readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-base-multilingual-cased-misogyny-sexism-decay0.01-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-decay0.01-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: 3.1385
  - Accuracy: 0.2369
  - F1: 0.1919
  - Precision: 0.1087
  - Recall: 0.8148
  - Mae: 0.7631
  - Tn: 1279
  - Fp: 6491
  - Fn: 180
  - Tp: 792
  
  ## 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    | Tn   | Fp   | Fn  | Tp  |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|:----:|:----:|:---:|:---:|
  | 0.2166        | 1.0   | 2233  | 1.2875          | 0.3377   | 0.2025 | 0.1169    | 0.7562 | 0.6623 | 2217 | 5553 | 237 | 735 |
  | 0.2068        | 2.0   | 4466  | 1.8399          | 0.3141   | 0.2154 | 0.1234    | 0.8467 | 0.6859 | 1923 | 5847 | 149 | 823 |
  | 0.2015        | 3.0   | 6699  | 1.5430          | 0.3543   | 0.2053 | 0.1189    | 0.75   | 0.6457 | 2368 | 5402 | 243 | 729 |
  | 0.1739        | 4.0   | 8932  | 1.8406          | 0.2815   | 0.1911 | 0.1092    | 0.7634 | 0.7185 | 1719 | 6051 | 230 | 742 |
  | 0.163         | 5.0   | 11165 | 2.0274          | 0.2170   | 0.1957 | 0.1105    | 0.8570 | 0.7830 | 1064 | 6706 | 139 | 833 |
  | 0.1481        | 6.0   | 13398 | 1.6407          | 0.2467   | 0.1931 | 0.1096    | 0.8107 | 0.7533 | 1369 | 6401 | 184 | 788 |
  | 0.1334        | 7.0   | 15631 | 3.0800          | 0.1875   | 0.1953 | 0.1097    | 0.8868 | 0.8125 | 777  | 6993 | 110 | 862 |
  | 0.12          | 8.0   | 17864 | 2.5311          | 0.2183   | 0.1962 | 0.1108    | 0.8580 | 0.7817 | 1074 | 6696 | 138 | 834 |
  | 0.1104        | 9.0   | 20097 | 2.9522          | 0.2135   | 0.1935 | 0.1092    | 0.8488 | 0.7865 | 1041 | 6729 | 147 | 825 |
  | 0.0938        | 10.0  | 22330 | 3.1385          | 0.2369   | 0.1919 | 0.1087    | 0.8148 | 0.7631 | 1279 | 6491 | 180 | 792 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.12.0+cu102
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  