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baidu-ultr_uva-mlm-ctr

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  Query-document vectors and clicks for a subset of the [Baidu Unbiased Learning to Rank
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  dataset](https://arxiv.org/abs/2207.03051).
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  This dataset uses a BERT cross-encoder with 12 layers trained on a Masked Language Modeling (MLM) and click-through-rate (CTR) prediction task to compute query-document vectors (768 dims).
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- The model is available under `model/`.
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  ## Setup
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  1. Install huggingface [datasets](https://huggingface.co/docs/datasets/installation)
 
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  Query-document vectors and clicks for a subset of the [Baidu Unbiased Learning to Rank
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  dataset](https://arxiv.org/abs/2207.03051).
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  This dataset uses a BERT cross-encoder with 12 layers trained on a Masked Language Modeling (MLM) and click-through-rate (CTR) prediction task to compute query-document vectors (768 dims).
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+ The model is available at: https://huggingface.co/philipphager/baidu-ultr_uva-bert_naive-pointwise
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  ## Setup
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  1. Install huggingface [datasets](https://huggingface.co/docs/datasets/installation)