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End of training

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README.md CHANGED
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  ---
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  library_name: transformers
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  license: apache-2.0
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- base_model: google/vit-base-patch16-224
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  tags:
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  - generated_from_trainer
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  datasets:
@@ -23,7 +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: 0.75
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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
@@ -31,10 +31,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # CIDAUTv2
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- This model is a fine-tuned version of [google/vit-base-patch16-224](https://huggingface.co/google/vit-base-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.5012
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- - Accuracy: 0.75
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  ## Model description
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@@ -68,16 +68,16 @@ 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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- | No log | 1.0 | 4 | 0.7104 | 0.5139 |
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- | No log | 2.0 | 8 | 0.6436 | 0.6065 |
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- | 0.685 | 3.0 | 12 | 0.6004 | 0.6944 |
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- | 0.685 | 4.0 | 16 | 0.5978 | 0.6759 |
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- | 0.5422 | 5.0 | 20 | 0.5582 | 0.7222 |
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- | 0.5422 | 6.0 | 24 | 0.5222 | 0.7361 |
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- | 0.5422 | 7.0 | 28 | 0.5060 | 0.7222 |
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- | 0.4521 | 8.0 | 32 | 0.4957 | 0.7269 |
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- | 0.4521 | 9.0 | 36 | 0.4781 | 0.75 |
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- | 0.3741 | 10.0 | 40 | 0.5012 | 0.75 |
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  ### Framework versions
 
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  ---
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  library_name: transformers
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  license: apache-2.0
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+ base_model: microsoft/beit-base-patch16-224-pt22k-ft22k
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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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  - name: Accuracy
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  type: accuracy
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+ value: 0.9259259259259259
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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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  # CIDAUTv2
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+ This model is a fine-tuned version of [microsoft/beit-base-patch16-224-pt22k-ft22k](https://huggingface.co/microsoft/beit-base-patch16-224-pt22k-ft22k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2719
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+ - Accuracy: 0.9259
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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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+ | No log | 1.0 | 4 | 0.7322 | 0.5880 |
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+ | No log | 2.0 | 8 | 0.6585 | 0.5972 |
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+ | 0.7438 | 3.0 | 12 | 0.6115 | 0.7222 |
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+ | 0.7438 | 4.0 | 16 | 0.5726 | 0.7546 |
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+ | 0.5781 | 5.0 | 20 | 0.4803 | 0.7824 |
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+ | 0.5781 | 6.0 | 24 | 0.4627 | 0.8333 |
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+ | 0.5781 | 7.0 | 28 | 0.4060 | 0.8056 |
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+ | 0.4511 | 8.0 | 32 | 0.3512 | 0.8796 |
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+ | 0.4511 | 9.0 | 36 | 0.2725 | 0.9028 |
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+ | 0.296 | 10.0 | 40 | 0.2719 | 0.9259 |
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  ### Framework versions
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