{ "repo_folder": "diversity_oriented", "paper_setting": "DIVERSITY-ORIENTED", "internal_run_name": "diversity-first", "selection_rule": "Top-ranked documents taken within each of the 24 WebOrganizer topics, each topic receiving a share of the source budget proportional to its share of the remaining pool, then rewritten.", "content": "rewritten", "composition": { "note": "This folder is the complete 10B-token mixture the models actually trained on: the shared 5B raw anchor plus this setting's 5B component, already merged and shuffled. The anchor is included in every setting folder.", "shuffle_seed": 42, "anchor_docs": 4120164, "anchor_tokens": 5000002332, "strategy_docs": 8336411, "strategy_tokens": 4889635504, "strategy_token_target": 5000000000, "strategy_token_shortfall": 110362164, "shortfall_reason": "Per-topic quotas could not be filled for 4 of 24 topics (Adult, History, Literature, Religion) and the assembly policy was 'A_no_cross_topic_backfill' -- backfilling from other topics would have destroyed the topical balance that defines this setting. This arm therefore ships 4.89B strategy tokens rather than 5.00B.", "sort_key": "fasttext-ranking-v2 (DESC, within topic)", "topup_policy": "A_no_cross_topic_backfill" }, "rewriter_model": "Qwen2.5-7B-Instruct (greedy decoding)", "prompt_style": "Nemotron-CC wikipedia-style rephrasing and distillation prompts, as released in the FinePhrase repository", "doc_count": 12456575, "token_count_llama2": 9889637833, "shard_count": 25, "columns": [ "doc_id", "orig_doc_id", "text", "source_prompt", "train_tokens", "topic" ], "provenance": { "source_folder": "/scratch/bvandur1/zhuicon1/data_rewrite/pretrain/diversity-first/shuffled", "tokenized_folder": "/scratch/bvandur1/zhuicon1/nanotron_tokenized/diversity-first/tokenized", "source_evidence": "datatrove executor.json (reader data_folder), confirmed by decoding 50 documents out of the .ds and matching them into this folder (50/50)", "trained_from_config": "config_diversity-first_10B_1.5B.yaml", "config_dir": "/scratch/bvandur1/zhuicon1/projects/nanotron/examples", "seeds": [ 42, 43, 44 ], "doc_content_digest_sha256": "6153917f59d5564da5720f94ce4636c0a9b0dddd532a6490ab83de18fd0529ad", "doc_id_digest_sha256": "fc0ca392c84f4a22b02272e5f60738bad18965f4112105237d790bbc91e86d6b" } }