MarianMT_Final.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "source": [
        "#### Cell to run\n",
        "!pip install datasets\n",
        "!pip install evaluate"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TI4jPUBRJP21",
        "outputId": "df502512-dd63-4bef-fafe-5753b9a8ec66"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting datasets\n",
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            "\u001b[?25hInstalling collected packages: xxhash, requests, pyarrow, fsspec, dill, multiprocess, datasets\n",
            "  Attempting uninstall: requests\n",
            "    Found existing installation: requests 2.31.0\n",
            "    Uninstalling requests-2.31.0:\n",
            "      Successfully uninstalled requests-2.31.0\n",
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            "    Found existing installation: pyarrow 14.0.2\n",
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            "      Successfully uninstalled pyarrow-14.0.2\n",
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            "      Successfully uninstalled fsspec-2024.6.1\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "torch 2.3.1+cu121 requires nvidia-cublas-cu12==12.1.3.1; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cuda-cupti-cu12==12.1.105; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cuda-nvrtc-cu12==12.1.105; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cuda-runtime-cu12==12.1.105; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cudnn-cu12==8.9.2.26; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cufft-cu12==11.0.2.54; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-curand-cu12==10.3.2.106; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cusolver-cu12==11.4.5.107; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-cusparse-cu12==12.1.0.106; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-nccl-cu12==2.20.5; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "torch 2.3.1+cu121 requires nvidia-nvtx-cu12==12.1.105; platform_system == \"Linux\" and platform_machine == \"x86_64\", which is not installed.\n",
            "cudf-cu12 24.4.1 requires pyarrow<15.0.0a0,>=14.0.1, but you have pyarrow 17.0.0 which is incompatible.\n",
            "gcsfs 2024.6.1 requires fsspec==2024.6.1, but you have fsspec 2024.5.0 which is incompatible.\n",
            "google-colab 1.0.0 requires requests==2.31.0, but you have requests 2.32.3 which is incompatible.\n",
            "ibis-framework 8.0.0 requires pyarrow<16,>=2, but you have pyarrow 17.0.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[0mSuccessfully installed datasets-2.20.0 dill-0.3.8 fsspec-2024.5.0 multiprocess-0.70.16 pyarrow-17.0.0 requests-2.32.3 xxhash-3.4.1\n",
            "Collecting evaluate\n",
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            "\u001b[?25hInstalling collected packages: evaluate\n",
            "Successfully installed evaluate-0.4.2\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "BI5MUgtuG459"
      },
      "outputs": [],
      "source": [
        "#### Cell to run\n",
        "\n",
        "import pandas as pd\n",
        "import torch\n",
        "import torch.nn as nn\n",
        "from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, TrainingArguments, Trainer\n",
        "from transformers import MarianMTModel, MarianTokenizer, AdamW\n",
        "import torch.distributed as dist\n",
        "from tqdm import tqdm\n",
        "from transformers import pipeline\n",
        "import evaluate\n",
        "import shutil\n",
        "from torch.utils.data import Dataset, DataLoader, ConcatDataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "qmvY3YWpG45_"
      },
      "outputs": [],
      "source": [
        "#### Cell to run\n",
        "\n",
        "# Loading Train, Test and Validation data of multilingual data\n",
        "\n",
        "Dutch_train_data = pd.read_csv('Dutch_train.csv')\n",
        "Dutch_val_data = pd.read_csv('Dutch_validation.csv')\n",
        "Dutch_test_data = pd.read_csv('Dutch_test.csv')\n",
        "\n",
        "Dutch_train_data = Dutch_train_data.drop(columns = ['Unnamed: 0'])\n",
        "Dutch_val_data = Dutch_val_data.drop(columns = ['Unnamed: 0'])\n",
        "Dutch_test_data = Dutch_test_data.drop(columns = ['Unnamed: 0'])\n",
        "\n",
        "German_train_data = pd.read_csv('German_train.csv')\n",
        "German_val_data = pd.read_csv('German_validation.csv')\n",
        "German_test_data = pd.read_csv('German_test.csv')\n",
        "\n",
        "German_train_data = German_train_data.drop(columns = ['Unnamed: 0'])\n",
        "German_val_data = German_val_data.drop(columns = ['Unnamed: 0'])\n",
        "German_test_data = German_test_data.drop(columns = ['Unnamed: 0'])\n",
        "\n",
        "Spanish_train_data = pd.read_csv('Spanish_train.csv')\n",
        "Spanish_val_data = pd.read_csv('Spanish_validation.csv')\n",
        "Spanish_test_data = pd.read_csv('Spanish_test.csv')\n",
        "\n",
        "Spanish_train_data = Spanish_train_data.drop(columns = ['Unnamed: 0'])\n",
        "Spanish_val_data = Spanish_val_data.drop(columns = ['Unnamed: 0'])\n",
        "Spanish_test_data = Spanish_test_data.drop(columns = ['Unnamed: 0'])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "5L-9wgy0G45_"
      },
      "source": [
        "#### MarianMT\n",
        "\n",
        "Three models for three languages\n",
        "\n",
        "Spanish Use:  model_name = \"Helsinki-NLP/opus-mt-en-es\"\n",
        "\n",
        "German Use: model_name  = \"Helsinki-NLP/opus-mt-en-de\"\n",
        "\n",
        "Dutch Use: model_name = \"Helsinki-NLP/opus-mt-en-nl\"\n",
        "\n",
        "So training requires separate datasets which makes it three models for MarianMT"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "n3JIZMVvG46B",
        "outputId": "4c7f1ec2-1cd2-4751-af80-e1d222d4b643"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/Users/marianivethaantonypushparaj/Library/Python/3.9/lib/python/site-packages/transformers/models/marian/tokenization_marian.py:197: UserWarning: Recommended: pip install sacremoses.\n",
            "  warnings.warn(\"Recommended: pip install sacremoses.\")\n"
          ]
        }
      ],
      "source": [
        "model_name = \"Helsinki-NLP/opus-mt-en-nl\"\n",
        "tokenizer = MarianTokenizer.from_pretrained(model_name)\n",
        "model = MarianMTModel.from_pretrained(model_name)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "HkqKBV0eG46B",
        "outputId": "18f9dc75-9a4c-4d45-de14-c32ac10a5915"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['En, zeg ik tegen mevrouw Reding, dank u voor de steun en de hulp die u tot nu toe hebt gegeven, ga door met het goede werk, we staan aan uw kant.',\n",
              " 'Ik zou u een paar voorbeelden willen geven om deze tegenstrijdigheden te illustreren.',\n",
              " 'De stemming vindt morgen om 11.00 uur plaats.']"
            ]
          },
          "execution_count": 27,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "src_text = Dutch_test_data[1:4]['English'].to_list()\n",
        "\n",
        "translated = model.generate(**tokenizer(src_text, return_tensors=\"pt\", padding=True))\n",
        "tgt_text = [tokenizer.decode(t, skip_special_tokens=True) for t in translated]\n",
        "tgt_text"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "-I7A-6JkG46B"
      },
      "outputs": [],
      "source": [
        "# Create new csv files to store inferences for MarianMT\n",
        "\n",
        "Dutch_outputs_df = Dutch_test_data.copy()\n",
        "Dutch_outputs_df ['MarianMT-pretrained'] = None\n",
        "\n",
        "German_outputs_df = German_test_data.copy()\n",
        "German_outputs_df ['MarianMT-pretrained'] = None\n",
        "\n",
        "Spanish_outputs_df = Spanish_test_data.copy()\n",
        "Spanish_outputs_df ['MarianMT-pretrained'] = None"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "pVSyNVK6G46C",
        "outputId": "9c6618c0-1490-4d9e-c5c3-5e1aa5864fc3"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/Users/marianivethaantonypushparaj/Library/Python/3.9/lib/python/site-packages/transformers/models/marian/tokenization_marian.py:197: UserWarning: Recommended: pip install sacremoses.\n",
            "  warnings.warn(\"Recommended: pip install sacremoses.\")\n",
            "Processing Batches: 100%|██████████| 1468/1468 [36:54<00:00,  1.51s/sentences]\n"
          ]
        }
      ],
      "source": [
        "# Dutch model\n",
        "\n",
        "src_text = Dutch_test_data['English'].to_list()\n",
        "\n",
        "model_name = \"Helsinki-NLP/opus-mt-en-nl\"\n",
        "translator = pipeline(\"translation_en_to_nl\", model=model_name, tokenizer=model_name)\n",
        "\n",
        "translations = []\n",
        "for i in tqdm(range(0, len(src_text)), desc=\"Processing Batches\", unit=\"sentences\"):\n",
        "    translations.append(translator(src_text[i])[0].get('translation_text'))\n",
        "\n",
        "# Run inference\n",
        "Dutch_outputs_df['MarianMT-pretrained'] = translations"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "jl9eqh6wG46C",
        "outputId": "9fc5755d-9f52-4e9b-8780-11a0f1d90f7d"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/Users/marianivethaantonypushparaj/Library/Python/3.9/lib/python/site-packages/transformers/models/marian/tokenization_marian.py:197: UserWarning: Recommended: pip install sacremoses.\n",
            "  warnings.warn(\"Recommended: pip install sacremoses.\")\n",
            "Processing Batches: 100%|██████████| 1478/1478 [36:02<00:00,  1.46s/sentences] \n"
          ]
        }
      ],
      "source": [
        "# German model\n",
        "\n",
        "src_text = German_test_data['English'].to_list()\n",
        "\n",
        "model_name = \"Helsinki-NLP/opus-mt-en-de\"\n",
        "translator = pipeline(\"translation_en_to_de\", model=model_name, tokenizer=model_name)\n",
        "\n",
        "translations = []\n",
        "for i in tqdm(range(0, len(src_text)), desc=\"Processing Batches\", unit=\"sentences\"):\n",
        "    translations.append(translator(src_text[i])[0].get('translation_text'))\n",
        "\n",
        "# Run inference\n",
        "German_outputs_df['MarianMT-pretrained']  = translations"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "K853ol-VG46C",
        "outputId": "fe394e08-1849-4cfc-8af0-82392dc50c87"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Processing Batches: 100%|██████████| 1476/1476 [38:23<00:00,  1.56s/sentences] \n"
          ]
        }
      ],
      "source": [
        "# Spanish\n",
        "\n",
        "src_text = Spanish_test_data['English'].to_list()\n",
        "model_name = \"Helsinki-NLP/opus-mt-en-es\"\n",
        "translator = pipeline(\"translation_en_to_es\", model=model_name, tokenizer=model_name)\n",
        "\n",
        "translations = []\n",
        "for i in tqdm(range(0, len(src_text)), desc=\"Processing Batches\", unit=\"sentences\"):\n",
        "    translations.append(translator(src_text[i])[0].get('translation_text'))\n",
        "\n",
        "# Run inference\n",
        "Spanish_outputs_df['MarianMT-pretrained']  = translations"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "RmnYX-43G46C"
      },
      "outputs": [],
      "source": [
        "# Save the dataframes as csv for evaluation\n",
        "\n",
        "Dutch_outputs_df.to_csv('Dutch outputs_MarianMT.csv',index=False)\n",
        "German_outputs_df.to_csv('German outputs_MarianMT.csv',index=False)\n",
        "Spanish_outputs_df.to_csv('Spanish outputs_MarianMT.csv',index=False)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "referenced_widgets": [
            "016d365debc14d78a40c1332dcbfc38e",
            "f34c33663af641ec900bb18ceead748f"
          ]
        },
        "id": "6bWJ9VNaG46C",
        "outputId": "b10333d8-d978-44c8-e1e1-09ba0213fa3a"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "016d365debc14d78a40c1332dcbfc38e",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Downloading builder script:   0%|          | 0.00/6.27k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f34c33663af641ec900bb18ceead748f",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Downloading builder script:   0%|          | 0.00/6.93k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package wordnet to\n",
            "[nltk_data]     /Users/marianivethaantonypushparaj/nltk_data...\n",
            "[nltk_data]   Package wordnet is already up-to-date!\n",
            "[nltk_data] Downloading package punkt to\n",
            "[nltk_data]     /Users/marianivethaantonypushparaj/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n",
            "[nltk_data] Downloading package omw-1.4 to\n",
            "[nltk_data]     /Users/marianivethaantonypushparaj/nltk_data...\n",
            "[nltk_data]   Package omw-1.4 is already up-to-date!\n"
          ]
        }
      ],
      "source": [
        "bleu_metric = evaluate.load(\"bleu\")\n",
        "rouge_metric = evaluate.load(\"rouge\")\n",
        "meteor_metric = evaluate.load(\"meteor\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "au7cY4BBG46C",
        "outputId": "7db800e1-04cf-4a36-b682-dff45cafe7a6"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "1468"
            ]
          },
          "execution_count": 57,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "len(Dutch_outputs_df['Dutch'].to_list())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_HyKAGInG46D",
        "outputId": "e5b83b5c-3c73-434b-81cb-b265b94f732e"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "BLEU score for Dutch Model: {'bleu': 0.23670363486569077, 'precisions': [0.5444265719155883, 0.28440960557421924, 0.17631714876033058, 0.11498510347048876], 'brevity_penalty': 1.0, 'length_ratio': 1.028951853956177, 'translation_length': 41653, 'reference_length': 40481}\n",
            "ROUGE score for Dutch Model: {'rouge1': 0.54880173272648, 'rouge2': 0.30545784259474906, 'rougeL': 0.4876714408446511, 'rougeLsum': 0.4878248561064088}\n",
            "METEOR score for Dutch Model: {'meteor': 0.4984006043414953}\n",
            "BLEU score for German Model: {'bleu': 0.24035835851731063, 'precisions': [0.5453654860587792, 0.2882448085150788, 0.17962284628951294, 0.1182023742227247], 'brevity_penalty': 1.0, 'length_ratio': 1.0151468788249693, 'translation_length': 39810, 'reference_length': 39216}\n",
            "ROUGE score for German Model: {'rouge1': 0.5291796376818525, 'rouge2': 0.30559721360263276, 'rougeL': 0.48128744855697725, 'rougeLsum': 0.4811391734559068}\n",
            "METEOR score for German Model: {'meteor': 0.5008671134114652}\n",
            "BLEU score for Spanish Model: {'bleu': 0.3383465289519025, 'precisions': [0.6339742703001798, 0.398396104826006, 0.277967443471377, 0.19766874630927622], 'brevity_penalty': 0.9857846726507689, 'length_ratio': 0.9858847596317764, 'translation_length': 43374, 'reference_length': 43995}\n",
            "ROUGE score for Spanish Model: {'rouge1': 0.6200020135941253, 'rouge2': 0.41344765979012843, 'rougeL': 0.5714314942254983, 'rougeLsum': 0.5716072577295339}\n",
            "METEOR score for Spanish Model: {'meteor': 0.5791250577075997}\n"
          ]
        }
      ],
      "source": [
        "# Compute metrics\n",
        "\n",
        "# bleu_metric = load_metric(\"bleu\",trust_remote_code=True)\n",
        "# rouge_metric = load_metric(\"rouge\",trust_remote_code=True)\n",
        "# meteor_metric = load_metric(\"meteor\",trust_remote_code=True)\n",
        "\n",
        "# Dutch model\n",
        "\n",
        "predictions = Dutch_outputs_df['MarianMT-pretrained'].to_list()\n",
        "references = Dutch_outputs_df['Dutch'].to_list()\n",
        "\n",
        "\n",
        "bleu_score = bleu_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"BLEU score for Dutch Model: {bleu_score}\")\n",
        "\n",
        "# Compute ROUGE score\n",
        "rouge_score = rouge_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"ROUGE score for Dutch Model: {rouge_score}\")\n",
        "\n",
        "# Compute METEOR score\n",
        "meteor_score = meteor_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"METEOR score for Dutch Model: {meteor_score}\")\n",
        "\n",
        "###########################################################################################\n",
        "\n",
        "# German model\n",
        "\n",
        "predictions = German_outputs_df['MarianMT-pretrained'].to_list()\n",
        "references = German_outputs_df['German'].to_list()\n",
        "\n",
        "\n",
        "bleu_score = bleu_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"BLEU score for German Model: {bleu_score}\")\n",
        "\n",
        "# Compute ROUGE score\n",
        "rouge_score = rouge_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"ROUGE score for German Model: {rouge_score}\")\n",
        "\n",
        "# Compute METEOR score\n",
        "meteor_score = meteor_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"METEOR score for German Model: {meteor_score}\")\n",
        "\n",
        "###########################################################################################\n",
        "\n",
        "# Spanish model\n",
        "\n",
        "predictions = Spanish_outputs_df['MarianMT-pretrained'].to_list()\n",
        "references = Spanish_outputs_df['Spanish'].to_list()\n",
        "\n",
        "\n",
        "bleu_score = bleu_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"BLEU score for Spanish Model: {bleu_score}\")\n",
        "\n",
        "# Compute ROUGE score\n",
        "rouge_score = rouge_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"ROUGE score for Spanish Model: {rouge_score}\")\n",
        "\n",
        "# Compute METEOR score\n",
        "meteor_score = meteor_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"METEOR score for Spanish Model: {meteor_score}\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dXTb3sY1G46D"
      },
      "source": [
        "### Dutch Model finetuning (en-nl)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "EJZvKkBJG46D"
      },
      "outputs": [],
      "source": [
        "#### Cell to run\n",
        "\n",
        "def preprocess_texts(texts, src_lang_code, tgt_lang_code):\n",
        "    processed_src_texts = []\n",
        "    processed_tgt_texts = []\n",
        "    for src_text, tgt_text in texts:\n",
        "        src_text = f\"{src_text} {tokenizer.eos_token} {src_lang_code}\"\n",
        "        tgt_text = f\"{tgt_lang_code} {tgt_text} {tokenizer.eos_token}\"\n",
        "        processed_src_texts.append(src_text)\n",
        "        processed_tgt_texts.append(tgt_text)\n",
        "    return processed_src_texts, processed_tgt_texts"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "272n_iwYG46D"
      },
      "outputs": [],
      "source": [
        "#### Cell to run\n",
        "\n",
        "class TranslationDataset(Dataset):\n",
        "    def __init__(self, texts, tokenizer, src_lang_code, tgt_lang_code):\n",
        "        self.texts = texts\n",
        "        self.tokenizer = tokenizer\n",
        "        self.src_lang_code = src_lang_code\n",
        "        self.tgt_lang_code = tgt_lang_code\n",
        "        self.src_texts, self.tgt_texts = preprocess_texts(texts, src_lang_code, tgt_lang_code)\n",
        "\n",
        "    def __len__(self):\n",
        "        return len(self.src_texts)\n",
        "\n",
        "    def __getitem__(self, idx):\n",
        "        src_text = self.src_texts[idx]\n",
        "        tgt_text = self.tgt_texts[idx]\n",
        "\n",
        "        inputs = self.tokenizer(src_text, return_tensors=\"pt\", padding=\"max_length\", truncation=True, max_length=128)\n",
        "        labels = self.tokenizer(tgt_text, return_tensors=\"pt\", padding=\"max_length\", truncation=True, max_length=128)\n",
        "\n",
        "        input_ids = inputs.input_ids.squeeze()\n",
        "        attention_mask = inputs.attention_mask.squeeze()\n",
        "        labels = labels.input_ids.squeeze()\n",
        "\n",
        "        labels[labels == self.tokenizer.pad_token_id] = -100\n",
        "\n",
        "        return {\n",
        "            \"input_ids\": input_ids,\n",
        "            \"attention_mask\": attention_mask,\n",
        "            \"labels\": labels\n",
        "        }\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ZoxQv3cJG46D",
        "outputId": "c3bf76f6-d625-48f8-d5ed-8ae2f786d483"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/models/marian/tokenization_marian.py:175: UserWarning: Recommended: pip install sacremoses.\n",
            "  warnings.warn(\"Recommended: pip install sacremoses.\")\n"
          ]
        }
      ],
      "source": [
        "model_name = \"Helsinki-NLP/opus-mt-en-nl\"\n",
        "tokenizer = MarianTokenizer.from_pretrained(model_name)\n",
        "model = MarianMTModel.from_pretrained(model_name)\n",
        "\n",
        "# model.qconfig = torch.quantization.get_default_qconfig('fbgemm')\n",
        "# torch.quantization.prepare(model, inplace=True)\n",
        "\n",
        "english_dutch_texts = list(zip(Dutch_train_data['English'].tolist(), Dutch_train_data['Dutch'].tolist()))\n",
        "\n",
        "dutch_train_datasets = TranslationDataset(english_dutch_texts, tokenizer, \"en\", \"nl\")\n",
        "# dutch_train_dataloader = DataLoader(dutch_datasets, batch_size=128, shuffle=True)\n",
        "\n",
        "english_dutch_texts = list(zip(Dutch_val_data['English'].tolist(), Dutch_val_data['Dutch'].tolist()))  # For Dutch translation\n",
        "dutch_eval_datasets = TranslationDataset(english_dutch_texts, tokenizer, \"en\", \"nl\")\n",
        "# dutch_eval_dataloader = DataLoader(dutch_datasets, batch_size=128, shuffle=True)"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "##### Run this cell\n",
        "\n",
        "# from transformers import TrainingArguments\n",
        "\n",
        "training_args = TrainingArguments(\n",
        "    output_dir='./results',\n",
        "    evaluation_strategy='epoch',\n",
        "    learning_rate=2e-5,\n",
        "    per_device_train_batch_size=4,\n",
        "    per_device_eval_batch_size=4,\n",
        "    num_train_epochs=5,\n",
        "    weight_decay=0.01,\n",
        "    save_total_limit=1,\n",
        "    logging_dir='./logs',\n",
        "    push_to_hub=False,\n",
        "    report_to='none',\n",
        "    logging_steps=10,\n",
        "    dataloader_num_workers=2,\n",
        ")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "9UND5W1lIaes",
        "outputId": "388f79e0-6783-4c3f-ab83-4b1ca25278a1"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/training_args.py:1494: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of 🤗 Transformers. Use `eval_strategy` instead\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "##### Run this cell\n",
        "\n",
        "trainer = Trainer(\n",
        "    model=model,\n",
        "    args=training_args,\n",
        "    train_dataset=dutch_train_datasets,\n",
        "    eval_dataset=dutch_eval_datasets,\n",
        "    tokenizer=tokenizer,\n",
        ")"
      ],
      "metadata": {
        "id": "QjhnDyY7Ivqi"
      },
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "##### Run this cell\n",
        "\n",
        "trainer.train()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "5QUuOZyFIm-S",
        "outputId": "82344c65-dbed-408d-b687-2d2c1a6e1a6a"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='14675' max='14675' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [14675/14675 13:54, Epoch 5/5]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              " <tr style=\"text-align: left;\">\n",
              "      <th>Epoch</th>\n",
              "      <th>Training Loss</th>\n",
              "      <th>Validation Loss</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>1.715400</td>\n",
              "      <td>1.569334</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>1.292100</td>\n",
              "      <td>1.382931</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>1.309500</td>\n",
              "      <td>1.313312</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>1.191900</td>\n",
              "      <td>1.278212</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>5</td>\n",
              "      <td>1.174700</td>\n",
              "      <td>1.269117</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table><p>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[67027]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "TrainOutput(global_step=14675, training_loss=1.469979932320382, metrics={'train_runtime': 834.6414, 'train_samples_per_second': 70.312, 'train_steps_per_second': 17.582, 'total_flos': 1989325545799680.0, 'train_loss': 1.469979932320382, 'epoch': 5.0})"
            ]
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from google.colab import drive\n",
        "drive.mount('/content/drive')"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UlmMHob5gLOr",
        "outputId": "25ea6520-bced-4d0f-f511-ee17fdd10618"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lDOiKqQ2G46D"
      },
      "outputs": [],
      "source": [
        "torch.save(model.state_dict(), '/content/drive/MyDrive/MarianMT_dutch_model_weights.pth')\n",
        "# shutil.copy('MarianMT_dutch_model_weights.pth', '/content/drive/MyDrive')"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "from transformers import pipeline"
      ],
      "metadata": {
        "id": "m9NmUYiYblFS"
      },
      "execution_count": 49,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_name = \"Helsinki-NLP/opus-mt-en-nl\"\n",
        "tokenizer = MarianTokenizer.from_pretrained(model_name)\n",
        "model = MarianMTModel.from_pretrained(model_name)\n",
        "model.load_state_dict(torch.load('/content/drive/MyDrive/MarianMT_dutch_model_weights.pth'),strict=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Fk1f9Tq_yFZS",
        "outputId": "de271267-9bf5-4634-b9ee-acfc854d6e65"
      },
      "execution_count": 94,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/models/marian/tokenization_marian.py:175: UserWarning: Recommended: pip install sacremoses.\n",
            "  warnings.warn(\"Recommended: pip install sacremoses.\")\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<All keys matched successfully>"
            ]
          },
          "metadata": {},
          "execution_count": 94
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "translations = []\n",
        "Dutch_outputs_df = pd.read_csv('Dutch outputs_MarianMT.csv')\n",
        "src_text = Dutch_outputs_df['English'].to_list()\n",
        "model.to('cuda')\n",
        "\n",
        "translator = pipeline(\"translation_en_to_nl\", model=model, tokenizer=tokenizer,device = 'cuda')\n",
        "translated_texts = [translator(text)[0]['translation_text'] for text in src_text]\n",
        "\n",
        "Dutch_outputs_df['MarianMT-finetuned']  = translated_texts"
      ],
      "metadata": {
        "id": "K8aOqzOWa7YV"
      },
      "execution_count": 96,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "Dutch_outputs_df.to_csv('Dutch outputs_MarianMT_finetuned.csv',index=False)"
      ],
      "metadata": {
        "id": "RPy8EIvwR7hI"
      },
      "execution_count": 99,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Compute metrics\n",
        "\n",
        "bleu_metric = evaluate.load(\"bleu\")\n",
        "rouge_metric = evaluate.load(\"rouge\")\n",
        "meteor_metric = evaluate.load(\"meteor\")\n",
        "\n",
        "# Dutch model\n",
        "\n",
        "predictions = Dutch_outputs_df['MarianMT-finetuned'].apply(lambda x: x[0] if isinstance(x, list) else x)\n",
        "references = Dutch_outputs_df['Dutch'].to_list()\n",
        "\n",
        "\n",
        "bleu_score = bleu_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"BLEU score for Dutch Model: {bleu_score}\")\n",
        "\n",
        "# Compute ROUGE score\n",
        "rouge_score = rouge_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"ROUGE score for Dutch Model: {rouge_score}\")\n",
        "\n",
        "# Compute METEOR score\n",
        "meteor_score = meteor_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"METEOR score for Dutch Model: {meteor_score}\")\n"
      ],
      "metadata": {
        "id": "jCDZzz78gp1Y",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f0ad4cc8-9b4c-4ca2-a3c4-0d3bf36d3836"
      },
      "execution_count": 98,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]   Package wordnet is already up-to-date!\n",
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n",
            "[nltk_data] Downloading package omw-1.4 to /root/nltk_data...\n",
            "[nltk_data]   Package omw-1.4 is already up-to-date!\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "BLEU score for Dutch Model: {'bleu': 0.2070843491637414, 'precisions': [0.5238598388047966, 0.25428265524625265, 0.14892884569552206, 0.09269972451790634], 'brevity_penalty': 1.0, 'length_ratio': 1.0053111336182408, 'translation_length': 40696, 'reference_length': 40481}\n",
            "ROUGE score for Dutch Model: {'rouge1': 0.5181524404497124, 'rouge2': 0.2702332215846026, 'rougeL': 0.45348876259616644, 'rougeLsum': 0.45335005224894187}\n",
            "METEOR score for Dutch Model: {'meteor': 0.4587905497275448}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### German model"
      ],
      "metadata": {
        "id": "AyuO7o8shxcO"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#### Cell to run\n",
        "\n",
        "\n",
        "model_name = \"Helsinki-NLP/opus-mt-en-de\"\n",
        "tokenizer = MarianTokenizer.from_pretrained(model_name)\n",
        "model = MarianMTModel.from_pretrained(model_name)\n",
        "\n",
        "# model.qconfig = torch.quantization.get_default_qconfig('fbgemm')\n",
        "# torch.quantization.prepare(model, inplace=True)\n",
        "\n",
        "english_german_texts = list(zip(German_train_data['English'].tolist(), German_train_data['German'].tolist()))\n",
        "\n",
        "german_train_datasets = TranslationDataset(english_german_texts, tokenizer, \"en\", \"de\")\n",
        "# german_train_dataloader = DataLoader(german_datasets, batch_size=128, shuffle=True)\n",
        "\n",
        "english_german_texts = list(zip(German_val_data['English'].tolist(), German_val_data['German'].tolist()))  # For German translation\n",
        "german_eval_datasets = TranslationDataset(english_german_texts, tokenizer, \"en\", \"de\")\n",
        "# german_eval_dataloader = DataLoader(german_datasets, batch_size=128, shuffle=True)"
      ],
      "metadata": {
        "id": "PV8X6p4Hgpys",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "62a02776-cf6a-4dc8-927f-8e7193a980c4"
      },
      "execution_count": 65,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/models/marian/tokenization_marian.py:175: UserWarning: Recommended: pip install sacremoses.\n",
            "  warnings.warn(\"Recommended: pip install sacremoses.\")\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "##### Run this cell\n",
        "\n",
        "# from transformers import TrainingArguments\n",
        "\n",
        "training_args = TrainingArguments(\n",
        "    output_dir='./results',\n",
        "    evaluation_strategy='epoch',\n",
        "    learning_rate=2e-5,\n",
        "    per_device_train_batch_size=4,\n",
        "    per_device_eval_batch_size=4,\n",
        "    num_train_epochs=5,\n",
        "    weight_decay=0.01,\n",
        "    save_total_limit=1,\n",
        "    logging_dir='./logs',\n",
        "    push_to_hub=False,\n",
        "    report_to='none',\n",
        "    logging_steps=10,\n",
        "    dataloader_num_workers=2,\n",
        ")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oNGBk9UzkCpQ",
        "outputId": "9402a158-e295-48c5-b610-02b63f24fa85"
      },
      "execution_count": 62,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/training_args.py:1494: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of 🤗 Transformers. Use `eval_strategy` instead\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "##### Run this cell\n",
        "\n",
        "trainer = Trainer(\n",
        "    model=model,\n",
        "    args=training_args,\n",
        "    train_dataset=german_train_datasets,\n",
        "    eval_dataset=german_eval_datasets,\n",
        "    tokenizer=tokenizer,\n",
        ")"
      ],
      "metadata": {
        "id": "l6RF4A_ikCm6"
      },
      "execution_count": 66,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "trainer.train()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "gsexAZ9AkCkV",
        "outputId": "4f804a96-c41a-4ba2-8c36-b7a7c1c822f4"
      },
      "execution_count": 67,
      "outputs": [
        {
          "metadata": {
            "tags": null
          },
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='14775' max='14775' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [14775/14775 14:11, Epoch 5/5]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              " <tr style=\"text-align: left;\">\n",
              "      <th>Epoch</th>\n",
              "      <th>Training Loss</th>\n",
              "      <th>Validation Loss</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>1.596000</td>\n",
              "      <td>1.506231</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>1.299500</td>\n",
              "      <td>1.329620</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>1.176400</td>\n",
              "      <td>1.264535</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>1.125600</td>\n",
              "      <td>1.237693</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>5</td>\n",
              "      <td>0.944100</td>\n",
              "      <td>1.229653</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table><p>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "metadata": {
            "tags": null
          },
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[58100]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "TrainOutput(global_step=14775, training_loss=1.3874550982054115, metrics={'train_runtime': 852.17, 'train_samples_per_second': 69.352, 'train_steps_per_second': 17.338, 'total_flos': 2003393367244800.0, 'train_loss': 1.3874550982054115, 'epoch': 5.0})"
            ]
          },
          "execution_count": 67,
          "metadata": {},
          "output_type": "execute_result"
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "torch.save(model.state_dict(), '/content/drive/MyDrive/MarianMT_german_model_weights.pth')\n",
        "# shutil.copy('MarianMT_dutch_model_weights.pth', '/content/drive/MyDrive')"
      ],
      "metadata": {
        "id": "upjMYOhjkCiI"
      },
      "execution_count": 68,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "model_name = \"Helsinki-NLP/opus-mt-en-de\"\n",
        "tokenizer = MarianTokenizer.from_pretrained(model_name)\n",
        "model = MarianMTModel.from_pretrained(model_name)\n",
        "model.load_state_dict(torch.load('/content/drive/MyDrive/MarianMT_german_model_weights.pth'),strict=False)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "CZfTK52Muhwd",
        "outputId": "7d473c69-3675-44f4-e6d3-af82e553d751"
      },
      "execution_count": 89,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/models/marian/tokenization_marian.py:175: UserWarning: Recommended: pip install sacremoses.\n",
            "  warnings.warn(\"Recommended: pip install sacremoses.\")\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<All keys matched successfully>"
            ]
          },
          "metadata": {},
          "execution_count": 89
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "translations = []\n",
        "German_outputs_df = pd.read_csv('German outputs_MarianMT.csv')\n",
        "src_text = German_outputs_df['English'].to_list()\n",
        "model.to('cuda')\n",
        "\n",
        "translator = pipeline(\"translation_en_to_de\", model=model, tokenizer=tokenizer,device = 'cuda')\n",
        "translated_texts = [translator(text)[0]['translation_text'] for text in src_text]\n",
        "\n",
        "German_outputs_df['MarianMT-finetuned']  = translated_texts"
      ],
      "metadata": {
        "id": "liPy_TOOkfcg"
      },
      "execution_count": 91,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "German_outputs_df.to_csv('German outputs_MarianMT_finetuned.csv',index=False)"
      ],
      "metadata": {
        "id": "AWLQtDpxufOu"
      },
      "execution_count": 92,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Compute metrics\n",
        "\n",
        "bleu_metric = evaluate.load(\"bleu\")\n",
        "rouge_metric = evaluate.load(\"rouge\")\n",
        "meteor_metric = evaluate.load(\"meteor\")\n",
        "\n",
        "# Dutch model\n",
        "\n",
        "predictions = German_outputs_df['MarianMT-finetuned'].apply(lambda x: x[0] if isinstance(x, list) else x)\n",
        "references = German_outputs_df['German'].to_list()\n",
        "\n",
        "\n",
        "bleu_score = bleu_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"BLEU score for German Model: {bleu_score}\")\n",
        "\n",
        "# Compute ROUGE score\n",
        "rouge_score = rouge_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"ROUGE score for German Model: {rouge_score}\")\n",
        "\n",
        "# Compute METEOR score\n",
        "meteor_score = meteor_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"METEOR score for German Model: {meteor_score}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hUIh8B4Rku2c",
        "outputId": "e5b3843e-75fd-49be-9a9f-fef39c777770"
      },
      "execution_count": 93,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]   Package wordnet is already up-to-date!\n",
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n",
            "[nltk_data] Downloading package omw-1.4 to /root/nltk_data...\n",
            "[nltk_data]   Package omw-1.4 is already up-to-date!\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "BLEU score for German Model: {'bleu': 0.21858831789182193, 'precisions': [0.5290947174823746, 0.26721529068224054, 0.15956124112397424, 0.1019067918658909], 'brevity_penalty': 0.9982645096493903, 'length_ratio': 0.9982660138718891, 'translation_length': 39148, 'reference_length': 39216}\n",
            "ROUGE score for German Model: {'rouge1': 0.5045687844070336, 'rouge2': 0.2779183874667054, 'rougeL': 0.45437414486358935, 'rougeLsum': 0.4545721738380622}\n",
            "METEOR score for German Model: {'meteor': 0.47222057766621955}\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "#### Spanish Model"
      ],
      "metadata": {
        "id": "4nlwF4zOL2BF"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "#### Cell to run\n",
        "\n",
        "model_name = \"Helsinki-NLP/opus-mt-en-es\"\n",
        "tokenizer = MarianTokenizer.from_pretrained(model_name)\n",
        "model = MarianMTModel.from_pretrained(model_name)\n",
        "\n",
        "# model.qconfig = torch.quantization.get_default_qconfig('fbgemm')\n",
        "# torch.quantization.prepare(model, inplace=True)\n",
        "\n",
        "english_spanish_texts = list(zip(Spanish_train_data['English'].tolist(), Spanish_train_data['Spanish'].tolist()))\n",
        "\n",
        "spanish_train_datasets = TranslationDataset(english_spanish_texts, tokenizer, \"en\", \"es\")\n",
        "# spanish_train_dataloader = DataLoader(spanish_datasets, batch_size=128, shuffle=True)\n",
        "\n",
        "english_spanish_texts = list(zip(Spanish_val_data['English'].tolist(), Spanish_val_data['Spanish'].tolist()))  # For Spanish translation\n",
        "spanish_eval_datasets = TranslationDataset(english_spanish_texts, tokenizer, \"en\", \"es\")\n",
        "# spanish_eval_dataloader = DataLoader(spanish_datasets, batch_size=128, shuffle=True)"
      ],
      "metadata": {
        "id": "PSR2v49SL1uQ",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297,
          "referenced_widgets": [
            "cd09315584b54c92a808fb3fc6c38909",
            "e4557cda3ff64865a5036a7f4f9cebd4",
            "74a258738884422d98959221f368ce95",
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        "outputId": "1c99116d-54d3-4447-8c0e-890fab7e4cb5"
      },
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/44.0 [00:00<?, ?B/s]"
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            "text/plain": [
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          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/models/marian/tokenization_marian.py:175: UserWarning: Recommended: pip install sacremoses.\n",
            "  warnings.warn(\"Recommended: pip install sacremoses.\")\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
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              "pytorch_model.bin:   0%|          | 0.00/312M [00:00<?, ?B/s]"
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          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "##### Run this cell\n",
        "\n",
        "# from transformers import TrainingArguments\n",
        "\n",
        "training_args = TrainingArguments(\n",
        "    output_dir='./results',\n",
        "    evaluation_strategy='epoch',\n",
        "    learning_rate=2e-5,\n",
        "    per_device_train_batch_size=4,\n",
        "    per_device_eval_batch_size=4,\n",
        "    num_train_epochs=5,\n",
        "    weight_decay=0.01,\n",
        "    save_total_limit=1,\n",
        "    logging_dir='./logs',\n",
        "    push_to_hub=False,\n",
        "    report_to='none',\n",
        "    logging_steps=10,\n",
        "    dataloader_num_workers=2,\n",
        ")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "21sYTxc_lmXg",
        "outputId": "3084989d-a0f1-426a-9ec4-c3bb67c24cca"
      },
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/training_args.py:1494: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of 🤗 Transformers. Use `eval_strategy` instead\n",
            "  warnings.warn(\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "##### Run this cell\n",
        "\n",
        "trainer = Trainer(\n",
        "    model=model,\n",
        "    args=training_args,\n",
        "    train_dataset=german_train_datasets,\n",
        "    eval_dataset=german_eval_datasets,\n",
        "    tokenizer=tokenizer,\n",
        ")"
      ],
      "metadata": {
        "id": "vncFrnTllmVO"
      },
      "execution_count": 82,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "trainer.train()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "uX_gefX6lmTF",
        "outputId": "8e728ef8-e6b0-4a43-9197-05fd4294fc83"
      },
      "execution_count": 83,
      "outputs": [
        {
          "metadata": {
            "tags": null
          },
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n"
          ]
        },
        {
          "data": {
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='6626' max='14775' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [ 6626/14775 06:21 < 07:49, 17.36 it/s, Epoch 2.24/5]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              " <tr style=\"text-align: left;\">\n",
              "      <th>Epoch</th>\n",
              "      <th>Training Loss</th>\n",
              "      <th>Validation Loss</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>3.824800</td>\n",
              "      <td>3.677544</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>3.275300</td>\n",
              "      <td>3.209465</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table><p>"
            ],
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              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "metadata": {
            "tags": null
          },
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ],
            "text/html": [
              "\n",
              "    <div>\n",
              "      \n",
              "      <progress value='14775' max='14775' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [14775/14775 14:19, Epoch 5/5]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              " <tr style=\"text-align: left;\">\n",
              "      <th>Epoch</th>\n",
              "      <th>Training Loss</th>\n",
              "      <th>Validation Loss</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>1</td>\n",
              "      <td>3.824800</td>\n",
              "      <td>3.677544</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>2</td>\n",
              "      <td>3.275300</td>\n",
              "      <td>3.209465</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>3</td>\n",
              "      <td>3.109600</td>\n",
              "      <td>2.988768</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>4</td>\n",
              "      <td>2.892100</td>\n",
              "      <td>2.879969</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>5</td>\n",
              "      <td>2.859000</td>\n",
              "      <td>2.842788</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table><p>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "Some non-default generation parameters are set in the model config. These should go into a GenerationConfig file (https://huggingface.co/docs/transformers/generation_strategies#save-a-custom-decoding-strategy-with-your-model) instead. This warning will be raised to an exception in v4.41.\n",
            "Non-default generation parameters: {'max_length': 512, 'num_beams': 4, 'bad_words_ids': [[65000]], 'forced_eos_token_id': 0}\n",
            "/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.\n",
            "  self.pid = os.fork()\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "TrainOutput(global_step=14775, training_loss=3.4441784489820453, metrics={'train_runtime': 860.023, 'train_samples_per_second': 68.719, 'train_steps_per_second': 17.18, 'total_flos': 2003393367244800.0, 'train_loss': 3.4441784489820453, 'epoch': 5.0})"
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "torch.save(model.state_dict(), '/content/drive/MyDrive/MarianMT_spanish_model_weights.pth')\n",
        "# shutil.copy('MarianMT_dutch_model_weights.pth', '/content/drive/MyDrive')"
      ],
      "metadata": {
        "id": "plnE1vRElmQx"
      },
      "execution_count": 85,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "translations = []\n",
        "Spanish_outputs_df = pd.read_csv('Spanish outputs_MarianMT.csv')\n",
        "src_text = Spanish_outputs_df['English'].to_list()\n",
        "model.to('cuda')\n",
        "\n",
        "translator = pipeline(\"translation_en_to_es\", model=model, tokenizer=tokenizer)\n",
        "translated_texts = [translator(text)[0]['translation_text'] for text in src_text]\n",
        "\n",
        "Spanish_outputs_df['MarianMT-finetuned']  = translated_texts"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IYzRJlu6lwdh",
        "outputId": "b497e04e-8d7e-4a9e-bebc-2e26227393d2"
      },
      "execution_count": 86,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "Hardware accelerator e.g. GPU is available in the environment, but no `device` argument is passed to the `Pipeline` object. Model will be on CPU.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Spanish_outputs_df.to_csv('Spanish outputs_MarianMT_finetuned.csv',index=False)"
      ],
      "metadata": {
        "id": "M6sONAT4uZN7"
      },
      "execution_count": 87,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "# Compute metrics\n",
        "\n",
        "bleu_metric = evaluate.load(\"bleu\")\n",
        "rouge_metric = evaluate.load(\"rouge\")\n",
        "meteor_metric = evaluate.load(\"meteor\")\n",
        "\n",
        "# Dutch model\n",
        "\n",
        "predictions = Spanish_outputs_df['MarianMT-finetuned'].apply(lambda x: x[0] if isinstance(x, list) else x)\n",
        "references = Spanish_outputs_df['Spanish'].to_list()\n",
        "\n",
        "\n",
        "bleu_score = bleu_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"BLEU score for spanish Model: {bleu_score}\")\n",
        "\n",
        "# Compute ROUGE score\n",
        "rouge_score = rouge_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"ROUGE score for spanish Model: {rouge_score}\")\n",
        "\n",
        "# Compute METEOR score\n",
        "meteor_score = meteor_metric.compute(predictions=predictions, references=references)\n",
        "print(f\"METEOR score for spanish Model: {meteor_score}\")\n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "f-5UTnVLlwbD",
        "outputId": "4bec6fc7-e872-44ce-e768-d3da6cdc1cbf"
      },
      "execution_count": 88,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stderr",
          "text": [
            "[nltk_data] Downloading package wordnet to /root/nltk_data...\n",
            "[nltk_data]   Package wordnet is already up-to-date!\n",
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n",
            "[nltk_data] Downloading package omw-1.4 to /root/nltk_data...\n",
            "[nltk_data]   Package omw-1.4 is already up-to-date!\n"
          ]
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "BLEU score for spanish Model: {'bleu': 0.010400569254565567, 'precisions': [0.11136637499014607, 0.012230734874772392, 0.00426349816529792, 0.0020149103364900263], 'brevity_penalty': 1.0, 'length_ratio': 2.018342993521991, 'translation_length': 88797, 'reference_length': 43995}\n",
            "ROUGE score for spanish Model: {'rouge1': 0.13546525599457826, 'rouge2': 0.026081957756840357, 'rougeL': 0.11003373250781623, 'rougeLsum': 0.10979627457516289}\n",
            "METEOR score for spanish Model: {'meteor': 0.13811856773690753}\n"
          ]
        }
      ]
    }
  ],
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