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vintage-lavender619
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vit-base-patch16-224-finalterm

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  1. README.md +18 -18
  2. model.safetensors +1 -1
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.9125
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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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: 0.2709
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- - Accuracy: 0.9125
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  ## Model description
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@@ -67,21 +67,21 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 1.4514 | 1.0 | 10 | 1.1676 | 0.5594 |
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- | 1.0123 | 2.0 | 20 | 0.8034 | 0.7 |
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- | 0.6949 | 3.0 | 30 | 0.5372 | 0.8281 |
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- | 0.5385 | 4.0 | 40 | 0.4333 | 0.8719 |
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- | 0.4984 | 5.0 | 50 | 0.3638 | 0.8844 |
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- | 0.4382 | 6.0 | 60 | 0.3199 | 0.8938 |
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- | 0.3739 | 7.0 | 70 | 0.3272 | 0.9 |
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- | 0.3692 | 8.0 | 80 | 0.3230 | 0.8906 |
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- | 0.3705 | 9.0 | 90 | 0.3308 | 0.8969 |
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- | 0.3458 | 10.0 | 100 | 0.2920 | 0.9 |
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- | 0.3176 | 11.0 | 110 | 0.2880 | 0.9062 |
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- | 0.3101 | 12.0 | 120 | 0.3041 | 0.8969 |
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- | 0.3224 | 13.0 | 130 | 0.2777 | 0.9031 |
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- | 0.2946 | 14.0 | 140 | 0.2676 | 0.9156 |
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- | 0.2693 | 15.0 | 150 | 0.2709 | 0.9125 |
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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: 0.88125
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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: 0.3547
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+ - Accuracy: 0.8812
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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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+ | 1.3999 | 1.0 | 10 | 1.1607 | 0.5094 |
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+ | 0.993 | 2.0 | 20 | 0.7807 | 0.7031 |
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+ | 0.6819 | 3.0 | 30 | 0.5753 | 0.8063 |
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+ | 0.5485 | 4.0 | 40 | 0.6475 | 0.7594 |
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+ | 0.463 | 5.0 | 50 | 0.4393 | 0.8406 |
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+ | 0.3929 | 6.0 | 60 | 0.4067 | 0.8625 |
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+ | 0.3636 | 7.0 | 70 | 0.3626 | 0.8875 |
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+ | 0.3719 | 8.0 | 80 | 0.3613 | 0.8875 |
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+ | 0.343 | 9.0 | 90 | 0.3624 | 0.8781 |
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+ | 0.3297 | 10.0 | 100 | 0.3800 | 0.8625 |
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+ | 0.2948 | 11.0 | 110 | 0.3320 | 0.8938 |
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+ | 0.33 | 12.0 | 120 | 0.3481 | 0.8781 |
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+ | 0.3281 | 13.0 | 130 | 0.3418 | 0.8875 |
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+ | 0.3 | 14.0 | 140 | 0.3425 | 0.8844 |
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+ | 0.3014 | 15.0 | 150 | 0.3547 | 0.8812 |
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  ### Framework versions
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