ml/catboost-train.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Requirement already satisfied: catboost in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (1.2.1)\n",
      "Requirement already satisfied: graphviz in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from catboost) (0.20.1)\n",
      "Requirement already satisfied: matplotlib in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from catboost) (3.7.2)\n",
      "Requirement already satisfied: numpy>=1.16.0 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from catboost) (1.25.2)\n",
      "Requirement already satisfied: pandas>=0.24 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from catboost) (2.1.0)\n",
      "Requirement already satisfied: scipy in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from catboost) (1.11.2)\n",
      "Requirement already satisfied: plotly in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from catboost) (5.16.1)\n",
      "Requirement already satisfied: six in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from catboost) (1.16.0)\n",
      "Requirement already satisfied: python-dateutil>=2.8.2 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from pandas>=0.24->catboost) (2.8.2)\n",
      "Requirement already satisfied: pytz>=2020.1 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from pandas>=0.24->catboost) (2023.3)\n",
      "Requirement already satisfied: tzdata>=2022.1 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from pandas>=0.24->catboost) (2023.3)\n",
      "Requirement already satisfied: contourpy>=1.0.1 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from matplotlib->catboost) (1.1.0)\n",
      "Requirement already satisfied: cycler>=0.10 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from matplotlib->catboost) (0.11.0)\n",
      "Requirement already satisfied: fonttools>=4.22.0 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from matplotlib->catboost) (4.42.1)\n",
      "Requirement already satisfied: kiwisolver>=1.0.1 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from matplotlib->catboost) (1.4.5)\n",
      "Requirement already satisfied: packaging>=20.0 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from matplotlib->catboost) (23.1)\n",
      "Requirement already satisfied: pillow>=6.2.0 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from matplotlib->catboost) (10.0.0)\n",
      "Requirement already satisfied: pyparsing<3.1,>=2.3.1 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from matplotlib->catboost) (3.0.9)\n",
      "Requirement already satisfied: tenacity>=6.2.0 in /Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages (from plotly->catboost) (8.2.3)\n"
     ]
    }
   ],
   "source": [
    "!pip3 install catboost"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pickle\n",
    "\n",
    "with open('cb.pickle', 'rb') as file:\n",
    "    cb_dataset = pickle.load(file)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from catboost import CatBoostClassifier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = CatBoostClassifier(iterations=50000,\n",
    "                          learning_rate=1e-2,\n",
    "                          depth=8)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "label2id = {\n",
    " 'AAA(RU)': 0,\n",
    " 'AA(RU)': 1, \n",
    " 'A+(RU)': 2,\n",
    " 'A(RU)': 3,\n",
    " 'A-(RU)': 4,\n",
    " 'BBB+(RU)': 5,\n",
    " 'BBB(RU)': 6, \n",
    " 'AA+(RU)': 7,\n",
    " 'BBB-(RU)': 8,\n",
    " 'AA-(RU)': 9,\n",
    " 'BB+(RU)': 10, \n",
    " 'BB-(RU)': 11, \n",
    " 'B+(RU)': 12,\n",
    " 'BB(RU)': 13, \n",
    " 'B(RU)': 14,\n",
    " 'B-(RU)': 15, \n",
    " 'C(RU)': 16\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "train = []\n",
    "train_labels = []\n",
    "for i in cb_dataset[0:6500]:\n",
    "    train.append([label2id[i['outs'][0]['answer']], i['outs'][0]['metric'], i['outs'][1]['metric'], label2id[i['outs'][1]['answer']], i['outs'][2]['metric'], label2id[i['outs'][2]['answer']]])\n",
    "    if not isinstance(i['label'], int):\n",
    "        train_labels.append(label2id[i['label'] + '(RU)'])\n",
    "    else:\n",
    "        train_labels.append(i['label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "test = []\n",
    "test_labels = []\n",
    "for i in cb_dataset[6500:]:\n",
    "    test.append([label2id[i['outs'][0]['answer']], i['outs'][0]['metric'], i['outs'][1]['metric'], label2id[i['outs'][1]['answer']], i['outs'][2]['metric'], label2id[i['outs'][2]['answer']]])\n",
    "    if not isinstance(i['label'], int):\n",
    "        test_labels.append(label2id[i['label'] + '(RU)'])\n",
    "    else:\n",
    "        test_labels.append(i['label'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "model.fit(train, train_labels)"
   ]
  }
 ],
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