---
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

```python
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
```