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# bertin-roberta-fine-tuned-text-classification-SL-data-augmentation-ds

This model is a fine-tuned version of [bertin-project/bertin-roberta-base-spanish](https://huggingface.co/bertin-project/bertin-roberta-base-spanish) on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.9552
- eval_f1: 0.6062
- eval_recall: 0.5982
- eval_accuracy: 0.5982
- eval_precision: 0.6312
- eval_runtime: 15.886
- eval_samples_per_second: 99.647
- eval_steps_per_second: 6.232
- epoch: 6.0
- step: 2772

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

{"license": "cc-by-4.0", "tags": ["generated_from_trainer"], "model-index": [{"name": "bertin-roberta-fine-tuned-text-classification-SL-data-augmentation-ds", "results": []}]}
transformers pytorch roberta text-classification generated_from_trainer license:cc-by-4.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 




# bertin-roberta-fine-tuned-text-classification-SL-data-augmentation-ds

This model is a fine-tuned version of bertin-project/bertin-roberta-base-spanish on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.9552
- eval_f1: 0.6062
- eval_recall: 0.5982
- eval_accuracy: 0.5982
- eval_precision: 0.6312
- eval_runtime: 15.886
- eval_samples_per_second: 99.647
- eval_steps_per_second: 6.232
- epoch: 6.0
- step: 2772

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10

### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3

# bertin-roberta-fine-tuned-text-classification-SL-data-augmentation-ds

This model is a fine-tuned version of bertin-project/bertin-roberta-base-spanish on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.9552
- eval_f1: 0.6062
- eval_recall: 0.5982
- eval_accuracy: 0.5982
- eval_precision: 0.6312
- eval_runtime: 15.886
- eval_samples_per_second: 99.647
- eval_steps_per_second: 6.232
- epoch: 6.0
- step: 2772 ## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10 ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 # bertin-roberta-fine-tuned-text-classification-SL-data-augmentation-ds

This model is a fine-tuned version of bertin-project/bertin-roberta-base-spanish on the None dataset.
It achieves the following results on the evaluation set:
- eval_loss: 1.9552
- eval_f1: 0.6062
- eval_recall: 0.5982
- eval_accuracy: 0.5982
- eval_precision: 0.6312
- eval_runtime: 15.886
- eval_samples_per_second: 99.647
- eval_steps_per_second: 6.232
- epoch: 6.0
- step: 2772 ## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10 ### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3