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vit-base-clothing-leafs-example-full-simple

Image Classification
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  ---
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  license: apache-2.0
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  tags:
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- - image-classification
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  - generated_from_trainer
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  metrics:
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  - accuracy
@@ -15,10 +14,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # vit-base-clothing-leafs-example-full-simple
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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: 0.9866
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- - Accuracy: 0.7118
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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: 5e-05
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  - train_batch_size: 32
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  - eval_batch_size: 8
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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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- | 1.7384 | 0.14 | 1000 | 1.3281 | 0.6473 |
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- | 1.2367 | 0.28 | 2000 | 1.1815 | 0.6703 |
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- | 1.1348 | 0.41 | 3000 | 1.1290 | 0.6794 |
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- | 1.1003 | 0.55 | 4000 | 1.0927 | 0.6883 |
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- | 1.0695 | 0.69 | 5000 | 1.0641 | 0.6911 |
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- | 1.0426 | 0.83 | 6000 | 1.0410 | 0.6958 |
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- | 1.0247 | 0.97 | 7000 | 1.0402 | 0.6937 |
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- | 0.9406 | 1.11 | 8000 | 1.0244 | 0.7004 |
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- | 0.8824 | 1.24 | 9000 | 1.0365 | 0.6993 |
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- | 0.8979 | 1.38 | 10000 | 1.0051 | 0.7067 |
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- | 0.8947 | 1.52 | 11000 | 0.9986 | 0.7089 |
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- | 0.8785 | 1.66 | 12000 | 0.9866 | 0.7118 |
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- | 0.8881 | 1.8 | 13000 | 0.9892 | 0.7112 |
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- | 0.8652 | 1.94 | 14000 | 0.9875 | 0.7112 |
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- | 0.7969 | 2.07 | 15000 | 1.0030 | 0.7083 |
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- | 0.7153 | 2.21 | 16000 | 1.0069 | 0.7085 |
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- | 0.7158 | 2.35 | 17000 | 1.0076 | 0.7080 |
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- | 0.7248 | 2.49 | 18000 | 1.0020 | 0.7108 |
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- | 0.7204 | 2.63 | 19000 | 0.9929 | 0.7131 |
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- | 0.7127 | 2.77 | 20000 | 0.9929 | 0.7139 |
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- | 0.7274 | 2.9 | 21000 | 0.9929 | 0.7105 |
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- | 0.6769 | 3.04 | 22000 | 1.0152 | 0.7118 |
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- | 0.5859 | 3.18 | 23000 | 1.0314 | 0.7089 |
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- | 0.5811 | 3.32 | 24000 | 1.0340 | 0.7106 |
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- | 0.5863 | 3.46 | 25000 | 1.0253 | 0.7105 |
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- | 0.5656 | 3.6 | 26000 | 1.0279 | 0.7104 |
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- | 0.5753 | 3.73 | 27000 | 1.0284 | 0.7108 |
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- | 0.5681 | 3.87 | 28000 | 1.0260 | 0.7112 |
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  ### Framework versions
 
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  ---
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  license: apache-2.0
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  tags:
 
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  - generated_from_trainer
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  metrics:
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  - accuracy
 
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  # vit-base-clothing-leafs-example-full-simple
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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: 1.0593
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+ - Accuracy: 0.7100
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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: 7.5e-05
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  - train_batch_size: 32
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  - eval_batch_size: 8
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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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+ | 1.6085 | 0.14 | 1000 | 1.2965 | 0.6414 |
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+ | 1.2071 | 0.28 | 2000 | 1.1638 | 0.6690 |
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+ | 1.1467 | 0.41 | 3000 | 1.1357 | 0.6722 |
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+ | 1.1073 | 0.55 | 4000 | 1.0940 | 0.6833 |
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+ | 1.0721 | 0.69 | 5000 | 1.0802 | 0.6859 |
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+ | 1.0607 | 0.83 | 6000 | 1.0509 | 0.6947 |
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+ | 1.032 | 0.97 | 7000 | 1.0557 | 0.6915 |
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+ | 0.9224 | 1.11 | 8000 | 1.0506 | 0.6966 |
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+ | 0.9029 | 1.24 | 9000 | 1.0421 | 0.6952 |
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+ | 0.8858 | 1.38 | 10000 | 1.0204 | 0.7019 |
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+ | 0.8943 | 1.52 | 11000 | 1.0182 | 0.7038 |
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+ | 0.8756 | 1.66 | 12000 | 1.0011 | 0.7108 |
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+ | 0.8657 | 1.8 | 13000 | 1.0035 | 0.7074 |
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+ | 0.8737 | 1.94 | 14000 | 0.9963 | 0.7102 |
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+ | 0.7893 | 2.07 | 15000 | 1.0208 | 0.7089 |
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+ | 0.7067 | 2.21 | 16000 | 1.0219 | 0.7076 |
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+ | 0.7072 | 2.35 | 17000 | 1.0181 | 0.7096 |
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+ | 0.6914 | 2.49 | 18000 | 1.0165 | 0.7123 |
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+ | 0.7044 | 2.63 | 19000 | 1.0173 | 0.7124 |
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+ | 0.7014 | 2.77 | 20000 | 1.0056 | 0.7145 |
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+ | 0.6997 | 2.9 | 21000 | 1.0049 | 0.7116 |
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+ | 0.6378 | 3.04 | 22000 | 1.0353 | 0.7105 |
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+ | 0.5446 | 3.18 | 23000 | 1.0574 | 0.7086 |
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+ | 0.5307 | 3.32 | 24000 | 1.0585 | 0.7079 |
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+ | 0.5269 | 3.46 | 25000 | 1.0661 | 0.7094 |
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+ | 0.525 | 3.6 | 26000 | 1.0599 | 0.7104 |
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+ | 0.516 | 3.73 | 27000 | 1.0658 | 0.7111 |
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+ | 0.5224 | 3.87 | 28000 | 1.0593 | 0.7100 |
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  ### Framework versions