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dyaminda
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image_classification

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
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  1. README.md +26 -26
  2. pytorch_model.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: 0.61875
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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: 1.2094
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- - Accuracy: 0.6188
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  ## Model description
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@@ -67,31 +67,31 @@ 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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- | 1.8174 | 1.0 | 10 | 1.8349 | 0.4062 |
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- | 1.7364 | 2.0 | 20 | 1.6966 | 0.4 |
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- | 1.6087 | 3.0 | 30 | 1.5892 | 0.45 |
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- | 1.4904 | 4.0 | 40 | 1.4914 | 0.4875 |
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- | 1.4009 | 5.0 | 50 | 1.4288 | 0.5125 |
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- | 1.3129 | 6.0 | 60 | 1.3619 | 0.575 |
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- | 1.2233 | 7.0 | 70 | 1.3622 | 0.5687 |
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- | 1.1419 | 8.0 | 80 | 1.3047 | 0.5188 |
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- | 1.094 | 9.0 | 90 | 1.2763 | 0.6062 |
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- | 1.0366 | 10.0 | 100 | 1.2496 | 0.5625 |
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- | 0.9785 | 11.0 | 110 | 1.2368 | 0.6 |
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- | 0.9435 | 12.0 | 120 | 1.1960 | 0.6438 |
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- | 0.9031 | 13.0 | 130 | 1.2083 | 0.5563 |
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- | 0.8829 | 14.0 | 140 | 1.2629 | 0.5188 |
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- | 0.824 | 15.0 | 150 | 1.2061 | 0.5938 |
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- | 0.7952 | 16.0 | 160 | 1.2630 | 0.55 |
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- | 0.7744 | 17.0 | 170 | 1.2329 | 0.5625 |
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- | 0.7487 | 18.0 | 180 | 1.2259 | 0.5437 |
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- | 0.7381 | 19.0 | 190 | 1.1750 | 0.5813 |
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- | 0.7261 | 20.0 | 200 | 1.1802 | 0.575 |
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  ### Framework versions
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- - Transformers 4.33.1
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- - Pytorch 2.0.1+cu118
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- - Datasets 2.14.5
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  - Tokenizers 0.13.3
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.5125
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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: 1.3634
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+ - Accuracy: 0.5125
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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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+ | 2.0947 | 1.0 | 10 | 2.0806 | 0.1375 |
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+ | 2.0549 | 2.0 | 20 | 2.0395 | 0.175 |
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+ | 1.9588 | 3.0 | 30 | 1.9427 | 0.2812 |
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+ | 1.8014 | 4.0 | 40 | 1.7817 | 0.3438 |
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+ | 1.6343 | 5.0 | 50 | 1.6330 | 0.4313 |
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+ | 1.5099 | 6.0 | 60 | 1.5820 | 0.4125 |
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+ | 1.4078 | 7.0 | 70 | 1.4982 | 0.4625 |
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+ | 1.3281 | 8.0 | 80 | 1.4624 | 0.4813 |
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+ | 1.253 | 9.0 | 90 | 1.4064 | 0.4813 |
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+ | 1.1858 | 10.0 | 100 | 1.4197 | 0.4938 |
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+ | 1.1196 | 11.0 | 110 | 1.3527 | 0.55 |
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+ | 1.0653 | 12.0 | 120 | 1.3507 | 0.4688 |
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+ | 1.0107 | 13.0 | 130 | 1.3738 | 0.5125 |
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+ | 0.988 | 14.0 | 140 | 1.3758 | 0.4938 |
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+ | 0.9433 | 15.0 | 150 | 1.3541 | 0.4813 |
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+ | 0.9243 | 16.0 | 160 | 1.3265 | 0.5125 |
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+ | 0.8914 | 17.0 | 170 | 1.3634 | 0.4938 |
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+ | 0.8715 | 18.0 | 180 | 1.3683 | 0.4875 |
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+ | 0.8679 | 19.0 | 190 | 1.3197 | 0.55 |
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+ | 0.8479 | 20.0 | 200 | 1.3085 | 0.5188 |
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  ### Framework versions
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+ - Transformers 4.33.2
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+ - Pytorch 2.0.1+cu117
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+ - Datasets 2.14.4
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  - Tokenizers 0.13.3
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