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update model card README.md

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  1. README.md +7 -7
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@@ -19,7 +19,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9898
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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
@@ -29,8 +29,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.0315
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- - Accuracy: 0.9898
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  ## Model description
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@@ -49,7 +49,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 5e-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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- | 0.3517 | 1.0 | 351 | 0.0601 | 0.9792 |
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- | 0.2232 | 2.0 | 702 | 0.0373 | 0.9872 |
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- | 0.203 | 3.0 | 1053 | 0.0315 | 0.9898 |
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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