readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  model-index:
  - name: bert-finetuned-resumes-sections
    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. -->
  
  # bert-finetuned-resumes-sections
  
  This model is a fine-tuned version of [dbmdz/bert-base-french-europeana-cased](https://huggingface.co/dbmdz/bert-base-french-europeana-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0333
  - F1: 0.9548
  - Roc Auc: 0.9732
  - Accuracy: 0.9493
  
  ## 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: 8
  - eval_batch_size: 8
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 12
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
  | 0.1659        | 1.0   | 601  | 0.0645          | 0.9201 | 0.9434  | 0.8910   |
  | 0.055         | 2.0   | 1202 | 0.0426          | 0.9407 | 0.9633  | 0.9309   |
  | 0.0324        | 3.0   | 1803 | 0.0371          | 0.9450 | 0.9663  | 0.9368   |
  | 0.0226        | 4.0   | 2404 | 0.0389          | 0.9402 | 0.9651  | 0.9343   |
  | 0.0125        | 5.0   | 3005 | 0.0354          | 0.9433 | 0.9650  | 0.9343   |
  | 0.0091        | 6.0   | 3606 | 0.0364          | 0.9482 | 0.9696  | 0.9434   |
  | 0.0075        | 7.0   | 4207 | 0.0363          | 0.9464 | 0.9676  | 0.9393   |
  | 0.007         | 8.0   | 4808 | 0.0333          | 0.9548 | 0.9732  | 0.9493   |
  | 0.0063        | 9.0   | 5409 | 0.0358          | 0.9501 | 0.9698  | 0.9434   |
  | 0.0043        | 10.0  | 6010 | 0.0380          | 0.9475 | 0.9707  | 0.9443   |
  | 0.0032        | 11.0  | 6611 | 0.0377          | 0.9491 | 0.9712  | 0.9468   |
  | 0.0031        | 12.0  | 7212 | 0.0375          | 0.9500 | 0.9716  | 0.9459   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  