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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: ZachBeesley/food-classifier |
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results: [] |
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datasets: |
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- food101 |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# ZachBeesley/food-classifier |
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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. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.3376 |
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- Validation Loss: 0.3213 |
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- Train Accuracy: 0.921 |
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- Epoch: 4 |
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## Model description |
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Image-classification model that can identify foods based on pictures |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 20000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Train Accuracy | Epoch | |
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|:----------:|:---------------:|:--------------:|:-----:| |
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| 2.6919 | 1.5372 | 0.848 | 0 | |
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| 1.1404 | 0.8059 | 0.881 | 1 | |
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| 0.6375 | 0.6164 | 0.865 | 2 | |
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| 0.4379 | 0.3822 | 0.915 | 3 | |
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| 0.3376 | 0.3213 | 0.921 | 4 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- TensorFlow 2.12.0 |
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- Datasets 2.14.4 |
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- Tokenizers 0.13.3 |
