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: 0.0947
  - Precision: 0.9851
  - Recall: 0.9887
  - F1: 0.9869
  - Accuracy: 0.9860
  
  ## 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 |
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
  | 0.1092        | 1.0   | 1355 | 0.0916          | 0.9872    | 0.9780 | 0.9826 | 0.9815   |
  | 0.0668        | 2.0   | 2710 | 0.0799          | 0.9835    | 0.9887 | 0.9861 | 0.9850   |
  | 0.0373        | 3.0   | 4065 | 0.0925          | 0.9822    | 0.9885 | 0.9853 | 0.9843   |
  | 0.0262        | 4.0   | 5420 | 0.0898          | 0.9886    | 0.9815 | 0.9850 | 0.9847   |
  | 0.0192        | 5.0   | 6775 | 0.0947          | 0.9851    | 0.9887 | 0.9869 | 0.9860   |
  
  
  ### Framework versions
  
  - Transformers 4.23.1
  - Pytorch 1.12.1+cu113
  - Datasets 2.5.2
  - Tokenizers 0.13.1
  