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metadata
license: cc-by-4.0
dataset_info:
  features:
    - name: text
      dtype: string
    - name: image
      dtype: image
  splits:
    - name: train
      num_bytes: 282285477
      num_examples: 10000
    - name: test
      num_bytes: 56612023.875
      num_examples: 2001
  download_size: 320681179
  dataset_size: 338897500.875
task_categories:
  - text-to-image
multilinguality:
  - monolingual
language:
  - de
size_categories:
  - 1K<n<10K
source_datasets:
  - original
pretty_name: Fashion12k DE



Finetuner logo: Finetuner helps you to create experiments in order to improve embeddings on search tasks. It accompanies you to deliver the last mile of performance-tuning for neural search applications.

The data offered by Jina AI, Finetuner team.

Summary

This dataset is a German-language dataset based on the Fashion12K dataset, which originally contains both English and German text descriptions for each item. This dataset was used to to finetuner CLIP using the Finetuner tool.

Fine-tuning

Please refer to our documentation: Multilingual Text-to-Image Search with MultilingualCLIP and blog Improving Search Quality for Non-English Queries with Fine-tuned Multilingual CLIP Models

Instances

Each data point consists of a 'text' and an 'image' field, where the 'text' field describes an item of clothing in German, and the 'image' field contains and image of that item of clothing.

Fields

  • 'text': A string describing the item of clothing.
  • 'image': A PIL.Image.Image object containing the image. Note that when accessing the image column: dataset[0]["image"] the image file is automatically decoded. Decoding of a large number of image files might take a significant amount of time. Thus it is important to first query the sample index before the "image" column, i.e. dataset[0]["image"] should always be preferred over dataset["image"][0].

Splits

train test
# of items 10000 2001

Source

Images were sampled from the Fashion200K dataset.

Annotations

Data was annotated using Toloka. See their site for more details.

Licensing Information

This work is licensed under a Creative Commons Attribution 4.0 International License.

Contributors

Thanks to contributors from Jina AI and Toloka for adding this dataset.