
# Test model for DL4NLP 2022 HW06  
xtremedistil-l6-h256-uncased trained on SQuAD

## Hyper parameters
- learning rate: 1e-5 
- weight decay: 0.01
- warm up steps: 0
- learning rate scheduler: linear 
- epochs: 1

## Metric results on the dev set
- F1: 65.48
- EM: 51.67
{"language": ["en"], "license": "mit", "tags": ["question-answering"], "datasets": ["SQuAD"], "metrics": ["EM", "F1"]}
transformers pytorch bert question-answering en dataset:SQuAD license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #question-answering #en #dataset-SQuAD #license-mit #endpoints_compatible #region-us 


# Test model for DL4NLP 2022 HW06  
xtremedistil-l6-h256-uncased trained on SQuAD

## Hyper parameters
- learning rate: 1e-5 
- weight decay: 0.01
- warm up steps: 0
- learning rate scheduler: linear 
- epochs: 1

## Metric results on the dev set
- F1: 65.48
- EM: 51.67
# Test model for DL4NLP 2022 HW06  
xtremedistil-l6-h256-uncased trained on SQuAD ## Hyper parameters
- learning rate: 1e-5 
- weight decay: 0.01
- warm up steps: 0
- learning rate scheduler: linear 
- epochs: 1 ## Metric results on the dev set
- F1: 65.48
- EM: 51.67
TAGS
#transformers #pytorch #bert #question-answering #en #dataset-SQuAD #license-mit #endpoints_compatible #region-us 
 # Test model for DL4NLP 2022 HW06  
xtremedistil-l6-h256-uncased trained on SQuAD ## Hyper parameters
- learning rate: 1e-5 
- weight decay: 0.01
- warm up steps: 0
- learning rate scheduler: linear 
- epochs: 1 ## Metric results on the dev set
- F1: 65.48
- EM: 51.67
passage: TAGS
#transformers #pytorch #bert #question-answering #en #dataset-SQuAD #license-mit #endpoints_compatible #region-us 
# Test model for DL4NLP 2022 HW06  
xtremedistil-l6-h256-uncased trained on SQuAD## Hyper parameters
- learning rate: 1e-5 
- weight decay: 0.01
- warm up steps: 0
- learning rate scheduler: linear 
- epochs: 1## Metric results on the dev set
- F1: 65.48
- EM: 51.67