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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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Vision Transformer |
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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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