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ongkn
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attraction-classifier

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

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  1. README.md +13 -16
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
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  ---
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  license: apache-2.0
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- base_model: microsoft/swin-tiny-patch4-window7-224
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  tags:
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  - generated_from_trainer
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  datasets:
@@ -8,7 +8,7 @@ datasets:
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  metrics:
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  - accuracy
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  model-index:
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- - name: attraction-classifier-swin
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  results:
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  - task:
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  name: Image Classification
@@ -22,18 +22,18 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.739010989010989
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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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  should probably proofread and complete it, then remove this comment. -->
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- # attraction-classifier-swin
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- This model is a fine-tuned version of [microsoft/swin-tiny-patch4-window7-224](https://huggingface.co/microsoft/swin-tiny-patch4-window7-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5367
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- - Accuracy: 0.7390
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  ## Model description
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@@ -65,15 +65,12 @@ 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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- | 0.6207 | 0.49 | 100 | 0.5599 | 0.7115 |
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- | 0.6256 | 0.98 | 200 | 0.5238 | 0.7225 |
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- | 0.597 | 1.46 | 300 | 0.5003 | 0.7418 |
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- | 0.6121 | 1.95 | 400 | 0.5409 | 0.7610 |
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- | 0.5457 | 2.44 | 500 | 0.5123 | 0.7555 |
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- | 0.5258 | 2.93 | 600 | 0.4792 | 0.7637 |
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- | 0.504 | 3.41 | 700 | 0.5169 | 0.7390 |
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- | 0.541 | 3.9 | 800 | 0.4858 | 0.7582 |
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- | 0.5704 | 4.39 | 900 | 0.5367 | 0.7390 |
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  ### Framework versions
 
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  ---
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  license: apache-2.0
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+ base_model: google/vit-base-patch16-224-in21k
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - accuracy
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  model-index:
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+ - name: attraction-classifier
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  results:
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  - task:
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  name: Image Classification
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7465940054495913
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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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  should probably proofread and complete it, then remove this comment. -->
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+ # attraction-classifier
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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: 0.7466
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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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+ | 0.6401 | 0.48 | 100 | 0.6248 | 0.6512 |
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+ | 0.5832 | 0.97 | 200 | 0.5530 | 0.7493 |
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+ | 0.6077 | 1.45 | 300 | 0.5085 | 0.7466 |
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+ | 0.5551 | 1.93 | 400 | 0.5322 | 0.7357 |
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+ | 0.4431 | 2.42 | 500 | 0.5745 | 0.7084 |
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+ | 0.4644 | 2.9 | 600 | 0.5204 | 0.7466 |
 
 
 
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  ### Framework versions
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