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I am training YOLO network consisting of resnet50 architecture.This problem is to find different text labels on the image and predict bounding boxes

During training, I am seeing very less change in both training and validation loss. What are different method / debugging techniques to know where exacly is the problem. I am training on 5000 images and have around 23M parameters to train. I am using batch size as 8 and training times as 5 and number of epochs as 50.

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vaibhav bansal
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1 Answers1

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Welcome to the site! My first thought is that 5k images is definitely not enough to hope to optimize 23m parameters, which is why your loss does not decrease.

Tom
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    Ok, data is not a problem for me as I am generating it myself. could you give sense of how much images i should go for to train 23M parameters.To give more information , I have 9 classes to predict on each image. – vaibhav bansal Sep 21 '18 at 10:07