readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-misogyny-sexism-indomain-mix
    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-indomain-mix
  
  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: 0.6467
  - Accuracy: 0.806
  - F1: 0.7820
  - Precision: 0.8923
  - Recall: 0.696
  - Mae: 0.194
  - Tn: 458
  - Fp: 42
  - Fn: 152
  - Tp: 348
  
  ## 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  |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----:|:---:|:--:|:---:|:---:|
  | 0.3643        | 1.0   | 2714  | 0.6727          | 0.718    | 0.6347 | 0.9007    | 0.49   | 0.282 | 473 | 27 | 255 | 245 |
  | 0.323         | 2.0   | 5428  | 0.7131          | 0.728    | 0.6402 | 0.9453    | 0.484  | 0.272 | 486 | 14 | 258 | 242 |
  | 0.2714        | 3.0   | 8142  | 0.6463          | 0.764    | 0.7115 | 0.9151    | 0.582  | 0.236 | 473 | 27 | 209 | 291 |
  | 0.2349        | 4.0   | 10856 | 0.6467          | 0.806    | 0.7820 | 0.8923    | 0.696  | 0.194 | 458 | 42 | 152 | 348 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  