My theory:
- Validation results that you see in Gitlab are just a model sanity check. I think it has nothing to do with what you see on your local machine. It just checks if your submission is worthy to assign pods to evaluate.
- Your local validation results are overfitted for the very obvious reason that some ~950 images are the same as that of the train. In case you have already removed these you will run into the problem of class imbalance with some classes not available at all. I created a new validation set for myself and I can say that it’s the best, the result I see on my local machine gives ~+6.0% (positive variance) jump on a test score.