readme: ---
  license: mit
  tags:
  - generated_from_trainer
  datasets:
  - allocine
  model-index:
  - name: model
    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. -->
  
  # model
  
  This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on the allocine dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.0254
  
  ## 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: 2e-05
  - train_batch_size: 64
  - eval_batch_size: 64
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 20.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss |
  |:-------------:|:-----:|:----:|:---------------:|
  | 2.4388        | 1.0   | 157  | 2.1637          |
  | 2.288         | 2.0   | 314  | 2.1697          |
  | 2.2444        | 3.0   | 471  | 2.1150          |
  | 2.2166        | 4.0   | 628  | 2.0906          |
  | 2.1754        | 5.0   | 785  | 2.0899          |
  | 2.1604        | 6.0   | 942  | 2.0797          |
  | 2.1299        | 7.0   | 1099 | 2.0589          |
  | 2.1195        | 8.0   | 1256 | 2.0178          |
  | 2.1258        | 9.0   | 1413 | 2.0348          |
  | 2.1071        | 10.0  | 1570 | 2.0090          |
  | 2.0888        | 11.0  | 1727 | 2.0047          |
  | 2.0792        | 12.0  | 1884 | 2.0219          |
  | 2.0687        | 13.0  | 2041 | 2.0080          |
  | 2.0527        | 14.0  | 2198 | 2.0298          |
  | 2.0589        | 15.0  | 2355 | 1.9869          |
  | 2.0518        | 16.0  | 2512 | 2.0152          |
  | 2.0409        | 17.0  | 2669 | 2.0247          |
  | 2.0507        | 18.0  | 2826 | 1.9928          |
  | 2.0366        | 19.0  | 2983 | 2.0175          |
  | 2.0386        | 20.0  | 3140 | 1.9487          |
  
  
  ### Framework versions
  
  - Transformers 4.21.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  