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I am looking through the MultipleNegativesRankingLoss.py code and I have question about the 'scale' hyperparameter. Also known as the 'temperature', the scale is used to stretch or compress the range …
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As a **developer**, I want **to run cross-validation and hyperparameter tuning on L2G** because **this will allow us to enhance the model performance**.
## Background
The L2G model is based on a…
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Did you use a special validation set for ultrafeedback when tuning the hyper-paramaters in Table 7, or just the `test_pref` set from the [original binarized ultrafeedback data](https://huggingface.co/…
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### Feature request
Adding generation configurations to the parameters that can be tuned in a `Trainer`.
### Motivation
When defining the Optuna hyper-parameter space, I would like to invest…
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Hi! I am trying to fit a glm to some spiking data from a bunch of neurons. My design matrix is the binned spike counts of all neurons, and my 'y' is the spike counts of the neuron I am interested in. …
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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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**Describe the bug**
When finetuning _chronos-t5-small_ on the ETTh1 dataset and ETTh2 dataset respectively, the performance drops compared to the zeroshot performance. Could that be the case be…
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I noticed the Hyperparameter Tuning portion of RiverML is marked `ToDo`. With the exception of `SuccessiveHalving`, does anyone have any libraries that are easily compatible with River? I found `SpotP…
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Hi!
I'm trying to reproduce numbers from Table 4 in https://arxiv.org/pdf/2203.05556.
For California Housing there should be 0,439 for MLP-T-LR.
When I use hyperparameter from https://github.com/…
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In FAQ, you mention that hyperparameters can be tuned using all the data:
"How do I select the hyperparameters of the first stage models?
Alternatively, you can pick the best first stage models …