Dataset Viewer (First 5GB)
Auto-converted to Parquet Duplicate
expr
string
val
string
category
string
ops_used
list
(-43)+(-48)
-91
+_d1
[ "-", "+" ]
2+2
4
+_d2
[ "+" ]
(13+18)+(abs(log(35.8)))
34.6
+_d3
[ "+", "abs", "log" ]
49-(-14)
63
-_d1
[ "-" ]
(-18)-7
-25
-_d2
[ "-" ]
(ln(sqrt(17.8)))-((-8)/(-11))
0.7
-_d3
[ "ln", "sqrt", "-", "/" ]
(-8)*9
-72
*_d1
[ "-", "*" ]
(-18)*8
-144
*_d2
[ "-", "*" ]
(abs(sqrt(73.3)))*(abs(sin(-3.9)))
5.9
*_d3
[ "abs", "sqrt", "*", "sin", "-" ]
(-27)/9
-3
/_d1
[ "-", "/" ]
1/(-7)
-0.1
/_d2
[ "/", "-" ]
((abs(-9)+0.1)^-1)/(17^3)
0
/_d3
[ "abs", "-", "+", "^", "/" ]
5^(-2)
0
^_d1
[ "^", "-" ]
(abs(-17)+0.1)^3
5000.2
^_d2
[ "abs", "-", "+", "^" ]
(2^-2)^2
0.1
^_d3
[ "^", "-" ]
sin(2.6)
0.5
sin_d1
[ "sin" ]
sin(3^2)
0.4
sin_d2
[ "sin", "^" ]
sin((-7)-18)
0.1
sin_d3
[ "sin", "-" ]
cos(-4.1)
-0.6
cos_d1
[ "cos", "-" ]
cos((-36)+6)
0.2
cos_d2
[ "cos", "-", "+" ]
cos(log(abs(cos(2.3))+0.1))
1
cos_d3
[ "cos", "log", "abs", "+" ]
tan(1.5)
14.1
tan_d1
[ "tan" ]
tan(sin(log(37.7)))
-0.5
tan_d2
[ "tan", "sin", "log" ]
tan(sin((-16)-3))
-0.2
tan_d3
[ "tan", "sin", "-" ]
log(34.4)
3.5
log_d1
[ "log" ]
log(abs(sin(3.2))+0.1)
-1.8
log_d2
[ "log", "abs", "sin", "+" ]
log(19-0)
2.9
log_d3
[ "log", "-" ]
ln(46.6)
3.8
ln_d1
[ "ln" ]
ln(tan(-2.9))
-1.4
ln_d2
[ "ln", "tan", "-" ]
ln(abs((-9)-(-7))+0.1)
0.7
ln_d3
[ "ln", "abs", "-", "+" ]
exp(2.9)
18.2
exp_d1
[ "exp" ]
exp(sin((-2)-(-49)))
1.1
exp_d2
[ "exp", "sin", "-" ]
exp(tan(sin(1.3)))
4.2
exp_d3
[ "exp", "tan", "sin" ]
sqrt(55.2)
7.4
sqrt_d1
[ "sqrt" ]
sqrt(exp(-2.6))
0.3
sqrt_d2
[ "sqrt", "exp", "-" ]
sqrt(sqrt(abs((-48)+(-10))))
2.8
sqrt_d3
[ "sqrt", "abs", "-", "+" ]
abs(-52)
52
abs_d1
[ "abs", "-" ]
abs(sqrt(80.8))
9
abs_d2
[ "abs", "sqrt" ]
abs(13+20)
33
abs_d3
[ "abs", "+" ]
28+(-26)
2
+_d1
[ "+", "-" ]
10+11
21
+_d2
[ "+" ]
(6-12)+(sin(10/10))
-5.2
+_d3
[ "-", "+", "sin", "/" ]
(-22)-(-41)
19
-_d1
[ "-" ]
19-(-13)
32
-_d2
[ "-" ]
(4-(-13))-(15*6)
-73
-_d3
[ "-", "*" ]
1*5
5
*_d1
[ "*" ]
17*(-20)
-340
*_d2
[ "*", "-" ]
((abs(-16)+0.1)^1)*((abs(-19)+0.1)^3)
112182.7
*_d3
[ "abs", "-", "+", "^", "*" ]
23/(-4)
-5.8
/_d1
[ "/", "-" ]
2/(-14)
-0.1
/_d2
[ "/", "-" ]
(abs(cos(-3.6)))/(8^3)
0
/_d3
[ "abs", "cos", "-", "/", "^" ]
3^1
3
^_d1
[ "^" ]
(abs(-13)+0.1)^3
2248.1
^_d2
[ "abs", "-", "+", "^" ]
(abs(sqrt(49.7)))^2
49.7
^_d3
[ "abs", "sqrt", "^" ]
sin(-5.8)
0.5
sin_d1
[ "sin", "-" ]
sin(ln(4.9))
1
sin_d2
[ "sin", "ln" ]
sin(ln(abs((-28)+(-48))+0.1))
-0.9
sin_d3
[ "sin", "ln", "abs", "-", "+" ]
cos(3.8)
-0.8
cos_d1
[ "cos" ]
cos(exp(-1.7))
1
cos_d2
[ "cos", "exp", "-" ]
cos(19*(-5))
0.7
cos_d3
[ "cos", "*", "-" ]
tan(-0.4)
-0.4
tan_d1
[ "tan", "-" ]
tan(sin(4.7))
-1.6
tan_d2
[ "tan", "sin" ]
tan(sin((abs(-8)+0.1)^2))
0.4
tan_d3
[ "tan", "sin", "abs", "-", "+", "^" ]
log(5.6)
1.7
log_d1
[ "log" ]
log(tan(0.7))
-0.2
log_d2
[ "log", "tan" ]
log(6*9)
4
log_d3
[ "log", "*" ]
ln(32.7)
3.5
ln_d1
[ "ln" ]
ln(sin(-4.3))
-0.1
ln_d2
[ "ln", "sin", "-" ]
ln(abs(sin(4.9)))
0
ln_d3
[ "ln", "abs", "sin" ]
exp(-1.7)
0.2
exp_d1
[ "exp", "-" ]
exp(sin(14/(-2)))
0.5
exp_d2
[ "exp", "sin", "/", "-" ]
exp(cos(abs(96)))
0.8
exp_d3
[ "exp", "cos", "abs" ]
sqrt(35.6)
6
sqrt_d1
[ "sqrt" ]
sqrt(5^3)
11.2
sqrt_d2
[ "sqrt", "^" ]
sqrt(exp(sin((-24)-(-39))))
1.4
sqrt_d3
[ "sqrt", "exp", "sin", "-" ]
abs(-91)
91
abs_d1
[ "abs", "-" ]
abs(1^1)
1
abs_d2
[ "abs", "^" ]
abs((-11)/11)
1
abs_d3
[ "abs", "-", "/" ]
37+9
46
+_d1
[ "+" ]
(-3)+(-8)
-11
+_d2
[ "-", "+" ]
(7+3)+((-6)+19)
23
+_d3
[ "+", "-" ]
15-(-21)
36
-_d1
[ "-" ]
(-11)-(-2)
-9
-_d2
[ "-" ]
(9-(-3))-(7+20)
-15
-_d3
[ "-", "+" ]
(-9)*7
-63
*_d1
[ "-", "*" ]
(-5)*(-17)
85
*_d2
[ "-", "*" ]
(log(sqrt(8)))*(exp(sin((-12)+(-48))))
1.4
*_d3
[ "log", "sqrt", "*", "exp", "sin", "-", "+" ]
14/6
2.3
/_d1
[ "/" ]
(-12)/10
-1.2
/_d2
[ "-", "/" ]
(sqrt(ln(24)))/(1)
1.8
/_d3
[ "sqrt", "ln", "/" ]
2^1
2
^_d1
[ "^" ]
(abs(-4)+0.1)^-2
0.1
^_d2
[ "abs", "-", "+", "^" ]
(abs(-20)+0.1)^1
20.1
^_d3
[ "abs", "-", "+", "^" ]
sin(4.5)
-1
sin_d1
[ "sin" ]
sin(cos(-2.4))
-0.7
sin_d2
[ "sin", "cos", "-" ]
sin((-14)/11)
-1
sin_d3
[ "sin", "-", "/" ]
cos(-4)
-0.7
cos_d1
[ "cos", "-" ]
cos((-49)+33)
-1
cos_d2
[ "cos", "-", "+" ]
cos(abs(sin(-1)))
0.7
cos_d3
[ "cos", "abs", "sin", "-" ]
tan(-6.1)
0.2
tan_d1
[ "tan", "-" ]
End of preview. Expand in Data Studio

YAML Metadata Warning:The task_categories "mathematical-modeling" is not in the official list: text-classification, token-classification, table-question-answering, question-answering, zero-shot-classification, translation, summarization, feature-extraction, text-generation, fill-mask, sentence-similarity, text-to-speech, text-to-audio, automatic-speech-recognition, audio-to-audio, audio-classification, audio-text-to-text, voice-activity-detection, depth-estimation, image-classification, object-detection, image-segmentation, text-to-image, image-to-text, image-to-image, image-to-video, unconditional-image-generation, video-classification, reinforcement-learning, robotics, tabular-classification, tabular-regression, tabular-to-text, table-to-text, multiple-choice, text-ranking, text-retrieval, time-series-forecasting, text-to-video, image-text-to-text, image-text-to-image, image-text-to-video, visual-question-answering, document-question-answering, zero-shot-image-classification, graph-ml, mask-generation, zero-shot-object-detection, text-to-3d, image-to-3d, image-feature-extraction, video-text-to-text, keypoint-detection, visual-document-retrieval, any-to-any, video-to-video, other

Transformer Math Dataset (54,000,000 Samples Sharded)

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

Dataset Structure

  • Total Samples: 54,000,000
  • Shard Format: JSONL sharded files (100,000 samples per shard)
  • Supported Operations: +, -, *, /, ^, sin, cos, tan, log, ln, exp, sqrt, abs
  • Expression Depth Range: Depth 1 to 2
  • Integer Operand Ratio: 0%

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-custom", streaming=True)
for sample in dataset["train"]:
    print(sample["expr"], "->", sample["val"], "ops:", sample["ops_used"])
    break
Downloads last month
999