readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-misogyny-sexism-4tweets-2e-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. -->
  
  # xlm-roberta-base-misogyny-sexism-4tweets-2e-05-0.05
  
  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: 0.7585
  - Accuracy: 0.6496
  - F1: 0.6615
  - Precision: 0.5962
  - Recall: 0.7429
  - Mae: 0.3504
  - Tn: 306
  - Fp: 231
  - Fn: 118
  - Tp: 341
  
  ## 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  |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:---:|:---:|:---:|:---:|
  | 0.4988        | 1.0   | 1655 | 0.6627          | 0.6165   | 0.6029 | 0.5765    | 0.6318 | 0.3835 | 324 | 213 | 169 | 290 |
  | 0.4367        | 2.0   | 3310 | 0.6523          | 0.6687   | 0.6118 | 0.6650    | 0.5664 | 0.3313 | 406 | 131 | 199 | 260 |
  | 0.3749        | 3.0   | 4965 | 0.6893          | 0.6616   | 0.6686 | 0.6093    | 0.7407 | 0.3384 | 319 | 218 | 119 | 340 |
  | 0.3274        | 4.0   | 6620 | 0.7585          | 0.6496   | 0.6615 | 0.5962    | 0.7429 | 0.3504 | 306 | 231 | 118 | 341 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  