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# bert-clean-semaphore-prediction-w8

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0669
- Accuracy: 0.9671
- F1: 0.9672

## 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 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1

{"tags": ["generated_from_trainer"], "metrics": ["accuracy", "f1"], "model-index": [{"name": "bert-clean-semaphore-prediction-w8", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 




# bert-clean-semaphore-prediction-w8

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0669
- Accuracy: 0.9671
- F1: 0.9672

## 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 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1

# bert-clean-semaphore-prediction-w8

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0669
- Accuracy: 0.9671
- F1: 0.9672 ## 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 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1
TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
 # bert-clean-semaphore-prediction-w8

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0669
- Accuracy: 0.9671
- F1: 0.9672 ## 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 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1
passage: TAGS
#transformers #pytorch #bert #text-classification #generated_from_trainer #autotrain_compatible #endpoints_compatible #region-us 
# bert-clean-semaphore-prediction-w8

This model is a fine-tuned version of dccuchile/bert-base-spanish-wwm-cased on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0669
- Accuracy: 0.9671
- F1: 0.9672## 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 4.19.2
- Pytorch 1.11.0
- Datasets 2.2.2
- Tokenizers 0.12.1