readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  model-index:
  - name: camembert-base-cae-ressentis-emotion
    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-emotion
  
  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: 1.0006
  - Precision: 0.7859
  - Recall: 0.7541
  - F1: 0.7628
  
  ## 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     |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
  | 1.2986        | 1.0   | 61   | 1.1007          | 0.2752    | 0.5246 | 0.3610 |
  | 1.0634        | 2.0   | 122  | 0.8015          | 0.6619    | 0.7049 | 0.6781 |
  | 0.6581        | 3.0   | 183  | 0.6695          | 0.7031    | 0.7459 | 0.7205 |
  | 0.3917        | 4.0   | 244  | 0.7579          | 0.7659    | 0.7623 | 0.7632 |
  | 0.2167        | 5.0   | 305  | 0.7555          | 0.7926    | 0.7787 | 0.7699 |
  | 0.1214        | 6.0   | 366  | 0.9429          | 0.7867    | 0.7705 | 0.7747 |
  | 0.086         | 7.0   | 427  | 0.9799          | 0.7691    | 0.7541 | 0.7578 |
  | 0.0399        | 8.0   | 488  | 0.9499          | 0.7961    | 0.7705 | 0.7792 |
  | 0.0345        | 9.0   | 549  | 0.9629          | 0.7910    | 0.7787 | 0.7818 |
  | 0.0247        | 10.0  | 610  | 1.0006          | 0.7859    | 0.7541 | 0.7628 |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.6.0
  - Tokenizers 0.13.1
  