NInjaQuarrior
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Training in progress epoch 0
Browse files- README.md +6 -6
- logs/train/events.out.tfevents.1701039353.2f60df693ac5.14913.0.v2 +3 -0
- logs/train/events.out.tfevents.1701039616.2f60df693ac5.14913.1.v2 +3 -0
- logs/train/events.out.tfevents.1701039679.2f60df693ac5.14913.2.v2 +3 -0
- logs/train/events.out.tfevents.1701039701.2f60df693ac5.14913.3.v2 +3 -0
- logs/train/events.out.tfevents.1701039848.2f60df693ac5.21505.0.v2 +3 -0
- logs/train/events.out.tfevents.1701040821.2f60df693ac5.21505.1.v2 +3 -0
- logs/validation/events.out.tfevents.1701041434.2f60df693ac5.21505.2.v2 +3 -0
- tf_model.h5 +2 -2
README.md
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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.
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- Train Accuracy: 0.
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- Train Top-3-accuracy: 1.0
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- Validation Loss: 0.
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- Validation Accuracy: 0.
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- Validation Top-3-accuracy: 1.0
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- Epoch: 0
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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':
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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.
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### Framework versions
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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: 0.4890
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- Train Accuracy: 0.9378
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- Train Top-3-accuracy: 1.0
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- Validation Loss: 0.1937
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- Validation Accuracy: 0.9733
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- Validation Top-3-accuracy: 1.0
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- Epoch: 0
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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': 219, '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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| 0.4890 | 0.9378 | 1.0 | 0.1937 | 0.9733 | 1.0 | 0 |
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### Framework versions
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logs/train/events.out.tfevents.1701039353.2f60df693ac5.14913.0.v2
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logs/validation/events.out.tfevents.1701041434.2f60df693ac5.21505.2.v2
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tf_model.h5
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