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ongkn
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attraction-classifier

Image Classification
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Safetensors
vit
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Eval Results
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End of training

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  1. README.md +15 -13
  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: 0.8209606986899564
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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-in21k](https://huggingface.co/google/vit-base-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: 0.4930
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- - Accuracy: 0.8210
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  ## Model description
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@@ -58,21 +58,23 @@ The following hyperparameters were used during training:
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  - seed: 69
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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: 0.05
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- - num_epochs: 10
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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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- | 0.4846 | 1.16 | 150 | 0.5930 | 0.7118 |
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- | 0.4383 | 2.33 | 300 | 0.4550 | 0.7751 |
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- | 0.3695 | 3.49 | 450 | 0.4941 | 0.7838 |
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- | 0.314 | 4.65 | 600 | 0.5041 | 0.7795 |
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- | 0.2717 | 5.81 | 750 | 0.4721 | 0.8057 |
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- | 0.2261 | 6.98 | 900 | 0.4459 | 0.8079 |
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- | 0.1931 | 8.14 | 1050 | 0.5161 | 0.7904 |
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- | 0.1703 | 9.3 | 1200 | 0.4930 | 0.8210 |
 
 
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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: 0.8187772925764192
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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 imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5072
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+ - Accuracy: 0.8188
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  ## Model description
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  - seed: 69
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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: 15
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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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+ | 0.4952 | 1.16 | 150 | 0.5743 | 0.7009 |
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+ | 0.4475 | 2.33 | 300 | 0.4772 | 0.7729 |
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+ | 0.4287 | 3.49 | 450 | 0.4688 | 0.7642 |
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+ | 0.2978 | 4.65 | 600 | 0.5202 | 0.7707 |
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+ | 0.3176 | 5.81 | 750 | 0.4475 | 0.7926 |
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+ | 0.2602 | 6.98 | 900 | 0.4760 | 0.7882 |
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+ | 0.2526 | 8.14 | 1050 | 0.4766 | 0.8188 |
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+ | 0.1601 | 9.3 | 1200 | 0.4925 | 0.8122 |
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+ | 0.1925 | 10.47 | 1350 | 0.5308 | 0.8079 |
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+ | 0.1343 | 11.63 | 1500 | 0.5072 | 0.8188 |
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  ### Framework versions
model.safetensors CHANGED
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