readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-misogyny-sexism-4tweets-2e-05-0.025
    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-05-0.025
  
  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: 0.7588
  - Accuracy: 0.6553
  - F1: 0.6803
  - Precision: 0.5942
  - Recall: 0.7957
  - Mae: 0.3447
  - Tn: 288
  - Fp: 250
  - Fn: 94
  - Tp: 366
  
  ## 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  |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:---:|:---:|:--:|:---:|
  | 0.519         | 1.0   | 1346 | 0.6736          | 0.6092   | 0.6585 | 0.5513    | 0.8174 | 0.3908 | 232 | 306 | 84 | 376 |
  | 0.4601        | 2.0   | 2692 | 0.6892          | 0.6403   | 0.6876 | 0.5733    | 0.8587 | 0.3597 | 244 | 294 | 65 | 395 |
  | 0.4169        | 3.0   | 4038 | 0.7763          | 0.6393   | 0.6875 | 0.5723    | 0.8609 | 0.3607 | 242 | 296 | 64 | 396 |
  | 0.3573        | 4.0   | 5384 | 0.7588          | 0.6553   | 0.6803 | 0.5942    | 0.7957 | 0.3447 | 288 | 250 | 94 | 366 |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  