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--- |
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dataset_info: |
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features: |
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- name: en |
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dtype: string |
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- name: 'no' |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 44628652 |
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num_examples: 758144 |
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download_size: 33446436 |
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dataset_size: 44628652 |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: data/train-* |
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license: cc |
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task_categories: |
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- translation |
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- summarization |
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language: |
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- 'no' |
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- nb |
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- en |
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pretty_name: Massive EN-NO shorter transfer |
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size_categories: |
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- 100K<n<1M |
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--- |
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# Massive EN-NO shorter and similar transfer |
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A dataset of EN-NO translations comprised of the following sources: |
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- https://huggingface.co/datasets/opus100 |
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- https://huggingface.co/datasets/opus_books |
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- https://huggingface.co/datasets/open_subtitles (https://huggingface.co/datasets/tollefj/subtitles-en-no-similar-shorter) |
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- https://huggingface.co/datasets/RuterNorway/Fleurs-Alpaca-EN-NO |
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And parsed by: |
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- simple preprocessing: stripping/misplaced punctuation |
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- computing all similarities with https://huggingface.co/NbAiLab/nb-sbert-base |
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- effectively aligning the translations |
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- filters out where the length of the target language (norwegian) is less than 70% the length of the source language (english) |
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- items with less than 6 words are passed regardless of length constraints |
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this results in a shorter and similar translation corpus. |
