Model save
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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: 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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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.31704202872849796
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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: 1.9972
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- Accuracy: 0.3170
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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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| 1.7068 | 0.9993 | 378 | 1.9533 | 0.2753 |
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| 1.6691 | 1.9987 | 756 | 1.9642 | 0.2864 |
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| 1.6278 | 2.9980 | 1134 | 1.9935 | 0.3018 |
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| 1.5837 | 4.0 | 1513 | 2.0155 | 0.3077 |
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| 1.5263 | 4.9993 | 1891 | 2.0283 | 0.3063 |
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| 1.4969 | 5.9987 | 2269 | 2.0026 | 0.3081 |
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| 1.5088 | 6.9980 | 2647 | 2.0275 | 0.3098 |
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| 1.4623 | 8.0 | 3026 | 2.0096 | 0.3137 |
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| 1.4305 | 8.9993 | 3404 | 2.0239 | 0.3154 |
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| 1.3895 | 9.9934 | 3780 | 1.9972 | 0.3170 |
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### Framework versions
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- Transformers 4.40.1
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- Pytorch 2.0.1+cu117
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- Datasets 2.19.1
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- Tokenizers 0.19.1
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