| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_keras_callback |
| | model-index: |
| | - name: akaashp15/food_classifier |
| | results: [] |
| | datasets: |
| | - food101 |
| | metrics: |
| | - accuracy |
| | --- |
| | |
| | <!-- 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. --> |
| |
|
| | # akaashp15/food_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: 3.8114 |
| | - Validation Loss: 4.0450 |
| | - Train Accuracy: 0.5875 |
| | - 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': 20000, '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 | |
| | |:----------:|:---------------:|:--------------:|:-----:| |
| | | 4.5874 | 4.5203 | 0.0875 | 0 | |
| | | 4.3743 | 4.4135 | 0.35 | 1 | |
| | | 4.1829 | 4.2913 | 0.55 | 2 | |
| | | 3.9908 | 4.1636 | 0.6125 | 3 | |
| | | 3.8114 | 4.0450 | 0.5875 | 4 | |
| |
|
| |
|
| | ### Framework versions |
| |
|
| | - Transformers 4.30.2 |
| | - TensorFlow 2.13.0-rc2 |
| | - Datasets 2.13.1 |
| | - Tokenizers 0.13.3 |
