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The hyperparameter values for SVC were obtained by performing GridSearchCV on the training set.
The code snippets given below can be used to validate the findings:
For Training SVM - with Data …
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## Model Sequential A:
### num_batch_size = 128
num_epochs = 250
Training Accuracy: 0.9536153078079224
Testing Accuracy: 0.89673912525177
num_ephocs = 200
Training Accuracy: 0.969986379146575…
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Dear Dr. Weikang Wan and Team,
I recently came across your fascinating work on the LOTUS algorithm, as detailed in your paper "LOTUS: Continual Imitation Learning for Robot Manipulation Through Un…
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Hi @Gofinge thanks for releasing the code!
The main datasets that PTv3 has been trained on are quite large in scale (Waymo or room-level datasets). Would you recommend any hyperparameters or best p…
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Thanks for the great work. One thing I'm curious about is that does it actually work well on SFT for LLMs? It is not covered in the paper, as well. I tried the following parameters on a 2B-sized model…
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Looking at bit into MLJ integration. For better or worse, hyper-parameter optimization (eg, grid search) in MLJ generally works by mutating the field values of the model struct. I wonder if TableTrans…
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Currently checking out cool AutoML Frameworks as this one :) for my master thesis.
I noticed that pipelines with faulty hyperparamters are getting compiled and evaluated, despite the implementati…
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**Is your feature request related to a problem? Please describe.**
Many DL models need extensive hyperparameter optimization in order to find the best-performing model. Since the `v0.1` version #142 …
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Hi Paul,
I'm trying to allow the full variance-covariance matrix of the random effects to vary across groups using the gr(re, by = "cat_var") syntax (from issue [365](https://github.com/paul-buerkn…