readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  model-index:
  - name: camembert-base-cae-ressentis-pensees
    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-ressentis-pensees
  
  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: 0.6742
  - Precision: 0.8398
  - Recall: 0.8417
  - F1: 0.8384
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
  | 1.2705        | 1.0   | 60   | 1.1442          | 0.2844    | 0.5333 | 0.3710 |
  | 1.0289        | 2.0   | 120  | 0.8098          | 0.8284    | 0.75   | 0.7533 |
  | 0.6056        | 3.0   | 180  | 0.5520          | 0.8345    | 0.8167 | 0.8042 |
  | 0.3228        | 4.0   | 240  | 0.5299          | 0.8198    | 0.825  | 0.8181 |
  | 0.1346        | 5.0   | 300  | 0.7416          | 0.8067    | 0.8083 | 0.7944 |
  | 0.0518        | 6.0   | 360  | 0.6852          | 0.8330    | 0.8333 | 0.8226 |
  | 0.0356        | 7.0   | 420  | 0.6758          | 0.8416    | 0.8417 | 0.8373 |
  | 0.0221        | 8.0   | 480  | 0.6996          | 0.8300    | 0.8333 | 0.8299 |
  | 0.0161        | 9.0   | 540  | 0.6701          | 0.8398    | 0.8417 | 0.8384 |
  | 0.0145        | 10.0  | 600  | 0.6742          | 0.8398    | 0.8417 | 0.8384 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.0
  - Tokenizers 0.13.1
  