readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - amazon_reviews_multi
  metrics:
  - accuracy
  model-index:
  - name: roberta-base-bne-finetuned-amazon_reviews_multi
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: amazon_reviews_multi
        type: amazon_reviews_multi
        args: es
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.93125
  ---
  
  <!-- 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-amazon_reviews_multi
  
  This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the amazon_reviews_multi dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.2328
  - Accuracy: 0.9313
  
  ## 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: 2
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|
  | 0.1985        | 1.0   | 1250 | 0.1730          | 0.9327   |
  | 0.0982        | 2.0   | 2500 | 0.2328          | 0.9313   |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - Pytorch 1.10.0+cu111
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  