readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: cptanalatriste/request-for-help
    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. -->
  
  # cptanalatriste/request-for-help
  
  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: 0.1342
  - Train Sparse Categorical Accuracy: 1.0
  - Validation Loss: 0.1514
  - Validation Sparse Categorical Accuracy: 0.9796
  - Epoch: 19
  
  ## 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': 3e-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 |
  |:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
  | 0.8291     | 0.375                             | 0.7483          | 0.3673                                 | 0     |
  | 0.7470     | 0.375                             | 0.6302          | 0.8163                                 | 1     |
  | 0.6504     | 0.625                             | 0.6079          | 0.9184                                 | 2     |
  | 0.6128     | 0.7812                            | 0.5882          | 0.8980                                 | 3     |
  | 0.5939     | 0.8125                            | 0.5639          | 0.9184                                 | 4     |
  | 0.5300     | 0.9688                            | 0.5378          | 0.9184                                 | 5     |
  | 0.5306     | 0.9688                            | 0.5098          | 0.9388                                 | 6     |
  | 0.4963     | 1.0                               | 0.4806          | 0.9388                                 | 7     |
  | 0.4683     | 0.9688                            | 0.4434          | 0.9592                                 | 8     |
  | 0.3959     | 1.0                               | 0.4070          | 0.9796                                 | 9     |
  | 0.3807     | 1.0                               | 0.3762          | 0.9796                                 | 10    |
  | 0.3509     | 1.0                               | 0.3439          | 0.9796                                 | 11    |
  | 0.3013     | 1.0                               | 0.3064          | 0.9796                                 | 12    |
  | 0.2848     | 1.0                               | 0.2931          | 0.9796                                 | 13    |
  | 0.2587     | 1.0                               | 0.2681          | 0.9796                                 | 14    |
  | 0.2510     | 1.0                               | 0.2295          | 0.9796                                 | 15    |
  | 0.1867     | 1.0                               | 0.2000          | 0.9796                                 | 16    |
  | 0.1652     | 1.0                               | 0.1793          | 0.9796                                 | 17    |
  | 0.1297     | 1.0                               | 0.1637          | 0.9796                                 | 18    |
  | 0.1342     | 1.0                               | 0.1514          | 0.9796                                 | 19    |
  
  
  ### Framework versions
  
  - Transformers 4.17.0
  - TensorFlow 2.6.2
  - Datasets 1.18.4
  - Tokenizers 0.11.6
  