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Update dataset card: 6MT-3digit (0-999), remove 5MT-3digit

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  1. README.md +10 -11
README.md CHANGED
@@ -12,30 +12,30 @@ configs:
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  data_files:
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  - split: train
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  path: 10BT/train-*.parquet
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- - config_name: 5MT-3digit
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  data_files:
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  - split: train
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- path: 5MT-3digit/train-*.parquet
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  - split: test
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- path: 5MT-3digit/test-*.parquet
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  ---
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  # Addition Dataset
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- Addition problems in the format `{a} + {b} = {c}` where operands have stratified digit counts (1-9 digits, uniformly sampled).
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  ## Subsets
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  - **test**: 5K held-out evaluation examples (operands >= 10, i.e. min 2 digits)
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  - **1BT**: ~85M training examples (~1 billion tokens under Llama-3 tokenizer)
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  - **10BT**: ~850M training examples (~10 billion tokens)
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- - **5MT-3digit**: Exhaustive 3-digit addition (all 900x900 = 810K ordered pairs, ~5.35M tokens). Symmetry-safe train/test split (10% test).
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  ## Deduplication
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- - Commutative dedup: if `a + b = c` exists, `b + a = c` is excluded
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  - Test exclusion: both orderings of test-set pairs are excluded from train splits
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- - 5MT-3digit: both orderings always in the same split (no commutative leakage)
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  ## Usage
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@@ -43,10 +43,9 @@ Addition problems in the format `{a} + {b} = {c}` where operands have stratified
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  from datasets import load_dataset
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  train = load_dataset("deqing/addition_dataset", "1BT", split="train")
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- train_10b = load_dataset("deqing/addition_dataset", "10BT", split="train")
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  test = load_dataset("deqing/addition_dataset", "test", split="test")
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- # 3-digit exhaustive
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- train_3d = load_dataset("deqing/addition_dataset", "5MT-3digit", split="train")
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- test_3d = load_dataset("deqing/addition_dataset", "5MT-3digit", split="test")
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  ```
 
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  data_files:
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  - split: train
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  path: 10BT/train-*.parquet
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+ - config_name: 6MT-3digit
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  data_files:
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  - split: train
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+ path: 6MT-3digit/train-*.parquet
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  - split: test
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+ path: 6MT-3digit/test-*.parquet
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  ---
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  # Addition Dataset
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+ Addition problems in the format `{a} + {b} = {c}`.
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  ## Subsets
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  - **test**: 5K held-out evaluation examples (operands >= 10, i.e. min 2 digits)
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  - **1BT**: ~85M training examples (~1 billion tokens under Llama-3 tokenizer)
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  - **10BT**: ~850M training examples (~10 billion tokens)
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+ - **6MT-3digit**: Exhaustive 0-999 addition (all 1000x1000 = 1M ordered pairs, ~6.5M tokens). Symmetry-safe train/test split (10% test).
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  ## Deduplication
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+ - Commutative dedup: if `a + b = c` exists, `b + a = c` is excluded (1BT/10BT)
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  - Test exclusion: both orderings of test-set pairs are excluded from train splits
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+ - 6MT-3digit: both orderings always in the same split (no commutative leakage)
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  ## Usage
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  from datasets import load_dataset
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  train = load_dataset("deqing/addition_dataset", "1BT", split="train")
 
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  test = load_dataset("deqing/addition_dataset", "test", split="test")
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+ # 3-digit exhaustive (0-999)
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+ train_3d = load_dataset("deqing/addition_dataset", "6MT-3digit", split="train")
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+ test_3d = load_dataset("deqing/addition_dataset", "6MT-3digit", split="test")
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  ```