readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  model-index:
  - name: test_trainer
    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. -->
  
  # test_trainer
  
  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: 0.5153
  - Precision: 0.8965
  - Recall: 0.8946
  - F1: 0.8950
  
  ## 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: 16
  - eval_batch_size: 16
  - 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     |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
  | 1.6953        | 1.0   | 292  | 0.8195          | 0.8238    | 0.8003 | 0.7599 |
  | 0.6393        | 2.0   | 584  | 0.5050          | 0.8479    | 0.8663 | 0.8558 |
  | 0.4071        | 3.0   | 876  | 0.4896          | 0.8525    | 0.8680 | 0.8582 |
  | 0.2786        | 4.0   | 1168 | 0.4720          | 0.8842    | 0.8835 | 0.8787 |
  | 0.1997        | 5.0   | 1460 | 0.5115          | 0.8832    | 0.8843 | 0.8828 |
  | 0.1464        | 6.0   | 1752 | 0.5247          | 0.8863    | 0.8843 | 0.8842 |
  | 0.1114        | 7.0   | 2044 | 0.5193          | 0.8946    | 0.8929 | 0.8933 |
  | 0.0836        | 8.0   | 2336 | 0.5153          | 0.8965    | 0.8946 | 0.8950 |
  | 0.0727        | 9.0   | 2628 | 0.5403          | 0.8896    | 0.8895 | 0.8891 |
  | 0.0597        | 10.0  | 2920 | 0.5471          | 0.8889    | 0.8886 | 0.8883 |
  
  
  ### Framework versions
  
  - Transformers 4.20.1
  - Pytorch 1.11.0+cu113
  - Datasets 2.3.2
  - Tokenizers 0.12.1
  