{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Setting Up the data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "source_language = \"fr\"\n",
    "target_language = \"ln\" # ln is the language code of lingala \n",
    "lc = False  # If True, lowercase the data.\n",
    "seed = 42  # Random seed for shuffling.\n",
    "tag = \"baseline\" # Give a unique name to your folder - this is to ensure you don't rewrite any models you've already submitted\n",
    "\n",
    "os.environ[\"src\"] = source_language # Sets them in bash as well, since we often use bash scripts\n",
    "os.environ[\"tgt\"] = target_language\n",
    "os.environ[\"tag\"] = tag\n",
    "\n",
    "# No need to use gdrive since we are training on gcp\n",
    "!mkdir -p \"$src-$tgt-$tag\"\n",
    "os.environ[\"gdrive_path\"] = \"%s-%s-%s\" % (source_language, target_language, tag) # saving directly on the vm"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "fr-ln-baseline\r\n"
     ]
    }
   ],
   "source": [
    "!echo $gdrive_path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Downloading the corpus data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "remove the old data and redownload them for verification puprose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "!rm -f w300.$src jw300.$tgt JW300_latest_xml_$src-$tgt.xml.gz JW300_latest_xml_$src-$tgt.xml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Alignment file /proj/nlpl/data/OPUS/JW300/latest/xml/fr-ln.xml.gz not found. The following files are available for downloading:\n",
      "\n",
      "   5 MB https://object.pouta.csc.fi/OPUS-JW300/v1/xml/fr-ln.xml.gz\n",
      " 278 MB https://object.pouta.csc.fi/OPUS-JW300/v1/xml/fr.zip\n",
      "  60 MB https://object.pouta.csc.fi/OPUS-JW300/v1/xml/ln.zip\n",
      "\n",
      " 344 MB Total size\n",
      "./JW300_latest_xml_fr-ln.xml.gz ... 100% of 5 MB\n",
      "./JW300_latest_xml_fr.zip ... 100% of 278 MB\n",
      "./JW300_latest_xml_ln.zip ... 100% of 60 MBzip ... 33% of 60 MB\n"
     ]
    }
   ],
   "source": [
    "# Downloading our corpus\n",
    "! opus_read -d JW300 -s $src -t $tgt -wm moses -w jw300.$src jw300.$tgt -q\n",
    "\n",
    "# extract the corpus file\n",
    "! gunzip JW300_latest_xml_$src-$tgt.xml.gz"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "#! wget https://raw.githubusercontent.com/espoirMur/masakhane/add-french-global-test-set/jw300_utils/test/test.fr-any.fr\n",
    "\n",
    "os.environ[\"trg\"] = target_language \n",
    "os.environ[\"src\"] = source_language \n",
    "\n",
    "#! wget https://raw.githubusercontent.com/juliakreutzer/masakhane/master/jw300_utils/test/test.en-$trg.en \n",
    "#! mv test.en-$trg.en test.en\n",
    "#! wget https://raw.githubusercontent.com/juliakreutzer/masakhane/master/jw300_utils/test/test.en-$trg.$trg \n",
    "#! mv test.en-$trg.$trg test.$trg"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "read the french test data generate in [this notebook](./buiding_french_global_test_set.ipynb) and save the data in a set for quick retrieval"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generating test Lingala dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "First we get the global english swahili congo test set "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2020-02-16 19:56:41--  https://raw.githubusercontent.com/juliakreutzer/masakhane/master/jw300_utils/test/test.en-ln.en\n",
      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.192.133, 151.101.128.133, 151.101.64.133, ...\n",
      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.192.133|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 205304 (200K) [text/plain]\n",
      "Saving to: ‘test.en-ln.en’\n",
      "\n",
      "test.en-ln.en       100%[===================>] 200.49K  --.-KB/s    in 0.04s   \n",
      "\n",
      "2020-02-16 19:56:41 (4.89 MB/s) - ‘test.en-ln.en’ saved [205304/205304]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "! wget https://raw.githubusercontent.com/juliakreutzer/masakhane/master/jw300_utils/test/test.en-ln.en"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2020-02-16 19:57:14--  https://raw.githubusercontent.com/juliakreutzer/masakhane/master/jw300_utils/test/test.en-ln.ln\n",
      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.192.133, 151.101.128.133, 151.101.64.133, ...\n",
      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.192.133|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 231696 (226K) [text/plain]\n",
      "Saving to: ‘test.en-ln.ln’\n",
      "\n",
      "test.en-ln.ln       100%[===================>] 226.27K  --.-KB/s    in 0.04s   \n",
      "\n",
      "2020-02-16 19:57:15 (5.15 MB/s) - ‘test.en-ln.ln’ saved [231696/231696]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "! wget https://raw.githubusercontent.com/juliakreutzer/masakhane/master/jw300_utils/test/test.en-$tgt.ln"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The we check if we have alogned data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Qui veut être millionnaire ?\r\n",
      "IL SEMBLE que ce soit là le désir de tout un chacun , ou presque .\r\n",
      "Or la solution la plus simple , dans l’esprit du public , est de gagner à la loterie ou au loto sportif * .\r\n",
      "Flattant les désirs du grand nombre — et convoitant les excédents qui reviendront à l’État — , de Moscou à Madrid , de Manille à Mexico , les gouvernements parrainent des loteries d’État qui peuvent faire gagner l’équivalent de plusieurs centaines de millions de francs français .\r\n",
      "Quelques joueurs deviennent effectivement millionnaires .\r\n",
      "Un Anglais , qui avait parié pendant 25 ans sur les matchs de football , a finalement gagné une somme fabuleuse .\r\n",
      "Une mise équivalant à moins de 3 francs français lui en a rapporté plus de 8 millions .\r\n",
      "Plus spectaculaire encore est le cas de cette New - yorkaise qui a gagné 55 millions de dollars à la loterie de Floride , l’un des plus importants gros lots jamais remportés .\r\n",
      "Mais ce ne sont là que des exceptions .\r\n",
      "Plus représentatif est cet employé de bureau espagnol qui achète des billets de loterie chaque semaine depuis 30 ans .\r\n"
     ]
    }
   ],
   "source": [
    "!head -10 jw300.$src"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Nani alingi kozala milionere ?\r\n",
      "EYANO emonani lokola ete , wana ezali mposa ya moto na moto to pene na bato nyonso .\r\n",
      "Nzokande , na makanisi ya bato , nzela ya pɛtɛɛ mpo na kozwa yango ezali kolónga na loterie to na momekano ya kosakola liboso équipe ya ndembo oyo ekolónga .\r\n",
      "Kolamusáká mposa ya bato mingi ​ — mpe koluláká kozwa misolo oyo Leta akozwa likoló ​ — kolongwa Moscou kino Madrid , kolongwa Manille kino Mexico , baguvernema bazali kopesa lisungi na loterie esalemi na Leta , kati na yango balóngi bakoki kozwa nkámá mingi ya bamilió ya badolare .\r\n",
      "Mwa babɛti na yango bazali mpenza kokóma bamilionere .\r\n",
      "Mongelesi moko oyo azalaki kosala momekano na boumeli ya mibu 25 mpo na kosakola liboso soki équipe nini ekolónga , azwaki mosolo mingi mpenza .\r\n",
      "Abɛtaki bobele na mosolo mokokani na franka 3 ya ba français , kasi azwaki koleka bamilió mwambe na franka ya ba français .\r\n",
      "Oyo ekamwisi mpenza ezali likambo ya mwasi oyo ya New York , oyo azwaki bamilió 55 ya dolare na loterie na mboka Floride , moko na libonza monene oyo lizwamaki naino te .\r\n",
      "Kasi baoyo bazali kolónga boye bazali sé moke mpenza .\r\n",
      "Ndakisa emonisi yango malamu ezali mosali na biro moko ya Espagne oyo azali kosomba tiké ya loterie poso na poso uta mibu 30 .\r\n"
     ]
    }
   ],
   "source": [
    "!head -10 jw300.$tgt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "source_file = f\"jw300.{source_language}\"\n",
    "target_file = f\"jw300.{target_language}\"\n",
    "test_file = f\"test.en-{target_language}.{target_language}\"\n",
    "with open(test_file) as ln_test_file, open(target_file) as ln_full_file, open(source_file) as fr_full_file:\n",
    "    ln_test_sentences = ln_test_file.readlines()\n",
    "    fr_full_sentences = fr_full_file.readlines()\n",
    "    ln_full_sentences = ln_full_file.readlines()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "ln_test_sentences = [sentence.strip() for sentence in ln_test_sentences]\n",
    "fr_full_sentences = [sentence.strip() for sentence in fr_full_sentences]\n",
    "ln_full_sentences = [sentence.strip() for sentence in ln_full_sentences]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Qui veut être millionnaire ?',\n",
       " 'IL SEMBLE que ce soit là le désir de tout un chacun , ou presque .',\n",
       " 'Or la solution la plus simple , dans l’esprit du public , est de gagner à la loterie ou au loto sportif * .',\n",
       " 'Flattant les désirs du grand nombre — et convoitant les excédents qui reviendront à l’État — , de Moscou à Madrid , de Manille à Mexico , les gouvernements parrainent des loteries d’État qui peuvent faire gagner l’équivalent de plusieurs centaines de millions de francs français .',\n",
       " 'Quelques joueurs deviennent effectivement millionnaires .',\n",
       " 'Un Anglais , qui avait parié pendant 25 ans sur les matchs de football , a finalement gagné une somme fabuleuse .',\n",
       " 'Une mise équivalant à moins de 3 francs français lui en a rapporté plus de 8 millions .',\n",
       " 'Plus spectaculaire encore est le cas de cette New - yorkaise qui a gagné 55 millions de dollars à la loterie de Floride , l’un des plus importants gros lots jamais remportés .',\n",
       " 'Mais ce ne sont là que des exceptions .',\n",
       " 'Plus représentatif est cet employé de bureau espagnol qui achète des billets de loterie chaque semaine depuis 30 ans .']"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "fr_full_sentences[:10]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Nani alingi kozala milionere ?',\n",
       " 'EYANO emonani lokola ete , wana ezali mposa ya moto na moto to pene na bato nyonso .',\n",
       " 'Nzokande , na makanisi ya bato , nzela ya pɛtɛɛ mpo na kozwa yango ezali kolónga na loterie to na momekano ya kosakola liboso équipe ya ndembo oyo ekolónga .',\n",
       " 'Kolamusáká mposa ya bato mingi \\u200b — mpe koluláká kozwa misolo oyo Leta akozwa likoló \\u200b — kolongwa Moscou kino Madrid , kolongwa Manille kino Mexico , baguvernema bazali kopesa lisungi na loterie esalemi na Leta , kati na yango balóngi bakoki kozwa nkámá mingi ya bamilió ya badolare .',\n",
       " 'Mwa babɛti na yango bazali mpenza kokóma bamilionere .',\n",
       " 'Mongelesi moko oyo azalaki kosala momekano na boumeli ya mibu 25 mpo na kosakola liboso soki équipe nini ekolónga , azwaki mosolo mingi mpenza .',\n",
       " 'Abɛtaki bobele na mosolo mokokani na franka 3 ya ba français , kasi azwaki koleka bamilió mwambe na franka ya ba français .',\n",
       " 'Oyo ekamwisi mpenza ezali likambo ya mwasi oyo ya New York , oyo azwaki bamilió 55 ya dolare na loterie na mboka Floride , moko na libonza monene oyo lizwamaki naino te .',\n",
       " 'Kasi baoyo bazali kolónga boye bazali sé moke mpenza .',\n",
       " 'Ndakisa emonisi yango malamu ezali mosali na biro moko ya Espagne oyo azali kosomba tiké ya loterie poso na poso uta mibu 30 .']"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ln_full_sentences[:10]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For any lingala sentence in the global lingala test set, get the french equivalent "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['Mpo ete lobɔkɔ na yo ezalaki na bozito likoló na ngai na moi na butu . ”',\n",
       " 'Kati na lisolo oyo , topesi bango nkombo mosusu .',\n",
       " 'Na lisolo oyo , topesi bato mosusu nkombo mosusu .',\n",
       " 'Ebimisami na Batatoli ya Yehova kasi enyatamaka lisusu te .',\n",
       " 'Lisusu , bóbenga moto moko te tata na bino awa na mabelé , mpo kaka moko nde azali Tata na bino , Oyo azali na likoló .']"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ln_test_sentences[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "matching_fr_test_sentences = []\n",
    "matching_ln_test_sentences = []\n",
    "\n",
    "for index, lingala_line in enumerate(ln_full_sentences):\n",
    "    if lingala_line in ln_test_sentences and lingala_line:\n",
    "        matching_fr_test_sentences.append(fr_full_sentences[index])\n",
    "        matching_ln_test_sentences.append(lingala_line)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "french_ln_test_dataset = pd.DataFrame(zip(matching_fr_test_sentences, matching_ln_test_sentences), columns=['french_sentence', 'lingala_sentence'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>french_sentence</th>\n",
       "      <th>lingala_sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Car jour et nuit ta main pesait sur moi . ” .</td>\n",
       "      <td>Mpo ete lobɔkɔ na yo ezalaki na bozito likoló ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Par souci d’anonymat , certains noms ont été c...</td>\n",
       "      <td>Kati na lisolo oyo , topesi bango nkombo mosusu .</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Par souci d’anonymat , certains noms ont été c...</td>\n",
       "      <td>Na lisolo oyo , topesi bato mosusu nkombo mosu...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Comment ?</td>\n",
       "      <td>Kasi , ndenge nini okoki kosala yango ?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Publié par les Témoins de Jéhovah , mais épuisé .</td>\n",
       "      <td>Ebimisami na Batatoli ya Yehova kasi enyatamak...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>En outre , n’appelez personne votre père sur l...</td>\n",
       "      <td>Lisusu , bóbenga moto moko te tata na bino awa...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Ne regarde pas tout autour , car je suis ton D...</td>\n",
       "      <td>Kotala epai na epai te , mpo nazali Nzambe na ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>« Les justes posséderont la terre , et sur ell...</td>\n",
       "      <td>“ Bayengebene bakozwa mabele , mpe bakofanda w...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Juste avant de créer une femme pour le premier...</td>\n",
       "      <td>Nakosalela ye mosungi , oyo abongi na ye . ”</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Jéhovah est le nom de Dieu révélé dans la Bible .</td>\n",
       "      <td>Yehova ezali nkombo ya Nzambe na Biblia .</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     french_sentence  \\\n",
       "0      Car jour et nuit ta main pesait sur moi . ” .   \n",
       "1  Par souci d’anonymat , certains noms ont été c...   \n",
       "2  Par souci d’anonymat , certains noms ont été c...   \n",
       "3                                          Comment ?   \n",
       "4  Publié par les Témoins de Jéhovah , mais épuisé .   \n",
       "5  En outre , n’appelez personne votre père sur l...   \n",
       "6  Ne regarde pas tout autour , car je suis ton D...   \n",
       "7  « Les justes posséderont la terre , et sur ell...   \n",
       "8  Juste avant de créer une femme pour le premier...   \n",
       "9  Jéhovah est le nom de Dieu révélé dans la Bible .   \n",
       "\n",
       "                                    lingala_sentence  \n",
       "0  Mpo ete lobɔkɔ na yo ezalaki na bozito likoló ...  \n",
       "1  Kati na lisolo oyo , topesi bango nkombo mosusu .  \n",
       "2  Na lisolo oyo , topesi bato mosusu nkombo mosu...  \n",
       "3            Kasi , ndenge nini okoki kosala yango ?  \n",
       "4  Ebimisami na Batatoli ya Yehova kasi enyatamak...  \n",
       "5  Lisusu , bóbenga moto moko te tata na bino awa...  \n",
       "6  Kotala epai na epai te , mpo nazali Nzambe na ...  \n",
       "7  “ Bayengebene bakozwa mabele , mpe bakofanda w...  \n",
       "8       Nakosalela ye mosungi , oyo abongi na ye . ”  \n",
       "9          Yehova ezali nkombo ya Nzambe na Biblia .  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "french_ln_test_dataset.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>french_sentence</th>\n",
       "      <th>lingala_sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3123</th>\n",
       "      <td>Et qu’est - ​ ce qui est plus joli : le bruit ...</td>\n",
       "      <td>Mpe okoloba nini mpo na makɛlɛlɛ ya mpɛpɔ ná k...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3124</th>\n",
       "      <td>Alors , qui est le plus intelligent : le créat...</td>\n",
       "      <td>Sikoyo , nani aleki na mayele : moto oyo asalá...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3125</th>\n",
       "      <td>Un père conseille : « Ne vous fatiguez jamais ...</td>\n",
       "      <td>Tata moko alobaki : “ Kolɛmba soki moke te kol...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3126</th>\n",
       "      <td>Quand ils étaient tout petits , je faisais 15 ...</td>\n",
       "      <td>Bandá ntango bazalaki bana mike , nazalaki koy...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3127</th>\n",
       "      <td>Avec le temps , j’ai obtenu beaucoup de répons...</td>\n",
       "      <td>Nsima ya mikolo , nazwaki biyano na mituna yan...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3128</th>\n",
       "      <td>C’est pour cela que c’est important que les pa...</td>\n",
       "      <td>Yango wana , ezali na ntina mingi ete baboti b...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3129</th>\n",
       "      <td>Montre - ​ leur que Jéhovah est vraiment réel ...</td>\n",
       "      <td>Tiká bana na yo bámona ete Yehova azali mpenza...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3130</th>\n",
       "      <td>« Nous disons à la plus grande : “ Fais totale...</td>\n",
       "      <td>Balobi boye : “ Toyebisaki mpe mwana na biso y...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3131</th>\n",
       "      <td>Lorsqu’elle voit comment les choses s’arrangen...</td>\n",
       "      <td>Ntango amonaki ndenge likambo yango esukaki , ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3132</th>\n",
       "      <td>C’est excellent pour sa foi en Dieu et en la B...</td>\n",
       "      <td>Yango ekómisaki makasi kondima na ye epai ya N...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                        french_sentence  \\\n",
       "3123  Et qu’est - ​ ce qui est plus joli : le bruit ...   \n",
       "3124  Alors , qui est le plus intelligent : le créat...   \n",
       "3125  Un père conseille : « Ne vous fatiguez jamais ...   \n",
       "3126  Quand ils étaient tout petits , je faisais 15 ...   \n",
       "3127  Avec le temps , j’ai obtenu beaucoup de répons...   \n",
       "3128  C’est pour cela que c’est important que les pa...   \n",
       "3129  Montre - ​ leur que Jéhovah est vraiment réel ...   \n",
       "3130  « Nous disons à la plus grande : “ Fais totale...   \n",
       "3131  Lorsqu’elle voit comment les choses s’arrangen...   \n",
       "3132  C’est excellent pour sa foi en Dieu et en la B...   \n",
       "\n",
       "                                       lingala_sentence  \n",
       "3123  Mpe okoloba nini mpo na makɛlɛlɛ ya mpɛpɔ ná k...  \n",
       "3124  Sikoyo , nani aleki na mayele : moto oyo asalá...  \n",
       "3125  Tata moko alobaki : “ Kolɛmba soki moke te kol...  \n",
       "3126  Bandá ntango bazalaki bana mike , nazalaki koy...  \n",
       "3127  Nsima ya mikolo , nazwaki biyano na mituna yan...  \n",
       "3128  Yango wana , ezali na ntina mingi ete baboti b...  \n",
       "3129  Tiká bana na yo bámona ete Yehova azali mpenza...  \n",
       "3130  Balobi boye : “ Toyebisaki mpe mwana na biso y...  \n",
       "3131  Ntango amonaki ndenge likambo yango esukaki , ...  \n",
       "3132  Yango ekómisaki makasi kondima na ye epai ya N...  "
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "french_ln_test_dataset.tail(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remove duplicates from both sides"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(2513, 2)"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "french_ln_test_dataset = french_ln_test_dataset.drop_duplicates(subset='french_sentence')\n",
    "french_ln_test_dataset = french_ln_test_dataset.drop_duplicates(subset='lingala_sentence')\n",
    "french_ln_test_dataset.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded 3332 global test sentences to filter from the training/dev data.\n"
     ]
    }
   ],
   "source": [
    "fr_test_sents = set()\n",
    "filter_test_sents = \"test.fr-any.fr\"\n",
    "j = 0\n",
    "with open(filter_test_sents) as f:\n",
    "    for line in f:\n",
    "        fr_test_sents.add(line.strip())\n",
    "        j += 1\n",
    "print('Loaded {} global test sentences to filter from the training/dev data.'.format(j))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(679, 2)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "french_ln_test_dataset.loc[~french_ln_test_dataset.french_sentence.isin(fr_test_sents)].shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Only 643 sentences are in the french lingala test set but not in the global test set, what should we do with them?"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Save the test set with to new files "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [],
   "source": [
    "french_ln_test_dataset.lingala_sentence.to_csv(\"test.ln\",sep='\\n', header=False, index=False)\n",
    "french_ln_test_dataset.french_sentence.to_csv(\"test.fr\",sep='\\n', header=False, index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "JW300_latest_xml_fr-ln.xml  baseline.ipynb  jw300.ln\t   test.fr\r\n",
      "JW300_latest_xml_fr.zip     fr-ln-baseline  test.en-ln.en  test.fr-any.fr\r\n",
      "JW300_latest_xml_ln.zip     jw300.fr\t    test.en-ln.ln  test.ln\r\n"
     ]
    }
   ],
   "source": [
    "!ls"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Building the model dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Car jour et nuit ta main pesait sur moi . ” .\r\n",
      "Par souci d’anonymat , certains noms ont été changés .\r\n",
      "Comment ?\r\n",
      "Publié par les Témoins de Jéhovah , mais épuisé .\r\n",
      "En outre , n’appelez personne votre père sur la terre , car un seul est votre Père , le Céleste .\r\n"
     ]
    }
   ],
   "source": [
    "!head -5 test.$src"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Mpo ete lobɔkɔ na yo ezalaki na bozito likoló na ngai na moi na butu . ”\r\n",
      "Kati na lisolo oyo , topesi bango nkombo mosusu .\r\n",
      "Kasi , ndenge nini okoki kosala yango ?\r\n",
      "Ebimisami na Batatoli ya Yehova kasi enyatamaka lisusu te .\r\n",
      "Lisusu , bóbenga moto moko te tata na bino awa na mabelé , mpo kaka moko nde azali Tata na bino , Oyo azali na likoló .\r\n"
     ]
    }
   ],
   "source": [
    "!head -5 test.$tgt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_lines_to_ignore = fr_test_sents.union(set(french_ln_test_dataset.french_sentence.unique()))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Loaded data and skipped 13730/590554 lines since contained in test set.\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>source_sentence</th>\n",
       "      <th>target_sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Qui veut être millionnaire ?</td>\n",
       "      <td>Nani alingi kozala milionere ?</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>IL SEMBLE que ce soit là le désir de tout un c...</td>\n",
       "      <td>EYANO emonani lokola ete , wana ezali mposa ya...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Or la solution la plus simple , dans l’esprit ...</td>\n",
       "      <td>Nzokande , na makanisi ya bato , nzela ya pɛtɛ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Flattant les désirs du grand nombre — et convo...</td>\n",
       "      <td>Kolamusáká mposa ya bato mingi ​ — mpe kolulák...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Quelques joueurs deviennent effectivement mill...</td>\n",
       "      <td>Mwa babɛti na yango bazali mpenza kokóma bamil...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Un Anglais , qui avait parié pendant 25 ans su...</td>\n",
       "      <td>Mongelesi moko oyo azalaki kosala momekano na ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Une mise équivalant à moins de 3 francs frança...</td>\n",
       "      <td>Abɛtaki bobele na mosolo mokokani na franka 3 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Plus spectaculaire encore est le cas de cette ...</td>\n",
       "      <td>Oyo ekamwisi mpenza ezali likambo ya mwasi oyo...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Mais ce ne sont là que des exceptions .</td>\n",
       "      <td>Kasi baoyo bazali kolónga boye bazali sé moke ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Plus représentatif est cet employé de bureau e...</td>\n",
       "      <td>Ndakisa emonisi yango malamu ezali mosali na b...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     source_sentence  \\\n",
       "0                       Qui veut être millionnaire ?   \n",
       "1  IL SEMBLE que ce soit là le désir de tout un c...   \n",
       "2  Or la solution la plus simple , dans l’esprit ...   \n",
       "3  Flattant les désirs du grand nombre — et convo...   \n",
       "4  Quelques joueurs deviennent effectivement mill...   \n",
       "5  Un Anglais , qui avait parié pendant 25 ans su...   \n",
       "6  Une mise équivalant à moins de 3 francs frança...   \n",
       "7  Plus spectaculaire encore est le cas de cette ...   \n",
       "8            Mais ce ne sont là que des exceptions .   \n",
       "9  Plus représentatif est cet employé de bureau e...   \n",
       "\n",
       "                                     target_sentence  \n",
       "0                     Nani alingi kozala milionere ?  \n",
       "1  EYANO emonani lokola ete , wana ezali mposa ya...  \n",
       "2  Nzokande , na makanisi ya bato , nzela ya pɛtɛ...  \n",
       "3  Kolamusáká mposa ya bato mingi ​ — mpe kolulák...  \n",
       "4  Mwa babɛti na yango bazali mpenza kokóma bamil...  \n",
       "5  Mongelesi moko oyo azalaki kosala momekano na ...  \n",
       "6  Abɛtaki bobele na mosolo mokokani na franka 3 ...  \n",
       "7  Oyo ekamwisi mpenza ezali likambo ya mwasi oyo...  \n",
       "8  Kasi baoyo bazali kolónga boye bazali sé moke ...  \n",
       "9  Ndakisa emonisi yango malamu ezali mosali na b...  "
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# TMX file to dataframe\n",
    "source_file = 'jw300.' + source_language\n",
    "target_file = 'jw300.' + target_language\n",
    "\n",
    "source = []\n",
    "target = []\n",
    "skip_lines = []  # Collect the line numbers of the source portion to skip the same lines for the target portion.\n",
    "with open(source_file) as f:\n",
    "    for i, line in enumerate(f):\n",
    "        # Skip sentences that are contained in the test set or in the frc_test_set\n",
    "        if line.strip() not in test_lines_to_ignore:\n",
    "            source.append(line.strip())\n",
    "        else:\n",
    "            skip_lines.append(i)             \n",
    "with open(target_file) as f:\n",
    "    for j, line in enumerate(f):\n",
    "        # Only add to corpus if corresponding source was not skipped.\n",
    "        if j not in skip_lines:\n",
    "            target.append(line.strip())\n",
    "    \n",
    "print('Loaded data and skipped {}/{} lines since contained in test set.'.format(len(skip_lines), i))\n",
    "    \n",
    "df = pd.DataFrame(zip(source, target), columns=['source_sentence', 'target_sentence'])\n",
    "# if you get TypeError: data argument can't be an iterator is because of your zip version run this below\n",
    "#df = pd.DataFrame(list(zip(source, target)), columns=['source_sentence', 'target_sentence'])\n",
    "df.head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Some tests :"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>source_sentence</th>\n",
       "      <th>target_sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>576815</th>\n",
       "      <td>Comme les chrétiens hébreux , nous pouvons étu...</td>\n",
       "      <td>Lokola bakristo Baebre , tokoki kotánga makamb...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576816</th>\n",
       "      <td>Pour montrer que cette promesse est biblique ,...</td>\n",
       "      <td>Mpo na komonisa ete elaka yango euti na Makoma...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576817</th>\n",
       "      <td>Nous sommes touchés de savoir que « la promess...</td>\n",
       "      <td>Koyeba ete “ elaka ya kokɔta na kopema [ ya Nz...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576818</th>\n",
       "      <td>Nous sommes convaincus que c’est possible d’en...</td>\n",
       "      <td>Tondimaka ete makambo oyo Biblia eteyaka na oy...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576819</th>\n",
       "      <td>Pas en obéissant à la Loi de Moïse , ni en fai...</td>\n",
       "      <td>Tosalaka yango te mpo na koluka kotosa Mibeko ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576820</th>\n",
       "      <td>Mais c’est plutôt en travaillant avec foi et d...</td>\n",
       "      <td>Kasi , lokola tondimelaka Nzambe , tosepelaka ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576821</th>\n",
       "      <td>De plus , des milliers de personnes dans le mo...</td>\n",
       "      <td>Ebele ya bato na mokili mobimba babandá mpe ko...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576822</th>\n",
       "      <td>Cette étude a motivé beaucoup d’entre elles à ...</td>\n",
       "      <td>Yango esalisaki mingi na bango bábongola bomoi...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576823</th>\n",
       "      <td>L’effet que « la parole de Dieu » a sur ces pe...</td>\n",
       "      <td>Ndenge oyo bazali kobongwana emonisi polele et...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576824</th>\n",
       "      <td>Les déclarations de Jéhovah sur son projet qui...</td>\n",
       "      <td>Makambo oyo Nzambe amonisá na Biblia mpo na mo...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          source_sentence  \\\n",
       "576815  Comme les chrétiens hébreux , nous pouvons étu...   \n",
       "576816  Pour montrer que cette promesse est biblique ,...   \n",
       "576817  Nous sommes touchés de savoir que « la promess...   \n",
       "576818  Nous sommes convaincus que c’est possible d’en...   \n",
       "576819  Pas en obéissant à la Loi de Moïse , ni en fai...   \n",
       "576820  Mais c’est plutôt en travaillant avec foi et d...   \n",
       "576821  De plus , des milliers de personnes dans le mo...   \n",
       "576822  Cette étude a motivé beaucoup d’entre elles à ...   \n",
       "576823  L’effet que « la parole de Dieu » a sur ces pe...   \n",
       "576824  Les déclarations de Jéhovah sur son projet qui...   \n",
       "\n",
       "                                          target_sentence  \n",
       "576815  Lokola bakristo Baebre , tokoki kotánga makamb...  \n",
       "576816  Mpo na komonisa ete elaka yango euti na Makoma...  \n",
       "576817  Koyeba ete “ elaka ya kokɔta na kopema [ ya Nz...  \n",
       "576818  Tondimaka ete makambo oyo Biblia eteyaka na oy...  \n",
       "576819  Tosalaka yango te mpo na koluka kotosa Mibeko ...  \n",
       "576820  Kasi , lokola tondimelaka Nzambe , tosepelaka ...  \n",
       "576821  Ebele ya bato na mokili mobimba babandá mpe ko...  \n",
       "576822  Yango esalisaki mingi na bango bábongola bomoi...  \n",
       "576823  Ndenge oyo bazali kobongwana emonisi polele et...  \n",
       "576824  Makambo oyo Nzambe amonisá na Biblia mpo na mo...  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Dans les cercles de jeu , on admire celui qui gagne ou qui mise de fortes sommes .'"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.source_sentence[100]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Na bisika ya masano , bakokumisaka moto oyo azwi libonza to oyo atii mosolo mingi .'"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.target_sentence[100]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Pre-processing and export\n",
    "\n",
    "It is generally a good idea to remove duplicate translations and conflicting translations from the corpus. In practice, these public corpora include some number of these that need to be cleaned.\n",
    "\n",
    "In addition we will split our data into dev/test/train and export to the filesystem."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_without_duplicates = df.drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_without_duplicates = df_without_duplicates.drop_duplicates(subset='source_sentence', inplace=False)\n",
    "df_without_duplicates = df_without_duplicates.drop_duplicates(subset='target_sentence', inplace=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Remove all sentences that can be found in the swahili test set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_without_duplicates = df_without_duplicates.loc[~df_without_duplicates.target_sentence.isin(french_ln_test_dataset.lingala_sentence)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(528304, 2)"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_without_duplicates.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following lines am checking that all sentences we have kept in the main dataset are not in the test set anymore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert  df_without_duplicates.loc[df_without_duplicates.target_sentence.isna()].shape[0] == 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also check if the splitting was done corectly "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert df_without_duplicates.loc[df_without_duplicates.source_sentence.isin(fr_test_sents)].shape[0] == 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert df_without_duplicates.loc[df_without_duplicates.source_sentence.isin(french_ln_test_dataset.french_sentence)].shape[0] == 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "assert df_without_duplicates.loc[df_without_duplicates.target_sentence.isin(french_ln_test_dataset.lingala_sentence)].shape[0] == 0"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If any of these test fails please check preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_without_duplicates = df_without_duplicates.sample(frac=1, random_state=seed).reset_index(drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>source_sentence</th>\n",
       "      <th>target_sentence</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>parce que vous donnez le dixième de la menthe ...</td>\n",
       "      <td>mpamba te bopesaka moko ya zomi ya manti mpe y...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Abraham n’a pas honte de pleurer , il ne cherc...</td>\n",
       "      <td>Na esika ete kolela yango ezala likambo ya nsɔ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Il y a cependant un aspect de la Bible qui , p...</td>\n",
       "      <td>Nzokande , okomona elembo oyo ezali komonisa e...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Or la solution la plus simple , dans l’esprit ...</td>\n",
       "      <td>Nzokande , na makanisi ya bato , nzela ya pɛtɛ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>” Loin de faire table rase des coutumes popula...</td>\n",
       "      <td>Na esika ete bálongola mimeseno ya bapakano mp...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>L’amour que Paul éprouvait pour les gens l’a p...</td>\n",
       "      <td>Lokola Paulo alingaki bato , yango etindaki ye...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Jéhovah est notre Auteur et , à ce titre , il ...</td>\n",
       "      <td>Mozalisi na biso , Yehova , apesá biso Liloba ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Le peuple était maintenu dans l’ignorance .</td>\n",
       "      <td>Bato mingi bazalaki na molili ya elimo .</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Notez que le terme ‘ supplier ’ emporte l’idée...</td>\n",
       "      <td>Tomoni ete Yesu asalelaki liloba “ malɔmbɔ , ”...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Consacrer sa vie à devenir riche n’est pas la ...</td>\n",
       "      <td>Komipesa mobimba na koluka bozwi epesaka eseng...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     source_sentence  \\\n",
       "0  parce que vous donnez le dixième de la menthe ...   \n",
       "1  Abraham n’a pas honte de pleurer , il ne cherc...   \n",
       "2  Il y a cependant un aspect de la Bible qui , p...   \n",
       "3  Or la solution la plus simple , dans l’esprit ...   \n",
       "4  ” Loin de faire table rase des coutumes popula...   \n",
       "5  L’amour que Paul éprouvait pour les gens l’a p...   \n",
       "6  Jéhovah est notre Auteur et , à ce titre , il ...   \n",
       "7        Le peuple était maintenu dans l’ignorance .   \n",
       "8  Notez que le terme ‘ supplier ’ emporte l’idée...   \n",
       "9  Consacrer sa vie à devenir riche n’est pas la ...   \n",
       "\n",
       "                                     target_sentence  \n",
       "0  mpamba te bopesaka moko ya zomi ya manti mpe y...  \n",
       "1  Na esika ete kolela yango ezala likambo ya nsɔ...  \n",
       "2  Nzokande , okomona elembo oyo ezali komonisa e...  \n",
       "3  Nzokande , na makanisi ya bato , nzela ya pɛtɛ...  \n",
       "4  Na esika ete bálongola mimeseno ya bapakano mp...  \n",
       "5  Lokola Paulo alingaki bato , yango etindaki ye...  \n",
       "6  Mozalisi na biso , Yehova , apesá biso Liloba ...  \n",
       "7           Bato mingi bazalaki na molili ya elimo .  \n",
       "8  Tomoni ete Yesu asalelaki liloba “ malɔmbɔ , ”...  \n",
       "9  Komipesa mobimba na koluka bozwi epesaka eseng...  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_without_duplicates.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(528304, 2)"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_without_duplicates.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "import time\n",
    "from fuzzywuzzy import process\n",
    "import numpy as np\n",
    "from os import cpu_count\n",
    "from functools import partial\n",
    "from multiprocessing import Pool"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "## reset the index after\n",
    "df_without_duplicates.reset_index(inplace=True, drop=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filtering function. Adjust pad to narrow down the candidate matches to\n",
    "# within a certain length of characters of the given sample.\n",
    "def fuzzfilter(sample, candidates, pad):\n",
    "    candidates = [x for x in candidates if len(x) <= len(sample)+pad and len(x) >= len(sample)-pad] \n",
    "    if len(candidates) > 0:\n",
    "        return process.extractOne(sample, candidates)[1]\n",
    "    else:\n",
    "        return np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '. .']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '» .']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․ ․']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '” ) .']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '◆ ◊ ◆']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '” » .']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '( . . . )']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '— ― ― ― ― ― ― ―']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '⇩']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '↓ ↓ ↓ ↓']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '● ● ● ● ●']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '’ ” .']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '’ ”']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '- - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '’ [ . . . ]']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '․']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '⇧']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '’ .']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '\\']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '» ) .']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '» ?']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '”']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '↓ ↓ ↓']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '[ . . . ]']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '↓ ↓']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '↓']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '” ’ ”']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '●']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '․ ․ ․']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '’ ?']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '․ ․ ․ ․ ․']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '” ’ ” .']\n",
      "WARNING:root:Applied processor reduces input query to empty string, all comparisons will have score 0. [Query: '” * .']\n"
     ]
    }
   ],
   "source": [
    "start_time = time.time()\n",
    "### iterating over pandas dataframe rows is not recomended, let use multi processing to apply the function\n",
    "\n",
    "with Pool(cpu_count()-1) as pool:\n",
    "    scores = pool.map(partial(fuzzfilter, candidates=list(fr_test_sents), pad=5), df_without_duplicates['source_sentence'])\n",
    "hours, rem = divmod(time.time() - start_time, 3600)\n",
    "minutes, seconds = divmod(rem, 60)\n",
    "print(\"done in {}h:{}min:{}seconds\".format(hours, minutes, seconds))\n",
    "\n",
    "# Filter out \"almost overlapping samples\"\n",
    "df_without_duplicates = df_without_duplicates.assign(scores=scores)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_without_duplicates = df_without_duplicates[df_without_duplicates['scores'] < 95]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {
    "scrolled": false
   },
   "outputs": [],
   "source": [
    "df_without_duplicates.to_csv('data_process_without_duplicates.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>source_sentence</th>\n",
       "      <th>target_sentence</th>\n",
       "      <th>scores</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>528294</th>\n",
       "      <td>528294</td>\n",
       "      <td>LE SOIR du 14 Nisan de l’an 33 de notre ère , ...</td>\n",
       "      <td>NA BUTU ya 14 Nisana ya mobu 33 T.B . , Yesu a...</td>\n",
       "      <td>54.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528295</th>\n",
       "      <td>528295</td>\n",
       "      <td>Le baptême — que les Témoins pratiquent par im...</td>\n",
       "      <td>Batisimo ​ — oyo Batemwe bapesaka na kozindisa...</td>\n",
       "      <td>56.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528296</th>\n",
       "      <td>528296</td>\n",
       "      <td>Paul a cité ces paroles d’Habaqouq : « Le just...</td>\n",
       "      <td>Ntoma Paulo azongelaki maloba ya Habakuku ntan...</td>\n",
       "      <td>59.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528297</th>\n",
       "      <td>528297</td>\n",
       "      <td>Pharaon , perplexe , convoque sur - le - champ...</td>\n",
       "      <td>Kobulunganisamáká na likamwisi wana , Falo abé...</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528298</th>\n",
       "      <td>528298</td>\n",
       "      <td>” Le médecin lui a alors vivement recommandé d...</td>\n",
       "      <td>Na yango , monganga asɛngaki ye alongola zemi ...</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528299</th>\n",
       "      <td>528299</td>\n",
       "      <td>Ils n’ont pas été témoins de la génération spo...</td>\n",
       "      <td>Bamoná naino te lolenge nini bomoi ebimaka pwa...</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528300</th>\n",
       "      <td>528300</td>\n",
       "      <td>La vérité et la Trinité</td>\n",
       "      <td>Solo mpe Bosato</td>\n",
       "      <td>43.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528301</th>\n",
       "      <td>528301</td>\n",
       "      <td>” Il est ensuite revenu à la table des matière...</td>\n",
       "      <td>Na nsima , afungolaki na lokasa oyo ezali na m...</td>\n",
       "      <td>55.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528302</th>\n",
       "      <td>528302</td>\n",
       "      <td>Elle peut vous protéger ou vous éviter d’agir ...</td>\n",
       "      <td>Yango ekoki kosalisa biso na komibatela to na ...</td>\n",
       "      <td>57.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>528303</th>\n",
       "      <td>528303</td>\n",
       "      <td>Il a envoyé un ange lui apporter une aide sur ...</td>\n",
       "      <td>Atindaki anzelu moko mpo na kopesa ye lisalisi...</td>\n",
       "      <td>54.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         index                                    source_sentence  \\\n",
       "528294  528294  LE SOIR du 14 Nisan de l’an 33 de notre ère , ...   \n",
       "528295  528295  Le baptême — que les Témoins pratiquent par im...   \n",
       "528296  528296  Paul a cité ces paroles d’Habaqouq : « Le just...   \n",
       "528297  528297  Pharaon , perplexe , convoque sur - le - champ...   \n",
       "528298  528298  ” Le médecin lui a alors vivement recommandé d...   \n",
       "528299  528299  Ils n’ont pas été témoins de la génération spo...   \n",
       "528300  528300                            La vérité et la Trinité   \n",
       "528301  528301  ” Il est ensuite revenu à la table des matière...   \n",
       "528302  528302  Elle peut vous protéger ou vous éviter d’agir ...   \n",
       "528303  528303  Il a envoyé un ange lui apporter une aide sur ...   \n",
       "\n",
       "                                          target_sentence  scores  \n",
       "528294  NA BUTU ya 14 Nisana ya mobu 33 T.B . , Yesu a...    54.0  \n",
       "528295  Batisimo ​ — oyo Batemwe bapesaka na kozindisa...    56.0  \n",
       "528296  Ntoma Paulo azongelaki maloba ya Habakuku ntan...    59.0  \n",
       "528297  Kobulunganisamáká na likamwisi wana , Falo abé...    53.0  \n",
       "528298  Na yango , monganga asɛngaki ye alongola zemi ...    53.0  \n",
       "528299  Bamoná naino te lolenge nini bomoi ebimaka pwa...    55.0  \n",
       "528300                                    Solo mpe Bosato    43.0  \n",
       "528301  Na nsima , afungolaki na lokasa oyo ezali na m...    55.0  \n",
       "528302  Yango ekoki kosalisa biso na komibatela to na ...    57.0  \n",
       "528303  Atindaki anzelu moko mpo na kopesa ye lisalisi...    54.0  "
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_without_duplicates.tail(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "splitting the data into train/test sets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "==> train.fr <==\n",
      "parce que vous donnez le dixième de la menthe et de l’aneth et du cumin , mais que vous avez laissé les points les plus importants de la Loi , à savoir la justice et la miséricorde et la fidélité . ” — Matthieu 23 : 23 .\n",
      "Abraham n’a pas honte de pleurer , il ne cherche pas à s’en cacher ; ses larmes sont l’expression d’un autre sentiment qui a dominé son existence : l’amour .\n",
      "Il y a cependant un aspect de la Bible qui , plus que tout autre , prouve son origine divine .\n",
      "Or la solution la plus simple , dans l’esprit du public , est de gagner à la loterie ou au loto sportif * .\n",
      "” Loin de faire table rase des coutumes populaires païennes et des rites magiques , le clergé ferma les yeux dessus et leur donna “ une signification chrétienne ” .\n",
      "L’amour que Paul éprouvait pour les gens l’a poussé à examiner soigneusement leurs pratiques religieuses .\n",
      "Jéhovah est notre Auteur et , à ce titre , il nous a donné sa Parole , la Bible , pour nous révéler la meilleure manière de vivre .\n",
      "Le peuple était maintenu dans l’ignorance .\n",
      "Notez que le terme ‘ supplier ’ emporte l’idée de prier avec beaucoup de ferveur .\n",
      "Consacrer sa vie à devenir riche n’est pas la voie du bonheur .\n",
      "\n",
      "==> train.ln <==\n",
      "mpamba te bopesaka moko ya zomi ya manti mpe ya aneti , mpe ya kumini , kasi bosili kotyola makambo ya Mibeko oyo ezali na ntina mingi , elingi koloba , bosembo mpe motema mawa mpe kondima . ” — Matai 23 : 23 .\n",
      "Na esika ete kolela yango ezala likambo ya nsɔni mpo na Abrahama , emonisi nde polele ezaleli mosusu ya malamu oyo Abrahama azalaki na yango : bolingo .\n",
      "Nzokande , okomona elembo oyo ezali komonisa ete Biblia eutaki mpenza epai na Nzambe .\n",
      "Nzokande , na makanisi ya bato , nzela ya pɛtɛɛ mpo na kozwa yango ezali kolónga na loterie to na momekano ya kosakola liboso équipe ya ndembo oyo ekolónga .\n",
      "Na esika ete bálongola mimeseno ya bapakano mpe milulu ya misala ya bilimu mabe , bakonzi ya mangomba bapesaki yango nzela mpe bakómisaki yango “ ya boklisto . ”\n",
      "Lokola Paulo alingaki bato , yango etindaki ye atalela malamumalamu makambo ya losambo na bango .\n",
      "Mozalisi na biso , Yehova , apesá biso Liloba na ye , Biblia , mpo na kolakisa biso ndenge tokoki kozala na bomoi ya malamu koleka .\n",
      "Bato mingi bazalaki na molili ya elimo .\n",
      "Tomoni ete Yesu asalelaki liloba “ malɔmbɔ , ” oyo ezali mabondeli ya mozindo .\n",
      "Komipesa mobimba na koluka bozwi epesaka esengo ya solosolo te .\n",
      "==> dev.fr <==\n",
      "Dans l’ensemble , David s’est montré un homme de foi .\n",
      "Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "Le récit déclare : “ Jéhovah plaça des hommes en embuscade contre les fils d’Ammôn , Moab et la région montagneuse de Séïr qui arrivaient en Juda , et ils se battirent entre eux .\n",
      "Peut - être comprenez - ​ vous ses proches .\n",
      "La capacité d’accepter une situation qui peut sembler loin d’être idéale dépend en grande partie de notre état d’esprit .\n",
      "À la maison , l’ambiance était chaleureuse et pleine d’amour , et mes parents m’ont enseigné des valeurs morales .\n",
      "Le bibliste Thomas Horne a dit qu ’ ‘ ils signalèrent le nombre d’occurrences de chaque lettre de l’alphabet [ hébreu ] dans l’ensemble des Écritures hébraïques ’ .\n",
      "Quand ils se marient , certains croient qu’ils vont vivre un conte de fées .\n",
      "\n",
      "==> dev.ln <==\n",
      "Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "Lisolo elobi boye : “ Yehova atyaki mibali oyo babombamaki mpo na kobimela bato ya Amona , Moaba mpe bangomba ya Seili oyo bazalaki koya na Yuda , mpe babundaki bango na bango .\n",
      "Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "Kondima likambo oyo ezali malamu mingi te etalelaka mingimingi makanisi oyo moto azali na yango .\n",
      "Nakolaki na libota oyo tozalaki kolingana mingi , mpe baboti na biso bateyaki ngai bizaleli malamu .\n",
      "Engebene nganga - mayele ya Biblia Thomas Hartwell Horne , batángaki “ mbala boni lɛtɛlɛ mokomoko ya alfabɛ [ ya Liebele ] ezongelamaki kati na Makomami ya Liebele . ”\n",
      "Bato mosusu oyo babalaka bakanisaka ete libala na bango ekokokana na makambo oyo bamonaka na bafilme ya bolingo .\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# We use 1000 dev test and the given test set.\n",
    "import csv\n",
    "\n",
    "# Do the split between dev/train and create parallel corpora\n",
    "num_dev_patterns = 1000\n",
    "\n",
    "# Optional: lower case the corpora - this will make it easier to generalize, but without proper casing.\n",
    "if lc:  # Julia: making lowercasing optional\n",
    "    df_without_duplicates[\"source_sentence\"] = df_without_duplicates[\"source_sentence\"].str.lower()\n",
    "    df_without_duplicates[\"target_sentence\"] = df_without_duplicates[\"target_sentence\"].str.lower()\n",
    "\n",
    "# Julia: test sets are already generated\n",
    "dev = df_without_duplicates.tail(num_dev_patterns) # Herman: Error in original\n",
    "stripped = df_without_duplicates.drop(df_without_duplicates.tail(num_dev_patterns).index)\n",
    "\n",
    "with open(\"train.\"+source_language, \"w\") as src_file, open(\"train.\"+target_language, \"w\") as trg_file:\n",
    "    for index, row in stripped.iterrows():\n",
    "        src_file.write(row[\"source_sentence\"]+\"\\n\")\n",
    "        trg_file.write(row[\"target_sentence\"]+\"\\n\")\n",
    "    \n",
    "with open(\"dev.\"+source_language, \"w\") as src_file, open(\"dev.\"+target_language, \"w\") as trg_file:\n",
    "    for index, row in dev.iterrows():\n",
    "        src_file.write(row[\"source_sentence\"]+\"\\n\")\n",
    "        trg_file.write(row[\"target_sentence\"]+\"\\n\")\n",
    "\n",
    "#stripped[[\"source_sentence\"]].to_csv(\"train.\"+source_language, header=False, index=False)  # Herman: Added `header=False` everywhere\n",
    "#stripped[[\"target_sentence\"]].to_csv(\"train.\"+target_language, header=False, index=False)  # Julia: Problematic handling of quotation marks.\n",
    "\n",
    "#dev[[\"source_sentence\"]].to_csv(\"dev.\"+source_language, header=False, index=False)\n",
    "#dev[[\"target_sentence\"]].to_csv(\"dev.\"+target_language, header=False, index=False)\n",
    "\n",
    "# Doublecheck the format below. There should be no extra quotation marks or weird characters.\n",
    "! head train.*\n",
    "! head dev.*"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "# checking if joeymnt is installed and skip the installation "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "joeynmt==0.0.1\r\n"
     ]
    }
   ],
   "source": [
    "!pip3 freeze | grep joeynmt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "subword-nmt==0.3.6\r\n"
     ]
    }
   ],
   "source": [
    "!pip3 freeze | grep subword-nmt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/usr/local/bin/subword-nmt\r\n"
     ]
    }
   ],
   "source": [
    "!which subword-nmt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Preprocessing the Data into Subword BPE Tokens\n",
    "\n",
    "- One of the most powerful improvements for agglutinative languages (a feature of most Bantu languages) is using BPE tokenization (Sennrich, 2015) .\n",
    "\n",
    "- It was also shown that by optimizing the umber of BPE codes we significantly improve results for low-resourced languages (Sennrich, 2019) (Martinus, 2019)\n",
    "\n",
    "- Below we have the scripts for doing BPE tokenization of our data. We use 4000 tokens as recommended by (Sennrich, 2019). You do not need to change anything. Simply running the below will be suitable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [],
   "source": [
    "from os import path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "create the new data folder from the working directory since joeymnt is already installed we are using another data folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "!mkdir data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Learn BPEs on the training data.\n",
    "os.environ[\"data_path\"] = path.join(\"data\", source_language + target_language) # Herma"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "! subword-nmt learn-joint-bpe-and-vocab --input train.$src train.$tgt -s 4000 -o bpe.codes.4000 --write-vocabulary vocab.$src vocab.$tgt\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Apply BPE splits to the development and test data.\n",
    "! subword-nmt apply-bpe -c bpe.codes.4000 --vocabulary vocab.$src < train.$src > train.bpe.$src\n",
    "! subword-nmt apply-bpe -c bpe.codes.4000 --vocabulary vocab.$tgt < train.$tgt > train.bpe.$tgt\n",
    "\n",
    "! subword-nmt apply-bpe -c bpe.codes.4000 --vocabulary vocab.$src < dev.$src > dev.bpe.$src\n",
    "! subword-nmt apply-bpe -c bpe.codes.4000 --vocabulary vocab.$tgt < dev.$tgt > dev.bpe.$tgt\n",
    "! subword-nmt apply-bpe -c bpe.codes.4000 --vocabulary vocab.$src < test.$src > test.bpe.$src\n",
    "! subword-nmt apply-bpe -c bpe.codes.4000 --vocabulary vocab.$tgt < test.$tgt > test.bpe.$tgt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "creating the data folder from my language and copying everything to it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "bpe.codes.4000\tdev.ln\t       test.en-ln.ln   train.bpe.fr\r\n",
      "dev.bpe.fr\ttest.bpe.fr    test.fr\t       train.bpe.ln\r\n",
      "dev.bpe.ln\ttest.bpe.ln    test.fr-any.fr  train.fr\r\n",
      "dev.fr\t\ttest.en-ln.en  test.ln\t       train.ln\r\n"
     ]
    }
   ],
   "source": [
    "! mkdir -p $data_path\n",
    "! cp train.* $data_path\n",
    "! cp test.* $data_path\n",
    "! cp dev.* $data_path\n",
    "! cp bpe.codes.4000 $data_path\n",
    "! ls $data_path"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Creating the vocabulary using joeymnt "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "getting the script manually and checking  and run it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--2020-02-17 07:33:34--  https://raw.githubusercontent.com/joeynmt/joeynmt/master/scripts/build_vocab.py\n",
      "Resolving raw.githubusercontent.com (raw.githubusercontent.com)... 151.101.192.133, 151.101.128.133, 151.101.64.133, ...\n",
      "Connecting to raw.githubusercontent.com (raw.githubusercontent.com)|151.101.192.133|:443... connected.\n",
      "HTTP request sent, awaiting response... 200 OK\n",
      "Length: 2034 (2.0K) [text/plain]\n",
      "Saving to: ‘build_vocab.py’\n",
      "\n",
      "build_vocab.py      100%[===================>]   1.99K  --.-KB/s    in 0s      \n",
      "\n",
      "2020-02-17 07:33:34 (32.2 MB/s) - ‘build_vocab.py’ saved [2034/2034]\n",
      "\n"
     ]
    }
   ],
   "source": [
    "!wget https://raw.githubusercontent.com/joeynmt/joeynmt/master/scripts/build_vocab.py"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "!python3 build_vocab.py data/$src$tgt/train.bpe.$src data/$src$tgt/train.bpe.$tgt --output_path data/$src$tgt/vocab.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "BPE Lingala Sentences\n",
      "Yango wana , ezali na ntina mingi ete baboti bá@@ koba koteya bana na bango . ”\n",
      "Tiká bana na yo bá@@ mona ete Yehova azali mpenza solo na miso na yo .\n",
      "B@@ alobi boye : “ T@@ oy@@ ebisaki mpe mwana na biso ya mwasi ya liboso ‘ aty@@ ela Yehova motema mobimba , ak@@ oba komipesa na mosala ya Bokonzi , mpe am@@ itung@@ isa mingi te . ’\n",
      "Ntango amonaki ndenge likambo yango es@@ ukaki , ayebaki ete Yehova azalaki kosalisa biso .\n",
      "Yango ekóm@@ isaki makasi kondima na ye epai ya Nzambe mpe na Biblia . ”\n",
      "Combined BPE Vocab\n",
      "β\n",
      "Ñ@@\n",
      "poque\n",
      "Ê\n",
      "ō@@\n",
      "ă\n",
      "ά@@\n",
      "κ@@\n",
      "ʽ\n",
      "d’hui\n"
     ]
    }
   ],
   "source": [
    "# Some output\n",
    "! echo \"BPE Lingala Sentences\"\n",
    "! tail -n 5 test.bpe.$tgt\n",
    "! echo \"Combined BPE Vocab\"\n",
    "! tail -n 10 data/$src$tgt/vocab.txt "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating the JoeyNMT Config\n",
    "\n",
    "JoeyNMT requires a yaml config. We provide a template below. We've also set a number of defaults with it, that you may play with!\n",
    "\n",
    "- We used Transformer architecture\n",
    "- We set our dropout to reasonably high: 0.3 (recommended in (Sennrich, 2019))\n",
    "Things worth playing with:\n",
    "\n",
    "- The batch size (also recommended to change for low-resourced languages)\n",
    "- The number of epochs (we've set it at 30 just so it runs in about an hour, for testing purposes)\n",
    "- The decoder options (beam_size, alpha)\n",
    "Evaluation metrics (BLEU versus Crhf4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "JW300_latest_xml_fr-ln.xml\t     dev.fr\t     test.fr-any.fr\r\n",
      "JW300_latest_xml_fr.zip\t\t     dev.ln\t     test.ln\r\n",
      "JW300_latest_xml_ln.zip\t\t     fr-ln-baseline  train.bpe.fr\r\n",
      "baseline.ipynb\t\t\t     jw300.fr\t     train.bpe.ln\r\n",
      "bpe.codes.4000\t\t\t     jw300.ln\t     train.fr\r\n",
      "build_vocab.py\t\t\t     test.bpe.fr     train.ln\r\n",
      "data\t\t\t\t     test.bpe.ln     vocab.fr\r\n",
      "data_process_without_duplicates.csv  test.en-ln.en   vocab.ln\r\n",
      "dev.bpe.fr\t\t\t     test.en-ln.ln\r\n",
      "dev.bpe.ln\t\t\t     test.fr\r\n"
     ]
    }
   ],
   "source": [
    "!ls "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "remove the old model folder"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "! rm -fr models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "!mkdir models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "!mkdir config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This creates the config file for our JoeyNMT system. It might seem overwhelming so we've provided a couple of useful parameters you'll need to update\n",
    "# (You can of course play with all the parameters if you'd like!)\n",
    "\n",
    "name = '{}{}'.format(source_language, target_language)\n",
    "gdrive_path = os.environ[\"gdrive_path\"]\n",
    "\n",
    "# Create the config\n",
    "config = \"\"\"\n",
    "name: \"{name}_transformer\"\n",
    "\n",
    "data:\n",
    "    src: \"{source_language}\"\n",
    "    trg: \"{target_language}\"\n",
    "    train: \"data/{name}/train.bpe\"\n",
    "    dev:   \"data/{name}/dev.bpe\"\n",
    "    test:  \"data/{name}/test.bpe\"\n",
    "    level: \"bpe\"\n",
    "    lowercase: False\n",
    "    max_sent_length: 100\n",
    "    src_vocab: \"data/{name}/vocab.txt\"\n",
    "    trg_vocab: \"data/{name}/vocab.txt\"\n",
    "\n",
    "testing:\n",
    "    beam_size: 5\n",
    "    alpha: 1.0\n",
    "\n",
    "training:\n",
    "    #load_model: \"{gdrive_path}/models/{name}_transformer/1.ckpt\" # if uncommented, load a pre-trained model from this checkpoint\n",
    "    random_seed: 42\n",
    "    optimizer: \"adam\"\n",
    "    normalization: \"tokens\"\n",
    "    adam_betas: [0.9, 0.999] \n",
    "    scheduling: \"plateau\"           # TODO: try switching from plateau to Noam scheduling\n",
    "    patience: 5                     # For plateau: decrease learning rate by decrease_factor if validation score has not improved for this many validation rounds.\n",
    "    learning_rate_factor: 0.5       # factor for Noam scheduler (used with Transformer)\n",
    "    learning_rate_warmup: 1000      # warmup steps for Noam scheduler (used with Transformer)\n",
    "    decrease_factor: 0.7\n",
    "    loss: \"crossentropy\"\n",
    "    learning_rate: 0.0003\n",
    "    learning_rate_min: 0.00000001\n",
    "    weight_decay: 0.0\n",
    "    label_smoothing: 0.1\n",
    "    batch_size: 4096\n",
    "    batch_type: \"token\"\n",
    "    eval_batch_size: 3600\n",
    "    eval_batch_type: \"token\"\n",
    "    batch_multiplier: 1\n",
    "    early_stopping_metric: \"ppl\"\n",
    "    epochs: 50                     # TODO: Decrease for when playing around and checking of working. Around 30 is sufficient to check if its working at all\n",
    "    validation_freq: 1000          # TODO: Set to at least once per epoch.\n",
    "    logging_freq: 100\n",
    "    eval_metric: \"bleu\"\n",
    "    model_dir: \"models/{name}_transformer\"\n",
    "    overwrite: False               # TODO: Set to True if you want to overwrite possibly existing models. \n",
    "    shuffle: True\n",
    "    use_cuda: True\n",
    "    max_output_length: 100\n",
    "    print_valid_sents: [0, 1, 2, 3, 5, 10]\n",
    "    keep_last_ckpts: 3\n",
    "\n",
    "model:\n",
    "    initializer: \"xavier\"\n",
    "    bias_initializer: \"zeros\"\n",
    "    init_gain: 1.0\n",
    "    embed_initializer: \"xavier\"\n",
    "    embed_init_gain: 1.0\n",
    "    tied_embeddings: True\n",
    "    tied_softmax: True\n",
    "    encoder:\n",
    "        type: \"transformer\"\n",
    "        num_layers: 6\n",
    "        num_heads: 4             # TODO: Increase to 8 for larger data.\n",
    "        embeddings:\n",
    "            embedding_dim: 256   # TODO: Increase to 512 for larger data.\n",
    "            scale: True\n",
    "            dropout: 0.2\n",
    "        # typically ff_size = 4 x hidden_size\n",
    "        hidden_size: 256         # TODO: Increase to 512 for larger data.\n",
    "        ff_size: 1024            # TODO: Increase to 2048 for larger data.\n",
    "        dropout: 0.3\n",
    "    decoder:\n",
    "        type: \"transformer\"\n",
    "        num_layers: 6\n",
    "        num_heads: 4              # TODO: Increase to 8 for larger data.\n",
    "        embeddings:\n",
    "            embedding_dim: 256    # TODO: Increase to 512 for larger data.\n",
    "            scale: True\n",
    "            dropout: 0.2\n",
    "        # typically ff_size = 4 x hidden_size\n",
    "        hidden_size: 256         # TODO: Increase to 512 for larger data.\n",
    "        ff_size: 1024            # TODO: Increase to 2048 for larger data.\n",
    "        dropout: 0.3\n",
    "\"\"\".format(name=name, gdrive_path=os.environ[\"gdrive_path\"], source_language=source_language, target_language=target_language)\n",
    "with open(\"config/transformer_{name}.yaml\".format(name=name),'w') as f:\n",
    "    f.write(config)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "transformer_frln.yaml\r\n"
     ]
    }
   ],
   "source": [
    "!ls config"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'frln'"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "name"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train the Model"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Trying to fix the issue with tensorboard not found"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "tensorboard==1.14.0\r\n"
     ]
    }
   ],
   "source": [
    "!pip3 freeze | grep tensorboard"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Collecting tensorboard==1.14.0\n",
      "  Using cached https://files.pythonhosted.org/packages/91/2d/2ed263449a078cd9c8a9ba50ebd50123adf1f8cfbea1492f9084169b89d9/tensorboard-1.14.0-py3-none-any.whl\n",
      "Collecting absl-py>=0.4 (from tensorboard==1.14.0)\n",
      "Collecting wheel>=0.26; python_version >= \"3\" (from tensorboard==1.14.0)\n",
      "  Downloading https://files.pythonhosted.org/packages/8c/23/848298cccf8e40f5bbb59009b32848a4c38f4e7f3364297ab3c3e2e2cd14/wheel-0.34.2-py2.py3-none-any.whl\n",
      "Collecting markdown>=2.6.8 (from tensorboard==1.14.0)\n",
      "  Downloading https://files.pythonhosted.org/packages/ab/c4/ba46d44855e6eb1770a12edace5a165a0c6de13349f592b9036257f3c3d3/Markdown-3.2.1-py2.py3-none-any.whl (88kB)\n",
      "\u001b[K    100% |████████████████████████████████| 92kB 3.4MB/s ta 0:00:011\n",
      "\u001b[?25hCollecting grpcio>=1.6.3 (from tensorboard==1.14.0)\n",
      "  Downloading https://files.pythonhosted.org/packages/f1/97/bece4417f349f8f83252232ef66ea63eb47f8044ca61b51e2a478e2c7a94/grpcio-1.27.2-cp36-cp36m-manylinux1_x86_64.whl (2.7MB)\n",
      "\u001b[K    100% |████████████████████████████████| 2.7MB 528kB/s eta 0:00:01\n",
      "\u001b[?25hCollecting werkzeug>=0.11.15 (from tensorboard==1.14.0)\n",
      "  Downloading https://files.pythonhosted.org/packages/ba/a5/d6f8a6e71f15364d35678a4ec8a0186f980b3bd2545f40ad51dd26a87fb1/Werkzeug-1.0.0-py2.py3-none-any.whl (298kB)\n",
      "\u001b[K    100% |████████████████████████████████| 307kB 4.6MB/s eta 0:00:01\n",
      "\u001b[?25hCollecting six>=1.10.0 (from tensorboard==1.14.0)\n",
      "  Using cached https://files.pythonhosted.org/packages/65/eb/1f97cb97bfc2390a276969c6fae16075da282f5058082d4cb10c6c5c1dba/six-1.14.0-py2.py3-none-any.whl\n",
      "Collecting protobuf>=3.6.0 (from tensorboard==1.14.0)\n",
      "  Downloading https://files.pythonhosted.org/packages/57/02/5432412c162989260fab61fa65e0a490c1872739eb91a659896e4d554b26/protobuf-3.11.3-cp36-cp36m-manylinux1_x86_64.whl (1.3MB)\n",
      "\u001b[K    100% |████████████████████████████████| 1.3MB 1.1MB/s eta 0:00:01\n",
      "\u001b[?25hCollecting numpy>=1.12.0 (from tensorboard==1.14.0)\n",
      "  Using cached https://files.pythonhosted.org/packages/62/20/4d43e141b5bc426ba38274933ef8e76e85c7adea2c321ecf9ebf7421cedf/numpy-1.18.1-cp36-cp36m-manylinux1_x86_64.whl\n",
      "Collecting setuptools>=41.0.0 (from tensorboard==1.14.0)\n",
      "  Downloading https://files.pythonhosted.org/packages/3d/72/1c1498c1e908e0562b1e1cd30012580baa7d33b5b0ffdbeb5fde2462cc71/setuptools-45.2.0-py3-none-any.whl (584kB)\n",
      "\u001b[K    100% |████████████████████████████████| 593kB 2.6MB/s eta 0:00:01\n",
      "\u001b[?25hInstalling collected packages: six, absl-py, wheel, setuptools, markdown, grpcio, werkzeug, protobuf, numpy, tensorboard\n",
      "Successfully installed absl-py-0.9.0 grpcio-1.27.2 markdown-3.2.1 numpy-1.18.1 protobuf-3.11.3 setuptools-45.2.0 six-1.14.0 tensorboard-1.14.0 werkzeug-1.0.0 wheel-0.34.2\n"
     ]
    }
   ],
   "source": [
    "!pip3 install tensorboard==1.14.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {},
   "outputs": [],
   "source": [
    "#!pip3 install --upgrade torch"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This single line of joeynmt runs the training using the config we made above"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n",
      "2020-02-17 07:37:22,763 Hello! This is Joey-NMT.\n",
      "2020-02-17 07:37:22,769 Total params: 12195584\n",
      "2020-02-17 07:37:22,771 Trainable parameters: ['decoder.layer_norm.bias', 'decoder.layer_norm.weight', 'decoder.layers.0.dec_layer_norm.bias', 'decoder.layers.0.dec_layer_norm.weight', 'decoder.layers.0.feed_forward.layer_norm.bias', 'decoder.layers.0.feed_forward.layer_norm.weight', 'decoder.layers.0.feed_forward.pwff_layer.0.bias', 'decoder.layers.0.feed_forward.pwff_layer.0.weight', 'decoder.layers.0.feed_forward.pwff_layer.3.bias', 'decoder.layers.0.feed_forward.pwff_layer.3.weight', 'decoder.layers.0.src_trg_att.k_layer.bias', 'decoder.layers.0.src_trg_att.k_layer.weight', 'decoder.layers.0.src_trg_att.output_layer.bias', 'decoder.layers.0.src_trg_att.output_layer.weight', 'decoder.layers.0.src_trg_att.q_layer.bias', 'decoder.layers.0.src_trg_att.q_layer.weight', 'decoder.layers.0.src_trg_att.v_layer.bias', 'decoder.layers.0.src_trg_att.v_layer.weight', 'decoder.layers.0.trg_trg_att.k_layer.bias', 'decoder.layers.0.trg_trg_att.k_layer.weight', 'decoder.layers.0.trg_trg_att.output_layer.bias', 'decoder.layers.0.trg_trg_att.output_layer.weight', 'decoder.layers.0.trg_trg_att.q_layer.bias', 'decoder.layers.0.trg_trg_att.q_layer.weight', 'decoder.layers.0.trg_trg_att.v_layer.bias', 'decoder.layers.0.trg_trg_att.v_layer.weight', 'decoder.layers.0.x_layer_norm.bias', 'decoder.layers.0.x_layer_norm.weight', 'decoder.layers.1.dec_layer_norm.bias', 'decoder.layers.1.dec_layer_norm.weight', 'decoder.layers.1.feed_forward.layer_norm.bias', 'decoder.layers.1.feed_forward.layer_norm.weight', 'decoder.layers.1.feed_forward.pwff_layer.0.bias', 'decoder.layers.1.feed_forward.pwff_layer.0.weight', 'decoder.layers.1.feed_forward.pwff_layer.3.bias', 'decoder.layers.1.feed_forward.pwff_layer.3.weight', 'decoder.layers.1.src_trg_att.k_layer.bias', 'decoder.layers.1.src_trg_att.k_layer.weight', 'decoder.layers.1.src_trg_att.output_layer.bias', 'decoder.layers.1.src_trg_att.output_layer.weight', 'decoder.layers.1.src_trg_att.q_layer.bias', 'decoder.layers.1.src_trg_att.q_layer.weight', 'decoder.layers.1.src_trg_att.v_layer.bias', 'decoder.layers.1.src_trg_att.v_layer.weight', 'decoder.layers.1.trg_trg_att.k_layer.bias', 'decoder.layers.1.trg_trg_att.k_layer.weight', 'decoder.layers.1.trg_trg_att.output_layer.bias', 'decoder.layers.1.trg_trg_att.output_layer.weight', 'decoder.layers.1.trg_trg_att.q_layer.bias', 'decoder.layers.1.trg_trg_att.q_layer.weight', 'decoder.layers.1.trg_trg_att.v_layer.bias', 'decoder.layers.1.trg_trg_att.v_layer.weight', 'decoder.layers.1.x_layer_norm.bias', 'decoder.layers.1.x_layer_norm.weight', 'decoder.layers.2.dec_layer_norm.bias', 'decoder.layers.2.dec_layer_norm.weight', 'decoder.layers.2.feed_forward.layer_norm.bias', 'decoder.layers.2.feed_forward.layer_norm.weight', 'decoder.layers.2.feed_forward.pwff_layer.0.bias', 'decoder.layers.2.feed_forward.pwff_layer.0.weight', 'decoder.layers.2.feed_forward.pwff_layer.3.bias', 'decoder.layers.2.feed_forward.pwff_layer.3.weight', 'decoder.layers.2.src_trg_att.k_layer.bias', 'decoder.layers.2.src_trg_att.k_layer.weight', 'decoder.layers.2.src_trg_att.output_layer.bias', 'decoder.layers.2.src_trg_att.output_layer.weight', 'decoder.layers.2.src_trg_att.q_layer.bias', 'decoder.layers.2.src_trg_att.q_layer.weight', 'decoder.layers.2.src_trg_att.v_layer.bias', 'decoder.layers.2.src_trg_att.v_layer.weight', 'decoder.layers.2.trg_trg_att.k_layer.bias', 'decoder.layers.2.trg_trg_att.k_layer.weight', 'decoder.layers.2.trg_trg_att.output_layer.bias', 'decoder.layers.2.trg_trg_att.output_layer.weight', 'decoder.layers.2.trg_trg_att.q_layer.bias', 'decoder.layers.2.trg_trg_att.q_layer.weight', 'decoder.layers.2.trg_trg_att.v_layer.bias', 'decoder.layers.2.trg_trg_att.v_layer.weight', 'decoder.layers.2.x_layer_norm.bias', 'decoder.layers.2.x_layer_norm.weight', 'decoder.layers.3.dec_layer_norm.bias', 'decoder.layers.3.dec_layer_norm.weight', 'decoder.layers.3.feed_forward.layer_norm.bias', 'decoder.layers.3.feed_forward.layer_norm.weight', 'decoder.layers.3.feed_forward.pwff_layer.0.bias', 'decoder.layers.3.feed_forward.pwff_layer.0.weight', 'decoder.layers.3.feed_forward.pwff_layer.3.bias', 'decoder.layers.3.feed_forward.pwff_layer.3.weight', 'decoder.layers.3.src_trg_att.k_layer.bias', 'decoder.layers.3.src_trg_att.k_layer.weight', 'decoder.layers.3.src_trg_att.output_layer.bias', 'decoder.layers.3.src_trg_att.output_layer.weight', 'decoder.layers.3.src_trg_att.q_layer.bias', 'decoder.layers.3.src_trg_att.q_layer.weight', 'decoder.layers.3.src_trg_att.v_layer.bias', 'decoder.layers.3.src_trg_att.v_layer.weight', 'decoder.layers.3.trg_trg_att.k_layer.bias', 'decoder.layers.3.trg_trg_att.k_layer.weight', 'decoder.layers.3.trg_trg_att.output_layer.bias', 'decoder.layers.3.trg_trg_att.output_layer.weight', 'decoder.layers.3.trg_trg_att.q_layer.bias', 'decoder.layers.3.trg_trg_att.q_layer.weight', 'decoder.layers.3.trg_trg_att.v_layer.bias', 'decoder.layers.3.trg_trg_att.v_layer.weight', 'decoder.layers.3.x_layer_norm.bias', 'decoder.layers.3.x_layer_norm.weight', 'decoder.layers.4.dec_layer_norm.bias', 'decoder.layers.4.dec_layer_norm.weight', 'decoder.layers.4.feed_forward.layer_norm.bias', 'decoder.layers.4.feed_forward.layer_norm.weight', 'decoder.layers.4.feed_forward.pwff_layer.0.bias', 'decoder.layers.4.feed_forward.pwff_layer.0.weight', 'decoder.layers.4.feed_forward.pwff_layer.3.bias', 'decoder.layers.4.feed_forward.pwff_layer.3.weight', 'decoder.layers.4.src_trg_att.k_layer.bias', 'decoder.layers.4.src_trg_att.k_layer.weight', 'decoder.layers.4.src_trg_att.output_layer.bias', 'decoder.layers.4.src_trg_att.output_layer.weight', 'decoder.layers.4.src_trg_att.q_layer.bias', 'decoder.layers.4.src_trg_att.q_layer.weight', 'decoder.layers.4.src_trg_att.v_layer.bias', 'decoder.layers.4.src_trg_att.v_layer.weight', 'decoder.layers.4.trg_trg_att.k_layer.bias', 'decoder.layers.4.trg_trg_att.k_layer.weight', 'decoder.layers.4.trg_trg_att.output_layer.bias', 'decoder.layers.4.trg_trg_att.output_layer.weight', 'decoder.layers.4.trg_trg_att.q_layer.bias', 'decoder.layers.4.trg_trg_att.q_layer.weight', 'decoder.layers.4.trg_trg_att.v_layer.bias', 'decoder.layers.4.trg_trg_att.v_layer.weight', 'decoder.layers.4.x_layer_norm.bias', 'decoder.layers.4.x_layer_norm.weight', 'decoder.layers.5.dec_layer_norm.bias', 'decoder.layers.5.dec_layer_norm.weight', 'decoder.layers.5.feed_forward.layer_norm.bias', 'decoder.layers.5.feed_forward.layer_norm.weight', 'decoder.layers.5.feed_forward.pwff_layer.0.bias', 'decoder.layers.5.feed_forward.pwff_layer.0.weight', 'decoder.layers.5.feed_forward.pwff_layer.3.bias', 'decoder.layers.5.feed_forward.pwff_layer.3.weight', 'decoder.layers.5.src_trg_att.k_layer.bias', 'decoder.layers.5.src_trg_att.k_layer.weight', 'decoder.layers.5.src_trg_att.output_layer.bias', 'decoder.layers.5.src_trg_att.output_layer.weight', 'decoder.layers.5.src_trg_att.q_layer.bias', 'decoder.layers.5.src_trg_att.q_layer.weight', 'decoder.layers.5.src_trg_att.v_layer.bias', 'decoder.layers.5.src_trg_att.v_layer.weight', 'decoder.layers.5.trg_trg_att.k_layer.bias', 'decoder.layers.5.trg_trg_att.k_layer.weight', 'decoder.layers.5.trg_trg_att.output_layer.bias', 'decoder.layers.5.trg_trg_att.output_layer.weight', 'decoder.layers.5.trg_trg_att.q_layer.bias', 'decoder.layers.5.trg_trg_att.q_layer.weight', 'decoder.layers.5.trg_trg_att.v_layer.bias', 'decoder.layers.5.trg_trg_att.v_layer.weight', 'decoder.layers.5.x_layer_norm.bias', 'decoder.layers.5.x_layer_norm.weight', 'encoder.layer_norm.bias', 'encoder.layer_norm.weight', 'encoder.layers.0.feed_forward.layer_norm.bias', 'encoder.layers.0.feed_forward.layer_norm.weight', 'encoder.layers.0.feed_forward.pwff_layer.0.bias', 'encoder.layers.0.feed_forward.pwff_layer.0.weight', 'encoder.layers.0.feed_forward.pwff_layer.3.bias', 'encoder.layers.0.feed_forward.pwff_layer.3.weight', 'encoder.layers.0.layer_norm.bias', 'encoder.layers.0.layer_norm.weight', 'encoder.layers.0.src_src_att.k_layer.bias', 'encoder.layers.0.src_src_att.k_layer.weight', 'encoder.layers.0.src_src_att.output_layer.bias', 'encoder.layers.0.src_src_att.output_layer.weight', 'encoder.layers.0.src_src_att.q_layer.bias', 'encoder.layers.0.src_src_att.q_layer.weight', 'encoder.layers.0.src_src_att.v_layer.bias', 'encoder.layers.0.src_src_att.v_layer.weight', 'encoder.layers.1.feed_forward.layer_norm.bias', 'encoder.layers.1.feed_forward.layer_norm.weight', 'encoder.layers.1.feed_forward.pwff_layer.0.bias', 'encoder.layers.1.feed_forward.pwff_layer.0.weight', 'encoder.layers.1.feed_forward.pwff_layer.3.bias', 'encoder.layers.1.feed_forward.pwff_layer.3.weight', 'encoder.layers.1.layer_norm.bias', 'encoder.layers.1.layer_norm.weight', 'encoder.layers.1.src_src_att.k_layer.bias', 'encoder.layers.1.src_src_att.k_layer.weight', 'encoder.layers.1.src_src_att.output_layer.bias', 'encoder.layers.1.src_src_att.output_layer.weight', 'encoder.layers.1.src_src_att.q_layer.bias', 'encoder.layers.1.src_src_att.q_layer.weight', 'encoder.layers.1.src_src_att.v_layer.bias', 'encoder.layers.1.src_src_att.v_layer.weight', 'encoder.layers.2.feed_forward.layer_norm.bias', 'encoder.layers.2.feed_forward.layer_norm.weight', 'encoder.layers.2.feed_forward.pwff_layer.0.bias', 'encoder.layers.2.feed_forward.pwff_layer.0.weight', 'encoder.layers.2.feed_forward.pwff_layer.3.bias', 'encoder.layers.2.feed_forward.pwff_layer.3.weight', 'encoder.layers.2.layer_norm.bias', 'encoder.layers.2.layer_norm.weight', 'encoder.layers.2.src_src_att.k_layer.bias', 'encoder.layers.2.src_src_att.k_layer.weight', 'encoder.layers.2.src_src_att.output_layer.bias', 'encoder.layers.2.src_src_att.output_layer.weight', 'encoder.layers.2.src_src_att.q_layer.bias', 'encoder.layers.2.src_src_att.q_layer.weight', 'encoder.layers.2.src_src_att.v_layer.bias', 'encoder.layers.2.src_src_att.v_layer.weight', 'encoder.layers.3.feed_forward.layer_norm.bias', 'encoder.layers.3.feed_forward.layer_norm.weight', 'encoder.layers.3.feed_forward.pwff_layer.0.bias', 'encoder.layers.3.feed_forward.pwff_layer.0.weight', 'encoder.layers.3.feed_forward.pwff_layer.3.bias', 'encoder.layers.3.feed_forward.pwff_layer.3.weight', 'encoder.layers.3.layer_norm.bias', 'encoder.layers.3.layer_norm.weight', 'encoder.layers.3.src_src_att.k_layer.bias', 'encoder.layers.3.src_src_att.k_layer.weight', 'encoder.layers.3.src_src_att.output_layer.bias', 'encoder.layers.3.src_src_att.output_layer.weight', 'encoder.layers.3.src_src_att.q_layer.bias', 'encoder.layers.3.src_src_att.q_layer.weight', 'encoder.layers.3.src_src_att.v_layer.bias', 'encoder.layers.3.src_src_att.v_layer.weight', 'encoder.layers.4.feed_forward.layer_norm.bias', 'encoder.layers.4.feed_forward.layer_norm.weight', 'encoder.layers.4.feed_forward.pwff_layer.0.bias', 'encoder.layers.4.feed_forward.pwff_layer.0.weight', 'encoder.layers.4.feed_forward.pwff_layer.3.bias', 'encoder.layers.4.feed_forward.pwff_layer.3.weight', 'encoder.layers.4.layer_norm.bias', 'encoder.layers.4.layer_norm.weight', 'encoder.layers.4.src_src_att.k_layer.bias', 'encoder.layers.4.src_src_att.k_layer.weight', 'encoder.layers.4.src_src_att.output_layer.bias', 'encoder.layers.4.src_src_att.output_layer.weight', 'encoder.layers.4.src_src_att.q_layer.bias', 'encoder.layers.4.src_src_att.q_layer.weight', 'encoder.layers.4.src_src_att.v_layer.bias', 'encoder.layers.4.src_src_att.v_layer.weight', 'encoder.layers.5.feed_forward.layer_norm.bias', 'encoder.layers.5.feed_forward.layer_norm.weight', 'encoder.layers.5.feed_forward.pwff_layer.0.bias', 'encoder.layers.5.feed_forward.pwff_layer.0.weight', 'encoder.layers.5.feed_forward.pwff_layer.3.bias', 'encoder.layers.5.feed_forward.pwff_layer.3.weight', 'encoder.layers.5.layer_norm.bias', 'encoder.layers.5.layer_norm.weight', 'encoder.layers.5.src_src_att.k_layer.bias', 'encoder.layers.5.src_src_att.k_layer.weight', 'encoder.layers.5.src_src_att.output_layer.bias', 'encoder.layers.5.src_src_att.output_layer.weight', 'encoder.layers.5.src_src_att.q_layer.bias', 'encoder.layers.5.src_src_att.q_layer.weight', 'encoder.layers.5.src_src_att.v_layer.bias', 'encoder.layers.5.src_src_att.v_layer.weight', 'src_embed.lut.weight']\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 07:37:27,953 cfg.name                           : frln_transformer\n",
      "2020-02-17 07:37:27,953 cfg.data.src                       : fr\n",
      "2020-02-17 07:37:27,953 cfg.data.trg                       : ln\n",
      "2020-02-17 07:37:27,953 cfg.data.train                     : data/frln/train.bpe\n",
      "2020-02-17 07:37:27,953 cfg.data.dev                       : data/frln/dev.bpe\n",
      "2020-02-17 07:37:27,954 cfg.data.test                      : data/frln/test.bpe\n",
      "2020-02-17 07:37:27,954 cfg.data.level                     : bpe\n",
      "2020-02-17 07:37:27,954 cfg.data.lowercase                 : False\n",
      "2020-02-17 07:37:27,954 cfg.data.max_sent_length           : 100\n",
      "2020-02-17 07:37:27,954 cfg.data.src_vocab                 : data/frln/vocab.txt\n",
      "2020-02-17 07:37:27,954 cfg.data.trg_vocab                 : data/frln/vocab.txt\n",
      "2020-02-17 07:37:27,954 cfg.testing.beam_size              : 5\n",
      "2020-02-17 07:37:27,954 cfg.testing.alpha                  : 1.0\n",
      "2020-02-17 07:37:27,954 cfg.training.random_seed           : 42\n",
      "2020-02-17 07:37:27,954 cfg.training.optimizer             : adam\n",
      "2020-02-17 07:37:27,954 cfg.training.normalization         : tokens\n",
      "2020-02-17 07:37:27,954 cfg.training.adam_betas            : [0.9, 0.999]\n",
      "2020-02-17 07:37:27,954 cfg.training.scheduling            : plateau\n",
      "2020-02-17 07:37:27,954 cfg.training.patience              : 5\n",
      "2020-02-17 07:37:27,954 cfg.training.learning_rate_factor  : 0.5\n",
      "2020-02-17 07:37:27,955 cfg.training.learning_rate_warmup  : 1000\n",
      "2020-02-17 07:37:27,955 cfg.training.decrease_factor       : 0.7\n",
      "2020-02-17 07:37:27,955 cfg.training.loss                  : crossentropy\n",
      "2020-02-17 07:37:27,955 cfg.training.learning_rate         : 0.0003\n",
      "2020-02-17 07:37:27,955 cfg.training.learning_rate_min     : 1e-08\n",
      "2020-02-17 07:37:27,955 cfg.training.weight_decay          : 0.0\n",
      "2020-02-17 07:37:27,955 cfg.training.label_smoothing       : 0.1\n",
      "2020-02-17 07:37:27,955 cfg.training.batch_size            : 4096\n",
      "2020-02-17 07:37:27,955 cfg.training.batch_type            : token\n",
      "2020-02-17 07:37:27,955 cfg.training.eval_batch_size       : 3600\n",
      "2020-02-17 07:37:27,955 cfg.training.eval_batch_type       : token\n",
      "2020-02-17 07:37:27,955 cfg.training.batch_multiplier      : 1\n",
      "2020-02-17 07:37:27,955 cfg.training.early_stopping_metric : ppl\n",
      "2020-02-17 07:37:27,955 cfg.training.epochs                : 50\n",
      "2020-02-17 07:37:27,955 cfg.training.validation_freq       : 1000\n",
      "2020-02-17 07:37:27,955 cfg.training.logging_freq          : 100\n",
      "2020-02-17 07:37:27,956 cfg.training.eval_metric           : bleu\n",
      "2020-02-17 07:37:27,956 cfg.training.model_dir             : models/frln_transformer\n",
      "2020-02-17 07:37:27,956 cfg.training.overwrite             : False\n",
      "2020-02-17 07:37:27,956 cfg.training.shuffle               : True\n",
      "2020-02-17 07:37:27,956 cfg.training.use_cuda              : True\n",
      "2020-02-17 07:37:27,956 cfg.training.max_output_length     : 100\n",
      "2020-02-17 07:37:27,956 cfg.training.print_valid_sents     : [0, 1, 2, 3, 5, 10]\n",
      "2020-02-17 07:37:27,956 cfg.training.keep_last_ckpts       : 3\n",
      "2020-02-17 07:37:27,956 cfg.model.initializer              : xavier\n",
      "2020-02-17 07:37:27,956 cfg.model.bias_initializer         : zeros\n",
      "2020-02-17 07:37:27,956 cfg.model.init_gain                : 1.0\n",
      "2020-02-17 07:37:27,956 cfg.model.embed_initializer        : xavier\n",
      "2020-02-17 07:37:27,956 cfg.model.embed_init_gain          : 1.0\n",
      "2020-02-17 07:37:27,956 cfg.model.tied_embeddings          : True\n",
      "2020-02-17 07:37:27,956 cfg.model.tied_softmax             : True\n",
      "2020-02-17 07:37:27,957 cfg.model.encoder.type             : transformer\n",
      "2020-02-17 07:37:27,957 cfg.model.encoder.num_layers       : 6\n",
      "2020-02-17 07:37:27,957 cfg.model.encoder.num_heads        : 4\n",
      "2020-02-17 07:37:27,957 cfg.model.encoder.embeddings.embedding_dim : 256\n",
      "2020-02-17 07:37:27,957 cfg.model.encoder.embeddings.scale : True\n",
      "2020-02-17 07:37:27,957 cfg.model.encoder.embeddings.dropout : 0.2\n",
      "2020-02-17 07:37:27,957 cfg.model.encoder.hidden_size      : 256\n",
      "2020-02-17 07:37:27,957 cfg.model.encoder.ff_size          : 1024\n",
      "2020-02-17 07:37:27,957 cfg.model.encoder.dropout          : 0.3\n",
      "2020-02-17 07:37:27,957 cfg.model.decoder.type             : transformer\n",
      "2020-02-17 07:37:27,957 cfg.model.decoder.num_layers       : 6\n",
      "2020-02-17 07:37:27,957 cfg.model.decoder.num_heads        : 4\n",
      "2020-02-17 07:37:27,957 cfg.model.decoder.embeddings.embedding_dim : 256\n",
      "2020-02-17 07:37:27,957 cfg.model.decoder.embeddings.scale : True\n",
      "2020-02-17 07:37:27,957 cfg.model.decoder.embeddings.dropout : 0.2\n",
      "2020-02-17 07:37:27,958 cfg.model.decoder.hidden_size      : 256\n",
      "2020-02-17 07:37:27,958 cfg.model.decoder.ff_size          : 1024\n",
      "2020-02-17 07:37:27,958 cfg.model.decoder.dropout          : 0.3\n",
      "2020-02-17 07:37:27,958 Data set sizes: \n",
      "\ttrain 521636,\n",
      "\tvalid 1000,\n",
      "\ttest 2513\n",
      "2020-02-17 07:37:27,958 First training example:\n",
      "\t[SRC] parce que vous donn@@ ez le di@@ xi@@ ème de la ment@@ h@@ e et de l’@@ an@@ et@@ h et du cu@@ mi@@ n , mais que vous avez laissé les po@@ ints les plus import@@ ants de la Loi , à savoir la justice et la miséricor@@ de et la fidélité . ” — Matthieu 23 : 23 .\n",
      "\t[TRG] mpamba te bo@@ pes@@ aka moko ya zomi ya man@@ ti mpe ya an@@ et@@ i , mpe ya k@@ um@@ ini , kasi bos@@ ili koty@@ ola makambo ya Mibeko oyo ezali na ntina mingi , elingi koloba , bosembo mpe motema mawa mpe kondima . ” — Matai 23 : 23 .\n",
      "2020-02-17 07:37:27,958 First 10 words (src): (0) <unk> (1) <pad> (2) <s> (3) </s> (4) , (5) . (6) na (7) ya (8) de (9) oyo\n",
      "2020-02-17 07:37:27,958 First 10 words (trg): (0) <unk> (1) <pad> (2) <s> (3) </s> (4) , (5) . (6) na (7) ya (8) de (9) oyo\n",
      "2020-02-17 07:37:27,959 Number of Src words (types): 4435\n",
      "2020-02-17 07:37:27,959 Number of Trg words (types): 4435\n",
      "2020-02-17 07:37:27,959 Model(\n",
      "\tencoder=TransformerEncoder(num_layers=6, num_heads=4),\n",
      "\tdecoder=TransformerDecoder(num_layers=6, num_heads=4),\n",
      "\tsrc_embed=Embeddings(embedding_dim=256, vocab_size=4435),\n",
      "\ttrg_embed=Embeddings(embedding_dim=256, vocab_size=4435))\n",
      "2020-02-17 07:37:27,964 EPOCH 1\n",
      "2020-02-17 07:37:57,663 Epoch   1 Step:      100 Batch Loss:     5.448908 Tokens per Sec:     6712, Lr: 0.000300\n",
      "2020-02-17 07:38:26,740 Epoch   1 Step:      200 Batch Loss:     5.287449 Tokens per Sec:     7150, Lr: 0.000300\n",
      "2020-02-17 07:38:55,604 Epoch   1 Step:      300 Batch Loss:     5.035553 Tokens per Sec:     6878, Lr: 0.000300\n",
      "2020-02-17 07:39:24,698 Epoch   1 Step:      400 Batch Loss:     4.880265 Tokens per Sec:     6923, Lr: 0.000300\n",
      "2020-02-17 07:39:53,749 Epoch   1 Step:      500 Batch Loss:     4.470695 Tokens per Sec:     6902, Lr: 0.000300\n",
      "2020-02-17 07:40:22,605 Epoch   1 Step:      600 Batch Loss:     4.357949 Tokens per Sec:     6816, Lr: 0.000300\n",
      "2020-02-17 07:40:51,954 Epoch   1 Step:      700 Batch Loss:     4.215805 Tokens per Sec:     7118, Lr: 0.000300\n",
      "2020-02-17 07:41:20,671 Epoch   1 Step:      800 Batch Loss:     3.960764 Tokens per Sec:     6852, Lr: 0.000300\n",
      "2020-02-17 07:41:49,731 Epoch   1 Step:      900 Batch Loss:     3.885895 Tokens per Sec:     7040, Lr: 0.000300\n",
      "2020-02-17 07:42:18,843 Epoch   1 Step:     1000 Batch Loss:     4.152622 Tokens per Sec:     6898, Lr: 0.000300\n",
      "2020-02-17 07:43:50,283 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 07:43:50,283 Saving new checkpoint.\n",
      "2020-02-17 07:43:50,538 Example #0\n",
      "2020-02-17 07:43:50,538 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 07:43:50,538 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 07:43:50,538 \tHypothesis: Na nsima , Yehova azali na ye .\n",
      "2020-02-17 07:43:50,538 Example #1\n",
      "2020-02-17 07:43:50,538 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 07:43:50,538 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 07:43:50,538 \tHypothesis: Na nsima , Yesu alobaki ete : “ Nakisaki ye . ”\n",
      "2020-02-17 07:43:50,539 Example #2\n",
      "2020-02-17 07:43:50,539 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 07:43:50,539 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 07:43:50,539 \tHypothesis: Na nsima , bato ya Yehova azali na ye , mpe na ye , mpe na ye , mpe na ye .\n",
      "2020-02-17 07:43:50,539 Example #3\n",
      "2020-02-17 07:43:50,539 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 07:43:50,539 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 07:43:50,539 \tHypothesis: Na nsima , na ye azalaki na ye , mpe na ye , mpe na ye .\n",
      "2020-02-17 07:43:50,539 Example #5\n",
      "2020-02-17 07:43:50,539 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 07:43:50,539 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 07:43:50,540 \tHypothesis: Kasi , tosengeli na biso ete Yehova azali na ye .\n",
      "2020-02-17 07:43:50,540 Example #10\n",
      "2020-02-17 07:43:50,540 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 07:43:50,540 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 07:43:50,540 \tHypothesis: Kasi , tosengeli kozala na biso ete tosengeli na biso .\n",
      "2020-02-17 07:43:50,540 Validation result at epoch   1, step     1000: bleu:   1.33, loss: 101679.1016, ppl:  49.3328, duration: 91.6966s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 07:44:20,176 Epoch   1 Step:     1100 Batch Loss:     4.097420 Tokens per Sec:     7052, Lr: 0.000300\n",
      "2020-02-17 07:44:48,995 Epoch   1 Step:     1200 Batch Loss:     3.525275 Tokens per Sec:     6676, Lr: 0.000300\n",
      "2020-02-17 07:45:18,163 Epoch   1 Step:     1300 Batch Loss:     3.554519 Tokens per Sec:     7032, Lr: 0.000300\n",
      "2020-02-17 07:45:47,337 Epoch   1 Step:     1400 Batch Loss:     3.798509 Tokens per Sec:     6973, Lr: 0.000300\n",
      "2020-02-17 07:46:16,107 Epoch   1 Step:     1500 Batch Loss:     3.629510 Tokens per Sec:     6829, Lr: 0.000300\n",
      "2020-02-17 07:46:45,715 Epoch   1 Step:     1600 Batch Loss:     3.515002 Tokens per Sec:     7166, Lr: 0.000300\n",
      "2020-02-17 07:47:15,026 Epoch   1 Step:     1700 Batch Loss:     3.729373 Tokens per Sec:     6947, Lr: 0.000300\n",
      "2020-02-17 07:47:43,901 Epoch   1 Step:     1800 Batch Loss:     3.536882 Tokens per Sec:     6722, Lr: 0.000300\n",
      "2020-02-17 07:48:13,400 Epoch   1 Step:     1900 Batch Loss:     3.587356 Tokens per Sec:     7003, Lr: 0.000300\n",
      "2020-02-17 07:48:42,299 Epoch   1 Step:     2000 Batch Loss:     3.259966 Tokens per Sec:     6967, Lr: 0.000300\n",
      "2020-02-17 07:50:13,862 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 07:50:13,862 Saving new checkpoint.\n",
      "2020-02-17 07:50:14,059 Example #0\n",
      "2020-02-17 07:50:14,060 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 07:50:14,060 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 07:50:14,060 \tHypothesis: Na nsima , Yesu azalaki na mposa ya Yesu .\n",
      "2020-02-17 07:50:14,060 Example #1\n",
      "2020-02-17 07:50:14,060 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 07:50:14,060 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 07:50:14,060 \tHypothesis: Na ndakisa , Yehova azali na bomoi ya Yehova .\n",
      "2020-02-17 07:50:14,060 Example #2\n",
      "2020-02-17 07:50:14,061 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 07:50:14,061 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 07:50:14,061 \tHypothesis: Na nsima , nazalaki na mposa ya kosala makambo oyo ezali na yango , mpe na yango ezali na ntina mingi , mpe na ntina na ntina na yango .\n",
      "2020-02-17 07:50:14,061 Example #3\n",
      "2020-02-17 07:50:14,061 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 07:50:14,061 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 07:50:14,061 \tHypothesis: Na yango , bato oyo bazali na yango , mpe na yango ezali na ntina mingi te .\n",
      "2020-02-17 07:50:14,061 Example #5\n",
      "2020-02-17 07:50:14,061 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 07:50:14,061 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 07:50:14,061 \tHypothesis: Soki ozali na mposa ya malamu , okozala na bomoi na ye .\n",
      "2020-02-17 07:50:14,062 Example #10\n",
      "2020-02-17 07:50:14,062 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 07:50:14,062 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 07:50:14,062 \tHypothesis: Kotosa ya Yehova ezali na ntina mingi mpo na kosalisa biso tótala makambo oyo Yehova azali na yango .\n",
      "2020-02-17 07:50:14,062 Validation result at epoch   1, step     2000: bleu:   2.45, loss: 88058.7031, ppl:  29.2639, duration: 91.7621s\n",
      "2020-02-17 07:50:43,230 Epoch   1 Step:     2100 Batch Loss:     3.226981 Tokens per Sec:     6959, Lr: 0.000300\n",
      "2020-02-17 07:51:12,237 Epoch   1 Step:     2200 Batch Loss:     3.366795 Tokens per Sec:     6807, Lr: 0.000300\n",
      "2020-02-17 07:51:41,317 Epoch   1 Step:     2300 Batch Loss:     2.886894 Tokens per Sec:     6972, Lr: 0.000300\n",
      "2020-02-17 07:52:10,330 Epoch   1 Step:     2400 Batch Loss:     3.208706 Tokens per Sec:     6838, Lr: 0.000300\n",
      "2020-02-17 07:52:39,698 Epoch   1 Step:     2500 Batch Loss:     3.327526 Tokens per Sec:     6989, Lr: 0.000300\n",
      "2020-02-17 07:53:08,961 Epoch   1 Step:     2600 Batch Loss:     3.037954 Tokens per Sec:     6912, Lr: 0.000300\n",
      "2020-02-17 07:53:38,060 Epoch   1 Step:     2700 Batch Loss:     3.423100 Tokens per Sec:     6829, Lr: 0.000300\n",
      "2020-02-17 07:54:07,073 Epoch   1 Step:     2800 Batch Loss:     3.218804 Tokens per Sec:     6954, Lr: 0.000300\n",
      "2020-02-17 07:54:35,941 Epoch   1 Step:     2900 Batch Loss:     3.069086 Tokens per Sec:     6865, Lr: 0.000300\n",
      "2020-02-17 07:55:04,730 Epoch   1 Step:     3000 Batch Loss:     3.179271 Tokens per Sec:     6951, Lr: 0.000300\n",
      "2020-02-17 07:56:36,174 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 07:56:36,174 Saving new checkpoint.\n",
      "2020-02-17 07:56:36,374 Example #0\n",
      "2020-02-17 07:56:36,374 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 07:56:36,374 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 07:56:36,374 \tHypothesis: Na ndakisa , Yehova apesaki ye toli oyo Davidi azalaki na yango .\n",
      "2020-02-17 07:56:36,374 Example #1\n",
      "2020-02-17 07:56:36,374 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 07:56:36,374 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 07:56:36,374 \tHypothesis: Liteya ya Yilimia : Yehova azali na mposa ya kosala makambo oyo Yehova azali na yango .\n",
      "2020-02-17 07:56:36,374 Example #2\n",
      "2020-02-17 07:56:36,375 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 07:56:36,375 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 07:56:36,375 \tHypothesis: Na yango , namonaki ete namoni ete namoni ete namoni ete namoni na bomoi na ngai .\n",
      "2020-02-17 07:56:36,375 Example #3\n",
      "2020-02-17 07:56:36,375 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 07:56:36,375 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 07:56:36,375 \tHypothesis: Na ntembe te , moto oyo azali na mposa ya kosala , kasi azali na mposa ya kosala yango .\n",
      "2020-02-17 07:56:36,375 Example #5\n",
      "2020-02-17 07:56:36,375 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 07:56:36,375 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 07:56:36,376 \tHypothesis: Soki ozali na mposa ya koyeba makambo oyo ozali na yango .\n",
      "2020-02-17 07:56:36,376 Example #10\n",
      "2020-02-17 07:56:36,376 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 07:56:36,376 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 07:56:36,376 \tHypothesis: Na yango , tokomona ete Yehova azali na mposa ya kosala mosala ya kosakola .\n",
      "2020-02-17 07:56:36,376 Validation result at epoch   1, step     3000: bleu:   4.07, loss: 80679.0000, ppl:  22.0520, duration: 91.6457s\n",
      "2020-02-17 07:57:05,798 Epoch   1 Step:     3100 Batch Loss:     3.186436 Tokens per Sec:     6894, Lr: 0.000300\n",
      "2020-02-17 07:57:35,332 Epoch   1 Step:     3200 Batch Loss:     3.143942 Tokens per Sec:     6960, Lr: 0.000300\n",
      "2020-02-17 07:58:04,348 Epoch   1 Step:     3300 Batch Loss:     3.194626 Tokens per Sec:     6780, Lr: 0.000300\n",
      "2020-02-17 07:58:33,699 Epoch   1 Step:     3400 Batch Loss:     3.332705 Tokens per Sec:     6988, Lr: 0.000300\n",
      "2020-02-17 07:59:02,880 Epoch   1 Step:     3500 Batch Loss:     3.094167 Tokens per Sec:     6917, Lr: 0.000300\n",
      "2020-02-17 07:59:31,869 Epoch   1 Step:     3600 Batch Loss:     2.923027 Tokens per Sec:     6948, Lr: 0.000300\n",
      "2020-02-17 08:00:01,160 Epoch   1 Step:     3700 Batch Loss:     3.163504 Tokens per Sec:     6934, Lr: 0.000300\n",
      "2020-02-17 08:00:30,202 Epoch   1 Step:     3800 Batch Loss:     3.241575 Tokens per Sec:     6835, Lr: 0.000300\n",
      "2020-02-17 08:00:59,730 Epoch   1 Step:     3900 Batch Loss:     3.500490 Tokens per Sec:     6981, Lr: 0.000300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 08:01:28,654 Epoch   1 Step:     4000 Batch Loss:     2.923391 Tokens per Sec:     6879, Lr: 0.000300\n",
      "2020-02-17 08:03:00,117 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 08:03:00,117 Saving new checkpoint.\n",
      "2020-02-17 08:03:00,340 Example #0\n",
      "2020-02-17 08:03:00,341 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 08:03:00,341 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 08:03:00,341 \tHypothesis: Na ntango wana , Davidi azalaki na kondima na ye .\n",
      "2020-02-17 08:03:00,341 Example #1\n",
      "2020-02-17 08:03:00,342 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 08:03:00,342 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 08:03:00,342 \tHypothesis: Eliya : Eliya azali na kondima ete Yehova azali na nguya ya Yehova .\n",
      "2020-02-17 08:03:00,342 Example #2\n",
      "2020-02-17 08:03:00,343 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 08:03:00,343 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 08:03:00,343 \tHypothesis: Yango wana , namonaki ete nakoki kosala mosala ya kosakola mpe na nsima ya mikolo na ngai .\n",
      "2020-02-17 08:03:00,343 Example #3\n",
      "2020-02-17 08:03:00,343 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 08:03:00,343 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 08:03:00,344 \tHypothesis: Bokeseni na makambo oyo ezali na yango , mpe na ntembe te , ekoki kozala ete moto moko te .\n",
      "2020-02-17 08:03:00,344 Example #5\n",
      "2020-02-17 08:03:00,344 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 08:03:00,344 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 08:03:00,344 \tHypothesis: Soki ozali na mposa ya kosala makambo oyo ozali na yango .\n",
      "2020-02-17 08:03:00,345 Example #10\n",
      "2020-02-17 08:03:00,345 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 08:03:00,345 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 08:03:00,345 \tHypothesis: Elikya ya malamu ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 08:03:00,345 Validation result at epoch   1, step     4000: bleu:   5.93, loss: 75131.7500, ppl:  17.8269, duration: 91.6900s\n",
      "2020-02-17 08:03:29,699 Epoch   1 Step:     4100 Batch Loss:     3.038280 Tokens per Sec:     6830, Lr: 0.000300\n",
      "2020-02-17 08:03:58,826 Epoch   1 Step:     4200 Batch Loss:     2.799111 Tokens per Sec:     6900, Lr: 0.000300\n",
      "2020-02-17 08:04:27,915 Epoch   1 Step:     4300 Batch Loss:     3.196914 Tokens per Sec:     6862, Lr: 0.000300\n",
      "2020-02-17 08:04:56,988 Epoch   1 Step:     4400 Batch Loss:     3.042674 Tokens per Sec:     6983, Lr: 0.000300\n",
      "2020-02-17 08:05:26,387 Epoch   1 Step:     4500 Batch Loss:     3.062103 Tokens per Sec:     6954, Lr: 0.000300\n",
      "2020-02-17 08:05:55,656 Epoch   1 Step:     4600 Batch Loss:     3.153376 Tokens per Sec:     7017, Lr: 0.000300\n",
      "2020-02-17 08:06:24,436 Epoch   1 Step:     4700 Batch Loss:     2.979376 Tokens per Sec:     6775, Lr: 0.000300\n",
      "2020-02-17 08:06:53,683 Epoch   1 Step:     4800 Batch Loss:     2.582123 Tokens per Sec:     6821, Lr: 0.000300\n",
      "2020-02-17 08:07:22,882 Epoch   1 Step:     4900 Batch Loss:     2.833968 Tokens per Sec:     6986, Lr: 0.000300\n",
      "2020-02-17 08:07:52,232 Epoch   1 Step:     5000 Batch Loss:     2.764673 Tokens per Sec:     6913, Lr: 0.000300\n",
      "2020-02-17 08:09:23,749 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 08:09:23,749 Saving new checkpoint.\n",
      "2020-02-17 08:09:23,976 Example #0\n",
      "2020-02-17 08:09:23,976 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 08:09:23,976 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 08:09:23,977 \tHypothesis: Na ntango wana , Davidi azalaki kondima na ye .\n",
      "2020-02-17 08:09:23,977 Example #1\n",
      "2020-02-17 08:09:23,977 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 08:09:23,977 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 08:09:23,977 \tHypothesis: Na ndakisa , Eliya alobaki ete Yehova azali na nguya ya kozala na boyokani na ye .\n",
      "2020-02-17 08:09:23,977 Example #2\n",
      "2020-02-17 08:09:23,977 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 08:09:23,977 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 08:09:23,977 \tHypothesis: Yango wana , namonaki ete nakoki kosala mosala ya kosakola mpe na nsuka ya mikolo na ngai .\n",
      "2020-02-17 08:09:23,977 Example #3\n",
      "2020-02-17 08:09:23,978 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 08:09:23,978 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 08:09:23,978 \tHypothesis: Mabele ya mayele ezali mpe na ntina mingi mpo na likambo yango .\n",
      "2020-02-17 08:09:23,978 Example #5\n",
      "2020-02-17 08:09:23,978 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 08:09:23,978 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 08:09:23,978 \tHypothesis: Mbala mosusu okoki kozala na mposa ya kokende na ndako .\n",
      "2020-02-17 08:09:23,978 Example #10\n",
      "2020-02-17 08:09:23,978 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 08:09:23,979 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 08:09:23,979 \tHypothesis: Elikya ya malamu ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 08:09:23,979 Validation result at epoch   1, step     5000: bleu:   6.59, loss: 71755.0000, ppl:  15.6620, duration: 91.7460s\n",
      "2020-02-17 08:09:53,115 Epoch   1 Step:     5100 Batch Loss:     2.933217 Tokens per Sec:     6862, Lr: 0.000300\n",
      "2020-02-17 08:10:22,393 Epoch   1 Step:     5200 Batch Loss:     2.786199 Tokens per Sec:     6912, Lr: 0.000300\n",
      "2020-02-17 08:10:51,285 Epoch   1 Step:     5300 Batch Loss:     2.645263 Tokens per Sec:     6865, Lr: 0.000300\n",
      "2020-02-17 08:11:20,826 Epoch   1 Step:     5400 Batch Loss:     2.655173 Tokens per Sec:     7015, Lr: 0.000300\n",
      "2020-02-17 08:11:50,082 Epoch   1 Step:     5500 Batch Loss:     2.642448 Tokens per Sec:     6823, Lr: 0.000300\n",
      "2020-02-17 08:12:18,810 Epoch   1 Step:     5600 Batch Loss:     2.959315 Tokens per Sec:     6930, Lr: 0.000300\n",
      "2020-02-17 08:12:48,094 Epoch   1 Step:     5700 Batch Loss:     2.565258 Tokens per Sec:     6971, Lr: 0.000300\n",
      "2020-02-17 08:13:17,223 Epoch   1 Step:     5800 Batch Loss:     2.707784 Tokens per Sec:     7015, Lr: 0.000300\n",
      "2020-02-17 08:13:46,480 Epoch   1 Step:     5900 Batch Loss:     3.166131 Tokens per Sec:     6812, Lr: 0.000300\n",
      "2020-02-17 08:14:15,884 Epoch   1 Step:     6000 Batch Loss:     2.602023 Tokens per Sec:     6987, Lr: 0.000300\n",
      "2020-02-17 08:15:47,390 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 08:15:47,390 Saving new checkpoint.\n",
      "2020-02-17 08:15:47,610 Example #0\n",
      "2020-02-17 08:15:47,610 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 08:15:47,611 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 08:15:47,611 \tHypothesis: Na ntango wana , Davidi azalaki na kondima ya solosolo .\n",
      "2020-02-17 08:15:47,611 Example #1\n",
      "2020-02-17 08:15:47,611 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 08:15:47,611 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 08:15:47,611 \tHypothesis: Na nsima , Eliya alobaki ete Yehova azali na komikitisa nyonso oyo ezali na Baevanzile .\n",
      "2020-02-17 08:15:47,611 Example #2\n",
      "2020-02-17 08:15:47,611 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 08:15:47,611 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 08:15:47,611 \tHypothesis: Na yango , namonaki ete nakoki kosala mosala ya kosakola , mpe nsukansuka , namonaki ete nakozwa bomoi na ngai .\n",
      "2020-02-17 08:15:47,611 Example #3\n",
      "2020-02-17 08:15:47,612 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 08:15:47,612 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 08:15:47,612 \tHypothesis: Na ntembe te , moto oyo azali na mposa ya kosomba ye , akoki mpe kosala yango .\n",
      "2020-02-17 08:15:47,612 Example #5\n",
      "2020-02-17 08:15:47,612 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 08:15:47,612 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 08:15:47,612 \tHypothesis: Mbala mosusu okoki kozala na boyokani na ye na ye .\n",
      "2020-02-17 08:15:47,612 Example #10\n",
      "2020-02-17 08:15:47,612 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 08:15:47,612 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 08:15:47,613 \tHypothesis: Elikya ya kozala na mpiko ya ntango nyonso ya mpasi mpo na Yehova .\n",
      "2020-02-17 08:15:47,613 Validation result at epoch   1, step     6000: bleu:   7.54, loss: 68735.8750, ppl:  13.9500, duration: 91.7279s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 08:16:17,128 Epoch   1 Step:     6100 Batch Loss:     2.360406 Tokens per Sec:     6953, Lr: 0.000300\n",
      "2020-02-17 08:16:45,974 Epoch   1 Step:     6200 Batch Loss:     2.695576 Tokens per Sec:     6831, Lr: 0.000300\n",
      "2020-02-17 08:17:15,264 Epoch   1 Step:     6300 Batch Loss:     2.552511 Tokens per Sec:     6984, Lr: 0.000300\n",
      "2020-02-17 08:17:44,324 Epoch   1 Step:     6400 Batch Loss:     2.707558 Tokens per Sec:     6966, Lr: 0.000300\n",
      "2020-02-17 08:18:13,580 Epoch   1 Step:     6500 Batch Loss:     2.552106 Tokens per Sec:     6863, Lr: 0.000300\n",
      "2020-02-17 08:18:42,551 Epoch   1 Step:     6600 Batch Loss:     2.971236 Tokens per Sec:     6944, Lr: 0.000300\n",
      "2020-02-17 08:19:11,220 Epoch   1 Step:     6700 Batch Loss:     2.601802 Tokens per Sec:     6722, Lr: 0.000300\n",
      "2020-02-17 08:19:40,007 Epoch   1 Step:     6800 Batch Loss:     2.661322 Tokens per Sec:     6915, Lr: 0.000300\n",
      "2020-02-17 08:19:43,944 Epoch   1: total training loss 22518.39\n",
      "2020-02-17 08:19:43,944 EPOCH 2\n",
      "2020-02-17 08:20:10,048 Epoch   2 Step:     6900 Batch Loss:     2.624306 Tokens per Sec:     6699, Lr: 0.000300\n",
      "2020-02-17 08:20:39,321 Epoch   2 Step:     7000 Batch Loss:     2.440353 Tokens per Sec:     6929, Lr: 0.000300\n",
      "2020-02-17 08:22:10,841 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 08:22:10,841 Saving new checkpoint.\n",
      "2020-02-17 08:22:11,058 Example #0\n",
      "2020-02-17 08:22:11,058 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 08:22:11,058 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 08:22:11,058 \tHypothesis: Na ndakisa , Davidi amonisaki kondima ya moto .\n",
      "2020-02-17 08:22:11,058 Example #1\n",
      "2020-02-17 08:22:11,058 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 08:22:11,059 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 08:22:11,059 \tHypothesis: Eliya : Eliya azalaki na komikitisa nyonso oyo Yehova azali na yango .\n",
      "2020-02-17 08:22:11,059 Example #2\n",
      "2020-02-17 08:22:11,059 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 08:22:11,059 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 08:22:11,059 \tHypothesis: Yango wana , nasengelaki kosala makasi mpo na kosala mosala ya kosakola , mpe nsukansuka nsukansuka , nsukansuka nsukansuka nasalaki yango .\n",
      "2020-02-17 08:22:11,059 Example #3\n",
      "2020-02-17 08:22:11,059 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 08:22:11,059 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 08:22:11,059 \tHypothesis: Soki moto moko te azali na likoki ya kosala yango , akoki kozala na likoki ya kosala yango .\n",
      "2020-02-17 08:22:11,060 Example #5\n",
      "2020-02-17 08:22:11,060 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 08:22:11,060 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 08:22:11,060 \tHypothesis: Mbala mosusu okoki koyeba ete ozali na mposa ya kosala mosala na ye .\n",
      "2020-02-17 08:22:11,060 Example #10\n",
      "2020-02-17 08:22:11,060 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 08:22:11,060 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 08:22:11,060 \tHypothesis: Elikya ya koyika mpiko ezali mpenza mpasi mpo na Yehova .\n",
      "2020-02-17 08:22:11,060 Validation result at epoch   2, step     7000: bleu:   8.02, loss: 66262.4062, ppl:  12.6878, duration: 91.7384s\n",
      "2020-02-17 08:22:40,387 Epoch   2 Step:     7100 Batch Loss:     2.988856 Tokens per Sec:     7076, Lr: 0.000300\n",
      "2020-02-17 08:23:09,725 Epoch   2 Step:     7200 Batch Loss:     2.695230 Tokens per Sec:     6948, Lr: 0.000300\n",
      "2020-02-17 08:23:38,747 Epoch   2 Step:     7300 Batch Loss:     2.420538 Tokens per Sec:     6818, Lr: 0.000300\n",
      "2020-02-17 08:24:08,029 Epoch   2 Step:     7400 Batch Loss:     2.635396 Tokens per Sec:     6878, Lr: 0.000300\n",
      "2020-02-17 08:24:37,070 Epoch   2 Step:     7500 Batch Loss:     2.889355 Tokens per Sec:     6815, Lr: 0.000300\n",
      "2020-02-17 08:25:06,895 Epoch   2 Step:     7600 Batch Loss:     2.679150 Tokens per Sec:     7035, Lr: 0.000300\n",
      "2020-02-17 08:25:35,445 Epoch   2 Step:     7700 Batch Loss:     2.155373 Tokens per Sec:     6670, Lr: 0.000300\n",
      "2020-02-17 08:26:04,688 Epoch   2 Step:     7800 Batch Loss:     2.899461 Tokens per Sec:     7019, Lr: 0.000300\n",
      "2020-02-17 08:26:33,808 Epoch   2 Step:     7900 Batch Loss:     2.503206 Tokens per Sec:     6881, Lr: 0.000300\n",
      "2020-02-17 08:27:02,880 Epoch   2 Step:     8000 Batch Loss:     2.596869 Tokens per Sec:     6881, Lr: 0.000300\n",
      "2020-02-17 08:28:34,407 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 08:28:34,407 Saving new checkpoint.\n",
      "2020-02-17 08:28:34,633 Example #0\n",
      "2020-02-17 08:28:34,634 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 08:28:34,634 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 08:28:34,634 \tHypothesis: Na ndakisa , Davidi azalaki na kondima ya solosolo .\n",
      "2020-02-17 08:28:34,634 Example #1\n",
      "2020-02-17 08:28:34,634 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 08:28:34,634 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 08:28:34,634 \tHypothesis: Eliya : Eliya azali na komikitisa nyonso oyo Yehova azali na Baala .\n",
      "2020-02-17 08:28:34,634 Example #2\n",
      "2020-02-17 08:28:34,634 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 08:28:34,635 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 08:28:34,635 \tHypothesis: Yango wana , nasengelaki kozwa ekateli ya kosala mosala ya kosakola , mpe na nsima , nsukansuka , nsukansuka , nakokoka kosala yango .\n",
      "2020-02-17 08:28:34,635 Example #3\n",
      "2020-02-17 08:28:34,635 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 08:28:34,635 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 08:28:34,635 \tHypothesis: Na esika ya kosala yango , moto akoki mpe koloba ete azali moto ya mayele .\n",
      "2020-02-17 08:28:34,635 Example #5\n",
      "2020-02-17 08:28:34,635 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 08:28:34,635 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 08:28:34,635 \tHypothesis: Mbala mosusu okoki kokanisa ete ozali na boyokani malamu na ye .\n",
      "2020-02-17 08:28:34,635 Example #10\n",
      "2020-02-17 08:28:34,636 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 08:28:34,636 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 08:28:34,636 \tHypothesis: Elikya ya koyika mpiko ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 08:28:34,636 Validation result at epoch   2, step     8000: bleu:   9.94, loss: 64169.5469, ppl:  11.7094, duration: 91.7546s\n",
      "2020-02-17 08:29:03,942 Epoch   2 Step:     8100 Batch Loss:     2.662070 Tokens per Sec:     7001, Lr: 0.000300\n",
      "2020-02-17 08:29:33,059 Epoch   2 Step:     8200 Batch Loss:     2.604672 Tokens per Sec:     6956, Lr: 0.000300\n",
      "2020-02-17 08:30:02,702 Epoch   2 Step:     8300 Batch Loss:     2.652258 Tokens per Sec:     7088, Lr: 0.000300\n",
      "2020-02-17 08:30:31,644 Epoch   2 Step:     8400 Batch Loss:     2.513211 Tokens per Sec:     6901, Lr: 0.000300\n",
      "2020-02-17 08:31:00,376 Epoch   2 Step:     8500 Batch Loss:     2.637931 Tokens per Sec:     6791, Lr: 0.000300\n",
      "2020-02-17 08:31:29,575 Epoch   2 Step:     8600 Batch Loss:     2.566800 Tokens per Sec:     6861, Lr: 0.000300\n",
      "2020-02-17 08:31:58,559 Epoch   2 Step:     8700 Batch Loss:     2.564637 Tokens per Sec:     6858, Lr: 0.000300\n",
      "2020-02-17 08:32:27,737 Epoch   2 Step:     8800 Batch Loss:     2.587095 Tokens per Sec:     7009, Lr: 0.000300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 08:32:57,314 Epoch   2 Step:     8900 Batch Loss:     2.620893 Tokens per Sec:     6979, Lr: 0.000300\n",
      "2020-02-17 08:33:26,596 Epoch   2 Step:     9000 Batch Loss:     2.254808 Tokens per Sec:     6850, Lr: 0.000300\n",
      "2020-02-17 08:34:57,982 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 08:34:57,983 Saving new checkpoint.\n",
      "2020-02-17 08:34:58,204 Example #0\n",
      "2020-02-17 08:34:58,205 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 08:34:58,205 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 08:34:58,205 \tHypothesis: Na ndakisa , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 08:34:58,205 Example #1\n",
      "2020-02-17 08:34:58,205 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 08:34:58,205 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 08:34:58,205 \tHypothesis: Eliya : Eliya azali na komikitisa nyonso oyo Yehova azali na Baala .\n",
      "2020-02-17 08:34:58,205 Example #2\n",
      "2020-02-17 08:34:58,205 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 08:34:58,206 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 08:34:58,206 \tHypothesis: Nazwaki ekateli ya kosala mosala ya soda mpe ya mwasi na ngai ya mwasi , mpe na nsima , natikaki kosala mosala ya soda .\n",
      "2020-02-17 08:34:58,206 Example #3\n",
      "2020-02-17 08:34:58,206 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 08:34:58,206 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 08:34:58,206 \tHypothesis: Soki moto azali na lokoso , akoki mpe kozala na lokoso ya moto oyo azali na yango .\n",
      "2020-02-17 08:34:58,206 Example #5\n",
      "2020-02-17 08:34:58,206 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 08:34:58,206 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 08:34:58,206 \tHypothesis: Mbala mosusu okomona ete ozali na baninga na ye .\n",
      "2020-02-17 08:34:58,206 Example #10\n",
      "2020-02-17 08:34:58,207 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 08:34:58,207 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 08:34:58,207 \tHypothesis: Elikya ya koyika mpiko ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 08:34:58,207 Validation result at epoch   2, step     9000: bleu:  11.03, loss: 62004.4883, ppl:  10.7766, duration: 91.6099s\n",
      "2020-02-17 08:35:27,310 Epoch   2 Step:     9100 Batch Loss:     2.198456 Tokens per Sec:     6818, Lr: 0.000300\n",
      "2020-02-17 08:35:56,385 Epoch   2 Step:     9200 Batch Loss:     2.300194 Tokens per Sec:     6808, Lr: 0.000300\n",
      "2020-02-17 08:36:25,822 Epoch   2 Step:     9300 Batch Loss:     2.180154 Tokens per Sec:     7015, Lr: 0.000300\n",
      "2020-02-17 08:36:55,223 Epoch   2 Step:     9400 Batch Loss:     2.384633 Tokens per Sec:     6926, Lr: 0.000300\n",
      "2020-02-17 08:37:24,451 Epoch   2 Step:     9500 Batch Loss:     2.304837 Tokens per Sec:     7022, Lr: 0.000300\n",
      "2020-02-17 08:37:53,871 Epoch   2 Step:     9600 Batch Loss:     2.551825 Tokens per Sec:     6965, Lr: 0.000300\n",
      "2020-02-17 08:38:23,085 Epoch   2 Step:     9700 Batch Loss:     2.408397 Tokens per Sec:     6969, Lr: 0.000300\n",
      "2020-02-17 08:38:52,042 Epoch   2 Step:     9800 Batch Loss:     2.465623 Tokens per Sec:     6794, Lr: 0.000300\n",
      "2020-02-17 08:39:21,646 Epoch   2 Step:     9900 Batch Loss:     2.633299 Tokens per Sec:     7171, Lr: 0.000300\n",
      "2020-02-17 08:39:50,520 Epoch   2 Step:    10000 Batch Loss:     2.227300 Tokens per Sec:     6703, Lr: 0.000300\n",
      "2020-02-17 08:41:22,031 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 08:41:22,031 Saving new checkpoint.\n",
      "2020-02-17 08:41:22,251 Example #0\n",
      "2020-02-17 08:41:22,251 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 08:41:22,251 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 08:41:22,251 \tHypothesis: Na ndakisa , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 08:41:22,251 Example #1\n",
      "2020-02-17 08:41:22,251 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 08:41:22,252 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 08:41:22,252 \tHypothesis: Eliya : Eliya azali komonisa ete Yehova azali Moyangeli ya Baefese .\n",
      "2020-02-17 08:41:22,252 Example #2\n",
      "2020-02-17 08:41:22,252 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 08:41:22,252 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 08:41:22,252 \tHypothesis: Na yango , nazwaki ekateli ya kosala mosala ya soda mpe ya liwa ya moto oyo azalaki na yango .\n",
      "2020-02-17 08:41:22,252 Example #3\n",
      "2020-02-17 08:41:22,252 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 08:41:22,252 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 08:41:22,252 \tHypothesis: Soki moto azali na likoki ya kosala bongo , akoki mpe kozala na likoki ya kosala yango .\n",
      "2020-02-17 08:41:22,252 Example #5\n",
      "2020-02-17 08:41:22,253 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 08:41:22,253 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 08:41:22,253 \tHypothesis: Mbala mosusu okoyoka yango .\n",
      "2020-02-17 08:41:22,253 Example #10\n",
      "2020-02-17 08:41:22,253 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 08:41:22,253 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 08:41:22,253 \tHypothesis: Kozanga mpiko na komekama ya ndenge wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 08:41:22,253 Validation result at epoch   2, step    10000: bleu:  11.97, loss: 60213.0391, ppl:  10.0613, duration: 91.7329s\n",
      "2020-02-17 08:41:51,781 Epoch   2 Step:    10100 Batch Loss:     2.531725 Tokens per Sec:     7096, Lr: 0.000300\n",
      "2020-02-17 08:42:20,931 Epoch   2 Step:    10200 Batch Loss:     2.408033 Tokens per Sec:     6924, Lr: 0.000300\n",
      "2020-02-17 08:42:49,952 Epoch   2 Step:    10300 Batch Loss:     2.477655 Tokens per Sec:     6876, Lr: 0.000300\n",
      "2020-02-17 08:43:19,344 Epoch   2 Step:    10400 Batch Loss:     2.293119 Tokens per Sec:     6952, Lr: 0.000300\n",
      "2020-02-17 08:43:48,257 Epoch   2 Step:    10500 Batch Loss:     2.348135 Tokens per Sec:     6695, Lr: 0.000300\n",
      "2020-02-17 08:44:17,218 Epoch   2 Step:    10600 Batch Loss:     2.374358 Tokens per Sec:     6802, Lr: 0.000300\n",
      "2020-02-17 08:44:46,371 Epoch   2 Step:    10700 Batch Loss:     2.353972 Tokens per Sec:     6905, Lr: 0.000300\n",
      "2020-02-17 08:45:15,730 Epoch   2 Step:    10800 Batch Loss:     2.310239 Tokens per Sec:     7042, Lr: 0.000300\n",
      "2020-02-17 08:45:44,898 Epoch   2 Step:    10900 Batch Loss:     2.511836 Tokens per Sec:     6967, Lr: 0.000300\n",
      "2020-02-17 08:46:13,975 Epoch   2 Step:    11000 Batch Loss:     2.253190 Tokens per Sec:     6774, Lr: 0.000300\n",
      "2020-02-17 08:47:45,488 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 08:47:45,488 Saving new checkpoint.\n",
      "2020-02-17 08:47:45,710 Example #0\n",
      "2020-02-17 08:47:45,711 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 08:47:45,711 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 08:47:45,711 \tHypothesis: Na ndakisa , Davidi amonisaki ete moto moko ya kondima azali .\n",
      "2020-02-17 08:47:45,711 Example #1\n",
      "2020-02-17 08:47:45,711 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 08:47:45,711 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 08:47:45,711 \tHypothesis: Na nsima , Eliya apesaki ndakisa ya Yehova ete azali Mobateli ya Baala .\n",
      "2020-02-17 08:47:45,711 Example #2\n",
      "2020-02-17 08:47:45,711 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 08:47:45,712 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 08:47:45,712 \tHypothesis: Na yango , nazwaki ekateli ya kosala yango mpe mpo na kozwa batisimo , mpo na koyeba soki natiki ngai .\n",
      "2020-02-17 08:47:45,712 Example #3\n",
      "2020-02-17 08:47:45,712 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 08:47:45,712 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 08:47:45,712 \tHypothesis: Bobele bongo , moto oyo azali na lokoso , azali mpe na mposa ya kosala bongo .\n",
      "2020-02-17 08:47:45,712 Example #5\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 08:47:45,712 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 08:47:45,712 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 08:47:45,712 \tHypothesis: Mbala mosusu okoki komona ete ozali na baninga na ye .\n",
      "2020-02-17 08:47:45,712 Example #10\n",
      "2020-02-17 08:47:45,713 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 08:47:45,713 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 08:47:45,713 \tHypothesis: Elikya ya koyika mpiko na komekama ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 08:47:45,713 Validation result at epoch   2, step    11000: bleu:  12.25, loss: 59205.4648, ppl:   9.6800, duration: 91.7366s\n",
      "2020-02-17 08:48:14,836 Epoch   2 Step:    11100 Batch Loss:     2.062212 Tokens per Sec:     6990, Lr: 0.000300\n",
      "2020-02-17 08:48:44,183 Epoch   2 Step:    11200 Batch Loss:     2.490015 Tokens per Sec:     7056, Lr: 0.000300\n",
      "2020-02-17 08:49:13,183 Epoch   2 Step:    11300 Batch Loss:     2.635970 Tokens per Sec:     6926, Lr: 0.000300\n",
      "2020-02-17 08:49:42,250 Epoch   2 Step:    11400 Batch Loss:     2.322071 Tokens per Sec:     6966, Lr: 0.000300\n",
      "2020-02-17 08:50:11,355 Epoch   2 Step:    11500 Batch Loss:     2.488194 Tokens per Sec:     7015, Lr: 0.000300\n",
      "2020-02-17 08:50:40,614 Epoch   2 Step:    11600 Batch Loss:     2.423447 Tokens per Sec:     7063, Lr: 0.000300\n",
      "2020-02-17 08:51:09,895 Epoch   2 Step:    11700 Batch Loss:     2.186171 Tokens per Sec:     7029, Lr: 0.000300\n",
      "2020-02-17 08:51:39,104 Epoch   2 Step:    11800 Batch Loss:     2.425178 Tokens per Sec:     7081, Lr: 0.000300\n",
      "2020-02-17 08:52:07,918 Epoch   2 Step:    11900 Batch Loss:     2.250606 Tokens per Sec:     6870, Lr: 0.000300\n",
      "2020-02-17 08:52:37,380 Epoch   2 Step:    12000 Batch Loss:     2.851729 Tokens per Sec:     6981, Lr: 0.000300\n",
      "2020-02-17 08:54:08,683 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 08:54:08,683 Saving new checkpoint.\n",
      "2020-02-17 08:54:08,910 Example #0\n",
      "2020-02-17 08:54:08,910 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 08:54:08,910 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 08:54:08,910 \tHypothesis: Na esika ya Yehova , Davidi amonisaki ete moto moko ya kondima azalaki na kondima .\n",
      "2020-02-17 08:54:08,911 Example #1\n",
      "2020-02-17 08:54:08,911 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 08:54:08,911 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 08:54:08,911 \tHypothesis: Eliya : Eliya apesaki Yehova lokumu monene na Baala .\n",
      "2020-02-17 08:54:08,911 Example #2\n",
      "2020-02-17 08:54:08,911 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 08:54:08,911 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 08:54:08,911 \tHypothesis: Na yango , nazwaki ekateli ya kosala mosala ya soda mpe ya malamu , mpo na kozwa bomoi na ngai .\n",
      "2020-02-17 08:54:08,911 Example #3\n",
      "2020-02-17 08:54:08,912 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 08:54:08,912 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 08:54:08,912 \tHypothesis: Koboma mpe kokɔtisa mokɛngɛli , ata soki azali na mposa ya kosala yango .\n",
      "2020-02-17 08:54:08,912 Example #5\n",
      "2020-02-17 08:54:08,912 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 08:54:08,912 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 08:54:08,912 \tHypothesis: Ekoki kozala ete ozali na mposa ya kozala na baninga na ye .\n",
      "2020-02-17 08:54:08,912 Example #10\n",
      "2020-02-17 08:54:08,913 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 08:54:08,913 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 08:54:08,913 \tHypothesis: Kozanga mpiko na komekama ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 08:54:08,913 Validation result at epoch   2, step    12000: bleu:  13.71, loss: 57379.7500, ppl:   9.0255, duration: 91.5323s\n",
      "2020-02-17 08:54:37,820 Epoch   2 Step:    12100 Batch Loss:     2.403936 Tokens per Sec:     6893, Lr: 0.000300\n",
      "2020-02-17 08:55:07,030 Epoch   2 Step:    12200 Batch Loss:     2.421860 Tokens per Sec:     6971, Lr: 0.000300\n",
      "2020-02-17 08:55:36,170 Epoch   2 Step:    12300 Batch Loss:     2.189918 Tokens per Sec:     6919, Lr: 0.000300\n",
      "2020-02-17 08:56:05,370 Epoch   2 Step:    12400 Batch Loss:     2.230463 Tokens per Sec:     6931, Lr: 0.000300\n",
      "2020-02-17 08:56:34,524 Epoch   2 Step:    12500 Batch Loss:     2.730872 Tokens per Sec:     6870, Lr: 0.000300\n",
      "2020-02-17 08:57:03,985 Epoch   2 Step:    12600 Batch Loss:     2.479726 Tokens per Sec:     7018, Lr: 0.000300\n",
      "2020-02-17 08:57:33,032 Epoch   2 Step:    12700 Batch Loss:     2.187266 Tokens per Sec:     6774, Lr: 0.000300\n",
      "2020-02-17 08:58:02,452 Epoch   2 Step:    12800 Batch Loss:     2.397758 Tokens per Sec:     7020, Lr: 0.000300\n",
      "2020-02-17 08:58:31,440 Epoch   2 Step:    12900 Batch Loss:     2.385113 Tokens per Sec:     6927, Lr: 0.000300\n",
      "2020-02-17 08:59:00,417 Epoch   2 Step:    13000 Batch Loss:     2.919387 Tokens per Sec:     6885, Lr: 0.000300\n",
      "2020-02-17 09:00:31,830 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 09:00:31,830 Saving new checkpoint.\n",
      "2020-02-17 09:00:32,055 Example #0\n",
      "2020-02-17 09:00:32,056 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 09:00:32,056 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 09:00:32,056 \tHypothesis: Na ndakisa , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 09:00:32,056 Example #1\n",
      "2020-02-17 09:00:32,056 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 09:00:32,056 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 09:00:32,056 \tHypothesis: Eliya alobaki ete Yehova azali na kati ya Baala .\n",
      "2020-02-17 09:00:32,056 Example #2\n",
      "2020-02-17 09:00:32,057 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 09:00:32,057 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 09:00:32,057 \tHypothesis: Na yango , nazwaki ekateli ya kosala makasi mpe ya kosala makasi mpo na kobatela bomoi na ngai .\n",
      "2020-02-17 09:00:32,057 Example #3\n",
      "2020-02-17 09:00:32,057 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 09:00:32,057 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 09:00:32,057 \tHypothesis: Soki moto azali na mposa ya kosala bongo , ata soki azali na bomoi ya malamu .\n",
      "2020-02-17 09:00:32,057 Example #5\n",
      "2020-02-17 09:00:32,057 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 09:00:32,057 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 09:00:32,058 \tHypothesis: Mbala mosusu okoki komona ete ozali na baninga na ye .\n",
      "2020-02-17 09:00:32,058 Example #10\n",
      "2020-02-17 09:00:32,058 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 09:00:32,058 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 09:00:32,058 \tHypothesis: Koyika mpiko na komekama ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 09:00:32,058 Validation result at epoch   2, step    13000: bleu:  14.61, loss: 56491.8281, ppl:   8.7234, duration: 91.6408s\n",
      "2020-02-17 09:01:01,456 Epoch   2 Step:    13100 Batch Loss:     2.567919 Tokens per Sec:     6893, Lr: 0.000300\n",
      "2020-02-17 09:01:30,452 Epoch   2 Step:    13200 Batch Loss:     1.800248 Tokens per Sec:     6887, Lr: 0.000300\n",
      "2020-02-17 09:01:59,591 Epoch   2 Step:    13300 Batch Loss:     2.185984 Tokens per Sec:     6937, Lr: 0.000300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 09:02:29,014 Epoch   2 Step:    13400 Batch Loss:     2.168905 Tokens per Sec:     7011, Lr: 0.000300\n",
      "2020-02-17 09:02:58,285 Epoch   2 Step:    13500 Batch Loss:     2.534457 Tokens per Sec:     6897, Lr: 0.000300\n",
      "2020-02-17 09:03:27,312 Epoch   2 Step:    13600 Batch Loss:     2.647233 Tokens per Sec:     6752, Lr: 0.000300\n",
      "2020-02-17 09:03:29,487 Epoch   2: total training loss 16748.52\n",
      "2020-02-17 09:03:29,487 EPOCH 3\n",
      "2020-02-17 09:03:57,353 Epoch   3 Step:    13700 Batch Loss:     1.993847 Tokens per Sec:     6691, Lr: 0.000300\n",
      "2020-02-17 09:04:27,102 Epoch   3 Step:    13800 Batch Loss:     2.300247 Tokens per Sec:     7135, Lr: 0.000300\n",
      "2020-02-17 09:04:56,126 Epoch   3 Step:    13900 Batch Loss:     2.545258 Tokens per Sec:     7000, Lr: 0.000300\n",
      "2020-02-17 09:05:25,381 Epoch   3 Step:    14000 Batch Loss:     2.381773 Tokens per Sec:     6880, Lr: 0.000300\n",
      "2020-02-17 09:06:56,782 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 09:06:56,783 Saving new checkpoint.\n",
      "2020-02-17 09:06:57,001 Example #0\n",
      "2020-02-17 09:06:57,001 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 09:06:57,001 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 09:06:57,001 \tHypothesis: Na ndakisa , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 09:06:57,001 Example #1\n",
      "2020-02-17 09:06:57,002 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 09:06:57,002 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 09:06:57,002 \tHypothesis: Na nsima , Eliya amikundwelaki Yehova motema mawa na ye .\n",
      "2020-02-17 09:06:57,002 Example #2\n",
      "2020-02-17 09:06:57,002 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 09:06:57,002 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 09:06:57,002 \tHypothesis: Yango wana , nazwaki ekateli ya kosala mosala ya soda , mpe mpo na kozwa bomoi na ngai , mpe mpo na kozwa ntango ya mpasi .\n",
      "2020-02-17 09:06:57,002 Example #3\n",
      "2020-02-17 09:06:57,002 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 09:06:57,002 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 09:06:57,003 \tHypothesis: Bavoovo yango ezali mpe na ntina mingi mpo na moto oyo azali na maladi , kasi soki azali na maladi .\n",
      "2020-02-17 09:06:57,003 Example #5\n",
      "2020-02-17 09:06:57,003 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 09:06:57,003 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 09:06:57,003 \tHypothesis: Mbala mosusu okoki komona ete ozali na baninga na yo .\n",
      "2020-02-17 09:06:57,003 Example #10\n",
      "2020-02-17 09:06:57,003 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 09:06:57,003 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 09:06:57,003 \tHypothesis: Koyika mpiko na komekama ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 09:06:57,003 Validation result at epoch   3, step    14000: bleu:  14.65, loss: 55644.2578, ppl:   8.4445, duration: 91.6220s\n",
      "2020-02-17 09:07:26,340 Epoch   3 Step:    14100 Batch Loss:     2.308134 Tokens per Sec:     7011, Lr: 0.000300\n",
      "2020-02-17 09:07:55,540 Epoch   3 Step:    14200 Batch Loss:     2.226135 Tokens per Sec:     6925, Lr: 0.000300\n",
      "2020-02-17 09:08:24,876 Epoch   3 Step:    14300 Batch Loss:     2.489031 Tokens per Sec:     6949, Lr: 0.000300\n",
      "2020-02-17 09:08:54,432 Epoch   3 Step:    14400 Batch Loss:     2.373739 Tokens per Sec:     6974, Lr: 0.000300\n",
      "2020-02-17 09:09:23,780 Epoch   3 Step:    14500 Batch Loss:     2.442060 Tokens per Sec:     7126, Lr: 0.000300\n",
      "2020-02-17 09:09:53,222 Epoch   3 Step:    14600 Batch Loss:     1.960461 Tokens per Sec:     7025, Lr: 0.000300\n",
      "2020-02-17 09:10:22,333 Epoch   3 Step:    14700 Batch Loss:     2.287452 Tokens per Sec:     6946, Lr: 0.000300\n",
      "2020-02-17 09:10:51,473 Epoch   3 Step:    14800 Batch Loss:     2.251009 Tokens per Sec:     6908, Lr: 0.000300\n",
      "2020-02-17 09:11:20,747 Epoch   3 Step:    14900 Batch Loss:     1.963124 Tokens per Sec:     6900, Lr: 0.000300\n",
      "2020-02-17 09:11:50,038 Epoch   3 Step:    15000 Batch Loss:     2.226466 Tokens per Sec:     6944, Lr: 0.000300\n",
      "2020-02-17 09:13:21,638 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 09:13:21,638 Saving new checkpoint.\n",
      "2020-02-17 09:13:21,862 Example #0\n",
      "2020-02-17 09:13:21,862 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 09:13:21,862 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 09:13:21,863 \tHypothesis: Davidi amonisaki ete moto ya kondima azalaki na kondima .\n",
      "2020-02-17 09:13:21,863 Example #1\n",
      "2020-02-17 09:13:21,863 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 09:13:21,863 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 09:13:21,863 \tHypothesis: Eliya apesaki ndakisa ya komonisa ete Yehova azali na ngɔlu na Baala .\n",
      "2020-02-17 09:13:21,863 Example #2\n",
      "2020-02-17 09:13:21,863 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 09:13:21,863 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 09:13:21,863 \tHypothesis: Yango wana , nazwaki ekateli ya kosala mosala ya kobɔkɔla ngai mpe ya kolata , mpo na kozwa bomoi na ngai .\n",
      "2020-02-17 09:13:21,863 Example #3\n",
      "2020-02-17 09:13:21,864 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 09:13:21,864 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 09:13:21,864 \tHypothesis: Soki moto azali na mayele ya kosala makambo oyo ezali na bokosi , ata soki azali na maladi .\n",
      "2020-02-17 09:13:21,864 Example #5\n",
      "2020-02-17 09:13:21,864 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 09:13:21,864 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 09:13:21,864 \tHypothesis: Mbala mosusu okoki komona ete ozali na baninga na ye .\n",
      "2020-02-17 09:13:21,864 Example #10\n",
      "2020-02-17 09:13:21,864 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 09:13:21,864 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 09:13:21,864 \tHypothesis: Koyika mpiko na komekama ya komekama ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 09:13:21,865 Validation result at epoch   3, step    15000: bleu:  15.58, loss: 54724.9805, ppl:   8.1521, duration: 91.8255s\n",
      "2020-02-17 09:13:50,842 Epoch   3 Step:    15100 Batch Loss:     2.260962 Tokens per Sec:     6904, Lr: 0.000300\n",
      "2020-02-17 09:14:19,813 Epoch   3 Step:    15200 Batch Loss:     2.304009 Tokens per Sec:     6887, Lr: 0.000300\n",
      "2020-02-17 09:14:49,131 Epoch   3 Step:    15300 Batch Loss:     2.161525 Tokens per Sec:     6895, Lr: 0.000300\n",
      "2020-02-17 09:15:18,278 Epoch   3 Step:    15400 Batch Loss:     2.122844 Tokens per Sec:     7006, Lr: 0.000300\n",
      "2020-02-17 09:15:47,770 Epoch   3 Step:    15500 Batch Loss:     2.227204 Tokens per Sec:     6983, Lr: 0.000300\n",
      "2020-02-17 09:16:17,385 Epoch   3 Step:    15600 Batch Loss:     2.264842 Tokens per Sec:     7017, Lr: 0.000300\n",
      "2020-02-17 09:16:46,512 Epoch   3 Step:    15700 Batch Loss:     1.937090 Tokens per Sec:     6801, Lr: 0.000300\n",
      "2020-02-17 09:17:15,473 Epoch   3 Step:    15800 Batch Loss:     2.205768 Tokens per Sec:     6854, Lr: 0.000300\n",
      "2020-02-17 09:17:44,608 Epoch   3 Step:    15900 Batch Loss:     2.136642 Tokens per Sec:     6828, Lr: 0.000300\n",
      "2020-02-17 09:18:13,608 Epoch   3 Step:    16000 Batch Loss:     2.286425 Tokens per Sec:     6905, Lr: 0.000300\n",
      "2020-02-17 09:19:44,883 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 09:19:44,883 Saving new checkpoint.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 09:19:45,101 Example #0\n",
      "2020-02-17 09:19:45,101 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 09:19:45,101 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 09:19:45,101 \tHypothesis: Na kati ya libota ya Davidi , Davidi amonisaki kondima .\n",
      "2020-02-17 09:19:45,102 Example #1\n",
      "2020-02-17 09:19:45,102 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 09:19:45,102 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 09:19:45,102 \tHypothesis: Eliya alobaki ete Yehova azali Mozwi - ya - Nguya - Nyonso .\n",
      "2020-02-17 09:19:45,102 Example #2\n",
      "2020-02-17 09:19:45,102 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 09:19:45,102 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 09:19:45,102 \tHypothesis: Na yango , nazwaki ekateli ya kosala mosala ya soda mpe ya nsuka , mpo na kozwa bomoi na ngai .\n",
      "2020-02-17 09:19:45,102 Example #3\n",
      "2020-02-17 09:19:45,103 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 09:19:45,103 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 09:19:45,103 \tHypothesis: Soki moto azali na mayele mingi , azali mpe na mposa ya kosikola ye .\n",
      "2020-02-17 09:19:45,103 Example #5\n",
      "2020-02-17 09:19:45,103 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 09:19:45,103 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 09:19:45,103 \tHypothesis: Mbala mosusu okoki komona ete ozali na baninga na ye .\n",
      "2020-02-17 09:19:45,103 Example #10\n",
      "2020-02-17 09:19:45,103 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 09:19:45,103 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 09:19:45,103 \tHypothesis: Koyika mpiko na komekama ya ndenge wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 09:19:45,103 Validation result at epoch   3, step    16000: bleu:  16.26, loss: 53939.6797, ppl:   7.9103, duration: 91.4941s\n",
      "2020-02-17 09:20:14,239 Epoch   3 Step:    16100 Batch Loss:     2.144011 Tokens per Sec:     6913, Lr: 0.000300\n",
      "2020-02-17 09:20:43,366 Epoch   3 Step:    16200 Batch Loss:     1.953776 Tokens per Sec:     6813, Lr: 0.000300\n",
      "2020-02-17 09:21:12,547 Epoch   3 Step:    16300 Batch Loss:     2.069379 Tokens per Sec:     6788, Lr: 0.000300\n",
      "2020-02-17 09:21:41,848 Epoch   3 Step:    16400 Batch Loss:     2.279624 Tokens per Sec:     7024, Lr: 0.000300\n",
      "2020-02-17 09:22:11,258 Epoch   3 Step:    16500 Batch Loss:     2.229335 Tokens per Sec:     7055, Lr: 0.000300\n",
      "2020-02-17 09:22:40,562 Epoch   3 Step:    16600 Batch Loss:     1.997895 Tokens per Sec:     6920, Lr: 0.000300\n",
      "2020-02-17 09:23:09,717 Epoch   3 Step:    16700 Batch Loss:     2.194762 Tokens per Sec:     6970, Lr: 0.000300\n",
      "2020-02-17 09:23:38,514 Epoch   3 Step:    16800 Batch Loss:     2.235805 Tokens per Sec:     6878, Lr: 0.000300\n",
      "2020-02-17 09:24:07,983 Epoch   3 Step:    16900 Batch Loss:     2.121127 Tokens per Sec:     6982, Lr: 0.000300\n",
      "2020-02-17 09:24:37,370 Epoch   3 Step:    17000 Batch Loss:     2.151195 Tokens per Sec:     6973, Lr: 0.000300\n",
      "2020-02-17 09:26:08,849 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 09:26:08,850 Saving new checkpoint.\n",
      "2020-02-17 09:26:09,076 Example #0\n",
      "2020-02-17 09:26:09,076 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 09:26:09,076 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 09:26:09,076 \tHypothesis: Na kati ya libondeli ya Davidi , Davidi amonisaki ete azalaki moto ya kondima .\n",
      "2020-02-17 09:26:09,077 Example #1\n",
      "2020-02-17 09:26:09,077 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 09:26:09,077 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 09:26:09,077 \tHypothesis: Eliya amonisaki ete Yehova azali na ngɔlu na Baala .\n",
      "2020-02-17 09:26:09,077 Example #2\n",
      "2020-02-17 09:26:09,077 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 09:26:09,077 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 09:26:09,077 \tHypothesis: Na yango , nazwaki ekateli ya kosala makambo oyo nakoki kosala , mpe mpo na libela , nsukansuka nakozwa ekateli ya kosala mikolo na ngai .\n",
      "2020-02-17 09:26:09,077 Example #3\n",
      "2020-02-17 09:26:09,078 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 09:26:09,078 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 09:26:09,078 \tHypothesis: Soki moto azali na maladi , akoki mpe kozala na bomoi ya malamu .\n",
      "2020-02-17 09:26:09,078 Example #5\n",
      "2020-02-17 09:26:09,078 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 09:26:09,078 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 09:26:09,078 \tHypothesis: Mbala mosusu okoki komona ete ozali na baninga na ye .\n",
      "2020-02-17 09:26:09,078 Example #10\n",
      "2020-02-17 09:26:09,078 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 09:26:09,079 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 09:26:09,079 \tHypothesis: Koyika mpiko na komekama ya ndenge wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 09:26:09,079 Validation result at epoch   3, step    17000: bleu:  16.71, loss: 53433.0781, ppl:   7.7581, duration: 91.7078s\n",
      "2020-02-17 09:26:37,815 Epoch   3 Step:    17100 Batch Loss:     2.129432 Tokens per Sec:     6725, Lr: 0.000300\n",
      "2020-02-17 09:27:07,389 Epoch   3 Step:    17200 Batch Loss:     2.136260 Tokens per Sec:     7060, Lr: 0.000300\n",
      "2020-02-17 09:27:36,434 Epoch   3 Step:    17300 Batch Loss:     1.905008 Tokens per Sec:     6858, Lr: 0.000300\n",
      "2020-02-17 09:28:05,831 Epoch   3 Step:    17400 Batch Loss:     1.603422 Tokens per Sec:     6972, Lr: 0.000300\n",
      "2020-02-17 09:28:34,864 Epoch   3 Step:    17500 Batch Loss:     2.476538 Tokens per Sec:     6826, Lr: 0.000300\n",
      "2020-02-17 09:29:04,055 Epoch   3 Step:    17600 Batch Loss:     2.179893 Tokens per Sec:     6948, Lr: 0.000300\n",
      "2020-02-17 09:29:33,296 Epoch   3 Step:    17700 Batch Loss:     1.951782 Tokens per Sec:     6964, Lr: 0.000300\n",
      "2020-02-17 09:30:02,584 Epoch   3 Step:    17800 Batch Loss:     2.281326 Tokens per Sec:     6927, Lr: 0.000300\n",
      "2020-02-17 09:30:32,251 Epoch   3 Step:    17900 Batch Loss:     2.322883 Tokens per Sec:     7037, Lr: 0.000300\n",
      "2020-02-17 09:31:01,283 Epoch   3 Step:    18000 Batch Loss:     1.874112 Tokens per Sec:     6940, Lr: 0.000300\n",
      "2020-02-17 09:32:32,712 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 09:32:32,712 Saving new checkpoint.\n",
      "2020-02-17 09:32:32,933 Example #0\n",
      "2020-02-17 09:32:32,934 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 09:32:32,934 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 09:32:32,934 \tHypothesis: Na kati ya libota ya Davidi , Davidi amonisaki moto moko ya kondima .\n",
      "2020-02-17 09:32:32,934 Example #1\n",
      "2020-02-17 09:32:32,934 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 09:32:32,934 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 09:32:32,934 \tHypothesis: Eliya alobaki boye : “ Eliya apesaki Yehova lokumu monene na Baala . ”\n",
      "2020-02-17 09:32:32,934 Example #2\n",
      "2020-02-17 09:32:32,935 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 09:32:32,935 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 09:32:32,935 \tHypothesis: Nazwaki ekateli ya kosala yango mpe mpo na kolonga yango , mpe mpo na kolonga yango , nsukansuka nasengelaki kosala yango .\n",
      "2020-02-17 09:32:32,935 Example #3\n",
      "2020-02-17 09:32:32,935 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 09:32:32,935 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 09:32:32,935 \tHypothesis: Koboma bato ezali mpe na ntina te , ata soki azali na maladi .\n",
      "2020-02-17 09:32:32,935 Example #5\n",
      "2020-02-17 09:32:32,935 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 09:32:32,936 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 09:32:32,936 \tHypothesis: Mbala mosusu okoki koyeba ete ozali na baninga na ye .\n",
      "2020-02-17 09:32:32,936 Example #10\n",
      "2020-02-17 09:32:32,936 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 09:32:32,936 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 09:32:32,936 \tHypothesis: Koyika mpiko na komekama ya ndenge wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 09:32:32,936 Validation result at epoch   3, step    18000: bleu:  17.02, loss: 52861.1523, ppl:   7.5898, duration: 91.6519s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 09:33:02,137 Epoch   3 Step:    18100 Batch Loss:     1.708775 Tokens per Sec:     6905, Lr: 0.000300\n",
      "2020-02-17 09:33:31,243 Epoch   3 Step:    18200 Batch Loss:     2.186720 Tokens per Sec:     6863, Lr: 0.000300\n",
      "2020-02-17 09:34:00,417 Epoch   3 Step:    18300 Batch Loss:     2.282720 Tokens per Sec:     6951, Lr: 0.000300\n",
      "2020-02-17 09:34:29,985 Epoch   3 Step:    18400 Batch Loss:     2.225725 Tokens per Sec:     7037, Lr: 0.000300\n",
      "2020-02-17 09:34:58,848 Epoch   3 Step:    18500 Batch Loss:     2.149023 Tokens per Sec:     6807, Lr: 0.000300\n",
      "2020-02-17 09:35:28,403 Epoch   3 Step:    18600 Batch Loss:     2.124123 Tokens per Sec:     7097, Lr: 0.000300\n",
      "2020-02-17 09:35:57,453 Epoch   3 Step:    18700 Batch Loss:     1.731421 Tokens per Sec:     6760, Lr: 0.000300\n",
      "2020-02-17 09:36:26,276 Epoch   3 Step:    18800 Batch Loss:     1.954953 Tokens per Sec:     6865, Lr: 0.000300\n",
      "2020-02-17 09:36:55,685 Epoch   3 Step:    18900 Batch Loss:     2.272881 Tokens per Sec:     6865, Lr: 0.000300\n",
      "2020-02-17 09:37:25,187 Epoch   3 Step:    19000 Batch Loss:     2.553698 Tokens per Sec:     7075, Lr: 0.000300\n",
      "2020-02-17 09:38:56,533 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 09:38:56,534 Saving new checkpoint.\n",
      "2020-02-17 09:38:56,751 Example #0\n",
      "2020-02-17 09:38:56,751 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 09:38:56,752 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 09:38:56,752 \tHypothesis: Na kati ya libondeli , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 09:38:56,752 Example #1\n",
      "2020-02-17 09:38:56,752 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 09:38:56,752 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 09:38:56,752 \tHypothesis: Eliya amonisaki ete Yehova azali Mozwi - ya - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - - -\n",
      "2020-02-17 09:38:56,752 Example #2\n",
      "2020-02-17 09:38:56,752 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 09:38:56,752 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 09:38:56,752 \tHypothesis: Yango wana , nazwaki ekateli ya kosala yango , mpe mpo na kokitisa motema na ngai , mpo na libela , nsukansuka nsukansuka , nsukansuka , nsukansuka , nsukansuka , nsukansuka , nsukansuka nsukansuka , nsukansuka , nsukansuka nsukansuka , nsukansuka namonaki ete natiki .\n",
      "2020-02-17 09:38:56,753 Example #3\n",
      "2020-02-17 09:38:56,753 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 09:38:56,753 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 09:38:56,753 \tHypothesis: Bavoka yango ezali mpe na ntina mingi mpo na kosikolama , atako ezali na ntina mingi .\n",
      "2020-02-17 09:38:56,753 Example #5\n",
      "2020-02-17 09:38:56,753 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 09:38:56,753 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 09:38:56,753 \tHypothesis: Mbala mosusu okoyoka baninga na ye .\n",
      "2020-02-17 09:38:56,753 Example #10\n",
      "2020-02-17 09:38:56,753 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 09:38:56,753 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 09:38:56,754 \tHypothesis: Elikya ya koyika mpiko na komekama ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 09:38:56,754 Validation result at epoch   3, step    19000: bleu:  17.63, loss: 52035.2812, ppl:   7.3532, duration: 91.5664s\n",
      "2020-02-17 09:39:25,802 Epoch   3 Step:    19100 Batch Loss:     1.976999 Tokens per Sec:     6905, Lr: 0.000300\n",
      "2020-02-17 09:39:54,500 Epoch   3 Step:    19200 Batch Loss:     2.182083 Tokens per Sec:     6730, Lr: 0.000300\n",
      "2020-02-17 09:40:23,938 Epoch   3 Step:    19300 Batch Loss:     2.039794 Tokens per Sec:     6946, Lr: 0.000300\n",
      "2020-02-17 09:40:53,446 Epoch   3 Step:    19400 Batch Loss:     2.074493 Tokens per Sec:     6970, Lr: 0.000300\n",
      "2020-02-17 09:41:22,481 Epoch   3 Step:    19500 Batch Loss:     2.106228 Tokens per Sec:     6782, Lr: 0.000300\n",
      "2020-02-17 09:41:51,492 Epoch   3 Step:    19600 Batch Loss:     2.055134 Tokens per Sec:     6934, Lr: 0.000300\n",
      "2020-02-17 09:42:20,631 Epoch   3 Step:    19700 Batch Loss:     1.911102 Tokens per Sec:     6904, Lr: 0.000300\n",
      "2020-02-17 09:42:50,241 Epoch   3 Step:    19800 Batch Loss:     2.089189 Tokens per Sec:     6980, Lr: 0.000300\n",
      "2020-02-17 09:43:19,544 Epoch   3 Step:    19900 Batch Loss:     1.919728 Tokens per Sec:     6734, Lr: 0.000300\n",
      "2020-02-17 09:43:48,196 Epoch   3 Step:    20000 Batch Loss:     1.976227 Tokens per Sec:     6812, Lr: 0.000300\n",
      "2020-02-17 09:45:19,560 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 09:45:19,560 Saving new checkpoint.\n",
      "2020-02-17 09:45:19,782 Example #0\n",
      "2020-02-17 09:45:19,782 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 09:45:19,782 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 09:45:19,782 \tHypothesis: Na kati ya libondeli , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 09:45:19,783 Example #1\n",
      "2020-02-17 09:45:19,783 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 09:45:19,783 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 09:45:19,783 \tHypothesis: Eliya amimonisaki ete Yehova azali na kati ya Baala .\n",
      "2020-02-17 09:45:19,783 Example #2\n",
      "2020-02-17 09:45:19,783 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 09:45:19,783 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 09:45:19,783 \tHypothesis: Yango wana , nazwaki ekateli ya kosala yango , mpe nsukansuka nasengelaki kosala yango .\n",
      "2020-02-17 09:45:19,784 Example #3\n",
      "2020-02-17 09:45:19,784 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 09:45:19,784 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 09:45:19,784 \tHypothesis: Soki moto azali na mposa ya kosala bongo , ata soki azali na mposa ya kosala yango .\n",
      "2020-02-17 09:45:19,784 Example #5\n",
      "2020-02-17 09:45:19,784 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 09:45:19,784 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 09:45:19,785 \tHypothesis: Mbala mosusu okoki koyoka baninga na ye .\n",
      "2020-02-17 09:45:19,785 Example #10\n",
      "2020-02-17 09:45:19,785 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 09:45:19,785 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 09:45:19,785 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 09:45:19,785 Validation result at epoch   3, step    20000: bleu:  17.72, loss: 51777.2344, ppl:   7.2808, duration: 91.5884s\n",
      "2020-02-17 09:45:49,197 Epoch   3 Step:    20100 Batch Loss:     2.268797 Tokens per Sec:     6933, Lr: 0.000300\n",
      "2020-02-17 09:46:17,692 Epoch   3 Step:    20200 Batch Loss:     2.157919 Tokens per Sec:     6811, Lr: 0.000300\n",
      "2020-02-17 09:46:47,091 Epoch   3 Step:    20300 Batch Loss:     2.226736 Tokens per Sec:     6967, Lr: 0.000300\n",
      "2020-02-17 09:47:15,628 Epoch   3: total training loss 14979.58\n",
      "2020-02-17 09:47:15,628 EPOCH 4\n",
      "2020-02-17 09:47:17,073 Epoch   4 Step:    20400 Batch Loss:     2.129927 Tokens per Sec:     2949, Lr: 0.000300\n",
      "2020-02-17 09:47:46,070 Epoch   4 Step:    20500 Batch Loss:     1.545408 Tokens per Sec:     6783, Lr: 0.000300\n",
      "2020-02-17 09:48:14,990 Epoch   4 Step:    20600 Batch Loss:     1.972607 Tokens per Sec:     6888, Lr: 0.000300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 09:48:44,168 Epoch   4 Step:    20700 Batch Loss:     2.197956 Tokens per Sec:     6913, Lr: 0.000300\n",
      "2020-02-17 09:49:13,122 Epoch   4 Step:    20800 Batch Loss:     2.067028 Tokens per Sec:     6957, Lr: 0.000300\n",
      "2020-02-17 09:49:42,085 Epoch   4 Step:    20900 Batch Loss:     1.997718 Tokens per Sec:     6982, Lr: 0.000300\n",
      "2020-02-17 09:50:11,321 Epoch   4 Step:    21000 Batch Loss:     2.022940 Tokens per Sec:     6960, Lr: 0.000300\n",
      "2020-02-17 09:51:42,786 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 09:51:42,786 Saving new checkpoint.\n",
      "2020-02-17 09:51:43,008 Example #0\n",
      "2020-02-17 09:51:43,009 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 09:51:43,009 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 09:51:43,009 \tHypothesis: Na esika ya liboso , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 09:51:43,009 Example #1\n",
      "2020-02-17 09:51:43,009 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 09:51:43,009 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 09:51:43,009 \tHypothesis: Eliya amonisaki ete Yehova azali na ngɔlu na Baala .\n",
      "2020-02-17 09:51:43,009 Example #2\n",
      "2020-02-17 09:51:43,010 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 09:51:43,010 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 09:51:43,010 \tHypothesis: Na yango , nazwaki ekateli ya kosala makambo ya mabe , mpe mpo na kosukisa yango na mikolo na ngai .\n",
      "2020-02-17 09:51:43,010 Example #3\n",
      "2020-02-17 09:51:43,010 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 09:51:43,010 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 09:51:43,010 \tHypothesis: Bato oyo bazali na maladi ya mposo bazali mpe na mposa ya kosɛka , ata soki bazali koyoka yango .\n",
      "2020-02-17 09:51:43,010 Example #5\n",
      "2020-02-17 09:51:43,010 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 09:51:43,010 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 09:51:43,011 \tHypothesis: Mbala mosusu okoki komona ete ozali na baninga na ye .\n",
      "2020-02-17 09:51:43,011 Example #10\n",
      "2020-02-17 09:51:43,011 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 09:51:43,011 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 09:51:43,011 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 09:51:43,011 Validation result at epoch   4, step    21000: bleu:  17.34, loss: 51327.2812, ppl:   7.1563, duration: 91.6889s\n",
      "2020-02-17 09:52:11,649 Epoch   4 Step:    21100 Batch Loss:     2.108730 Tokens per Sec:     6920, Lr: 0.000300\n",
      "2020-02-17 09:52:41,052 Epoch   4 Step:    21200 Batch Loss:     2.321123 Tokens per Sec:     6982, Lr: 0.000300\n",
      "2020-02-17 09:53:10,373 Epoch   4 Step:    21300 Batch Loss:     2.274537 Tokens per Sec:     6864, Lr: 0.000300\n",
      "2020-02-17 09:53:39,830 Epoch   4 Step:    21400 Batch Loss:     1.988592 Tokens per Sec:     7044, Lr: 0.000300\n",
      "2020-02-17 09:54:09,131 Epoch   4 Step:    21500 Batch Loss:     1.971646 Tokens per Sec:     6955, Lr: 0.000300\n",
      "2020-02-17 09:54:38,455 Epoch   4 Step:    21600 Batch Loss:     2.137237 Tokens per Sec:     6981, Lr: 0.000300\n",
      "2020-02-17 09:55:07,948 Epoch   4 Step:    21700 Batch Loss:     2.421207 Tokens per Sec:     7012, Lr: 0.000300\n",
      "2020-02-17 09:55:36,835 Epoch   4 Step:    21800 Batch Loss:     2.284278 Tokens per Sec:     6739, Lr: 0.000300\n",
      "2020-02-17 09:56:06,112 Epoch   4 Step:    21900 Batch Loss:     2.023875 Tokens per Sec:     7004, Lr: 0.000300\n",
      "2020-02-17 09:56:35,084 Epoch   4 Step:    22000 Batch Loss:     2.113459 Tokens per Sec:     6865, Lr: 0.000300\n",
      "2020-02-17 09:58:06,565 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 09:58:06,565 Saving new checkpoint.\n",
      "2020-02-17 09:58:06,793 Example #0\n",
      "2020-02-17 09:58:06,794 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 09:58:06,794 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 09:58:06,794 \tHypothesis: Davidi azalaki moto ya kondima .\n",
      "2020-02-17 09:58:06,794 Example #1\n",
      "2020-02-17 09:58:06,794 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 09:58:06,794 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 09:58:06,794 \tHypothesis: Eliya amonisi ete Yehova azali na Baala .\n",
      "2020-02-17 09:58:06,795 Example #2\n",
      "2020-02-17 09:58:06,795 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 09:58:06,795 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 09:58:06,795 \tHypothesis: Yango wana , nazwaki ekateli ya kosala makasi mpe ya makasi , mpo na libela , nasengelaki kotika mikolo na ngai .\n",
      "2020-02-17 09:58:06,795 Example #3\n",
      "2020-02-17 09:58:06,795 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 09:58:06,795 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 09:58:06,795 \tHypothesis: Moto oyo azali na maladi ya monganga akoki mpe kosala yango , ata soki azali na mawa .\n",
      "2020-02-17 09:58:06,795 Example #5\n",
      "2020-02-17 09:58:06,796 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 09:58:06,796 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 09:58:06,796 \tHypothesis: Mbala mosusu okomona ete baninga na ye bazali na baninga na ye .\n",
      "2020-02-17 09:58:06,796 Example #10\n",
      "2020-02-17 09:58:06,796 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 09:58:06,796 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 09:58:06,796 \tHypothesis: Koyika mpiko na komekama ya ndenge wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 09:58:06,796 Validation result at epoch   4, step    22000: bleu:  18.16, loss: 50891.7656, ppl:   7.0378, duration: 91.7114s\n",
      "2020-02-17 09:58:36,422 Epoch   4 Step:    22100 Batch Loss:     2.192887 Tokens per Sec:     7039, Lr: 0.000300\n",
      "2020-02-17 09:59:05,191 Epoch   4 Step:    22200 Batch Loss:     2.172931 Tokens per Sec:     7025, Lr: 0.000300\n",
      "2020-02-17 09:59:34,173 Epoch   4 Step:    22300 Batch Loss:     2.077983 Tokens per Sec:     6861, Lr: 0.000300\n",
      "2020-02-17 10:00:03,494 Epoch   4 Step:    22400 Batch Loss:     2.311180 Tokens per Sec:     7116, Lr: 0.000300\n",
      "2020-02-17 10:00:32,533 Epoch   4 Step:    22500 Batch Loss:     1.869059 Tokens per Sec:     6861, Lr: 0.000300\n",
      "2020-02-17 10:01:01,592 Epoch   4 Step:    22600 Batch Loss:     2.184363 Tokens per Sec:     6982, Lr: 0.000300\n",
      "2020-02-17 10:01:30,834 Epoch   4 Step:    22700 Batch Loss:     2.030013 Tokens per Sec:     6968, Lr: 0.000300\n",
      "2020-02-17 10:01:59,829 Epoch   4 Step:    22800 Batch Loss:     2.226965 Tokens per Sec:     6850, Lr: 0.000300\n",
      "2020-02-17 10:02:29,098 Epoch   4 Step:    22900 Batch Loss:     2.042089 Tokens per Sec:     6948, Lr: 0.000300\n",
      "2020-02-17 10:02:57,985 Epoch   4 Step:    23000 Batch Loss:     2.131423 Tokens per Sec:     7039, Lr: 0.000300\n",
      "2020-02-17 10:04:29,344 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 10:04:29,344 Saving new checkpoint.\n",
      "2020-02-17 10:04:29,571 Example #0\n",
      "2020-02-17 10:04:29,572 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 10:04:29,572 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 10:04:29,572 \tHypothesis: Na kati ya libota ya Davidi , Davidi amonisaki kondima makasi .\n",
      "2020-02-17 10:04:29,572 Example #1\n",
      "2020-02-17 10:04:29,572 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 10:04:29,572 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 10:04:29,573 \tHypothesis: Eliya amonisaki ete Yehova azali na kati ya Baala .\n",
      "2020-02-17 10:04:29,573 Example #2\n",
      "2020-02-17 10:04:29,573 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 10:04:29,573 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 10:04:29,573 \tHypothesis: Na yango , nazwaki ekateli ya kosala yango mpe mpo na kokólisa yango , mpo na libela , nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka .\n",
      "2020-02-17 10:04:29,573 Example #3\n",
      "2020-02-17 10:04:29,574 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 10:04:29,574 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 10:04:29,574 \tHypothesis: Soki moto azali na maladi ya ntolo , akoki mpe kosala yango na ndenge ya malamu .\n",
      "2020-02-17 10:04:29,574 Example #5\n",
      "2020-02-17 10:04:29,574 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 10:04:29,574 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 10:04:29,574 \tHypothesis: Mbala mosusu , okoki koyeba baninga na ye .\n",
      "2020-02-17 10:04:29,574 Example #10\n",
      "2020-02-17 10:04:29,575 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 10:04:29,575 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 10:04:29,575 \tHypothesis: Koyika mpiko na komekama ya ndenge wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 10:04:29,575 Validation result at epoch   4, step    23000: bleu:  18.18, loss: 50144.2617, ppl:   6.8390, duration: 91.5895s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 10:04:58,467 Epoch   4 Step:    23100 Batch Loss:     2.035593 Tokens per Sec:     6812, Lr: 0.000300\n",
      "2020-02-17 10:05:27,402 Epoch   4 Step:    23200 Batch Loss:     2.139553 Tokens per Sec:     6869, Lr: 0.000300\n",
      "2020-02-17 10:05:56,351 Epoch   4 Step:    23300 Batch Loss:     1.857862 Tokens per Sec:     6869, Lr: 0.000300\n",
      "2020-02-17 10:06:25,299 Epoch   4 Step:    23400 Batch Loss:     1.932727 Tokens per Sec:     6876, Lr: 0.000300\n",
      "2020-02-17 10:06:54,585 Epoch   4 Step:    23500 Batch Loss:     1.720197 Tokens per Sec:     6792, Lr: 0.000300\n",
      "2020-02-17 10:07:23,935 Epoch   4 Step:    23600 Batch Loss:     2.016006 Tokens per Sec:     7092, Lr: 0.000300\n",
      "2020-02-17 10:07:52,864 Epoch   4 Step:    23700 Batch Loss:     2.253616 Tokens per Sec:     6864, Lr: 0.000300\n",
      "2020-02-17 10:08:21,725 Epoch   4 Step:    23800 Batch Loss:     2.016414 Tokens per Sec:     6837, Lr: 0.000300\n",
      "2020-02-17 10:08:51,059 Epoch   4 Step:    23900 Batch Loss:     1.954718 Tokens per Sec:     7001, Lr: 0.000300\n",
      "2020-02-17 10:09:20,266 Epoch   4 Step:    24000 Batch Loss:     2.517013 Tokens per Sec:     6981, Lr: 0.000300\n",
      "2020-02-17 10:10:51,631 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 10:10:51,631 Saving new checkpoint.\n",
      "2020-02-17 10:10:51,864 Example #0\n",
      "2020-02-17 10:10:51,864 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 10:10:51,864 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 10:10:51,864 \tHypothesis: Na esika yango , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 10:10:51,864 Example #1\n",
      "2020-02-17 10:10:51,864 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 10:10:51,865 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 10:10:51,865 \tHypothesis: Eliya amonisaki ete Yehova azali mpenza Mozwi - ya - Nguya - Nyonso .\n",
      "2020-02-17 10:10:51,865 Example #2\n",
      "2020-02-17 10:10:51,865 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 10:10:51,865 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 10:10:51,865 \tHypothesis: Na yango , nazwaki ekateli ya kosala makambo oyo nasengeli kosala mpe kosala mpo na kosilisa yango mikolo na ngai .\n",
      "2020-02-17 10:10:51,865 Example #3\n",
      "2020-02-17 10:10:51,865 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 10:10:51,865 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 10:10:51,865 \tHypothesis: Bato ya mayele bazali mpe na mposa ya kosɛka , ata soki bazali na mawa .\n",
      "2020-02-17 10:10:51,865 Example #5\n",
      "2020-02-17 10:10:51,866 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 10:10:51,866 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 10:10:51,866 \tHypothesis: Mbala mosusu okoki koyeba makambo oyo azali kosala .\n",
      "2020-02-17 10:10:51,866 Example #10\n",
      "2020-02-17 10:10:51,866 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 10:10:51,866 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 10:10:51,866 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 10:10:51,866 Validation result at epoch   4, step    24000: bleu:  18.82, loss: 49846.0352, ppl:   6.7612, duration: 91.5993s\n",
      "2020-02-17 10:11:20,673 Epoch   4 Step:    24100 Batch Loss:     1.873614 Tokens per Sec:     6886, Lr: 0.000300\n",
      "2020-02-17 10:11:49,526 Epoch   4 Step:    24200 Batch Loss:     2.138924 Tokens per Sec:     6966, Lr: 0.000300\n",
      "2020-02-17 10:12:18,730 Epoch   4 Step:    24300 Batch Loss:     2.017256 Tokens per Sec:     6924, Lr: 0.000300\n",
      "2020-02-17 10:12:47,747 Epoch   4 Step:    24400 Batch Loss:     2.640172 Tokens per Sec:     6933, Lr: 0.000300\n",
      "2020-02-17 10:13:16,756 Epoch   4 Step:    24500 Batch Loss:     1.889686 Tokens per Sec:     6822, Lr: 0.000300\n",
      "2020-02-17 10:13:45,737 Epoch   4 Step:    24600 Batch Loss:     2.114933 Tokens per Sec:     6917, Lr: 0.000300\n",
      "2020-02-17 10:14:14,718 Epoch   4 Step:    24700 Batch Loss:     2.173618 Tokens per Sec:     6928, Lr: 0.000300\n",
      "2020-02-17 10:14:43,986 Epoch   4 Step:    24800 Batch Loss:     2.076092 Tokens per Sec:     7055, Lr: 0.000300\n",
      "2020-02-17 10:15:12,959 Epoch   4 Step:    24900 Batch Loss:     2.071868 Tokens per Sec:     6882, Lr: 0.000300\n",
      "2020-02-17 10:15:42,186 Epoch   4 Step:    25000 Batch Loss:     1.974896 Tokens per Sec:     7032, Lr: 0.000300\n",
      "2020-02-17 10:17:13,487 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 10:17:13,488 Saving new checkpoint.\n",
      "2020-02-17 10:17:13,708 Example #0\n",
      "2020-02-17 10:17:13,708 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 10:17:13,708 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 10:17:13,708 \tHypothesis: Na esika moko , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 10:17:13,708 Example #1\n",
      "2020-02-17 10:17:13,708 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 10:17:13,708 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 10:17:13,708 \tHypothesis: Eliya amonisaki ete Yehova azali Mozwi - ya - Nguya - Nyonso .\n",
      "2020-02-17 10:17:13,708 Example #2\n",
      "2020-02-17 10:17:13,709 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 10:17:13,709 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 10:17:13,709 \tHypothesis: Nazwaki ekateli ya kosala yango mpe mpo na ngai , mpo na kozwa mikolo na ngai .\n",
      "2020-02-17 10:17:13,709 Example #3\n",
      "2020-02-17 10:17:13,709 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 10:17:13,709 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 10:17:13,709 \tHypothesis: Soki moto azali na maladi ya monganga , ata soki azali na maladi .\n",
      "2020-02-17 10:17:13,709 Example #5\n",
      "2020-02-17 10:17:13,709 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 10:17:13,709 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 10:17:13,710 \tHypothesis: Mbala mosusu okoki koyeba ete ozali na baninga na ye .\n",
      "2020-02-17 10:17:13,710 Example #10\n",
      "2020-02-17 10:17:13,710 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 10:17:13,710 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 10:17:13,710 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 10:17:13,710 Validation result at epoch   4, step    25000: bleu:  18.57, loss: 49549.5508, ppl:   6.6848, duration: 91.5232s\n",
      "2020-02-17 10:17:42,976 Epoch   4 Step:    25100 Batch Loss:     1.965119 Tokens per Sec:     6984, Lr: 0.000300\n",
      "2020-02-17 10:18:12,466 Epoch   4 Step:    25200 Batch Loss:     2.003838 Tokens per Sec:     6996, Lr: 0.000300\n",
      "2020-02-17 10:18:41,764 Epoch   4 Step:    25300 Batch Loss:     1.767719 Tokens per Sec:     7016, Lr: 0.000300\n",
      "2020-02-17 10:19:11,045 Epoch   4 Step:    25400 Batch Loss:     2.364821 Tokens per Sec:     6974, Lr: 0.000300\n",
      "2020-02-17 10:19:39,850 Epoch   4 Step:    25500 Batch Loss:     1.820521 Tokens per Sec:     6935, Lr: 0.000300\n",
      "2020-02-17 10:20:08,746 Epoch   4 Step:    25600 Batch Loss:     2.070457 Tokens per Sec:     6875, Lr: 0.000300\n",
      "2020-02-17 10:20:37,769 Epoch   4 Step:    25700 Batch Loss:     2.004165 Tokens per Sec:     7009, Lr: 0.000300\n",
      "2020-02-17 10:21:06,727 Epoch   4 Step:    25800 Batch Loss:     1.899077 Tokens per Sec:     6845, Lr: 0.000300\n",
      "2020-02-17 10:21:35,978 Epoch   4 Step:    25900 Batch Loss:     1.969135 Tokens per Sec:     7037, Lr: 0.000300\n",
      "2020-02-17 10:22:05,296 Epoch   4 Step:    26000 Batch Loss:     2.304332 Tokens per Sec:     7130, Lr: 0.000300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 10:23:36,755 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 10:23:36,755 Saving new checkpoint.\n",
      "2020-02-17 10:23:36,976 Example #0\n",
      "2020-02-17 10:23:36,977 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 10:23:36,977 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 10:23:36,977 \tHypothesis: Na kati ya libota , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 10:23:36,977 Example #1\n",
      "2020-02-17 10:23:36,977 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 10:23:36,977 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 10:23:36,977 \tHypothesis: Eliya amonisaki ete Yehova azali na ngámbo ya Baala .\n",
      "2020-02-17 10:23:36,977 Example #2\n",
      "2020-02-17 10:23:36,977 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 10:23:36,977 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 10:23:36,977 \tHypothesis: Na yango , nazwaki ekateli ya kosala makambo oyo nazalaki kosala mpe mpo na mwa ntango , natikaki kotika mikolo na ngai .\n",
      "2020-02-17 10:23:36,978 Example #3\n",
      "2020-02-17 10:23:36,978 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 10:23:36,978 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 10:23:36,978 \tHypothesis: Moto oyo azali na maladi ya ntolo azali mpe na mposa ya kosembola ye , ata soki azali koyoka ye .\n",
      "2020-02-17 10:23:36,978 Example #5\n",
      "2020-02-17 10:23:36,978 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 10:23:36,978 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 10:23:36,978 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 10:23:36,978 Example #10\n",
      "2020-02-17 10:23:36,979 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 10:23:36,979 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 10:23:36,979 \tHypothesis: Koyika mpiko na komekama ya ndenge wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 10:23:36,979 Validation result at epoch   4, step    26000: bleu:  19.03, loss: 49035.4258, ppl:   6.5543, duration: 91.6818s\n",
      "2020-02-17 10:24:05,733 Epoch   4 Step:    26100 Batch Loss:     2.043577 Tokens per Sec:     6720, Lr: 0.000300\n",
      "2020-02-17 10:24:35,148 Epoch   4 Step:    26200 Batch Loss:     2.117927 Tokens per Sec:     7065, Lr: 0.000300\n",
      "2020-02-17 10:25:04,321 Epoch   4 Step:    26300 Batch Loss:     2.241499 Tokens per Sec:     6880, Lr: 0.000300\n",
      "2020-02-17 10:25:33,422 Epoch   4 Step:    26400 Batch Loss:     1.808983 Tokens per Sec:     6924, Lr: 0.000300\n",
      "2020-02-17 10:26:02,122 Epoch   4 Step:    26500 Batch Loss:     2.023237 Tokens per Sec:     6933, Lr: 0.000300\n",
      "2020-02-17 10:26:31,631 Epoch   4 Step:    26600 Batch Loss:     2.034943 Tokens per Sec:     7079, Lr: 0.000300\n",
      "2020-02-17 10:27:00,630 Epoch   4 Step:    26700 Batch Loss:     1.828008 Tokens per Sec:     6909, Lr: 0.000300\n",
      "2020-02-17 10:27:29,817 Epoch   4 Step:    26800 Batch Loss:     2.125790 Tokens per Sec:     7014, Lr: 0.000300\n",
      "2020-02-17 10:27:58,918 Epoch   4 Step:    26900 Batch Loss:     2.387079 Tokens per Sec:     6864, Lr: 0.000300\n",
      "2020-02-17 10:28:28,236 Epoch   4 Step:    27000 Batch Loss:     1.850065 Tokens per Sec:     6977, Lr: 0.000300\n",
      "2020-02-17 10:29:59,656 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 10:29:59,657 Saving new checkpoint.\n",
      "2020-02-17 10:29:59,882 Example #0\n",
      "2020-02-17 10:29:59,883 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 10:29:59,883 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 10:29:59,883 \tHypothesis: Na esika moko , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 10:29:59,883 Example #1\n",
      "2020-02-17 10:29:59,883 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 10:29:59,883 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 10:29:59,883 \tHypothesis: Eliya amonisaki ete Yehova azali na Baala .\n",
      "2020-02-17 10:29:59,883 Example #2\n",
      "2020-02-17 10:29:59,884 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 10:29:59,884 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 10:29:59,884 \tHypothesis: Na yango , namonaki ete nakoki kosala makambo oyo nasengeli kosala mpe nakoki kosala yango .\n",
      "2020-02-17 10:29:59,884 Example #3\n",
      "2020-02-17 10:29:59,884 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 10:29:59,884 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 10:29:59,884 \tHypothesis: Bato ya mayele bazali mpe na mposa ya kosikolama , ata soki moto azali na maladi .\n",
      "2020-02-17 10:29:59,884 Example #5\n",
      "2020-02-17 10:29:59,884 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 10:29:59,884 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 10:29:59,884 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 10:29:59,884 Example #10\n",
      "2020-02-17 10:29:59,885 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 10:29:59,885 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 10:29:59,885 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 10:29:59,885 Validation result at epoch   4, step    27000: bleu:  19.11, loss: 48913.8008, ppl:   6.5238, duration: 91.6483s\n",
      "2020-02-17 10:30:28,828 Epoch   4 Step:    27100 Batch Loss:     2.177678 Tokens per Sec:     6848, Lr: 0.000300\n",
      "2020-02-17 10:30:57,639 Epoch   4: total training loss 14063.12\n",
      "2020-02-17 10:30:57,640 EPOCH 5\n",
      "2020-02-17 10:30:58,755 Epoch   5 Step:    27200 Batch Loss:     2.439710 Tokens per Sec:     1805, Lr: 0.000300\n",
      "2020-02-17 10:31:27,678 Epoch   5 Step:    27300 Batch Loss:     2.006413 Tokens per Sec:     6803, Lr: 0.000300\n",
      "2020-02-17 10:31:56,439 Epoch   5 Step:    27400 Batch Loss:     2.017156 Tokens per Sec:     6869, Lr: 0.000300\n",
      "2020-02-17 10:32:25,604 Epoch   5 Step:    27500 Batch Loss:     2.305367 Tokens per Sec:     7007, Lr: 0.000300\n",
      "2020-02-17 10:32:54,608 Epoch   5 Step:    27600 Batch Loss:     2.138038 Tokens per Sec:     6898, Lr: 0.000300\n",
      "2020-02-17 10:33:24,118 Epoch   5 Step:    27700 Batch Loss:     1.895322 Tokens per Sec:     7065, Lr: 0.000300\n",
      "2020-02-17 10:33:53,224 Epoch   5 Step:    27800 Batch Loss:     2.255763 Tokens per Sec:     6853, Lr: 0.000300\n",
      "2020-02-17 10:34:22,295 Epoch   5 Step:    27900 Batch Loss:     1.880997 Tokens per Sec:     6770, Lr: 0.000300\n",
      "2020-02-17 10:34:51,654 Epoch   5 Step:    28000 Batch Loss:     1.665444 Tokens per Sec:     6980, Lr: 0.000300\n",
      "2020-02-17 10:36:23,000 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 10:36:23,000 Saving new checkpoint.\n",
      "2020-02-17 10:36:23,231 Example #0\n",
      "2020-02-17 10:36:23,231 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 10:36:23,231 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 10:36:23,231 \tHypothesis: Na esika moko , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 10:36:23,232 Example #1\n",
      "2020-02-17 10:36:23,232 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 10:36:23,232 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 10:36:23,232 \tHypothesis: Eliya amonisaki ete Yehova azali mpenza Mozwi - ya - Nguya - Nyonso .\n",
      "2020-02-17 10:36:23,232 Example #2\n",
      "2020-02-17 10:36:23,232 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 10:36:23,232 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 10:36:23,232 \tHypothesis: Yango wana , nazwaki ekateli ya kosala makasi mpo na kobongisa makambo na ngai , mpe mpo na libela , nsukansuka nakotika mikolo na ngai .\n",
      "2020-02-17 10:36:23,232 Example #3\n",
      "2020-02-17 10:36:23,232 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 10:36:23,233 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 10:36:23,233 \tHypothesis: Moto oyo azali na maladi ya ntolo azali mpe na mposa ya kosopa zemi , ata soki azali koyoka ye .\n",
      "2020-02-17 10:36:23,233 Example #5\n",
      "2020-02-17 10:36:23,233 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 10:36:23,233 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 10:36:23,233 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 10:36:23,233 Example #10\n",
      "2020-02-17 10:36:23,233 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 10:36:23,233 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 10:36:23,233 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 10:36:23,234 Validation result at epoch   5, step    28000: bleu:  19.39, loss: 48533.0664, ppl:   6.4293, duration: 91.5793s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 10:36:52,700 Epoch   5 Step:    28100 Batch Loss:     1.766538 Tokens per Sec:     7066, Lr: 0.000300\n",
      "2020-02-17 10:37:21,777 Epoch   5 Step:    28200 Batch Loss:     2.064702 Tokens per Sec:     6891, Lr: 0.000300\n",
      "2020-02-17 10:39:47,332 Epoch   5 Step:    28700 Batch Loss:     2.119048 Tokens per Sec:     6841, Lr: 0.000300\n",
      "2020-02-17 10:40:16,205 Epoch   5 Step:    28800 Batch Loss:     1.645769 Tokens per Sec:     6835, Lr: 0.000300\n",
      "2020-02-17 10:40:45,513 Epoch   5 Step:    28900 Batch Loss:     2.072735 Tokens per Sec:     7038, Lr: 0.000300\n",
      "2020-02-17 10:41:13,975 Epoch   5 Step:    29000 Batch Loss:     2.024241 Tokens per Sec:     6818, Lr: 0.000300\n",
      "2020-02-17 10:42:45,293 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 10:42:45,294 Saving new checkpoint.\n",
      "2020-02-17 10:42:45,518 Example #0\n",
      "2020-02-17 10:42:45,519 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 10:42:45,519 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 10:42:45,519 \tHypothesis: Na boyokani na ye elongo , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 10:42:45,519 Example #1\n",
      "2020-02-17 10:42:45,519 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 10:42:45,519 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 10:42:45,519 \tHypothesis: Eliya amonisaki ete Yehova azali na Baala .\n",
      "2020-02-17 10:42:45,519 Example #2\n",
      "2020-02-17 10:42:45,520 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 10:42:45,520 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 10:42:45,520 \tHypothesis: Na yango , nazwaki ekateli ya kosala makambo oyo nasengeli kosala , mpe nsukansuka natikaki mosala na ngai ya soda .\n",
      "2020-02-17 10:42:45,520 Example #3\n",
      "2020-02-17 10:42:45,520 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 10:42:45,520 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 10:42:45,520 \tHypothesis: Bato ya mayele bazali mpe na mposa ya kosembola , ata soki bazali koyoka ye .\n",
      "2020-02-17 10:42:45,520 Example #5\n",
      "2020-02-17 10:42:45,520 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 10:42:45,520 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 10:42:45,520 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 10:42:45,521 Example #10\n",
      "2020-02-17 10:42:45,521 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 10:42:45,521 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 10:42:45,521 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 10:42:45,521 Validation result at epoch   5, step    29000: bleu:  19.44, loss: 48354.8945, ppl:   6.3855, duration: 91.5452s\n",
      "2020-02-17 10:43:14,745 Epoch   5 Step:    29100 Batch Loss:     1.992519 Tokens per Sec:     7129, Lr: 0.000300\n",
      "2020-02-17 10:43:43,742 Epoch   5 Step:    29200 Batch Loss:     2.197410 Tokens per Sec:     6822, Lr: 0.000300\n",
      "2020-02-17 10:44:12,765 Epoch   5 Step:    29300 Batch Loss:     1.936037 Tokens per Sec:     6850, Lr: 0.000300\n",
      "2020-02-17 10:44:42,024 Epoch   5 Step:    29400 Batch Loss:     1.906659 Tokens per Sec:     7027, Lr: 0.000300\n",
      "2020-02-17 10:45:11,415 Epoch   5 Step:    29500 Batch Loss:     1.947223 Tokens per Sec:     7009, Lr: 0.000300\n",
      "2020-02-17 10:45:40,277 Epoch   5 Step:    29600 Batch Loss:     1.927097 Tokens per Sec:     6731, Lr: 0.000300\n",
      "2020-02-17 10:46:09,887 Epoch   5 Step:    29700 Batch Loss:     1.988719 Tokens per Sec:     7109, Lr: 0.000300\n",
      "2020-02-17 10:46:39,024 Epoch   5 Step:    29800 Batch Loss:     1.902413 Tokens per Sec:     6972, Lr: 0.000300\n",
      "2020-02-17 10:47:08,425 Epoch   5 Step:    29900 Batch Loss:     2.098003 Tokens per Sec:     6985, Lr: 0.000300\n",
      "2020-02-17 10:47:37,811 Epoch   5 Step:    30000 Batch Loss:     1.993972 Tokens per Sec:     6966, Lr: 0.000300\n",
      "2020-02-17 10:49:09,206 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 10:49:09,206 Saving new checkpoint.\n",
      "2020-02-17 10:49:09,433 Example #0\n",
      "2020-02-17 10:49:09,433 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 10:49:09,434 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 10:49:09,434 \tHypothesis: Na esika moko , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 10:49:09,434 Example #1\n",
      "2020-02-17 10:49:09,434 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 10:49:09,434 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 10:49:09,434 \tHypothesis: Eliya amonisaki ete Yehova azali Moala .\n",
      "2020-02-17 10:49:09,434 Example #2\n",
      "2020-02-17 10:49:09,434 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 10:49:09,434 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 10:49:09,434 \tHypothesis: Yango wana , nazwaki ekateli ya kosala makasi mpo na kosilisa mikakatano na ngai , mpe nsukansuka nakotika mikolo na ngai .\n",
      "2020-02-17 10:49:09,434 Example #3\n",
      "2020-02-17 10:49:09,435 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 10:49:09,435 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 10:49:09,435 \tHypothesis: Bato ya mayele bazali mpe na mposa ya kozwa zemi , ata soki bazali koyoka ye .\n",
      "2020-02-17 10:49:09,435 Example #5\n",
      "2020-02-17 10:49:09,435 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 10:49:09,435 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 10:49:09,435 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 10:49:09,435 Example #10\n",
      "2020-02-17 10:49:09,436 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 10:49:09,436 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 10:49:09,436 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 10:49:09,436 Validation result at epoch   5, step    30000: bleu:  19.63, loss: 47965.7539, ppl:   6.2909, duration: 91.6242s\n",
      "2020-02-17 10:49:38,249 Epoch   5 Step:    30100 Batch Loss:     2.067574 Tokens per Sec:     6936, Lr: 0.000300\n",
      "2020-02-17 10:50:07,562 Epoch   5 Step:    30200 Batch Loss:     2.028629 Tokens per Sec:     6864, Lr: 0.000300\n",
      "2020-02-17 10:50:36,772 Epoch   5 Step:    30300 Batch Loss:     1.911283 Tokens per Sec:     7086, Lr: 0.000300\n",
      "2020-02-17 10:51:05,969 Epoch   5 Step:    30400 Batch Loss:     2.048156 Tokens per Sec:     7035, Lr: 0.000300\n",
      "2020-02-17 10:51:34,940 Epoch   5 Step:    30500 Batch Loss:     1.847423 Tokens per Sec:     6888, Lr: 0.000300\n",
      "2020-02-17 10:52:04,395 Epoch   5 Step:    30600 Batch Loss:     2.058003 Tokens per Sec:     7029, Lr: 0.000300\n",
      "2020-02-17 10:52:33,528 Epoch   5 Step:    30700 Batch Loss:     2.093696 Tokens per Sec:     6838, Lr: 0.000300\n",
      "2020-02-17 10:53:02,816 Epoch   5 Step:    30800 Batch Loss:     2.027654 Tokens per Sec:     6956, Lr: 0.000300\n",
      "2020-02-17 10:53:31,696 Epoch   5 Step:    30900 Batch Loss:     1.991518 Tokens per Sec:     6901, Lr: 0.000300\n",
      "2020-02-17 10:54:00,878 Epoch   5 Step:    31000 Batch Loss:     1.854826 Tokens per Sec:     7000, Lr: 0.000300\n",
      "2020-02-17 10:55:32,286 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 10:55:32,286 Saving new checkpoint.\n",
      "2020-02-17 10:55:32,504 Example #0\n",
      "2020-02-17 10:55:32,505 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 10:55:32,505 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 10:55:32,505 \tHypothesis: Na esika moko , Davidi amonisaki moto moko ya kondima .\n",
      "2020-02-17 10:55:32,505 Example #1\n",
      "2020-02-17 10:55:32,505 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 10:55:32,505 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 10:55:32,505 \tHypothesis: Eliya amonisaki ete Yehova azali mpenza Mozwi - ya - Nguya - Nyonso .\n",
      "2020-02-17 10:55:32,505 Example #2\n",
      "2020-02-17 10:55:32,505 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 10:55:32,506 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 10:55:32,506 \tHypothesis: Nazwaki ekateli ya kosala makasi mpo na kokata likambo yango , mpe nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka nakokufa .\n",
      "2020-02-17 10:55:32,506 Example #3\n",
      "2020-02-17 10:55:32,506 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 10:55:32,506 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 10:55:32,506 \tHypothesis: Moto oyo azali na maladi ya ntolo azali mpe na mposa ya kosɛka , ata soki azali koyoka ye .\n",
      "2020-02-17 10:55:32,506 Example #5\n",
      "2020-02-17 10:55:32,506 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 10:55:32,506 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 10:55:32,506 \tHypothesis: Mbala mosusu okoyeba baninga na ye .\n",
      "2020-02-17 10:55:32,506 Example #10\n",
      "2020-02-17 10:55:32,507 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 10:55:32,507 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 10:55:32,507 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 10:55:32,507 Validation result at epoch   5, step    31000: bleu:  20.15, loss: 47858.8477, ppl:   6.2652, duration: 91.6284s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 10:56:02,117 Epoch   5 Step:    31100 Batch Loss:     1.977275 Tokens per Sec:     7150, Lr: 0.000300\n",
      "2020-02-17 10:56:31,081 Epoch   5 Step:    31200 Batch Loss:     2.323686 Tokens per Sec:     6807, Lr: 0.000300\n",
      "2020-02-17 10:57:00,535 Epoch   5 Step:    31300 Batch Loss:     2.118838 Tokens per Sec:     7051, Lr: 0.000300\n",
      "2020-02-17 10:57:29,591 Epoch   5 Step:    31400 Batch Loss:     2.168788 Tokens per Sec:     6922, Lr: 0.000300\n",
      "2020-02-17 10:57:58,405 Epoch   5 Step:    31500 Batch Loss:     1.920644 Tokens per Sec:     6784, Lr: 0.000300\n",
      "2020-02-17 10:58:27,944 Epoch   5 Step:    31600 Batch Loss:     1.927110 Tokens per Sec:     7085, Lr: 0.000300\n",
      "2020-02-17 10:58:56,930 Epoch   5 Step:    31700 Batch Loss:     2.047647 Tokens per Sec:     6862, Lr: 0.000300\n",
      "2020-02-17 10:59:26,249 Epoch   5 Step:    31800 Batch Loss:     1.771385 Tokens per Sec:     6917, Lr: 0.000300\n",
      "2020-02-17 10:59:55,244 Epoch   5 Step:    31900 Batch Loss:     1.898548 Tokens per Sec:     6863, Lr: 0.000300\n",
      "2020-02-17 11:00:24,407 Epoch   5 Step:    32000 Batch Loss:     1.908788 Tokens per Sec:     6814, Lr: 0.000300\n",
      "2020-02-17 11:01:55,913 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 11:01:55,913 Saving new checkpoint.\n",
      "2020-02-17 11:01:56,142 Example #0\n",
      "2020-02-17 11:01:56,142 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 11:01:56,142 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 11:01:56,142 \tHypothesis: Na esika yango , Davidi amonisaki moto moko ya kondima .\n",
      "2020-02-17 11:01:56,143 Example #1\n",
      "2020-02-17 11:01:56,143 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 11:01:56,143 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 11:01:56,143 \tHypothesis: Eliya amonisaki ete Yehova azali na kati ya Baala .\n",
      "2020-02-17 11:01:56,143 Example #2\n",
      "2020-02-17 11:01:56,143 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 11:01:56,143 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 11:01:56,143 \tHypothesis: Yango wana , nazwaki ekateli ya kosala makambo ya mabe mpe ya kokata makambo oyo nasengelaki kosala mpo na kosilisa yango mikolo na ngai .\n",
      "2020-02-17 11:01:56,143 Example #3\n",
      "2020-02-17 11:01:56,143 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 11:01:56,144 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 11:01:56,144 \tHypothesis: Bato oyo bakanisaka ete moto oyo azali na maladi ya ndɛkɛ , ata soki azali na mposa ya lisalisi .\n",
      "2020-02-17 11:01:56,144 Example #5\n",
      "2020-02-17 11:01:56,144 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 11:01:56,144 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 11:01:56,144 \tHypothesis: Mbala mosusu oyebi ete ozali na baninga na ye .\n",
      "2020-02-17 11:01:56,144 Example #10\n",
      "2020-02-17 11:01:56,144 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 11:01:56,144 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 11:01:56,144 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 11:01:56,144 Validation result at epoch   5, step    32000: bleu:  20.04, loss: 47841.9531, ppl:   6.2611, duration: 91.7367s\n",
      "2020-02-17 11:02:25,197 Epoch   5 Step:    32100 Batch Loss:     2.175315 Tokens per Sec:     6852, Lr: 0.000300\n",
      "2020-02-17 11:02:54,344 Epoch   5 Step:    32200 Batch Loss:     1.799944 Tokens per Sec:     6977, Lr: 0.000300\n",
      "2020-02-17 11:03:23,383 Epoch   5 Step:    32300 Batch Loss:     1.878414 Tokens per Sec:     6939, Lr: 0.000300\n",
      "2020-02-17 11:03:52,739 Epoch   5 Step:    32400 Batch Loss:     1.902613 Tokens per Sec:     7062, Lr: 0.000300\n",
      "2020-02-17 11:04:21,883 Epoch   5 Step:    32500 Batch Loss:     2.180094 Tokens per Sec:     6863, Lr: 0.000300\n",
      "2020-02-17 11:04:51,062 Epoch   5 Step:    32600 Batch Loss:     2.162165 Tokens per Sec:     7049, Lr: 0.000300\n",
      "2020-02-17 11:05:20,092 Epoch   5 Step:    32700 Batch Loss:     2.086959 Tokens per Sec:     6885, Lr: 0.000300\n",
      "2020-02-17 11:05:48,571 Epoch   5 Step:    32800 Batch Loss:     1.982254 Tokens per Sec:     6687, Lr: 0.000300\n",
      "2020-02-17 11:06:17,929 Epoch   5 Step:    32900 Batch Loss:     2.149108 Tokens per Sec:     6944, Lr: 0.000300\n",
      "2020-02-17 11:06:46,673 Epoch   5 Step:    33000 Batch Loss:     1.809000 Tokens per Sec:     6803, Lr: 0.000300\n",
      "2020-02-17 11:08:18,062 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 11:08:18,062 Saving new checkpoint.\n",
      "2020-02-17 11:08:18,286 Example #0\n",
      "2020-02-17 11:08:18,287 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 11:08:18,287 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 11:08:18,287 \tHypothesis: Na esika yango , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 11:08:18,287 Example #1\n",
      "2020-02-17 11:08:18,287 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 11:08:18,287 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 11:08:18,287 \tHypothesis: Eliya amonisaki ete Yehova azali na Baala .\n",
      "2020-02-17 11:08:18,287 Example #2\n",
      "2020-02-17 11:08:18,288 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 11:08:18,288 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 11:08:18,288 \tHypothesis: Nazwaki ekateli ya kosala mosala ya kobuka mbuma mpe ya makasi , ya kolongola mikolo na ngai .\n",
      "2020-02-17 11:08:18,288 Example #3\n",
      "2020-02-17 11:08:18,288 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 11:08:18,288 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 11:08:18,288 \tHypothesis: Bato ya mayele bazali mpe na mposa ya kosɛka , ata soki azali na mawa .\n",
      "2020-02-17 11:08:18,288 Example #5\n",
      "2020-02-17 11:08:18,288 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 11:08:18,288 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 11:08:18,288 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 11:08:18,289 Example #10\n",
      "2020-02-17 11:08:18,289 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 11:08:18,289 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 11:08:18,289 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na motuya mingi mpo na Yehova .\n",
      "2020-02-17 11:08:18,289 Validation result at epoch   5, step    33000: bleu:  19.64, loss: 47557.2461, ppl:   6.1932, duration: 91.6153s\n",
      "2020-02-17 11:08:47,430 Epoch   5 Step:    33100 Batch Loss:     2.022693 Tokens per Sec:     6916, Lr: 0.000300\n",
      "2020-02-17 11:09:16,361 Epoch   5 Step:    33200 Batch Loss:     2.316221 Tokens per Sec:     6983, Lr: 0.000300\n",
      "2020-02-17 11:09:45,334 Epoch   5 Step:    33300 Batch Loss:     2.145086 Tokens per Sec:     6933, Lr: 0.000300\n",
      "2020-02-17 11:10:14,415 Epoch   5 Step:    33400 Batch Loss:     1.579218 Tokens per Sec:     6915, Lr: 0.000300\n",
      "2020-02-17 11:10:43,525 Epoch   5 Step:    33500 Batch Loss:     1.862299 Tokens per Sec:     6925, Lr: 0.000300\n",
      "2020-02-17 11:11:12,634 Epoch   5 Step:    33600 Batch Loss:     2.178029 Tokens per Sec:     6852, Lr: 0.000300\n",
      "2020-02-17 11:11:41,681 Epoch   5 Step:    33700 Batch Loss:     2.008257 Tokens per Sec:     6884, Lr: 0.000300\n",
      "2020-02-17 11:12:11,156 Epoch   5 Step:    33800 Batch Loss:     1.869916 Tokens per Sec:     7089, Lr: 0.000300\n",
      "2020-02-17 11:12:39,936 Epoch   5 Step:    33900 Batch Loss:     2.016352 Tokens per Sec:     6820, Lr: 0.000300\n",
      "2020-02-17 11:13:09,096 Epoch   5 Step:    34000 Batch Loss:     1.719110 Tokens per Sec:     6875, Lr: 0.000300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 11:14:40,609 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 11:14:40,609 Saving new checkpoint.\n",
      "2020-02-17 11:14:40,837 Example #0\n",
      "2020-02-17 11:14:40,838 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 11:14:40,838 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 11:14:40,838 \tHypothesis: Na esika moko , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 11:14:40,838 Example #1\n",
      "2020-02-17 11:14:40,838 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 11:14:40,838 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 11:14:40,838 \tHypothesis: Eliya amonisaki ete Yehova azali na Baala .\n",
      "2020-02-17 11:14:40,838 Example #2\n",
      "2020-02-17 11:14:40,839 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 11:14:40,839 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 11:14:40,839 \tHypothesis: Na yango , namonaki ete nakoki kosala yango , mpe nsukansuka natikaki kotika mikolo na ngai .\n",
      "2020-02-17 11:14:40,839 Example #3\n",
      "2020-02-17 11:14:40,839 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 11:14:40,839 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 11:14:40,839 \tHypothesis: Bato ya siansi bazali mpe na mposa ya kosopa zemi , ata soki bazali koyoka ye .\n",
      "2020-02-17 11:14:40,839 Example #5\n",
      "2020-02-17 11:14:40,839 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 11:14:40,839 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 11:14:40,839 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 11:14:40,839 Example #10\n",
      "2020-02-17 11:14:40,840 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 11:14:40,840 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 11:14:40,840 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 11:14:40,840 Validation result at epoch   5, step    34000: bleu:  19.80, loss: 47185.0430, ppl:   6.1054, duration: 91.7431s\n",
      "2020-02-17 11:14:42,900 Epoch   5: total training loss 13481.46\n",
      "2020-02-17 11:14:42,900 EPOCH 6\n",
      "2020-02-17 11:15:10,625 Epoch   6 Step:    34100 Batch Loss:     2.052289 Tokens per Sec:     6733, Lr: 0.000300\n",
      "2020-02-17 11:15:40,019 Epoch   6 Step:    34200 Batch Loss:     1.870525 Tokens per Sec:     7061, Lr: 0.000300\n",
      "2020-02-17 11:16:08,804 Epoch   6 Step:    34300 Batch Loss:     2.088424 Tokens per Sec:     6839, Lr: 0.000300\n",
      "2020-02-17 11:16:38,046 Epoch   6 Step:    34400 Batch Loss:     2.026348 Tokens per Sec:     6917, Lr: 0.000300\n",
      "2020-02-17 11:17:07,301 Epoch   6 Step:    34500 Batch Loss:     1.958876 Tokens per Sec:     6889, Lr: 0.000300\n",
      "2020-02-17 11:17:36,945 Epoch   6 Step:    34600 Batch Loss:     2.070350 Tokens per Sec:     7000, Lr: 0.000300\n",
      "2020-02-17 11:18:06,162 Epoch   6 Step:    34700 Batch Loss:     1.796539 Tokens per Sec:     6961, Lr: 0.000300\n",
      "2020-02-17 11:18:35,309 Epoch   6 Step:    34800 Batch Loss:     2.149239 Tokens per Sec:     6914, Lr: 0.000300\n",
      "2020-02-17 11:19:04,228 Epoch   6 Step:    34900 Batch Loss:     1.895726 Tokens per Sec:     6762, Lr: 0.000300\n",
      "2020-02-17 11:19:33,622 Epoch   6 Step:    35000 Batch Loss:     2.152406 Tokens per Sec:     7025, Lr: 0.000300\n",
      "2020-02-17 11:21:05,184 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 11:21:05,184 Saving new checkpoint.\n",
      "2020-02-17 11:21:05,415 Example #0\n",
      "2020-02-17 11:21:05,415 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 11:21:05,416 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 11:21:05,416 \tHypothesis: Na esika yango , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 11:21:05,416 Example #1\n",
      "2020-02-17 11:21:05,416 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 11:21:05,416 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 11:21:05,416 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 11:21:05,416 Example #2\n",
      "2020-02-17 11:21:05,416 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 11:21:05,416 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 11:21:05,416 \tHypothesis: Yango wana , nazwaki ekateli ya kokangama na ngai mpe ya kokitisa motema , kotika mikolo na ngai .\n",
      "2020-02-17 11:21:05,417 Example #3\n",
      "2020-02-17 11:21:05,417 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 11:21:05,417 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 11:21:05,417 \tHypothesis: Moto oyo azali na maladi ya kasɛti yango azali mpe na mposa ya kosembola ye , ata soki azali koyoka ye .\n",
      "2020-02-17 11:21:05,417 Example #5\n",
      "2020-02-17 11:21:05,417 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 11:21:05,417 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 11:21:05,417 \tHypothesis: Mbala mosusu okoyeba baninga na ye .\n",
      "2020-02-17 11:21:05,417 Example #10\n",
      "2020-02-17 11:21:05,418 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 11:21:05,418 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 11:21:05,418 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 11:21:05,418 Validation result at epoch   6, step    35000: bleu:  20.57, loss: 46868.4336, ppl:   6.0317, duration: 91.7946s\n",
      "2020-02-17 11:21:34,899 Epoch   6 Step:    35100 Batch Loss:     2.113610 Tokens per Sec:     6861, Lr: 0.000300\n",
      "2020-02-17 11:22:03,972 Epoch   6 Step:    35200 Batch Loss:     2.020036 Tokens per Sec:     6935, Lr: 0.000300\n",
      "2020-02-17 11:22:33,174 Epoch   6 Step:    35300 Batch Loss:     2.184351 Tokens per Sec:     6971, Lr: 0.000300\n",
      "2020-02-17 11:23:02,232 Epoch   6 Step:    35400 Batch Loss:     2.245761 Tokens per Sec:     6851, Lr: 0.000300\n",
      "2020-02-17 11:23:31,780 Epoch   6 Step:    35500 Batch Loss:     1.783015 Tokens per Sec:     7048, Lr: 0.000300\n",
      "2020-02-17 11:24:00,756 Epoch   6 Step:    35600 Batch Loss:     1.790472 Tokens per Sec:     6908, Lr: 0.000300\n",
      "2020-02-17 11:24:30,240 Epoch   6 Step:    35700 Batch Loss:     1.741906 Tokens per Sec:     6914, Lr: 0.000300\n",
      "2020-02-17 11:24:58,947 Epoch   6 Step:    35800 Batch Loss:     1.943333 Tokens per Sec:     6780, Lr: 0.000300\n",
      "2020-02-17 11:25:28,658 Epoch   6 Step:    35900 Batch Loss:     2.071971 Tokens per Sec:     7065, Lr: 0.000300\n",
      "2020-02-17 11:25:58,019 Epoch   6 Step:    36000 Batch Loss:     1.890897 Tokens per Sec:     6951, Lr: 0.000300\n",
      "2020-02-17 11:27:29,443 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 11:27:29,443 Saving new checkpoint.\n",
      "2020-02-17 11:27:29,671 Example #0\n",
      "2020-02-17 11:27:29,671 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 11:27:29,671 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 11:27:29,671 \tHypothesis: Na esika moko , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 11:27:29,671 Example #1\n",
      "2020-02-17 11:27:29,672 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 11:27:29,672 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 11:27:29,672 \tHypothesis: Eliya amonisaki ete Yehova azali na Baala .\n",
      "2020-02-17 11:27:29,672 Example #2\n",
      "2020-02-17 11:27:29,672 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 11:27:29,672 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 11:27:29,672 \tHypothesis: Yango wana , nazwaki ekateli ya kosala makambo oyo nasengeli kosala mpe nsukansuka nsukansuka nsukansuka nsukansuka nakokóma na bomoi ya malamu .\n",
      "2020-02-17 11:27:29,672 Example #3\n",
      "2020-02-17 11:27:29,673 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 11:27:29,673 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 11:27:29,673 \tHypothesis: Moto oyo azali na maladi ya ntolo azali mpe na maladi ya kosopa zemi , ata soki azali koyoka .\n",
      "2020-02-17 11:27:29,673 Example #5\n",
      "2020-02-17 11:27:29,673 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 11:27:29,673 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 11:27:29,673 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 11:27:29,673 Example #10\n",
      "2020-02-17 11:27:29,673 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 11:27:29,673 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 11:27:29,673 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 11:27:29,673 Validation result at epoch   6, step    36000: bleu:  20.46, loss: 46619.8594, ppl:   5.9745, duration: 91.6535s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 11:27:59,237 Epoch   6 Step:    36100 Batch Loss:     1.910158 Tokens per Sec:     6981, Lr: 0.000300\n",
      "2020-02-17 11:28:28,086 Epoch   6 Step:    36200 Batch Loss:     1.809040 Tokens per Sec:     6753, Lr: 0.000300\n",
      "2020-02-17 11:28:57,742 Epoch   6 Step:    36300 Batch Loss:     1.982978 Tokens per Sec:     7026, Lr: 0.000300\n",
      "2020-02-17 11:29:27,137 Epoch   6 Step:    36400 Batch Loss:     1.751315 Tokens per Sec:     6880, Lr: 0.000300\n",
      "2020-02-17 11:29:56,294 Epoch   6 Step:    36500 Batch Loss:     2.023170 Tokens per Sec:     6939, Lr: 0.000300\n",
      "2020-02-17 11:30:25,497 Epoch   6 Step:    36600 Batch Loss:     1.770446 Tokens per Sec:     6876, Lr: 0.000300\n",
      "2020-02-17 11:30:54,524 Epoch   6 Step:    36700 Batch Loss:     2.014627 Tokens per Sec:     6891, Lr: 0.000300\n",
      "2020-02-17 11:31:23,960 Epoch   6 Step:    36800 Batch Loss:     2.115412 Tokens per Sec:     6809, Lr: 0.000300\n",
      "2020-02-17 11:31:52,878 Epoch   6 Step:    36900 Batch Loss:     2.063391 Tokens per Sec:     6870, Lr: 0.000300\n",
      "2020-02-17 11:32:22,445 Epoch   6 Step:    37000 Batch Loss:     1.916596 Tokens per Sec:     7015, Lr: 0.000300\n",
      "2020-02-17 11:33:53,907 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 11:33:53,907 Saving new checkpoint.\n",
      "2020-02-17 11:33:54,136 Example #0\n",
      "2020-02-17 11:33:54,137 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 11:33:54,137 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 11:33:54,137 \tHypothesis: Na kati ya libota ya Davidi , Davidi amonisaki kondima .\n",
      "2020-02-17 11:33:54,137 Example #1\n",
      "2020-02-17 11:33:54,137 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 11:33:54,137 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 11:33:54,137 \tHypothesis: Eliya amonisaki ete Yehova azali na Baala .\n",
      "2020-02-17 11:33:54,137 Example #2\n",
      "2020-02-17 11:33:54,138 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 11:33:54,138 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 11:33:54,138 \tHypothesis: Nazwaki ekateli ya kosala makambo na ndenge ya mabe mpe ya mpasi , ya kotika mikolo na ngai .\n",
      "2020-02-17 11:33:54,138 Example #3\n",
      "2020-02-17 11:33:54,138 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 11:33:54,138 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 11:33:54,138 \tHypothesis: Bato ya siansi bazali mpe na mposa ya kosembola , ata soki azali na mawa .\n",
      "2020-02-17 11:33:54,138 Example #5\n",
      "2020-02-17 11:33:54,138 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 11:33:54,139 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 11:33:54,139 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 11:33:54,139 Example #10\n",
      "2020-02-17 11:33:54,139 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 11:33:54,139 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 11:33:54,139 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 11:33:54,139 Validation result at epoch   6, step    37000: bleu:  20.56, loss: 46506.6641, ppl:   5.9486, duration: 91.6928s\n",
      "2020-02-17 11:34:22,859 Epoch   6 Step:    37100 Batch Loss:     1.989690 Tokens per Sec:     6853, Lr: 0.000300\n",
      "2020-02-17 11:34:52,198 Epoch   6 Step:    37200 Batch Loss:     1.760239 Tokens per Sec:     6942, Lr: 0.000300\n",
      "2020-02-17 11:35:21,593 Epoch   6 Step:    37300 Batch Loss:     1.853842 Tokens per Sec:     6951, Lr: 0.000300\n",
      "2020-02-17 11:35:50,846 Epoch   6 Step:    37400 Batch Loss:     1.963384 Tokens per Sec:     6791, Lr: 0.000300\n",
      "2020-02-17 11:36:20,416 Epoch   6 Step:    37500 Batch Loss:     1.955995 Tokens per Sec:     7060, Lr: 0.000300\n",
      "2020-02-17 11:36:49,562 Epoch   6 Step:    37600 Batch Loss:     1.919203 Tokens per Sec:     6844, Lr: 0.000300\n",
      "2020-02-17 11:37:18,296 Epoch   6 Step:    37700 Batch Loss:     1.884250 Tokens per Sec:     6930, Lr: 0.000300\n",
      "2020-02-17 11:37:47,339 Epoch   6 Step:    37800 Batch Loss:     1.943000 Tokens per Sec:     6971, Lr: 0.000300\n",
      "2020-02-17 11:38:16,691 Epoch   6 Step:    37900 Batch Loss:     1.925414 Tokens per Sec:     7055, Lr: 0.000300\n",
      "2020-02-17 11:38:46,134 Epoch   6 Step:    38000 Batch Loss:     1.907482 Tokens per Sec:     6946, Lr: 0.000300\n",
      "2020-02-17 11:40:17,583 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 11:40:17,584 Saving new checkpoint.\n",
      "2020-02-17 11:40:17,811 Example #0\n",
      "2020-02-17 11:40:17,811 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 11:40:17,811 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 11:40:17,811 \tHypothesis: Na esika moko , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 11:40:17,811 Example #1\n",
      "2020-02-17 11:40:17,812 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 11:40:17,812 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 11:40:17,812 \tHypothesis: Eliya amonisaki ete Yehova azali na Baala .\n",
      "2020-02-17 11:40:17,812 Example #2\n",
      "2020-02-17 11:40:17,812 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 11:40:17,812 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 11:40:17,812 \tHypothesis: Yango wana , nazwaki ekateli ya kosala makambo ya mabe mpe ya makasi mpo na libela , kotika yango na mikolo na ngai .\n",
      "2020-02-17 11:40:17,812 Example #3\n",
      "2020-02-17 11:40:17,813 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 11:40:17,813 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 11:40:17,813 \tHypothesis: Moto oyo azali na maladi ya miso azali mpe na mposa ya kosɛka , ata soki azali na mawa .\n",
      "2020-02-17 11:40:17,813 Example #5\n",
      "2020-02-17 11:40:17,813 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 11:40:17,813 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 11:40:17,813 \tHypothesis: Mbala mosusu oyebi baninga na ye .\n",
      "2020-02-17 11:40:17,813 Example #10\n",
      "2020-02-17 11:40:17,814 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 11:40:17,814 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 11:40:17,814 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 11:40:17,814 Validation result at epoch   6, step    38000: bleu:  20.62, loss: 46380.8789, ppl:   5.9200, duration: 91.6797s\n",
      "2020-02-17 11:40:47,123 Epoch   6 Step:    38100 Batch Loss:     2.004714 Tokens per Sec:     6938, Lr: 0.000300\n",
      "2020-02-17 11:41:16,275 Epoch   6 Step:    38200 Batch Loss:     1.689589 Tokens per Sec:     6858, Lr: 0.000300\n",
      "2020-02-17 11:41:45,336 Epoch   6 Step:    38300 Batch Loss:     2.237243 Tokens per Sec:     6900, Lr: 0.000300\n",
      "2020-02-17 11:42:14,225 Epoch   6 Step:    38400 Batch Loss:     2.078677 Tokens per Sec:     6905, Lr: 0.000300\n",
      "2020-02-17 11:42:43,170 Epoch   6 Step:    38500 Batch Loss:     1.783318 Tokens per Sec:     6911, Lr: 0.000300\n",
      "2020-02-17 11:43:12,074 Epoch   6 Step:    38600 Batch Loss:     1.852196 Tokens per Sec:     6854, Lr: 0.000300\n",
      "2020-02-17 11:43:41,269 Epoch   6 Step:    38700 Batch Loss:     1.866675 Tokens per Sec:     6978, Lr: 0.000300\n",
      "2020-02-17 11:44:10,436 Epoch   6 Step:    38800 Batch Loss:     1.799803 Tokens per Sec:     6911, Lr: 0.000300\n",
      "2020-02-17 11:44:39,609 Epoch   6 Step:    38900 Batch Loss:     1.804395 Tokens per Sec:     6852, Lr: 0.000300\n",
      "2020-02-17 11:45:08,746 Epoch   6 Step:    39000 Batch Loss:     1.830942 Tokens per Sec:     6851, Lr: 0.000300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 11:46:40,239 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 11:46:40,239 Saving new checkpoint.\n",
      "2020-02-17 11:46:40,465 Example #0\n",
      "2020-02-17 11:46:40,465 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 11:46:40,465 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 11:46:40,465 \tHypothesis: Na boyokani na ye , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 11:46:40,465 Example #1\n",
      "2020-02-17 11:46:40,466 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 11:46:40,466 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 11:46:40,466 \tHypothesis: Eliya amonisaki ete Yehova azali na Baala .\n",
      "2020-02-17 11:46:40,466 Example #2\n",
      "2020-02-17 11:46:40,466 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 11:46:40,466 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 11:46:40,466 \tHypothesis: Yango wana , nazwaki ekateli ya kosala makambo na ndenge ya malamu , mpe nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka , nsukansuka nsukansuka nsukansuka nsukansuka .\n",
      "2020-02-17 11:46:40,466 Example #3\n",
      "2020-02-17 11:46:40,467 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 11:46:40,467 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 11:46:40,467 \tHypothesis: Bato ya mayele bazali mpe na mposa ya kosembola moto , ata soki azali na mawa .\n",
      "2020-02-17 11:46:40,467 Example #5\n",
      "2020-02-17 11:46:40,467 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 11:46:40,467 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 11:46:40,467 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 11:46:40,467 Example #10\n",
      "2020-02-17 11:46:40,467 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 11:46:40,467 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 11:46:40,468 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 11:46:40,468 Validation result at epoch   6, step    39000: bleu:  20.51, loss: 46074.7070, ppl:   5.8509, duration: 91.7207s\n",
      "2020-02-17 11:47:09,527 Epoch   6 Step:    39100 Batch Loss:     2.083749 Tokens per Sec:     6890, Lr: 0.000300\n",
      "2020-02-17 11:47:38,400 Epoch   6 Step:    39200 Batch Loss:     2.022043 Tokens per Sec:     6859, Lr: 0.000300\n",
      "2020-02-17 11:48:07,292 Epoch   6 Step:    39300 Batch Loss:     1.719242 Tokens per Sec:     6974, Lr: 0.000300\n",
      "2020-02-17 11:48:36,354 Epoch   6 Step:    39400 Batch Loss:     2.018958 Tokens per Sec:     6925, Lr: 0.000300\n",
      "2020-02-17 11:49:05,478 Epoch   6 Step:    39500 Batch Loss:     2.005920 Tokens per Sec:     6985, Lr: 0.000300\n",
      "2020-02-17 11:49:34,356 Epoch   6 Step:    39600 Batch Loss:     1.889007 Tokens per Sec:     6921, Lr: 0.000300\n",
      "2020-02-17 11:50:03,690 Epoch   6 Step:    39700 Batch Loss:     1.878966 Tokens per Sec:     7015, Lr: 0.000300\n",
      "2020-02-17 11:50:32,738 Epoch   6 Step:    39800 Batch Loss:     1.862135 Tokens per Sec:     6880, Lr: 0.000300\n",
      "2020-02-17 11:51:01,685 Epoch   6 Step:    39900 Batch Loss:     1.833821 Tokens per Sec:     6874, Lr: 0.000300\n",
      "2020-02-17 11:51:30,388 Epoch   6 Step:    40000 Batch Loss:     1.853044 Tokens per Sec:     6659, Lr: 0.000300\n",
      "2020-02-17 11:53:01,866 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 11:53:01,867 Saving new checkpoint.\n",
      "2020-02-17 11:53:02,095 Example #0\n",
      "2020-02-17 11:53:02,095 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 11:53:02,095 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 11:53:02,095 \tHypothesis: Na esika ya liboso , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 11:53:02,096 Example #1\n",
      "2020-02-17 11:53:02,096 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 11:53:02,096 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 11:53:02,096 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 11:53:02,096 Example #2\n",
      "2020-02-17 11:53:02,096 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 11:53:02,096 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 11:53:02,096 \tHypothesis: Na yango , nazwaki ekateli ya kosala makambo oyo nakoki kosala , mpe nsukansuka nsukansuka nsukansuka nsukansuka , nsukansuka nsukansuka nsukansuka , nsukansuka nsukansuka nakozonga lisusu .\n",
      "2020-02-17 11:53:02,097 Example #3\n",
      "2020-02-17 11:53:02,097 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 11:53:02,097 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 11:53:02,097 \tHypothesis: Azali mpe na mposa ya kosembola moto oyo azali na maladi , ata soki azali na maladi .\n",
      "2020-02-17 11:53:02,097 Example #5\n",
      "2020-02-17 11:53:02,097 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 11:53:02,097 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 11:53:02,097 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 11:53:02,097 Example #10\n",
      "2020-02-17 11:53:02,098 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 11:53:02,098 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 11:53:02,098 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 11:53:02,098 Validation result at epoch   6, step    40000: bleu:  20.73, loss: 46016.9375, ppl:   5.8380, duration: 91.7089s\n",
      "2020-02-17 11:53:31,561 Epoch   6 Step:    40100 Batch Loss:     1.882800 Tokens per Sec:     7025, Lr: 0.000300\n",
      "2020-02-17 11:54:00,282 Epoch   6 Step:    40200 Batch Loss:     1.900829 Tokens per Sec:     6758, Lr: 0.000300\n",
      "2020-02-17 11:54:29,712 Epoch   6 Step:    40300 Batch Loss:     1.713065 Tokens per Sec:     6949, Lr: 0.000300\n",
      "2020-02-17 11:54:59,147 Epoch   6 Step:    40400 Batch Loss:     1.795752 Tokens per Sec:     6904, Lr: 0.000300\n",
      "2020-02-17 11:55:28,329 Epoch   6 Step:    40500 Batch Loss:     1.868797 Tokens per Sec:     7022, Lr: 0.000300\n",
      "2020-02-17 11:55:57,711 Epoch   6 Step:    40600 Batch Loss:     1.884012 Tokens per Sec:     6967, Lr: 0.000300\n",
      "2020-02-17 11:56:26,868 Epoch   6 Step:    40700 Batch Loss:     1.844944 Tokens per Sec:     6835, Lr: 0.000300\n",
      "2020-02-17 11:56:55,999 Epoch   6 Step:    40800 Batch Loss:     1.945317 Tokens per Sec:     6837, Lr: 0.000300\n",
      "2020-02-17 11:57:00,385 Epoch   6: total training loss 13053.17\n",
      "2020-02-17 11:57:00,385 EPOCH 7\n",
      "2020-02-17 11:57:25,772 Epoch   7 Step:    40900 Batch Loss:     1.898839 Tokens per Sec:     6401, Lr: 0.000300\n",
      "2020-02-17 11:57:54,870 Epoch   7 Step:    41000 Batch Loss:     1.949426 Tokens per Sec:     6959, Lr: 0.000300\n",
      "2020-02-17 11:59:26,387 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 11:59:26,388 Saving new checkpoint.\n",
      "2020-02-17 11:59:26,616 Example #0\n",
      "2020-02-17 11:59:26,617 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 11:59:26,617 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 11:59:26,617 \tHypothesis: Na esika moko , Davidi amonisaki ete azalaki moto ya kondima .\n",
      "2020-02-17 11:59:26,617 Example #1\n",
      "2020-02-17 11:59:26,617 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 11:59:26,617 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 11:59:26,618 \tHypothesis: Eliya alobaki ete Yehova aleki Baala .\n",
      "2020-02-17 11:59:26,618 Example #2\n",
      "2020-02-17 11:59:26,618 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 11:59:26,618 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 11:59:26,618 \tHypothesis: Yango wana , nazwaki ekateli ya kosala makambo oyo nasengeli kosala , mpe nsukansuka natikaki yango .\n",
      "2020-02-17 11:59:26,618 Example #3\n",
      "2020-02-17 11:59:26,618 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 11:59:26,618 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 11:59:26,618 \tHypothesis: Abakisi mpe ete moto oyo azali na maladi azali na maladi , ata soki azali na maladi .\n",
      "2020-02-17 11:59:26,618 Example #5\n",
      "2020-02-17 11:59:26,619 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 11:59:26,619 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 11:59:26,619 \tHypothesis: Mbala mosusu oyebaka baninga na ye .\n",
      "2020-02-17 11:59:26,619 Example #10\n",
      "2020-02-17 11:59:26,619 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 11:59:26,619 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 11:59:26,619 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 11:59:26,619 Validation result at epoch   7, step    41000: bleu:  20.76, loss: 45913.7578, ppl:   5.8149, duration: 91.7481s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 11:59:55,972 Epoch   7 Step:    41100 Batch Loss:     1.917999 Tokens per Sec:     7001, Lr: 0.000300\n",
      "2020-02-17 12:00:25,139 Epoch   7 Step:    41200 Batch Loss:     2.326165 Tokens per Sec:     6916, Lr: 0.000300\n",
      "2020-02-17 12:00:54,428 Epoch   7 Step:    41300 Batch Loss:     1.879264 Tokens per Sec:     6884, Lr: 0.000300\n",
      "2020-02-17 12:01:23,520 Epoch   7 Step:    41400 Batch Loss:     1.917291 Tokens per Sec:     7020, Lr: 0.000300\n",
      "2020-02-17 12:01:52,254 Epoch   7 Step:    41500 Batch Loss:     1.965479 Tokens per Sec:     6698, Lr: 0.000300\n",
      "2020-02-17 12:02:21,200 Epoch   7 Step:    41600 Batch Loss:     1.924100 Tokens per Sec:     6935, Lr: 0.000300\n",
      "2020-02-17 12:02:50,574 Epoch   7 Step:    41700 Batch Loss:     2.188943 Tokens per Sec:     7034, Lr: 0.000300\n",
      "2020-02-17 12:03:19,685 Epoch   7 Step:    41800 Batch Loss:     2.023562 Tokens per Sec:     6779, Lr: 0.000300\n",
      "2020-02-17 12:03:49,301 Epoch   7 Step:    41900 Batch Loss:     2.212396 Tokens per Sec:     6914, Lr: 0.000300\n",
      "2020-02-17 12:04:18,503 Epoch   7 Step:    42000 Batch Loss:     1.831237 Tokens per Sec:     6820, Lr: 0.000300\n",
      "2020-02-17 12:05:49,971 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 12:05:49,971 Saving new checkpoint.\n",
      "2020-02-17 12:05:50,200 Example #0\n",
      "2020-02-17 12:05:50,200 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 12:05:50,200 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 12:05:50,200 \tHypothesis: Na esika moko , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 12:05:50,200 Example #1\n",
      "2020-02-17 12:05:50,200 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 12:05:50,200 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 12:05:50,201 \tHypothesis: Eliya amonisaki ete Yehova azali na Baala .\n",
      "2020-02-17 12:05:50,201 Example #2\n",
      "2020-02-17 12:05:50,201 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 12:05:50,201 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 12:05:50,201 \tHypothesis: Nazwaki ekateli ya kosala yango , mpe nsukansuka nsukansuka nsukansuka natikaki mosala na ngai .\n",
      "2020-02-17 12:05:50,201 Example #3\n",
      "2020-02-17 12:05:50,202 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 12:05:50,202 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 12:05:50,202 \tHypothesis: Bato ya siansi bazali mpe na mposa ya kosopa zemi , atako ezali na ntina mingi .\n",
      "2020-02-17 12:05:50,202 Example #5\n",
      "2020-02-17 12:05:50,202 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 12:05:50,202 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 12:05:50,202 \tHypothesis: Mbala mosusu okoki koyeba baninga na yo .\n",
      "2020-02-17 12:05:50,202 Example #10\n",
      "2020-02-17 12:05:50,202 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 12:05:50,202 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 12:05:50,202 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 12:05:50,203 Validation result at epoch   7, step    42000: bleu:  20.98, loss: 45596.5234, ppl:   5.7446, duration: 91.6990s\n",
      "2020-02-17 12:06:19,541 Epoch   7 Step:    42100 Batch Loss:     1.702299 Tokens per Sec:     6995, Lr: 0.000300\n",
      "2020-02-17 12:06:48,772 Epoch   7 Step:    42200 Batch Loss:     1.830504 Tokens per Sec:     7059, Lr: 0.000300\n",
      "2020-02-17 12:07:18,191 Epoch   7 Step:    42300 Batch Loss:     1.854513 Tokens per Sec:     6973, Lr: 0.000300\n",
      "2020-02-17 12:07:47,412 Epoch   7 Step:    42400 Batch Loss:     1.679214 Tokens per Sec:     6970, Lr: 0.000300\n",
      "2020-02-17 12:08:16,611 Epoch   7 Step:    42500 Batch Loss:     1.854021 Tokens per Sec:     6921, Lr: 0.000300\n",
      "2020-02-17 12:08:45,687 Epoch   7 Step:    42600 Batch Loss:     2.043710 Tokens per Sec:     6972, Lr: 0.000300\n",
      "2020-02-17 12:09:14,578 Epoch   7 Step:    42700 Batch Loss:     1.879701 Tokens per Sec:     6794, Lr: 0.000300\n",
      "2020-02-17 12:09:43,628 Epoch   7 Step:    42800 Batch Loss:     1.823946 Tokens per Sec:     6932, Lr: 0.000300\n",
      "2020-02-17 12:10:12,731 Epoch   7 Step:    42900 Batch Loss:     1.928365 Tokens per Sec:     6832, Lr: 0.000300\n",
      "2020-02-17 12:10:42,081 Epoch   7 Step:    43000 Batch Loss:     2.284111 Tokens per Sec:     7139, Lr: 0.000300\n",
      "2020-02-17 12:12:13,467 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 12:12:13,468 Saving new checkpoint.\n",
      "2020-02-17 12:12:13,691 Example #0\n",
      "2020-02-17 12:12:13,691 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 12:12:13,691 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 12:12:13,691 \tHypothesis: Na esika moko , Davidi amonisaki kondima .\n",
      "2020-02-17 12:12:13,691 Example #1\n",
      "2020-02-17 12:12:13,691 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 12:12:13,692 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 12:12:13,692 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 12:12:13,692 Example #2\n",
      "2020-02-17 12:12:13,692 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 12:12:13,692 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 12:12:13,692 \tHypothesis: Na yango , nazwaki ekateli ya kobalana mpe ya makasi koleka , ya kosilisa mikolo na ngai .\n",
      "2020-02-17 12:12:13,692 Example #3\n",
      "2020-02-17 12:12:13,692 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 12:12:13,692 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 12:12:13,692 \tHypothesis: Bato ya siansi bazali mpe na mposa ya kosembola , ata soki bazali koyoka ye .\n",
      "2020-02-17 12:12:13,692 Example #5\n",
      "2020-02-17 12:12:13,693 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 12:12:13,693 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 12:12:13,693 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 12:12:13,693 Example #10\n",
      "2020-02-17 12:12:13,693 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 12:12:13,693 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 12:12:13,693 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 12:12:13,693 Validation result at epoch   7, step    43000: bleu:  21.20, loss: 45430.0430, ppl:   5.7081, duration: 91.6120s\n",
      "2020-02-17 12:12:42,659 Epoch   7 Step:    43100 Batch Loss:     1.777134 Tokens per Sec:     6859, Lr: 0.000300\n",
      "2020-02-17 12:13:11,883 Epoch   7 Step:    43200 Batch Loss:     1.779885 Tokens per Sec:     6928, Lr: 0.000300\n",
      "2020-02-17 12:13:40,537 Epoch   7 Step:    43300 Batch Loss:     1.870552 Tokens per Sec:     6893, Lr: 0.000300\n",
      "2020-02-17 12:14:09,795 Epoch   7 Step:    43400 Batch Loss:     1.692763 Tokens per Sec:     7047, Lr: 0.000300\n",
      "2020-02-17 12:14:38,645 Epoch   7 Step:    43500 Batch Loss:     1.837333 Tokens per Sec:     6785, Lr: 0.000300\n",
      "2020-02-17 12:15:07,831 Epoch   7 Step:    43600 Batch Loss:     1.835503 Tokens per Sec:     6962, Lr: 0.000300\n",
      "2020-02-17 12:15:36,688 Epoch   7 Step:    43700 Batch Loss:     1.912813 Tokens per Sec:     6927, Lr: 0.000300\n",
      "2020-02-17 12:16:05,441 Epoch   7 Step:    43800 Batch Loss:     1.675855 Tokens per Sec:     6741, Lr: 0.000300\n",
      "2020-02-17 12:16:34,941 Epoch   7 Step:    43900 Batch Loss:     1.979555 Tokens per Sec:     7116, Lr: 0.000300\n",
      "2020-02-17 12:17:03,856 Epoch   7 Step:    44000 Batch Loss:     1.890293 Tokens per Sec:     6850, Lr: 0.000300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 12:18:35,249 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 12:18:35,249 Saving new checkpoint.\n",
      "2020-02-17 12:18:35,477 Example #0\n",
      "2020-02-17 12:18:35,477 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 12:18:35,477 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 12:18:35,478 \tHypothesis: Davidi amonisaki ete azalaki moto ya kondima .\n",
      "2020-02-17 12:18:35,478 Example #1\n",
      "2020-02-17 12:18:35,478 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 12:18:35,478 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 12:18:35,478 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 12:18:35,478 Example #2\n",
      "2020-02-17 12:18:35,478 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 12:18:35,478 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 12:18:35,478 \tHypothesis: Yango wana , nazwaki ekateli ya kobundisa ngai mpe ya makasi , ya kosilisa mikolo na ngai .\n",
      "2020-02-17 12:18:35,479 Example #3\n",
      "2020-02-17 12:18:35,479 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 12:18:35,479 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 12:18:35,479 \tHypothesis: Bato ya siansi bazali mpe na mposa ya kosembola , atako ezali na likama .\n",
      "2020-02-17 12:18:35,479 Example #5\n",
      "2020-02-17 12:18:35,479 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 12:18:35,479 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 12:18:35,479 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 12:18:35,479 Example #10\n",
      "2020-02-17 12:18:35,480 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 12:18:35,480 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 12:18:35,480 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 12:18:35,480 Validation result at epoch   7, step    44000: bleu:  21.41, loss: 45194.3398, ppl:   5.6567, duration: 91.6236s\n",
      "2020-02-17 12:19:04,581 Epoch   7 Step:    44100 Batch Loss:     1.958442 Tokens per Sec:     7020, Lr: 0.000300\n",
      "2020-02-17 12:19:33,973 Epoch   7 Step:    44200 Batch Loss:     1.926605 Tokens per Sec:     6949, Lr: 0.000300\n",
      "2020-02-17 12:20:03,114 Epoch   7 Step:    44300 Batch Loss:     1.880815 Tokens per Sec:     6976, Lr: 0.000300\n",
      "2020-02-17 12:20:32,091 Epoch   7 Step:    44400 Batch Loss:     1.890366 Tokens per Sec:     6870, Lr: 0.000300\n",
      "2020-02-17 12:21:01,485 Epoch   7 Step:    44500 Batch Loss:     1.992132 Tokens per Sec:     7172, Lr: 0.000300\n",
      "2020-02-17 12:21:30,651 Epoch   7 Step:    44600 Batch Loss:     1.870546 Tokens per Sec:     6894, Lr: 0.000300\n",
      "2020-02-17 12:21:59,783 Epoch   7 Step:    44700 Batch Loss:     1.814525 Tokens per Sec:     7050, Lr: 0.000300\n",
      "2020-02-17 12:22:28,976 Epoch   7 Step:    44800 Batch Loss:     1.797222 Tokens per Sec:     6923, Lr: 0.000300\n",
      "2020-02-17 12:22:57,841 Epoch   7 Step:    44900 Batch Loss:     2.092014 Tokens per Sec:     6844, Lr: 0.000300\n",
      "2020-02-17 12:23:26,602 Epoch   7 Step:    45000 Batch Loss:     1.757821 Tokens per Sec:     6892, Lr: 0.000300\n",
      "2020-02-17 12:24:58,007 Example #0\n",
      "2020-02-17 12:24:58,007 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 12:24:58,008 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 12:24:58,008 \tHypothesis: Na boyokani na Davidi , azalaki moto ya kondima .\n",
      "2020-02-17 12:24:58,008 Example #1\n",
      "2020-02-17 12:24:58,008 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 12:24:58,008 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 12:24:58,008 \tHypothesis: Eliya amonisaki ete Yehova azali lisusu na Baala te .\n",
      "2020-02-17 12:24:58,008 Example #2\n",
      "2020-02-17 12:24:58,008 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 12:24:58,008 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 12:24:58,008 \tHypothesis: Yango wana , nazwaki ekateli ya kobaluka mpe ya makasi , kotika mikolo na ngai .\n",
      "2020-02-17 12:24:58,008 Example #3\n",
      "2020-02-17 12:24:58,009 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 12:24:58,009 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 12:24:58,009 \tHypothesis: Soki moto azali na maladi , akomona mpe ete azali na maladi .\n",
      "2020-02-17 12:24:58,009 Example #5\n",
      "2020-02-17 12:24:58,009 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 12:24:58,009 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 12:24:58,009 \tHypothesis: Mbala mosusu oyebi ete baninga na ye bazali .\n",
      "2020-02-17 12:24:58,009 Example #10\n",
      "2020-02-17 12:24:58,009 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 12:24:58,009 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 12:24:58,010 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 12:24:58,010 Validation result at epoch   7, step    45000: bleu:  20.81, loss: 45369.0781, ppl:   5.6948, duration: 91.4069s\n",
      "2020-02-17 12:25:26,917 Epoch   7 Step:    45100 Batch Loss:     1.700929 Tokens per Sec:     6887, Lr: 0.000300\n",
      "2020-02-17 12:25:56,389 Epoch   7 Step:    45200 Batch Loss:     1.727460 Tokens per Sec:     7143, Lr: 0.000300\n",
      "2020-02-17 12:26:25,476 Epoch   7 Step:    45300 Batch Loss:     1.944350 Tokens per Sec:     6769, Lr: 0.000300\n",
      "2020-02-17 12:28:50,897 Epoch   7 Step:    45800 Batch Loss:     1.751327 Tokens per Sec:     6773, Lr: 0.000300\n",
      "2020-02-17 12:29:20,040 Epoch   7 Step:    45900 Batch Loss:     1.958942 Tokens per Sec:     6876, Lr: 0.000300\n",
      "2020-02-17 12:29:48,690 Epoch   7 Step:    46000 Batch Loss:     1.760660 Tokens per Sec:     6810, Lr: 0.000300\n",
      "2020-02-17 12:31:19,908 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 12:31:19,908 Saving new checkpoint.\n",
      "2020-02-17 12:31:20,133 Example #0\n",
      "2020-02-17 12:31:20,134 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 12:31:20,134 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 12:31:20,134 \tHypothesis: Na esika ya liboso , Davidi amonisaki moto moko ya kondima .\n",
      "2020-02-17 12:31:20,134 Example #1\n",
      "2020-02-17 12:31:20,134 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 12:31:20,134 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 12:31:20,134 \tHypothesis: Eliya amonisaki ete Yehova azali mpenza na Baala .\n",
      "2020-02-17 12:31:20,134 Example #2\n",
      "2020-02-17 12:31:20,134 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 12:31:20,134 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 12:31:20,135 \tHypothesis: Yango wana , nazwaki ekateli ya kobundisa ngai mpe mpo na mwa ntango moke , natikaki mosala na ngai .\n",
      "2020-02-17 12:31:20,135 Example #3\n",
      "2020-02-17 12:31:20,135 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 12:31:20,135 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 12:31:20,135 \tHypothesis: Zulunalo yango ezali mpe na frigo , ata soki ezali na nkanda .\n",
      "2020-02-17 12:31:20,135 Example #5\n",
      "2020-02-17 12:31:20,135 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 12:31:20,135 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 12:31:20,135 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 12:31:20,135 Example #10\n",
      "2020-02-17 12:31:20,136 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 12:31:20,136 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 12:31:20,136 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 12:31:20,136 Validation result at epoch   7, step    46000: bleu:  21.18, loss: 45157.3828, ppl:   5.6487, duration: 91.4447s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 12:31:49,507 Epoch   7 Step:    46100 Batch Loss:     1.997288 Tokens per Sec:     7130, Lr: 0.000300\n",
      "2020-02-17 12:33:46,060 Epoch   7 Step:    46500 Batch Loss:     1.830346 Tokens per Sec:     7065, Lr: 0.000300\n",
      "2020-02-17 12:34:15,195 Epoch   7 Step:    46600 Batch Loss:     1.865857 Tokens per Sec:     6904, Lr: 0.000300\n",
      "2020-02-17 12:34:44,105 Epoch   7 Step:    46700 Batch Loss:     1.498955 Tokens per Sec:     6760, Lr: 0.000300\n",
      "2020-02-17 12:35:13,227 Epoch   7 Step:    46800 Batch Loss:     1.782885 Tokens per Sec:     6846, Lr: 0.000300\n",
      "2020-02-17 12:35:42,488 Epoch   7 Step:    46900 Batch Loss:     1.794786 Tokens per Sec:     7064, Lr: 0.000300\n",
      "2020-02-17 12:36:11,511 Epoch   7 Step:    47000 Batch Loss:     1.834141 Tokens per Sec:     6838, Lr: 0.000300\n",
      "2020-02-17 12:37:42,824 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 12:37:42,824 Saving new checkpoint.\n",
      "2020-02-17 12:37:43,053 Example #0\n",
      "2020-02-17 12:37:43,053 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 12:37:43,053 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 12:37:43,053 \tHypothesis: Na esika moko , Davidi amonisaki ete azalaki moto ya kondima .\n",
      "2020-02-17 12:37:43,053 Example #1\n",
      "2020-02-17 12:37:43,054 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 12:37:43,054 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 12:37:43,054 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 12:37:43,054 Example #2\n",
      "2020-02-17 12:37:43,054 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 12:37:43,054 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 12:37:43,054 \tHypothesis: Na yango , nazwaki ekateli ya kosala yango mpe mpo na libela , natikaki te ete mikolo na ngai ezala lisusu makasi .\n",
      "2020-02-17 12:37:43,054 Example #3\n",
      "2020-02-17 12:37:43,054 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 12:37:43,054 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 12:37:43,055 \tHypothesis: Ankɛtɛ yango ebatelaka mpe avoka na ye , ata soki azali na mawa .\n",
      "2020-02-17 12:37:43,055 Example #5\n",
      "2020-02-17 12:37:43,055 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 12:37:43,055 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 12:37:43,055 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 12:37:43,055 Example #10\n",
      "2020-02-17 12:37:43,055 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 12:37:43,055 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 12:37:43,055 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 12:37:43,055 Validation result at epoch   7, step    47000: bleu:  21.41, loss: 44869.4766, ppl:   5.5867, duration: 91.5435s\n",
      "2020-02-17 12:38:12,282 Epoch   7 Step:    47100 Batch Loss:     1.776924 Tokens per Sec:     6936, Lr: 0.000300\n",
      "2020-02-17 12:38:41,607 Epoch   7 Step:    47200 Batch Loss:     1.814198 Tokens per Sec:     6926, Lr: 0.000300\n",
      "2020-02-17 12:39:10,478 Epoch   7 Step:    47300 Batch Loss:     1.849054 Tokens per Sec:     6884, Lr: 0.000300\n",
      "2020-02-17 12:39:39,771 Epoch   7 Step:    47400 Batch Loss:     2.014489 Tokens per Sec:     7031, Lr: 0.000300\n",
      "2020-02-17 12:40:08,854 Epoch   7 Step:    47500 Batch Loss:     1.956474 Tokens per Sec:     6709, Lr: 0.000300\n",
      "2020-02-17 12:40:38,413 Epoch   7 Step:    47600 Batch Loss:     2.125072 Tokens per Sec:     7115, Lr: 0.000300\n",
      "2020-02-17 12:40:44,917 Epoch   7: total training loss 12702.68\n",
      "2020-02-17 12:40:44,917 EPOCH 8\n",
      "2020-02-17 12:41:08,168 Epoch   8 Step:    47700 Batch Loss:     1.612183 Tokens per Sec:     6653, Lr: 0.000300\n",
      "2020-02-17 12:41:37,302 Epoch   8 Step:    47800 Batch Loss:     1.817555 Tokens per Sec:     6882, Lr: 0.000300\n",
      "2020-02-17 12:42:06,509 Epoch   8 Step:    47900 Batch Loss:     1.738038 Tokens per Sec:     7013, Lr: 0.000300\n",
      "2020-02-17 12:42:35,896 Epoch   8 Step:    48000 Batch Loss:     1.946712 Tokens per Sec:     7068, Lr: 0.000300\n",
      "2020-02-17 12:44:07,235 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 12:44:07,235 Saving new checkpoint.\n",
      "2020-02-17 12:44:07,462 Example #0\n",
      "2020-02-17 12:44:07,462 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 12:44:07,462 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 12:44:07,462 \tHypothesis: Davidi azalaki na kondima .\n",
      "2020-02-17 12:44:07,462 Example #1\n",
      "2020-02-17 12:44:07,462 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 12:44:07,462 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 12:44:07,463 \tHypothesis: Eliya amonisaki ete Yehova azali lisusu na Baala te .\n",
      "2020-02-17 12:44:07,463 Example #2\n",
      "2020-02-17 12:44:07,463 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 12:44:07,463 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 12:44:07,463 \tHypothesis: Na yango , nazwaki ekateli ya kosala makambo oyo namekaka mpe nsukansuka , nsukansuka nsukansuka nsukansuka natikaki mosala na ngai .\n",
      "2020-02-17 12:44:07,463 Example #3\n",
      "2020-02-17 12:44:07,463 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 12:44:07,463 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 12:44:07,463 \tHypothesis: Azali mpe na mposa ya kosembola bato , ata soki bazali koyoka ye .\n",
      "2020-02-17 12:44:07,463 Example #5\n",
      "2020-02-17 12:44:07,464 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 12:44:07,464 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 12:44:07,464 \tHypothesis: Mbala mosusu oyebi baninga na ye .\n",
      "2020-02-17 12:44:07,464 Example #10\n",
      "2020-02-17 12:44:07,464 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 12:44:07,464 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 12:44:07,464 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 12:44:07,464 Validation result at epoch   8, step    48000: bleu:  21.66, loss: 44749.1602, ppl:   5.5610, duration: 91.5670s\n",
      "2020-02-17 12:44:36,792 Epoch   8 Step:    48100 Batch Loss:     1.828245 Tokens per Sec:     6964, Lr: 0.000300\n",
      "2020-02-17 12:45:06,301 Epoch   8 Step:    48200 Batch Loss:     1.733483 Tokens per Sec:     7073, Lr: 0.000300\n",
      "2020-02-17 12:45:35,608 Epoch   8 Step:    48300 Batch Loss:     1.867752 Tokens per Sec:     7045, Lr: 0.000300\n",
      "2020-02-17 12:46:04,494 Epoch   8 Step:    48400 Batch Loss:     1.835824 Tokens per Sec:     6927, Lr: 0.000300\n",
      "2020-02-17 12:46:33,948 Epoch   8 Step:    48500 Batch Loss:     1.768475 Tokens per Sec:     7102, Lr: 0.000300\n",
      "2020-02-17 12:47:02,993 Epoch   8 Step:    48600 Batch Loss:     1.565998 Tokens per Sec:     6755, Lr: 0.000300\n",
      "2020-02-17 12:47:32,186 Epoch   8 Step:    48700 Batch Loss:     1.721498 Tokens per Sec:     6914, Lr: 0.000300\n",
      "2020-02-17 12:48:01,082 Epoch   8 Step:    48800 Batch Loss:     2.255071 Tokens per Sec:     6907, Lr: 0.000300\n",
      "2020-02-17 12:48:30,365 Epoch   8 Step:    48900 Batch Loss:     2.195674 Tokens per Sec:     6916, Lr: 0.000300\n",
      "2020-02-17 12:48:59,689 Epoch   8 Step:    49000 Batch Loss:     1.795064 Tokens per Sec:     7012, Lr: 0.000300\n",
      "2020-02-17 12:50:31,035 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 12:50:31,035 Saving new checkpoint.\n",
      "2020-02-17 12:50:31,303 Example #0\n",
      "2020-02-17 12:50:31,303 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 12:50:31,303 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 12:50:31,303 \tHypothesis: Na boyokani na Davidi , azalaki moto ya kondima .\n",
      "2020-02-17 12:50:31,303 Example #1\n",
      "2020-02-17 12:50:31,304 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 12:50:31,304 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 12:50:31,304 \tHypothesis: Na mokuse : Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 12:50:31,304 Example #2\n",
      "2020-02-17 12:50:31,304 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 12:50:31,304 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 12:50:31,304 \tHypothesis: Yango wana , nazwaki ekateli ya kosala makambo na ndenge ya malamu mpe ya kosilisa yango na mikolo na ngai .\n",
      "2020-02-17 12:50:31,304 Example #3\n",
      "2020-02-17 12:50:31,304 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 12:50:31,304 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 12:50:31,304 \tHypothesis: Asiri mpe azali na frigo , atako azali koyoka ye .\n",
      "2020-02-17 12:50:31,305 Example #5\n",
      "2020-02-17 12:50:31,305 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 12:50:31,305 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 12:50:31,305 \tHypothesis: Mbala mosusu oyebi baninga na ye .\n",
      "2020-02-17 12:50:31,305 Example #10\n",
      "2020-02-17 12:50:31,305 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 12:50:31,305 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 12:50:31,305 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 12:50:31,305 Validation result at epoch   8, step    49000: bleu:  21.63, loss: 44515.6133, ppl:   5.5114, duration: 91.6160s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 12:51:00,576 Epoch   8 Step:    49100 Batch Loss:     1.916407 Tokens per Sec:     6931, Lr: 0.000300\n",
      "2020-02-17 12:51:29,319 Epoch   8 Step:    49200 Batch Loss:     1.949221 Tokens per Sec:     6817, Lr: 0.000300\n",
      "2020-02-17 12:51:58,608 Epoch   8 Step:    49300 Batch Loss:     1.717204 Tokens per Sec:     6911, Lr: 0.000300\n",
      "2020-02-17 12:52:27,703 Epoch   8 Step:    49400 Batch Loss:     1.553418 Tokens per Sec:     6842, Lr: 0.000300\n",
      "2020-02-17 12:52:56,665 Epoch   8 Step:    49500 Batch Loss:     1.721062 Tokens per Sec:     6918, Lr: 0.000300\n",
      "2020-02-17 12:53:25,852 Epoch   8 Step:    49600 Batch Loss:     1.725162 Tokens per Sec:     6791, Lr: 0.000300\n",
      "2020-02-17 12:53:54,885 Epoch   8 Step:    49700 Batch Loss:     2.003867 Tokens per Sec:     6947, Lr: 0.000300\n",
      "2020-02-17 12:54:24,366 Epoch   8 Step:    49800 Batch Loss:     1.899578 Tokens per Sec:     6986, Lr: 0.000300\n",
      "2020-02-17 12:54:53,609 Epoch   8 Step:    49900 Batch Loss:     2.021240 Tokens per Sec:     6838, Lr: 0.000300\n",
      "2020-02-17 12:55:22,868 Epoch   8 Step:    50000 Batch Loss:     1.775718 Tokens per Sec:     6977, Lr: 0.000300\n",
      "2020-02-17 12:56:54,257 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 12:56:54,257 Saving new checkpoint.\n",
      "2020-02-17 12:56:54,475 Example #0\n",
      "2020-02-17 12:56:54,475 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 12:56:54,475 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 12:56:54,475 \tHypothesis: Na esika moko , Davidi amonisaki ete azalaki na kondima .\n",
      "2020-02-17 12:56:54,475 Example #1\n",
      "2020-02-17 12:56:54,475 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 12:56:54,475 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 12:56:54,476 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 12:56:54,476 Example #2\n",
      "2020-02-17 12:56:54,476 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 12:56:54,476 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 12:56:54,476 \tHypothesis: Na yango , nazwaki ekateli ya kobalana mpe ya kokitisa motema , ya kosilisa mikolo na ngai .\n",
      "2020-02-17 12:56:54,476 Example #3\n",
      "2020-02-17 12:56:54,476 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 12:56:54,476 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 12:56:54,476 \tHypothesis: Asiri mpe azali na bomoi ya malamu , ata soki azali koyoka ye .\n",
      "2020-02-17 12:56:54,476 Example #5\n",
      "2020-02-17 12:56:54,477 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 12:56:54,477 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 12:56:54,477 \tHypothesis: Mbala mosusu oyebi ete ozali na baninga na ye .\n",
      "2020-02-17 12:56:54,477 Example #10\n",
      "2020-02-17 12:56:54,477 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 12:56:54,477 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 12:56:54,477 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 12:56:54,477 Validation result at epoch   8, step    50000: bleu:  21.37, loss: 44514.0664, ppl:   5.5111, duration: 91.6084s\n",
      "2020-02-17 12:57:23,380 Epoch   8 Step:    50100 Batch Loss:     1.911215 Tokens per Sec:     6792, Lr: 0.000300\n",
      "2020-02-17 12:57:52,977 Epoch   8 Step:    50200 Batch Loss:     1.862926 Tokens per Sec:     7056, Lr: 0.000300\n",
      "2020-02-17 12:58:22,104 Epoch   8 Step:    50300 Batch Loss:     1.729077 Tokens per Sec:     6904, Lr: 0.000300\n",
      "2020-02-17 12:58:51,087 Epoch   8 Step:    50400 Batch Loss:     1.916708 Tokens per Sec:     6879, Lr: 0.000300\n",
      "2020-02-17 12:59:20,363 Epoch   8 Step:    50500 Batch Loss:     1.892830 Tokens per Sec:     6922, Lr: 0.000300\n",
      "2020-02-17 12:59:49,624 Epoch   8 Step:    50600 Batch Loss:     1.695688 Tokens per Sec:     6903, Lr: 0.000300\n",
      "2020-02-17 13:00:18,893 Epoch   8 Step:    50700 Batch Loss:     1.822721 Tokens per Sec:     6944, Lr: 0.000300\n",
      "2020-02-17 13:00:48,064 Epoch   8 Step:    50800 Batch Loss:     1.905492 Tokens per Sec:     6940, Lr: 0.000300\n",
      "2020-02-17 13:01:17,378 Epoch   8 Step:    50900 Batch Loss:     1.916833 Tokens per Sec:     6948, Lr: 0.000300\n",
      "2020-02-17 13:01:46,240 Epoch   8 Step:    51000 Batch Loss:     1.560352 Tokens per Sec:     6832, Lr: 0.000300\n",
      "2020-02-17 13:03:17,536 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 13:03:17,536 Saving new checkpoint.\n",
      "2020-02-17 13:03:17,757 Example #0\n",
      "2020-02-17 13:03:17,758 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 13:03:17,758 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 13:03:17,758 \tHypothesis: Na esika moko , Davidi amonisaki ete azalaki na kondima .\n",
      "2020-02-17 13:03:17,758 Example #1\n",
      "2020-02-17 13:03:17,758 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 13:03:17,758 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 13:03:17,758 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 13:03:17,758 Example #2\n",
      "2020-02-17 13:03:17,758 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 13:03:17,758 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 13:03:17,759 \tHypothesis: Yango wana , nazwaki ekateli ya kosala makasi mpe ya kosilisa yango na bomoi na ngai mobimba .\n",
      "2020-02-17 13:03:17,759 Example #3\n",
      "2020-02-17 13:03:17,759 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 13:03:17,759 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 13:03:17,759 \tHypothesis: Bato ya siansi bazali mpe na mposa ya kosembola bato , atako bazali na mawa .\n",
      "2020-02-17 13:03:17,759 Example #5\n",
      "2020-02-17 13:03:17,759 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 13:03:17,759 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 13:03:17,759 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 13:03:17,759 Example #10\n",
      "2020-02-17 13:03:17,760 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 13:03:17,760 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 13:03:17,760 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 13:03:17,760 Validation result at epoch   8, step    51000: bleu:  21.89, loss: 44464.1641, ppl:   5.5006, duration: 91.5191s\n",
      "2020-02-17 13:03:46,980 Epoch   8 Step:    51100 Batch Loss:     1.724134 Tokens per Sec:     6806, Lr: 0.000300\n",
      "2020-02-17 13:04:16,141 Epoch   8 Step:    51200 Batch Loss:     1.822908 Tokens per Sec:     6883, Lr: 0.000300\n",
      "2020-02-17 13:04:45,619 Epoch   8 Step:    51300 Batch Loss:     1.850873 Tokens per Sec:     6994, Lr: 0.000300\n",
      "2020-02-17 13:05:14,309 Epoch   8 Step:    51400 Batch Loss:     1.735899 Tokens per Sec:     6881, Lr: 0.000300\n",
      "2020-02-17 13:05:43,709 Epoch   8 Step:    51500 Batch Loss:     1.901455 Tokens per Sec:     6916, Lr: 0.000300\n",
      "2020-02-17 13:06:13,185 Epoch   8 Step:    51600 Batch Loss:     1.612444 Tokens per Sec:     7006, Lr: 0.000300\n",
      "2020-02-17 13:06:42,192 Epoch   8 Step:    51700 Batch Loss:     1.823906 Tokens per Sec:     6933, Lr: 0.000300\n",
      "2020-02-17 13:07:11,063 Epoch   8 Step:    51800 Batch Loss:     1.946773 Tokens per Sec:     6845, Lr: 0.000300\n",
      "2020-02-17 13:07:40,451 Epoch   8 Step:    51900 Batch Loss:     2.013166 Tokens per Sec:     7005, Lr: 0.000300\n",
      "2020-02-17 13:08:09,815 Epoch   8 Step:    52000 Batch Loss:     1.960944 Tokens per Sec:     7033, Lr: 0.000300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 13:09:41,093 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 13:09:41,094 Saving new checkpoint.\n",
      "2020-02-17 13:09:41,322 Example #0\n",
      "2020-02-17 13:09:41,323 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 13:09:41,323 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 13:09:41,323 \tHypothesis: Na esika ya liboso , Davidi amonisaki kondima .\n",
      "2020-02-17 13:09:41,323 Example #1\n",
      "2020-02-17 13:09:41,323 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 13:09:41,323 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 13:09:41,323 \tHypothesis: Eliya amonisaki ete Yehova azali moto ya Baala .\n",
      "2020-02-17 13:09:41,323 Example #2\n",
      "2020-02-17 13:09:41,323 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 13:09:41,323 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 13:09:41,324 \tHypothesis: Nazwaki ekateli ya kosala makasi mpo na kolonga , mpe mpo na libela , nsukansuka nabosanaka mikolo na ngai .\n",
      "2020-02-17 13:09:41,324 Example #3\n",
      "2020-02-17 13:09:41,324 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 13:09:41,324 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 13:09:41,324 \tHypothesis: Ankɛtɛ yango ezali mpe na frigo , ata soki ezali na ntina .\n",
      "2020-02-17 13:09:41,324 Example #5\n",
      "2020-02-17 13:09:41,324 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 13:09:41,324 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 13:09:41,324 \tHypothesis: Mbala mosusu okoki koyeba baninga na ye .\n",
      "2020-02-17 13:09:41,324 Example #10\n",
      "2020-02-17 13:09:41,325 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 13:09:41,325 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 13:09:41,325 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 13:09:41,325 Validation result at epoch   8, step    52000: bleu:  21.83, loss: 44206.9062, ppl:   5.4466, duration: 91.5093s\n",
      "2020-02-17 13:10:10,318 Epoch   8 Step:    52100 Batch Loss:     1.896396 Tokens per Sec:     6826, Lr: 0.000300\n",
      "2020-02-17 13:10:39,671 Epoch   8 Step:    52200 Batch Loss:     1.959862 Tokens per Sec:     6942, Lr: 0.000300\n",
      "2020-02-17 13:11:08,491 Epoch   8 Step:    52300 Batch Loss:     1.886474 Tokens per Sec:     6931, Lr: 0.000300\n",
      "2020-02-17 13:11:37,707 Epoch   8 Step:    52400 Batch Loss:     1.862457 Tokens per Sec:     6900, Lr: 0.000300\n",
      "2020-02-17 13:12:06,962 Epoch   8 Step:    52500 Batch Loss:     1.879316 Tokens per Sec:     7122, Lr: 0.000300\n",
      "2020-02-17 13:12:35,817 Epoch   8 Step:    52600 Batch Loss:     1.759960 Tokens per Sec:     6810, Lr: 0.000300\n",
      "2020-02-17 13:13:05,219 Epoch   8 Step:    52700 Batch Loss:     1.764666 Tokens per Sec:     6909, Lr: 0.000300\n",
      "2020-02-17 13:13:33,921 Epoch   8 Step:    52800 Batch Loss:     1.701157 Tokens per Sec:     6924, Lr: 0.000300\n",
      "2020-02-17 13:14:02,877 Epoch   8 Step:    52900 Batch Loss:     1.699708 Tokens per Sec:     6922, Lr: 0.000300\n",
      "2020-02-17 13:14:31,674 Epoch   8 Step:    53000 Batch Loss:     1.727471 Tokens per Sec:     6776, Lr: 0.000300\n",
      "2020-02-17 13:16:02,980 Example #0\n",
      "2020-02-17 13:16:02,981 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 13:16:02,981 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 13:16:02,981 \tHypothesis: Na esika ya liboso , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 13:16:02,981 Example #1\n",
      "2020-02-17 13:16:02,981 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 13:16:02,981 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 13:16:02,982 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 13:16:02,982 Example #2\n",
      "2020-02-17 13:16:02,982 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 13:16:02,982 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 13:16:02,982 \tHypothesis: Yango wana , nazwaki ekateli ya kobalana mpe ya kokitisa motema , ya kosilisa mikolo na ngai .\n",
      "2020-02-17 13:16:02,982 Example #3\n",
      "2020-02-17 13:16:02,982 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 13:16:02,982 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 13:16:02,982 \tHypothesis: Asiri mpe azali na makanisi ya mabe , atako azali na mawa .\n",
      "2020-02-17 13:16:02,982 Example #5\n",
      "2020-02-17 13:16:02,983 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 13:16:02,983 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 13:16:02,983 \tHypothesis: Mbala mosusu okoki koyeba baninga na yo .\n",
      "2020-02-17 13:16:02,983 Example #10\n",
      "2020-02-17 13:16:02,983 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 13:16:02,983 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 13:16:02,983 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 13:16:02,983 Validation result at epoch   8, step    53000: bleu:  21.38, loss: 44414.1914, ppl:   5.4900, duration: 91.3089s\n",
      "2020-02-17 13:16:32,117 Epoch   8 Step:    53100 Batch Loss:     2.054765 Tokens per Sec:     7114, Lr: 0.000300\n",
      "2020-02-17 13:17:01,197 Epoch   8 Step:    53200 Batch Loss:     1.743430 Tokens per Sec:     7014, Lr: 0.000300\n",
      "2020-02-17 13:17:29,860 Epoch   8 Step:    53300 Batch Loss:     1.762972 Tokens per Sec:     6904, Lr: 0.000300\n",
      "2020-02-17 13:17:58,652 Epoch   8 Step:    53400 Batch Loss:     1.484822 Tokens per Sec:     6862, Lr: 0.000300\n",
      "2020-02-17 13:18:27,601 Epoch   8 Step:    53500 Batch Loss:     1.816580 Tokens per Sec:     6939, Lr: 0.000300\n",
      "2020-02-17 13:18:56,618 Epoch   8 Step:    53600 Batch Loss:     1.761999 Tokens per Sec:     6998, Lr: 0.000300\n",
      "2020-02-17 13:19:25,683 Epoch   8 Step:    53700 Batch Loss:     1.746089 Tokens per Sec:     6818, Lr: 0.000300\n",
      "2020-02-17 13:19:54,544 Epoch   8 Step:    53800 Batch Loss:     1.961913 Tokens per Sec:     6878, Lr: 0.000300\n",
      "2020-02-17 13:20:23,447 Epoch   8 Step:    53900 Batch Loss:     1.669197 Tokens per Sec:     6849, Lr: 0.000300\n",
      "2020-02-17 13:20:52,380 Epoch   8 Step:    54000 Batch Loss:     1.918469 Tokens per Sec:     6857, Lr: 0.000300\n",
      "2020-02-17 13:22:23,763 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 13:22:23,763 Saving new checkpoint.\n",
      "2020-02-17 13:22:23,992 Example #0\n",
      "2020-02-17 13:22:23,993 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 13:22:23,993 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 13:22:23,993 \tHypothesis: Na esika moko , Davidi amonisaki moto ya kondima .\n",
      "2020-02-17 13:22:23,993 Example #1\n",
      "2020-02-17 13:22:23,993 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 13:22:23,993 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 13:22:23,993 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 13:22:23,993 Example #2\n",
      "2020-02-17 13:22:23,994 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 13:22:23,994 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 13:22:23,994 \tHypothesis: Yango wana , nazwaki ekateli ya kobundisa ngai mpe nsukansuka nsukansuka nsukansuka nsukansuka nsukansuka naboya bomoi na ngai .\n",
      "2020-02-17 13:22:23,994 Example #3\n",
      "2020-02-17 13:22:23,994 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 13:22:23,994 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 13:22:23,994 \tHypothesis: Asiri ezali mpe na ntina mingi mpo na moto oyo azali na maladi ya motó , ata soki azali na mposa ya kosala yango .\n",
      "2020-02-17 13:22:23,994 Example #5\n",
      "2020-02-17 13:22:23,994 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 13:22:23,994 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 13:22:23,995 \tHypothesis: Mbala mosusu ozali kokanga ntina ya bandeko na yo .\n",
      "2020-02-17 13:22:23,995 Example #10\n",
      "2020-02-17 13:22:23,995 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 13:22:23,995 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 13:22:23,995 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 13:22:23,995 Validation result at epoch   8, step    54000: bleu:  21.86, loss: 43957.0820, ppl:   5.3946, duration: 91.6141s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 13:22:53,007 Epoch   8 Step:    54100 Batch Loss:     1.771764 Tokens per Sec:     7000, Lr: 0.000300\n",
      "2020-02-17 13:23:21,914 Epoch   8 Step:    54200 Batch Loss:     1.804333 Tokens per Sec:     6948, Lr: 0.000300\n",
      "2020-02-17 13:23:51,269 Epoch   8 Step:    54300 Batch Loss:     1.421055 Tokens per Sec:     7024, Lr: 0.000300\n",
      "2020-02-17 13:24:20,191 Epoch   8 Step:    54400 Batch Loss:     1.897072 Tokens per Sec:     6843, Lr: 0.000300\n",
      "2020-02-17 13:24:30,240 Epoch   8: total training loss 12457.95\n",
      "2020-02-17 13:24:30,240 EPOCH 9\n",
      "2020-02-17 13:24:49,981 Epoch   9 Step:    54500 Batch Loss:     1.861432 Tokens per Sec:     6604, Lr: 0.000300\n",
      "2020-02-17 13:25:18,906 Epoch   9 Step:    54600 Batch Loss:     1.742061 Tokens per Sec:     6804, Lr: 0.000300\n",
      "2020-02-17 13:25:47,827 Epoch   9 Step:    54700 Batch Loss:     1.849181 Tokens per Sec:     6891, Lr: 0.000300\n",
      "2020-02-17 13:26:17,303 Epoch   9 Step:    54800 Batch Loss:     1.991601 Tokens per Sec:     6957, Lr: 0.000300\n",
      "2020-02-17 13:26:46,172 Epoch   9 Step:    54900 Batch Loss:     1.590799 Tokens per Sec:     6846, Lr: 0.000300\n",
      "2020-02-17 13:27:15,695 Epoch   9 Step:    55000 Batch Loss:     1.777363 Tokens per Sec:     7037, Lr: 0.000300\n",
      "2020-02-17 13:28:47,116 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 13:28:47,117 Saving new checkpoint.\n",
      "2020-02-17 13:28:47,343 Example #0\n",
      "2020-02-17 13:28:47,343 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 13:28:47,343 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 13:28:47,344 \tHypothesis: Na esika moko , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 13:28:47,344 Example #1\n",
      "2020-02-17 13:28:47,344 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 13:28:47,344 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 13:28:47,344 \tHypothesis: Na mokuse : Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 13:28:47,344 Example #2\n",
      "2020-02-17 13:28:47,344 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 13:28:47,344 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 13:28:47,344 \tHypothesis: Nazwaki ekateli ya kosala makasi mpo na kosilisa mokakatano yango , mpe nsukansuka nsukansuka nsukansuka nakokufa .\n",
      "2020-02-17 13:28:47,344 Example #3\n",
      "2020-02-17 13:28:47,345 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 13:28:47,345 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 13:28:47,345 \tHypothesis: Asiri yango ezali mpe na esika ya kofanda na ndako , ata soki azali koyoka mpasi .\n",
      "2020-02-17 13:28:47,345 Example #5\n",
      "2020-02-17 13:28:47,345 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 13:28:47,345 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 13:28:47,345 \tHypothesis: Mbala mosusu okoki koyeba baninga na yo .\n",
      "2020-02-17 13:28:47,345 Example #10\n",
      "2020-02-17 13:28:47,345 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 13:28:47,345 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 13:28:47,346 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 13:28:47,346 Validation result at epoch   9, step    55000: bleu:  21.85, loss: 43946.1875, ppl:   5.3924, duration: 91.6502s\n",
      "2020-02-17 13:29:15,956 Epoch   9 Step:    55100 Batch Loss:     1.722239 Tokens per Sec:     6803, Lr: 0.000300\n",
      "2020-02-17 13:29:45,500 Epoch   9 Step:    55200 Batch Loss:     1.627524 Tokens per Sec:     7106, Lr: 0.000300\n",
      "2020-02-17 13:30:14,755 Epoch   9 Step:    55300 Batch Loss:     1.791506 Tokens per Sec:     7021, Lr: 0.000300\n",
      "2020-02-17 13:30:43,913 Epoch   9 Step:    55400 Batch Loss:     1.704188 Tokens per Sec:     6892, Lr: 0.000300\n",
      "2020-02-17 13:31:13,277 Epoch   9 Step:    55500 Batch Loss:     1.714112 Tokens per Sec:     7062, Lr: 0.000300\n",
      "2020-02-17 13:31:42,047 Epoch   9 Step:    55600 Batch Loss:     1.918557 Tokens per Sec:     6870, Lr: 0.000300\n",
      "2020-02-17 13:32:11,477 Epoch   9 Step:    55700 Batch Loss:     1.625623 Tokens per Sec:     7057, Lr: 0.000300\n",
      "2020-02-17 13:32:40,898 Epoch   9 Step:    55800 Batch Loss:     1.549102 Tokens per Sec:     6918, Lr: 0.000300\n",
      "2020-02-17 13:33:09,860 Epoch   9 Step:    55900 Batch Loss:     1.892009 Tokens per Sec:     6816, Lr: 0.000300\n",
      "2020-02-17 13:33:39,036 Epoch   9 Step:    56000 Batch Loss:     1.644648 Tokens per Sec:     6858, Lr: 0.000300\n",
      "2020-02-17 13:35:10,444 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 13:35:10,444 Saving new checkpoint.\n",
      "2020-02-17 13:35:10,716 Example #0\n",
      "2020-02-17 13:35:10,716 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 13:35:10,717 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 13:35:10,717 \tHypothesis: Na esika moko , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 13:35:10,717 Example #1\n",
      "2020-02-17 13:35:10,717 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 13:35:10,717 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 13:35:10,717 \tHypothesis: Na mokuse : Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 13:35:10,717 Example #2\n",
      "2020-02-17 13:35:10,717 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 13:35:10,717 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 13:35:10,718 \tHypothesis: Yango wana , nazwaki ekateli ya kosala makasi mpo na kosilisa mikakatano na ngai mpe mpo na mbala moko , nsukansuka naboma yango .\n",
      "2020-02-17 13:35:10,718 Example #3\n",
      "2020-02-17 13:35:10,718 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 13:35:10,718 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 13:35:10,718 \tHypothesis: Bato ya siansi bazali mpe na bomoi ya malamu , ata soki bazali na esengo .\n",
      "2020-02-17 13:35:10,718 Example #5\n",
      "2020-02-17 13:35:10,718 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 13:35:10,718 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 13:35:10,718 \tHypothesis: Mbala mosusu oyebi ete ozali na baninga na ye .\n",
      "2020-02-17 13:35:10,718 Example #10\n",
      "2020-02-17 13:35:10,719 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 13:35:10,719 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 13:35:10,719 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 13:35:10,719 Validation result at epoch   9, step    56000: bleu:  22.03, loss: 43917.2734, ppl:   5.3864, duration: 91.6824s\n",
      "2020-02-17 13:35:39,905 Epoch   9 Step:    56100 Batch Loss:     1.758474 Tokens per Sec:     6904, Lr: 0.000300\n",
      "2020-02-17 13:36:09,054 Epoch   9 Step:    56200 Batch Loss:     1.915006 Tokens per Sec:     6888, Lr: 0.000300\n",
      "2020-02-17 13:36:38,748 Epoch   9 Step:    56300 Batch Loss:     1.671252 Tokens per Sec:     7050, Lr: 0.000300\n",
      "2020-02-17 13:37:07,785 Epoch   9 Step:    56400 Batch Loss:     1.740269 Tokens per Sec:     6953, Lr: 0.000300\n",
      "2020-02-17 13:37:36,843 Epoch   9 Step:    56500 Batch Loss:     1.694737 Tokens per Sec:     6841, Lr: 0.000300\n",
      "2020-02-17 13:38:06,135 Epoch   9 Step:    56600 Batch Loss:     1.872827 Tokens per Sec:     7011, Lr: 0.000300\n",
      "2020-02-17 13:38:35,458 Epoch   9 Step:    56700 Batch Loss:     1.792254 Tokens per Sec:     6973, Lr: 0.000300\n",
      "2020-02-17 13:39:04,745 Epoch   9 Step:    56800 Batch Loss:     1.558856 Tokens per Sec:     6947, Lr: 0.000300\n",
      "2020-02-17 13:39:33,974 Epoch   9 Step:    56900 Batch Loss:     1.490491 Tokens per Sec:     7056, Lr: 0.000300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 13:40:03,037 Epoch   9 Step:    57000 Batch Loss:     1.898524 Tokens per Sec:     6911, Lr: 0.000300\n",
      "2020-02-17 13:41:34,421 Example #0\n",
      "2020-02-17 13:41:34,422 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 13:41:34,422 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 13:41:34,422 \tHypothesis: Davidi azalaki moto ya kondima .\n",
      "2020-02-17 13:41:34,422 Example #1\n",
      "2020-02-17 13:41:34,422 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 13:41:34,422 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 13:41:34,422 \tHypothesis: Na mokuse : Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 13:41:34,422 Example #2\n",
      "2020-02-17 13:41:34,422 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 13:41:34,423 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 13:41:34,423 \tHypothesis: Yango wana , nazwaki ekateli ya kosilisa yango mpe nsukansuka , nsukansuka nsukansuka nsukansuka naboya yango .\n",
      "2020-02-17 13:41:34,423 Example #3\n",
      "2020-02-17 13:41:34,423 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 13:41:34,423 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 13:41:34,423 \tHypothesis: Zulunalo yango ebatelaka mpe moto oyo azali na maladi , ata soki azali na maladi .\n",
      "2020-02-17 13:41:34,423 Example #5\n",
      "2020-02-17 13:41:34,423 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 13:41:34,423 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 13:41:34,423 \tHypothesis: Mbala mosusu okoki koyeba baninga na yo .\n",
      "2020-02-17 13:41:34,423 Example #10\n",
      "2020-02-17 13:41:34,424 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 13:41:34,424 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 13:41:34,424 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 13:41:34,424 Validation result at epoch   9, step    57000: bleu:  22.03, loss: 43951.1602, ppl:   5.3934, duration: 91.3862s\n",
      "2020-02-17 13:42:03,233 Epoch   9 Step:    57100 Batch Loss:     1.770889 Tokens per Sec:     6881, Lr: 0.000300\n",
      "2020-02-17 13:42:32,694 Epoch   9 Step:    57200 Batch Loss:     1.919787 Tokens per Sec:     6966, Lr: 0.000300\n",
      "2020-02-17 13:43:01,792 Epoch   9 Step:    57300 Batch Loss:     1.667092 Tokens per Sec:     6877, Lr: 0.000300\n",
      "2020-02-17 13:43:31,190 Epoch   9 Step:    57400 Batch Loss:     1.681428 Tokens per Sec:     6968, Lr: 0.000300\n",
      "2020-02-17 13:44:00,104 Epoch   9 Step:    57500 Batch Loss:     1.684963 Tokens per Sec:     6888, Lr: 0.000300\n",
      "2020-02-17 13:44:29,403 Epoch   9 Step:    57600 Batch Loss:     1.716002 Tokens per Sec:     7017, Lr: 0.000300\n",
      "2020-02-17 13:44:58,849 Epoch   9 Step:    57700 Batch Loss:     1.891040 Tokens per Sec:     7093, Lr: 0.000300\n",
      "2020-02-17 13:45:28,154 Epoch   9 Step:    57800 Batch Loss:     1.623294 Tokens per Sec:     7008, Lr: 0.000300\n",
      "2020-02-17 13:45:57,453 Epoch   9 Step:    57900 Batch Loss:     1.793091 Tokens per Sec:     6958, Lr: 0.000300\n",
      "2020-02-17 13:46:26,556 Epoch   9 Step:    58000 Batch Loss:     1.755874 Tokens per Sec:     6872, Lr: 0.000300\n",
      "2020-02-17 13:47:57,927 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 13:47:57,927 Saving new checkpoint.\n",
      "2020-02-17 13:47:58,155 Example #0\n",
      "2020-02-17 13:47:58,155 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 13:47:58,155 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 13:47:58,156 \tHypothesis: Na esika ya liboso , Davidi amonisaki ete azalaki moto ya kondima .\n",
      "2020-02-17 13:47:58,156 Example #1\n",
      "2020-02-17 13:47:58,156 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 13:47:58,156 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 13:47:58,156 \tHypothesis: Eliya alobaki boye : “ Eliya amonisi ete Yehova aleki Baala . ”\n",
      "2020-02-17 13:47:58,156 Example #2\n",
      "2020-02-17 13:47:58,156 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 13:47:58,156 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 13:47:58,156 \tHypothesis: Yango wana , nazwaki ekateli ya kobundisa ngai mpe ya kosilisa mikakatano na ngai na mikolo na ngai .\n",
      "2020-02-17 13:47:58,156 Example #3\n",
      "2020-02-17 13:47:58,157 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 13:47:58,157 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 13:47:58,157 \tHypothesis: Asiri mpe azali na makanisi ya malamu , ata soki azali na mawa .\n",
      "2020-02-17 13:47:58,157 Example #5\n",
      "2020-02-17 13:47:58,157 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 13:47:58,157 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 13:47:58,157 \tHypothesis: Mbala mosusu oyebi ete baninga na ye bazali na makoki ya kososola .\n",
      "2020-02-17 13:47:58,157 Example #10\n",
      "2020-02-17 13:47:58,157 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 13:47:58,157 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 13:47:58,158 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 13:47:58,158 Validation result at epoch   9, step    58000: bleu:  22.29, loss: 43622.5781, ppl:   5.3259, duration: 91.6010s\n",
      "2020-02-17 13:48:26,911 Epoch   9 Step:    58100 Batch Loss:     1.774589 Tokens per Sec:     6756, Lr: 0.000300\n",
      "2020-02-17 13:48:56,183 Epoch   9 Step:    58200 Batch Loss:     1.676244 Tokens per Sec:     6924, Lr: 0.000300\n",
      "2020-02-17 13:49:25,493 Epoch   9 Step:    58300 Batch Loss:     1.939364 Tokens per Sec:     6973, Lr: 0.000300\n",
      "2020-02-17 13:49:54,560 Epoch   9 Step:    58400 Batch Loss:     1.686922 Tokens per Sec:     7029, Lr: 0.000300\n",
      "2020-02-17 13:50:23,518 Epoch   9 Step:    58500 Batch Loss:     1.798144 Tokens per Sec:     6942, Lr: 0.000300\n",
      "2020-02-17 13:50:52,835 Epoch   9 Step:    58600 Batch Loss:     1.708738 Tokens per Sec:     7025, Lr: 0.000300\n",
      "2020-02-17 13:51:22,257 Epoch   9 Step:    58700 Batch Loss:     1.778825 Tokens per Sec:     7010, Lr: 0.000300\n",
      "2020-02-17 13:51:51,166 Epoch   9 Step:    58800 Batch Loss:     1.783229 Tokens per Sec:     6713, Lr: 0.000300\n",
      "2020-02-17 13:52:20,045 Epoch   9 Step:    58900 Batch Loss:     1.737428 Tokens per Sec:     7017, Lr: 0.000300\n",
      "2020-02-17 13:52:49,336 Epoch   9 Step:    59000 Batch Loss:     1.759050 Tokens per Sec:     7003, Lr: 0.000300\n",
      "2020-02-17 13:54:20,691 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 13:54:20,691 Saving new checkpoint.\n",
      "2020-02-17 13:54:20,909 Example #0\n",
      "2020-02-17 13:54:20,910 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 13:54:20,910 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 13:54:20,910 \tHypothesis: Na esika moko , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 13:54:20,910 Example #1\n",
      "2020-02-17 13:54:20,910 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 13:54:20,910 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 13:54:20,910 \tHypothesis: Eliya alobaki ete Yehova aleki Baala .\n",
      "2020-02-17 13:54:20,910 Example #2\n",
      "2020-02-17 13:54:20,910 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 13:54:20,911 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 13:54:20,911 \tHypothesis: Na yango , nazwaki ekateli ya kosala likambo moko oyo nakoki kosala , mpe nsukansuka nakotika yango .\n",
      "2020-02-17 13:54:20,911 Example #3\n",
      "2020-02-17 13:54:20,911 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 13:54:20,911 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 13:54:20,911 \tHypothesis: Asiri ezali mpe na ntina mingi mpo na kosembola bato , ata soki bazali na mposa ya kosopa zemi .\n",
      "2020-02-17 13:54:20,911 Example #5\n",
      "2020-02-17 13:54:20,911 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 13:54:20,911 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 13:54:20,911 \tHypothesis: Mbala mosusu yo mpe okoki koyeba baninga na yo .\n",
      "2020-02-17 13:54:20,911 Example #10\n",
      "2020-02-17 13:54:20,912 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 13:54:20,912 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 13:54:20,912 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 13:54:20,912 Validation result at epoch   9, step    59000: bleu:  22.05, loss: 43329.0273, ppl:   5.2663, duration: 91.5751s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 13:54:49,783 Epoch   9 Step:    59100 Batch Loss:     1.805490 Tokens per Sec:     6993, Lr: 0.000300\n",
      "2020-02-17 13:55:18,639 Epoch   9 Step:    59200 Batch Loss:     1.721259 Tokens per Sec:     6928, Lr: 0.000300\n",
      "2020-02-17 13:55:47,592 Epoch   9 Step:    59300 Batch Loss:     1.861143 Tokens per Sec:     6935, Lr: 0.000300\n",
      "2020-02-17 13:56:16,525 Epoch   9 Step:    59400 Batch Loss:     1.819379 Tokens per Sec:     6770, Lr: 0.000300\n",
      "2020-02-17 13:56:45,970 Epoch   9 Step:    59500 Batch Loss:     1.891234 Tokens per Sec:     7034, Lr: 0.000300\n",
      "2020-02-17 13:57:14,664 Epoch   9 Step:    59600 Batch Loss:     1.829322 Tokens per Sec:     6888, Lr: 0.000300\n",
      "2020-02-17 13:57:43,841 Epoch   9 Step:    59700 Batch Loss:     1.668000 Tokens per Sec:     6811, Lr: 0.000300\n",
      "2020-02-17 13:58:13,596 Epoch   9 Step:    59800 Batch Loss:     1.790246 Tokens per Sec:     7142, Lr: 0.000300\n",
      "2020-02-17 13:58:42,773 Epoch   9 Step:    59900 Batch Loss:     1.934462 Tokens per Sec:     6899, Lr: 0.000300\n",
      "2020-02-17 13:59:11,905 Epoch   9 Step:    60000 Batch Loss:     1.740520 Tokens per Sec:     6966, Lr: 0.000300\n",
      "2020-02-17 14:00:43,354 Example #0\n",
      "2020-02-17 14:00:43,354 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 14:00:43,354 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 14:00:43,354 \tHypothesis: Na esika moko , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 14:00:43,354 Example #1\n",
      "2020-02-17 14:00:43,355 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 14:00:43,355 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:00:43,355 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 14:00:43,355 Example #2\n",
      "2020-02-17 14:00:43,355 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 14:00:43,355 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 14:00:43,355 \tHypothesis: Yango wana , nazwaki ekateli ya kobundisa ngai mpe nsukansuka , nsukansuka natikaki mosala na ngai .\n",
      "2020-02-17 14:00:43,355 Example #3\n",
      "2020-02-17 14:00:43,355 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 14:00:43,355 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 14:00:43,355 \tHypothesis: Asiri ezali mpe na esika ya kobomba biloko , ata soki moto moko ayoki yango .\n",
      "2020-02-17 14:00:43,356 Example #5\n",
      "2020-02-17 14:00:43,356 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 14:00:43,356 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 14:00:43,356 \tHypothesis: Mbala mosusu okoki koyeba baninga na yo ya motema .\n",
      "2020-02-17 14:00:43,356 Example #10\n",
      "2020-02-17 14:00:43,356 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 14:00:43,356 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 14:00:43,356 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 14:00:43,356 Validation result at epoch   9, step    60000: bleu:  22.44, loss: 43353.4727, ppl:   5.2712, duration: 91.4508s\n",
      "2020-02-17 14:01:12,630 Epoch   9 Step:    60100 Batch Loss:     1.841524 Tokens per Sec:     6956, Lr: 0.000300\n",
      "2020-02-17 14:01:41,950 Epoch   9 Step:    60200 Batch Loss:     1.676529 Tokens per Sec:     6977, Lr: 0.000300\n",
      "2020-02-17 14:02:11,120 Epoch   9 Step:    60300 Batch Loss:     1.725933 Tokens per Sec:     6934, Lr: 0.000300\n",
      "2020-02-17 14:02:39,998 Epoch   9 Step:    60400 Batch Loss:     1.791473 Tokens per Sec:     6799, Lr: 0.000300\n",
      "2020-02-17 14:03:09,461 Epoch   9 Step:    60500 Batch Loss:     1.838709 Tokens per Sec:     6950, Lr: 0.000300\n",
      "2020-02-17 14:03:38,234 Epoch   9 Step:    60600 Batch Loss:     1.792867 Tokens per Sec:     6874, Lr: 0.000300\n",
      "2020-02-17 14:04:07,153 Epoch   9 Step:    60700 Batch Loss:     2.058123 Tokens per Sec:     6950, Lr: 0.000300\n",
      "2020-02-17 14:04:36,578 Epoch   9 Step:    60800 Batch Loss:     1.854313 Tokens per Sec:     7093, Lr: 0.000300\n",
      "2020-02-17 14:05:05,978 Epoch   9 Step:    60900 Batch Loss:     1.947526 Tokens per Sec:     6997, Lr: 0.000300\n",
      "2020-02-17 14:05:35,368 Epoch   9 Step:    61000 Batch Loss:     1.772089 Tokens per Sec:     6985, Lr: 0.000300\n",
      "2020-02-17 14:07:06,723 Example #0\n",
      "2020-02-17 14:07:06,723 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 14:07:06,723 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 14:07:06,723 \tHypothesis: Na esika moko , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 14:07:06,723 Example #1\n",
      "2020-02-17 14:07:06,723 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 14:07:06,723 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:07:06,723 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 14:07:06,724 Example #2\n",
      "2020-02-17 14:07:06,724 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 14:07:06,724 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 14:07:06,724 \tHypothesis: Yango wana , nazwaki ekateli ya kosilisa mikakatano mpe ya nsuka ya mikolo na ngai .\n",
      "2020-02-17 14:07:06,724 Example #3\n",
      "2020-02-17 14:07:06,724 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 14:07:06,724 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 14:07:06,724 \tHypothesis: Aprili mpe azali na bomoi ya malamu , ata soki azali koyoka ye .\n",
      "2020-02-17 14:07:06,724 Example #5\n",
      "2020-02-17 14:07:06,724 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 14:07:06,725 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 14:07:06,725 \tHypothesis: Mbala mosusu , okoki koyeba baninga na yo .\n",
      "2020-02-17 14:07:06,725 Example #10\n",
      "2020-02-17 14:07:06,725 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 14:07:06,725 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 14:07:06,725 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 14:07:06,725 Validation result at epoch   9, step    61000: bleu:  22.72, loss: 43338.0117, ppl:   5.2681, duration: 91.3564s\n",
      "2020-02-17 14:07:35,979 Epoch   9 Step:    61100 Batch Loss:     1.958816 Tokens per Sec:     7025, Lr: 0.000300\n",
      "2020-02-17 14:08:05,293 Epoch   9 Step:    61200 Batch Loss:     1.728232 Tokens per Sec:     6996, Lr: 0.000300\n",
      "2020-02-17 14:08:09,818 Epoch   9: total training loss 12172.46\n",
      "2020-02-17 14:08:09,819 EPOCH 10\n",
      "2020-02-17 14:08:35,195 Epoch  10 Step:    61300 Batch Loss:     1.724200 Tokens per Sec:     6670, Lr: 0.000300\n",
      "2020-02-17 14:09:04,341 Epoch  10 Step:    61400 Batch Loss:     1.717892 Tokens per Sec:     6970, Lr: 0.000300\n",
      "2020-02-17 14:09:33,481 Epoch  10 Step:    61500 Batch Loss:     1.813729 Tokens per Sec:     6969, Lr: 0.000300\n",
      "2020-02-17 14:10:02,891 Epoch  10 Step:    61600 Batch Loss:     1.769786 Tokens per Sec:     6978, Lr: 0.000300\n",
      "2020-02-17 14:10:31,669 Epoch  10 Step:    61700 Batch Loss:     1.710937 Tokens per Sec:     6980, Lr: 0.000300\n",
      "2020-02-17 14:11:01,208 Epoch  10 Step:    61800 Batch Loss:     1.617191 Tokens per Sec:     7073, Lr: 0.000300\n",
      "2020-02-17 14:11:30,303 Epoch  10 Step:    61900 Batch Loss:     1.588266 Tokens per Sec:     6821, Lr: 0.000300\n",
      "2020-02-17 14:11:59,764 Epoch  10 Step:    62000 Batch Loss:     1.769851 Tokens per Sec:     7053, Lr: 0.000300\n",
      "2020-02-17 14:13:31,237 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 14:13:31,237 Saving new checkpoint.\n",
      "2020-02-17 14:13:31,506 Example #0\n",
      "2020-02-17 14:13:31,507 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 14:13:31,507 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 14:13:31,507 \tHypothesis: Na esika moko , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 14:13:31,507 Example #1\n",
      "2020-02-17 14:13:31,507 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 14:13:31,507 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:13:31,507 \tHypothesis: Na mokuse : Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 14:13:31,507 Example #2\n",
      "2020-02-17 14:13:31,507 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 14:13:31,507 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 14:13:31,507 \tHypothesis: Yango wana , nazwaki ekateli ya kosilisa yango mpe nsukansuka , nsukansuka nsukansuka nakotika yango .\n",
      "2020-02-17 14:13:31,508 Example #3\n",
      "2020-02-17 14:13:31,508 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 14:13:31,508 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 14:13:31,508 \tHypothesis: Awa mpe , avoka ezali na frigo , ata soki azali na zemi .\n",
      "2020-02-17 14:13:31,508 Example #5\n",
      "2020-02-17 14:13:31,508 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 14:13:31,508 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 14:13:31,508 \tHypothesis: Mbala mosusu oyebi ete ozali na baninga na ye .\n",
      "2020-02-17 14:13:31,508 Example #10\n",
      "2020-02-17 14:13:31,508 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 14:13:31,509 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 14:13:31,509 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 14:13:31,509 Validation result at epoch  10, step    62000: bleu:  22.61, loss: 43176.9766, ppl:   5.2357, duration: 91.7436s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 14:14:01,048 Epoch  10 Step:    62100 Batch Loss:     1.792474 Tokens per Sec:     6981, Lr: 0.000300\n",
      "2020-02-17 14:14:30,142 Epoch  10 Step:    62200 Batch Loss:     1.584724 Tokens per Sec:     6820, Lr: 0.000300\n",
      "2020-02-17 14:14:59,516 Epoch  10 Step:    62300 Batch Loss:     1.680659 Tokens per Sec:     7012, Lr: 0.000300\n",
      "2020-02-17 14:15:28,466 Epoch  10 Step:    62400 Batch Loss:     1.860572 Tokens per Sec:     6916, Lr: 0.000300\n",
      "2020-02-17 14:15:57,632 Epoch  10 Step:    62500 Batch Loss:     1.915441 Tokens per Sec:     6898, Lr: 0.000300\n",
      "2020-02-17 14:16:26,379 Epoch  10 Step:    62600 Batch Loss:     1.680018 Tokens per Sec:     6701, Lr: 0.000300\n",
      "2020-02-17 14:16:55,477 Epoch  10 Step:    62700 Batch Loss:     1.893370 Tokens per Sec:     6833, Lr: 0.000300\n",
      "2020-02-17 14:17:24,807 Epoch  10 Step:    62800 Batch Loss:     1.761608 Tokens per Sec:     7027, Lr: 0.000300\n",
      "2020-02-17 14:17:53,600 Epoch  10 Step:    62900 Batch Loss:     1.848719 Tokens per Sec:     6734, Lr: 0.000300\n",
      "2020-02-17 14:18:22,536 Epoch  10 Step:    63000 Batch Loss:     1.872924 Tokens per Sec:     6872, Lr: 0.000300\n",
      "2020-02-17 14:19:54,001 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 14:19:54,001 Saving new checkpoint.\n",
      "2020-02-17 14:19:54,227 Example #0\n",
      "2020-02-17 14:19:54,227 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 14:19:54,227 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 14:19:54,228 \tHypothesis: Na esika ya liboso , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 14:19:54,228 Example #1\n",
      "2020-02-17 14:19:54,228 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 14:19:54,228 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:19:54,228 \tHypothesis: Na mokuse : Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 14:19:54,228 Example #2\n",
      "2020-02-17 14:19:54,228 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 14:19:54,228 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 14:19:54,228 \tHypothesis: Yango wana , nazwaki ekateli ya kosilisa mikakatano na ngai , mpe mpo na kosilisa yango mikolo na ngai .\n",
      "2020-02-17 14:19:54,228 Example #3\n",
      "2020-02-17 14:19:54,229 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 14:19:54,229 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 14:19:54,229 \tHypothesis: Asiri yango ezali mpe na frigo , ata soki ezali malamu .\n",
      "2020-02-17 14:19:54,229 Example #5\n",
      "2020-02-17 14:19:54,229 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 14:19:54,229 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 14:19:54,229 \tHypothesis: Mbala mosusu okoki koyeba baninga na yo .\n",
      "2020-02-17 14:19:54,229 Example #10\n",
      "2020-02-17 14:19:54,229 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 14:19:54,229 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 14:19:54,230 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 14:19:54,230 Validation result at epoch  10, step    63000: bleu:  22.23, loss: 43042.3516, ppl:   5.2087, duration: 91.6932s\n",
      "2020-02-17 14:20:23,472 Epoch  10 Step:    63100 Batch Loss:     1.857152 Tokens per Sec:     6939, Lr: 0.000300\n",
      "2020-02-17 14:20:52,676 Epoch  10 Step:    63200 Batch Loss:     1.870210 Tokens per Sec:     6871, Lr: 0.000300\n",
      "2020-02-17 14:21:21,430 Epoch  10 Step:    63300 Batch Loss:     1.812149 Tokens per Sec:     6856, Lr: 0.000300\n",
      "2020-02-17 14:21:50,368 Epoch  10 Step:    63400 Batch Loss:     1.754713 Tokens per Sec:     6896, Lr: 0.000300\n",
      "2020-02-17 14:22:19,028 Epoch  10 Step:    63500 Batch Loss:     1.869361 Tokens per Sec:     6792, Lr: 0.000300\n",
      "2020-02-17 14:22:48,564 Epoch  10 Step:    63600 Batch Loss:     1.850524 Tokens per Sec:     7013, Lr: 0.000300\n",
      "2020-02-17 14:23:17,534 Epoch  10 Step:    63700 Batch Loss:     1.804769 Tokens per Sec:     6818, Lr: 0.000300\n",
      "2020-02-17 14:23:46,741 Epoch  10 Step:    63800 Batch Loss:     1.774866 Tokens per Sec:     6931, Lr: 0.000300\n",
      "2020-02-17 14:24:16,271 Epoch  10 Step:    63900 Batch Loss:     1.774245 Tokens per Sec:     6989, Lr: 0.000300\n",
      "2020-02-17 14:24:45,435 Epoch  10 Step:    64000 Batch Loss:     1.760762 Tokens per Sec:     6945, Lr: 0.000300\n",
      "2020-02-17 14:26:16,960 Example #0\n",
      "2020-02-17 14:26:16,961 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 14:26:16,961 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 14:26:16,961 \tHypothesis: Davidi azalaki moto ya kondima .\n",
      "2020-02-17 14:26:16,961 Example #1\n",
      "2020-02-17 14:26:16,961 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 14:26:16,961 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:26:16,961 \tHypothesis: Na mokuse : Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 14:26:16,962 Example #2\n",
      "2020-02-17 14:26:16,962 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 14:26:16,962 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 14:26:16,962 \tHypothesis: Yango wana , nazwaki ekateli ya kobundisa ngai mpe kotika ete nsukansuka naboma ngai .\n",
      "2020-02-17 14:26:16,962 Example #3\n",
      "2020-02-17 14:26:16,962 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 14:26:16,963 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 14:26:16,963 \tHypothesis: Awa , avoka ezali mpe na esika oyo bato bazali na yango , ata soki azali na mposa ya lisalisi .\n",
      "2020-02-17 14:26:16,963 Example #5\n",
      "2020-02-17 14:26:16,963 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 14:26:16,963 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 14:26:16,963 \tHypothesis: Mbala mosusu oyebi bandeko na yo .\n",
      "2020-02-17 14:26:16,963 Example #10\n",
      "2020-02-17 14:26:16,963 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 14:26:16,963 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 14:26:16,963 \tHypothesis: Koyika mpiko na ntango ya komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 14:26:16,964 Validation result at epoch  10, step    64000: bleu:  22.41, loss: 43078.1484, ppl:   5.2159, duration: 91.5282s\n",
      "2020-02-17 14:26:45,899 Epoch  10 Step:    64100 Batch Loss:     1.898014 Tokens per Sec:     6944, Lr: 0.000300\n",
      "2020-02-17 14:27:14,733 Epoch  10 Step:    64200 Batch Loss:     1.808384 Tokens per Sec:     6886, Lr: 0.000300\n",
      "2020-02-17 14:27:44,090 Epoch  10 Step:    64300 Batch Loss:     1.754691 Tokens per Sec:     7031, Lr: 0.000300\n",
      "2020-02-17 14:28:12,889 Epoch  10 Step:    64400 Batch Loss:     1.752199 Tokens per Sec:     6817, Lr: 0.000300\n",
      "2020-02-17 14:28:42,119 Epoch  10 Step:    64500 Batch Loss:     1.704812 Tokens per Sec:     6985, Lr: 0.000300\n",
      "2020-02-17 14:29:11,319 Epoch  10 Step:    64600 Batch Loss:     1.742059 Tokens per Sec:     6943, Lr: 0.000300\n",
      "2020-02-17 14:29:40,402 Epoch  10 Step:    64700 Batch Loss:     1.709361 Tokens per Sec:     6815, Lr: 0.000300\n",
      "2020-02-17 14:30:09,549 Epoch  10 Step:    64800 Batch Loss:     1.794963 Tokens per Sec:     6983, Lr: 0.000300\n",
      "2020-02-17 14:30:38,826 Epoch  10 Step:    64900 Batch Loss:     1.758307 Tokens per Sec:     6865, Lr: 0.000300\n",
      "2020-02-17 14:31:07,656 Epoch  10 Step:    65000 Batch Loss:     1.960452 Tokens per Sec:     6830, Lr: 0.000300\n",
      "2020-02-17 14:32:39,023 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 14:32:39,023 Saving new checkpoint.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 14:32:39,250 Example #0\n",
      "2020-02-17 14:32:39,250 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 14:32:39,250 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 14:32:39,250 \tHypothesis: Davidi azalaki moto ya kondima .\n",
      "2020-02-17 14:32:39,250 Example #1\n",
      "2020-02-17 14:32:39,250 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 14:32:39,250 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:32:39,250 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 14:32:39,250 Example #2\n",
      "2020-02-17 14:32:39,251 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 14:32:39,251 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 14:32:39,251 \tHypothesis: Yango wana , nazwaki ekateli ya kobundisa ngai mpe ya kokitisa motema , ya kosilisa mikolo na ngai .\n",
      "2020-02-17 14:32:39,251 Example #3\n",
      "2020-02-17 14:32:39,251 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 14:32:39,251 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 14:32:39,251 \tHypothesis: Awa mpe , avoka ezali na frigo , ata soki azali na mposa ya lisalisi .\n",
      "2020-02-17 14:32:39,251 Example #5\n",
      "2020-02-17 14:32:39,251 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 14:32:39,252 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 14:32:39,252 \tHypothesis: Mbala mosusu okoki koyeba baninga na yo .\n",
      "2020-02-17 14:32:39,252 Example #10\n",
      "2020-02-17 14:32:39,252 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 14:32:39,252 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 14:32:39,252 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 14:32:39,252 Validation result at epoch  10, step    65000: bleu:  22.63, loss: 42972.9297, ppl:   5.1949, duration: 91.5948s\n",
      "2020-02-17 14:33:08,546 Epoch  10 Step:    65100 Batch Loss:     1.824418 Tokens per Sec:     6977, Lr: 0.000300\n",
      "2020-02-17 14:33:37,642 Epoch  10 Step:    65200 Batch Loss:     1.997360 Tokens per Sec:     6810, Lr: 0.000300\n",
      "2020-02-17 14:34:06,832 Epoch  10 Step:    65300 Batch Loss:     1.576018 Tokens per Sec:     6994, Lr: 0.000300\n",
      "2020-02-17 14:34:36,040 Epoch  10 Step:    65400 Batch Loss:     1.722017 Tokens per Sec:     6875, Lr: 0.000300\n",
      "2020-02-17 14:35:05,018 Epoch  10 Step:    65500 Batch Loss:     1.878094 Tokens per Sec:     6922, Lr: 0.000300\n",
      "2020-02-17 14:35:34,414 Epoch  10 Step:    65600 Batch Loss:     1.869514 Tokens per Sec:     6952, Lr: 0.000300\n",
      "2020-02-17 14:36:03,279 Epoch  10 Step:    65700 Batch Loss:     1.850195 Tokens per Sec:     6847, Lr: 0.000300\n",
      "2020-02-17 14:36:32,325 Epoch  10 Step:    65800 Batch Loss:     1.864160 Tokens per Sec:     6932, Lr: 0.000300\n",
      "2020-02-17 14:37:01,577 Epoch  10 Step:    65900 Batch Loss:     1.921000 Tokens per Sec:     6954, Lr: 0.000300\n",
      "2020-02-17 14:37:30,990 Epoch  10 Step:    66000 Batch Loss:     1.742989 Tokens per Sec:     6901, Lr: 0.000300\n",
      "2020-02-17 14:39:02,428 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 14:39:02,429 Saving new checkpoint.\n",
      "2020-02-17 14:39:02,656 Example #0\n",
      "2020-02-17 14:39:02,657 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 14:39:02,657 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 14:39:02,657 \tHypothesis: Na esika ya liboso , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 14:39:02,657 Example #1\n",
      "2020-02-17 14:39:02,657 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 14:39:02,657 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:39:02,657 \tHypothesis: Eliya alobaki boye : “ Eliya aleki Baala . ”\n",
      "2020-02-17 14:39:02,657 Example #2\n",
      "2020-02-17 14:39:02,658 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 14:39:02,658 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 14:39:02,658 \tHypothesis: Na yango , nazwaki ekateli ya kosala likambo moko ya mabe , mpe mpo na yango , nsukansuka nsukansuka nsukansuka naboma ngai .\n",
      "2020-02-17 14:39:02,658 Example #3\n",
      "2020-02-17 14:39:02,658 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 14:39:02,658 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 14:39:02,658 \tHypothesis: Asiri yango ezali mpe na makambo oyo ezali na kati ya bato oyo bazali na bomoi , ata soki bazali na mawa .\n",
      "2020-02-17 14:39:02,658 Example #5\n",
      "2020-02-17 14:39:02,658 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 14:39:02,659 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 14:39:02,659 \tHypothesis: Mbala mosusu okoki koyeba baninga na yo .\n",
      "2020-02-17 14:39:02,659 Example #10\n",
      "2020-02-17 14:39:02,659 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 14:39:02,659 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 14:39:02,659 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na motuya mingi mpo na Yehova .\n",
      "2020-02-17 14:39:02,659 Validation result at epoch  10, step    66000: bleu:  22.75, loss: 42892.0977, ppl:   5.1788, duration: 91.6678s\n",
      "2020-02-17 14:39:31,473 Epoch  10 Step:    66100 Batch Loss:     1.635085 Tokens per Sec:     6866, Lr: 0.000300\n",
      "2020-02-17 14:40:00,616 Epoch  10 Step:    66200 Batch Loss:     1.747231 Tokens per Sec:     6925, Lr: 0.000300\n",
      "2020-02-17 14:40:30,034 Epoch  10 Step:    66300 Batch Loss:     1.787401 Tokens per Sec:     7074, Lr: 0.000300\n",
      "2020-02-17 14:40:59,208 Epoch  10 Step:    66400 Batch Loss:     1.823970 Tokens per Sec:     6915, Lr: 0.000300\n",
      "2020-02-17 14:41:28,501 Epoch  10 Step:    66500 Batch Loss:     1.956393 Tokens per Sec:     7008, Lr: 0.000300\n",
      "2020-02-17 14:41:57,707 Epoch  10 Step:    66600 Batch Loss:     1.491911 Tokens per Sec:     6993, Lr: 0.000300\n",
      "2020-02-17 14:42:26,817 Epoch  10 Step:    66700 Batch Loss:     1.910508 Tokens per Sec:     6972, Lr: 0.000300\n",
      "2020-02-17 14:42:56,049 Epoch  10 Step:    66800 Batch Loss:     1.635850 Tokens per Sec:     7074, Lr: 0.000300\n",
      "2020-02-17 14:43:25,160 Epoch  10 Step:    66900 Batch Loss:     1.753116 Tokens per Sec:     6899, Lr: 0.000300\n",
      "2020-02-17 14:43:54,069 Epoch  10 Step:    67000 Batch Loss:     1.898013 Tokens per Sec:     6793, Lr: 0.000300\n",
      "2020-02-17 14:45:25,561 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 14:45:25,561 Saving new checkpoint.\n",
      "2020-02-17 14:45:25,784 Example #0\n",
      "2020-02-17 14:45:25,784 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 14:45:25,785 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 14:45:25,785 \tHypothesis: Na esika nyonso , Davidi amonisaki kondima .\n",
      "2020-02-17 14:45:25,785 Example #1\n",
      "2020-02-17 14:45:25,785 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 14:45:25,785 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:45:25,785 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 14:45:25,785 Example #2\n",
      "2020-02-17 14:45:25,785 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 14:45:25,785 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 14:45:25,785 \tHypothesis: Yango wana , nazwaki ekateli ya kosilisa mokakatano yango mpe nsukansuka , nsukansuka natikaki yango .\n",
      "2020-02-17 14:45:25,786 Example #3\n",
      "2020-02-17 14:45:25,786 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 14:45:25,786 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 14:45:25,786 \tHypothesis: Bato ya siansi bazali mpe kobatela yango na ndenge ya mabe , ata soki bazali na mposa ya lisalisi .\n",
      "2020-02-17 14:45:25,786 Example #5\n",
      "2020-02-17 14:45:25,786 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 14:45:25,786 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 14:45:25,786 \tHypothesis: Mbala mosusu okoki koyeba ete ozali na boyokani malamu na ye .\n",
      "2020-02-17 14:45:25,786 Example #10\n",
      "2020-02-17 14:45:25,786 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 14:45:25,787 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 14:45:25,787 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na motuya mingi mpo na Yehova .\n",
      "2020-02-17 14:45:25,787 Validation result at epoch  10, step    67000: bleu:  22.40, loss: 42809.8359, ppl:   5.1625, duration: 91.7169s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 14:45:54,874 Epoch  10 Step:    67100 Batch Loss:     1.593478 Tokens per Sec:     6997, Lr: 0.000300\n",
      "2020-02-17 14:46:24,296 Epoch  10 Step:    67200 Batch Loss:     1.693728 Tokens per Sec:     6942, Lr: 0.000300\n",
      "2020-02-17 14:46:53,757 Epoch  10 Step:    67300 Batch Loss:     1.848038 Tokens per Sec:     6953, Lr: 0.000300\n",
      "2020-02-17 14:47:23,012 Epoch  10 Step:    67400 Batch Loss:     1.517232 Tokens per Sec:     7001, Lr: 0.000300\n",
      "2020-02-17 14:47:52,318 Epoch  10 Step:    67500 Batch Loss:     1.825054 Tokens per Sec:     6990, Lr: 0.000300\n",
      "2020-02-17 14:48:21,588 Epoch  10 Step:    67600 Batch Loss:     1.668686 Tokens per Sec:     6838, Lr: 0.000300\n",
      "2020-02-17 14:48:51,003 Epoch  10 Step:    67700 Batch Loss:     1.864065 Tokens per Sec:     6871, Lr: 0.000300\n",
      "2020-02-17 14:49:20,161 Epoch  10 Step:    67800 Batch Loss:     1.688245 Tokens per Sec:     7008, Lr: 0.000300\n",
      "2020-02-17 14:49:49,326 Epoch  10 Step:    67900 Batch Loss:     1.665091 Tokens per Sec:     6917, Lr: 0.000300\n",
      "2020-02-17 14:50:18,359 Epoch  10 Step:    68000 Batch Loss:     1.913474 Tokens per Sec:     6992, Lr: 0.000300\n",
      "2020-02-17 14:51:49,883 Example #0\n",
      "2020-02-17 14:51:49,883 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 14:51:49,883 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 14:51:49,884 \tHypothesis: Na esika ya liboso , Davidi amonisaki kondima .\n",
      "2020-02-17 14:51:49,884 Example #1\n",
      "2020-02-17 14:51:49,884 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 14:51:49,884 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:51:49,884 \tHypothesis: Na mokuse : Eliya amimonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:51:49,884 Example #2\n",
      "2020-02-17 14:51:49,884 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 14:51:49,884 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 14:51:49,884 \tHypothesis: Yango wana , nazwaki ekateli ya kosilisa mikakatano na ngai , mpe nsukansuka nsukansuka nabomaki mikolo na ngai .\n",
      "2020-02-17 14:51:49,884 Example #3\n",
      "2020-02-17 14:51:49,885 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 14:51:49,885 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 14:51:49,885 \tHypothesis: Awa avoka ezali mpe na ntina mingi mpo na kosembola , ata soki azali na mposa ya lisalisi .\n",
      "2020-02-17 14:51:49,885 Example #5\n",
      "2020-02-17 14:51:49,885 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 14:51:49,885 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 14:51:49,885 \tHypothesis: Mbala mosusu okososola baninga na ye .\n",
      "2020-02-17 14:51:49,885 Example #10\n",
      "2020-02-17 14:51:49,886 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 14:51:49,886 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 14:51:49,886 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na motuya mingi mpo na Yehova .\n",
      "2020-02-17 14:51:49,886 Validation result at epoch  10, step    68000: bleu:  22.52, loss: 42824.8320, ppl:   5.1655, duration: 91.5255s\n",
      "2020-02-17 14:51:56,125 Epoch  10: total training loss 12032.55\n",
      "2020-02-17 14:51:56,126 EPOCH 11\n",
      "2020-02-17 14:52:19,701 Epoch  11 Step:    68100 Batch Loss:     1.888504 Tokens per Sec:     6678, Lr: 0.000300\n",
      "2020-02-17 14:52:48,752 Epoch  11 Step:    68200 Batch Loss:     1.741653 Tokens per Sec:     6810, Lr: 0.000300\n",
      "2020-02-17 14:53:18,139 Epoch  11 Step:    68300 Batch Loss:     1.680669 Tokens per Sec:     6892, Lr: 0.000300\n",
      "2020-02-17 14:53:47,251 Epoch  11 Step:    68400 Batch Loss:     1.593404 Tokens per Sec:     6871, Lr: 0.000300\n",
      "2020-02-17 14:54:15,981 Epoch  11 Step:    68500 Batch Loss:     1.826065 Tokens per Sec:     6670, Lr: 0.000300\n",
      "2020-02-17 14:54:45,332 Epoch  11 Step:    68600 Batch Loss:     1.758092 Tokens per Sec:     6853, Lr: 0.000300\n",
      "2020-02-17 14:55:14,833 Epoch  11 Step:    68700 Batch Loss:     1.687380 Tokens per Sec:     6962, Lr: 0.000300\n",
      "2020-02-17 14:55:43,732 Epoch  11 Step:    68800 Batch Loss:     1.607819 Tokens per Sec:     6792, Lr: 0.000300\n",
      "2020-02-17 14:56:12,988 Epoch  11 Step:    68900 Batch Loss:     1.840090 Tokens per Sec:     6966, Lr: 0.000300\n",
      "2020-02-17 14:56:42,337 Epoch  11 Step:    69000 Batch Loss:     1.577152 Tokens per Sec:     7029, Lr: 0.000300\n",
      "2020-02-17 14:58:13,884 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 14:58:13,884 Saving new checkpoint.\n",
      "2020-02-17 14:58:14,148 Example #0\n",
      "2020-02-17 14:58:14,149 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 14:58:14,149 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 14:58:14,149 \tHypothesis: Na esika moko , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 14:58:14,149 Example #1\n",
      "2020-02-17 14:58:14,149 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 14:58:14,149 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:58:14,149 \tHypothesis: Eyano : Eliya amimonisi ete Yehova aleki Baala .\n",
      "2020-02-17 14:58:14,149 Example #2\n",
      "2020-02-17 14:58:14,150 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 14:58:14,150 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 14:58:14,150 \tHypothesis: Na yango , nazwaki ekateli ya kosilisa matata mpe ya monene , ya kosilisa mikolo na ngai .\n",
      "2020-02-17 14:58:14,150 Example #3\n",
      "2020-02-17 14:58:14,150 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 14:58:14,150 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 14:58:14,150 \tHypothesis: Bato ya siansi bazali mpe na frigo , ata soki bazali koyoka ye .\n",
      "2020-02-17 14:58:14,150 Example #5\n",
      "2020-02-17 14:58:14,150 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 14:58:14,150 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 14:58:14,150 \tHypothesis: Mbala mosusu oyebi baninga na ye .\n",
      "2020-02-17 14:58:14,151 Example #10\n",
      "2020-02-17 14:58:14,151 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 14:58:14,151 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 14:58:14,151 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na motuya mingi mpo na Yehova .\n",
      "2020-02-17 14:58:14,151 Validation result at epoch  11, step    69000: bleu:  22.52, loss: 42665.9297, ppl:   5.1341, duration: 91.8128s\n",
      "2020-02-17 14:58:43,147 Epoch  11 Step:    69100 Batch Loss:     1.873644 Tokens per Sec:     6827, Lr: 0.000300\n",
      "2020-02-17 14:59:12,427 Epoch  11 Step:    69200 Batch Loss:     1.686011 Tokens per Sec:     6964, Lr: 0.000300\n",
      "2020-02-17 14:59:41,233 Epoch  11 Step:    69300 Batch Loss:     1.467893 Tokens per Sec:     6798, Lr: 0.000300\n",
      "2020-02-17 15:00:10,748 Epoch  11 Step:    69400 Batch Loss:     1.728103 Tokens per Sec:     6963, Lr: 0.000300\n",
      "2020-02-17 15:00:39,988 Epoch  11 Step:    69500 Batch Loss:     1.717358 Tokens per Sec:     6864, Lr: 0.000300\n",
      "2020-02-17 15:01:08,843 Epoch  11 Step:    69600 Batch Loss:     1.819776 Tokens per Sec:     6905, Lr: 0.000300\n",
      "2020-02-17 15:01:38,242 Epoch  11 Step:    69700 Batch Loss:     1.583284 Tokens per Sec:     6958, Lr: 0.000300\n",
      "2020-02-17 15:02:07,600 Epoch  11 Step:    69800 Batch Loss:     2.025096 Tokens per Sec:     7086, Lr: 0.000300\n",
      "2020-02-17 15:02:36,785 Epoch  11 Step:    69900 Batch Loss:     1.696556 Tokens per Sec:     6849, Lr: 0.000300\n",
      "2020-02-17 15:03:06,270 Epoch  11 Step:    70000 Batch Loss:     1.783847 Tokens per Sec:     6936, Lr: 0.000300\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 15:04:37,774 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 15:04:37,774 Saving new checkpoint.\n",
      "2020-02-17 15:04:37,998 Example #0\n",
      "2020-02-17 15:04:37,998 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 15:04:37,998 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 15:04:37,998 \tHypothesis: Na esika nyonso , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 15:04:37,998 Example #1\n",
      "2020-02-17 15:04:37,999 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 15:04:37,999 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 15:04:37,999 \tHypothesis: Ebandeli : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 15:04:37,999 Example #2\n",
      "2020-02-17 15:04:37,999 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 15:04:37,999 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 15:04:37,999 \tHypothesis: Yango wana , nazwaki ekateli ya kosilisa mikakatano mpe ya mpasi oyo nasengelaki kosala mpo na kosilisa yango .\n",
      "2020-02-17 15:04:37,999 Example #3\n",
      "2020-02-17 15:04:37,999 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 15:04:38,000 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 15:04:38,000 \tHypothesis: Asilikaka mpe ebatelaka moto oyo azali na maladi , ata soki azali na mposa ya koyeba makambo oyo azali kosala .\n",
      "2020-02-17 15:04:38,000 Example #5\n",
      "2020-02-17 15:04:38,000 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 15:04:38,000 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 15:04:38,000 \tHypothesis: Mbala mosusu oyebi ete baninga na yo ya motema bakoki kososola yo .\n",
      "2020-02-17 15:04:38,000 Example #10\n",
      "2020-02-17 15:04:38,000 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 15:04:38,000 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 15:04:38,000 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 15:04:38,000 Validation result at epoch  11, step    70000: bleu:  22.84, loss: 42583.8398, ppl:   5.1179, duration: 91.7293s\n",
      "2020-02-17 15:05:06,799 Epoch  11 Step:    70100 Batch Loss:     1.670974 Tokens per Sec:     6904, Lr: 0.000300\n",
      "2020-02-17 15:05:35,920 Epoch  11 Step:    70200 Batch Loss:     1.681582 Tokens per Sec:     6909, Lr: 0.000300\n",
      "2020-02-17 15:06:05,082 Epoch  11 Step:    70300 Batch Loss:     1.822532 Tokens per Sec:     6910, Lr: 0.000300\n",
      "2020-02-17 15:06:34,219 Epoch  11 Step:    70400 Batch Loss:     1.790552 Tokens per Sec:     6887, Lr: 0.000300\n",
      "2020-02-17 15:07:03,143 Epoch  11 Step:    70500 Batch Loss:     1.773831 Tokens per Sec:     6803, Lr: 0.000300\n",
      "2020-02-17 15:07:32,007 Epoch  11 Step:    70600 Batch Loss:     1.892465 Tokens per Sec:     6806, Lr: 0.000300\n",
      "2020-02-17 15:08:01,169 Epoch  11 Step:    70700 Batch Loss:     1.568589 Tokens per Sec:     7018, Lr: 0.000300\n",
      "2020-02-17 15:08:30,576 Epoch  11 Step:    70800 Batch Loss:     1.658532 Tokens per Sec:     6879, Lr: 0.000300\n",
      "2020-02-17 15:08:59,877 Epoch  11 Step:    70900 Batch Loss:     1.908298 Tokens per Sec:     7098, Lr: 0.000300\n",
      "2020-02-17 15:09:29,225 Epoch  11 Step:    71000 Batch Loss:     1.787230 Tokens per Sec:     6936, Lr: 0.000300\n",
      "2020-02-17 15:11:00,725 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 15:11:00,725 Saving new checkpoint.\n",
      "2020-02-17 15:11:00,949 Example #0\n",
      "2020-02-17 15:11:00,949 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 15:11:00,950 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 15:11:00,950 \tHypothesis: Na boyokani na ye , Davidi amonisaki kondima .\n",
      "2020-02-17 15:11:00,950 Example #1\n",
      "2020-02-17 15:11:00,950 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 15:11:00,950 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 15:11:00,950 \tHypothesis: Ebandeli : Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 15:11:00,950 Example #2\n",
      "2020-02-17 15:11:00,950 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 15:11:00,950 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 15:11:00,950 \tHypothesis: Yango wana , nazwaki ekateli ya kosilisa mikakatano mpe ya makasi , ya kosilisa mikolo na ngai .\n",
      "2020-02-17 15:11:00,950 Example #3\n",
      "2020-02-17 15:11:00,951 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 15:11:00,951 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 15:11:00,951 \tHypothesis: Asiliki ezali mpe na likama , ata soki moto moko azali na mposa ya kosembola ye .\n",
      "2020-02-17 15:11:00,951 Example #5\n",
      "2020-02-17 15:11:00,951 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 15:11:00,951 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 15:11:00,951 \tHypothesis: Mbala mosusu oyebi baninga na yo .\n",
      "2020-02-17 15:11:00,951 Example #10\n",
      "2020-02-17 15:11:00,951 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 15:11:00,951 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 15:11:00,952 \tHypothesis: Koyika mpiko na komekama ya ndenge wana ezali na motuya mingi mpo na Yehova .\n",
      "2020-02-17 15:11:00,952 Validation result at epoch  11, step    71000: bleu:  23.10, loss: 42339.4062, ppl:   5.0702, duration: 91.7257s\n",
      "2020-02-17 15:11:30,173 Epoch  11 Step:    71100 Batch Loss:     1.711482 Tokens per Sec:     7010, Lr: 0.000300\n",
      "2020-02-17 15:11:59,046 Epoch  11 Step:    71200 Batch Loss:     1.743942 Tokens per Sec:     6840, Lr: 0.000300\n",
      "2020-02-17 15:12:27,698 Epoch  11 Step:    71300 Batch Loss:     1.744322 Tokens per Sec:     6784, Lr: 0.000300\n",
      "2020-02-17 15:12:56,888 Epoch  11 Step:    71400 Batch Loss:     1.813094 Tokens per Sec:     6904, Lr: 0.000300\n",
      "2020-02-17 15:13:26,366 Epoch  11 Step:    71500 Batch Loss:     1.859554 Tokens per Sec:     7092, Lr: 0.000300\n",
      "2020-02-17 15:13:55,724 Epoch  11 Step:    71600 Batch Loss:     1.638755 Tokens per Sec:     6919, Lr: 0.000300\n",
      "2020-02-17 15:14:24,764 Epoch  11 Step:    71700 Batch Loss:     1.664946 Tokens per Sec:     6803, Lr: 0.000300\n",
      "2020-02-17 15:14:54,077 Epoch  11 Step:    71800 Batch Loss:     1.633634 Tokens per Sec:     7058, Lr: 0.000300\n",
      "2020-02-17 15:15:23,295 Epoch  11 Step:    71900 Batch Loss:     1.437943 Tokens per Sec:     6960, Lr: 0.000300\n",
      "2020-02-17 15:15:52,791 Epoch  11 Step:    72000 Batch Loss:     1.765059 Tokens per Sec:     7078, Lr: 0.000300\n",
      "2020-02-17 15:17:24,262 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 15:17:24,263 Saving new checkpoint.\n",
      "2020-02-17 15:17:24,483 Example #0\n",
      "2020-02-17 15:17:24,484 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 15:17:24,484 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 15:17:24,484 \tHypothesis: Na esika ya kosala bongo , Davidi amonisaki ete azalaki na kondima .\n",
      "2020-02-17 15:17:24,484 Example #1\n",
      "2020-02-17 15:17:24,484 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 15:17:24,484 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 15:17:24,484 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 15:17:24,484 Example #2\n",
      "2020-02-17 15:17:24,485 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 15:17:24,485 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 15:17:24,485 \tHypothesis: Na yango , nazwaki ekateli ya kobundisa ngai mpe mpo na bopemi oyo eleki monene , nsukansuka naboma mikolo na ngai .\n",
      "2020-02-17 15:17:24,485 Example #3\n",
      "2020-02-17 15:17:24,485 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 15:17:24,485 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 15:17:24,485 \tHypothesis: Ankɛtɛ yango mpe ebatelaka moto oyo azali na maladi ya motó , ata soki azali koyoka .\n",
      "2020-02-17 15:17:24,485 Example #5\n",
      "2020-02-17 15:17:24,486 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 15:17:24,486 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 15:17:24,486 \tHypothesis: Mbala mosusu oyebi baninga na ye ya motema .\n",
      "2020-02-17 15:17:24,486 Example #10\n",
      "2020-02-17 15:17:24,486 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 15:17:24,486 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 15:17:24,487 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 15:17:24,487 Validation result at epoch  11, step    72000: bleu:  22.49, loss: 42293.7656, ppl:   5.0613, duration: 91.6949s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 15:17:53,938 Epoch  11 Step:    72100 Batch Loss:     1.607217 Tokens per Sec:     6987, Lr: 0.000300\n",
      "2020-02-17 15:18:22,916 Epoch  11 Step:    72200 Batch Loss:     1.866704 Tokens per Sec:     6823, Lr: 0.000300\n",
      "2020-02-17 15:18:52,232 Epoch  11 Step:    72300 Batch Loss:     1.732466 Tokens per Sec:     7023, Lr: 0.000300\n",
      "2020-02-17 15:19:21,337 Epoch  11 Step:    72400 Batch Loss:     1.838544 Tokens per Sec:     6903, Lr: 0.000300\n",
      "2020-02-17 15:19:50,771 Epoch  11 Step:    72500 Batch Loss:     1.624543 Tokens per Sec:     6998, Lr: 0.000300\n",
      "2020-02-17 15:20:19,710 Epoch  11 Step:    72600 Batch Loss:     1.810646 Tokens per Sec:     6802, Lr: 0.000300\n",
      "2020-02-17 15:20:49,246 Epoch  11 Step:    72700 Batch Loss:     1.812209 Tokens per Sec:     7030, Lr: 0.000300\n",
      "2020-02-17 15:21:18,047 Epoch  11 Step:    72800 Batch Loss:     1.849613 Tokens per Sec:     6867, Lr: 0.000300\n",
      "2020-02-17 15:21:47,284 Epoch  11 Step:    72900 Batch Loss:     1.854045 Tokens per Sec:     6866, Lr: 0.000300\n",
      "2020-02-17 15:22:16,149 Epoch  11 Step:    73000 Batch Loss:     1.624420 Tokens per Sec:     6988, Lr: 0.000300\n",
      "2020-02-17 15:23:47,575 Example #0\n",
      "2020-02-17 15:23:47,575 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 15:23:47,575 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 15:23:47,575 \tHypothesis: Na esika ya liboso , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 15:23:47,576 Example #1\n",
      "2020-02-17 15:23:47,576 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 15:23:47,576 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 15:23:47,576 \tHypothesis: Eliya alobaki boye : “ Eliya aleki Baala . ”\n",
      "2020-02-17 15:23:47,576 Example #2\n",
      "2020-02-17 15:23:47,576 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 15:23:47,576 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 15:23:47,576 \tHypothesis: Na yango , nazwaki ekateli ya kosilisa mikakatano mpe ya makasi , ya kosilisa yango mikolo na ngai .\n",
      "2020-02-17 15:23:47,576 Example #3\n",
      "2020-02-17 15:23:47,577 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 15:23:47,577 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 15:23:47,577 \tHypothesis: Awa mpe , avoka ezali mpe na frigo , atako ezali na ntina mingi .\n",
      "2020-02-17 15:23:47,577 Example #5\n",
      "2020-02-17 15:23:47,577 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 15:23:47,577 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 15:23:47,577 \tHypothesis: Mbala mosusu oyebi ete baninga na yo ya motema bakoki kososola makambo oyo ezali na ntina mingi .\n",
      "2020-02-17 15:23:47,577 Example #10\n",
      "2020-02-17 15:23:47,577 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 15:23:47,577 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 15:23:47,577 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na motuya mingi mpo na Yehova .\n",
      "2020-02-17 15:23:47,578 Validation result at epoch  11, step    73000: bleu:  23.01, loss: 42467.1562, ppl:   5.0951, duration: 91.4274s\n",
      "2020-02-17 15:24:16,698 Epoch  11 Step:    73100 Batch Loss:     1.633065 Tokens per Sec:     6833, Lr: 0.000300\n",
      "2020-02-17 15:24:46,431 Epoch  11 Step:    73200 Batch Loss:     1.705921 Tokens per Sec:     7090, Lr: 0.000300\n",
      "2020-02-17 15:25:15,574 Epoch  11 Step:    73300 Batch Loss:     1.545395 Tokens per Sec:     6886, Lr: 0.000300\n",
      "2020-02-17 15:25:44,717 Epoch  11 Step:    73400 Batch Loss:     1.948799 Tokens per Sec:     6966, Lr: 0.000300\n",
      "2020-02-17 15:26:14,357 Epoch  11 Step:    73500 Batch Loss:     1.730844 Tokens per Sec:     7105, Lr: 0.000300\n",
      "2020-02-17 15:26:43,387 Epoch  11 Step:    73600 Batch Loss:     1.796589 Tokens per Sec:     6925, Lr: 0.000300\n",
      "2020-02-17 15:27:12,615 Epoch  11 Step:    73700 Batch Loss:     1.416343 Tokens per Sec:     7011, Lr: 0.000300\n",
      "2020-02-17 15:27:41,854 Epoch  11 Step:    73800 Batch Loss:     2.095004 Tokens per Sec:     6959, Lr: 0.000300\n",
      "2020-02-17 15:28:11,373 Epoch  11 Step:    73900 Batch Loss:     1.825400 Tokens per Sec:     6980, Lr: 0.000300\n",
      "2020-02-17 15:28:40,581 Epoch  11 Step:    74000 Batch Loss:     1.732277 Tokens per Sec:     6922, Lr: 0.000300\n",
      "2020-02-17 15:30:11,915 Example #0\n",
      "2020-02-17 15:30:11,915 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 15:30:11,915 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 15:30:11,915 \tHypothesis: Davidi azalaki moto ya kondima .\n",
      "2020-02-17 15:30:11,915 Example #1\n",
      "2020-02-17 15:30:11,915 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 15:30:11,916 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 15:30:11,916 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 15:30:11,916 Example #2\n",
      "2020-02-17 15:30:11,916 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 15:30:11,916 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 15:30:11,916 \tHypothesis: Yango wana , nazwaki ekateli ya kosilisa mokakatano yango mpe mpo na mwa ntango , natikaki mikolo na ngai .\n",
      "2020-02-17 15:30:11,916 Example #3\n",
      "2020-02-17 15:30:11,916 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 15:30:11,916 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 15:30:11,916 \tHypothesis: Asiri ezali mpe na molobi ya frigo , ata soki azali na mposa ya lisalisi .\n",
      "2020-02-17 15:30:11,916 Example #5\n",
      "2020-02-17 15:30:11,917 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 15:30:11,917 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 15:30:11,917 \tHypothesis: Mbala mosusu okoki koyeba baninga na yo .\n",
      "2020-02-17 15:30:11,917 Example #10\n",
      "2020-02-17 15:30:11,917 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 15:30:11,917 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 15:30:11,917 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na ntina mingi mpo na Yehova .\n",
      "2020-02-17 15:30:11,917 Validation result at epoch  11, step    74000: bleu:  23.20, loss: 42306.4336, ppl:   5.0638, duration: 91.3352s\n",
      "2020-02-17 15:30:40,848 Epoch  11 Step:    74100 Batch Loss:     1.788749 Tokens per Sec:     6889, Lr: 0.000300\n",
      "2020-02-17 15:31:09,943 Epoch  11 Step:    74200 Batch Loss:     1.616085 Tokens per Sec:     6913, Lr: 0.000300\n",
      "2020-02-17 15:31:39,216 Epoch  11 Step:    74300 Batch Loss:     2.023425 Tokens per Sec:     7019, Lr: 0.000300\n",
      "2020-02-17 15:32:08,291 Epoch  11 Step:    74400 Batch Loss:     1.737873 Tokens per Sec:     6788, Lr: 0.000300\n",
      "2020-02-17 15:32:37,695 Epoch  11 Step:    74500 Batch Loss:     1.822094 Tokens per Sec:     6992, Lr: 0.000300\n",
      "2020-02-17 15:33:06,809 Epoch  11 Step:    74600 Batch Loss:     1.559202 Tokens per Sec:     6969, Lr: 0.000300\n",
      "2020-02-17 15:33:36,305 Epoch  11 Step:    74700 Batch Loss:     1.803221 Tokens per Sec:     6961, Lr: 0.000300\n",
      "2020-02-17 15:34:05,277 Epoch  11 Step:    74800 Batch Loss:     1.576294 Tokens per Sec:     6925, Lr: 0.000300\n",
      "2020-02-17 15:34:10,197 Epoch  11: total training loss 11857.03\n",
      "2020-02-17 15:34:10,198 EPOCH 12\n",
      "2020-02-17 15:34:35,062 Epoch  12 Step:    74900 Batch Loss:     1.896919 Tokens per Sec:     6693, Lr: 0.000300\n",
      "2020-02-17 15:35:04,365 Epoch  12 Step:    75000 Batch Loss:     1.743639 Tokens per Sec:     6919, Lr: 0.000300\n",
      "2020-02-17 15:36:35,723 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 15:36:35,724 Saving new checkpoint.\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 15:36:35,951 Example #0\n",
      "2020-02-17 15:36:35,951 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 15:36:35,951 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 15:36:35,951 \tHypothesis: Na esika yango , Davidi azalaki na kondima .\n",
      "2020-02-17 15:36:35,951 Example #1\n",
      "2020-02-17 15:36:35,951 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 15:36:35,951 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 15:36:35,951 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 15:36:35,952 Example #2\n",
      "2020-02-17 15:36:35,952 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 15:36:35,952 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 15:36:35,952 \tHypothesis: Yango wana , nazwaki ekateli ya kobunda na ngai mpe nsukansuka , nsukansuka naboma ngai .\n",
      "2020-02-17 15:36:35,952 Example #3\n",
      "2020-02-17 15:36:35,952 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 15:36:35,952 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 15:36:35,952 \tHypothesis: Moto oyo azali na maladi ya sida akoki mpe kozala na bomoi ya malamu , ata soki azali na mposa ya lisalisi .\n",
      "2020-02-17 15:36:35,952 Example #5\n",
      "2020-02-17 15:36:35,952 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 15:36:35,953 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 15:36:35,953 \tHypothesis: Mbala mosusu oyebi baninga na ye .\n",
      "2020-02-17 15:36:35,953 Example #10\n",
      "2020-02-17 15:36:35,953 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 15:36:35,953 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 15:36:35,953 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na motuya mingi mpo na Yehova .\n",
      "2020-02-17 15:36:35,953 Validation result at epoch  12, step    75000: bleu:  22.89, loss: 42134.8477, ppl:   5.0306, duration: 91.5873s\n",
      "2020-02-17 15:37:04,828 Epoch  12 Step:    75100 Batch Loss:     1.952162 Tokens per Sec:     6889, Lr: 0.000300\n",
      "2020-02-17 15:37:33,970 Epoch  12 Step:    75200 Batch Loss:     1.466928 Tokens per Sec:     7000, Lr: 0.000300\n",
      "2020-02-17 15:38:03,051 Epoch  12 Step:    75300 Batch Loss:     1.896352 Tokens per Sec:     6855, Lr: 0.000300\n",
      "2020-02-17 15:38:32,097 Epoch  12 Step:    75400 Batch Loss:     1.862963 Tokens per Sec:     6925, Lr: 0.000300\n",
      "2020-02-17 15:39:00,926 Epoch  12 Step:    75500 Batch Loss:     1.846097 Tokens per Sec:     6792, Lr: 0.000300\n",
      "2020-02-17 15:39:30,326 Epoch  12 Step:    75600 Batch Loss:     1.779379 Tokens per Sec:     6993, Lr: 0.000300\n",
      "2020-02-17 15:39:59,156 Epoch  12 Step:    75700 Batch Loss:     1.834236 Tokens per Sec:     6995, Lr: 0.000300\n",
      "2020-02-17 15:40:28,037 Epoch  12 Step:    75800 Batch Loss:     1.780199 Tokens per Sec:     6861, Lr: 0.000300\n",
      "2020-02-17 15:40:56,957 Epoch  12 Step:    75900 Batch Loss:     1.877774 Tokens per Sec:     6870, Lr: 0.000300\n",
      "2020-02-17 15:41:25,922 Epoch  12 Step:    76000 Batch Loss:     1.459790 Tokens per Sec:     6777, Lr: 0.000300\n",
      "2020-02-17 15:42:57,134 Example #0\n",
      "2020-02-17 15:42:57,134 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 15:42:57,134 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 15:42:57,134 \tHypothesis: Na esika yango , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 15:42:57,134 Example #1\n",
      "2020-02-17 15:42:57,134 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 15:42:57,134 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 15:42:57,135 \tHypothesis: Na mokuse : Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 15:42:57,135 Example #2\n",
      "2020-02-17 15:42:57,135 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 15:42:57,135 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 15:42:57,135 \tHypothesis: Yango wana , nazwaki ekateli ya kobunda mpe ya nsuka , ya kosilisa mikolo na ngai .\n",
      "2020-02-17 15:42:57,135 Example #3\n",
      "2020-02-17 15:42:57,135 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 15:42:57,135 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 15:42:57,135 \tHypothesis: Asiliki mpe ebatelaka moto oyo azali na maladi ya motó , atako azali na mposa ya kosembola ye .\n",
      "2020-02-17 15:42:57,135 Example #5\n",
      "2020-02-17 15:42:57,136 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 15:42:57,136 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 15:42:57,136 \tHypothesis: Mbala mosusu oyebi bandeko na ye .\n",
      "2020-02-17 15:42:57,136 Example #10\n",
      "2020-02-17 15:42:57,136 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 15:42:57,136 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 15:42:57,136 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na motuya mingi mpo na Yehova .\n",
      "2020-02-17 15:42:57,136 Validation result at epoch  12, step    76000: bleu:  22.88, loss: 42335.3477, ppl:   5.0694, duration: 91.2137s\n",
      "2020-02-17 15:43:26,585 Epoch  12 Step:    76100 Batch Loss:     1.895218 Tokens per Sec:     7002, Lr: 0.000300\n",
      "2020-02-17 15:43:55,860 Epoch  12 Step:    76200 Batch Loss:     1.697705 Tokens per Sec:     6967, Lr: 0.000300\n",
      "2020-02-17 15:44:25,161 Epoch  12 Step:    76300 Batch Loss:     1.657569 Tokens per Sec:     6982, Lr: 0.000300\n",
      "2020-02-17 15:44:54,186 Epoch  12 Step:    76400 Batch Loss:     1.658546 Tokens per Sec:     6864, Lr: 0.000300\n",
      "2020-02-17 15:45:23,592 Epoch  12 Step:    76500 Batch Loss:     1.914333 Tokens per Sec:     7003, Lr: 0.000300\n",
      "2020-02-17 15:45:52,711 Epoch  12 Step:    76600 Batch Loss:     1.976313 Tokens per Sec:     6932, Lr: 0.000300\n",
      "2020-02-17 15:46:22,038 Epoch  12 Step:    76700 Batch Loss:     1.767531 Tokens per Sec:     6961, Lr: 0.000300\n",
      "2020-02-17 15:46:51,440 Epoch  12 Step:    76800 Batch Loss:     1.815468 Tokens per Sec:     6926, Lr: 0.000300\n",
      "2020-02-17 15:47:20,654 Epoch  12 Step:    76900 Batch Loss:     1.671108 Tokens per Sec:     7010, Lr: 0.000300\n",
      "2020-02-17 15:47:49,835 Epoch  12 Step:    77000 Batch Loss:     1.834642 Tokens per Sec:     6926, Lr: 0.000300\n",
      "2020-02-17 15:49:21,317 Example #0\n",
      "2020-02-17 15:49:21,317 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 15:49:21,317 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 15:49:21,317 \tHypothesis: Davidi azalaki moto ya kondima .\n",
      "2020-02-17 15:49:21,317 Example #1\n",
      "2020-02-17 15:49:21,318 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 15:49:21,318 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 15:49:21,318 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 15:49:21,318 Example #2\n",
      "2020-02-17 15:49:21,318 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 15:49:21,318 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 15:49:21,318 \tHypothesis: Na yango , nazwaki ekateli ya kosilisa yango mpe nsukansuka , natikaki yango .\n",
      "2020-02-17 15:49:21,318 Example #3\n",
      "2020-02-17 15:49:21,318 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 15:49:21,318 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 15:49:21,319 \tHypothesis: Awa mpe , avoka ezali na esika ya kozongisa ye na bomoi , ata soki azali na mposa ya koyeba .\n",
      "2020-02-17 15:49:21,319 Example #5\n",
      "2020-02-17 15:49:21,319 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 15:49:21,319 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 15:49:21,319 \tHypothesis: Mbala mosusu oyebi ete baninga na ye bazali na ntina .\n",
      "2020-02-17 15:49:21,319 Example #10\n",
      "2020-02-17 15:49:21,319 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 15:49:21,319 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 15:49:21,319 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 15:49:21,319 Validation result at epoch  12, step    77000: bleu:  22.98, loss: 42171.8633, ppl:   5.0377, duration: 91.4836s\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 15:49:50,392 Epoch  12 Step:    77100 Batch Loss:     1.589444 Tokens per Sec:     6882, Lr: 0.000300\n",
      "2020-02-17 15:50:19,163 Epoch  12 Step:    77200 Batch Loss:     2.021142 Tokens per Sec:     6732, Lr: 0.000300\n",
      "2020-02-17 15:50:48,742 Epoch  12 Step:    77300 Batch Loss:     1.559689 Tokens per Sec:     7161, Lr: 0.000300\n",
      "2020-02-17 15:51:17,988 Epoch  12 Step:    77400 Batch Loss:     1.802407 Tokens per Sec:     6870, Lr: 0.000300\n",
      "2020-02-17 15:51:47,012 Epoch  12 Step:    77500 Batch Loss:     1.895083 Tokens per Sec:     6985, Lr: 0.000300\n",
      "2020-02-17 15:52:16,593 Epoch  12 Step:    77600 Batch Loss:     1.603928 Tokens per Sec:     6907, Lr: 0.000300\n",
      "2020-02-17 15:52:45,614 Epoch  12 Step:    77700 Batch Loss:     1.691057 Tokens per Sec:     6833, Lr: 0.000300\n",
      "2020-02-17 15:53:14,768 Epoch  12 Step:    77800 Batch Loss:     1.941882 Tokens per Sec:     7020, Lr: 0.000300\n",
      "2020-02-17 15:53:44,012 Epoch  12 Step:    77900 Batch Loss:     1.781670 Tokens per Sec:     6987, Lr: 0.000300\n",
      "2020-02-17 15:54:13,327 Epoch  12 Step:    78000 Batch Loss:     1.696551 Tokens per Sec:     6886, Lr: 0.000300\n",
      "2020-02-17 15:55:44,807 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 15:55:44,807 Saving new checkpoint.\n",
      "2020-02-17 15:55:45,034 Example #0\n",
      "2020-02-17 15:55:45,035 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 15:55:45,035 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 15:55:45,035 \tHypothesis: Na boyokani na ye , Davidi azalaki moto ya kondima .\n",
      "2020-02-17 15:55:45,035 Example #1\n",
      "2020-02-17 15:55:45,035 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 15:55:45,035 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 15:55:45,035 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 15:55:45,035 Example #2\n",
      "2020-02-17 15:55:45,035 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 15:55:45,036 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 15:55:45,036 \tHypothesis: Yango wana , nazwaki ekateli ya kosilisa mikakatano na ngai mpe mpo na mwa ntango , nsukansuka natikaki mikolo na ngai .\n",
      "2020-02-17 15:55:45,036 Example #3\n",
      "2020-02-17 15:55:45,036 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 15:55:45,036 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 15:55:45,036 \tHypothesis: Asiri mpe ezali na esika ya kozongisa moto oyo azali na maladi , ata soki azali na mposa ya lisalisi .\n",
      "2020-02-17 15:55:45,036 Example #5\n",
      "2020-02-17 15:55:45,036 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 15:55:45,036 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 15:55:45,036 \tHypothesis: Mbala mosusu oyebi ete baninga na ye bazali na boyokani malamu .\n",
      "2020-02-17 15:55:45,036 Example #10\n",
      "2020-02-17 15:55:45,037 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 15:55:45,037 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 15:55:45,037 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na ntina mingi mpo na Yehova .\n",
      "2020-02-17 15:55:45,037 Validation result at epoch  12, step    78000: bleu:  23.04, loss: 41915.0586, ppl:   4.9884, duration: 91.7093s\n",
      "2020-02-17 15:56:13,976 Epoch  12 Step:    78100 Batch Loss:     1.391871 Tokens per Sec:     6926, Lr: 0.000300\n",
      "2020-02-17 15:56:43,223 Epoch  12 Step:    78200 Batch Loss:     1.781502 Tokens per Sec:     6871, Lr: 0.000300\n",
      "2020-02-17 15:57:11,894 Epoch  12 Step:    78300 Batch Loss:     1.706887 Tokens per Sec:     6758, Lr: 0.000300\n",
      "2020-02-17 15:57:41,116 Epoch  12 Step:    78400 Batch Loss:     1.850405 Tokens per Sec:     7046, Lr: 0.000300\n",
      "2020-02-17 15:58:10,123 Epoch  12 Step:    78500 Batch Loss:     1.703454 Tokens per Sec:     6942, Lr: 0.000300\n",
      "2020-02-17 15:58:39,350 Epoch  12 Step:    78600 Batch Loss:     1.996739 Tokens per Sec:     6976, Lr: 0.000300\n",
      "2020-02-17 15:59:08,462 Epoch  12 Step:    78700 Batch Loss:     1.719445 Tokens per Sec:     6842, Lr: 0.000300\n",
      "2020-02-17 15:59:37,337 Epoch  12 Step:    78800 Batch Loss:     1.781258 Tokens per Sec:     6908, Lr: 0.000300\n",
      "2020-02-17 16:00:06,523 Epoch  12 Step:    78900 Batch Loss:     1.633644 Tokens per Sec:     6866, Lr: 0.000300\n",
      "2020-02-17 16:00:35,636 Epoch  12 Step:    79000 Batch Loss:     1.529018 Tokens per Sec:     6994, Lr: 0.000300\n",
      "2020-02-17 16:02:07,077 Example #0\n",
      "2020-02-17 16:02:07,078 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 16:02:07,078 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 16:02:07,078 \tHypothesis: Davidi azalaki moto ya kondima .\n",
      "2020-02-17 16:02:07,078 Example #1\n",
      "2020-02-17 16:02:07,078 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 16:02:07,078 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 16:02:07,078 \tHypothesis: Eliya alobaki boye : “ Eliya amonisi ete Yehova aleki Baala . ”\n",
      "2020-02-17 16:02:07,078 Example #2\n",
      "2020-02-17 16:02:07,078 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 16:02:07,079 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 16:02:07,079 \tHypothesis: Yango wana , nazwaki ekateli ya kobunda etumba mpe ya nsuka , ya kosilisa mikolo na ngai .\n",
      "2020-02-17 16:02:07,079 Example #3\n",
      "2020-02-17 16:02:07,079 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 16:02:07,079 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 16:02:07,079 \tHypothesis: Asiliki yango ezali mpe na frigo , atako ezali mpenza malamu .\n",
      "2020-02-17 16:02:07,079 Example #5\n",
      "2020-02-17 16:02:07,079 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 16:02:07,079 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 16:02:07,079 \tHypothesis: Mbala mosusu oyebi ete baninga na ye bazali baninga na ye .\n",
      "2020-02-17 16:02:07,079 Example #10\n",
      "2020-02-17 16:02:07,080 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 16:02:07,080 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 16:02:07,080 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na motuya mingi mpo na Yehova .\n",
      "2020-02-17 16:02:07,080 Validation result at epoch  12, step    79000: bleu:  23.08, loss: 42061.4688, ppl:   5.0165, duration: 91.4427s\n",
      "2020-02-17 16:02:36,362 Epoch  12 Step:    79100 Batch Loss:     1.703439 Tokens per Sec:     6907, Lr: 0.000300\n",
      "2020-02-17 16:03:05,206 Epoch  12 Step:    79200 Batch Loss:     1.661050 Tokens per Sec:     6904, Lr: 0.000300\n",
      "2020-02-17 16:03:34,724 Epoch  12 Step:    79300 Batch Loss:     1.868458 Tokens per Sec:     7069, Lr: 0.000300\n",
      "2020-02-17 16:04:03,963 Epoch  12 Step:    79400 Batch Loss:     1.724734 Tokens per Sec:     6895, Lr: 0.000300\n",
      "2020-02-17 16:04:33,160 Epoch  12 Step:    79500 Batch Loss:     1.876484 Tokens per Sec:     6884, Lr: 0.000300\n",
      "2020-02-17 16:05:02,355 Epoch  12 Step:    79600 Batch Loss:     1.810678 Tokens per Sec:     6911, Lr: 0.000300\n",
      "2020-02-17 16:05:31,355 Epoch  12 Step:    79700 Batch Loss:     1.660647 Tokens per Sec:     6903, Lr: 0.000300\n",
      "2020-02-17 16:06:00,566 Epoch  12 Step:    79800 Batch Loss:     1.622740 Tokens per Sec:     6905, Lr: 0.000300\n",
      "2020-02-17 16:06:29,569 Epoch  12 Step:    79900 Batch Loss:     1.729051 Tokens per Sec:     6915, Lr: 0.000300\n",
      "2020-02-17 16:06:58,759 Epoch  12 Step:    80000 Batch Loss:     1.735112 Tokens per Sec:     6935, Lr: 0.000300\n",
      "2020-02-17 16:08:30,206 Example #0\n",
      "2020-02-17 16:08:30,207 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 16:08:30,207 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 16:08:30,207 \tHypothesis: Davidi amonisaki kondima na ye .\n",
      "2020-02-17 16:08:30,207 Example #1\n",
      "2020-02-17 16:08:30,207 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 16:08:30,207 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 16:08:30,207 \tHypothesis: Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 16:08:30,207 Example #2\n",
      "2020-02-17 16:08:30,207 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 16:08:30,208 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 16:08:30,208 \tHypothesis: Yango wana , nazwaki ekateli ya kobunda na ngai , mpe mpo na mwa ntango , nsukansuka naboma mikolo na ngai .\n",
      "2020-02-17 16:08:30,208 Example #3\n",
      "2020-02-17 16:08:30,208 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 16:08:30,208 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 16:08:30,208 \tHypothesis: Vavoka ezali mpe na frigo , atako ezali na mbongwana .\n",
      "2020-02-17 16:08:30,208 Example #5\n",
      "2020-02-17 16:08:30,208 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 16:08:30,208 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 16:08:30,208 \tHypothesis: Mbala mosusu oyebi baninga na ye .\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-17 16:08:30,208 Example #10\n",
      "2020-02-17 16:08:30,209 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 16:08:30,209 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 16:08:30,209 \tHypothesis: Koyika mpiko na komekama motindo wana ezali na motuya mingi mpo na Yehova .\n",
      "2020-02-17 16:08:30,209 Validation result at epoch  12, step    80000: bleu:  22.99, loss: 42113.1836, ppl:   5.0264, duration: 91.4490s\n",
      "2020-02-17 16:08:59,326 Epoch  12 Step:    80100 Batch Loss:     1.723535 Tokens per Sec:     6863, Lr: 0.000300\n",
      "2020-02-17 16:09:28,938 Epoch  12 Step:    80200 Batch Loss:     1.815298 Tokens per Sec:     7162, Lr: 0.000300\n",
      "2020-02-17 16:09:58,070 Epoch  12 Step:    80300 Batch Loss:     1.631668 Tokens per Sec:     6870, Lr: 0.000300\n",
      "2020-02-17 16:10:27,020 Epoch  12 Step:    80400 Batch Loss:     1.750991 Tokens per Sec:     6832, Lr: 0.000300\n",
      "2020-02-17 16:10:56,152 Epoch  12 Step:    80500 Batch Loss:     1.494102 Tokens per Sec:     6977, Lr: 0.000300\n",
      "2020-02-17 16:11:25,059 Epoch  12 Step:    80600 Batch Loss:     1.774574 Tokens per Sec:     6786, Lr: 0.000300\n",
      "2020-02-17 16:11:54,261 Epoch  12 Step:    80700 Batch Loss:     1.830595 Tokens per Sec:     6895, Lr: 0.000300\n",
      "2020-02-17 16:12:23,637 Epoch  12 Step:    80800 Batch Loss:     1.672062 Tokens per Sec:     7041, Lr: 0.000300\n",
      "2020-02-17 16:12:52,604 Epoch  12 Step:    80900 Batch Loss:     1.714442 Tokens per Sec:     6847, Lr: 0.000300\n",
      "2020-02-17 16:13:21,777 Epoch  12 Step:    81000 Batch Loss:     1.645643 Tokens per Sec:     6833, Lr: 0.000300\n",
      "2020-02-17 16:14:53,254 Hooray! New best validation result [ppl]!\n",
      "2020-02-17 16:14:53,254 Saving new checkpoint.\n",
      "2020-02-17 16:14:53,480 Example #0\n",
      "2020-02-17 16:14:53,480 \tSource:     Dans l’ensemble , David s’est montré un homme de foi .\n",
      "2020-02-17 16:14:53,480 \tReference:  Mokonzi Davidi azalaki moto ya sembo , mpe Yehova azalaki kolinga ye mingi .\n",
      "2020-02-17 16:14:53,480 \tHypothesis: Na kati ya bato nyonso , Davidi amonisaki kondima .\n",
      "2020-02-17 16:14:53,480 Example #1\n",
      "2020-02-17 16:14:53,481 \tSource:     Résumé : Éliya apporte la preuve que Jéhovah est supérieur à Baal .\n",
      "2020-02-17 16:14:53,481 \tReference:  Na mokuse : Eliya amonisi ete Yehova aleki Baala .\n",
      "2020-02-17 16:14:53,481 \tHypothesis: Na mokuse : Eliya amonisaki ete Yehova aleki Baala .\n",
      "2020-02-17 16:14:53,481 Example #2\n",
      "2020-02-17 16:14:53,481 \tSource:     J’ai donc décidé de me confesser et , pour pénitence suprême , de mettre fin à mes jours .\n",
      "2020-02-17 16:14:53,481 \tReference:  Lokola namonaki ete nakokoka te kofuta mbongo yango , nakómaki kaka mawamawa .\n",
      "2020-02-17 16:14:53,481 \tHypothesis: Yango wana , nazwaki ekateli ya kosilisa mikakatano na ngai mpe mpo na mwa ntango , nsukansuka natikaki yango .\n",
      "2020-02-17 16:14:53,481 Example #3\n",
      "2020-02-17 16:14:53,481 \tSource:     L’avocat se conserve également au réfrigérateur , même s’il est entamé .\n",
      "2020-02-17 16:14:53,481 \tReference:  Mpo mosuni na yango ekóma moindo te , okoki kosopa mwa mai ya lilala ya ngai likoló na esika oyo okataki yango .\n",
      "2020-02-17 16:14:53,481 \tHypothesis: Vavoka ezali mpe na molɔngɔ ya bato oyo bazali na maladi ya motó , atako bazali na mposa ya kobikela .\n",
      "2020-02-17 16:14:53,482 Example #5\n",
      "2020-02-17 16:14:53,482 \tSource:     Peut - être comprenez - ​ vous ses proches .\n",
      "2020-02-17 16:14:53,482 \tReference:  Ntango mosusu okoki kozala na likanisi ndenge moko na bato ya libota na ye .\n",
      "2020-02-17 16:14:53,482 \tHypothesis: Mbala mosusu oyebi baninga na ye .\n",
      "2020-02-17 16:14:53,482 Example #10\n",
      "2020-02-17 16:14:53,482 \tSource:     L’endurance face à de telles épreuves est particulièrement précieuse pour Jéhovah .\n",
      "2020-02-17 16:14:53,482 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\n",
      "2020-02-17 16:14:53,482 \tHypothesis: Koyika mpiko na komekama motindo wana ezali mpenza na motuya mingi mpo na Yehova .\n",
      "2020-02-17 16:14:53,482 Validation result at epoch  12, step    81000: bleu:  22.87, loss: 41758.3984, ppl:   4.9585, duration: 91.7044s\n",
      "2020-02-17 16:15:22,880 Epoch  12 Step:    81100 Batch Loss:     1.684632 Tokens per Sec:     7034, Lr: 0.000300\n",
      "2020-02-17 16:15:52,183 Epoch  12 Step:    81200 Batch Loss:     1.757635 Tokens per Sec:     6925, Lr: 0.000300\n",
      "2020-02-17 16:16:21,632 Epoch  12 Step:    81300 Batch Loss:     1.758797 Tokens per Sec:     7007, Lr: 0.000300\n",
      "2020-02-17 16:16:50,818 Epoch  12 Step:    81400 Batch Loss:     1.642899 Tokens per Sec:     6859, Lr: 0.000300\n",
      "2020-02-17 16:17:20,106 Epoch  12 Step:    81500 Batch Loss:     1.718354 Tokens per Sec:     7049, Lr: 0.000300\n",
      "2020-02-17 16:17:49,118 Epoch  12 Step:    81600 Batch Loss:     1.848339 Tokens per Sec:     6987, Lr: 0.000300\n",
      "2020-02-17 16:17:54,777 Epoch  12: total training loss 11729.87\n",
      "2020-02-17 16:17:54,777 EPOCH 13\n",
      "2020-02-17 16:18:19,267 Epoch  13 Step:    81700 Batch Loss:     1.745218 Tokens per Sec:     6728, Lr: 0.000300\n",
      "2020-02-17 16:18:48,009 Epoch  13 Step:    81800 Batch Loss:     1.900148 Tokens per Sec:     6942, Lr: 0.000300\n",
      "2020-02-17 16:19:17,312 Epoch  13 Step:    81900 Batch Loss:     1.822659 Tokens per Sec:     6920, Lr: 0.000300\n"
     ]
    }
   ],
   "source": [
    "# Train the model\n",
    "# You can press Ctrl-C to stop. And then run the next cell to save your checkpoints! \n",
    "!python3 -m joeynmt train config/transformer_$src$tgt.yaml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "00340000.hyps.dev   161000.hyps  225000.hyps  29000.hyps   44000.hyps\r\n",
      "00340000.hyps.test  162000.hyps  226000.hyps  290000.hyps  45000.hyps\r\n",
      "1000.hyps\t    163000.hyps  227000.hyps  291000.hyps  46000.hyps\r\n",
      "10000.hyps\t    164000.hyps  228000.hyps  292000.hyps  47000.hyps\r\n",
      "100000.hyps\t    165000.hyps  229000.hyps  293000.hyps  48000.hyps\r\n",
      "101000.hyps\t    166000.hyps  23000.hyps   294000.hyps  49000.hyps\r\n",
      "102000.hyps\t    167000.hyps  230000.hyps  295000.hyps  5000.hyps\r\n",
      "103000.hyps\t    168000.hyps  231000.hyps  296000.hyps  50000.hyps\r\n",
      "104000.hyps\t    169000.hyps  232000.hyps  297000.hyps  51000.hyps\r\n",
      "105000.hyps\t    17000.hyps\t 233000.hyps  298000.hyps  52000.hyps\r\n",
      "106000.hyps\t    170000.hyps  234000.hyps  299000.hyps  53000.hyps\r\n",
      "107000.hyps\t    171000.hyps  235000.hyps  3000.hyps    54000.hyps\r\n",
      "108000.hyps\t    172000.hyps  236000.hyps  30000.hyps   55000.hyps\r\n",
      "109000.hyps\t    173000.hyps  237000.hyps  300000.hyps  56000.hyps\r\n",
      "11000.hyps\t    174000.hyps  238000.hyps  301000.hyps  57000.hyps\r\n",
      "110000.hyps\t    175000.hyps  239000.hyps  302000.hyps  58000.hyps\r\n",
      "111000.hyps\t    176000.hyps  24000.hyps   303000.hyps  59000.hyps\r\n",
      "112000.hyps\t    177000.hyps  240000.hyps  304000.hyps  6000.hyps\r\n",
      "113000.hyps\t    178000.hyps  241000.hyps  305000.hyps  60000.hyps\r\n",
      "114000.hyps\t    179000.hyps  242000.hyps  306000.hyps  61000.hyps\r\n",
      "115000.hyps\t    18000.hyps\t 243000.hyps  307000.hyps  62000.hyps\r\n",
      "116000.hyps\t    180000.hyps  244000.hyps  308000.hyps  63000.hyps\r\n",
      "117000.hyps\t    181000.hyps  245000.hyps  309000.hyps  64000.hyps\r\n",
      "118000.hyps\t    182000.hyps  246000.hyps  31000.hyps   65000.hyps\r\n",
      "119000.hyps\t    183000.hyps  247000.hyps  310000.hyps  66000.hyps\r\n",
      "12000.hyps\t    184000.hyps  248000.hyps  311000.hyps  67000.hyps\r\n",
      "120000.hyps\t    185000.hyps  249000.hyps  312000.hyps  68000.hyps\r\n",
      "121000.hyps\t    186000.hyps  25000.hyps   313000.hyps  69000.hyps\r\n",
      "122000.hyps\t    187000.hyps  250000.hyps  314000.hyps  7000.hyps\r\n",
      "123000.hyps\t    188000.hyps  251000.hyps  315000.hyps  70000.hyps\r\n",
      "124000.hyps\t    189000.hyps  252000.hyps  316000.hyps  71000.hyps\r\n",
      "125000.hyps\t    19000.hyps\t 253000.hyps  317000.hyps  72000.hyps\r\n",
      "126000.hyps\t    190000.hyps  254000.hyps  318000.hyps  73000.hyps\r\n",
      "127000.hyps\t    191000.hyps  255000.hyps  319000.hyps  74000.hyps\r\n",
      "128000.hyps\t    192000.hyps  256000.hyps  32000.hyps   75000.hyps\r\n",
      "129000.hyps\t    193000.hyps  257000.hyps  320000.hyps  76000.hyps\r\n",
      "13000.hyps\t    194000.hyps  258000.hyps  321000.hyps  77000.hyps\r\n",
      "130000.hyps\t    195000.hyps  259000.hyps  322000.hyps  78000.hyps\r\n",
      "131000.hyps\t    196000.hyps  26000.hyps   323000.hyps  79000.hyps\r\n",
      "132000.hyps\t    197000.hyps  260000.hyps  324000.hyps  8000.hyps\r\n",
      "133000.hyps\t    198000.hyps  261000.hyps  325000.hyps  80000.hyps\r\n",
      "134000.hyps\t    199000.hyps  262000.hyps  326000.hyps  81000.hyps\r\n",
      "135000.hyps\t    2000.hyps\t 263000.hyps  327000.hyps  82000.hyps\r\n",
      "136000.hyps\t    20000.hyps\t 264000.hyps  328000.hyps  83000.hyps\r\n",
      "137000.hyps\t    200000.hyps  265000.hyps  329000.hyps  84000.hyps\r\n",
      "138000.hyps\t    201000.hyps  266000.hyps  33000.hyps   85000.hyps\r\n",
      "139000.hyps\t    202000.hyps  267000.hyps  330000.hyps  86000.hyps\r\n",
      "14000.hyps\t    203000.hyps  268000.hyps  331000.hyps  87000.hyps\r\n",
      "140000.hyps\t    204000.hyps  269000.hyps  332000.hyps  88000.hyps\r\n",
      "141000.hyps\t    205000.hyps  27000.hyps   333000.hyps  89000.hyps\r\n",
      "142000.hyps\t    206000.hyps  270000.hyps  334000.hyps  9000.hyps\r\n",
      "143000.hyps\t    207000.hyps  271000.hyps  335000.hyps  90000.hyps\r\n",
      "144000.hyps\t    208000.hyps  272000.hyps  336000.hyps  91000.hyps\r\n",
      "145000.hyps\t    209000.hyps  273000.hyps  337000.hyps  92000.hyps\r\n",
      "146000.hyps\t    21000.hyps\t 274000.hyps  338000.ckpt  93000.hyps\r\n",
      "147000.hyps\t    210000.hyps  275000.hyps  338000.hyps  94000.hyps\r\n",
      "148000.hyps\t    211000.hyps  276000.hyps  339000.ckpt  95000.hyps\r\n",
      "149000.hyps\t    212000.hyps  277000.hyps  339000.hyps  96000.hyps\r\n",
      "15000.hyps\t    213000.hyps  278000.hyps  34000.hyps   97000.hyps\r\n",
      "150000.hyps\t    214000.hyps  279000.hyps  340000.ckpt  98000.hyps\r\n",
      "151000.hyps\t    215000.hyps  28000.hyps   340000.hyps  99000.hyps\r\n",
      "152000.hyps\t    216000.hyps  280000.hyps  35000.hyps   best.ckpt\r\n",
      "153000.hyps\t    217000.hyps  281000.hyps  36000.hyps   config.yaml\r\n",
      "154000.hyps\t    218000.hyps  282000.hyps  37000.hyps   src_vocab.txt\r\n",
      "155000.hyps\t    219000.hyps  283000.hyps  38000.hyps   tensorboard\r\n",
      "156000.hyps\t    22000.hyps\t 284000.hyps  39000.hyps   train.log\r\n",
      "157000.hyps\t    220000.hyps  285000.hyps  4000.hyps    trg_vocab.txt\r\n",
      "158000.hyps\t    221000.hyps  286000.hyps  40000.hyps   validations.txt\r\n",
      "159000.hyps\t    222000.hyps  287000.hyps  41000.hyps\r\n",
      "16000.hyps\t    223000.hyps  288000.hyps  42000.hyps\r\n",
      "160000.hyps\t    224000.hyps  289000.hyps  43000.hyps\r\n"
     ]
    }
   ],
   "source": [
    "!ls models/${src}${tgt}_transformer"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-18 21:41:02,507 \tReference:  Koyika mpiko liboso ya komekama wana ezali na motuya mingi na miso ya Yehova .\r\n",
      "2020-02-18 21:41:02,507 \tHypothesis: Koyika mpiko na mikakatano ya ndenge wana ezali na ntina mingi mpo na Yehova .\r\n",
      "2020-02-18 21:41:02,507 Validation result at epoch  50, step   340000: bleu:  26.01, loss: 36485.8125, ppl:   4.0509, duration: 91.8879s\r\n",
      "2020-02-18 21:41:15,915 Epoch  50: total training loss 9823.72\r\n",
      "2020-02-18 21:41:15,916 Training ended after  50 epochs.\r\n",
      "2020-02-18 21:41:15,917 Best validation result at step   340000:   4.05 ppl.\r\n",
      "2020-02-18 21:42:16,780  dev bleu:  26.41 [Beam search decoding with beam size = 5 and alpha = 1.0]\r\n",
      "2020-02-18 21:42:16,781 Translations saved to: models/frln_transformer/00340000.hyps.dev\r\n",
      "2020-02-18 21:43:42,414 test bleu:  39.81 [Beam search decoding with beam size = 5 and alpha = 1.0]\r\n",
      "2020-02-18 21:43:42,415 Translations saved to: models/frln_transformer/00340000.hyps.test\r\n"
     ]
    }
   ],
   "source": [
    "! tail -10 models/${src}${tgt}_transformer/train.log"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Steps: 1000\tLoss: 101679.10156\tPPL: 49.33279\tbleu: 1.33240\tLR: 0.00030000\t*\r\n",
      "Steps: 2000\tLoss: 88058.70312\tPPL: 29.26390\tbleu: 2.45411\tLR: 0.00030000\t*\r\n",
      "Steps: 3000\tLoss: 80679.00000\tPPL: 22.05196\tbleu: 4.06626\tLR: 0.00030000\t*\r\n",
      "Steps: 4000\tLoss: 75131.75000\tPPL: 17.82689\tbleu: 5.93282\tLR: 0.00030000\t*\r\n",
      "Steps: 5000\tLoss: 71755.00000\tPPL: 15.66199\tbleu: 6.58848\tLR: 0.00030000\t*\r\n",
      "Steps: 6000\tLoss: 68735.87500\tPPL: 13.94997\tbleu: 7.54377\tLR: 0.00030000\t*\r\n",
      "Steps: 7000\tLoss: 66262.40625\tPPL: 12.68777\tbleu: 8.01831\tLR: 0.00030000\t*\r\n",
      "Steps: 8000\tLoss: 64169.54688\tPPL: 11.70943\tbleu: 9.94326\tLR: 0.00030000\t*\r\n",
      "Steps: 9000\tLoss: 62004.48828\tPPL: 10.77665\tbleu: 11.03149\tLR: 0.00030000\t*\r\n",
      "Steps: 10000\tLoss: 60213.03906\tPPL: 10.06127\tbleu: 11.97307\tLR: 0.00030000\t*\r\n",
      "Steps: 11000\tLoss: 59205.46484\tPPL: 9.67999\tbleu: 12.25209\tLR: 0.00030000\t*\r\n",
      "Steps: 12000\tLoss: 57379.75000\tPPL: 9.02555\tbleu: 13.70872\tLR: 0.00030000\t*\r\n",
      "Steps: 13000\tLoss: 56491.82812\tPPL: 8.72345\tbleu: 14.60505\tLR: 0.00030000\t*\r\n",
      "Steps: 14000\tLoss: 55644.25781\tPPL: 8.44451\tbleu: 14.64641\tLR: 0.00030000\t*\r\n",
      "Steps: 15000\tLoss: 54724.98047\tPPL: 8.15205\tbleu: 15.57949\tLR: 0.00030000\t*\r\n",
      "Steps: 16000\tLoss: 53939.67969\tPPL: 7.91026\tbleu: 16.26362\tLR: 0.00030000\t*\r\n",
      "Steps: 17000\tLoss: 53433.07812\tPPL: 7.75809\tbleu: 16.70799\tLR: 0.00030000\t*\r\n",
      "Steps: 18000\tLoss: 52861.15234\tPPL: 7.58981\tbleu: 17.01954\tLR: 0.00030000\t*\r\n",
      "Steps: 19000\tLoss: 52035.28125\tPPL: 7.35324\tbleu: 17.63327\tLR: 0.00030000\t*\r\n",
      "Steps: 20000\tLoss: 51777.23438\tPPL: 7.28085\tbleu: 17.72100\tLR: 0.00030000\t*\r\n",
      "Steps: 21000\tLoss: 51327.28125\tPPL: 7.15631\tbleu: 17.33761\tLR: 0.00030000\t*\r\n",
      "Steps: 22000\tLoss: 50891.76562\tPPL: 7.03781\tbleu: 18.16474\tLR: 0.00030000\t*\r\n",
      "Steps: 23000\tLoss: 50144.26172\tPPL: 6.83896\tbleu: 18.18213\tLR: 0.00030000\t*\r\n",
      "Steps: 24000\tLoss: 49846.03516\tPPL: 6.76121\tbleu: 18.82128\tLR: 0.00030000\t*\r\n",
      "Steps: 25000\tLoss: 49549.55078\tPPL: 6.68478\tbleu: 18.57156\tLR: 0.00030000\t*\r\n",
      "Steps: 26000\tLoss: 49035.42578\tPPL: 6.55430\tbleu: 19.03277\tLR: 0.00030000\t*\r\n",
      "Steps: 27000\tLoss: 48913.80078\tPPL: 6.52380\tbleu: 19.10633\tLR: 0.00030000\t*\r\n",
      "Steps: 28000\tLoss: 48533.06641\tPPL: 6.42926\tbleu: 19.39287\tLR: 0.00030000\t*\r\n",
      "Steps: 29000\tLoss: 48354.89453\tPPL: 6.38549\tbleu: 19.43792\tLR: 0.00030000\t*\r\n",
      "Steps: 30000\tLoss: 47965.75391\tPPL: 6.29092\tbleu: 19.62763\tLR: 0.00030000\t*\r\n",
      "Steps: 31000\tLoss: 47858.84766\tPPL: 6.26518\tbleu: 20.14754\tLR: 0.00030000\t*\r\n",
      "Steps: 32000\tLoss: 47841.95312\tPPL: 6.26113\tbleu: 20.04378\tLR: 0.00030000\t*\r\n",
      "Steps: 33000\tLoss: 47557.24609\tPPL: 6.19315\tbleu: 19.63941\tLR: 0.00030000\t*\r\n",
      "Steps: 34000\tLoss: 47185.04297\tPPL: 6.10540\tbleu: 19.80409\tLR: 0.00030000\t*\r\n",
      "Steps: 35000\tLoss: 46868.43359\tPPL: 6.03173\tbleu: 20.57481\tLR: 0.00030000\t*\r\n",
      "Steps: 36000\tLoss: 46619.85938\tPPL: 5.97451\tbleu: 20.45801\tLR: 0.00030000\t*\r\n",
      "Steps: 37000\tLoss: 46506.66406\tPPL: 5.94864\tbleu: 20.56136\tLR: 0.00030000\t*\r\n",
      "Steps: 38000\tLoss: 46380.87891\tPPL: 5.92002\tbleu: 20.62308\tLR: 0.00030000\t*\r\n",
      "Steps: 39000\tLoss: 46074.70703\tPPL: 5.85093\tbleu: 20.51120\tLR: 0.00030000\t*\r\n",
      "Steps: 40000\tLoss: 46016.93750\tPPL: 5.83798\tbleu: 20.72798\tLR: 0.00030000\t*\r\n",
      "Steps: 41000\tLoss: 45913.75781\tPPL: 5.81493\tbleu: 20.76427\tLR: 0.00030000\t*\r\n",
      "Steps: 42000\tLoss: 45596.52344\tPPL: 5.74463\tbleu: 20.97934\tLR: 0.00030000\t*\r\n",
      "Steps: 43000\tLoss: 45430.04297\tPPL: 5.70808\tbleu: 21.19879\tLR: 0.00030000\t*\r\n",
      "Steps: 44000\tLoss: 45194.33984\tPPL: 5.65673\tbleu: 21.41042\tLR: 0.00030000\t*\r\n",
      "Steps: 45000\tLoss: 45369.07812\tPPL: 5.69475\tbleu: 20.80849\tLR: 0.00030000\t\r\n",
      "Steps: 46000\tLoss: 45157.38281\tPPL: 5.64872\tbleu: 21.17630\tLR: 0.00030000\t*\r\n",
      "Steps: 47000\tLoss: 44869.47656\tPPL: 5.58670\tbleu: 21.40846\tLR: 0.00030000\t*\r\n",
      "Steps: 48000\tLoss: 44749.16016\tPPL: 5.56099\tbleu: 21.66075\tLR: 0.00030000\t*\r\n",
      "Steps: 49000\tLoss: 44515.61328\tPPL: 5.51142\tbleu: 21.63240\tLR: 0.00030000\t*\r\n",
      "Steps: 50000\tLoss: 44514.06641\tPPL: 5.51109\tbleu: 21.36828\tLR: 0.00030000\t*\r\n",
      "Steps: 51000\tLoss: 44464.16406\tPPL: 5.50055\tbleu: 21.88695\tLR: 0.00030000\t*\r\n",
      "Steps: 52000\tLoss: 44206.90625\tPPL: 5.44657\tbleu: 21.82749\tLR: 0.00030000\t*\r\n",
      "Steps: 53000\tLoss: 44414.19141\tPPL: 5.49003\tbleu: 21.38103\tLR: 0.00030000\t\r\n",
      "Steps: 54000\tLoss: 43957.08203\tPPL: 5.39464\tbleu: 21.86449\tLR: 0.00030000\t*\r\n",
      "Steps: 55000\tLoss: 43946.18750\tPPL: 5.39239\tbleu: 21.84823\tLR: 0.00030000\t*\r\n",
      "Steps: 56000\tLoss: 43917.27344\tPPL: 5.38641\tbleu: 22.03345\tLR: 0.00030000\t*\r\n",
      "Steps: 57000\tLoss: 43951.16016\tPPL: 5.39342\tbleu: 22.03252\tLR: 0.00030000\t\r\n",
      "Steps: 58000\tLoss: 43622.57812\tPPL: 5.32589\tbleu: 22.28939\tLR: 0.00030000\t*\r\n",
      "Steps: 59000\tLoss: 43329.02734\tPPL: 5.26629\tbleu: 22.05428\tLR: 0.00030000\t*\r\n",
      "Steps: 60000\tLoss: 43353.47266\tPPL: 5.27122\tbleu: 22.43904\tLR: 0.00030000\t\r\n",
      "Steps: 61000\tLoss: 43338.01172\tPPL: 5.26810\tbleu: 22.72373\tLR: 0.00030000\t\r\n",
      "Steps: 62000\tLoss: 43176.97656\tPPL: 5.23567\tbleu: 22.60875\tLR: 0.00030000\t*\r\n",
      "Steps: 63000\tLoss: 43042.35156\tPPL: 5.20872\tbleu: 22.23387\tLR: 0.00030000\t*\r\n",
      "Steps: 64000\tLoss: 43078.14844\tPPL: 5.21587\tbleu: 22.40861\tLR: 0.00030000\t\r\n",
      "Steps: 65000\tLoss: 42972.92969\tPPL: 5.19487\tbleu: 22.62606\tLR: 0.00030000\t*\r\n",
      "Steps: 66000\tLoss: 42892.09766\tPPL: 5.17880\tbleu: 22.74644\tLR: 0.00030000\t*\r\n",
      "Steps: 67000\tLoss: 42809.83594\tPPL: 5.16249\tbleu: 22.39873\tLR: 0.00030000\t*\r\n",
      "Steps: 68000\tLoss: 42824.83203\tPPL: 5.16546\tbleu: 22.52395\tLR: 0.00030000\t\r\n",
      "Steps: 69000\tLoss: 42665.92969\tPPL: 5.13408\tbleu: 22.52202\tLR: 0.00030000\t*\r\n",
      "Steps: 70000\tLoss: 42583.83984\tPPL: 5.11795\tbleu: 22.84108\tLR: 0.00030000\t*\r\n",
      "Steps: 71000\tLoss: 42339.40625\tPPL: 5.07021\tbleu: 23.10021\tLR: 0.00030000\t*\r\n",
      "Steps: 72000\tLoss: 42293.76562\tPPL: 5.06134\tbleu: 22.49275\tLR: 0.00030000\t*\r\n",
      "Steps: 73000\tLoss: 42467.15625\tPPL: 5.09510\tbleu: 23.01485\tLR: 0.00030000\t\r\n",
      "Steps: 74000\tLoss: 42306.43359\tPPL: 5.06380\tbleu: 23.19691\tLR: 0.00030000\t\r\n",
      "Steps: 75000\tLoss: 42134.84766\tPPL: 5.03059\tbleu: 22.88508\tLR: 0.00030000\t*\r\n",
      "Steps: 76000\tLoss: 42335.34766\tPPL: 5.06942\tbleu: 22.88428\tLR: 0.00030000\t\r\n",
      "Steps: 77000\tLoss: 42171.86328\tPPL: 5.03774\tbleu: 22.97889\tLR: 0.00030000\t\r\n",
      "Steps: 78000\tLoss: 41915.05859\tPPL: 4.98838\tbleu: 23.03592\tLR: 0.00030000\t*\r\n",
      "Steps: 79000\tLoss: 42061.46875\tPPL: 5.01646\tbleu: 23.08098\tLR: 0.00030000\t\r\n",
      "Steps: 80000\tLoss: 42113.18359\tPPL: 5.02642\tbleu: 22.98955\tLR: 0.00030000\t\r\n",
      "Steps: 81000\tLoss: 41758.39844\tPPL: 4.95851\tbleu: 22.86890\tLR: 0.00030000\t*\r\n",
      "Steps: 82000\tLoss: 41731.75391\tPPL: 4.95344\tbleu: 23.23269\tLR: 0.00030000\t*\r\n",
      "Steps: 83000\tLoss: 41801.21484\tPPL: 4.96665\tbleu: 23.31127\tLR: 0.00030000\t\r\n",
      "Steps: 84000\tLoss: 41782.59375\tPPL: 4.96311\tbleu: 23.22442\tLR: 0.00030000\t\r\n",
      "Steps: 85000\tLoss: 41711.61719\tPPL: 4.94962\tbleu: 23.37525\tLR: 0.00030000\t*\r\n",
      "Steps: 86000\tLoss: 41770.56641\tPPL: 4.96082\tbleu: 23.11197\tLR: 0.00030000\t\r\n",
      "Steps: 87000\tLoss: 41436.55078\tPPL: 4.89769\tbleu: 23.20010\tLR: 0.00030000\t*\r\n",
      "Steps: 88000\tLoss: 41524.67578\tPPL: 4.91427\tbleu: 23.49476\tLR: 0.00030000\t\r\n",
      "Steps: 89000\tLoss: 41540.50391\tPPL: 4.91725\tbleu: 23.34480\tLR: 0.00030000\t\r\n",
      "Steps: 90000\tLoss: 41290.56641\tPPL: 4.87035\tbleu: 23.12195\tLR: 0.00030000\t*\r\n",
      "Steps: 91000\tLoss: 41327.60547\tPPL: 4.87728\tbleu: 23.44402\tLR: 0.00030000\t\r\n",
      "Steps: 92000\tLoss: 41247.03125\tPPL: 4.86223\tbleu: 23.15953\tLR: 0.00030000\t*\r\n",
      "Steps: 93000\tLoss: 41187.75000\tPPL: 4.85119\tbleu: 23.57970\tLR: 0.00030000\t*\r\n",
      "Steps: 94000\tLoss: 41166.05469\tPPL: 4.84716\tbleu: 23.67379\tLR: 0.00030000\t*\r\n",
      "Steps: 95000\tLoss: 41061.65234\tPPL: 4.82779\tbleu: 23.50138\tLR: 0.00030000\t*\r\n",
      "Steps: 96000\tLoss: 41026.46094\tPPL: 4.82128\tbleu: 23.74046\tLR: 0.00030000\t*\r\n",
      "Steps: 97000\tLoss: 40990.12500\tPPL: 4.81457\tbleu: 23.74295\tLR: 0.00030000\t*\r\n",
      "Steps: 98000\tLoss: 40944.87891\tPPL: 4.80623\tbleu: 23.84000\tLR: 0.00030000\t*\r\n",
      "Steps: 99000\tLoss: 41057.69531\tPPL: 4.82706\tbleu: 23.80839\tLR: 0.00030000\t\r\n",
      "Steps: 100000\tLoss: 40912.97656\tPPL: 4.80035\tbleu: 23.53383\tLR: 0.00030000\t*\r\n",
      "Steps: 101000\tLoss: 40766.28516\tPPL: 4.77343\tbleu: 24.25189\tLR: 0.00030000\t*\r\n",
      "Steps: 102000\tLoss: 40830.78125\tPPL: 4.78525\tbleu: 23.38600\tLR: 0.00030000\t\r\n",
      "Steps: 103000\tLoss: 40713.16406\tPPL: 4.76371\tbleu: 24.02089\tLR: 0.00030000\t*\r\n",
      "Steps: 104000\tLoss: 40834.70312\tPPL: 4.78597\tbleu: 23.53414\tLR: 0.00030000\t\r\n",
      "Steps: 105000\tLoss: 40768.17578\tPPL: 4.77377\tbleu: 23.88244\tLR: 0.00030000\t\r\n",
      "Steps: 106000\tLoss: 40597.51172\tPPL: 4.74264\tbleu: 23.86986\tLR: 0.00030000\t*\r\n",
      "Steps: 107000\tLoss: 40599.54297\tPPL: 4.74301\tbleu: 24.01265\tLR: 0.00030000\t\r\n",
      "Steps: 108000\tLoss: 40465.15625\tPPL: 4.71863\tbleu: 23.77551\tLR: 0.00030000\t*\r\n",
      "Steps: 109000\tLoss: 40399.41797\tPPL: 4.70675\tbleu: 23.87734\tLR: 0.00030000\t*\r\n",
      "Steps: 110000\tLoss: 40642.17578\tPPL: 4.75077\tbleu: 23.86125\tLR: 0.00030000\t\r\n",
      "Steps: 111000\tLoss: 40342.22656\tPPL: 4.69644\tbleu: 24.20626\tLR: 0.00030000\t*\r\n",
      "Steps: 112000\tLoss: 40421.64453\tPPL: 4.71076\tbleu: 23.87079\tLR: 0.00030000\t\r\n",
      "Steps: 113000\tLoss: 40385.76172\tPPL: 4.70429\tbleu: 24.06776\tLR: 0.00030000\t\r\n",
      "Steps: 114000\tLoss: 40343.88281\tPPL: 4.69674\tbleu: 24.07500\tLR: 0.00030000\t\r\n",
      "Steps: 115000\tLoss: 40497.32812\tPPL: 4.72445\tbleu: 24.32898\tLR: 0.00030000\t\r\n",
      "Steps: 116000\tLoss: 40240.77734\tPPL: 4.67821\tbleu: 24.41094\tLR: 0.00030000\t*\r\n",
      "Steps: 117000\tLoss: 40269.53516\tPPL: 4.68337\tbleu: 24.32106\tLR: 0.00030000\t\r\n",
      "Steps: 118000\tLoss: 40206.21484\tPPL: 4.67201\tbleu: 24.24703\tLR: 0.00030000\t*\r\n",
      "Steps: 119000\tLoss: 40100.55469\tPPL: 4.65312\tbleu: 24.40075\tLR: 0.00030000\t*\r\n",
      "Steps: 120000\tLoss: 40076.69531\tPPL: 4.64887\tbleu: 23.82390\tLR: 0.00030000\t*\r\n",
      "Steps: 121000\tLoss: 39988.56641\tPPL: 4.63319\tbleu: 24.45055\tLR: 0.00030000\t*\r\n",
      "Steps: 122000\tLoss: 40067.46875\tPPL: 4.64723\tbleu: 24.01967\tLR: 0.00030000\t\r\n",
      "Steps: 123000\tLoss: 40119.18750\tPPL: 4.65645\tbleu: 24.15491\tLR: 0.00030000\t\r\n",
      "Steps: 124000\tLoss: 40116.58203\tPPL: 4.65599\tbleu: 23.83102\tLR: 0.00030000\t\r\n",
      "Steps: 125000\tLoss: 40037.85547\tPPL: 4.64195\tbleu: 24.24915\tLR: 0.00030000\t\r\n",
      "Steps: 126000\tLoss: 39932.27344\tPPL: 4.62320\tbleu: 23.78899\tLR: 0.00030000\t*\r\n",
      "Steps: 127000\tLoss: 40056.46875\tPPL: 4.64527\tbleu: 23.75064\tLR: 0.00030000\t\r\n",
      "Steps: 128000\tLoss: 39960.00391\tPPL: 4.62812\tbleu: 24.20816\tLR: 0.00030000\t\r\n",
      "Steps: 129000\tLoss: 39824.81641\tPPL: 4.60419\tbleu: 24.08688\tLR: 0.00030000\t*\r\n",
      "Steps: 130000\tLoss: 40194.14844\tPPL: 4.66985\tbleu: 23.89545\tLR: 0.00030000\t\r\n",
      "Steps: 131000\tLoss: 39864.52344\tPPL: 4.61120\tbleu: 24.52751\tLR: 0.00030000\t\r\n",
      "Steps: 132000\tLoss: 39867.10547\tPPL: 4.61166\tbleu: 24.30390\tLR: 0.00030000\t\r\n",
      "Steps: 133000\tLoss: 39768.19531\tPPL: 4.59420\tbleu: 24.12154\tLR: 0.00030000\t*\r\n",
      "Steps: 134000\tLoss: 39608.72266\tPPL: 4.56620\tbleu: 24.05779\tLR: 0.00030000\t*\r\n",
      "Steps: 135000\tLoss: 39667.46484\tPPL: 4.57649\tbleu: 24.45814\tLR: 0.00030000\t\r\n",
      "Steps: 136000\tLoss: 39619.28906\tPPL: 4.56805\tbleu: 24.36177\tLR: 0.00030000\t\r\n",
      "Steps: 137000\tLoss: 39684.97656\tPPL: 4.57957\tbleu: 24.21350\tLR: 0.00030000\t\r\n",
      "Steps: 138000\tLoss: 39768.20312\tPPL: 4.59421\tbleu: 24.20446\tLR: 0.00030000\t\r\n",
      "Steps: 139000\tLoss: 39662.10938\tPPL: 4.57556\tbleu: 24.77856\tLR: 0.00030000\t\r\n",
      "Steps: 140000\tLoss: 39570.71484\tPPL: 4.55955\tbleu: 23.79534\tLR: 0.00030000\t*\r\n",
      "Steps: 141000\tLoss: 39411.42969\tPPL: 4.53179\tbleu: 24.67024\tLR: 0.00030000\t*\r\n",
      "Steps: 142000\tLoss: 39430.42188\tPPL: 4.53509\tbleu: 23.93959\tLR: 0.00030000\t\r\n",
      "Steps: 143000\tLoss: 39545.50000\tPPL: 4.55514\tbleu: 24.50400\tLR: 0.00030000\t\r\n",
      "Steps: 144000\tLoss: 39565.53906\tPPL: 4.55864\tbleu: 24.34218\tLR: 0.00030000\t\r\n",
      "Steps: 145000\tLoss: 39404.74219\tPPL: 4.53063\tbleu: 24.04266\tLR: 0.00030000\t*\r\n",
      "Steps: 146000\tLoss: 39470.20312\tPPL: 4.54201\tbleu: 24.45154\tLR: 0.00030000\t\r\n",
      "Steps: 147000\tLoss: 39418.54688\tPPL: 4.53302\tbleu: 24.41024\tLR: 0.00030000\t\r\n",
      "Steps: 148000\tLoss: 39543.28906\tPPL: 4.55476\tbleu: 24.66010\tLR: 0.00030000\t\r\n",
      "Steps: 149000\tLoss: 39386.12500\tPPL: 4.52739\tbleu: 24.63091\tLR: 0.00030000\t*\r\n",
      "Steps: 150000\tLoss: 39426.64844\tPPL: 4.53443\tbleu: 24.64088\tLR: 0.00030000\t\r\n",
      "Steps: 151000\tLoss: 39362.42969\tPPL: 4.52328\tbleu: 24.27962\tLR: 0.00030000\t*\r\n",
      "Steps: 152000\tLoss: 39311.46484\tPPL: 4.51445\tbleu: 24.50753\tLR: 0.00030000\t*\r\n",
      "Steps: 153000\tLoss: 39197.44141\tPPL: 4.49476\tbleu: 24.58805\tLR: 0.00030000\t*\r\n",
      "Steps: 154000\tLoss: 39326.75000\tPPL: 4.51710\tbleu: 24.69803\tLR: 0.00030000\t\r\n",
      "Steps: 155000\tLoss: 39259.05078\tPPL: 4.50539\tbleu: 24.81798\tLR: 0.00030000\t\r\n",
      "Steps: 156000\tLoss: 39199.46875\tPPL: 4.49511\tbleu: 24.57370\tLR: 0.00030000\t\r\n",
      "Steps: 157000\tLoss: 39282.15625\tPPL: 4.50938\tbleu: 24.73571\tLR: 0.00030000\t\r\n",
      "Steps: 158000\tLoss: 39249.12891\tPPL: 4.50367\tbleu: 24.72239\tLR: 0.00030000\t\r\n",
      "Steps: 159000\tLoss: 39104.40234\tPPL: 4.47875\tbleu: 24.96477\tLR: 0.00030000\t*\r\n",
      "Steps: 160000\tLoss: 39214.86719\tPPL: 4.49776\tbleu: 24.05002\tLR: 0.00030000\t\r\n",
      "Steps: 161000\tLoss: 39105.10156\tPPL: 4.47887\tbleu: 24.28783\tLR: 0.00030000\t\r\n",
      "Steps: 162000\tLoss: 39018.82422\tPPL: 4.46408\tbleu: 24.73780\tLR: 0.00030000\t*\r\n",
      "Steps: 163000\tLoss: 38984.87500\tPPL: 4.45827\tbleu: 24.86656\tLR: 0.00030000\t*\r\n",
      "Steps: 164000\tLoss: 39074.98047\tPPL: 4.47370\tbleu: 24.85352\tLR: 0.00030000\t\r\n",
      "Steps: 165000\tLoss: 39015.23047\tPPL: 4.46347\tbleu: 24.23604\tLR: 0.00030000\t\r\n",
      "Steps: 166000\tLoss: 39068.39453\tPPL: 4.47257\tbleu: 24.49343\tLR: 0.00030000\t\r\n",
      "Steps: 167000\tLoss: 39021.19531\tPPL: 4.46449\tbleu: 24.49139\tLR: 0.00030000\t\r\n",
      "Steps: 168000\tLoss: 38896.71875\tPPL: 4.44323\tbleu: 24.89473\tLR: 0.00030000\t*\r\n",
      "Steps: 169000\tLoss: 38997.51562\tPPL: 4.46043\tbleu: 24.82493\tLR: 0.00030000\t\r\n",
      "Steps: 170000\tLoss: 38739.85547\tPPL: 4.41659\tbleu: 24.71142\tLR: 0.00030000\t*\r\n",
      "Steps: 171000\tLoss: 38971.53906\tPPL: 4.45599\tbleu: 24.65804\tLR: 0.00030000\t\r\n",
      "Steps: 172000\tLoss: 38906.62500\tPPL: 4.44492\tbleu: 24.59160\tLR: 0.00030000\t\r\n",
      "Steps: 173000\tLoss: 38903.49219\tPPL: 4.44438\tbleu: 24.52246\tLR: 0.00030000\t\r\n",
      "Steps: 174000\tLoss: 38875.42188\tPPL: 4.43960\tbleu: 25.01598\tLR: 0.00030000\t\r\n",
      "Steps: 175000\tLoss: 38816.67969\tPPL: 4.42961\tbleu: 25.02861\tLR: 0.00030000\t\r\n",
      "Steps: 176000\tLoss: 38755.00391\tPPL: 4.41915\tbleu: 24.79982\tLR: 0.00021000\t\r\n",
      "Steps: 177000\tLoss: 38593.99609\tPPL: 4.39195\tbleu: 24.91530\tLR: 0.00021000\t*\r\n",
      "Steps: 178000\tLoss: 38723.52344\tPPL: 4.41382\tbleu: 24.98486\tLR: 0.00021000\t\r\n",
      "Steps: 179000\tLoss: 38475.04297\tPPL: 4.37197\tbleu: 25.30374\tLR: 0.00021000\t*\r\n",
      "Steps: 180000\tLoss: 38445.12891\tPPL: 4.36696\tbleu: 25.03510\tLR: 0.00021000\t*\r\n",
      "Steps: 181000\tLoss: 38434.19922\tPPL: 4.36513\tbleu: 25.15144\tLR: 0.00021000\t*\r\n",
      "Steps: 182000\tLoss: 38472.80078\tPPL: 4.37159\tbleu: 25.40420\tLR: 0.00021000\t\r\n",
      "Steps: 183000\tLoss: 38301.28516\tPPL: 4.34294\tbleu: 25.08173\tLR: 0.00021000\t*\r\n",
      "Steps: 184000\tLoss: 38346.58594\tPPL: 4.35049\tbleu: 25.42036\tLR: 0.00021000\t\r\n",
      "Steps: 185000\tLoss: 38335.68750\tPPL: 4.34867\tbleu: 25.23870\tLR: 0.00021000\t\r\n",
      "Steps: 186000\tLoss: 38368.85547\tPPL: 4.35421\tbleu: 25.07541\tLR: 0.00021000\t\r\n",
      "Steps: 187000\tLoss: 38303.77344\tPPL: 4.34335\tbleu: 25.15464\tLR: 0.00021000\t\r\n",
      "Steps: 188000\tLoss: 38259.19922\tPPL: 4.33594\tbleu: 25.08374\tLR: 0.00021000\t*\r\n",
      "Steps: 189000\tLoss: 38157.01953\tPPL: 4.31898\tbleu: 25.18103\tLR: 0.00021000\t*\r\n",
      "Steps: 190000\tLoss: 38184.35938\tPPL: 4.32351\tbleu: 25.07878\tLR: 0.00021000\t\r\n",
      "Steps: 191000\tLoss: 38139.82422\tPPL: 4.31614\tbleu: 25.33993\tLR: 0.00021000\t*\r\n",
      "Steps: 192000\tLoss: 38227.16406\tPPL: 4.33061\tbleu: 25.16416\tLR: 0.00021000\t\r\n",
      "Steps: 193000\tLoss: 38130.87500\tPPL: 4.31465\tbleu: 25.05110\tLR: 0.00021000\t*\r\n",
      "Steps: 194000\tLoss: 38223.31250\tPPL: 4.32997\tbleu: 25.31304\tLR: 0.00021000\t\r\n",
      "Steps: 195000\tLoss: 38078.04297\tPPL: 4.30592\tbleu: 24.60500\tLR: 0.00021000\t*\r\n",
      "Steps: 196000\tLoss: 38149.82031\tPPL: 4.31779\tbleu: 24.95405\tLR: 0.00021000\t\r\n",
      "Steps: 197000\tLoss: 38087.96875\tPPL: 4.30756\tbleu: 25.21499\tLR: 0.00021000\t\r\n",
      "Steps: 198000\tLoss: 38160.57031\tPPL: 4.31957\tbleu: 25.16539\tLR: 0.00021000\t\r\n",
      "Steps: 199000\tLoss: 38017.49219\tPPL: 4.29594\tbleu: 25.43484\tLR: 0.00021000\t*\r\n",
      "Steps: 200000\tLoss: 37982.92578\tPPL: 4.29025\tbleu: 25.19321\tLR: 0.00021000\t*\r\n",
      "Steps: 201000\tLoss: 38074.82812\tPPL: 4.30539\tbleu: 25.09514\tLR: 0.00021000\t\r\n",
      "Steps: 202000\tLoss: 38016.60547\tPPL: 4.29579\tbleu: 25.77261\tLR: 0.00021000\t\r\n",
      "Steps: 203000\tLoss: 37956.78516\tPPL: 4.28595\tbleu: 26.02557\tLR: 0.00021000\t*\r\n",
      "Steps: 204000\tLoss: 38033.40625\tPPL: 4.29856\tbleu: 25.30841\tLR: 0.00021000\t\r\n",
      "Steps: 205000\tLoss: 37942.58984\tPPL: 4.28362\tbleu: 25.34179\tLR: 0.00021000\t*\r\n",
      "Steps: 206000\tLoss: 37963.04688\tPPL: 4.28698\tbleu: 25.23448\tLR: 0.00021000\t\r\n",
      "Steps: 207000\tLoss: 38020.93359\tPPL: 4.29651\tbleu: 25.27771\tLR: 0.00021000\t\r\n",
      "Steps: 208000\tLoss: 37940.99219\tPPL: 4.28336\tbleu: 25.38197\tLR: 0.00021000\t*\r\n",
      "Steps: 209000\tLoss: 37889.30078\tPPL: 4.27488\tbleu: 25.30438\tLR: 0.00021000\t*\r\n",
      "Steps: 210000\tLoss: 37865.97266\tPPL: 4.27105\tbleu: 25.18989\tLR: 0.00021000\t*\r\n",
      "Steps: 211000\tLoss: 38023.90625\tPPL: 4.29700\tbleu: 24.80337\tLR: 0.00021000\t\r\n",
      "Steps: 212000\tLoss: 37999.51953\tPPL: 4.29298\tbleu: 25.52267\tLR: 0.00021000\t\r\n",
      "Steps: 213000\tLoss: 37902.60547\tPPL: 4.27706\tbleu: 25.30063\tLR: 0.00021000\t\r\n",
      "Steps: 214000\tLoss: 37843.68359\tPPL: 4.26740\tbleu: 25.59574\tLR: 0.00021000\t*\r\n",
      "Steps: 215000\tLoss: 37817.71484\tPPL: 4.26316\tbleu: 25.63685\tLR: 0.00021000\t*\r\n",
      "Steps: 216000\tLoss: 37821.46094\tPPL: 4.26377\tbleu: 25.69784\tLR: 0.00021000\t\r\n",
      "Steps: 217000\tLoss: 37751.98047\tPPL: 4.25243\tbleu: 25.52260\tLR: 0.00021000\t*\r\n",
      "Steps: 218000\tLoss: 37836.71875\tPPL: 4.26627\tbleu: 25.10352\tLR: 0.00021000\t\r\n",
      "Steps: 219000\tLoss: 37833.86328\tPPL: 4.26580\tbleu: 25.44552\tLR: 0.00021000\t\r\n",
      "Steps: 220000\tLoss: 37812.90625\tPPL: 4.26237\tbleu: 25.70065\tLR: 0.00021000\t\r\n",
      "Steps: 221000\tLoss: 37815.27344\tPPL: 4.26276\tbleu: 25.50028\tLR: 0.00021000\t\r\n",
      "Steps: 222000\tLoss: 37727.88672\tPPL: 4.24850\tbleu: 25.53643\tLR: 0.00021000\t*\r\n",
      "Steps: 223000\tLoss: 37842.30469\tPPL: 4.26718\tbleu: 25.57224\tLR: 0.00021000\t\r\n",
      "Steps: 224000\tLoss: 37722.79688\tPPL: 4.24767\tbleu: 25.39376\tLR: 0.00021000\t*\r\n",
      "Steps: 225000\tLoss: 37871.88672\tPPL: 4.27202\tbleu: 25.80594\tLR: 0.00021000\t\r\n",
      "Steps: 226000\tLoss: 37771.59375\tPPL: 4.25563\tbleu: 25.94872\tLR: 0.00021000\t\r\n",
      "Steps: 227000\tLoss: 37692.67188\tPPL: 4.24277\tbleu: 25.67657\tLR: 0.00021000\t*\r\n",
      "Steps: 228000\tLoss: 37724.60156\tPPL: 4.24796\tbleu: 25.51654\tLR: 0.00021000\t\r\n",
      "Steps: 229000\tLoss: 37770.45312\tPPL: 4.25544\tbleu: 25.57260\tLR: 0.00021000\t\r\n",
      "Steps: 230000\tLoss: 37702.49609\tPPL: 4.24437\tbleu: 25.59541\tLR: 0.00021000\t\r\n",
      "Steps: 231000\tLoss: 37670.80078\tPPL: 4.23921\tbleu: 25.39550\tLR: 0.00021000\t*\r\n",
      "Steps: 232000\tLoss: 37724.08984\tPPL: 4.24788\tbleu: 25.57189\tLR: 0.00021000\t\r\n",
      "Steps: 233000\tLoss: 37814.49609\tPPL: 4.26263\tbleu: 25.27768\tLR: 0.00021000\t\r\n",
      "Steps: 234000\tLoss: 37659.94531\tPPL: 4.23745\tbleu: 25.37481\tLR: 0.00021000\t*\r\n",
      "Steps: 235000\tLoss: 37660.64844\tPPL: 4.23756\tbleu: 25.60212\tLR: 0.00021000\t\r\n",
      "Steps: 236000\tLoss: 37697.83203\tPPL: 4.24361\tbleu: 25.60651\tLR: 0.00021000\t\r\n",
      "Steps: 237000\tLoss: 37634.68750\tPPL: 4.23335\tbleu: 25.39906\tLR: 0.00021000\t*\r\n",
      "Steps: 238000\tLoss: 37526.92188\tPPL: 4.21589\tbleu: 25.72407\tLR: 0.00021000\t*\r\n",
      "Steps: 239000\tLoss: 37695.78125\tPPL: 4.24327\tbleu: 25.87622\tLR: 0.00021000\t\r\n",
      "Steps: 240000\tLoss: 37621.14844\tPPL: 4.23115\tbleu: 25.73335\tLR: 0.00021000\t\r\n",
      "Steps: 241000\tLoss: 37523.16797\tPPL: 4.21528\tbleu: 25.71153\tLR: 0.00021000\t*\r\n",
      "Steps: 242000\tLoss: 37669.21484\tPPL: 4.23895\tbleu: 25.37726\tLR: 0.00021000\t\r\n",
      "Steps: 243000\tLoss: 37675.76953\tPPL: 4.24002\tbleu: 25.64237\tLR: 0.00021000\t\r\n",
      "Steps: 244000\tLoss: 37651.60938\tPPL: 4.23609\tbleu: 26.00652\tLR: 0.00021000\t\r\n",
      "Steps: 245000\tLoss: 37556.82031\tPPL: 4.22073\tbleu: 25.51997\tLR: 0.00021000\t\r\n",
      "Steps: 246000\tLoss: 37499.15234\tPPL: 4.21140\tbleu: 25.88419\tLR: 0.00021000\t*\r\n",
      "Steps: 247000\tLoss: 37545.07812\tPPL: 4.21883\tbleu: 25.43764\tLR: 0.00021000\t\r\n",
      "Steps: 248000\tLoss: 37536.69531\tPPL: 4.21747\tbleu: 25.46249\tLR: 0.00021000\t\r\n",
      "Steps: 249000\tLoss: 37451.72656\tPPL: 4.20375\tbleu: 25.44855\tLR: 0.00021000\t*\r\n",
      "Steps: 250000\tLoss: 37432.56641\tPPL: 4.20066\tbleu: 25.67750\tLR: 0.00021000\t*\r\n",
      "Steps: 251000\tLoss: 37463.46484\tPPL: 4.20564\tbleu: 25.77836\tLR: 0.00021000\t\r\n",
      "Steps: 252000\tLoss: 37413.18359\tPPL: 4.19754\tbleu: 25.82808\tLR: 0.00021000\t*\r\n",
      "Steps: 253000\tLoss: 37449.60938\tPPL: 4.20341\tbleu: 25.46119\tLR: 0.00021000\t\r\n",
      "Steps: 254000\tLoss: 37523.71484\tPPL: 4.21537\tbleu: 25.47830\tLR: 0.00021000\t\r\n",
      "Steps: 255000\tLoss: 37528.75781\tPPL: 4.21619\tbleu: 25.32843\tLR: 0.00021000\t\r\n",
      "Steps: 256000\tLoss: 37413.21875\tPPL: 4.19755\tbleu: 25.41581\tLR: 0.00021000\t\r\n",
      "Steps: 257000\tLoss: 37523.89844\tPPL: 4.21540\tbleu: 25.54990\tLR: 0.00021000\t\r\n",
      "Steps: 258000\tLoss: 37450.37891\tPPL: 4.20353\tbleu: 25.57636\tLR: 0.00014700\t\r\n",
      "Steps: 259000\tLoss: 37343.07422\tPPL: 4.18628\tbleu: 25.49683\tLR: 0.00014700\t*\r\n",
      "Steps: 260000\tLoss: 37324.61328\tPPL: 4.18331\tbleu: 25.43494\tLR: 0.00014700\t*\r\n",
      "Steps: 261000\tLoss: 37309.24219\tPPL: 4.18085\tbleu: 25.51379\tLR: 0.00014700\t*\r\n",
      "Steps: 262000\tLoss: 37312.06641\tPPL: 4.18130\tbleu: 25.72165\tLR: 0.00014700\t\r\n",
      "Steps: 263000\tLoss: 37219.73047\tPPL: 4.16652\tbleu: 25.69753\tLR: 0.00014700\t*\r\n",
      "Steps: 264000\tLoss: 37193.00781\tPPL: 4.16226\tbleu: 25.75202\tLR: 0.00014700\t*\r\n",
      "Steps: 265000\tLoss: 37162.17578\tPPL: 4.15734\tbleu: 25.84220\tLR: 0.00014700\t*\r\n",
      "Steps: 266000\tLoss: 37253.67969\tPPL: 4.17195\tbleu: 25.78585\tLR: 0.00014700\t\r\n",
      "Steps: 267000\tLoss: 37250.19531\tPPL: 4.17139\tbleu: 25.94245\tLR: 0.00014700\t\r\n",
      "Steps: 268000\tLoss: 37314.25391\tPPL: 4.18165\tbleu: 25.65317\tLR: 0.00014700\t\r\n",
      "Steps: 269000\tLoss: 37204.30859\tPPL: 4.16406\tbleu: 25.92737\tLR: 0.00014700\t\r\n",
      "Steps: 270000\tLoss: 37158.15234\tPPL: 4.15670\tbleu: 25.48107\tLR: 0.00014700\t*\r\n",
      "Steps: 271000\tLoss: 37141.62500\tPPL: 4.15407\tbleu: 25.45889\tLR: 0.00014700\t*\r\n",
      "Steps: 272000\tLoss: 37141.87891\tPPL: 4.15411\tbleu: 25.54128\tLR: 0.00014700\t\r\n",
      "Steps: 273000\tLoss: 37172.92188\tPPL: 4.15905\tbleu: 25.41002\tLR: 0.00014700\t\r\n",
      "Steps: 274000\tLoss: 37127.59375\tPPL: 4.15183\tbleu: 25.74373\tLR: 0.00014700\t*\r\n",
      "Steps: 275000\tLoss: 37145.99219\tPPL: 4.15476\tbleu: 25.78832\tLR: 0.00014700\t\r\n",
      "Steps: 276000\tLoss: 37175.78516\tPPL: 4.15951\tbleu: 25.92894\tLR: 0.00014700\t\r\n",
      "Steps: 277000\tLoss: 37051.82031\tPPL: 4.13979\tbleu: 25.85361\tLR: 0.00014700\t*\r\n",
      "Steps: 278000\tLoss: 37125.60938\tPPL: 4.15152\tbleu: 25.67788\tLR: 0.00014700\t\r\n",
      "Steps: 279000\tLoss: 37140.47266\tPPL: 4.15388\tbleu: 25.47202\tLR: 0.00014700\t\r\n",
      "Steps: 280000\tLoss: 37050.26953\tPPL: 4.13954\tbleu: 25.38311\tLR: 0.00014700\t*\r\n",
      "Steps: 281000\tLoss: 37091.80859\tPPL: 4.14614\tbleu: 26.16863\tLR: 0.00014700\t\r\n",
      "Steps: 282000\tLoss: 37114.80078\tPPL: 4.14980\tbleu: 25.72734\tLR: 0.00014700\t\r\n",
      "Steps: 283000\tLoss: 37117.13281\tPPL: 4.15017\tbleu: 25.95258\tLR: 0.00014700\t\r\n",
      "Steps: 284000\tLoss: 37022.66797\tPPL: 4.13516\tbleu: 25.65332\tLR: 0.00014700\t*\r\n",
      "Steps: 285000\tLoss: 37009.03125\tPPL: 4.13300\tbleu: 25.76521\tLR: 0.00014700\t*\r\n",
      "Steps: 286000\tLoss: 37025.71094\tPPL: 4.13564\tbleu: 25.92134\tLR: 0.00014700\t\r\n",
      "Steps: 287000\tLoss: 37055.04688\tPPL: 4.14030\tbleu: 25.79829\tLR: 0.00014700\t\r\n",
      "Steps: 288000\tLoss: 37085.97266\tPPL: 4.14521\tbleu: 25.44130\tLR: 0.00014700\t\r\n",
      "Steps: 289000\tLoss: 37097.08594\tPPL: 4.14698\tbleu: 25.59894\tLR: 0.00014700\t\r\n",
      "Steps: 290000\tLoss: 37006.37500\tPPL: 4.13258\tbleu: 25.28597\tLR: 0.00014700\t*\r\n",
      "Steps: 291000\tLoss: 37046.75000\tPPL: 4.13898\tbleu: 26.16360\tLR: 0.00014700\t\r\n",
      "Steps: 292000\tLoss: 36936.73828\tPPL: 4.12156\tbleu: 25.87446\tLR: 0.00014700\t*\r\n",
      "Steps: 293000\tLoss: 36993.19141\tPPL: 4.13049\tbleu: 25.52042\tLR: 0.00014700\t\r\n",
      "Steps: 294000\tLoss: 37010.67188\tPPL: 4.13326\tbleu: 25.65068\tLR: 0.00014700\t\r\n",
      "Steps: 295000\tLoss: 37017.54688\tPPL: 4.13435\tbleu: 25.50772\tLR: 0.00014700\t\r\n",
      "Steps: 296000\tLoss: 37003.75391\tPPL: 4.13216\tbleu: 25.93151\tLR: 0.00014700\t\r\n",
      "Steps: 297000\tLoss: 36973.04297\tPPL: 4.12730\tbleu: 25.58332\tLR: 0.00014700\t\r\n",
      "Steps: 298000\tLoss: 36969.85938\tPPL: 4.12680\tbleu: 25.59412\tLR: 0.00010290\t\r\n",
      "Steps: 299000\tLoss: 36896.74609\tPPL: 4.11524\tbleu: 25.80043\tLR: 0.00010290\t*\r\n",
      "Steps: 300000\tLoss: 36879.19922\tPPL: 4.11248\tbleu: 25.84867\tLR: 0.00010290\t*\r\n",
      "Steps: 301000\tLoss: 36855.51953\tPPL: 4.10874\tbleu: 25.96104\tLR: 0.00010290\t*\r\n",
      "Steps: 302000\tLoss: 36791.17578\tPPL: 4.09862\tbleu: 26.02235\tLR: 0.00010290\t*\r\n",
      "Steps: 303000\tLoss: 36760.48828\tPPL: 4.09380\tbleu: 25.51072\tLR: 0.00010290\t*\r\n",
      "Steps: 304000\tLoss: 36776.59375\tPPL: 4.09633\tbleu: 25.81774\tLR: 0.00010290\t\r\n",
      "Steps: 305000\tLoss: 36797.21094\tPPL: 4.09957\tbleu: 25.83430\tLR: 0.00010290\t\r\n",
      "Steps: 306000\tLoss: 36784.70312\tPPL: 4.09760\tbleu: 25.68782\tLR: 0.00010290\t\r\n",
      "Steps: 307000\tLoss: 36788.43750\tPPL: 4.09819\tbleu: 25.98448\tLR: 0.00010290\t\r\n",
      "Steps: 308000\tLoss: 36842.66797\tPPL: 4.10672\tbleu: 25.65559\tLR: 0.00010290\t\r\n",
      "Steps: 309000\tLoss: 36827.51562\tPPL: 4.10434\tbleu: 25.91949\tLR: 0.00007203\t\r\n",
      "Steps: 310000\tLoss: 36703.05078\tPPL: 4.08480\tbleu: 26.13411\tLR: 0.00007203\t*\r\n",
      "Steps: 311000\tLoss: 36705.45703\tPPL: 4.08517\tbleu: 26.09818\tLR: 0.00007203\t\r\n",
      "Steps: 312000\tLoss: 36699.12500\tPPL: 4.08418\tbleu: 26.16370\tLR: 0.00007203\t*\r\n",
      "Steps: 313000\tLoss: 36686.39062\tPPL: 4.08219\tbleu: 25.95801\tLR: 0.00007203\t*\r\n",
      "Steps: 314000\tLoss: 36661.12109\tPPL: 4.07823\tbleu: 26.08803\tLR: 0.00007203\t*\r\n",
      "Steps: 315000\tLoss: 36654.57422\tPPL: 4.07721\tbleu: 26.16156\tLR: 0.00007203\t*\r\n",
      "Steps: 316000\tLoss: 36689.62109\tPPL: 4.08269\tbleu: 25.80715\tLR: 0.00007203\t\r\n",
      "Steps: 317000\tLoss: 36683.74609\tPPL: 4.08177\tbleu: 26.14141\tLR: 0.00007203\t\r\n",
      "Steps: 318000\tLoss: 36638.37109\tPPL: 4.07468\tbleu: 26.24987\tLR: 0.00007203\t*\r\n",
      "Steps: 319000\tLoss: 36630.06250\tPPL: 4.07338\tbleu: 26.13314\tLR: 0.00007203\t*\r\n",
      "Steps: 320000\tLoss: 36659.22266\tPPL: 4.07794\tbleu: 26.20105\tLR: 0.00007203\t\r\n",
      "Steps: 321000\tLoss: 36680.90234\tPPL: 4.08133\tbleu: 25.90967\tLR: 0.00007203\t\r\n",
      "Steps: 322000\tLoss: 36652.36328\tPPL: 4.07686\tbleu: 26.06344\tLR: 0.00007203\t\r\n",
      "Steps: 323000\tLoss: 36628.85547\tPPL: 4.07319\tbleu: 26.41735\tLR: 0.00007203\t*\r\n",
      "Steps: 324000\tLoss: 36661.19531\tPPL: 4.07825\tbleu: 26.27573\tLR: 0.00007203\t\r\n",
      "Steps: 325000\tLoss: 36650.85156\tPPL: 4.07663\tbleu: 26.21061\tLR: 0.00007203\t\r\n",
      "Steps: 326000\tLoss: 36562.79688\tPPL: 4.06289\tbleu: 26.05663\tLR: 0.00007203\t*\r\n",
      "Steps: 327000\tLoss: 36654.52344\tPPL: 4.07720\tbleu: 26.33627\tLR: 0.00007203\t\r\n",
      "Steps: 328000\tLoss: 36548.41406\tPPL: 4.06065\tbleu: 26.37135\tLR: 0.00007203\t*\r\n",
      "Steps: 329000\tLoss: 36638.36328\tPPL: 4.07468\tbleu: 26.24693\tLR: 0.00007203\t\r\n",
      "Steps: 330000\tLoss: 36661.63281\tPPL: 4.07831\tbleu: 26.12458\tLR: 0.00007203\t\r\n",
      "Steps: 331000\tLoss: 36612.80469\tPPL: 4.07068\tbleu: 25.93970\tLR: 0.00007203\t\r\n",
      "Steps: 332000\tLoss: 36565.21484\tPPL: 4.06326\tbleu: 26.01312\tLR: 0.00007203\t\r\n",
      "Steps: 333000\tLoss: 36556.73047\tPPL: 4.06194\tbleu: 26.25776\tLR: 0.00007203\t\r\n",
      "Steps: 334000\tLoss: 36571.25781\tPPL: 4.06421\tbleu: 26.12196\tLR: 0.00005042\t\r\n",
      "Steps: 335000\tLoss: 36551.07422\tPPL: 4.06106\tbleu: 26.39055\tLR: 0.00005042\t\r\n",
      "Steps: 336000\tLoss: 36534.69531\tPPL: 4.05851\tbleu: 26.26003\tLR: 0.00005042\t*\r\n",
      "Steps: 337000\tLoss: 36545.08203\tPPL: 4.06013\tbleu: 26.21381\tLR: 0.00005042\t\r\n",
      "Steps: 338000\tLoss: 36508.16016\tPPL: 4.05439\tbleu: 26.36664\tLR: 0.00005042\t*\r\n",
      "Steps: 339000\tLoss: 36491.43359\tPPL: 4.05179\tbleu: 26.00613\tLR: 0.00005042\t*\r\n",
      "Steps: 340000\tLoss: 36485.81250\tPPL: 4.05091\tbleu: 26.01383\tLR: 0.00005042\t*\r\n"
     ]
    }
   ],
   "source": [
    "! cat models/${src}${tgt}_transformer/validations.txt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:541: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint8 = np.dtype([(\"qint8\", np.int8, 1)])\n",
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:542: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint8 = np.dtype([(\"quint8\", np.uint8, 1)])\n",
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:543: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint16 = np.dtype([(\"qint16\", np.int16, 1)])\n",
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:544: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_quint16 = np.dtype([(\"quint16\", np.uint16, 1)])\n",
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:545: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  _np_qint32 = np.dtype([(\"qint32\", np.int32, 1)])\n",
      "/home/espoir_mur_gmail_com/.local/lib/python3.6/site-packages/tensorboard/compat/tensorflow_stub/dtypes.py:550: FutureWarning: Passing (type, 1) or '1type' as a synonym of type is deprecated; in a future version of numpy, it will be understood as (type, (1,)) / '(1,)type'.\n",
      "  np_resource = np.dtype([(\"resource\", np.ubyte, 1)])\n",
      "2020-02-19 07:58:26,696 -  dev bleu:  26.41 [Beam search decoding with beam size = 5 and alpha = 1.0]\n",
      "2020-02-19 07:59:52,231 - test bleu:  39.81 [Beam search decoding with beam size = 5 and alpha = 1.0]\n"
     ]
    }
   ],
   "source": [
    "!python3 -m joeynmt test config/transformer_$src$tgt.yaml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "Save the results to the folder"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}