{"id":13743339,"url":"https://github.com/EmreTaha/Unsupervised-Domain-Adaptation-with-BERT","last_synced_at":"2025-05-09T01:30:35.591Z","repository":{"id":217213232,"uuid":"211874904","full_name":"EmreTaha/Unsupervised-Domain-Adaptation-with-BERT","owner":"EmreTaha","description":"Unsupervised domain adaptation with BERT for Amazon food product reviews sentiment analysis. ","archived":false,"fork":false,"pushed_at":"2020-10-06T00:39:09.000Z","size":160,"stargazers_count":14,"open_issues_count":0,"forks_count":2,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-11-15T14:35:27.719Z","etag":null,"topics":["adversarial-learning","amazon-food-reviews","bert","bert-model","colab","domain-adaptation","nlp","sentiment-analysis","tensorflow","unsupervised-learning"],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/EmreTaha.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2019-09-30T14:08:15.000Z","updated_at":"2024-04-01T19:18:41.000Z","dependencies_parsed_at":null,"dependency_job_id":"8cb58fd4-1024-4426-9c3a-b900fb755c58","html_url":"https://github.com/EmreTaha/Unsupervised-Domain-Adaptation-with-BERT","commit_stats":null,"previous_names":["emretaha/unsupervised-domain-adaptation-with-bert"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EmreTaha%2FUnsupervised-Domain-Adaptation-with-BERT","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EmreTaha%2FUnsupervised-Domain-Adaptation-with-BERT/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EmreTaha%2FUnsupervised-Domain-Adaptation-with-BERT/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/EmreTaha%2FUnsupervised-Domain-Adaptation-with-BERT/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/EmreTaha","download_url":"https://codeload.github.com/EmreTaha/Unsupervised-Domain-Adaptation-with-BERT/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":253174168,"owners_count":21865821,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["adversarial-learning","amazon-food-reviews","bert","bert-model","colab","domain-adaptation","nlp","sentiment-analysis","tensorflow","unsupervised-learning"],"created_at":"2024-08-03T05:00:44.860Z","updated_at":"2025-05-09T01:30:35.181Z","avatar_url":"https://github.com/EmreTaha.png","language":"Jupyter Notebook","funding_links":[],"categories":["Alignment-based"],"sub_categories":[],"readme":"# Unsupervised-Domain-Adaptation-with-BERT\nA novel approach for BERT usage in an adversarial unsupervised domain adaptation manner for a NLP tasks. The topic is **Unsupervised domain adaptation between two Amazon product reviews categories with BERT and a domain discriminator network for the sentiment analysis**.\n\nPlease cite original [BERT](https://arxiv.org/abs/1810.04805) paper when using the code.\n\nThe code based on BERT in the TF-Hub. `BERTOptimizer.py` file is modified for freezing the network partially. \n\n## Getting Started\nUpload ipynb file, `BERTOptimizer.py`, `utils.py` files to Google Colab. The data (from Stanford) is downloaded and processed within the code\n\n## Requirements\n* Python 3.6\n* pandas \n* Tensorflow 1.x\n* Numpy\n* Matplotlib\n* Scipy\n* Google Colab\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FEmreTaha%2FUnsupervised-Domain-Adaptation-with-BERT","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FEmreTaha%2FUnsupervised-Domain-Adaptation-with-BERT","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FEmreTaha%2FUnsupervised-Domain-Adaptation-with-BERT/lists"}