readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-finetuned-misogyny
    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
  
  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: 0.7913
  - Accuracy: 0.8925
  - F1: 0.8280
  - Precision: 0.8240
  - Recall: 0.8320
  - Mae: 0.1075
  
  ## 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    |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.328         | 1.0   | 828  | 0.3477          | 0.8732   | 0.7831 | 0.8366    | 0.7359 | 0.1268 |
  | 0.273         | 2.0   | 1656 | 0.2921          | 0.8910   | 0.8269 | 0.8171    | 0.8369 | 0.1090 |
  | 0.2342        | 3.0   | 2484 | 0.3222          | 0.8834   | 0.8176 | 0.7965    | 0.8398 | 0.1166 |
  | 0.2132        | 4.0   | 3312 | 0.3801          | 0.8852   | 0.8223 | 0.7933    | 0.8534 | 0.1148 |
  | 0.1347        | 5.0   | 4140 | 0.5474          | 0.8955   | 0.8314 | 0.8346    | 0.8282 | 0.1045 |
  | 0.1187        | 6.0   | 4968 | 0.5853          | 0.8886   | 0.8137 | 0.8475    | 0.7825 | 0.1114 |
  | 0.0968        | 7.0   | 5796 | 0.6378          | 0.8916   | 0.8267 | 0.8223    | 0.8311 | 0.1084 |
  | 0.0533        | 8.0   | 6624 | 0.7397          | 0.8831   | 0.8191 | 0.7899    | 0.8505 | 0.1169 |
  | 0.06          | 9.0   | 7452 | 0.8112          | 0.8861   | 0.8224 | 0.7987    | 0.8476 | 0.1139 |
  | 0.0287        | 10.0  | 8280 | 0.7913          | 0.8925   | 0.8280 | 0.8240    | 0.8320 | 0.1075 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.9.0+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  