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 [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-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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- 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:
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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.
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| 0.
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| 0.
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| 0.0003 | 6.0 | 5538 | 1.5337 | 0.8331 |
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| 0.0635 | 7.0 | 6461 | 1.5787 | 0.8377 |
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| 0.0071 | 8.0 | 7384 | 1.6914 | 0.8350 |
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| 0.0 | 9.0 | 8307 | 1.7195 | 0.8404 |
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| 0.0 | 10.0 | 9230 | 1.7296 | 0.8420 |
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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: 0.8406504065040651
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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 [microsoft/beit-large-patch16-224](https://huggingface.co/microsoft/beit-large-patch16-224) on the imagefolder dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2276
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- Accuracy: 0.8407
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## Model description
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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: 5
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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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| 0.3425 | 1.0 | 923 | 0.4401 | 0.8230 |
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| 0.2611 | 2.0 | 1846 | 0.4241 | 0.8314 |
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| 0.1595 | 3.0 | 2769 | 0.5720 | 0.8363 |
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| 0.1001 | 4.0 | 3692 | 0.9325 | 0.8344 |
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| 0.0096 | 5.0 | 4615 | 1.2276 | 0.8407 |
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### Framework versions
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