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Datasets:
nkthebass
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tinybrainbot-3m-math-data

Tasks:
Text Generation
Modalities:
Text
Formats:
parquet
Languages:
English
Size:
10M - 100M
Tags:
math
arithmetic
Synthetic
pretraining
small-language-models
Libraries:
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Dask
Polars
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metadata 
license: apache-2.0
language:
  - en
task_categories:
  - text-generation
tags:
  - math
  - arithmetic
  - synthetic
  - pretraining
  - small-language-models
size_categories:
  - 100M<n<1B
configs:
  - config_name: math-story
    data_files:
      - split: train
        path: data/math-story/*.parquet
  - config_name: math-rel
    data_files:
      - split: train
        path: data/math-rel/*.parquet
  - config_name: math-rel-nf
    data_files:
      - split: train
        path: data/math-rel-nf/*.parquet
  - config_name: math-am-nf
    data_files:
      - split: train
        path: data/math-am-nf/*.parquet
  - config_name: math-am2-nf
    data_files:
      - split: train
        path: data/math-am2-nf/*.parquet
  - config_name: math-am3
    data_files:
      - split: train
        path: data/math-am3/*.parquet
  - config_name: math-am3-nf
    data_files:
      - split: train
        path: data/math-am3-nf/*.parquet
  - config_name: math-frames
    data_files:
      - split: train
        path: data/math-frames/*.parquet
  - config_name: math-frames2
    data_files:
      - split: train
        path: data/math-frames2/*.parquet
  - config_name: math-frames2w
    data_files:
      - split: train
        path: data/math-frames2w/*.parquet
  - config_name: math-frames3
    data_files:
      - split: train
        path: data/math-frames3/*.parquet
  - config_name: math-topics
    data_files:
      - split: train
        path: data/math-topics/*.parquet
  - config_name: math-topics-frames
    data_files:
      - split: train
        path: data/math-topics-frames/*.parquet
  - config_name: math-expr
    data_files:
      - split: train
        path: data/math-expr/*.parquet
  - config_name: math-words
    data_files:
      - split: train
        path: data/math-words/*.parquet
  - config_name: math-formats
    data_files:
      - split: train
        path: data/math-formats/*.parquet
  - config_name: math-ws
    data_files:
      - split: train
        path: data/math-ws/*.parquet
  - config_name: math-neg
    data_files:
      - split: train
        path: data/math-neg/*.parquet
  - config_name: math-v8
    data_files:
      - split: train
        path: data/math-v8/*.parquet

TinyBrainBot 3M math data

Every arithmetic dataset used to train the TinyBrainBot 3M math models (the 3M-Base punch runs and 3M-Loop series). "Used by" names the public nkthebass/tinybrainbot-* models. Each set is its own folder / config:

from datasets import load_dataset
ds = load_dataset("nkthebass/tinybrainbot-3m-math-data", "math-expr", split="train")

Every number and answer is computed in Python. Where a set uses LLM-written sentence frames, the LLM only wrote the wording with placeholders; the numbers were filled in and solved by Python. No benchmark train or test data is included.

Config What it is How it was made Used by Text Rows
math-story Story arithmetic in many sentence shapes: add/subtract, groups, sharing, money, time, measurement, area/perimeter, fractions, patterns, tallies tiny3m/gen_math_story.py (Python templates) 3m-base, 3m-loop, 3m-loop-v2, 3m-loop-v3, 3m-loop-v4 6000M 13,963,297
math-rel Relational arithmetic: 'X is 30 cm taller than Y', older/younger, more/fewer, with the result stated Python templates 3m-loop, 3m-loop-v2, 3m-loop-v3, 3m-loop-v4 1200M 1,643,821
math-rel-nf math-rel without the worked numbers in brackets Python templates 3m-loop, 3m-loop-v2, 3m-loop-v3 1200M 1,641,096
math-am-nf ArithMark-1-style word problems (built to resemble ArithMark phrasing - see notes) Python templates 3m-base (punch), early 3M-Loop runs 1200M 2,432,712
math-am2-nf ArithMark-2-style problems (built to resemble ArithMark phrasing - see notes) Python templates early 3M-Loop runs 1200M 2,407,200
math-am3 ArithMark-3-style continuations (built to resemble ArithMark phrasing - see notes) Python templates early 3M-Loop runs 1200M 2,440,467
math-am3-nf math-am3 without worked steps Python templates early 3M-Loop runs 1200M 2,404,970
math-frames Story problems in LLM-written sentence frames; every number filled in and computed by Python tiny3m/gen_math_frames.py, frames by Ling-3.0-Flash an early 3M-Loop run 2640M 2,524,390
math-frames2 Same idea, two writer families frames by Ling-3.0-Flash + Mistral-Small-3.2 3m-loop 3795M 3,772,927
math-frames2w math-frames2 with numbers written as words frames by Ling-3.0-Flash + Mistral-Small-3.2 3m-loop-v2, 3m-loop-v3, 3m-loop-v4 1650M 1,566,265
math-frames3 More frames, plus optional irrelevant-number distractors frames by Ling-3.0-Flash + Mistral Nemo 3m-loop-v4 1980M 1,825,387
math-topics 23 grade-school topics ArithMark-3 lacks: remainders, unit conversion, elapsed time, days of the week, rounding, place value, fractions, percent, averages, 3-step, dozen, odd/even, multiples, money in words tiny3m/gen_math_topics.py (Python templates) 3m-loop-v4 690M 1,162,281
math-topics-frames The topics above in LLM-written frames tiny3m/gen_math_frames.py --skills topics 3m-loop-v4 1155M 1,181,300
math-expr Bare expressions: order of operations, parentheses, negatives, 2-5 operands, ~19 forms tiny3m/gen_math_expr.py 3m-loop-v2, 3m-loop-v3, 3m-loop-v4 1560M 3,381,454
math-words Numbers written as words, both directions, inside sums and comparisons tiny3m/gen_math_words.py 3m-loop-v2, 3m-loop-v3, 3m-loop-v4 680M 1,066,765
math-formats Large numbers, thousands commas, money, decimals, mixed into short stories tiny3m/gen_math_formats.py 3m-loop-v3, 3m-loop-v4 1920M 1,682,618
math-ws Whitespace variants before numbers (double spaces, tabs, newlines) tiny3m/gen_math_ws.py 3m-loop-v4 1200M 1,580,637
math-neg Negative numbers: 8 sign shapes, temperatures, comparisons tiny3m/gen_math_neg.py 3m-loop-v4 300M 501,552
math-v8 Unknown positions (? + 5 = 12), irrelevant-detail distractors, layouts, sequences, small tables, comparisons tiny3m/gen_math_v8.py 3m-loop-v4 1610M 2,180,515

Notes from training with it

  • math-am* were built to resemble ArithMark phrasing. They raise ArithMark scores much more than arithmetic in other wordings (a 3M on one phrasing family solved 99% in that phrasing and 10-30% elsewhere). They were dropped after the early 3M-Loop runs.
  • Story-style sets (math-story, math-frames*) lift ArithMark-3 about 3x faster than held-out arithmetic. Our later general models use only a pinch of them.
  • math-topics / math-topics-frames cover skills ArithMark-3 does not test. Training on them also inflates any test built from the same generator, so evaluate with held-out wordings.
  • math-ws exists because lm-eval's default target delimiter adds a second space before the answer; models that never saw that collapsed on it.

License

Apache-2.0. Frames were written by Ling-3.0-Flash (inclusionAI), Mistral-Small-3.2 and Mistral Nemo (Mistral AI); all numbers and answers were generated by our own Python code.