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update model card README.md

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@@ -21,7 +21,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.954140127388535
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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
@@ -29,10 +29,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # plant-seedlings-model
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- This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2858
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- - Accuracy: 0.9541
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  ## Model description
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@@ -64,21 +64,21 @@ 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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- | 1.2496 | 1.27 | 500 | 1.2172 | 0.5637 |
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- | 0.7542 | 2.54 | 1000 | 0.8994 | 0.6898 |
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- | 0.6158 | 3.82 | 1500 | 0.6794 | 0.7720 |
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- | 0.4306 | 5.09 | 2000 | 0.4715 | 0.8331 |
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- | 0.3066 | 6.36 | 2500 | 0.4127 | 0.8567 |
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- | 0.2851 | 7.63 | 3000 | 0.3460 | 0.8803 |
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- | 0.3096 | 8.91 | 3500 | 0.2714 | 0.9019 |
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- | 0.1086 | 10.18 | 4000 | 0.2760 | 0.9268 |
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- | 0.1209 | 11.45 | 4500 | 0.2881 | 0.9229 |
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- | 0.1036 | 12.72 | 5000 | 0.2566 | 0.9357 |
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- | 0.0716 | 13.99 | 5500 | 0.2792 | 0.9382 |
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- | 0.0168 | 15.27 | 6000 | 0.2604 | 0.9376 |
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- | 0.0004 | 16.54 | 6500 | 0.3676 | 0.9363 |
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- | 0.0017 | 17.81 | 7000 | 0.2969 | 0.9529 |
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- | 0.0005 | 19.08 | 7500 | 0.2858 | 0.9541 |
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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: 0.978343949044586
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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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  # plant-seedlings-model
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+ This model is a fine-tuned version of [google/vit-large-patch16-224-in21k](https://huggingface.co/google/vit-large-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: 0.1235
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+ - Accuracy: 0.9783
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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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+ | 0.3236 | 1.27 | 500 | 0.2747 | 0.9019 |
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+ | 0.2273 | 2.54 | 1000 | 0.3031 | 0.9038 |
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+ | 0.082 | 3.82 | 1500 | 0.2103 | 0.9280 |
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+ | 0.061 | 5.09 | 2000 | 0.2235 | 0.9408 |
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+ | 0.0668 | 6.36 | 2500 | 0.1633 | 0.9554 |
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+ | 0.0739 | 7.63 | 3000 | 0.1561 | 0.9586 |
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+ | 0.0836 | 8.91 | 3500 | 0.1904 | 0.9446 |
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+ | 0.0078 | 10.18 | 4000 | 0.2045 | 0.9535 |
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+ | 0.087 | 11.45 | 4500 | 0.4487 | 0.9146 |
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+ | 0.0119 | 12.72 | 5000 | 0.2162 | 0.9567 |
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+ | 0.0002 | 13.99 | 5500 | 0.1157 | 0.9758 |
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+ | 0.0001 | 15.27 | 6000 | 0.1199 | 0.9771 |
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+ | 0.0001 | 16.54 | 6500 | 0.1215 | 0.9790 |
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+ | 0.0001 | 17.81 | 7000 | 0.1223 | 0.9790 |
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+ | 0.0001 | 19.08 | 7500 | 0.1235 | 0.9783 |
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  ### Framework versions