Hindi_Finetuned.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "InLFsu_NGvmV",
        "outputId": "b0e59934-cbae-4ebb-d047-1e2901921f42"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
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            "\u001b[?25hInstalling collected packages: xxhash, ruamel.yaml.clib, dill, ruamel.yaml, multiprocess, hyperpyyaml, speechbrain, datasets\n",
            "Successfully installed datasets-3.0.2 dill-0.3.8 hyperpyyaml-1.2.2 multiprocess-0.70.16 ruamel.yaml-0.18.6 ruamel.yaml.clib-0.2.12 speechbrain-0.5.16 xxhash-3.5.0\n"
          ]
        }
      ],
      "source": [
        "!pip install transformers datasets soundfile accelerate speechbrain==0.5.16"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 145,
          "referenced_widgets": [
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            "3492553018724f388dd3a76def37ca60",
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          ]
        },
        "id": "q4YEzYfYGxQf",
        "outputId": "2c98dbeb-1329-47c5-94e3-5036b61b1a0e"
      },
      "outputs": [
        {
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            "text/plain": [
              "VBox(children=(HTML(value='<center> <img\\nsrc=https://huggingface.co/front/assets/huggingface_logo-noborder.sv…"
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          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from huggingface_hub import notebook_login\n",
        "\n",
        "notebook_login()"
      ]
    },
    {
      "cell_type": "code",
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      "metadata": {
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            "/usr/local/lib/python3.10/dist-packages/huggingface_hub/utils/_token.py:89: UserWarning: \n",
            "The secret `HF_TOKEN` does not exist in your Colab secrets.\n",
            "To authenticate with the Hugging Face Hub, create a token in your settings tab (https://huggingface.co/settings/tokens), set it as secret in your Google Colab and restart your session.\n",
            "You will be able to reuse this secret in all of your notebooks.\n",
            "Please note that authentication is recommended but still optional to access public models or datasets.\n",
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            "text/plain": [
              "Generating validated split: 0 examples [00:00, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "\n",
            "Reading metadata...: 0it [00:00, ?it/s]\u001b[A\n",
            "Reading metadata...: 10329it [00:00, 57867.50it/s]\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "DatasetDict({\n",
              "    train: Dataset({\n",
              "        features: ['client_id', 'path', 'audio', 'sentence', 'up_votes', 'down_votes', 'age', 'gender', 'accent', 'locale', 'segment', 'variant'],\n",
              "        num_rows: 4689\n",
              "    })\n",
              "    validation: Dataset({\n",
              "        features: ['client_id', 'path', 'audio', 'sentence', 'up_votes', 'down_votes', 'age', 'gender', 'accent', 'locale', 'segment', 'variant'],\n",
              "        num_rows: 2428\n",
              "    })\n",
              "    test: Dataset({\n",
              "        features: ['client_id', 'path', 'audio', 'sentence', 'up_votes', 'down_votes', 'age', 'gender', 'accent', 'locale', 'segment', 'variant'],\n",
              "        num_rows: 3154\n",
              "    })\n",
              "    other: Dataset({\n",
              "        features: ['client_id', 'path', 'audio', 'sentence', 'up_votes', 'down_votes', 'age', 'gender', 'accent', 'locale', 'segment', 'variant'],\n",
              "        num_rows: 4044\n",
              "    })\n",
              "    invalidated: Dataset({\n",
              "        features: ['client_id', 'path', 'audio', 'sentence', 'up_votes', 'down_votes', 'age', 'gender', 'accent', 'locale', 'segment', 'variant'],\n",
              "        num_rows: 775\n",
              "    })\n",
              "    validated: Dataset({\n",
              "        features: ['client_id', 'path', 'audio', 'sentence', 'up_votes', 'down_votes', 'age', 'gender', 'accent', 'locale', 'segment', 'variant'],\n",
              "        num_rows: 10329\n",
              "    })\n",
              "})"
            ]
          },
          "execution_count": 4,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "from datasets import load_dataset, Audio\n",
        "#https://huggingface.co/datasets/mozilla-foundation/common_voice_17_0/viewer/hi\n",
        "dataset = load_dataset(\"mozilla-foundation/common_voice_17_0\", \"hi\", trust_remote_code=True)\n",
        "dataset"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "UNMYK4RuFeuP"
      },
      "outputs": [],
      "source": [
        "dataset = dataset['validated']\n",
        "\n",
        "# Now `full_dataset` contains the combined data of all splits\n",
        "print(dataset)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "33GgyjE3HtFX",
        "outputId": "c037d4a0-2ed5-45f9-893e-697ac92ebdce"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "10329"
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "len(dataset)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "4gGgIfM9Kebq"
      },
      "outputs": [],
      "source": [
        "print(dataset)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LK4qrOobKlTF"
      },
      "source": [
        "We are using just the 1/16th of the data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "JKXQnTfoJNHe"
      },
      "outputs": [],
      "source": [
        "dataset = dataset.cast_column(\"audio\", Audio(sampling_rate=16000))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 283,
          "referenced_widgets": [
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            "aa2ca64d59ac41d68732c4c330a7f93a"
          ]
        },
        "collapsed": true,
        "id": "rZaO2dNGJO6r",
        "outputId": "ca45635c-e79a-46c3-a83f-a5cb51333db1"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "The cache for model files in Transformers v4.22.0 has been updated. Migrating your old cache. This is a one-time only operation. You can interrupt this and resume the migration later on by calling `transformers.utils.move_cache()`.\n"
          ]
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "b8fd3fba516f4ab88ba164fa37a73a8d",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "0it [00:00, ?it/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "592dc9f2f7814f939c11574921632122",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "preprocessor_config.json:   0%|          | 0.00/433 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "bdec65c9bafc4beeacbb6ef75ab4b044",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/232 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "3602a6141752492781b52ef47d2dc0f0",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "spm_char.model:   0%|          | 0.00/238k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "413ad0fe9fb94e8d8c9303a506b2deb9",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "added_tokens.json:   0%|          | 0.00/40.0 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "c435e518dfff4e87bdc217ed9b036d8d",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "special_tokens_map.json:   0%|          | 0.00/234 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/tokenization_utils_base.py:1601: FutureWarning: `clean_up_tokenization_spaces` was not set. It will be set to `True` by default. This behavior will be depracted in transformers v4.45, and will be then set to `False` by default. For more details check this issue: https://github.com/huggingface/transformers/issues/31884\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "from transformers import SpeechT5Processor\n",
        "\n",
        "checkpoint = \"microsoft/speecht5_tts\"\n",
        "processor = SpeechT5Processor.from_pretrained(checkpoint)\n"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "41HXlo_WJQZ8"
      },
      "outputs": [],
      "source": [
        "tokenizer = processor.tokenizer"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AgVKf7yEJR3Y",
        "outputId": "95fc5940-f039-49ee-97e0-dea2084fcffd"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{'client_id': ['0a0db76f30e3d011216425efa204fa0d3064767656b913c1a15964ff4d3409d95a04609ab2c57d21c7ae225ce115dbc38160c92974e7194071f4af178f4ea762',\n",
              "  '18ac148b1b14b3b66a0116ecc3f445d74b049106dc0b0c39ba266ed130105ea5cba16d4e6220aaff9e2757009e3e3789ac98602887ee11491fcb207b874732c2',\n",
              "  '1cec8b78e84c018a6efce5b69c1f3837d98aa06f2ab20d370caab36ca0938d09dd89e21b83d94073d8ea3af821ee74327d647929fd4e8051688c8730f024d6ab'],\n",
              " 'path': ['/root/.cache/huggingface/datasets/downloads/extracted/64bb12b7a828d1bd1eb00691c002aa7af4881c590b66cf78d8068ba87b979803/hi_validated_0/common_voice_hi_32761781.mp3',\n",
              "  '/root/.cache/huggingface/datasets/downloads/extracted/64bb12b7a828d1bd1eb00691c002aa7af4881c590b66cf78d8068ba87b979803/hi_validated_0/common_voice_hi_27801063.mp3',\n",
              "  '/root/.cache/huggingface/datasets/downloads/extracted/64bb12b7a828d1bd1eb00691c002aa7af4881c590b66cf78d8068ba87b979803/hi_validated_0/common_voice_hi_28439063.mp3'],\n",
              " 'audio': [{'path': '/root/.cache/huggingface/datasets/downloads/extracted/64bb12b7a828d1bd1eb00691c002aa7af4881c590b66cf78d8068ba87b979803/hi_validated_0/common_voice_hi_32761781.mp3',\n",
              "   'array': array([-1.45519152e-10, -4.51109372e-10, -1.45519152e-10, ...,\n",
              "          -1.36980470e-05, -1.05143886e-06, -9.05533125e-06]),\n",
              "   'sampling_rate': 16000},\n",
              "  {'path': '/root/.cache/huggingface/datasets/downloads/extracted/64bb12b7a828d1bd1eb00691c002aa7af4881c590b66cf78d8068ba87b979803/hi_validated_0/common_voice_hi_27801063.mp3',\n",
              "   'array': array([3.63797881e-10, 5.82076609e-11, 5.82076609e-11, ...,\n",
              "          2.23415555e-07, 2.78450898e-07, 1.87879778e-07]),\n",
              "   'sampling_rate': 16000},\n",
              "  {'path': '/root/.cache/huggingface/datasets/downloads/extracted/64bb12b7a828d1bd1eb00691c002aa7af4881c590b66cf78d8068ba87b979803/hi_validated_0/common_voice_hi_28439063.mp3',\n",
              "   'array': array([ 5.45696821e-12, -4.54747351e-12,  7.38964445e-12, ...,\n",
              "          -3.64624138e-05,  3.39112012e-05,  3.91266803e-05]),\n",
              "   'sampling_rate': 16000}],\n",
              " 'sentence': [\"अब रामपुर में अखिलेश बांटेंगे लैपटॉप का 'लॉलीपॉप'\",\n",
              "  'नाइजीरिया स्कूल हमला: पीएम नरेंद्र मोदी ने की घटना की निंदा',\n",
              "  'मैं तुम्हें तुम्हारे होमवर्क के साथ मदद करना चाहता हूँ।'],\n",
              " 'up_votes': [2, 2, 2],\n",
              " 'down_votes': [0, 0, 0],\n",
              " 'age': ['', '', ''],\n",
              " 'gender': ['', '', ''],\n",
              " 'accent': ['', '', ''],\n",
              " 'locale': ['hi', 'hi', 'hi'],\n",
              " 'segment': ['', '', ''],\n",
              " 'variant': ['', '', '']}"
            ]
          },
          "execution_count": 11,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dataset[2:5]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "H0GPu2dUHSfE"
      },
      "source": [
        "Let's normalize the dataset, create a column called \"normalized_text\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "bfaaad23a3c54631bb9bc8025a0958f1",
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            "239439fa48094dc7afc172490958b268",
            "ef687c5004304ff7891801bf4272ccb0",
            "5b00907174734c4483b077a69c979d35",
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            "cb6d6f6661554c93afcb6223950d6a9b",
            "7a75b8b2aa9e4de09712d658d6f6de7c"
          ]
        },
        "collapsed": true,
        "id": "IUDgWGNbJTJl",
        "outputId": "dd72648f-010b-47b7-9625-27e2558a9030"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "bfaaad23a3c54631bb9bc8025a0958f1",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Map:   0%|          | 0/10329 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "def extract_all_chars(batch):\n",
        "    all_text = \" \".join(batch[\"sentence\"])\n",
        "    vocab = list(set(all_text))\n",
        "    return {\"vocab\": [vocab], \"all_text\": [all_text]}\n",
        "\n",
        "\n",
        "vocabs = dataset.map(\n",
        "    extract_all_chars,\n",
        "    batched=True,\n",
        "    batch_size=-1,\n",
        "    keep_in_memory=True,\n",
        "    remove_columns=dataset.column_names,\n",
        ")\n",
        "\n",
        "dataset_vocab = set(vocabs[\"vocab\"][0])\n",
        "tokenizer_vocab = {k for k, _ in tokenizer.get_vocab().items()}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "PWPcRXZpJY-W",
        "outputId": "2f4f8d1e-bd3a-4183-dc84-d0286babd8bd"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{' ',\n",
              " '&',\n",
              " '|',\n",
              " 'ँ',\n",
              " 'ं',\n",
              " 'ः',\n",
              " 'अ',\n",
              " 'आ',\n",
              " 'इ',\n",
              " 'ई',\n",
              " 'उ',\n",
              " 'ऊ',\n",
              " 'ऋ',\n",
              " 'ए',\n",
              " 'ऐ',\n",
              " 'ऑ',\n",
              " 'ओ',\n",
              " 'औ',\n",
              " 'क',\n",
              " 'ख',\n",
              " 'ग',\n",
              " 'घ',\n",
              " 'च',\n",
              " 'छ',\n",
              " 'ज',\n",
              " 'झ',\n",
              " 'ञ',\n",
              " 'ट',\n",
              " 'ठ',\n",
              " 'ड',\n",
              " 'ढ',\n",
              " 'ण',\n",
              " 'त',\n",
              " 'थ',\n",
              " 'द',\n",
              " 'ध',\n",
              " 'न',\n",
              " 'प',\n",
              " 'फ',\n",
              " 'ब',\n",
              " 'भ',\n",
              " 'म',\n",
              " 'य',\n",
              " 'र',\n",
              " 'ल',\n",
              " 'व',\n",
              " 'श',\n",
              " 'ष',\n",
              " 'स',\n",
              " 'ह',\n",
              " '़',\n",
              " 'ा',\n",
              " 'ि',\n",
              " 'ी',\n",
              " 'ु',\n",
              " 'ू',\n",
              " 'ृ',\n",
              " 'ॅ',\n",
              " 'े',\n",
              " 'ै',\n",
              " 'ॉ',\n",
              " 'ो',\n",
              " 'ौ',\n",
              " '्',\n",
              " 'क़',\n",
              " 'ख़',\n",
              " 'ग़',\n",
              " 'ज़',\n",
              " 'ड़',\n",
              " 'ढ़',\n",
              " 'फ़',\n",
              " '।',\n",
              " '–',\n",
              " '‘',\n",
              " '’',\n",
              " '“',\n",
              " '”'}"
            ]
          },
          "execution_count": 13,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dataset_vocab - tokenizer_vocab"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "tyGUOmpbLAPT"
      },
      "outputs": [],
      "source": [
        "# import re\n",
        "\n",
        "# def normalize_text(text):\n",
        "#     # Convert to lowercase\n",
        "#     text = text.lower()\n",
        "\n",
        "#     # Remove punctuation (except apostrophes)\n",
        "#     text = re.sub(r'[^\\w\\s\\']', '', text)\n",
        "\n",
        "#     # Remove extra whitespace\n",
        "#     text = ' '.join(text.split())\n",
        "\n",
        "#     return text\n",
        "\n",
        "# # Define a function to add the normalized_text column\n",
        "# def add_normalized_text(example):\n",
        "#     example['normalized_text'] = normalize_text(example['transcription'])\n",
        "#     return example\n",
        "\n",
        "# # Apply the function to the dataset\n",
        "# dataset = dataset.map(add_normalized_text)\n",
        "\n",
        "# # Print the first few examples to verify\n",
        "# print(dataset[2:5])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "_AfJj2FNJtKQ"
      },
      "outputs": [],
      "source": [
        "# def extract_all_chars(batch):\n",
        "#     all_text = \" \".join(batch[\"normalized_text\"])\n",
        "#     vocab = list(set(all_text))\n",
        "#     return {\"vocab\": [vocab], \"all_text\": [all_text]}\n",
        "\n",
        "\n",
        "# vocabs = dataset.map(\n",
        "#     extract_all_chars,\n",
        "#     batched=True,\n",
        "#     batch_size=-1,\n",
        "#     keep_in_memory=True,\n",
        "#     remove_columns=dataset.column_names,\n",
        "# )\n",
        "\n",
        "# dataset_vocab = set(vocabs[\"vocab\"][0])\n",
        "# tokenizer_vocab = {k for k, _ in tokenizer.get_vocab().items()}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "lJRpRh-JbjXZ"
      },
      "outputs": [],
      "source": [
        "# dataset_vocab - tokenizer_vocab"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "bfc01943a5304127803a569e1e9ec06a",
            "237f5f588c4c4dc0a4ab4bc07b7aced2",
            "4ae1357b913e4455ba3e15d626cc0d29",
            "8cd3054b9cd9424f860b249b12f37fd2",
            "564c947bee9f41bb9f95fc8aea4627dd",
            "e39425a8c9d544b4b9ecc78995bd71ba",
            "90bad58c8efc4c32bfe8a3edfe146d50",
            "e379df1a5fe8494c926792e08a8be255",
            "62a5a449a42f419783356e375e68e553",
            "e7f40be25eb44d6385faccf8d0ba8d1e",
            "16559415aa71481ba123ca03c5a113f6"
          ]
        },
        "id": "KRzENvUhbn-J",
        "outputId": "72436b3d-b3d9-430a-a72b-51789506ebaf"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "bfc01943a5304127803a569e1e9ec06a",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Map:   0%|          | 0/10329 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "replacements = [\n",
        "    # Vowels and vowel matras\n",
        "    (\"अ\", \"a\"),\n",
        "    (\"आ\", \"aa\"),\n",
        "    (\"इ\", \"i\"),\n",
        "    (\"ई\", \"ee\"),\n",
        "    (\"उ\", \"u\"),\n",
        "    (\"ऊ\", \"oo\"),\n",
        "    (\"ऋ\", \"ri\"),\n",
        "    (\"ए\", \"e\"),\n",
        "    (\"ऐ\", \"ai\"),\n",
        "    (\"ऑ\", \"o\"),  # More accurate than 'au' for ऑ\n",
        "    (\"ओ\", \"o\"),\n",
        "    (\"औ\", \"au\"),\n",
        "\n",
        "    # Consonants\n",
        "    (\"क\", \"k\"),\n",
        "    (\"ख\", \"kh\"),\n",
        "    (\"ग\", \"g\"),\n",
        "    (\"घ\", \"gh\"),\n",
        "    (\"ङ\", \"ng\"),  # nasal sound\n",
        "    (\"च\", \"ch\"),\n",
        "    (\"छ\", \"chh\"),\n",
        "    (\"ज\", \"j\"),\n",
        "    (\"झ\", \"jh\"),\n",
        "    (\"ञ\", \"ny\"),  # 'ny' closer to the actual sound\n",
        "    (\"ट\", \"t\"),\n",
        "    (\"ठ\", \"th\"),\n",
        "    (\"ड\", \"d\"),\n",
        "    (\"ढ\", \"dh\"),\n",
        "    (\"ण\", \"n\"),  # Slight improvement for easier pronunciation\n",
        "    (\"त\", \"t\"),\n",
        "    (\"थ\", \"th\"),\n",
        "    (\"द\", \"d\"),\n",
        "    (\"ध\", \"dh\"),\n",
        "    (\"न\", \"n\"),\n",
        "    (\"प\", \"p\"),\n",
        "    (\"फ\", \"ph\"),\n",
        "    (\"ब\", \"b\"),\n",
        "    (\"भ\", \"bh\"),\n",
        "    (\"म\", \"m\"),\n",
        "    (\"य\", \"y\"),\n",
        "    (\"र\", \"r\"),\n",
        "    (\"ल\", \"l\"),\n",
        "    (\"व\", \"v\"),  # 'v' is closer to the Hindi 'व'\n",
        "    (\"श\", \"sh\"),\n",
        "    (\"ष\", \"sh\"),  # Same sound in modern pronunciation\n",
        "    (\"स\", \"s\"),\n",
        "    (\"ह\", \"h\"),\n",
        "\n",
        "    # Consonant clusters and special consonants\n",
        "    (\"क्ष\", \"ksh\"),\n",
        "    (\"त्र\", \"tr\"),\n",
        "    (\"ज्ञ\", \"gya\"),\n",
        "    (\"श्र\", \"shra\"),\n",
        "\n",
        "    # Special characters\n",
        "    (\"़\", \"\"),    # Ignore nukta; can vary with regional pronunciation\n",
        "    (\"्\", \"\"),    # Halant - schwa dropping (handled contextually)\n",
        "    (\"ऽ\", \"\"),    # Avagraha - no direct pronunciation, often ignored\n",
        "    (\"ं\", \"n\"),   # Anusvara - nasalization\n",
        "    (\"ः\", \"h\"),   # Visarga - adds an 'h' sound\n",
        "    (\"ँ\", \"n\"),   # Chandrabindu - nasalization\n",
        "\n",
        "    # Vowel matras (diacritic marks)\n",
        "    (\"ा\", \"a\"),\n",
        "    (\"ि\", \"i\"),\n",
        "    (\"ी\", \"ee\"),\n",
        "    (\"ु\", \"u\"),\n",
        "    (\"ू\", \"oo\"),\n",
        "    (\"े\", \"e\"),\n",
        "    (\"ै\", \"ai\"),\n",
        "    (\"ो\", \"o\"),\n",
        "    (\"ौ\", \"au\"),\n",
        "    (\"ृ\", \"ri\"),  # Vowel-matra equivalent of ऋ\n",
        "\n",
        "    # Nasalization and other marks\n",
        "    (\"ॅ\", \"e\"),   # Short 'e' sound (very rare)\n",
        "    (\"ॉ\", \"o\"),   # Short 'o' sound (very rare)\n",
        "\n",
        "    # Loanwords and aspirated consonants\n",
        "    (\"क़\", \"q\"),\n",
        "    (\"ख़\", \"kh\"),\n",
        "    (\"ग़\", \"gh\"),\n",
        "    (\"ज़\", \"z\"),\n",
        "    (\"ड़\", \"r\"),\n",
        "    (\"ढ़\", \"rh\"),\n",
        "    (\"फ़\", \"f\"),\n",
        "\n",
        "    # Punctuation\n",
        "    (\"।\", \".\"),   # Hindi sentence-ending marker -> period\n",
        "]\n",
        "\n",
        "def cleanup_text(inputs):\n",
        "    for src, dst in replacements:\n",
        "        inputs[\"sentence\"] = inputs[\"sentence\"].replace(src, dst)\n",
        "    return inputs\n",
        "\n",
        "dataset = dataset.map(cleanup_text)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "119b98ceb88d4e10bc6ea212193c8efc",
            "6ea15445d3a5442980775420c0ef1960",
            "202c3a28b17d495a9ac3360f6a85bf12",
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            "0a53ed0435c9478ea4c550f815b5e159",
            "58070cfc123b461d97ce3324146f887d",
            "c219b1f88b6b4071b1a5d74a3d9ff9a6",
            "3ba3762f5821456abf25616a17ecb8a2",
            "47688230646843b9b5dfced87d0757e0"
          ]
        },
        "id": "B6xzTZXyHncT",
        "outputId": "708654b6-ef6b-45c4-88ed-14264c96b941"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "119b98ceb88d4e10bc6ea212193c8efc",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Map:   0%|          | 0/10329 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "def extract_all_chars(batch):\n",
        "    all_text = \" \".join(batch[\"sentence\"])\n",
        "    vocab = list(set(all_text))\n",
        "    return {\"vocab\": [vocab], \"all_text\": [all_text]}\n",
        "\n",
        "\n",
        "vocabs = dataset.map(\n",
        "    extract_all_chars,\n",
        "    batched=True,\n",
        "    batch_size=-1,\n",
        "    keep_in_memory=True,\n",
        "    remove_columns=dataset.column_names,\n",
        ")\n",
        "\n",
        "dataset_vocab = set(vocabs[\"vocab\"][0])\n",
        "tokenizer_vocab = {k for k, _ in tokenizer.get_vocab().items()}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z8Pn-PxjHt9R",
        "outputId": "3aa8149b-8535-45b9-beab-1f181351ae23"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{' ', '&', '|', '–', '‘', '’', '“', '”'}"
            ]
          },
          "execution_count": 16,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dataset_vocab - tokenizer_vocab"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "153fabf9a27048de81eb0d7d5e63a60c",
            "4a2eb6afc00e41d2bfff565334744f75",
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            "d2b8cf13c5454c62b358fdd337148013"
          ]
        },
        "id": "JtB79J5ZH08x",
        "outputId": "80255a73-9252-44a9-99f7-30efbdea3728"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "153fabf9a27048de81eb0d7d5e63a60c",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Map:   0%|          | 0/10329 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import re\n",
        "\n",
        "def normalize_text(text):\n",
        "    # Convert to lowercase\n",
        "    text = text.lower()\n",
        "\n",
        "    # Remove punctuation (except apostrophes)\n",
        "    text = re.sub(r'[^\\w\\s\\']', '', text)\n",
        "\n",
        "    # Remove extra whitespace\n",
        "    text = ' '.join(text.split())\n",
        "\n",
        "    return text\n",
        "\n",
        "# Define a function to add the normalized_text column\n",
        "def add_normalized_text(example):\n",
        "    example['sentence'] = normalize_text(example['sentence'])\n",
        "    return example\n",
        "\n",
        "# Apply the function to the dataset\n",
        "dataset = dataset.map(add_normalized_text)\n",
        "\n",
        "# Print the first few examples to verify\n",
        "# print(dataset[2:5])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "3bc814914d1e4bfda6975ead26de7562",
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        },
        "id": "5KZM40b8IAvy",
        "outputId": "9a4daa05-12cb-49d0-bfa3-8c0746f75733"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "3bc814914d1e4bfda6975ead26de7562",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Map:   0%|          | 0/10329 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "def extract_all_chars(batch):\n",
        "    all_text = \" \".join(batch[\"sentence\"])\n",
        "    vocab = list(set(all_text))\n",
        "    return {\"vocab\": [vocab], \"all_text\": [all_text]}\n",
        "\n",
        "\n",
        "vocabs = dataset.map(\n",
        "    extract_all_chars,\n",
        "    batched=True,\n",
        "    batch_size=-1,\n",
        "    keep_in_memory=True,\n",
        "    remove_columns=dataset.column_names,\n",
        ")\n",
        "\n",
        "dataset_vocab = set(vocabs[\"vocab\"][0])\n",
        "tokenizer_vocab = {k for k, _ in tokenizer.get_vocab().items()}"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pDPFGZw2IDMb",
        "outputId": "1990744b-0916-4201-99b9-41eeea790248"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "{' '}"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dataset_vocab - tokenizer_vocab"
      ]
    },
    {
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      "execution_count": 20,
      "metadata": {
        "colab": {
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        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "dba9ae263cbf4439a0040b312b2558e2",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "hyperparams.yaml:   0%|          | 0.00/2.04k [00:00<?, ?B/s]"
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              "version_major": 2,
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            "text/plain": [
              "embedding_model.ckpt:   0%|          | 0.00/16.9M [00:00<?, ?B/s]"
            ]
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          "metadata": {},
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        {
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              "mean_var_norm_emb.ckpt:   0%|          | 0.00/3.20k [00:00<?, ?B/s]"
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            "text/plain": [
              "classifier.ckpt:   0%|          | 0.00/15.9M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "08893cb2c34a4984a4586468d9f31b28",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "label_encoder.txt:   0%|          | 0.00/129k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/speechbrain/utils/checkpoints.py:147: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
            "  torch.load(path, map_location=device), strict=False\n",
            "/usr/local/lib/python3.10/dist-packages/speechbrain/processing/features.py:1215: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.\n",
            "  stats = torch.load(path, map_location=device)\n"
          ]
        }
      ],
      "source": [
        "import os\n",
        "import torch\n",
        "from speechbrain.pretrained import EncoderClassifier\n",
        "\n",
        "spk_model_name = \"speechbrain/spkrec-xvect-voxceleb\"\n",
        "\n",
        "device = \"cuda\" if torch.cuda.is_available() else \"cpu\"\n",
        "speaker_model = EncoderClassifier.from_hparams(\n",
        "    source=spk_model_name,\n",
        "    run_opts={\"device\": device},\n",
        "    savedir=os.path.join(\"/tmp\", spk_model_name),\n",
        ")\n",
        "\n",
        "\n",
        "def create_speaker_embedding(waveform):\n",
        "    with torch.no_grad():\n",
        "        speaker_embeddings = speaker_model.encode_batch(torch.tensor(waveform))\n",
        "        speaker_embeddings = torch.nn.functional.normalize(speaker_embeddings, dim=2)\n",
        "        speaker_embeddings = speaker_embeddings.squeeze().cpu().numpy()\n",
        "    return speaker_embeddings"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "OdM2RWNfg1gH"
      },
      "outputs": [],
      "source": [
        "def prepare_dataset(example):\n",
        "    audio = example[\"audio\"]\n",
        "\n",
        "    example = processor(\n",
        "        text=example[\"sentence\"],\n",
        "        audio_target=audio[\"array\"],\n",
        "        sampling_rate=audio[\"sampling_rate\"],\n",
        "        return_attention_mask=False,\n",
        "    )\n",
        "\n",
        "    # strip off the batch dimension\n",
        "    example[\"labels\"] = example[\"labels\"][0]\n",
        "\n",
        "    # use SpeechBrain to obtain x-vector\n",
        "    example[\"speaker_embeddings\"] = create_speaker_embedding(audio[\"array\"])\n",
        "\n",
        "    return example"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JI6x3PD-g13d",
        "outputId": "dbfbb04c-bd08-4abc-84d1-3ecfe5b8a5bf"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "['input_ids', 'labels', 'speaker_embeddings']"
            ]
          },
          "execution_count": 22,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "processed_example = prepare_dataset(dataset[0])\n",
        "list(processed_example.keys())"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0oTcqW8sg3os",
        "outputId": "ad927ba2-bec3-424d-cf9e-193d30389013"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "(512,)"
            ]
          },
          "execution_count": 23,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "processed_example[\"speaker_embeddings\"].shape"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 49,
          "referenced_widgets": [
            "36b157d40886445c9216a6b8aba0d3a6",
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            "6d874ab9ef1042b08e39ac51d6ac3daf",
            "9b52c73b85784d7a8bca07f50e6da52f",
            "769e6cec494e462e8fab5bc32cafb95d",
            "c9a034dae54d428da02e339536941de8",
            "218fcb89524a4805bae8ed80e7c136af",
            "406c6c47d6df4d03a0c7242bdcb2f436",
            "7bdd042b09464160bd68e1b3f2ad3dcb",
            "4080d702e3f940a9858ce8f5d0349edd"
          ]
        },
        "id": "zpF2x6jlg8-U",
        "outputId": "0a7c3971-84ba-443c-fc0c-53ae6989ec4b"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "36b157d40886445c9216a6b8aba0d3a6",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Map:   0%|          | 0/10329 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "dataset = dataset.map(prepare_dataset, remove_columns=dataset.column_names)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 67,
          "referenced_widgets": [
            "ef86339de4da498998de3578acd04a66",
            "29397a19e004463bb51eac4e940e7fc3",
            "05c6a89120e9447b8f9b856a07cdc9aa",
            "3654c58622034d009b09a36e810a181f",
            "ec1d3b92e7584f86a16e5da85ce3248b",
            "d2b447634ebd44559e31884eda258a61",
            "ab60fbca4bf542e1aa241f8bd8874361",
            "c22efabac5604ae8aec7a606e3cd4e4d",
            "45eb920d33174f0ba17e7e8351ac5bff",
            "5c47cc2d817147b1907287a5a636f95e",
            "210e929ca79b4b5c9a5d19e5dc9a150b"
          ]
        },
        "id": "QnoDYrafhBeP",
        "outputId": "f8b5f34b-e79a-40e8-f11e-dff0540e0a70"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "ef86339de4da498998de3578acd04a66",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Filter:   0%|          | 0/10329 [00:00<?, ? examples/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "text/plain": [
              "10329"
            ]
          },
          "execution_count": 25,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "def is_not_too_long(input_ids):\n",
        "    input_length = len(input_ids)\n",
        "    return input_length < 200\n",
        "\n",
        "dataset = dataset.filter(is_not_too_long, input_columns=[\"input_ids\"])\n",
        "len(dataset)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 26,
      "metadata": {
        "id": "ux7w-nybhNCF"
      },
      "outputs": [],
      "source": [
        "dataset = dataset.train_test_split(test_size=0.1)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 27,
      "metadata": {
        "id": "GXRcMXXdhQ1C"
      },
      "outputs": [],
      "source": [
        "from dataclasses import dataclass\n",
        "from typing import Any, Dict, List, Union\n",
        "\n",
        "\n",
        "@dataclass\n",
        "class TTSDataCollatorWithPadding:\n",
        "    processor: Any\n",
        "\n",
        "    def __call__(\n",
        "        self, features: List[Dict[str, Union[List[int], torch.Tensor]]]\n",
        "    ) -> Dict[str, torch.Tensor]:\n",
        "        input_ids = [{\"input_ids\": feature[\"input_ids\"]} for feature in features]\n",
        "        label_features = [{\"input_values\": feature[\"labels\"]} for feature in features]\n",
        "        speaker_features = [feature[\"speaker_embeddings\"] for feature in features]\n",
        "\n",
        "        # collate the inputs and targets into a batch\n",
        "        batch = processor.pad(\n",
        "            input_ids=input_ids, labels=label_features, return_tensors=\"pt\"\n",
        "        )\n",
        "\n",
        "        # replace padding with -100 to ignore loss correctly\n",
        "        batch[\"labels\"] = batch[\"labels\"].masked_fill(\n",
        "            batch.decoder_attention_mask.unsqueeze(-1).ne(1), -100\n",
        "        )\n",
        "\n",
        "        # not used during fine-tuning\n",
        "        del batch[\"decoder_attention_mask\"]\n",
        "\n",
        "        # round down target lengths to multiple of reduction factor\n",
        "        if model.config.reduction_factor > 1:\n",
        "            target_lengths = torch.tensor(\n",
        "                [len(feature[\"input_values\"]) for feature in label_features]\n",
        "            )\n",
        "            target_lengths = target_lengths.new(\n",
        "                [\n",
        "                    length - length % model.config.reduction_factor\n",
        "                    for length in target_lengths\n",
        "                ]\n",
        "            )\n",
        "            max_length = max(target_lengths)\n",
        "            batch[\"labels\"] = batch[\"labels\"][:, :max_length]\n",
        "\n",
        "        # also add in the speaker embeddings\n",
        "        batch[\"speaker_embeddings\"] = torch.tensor(speaker_features)\n",
        "\n",
        "        return batch"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 28,
      "metadata": {
        "id": "_Z2Q_KrshSNi"
      },
      "outputs": [],
      "source": [
        "data_collator = TTSDataCollatorWithPadding(processor=processor)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 29,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81,
          "referenced_widgets": [
            "4892ee485ea242dba4ac938b47ecdd49",
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            "2c189ee40efe4841ace4638ed6c5ac91",
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            "3c27f2c01aa74f36afee1c8633fbad18",
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            "147c0c21eb134502b5656b320477df83",
            "b59b8f5b9f324722aa48ac420286444b"
          ]
        },
        "id": "rXVZzQYphZim",
        "outputId": "9a3d7a09-679f-4dad-8ca8-c2bd918f5656"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "4892ee485ea242dba4ac938b47ecdd49",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "config.json:   0%|          | 0.00/2.06k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "fd6fed2ed27344f49bf1031f6cd32265",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "pytorch_model.bin:   0%|          | 0.00/585M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from transformers import SpeechT5ForTextToSpeech\n",
        "\n",
        "model = SpeechT5ForTextToSpeech.from_pretrained(checkpoint)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 30,
      "metadata": {
        "id": "ESMgm4K5hdDi"
      },
      "outputs": [],
      "source": [
        "from functools import partial\n",
        "\n",
        "# disable cache during training since it's incompatible with gradient checkpointing\n",
        "model.config.use_cache = False\n",
        "\n",
        "# set language and task for generation and re-enable cache\n",
        "model.generate = partial(model.generate, use_cache=True)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 31,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "U8BoZ8xuhe8i",
        "outputId": "5551e967-7461-4afb-d94e-3542f1c0ac2b"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/transformers/training_args.py:1525: FutureWarning: `evaluation_strategy` is deprecated and will be removed in version 4.46 of 🤗 Transformers. Use `eval_strategy` instead\n",
            "  warnings.warn(\n"
          ]
        }
      ],
      "source": [
        "from transformers import Seq2SeqTrainingArguments\n",
        "\n",
        "training_args = Seq2SeqTrainingArguments(\n",
        "    output_dir=\"Hindi_SpeechT5_finetuned\",  # change to a repo name of your choice\n",
        "    per_device_train_batch_size=4,\n",
        "    gradient_accumulation_steps=8,\n",
        "    learning_rate=0.0001,\n",
        "    warmup_steps=100,\n",
        "    max_steps=1500,\n",
        "    gradient_checkpointing=True,\n",
        "    fp16=True,\n",
        "    evaluation_strategy=\"steps\",\n",
        "    per_device_eval_batch_size=2,\n",
        "    save_steps=100,\n",
        "    eval_steps=100,\n",
        "    logging_steps=50,\n",
        "    report_to=[\"tensorboard\"],\n",
        "    load_best_model_at_end=True,\n",
        "    greater_is_better=False,\n",
        "    label_names=[\"labels\"],\n",
        "    push_to_hub=True,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "2-HhrQ_Gh2Gf",
        "outputId": "771adda5-b207-4634-c898-3bbfacce8add"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/accelerate/accelerator.py:494: FutureWarning: `torch.cuda.amp.GradScaler(args...)` is deprecated. Please use `torch.amp.GradScaler('cuda', args...)` instead.\n",
            "  self.scaler = torch.cuda.amp.GradScaler(**kwargs)\n",
            "max_steps is given, it will override any value given in num_train_epochs\n"
          ]
        }
      ],
      "source": [
        "from transformers import Seq2SeqTrainer\n",
        "\n",
        "trainer = Seq2SeqTrainer(\n",
        "    args=training_args,\n",
        "    model=model,\n",
        "    train_dataset=dataset[\"train\"],\n",
        "    eval_dataset=dataset[\"test\"],\n",
        "    data_collator=data_collator,\n",
        "    tokenizer=processor,\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 33,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "71Le1psSjbXv",
        "outputId": "569b9c54-5a5c-4662-971a-5233e6c7e119"
      },
      "outputs": [
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\n"
          ]
        },
        {
          "data": {
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              "      \n",
              "      <progress value='1500' max='1500' style='width:300px; height:20px; vertical-align: middle;'></progress>\n",
              "      [1500/1500 1:00:29, Epoch 5/6]\n",
              "    </div>\n",
              "    <table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              " <tr style=\"text-align: left;\">\n",
              "      <th>Step</th>\n",
              "      <th>Training Loss</th>\n",
              "      <th>Validation Loss</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <td>100</td>\n",
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              "    <tr>\n",
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              "      <td>0.554000</td>\n",
              "      <td>0.508966</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>400</td>\n",
              "      <td>0.539700</td>\n",
              "      <td>0.502509</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>500</td>\n",
              "      <td>0.526000</td>\n",
              "      <td>0.487176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>600</td>\n",
              "      <td>0.522400</td>\n",
              "      <td>0.484650</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>700</td>\n",
              "      <td>0.515000</td>\n",
              "      <td>0.475371</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>800</td>\n",
              "      <td>0.504700</td>\n",
              "      <td>0.470318</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>900</td>\n",
              "      <td>0.501400</td>\n",
              "      <td>0.468941</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1000</td>\n",
              "      <td>0.494600</td>\n",
              "      <td>0.460144</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1100</td>\n",
              "      <td>0.491200</td>\n",
              "      <td>0.458416</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1200</td>\n",
              "      <td>0.484700</td>\n",
              "      <td>0.455372</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1300</td>\n",
              "      <td>0.482400</td>\n",
              "      <td>0.451364</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1400</td>\n",
              "      <td>0.483100</td>\n",
              "      <td>0.450094</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <td>1500</td>\n",
              "      <td>0.472300</td>\n",
              "      <td>0.448437</td>\n",
              "    </tr>\n",
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              "</table><p>"
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              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n",
            "/usr/local/lib/python3.10/dist-packages/torch/_dynamo/eval_frame.py:632: UserWarning: torch.utils.checkpoint: the use_reentrant parameter should be passed explicitly. In version 2.5 we will raise an exception if use_reentrant is not passed. use_reentrant=False is recommended, but if you need to preserve the current default behavior, you can pass use_reentrant=True. Refer to docs for more details on the differences between the two variants.\n",
            "  return fn(*args, **kwargs)\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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n"
          ]
        },
        {
          "data": {
            "text/plain": [
              "TrainOutput(global_step=1500, training_loss=0.5311578127543132, metrics={'train_runtime': 3632.9281, 'train_samples_per_second': 13.212, 'train_steps_per_second': 0.413, 'total_flos': 2810069620139232.0, 'train_loss': 0.5311578127543132, 'epoch': 5.163511187607573})"
            ]
          },
          "execution_count": 33,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "trainer.train()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 34,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 128
        },
        "id": "0xn3lA-Ah2nM",
        "outputId": "69690323-c103-4ea2-dda5-57dfdcc83dbf"
      },
      "outputs": [
        {
          "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': 1876}\n",
            "Your generation config was originally created from the model config, but the model config has changed since then. Unless you pass the `generation_config` argument to this model's `generate` calls, they will revert to the legacy behavior where the base `generate` parameterization is loaded from the model config instead. To avoid this behavior and this warning, we recommend you to overwrite the generation config model attribute before calling the model's `save_pretrained`, preferably also removing any generation kwargs from the model config. This warning will be raised to an exception in v4.41.\n"
          ]
        },
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "CommitInfo(commit_url='https://huggingface.co/Sana1207/Hindi_SpeechT5_finetuned/commit/643487c74323d7f6c601479f362fba66e648b85b', commit_message='End of training', commit_description='', oid='643487c74323d7f6c601479f362fba66e648b85b', pr_url=None, pr_revision=None, pr_num=None)"
            ]
          },
          "execution_count": 34,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "trainer.push_to_hub()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3oVec-aUN2is"
      },
      "source": [
        "# Inference"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 113,
          "referenced_widgets": [
            "3d13133dd6874235aa388882ca78c10b",
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            "d616d04bb13242999ede9f22487d0041",
            "8fae54c1ffac4a5493704cb2d7aed449",
            "5ca90b44922d4425ab40aee0fb3ee166",
            "df88a481ccfe4204bcb3712e442c7a68",
            "a7cce7c899254616b9101f669514b763",
            "c11a6f1f853d4e7baabe87fd39c368cf",
            "18fae7baa30243d5b6c95dcb681b5c01",
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            "cdc2687d232640bf8c74c63681b0c1eb",
            "6e3b360e3c034fadb1f4a96f77d652c5",
            "2f179af12fb541c593cd96fa15b2f4bc"
          ]
        },
        "id": "DttRwG_Qh6jP",
        "outputId": "894ccd2c-8289-411d-dcb9-063c8c0a3771"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "3d13133dd6874235aa388882ca78c10b",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "config.json:   0%|          | 0.00/2.10k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "8eb69c1cd9804e6295e26cde7257ec00",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "model.safetensors:   0%|          | 0.00/578M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "d616d04bb13242999ede9f22487d0041",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "generation_config.json:   0%|          | 0.00/185 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "model = SpeechT5ForTextToSpeech.from_pretrained(\n",
        "    \"Saurabh_Kumar/Hindi_SpeechT5_finetuned\"\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "X5Iipatxh_8z"
      },
      "outputs": [],
      "source": [
        "example = dataset[\"test\"][304]\n",
        "speaker_embeddings = torch.tensor(example[\"speaker_embeddings\"]).unsqueeze(0)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "hu_9NGOyiCop"
      },
      "outputs": [],
      "source": [
        "text = \"मेरा नाम सौरभ है\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "LQTOgkZ9xCIA"
      },
      "outputs": [],
      "source": [
        "# number_words = {\n",
        "#     0: \"sıfır\", 1: \"bir\", 2: \"iki\", 3: \"üç\", 4: \"dört\", 5: \"beş\", 6: \"altı\", 7: \"yedi\", 8: \"sekiz\", 9: \"dokuz\",\n",
        "#     10: \"on\", 11: \"on bir\", 12: \"on iki\", 13: \"on üç\", 14: \"on dört\", 15: \"on beş\", 16: \"on altı\", 17: \"on yedi\",\n",
        "#     18: \"on sekiz\", 19: \"on dokuz\", 20: \"yirmi\", 30: \"otuz\", 40: \"kırk\", 50: \"elli\", 60: \"altmış\", 70: \"yetmiş\",\n",
        "#     80: \"seksen\", 90: \"doksan\", 100: \"yüz\", 1000: \"bin\"\n",
        "# }\n",
        "\n",
        "# def number_to_words(number):\n",
        "#     if number < 20:\n",
        "#         return number_words[number]\n",
        "#     elif number < 100:\n",
        "#         tens, unit = divmod(number, 10)\n",
        "#         return number_words[tens * 10] + (\" \" + number_words[unit] if unit else \"\")\n",
        "#     elif number < 1000:\n",
        "#         hundreds, remainder = divmod(number, 100)\n",
        "#         return (number_words[hundreds] + \" yüz\" if hundreds > 1 else \"yüz\") + (\" \" + number_to_words(remainder) if remainder else \"\")\n",
        "#     elif number < 1000000:\n",
        "#         thousands, remainder = divmod(number, 1000)\n",
        "#         return (number_to_words(thousands) + \" bin\" if thousands > 1 else \"bin\") + (\" \" + number_to_words(remainder) if remainder else \"\")\n",
        "#     elif number < 1000000000:\n",
        "#         millions, remainder = divmod(number, 1000000)\n",
        "#         return number_to_words(millions) + \" milyon\" + (\" \" + number_to_words(remainder) if remainder else \"\")\n",
        "#     elif number < 1000000000000:\n",
        "#         billions, remainder = divmod(number, 1000000000)\n",
        "#         return number_to_words(billions) + \" milyar\" + (\" \" + number_to_words(remainder) if remainder else \"\")\n",
        "#     else:\n",
        "#         return str(number)\n",
        "\n",
        "# def replace_numbers_with_words(text):\n",
        "\n",
        "#     def replace(match):\n",
        "#         number = int(match.group())\n",
        "#         return number_to_words(number)\n",
        "\n",
        "#     # Find the numbers and change with words.\n",
        "#     result = re.sub(r'\\b\\d+\\b', replace, text)\n",
        "\n",
        "#     return result"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "tE9SBjH2j4Vk"
      },
      "outputs": [],
      "source": [
        "# Function to clean up text using the replacement pairs\n",
        "def cleanup_text(text):\n",
        "    for src, dst in replacements:\n",
        "        text = text.replace(src, dst)\n",
        "    return text"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 36
        },
        "id": "W842Kdt8j61e",
        "outputId": "83d1e4c1-41b5-4593-f262-aeb8d390a662"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'mera nam saurbh hai'"
            ]
          },
          "execution_count": 52,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# converted_text = replace_numbers_with_words(text)\n",
        "cleaned_text = cleanup_text(text)\n",
        "final_text = normalize_text(cleaned_text)\n",
        "final_text"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "427k1nlViGDn"
      },
      "outputs": [],
      "source": [
        "inputs = processor(text=final_text, return_tensors=\"pt\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81,
          "referenced_widgets": [
            "1b617bca76d6490fafbe5157ee2797a8",
            "eae0df7a97b94313b1281fd0862e3511",
            "2fe8a63ab66841e99102ec70a098272d",
            "33bb7bc8850c4721819302571d6664dd",
            "28c6cef9133f496b9b55b9305957e60d",
            "8ff32f795ced42749ef31b64326b1445",
            "df697dd7a749400aac430af4b6cf0338",
            "68940dca1369475e9774ace6e75f572c",
            "7c381cc6bf174c20bb904dd057b73aec",
            "2597379f6034448da45f50f96be81028",
            "6f524de6f7cf43a8b5bf599f71ffc414",
            "d5042fe641a34dd69e30ae8dde15b211",
            "2538f633f208466eb7c7601c6e5ecfee",
            "707475350003407ab4dd0ce684c1f2eb",
            "8e37a61c880943ca9728fefb18794d2a",
            "4bbf68def5b14f20af492ae0f0800690",
            "57883ec2a207410cad0b8282186d8b09",
            "6d154aae82a141ce9dc8ad68c8d33181",
            "566a8d5ca0534eb593717dbf14c8ebca",
            "519eb1bf2b184f909da24b216cfa8026",
            "d4ce84f0caf5467ea3551756ed457492",
            "69dafe213e3b4ff5985290a09f9db475"
          ]
        },
        "id": "or8TQBPyiLiA",
        "outputId": "2618fa5f-5571-4a63-b37e-549b949b026f"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "1b617bca76d6490fafbe5157ee2797a8",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "config.json:   0%|          | 0.00/636 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "d5042fe641a34dd69e30ae8dde15b211",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "pytorch_model.bin:   0%|          | 0.00/50.7M [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "from transformers import SpeechT5HifiGan\n",
        "\n",
        "vocoder = SpeechT5HifiGan.from_pretrained(\"microsoft/speecht5_hifigan\")\n",
        "speech = model.generate_speech(inputs[\"input_ids\"], speaker_embeddings, vocoder=vocoder)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "S289pqndiNDW"
      },
      "outputs": [],
      "source": [
        "from IPython.display import Audio\n",
        "import soundfile as sf\n",
        "\n",
        "Audio(speech.numpy(), rate=16000)\n",
        "# Save the audio to a file (e.g., 'output.wav')\n",
        "sf.write('output.wav', speech.numpy(), 16000)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "rq9mOAuR04CP"
      },
      "outputs": [],
      "source": [
        "text = \"मैं एक छात्र हूँ\"\n",
        "# converted_text = replace_numbers_with_words(text)\n",
        "cleaned_text = cleanup_text(text)\n",
        "final_text = normalize_text(cleaned_text)\n",
        "inputs = processor(text=final_text, return_tensors=\"pt\")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 76
        },
        "id": "8HNmusVgc6gO",
        "outputId": "83a95b3b-1524-4a4e-f158-3b09f951c7b9"
      },
      "outputs": [
        {
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type=\"audio/wav\" />\n",
              "                    Your browser does not support the audio element.\n",
              "                </audio>\n",
              "              "
            ],
            "text/plain": [
              "<IPython.lib.display.Audio object>"
            ]
          },
          "execution_count": 59,
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        }
      ],
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        "\n",
        "speech = model.generate_speech(inputs[\"input_ids\"], speaker_embeddings, vocoder=vocoder)\n",
        "# Save the audio to a file (e.g., 'output.wav')\n",
        "sf.write('output_1.wav', speech.numpy(), 16000)\n",
        "Audio(speech.numpy(), rate=16000)\n"
      ]
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      "metadata": {
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      },
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      "source": []
    }
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