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ongkn
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attraction-classifier

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Eval Results
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End of training

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  1. README.md +17 -17
  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: 0.7962184873949579
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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: 0.4741
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- - Accuracy: 0.7962
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  ## Model description
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@@ -68,20 +68,20 @@ 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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- | 0.6895 | 0.9 | 15 | 0.6560 | 0.6702 |
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- | 0.5774 | 1.79 | 30 | 0.5608 | 0.6954 |
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- | 0.5128 | 2.69 | 45 | 0.5295 | 0.7290 |
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- | 0.4492 | 3.58 | 60 | 0.5158 | 0.7374 |
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- | 0.4045 | 4.48 | 75 | 0.4715 | 0.7605 |
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- | 0.3634 | 5.37 | 90 | 0.4565 | 0.7878 |
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- | 0.3397 | 6.27 | 105 | 0.4294 | 0.7962 |
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- | 0.3075 | 7.16 | 120 | 0.4783 | 0.7962 |
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- | 0.2943 | 8.06 | 135 | 0.5015 | 0.7878 |
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- | 0.2887 | 8.96 | 150 | 0.4621 | 0.7983 |
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- | 0.2645 | 9.85 | 165 | 0.4326 | 0.8109 |
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- | 0.276 | 10.75 | 180 | 0.4494 | 0.8088 |
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- | 0.2413 | 11.64 | 195 | 0.5029 | 0.7794 |
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- | 0.22 | 12.54 | 210 | 0.4741 | 0.7962 |
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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: 0.8158995815899581
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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: 0.4121
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+ - Accuracy: 0.8159
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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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+ | 0.6839 | 0.89 | 15 | 0.6438 | 0.6757 |
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+ | 0.5555 | 1.78 | 30 | 0.5198 | 0.7364 |
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+ | 0.4995 | 2.67 | 45 | 0.5212 | 0.7469 |
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+ | 0.4177 | 3.56 | 60 | 0.4447 | 0.7866 |
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+ | 0.415 | 4.44 | 75 | 0.4438 | 0.7929 |
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+ | 0.3737 | 5.33 | 90 | 0.4302 | 0.7866 |
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+ | 0.3588 | 6.22 | 105 | 0.4452 | 0.7992 |
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+ | 0.3343 | 7.11 | 120 | 0.4666 | 0.7908 |
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+ | 0.3095 | 8.0 | 135 | 0.4727 | 0.7720 |
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+ | 0.2951 | 8.89 | 150 | 0.4162 | 0.8138 |
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+ | 0.2819 | 9.78 | 165 | 0.4299 | 0.8159 |
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+ | 0.257 | 10.67 | 180 | 0.4497 | 0.8033 |
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+ | 0.2625 | 11.56 | 195 | 0.4642 | 0.7971 |
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+ | 0.2287 | 12.44 | 210 | 0.4121 | 0.8159 |
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  ### Framework versions
model.safetensors CHANGED
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