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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: YKXBCi/resnet-50-ucSat |
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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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# YKXBCi/resnet-50-ucSat |
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This model is a fine-tuned version of [microsoft/resnet-50](https://huggingface.co/microsoft/resnet-50) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.9091 |
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- Train Accuracy: 0.7125 |
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- Train Top-3-accuracy: 0.9227 |
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- Validation Loss: 1.0869 |
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- Validation Accuracy: 0.6562 |
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- Validation Top-3-accuracy: 0.8924 |
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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': 275, '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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| 2.6504 | 0.2057 | 0.3591 | 2.2693 | 0.3299 | 0.5069 | 0 | |
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| 1.8871 | 0.4062 | 0.6494 | 1.6561 | 0.4618 | 0.7083 | 1 | |
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| 1.4603 | 0.5278 | 0.7790 | 1.4162 | 0.5417 | 0.8021 | 2 | |
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| 1.1499 | 0.6199 | 0.8676 | 1.2030 | 0.625 | 0.8646 | 3 | |
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| 0.9091 | 0.7125 | 0.9227 | 1.0869 | 0.6562 | 0.8924 | 4 | |
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### Framework versions |
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- Transformers 4.18.0 |
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- TensorFlow 2.6.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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