{"id":24098447,"url":"https://github.com/matlab-deep-learning/fine-tune-bert-classification","last_synced_at":"2026-03-01T22:41:16.178Z","repository":{"id":233983554,"uuid":"788127095","full_name":"matlab-deep-learning/fine-tune-BERT-classification","owner":"matlab-deep-learning","description":null,"archived":false,"fork":false,"pushed_at":"2024-04-18T15:41:26.000Z","size":154,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":5,"default_branch":"main","last_synced_at":"2025-02-27T20:24:06.507Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/matlab-deep-learning.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"license.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":"SECURITY.md","support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-04-17T20:33:41.000Z","updated_at":"2024-04-17T20:33:42.000Z","dependencies_parsed_at":null,"dependency_job_id":"71abe29d-91d4-4d21-a2dc-78e30e06ebd2","html_url":"https://github.com/matlab-deep-learning/fine-tune-BERT-classification","commit_stats":null,"previous_names":["matlab-deep-learning/fine-tune-bert-classification"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/matlab-deep-learning/fine-tune-BERT-classification","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matlab-deep-learning%2Ffine-tune-BERT-classification","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matlab-deep-learning%2Ffine-tune-BERT-classification/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matlab-deep-learning%2Ffine-tune-BERT-classification/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matlab-deep-learning%2Ffine-tune-BERT-classification/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/matlab-deep-learning","download_url":"https://codeload.github.com/matlab-deep-learning/fine-tune-BERT-classification/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/matlab-deep-learning%2Ffine-tune-BERT-classification/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29987636,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-01T21:06:37.093Z","status":"ssl_error","status_checked_at":"2026-03-01T21:05:45.052Z","response_time":124,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-01-10T14:45:54.419Z","updated_at":"2026-03-01T22:41:16.168Z","avatar_url":"https://github.com/matlab-deep-learning.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Fine-Tune BERT to Classify Text Data in MATLAB®\n\n\n## Getting started\n\nThis example shows how to fine-tune a pretrained BERT model for performing text classification. \n\n\n## Overview\n\nIn this example, you modify a pretrained BERT model for text classification. First, add new layers for classification. Then, retrain the model to fine-tune it, using the original parameters as a starting point. It includes three steps:\n1.\tPreprocess text data and initialize BERT model\n2.\tSet up and train the network\n3.\tTest the model\n\nThis example shows the steps for fine-tuning BERT in detail. An alternative approach for document classification using BERT is to use [trainBERTDocumentClassifier](https://www.mathworks.com/help/textanalytics/ref/trainbertdocumentclassifier.html) function.\n\n## Setup\nClone the repository into a local directory. Open the example script \"FineTuning_BERT_for_Classification.mlx\".\n\nThe example requires data to run. To download the data: : \n- Go to https://www.mathworks.com/help/textanalytics/ug/create-simple-text-model-for-classification.html. \n- Click on the button \"Copy Command\" on the top right of the page and paste it in MATLAB Command Window. This will open the example in the directory where the CSV file is stored. \n- Copy the CSV file from the example, and paste it in the cloned repository.\n- If the file is saved in a different location, change the code to point to the file.\n\n## Required Products\n- MATLAB (R2024a or later) \n- Text Analytics Toolbox\u0026trade; (R2024a or later)\n- Deep Learning Toolbox\u0026trade; (R2024a or later)\n\n## Contact\nSohini Sarkar, ssarkar@mathworks.com\n\n## License\nThe license is available in license.txt file in this GitHub repository.\n\n## Community Support\n[MATLAB Central](https://www.mathworks.com/matlabcentral)\n\n\nCopyright 2024, The MathWorks, Inc.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmatlab-deep-learning%2Ffine-tune-bert-classification","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmatlab-deep-learning%2Ffine-tune-bert-classification","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmatlab-deep-learning%2Ffine-tune-bert-classification/lists"}