| | --- |
| | license: apache-2.0 |
| | base_model: google/vit-base-patch16-224-in21k |
| | tags: |
| | - generated_from_keras_callback |
| | model-index: |
| | - name: Remunata/rupiah_classifier |
| | 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. --> |
| |
|
| | # Remunata/rupiah_classifier |
| | |
| | This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Train Loss: 0.1165 |
| | - Train Accuracy: 0.9065 |
| | - Validation Loss: 0.4728 |
| | - Validation Accuracy: 0.9065 |
| | - Epoch: 14 |
| | |
| | ## 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': 70950, '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 | Validation Loss | Validation Accuracy | Epoch | |
| | |:----------:|:--------------:|:---------------:|:-------------------:|:-----:| |
| | | 1.0522 | 0.8485 | 0.6303 | 0.8485 | 0 | |
| | | 0.3967 | 0.8838 | 0.4676 | 0.8838 | 1 | |
| | | 0.2908 | 0.8956 | 0.4541 | 0.8956 | 2 | |
| | | 0.2311 | 0.8675 | 0.5276 | 0.8675 | 3 | |
| | | 0.1810 | 0.8956 | 0.4133 | 0.8956 | 4 | |
| | | 0.1782 | 0.8929 | 0.4567 | 0.8929 | 5 | |
| | | 0.1617 | 0.8730 | 0.5800 | 0.8730 | 6 | |
| | | 0.1442 | 0.9047 | 0.4201 | 0.9047 | 7 | |
| | | 0.1471 | 0.9102 | 0.4024 | 0.9102 | 8 | |
| | | 0.1149 | 0.9093 | 0.4297 | 0.9093 | 9 | |
| | | 0.1198 | 0.9056 | 0.4753 | 0.9056 | 10 | |
| | | 0.1132 | 0.9056 | 0.4562 | 0.9056 | 11 | |
| | | 0.1132 | 0.9102 | 0.3935 | 0.9102 | 12 | |
| | | 0.1015 | 0.9056 | 0.4687 | 0.9056 | 13 | |
| | | 0.1165 | 0.9065 | 0.4728 | 0.9065 | 14 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.41.2 |
| | - TensorFlow 2.15.0 |
| | - Datasets 2.19.2 |
| | - Tokenizers 0.19.1 |
| |
|
