readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-base-multilingual-cased-finetuned-misogyny-sexism-multilingual
    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. -->
  
  # distilbert-base-multilingual-cased-finetuned-misogyny-sexism-multilingual
  
  This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.2382
  - Accuracy: 0.8435
  - F1: 0.7857
  - Precision: 0.7689
  - Recall: 0.8031
  - Mae: 0.1565
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.3663        | 1.0   | 2062  | 0.3696          | 0.8363   | 0.7605 | 0.7967    | 0.7274 | 0.1637 |
  | 0.2937        | 2.0   | 4124  | 0.3592          | 0.8504   | 0.7891 | 0.7948    | 0.7834 | 0.1496 |
  | 0.2189        | 3.0   | 6186  | 0.4189          | 0.8442   | 0.7855 | 0.7727    | 0.7987 | 0.1558 |
  | 0.1418        | 4.0   | 8248  | 0.6393          | 0.8409   | 0.7863 | 0.7558    | 0.8194 | 0.1591 |
  | 0.1091        | 5.0   | 10310 | 0.7583          | 0.8284   | 0.7794 | 0.7207    | 0.8486 | 0.1716 |
  | 0.0901        | 6.0   | 12372 | 0.8695          | 0.8410   | 0.7836 | 0.7628    | 0.8055 | 0.1590 |
  | 0.0562        | 7.0   | 14434 | 1.0722          | 0.8405   | 0.7838 | 0.7600    | 0.8092 | 0.1595 |
  | 0.0444        | 8.0   | 16496 | 1.0797          | 0.8433   | 0.7804 | 0.7815    | 0.7794 | 0.1567 |
  | 0.0227        | 9.0   | 18558 | 1.1605          | 0.8429   | 0.7823 | 0.7743    | 0.7906 | 0.1571 |
  | 0.0131        | 10.0  | 20620 | 1.2382          | 0.8435   | 0.7857 | 0.7689    | 0.8031 | 0.1565 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.9.0+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  