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I was wondering if there are any examples of how to do hyperparameter optimization with fairseq. My idea was to use tune (https://docs.ray.io/en/latest/tune.html) and wire it into a custom task, which…
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Allow the topics to be of varying sizes
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We should make clear that are not yet another HPO library.
I suggest we should start documenting examples or areas where black-box optimization is applied.
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I produced **very poor results** when running Gaussian_stlatting, **not only on my own dataset, but also on the MipNeRF360 scenes** `tandt_db` provided by the training project.
There is a significa…
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In #356 we started seeing that we can play with hyperparameters to reduce the runtime while having high accuracy.
Once #321 is resolved, we can start looking into hyperparameter optimization:
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**Is your feature request related to a problem? Please describe.**
Tracking and managing hyperparameter tuning experiments for machine learning models can be challenging without detailed information …
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**Is your feature request related to a problem? Please describe.**
When using the benchmark_filename parameter for sequential recommendation, it requires specifying train, validation, and test sets i…
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## Motivation
The rapid advancements and growing popularity of Large Language Models (LLMs) have driven an increased need for effective LLMOps in Kubernetes environments. To address this, we develope…
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Optimization of noise (`sigma_n`, `sigma_p`) and of the number of basis functions (`order`).
Similar to `optimize` for Gaussian Processes.
Good Summary: http://krasserm.github.io/2019/02/23/bayesi…
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**What happened**:
I tried the example for hyperparameter optimization: https://examples.dask.org/machine-learning/hyperparam-opt.html
**What you expected to happen**:
it to not fail
**M…