readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: roberta-base_edos_b
    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_edos_b
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3797
  - Accuracy: 0.6337
  - F1: 0.6259
  - Precision: 0.6395
  - Recall: 0.6155
  
  ## 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 | Accuracy | F1     | Precision | Recall |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
  | 0.9275        | 1.0   | 638  | 0.8373          | 0.6502   | 0.6579 | 0.6348    | 0.6989 |
  | 0.5744        | 2.0   | 1276 | 1.1104          | 0.6337   | 0.6187 | 0.6332    | 0.6225 |
  | 0.334         | 3.0   | 1914 | 1.3797          | 0.6337   | 0.6259 | 0.6395    | 0.6155 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Datasets 2.8.0
  - Tokenizers 0.13.2
  