| | --- |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch32-384 |
| | tags: |
| | - generated_from_keras_callback |
| | model-index: |
| | - name: Prahas10/roof-test |
| | 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. --> |
| |
|
| | # Prahas10/roof-test |
| |
|
| | This model is a fine-tuned version of [google/vit-base-patch32-384](https://huggingface.co/google/vit-base-patch32-384) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Train Loss: 0.0637 |
| | - Validation Loss: 0.1264 |
| | - Train Accuracy: 0.9474 |
| | - Epoch: 28 |
| |
|
| | ## 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': 4e-05, 'decay_steps': 3990, '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': 0.0001} |
| | - training_precision: float32 |
| | |
| | ### Training results |
| | |
| | | Train Loss | Validation Loss | Train Accuracy | Epoch | |
| | |:----------:|:---------------:|:--------------:|:-----:| |
| | | 2.6939 | 2.4863 | 0.2807 | 0 | |
| | | 2.1820 | 2.2454 | 0.4912 | 1 | |
| | | 1.8026 | 1.8798 | 0.4912 | 2 | |
| | | 1.4641 | 1.6673 | 0.5439 | 3 | |
| | | 1.1288 | 1.3594 | 0.6842 | 4 | |
| | | 0.9426 | 1.0517 | 0.8070 | 5 | |
| | | 0.6577 | 0.8531 | 0.8421 | 6 | |
| | | 0.5025 | 0.6971 | 0.8772 | 7 | |
| | | 0.3976 | 0.5785 | 0.8596 | 8 | |
| | | 0.3052 | 0.5568 | 0.9123 | 9 | |
| | | 0.2562 | 0.5137 | 0.8947 | 10 | |
| | | 0.3250 | 0.4415 | 0.9298 | 11 | |
| | | 0.2773 | 0.8003 | 0.7368 | 12 | |
| | | 0.2694 | 0.4544 | 0.8421 | 13 | |
| | | 0.2180 | 0.5179 | 0.8947 | 14 | |
| | | 0.1515 | 0.3450 | 0.9825 | 15 | |
| | | 0.1386 | 0.2818 | 0.9825 | 16 | |
| | | 0.1058 | 0.1962 | 0.9649 | 17 | |
| | | 0.0724 | 0.2456 | 0.9825 | 18 | |
| | | 0.0604 | 0.2432 | 0.9649 | 19 | |
| | | 0.0718 | 0.2548 | 1.0 | 20 | |
| | | 0.0507 | 0.2760 | 0.9474 | 21 | |
| | | 0.0453 | 0.1565 | 0.9825 | 22 | |
| | | 0.0274 | 0.1377 | 0.9825 | 23 | |
| | | 0.0396 | 0.1906 | 0.9649 | 24 | |
| | | 0.0360 | 0.1217 | 0.9825 | 25 | |
| | | 0.0307 | 0.2234 | 0.9474 | 26 | |
| | | 0.0427 | 0.2861 | 0.9298 | 27 | |
| | | 0.0637 | 0.1264 | 0.9474 | 28 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.38.2 |
| | - TensorFlow 2.15.0 |
| | - Datasets 2.16.1 |
| | - Tokenizers 0.15.2 |
| | |
