readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: roberta-large-mnli-misogyny-sexism-4tweets-3e-05-0.05
    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-large-mnli-misogyny-sexism-4tweets-3e-05-0.05
  
  This model is a fine-tuned version of [roberta-large-mnli](https://huggingface.co/roberta-large-mnli) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.9069
  - Accuracy: 0.6914
  - F1: 0.7061
  - Precision: 0.6293
  - Recall: 0.8043
  - Mae: 0.3086
  - Tn: 320
  - Fp: 218
  - Fn: 90
  - Tp: 370
  
  ## 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: 3e-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: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Mae    | Tn  | Fp  | Fn  | Tp  |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:---:|:---:|:---:|:---:|
  | 0.5248        | 1.0   | 1346 | 0.7245          | 0.6513   | 0.6234 | 0.6207    | 0.6261 | 0.3487 | 362 | 176 | 172 | 288 |
  | 0.4553        | 2.0   | 2692 | 0.6894          | 0.6693   | 0.7043 | 0.5991    | 0.8543 | 0.3307 | 275 | 263 | 67  | 393 |
  | 0.3753        | 3.0   | 4038 | 0.6966          | 0.7234   | 0.7326 | 0.6608    | 0.8217 | 0.2766 | 344 | 194 | 82  | 378 |
  | 0.2986        | 4.0   | 5384 | 0.9069          | 0.6914   | 0.7061 | 0.6293    | 0.8043 | 0.3086 | 320 | 218 | 90  | 370 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  