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--- |
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license: cc-by-sa-4.0 |
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task_categories: |
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- text-generation |
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- question-answering |
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language: |
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- en |
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pretty_name: MathText |
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size_categories: |
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- 10B<n<100B |
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configs: |
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- config_name: web-0.5 |
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data_files: |
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- split: train |
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path: |
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- data/web/0.95-1.00.jsonl |
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- data/web/0.90-0.95.jsonl |
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- data/web/0.85-0.90.jsonl |
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- data/web/0.80-0.85.jsonl |
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- data/web/0.75-0.80.jsonl |
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- data/web/0.70-0.75.jsonl |
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- data/web/0.65-0.70.jsonl |
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- data/web/0.60-0.65.jsonl |
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- data/web/0.55-0.60.jsonl |
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- data/web/0.50-0.55.jsonl |
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default: true |
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- config_name: web-0.6 |
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data_files: |
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- split: train |
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path: |
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- data/web/0.95-1.00.jsonl |
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- data/web/0.90-0.95.jsonl |
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- data/web/0.85-0.90.jsonl |
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- data/web/0.80-0.85.jsonl |
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- data/web/0.75-0.80.jsonl |
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- data/web/0.70-0.75.jsonl |
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- data/web/0.65-0.70.jsonl |
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- data/web/0.60-0.65.jsonl |
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- config_name: web-0.7 |
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data_files: |
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- split: train |
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path: |
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- data/web/0.95-1.00.jsonl |
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- data/web/0.90-0.95.jsonl |
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- data/web/0.85-0.90.jsonl |
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- data/web/0.80-0.85.jsonl |
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- data/web/0.75-0.80.jsonl |
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- data/web/0.70-0.75.jsonl |
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- config_name: web-full |
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data_files: data/web/*.jsonl |
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tags: |
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- mathematical-reasoning |
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- reasoning |
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- finetuning |
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- pretraining |
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- llm |
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--- |
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# MathText |
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MathText is an extensive and carefully curated dataset encompassing **200 GB** of mathematical texts. It's a unique compilation sourced from a diverse range of platforms including various websites, arXiv, and GitHub (OpenWebMath, RedPajama, Algebraic Stack). This rich repository has been **autonomously labeled by the state-of-the-art open-sourced language model**, Qwen-72B. Each piece of content in the dataset is assigned **a score `lm_q1q2_score` within the range of [0, 1]**, reflecting its relevance, quality and educational value in the context of mathematical intelligence. |
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## Objective |
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The primary aim of the MathText dataset is to provide a comprehensive and reliable resource for a wide array of users - from academic researchers and educators to AI practitioners and mathematics enthusiasts. This dataset is particularly geared towards: |
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- Facilitating advanced research in the intersection of mathematics and artificial intelligence. |
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- Serving as an educational tool for learning and teaching complex mathematical concepts. |
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- Providing a robust foundation for developing and training AI models specialized in processing and understanding mathematical content. |
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## Features |
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- **Volume**: Approximately 200 GB of text data. |
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- **Content**: A diverse collection of mathematical texts, including but not limited to research papers, educational articles, and code documentation. |
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- **Labeling**: Every text is scored by Qwen-72B, a sophisticated language model, ensuring a high standard of relevance and accuracy. |
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- **Scope**: Covers a wide spectrum of mathematical topics, making it suitable for various applications in research and education. |
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