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  1. README.md +16 -4
  2. model.safetensors +1 -1
  3. runs/Mar18_06-11-10_41edc3304339/events.out.tfevents.1710742294.41edc3304339.7217.0 +3 -0
  4. training_args.bin +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: 0.8907407407407407
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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: 0.4002
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- - Accuracy: 0.8907
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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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- | 0.0841 | 3.7 | 1000 | 0.4002 | 0.8907 |
 
 
 
 
 
 
 
 
 
 
 
 
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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: 0.9101851851851852
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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: 0.3224
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+ - Accuracy: 0.9102
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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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+ | 1.2269 | 0.37 | 100 | 1.2058 | 0.6019 |
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+ | 1.0891 | 0.74 | 200 | 0.9254 | 0.7046 |
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+ | 0.5328 | 1.11 | 300 | 0.7417 | 0.7741 |
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+ | 0.5259 | 1.48 | 400 | 0.7145 | 0.7722 |
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+ | 0.4889 | 1.85 | 500 | 0.5621 | 0.825 |
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+ | 0.2753 | 2.22 | 600 | 0.5251 | 0.8444 |
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+ | 0.2569 | 2.59 | 700 | 0.5792 | 0.8259 |
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+ | 0.2251 | 2.96 | 800 | 0.4169 | 0.8731 |
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+ | 0.086 | 3.33 | 900 | 0.4182 | 0.8843 |
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+ | 0.1352 | 3.7 | 1000 | 0.3711 | 0.8880 |
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+ | 0.0608 | 4.07 | 1100 | 0.3430 | 0.9046 |
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+ | 0.0175 | 4.44 | 1200 | 0.3241 | 0.9185 |
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+ | 0.0149 | 4.81 | 1300 | 0.3224 | 0.9102 |
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  ### Framework versions
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