Comments (2)
Thank you. I have unterstood what you said. Your code is clear and straightforward. It's excellent!The folders are also well-organized. I've benefited a lot.
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What is the purpose of the classifier_main file?
SimSiam is a self-supervised pretraining approach. After pre-training your model, you use the pre-trained model for initialization before fine-tuning on a down-stream task (e.g., a classification task).
Concretely, this repos is designed to run pretrain_main.py first. After completion, use the checkpoint created by pre-training, to fine-tune a model on a down-stream task (e.g., classifier_main.py)
Please make sure to read SimSiam paper.
How can I use model_best.pth
?
After you train your model on a training split, you want to evaluate it on a val/test split.
Some people use the last checkpoint to evaluate their model. For instance, if a model is trained for 200 epochs, the checkpoint_200.pt is used for evaluation. Yet, this is not the only way for evaluation.
Some people use the checkpoint that achieved the best performance on the validation split to evaluate on a test split. This approach can be regarded as an early stopping approach.model_best.pth
is the checkpoint that achieved the best performance on the validation split, and accordingly, you can use it evaluate on a test split
I hope this helps.
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