readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  model-index:
  - name: camembert-base-cae-composante
    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-composante
  
  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: 0.2323
  - Precision: 0.9589
  - Recall: 0.9579
  - F1: 0.9582
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
  | 0.8329        | 1.0   | 309  | 0.2321          | 0.9459    | 0.9450 | 0.9451 |
  | 0.2118        | 2.0   | 618  | 0.2280          | 0.9447    | 0.9434 | 0.9433 |
  | 0.11          | 3.0   | 927  | 0.2795          | 0.9531    | 0.9498 | 0.9505 |
  | 0.0572        | 4.0   | 1236 | 0.2323          | 0.9589    | 0.9579 | 0.9582 |
  | 0.0269        | 5.0   | 1545 | 0.2765          | 0.9559    | 0.9547 | 0.9549 |
  | 0.0166        | 6.0   | 1854 | 0.2997          | 0.9546    | 0.9531 | 0.9534 |
  | 0.0137        | 7.0   | 2163 | 0.2898          | 0.9555    | 0.9547 | 0.9549 |
  | 0.0092        | 8.0   | 2472 | 0.3108          | 0.9538    | 0.9531 | 0.9533 |
  | 0.0065        | 9.0   | 2781 | 0.3247          | 0.9560    | 0.9547 | 0.9550 |
  | 0.0091        | 10.0  | 3090 | 0.3288          | 0.9546    | 0.9531 | 0.9534 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.0
  - Tokenizers 0.13.1
  