readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  datasets:
    - disfl_qa
  metrics:
    - validation_accuracy
  model-index:
  - name: fintuned-bert-disfluency
    results:
    - task:
        name: Text Classification
        type: text-classification
      dataset:
        name: disfl_qa
        type: disfl_qa
        args: disfl_qa
      metrics:
      - name: Validation Accuracy
        type: validation_accuracy
        value: 0.9795
  widget:
  - text: "I love football so much"
    example_title: "Non Disfluent"
  - text: "I love love football I like it"
    example_title: "Disfluent"
  ---
  
  <!-- 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. -->
  
  # fintuned-bert-disfluency
  
  This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.0814
  - Train Sparse Categorical Accuracy: 0.9795
  - Validation Loss: 0.0816
  - Validation Sparse Categorical Accuracy: 0.9795
  - Epoch: 2
  
  ## 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': 5e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  - training_precision: float32
  
  ### Training results
  
  | Train Loss | Train Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch |
  |:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
  | 0.1105     | 0.9694                            | 0.0821          | 0.9800                                 | 0     |
  | 0.0942     | 0.9759                            | 0.0987          | 0.9765                                 | 1     |
  | 0.0814     | 0.9795                            | 0.0816          | 0.9795                                 | 2     |
  
  
  ### Framework versions
  
  - Transformers 4.21.3
  - TensorFlow 2.8.2
  - Datasets 2.4.0
  - Tokenizers 0.12.1
  