how to adjust learning rates or something to be better when using a pretrained model to train my dataset?please give me some advice

[J-LINC]

I'm trying to train my own data set using pretrained weights, BDD100K. Can you give me some advice? (All parameters unchanged, e.g. learning rate and step of learning rate decay) Below is the result of my 12 epoch training. I think map is a little too low, but the values of each loss function shown in the diagram are very small. I am worried that if I continue without any hyper parameter changes, the model will be overfitting. I currently set the number of training rounds to 250 epoch, which is evaluated every 10 rounds, and every 50 epochs saves the model.The following image shows the losses I have trained for 10 epochs and the evaluation results on the validation set