Comments (4)
Hi Gabriel,
Sorry I missed your comment here. My Harvard email turned off, and I just realized I wasn't getting notifications.
If you're willing to put some time in to set it up, Spearmint (https://github.com/HIPS/Spearmint) is a great option for performing hyper-parameter searches. It sounds like your models are training quickly, so maybe you can perform a grid search in a reasonable amount of time, too.
Best,
Dave
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@GabrielHoffman were you able to perform a search?
@davek44 are the parameters specified in https://github.com/davek44/Basset/blob/master/data/models/pretrained_params.txt the ones you used to train the final model the numbers of which you reported in the paper?
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@suragnair Yes, I'm pretty sure that's true. I can check if you need a definitive answer. In general, it's pretty robust to small changes to the model architecture, and more sensitive to optimization parameters.
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Hi @suragnair, I used the default model architecture in my current application, but I hope to get all to a more thorough search soon
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Related Issues (20)
- Training takes too long HOT 3
- Pre-trained Weights? HOT 1
- Torch-HDF5 Failure during Writing Output by basset_motifs_predict.lua HOT 3
- First Epoch Loss is Bigger than Expected HOT 2
- Nucleotide Order in Motif Heatmap Reversed HOT 1
- how are filters combined HOT 2
- Error in running basset_sat_vcf.py HOT 1
- Convolutional layers - padding and bias HOT 1
- input and target size mismatch when running test.lua HOT 3
- Citation on README HOT 1
- Prediction tasks specification HOT 1
- install_data.py requires more than 30 GiB of memory HOT 2
- Docker image Lua and Python setups wrong
- how to install 'convnet' module HOT 1
- ENUM error when running basset_train.lua HOT 7
- preprocess_features.py file is generating empty output bed files HOT 2
- bedtools getfasta skipping problem HOT 1
- Used in non human species HOT 1
- Original dataset Basset is trained on HOT 1
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