readme: ---
  license: mit
  tags:
  - generated_from_trainer
  metrics:
  - f1
  - accuracy
  model-index:
  - name: bert-finetuned-Age
    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-Age
  
  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: 0.4642
  - F1: 0.7254
  - Roc Auc: 0.7940
  - Accuracy: 0.7249
  
  ## 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: 8
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
  |:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
  | 0.4564        | 1.0   | 965  | 0.4642          | 0.7254 | 0.7940  | 0.7254   |
  | 0.4443        | 2.0   | 1930 | 0.4662          | 0.7254 | 0.7940  | 0.7254   |
  | 0.4388        | 3.0   | 2895 | 0.4628          | 0.7254 | 0.7940  | 0.7254   |
  | 0.4486        | 4.0   | 3860 | 0.4642          | 0.7254 | 0.7940  | 0.7249   |
  | 0.4287        | 5.0   | 4825 | 0.4958          | 0.7214 | 0.7907  | 0.7150   |
  | 0.4055        | 6.0   | 5790 | 0.5325          | 0.6961 | 0.7715  | 0.6782   |
  | 0.3514        | 7.0   | 6755 | 0.5588          | 0.6586 | 0.7443  | 0.6223   |
  | 0.3227        | 8.0   | 7720 | 0.5944          | 0.6625 | 0.7470  | 0.6295   |
  
  
  ### Framework versions
  
  - Transformers 4.19.2
  - Pytorch 1.11.0+cu113
  - Datasets 2.2.2
  - Tokenizers 0.12.1
  