metadata
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: Alph0nse/vit-base-patch16-224-in21k_breed_cls
results: []
Alph0nse/vit-base-patch16-224-in21k_breed_cls
This model is a fine-tuned version of google/vit-base-patch16-224-in21k on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 0.7030
- Train Accuracy: 0.9096
- Train Top-3-accuracy: 0.9690
- Validation Loss: 0.7398
- Validation Accuracy: 0.9214
- Validation Top-3-accuracy: 0.9743
- 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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 1125, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: float32
Training results
Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
---|---|---|---|---|---|---|
2.1799 | 0.6071 | 0.7594 | 1.6173 | 0.8262 | 0.9238 | 0 |
1.1190 | 0.8685 | 0.9480 | 1.0225 | 0.8936 | 0.9619 | 1 |
0.7030 | 0.9096 | 0.9690 | 0.7398 | 0.9214 | 0.9743 | 2 |
Framework versions
- Transformers 4.38.2
- TensorFlow 2.15.0
- Datasets 2.18.0
- Tokenizers 0.15.2