readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  model-index:
  - name: roberta-base-bne-finetuned-mnli
    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-mnli
  
  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: 0.2869
  - Accuracy: 0.9012
  
  ## 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: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.3222        | 1.0   | 1255 | 0.2869          | 0.9012   |
  | 0.2418        | 2.0   | 2510 | 0.3125          | 0.8987   |
  | 0.1726        | 3.0   | 3765 | 0.4120          | 0.8943   |
  | 0.0685        | 4.0   | 5020 | 0.5239          | 0.8919   |
  | 0.0245        | 5.0   | 6275 | 0.5910          | 0.8947   |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  