---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: roberta-finetuned-CPV_Spanish
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# roberta-finetuned-CPV_Spanish

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: 0.0417
- F1: 0.7757
- Roc Auc: 0.8684
- Accuracy: 0.7223
- Coverage Error: 11.7873
- Label Ranking Average Precision Score: 0.7728

## 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: 10

### Training results

| Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy | Coverage Error | Label Ranking Average Precision Score |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|:--------------:|:-------------------------------------:|
| 0.0582        | 1.0   | 2039  | 0.0554          | 0.6291 | 0.7463  | 0.5235   | 21.9642        | 0.5547                                |
| 0.0413        | 2.0   | 4078  | 0.0437          | 0.7054 | 0.7959  | 0.6239   | 17.5374        | 0.6589                                |
| 0.0295        | 3.0   | 6117  | 0.0403          | 0.7391 | 0.8285  | 0.6788   | 14.7700        | 0.7197                                |
| 0.022         | 4.0   | 8156  | 0.0390          | 0.7562 | 0.8414  | 0.6987   | 13.8217        | 0.7425                                |
| 0.0168        | 5.0   | 10195 | 0.0393          | 0.7600 | 0.8547  | 0.7007   | 12.8532        | 0.7542                                |
| 0.0127        | 6.0   | 12234 | 0.0396          | 0.7645 | 0.8606  | 0.7099   | 12.3890        | 0.7622                                |
| 0.0094        | 7.0   | 14273 | 0.0406          | 0.7642 | 0.8675  | 0.7027   | 11.8679        | 0.7628                                |
| 0.0066        | 8.0   | 16312 | 0.0404          | 0.7706 | 0.8641  | 0.7173   | 12.0876        | 0.7681                                |
| 0.0052        | 9.0   | 18351 | 0.0411          | 0.7748 | 0.8679  | 0.7182   | 11.8149        | 0.7705                                |
| 0.0042        | 10.0  | 20390 | 0.0417          | 0.7757 | 0.8684  | 0.7223   | 11.7873        | 0.7728                                |


### Framework versions

- Transformers 4.16.2
- Pytorch 1.9.1
- Datasets 1.18.4
- Tokenizers 0.11.6