analysis_geitje_uf.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from datasets import load_dataset\n",
    "\n",
    "ds_name = \"davidberenstein1957/ultra_feedback_dutch_cleaned_helm_instruct_geitje_ultra_vs_gpt4_turbo\"\n",
    "ds = load_dataset(ds_name)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(['rating_Helpfulness_GEITje-7B-ultra',\n",
       "  'rating_Understandability_GEITje-7B-ultra',\n",
       "  'rating_Completeness_GEITje-7B-ultra',\n",
       "  'rating_Conciseness_GEITje-7B-ultra',\n",
       "  'rating_dutchness_GEITje-7B-ultra'],\n",
       " ['rating_Helpfulness_gpt-4-turbo',\n",
       "  'rating_Understandability_gpt-4-turbo',\n",
       "  'rating_Completeness_gpt-4-turbo',\n",
       "  'rating_Conciseness_gpt-4-turbo',\n",
       "  'rating_dutchness_gpt-4-turbo'])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "def get_columns(model):\n",
    "    return [\n",
    "        column for column in ds.column_names[\"train\"]\n",
    "        if model in column and \"rating\" in column and \"Harmlessness\" not in column\n",
    "    ]\n",
    "columns_nl = get_columns(\"GEITje\")\n",
    "columns_en = get_columns(\"gpt-4\")\n",
    "columns_nl, columns_en"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatasetDict({\n",
       "    train: Dataset({\n",
       "        features: ['GEITje-7B-ultra', 'TowerInstruct-13B-v0.1', 'TowerInstruct-7B-v0.2', 'geitje-7b-chat', 'gpt-4-turbo', 'llama-2-13b-chat-dutch', 'prompt_english', 'prompt', 'labelling_model', 'labelling_prompt', 'raw_labelling_response', 'rating_Helpfulness_GEITje-7B-ultra', 'rationale_Helpfulness_GEITje-7B-ultra', 'generations_Helpfulness_GEITje-7B-ultra', 'rating_Understandability_GEITje-7B-ultra', 'rationale_Understandability_GEITje-7B-ultra', 'generations_Understandability_GEITje-7B-ultra', 'rating_Completeness_GEITje-7B-ultra', 'rationale_Completeness_GEITje-7B-ultra', 'generations_Completeness_GEITje-7B-ultra', 'rating_Conciseness_GEITje-7B-ultra', 'rationale_Conciseness_GEITje-7B-ultra', 'generations_Conciseness_GEITje-7B-ultra', 'rating_Harmlessness_GEITje-7B-ultra', 'rationale_Harmlessness_GEITje-7B-ultra', 'generations_Harmlessness_GEITje-7B-ultra', 'rating_dutchness_GEITje-7B-ultra', 'rationale_dutchness_GEITje-7B-ultra', 'generations_dutchness_GEITje-7B-ultra', 'rating_Helpfulness_gpt-4-turbo', 'rationale_Helpfulness_gpt-4-turbo', 'generations_Helpfulness_gpt-4-turbo', 'rating_Understandability_gpt-4-turbo', 'rationale_Understandability_gpt-4-turbo', 'generations_Understandability_gpt-4-turbo', 'rating_Completeness_gpt-4-turbo', 'rationale_Completeness_gpt-4-turbo', 'generations_Completeness_gpt-4-turbo', 'rating_Conciseness_gpt-4-turbo', 'rationale_Conciseness_gpt-4-turbo', 'generations_Conciseness_gpt-4-turbo', 'rating_Harmlessness_gpt-4-turbo', 'rationale_Harmlessness_gpt-4-turbo', 'generations_Harmlessness_gpt-4-turbo', 'rating_dutchness_gpt-4-turbo', 'rationale_dutchness_gpt-4-turbo', 'generations_dutchness_gpt-4-turbo', 'average_score_nl', 'average_score_en'],\n",
       "        num_rows: 100\n",
       "    })\n",
       "})"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_processed = ds.map(\n",
    "    lambda x: {\n",
    "        \"average_score_nl\": sum(\n",
    "            [x[column] for column in columns_nl if x[column]]\n",
    "        )\n",
    "        / len(columns_nl),\n",
    "        \"average_score_en\": sum(\n",
    "            [x[column] for column in columns_en if x[column]]\n",
    "        )\n",
    "        / len(columns_en),\n",
    "    }\n",
    ")\n",
    "ds_processed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "rating_Helpfulness_GEITje-7B-ultra wins 1.03% of the time\n",
      "rating_Understandability_GEITje-7B-ultra wins 2.00% of the time\n",
      "rating_Completeness_GEITje-7B-ultra wins 0.00% of the time\n",
      "rating_Conciseness_GEITje-7B-ultra wins 2.00% of the time\n",
      "rating_dutchness_GEITje-7B-ultra wins 4.04% of the time\n",
      "average_score_nl wins 4.00% of the time\n"
     ]
    }
   ],
   "source": [
    "def win_rate_per_column_pair(column_nl, columns_en):\n",
    "    wins = []\n",
    "    for idx in range(len(ds_processed[\"train\"])):\n",
    "        value_nl = ds_processed[\"train\"][idx][column_nl]\n",
    "        value_en = ds_processed[\"train\"][idx][columns_en]\n",
    "        if value_nl and value_en:\n",
    "            if value_nl > value_en:\n",
    "                wins.append(1)\n",
    "            else:\n",
    "                wins.append(0)\n",
    "    return sum(wins) / len(wins)\n",
    "\n",
    "for column_nl, column_en in zip(columns_nl+[\"average_score_nl\"], columns_en+[\"average_score_en\"]):\n",
    "    win_rate = win_rate_per_column_pair(column_nl, column_en)\n",
    "    print(f\"{column_nl} wins {win_rate:.2%} of the time\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Average rating_Helpfulness_GEITje-7B-ultra: 2.88\n",
      "Average rating_Understandability_GEITje-7B-ultra: 3.43\n",
      "Average rating_Completeness_GEITje-7B-ultra: 2.92\n",
      "Average rating_Conciseness_GEITje-7B-ultra: 2.58\n",
      "Average rating_dutchness_GEITje-7B-ultra: 2.82\n",
      "Average average_score_nl: 2.91\n",
      "Average rating_Helpfulness_gpt-4-turbo: 3.95\n",
      "Average rating_Understandability_gpt-4-turbo: 4.70\n",
      "Average rating_Completeness_gpt-4-turbo: 4.16\n",
      "Average rating_Conciseness_gpt-4-turbo: 3.86\n",
      "Average rating_dutchness_gpt-4-turbo: 4.31\n",
      "Average average_score_en: 4.19\n"
     ]
    }
   ],
   "source": [
    "def average_per_column(column):\n",
    "    values = [x[column] for x in ds_processed[\"train\"] if x[column]]\n",
    "    return sum(values) / len(values)\n",
    "\n",
    "for column in columns_nl+[\"average_score_nl\"] + columns_en+[\"average_score_en\"]:\n",
    "    average = average_per_column(column)\n",
    "    print(f\"Average {column}: {average:.2f}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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hxLbIyMhL/mbbqFEjPfroo65LNlu1aqVXXnnF9YFW0ngsXLhQHTt2LDKx7/jx466Jwp4ofL127typTp06ucrPnj2r7Oxstw/ehQsXqmHDhnr//ffd2jdu3Lhit13c++z777/3ys2ySnu/tmzZUtddd53mzJmjunXrau/evfrrX//q0fbT0tIUFBSkOXPmlHmSakVp1KiRjDFq0KBBifcSkX4LZYVXf0jFf0gfPHhQn376qYYOHerxJfa//vqrpP8dLXrllVfcfs8LJ0MXHn278IaGhUfhLsbTv1We/B2EbzHn4wpR+C3owm+5xd0ZsvBaeG/e4bRz584KDg7WjBkz3Mr/9re/lWt7PXv21Pr167Vx40a38uPHj2vOnDlq1apVmU5dFLfdAwcOaOHCha6yU6dO6Y033nCrl5KSokaNGunll18ucjheUpHLjItz6tSpIlf6NGrUSNWqVXO7tDc8PLzYsQgKCioyngsWLNB///vfi+67ONdff71q166t1157ze0Q+ezZs4vsv7j304YNG7Ru3bpit7148WK3dn3xxRfasGGD6yqjSxEeHl7q4fK7775bH3/8saZMmaKaNWt6vM969erp3nvv1dKlS0t8v/rqCJ+n+vXrp6CgII0fP75Im4wxrstJGzZsqC5duriWm2++uci25s2bp4KCgnIFriVLlkiSK7CmpKS47a958+aSfgu8QUFBWrNmjdvzp0+fXqb9lPS7URJP/g7CtzjycYWIjIxUu3btNHHiRJ09e1Z16tTRxx9/rOzs7CJ1U1JSJP12GePAgQNVpUoV9e7d+5Ju0BMbG6tHHnlEr7zyin7/+9+rR48e+uabb7R06VLVqlXL428wY8eO1YIFC9SuXTs99NBDatasmQ4cOKDZs2fr4MGDmjVrVrna+cADD+hvf/ub7rnnHm3cuFHx8fF65513FBYW5lYvMDBQM2fOVFpamlq0aKFhw4apTp06+u9//6tPP/1UkZGR+uCDD0rd1/fff6/OnTtrwIABat68uYKDg7Vo0SIdOnRIAwcOdNVLSUnRjBkz9MILL6hx48aKiYlRp06ddOutt+q5557TsGHDdNNNN2nr1q2aM2dOsfMzyqJKlSp64YUX9NBDD6lTp0668847lZ2drVmzZhXZ5q233qr3339fffv2Va9evZSdna3XXntNzZs3LzaMNW7cWLfccosefvhhOZ1OVxB44oknytXW86WkpGj+/PkaM2aMbrjhBkVERKh3796u9YMHD9YTTzyhRYsW6eGHH3bNe/DElClTlJ2drZEjR2revHnq3bu3YmJidOTIEa1du1YffPBBkXlB0m9jXNwpmdjYWLdblXtLo0aN9MILLygjI0N79uxRnz59VK1aNWVnZ2vRokV68MEH9dhjj5VpW3PmzFFCQsJF/6fPZ5995grRx44d0//7f/9PWVlZGjhwoOuUVUmioqJ0xx136K9//asCAgLUqFEjLVmypMhcjJKkpKTok08+0auvvqqEhAQ1aNBAbdq0KbG+J38H4WMVco0NfKrwMrOffvrJrXz//v2mb9++pnr16iYqKsrccccd5sCBA0aSGTdunFvd559/3tSpU8cEBga6XXZb0qW2X375pdvzi7uE7tdffzVPP/20iYuLM6GhoaZTp07mP//5j6lZs6YZPny4x/3cv3+/uf/++02dOnVMcHCwiY6ONrfeeqtZv359kbrt27c3LVq0KFI+ZMiQIpdp/vjjj+b3v/+9CQsLM7Vq1TKPPPKIWbZsWbGXBG7atMn069fP1KxZ0zgcDpOUlGQGDBhgVq5c6apT0ngcOXLEpKenm2bNmpnw8HATFRVl2rRp43aZrzG/Xabcq1cvU61aNbdLXk+fPm0effRREx8fb0JDQ83NN99s1q1bZ9q3b+92KWnhWCxYsMBtu8VdzmiMMdOnTzcNGjQwDofDXH/99WbNmjVFtllQUGBeeuklk5SUZBwOh7nuuuvMkiVLiryehfuYNGmSeeWVV0xiYqJxOBymbdu25ptvvnHbb3kvtT158qQZPHiwqV69upFU7GW3PXv2NJLM559/XmRdWf36669m1qxZplOnTiY6OtoEBwebWrVqmc6dO5vXXnvN/PLLL271Vcqltue/lt681LbQP//5T3PLLbeY8PBwEx4ebpo1a2bS09PNjh07ytTX7777zkgyY8aMKbFOcZfahoSEmGbNmpkXX3zRnDlzpkz7+umnn0z//v1NWFiYqVGjhnnooYfMtm3bynSp7XfffWfatWtnQkND3S7ZL+l3zhjP/g7CdwKMuUyOF+KKdPz4cdWoUUMvvPCC6yZagLf17dtXW7duLfaOrv6scIJy4RwLwF8w5wPWFHd1SuG51vL8u3agLA4ePKgPP/xQd999d0U3xesOHjxYrsnFQEVjzgesmT9/vmbPnq2ePXsqIiJC//73v/Xuu++qW7durglvOTk5pW7D1v0B4P+ys7O1du1azZw5U1WqVNFDDz1UpI6/vt9++OEHLVq0SAsWLPD4MljgckD4gDXJyckKDg7WxIkTlZeX55qE+sILL7jqxMfHl7qNwvsDABeTlZWlYcOGqV69enrrrbeKvfrJX99va9as0fjx49WhQwe9+uqrFd0cwGPM+cBl5ZNPPil1fUJCgusyPeBS8X4DKgbhAwAAWMWEUwAAYNVlN+ejoKBABw4cULVq1Xxym28AAOB9xhidOHFCCQkJrv+4XZLLLnwcOHBAiYmJFd0MAABQDvv27VPdunVLrXPZhY/Cf1+9b98+RUZGVnBrAABAWeTl5SkxMdH1OV6ayy58FJ5qiYyMJHwAAOBnyjJlggmnAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwKriiGwB4qv7YD32y3T0TevlkuwAAdxz5AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYJVH4WPGjBlKTk5WZGSkIiMjlZqaqqVLl7rWd+jQQQEBAW7L8OHDvd5oAADgv4I9qVy3bl1NmDBBTZo0kTFGb731lm677TZt2rRJLVq0kCQ98MADeu6551zPCQsL826LAQCAX/MofPTu3dvt8YsvvqgZM2Zo/fr1rvARFhamuLg477UQAABUKuWe83Hu3DnNmzdP+fn5Sk1NdZXPmTNHtWrVUsuWLZWRkaFTp06Vuh2n06m8vDy3BQAAVF4eHfmQpK1btyo1NVWnT59WRESEFi1apObNm0uSBg8erKSkJCUkJGjLli168skntWPHDr3//vslbi8zM1Pjx48vfw8AAIBfCTDGGE+ecObMGe3du1e5ublauHChZs6cqaysLFcAOd+qVavUuXNn7dq1S40aNSp2e06nU06n0/U4Ly9PiYmJys3NVWRkpIfdwZWg/tgPfbLdPRN6+WS7AHAlyMvLU1RUVJk+vz0+8hESEqLGjRtLklJSUvTll19q6tSpev3114vUbdOmjSSVGj4cDoccDoenzQAAAH7qku/zUVBQ4Hbk4nybN2+WJMXHx1/qbgAAQCXh0ZGPjIwMpaWlqV69ejpx4oTmzp2r1atXa/ny5dq9e7fmzp2rnj17qmbNmtqyZYtGjx6tdu3aKTk52VftBwAAfsaj8HH48GHdc889OnjwoKKiopScnKzly5era9eu2rdvnz755BNNmTJF+fn5SkxMVP/+/fXUU0/5qu0AAMAPeRQ+3nzzzRLXJSYmKisr65IbBAAAKjf+twsAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqj8LHjBkzlJycrMjISEVGRio1NVVLly51rT99+rTS09NVs2ZNRUREqH///jp06JDXGw0AAPyXR+Gjbt26mjBhgjZu3KivvvpKnTp10m233abt27dLkkaPHq0PPvhACxYsUFZWlg4cOKB+/fr5pOEAAMA/BRhjzKVsIDo6WpMmTdLtt9+u2rVra+7cubr99tslSd99952uvvpqrVu3TjfeeGOxz3c6nXI6na7HeXl5SkxMVG5uriIjIy+laaik6o/90Cfb3TOhl0+2CwBXgry8PEVFRZXp87vccz7OnTunefPmKT8/X6mpqdq4caPOnj2rLl26uOo0a9ZM9erV07p160rcTmZmpqKiolxLYmJieZsEAAD8gMfhY+vWrYqIiJDD4dDw4cO1aNEiNW/eXDk5OQoJCVH16tXd6sfGxionJ6fE7WVkZCg3N9e17Nu3z+NOAAAA/xHs6ROaNm2qzZs3Kzc3VwsXLtSQIUOUlZVV7gY4HA45HI5yPx8AAPgXj8NHSEiIGjduLElKSUnRl19+qalTp+rOO+/UmTNndPz4cbejH4cOHVJcXJzXGgwAAPzbJd/no6CgQE6nUykpKapSpYpWrlzpWrdjxw7t3btXqampl7obAABQSXh05CMjI0NpaWmqV6+eTpw4oblz52r16tVavny5oqKidN9992nMmDGKjo5WZGSkRo4cqdTU1BKvdAEAAFcej8LH4cOHdc899+jgwYOKiopScnKyli9frq5du0qSJk+erMDAQPXv319Op1Pdu3fX9OnTfdJwAADgny75Ph/e5sl1wrgycZ8PALj8WLnPBwAAQHkQPgAAgFUeX2oLALiy+erUp8TpzysFRz4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVnGTMQAALkOV+WZuHPkAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABglUfhIzMzUzfccIOqVaummJgY9enTRzt27HCr06FDBwUEBLgtw4cP92qjAQCA//IofGRlZSk9PV3r16/XihUrdPbsWXXr1k35+flu9R544AEdPHjQtUycONGrjQYAAP4r2JPKy5Ytc3s8e/ZsxcTEaOPGjWrXrp2rPCwsTHFxcd5pIQAAqFQuac5Hbm6uJCk6OtqtfM6cOapVq5ZatmypjIwMnTp1qsRtOJ1O5eXluS0AAKDy8ujIx/kKCgo0atQo3XzzzWrZsqWrfPDgwUpKSlJCQoK2bNmiJ598Ujt27ND7779f7HYyMzM1fvz48jYDAAD4mXKHj/T0dG3btk3//ve/3coffPBB18/XXHON4uPj1blzZ+3evVuNGjUqsp2MjAyNGTPG9TgvL0+JiYnlbRYAALjMlSt8jBgxQkuWLNGaNWtUt27dUuu2adNGkrRr165iw4fD4ZDD4ShPMwAAgB/yKHwYYzRy5EgtWrRIq1evVoMGDS76nM2bN0uS4uPjy9VAAABQuXgUPtLT0zV37lz961//UrVq1ZSTkyNJioqKUmhoqHbv3q25c+eqZ8+eqlmzprZs2aLRo0erXbt2Sk5O9kkHAACAf/EofMyYMUPSbzcSO9+sWbM0dOhQhYSE6JNPPtGUKVOUn5+vxMRE9e/fX0899ZTXGgwAAPybx6ddSpOYmKisrKxLahAAAKjc+N8uAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArPIofGRmZuqGG25QtWrVFBMToz59+mjHjh1udU6fPq309HTVrFlTERER6t+/vw4dOuTVRgMAAP/lUfjIyspSenq61q9frxUrVujs2bPq1q2b8vPzXXVGjx6tDz74QAsWLFBWVpYOHDigfv36eb3hAADAPwV7UnnZsmVuj2fPnq2YmBht3LhR7dq1U25urt58803NnTtXnTp1kiTNmjVLV199tdavX68bb7zRey0HAAB+6ZLmfOTm5kqSoqOjJUkbN27U2bNn1aVLF1edZs2aqV69elq3bl2x23A6ncrLy3NbAABA5VXu8FFQUKBRo0bp5ptvVsuWLSVJOTk5CgkJUfXq1d3qxsbGKicnp9jtZGZmKioqyrUkJiaWt0kAAMAPlDt8pKena9u2bZo3b94lNSAjI0O5ubmuZd++fZe0PQAAcHnzaM5HoREjRmjJkiVas2aN6tat6yqPi4vTmTNndPz4cbejH4cOHVJcXFyx23I4HHI4HOVpBgAA8EMeHfkwxmjEiBFatGiRVq1apQYNGritT0lJUZUqVbRy5UpX2Y4dO7R3716lpqZ6p8UAAMCveXTkIz09XXPnztW//vUvVatWzTWPIyoqSqGhoYqKitJ9992nMWPGKDo6WpGRkRo5cqRSU1O50gUAAEjyMHzMmDFDktShQwe38lmzZmno0KGSpMmTJyswMFD9+/eX0+lU9+7dNX36dK80FgAA+D+Pwocx5qJ1qlatqmnTpmnatGnlbhQAAKi8+N8uAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCrCBwAAsIrwAQAArPI4fKxZs0a9e/dWQkKCAgICtHjxYrf1Q4cOVUBAgNvSo0cPb7UXAAD4OY/DR35+vq699lpNmzatxDo9evTQwYMHXcu77757SY0EAACVR7CnT0hLS1NaWlqpdRwOh+Li4srdKAAAUHn5ZM7H6tWrFRMTo6ZNm+rhhx/W0aNHS6zrdDqVl5fntgAAgMrL6+GjR48eevvtt7Vy5Ur95S9/UVZWltLS0nTu3Lli62dmZioqKsq1JCYmertJAADgMuLxaZeLGThwoOvna665RsnJyWrUqJFWr16tzp07F6mfkZGhMWPGuB7n5eURQAAAqMR8fqltw4YNVatWLe3atavY9Q6HQ5GRkW4LAACovHwePvbv36+jR48qPj7e17sCAAB+wOPTLidPnnQ7ipGdna3NmzcrOjpa0dHRGj9+vPr376+4uDjt3r1bTzzxhBo3bqzu3bt7teEAAMA/eRw+vvrqK3Xs2NH1uHC+xpAhQzRjxgxt2bJFb731lo4fP66EhAR169ZNzz//vBwOh/daDQAA/JbH4aNDhw4yxpS4fvny5ZfUIAAAULnxv10AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWeRw+1qxZo969eyshIUEBAQFavHix23pjjJ555hnFx8crNDRUXbp00c6dO73VXgAA4Oc8Dh/5+fm69tprNW3atGLXT5w4Uf/3f/+n1157TRs2bFB4eLi6d++u06dPX3JjAQCA/wv29AlpaWlKS0srdp0xRlOmTNFTTz2l2267TZL09ttvKzY2VosXL9bAgQMvrbUAAMDveXXOR3Z2tnJyctSlSxdXWVRUlNq0aaN169YV+xyn06m8vDy3BQAAVF5eDR85OTmSpNjYWLfy2NhY17oLZWZmKioqyrUkJiZ6s0kAAOAyU+FXu2RkZCg3N9e17Nu3r6KbBAAAfMir4SMuLk6SdOjQIbfyQ4cOudZdyOFwKDIy0m0BAACVl1fDR4MGDRQXF6eVK1e6yvLy8rRhwwalpqZ6c1cAAMBPeXy1y8mTJ7Vr1y7X4+zsbG3evFnR0dGqV6+eRo0apRdeeEFNmjRRgwYN9PTTTyshIUF9+vTxZrsBAICf8jh8fPXVV+rYsaPr8ZgxYyRJQ4YM0ezZs/XEE08oPz9fDz74oI4fP65bbrlFy5YtU9WqVb3XagAA4Lc8Dh8dOnSQMabE9QEBAXruuef03HPPXVLDAABA5VThV7sAAIArC+EDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVnk9fDz77LMKCAhwW5o1a+bt3QAAAD8V7IuNtmjRQp988sn/dhLsk90AAAA/5JNUEBwcrLi4OF9sGgAA+DmfzPnYuXOnEhIS1LBhQ911113au3dviXWdTqfy8vLcFgAAUHl5PXy0adNGs2fP1rJlyzRjxgxlZ2erbdu2OnHiRLH1MzMzFRUV5VoSExO93SQAAHAZ8Xr4SEtL0x133KHk5GR1795dH330kY4fP6733nuv2PoZGRnKzc11Lfv27fN2kwAAwGXE5zNBq1evrquuukq7du0qdr3D4ZDD4fB1MwAAwGXC5/f5OHnypHbv3q34+Hhf7woAAPgBr4ePxx57TFlZWdqzZ48+//xz9e3bV0FBQRo0aJC3dwUAAPyQ10+77N+/X4MGDdLRo0dVu3Zt3XLLLVq/fr1q167t7V0BAAA/5PXwMW/ePG9vEgAAVCL8bxcAAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYBXhAwAAWEX4AAAAVhE+AACAVYQPAABgFeEDAABYRfgAAABWef1/uwBAaeqP/dBn294zoZfPtg3AezjyAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKy64u5w6qu7K3JnRQAAyoYjHwAAwCrCBwAAsIrwAQAArCJ8AAAAqwgfAADAKsIHAACwivABAACsInwAAACrCB8AAMAqwgcAALCK8AEAAKwifAAAAKsIHwAAwCqfhY9p06apfv36qlq1qtq0aaMvvvjCV7sCAAB+xCfhY/78+RozZozGjRunr7/+Wtdee626d++uw4cP+2J3AADAj/gkfLz66qt64IEHNGzYMDVv3lyvvfaawsLC9Pe//90XuwMAAH4k2NsbPHPmjDZu3KiMjAxXWWBgoLp06aJ169YVqe90OuV0Ol2Pc3NzJUl5eXnebpokqcB5yifb9VV7URRj6N98NX4SY2gLY2iHv73Ohds0xly0rtfDx5EjR3Tu3DnFxsa6lcfGxuq7774rUj8zM1Pjx48vUp6YmOjtpvlU1JSKbgEuFWPo/xhD/8cY2uHL1/nEiROKiooqtY7Xw4enMjIyNGbMGNfjgoICHTt2TDVr1lRAQIBX95WXl6fExETt27dPkZGRXt325aCy90+q/H2kf/6vsveR/vk/X/XRGKMTJ04oISHhonW9Hj5q1aqloKAgHTp0yK380KFDiouLK1Lf4XDI4XC4lVWvXt3bzXITGRlZad9UUuXvn1T5+0j//F9l7yP983++6OPFjngU8vqE05CQEKWkpGjlypWusoKCAq1cuVKpqane3h0AAPAzPjntMmbMGA0ZMkTXX3+9WrdurSlTpig/P1/Dhg3zxe4AAIAf8Un4uPPOO/XTTz/pmWeeUU5Ojlq1aqVly5YVmYRqm8Ph0Lhx44qc5qksKnv/pMrfR/rn/yp7H+mf/7sc+hhgynJNDAAAgJfwv10AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWVJnysWbNGvXv3VkJCggICArR48eKLPmf16tX63e9+J4fDocaNG2v27Nk+b+el8LSPq1evVkBAQJElJyfHToM9lJmZqRtuuEHVqlVTTEyM+vTpox07dlz0eQsWLFCzZs1UtWpVXXPNNfroo48stNZz5enf7Nmzi4xf1apVLbXYMzNmzFBycrLrrompqalaunRpqc/xl7Er5Gkf/Wn8ijNhwgQFBARo1KhRpdbzt3EsVJb++dsYPvvss0Xa26xZs1KfUxHjV2nCR35+vq699lpNmzatTPWzs7PVq1cvdezYUZs3b9aoUaN0//33a/ny5T5uafl52sdCO3bs0MGDB11LTEyMj1p4abKyspSenq7169drxYoVOnv2rLp166b8/PwSn/P5559r0KBBuu+++7Rp0yb16dNHffr00bZt2yy2vGzK0z/pt1sgnz9+P/74o6UWe6Zu3bqaMGGCNm7cqK+++kqdOnXSbbfdpu3btxdb35/GrpCnfZT8Z/wu9OWXX+r1119XcnJyqfX8cRylsvdP8r8xbNGihVt7//3vf5dYt8LGz1RCksyiRYtKrfPEE0+YFi1auJXdeeedpnv37j5smfeUpY+ffvqpkWR+/vlnK23ytsOHDxtJJisrq8Q6AwYMML169XIra9OmjXnooYd83bxLVpb+zZo1y0RFRdlrlJfVqFHDzJw5s9h1/jx25yutj/46fidOnDBNmjQxK1asMO3btzePPPJIiXX9cRw96Z+/jeG4cePMtddeW+b6FTV+lebIh6fWrVunLl26uJV1795d69atq6AW+U6rVq0UHx+vrl27au3atRXdnDLLzc2VJEVHR5dYx5/HsSz9k6STJ08qKSlJiYmJF/2Wfbk4d+6c5s2bp/z8/BL/p5M/j51Utj5K/jl+6enp6tWrV5HxKY4/jqMn/ZP8bwx37typhIQENWzYUHfddZf27t1bYt2KGj+f3F7dH+Tk5BS53XtsbKzy8vL0yy+/KDQ0tIJa5j3x8fF67bXXdP3118vpdGrmzJnq0KGDNmzYoN/97ncV3bxSFRQUaNSoUbr55pvVsmXLEuuVNI6X67yWQmXtX9OmTfX3v/9dycnJys3N1csvv6ybbrpJ27dvV926dS22uGy2bt2q1NRUnT59WhEREVq0aJGaN29ebF1/HTtP+uhv4ydJ8+bN09dff60vv/yyTPX9bRw97Z+/jWGbNm00e/ZsNW3aVAcPHtT48ePVtm1bbdu2TdWqVStSv6LG74oNH1eCpk2bqmnTpq7HN910k3bv3q3JkyfrnXfeqcCWXVx6erq2bdtW6rlKf1bW/qWmprp9q77pppt09dVX6/XXX9fzzz/v62Z6rGnTptq8ebNyc3O1cOFCDRkyRFlZWSV+OPsjT/rob+O3b98+PfLII1qxYsVlPamyvMrTP38bw7S0NNfPycnJatOmjZKSkvTee+/pvvvuq8CWubtiw0dcXJwOHTrkVnbo0CFFRkZWiqMeJWnduvVl/4E+YsQILVmyRGvWrLnoN4uSxjEuLs6XTbwknvTvQlWqVNF1112nXbt2+ah1lyYkJESNGzeWJKWkpOjLL7/U1KlT9frrrxep649jJ3nWxwtd7uO3ceNGHT582O3I6Llz57RmzRr97W9/k9PpVFBQkNtz/Gkcy9O/C13uY3ih6tWr66qrriqxvRU1flfsnI/U1FStXLnSrWzFihWlnrutDDZv3qz4+PiKbkaxjDEaMWKEFi1apFWrVqlBgwYXfY4/jWN5+nehc+fOaevWrZftGF6ooKBATqez2HX+NHalKa2PF7rcx69z587aunWrNm/e7Fquv/563XXXXdq8eXOxH8z+NI7l6d+FLvcxvNDJkye1e/fuEttbYePn0+msFp04ccJs2rTJbNq0yUgyr776qtm0aZP58ccfjTHGjB071tx9992u+j/88IMJCwszjz/+uPnPf/5jpk2bZoKCgsyyZcsqqgsX5WkfJ0+ebBYvXmx27txptm7dah555BETGBhoPvnkk4rqQqkefvhhExUVZVavXm0OHjzoWk6dOuWqc/fdd5uxY8e6Hq9du9YEBwebl19+2fznP/8x48aNM1WqVDFbt26tiC6Uqjz9Gz9+vFm+fLnZvXu32bhxoxk4cKCpWrWq2b59e0V0oVRjx441WVlZJjs722zZssWMHTvWBAQEmI8//tgY499jV8jTPvrT+JXkwqtBKsM4nu9i/fO3MXz00UfN6tWrTXZ2tlm7dq3p0qWLqVWrljl8+LAx5vIZv0oTPgovK71wGTJkiDHGmCFDhpj27dsXeU6rVq1MSEiIadiwoZk1a5b1dnvC0z7+5S9/MY0aNTJVq1Y10dHRpkOHDmbVqlUV0/gyKK5vktzGpX379q7+FnrvvffMVVddZUJCQkyLFi3Mhx9+aLfhZVSe/o0aNcrUq1fPhISEmNjYWNOzZ0/z9ddf2298Gdx7770mKSnJhISEmNq1a5vOnTu7PpSN8e+xK+RpH/1p/Epy4YdzZRjH812sf/42hnfeeaeJj483ISEhpk6dOubOO+80u3btcq2/XMYvwBhjfHtsBQAA4H+u2DkfAACgYhA+AACAVYQPAABgFeEDAABYRfgAAABWET4AAIBVhA8AAGAV4QMAAFhF+AAAAFYRPgAAgFWEDwAAYNX/B4+ynWwqEiwoAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# create histograms\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "def plot_histogram(column):\n",
    "    values = [x[column] for x in ds_processed[\"train\"] if x[column]]\n",
    "    plt.hist(values, bins=20)\n",
    "    plt.title(column)\n",
    "    plt.show()\n",
    "\n",
    "for column in columns_nl+[\"average_score_nl\"] + columns_en+[\"average_score_en\"]:\n",
    "    plot_histogram(column)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between rating_Helpfulness_gpt-4-turbo and rating_Understandability_gpt-4-turbo: 0.63\n",
      "Correlation between rating_Helpfulness_gpt-4-turbo and rating_Completeness_gpt-4-turbo: 0.64\n",
      "Correlation between rating_Helpfulness_gpt-4-turbo and rating_Conciseness_gpt-4-turbo: 0.40\n",
      "Correlation between rating_Helpfulness_gpt-4-turbo and rating_dutchness_gpt-4-turbo: 0.39\n",
      "Correlation between rating_Understandability_gpt-4-turbo and rating_Helpfulness_gpt-4-turbo: 0.63\n",
      "Correlation between rating_Understandability_gpt-4-turbo and rating_Completeness_gpt-4-turbo: 0.57\n",
      "Correlation between rating_Understandability_gpt-4-turbo and rating_Conciseness_gpt-4-turbo: 0.52\n",
      "Correlation between rating_Understandability_gpt-4-turbo and rating_dutchness_gpt-4-turbo: 0.57\n",
      "Correlation between rating_Completeness_gpt-4-turbo and rating_Helpfulness_gpt-4-turbo: 0.64\n",
      "Correlation between rating_Completeness_gpt-4-turbo and rating_Understandability_gpt-4-turbo: 0.57\n",
      "Correlation between rating_Completeness_gpt-4-turbo and rating_Conciseness_gpt-4-turbo: 0.36\n",
      "Correlation between rating_Completeness_gpt-4-turbo and rating_dutchness_gpt-4-turbo: 0.48\n",
      "Correlation between rating_Conciseness_gpt-4-turbo and rating_Helpfulness_gpt-4-turbo: 0.40\n",
      "Correlation between rating_Conciseness_gpt-4-turbo and rating_Understandability_gpt-4-turbo: 0.52\n",
      "Correlation between rating_Conciseness_gpt-4-turbo and rating_Completeness_gpt-4-turbo: 0.36\n",
      "Correlation between rating_Conciseness_gpt-4-turbo and rating_dutchness_gpt-4-turbo: 0.29\n",
      "Correlation between rating_dutchness_gpt-4-turbo and rating_Helpfulness_gpt-4-turbo: 0.39\n",
      "Correlation between rating_dutchness_gpt-4-turbo and rating_Understandability_gpt-4-turbo: 0.57\n",
      "Correlation between rating_dutchness_gpt-4-turbo and rating_Completeness_gpt-4-turbo: 0.48\n",
      "Correlation between rating_dutchness_gpt-4-turbo and rating_Conciseness_gpt-4-turbo: 0.29\n"
     ]
    }
   ],
   "source": [
    "import numpy as np\n",
    "def compute_column_correlation(col_x, col_y):\n",
    "    values_x = []\n",
    "    values_y = []\n",
    "    for x, y in zip(ds_processed[\"train\"], ds_processed[\"train\"]):\n",
    "        if x[col_x] and y[col_y]:\n",
    "            values_x.append(x[col_x])\n",
    "            values_y.append(y[col_y])\n",
    "\n",
    "    return np.corrcoef(values_x, values_y)[0, 1]\n",
    "\n",
    "for column_x in columns_en:\n",
    "    for column_y in columns_en:\n",
    "        if not column_x == column_y:\n",
    "            correlation = compute_column_correlation(column_x, column_y)\n",
    "            print(f\"Correlation between {column_x} and {column_y}: {correlation:.2f}\")\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": ".venv",
   "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": "3.10.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}