readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: run-3
    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-3
  
  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: 2.4223
  - Accuracy: 0.75
  - Precision: 0.7128
  - Recall: 0.6998
  - F1: 0.7043
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | 1.0025        | 1.0   | 50   | 0.8925          | 0.63     | 0.6703    | 0.5704 | 0.5060 |
  | 0.8187        | 2.0   | 100  | 0.7915          | 0.595    | 0.6007    | 0.5926 | 0.5344 |
  | 0.5671        | 3.0   | 150  | 0.9573          | 0.695    | 0.6520    | 0.6350 | 0.6380 |
  | 0.3218        | 4.0   | 200  | 0.9195          | 0.68     | 0.6447    | 0.6539 | 0.6461 |
  | 0.2208        | 5.0   | 250  | 1.2429          | 0.715    | 0.6801    | 0.6617 | 0.6663 |
  | 0.1614        | 6.0   | 300  | 1.5295          | 0.71     | 0.6736    | 0.6543 | 0.6423 |
  | 0.1129        | 7.0   | 350  | 2.1055          | 0.71     | 0.6779    | 0.6413 | 0.6511 |
  | 0.098         | 8.0   | 400  | 1.9579          | 0.705    | 0.6697    | 0.6558 | 0.6601 |
  | 0.0479        | 9.0   | 450  | 2.0535          | 0.72     | 0.6794    | 0.6663 | 0.6711 |
  | 0.0173        | 10.0  | 500  | 2.5381          | 0.7      | 0.6838    | 0.6604 | 0.6608 |
  | 0.0308        | 11.0  | 550  | 2.4592          | 0.735    | 0.7014    | 0.6851 | 0.6901 |
  | 0.0265        | 12.0  | 600  | 2.3131          | 0.725    | 0.6910    | 0.6845 | 0.6849 |
  | 0.016         | 13.0  | 650  | 2.4025          | 0.74     | 0.7035    | 0.6915 | 0.6949 |
  | 0.013         | 14.0  | 700  | 2.3933          | 0.745    | 0.7070    | 0.6831 | 0.6909 |
  | 0.016         | 15.0  | 750  | 2.6819          | 0.725    | 0.7006    | 0.6738 | 0.6759 |
  | 0.0126        | 16.0  | 800  | 2.3679          | 0.74     | 0.7050    | 0.6839 | 0.6898 |
  | 0.0023        | 17.0  | 850  | 2.5252          | 0.745    | 0.7119    | 0.6880 | 0.6933 |
  | 0.01          | 18.0  | 900  | 2.5598          | 0.74     | 0.7056    | 0.6828 | 0.6906 |
  | 0.0093        | 19.0  | 950  | 2.4353          | 0.745    | 0.7057    | 0.6922 | 0.6974 |
  | 0.0039        | 20.0  | 1000 | 2.4223          | 0.75     | 0.7128    | 0.6998 | 0.7043 |
  
  
  ### Framework versions
  
  - Transformers 4.25.1
  - Pytorch 1.13.1+cu116
  - Tokenizers 0.13.2
  