| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: google/vit-base-patch16-224-in21k |
| tags: |
| - generated_from_keras_callback |
| model-index: |
| - name: CodeMania/Vehicle_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. --> |
|
|
| # CodeMania/Vehicle_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: 0.4395 |
| - Validation Loss: 0.5309 |
| - Train Accuracy: 0.8601 |
| - Epoch: 4 |
| |
| ## 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': 13595, '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 | Validation Loss | Train Accuracy | Epoch | |
| |:----------:|:---------------:|:--------------:|:-----:| |
| | 1.8665 | 1.3278 | 0.6654 | 0 | |
| | 1.1317 | 0.9559 | 0.7569 | 1 | |
| | 0.7964 | 0.7558 | 0.7908 | 2 | |
| | 0.5967 | 0.6633 | 0.8183 | 3 | |
| | 0.4395 | 0.5309 | 0.8601 | 4 | |
|
|
|
|
| ### Framework versions |
|
|
| - Transformers 4.44.2 |
| - TensorFlow 2.17.0 |
| - Datasets 3.0.0 |
| - Tokenizers 0.19.1 |
|
|
