metadata
library_name: transformers
license: apache-2.0
base_model: google/vit-base-patch16-224-in21k
tags:
- generated_from_keras_callback
model-index:
- name: Entrnal_eyes_data_5class_RVO_resize_224_model
results: []
Entrnal_eyes_data_5class_RVO_resize_224_model
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: 0.0870
- Train Accuracy: 0.9372
- Train Top-3-accuracy: 0.9944
- Validation Loss: 0.2468
- Validation Accuracy: 0.9406
- Validation Top-3-accuracy: 0.9948
- Epoch: 6
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': 784, '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 |
|---|---|---|---|---|---|---|
| 0.9323 | 0.6128 | 0.8870 | 0.4850 | 0.7838 | 0.9644 | 0 |
| 0.3507 | 0.8315 | 0.9758 | 0.3223 | 0.8593 | 0.9822 | 1 |
| 0.2174 | 0.8787 | 0.9858 | 0.2710 | 0.8925 | 0.9883 | 2 |
| 0.1573 | 0.9034 | 0.9899 | 0.3544 | 0.9108 | 0.9911 | 3 |
| 0.1231 | 0.9172 | 0.9920 | 0.2527 | 0.9235 | 0.9928 | 4 |
| 0.0963 | 0.9287 | 0.9934 | 0.2485 | 0.9333 | 0.9940 | 5 |
| 0.0870 | 0.9372 | 0.9944 | 0.2468 | 0.9406 | 0.9948 | 6 |
Framework versions
- Transformers 4.44.2
- TensorFlow 2.15.1
- Datasets 3.0.0
- Tokenizers 0.19.1