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deqing/addition_dataset

Addition Dataset Addition problems in the format {a} + {b} = {c}. Subsets test: 5K held-out evaluation examples (operands >= 10, i.e. min 2 digits) 1BT: 85M training examples (1 billion tokens under Llama-3 tokenizer) 10BT: 850M training examples (10 billion tokens) 3MT-3digit: Exhaustive single-token addition: all (a, b) with a, b in [0, 999] and a+b <= 999. 500,500 ordered pairs, ~3M tokens. All of a, b, c are single tokens. Symmetry-safe train/test split (10%… See the full description on the dataset page: https://huggingface.co/datasets/deqing/addition_dataset.

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Addition Dataset

Addition problems in the format {a} + {b} = {c}.

Subsets

  • —test: 5K held-out evaluation examples (operands >= 10, i.e. min 2 digits)
  • —1BT: ~85M training examples (~1 billion tokens under Llama-3 tokenizer)
  • —10BT: ~850M training examples (~10 billion tokens)
  • —3MT-3digit: Exhaustive single-token addition: all (a, b) with a, b in [0, 999] and a+b <= 999. 500,500 ordered pairs, ~3M tokens. All of a, b, c are single tokens. Symmetry-safe train/test split (10% test).

Deduplication

  • —Commutative dedup: if a + b = c exists, b + a = c is excluded (1BT/10BT)
  • —Test exclusion: both orderings of test-set pairs are excluded from train splits
  • —3MT-3digit: both orderings always in the same split (no commutative leakage)

Usage

python
from datasets import load_dataset

train = load_dataset("deqing/addition_dataset", "1BT", split="train")
test = load_dataset("deqing/addition_dataset", "test", split="test")

# Single-token exhaustive (0-999, a+b<=999)
train_3d = load_dataset("deqing/addition_dataset", "3MT-3digit", split="train")
test_3d = load_dataset("deqing/addition_dataset", "3MT-3digit", split="test")