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ongkn
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attraction-classifier

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Model card Files
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End of training

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  1. README.md +13 -16
  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: 0.8092105263157895
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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: 0.4681
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- - Accuracy: 0.8092
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  ## Model description
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@@ -65,19 +65,16 @@ 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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- | 0.535 | 0.59 | 150 | 0.5924 | 0.6798 |
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- | 0.6195 | 1.17 | 300 | 0.5788 | 0.6711 |
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- | 0.5 | 1.76 | 450 | 0.5351 | 0.7083 |
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- | 0.4374 | 2.34 | 600 | 0.4798 | 0.7654 |
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- | 0.4301 | 2.93 | 750 | 0.4351 | 0.7873 |
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- | 0.3583 | 3.52 | 900 | 0.4604 | 0.7741 |
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- | 0.3514 | 4.1 | 1050 | 0.4616 | 0.7785 |
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- | 0.3666 | 4.69 | 1200 | 0.4592 | 0.7917 |
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- | 0.2873 | 5.27 | 1350 | 0.4872 | 0.7807 |
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- | 0.3231 | 5.86 | 1500 | 0.4409 | 0.8136 |
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- | 0.2683 | 6.45 | 1650 | 0.4806 | 0.7939 |
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- | 0.2199 | 7.03 | 1800 | 0.4561 | 0.8070 |
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- | 0.1951 | 7.62 | 1950 | 0.4681 | 0.8092 |
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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: 0.777292576419214
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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: 0.5204
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+ - Accuracy: 0.7773
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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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+ | 0.598 | 0.58 | 150 | 0.5666 | 0.7009 |
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+ | 0.5215 | 1.16 | 300 | 0.5232 | 0.7336 |
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+ | 0.482 | 1.74 | 450 | 0.4753 | 0.7729 |
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+ | 0.4054 | 2.33 | 600 | 0.4420 | 0.7926 |
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+ | 0.4036 | 2.91 | 750 | 0.5779 | 0.7314 |
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+ | 0.373 | 3.49 | 900 | 0.4676 | 0.7969 |
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+ | 0.3633 | 4.07 | 1050 | 0.4585 | 0.7991 |
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+ | 0.3547 | 4.65 | 1200 | 0.4677 | 0.7926 |
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+ | 0.2572 | 5.23 | 1350 | 0.5232 | 0.7773 |
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+ | 0.3254 | 5.81 | 1500 | 0.5204 | 0.7773 |
 
 
 
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  ### Framework versions
model.safetensors CHANGED
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