readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-base-multilingual-cased-finetuned-misogyny
    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
  
  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: 0.0045
  - Accuracy: 0.9990
  - F1: 0.9989
  - Precision: 0.9989
  - Recall: 0.9989
  - Mae: 0.0010
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.2987        | 1.0   | 1759  | 0.3910          | 0.8164   | 0.8186 | 0.7793    | 0.8621 | 0.1836 |
  | 0.2507        | 2.0   | 3518  | 0.2399          | 0.9029   | 0.9043 | 0.8589    | 0.9547 | 0.0971 |
  | 0.1793        | 3.0   | 5277  | 0.1412          | 0.9479   | 0.9483 | 0.9068    | 0.9937 | 0.0521 |
  | 0.1062        | 4.0   | 7036  | 0.0570          | 0.9828   | 0.9823 | 0.9702    | 0.9947 | 0.0172 |
  | 0.0732        | 5.0   | 8795  | 0.0293          | 0.9924   | 0.9921 | 0.9885    | 0.9958 | 0.0076 |
  | 0.0461        | 6.0   | 10554 | 0.0157          | 0.9960   | 0.9958 | 0.9937    | 0.9979 | 0.0040 |
  | 0.037         | 7.0   | 12313 | 0.0126          | 0.9975   | 0.9974 | 0.9948    | 1.0    | 0.0025 |
  | 0.0311        | 8.0   | 14072 | 0.0092          | 0.9980   | 0.9979 | 0.9958    | 1.0    | 0.0020 |
  | 0.0141        | 9.0   | 15831 | 0.0065          | 0.9985   | 0.9984 | 0.9979    | 0.9989 | 0.0015 |
  | 0.0119        | 10.0  | 17590 | 0.0045          | 0.9990   | 0.9989 | 0.9989    | 0.9989 | 0.0010 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.9.0+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  