{ "cells": [ { "cell_type": "code", "execution_count": 3, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "snR6wRVuRQ1K", "outputId": "ad3352f3-1c3e-4506-e4e2-20ffa9744058", "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. 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It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", "\u001b[0m" ] } ], "source": [ "\n", "!pip install datasets>=2.6.1\n", "# !pip install git+https://github.com/huggingface/transformers\n", "!pip install librosa\n", "!pip install evaluate<=0.30\n", "!pip install jiwer\n", "!pip install gradio" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "AngpP8N0SN98", "outputId": "0c76099b-55ff-4432-d621-3b1492132554", "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: transformers==4.27.0 in /opt/conda/lib/python3.10/site-packages (4.27.0)\n", "Requirement already satisfied: filelock in /opt/conda/lib/python3.10/site-packages (from transformers==4.27.0) (3.12.0)\n", "Requirement already satisfied: huggingface-hub<1.0,>=0.11.0 in /opt/conda/lib/python3.10/site-packages (from transformers==4.27.0) (0.14.1)\n", "Requirement already satisfied: numpy>=1.17 in /opt/conda/lib/python3.10/site-packages (from transformers==4.27.0) (1.23.5)\n", "Requirement already satisfied: packaging>=20.0 in /opt/conda/lib/python3.10/site-packages (from transformers==4.27.0) (23.1)\n", "Requirement already satisfied: pyyaml>=5.1 in /opt/conda/lib/python3.10/site-packages (from transformers==4.27.0) (5.4.1)\n", "Requirement already satisfied: regex!=2019.12.17 in /opt/conda/lib/python3.10/site-packages (from transformers==4.27.0) (2023.5.5)\n", "Requirement already satisfied: requests in /opt/conda/lib/python3.10/site-packages (from transformers==4.27.0) (2.28.2)\n", "Requirement already satisfied: tokenizers!=0.11.3,<0.14,>=0.11.1 in /opt/conda/lib/python3.10/site-packages (from transformers==4.27.0) (0.13.3)\n", "Requirement already satisfied: tqdm>=4.27 in /opt/conda/lib/python3.10/site-packages (from transformers==4.27.0) (4.65.0)\n", "Requirement already satisfied: fsspec in /opt/conda/lib/python3.10/site-packages (from huggingface-hub<1.0,>=0.11.0->transformers==4.27.0) (2023.5.0)\n", "Requirement already satisfied: typing-extensions>=3.7.4.3 in /opt/conda/lib/python3.10/site-packages (from huggingface-hub<1.0,>=0.11.0->transformers==4.27.0) (4.5.0)\n", "Requirement already satisfied: charset-normalizer<4,>=2 in /opt/conda/lib/python3.10/site-packages (from requests->transformers==4.27.0) (3.1.0)\n", "Requirement already satisfied: idna<4,>=2.5 in /opt/conda/lib/python3.10/site-packages (from requests->transformers==4.27.0) (3.4)\n", "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /opt/conda/lib/python3.10/site-packages (from requests->transformers==4.27.0) (1.26.15)\n", "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/lib/python3.10/site-packages (from requests->transformers==4.27.0) (2023.5.7)\n", "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", "\u001b[0m" ] } ], "source": [ "!pip install transformers==4.27.0" ] }, { "cell_type": "code", "execution_count": 5, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: ipywidgets in /opt/conda/lib/python3.10/site-packages (8.0.6)\n", "Requirement already satisfied: ipykernel>=4.5.1 in /opt/conda/lib/python3.10/site-packages (from ipywidgets) (6.23.0)\n", "Requirement already satisfied: ipython>=6.1.0 in /opt/conda/lib/python3.10/site-packages (from ipywidgets) (8.13.2)\n", "Requirement already satisfied: traitlets>=4.3.1 in /opt/conda/lib/python3.10/site-packages (from ipywidgets) (5.9.0)\n", "Requirement already satisfied: widgetsnbextension~=4.0.7 in /opt/conda/lib/python3.10/site-packages (from ipywidgets) (4.0.7)\n", "Requirement already satisfied: jupyterlab-widgets~=3.0.7 in 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It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", "\u001b[0m" ] } ], "source": [ "!pip install ipywidgets" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: jupyter in /opt/conda/lib/python3.10/site-packages (1.0.0)\n", "Requirement already satisfied: notebook in /opt/conda/lib/python3.10/site-packages (from jupyter) (6.5.4)\n", "Requirement already satisfied: qtconsole in /opt/conda/lib/python3.10/site-packages (from jupyter) (5.3.2)\n", "Requirement already satisfied: jupyter-console in /opt/conda/lib/python3.10/site-packages (from jupyter) (6.4.3)\n", "Requirement already satisfied: nbconvert in /opt/conda/lib/python3.10/site-packages (from jupyter) (7.3.1)\n", "Requirement already satisfied: ipykernel in /opt/conda/lib/python3.10/site-packages (from jupyter) (6.20.2)\n", "Requirement already 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"Requirement already satisfied: pyyaml>=5.3 in /opt/conda/lib/python3.10/site-packages (from jupyter-events>=0.4.0->jupyter-server>=1.8->nbclassic>=0.4.7->notebook->jupyter) (5.4.1)\n", "Requirement already satisfied: rfc3339-validator in /opt/conda/lib/python3.10/site-packages (from jupyter-events>=0.4.0->jupyter-server>=1.8->nbclassic>=0.4.7->notebook->jupyter) (0.1.4)\n", "Requirement already satisfied: rfc3986-validator>=0.1.1 in /opt/conda/lib/python3.10/site-packages (from jupyter-events>=0.4.0->jupyter-server>=1.8->nbclassic>=0.4.7->notebook->jupyter) (0.1.1)\n", "\u001b[33mWARNING: jsonschema 3.2.0 does not provide the extra 'format-nongpl'\u001b[0m\u001b[33m\n", "\u001b[0m\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", "\u001b[0m" ] } ], "source": [ "!pip install jupyter" ] }, { "cell_type": "code", "execution_count": 6, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "usage: huggingface-cli []\n", "huggingface-cli: error: unrecognized arguments: --add_to_git_credential True\n" ] } ], "source": [ "!huggingface-cli login --token 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 --add_to_git_credential True" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", "\u001b[0m" ] } ], "source": [ "!pip install --upgrade --quiet jupyter_client ipywidgets" ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 249, "referenced_widgets": [ "a9ebf75c8ab94d6c9b6b0163967a99fc", "2db9f6487a654e848151e67234f3ac97", "c34b312163d24251aebf9e94cb4ee695", "58f48427f17d46efb9f1f3b08edcd944", "f3add4326ba348c3920af163a600c514", "8022a4def1cb46c9b0bdf412d8aa20b5", "163666d40091485092c98f16aa35e736", "3990e339631b48368a8f27ad98153477", "6f1fad8d3205450cbd0e5dfa7905bae9", "917274df4dc042ed80a251ec32c1152d", "5b09e1720f3c4cf4816068bd21968df2", "b8a25009ddb147f9a8336094bb08dbca", "08db23fa63da49dfa8c5406d9a76f3a5", "20233d30d8ca4d7aad983685b1dfa39f", "961782d8d94d4727b1ce098fec3071aa", "bc42f2c2874f4444921ffdd8f08bba43", "9b8499c3df044831a2036d9732d945c6", "c5708e00fad3456ca2e3de3d55836b16", "83e539ffb6a94c6b9cc260bfbcc88e0e", "88fc8da68c824af08aca2d7080038369", "3a376076e2b649a8b7a2ddbd1f95ec34", "969cbdf81771456e9872a0ad6b9a0bbe", "5bd23056775748bfaf613b2d685e8515", "4b2a9e9cdd2e48959222981c1b39af2f", "17a5c8517e0c48fa8e5a8ee8c2bbc557", "6a40d1ece4434df69dfed483c1c83a27", "b6bee1b3bebc4043b5987714a30288dd", "f46eab983f5441afbb563ca31080011b", "2460715568ba447d97ce767217fce7ef", "63593a0d4d144a6396911be6877501ee", "2bcc7b19a4e044e98f4431e2ad32ec45", "a8ed749e9d814c6db3d76da509b99046", "b513297fc9964eec818329f0c49f86a0", "2024601d870a47f6a2c5d5ade240136e", "974fb8d841844413b5d67eb339f68ae9", "81e9e1ed3ea44d9d90459140b213e34b", "1531a50c2d8649499cd9658bff8f7a9f", "e27d7fc8ff404c259724a1adb4fb2a25", "2ea78537b2d142d195f11e6332b7eeb0", "53c359a5e0634272bbf1aa1d63f99f90", "7e9de33215f24bf9a8419769416d0db3", "0b1f7ae13aca4d809b6e83e59a5fc904", "777a3a61d21046418787d4d283d12de0", "ef706327811543f0813583e9823197ac", "04a6a943dfa44bfba948fd2a892f6452", "be3e7936451e4c9d92f747df596b41e4", "81abf347b6cb41f0a48e4e27c56aa0a3", "2966843dab824086abf753a809757662", "3fc462edd6f344db93e433fa8ae2827f", "32d897d845874bb8933953158eb2a0da", "d2bdc42f4c7548dd846456a69f1b0a0c", "ccce9a40ebbb4223b826ad86fa80750d", "ec54654f606f4932ba9a8cf6ebb9bb47", "d7d7839838224039b2122c66ff2a0a9d", "e76ead3e254a48fba9b9f2a79eaa6a62", "7b123ff75b114faf9d82d097ea9f34c2", "ee1d4c3d202d459684585f45fe8d046e", "0263a423aff34e75bcf0568052eba549", "2092db1c599a48ba83f1a8aeb5fa51bb", "fb912383875a45b28aada90b70cadcc9", "45fb1c04a81f4929a1136dbfb16674bf", "24486e2f37c44ee89e4161cb23b27d15", "fdc0d045ca914a649d5076f1ad3310bf", "765e2c66271f43769f4abe3e8cbbbafa", "20a4026d97ef49629be444f680e4f51d", "d787cb908d08400596753ac2da4260af", "ca6ebb7065304a839f9b244ba7b48339", "ea8549b89151477f858e2b61356205ef", "ad9270081c574850bac00c5764dbf59f", "f2f28f98c8b14c01878192d8a54b8dd8", "587c4718096a4b85b2e79df8cf838879", "34eb01b6836f42909e4af942175b77f3", "dc45c2941b3c44fb9781b2dd037b4b5b", "b363ded122d6408ea43923f2b4c194ce", "b39f0dff201749d68deda2d1618710e0", "cc5237b99b044e2ba4b6cf23825818f5", "5f2cdc656f1540669fa50aef45672ac3" ] }, "id": "2sF0HNKz5A-U", "outputId": "b9eb3844-e306-42b5-a370-8d986afe09c9", "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Found cached dataset parquet (/root/.cache/huggingface/datasets/mskov___parquet/mskov--misophonia_Sounds-28edff94f9889528/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec)\n", "Found cached dataset parquet (/root/.cache/huggingface/datasets/mskov___parquet/mskov--misophonia_Sounds-28edff94f9889528/0.0.0/2a3b91fbd88a2c90d1dbbb32b460cf621d31bd5b05b934492fdef7d8d6f236ec)\n" ] } ], "source": [ "from datasets import load_dataset, DatasetDict, Audio\n", "\n", "miso = DatasetDict()\n", "\n", "miso[\"train\"] = load_dataset(\"mskov/misophonia_Sounds\", split=\"train\", use_auth_token=True)\n", "miso[\"test\"] = load_dataset(\"mskov/misophonia_Sounds\", split=\"test\", use_auth_token=True)\n", "\n", "#print(esc50['test']['audio'])" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 77, "referenced_widgets": [ "88a76cfb2ecc4897910274c057358b4a", "4410853c857748ddbdb2a6c9a3cde82e", "0edc493ce270498186e1b68e9c4d8f40", "81fd71e6883d41468b861f3d85d4bf53", "628be17ad1bd4cd0ac471be7230a310a", "6cba1c7ca31b4624805e7233ecfa97cc", "01967bac433f485f9a22422050a9c36c", "43ce3cd5c1c44c34a4fbe447071a3039", "437b7b59bcd342989d42ac2e09cd79f2", "b71e69d720614ee0bc61e2b680eb945c", "232810b838f340b1b33781e4917744e9" ] }, "id": "sXCQAmVjhcQW", "outputId": "d86ea782-7b60-4dbf-9298-0675fa1ce54e", "tags": [] }, "outputs": [], "source": [ "from transformers import WhisperFeatureExtractor\n", "\n", "feature_extractor = WhisperFeatureExtractor.from_pretrained(\"openai/whisper-small\")" ] }, { "cell_type": "code", "execution_count": 14, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 317, "referenced_widgets": [ "c5f96b875c404289a187895bd24a6374", "eaca5d44336e46f88df2efbf86b8818e", "5662b33616324231b73f2c34b58f4c79", "98464a05a0a5464f930062dbcf865e43", "d11ed43a285e4c69b95fcd7edae7cdf7", "e879c0cfdc31457fa6f483169fadd2ad", "2961be312f0f4d379733bb0a8a17781a", "09c51c6a0c2b43dcb0085088f6a685f7", "7416590fbe1a45889f3a7b03cc434da5", "6763a10c47894602bb161abce6da24a9", "9a5f66418f4a4c44b4704f47ed080e6d", "a4f1f8f405f54466ab25f1533df77294", "7c62b7555788460997ed331ae9e84fee", "fa7d02501965408fb2c0f2ff459b7586", "622964ae006c417b9658f2b134d55bba", "b231d6fb14f24e398a31ed5da16e9ceb", "9efa1161044f4c7a874c2140346d4dc1", "3f460c4b1a644b43bb82e54203b88e81", "69670eeff5004f3ea9e253f531dd3cd2", "11d5121af8964cb788939a76658ea2ce", "0a6236acf36c46b4a914e44b2b6f0312", "f7f7a63adc73463295882e49ac51a9e5", "84b05f0129e9435381811feacac2032c", "598c752355224a8da3c02bb58d24a5ca", "3f436b916ad14288904c8ceb761a5379", "917dd9f36c06417ea7b37084b123f33e", "cd666e8bbb144a9487f7e5233f376f59", "4f6b21b36c1d41cfa302bbf077541db0", "9bb2d59589bf4e0fa3fed628e44219e5", "229098f8a09a4195ba60aac696ce211d", "b9da8a79c3a64c3db9a74bc046fa2bd9", "1ad553c9aa7a43dca071e788d8bd9d95", "93ea24c0acfb4305a256276f95674244", "8eaf802884b140e1a1a043a43e4f851c", "9fb2c8c93e2c463e87a8220e093ac411", "7150942e892542bf921120fa1155eee1", "83687b24aead4bc6a5501894bdd74474", "30e55d7ed3f8434c89fd3e173f426a78", "d9d2ecb07ac64cbb9e2cf2ba161f4471", "3da07e2ff73e4c409025fe6380231ea3", "27c8d56fd8074ac0acca452ff4005eb5", "47cb358ce2cb4b4a9b2c964c3b50df1e", "be79cec0383d4010bbf62b4b64c1dd5a", "96b5da94c3c64f69bc832c436d07948d", "676c7f2d63d54d7097aec48ada21e26a", "db9855cefeb748b58bb6e46525ebb849", "62f583e9c3e74374a43e65a93ac4b885", "6a68b656e58c43e592c14e234fe050c5", "403f0470eac84ceda46a8f5fcfeb07d8", "010ffd1a6020488d8a2254fbcf8b64c8", "112edf3a5f044f8080937fcb53a314f2", "5d26220651a44039ba9e404da964f03f", "949f19f888524397aedf0ea11bfc1024", "70acab7e86824b20b316883f3c7f733f", "72c4e763d3f143a29c3dd2c0458af722" ] }, "id": "GFnqiveohvlR", "outputId": "38940b45-70a5-4618-dab6-fa60214d5de1", "tags": [] }, "outputs": [], "source": [ "from transformers import WhisperTokenizer\n", "\n", "tokenizer = WhisperTokenizer.from_pretrained(\"openai/whisper-small\", task=\"transcribe\")" ] }, { "cell_type": "code", "execution_count": 15, "metadata": { "id": "nL1tBMRAh3aZ", "tags": [] }, "outputs": [], "source": [ "from transformers import WhisperProcessor\n", "\n", "processor = WhisperProcessor.from_pretrained(\"openai/whisper-small\", task=\"transcribe\")" ] }, { "cell_type": "code", "execution_count": 16, "metadata": { "id": "vAWjc1QPiPYe", "tags": [] }, "outputs": [], "source": [ "from datasets import Audio\n", "\n", "miso =miso.cast_column(\"audio\", Audio(sampling_rate=16000))" ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "id": "LrVZdlCZi7_8", "tags": [] }, "outputs": [], "source": [ "def prepare_dataset(batch):\n", " # load and resample audio data from 48 to 16kHz\n", " audio = batch[\"audio\"]\n", "\n", " # compute log-Mel input features from input audio array \n", " batch[\"input_features\"] = feature_extractor(audio[\"array\"], sampling_rate=audio[\"sampling_rate\"]).input_features[0]\n", "\n", " # encode target text to label ids \n", " batch[\"labels\"] = tokenizer(batch[\"sentence\"]).input_ids\n", " return batch" ] }, { "cell_type": "code", "execution_count": 20, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 17, "referenced_widgets": [ "d99270f5614a40bd99de0cf31177c457", "672b69170fd5431494235679c7c230c4", "73c97342df4a4f8fa697c103c76db4fb", "72822c9f3d404124bb1958f30de04a3c", "5a9364c8935043c2b03634f8ce5515c7", "bfc55f3665434d3fb34ee27b09fa90c8", "4066515cdde4402cb3f871419779c478", "9f2775b714fc448c9d5094378acc213d", "082c06e3aa254a3fade092d38a8bf941", "007c75abe8b0401fa7fdbe75e227202b", "1d2ba76b871f4896b6c0f966ecf44bf3", "7a9a26a799f94921a21789fb613402b8", "fe343e22241f42ae89c4d3be94684bf7", "f7123cce42e2478ba1eb04f75bdfe690", "03bf0dbe1c134af4bf95f9a98afefc0c", "f4773b66b0e04ed0acf35451cbba36cf", "570d27a29418489f909938e2693d9c39", "689aeae2c6574dd39003bd2ad332528d", "05e9b33b463243a9acfc09ac6531d87a", "f85a4f70de5244cca3d28cfe7895ec55", "333b1d2e5d7842998fe12bb308ede2c1", "09e178caa6ba42029f8a5b64c62b33bc" ] }, "id": "_sVXUyMJj_IO", "outputId": "576c42fe-b87d-469f-a73a-c01dddca30bf", "tags": [] }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "3a89aa478537495793ed1ae4f2163615", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Map: 0%| | 0/22 [00:00=2.0 in /opt/conda/lib/python3.10/site-packages (from jinja2->torch) (2.1.2)\n", "Requirement already satisfied: mpmath>=0.19 in /opt/conda/lib/python3.10/site-packages (from sympy->torch) (1.3.0)\n", "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", "\u001b[0m" ] } ], "source": [ "!pip install torch" ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "id": "mXlb7erymQ3O", "tags": [] }, "outputs": [], "source": [ "import torch\n", "\n", "from dataclasses import dataclass\n", "from typing import Any, Dict, List, Union\n", "\n", "@dataclass\n", "class DataCollatorSpeechSeq2SeqWithPadding:\n", " processor: Any\n", "\n", " def __call__(self, features: List[Dict[str, Union[List[int], torch.Tensor]]]) -> Dict[str, torch.Tensor]:\n", " # split inputs and labels since they have to be of different lengths and need different padding methods\n", " # first treat the audio inputs by simply returning torch tensors\n", " input_features = [{\"input_features\": feature[\"input_features\"]} for feature in features]\n", " batch = self.processor.feature_extractor.pad(input_features, return_tensors=\"pt\")\n", "\n", " # get the tokenized label sequences\n", " label_features = [{\"input_ids\": feature[\"labels\"]} for feature in features]\n", " # pad the labels to max length\n", " labels_batch = self.processor.tokenizer.pad(label_features, return_tensors=\"pt\")\n", "\n", " # replace padding with -100 to ignore loss correctly\n", " labels = labels_batch[\"input_ids\"].masked_fill(labels_batch.attention_mask.ne(1), -100)\n", "\n", " # if bos token is appended in previous tokenization step,\n", " # cut bos token here as it's append later anyways\n", " if (labels[:, 0] == self.processor.tokenizer.bos_token_id).all().cpu().item():\n", " labels = labels[:, 1:]\n", "\n", " batch[\"labels\"] = labels\n", "\n", " return batch" ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "id": "AdUZrfeWmUWT", "tags": [] }, "outputs": [], "source": [ "data_collator = DataCollatorSpeechSeq2SeqWithPadding(processor=processor)" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 77, "referenced_widgets": [ "2d2c3e318d7e49c58f9be48578eb7f95", "3479cf07075644bfa1ce58ae13701079", "3e40c25901504064b5778ab9171e1b46", "c367339212864777be021e6e6fcc9e27", "d921481434f343d39bcb2f5a73d70d87", "0a7e5502a9df43b38a72e80ba1ae4689", "5410e3a1585a48b388da33a7e0a01efb", "269eb9da3f4d4c5a8cdb6d8e9fc14c5f", "488be7f2507d4572a38055bd6777edf9", "c6b34169cd42408a8067c7d2f80920cf", "6d1a1d80867b47bab9406d7a5d247745" ] }, "id": "KVuTyjU4mXxV", "outputId": "7bb6b76c-f3db-4b92-83e3-418bc988467f", "tags": [] }, "outputs": [], "source": [ "import evaluate\n", "\n", "metric = evaluate.load(\"wer\")" ] }, { "cell_type": "code", "execution_count": 25, "metadata": { "id": "aZDz74e5mbhj", "tags": [] }, "outputs": [], "source": [ "def compute_metrics(pred):\n", " pred_ids = pred.predictions\n", " label_ids = pred.label_ids\n", "\n", " # replace -100 with the pad_token_id\n", " label_ids[label_ids == -100] = tokenizer.pad_token_id\n", "\n", " # we do not want to group tokens when computing the metrics\n", " pred_str = tokenizer.batch_decode(pred_ids, skip_special_tokens=True)\n", " label_str = tokenizer.batch_decode(label_ids, skip_special_tokens=True)\n", "\n", " wer = 100 * metric.compute(predictions=pred_str, references=label_str)\n", "\n", " return {\"wer\": wer}" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: torch in /opt/conda/lib/python3.10/site-packages (2.0.0)\n", "Requirement already satisfied: filelock in /opt/conda/lib/python3.10/site-packages (from torch) (3.12.0)\n", "Requirement already satisfied: typing-extensions in /opt/conda/lib/python3.10/site-packages (from torch) (4.5.0)\n", "Requirement already satisfied: sympy in /opt/conda/lib/python3.10/site-packages (from torch) (1.11.1)\n", "Requirement already satisfied: networkx in /opt/conda/lib/python3.10/site-packages (from torch) (3.1)\n", "Requirement already satisfied: jinja2 in /opt/conda/lib/python3.10/site-packages (from torch) (3.1.2)\n", "Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/lib/python3.10/site-packages (from jinja2->torch) (2.1.2)\n", "Requirement already satisfied: mpmath>=0.19 in /opt/conda/lib/python3.10/site-packages (from sympy->torch) (1.3.0)\n", "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", "\u001b[0m" ] } ], "source": [ "!pip install torch" ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: pip in /opt/conda/lib/python3.10/site-packages (23.1.2)\n", "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", "\u001b[0m" ] } ], "source": [ "!pip install --upgrade pip" ] }, { "cell_type": "code", "execution_count": 26, "metadata": { "colab": { "base_uri": "https://localhost:8080/", "height": 197, "referenced_widgets": [ "f93294d36a394e5897a43db8e632438a", "6d4bbcb44d424c8eba398e76092ad9ce", "cf6ade6ce7a04ee5ba6d35bda25d0f68", "f986fbd442ce4488bf5af72cb709db12", "db8fec8c57524122ae433027327136f9", "0a6a27cd7226483495fa015ee437a851", "e658ae6a860e44bb8f01e1ed4ec0c683", "5ed59fbe5c9642eba1ba26b1fad7cd3d", "be488d4f9f554cbdaafb2604f399dcfc", "1c3e76ff947d4c469af658d5f57afd32", "5a009aa971424b90a8974556cca8d4bf", "b22f888a1b8d4b0cb63d01946ebd4901", "5883c5fefc7f44a0a9d685cb67a18007", "a60a65f831994926a6e9bcd6ce76a0a5", "9e9c86dcb226473b9b9919766118eb34", "026057b7ab0b4431a4f2674801d67b8f", "09f73e2f1c6c4c68852ae9b64e399a4d", "7c654f9c2eb2429a9a8ce1ec73783311", "e417a506ad3f4c7da844d981c8adc009", "161f3cd04df5435db7f8a3a4d8211fd8", "31c4c8014e914093a262a5725a2491fb", "7c6d1dc23b264dc9a80a195901a46e12", "bb8d9ac612464d7198694d34cb4f434b", "7af36c0e33f94205bd5a64e82c35ccdd", "1ab7137372c3446885a02dedf9781c65", "5e3dddf77c3b4cfc991e2986f0cc316a", "9ae73d9c686846019138c2177453ef0e", "c771327d2eae458b8a005eb67b0aef3d", "c229c029928b4b80a95cf07b5865bf43", "1f739161424742839292cdbafdbab05e", "41ac51b174494c4daa72986b16a4b504", "6f6998d1a60d49018a47e3dcfdf73029", "72b8045ff634405ea7467d4d4a075c17" ] }, "id": "ALNdSAPrmequ", "outputId": "8cf99115-0a69-4f5a-ca15-c206ec85adff", "tags": [] }, "outputs": [], "source": [ "from transformers import WhisperForConditionalGeneration\n", "\n", "model = WhisperForConditionalGeneration.from_pretrained(\"openai/whisper-small\")" ] }, { "cell_type": "code", "execution_count": 27, "metadata": { "id": "7DsMrQmmm06i", "tags": [] }, "outputs": [], "source": [ "model.config.forced_decoder_ids = None\n", "model.config.suppress_tokens = []" ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "id": "RDWWgLwWna6v", "tags": [] }, "outputs": [], "source": [ "from transformers import Seq2SeqTrainingArguments\n", "\n", "training_args = Seq2SeqTrainingArguments(\n", " output_dir=\"mskov/whisper_miso\", # change to a repo name of your choice\n", " per_device_train_batch_size=8,\n", " gradient_accumulation_steps=1, # increase by 2x for every 2x decrease in batch size\n", " learning_rate=1e-5,\n", " warmup_steps=500,\n", " max_steps=4000,\n", " gradient_checkpointing=True,\n", " fp16=False,\n", " evaluation_strategy=\"steps\",\n", " per_device_eval_batch_size=8,\n", " predict_with_generate=True,\n", " generation_max_length=225,\n", " save_steps=1000,\n", " eval_steps=1000,\n", " logging_steps=25,\n", " report_to=[\"tensorboard\"],\n", " load_best_model_at_end=True,\n", " metric_for_best_model=\"wer\",\n", " greater_is_better=False,\n", " push_to_hub=True,\n", ")" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Requirement already satisfied: tensorboardX in /opt/conda/lib/python3.10/site-packages (2.6)\n", "Requirement already satisfied: numpy in /opt/conda/lib/python3.10/site-packages (from tensorboardX) (1.23.5)\n", "Requirement already satisfied: packaging in /opt/conda/lib/python3.10/site-packages (from tensorboardX) (23.1)\n", "Requirement already satisfied: protobuf<4,>=3.8.0 in /opt/conda/lib/python3.10/site-packages (from tensorboardX) (3.20.3)\n", "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", "\u001b[0m" ] } ], "source": [ "!pip install tensorboardX" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Collecting package metadata (current_repodata.json): done\n", "Solving environment: done\n", "\n", "\n", "==> WARNING: A newer version of conda exists. <==\n", " current version: 23.3.1\n", " latest version: 23.5.0\n", "\n", "Please update conda by running\n", "\n", " $ conda update -n base -c conda-forge conda\n", "\n", "Or to minimize the number of packages updated during conda update use\n", "\n", " conda install conda=23.5.0\n", "\n", "\n", "\n", "## Package Plan ##\n", "\n", " environment location: /opt/conda\n", "\n", " added / updated specs:\n", " - git-lfs\n", "\n", "\n", "The following packages will be downloaded:\n", "\n", " package | build\n", " ---------------------------|-----------------\n", " openssl-3.1.1 | hd590300_1 2.5 MB conda-forge\n", " ------------------------------------------------------------\n", " Total: 2.5 MB\n", "\n", "The following packages will be UPDATED:\n", "\n", " openssl 3.1.0-hd590300_3 --> 3.1.1-hd590300_1 \n", "\n", "\n", "\n", "Downloading and Extracting Packages\n", " \n", "Preparing transaction: done\n", "Verifying transaction: done\n", "Executing transaction: done\n" ] } ], "source": [ "!conda install git-lfs --yes" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "tags": [] }, "outputs": [ { "data": { "text/plain": [ "'|===========================================================================|\\n| PyTorch CUDA memory summary, device ID 0 |\\n|---------------------------------------------------------------------------|\\n| CUDA OOMs: 3 | cudaMalloc retries: 3 |\\n|===========================================================================|\\n| Metric | Cur Usage | Peak Usage | Tot Alloc | Tot Freed |\\n|---------------------------------------------------------------------------|\\n| Allocated memory | 49053 KiB | 49053 KiB | 49053 KiB | 0 B |\\n| from large pool | 48276 KiB | 48276 KiB | 48276 KiB | 0 B |\\n| from small pool | 777 KiB | 777 KiB | 777 KiB | 0 B |\\n|---------------------------------------------------------------------------|\\n| Active memory | 49053 KiB | 49053 KiB | 49053 KiB | 0 B |\\n| from large pool | 48276 KiB | 48276 KiB | 48276 KiB | 0 B |\\n| from small pool | 777 KiB | 777 KiB | 777 KiB | 0 B |\\n|---------------------------------------------------------------------------|\\n| Requested memory | 49053 KiB | 49053 KiB | 49053 KiB | 0 B |\\n| from large pool | 48276 KiB | 48276 KiB | 48276 KiB | 0 B |\\n| from small pool | 777 KiB | 777 KiB | 777 KiB | 0 B |\\n|---------------------------------------------------------------------------|\\n| GPU reserved memory | 63488 KiB | 63488 KiB | 63488 KiB | 0 B |\\n| from large pool | 61440 KiB | 61440 KiB | 61440 KiB | 0 B |\\n| from small pool | 2048 KiB | 2048 KiB | 2048 KiB | 0 B |\\n|---------------------------------------------------------------------------|\\n| Non-releasable memory | 14435 KiB | 23675 KiB | 44336 KiB | 29901 KiB |\\n| from large pool | 13164 KiB | 22380 KiB | 43008 KiB | 29844 KiB |\\n| from small pool | 1271 KiB | 1328 KiB | 1328 KiB | 57 KiB |\\n|---------------------------------------------------------------------------|\\n| Allocations | 29 | 29 | 29 | 0 |\\n| from large pool | 12 | 12 | 12 | 0 |\\n| from small pool | 17 | 17 | 17 | 0 |\\n|---------------------------------------------------------------------------|\\n| Active allocs | 29 | 29 | 29 | 0 |\\n| from large pool | 12 | 12 | 12 | 0 |\\n| from small pool | 17 | 17 | 17 | 0 |\\n|---------------------------------------------------------------------------|\\n| GPU reserved segments | 4 | 4 | 4 | 0 |\\n| from large pool | 3 | 3 | 3 | 0 |\\n| from small pool | 1 | 1 | 1 | 0 |\\n|---------------------------------------------------------------------------|\\n| Non-releasable allocs | 4 | 4 | 4 | 0 |\\n| from large pool | 3 | 3 | 3 | 0 |\\n| from small pool | 1 | 1 | 1 | 0 |\\n|---------------------------------------------------------------------------|\\n| Oversize allocations | 0 | 0 | 0 | 0 |\\n|---------------------------------------------------------------------------|\\n| Oversize GPU segments | 0 | 0 | 0 | 0 |\\n|===========================================================================|\\n'" ] }, "execution_count": 38, "metadata": {}, "output_type": "execute_result" } ], "source": [ "torch.cuda.memory_summary(device=None, abbreviated=False)" ] }, { "cell_type": "code", "execution_count": 42, "metadata": { "tags": [] }, "outputs": [], "source": [ "torch.cuda.empty_cache()" ] }, { "cell_type": "code", "execution_count": 44, "metadata": { "colab": { "base_uri": "https://localhost:8080/" }, "id": "zwgKScEVn5BP", "outputId": "fe6b9d5f-8f9a-4965-98dd-f7c455593730", "tags": [] }, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ "Cloning https://huggingface.co/mskov/whisper_miso into local empty directory.\n" ] }, { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "18c5f903e8ad4ea3ba526e6ee943fc2e", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Download file pytorch_model.bin: 0%| | 7.90k/922M [00:00\n", " \n", " \n", " [4000/4000 5:24:20, Epoch 1333/1334]\n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", " \n", "
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" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stderr", "output_type": "stream", "text": [ "Several commits (2) will be pushed upstream.\n", "Several commits (3) will be pushed upstream.\n", "Several commits (4) will be pushed upstream.\n" ] }, { "data": { "text/plain": [ "TrainOutput(global_step=4000, training_loss=0.06265443535902454, metrics={'train_runtime': 19467.4471, 'train_samples_per_second': 1.644, 'train_steps_per_second': 0.205, 'total_flos': 8.46536413298688e+18, 'train_loss': 0.06265443535902454, 'epoch': 1333.33})" ] }, "execution_count": 46, "metadata": {}, "output_type": "execute_result" } ], "source": [ "trainer.train()" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "accelerator": "GPU", "availableInstances": [ { "_defaultOrder": 0, "_isFastLaunch": true, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 4, "name": "ml.t3.medium", "vcpuNum": 2 }, { "_defaultOrder": 1, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 8, "name": "ml.t3.large", "vcpuNum": 2 }, { "_defaultOrder": 2, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 16, "name": "ml.t3.xlarge", "vcpuNum": 4 }, { "_defaultOrder": 3, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 32, "name": "ml.t3.2xlarge", "vcpuNum": 8 }, { "_defaultOrder": 4, "_isFastLaunch": true, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 8, "name": "ml.m5.large", "vcpuNum": 2 }, { "_defaultOrder": 5, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 16, "name": "ml.m5.xlarge", "vcpuNum": 4 }, { "_defaultOrder": 6, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 32, "name": "ml.m5.2xlarge", "vcpuNum": 8 }, { "_defaultOrder": 7, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 64, "name": "ml.m5.4xlarge", "vcpuNum": 16 }, { "_defaultOrder": 8, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 128, "name": "ml.m5.8xlarge", "vcpuNum": 32 }, { "_defaultOrder": 9, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 192, "name": "ml.m5.12xlarge", "vcpuNum": 48 }, { "_defaultOrder": 10, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 256, "name": "ml.m5.16xlarge", "vcpuNum": 64 }, { "_defaultOrder": 11, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 384, "name": "ml.m5.24xlarge", "vcpuNum": 96 }, { "_defaultOrder": 12, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 8, "name": "ml.m5d.large", "vcpuNum": 2 }, { "_defaultOrder": 13, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 16, "name": "ml.m5d.xlarge", "vcpuNum": 4 }, { "_defaultOrder": 14, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 32, "name": "ml.m5d.2xlarge", "vcpuNum": 8 }, { "_defaultOrder": 15, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 64, "name": "ml.m5d.4xlarge", "vcpuNum": 16 }, { "_defaultOrder": 16, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 128, "name": "ml.m5d.8xlarge", "vcpuNum": 32 }, { "_defaultOrder": 17, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 192, "name": "ml.m5d.12xlarge", "vcpuNum": 48 }, { "_defaultOrder": 18, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 256, "name": "ml.m5d.16xlarge", "vcpuNum": 64 }, { "_defaultOrder": 19, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 384, "name": "ml.m5d.24xlarge", "vcpuNum": 96 }, { "_defaultOrder": 20, "_isFastLaunch": false, "category": "General purpose", "gpuNum": 0, "hideHardwareSpecs": true, "memoryGiB": 0, "name": "ml.geospatial.interactive", "supportedImageNames": [ "sagemaker-geospatial-v1-0" ], "vcpuNum": 0 }, { "_defaultOrder": 21, "_isFastLaunch": true, "category": "Compute optimized", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 4, "name": "ml.c5.large", "vcpuNum": 2 }, { "_defaultOrder": 22, "_isFastLaunch": false, "category": "Compute optimized", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 8, "name": "ml.c5.xlarge", "vcpuNum": 4 }, { "_defaultOrder": 23, "_isFastLaunch": false, "category": "Compute optimized", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 16, "name": "ml.c5.2xlarge", "vcpuNum": 8 }, { "_defaultOrder": 24, "_isFastLaunch": false, "category": "Compute optimized", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 32, "name": "ml.c5.4xlarge", "vcpuNum": 16 }, { "_defaultOrder": 25, "_isFastLaunch": false, "category": "Compute optimized", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 72, "name": "ml.c5.9xlarge", "vcpuNum": 36 }, { "_defaultOrder": 26, "_isFastLaunch": false, "category": "Compute optimized", "gpuNum": 0, "hideHardwareSpecs": false, "memoryGiB": 96, "name": "ml.c5.12xlarge", "vcpuNum": 48 }, { "_defaultOrder": 27, "_isFastLaunch": false, "category": "Compute 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