readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  model-index:
  - name: camembert-base-cae-fait-ext
    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. -->
  
  # camembert-base-cae-fait-ext
  
  This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 1.3098
  - Precision: 0.7339
  - Recall: 0.7107
  - F1: 0.7161
  
  ## 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: 5e-05
  - train_batch_size: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - lr_scheduler_warmup_ratio: 0.1
  - num_epochs: 10.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
  | 1.2626        | 1.0   | 61   | 1.1255          | 0.2541    | 0.5041 | 0.3379 |
  | 1.0858        | 2.0   | 122  | 0.9264          | 0.6300    | 0.6198 | 0.5705 |
  | 0.8364        | 3.0   | 183  | 0.8741          | 0.6460    | 0.6446 | 0.6391 |
  | 0.5045        | 4.0   | 244  | 0.7836          | 0.7252    | 0.7273 | 0.7171 |
  | 0.2866        | 5.0   | 305  | 0.9903          | 0.7352    | 0.6860 | 0.6918 |
  | 0.1896        | 6.0   | 366  | 1.0289          | 0.7422    | 0.7190 | 0.7257 |
  | 0.0975        | 7.0   | 427  | 1.1272          | 0.7565    | 0.7355 | 0.7396 |
  | 0.0679        | 8.0   | 488  | 1.2209          | 0.7389    | 0.7190 | 0.7237 |
  | 0.058         | 9.0   | 549  | 1.2647          | 0.7318    | 0.7025 | 0.7079 |
  | 0.0431        | 10.0  | 610  | 1.3098          | 0.7339    | 0.7107 | 0.7161 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.0
  - Tokenizers 0.13.1
  