readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - f1
  - precision
  - recall
  model-index:
  - name: distilbert-base-multilingual-cased-finetuned-misogyny-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-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: 0.9917
  - Accuracy: 0.8808
  - F1: 0.7543
  - Precision: 0.7669
  - Recall: 0.7421
  - Mae: 0.1192
  
  ## 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    |
  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|:------:|
  | 0.3366        | 1.0   | 1407  | 0.3297          | 0.8630   | 0.6862 | 0.7886    | 0.6073 | 0.1370 |
  | 0.2371        | 2.0   | 2814  | 0.3423          | 0.8802   | 0.7468 | 0.7802    | 0.7161 | 0.1198 |
  | 0.1714        | 3.0   | 4221  | 0.4373          | 0.8749   | 0.7351 | 0.7693    | 0.7039 | 0.1251 |
  | 0.1161        | 4.0   | 5628  | 0.5584          | 0.8699   | 0.7525 | 0.7089    | 0.8019 | 0.1301 |
  | 0.0646        | 5.0   | 7035  | 0.7005          | 0.8788   | 0.7357 | 0.7961    | 0.6837 | 0.1212 |
  | 0.0539        | 6.0   | 8442  | 0.7866          | 0.8710   | 0.7465 | 0.7243    | 0.7702 | 0.1290 |
  | 0.0336        | 7.0   | 9849  | 0.8967          | 0.8783   | 0.7396 | 0.7828    | 0.7010 | 0.1217 |
  | 0.0202        | 8.0   | 11256 | 0.9053          | 0.8810   | 0.7472 | 0.7845    | 0.7133 | 0.1190 |
  | 0.018         | 9.0   | 12663 | 0.9785          | 0.8792   | 0.7478 | 0.7706    | 0.7262 | 0.1208 |
  | 0.0069        | 10.0  | 14070 | 0.9917          | 0.8808   | 0.7543 | 0.7669    | 0.7421 | 0.1192 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.9.0+cu111
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  