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It encompasses steps including data loading, preprocessing, and filtering for relevant content, along with cleaning and balancing the data. The notebook then proceeds to initialize and fine-tune the DistilBERT model for sequence classification, aiming to distinguish between high and low-quality reviews. The fine-tuned model is evaluated and saved, with the option to upload it to the Hugging Face Hub. This exercise aims to leverage the capabilities of DistilBERT for nuanced text classification tasks in the pharmaceutical domain.\n", + "\n", + "\n", + "**License**:\n", + "This work is licensed under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0). Free for educational and research use.\n", + "\n" + ], + "metadata": { + "id": "J0KM5uEIgTDO" + } + }, + { + "cell_type": "markdown", + "source": [ + "## STEP 1: SETTING UP THE ENVIRONMENT" + ], + "metadata": { + "id": "kJK4WrJB4JR1" + } + }, + { + "cell_type": "markdown", + "source": [ + "### Load Necessary Libraries" + ], + "metadata": { + "id": "zzrRM4P14M7-" + } + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "id": "zbzxLSs_tKQ4" + }, + "outputs": [], + "source": [ + "# Enable automatic module reloading to reflect changes in external .py files\n", + "%load_ext autoreload\n", + "# Reload all modules before executing code, keeping modules up-to-date\n", + "%autoreload 2" + ] + }, + { + "cell_type": "markdown", + "source": [ + "### Install Required Packages" + ], + "metadata": { + "id": "WFYXS6a9c4d2" + } + }, + { + "cell_type": "code", + "source": [ + "!pip install transformers" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/" + 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responses-0.18.0\n" + ] + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "### Import Necessary Libraries" + ], + "metadata": { + "id": "slQJPHqLdCeC" + } + }, + { + "cell_type": "code", + "source": [ + "import numpy as np\n", + "from datasets import load_dataset, load_metric, concatenate_datasets\n", + "from transformers import DistilBertForSequenceClassification, DistilBertTokenizer, Trainer, TrainingArguments\n", + "import evaluate\n", + "import html\n", + "import re\n", + "import csv\n", + "from collections import Counter\n", + "import pandas as pd" + ], + "metadata": { + "id": "ZPQo3nOFtpX-" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "markdown", + "source": [ + "### Initialize Weights & Biases for Experiment Tracking" + ], + "metadata": { + "id": "CAc15TpfT0m6" + } + }, + { + "cell_type": "code", + "source": [ + "# Import Weights & Biases for experiment tracking\n", + "import wandb" + ], + "metadata": { + "id": "gu1-uIyZT179" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# Initialize wandb for tracking and visualizing the training\n", + "wandb.init(project=\"distilbert-drugscom_depression_reviews\", name=\"run_1\")" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 214 + }, + "id": "FAcoX4eniLWc", + "outputId": "bc48d59d-a0f5-4725-be28-d60a36fc67c7" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "application/javascript": [ + "\n", + " window._wandbApiKey = new Promise((resolve, reject) => {\n", + " function loadScript(url) {\n", + " return new Promise(function(resolve, reject) {\n", + " let newScript = document.createElement(\"script\");\n", + " newScript.onerror = reject;\n", + " newScript.onload = resolve;\n", + " document.body.appendChild(newScript);\n", + " newScript.src = url;\n", + " });\n", + " }\n", + " loadScript(\"https://cdn.jsdelivr.net/npm/postmate/build/postmate.min.js\").then(() => {\n", + " const iframe = document.createElement('iframe')\n", + " iframe.style.cssText = \"width:0;height:0;border:none\"\n", + " document.body.appendChild(iframe)\n", + " const handshake = new Postmate({\n", + " container: iframe,\n", + " url: 'https://wandb.ai/authorize'\n", + " });\n", + " const timeout = setTimeout(() => reject(\"Couldn't auto authenticate\"), 5000)\n", + " handshake.then(function(child) {\n", + " child.on('authorize', data => {\n", + " clearTimeout(timeout)\n", + " resolve(data)\n", + " });\n", + " });\n", + " })\n", + " });\n", + " " + ] + }, + "metadata": {} + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\u001b[34m\u001b[1mwandb\u001b[0m: Logging into wandb.ai. (Learn how to deploy a W&B server locally: https://wandb.me/wandb-server)\n", + "\u001b[34m\u001b[1mwandb\u001b[0m: You can find your API key in your browser here: https://wandb.ai/authorize\n", + "wandb: Paste an API key from your profile and hit enter, or press ctrl+c to quit:" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + " ··········\n" + ] + }, + { + "output_type": "stream", + "name": "stderr", + "text": [ + "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n" + ] + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "Tracking run with wandb version 0.16.1" + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "Run data is saved locally in /content/wandb/run-20231206_115741-0ik9cdfq" + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + "Syncing run run_1 to Weights & Biases (docs)
" + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + " View project at https://wandb.ai/team-zakia/distilbert-drugscom_depression_reviews" + ] + }, + "metadata": {} + }, + { + "output_type": "display_data", + "data": { + "text/plain": [ + "" + ], + "text/html": [ + " View run at https://wandb.ai/team-zakia/distilbert-drugscom_depression_reviews/runs/0ik9cdfq" + ] + }, + "metadata": {} + }, + { + "output_type": "execute_result", + "data": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "execution_count": 10 + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "## STEP 2: LOAD AND PRE-PROCESS DRUG REVIEWS DATASET" + ], + "metadata": { + "id": "LGYKu-eF4ZvJ" + } + }, + { + "cell_type": "code", + "source": [ + "dataset_name = \"Zakia/drugscom_reviews\"" + ], + "metadata": { + "id": "v_FNuZmvtsY1" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "train_ds = load_dataset(dataset_name, split=\"train\")" + ], + "metadata": { + "id": "DyK71VIut7kf", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 241, + "referenced_widgets": [ + "159a87d01d374fe2878d7ab3c6844d93", + "0ed37c139fef4940aed6982a58aeb792", + "69ff48a64d57439cbd35b33efb50598a", + "b9fbc3ccaf964faabceb5e3d19bfa1c5", + "c20bac98a15b413484747e57a4715d09", + "9036d81ba2b643e3b4617e309aa2cdb7", + "eb498ea550d340ec9ea76501b215964a", + "fdab1d025be743b39608d110d08320af", + "8ff5e445704b400e9796602035701efb", + "636e5430653548d3b5b074d5e1f4a995", + "741606d62dc84c3d84114e2f9d5195df", + "07f8ae49ba55421f9c7efb43a8ddcfba", + "e3621468fa00474db14b7f04e108ea2b", + "fbf6c587e08e480192fdaca81c6255d7", + "7e8e8276be4148d488a129c21b8d1deb", + "d0cd6b570c654108b35ab4dbe3a1afca", + "ab624303b997454dab280ffbf6b65fc6", + "f88df2713a514ef58c9f2a1b867aeb57", + "cd00c6c6d3a04515a8696a6429446568", + "a50fb77e114945b587c1e07eeec989b9", + "a27d06511e114ff0827d4e34cf196526", + "3a2fe9cda338440181aec790f0b782d0", + "b3efcb2bea9744fc83a3129470cf339c", + "803b7a7993f04b389f1081317ec5b90d", + "65e78c4f085048a592ab6e183a45618a", + "6e2f337994444ca6a2744a29eeeae7bf", + "4d173a09af2c4c1fa5080b1409748b8e", + "9c60750d0ec1432ba5579ed8aafa5847", + "ca2ca1fe04e744519f73eb5401968653", + "a76fadd308164b2b97f9d65629e0c742", + "134c1239728d46f98fca2612d8243248", + "4184a147d65d45e8a62bdc8e925012a9", + "7dd5a4b864154585a245cd099ee9c67b", + "3073f4def2ff4e6098e79c5d23de9d31", + "37b1b0fde7874fc293c2e6e3e4e80d06", + "26574f1956034fc7923f7c15332a084c", + "727eeeec187844f4986de7c3ad844095", + "60ef6a86e0c04bc99999fc3d24c8a69b", + "40aa1968a384483eb2b9330648fddf93", + "fc196f0fe6194a3895046afed86a3a0c", + "33edbb32baea41d18d261f3cd7227c35", + "25681b7edae44a16a0333ab4f430f028", + "82c04c19f6884cc3a6fd8e7d7c268ace", + "a8e1ab37b3904349af3603ef6945df29", + "f8dae3b74ea34ce2ba93581b6493f0fd", + "59837565048e4293bdd9c9e0a0b3ea3d", + "dfcc0e53e5294a96b766676f1009265a", + "fc8e19a0bf5f41449f1b8789a5ce3c6e", + "f133c720943a4487b6700f4b034b0dda", + "129b4be73ff645faaee30591458593bb", + "a73d144eae264b57aae64d3fd014aafe", + "02fb810f07d14b6491d08c4774524752", + "66d8649970374fb3b1fadb1500688135", + "a7f70dc5c7164193937efa3dfa3c4e83", + "4423c35c347149a5b13a49c6d3e97bf4", + "a1e1995378b9456ebc06cb70aaef20d0", + "9f7ce81d88b0477ebeab08369c41bf10", + "53e6a9f7290444ec941df59b6e873d2f", + "a9c373347444420da58c4df1933ca9c7", + "e09a53a1cab1427e83e80a928bf213a2", + "a08f4c99d3024e7fa4fe23bfcb72d0e1", + "469d30176679485db760119a94a7ae54", + "49b2766eaba34aa78028c862419ace35", + "b9b47942c66a4d24b4cecd4387544217", + "3188a11044284d7bbf35f6f79b43c6e7", + "4ef74319a3944683ba950e325b69b253", + "ed4dabf40a9b44e29f5048ec7b27ae9c", + "7542c74a04f74b6588b302805c1e2e95", + "ac079bdadd694b6ead90dfe147a28c60", + "039eeb984f5f4365a69139eb1ed40f74", + "60fa03127e3e41d0b87502c1453f1213", + "0c7c4513cfe54caa9d542076e1ffcba9", + "e816e9e3615246c695fff4373ebd29ee", + "706ec76aa5ac4a6a8c12a08f29176afa", + "aaf933351cbd470fba3a273c21501eec", + "b78d12c084b940d392cfa3b13e7d8ea4", + "b6f07f9ed23d4e998b1a33b4259cf06f" + ] + }, + "outputId": "c590b863-beed-46ba-8a1d-c9df96e50278" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Downloading readme: 0%| | 0.00/6.59k [00:00', '', text) # Remove HTML tags\n", + " return text" + ], + "metadata": { + "id": "2GmihTdSuMPF" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# Clean the reviews\n", + "# Apply the clean_review function in a batched manner\n", + "def clean_reviews(batch):\n", + " # Apply clean_review to each review in the batch and return the modified batch\n", + " return {\"review\": [clean_review(review) for review in batch[\"review\"]]}" + ], + "metadata": { + "id": "jSEt0xnfuSQu" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# Clean the reviews for the train dataset\n", + "train_ds = train_ds.map(clean_reviews, batched=True)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 49, + "referenced_widgets": [ + "08bce8a0de8443f8befdaa81cbd3396e", + "0ed633424ede4c8784d545d5c1cf2f45", + "b15078202f204ab497bb6713d85c9b9c", + "6cbafdfa31bf4a4ea628c07d64772ebb", + "b29767f814c447be905f7435cf14664e", + "f330447c13644bfba10cf206fb4f139a", + "3705ce91e02b4c679f8d9417d78b3342", + "5a302c72d5324f94ad1d49e2bf03b19e", + "0511f90cf66f4c7492006c98fdd55316", + "a98a853bf24e4b079b31a14e86e5214e", + "05da444268d44607ae6fe181b84f5688" + ] + }, + "id": "T_xn2iODIHIS", + "outputId": "de603bc7-a921-4c2a-aac5-7e3e8f673949" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Map: 0%| | 0/9069 [00:00 RATING_THRESHOLD # Assuming a rating above 5 is positive\n", + " is_high_usefulCount = text[\"usefulCount\"] > USEFUL_COUNT_THRESHOLD\n", + " return {\"high_quality_review\": int(is_high_rating and is_high_usefulCount)}" + ], + "metadata": { + "id": "UE6saXmLuctW" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# Apply the high_quality_review function to the train dataset\n", + "train_ds = train_ds.map(high_quality_review)" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 49, + "referenced_widgets": [ + "f1b1e59a777643b9a30c7e403b90cfdf", + "20bcee7a1e134fd3a11184b20e201dea", + "931c82d855804653bdf7b09bda0f8438", + "e352778970e74b8c9424d2ea100230fa", + "59675ac2b32f4e6bab6affe670b36ade", + "80f7a63437a34be6a0e7c2c1168c3ab9", + "33415320d4d54c7086aee9a295b78652", + "b62149a22ea7477dbedb098fad927e0e", + "60d900515943462989383c892e8f372c", + "952a674afdd84870aa05630a1362892a", + "ea1ffe44863c4f279673391b1c09082a" + ] + }, + "id": "14aQWAKOIoFl", + "outputId": "95fc3f91-4763-4c79-f8a8-e1c0575096c4" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Map: 0%| | 0/9069 [00:00 512). Running this sequence through the model will result in indexing errors\n" + ] + }, + { + "output_type": "stream", + "name": "stdout", + "text": [ + "The longest review is 672 tokens long.\n" + ] + } + ] + }, + { + "cell_type": "code", + "source": [ + "# Apply the encode function to the balanced training dataset\n", + "train_encoded = balanced_train_ds.map(encode, batched=True)" + ], + "metadata": { + "id": "18v0sBsc058q", + "colab": { + "base_uri": "https://localhost:8080/", + "height": 49, + "referenced_widgets": [ + "a5e3115e4bc84333a83e4b32382d382d", + "d0cd69b92863460ba237ceb8d05cc05a", + "9e1f10b34c8545e694dd5223e7991f01", + "cac87a556d1b4c44bc15635ea88a0ba1", + "e27d5e192e334e89b95d74c1fca2b2ee", + "1eaad091a2ce4f18bec0ac9bface4e3a", + "41407df8693a42978fabe25ece3b9309", + "0cf1e2bff7924380900968ed3192c2e5", + "21323711b47f4daaa06ce237c0603eca", + "ac79b4f3dc3d4448a6389d2cee919503", + "ada666273e3849179ca1292a0d36ed61" + ] + }, + "outputId": "69f33ea6-908f-4b59-d09a-4aae3edfa978" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "Map: 0%| | 0/4240 [00:00" + ], + "text/html": [ + "\n", + "
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" + ] + }, + "metadata": {} + }, + { + "output_type": "execute_result", + "data": { + "text/plain": [ + "TrainOutput(global_step=265, training_loss=0.18166468638294148, metrics={'train_runtime': 256.159, 'train_samples_per_second': 16.552, 'train_steps_per_second': 1.035, 'total_flos': 561661770301440.0, 'train_loss': 0.18166468638294148, 'epoch': 1.0})" + ] + }, + "metadata": {}, + "execution_count": 65 + } + ] + }, + { + "cell_type": "markdown", + "source": [ + "## STEP 5: SAVE THE FINE-TUNED DISTILBERT MODEL: distilbert-drugscom_depression_reviews" + ], + "metadata": { + "id": "EFH89vCQ0pMf" + } + }, + { + "cell_type": "code", + "source": [ + "from huggingface_hub import notebook_login # To log to our Hugging Face account to be able to upload models to the Hub." + ], + "metadata": { + "id": "LthX-XqW5Agq" + }, + "execution_count": null, + "outputs": [] + }, + { + "cell_type": "code", + "source": [ + "# Login to Hugging Face within the notebook\n", + "notebook_login()\n", + "!git config --global credential.helper store" + ], + "metadata": { + "colab": { + "base_uri": "https://localhost:8080/", + "height": 145, + "referenced_widgets": [ + "98f03850a01d425e82f4edd0f7218281", + "a0416f5afb62412996814f538ba5268b", + "3b2c10c8b24e4a4c88e2e4fd2564b619", + "84b1a675346d4601b73c3a6b2ebf5815", + "19c44ca8d64d47b0bef4eea7cbe73bbb", + "83bae9a984fc4f6aa689abb077a05ead", + "982b11ab3b474001b9018a4f7ab7e7ac", + "81a1021ec0944d9d9f1b33f5e9184078", + "eebe3f60174240e5a71ffc054f3bf3df", + "3ea1e55d19744eacadc64e50ccbeca99", + "79ca81748cdb42d281112c64412a6ed9", + "385c71653c9648f5b9e629ba017c9b87", + "eab6012065314537960397f508af055d", + "3afc1e733ad344e1a67d9d9673c68f72", + "528328fb552c49e48fdfeb476d61b890", + "5146404d17b8401b8afca36c896cf0ca", + "eaa051e8e6734f069bfd8779ce465373", + "798ad4546b5c4977a2f6270ae518e124", + "9ebc093be8a647a6af8fea7d04656619", + "32fd60c986dd4a97b532be2f476c33f1", + "1223c060acdf499cb571ea98332c37ac", + "b88d1d7ed93c40a58ac420b5516d2b85", + "c814dd02eb0f430b90d7a88f8f692e78", + "949735e1cfd44d50a36d29dff40fe41e", + "d9ebd1d1762d4e6ba2e7e9d601b4d2ca", + "48531ee1bb6c4ead9ab152d97be3955f", + "13d5ad5688944d05a31f7a45ac272f17", + "34b6076372d94601ab30ce849aff525f", + "d47c31a9cf674660882725a4e98f4c0e", + "56861d81a5544566a5339fbc918ad24c", + "9b7c08fdd70c48e3a957ee46fee5113d", + "2a503b9ba46e4375b1a2be180f116d93" + ] + }, + "id": "X_g76SB35CDE", + "outputId": "6f5198e4-afc6-4269-dcfd-7d83ffcae023" + }, + "execution_count": null, + "outputs": [ + { + "output_type": "display_data", + "data": { + "text/plain": [ + "VBox(children=(HTML(value='