I am using transfer learnig on vgg11 and train my model on dataset A and testing on dataset B and C to perform binary classification.
Initially, the learnign rate was 0.001 and I used a scheduler every 2 epochs the accuracy doesnt decrease the accuracy would drop to 1/10th of the current learnign rate.
When I used this method, the accuracy of the model was stryggling to go voer 50% thought the learning rate was decreasing.
Then I initiated the learning rate at 0.0001 and the model accuracy after the first epoch is 90% and it keeps increasing.
Some more infromation about my training loop:
- My batch sie is 16
2)I update the weights every batch size
- At the end of each epoch I evaluate the model by testing it on the other datasets and the mean accuracy is 85% ± 2% and mean loss varies from 0.3 to 1.1