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  1. README.md +12 -12
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@@ -3,8 +3,6 @@ library_name: transformers
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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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- - image-classification
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- - vision
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  - generated_from_trainer
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  datasets:
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  - imagefolder
@@ -25,7 +23,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.7739130434782608
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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
@@ -35,8 +33,8 @@ 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: 0.4626
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- - Accuracy: 0.7739
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  ## Model description
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@@ -65,13 +63,15 @@ The following hyperparameters were used during training:
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.448 | 1.0 | 82 | 0.5725 | 0.7304 |
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- | 0.5097 | 2.0 | 164 | 0.4946 | 0.7652 |
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- | 0.452 | 3.0 | 246 | 0.4841 | 0.7565 |
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- | 0.3885 | 4.0 | 328 | 0.4812 | 0.7565 |
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- | 0.4743 | 5.0 | 410 | 0.4626 | 0.7739 |
 
 
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  ### Framework versions
 
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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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  - imagefolder
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.8597560975609756
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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: 0.3956
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+ - Accuracy: 0.8598
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  ## Model description
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  ### Training results
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+ | Training Loss | Epoch | Step | Accuracy | Validation Loss |
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+ |:-------------:|:-----:|:----:|:--------:|:---------------:|
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+ | 0.448 | 1.0 | 82 | 0.7304 | 0.5725 |
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+ | 0.5097 | 2.0 | 164 | 0.7652 | 0.4946 |
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+ | 0.452 | 3.0 | 246 | 0.7565 | 0.4841 |
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+ | 0.3885 | 4.0 | 328 | 0.7565 | 0.4812 |
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+ | 0.4743 | 5.0 | 410 | 0.7739 | 0.4626 |
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+ | 0.4749 | 4.0 | 464 | 0.4572 | 0.7988 |
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+ | 0.4319 | 5.0 | 580 | 0.3956 | 0.8598 |
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  ### Framework versions