{"id":15065070,"url":"https://github.com/v0idzdev/mbti","last_synced_at":"2026-04-02T17:54:09.712Z","repository":{"id":57440135,"uuid":"461314045","full_name":"v0idzdev/mbti","owner":"v0idzdev","description":"Myers-briggs type indicator predictor using a machine learning model.","archived":false,"fork":false,"pushed_at":"2022-02-22T17:30:17.000Z","size":24598,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-09-09T16:45:48.308Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/v0idzdev.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}},"created_at":"2022-02-19T21:10:22.000Z","updated_at":"2023-05-25T16:56:15.000Z","dependencies_parsed_at":"2022-09-26T17:21:02.357Z","dependency_job_id":null,"html_url":"https://github.com/v0idzdev/mbti","commit_stats":null,"previous_names":["matthewflegg/mbti"],"tags_count":2,"template":false,"template_full_name":null,"purl":"pkg:github/v0idzdev/mbti","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/v0idzdev%2Fmbti","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/v0idzdev%2Fmbti/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/v0idzdev%2Fmbti/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/v0idzdev%2Fmbti/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/v0idzdev","download_url":"https://codeload.github.com/v0idzdev/mbti/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/v0idzdev%2Fmbti/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31312744,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-02T12:59:32.332Z","status":"ssl_error","status_checked_at":"2026-04-02T12:54:48.875Z","response_time":89,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 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":[],"created_at":"2024-09-25T00:30:33.606Z","updated_at":"2026-04-02T17:54:09.689Z","avatar_url":"https://github.com/v0idzdev.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# MBTI Predictor\nPredicting someone's MBTI type based on their online posts, using AI.\n\n### Approach\nI originally attempted to use a simple LSTM, using nltk and Keras. However, this approach led to the model badly overfitting.\n\nI opted for a bidirectional LSTM, treating the data differently with techniques such as lemmatization. This approach led to significantly slower learning - the model improved less and less per epoch. However, the validation accuracy did increase per epoch, as opposed to decreasing or remaining static. \n\nAs a last resort, I chose to use the BERT transformer with the AutoTokenizer from 'transformers.' In theory, it would have led to significantly better results - however, the large number of parameters meant it couldn't run on my GTX 1050. \n\nFeel free to download the source code, if your hardware resources could accommodate training the BERT model. \n\n### Findings\nI could not find a significant correlation between a post and the MBTI type of its poster, using both a standard LSTM and its bidirectional variant. \n\nThe dataset was unbalanced, with the number of posts per MBTI type differing greatly. I decided not to rectify this issue initially because the training data was already small at around 9000 entries. I may revisit this project if I find a more balanced and extensive dataset.\n\nFeel free to download the source code and try for yourself.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fv0idzdev%2Fmbti","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fv0idzdev%2Fmbti","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fv0idzdev%2Fmbti/lists"}