README.md

metadata

license: mit
task_categories:
  - text-generation
  - mathematical-modeling
language:
  - en
tags:
  - math
  - transformer
  - symbolic-math
  - jax
  - arithmetic
size_categories:
  - 100M-1B

Transformer Math Dataset (250,000,000 Samples Sharded)

High-precision synthetic mathematical expression dataset generated for training sequence-to-sequence math Transformers in JAX/Flax.

Dataset Structure

• Total Samples: 250,000,000
• Shard Format: JSONL sharded files (100,000 samples per shard)
• Supported Operations: +, -, *, /, ^, sin, cos, tan, log, ln, exp, sqrt, abs
• Expression Depth Range: Depth 4 to 6
• Integer Operand Ratio: 20%

Data Fields

Each line in the .jsonl shard files is a JSON object with the following fields:

• expr (str): Syntactically valid mathematical expression (e.g. "sin((3.5))+cos((1.2))")
• val (str): Target evaluated numerical result formatted to precision (e.g. "0.6")
• category (str): Operation-depth category bucket (e.g. "sin_d4")
• ops_used (list[str]): List of mathematical functions/operators present in the expression (e.g. ["sin", "+", "cos"])

Usage Example

from datasets import load_dataset

dataset = load_dataset("saidurga001301/mathmetics-dataset-float-long", streaming=True)
for sample in dataset["train"]:
    print(sample["expr"], "->", sample["val"], "ops:", sample["ops_used"])
    break