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  license: cc-by-4.0
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  # FiD model trained on TQA
  
  -- This is the model checkpoint of FiD [2], based on the T5 large (with 770M parameters) and trained on the TriviaQA dataset [1]. 
  
  -- Hyperparameters: 8 x 40GB A100 GPUs; batch size 8; AdamW; LR 3e-5; 30000 steps
  
  References: 
  
  [1] TriviaQA: A Large Scale Dataset for Reading Comprehension and Question Answering. ACL 2017
  
  [2] Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering. EACL 2021. 
  
  ## Model performance 
  
  We evaluate it on the TriviaQA dataset, the EM score is 68.5 (0.8 higher than the original performance reported in the paper).
  
  
  <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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