readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: Metformin/BART_medFineTune
    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. -->
  
  # Metformin/BART_medFineTune
  
  This model is a fine-tuned version of [facebook/bart-base](https://huggingface.co/facebook/bart-base) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.7982
  - Validation Loss: 0.9953
  - Epoch: 29
  
  ## 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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 1e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 1e-05, 'decay_steps': 7820, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 100, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Validation Loss | Epoch |
  |:----------:|:---------------:|:-----:|
  | 2.1563     | 1.3468          | 0     |
  | 1.4157     | 1.2090          | 1     |
  | 1.2579     | 1.1387          | 2     |
  | 1.1819     | 1.0888          | 3     |
  | 1.1438     | 1.0848          | 4     |
  | 1.0629     | 1.0512          | 5     |
  | 1.0163     | 1.0454          | 6     |
  | 0.9801     | 1.0248          | 7     |
  | 0.9530     | 1.0171          | 8     |
  | 0.9262     | 1.0108          | 9     |
  | 0.9124     | 1.0116          | 10    |
  | 0.8853     | 1.0043          | 11    |
  | 0.8658     | 1.0023          | 12    |
  | 0.8511     | 0.9987          | 13    |
  | 0.8394     | 0.9988          | 14    |
  | 0.8298     | 0.9994          | 15    |
  | 0.8175     | 0.9985          | 16    |
  | 0.8105     | 0.9936          | 17    |
  | 0.8033     | 0.9974          | 18    |
  | 0.8012     | 0.9948          | 19    |
  | 0.7997     | 0.9948          | 20    |
  | 0.7970     | 0.9957          | 21    |
  | 0.7956     | 0.9958          | 22    |
  | 0.8002     | 0.9954          | 23    |
  | 0.7951     | 0.9957          | 24    |
  | 0.7994     | 0.9948          | 25    |
  | 0.7964     | 0.9958          | 26    |
  | 0.7948     | 0.9957          | 27    |
  | 0.7979     | 0.9956          | 28    |
  | 0.7982     | 0.9953          | 29    |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - TensorFlow 2.6.3
  - Datasets 2.0.0
  - Tokenizers 0.12.1
  