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README.md
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the cifar10 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.
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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: 32
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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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| 0.
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| 0.
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| 0.
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### Framework versions
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9918
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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This model is a fine-tuned version of [microsoft/beit-base-patch16-224](https://huggingface.co/microsoft/beit-base-patch16-224) on the cifar10 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0256
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- Accuracy: 0.9918
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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: 3e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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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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| 0.3296 | 1.0 | 351 | 0.0492 | 0.9862 |
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| 0.2353 | 2.0 | 702 | 0.0331 | 0.9894 |
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| 0.2127 | 3.0 | 1053 | 0.0256 | 0.9918 |
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### Framework versions
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