readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: roberta-large-mnli-misogyny-sexism-4tweets-3e-05-0.07
    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-05-0.07
  
  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: 0.9791
  - Accuracy: 0.7074
  - F1: 0.7230
  - Precision: 0.6414
  - Recall: 0.8283
  - Mae: 0.2926
  - Tn: 325
  - Fp: 213
  - Fn: 79
  - Tp: 381
  
  ## 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  |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:---:|:---:|:---:|:---:|
  | 0.515         | 1.0   | 1346 | 0.6865          | 0.6323   | 0.6501 | 0.5789    | 0.7413 | 0.3677 | 290 | 248 | 119 | 341 |
  | 0.4468        | 2.0   | 2692 | 0.7147          | 0.6493   | 0.6908 | 0.5818    | 0.85   | 0.3507 | 257 | 281 | 69  | 391 |
  | 0.3758        | 3.0   | 4038 | 0.8377          | 0.6713   | 0.7045 | 0.6015    | 0.85   | 0.3287 | 279 | 259 | 69  | 391 |
  | 0.2928        | 4.0   | 5384 | 0.9791          | 0.7074   | 0.7230 | 0.6414    | 0.8283 | 0.2926 | 325 | 213 | 79  | 381 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  