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# bert-base-spanish-wwm-cased-finetuned-squad2-es-finetuned-sqac

This model is a fine-tuned version of [ockapuh/bert-base-spanish-wwm-cased-finetuned-squad2-es](https://huggingface.co/ockapuh/bert-base-spanish-wwm-cased-finetuned-squad2-es) on the sqac dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9263
- {'exact_match': 65.55793991416309, 'f1': 82.72322701572416}

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-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


### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3

{"language": ["es"], "tags": ["generated_from_trainer"], "datasets": ["sqac"], "model-index": [{"name": "bert-base-spanish-wwm-cased-finetuned-squad2-es-finetuned-sqac", "results": []}]}
transformers pytorch tensorboard bert question-answering generated_from_trainer es dataset:sqac endpoints_compatible region:us
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #es #dataset-sqac #endpoints_compatible #region-us 




# bert-base-spanish-wwm-cased-finetuned-squad2-es-finetuned-sqac

This model is a fine-tuned version of ockapuh/bert-base-spanish-wwm-cased-finetuned-squad2-es on the sqac dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9263
- {'exact_match': 65.55793991416309, 'f1': 82.72322701572416}

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-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


### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3

# bert-base-spanish-wwm-cased-finetuned-squad2-es-finetuned-sqac

This model is a fine-tuned version of ockapuh/bert-base-spanish-wwm-cased-finetuned-squad2-es on the sqac dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9263
- {'exact_match': 65.55793991416309, 'f1': 82.72322701572416} ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-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 ### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3
TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #es #dataset-sqac #endpoints_compatible #region-us 
 # bert-base-spanish-wwm-cased-finetuned-squad2-es-finetuned-sqac

This model is a fine-tuned version of ockapuh/bert-base-spanish-wwm-cased-finetuned-squad2-es on the sqac dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9263
- {'exact_match': 65.55793991416309, 'f1': 82.72322701572416} ### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-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 ### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3
passage: TAGS
#transformers #pytorch #tensorboard #bert #question-answering #generated_from_trainer #es #dataset-sqac #endpoints_compatible #region-us 
# bert-base-spanish-wwm-cased-finetuned-squad2-es-finetuned-sqac

This model is a fine-tuned version of ockapuh/bert-base-spanish-wwm-cased-finetuned-squad2-es on the sqac dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9263
- {'exact_match': 65.55793991416309, 'f1': 82.72322701572416}### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-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### Framework versions

- Transformers 4.14.1
- Pytorch 1.10.0+cu111
- Datasets 1.17.0
- Tokenizers 0.10.3