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

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:
- Loss: 2.7374
- F1: 0.1580
- Recall: 0.3233
- Accuracy: 0.3233
- Precision: 0.1045

## 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: 0.0001
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:---------:|
| 2.7132        | 1.0   | 6530  | 2.7463          | 0.1580 | 0.3233 | 0.3233   | 0.1045    |
| 2.7441        | 2.0   | 13060 | 2.7423          | 0.1580 | 0.3233 | 0.3233   | 0.1045    |
| 2.7328        | 3.0   | 19590 | 2.7365          | 0.1580 | 0.3233 | 0.3233   | 0.1045    |
| 2.7464        | 4.0   | 26120 | 2.7374          | 0.1580 | 0.3233 | 0.3233   | 0.1045    |
| 2.7178        | 5.0   | 32650 | 2.7374          | 0.1580 | 0.3233 | 0.3233   | 0.1045    |


### 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"], "metrics": ["f1", "recall", "accuracy", "precision"], "model-index": [{"name": "bertin-roberta-fine-tuned-text-classification-SL-data-augmentation-test", "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-test
=======================================================================


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:


* Loss: 2.7374
* F1: 0.1580
* Recall: 0.3233
* Accuracy: 0.3233
* Precision: 0.1045


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: 0.0001
* 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: 0.0001
* 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-cc-by-4.0 #autotrain_compatible #endpoints_compatible #region-us 
 ### Training hyperparameters


The following hyperparameters were used during training:


* learning\_rate: 0.0001
* 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