readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: roberta-base-bne-finetuned-detests
    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-detests
  
  This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.0716
  - Accuracy: 0.8396
  
  ## 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: 16
  - eval_batch_size: 16
  - 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 | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.2972        | 1.0   | 153  | 0.3359          | 0.8462   |
  | 0.2924        | 2.0   | 306  | 0.4509          | 0.8249   |
  | 0.0663        | 3.0   | 459  | 0.7186          | 0.8527   |
  | 0.0018        | 4.0   | 612  | 0.8081          | 0.8314   |
  | 0.0004        | 5.0   | 765  | 0.8861          | 0.8560   |
  | 0.0003        | 6.0   | 918  | 0.9940          | 0.8380   |
  | 0.0002        | 7.0   | 1071 | 1.0330          | 0.8396   |
  | 0.0002        | 8.0   | 1224 | 1.0545          | 0.8396   |
  | 0.0002        | 9.0   | 1377 | 1.0673          | 0.8396   |
  | 0.0002        | 10.0  | 1530 | 1.0716          | 0.8396   |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  