readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-finetuned-misogyny-sexism22
    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-sexism22
  
  This model was trained from scratch on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.7529
  - Accuracy: 0.7628
  - F1: 0.7647
  - Precision: 0.7306
  - Recall: 0.8021
  - Mae: 0.2372
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.1603        | 1.0   | 2656  | 1.5452          | 0.7491   | 0.7660 | 0.6940    | 0.8547 | 0.2509 |
  | 0.1463        | 2.0   | 5312  | 1.7572          | 0.7511   | 0.7208 | 0.7820    | 0.6684 | 0.2489 |
  | 0.1514        | 3.0   | 7968  | 1.4921          | 0.7628   | 0.7509 | 0.7578    | 0.7442 | 0.2372 |
  | 0.139         | 4.0   | 10624 | 1.4875          | 0.7648   | 0.7582 | 0.7492    | 0.7674 | 0.2352 |
  | 0.1279        | 5.0   | 13280 | 1.3906          | 0.7719   | 0.7742 | 0.7383    | 0.8137 | 0.2281 |
  | 0.1147        | 6.0   | 15936 | 1.5939          | 0.7709   | 0.7709 | 0.7420    | 0.8021 | 0.2291 |
  | 0.0881        | 7.0   | 18592 | 1.7529          | 0.7628   | 0.7647 | 0.7306    | 0.8021 | 0.2372 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  