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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: Imene/vit-base-patch16-224-wi2 |
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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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# Imene/vit-base-patch16-224-wi2 |
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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: 0.3098 |
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- Train Accuracy: 0.9821 |
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- Train Top-5-accuracy: 0.9971 |
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- Validation Loss: 3.0737 |
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- Validation Accuracy: 0.2491 |
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- Validation Top-5-accuracy: 0.4476 |
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- Epoch: 9 |
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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: {'inner_optimizer': {'class_name': 'AdamWeightDecay', 'config': {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0003, 'decay_steps': 1750, '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': 0.001}}, 'dynamic': True, 'initial_scale': 32768.0, 'dynamic_growth_steps': 2000} |
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- training_precision: mixed_float16 |
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### Training results |
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| Train Loss | Train Accuracy | Train Top-5-accuracy | Validation Loss | Validation Accuracy | Validation Top-5-accuracy | Epoch | |
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|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:| |
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| 4.4859 | 0.0195 | 0.0579 | 4.2995 | 0.0368 | 0.0865 | 0 | |
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| 4.1729 | 0.0355 | 0.0987 | 4.0916 | 0.0472 | 0.1266 | 1 | |
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| 3.9541 | 0.0666 | 0.1641 | 3.8050 | 0.0781 | 0.2035 | 2 | |
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| 3.5823 | 0.1247 | 0.2615 | 3.4015 | 0.1429 | 0.2950 | 3 | |
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| 3.0156 | 0.1913 | 0.3987 | 3.0598 | 0.1880 | 0.3916 | 4 | |
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| 2.4618 | 0.3077 | 0.5572 | 2.9869 | 0.2056 | 0.4129 | 5 | |
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| 1.8979 | 0.4541 | 0.7165 | 2.9507 | 0.2298 | 0.4425 | 6 | |
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| 1.2075 | 0.6914 | 0.8886 | 3.0106 | 0.2394 | 0.4425 | 7 | |
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| 0.6026 | 0.9097 | 0.9810 | 3.0739 | 0.2428 | 0.4413 | 8 | |
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| 0.3098 | 0.9821 | 0.9971 | 3.0737 | 0.2491 | 0.4476 | 9 | |
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### Framework versions |
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- Transformers 4.21.3 |
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- TensorFlow 2.8.2 |
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- Datasets 2.4.0 |
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- Tokenizers 0.12.1 |
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