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hybrid-diff-ar
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olmo-data-160B

Tasks:
Text Generation
Languages:
English
Tags:
pretraining
olmo
olmo-core
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  1. README.md +85 -0
  2. eval-data/perplexity/v3_small_dolma2-tokenizer/c4_en/val/part-0-00000.npy +3 -0
  3. eval-data/perplexity/v3_small_dolma2-tokenizer/dolma_stack/val/part-0-00000.npy +3 -0
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  49. subset_plan.tsv +51 -0
  50. train_files.txt +50 -0
README.md ADDED
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+ ---
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+ license: odc-by
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+ pretty_name: OLMoE-mix-0824 160B-token subset (dolma2 tokenizer)
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+ language:
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+ - en
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+ task_categories:
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+ - text-generation
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+ tags:
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+ - pretraining
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+ - olmo
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+ - olmo-core
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+ ---
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+
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+ # OLMoE-mix-0824, 160B-token subset (dolma2-tokenized)
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+
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+ > A larger sibling of [hybrid-diff-ar/olmo-data-50B](https://huggingface.co/datasets/hybrid-diff-ar/olmo-data-50B)
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+ > (same sampling, same seed): every whole file there is also here, and its 7 partial (`*.prefix*`)
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+ > files are replaced by longer extents.
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+
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+ A 160.0B-token, source-proportional subset of **OLMoE-mix-0824**, the pretraining mix of the
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+ standard OLMo2 model ladder in [OLMo-core](https://github.com/allenai/OLMo-core) (≤ v2.4.0,
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+ `src/scripts/train/OLMo2/OLMo2-ladder.py`). It also includes the full
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+ **v3-small perplexity validation sets** used by that ladder. Everything is pre-tokenized with
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+ the `allenai/dolma2-tokenizer` and laid out exactly like `http://olmo-data.org`, so OLMo-core can
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+ read it with `mix_base_dir` / `--data-root` pointed at a local download of this repo.
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+
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+ 160B tokens covers a 10×Chinchilla run of the 600M ladder model (119.48B tokens) in under one epoch.
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+
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+ ## Contents
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+
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+ | split | files | tokens | size |
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+ |---|---|---|---|
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+ | train (`preprocessed/`) | 50 | 160.000B | 640.0 GB |
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+ | validation (`eval-data/perplexity/v3_small_dolma2-tokenizer/`) | 11 | 6.69M | 26.7 MB |
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+
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+ Train composition (identical to the full mix's token shares):
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+
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+ | source | tokens | share |
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+ |---|---|---|
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+ | dclm | 152.15B | 95.10% |
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+ | starcoder | 3.43B | 2.14% |
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+ | pes2o | 2.42B | 1.51% |
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+ | proofpile-2-arxiv | 0.86B | 0.54% |
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+ | proofpile-2-open-web-math | 0.50B | 0.31% |
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+ | proofpile-2-stack | 0.49B | 0.31% |
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+ | wikipedia | 0.15B | 0.09% |
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+
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+ Validation sets: c4_en, dolma_books, dolma_common-crawl, dolma_pes2o, dolma_reddit, dolma_stack,
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+ dolma_wiki, ice, m2d2_s2orc, pile, wikitext_103.
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+
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+ ## How the subset was made
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+
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+ Each source gets a token budget proportional to its share of the full mix (3.875T tokens, 1,117
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+ files). Within a source, files are taken whole in a seeded random order (seed 34521), and the
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+ budget is topped off with a **prefix** of one more file. Those files are named
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+ `*.prefix<NUM_BYTES>.npy`. `subset_plan.tsv` lists every file with its original path and the
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+ number of bytes taken; `train_files.txt` lists the train files as `label,path` lines.
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+
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+ ## File format
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+
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+ Each `.npy` file is a **raw `uint32` token array with no NumPy header** (the OLMo convention),
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+ i.e. read it with `numpy.memmap(path, dtype=numpy.uint32, mode="r")`. Documents are separated by
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+ the EOS token (id 100257).
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+
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+ ## Usage with OLMo-core
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+
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+ ```python
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+ from olmo_core.data import NumpyFSLDatasetConfig, TokenizerConfig
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+
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+ root = "/path/to/olmo-data-160B"
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+ paths = [f"{root}/{line.split(',', 1)[1].strip()}" for line in open(f"{root}/train_files.txt")]
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+ dataset = NumpyFSLDatasetConfig(
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+ paths=paths, sequence_length=2048, tokenizer=TokenizerConfig.dolma2(), work_dir="/tmp/olmo-work"
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+ )
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+ ```
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+
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+ For validation, use `DataMix.v3_small_ppl_validation` with `mix_base_dir=root`.
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+
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+ ## License and attribution
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+
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+ The data is a redistribution of a subset of AI2's OLMoE-mix-0824 (downloaded from
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+ `http://olmo-data.org`), released under the
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+ [ODC-By 1.0](https://opendatacommons.org/licenses/by/1-0/) license. Each component keeps its
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+ original license and terms of use (e.g. DCLM, The Stack / StarCoder data, peS2o, Proof-Pile-2,
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+ Wikipedia); please consult them before use. Credit: Allen Institute for AI (OLMo / OLMoE).
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