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# roberta-bne-fine-tuned-text-classification-SL-data-augmentation-dss

This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3544
- F1: 0.4643
- Recall: 0.4629
- Accuracy: 0.4629
- Precision: 0.4880

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Recall | Accuracy | Precision |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:--------:|:---------:|
| 3.3244        | 1.0   | 562  | 2.7345          | 0.3306 | 0.3939 | 0.3939   | 0.3500    |
| 2.4396        | 2.0   | 1124 | 2.4186          | 0.4061 | 0.4468 | 0.4468   | 0.4349    |
| 1.8841        | 3.0   | 1686 | 2.2738          | 0.4453 | 0.4702 | 0.4702   | 0.4583    |
| 1.4409        | 4.0   | 2248 | 2.2984          | 0.4500 | 0.4582 | 0.4582   | 0.4625    |
| 1.0328        | 5.0   | 2810 | 2.3544          | 0.4643 | 0.4629 | 0.4629   | 0.4880    |


### Framework versions

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

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1", "recall", "accuracy", "precision"], "model-index": [{"name": "roberta-bne-fine-tuned-text-classification-SL-data-augmentation-dss", "results": []}]}
transformers pytorch roberta text-classification generated_from_trainer license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #roberta #text-classification #generated_from_trainer #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 

roberta-bne-fine-tuned-text-classification-SL-data-augmentation-dss
===================================================================


This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-bne on the None dataset.
It achieves the following results on the evaluation set:


* Loss: 2.3544
* F1: 0.4643
* Recall: 0.4629
* Accuracy: 0.4629
* Precision: 0.4880


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: 5


### Training results



### Framework versions


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



### 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: 5 ### Training results ### 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-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### 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: 5 ### Training results ### Framework versions


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