readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: cakiki/distilbert-base-uncased-finetuned-tweet-sentiment
    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. -->
  
  # cakiki/distilbert-base-uncased-finetuned-tweet-sentiment
  
  This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.1025
  - Train Sparse Categorical Accuracy: 0.9511
  - Validation Loss: 0.1455
  - Validation Sparse Categorical Accuracy: 0.9365
  - 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 |
  |:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:|
  | 0.5409     | 0.8158                            | 0.2115          | 0.9265                                 | 0     |
  | 0.1442     | 0.9373                            | 0.1411          | 0.9380                                 | 1     |
  | 0.1025     | 0.9511                            | 0.1455          | 0.9365                                 | 2     |
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - TensorFlow 2.9.0-rc0
  - Datasets 2.1.0
  - Tokenizers 0.12.1
  