Open swz30 opened 6 years ago
I also can't seem to reproduce the pre-trained model, even for the axis aligned version.
I am using author's config-file, data, and scripts but the network I get is not of comparable fidelity.
Does anyone know what might be causing this or what hyperparameters (LR etc.) were used to get the author's network?
@swz30 @MaxBazik @swz30 How many gpus you used? The learning rate need to be set according to the number of gpus. Our default setting is for 4 gpus. See this https://github.com/msracver/Deformable-ConvNets/issues/146.
Hello,
By using the provided code, I am trying to reproduce the model of Faster-RCNN for DOTA. So that I can train it on my data. After training of 60 epochs, the mAP on validation set of my trained model should be similar to the provided pre-trained model, but they are not (mine is much worse). I tried to preprocess the data using the get_best_begin_point function from DOTA Devkit as the authors mentioned in the disclaimer but it did not help either. Does anyone know what could be the problem, what I might be doing wrong?
During training, between epoch 23 to epoch 43, the RCNNLogLoss decreases from 0.18 to 0.17, is it normal? (The authors are decreasing learning rate as the training progresses.)