Baseline1.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "QfCbUjWSgMTJ"
   },
   "source": [
    "## Zimnat Insurance Recommendation Challenge\n",
    "Can you predict which insurance products existing clients will want next?\n",
    "### Baseline with catboost"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "82PpxfmqglcE"
   },
   "source": [
    "### Get data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "3arOHSJwCtNq"
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "from tqdm import tqdm\n",
    "import copy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "s3ZCXtzKDiDe"
   },
   "outputs": [],
   "source": [
    "train = pd.read_csv('Train.csv')\n",
    "test = pd.read_csv('Test.csv')\n",
    "submission = pd.read_csv('SampleSubmission.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "o_ELVeoVgv3v"
   },
   "source": [
    "### New format"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "oxjj_QAfEyZw"
   },
   "outputs": [],
   "source": [
    "X_train = []\n",
    "X_train_columns = train.columns\n",
    "c = 0\n",
    "for v in train.values:\n",
    "  info = v[:8]\n",
    "  binary = v[8:]\n",
    "  index = [k for k, i in enumerate(binary) if i == 1]\n",
    "  for i in index:\n",
    "    c+=1\n",
    "    for k in range(len(binary)):\n",
    "      if k == i:\n",
    "        binary_transformed = list(copy.copy(binary))\n",
    "        binary_transformed[i] = 0\n",
    "        X_train.append(list(info) + binary_transformed + [X_train_columns[8+k]] + [c])\n",
    "\n",
    "X_train = pd.DataFrame(X_train)\n",
    "X_train.columns = ['ID', 'join_date', 'sex', 'marital_status', 'birth_year', 'branch_code',\n",
    "       'occupation_code', 'occupation_category_code', 'P5DA', 'RIBP', '8NN1',\n",
    "       '7POT', '66FJ', 'GYSR', 'SOP4', 'RVSZ', 'PYUQ', 'LJR9', 'N2MW', 'AHXO',\n",
    "       'BSTQ', 'FM3X', 'K6QO', 'QBOL', 'JWFN', 'JZ9D', 'J9JW', 'GHYX', 'ECY3', 'product_pred', 'ID2']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "URdSMgJeOnLE"
   },
   "outputs": [],
   "source": [
    "X_test = []\n",
    "true_values = []\n",
    "c = 0\n",
    "for v in test.values:\n",
    "  c += 1\n",
    "  info = v[:8]\n",
    "  binary = v[8:]\n",
    "  index = [k for k, i in enumerate(binary) if i == 1]\n",
    "  X_test.append(list(info) + list(binary) + [c])\n",
    "  for k in test.columns[8:][index]:\n",
    "    true_values.append(v[0] + ' X ' + k)\n",
    "\n",
    "X_test = pd.DataFrame(X_test)\n",
    "X_test.columns = ['ID', 'join_date', 'sex', 'marital_status', 'birth_year', 'branch_code',\n",
    "       'occupation_code', 'occupation_category_code', 'P5DA', 'RIBP', '8NN1',\n",
    "       '7POT', '66FJ', 'GYSR', 'SOP4', 'RVSZ', 'PYUQ', 'LJR9', 'N2MW', 'AHXO',\n",
    "       'BSTQ', 'FM3X', 'K6QO', 'QBOL', 'JWFN', 'JZ9D', 'J9JW', 'GHYX', 'ECY3', 'ID2']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "s1KcI9I6g1de"
   },
   "source": [
    "### Transform data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "ttUKNdnAczTd"
   },
   "outputs": [],
   "source": [
    "features_train = []\n",
    "features_test = []\n",
    "columns = []\n",
    "\n",
    "append_features = ['P5DA', 'RIBP', '8NN1', '7POT', '66FJ', 'GYSR', 'SOP4', 'RVSZ', 'PYUQ', 'LJR9', \n",
    "'N2MW', 'AHXO','BSTQ', 'FM3X', 'K6QO', 'QBOL', 'JWFN', 'JZ9D', 'J9JW', 'GHYX', \n",
    "'ECY3', 'ID', 'ID2', 'join_date', 'sex', 'marital_status', 'branch_code', 'occupation_code', 'occupation_category_code',\n",
    "'birth_year']\n",
    "for v in append_features:\n",
    "  features_train.append(X_train[v].values.reshape(-1, 1))\n",
    "  features_test.append(X_test[v].values.reshape(-1, 1))\n",
    "  columns.append(np.array([v]))\n",
    "\n",
    "y_train = X_train[['product_pred']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "kWCK5LrfkPp-"
   },
   "outputs": [],
   "source": [
    "features_train = np.concatenate(features_train, axis=1)\n",
    "features_test = np.concatenate(features_test, axis=1)\n",
    "columns = np.concatenate(np.array(columns))\n",
    "\n",
    "X_train = pd.DataFrame(features_train)\n",
    "X_train.columns = columns\n",
    "X_test = pd.DataFrame(features_test)\n",
    "X_test.columns = columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "YVUKKo3llI0y"
   },
   "source": [
    "### New features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "NhfA7yullH76"
   },
   "outputs": [],
   "source": [
    "X_train['date1'] = X_train['join_date'].apply(lambda x: int(x.split('/')[0]) if (x == x) else np.nan)\n",
    "X_train['date2'] = X_train['join_date'].apply(lambda x: int(x.split('/')[1]) if (x == x) else np.nan)\n",
    "X_train['date3'] = X_train['join_date'].apply(lambda x: int(x.split('/')[2]) if (x == x) else np.nan)\n",
    "X_train.drop('join_date', axis=1, inplace=True)\n",
    "\n",
    "X_test['date1'] = X_test['join_date'].apply(lambda x: int(x.split('/')[0]) if (x == x) else np.nan)\n",
    "X_test['date2'] = X_test['join_date'].apply(lambda x: int(x.split('/')[1]) if (x == x) else np.nan)\n",
    "X_test['date3'] = X_test['join_date'].apply(lambda x: int(x.split('/')[2]) if (x == x) else np.nan)\n",
    "X_test.drop('join_date', axis=1, inplace=True)\n",
    "\n",
    "X_train['date_diff'] = X_train['date3'] - X_train['birth_year']\n",
    "X_test['date_diff'] = X_test['date3'] - X_test['birth_year']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "GDTy7qyulLoP"
   },
   "source": [
    "### Change types"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "YFf8xSoc3kN4"
   },
   "outputs": [],
   "source": [
    "X_train = X_train.fillna(0)\n",
    "X_test = X_test.fillna(0)\n",
    "y_train = y_train.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "mTCyVmQjS9nv"
   },
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "le = LabelEncoder()\n",
    "data = X_train.append(X_test)\n",
    "for v in ['sex', 'marital_status', 'branch_code', 'occupation_code', 'occupation_category_code',]:\n",
    "  data.loc[:,v] = le.fit_transform(data.loc[:,v])\n",
    "X_train = data[:X_train.shape[0]]\n",
    "X_test = data[-X_test.shape[0]:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "OtwJsy7ZnIuO"
   },
   "outputs": [],
   "source": [
    "le.fit(y_train.iloc[:,0])\n",
    "y_train = pd.DataFrame(le.transform(y_train.iloc[:,0]))\n",
    "y_train.columns = ['target']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "qn9zHq0iqhA3"
   },
   "source": [
    "### Model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "colab_type": "code",
    "id": "kANA1SPmgfS6",
    "outputId": "78dc5019-8af1-444e-9c3e-2874c532577f"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Learning rate set to 0.098003\n",
      "0:\tlearn: 1.7837255\ttotal: 9.4s\tremaining: 2h 36m 27s\n",
      "1:\tlearn: 1.5780548\ttotal: 18.5s\tremaining: 2h 33m 46s\n",
      "2:\tlearn: 1.4111625\ttotal: 27.9s\tremaining: 2h 34m 40s\n",
      "3:\tlearn: 1.3028152\ttotal: 33.4s\tremaining: 2h 18m 36s\n",
      "4:\tlearn: 1.1926574\ttotal: 43.4s\tremaining: 2h 24m 4s\n",
      "5:\tlearn: 1.1052790\ttotal: 52.9s\tremaining: 2h 25m 58s\n",
      "6:\tlearn: 1.0376100\ttotal: 1m 2s\tremaining: 2h 28m 3s\n",
      "7:\tlearn: 0.9787207\ttotal: 1m 12s\tremaining: 2h 29m 44s\n",
      "8:\tlearn: 0.9277719\ttotal: 1m 22s\tremaining: 2h 30m 56s\n",
      "9:\tlearn: 0.8868196\ttotal: 1m 32s\tremaining: 2h 33m 3s\n",
      "10:\tlearn: 0.8507237\ttotal: 1m 42s\tremaining: 2h 33m 33s\n",
      "11:\tlearn: 0.8163409\ttotal: 1m 52s\tremaining: 2h 34m 48s\n",
      "12:\tlearn: 0.7856310\ttotal: 2m 2s\tremaining: 2h 34m 50s\n",
      "13:\tlearn: 0.7592917\ttotal: 2m 11s\tremaining: 2h 34m 22s\n",
      "14:\tlearn: 0.7338182\ttotal: 2m 20s\tremaining: 2h 33m 48s\n",
      "15:\tlearn: 0.7121350\ttotal: 2m 29s\tremaining: 2h 33m 22s\n",
      "16:\tlearn: 0.6930758\ttotal: 2m 38s\tremaining: 2h 32m 58s\n",
      "17:\tlearn: 0.6747357\ttotal: 2m 48s\tremaining: 2h 33m 16s\n",
      "18:\tlearn: 0.6597251\ttotal: 2m 57s\tremaining: 2h 33m\n",
      "19:\tlearn: 0.6451517\ttotal: 3m 6s\tremaining: 2h 32m 37s\n",
      "20:\tlearn: 0.6320649\ttotal: 3m 16s\tremaining: 2h 33m 2s\n",
      "21:\tlearn: 0.6202183\ttotal: 3m 26s\tremaining: 2h 33m 13s\n",
      "22:\tlearn: 0.6100344\ttotal: 3m 36s\tremaining: 2h 33m 5s\n",
      "23:\tlearn: 0.6000709\ttotal: 3m 45s\tremaining: 2h 33m 8s\n",
      "24:\tlearn: 0.5904606\ttotal: 3m 55s\tremaining: 2h 33m 19s\n",
      "25:\tlearn: 0.5832686\ttotal: 4m 6s\tremaining: 2h 34m 10s\n",
      "26:\tlearn: 0.5752092\ttotal: 4m 18s\tremaining: 2h 35m\n",
      "27:\tlearn: 0.5647953\ttotal: 4m 26s\tremaining: 2h 34m 25s\n",
      "28:\tlearn: 0.5580123\ttotal: 4m 36s\tremaining: 2h 34m 8s\n",
      "29:\tlearn: 0.5522947\ttotal: 4m 48s\tremaining: 2h 35m 35s\n",
      "30:\tlearn: 0.5464298\ttotal: 5m 1s\tremaining: 2h 37m 15s\n",
      "31:\tlearn: 0.5411205\ttotal: 5m 12s\tremaining: 2h 37m 44s\n",
      "32:\tlearn: 0.5364359\ttotal: 5m 24s\tremaining: 2h 38m 17s\n",
      "33:\tlearn: 0.5304899\ttotal: 5m 32s\tremaining: 2h 37m 39s\n",
      "34:\tlearn: 0.5255948\ttotal: 5m 41s\tremaining: 2h 37m\n",
      "35:\tlearn: 0.5212768\ttotal: 5m 50s\tremaining: 2h 36m 31s\n",
      "36:\tlearn: 0.5175026\ttotal: 6m\tremaining: 2h 36m 33s\n",
      "37:\tlearn: 0.5132375\ttotal: 6m 9s\tremaining: 2h 35m 58s\n",
      "38:\tlearn: 0.5108200\ttotal: 6m 21s\tremaining: 2h 36m 35s\n",
      "39:\tlearn: 0.5081632\ttotal: 6m 32s\tremaining: 2h 37m 7s\n",
      "40:\tlearn: 0.5045514\ttotal: 6m 41s\tremaining: 2h 36m 38s\n",
      "41:\tlearn: 0.5031586\ttotal: 6m 53s\tremaining: 2h 37m 11s\n",
      "42:\tlearn: 0.5000692\ttotal: 7m 5s\tremaining: 2h 37m 45s\n",
      "43:\tlearn: 0.4971258\ttotal: 7m 16s\tremaining: 2h 38m 13s\n",
      "44:\tlearn: 0.4947079\ttotal: 7m 28s\tremaining: 2h 38m 30s\n",
      "45:\tlearn: 0.4918424\ttotal: 7m 38s\tremaining: 2h 38m 22s\n",
      "46:\tlearn: 0.4895121\ttotal: 7m 47s\tremaining: 2h 38m 3s\n",
      "47:\tlearn: 0.4878115\ttotal: 7m 58s\tremaining: 2h 38m 2s\n",
      "48:\tlearn: 0.4850263\ttotal: 8m 9s\tremaining: 2h 38m 13s\n",
      "49:\tlearn: 0.4831846\ttotal: 8m 20s\tremaining: 2h 38m 36s\n",
      "50:\tlearn: 0.4806554\ttotal: 8m 32s\tremaining: 2h 38m 57s\n",
      "51:\tlearn: 0.4783515\ttotal: 8m 43s\tremaining: 2h 39m 7s\n",
      "52:\tlearn: 0.4767030\ttotal: 8m 53s\tremaining: 2h 38m 56s\n",
      "53:\tlearn: 0.4742118\ttotal: 9m 4s\tremaining: 2h 38m 52s\n",
      "54:\tlearn: 0.4718015\ttotal: 9m 14s\tremaining: 2h 38m 51s\n",
      "55:\tlearn: 0.4699631\ttotal: 9m 23s\tremaining: 2h 38m 23s\n",
      "56:\tlearn: 0.4682218\ttotal: 9m 34s\tremaining: 2h 38m 28s\n",
      "57:\tlearn: 0.4656518\ttotal: 9m 45s\tremaining: 2h 38m 28s\n",
      "58:\tlearn: 0.4641134\ttotal: 9m 55s\tremaining: 2h 38m 24s\n",
      "59:\tlearn: 0.4619079\ttotal: 10m 7s\tremaining: 2h 38m 35s\n",
      "60:\tlearn: 0.4603404\ttotal: 10m 18s\tremaining: 2h 38m 41s\n",
      "61:\tlearn: 0.4590167\ttotal: 10m 27s\tremaining: 2h 38m 20s\n",
      "62:\tlearn: 0.4580077\ttotal: 10m 39s\tremaining: 2h 38m 34s\n",
      "63:\tlearn: 0.4553096\ttotal: 10m 48s\tremaining: 2h 38m 5s\n",
      "64:\tlearn: 0.4536051\ttotal: 10m 59s\tremaining: 2h 38m 8s\n",
      "65:\tlearn: 0.4528149\ttotal: 11m 11s\tremaining: 2h 38m 27s\n",
      "66:\tlearn: 0.4515903\ttotal: 11m 22s\tremaining: 2h 38m 19s\n",
      "67:\tlearn: 0.4502990\ttotal: 11m 32s\tremaining: 2h 38m 7s\n",
      "68:\tlearn: 0.4496116\ttotal: 11m 43s\tremaining: 2h 38m 18s\n",
      "69:\tlearn: 0.4485016\ttotal: 11m 55s\tremaining: 2h 38m 32s\n",
      "70:\tlearn: 0.4472330\ttotal: 12m 8s\tremaining: 2h 38m 50s\n",
      "71:\tlearn: 0.4463449\ttotal: 12m 20s\tremaining: 2h 39m\n",
      "72:\tlearn: 0.4449483\ttotal: 12m 31s\tremaining: 2h 39m\n",
      "73:\tlearn: 0.4438004\ttotal: 12m 41s\tremaining: 2h 38m 51s\n",
      "74:\tlearn: 0.4426364\ttotal: 12m 53s\tremaining: 2h 39m 4s\n",
      "75:\tlearn: 0.4417228\ttotal: 13m 5s\tremaining: 2h 39m 5s\n",
      "76:\tlearn: 0.4403898\ttotal: 13m 15s\tremaining: 2h 38m 52s\n",
      "77:\tlearn: 0.4393742\ttotal: 13m 28s\tremaining: 2h 39m 18s\n",
      "78:\tlearn: 0.4385876\ttotal: 13m 39s\tremaining: 2h 39m 18s\n",
      "79:\tlearn: 0.4375723\ttotal: 13m 50s\tremaining: 2h 39m 5s\n",
      "80:\tlearn: 0.4365698\ttotal: 14m\tremaining: 2h 38m 56s\n",
      "81:\tlearn: 0.4357098\ttotal: 14m 14s\tremaining: 2h 39m 21s\n",
      "82:\tlearn: 0.4350620\ttotal: 14m 26s\tremaining: 2h 39m 32s\n",
      "83:\tlearn: 0.4343343\ttotal: 14m 37s\tremaining: 2h 39m 33s\n",
      "84:\tlearn: 0.4337311\ttotal: 14m 51s\tremaining: 2h 39m 54s\n",
      "85:\tlearn: 0.4333818\ttotal: 15m 5s\tremaining: 2h 40m 21s\n",
      "86:\tlearn: 0.4328587\ttotal: 15m 19s\tremaining: 2h 40m 48s\n",
      "87:\tlearn: 0.4320780\ttotal: 15m 30s\tremaining: 2h 40m 41s\n",
      "88:\tlearn: 0.4302352\ttotal: 15m 39s\tremaining: 2h 40m 20s\n",
      "89:\tlearn: 0.4293915\ttotal: 15m 51s\tremaining: 2h 40m 20s\n",
      "90:\tlearn: 0.4280966\ttotal: 16m 2s\tremaining: 2h 40m 14s\n",
      "91:\tlearn: 0.4274178\ttotal: 16m 12s\tremaining: 2h 39m 53s\n",
      "92:\tlearn: 0.4267133\ttotal: 16m 23s\tremaining: 2h 39m 54s\n",
      "93:\tlearn: 0.4261618\ttotal: 16m 34s\tremaining: 2h 39m 43s\n",
      "94:\tlearn: 0.4259969\ttotal: 16m 47s\tremaining: 2h 39m 53s\n",
      "95:\tlearn: 0.4255187\ttotal: 17m\tremaining: 2h 40m 12s\n",
      "96:\tlearn: 0.4250529\ttotal: 17m 13s\tremaining: 2h 40m 20s\n",
      "97:\tlearn: 0.4247380\ttotal: 17m 24s\tremaining: 2h 40m 13s\n",
      "98:\tlearn: 0.4237646\ttotal: 17m 35s\tremaining: 2h 40m 6s\n",
      "99:\tlearn: 0.4230192\ttotal: 17m 45s\tremaining: 2h 39m 53s\n",
      "100:\tlearn: 0.4224524\ttotal: 17m 57s\tremaining: 2h 39m 52s\n",
      "101:\tlearn: 0.4218255\ttotal: 18m 9s\tremaining: 2h 39m 51s\n",
      "102:\tlearn: 0.4215002\ttotal: 18m 19s\tremaining: 2h 39m 31s\n",
      "103:\tlearn: 0.4208977\ttotal: 18m 31s\tremaining: 2h 39m 34s\n",
      "104:\tlearn: 0.4197402\ttotal: 18m 40s\tremaining: 2h 39m 13s\n",
      "105:\tlearn: 0.4192934\ttotal: 18m 53s\tremaining: 2h 39m 22s\n",
      "106:\tlearn: 0.4189210\ttotal: 19m 6s\tremaining: 2h 39m 28s\n",
      "107:\tlearn: 0.4184323\ttotal: 19m 19s\tremaining: 2h 39m 37s\n",
      "108:\tlearn: 0.4174847\ttotal: 19m 28s\tremaining: 2h 39m 12s\n",
      "109:\tlearn: 0.4171153\ttotal: 19m 39s\tremaining: 2h 39m 4s\n",
      "110:\tlearn: 0.4159795\ttotal: 19m 50s\tremaining: 2h 38m 50s\n",
      "111:\tlearn: 0.4152417\ttotal: 20m\tremaining: 2h 38m 38s\n",
      "112:\tlearn: 0.4148281\ttotal: 20m 10s\tremaining: 2h 38m 24s\n",
      "113:\tlearn: 0.4141247\ttotal: 20m 23s\tremaining: 2h 38m 28s\n",
      "114:\tlearn: 0.4130464\ttotal: 20m 35s\tremaining: 2h 38m 26s\n",
      "115:\tlearn: 0.4117081\ttotal: 20m 44s\tremaining: 2h 38m 1s\n",
      "116:\tlearn: 0.4106482\ttotal: 20m 53s\tremaining: 2h 37m 38s\n",
      "117:\tlearn: 0.4095354\ttotal: 21m 4s\tremaining: 2h 37m 30s\n",
      "118:\tlearn: 0.4092348\ttotal: 21m 14s\tremaining: 2h 37m 18s\n",
      "119:\tlearn: 0.4087543\ttotal: 21m 26s\tremaining: 2h 37m 17s\n",
      "120:\tlearn: 0.4079768\ttotal: 21m 37s\tremaining: 2h 37m 8s\n",
      "121:\tlearn: 0.4071889\ttotal: 21m 47s\tremaining: 2h 36m 48s\n",
      "122:\tlearn: 0.4061557\ttotal: 21m 56s\tremaining: 2h 36m 24s\n",
      "123:\tlearn: 0.4054506\ttotal: 22m 6s\tremaining: 2h 36m 12s\n",
      "124:\tlearn: 0.4050130\ttotal: 22m 17s\tremaining: 2h 35m 59s\n",
      "125:\tlearn: 0.4042024\ttotal: 22m 26s\tremaining: 2h 35m 43s\n",
      "126:\tlearn: 0.4039564\ttotal: 22m 40s\tremaining: 2h 35m 51s\n",
      "127:\tlearn: 0.4032906\ttotal: 22m 51s\tremaining: 2h 35m 45s\n",
      "128:\tlearn: 0.4028244\ttotal: 23m 3s\tremaining: 2h 35m 39s\n",
      "129:\tlearn: 0.4020784\ttotal: 23m 13s\tremaining: 2h 35m 26s\n",
      "130:\tlearn: 0.4015778\ttotal: 23m 24s\tremaining: 2h 35m 14s\n",
      "131:\tlearn: 0.4008400\ttotal: 23m 34s\tremaining: 2h 35m\n",
      "132:\tlearn: 0.4004144\ttotal: 23m 46s\tremaining: 2h 35m\n",
      "133:\tlearn: 0.3999157\ttotal: 23m 58s\tremaining: 2h 34m 53s\n",
      "134:\tlearn: 0.3991793\ttotal: 24m 6s\tremaining: 2h 34m 31s\n",
      "135:\tlearn: 0.3988346\ttotal: 24m 17s\tremaining: 2h 34m 16s\n",
      "136:\tlearn: 0.3983680\ttotal: 24m 27s\tremaining: 2h 34m 4s\n",
      "137:\tlearn: 0.3979782\ttotal: 24m 39s\tremaining: 2h 34m 1s\n",
      "138:\tlearn: 0.3974635\ttotal: 24m 48s\tremaining: 2h 33m 40s\n",
      "139:\tlearn: 0.3962104\ttotal: 24m 57s\tremaining: 2h 33m 18s\n",
      "140:\tlearn: 0.3957810\ttotal: 25m 7s\tremaining: 2h 33m 6s\n",
      "141:\tlearn: 0.3951165\ttotal: 25m 18s\tremaining: 2h 32m 54s\n",
      "142:\tlearn: 0.3944467\ttotal: 25m 29s\tremaining: 2h 32m 47s\n",
      "143:\tlearn: 0.3941542\ttotal: 25m 40s\tremaining: 2h 32m 38s\n",
      "144:\tlearn: 0.3936953\ttotal: 25m 51s\tremaining: 2h 32m 29s\n",
      "145:\tlearn: 0.3935823\ttotal: 26m 2s\tremaining: 2h 32m 20s\n",
      "146:\tlearn: 0.3933013\ttotal: 26m 14s\tremaining: 2h 32m 14s\n",
      "147:\tlearn: 0.3928242\ttotal: 26m 25s\tremaining: 2h 32m 6s\n",
      "148:\tlearn: 0.3920415\ttotal: 26m 37s\tremaining: 2h 32m 3s\n",
      "149:\tlearn: 0.3915872\ttotal: 26m 46s\tremaining: 2h 31m 45s\n",
      "150:\tlearn: 0.3912980\ttotal: 26m 57s\tremaining: 2h 31m 35s\n",
      "151:\tlearn: 0.3907237\ttotal: 27m 10s\tremaining: 2h 31m 35s\n",
      "152:\tlearn: 0.3901988\ttotal: 27m 21s\tremaining: 2h 31m 26s\n",
      "153:\tlearn: 0.3897936\ttotal: 27m 30s\tremaining: 2h 31m 8s\n",
      "154:\tlearn: 0.3893269\ttotal: 27m 40s\tremaining: 2h 30m 51s\n",
      "155:\tlearn: 0.3888015\ttotal: 27m 51s\tremaining: 2h 30m 44s\n",
      "156:\tlearn: 0.3885350\ttotal: 28m 3s\tremaining: 2h 30m 40s\n",
      "157:\tlearn: 0.3884837\ttotal: 28m 17s\tremaining: 2h 30m 43s\n",
      "158:\tlearn: 0.3881946\ttotal: 28m 30s\tremaining: 2h 30m 45s\n",
      "159:\tlearn: 0.3877708\ttotal: 28m 41s\tremaining: 2h 30m 36s\n",
      "160:\tlearn: 0.3875652\ttotal: 28m 52s\tremaining: 2h 30m 30s\n",
      "161:\tlearn: 0.3873420\ttotal: 29m 4s\tremaining: 2h 30m 25s\n",
      "162:\tlearn: 0.3872082\ttotal: 29m 16s\tremaining: 2h 30m 22s\n",
      "163:\tlearn: 0.3868208\ttotal: 29m 30s\tremaining: 2h 30m 22s\n",
      "164:\tlearn: 0.3866008\ttotal: 29m 42s\tremaining: 2h 30m 21s\n",
      "165:\tlearn: 0.3863091\ttotal: 29m 54s\tremaining: 2h 30m 17s\n",
      "166:\tlearn: 0.3859148\ttotal: 30m 8s\tremaining: 2h 30m 22s\n",
      "167:\tlearn: 0.3853802\ttotal: 30m 17s\tremaining: 2h 30m 2s\n",
      "168:\tlearn: 0.3852431\ttotal: 30m 29s\tremaining: 2h 29m 57s\n",
      "169:\tlearn: 0.3850010\ttotal: 30m 41s\tremaining: 2h 29m 52s\n",
      "170:\tlearn: 0.3848087\ttotal: 30m 52s\tremaining: 2h 29m 41s\n",
      "171:\tlearn: 0.3846390\ttotal: 31m 4s\tremaining: 2h 29m 33s\n",
      "172:\tlearn: 0.3844879\ttotal: 31m 13s\tremaining: 2h 29m 15s\n",
      "173:\tlearn: 0.3842479\ttotal: 31m 25s\tremaining: 2h 29m 9s\n",
      "174:\tlearn: 0.3838899\ttotal: 31m 37s\tremaining: 2h 29m 6s\n",
      "175:\tlearn: 0.3835327\ttotal: 31m 49s\tremaining: 2h 28m 58s\n",
      "176:\tlearn: 0.3830743\ttotal: 31m 58s\tremaining: 2h 28m 40s\n",
      "177:\tlearn: 0.3827548\ttotal: 32m 11s\tremaining: 2h 28m 37s\n",
      "178:\tlearn: 0.3821008\ttotal: 32m 20s\tremaining: 2h 28m 21s\n",
      "179:\tlearn: 0.3818018\ttotal: 32m 32s\tremaining: 2h 28m 14s\n",
      "180:\tlearn: 0.3815513\ttotal: 32m 43s\tremaining: 2h 28m 5s\n",
      "181:\tlearn: 0.3813714\ttotal: 32m 55s\tremaining: 2h 28m\n",
      "182:\tlearn: 0.3812098\ttotal: 33m 8s\tremaining: 2h 27m 59s\n",
      "183:\tlearn: 0.3809508\ttotal: 33m 18s\tremaining: 2h 27m 41s\n",
      "184:\tlearn: 0.3806477\ttotal: 33m 27s\tremaining: 2h 27m 24s\n",
      "185:\tlearn: 0.3805128\ttotal: 33m 40s\tremaining: 2h 27m 20s\n",
      "186:\tlearn: 0.3801696\ttotal: 33m 52s\tremaining: 2h 27m 14s\n",
      "187:\tlearn: 0.3796606\ttotal: 34m 3s\tremaining: 2h 27m 4s\n",
      "188:\tlearn: 0.3794417\ttotal: 34m 16s\tremaining: 2h 27m 3s\n",
      "189:\tlearn: 0.3793117\ttotal: 34m 27s\tremaining: 2h 26m 52s\n",
      "190:\tlearn: 0.3791260\ttotal: 34m 39s\tremaining: 2h 26m 49s\n",
      "191:\tlearn: 0.3789930\ttotal: 34m 51s\tremaining: 2h 26m 42s\n",
      "192:\tlearn: 0.3784079\ttotal: 35m 2s\tremaining: 2h 26m 29s\n",
      "193:\tlearn: 0.3781140\ttotal: 35m 15s\tremaining: 2h 26m 27s\n",
      "194:\tlearn: 0.3779652\ttotal: 35m 27s\tremaining: 2h 26m 21s\n",
      "195:\tlearn: 0.3776176\ttotal: 35m 38s\tremaining: 2h 26m 10s\n",
      "196:\tlearn: 0.3774561\ttotal: 35m 49s\tremaining: 2h 26m 1s\n",
      "197:\tlearn: 0.3773722\ttotal: 35m 59s\tremaining: 2h 25m 45s\n",
      "198:\tlearn: 0.3772872\ttotal: 36m 10s\tremaining: 2h 25m 36s\n",
      "199:\tlearn: 0.3772193\ttotal: 36m 21s\tremaining: 2h 25m 27s\n",
      "200:\tlearn: 0.3770947\ttotal: 36m 34s\tremaining: 2h 25m 23s\n",
      "201:\tlearn: 0.3767749\ttotal: 36m 45s\tremaining: 2h 25m 13s\n",
      "202:\tlearn: 0.3765838\ttotal: 36m 57s\tremaining: 2h 25m 7s\n",
      "203:\tlearn: 0.3764483\ttotal: 37m 10s\tremaining: 2h 25m 3s\n",
      "204:\tlearn: 0.3762619\ttotal: 37m 22s\tremaining: 2h 24m 55s\n",
      "205:\tlearn: 0.3755796\ttotal: 37m 34s\tremaining: 2h 24m 50s\n",
      "206:\tlearn: 0.3750550\ttotal: 37m 45s\tremaining: 2h 24m 39s\n",
      "207:\tlearn: 0.3749126\ttotal: 38m\tremaining: 2h 24m 42s\n",
      "208:\tlearn: 0.3744766\ttotal: 38m 10s\tremaining: 2h 24m 28s\n",
      "209:\tlearn: 0.3744049\ttotal: 38m 22s\tremaining: 2h 24m 22s\n",
      "210:\tlearn: 0.3742045\ttotal: 38m 34s\tremaining: 2h 24m 14s\n",
      "211:\tlearn: 0.3736589\ttotal: 38m 45s\tremaining: 2h 24m 3s\n",
      "212:\tlearn: 0.3734463\ttotal: 38m 55s\tremaining: 2h 23m 49s\n",
      "213:\tlearn: 0.3731525\ttotal: 39m 8s\tremaining: 2h 23m 47s\n",
      "214:\tlearn: 0.3731020\ttotal: 39m 22s\tremaining: 2h 23m 46s\n",
      "215:\tlearn: 0.3724869\ttotal: 39m 31s\tremaining: 2h 23m 27s\n",
      "216:\tlearn: 0.3721034\ttotal: 39m 42s\tremaining: 2h 23m 17s\n",
      "217:\tlearn: 0.3719772\ttotal: 39m 55s\tremaining: 2h 23m 14s\n",
      "218:\tlearn: 0.3717985\ttotal: 40m 6s\tremaining: 2h 23m\n",
      "219:\tlearn: 0.3716648\ttotal: 40m 17s\tremaining: 2h 22m 52s\n",
      "220:\tlearn: 0.3712088\ttotal: 40m 29s\tremaining: 2h 22m 43s\n",
      "221:\tlearn: 0.3711248\ttotal: 40m 42s\tremaining: 2h 22m 39s\n",
      "222:\tlearn: 0.3710327\ttotal: 40m 56s\tremaining: 2h 22m 37s\n",
      "223:\tlearn: 0.3708418\ttotal: 41m 7s\tremaining: 2h 22m 29s\n",
      "224:\tlearn: 0.3706974\ttotal: 41m 20s\tremaining: 2h 22m 24s\n",
      "225:\tlearn: 0.3706356\ttotal: 41m 32s\tremaining: 2h 22m 16s\n",
      "226:\tlearn: 0.3704970\ttotal: 41m 46s\tremaining: 2h 22m 14s\n",
      "227:\tlearn: 0.3700942\ttotal: 41m 57s\tremaining: 2h 22m 3s\n",
      "228:\tlearn: 0.3700621\ttotal: 42m 8s\tremaining: 2h 21m 53s\n",
      "229:\tlearn: 0.3699880\ttotal: 42m 22s\tremaining: 2h 21m 50s\n",
      "230:\tlearn: 0.3694704\ttotal: 42m 33s\tremaining: 2h 21m 40s\n",
      "231:\tlearn: 0.3691681\ttotal: 42m 45s\tremaining: 2h 21m 32s\n",
      "232:\tlearn: 0.3690759\ttotal: 42m 55s\tremaining: 2h 21m 19s\n",
      "233:\tlearn: 0.3689825\ttotal: 43m 9s\tremaining: 2h 21m 17s\n",
      "234:\tlearn: 0.3687457\ttotal: 43m 21s\tremaining: 2h 21m 8s\n",
      "235:\tlearn: 0.3683672\ttotal: 43m 32s\tremaining: 2h 20m 57s\n",
      "236:\tlearn: 0.3679510\ttotal: 43m 41s\tremaining: 2h 20m 40s\n",
      "237:\tlearn: 0.3676845\ttotal: 43m 52s\tremaining: 2h 20m 29s\n",
      "238:\tlearn: 0.3675324\ttotal: 44m 5s\tremaining: 2h 20m 24s\n",
      "239:\tlearn: 0.3673053\ttotal: 44m 17s\tremaining: 2h 20m 14s\n",
      "240:\tlearn: 0.3672322\ttotal: 44m 30s\tremaining: 2h 20m 10s\n",
      "241:\tlearn: 0.3670372\ttotal: 44m 42s\tremaining: 2h 20m\n",
      "242:\tlearn: 0.3668953\ttotal: 44m 54s\tremaining: 2h 19m 53s\n",
      "243:\tlearn: 0.3667689\ttotal: 45m 6s\tremaining: 2h 19m 45s\n",
      "244:\tlearn: 0.3664399\ttotal: 45m 17s\tremaining: 2h 19m 34s\n",
      "245:\tlearn: 0.3663037\ttotal: 45m 30s\tremaining: 2h 19m 29s\n",
      "246:\tlearn: 0.3658122\ttotal: 45m 40s\tremaining: 2h 19m 13s\n",
      "247:\tlearn: 0.3657770\ttotal: 45m 50s\tremaining: 2h 19m\n",
      "248:\tlearn: 0.3656746\ttotal: 46m 3s\tremaining: 2h 18m 56s\n",
      "249:\tlearn: 0.3654031\ttotal: 46m 15s\tremaining: 2h 18m 46s\n",
      "250:\tlearn: 0.3652859\ttotal: 46m 28s\tremaining: 2h 18m 40s\n",
      "251:\tlearn: 0.3651657\ttotal: 46m 40s\tremaining: 2h 18m 32s\n",
      "252:\tlearn: 0.3651034\ttotal: 46m 53s\tremaining: 2h 18m 26s\n",
      "253:\tlearn: 0.3649646\ttotal: 47m 5s\tremaining: 2h 18m 17s\n",
      "254:\tlearn: 0.3648873\ttotal: 47m 15s\tremaining: 2h 18m 3s\n",
      "255:\tlearn: 0.3648466\ttotal: 47m 27s\tremaining: 2h 17m 55s\n",
      "256:\tlearn: 0.3646575\ttotal: 47m 40s\tremaining: 2h 17m 48s\n",
      "257:\tlearn: 0.3644938\ttotal: 47m 51s\tremaining: 2h 17m 38s\n",
      "258:\tlearn: 0.3643079\ttotal: 48m 3s\tremaining: 2h 17m 30s\n",
      "259:\tlearn: 0.3642229\ttotal: 48m 14s\tremaining: 2h 17m 17s\n",
      "260:\tlearn: 0.3641717\ttotal: 48m 25s\tremaining: 2h 17m 5s\n",
      "261:\tlearn: 0.3641420\ttotal: 48m 33s\tremaining: 2h 16m 47s\n",
      "262:\tlearn: 0.3640442\ttotal: 48m 41s\tremaining: 2h 16m 27s\n",
      "263:\tlearn: 0.3639387\ttotal: 48m 54s\tremaining: 2h 16m 20s\n",
      "264:\tlearn: 0.3636449\ttotal: 49m 5s\tremaining: 2h 16m 10s\n",
      "265:\tlearn: 0.3634481\ttotal: 49m 17s\tremaining: 2h 16m\n",
      "266:\tlearn: 0.3634001\ttotal: 49m 27s\tremaining: 2h 15m 47s\n",
      "267:\tlearn: 0.3632173\ttotal: 49m 40s\tremaining: 2h 15m 39s\n",
      "268:\tlearn: 0.3629681\ttotal: 49m 50s\tremaining: 2h 15m 26s\n",
      "269:\tlearn: 0.3627139\ttotal: 50m 2s\tremaining: 2h 15m 16s\n",
      "270:\tlearn: 0.3626776\ttotal: 50m 14s\tremaining: 2h 15m 9s\n",
      "271:\tlearn: 0.3626058\ttotal: 50m 24s\tremaining: 2h 14m 55s\n",
      "272:\tlearn: 0.3624811\ttotal: 50m 36s\tremaining: 2h 14m 45s\n",
      "273:\tlearn: 0.3624164\ttotal: 50m 46s\tremaining: 2h 14m 31s\n",
      "274:\tlearn: 0.3623746\ttotal: 50m 59s\tremaining: 2h 14m 25s\n",
      "275:\tlearn: 0.3621695\ttotal: 51m 11s\tremaining: 2h 14m 17s\n",
      "276:\tlearn: 0.3619596\ttotal: 51m 23s\tremaining: 2h 14m 9s\n",
      "277:\tlearn: 0.3618292\ttotal: 51m 36s\tremaining: 2h 14m 2s\n",
      "278:\tlearn: 0.3617632\ttotal: 51m 47s\tremaining: 2h 13m 49s\n",
      "279:\tlearn: 0.3616792\ttotal: 51m 58s\tremaining: 2h 13m 38s\n",
      "280:\tlearn: 0.3615570\ttotal: 52m 12s\tremaining: 2h 13m 34s\n",
      "281:\tlearn: 0.3611780\ttotal: 52m 24s\tremaining: 2h 13m 26s\n",
      "282:\tlearn: 0.3611557\ttotal: 52m 36s\tremaining: 2h 13m 16s\n",
      "283:\tlearn: 0.3609620\ttotal: 52m 46s\tremaining: 2h 13m 3s\n",
      "284:\tlearn: 0.3608193\ttotal: 52m 59s\tremaining: 2h 12m 55s\n",
      "285:\tlearn: 0.3606926\ttotal: 53m 12s\tremaining: 2h 12m 50s\n",
      "286:\tlearn: 0.3606313\ttotal: 53m 25s\tremaining: 2h 12m 43s\n",
      "287:\tlearn: 0.3604567\ttotal: 53m 37s\tremaining: 2h 12m 34s\n",
      "288:\tlearn: 0.3602901\ttotal: 53m 48s\tremaining: 2h 12m 23s\n",
      "289:\tlearn: 0.3602151\ttotal: 54m 2s\tremaining: 2h 12m 17s\n",
      "290:\tlearn: 0.3601734\ttotal: 54m 15s\tremaining: 2h 12m 10s\n",
      "291:\tlearn: 0.3600605\ttotal: 54m 27s\tremaining: 2h 12m 1s\n",
      "292:\tlearn: 0.3599908\ttotal: 54m 40s\tremaining: 2h 11m 54s\n",
      "293:\tlearn: 0.3599406\ttotal: 54m 51s\tremaining: 2h 11m 44s\n",
      "294:\tlearn: 0.3597645\ttotal: 55m 3s\tremaining: 2h 11m 35s\n",
      "295:\tlearn: 0.3596742\ttotal: 55m 15s\tremaining: 2h 11m 25s\n",
      "296:\tlearn: 0.3596366\ttotal: 55m 28s\tremaining: 2h 11m 18s\n",
      "297:\tlearn: 0.3593959\ttotal: 55m 40s\tremaining: 2h 11m 8s\n",
      "298:\tlearn: 0.3593269\ttotal: 55m 52s\tremaining: 2h 11m\n",
      "299:\tlearn: 0.3592205\ttotal: 56m 5s\tremaining: 2h 10m 52s\n",
      "300:\tlearn: 0.3591652\ttotal: 56m 15s\tremaining: 2h 10m 39s\n",
      "301:\tlearn: 0.3590773\ttotal: 56m 26s\tremaining: 2h 10m 26s\n",
      "302:\tlearn: 0.3589843\ttotal: 56m 39s\tremaining: 2h 10m 19s\n",
      "303:\tlearn: 0.3589553\ttotal: 56m 51s\tremaining: 2h 10m 11s\n",
      "304:\tlearn: 0.3588800\ttotal: 57m 4s\tremaining: 2h 10m 3s\n",
      "305:\tlearn: 0.3588587\ttotal: 57m 17s\tremaining: 2h 9m 55s\n",
      "306:\tlearn: 0.3587530\ttotal: 57m 27s\tremaining: 2h 9m 42s\n",
      "307:\tlearn: 0.3584969\ttotal: 57m 38s\tremaining: 2h 9m 30s\n",
      "308:\tlearn: 0.3581107\ttotal: 57m 47s\tremaining: 2h 9m 14s\n",
      "309:\tlearn: 0.3580402\ttotal: 58m\tremaining: 2h 9m 6s\n",
      "310:\tlearn: 0.3578170\ttotal: 58m 14s\tremaining: 2h 9m 1s\n",
      "311:\tlearn: 0.3577466\ttotal: 58m 27s\tremaining: 2h 8m 54s\n",
      "312:\tlearn: 0.3575154\ttotal: 58m 39s\tremaining: 2h 8m 45s\n",
      "313:\tlearn: 0.3574646\ttotal: 58m 51s\tremaining: 2h 8m 34s\n",
      "314:\tlearn: 0.3573012\ttotal: 59m 3s\tremaining: 2h 8m 24s\n",
      "315:\tlearn: 0.3571376\ttotal: 59m 14s\tremaining: 2h 8m 14s\n",
      "316:\tlearn: 0.3568873\ttotal: 59m 26s\tremaining: 2h 8m 4s\n",
      "317:\tlearn: 0.3568059\ttotal: 59m 39s\tremaining: 2h 7m 55s\n",
      "318:\tlearn: 0.3567200\ttotal: 59m 50s\tremaining: 2h 7m 45s\n",
      "319:\tlearn: 0.3565994\ttotal: 1h 3s\tremaining: 2h 7m 37s\n",
      "320:\tlearn: 0.3564040\ttotal: 1h 16s\tremaining: 2h 7m 30s\n",
      "321:\tlearn: 0.3563745\ttotal: 1h 27s\tremaining: 2h 7m 18s\n",
      "322:\tlearn: 0.3563047\ttotal: 1h 40s\tremaining: 2h 7m 9s\n",
      "323:\tlearn: 0.3559195\ttotal: 1h 48s\tremaining: 2h 6m 53s\n",
      "324:\tlearn: 0.3558322\ttotal: 1h 1m 1s\tremaining: 2h 6m 45s\n",
      "325:\tlearn: 0.3557857\ttotal: 1h 1m 15s\tremaining: 2h 6m 39s\n",
      "326:\tlearn: 0.3557192\ttotal: 1h 1m 29s\tremaining: 2h 6m 33s\n",
      "327:\tlearn: 0.3556780\ttotal: 1h 1m 41s\tremaining: 2h 6m 24s\n",
      "328:\tlearn: 0.3555335\ttotal: 1h 1m 54s\tremaining: 2h 6m 16s\n",
      "329:\tlearn: 0.3554145\ttotal: 1h 2m 8s\tremaining: 2h 6m 9s\n",
      "330:\tlearn: 0.3553099\ttotal: 1h 2m 22s\tremaining: 2h 6m 3s\n",
      "331:\tlearn: 0.3552426\ttotal: 1h 2m 35s\tremaining: 2h 5m 56s\n",
      "332:\tlearn: 0.3550529\ttotal: 1h 2m 47s\tremaining: 2h 5m 45s\n",
      "333:\tlearn: 0.3550218\ttotal: 1h 2m 58s\tremaining: 2h 5m 33s\n",
      "334:\tlearn: 0.3549103\ttotal: 1h 3m 9s\tremaining: 2h 5m 22s\n",
      "335:\tlearn: 0.3547402\ttotal: 1h 3m 19s\tremaining: 2h 5m 7s\n",
      "336:\tlearn: 0.3547224\ttotal: 1h 3m 32s\tremaining: 2h 4m 59s\n",
      "337:\tlearn: 0.3545708\ttotal: 1h 3m 43s\tremaining: 2h 4m 49s\n",
      "338:\tlearn: 0.3545123\ttotal: 1h 3m 57s\tremaining: 2h 4m 42s\n",
      "339:\tlearn: 0.3543589\ttotal: 1h 4m 11s\tremaining: 2h 4m 36s\n",
      "340:\tlearn: 0.3542976\ttotal: 1h 4m 24s\tremaining: 2h 4m 27s\n",
      "341:\tlearn: 0.3542773\ttotal: 1h 4m 34s\tremaining: 2h 4m 14s\n",
      "342:\tlearn: 0.3541559\ttotal: 1h 4m 46s\tremaining: 2h 4m 4s\n",
      "343:\tlearn: 0.3538933\ttotal: 1h 4m 57s\tremaining: 2h 3m 52s\n",
      "344:\tlearn: 0.3538289\ttotal: 1h 5m 12s\tremaining: 2h 3m 47s\n",
      "345:\tlearn: 0.3537247\ttotal: 1h 5m 23s\tremaining: 2h 3m 36s\n",
      "346:\tlearn: 0.3535715\ttotal: 1h 5m 35s\tremaining: 2h 3m 25s\n",
      "347:\tlearn: 0.3534663\ttotal: 1h 5m 48s\tremaining: 2h 3m 17s\n",
      "348:\tlearn: 0.3534182\ttotal: 1h 5m 59s\tremaining: 2h 3m 5s\n",
      "349:\tlearn: 0.3533090\ttotal: 1h 6m 12s\tremaining: 2h 2m 57s\n",
      "350:\tlearn: 0.3531710\ttotal: 1h 6m 24s\tremaining: 2h 2m 48s\n",
      "351:\tlearn: 0.3530324\ttotal: 1h 6m 36s\tremaining: 2h 2m 36s\n",
      "352:\tlearn: 0.3529930\ttotal: 1h 6m 48s\tremaining: 2h 2m 27s\n",
      "353:\tlearn: 0.3528951\ttotal: 1h 7m 2s\tremaining: 2h 2m 19s\n",
      "354:\tlearn: 0.3528101\ttotal: 1h 7m 12s\tremaining: 2h 2m 7s\n",
      "355:\tlearn: 0.3525720\ttotal: 1h 7m 22s\tremaining: 2h 1m 52s\n",
      "356:\tlearn: 0.3524544\ttotal: 1h 7m 35s\tremaining: 2h 1m 45s\n",
      "357:\tlearn: 0.3522598\ttotal: 1h 7m 48s\tremaining: 2h 1m 36s\n",
      "358:\tlearn: 0.3520859\ttotal: 1h 8m\tremaining: 2h 1m 26s\n",
      "359:\tlearn: 0.3519683\ttotal: 1h 8m 12s\tremaining: 2h 1m 16s\n",
      "360:\tlearn: 0.3519214\ttotal: 1h 8m 26s\tremaining: 2h 1m 8s\n",
      "361:\tlearn: 0.3518610\ttotal: 1h 8m 38s\tremaining: 2h 59s\n",
      "362:\tlearn: 0.3518281\ttotal: 1h 8m 51s\tremaining: 2h 50s\n",
      "363:\tlearn: 0.3517894\ttotal: 1h 9m 5s\tremaining: 2h 43s\n",
      "364:\tlearn: 0.3516808\ttotal: 1h 9m 17s\tremaining: 2h 33s\n",
      "365:\tlearn: 0.3516133\ttotal: 1h 9m 31s\tremaining: 2h 25s\n",
      "366:\tlearn: 0.3514433\ttotal: 1h 9m 46s\tremaining: 2h 20s\n",
      "367:\tlearn: 0.3513406\ttotal: 1h 9m 57s\tremaining: 2h 7s\n",
      "368:\tlearn: 0.3512818\ttotal: 1h 10m 14s\tremaining: 2h 6s\n",
      "369:\tlearn: 0.3511347\ttotal: 1h 10m 27s\tremaining: 1h 59m 58s\n",
      "370:\tlearn: 0.3509451\ttotal: 1h 10m 42s\tremaining: 1h 59m 52s\n",
      "371:\tlearn: 0.3507993\ttotal: 1h 10m 59s\tremaining: 1h 59m 50s\n",
      "372:\tlearn: 0.3507668\ttotal: 1h 11m 11s\tremaining: 1h 59m 40s\n",
      "373:\tlearn: 0.3506993\ttotal: 1h 11m 25s\tremaining: 1h 59m 32s\n",
      "374:\tlearn: 0.3506095\ttotal: 1h 11m 39s\tremaining: 1h 59m 25s\n",
      "375:\tlearn: 0.3503773\ttotal: 1h 11m 51s\tremaining: 1h 59m 15s\n",
      "376:\tlearn: 0.3500624\ttotal: 1h 12m 6s\tremaining: 1h 59m 9s\n",
      "377:\tlearn: 0.3499844\ttotal: 1h 12m 19s\tremaining: 1h 59m\n",
      "378:\tlearn: 0.3499443\ttotal: 1h 12m 31s\tremaining: 1h 58m 49s\n",
      "379:\tlearn: 0.3498614\ttotal: 1h 12m 47s\tremaining: 1h 58m 46s\n",
      "380:\tlearn: 0.3496813\ttotal: 1h 13m\tremaining: 1h 58m 36s\n",
      "381:\tlearn: 0.3495861\ttotal: 1h 13m 15s\tremaining: 1h 58m 31s\n",
      "382:\tlearn: 0.3495115\ttotal: 1h 13m 27s\tremaining: 1h 58m 20s\n",
      "383:\tlearn: 0.3494506\ttotal: 1h 13m 41s\tremaining: 1h 58m 12s\n",
      "384:\tlearn: 0.3492314\ttotal: 1h 13m 51s\tremaining: 1h 57m 58s\n",
      "385:\tlearn: 0.3491910\ttotal: 1h 14m 4s\tremaining: 1h 57m 50s\n",
      "386:\tlearn: 0.3489525\ttotal: 1h 14m 14s\tremaining: 1h 57m 36s\n",
      "387:\tlearn: 0.3488752\ttotal: 1h 14m 30s\tremaining: 1h 57m 31s\n",
      "388:\tlearn: 0.3487881\ttotal: 1h 14m 41s\tremaining: 1h 57m 18s\n",
      "389:\tlearn: 0.3487617\ttotal: 1h 14m 53s\tremaining: 1h 57m 8s\n",
      "390:\tlearn: 0.3486367\ttotal: 1h 15m 5s\tremaining: 1h 56m 57s\n",
      "391:\tlearn: 0.3485809\ttotal: 1h 15m 19s\tremaining: 1h 56m 50s\n",
      "392:\tlearn: 0.3484431\ttotal: 1h 15m 33s\tremaining: 1h 56m 41s\n",
      "393:\tlearn: 0.3483883\ttotal: 1h 15m 44s\tremaining: 1h 56m 30s\n",
      "394:\tlearn: 0.3483008\ttotal: 1h 15m 57s\tremaining: 1h 56m 19s\n",
      "395:\tlearn: 0.3480108\ttotal: 1h 16m 10s\tremaining: 1h 56m 11s\n",
      "396:\tlearn: 0.3479149\ttotal: 1h 16m 24s\tremaining: 1h 56m 3s\n",
      "397:\tlearn: 0.3477217\ttotal: 1h 16m 40s\tremaining: 1h 55m 58s\n",
      "398:\tlearn: 0.3476930\ttotal: 1h 16m 52s\tremaining: 1h 55m 47s\n",
      "399:\tlearn: 0.3476494\ttotal: 1h 17m 6s\tremaining: 1h 55m 39s\n",
      "400:\tlearn: 0.3475236\ttotal: 1h 17m 20s\tremaining: 1h 55m 31s\n",
      "401:\tlearn: 0.3473911\ttotal: 1h 17m 46s\tremaining: 1h 55m 41s\n",
      "402:\tlearn: 0.3472786\ttotal: 1h 18m\tremaining: 1h 55m 34s\n",
      "403:\tlearn: 0.3472404\ttotal: 1h 18m 14s\tremaining: 1h 55m 25s\n",
      "404:\tlearn: 0.3471193\ttotal: 1h 18m 27s\tremaining: 1h 55m 15s\n",
      "405:\tlearn: 0.3471095\ttotal: 1h 18m 39s\tremaining: 1h 55m 4s\n",
      "406:\tlearn: 0.3470247\ttotal: 1h 18m 51s\tremaining: 1h 54m 53s\n",
      "407:\tlearn: 0.3468965\ttotal: 1h 19m 6s\tremaining: 1h 54m 46s\n",
      "408:\tlearn: 0.3468781\ttotal: 1h 19m 17s\tremaining: 1h 54m 34s\n",
      "409:\tlearn: 0.3468029\ttotal: 1h 19m 33s\tremaining: 1h 54m 28s\n",
      "410:\tlearn: 0.3466001\ttotal: 1h 19m 47s\tremaining: 1h 54m 21s\n",
      "411:\tlearn: 0.3465619\ttotal: 1h 19m 58s\tremaining: 1h 54m 8s\n",
      "412:\tlearn: 0.3465278\ttotal: 1h 20m 12s\tremaining: 1h 53m 59s\n",
      "413:\tlearn: 0.3463720\ttotal: 1h 20m 26s\tremaining: 1h 53m 52s\n",
      "414:\tlearn: 0.3462904\ttotal: 1h 20m 40s\tremaining: 1h 53m 43s\n",
      "415:\tlearn: 0.3461456\ttotal: 1h 20m 55s\tremaining: 1h 53m 35s\n",
      "416:\tlearn: 0.3460696\ttotal: 1h 21m 7s\tremaining: 1h 53m 24s\n",
      "417:\tlearn: 0.3458691\ttotal: 1h 21m 20s\tremaining: 1h 53m 15s\n",
      "418:\tlearn: 0.3457401\ttotal: 1h 21m 36s\tremaining: 1h 53m 9s\n",
      "419:\tlearn: 0.3456628\ttotal: 1h 21m 51s\tremaining: 1h 53m 2s\n",
      "420:\tlearn: 0.3455138\ttotal: 1h 22m 3s\tremaining: 1h 52m 51s\n",
      "421:\tlearn: 0.3454191\ttotal: 1h 22m 14s\tremaining: 1h 52m 38s\n",
      "422:\tlearn: 0.3453397\ttotal: 1h 22m 27s\tremaining: 1h 52m 28s\n",
      "423:\tlearn: 0.3452956\ttotal: 1h 22m 38s\tremaining: 1h 52m 15s\n",
      "424:\tlearn: 0.3452295\ttotal: 1h 22m 49s\tremaining: 1h 52m 3s\n",
      "425:\tlearn: 0.3451114\ttotal: 1h 23m 3s\tremaining: 1h 51m 54s\n",
      "426:\tlearn: 0.3449855\ttotal: 1h 23m 17s\tremaining: 1h 51m 45s\n",
      "427:\tlearn: 0.3447771\ttotal: 1h 23m 31s\tremaining: 1h 51m 37s\n",
      "428:\tlearn: 0.3446625\ttotal: 1h 23m 46s\tremaining: 1h 51m 30s\n",
      "429:\tlearn: 0.3444768\ttotal: 1h 23m 58s\tremaining: 1h 51m 19s\n",
      "430:\tlearn: 0.3443147\ttotal: 1h 24m 10s\tremaining: 1h 51m 7s\n",
      "431:\tlearn: 0.3442018\ttotal: 1h 24m 24s\tremaining: 1h 50m 58s\n",
      "432:\tlearn: 0.3440572\ttotal: 1h 24m 36s\tremaining: 1h 50m 47s\n",
      "433:\tlearn: 0.3438666\ttotal: 1h 24m 48s\tremaining: 1h 50m 36s\n",
      "434:\tlearn: 0.3436258\ttotal: 1h 25m 1s\tremaining: 1h 50m 25s\n",
      "435:\tlearn: 0.3435179\ttotal: 1h 25m 12s\tremaining: 1h 50m 13s\n",
      "436:\tlearn: 0.3434106\ttotal: 1h 25m 25s\tremaining: 1h 50m 3s\n",
      "437:\tlearn: 0.3433161\ttotal: 1h 25m 38s\tremaining: 1h 49m 52s\n",
      "438:\tlearn: 0.3432338\ttotal: 1h 25m 51s\tremaining: 1h 49m 43s\n",
      "439:\tlearn: 0.3431248\ttotal: 1h 26m 2s\tremaining: 1h 49m 30s\n",
      "440:\tlearn: 0.3430411\ttotal: 1h 26m 15s\tremaining: 1h 49m 19s\n",
      "441:\tlearn: 0.3429285\ttotal: 1h 26m 29s\tremaining: 1h 49m 11s\n",
      "442:\tlearn: 0.3428924\ttotal: 1h 26m 43s\tremaining: 1h 49m 2s\n",
      "443:\tlearn: 0.3428539\ttotal: 1h 26m 52s\tremaining: 1h 48m 47s\n",
      "444:\tlearn: 0.3428334\ttotal: 1h 27m 3s\tremaining: 1h 48m 34s\n",
      "445:\tlearn: 0.3427951\ttotal: 1h 27m 16s\tremaining: 1h 48m 24s\n",
      "446:\tlearn: 0.3426412\ttotal: 1h 27m 29s\tremaining: 1h 48m 14s\n",
      "447:\tlearn: 0.3426361\ttotal: 1h 27m 43s\tremaining: 1h 48m 5s\n",
      "448:\tlearn: 0.3425643\ttotal: 1h 27m 54s\tremaining: 1h 47m 53s\n",
      "449:\tlearn: 0.3425185\ttotal: 1h 28m 5s\tremaining: 1h 47m 40s\n",
      "450:\tlearn: 0.3423478\ttotal: 1h 28m 19s\tremaining: 1h 47m 31s\n",
      "451:\tlearn: 0.3422682\ttotal: 1h 28m 32s\tremaining: 1h 47m 21s\n",
      "452:\tlearn: 0.3422006\ttotal: 1h 28m 45s\tremaining: 1h 47m 10s\n",
      "453:\tlearn: 0.3421278\ttotal: 1h 29m\tremaining: 1h 47m 2s\n",
      "454:\tlearn: 0.3421037\ttotal: 1h 29m 13s\tremaining: 1h 46m 51s\n",
      "455:\tlearn: 0.3420619\ttotal: 1h 29m 25s\tremaining: 1h 46m 41s\n",
      "456:\tlearn: 0.3420026\ttotal: 1h 29m 38s\tremaining: 1h 46m 30s\n",
      "457:\tlearn: 0.3419493\ttotal: 1h 29m 50s\tremaining: 1h 46m 18s\n",
      "458:\tlearn: 0.3419043\ttotal: 1h 30m 3s\tremaining: 1h 46m 9s\n",
      "459:\tlearn: 0.3418169\ttotal: 1h 30m 14s\tremaining: 1h 45m 56s\n",
      "460:\tlearn: 0.3416701\ttotal: 1h 30m 28s\tremaining: 1h 45m 47s\n",
      "461:\tlearn: 0.3415399\ttotal: 1h 30m 40s\tremaining: 1h 45m 35s\n",
      "462:\tlearn: 0.3414867\ttotal: 1h 30m 54s\tremaining: 1h 45m 26s\n",
      "463:\tlearn: 0.3413205\ttotal: 1h 31m 7s\tremaining: 1h 45m 15s\n",
      "464:\tlearn: 0.3412565\ttotal: 1h 31m 18s\tremaining: 1h 45m 3s\n",
      "465:\tlearn: 0.3411320\ttotal: 1h 31m 31s\tremaining: 1h 44m 52s\n",
      "466:\tlearn: 0.3410036\ttotal: 1h 31m 43s\tremaining: 1h 44m 41s\n",
      "467:\tlearn: 0.3409338\ttotal: 1h 31m 57s\tremaining: 1h 44m 31s\n",
      "468:\tlearn: 0.3409069\ttotal: 1h 32m 8s\tremaining: 1h 44m 19s\n",
      "469:\tlearn: 0.3408047\ttotal: 1h 32m 21s\tremaining: 1h 44m 9s\n",
      "470:\tlearn: 0.3406264\ttotal: 1h 32m 35s\tremaining: 1h 43m 59s\n",
      "471:\tlearn: 0.3404199\ttotal: 1h 32m 47s\tremaining: 1h 43m 48s\n",
      "472:\tlearn: 0.3403781\ttotal: 1h 32m 59s\tremaining: 1h 43m 35s\n",
      "473:\tlearn: 0.3403508\ttotal: 1h 33m 10s\tremaining: 1h 43m 23s\n",
      "474:\tlearn: 0.3402890\ttotal: 1h 33m 24s\tremaining: 1h 43m 14s\n",
      "475:\tlearn: 0.3402250\ttotal: 1h 33m 38s\tremaining: 1h 43m 4s\n",
      "476:\tlearn: 0.3399778\ttotal: 1h 33m 49s\tremaining: 1h 42m 52s\n",
      "477:\tlearn: 0.3398713\ttotal: 1h 34m 2s\tremaining: 1h 42m 42s\n",
      "478:\tlearn: 0.3397964\ttotal: 1h 34m 14s\tremaining: 1h 42m 30s\n",
      "479:\tlearn: 0.3397548\ttotal: 1h 34m 29s\tremaining: 1h 42m 21s\n",
      "480:\tlearn: 0.3396763\ttotal: 1h 34m 42s\tremaining: 1h 42m 11s\n",
      "481:\tlearn: 0.3396494\ttotal: 1h 34m 53s\tremaining: 1h 41m 58s\n",
      "482:\tlearn: 0.3396284\ttotal: 1h 35m 6s\tremaining: 1h 41m 48s\n",
      "483:\tlearn: 0.3395737\ttotal: 1h 35m 18s\tremaining: 1h 41m 36s\n",
      "484:\tlearn: 0.3394618\ttotal: 1h 35m 30s\tremaining: 1h 41m 24s\n",
      "485:\tlearn: 0.3393576\ttotal: 1h 35m 44s\tremaining: 1h 41m 15s\n",
      "486:\tlearn: 0.3391942\ttotal: 1h 35m 56s\tremaining: 1h 41m 3s\n",
      "487:\tlearn: 0.3390094\ttotal: 1h 36m 8s\tremaining: 1h 40m 52s\n",
      "488:\tlearn: 0.3389238\ttotal: 1h 36m 22s\tremaining: 1h 40m 42s\n",
      "489:\tlearn: 0.3388842\ttotal: 1h 36m 36s\tremaining: 1h 40m 32s\n",
      "490:\tlearn: 0.3387742\ttotal: 1h 36m 50s\tremaining: 1h 40m 23s\n",
      "491:\tlearn: 0.3387558\ttotal: 1h 37m 1s\tremaining: 1h 40m 10s\n",
      "492:\tlearn: 0.3387275\ttotal: 1h 37m 13s\tremaining: 1h 39m 58s\n",
      "493:\tlearn: 0.3385309\ttotal: 1h 37m 27s\tremaining: 1h 39m 49s\n",
      "494:\tlearn: 0.3384729\ttotal: 1h 37m 37s\tremaining: 1h 39m 35s\n",
      "495:\tlearn: 0.3383861\ttotal: 1h 37m 46s\tremaining: 1h 39m 21s\n",
      "496:\tlearn: 0.3383141\ttotal: 1h 37m 57s\tremaining: 1h 39m 7s\n",
      "497:\tlearn: 0.3382644\ttotal: 1h 38m 9s\tremaining: 1h 38m 56s\n",
      "498:\tlearn: 0.3381695\ttotal: 1h 38m 21s\tremaining: 1h 38m 45s\n",
      "499:\tlearn: 0.3381490\ttotal: 1h 38m 34s\tremaining: 1h 38m 34s\n",
      "500:\tlearn: 0.3379948\ttotal: 1h 38m 47s\tremaining: 1h 38m 23s\n",
      "501:\tlearn: 0.3379076\ttotal: 1h 39m\tremaining: 1h 38m 13s\n",
      "502:\tlearn: 0.3378041\ttotal: 1h 39m 13s\tremaining: 1h 38m 2s\n",
      "503:\tlearn: 0.3377768\ttotal: 1h 39m 24s\tremaining: 1h 37m 49s\n",
      "504:\tlearn: 0.3377013\ttotal: 1h 39m 36s\tremaining: 1h 37m 37s\n",
      "505:\tlearn: 0.3376896\ttotal: 1h 39m 46s\tremaining: 1h 37m 24s\n",
      "506:\tlearn: 0.3376569\ttotal: 1h 39m 59s\tremaining: 1h 37m 14s\n",
      "507:\tlearn: 0.3376110\ttotal: 1h 40m 13s\tremaining: 1h 37m 4s\n",
      "508:\tlearn: 0.3375580\ttotal: 1h 40m 25s\tremaining: 1h 36m 52s\n",
      "509:\tlearn: 0.3375292\ttotal: 1h 40m 38s\tremaining: 1h 36m 41s\n",
      "510:\tlearn: 0.3374533\ttotal: 1h 40m 52s\tremaining: 1h 36m 32s\n",
      "511:\tlearn: 0.3374158\ttotal: 1h 41m 3s\tremaining: 1h 36m 19s\n",
      "512:\tlearn: 0.3373103\ttotal: 1h 41m 16s\tremaining: 1h 36m 8s\n",
      "513:\tlearn: 0.3372180\ttotal: 1h 41m 31s\tremaining: 1h 35m 59s\n",
      "514:\tlearn: 0.3371469\ttotal: 1h 41m 46s\tremaining: 1h 35m 50s\n",
      "515:\tlearn: 0.3371347\ttotal: 1h 42m 2s\tremaining: 1h 35m 42s\n",
      "516:\tlearn: 0.3370804\ttotal: 1h 42m 15s\tremaining: 1h 35m 32s\n",
      "517:\tlearn: 0.3369960\ttotal: 1h 42m 27s\tremaining: 1h 35m 20s\n",
      "518:\tlearn: 0.3369204\ttotal: 1h 42m 41s\tremaining: 1h 35m 10s\n",
      "519:\tlearn: 0.3367717\ttotal: 1h 42m 54s\tremaining: 1h 34m 59s\n",
      "520:\tlearn: 0.3367605\ttotal: 1h 43m 7s\tremaining: 1h 34m 48s\n",
      "521:\tlearn: 0.3366653\ttotal: 1h 43m 19s\tremaining: 1h 34m 36s\n",
      "522:\tlearn: 0.3365400\ttotal: 1h 43m 30s\tremaining: 1h 34m 23s\n",
      "523:\tlearn: 0.3364841\ttotal: 1h 43m 43s\tremaining: 1h 34m 13s\n",
      "524:\tlearn: 0.3363807\ttotal: 1h 43m 57s\tremaining: 1h 34m 3s\n",
      "525:\tlearn: 0.3362921\ttotal: 1h 44m 9s\tremaining: 1h 33m 51s\n",
      "526:\tlearn: 0.3362028\ttotal: 1h 44m 22s\tremaining: 1h 33m 40s\n",
      "527:\tlearn: 0.3361664\ttotal: 1h 44m 33s\tremaining: 1h 33m 28s\n",
      "528:\tlearn: 0.3361303\ttotal: 1h 44m 48s\tremaining: 1h 33m 18s\n",
      "529:\tlearn: 0.3360942\ttotal: 1h 44m 59s\tremaining: 1h 33m 6s\n",
      "530:\tlearn: 0.3360372\ttotal: 1h 45m 13s\tremaining: 1h 32m 56s\n",
      "531:\tlearn: 0.3358283\ttotal: 1h 45m 25s\tremaining: 1h 32m 44s\n",
      "532:\tlearn: 0.3358189\ttotal: 1h 45m 38s\tremaining: 1h 32m 33s\n",
      "533:\tlearn: 0.3357330\ttotal: 1h 45m 53s\tremaining: 1h 32m 24s\n",
      "534:\tlearn: 0.3355283\ttotal: 1h 46m 5s\tremaining: 1h 32m 12s\n",
      "535:\tlearn: 0.3354916\ttotal: 1h 46m 15s\tremaining: 1h 31m 59s\n",
      "536:\tlearn: 0.3354320\ttotal: 1h 46m 28s\tremaining: 1h 31m 48s\n",
      "537:\tlearn: 0.3352881\ttotal: 1h 46m 41s\tremaining: 1h 31m 37s\n",
      "538:\tlearn: 0.3352511\ttotal: 1h 46m 55s\tremaining: 1h 31m 26s\n",
      "539:\tlearn: 0.3348933\ttotal: 1h 47m 5s\tremaining: 1h 31m 13s\n",
      "540:\tlearn: 0.3348511\ttotal: 1h 47m 17s\tremaining: 1h 31m 1s\n",
      "541:\tlearn: 0.3348480\ttotal: 1h 47m 31s\tremaining: 1h 30m 51s\n",
      "542:\tlearn: 0.3344738\ttotal: 1h 47m 42s\tremaining: 1h 30m 38s\n",
      "543:\tlearn: 0.3343642\ttotal: 1h 47m 55s\tremaining: 1h 30m 27s\n",
      "544:\tlearn: 0.3343342\ttotal: 1h 48m 7s\tremaining: 1h 30m 15s\n",
      "545:\tlearn: 0.3342853\ttotal: 1h 48m 21s\tremaining: 1h 30m 5s\n",
      "546:\tlearn: 0.3341331\ttotal: 1h 48m 32s\tremaining: 1h 29m 53s\n",
      "547:\tlearn: 0.3340540\ttotal: 1h 48m 45s\tremaining: 1h 29m 42s\n",
      "548:\tlearn: 0.3339584\ttotal: 1h 48m 58s\tremaining: 1h 29m 31s\n",
      "549:\tlearn: 0.3339029\ttotal: 1h 49m 12s\tremaining: 1h 29m 21s\n",
      "550:\tlearn: 0.3338012\ttotal: 1h 49m 25s\tremaining: 1h 29m 9s\n",
      "551:\tlearn: 0.3336937\ttotal: 1h 49m 35s\tremaining: 1h 28m 56s\n",
      "552:\tlearn: 0.3336207\ttotal: 1h 49m 45s\tremaining: 1h 28m 43s\n",
      "553:\tlearn: 0.3335480\ttotal: 1h 49m 57s\tremaining: 1h 28m 31s\n",
      "554:\tlearn: 0.3334604\ttotal: 1h 50m 10s\tremaining: 1h 28m 20s\n",
      "555:\tlearn: 0.3334395\ttotal: 1h 50m 21s\tremaining: 1h 28m 7s\n",
      "556:\tlearn: 0.3333529\ttotal: 1h 50m 33s\tremaining: 1h 27m 56s\n",
      "557:\tlearn: 0.3332654\ttotal: 1h 50m 48s\tremaining: 1h 27m 46s\n",
      "558:\tlearn: 0.3332242\ttotal: 1h 50m 59s\tremaining: 1h 27m 33s\n",
      "559:\tlearn: 0.3331925\ttotal: 1h 51m 10s\tremaining: 1h 27m 21s\n",
      "560:\tlearn: 0.3331303\ttotal: 1h 51m 25s\tremaining: 1h 27m 11s\n",
      "561:\tlearn: 0.3330686\ttotal: 1h 51m 39s\tremaining: 1h 27m 1s\n",
      "562:\tlearn: 0.3329121\ttotal: 1h 51m 51s\tremaining: 1h 26m 49s\n",
      "563:\tlearn: 0.3328236\ttotal: 1h 52m 5s\tremaining: 1h 26m 39s\n",
      "564:\tlearn: 0.3326175\ttotal: 1h 52m 18s\tremaining: 1h 26m 28s\n",
      "565:\tlearn: 0.3325402\ttotal: 1h 52m 32s\tremaining: 1h 26m 17s\n",
      "566:\tlearn: 0.3324878\ttotal: 1h 52m 43s\tremaining: 1h 26m 4s\n",
      "567:\tlearn: 0.3324263\ttotal: 1h 52m 54s\tremaining: 1h 25m 52s\n",
      "568:\tlearn: 0.3321852\ttotal: 1h 53m 8s\tremaining: 1h 25m 41s\n",
      "569:\tlearn: 0.3321352\ttotal: 1h 53m 20s\tremaining: 1h 25m 30s\n",
      "570:\tlearn: 0.3319875\ttotal: 1h 53m 31s\tremaining: 1h 25m 17s\n",
      "571:\tlearn: 0.3319206\ttotal: 1h 53m 45s\tremaining: 1h 25m 7s\n",
      "572:\tlearn: 0.3318720\ttotal: 1h 53m 59s\tremaining: 1h 24m 57s\n",
      "573:\tlearn: 0.3318021\ttotal: 1h 54m 13s\tremaining: 1h 24m 46s\n",
      "574:\tlearn: 0.3317192\ttotal: 1h 54m 29s\tremaining: 1h 24m 37s\n",
      "575:\tlearn: 0.3316163\ttotal: 1h 54m 40s\tremaining: 1h 24m 25s\n",
      "576:\tlearn: 0.3315738\ttotal: 1h 54m 52s\tremaining: 1h 24m 13s\n",
      "577:\tlearn: 0.3315276\ttotal: 1h 55m 7s\tremaining: 1h 24m 2s\n",
      "578:\tlearn: 0.3314659\ttotal: 1h 55m 18s\tremaining: 1h 23m 50s\n",
      "579:\tlearn: 0.3313487\ttotal: 1h 55m 30s\tremaining: 1h 23m 38s\n",
      "580:\tlearn: 0.3311357\ttotal: 1h 55m 45s\tremaining: 1h 23m 29s\n",
      "581:\tlearn: 0.3311139\ttotal: 1h 56m 1s\tremaining: 1h 23m 19s\n",
      "582:\tlearn: 0.3309926\ttotal: 1h 56m 17s\tremaining: 1h 23m 10s\n",
      "583:\tlearn: 0.3309374\ttotal: 1h 56m 34s\tremaining: 1h 23m 2s\n",
      "584:\tlearn: 0.3308968\ttotal: 1h 56m 49s\tremaining: 1h 22m 52s\n",
      "585:\tlearn: 0.3307721\ttotal: 1h 57m 2s\tremaining: 1h 22m 41s\n",
      "586:\tlearn: 0.3306445\ttotal: 1h 57m 17s\tremaining: 1h 22m 31s\n",
      "587:\tlearn: 0.3305515\ttotal: 1h 57m 30s\tremaining: 1h 22m 19s\n",
      "588:\tlearn: 0.3304684\ttotal: 1h 57m 42s\tremaining: 1h 22m 8s\n",
      "589:\tlearn: 0.3303958\ttotal: 1h 57m 56s\tremaining: 1h 21m 57s\n",
      "590:\tlearn: 0.3303277\ttotal: 1h 58m 6s\tremaining: 1h 21m 43s\n",
      "591:\tlearn: 0.3302511\ttotal: 1h 58m 20s\tremaining: 1h 21m 33s\n",
      "592:\tlearn: 0.3301716\ttotal: 1h 58m 36s\tremaining: 1h 21m 24s\n",
      "593:\tlearn: 0.3300880\ttotal: 1h 58m 47s\tremaining: 1h 21m 11s\n",
      "594:\tlearn: 0.3300392\ttotal: 1h 59m 2s\tremaining: 1h 21m 1s\n",
      "595:\tlearn: 0.3299877\ttotal: 1h 59m 15s\tremaining: 1h 20m 50s\n",
      "596:\tlearn: 0.3299057\ttotal: 1h 59m 25s\tremaining: 1h 20m 37s\n",
      "597:\tlearn: 0.3298346\ttotal: 1h 59m 35s\tremaining: 1h 20m 23s\n",
      "598:\tlearn: 0.3297779\ttotal: 1h 59m 46s\tremaining: 1h 20m 10s\n",
      "599:\tlearn: 0.3296507\ttotal: 1h 59m 57s\tremaining: 1h 19m 58s\n",
      "600:\tlearn: 0.3295176\ttotal: 2h 9s\tremaining: 1h 19m 46s\n",
      "601:\tlearn: 0.3294188\ttotal: 2h 21s\tremaining: 1h 19m 34s\n",
      "602:\tlearn: 0.3292929\ttotal: 2h 32s\tremaining: 1h 19m 21s\n",
      "603:\tlearn: 0.3292533\ttotal: 2h 42s\tremaining: 1h 19m 8s\n",
      "604:\tlearn: 0.3292137\ttotal: 2h 52s\tremaining: 1h 18m 55s\n",
      "605:\tlearn: 0.3290463\ttotal: 2h 1m 5s\tremaining: 1h 18m 43s\n",
      "606:\tlearn: 0.3289349\ttotal: 2h 1m 15s\tremaining: 1h 18m 30s\n",
      "607:\tlearn: 0.3287812\ttotal: 2h 1m 27s\tremaining: 1h 18m 18s\n",
      "608:\tlearn: 0.3287720\ttotal: 2h 1m 39s\tremaining: 1h 18m 6s\n",
      "609:\tlearn: 0.3287174\ttotal: 2h 1m 51s\tremaining: 1h 17m 54s\n",
      "610:\tlearn: 0.3285899\ttotal: 2h 2m 2s\tremaining: 1h 17m 42s\n",
      "611:\tlearn: 0.3285504\ttotal: 2h 2m 16s\tremaining: 1h 17m 30s\n",
      "612:\tlearn: 0.3285239\ttotal: 2h 2m 25s\tremaining: 1h 17m 17s\n",
      "613:\tlearn: 0.3284702\ttotal: 2h 2m 36s\tremaining: 1h 17m 4s\n",
      "614:\tlearn: 0.3284399\ttotal: 2h 2m 48s\tremaining: 1h 16m 52s\n",
      "615:\tlearn: 0.3283701\ttotal: 2h 3m 1s\tremaining: 1h 16m 41s\n",
      "616:\tlearn: 0.3283407\ttotal: 2h 3m 9s\tremaining: 1h 16m 27s\n",
      "617:\tlearn: 0.3281299\ttotal: 2h 3m 22s\tremaining: 1h 16m 15s\n",
      "618:\tlearn: 0.3280273\ttotal: 2h 3m 33s\tremaining: 1h 16m 2s\n",
      "619:\tlearn: 0.3278532\ttotal: 2h 3m 45s\tremaining: 1h 15m 51s\n",
      "620:\tlearn: 0.3277986\ttotal: 2h 3m 58s\tremaining: 1h 15m 39s\n",
      "621:\tlearn: 0.3277603\ttotal: 2h 4m 8s\tremaining: 1h 15m 26s\n",
      "622:\tlearn: 0.3277054\ttotal: 2h 4m 20s\tremaining: 1h 15m 14s\n",
      "623:\tlearn: 0.3276373\ttotal: 2h 4m 33s\tremaining: 1h 15m 3s\n",
      "624:\tlearn: 0.3275172\ttotal: 2h 4m 46s\tremaining: 1h 14m 51s\n",
      "625:\tlearn: 0.3274493\ttotal: 2h 4m 58s\tremaining: 1h 14m 39s\n",
      "626:\tlearn: 0.3273800\ttotal: 2h 5m 12s\tremaining: 1h 14m 29s\n",
      "627:\tlearn: 0.3273337\ttotal: 2h 5m 24s\tremaining: 1h 14m 17s\n",
      "628:\tlearn: 0.3272349\ttotal: 2h 5m 38s\tremaining: 1h 14m 6s\n",
      "629:\tlearn: 0.3271740\ttotal: 2h 5m 49s\tremaining: 1h 13m 54s\n",
      "630:\tlearn: 0.3271232\ttotal: 2h 5m 58s\tremaining: 1h 13m 40s\n",
      "631:\tlearn: 0.3269918\ttotal: 2h 6m 10s\tremaining: 1h 13m 28s\n",
      "632:\tlearn: 0.3269435\ttotal: 2h 6m 24s\tremaining: 1h 13m 17s\n",
      "633:\tlearn: 0.3268055\ttotal: 2h 6m 33s\tremaining: 1h 13m 3s\n",
      "634:\tlearn: 0.3266667\ttotal: 2h 6m 47s\tremaining: 1h 12m 52s\n",
      "635:\tlearn: 0.3264590\ttotal: 2h 7m\tremaining: 1h 12m 41s\n",
      "636:\tlearn: 0.3263422\ttotal: 2h 7m 12s\tremaining: 1h 12m 29s\n",
      "637:\tlearn: 0.3262133\ttotal: 2h 7m 25s\tremaining: 1h 12m 18s\n",
      "638:\tlearn: 0.3260687\ttotal: 2h 7m 38s\tremaining: 1h 12m 6s\n",
      "639:\tlearn: 0.3259961\ttotal: 2h 7m 50s\tremaining: 1h 11m 54s\n",
      "640:\tlearn: 0.3259267\ttotal: 2h 8m 2s\tremaining: 1h 11m 42s\n",
      "641:\tlearn: 0.3258616\ttotal: 2h 8m 13s\tremaining: 1h 11m 30s\n",
      "642:\tlearn: 0.3258280\ttotal: 2h 8m 27s\tremaining: 1h 11m 19s\n",
      "643:\tlearn: 0.3257983\ttotal: 2h 8m 39s\tremaining: 1h 11m 7s\n",
      "644:\tlearn: 0.3257785\ttotal: 2h 8m 49s\tremaining: 1h 10m 54s\n",
      "645:\tlearn: 0.3257025\ttotal: 2h 9m 2s\tremaining: 1h 10m 42s\n",
      "646:\tlearn: 0.3256713\ttotal: 2h 9m 15s\tremaining: 1h 10m 31s\n",
      "647:\tlearn: 0.3256494\ttotal: 2h 9m 26s\tremaining: 1h 10m 18s\n",
      "648:\tlearn: 0.3255533\ttotal: 2h 9m 39s\tremaining: 1h 10m 7s\n",
      "649:\tlearn: 0.3254186\ttotal: 2h 9m 51s\tremaining: 1h 9m 55s\n",
      "650:\tlearn: 0.3253896\ttotal: 2h 10m 7s\tremaining: 1h 9m 45s\n",
      "651:\tlearn: 0.3252599\ttotal: 2h 10m 20s\tremaining: 1h 9m 33s\n",
      "652:\tlearn: 0.3251342\ttotal: 2h 10m 33s\tremaining: 1h 9m 22s\n",
      "653:\tlearn: 0.3250686\ttotal: 2h 10m 44s\tremaining: 1h 9m 10s\n",
      "654:\tlearn: 0.3250100\ttotal: 2h 10m 55s\tremaining: 1h 8m 57s\n",
      "655:\tlearn: 0.3249237\ttotal: 2h 11m 7s\tremaining: 1h 8m 45s\n",
      "656:\tlearn: 0.3248084\ttotal: 2h 11m 19s\tremaining: 1h 8m 33s\n",
      "657:\tlearn: 0.3245714\ttotal: 2h 11m 33s\tremaining: 1h 8m 22s\n",
      "658:\tlearn: 0.3244552\ttotal: 2h 11m 44s\tremaining: 1h 8m 10s\n",
      "659:\tlearn: 0.3244288\ttotal: 2h 11m 58s\tremaining: 1h 7m 59s\n",
      "660:\tlearn: 0.3244101\ttotal: 2h 12m 15s\tremaining: 1h 7m 49s\n",
      "661:\tlearn: 0.3243723\ttotal: 2h 12m 33s\tremaining: 1h 7m 40s\n",
      "662:\tlearn: 0.3241895\ttotal: 2h 12m 54s\tremaining: 1h 7m 33s\n",
      "663:\tlearn: 0.3241348\ttotal: 2h 13m 4s\tremaining: 1h 7m 20s\n",
      "664:\tlearn: 0.3240372\ttotal: 2h 13m 17s\tremaining: 1h 7m 9s\n",
      "665:\tlearn: 0.3239094\ttotal: 2h 13m 30s\tremaining: 1h 6m 57s\n",
      "666:\tlearn: 0.3237989\ttotal: 2h 13m 45s\tremaining: 1h 6m 46s\n",
      "667:\tlearn: 0.3237104\ttotal: 2h 14m\tremaining: 1h 6m 36s\n",
      "668:\tlearn: 0.3236649\ttotal: 2h 14m 13s\tremaining: 1h 6m 24s\n",
      "669:\tlearn: 0.3236553\ttotal: 2h 14m 27s\tremaining: 1h 6m 13s\n",
      "670:\tlearn: 0.3235308\ttotal: 2h 14m 40s\tremaining: 1h 6m 1s\n",
      "671:\tlearn: 0.3233973\ttotal: 2h 14m 54s\tremaining: 1h 5m 51s\n",
      "672:\tlearn: 0.3232933\ttotal: 2h 15m 8s\tremaining: 1h 5m 39s\n",
      "673:\tlearn: 0.3232343\ttotal: 2h 15m 22s\tremaining: 1h 5m 28s\n",
      "674:\tlearn: 0.3231510\ttotal: 2h 15m 35s\tremaining: 1h 5m 17s\n",
      "675:\tlearn: 0.3230318\ttotal: 2h 15m 49s\tremaining: 1h 5m 5s\n",
      "676:\tlearn: 0.3228938\ttotal: 2h 15m 59s\tremaining: 1h 4m 52s\n",
      "677:\tlearn: 0.3228310\ttotal: 2h 16m 14s\tremaining: 1h 4m 42s\n",
      "678:\tlearn: 0.3227359\ttotal: 2h 16m 30s\tremaining: 1h 4m 32s\n",
      "679:\tlearn: 0.3227113\ttotal: 2h 16m 44s\tremaining: 1h 4m 20s\n",
      "680:\tlearn: 0.3225877\ttotal: 2h 16m 54s\tremaining: 1h 4m 8s\n",
      "681:\tlearn: 0.3225411\ttotal: 2h 17m 6s\tremaining: 1h 3m 55s\n",
      "682:\tlearn: 0.3224625\ttotal: 2h 17m 20s\tremaining: 1h 3m 44s\n",
      "683:\tlearn: 0.3223034\ttotal: 2h 17m 34s\tremaining: 1h 3m 33s\n",
      "684:\tlearn: 0.3222834\ttotal: 2h 17m 45s\tremaining: 1h 3m 20s\n",
      "685:\tlearn: 0.3222004\ttotal: 2h 17m 58s\tremaining: 1h 3m 9s\n",
      "686:\tlearn: 0.3221334\ttotal: 2h 18m 11s\tremaining: 1h 2m 57s\n",
      "687:\tlearn: 0.3220097\ttotal: 2h 18m 25s\tremaining: 1h 2m 46s\n",
      "688:\tlearn: 0.3218783\ttotal: 2h 18m 38s\tremaining: 1h 2m 34s\n",
      "689:\tlearn: 0.3217938\ttotal: 2h 18m 49s\tremaining: 1h 2m 22s\n",
      "690:\tlearn: 0.3217093\ttotal: 2h 19m\tremaining: 1h 2m 9s\n",
      "691:\tlearn: 0.3215752\ttotal: 2h 19m 13s\tremaining: 1h 1m 57s\n",
      "692:\tlearn: 0.3215313\ttotal: 2h 19m 27s\tremaining: 1h 1m 46s\n",
      "693:\tlearn: 0.3214557\ttotal: 2h 19m 41s\tremaining: 1h 1m 35s\n",
      "694:\tlearn: 0.3213946\ttotal: 2h 19m 52s\tremaining: 1h 1m 22s\n",
      "695:\tlearn: 0.3213756\ttotal: 2h 20m 8s\tremaining: 1h 1m 12s\n",
      "696:\tlearn: 0.3212522\ttotal: 2h 20m 19s\tremaining: 1h 1m\n",
      "697:\tlearn: 0.3212243\ttotal: 2h 20m 33s\tremaining: 1h 48s\n",
      "698:\tlearn: 0.3211867\ttotal: 2h 20m 45s\tremaining: 1h 36s\n",
      "699:\tlearn: 0.3211679\ttotal: 2h 20m 58s\tremaining: 1h 25s\n",
      "700:\tlearn: 0.3211389\ttotal: 2h 21m 8s\tremaining: 1h 12s\n",
      "701:\tlearn: 0.3210438\ttotal: 2h 21m 20s\tremaining: 59m 59s\n",
      "702:\tlearn: 0.3209090\ttotal: 2h 21m 32s\tremaining: 59m 47s\n",
      "703:\tlearn: 0.3208929\ttotal: 2h 21m 46s\tremaining: 59m 36s\n",
      "704:\tlearn: 0.3208217\ttotal: 2h 21m 56s\tremaining: 59m 23s\n",
      "705:\tlearn: 0.3207301\ttotal: 2h 22m 10s\tremaining: 59m 12s\n",
      "706:\tlearn: 0.3206421\ttotal: 2h 22m 22s\tremaining: 59m\n",
      "707:\tlearn: 0.3205742\ttotal: 2h 22m 37s\tremaining: 58m 49s\n",
      "708:\tlearn: 0.3204420\ttotal: 2h 22m 48s\tremaining: 58m 36s\n",
      "709:\tlearn: 0.3204021\ttotal: 2h 22m 58s\tremaining: 58m 24s\n",
      "710:\tlearn: 0.3203577\ttotal: 2h 23m 12s\tremaining: 58m 12s\n",
      "711:\tlearn: 0.3202021\ttotal: 2h 23m 24s\tremaining: 58m\n",
      "712:\tlearn: 0.3201448\ttotal: 2h 23m 37s\tremaining: 57m 48s\n",
      "713:\tlearn: 0.3201136\ttotal: 2h 23m 47s\tremaining: 57m 35s\n",
      "714:\tlearn: 0.3200645\ttotal: 2h 24m\tremaining: 57m 24s\n",
      "715:\tlearn: 0.3199045\ttotal: 2h 24m 13s\tremaining: 57m 12s\n",
      "716:\tlearn: 0.3198644\ttotal: 2h 24m 26s\tremaining: 57m\n",
      "717:\tlearn: 0.3198154\ttotal: 2h 24m 40s\tremaining: 56m 49s\n",
      "718:\tlearn: 0.3197721\ttotal: 2h 24m 52s\tremaining: 56m 37s\n",
      "719:\tlearn: 0.3195829\ttotal: 2h 25m 4s\tremaining: 56m 24s\n",
      "720:\tlearn: 0.3194138\ttotal: 2h 25m 15s\tremaining: 56m 12s\n",
      "721:\tlearn: 0.3193220\ttotal: 2h 25m 30s\tremaining: 56m 1s\n",
      "722:\tlearn: 0.3192527\ttotal: 2h 25m 44s\tremaining: 55m 50s\n",
      "723:\tlearn: 0.3191091\ttotal: 2h 25m 54s\tremaining: 55m 37s\n",
      "724:\tlearn: 0.3190602\ttotal: 2h 26m 7s\tremaining: 55m 25s\n",
      "725:\tlearn: 0.3188653\ttotal: 2h 26m 21s\tremaining: 55m 14s\n",
      "726:\tlearn: 0.3188133\ttotal: 2h 26m 34s\tremaining: 55m 2s\n",
      "727:\tlearn: 0.3187651\ttotal: 2h 26m 48s\tremaining: 54m 50s\n",
      "728:\tlearn: 0.3187253\ttotal: 2h 27m\tremaining: 54m 38s\n",
      "729:\tlearn: 0.3187055\ttotal: 2h 27m 16s\tremaining: 54m 28s\n",
      "730:\tlearn: 0.3186936\ttotal: 2h 27m 27s\tremaining: 54m 15s\n",
      "731:\tlearn: 0.3185512\ttotal: 2h 27m 41s\tremaining: 54m 4s\n",
      "732:\tlearn: 0.3185293\ttotal: 2h 27m 56s\tremaining: 53m 53s\n",
      "733:\tlearn: 0.3185102\ttotal: 2h 28m 10s\tremaining: 53m 41s\n",
      "734:\tlearn: 0.3184208\ttotal: 2h 28m 22s\tremaining: 53m 29s\n",
      "735:\tlearn: 0.3183993\ttotal: 2h 28m 38s\tremaining: 53m 18s\n",
      "736:\tlearn: 0.3182610\ttotal: 2h 28m 50s\tremaining: 53m 6s\n",
      "737:\tlearn: 0.3181082\ttotal: 2h 29m 2s\tremaining: 52m 54s\n",
      "738:\tlearn: 0.3180685\ttotal: 2h 29m 18s\tremaining: 52m 43s\n",
      "739:\tlearn: 0.3179909\ttotal: 2h 29m 30s\tremaining: 52m 31s\n",
      "740:\tlearn: 0.3178800\ttotal: 2h 29m 43s\tremaining: 52m 19s\n",
      "741:\tlearn: 0.3178511\ttotal: 2h 29m 55s\tremaining: 52m 7s\n",
      "742:\tlearn: 0.3177840\ttotal: 2h 30m 5s\tremaining: 51m 55s\n",
      "743:\tlearn: 0.3177293\ttotal: 2h 30m 18s\tremaining: 51m 43s\n",
      "744:\tlearn: 0.3176566\ttotal: 2h 30m 29s\tremaining: 51m 30s\n",
      "745:\tlearn: 0.3175473\ttotal: 2h 30m 42s\tremaining: 51m 18s\n",
      "746:\tlearn: 0.3175165\ttotal: 2h 30m 53s\tremaining: 51m 6s\n",
      "747:\tlearn: 0.3173723\ttotal: 2h 31m 6s\tremaining: 50m 54s\n",
      "748:\tlearn: 0.3172837\ttotal: 2h 31m 19s\tremaining: 50m 42s\n",
      "749:\tlearn: 0.3172003\ttotal: 2h 31m 31s\tremaining: 50m 30s\n",
      "750:\tlearn: 0.3171095\ttotal: 2h 31m 46s\tremaining: 50m 19s\n",
      "751:\tlearn: 0.3170674\ttotal: 2h 31m 58s\tremaining: 50m 7s\n",
      "752:\tlearn: 0.3170348\ttotal: 2h 32m 12s\tremaining: 49m 55s\n",
      "753:\tlearn: 0.3170008\ttotal: 2h 32m 24s\tremaining: 49m 43s\n",
      "754:\tlearn: 0.3167279\ttotal: 2h 32m 37s\tremaining: 49m 31s\n",
      "755:\tlearn: 0.3167013\ttotal: 2h 32m 50s\tremaining: 49m 19s\n",
      "756:\tlearn: 0.3166651\ttotal: 2h 33m 5s\tremaining: 49m 8s\n",
      "757:\tlearn: 0.3165803\ttotal: 2h 33m 17s\tremaining: 48m 56s\n",
      "758:\tlearn: 0.3165367\ttotal: 2h 33m 28s\tremaining: 48m 44s\n",
      "759:\tlearn: 0.3164749\ttotal: 2h 33m 44s\tremaining: 48m 32s\n",
      "760:\tlearn: 0.3164003\ttotal: 2h 34m\tremaining: 48m 22s\n",
      "761:\tlearn: 0.3163587\ttotal: 2h 34m 17s\tremaining: 48m 11s\n",
      "762:\tlearn: 0.3162300\ttotal: 2h 34m 32s\tremaining: 48m\n",
      "763:\tlearn: 0.3161469\ttotal: 2h 34m 45s\tremaining: 47m 48s\n",
      "764:\tlearn: 0.3161129\ttotal: 2h 34m 58s\tremaining: 47m 36s\n",
      "765:\tlearn: 0.3160778\ttotal: 2h 35m 11s\tremaining: 47m 24s\n",
      "766:\tlearn: 0.3159767\ttotal: 2h 35m 27s\tremaining: 47m 13s\n",
      "767:\tlearn: 0.3158835\ttotal: 2h 35m 41s\tremaining: 47m 1s\n",
      "768:\tlearn: 0.3158340\ttotal: 2h 35m 55s\tremaining: 46m 50s\n",
      "769:\tlearn: 0.3157999\ttotal: 2h 36m 12s\tremaining: 46m 39s\n",
      "770:\tlearn: 0.3157308\ttotal: 2h 36m 26s\tremaining: 46m 27s\n",
      "771:\tlearn: 0.3156973\ttotal: 2h 36m 40s\tremaining: 46m 16s\n",
      "772:\tlearn: 0.3156386\ttotal: 2h 36m 54s\tremaining: 46m 4s\n",
      "773:\tlearn: 0.3156167\ttotal: 2h 37m 5s\tremaining: 45m 52s\n",
      "774:\tlearn: 0.3155354\ttotal: 2h 37m 18s\tremaining: 45m 40s\n",
      "775:\tlearn: 0.3154759\ttotal: 2h 37m 29s\tremaining: 45m 27s\n",
      "776:\tlearn: 0.3154397\ttotal: 2h 37m 41s\tremaining: 45m 15s\n",
      "777:\tlearn: 0.3153551\ttotal: 2h 37m 54s\tremaining: 45m 3s\n",
      "778:\tlearn: 0.3152726\ttotal: 2h 38m 9s\tremaining: 44m 52s\n",
      "779:\tlearn: 0.3152510\ttotal: 2h 38m 25s\tremaining: 44m 41s\n",
      "780:\tlearn: 0.3151135\ttotal: 2h 38m 38s\tremaining: 44m 29s\n",
      "781:\tlearn: 0.3150913\ttotal: 2h 38m 53s\tremaining: 44m 17s\n",
      "782:\tlearn: 0.3150391\ttotal: 2h 39m 7s\tremaining: 44m 5s\n",
      "783:\tlearn: 0.3149903\ttotal: 2h 39m 19s\tremaining: 43m 53s\n",
      "784:\tlearn: 0.3149273\ttotal: 2h 39m 32s\tremaining: 43m 41s\n",
      "785:\tlearn: 0.3148440\ttotal: 2h 39m 43s\tremaining: 43m 29s\n",
      "786:\tlearn: 0.3148037\ttotal: 2h 39m 54s\tremaining: 43m 16s\n",
      "787:\tlearn: 0.3147163\ttotal: 2h 40m 6s\tremaining: 43m 4s\n",
      "788:\tlearn: 0.3146732\ttotal: 2h 40m 20s\tremaining: 42m 52s\n",
      "789:\tlearn: 0.3146058\ttotal: 2h 40m 34s\tremaining: 42m 41s\n",
      "790:\tlearn: 0.3145306\ttotal: 2h 40m 48s\tremaining: 42m 29s\n",
      "791:\tlearn: 0.3144576\ttotal: 2h 41m 1s\tremaining: 42m 17s\n",
      "792:\tlearn: 0.3144044\ttotal: 2h 41m 12s\tremaining: 42m 4s\n",
      "793:\tlearn: 0.3143663\ttotal: 2h 41m 22s\tremaining: 41m 52s\n",
      "794:\tlearn: 0.3142879\ttotal: 2h 41m 36s\tremaining: 41m 40s\n",
      "795:\tlearn: 0.3142188\ttotal: 2h 41m 51s\tremaining: 41m 28s\n",
      "796:\tlearn: 0.3141111\ttotal: 2h 42m 2s\tremaining: 41m 16s\n",
      "797:\tlearn: 0.3140632\ttotal: 2h 42m 19s\tremaining: 41m 5s\n",
      "798:\tlearn: 0.3140314\ttotal: 2h 42m 32s\tremaining: 40m 53s\n",
      "799:\tlearn: 0.3139488\ttotal: 2h 42m 46s\tremaining: 40m 41s\n",
      "800:\tlearn: 0.3138752\ttotal: 2h 42m 58s\tremaining: 40m 29s\n",
      "801:\tlearn: 0.3138154\ttotal: 2h 43m 10s\tremaining: 40m 17s\n",
      "802:\tlearn: 0.3136344\ttotal: 2h 43m 23s\tremaining: 40m 5s\n",
      "803:\tlearn: 0.3135474\ttotal: 2h 43m 37s\tremaining: 39m 53s\n",
      "804:\tlearn: 0.3135063\ttotal: 2h 43m 50s\tremaining: 39m 41s\n",
      "805:\tlearn: 0.3134211\ttotal: 2h 44m 4s\tremaining: 39m 29s\n",
      "806:\tlearn: 0.3133562\ttotal: 2h 44m 17s\tremaining: 39m 17s\n",
      "807:\tlearn: 0.3132875\ttotal: 2h 44m 31s\tremaining: 39m 5s\n",
      "808:\tlearn: 0.3132176\ttotal: 2h 44m 41s\tremaining: 38m 52s\n",
      "809:\tlearn: 0.3131673\ttotal: 2h 44m 54s\tremaining: 38m 40s\n",
      "810:\tlearn: 0.3130598\ttotal: 2h 45m 7s\tremaining: 38m 28s\n",
      "811:\tlearn: 0.3129875\ttotal: 2h 45m 19s\tremaining: 38m 16s\n",
      "812:\tlearn: 0.3129071\ttotal: 2h 45m 31s\tremaining: 38m 4s\n",
      "813:\tlearn: 0.3128192\ttotal: 2h 45m 45s\tremaining: 37m 52s\n",
      "814:\tlearn: 0.3127780\ttotal: 2h 45m 58s\tremaining: 37m 40s\n",
      "815:\tlearn: 0.3124023\ttotal: 2h 46m 9s\tremaining: 37m 28s\n",
      "816:\tlearn: 0.3123444\ttotal: 2h 46m 23s\tremaining: 37m 16s\n",
      "817:\tlearn: 0.3122009\ttotal: 2h 46m 36s\tremaining: 37m 4s\n",
      "818:\tlearn: 0.3121440\ttotal: 2h 46m 50s\tremaining: 36m 52s\n",
      "819:\tlearn: 0.3119799\ttotal: 2h 47m 3s\tremaining: 36m 40s\n",
      "820:\tlearn: 0.3118494\ttotal: 2h 47m 15s\tremaining: 36m 28s\n",
      "821:\tlearn: 0.3116721\ttotal: 2h 47m 28s\tremaining: 36m 15s\n",
      "822:\tlearn: 0.3116546\ttotal: 2h 47m 40s\tremaining: 36m 3s\n",
      "823:\tlearn: 0.3116376\ttotal: 2h 47m 53s\tremaining: 35m 51s\n",
      "824:\tlearn: 0.3115996\ttotal: 2h 48m 3s\tremaining: 35m 38s\n",
      "825:\tlearn: 0.3114344\ttotal: 2h 48m 15s\tremaining: 35m 26s\n",
      "826:\tlearn: 0.3113771\ttotal: 2h 48m 24s\tremaining: 35m 13s\n",
      "827:\tlearn: 0.3113161\ttotal: 2h 48m 37s\tremaining: 35m 1s\n",
      "828:\tlearn: 0.3112471\ttotal: 2h 48m 50s\tremaining: 34m 49s\n",
      "829:\tlearn: 0.3111469\ttotal: 2h 49m 3s\tremaining: 34m 37s\n",
      "830:\tlearn: 0.3110460\ttotal: 2h 49m 16s\tremaining: 34m 25s\n",
      "831:\tlearn: 0.3109447\ttotal: 2h 49m 29s\tremaining: 34m 13s\n",
      "832:\tlearn: 0.3109188\ttotal: 2h 49m 42s\tremaining: 34m 1s\n",
      "833:\tlearn: 0.3108455\ttotal: 2h 49m 57s\tremaining: 33m 49s\n",
      "834:\tlearn: 0.3107758\ttotal: 2h 50m 9s\tremaining: 33m 37s\n",
      "835:\tlearn: 0.3106762\ttotal: 2h 50m 23s\tremaining: 33m 25s\n",
      "836:\tlearn: 0.3106550\ttotal: 2h 50m 34s\tremaining: 33m 13s\n",
      "837:\tlearn: 0.3105896\ttotal: 2h 50m 47s\tremaining: 33m 1s\n",
      "838:\tlearn: 0.3105278\ttotal: 2h 51m\tremaining: 32m 48s\n",
      "839:\tlearn: 0.3103893\ttotal: 2h 51m 11s\tremaining: 32m 36s\n",
      "840:\tlearn: 0.3103110\ttotal: 2h 51m 23s\tremaining: 32m 24s\n",
      "841:\tlearn: 0.3101146\ttotal: 2h 51m 37s\tremaining: 32m 12s\n",
      "842:\tlearn: 0.3100889\ttotal: 2h 51m 47s\tremaining: 31m 59s\n",
      "843:\tlearn: 0.3100153\ttotal: 2h 52m\tremaining: 31m 47s\n",
      "844:\tlearn: 0.3099841\ttotal: 2h 52m 11s\tremaining: 31m 35s\n",
      "845:\tlearn: 0.3099016\ttotal: 2h 52m 22s\tremaining: 31m 22s\n",
      "846:\tlearn: 0.3097931\ttotal: 2h 52m 34s\tremaining: 31m 10s\n",
      "847:\tlearn: 0.3097455\ttotal: 2h 52m 46s\tremaining: 30m 58s\n",
      "848:\tlearn: 0.3096572\ttotal: 2h 52m 57s\tremaining: 30m 45s\n",
      "849:\tlearn: 0.3096411\ttotal: 2h 53m 9s\tremaining: 30m 33s\n",
      "850:\tlearn: 0.3095685\ttotal: 2h 53m 23s\tremaining: 30m 21s\n",
      "851:\tlearn: 0.3093732\ttotal: 2h 53m 36s\tremaining: 30m 9s\n",
      "852:\tlearn: 0.3093519\ttotal: 2h 53m 49s\tremaining: 29m 57s\n",
      "853:\tlearn: 0.3093158\ttotal: 2h 54m 2s\tremaining: 29m 45s\n",
      "854:\tlearn: 0.3091961\ttotal: 2h 54m 14s\tremaining: 29m 33s\n",
      "855:\tlearn: 0.3091519\ttotal: 2h 54m 24s\tremaining: 29m 20s\n",
      "856:\tlearn: 0.3090806\ttotal: 2h 54m 38s\tremaining: 29m 8s\n",
      "857:\tlearn: 0.3089569\ttotal: 2h 54m 51s\tremaining: 28m 56s\n",
      "858:\tlearn: 0.3088583\ttotal: 2h 55m 3s\tremaining: 28m 44s\n",
      "859:\tlearn: 0.3087922\ttotal: 2h 55m 15s\tremaining: 28m 31s\n",
      "860:\tlearn: 0.3087670\ttotal: 2h 55m 25s\tremaining: 28m 19s\n",
      "861:\tlearn: 0.3086642\ttotal: 2h 55m 37s\tremaining: 28m 7s\n",
      "862:\tlearn: 0.3084968\ttotal: 2h 55m 50s\tremaining: 27m 54s\n",
      "863:\tlearn: 0.3084141\ttotal: 2h 56m 2s\tremaining: 27m 42s\n",
      "864:\tlearn: 0.3083615\ttotal: 2h 56m 15s\tremaining: 27m 30s\n",
      "865:\tlearn: 0.3082706\ttotal: 2h 56m 27s\tremaining: 27m 18s\n",
      "866:\tlearn: 0.3082292\ttotal: 2h 56m 40s\tremaining: 27m 6s\n",
      "867:\tlearn: 0.3081808\ttotal: 2h 56m 52s\tremaining: 26m 53s\n",
      "868:\tlearn: 0.3081156\ttotal: 2h 57m 3s\tremaining: 26m 41s\n",
      "869:\tlearn: 0.3080454\ttotal: 2h 57m 17s\tremaining: 26m 29s\n",
      "870:\tlearn: 0.3079500\ttotal: 2h 57m 30s\tremaining: 26m 17s\n",
      "871:\tlearn: 0.3079077\ttotal: 2h 57m 44s\tremaining: 26m 5s\n",
      "872:\tlearn: 0.3078545\ttotal: 2h 57m 57s\tremaining: 25m 53s\n",
      "873:\tlearn: 0.3078154\ttotal: 2h 58m 9s\tremaining: 25m 41s\n",
      "874:\tlearn: 0.3076862\ttotal: 2h 58m 21s\tremaining: 25m 28s\n",
      "875:\tlearn: 0.3076124\ttotal: 2h 58m 33s\tremaining: 25m 16s\n",
      "876:\tlearn: 0.3075332\ttotal: 2h 58m 44s\tremaining: 25m 4s\n",
      "877:\tlearn: 0.3074899\ttotal: 2h 58m 56s\tremaining: 24m 51s\n",
      "878:\tlearn: 0.3073972\ttotal: 2h 59m 10s\tremaining: 24m 39s\n",
      "879:\tlearn: 0.3073468\ttotal: 2h 59m 21s\tremaining: 24m 27s\n",
      "880:\tlearn: 0.3072950\ttotal: 2h 59m 32s\tremaining: 24m 15s\n",
      "881:\tlearn: 0.3072112\ttotal: 2h 59m 43s\tremaining: 24m 2s\n",
      "882:\tlearn: 0.3070001\ttotal: 2h 59m 55s\tremaining: 23m 50s\n",
      "883:\tlearn: 0.3069421\ttotal: 3h 8s\tremaining: 23m 38s\n",
      "884:\tlearn: 0.3068929\ttotal: 3h 19s\tremaining: 23m 25s\n",
      "885:\tlearn: 0.3068645\ttotal: 3h 29s\tremaining: 23m 13s\n",
      "886:\tlearn: 0.3068273\ttotal: 3h 43s\tremaining: 23m 1s\n",
      "887:\tlearn: 0.3067947\ttotal: 3h 56s\tremaining: 22m 49s\n",
      "888:\tlearn: 0.3066520\ttotal: 3h 1m 7s\tremaining: 22m 36s\n",
      "889:\tlearn: 0.3065425\ttotal: 3h 1m 17s\tremaining: 22m 24s\n",
      "890:\tlearn: 0.3064359\ttotal: 3h 1m 29s\tremaining: 22m 12s\n",
      "891:\tlearn: 0.3063573\ttotal: 3h 1m 39s\tremaining: 21m 59s\n",
      "892:\tlearn: 0.3062487\ttotal: 3h 1m 52s\tremaining: 21m 47s\n",
      "893:\tlearn: 0.3062199\ttotal: 3h 2m 6s\tremaining: 21m 35s\n",
      "894:\tlearn: 0.3061592\ttotal: 3h 2m 20s\tremaining: 21m 23s\n",
      "895:\tlearn: 0.3060281\ttotal: 3h 2m 32s\tremaining: 21m 11s\n",
      "896:\tlearn: 0.3059728\ttotal: 3h 2m 42s\tremaining: 20m 58s\n",
      "897:\tlearn: 0.3058163\ttotal: 3h 2m 53s\tremaining: 20m 46s\n",
      "898:\tlearn: 0.3058023\ttotal: 3h 3m 5s\tremaining: 20m 34s\n",
      "899:\tlearn: 0.3056832\ttotal: 3h 3m 16s\tremaining: 20m 21s\n",
      "900:\tlearn: 0.3056045\ttotal: 3h 3m 30s\tremaining: 20m 9s\n",
      "901:\tlearn: 0.3055778\ttotal: 3h 3m 40s\tremaining: 19m 57s\n",
      "902:\tlearn: 0.3055463\ttotal: 3h 3m 52s\tremaining: 19m 45s\n",
      "903:\tlearn: 0.3055017\ttotal: 3h 4m 5s\tremaining: 19m 32s\n",
      "904:\tlearn: 0.3053947\ttotal: 3h 4m 16s\tremaining: 19m 20s\n",
      "905:\tlearn: 0.3053549\ttotal: 3h 4m 29s\tremaining: 19m 8s\n",
      "906:\tlearn: 0.3051015\ttotal: 3h 4m 40s\tremaining: 18m 56s\n",
      "907:\tlearn: 0.3049942\ttotal: 3h 4m 51s\tremaining: 18m 43s\n",
      "908:\tlearn: 0.3049422\ttotal: 3h 5m\tremaining: 18m 31s\n",
      "909:\tlearn: 0.3048190\ttotal: 3h 5m 11s\tremaining: 18m 18s\n",
      "910:\tlearn: 0.3046984\ttotal: 3h 5m 22s\tremaining: 18m 6s\n",
      "911:\tlearn: 0.3046272\ttotal: 3h 5m 33s\tremaining: 17m 54s\n",
      "912:\tlearn: 0.3045384\ttotal: 3h 5m 46s\tremaining: 17m 42s\n",
      "913:\tlearn: 0.3045182\ttotal: 3h 5m 58s\tremaining: 17m 29s\n",
      "914:\tlearn: 0.3044199\ttotal: 3h 6m 12s\tremaining: 17m 17s\n",
      "915:\tlearn: 0.3042372\ttotal: 3h 6m 24s\tremaining: 17m 5s\n",
      "916:\tlearn: 0.3041490\ttotal: 3h 6m 35s\tremaining: 16m 53s\n",
      "917:\tlearn: 0.3041255\ttotal: 3h 6m 48s\tremaining: 16m 41s\n",
      "918:\tlearn: 0.3039539\ttotal: 3h 6m 59s\tremaining: 16m 28s\n",
      "919:\tlearn: 0.3039368\ttotal: 3h 7m 13s\tremaining: 16m 16s\n",
      "920:\tlearn: 0.3037256\ttotal: 3h 7m 25s\tremaining: 16m 4s\n",
      "921:\tlearn: 0.3036412\ttotal: 3h 7m 36s\tremaining: 15m 52s\n",
      "922:\tlearn: 0.3035970\ttotal: 3h 7m 47s\tremaining: 15m 39s\n",
      "923:\tlearn: 0.3033720\ttotal: 3h 7m 59s\tremaining: 15m 27s\n",
      "924:\tlearn: 0.3033594\ttotal: 3h 8m 9s\tremaining: 15m 15s\n",
      "925:\tlearn: 0.3032517\ttotal: 3h 8m 22s\tremaining: 15m 3s\n",
      "926:\tlearn: 0.3031456\ttotal: 3h 8m 35s\tremaining: 14m 51s\n",
      "927:\tlearn: 0.3030907\ttotal: 3h 8m 45s\tremaining: 14m 38s\n",
      "928:\tlearn: 0.3030198\ttotal: 3h 8m 57s\tremaining: 14m 26s\n",
      "929:\tlearn: 0.3029739\ttotal: 3h 9m 9s\tremaining: 14m 14s\n",
      "930:\tlearn: 0.3028473\ttotal: 3h 9m 23s\tremaining: 14m 2s\n",
      "931:\tlearn: 0.3026458\ttotal: 3h 9m 34s\tremaining: 13m 49s\n",
      "932:\tlearn: 0.3025304\ttotal: 3h 9m 47s\tremaining: 13m 37s\n",
      "933:\tlearn: 0.3024899\ttotal: 3h 9m 59s\tremaining: 13m 25s\n",
      "934:\tlearn: 0.3024430\ttotal: 3h 10m 13s\tremaining: 13m 13s\n",
      "935:\tlearn: 0.3022028\ttotal: 3h 10m 25s\tremaining: 13m 1s\n",
      "936:\tlearn: 0.3021232\ttotal: 3h 10m 37s\tremaining: 12m 49s\n",
      "937:\tlearn: 0.3019256\ttotal: 3h 10m 49s\tremaining: 12m 36s\n",
      "938:\tlearn: 0.3018474\ttotal: 3h 11m 1s\tremaining: 12m 24s\n",
      "939:\tlearn: 0.3017454\ttotal: 3h 11m 14s\tremaining: 12m 12s\n",
      "940:\tlearn: 0.3017053\ttotal: 3h 11m 26s\tremaining: 12m\n",
      "941:\tlearn: 0.3016422\ttotal: 3h 11m 39s\tremaining: 11m 48s\n",
      "942:\tlearn: 0.3015403\ttotal: 3h 11m 50s\tremaining: 11m 35s\n",
      "943:\tlearn: 0.3014892\ttotal: 3h 12m 4s\tremaining: 11m 23s\n",
      "944:\tlearn: 0.3014352\ttotal: 3h 12m 17s\tremaining: 11m 11s\n",
      "945:\tlearn: 0.3013872\ttotal: 3h 12m 27s\tremaining: 10m 59s\n",
      "946:\tlearn: 0.3013595\ttotal: 3h 12m 41s\tremaining: 10m 47s\n",
      "947:\tlearn: 0.3013191\ttotal: 3h 12m 54s\tremaining: 10m 34s\n",
      "948:\tlearn: 0.3012317\ttotal: 3h 13m 6s\tremaining: 10m 22s\n",
      "949:\tlearn: 0.3011968\ttotal: 3h 13m 18s\tremaining: 10m 10s\n",
      "950:\tlearn: 0.3011829\ttotal: 3h 13m 31s\tremaining: 9m 58s\n",
      "951:\tlearn: 0.3011197\ttotal: 3h 13m 42s\tremaining: 9m 46s\n",
      "952:\tlearn: 0.3010975\ttotal: 3h 13m 55s\tremaining: 9m 33s\n",
      "953:\tlearn: 0.3010352\ttotal: 3h 14m 6s\tremaining: 9m 21s\n",
      "954:\tlearn: 0.3008686\ttotal: 3h 14m 16s\tremaining: 9m 9s\n",
      "955:\tlearn: 0.3007518\ttotal: 3h 14m 29s\tremaining: 8m 57s\n",
      "956:\tlearn: 0.3006342\ttotal: 3h 14m 40s\tremaining: 8m 44s\n",
      "957:\tlearn: 0.3004590\ttotal: 3h 14m 52s\tremaining: 8m 32s\n",
      "958:\tlearn: 0.3004095\ttotal: 3h 15m 6s\tremaining: 8m 20s\n",
      "959:\tlearn: 0.3003027\ttotal: 3h 15m 19s\tremaining: 8m 8s\n",
      "960:\tlearn: 0.3002425\ttotal: 3h 15m 29s\tremaining: 7m 56s\n",
      "961:\tlearn: 0.3002119\ttotal: 3h 15m 42s\tremaining: 7m 43s\n",
      "962:\tlearn: 0.3000001\ttotal: 3h 15m 55s\tremaining: 7m 31s\n",
      "963:\tlearn: 0.2999023\ttotal: 3h 16m 5s\tremaining: 7m 19s\n",
      "964:\tlearn: 0.2998650\ttotal: 3h 16m 18s\tremaining: 7m 7s\n",
      "965:\tlearn: 0.2997414\ttotal: 3h 16m 30s\tremaining: 6m 54s\n",
      "966:\tlearn: 0.2997163\ttotal: 3h 16m 43s\tremaining: 6m 42s\n",
      "967:\tlearn: 0.2996964\ttotal: 3h 16m 54s\tremaining: 6m 30s\n",
      "968:\tlearn: 0.2996610\ttotal: 3h 17m 7s\tremaining: 6m 18s\n",
      "969:\tlearn: 0.2995855\ttotal: 3h 17m 19s\tremaining: 6m 6s\n",
      "970:\tlearn: 0.2995058\ttotal: 3h 17m 30s\tremaining: 5m 53s\n",
      "971:\tlearn: 0.2994437\ttotal: 3h 17m 44s\tremaining: 5m 41s\n",
      "972:\tlearn: 0.2993497\ttotal: 3h 17m 55s\tremaining: 5m 29s\n",
      "973:\tlearn: 0.2993328\ttotal: 3h 18m 6s\tremaining: 5m 17s\n",
      "974:\tlearn: 0.2991929\ttotal: 3h 18m 21s\tremaining: 5m 5s\n",
      "975:\tlearn: 0.2991438\ttotal: 3h 18m 33s\tremaining: 4m 52s\n",
      "976:\tlearn: 0.2990875\ttotal: 3h 18m 45s\tremaining: 4m 40s\n",
      "977:\tlearn: 0.2990748\ttotal: 3h 18m 56s\tremaining: 4m 28s\n",
      "978:\tlearn: 0.2990110\ttotal: 3h 19m 10s\tremaining: 4m 16s\n",
      "979:\tlearn: 0.2989892\ttotal: 3h 19m 23s\tremaining: 4m 4s\n",
      "980:\tlearn: 0.2989398\ttotal: 3h 19m 37s\tremaining: 3m 51s\n",
      "981:\tlearn: 0.2988879\ttotal: 3h 19m 53s\tremaining: 3m 39s\n",
      "982:\tlearn: 0.2987896\ttotal: 3h 20m 7s\tremaining: 3m 27s\n",
      "983:\tlearn: 0.2985838\ttotal: 3h 20m 22s\tremaining: 3m 15s\n",
      "984:\tlearn: 0.2985375\ttotal: 3h 20m 35s\tremaining: 3m 3s\n",
      "985:\tlearn: 0.2985053\ttotal: 3h 20m 49s\tremaining: 2m 51s\n",
      "986:\tlearn: 0.2984600\ttotal: 3h 21m 5s\tremaining: 2m 38s\n",
      "987:\tlearn: 0.2983530\ttotal: 3h 21m 17s\tremaining: 2m 26s\n",
      "988:\tlearn: 0.2982612\ttotal: 3h 21m 32s\tremaining: 2m 14s\n",
      "989:\tlearn: 0.2982195\ttotal: 3h 21m 45s\tremaining: 2m 2s\n",
      "990:\tlearn: 0.2981956\ttotal: 3h 21m 57s\tremaining: 1m 50s\n",
      "991:\tlearn: 0.2981481\ttotal: 3h 22m 11s\tremaining: 1m 37s\n",
      "992:\tlearn: 0.2981030\ttotal: 3h 22m 23s\tremaining: 1m 25s\n",
      "993:\tlearn: 0.2980367\ttotal: 3h 22m 35s\tremaining: 1m 13s\n",
      "994:\tlearn: 0.2980121\ttotal: 3h 22m 48s\tremaining: 1m 1s\n",
      "995:\tlearn: 0.2979842\ttotal: 3h 23m\tremaining: 48.9s\n",
      "996:\tlearn: 0.2979590\ttotal: 3h 23m 11s\tremaining: 36.7s\n",
      "997:\tlearn: 0.2979290\ttotal: 3h 23m 25s\tremaining: 24.5s\n",
      "998:\tlearn: 0.2978517\ttotal: 3h 23m 37s\tremaining: 12.2s\n",
      "999:\tlearn: 0.2977931\ttotal: 3h 23m 50s\tremaining: 0us\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<catboost.core.CatBoostClassifier at 0x168585e3a48>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from catboost import CatBoostClassifier\n",
    "model = CatBoostClassifier()\n",
    "model.fit(X_train.drop(columns=['ID', 'ID2']), y_train, cat_features=['sex','marital_status','branch_code','occupation_code','occupation_category_code'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "nypr7XQ3ubkl"
   },
   "outputs": [],
   "source": [
    "proba = model.predict_proba(X_test.drop(columns=['ID','ID2'], axis=1))\n",
    "y_test = pd.DataFrame(proba)\n",
    "y_test.columns = le.inverse_transform(y_test.columns)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "W7NYpdx0nc4s"
   },
   "source": [
    "### Submit"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 122
    },
    "colab_type": "code",
    "id": "H8VHTNphyCDC",
    "outputId": "462812c6-d47a-4720-eaef-7d74240e2484"
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SHOLAY\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py:671: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
      "  self._setitem_with_indexer(indexer, value)\n"
     ]
    }
   ],
   "source": [
    "answer_mass = []\n",
    "for i in range(X_test.shape[0]):\n",
    "  id = X_test['ID'].iloc[i]\n",
    "  for c in y_test.columns:\n",
    "    answer_mass.append([id + ' X ' + c, y_test[c].iloc[i]])\n",
    "\n",
    "df_answer = pd.DataFrame(answer_mass)\n",
    "df_answer.columns = ['ID X PCODE', 'Label']\n",
    "for i in range(df_answer.shape[0]):\n",
    "  if df_answer['ID X PCODE'].iloc[i] in true_values:\n",
    "    df_answer['Label'].iloc[i] = 1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "colab": {},
    "colab_type": "code",
    "id": "zgIYeYwzzP1B"
   },
   "outputs": [],
   "source": [
    "df_answer.reset_index(drop=True, inplace=True)\n",
    "df_answer.to_csv('submission1.csv', index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "colab_type": "text",
    "id": "1ZTTmnHMmev1"
   },
   "source": [
    "Submit"
   ]
  }
 ],
 "metadata": {
  "colab": {
   "collapsed_sections": [],
   "include_colab_link": true,
   "name": "Baseline1.ipynb",
   "provenance": []
  },
  "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": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}