readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-base-multilingual-cased-misogyny-sexism-decay0.05-fr-outofdomain
    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-misogyny-sexism-decay0.05-fr-outofdomain
  
  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: 0.9920
  - Accuracy: 0.2851
  - F1: 0.1967
  - Precision: 0.1124
  - Recall: 0.7870
  - Mae: 0.7149
  - Tn: 1727
  - Fp: 6043
  - Fn: 207
  - Tp: 765
  
  ## 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: 3
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall | Mae    | Tn   | Fp   | Fn  | Tp  |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:----:|:----:|:---:|:---:|
  | 0.3603        | 1.0   | 2233 | 0.8218          | 0.3251   | 0.2021 | 0.1163    | 0.7685 | 0.6749 | 2095 | 5675 | 225 | 747 |
  | 0.298         | 2.0   | 4466 | 0.9031          | 0.3164   | 0.2047 | 0.1175    | 0.7912 | 0.6836 | 1997 | 5773 | 203 | 769 |
  | 0.2438        | 3.0   | 6699 | 0.9920          | 0.2851   | 0.1967 | 0.1124    | 0.7870 | 0.7149 | 1727 | 6043 | 207 | 765 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  