readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-finetuned-misogyny-sexism2
    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-finetuned-misogyny-sexism2
  
  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: 1.5455
  - Accuracy: 0.7628
  - F1: 0.7606
  - Precision: 0.7384
  - Recall: 0.7842
  - Mae: 0.2372
  
  ## 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Mae    |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.1887        | 1.0   | 2656 | 1.2287          | 0.7790   | 0.7863 | 0.7342    | 0.8463 | 0.2210 |
  | 0.1556        | 2.0   | 5312 | 1.4944          | 0.7633   | 0.7547 | 0.7516    | 0.7579 | 0.2367 |
  | 0.1172        | 3.0   | 7968 | 1.5455          | 0.7628   | 0.7606 | 0.7384    | 0.7842 | 0.2372 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  