readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  model-index:
  - name: camembert-base-cae-ressentis
    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
  
  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: 0.8112
  - Precision: 0.8116
  - Recall: 0.8034
  - F1: 0.8060
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
  | 1.2699        | 1.0   | 59   | 1.1005          | 0.2718    | 0.5214 | 0.3573 |
  | 1.0852        | 2.0   | 118  | 0.8127          | 0.6403    | 0.7179 | 0.6708 |
  | 0.7006        | 3.0   | 177  | 0.6582          | 0.7407    | 0.7436 | 0.7310 |
  | 0.4187        | 4.0   | 236  | 0.5833          | 0.8075    | 0.7863 | 0.7817 |
  | 0.2017        | 5.0   | 295  | 0.5869          | 0.8537    | 0.8376 | 0.8400 |
  | 0.1142        | 6.0   | 354  | 0.6433          | 0.8125    | 0.8034 | 0.8064 |
  | 0.0735        | 7.0   | 413  | 0.7700          | 0.8027    | 0.7949 | 0.7959 |
  | 0.0572        | 8.0   | 472  | 0.8023          | 0.7915    | 0.7863 | 0.7877 |
  | 0.0445        | 9.0   | 531  | 0.8010          | 0.8116    | 0.8034 | 0.8060 |
  | 0.033         | 10.0  | 590  | 0.8112          | 0.8116    | 0.8034 | 0.8060 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.0
  - Tokenizers 0.13.1
  