
xtremedistil-l12-h384-uncased model trained on a subset of "Natural Questions Short".
Done for the "Deep Learning for Natural Language Processing" course at TU Darmstadt.
Group 69.

Squad metric:
- 'exact_match': 40.217
- 'f1': 62.3873
{"language": "en", "license": "mit", "tags": ["question-answering"]}
transformers pytorch bert question-answering en license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #question-answering #en #license-mit #endpoints_compatible #region-us 


xtremedistil-l12-h384-uncased model trained on a subset of "Natural Questions Short".
Done for the "Deep Learning for Natural Language Processing" course at TU Darmstadt.
Group 69.

Squad metric:
- 'exact_match': 40.217
- 'f1': 62.3873
TAGS
#transformers #pytorch #bert #question-answering #en #license-mit #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #bert #question-answering #en #license-mit #endpoints_compatible #region-us 
