{"id":19213533,"url":"https://github.com/sminerport/imdbsentimentclassifier","last_synced_at":"2026-04-29T21:05:50.795Z","repository":{"id":261858490,"uuid":"884689075","full_name":"sminerport/IMDbSentimentClassifier","owner":"sminerport","description":"A sentiment analysis model trained on the IMDb Movie Reviews Dataset to classify reviews as positive or negative. This project uses a Bidirectional LSTM with GloVe embeddings, batch normalization, and regularization to improve accuracy and generalization. Includes data preprocessing, model training, and evaluation.","archived":false,"fork":false,"pushed_at":"2024-12-23T00:37:20.000Z","size":26258,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-23T08:17:01.922Z","etag":null,"topics":["bidirectional-lstm","deep-learnning","git-lfs","glove","imdb-dataset","keras","lstm","machine-learning","movie-review-app","natural-language-processing","nlp","opinion-mining","python","sentimental-analysis","tensorflow","text-classification"],"latest_commit_sha":null,"homepage":"https://scottminer.netlify.app","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/sminerport.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":"2024-11-07T08:02:08.000Z","updated_at":"2024-11-08T20:08:45.000Z","dependencies_parsed_at":"2024-11-08T21:19:31.688Z","dependency_job_id":"ca984ae7-c4c8-42be-b8c9-00d844147bee","html_url":"https://github.com/sminerport/IMDbSentimentClassifier","commit_stats":null,"previous_names":["sminerport/imdbsentimentclassifier"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/sminerport/IMDbSentimentClassifier","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sminerport%2FIMDbSentimentClassifier","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sminerport%2FIMDbSentimentClassifier/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sminerport%2FIMDbSentimentClassifier/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sminerport%2FIMDbSentimentClassifier/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/sminerport","download_url":"https://codeload.github.com/sminerport/IMDbSentimentClassifier/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/sminerport%2FIMDbSentimentClassifier/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32443598,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-29T20:22:27.477Z","status":"ssl_error","status_checked_at":"2026-04-29T20:22:26.507Z","response_time":110,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.6:443 state=error: 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":["bidirectional-lstm","deep-learnning","git-lfs","glove","imdb-dataset","keras","lstm","machine-learning","movie-review-app","natural-language-processing","nlp","opinion-mining","python","sentimental-analysis","tensorflow","text-classification"],"created_at":"2024-11-09T14:06:09.233Z","updated_at":"2026-04-29T21:05:50.768Z","avatar_url":"https://github.com/sminerport.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# IMDb Sentiment Classifier\n\nThis project is a sentiment classifier for IMDb movie reviews. It uses a pre-trained GloVe word embedding model and a Bidirectional LSTM network to classify reviews as positive or negative.\n\n## Features\n\n- Loads IMDb movie reviews for training, validation, and testing.\n- Uses [GloVe embeddings](https://nlp.stanford.edu/projects/glove/) for enhanced text representation.\n- Trains a [Bidirectional LSTM (Long Short-Term Memory)](https://colah.github.io/posts/2015-08-Understanding-LSTMs/) model to classify reviews as positive or negative.\n- Achieves high accuracy on both validation and test sets.\n\n## Setup\n\n1. Clone this repository:\n\n   ```bash\n   git clone https://github.com/sminerport/IMDbSentimentClassifier.git\n   cd IMDbSentimentClassifier\n   ```\n\n2. Install dependencies:\n\n   ```bash\n   pip install -r requirements.txt\n   ```\n\n3. Run the model:\n   ```bash\n   python src/main.py\n   ```\n\n## Data\n\nThe model uses IMDb review data split into training, validation, and test sets. These files are stored in the `data/` directory and are managed with **Git Large File Storage (Git LFS)** to optimize storage and download efficiency.\n\nTo ensure access to the data files, please install **Git LFS** if you haven’t already. You can download Git LFS [here](https://git-lfs.github.com/).\n\n```bash\n# Install Git LFS\ngit lfs install\n```\n\nThen, clone the repository as usual:\n\n```bash\ngit clone https://github.com/sminerport/IMDbSentimentClassifier.git\ncd IMDbSentimentClassifier\n```\n\nIf you’ve already cloned the repository without Git LFS, run the following command to pull the LFS files:\n\n```bash\ngit lfs pull\n```\n\n## Usage\n\nTo train the model:\n\n```bash\npython src/main.py\n```\n\nAfter running, the script will automatically download and clean up GloVe embeddings to save space.\n\n## Model Training Output\n\nBelow is a snapshot of the model's training and validation accuracy and loss across epochs:\n\n![Model Training Output](images/model-output.png)\n\nThis image provides a visual summary of the training process. Each epoch displays the model's accuracy and loss on both the training and validation sets, showing the progression as the model improves over time.\n\n## Cleanup\n\nThe script will delete the GloVe embeddings and the saved model (`best_model.keras`) after evaluation to conserve storage. If you'd like to keep these files, set the `cleanup` variable to `False` in the script.\n\n## Notes\n\n- To adjust storage usage, toggle the `cleanup` variable in the script.\n- `requirements.txt` is generated by running `pip freeze \u003e requirements.txt` in a Colab environment or your local environment.\n\n## License\n\nThis project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsminerport%2Fimdbsentimentclassifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fsminerport%2Fimdbsentimentclassifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fsminerport%2Fimdbsentimentclassifier/lists"}