readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-finetuned-misogyny-sexism
    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-sexism
  
  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: 0.9064
  - Accuracy: 0.8334
  - F1: 0.3322
  - Precision: 0.2498
  - Recall: 0.4961
  - Mae: 0.1666
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.3869        | 1.0   | 2395  | 0.2905          | 0.8778   | 0.3528 | 0.3164    | 0.3988 | 0.1222 |
  | 0.3539        | 2.0   | 4790  | 0.4143          | 0.8278   | 0.3465 | 0.2536    | 0.5467 | 0.1722 |
  | 0.3124        | 3.0   | 7185  | 0.3327          | 0.8568   | 0.3583 | 0.2864    | 0.4786 | 0.1432 |
  | 0.2817        | 4.0   | 9580  | 0.5621          | 0.7329   | 0.3092 | 0.1972    | 0.7160 | 0.2671 |
  | 0.2651        | 5.0   | 11975 | 0.4376          | 0.8520   | 0.3607 | 0.2821    | 0.5    | 0.1480 |
  | 0.2249        | 6.0   | 14370 | 0.5581          | 0.8326   | 0.3312 | 0.2485    | 0.4961 | 0.1674 |
  | 0.1958        | 7.0   | 16765 | 0.6728          | 0.8382   | 0.3234 | 0.2484    | 0.4630 | 0.1618 |
  | 0.1899        | 8.0   | 19160 | 0.7404          | 0.8304   | 0.3316 | 0.2471    | 0.5039 | 0.1696 |
  | 0.1619        | 9.0   | 21555 | 0.8309          | 0.8461   | 0.3382 | 0.2639    | 0.4708 | 0.1539 |
  | 0.1453        | 10.0  | 23950 | 0.9064          | 0.8334   | 0.3322 | 0.2498    | 0.4961 | 0.1666 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  