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# ai-club-inductions-21-nlp-ELECTRA-base-squad

This model is the deepset/electra-base-squad2 pre-trained model trained on data from AI Inductions 21 NLP competition (https://www.kaggle.com/c/ai-inductions-21-nlp) for extractive QA.

## Model description

More information needed

## Intended uses & limitations

AI Inductions 21 NLP competition

## Training and evaluation data

AI Inductions 21 NLP competition data

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- max_length = 512
- doc_stride = 384
- learning_rate: 2e-05
- weight_decay=0.01
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Framework versions

- Transformers 4.11.3
- Pytorch 1.7.1+cpu
- Datasets 1.14.0
- Tokenizers 0.10.3

{"tags": ["generated_from_trainer"], "model-index": [{"name": "ai-club-inductions-21-nlp-ELECTRA-base-squad", "results": []}]}
transformers pytorch electra question-answering generated_from_trainer endpoints_compatible region:us
TAGS
#transformers #pytorch #electra #question-answering #generated_from_trainer #endpoints_compatible #region-us 




# ai-club-inductions-21-nlp-ELECTRA-base-squad

This model is the deepset/electra-base-squad2 pre-trained model trained on data from AI Inductions 21 NLP competition (URL for extractive QA.

## Model description

More information needed

## Intended uses & limitations

AI Inductions 21 NLP competition

## Training and evaluation data

AI Inductions 21 NLP competition data

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- max_length = 512
- doc_stride = 384
- learning_rate: 2e-05
- weight_decay=0.01
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Framework versions

- Transformers 4.11.3
- Pytorch 1.7.1+cpu
- Datasets 1.14.0
- Tokenizers 0.10.3

# ai-club-inductions-21-nlp-ELECTRA-base-squad

This model is the deepset/electra-base-squad2 pre-trained model trained on data from AI Inductions 21 NLP competition (URL for extractive QA. ## Model description

More information needed ## Intended uses & limitations

AI Inductions 21 NLP competition ## Training and evaluation data

AI Inductions 21 NLP competition data ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- max_length = 512
- doc_stride = 384
- learning_rate: 2e-05
- weight_decay=0.01
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10 ### Framework versions

- Transformers 4.11.3
- Pytorch 1.7.1+cpu
- Datasets 1.14.0
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #electra #question-answering #generated_from_trainer #endpoints_compatible #region-us 
 # ai-club-inductions-21-nlp-ELECTRA-base-squad

This model is the deepset/electra-base-squad2 pre-trained model trained on data from AI Inductions 21 NLP competition (URL for extractive QA. ## Model description

More information needed ## Intended uses & limitations

AI Inductions 21 NLP competition ## Training and evaluation data

AI Inductions 21 NLP competition data ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- max_length = 512
- doc_stride = 384
- learning_rate: 2e-05
- weight_decay=0.01
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10 ### Framework versions

- Transformers 4.11.3
- Pytorch 1.7.1+cpu
- Datasets 1.14.0
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #electra #question-answering #generated_from_trainer #endpoints_compatible #region-us 
# ai-club-inductions-21-nlp-ELECTRA-base-squad

This model is the deepset/electra-base-squad2 pre-trained model trained on data from AI Inductions 21 NLP competition (URL for extractive QA.## Model description

More information needed## Intended uses & limitations

AI Inductions 21 NLP competition## Training and evaluation data

AI Inductions 21 NLP competition data## Training procedure### Training hyperparameters

The following hyperparameters were used during training:
- max_length = 512
- doc_stride = 384
- learning_rate: 2e-05
- weight_decay=0.01
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10### Framework versions

- Transformers 4.11.3
- Pytorch 1.7.1+cpu
- Datasets 1.14.0
- Tokenizers 0.10.3