Is timm/utils/metrics.py reliable for completely imbalanced datasets? #1272
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bryanpiguave
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does this repo have an example of how to build and display the confusion matrix after train.py is run? |
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I am currently working on long-tailed recognition. Everything seems to be ok when I trained the model. The model obtained a 91% accuracy in top1 in the validation set. However, when I created the confusion matrix, the weighted average accuracy was 72%. It seems to me that the accuracy does not consider a weighted accuracy, it is calculated in terms of the batch and it is gradually updated. Should I consider the implemented function as reliable for my study case?
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