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# spanish-nominal-group

This model is a fine-tuned version of [dccuchile/bert-base-spanish-wwm-cased](https://huggingface.co/dccuchile/bert-base-spanish-wwm-cased) on the jorgeortizfuentes/spanish_nominal_groups_conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2590
- Ng Precision: 0.7311
- Ng Recall: 0.7725
- Ng F1: 0.7512
- Ng Number: 4321
- Overall Precision: 0.7311
- Overall Recall: 0.7725
- Overall F1: 0.7512
- Overall Accuracy: 0.9191

## 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 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2

{"tags": ["generated_from_trainer"], "datasets": ["jorgeortizfuentes/spanish_nominal_groups_conll2003"], "model-index": [{"name": "spanish-nominal-group", "results": []}]}
transformers pytorch bert token-classification generated_from_trainer dataset:jorgeortizfuentes/spanish_nominal_groups_conll2003 autotrain_compatible endpoints_compatible has_space region:us
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #dataset-jorgeortizfuentes/spanish_nominal_groups_conll2003 #autotrain_compatible #endpoints_compatible #has_space #region-us 




# spanish-nominal-group

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the jorgeortizfuentes/spanish_nominal_groups_conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2590
- Ng Precision: 0.7311
- Ng Recall: 0.7725
- Ng F1: 0.7512
- Ng Number: 4321
- Overall Precision: 0.7311
- Overall Recall: 0.7725
- Overall F1: 0.7512
- Overall Accuracy: 0.9191

## 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 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2

# spanish-nominal-group

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the jorgeortizfuentes/spanish_nominal_groups_conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2590
- Ng Precision: 0.7311
- Ng Recall: 0.7725
- Ng F1: 0.7512
- Ng Number: 4321
- Overall Precision: 0.7311
- Overall Recall: 0.7725
- Overall F1: 0.7512
- Overall Accuracy: 0.9191 ## 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 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2
TAGS
#transformers #pytorch #bert #token-classification #generated_from_trainer #dataset-jorgeortizfuentes/spanish_nominal_groups_conll2003 #autotrain_compatible #endpoints_compatible #has_space #region-us 
 # spanish-nominal-group

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the jorgeortizfuentes/spanish_nominal_groups_conll2003 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2590
- Ng Precision: 0.7311
- Ng Recall: 0.7725
- Ng F1: 0.7512
- Ng Number: 4321
- Overall Precision: 0.7311
- Overall Recall: 0.7725
- Overall F1: 0.7512
- Overall Accuracy: 0.9191 ## 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 4.26.1
- Pytorch 1.13.1+cu117
- Datasets 2.9.0
- Tokenizers 0.13.2