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the output is strange after training on my own dataset #7
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Hi, it is pretty strange. There must be some bugs while transplanting to your dataset. I could not ensure the problems with the information provided. Have you modified the loss by the way or adjust the hyper-parameters? Will the training loss decrease in the training? |
Also I change the lr decrease steps, so the lr is normal, I think. I also tried to use the pre-trained res-151 model to initialize the network but it turned out to be the same. |
Sorry, I still don't know the causes from your description :( |
Hi,friend, it's me again. <_>
![image](https://user-images.githubusercontent.com/17823646/48963573-0b806500-efd0-11e8-9444-2152a84c29bc.png)
I use my own data to train my network. Because I only recorded the steer angle, so I modified it to output only one float, the steer angle. However something strange happened. The mean loss in training stage stays high. Then I check the output on the val dataset and find the values are all positive. Though my dataset is not as big as yours, it still contains thousands samples from 4 scenes. Some of my outputs are in the picture. I tried to normalized the data, but it did not work. What should I do to solve the problem?
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