update model card README.md
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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 food101 dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Accuracy: 0.
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## Model description
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- total_train_batch_size: 512
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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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- num_epochs: 3
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- mixed_precision_training: Native AMP
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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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| No log | 1.0 | 9 |
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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: 0.96
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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 food101 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1448
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- Accuracy: 0.96
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## Model description
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- total_train_batch_size: 512
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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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- num_epochs: 5
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- mixed_precision_training: Native AMP
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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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| No log | 1.0 | 9 | 0.5069 | 0.896 |
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| 2.1627 | 2.0 | 18 | 0.1891 | 0.946 |
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| 0.3451 | 3.0 | 27 | 0.1448 | 0.96 |
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| 0.2116 | 4.0 | 36 | 0.1509 | 0.958 |
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| 0.1711 | 5.0 | 45 | 0.1498 | 0.958 |
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### Framework versions
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