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