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1
- ---
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- dataset_info:
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- - config_name: finance
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- - config_name: finance_test_prompts
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- - config_name: science_test_prompts
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- data_files:
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- - split: test_prompts
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- path: science_test_prompts/test_prompts-*
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- ---
 
 
 
 
445
  # Dataset Card for "compred"
446
 
447
- [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ - name: score_ratio
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+ - name: len_ratio
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+ dtype: float64
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+ splits:
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+ - name: validation_pref
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+ num_bytes: 144623174
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+ num_examples: 83290
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+ - name: test_pref
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+ num_bytes: 162259697
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+ num_examples: 95042
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+ - name: train_pref
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+ num_bytes: 5691098839
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+ num_examples: 3411735
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+ download_size: 453464096
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+ dataset_size: 5997981710
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+ - config_name: politics_test_prompts
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+ features:
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+ - name: rank
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+ dtype: int64
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+ - name: only_comment
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+ dtype: bool
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+ - name: domain
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+ dtype: string
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+ - name: post_id
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+ dtype: string
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+ - name: title
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+ dtype: string
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+ - name: history
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+ dtype: string
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+ - name: c_root_id
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+ dtype: string
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+ - name: created_at_utc
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+ dtype: float64
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+ - name: score
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+ dtype: int64
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+ - name: human_ref
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+ dtype: string
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+ splits:
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+ - name: test_prompts
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+ num_bytes: 9753539
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+ num_examples: 8156
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+ download_size: 4811733
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+ dataset_size: 9753539
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+ - config_name: science
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+ features:
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+ - name: domain
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+ dtype: string
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+ - name: post_id
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+ dtype: string
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+ - name: history
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+ dtype: string
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+ - name: labels
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+ - name: overlap_ratio
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+ dtype: float64
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+ - name: seconds_difference
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+ dtype: float64
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+ - name: score_ratio
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+ - name: len_ratio
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+ dtype: float64
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+ - name: validation_pref
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+ - name: test_pref
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+ num_bytes: 49485277
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+ num_examples: 28595
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+ - name: train_pref
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+ num_bytes: 1886530811
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+ num_examples: 1092551
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+ download_size: 214600434
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+ dataset_size: 1985159520
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+ - config_name: science_test_prompts
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+ features:
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+ - name: rank
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+ dtype: int64
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+ - name: only_comment
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+ dtype: bool
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+ - name: domain
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+ dtype: string
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+ - name: post_id
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+ dtype: string
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+ - name: title
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+ - name: c_root_id
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+ splits:
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+ - name: test_prompts
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+ num_bytes: 6695945
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+ num_examples: 5495
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+ download_size: 3505358
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+ dataset_size: 6695945
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+ configs:
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+ - config_name: finance
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+ data_files:
386
+ - split: validation_pref
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+ path: finance/validation_pref-*
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+ - split: test_pref
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+ path: finance/test_pref-*
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+ - split: train_pref
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+ path: finance/train_pref-*
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+ - config_name: finance_test_prompts
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+ data_files:
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+ - split: test_prompts
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+ path: finance_test_prompts/test_prompts-*
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+ - config_name: gender_sexuality
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+ data_files:
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+ - split: validation_pref
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+ path: gender_sexuality/validation_pref-*
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+ - split: test_pref
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+ path: gender_sexuality/test_pref-*
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+ - split: train_pref
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+ path: gender_sexuality/train_pref-*
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+ - config_name: gender_sexuality_test_prompts
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+ data_files:
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+ - split: test_prompts
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+ path: gender_sexuality_test_prompts/test_prompts-*
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+ - config_name: history
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+ data_files:
410
+ - split: validation_pref
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+ path: history/validation_pref-*
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+ - split: test_pref
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+ path: history/test_pref-*
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+ - split: train_pref
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+ path: history/train_pref-*
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+ - config_name: history_test_prompts
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+ data_files:
418
+ - split: test_prompts
419
+ path: history_test_prompts/test_prompts-*
420
+ - config_name: politics
421
+ data_files:
422
+ - split: validation_pref
423
+ path: politics/validation_pref-*
424
+ - split: test_pref
425
+ path: politics/test_pref-*
426
+ - split: train_pref
427
+ path: politics/train_pref-*
428
+ - config_name: politics_test_prompts
429
+ data_files:
430
+ - split: test_prompts
431
+ path: politics_test_prompts/test_prompts-*
432
+ - config_name: science
433
+ data_files:
434
+ - split: validation_pref
435
+ path: science/validation_pref-*
436
+ - split: test_pref
437
+ path: science/test_pref-*
438
+ - split: train_pref
439
+ path: science/train_pref-*
440
+ - config_name: science_test_prompts
441
+ data_files:
442
+ - split: test_prompts
443
+ path: science_test_prompts/test_prompts-*
444
+ license: odc-by
445
+ language:
446
+ - en
447
+ pretty_name: c
448
+ ---
449
  # Dataset Card for "compred"
450
 
451
+ ## Dataset Details
452
+
453
+ ### Dataset Description
454
+
455
+ Conventional algorithms for training language models (LMs) with human feedback rely on preferences that are assumed to account for an average user,
456
+ disregarding subjectivity and finer-grained variations. Recent studies have raised concerns about aggregating such diverse, often contradictory human feedback to train
457
+ a single universal reward model, questioning which values or voices the models align with.
458
+ Finetuning models to maximize such reward results in generic models that produce outputs not preferred by many user groups,
459
+ as they tend to average out styles and norms. To study this issue, we collect and release **ComPRed**,
460
+ a question-answering dataset with community-level preferences from Reddit.
461
+ This dataset facilitates studying diversity in preferences without incurring privacy concerns associated with individual feedback.
462
+
463
+ - **Curated by:** Allen Institute for AI, The Ohio State University, Carnegie Mellon University
464
+ - **Paper:** [ArXiv](#)
465
+ - **Repository:** [https://github.com/allenai/compred](https://github.com/allenai/compred)
466
+ - **Language(s) (NLP):** English
467
+ - **License:** https://opendatacommons.org/licenses/by/odc_by_1.0_public_text.txt
468
+ - **Point of Contact:** [Sachin Kumar & Chan Young Park](mailto:kumar.1145@osu.edu, chanyoun@andrew.cmu.edu)
469
+
470
+
471
+ ## Uses
472
+
473
+ ComPreD contains five subsets divided based on factors driving diverging user preferences (we followed a similar process as [SHP](https://huggingface.co/datasets/stanfordnlp/SHP) to create this dataset).
474
+
475
+ | Subset(s) | Factor |
476
+ | -------- | ------- |
477
+ | politics | Ideologies |
478
+ | gender_and_sexuality | Demographics |
479
+ | finance, history | Community Norms |
480
+ | science | Level of expertise / Community Norms |
481
+
482
+ ### Loading
483
+
484
+ ```python
485
+ from datasets import load_dataset
486
+
487
+
488
+ # load finance train set
489
+ finance_train_pref = load_dataset("allenai/compred", "finance", split="train_pref")
490
+
491
+ # load finance test prompts
492
+ finance_test_prompts = load_dataset("allenai/compred", "finance_test_prompts", split="test_prompts")
493
+ ```
494
+
495
+ ### Dataset Structure
496
+
497
+ Coming soon
498
+
499
+ <!-- Preference data in each subset (train_pref, validation_pref, test_pref) has the following fields:
500
+ - id (str): a unique identifier
501
+ - prompt (`str`): the instruction/query which can be safely complied with
502
+ - chosen (`str`): the compliant response from a stronger model
503
+ - chosen_model (`str`): gpt-4
504
+ - rejected (`str`): the noncompliant response from a weaker model
505
+ - rejected_model (`str`): where applicable
506
+
507
+ Test prompts in each subset (test_prompts) has the following fields:
508
+
509
+ - id (str): a unique identifier
510
+ - prompt (str): the instruction/query which should NOT be complied with (original set) or should be complied with (contrast)
511
+ - response (str): the noncompliant or compliant response (only in train split)
512
+ - category (str): a high-level noncompliance category defined in our taxonomy including: "incomplete requests", "unsupported requests", "indeterminate requests", "humanizing requests", and "requests with safety concerns"
513
+ - subcategory (str): a fine-grained subcategory under each category
514
+ -->
515
+
516
+ ### Data Creation
517
+
518
+ Please refer to our [paper](#) for details on our dataset collection.
519
+
520
+
521
+ ## Licensing Information
522
+
523
+ ComPreD is made available under the ODC-BY requiring the user to follow the licenses of the subsequent parts.
524
+
525
+ ## Citation
526
+
527
+ ```
528
+ @article{kumar-park2024,
529
+ title={{Personalized LMs: Aligning Language Models with Diverse Human Preferences}},
530
+ author={Sachin Kumar, Chan Young Park, Yulia Tsvetkov, Noah A. Smith, Hannaneh Hajishirzi},
531
+ journal={},
532
+ year={2024}
533
+ }
534
+ ```