readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  model-index:
  - name: distilcamembert-cae-component
    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. -->
  
  # distilcamembert-cae-component
  
  This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.3683
  - Precision: 0.9317
  - Recall: 0.9303
  - F1: 0.9306
  
  ## 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: 5.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
  | 0.6221        | 1.0   | 309  | 0.3860          | 0.9007    | 0.8720 | 0.8761 |
  | 0.1723        | 2.0   | 618  | 0.3505          | 0.9233    | 0.9157 | 0.9168 |
  | 0.0604        | 3.0   | 927  | 0.3683          | 0.9317    | 0.9303 | 0.9306 |
  | 0.0117        | 4.0   | 1236 | 0.4214          | 0.9311    | 0.9303 | 0.9304 |
  | 0.0061        | 5.0   | 1545 | 0.4232          | 0.9317    | 0.9303 | 0.9305 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  