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mhdiqbalpradipta
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minang_food_classification

Image Classification
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vit
Generated from Trainer
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mhdiqbalpradipta commited on
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  1. README.md +26 -26
  2. model.safetensors +1 -1
  3. runs/May16_06-08-24_ace45c84f0d7/events.out.tfevents.1715840257.ace45c84f0d7.1140.6 +3 -0
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: 0.9388888888888889
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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](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: 0.7593
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- - Accuracy: 0.9389
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  ## Model description
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@@ -65,31 +65,31 @@ 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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- | 1.3787 | 1.0 | 45 | 1.3959 | 0.75 |
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- | 1.283 | 2.0 | 90 | 1.2962 | 0.7889 |
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- | 1.1978 | 3.0 | 135 | 1.2320 | 0.8056 |
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- | 1.1274 | 4.0 | 180 | 1.1618 | 0.8333 |
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- | 1.0807 | 5.0 | 225 | 1.0641 | 0.8556 |
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- | 1.0178 | 6.0 | 270 | 1.0442 | 0.8333 |
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- | 0.9573 | 7.0 | 315 | 0.9657 | 0.8889 |
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- | 0.9072 | 8.0 | 360 | 0.9505 | 0.8833 |
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- | 0.872 | 9.0 | 405 | 0.9192 | 0.8944 |
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- | 0.8334 | 10.0 | 450 | 0.9023 | 0.8722 |
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- | 0.814 | 11.0 | 495 | 0.8054 | 0.9278 |
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- | 0.7668 | 12.0 | 540 | 0.8127 | 0.9444 |
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- | 0.7569 | 13.0 | 585 | 0.7832 | 0.9167 |
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- | 0.7483 | 14.0 | 630 | 0.8084 | 0.8833 |
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- | 0.7548 | 15.0 | 675 | 0.7762 | 0.8833 |
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- | 0.7258 | 16.0 | 720 | 0.7698 | 0.8889 |
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- | 0.7149 | 17.0 | 765 | 0.7466 | 0.9111 |
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- | 0.7001 | 18.0 | 810 | 0.7655 | 0.9222 |
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- | 0.7159 | 19.0 | 855 | 0.7529 | 0.9 |
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- | 0.7073 | 20.0 | 900 | 0.8048 | 0.8889 |
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  ### Framework versions
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- - Transformers 4.38.2
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  - Pytorch 2.2.1+cu121
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- - Datasets 2.18.0
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- - Tokenizers 0.15.2
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7388888888888889
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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](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: 1.4322
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+ - Accuracy: 0.7389
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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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+ | 2.1765 | 1.0 | 45 | 2.1135 | 0.1944 |
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+ | 2.0794 | 2.0 | 90 | 2.0191 | 0.3056 |
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+ | 2.014 | 3.0 | 135 | 2.0172 | 0.2722 |
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+ | 1.9374 | 4.0 | 180 | 1.8951 | 0.3722 |
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+ | 1.8757 | 5.0 | 225 | 1.7853 | 0.5 |
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+ | 1.7953 | 6.0 | 270 | 1.7469 | 0.4944 |
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+ | 1.7265 | 7.0 | 315 | 1.6992 | 0.5722 |
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+ | 1.6665 | 8.0 | 360 | 1.6337 | 0.6 |
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+ | 1.6208 | 9.0 | 405 | 1.5924 | 0.6611 |
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+ | 1.557 | 10.0 | 450 | 1.5561 | 0.6667 |
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+ | 1.5172 | 11.0 | 495 | 1.4839 | 0.7167 |
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+ | 1.4805 | 12.0 | 540 | 1.4971 | 0.7278 |
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+ | 1.4655 | 13.0 | 585 | 1.4299 | 0.75 |
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+ | 1.4332 | 14.0 | 630 | 1.4313 | 0.7111 |
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+ | 1.4312 | 15.0 | 675 | 1.4258 | 0.7278 |
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+ | 1.3964 | 16.0 | 720 | 1.4136 | 0.7333 |
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+ | 1.3765 | 17.0 | 765 | 1.3875 | 0.8056 |
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+ | 1.3719 | 18.0 | 810 | 1.4031 | 0.7389 |
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+ | 1.3857 | 19.0 | 855 | 1.4242 | 0.7389 |
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+ | 1.3845 | 20.0 | 900 | 1.4025 | 0.75 |
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  ### Framework versions
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+ - Transformers 4.40.2
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  - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.1
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+ - Tokenizers 0.19.1
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