readme: ---
  license: mit
  tags:
  - generated_from_keras_callback
  model-index:
  - name: huynhdoo/distilcamembert-base-finetuned-jva-missions-report
    results: []
  ---
  
  <!-- This model card has been generated automatically according to the information Keras had access to. You should
  probably proofread and complete it, then remove this comment. -->
  
  # huynhdoo/distilcamembert-base-finetuned-jva-missions-report
  
  This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.0336
  - Validation Loss: 1.1880
  - Train F1: 0.0391
  - Epoch: 17
  
  ## 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:
  - optimizer: {'name': 'Adam', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 3000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Validation Loss | Train F1 | Epoch |
  |:----------:|:---------------:|:--------:|:-----:|
  | 0.5225     | 0.4756          | 0.3575   | 0     |
  | 0.4079     | 0.4294          | 0.2961   | 1     |
  | 0.3439     | 0.5053          | 0.2961   | 2     |
  | 0.2765     | 0.5106          | 0.2346   | 3     |
  | 0.2044     | 0.5352          | 0.1788   | 4     |
  | 0.1774     | 0.6706          | 0.1341   | 5     |
  | 0.1690     | 0.8693          | 0.1676   | 6     |
  | 0.1143     | 0.7711          | 0.0726   | 7     |
  | 0.0930     | 0.9906          | 0.0950   | 8     |
  | 0.1091     | 0.9093          | 0.1117   | 9     |
  | 0.0576     | 0.8518          | 0.0894   | 10    |
  | 0.0500     | 1.2538          | 0.0950   | 11    |
  | 0.0541     | 0.7193          | 0.0838   | 12    |
  | 0.0461     | 0.9906          | 0.0503   | 13    |
  | 0.0359     | 0.9036          | 0.0447   | 14    |
  | 0.0320     | 1.1648          | 0.0391   | 15    |
  | 0.0299     | 1.0017          | 0.0279   | 16    |
  | 0.0336     | 1.1880          | 0.0391   | 17    |
  
  
  ### Framework versions
  
  - Transformers 4.26.0
  - TensorFlow 2.9.2
  - Datasets 2.9.0
  - Tokenizers 0.13.2
  