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

Image Classification
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vit
Generated from Trainer
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update model card README.md

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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: 0.9991
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- - Accuracy: 0.7126
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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: 2e-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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- | 2.1442 | 0.14 | 1000 | 1.6088 | 0.6230 |
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- | 1.4492 | 0.28 | 2000 | 1.3311 | 0.6612 |
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- | 1.2669 | 0.41 | 3000 | 1.2137 | 0.6771 |
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- | 1.1901 | 0.55 | 4000 | 1.1688 | 0.6790 |
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- | 1.1535 | 0.69 | 5000 | 1.1221 | 0.6876 |
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- | 1.1027 | 0.83 | 6000 | 1.0926 | 0.6927 |
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- | 1.0715 | 0.97 | 7000 | 1.0783 | 0.6932 |
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- | 1.0052 | 1.11 | 8000 | 1.0529 | 0.7012 |
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- | 0.9777 | 1.24 | 9000 | 1.0450 | 0.7022 |
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- | 0.9798 | 1.38 | 10000 | 1.0449 | 0.7013 |
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- | 0.9473 | 1.52 | 11000 | 1.0282 | 0.7041 |
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- | 0.9463 | 1.66 | 12000 | 1.0422 | 0.6972 |
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- | 0.9508 | 1.8 | 13000 | 1.0289 | 0.7026 |
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- | 0.9447 | 1.94 | 14000 | 1.0159 | 0.7070 |
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- | 0.8831 | 2.07 | 15000 | 1.0163 | 0.7082 |
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- | 0.8581 | 2.21 | 16000 | 1.0117 | 0.7076 |
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- | 0.8453 | 2.35 | 17000 | 1.0045 | 0.7118 |
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- | 0.8422 | 2.49 | 18000 | 1.0125 | 0.7068 |
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- | 0.8451 | 2.63 | 19000 | 1.0195 | 0.7045 |
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- | 0.8348 | 2.77 | 20000 | 1.0000 | 0.7131 |
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- | 0.8319 | 2.9 | 21000 | 0.9991 | 0.7126 |
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- | 0.8165 | 3.04 | 22000 | 1.0051 | 0.7118 |
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- | 0.7483 | 3.18 | 23000 | 1.0074 | 0.7133 |
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- | 0.7689 | 3.32 | 24000 | 1.0144 | 0.7098 |
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- | 0.7574 | 3.46 | 25000 | 1.0074 | 0.7123 |
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- | 0.7625 | 3.6 | 26000 | 1.0112 | 0.7105 |
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- | 0.7667 | 3.73 | 27000 | 1.0088 | 0.7107 |
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- | 0.7472 | 3.87 | 28000 | 1.0082 | 0.7117 |
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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: 1.0154
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+ - Accuracy: 0.7155
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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: 3e-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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+ | 1.9495 | 0.14 | 1000 | 1.4553 | 0.6307 |
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+ | 1.3079 | 0.28 | 2000 | 1.2347 | 0.6677 |
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+ | 1.178 | 0.41 | 3000 | 1.1607 | 0.6758 |
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+ | 1.1324 | 0.55 | 4000 | 1.1307 | 0.6824 |
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+ | 1.0928 | 0.69 | 5000 | 1.0956 | 0.6909 |
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+ | 1.0679 | 0.83 | 6000 | 1.0790 | 0.6912 |
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+ | 1.0488 | 0.97 | 7000 | 1.0486 | 0.7014 |
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+ | 0.9548 | 1.11 | 8000 | 1.0449 | 0.7016 |
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+ | 0.9352 | 1.24 | 9000 | 1.0348 | 0.7042 |
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+ | 0.9164 | 1.38 | 10000 | 1.0340 | 0.7034 |
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+ | 0.9267 | 1.52 | 11000 | 1.0178 | 0.7089 |
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+ | 0.9058 | 1.66 | 12000 | 1.0160 | 0.7063 |
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+ | 0.9028 | 1.8 | 13000 | 1.0084 | 0.7111 |
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+ | 0.9093 | 1.94 | 14000 | 1.0009 | 0.7136 |
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+ | 0.8346 | 2.07 | 15000 | 1.0152 | 0.7117 |
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+ | 0.7897 | 2.21 | 16000 | 1.0072 | 0.7141 |
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+ | 0.7869 | 2.35 | 17000 | 1.0088 | 0.7083 |
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+ | 0.7853 | 2.49 | 18000 | 0.9981 | 0.7162 |
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+ | 0.7732 | 2.63 | 19000 | 1.0030 | 0.7149 |
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+ | 0.779 | 2.77 | 20000 | 0.9954 | 0.7155 |
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+ | 0.7655 | 2.9 | 21000 | 0.9972 | 0.7179 |
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+ | 0.74 | 3.04 | 22000 | 1.0114 | 0.7138 |
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+ | 0.6824 | 3.18 | 23000 | 1.0171 | 0.7130 |
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+ | 0.68 | 3.32 | 24000 | 1.0111 | 0.7178 |
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+ | 0.6787 | 3.46 | 25000 | 1.0124 | 0.7151 |
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+ | 0.6808 | 3.6 | 26000 | 1.0181 | 0.7150 |
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+ | 0.6561 | 3.73 | 27000 | 1.0144 | 0.7168 |
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+ | 0.6611 | 3.87 | 28000 | 1.0154 | 0.7155 |
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  ### Framework versions