---
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: 0.0463
- F1: 0.7931
- Roc Auc: 0.8858
- Accuracy: 0.7376
- Coverage Error: 10.3626
- Label Ranking Average Precision Score: 0.7968

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|:--------------:|:-------------------------------------:|
| 0.0355        | 1.0   | 9054  | 0.0366          | 0.7550 | 0.8373  | 0.6950   | 14.1539        | 0.7347                                |
| 0.0309        | 2.0   | 18108 | 0.0330          | 0.7773 | 0.8553  | 0.7204   | 12.6503        | 0.7647                                |
| 0.0234        | 3.0   | 27162 | 0.0330          | 0.7836 | 0.8693  | 0.7293   | 11.6192        | 0.7799                                |
| 0.0159        | 4.0   | 36216 | 0.0348          | 0.7830 | 0.8709  | 0.7291   | 11.5355        | 0.7810                                |
| 0.0109        | 5.0   | 45270 | 0.0376          | 0.7789 | 0.8786  | 0.7201   | 10.9898        | 0.7812                                |
| 0.0075        | 6.0   | 54324 | 0.0397          | 0.7838 | 0.8813  | 0.7241   | 10.7035        | 0.7861                                |
| 0.0039        | 7.0   | 63378 | 0.0415          | 0.7888 | 0.8818  | 0.7309   | 10.6559        | 0.7898                                |
| 0.0028        | 8.0   | 72432 | 0.0437          | 0.7906 | 0.8838  | 0.7326   | 10.5117        | 0.7924                                |
| 0.0016        | 9.0   | 81486 | 0.0453          | 0.7908 | 0.8890  | 0.7308   | 10.0988        | 0.7957                                |
| 0.001         | 10.0  | 90540 | 0.0463          | 0.7931 | 0.8858  | 0.7376   | 10.3626        | 0.7968                                |


### Framework versions

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