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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](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder 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 Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.
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| 0.0004 | 10.
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| 0.0003 |
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| 0.0003 | 20.0 | 300 | 0.2924 | 0.9444 |
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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: 0.8181818181818182
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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](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6744
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- Accuracy: 0.8182
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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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| 0.0099 | 3.57 | 50 | 0.6155 | 0.8182 |
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| 0.0007 | 7.14 | 100 | 0.7441 | 0.7576 |
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| 0.0004 | 10.71 | 150 | 0.6925 | 0.8182 |
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| 0.0003 | 14.29 | 200 | 0.6793 | 0.8182 |
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| 0.0003 | 17.86 | 250 | 0.6744 | 0.8182 |
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### Framework versions
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