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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: eyesCare_firstTryEntrnal_mix_model-1 |
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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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# eyesCare_firstTryEntrnal_mix_model-1 |
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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: 0.0066 |
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- Train Accuracy: 0.8616 |
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- Train Top-3-accuracy: 0.9785 |
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- Validation Loss: 1.9942 |
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- Validation Accuracy: 0.8627 |
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- Validation Top-3-accuracy: 0.9787 |
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- Epoch: 29 |
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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': 4e-05, 'decay_steps': 4950, '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': 0.001} |
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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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| 1.3981 | 0.3217 | 0.7428 | 1.1812 | 0.4135 | 0.8283 | 0 | |
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| 1.1137 | 0.4540 | 0.8600 | 1.0974 | 0.4763 | 0.8802 | 1 | |
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| 0.9296 | 0.5034 | 0.8955 | 1.0739 | 0.5231 | 0.9065 | 2 | |
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| 0.7444 | 0.5473 | 0.9155 | 1.1126 | 0.5663 | 0.9225 | 3 | |
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| 0.5534 | 0.5880 | 0.9285 | 1.1673 | 0.6076 | 0.9342 | 4 | |
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| 0.4105 | 0.6261 | 0.9387 | 1.1547 | 0.6422 | 0.9428 | 5 | |
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| 0.2830 | 0.6586 | 0.9462 | 1.3119 | 0.6729 | 0.9493 | 6 | |
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| 0.1984 | 0.6874 | 0.9519 | 1.3821 | 0.6990 | 0.9540 | 7 | |
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| 0.1224 | 0.7104 | 0.9559 | 1.4778 | 0.7213 | 0.9576 | 8 | |
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| 0.1021 | 0.7313 | 0.9591 | 1.5426 | 0.7400 | 0.9603 | 9 | |
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| 0.1017 | 0.7478 | 0.9615 | 1.6387 | 0.7545 | 0.9625 | 10 | |
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| 0.0646 | 0.7613 | 0.9635 | 1.6226 | 0.7678 | 0.9644 | 11 | |
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| 0.0500 | 0.7738 | 0.9654 | 1.6646 | 0.7793 | 0.9662 | 12 | |
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| 0.0571 | 0.7843 | 0.9669 | 1.7492 | 0.7890 | 0.9675 | 13 | |
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| 0.0248 | 0.7935 | 0.9682 | 1.6984 | 0.7978 | 0.9689 | 14 | |
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| 0.0185 | 0.8020 | 0.9695 | 1.7302 | 0.8059 | 0.9701 | 15 | |
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| 0.0145 | 0.8096 | 0.9707 | 1.7669 | 0.8129 | 0.9712 | 16 | |
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| 0.0129 | 0.8163 | 0.9718 | 1.7972 | 0.8193 | 0.9722 | 17 | |
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| 0.0116 | 0.8223 | 0.9727 | 1.8276 | 0.8251 | 0.9732 | 18 | |
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| 0.0106 | 0.8277 | 0.9736 | 1.8544 | 0.8302 | 0.9739 | 19 | |
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| 0.0098 | 0.8326 | 0.9743 | 1.8792 | 0.8348 | 0.9746 | 20 | |
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| 0.0091 | 0.8370 | 0.9749 | 1.9012 | 0.8391 | 0.9752 | 21 | |
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| 0.0085 | 0.8411 | 0.9755 | 1.9212 | 0.8430 | 0.9758 | 22 | |
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| 0.0080 | 0.8448 | 0.9761 | 1.9391 | 0.8465 | 0.9763 | 23 | |
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| 0.0076 | 0.8482 | 0.9766 | 1.9547 | 0.8498 | 0.9768 | 24 | |
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| 0.0073 | 0.8513 | 0.9770 | 1.9682 | 0.8527 | 0.9772 | 25 | |
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| 0.0070 | 0.8542 | 0.9774 | 1.9789 | 0.8555 | 0.9777 | 26 | |
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| 0.0068 | 0.8568 | 0.9778 | 1.9871 | 0.8580 | 0.9780 | 27 | |
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| 0.0067 | 0.8593 | 0.9782 | 1.9924 | 0.8605 | 0.9784 | 28 | |
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| 0.0066 | 0.8616 | 0.9785 | 1.9942 | 0.8627 | 0.9787 | 29 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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