ansilmbabl/vit-base-patch16-224-in21k-Cards
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: 0.0861
- Train Accuracy: 0.9775
- Train Top-3-accuracy: 0.9991
- Validation Loss: 0.6749
- Validation Accuracy: 0.8113
- Validation Top-3-accuracy: 0.9740
- Epoch: 5
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': {'module': 'transformers.optimization_tf', 'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 53200, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.8999999761581421, 'beta_2': 0.9990000128746033, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}, 'registered_name': 'AdamWeightDecay'}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000}
- training_precision: mixed_float16
Training results
| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch |
|---|---|---|---|---|---|---|
| 1.3188 | 0.6043 | 0.8822 | 0.8883 | 0.7130 | 0.9537 | 0 |
| 0.6864 | 0.7853 | 0.9705 | 0.6807 | 0.7647 | 0.9650 | 1 |
| 0.3966 | 0.8815 | 0.9896 | 0.5364 | 0.8120 | 0.9777 | 2 |
| 0.2310 | 0.9338 | 0.9964 | 0.4965 | 0.8427 | 0.9817 | 3 |
| 0.1333 | 0.9649 | 0.9981 | 0.4799 | 0.8513 | 0.9837 | 4 |
| 0.0861 | 0.9775 | 0.9991 | 0.6749 | 0.8113 | 0.9740 | 5 |
Framework versions
- Transformers 4.41.2
- TensorFlow 2.14.0
- Datasets 2.19.1
- Tokenizers 0.19.1