readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-misogyny-sexism-tweets
    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. -->
  
  # xlm-roberta-base-misogyny-sexism-tweets
  
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.5009
  - Accuracy: 0.796
  - F1: 0.8132
  - Precision: 0.75
  - Recall: 0.888
  - Mae: 0.204
  - Tn: 352
  - Fp: 148
  - Fn: 56
  - Tp: 444
  
  ## 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: 2e-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  |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----:|:---:|:---:|:--:|:---:|
  | 0.4947        | 1.0   | 1646 | 0.4683          | 0.765    | 0.7866 | 0.7205    | 0.866  | 0.235 | 332 | 168 | 67 | 433 |
  | 0.4285        | 2.0   | 3292 | 0.4514          | 0.779    | 0.8004 | 0.7298    | 0.886  | 0.221 | 336 | 164 | 57 | 443 |
  | 0.3721        | 3.0   | 4938 | 0.4430          | 0.781    | 0.8060 | 0.7234    | 0.91   | 0.219 | 326 | 174 | 45 | 455 |
  | 0.3127        | 4.0   | 6584 | 0.5009          | 0.796    | 0.8132 | 0.75      | 0.888  | 0.204 | 352 | 148 | 56 | 444 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  