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# roberta-base-fine-tuned-text-classification-pesos-fixed-2

This model is a fine-tuned version of [PlanTL-GOB-ES/roberta-base-bne](https://huggingface.co/PlanTL-GOB-ES/roberta-base-bne) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0640
- F1: 0.5201
- Accuracy: 0.3302

## 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
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:|
| 0.0626        | 1.0   | 6527  | 0.0628          | 0.3484 | 0.1556   |
| 0.0522        | 2.0   | 13054 | 0.0568          | 0.4758 | 0.2903   |
| 0.0389        | 3.0   | 19581 | 0.0581          | 0.5229 | 0.3294   |
| 0.0264        | 4.0   | 26108 | 0.0640          | 0.5201 | 0.3302   |


### Framework versions

- Transformers 4.28.1
- Pytorch 1.12.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.3

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "metrics": ["f1", "accuracy"], "model-index": [{"name": "roberta-base-fine-tuned-text-classification-pesos-fixed-2", "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-base-fine-tuned-text-classification-pesos-fixed-2
=========================================================


This model is a fine-tuned version of PlanTL-GOB-ES/roberta-base-bne on an unknown dataset.
It achieves the following results on the evaluation set:


* Loss: 0.0640
* F1: 0.5201
* Accuracy: 0.3302


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
* num\_epochs: 4


### Training results



### Framework versions


* Transformers 4.28.1
* Pytorch 1.12.1+cu116
* Datasets 2.11.0
* 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
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.12.1+cu116
* Datasets 2.11.0
* 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
* num\_epochs: 4 ### Training results ### Framework versions


* Transformers 4.28.1
* Pytorch 1.12.1+cu116
* Datasets 2.11.0
* 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
* num\_epochs: 4### Training results### Framework versions


* Transformers 4.28.1
* Pytorch 1.12.1+cu116
* Datasets 2.11.0
* Tokenizers 0.13.3