readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  datasets:
  - tecla
  metrics:
  - accuracy
  model-index:
  - name: roberta-base-ca-finetuned-mnli
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: tecla
        type: tecla
        args: tecla
      metrics:
      - name: Accuracy
        type: accuracy
        value: 0.7361816335412737
  ---
  
  <!-- 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-ca-finetuned-mnli
  
  This model is a fine-tuned version of [BSC-TeMU/roberta-base-ca](https://huggingface.co/BSC-TeMU/roberta-base-ca) on the tecla dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9354
  - Accuracy: 0.7362
  
  ## 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 |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
  | 0.8465        | 1.0   | 6888  | 0.8222          | 0.6990   |
  | 0.6966        | 2.0   | 13776 | 0.7872          | 0.7157   |
  | 0.5643        | 3.0   | 20664 | 0.8060          | 0.7268   |
  | 0.4435        | 4.0   | 27552 | 0.8470          | 0.7333   |
  | 0.3206        | 5.0   | 34440 | 0.9354          | 0.7362   |
  
  
  ### Framework versions
  
  - Transformers 4.11.3
  - Pytorch 1.9.0+cu111
  - Datasets 1.12.1
  - Tokenizers 0.10.3
  