readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-finetuned-misogyny-en-it-hi-beng
    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-en-it-hi-beng
  
  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: 0.0140
  - Accuracy: 0.9970
  - F1: 0.9969
  - Precision: 0.9937
  - Recall: 1.0
  - Mae: 0.0030
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.3131        | 1.0   | 1759  | 0.4655          | 0.7820   | 0.7682 | 0.7855    | 0.7516 | 0.2180 |
  | 0.2644        | 2.0   | 3518  | 0.3231          | 0.8619   | 0.8665 | 0.8091    | 0.9326 | 0.1381 |
  | 0.2408        | 3.0   | 5277  | 0.3515          | 0.8801   | 0.8877 | 0.8071    | 0.9863 | 0.1199 |
  | 0.1927        | 4.0   | 7036  | 0.1428          | 0.9514   | 0.9512 | 0.9194    | 0.9853 | 0.0486 |
  | 0.1333        | 5.0   | 8795  | 0.1186          | 0.9712   | 0.9707 | 0.9478    | 0.9947 | 0.0288 |
  | 0.1163        | 6.0   | 10554 | 0.0546          | 0.9879   | 0.9875 | 0.9803    | 0.9947 | 0.0121 |
  | 0.0854        | 7.0   | 12313 | 0.0412          | 0.9899   | 0.9896 | 0.9804    | 0.9989 | 0.0101 |
  | 0.086         | 8.0   | 14072 | 0.0252          | 0.9949   | 0.9948 | 0.9896    | 1.0    | 0.0051 |
  | 0.0395        | 9.0   | 15831 | 0.0179          | 0.9965   | 0.9963 | 0.9927    | 1.0    | 0.0035 |
  | 0.0343        | 10.0  | 17590 | 0.0140          | 0.9970   | 0.9969 | 0.9937    | 1.0    | 0.0030 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.9.0+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  