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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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Files changed (2) hide show
  1. README.md +14 -15
  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: 0.7939814814814815
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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: 0.5004
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- - Accuracy: 0.7940
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 4e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 69
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.5938 | 0.62 | 150 | 0.5738 | 0.7199 |
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- | 0.4934 | 1.23 | 300 | 0.5229 | 0.7454 |
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- | 0.5048 | 1.85 | 450 | 0.5361 | 0.7222 |
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- | 0.4615 | 2.47 | 600 | 0.4958 | 0.7685 |
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- | 0.4591 | 3.09 | 750 | 0.4720 | 0.7639 |
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- | 0.3679 | 3.7 | 900 | 0.5321 | 0.7454 |
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- | 0.3366 | 4.32 | 1050 | 0.6765 | 0.7083 |
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- | 0.3057 | 4.94 | 1200 | 0.4633 | 0.7940 |
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- | 0.316 | 5.56 | 1350 | 0.5217 | 0.7639 |
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- | 0.3186 | 6.17 | 1500 | 0.5226 | 0.7708 |
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- | 0.2319 | 6.79 | 1650 | 0.5004 | 0.7940 |
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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: 0.7786790266512167
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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: 0.4928
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+ - Accuracy: 0.7787
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5e-05
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  - train_batch_size: 16
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  - eval_batch_size: 16
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  - seed: 69
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | 0.5947 | 0.69 | 150 | 0.5553 | 0.7207 |
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+ | 0.5428 | 1.39 | 300 | 0.5073 | 0.7428 |
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+ | 0.5383 | 2.08 | 450 | 0.4809 | 0.7729 |
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+ | 0.5369 | 2.78 | 600 | 0.4887 | 0.7520 |
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+ | 0.3966 | 3.47 | 750 | 0.5199 | 0.7520 |
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+ | 0.3722 | 4.17 | 900 | 0.4805 | 0.7706 |
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+ | 0.3758 | 4.86 | 1050 | 0.4658 | 0.7868 |
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+ | 0.2742 | 5.56 | 1200 | 0.4732 | 0.7949 |
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+ | 0.2333 | 6.25 | 1350 | 0.4981 | 0.7822 |
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+ | 0.2318 | 6.94 | 1500 | 0.4928 | 0.7787 |
 
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  ### Framework versions
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