readme: ---
  tags:
  - generated_from_trainer
  metrics:
  - precision
  - recall
  - f1
  - accuracy
  model-index:
  - name: camembert-ner-finetuned-ner
    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-ner-finetuned-ner
  
  This model is a fine-tuned version of [Jean-Baptiste/camembert-ner](https://huggingface.co/Jean-Baptiste/camembert-ner) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.1258
  - Precision: 0.9791
  - Recall: 0.9723
  - F1: 0.9757
  - Accuracy: 0.9775
  
  ## 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: 16
  - eval_batch_size: 16
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 5
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | No log        | 1.0   | 219  | 0.1130          | 0.9569    | 0.9723 | 0.9645 | 0.9687   |
  | No log        | 2.0   | 438  | 0.1681          | 0.9528    | 0.9769 | 0.9647 | 0.9646   |
  | 0.1656        | 3.0   | 657  | 0.1253          | 0.9693    | 0.9827 | 0.9759 | 0.9779   |
  | 0.1656        | 4.0   | 876  | 0.1230          | 0.9692    | 0.9804 | 0.9748 | 0.9783   |
  | 0.047         | 5.0   | 1095 | 0.1258          | 0.9791    | 0.9723 | 0.9757 | 0.9775   |
  
  
  ### Framework versions
  
  - Transformers 4.22.2
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.1
  - Tokenizers 0.12.1
  