End of training
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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 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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| 0.1666 | 10.31 | 1350 | 0.5859 | 0.7811 |
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| 0.1515 | 11.45 | 1500 | 0.4683 | 0.8283 |
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| 0.1315 | 12.6 | 1650 | 0.5178 | 0.8026 |
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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: 0.7733050847457628
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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 imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5835
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- Accuracy: 0.7733
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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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| 0.5128 | 1.13 | 150 | 0.5352 | 0.7331 |
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| 0.4228 | 2.26 | 300 | 0.4504 | 0.7775 |
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| 0.3536 | 3.38 | 450 | 0.5563 | 0.7542 |
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| 0.3233 | 4.51 | 600 | 0.5737 | 0.7797 |
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| 0.324 | 5.64 | 750 | 0.4690 | 0.8030 |
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| 0.2677 | 6.77 | 900 | 0.5285 | 0.7669 |
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| 0.2755 | 7.89 | 1050 | 0.4705 | 0.7797 |
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| 0.1914 | 9.02 | 1200 | 0.5835 | 0.7733 |
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### Framework versions
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model.safetensors
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