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--- |
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library_name: transformers |
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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: traynothein_resize_foreclasss |
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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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# traynothein_resize_foreclasss |
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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: 0.0744 |
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- Train Accuracy: 0.9404 |
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- Train Top-3-accuracy: 0.9991 |
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- Validation Loss: 0.2720 |
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- Validation Accuracy: 0.9431 |
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- Validation Top-3-accuracy: 0.9991 |
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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': 658, '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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| 0.6708 | 0.7378 | 0.9752 | 0.4218 | 0.8246 | 0.9933 | 0 | |
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| 0.3109 | 0.8569 | 0.9956 | 0.3083 | 0.8754 | 0.9968 | 1 | |
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| 0.2024 | 0.8899 | 0.9975 | 0.2776 | 0.9011 | 0.9979 | 2 | |
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| 0.1370 | 0.9104 | 0.9982 | 0.2734 | 0.9170 | 0.9985 | 3 | |
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| 0.0996 | 0.9237 | 0.9986 | 0.2775 | 0.9288 | 0.9988 | 4 | |
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| 0.0814 | 0.9334 | 0.9989 | 0.2695 | 0.9372 | 0.9990 | 5 | |
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| 0.0744 | 0.9404 | 0.9991 | 0.2720 | 0.9431 | 0.9991 | 6 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- TensorFlow 2.15.1 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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