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# bert-base-spanish-wwm-cased-finetuned-sqac-finetuned-squad

This model is a fine-tuned version of [MMG/bert-base-spanish-wwm-cased-finetuned-sqac](https://huggingface.co/MMG/bert-base-spanish-wwm-cased-finetuned-sqac) on the squad_es dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5325
- {'exact_match': 60.30274361400189, 'f1': 77.01962587890856}


## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

### Framework versions

- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3

{"language": ["es"], "tags": ["generated_from_trainer"], "datasets": ["squad_es"], "model-index": [{"name": "bert-base-spanish-wwm-cased-finetuned-sqac-finetuned-squad", "results": []}]}
transformers pytorch tensorboard bert question-answering generated_from_trainer es dataset:squad_es endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #es #dataset-squad_es #endpoints_compatible #region-us 




# bert-base-spanish-wwm-cased-finetuned-sqac-finetuned-squad

This model is a fine-tuned version of MMG/bert-base-spanish-wwm-cased-finetuned-sqac on the squad_es dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5325
- {'exact_match': 60.30274361400189, 'f1': 77.01962587890856}


## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

### Framework versions

- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3

# bert-base-spanish-wwm-cased-finetuned-sqac-finetuned-squad

This model is a fine-tuned version of MMG/bert-base-spanish-wwm-cased-finetuned-sqac on the squad_es dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5325
- {'exact_match': 60.30274361400189, 'f1': 77.01962587890856} ## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3 ### Training results ### Framework versions

- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #es #dataset-squad_es #endpoints_compatible #region-us 
 # bert-base-spanish-wwm-cased-finetuned-sqac-finetuned-squad

This model is a fine-tuned version of MMG/bert-base-spanish-wwm-cased-finetuned-sqac on the squad_es dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5325
- {'exact_match': 60.30274361400189, 'f1': 77.01962587890856} ## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3 ### Training results ### Framework versions

- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #es #dataset-squad_es #endpoints_compatible #region-us 
# bert-base-spanish-wwm-cased-finetuned-sqac-finetuned-squad

This model is a fine-tuned version of MMG/bert-base-spanish-wwm-cased-finetuned-sqac on the squad_es dataset.
It achieves the following results on the evaluation set:
- Loss: 1.5325
- {'exact_match': 60.30274361400189, 'f1': 77.01962587890856}## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3### Training results### Framework versions

- Transformers 4.13.0
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3