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update model card README.md
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README.md
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---
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license: apache-2.0
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tags:
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- image-classification
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- generated_from_trainer
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metrics:
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- accuracy
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# vit-base-clothing-leafs-example-full-simple
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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 the
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate:
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- train_batch_size: 32
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- eval_batch_size: 8
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- seed: 42
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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### Framework versions
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---
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license: apache-2.0
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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# vit-base-clothing-leafs-example-full-simple
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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 the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0039
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- Accuracy: 0.7146
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## Model description
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1.75e-05
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- train_batch_size: 32
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- eval_batch_size: 8
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- seed: 42
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 2.1712 | 0.14 | 1000 | 1.6429 | 0.6206 |
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| 1.4661 | 0.28 | 2000 | 1.3387 | 0.6625 |
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| 1.2803 | 0.41 | 3000 | 1.2176 | 0.6767 |
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| 1.2063 | 0.55 | 4000 | 1.1589 | 0.6827 |
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| 1.1377 | 0.69 | 5000 | 1.0993 | 0.6957 |
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| 1.1039 | 0.83 | 6000 | 1.0647 | 0.7012 |
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| 1.0691 | 0.97 | 7000 | 1.0476 | 0.7037 |
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| 0.9729 | 1.11 | 8000 | 1.0341 | 0.7060 |
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| 0.9621 | 1.24 | 9000 | 1.0242 | 0.7090 |
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| 0.9344 | 1.38 | 10000 | 1.0159 | 0.7104 |
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| 0.9364 | 1.52 | 11000 | 1.0165 | 0.7083 |
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| 0.9235 | 1.66 | 12000 | 1.0139 | 0.7089 |
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| 0.9264 | 1.8 | 13000 | 1.0029 | 0.7109 |
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| 0.9161 | 1.94 | 14000 | 0.9822 | 0.7145 |
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| 0.8473 | 2.07 | 15000 | 1.0041 | 0.7135 |
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| 0.7759 | 2.21 | 16000 | 1.0011 | 0.7137 |
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| 0.7743 | 2.35 | 17000 | 1.0025 | 0.7119 |
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| 0.7699 | 2.49 | 18000 | 0.9976 | 0.7148 |
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| 0.7691 | 2.63 | 19000 | 1.0039 | 0.7146 |
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### Framework versions
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