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I saw you are keeping the dropout during the testing phase in test_pretrained_SemanticKITTI.py. When I trained the model, the results turned out well, reaching 75% MIOU. I went on to validate the model using test_pretrained_SemanticKITTI.py and found the MIOU went down to nearly 55%. Also, each inference generates a quite different answer; over 30% of labels were changed each time.
Is it supposed to be that drastic? Should I change the dropout rate to 0 when inferencing?
The text was updated successfully, but these errors were encountered:
I saw you are keeping the dropout during the testing phase in test_pretrained_SemanticKITTI.py. When I trained the model, the results turned out well, reaching 75% MIOU. I went on to validate the model using test_pretrained_SemanticKITTI.py and found the MIOU went down to nearly 55%. Also, each inference generates a quite different answer; over 30% of labels were changed each time.
Is it supposed to be that drastic? Should I change the dropout rate to 0 when inferencing?
The text was updated successfully, but these errors were encountered: