readme: ---
  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: 0.0422
  - F1: 0.7739
  - Roc Auc: 0.8704
  - Accuracy: 0.7201
  - Coverage Error: 11.5798
  - Label Ranking Average Precision Score: 0.7742
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|:--------------:|:-------------------------------------:|
  | 0.0579        | 1.0   | 2039  | 0.0548          | 0.6327 | 0.7485  | 0.5274   | 21.7879        | 0.5591                                |
  | 0.0411        | 2.0   | 4078  | 0.0441          | 0.7108 | 0.8027  | 0.6386   | 16.8647        | 0.6732                                |
  | 0.0294        | 3.0   | 6117  | 0.0398          | 0.7437 | 0.8295  | 0.6857   | 14.6700        | 0.7249                                |
  | 0.0223        | 4.0   | 8156  | 0.0389          | 0.7568 | 0.8453  | 0.7056   | 13.3552        | 0.7494                                |
  | 0.0163        | 5.0   | 10195 | 0.0397          | 0.7626 | 0.8569  | 0.7097   | 12.5895        | 0.7620                                |
  | 0.0132        | 6.0   | 12234 | 0.0395          | 0.7686 | 0.8620  | 0.7126   | 12.1926        | 0.7656                                |
  | 0.0095        | 7.0   | 14273 | 0.0409          | 0.7669 | 0.8694  | 0.7109   | 11.5978        | 0.7700                                |
  | 0.0066        | 8.0   | 16312 | 0.0415          | 0.7705 | 0.8726  | 0.7107   | 11.4252        | 0.7714                                |
  | 0.0055        | 9.0   | 18351 | 0.0417          | 0.7720 | 0.8689  | 0.7163   | 11.6987        | 0.7716                                |
  | 0.0045        | 10.0  | 20390 | 0.0422          | 0.7739 | 0.8704  | 0.7201   | 11.5798        | 0.7742                                |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.12.1
  