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  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "8c8s6PNOvn2p"
      },
      "outputs": [],
      "source": [
        "#from google.colab import drive\n",
        "#drive.mount('/content/drive')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install datasets"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EuzO7di90z5T",
        "outputId": "61c41ef5-0024-4225-991b-357bf3e916a1"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: datasets in /usr/local/lib/python3.10/dist-packages (2.20.0)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from datasets) (3.15.3)\n",
            "Requirement already satisfied: numpy>=1.17 in /usr/local/lib/python3.10/dist-packages (from datasets) (1.25.2)\n",
            "Requirement already satisfied: pyarrow>=15.0.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (16.1.0)\n",
            "Requirement already satisfied: pyarrow-hotfix in /usr/local/lib/python3.10/dist-packages (from datasets) (0.6)\n",
            "Requirement already satisfied: dill<0.3.9,>=0.3.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.3.8)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from datasets) (2.0.3)\n",
            "Requirement already satisfied: requests>=2.32.2 in /usr/local/lib/python3.10/dist-packages (from datasets) (2.32.3)\n",
            "Requirement already satisfied: tqdm>=4.66.3 in /usr/local/lib/python3.10/dist-packages (from datasets) (4.66.4)\n",
            "Requirement already satisfied: xxhash in /usr/local/lib/python3.10/dist-packages (from datasets) (3.4.1)\n",
            "Requirement already satisfied: multiprocess in /usr/local/lib/python3.10/dist-packages (from datasets) (0.70.16)\n",
            "Requirement already satisfied: fsspec[http]<=2024.5.0,>=2023.1.0 in /usr/local/lib/python3.10/dist-packages (from datasets) (2023.6.0)\n",
            "Requirement already satisfied: aiohttp in /usr/local/lib/python3.10/dist-packages (from datasets) (3.9.5)\n",
            "Requirement already satisfied: huggingface-hub>=0.21.2 in /usr/local/lib/python3.10/dist-packages (from datasets) (0.23.4)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.10/dist-packages (from datasets) (24.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from datasets) (6.0.1)\n",
            "Requirement already satisfied: aiosignal>=1.1.2 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.3.1)\n",
            "Requirement already satisfied: attrs>=17.3.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (23.2.0)\n",
            "Requirement already satisfied: frozenlist>=1.1.1 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.4.1)\n",
            "Requirement already satisfied: multidict<7.0,>=4.5 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (6.0.5)\n",
            "Requirement already satisfied: yarl<2.0,>=1.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (1.9.4)\n",
            "Requirement already satisfied: async-timeout<5.0,>=4.0 in /usr/local/lib/python3.10/dist-packages (from aiohttp->datasets) (4.0.3)\n",
            "Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub>=0.21.2->datasets) (4.12.2)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests>=2.32.2->datasets) (2024.6.2)\n",
            "Requirement already satisfied: python-dateutil>=2.8.2 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2.8.2)\n",
            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2023.4)\n",
            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas->datasets) (2024.1)\n",
            "Requirement already satisfied: six>=1.5 in /usr/local/lib/python3.10/dist-packages (from python-dateutil>=2.8.2->pandas->datasets) (1.16.0)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from datasets import load_dataset\n",
        "\n",
        "ds = load_dataset(\"persiannlp/parsinlu_translation_en_fa\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f2_sUUwE0y7K",
        "outputId": "11678547-45fc-48c5-8d9b-ac449e06dcbd"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "#import pandas as pd\n",
        "#dataframe=pd.read_csv('/content/contentdrive/MyDrive/MTM data/TR2EN.txt',sep='\\t')"
      ],
      "metadata": {
        "id": "W2ZP0ln-v8yk"
      },
      "execution_count": 4,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ds.column_names"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QIOf_1df1C3E",
        "outputId": "cf8ee4a8-1815-43ed-fb4f-19ffaa73c47c"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'train': ['source', 'targets', 'category'],\n",
              " 'test': ['source', 'targets', 'category'],\n",
              " 'validation': ['source', 'targets', 'category']}"
            ]
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_data= ds['train']\n",
        "test_set= ds['test']\n",
        "validation_set= ds['validation']"
      ],
      "metadata": {
        "id": "nzJBxGga1Mlk"
      },
      "execution_count": 6,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "train_data[0]"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LXygIaV1KE9g",
        "outputId": "aadd0d38-3ec0-47c1-e875-3159df7b82de"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'source': 'Due Thank You note by Egyptian blogger Abdel Monem Mahmoud: Following his release from prison, he wrote his first blog titled “Ana ikhwan… I am free”.',\n",
              " 'targets': ['بلاگر مصری عبدل منعم محمود (عربی) پس از آزاد شدنش از زندان تیتر اولین مطلب خود را «من آزاد هستم» (عربی) انتخاب کرد.'],\n",
              " 'category': 'global_voices_en_fa'}"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(train_data)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "4rhaY-iAKaav",
        "outputId": "1679df13-7a00-4d68-de61-7dd9aaf3f351"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "1621665"
            ]
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(train_data[0]['source'])\n",
        "print(train_data[0]['targets'][0])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nqXoAs3P1cre",
        "outputId": "3d237d12-23f4-4273-d7bc-93b55f5e9081"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Due Thank You note by Egyptian blogger Abdel Monem Mahmoud: Following his release from prison, he wrote his first blog titled “Ana ikhwan… I am free”.\n",
            "بلاگر مصری عبدل منعم محمود (عربی) پس از آزاد شدنش از زندان تیتر اولین مطلب خود را «من آزاد هستم» (عربی) انتخاب کرد.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_data_source=[]\n",
        "train_data_targets=[]\n",
        "\n",
        "for i in range(40000):\n",
        "   train_data_source.append(train_data[i]['source'])\n",
        "   train_data_targets.append(train_data[i]['targets'][0])"
      ],
      "metadata": {
        "id": "cZZ7_UTk334W"
      },
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "print(len(train_data_source))\n",
        "print(len(train_data_targets))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-Wh7uhVb5DGU",
        "outputId": "b2623840-4475-4734-c976-e8e8a16b4733"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "40000\n",
            "40000\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(train_data_source[3])\n",
        "print(train_data_targets[3])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qF1HgVLoKn15",
        "outputId": "33f8fc79-d9f0-4c6e-d811-bd27571ea906"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "He had the intention to write about his last experience in detention, however he felt so overwhelmed with the sincere feelings from everyone around that he could not write but to thank everyone.\n",
            "وی گفت در ابتدا قصد داشت درباره تجربه‌اش در زندان بنویسد ولی از احساسات تمامی اطرافیانش چنان به وجد آمده که فقط می‌تواند تشکر کند.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "7PkfEZlJwZE0"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#data=[]\n",
        "#for item in dataframe[:10000] .iterrows():\n",
        " #   data.append(['Eng to Tur', item[1].EN, item[1].TR])\n",
        "prefix=[]\n",
        "for i in range (40000):\n",
        "   prefix.append('En to Fa translation')"
      ],
      "metadata": {
        "collapsed": true,
        "id": "QyT7SQSpwA4K"
      },
      "execution_count": 13,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd"
      ],
      "metadata": {
        "id": "ei7sM8Ce51dp"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "ddata= [prefix,train_data_source,train_data_targets]\n",
        "maindata= pd.DataFrame(zip(*ddata), columns=['prefix','input_text', 'target_text'])"
      ],
      "metadata": {
        "id": "X36BN0mkyH37"
      },
      "execution_count": 15,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "OkpKGdYn6tfX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "maindata.head()"
      ],
      "metadata": {
        "id": "zQquofm9A5th",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "outputId": "b02b39b1-b41a-4703-8c43-94a882b2f0f3"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 prefix                                         input_text  \\\n",
              "0  En to Fa translation  Due Thank You note by Egyptian blogger Abdel M...   \n",
              "1  En to Fa translation  He thanked all fellow bloggers and organizatio...   \n",
              "2  En to Fa translation  He was extremely surprised and happy to receiv...   \n",
              "3  En to Fa translation  He had the intention to write about his last e...   \n",
              "4  En to Fa translation  He concludes his post saying that freedom is t...   \n",
              "\n",
              "                                         target_text  \n",
              "0  بلاگر مصری عبدل منعم محمود (عربی) پس از آزاد ش...  \n",
              "1  وی از تمامی بلاگرها، سازمان‌ها و افرادی که از ...  \n",
              "2  وی همچنین از دریافت تعداد بسیار زیادی پیام تبر...  \n",
              "3  وی گفت در ابتدا قصد داشت درباره تجربه‌اش در زن...  \n",
              "4  وی در پایان نوشته‌اش می‌نویسد آزادی واقعا بها ...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-a78cfa2d-90ea-43d8-b1fc-05262586c1f5\" class=\"colab-df-container\">\n",
              "    <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>prefix</th>\n",
              "      <th>input_text</th>\n",
              "      <th>target_text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>Due Thank You note by Egyptian blogger Abdel M...</td>\n",
              "      <td>بلاگر مصری عبدل منعم محمود (عربی) پس از آزاد ش...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He thanked all fellow bloggers and organizatio...</td>\n",
              "      <td>وی از تمامی بلاگرها، سازمان‌ها و افرادی که از ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He was extremely surprised and happy to receiv...</td>\n",
              "      <td>وی همچنین از دریافت تعداد بسیار زیادی پیام تبر...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He had the intention to write about his last e...</td>\n",
              "      <td>وی گفت در ابتدا قصد داشت درباره تجربه‌اش در زن...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He concludes his post saying that freedom is t...</td>\n",
              "      <td>وی در پایان نوشته‌اش می‌نویسد آزادی واقعا بها ...</td>\n",
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              "    <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a78cfa2d-90ea-43d8-b1fc-05262586c1f5')\"\n",
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              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
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              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-a78cfa2d-90ea-43d8-b1fc-05262586c1f5 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-a78cfa2d-90ea-43d8-b1fc-05262586c1f5');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' 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",
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              "\n",
              "\n",
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              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
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              "      --disabled-fill-color: #AAA;\n",
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              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
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              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-ab5bd635-2401-4cd8-99d9-b15f7cdf491f button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "maindata",
              "summary": "{\n  \"name\": \"maindata\",\n  \"rows\": 40000,\n  \"fields\": [\n    {\n      \"column\": \"prefix\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"En to Fa translation\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"input_text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 39754,\n        \"samples\": [\n          \"Mugabe responded to allegations of rigging by telling critics to \\\"go hang.\\\"\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"target_text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 39730,\n        \"samples\": [\n          \"\\u0645\\u0623\\u0645\\u0648\\u0631 \\u067e\\u0644\\u06cc\\u0633: \\u062e\\u0628 \\u062f\\u06cc \\u06af\\u0647\\u060c \\u0628\\u0647 \\u0633\\u0647 \\u062f\\u06cc \\u06af\\u0647!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "maindata.head()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 206
        },
        "id": "HKL5phYEyidM",
        "outputId": "edc54791-aabd-4c9f-c776-dcf85d8e55e3"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                 prefix                                         input_text  \\\n",
              "0  En to Fa translation  Due Thank You note by Egyptian blogger Abdel M...   \n",
              "1  En to Fa translation  He thanked all fellow bloggers and organizatio...   \n",
              "2  En to Fa translation  He was extremely surprised and happy to receiv...   \n",
              "3  En to Fa translation  He had the intention to write about his last e...   \n",
              "4  En to Fa translation  He concludes his post saying that freedom is t...   \n",
              "\n",
              "                                         target_text  \n",
              "0  بلاگر مصری عبدل منعم محمود (عربی) پس از آزاد ش...  \n",
              "1  وی از تمامی بلاگرها، سازمان‌ها و افرادی که از ...  \n",
              "2  وی همچنین از دریافت تعداد بسیار زیادی پیام تبر...  \n",
              "3  وی گفت در ابتدا قصد داشت درباره تجربه‌اش در زن...  \n",
              "4  وی در پایان نوشته‌اش می‌نویسد آزادی واقعا بها ...  "
            ],
            "text/html": [
              "\n",
              "  <div id=\"df-1eaf93ab-4027-4a17-9b52-afdf1a676c39\" class=\"colab-df-container\">\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
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              "      <th></th>\n",
              "      <th>prefix</th>\n",
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>Due Thank You note by Egyptian blogger Abdel M...</td>\n",
              "      <td>بلاگر مصری عبدل منعم محمود (عربی) پس از آزاد ش...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He thanked all fellow bloggers and organizatio...</td>\n",
              "      <td>وی از تمامی بلاگرها، سازمان‌ها و افرادی که از ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He was extremely surprised and happy to receiv...</td>\n",
              "      <td>وی همچنین از دریافت تعداد بسیار زیادی پیام تبر...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He had the intention to write about his last e...</td>\n",
              "      <td>وی گفت در ابتدا قصد داشت درباره تجربه‌اش در زن...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He concludes his post saying that freedom is t...</td>\n",
              "      <td>وی در پایان نوشته‌اش می‌نویسد آزادی واقعا بها ...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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              "    <div class=\"colab-df-buttons\">\n",
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              "        document.querySelector('#df-1eaf93ab-4027-4a17-9b52-afdf1a676c39 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
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              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-1eaf93ab-4027-4a17-9b52-afdf1a676c39');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' 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",
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              "            title=\"Suggest charts\"\n",
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              "\n",
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              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
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              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "\n",
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              "    background-color: var(--bg-color);\n",
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              "    border-radius: 50%;\n",
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              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
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              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
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              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-861679b8-35df-44f7-b1da-32eb6a568305 button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "maindata",
              "summary": "{\n  \"name\": \"maindata\",\n  \"rows\": 40000,\n  \"fields\": [\n    {\n      \"column\": \"prefix\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"En to Fa translation\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"input_text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 39754,\n        \"samples\": [\n          \"Mugabe responded to allegations of rigging by telling critics to \\\"go hang.\\\"\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"target_text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 39730,\n        \"samples\": [\n          \"\\u0645\\u0623\\u0645\\u0648\\u0631 \\u067e\\u0644\\u06cc\\u0633: \\u062e\\u0628 \\u062f\\u06cc \\u06af\\u0647\\u060c \\u0628\\u0647 \\u0633\\u0647 \\u062f\\u06cc \\u06af\\u0647!\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "train_df= maindata[:34000]\n",
        "eval_df = maindata [34000:40000]"
      ],
      "metadata": {
        "id": "fnFwgbhXyn8a"
      },
      "execution_count": 18,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "train_df"
      ],
      "metadata": {
        "collapsed": true,
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 423
        },
        "id": "VeWR4t2My2sr",
        "outputId": "c2084a60-476e-4bed-9bf5-a82a04061bbf"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "                     prefix  \\\n",
              "0      En to Fa translation   \n",
              "1      En to Fa translation   \n",
              "2      En to Fa translation   \n",
              "3      En to Fa translation   \n",
              "4      En to Fa translation   \n",
              "...                     ...   \n",
              "33995  En to Fa translation   \n",
              "33996  En to Fa translation   \n",
              "33997  En to Fa translation   \n",
              "33998  En to Fa translation   \n",
              "33999  En to Fa translation   \n",
              "\n",
              "                                              input_text  \\\n",
              "0      Due Thank You note by Egyptian blogger Abdel M...   \n",
              "1      He thanked all fellow bloggers and organizatio...   \n",
              "2      He was extremely surprised and happy to receiv...   \n",
              "3      He had the intention to write about his last e...   \n",
              "4      He concludes his post saying that freedom is t...   \n",
              "...                                                  ...   \n",
              "33995  Presently the talking to wore itself out in as...   \n",
              "33996                    The parents were now satisfied.   \n",
              "33997  Dorothy had had her lesson and would doubtless...   \n",
              "33998  they did not bear her any malice and were not ...   \n",
              "33999  They said good bye to Mrs Creevy, said good by...   \n",
              "\n",
              "                                             target_text  \n",
              "0      بلاگر مصری عبدل منعم محمود (عربی) پس از آزاد ش...  \n",
              "1      وی از تمامی بلاگرها، سازمان‌ها و افرادی که از ...  \n",
              "2      وی همچنین از دریافت تعداد بسیار زیادی پیام تبر...  \n",
              "3      وی گفت در ابتدا قصد داشت درباره تجربه‌اش در زن...  \n",
              "4      وی در پایان نوشته‌اش می‌نویسد آزادی واقعا بها ...  \n",
              "...                                                  ...  \n",
              "33995  لحظاتی بعد تذکر دادن‌های خانم کری وی بالاخره ب...  \n",
              "33996                   پدر و مادرها دیگر راضی شده بودند  \n",
              "33997  در وتی نیز درس عبرت لازم را گرفته و شکی نبود ک...  \n",
              "33998  آن‌ها نیز در واقع هیچ خصومتی ‌نسبت به وی نداشت...  \n",
              "33999  آنان با خانم کری وی و دروتی البته با لحنی سردت...  \n",
              "\n",
              "[34000 rows x 3 columns]"
            ],
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              "\n",
              "  <div id=\"df-41763bc7-4c6a-4bfc-a0e8-7db7d0a37b82\" class=\"colab-df-container\">\n",
              "    <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",
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              "<table border=\"1\" class=\"dataframe\">\n",
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              "      <th></th>\n",
              "      <th>prefix</th>\n",
              "      <th>input_text</th>\n",
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              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>Due Thank You note by Egyptian blogger Abdel M...</td>\n",
              "      <td>بلاگر مصری عبدل منعم محمود (عربی) پس از آزاد ش...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He thanked all fellow bloggers and organizatio...</td>\n",
              "      <td>وی از تمامی بلاگرها، سازمان‌ها و افرادی که از ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He was extremely surprised and happy to receiv...</td>\n",
              "      <td>وی همچنین از دریافت تعداد بسیار زیادی پیام تبر...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He had the intention to write about his last e...</td>\n",
              "      <td>وی گفت در ابتدا قصد داشت درباره تجربه‌اش در زن...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He concludes his post saying that freedom is t...</td>\n",
              "      <td>وی در پایان نوشته‌اش می‌نویسد آزادی واقعا بها ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33995</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>Presently the talking to wore itself out in as...</td>\n",
              "      <td>لحظاتی بعد تذکر دادن‌های خانم کری وی بالاخره ب...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33996</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>The parents were now satisfied.</td>\n",
              "      <td>پدر و مادرها دیگر راضی شده بودند</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33997</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>Dorothy had had her lesson and would doubtless...</td>\n",
              "      <td>در وتی نیز درس عبرت لازم را گرفته و شکی نبود ک...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33998</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>they did not bear her any malice and were not ...</td>\n",
              "      <td>آن‌ها نیز در واقع هیچ خصومتی ‌نسبت به وی نداشت...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33999</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>They said good bye to Mrs Creevy, said good by...</td>\n",
              "      <td>آنان با خانم کری وی و دروتی البته با لحنی سردت...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>34000 rows × 3 columns</p>\n",
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              "  </svg>\n",
              "    </button>\n",
              "\n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
              "      const buttonEl =\n",
              "        document.querySelector('#df-41763bc7-4c6a-4bfc-a0e8-7db7d0a37b82 button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-41763bc7-4c6a-4bfc-a0e8-7db7d0a37b82');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' 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",
              "\n",
              "\n",
              "<div id=\"df-00560c02-1ee9-41fa-9777-cc272011846a\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-00560c02-1ee9-41fa-9777-cc272011846a')\"\n",
              "            title=\"Suggest charts\"\n",
              "            style=\"display:none;\">\n",
              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "     width=\"24px\">\n",
              "    <g>\n",
              "        <path d=\"M19 3H5c-1.1 0-2 .9-2 2v14c0 1.1.9 2 2 2h14c1.1 0 2-.9 2-2V5c0-1.1-.9-2-2-2zM9 17H7v-7h2v7zm4 0h-2V7h2v10zm4 0h-2v-4h2v4z\"/>\n",
              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
              "      --hover-fill-color: #FFFFFF;\n",
              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    30% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    40% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-top-color: var(--fill-color);\n",
              "    }\n",
              "    60% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-00560c02-1ee9-41fa-9777-cc272011846a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "dataframe",
              "variable_name": "train_df",
              "summary": "{\n  \"name\": \"train_df\",\n  \"rows\": 34000,\n  \"fields\": [\n    {\n      \"column\": \"prefix\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"En to Fa translation\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"input_text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 33858,\n        \"samples\": [\n          \"So, organically, I was efficient in the desert, felt neither hunger nor surfeit, and was not distracted by thought of food.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"target_text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 33814,\n        \"samples\": [\n          \"\\u0622\\u0646 \\u067e\\u0644\\u06cc \\u0628\\u0648\\u062f \\u06a9\\u0647 \\u0645\\u0627 \\u0627\\u0632 \\u0628\\u0627\\u0644\\u0627 \\u0645\\u06cc\\u200c\\u062f\\u06cc\\u062f\\u06cc\\u0645.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install simpletransformers==0.61.0"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ou4tRtmQzTS6",
        "outputId": "e95e5b48-c3c6-4e55-ace1-aa476db1df8d"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: simpletransformers==0.61.0 in /usr/local/lib/python3.10/dist-packages (0.61.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (1.25.2)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (2.32.3)\n",
            "Requirement already satisfied: tqdm>=4.47.0 in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (4.66.4)\n",
            "Requirement already satisfied: regex in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (2024.5.15)\n",
            "Requirement already satisfied: transformers>=4.2.0 in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (4.41.2)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (1.11.4)\n",
            "Requirement already satisfied: scikit-learn in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (1.2.2)\n",
            "Requirement already satisfied: seqeval in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (1.2.2)\n",
            "Requirement already satisfied: tensorboardx in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (2.6.2.2)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (2.0.3)\n",
            "Requirement already satisfied: tokenizers in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (0.19.1)\n",
            "Requirement already satisfied: wandb in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (0.17.3)\n",
            "Requirement already satisfied: streamlit in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (1.36.0)\n",
            "Requirement already satisfied: sentencepiece in /usr/local/lib/python3.10/dist-packages (from simpletransformers==0.61.0) (0.1.99)\n",
            "Requirement already satisfied: filelock in /usr/local/lib/python3.10/dist-packages (from transformers>=4.2.0->simpletransformers==0.61.0) (3.15.3)\n",
            "Requirement already satisfied: huggingface-hub<1.0,>=0.23.0 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.2.0->simpletransformers==0.61.0) (0.23.4)\n",
            "Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.2.0->simpletransformers==0.61.0) (24.1)\n",
            "Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.2.0->simpletransformers==0.61.0) (6.0.1)\n",
            "Requirement already satisfied: safetensors>=0.4.1 in /usr/local/lib/python3.10/dist-packages (from transformers>=4.2.0->simpletransformers==0.61.0) (0.4.3)\n",
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            "Requirement already satisfied: pytz>=2020.1 in /usr/local/lib/python3.10/dist-packages (from pandas->simpletransformers==0.61.0) (2023.4)\n",
            "Requirement already satisfied: tzdata>=2022.1 in /usr/local/lib/python3.10/dist-packages (from pandas->simpletransformers==0.61.0) (2024.1)\n",
            "Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/dist-packages (from requests->simpletransformers==0.61.0) (3.3.2)\n",
            "Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/dist-packages (from requests->simpletransformers==0.61.0) (3.7)\n",
            "Requirement already satisfied: urllib3<3,>=1.21.1 in /usr/local/lib/python3.10/dist-packages (from requests->simpletransformers==0.61.0) (2.0.7)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/dist-packages (from requests->simpletransformers==0.61.0) (2024.6.2)\n",
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            "Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.10/dist-packages (from scikit-learn->simpletransformers==0.61.0) (3.5.0)\n",
            "Requirement already satisfied: altair<6,>=4.0 in /usr/local/lib/python3.10/dist-packages (from streamlit->simpletransformers==0.61.0) (4.2.2)\n",
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            "Requirement already satisfied: cachetools<6,>=4.0 in /usr/local/lib/python3.10/dist-packages (from streamlit->simpletransformers==0.61.0) (5.3.3)\n",
            "Requirement already satisfied: click<9,>=7.0 in /usr/local/lib/python3.10/dist-packages (from streamlit->simpletransformers==0.61.0) (8.1.7)\n",
            "Requirement already satisfied: pillow<11,>=7.1.0 in /usr/local/lib/python3.10/dist-packages (from streamlit->simpletransformers==0.61.0) (9.4.0)\n",
            "Requirement already satisfied: protobuf<6,>=3.20 in /usr/local/lib/python3.10/dist-packages (from streamlit->simpletransformers==0.61.0) (3.20.3)\n",
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            "Requirement already satisfied: psutil>=5.0.0 in /usr/local/lib/python3.10/dist-packages (from wandb->simpletransformers==0.61.0) (5.9.5)\n",
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            "Requirement already satisfied: setproctitle in /usr/local/lib/python3.10/dist-packages (from wandb->simpletransformers==0.61.0) (1.3.3)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.10/dist-packages (from wandb->simpletransformers==0.61.0) (67.7.2)\n",
            "Requirement already satisfied: entrypoints in /usr/local/lib/python3.10/dist-packages (from altair<6,>=4.0->streamlit->simpletransformers==0.61.0) (0.4)\n",
            "Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/dist-packages (from altair<6,>=4.0->streamlit->simpletransformers==0.61.0) (3.1.4)\n",
            "Requirement already satisfied: jsonschema>=3.0 in /usr/local/lib/python3.10/dist-packages (from altair<6,>=4.0->streamlit->simpletransformers==0.61.0) (4.19.2)\n",
            "Requirement already satisfied: toolz in /usr/local/lib/python3.10/dist-packages (from altair<6,>=4.0->streamlit->simpletransformers==0.61.0) (0.12.1)\n",
            "Requirement already satisfied: six>=1.4.0 in /usr/local/lib/python3.10/dist-packages (from docker-pycreds>=0.4.0->wandb->simpletransformers==0.61.0) (1.16.0)\n",
            "Requirement already satisfied: gitdb<5,>=4.0.1 in /usr/local/lib/python3.10/dist-packages (from gitpython!=3.1.19,<4,>=3.0.7->streamlit->simpletransformers==0.61.0) (4.0.11)\n",
            "Requirement already satisfied: fsspec>=2023.5.0 in /usr/local/lib/python3.10/dist-packages (from huggingface-hub<1.0,>=0.23.0->transformers>=4.2.0->simpletransformers==0.61.0) (2023.6.0)\n",
            "Requirement already satisfied: markdown-it-py>=2.2.0 in /usr/local/lib/python3.10/dist-packages (from rich<14,>=10.14.0->streamlit->simpletransformers==0.61.0) (3.0.0)\n",
            "Requirement already satisfied: pygments<3.0.0,>=2.13.0 in /usr/local/lib/python3.10/dist-packages (from rich<14,>=10.14.0->streamlit->simpletransformers==0.61.0) (2.16.1)\n",
            "Requirement already satisfied: smmap<6,>=3.0.1 in /usr/local/lib/python3.10/dist-packages (from gitdb<5,>=4.0.1->gitpython!=3.1.19,<4,>=3.0.7->streamlit->simpletransformers==0.61.0) (5.0.1)\n",
            "Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/dist-packages (from jinja2->altair<6,>=4.0->streamlit->simpletransformers==0.61.0) (2.1.5)\n",
            "Requirement already satisfied: attrs>=22.2.0 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit->simpletransformers==0.61.0) (23.2.0)\n",
            "Requirement already satisfied: jsonschema-specifications>=2023.03.6 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit->simpletransformers==0.61.0) (2023.12.1)\n",
            "Requirement already satisfied: referencing>=0.28.4 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit->simpletransformers==0.61.0) (0.35.1)\n",
            "Requirement already satisfied: rpds-py>=0.7.1 in /usr/local/lib/python3.10/dist-packages (from jsonschema>=3.0->altair<6,>=4.0->streamlit->simpletransformers==0.61.0) (0.18.1)\n",
            "Requirement already satisfied: mdurl~=0.1 in /usr/local/lib/python3.10/dist-packages (from markdown-it-py>=2.2.0->rich<14,>=10.14.0->streamlit->simpletransformers==0.61.0) (0.1.2)\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from simpletransformers.t5 import T5Model, T5Args"
      ],
      "metadata": {
        "id": "pD0PoLBNy7jh"
      },
      "execution_count": 21,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "source": [],
      "metadata": {
        "id": "LN9lDWu4L0af"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "model_args= T5Args()"
      ],
      "metadata": {
        "id": "eMBjjmyRzzxS"
      },
      "execution_count": 22,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_args.fp16= False\n",
        "model_args.max_seq_length= 128\n",
        "model_args.train_batch_size= 8\n",
        "model_args.eval_batch_size = 8\n",
        "model_args.num_train_epochs = 5\n",
        "model_args.evaluate_during_training= True\n",
        "model_args.evaluate_during_training_steps= 10000\n",
        "model_args.use_multiprocessing= False\n",
        "model_args.reprocess_input_data=True\n",
        "model_args.overwrite_output_dir= True\n",
        "model_args.save_steps=-1\n",
        "model_args.no_cache= True\n",
        "model_args.preprocess_inputs= False\n",
        "model_args.num_return_sequences = 1\n",
        "model_args.save_eval_checkpoints= False\n",
        "model_args.max_length=128\n",
        "model_args.num_beams=4\n"
      ],
      "metadata": {
        "id": "jPR0GUJv0AD6"
      },
      "execution_count": 23,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model= T5Model (\"mt5\", \"google/mt5-base\",args=model_args, use_cuda=True)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "osAM_qp_1Yn7",
        "outputId": "69b8afd5-8a79-4050-e804-5b102ee2cdab"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/file_download.py:1132: FutureWarning: `resume_download` is deprecated and will be removed in version 1.0.0. Downloads always resume when possible. If you want to force a new download, use `force_download=True`.\n",
            "  warnings.warn(\n",
            "You are using the default legacy behaviour of the <class 'transformers.models.t5.tokenization_t5.T5Tokenizer'>. This is expected, and simply means that the `legacy` (previous) behavior will be used so nothing changes for you. If you want to use the new behaviour, set `legacy=False`. This should only be set if you understand what it means, and thoroughly read the reason why this was added as explained in https://github.com/huggingface/transformers/pull/24565\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "print(len(train_df))\n",
        "print (len(eval_df))"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BQYFe5uC5qQx",
        "outputId": "27fab1ad-513e-4690-f7d2-975977a97f05"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "34000\n",
            "6000\n"
          ]
        }
      ]
    },
    {
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      "execution_count": 26,
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            "text/plain": [
              "                 prefix                                         input_text  \\\n",
              "0  En to Fa translation  Due Thank You note by Egyptian blogger Abdel M...   \n",
              "1  En to Fa translation  He thanked all fellow bloggers and organizatio...   \n",
              "2  En to Fa translation  He was extremely surprised and happy to receiv...   \n",
              "3  En to Fa translation  He had the intention to write about his last e...   \n",
              "4  En to Fa translation  He concludes his post saying that freedom is t...   \n",
              "\n",
              "                                         target_text  \n",
              "0  بلاگر مصری عبدل منعم محمود (عربی) پس از آزاد ش...  \n",
              "1  وی از تمامی بلاگرها، سازمان‌ها و افرادی که از ...  \n",
              "2  وی همچنین از دریافت تعداد بسیار زیادی پیام تبر...  \n",
              "3  وی گفت در ابتدا قصد داشت درباره تجربه‌اش در زن...  \n",
              "4  وی در پایان نوشته‌اش می‌نویسد آزادی واقعا بها ...  "
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              "      <th>1</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He thanked all fellow bloggers and organizatio...</td>\n",
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              "      <th>2</th>\n",
              "      <td>En to Fa translation</td>\n",
              "      <td>He was extremely surprised and happy to receiv...</td>\n",
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              "      <td>He had the intention to write about his last e...</td>\n",
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              "variable_name": "train_df",
              "summary": "{\n  \"name\": \"train_df\",\n  \"rows\": 34000,\n  \"fields\": [\n    {\n      \"column\": \"prefix\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 1,\n        \"samples\": [\n          \"En to Fa translation\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"input_text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 33858,\n        \"samples\": [\n          \"So, organically, I was efficient in the desert, felt neither hunger nor surfeit, and was not distracted by thought of food.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"target_text\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 33814,\n        \"samples\": [\n          \"\\u0622\\u0646 \\u067e\\u0644\\u06cc \\u0628\\u0648\\u062f \\u06a9\\u0647 \\u0645\\u0627 \\u0627\\u0632 \\u0628\\u0627\\u0644\\u0627 \\u0645\\u06cc\\u200c\\u062f\\u06cc\\u062f\\u06cc\\u0645.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
            }
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
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        "model.train_model(train_data=train_df,eval_data=eval_df)"
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        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "  0%|          | 0/34000 [00:00<?, ?it/s]"
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          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:4072: FutureWarning: \n",
            "`prepare_seq2seq_batch` is deprecated and will be removed in version 5 of HuggingFace Transformers. Use the regular\n",
            "`__call__` method to prepare your inputs and targets.\n",
            "\n",
            "Here is a short example:\n",
            "\n",
            "model_inputs = tokenizer(src_texts, text_target=tgt_texts, ...)\n",
            "\n",
            "If you either need to use different keyword arguments for the source and target texts, you should do two calls like\n",
            "this:\n",
            "\n",
            "model_inputs = tokenizer(src_texts, ...)\n",
            "labels = tokenizer(text_target=tgt_texts, ...)\n",
            "model_inputs[\"labels\"] = labels[\"input_ids\"]\n",
            "\n",
            "See the documentation of your specific tokenizer for more details on the specific arguments to the tokenizer of choice.\n",
            "For a more complete example, see the implementation of `prepare_seq2seq_batch`.\n",
            "\n",
            "  warnings.warn(formatted_warning, FutureWarning)\n",
            "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:3946: UserWarning: `as_target_tokenizer` is deprecated and will be removed in v5 of Transformers. You can tokenize your labels by using the argument `text_target` of the regular `__call__` method (either in the same call as your input texts if you use the same keyword arguments, or in a separate call.\n",
            "  warnings.warn(\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Using Adafactor for T5\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "Epoch:   0%|          | 0/5 [00:00<?, ?it/s]"
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          "data": {
            "text/plain": [
              "Running Epoch 0 of 5:   0%|          | 0/4250 [00:00<?, ?it/s]"
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          "traceback": [
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            "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
            "\u001b[0;32m<ipython-input-28-3bf9845e878f>\u001b[0m in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtrain_model\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtrain_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtrain_df\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0meval_data\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0meval_df\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/python3.10/dist-packages/simpletransformers/t5/t5_model.py\u001b[0m in \u001b[0;36mtrain_model\u001b[0;34m(self, train_data, output_dir, show_running_loss, args, eval_data, verbose, **kwargs)\u001b[0m\n\u001b[1;32m    198\u001b[0m         \u001b[0mos\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmakedirs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0moutput_dir\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mexist_ok\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    199\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 200\u001b[0;31m         global_step, training_details = self.train(\n\u001b[0m\u001b[1;32m    201\u001b[0m             \u001b[0mtrain_dataset\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    202\u001b[0m             \u001b[0moutput_dir\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/python3.10/dist-packages/simpletransformers/t5/t5_model.py\u001b[0m in \u001b[0;36mtrain\u001b[0;34m(self, train_dataset, output_dir, show_running_loss, eval_data, verbose, **kwargs)\u001b[0m\n\u001b[1;32m    476\u001b[0m                         \u001b[0mscaler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mupdate\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    477\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--> 478\u001b[0;31m                         \u001b[0moptimizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\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    479\u001b[0m                     \u001b[0mscheduler\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstep\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m  \u001b[0;31m# Update learning rate schedule\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    480\u001b[0m                     \u001b[0mmodel\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mzero_grad\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[0;32m/usr/local/lib/python3.10/dist-packages/torch/optim/lr_scheduler.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     73\u001b[0m                 \u001b[0minstance\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_step_count\u001b[0m \u001b[0;34m+=\u001b[0m \u001b[0;36m1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     74\u001b[0m                 \u001b[0mwrapped\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__get__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minstance\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---> 75\u001b[0;31m                 \u001b[0;32mreturn\u001b[0m \u001b[0mwrapped\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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     76\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     77\u001b[0m             \u001b[0;31m# Note that the returned function here is no longer a bound method,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/optim/optimizer.py\u001b[0m in \u001b[0;36mwrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    389\u001b[0m                             )\n\u001b[1;32m    390\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 391\u001b[0;31m                 \u001b[0mout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    392\u001b[0m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_optimizer_step_code\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    393\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/torch/utils/_contextlib.py\u001b[0m in \u001b[0;36mdecorate_context\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    113\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mdecorate_context\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    114\u001b[0m         \u001b[0;32mwith\u001b[0m \u001b[0mctx_factory\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[0;32m--> 115\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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    116\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    117\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mdecorate_context\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;32m/usr/local/lib/python3.10/dist-packages/transformers/optimization.py\u001b[0m in \u001b[0;36mstep\u001b[0;34m(self, closure)\u001b[0m\n\u001b[1;32m    872\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    873\u001b[0m                 \u001b[0mbeta2t\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m1.0\u001b[0m \u001b[0;34m-\u001b[0m \u001b[0mmath\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpow\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"step\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"decay_rate\"\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[0;32m--> 874\u001b[0;31m                 \u001b[0mupdate\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mgrad\u001b[0m\u001b[0;34m**\u001b[0m\u001b[0;36m2\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mgroup\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"eps\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\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    875\u001b[0m                 \u001b[0;32mif\u001b[0m \u001b[0mfactored\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    876\u001b[0m                     \u001b[0mexp_avg_sq_row\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mstate\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"exp_avg_sq_row\"\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/python3.10/dist-packages/torch/_tensor.py\u001b[0m in \u001b[0;36mwrapped\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m     38\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mhas_torch_function\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[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     39\u001b[0m                 \u001b[0;32mreturn\u001b[0m \u001b[0mhandle_torch_function\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mwrapped\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 40\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\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     41\u001b[0m         \u001b[0;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     42\u001b[0m             \u001b[0;32mreturn\u001b[0m \u001b[0mNotImplemented\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
            "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!cp -r '/content/outputs/best_model' '/content/contentdrive/MyDrive/MT5 en to Persian MT'\n",
        "\n"
      ],
      "metadata": {
        "id": "RDJzUqcN-FJn"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.predict('this is a good day')"
      ],
      "metadata": {
        "id": "RTqFbR4g_DQQ"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model.predict('this is a good day')"
      ],
      "metadata": {
        "id": "YbRujANwAMwo"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "y"
      ],
      "metadata": {
        "id": "ScZ9k_WkPsq2"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import (T5Tokenizer, MT5ForConditionalGeneration, Text2TextGenerationPipeline, )\n",
        "\n",
        "path = \"/content/outputs/best_model\"\n",
        "\n",
        "pipe = Text2TextGenerationPipeline( model=MT5ForConditionalGeneration.from_pretrained(path), tokenizer=T5Tokenizer.from_pretrained(path), )\n"
      ],
      "metadata": {
        "id": "Li13g670OA8N"
      },
      "execution_count": 35,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "sentence = \"How do yu know that this book is good.\"\n",
        "\n",
        "#res = pipe(sentence, max_length=100, num_beams=4\n",
        "\n",
        "res = pipe(sentence, max_length=128,num_beams=4)\n",
        "\n",
        "print(res[0]['generated_text'])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "c_lDFMwPDws3",
        "outputId": "b64ee6d1-08f8-4439-9e05-23deb04b17ba"
      },
      "execution_count": 36,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "این کتاب خوب است.\n"
          ]
        }
      ]
    }
  ]
}