xlm_roberta_base_commonlanguage_language_detector.ipynb

{"cells":[{"cell_type":"markdown","metadata":{},"source":["<a href=\"https://colab.research.google.com/github/IvanLauLinTiong/language-detector/blob/main/xlm_roberta_base_commonlanguage_language_detector.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"]},{"cell_type":"markdown","metadata":{"id":"D0V0wHWbPF9s"},"source":["# Installation and Import Libraries"]},{"cell_type":"code","execution_count":1,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":21408,"status":"ok","timestamp":1637737698547,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"FkC_Cc7uPJtO","outputId":"9a4fec9d-63bc-495a-aab2-1f005c7209fe","scrolled":true},"outputs":[{"name":"stdout","output_type":"stream","text":["Collecting datasets\n","  Downloading datasets-1.15.1-py3-none-any.whl (290 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(21.3)\n","Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->bleach->nbconvert->notebook>=4.4.1->widgetsnbextension~=3.5.0->ipywidgets) (3.0.6)\n","Requirement already satisfied: sklearn in /usr/local/lib/python3.7/dist-packages (0.0)\n","Requirement already satisfied: scikit-learn in /usr/local/lib/python3.7/dist-packages (from sklearn) (1.0.1)\n","Requirement already satisfied: numpy>=1.14.6 in /usr/local/lib/python3.7/dist-packages (from scikit-learn->sklearn) (1.19.5)\n","Requirement already satisfied: scipy>=1.1.0 in /usr/local/lib/python3.7/dist-packages (from scikit-learn->sklearn) (1.4.1)\n","Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.7/dist-packages (from scikit-learn->sklearn) (1.1.0)\n","Requirement already satisfied: threadpoolctl>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from scikit-learn->sklearn) (3.0.0)\n"]}],"source":["!pip install datasets transformers[sentencepiece]\n","!pip install ipywidgets\n","!pip install sklearn\n","# !jupyter nbextension enable --py widgetsnbextension\n","# !jupyter labextension install @jupyter-widgets/jupyterlab-manager"]},{"cell_type":"code","execution_count":2,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":4830,"status":"ok","timestamp":1637737703371,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"DQ9xY0KK59cC","outputId":"abb10b64-43b8-4aa6-8eac-39482e2a1bf8","scrolled":true},"outputs":[{"name":"stdout","output_type":"stream","text":["Reading package lists... Done\n","Building dependency tree       \n","Reading state information... Done\n","The following NEW packages will be installed:\n","  git-lfs\n","0 upgraded, 1 newly installed, 0 to remove and 37 not upgraded.\n","Need to get 2,129 kB of archives.\n","After this operation, 7,662 kB of additional disk space will be used.\n","Get:1 http://archive.ubuntu.com/ubuntu bionic/universe amd64 git-lfs amd64 2.3.4-1 [2,129 kB]\n","Fetched 2,129 kB in 0s (13.9 MB/s)\n","debconf: unable to initialize frontend: Dialog\n","debconf: (No usable dialog-like program is installed, so the dialog based frontend cannot be used. at /usr/share/perl5/Debconf/FrontEnd/Dialog.pm line 76, <> line 1.)\n","debconf: falling back to frontend: Readline\n","debconf: unable to initialize frontend: Readline\n","debconf: (This frontend requires a controlling tty.)\n","debconf: falling back to frontend: Teletype\n","dpkg-preconfigure: unable to re-open stdin: \n","Selecting previously unselected package git-lfs.\n","(Reading database ... 155222 files and directories currently installed.)\n","Preparing to unpack .../git-lfs_2.3.4-1_amd64.deb ...\n","Unpacking git-lfs (2.3.4-1) ...\n","Setting up git-lfs (2.3.4-1) ...\n","Processing triggers for man-db (2.8.3-2ubuntu0.1) ...\n"]}],"source":["# install git lfs \n","!sudo apt-get install git-lfs\n","# !git lfs install"]},{"cell_type":"code","execution_count":3,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":238,"referenced_widgets":["972739ff643f47da8a7c273abf385b8f","64816c384a814894bcb7eb800cb8b57c","d5c2a8163c954c1baa2b2ccb265b0bf6","6b4b23f52bcc46639dbde880db62370b","f7a4f394002d46c483f65f1d221aa7e0","4a1f25692e45486ca3362ce0c013f38b","fb64480d9b0344dfbce07c2d22e94ca5","9b3b6599544842259464a50087a53970","78b6bb417c62493fb4e21c5a742fb119","0ba96d5e612f4234a56181dfac196a16","fcf10cfe5ebe4a41b2ba54316e1c379c","f9a374323dcb45f08634a3b7cffaf1ff","5d86bdccb03341f6a6c50788a81affc8","8ec9a2feffee445ea059b1b265a68936","d1ce5970304f43b29205bbd86e3c4699","994ac3f6fdfd42f68dffadac361776fc"]},"executionInfo":{"elapsed":6684,"status":"ok","timestamp":1637737751992,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"wPMTH4Uiadnu","outputId":"c8143c99-edb9-44e5-c007-53ed3fb7f067"},"outputs":[{"name":"stdout","output_type":"stream","text":["Login successful\n","Your token has been saved to /root/.huggingface/token\n","\u001b[1m\u001b[31mAuthenticated through git-crendential store but this isn't the helper defined on your machine.\n","You will have to re-authenticate when pushing to the Hugging Face Hub. Run the following command in your terminal to set it as the default\n","\n","git config --global credential.helper store\u001b[0m\n"]}],"source":["# Login your HF account and retrueve HF token\n","# Note: you must have a HF account created before running this cell \n","# and go to next step\n","from huggingface_hub import notebook_login\n","\n","notebook_login()\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":35},"executionInfo":{"elapsed":561,"status":"ok","timestamp":1637737774001,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"4G-rtQMF7TS3","outputId":"0b8d35b1-c591-4d38-afff-4b3d7788d6ce"},"outputs":[],"source":["from huggingface_hub import HfFolder\n","HF_TOKEN = HfFolder.get_token() "]},{"cell_type":"markdown","metadata":{"id":"2XS27QfzP1Qt"},"source":["# Preprocessing"]},{"cell_type":"code","execution_count":5,"metadata":{"executionInfo":{"elapsed":3592,"status":"ok","timestamp":1637737779652,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"q23NgfkgPWXm"},"outputs":[],"source":["from datasets import load_dataset\n","from transformers import AutoTokenizer\n","\n","# checkpoint used in preprocessing and modelling\n","checkpoint = 'xlm-roberta-base'\n","\n","# dataset used\n","dataset_name = 'common_language' #'amazon_reviews_multi'\n","\n","# cache dirs\n","# CACHE_DATASETS = './cache/datasets/'\n","# CACHE_PRETRAINED = './cache/pretrained/'\n"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"referenced_widgets":["8c067b1a25eb420297a372a831149613","37d7883b85e7417492fdbccfdc46212d","b7e4837570d34ffebca131c2a461b2c8","9d44844e09444e3e8fe4c08327a57eec","4e5207ce671a4d7081a171c3ab825482","49fd3a1e54d84644a183f6bb3d0adfa3","05f14f22fa9a4f1e9b25a4f5487d35a8","a65ed0793a214c398f107bb65eeaba37","b780e6e17add446ab5194ab68307adbe","f81f1f9addd64883be34d7f11ae95f1a","230c6959965d443d81744b91e94d55e6","fc1789cad57641d98d68268160463096","b96ec846bb744faa8e35b7192c979997","4d780b43b9fd4c9bb4eafb060917dd2e","bc3db8821aed42618f76401e5a2f4d4d","4f18ffad576f4e73840c6d924247ff53","8925cb440a6c4dac98ce944420cde933","ed832e4ea6e94d71aa48be1e828883ac","4937596dba624a2882f7a91ebd424885","c024759087e242d288d3464f5fe0d757","5cc5eed6f00e401b9404e693da470778","550ee2ce1f4a4ea4b2aa4f15523e341d","f699e4c9bd344da7bd77ee1946d86e4b","3f64e80444704bf7a27720b0ba897c51","ff1f27c4b61f42678e0fb4cf9348dc87","4374be2fc4fa4235adcb5cf6bad23ecf","73202845a8be4f60b33947922c48c93b","9316f6430f914235993fe54475430cdc","622286cd266a45b5babc59eb28b5116a","9567d11e3bbb42e58d519623c5b4d50d","5ecad404a85b4917a1c3a2f4ff57db98","a16c3e413e544c258c4f59df9cadb834","417f7075ed48489a9e6b058123b2ff1f","cfa2a81f21854e8c8a9a66f9aba3f09c","93d73b42f3504f08a250096d05745bb2","467ed70b5cad40f9a450afb7a62006e2","9c146b3918574d90a8f1a6f2eff00ac3","5fcfddf413a044a3ad50eacbf8acdd2f","2f7159c5678e4e3cb7799ed4a8316427","2f11f96b92c6490c893fa6bea4b92275","9c648074a7be48a29cd9aedbbf9a821d","6ca897464b5941f7a685d2f4e27364ec","4fe3704cf280439fba2dbbcdc90053be","08e3361a136b4292a20d69b44d3fcfc1","02ad8ede447148fd994841545b3385f5","c47bdc84165a4ee2bbe055f7c315a668","4b9b8b7f131b4c0c8bb732dff8a08be0","3b913cc5dcc14db88a03095658e0de93","5d7242cee1524ca5aed0071e2460fd59","234fd904efa64245bbad68511e9d8704","db5dc6f20b4342369186f99c1505ea2b","a9fd1b4aee0f45c7acc36db4fa848536","2d7f56a4ee81401a826fccc0c5075b70","be14bd2cd8664dedb30a61b7d34bfdce","0bf2337d720443d5b4437e8713b37f82","84436c2d11f54f38bba06c20835f881a","03f595da45114256b1612ee4459b5089","84747182e13242d6bdf58d231e2da09e","aff31574964249e989c2359a95905147","df14e975017341569d8c92553eaad888","e54b4bfdc4de4f72b4ba2fbd7d6bce5b","986448150dd045bfae4d1a61c84c8b7f","64ce0ae9d4544df188ee60caa16add8f","e84cc0e684fb4f0082a5a5ba2e795a78","d318a2e028a44f29a831f656dbdbbe2b","15b80ecabd154db4aed6391582f81d7e","daa6e39b37b5422fb86b600ded955d1f","12d841b5c30a4d99a024dc6e0f6efe75","f1b07b00009e4e62956df278e75958e3","b2546fb144bf482681ff69d59dda5687","038194ebca9e468e9ff467912db307cf","5f09449c6c854fc98c4877d764c12245","e083e4cc94be432b95b8304a0e2db626","d7fcebe985634501922ee8ce48ba6916","5bc8b3a16a3d4a978c3fdc05233237f2","27cae86cf1d140b5b3a2bc9ec9864335","5596349b91c34f918782d750445c5ef8","3c2f4060a18445c081a66b6d04967897","263bb60582a7463f9cd6c999f85c9d27","9596e7cb0236461dacc05b802f213468","e1df8349babd418e92adde5e5c79adfc","9f565f3cd85e47a8ada6c3445e2859e3","04028d23a59f4db8bb13d24a90c01da7","8ac90aac89144e5cb4f829930cf1760f","888c0815b18a440388b0751294957435","507ca7ef417649deb67135a065695983","36c6f4c703f247fd931e51fa1af258ce","5fae564219824f95bc0291ef37bb2b76","6d71df9ac17d40e1a66c3bd86d536f3c","ea6eeb699b384fadb75847a1b409e642","50a5b74e8c6a4631a1c82d8b3ea24753","aefdbf5a32884912b1a3d7180ad285f4","141ba86526fb44388988656fa1ecf76f","66618430b6f54339bd94b7b41239e563","7ee98306fa8c4551b4686deca7891bb8","db0550e4526745078813d7dc80b6c594","f0f83be9a60441f18a7c2fe5ba46a61c","80d2cdc8657e4a90b8dd473f3b561eb9","665f97127d3049ae9c21175c3add74b6","f490727227ae4663abe1fbc79138209a","87d0f789a30e4baca167edd45c60e9e4","62486217af3445ed991494879b67b53e","1c6bae04f53b4233bba2602befe13f69","7ae406f6ebb3492da4ad3be1b2475a9c","4d4055e231ba43e8a7cc4aaad8d20f83","c4a43d33402c4ec38c4204ffab98415c","cb3985ea025843b8a6b986aa403c0284","2ffe72e814264c81bb61eb7775e54eab","0dff70a2763a48aa8300bc1f9cb80c7a","03211d9a53eb43f69d8ec9ae1402f582","0a0d66958d594b5eb3c0ab160320631f","236f0186feb84cb6ab16ed73612e832b","82ed078c50ef45e8ab9a2861bc48586b","949b61c47a1c4589aa2d71e8fd3e4108","78377481789b4eaab20efb4e305f97b2","d896accef5034358a37a1e9300472f99","6dfe2c83840c47ae90f8b0058aabc06e","a1f90d8dfa1947198425427c28837ff2","111d9b8310f64e72a884801914b44815","de80db8b5b5d4bf48aa01fb7713600d3","c8ed193df85244aa82a991452a7d43fa","52c1875e4d504b1baff3e64b62bacae7","ffe1d9cb52c742cb81247caf04822746","5e6f6b846da44c25831d8fcf9ce78814","2a17a357a1e941a2a1e9bfc23ab040c7","9f43baf5a9554abeb50070b180991967","d0393751bc3c4cd6925b045ec685232f","38f24ef899254f6494b60a7069f84e87","3b8a579fe8634a388a4edf0be40ac1b2","ad5bfd7127e0412fbbd59024f16fca83","bad85cf58c474610bf943c2b07386bcb","4df81ab8133d4b21bd9b7b98b1187de4","ff2d7800bc724cb1b7e188e13cff9361","491d19218054486fbc628c18a336d986","48f7bc8895bb49018cf02ed5b01de66b","687aa99b076a45a9a2ec3bd3c21fe55c","326b708658bd4e2fa8e3afca48b9ceb4","41b1a6c0c6c6481499c0b4ca7b7d7a17","3d799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Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"PU4hwS4nP8qy","outputId":"690354a4-eb00-48c0-d79d-2d3fa5bc2a6a"},"outputs":[{"name":"stdout","output_type":"stream","text":["Downloading and preparing dataset common_language/full (download: 3.50 GiB, generated: 10.35 MiB, post-processed: Unknown size, total: 3.51 GiB) to C:\\Users\\Ivan\\.cache\\huggingface\\datasets\\common_language\\full\\0.1.0\\58dfd47953a9a67e82ae6d18c796f4d4f7f9025fa46730bbfcdfeaa5e6d12bf1...\n"]},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"352e1398769140ccb9eadec57f020b67","version_major":2,"version_minor":0},"text/plain":["Downloading:   0%|          | 0.00/3.76G [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"","version_major":2,"version_minor":0},"text/plain":["0 examples [00:00, ? examples/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"","version_major":2,"version_minor":0},"text/plain":["0 examples [00:00, ? examples/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"","version_major":2,"version_minor":0},"text/plain":["0 examples [00:00, ? examples/s]"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["Dataset common_language downloaded and prepared to C:\\Users\\Ivan\\.cache\\huggingface\\datasets\\common_language\\full\\0.1.0\\58dfd47953a9a67e82ae6d18c796f4d4f7f9025fa46730bbfcdfeaa5e6d12bf1. Subsequent calls will reuse this data.\n"]},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"bdc9c5778c264c278685617468f30ae0","version_major":2,"version_minor":0},"text/plain":["  0%|          | 0/3 [00:00<?, ?it/s]"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["DatasetDict({\n","    train: Dataset({\n","        features: ['client_id', 'path', 'audio', 'sentence', 'age', 'gender', 'language'],\n","        num_rows: 22194\n","    })\n","    validation: Dataset({\n","        features: ['client_id', 'path', 'audio', 'sentence', 'age', 'gender', 'language'],\n","        num_rows: 5888\n","    })\n","    test: Dataset({\n","        features: ['client_id', 'path', 'audio', 'sentence', 'age', 'gender', 'language'],\n","        num_rows: 5963\n","    })\n","})\n"]}],"source":["# load dataset\n","# train_dataset, test_dataset = load_dataset(dataset_name, \n","# #                                            \"all_languages\", \n","#                                            split=['train', 'test'], \n","# #                                            cache_dir=CACHE_DATASETS\n","# #                                            download_mode=\"force_redownload\"\n","#                                           )\n","# print(train_dataset)\n","# print(test_dataset)\n","\n","\n","dataset = load_dataset(dataset_name)\n","print(dataset)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":308,"status":"ok","timestamp":1637690726795,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"QvV4TaYc-SMw","outputId":"c6cb14bd-6735-44f8-8abe-bcad2458e168"},"outputs":[{"name":"stdout","output_type":"stream","text":["Dataset({\n","    features: ['client_id', 'path', 'audio', 'sentence', 'age', 'gender', 'language'],\n","    num_rows: 22194\n","})\n","Dataset({\n","    features: ['client_id', 'path', 'audio', 'sentence', 'age', 'gender', 'language'],\n","    num_rows: 5963\n","})\n"]}],"source":["train_dataset = dataset['train']\n","test_dataset = dataset['test']\n","print(train_dataset)\n","print(test_dataset)"]},{"cell_type":"code","execution_count":null,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":1000,"referenced_widgets":["8ce5e47b6bd2496ca1e514bda0854a44","75a5023baab741619b3009380f31ff2f","728c63bdd960411cad7bace4177fa19c","aeea0c2002b64bce900dcf6cf7c0fc10","fbf270767fd4431caaff93ac73798238","277de21eea8d44e6a24fa4bdde573491","15034632e972452d9f399addc373ea4a","3216b06dfcb34e138c60440053081b51","0c573c2f10314fb7bc4145366a1557bd","3c79daf06eb1441db841ba07cf3ff346","0274029bdbe349909ca44859edeec0c5","23e2a9fc2c974ee69d744246f154c7b5","5ec1cce9fcd6441cba62a8c8de0e4127","abb2ff89aea549f99c0356ddc6a6e999","0980d582e6ea4ef098811edd5ab73a8c","11d0b9d7c6194864b95d39e673247da8","35716b43cb1f4882aabbfa2482547e9a","8d3bec8800f04b33b533df096fe5662d","3d6cfdcec3d04d45866cc795460311e6","0eceab111b9c4d2688d7367437a4ef74","8d26c0f014424f049b012d557f8f9bb7","36547cc1066b4ba5b6734731603ab743","ce91f0d7f54c4849aeb6b4ba9e3ba471","46270495ffc14f44855b6f7ffdb8b822"]},"executionInfo":{"elapsed":303509,"status":"ok","timestamp":1637691068695,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"NrJblbZwQCfk","outputId":"6f58c76b-d368-4085-85b4-b153e2eedd18"},"outputs":[{"name":"stderr","output_type":"stream","text":["Loading cached shuffled indices for dataset at C:\\Users\\Ivan\\.cache\\huggingface\\datasets\\common_language\\full\\0.1.0\\58dfd47953a9a67e82ae6d18c796f4d4f7f9025fa46730bbfcdfeaa5e6d12bf1\\cache-99b286d0c1d97efc.arrow\n"]},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"ce91f0d7f54c4849aeb6b4ba9e3ba471","version_major":2,"version_minor":0},"text/plain":["  0%|          | 0/23 [00:00<?, ?ba/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"46270495ffc14f44855b6f7ffdb8b822","version_major":2,"version_minor":0},"text/plain":["  0%|          | 0/6 [00:00<?, ?ba/s]"]},"metadata":{},"output_type":"display_data"},{"name":"stdout","output_type":"stream","text":["Dataset({\n","    features: ['attention_mask', 'input_ids', 'labels'],\n","    num_rows: 22194\n","})\n","Dataset({\n","    features: ['attention_mask', 'input_ids', 'labels'],\n","    num_rows: 5963\n","})\n"]}],"source":["max_input_length = 514\n","\n","# shuffle dataset\n","train_dataset = train_dataset.shuffle()\n","test_dataset = test_dataset.shuffle()\n","\n","# tokenizer\n","tokenizer = AutoTokenizer.from_pretrained(checkpoint,\n","#                                           cache_dir=CACHE_PRETRAINED\n","                                         )\n","\n","# tokenizer helper function\n","def tokenize(batch):\n","#     return tokenizer(batch['review_body'], truncation=True, max_length=max_input_length)\n","    return tokenizer(batch['sentence'], truncation=True, max_length=max_input_length)\n","\n","# collator\n","from transformers import DataCollatorWithPadding\n","data_collator = DataCollatorWithPadding(tokenizer=tokenizer)\n","\n","# tokenize dataset\n","train_dataset = train_dataset.map(tokenize, batched=True)\n","test_dataset = test_dataset.map(tokenize, batched=True)\n","\n","# set format for pytorch\n","# train_dataset = train_dataset.remove_columns(['review_body','review_id', 'product_id', 'reviewer_id', 'stars', 'review_title', 'product_category'])\n","# train_dataset =  train_dataset.rename_column(\"language\", \"labels\")\n","# train_dataset.set_format('torch', columns=['input_ids', 'attention_mask', 'labels'])\n","# test_dataset = test_dataset.remove_columns(['review_body','review_id', 'product_id', 'reviewer_id', 'stars', 'review_title', 'product_category'])\n","# test_dataset =  test_dataset.rename_column(\"language\", \"labels\")\n","# test_dataset.set_format('torch', columns=['input_ids', 'attention_mask', 'labels'])\n","\n","\n","train_dataset = train_dataset.remove_columns(['client_id','path', 'sentence', 'age', 'gender', 'audio'])\n","train_dataset =  train_dataset.rename_column(\"language\", \"labels\")\n","train_dataset.set_format('torch', columns=['input_ids', 'attention_mask', 'labels'])\n","test_dataset = test_dataset.remove_columns(['client_id','path', 'sentence', 'age', 'gender', 'audio'])\n","test_dataset =  test_dataset.rename_column(\"language\", \"labels\")\n","test_dataset.set_format('torch', columns=['input_ids', 'attention_mask', 'labels'])\n","\n","print(train_dataset)\n","print(test_dataset)"]},{"cell_type":"code","execution_count":6,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":113,"referenced_widgets":["bb3b2e82257f468fa139aff1e5fafa30","03425d16ff394e968cc1bd0e9b2ce59d","ef0127b3368a4b15a9a10a06c47ecfa3","f0988724b01e4161b8dc8f75fad15085","597ed1ebbd40473da0dccc03d6cfffc3","707c95abcf5a4f7eb434aee09e7286a1","9f357be59fe2435087d811c86fe09e18","c97278b40f104295afc80866096a9af5","838ae6ed65b74a8dae8e5498111e8c6a","85d59d1d44214d47a79d25c628530423","dc88d8dc66d446eaa075c778c1e5f825","39af72012b1f4b71ab9e3fd20df51b16","cac295b343874afb86cb7717444024a3","56685d7f7b974c51a9cc7e9df5682e56","e2f6fe6c2a3d4208802de3688d10c8ed","589ab93e92e5450e9646f42989e2e8da","5fe7dde7de2e4353b7237da8408231f2","70c71ac39b8144ec9592f9e7de4f038e","c32015a781bd4e7cb50cf2e475e10e31","ac39f1b9b9f0462f9d9c490bf09f4cee","18199f950bb54545a16e3cc505f09b54","267e8f1053da48e68c5a94c437053c76","13beeb4d79bc4302938399146ed2d879","9c5a8a7a4ce94cd7ad8b58e5f0284057","ea9ad1c1dfcb42aa889de6565f153c99","d2848da88ecb44689d059ad96025807c","02d5ccaf326e4f8e9336a0698f789447","aa45a8e4f8ac48f3942da82e3266017f","e046e66cb79d40e7b2b545230b973da4","caf29babc89d4c3bbb9fb50a7b944bdf","a15a302ca8934366b824733938055ce2","77962d9591044364914ad736a24f6baa","a733cd52c1d94032aa2ba45a1cd985d2"]},"executionInfo":{"elapsed":7038,"status":"ok","timestamp":1637737795822,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"h67bjs-Fs_pK","outputId":"cb9e29e6-d914-4765-fc45-ed1882999abe"},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"bb3b2e82257f468fa139aff1e5fafa30","version_major":2,"version_minor":0},"text/plain":["Downloading:   0%|          | 0.00/512 [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"39af72012b1f4b71ab9e3fd20df51b16","version_major":2,"version_minor":0},"text/plain":["Downloading:   0%|          | 0.00/4.83M [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"13beeb4d79bc4302938399146ed2d879","version_major":2,"version_minor":0},"text/plain":["Downloading:   0%|          | 0.00/8.68M [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"}],"source":["# tokenizer\n","tokenizer = AutoTokenizer.from_pretrained(checkpoint,\n","#                                           cache_dir=CACHE_PRETRAINED\n","                                         )\n","\n","# tokenizer helper function\n","def tokenize(batch):\n","#     return tokenizer(batch['review_body'], truncation=True, max_length=max_input_length)\n","    return tokenizer(batch['sentence'], truncation=True, max_length=max_input_length)\n","\n","# collator\n","from transformers import DataCollatorWithPadding\n","data_collator = DataCollatorWithPadding(tokenizer=tokenizer)"]},{"cell_type":"code","execution_count":7,"metadata":{"executionInfo":{"elapsed":13,"status":"ok","timestamp":1637737795824,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"6b5hzMCnQD57"},"outputs":[],"source":["# save datasets to datasets folder\n","\n","training_input_path = f'dataset/train'\n","train_dataset.save_to_disk(training_input_path)\n","\n","test_input_path = f'dataset/test'\n","test_dataset.save_to_disk(test_input_path)"]},{"cell_type":"markdown","metadata":{"id":"qYeNszJ3s3yL"},"source":["# Training"]},{"cell_type":"code","execution_count":8,"metadata":{"executionInfo":{"elapsed":12,"status":"ok","timestamp":1637737795825,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"mpPwzP2ZnaWa"},"outputs":[],"source":["\n","import numpy as np\n","from datasets import load_from_disk, load_metric\n","from transformers import AutoModelForSequenceClassification\n","from transformers import  Trainer, TrainingArguments\n","from transformers.trainer_utils import get_last_checkpoint"]},{"cell_type":"code","execution_count":9,"metadata":{"executionInfo":{"elapsed":592,"status":"ok","timestamp":1637737796406,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"PRrNYkN9QECJ"},"outputs":[],"source":["# hub model id\n","hub_model_id = f'language-detection-fine-tuned-on-{checkpoint}'"]},{"cell_type":"code","execution_count":11,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":84,"referenced_widgets":["c1517fa0825044d3bbe22e1fe2a33279","84b0c746781a4712ac518bc5cbdff432","64c473b47343459baa5d1fa2d89d7c83","dead292ceea24a9e8526cd17cd003636","78b48c70ec1544ff813df3b82cc0655b","0690bae783244bcea6adecf5ab01fe99","a70ad78132034018b65fe38f17b79e28","52bce36a55294a7bbf2f5cf60f8d6d30","cb4538f63af74cc7b1221071d52907ee","d73e1a85691f42b3948e9160800dcd00","4c5ecb6ddcf14992b9fd51d7a5f76328"]},"executionInfo":{"elapsed":1145,"status":"ok","timestamp":1637737802523,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"XnFBew2lQEKF","outputId":"2f98d313-b31b-4c92-a64c-0d7fd033d7b2"},"outputs":[{"name":"stdout","output_type":"stream","text":["2021-11-24 07:10:01,488 - __main__ - INFO -  loaded train_dataset length is: 22194\n","2021-11-24 07:10:01,491 - __main__ - INFO -  loaded test_dataset length is: 5963\n"]},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"c1517fa0825044d3bbe22e1fe2a33279","version_major":2,"version_minor":0},"text/plain":["Downloading:   0%|          | 0.00/1.42k [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"}],"source":[" # load datasets\n","train_dataset = load_from_disk(training_input_path)\n","test_dataset = load_from_disk(test_input_path)\n","\n","print(f\"loaded train_dataset length is: {len(train_dataset)}\")\n","print(f\"loaded test_dataset length is: {len(test_dataset)}\")\n","\n","# define metrics and metrics function\n","metric = load_metric(\"accuracy\")\n","\n","def compute_metrics(eval_pred):\n","    predictions, labels = eval_pred\n","    predictions = np.argmax(predictions, axis=1)\n","    return metric.compute(predictions=predictions, references=labels)\n","\n","# Prepare model labels - useful in inference API\n","labels = train_dataset.features[\"labels\"].names\n","num_labels = len(labels)\n","label2id, id2label = dict(), dict()\n","for i, label in enumerate(labels):\n","    label2id[label] = str(i)\n","    id2label[str(i)] = label"]},{"cell_type":"code","execution_count":11,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":307,"status":"ok","timestamp":1637736439419,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"PZBNNPIGDA-o","outputId":"5b0d76f6-1c48-4983-b6d9-42e9590c8a63"},"outputs":[{"data":{"text/plain":["{'attention_mask': Sequence(feature=Value(dtype='int8', id=None), length=-1, id=None),\n"," 'input_ids': Sequence(feature=Value(dtype='int32', id=None), length=-1, id=None),\n"," 'labels': ClassLabel(num_classes=45, names=['Arabic', 'Basque', 'Breton', 'Catalan', 'Chinese_China', 'Chinese_Hongkong', 'Chinese_Taiwan', 'Chuvash', 'Czech', 'Dhivehi', 'Dutch', 'English', 'Esperanto', 'Estonian', 'French', 'Frisian', 'Georgian', 'German', 'Greek', 'Hakha_Chin', 'Indonesian', 'Interlingua', 'Italian', 'Japanese', 'Kabyle', 'Kinyarwanda', 'Kyrgyz', 'Latvian', 'Maltese', 'Mangolian', 'Persian', 'Polish', 'Portuguese', 'Romanian', 'Romansh_Sursilvan', 'Russian', 'Sakha', 'Slovenian', 'Spanish', 'Swedish', 'Tamil', 'Tatar', 'Turkish', 'Ukranian', 'Welsh'], names_file=None, id=None)}"]},"execution_count":11,"metadata":{},"output_type":"execute_result"}],"source":["train_dataset.features"]},{"cell_type":"code","execution_count":12,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":156,"referenced_widgets":["c594050d82c04cc1b15eb0efa5930e54","2fc6052165ce4148ac1ecb25a7a96ac1","a8f225090989477986c8b541630f1ad4","1d62be2c2fd4420e8648cc6870559751","ab9f81762520422784caf77765214fab","b372af77cf134f31abf8008fcf7e42a8","4dbabbaf0a4147adad4178fb8318aa8b","9254e04868d64256bae16d52d3631b1f","c1fc76427bcb425987051f5ba7f57b64","5911364f16de4f82ac4a09b2addbcd80","30d27216e64c473787ee4ab0af5a3ebd"]},"executionInfo":{"elapsed":39852,"status":"ok","timestamp":1637737846787,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"oRub-IfXQEQB","outputId":"254a0766-96de-44f3-f0b4-2bbcd524693d"},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"c594050d82c04cc1b15eb0efa5930e54","version_major":2,"version_minor":0},"text/plain":["Downloading:   0%|          | 0.00/1.04G [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["Some weights of the model checkpoint at xlm-roberta-base were not used when initializing XLMRobertaForSequenceClassification: ['lm_head.dense.weight', 'lm_head.decoder.weight', 'roberta.pooler.dense.weight', 'lm_head.layer_norm.weight', 'lm_head.bias', 'lm_head.layer_norm.bias', 'roberta.pooler.dense.bias', 'lm_head.dense.bias']\n","- This IS expected if you are initializing XLMRobertaForSequenceClassification from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n","- This IS NOT expected if you are initializing XLMRobertaForSequenceClassification from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n","Some weights of XLMRobertaForSequenceClassification were not initialized from the model checkpoint at xlm-roberta-base and are newly initialized: ['classifier.out_proj.bias', 'classifier.dense.weight', 'classifier.out_proj.weight', 'classifier.dense.bias']\n","You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\n"]}],"source":["# download model from model hub\n","model = AutoModelForSequenceClassification.from_pretrained(\n","    checkpoint, \n","    num_labels=num_labels, \n","    label2id=label2id, \n","    id2label=id2label,\n","#     cache_dir=CACHE_PRETRAINED\n",")\n","# tokenizer = AutoTokenizer.from_pretrained(checkpoint)"]},{"cell_type":"code","execution_count":13,"metadata":{"executionInfo":{"elapsed":6,"status":"ok","timestamp":1637737848077,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"kNGC2R7vQEVp"},"outputs":[],"source":["# define training args\n","training_args = TrainingArguments(\n","        hub_model_id,\n","        evaluation_strategy='epoch',\n","        save_strategy='epoch',\n","\n","        num_train_epochs=1,\n","        per_device_train_batch_size=1,\n","        per_device_eval_batch_size=1,\n","        warmup_steps=500,\n","        fp16=True,\n","        learning_rate=3e-5,\n","        load_best_model_at_end=True,\n","        metric_for_best_model=\"accuracy\",\n","        # push to hub parameters\n","        push_to_hub=True,\n","        hub_strategy='every_save',\n","        hub_model_id=hub_model_id,\n","        hub_token=HF_TOKEN,\n","    )\n"]},{"cell_type":"code","execution_count":14,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":650},"executionInfo":{"elapsed":7437966,"status":"ok","timestamp":1637745286039,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"3yVYX-WMQEX8","outputId":"ecf3a394-30d8-434d-fe78-3dadedf0235c"},"outputs":[{"name":"stderr","output_type":"stream","text":["Cloning https://huggingface.co/ivanlau/language-detection-fine-tuned-on-xlm-roberta-base into local empty directory.\n"]},{"name":"stdout","output_type":"stream","text":["2021-11-24 07:11:02,095 - huggingface_hub.repository - WARNING - Cloning https://huggingface.co/ivanlau/language-detection-fine-tuned-on-xlm-roberta-base into local empty directory.\n"]},{"name":"stderr","output_type":"stream","text":["Using amp fp16 backend\n","***** Running training *****\n","  Num examples = 22194\n","  Num Epochs = 1\n","  Instantaneous batch size per device = 1\n","  Total train batch size (w. parallel, distributed & accumulation) = 1\n","  Gradient Accumulation steps = 1\n","  Total optimization steps = 22194\n"]},{"data":{"text/html":["\n","    <div>\n","      \n","      <progress value='22194' max='22194' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [22194/22194 1:59:32, Epoch 1/1]\n","    </div>\n","    <table border=\"1\" class=\"dataframe\">\n","  <thead>\n","    <tr style=\"text-align: left;\">\n","      <th>Epoch</th>\n","      <th>Training Loss</th>\n","      <th>Validation Loss</th>\n","      <th>Accuracy</th>\n","    </tr>\n","  </thead>\n","  <tbody>\n","    <tr>\n","      <td>1</td>\n","      <td>0.100000</td>\n","      <td>0.188630</td>\n","      <td>0.973839</td>\n","    </tr>\n","  </tbody>\n","</table><p>"],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["***** Running Evaluation *****\n","  Num examples = 5963\n","  Batch size = 1\n","Saving model checkpoint to language-detection-fine-tuned-on-xlm-roberta-base/checkpoint-22194\n","Configuration saved in language-detection-fine-tuned-on-xlm-roberta-base/checkpoint-22194/config.json\n","Model weights saved in language-detection-fine-tuned-on-xlm-roberta-base/checkpoint-22194/pytorch_model.bin\n","tokenizer config file saved in language-detection-fine-tuned-on-xlm-roberta-base/checkpoint-22194/tokenizer_config.json\n","Special tokens file saved in language-detection-fine-tuned-on-xlm-roberta-base/checkpoint-22194/special_tokens_map.json\n","tokenizer config file saved in language-detection-fine-tuned-on-xlm-roberta-base/tokenizer_config.json\n","Special tokens file saved in language-detection-fine-tuned-on-xlm-roberta-base/special_tokens_map.json\n","\n","\n","Training completed. Do not forget to share your model on huggingface.co/models =)\n","\n","\n","Loading best model from language-detection-fine-tuned-on-xlm-roberta-base/checkpoint-22194 (score: 0.9738386718094919).\n","***** Running Evaluation *****\n","  Num examples = 5963\n","  Batch size = 1\n"]},{"data":{"text/html":["\n","    <div>\n","      \n","      <progress value='5963' max='5963' style='width:300px; height:20px; vertical-align: middle;'></progress>\n","      [5963/5963 04:05]\n","    </div>\n","    "],"text/plain":["<IPython.core.display.HTML object>"]},"metadata":{},"output_type":"display_data"}],"source":["# create Trainer instance\n","trainer = Trainer(\n","    model=model,\n","    args=training_args,\n","    compute_metrics=compute_metrics,\n","    train_dataset=train_dataset,\n","    eval_dataset=test_dataset,\n","    tokenizer=tokenizer,\n","    data_collator=data_collator,\n",")\n","\n","# train model\n","trainer.train()\n","\n","# evaluate model\n","eval_result = trainer.evaluate(eval_dataset=test_dataset)"]},{"cell_type":"code","execution_count":15,"metadata":{"colab":{"base_uri":"https://localhost:8080/","height":440,"referenced_widgets":["abe1acd34e934a4389ea538973ebf7a5","952a0fb5c59540ada9c5e67df1b5c162","8e007c5869ec4a7d989f0886444bac77","dbed97b65fc24b84adfe278af4912832","709f4975a259485f833ce0bd0ba1e4fe","1d00b7f2d781488eade7b0dbd7189a28","ed5bb04202364cd2be644973ce6093df","a4db66b7b98b4764b56e36d13535729d","b9f78b55a1da48928925e578447575c6","6ecd1b6130c34006bce61be5bf056585","2433b20ff82349e082b968f4fa2d6db5","621e26f63397464a9694641b4a871c1f","6e7afd909d5142d190d8b94aabdfd388","d1777dd9f8d14f469bb2873ff78a560e","fae5771962634a0c9bd852a0c0de6b7c","3de0618549a34ed389f6f658d0ec7662","131b280b71bf4ca6863b7ab11063a991","c0c4d9ccf7914e229043df9fa4e4de07","6bf0145581894d6c8df9eb7a0543628d","c325e18f98f94845a5a26977da2e67ee","61beaf443c1b40afaf80c4305f7fa8d3","8f26537cc67d41cea7ea32447bac41e0","6394517233cb4a9c931bb56b7ec00520","dc28f4734623476d895e4016ca75ab5c","13743bdea9da4615ab0769defc42eebc","b2e20e1f8a2e4ec0b584c515c243db77","f335b430b1104f7eb293301039ca6a0a","88194eb9874941d3b5a8e1c073b8450d","e5a6423a14754c429394ffc12ee57691","38cef63d9b994317b2310803409e49c4","bef1f10af3d94081bd6856ea77d5d075","3d17077f62704f99a9e057d0cb3d301a","1d10b6217a1940859996323f9cc24dc9"]},"executionInfo":{"elapsed":1737047,"status":"ok","timestamp":1637747023470,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"2AKJ2XeeQEaJ","outputId":"fc575493-b7af-463a-912f-f1835acd4e7f"},"outputs":[{"name":"stderr","output_type":"stream","text":["Saving model checkpoint to language-detection-fine-tuned-on-xlm-roberta-base\n","Configuration saved in language-detection-fine-tuned-on-xlm-roberta-base/config.json\n","Model weights saved in language-detection-fine-tuned-on-xlm-roberta-base/pytorch_model.bin\n","tokenizer config file saved in language-detection-fine-tuned-on-xlm-roberta-base/tokenizer_config.json\n","Special tokens file saved in language-detection-fine-tuned-on-xlm-roberta-base/special_tokens_map.json\n","Several commits (2) will be pushed upstream.\n"]},{"name":"stdout","output_type":"stream","text":["2021-11-24 09:15:13,648 - huggingface_hub.repository - WARNING - Several commits (2) will be pushed upstream.\n"]},{"name":"stderr","output_type":"stream","text":["The progress bars may be unreliable.\n"]},{"name":"stdout","output_type":"stream","text":["2021-11-24 09:15:13,658 - huggingface_hub.repository - WARNING - The progress bars may be unreliable.\n"]},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"abe1acd34e934a4389ea538973ebf7a5","version_major":2,"version_minor":0},"text/plain":["Upload file pytorch_model.bin:   0%|          | 3.35k/1.04G [00:00<?, ?B/s]"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"621e26f63397464a9694641b4a871c1f","version_major":2,"version_minor":0},"text/plain":["Upload file runs/Nov24_07-10-47_68a9c49ae68b/events.out.tfevents.1637737867.68a9c49ae68b.73.0:  27%|##6       …"]},"metadata":{},"output_type":"display_data"},{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"6394517233cb4a9c931bb56b7ec00520","version_major":2,"version_minor":0},"text/plain":["Upload file runs/Nov24_07-10-47_68a9c49ae68b/events.out.tfevents.1637745286.68a9c49ae68b.73.2: 100%|##########…"]},"metadata":{},"output_type":"display_data"},{"name":"stderr","output_type":"stream","text":["To https://huggingface.co/ivanlau/language-detection-fine-tuned-on-xlm-roberta-base\n","   9411137..824c539  main -> main\n","\n"]},{"name":"stdout","output_type":"stream","text":["2021-11-24 09:43:42,417 - huggingface_hub.repository - WARNING - To https://huggingface.co/ivanlau/language-detection-fine-tuned-on-xlm-roberta-base\n","   9411137..824c539  main -> main\n","\n"]},{"data":{"application/vnd.google.colaboratory.intrinsic+json":{"type":"string"},"text/plain":["'https://huggingface.co/ivanlau/language-detection-fine-tuned-on-xlm-roberta-base/commit/824c5397db59b4d9ac9f6dc16f70aaa13afd5b1a'"]},"execution_count":15,"metadata":{},"output_type":"execute_result"}],"source":["# save best model, metrics and create model card\n","trainer.create_model_card(model_name=hub_model_id)\n","trainer.push_to_hub()\n"]},{"cell_type":"code","execution_count":16,"metadata":{"colab":{"base_uri":"https://localhost:8080/"},"executionInfo":{"elapsed":5783,"status":"ok","timestamp":1637747029246,"user":{"displayName":"LinTiong Lau","photoUrl":"https://lh3.googleusercontent.com/a/default-user=s64","userId":"07033255899381194111"},"user_tz":-480},"id":"AfIEDlWt5O-8","outputId":"9e539e65-124d-4aef-eea6-bc3fc71e28b0"},"outputs":[{"name":"stderr","output_type":"stream","text":["Saving model checkpoint to model/\n","Configuration saved in model/config.json\n","Model weights saved in model/pytorch_model.bin\n","tokenizer config file saved in model/tokenizer_config.json\n","Special tokens file saved in model/special_tokens_map.json\n"]}],"source":["# Saves the 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