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README.md CHANGED
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  ---
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  license: apache-2.0
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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  license: apache-2.0
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+ task_categories:
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+ - text-generation
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+ language:
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+ - id
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+ - en
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+ tags:
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+ - math
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+ - reasoning
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+ - cot
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+ - tool-use
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+ - code-interpreter
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+ - engineering
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+ - quantitative-finance
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+ - olympic-math
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+ size_categories:
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+ - 100K<n<1M
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: data/train-*
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+ - split: validation
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+ path: data/validation-*
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  ---
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+
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+ # Lumina-Math-Repository (Lumina-Math-Foundation-V2)
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+
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+ Lumina-Math-Foundation-V2 is a massive, high-density mathematical and engineering reasoning dataset comprising **500,000 training instances** and **5,100 validation instances** uniformly spanning **255 specialized domain batches**.
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+
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+ Designed specifically for **Modular Tool-Integrated Reasoning (Code-Interpreter)**, each instance cleanly isolates conceptual mathematical reasoning from executable Python verification code, execution output, and final formal solutions.
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+
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+ ## Key Highlights
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+ - **100% Non-Trivial Ground Truth:** Every mathematical derivation and industrial design equation adheres to real engineering and academic standards (ASME, AISC, SNI, Uniswap v3 / Curve invariants, Calabi-Yau 3-folds, and GPU Roofline performance models). No toy formulas or dummy math.
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+ - **Modular Tool-Integrated Reasoning (Code-Interpreter):**
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+ - `thought`: Pure conceptual mathematical thinking and planning before code execution. Free of artificial phase markers or sycophancy.
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+ - `code`: Deterministic, executable Python verification script (clean code without decorative ASCII boxes or curriculum fluff).
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+ - `code_output`: Deterministic runtime / assertion confirmation.
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+ - `thought_2`: Post-execution synthesis evaluating computational verification against analytical derivation.
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+ - `solution`: Clean formal mathematical solution with unnumbered, standard headings (`Langkah Penyelesaian` & `Jawaban Akhir`).
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+ - **Multi-Mode Reasoning Velocity:**
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+ - **Short (~25%):** High-velocity derivation directly yielding the target answer.
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+ - **Medium (~50%):** Standard balanced Chain-of-Thought (CoT) diagnostic and step-by-step resolution.
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+ - **Long (~25%):** Comprehensive axiomatic derivation exploring boundary cases and formal verification.
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+ - **Balanced 255-Batch Coverage:**
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+ - Training set: ~1,960 - 1,961 records per batch across all 255 batches.
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+ - Validation set: Exactly 20 records per batch across all 255 batches ($255 \times 20 = 5,100$). Disjoint seed space guarantees zero data contamination.
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+ - **Direct Parquet Format:** Compact, columnar, and immediately queryable through the Hugging Face Dataset Viewer and `datasets.load_dataset`.
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+
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+ ## Dataset Structure
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+
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+ ### Features
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+ | Column | Type | Description |
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+ |---|---|---|
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+ | `id` | string | Unique deterministic record identifier |
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+ | `domain` | string | Specialized domain classification |
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+ | `topic` | string | Specific mathematical/engineering topic |
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+ | `mode` | string | Reasoning mode (`short`, `medium`, `long`) |
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+ | `problem` | string | Clean problem statement / prompt |
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+ | `thought` | string | Conceptual mathematical reasoning before code execution |
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+ | `code` | string | Deterministic executable Python verification script |
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+ | `code_output` | string | Execution output / assertion verification |
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+ | `thought_2` | string | Post-execution synthesis reasoning |
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+ | `solution` | string | Clean formal solution dossier (`Langkah Penyelesaian` & `Jawaban Akhir`) |
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+ | `final_answer` | string | Extracted scalar/expression answer |
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+ | `boxed_answer` | string | LaTeX boxed representation `\boxed{...}` |
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+
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+ ## Usage
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+ ```python
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+ from datasets import load_dataset
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+
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+ ds = load_dataset("cloverx-id/Lumina-Math-Repository")
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+ print(ds["train"][0])
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+ print(ds["validation"][0])
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+ ```
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