rshrott commited on
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Model save

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README.md CHANGED
@@ -2,7 +2,6 @@
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  license: apache-2.0
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  base_model: google/vit-base-patch16-224-in21k
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  tags:
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- - image-classification
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  - generated_from_trainer
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  model-index:
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  - name: ryan_model3272024
@@ -14,12 +13,12 @@ should probably proofread and complete it, then remove this comment. -->
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  # ryan_model3272024
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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 beans dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.0327
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- - Na Accuracy: 0.956
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- - Ordinal Accuracy: 0.568
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- - Ordinal Mae: 56.3484
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  ## Model description
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@@ -51,18 +50,18 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Na Accuracy | Ordinal Accuracy | Ordinal Mae |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------:|:----------------:|:-----------:|
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- | 1.3578 | 0.32 | 100 | 1.2058 | 0.944 | 0.54 | 90.9846 |
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- | 1.089 | 0.64 | 200 | 1.0987 | 0.95 | 0.548 | 120.7097 |
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- | 0.924 | 0.96 | 300 | 1.0838 | 0.946 | 0.568 | 76.7982 |
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- | 0.694 | 1.28 | 400 | 1.0680 | 0.942 | 0.556 | 105.6312 |
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- | 0.7739 | 1.6 | 500 | 1.0327 | 0.956 | 0.568 | 56.3484 |
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- | 0.5935 | 1.92 | 600 | 1.0479 | 0.932 | 0.598 | 50.4520 |
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- | 0.3525 | 2.24 | 700 | 1.1915 | 0.94 | 0.578 | 68.5099 |
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- | 0.2385 | 2.56 | 800 | 1.1303 | 0.948 | 0.586 | 43.0221 |
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- | 0.3423 | 2.88 | 900 | 1.1767 | 0.94 | 0.604 | 72.1437 |
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- | 0.0674 | 3.19 | 1000 | 1.2294 | 0.938 | 0.606 | 28.0702 |
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- | 0.1206 | 3.51 | 1100 | 1.2336 | 0.938 | 0.616 | 65.0794 |
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- | 0.1261 | 3.83 | 1200 | 1.2907 | 0.938 | 0.604 | 45.8334 |
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  ### Framework versions
 
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  license: apache-2.0
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  base_model: google/vit-base-patch16-224-in21k
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  tags:
 
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  - generated_from_trainer
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  model-index:
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  - name: ryan_model3272024
 
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  # ryan_model3272024
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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 None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2868
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+ - Na Accuracy: 0.95
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+ - Ordinal Accuracy: 0.6711
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+ - Ordinal Mae: 1.1626
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Na Accuracy | Ordinal Accuracy | Ordinal Mae |
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  |:-------------:|:-----:|:----:|:---------------:|:-----------:|:----------------:|:-----------:|
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+ | 0.3853 | 0.32 | 100 | 0.3272 | 0.924 | 0.52 | 1.2106 |
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+ | 0.3396 | 0.64 | 200 | 0.2741 | 0.94 | 0.5644 | 1.1640 |
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+ | 0.2075 | 0.96 | 300 | 0.2772 | 0.946 | 0.5933 | 1.1942 |
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+ | 0.196 | 1.28 | 400 | 0.2738 | 0.95 | 0.6133 | 1.1984 |
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+ | 0.2228 | 1.6 | 500 | 0.2685 | 0.956 | 0.62 | 1.1989 |
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+ | 0.1816 | 1.92 | 600 | 0.2552 | 0.95 | 0.6267 | 1.1586 |
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+ | 0.0682 | 2.24 | 700 | 0.2721 | 0.952 | 0.6578 | 1.1558 |
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+ | 0.0795 | 2.56 | 800 | 0.2754 | 0.948 | 0.6333 | 1.1599 |
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+ | 0.1367 | 2.88 | 900 | 0.2953 | 0.946 | 0.64 | 1.1667 |
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+ | 0.0387 | 3.19 | 1000 | 0.2923 | 0.944 | 0.6378 | 1.2025 |
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+ | 0.0293 | 3.51 | 1100 | 0.2885 | 0.948 | 0.6644 | 1.1666 |
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+ | 0.0286 | 3.83 | 1200 | 0.2868 | 0.95 | 0.6711 | 1.1626 |
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  ### Framework versions
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