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vit-base-patch16-224-in21k-finetuned-lora-food101

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  1. README.md +9 -8
  2. adapter_model.safetensors +1 -1
README.md CHANGED
@@ -14,13 +14,14 @@ model-index:
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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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  should probably proofread and complete it, then remove this comment. -->
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- [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/saeid93/huggingface/runs/hyirhij9)
 
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  # vit-base-patch16-224-in21k-finetuned-lora-food101
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.1574
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- - Accuracy: 0.948
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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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- | No log | 1.0 | 9 | 0.6507 | 0.872 |
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- | 2.2113 | 2.0 | 18 | 0.2310 | 0.934 |
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- | 0.3841 | 3.0 | 27 | 0.1893 | 0.936 |
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- | 0.2264 | 4.0 | 36 | 0.1719 | 0.946 |
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- | 0.1946 | 5.0 | 45 | 0.1574 | 0.948 |
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  ### Framework versions
 
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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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  should probably proofread and complete it, then remove this comment. -->
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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/saeid93/huggingface/runs/2ghiy1dr)
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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/saeid93/huggingface/runs/2ghiy1dr)
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  # vit-base-patch16-224-in21k-finetuned-lora-food101
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.1403
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+ - Accuracy: 0.95
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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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+ | No log | 1.0 | 9 | 0.6670 | 0.864 |
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+ | 2.2303 | 2.0 | 18 | 0.2156 | 0.93 |
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+ | 0.3942 | 3.0 | 27 | 0.1582 | 0.956 |
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+ | 0.2467 | 4.0 | 36 | 0.1474 | 0.948 |
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+ | 0.1852 | 5.0 | 45 | 0.1403 | 0.95 |
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  ### Framework versions
adapter_model.safetensors CHANGED
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