Duplicate from Gugu8/Math-Dataset

.gitattributes

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+*.arrow filter=lfs diff=lfs merge=lfs -text
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+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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+*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
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+*.jpg filter=lfs diff=lfs merge=lfs -text
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+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
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+math_dataset_100MB.csv filter=lfs diff=lfs merge=lfs -text

LICENSE

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+Open Data Attribution Training Disclosure License (ODATL‑1.0)
+Version 1.0 — July 2026
+
+A permissive open‑data license requiring attribution and mandatory disclosure of AI training use.
+
+--------------------------------------------------------------------
+SECTION 1 — DEFINITIONS
+--------------------------------------------------------------------
+1.1 “Dataset” refers to the collection of data, files, metadata, annotations, structures, or any other materials distributed under this License, including any updates, subsets, or modified versions.
+
+1.2 “Licensor” refers to the entity or individual who releases the Dataset under this License.
+
+1.3 “Licensee” refers to any person, organization, or system that accesses, uses, modifies, redistributes, or incorporates the Dataset.
+
+1.4 “Model” refers to any machine learning system, artificial intelligence system, algorithm, statistical model, or computational process trained, fine‑tuned, evaluated, or otherwise developed using the Dataset.
+
+1.5 “Public Notice” refers to a clear, visible, and publicly accessible statement acknowledging use of the Dataset.
+
+1.6 “Derivative Dataset” refers to any dataset created by modifying, transforming, filtering, augmenting, or otherwise altering the original Dataset.
+
+1.7 “Derivative Model” refers to any Model whose training data includes the Dataset or any Derivative Dataset.
+
+--------------------------------------------------------------------
+SECTION 2 — GRANT OF RIGHTS
+--------------------------------------------------------------------
+2.1 The Licensor grants the Licensee a worldwide, royalty‑free, non‑exclusive, irrevocable permission to:
+- Use, copy, and redistribute the Dataset for any purpose.
+- Modify, transform, or build upon the Dataset.
+- Create Derivative Datasets.
+- Train, fine‑tune, evaluate, or otherwise use the Dataset for machine learning or AI development.
+- Create Derivative Models based on the Dataset.
+
+2.2 These rights are intended to be compatible with open‑source and open‑data principles, including but not limited to CC‑BY, ODC‑BY, and other permissive data licenses.
+
+2.3 No patent rights are granted or implied by this License.
+
+--------------------------------------------------------------------
+SECTION 3 — MANDATORY ATTRIBUTION
+--------------------------------------------------------------------
+3.1 Any public use, redistribution, publication, or derivative work involving the Dataset must include the following attribution:
+
+“This work uses data provided under the Open Data Attribution Training Disclosure License (ODATL‑1.0).”
+
+3.2 Attribution must appear in:
+- Documentation
+- Research papers
+- Model cards
+- Public datasets
+- Product descriptions
+- Any public‑facing material referencing the Dataset
+
+3.3 Attribution must remain intact and may not be removed, obscured, or altered.
+
+--------------------------------------------------------------------
+SECTION 4 — MANDATORY TRAINING DISCLOSURE
+--------------------------------------------------------------------
+4.1 If the Dataset is used to train, fine‑tune, evaluate, or otherwise develop any Model, the Licensee must provide a Public Notice stating:
+
+“This model was trained using data provided under the Open Data Attribution Training Disclosure License (ODATL‑1.0).”
+
+4.2 This disclosure must appear in:
+- Model cards
+- Public releases of the Model
+- Research publications
+- Technical documentation
+- Product descriptions
+- Any public announcement or description of the Model
+
+4.3 Disclosure must be truthful, visible, and accessible to the general public.
+
+4.4 Failure to provide this disclosure immediately terminates all rights granted under this License.
+
+--------------------------------------------------------------------
+SECTION 5 — REDISTRIBUTION REQUIREMENTS
+--------------------------------------------------------------------
+5.1 If the Licensee redistributes the Dataset or any Derivative Dataset, the Licensee must:
+- Include this License in full.
+- Clearly indicate any modifications made.
+- Preserve all attribution and disclosure requirements.
+
+5.2 Derivative Datasets may be dual‑licensed under other open‑data licenses, provided this License remains included and enforceable.
+
+--------------------------------------------------------------------
+SECTION 6 — OPEN‑SOURCE COMPATIBILITY
+--------------------------------------------------------------------
+6.1 This License is designed to be compatible with:
+- Open Data Commons Attribution (ODC‑BY)
+- Creative Commons Attribution (CC‑BY)
+- Open‑source AI research workflows
+- Open‑data distribution platforms
+
+6.2 Redistribution through open‑source repositories (e.g., GitHub, HuggingFace, Kaggle) is permitted and encouraged.
+
+6.3 Licensees may combine the Dataset with other open datasets, provided attribution and training disclosure obligations remain intact.
+
+--------------------------------------------------------------------
+SECTION 7 — PROHIBITED USES
+--------------------------------------------------------------------
+7.1 The Licensee may not:
+- Claim exclusive ownership of the Dataset.
+- Remove or alter attribution or disclosure requirements.
+- Use the Dataset in violation of applicable laws or regulations.
+- Misrepresent the origin, nature, or licensing of the Dataset.
+
+7.2 The Licensee may not apply technical or legal measures that restrict others from exercising rights granted under this License.
+
+--------------------------------------------------------------------
+SECTION 8 — NO WARRANTY
+--------------------------------------------------------------------
+8.1 The Dataset is provided “as‑is,” without warranty of any kind, express or implied.
+
+8.2 The Licensor is not liable for any damages, losses, or claims arising from use of the Dataset or any Derivative Model.
+
+--------------------------------------------------------------------
+SECTION 9 — TERMINATION
+--------------------------------------------------------------------
+9.1 Rights under this License automatically terminate if the Licensee:
+- Fails to provide required attribution.
+- Fails to provide required training disclosure.
+- Violates any other term of this License.
+
+9.2 Rights may be reinstated upon correction of the violation, unless the Licensor explicitly revokes permission.
+
+--------------------------------------------------------------------
+SECTION 10 — ACCEPTANCE
+--------------------------------------------------------------------
+10.1 By accessing or using the Dataset, the Licensee agrees to be bound by the terms of this License.
+
+10.2 Continued use of the Dataset constitutes ongoing acceptance of all terms.
+
+--------------------------------------------------------------------
+SECTION 11 — CONTACT
+--------------------------------------------------------------------
+11.1 For permissions beyond this License, contact the Licensor.

README.md

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+---
+license: other
+license_name: open-data-attribution-training-disclosure-license-odatl-1.0
+license_link: LICENSE
+language:
+- en
+tags:
+- math
+---
+# Math Teaching Dataset - 100MB / 735k Rows
+
+A large math dataset designed for training and fine-tuning AI models with step-by-step reasoning.
+
+## Files
+
+- `math_dataset_100MB.csv` - Full dataset, 100.33 MB, 735,000 rows
+- `math_dataset_100MB.csv.gz` - Compressed version, 18.95 MB
+- `splits/math_part_1.csv` to `math_part_10.csv` - 10 x ~10MB chunks
+
+## Dataset Stats
+
+- **Total rows:** 735,000
+- **Size:** 100.33 MB raw, 18.95 MB gzipped
+- **Format:** CSV, UTF-8, with header
+
+### Topic Distribution
+
+| Topic | Count | Description |
+|-------|-------|-------------|
+| arithmetic | 184,304 | Addition, subtraction, multiplication, division, order of operations |
+| algebra | 91,880 | Linear equations and quadratics |
+| calculus | 91,675 | Basic derivatives and integrals |
+| geometry | 46,373 | Area and perimeter of rectangles, circles, triangles |
+| exponents | 46,303 | Powers |
+| word_problems | 45,929 | Applied addition problems |
+| statistics | 45,920 | Mean / average |
+| percentages | 45,857 | Percentage calculations |
+| number_theory | 45,789 | GCD and LCM |
+| roots | 45,567 | Square roots |
+| fractions | 45,403 | Fraction addition, subtraction, multiplication |
+
+### Difficulty
+- `easy` - single-step problems
+- `medium` - multi-step problems
+
+## Schema
+
+| Column | Type | Description |
+|--------|------|-------------|
+| `id` | int | Unique row ID |
+| `topic` | string | High-level topic |
+| `difficulty` | string | easy or medium |
+| `question` | string | The math problem |
+| `answer` | string | Final answer |
+| `reasoning` | string | Step-by-step explanation |
+| `category` | string | Specific sub-type of problem |
+
+## Example Rows
+
+"What is 1900 / 5?" -> Answer: 380
+Reasoning: "Divide: 1900 ÷ 5 = 380 because 5*380=1900."
+
+"Solve for x: 12x + 15 = 87" -> Answer: 6
+Reasoning: "Subtract 15 from both sides: 12x = 72. Then divide by 12: x = 6."
+
+"What is 3/4 + 2/5?" -> Answer: "23/20"
+Reasoning: "Common denominator 20. 3/4=15/20, 2/5=8/20. Sum = 23/20."
+
+"What is the derivative of 7x^5 with respect to x?" -> Answer: "35x^4"
+Reasoning: "Power rule: d/dx [x^n] = n*x^(n-1). So 7*5*x^4 = 35x^4."
+
+## Intended Use
+
+Built for instruction tuning and chain-of-thought training.
+
+Recommended training format:
+Input: {question}
+Target: {reasoning} Answer: {answer}
+
+Works for:
+- Fine-tuning language models for math reasoning
+- Teaching step-by-step problem solving
+- Evaluating math capabilities
+- Data augmentation alongside other math datasets
+
+## License
+
+open-data-attribution-training-disclosure-license-odatl-1.0

math_dataset_100MB.csv

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