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rshrott
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ryan_model3272024

Image Classification
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Safetensors
vit
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  1. README.md +15 -9
  2. model.safetensors +1 -1
  3. runs/Mar27_22-12-30_ryanserver/events.out.tfevents.1711591955.ryanserver.19364.0 +2 -2
README.md CHANGED
@@ -15,10 +15,10 @@ 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 None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3657
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- - Na Accuracy: 0.625
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- - Ordinal Accuracy: 0.4762
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- - Ordinal Mae: 0.8694
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  ## Model description
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@@ -50,11 +50,17 @@ 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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- | 0.412 | 0.78 | 25 | 0.3861 | 0.875 | 0.2143 | 1.0826 |
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- | 0.2394 | 1.56 | 50 | 0.4621 | 0.5 | 0.1905 | 1.0658 |
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- | 0.2287 | 2.34 | 75 | 0.5636 | 0.25 | 0.2857 | 0.9874 |
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- | 0.1518 | 3.12 | 100 | 0.3832 | 0.625 | 0.3810 | 0.9202 |
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- | 0.1448 | 3.91 | 125 | 0.3657 | 0.625 | 0.4762 | 0.8694 |
 
 
 
 
 
 
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  ### Framework versions
 
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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: 0.3366
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+ - Na Accuracy: 0.5946
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+ - Ordinal Accuracy: 0.5171
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+ - Ordinal Mae: 0.6727
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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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+ | 0.4062 | 0.13 | 25 | 0.3799 | 0.6216 | 0.2395 | 0.9244 |
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+ | 0.3536 | 0.27 | 50 | 0.3700 | 0.6757 | 0.3840 | 0.9067 |
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+ | 0.4295 | 0.4 | 75 | 0.3405 | 0.7838 | 0.2966 | 0.8798 |
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+ | 0.4114 | 0.53 | 100 | 0.3906 | 0.7297 | 0.3536 | 0.8806 |
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+ | 0.3521 | 0.66 | 125 | 0.3530 | 0.8108 | 0.4259 | 0.8442 |
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+ | 0.3349 | 0.8 | 150 | 0.3412 | 0.7297 | 0.4753 | 0.8016 |
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+ | 0.4612 | 0.93 | 175 | 0.3639 | 0.5405 | 0.4677 | 0.7604 |
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+ | 0.2424 | 1.06 | 200 | 0.3297 | 0.7027 | 0.4867 | 0.7117 |
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+ | 0.2928 | 1.2 | 225 | 0.3494 | 0.6757 | 0.5285 | 0.6955 |
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+ | 0.2436 | 1.33 | 250 | 0.3037 | 0.7297 | 0.5285 | 0.6723 |
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+ | 0.2776 | 1.46 | 275 | 0.3366 | 0.5946 | 0.5171 | 0.6727 |
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  ### Framework versions
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