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# bert_medium_pretrain_squad

This model is a fine-tuned version of [anas-awadalla/bert-medium-pretrained-on-squad](https://huggingface.co/anas-awadalla/bert-medium-pretrained-on-squad) on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0973
- "exact_match": 77.95648060548723
- "f1": 85.85300366384631

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- 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: 3.0

### Training results



### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3

{"license": "mit", "tags": ["generated_from_trainer"], "datasets": ["squad"], "model-index": [{"name": "bert_medium_pretrain_squad", "results": []}]}
transformers pytorch bert question-answering generated_from_trainer dataset:squad license:mit endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us 




# bert_medium_pretrain_squad

This model is a fine-tuned version of anas-awadalla/bert-medium-pretrained-on-squad on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0973
- "exact_match": 77.95648060548723
- "f1": 85.85300366384631

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- 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: 3.0

### Training results



### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3

# bert_medium_pretrain_squad

This model is a fine-tuned version of anas-awadalla/bert-medium-pretrained-on-squad on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0973
- "exact_match": 77.95648060548723
- "f1": 85.85300366384631 ## Model description

More information needed ## Intended uses & limitations

More information needed ## Training and evaluation data

More information needed ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- 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: 3.0 ### Training results ### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #bert #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us 
 # bert_medium_pretrain_squad

This model is a fine-tuned version of anas-awadalla/bert-medium-pretrained-on-squad on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0973
- "exact_match": 77.95648060548723
- "f1": 85.85300366384631 ## Model description

More information needed ## Intended uses & limitations

More information needed ## Training and evaluation data

More information needed ## Training procedure ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- 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: 3.0 ### Training results ### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #bert #question-answering #generated_from_trainer #dataset-squad #license-mit #endpoints_compatible #region-us 
# bert_medium_pretrain_squad

This model is a fine-tuned version of anas-awadalla/bert-medium-pretrained-on-squad on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0973
- "exact_match": 77.95648060548723
- "f1": 85.85300366384631## Model description

More information needed## Intended uses & limitations

More information needed## Training and evaluation data

More information needed## Training procedure### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- 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: 3.0### Training results### Framework versions

- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.0
- Tokenizers 0.10.3