
# FiD model trained on NQ

-- This is the model checkpoint of FiD [2], based on the T5 (with 3B parameters) and trained on the NQ dataset [1]. 

-- Hyperparameters: 8 x 40GB A100 GPUs; batch size 8; AdamW; LR 3e-5; 30000 steps

References: 

[1] Natural Questions: A Benchmark for Question Answering Research. TACL 2019. 

[2] Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering. EACL 2021. 

## Model performance 

We evaluate it on the NQ dataset, the EM score is 50.6 on the test set.


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


{"license": "cc-by-4.0"}
transformers pytorch t5 license:cc-by-4.0 endpoints_compatible text-generation-inference region:us
TAGS
#transformers #pytorch #t5 #license-cc-by-4.0 #endpoints_compatible #text-generation-inference #region-us 


# FiD model trained on NQ

-- This is the model checkpoint of FiD [2], based on the T5 (with 3B parameters) and trained on the NQ dataset [1]. 

-- Hyperparameters: 8 x 40GB A100 GPUs; batch size 8; AdamW; LR 3e-5; 30000 steps

References: 

[1] Natural Questions: A Benchmark for Question Answering Research. TACL 2019. 

[2] Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering. EACL 2021. 

## Model performance 

We evaluate it on the NQ dataset, the EM score is 50.6 on the test set.


<a href="URL
	<img width="300px" src="URL
</a>


# FiD model trained on NQ

-- This is the model checkpoint of FiD [2], based on the T5 (with 3B parameters) and trained on the NQ dataset [1]. 

-- Hyperparameters: 8 x 40GB A100 GPUs; batch size 8; AdamW; LR 3e-5; 30000 steps

References: 

[1] Natural Questions: A Benchmark for Question Answering Research. TACL 2019. 

[2] Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering. EACL 2021. ## Model performance 

We evaluate it on the NQ dataset, the EM score is 50.6 on the test set.


<a href="URL
	<img width="300px" src="URL
</a>
TAGS
#transformers #pytorch #t5 #license-cc-by-4.0 #endpoints_compatible #text-generation-inference #region-us 
 # FiD model trained on NQ

-- This is the model checkpoint of FiD [2], based on the T5 (with 3B parameters) and trained on the NQ dataset [1]. 

-- Hyperparameters: 8 x 40GB A100 GPUs; batch size 8; AdamW; LR 3e-5; 30000 steps

References: 

[1] Natural Questions: A Benchmark for Question Answering Research. TACL 2019. 

[2] Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering. EACL 2021. ## Model performance 

We evaluate it on the NQ dataset, the EM score is 50.6 on the test set.


<a href="URL
	<img width="300px" src="URL
</a>
TAGS
#transformers #pytorch #t5 #license-cc-by-4.0 #endpoints_compatible #text-generation-inference #region-us 
# FiD model trained on NQ

-- This is the model checkpoint of FiD [2], based on the T5 (with 3B parameters) and trained on the NQ dataset [1]. 

-- Hyperparameters: 8 x 40GB A100 GPUs; batch size 8; AdamW; LR 3e-5; 30000 steps

References: 

[1] Natural Questions: A Benchmark for Question Answering Research. TACL 2019. 

[2] Leveraging Passage Retrieval with Generative Models for Open Domain Question Answering. EACL 2021.## Model performance 

We evaluate it on the NQ dataset, the EM score is 50.6 on the test set.


<a href="URL
	<img width="300px" src="URL
</a>