readme: ---
  language: es
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - sqac
  
  metrics:
  - f1
  model-index:
  - name: roberta-base-bne-finetuned-sqac
    results:
    - task:
        name: Question Answering
        type: Question-Answering
      dataset:
        name: sqac
        type: sqac
        args: 
      metrics:
      - name: f1
        type: f1
        value: 0.7903
  ---
  
  <!-- 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-sqac
  
  This model is a fine-tuned version of [BSC-TeMU/roberta-base-bne](https://huggingface.co/BSC-TeMU/roberta-base-bne) on the sqac dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2111
  
  ## 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 0.9971        | 1.0   | 1196 | 0.8646          |
  | 0.482         | 2.0   | 2392 | 0.9334          |
  | 0.1652        | 3.0   | 3588 | 1.2111          |
  
  
  ### Framework versions
  
  - Transformers 4.11.2
  - Pytorch 1.9.0+cu111
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  