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Datasets:
ngqtrung
/
mopd-data

Tasks:
Image-Text-to-Text
Video-Text-to-Text
Modalities:
Text
Size:
1M - 10M
Tags:
multimodal
reasoning
sft
rl
distillation
mopd
License:
Dataset card Data Studio Files
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  1. .gitattributes +1 -0
  2. README.md +56 -0
  3. media_index.tsv +3 -0
  4. media_zips/mix-00000.zip +3 -0
  5. media_zips/mix-00001.zip +3 -0
  6. media_zips/mix-00002.zip +3 -0
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  23. media_zips/rows-00000.zip +3 -0
  24. media_zips/rows-00001.zip +3 -0
  25. media_zips/rows-00002.zip +3 -0
  26. media_zips/rows-00003.zip +3 -0
  27. media_zips/rows_vid-00000.zip +3 -0
  28. media_zips/rows_vid-00001.zip +3 -0
  29. media_zips/rows_vid-00003.zip +3 -0
  30. media_zips/rows_vid-00004.zip +3 -0
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  32. media_zips/rows_vid-00006.zip +3 -0
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  36. media_zips/rows_vid-00010.zip +3 -0
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  47. media_zips/rows_vid-00029.zip +3 -0
  48. media_zips/rows_vid-00030.zip +3 -0
  49. media_zips/rows_vid-00031.zip +3 -0
  50. media_zips/videorft-00000.zip +3 -0
.gitattributes CHANGED
@@ -58,3 +58,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
 
 
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
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+ media_index.tsv filter=lfs diff=lfs merge=lfs -text
README.md ADDED
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+ ---
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+ license: other
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+ license_name: mixed-source
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+ task_categories: [image-text-to-text, video-text-to-text]
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+ tags: [multimodal, reasoning, sft, rl, distillation, mopd]
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+ configs:
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+ - config_name: sft_imgr
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+ data_files: sft_v4/imgr/*.jsonl
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+ - config_name: sft_imgp
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+ data_files: sft_v4/imgp/*.jsonl
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+ - config_name: sft_vid
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+ data_files: sft_v4/vid/*.jsonl
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+ - config_name: rl_imgr
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+ data_files: rl_v2/imgr.parquet
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+ - config_name: rl_imgp
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+ data_files: rl_v2/imgp.parquet
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+ - config_name: rl_vid
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+ data_files: rl_v2/vid.parquet
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+ ---
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+
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+ # MOPD training data (SFT v4 + RL v2, full media)
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+
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+ The data that trains the MOPD domain teachers on Qwen3.5-9B: one SFT set and one RL prompt set per domain
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+ (`imgr` image reasoning, `imgp` image perception, `vid` video).
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+
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+ | Split | Rows | Format | Media |
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+ |---|---|---|---|
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+ | `sft_v4/imgr` | 1,022,304 | chat jsonl (`messages`, `meta`) | images in `media/` |
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+ | `sft_v4/imgp` | 1,456,403 | chat jsonl | images in `media/` |
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+ | `sft_v4/vid` | 710,735 | chat jsonl | videos in `media/` |
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+ | `rl_v2/imgr` | 64,307 | verl parquet (`prompt`, `images`, `reward_model.ground_truth`, `extra_info`) | images embedded (bytes) |
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+ | `rl_v2/imgp` | 67,915 | verl parquet | images embedded (bytes) |
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+ | `rl_v2/vid` | 60,805 | verl parquet | videos in `media/` |
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+
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+ **SFT rows**: single-turn multimodal questions pooled from public datasets; the assistant turn is a reasoning trace
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+ (`<think>...</think>` + answer, final answer in `\boxed{}`) written by Qwen3.8-Flash-Next with the gold answer given,
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+ then filtered by agreement with the gold. `meta` keeps the source card, task type and generator.
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+ **RL rows**: prompts with a rule-checkable gold answer (`reward_model.ground_truth`, `extra_info.task_type`), decontaminated
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+ against our eval benchmarks.
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+
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+ ## Media
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+
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+ 65 store-only zip shards in `media_zips/` (523 GB). Unzip all at the repo root:
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+
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+ ```bash
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+ huggingface-cli download ngqtrung/mopd-data --repo-type dataset --local-dir mopd-data
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+ cd mopd-data && for z in media_zips/*.zip; do unzip -q -n "$z"; done # -> media/<group>/...
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+ ```
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+ Every media path in the rows is relative to the repo root (`media/...`). `media_index.tsv` lists path, bytes and shard.
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+ Media processing used in training: images 65,536-1,605,632 px; videos 1 fps, 4-150 frames, ≤ 65,536 px per frame.
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+
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+ ## Sources and license
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+
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+ The questions and media come from public datasets (e.g. LLaVA-Video-178K, FineVideo, Vript, VideoRFT, LLaVA-OneVision,
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+ and others listed in `meta.card_id`). Each source keeps its own license; check it before use. The reasoning traces are
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+ model-generated. Released for research.
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