README.md

metadata

language:
  - en
license: mit
size_categories:
  - 1K<n<10K
task_categories:
  - image-classification
pretty_name: Metashift subset for PCBM reproduction
viewer: false
dataset_info:
  - config_name: cherrypicked_task_1_bed_cat_dog
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': airplane
              '1': bed
              '2': car
              '3': cow
              '4': keyboard
    splits:
      - name: train
        num_bytes: 28494
        num_examples: 500
      - name: test
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        num_examples: 500
    download_size: 477673284
    dataset_size: 56980
  - config_name: cherrypicked_task_1_bed_dog_cat
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': airplane
              '1': bed
              '2': car
              '3': cow
              '4': keyboard
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        num_examples: 500
      - name: test
        num_bytes: 28478
        num_examples: 500
    download_size: 477673272
    dataset_size: 56968
  - config_name: cherrypicked_task_2_table_books_cat
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': beach
              '1': computer
              '2': motorcycle
              '3': stove
              '4': table
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      - name: train
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        num_examples: 500
      - name: test
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        num_examples: 500
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    dataset_size: 56891
  - config_name: cherrypicked_task_2_table_books_dog
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': beach
              '1': computer
              '2': motorcycle
              '3': stove
              '4': table
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      - name: train
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        num_examples: 500
      - name: test
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        num_examples: 500
    download_size: 477673220
    dataset_size: 56888
  - config_name: cherrypicked_task_2_table_cat_dog
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': beach
              '1': computer
              '2': motorcycle
              '3': stove
              '4': table
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        num_examples: 500
      - name: test
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        num_examples: 500
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    dataset_size: 56962
  - config_name: cherrypicked_task_2_table_dog_cat
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': beach
              '1': computer
              '2': motorcycle
              '3': stove
              '4': table
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      - name: train
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        num_examples: 500
      - name: test
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        num_examples: 500
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    dataset_size: 56960
  - config_name: seed42_task_1_bed_cat_dog
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': airplane
              '1': bed
              '2': car
              '3': cow
              '4': keyboard
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      - name: train
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        num_examples: 500
      - name: test
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        num_examples: 500
    download_size: 477673282
    dataset_size: 56978
  - config_name: seed42_task_1_bed_dog_cat
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': airplane
              '1': bed
              '2': car
              '3': cow
              '4': keyboard
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      - name: train
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        num_examples: 500
      - name: test
        num_bytes: 28485
        num_examples: 500
    download_size: 477673290
    dataset_size: 56986
  - config_name: seed42_task_2_table_books_cat
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': beach
              '1': computer
              '2': motorcycle
              '3': stove
              '4': table
    splits:
      - name: train
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        num_examples: 500
      - name: test
        num_bytes: 28481
        num_examples: 500
    download_size: 477673247
    dataset_size: 56915
  - config_name: seed42_task_2_table_books_dog
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': beach
              '1': computer
              '2': motorcycle
              '3': stove
              '4': table
    splits:
      - name: train
        num_bytes: 28434
        num_examples: 500
      - name: test
        num_bytes: 28479
        num_examples: 500
    download_size: 477673245
    dataset_size: 56913
  - config_name: seed42_task_2_table_cat_dog
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': beach
              '1': computer
              '2': motorcycle
              '3': stove
              '4': table
    splits:
      - name: train
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        num_examples: 500
      - name: test
        num_bytes: 28479
        num_examples: 500
    download_size: 477673274
    dataset_size: 56944
  - config_name: seed42_task_2_table_dog_cat
    features:
      - name: image
        dtype: image
      - name: label
        dtype:
          class_label:
            names:
              '0': beach
              '1': computer
              '2': motorcycle
              '3': stove
              '4': table
    splits:
      - name: train
        num_bytes: 28463
        num_examples: 500
      - name: test
        num_bytes: 28481
        num_examples: 500
    download_size: 477673274
    dataset_size: 56944

PCBM Metashift

For the sake of reproducibility, this dataset hosts the postprocessed Metashift according to [Yuksekgonul et al.] for the use in Post-Hoc Concept Bottleneck Models.

Config Name	Description
task_1_bed_cat_dog	Task 1: bed(cat) -> bed(dog)
task_1_bed_dog_cat	Task 1: bed(dog) -> bed(cat)
task_2_table_books_cat	Task 2: table(books) -> table(cat)
task_2_table_books_dog	Task 2: table(books) -> table(dog)
task_2_table_cat_dog	Task 2: table(cat) -> table(dog)
task_2_table_dog_cat	Task 2: table(dog) -> table(cat)

The script to generate this dataset can be found at scripts/generate.py. You will need to download the Metashift repo and the Visual Genome dataset as instructed in the Metashift repo.