readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: run-4
    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. -->
  
  # run-4
  
  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: 2.6296
  - Accuracy: 0.685
  - Precision: 0.6248
  - Recall: 0.6164
  - F1: 0.6188
  
  ## 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: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 1.0195        | 1.0   | 50   | 0.8393          | 0.615    | 0.4126    | 0.5619 | 0.4606 |
  | 0.7594        | 2.0   | 100  | 0.7077          | 0.7      | 0.6896    | 0.6663 | 0.6178 |
  | 0.5515        | 3.0   | 150  | 0.9342          | 0.68     | 0.6334    | 0.5989 | 0.6016 |
  | 0.3739        | 4.0   | 200  | 0.7755          | 0.735    | 0.7032    | 0.7164 | 0.7063 |
  | 0.2648        | 5.0   | 250  | 0.9200          | 0.7      | 0.6584    | 0.6677 | 0.6611 |
  | 0.1726        | 6.0   | 300  | 1.1898          | 0.71     | 0.6653    | 0.6550 | 0.6570 |
  | 0.1452        | 7.0   | 350  | 1.5086          | 0.73     | 0.6884    | 0.6768 | 0.6812 |
  | 0.0856        | 8.0   | 400  | 2.6159          | 0.68     | 0.6754    | 0.5863 | 0.5951 |
  | 0.1329        | 9.0   | 450  | 1.9491          | 0.71     | 0.6692    | 0.6442 | 0.6463 |
  | 0.0322        | 10.0  | 500  | 1.7897          | 0.74     | 0.6977    | 0.6939 | 0.6946 |
  | 0.0345        | 11.0  | 550  | 1.9100          | 0.725    | 0.6827    | 0.6853 | 0.6781 |
  | 0.026         | 12.0  | 600  | 2.5041          | 0.68     | 0.6246    | 0.6115 | 0.6137 |
  | 0.0084        | 13.0  | 650  | 2.5343          | 0.715    | 0.6708    | 0.6617 | 0.6637 |
  | 0.0145        | 14.0  | 700  | 2.4112          | 0.715    | 0.6643    | 0.6595 | 0.6614 |
  | 0.0119        | 15.0  | 750  | 2.5303          | 0.705    | 0.6479    | 0.6359 | 0.6390 |
  | 0.0026        | 16.0  | 800  | 2.6299          | 0.705    | 0.6552    | 0.6447 | 0.6455 |
  | 0.0077        | 17.0  | 850  | 2.4044          | 0.715    | 0.6667    | 0.6576 | 0.6596 |
  | 0.0055        | 18.0  | 900  | 2.8077          | 0.68     | 0.6208    | 0.6065 | 0.6098 |
  | 0.0078        | 19.0  | 950  | 2.5608          | 0.68     | 0.6200    | 0.6104 | 0.6129 |
  | 0.0018        | 20.0  | 1000 | 2.6296          | 0.685    | 0.6248    | 0.6164 | 0.6188 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Tokenizers 0.13.2
  