readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: roberta-base-finetuned-filtered-0609
    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-finetuned-filtered-0609
  
  This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1343
  - Accuracy: 0.9824
  - Precision: 0.9824
  - Recall: 0.9824
  - F1: 0.9824
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_steps: 1000
  - num_epochs: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 0.1817        | 1.0   | 3180  | 0.1883          | 0.9651   | 0.9654    | 0.9651 | 0.9651 |
  | 0.1647        | 2.0   | 6360  | 0.1264          | 0.9777   | 0.9778    | 0.9777 | 0.9777 |
  | 0.1295        | 3.0   | 9540  | 0.1514          | 0.9723   | 0.9724    | 0.9723 | 0.9723 |
  | 0.0991        | 4.0   | 12720 | 0.1487          | 0.9761   | 0.9763    | 0.9761 | 0.9761 |
  | 0.0749        | 5.0   | 15900 | 0.1119          | 0.9802   | 0.9802    | 0.9802 | 0.9802 |
  | 0.0532        | 6.0   | 19080 | 0.1357          | 0.9789   | 0.9790    | 0.9789 | 0.9789 |
  | 0.0471        | 7.0   | 22260 | 0.1397          | 0.9780   | 0.9782    | 0.9780 | 0.9780 |
  | 0.0153        | 8.0   | 25440 | 0.1568          | 0.9777   | 0.9778    | 0.9777 | 0.9777 |
  | 0.0147        | 9.0   | 28620 | 0.1274          | 0.9824   | 0.9824    | 0.9824 | 0.9824 |
  | 0.0135        | 10.0  | 31800 | 0.1343          | 0.9824   | 0.9824    | 0.9824 | 0.9824 |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.9.1+cu111
  - Datasets 1.16.1
  - Tokenizers 0.12.1
  