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smids_5x_deit_tiny_adamax_0001_fold1

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vit
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  1. README.md +55 -55
  2. pytorch_model.bin +1 -1
README.md CHANGED
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  ---
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  license: apache-2.0
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- base_model: facebook/deit-tiny-patch16-224
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  tags:
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  - generated_from_trainer
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  datasets:
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.8998330550918197
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -30,10 +30,10 @@ should probably proofread and complete it, then remove this comment. -->
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  # smids_5x_deit_tiny_adamax_0001_fold1
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- This model is a fine-tuned version of [facebook/deit-tiny-patch16-224](https://huggingface.co/facebook/deit-tiny-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.8767
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- - Accuracy: 0.8998
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  ## Model description
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@@ -65,56 +65,56 @@ 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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- | 0.2424 | 1.0 | 376 | 0.2737 | 0.8965 |
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- | 0.1535 | 2.0 | 752 | 0.2697 | 0.8998 |
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- | 0.1563 | 3.0 | 1128 | 0.3321 | 0.8915 |
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- | 0.1275 | 4.0 | 1504 | 0.4407 | 0.8815 |
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- | 0.0346 | 5.0 | 1880 | 0.5426 | 0.8881 |
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- | 0.0225 | 6.0 | 2256 | 0.6943 | 0.8698 |
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- | 0.0208 | 7.0 | 2632 | 0.6500 | 0.8881 |
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- | 0.002 | 8.0 | 3008 | 0.7688 | 0.8781 |
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- | 0.0284 | 9.0 | 3384 | 0.7013 | 0.8915 |
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- | 0.0031 | 10.0 | 3760 | 0.8483 | 0.8765 |
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- | 0.0184 | 11.0 | 4136 | 0.7306 | 0.8932 |
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- | 0.0248 | 12.0 | 4512 | 0.7915 | 0.8815 |
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- | 0.0007 | 13.0 | 4888 | 0.7856 | 0.9015 |
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- | 0.0095 | 14.0 | 5264 | 0.8272 | 0.8982 |
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- | 0.0002 | 15.0 | 5640 | 0.8161 | 0.8965 |
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- | 0.0017 | 16.0 | 6016 | 0.9184 | 0.8865 |
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- | 0.0 | 17.0 | 6392 | 0.8425 | 0.8915 |
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- | 0.0 | 18.0 | 6768 | 0.8243 | 0.8865 |
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- | 0.0002 | 19.0 | 7144 | 0.7089 | 0.9032 |
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- | 0.0329 | 20.0 | 7520 | 0.8360 | 0.8965 |
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- | 0.0 | 21.0 | 7896 | 0.9051 | 0.8982 |
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- | 0.0 | 22.0 | 8272 | 0.8846 | 0.8932 |
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- | 0.0 | 23.0 | 8648 | 0.9073 | 0.8965 |
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- | 0.0 | 24.0 | 9024 | 0.8258 | 0.9032 |
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- | 0.0 | 25.0 | 9400 | 0.7870 | 0.8982 |
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- | 0.0078 | 26.0 | 9776 | 0.7859 | 0.8998 |
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- | 0.0 | 27.0 | 10152 | 0.8761 | 0.8965 |
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- | 0.0 | 28.0 | 10528 | 0.8403 | 0.8948 |
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- | 0.0064 | 29.0 | 10904 | 0.8789 | 0.8948 |
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- | 0.0067 | 30.0 | 11280 | 0.8065 | 0.9048 |
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- | 0.0 | 31.0 | 11656 | 0.8436 | 0.9015 |
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- | 0.0 | 32.0 | 12032 | 0.8304 | 0.8965 |
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- | 0.0 | 33.0 | 12408 | 0.8352 | 0.8932 |
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- | 0.0 | 34.0 | 12784 | 0.8552 | 0.8998 |
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- | 0.0 | 35.0 | 13160 | 0.8399 | 0.8998 |
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- | 0.0 | 36.0 | 13536 | 0.8312 | 0.8965 |
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- | 0.0 | 37.0 | 13912 | 0.8449 | 0.9015 |
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- | 0.0 | 38.0 | 14288 | 0.8413 | 0.8948 |
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- | 0.0 | 39.0 | 14664 | 0.8495 | 0.8915 |
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- | 0.0 | 40.0 | 15040 | 0.8477 | 0.8915 |
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- | 0.0 | 41.0 | 15416 | 0.8579 | 0.8998 |
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- | 0.0 | 42.0 | 15792 | 0.8591 | 0.8998 |
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- | 0.0 | 43.0 | 16168 | 0.8599 | 0.8965 |
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- | 0.0 | 44.0 | 16544 | 0.8652 | 0.8965 |
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- | 0.0 | 45.0 | 16920 | 0.8676 | 0.8998 |
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- | 0.0032 | 46.0 | 17296 | 0.8701 | 0.9015 |
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- | 0.0 | 47.0 | 17672 | 0.8734 | 0.8998 |
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- | 0.0 | 48.0 | 18048 | 0.8744 | 0.8998 |
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- | 0.0 | 49.0 | 18424 | 0.8758 | 0.8998 |
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- | 0.0023 | 50.0 | 18800 | 0.8767 | 0.8998 |
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  ### Framework versions
 
1
  ---
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  license: apache-2.0
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+ base_model: facebook/deit-small-patch16-224
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  tags:
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  - generated_from_trainer
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  datasets:
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.9115191986644408
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
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  # smids_5x_deit_tiny_adamax_0001_fold1
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+ This model is a fine-tuned version of [facebook/deit-small-patch16-224](https://huggingface.co/facebook/deit-small-patch16-224) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7374
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+ - Accuracy: 0.9115
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|
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+ | 0.2308 | 1.0 | 376 | 0.2388 | 0.9115 |
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+ | 0.1317 | 2.0 | 752 | 0.2582 | 0.9098 |
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+ | 0.1686 | 3.0 | 1128 | 0.4270 | 0.8831 |
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+ | 0.0405 | 4.0 | 1504 | 0.4962 | 0.8781 |
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+ | 0.0366 | 5.0 | 1880 | 0.4884 | 0.8965 |
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+ | 0.0181 | 6.0 | 2256 | 0.6032 | 0.8982 |
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+ | 0.0062 | 7.0 | 2632 | 0.6900 | 0.8965 |
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+ | 0.0021 | 8.0 | 3008 | 0.5787 | 0.9115 |
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+ | 0.0022 | 9.0 | 3384 | 0.7270 | 0.8932 |
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+ | 0.0002 | 10.0 | 3760 | 0.6268 | 0.9115 |
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+ | 0.0012 | 11.0 | 4136 | 0.5883 | 0.9082 |
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+ | 0.0001 | 12.0 | 4512 | 0.5732 | 0.9165 |
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+ | 0.0 | 13.0 | 4888 | 0.5583 | 0.9215 |
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+ | 0.011 | 14.0 | 5264 | 0.7089 | 0.9032 |
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+ | 0.0002 | 15.0 | 5640 | 0.7954 | 0.8815 |
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+ | 0.0 | 16.0 | 6016 | 0.6772 | 0.8965 |
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+ | 0.0 | 17.0 | 6392 | 0.6923 | 0.9032 |
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+ | 0.0 | 18.0 | 6768 | 0.7006 | 0.8982 |
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+ | 0.0 | 19.0 | 7144 | 0.6930 | 0.9032 |
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+ | 0.0149 | 20.0 | 7520 | 0.7767 | 0.8948 |
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+ | 0.0 | 21.0 | 7896 | 0.6643 | 0.9132 |
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+ | 0.0 | 22.0 | 8272 | 0.6887 | 0.9015 |
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+ | 0.0 | 23.0 | 8648 | 0.6854 | 0.8998 |
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+ | 0.0001 | 24.0 | 9024 | 0.6666 | 0.9132 |
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+ | 0.0 | 25.0 | 9400 | 0.6680 | 0.9082 |
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+ | 0.0033 | 26.0 | 9776 | 0.6701 | 0.9115 |
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+ | 0.0 | 27.0 | 10152 | 0.6769 | 0.8998 |
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+ | 0.0 | 28.0 | 10528 | 0.6638 | 0.9115 |
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+ | 0.0042 | 29.0 | 10904 | 0.6671 | 0.9165 |
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+ | 0.004 | 30.0 | 11280 | 0.6642 | 0.9115 |
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+ | 0.0 | 31.0 | 11656 | 0.6776 | 0.9098 |
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+ | 0.0 | 32.0 | 12032 | 0.6835 | 0.9098 |
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+ | 0.0 | 33.0 | 12408 | 0.7324 | 0.9048 |
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+ | 0.0 | 34.0 | 12784 | 0.7298 | 0.9048 |
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+ | 0.0 | 35.0 | 13160 | 0.7063 | 0.9098 |
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+ | 0.0 | 36.0 | 13536 | 0.7145 | 0.9098 |
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+ | 0.0 | 37.0 | 13912 | 0.7213 | 0.9082 |
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+ | 0.0 | 38.0 | 14288 | 0.7239 | 0.9098 |
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+ | 0.0 | 39.0 | 14664 | 0.7296 | 0.9065 |
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+ | 0.0 | 40.0 | 15040 | 0.7280 | 0.9082 |
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+ | 0.0 | 41.0 | 15416 | 0.7172 | 0.9098 |
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+ | 0.0 | 42.0 | 15792 | 0.7224 | 0.9098 |
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+ | 0.0 | 43.0 | 16168 | 0.7245 | 0.9115 |
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+ | 0.0 | 44.0 | 16544 | 0.7307 | 0.9098 |
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+ | 0.0 | 45.0 | 16920 | 0.7306 | 0.9098 |
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+ | 0.0026 | 46.0 | 17296 | 0.7273 | 0.9098 |
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+ | 0.0 | 47.0 | 17672 | 0.7340 | 0.9132 |
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+ | 0.0 | 48.0 | 18048 | 0.7346 | 0.9132 |
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+ | 0.0 | 49.0 | 18424 | 0.7359 | 0.9132 |
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+ | 0.0022 | 50.0 | 18800 | 0.7374 | 0.9115 |
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  ### Framework versions
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