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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| 0.1638 | 13.74 | 1800 | 0.5052 | 0.8197 |
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| 0.0869 | 14.89 | 1950 | 0.5427 | 0.8133 |
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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: 0.8025751072961373
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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: 0.5178
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- Accuracy: 0.8026
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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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| 0.4933 | 1.15 | 150 | 0.5452 | 0.7124 |
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| 0.4157 | 2.29 | 300 | 0.4775 | 0.7854 |
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| 0.415 | 3.44 | 450 | 0.4764 | 0.7704 |
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| 0.3509 | 4.58 | 600 | 0.4882 | 0.7961 |
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| 0.2829 | 5.73 | 750 | 0.4654 | 0.7768 |
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| 0.2706 | 6.87 | 900 | 0.4954 | 0.7961 |
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| 0.2507 | 8.02 | 1050 | 0.4421 | 0.8283 |
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| 0.2115 | 9.16 | 1200 | 0.4161 | 0.8305 |
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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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model.safetensors
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