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This dataset has been created as an artefact of the paper [AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets (Lesci and Vlachos, 2024)](https://arxiv.org/abs/2404.05623).
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More info about this dataset in appendix of the paper.
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This dataset has been created as an artefact of the paper [AnchorAL: Computationally Efficient Active Learning for Large and Imbalanced Datasets (Lesci and Vlachos, 2024)](https://arxiv.org/abs/2404.05623).
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More info about this dataset in the appendix of the paper.
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The AmazonCat-13k dataset was released by [McAuley and Leskovec (2013)](https://dl.acm.org/doi/pdf/10.1145/2507157.2507163)
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and is composed of product descriptions and reviews classified into 13k multi-label categories.
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The dataset is split into 1.2M train and 300k evaluation instances.
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It is commonly used as an [extreme classification benchmark](http://manikvarma.org/downloads/XC/XMLRepository.html)
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[(You et al., 2019)](https://proceedings.neurips.cc/paper_files/paper/2019/file/9e6a921fbc428b5638b3986e365d4f21-Paper.pdf) where the goal is to classify an item into its categories.
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The data are exactly the same as the original available at [this Google Drive link](https://drive.google.com/u/0/uc?id=17rVRDarPwlMpb3l5zof9h34FlwbpTu4l)
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with the following additions:
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1. A unique identifier, `uid` column.
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1. Indices, that is, 3 columns with the embeddings of 3 different sentence-transformers
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- `all-mpnet-base-v2`
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- `multi-qa-mpnet-base-dot-v1`
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- `all-MiniLM-L12-v2`
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1. Renaming of the `label` column to `labels` for easier compatibility with the transformers library.
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