
Model based on distilbert-base-uncased model trained on natural question short dataset.
Trained for one episode with AdamW optimizer and learning rate of 5e-03 and no warmup steps.
We achieved a f1 score of 32.67 and an em score of 10.35
{"language": ["en"], "tags": ["question-answering"], "datasets": ["nq", "natural-question", "natural-question-short"], "metrics": ["squad"]}
transformers pytorch distilbert question-answering en dataset:nq dataset:natural-question dataset:natural-question-short endpoints_compatible region:us
TAGS
#transformers #pytorch #distilbert #question-answering #en #dataset-nq #dataset-natural-question #dataset-natural-question-short #endpoints_compatible #region-us 


Model based on distilbert-base-uncased model trained on natural question short dataset.
Trained for one episode with AdamW optimizer and learning rate of 5e-03 and no warmup steps.
We achieved a f1 score of 32.67 and an em score of 10.35
TAGS
#transformers #pytorch #distilbert #question-answering #en #dataset-nq #dataset-natural-question #dataset-natural-question-short #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #distilbert #question-answering #en #dataset-nq #dataset-natural-question #dataset-natural-question-short #endpoints_compatible #region-us 
