{"id":17099016,"url":"https://github.com/dinhanhx/performance_calculation_tool_for_hm","last_synced_at":"2026-05-10T09:40:57.885Z","repository":{"id":112393492,"uuid":"393977606","full_name":"dinhanhx/performance_calculation_tool_for_hm","owner":"dinhanhx","description":"Performance calculation tool for Hateful Memes Challenge","archived":false,"fork":false,"pushed_at":"2021-08-08T14:26:40.000Z","size":625,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-28T23:50:04.154Z","etag":null,"topics":["accuracy-score","auc-roc-score","cli","dataset","hateful-memes-challenge","python-3","python3"],"latest_commit_sha":null,"homepage":"","language":"Python","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/dinhanhx.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":"2021-08-08T14:06:30.000Z","updated_at":"2021-08-09T01:07:17.000Z","dependencies_parsed_at":"2023-05-14T06:45:39.293Z","dependency_job_id":null,"html_url":"https://github.com/dinhanhx/performance_calculation_tool_for_hm","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dinhanhx%2Fperformance_calculation_tool_for_hm","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dinhanhx%2Fperformance_calculation_tool_for_hm/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dinhanhx%2Fperformance_calculation_tool_for_hm/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dinhanhx%2Fperformance_calculation_tool_for_hm/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dinhanhx","download_url":"https://codeload.github.com/dinhanhx/performance_calculation_tool_for_hm/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245144972,"owners_count":20568056,"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":["accuracy-score","auc-roc-score","cli","dataset","hateful-memes-challenge","python-3","python3"],"created_at":"2024-10-14T15:08:48.092Z","updated_at":"2026-05-10T09:40:57.823Z","avatar_url":"https://github.com/dinhanhx.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Performance calculation tool for [Hateful Memes Challenge](https://hatefulmemeschallenge.com/)\n\nThis simple project uses simple functions from [pretty errors](https://pypi.org/project/pretty-errors/), [click](https://click.palletsprojects.com/en/8.0.x/), [pandas](https://pandas.pydata.org/getting_started.html), [sklearn](https://scikit-learn.org/stable/install.html). Therefore, one can go to these link and install as instructions. This works with Python 3.7\n\n`calc_test.py` calculates AUC ROC and Accuracy scores. One can run `python calc_test.py --help` for instruction or can read the source code. It's very simple.\n\n`calc_test.py` takes `test_seen.jsonl` ([Phase 1](https://www.drivendata.org/competitions/64/hateful-memes/page/206/)) or `test_unseen.jsonl` ([Phase 2](https://www.drivendata.org/competitions/70/hateful-memes-phase-2/page/267/)) **and** `result.csv`. Importantly, `test_seen.jsonl`, `test_unseen.jsonl` must have labels.  \n\n`result.csv` must have to three columns:\n- Meme identification number, `id`\n- Probability that the meme is hateful, `proba` (must be a float)\n- Binary label that the meme is hateful (`1`) or non-hateful (`0`), `label` (must be an int)\n\n## Other scripts\n\n`combine.py` is meant to combine all `train.jsonl`, `dev_seen.jsonl`, `dev_unseen.jsonl`, `test_seen.jsonl`, `test_unseen.jsonl` into `data_test.jsonl`. Importantly, `test_seen.jsonl`, `test_unseen.jsonl` must have labels. By combining so, `data_test.jsonl` contains all metadata of all memes in the dataset.\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdinhanhx%2Fperformance_calculation_tool_for_hm","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdinhanhx%2Fperformance_calculation_tool_for_hm","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdinhanhx%2Fperformance_calculation_tool_for_hm/lists"}