readme: ---
  license: apache-2.0
  tags:
  - generated_from_keras_callback
  model-index:
  - name: vit_spectrogram
    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. -->
  
  # vit_spectrogram
  
  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on a dataset containing
  images of Mel spectrogram belonging to the classes 'Male' and 'Female'. This model is still being fine tuned and tested.
  It achieves the following results on the evaluation set:
  - Train Loss: 0.2893 
  - Train Accuracy: 0.8757 
  - Train Top-3-accuracy: 1.0000
  - Validation Loss: 0.8757 
  - Validation Accuracy: 0.9366 
  - Validation Top-3-accuracy: 1.0
  - Epoch: 1
  
  
  ## 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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 3032, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
  - training_precision: mixed_float16
  
  ### Training results
  
  
  
  ### Framework versions
  
  - Transformers 4.18.0
  - TensorFlow 2.4.0
  - Datasets 2.0.0
  - Tokenizers 0.11.6
  