We are trying to detect foreign objects by using custom model. The model has 5 classes and for each class we have taken 48 images. We have trained our ssd model by using jetson-train github repo for around 1200 epoch. However at 1200 epoch our loss was around 1.64. My questions are:
- Would it have decreased if we had trained the model more?
- How many images should be in the dataset for each class to get a well-trained model?
- How much epoch do you suggest us to train our model? I mean should we train our model up until the loss decreases around 0.1 or 0.01 assuming that it will reach that threshold at some point?
- We have tested our model by showing the objects that it is trained with to the camera and confidence was around %90-100. However, when we show another object that the model didn’t see before the confidence was decreased around %65. Is there a possibility of overfitting to be occured in our model? If so how can we detect it and how can we prevent our model to be overfitted?