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--- |
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license: apache-2.0 |
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task_categories: |
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- text-classification |
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language: |
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- en |
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tags: |
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- Jokes |
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--- |
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# 🃏 Labelled r/Jokes Dataset |
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A dataset of Reddit jokes from r/Jokes annotated with humor, offensiveness, and sentiment using large language models (LLMs). |
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## 📊 Dataset Overview |
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- **LLM-Labeled Subset (Mistral-7B):** 55,278 jokes |
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- **Model-Predicted Subset (Fine-tuned RoBERTa):** 518,124 jokes |
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<table> |
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<tr> |
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<td><img src="https://cdn-uploads.huggingface.co/production/uploads/63f0e7de9cf89c9ed1bf92a2/Iygh4z3z42moUyNm3zEV1.png" width="400"/></td> |
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<td><img src="https://cdn-uploads.huggingface.co/production/uploads/63f0e7de9cf89c9ed1bf92a2/JU_-b0OQ7zrQNSN-TXWZZ.png" width="400"/></td> |
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</tr> |
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</table> |
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## 📄 Column Descriptions |
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| Column | Description | |
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|------------------|-----------------------------------------------------------------------------| |
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| `date` | Date the joke was posted on Reddit (r/Jokes) | |
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| `joke` | The full text of the joke | |
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| `score` | Number of upvotes received in the subreddit | |
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| `humor` | Binary label: 1 = humorous, 0 = not humorous | |
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| `offensiveness` | Binary label: 1 = offensive, 0 = not offensive | |
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| `sentiment` | Sentiment score: -1 = negative, 0 = neutral, 1 = positive | |
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| `source` | Indicates labeling source: `llm` (Mistral-7B) or `roberta` (fine-tuned RoBERTa) | |
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## 💡 Use Cases |
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- Humor detection and classification |
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- Offensive content moderation |
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- Sentiment-aware joke recommendation |
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- Multi-label text classification tasks |
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## 🚀 Usage |
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This dataset was used to fine-tune the RoBERTa model available here: |
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👉 [SajilAwale/FunnyModel](https://huggingface.co/SajilAwale/FunnyModel) |
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## 📝 Source |
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Original joke dataset: [rJokesData GitHub Repository](https://github.com/orionw/rJokesData) |
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