-
Hello!
I like the way you implemented the decreasing in mutation probability to balance exploitation and exploration and the hyperparameter grid search
The first thing I would try to address is t…
-
Hi, I have tried several sets of hyperparameters according to the original paper, for example: [5, inf) for user and item filtering, LS+TO+pop100 for evaluation, 256 batch size for training, and 200 f…
-
I faced another issue with finetuning.
the training loss after each epoch is zero. I tried varying the hyperparameters and using the ones in the script, but it still gives the same thing.
Can you s…
-
Somewhat related to #161
IHR priors and stuff are currently specified in the likelihood function directly instead of in the config json. There is room to move them into the config, although I can …
-
Actually, I can't reproduce the results in the table by myself. And what the "CVR" and "CTCVR" mean in the table, respectively?
Could you provide some ways to reproduce the results in the table?
-
Clicking on row of priors table should bring up modal window where user can view and modify hyperparameters, *e.g.*, mean and standard deviation of normal distribution.
Let's not worry about visualiz…
-
Hi,
I'm trying to run your code for text classification tasks but I'm not sure about the hyperparameters setting here.
Currently, I'm using alpha = 0.05, and **normalize the final features as wh…
-
https://github.com/Sorooshi/Rotten_Tomatoes_DataSet/blob/cb60db8979fbc835bbaf274ecd0e3bbace7af365/src/extract_features_bu.py#L282
Runnig fine_tune_the_model() from FineTuneLstmAe class produces th…
-
**Describe the bug**
I would like to pass hyperparameters to my sagemaker job that are of type string. However, when I do this I get an error saying that they failed to parse
**To reproduce**
```…
-
It would be very useful to allow filtering on hyperparameters in the hparams UI. There doesn't seem to be such a functionality.
In my case, filtering on runs via a regex (similar to the standard pl…