readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: robbery_dataset_tf_finetuned_20221113
    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. -->
  
  # robbery_dataset_tf_finetuned_20221113
  
  This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.0506
  - Train Sparse Categorical Accuracy: 0.9844
  - Validation Loss: 0.4108
  - Validation Sparse Categorical Accuracy: 0.9068
  - 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': '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 |
  |:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
  | 0.4908     | 0.8335                            | 0.2872          | 0.9060                                 | 0     |
  | 0.2496     | 0.9180                            | 0.3137          | 0.8978                                 | 1     |
  | 0.1947     | 0.9351                            | 0.3234          | 0.9062                                 | 2     |
  | 0.1597     | 0.9483                            | 0.3092          | 0.9087                                 | 3     |
  | 0.1304     | 0.9580                            | 0.2928          | 0.9140                                 | 4     |
  | 0.1013     | 0.9684                            | 0.3450          | 0.9143                                 | 5     |
  | 0.0785     | 0.9742                            | 0.3590          | 0.9080                                 | 6     |
  | 0.0709     | 0.9778                            | 0.3711          | 0.9057                                 | 7     |
  | 0.0541     | 0.9821                            | 0.4010          | 0.9128                                 | 8     |
  | 0.0506     | 0.9844                            | 0.4108          | 0.9068                                 | 9     |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - TensorFlow 2.9.2
  - Datasets 2.6.1
  - Tokenizers 0.13.2
  