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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- seed: 69
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.
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- num_epochs:
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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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: 0.8187772925764192
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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: 0.5072
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- Accuracy: 0.8188
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## Model description
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- seed: 69
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.4952 | 1.16 | 150 | 0.5743 | 0.7009 |
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| 0.4475 | 2.33 | 300 | 0.4772 | 0.7729 |
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| 0.4287 | 3.49 | 450 | 0.4688 | 0.7642 |
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| 0.2978 | 4.65 | 600 | 0.5202 | 0.7707 |
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| 0.3176 | 5.81 | 750 | 0.4475 | 0.7926 |
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| 0.2602 | 6.98 | 900 | 0.4760 | 0.7882 |
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| 0.2526 | 8.14 | 1050 | 0.4766 | 0.8188 |
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| 0.1601 | 9.3 | 1200 | 0.4925 | 0.8122 |
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| 0.1925 | 10.47 | 1350 | 0.5308 | 0.8079 |
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| 0.1343 | 11.63 | 1500 | 0.5072 | 0.8188 |
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### Framework versions
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model.safetensors
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