readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-misogyny-sexism-indomain-mix-trans
    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-indomain-mix-trans
  
  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: 0.8397
  - Accuracy: 0.797
  - F1: 0.7691
  - Precision: 0.8918
  - Recall: 0.676
  - Mae: 0.203
  - Tn: 459
  - Fp: 41
  - Fn: 162
  - Tp: 338
  
  ## 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: 4
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall | Mae   | Tn  | Fp | Fn  | Tp  |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:-----:|:---:|:--:|:---:|:---:|
  | 0.2914        | 1.0   | 2711  | 0.5846          | 0.794    | 0.7726 | 0.8621    | 0.7    | 0.206 | 444 | 56 | 150 | 350 |
  | 0.2836        | 2.0   | 5422  | 0.6752          | 0.785    | 0.7491 | 0.8992    | 0.642  | 0.215 | 464 | 36 | 179 | 321 |
  | 0.2516        | 3.0   | 8133  | 0.7715          | 0.769    | 0.7214 | 0.9088    | 0.598  | 0.231 | 470 | 30 | 201 | 299 |
  | 0.2047        | 4.0   | 10844 | 0.8397          | 0.797    | 0.7691 | 0.8918    | 0.676  | 0.203 | 459 | 41 | 162 | 338 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  