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MinhLe999
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3class_EfficientFormer30M_ForTesting

Image Classification
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universal_vision
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End of training

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  1. README.md +16 -16
  2. model.safetensors +1 -1
  3. training_args.bin +2 -2
README.md CHANGED
@@ -19,12 +19,12 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.0820
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- - Precision: 0.9831
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- - Recall: 0.9790
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  - Accuracy: 0.9844
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- - F1: 0.9809
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- - Roc Auc: 0.9981
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  ## Model description
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@@ -56,17 +56,17 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 | Roc Auc |
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  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|:-------:|
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- | 0.1609 | 0.3436 | 200 | 0.0851 | 0.9673 | 0.9645 | 0.9718 | 0.9658 | 0.9964 |
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- | 0.0811 | 0.6873 | 400 | 0.0652 | 0.9767 | 0.9725 | 0.9790 | 0.9745 | 0.9981 |
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- | 0.0418 | 1.0309 | 600 | 0.1268 | 0.9602 | 0.9661 | 0.9690 | 0.9628 | 0.9948 |
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- | 0.0427 | 1.3746 | 800 | 0.0735 | 0.9756 | 0.9744 | 0.9793 | 0.9750 | 0.9973 |
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- | 0.0054 | 1.7182 | 1000 | 0.0614 | 0.9823 | 0.9779 | 0.9834 | 0.9800 | 0.9982 |
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- | 0.0293 | 2.0619 | 1200 | 0.0681 | 0.9812 | 0.9788 | 0.9834 | 0.9800 | 0.9983 |
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- | 0.0020 | 2.4055 | 1400 | 0.0676 | 0.9818 | 0.9787 | 0.9837 | 0.9802 | 0.9984 |
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- | 0.0332 | 2.7491 | 1600 | 0.0818 | 0.9812 | 0.9759 | 0.9823 | 0.9784 | 0.9982 |
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- | 0.0005 | 3.0928 | 1800 | 0.0755 | 0.9824 | 0.9793 | 0.9841 | 0.9808 | 0.9982 |
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- | 0.0017 | 3.4364 | 2000 | 0.0842 | 0.9819 | 0.9775 | 0.9832 | 0.9796 | 0.9979 |
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- | 0.0049 | 3.7801 | 2200 | 0.0820 | 0.9831 | 0.9790 | 0.9844 | 0.9809 | 0.9981 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.0789
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+ - Precision: 0.9828
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+ - Recall: 0.9793
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  - Accuracy: 0.9844
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+ - F1: 0.9810
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+ - Roc Auc: 0.9979
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | Accuracy | F1 | Roc Auc |
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  |:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:--------:|:------:|:-------:|
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+ | 0.1255 | 0.3436 | 200 | 0.0861 | 0.9693 | 0.9606 | 0.9711 | 0.9646 | 0.9965 |
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+ | 0.0694 | 0.6873 | 400 | 0.0761 | 0.9735 | 0.9657 | 0.9748 | 0.9692 | 0.9973 |
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+ | 0.0347 | 1.0309 | 600 | 0.0843 | 0.9727 | 0.9730 | 0.9774 | 0.9728 | 0.9964 |
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+ | 0.0632 | 1.3746 | 800 | 0.0855 | 0.9691 | 0.9716 | 0.9753 | 0.9703 | 0.9972 |
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+ | 0.0132 | 1.7182 | 1000 | 0.0731 | 0.9763 | 0.9751 | 0.9797 | 0.9757 | 0.9976 |
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+ | 0.0222 | 2.0619 | 1200 | 0.0671 | 0.9792 | 0.9785 | 0.9825 | 0.9789 | 0.9981 |
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+ | 0.0024 | 2.4055 | 1400 | 0.0739 | 0.9813 | 0.9786 | 0.9834 | 0.9799 | 0.9978 |
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+ | 0.0030 | 2.7491 | 1600 | 0.0793 | 0.9828 | 0.9780 | 0.9837 | 0.9803 | 0.9978 |
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+ | 0.0021 | 3.0928 | 1800 | 0.0751 | 0.9823 | 0.9797 | 0.9844 | 0.9810 | 0.9980 |
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+ | 0.0008 | 3.4364 | 2000 | 0.0821 | 0.9832 | 0.9789 | 0.9844 | 0.9810 | 0.9978 |
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+ | 0.0016 | 3.7801 | 2200 | 0.0789 | 0.9828 | 0.9793 | 0.9844 | 0.9810 | 0.9979 |
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  ### Framework versions
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