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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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model-index:
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- name: vit-base-cifar10
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results: []
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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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should probably proofread and complete it, then remove this comment. -->
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# vit-base-cifar10
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This model is a fine-tuned version of [nateraw/vit-base-patch16-224-cifar10](https://huggingface.co/nateraw/vit-base-patch16-224-cifar10) on the cifar10-upside-down dataset.
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It achieves the following results on the evaluation set:
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- eval_loss: 0.2348
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- eval_accuracy: 0.9134
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- eval_runtime: 157.4172
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- eval_samples_per_second: 127.051
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- eval_steps_per_second: 1.988
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- epoch: 0.02
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- step: 26
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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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- learning_rate: 0.0002
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 5
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- mixed_precision_training: Native AMP
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### Framework versions
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- Transformers 4.18.0
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- Pytorch 1.10.0+cu111
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- Datasets 2.0.0
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- Tokenizers 0.11.6
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