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# 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

{"license": "apache-2.0", "tags": ["generated_from_keras_callback"], "model-index": [{"name": "vit_spectrogram", "results": []}]}
transformers tf vit image-classification generated_from_keras_callback license:apache-2.0 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #tf #vit #image-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 




# vit_spectrogram

This model is a fine-tuned version of 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

# vit_spectrogram

This model is a fine-tuned version of 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
TAGS
#transformers #tf #vit #image-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
 # vit_spectrogram

This model is a fine-tuned version of 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
passage: TAGS
#transformers #tf #vit #image-classification #generated_from_keras_callback #license-apache-2.0 #autotrain_compatible #endpoints_compatible #region-us 
# vit_spectrogram

This model is a fine-tuned version of 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