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rayhanozzy
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image_classification

Image Classification
Transformers
PyTorch
vit
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Community
rayhanozzy commited on
Commit
7749379
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1 Parent(s): 8492c1b

End of training

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Files changed (2) hide show
  1. README.md +23 -23
  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: 0.58125
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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: 1.5857
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- - Accuracy: 0.5813
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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 | 80 | 1.4085 | 0.5062 |
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- | No log | 2.0 | 160 | 1.5462 | 0.5062 |
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- | No log | 3.0 | 240 | 1.5687 | 0.525 |
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- | No log | 4.0 | 320 | 1.5465 | 0.5625 |
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- | No log | 5.0 | 400 | 1.7599 | 0.5 |
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- | No log | 6.0 | 480 | 1.8047 | 0.5312 |
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- | 0.244 | 7.0 | 560 | 1.8441 | 0.525 |
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- | 0.244 | 8.0 | 640 | 1.7620 | 0.5375 |
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- | 0.244 | 9.0 | 720 | 1.5618 | 0.5563 |
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- | 0.244 | 10.0 | 800 | 1.8267 | 0.5125 |
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- | 0.244 | 11.0 | 880 | 1.5343 | 0.6 |
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- | 0.244 | 12.0 | 960 | 1.8340 | 0.5375 |
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- | 0.237 | 13.0 | 1040 | 1.7273 | 0.575 |
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- | 0.237 | 14.0 | 1120 | 1.7158 | 0.5563 |
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- | 0.237 | 15.0 | 1200 | 1.6075 | 0.55 |
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- | 0.237 | 16.0 | 1280 | 1.6131 | 0.5687 |
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- | 0.237 | 17.0 | 1360 | 1.8439 | 0.55 |
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- | 0.237 | 18.0 | 1440 | 1.9079 | 0.5188 |
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- | 0.1695 | 19.0 | 1520 | 1.7325 | 0.5687 |
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- | 0.1695 | 20.0 | 1600 | 1.5776 | 0.5938 |
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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: 0.59375
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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: 1.3020
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+ - Accuracy: 0.5938
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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 | 80 | 1.3711 | 0.4313 |
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+ | No log | 2.0 | 160 | 1.2946 | 0.5188 |
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+ | No log | 3.0 | 240 | 1.1760 | 0.5563 |
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+ | No log | 4.0 | 320 | 1.3317 | 0.5 |
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+ | No log | 5.0 | 400 | 1.3201 | 0.4938 |
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+ | No log | 6.0 | 480 | 1.2809 | 0.5375 |
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+ | 0.8929 | 7.0 | 560 | 1.3645 | 0.5 |
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+ | 0.8929 | 8.0 | 640 | 1.2415 | 0.5563 |
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+ | 0.8929 | 9.0 | 720 | 1.4341 | 0.5125 |
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+ | 0.8929 | 10.0 | 800 | 1.3027 | 0.5625 |
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+ | 0.8929 | 11.0 | 880 | 1.3131 | 0.5813 |
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+ | 0.8929 | 12.0 | 960 | 1.4144 | 0.525 |
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+ | 0.3836 | 13.0 | 1040 | 1.3987 | 0.5563 |
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+ | 0.3836 | 14.0 | 1120 | 1.3167 | 0.5938 |
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+ | 0.3836 | 15.0 | 1200 | 1.3588 | 0.6 |
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+ | 0.3836 | 16.0 | 1280 | 1.2747 | 0.625 |
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+ | 0.3836 | 17.0 | 1360 | 1.4555 | 0.575 |
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+ | 0.3836 | 18.0 | 1440 | 1.3795 | 0.5875 |
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+ | 0.2078 | 19.0 | 1520 | 1.5430 | 0.525 |
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+ | 0.2078 | 20.0 | 1600 | 1.4164 | 0.5813 |
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  ### Framework versions
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