Sys2Rreasoning 100000 contains 100,000 synthetic algebra-heavy math reasoning problems. The dataset, created by xortron, includes fields for question, problem, how_to_solve, and answer.
Use Cases
- Train a sequence-to-sequence model on the question and answer fields to generate algebraic solutions.
- Analyze the how_to_solve text to classify common reasoning strategies for algebra problems.
- Use the problem descriptions to benchmark the logical consistency of large language models.
- Fine-tune a model to predict answer correctness from the provided how_to_solve steps.
Strengths
- Contains 100,000 entries, providing substantial scale for training.
- Includes four distinct data fields (question, problem, how_to_solve, answer) per entry.
- Focuses on algebra-heavy math reasoning, a specific and challenging domain.
Limitations
- Data is synthetic, which may not fully capture the complexity or distribution of real-world math problems.
- Unknown row and column counts beyond the stated 100,000 entries limit detailed structural assessment.
- Lacks metadata on problem difficulty levels or solution verification methods.
Provenance
- Source
- huggingface, author xortron
- Collection Method
- Synthetic data generation
- Time Range
- null
- Freshness
- Last updated on 2026-01 02.
- Geography
- null