readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-misogyny-sexism-decay0.05-fr-indomain
    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-decay0.05-fr-indomain
  
  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: 1.2200
  - Accuracy: 0.8708
  - F1: 0.0040
  - Precision: 0.1
  - Recall: 0.0021
  - Mae: 0.1292
  
  ## 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: 7
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall | Mae    |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.2085        | 1.0   | 2302  | 1.0000          | 0.8674   | 0.0212 | 0.1719    | 0.0113 | 0.1326 |
  | 0.18          | 2.0   | 4604  | 1.0566          | 0.8527   | 0.0157 | 0.0520    | 0.0093 | 0.1473 |
  | 0.1614        | 3.0   | 6906  | 1.1284          | 0.8673   | 0.0020 | 0.0222    | 0.0010 | 0.1327 |
  | 0.1428        | 4.0   | 9208  | 1.1329          | 0.8714   | 0.0020 | 0.0714    | 0.0010 | 0.1286 |
  | 0.1467        | 5.0   | 11510 | 1.1814          | 0.8708   | 0.0040 | 0.1       | 0.0021 | 0.1292 |
  | 0.1375        | 6.0   | 13812 | 1.2020          | 0.8706   | 0.0020 | 0.05      | 0.0010 | 0.1294 |
  | 0.1093        | 7.0   | 16114 | 1.2200          | 0.8708   | 0.0040 | 0.1       | 0.0021 | 0.1292 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  