metadata
license: apache-2.0
task_categories:
- text-classification
language:
- en
tags:
- Jokes
🃏 Labelled r/Jokes Dataset
A dataset of Reddit jokes from r/Jokes annotated with humor, offensiveness, and sentiment using large language models (LLMs).
📊 Dataset Overview
- LLM-Labeled Subset (Mistral-7B): 55,278 jokes
- Model-Predicted Subset (Fine-tuned RoBERTa): 518,124 jokes
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📄 Column Descriptions
| Column | Description |
|---|---|
date |
Date the joke was posted on Reddit (r/Jokes) |
joke |
The full text of the joke |
score |
Number of upvotes received in the subreddit |
humor |
Binary label: 1 = humorous, 0 = not humorous |
offensiveness |
Binary label: 1 = offensive, 0 = not offensive |
sentiment |
Sentiment score: -1 = negative, 0 = neutral, 1 = positive |
source |
Indicates labeling source: llm (Mistral-7B) or roberta (fine-tuned RoBERTa) |
💡 Use Cases
- Humor detection and classification
- Offensive content moderation
- Sentiment-aware joke recommendation
- Multi-label text classification tasks
🚀 Usage
This dataset was used to fine-tune the RoBERTa model available here:
👉 SajilAwale/FunnyModel
📝 Source
Original joke dataset: rJokesData GitHub Repository