{"id":15157761,"url":"https://github.com/vlada-pv/bert-predict-text-rating","last_synced_at":"2026-01-19T09:06:22.945Z","repository":{"id":253465748,"uuid":"843592268","full_name":"vlada-pv/BERT-predict-text-rating","owner":"vlada-pv","description":"BERT-based model for text classification tasks.","archived":false,"fork":false,"pushed_at":"2024-08-16T21:41:49.000Z","size":55,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-13T17:18:01.735Z","etag":null,"topics":["bert","bert-embeddings","neural-networks","pytorch","text-classification","text-rating"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/vlada-pv.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"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":"2024-08-16T21:33:02.000Z","updated_at":"2024-08-16T21:43:43.000Z","dependencies_parsed_at":null,"dependency_job_id":"d34f1aa4-ade7-4d1c-a7a1-32e7eefa288d","html_url":"https://github.com/vlada-pv/BERT-predict-text-rating","commit_stats":{"total_commits":4,"total_committers":1,"mean_commits":4.0,"dds":0.0,"last_synced_commit":"30770e6f1ffd6920d3913218d1c7660aa2c87fa5"},"previous_names":["vlada-pv/bert-predict-text-rating"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vlada-pv%2FBERT-predict-text-rating","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vlada-pv%2FBERT-predict-text-rating/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vlada-pv%2FBERT-predict-text-rating/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/vlada-pv%2FBERT-predict-text-rating/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/vlada-pv","download_url":"https://codeload.github.com/vlada-pv/BERT-predict-text-rating/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247675628,"owners_count":20977376,"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":["bert","bert-embeddings","neural-networks","pytorch","text-classification","text-rating"],"created_at":"2024-09-26T20:02:46.225Z","updated_at":"2026-01-19T09:06:22.904Z","avatar_url":"https://github.com/vlada-pv.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Text Classification with BERT\nThis project demonstrates the application of a BERT-based model for text classification tasks. The project is implemented using **PyTorch** and involves various stages of data preprocessing, model training, and evaluation.\n\n## Project Overview\nThe project is focused on building and evaluating a text classification model using a dataset from Kaggle. The key steps involved in this project include:\n\n**1) Data Loading and Preprocessing:**\n\nData is loaded from CSV files provided in the Kaggle dataset.\nText data is tokenized, cleaned, and prepared for model input using tools like NLTK and custom preprocessing functions.\n\n**2) Model Implementation:**\n\nA BERT-based model is implemented using the PyTorch framework.\nThe model architecture is designed to handle classification tasks, with appropriate layers and configurations for text data.\n\n**3) Training and Evaluation:**\n\nThe dataset is split into training and validation sets using scikit-learn.\nThe model is trained and optimized using various hyperparameters, and its performance is evaluated using metrics such as accuracy.\n\n**4) Results:**\n\nThe trained model is tested on unseen data, and results are reported in terms of accuracy and other relevant metrics.\n\n## Getting Started\n**Prerequisites:**\n* Python 3.x\n* PyTorch\n* scikit-learn\n* NLTK\n* Matplotlib\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvlada-pv%2Fbert-predict-text-rating","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fvlada-pv%2Fbert-predict-text-rating","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fvlada-pv%2Fbert-predict-text-rating/lists"}