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license: cc-by-4.0
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# GenRead (MergeDPR): FiD model trained on WebQ

-- This is the model checkpoint of GenRead [2], based on the T5-3B and trained on the WebQ dataset [1]. 

-- Hyperparameters: 8 x 80GB A100 GPUs; batch size 16; AdamW; LR 5e-5; best dev at 18000 steps.

References: 

[1] Semantic parsing on freebase from question-answer pairs. EMNLP 2013.

[2] Generate rather than Retrieve: Large Language Models are Strong Context Generators. arXiv 2022

## Model performance 

We evaluate it on the WebQ dataset, the EM score is 56.25.


<a href="https://huggingface.co/exbert/?model=bert-base-uncased">
	<img width="300px" src="https://cdn-media.huggingface.co/exbert/button.png">
</a>
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license: cc-by-4.0
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license: cc-by-4.0
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