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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: vit-base-patch16-224-4class224 |
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results: [] |
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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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# vit-base-patch16-224-4class224 |
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This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.0136 |
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- Train Accuracy: 0.9421 |
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- Train Top-3-accuracy: 0.9958 |
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- Validation Loss: 0.1390 |
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- Validation Accuracy: 0.9458 |
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- Validation Top-3-accuracy: 0.9961 |
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- Epoch: 6 |
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## Model description |
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More information needed |
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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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 455, '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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train Accuracy | Train Top-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch | |
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|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:| |
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| 0.7231 | 0.5836 | 0.9174 | 0.3551 | 0.7352 | 0.9701 | 0 | |
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| 0.2208 | 0.8012 | 0.9802 | 0.2265 | 0.8400 | 0.9858 | 1 | |
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| 0.0854 | 0.8664 | 0.9886 | 0.1859 | 0.8862 | 0.9907 | 2 | |
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| 0.0372 | 0.8996 | 0.9920 | 0.1565 | 0.9111 | 0.9931 | 3 | |
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| 0.0212 | 0.9199 | 0.9938 | 0.1411 | 0.9272 | 0.9945 | 4 | |
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| 0.0167 | 0.9328 | 0.9950 | 0.1374 | 0.9379 | 0.9954 | 5 | |
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| 0.0136 | 0.9421 | 0.9958 | 0.1390 | 0.9458 | 0.9961 | 6 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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