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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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the fashion_mnist dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.
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- Accuracy: 0.
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.
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### Framework versions
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- Transformers 4.31.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.
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- Tokenizers 0.13.3
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.792
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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 [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the fashion_mnist dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.0461
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- Accuracy: 0.792
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## Model description
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.285 | 0.99 | 62 | 1.2299 | 0.718 |
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| 1.2002 | 2.0 | 125 | 1.2043 | 0.744 |
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| 1.0345 | 2.98 | 186 | 1.0461 | 0.792 |
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### Framework versions
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- Transformers 4.31.0.dev0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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