readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: xlm-roberta-base-finetuned-misogyny-sexism-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-sexism-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: 0.0295
  - Accuracy: 0.9924
  - F1: 0.9922
  - Precision: 0.9845
  - Recall: 1.0
  - Mae: 0.0076
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.3723        | 1.0   | 2778  | 0.4446          | 0.7876   | 0.7967 | 0.7375    | 0.8663 | 0.2124 |
  | 0.3257        | 2.0   | 5556  | 0.4372          | 0.8381   | 0.8509 | 0.7634    | 0.9611 | 0.1619 |
  | 0.2903        | 3.0   | 8334  | 0.2384          | 0.9044   | 0.9055 | 0.8627    | 0.9526 | 0.0956 |
  | 0.244         | 4.0   | 11112 | 0.1500          | 0.9514   | 0.9509 | 0.9245    | 0.9789 | 0.0486 |
  | 0.2169        | 5.0   | 13890 | 0.1024          | 0.9717   | 0.9709 | 0.9580    | 0.9842 | 0.0283 |
  | 0.1987        | 6.0   | 16668 | 0.0879          | 0.9767   | 0.9762 | 0.9612    | 0.9916 | 0.0233 |
  | 0.1659        | 7.0   | 19446 | 0.0557          | 0.9848   | 0.9843 | 0.9812    | 0.9874 | 0.0152 |
  | 0.1593        | 8.0   | 22224 | 0.0397          | 0.9894   | 0.9891 | 0.9794    | 0.9989 | 0.0106 |
  | 0.1384        | 9.0   | 25002 | 0.0315          | 0.9924   | 0.9922 | 0.9855    | 0.9989 | 0.0076 |
  | 0.1186        | 10.0  | 27780 | 0.0295          | 0.9924   | 0.9922 | 0.9845    | 1.0    | 0.0076 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.9.0+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  