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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: arieg/bw_spec_cls_4_01_noise_200_confirm |
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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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# arieg/bw_spec_cls_4_01_noise_200_confirm |
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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: 0.0143 |
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- Train Sparse Categorical Accuracy: 1.0 |
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- Validation Loss: 0.0140 |
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- Validation Sparse Categorical Accuracy: 1.0 |
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- Epoch: 19 |
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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', 'clipnorm': 1.0, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 3e-05, 'decay_steps': 14400, '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 Sparse Categorical Accuracy | Validation Loss | Validation Sparse Categorical Accuracy | Epoch | |
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|:----------:|:---------------------------------:|:---------------:|:--------------------------------------:|:-----:| |
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| 0.6064 | 0.9569 | 0.2224 | 1.0 | 0 | |
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| 0.1543 | 1.0 | 0.1168 | 1.0 | 1 | |
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| 0.0979 | 1.0 | 0.0858 | 1.0 | 2 | |
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| 0.0769 | 1.0 | 0.0709 | 1.0 | 3 | |
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| 0.0647 | 1.0 | 0.0603 | 1.0 | 4 | |
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| 0.0558 | 1.0 | 0.0528 | 1.0 | 5 | |
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| 0.0490 | 1.0 | 0.0465 | 1.0 | 6 | |
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| 0.0434 | 1.0 | 0.0414 | 1.0 | 7 | |
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| 0.0387 | 1.0 | 0.0369 | 1.0 | 8 | |
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| 0.0347 | 1.0 | 0.0332 | 1.0 | 9 | |
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| 0.0312 | 1.0 | 0.0300 | 1.0 | 10 | |
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| 0.0282 | 1.0 | 0.0272 | 1.0 | 11 | |
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| 0.0256 | 1.0 | 0.0248 | 1.0 | 12 | |
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| 0.0234 | 1.0 | 0.0226 | 1.0 | 13 | |
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| 0.0214 | 1.0 | 0.0207 | 1.0 | 14 | |
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| 0.0196 | 1.0 | 0.0190 | 1.0 | 15 | |
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| 0.0181 | 1.0 | 0.0176 | 1.0 | 16 | |
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| 0.0167 | 1.0 | 0.0162 | 1.0 | 17 | |
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| 0.0155 | 1.0 | 0.0150 | 1.0 | 18 | |
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| 0.0143 | 1.0 | 0.0140 | 1.0 | 19 | |
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### Framework versions |
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- Transformers 4.35.0 |
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- TensorFlow 2.14.0 |
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- Datasets 2.14.6 |
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- Tokenizers 0.14.1 |
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