readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  model-index:
  - name: extended_distilBERT-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. -->
  
  # extended_distilBERT-finetuned-resumes-sections
  
  This model is a fine-tuned version of [Geotrend/distilbert-base-en-fr-cased](https://huggingface.co/Geotrend/distilbert-base-en-fr-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Loss: 0.0321
  - F1: 0.9735
  - Roc Auc: 0.9850
  - Accuracy: 0.9715
  
  ## 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: 20
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | F1     | Roc Auc | Accuracy |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:-------:|:--------:|
  | 0.0283        | 1.0   | 2213  | 0.0247          | 0.9610 | 0.9763  | 0.9539   |
  | 0.0153        | 2.0   | 4426  | 0.0223          | 0.9634 | 0.9789  | 0.9593   |
  | 0.01          | 3.0   | 6639  | 0.0199          | 0.9702 | 0.9835  | 0.9675   |
  | 0.0073        | 4.0   | 8852  | 0.0218          | 0.9710 | 0.9838  | 0.9690   |
  | 0.0063        | 5.0   | 11065 | 0.0244          | 0.9706 | 0.9835  | 0.9684   |
  | 0.0037        | 6.0   | 13278 | 0.0251          | 0.9700 | 0.9833  | 0.9684   |
  | 0.004         | 7.0   | 15491 | 0.0273          | 0.9712 | 0.9837  | 0.9693   |
  | 0.003         | 8.0   | 17704 | 0.0266          | 0.9719 | 0.9841  | 0.9695   |
  | 0.0027        | 9.0   | 19917 | 0.0294          | 0.9697 | 0.9831  | 0.9679   |
  | 0.0014        | 10.0  | 22130 | 0.0275          | 0.9714 | 0.9844  | 0.9690   |
  | 0.0016        | 11.0  | 24343 | 0.0299          | 0.9714 | 0.9839  | 0.9697   |
  | 0.0013        | 12.0  | 26556 | 0.0297          | 0.9719 | 0.9852  | 0.9697   |
  | 0.0006        | 13.0  | 28769 | 0.0312          | 0.9711 | 0.9843  | 0.9697   |
  | 0.0004        | 14.0  | 30982 | 0.0305          | 0.9731 | 0.9849  | 0.9720   |
  | 0.0004        | 15.0  | 33195 | 0.0312          | 0.9723 | 0.9845  | 0.9704   |
  | 0.0005        | 16.0  | 35408 | 0.0331          | 0.9716 | 0.9843  | 0.9697   |
  | 0.0006        | 17.0  | 37621 | 0.0321          | 0.9735 | 0.9850  | 0.9715   |
  | 0.0004        | 18.0  | 39834 | 0.0322          | 0.9731 | 0.9850  | 0.9711   |
  | 0.0003        | 19.0  | 42047 | 0.0332          | 0.9722 | 0.9847  | 0.9706   |
  | 0.0004        | 20.0  | 44260 | 0.0334          | 0.9720 | 0.9846  | 0.9704   |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - Pytorch 1.12.1+cu113
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  