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vit-base-patch16-224-dmae-va-U5-20-45-5e-05

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  1. README.md +22 -22
  2. model.safetensors +1 -1
  3. runs/Apr26_09-31-31_DESKTOP-SKBE9FB/events.out.tfevents.1714145493.DESKTOP-SKBE9FB.12852.0 +2 -2
README.md CHANGED
@@ -17,8 +17,8 @@ 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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.6623
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- - Accuracy: 0.85
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  ## Model description
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@@ -37,7 +37,7 @@ More information needed
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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- - learning_rate: 4.5e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
@@ -52,25 +52,25 @@ 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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- | No log | 0.9 | 7 | 1.3649 | 0.4667 |
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- | 1.3776 | 1.94 | 15 | 1.2819 | 0.5667 |
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- | 1.3038 | 2.97 | 23 | 1.1887 | 0.6 |
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- | 1.1739 | 4.0 | 31 | 1.0934 | 0.5667 |
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- | 1.1739 | 4.9 | 38 | 1.0219 | 0.6333 |
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- | 1.0493 | 5.94 | 46 | 0.9808 | 0.6 |
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- | 0.9577 | 6.97 | 54 | 0.9218 | 0.6167 |
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- | 0.8851 | 8.0 | 62 | 0.8690 | 0.75 |
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- | 0.8851 | 8.9 | 69 | 0.8580 | 0.7667 |
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- | 0.799 | 9.94 | 77 | 0.7987 | 0.8167 |
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- | 0.7312 | 10.97 | 85 | 0.7691 | 0.8 |
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- | 0.6537 | 12.0 | 93 | 0.7436 | 0.8167 |
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- | 0.5996 | 12.9 | 100 | 0.7191 | 0.8 |
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- | 0.5996 | 13.94 | 108 | 0.6922 | 0.8333 |
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- | 0.545 | 14.97 | 116 | 0.6697 | 0.8333 |
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- | 0.511 | 16.0 | 124 | 0.6623 | 0.85 |
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- | 0.4949 | 16.9 | 131 | 0.6791 | 0.8167 |
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- | 0.4949 | 17.94 | 139 | 0.6556 | 0.85 |
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- | 0.4916 | 18.06 | 140 | 0.6553 | 0.85 |
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  ### Framework versions
 
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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 an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.5675
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+ - Accuracy: 0.8667
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 5.5e-05
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  - train_batch_size: 32
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  - eval_batch_size: 32
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  - seed: 42
 
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|
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+ | No log | 0.9 | 7 | 1.3607 | 0.4833 |
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+ | 1.3752 | 1.94 | 15 | 1.2550 | 0.5833 |
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+ | 1.2809 | 2.97 | 23 | 1.1436 | 0.65 |
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+ | 1.1273 | 4.0 | 31 | 1.0381 | 0.5833 |
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+ | 1.1273 | 4.9 | 38 | 0.9620 | 0.6833 |
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+ | 0.9919 | 5.94 | 46 | 0.9154 | 0.65 |
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+ | 0.8971 | 6.97 | 54 | 0.8502 | 0.7667 |
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+ | 0.8049 | 8.0 | 62 | 0.8644 | 0.75 |
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+ | 0.8049 | 8.9 | 69 | 0.8010 | 0.7833 |
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+ | 0.7119 | 9.94 | 77 | 0.7276 | 0.8333 |
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+ | 0.6172 | 10.97 | 85 | 0.6699 | 0.8167 |
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+ | 0.5294 | 12.0 | 93 | 0.6532 | 0.8167 |
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+ | 0.4696 | 12.9 | 100 | 0.6265 | 0.85 |
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+ | 0.4696 | 13.94 | 108 | 0.6012 | 0.85 |
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+ | 0.4074 | 14.97 | 116 | 0.5800 | 0.8833 |
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+ | 0.3822 | 16.0 | 124 | 0.5692 | 0.8667 |
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+ | 0.3651 | 16.9 | 131 | 0.6065 | 0.8 |
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+ | 0.3651 | 17.94 | 139 | 0.5681 | 0.8667 |
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+ | 0.3731 | 18.06 | 140 | 0.5675 | 0.8667 |
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  ### Framework versions
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