@ntlworldcom, pimp, right-to-left,\n",
      "Nearest to so: exam, sword, simplify, checksumming, criticise, maida, concur, stake,\n",
      "Nearest to where: def, fully, enable, struggle, era, darren, meant, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, resource, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, isn't, said, rightmove, is,\n",
      "Nearest to same: worst, pawned, best, idiot, irssi, venturebeat, proj, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, learnings, comment, ththrough,\n",
      "Nearest to way: pot, junior, prank, favor, 4g, chunk, saftey, initial,\n",
      "Nearest to would: can, will, could, won't, doesn't, should, midori, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, means, wants, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, reckon, didn't, rt, won't, can't, should, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, they're, thrown, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  234000 :  3.97699258184 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  236000 :  3.93578546196 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, spiderpig, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, audit, cloudshell,\n",
      "Nearest to very: pretty, monolith, exposure, angularjs, seat, hilarious, vba, discontinuity,\n",
      "Nearest to then: burning, injury, addresses, discreet, cyclists, simonspringett@ntlworldcom, pimp, harp,\n",
      "Nearest to so: exam, sword, simplify, criticise, checksumming, maida, concur, stake,\n",
      "Nearest to where: def, fully, enable, struggle, era, darren, meant, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, resource, bacalhau, will, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, isn't, rightmove, said, is,\n",
      "Nearest to same: worst, pawned, best, idiot, irssi, proj, venturebeat, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, learnings, comment, ththrough,\n",
      "Nearest to way: pot, junior, favor, prank, 4g, chunk, saftey, initial,\n",
      "Nearest to would: will, can, could, won't, doesn't, should, midori, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, wants, means, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, gifs, descriptor,\n",
      "Nearest to don't: dont, reckon, didn't, rt, won't, can't, should, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, thrown, they're, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  238000 :  3.96893555029 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  240000 :  3.95295016682 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, lite, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, angularjs, seat, hilarious, vba, discontinuity,\n",
      "Nearest to then: burning, injury, addresses, discreet, cyclists, simonspringett@ntlworldcom, right-to-left, pimp,\n",
      "Nearest to so: exam, sword, simplify, criticise, maida, checksumming, stake, concur,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, resource, bacalhau, will, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, isn't, rightmove, said, is,\n",
      "Nearest to same: worst, pawned, best, idiot, irssi, proj, venturebeat, :pp,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, learnings, comment, ththrough,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, saftey, initial,\n",
      "Nearest to would: will, can, could, won't, should, doesn't, midori, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, means, wants, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, descriptor, gifs,\n",
      "Nearest to don't: dont, reckon, didn't, won't, rt, can't, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, thrown, barbican, --abbrev-commit, they're,\n",
      "\n",
      "\n",
      "Average loss at step  242000 :  3.93901401452 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  244000 :  3.96605095673 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, lite, doppelganger, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, angularjs, rt, seat, vba, discontinuity,\n",
      "Nearest to then: burning, addresses, injury, discreet, cyclists, simonspringett@ntlworldcom, right-to-left, harp,\n",
      "Nearest to so: exam, sword, simplify, maida, criticise, checksumming, stake, concur,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, permission, darren,\n",
      "Nearest to i'll: ill, rt, scala, haskell, resource, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, isn't, rightmove, said, is,\n",
      "Nearest to same: worst, pawned, idiot, best, irssi, venturebeat, proj, visibly,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, learnings, comment, ththrough,\n",
      "Nearest to way: pot, junior, prank, favor, 4g, chunk, saftey, initial,\n",
      "Nearest to would: can, will, could, won't, should, midori, doesn't, rt,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, wants, had, means,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, descriptor, gifs,\n",
      "Nearest to don't: dont, reckon, rt, didn't, can't, won't, should, he'll,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, thrown, they're, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  246000 :  3.92163406968 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  248000 :  3.9486722919 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, lite, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, angularjs, seat, vba, discontinuity, hilarious,\n",
      "Nearest to then: burning, injury, addresses, discreet, cyclists, right-to-left, harp, simonspringett@ntlworldcom,\n",
      "Nearest to so: exam, sword, simplify, maida, criticise, checksumming, stake, disappointed,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, darren, permission,\n",
      "Nearest to i'll: ill, rt, scala, haskell, resource, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, isn't, rightmove, said, is,\n",
      "Nearest to same: worst, pawned, best, idiot, irssi, proj, venturebeat, visibly,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, learnings, comment, ththrough,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, saftey, /await,\n",
      "Nearest to would: can, will, could, won't, should, midori, doesn't, *production,\n",
      "Nearest to has: have, perform, needs, 1bl, agriculture, wants, had, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, descriptor, gifs,\n",
      "Nearest to don't: dont, reckon, rt, didn't, won't, can't, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, they're, --abbrev-commit, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  250000 :  3.93759115273 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  252000 :  3.93883729601 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, lite, spiderpig, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, angularjs, seat, vba, super, hilarious,\n",
      "Nearest to then: burning, addresses, injury, discreet, cyclists, right-to-left, simonspringett@ntlworldcom, harp,\n",
      "Nearest to so: exam, sword, simplify, maida, criticise, checksumming, stake, concur,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, permission, darren,\n",
      "Nearest to i'll: ill, scala, rt, haskell, resource, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, isn't, said, average,\n",
      "Nearest to same: worst, pawned, best, irssi, idiot, venturebeat, proj, visibly,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, learnings, comment, pilau,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, saftey, initial,\n",
      "Nearest to would: can, will, could, won't, should, midori, doesn't, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, wants, had, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, descriptor, gifs,\n",
      "Nearest to don't: dont, reckon, rt, didn't, won't, can't, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, they're, --abbrev-commit, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  254000 :  3.94409258854 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  256000 :  3.91296033674 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, angularjs, vba, super, seat, rt,\n",
      "Nearest to then: burning, addresses, injury, discreet, cyclists, right-to-left, simonspringett@ntlworldcom, harp,\n",
      "Nearest to so: exam, sword, simplify, criticise, maida, checksumming, stake, concur,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, rt, haskell, resource, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, said, isn't, is,\n",
      "Nearest to same: worst, pawned, idiot, irssi, best, venturebeat, proj, visibly,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, learnings, pilau, comment,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, saftey, initial,\n",
      "Nearest to would: can, will, won't, could, should, midori, doesn't, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, wants, donutsthey'll, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, descriptor, recruit,\n",
      "Nearest to don't: dont, reckon, didn't, won't, rt, can't, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, they're, thrown, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  258000 :  3.95268396187 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  260000 :  3.91116831976 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, lite, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, pushes, on), audit, cloudshell,\n",
      "Nearest to very: pretty, monolith, exposure, super, angularjs, vba, discontinuity, seat,\n",
      "Nearest to then: burning, addresses, injury, discreet, cyclists, right-to-left, harp, simonspringett@ntlworldcom,\n",
      "Nearest to so: exam, sword, simplify, criticise, maida, checksumming, stake, concur,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, rt, haskell, resource, bacalhau, -t, will,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, said, isn't, average,\n",
      "Nearest to same: worst, pawned, best, irssi, idiot, venturebeat, proj, visibly,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, learnings, pilau, ththrough,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, saftey, fusion,\n",
      "Nearest to would: will, can, won't, could, should, midori, doesn't, wouldn't,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, wants, donutsthey'll, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, descriptor, recruit,\n",
      "Nearest to don't: dont, reckon, rt, won't, didn't, can't, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, thrown, --abbrev-commit, they're,\n",
      "\n",
      "\n",
      "Average loss at step  262000 :  3.93547050278 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  264000 :  3.92599414301 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, lite, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, angularjs, vba, discontinuity, seat,\n",
      "Nearest to then: burning, addresses, injury, discreet, cyclists, right-to-left, harp, simonspringett@ntlworldcom,\n",
      "Nearest to so: exam, sword, simplify, criticise, maida, checksumming, stake, disappointed,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, resource, bacalhau, will, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, said, isn't, average,\n",
      "Nearest to same: worst, pawned, best, irssi, idiot, venturebeat, proj, visibly,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, learnings, ththrough, pilau,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, saftey, fusion,\n",
      "Nearest to would: can, will, won't, could, should, midori, doesn't, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, agriculture, wants, had, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, descriptor, recruit,\n",
      "Nearest to don't: dont, reckon, didn't, won't, rt, can't, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, thrown, they're, barbican, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  266000 :  3.89778653836 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  268000 :  3.94250802881 \n",
      "\n",
      "\n",
      "Nearest to your: my, license), laugh, er;, lite, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, angularjs, vba, discontinuity, seat,\n",
      "Nearest to then: burning, addresses, injury, discreet, cyclists, right-to-left, harp, simonspringett@ntlworldcom,\n",
      "Nearest to so: exam, sword, simplify, criticise, maida, checksumming, stake, disappointed,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, resource, bacalhau, rt, -t, we'll,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, isn't, said, is,\n",
      "Nearest to same: worst, pawned, best, irssi, idiot, venturebeat, proj, visibly,\n",
      "Nearest to how: initd, :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, minerals, robomongo, elections, learnings, ththrough, pilau,\n",
      "Nearest to way: pot, junior, prank, favor, chunk, 4g, saftey, fusion,\n",
      "Nearest to would: can, will, won't, could, should, midori, doesn't, wouldn't,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, agriculture, had, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, nay, descriptor, panic,\n",
      "Nearest to don't: dont, reckon, didn't, won't, can't, he'll, rt, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, thrown, they're, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  270000 :  3.89657652724 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  272000 :  3.94605072904 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, lite, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, quarry,\n",
      "Nearest to very: pretty, monolith, exposure, super, angularjs, vba, discontinuity, seat,\n",
      "Nearest to then: burning, addresses, injury, discreet, cyclists, right-to-left, harp, simonspringett@ntlworldcom,\n",
      "Nearest to so: exam, sword, simplify, maida, criticise, checksumming, disappointed, stake,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, resource, bacalhau, -t, we'll,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, isn't, said, average,\n",
      "Nearest to same: worst, pawned, irssi, best, idiot, proj, venturebeat, visibly,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, elections, learnings, pilau, ththrough,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, saftey, use*,\n",
      "Nearest to would: can, will, won't, could, should, midori, doesn't, wouldn't,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, agriculture, had, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, descriptor, nay, panic,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, --abbrev-commit, they're, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  274000 :  3.91269724691 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  276000 :  3.90101054082 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, spiderpig, ctrl-chop-head-of-chicken-and-rage-quit, lite, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, pushes, on), cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, angularjs, discontinuity, vba, seat,\n",
      "Nearest to then: burning, addresses, injury, discreet, cyclists, right-to-left, harp, simonspringett@ntlworldcom,\n",
      "Nearest to so: exam, sword, simplify, criticise, maida, checksumming, stake, disappointed,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, resource, rt, bacalhau, -t, we'll,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, isn't, said, average,\n",
      "Nearest to same: worst, pawned, irssi, best, idiot, venturebeat, proj, visibly,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, elections, learnings, pilau, ththrough,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, saftey, use*,\n",
      "Nearest to would: will, can, won't, could, should, midori, doesn't, wouldn't,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, agriculture, donutsthey'll, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, descriptor, panic, buuuurn,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, rt, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, they're, youre, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  278000 :  3.92093862909 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  280000 :  3.89264701702 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, spiderpig, doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, lite,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, angularjs, vba, discontinuity, seat,\n",
      "Nearest to then: burning, addresses, injury, discreet, cyclists, right-to-left, harp, simonspringett@ntlworldcom,\n",
      "Nearest to so: exam, sword, simplify, maida, criticise, checksumming, disappointed, stake,\n",
      "Nearest to where: def, fully, enable, era, struggle, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, rt, haskell, resource, bacalhau, we'll, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, said, isn't, average,\n",
      "Nearest to same: worst, pawned, irssi, best, idiot, venturebeat, proj, visibly,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, elections, learnings, pilau, abortion,\n",
      "Nearest to way: pot, junior, prank, favor, chunk, 4g, use*, saftey,\n",
      "Nearest to would: can, will, won't, could, should, midori, doesn't, wouldn't,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, agriculture, donutsthey'll, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, descriptor, panic, buuuurn,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, youre, they're, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  282000 :  3.92857906371 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  284000 :  3.88584715128 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, spiderpig, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, lite,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, angularjs, vba, seat,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, harp, coopers,\n",
      "Nearest to so: exam, sword, simplify, criticise, maida, checksumming, disappointed, stake,\n",
      "Nearest to where: def, fully, enable, era, struggle, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, rt, haskell, resource, bacalhau, we'll, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, isn't, said, average,\n",
      "Nearest to same: worst, pawned, irssi, best, idiot, venturebeat, proj, visibly,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, elections, learnings, pa, pilau,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, use*, saftey,\n",
      "Nearest to would: will, can, won't, could, should, midori, doesn't, wouldn't,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, agriculture, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, descriptor, panic, buuuurn,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, youre, thrown, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  286000 :  3.91195108803 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  288000 :  3.90404533452 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, doppelganger, spiderpig, ctrl-chop-head-of-chicken-and-rage-quit, lite,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, vba, discontinuity, angularjs, seat,\n",
      "Nearest to then: burning, addresses, injury, discreet, cyclists, right-to-left, harp, coopers,\n",
      "Nearest to so: exam, sword, simplify, maida, criticise, checksumming, stake, disappointed,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, resource, rt, bacalhau, we'll, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, isn't, said, average,\n",
      "Nearest to same: worst, pawned, best, irssi, idiot, proj, venturebeat, visibly,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, elections, learnings, pilau, abortion,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, use*, saftey,\n",
      "Nearest to would: will, can, won't, could, should, midori, doesn't, wouldn't,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, agriculture, had, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, descriptor, panic, recruit,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, rt, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, they're, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  290000 :  3.88396418871 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  292000 :  3.92019694602 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, doppelganger, lite, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, pushes, cloudshell, on), alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, vba, discontinuity, angularjs, seat,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, harp, coopers,\n",
      "Nearest to so: exam, simplify, sword, criticise, maida, checksumming, stake, disappointed,\n",
      "Nearest to where: def, fully, enable, era, struggle, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, resource, rt, bacalhau, we'll, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, isn't, said, average,\n",
      "Nearest to same: worst, pawned, irssi, best, idiot, proj, venturebeat, visibly,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, elections, learnings, pa, ththrough,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, use*, saftey,\n",
      "Nearest to would: will, can, won't, could, should, midori, doesn't, wouldn't,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, agriculture, had, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, descriptor, buuuurn,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, rt, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, youre, they're, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  294000 :  3.87551894754 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  296000 :  3.89915909083 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig, lite,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, seat,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, harp, coopers,\n",
      "Nearest to so: exam, simplify, sword, maida, criticise, checksumming, disappointed, stake,\n",
      "Nearest to where: def, fully, enable, struggle, era, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, resource, bacalhau, we'll, rt, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, isn't, said, average,\n",
      "Nearest to same: worst, pawned, irssi, best, idiot, visibly, proj, venturebeat,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, elections, learnings, pa, abortion,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, use*, saftey,\n",
      "Nearest to would: will, can, won't, could, should, midori, wouldn't, doesn't,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, had, agriculture,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, descriptor, buuuurn,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, rt, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, they're, youre, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  298000 :  3.88732713622 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  300000 :  3.90909210569 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, pushes, on), cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, seat,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, harp, coopers,\n",
      "Nearest to so: exam, simplify, sword, criticise, maida, checksumming, disappointed, stake,\n",
      "Nearest to where: def, fully, struggle, era, enable, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, resource, we'll, bacalhau, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, isn't, said, average,\n",
      "Nearest to same: worst, pawned, irssi, visibly, best, idiot, venturebeat, proj,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, elections, learnings, pilau, pa,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, use*, saftey,\n",
      "Nearest to would: will, can, won't, could, midori, should, wouldn't, doesn't,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, had, agriculture,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, descriptor, buuuurn,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, they're, youre, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  302000 :  3.89612852645 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  304000 :  3.87574259274 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite, doppelganger,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, pushes, on), cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, seat,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, harp, coopers,\n",
      "Nearest to so: exam, simplify, sword, maida, criticise, checksumming, disappointed, stake,\n",
      "Nearest to where: def, era, struggle, fully, enable, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, resource, we'll, bacalhau, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, said, isn't, average,\n",
      "Nearest to same: worst, pawned, irssi, best, visibly, idiot, venturebeat, proj,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, learnings, elections, pa, pilau,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, use*, saftey,\n",
      "Nearest to would: will, can, won't, could, should, midori, wouldn't, doesn't,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, had, finished),\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, descriptor, recruit,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, they're, barbican, speculative,\n",
      "\n",
      "\n",
      "Average loss at step  306000 :  3.90884899205 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  308000 :  3.86618660182 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, doppelganger, lite,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, pushes, on), cloudshell, audit,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, seat,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, harp, coopers,\n",
      "Nearest to so: exam, simplify, sword, maida, criticise, checksumming, disappointed, stake,\n",
      "Nearest to where: def, struggle, era, fully, enable, meant, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, resource, we'll, bacalhau, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, said, average, isn't,\n",
      "Nearest to same: worst, pawned, irssi, visibly, best, venturebeat, proj, idiot,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, elections, learnings, pa, pilau,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, use*, saftey,\n",
      "Nearest to would: will, won't, can, could, midori, should, wouldn't, doesn't,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, had, finished),\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, descriptor, recruit,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, thrown, they're,\n",
      "\n",
      "\n",
      "Average loss at step  310000 :  3.90932623676 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  312000 :  3.88287237847 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, seat,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, coopers, harp,\n",
      "Nearest to so: exam, simplify, sword, maida, criticise, checksumming, disappointed, stake,\n",
      "Nearest to where: def, era, struggle, fully, meant, enable, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, resource, we'll, bacalhau, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, said, isn't,\n",
      "Nearest to same: worst, pawned, irssi, visibly, best, proj, venturebeat, idiot,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, learnings, elections, pa, pilau,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, 4g, use*, saftey,\n",
      "Nearest to would: will, won't, can, could, midori, should, wouldn't, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, had, agriculture,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, descriptor, recruit,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, they're, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  314000 :  3.87055973387 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  316000 :  3.89569353396 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig, lite,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, pushes, on), cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, seat,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, coopers, harp,\n",
      "Nearest to so: exam, simplify, criticise, maida, sword, checksumming, disappointed, stake,\n",
      "Nearest to where: def, era, struggle, meant, enable, fully, darren, permission,\n",
      "Nearest to i'll: ill, scala, rt, haskell, resource, we'll, bacalhau, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, isn't, said,\n",
      "Nearest to same: worst, pawned, irssi, visibly, proj, venturebeat, best, idiot,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, learnings, elections, pa, lag,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, use*, 4g, saftey,\n",
      "Nearest to would: will, can, won't, could, midori, should, wouldn't, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, had, agriculture,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, descriptor, recruit,\n",
      "Nearest to don't: dont, reckon, won't, didn't, rt, can't, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, they're, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  318000 :  3.86028462809 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  320000 :  3.88797318168 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, rt,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, coopers, harp,\n",
      "Nearest to so: exam, simplify, maida, sword, criticise, checksumming, disappointed, stake,\n",
      "Nearest to where: def, struggle, era, meant, enable, fully, darren, permission,\n",
      "Nearest to i'll: ill, scala, rt, haskell, we'll, resource, bacalhau, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, said, isn't,\n",
      "Nearest to same: worst, pawned, irssi, visibly, proj, venturebeat, best, idiot,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, learnings, elections, pa, lag,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, use*, 4g, saftey,\n",
      "Nearest to would: will, can, won't, could, should, midori, wouldn't, rt,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, had, agriculture,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, descriptor, buuuurn,\n",
      "Nearest to don't: dont, reckon, rt, won't, didn't, can't, he'll, should,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, youre, they're, speculative,\n",
      "\n",
      "\n",
      "Average loss at step  322000 :  3.8587743566 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  324000 :  3.89469866519 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, pushes, cloudshell, on), alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, seat,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, coopers, harp,\n",
      "Nearest to so: exam, simplify, maida, sword, criticise, checksumming, disappointed, stake,\n",
      "Nearest to where: def, struggle, meant, era, enable, fully, darren, permission,\n",
      "Nearest to i'll: ill, scala, rt, haskell, we'll, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, said, csysdig,\n",
      "Nearest to same: worst, pawned, irssi, visibly, proj, venturebeat, best, hoekapplydefaults(config,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, learnings, pa, pilau, elections,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, use*, 4g, saftey,\n",
      "Nearest to would: will, won't, can, could, midori, should, wouldn't, rt,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, had, finished),\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, descriptor, buuuurn,\n",
      "Nearest to don't: dont, reckon, won't, rt, didn't, can't, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, barbican, youre, they're, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  326000 :  3.87335820705 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  328000 :  3.84803798563 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, on), cloudshell, pushes, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, location-service,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, coopers, harp,\n",
      "Nearest to so: exam, simplify, maida, sword, criticise, checksumming, disappointed, tennis,\n",
      "Nearest to where: def, struggle, era, meant, fully, enable, darren, permission,\n",
      "Nearest to i'll: ill, scala, rt, haskell, we'll, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, said, average, csysdig,\n",
      "Nearest to same: pawned, worst, irssi, visibly, hoekapplydefaults(config, proj, best, venturebeat,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, learnings, pa, pilau, elections,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, use*, 4g, saftey,\n",
      "Nearest to would: will, won't, can, should, midori, could, wouldn't, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, finished), had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, descriptor, buuuurn,\n",
      "Nearest to don't: dont, reckon, rt, won't, didn't, can't, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, they're, barbican, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  330000 :  3.89057984579 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  332000 :  3.84533194888 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, pushes, on), cloudshell, spread,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, location-service,\n",
      "Nearest to then: addresses, burning, discreet, injury, cyclists, right-to-left, coopers, harp,\n",
      "Nearest to so: exam, simplify, maida, criticise, sword, checksumming, disappointed, stake,\n",
      "Nearest to where: def, struggle, era, meant, fully, enable, darren, permission,\n",
      "Nearest to i'll: ill, scala, rt, haskell, we'll, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, said,\n",
      "Nearest to same: pawned, worst, irssi, visibly, proj, venturebeat, hoekapplydefaults(config, best,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, learnings, pa, lag, elections,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, use*, 4g, saftey,\n",
      "Nearest to would: will, won't, can, should, midori, could, wouldn't, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, finished), donutsthey'll, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, rt, won't, didn't, can't, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, thrown, they're,\n",
      "\n",
      "\n",
      "Average loss at step  334000 :  3.8723968878 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  336000 :  3.86810160238 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, on), pushes, cloudshell, alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, location-service,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, coopers, strip;,\n",
      "Nearest to so: exam, simplify, maida, criticise, sword, checksumming, disappointed, stake,\n",
      "Nearest to where: def, struggle, era, meant, enable, fully, darren, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, we'll, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, said,\n",
      "Nearest to same: pawned, worst, irssi, visibly, proj, best, hoekapplydefaults(config, venturebeat,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, learnings, pa, lag, elections,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, use*, 4g, saftey,\n",
      "Nearest to would: won't, will, can, midori, could, should, wouldn't, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, finished), donutsthey'll, had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, they're, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  338000 :  3.85081793823 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  340000 :  3.87379814684 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, pushes, cloudshell, on), alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, location-service,\n",
      "Nearest to then: burning, addresses, discreet, injury, cyclists, right-to-left, coopers, strip;,\n",
      "Nearest to so: exam, simplify, maida, criticise, sword, checksumming, disappointed, stake,\n",
      "Nearest to where: def, struggle, meant, era, enable, darren, fully, permission,\n",
      "Nearest to i'll: ill, scala, haskell, rt, we'll, resource, bacalhau, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, said,\n",
      "Nearest to same: pawned, worst, visibly, irssi, venturebeat, proj, hoekapplydefaults(config, best,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, pa, learnings, lag, elections,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, use*, 4g, fusion,\n",
      "Nearest to would: will, won't, can, midori, should, could, wouldn't, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, finished), had,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, they're, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  342000 :  3.83045902858 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  344000 :  3.8701894072 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, cloudshell, pushes, on), spread,\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, angularjs, location-service,\n",
      "Nearest to then: addresses, burning, discreet, injury, cyclists, right-to-left, coopers, harp,\n",
      "Nearest to so: exam, simplify, maida, criticise, sword, checksumming, disappointed, stake,\n",
      "Nearest to where: def, struggle, meant, era, darren, enable, fully, permission,\n",
      "Nearest to i'll: ill, scala, haskell, we'll, rt, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, said,\n",
      "Nearest to same: pawned, worst, visibly, irssi, proj, hoekapplydefaults(config, venturebeat, best,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, learnings, pa, elections, <marquee><blink>:eyes:</blink></marquee>,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, use*, 4g, fusion,\n",
      "Nearest to would: won't, will, can, could, should, midori, wouldn't, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, finished), $16843,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, rt, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, they're, speculative,\n",
      "\n",
      "\n",
      "Average loss at step  346000 :  3.83929797465 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  348000 :  3.86118959289 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, doppelganger, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, cloudshell, pushes, on), alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, angularjs, location-service,\n",
      "Nearest to then: addresses, burning, discreet, injury, cyclists, right-to-left, coopers, harp,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, sword, checksumming, stake,\n",
      "Nearest to where: def, meant, struggle, era, darren, fully, enable, flew,\n",
      "Nearest to i'll: ill, scala, haskell, we'll, rt, resource, bacalhau, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, said,\n",
      "Nearest to same: pawned, worst, visibly, irssi, hoekapplydefaults(config, proj, venturebeat, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, learnings, <marquee><blink>:eyes:</blink></marquee>, webp, pa,\n",
      "Nearest to way: pot, junior, favor, prank, chunk, use*, 4g, fusion,\n",
      "Nearest to would: won't, will, can, should, wouldn't, could, midori, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, donutsthey'll, finished), $16843,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, rt, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, speculative, they're,\n",
      "\n",
      "\n",
      "Average loss at step  350000 :  3.85484705085 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  352000 :  3.83358655885 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, dialect, custard, pushes, cloudshell, on), alarms,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, location-service, angularjs,\n",
      "Nearest to then: addresses, burning, discreet, injury, cyclists, right-to-left, coopers, harp,\n",
      "Nearest to so: exam, simplify, maida, sword, criticise, checksumming, disappointed, stake,\n",
      "Nearest to where: def, struggle, meant, era, darren, fully, enable, permission,\n",
      "Nearest to i'll: ill, scala, rt, haskell, we'll, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, said,\n",
      "Nearest to same: pawned, worst, visibly, irssi, hoekapplydefaults(config, proj, venturebeat, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, learnings, <marquee><blink>:eyes:</blink></marquee>, pilau, webp,\n",
      "Nearest to way: pot, junior, favor, prank, use*, chunk, 4g, fusion,\n",
      "Nearest to would: won't, will, can, should, wouldn't, midori, could, *production,\n",
      "Nearest to has: needs, have, perform, wants, 1bl, finished), donutsthey'll, $16843,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, they're, thrown,\n",
      "\n",
      "\n",
      "Average loss at step  354000 :  3.87188392413 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  356000 :  3.82742276722 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, pushes, cloudshell, on), audit,\n",
      "Nearest to very: pretty, monolith, exposure, super, discontinuity, vba, location-service, angularjs,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, cyclists, injury, coopers, harp,\n",
      "Nearest to so: exam, simplify, maida, criticise, sword, checksumming, disappointed, stake,\n",
      "Nearest to where: def, struggle, meant, era, darren, flew, permission, fully,\n",
      "Nearest to i'll: ill, scala, rt, haskell, we'll, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, said,\n",
      "Nearest to same: pawned, worst, visibly, irssi, hoekapplydefaults(config, proj, venturebeat, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, <marquee><blink>:eyes:</blink></marquee>, pa, lag, learnings,\n",
      "Nearest to way: pot, junior, favor, prank, use*, chunk, 4g, fusion,\n",
      "Nearest to would: will, won't, can, should, midori, wouldn't, could, *production,\n",
      "Nearest to has: needs, have, perform, 1bl, wants, finished), donutsthey'll, $16843,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, they're, speculative,\n",
      "\n",
      "\n",
      "Average loss at step  358000 :  3.86471633067 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  360000 :  3.84657500648 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, er;, license), doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, uncap,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, cloudshell, pushes, on), alarms,\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, location-service, angularjs,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, injury, cyclists, coopers, strip;,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, sword, checksumming, launched:,\n",
      "Nearest to where: def, struggle, meant, era, darren, flew, permission, enable,\n",
      "Nearest to i'll: ill, rt, scala, haskell, we'll, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, isn't,\n",
      "Nearest to same: pawned, worst, visibly, irssi, hoekapplydefaults(config, proj, venturebeat, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, webp, learnings, <marquee><blink>:eyes:</blink></marquee>, lag,\n",
      "Nearest to way: pot, junior, favor, prank, use*, chunk, 4g, fusion,\n",
      "Nearest to would: won't, will, can, midori, should, wouldn't, could, *production,\n",
      "Nearest to has: needs, have, perform, 1bl, wants, finished), donutsthey'll, $16843,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, tottaly, panic, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, won't, rt, didn't, can't, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, thrown, they're,\n",
      "\n",
      "\n",
      "Average loss at step  362000 :  3.83221714577 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  364000 :  3.85589763904 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, cloudshell, pushes, on), alarms,\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, angularjs, location-service,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, coopers, injury, cyclists, strip;,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, checksumming, sword, stake,\n",
      "Nearest to where: def, struggle, meant, era, darren, flew, permission, enable,\n",
      "Nearest to i'll: ill, rt, scala, haskell, we'll, resource, bacalhau, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, is,\n",
      "Nearest to same: pawned, worst, visibly, irssi, hoekapplydefaults(config, proj, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:, venturebeat,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, robomongo, minerals, lag, webp, learnings, pa,\n",
      "Nearest to way: pot, junior, favor, prank, use*, chunk, 4g, fusion,\n",
      "Nearest to would: won't, will, can, midori, should, wouldn't, could, *production,\n",
      "Nearest to has: have, needs, perform, 1bl, wants, finished), $16843, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, panic, tottaly, buuuurn, recruit,\n",
      "Nearest to don't: dont, reckon, won't, didn't, rt, can't, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, they're, speculative,\n",
      "\n",
      "\n",
      "Average loss at step  366000 :  3.82010467503 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  368000 :  3.86031310213 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, er;, license), doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, cloudshell, on), pushes, alarms,\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, angularjs, location-service,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, cyclists, coopers, injury, strip;,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, checksumming, launched:, sword,\n",
      "Nearest to where: def, meant, struggle, era, darren, flew, permission, enable,\n",
      "Nearest to i'll: ill, scala, rt, haskell, we'll, resource, bacalhau, -t,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, is,\n",
      "Nearest to same: pawned, worst, visibly, irssi, hoekapplydefaults(config, proj, venturebeat, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, lag, pa, <marquee><blink>:eyes:</blink></marquee>, learnings,\n",
      "Nearest to way: pot, junior, favor, prank, use*, chunk, 4g, fusion,\n",
      "Nearest to would: won't, can, will, wouldn't, should, midori, could, *production,\n",
      "Nearest to has: have, needs, perform, wants, 1bl, finished), donutsthey'll, $16843,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, panic, tottaly, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, speculative, they're,\n",
      "\n",
      "\n",
      "Average loss at step  370000 :  3.8197380262 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  372000 :  3.84557674189 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, cloudshell, pushes, alarms, on),\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, location-service, really,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, cyclists, injury, coopers, strip;,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, checksumming, sword, stake,\n",
      "Nearest to where: def, meant, struggle, darren, era, permission, flew, enable,\n",
      "Nearest to i'll: ill, scala, haskell, we'll, rt, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, isn't,\n",
      "Nearest to same: pawned, worst, visibly, irssi, hoekapplydefaults(config, proj, venturebeat, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, webp, <marquee><blink>:eyes:</blink></marquee>, learnings, pa,\n",
      "Nearest to way: pot, junior, favor, prank, use*, chunk, 4g, fusion,\n",
      "Nearest to would: won't, will, can, wouldn't, midori, should, could, *production,\n",
      "Nearest to has: needs, have, perform, 1bl, wants, finished), donutsthey'll, $16843,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, panic, tottaly, buuuurn, recruit,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, cannot, rt,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, speculative, they're,\n",
      "\n",
      "\n",
      "Average loss at step  374000 :  3.83961944109 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  376000 :  3.80752053474 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, pushes, cloudshell, on), alarms,\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, location-service, really,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, cyclists, coopers, injury, harp,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, sword, checksumming, tennis,\n",
      "Nearest to where: def, struggle, meant, era, darren, flew, permission, enable,\n",
      "Nearest to i'll: ill, scala, haskell, we'll, rt, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, said,\n",
      "Nearest to same: pawned, worst, visibly, hoekapplydefaults(config, irssi, proj, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:, venturebeat,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, pa, learnings, <marquee><blink>:eyes:</blink></marquee>, pilau,\n",
      "Nearest to way: pot, junior, favor, use*, prank, chunk, fusion, 4g,\n",
      "Nearest to would: won't, will, can, wouldn't, should, midori, could, *production,\n",
      "Nearest to has: needs, have, perform, finished), 1bl, wants, donutsthey'll, $16843,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, panic, tottaly, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, cannot, rt,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, speculative, they're,\n",
      "\n",
      "\n",
      "Average loss at step  378000 :  3.85632960904 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  380000 :  3.80744272542 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, ctrl-chop-head-of-chicken-and-rage-quit, doppelganger, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, cloudshell, pushes, alarms, on),\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, location-service, really,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, cyclists, coopers, injury, harp,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, checksumming, tennis, sword,\n",
      "Nearest to where: def, struggle, meant, era, darren, flew, permission, enable,\n",
      "Nearest to i'll: ill, scala, haskell, we'll, rt, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, said,\n",
      "Nearest to same: pawned, worst, visibly, hoekapplydefaults(config, irssi, proj, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:, venturebeat,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, pa, lag, webp, <marquee><blink>:eyes:</blink></marquee>,\n",
      "Nearest to way: pot, junior, favor, use*, prank, chunk, fusion, 4g,\n",
      "Nearest to would: won't, will, can, wouldn't, should, midori, could, *production,\n",
      "Nearest to has: needs, have, perform, finished), 1bl, wants, donutsthey'll, $16843,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, panic, tottaly, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, cannot, rt,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, speculative, barbican, they're,\n",
      "\n",
      "\n",
      "Average loss at step  382000 :  3.8486471821 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  384000 :  3.83219981349 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, license), er;, doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, cloudshell, on), pushes, spread,\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, really, location-service,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, coopers, cyclists, injury, harp,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, checksumming, sword, tennis,\n",
      "Nearest to where: def, meant, struggle, era, darren, flew, permission, enable,\n",
      "Nearest to i'll: ill, scala, rt, haskell, we'll, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, said,\n",
      "Nearest to same: pawned, worst, visibly, hoekapplydefaults(config, irssi, proj, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:, venturebeat,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, webp, lag, pa, <marquee><blink>:eyes:</blink></marquee>,\n",
      "Nearest to way: pot, junior, favor, use*, prank, chunk, fusion, 4g,\n",
      "Nearest to would: won't, will, can, wouldn't, should, midori, *production, could,\n",
      "Nearest to has: needs, have, perform, 1bl, finished), wants, $16843, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, panic, tottaly, buuuurn, descriptor,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, barbican, speculative, they're,\n",
      "\n",
      "\n",
      "Average loss at step  386000 :  3.82228505553 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  388000 :  3.84018994057 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, er;, license), doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite,\n",
      "Nearest to for: authorities, datacentres, custard, dialect, pushes, cloudshell, on), spread,\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, location-service, really,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, cyclists, coopers, injury, strip;,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, checksumming, launched:, stake,\n",
      "Nearest to where: def, meant, struggle, era, darren, flew, permission, enable,\n",
      "Nearest to i'll: ill, scala, rt, haskell, we'll, resource, -t, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, average, csysdig, is,\n",
      "Nearest to same: pawned, worst, visibly, hoekapplydefaults(config, irssi, proj, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:, venturebeat,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, robomongo, minerals, lag, webp, pa, <marquee><blink>:eyes:</blink></marquee>,\n",
      "Nearest to way: pot, junior, favor, use*, prank, chunk, fusion, 4g,\n",
      "Nearest to would: won't, will, can, wouldn't, midori, should, *production, could,\n",
      "Nearest to has: have, needs, perform, finished), 1bl, wants, $16843, donutsthey'll,\n",
      "Nearest to guys: 2002, 100ms, 20~22, permutation, panic, tottaly, buuuurn, recruit,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, rt, he'll, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, speculative, barbican, they're,\n",
      "\n",
      "\n",
      "Average loss at step  390000 :  3.81010341561 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  392000 :  3.8452466408 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, er;, license), doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, cloudshell, pushes, on), alarms,\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, location-service, really,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, coopers, cyclists, injury, strip;,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, checksumming, stake, launched:,\n",
      "Nearest to where: def, meant, struggle, era, darren, flew, permission, enable,\n",
      "Nearest to i'll: ill, scala, rt, haskell, we'll, resource, -t, bacalhau,\n",
      "Nearest to was: &@dscape, pursue, anticipated, blankey, rightmove, average, csysdig, is,\n",
      "Nearest to same: pawned, worst, visibly, hoekapplydefaults(config, irssi, proj, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:, venturebeat,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, robomongo, minerals, webp, <marquee><blink>:eyes:</blink></marquee>, pa, lag,\n",
      "Nearest to way: pot, junior, favor, use*, prank, chunk, fusion, 4g,\n",
      "Nearest to would: won't, will, can, wouldn't, should, midori, *production, could,\n",
      "Nearest to has: have, needs, perform, finished), 1bl, wants, $16843, donutsthey'll,\n",
      "Nearest to guys: 2002, 100ms, 20~22, permutation, panic, tottaly, buuuurn, recruit,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, rt, cannot,\n",
      "Nearest to i'm: im, norm, you're, nvidia, youre, speculative, barbican, --abbrev-commit,\n",
      "\n",
      "\n",
      "Average loss at step  394000 :  3.79929989564 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  396000 :  3.84349288564 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, er;, license), doppelganger, spiderpig, ctrl-chop-head-of-chicken-and-rage-quit, lite,\n",
      "Nearest to for: datacentres, authorities, custard, dialect, pushes, cloudshell, on), alarms,\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, really, location-service,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, coopers, cyclists, injury, strip;,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, checksumming, tennis, launched:,\n",
      "Nearest to where: def, meant, darren, struggle, era, flew, permission, enable,\n",
      "Nearest to i'll: ill, scala, haskell, rt, we'll, resource, -t, bacalhau,\n",
      "Nearest to was: &@dscape, pursue, anticipated, blankey, rightmove, average, csysdig, is,\n",
      "Nearest to same: pawned, worst, visibly, hoekapplydefaults(config, irssi, proj, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:, venturebeat,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, robomongo, minerals, webp, <marquee><blink>:eyes:</blink></marquee>, pa, learnings,\n",
      "Nearest to way: pot, junior, favor, use*, prank, chunk, fusion, 4g,\n",
      "Nearest to would: won't, will, can, wouldn't, midori, should, *production, could,\n",
      "Nearest to has: needs, have, perform, finished), wants, 1bl, $16843, donutsthey'll,\n",
      "Nearest to guys: 100ms, 2002, 20~22, permutation, panic, tottaly, buuuurn, recruit,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, rt, cannot,\n",
      "Nearest to i'm: im, norm, you're, youre, nvidia, speculative, barbican, they're,\n",
      "\n",
      "\n",
      "Average loss at step  398000 :  3.82324915504 \n",
      "\n",
      "\n",
      "\n",
      "\n",
      "Average loss at step  400000 :  3.79263622893 \n",
      "\n",
      "\n",
      "Nearest to your: my, laugh, er;, license), doppelganger, ctrl-chop-head-of-chicken-and-rage-quit, spiderpig, lite,\n",
      "Nearest to for: datacentres, authorities, dialect, custard, cloudshell, pushes, on), alarms,\n",
      "Nearest to very: pretty, exposure, monolith, super, discontinuity, vba, really, location-service,\n",
      "Nearest to then: addresses, burning, discreet, right-to-left, cyclists, coopers, injury, harp,\n",
      "Nearest to so: exam, simplify, maida, criticise, disappointed, checksumming, tennis, launched:,\n",
      "Nearest to where: def, struggle, darren, meant, era, flew, permission, enable,\n",
      "Nearest to i'll: ill, scala, we'll, haskell, rt, -t, resource, bacalhau,\n",
      "Nearest to was: pursue, &@dscape, blankey, anticipated, rightmove, csysdig, average, is,\n",
      "Nearest to same: pawned, worst, visibly, hoekapplydefaults(config, irssi, proj, :thumbs_down_sign::emoji_modifier_fitzpatrick_type-1-2:, venturebeat,\n",
      "Nearest to how: :smiling_face_with_heart-shaped_eyes::smiling_face_with_heart-shaped_eyes:, initd, minerals, robomongo, webp, <marquee><blink>:eyes:</blink></marquee>, learnings, pa,\n",
      "Nearest to way: pot, junior, use*, favor, prank, chunk, fusion, 4g,\n",
      "Nearest to would: won't, will, can, wouldn't, should, midori, *production, could,\n",
      "Nearest to has: needs, have, perform, finished), 1bl, wants, donutsthey'll, $16843,\n",
      "Nearest to guys: 2002, 100ms, 20~22, permutation, panic, tottaly, buuuurn, recruit,\n",
      "Nearest to don't: dont, reckon, won't, didn't, can't, he'll, cannot, rt,\n",
      "Nearest to i'm: im, norm, you're, youre, nvidia, speculative, barbican, they're,\n"
     ]
    }
   ],
   "source": [
    "# Step 5: Begin training.\n",
    "num_steps = 400001\n",
    "\n",
    "with tf.Session(graph=graph) as session:\n",
    "  # We must initialize all variables before we use them.\n",
    "  init.run()\n",
    "  print(\"Initialized\")\n",
    "\n",
    "  average_loss = 0\n",
    "  for step in xrange(num_steps):\n",
    "    batch_inputs, batch_labels = generate_batch(\n",
    "        batch_size, num_skips, skip_window)\n",
    "    feed_dict = {train_inputs : batch_inputs, train_labels : batch_labels}\n",
    "\n",
    "    # We perform one update step by evaluating the optimizer op (including it\n",
    "    # in the list of returned values for session.run()\n",
    "    _, loss_val = session.run([optimizer, loss], feed_dict=feed_dict)\n",
    "    average_loss += loss_val\n",
    "\n",
    "    if step % 2000 == 0:\n",
    "      if step > 0:\n",
    "        average_loss /= 2000\n",
    "      # The average loss is an estimate of the loss over the last 2000 batches.\n",
    "      print(\"\\n\\nAverage loss at step \", step, \": \", average_loss, \"\\n\\n\")\n",
    "      average_loss = 0\n",
    "\n",
    "    # Note that this is expensive (~20% slowdown if computed every 500 steps)\n",
    "    if step % 4000 == 0:\n",
    "      sim = similarity.eval()\n",
    "      for i in xrange(valid_size):\n",
    "        valid_word = reverse_dictionary[valid_examples[i]]\n",
    "        top_k = 8 # number of nearest neighbors\n",
    "        nearest = (-sim[i, :]).argsort()[1:top_k+1]\n",
    "        log_str = \"Nearest to %s:\" % valid_word\n",
    "        for k in xrange(top_k):\n",
    "          close_word = reverse_dictionary[nearest[k]]\n",
    "          log_str = \"%s %s,\" % (log_str, close_word)\n",
    "        print(log_str)\n",
    "  final_embeddings = normalized_embeddings.eval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# Step 6: Visualize the embeddings.\n",
    "def plot_with_labels(low_dim_embs, labels, filename='tsne.png'):\n",
    "  assert low_dim_embs.shape[0] >= len(labels), \"More labels than embeddings\"\n",
    "  plt.figure(figsize=(18, 18))  #in inches\n",
    "  for i, label in enumerate(labels):\n",
    "    x, y = low_dim_embs[i,:]\n",
    "    plt.scatter(x, y)\n",
    "    plt.annotate(label,\n",
    "                 xy=(x, y),\n",
    "                 xytext=(5, 2),\n",
    "                 textcoords='offset points',\n",
    "                 ha='right',\n",
    "                 va='bottom')\n",
    "\n",
    "  plt.savefig(filename)\n",
    "  plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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GOj0NBoOGDh2qXbt2qXfv3jIYDOrTp4+eeeaZQv8/GAwG9e/fXxMm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mzO5MUYY02c/NTz0g1dPPWcsYauKjGSG0pjhZWVVYOpa31iYGCA8PAj3NjHXqkkOah8x5cP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3Kz9bWVmxd+9etWNKTwZoY2NTpkbj7NmzmT17dpnnevfdd3n33Xerqusaz8jIqNwa5Fpa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y5Aj27t2Lq1evQl9fHzY2NiID3ZUHwwoKCrB+/Xrs27cPMTExuH//PhYsWPDOdjVk0uymlKC7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GvXrmFhYUHTpk1Zvnw57u7uSJJEy5Yt5TYgxSM7du7cSYsWLTA0NGT79u1MmzZNroIePnw4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\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xhY+fnx+enp706tWLrVu3cu7cOfbs2cP7779PUlJSySeoIry8vLhx4wYLFy5UgtYFvbTj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\n11e9e/emnAgqjbi4OHXu3FmjR4/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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7ffa32ca2550>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "try:\n",
    "  from sklearn.manifold import TSNE\n",
    "  import matplotlib.pyplot as plt\n",
    "\n",
    "  tsne = TSNE(perplexity=30, n_components=2, init='pca', n_iter=15000)\n",
    "  plot_only = 500\n",
    "  low_dim_embs = tsne.fit_transform(final_embeddings[:plot_only,:])\n",
    "  labels = [reverse_dictionary[i] for i in xrange(plot_only)]\n",
    "  plot_with_labels(low_dim_embs, labels)\n",
    "\n",
    "except ImportError:\n",
    "  print(\"Please install sklearn, matplotlib, and scipy to visualize embeddings.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": false,
    "scrolled": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 2",
   "language": "python",
   "name": "python2"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}