readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  model-index:
  - name: distilcamembert-cae-territory
    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. -->
  
  # distilcamembert-cae-territory
  
  This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.7346
  - Precision: 0.7139
  - Recall: 0.6835
  - F1: 0.6887
  
  ## 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: 5.0
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
  | 1.1749        | 1.0   | 40   | 1.0498          | 0.1963    | 0.4430 | 0.2720 |
  | 0.9833        | 2.0   | 80   | 0.8853          | 0.7288    | 0.6709 | 0.6625 |
  | 0.6263        | 3.0   | 120  | 0.7503          | 0.7237    | 0.6709 | 0.6689 |
  | 0.3563        | 4.0   | 160  | 0.7346          | 0.7139    | 0.6835 | 0.6887 |
  | 0.2253        | 5.0   | 200  | 0.7303          | 0.7139    | 0.6835 | 0.6887 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.1
  - Tokenizers 0.13.2
  