diff --git "a/Untitled1.ipynb" "b/Untitled1.ipynb"
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+++ "b/Untitled1.ipynb"
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 23644,
+     "status": "ok",
+     "timestamp": 1669576254858,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "1jUAOZGjfYt8",
+    "outputId": "11f8fd4f-1229-4ce4-96cf-6662f2c706b1"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Defaulting to user installation because normal site-packages is not writeable\n",
+      "Requirement already satisfied: datasets in /home/user/.local/lib/python3.10/site-packages (2.6.1)\n",
+      "Requirement already satisfied: transformers in /home/user/.local/lib/python3.10/site-packages (4.20.0)\n",
+      "Requirement already satisfied: rouge-score in /home/user/.local/lib/python3.10/site-packages (0.1.2)\n",
+      "Requirement already satisfied: nltk in /home/user/.local/lib/python3.10/site-packages (3.7)\n",
+      "Requirement already satisfied: requests>=2.19.0 in /usr/lib/python3/dist-packages (from datasets) (2.25.1)\n",
+      "Requirement already satisfied: pyyaml>=5.1 in /usr/lib/python3/dist-packages (from datasets) (5.4.1)\n",
+      "Requirement already satisfied: dill<0.3.6 in /home/user/.local/lib/python3.10/site-packages (from datasets) (0.3.5.1)\n",
+      "Requirement already satisfied: numpy>=1.17 in /home/user/.local/lib/python3.10/site-packages (from datasets) (1.23.3)\n",
+      "Requirement already satisfied: xxhash in /home/user/.local/lib/python3.10/site-packages (from datasets) (3.1.0)\n",
+      "Requirement already satisfied: pandas in /home/user/.local/lib/python3.10/site-packages (from datasets) (1.5.0)\n",
+      "Requirement already satisfied: aiohttp in /home/user/.local/lib/python3.10/site-packages (from datasets) (3.8.3)\n",
+      "Requirement already satisfied: responses<0.19 in /home/user/.local/lib/python3.10/site-packages (from datasets) (0.18.0)\n",
+      "Requirement already satisfied: pyarrow>=6.0.0 in /home/user/.local/lib/python3.10/site-packages (from datasets) (10.0.0)\n",
+      "Requirement already satisfied: multiprocess in /home/user/.local/lib/python3.10/site-packages (from datasets) (0.70.13)\n",
+      "Requirement already satisfied: fsspec[http]>=2021.11.1 in /home/user/.local/lib/python3.10/site-packages (from datasets) (2022.10.0)\n",
+      "Requirement already satisfied: packaging in /home/user/.local/lib/python3.10/site-packages (from datasets) (21.3)\n",
+      "Requirement already satisfied: tqdm>=4.62.1 in /home/user/.local/lib/python3.10/site-packages (from datasets) (4.64.1)\n",
+      "Requirement already satisfied: huggingface-hub<1.0.0,>=0.2.0 in /home/user/.local/lib/python3.10/site-packages (from datasets) (0.10.1)\n",
+      "Requirement already satisfied: tokenizers!=0.11.3,<0.13,>=0.11.1 in /home/user/.local/lib/python3.10/site-packages (from transformers) (0.12.1)\n",
+      "Requirement already satisfied: filelock in /usr/lib/python3/dist-packages (from transformers) (3.6.0)\n",
+      "Requirement already satisfied: regex!=2019.12.17 in /home/user/.local/lib/python3.10/site-packages (from transformers) (2022.9.13)\n",
+      "Requirement already satisfied: six>=1.14.0 in /usr/lib/python3/dist-packages (from rouge-score) (1.16.0)\n",
+      "Requirement already satisfied: absl-py in /home/user/.local/lib/python3.10/site-packages (from rouge-score) (1.2.0)\n",
+      "Requirement already satisfied: joblib in /home/user/.local/lib/python3.10/site-packages (from nltk) (1.2.0)\n",
+      "Requirement already satisfied: click in /usr/lib/python3/dist-packages (from nltk) (8.0.3)\n",
+      "Requirement already satisfied: multidict<7.0,>=4.5 in /home/user/.local/lib/python3.10/site-packages (from aiohttp->datasets) (6.0.2)\n",
+      "Requirement already satisfied: aiosignal>=1.1.2 in /home/user/.local/lib/python3.10/site-packages (from aiohttp->datasets) (1.2.0)\n",
+      "Requirement already satisfied: charset-normalizer<3.0,>=2.0 in /home/user/.local/lib/python3.10/site-packages (from aiohttp->datasets) (2.1.1)\n",
+      "Requirement already satisfied: frozenlist>=1.1.1 in /home/user/.local/lib/python3.10/site-packages (from aiohttp->datasets) (1.3.1)\n",
+      "Requirement already satisfied: async-timeout<5.0,>=4.0.0a3 in /home/user/.local/lib/python3.10/site-packages (from aiohttp->datasets) (4.0.2)\n",
+      "Requirement already satisfied: attrs>=17.3.0 in /home/user/.local/lib/python3.10/site-packages (from aiohttp->datasets) (22.1.0)\n",
+      "Requirement already satisfied: yarl<2.0,>=1.0 in /home/user/.local/lib/python3.10/site-packages (from aiohttp->datasets) (1.8.1)\n",
+      "Requirement already satisfied: typing-extensions>=3.7.4.3 in /home/user/.local/lib/python3.10/site-packages (from huggingface-hub<1.0.0,>=0.2.0->datasets) (4.4.0)\n",
+      "Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/lib/python3/dist-packages (from packaging->datasets) (2.4.7)\n",
+      "Requirement already satisfied: urllib3>=1.25.10 in /usr/lib/python3/dist-packages (from responses<0.19->datasets) (1.26.5)\n",
+      "Requirement already satisfied: python-dateutil>=2.8.1 in /home/user/.local/lib/python3.10/site-packages (from pandas->datasets) (2.8.2)\n",
+      "Requirement already satisfied: pytz>=2020.1 in /usr/lib/python3/dist-packages (from pandas->datasets) (2022.1)\n",
+      "Requirement already satisfied: idna>=2.0 in /usr/lib/python3/dist-packages (from yarl<2.0,>=1.0->aiohttp->datasets) (3.3)\n"
+     ]
+    }
+   ],
+   "source": [
+    "! pip install datasets transformers rouge-score nltk"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 331,
+     "referenced_widgets": [
+      "c38b3a29bdb24edf9f9ffc2a1d7ea136",
+      "bd4317d0cace4fa8a9d4e6f55643457f",
+      "1458810480da42cc81793be5af19d9fd",
+      "8a1d2e60bee942129dad6a705ed03aa5",
+      "a6f0d0297c6347c9a271bf33c27d3e8e",
+      "80ed1d76abc34b0a9d95d937eae6b626",
+      "3b9d888697984453978d8b82e167a7cd",
+      "5468607c66ac4a5d893b66de7803a1da",
+      "ec07fb7fa6754fe3ad81d7e8a128fac3",
+      "bd84f71efa3942b69c337203376d6f9d",
+      "50339a3619674663958b9cacc42224b0",
+      "8916adf78ef54b1b80e04a3a4f9bdf8c",
+      "a6bd07e3118f42e79e1b3d7675dd28e3",
+      "14946c0a0b124448aec12ab62adecee9",
+      "c7630aea76ff4160a20578c22f8e97e8",
+      "75149305e7614e0b84cbebb12fc7340b",
+      "f3fd3ead9fb44d0d9616d89b1992c7ba"
+     ]
+    },
+    "executionInfo": {
+     "elapsed": 333,
+     "status": "ok",
+     "timestamp": 1669576266320,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "6IuXlV3Ffanz",
+    "outputId": "bb952e77-9ef9-482e-c532-502b9b20462c"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Login successful\n",
+      "Your token has been saved to /home/user/.huggingface/token\n",
+      "\u001b[1m\u001b[31mAuthenticated through git-credential store but this isn't the helper defined on your machine.\n",
+      "You might have to re-authenticate when pushing to the Hugging Face Hub. Run the following command in your terminal in case you want to set this credential helper as the default\n",
+      "\n",
+      "git config --global credential.helper store\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "from huggingface_hub import notebook_login\n",
+    "\n",
+    "notebook_login()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "!git config --global credential.helper store\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 1875,
+     "status": "ok",
+     "timestamp": 1669576287294,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "zA3LmEG9fu80",
+    "outputId": "f9583b3c-db03-41e0-b153-b912a0020595"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[1;31mE: \u001b[0mCould not open lock file /var/lib/dpkg/lock-frontend - open (13: Permission denied)\u001b[0m\r\n",
+      "\u001b[1;31mE: \u001b[0mUnable to acquire the dpkg frontend lock (/var/lib/dpkg/lock-frontend), are you root?\u001b[0m\r\n"
+     ]
+    }
+   ],
+   "source": [
+    "!apt install git-lfs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 2483,
+     "status": "ok",
+     "timestamp": 1669576292029,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "50K-4gBfgGRh",
+    "outputId": "cf0ee968-30ef-44cc-e00c-1401fd6efe09"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "4.20.0\n"
+     ]
+    }
+   ],
+   "source": [
+    "import transformers\n",
+    "\n",
+    "print(transformers.__version__)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {
+    "executionInfo": {
+     "elapsed": 358,
+     "status": "ok",
+     "timestamp": 1669576294061,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "ymFBPi-XgJ0_"
+   },
+   "outputs": [],
+   "source": [
+    "model_checkpoint = 'facebook/bart-large-cnn'"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 712,
+     "referenced_widgets": [
+      "d2e8b31a5ff34826a0a9add966b3a612",
+      "522be447cd3a49e5abc09c438405dd2c",
+      "179dd0a736aa470a993585febe5c1462",
+      "4e3e2875eb2b47abbdfd0994a1a1ab77",
+      "56ac28edb6ca4415ba964f42d4d27bed",
+      "83d334d4b71e4c07a1fc3dac8115f948",
+      "c1aa4ce82ce44a6fbe342d6f9d27ace3",
+      "6ff11cd026154544bee3ea10ceff2c2d",
+      "3aef5fca9d01411dbf02c42bb9edd293",
+      "fa597dbb89aa4f5fac6cc6e0a9859d59",
+      "867595abfc9c4dd28a19346afb584534"
+     ]
+    },
+    "executionInfo": {
+     "elapsed": 2879,
+     "status": "ok",
+     "timestamp": 1669576300418,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "57B0I_4zguys",
+    "outputId": "0945df5a-9aee-4441-b006-55d10db99374"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/tmp/ipykernel_47026/939338506.py:3: FutureWarning: load_metric is deprecated and will be removed in the next major version of datasets. Use 'evaluate.load' instead, from the new library 🤗 Evaluate: https://huggingface.co/docs/evaluate\n",
+      "  load_metric('rouge')\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "c802d13e0abb4a44a77e3cb10af6651e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading builder script:   0%|          | 0.00/2.16k [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Metric(name: \"rouge\", features: {'predictions': Value(dtype='string', id='sequence'), 'references': Value(dtype='string', id='sequence')}, usage: \"\"\"\n",
+       "Calculates average rouge scores for a list of hypotheses and references\n",
+       "Args:\n",
+       "    predictions: list of predictions to score. Each prediction\n",
+       "        should be a string with tokens separated by spaces.\n",
+       "    references: list of reference for each prediction. Each\n",
+       "        reference should be a string with tokens separated by spaces.\n",
+       "    rouge_types: A list of rouge types to calculate.\n",
+       "        Valid names:\n",
+       "        `\"rouge{n}\"` (e.g. `\"rouge1\"`, `\"rouge2\"`) where: {n} is the n-gram based scoring,\n",
+       "        `\"rougeL\"`: Longest common subsequence based scoring.\n",
+       "        `\"rougeLSum\"`: rougeLsum splits text using `\"\n",
+       "\"`.\n",
+       "        See details in https://github.com/huggingface/datasets/issues/617\n",
+       "    use_stemmer: Bool indicating whether Porter stemmer should be used to strip word suffixes.\n",
+       "    use_aggregator: Return aggregates if this is set to True\n",
+       "Returns:\n",
+       "    rouge1: rouge_1 (precision, recall, f1),\n",
+       "    rouge2: rouge_2 (precision, recall, f1),\n",
+       "    rougeL: rouge_l (precision, recall, f1),\n",
+       "    rougeLsum: rouge_lsum (precision, recall, f1)\n",
+       "Examples:\n",
+       "\n",
+       "    >>> rouge = datasets.load_metric('rouge')\n",
+       "    >>> predictions = [\"hello there\", \"general kenobi\"]\n",
+       "    >>> references = [\"hello there\", \"general kenobi\"]\n",
+       "    >>> results = rouge.compute(predictions=predictions, references=references)\n",
+       "    >>> print(list(results.keys()))\n",
+       "    ['rouge1', 'rouge2', 'rougeL', 'rougeLsum']\n",
+       "    >>> print(results[\"rouge1\"])\n",
+       "    AggregateScore(low=Score(precision=1.0, recall=1.0, fmeasure=1.0), mid=Score(precision=1.0, recall=1.0, fmeasure=1.0), high=Score(precision=1.0, recall=1.0, fmeasure=1.0))\n",
+       "    >>> print(results[\"rouge1\"].mid.fmeasure)\n",
+       "    1.0\n",
+       "\"\"\", stored examples: 0)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from datasets import load_dataset, load_metric\n",
+    "\n",
+    "load_metric('rouge')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 912,
+     "status": "ok",
+     "timestamp": 1669576305170,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "ycjFViueiC1x",
+    "outputId": "d982e6dd-79ee-4ffb-abe7-89002fd2d7bc"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "[nltk_data] Downloading package punkt to /home/user/nltk_data...\n",
+      "[nltk_data]   Package punkt is already up-to-date!\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "True"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "import numpy as np\n",
+    "import nltk\n",
+    "nltk.download('punkt')\n",
+    "  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {
+    "executionInfo": {
+     "elapsed": 354,
+     "status": "ok",
+     "timestamp": 1669576330301,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "YHBxeIxlhJ-t"
+   },
+   "outputs": [],
+   "source": [
+    "result = pd.read_csv('results.csv')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {
+    "executionInfo": {
+     "elapsed": 303,
+     "status": "ok",
+     "timestamp": 1669576335012,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "Gq6dBpcsiAKS"
+   },
+   "outputs": [],
+   "source": [
+    "red_panel = pd.read_csv('red_panel.csv')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 424
+    },
+    "executionInfo": {
+     "elapsed": 323,
+     "status": "ok",
+     "timestamp": 1669576337691,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "NaXyZezfi8jZ",
+    "outputId": "fd7cec48-c512-45b7-f9d1-4f5face4e677"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>red_panel_text_box_body</th>\n",
+       "      <th>Unnamed: 1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>The numerical model, was able to predict a rea...</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>Lines with recessive ppd-H1 presented delayed ...</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>Tumor- but not macrophage-derived PGRN is asso...</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>A total of 449 BCs were analyzed.Sensitivities...</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Factors for non-adherent behavior were examine...</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90</th>\n",
+       "      <td>Results: The mean age of participants was 50 y...</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91</th>\n",
+       "      <td>NaN</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>92</th>\n",
+       "      <td>Subjects with reduced left ventricular systoli...</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>93</th>\n",
+       "      <td>Results A total of 47 722 new cases were repor...</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>94</th>\n",
+       "      <td>In isolated hearts, CPT showed a biphasic effe...</td>\n",
+       "      <td>NaN</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>95 rows × 2 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                              red_panel_text_box_body Unnamed: 1\n",
+       "0   The numerical model, was able to predict a rea...        NaN\n",
+       "1   Lines with recessive ppd-H1 presented delayed ...        NaN\n",
+       "2   Tumor- but not macrophage-derived PGRN is asso...        NaN\n",
+       "3   A total of 449 BCs were analyzed.Sensitivities...        NaN\n",
+       "4   Factors for non-adherent behavior were examine...        NaN\n",
+       "..                                                ...        ...\n",
+       "90  Results: The mean age of participants was 50 y...        NaN\n",
+       "91                                                NaN        NaN\n",
+       "92  Subjects with reduced left ventricular systoli...        NaN\n",
+       "93  Results A total of 47 722 new cases were repor...        NaN\n",
+       "94  In isolated hearts, CPT showed a biphasic effe...        NaN\n",
+       "\n",
+       "[95 rows x 2 columns]"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 424
+    },
+    "executionInfo": {
+     "elapsed": 422,
+     "status": "ok",
+     "timestamp": 1669576343162,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "5sIYZmxljbdD",
+    "outputId": "7f44fed4-8329-4341-87a5-b34ddedb62cb"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>red_panel_text_box_body</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>For metaphyseal fracture healing in the distal...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>For breeding of high-yielding cultivars with s...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>In pancreatic ductal adenocarcinoma: We show a...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>For the detection of frequent Gram-negatives d...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>Patients with cluster headache:  Tended to hav...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>90</th>\n",
+       "      <td>After bariatric surgery: Reduced anti-apoA-1 I...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>91</th>\n",
+       "      <td>For children/young adults with diabetes and di...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>92</th>\n",
+       "      <td>In dilated cardiomyopathy: Advanced flow imagi...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>93</th>\n",
+       "      <td>For COVID-19: Approximately 85% of the Chinese...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>94</th>\n",
+       "      <td>In the heart: CPT may affect contraction and a...</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>95 rows × 1 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                              red_panel_text_box_body\n",
+       "0   For metaphyseal fracture healing in the distal...\n",
+       "1   For breeding of high-yielding cultivars with s...\n",
+       "2   In pancreatic ductal adenocarcinoma: We show a...\n",
+       "3   For the detection of frequent Gram-negatives d...\n",
+       "4   Patients with cluster headache:  Tended to hav...\n",
+       "..                                                ...\n",
+       "90  After bariatric surgery: Reduced anti-apoA-1 I...\n",
+       "91  For children/young adults with diabetes and di...\n",
+       "92  In dilated cardiomyopathy: Advanced flow imagi...\n",
+       "93  For COVID-19: Approximately 85% of the Chinese...\n",
+       "94  In the heart: CPT may affect contraction and a...\n",
+       "\n",
+       "[95 rows x 1 columns]"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "red_panel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {
+    "executionInfo": {
+     "elapsed": 414,
+     "status": "ok",
+     "timestamp": 1669576345836,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "Wlchlv9ejd_J"
+   },
+   "outputs": [],
+   "source": [
+    "import datasets\n",
+    "import random\n",
+    "import pandas as pd\n",
+    "from IPython.display import display, HTML\n",
+    "\n",
+    "def show_random_elements(dataset, num_examples=5):\n",
+    "    assert num_examples <= len(dataset), \"Can't pick more elements than there are in the dataset.\"\n",
+    "    picks = []\n",
+    "    for _ in range(num_examples):\n",
+    "        pick = random.randint(0, len(dataset)-1)\n",
+    "        while pick in picks:\n",
+    "            pick = random.randint(0, len(dataset)-1)\n",
+    "        picks.append(pick)\n",
+    "    \n",
+    "    df = pd.DataFrame(dataset[picks])\n",
+    "    for column, typ in dataset.features.items():\n",
+    "        if isinstance(typ, datasets.ClassLabel):\n",
+    "            df[column] = df[column].transform(lambda i: typ.names[i])\n",
+    "    display(HTML(df.to_html()))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 313,
+     "status": "ok",
+     "timestamp": 1669576349464,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "wVadlxpikhyQ",
+    "outputId": "c2ce7fad-8455-4705-970c-6e31910bfac6"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "95"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "len(result)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 313
+    },
+    "executionInfo": {
+     "elapsed": 385,
+     "status": "error",
+     "timestamp": 1669576351222,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "VD4OhkhBj7eT",
+    "outputId": "7b7ec7fd-8f06-4550-f6fa-0f6c78e737cb"
+   },
+   "outputs": [
+    {
+     "ename": "KeyError",
+     "evalue": "\"None of [Int64Index([53, 82, 92, 63, 6], dtype='int64')] are in the [columns]\"",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn [16], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mshow_random_elements\u001b[49m\u001b[43m(\u001b[49m\u001b[43mresult\u001b[49m\u001b[43m)\u001b[49m\n",
+      "Cell \u001b[0;32mIn [14], line 15\u001b[0m, in \u001b[0;36mshow_random_elements\u001b[0;34m(dataset, num_examples)\u001b[0m\n\u001b[1;32m     12\u001b[0m         pick \u001b[38;5;241m=\u001b[39m random\u001b[38;5;241m.\u001b[39mrandint(\u001b[38;5;241m0\u001b[39m, \u001b[38;5;28mlen\u001b[39m(dataset)\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m)\n\u001b[1;32m     13\u001b[0m     picks\u001b[38;5;241m.\u001b[39mappend(pick)\n\u001b[0;32m---> 15\u001b[0m df \u001b[38;5;241m=\u001b[39m pd\u001b[38;5;241m.\u001b[39mDataFrame(\u001b[43mdataset\u001b[49m\u001b[43m[\u001b[49m\u001b[43mpicks\u001b[49m\u001b[43m]\u001b[49m)\n\u001b[1;32m     16\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m column, typ \u001b[38;5;129;01min\u001b[39;00m dataset\u001b[38;5;241m.\u001b[39mfeatures\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m     17\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(typ, datasets\u001b[38;5;241m.\u001b[39mClassLabel):\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/frame.py:3811\u001b[0m, in \u001b[0;36mDataFrame.__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   3809\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m is_iterator(key):\n\u001b[1;32m   3810\u001b[0m         key \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(key)\n\u001b[0;32m-> 3811\u001b[0m     indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcolumns\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_get_indexer_strict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mcolumns\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m[\u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m   3813\u001b[0m \u001b[38;5;66;03m# take() does not accept boolean indexers\u001b[39;00m\n\u001b[1;32m   3814\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(indexer, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mdtype\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m) \u001b[38;5;241m==\u001b[39m \u001b[38;5;28mbool\u001b[39m:\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/indexes/base.py:6108\u001b[0m, in \u001b[0;36mIndex._get_indexer_strict\u001b[0;34m(self, key, axis_name)\u001b[0m\n\u001b[1;32m   6105\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   6106\u001b[0m     keyarr, indexer, new_indexer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_reindex_non_unique(keyarr)\n\u001b[0;32m-> 6108\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_raise_if_missing\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkeyarr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindexer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis_name\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   6110\u001b[0m keyarr \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtake(indexer)\n\u001b[1;32m   6111\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(key, Index):\n\u001b[1;32m   6112\u001b[0m     \u001b[38;5;66;03m# GH 42790 - Preserve name from an Index\u001b[39;00m\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/indexes/base.py:6168\u001b[0m, in \u001b[0;36mIndex._raise_if_missing\u001b[0;34m(self, key, indexer, axis_name)\u001b[0m\n\u001b[1;32m   6166\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m use_interval_msg:\n\u001b[1;32m   6167\u001b[0m         key \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(key)\n\u001b[0;32m-> 6168\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mNone of [\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mkey\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m] are in the [\u001b[39m\u001b[38;5;132;01m{\u001b[39;00maxis_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m]\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m   6170\u001b[0m not_found \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mlist\u001b[39m(ensure_index(key)[missing_mask\u001b[38;5;241m.\u001b[39mnonzero()[\u001b[38;5;241m0\u001b[39m]]\u001b[38;5;241m.\u001b[39munique())\n\u001b[1;32m   6171\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnot_found\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m not in index\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
+      "\u001b[0;31mKeyError\u001b[0m: \"None of [Int64Index([53, 82, 92, 63, 6], dtype='int64')] are in the [columns]\""
+     ]
+    }
+   ],
+   "source": [
+    "show_random_elements(result)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 313
+    },
+    "executionInfo": {
+     "elapsed": 387,
+     "status": "error",
+     "timestamp": 1669576355089,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "4UubtsoakHA3",
+    "outputId": "19c6e23f-e9fa-498f-cc4c-df63f8207b70"
+   },
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "ignored",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-18-8e356f7844d3>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mraw_datasets\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mload_dataset\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mresult\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/datasets/load.py\u001b[0m in \u001b[0;36mload_dataset\u001b[0;34m(path, name, data_dir, data_files, split, cache_dir, features, download_config, download_mode, ignore_verifications, keep_in_memory, save_infos, revision, use_auth_token, task, streaming, num_proc, **config_kwargs)\u001b[0m\n\u001b[1;32m   1700\u001b[0m     \u001b[0;31m`\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;31m`\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1701\u001b[0m     \"\"\"\n\u001b[0;32m-> 1702\u001b[0;31m     \u001b[0;32mif\u001b[0m \u001b[0mPath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mconfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mDATASET_STATE_JSON_FILENAME\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexists\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1703\u001b[0m         raise ValueError(\n\u001b[1;32m   1704\u001b[0m             \u001b[0;34m\"You are trying to load a dataset that was saved using `save_to_disk`. \"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/usr/lib/python3.7/pathlib.py\u001b[0m in \u001b[0;36m__new__\u001b[0;34m(cls, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1025\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mcls\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mPath\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1026\u001b[0m             \u001b[0mcls\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mWindowsPath\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m'nt'\u001b[0m \u001b[0;32melse\u001b[0m \u001b[0mPosixPath\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1027\u001b[0;31m         \u001b[0mself\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcls\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_from_parts\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1028\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_flavour\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mis_supported\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1029\u001b[0m             raise NotImplementedError(\"cannot instantiate %r on your system\"\n",
+      "\u001b[0;32m/usr/lib/python3.7/pathlib.py\u001b[0m in \u001b[0;36m_from_parts\u001b[0;34m(cls, args, init)\u001b[0m\n\u001b[1;32m    672\u001b[0m         \u001b[0;31m# right flavour.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    673\u001b[0m         \u001b[0mself\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mobject\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__new__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcls\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 674\u001b[0;31m         \u001b[0mdrv\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mroot\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mparts\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parse_args\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    675\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drv\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdrv\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    676\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_root\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mroot\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/usr/lib/python3.7/pathlib.py\u001b[0m in \u001b[0;36m_parse_args\u001b[0;34m(cls, args)\u001b[0m\n\u001b[1;32m    656\u001b[0m                 \u001b[0mparts\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_parts\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    657\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 658\u001b[0;31m                 \u001b[0ma\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfspath\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    659\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    660\u001b[0m                     \u001b[0;31m# Force-cast str subclasses to str (issue #21127)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mTypeError\u001b[0m: expected str, bytes or os.PathLike object, not DataFrame"
+     ]
+    }
+   ],
+   "source": [
+    "raw_datasets = load_dataset(result)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 145,
+     "referenced_widgets": [
+      "0b38e872bc524464a2b3abe7f2f9b0be",
+      "c6a5f491bb4c4136bcb5f90d3365bd5f",
+      "05b2a71290474944b5ae83e6acbe6adc",
+      "b8b0c77876a0404db627bac733d028e8",
+      "92023e14dbcf4c218f338c926e40ae14",
+      "03c8bdaa055e465f8a941ff333767409",
+      "664e934211bb4356ae5426686f0035b3",
+      "c80b42c6b5c04f4e9452c7af595f1d2c",
+      "ef09742724b34b75b051ac54db2383ed",
+      "0c4d50cf8f8d425e86960bc2dc269c89",
+      "01c98b14c07d4258aab7671240838ef6",
+      "243833c3431e4353af27113e5a8b0a7f",
+      "465d36a2f4b340dbbb7844f5187a91c6",
+      "6bc673e8cebe4c28bc7fb967615bed9a",
+      "a68722b5ccb144e2bca404b7cd00cfcb",
+      "b8ad8216b8df4dfb9f87d82824c65087",
+      "ef9b130ff1264814bb2f80c597466689",
+      "3ff8b3ad219c430083498e2710f9783b",
+      "d27a766c98bf4b858d145d88c69d34f6",
+      "67627aa46685425fba1b801c25d8f5c0",
+      "47f89064d61442caba4adf13852b1708",
+      "5168fe5634ee4077a558b7328f3a1dbc",
+      "4f5c545ae1c949a2990d557fa6152376",
+      "33e5a40561e64bae86a488e0e62e7597",
+      "9c73476e79a84b1a9361842441c52d53",
+      "07198da37bbe454db23f02d9bf9ad855",
+      "2a3b7cc5e582416caa24dd2360bb2664",
+      "158c7ddf69924f27b637b9a2f11bcaa0",
+      "1bee7da564a74fbb9521433b2bd8ad54",
+      "05aec460b82241ad9da702e6398f83a9",
+      "38fb2ec3ed86413bacf3213f71cbe4cd",
+      "df0b2994481f47568d388440024dff5a",
+      "103fbfda1b924f1b87ead6dd93ebe447",
+      "3c70c6d3f27e4ed6ad3e11833ab5a5fc",
+      "2205adb4fcd649e78977990748e1e0f3",
+      "568fc52953454ea398132e8eabf2f7a3",
+      "ba63044392144348b8e4c30869643010",
+      "679aadea6b11431682f884b5ef26c0d3",
+      "e07d939742d54ac29c8f8e00b7af5604",
+      "01d888d4b4f449af85114e6da4570452",
+      "558a98c82b4a458096d2f7f5e1088673",
+      "90697bae783b45aeaf1f448d31e3b4c5",
+      "ecbbff87ffa1445e8946155b04f7cc0d",
+      "80d4b0bdb13e444a84b3ccebb6f7eeb0"
+     ]
+    },
+    "executionInfo": {
+     "elapsed": 5037,
+     "status": "ok",
+     "timestamp": 1669576365017,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "ZdPQtI-WlD5H",
+    "outputId": "b882fa2a-c627-4203-d520-f8f000d7597e"
+   },
+   "outputs": [],
+   "source": [
+    "from transformers import AutoTokenizer\n",
+    "    \n",
+    "tokenizer = AutoTokenizer.from_pretrained(model_checkpoint)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 492,
+     "status": "ok",
+     "timestamp": 1669280828857,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "kjc19-dOl-JX",
+    "outputId": "f21bb653-ef50-44fd-9e00-b85628d910bd"
+   },
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'input_ids': [0, 31414, 6, 42, 65, 3645, 328, 2], 'attention_mask': [1, 1, 1, 1, 1, 1, 1, 1]}"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tokenizer(\"Hello, this one sentence!\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 1041,
+     "status": "ok",
+     "timestamp": 1669576379512,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "gduPqN_OmDrY",
+    "outputId": "9f0aa066-7140-4aaf-d3f3-b99257ef5e82"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'input_ids': [[0, 31414, 6, 42, 65, 3645, 328, 2], [0, 713, 16, 277, 3645, 4, 2]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1]]}\n"
+     ]
+    }
+   ],
+   "source": [
+    "with tokenizer.as_target_tokenizer():\n",
+    "    print(tokenizer([\"Hello, this one sentence!\", \"This is another sentence.\"]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 428,
+     "status": "ok",
+     "timestamp": 1669576381572,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "7cRl0UmbmPBv",
+    "outputId": "bcda0139-7288-423e-a570-7d525e1af848"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'input_ids': [[0, 133, 37920, 1421, 6, 21, 441, 7, 7006, 10, 10556, 22259, 11759, 609, 11, 10, 1810, 3143, 9, 29943, 5473, 11174, 4458, 4, 18547, 46602, 7085, 8, 4412, 6979, 4040, 991, 3809, 260, 1827, 1021, 7485, 5000, 21, 6126, 11, 5, 18067, 443, 396, 486, 687, 9285, 4, 133, 1421, 6, 3891, 6, 2092, 3901, 7, 892, 41724, 219, 1090, 337, 9013, 11759, 223, 28900, 12418, 1274, 8, 41724, 219, 1090, 337, 28456, 11, 430, 12396, 8, 22259, 3505, 4, 2], [0, 574, 3141, 19, 23459, 2088, 33906, 417, 12, 725, 134, 2633, 5943, 709, 1118, 7, 2301, 19, 5, 5685, 221, 6153, 12, 725, 134, 48661, 6, 420, 5, 80, 434, 17369, 1687, 4, 18522, 5181, 5943, 39209, 11, 70, 542, 12170, 337, 1538, 3451, 6, 8, 11, 1437, 12170, 337, 1538, 2428, 2003, 21242, 3406, 5, 29401, 33906, 417, 12, 725, 134, 48661, 6, 11187, 24, 13072, 39209, 11, 2428, 2003, 21242, 19, 5, 5685, 221, 6153, 12, 725, 134, 48661, 4, 713, 2609, 24864, 41, 10405, 227, 221, 6153, 12, 725, 134, 6, 5181, 8, 1437, 12170, 337, 1938, 4, 3750, 5, 239, 5181, 6, 221, 6153, 12, 725, 134, 2301, 11, 2428, 14218, 36, 13055, 487, 12, 725, 134, 12, 406, 43, 19057, 55, 6, 9641, 2301, 19, 33906, 417, 12, 725, 134, 58, 275, 11, 748, 27771, 12, 725, 134, 3618, 4, 2], [0, 565, 783, 368, 12, 53, 45, 13418, 21130, 1580, 12, 38871, 221, 11621, 487, 16, 3059, 19, 2129, 1374, 7967, 11, 11707, 2562, 4, 43253, 1178, 13998, 2678, 661, 39917, 924, 614, 256, 13459, 1380, 38, 36, 448, 13459, 100, 43, 8151, 8, 1762, 9, 7522, 398, 2744, 255, 3551, 38763, 11, 221, 11621, 487, 12, 3530, 23991, 4, 1121, 44161, 9, 221, 11621, 487, 4091, 10191, 1626, 7241, 6673, 37263, 12, 30231, 256, 13459, 100, 30223, 8, 42625, 256, 13459, 100, 8151, 15, 11707, 2562, 4590, 4, 18348, 1452, 9956, 12, 805, 21912, 9, 221, 11621, 487, 11, 10, 11707, 2562, 18292, 1421, 20635, 263, 24608, 1626, 16570, 34939, 8, 16739, 4, 7199, 4735, 6, 23991, 11509, 24756, 448, 846, 12, 44191, 3103, 25, 10, 1421, 44368, 32, 18105, 37174, 7, 48291, 3103, 12, 6078, 500, 6214, 44131, 255, 3551, 12, 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+     ]
+    }
+   ],
+   "source": [
+    "with tokenizer.as_target_tokenizer():\n",
+    "    print(tokenizer([str(item['red_panel_text_box_body']) for idx, item in result.iterrows()]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {
+    "executionInfo": {
+     "elapsed": 374,
+     "status": "ok",
+     "timestamp": 1669576385830,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "YgNwfk7Hm352"
+   },
+   "outputs": [],
+   "source": [
+    "if model_checkpoint in [\"t5-small\", \"t5-base\", \"t5-larg\", \"t5-3b\", \"t5-11b\"]:\n",
+    "    prefix = \"summarize: \"\n",
+    "else:\n",
+    "    prefix = \"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {
+    "executionInfo": {
+     "elapsed": 271,
+     "status": "ok",
+     "timestamp": 1669576390877,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "7p69v3F-7y3l"
+   },
+   "outputs": [],
+   "source": [
+    "from datasets import Dataset, DatasetDict\n",
+    "\n",
+    "raw_data = Dataset.from_pandas(red_panel)\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {
+    "executionInfo": {
+     "elapsed": 623,
+     "status": "ok",
+     "timestamp": 1669576398897,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "uMYy0T5snVms"
+   },
+   "outputs": [],
+   "source": [
+    "max_input_length = 256\n",
+    "max_target_length = 128\n",
+    "\n",
+    "def preprocess_function(examples):\n",
+    "    inputs = [prefix + doc for doc in examples[\"red_panel_text_box_body\"]]\n",
+    "    model_inputs = tokenizer(inputs, max_length=max_input_length, truncation=True)\n",
+    "    print('here')\n",
+    "    # Setup the tokenizer for targets\n",
+    "    with tokenizer.as_target_tokenizer():\n",
+    "        labels = tokenizer([str(i) for i in examples['red_panel_text_box_body']], max_length=max_target_length, truncation=True)\n",
+    "\n",
+    "    model_inputs[\"labels\"] = labels[\"input_ids\"]\n",
+    "    return model_inputs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 321,
+     "status": "ok",
+     "timestamp": 1669576404041,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "LY8V30iknZkK",
+    "outputId": "dadf1d4b-4549-48b4-ea0a-a9b80c53d41e"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "here\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'input_ids': [[0, 2709, 41724, 219, 1090, 337, 22259, 11759, 11, 5, 7018, 337, 29943, 35, 83, 37920, 1421, 16, 441, 7, 7006, 10, 10556, 22259, 11759, 609, 11, 10, 1810, 3143, 9, 29943, 5473, 11174, 4458, 2], [0, 2709, 16828, 9, 239, 12, 219, 22613, 38175, 2726, 19, 2167, 21092, 9, 538, 14082, 14819, 17719, 7, 499, 23377, 5183, 1274, 35, 497, 5, 239, 5181, 6, 221, 6153, 12, 725, 134, 2301, 11, 2428, 14218, 36, 13055, 487, 12, 725, 134, 12, 406, 43, 19057, 55, 6, 9641, 2301, 19, 33906, 417, 12, 725, 134, 58, 275, 11, 748, 27771, 12, 725, 134, 3618, 2]], 'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]], 'labels': [[0, 2709, 41724, 219, 1090, 337, 22259, 11759, 11, 5, 7018, 337, 29943, 35, 83, 37920, 1421, 16, 441, 7, 7006, 10, 10556, 22259, 11759, 609, 11, 10, 1810, 3143, 9, 29943, 5473, 11174, 4458, 2], [0, 2709, 16828, 9, 239, 12, 219, 22613, 38175, 2726, 19, 2167, 21092, 9, 538, 14082, 14819, 17719, 7, 499, 23377, 5183, 1274, 35, 497, 5, 239, 5181, 6, 221, 6153, 12, 725, 134, 2301, 11, 2428, 14218, 36, 13055, 487, 12, 725, 134, 12, 406, 43, 19057, 55, 6, 9641, 2301, 19, 33906, 417, 12, 725, 134, 58, 275, 11, 748, 27771, 12, 725, 134, 3618, 2]]}"
+      ]
+     },
+     "execution_count": 24,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "preprocess_function(red_panel[:2])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 66,
+     "referenced_widgets": [
+      "bdfff319aabb4945839b4005998a33f6",
+      "0e829cb1baaa4f328c81962b8387d7b2",
+      "cd5a450b5aa64a26b0bce472d9cb3876",
+      "ad906e312a214064ab07fbc101dd38a8",
+      "529be118e3874e89aa14be376861b9e6",
+      "03cc14e13e57403290726fbaa456ad1b",
+      "fd96d7b076b841df9b3f59f2906e3e2e",
+      "69dfaff72d6c45aabdbd920709914a94",
+      "47e1811ef6784f808202d973b364ec34",
+      "8a3d504e7bab45289110d16a637b5cab",
+      "18c3aea650934b52abbd1a54ab659581"
+     ]
+    },
+    "executionInfo": {
+     "elapsed": 404,
+     "status": "ok",
+     "timestamp": 1669576408931,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "wDwXFKU_oHlt",
+    "outputId": "479d2bd3-70b4-48be-cbe5-77e2b629d48b"
+   },
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "31bb088fedaa408f974ce97de968a715",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "  0%|          | 0/1 [00:00<?, ?ba/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "here\n"
+     ]
+    }
+   ],
+   "source": [
+    "tokenized_datasets = raw_data.map(preprocess_function, batched=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 49,
+     "referenced_widgets": [
+      "310364ac4e554a71bb800150efb4e95b",
+      "f8ee3ffd41f043e6a69441425bf9e8eb",
+      "b3c8ba9d9dba4a91b59cd80c9613df72",
+      "b5bb11c9831343aaba8f762c96458ba8",
+      "3c82385919ad4a6eb7602b4fc572b4b6",
+      "04e7b764ddc84f82be0c8d770b917338",
+      "32b08866ffec461ebaec8ea1e31c6214",
+      "23233289ad584854ae941a706b940529",
+      "384c726225514427b5842166b93eea50",
+      "2c8fe9936b544b14984723e82b1106a1",
+      "365047e08ee64faba80eb1ad825bca1b"
+     ]
+    },
+    "executionInfo": {
+     "elapsed": 37257,
+     "status": "ok",
+     "timestamp": 1669576448765,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "Hjl5EBndpPwm",
+    "outputId": "799e7e00-f6bf-44b6-fbf9-5553451c8dd8"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2022-11-28 00:17:55.780028: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX2 FMA\n",
+      "To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
+      "2022-11-28 00:17:56.127084: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\n",
+      "2022-11-28 00:17:56.127127: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\n",
+      "2022-11-28 00:17:56.181546: E tensorflow/stream_executor/cuda/cuda_blas.cc:2981] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+      "2022-11-28 00:17:57.172608: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory\n",
+      "2022-11-28 00:17:57.172712: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory\n",
+      "2022-11-28 00:17:57.172721: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "8a44e797bed24acdac206b01e750eb73",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Downloading:   0%|          | 0.00/1.51G [00:00<?, ?B/s]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from transformers import AutoModelForSeq2SeqLM, DataCollatorForSeq2Seq, Seq2SeqTrainingArguments, Seq2SeqTrainer\n",
+    "\n",
+    "model = AutoModelForSeq2SeqLM.from_pretrained(model_checkpoint)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {
+    "executionInfo": {
+     "elapsed": 418,
+     "status": "ok",
+     "timestamp": 1669576453237,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "2C_UCugqr4Mo"
+   },
+   "outputs": [],
+   "source": [
+    "batch_size = 16\n",
+    "model_name = model_checkpoint.split(\"/\")[-1]\n",
+    "args = Seq2SeqTrainingArguments(\n",
+    "    f\"{model_name}-finetuned-xsum\",\n",
+    "    evaluation_strategy = \"epoch\",\n",
+    "    learning_rate=2e-5,\n",
+    "    per_device_train_batch_size=batch_size,\n",
+    "    per_device_eval_batch_size=batch_size,\n",
+    "    weight_decay=0.01,\n",
+    "    save_total_limit=3,\n",
+    "    num_train_epochs=1,\n",
+    "    predict_with_generate=True,\n",
+    "    push_to_hub=True,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {
+    "executionInfo": {
+     "elapsed": 422,
+     "status": "ok",
+     "timestamp": 1669576459547,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "BvGXfqnCsZFl"
+   },
+   "outputs": [],
+   "source": [
+    "data_collator = DataCollatorForSeq2Seq(tokenizer, model=model)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {
+    "executionInfo": {
+     "elapsed": 10,
+     "status": "ok",
+     "timestamp": 1669576461903,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "eKE60Ta8tXjq"
+   },
+   "outputs": [],
+   "source": [
+    "import nltk\n",
+    "import numpy as np\n",
+    "\n",
+    "def compute_metrics(eval_pred):\n",
+    "    predictions, labels = eval_pred\n",
+    "    decoded_preds = tokenizer.batch_decode(predictions, skip_special_tokens=True)\n",
+    "    # Replace -100 in the labels as we can't decode them.\n",
+    "    labels = np.where(labels != -100, labels, tokenizer.pad_token_id)\n",
+    "    decoded_labels = tokenizer.batch_decode(labels, skip_special_tokens=True)\n",
+    "    \n",
+    "    # Rouge expects a newline after each sentence\n",
+    "    decoded_preds = [\"\\n\".join(nltk.sent_tokenize(pred.strip())) for pred in decoded_preds]\n",
+    "    decoded_labels = [\"\\n\".join(nltk.sent_tokenize(label.strip())) for label in decoded_labels]\n",
+    "    \n",
+    "    result = metric.compute(predictions=decoded_preds, references=decoded_labels, use_stemmer=True)\n",
+    "    # Extract a few results\n",
+    "    result = {key: value.mid.fmeasure * 100 for key, value in result.items()}\n",
+    "    \n",
+    "    # Add mean generated length\n",
+    "    prediction_lens = [np.count_nonzero(pred != tokenizer.pad_token_id) for pred in predictions]\n",
+    "    result[\"gen_len\"] = np.mean(prediction_lens)\n",
+    "    \n",
+    "    return {k: round(v, 4) for k, v in result.items()}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 9965,
+     "status": "ok",
+     "timestamp": 1669576476542,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "CUrBxFvltm1W",
+    "outputId": "11588487-4973-406c-9e93-fb1b6f27010b"
+   },
+   "outputs": [
+    {
+     "ename": "OSError",
+     "evalue": "Looks like you do not have git-lfs installed, please install. You can install from https://git-lfs.github.com/. Then run `git lfs install` (you only have to do this once).",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/huggingface_hub/repository.py:599\u001b[0m, in \u001b[0;36mRepository.check_git_versions\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    598\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 599\u001b[0m     lfs_version \u001b[38;5;241m=\u001b[39m \u001b[43mrun_subprocess\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    600\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mgit-lfs --version\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msplit\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mlocal_dir\u001b[49m\n\u001b[1;32m    601\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;241m.\u001b[39mstdout\u001b[38;5;241m.\u001b[39mstrip()\n\u001b[1;32m    602\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m:\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/huggingface_hub/utils/_subprocess.py:52\u001b[0m, in \u001b[0;36mrun_subprocess\u001b[0;34m(command, folder, check, **kwargs)\u001b[0m\n\u001b[1;32m     50\u001b[0m     command \u001b[38;5;241m=\u001b[39m command\u001b[38;5;241m.\u001b[39msplit()\n\u001b[0;32m---> 52\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43msubprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m     53\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcommand\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     54\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstderr\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msubprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mPIPE\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     55\u001b[0m \u001b[43m    \u001b[49m\u001b[43mstdout\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43msubprocess\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mPIPE\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     56\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcheck\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcheck\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     57\u001b[0m \u001b[43m    \u001b[49m\u001b[43mencoding\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mutf-8\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     58\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcwd\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mfolder\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mos\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgetcwd\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     59\u001b[0m \u001b[43m    \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     60\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m/usr/lib/python3.10/subprocess.py:501\u001b[0m, in \u001b[0;36mrun\u001b[0;34m(input, capture_output, timeout, check, *popenargs, **kwargs)\u001b[0m\n\u001b[1;32m    499\u001b[0m     kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mstderr\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m PIPE\n\u001b[0;32m--> 501\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mPopen\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mpopenargs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m process:\n\u001b[1;32m    502\u001b[0m     \u001b[38;5;28;01mtry\u001b[39;00m:\n",
+      "File \u001b[0;32m/usr/lib/python3.10/subprocess.py:969\u001b[0m, in \u001b[0;36mPopen.__init__\u001b[0;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds, user, group, extra_groups, encoding, errors, text, umask, pipesize)\u001b[0m\n\u001b[1;32m    966\u001b[0m             \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstderr \u001b[38;5;241m=\u001b[39m io\u001b[38;5;241m.\u001b[39mTextIOWrapper(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstderr,\n\u001b[1;32m    967\u001b[0m                     encoding\u001b[38;5;241m=\u001b[39mencoding, errors\u001b[38;5;241m=\u001b[39merrors)\n\u001b[0;32m--> 969\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_execute_child\u001b[49m\u001b[43m(\u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexecutable\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpreexec_fn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mclose_fds\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    970\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mpass_fds\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcwd\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43menv\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    971\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mstartupinfo\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcreationflags\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mshell\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    972\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mp2cread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mp2cwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    973\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mc2pread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mc2pwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    974\u001b[0m \u001b[43m                        \u001b[49m\u001b[43merrread\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43merrwrite\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    975\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mrestore_signals\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    976\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mgid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgids\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43muid\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mumask\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    977\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mstart_new_session\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    978\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m:\n\u001b[1;32m    979\u001b[0m     \u001b[38;5;66;03m# Cleanup if the child failed starting.\u001b[39;00m\n",
+      "File \u001b[0;32m/usr/lib/python3.10/subprocess.py:1845\u001b[0m, in \u001b[0;36mPopen._execute_child\u001b[0;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, restore_signals, gid, gids, uid, umask, start_new_session)\u001b[0m\n\u001b[1;32m   1844\u001b[0m         err_msg \u001b[38;5;241m=\u001b[39m os\u001b[38;5;241m.\u001b[39mstrerror(errno_num)\n\u001b[0;32m-> 1845\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m child_exception_type(errno_num, err_msg, err_filename)\n\u001b[1;32m   1846\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m child_exception_type(err_msg)\n",
+      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: 'git-lfs'",
+      "\nDuring handling of the above exception, another exception occurred:\n",
+      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn [38], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m trainer \u001b[38;5;241m=\u001b[39m \u001b[43mSeq2SeqTrainer\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      2\u001b[0m \u001b[43m    \u001b[49m\u001b[43mmodel\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      3\u001b[0m \u001b[43m    \u001b[49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtrain_dataset\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtokenized_datasets\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[43m    \u001b[49m\u001b[43meval_dataset\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtokenized_datasets\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[43m    \u001b[49m\u001b[43mdata_collator\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mdata_collator\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      7\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtokenizer\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtokenizer\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      8\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcompute_metrics\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcompute_metrics\u001b[49m\n\u001b[1;32m      9\u001b[0m \u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/transformers/trainer.py:464\u001b[0m, in \u001b[0;36mTrainer.__init__\u001b[0;34m(self, model, args, data_collator, train_dataset, eval_dataset, tokenizer, model_init, compute_metrics, callbacks, optimizers, preprocess_logits_for_metrics)\u001b[0m\n\u001b[1;32m    462\u001b[0m \u001b[38;5;66;03m# Create clone of distant repo and output directory if needed\u001b[39;00m\n\u001b[1;32m    463\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs\u001b[38;5;241m.\u001b[39mpush_to_hub:\n\u001b[0;32m--> 464\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minit_git_repo\u001b[49m\u001b[43m(\u001b[49m\u001b[43mat_init\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m\n\u001b[1;32m    465\u001b[0m     \u001b[38;5;66;03m# In case of pull, we need to make sure every process has the latest.\u001b[39;00m\n\u001b[1;32m    466\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m is_torch_tpu_available():\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/transformers/trainer.py:3106\u001b[0m, in \u001b[0;36mTrainer.init_git_repo\u001b[0;34m(self, at_init)\u001b[0m\n\u001b[1;32m   3103\u001b[0m     repo_name \u001b[38;5;241m=\u001b[39m get_full_repo_name(repo_name, token\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs\u001b[38;5;241m.\u001b[39mhub_token)\n\u001b[1;32m   3105\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m-> 3106\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrepo \u001b[38;5;241m=\u001b[39m \u001b[43mRepository\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   3107\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moutput_dir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3108\u001b[0m \u001b[43m        \u001b[49m\u001b[43mclone_from\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrepo_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3109\u001b[0m \u001b[43m        \u001b[49m\u001b[43muse_auth_token\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43muse_auth_token\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3110\u001b[0m \u001b[43m        \u001b[49m\u001b[43mprivate\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43margs\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mhub_private_repo\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3111\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3112\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mEnvironmentError\u001b[39;00m:\n\u001b[1;32m   3113\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39margs\u001b[38;5;241m.\u001b[39moverwrite_output_dir \u001b[38;5;129;01mand\u001b[39;00m at_init:\n\u001b[1;32m   3114\u001b[0m         \u001b[38;5;66;03m# Try again after wiping output_dir\u001b[39;00m\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/huggingface_hub/utils/_deprecation.py:98\u001b[0m, in \u001b[0;36m_deprecate_arguments.<locals>._inner_deprecate_positional_args.<locals>.inner_f\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     96\u001b[0m         message \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m custom_message\n\u001b[1;32m     97\u001b[0m     warnings\u001b[38;5;241m.\u001b[39mwarn(message, \u001b[38;5;167;01mFutureWarning\u001b[39;00m)\n\u001b[0;32m---> 98\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mf\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/huggingface_hub/repository.py:497\u001b[0m, in \u001b[0;36mRepository.__init__\u001b[0;34m(self, local_dir, clone_from, repo_type, use_auth_token, git_user, git_email, revision, private, skip_lfs_files, client)\u001b[0m\n\u001b[1;32m    494\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mskip_lfs_files \u001b[38;5;241m=\u001b[39m skip_lfs_files\n\u001b[1;32m    495\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mclient \u001b[38;5;241m=\u001b[39m client \u001b[38;5;28;01mif\u001b[39;00m client \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;28;01melse\u001b[39;00m HfApi()\n\u001b[0;32m--> 497\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcheck_git_versions\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    499\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(use_auth_token, \u001b[38;5;28mstr\u001b[39m):\n\u001b[1;32m    500\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhuggingface_token \u001b[38;5;241m=\u001b[39m use_auth_token\n",
+      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/huggingface_hub/repository.py:603\u001b[0m, in \u001b[0;36mRepository.check_git_versions\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    599\u001b[0m     lfs_version \u001b[38;5;241m=\u001b[39m run_subprocess(\n\u001b[1;32m    600\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgit-lfs --version\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39msplit(), \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mlocal_dir\n\u001b[1;32m    601\u001b[0m     )\u001b[38;5;241m.\u001b[39mstdout\u001b[38;5;241m.\u001b[39mstrip()\n\u001b[1;32m    602\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mFileNotFoundError\u001b[39;00m:\n\u001b[0;32m--> 603\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mEnvironmentError\u001b[39;00m(\n\u001b[1;32m    604\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mLooks like you do not have git-lfs installed, please install.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    605\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m You can install from https://git-lfs.github.com/.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    606\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m Then run `git lfs install` (you only have to do this once).\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    607\u001b[0m     )\n\u001b[1;32m    608\u001b[0m logger\u001b[38;5;241m.\u001b[39minfo(git_version \u001b[38;5;241m+\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;130;01m\\n\u001b[39;00m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;241m+\u001b[39m lfs_version)\n",
+      "\u001b[0;31mOSError\u001b[0m: Looks like you do not have git-lfs installed, please install. You can install from https://git-lfs.github.com/. Then run `git lfs install` (you only have to do this once)."
+     ]
+    }
+   ],
+   "source": [
+    "trainer = Seq2SeqTrainer(\n",
+    "    model,\n",
+    "    args,\n",
+    "    train_dataset=tokenized_datasets,\n",
+    "    eval_dataset=tokenized_datasets,\n",
+    "    data_collator=data_collator,\n",
+    "    tokenizer=tokenizer,\n",
+    "    compute_metrics=compute_metrics\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "executionInfo": {
+     "elapsed": 578,
+     "status": "ok",
+     "timestamp": 1669576480801,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "iWtpY6UvsrqL"
+   },
+   "outputs": [],
+   "source": [
+    "metric = load_metric(\"rouge\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 474
+    },
+    "executionInfo": {
+     "elapsed": 32697,
+     "status": "ok",
+     "timestamp": 1669576769127,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "59h69HXKttbi",
+    "outputId": "b885f66c-2377-4826-c85e-adb42b5132d7"
+   },
+   "outputs": [],
+   "source": [
+    "trainer.train()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/"
+    },
+    "executionInfo": {
+     "elapsed": 328,
+     "status": "ok",
+     "timestamp": 1669576814482,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "9Ewl0xuLhzr1",
+    "outputId": "c4d22171-c1ac-40e3-9f0a-b058271a2c71"
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Error: Failed to call git rev-parse --git-dir --show-toplevel: \"fatal: not a git repository (or any of the parent directories): .git\\n\"\n",
+      "Git LFS initialized.\n"
+     ]
+    }
+   ],
+   "source": [
+    "!git lfs install"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "metadata": {
+    "colab": {
+     "base_uri": "https://localhost:8080/",
+     "height": 1000,
+     "referenced_widgets": [
+      "e6da8f1c969c4116b54e964b78eeacfe",
+      "66292eb8434a4ce6a6d87b80c1a5d5cf",
+      "51ecb48b3aeb41cca1b2544aaa6d4297",
+      "227f48e8b0c54dedafe8837de08c046b",
+      "9bd09f0209b34586a8e52e549371dc9a",
+      "c6b05ef0ab714f6ebcb36f1ae3cd9706",
+      "0083d899a9fe4a75ac2ecc399d78f7e5",
+      "9e24fad5fa2244efb3789fd73f04780a",
+      "afa8052f63af4e2889921afbf6966f97",
+      "5b600008c0204e17b3a499c383486a45",
+      "1c751ee6ba044b26934f26a39981db27",
+      "2c1637186ffa402fbf9a581558931503",
+      "65020f9d0bb74135afd0a4958b652e7d",
+      "f2d03ae9392b47fb9c0ddf08097a9651",
+      "6a724ac6378641889ebf41de6d6885d4",
+      "d7c1ac4f603f4a518679ef85e3b1224a",
+      "7bf2ca5db1b14122a6a781df43c12acd",
+      "cb513a3c13dd4afa9e9967ac18cbe3c9",
+      "e38a776b6c1b4a269af32e38efde579c",
+      "39e1026c224a4b7689d60ab3d354fe50",
+      "ac44a05a3ac442f78082e6387090a984",
+      "94ec073846444cf6bc988e00b4b8bbce"
+     ]
+    },
+    "executionInfo": {
+     "elapsed": 26742,
+     "status": "error",
+     "timestamp": 1669576920460,
+     "user": {
+      "displayName": "Hayk Nersesyan",
+      "userId": "12126341854567580260"
+     },
+     "user_tz": -240
+    },
+    "id": "KVmCwgAS7SI_",
+    "outputId": "524fabd2-18bf-445a-ce63-bdd6bed6331a"
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Saving model checkpoint to bart-large-cnn-finetuned-xsum\n",
+      "Configuration saved in bart-large-cnn-finetuned-xsum/config.json\n",
+      "Model weights saved in bart-large-cnn-finetuned-xsum/pytorch_model.bin\n",
+      "tokenizer config file saved in bart-large-cnn-finetuned-xsum/tokenizer_config.json\n",
+      "Special tokens file saved in bart-large-cnn-finetuned-xsum/special_tokens_map.json\n",
+      "Several commits (2) will be pushed upstream.\n",
+      "WARNING:huggingface_hub.repository:Several commits (2) will be pushed upstream.\n",
+      "The progress bars may be unreliable.\n",
+      "WARNING:huggingface_hub.repository:The progress bars may be unreliable.\n"
+     ]
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "e6da8f1c969c4116b54e964b78eeacfe",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Upload file runs/Nov27_19-14-12_8af7ca6e45dd/1669576736.3078728/events.out.tfevents.1669576736.8af7ca6e45dd.77…"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "2c1637186ffa402fbf9a581558931503",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "Upload file runs/Nov27_19-14-12_8af7ca6e45dd/events.out.tfevents.1669576736.8af7ca6e45dd.77.2:  60%|#####9    …"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "remote: \u001b[0;31m----------------------------------------------------------\u001b[0;0m        \n",
+      "remote: \u001b[0;31mYour push was rejected for the following reasons:\u001b[0;0m        \n",
+      "remote: \u001b[0;31mDENIED update refs/heads/main: forbidden\u001b[0;0m        \n",
+      "remote: \u001b[0;31m----------------------------------------------------------\u001b[0;0m        \n",
+      "To https://huggingface.co/Hayk96/bart-large-cnn-finetuned-xsum\n",
+      " ! [remote rejected] main -> main (pre-receive hook declined)\n",
+      "error: failed to push some refs to 'https://user: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@huggingface.co/Hayk96/bart-large-cnn-finetuned-xsum'\n",
+      "\n",
+      "WARNING:huggingface_hub.repository:remote: \u001b[0;31m----------------------------------------------------------\u001b[0;0m        \n",
+      "remote: \u001b[0;31mYour push was rejected for the following reasons:\u001b[0;0m        \n",
+      "remote: \u001b[0;31mDENIED update refs/heads/main: forbidden\u001b[0;0m        \n",
+      "remote: \u001b[0;31m----------------------------------------------------------\u001b[0;0m        \n",
+      "To https://huggingface.co/Hayk96/bart-large-cnn-finetuned-xsum\n",
+      " ! [remote rejected] main -> main (pre-receive hook declined)\n",
+      "error: failed to push some refs to 'https://user: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@huggingface.co/Hayk96/bart-large-cnn-finetuned-xsum'\n",
+      "\n"
+     ]
+    },
+    {
+     "ename": "OSError",
+     "evalue": "ignored",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mCalledProcessError\u001b[0m                        Traceback (most recent call last)",
+      "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/huggingface_hub/repository.py\u001b[0m in \u001b[0;36mgit_push\u001b[0;34m(self, upstream, blocking, auto_lfs_prune)\u001b[0m\n\u001b[1;32m   1207\u001b[0m                         raise subprocess.CalledProcessError(\n\u001b[0;32m-> 1208\u001b[0;31m                             \u001b[0mreturn_code\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mprocess\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0moutput\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstdout\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mstderr\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mstderr\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1209\u001b[0m                         )\n",
+      "\u001b[0;31mCalledProcessError\u001b[0m: Command '['git', 'push', '--set-upstream', 'origin', 'main']' returned non-zero exit status 1.",
+      "\nDuring handling of the above exception, another exception occurred:\n",
+      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-42-8fcc5527db7e>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mtrainer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpush_to_hub\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/transformers/trainer.py\u001b[0m in \u001b[0;36mpush_to_hub\u001b[0;34m(self, commit_message, blocking, **kwargs)\u001b[0m\n\u001b[1;32m   3451\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3452\u001b[0m         git_head_commit_url = self.repo.push_to_hub(\n\u001b[0;32m-> 3453\u001b[0;31m             \u001b[0mcommit_message\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcommit_message\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mblocking\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mblocking\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mauto_lfs_prune\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3454\u001b[0m         )\n\u001b[1;32m   3455\u001b[0m         \u001b[0;31m# push separately the model card to be independant from the rest of the model\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/huggingface_hub/repository.py\u001b[0m in \u001b[0;36mpush_to_hub\u001b[0;34m(self, commit_message, blocking, clean_ok, auto_lfs_prune)\u001b[0m\n\u001b[1;32m   1433\u001b[0m             \u001b[0mupstream\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34mf\"origin {self.current_branch}\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1434\u001b[0m             \u001b[0mblocking\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mblocking\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1435\u001b[0;31m             \u001b[0mauto_lfs_prune\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mauto_lfs_prune\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1436\u001b[0m         )\n\u001b[1;32m   1437\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;32m/usr/local/lib/python3.7/dist-packages/huggingface_hub/repository.py\u001b[0m in \u001b[0;36mgit_push\u001b[0;34m(self, upstream, blocking, auto_lfs_prune)\u001b[0m\n\u001b[1;32m   1210\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1211\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0msubprocess\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mCalledProcessError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1212\u001b[0;31m             \u001b[0;32mraise\u001b[0m \u001b[0mEnvironmentError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstderr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1213\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1214\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mblocking\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mOSError\u001b[0m: remote: \u001b[0;31m----------------------------------------------------------\u001b[0;0m        \nremote: \u001b[0;31mYour push was rejected for the following reasons:\u001b[0;0m        \nremote: \u001b[0;31mDENIED update refs/heads/main: forbidden\u001b[0;0m        \nremote: \u001b[0;31m----------------------------------------------------------\u001b[0;0m        \nTo https://huggingface.co/Hayk96/bart-large-cnn-finetuned-xsum\n ! [remote rejected] main -> main (pre-receive hook declined)\nerror: failed to push some refs to 'https://user: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@huggingface.co/Hayk96/bart-large-cnn-finetuned-xsum'\n"
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