readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: roberta-base-bne-finetuned-recores2
    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-base-bne-finetuned-recores2
  
  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: 8.9761
  - Accuracy: 0.3113
  
  ## 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: 5e-05
  - train_batch_size: 1
  - eval_batch_size: 1
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 25
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 1.6094        | 1.0   | 1047  | 1.6094          | 0.2259   |
  | 1.6094        | 2.0   | 2094  | 1.6094          | 0.2121   |
  | 1.6094        | 3.0   | 3141  | 1.6094          | 0.2314   |
  | 1.6094        | 4.0   | 4188  | 1.6094          | 0.1956   |
  | 1.6094        | 5.0   | 5235  | 1.6094          | 0.2121   |
  | 1.6121        | 6.0   | 6282  | 1.6094          | 0.1818   |
  | 1.6094        | 7.0   | 7329  | 1.6094          | 0.2259   |
  | 1.6092        | 8.0   | 8376  | 1.6094          | 0.1736   |
  | 1.6094        | 9.0   | 9423  | 1.6094          | 0.1956   |
  | 1.6094        | 10.0  | 10470 | 1.6094          | 0.1736   |
  | 1.6094        | 11.0  | 11517 | 1.6094          | 0.1983   |
  | 1.6094        | 12.0  | 12564 | 1.6094          | 0.2176   |
  | 1.6094        | 13.0  | 13611 | 1.6094          | 0.1928   |
  | 1.6096        | 14.0  | 14658 | 1.6094          | 0.1846   |
  | 1.6145        | 15.0  | 15705 | 1.6094          | 0.2066   |
  | 1.6094        | 16.0  | 16752 | 1.6022          | 0.2121   |
  | 1.8471        | 17.0  | 17799 | 1.6101          | 0.1763   |
  | 2.8148        | 18.0  | 18846 | 2.7585          | 0.2452   |
  | 2.5445        | 19.0  | 19893 | 2.4576          | 0.2920   |
  | 1.9972        | 20.0  | 20940 | 3.6002          | 0.2865   |
  | 1.9844        | 21.0  | 21987 | 5.3809          | 0.3168   |
  | 2.849         | 22.0  | 23034 | 7.2230          | 0.3140   |
  | 1.4208        | 23.0  | 24081 | 8.0602          | 0.2975   |
  | 0.4045        | 24.0  | 25128 | 8.2947          | 0.3058   |
  | 0.3052        | 25.0  | 26175 | 8.9761          | 0.3113   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  