readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - accuracy
  - precision
  - recall
  - f1
  model-index:
  - name: distilbert-profane-final
    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-profane-final
  
  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: 0.2773
  - Accuracy: 0.8992
  - Precision: 0.8261
  - Recall: 0.7987
  - F1: 0.8114
  
  ## 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: 1e-05
  - train_batch_size: 32
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
  | No log        | 1.0   | 296  | 0.2862          | 0.8907   | 0.8230    | 0.7528 | 0.7807 |
  | 0.3379        | 2.0   | 592  | 0.2650          | 0.9097   | 0.8748    | 0.7778 | 0.8148 |
  | 0.3379        | 3.0   | 888  | 0.2632          | 0.9049   | 0.8417    | 0.7999 | 0.8185 |
  | 0.221         | 4.0   | 1184 | 0.2772          | 0.8916   | 0.8055    | 0.8055 | 0.8055 |
  | 0.221         | 5.0   | 1480 | 0.2773          | 0.8992   | 0.8261    | 0.7987 | 0.8114 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0.dev0
  - Pytorch 1.11.0+cu102
  - Datasets 2.6.1
  - Tokenizers 0.13.1
  