readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: Metformin/T5model_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/T5model_medFineTune
  
  This model is a fine-tuned version of [google/mt5-small](https://huggingface.co/google/mt5-small) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 9.0442
  - Validation Loss: 6.1005
  - Epoch: 9
  
  ## 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 |
  |:----------:|:---------------:|:-----:|
  | 42.6321    | 28.0647         | 0     |
  | 31.2672    | 21.0068         | 1     |
  | 24.8310    | 16.6186         | 2     |
  | 20.5368    | 13.8025         | 3     |
  | 17.3796    | 11.7180         | 4     |
  | 15.0329    | 10.0404         | 5     |
  | 13.0886    | 8.6286          | 6     |
  | 11.5235    | 7.5594          | 7     |
  | 10.1123    | 6.8079          | 8     |
  | 9.0442     | 6.1005          | 9     |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - TensorFlow 2.6.3
  - Datasets 2.0.0
  - Tokenizers 0.12.1
  