{"id":19462663,"url":"https://github.com/dair-ai/emotion_dataset","last_synced_at":"2025-06-25T16:07:46.496Z","repository":{"id":39607654,"uuid":"253049566","full_name":"dair-ai/emotion_dataset","owner":"dair-ai","description":":smile: Dataset for Emotion Recognition Research","archived":false,"fork":false,"pushed_at":"2022-12-29T04:23:08.000Z","size":37,"stargazers_count":211,"open_issues_count":1,"forks_count":28,"subscribers_count":8,"default_branch":"master","last_synced_at":"2025-06-11T09:30:01.142Z","etag":null,"topics":["dataset","machine-learning","nlp","pytorch"],"latest_commit_sha":null,"homepage":"","language":null,"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/dair-ai.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}},"created_at":"2020-04-04T16:45:52.000Z","updated_at":"2025-06-03T03:29:15.000Z","dependencies_parsed_at":"2023-01-31T08:01:11.218Z","dependency_job_id":null,"html_url":"https://github.com/dair-ai/emotion_dataset","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/dair-ai/emotion_dataset","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dair-ai%2Femotion_dataset","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dair-ai%2Femotion_dataset/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dair-ai%2Femotion_dataset/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dair-ai%2Femotion_dataset/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dair-ai","download_url":"https://codeload.github.com/dair-ai/emotion_dataset/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dair-ai%2Femotion_dataset/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":260023306,"owners_count":22947354,"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":["dataset","machine-learning","nlp","pytorch"],"created_at":"2024-11-10T18:04:35.619Z","updated_at":"2025-06-25T16:07:46.437Z","avatar_url":"https://github.com/dair-ai.png","language":null,"funding_links":[],"categories":["Others"],"sub_categories":[],"readme":"# Emotion Dataset\n\nThis is a dataset that can be used for emotion classification. It has already been preprocessed based on the approach described in our [paper](https://www.aclweb.org/anthology/D18-1404/). It is also stored as a pandas dataframe and ready to be used in an NLP pipeline.\n\nNote that the version of the data provided here corresponds to a six emotions variant that's meant to be used for educational and research purposes. \n\n## Download \n\nHugging Face: https://huggingface.co/datasets/emotion\n\nDownload link: https://www.icloud.com/iclouddrive/084E9TMZ_lykn3QhU-kIX1DDQ#merged_training\n\nPapers with Code Public Leaderboad: https://paperswithcode.com/sota/text-classification-on-emotion\n\n## Load the Dataset Using Pandas\n\n```python\nimport pandas as pd\n\ndf = pd.read_pickle(\"merged_training.pkl\")\n```\n\n## Notebooks\n\nHere is a [notebook](https://colab.research.google.com/drive/1nwCE6b9PXIKhv2hvbqf1oZKIGkXMTi1X#scrollTo=t23zHggkEpc-) showing how to use it for fine-tuning a pretrained language model for the task of emotion classification.\n\nHere is another [notebook](https://colab.research.google.com/drive/176NSaYjc2eeI-78oLH_F9-YV3po3qQQO?usp=sharing) which shows how to fine-tune T5 model for emotion classification along with other tasks.\n\nHere is also a hosted [fine-tuned model](https://huggingface.co/mrm8488/distilroberta-base-finetuned-sentiment) on HuggingFace which you can directly use for inference in your NLP pipeline. \n\nFeel free to reach out to me on [Twitter](https://twitter.com/omarsar0) for more questions about the dataset.\n\n## Usage \n\nThe dataset should be used for educational and research purposes only. If you use it, please cite:\n\n```\n@inproceedings{saravia-etal-2018-carer,\n    title = \"{CARER}: Contextualized Affect Representations for Emotion Recognition\",\n    author = \"Saravia, Elvis  and\n      Liu, Hsien-Chi Toby  and\n      Huang, Yen-Hao  and\n      Wu, Junlin  and\n      Chen, Yi-Shin\",\n    booktitle = \"Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing\",\n    month = oct # \"-\" # nov,\n    year = \"2018\",\n    address = \"Brussels, Belgium\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://www.aclweb.org/anthology/D18-1404\",\n    doi = \"10.18653/v1/D18-1404\",\n    pages = \"3687--3697\",\n    abstract = \"Emotions are expressed in nuanced ways, which varies by collective or individual experiences, knowledge, and beliefs. Therefore, to understand emotion, as conveyed through text, a robust mechanism capable of capturing and modeling different linguistic nuances and phenomena is needed. We propose a semi-supervised, graph-based algorithm to produce rich structural descriptors which serve as the building blocks for constructing contextualized affect representations from text. The pattern-based representations are further enriched with word embeddings and evaluated through several emotion recognition tasks. Our experimental results demonstrate that the proposed method outperforms state-of-the-art techniques on emotion recognition tasks.\",\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdair-ai%2Femotion_dataset","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdair-ai%2Femotion_dataset","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdair-ai%2Femotion_dataset/lists"}