readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-misogyny-sexism-out-of-sample-test
    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-out-of-sample-test
  
  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: 2.4319
  - Accuracy: 0.6329
  - F1: 0.5384
  - Precision: 0.6311
  - Recall: 0.4694
  - Mae: 0.3671
  
  ## 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: 10
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall | Mae    |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.3447        | 1.0   | 2157  | 0.8407          | 0.6264   | 0.4817 | 0.6555    | 0.3808 | 0.3736 |
  | 0.3105        | 2.0   | 4314  | 0.9660          | 0.6244   | 0.4840 | 0.6480    | 0.3863 | 0.3756 |
  | 0.3036        | 3.0   | 6471  | 1.0797          | 0.6218   | 0.5499 | 0.6014    | 0.5065 | 0.3782 |
  | 0.2643        | 4.0   | 8628  | 1.6355          | 0.6301   | 0.4790 | 0.6696    | 0.3728 | 0.3699 |
  | 0.2591        | 5.0   | 10785 | 1.4902          | 0.6173   | 0.5308 | 0.6020    | 0.4747 | 0.3827 |
  | 0.2052        | 6.0   | 12942 | 1.6884          | 0.6236   | 0.5166 | 0.6235    | 0.4410 | 0.3764 |
  | 0.2017        | 7.0   | 15099 | 2.1026          | 0.6323   | 0.5341 | 0.6325    | 0.4622 | 0.3677 |
  | 0.1715        | 8.0   | 17256 | 2.3440          | 0.6292   | 0.5381 | 0.6229    | 0.4736 | 0.3708 |
  | 0.1543        | 9.0   | 19413 | 2.2136          | 0.6301   | 0.5411 | 0.6230    | 0.4783 | 0.3699 |
  | 0.1456        | 10.0  | 21570 | 2.4319          | 0.6329   | 0.5384 | 0.6311    | 0.4694 | 0.3671 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.9.0+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  