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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: aalonso-developer/vit-base-patch16-224-in21k-euroSat |
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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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# aalonso-developer/vit-base-patch16-224-in21k-euroSat |
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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: 0.0212 |
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- Train Accuracy: 0.9992 |
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- Train Top-3-accuracy: 1.0000 |
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- Validation Loss: 0.0613 |
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- Validation Accuracy: 0.9864 |
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- Validation Top-3-accuracy: 0.9998 |
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- Epoch: 4 |
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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': 3e-05, 'decay_steps': 3590, '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}}, '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-3-accuracy | Validation Loss | Validation Accuracy | Validation Top-3-accuracy | Epoch | |
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|:----------:|:--------------:|:--------------------:|:---------------:|:-------------------:|:-------------------------:|:-----:| |
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| 0.4737 | 0.9429 | 0.9862 | 0.1568 | 0.9788 | 0.9993 | 0 | |
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| 0.0998 | 0.9878 | 0.9996 | 0.1010 | 0.9805 | 0.9993 | 1 | |
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| 0.0503 | 0.9946 | 0.9999 | 0.0720 | 0.9857 | 0.9998 | 2 | |
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| 0.0297 | 0.9978 | 1.0000 | 0.0606 | 0.9881 | 0.9995 | 3 | |
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| 0.0212 | 0.9992 | 1.0000 | 0.0613 | 0.9864 | 0.9998 | 4 | |
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### Framework versions |
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- Transformers 4.29.1 |
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- TensorFlow 2.11.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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