readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-base-multilingual-cased-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. -->
  
  # distilbert-base-multilingual-cased-finetuned-misogyny-sexism
  
  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: 0.0013
  - Accuracy: 0.9995
  - F1: 0.9995
  - Precision: 0.9989
  - Recall: 1.0
  - Mae: 0.0005
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.301         | 1.0   | 1759  | 0.3981          | 0.8194   | 0.8268 | 0.7669    | 0.8968 | 0.1806 |
  | 0.2573        | 2.0   | 3518  | 0.2608          | 0.8887   | 0.8902 | 0.8463    | 0.9389 | 0.1113 |
  | 0.1818        | 3.0   | 5277  | 0.1608          | 0.9418   | 0.9426 | 0.8965    | 0.9937 | 0.0582 |
  | 0.1146        | 4.0   | 7036  | 0.0667          | 0.9793   | 0.9787 | 0.9652    | 0.9926 | 0.0207 |
  | 0.0829        | 5.0   | 8795  | 0.0292          | 0.9924   | 0.9921 | 0.9875    | 0.9968 | 0.0076 |
  | 0.059         | 6.0   | 10554 | 0.0221          | 0.9939   | 0.9937 | 0.9916    | 0.9958 | 0.0061 |
  | 0.0434        | 7.0   | 12313 | 0.0177          | 0.9954   | 0.9953 | 0.9916    | 0.9989 | 0.0046 |
  | 0.0165        | 8.0   | 14072 | 0.0014          | 0.9995   | 0.9995 | 0.9989    | 1.0    | 0.0005 |
  | 0.0144        | 9.0   | 15831 | 0.0008          | 0.9995   | 0.9995 | 0.9989    | 1.0    | 0.0005 |
  | 0.012         | 10.0  | 17590 | 0.0013          | 0.9995   | 0.9995 | 0.9989    | 1.0    | 0.0005 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.9.0+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  