News_Summarization.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "source": [
        "## Requirements"
      ],
      "metadata": {
        "id": "Y1uDRTBs1Mv4"
      }
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Xhr8yfO7Y0QA"
      },
      "outputs": [],
      "source": [
        "!pip install transformers\n",
        "!pip install datasets\n",
        "!pip install sentencepiece\n",
        "!pip install evaluate\n",
        "!pip install rouge_score\n",
        "!pip install bert_score"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Dataset"
      ],
      "metadata": {
        "id": "U6WnzLSV1Hnu"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Here we import the dataset."
      ],
      "metadata": {
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      }
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        {
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              "Downloading readme:   0%|          | 0.00/10.4k [00:00<?, ?B/s]"
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        {
          "output_type": "stream",
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          "text": [
            "Downloading and preparing dataset pn_summary/1.0.0 to /root/.cache/huggingface/datasets/pn_summary/1.0.0/1.0.0/1429f2d17a6be7eb689d68d8cc17649ac07dce32dd69929acf95bdc791009d44...\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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              "version_major": 2,
              "version_minor": 0,
              "model_id": "73d0609141214d37a135b909aec8c420"
            }
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Generating train split:   0%|          | 0/82022 [00:00<?, ? examples/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "bd7bae8a404749b3a6505eda31274397"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
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              "version_major": 2,
              "version_minor": 0,
              "model_id": "470e1fcb91374f6ba824065cb73093f1"
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          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
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            ],
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              "version_major": 2,
              "version_minor": 0,
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          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Dataset pn_summary downloaded and prepared to /root/.cache/huggingface/datasets/pn_summary/1.0.0/1.0.0/1429f2d17a6be7eb689d68d8cc17649ac07dce32dd69929acf95bdc791009d44. Subsequent calls will reuse this data.\n"
          ]
        },
        {
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              "model_id": "f17cd7fa5e214c22a37d5209ffb98ada"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "import pandas as pd\n",
        "from datasets import load_dataset, Dataset\n",
        "\n",
        "dataset = load_dataset(\"pn_summary\")"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "dataset"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JeyDd_Zd_ckQ",
        "outputId": "115da184-8700-4496-f9f1-5ef0e3dcb056"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "DatasetDict({\n",
              "    train: Dataset({\n",
              "        features: ['id', 'title', 'article', 'summary', 'category', 'categories', 'network', 'link'],\n",
              "        num_rows: 82022\n",
              "    })\n",
              "    validation: Dataset({\n",
              "        features: ['id', 'title', 'article', 'summary', 'category', 'categories', 'network', 'link'],\n",
              "        num_rows: 5592\n",
              "    })\n",
              "    test: Dataset({\n",
              "        features: ['id', 'title', 'article', 'summary', 'category', 'categories', 'network', 'link'],\n",
              "        num_rows: 5593\n",
              "    })\n",
              "})"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Fine-tune and load the model"
      ],
      "metadata": {
        "id": "99D8dJQv1PkF"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Due to the size of models and space to fine-tune it with the dataset, we fine-tuned it on Hugging Face AutoTrain and push the fine-tuned models to the hub."
      ],
      "metadata": {
        "id": "AtLo8Hds1T5e"
      }
    },
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      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)okenizer_config.json:   0%|          | 0.00/478 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)\"spiece.model\";:   0%|          | 0.00/4.31M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "b1b50d9c2bad4a1e930fab8489c8c287"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)\"tokenizer.json\";:   0%|          | 0.00/16.3M [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
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              "model_id": "678ee56e09eb4630bfc317aa82e8ecde"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)cial_tokens_map.json:   0%|          | 0.00/74.0 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "b4d8016cfa254625b6a16576dbc98fd8"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)lve/main/config.json:   0%|          | 0.00/884 [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "89d916fe9eec4a18b45c2b2462cbe0b2"
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          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Downloading (…)\"pytorch_model.bin\";:   0%|          | 0.00/2.33G [00:00<?, ?B/s]"
            ],
            "application/vnd.jupyter.widget-view+json": {
              "version_major": 2,
              "version_minor": 0,
              "model_id": "e73c8bde85bf460b9f20870ea99715c7"
            }
          },
          "metadata": {}
        }
      ],
      "source": [
        "from transformers import AutoTokenizer, AutoModelForSeq2SeqLM\n",
        "\n",
        "token='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'\n",
        "tokenizer = AutoTokenizer.from_pretrained(\"arshandalili/autotrain-news-summarization-3366493100\", use_auth_token=token)\n",
        "model = AutoModelForSeq2SeqLM.from_pretrained(\"arshandalili/autotrain-news-summarization-3366493100\", use_auth_token=token)"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Evaluation"
      ],
      "metadata": {
        "id": "XT5mZOMq1qe-"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Here we sample 10 instances from test and see their results and compute evaluation metrics."
      ],
      "metadata": {
        "id": "XJDKYugz1spM"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "test_data = dataset['train'].shuffle(0).select(range(10))"
      ],
      "metadata": {
        "id": "ERLFO71wNngY"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "evaluate.list_evaluation_modules()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "lOT3NR_P4FFZ",
        "outputId": "d717d487-4999-410b-c437-79480e104de7"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['lvwerra/test',\n",
              " 'precision',\n",
              " 'code_eval',\n",
              " 'roc_auc',\n",
              " 'cuad',\n",
              " 'xnli',\n",
              " 'rouge',\n",
              " 'pearsonr',\n",
              " 'mse',\n",
              " 'super_glue',\n",
              " 'comet',\n",
              " 'cer',\n",
              " 'sacrebleu',\n",
              " 'mahalanobis',\n",
              " 'wer',\n",
              " 'competition_math',\n",
              " 'f1',\n",
              " 'recall',\n",
              " 'coval',\n",
              " 'mauve',\n",
              " 'xtreme_s',\n",
              " 'bleurt',\n",
              " 'ter',\n",
              " 'accuracy',\n",
              " 'exact_match',\n",
              " 'indic_glue',\n",
              " 'spearmanr',\n",
              " 'mae',\n",
              " 'squad',\n",
              " 'chrf',\n",
              " 'glue',\n",
              " 'perplexity',\n",
              " 'mean_iou',\n",
              " 'squad_v2',\n",
              " 'meteor',\n",
              " 'bleu',\n",
              " 'wiki_split',\n",
              " 'sari',\n",
              " 'frugalscore',\n",
              " 'google_bleu',\n",
              " 'bertscore',\n",
              " 'matthews_correlation',\n",
              " 'seqeval',\n",
              " 'trec_eval',\n",
              " 'rl_reliability',\n",
              " 'jordyvl/ece',\n",
              " 'angelina-wang/directional_bias_amplification',\n",
              " 'cpllab/syntaxgym',\n",
              " 'lvwerra/bary_score',\n",
              " 'kaggle/amex',\n",
              " 'kaggle/ai4code',\n",
              " 'hack/test_metric',\n",
              " 'yzha/ctc_eval',\n",
              " 'codeparrot/apps_metric',\n",
              " 'mfumanelli/geometric_mean',\n",
              " 'daiyizheng/valid',\n",
              " 'poseval',\n",
              " 'erntkn/dice_coefficient',\n",
              " 'mgfrantz/roc_auc_macro',\n",
              " 'Vlasta/pr_auc',\n",
              " 'gorkaartola/metric_for_tp_fp_samples',\n",
              " 'idsedykh/metric',\n",
              " 'idsedykh/codebleu2',\n",
              " 'idsedykh/codebleu',\n",
              " 'idsedykh/megaglue',\n",
              " 'kasmith/woodscore',\n",
              " 'cakiki/ndcg',\n",
              " 'brier_score',\n",
              " 'Vertaix/vendiscore',\n",
              " 'GMFTBY/dailydialogevaluate',\n",
              " 'GMFTBY/dailydialog_evaluate',\n",
              " 'jzm-mailchimp/joshs_second_test_metric',\n",
              " 'ola13/precision_at_k',\n",
              " 'yulong-me/yl_metric',\n",
              " 'abidlabs/mean_iou',\n",
              " 'abidlabs/mean_iou2',\n",
              " 'KevinSpaghetti/accuracyk',\n",
              " 'Felipehonorato/my_metric',\n",
              " 'NimaBoscarino/weat',\n",
              " 'ronaldahmed/nwentfaithfulness',\n",
              " 'Viona/infolm',\n",
              " 'kyokote/my_metric2',\n",
              " 'kashif/mape',\n",
              " 'Ochiroo/rouge_mn',\n",
              " 'giulio98/code_eval_outputs',\n",
              " 'leslyarun/fbeta_score',\n",
              " 'giulio98/codebleu',\n",
              " 'anz2/iliauniiccocrevaluation',\n",
              " 'zbeloki/m2',\n",
              " 'xu1998hz/sescore',\n",
              " 'mase',\n",
              " 'mape',\n",
              " 'smape',\n",
              " 'dvitel/codebleu',\n",
              " 'NCSOFT/harim_plus',\n",
              " 'JP-SystemsX/nDCG',\n",
              " 'sportlosos/sescore',\n",
              " 'Drunper/metrica_tesi',\n",
              " 'jpxkqx/peak_signal_to_noise_ratio',\n",
              " 'jpxkqx/signal_to_reconstrution_error',\n",
              " 'hpi-dhc/FairEval',\n",
              " 'nist_mt',\n",
              " 'lvwerra/accuracy_score',\n",
              " 'character',\n",
              " 'charcut_mt',\n",
              " 'ybelkada/cocoevaluate',\n",
              " 'harshhpareek/bertscore',\n",
              " 'posicube/mean_reciprocal_rank',\n",
              " 'bstrai/classification_report',\n",
              " 'omidf/squad_precision_recall',\n",
              " 'Josh98/nl2bash_m',\n",
              " 'BucketHeadP65/confusion_matrix',\n",
              " 'BucketHeadP65/roc_curve',\n",
              " 'mcnemar',\n",
              " 'exact_match',\n",
              " 'wilcoxon',\n",
              " 'ncoop57/levenshtein_distance',\n",
              " 'kaleidophon/almost_stochastic_order',\n",
              " 'word_length',\n",
              " 'lvwerra/element_count',\n",
              " 'word_count',\n",
              " 'text_duplicates',\n",
              " 'perplexity',\n",
              " 'label_distribution',\n",
              " 'toxicity',\n",
              " 'prb977/cooccurrence_count',\n",
              " 'regard',\n",
              " 'honest',\n",
              " 'NimaBoscarino/pseudo_perplexity']"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import evaluate\n",
        "import numpy as np\n",
        "import nltk\n",
        "\n",
        "rouge = evaluate.load('rouge')\n",
        "bleu = evaluate.load('bleu')\n",
        "bertscore = evaluate.load('bertscore')\n",
        "\n",
        "nltk.download('punkt')\n",
        "\n",
        "def compute_metrics(eval_preds, metric, bertscore=False, rouge=True):\n",
        "    preds = [res['generated_summary'] for res in eval_preds]\n",
        "    labels = [res['original_summary'] for res in eval_preds]\n",
        "    preds = [\"\\n\".join(nltk.sent_tokenize(pred.strip())) for pred in preds]\n",
        "    labels = [\"\\n\".join(nltk.sent_tokenize(label.strip())) for label in labels]\n",
        "    \n",
        "    if rouge:\n",
        "      result = metric.compute(predictions=preds, references=labels, tokenizer=lambda x: x.split())\n",
        "    elif bertscore:\n",
        "      result = metric.compute(predictions=preds, references=labels, lang='fa')\n",
        "    else:\n",
        "      result = metric.compute(predictions=preds, references=labels)\n",
        "    return result"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7kKvy0pE256g",
        "outputId": "e1130690-5b9b-4997-9033-409b67cd391e"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "result = []\n",
        "for data in test_data:\n",
        "\n",
        "  input_ids = tokenizer(\n",
        "      data['article'],\n",
        "      return_tensors=\"pt\",\n",
        "      padding=\"max_length\",\n",
        "      truncation=True,\n",
        "      max_length=512\n",
        "    )['input_ids']\n",
        "\n",
        "  output_ids = model.generate(\n",
        "    input_ids=input_ids,\n",
        "    max_length=84,\n",
        "    no_repeat_ngram_size=2,\n",
        "    num_beams=4\n",
        "  )[0]\n",
        "\n",
        "  summary = tokenizer.decode(\n",
        "    output_ids,\n",
        "    skip_special_tokens=True,\n",
        "    clean_up_tokenization_spaces=False\n",
        "  )\n",
        "\n",
        "  result.append({\n",
        "      'article': data['article'],\n",
        "      'original_summary': data['summary'],\n",
        "      'generated_summary': summary\n",
        "  })"
      ],
      "metadata": {
        "id": "vNHeK0HbObWA"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.DataFrame(result)\n",
        "df"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1629
        },
        "id": "YQkx5Z41PJ7M",
        "outputId": "85b2236d-b234-4a66-a9cd-d583684133ce"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                                             article  \\\n",
              "0  به گزارش خبرگزاری مهر به نقل از روابط عمومی مؤ...   \n",
              "1  به گزارش ایمنا، احمد پورحیدر، با اشاره به ظرفی...   \n",
              "2  به گفته توتال، این شرکت همچنین در نظر دارد ۱۸۰...   \n",
              "3  به گزارش خبرگزاری خبرآنلاین؛ ال‌کلاسیکوی ۲۷۸ ا...   \n",
              "4  به گزارش ایمنا، مصطفی نیک‌نقش بر ضرورت ایجاد د...   \n",
              "5  رسول جهانگیری در گفت‌وگو با خبرنگار ایمنا اظها...   \n",
              "6  به گزارش ایرنا، نام‌گذاری روز نخست هفته پارالم...   \n",
              "7  به گزارش بازار، میزان بارش‌های کشور تا بیست به...   \n",
              "8  سید علیرضا مروجی در گفت‌وگو با خبرنگار ایمنا ب...   \n",
              "9  به گزارش شانا به نقل از مرکز پژوهش‌های مجلس شو...   \n",
              "\n",
              "                                    original_summary  \\\n",
              "0  تور هنری ایتالیا در آرته با محوریت تبادل فرهنگ...   \n",
              "1  مدیرکل گمرک منطقه ویژه اقتصادی انرژی پارس جنوب...   \n",
              "2  شرکت بزرگ نفتی توتال فرانسه از توقف پالایش نفت...   \n",
              "3  ال‌کلاسیکوی شماره ۲۷۸ در حالی که تماشاگر نداشت...   \n",
              "4  معاون خدمات شهری شهردار ساری تشکیل کمیته‌های د...   \n",
              "5  رئیس اتاق اصناف اصفهان گفت: به عنوان یک شهروند...   \n",
              "6  دارنده مدال طلای بازی‌های پاراآسیایی جاکارتا د...   \n",
              "7  میزان بارش‌های کشور درسال آبی جاری از ابتدای م...   \n",
              "8  رئیس دانشگاه علوم پزشکی کاشان گفت: طی ۲۴ ساعت ...   \n",
              "9  نخستین نشست کمیته کارشناسی مشترک حوزه انرژی با...   \n",
              "\n",
              "                                   generated_summary  \n",
              "0  مؤسسه هنری سکو، تور فرهنگی تاریخی در آرته با م...  \n",
              "1  مدیرکل گمرک منطقه ویژه اقتصادی انرژی پارس جنوب...  \n",
              "2  توتال، بزرگترین شرکت پالایش اروپا، اعلام کرد ک...  \n",
              "3  تیم فوتبال رئال مادرید با نتیجه ۳ بر یک در ورز...  \n",
              "4  معاون خدمات شهری شهردار ساری گفت: تلاش می کنیم...  \n",
              "5  رئیس اتاق اصناف اصفهان از تعطیل کردن برخی از و...  \n",
              "6  ورزشکاران نابینا با مشکل دیگری به نام همراه ند...  \n",
              "7  میزان بارش های کشور تا بیست بهمن ماه سال آبی ج...  \n",
              "8  رئیس دانشگاه علوم پزشکی کاشان گفت: طی ۲۴ ساعت ...  \n",
              "9  نخستین نشست کمیته کارشناسی مشترک حوزه انرژی ام...  "
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              "      <td>به گزارش خبرگزاری مهر به نقل از روابط عمومی مؤ...</td>\n",
              "      <td>تور هنری ایتالیا در آرته با محوریت تبادل فرهنگ...</td>\n",
              "      <td>مؤسسه هنری سکو، تور فرهنگی تاریخی در آرته با م...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>به گزارش ایمنا، احمد پورحیدر، با اشاره به ظرفی...</td>\n",
              "      <td>مدیرکل گمرک منطقه ویژه اقتصادی انرژی پارس جنوب...</td>\n",
              "      <td>مدیرکل گمرک منطقه ویژه اقتصادی انرژی پارس جنوب...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>به گفته توتال، این شرکت همچنین در نظر دارد ۱۸۰...</td>\n",
              "      <td>شرکت بزرگ نفتی توتال فرانسه از توقف پالایش نفت...</td>\n",
              "      <td>توتال، بزرگترین شرکت پالایش اروپا، اعلام کرد ک...</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>به گزارش خبرگزاری خبرآنلاین؛ ال‌کلاسیکوی ۲۷۸ ا...</td>\n",
              "      <td>ال‌کلاسیکوی شماره ۲۷۸ در حالی که تماشاگر نداشت...</td>\n",
              "      <td>تیم فوتبال رئال مادرید با نتیجه ۳ بر یک در ورز...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>به گزارش ایمنا، مصطفی نیک‌نقش بر ضرورت ایجاد د...</td>\n",
              "      <td>معاون خدمات شهری شهردار ساری تشکیل کمیته‌های د...</td>\n",
              "      <td>معاون خدمات شهری شهردار ساری گفت: تلاش می کنیم...</td>\n",
              "    </tr>\n",
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              "      <th>5</th>\n",
              "      <td>رسول جهانگیری در گفت‌وگو با خبرنگار ایمنا اظها...</td>\n",
              "      <td>رئیس اتاق اصناف اصفهان گفت: به عنوان یک شهروند...</td>\n",
              "      <td>رئیس اتاق اصناف اصفهان از تعطیل کردن برخی از و...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>به گزارش ایرنا، نام‌گذاری روز نخست هفته پارالم...</td>\n",
              "      <td>دارنده مدال طلای بازی‌های پاراآسیایی جاکارتا د...</td>\n",
              "      <td>ورزشکاران نابینا با مشکل دیگری به نام همراه ند...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>به گزارش بازار، میزان بارش‌های کشور تا بیست به...</td>\n",
              "      <td>میزان بارش‌های کشور درسال آبی جاری از ابتدای م...</td>\n",
              "      <td>میزان بارش های کشور تا بیست بهمن ماه سال آبی ج...</td>\n",
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              "      <td>سید علیرضا مروجی در گفت‌وگو با خبرنگار ایمنا ب...</td>\n",
              "      <td>رئیس دانشگاه علوم پزشکی کاشان گفت: طی ۲۴ ساعت ...</td>\n",
              "      <td>رئیس دانشگاه علوم پزشکی کاشان گفت: طی ۲۴ ساعت ...</td>\n",
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              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
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      "source": [
        "print('ROUGE Score:')\n",
        "compute_metrics(result, rouge, rouge=True)"
      ],
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        "id": "T9Rkvg3zQxLf",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "6f896d54-fad5-4b37-8bf1-15e27f354122"
      },
      "execution_count": 66,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "ROUGE Score:\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'rouge1': 0.42019442558745246,\n",
              " 'rouge2': 0.2740388642885063,\n",
              " 'rougeL': 0.3772799697364326,\n",
              " 'rougeLsum': 0.38573884980348727}"
            ]
          },
          "metadata": {},
          "execution_count": 66
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('BLEU Score:')\n",
        "compute_metrics(result, bleu)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "aeHa5IZE5ssl",
        "outputId": "6328deb0-cf6e-4206-b504-a1149f0a21ac"
      },
      "execution_count": 55,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "BLEU Score:\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'bleu': 0.22912224597915648,\n",
              " 'precisions': [0.5512820512820513,\n",
              "  0.35714285714285715,\n",
              "  0.2897196261682243,\n",
              "  0.24509803921568626],\n",
              " 'brevity_penalty': 0.6663215574396286,\n",
              " 'length_ratio': 0.7112462006079028,\n",
              " 'translation_length': 234,\n",
              " 'reference_length': 329}"
            ]
          },
          "metadata": {},
          "execution_count": 55
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print('Bert Score:')\n",
        "compute_metrics(result, bertscore, bertscore=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
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        "outputId": "ba4801b9-8933-4802-8cd9-7151fce6998e"
      },
      "execution_count": 56,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Bert Score:\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
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              "  0.8496161699295044,\n",
              "  0.7083439230918884,\n",
              "  0.6703019738197327,\n",
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              "  0.8232523202896118,\n",
              "  0.9516125917434692,\n",
              "  0.8308478593826294],\n",
              " 'recall': [0.8510735034942627,\n",
              "  0.8170831203460693,\n",
              "  0.7802513241767883,\n",
              "  0.6320977210998535,\n",
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              "  0.8238754272460938,\n",
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              "  0.7728919982910156,\n",
              "  0.824344277381897,\n",
              "  0.8791366219520569],\n",
              " 'f1': [0.8354479670524597,\n",
              "  0.8330321311950684,\n",
              "  0.742560863494873,\n",
              "  0.650639533996582,\n",
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              "  0.7972776889801025,\n",
              "  0.8834182620048523,\n",
              "  0.8543103337287903],\n",
              " 'hashcode': 'bert-base-multilingual-cased_L9_no-idf_version=0.3.12(hug_trans=4.26.1)'}"
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          },
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          "execution_count": 56
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