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vit-base-patch16-224-in21k-finetune

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  1. README.md +9 -9
  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: 0.22988505747126436
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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 image_folder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.6043
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- - Accuracy: 0.2299
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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: 64
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  - eval_batch_size: 64
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  - seed: 42
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | No log | 0.92 | 3 | 1.6377 | 0.0920 |
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- | No log | 1.85 | 6 | 1.6208 | 0.1954 |
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- | No log | 2.77 | 9 | 1.6120 | 0.2184 |
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- | 1.5539 | 4.0 | 13 | 1.6054 | 0.2299 |
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- | 1.5539 | 4.62 | 15 | 1.6043 | 0.2299 |
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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: 0.28735632183908044
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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 image_folder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.5921
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+ - Accuracy: 0.2874
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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: 2e-05
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  - train_batch_size: 64
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  - eval_batch_size: 64
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.92 | 3 | 1.6042 | 0.2414 |
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+ | No log | 1.85 | 6 | 1.6004 | 0.2414 |
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+ | No log | 2.77 | 9 | 1.5964 | 0.2759 |
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+ | 1.4057 | 4.0 | 13 | 1.5928 | 0.2874 |
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+ | 1.4057 | 4.62 | 15 | 1.5921 | 0.2874 |
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  ### Framework versions
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